pax_global_header00006660000000000000000000000064147145165100014516gustar00rootroot0000000000000052 comment=a0ec05bbb4da7d845caf81b10022b9455ec66363 pyrgg-1.6/000077500000000000000000000000001471451651000125145ustar00rootroot00000000000000pyrgg-1.6/.coveragerc000066400000000000000000000002531471451651000146350ustar00rootroot00000000000000[run] branch = True omit = */pyrgg/__main__.py */pyrgg/__init__.py [report] # Regexes for lines to exclude from consideration exclude_lines = pragma: no cover pyrgg-1.6/.github/000077500000000000000000000000001471451651000140545ustar00rootroot00000000000000pyrgg-1.6/.github/CODE_OF_CONDUCT.md000066400000000000000000000064231471451651000166600ustar00rootroot00000000000000# Contributor Covenant Code of Conduct ## Our Pledge In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, sex characteristics, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, religion, or sexual identity and orientation. ## Our Standards Examples of behavior that contributes to creating a positive environment include: * Using welcoming and inclusive language * Being respectful of differing viewpoints and experiences * Gracefully accepting constructive criticism * Focusing on what is best for the community * Showing empathy towards other community members Examples of unacceptable behavior by participants include: * The use of sexualized language or imagery and unwelcome sexual attention or advances * Trolling, insulting/derogatory comments, and personal or political attacks * Public or private harassment * Publishing others' private information, such as a physical or electronic address, without explicit permission * Other conduct which could reasonably be considered inappropriate in a professional setting ## Our Responsibilities Project maintainers are responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behavior. Project maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, or to ban temporarily or permanently any contributor for other behaviors that they deem inappropriate, threatening, offensive, or harmful. ## Scope This Code of Conduct applies both within project spaces and in public spaces when an individual is representing the project or its community. Examples of representing a project or community include using an official project e-mail address, posting via an official social media account, or acting as an appointed representative at an online or offline event. Representation of a project may be further defined and clarified by project maintainers. ## Enforcement Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by contacting the project team at info@pyrgg.site. All complaints will be reviewed and investigated and will result in a response that is deemed necessary and appropriate to the circumstances. The project team is obligated to maintain confidentiality with regard to the reporter of an incident. Further details of specific enforcement policies may be posted separately. Project maintainers who do not follow or enforce the Code of Conduct in good faith may face temporary or permanent repercussions as determined by other members of the project's leadership. ## Attribution This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4, available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html [homepage]: https://www.contributor-covenant.org For answers to common questions about this code of conduct, see https://www.contributor-covenant.org/faq pyrgg-1.6/.github/CONTRIBUTING.md000066400000000000000000000013101471451651000163000ustar00rootroot00000000000000# Contribution Changes and improvements are more than welcome! ❤️ Feel free to fork and open a pull request. Please consider the following : 1. Fork it! 2. Create your feature branch (under `dev` branch) 3. Add your functions/methods to proper files 4. Add standard `docstring` to your functions/methods 5. Add tests for your functions/methods (`doctest` testcases in `test` folder) 6. Pass all CI tests 7. Update `References` section in `README.md` (`MLA` format) 8. Update `CHANGELOG.md` - Describe changes under `[Unreleased]` section 9. Update `AUTHORS.md` - Add your name under `# Other Contributors #` section 10. Submit a pull request into `dev` (please complete the pull request template)pyrgg-1.6/.github/FUNDING.yml000066400000000000000000000000521471451651000156660ustar00rootroot00000000000000custom: https://www.pyrgg.site/donate.htmlpyrgg-1.6/.github/ISSUE_TEMPLATE/000077500000000000000000000000001471451651000162375ustar00rootroot00000000000000pyrgg-1.6/.github/ISSUE_TEMPLATE/bug_report.yml000066400000000000000000000054171471451651000211410ustar00rootroot00000000000000name: Bug Report description: File a bug report title: "[Bug]: " body: - type: markdown attributes: value: | Thanks for your time to fill out this bug report! - type: input id: contact attributes: label: Contact details description: How can we get in touch with you if we need more info? placeholder: ex. email@example.com validations: required: false - type: textarea id: what-happened attributes: label: What happened? description: Provide a clear and concise description of what the bug is. placeholder: > Tell us a description of the bug. validations: required: true - type: textarea id: step-to-reproduce attributes: label: Steps to reproduce description: Provide details of how to reproduce the bug. placeholder: > ex. 1. Go to '...' validations: required: true - type: textarea id: expected-behavior attributes: label: Expected behavior description: What did you expect to happen? placeholder: > ex. I expected '...' to happen validations: required: true - type: textarea id: actual-behavior attributes: label: Actual behavior description: What did actually happen? placeholder: > ex. Instead '...' happened validations: required: true - type: dropdown id: operating-system attributes: label: Operating system description: Which operating system are you using? options: - Windows - macOS - Linux default: 0 validations: required: true - type: dropdown id: python-version attributes: label: Python version description: Which version of Python are you using? options: - Python 3.13 - Python 3.12 - Python 3.11 - Python 3.10 - Python 3.9 - Python 3.8 - Python 3.7 - Python 3.6 - Python 3.5 default: 1 validations: required: true - type: dropdown id: Pyrgg-version attributes: label: PyRGG version description: Which version of PyRGG are you using? options: - PyRGG 1.6 - PyRGG 1.5 - PyRGG 1.4 - PyRGG 1.3 - PyRGG 1.2 - PyRGG 1.1 - PyRGG 1.0 - PyRGG 0.9 - PyRGG 0.8 - PyRGG 0.7 - PyRGG 0.6 - PyRGG 0.5 - PyRGG 0.4 - PyRGG 0.3 - PyRGG 0.2 - PyRGG 0.1 default: 0 validations: required: true - type: textarea id: logs attributes: label: Relevant log output description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks. render: shell pyrgg-1.6/.github/ISSUE_TEMPLATE/config.yml000066400000000000000000000002641471451651000202310ustar00rootroot00000000000000blank_issues_enabled: false contact_links: - name: Discord url: https://discord.com/invite/dfYAWVMaCW about: Ask questions and discuss with other PyRGG community members pyrgg-1.6/.github/ISSUE_TEMPLATE/feature_request.yml000066400000000000000000000017071471451651000221720ustar00rootroot00000000000000name: Feature Request description: Suggest a feature for this project title: "[Feature]: " body: - type: textarea id: description attributes: label: Describe the feature you want to add placeholder: > I'd like to be able to [...] validations: required: true - type: textarea id: possible-solution attributes: label: Describe your proposed solution placeholder: > I think this could be done by [...] validations: required: false - type: textarea id: alternatives attributes: label: Describe alternatives you've considered, if relevant placeholder: > Another way to do this would be [...] validations: required: false - type: textarea id: additional-context attributes: label: Additional context placeholder: > Add any other context or screenshots about the feature request here. validations: required: false pyrgg-1.6/.github/PULL_REQUEST_TEMPLATE.md000066400000000000000000000001601471451651000176520ustar00rootroot00000000000000#### Reference Issues/PRs #### What does this implement/fix? Explain your changes. #### Any other comments? pyrgg-1.6/.github/dependabot.yml000066400000000000000000000002451471451651000167050ustar00rootroot00000000000000version: 2 updates: - package-ecosystem: pip directory: "/" schedule: interval: weekly time: "01:30" open-pull-requests-limit: 10 target-branch: dev pyrgg-1.6/.github/workflows/000077500000000000000000000000001471451651000161115ustar00rootroot00000000000000pyrgg-1.6/.github/workflows/publish_conda.yaml000066400000000000000000000006721471451651000216140ustar00rootroot00000000000000name: publish_conda on: push: # Sequence of patterns matched against refs/tags tags: - '*' # Push events to matching v*, i.e. v1.0, v20.15.10 jobs: publish: runs-on: ubuntu-latest steps: - uses: actions/checkout@v1 - name: publish-to-conda uses: sepandhaghighi/conda-package-publish-action@v1.2 with: subDir: 'otherfile' AnacondaToken: ${{ secrets.ANACONDA_TOKEN }} pyrgg-1.6/.github/workflows/publish_pypi.yml000066400000000000000000000017551471451651000213530ustar00rootroot00000000000000# This workflow will upload a Python Package using Twine when a release is created # For more information see: https://help.github.com/en/actions/language-and-framework-guides/using-python-with-github-actions#publishing-to-package-registries name: Upload Python Package on: push: # Sequence of patterns matched against refs/tags tags: - '*' # Push events to matching v*, i.e. v1.0, v20.15.10 jobs: deploy: runs-on: ubuntu-latest steps: - uses: actions/checkout@v2 - name: Set up Python uses: actions/setup-python@v1 with: python-version: '3.x' - name: Install dependencies run: | python -m pip install --upgrade pip pip install setuptools wheel twine - name: Build and publish env: TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }} TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }} run: | python setup.py sdist bdist_wheel twine upload dist/*.tar.gz twine upload dist/*.whl pyrgg-1.6/.github/workflows/test.yml000066400000000000000000000044601471451651000176170ustar00rootroot00000000000000# This workflow will install Python dependencies, run tests with a variety of Python versions # For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions name: CI on: push: branches: - master - dev pull_request: branches: - master - dev env: TEST_PYTHON_VERSION: 3.9 TEST_OS: 'ubuntu-20.04' jobs: build: runs-on: ${{ matrix.os }} strategy: fail-fast: false matrix: os: [ubuntu-20.04, windows-2022, macOS-13] python-version: [3.6, 3.7, 3.8, 3.9, 3.10.0, 3.11.0, 3.12.0, 3.13.0] steps: - uses: actions/checkout@v2 - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v2 with: python-version: ${{ matrix.python-version }} - name: Installation run: | python -m pip install --upgrade pip pip install . - name: First test run: | pyrgg test pyrgg --version - name: Test requirements Installation run: | python otherfile/requirements-splitter.py pip install --upgrade --upgrade-strategy=only-if-needed -r test-requirements.txt - name: Test with pytest run: | python -m pytest test --cov=pyrgg --cov-report=term - name: Version check run: | python otherfile/version_check.py if: matrix.python-version == env.TEST_PYTHON_VERSION - name: Other tests run: | python -m vulture pyrgg/ otherfile/ setup.py --min-confidence 65 --exclude=__init__.py --sort-by-size python -m bandit -r pyrgg -s B311,B403 python -m pydocstyle -v --match-dir=pyrgg if: matrix.python-version == env.TEST_PYTHON_VERSION - name: Upload coverage to Codecov uses: codecov/codecov-action@v3 with: fail_ci_if_error: false if: matrix.python-version == env.TEST_PYTHON_VERSION && matrix.os == env.TEST_OS - name: cProfile - PyRGG Engine run: | python -m cProfile -s cumtime otherfile/profiles/pyrgg_profile.py - name: cProfile - Erdos Reyni Gilbert Engine run: | python -m cProfile -s cumtime otherfile/profiles/erg_profile.py - name: cProfile - Erdos Reyni Engine run: | python -m cProfile -s cumtime otherfile/profiles/er_profile.py pyrgg-1.6/.gitignore000066400000000000000000000024101471451651000145010ustar00rootroot00000000000000# Created by .ignore support plugin (hsz.mobi) ### Python template # Byte-compiled / optimized / DLL files node_modules/ datasets/ __pycache__/ *.py[cod] *$py.class *.gr *.json *.csv *.wel *.lp *.p *.dl *.tgf # C extensions *.so # Distribution / packaging .Python env/ build/ develop-eggs/ dist/ downloads/ eggs/ .eggs/ lib/ lib64/ parts/ sdist/ var/ *.egg-info/ .installed.cfg *.egg # PyInstaller # Usually these files are written by a python script from a template # before PyInstaller builds the exe, so as to inject date/other infos into it. *.manifest # Installer logs pip-log.txt pip-delete-this-directory.txt # Unit test / coverage reports htmlcov/ .tox/ .coverage .coverage.* .cache nosetests.xml coverage.xml *,cover .hypothesis/ # Translations *.mo *.pot # Django stuff: *.log local_settings.py # Flask stuff: instance/ .webassets-cache # Scrapy stuff: .scrapy # Sphinx documentation docs/_build/ # PyBuilder target/ # Jupyter Notebook .ipynb_checkpoints # pyenv .python-version # celery beat schedule file celerybeat-schedule # dotenv .env # virtualenv .venv/ venv/ ENV/ # Spyder project settings .spyderproject # Rope project settings .ropeproject ### Example user template template ### Example user template # IntelliJ project files .idea *.iml out gen pyrgg-1.6/AUTHORS.md000066400000000000000000000006131471451651000141630ustar00rootroot00000000000000# Core Developers ---------- - Sepand Haghighi - Open Science Laboratory ([Github](https://github.com/sepandhaghighi)) - Sadra Sabouri - Open Science Laboratory ([Github](https://github.com/sadrasabouri)) # Other Contributors ---------- - [@zhmbshr](https://github.com/zhmbshr) ** - [@ivanovmg](https://github.com/ivanovmg) - [@ahmadsalimi](https://github.com/ahmadsalimi) ** Graphic designerpyrgg-1.6/CHANGELOG.md000066400000000000000000000152471471451651000143360ustar00rootroot00000000000000# Changelog All notable changes to this project will be documented in this file. The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/) and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.html). ## [Unreleased] ## [1.6] - 2024-11-13 ### Added - `pyrgg.engines.erdos_reyni` module - `save_log` function ### Changed - PyPI badge in `README.md` updated - `logger` function format for `erdos_reyni_gilbert` changed - GitHub actions are limited to the `dev` and `master` branches - `README.md` modified - `build_exe.bat` modified - `Python 3.13` added to `test.yml` ## [1.5] - 2024-09-16 ### Added - `feature_request.yml` template - `config.yml` for issue template - `pyrgg.engines` package - `pyrgg.engines.pyrgg` module - `pyrgg.engines.erdos_reyni_gilbert` module - `Erdős-Rényi-Gilbert` generation model - Generation engine menu - `handle_string` function - `handle_pos_int` function - `handle_output_format` function - `handle_engine` function - `SECURITY.md` ### Changed - Metadata in files modified - `Python 3.5` support dropped - Bug report template modified - Cprofile tests separated in files for engines - `README.md` modified - `Python 3.12` added to `test.yml` - Menu options bug fixed - Test system modified - `engine` parameter added to `logger` function - `MENU_ITEMS1` parameter changed to `MENU_ITEMS` - `MENU_ITEMS2` parameter changed to `PYRGG_ENGINE_PARAMS` - `_update_using_first_menu` function changed to `_update_using_menu` - `_update_using_second_menu` function changed to `_update_with_engine_params` - `ITEM_CONVERTORS` renamed to `ITEM_HANDLERS` - Website domain changed to [https://www.pyrgg.site](https://www.pyrgg.site) ### Removed - `dimacs_init` function ## [1.4] - 2023-07-06 ### Added - `check_for_config` function - `load_config` function - `save_config` function ### Changed - `README.md` modified - Logo changed - `codecov` removed from `dev-requirements.txt` - Test system modified - Error messages updated ## [1.3] - 2022-11-30 ### Added - Graphviz(DOT) format ### Changed - [asciinema](https://asciinema.org) instruction video updated - Test system modified - `README.md` modified - `Python 3.11` added to `test.yml` - CLI mode updated - `dev-requirements.txt` updated - To-do list moved to `TODO.md` ## [1.2] - 2022-09-07 ### Added - Anaconda workflow - Discord badge ### Changed - Menu optimized - Docstrings modified - `branch_gen` function modified - `edge_gen` function modified - `precision` and `min_edge` parameters added to `branch_gen` function - `random_edge` parameter removed from `branch_gen` function - Test system modified - `AUTHORS.md` updated - License updated - `README.md` modified - `Python 3.10` added to `test.yml` ### Removed - `sign_gen` function - `random_edge_limits` function ## [1.1] - 2021-06-09 ### Added - `requirements-splitter.py` - `is_weighted` function - `_write_properties_to_json` function - `PYRGG_TEST_MODE` parameter ### Changed - Test system modified - JSON, YAML and Pickle formats value changed from `string` to `number` - `properties` section added to JSON, YAML and Pickle formats - `_write_to_json` function renamed to `_write_data_to_json` - `logger` function modified - `time_convert` function modified - `branch_gen` function modified - References updated ## [1.0] - 2021-01-11 ### Added - Number of files option ### Changed - All flags type changed to `bool` - Menu optimized - The `logger` function enhanced. - Time format in the `logger` changed to `%Y-%m-%d %H:%M:%S` - `dl_maker` function modified - `tgf_maker` function modified - `gdf_maker` function modified - `run` function modified ## [0.9] - 2020-10-07 ### Added - GEXF format - Float weight support - `tox.ini` ### Changed - Menu optimized - `pyrgg.py` renamed to `graph_gen.py` - Other functions moved to `functions.py` - Test system modified - `params.py` refactored - `graph_gen.py` refactored - `functions.py` refactored - `weight_str_to_number` function renamed to `convert_str_to_number` - `branch_gen` function bugs fixed - `input_filter` function bug fixed - `gl_maker` function bug fixed - `CONTRIBUTING.md` updated - `AUTHORS.md` updated ### Removed - `print_test` function - `left_justify` function - `justify` function - `zero_insert` function ## [0.8] - 2020-08-19 ### Added - GDF format - GML format ### Changed - CLI snapshots updated - `AUTHORS.md` updated ## [0.7] - 2020-08-07 ### Added - Graph Line format ### Changed - Menu optimized ## [0.6] - 2020-07-24 ### Added - Matrix Market format ### Changed - `json_maker` function optimized - `dl_maker` function optimized - `tgf_maker` function optimized - `lp_maker` function optimized ## [0.5] - 2020-07-01 ### Added - TSV format - Multigraph control ### Changed - `branch_gen` function modified - Website changed to [https://www.pyrgg.ir](https://www.pyrgg.ir) ## [0.4] - 2020-06-17 ### Added - Self loop control - Github action ### Changed - `appveyor.yml` updated ## [0.3] - 2019-11-29 ### Added - `__version__` variable - `CHANGELOG.md` - `dev-requirements.txt` - `requirements.txt` - `CODE_OF_CONDUCT.md` - `ISSUE_TEMPLATE.md` - `PULL_REQUEST_TEMPLATE.md` - `CONTRIBUTING.md` - `version_check.py` - `pyrgg_profile.py` - Unweighted graph - Undirected graph - Exe version ### Changed - Test system modified - `README.md` modified - Docstrings modified - `get_input` function modified - `edge_gen` function modified - Parameters moved to `params.py` ## [0.2] - 2017-09-20 ### Added - CSV format - YAML format - Weighted edge list format (WEL) - ASP format - Trivial graph format (TGF) - UCINET DL format - Pickle format ## [0.1] - 2017-08-19 ### Added - DIMACS format - JSON format - README [Unreleased]: https://github.com/sepandhaghighi/pyrgg/compare/v1.6...dev [1.6]: https://github.com/sepandhaghighi/pyrgg/compare/v1.5...v1.6 [1.5]: https://github.com/sepandhaghighi/pyrgg/compare/v1.4...v1.5 [1.4]: https://github.com/sepandhaghighi/pyrgg/compare/v1.3...v1.4 [1.3]: https://github.com/sepandhaghighi/pyrgg/compare/v1.2...v1.3 [1.2]: https://github.com/sepandhaghighi/pyrgg/compare/v1.1...v1.2 [1.1]: https://github.com/sepandhaghighi/pyrgg/compare/v1.0...v1.1 [1.0]: https://github.com/sepandhaghighi/pyrgg/compare/v0.9...v1.0 [0.9]: https://github.com/sepandhaghighi/pyrgg/compare/v0.8...v0.9 [0.8]: https://github.com/sepandhaghighi/pyrgg/compare/v0.7...v0.8 [0.7]: https://github.com/sepandhaghighi/pyrgg/compare/v0.6...v0.7 [0.6]: https://github.com/sepandhaghighi/pyrgg/compare/v0.5...v0.6 [0.5]: https://github.com/sepandhaghighi/pyrgg/compare/v0.4...v0.5 [0.4]: https://github.com/sepandhaghighi/pyrgg/compare/v0.3...v0.4 [0.3]: https://github.com/sepandhaghighi/pyrgg/compare/v0.2...v0.3 [0.2]: https://github.com/sepandhaghighi/pyrgg/compare/v0.1...v0.2 [0.1]: https://github.com/sepandhaghighi/pyrgg/compare/1e238cd...v0.1 pyrgg-1.6/LICENSE000066400000000000000000000021221471451651000135160ustar00rootroot00000000000000MIT License Copyright (c) 2017 Sepand Haghighi Copyright (c) 2021 Sadra Sabouri Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. pyrgg-1.6/MANIFEST.in000066400000000000000000000002561471451651000142550ustar00rootroot00000000000000include LICENSE include *.md include *.spec include *.txt include *.yml include *.ini recursive-include paper *.bib recursive-include paper *.md recursive-include paper *.pdfpyrgg-1.6/PYRGG.spec000066400000000000000000000014571471451651000142670ustar00rootroot00000000000000# -*- mode: python -*- block_cipher = None pyrgg_version = "1.6" a = Analysis(['pyrgg/__main__.py'], pathex=['pyrgg'], binaries=[], datas=[], hiddenimports=[], hookspath=[], runtime_hooks=[], excludes=[], win_no_prefer_redirects=False, win_private_assemblies=False, cipher=block_cipher) pyz = PYZ(a.pure, a.zipped_data, cipher=block_cipher) exe = EXE(pyz, a.scripts, a.binaries, a.zipfiles, a.datas, name='PYRGG-'+pyrgg_version, debug=False, strip=False, upx=True, runtime_tmpdir=None, icon='otherfile/icon.ico', version="otherfile/Version.rc", console=True ) pyrgg-1.6/README.md000066400000000000000000000455271471451651000140100ustar00rootroot00000000000000

PyRGG: Python Random Graph Generator

PyPI version Codecov built with Python3 Discord Channel
## Overview

PyRGG is a user-friendly synthetic random graph generator that is written in Python and supports multiple graph file formats, such as DIMACS-Graph files. It can generate graphs of various sizes and is specifically designed to create input files for a wide range of graph-based research applications, including testing, benchmarking, and performance analysis of graph processing frameworks. PyRGG is aimed at computer scientists who are studying graph algorithms and graph processing frameworks.

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## Installation ### PyPI - Check [Python Packaging User Guide](https://packaging.python.org/installing/) - `pip install pyrgg==1.6` ### Source Code - Download [Version 1.6](https://github.com/sepandhaghighi/pyrgg/archive/v1.6.zip) or [Latest Source ](https://github.com/sepandhaghighi/pyrgg/archive/dev.zip) - `pip install .` ### Conda - Check [Conda Managing Package](https://conda.io) - `conda install -c sepandhaghighi pyrgg` ### Exe Version ⚠️ Only Windows ⚠️ For PyRGG targeting Windows < 10, the user needs to take special care to include the Visual C++ run-time `.dlls`(for more information visit [here](https://pyinstaller.org/en/v3.3.1/usage.html#windows)) - Download [Exe-Version 1.6](https://github.com/sepandhaghighi/pyrgg/releases/download/v1.6/PYRGG-1.6.exe) - Run `PYRGG-1.6.exe` ### System Requirements PyRGG will likely run on a modern dual core PC. Typical configuration is: - Dual Core CPU (2.0 Ghz+) - 4GB of RAM ⚠️ Note that it may run on lower end equipment though good performance is not guaranteed ## Usage - Open `CMD` (Windows) or `Terminal` (Linux) - Run `pyrgg` or `python -m pyrgg` (or run `PYRGG.exe`) - Enter data
## Engines ### PyRGG
Parameter Description
Vertices Number The total number of vertices in the graph
Min Edge Number The minimum number of edges connected to each vertex
Max Edge Number The maximum number of edges connected to each vertex
Weighted / Unweighted Specifies whether the graph is weighted or unweighted
Min Weight The minimum weight of the edges (if weighted)
Max Weight The maximum weight of the edges (if weighted)
Signed / Unsigned Specifies whether the edge weights are signed or unsigned
Directed / Undirected Specifies whether the graph is directed or undirected
Self Loop / No Self Loop Specifies whether self-loop is allowed or not
Simple / Multigraph Specifies whether the graph is a simple graph or a multigraph
### Erdős–Rényi-Gilbert
Parameter Description
Vertices Number The total number of vertices in the graph
Probability The probability for edge creation between any two vertices
Directed / Undirected Specifies whether the graph is directed or undirected
### Erdős–Rényi
Parameter Description
Vertices Number The total number of vertices in the graph
Edge Number The total number of edges in the graph
Directed / Undirected Specifies whether the graph is directed or undirected
## Supported Formats ### DIMACS ``` p sp a . . . a ``` * [Document](http://www.diag.uniroma1.it/challenge9/format.shtml) * [Sample 1](https://www.dropbox.com/s/i80tnwuuv4iyqet/100.gr.gz?dl=0) (100 Vertices , 3KB) * [Sample 2](https://www.dropbox.com/s/lqk42pwu7o4xauv/1000.gr.gz?dl=0) (1000 Vertices , 13KB) * [Sample 3](https://www.dropbox.com/s/93dp8cjs6lnu83u/1000000.gr.gz?dl=0) (1000000 Vertices , 7MB) * [Sample 4](https://www.dropbox.com/s/rrxdc4wt0ldonfk/5000000.gr.gz?dl=0) (5000000 Vertices , 37MB) ### CSV ``` ,, . . . ,, ``` * [Document](https://en.wikipedia.org/wiki/Comma-separated_values) * [Sample 1](https://www.dropbox.com/s/dmld0eadftnatr5/100.csv?dl=0) (100 Vertices , 3KB) * [Sample 2](https://www.dropbox.com/s/juxah4nwamzdegr/1000.csv?dl=0) (1000 Vertices , 51KB) ### TSV ``` . . . ``` * [Document](https://en.wikipedia.org/wiki/Tab-separated_values) * [Sample 1](https://www.dropbox.com/s/j3zgs4kx2paxe75/100.tsv?dl=0) (100 Vertices , 29KB) * [Sample 2](https://www.dropbox.com/s/ykagmjgwlpim6dq/1000.tsv?dl=0) (1000 Vertices , 420KB) ### JSON ``` { "properties": { "directed": true, "signed": true, "multigraph": true, "weighted": true, "self_loop": true }, "graph": { "nodes":[ { "id": 1 }, . . . { "id": n } ], "edges":[ { "source": head_1, "target": tail_1, "weight": weight_1 }, . . . { "source": head_n, "target": tail_n, "weight": weight_n } ] } } ``` * [Document](https://en.wikipedia.org/wiki/JSON) * [Sample 1](https://www.dropbox.com/s/yvevoyb8559nytb/100.json?dl=0) (100 Vertices , 26KB) * [Sample 2](https://www.dropbox.com/s/f6kljlch7p2rfhy/1000.json?dl=0) (1000 Vertices , 494KB) ### YAML ``` graph: edges: - source: head_1 target: tail_1 weight: weight_1 . . . - source: head_n target: tail_n weight: weight_n nodes: - id: 1 . . . - id: n properties: directed: true multigraph: true self_loop: true signed: true weighted: true ``` * [Document](https://en.wikipedia.org/wiki/YAML) * [Sample 1](https://www.dropbox.com/s/9seljohtoqjzjzy/30.yaml?dl=0) (30 Vertices , 6KB) * [Sample 2](https://www.dropbox.com/s/wtfh38rgmn29npi/100.yaml?dl=0) (100 Vertices , 35KB) ### Weighted Edge List ``` . . . ``` * [Document](http://www.cs.cmu.edu/~pbbs/benchmarks/graphIO.html) * [Sample 1](https://www.dropbox.com/s/moie1xb2wj90y33/100.wel?dl=0) (100 Vertices , 5KB) * [Sample 2](https://www.dropbox.com/s/h6pohl60okhdnt7/1000.wel?dl=0) (1000 Vertices , 192KB) ### ASP ``` node(1). . . . node(n). edge(head_1,tail_1,weight_1). . . . edge(head_n,tail_n,weight_n). ``` * [Document](https://www.mat.unical.it/aspcomp2013/MaximalClique) * [Sample 1](https://www.dropbox.com/s/4bufa1m4uamv48z/100.lp?dl=0) (100 Vertices , 7KB) * [Sample 2](https://www.dropbox.com/s/w79fh1qva64namw/1000.lp?dl=0) (1000 Vertices , 76KB) ### Trivial Graph Format ``` 1 . . . n # 1 2 weight_1 . . . n k weight_n ``` * [Document](https://en.wikipedia.org/wiki/Trivial_Graph_Format) * [Sample 1](https://www.dropbox.com/s/tehb6f3gz2o5v9c/100.tgf?dl=0) (100 Vertices , 4KB) * [Sample 2](https://www.dropbox.com/s/9mjeq4w973189cc/1000.tgf?dl=0) (1000 Vertices , 61KB) ### UCINET DL Format ``` dl format=edgelist1 n= data: 1 2 weight_1 . . . n k weight_n ``` * [Document](https://sites.google.com/site/ucinetsoftware/home) * [Sample 1](https://www.dropbox.com/s/82wrl86uowwjud2/100.dl?dl=0) (100 Vertices , 8KB) * [Sample 2](https://www.dropbox.com/s/kbzbsy47uvfqdsi/1000.dl?dl=0) (1000 Vertices , 729KB) ### Matrix Market ``` %%MatrixMarket matrix coordinate real general . . . ``` * [Document](https://math.nist.gov/MatrixMarket/formats.html) * [Sample 1](https://www.dropbox.com/s/ztw3vg0roups82q/100.mtx?dl=0) (100 Vertices , 59KB) * [Sample 2](https://www.dropbox.com/s/skjjvbbzrpvryl4/1000.mtx?dl=0) (1000 Vertices , 1.8MB) ### Graph Line ``` : : ... : : : ... : . . . : : ... : ``` * [Sample 1](https://www.dropbox.com/s/obmmb5nw1lca9z3/100.gl?dl=0) (100 Vertices , 17KB) * [Sample 2](https://www.dropbox.com/s/intufsbudnmfv8m/1000.gl?dl=0) (1000 Vertices , 2.4MB) ### GDF ``` nodedef>name VARCHAR,label VARCHAR node_1,node_1_label node_2,node_2_label . . . node_n,node_n_label edgedef>node1 VARCHAR,node2 VARCHAR, weight DOUBLE node_1,node_2,weight_1 node_1,node_3,weight_2 . . . node_n,node_2,weight_n ``` * [Sample 1](https://www.dropbox.com/s/7dqox0f8e1f859s/100.gdf?dl=0) (100 Vertices , 21KB) * [Sample 2](https://www.dropbox.com/s/xabjzpp0p5sr4b9/1000.gdf?dl=0) (1000 Vertices , 690KB) ### GML ``` graph [ multigraph 0 directed 0 node [ id 1 label "Node 1" ] node [ id 2 label "Node 2" ] . . . node [ id n label "Node n" ] edge [ source 1 target 2 value W1 ] edge [ source 2 target 4 value W2 ] . . . edge [ source n target r value Wn ] ] ``` * [Document](https://en.wikipedia.org/wiki/Graph_Modelling_Language) * [Sample 1](https://www.dropbox.com/s/g9uvywn1fwt9aq7/100.gml?dl=0) (100 Vertices , 120KB) * [Sample 2](https://www.dropbox.com/s/5gt5udezy56mlz9/1000.gml?dl=0) (1000 Vertices , 2.4MB) ### GEXF ``` PyRGG File Name ... ... ``` * [Document](https://github.com/gephi/gexf/wiki/Basic-Concepts#network-topology) * [Sample 1](https://www.dropbox.com/s/kgx8xl9j0dpk4us/100.gexf?dl=0) (100 Vertices , 63KB) * [Sample 2](https://www.dropbox.com/s/7a380kf35buvusr/1000.gexf?dl=0) (1000 Vertices , 6.4MB) ### Graphviz ``` graph example { node1 -- node2 [weight=W1]; node3 -- node4 [weight=W2]; node1 -- node3 [weight=W3]; . . . } ``` * [Document](https://graphviz.org/doc/info/lang.html) * [Sample 1](https://www.dropbox.com/s/ukev1hi4kguomri/100.gv?dl=0) (100 Vertices , 11KB) * [Sample 2](https://www.dropbox.com/s/vpvvliz96mdea1p/1000.gv?dl=0) (1000 Vertices , 106KB) * [Online Visualization](https://dreampuf.github.io/GraphvizOnline/) ### Pickle ⚠️ Binary format * [Document](https://docs.python.org/3.10/library/pickle.html) * [Sample 1](https://www.dropbox.com/s/4s8zt9i13z39gts/100.p?dl=0) (100 Vertices , 12KB) * [Sample 2](https://www.dropbox.com/s/fzurqu5au0p1b54/1000.p?dl=0) (1000 Vertices , 340KB) ## Issues & Bug Reports Just fill an issue and describe it. We'll check it ASAP! or send an email to [info@pyrgg.site](mailto:info@pyrgg.site "info@pyrgg.site"). You can also join our discord server Discord Channel ## Citing If you use PyRGG in your research, please cite the [JOSS paper](http://joss.theoj.org/papers/da33f691984d9a35f66ff93a391bbc26 "PyRGG JOSS Paper") ;-) 
@article{Haghighi2017,
  doi = {10.21105/joss.00331},
  url = {https://doi.org/10.21105/joss.00331},
  year  = {2017},
  month = {sep},
  publisher = {The Open Journal},
  volume = {2},
  number = {17},
  author = {Sepand Haghighi},
  title = {Pyrgg: Python Random Graph Generator},
  journal = {The Journal of Open Source Software}
}
JOSS
Zenodo DOI
## References
1- 9th DIMACS Implementation Challenge - Shortest Paths
2- Problem Based Benchmark Suite
3- MaximalClique - ASP Competition 2013
4- Pitas, Ioannis, ed. Graph-based social media analysis. Vol. 39. CRC Press, 2016.
5- Roughan, Matthew, and Jonathan Tuke. "The hitchhikers guide to sharing graph data." 2015 3rd International Conference on Future Internet of Things and Cloud. IEEE, 2015.
6- Borgatti, Stephen P., Martin G. Everett, and Linton C. Freeman. "Ucinet for Windows: Software for social network analysis." Harvard, MA: analytic technologies 6 (2002).
7- Matrix Market: File Formats
8- Social Network Visualizer
9- Adar, Eytan. "GUESS: a language and interface for graph exploration." Proceedings of the SIGCHI conference on Human Factors in computing systems. 2006.
10- Skiena, Steven S. The algorithm design manual. Springer International Publishing, 2020.
11- Chakrabarti, Deepayan, Yiping Zhan, and Christos Faloutsos. "R-MAT: A recursive model for graph mining." Proceedings of the 2004 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, 2004.
12- Zhong, Jianlong, and Bingsheng He. "An overview of medusa: simplified graph processing on gpus." ACM SIGPLAN Notices 47.8 (2012): 283-284.
13- Ellson, John, et al. "Graphviz and dynagraph—static and dynamic graph drawing tools." Graph drawing software. Springer, Berlin, Heidelberg, 2004. 127-148.
14- Gilbert, Edgar N. "Random graphs." The Annals of Mathematical Statistics 30.4 (1959): 1141-1144.
15- Erdős, Paul, and Alfréd Rényi. "On the strength of connectedness of a random graph." Acta Mathematica Hungarica 12.1 (1961): 261-267.
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If you do like our project and we hope that you do, can you please support us? Our project is not and is never going to be working for profit. We need the money just so we can continue doing what we do ;-) . PyRGG Donation pyrgg-1.6/SECURITY.md000066400000000000000000000007501471451651000143070ustar00rootroot00000000000000# Security Policy ## Supported Versions | Version | Supported | | ------------- | ------------------ | | 1.6 | :white_check_mark: | | < 1.6 | :x: | ## Reporting a Vulnerability Please report security vulnerabilities by email to [info@pyrgg.site](mailto:info@pyrgg.site "info@pyrgg.site"). If the security vulnerability is accepted, a dedicated bugfix release will be issued as soon as possible (depending on the complexity of the fix).pyrgg-1.6/autopep8.bat000066400000000000000000000006161471451651000147540ustar00rootroot00000000000000python -m autopep8 pyrgg --recursive --aggressive --aggressive --in-place --pep8-passes 2000 --max-line-length 120 --verbose python -m autopep8 setup.py --recursive --aggressive --aggressive --in-place --pep8-passes 2000 --max-line-length 120 --verbose python -m autopep8 otherfile/version_check.py --recursive --aggressive --aggressive --in-place --pep8-passes 2000 --max-line-length 120 --verbosepyrgg-1.6/build_exe.bat000066400000000000000000000004211471451651000151410ustar00rootroot00000000000000@echo off FOR /F "tokens=* USEBACKQ" %%F IN (`python --version`) DO ( SET py_version_str=%%F ) SET py_version=%py_version_str:~7% echo Your Python Version : %py_version% echo Recommended Python Version : ^>= 3.6 echo ----- echo ----- python -m PyInstaller PYRGG.spec pausepyrgg-1.6/codecov.yml000066400000000000000000000003071471451651000146610ustar00rootroot00000000000000codecov: require_ci_to_pass: yes coverage: precision: 2 round: up range: "70...100" status: patch: default: enabled: no project: default: threshold: 1% pyrgg-1.6/dev-requirements.txt000066400000000000000000000002551471451651000165560ustar00rootroot00000000000000art==6.3 pyyaml==6.0.2 scipy>=1.2.0 networkx>=2.1 pydot>=1.2.4 pytest>=4.3.1 pytest-cov>=2.6.1 setuptools>=40.8.0 vulture>=1.0 bandit>=1.5.1 pydocstyle>=3.0.0 flake8>=3.5.0 pyrgg-1.6/otherfile/000077500000000000000000000000001471451651000144755ustar00rootroot00000000000000pyrgg-1.6/otherfile/RELEASE.md000066400000000000000000000031341471451651000161000ustar00rootroot00000000000000# PyRGG Release Instructions **Last Update: 2024-10-06** 1. Create the `release` branch under `dev` 2. Update all version tags 1. `setup.py` 2. `README.md` 3. `SECURITY.md` 4. `PYRGG.spec` 5. `otherfile/version_check.py` 6. `otherfile/meta.yaml` 7. `otherfile/Version.rc` 8. `pyrgg/params.py` 3. Update `CHANGELOG.md` 1. Add a new header under `Unreleased` section (Example: `## [0.1] - 2022-08-17`) 2. Add a new compare link to the end of the file (Example: `[0.2]: https://github.com/sepandhaghighi/pyrgg/compare/v0.1...v0.2`) 3. Update `dev` compare link (Example: `[Unreleased]: https://github.com/sepandhaghighi/pyrgg/compare/v0.2...dev`) 4. Update `.github/ISSUE_TEMPLATE/bug_report.yml` 1. Add new version tag to `PyRGG version` dropbox options 5. Create a PR from `release` to `dev` 1. Title: `Version x.x` (Example: `Version 0.1`) 2. Tag all related issues 3. Labels: `release` 4. Set milestone 5. Wait for all CI pass 6. Need review (**1** reviewer) 7. Squash and merge 8. Delete `release` branch 6. Merge `dev` branch into `master` 1. Checkout to `master` 2. `git merge dev` 3. `git push origin master` 4. Wait for all CI pass 7. Build EXE file 1. Run `build_exe.bat` (Use `Python >= 3.6`) 8. Create a new release 1. Target branch: `master` 2. Tag: `vx.x` (Example: `v0.1`) 3. Title: `Version x.x` (Example: `Version 0.1`) 4. Copy changelogs 5. Tag all related issues 6. Upload EXE file 9. Bump!! 10. Close this version issues 11. Close milestone 12. Update website 1. `git checkout gh-pages` 2. Update all version tags 1. `index.html` 3. 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It can generate graphs of various sizes and is specifically designed to create input files for a wide range of graph-based research applications, including testing, benchmarking, and performance analysis of graph processing frameworks. PyRGG is aimed at computer scientists who are studying graph algorithms and graph processing frameworks. Website: https://www.pyrgg.site Repo: https://github.com/sepandhaghighi/pyrgg extra: recipe-maintainers: - sepandhaghighi pyrgg-1.6/otherfile/profiles/000077500000000000000000000000001471451651000163205ustar00rootroot00000000000000pyrgg-1.6/otherfile/profiles/er_profile.py000066400000000000000000000005041471451651000210170ustar00rootroot00000000000000# -*- coding: utf-8 -*- """Profile file.""" from pyrgg import * import pyrgg.engines.erdos_reyni as er_engine import random os.environ["PYRGG_TEST_MODE"] = "1" random.seed(400) er_engine.gen_using( dimacs_maker, 'profile', { 'vertices': 10000, 'edge_number': 5000, 'direct': 1, } ) pyrgg-1.6/otherfile/profiles/erg_profile.py000066400000000000000000000005151471451651000211700ustar00rootroot00000000000000# -*- coding: utf-8 -*- """Profile file.""" from pyrgg import * import pyrgg.engines.erdos_reyni_gilbert as erg_engine import random os.environ["PYRGG_TEST_MODE"] = "1" random.seed(400) erg_engine.gen_using( dimacs_maker, 'profile', { 'vertices': 10000, 'probability': 0.5, 'direct': 1, } ) pyrgg-1.6/otherfile/profiles/pyrgg_profile.py000066400000000000000000000007071471451651000215460ustar00rootroot00000000000000# -*- coding: utf-8 -*- """Profile file.""" from pyrgg import * import pyrgg.engines.pyrgg as pyrgg_engine import random os.environ["PYRGG_TEST_MODE"] = "1" random.seed(400) pyrgg_engine.gen_using( dimacs_maker, 'profile', { 'min_weight':1, 'max_weight':5000, 'vertices':10000, 'min_edge':5, 'max_edge':600, 'sign':0, 'direct':1, 'self_loop':1, 'multigraph':1, } ) pyrgg-1.6/otherfile/requirements-splitter.py000066400000000000000000000004041471451651000214340ustar00rootroot00000000000000# -*- coding: utf-8 -*- """Requirements splitter.""" test_req = "" with open('dev-requirements.txt', 'r') as f: for line in f: if '==' not in line: test_req += line with open('test-requirements.txt', 'w') as f: f.write(test_req) pyrgg-1.6/otherfile/version_check.py000066400000000000000000000065431471451651000177010ustar00rootroot00000000000000# -*- coding: utf-8 -*- """Version-check script.""" import os import sys import codecs Failed = 0 VERSION = "1.6" VERSION_1 = VERSION.split(".")[0] VERSION_2 = str(int(float(VERSION) * 10 - int(VERSION_1) * 10)) VERSION_3 = str(int(float(VERSION) * 100 - int(VERSION_1) * 100 - int(VERSION_2) * 10)) VERSION_4 = "0" SETUP_ITEMS = [ "version='{0}'", 'https://github.com/sepandhaghighi/pyrgg/tarball/v{0}'] README_ITEMS = [ "[Version {0}](https://github.com/sepandhaghighi/pyrgg/archive/v{0}.zip)", "[Exe-Version {0}](https://github.com/sepandhaghighi/pyrgg/releases/download/v{0}/PYRGG-{0}.exe)", "Run `PYRGG-{0}.exe`", "pip install pyrgg=={0}"] CHANGELOG_ITEMS = [ "## [{0}]", "https://github.com/sepandhaghighi/pyrgg/compare/v{0}...dev", "[{0}]:"] RC_ITEMS = [ "filevers=({0}, {1}, {2}, {3})", "prodvers=({0}, {1}, {2}, {3})", "(u'FileVersion', u'{0}.{1}.{2}.{3}'),", "(u'ProductVersion', u'{0}, {1}, {2}, {3}')"] PARAMS_ITEMS = ['PYRGG_VERSION = "{0}"'] META_ITEMS = ['% set version = "{0}" %'] SPEC_ITEMS = ['pyrgg_version = "{0}"'] ISSUE_TEMPLATE_ITEMS = ["- PyRGG {0}"] SECURITY_ITEMS = ["| {0} | :white_check_mark: |", "| < {0} | :x: |"] FILES = { "setup.py": SETUP_ITEMS, "PYRGG.spec": SPEC_ITEMS, "README.md": README_ITEMS, "CHANGELOG.md": CHANGELOG_ITEMS, "SECURITY.md": SECURITY_ITEMS, os.path.join( "pyrgg", "params.py"): PARAMS_ITEMS, os.path.join( "otherfile", "meta.yaml"): META_ITEMS, os.path.join( ".github", "ISSUE_TEMPLATE", "bug_report.yml"): ISSUE_TEMPLATE_ITEMS, } TEST_NUMBER = len(FILES.keys()) + 1 def print_result(failed=False): """ Print final result. :param failed: failed flag :type failed: bool :return: None """ message = "Version tag tests " if not failed: print("\n" + message + "passed!") else: print("\n" + message + "failed!") print("Passed : " + str(TEST_NUMBER - Failed) + "/" + str(TEST_NUMBER)) if __name__ == "__main__": for file_name in FILES.keys(): try: file_content = codecs.open( file_name, "r", "utf-8", 'ignore').read() for test_item in FILES[file_name]: if file_content.find(test_item.format(VERSION)) == -1: print("Incorrect version tag in " + file_name) Failed += 1 break except Exception as e: Failed += 1 print("Error in " + file_name + "\n" + "Message : " + str(e)) try: file_content = codecs.open( os.path.join( "otherfile", "Version.rc"), "r", "utf-8", 'ignore').read() for test_item in RC_ITEMS: if file_content.find( test_item.format( VERSION_1, VERSION_2, VERSION_3, VERSION_4)) == -1: print("Incorrect version tag in " + "Version.rc") Failed += 1 break except Exception as e: Failed += 1 print("Error in Version.rc" + "\n" + "Message : " + str(e)) if Failed == 0: print_result(False) sys.exit(0) else: print_result(True) sys.exit(1) pyrgg-1.6/paper/000077500000000000000000000000001471451651000136235ustar00rootroot00000000000000pyrgg-1.6/paper/10.21105.joss.00331.pdf000066400000000000000000006032451471451651000166410ustar00rootroot00000000000000%PDF-1.5 % 19 0 obj << /Length 1413 /Filter /FlateDecode >> stream xڭWY6~ϯУ THL{4 r,bEhIYYHy7ίC9E  i,7b',Ȳv,J cYc}8]CK-Fg,_oXPJ4eV@Y2΃()/Hpe Q7-nƒyL"#̓p^EjOe I  K/ݠ}{?cy(iG;ry,kS ORRdK/],( ˬF49#E{w8 `o6W@2JrfƊpyT%JsCti?+cHsNO"tڌV{)pSzѸЬnG7ݭZmžQv픊Ox3NC Uet~:?g$tH#M& ӧ@nnxVYo]';cY-tN+#"|Q:"&hSւU. 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Pyrgg has the ability to generate graphs of different sizes and is designed to provide input files for broad range of graph-based research applications, including but not limited to testing, benchmarking and performance-analysis of graph processing frameworks. [@Zhong2012; @Chakrabarti2004] Pyrgg target audiences are computer scientists who study graph algorithms and graph processing frameworks. Graph Specifications : - Weighted - Signed - Self Loop - Parallel Arc - Sparse - Dense Supported Formats: - DIMACS(.gr) - CSV(.csv) - JSON(.json) - YAML(.yaml) - Weighted Edge List(.wel) - ASP(.lp) - Trivial Graph Format(.tgf) - UCINET DL Format(.dl) - Pickle(.p) See README.md from the Pyrgg repository for further details website : pyrgg.shaghighi.ir ![Pyrgg Logo](pyrgg-logo.png) # References pyrgg-1.6/paper/pyrgg-logo.png000066400000000000000000001151501471451651000164220ustar00rootroot00000000000000PNG  IHDRZb.vsRGBgAMA a pHYs]IDATx^TE֮όP (Č  0`#f0 f1Y Pq`BI*f翷oM{t<>O=ݽjUUV B!"O!Bc$B!򄄖B!DB!ZB!yBBK!"OHh !B -!B<jD߫F_ߚiy^z軵tҰ`0eʔ駟s/.m7zj8:c]B! -Q%T Bf޼y᪫ w_sEvQ;;Z+kQԘ?~:ujx믿>ￛȣO?dCb~I'dB,*BbCBKG w^3gNf=1u6dAJÙO?t3F0BN̻F'zΗB! X-^8y4OM.rv}pg[guqAUieTCu]y֢bo ]vY8Sl[5% !(6$DY&M w\裏َ4m / vX?Qk˛jzo~[k}y[7t0-!ń0\d1?-\КꈏE93¥^jڣxcѤ><}:t`}6h#-!E0~GpդIpmY5MTp1r/W^y-=Mx܈EB!ĊЪp".V=Q. {ænj"Q}r p >pGYf%V[m^|EfD!DB"7;wND^oݼF,T\"3gD4y22PB{BN_ qQ5{p'4G O{Bl B>Yxz- bQB! 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W^yܫ) wm]s5aѢE&0ɋN:ɚPz!D"%;:͛CBuϤӬXMM (i`-2qvf Q.Bj!.2j]p N枭J9rBRfbP>!~-7:/PNy%'F@\@׮]Ë/hqn 4(ԥ 9, Xc wF\'KBKGBKQc ~ac=̣4u։mJ?>,.6!G-".Ą叚5["B ?`>=_ ?ix9Hd Q GKQ!!8o5\3O CZӚ38#qvy0f]\ =ȣ%Q\daȐ!a G}4\~&V-8n)r-Yt|:YB.$5*[j^ +LФx)v;Я_?dq}$"o /v^QF rYgHDċ75#bDP4CFY ݻwOx?T~B;WTTXwy'!^y*&!\x[,DzڄNMBN^QP+ad 7ܐ#<:s=C-/ AŨIq~, Ⱥl[U"Kڋ":s_oMtV[o=lv{j!LN;0zhE?O=p뭷Jd ! B$k!fy@S~rB5xMCH&Zk-;ODe]&Ob9B s 7'E\_CggrBQZBs4vX޼yl?\ EyCJ |_?t9#,\:$%""=ȏ5*L81|嗶o{H " + SOURCE_DIR) with open("logfile.log", "a") as file: ENGINE_MAPPER[engine].logger(file, file_name + SUFFIX_MENU[output_format], elapsed_time_format, input_dict) def run(input_dict=None): """ Run proper converter. :param input_dict: input data :type input_dict: dict :return: None """ if input_dict is None: input_dict = get_input() if input_dict["config"] is True: print("Config --> " + save_config(input_dict)) file_name = input_dict["file_name"] number_of_files = input_dict["number_of_files"] line(40) for i in range(number_of_files): print("Generating {0} from {1}".format(i + 1, number_of_files)) file_name_temp = file_name if number_of_files > 1: file_name_temp = file_name + "_" + str(i + 1) gen_graph(input_dict, file_name_temp) line(40) def main(): """ CLI main function. :return: None """ parser = argparse.ArgumentParser() parser.add_argument('--version', help='version', nargs="?", const=1) parser.add_argument('--config', help='config') parser.add_argument('test', help='test', nargs="?", const=1) args = parser.parse_args() if args.version: print(PYRGG_VERSION) elif args.test: print("Testing ...") error_flag = doctest.testfile("test.py", verbose=False)[0] if error_flag == 0: print("Done!") sys.exit(error_flag) else: tprint("PyRGG", "larry3d") tprint("v" + PYRGG_VERSION) description_print() EXIT_FLAG = False input_dict = None while not EXIT_FLAG: if args.config: input_dict = load_config(args.config) else: input_dict = check_for_config() run(input_dict) INPUTINDEX = str( input("Press [R] to restart PyRGG or any other key to exit.")) if INPUTINDEX.upper() != "R": EXIT_FLAG = True if __name__ == "__main__": main() pyrgg-1.6/pyrgg/engines/000077500000000000000000000000001471451651000152745ustar00rootroot00000000000000pyrgg-1.6/pyrgg/engines/__init__.py000066400000000000000000000000561471451651000174060ustar00rootroot00000000000000# -*- coding: utf-8 -*- """Engines module.""" pyrgg-1.6/pyrgg/engines/erdos_reyni.py000066400000000000000000000056651471451651000202040ustar00rootroot00000000000000# -*- coding: utf-8 -*- """Erdős-Rényi Engine module.""" from random import shuffle from pyrgg.params import ENGINE_MENU, PYRGG_LOGGER_ERROR_MESSAGE from pyrgg.functions import save_log def edge_gen(n, m, direct): """ Generate each vertex connection number. :param n: number of vertices :type n: int :param m: number of edges :type m: int :param direct: directed graph flag :type direct: bool :return: list of dicts """ edge_dic = {} weight_list = [] edge_mold = [] max_edge = (n * (n - 1)) // 2 if direct: max_edge *= 2 m = min(m, max_edge) edge_mold = m * [1] + (max_edge - m) * [0] shuffle(edge_mold) for i in range(1, n + 1): edge_dic[i] = [] temp_list = [] dest_list = range(i + 1, n + 1) if direct: dest_list = [*range(1, i), *dest_list] for j in dest_list: if edge_mold.pop() == 1: temp_list.append(1) edge_dic[i].append(j) weight_list.append(temp_list) return [edge_dic, dict(zip(range(1, n + 1), weight_list)), m] def gen_using( gen_function, file_name, input_dict): """ Generate graph using given function based on Erdos Renyi - G(n, m) model. Refer to (https://en.wikipedia.org/wiki/Erd%C5%91s%E2%80%93R%C3%A9nyi_model). :param gen_function: generation function :type gen_function: function object :param file_name: file name :type file_name: str :param input_dict: input data :type input_dict: dict :return: number of edges as int """ edge_dic, weight_dic, edge_number = edge_gen( input_dict['vertices'], input_dict['edge_number'], input_dict['direct']) gen_function( edge_dic, weight_dic, { "file_name": file_name, "vertices_number": input_dict['vertices'], "edge_number": edge_number, "weighted": False, "max_weight": 1, "min_weight": 1, "direct": input_dict['direct'], "multigraph": False, }) return edge_number def logger(file, file_name, elapsed_time, input_dict): """ Save generated graph logs for Erdős-Rényi engine. :param file: file to write log into :type file: file object :param file_name: file name :type file_name: str :param elapsed_time: elapsed time :type elapsed_time: str :param input_dict: input data :type input_dict: dict :return: None """ try: text = "Vertices : {0}\n".format(input_dict['vertices']) text += "Total Edges : {0}\n".format(input_dict['edge_number']) text += "Directed : {0}\n".format(bool(input_dict['direct'])) text += "Engine : {0} ({1})\n".format(input_dict['engine'], ENGINE_MENU[input_dict['engine']]) save_log(file, file_name, elapsed_time, text) except Exception: print(PYRGG_LOGGER_ERROR_MESSAGE) pyrgg-1.6/pyrgg/engines/erdos_reyni_gilbert.py000066400000000000000000000056201471451651000217030ustar00rootroot00000000000000# -*- coding: utf-8 -*- """Erdős-Rényi-Gilbert Engine module.""" from random import random from pyrgg.params import ENGINE_MENU, PYRGG_LOGGER_ERROR_MESSAGE from pyrgg.functions import save_log def edge_gen(n, p, direct): """ Generate each vertex connection number. :param n: number of vertices :type n: int :param p: probability :type p: float :param direct: directed graph flag :type direct: bool :return: list of dicts """ edge_dic = {} edge_number = 0 weight_list = [] for i in range(1, n + 1): edge_dic[i] = [] temp_list = [] dest_list = range(i + 1, n + 1) if direct: dest_list = [*range(1, i), *dest_list] for j in dest_list: if random() < p: temp_list.append(1) edge_dic[i].append(j) edge_number += 1 weight_list.append(temp_list) return [edge_dic, dict(zip(range(1, n + 1), weight_list)), edge_number] def gen_using( gen_function, file_name, input_dict): """ Generate graph using given function based on Erdos Renyi Gilbert - G(n, p) model. Refer to (https://en.wikipedia.org/wiki/Erd%C5%91s%E2%80%93R%C3%A9nyi_model). :param gen_function: generation function :type gen_function: function object :param file_name: file name :type file_name: str :param input_dict: input data :type input_dict: dict :return: number of edges as int """ edge_dic, weight_dic, edge_number = edge_gen( input_dict['vertices'], input_dict['probability'], input_dict['direct']) gen_function( edge_dic, weight_dic, { "file_name": file_name, "vertices_number": input_dict['vertices'], "edge_number": edge_number, "weighted": False, "max_weight": 1, "min_weight": 1, "direct": input_dict['direct'], "multigraph": False, }) return edge_number def logger(file, file_name, elapsed_time, input_dict): """ Save generated graph logs for Erdős-Rényi-Gilbert engine. :param file: file to write log into :type file: file object :param file_name: file name :type file_name: str :param elapsed_time: elapsed time :type elapsed_time: str :param input_dict: input data :type input_dict: dict :return: None """ try: text = "Vertices : {0}\n".format(input_dict['vertices']) text += "Probability : {0}\n".format(input_dict['probability']) text += "Total Edges : {0}\n".format(input_dict['edge_number']) text += "Directed : {0}\n".format(bool(input_dict['direct'])) text += "Engine : {0} ({1})\n".format(input_dict['engine'], ENGINE_MENU[input_dict['engine']]) save_log(file, file_name, elapsed_time, text) except Exception: print(PYRGG_LOGGER_ERROR_MESSAGE) pyrgg-1.6/pyrgg/engines/pyrgg.py000066400000000000000000000217721471451651000170070ustar00rootroot00000000000000# -*- coding: utf-8 -*- """PyRGG Engine module.""" import os from random import randint, uniform, choice from pyrgg.params import ENGINE_MENU, PYRGG_LOGGER_ERROR_MESSAGE from pyrgg.functions import is_weighted, get_precision, threshold_calc from pyrgg.functions import get_min_max_weight, is_multigraph from pyrgg.functions import save_log def branch_gen( vertex_index, max_edge, min_edge, min_weight, max_weight, precision, sign, direct, self_loop, multigraph, used_vertices, degree_dict, degree_sort_dict): """ Generate branch and weight vector of each vertex. :param vertex_index: origin vertex index :type vertex_index: int :param max_edge: maximum number of edges (connected to each vertex) :type max_edge: int :param min_edge: minimum number of edges (connected to each vertex) :type min_edge: int :param min_weight: weight min range :type min_weight: int :param max_weight: weight max range :type max_weight: int :param precision: numbers precision :type precision: int :param sign: weight sign flag :type sign: bool :param direct: directed and undirected graph flag :type direct: bool :param self_loop: self loop flag :type self_loop: bool :param multigraph: multigraph flag :type multigraph: bool :param used_vertices: used vertices dictionary :type used_vertices: dict :param degree_dict: all vertices degree :type degree_dict: dict :param degree_sort_dict: degree to vertices list :type degree_sort_dict: dict :return: branch and weight list """ index = 0 branch_list = [] weight_list = [] reference_vertices = [] random_unit = randint vertex_degree = degree_dict[vertex_index] if vertex_degree >= max_edge: return [branch_list, weight_list] threshold = threshold_calc( min_edge=min_edge, max_edge=max_edge, vertex_degree=vertex_degree) for i in range(max_edge + 1): reference_vertices.extend(list(degree_sort_dict[i].values())) if len(reference_vertices) >= threshold: break if precision > 0: random_unit = uniform if not direct and ( vertex_index in used_vertices) and not multigraph: reference_vertices = list( set(reference_vertices) - set(used_vertices[vertex_index])) if not self_loop and vertex_index in reference_vertices: reference_vertices.remove(vertex_index) if int(os.environ.get("PYRGG_TEST_MODE", 0)): reference_vertices.sort() while (index < threshold): vertex_degree = degree_dict[vertex_index] if vertex_degree >= max_edge: break if len(reference_vertices) == 0: break random_tail_index = choice( range(len(reference_vertices))) random_tail = reference_vertices[random_tail_index] random_tail_degree = degree_dict[random_tail] if random_tail_degree >= max_edge or ( random_tail == vertex_index and random_tail_degree >= ( max_edge - 1)): reference_vertices.pop(random_tail_index) continue if not direct: try: used_vertices[random_tail].append(vertex_index) except KeyError: used_vertices[random_tail] = [vertex_index] weight_sign = 1 if sign: weight_sign = choice([1, -1]) random_weight = weight_sign * random_unit(min_weight, max_weight) random_weight = round(random_weight, precision) branch_list.append(random_tail) weight_list.append(random_weight) index += 1 del degree_sort_dict[vertex_degree][vertex_index] degree_dict[random_tail] += 1 degree_dict[vertex_index] += 1 degree_sort_dict[degree_dict[vertex_index] ][vertex_index] = vertex_index if random_tail != vertex_index: del degree_sort_dict[random_tail_degree][random_tail] degree_sort_dict[degree_dict[random_tail] ][random_tail] = random_tail if not multigraph: reference_vertices.pop(random_tail_index) return [branch_list, weight_list] def edge_gen( vertices_number, min_weight, max_weight, min_edge, max_edge, sign, direct, self_loop, multigraph): """ Generate each vertex connection number. :param vertices_number: number of vertices :type vertices_number: int :param min_weight: weight min range :type min_weight: int :param max_weight: weight max range :type max_weight: int :param min_edge: minimum number of edges (connected to each vertex) :type min_edge: int :param max_edge: maximum number of edges (connected to each vertex) :type max_edge: int :param sign: weight sign flag :type sign: bool :param direct: directed and undirected graph flag :type direct: bool :param self_loop: self loop flag :type self_loop: bool :param multigraph: multigraph flag :type multigraph: bool :return: list of dicts """ precision = max( get_precision(max_weight), get_precision(min_weight)) temp = 0 vertices_id = list(range(1, vertices_number + 1)) vertices_edge = [] weight_list = [] used_vertices = {} degree_sort_dict = {i: {} for i in range(max_edge + 1)} degree_dict = {} for i in vertices_id: degree_dict[i] = 0 degree_sort_dict[0][i] = i branch_gen_params = { "max_edge": max_edge, "min_edge": min_edge, "min_weight": min_weight, "max_weight": max_weight, "sign": sign, "direct": direct, "self_loop": self_loop, "multigraph": multigraph, "used_vertices": used_vertices, "degree_dict": degree_dict, "degree_sort_dict": degree_sort_dict, "precision": precision} for i in vertices_id: temp_list = branch_gen(vertex_index=i, **branch_gen_params) vertices_edge.append(temp_list[0]) weight_list.append(temp_list[1]) temp = temp + len(temp_list[0]) return [dict(zip(vertices_id, vertices_edge)), dict(zip(vertices_id, weight_list)), temp] def gen_using( gen_function, file_name, input_dict): """ Generate graph using given function based on PyRGG model. :param gen_function: generation function :type gen_function: function object :param file_name: file name :type file_name: str :param input_dict: input data :type input_dict: dict :return: number of edges as int """ edge_dic, weight_dic, edge_number = edge_gen( input_dict['vertices'], input_dict['min_weight'], input_dict['max_weight'], input_dict['min_edge'], input_dict['max_edge'], input_dict['sign'], input_dict['direct'], input_dict['self_loop'], input_dict['multigraph']) min_weight, max_weight = get_min_max_weight(weight_dic) weighted = is_weighted(max_weight, min_weight, bool(input_dict['sign'])) gen_function( edge_dic, weight_dic, { "file_name": file_name, "vertices_number": input_dict['vertices'], "weighted": weighted, "edge_number": edge_number, "min_weight": min_weight, "max_weight": max_weight, "direct": input_dict['direct'], "multigraph": is_multigraph(edge_dic), }) return edge_number def logger(file, file_name, elapsed_time, input_dict): """ Save generated graph logs for PyRGG engine. :param file: file to write log into :type file: file object :param file_name: file name :type file_name: str :param elapsed_time: elapsed time :type elapsed_time: str :param input_dict: input data :type input_dict: dict :return: None """ try: text = "Vertices : {0}\n".format(input_dict['vertices']) text += "Total Edges : {0}\n".format(input_dict['edge_number']) text += "Max Edge : {0}\n".format(input_dict['max_edge']) text += "Min Edge : {0}\n".format(input_dict['min_edge']) text += "Directed : {0}\n".format(bool(input_dict['direct'])) text += "Signed : {0}\n".format(bool(input_dict['sign'])) text += "Multigraph : {0}\n".format(bool(input_dict['multigraph'])) text += "Self Loop : {0}\n".format(bool(input_dict['self_loop'])) text += "Weighted : {0}\n".format( is_weighted(input_dict['max_weight'], input_dict['min_weight'], bool(input_dict['sign']))) text += "Max Weight : {0}\n".format(input_dict['max_weight']) text += "Min Weight : {0}\n".format(input_dict['min_weight']) text += "Engine : {0} ({1})\n".format( input_dict['engine'], ENGINE_MENU[input_dict['engine']]) save_log(file, file_name, elapsed_time, text) except Exception: print(PYRGG_LOGGER_ERROR_MESSAGE) pyrgg-1.6/pyrgg/functions.py000066400000000000000000000370641471451651000162400ustar00rootroot00000000000000# -*- coding: utf-8 -*- """Pyrgg functions module.""" import os from random import randint from json import loads as json_loads from json import dump as json_dump from pickle import dump as pickle_dump from yaml import safe_dump as yaml_dump import datetime import pyrgg.params def is_weighted(max_weight, min_weight, signed): """ Check the graph is weighted or not. :param max_weight: maximum weight :type max_weight: int :param min_weight: minimum weight :type min_weight: int :param signed: weight sign flag :type signed: bool :return: result as bool """ if max_weight == min_weight and min_weight == 0: return False if max_weight == min_weight and min_weight == 1 and not signed: return False return True def get_min_max_weight(weight_dic): """ Get minimum and maximum weight values. :param weight_dic: weight dictionary :type weight_dic: dict :return: minimum and maximum weight values """ all_weights = [abs(w) for weights in weight_dic.values() for w in weights] return min(all_weights), max(all_weights) def is_signed(weight_dic): # pragma: no cover """ Check if the graph is signed. :param weight_dic: weight dictionary :type weight_dic: dict :return: signed flag """ return any([any([w < 0 for w in weights]) for weights in weight_dic.values()]) def has_self_loop(edge_dic): # pragma: no cover """ Check if the graph has self loops. :param edge_dic: edge dictionary :type edge_dic: dict :return: self looped flag """ return any([v in edges for v, edges in edge_dic.items()]) def is_multigraph(edge_dic): """ Check if the graph is a multigraph. :param edge_dic: edge dictionary :type edge_dic: dict :return: multigraph flag """ return any([len(set(edges)) != len(edges) for edges in edge_dic.values()]) def get_precision(input_number): """ Return precision of input number. :param input_number: input number :type input_number: float :return: precision as int """ try: number_str = str(input_number) _, decimal_part = number_str.split(".") return len(decimal_part) except Exception: return 0 def threshold_calc(min_edge, max_edge, vertex_degree): """ Calculate threshold for branch_gen_pyrgg function. :param min_edge: minimum number of edges (connected to each vertex) :type min_edge: int :param max_edge: maximum number of edges (connected to each vertex) :type max_edge: int :param vertex_degree: vertex degree :type vertex_degree: int :return: threshold as int """ threshold = min_edge lower_limit = 0 upper_limit = max_edge - vertex_degree if vertex_degree < min_edge: lower_limit = min_edge - vertex_degree if upper_limit > lower_limit: threshold = randint(lower_limit, upper_limit) return threshold def is_float(input_number): """ Check input for float conversion. :param input_number: input number :type input_number: float or int or str :return: result as bool """ try: _, decimal_part = divmod(float(input_number), 1) except TypeError: return False else: return True if decimal_part else False def handle_string(string): """ Handle string and raise ValueError if it is empty. :param string: input string :type string: str :return: result as str """ if string == "": raise ValueError return string def handle_pos_int(input_number): """ Handle input number and raise ValueError if it is negative. :param input_number: input number :type input_number: float or int or str :return: result as int """ val = int(input_number) if val < 0: raise ValueError return val def handle_str_to_number(string): """ Convert string to float or int. :param string: input string :type string: str :return: result as float or int """ return float(string) if is_float(string) else int(string) def handle_str_prob(string): """ Convert string to float and raise ValueError if string is invalid. :param string: input string :type string: str :return: result as float """ val = handle_str_to_number(string) if val < 0: raise ValueError if val > 1: raise ValueError return val def handle_str_to_bool(string): """ Convert 0/1 string to bool and raise ValueError if string is invalid. :param string: input string :type string: str :return: result as bool """ val = int(string) if val not in [0, 1]: raise ValueError return bool(val) def handle_output_format(string): """ Convert string to output format index. :param string: input string :type string: str :return: output format index as int """ output_format = handle_pos_int(string) if output_format not in pyrgg.params.SUFFIX_MENU: raise ValueError return output_format def handle_engine(string): """ Convert string to engine index. :param string: input string :type string: str :return: engine index as int """ engine = handle_pos_int(string) if engine not in pyrgg.params.ENGINE_MENU: raise ValueError return engine ITEM_HANDLERS = { "file_name": handle_string, "output_format": handle_output_format, "weight": handle_str_to_bool, "engine": handle_engine, "vertices": handle_pos_int, "number_of_files": handle_pos_int, "max_weight": handle_str_to_number, "min_weight": handle_str_to_number, "min_edge": handle_pos_int, "max_edge": handle_pos_int, "edge_number": handle_pos_int, "sign": handle_str_to_bool, "direct": handle_str_to_bool, "self_loop": handle_str_to_bool, "multigraph": handle_str_to_bool, "config": handle_str_to_bool, "probability": handle_str_prob, } def description_print(): """ Print justified description for overview in console. :return: None """ print(pyrgg.params.PYRGG_LINKS) line(40) print("\n") print(pyrgg.params.PYRGG_DESCRIPTION) print("\n") line(40) def line(num=11, char="#"): """ Print line of char. :param num: number of character in this line :type num : int :param char: character :type char: str :return: None """ print(char * num) def convert_bytes(num): """ Convert num to idiomatic byte unit. :param num: the input number. :type num: int :return: result as str """ for x in ['bytes', 'KB', 'MB', 'GB', 'TB']: if num < 1024.0: return "%3.1f %s" % (num, x) num /= 1024.0 def filesize(fileaddr): # pragma: no cover """ Calculate output file size. :param fileaddr: file addresses :type fileaddr: str :return: file size for print as string """ file_info = os.stat(fileaddr) file_size = file_info.st_size print("Graph File Size : " + convert_bytes(file_size)) def time_convert(input_time): """ Convert input_time from sec to DD,HH,MM,SS format. :param input_time: input time in sec :type input_time: float :return: converted time as str """ postfix_dict = {"s": "second", "d": "day", "h": "hour", "m": "minute"} value_dict = {"s": 0, "d": 0, "h": 0, "m": 0} value_dict["s"] = float(input_time) value_dict["d"], value_dict["s"] = divmod(value_dict["s"], 24 * 3600) value_dict["h"], value_dict["s"] = divmod(value_dict["s"], 3600) value_dict["m"], value_dict["s"] = divmod(value_dict["s"], 60) for i in postfix_dict: if value_dict[i] != 1: postfix_dict[i] += "s" return ", ".join([ "{0:02.0f} {1}".format(value_dict["d"], postfix_dict["d"]), "{0:02.0f} {1}".format(value_dict["h"], postfix_dict["h"]), "{0:02.0f} {1}".format(value_dict["m"], postfix_dict["m"]), "{0:02.0f} {1}".format(value_dict["s"], postfix_dict["s"]), ]) def input_filter(input_dict): """ Filter input data. :param input_dict: input dictionary :type input_dict: dict :return: filtered data as dict """ filtered_dict = input_dict.copy() edge_upper_threshold = filtered_dict["vertices"] for key in ["min_edge", "max_edge", "vertices"]: if filtered_dict[key] < 0: filtered_dict[key] *= -1 if filtered_dict["min_weight"] > filtered_dict["max_weight"]: filtered_dict["min_weight"], filtered_dict["max_weight"] = ( filtered_dict["max_weight"], filtered_dict["min_weight"] ) if filtered_dict["min_edge"] > filtered_dict["max_edge"]: filtered_dict["min_edge"], filtered_dict["max_edge"] = ( filtered_dict["max_edge"], filtered_dict["min_edge"] ) if not filtered_dict["self_loop"]: edge_upper_threshold -= 1 if not filtered_dict["multigraph"]: for key in ["min_edge", "max_edge"]: filtered_dict[key] = min(filtered_dict[key], edge_upper_threshold) return filtered_dict def get_input(input_func=input): """ Get input from user and return as dictionary. :param input_func: input function :type input_func: function object :return: inputs as dict """ result_dict = { "file_name": "", "number_of_files": 1, "vertices": 0, "max_weight": 1, "min_weight": 1, "min_edge": 0, "max_edge": 0, "edge_number": 0, "sign": True, "output_format": 1, "weight": True, "engine": 1, "direct": True, "self_loop": True, "multigraph": False, "config": False, "probability": 0.5, } result_dict = _update_using_menu(result_dict, input_func) result_dict = _update_with_engine_params( result_dict, input_func, pyrgg.params.ENGINE_PARAM_MAP[result_dict['engine']]) return input_filter(result_dict) def _update_using_menu(result_dict, input_func): """ Update result_dict using user input from the menu. :param result_dict: result data :type result_dict: dict :param input_func: input function :type input_func: function object :return: result_dict as dict """ for index in sorted(pyrgg.params.MENU_ITEMS): item1, item2 = pyrgg.params.MENU_ITEMS[index] while True: try: result_dict[item1] = ITEM_HANDLERS[item1]( input_func(item2) ) except Exception: print(pyrgg.params.PYRGG_INPUT_ERROR_MESSAGE) else: break return result_dict def _update_with_engine_params(result_dict, input_func, engine_params): """ Update result_dict using user input based on given engine requirements. :param result_dict: result data :type result_dict: dict :param input_func: input function :type input_func: function object :param engine_params: engine parameters :type engine_params: dict :return: result_dict as dict """ for index in sorted(engine_params): item1, item2 = engine_params[index] if not result_dict["weight"] and item1 in ["max_weight", "min_weight"]: continue while True: try: result_dict[item1] = ITEM_HANDLERS[item1]( input_func(item2) ) except Exception: print(pyrgg.params.PYRGG_INPUT_ERROR_MESSAGE) else: break return result_dict def json_to_yaml(filename): """ Convert json file to yaml file. :param filename: filename :type filename: str :return: None """ try: with open(filename + ".json", "r") as json_file: json_data = json_loads(json_file.read()) with open(filename + ".yaml", "w") as yaml_file: yaml_dump(json_data, yaml_file, default_flow_style=False) except FileNotFoundError: print(pyrgg.params.PYRGG_YAML_ERROR_MESSAGE) def json_to_pickle(filename): """ Convert json file to pickle file. :param filename: filename :type filename: str :return: None """ try: with open(filename + ".json", "r") as json_file: json_data = json_loads(json_file.read()) with open(filename + ".p", "wb") as pickle_file: pickle_dump(json_data, pickle_file) except FileNotFoundError: print(pyrgg.params.PYRGG_PICKLE_ERROR_MESSAGE) def save_config(input_dict): """ Save input_dict as the generation config. :param input_dict: input data :type input_dict: dict :return: path to file as str """ try: input_dict_temp = input_dict.copy() input_dict_temp['engine'] = pyrgg.params.ENGINE_MENU[input_dict_temp['engine']] input_dict_temp['pyrgg_version'] = pyrgg.params.PYRGG_VERSION input_dict_temp['output_format'] = pyrgg.params.OUTPUT_FORMAT[input_dict_temp['output_format']] fname = pyrgg.params.CONFIG_FILE_FORMAT.format( input_dict_temp['file_name']) with open(fname, "w") as json_file: json_dump(input_dict_temp, json_file, indent=2) return os.path.abspath(fname) except BaseException: print(pyrgg.params.PYRGG_CONFIG_SAVE_ERROR_MESSAGE) def load_config(path): """ Load config based on given path. :param path: path to config file :type path: str :return: input data as dict """ try: with open(path, "r") as json_file: config = json_loads(json_file.read()) config['output_format'] = pyrgg.params.OUTPUT_FORMAT_INV[config['output_format']] config['engine'] = pyrgg.params.ENGINE_MENU_INV[config['engine']] return input_filter(config) except BaseException: print(pyrgg.params.PYRGG_CONFIG_LOAD_ERROR_MESSAGE) def _print_select_config(configs, input_func=input): """ Print configs in current directory and get input from user. :param configs: configs path :type configs: list :param input_func: input function :type input_func: function object :return: input data as dict """ if len(configs) == 0: return None print(pyrgg.params.PYRGG_CONFIG_LIST_MESSAGE) for i, config in enumerate(configs): print("[{}] - {}".format(i + 1, config)) key = input_func(pyrgg.params.PYRGG_CONFIG_LOAD_MESSAGE) try: return load_config(configs[int(key) - 1]) except BaseException: return None def check_for_config(input_func=input): """ Check for config files in source directory. :param input_func: input function :type input_func: function object :return: input data as dict """ configs = [] for filename in os.listdir(pyrgg.params.SOURCE_DIR): file = os.path.join(pyrgg.params.SOURCE_DIR, filename) if os.path.isfile(file) and filename.endswith( pyrgg.params.CONFIG_FILE_FORMAT.format("")): configs.append(file) return _print_select_config(configs, input_func) def save_log(file, file_name, elapsed_time, text): """ Save generated graph logs. :param file: file to write log into :type file: file object :param file_name: file name :type file_name: str :param elapsed_time: elapsed time :type elapsed_time: str :param text: rest part of the text to write :type text: str :return: None """ text2file = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S') + "\n" text2file += "Filename : {0}\n".format(file_name) text2file += text text2file += "Elapsed Time : {0}\n".format(elapsed_time) text2file += "-------------------------------\n" file.write(text2file) pyrgg-1.6/pyrgg/graph_gen.py000066400000000000000000000370571471451651000161640ustar00rootroot00000000000000# -*- coding: utf-8 -*- """PyRGG graph generators module.""" import random import datetime from pyrgg.params import * from pyrgg.functions import * # random_system=random.SystemRandom() random_system = random def dimacs_maker( edge_dic, weight_dic, mdata): """ Create output file and fill in. :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :param mdata: meta data :type mdata: dict :return: None """ with open(mdata['file_name'] + ".gr", "w") as buf: buf.write( DIMACS_FIX.format( mdata['file_name'], str(mdata['vertices_number']), str(mdata['edge_number']), str(mdata['max_weight']), str(mdata['min_weight']))) _write_separated_file( buf, edge_dic, weight_dic, separator=' ', prefix='a', ) def json_maker( edge_dic, weight_dic, mdata): """ Create output file in json format. :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :param mdata: meta data :type mdata: dict :return: None """ with open(mdata['file_name'] + ".json", "w") as buf: _write_properties_to_json( buf, mdata['weighted'], mdata['direct'], mdata['multigraph'],) _write_data_to_json( buf, edge_dic, weight_dic, ) def _write_data_to_json(buf, edge_dic, weight_dic): """Write data to json buffer. :param buf: output file object :type buf: file_object :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :return: None """ buf.write('\n\t"graph": {\n') _write_nodes_to_json(buf, edge_dic) buf.write("\n\t\t],\n") _write_edges_to_json(buf, edge_dic, weight_dic) buf.write("\n\t\t]\n\t}\n}") def _write_properties_to_json( buf, weighted, direct, multigraph): """ Write properties to json buffer. :param buf: output file object :type buf: file_object :param weighted: weighted graph flag :type weighted: bool :param direct: directed and undirected graph flag :type direct: bool :param multigraph: multigraph flag :type multigraph: bool :return: None """ buf.write('{\n\t"properties": {\n') buf.write('\t\t"weighted": ' + str(weighted).lower() + ",\n") buf.write('\t\t"multigraph": ' + str(multigraph).lower() + ",\n") buf.write('\t\t"directed": ' + str(direct).lower() + "\n") buf.write("},\n") def _write_nodes_to_json(buf, edge_dic): """Write nodes to json. :param buf: output file object :type buf: file_object :param edge_dic: dictionary containing edges data :type edge_dic: dict :return: None """ first_line = True nodes = '\t\t"nodes":[\n' buf.write(nodes) for key in edge_dic: nodes = "" if first_line: first_line = False else: nodes += ",\n" nodes = "".join([ nodes, '\t\t{\n\t\t\t', '"id": ', str(key), '\n\t\t}' ]) buf.write(nodes) def _write_edges_to_json(buf, edge_dic, weight_dic): """Write edges to json. :param buf: output file object :type buf: file_object :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :return: None """ edges = '\t\t"edges":[\n' first_line = True buf.write(edges) for key, edge_val in edge_dic.items(): for j, value in enumerate(edge_val): edges = "" if first_line: first_line = False else: edges += ",\n" edges = "".join([ edges, '\t\t{\n\t\t\t"source": ', str(key), ',\n\t\t\t', '"target": ', str(value), ',\n\t\t\t', '"weight": ', str(weight_dic[key][j]), '\n\t\t}' ]) buf.write(edges) def csv_maker( edge_dic, weight_dic, mdata): """ Create output file in csv format. :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :param mdata: meta data :type mdata: dict :return: None """ with open(mdata['file_name'] + ".csv", "w") as buf: _write_separated_file(buf, edge_dic, weight_dic, separator=',') def tsv_maker( edge_dic, weight_dic, mdata): """ Create output file in tsv format. :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :param mdata: meta data :type mdata: dict :return: None """ with open(mdata['file_name'] + ".tsv", "w") as buf: _write_separated_file(buf, edge_dic, weight_dic, separator='\t') def _write_separated_file(buf, edge_dic, weight_dic, separator, prefix=''): r"""Write data to buffer separated with ``separator``. :param buf: output file object :type buf: file_object :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :param separator: separator in a separated file, like ',', '\t', ' ', etc. :type separator: str :param prefix: prefix to be added in front of each line :type prefix: str :return: None """ dummy_prefix = object() prefix = prefix or dummy_prefix for key, edge_val in edge_dic.items(): for j, value in enumerate(edge_val): elements = [ prefix, str(key), str(value), str(weight_dic[key][j]) + "\n" ] string = separator.join(x for x in elements if x != dummy_prefix) buf.write(string) def wel_maker( edge_dic, weight_dic, mdata): """ Create output file in wel format. :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :param mdata: meta data :type mdata: dict :return: None """ with open(mdata['file_name'] + ".wel", "w") as buf: _write_separated_file(buf, edge_dic, weight_dic, separator=' ') def mtx_maker( edge_dic, weight_dic, mdata): """ Create output file in Matrix Market format. :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :param mdata: meta data :type mdata: dict :return: None """ max_edge_length = len(str(mdata['vertices_number'])) with open(mdata['file_name'] + ".mtx", "w") as buf: buf.write("%%MatrixMarket matrix coordinate real general\n") buf.write( "{0} {0} {1}\n".format(str(mdata['vertices_number']), str(mdata['edge_number'])) ) for key, edge_val in edge_dic.items(): for j, value in enumerate(edge_val): shift1 = (max_edge_length - len(str(key))) + 4 shift2 = (max_edge_length - len(str(value))) + 4 buf.write(str(key) + shift1 * " " + str(value) + shift2 * " " + str(weight_dic[key][j]) + "\n") def lp_maker( edge_dic, weight_dic, mdata): """ Create output file in ASP format. :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :param mdata: meta data :type mdata: dict :return: None """ with open(mdata['file_name'] + ".lp", "w") as buf: for key in edge_dic: buf.write('node(' + str(key) + ").\n") for key, edge_val in edge_dic.items(): for j, value in enumerate(edge_val): buf.write('edge(' + str(key) + "," + str(value) + "," + str(weight_dic[key][j]) + ").\n") def tgf_maker( edge_dic, weight_dic, mdata): """ Create output file in Trivial Graph Format (TGF). :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :param mdata: meta data :type mdata: dict :return: None """ with open(mdata['file_name'] + ".tgf", "w") as buf: for key in edge_dic: buf.write(str(key) + "\n") buf.write("#\n") _write_separated_file(buf, edge_dic, weight_dic, separator=' ') def gl_maker( edge_dic, weight_dic, mdata): """ Create output file in Graph Line(GL). :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :param mdata: meta data :type mdata: dict :return: None """ with open(mdata['file_name'] + ".gl", "w") as buf: for key, edge_val in edge_dic.items(): line_data = str(key) write_flag = False for j, value in enumerate(edge_val): write_flag = True line_data += " " + str(value) + ":" + str(weight_dic[key][j]) if write_flag: buf.write(line_data + "\n") def dl_maker( edge_dic, weight_dic, mdata): """ Create output file in UCINET DL Format. :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :param mdata: meta data :type mdata: dict :return: None """ with open(mdata['file_name'] + ".dl", "w") as buf: buf.write("dl\nformat=edgelist1\nn=" + str(mdata['vertices_number']) + "\ndata:\n") _write_separated_file(buf, edge_dic, weight_dic, separator=' ') def gdf_maker( edge_dic, weight_dic, mdata): """ Create output file in GDF Format. :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :param mdata: meta data :type mdata: dict :return: None """ with open(mdata['file_name'] + ".gdf", "w") as buf: buf.write("nodedef>name VARCHAR,label VARCHAR\n") for key in edge_dic: buf.write(str(key) + "," + "Node{0}".format(str(key)) + "\n") buf.write("edgedef>node1 VARCHAR,node2 VARCHAR,weight DOUBLE\n") _write_separated_file(buf, edge_dic, weight_dic, separator=',') def gml_maker( edge_dic, weight_dic, mdata): """ Create output file in GML Format. :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :param mdata: meta data :type mdata: dict :return: None """ header = 'graph\n[\n multigraph {0}\n directed {1}\n'.format( int(mdata['multigraph']), int(mdata['direct'])) with open(mdata['file_name'] + ".gml", "w") as buf: buf.write(header) for key in edge_dic: buf.write( " node\n [\n id " + str(key) + "\n" + ' label "Node {0}"\n'.format( str(key)) + " ]\n") for key, edge_val in edge_dic.items(): for j, value in enumerate(edge_val): buf.write(" edge\n [\n source " + str(key) + "\n" + " target " + str(value) + "\n" + " value " + str(weight_dic[key][j]) + "\n" + " ]\n") buf.write("]") def gexf_maker( edge_dic, weight_dic, mdata): """ Create output file in GEXF Format. :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :param mdata: meta data :type mdata: dict :return: None """ header = '\n' header += '\n' date = datetime.datetime.now().date() meta = " " * 4 + '\n'.format(date) meta += " " * 8 + 'PyRGG\n' meta += " " * 8 + '{0}\n'.format(mdata['file_name']) meta += " " * 4 + '\n' if mdata['direct']: defaultedgetype = "directed" else: defaultedgetype = "undirected" with open(mdata['file_name'] + ".gexf", "w") as buf: buf.write(header) buf.write(meta) buf.write( " " * 4 + '\n' ) buf.write(" " * 8 + "\n") for key in edge_dic: buf.write( " " * 12 + ''.format( str(key)) + "\n") buf.write(" " * 8 + "\n") buf.write(" " * 8 + "\n") edge_id = 1 for key, edge_val in edge_dic.items(): for j, value in enumerate(edge_val): buf.write( " " * 12 + ''.format( str(weight_dic[key][j])) + "\n") edge_id += 1 buf.write(" " * 8 + "\n") buf.write(" " * 4 + "\n") buf.write("") def dot_maker( edge_dic, weight_dic, mdata): """ Create output file in Dot Format. :param edge_dic: dictionary containing edges data :type edge_dic: dict :param weight_dic: dictionary containing weights data :type weight_dic: dict :param mdata: meta data :type mdata: dict :return: None """ header = "{0} {1}" linker = "--" if mdata['direct']: header = header.format("digraph", mdata['file_name']) linker = "->" else: header = header.format("graph", mdata['file_name']) with open(mdata['file_name'] + ".gv", "w") as buf: buf.write(header + " {") for key, edge_val in edge_dic.items(): for j, value in enumerate(edge_val): buf.write( "\n" + str(key) + " " + linker + " " + str(value) + " [weight={}]".format( weight_dic[key][j]) + ";") buf.write("\n}") pyrgg-1.6/pyrgg/params.py000066400000000000000000000104261471451651000155040ustar00rootroot00000000000000# -*- coding: utf-8 -*- """PyRGG params.""" from textwrap import dedent, fill import os os.environ["PYRGG_TEST_MODE"] = "0" MENU_ITEMS = { 1: ["engine", dedent( """\ - Select generation engine : 1- PyRGG 2- Erdos-Renyi-Gilbert - G(n, p) 3- Erdos-Renyi - G(n, m) """ )], 2: ["file_name", "- File Name (Not Empty) : "], 3: ["number_of_files", "- Number of Files (>=0) : "], 4: ["output_format", dedent( """\ - Graph Formats : 1- DIMACS(.gr) 2- JSON(.json) 3- CSV(.csv) 4- YAML(.yaml) 5- WEL(.wel) 6- ASP(.lp) 7- Pickle(.p) 8- UCINET DL(.dl) 9- TGF(.tgf) 10- TSV(.tsv) 11- Matrix Market(.mtx) 12- Graph Line(.gl) 13- GDF(.gdf) 14- GML(.gml) 15- GEXF(.gexf) 16- DOT(.gv) """ )], 5: ["config", "- Save Config[1] or Not[0]"], } SUFFIX_MENU = { 1: ".gr", 2: ".json", 3: ".csv", 4: ".yaml", 5: ".wel", 6: ".lp", 7: ".p", 8: ".dl", 9: ".tgf", 10: ".tsv", 11: ".mtx", 12: ".gl", 13: ".gdf", 14: ".gml", 15: ".gexf", 16: ".gv" } ENGINE_MENU = { 1: "pyrgg", 2: "erg", 3: "er", } ENGINE_MENU_INV = {v: k for k, v in ENGINE_MENU.items()} PYRGG_ENGINE_PARAMS = { 1: ["vertices", "- Vertices Number (>=0) : "], 2: ["min_edge", "- Min Edge Number - Connected to Each Vertex (>=0) : "], 3: ["max_edge", "- Max Edge Number - Connected to Each Vertex (>=0) : "], 4: ["weight", "- Unweighted[0] or Weighted[1]"], 5: ["min_weight", "- Min Weight : "], 6: ["max_weight", "- Max Weight : "], 7: ["sign", "- Unsigned[0] or Signed[1]"], 8: ["direct", "- Undirected[0] or Directed[1]"], 9: ["self_loop", "- No Self Loop[0] or Self Loop[1]"], 10: ["multigraph", "- Simple[0] or Multigraph[1]"], } ERG_ENGINE_PARAMS = { 1: ["vertices", "- Vertices Number (>=0) : "], 2: ["probability", "- Probability (0 <= p <= 1) : "], 3: ["direct", "- Undirected[0] or Directed[1]"], } ER_ENGINE_PARAMS = { 1: ["vertices", "- Vertices Number (>=0) : "], 2: ["edge_number", "- Edge Number (>=0) : "], 3: ["direct", "- Undirected[0] or Directed[1]"], } ENGINE_PARAM_MAP = { 1: PYRGG_ENGINE_PARAMS, 2: ERG_ENGINE_PARAMS, 3: ER_ENGINE_PARAMS, } OUTPUT_FORMAT = {i: output_format[1:].upper() for i, output_format in SUFFIX_MENU.items()} OUTPUT_FORMAT_INV = {v: k for k, v in OUTPUT_FORMAT.items()} PYRGG_VERSION = "1.6" SOURCE_DIR = os.getcwd() CONFIG_FILE_FORMAT = "{}.pyrgg.config.json" PYRGG_LINKS = """ Webpage : https://www.pyrgg.site Repository : https://github.com/sepandhaghighi/pyrgg Paper : https://doi.org/10.21105/joss.00331 * If you use PyRGG in your research, please cite our paper """ _description = """\ PyRGG is a user-friendly synthetic random graph generator that is written in Python and supports multiple graph file formats, such as DIMACS-Graph files. It can generate graphs of various sizes and is specifically designed to create input files for a wide range of graph-based research applications, including testing, benchmarking, and performance analysis of graph processing frameworks. PyRGG is aimed at computer scientists who are studying graph algorithms and graph processing frameworks. """ PYRGG_DESCRIPTION = fill(_description, width=113) PYRGG_INPUT_ERROR_MESSAGE = "[Error] Bad input!" PYRGG_FILE_ERROR_MESSAGE = "[Error] Bad input file!" PYRGG_INVALID_ENGINE_ERROR_MESSAGE = "[Error] Invalid engine!" PYRGG_YAML_ERROR_MESSAGE = "[Error] Failed to generate YAML file!" PYRGG_PICKLE_ERROR_MESSAGE = "[Error] Failed to generate Pickle file!" PYRGG_LOGGER_ERROR_MESSAGE = "[Error] Logger failed!" PYRGG_CONFIG_LOAD_ERROR_MESSAGE = "[Error] Failed to load config file!" PYRGG_CONFIG_SAVE_ERROR_MESSAGE = "[Error] Failed to save config file!" PYRGG_CONFIG_LIST_MESSAGE = "Config files detected in the current directory are listed below:" PYRGG_CONFIG_LOAD_MESSAGE = "Press the config index to load or any other keys to start with the new one:" DIMACS_FIX = dedent( """\ c FILE :{0}.gr c No. of vertices :{1} c No. of edges :{2} c Max. weight :{3} c Min. weight :{4} p sp {1} {2} """ ) pyrgg-1.6/pyrgg/test.py000066400000000000000000000635651471451651000152140ustar00rootroot00000000000000# -*- coding: utf-8 -*- """Test file.""" """ >>> from pyrgg import * >>> import pyrgg.params >>> import random >>> import os >>> import json >>> import yaml >>> import pickle >>> os.environ["PYRGG_TEST_MODE"] = "1" >>> import pyrgg.engines.pyrgg as engine >>> get_precision(2) 0 >>> get_precision(2.2) 1 >>> get_precision(2.22) 2 >>> get_precision(2.223) 3 >>> handle_str_to_number("20") 20 >>> handle_str_to_number("20.2") 20.2 >>> handle_str_to_bool("1") True >>> handle_str_to_bool("3") Traceback (most recent call last): ... ValueError >>> handle_str_to_bool("0") False >>> is_float(10) False >>> is_float(10.2) True >>> is_float(None) False >>> result = input_filter({"file_name": "test","vertices": 5,"max_weight": 1000,"min_weight":455,"min_edge": -45,"max_edge": -11,"sign": False,"output_format": 1, "direct": False,"self_loop": True,"multigraph":False,"number_of_files":2,"engine":1}) >>> result == {'output_format': 1, 'min_weight': 455, 'min_edge': 5, 'max_edge': 5, 'file_name': 'test', 'vertices': 5, 'max_weight': 1000, 'sign': False, "direct": False,"self_loop": True,"multigraph":False,"number_of_files":2,"engine":1} True >>> result = input_filter({"file_name": "test","vertices": 5,"max_weight": 1000,"min_weight":455,"min_edge": -45,"max_edge": -11,"sign": False,"output_format": 1, "direct": False,"self_loop": False,"multigraph":False,"number_of_files":2,"engine":1}) >>> result == {'output_format': 1, 'min_weight': 455, 'min_edge': 4, 'max_edge': 4, 'file_name': 'test', 'vertices': 5, 'max_weight': 1000, 'sign': False, "direct": False,"self_loop": False,"multigraph":False,"number_of_files":2,"engine":1} True >>> result = input_filter({"file_name": "test","vertices": -5,"max_weight": 1000,"min_weight":455,"min_edge": -45,"max_edge": -11,"sign": False,"output_format": 1, "direct": False,"self_loop": False,"multigraph":True,"number_of_files":1,"engine":1}) >>> result == {'output_format': 1, 'min_weight': 455, 'min_edge': 11, 'max_edge': 45, 'file_name': 'test', 'vertices': 5, 'max_weight': 1000, 'sign': False, "direct": False,"self_loop": False,"multigraph":True,"number_of_files":1,"engine":1} True >>> result = input_filter({"file_name": "test2","vertices": 23,"max_weight": 2,"min_weight": 80,"min_edge": 23,"max_edge": 1,"sign": True,"output_format": 1, "direct": False,"self_loop": True,"multigraph":False,"number_of_files":100,"engine":1}) >>> result == {'min_weight': 2, 'vertices': 23, 'file_name': 'test2', 'max_edge': 23, 'min_edge': 1, 'max_weight': 80, 'output_format': 1, 'sign': True, "direct": False,"self_loop": True,"multigraph":False,"number_of_files":100,"engine":1} True >>> with open('logfile.log','a') as file: ... engine.logger(file,'test','2min',{'vertices':100,'edge_number':50,'max_edge':1000,'min_edge':10,'direct':1,'sign':0,'multigraph':0,'self_loop':1,'max_weight':20,'min_weight':1,'engine':1,'output_format':1}) >>> file = open('logfile.log','r') >>> print("\n".join(file.read().splitlines()[1:-1])) Filename : test Vertices : 100 Total Edges : 50 Max Edge : 1000 Min Edge : 10 Directed : True Signed : False Multigraph : False Self Loop : True Weighted : True Max Weight : 20 Min Weight : 1 Engine : 1 (pyrgg) Elapsed Time : 2min >>> convert_bytes(200) '200.0 bytes' >>> convert_bytes(6000) '5.9 KB' >>> convert_bytes(80000) '78.1 KB' >>> time_convert(33) '00 days, 00 hours, 00 minutes, 33 seconds' >>> time_convert(15000) '00 days, 04 hours, 10 minutes, 00 seconds' >>> time_convert('sadasdasd') Traceback (most recent call last): ... ValueError: could not convert string to float: 'sadasdasd' >>> line(12,"*") ************ >>> used_vertices = {k:[] for k in range(1,41)} >>> degree_dict = {k:0 for k in range(1,41)} >>> degree_dict_sort = {k:{} for k in range(41)} >>> degree_dict_sort[0] = {i:i for i in range(1,41)} >>> all_vertices = list(range(1, 41)) >>> random.seed(2) >>> engine.branch_gen(1,10,10,1,20,0,True,True,True,False,used_vertices,degree_dict,degree_dict_sort) [[4, 25, 18, 3, 30, 34, 2, 26, 14, 11], [3, 10, 20, 14, -18, -2, -15, -14, 8, 6]] >>> random.seed(20) >>> engine.branch_gen(1,10,4,1,20,0,False,True,True,False,used_vertices,degree_dict,degree_dict_sort) [[], []] >>> used_vertices = {k:[] for k in range(1,41)} >>> degree_dict = {k:0 for k in range(1,41)} >>> degree_dict_sort = {k:{} for k in range(41)} >>> degree_dict_sort[0] = {i:i for i in range(1,41)} >>> engine.branch_gen(1,10,4,1,20,0,False,True,True,False,used_vertices,degree_dict,degree_dict_sort) [[10, 7, 39, 2, 30, 9, 25, 35, 18], [9, 11, 6, 14, 3, 5, 16, 14, 7]] >>> engine.branch_gen(40,1,20,1) Traceback (most recent call last): ... TypeError: branch_gen() missing 9 required positional arguments: 'max_weight', 'precision', 'sign', 'direct', 'self_loop', 'multigraph', 'used_vertices', 'degree_dict', and 'degree_sort_dict' >>> random.seed(2) >>> engine.edge_gen(20,0,400,2,10,True,True,True,False) [{1: [3, 7], 2: [4, 17, 20, 9, 11], 3: [14, 8, 5, 12, 16, 19, 15], 4: [15, 17, 12, 8, 14, 13], 5: [16, 9, 7, 20, 19, 18, 13, 5], 6: [6, 10], 7: [18, 10, 11], 8: [], 9: [], 10: [12, 18, 8, 1, 14], 11: [9, 11], 12: [], 13: [], 14: [19, 16, 17, 20, 15], 15: [6, 1, 19], 16: [12, 13, 8, 9, 17], 17: [], 18: [9, 12, 17, 6, 20, 19, 1], 19: [13], 20: []}, {1: [184, -128], 2: [220, -278, -257, 14, -163], 3: [286, 118, 166, 261, -263, 228, -303], 4: [-82, -335, 250, -256, -338, -179], 5: [-337, -358, -395, -155, -159, 250, -350, -371], 6: [30, -302], 7: [386, -125, 216], 8: [], 9: [], 10: [127, 42, 12, 191, 80], 11: [-301, 77], 12: [], 13: [], 14: [146, -15, -282, 135, 242], 15: [-52, -65, -249], 16: [-132, -334, 343, -17, 87], 17: [], 18: [126, -37, 302, -131, -142, 77, -209], 19: [123], 20: []}, 61] >>> random.seed(11) >>> engine.edge_gen(20,0,100,2,10,False,True,True,False) [{1: [18, 15, 19, 7, 20, 11, 2, 6, 3], 2: [17], 3: [8, 4, 5, 9, 12, 10, 14, 16], 4: [20, 13, 4, 6], 5: [12, 7, 11, 10, 14], 6: [9], 7: [19], 8: [8, 18, 11, 2, 16, 17, 10], 9: [15, 12, 18], 10: [20, 14, 13, 15, 17, 16], 11: [19, 7, 20], 12: [13], 13: [2, 16, 13], 14: [18, 19, 6, 14, 17, 15], 15: [6, 7, 16], 16: [17, 20, 12, 18], 17: [19], 18: [7, 6, 9, 12, 20], 19: [19, 11, 4], 20: []}, {1: [99, 57, 75, 23, 80, 23, 57, 18, 68], 2: [50], 3: [79, 67, 7, 24, 76, 99, 41, 75], 4: [29, 63, 84, 58], 5: [70, 90, 40, 65, 3], 6: [51], 7: [37], 8: [2, 0, 26, 60, 90, 53, 72], 9: [43, 39, 1], 10: [15, 31, 1, 59, 22, 57], 11: [98, 53, 49], 12: [53], 13: [34, 2, 23], 14: [82, 12, 18, 56, 1, 37], 15: [9, 26, 1], 16: [47, 58, 75, 73], 17: [23], 18: [39, 78, 92, 20, 49], 19: [10, 6, 13], 20: []}, 74] >>> engine.edge_gen(0,400,2,10,1) Traceback (most recent call last): ... TypeError: edge_gen() missing 4 required positional arguments: 'sign', 'direct', 'self_loop', and 'multigraph' >>> random.seed(2) >>> engine.gen_using(dimacs_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.gr','r') >>> print(file.read()) c FILE :testfile.gr c No. of vertices :10 c No. of edges :7 c Max. weight :148 c Min. weight :7 p sp 10 7 a 4 3 -64 a 5 6 148 a 5 9 110 a 6 10 -139 a 7 7 7 a 8 2 -97 a 9 1 60 >>> random.seed(4) >>> engine.gen_using(dimacs_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 35 >>> file=open('testfile2.gr','r') >>> print(file.read()) c FILE :testfile2.gr c No. of vertices :30 c No. of edges :35 c Max. weight :50 c Min. weight :2 p sp 30 35 a 1 10 46 a 2 18 5 a 2 4 25 a 2 22 -48 a 4 23 -17 a 5 7 -13 a 7 15 10 a 7 17 -40 a 8 8 -42 a 8 25 11 a 9 29 -5 a 10 3 -36 a 10 27 -48 a 11 13 -27 a 11 26 -27 a 11 21 14 a 11 16 -2 a 14 20 -44 a 14 14 43 a 14 12 26 a 15 28 -11 a 16 30 -40 a 16 24 20 a 19 19 7 a 20 12 -29 a 20 1 22 a 22 24 20 a 22 23 -9 a 23 18 18 a 23 27 28 a 24 6 -24 a 25 17 23 a 27 6 -50 a 28 21 28 a 28 13 -13 >>> random.seed(20) >>> engine.gen_using(dimacs_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':0, 'direct':1, 'self_loop':1, 'multigraph':0}) 137 >>> file=open('testfile3.gr','r') >>> print(file.read()) c FILE :testfile3.gr c No. of vertices :100 c No. of edges :137 c Max. weight :30 c Min. weight :10 p sp 100 137 a 1 34 30 a 3 76 15 a 3 5 23 a 4 13 13 a 4 21 20 a 4 67 28 a 5 60 16 a 5 32 20 a 5 92 20 a 6 64 12 a 6 94 26 a 7 62 12 a 7 36 28 a 7 42 11 a 8 20 12 a 9 47 19 a 10 49 15 a 10 27 10 a 11 48 17 a 11 51 11 a 13 58 14 a 13 70 29 a 14 37 30 a 14 61 27 a 14 87 15 a 15 84 13 a 16 83 28 a 17 45 17 a 17 24 29 a 17 18 26 a 18 59 15 a 19 98 12 a 21 2 30 a 21 99 20 a 22 69 26 a 22 96 11 a 22 88 15 a 24 79 20 a 24 12 12 a 24 82 13 a 26 50 30 a 26 30 19 a 29 52 26 a 31 25 26 a 32 68 14 a 33 65 13 a 33 78 13 a 33 55 17 a 34 63 13 a 35 44 27 a 35 57 14 a 37 74 10 a 37 41 16 a 37 100 30 a 38 72 13 a 38 56 16 a 39 91 19 a 39 43 13 a 41 28 22 a 41 81 19 a 42 90 13 a 42 46 28 a 42 97 16 a 45 86 10 a 45 53 18 a 46 85 13 a 46 23 11 a 47 71 29 a 48 95 12 a 48 77 19 a 48 93 11 a 49 75 22 a 50 73 18 a 50 40 24 a 50 54 28 a 51 80 17 a 51 66 19 a 51 89 20 a 52 58 29 a 52 16 21 a 52 43 12 a 53 8 13 a 53 98 17 a 54 55 10 a 56 62 26 a 56 27 10 a 57 70 26 a 58 44 22 a 59 90 27 a 59 91 19 a 59 78 29 a 60 87 12 a 60 92 25 a 61 69 14 a 61 79 17 a 62 25 21 a 63 97 27 a 63 29 30 a 65 9 26 a 65 64 21 a 66 67 27 a 66 95 19 a 66 93 30 a 68 30 18 a 70 83 12 a 70 99 15 a 71 31 17 a 71 89 20 a 73 36 18 a 75 72 12 a 76 2 26 a 76 12 25 a 76 86 22 a 78 23 19 a 78 100 27 a 79 40 24 a 80 84 26 a 80 80 14 a 81 20 16 a 82 15 16 a 82 88 22 a 83 19 19 a 84 85 13 a 84 28 16 a 85 77 16 a 85 94 23 a 86 1 21 a 87 74 15 a 87 96 19 a 90 93 22 a 92 49 14 a 95 98 26 a 95 55 11 a 97 38 28 a 99 19 29 a 99 89 24 a 100 40 11 >>> dimacs_maker({}) Traceback (most recent call last): ... TypeError: dimacs_maker() missing 2 required positional arguments: 'weight_dic' and 'mdata' >>> random.seed(2) >>> engine.gen_using(json_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.json','r') >>> testfile_1=json.load(file) >>> testfile_1['graph']['nodes'][1] {'id': 2} >>> testfile_1['graph']['edges'][1]['source'] 5 >>> testfile_1['graph']['edges'][1]['target'] 6 >>> testfile_1['graph']['edges'][1]['weight'] 148 >>> json_to_yaml('testfile') >>> file=open('testfile.yaml','r') >>> testfile_1_yaml=yaml.safe_load(file) >>> testfile_1_yaml['graph']['edges'][1]['source'] 5 >>> testfile_1_yaml['graph']['edges'][1]['target'] 6 >>> testfile_1_yaml['graph']['edges'][1]['weight'] 148 >>> json_to_pickle('testfile') >>> testfile_1_p=pickle.load( open( 'testfile.p', 'rb' ) ) >>> testfile_1_p['graph']['edges'][1]['source'] 5 >>> testfile_1_p['graph']['edges'][1]['target'] 6 >>> testfile_1_p['graph']['edges'][1]['weight'] 148 >>> random.seed(4) >>> engine.gen_using(json_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 35 >>> file=open('testfile2.json','r') >>> testfile_2=json.load(file) >>> testfile_2['graph']['nodes'][1] {'id': 2} >>> testfile_2['graph']['edges'][1]['source'] 2 >>> testfile_2['graph']['edges'][1]['target'] 18 >>> testfile_2['graph']['edges'][1]['weight'] 5 >>> json_to_yaml('testfile2') >>> file=open('testfile2.yaml','r') >>> testfile_2_yaml=yaml.safe_load(file) >>> testfile_2_yaml['graph']['nodes'][1] {'id': 2} >>> testfile_2_yaml['graph']['edges'][1]['source'] 2 >>> testfile_2_yaml['graph']['edges'][1]['target'] 18 >>> testfile_2_yaml['graph']['edges'][1]['weight'] 5 >>> json_to_pickle('testfile2') >>> testfile_2_p=pickle.load( open( 'testfile2.p', 'rb' ) ) >>> testfile_2_p['graph']['edges'][1]['source'] 2 >>> testfile_2_p['graph']['edges'][1]['target'] 18 >>> testfile_2_p['graph']['edges'][1]['weight'] 5 >>> random.seed(20) >>> engine.gen_using(json_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':0, 'direct':1, 'self_loop':1, 'multigraph':0}) 137 >>> file=open('testfile3.json','r') >>> testfile_3=json.load(file) >>> testfile_3['graph']['nodes'][1] {'id': 2} >>> testfile_3['graph']['edges'][1]['source'] 3 >>> testfile_3['graph']['edges'][1]['target'] 76 >>> testfile_3['graph']['edges'][1]['weight'] 15 >>> json_to_yaml('testfile3') >>> file=open('testfile3.yaml','r') >>> testfile_3_yaml=yaml.safe_load(file) >>> testfile_3_yaml['graph']['nodes'][1] {'id': 2} >>> testfile_3_yaml['graph']['edges'][1]['source'] 3 >>> testfile_3_yaml['graph']['edges'][1]['target'] 76 >>> testfile_3_yaml['graph']['edges'][1]['weight'] 15 >>> json_to_yaml('testfile24') [Error] Failed to generate YAML file! >>> json_to_pickle('testfile24') [Error] Failed to generate Pickle file! >>> json_maker({}, {}) Traceback (most recent call last): ... TypeError: json_maker() missing 1 required positional argument: 'mdata' >>> json_to_pickle('testfile3') >>> testfile_3_p=pickle.load( open( 'testfile3.p', 'rb' ) ) >>> testfile_3_p['graph']['edges'][1]['source'] 3 >>> testfile_3_p['graph']['edges'][1]['target'] 76 >>> testfile_3_p['graph']['edges'][1]['weight'] 15 >>> random.seed(2) >>> engine.gen_using(csv_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> random.seed(2) >>> engine.gen_using(gml_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.gml','r') >>> print(file.read()) graph [ multigraph 0 directed 1 node [ id 1 label "Node 1" ] node [ id 2 label "Node 2" ] node [ id 3 label "Node 3" ] node [ id 4 label "Node 4" ] node [ id 5 label "Node 5" ] node [ id 6 label "Node 6" ] node [ id 7 label "Node 7" ] node [ id 8 label "Node 8" ] node [ id 9 label "Node 9" ] node [ id 10 label "Node 10" ] edge [ source 4 target 3 value -64 ] edge [ source 5 target 6 value 148 ] edge [ source 5 target 9 value 110 ] edge [ source 6 target 10 value -139 ] edge [ source 7 target 7 value 7 ] edge [ source 8 target 2 value -97 ] edge [ source 9 target 1 value 60 ] ] >>> random.seed(2) >>> engine.gen_using(gexf_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.gexf', 'r') >>> random.seed(2) >>> engine.gen_using(mtx_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> random.seed(2) >>> engine.gen_using(tsv_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.mtx','r') >>> print(file.read()) %%MatrixMarket matrix coordinate real general 10 10 7 4 3 -64 5 6 148 5 9 110 6 10 -139 7 7 7 8 2 -97 9 1 60 >>> random.seed(2) >>> engine.gen_using(gdf_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.gdf','r') >>> print(file.read()) nodedef>name VARCHAR,label VARCHAR 1,Node1 2,Node2 3,Node3 4,Node4 5,Node5 6,Node6 7,Node7 8,Node8 9,Node9 10,Node10 edgedef>node1 VARCHAR,node2 VARCHAR,weight DOUBLE 4,3,-64 5,6,148 5,9,110 6,10,-139 7,7,7 8,2,-97 9,1,60 >>> random.seed(2) >>> engine.gen_using(gl_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.gl','r') >>> print(file.read()) 4 3:-64 5 6:148 9:110 6 10:-139 7 7:7 8 2:-97 9 1:60 >>> file=open('testfile.csv','r') >>> print(file.read()) 4,3,-64 5,6,148 5,9,110 6,10,-139 7,7,7 8,2,-97 9,1,60 >>> random.seed(4) >>> engine.gen_using(csv_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 35 >>> file=open('testfile2.csv','r') >>> print(file.read()) 1,10,46 2,18,5 2,4,25 2,22,-48 4,23,-17 5,7,-13 7,15,10 7,17,-40 8,8,-42 8,25,11 9,29,-5 10,3,-36 10,27,-48 11,13,-27 11,26,-27 11,21,14 11,16,-2 14,20,-44 14,14,43 14,12,26 15,28,-11 16,30,-40 16,24,20 19,19,7 20,12,-29 20,1,22 22,24,20 22,23,-9 23,18,18 23,27,28 24,6,-24 25,17,23 27,6,-50 28,21,28 28,13,-13 >>> random.seed(4) >>> engine.gen_using(csv_maker, 'testfile4', {'min_weight':0, 'max_weight':50.2, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 41 >>> file=open('testfile4.csv','r') >>> print(file.read()) 1,10,36.2 2,6,3.3 2,16,-40.2 2,29,11.1 3,17,-39.1 3,7,-10.8 3,3,-40.2 4,12,-14.5 5,9,-33.7 5,28,8.9 6,21,47.4 6,27,-0.4 6,15,-42.6 7,20,-30.1 8,23,11.7 8,18,4.1 8,25,-26.0 9,24,50.1 9,13,20.7 9,14,-13.9 10,26,-31.8 10,19,-5.1 12,22,6.1 13,30,-1.3 14,11,-36.9 14,22,16.2 15,16,-43.2 15,11,-31.0 16,19,12.6 17,21,18.2 18,18,-39.3 18,25,-28.7 19,23,-46.0 24,20,27.4 25,4,-50.1 25,1,-38.8 26,27,-10.1 26,30,-24.7 26,29,-12.5 27,28,-9.4 29,20,26.4 >>> random.seed(20) >>> engine.gen_using(csv_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':0, 'direct':1, 'self_loop':1, 'multigraph':0}) 137 >>> file=open('testfile3.csv','r') >>> print(file.read()) 1,34,30 3,76,15 3,5,23 4,13,13 4,21,20 4,67,28 5,60,16 5,32,20 5,92,20 6,64,12 6,94,26 7,62,12 7,36,28 7,42,11 8,20,12 9,47,19 10,49,15 10,27,10 11,48,17 11,51,11 13,58,14 13,70,29 14,37,30 14,61,27 14,87,15 15,84,13 16,83,28 17,45,17 17,24,29 17,18,26 18,59,15 19,98,12 21,2,30 21,99,20 22,69,26 22,96,11 22,88,15 24,79,20 24,12,12 24,82,13 26,50,30 26,30,19 29,52,26 31,25,26 32,68,14 33,65,13 33,78,13 33,55,17 34,63,13 35,44,27 35,57,14 37,74,10 37,41,16 37,100,30 38,72,13 38,56,16 39,91,19 39,43,13 41,28,22 41,81,19 42,90,13 42,46,28 42,97,16 45,86,10 45,53,18 46,85,13 46,23,11 47,71,29 48,95,12 48,77,19 48,93,11 49,75,22 50,73,18 50,40,24 50,54,28 51,80,17 51,66,19 51,89,20 52,58,29 52,16,21 52,43,12 53,8,13 53,98,17 54,55,10 56,62,26 56,27,10 57,70,26 58,44,22 59,90,27 59,91,19 59,78,29 60,87,12 60,92,25 61,69,14 61,79,17 62,25,21 63,97,27 63,29,30 65,9,26 65,64,21 66,67,27 66,95,19 66,93,30 68,30,18 70,83,12 70,99,15 71,31,17 71,89,20 73,36,18 75,72,12 76,2,26 76,12,25 76,86,22 78,23,19 78,100,27 79,40,24 80,84,26 80,80,14 81,20,16 82,15,16 82,88,22 83,19,19 84,85,13 84,28,16 85,77,16 85,94,23 86,1,21 87,74,15 87,96,19 90,93,22 92,49,14 95,98,26 95,55,11 97,38,28 99,19,29 99,89,24 100,40,11 >>> csv_maker({}) Traceback (most recent call last): ... TypeError: csv_maker() missing 2 required positional arguments: 'weight_dic' and 'mdata' >>> random.seed(2) >>> engine.gen_using(wel_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.wel','r') >>> print(file.read()) 4 3 -64 5 6 148 5 9 110 6 10 -139 7 7 7 8 2 -97 9 1 60 >>> random.seed(4) >>> engine.gen_using(wel_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 35 >>> file=open('testfile2.wel','r') >>> print(file.read()) 1 10 46 2 18 5 2 4 25 2 22 -48 4 23 -17 5 7 -13 7 15 10 7 17 -40 8 8 -42 8 25 11 9 29 -5 10 3 -36 10 27 -48 11 13 -27 11 26 -27 11 21 14 11 16 -2 14 20 -44 14 14 43 14 12 26 15 28 -11 16 30 -40 16 24 20 19 19 7 20 12 -29 20 1 22 22 24 20 22 23 -9 23 18 18 23 27 28 24 6 -24 25 17 23 27 6 -50 28 21 28 28 13 -13 >>> random.seed(20) >>> engine.gen_using(wel_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':0, 'direct':1, 'self_loop':1, 'multigraph':0}) 137 >>> file=open('testfile3.wel','r') >>> print(file.read()) 1 34 30 3 76 15 3 5 23 4 13 13 4 21 20 4 67 28 5 60 16 5 32 20 5 92 20 6 64 12 6 94 26 7 62 12 7 36 28 7 42 11 8 20 12 9 47 19 10 49 15 10 27 10 11 48 17 11 51 11 13 58 14 13 70 29 14 37 30 14 61 27 14 87 15 15 84 13 16 83 28 17 45 17 17 24 29 17 18 26 18 59 15 19 98 12 21 2 30 21 99 20 22 69 26 22 96 11 22 88 15 24 79 20 24 12 12 24 82 13 26 50 30 26 30 19 29 52 26 31 25 26 32 68 14 33 65 13 33 78 13 33 55 17 34 63 13 35 44 27 35 57 14 37 74 10 37 41 16 37 100 30 38 72 13 38 56 16 39 91 19 39 43 13 41 28 22 41 81 19 42 90 13 42 46 28 42 97 16 45 86 10 45 53 18 46 85 13 46 23 11 47 71 29 48 95 12 48 77 19 48 93 11 49 75 22 50 73 18 50 40 24 50 54 28 51 80 17 51 66 19 51 89 20 52 58 29 52 16 21 52 43 12 53 8 13 53 98 17 54 55 10 56 62 26 56 27 10 57 70 26 58 44 22 59 90 27 59 91 19 59 78 29 60 87 12 60 92 25 61 69 14 61 79 17 62 25 21 63 97 27 63 29 30 65 9 26 65 64 21 66 67 27 66 95 19 66 93 30 68 30 18 70 83 12 70 99 15 71 31 17 71 89 20 73 36 18 75 72 12 76 2 26 76 12 25 76 86 22 78 23 19 78 100 27 79 40 24 80 84 26 80 80 14 81 20 16 82 15 16 82 88 22 83 19 19 84 85 13 84 28 16 85 77 16 85 94 23 86 1 21 87 74 15 87 96 19 90 93 22 92 49 14 95 98 26 95 55 11 97 38 28 99 19 29 99 89 24 100 40 11 >>> wel_maker({}, {}) Traceback (most recent call last): ... TypeError: wel_maker() missing 1 required positional argument: 'mdata' >>> random.seed(2) >>> engine.gen_using(lp_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.lp','r') >>> print(file.read()) node(1). node(2). node(3). node(4). node(5). node(6). node(7). node(8). node(9). node(10). edge(4,3,-64). edge(5,6,148). edge(5,9,110). edge(6,10,-139). edge(7,7,7). edge(8,2,-97). edge(9,1,60). >>> random.seed(4) >>> engine.gen_using(lp_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 35 >>> file=open('testfile2.lp','r') >>> print(file.read()) node(1). node(2). node(3). node(4). node(5). node(6). node(7). node(8). node(9). node(10). node(11). node(12). node(13). node(14). node(15). node(16). node(17). node(18). node(19). node(20). node(21). node(22). node(23). node(24). node(25). node(26). node(27). node(28). node(29). node(30). edge(1,10,46). edge(2,18,5). edge(2,4,25). edge(2,22,-48). edge(4,23,-17). edge(5,7,-13). edge(7,15,10). edge(7,17,-40). edge(8,8,-42). edge(8,25,11). edge(9,29,-5). edge(10,3,-36). edge(10,27,-48). edge(11,13,-27). edge(11,26,-27). edge(11,21,14). edge(11,16,-2). edge(14,20,-44). edge(14,14,43). edge(14,12,26). edge(15,28,-11). edge(16,30,-40). edge(16,24,20). edge(19,19,7). edge(20,12,-29). edge(20,1,22). edge(22,24,20). edge(22,23,-9). edge(23,18,18). edge(23,27,28). edge(24,6,-24). edge(25,17,23). edge(27,6,-50). edge(28,21,28). edge(28,13,-13). >>> random.seed(2) >>> engine.gen_using(tgf_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.tgf','r') >>> print(file.read()) 1 2 3 4 5 6 7 8 9 10 # 4 3 -64 5 6 148 5 9 110 6 10 -139 7 7 7 8 2 -97 9 1 60 >>> random.seed(4) >>> engine.gen_using(tgf_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 35 >>> file=open('testfile2.tgf','r') >>> print(file.read()) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 # 1 10 46 2 18 5 2 4 25 2 22 -48 4 23 -17 5 7 -13 7 15 10 7 17 -40 8 8 -42 8 25 11 9 29 -5 10 3 -36 10 27 -48 11 13 -27 11 26 -27 11 21 14 11 16 -2 14 20 -44 14 14 43 14 12 26 15 28 -11 16 30 -40 16 24 20 19 19 7 20 12 -29 20 1 22 22 24 20 22 23 -9 23 18 18 23 27 28 24 6 -24 25 17 23 27 6 -50 28 21 28 28 13 -13 >>> random.seed(2) >>> engine.gen_using(dl_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.dl','r') >>> print(file.read()) dl format=edgelist1 n=10 data: 4 3 -64 5 6 148 5 9 110 6 10 -139 7 7 7 8 2 -97 9 1 60 >>> random.seed(4) >>> engine.gen_using(dl_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 35 >>> file=open('testfile2.dl','r') >>> print(file.read()) dl format=edgelist1 n=30 data: 1 10 46 2 18 5 2 4 25 2 22 -48 4 23 -17 5 7 -13 7 15 10 7 17 -40 8 8 -42 8 25 11 9 29 -5 10 3 -36 10 27 -48 11 13 -27 11 26 -27 11 21 14 11 16 -2 14 20 -44 14 14 43 14 12 26 15 28 -11 16 30 -40 16 24 20 19 19 7 20 12 -29 20 1 22 22 24 20 22 23 -9 23 18 18 23 27 28 24 6 -24 25 17 23 27 6 -50 28 21 28 28 13 -13 >>> file.close() >>> os.remove('testfile.csv') >>> os.remove('testfile.gml') >>> os.remove('testfile.gexf') >>> os.remove('testfile.tsv') >>> os.remove('testfile.dl') >>> os.remove('testfile.gr') >>> os.remove('testfile.json') >>> os.remove('testfile.lp') >>> os.remove('testfile.p') >>> os.remove('testfile.tgf') >>> os.remove('testfile.wel') >>> os.remove('testfile.yaml') >>> os.remove('testfile.mtx') >>> os.remove('testfile.gdf') >>> os.remove('testfile.gl') >>> os.remove('testfile2.csv') >>> os.remove('testfile2.dl') >>> os.remove('testfile2.gr') >>> os.remove('testfile2.json') >>> os.remove('testfile2.lp') >>> os.remove('testfile2.p') >>> os.remove('testfile2.tgf') >>> os.remove('testfile2.wel') >>> os.remove('testfile2.yaml') >>> os.remove('testfile3.csv') >>> os.remove('testfile4.csv') >>> os.remove('testfile3.gr') >>> os.remove('testfile3.json') >>> os.remove('testfile3.p') >>> os.remove('testfile3.wel') >>> os.remove('testfile3.yaml') >>> os.remove('logfile.log') """ pyrgg-1.6/pytest.ini000066400000000000000000000001571471451651000145500ustar00rootroot00000000000000# content of pytest.ini [pytest] addopts = --doctest-modules doctest_optionflags= NORMALIZE_WHITESPACE ELLIPSISpyrgg-1.6/requirements.txt000066400000000000000000000000251471451651000157750ustar00rootroot00000000000000pyyaml>=3.12 art>=0.7pyrgg-1.6/setup.py000066400000000000000000000065761471451651000142440ustar00rootroot00000000000000# -*- coding: utf-8 -*- """Setup module.""" try: from setuptools import setup except ImportError: from distutils.core import setup from textwrap import fill _description = """\ PyRGG is a user-friendly synthetic random graph generator that is written in Python and supports multiple graph file formats, such as DIMACS-Graph files. It can generate graphs of various sizes and is specifically designed to create input files for a wide range of graph-based research applications, including testing, benchmarking, and performance analysis of graph processing frameworks. PyRGG is aimed at computer scientists who are studying graph algorithms and graph processing frameworks. """ PYRGG_DESCRIPTION = fill(_description, width=113) def get_requires(): """Read requirements.txt.""" requirements = open("requirements.txt", "r").read() return list(filter(lambda x: x != "", requirements.split())) def read_description(): """Read README.md and CHANGELOG.md.""" try: with open("README.md") as r: description = "\n" description += r.read() with open("CHANGELOG.md") as c: description += "\n" description += c.read() return description except Exception: return PYRGG_DESCRIPTION.replace("\n", " ") setup( name='pyrgg', packages=['pyrgg', 'pyrgg.engines'], version='1.6', description='Python Random Graph Generator', long_description=read_description(), long_description_content_type='text/markdown', author='PyRGG Development Team', author_email='info@pyrgg.site', url='https://github.com/sepandhaghighi/pyrgg', download_url='https://github.com/sepandhaghighi/pyrgg/tarball/v1.6', keywords='random graph python3 python generator graph-process generator DIMACS JSON YAML Pickle CSV TSV WEL ASP TGF UCINET', project_urls={ 'Webpage': 'https://www.pyrgg.site', 'Source': 'https://github.com/sepandhaghighi/pyrgg', }, install_requires=get_requires(), python_requires='>=3.6', classifiers=[ 'Development Status :: 5 - Production/Stable', 'Intended Audience :: Developers', 'Natural Language :: English', 'License :: OSI Approved :: MIT License', 'Operating System :: OS Independent', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: 3.8', 'Programming Language :: Python :: 3.9', 'Programming Language :: Python :: 3.10', 'Programming Language :: Python :: 3.11', 'Programming Language :: Python :: 3.12', 'Programming Language :: Python :: 3.13', 'Intended Audience :: Developers', 'Intended Audience :: Education', 'Intended Audience :: End Users/Desktop', 'Intended Audience :: Manufacturing', 'Intended Audience :: Science/Research', 'Topic :: Scientific/Engineering :: Information Analysis', 'Topic :: Education', 'Topic :: Scientific/Engineering', 'Topic :: Scientific/Engineering :: Artificial Intelligence', 'Topic :: Scientific/Engineering :: Human Machine Interfaces', 'Topic :: Scientific/Engineering :: Mathematics', 'Topic :: Scientific/Engineering :: Physics', ], license='MIT', entry_points={ 'console_scripts': [ 'pyrgg = pyrgg.__main__:main', ]}) pyrgg-1.6/test/000077500000000000000000000000001471451651000134735ustar00rootroot00000000000000pyrgg-1.6/test/engines/000077500000000000000000000000001471451651000151235ustar00rootroot00000000000000pyrgg-1.6/test/engines/erdos_reyni_gilbert_test.py000066400000000000000000000270701471451651000225740ustar00rootroot00000000000000# -*- coding: utf-8 -*- """ >>> from pyrgg.functions import * >>> from pyrgg.graph_gen import * >>> import pyrgg.params >>> import random >>> import os >>> import json >>> import pyrgg.engines.erdos_reyni_gilbert as engine >>> os.environ["PYRGG_TEST_MODE"] = "1" >>> ###################################### >>> ## ========= logger function ========= >>> ###################################### >>> with open('logfile.log','a') as file: ... engine.logger(file,'test','2min',{'vertices':100,'edge_number':50,'direct':0,'engine':2,'probability':0.5,'output_format':1}) >>> file = open('logfile.log','r') >>> print("\\n".join(file.read().splitlines()[1:-1])) Filename : test Vertices : 100 Probability : 0.5 Total Edges : 50 Directed : False Engine : 2 (erg) Elapsed Time : 2min >>> class StrError: ... def __init__(self): ... pass ... def __str__(self): ... raise ValueError >>> str_error_object = StrError() >>> with open('logfile.log','a') as file: ... engine.logger(file,'test','2min',{'vertices':str_error_object,'edge_number':50,'direct':0,'engine':2,'probability':0.5,'output_format':1}) [Error] Logger failed! >>> ########################################## >>> ## ========= edge_gen function ========= >>> ########################################## >>> random.seed(2) >>> edge_dic, weight_dic, edge_number = engine.edge_gen(20, 0.5, False) >>> edge_dic == {1: [4, 5, 9, 13, 14, 15, 20], 2: [3, 4, 5, 6, 7, 8, 12, 13, 14, 15, 19], 3: [9, 12, 15, 17], 4: [5, 8, 12, 13, 14, 16, 18, 20], 5: [12, 13, 17], 6: [7, 9, 11, 12, 14, 17, 18, 20],7: [9, 10, 11, 13, 15, 17, 18, 20], 8: [9, 11, 12, 14, 15, 16, 19, 20], 9: [10, 11, 18, 19], 10: [11, 12, 13, 15, 17, 19], 11: [12, 14, 15, 17, 18, 19, 20], 12: [13, 19, 20], 13: [14, 19, 20], 14: [16, 17, 18, 19], 15: [16, 17, 18, 19, 20], 16: [18, 19], 17: [18], 18: [20], 19: [], 20: []} True >>> edge_number == 93 True >>> random.seed(11) >>> edge_dic, weight_dic, edge_number = engine.edge_gen(20, 0.1, True) >>> edge_dic == {1: [12, 14, 17], 2: [4, 6, 9], 3: [7, 14, 20], 4: [5, 12], 5: [], 6: [1, 2], 7: [8, 18], 8: [6, 10], 9: [2, 3, 7, 14], 10: [15], 11: [5, 7, 17], 12: [], 13: [16, 17, 19], 14: [4, 7, 11], 15: [3, 17], 16: [], 17: [7, 12, 14], 18: [9], 19: [12], 20: [1, 19]} True >>> edge_number == 40 True >>> engine.edge_gen(0) Traceback (most recent call last): ... TypeError: edge_gen() missing 2 required positional arguments: 'p' and 'direct' >>> ######################################### >>> ## ========= gen_using function ========= >>> ######################################### >>> #################### dimacs_maker #################### >>> random.seed(2) >>> engine.gen_using(dimacs_maker, 'testfile', {'vertices':10, 'probability':0.1, 'direct':0}) 5 >>> file=open('testfile.gr','r') >>> print(file.read()) c FILE :testfile.gr c No. of vertices :10 c No. of edges :5 c Max. weight :1 c Min. weight :1 p sp 10 5 a 1 4 1 a 1 5 1 a 3 7 1 a 3 8 1 a 4 10 1 >>> random.seed(4) >>> engine.gen_using(dimacs_maker, 'testfile2', {'vertices':10, 'probability':0.1, 'direct':1}) 8 >>> file=open('testfile2.gr','r') >>> print(file.read()) c FILE :testfile2.gr c No. of vertices :10 c No. of edges :8 c Max. weight :1 c Min. weight :1 p sp 10 8 a 1 6 1 a 3 9 1 a 4 6 1 a 6 3 1 a 6 4 1 a 8 4 1 a 9 3 1 a 9 10 1 >>> #################### json_maker #################### >>> random.seed(2) >>> engine.gen_using(json_maker, 'testfile', {'vertices':10, 'probability':0.1, 'direct':0}) 5 >>> file=open('testfile.json','r') >>> testfile_1=json.load(file) >>> testfile_1['graph']['nodes'][1] {'id': 2} >>> testfile_1['graph']['edges'][1]['source'] 1 >>> testfile_1['graph']['edges'][1]['target'] 5 >>> random.seed(4) >>> engine.gen_using(json_maker, 'testfile2', {'vertices':10, 'probability':0.1, 'direct':1}) 8 >>> file=open('testfile2.json','r') >>> testfile_2=json.load(file) >>> testfile_2['graph']['nodes'][1] {'id': 2} >>> testfile_2['graph']['edges'][1]['source'] 3 >>> testfile_2['graph']['edges'][1]['target'] 9 >>> #################### csv_maker #################### >>> random.seed(2) >>> engine.gen_using(csv_maker, 'testfile', {'vertices':10, 'probability':0.1, 'direct':0}) 5 >>> file=open('testfile.csv','r') >>> print(file.read()) 1,4,1 1,5,1 3,7,1 3,8,1 4,10,1 >>> random.seed(4) >>> engine.gen_using(csv_maker, 'testfile2', {'vertices':10, 'probability':0.1, 'direct':1}) 8 >>> file=open('testfile2.csv','r') >>> print(file.read()) 1,6,1 3,9,1 4,6,1 6,3,1 6,4,1 8,4,1 9,3,1 9,10,1 >>> #################### gdf_maker #################### >>> random.seed(2) >>> engine.gen_using(gdf_maker, 'testfile', {'vertices':10, 'probability':0.1, 'direct':0}) 5 >>> file=open('testfile.gdf','r') >>> print(file.read()) nodedef>name VARCHAR,label VARCHAR 1,Node1 2,Node2 3,Node3 4,Node4 5,Node5 6,Node6 7,Node7 8,Node8 9,Node9 10,Node10 edgedef>node1 VARCHAR,node2 VARCHAR,weight DOUBLE 1,4,1 1,5,1 3,7,1 3,8,1 4,10,1 >>> random.seed(4) >>> engine.gen_using(gdf_maker, 'testfile2', {'vertices':10, 'probability':0.1, 'direct':1}) 8 >>> file=open('testfile2.gdf','r') >>> print(file.read()) nodedef>name VARCHAR,label VARCHAR 1,Node1 2,Node2 3,Node3 4,Node4 5,Node5 6,Node6 7,Node7 8,Node8 9,Node9 10,Node10 edgedef>node1 VARCHAR,node2 VARCHAR,weight DOUBLE 1,6,1 3,9,1 4,6,1 6,3,1 6,4,1 8,4,1 9,3,1 9,10,1 >>> #################### gl_maker #################### >>> random.seed(2) >>> engine.gen_using(gl_maker, 'testfile', {'vertices':10, 'probability':0.1, 'direct':0}) 5 >>> file=open('testfile.gl','r') >>> print(file.read()) 1 4:1 5:1 3 7:1 8:1 4 10:1 >>> random.seed(4) >>> engine.gen_using(gl_maker, 'testfile2', {'vertices':10, 'probability':0.1, 'direct':1}) 8 >>> file=open('testfile2.gl','r') >>> print(file.read()) 1 6:1 3 9:1 4 6:1 6 3:1 4:1 8 4:1 9 3:1 10:1 >>> #################### mtx_maker #################### >>> from scipy.io import mmread >>> random.seed(2) >>> engine.gen_using(mtx_maker, 'testfile', {'vertices':10, 'probability':0.1, 'direct':0}) 5 >>> g = mmread("testfile.mtx") >>> print(g.data.tolist()) [1.0, 1.0, 1.0, 1.0, 1.0] >>> random.seed(4) >>> engine.gen_using(mtx_maker, 'testfile2', {'vertices':10, 'probability':0.1, 'direct':1}) 8 >>> g = mmread("testfile2.mtx") >>> print(g.data.tolist()) [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0] >>> #################### tsv_maker #################### >>> random.seed(2) >>> engine.gen_using(tsv_maker, 'testfile', {'vertices':10, 'probability':0.1, 'direct':0}) 5 >>> file=open('testfile.tsv','r') >>> print(file.read()) 1 4 1 1 5 1 3 7 1 3 8 1 4 10 1 >>> random.seed(4) >>> engine.gen_using(tsv_maker, 'testfile2', {'vertices':10, 'probability':0.1, 'direct':1}) 8 >>> file=open('testfile2.tsv','r') >>> print(file.read()) 1 6 1 3 9 1 4 6 1 6 3 1 6 4 1 8 4 1 9 3 1 9 10 1 >>> #################### wel_maker #################### >>> random.seed(2) >>> engine.gen_using(wel_maker, 'testfile', {'vertices':10, 'probability':0.1, 'direct':0}) 5 >>> file=open('testfile.wel','r') >>> print(file.read()) 1 4 1 1 5 1 3 7 1 3 8 1 4 10 1 >>> random.seed(4) >>> engine.gen_using(wel_maker, 'testfile2', {'vertices':10, 'probability':0.1, 'direct':1}) 8 >>> file=open('testfile2.wel','r') >>> print(file.read()) 1 6 1 3 9 1 4 6 1 6 3 1 6 4 1 8 4 1 9 3 1 9 10 1 >>> #################### lp_maker #################### >>> random.seed(2) >>> engine.gen_using(lp_maker, 'testfile', {'vertices':10, 'probability':0.1, 'direct':0}) 5 >>> file=open('testfile.lp','r') >>> print(file.read()) node(1). node(2). node(3). node(4). node(5). node(6). node(7). node(8). node(9). node(10). edge(1,4,1). edge(1,5,1). edge(3,7,1). edge(3,8,1). edge(4,10,1). >>> random.seed(4) >>> engine.gen_using(lp_maker, 'testfile2', {'vertices':10, 'probability':0.1, 'direct':1}) 8 >>> file=open('testfile2.lp','r') >>> print(file.read()) node(1). node(2). node(3). node(4). node(5). node(6). node(7). node(8). node(9). node(10). edge(1,6,1). edge(3,9,1). edge(4,6,1). edge(6,3,1). edge(6,4,1). edge(8,4,1). edge(9,3,1). edge(9,10,1). >>> #################### tgf_maker #################### >>> random.seed(2) >>> engine.gen_using(tgf_maker, 'testfile', {'vertices':10, 'probability':0.1, 'direct':0}) 5 >>> file=open('testfile.tgf','r') >>> print(file.read()) 1 2 3 4 5 6 7 8 9 10 # 1 4 1 1 5 1 3 7 1 3 8 1 4 10 1 >>> random.seed(4) >>> engine.gen_using(tgf_maker, 'testfile2', {'vertices':10, 'probability':0.1, 'direct':1}) 8 >>> file=open('testfile2.tgf','r') >>> print(file.read()) 1 2 3 4 5 6 7 8 9 10 # 1 6 1 3 9 1 4 6 1 6 3 1 6 4 1 8 4 1 9 3 1 9 10 1 >>> #################### dl_maker #################### >>> random.seed(2) >>> engine.gen_using(dl_maker, 'testfile', {'vertices':10, 'probability':0.1, 'direct':0}) 5 >>> file=open('testfile.dl','r') >>> print(file.read()) dl format=edgelist1 n=10 data: 1 4 1 1 5 1 3 7 1 3 8 1 4 10 1 >>> random.seed(4) >>> engine.gen_using(dl_maker, 'testfile2', {'vertices':10, 'probability':0.1, 'direct':1}) 8 >>> file=open('testfile2.dl','r') >>> print(file.read()) dl format=edgelist1 n=10 data: 1 6 1 3 9 1 4 6 1 6 3 1 6 4 1 8 4 1 9 3 1 9 10 1 >>> #################### gml_maker #################### >>> from networkx.readwrite.gml import read_gml >>> random.seed(2) >>> engine.gen_using(gml_maker, 'testfile', {'vertices':10, 'probability':0.1, 'direct':0}) 5 >>> gml1 = read_gml("testfile.gml") >>> type(gml1) >>> random.seed(4) >>> engine.gen_using(gml_maker, 'testfile2', {'vertices':10, 'probability':0.1, 'direct':1}) 8 >>> gml2 = read_gml("testfile2.gml") >>> type(gml2) >>> #################### gexf_maker #################### >>> from networkx.readwrite.gexf import read_gexf >>> random.seed(2) >>> engine.gen_using(gexf_maker, 'testfile', {'vertices':10, 'probability':0.1, 'direct':0}) 5 >>> gexf1 = read_gexf("testfile.gexf") >>> type(gexf1) >>> random.seed(4) >>> engine.gen_using(gexf_maker, 'testfile2', {'vertices':10, 'probability':0.1, 'direct':1}) 8 >>> gexf2 = read_gexf("testfile2.gexf") >>> type(gexf2) >>> #################### dot_maker #################### >>> import pydot >>> random.seed(2) >>> engine.gen_using(dot_maker, 'testfile', {'vertices':10, 'probability':0.1, 'direct':0}) 5 >>> file=open('testfile.gv','r') >>> g1 = pydot.graph_from_dot_data(file.read()) >>> g1[0].get_type() 'graph' >>> len(g1[0].get_edge_list()) 5 >>> random.seed(4) >>> engine.gen_using(dot_maker, 'testfile2', {'vertices':10, 'probability':0.1, 'direct':1}) 8 >>> file=open('testfile2.gv','r') >>> g2 = pydot.graph_from_dot_data(file.read()) >>> g2[0].get_type() 'digraph' >>> len(g2[0].get_edge_list()) 8 >>> file.close() >>> os.remove('testfile.gr') >>> os.remove('testfile2.gr') >>> os.remove('testfile.json') >>> os.remove('testfile2.json') >>> os.remove('testfile.csv') >>> os.remove('testfile2.csv') >>> os.remove('testfile.gdf') >>> os.remove('testfile2.gdf') >>> os.remove('testfile.gl') >>> os.remove('testfile2.gl') >>> os.remove('testfile.mtx') >>> os.remove('testfile2.mtx') >>> os.remove('testfile.tsv') >>> os.remove('testfile2.tsv') >>> os.remove('testfile.wel') >>> os.remove('testfile2.wel') >>> os.remove('testfile.lp') >>> os.remove('testfile2.lp') >>> os.remove('testfile.tgf') >>> os.remove('testfile2.tgf') >>> os.remove('testfile.dl') >>> os.remove('testfile2.dl') >>> os.remove('testfile.gml') >>> os.remove('testfile2.gml') >>> os.remove('testfile.gexf') >>> os.remove('testfile2.gexf') >>> os.remove('testfile.gv') >>> os.remove('testfile2.gv') >>> os.remove('logfile.log') """ pyrgg-1.6/test/engines/erdos_reyni_test.py000066400000000000000000000266311471451651000210660ustar00rootroot00000000000000# -*- coding: utf-8 -*- """ >>> from pyrgg.functions import * >>> from pyrgg.graph_gen import * >>> import pyrgg.params >>> import random >>> import os >>> import json >>> import pyrgg.engines.erdos_reyni as engine >>> os.environ["PYRGG_TEST_MODE"] = "1" >>> ###################################### >>> ## ========= logger function ========= >>> ###################################### >>> with open('logfile.log','a') as file: ... engine.logger(file,'test','2min',{'vertices':100,'edge_number':50,'direct':0,'engine':3,'output_format':1}) >>> file = open('logfile.log','r') >>> print("\\n".join(file.read().splitlines()[1:-1])) Filename : test Vertices : 100 Total Edges : 50 Directed : False Engine : 3 (er) Elapsed Time : 2min >>> class StrError: ... def __init__(self): ... pass ... def __str__(self): ... raise ValueError >>> str_error_object = StrError() >>> with open('logfile.log','a') as file: ... engine.logger(file,'test','2min',{'vertices':str_error_object,'edge_number':50,'direct':0,'engine':3,'output_format':1}) [Error] Logger failed! >>> ########################################## >>> ## ========= edge_gen function ========= >>> ########################################## >>> random.seed(2) >>> edge_dic, weight_dic, edge_number = engine.edge_gen(20, 10, False) >>> edge_dic == {1: [13], 2: [9], 3: [4], 4: [], 5: [], 6: [], 7: [16], 8: [], 9: [10, 18], 10: [12, 17], 11: [13], 12: [], 13: [], 14: [], 15: [], 16: [], 17: [], 18: [20], 19: [], 20: []} True >>> edge_number == 10 True >>> random.seed(11) >>> edge_dic, weight_dic, edge_number = engine.edge_gen(20, 100, True) >>> edge_dic == {1: [8, 9, 14, 15, 18, 19], 2: [4, 11, 13, 15, 16, 17], 3: [1, 13, 14, 19], 4: [7, 9, 14, 15, 16, 19], 5: [4, 10, 15, 16, 18, 19], 6: [3, 4, 9, 12, 19], 7: [5, 10, 13, 15, 16, 17, 20], 8: [1, 18, 19, 20], 9: [3, 6, 11, 13, 16, 18, 20], 10: [1, 3, 4, 13, 17], 11: [6, 7, 8, 17, 18], 12: [3, 5, 8, 17], 13: [5, 15], 14: [7, 12, 17, 19], 15: [1, 4, 7, 9, 14, 19, 20], 16: [3, 7, 8, 9, 12, 20], 17: [3, 5, 8, 14, 16], 18: [2, 9, 10, 11, 14], 19: [4, 9, 12], 20: [1, 12, 13]} True >>> edge_number == 100 True >>> engine.edge_gen(0) Traceback (most recent call last): ... TypeError: edge_gen() missing 2 required positional arguments: 'm' and 'direct' >>> ######################################### >>> ## ========= gen_using function ========= >>> ######################################### >>> #################### dimacs_maker #################### >>> random.seed(2) >>> engine.gen_using(dimacs_maker, 'testfile', {'vertices':10, 'edge_number':5, 'direct':0}) 5 >>> file=open('testfile.gr','r') >>> print(file.read()) c FILE :testfile.gr c No. of vertices :10 c No. of edges :5 c Max. weight :1 c Min. weight :1 p sp 10 5 a 1 2 1 a 1 10 1 a 3 6 1 a 3 7 1 a 6 10 1 >>> random.seed(4) >>> engine.gen_using(dimacs_maker, 'testfile2', {'vertices':10, 'edge_number':8, 'direct':1}) 8 >>> file=open('testfile2.gr','r') >>> print(file.read()) c FILE :testfile2.gr c No. of vertices :10 c No. of edges :8 c Max. weight :1 c Min. weight :1 p sp 10 8 a 1 10 1 a 2 5 1 a 3 6 1 a 4 10 1 a 6 5 1 a 8 3 1 a 9 8 1 a 10 2 1 >>> #################### json_maker #################### >>> random.seed(2) >>> engine.gen_using(json_maker, 'testfile', {'vertices':10, 'edge_number':5, 'direct':0}) 5 >>> file=open('testfile.json','r') >>> testfile_1=json.load(file) >>> testfile_1['graph']['nodes'][1] {'id': 2} >>> testfile_1['graph']['edges'][1]['source'] 1 >>> testfile_1['graph']['edges'][1]['target'] 10 >>> random.seed(4) >>> engine.gen_using(json_maker, 'testfile2', {'vertices':10, 'edge_number':8, 'direct':1}) 8 >>> file=open('testfile2.json','r') >>> testfile_2=json.load(file) >>> testfile_2['graph']['nodes'][1] {'id': 2} >>> testfile_2['graph']['edges'][1]['source'] 2 >>> testfile_2['graph']['edges'][1]['target'] 5 >>> #################### csv_maker #################### >>> random.seed(2) >>> engine.gen_using(csv_maker, 'testfile', {'vertices':10, 'edge_number':5, 'direct':0}) 5 >>> file=open('testfile.csv','r') >>> print(file.read()) 1,2,1 1,10,1 3,6,1 3,7,1 6,10,1 >>> random.seed(4) >>> engine.gen_using(csv_maker, 'testfile2', {'vertices':10, 'edge_number':8, 'direct':1}) 8 >>> file=open('testfile2.csv','r') >>> print(file.read()) 1,10,1 2,5,1 3,6,1 4,10,1 6,5,1 8,3,1 9,8,1 10,2,1 >>> #################### gdf_maker #################### >>> random.seed(2) >>> engine.gen_using(gdf_maker, 'testfile', {'vertices':10, 'edge_number':5, 'direct':0}) 5 >>> file=open('testfile.gdf','r') >>> print(file.read()) nodedef>name VARCHAR,label VARCHAR 1,Node1 2,Node2 3,Node3 4,Node4 5,Node5 6,Node6 7,Node7 8,Node8 9,Node9 10,Node10 edgedef>node1 VARCHAR,node2 VARCHAR,weight DOUBLE 1,2,1 1,10,1 3,6,1 3,7,1 6,10,1 >>> random.seed(4) >>> engine.gen_using(gdf_maker, 'testfile2', {'vertices':10, 'edge_number':8, 'direct':1}) 8 >>> file=open('testfile2.gdf','r') >>> print(file.read()) nodedef>name VARCHAR,label VARCHAR 1,Node1 2,Node2 3,Node3 4,Node4 5,Node5 6,Node6 7,Node7 8,Node8 9,Node9 10,Node10 edgedef>node1 VARCHAR,node2 VARCHAR,weight DOUBLE 1,10,1 2,5,1 3,6,1 4,10,1 6,5,1 8,3,1 9,8,1 10,2,1 >>> #################### gl_maker #################### >>> random.seed(2) >>> engine.gen_using(gl_maker, 'testfile', {'vertices':10, 'edge_number':5, 'direct':0}) 5 >>> file=open('testfile.gl','r') >>> print(file.read()) 1 2:1 10:1 3 6:1 7:1 6 10:1 >>> random.seed(4) >>> engine.gen_using(gl_maker, 'testfile2', {'vertices':10, 'edge_number':8, 'direct':1}) 8 >>> file=open('testfile2.gl','r') >>> print(file.read()) 1 10:1 2 5:1 3 6:1 4 10:1 6 5:1 8 3:1 9 8:1 10 2:1 >>> #################### mtx_maker #################### >>> from scipy.io import mmread >>> random.seed(2) >>> engine.gen_using(mtx_maker, 'testfile', {'vertices':10, 'edge_number':5, 'direct':0}) 5 >>> g = mmread("testfile.mtx") >>> print(g.data.tolist()) [1.0, 1.0, 1.0, 1.0, 1.0] >>> random.seed(4) >>> engine.gen_using(mtx_maker, 'testfile2', {'vertices':10, 'edge_number':8, 'direct':1}) 8 >>> g = mmread("testfile2.mtx") >>> print(g.data.tolist()) [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0] >>> #################### tsv_maker #################### >>> random.seed(2) >>> engine.gen_using(tsv_maker, 'testfile', {'vertices':10, 'edge_number':5, 'direct':0}) 5 >>> file=open('testfile.tsv','r') >>> print(file.read()) 1 2 1 1 10 1 3 6 1 3 7 1 6 10 1 >>> random.seed(4) >>> engine.gen_using(tsv_maker, 'testfile2', {'vertices':10, 'edge_number':8, 'direct':1}) 8 >>> file=open('testfile2.tsv','r') >>> print(file.read()) 1 10 1 2 5 1 3 6 1 4 10 1 6 5 1 8 3 1 9 8 1 10 2 1 >>> #################### wel_maker #################### >>> random.seed(2) >>> engine.gen_using(wel_maker, 'testfile', {'vertices':10, 'edge_number':5, 'direct':0}) 5 >>> file=open('testfile.wel','r') >>> print(file.read()) 1 2 1 1 10 1 3 6 1 3 7 1 6 10 1 >>> random.seed(4) >>> engine.gen_using(wel_maker, 'testfile2', {'vertices':10, 'edge_number':8, 'direct':1}) 8 >>> file=open('testfile2.wel','r') >>> print(file.read()) 1 10 1 2 5 1 3 6 1 4 10 1 6 5 1 8 3 1 9 8 1 10 2 1 >>> #################### lp_maker #################### >>> random.seed(2) >>> engine.gen_using(lp_maker, 'testfile', {'vertices':10, 'edge_number':5, 'direct':0}) 5 >>> file=open('testfile.lp','r') >>> print(file.read()) node(1). node(2). node(3). node(4). node(5). node(6). node(7). node(8). node(9). node(10). edge(1,2,1). edge(1,10,1). edge(3,6,1). edge(3,7,1). edge(6,10,1). >>> random.seed(4) >>> engine.gen_using(lp_maker, 'testfile2', {'vertices':10, 'edge_number':8, 'direct':1}) 8 >>> file=open('testfile2.lp','r') >>> print(file.read()) node(1). node(2). node(3). node(4). node(5). node(6). node(7). node(8). node(9). node(10). edge(1,10,1). edge(2,5,1). edge(3,6,1). edge(4,10,1). edge(6,5,1). edge(8,3,1). edge(9,8,1). edge(10,2,1). >>> #################### tgf_maker #################### >>> random.seed(2) >>> engine.gen_using(tgf_maker, 'testfile', {'vertices':10, 'edge_number':5, 'direct':0}) 5 >>> file=open('testfile.tgf','r') >>> print(file.read()) 1 2 3 4 5 6 7 8 9 10 # 1 2 1 1 10 1 3 6 1 3 7 1 6 10 1 >>> random.seed(4) >>> engine.gen_using(tgf_maker, 'testfile2', {'vertices':10, 'edge_number':8, 'direct':1}) 8 >>> file=open('testfile2.tgf','r') >>> print(file.read()) 1 2 3 4 5 6 7 8 9 10 # 1 10 1 2 5 1 3 6 1 4 10 1 6 5 1 8 3 1 9 8 1 10 2 1 >>> #################### dl_maker #################### >>> random.seed(2) >>> engine.gen_using(dl_maker, 'testfile', {'vertices':10, 'edge_number':5, 'direct':0}) 5 >>> file=open('testfile.dl','r') >>> print(file.read()) dl format=edgelist1 n=10 data: 1 2 1 1 10 1 3 6 1 3 7 1 6 10 1 >>> random.seed(4) >>> engine.gen_using(dl_maker, 'testfile2', {'vertices':10, 'edge_number':8, 'direct':1}) 8 >>> file=open('testfile2.dl','r') >>> print(file.read()) dl format=edgelist1 n=10 data: 1 10 1 2 5 1 3 6 1 4 10 1 6 5 1 8 3 1 9 8 1 10 2 1 >>> #################### gml_maker #################### >>> from networkx.readwrite.gml import read_gml >>> random.seed(2) >>> engine.gen_using(gml_maker, 'testfile', {'vertices':10, 'edge_number':5, 'direct':0}) 5 >>> gml1 = read_gml("testfile.gml") >>> type(gml1) >>> random.seed(4) >>> engine.gen_using(gml_maker, 'testfile2', {'vertices':10, 'edge_number':8, 'direct':1}) 8 >>> gml2 = read_gml("testfile2.gml") >>> type(gml2) >>> #################### gexf_maker #################### >>> from networkx.readwrite.gexf import read_gexf >>> random.seed(2) >>> engine.gen_using(gexf_maker, 'testfile', {'vertices':10, 'edge_number':5, 'direct':0}) 5 >>> gexf1 = read_gexf("testfile.gexf") >>> type(gexf1) >>> random.seed(4) >>> engine.gen_using(gexf_maker, 'testfile2', {'vertices':10, 'edge_number':8, 'direct':1}) 8 >>> gexf2 = read_gexf("testfile2.gexf") >>> type(gexf2) >>> #################### dot_maker #################### >>> import pydot >>> random.seed(2) >>> engine.gen_using(dot_maker, 'testfile', {'vertices':10, 'edge_number':5, 'direct':0}) 5 >>> file=open('testfile.gv','r') >>> g1 = pydot.graph_from_dot_data(file.read()) >>> g1[0].get_type() 'graph' >>> len(g1[0].get_edge_list()) 5 >>> random.seed(4) >>> engine.gen_using(dot_maker, 'testfile2', {'vertices':10, 'edge_number':8, 'direct':1}) 8 >>> file=open('testfile2.gv','r') >>> g2 = pydot.graph_from_dot_data(file.read()) >>> g2[0].get_type() 'digraph' >>> len(g2[0].get_edge_list()) 8 >>> file.close() >>> os.remove('testfile.gr') >>> os.remove('testfile2.gr') >>> os.remove('testfile.json') >>> os.remove('testfile2.json') >>> os.remove('testfile.csv') >>> os.remove('testfile2.csv') >>> os.remove('testfile.gdf') >>> os.remove('testfile2.gdf') >>> os.remove('testfile.gl') >>> os.remove('testfile2.gl') >>> os.remove('testfile.mtx') >>> os.remove('testfile2.mtx') >>> os.remove('testfile.tsv') >>> os.remove('testfile2.tsv') >>> os.remove('testfile.wel') >>> os.remove('testfile2.wel') >>> os.remove('testfile.lp') >>> os.remove('testfile2.lp') >>> os.remove('testfile.tgf') >>> os.remove('testfile2.tgf') >>> os.remove('testfile.dl') >>> os.remove('testfile2.dl') >>> os.remove('testfile.gml') >>> os.remove('testfile2.gml') >>> os.remove('testfile.gexf') >>> os.remove('testfile2.gexf') >>> os.remove('testfile.gv') >>> os.remove('testfile2.gv') >>> os.remove('logfile.log') """ pyrgg-1.6/test/engines/pyrgg_test.py000066400000000000000000001044341471451651000176720ustar00rootroot00000000000000# -*- coding: utf-8 -*- """ >>> from pyrgg.functions import * >>> from pyrgg.graph_gen import * >>> import pyrgg.params >>> import random >>> import os >>> import json >>> import pyrgg.engines.pyrgg as engine >>> os.environ["PYRGG_TEST_MODE"] = "1" >>> ###################################### >>> ## ========= logger function ========= >>> ###################################### >>> with open('logfile.log','a') as file: ... engine.logger(file,'test','2min',{'vertices':100,'edge_number':50,'max_edge':1000,'min_edge':10,'direct':1,'sign':0,'multigraph':0,'self_loop':1,'max_weight':20,'min_weight':1,'engine':1,'output_format':1}) >>> file = open('logfile.log','r') >>> print("\\n".join(file.read().splitlines()[1:-1])) Filename : test Vertices : 100 Total Edges : 50 Max Edge : 1000 Min Edge : 10 Directed : True Signed : False Multigraph : False Self Loop : True Weighted : True Max Weight : 20 Min Weight : 1 Engine : 1 (pyrgg) Elapsed Time : 2min >>> class StrError: ... def __init__(self): ... pass ... def __str__(self): ... raise ValueError >>> str_error_object = StrError() >>> with open('logfile.log','a') as file: ... engine.logger(file,'test','2min',{'vertices':str_error_object,'edge_number':50,'max_edge':1000,'min_edge':10,'direct':1,'sign':0,'multigraph':0,'self_loop':1,'max_weight':20,'min_weight':1,'engine':1,'output_format':1}) [Error] Logger failed! >>> ########################################## >>> ## ========= branch_gen function ========= >>> ########################################## >>> used_vertices = {k:[] for k in range(1,6)} >>> degree_dict = {1:2,2:3,3:3,4:3,5:3} >>> degree_dict_sort = {0:{},1:{},2:{1:1},3:{2:2,3:3,4:4,5:5},4:{},5:{}} >>> all_vertices = list(range(1, 6)) >>> engine.branch_gen(1,3,3,300,3000,0,True,False,False,False,used_vertices,degree_dict,degree_dict_sort) [[], []] >>> used_vertices = {k:[] for k in range(1,41)} >>> degree_dict = {k:0 for k in range(1,41)} >>> degree_dict_sort = {k:{} for k in range(41)} >>> degree_dict_sort[0] = {i:i for i in range(1,41)} >>> all_vertices = list(range(1, 41)) >>> random.seed(2) >>> engine.branch_gen(1,10,10,1,20,0,True,True,True,False,used_vertices,degree_dict,degree_dict_sort) [[4, 25, 18, 3, 30, 34, 2, 26, 14, 11], [3, 10, 20, 14, -18, -2, -15, -14, 8, 6]] >>> random.seed(20) >>> engine.branch_gen(1,10,4,1,20,0,False,True,True,False,used_vertices,degree_dict,degree_dict_sort) [[], []] >>> used_vertices = {k:[] for k in range(1,41)} >>> degree_dict = {k:0 for k in range(1,41)} >>> degree_dict_sort = {k:{} for k in range(41)} >>> degree_dict_sort[0] = {i:i for i in range(1,41)} >>> engine.branch_gen(1,10,4,1,20,0,False,True,True,False,used_vertices,degree_dict,degree_dict_sort) [[10, 7, 39, 2, 30, 9, 25, 35, 18], [9, 11, 6, 14, 3, 5, 16, 14, 7]] >>> engine.branch_gen(40,1,20,1) Traceback (most recent call last): ... TypeError: branch_gen() missing 9 required positional arguments: 'max_weight', 'precision', 'sign', 'direct', 'self_loop', 'multigraph', 'used_vertices', 'degree_dict', and 'degree_sort_dict' >>> ########################################## >>> ## ========= edge_gen function ========= >>> ########################################## >>> random.seed(2) >>> engine.edge_gen(20,0,400,2,10,True,True,True,False) [{1: [3, 7], 2: [4, 17, 20, 9, 11], 3: [14, 8, 5, 12, 16, 19, 15], 4: [15, 17, 12, 8, 14, 13], 5: [16, 9, 7, 20, 19, 18, 13, 5], 6: [6, 10], 7: [18, 10, 11], 8: [], 9: [], 10: [12, 18, 8, 1, 14], 11: [9, 11], 12: [], 13: [], 14: [19, 16, 17, 20, 15], 15: [6, 1, 19], 16: [12, 13, 8, 9, 17], 17: [], 18: [9, 12, 17, 6, 20, 19, 1], 19: [13], 20: []}, {1: [184, -128], 2: [220, -278, -257, 14, -163], 3: [286, 118, 166, 261, -263, 228, -303], 4: [-82, -335, 250, -256, -338, -179], 5: [-337, -358, -395, -155, -159, 250, -350, -371], 6: [30, -302], 7: [386, -125, 216], 8: [], 9: [], 10: [127, 42, 12, 191, 80], 11: [-301, 77], 12: [], 13: [], 14: [146, -15, -282, 135, 242], 15: [-52, -65, -249], 16: [-132, -334, 343, -17, 87], 17: [], 18: [126, -37, 302, -131, -142, 77, -209], 19: [123], 20: []}, 61] >>> random.seed(11) >>> engine.edge_gen(20,0,100,2,10,False,True,True,False) [{1: [18, 15, 19, 7, 20, 11, 2, 6, 3], 2: [17], 3: [8, 4, 5, 9, 12, 10, 14, 16], 4: [20, 13, 4, 6], 5: [12, 7, 11, 10, 14], 6: [9], 7: [19], 8: [8, 18, 11, 2, 16, 17, 10], 9: [15, 12, 18], 10: [20, 14, 13, 15, 17, 16], 11: [19, 7, 20], 12: [13], 13: [2, 16, 13], 14: [18, 19, 6, 14, 17, 15], 15: [6, 7, 16], 16: [17, 20, 12, 18], 17: [19], 18: [7, 6, 9, 12, 20], 19: [19, 11, 4], 20: []}, {1: [99, 57, 75, 23, 80, 23, 57, 18, 68], 2: [50], 3: [79, 67, 7, 24, 76, 99, 41, 75], 4: [29, 63, 84, 58], 5: [70, 90, 40, 65, 3], 6: [51], 7: [37], 8: [2, 0, 26, 60, 90, 53, 72], 9: [43, 39, 1], 10: [15, 31, 1, 59, 22, 57], 11: [98, 53, 49], 12: [53], 13: [34, 2, 23], 14: [82, 12, 18, 56, 1, 37], 15: [9, 26, 1], 16: [47, 58, 75, 73], 17: [23], 18: [39, 78, 92, 20, 49], 19: [10, 6, 13], 20: []}, 74] >>> engine.edge_gen(0,400,2,10,1) Traceback (most recent call last): ... TypeError: edge_gen() missing 4 required positional arguments: 'sign', 'direct', 'self_loop', and 'multigraph' >>> ######################################### >>> ## ========= gen_using function ========= >>> ######################################### >>> #################### dimacs_maker #################### >>> random.seed(2) >>> engine.gen_using(dimacs_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.gr','r') >>> print(file.read()) c FILE :testfile.gr c No. of vertices :10 c No. of edges :7 c Max. weight :148 c Min. weight :7 p sp 10 7 a 4 3 -64 a 5 6 148 a 5 9 110 a 6 10 -139 a 7 7 7 a 8 2 -97 a 9 1 60 >>> random.seed(4) >>> engine.gen_using(dimacs_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 35 >>> file=open('testfile2.gr','r') >>> print(file.read()) c FILE :testfile2.gr c No. of vertices :30 c No. of edges :35 c Max. weight :50 c Min. weight :2 p sp 30 35 a 1 10 46 a 2 18 5 a 2 4 25 a 2 22 -48 a 4 23 -17 a 5 7 -13 a 7 15 10 a 7 17 -40 a 8 8 -42 a 8 25 11 a 9 29 -5 a 10 3 -36 a 10 27 -48 a 11 13 -27 a 11 26 -27 a 11 21 14 a 11 16 -2 a 14 20 -44 a 14 14 43 a 14 12 26 a 15 28 -11 a 16 30 -40 a 16 24 20 a 19 19 7 a 20 12 -29 a 20 1 22 a 22 24 20 a 22 23 -9 a 23 18 18 a 23 27 28 a 24 6 -24 a 25 17 23 a 27 6 -50 a 28 21 28 a 28 13 -13 >>> random.seed(20) >>> engine.gen_using(dimacs_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':0, 'direct':1, 'self_loop':1, 'multigraph':0}) 137 >>> file=open('testfile3.gr','r') >>> print(file.read()) c FILE :testfile3.gr c No. of vertices :100 c No. of edges :137 c Max. weight :30 c Min. weight :10 p sp 100 137 a 1 34 30 a 3 76 15 a 3 5 23 a 4 13 13 a 4 21 20 a 4 67 28 a 5 60 16 a 5 32 20 a 5 92 20 a 6 64 12 a 6 94 26 a 7 62 12 a 7 36 28 a 7 42 11 a 8 20 12 a 9 47 19 a 10 49 15 a 10 27 10 a 11 48 17 a 11 51 11 a 13 58 14 a 13 70 29 a 14 37 30 a 14 61 27 a 14 87 15 a 15 84 13 a 16 83 28 a 17 45 17 a 17 24 29 a 17 18 26 a 18 59 15 a 19 98 12 a 21 2 30 a 21 99 20 a 22 69 26 a 22 96 11 a 22 88 15 a 24 79 20 a 24 12 12 a 24 82 13 a 26 50 30 a 26 30 19 a 29 52 26 a 31 25 26 a 32 68 14 a 33 65 13 a 33 78 13 a 33 55 17 a 34 63 13 a 35 44 27 a 35 57 14 a 37 74 10 a 37 41 16 a 37 100 30 a 38 72 13 a 38 56 16 a 39 91 19 a 39 43 13 a 41 28 22 a 41 81 19 a 42 90 13 a 42 46 28 a 42 97 16 a 45 86 10 a 45 53 18 a 46 85 13 a 46 23 11 a 47 71 29 a 48 95 12 a 48 77 19 a 48 93 11 a 49 75 22 a 50 73 18 a 50 40 24 a 50 54 28 a 51 80 17 a 51 66 19 a 51 89 20 a 52 58 29 a 52 16 21 a 52 43 12 a 53 8 13 a 53 98 17 a 54 55 10 a 56 62 26 a 56 27 10 a 57 70 26 a 58 44 22 a 59 90 27 a 59 91 19 a 59 78 29 a 60 87 12 a 60 92 25 a 61 69 14 a 61 79 17 a 62 25 21 a 63 97 27 a 63 29 30 a 65 9 26 a 65 64 21 a 66 67 27 a 66 95 19 a 66 93 30 a 68 30 18 a 70 83 12 a 70 99 15 a 71 31 17 a 71 89 20 a 73 36 18 a 75 72 12 a 76 2 26 a 76 12 25 a 76 86 22 a 78 23 19 a 78 100 27 a 79 40 24 a 80 84 26 a 80 80 14 a 81 20 16 a 82 15 16 a 82 88 22 a 83 19 19 a 84 85 13 a 84 28 16 a 85 77 16 a 85 94 23 a 86 1 21 a 87 74 15 a 87 96 19 a 90 93 22 a 92 49 14 a 95 98 26 a 95 55 11 a 97 38 28 a 99 19 29 a 99 89 24 a 100 40 11 >>> random.seed(20) >>> engine.gen_using(dimacs_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':0, 'direct':0, 'self_loop':1, 'multigraph':1}) 131 >>> file=open('testfile3.gr','r') >>> print(file.read()) c FILE :testfile3.gr c No. of vertices :100 c No. of edges :131 c Max. weight :30 c Min. weight :10 p sp 100 131 a 1 34 30 a 3 76 15 a 3 5 23 a 4 13 13 a 4 20 20 a 4 65 28 a 5 60 16 a 5 32 20 a 5 90 20 a 6 64 12 a 6 93 26 a 7 62 12 a 7 36 28 a 7 41 11 a 8 21 12 a 9 47 19 a 10 49 15 a 10 27 10 a 11 48 17 a 11 100 17 a 14 61 18 a 14 33 30 a 14 68 29 a 14 84 14 a 15 87 15 a 15 42 22 a 17 82 28 a 18 46 17 a 18 24 29 a 18 18 26 a 19 57 15 a 20 97 12 a 22 2 30 a 22 95 20 a 23 69 26 a 23 94 11 a 23 85 15 a 25 78 20 a 25 12 12 a 25 79 13 a 27 52 30 a 27 31 19 a 30 51 26 a 32 26 26 a 33 66 14 a 34 59 13 a 34 74 13 a 34 54 17 a 35 56 13 a 36 44 27 a 36 83 14 a 38 70 10 a 38 39 16 a 38 91 30 a 39 67 13 a 39 99 19 a 40 63 29 a 41 43 13 a 41 16 18 a 43 75 19 a 43 77 24 a 43 45 12 a 44 58 10 a 44 96 12 a 44 98 29 a 45 86 10 a 45 37 18 a 46 81 13 a 46 28 11 a 47 55 29 a 48 92 12 a 48 92 21 a 48 72 24 a 50 88 27 a 51 73 18 a 51 29 24 a 51 29 28 a 52 80 17 a 52 71 19 a 52 89 20 a 53 58 29 a 53 16 21 a 53 40 12 a 54 8 13 a 54 98 17 a 55 55 10 a 56 82 21 a 57 73 14 a 57 2 17 a 58 76 24 a 59 67 22 a 60 78 29 a 60 88 19 a 62 61 21 a 62 99 14 a 62 75 17 a 63 26 21 a 63 66 30 a 63 87 14 a 65 12 26 a 65 37 21 a 66 50 27 a 67 74 25 a 67 42 14 a 68 72 10 a 70 84 18 a 71 91 20 a 74 30 13 a 76 13 25 a 78 9 25 a 78 81 22 a 80 96 19 a 81 90 23 a 81 28 24 a 82 93 25 a 83 31 16 a 85 21 16 a 85 94 22 a 86 17 19 a 86 86 27 a 89 97 19 a 91 49 23 a 91 77 13 a 92 100 17 a 93 24 27 a 93 69 19 a 96 64 14 a 97 95 14 a 98 1 15 a 98 1 13 a 99 35 28 >>> random.seed(4) >>> engine.gen_using(dimacs_maker, 'testfile4', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':0, 'multigraph':0}) 37 >>> file=open('testfile4.gr','r') >>> print(file.read()) c FILE :testfile4.gr c No. of vertices :30 c No. of edges :37 c Max. weight :50 c Min. weight :0 p sp 30 37 a 1 11 46 a 2 19 5 a 2 5 25 a 2 23 -48 a 4 24 -17 a 5 8 -13 a 7 16 10 a 7 18 -40 a 8 9 -42 a 8 26 11 a 9 30 -5 a 10 29 0 a 10 14 -48 a 10 22 26 a 10 20 -27 a 11 12 19 a 11 17 5 a 11 3 -40 a 12 25 -44 a 12 15 43 a 13 6 -12 a 14 27 22 a 14 28 -40 a 14 21 -6 a 16 19 7 a 17 15 -29 a 17 1 22 a 19 25 20 a 20 21 49 a 20 28 -39 a 21 4 -39 a 21 18 -18 a 22 24 -38 a 23 13 23 a 25 6 -50 a 26 29 28 a 26 3 -13 >>> #################### json_maker #################### >>> random.seed(2) >>> engine.gen_using(json_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':True, 'direct':True, 'self_loop':True, 'multigraph':False}) 7 >>> file=open('testfile.json','r') >>> testfile_1=json.load(file) >>> testfile_1['graph']['nodes'][1] {'id': 2} >>> testfile_1['graph']['edges'][1]['source'] 5 >>> testfile_1['graph']['edges'][1]['target'] 6 >>> testfile_1['graph']['edges'][1]['weight'] 148 >>> testfile_1['properties']['directed'] True >>> testfile_1['properties']['multigraph'] False >>> testfile_1['properties']['weighted'] True >>> random.seed(4) >>> engine.gen_using(json_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':True, 'direct':True, 'self_loop':True, 'multigraph':False}) 35 >>> file=open('testfile2.json','r') >>> testfile_2=json.load(file) >>> testfile_2['graph']['nodes'][1] {'id': 2} >>> testfile_2['graph']['edges'][1]['source'] 2 >>> testfile_2['graph']['edges'][1]['target'] 18 >>> testfile_2['graph']['edges'][1]['weight'] 5 >>> testfile_2['properties']['multigraph'] False >>> testfile_2['properties']['directed'] True >>> testfile_2['properties']['weighted'] True >>> random.seed(20) >>> engine.gen_using(json_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':False, 'direct':True, 'self_loop':True, 'multigraph':False}) 137 >>> file=open('testfile3.json','r') >>> testfile_3=json.load(file) >>> testfile_3['graph']['nodes'][1] {'id': 2} >>> testfile_3['graph']['edges'][1]['source'] 3 >>> testfile_3['graph']['edges'][1]['target'] 76 >>> testfile_3['graph']['edges'][1]['weight'] 15 >>> testfile_3['properties']['directed'] True >>> testfile_3['properties']['multigraph'] False >>> testfile_3['properties']['weighted'] True >>> random.seed(20) >>> engine.gen_using(json_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':False, 'direct':False, 'self_loop':True, 'multigraph':True}) 131 >>> file=open('testfile3.json','r') >>> testfile_3=json.load(file) >>> testfile_3['properties']['directed'] False >>> testfile_3['properties']['multigraph'] True >>> testfile_3['properties']['weighted'] True >>> random.seed(21) >>> engine.gen_using(json_maker, 'testfile3', {'min_weight':1, 'max_weight':1, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':False, 'direct':False, 'self_loop':True, 'multigraph':True}) 136 >>> file=open('testfile3.json','r') >>> testfile_3=json.load(file) >>> testfile_3['properties']['weighted'] False >>> random.seed(21) >>> engine.gen_using(json_maker, 'testfile3', {'min_weight':1, 'max_weight':1, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':True, 'direct':False, 'self_loop':True, 'multigraph':True}) 158 >>> file=open('testfile3.json','r') >>> testfile_3=json.load(file) >>> testfile_3['properties']['weighted'] True >>> #################### csv_maker #################### >>> random.seed(2) >>> engine.gen_using(csv_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':True, 'direct':True, 'self_loop':True, 'multigraph':False}) 7 >>> file=open('testfile.csv','r') >>> print(file.read()) 4,3,-64 5,6,148 5,9,110 6,10,-139 7,7,7 8,2,-97 9,1,60 >>> random.seed(4) >>> engine.gen_using(csv_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':True, 'direct':True, 'self_loop':True, 'multigraph':False}) 35 >>> file=open('testfile2.csv','r') >>> print(file.read()) 1,10,46 2,18,5 2,4,25 2,22,-48 4,23,-17 5,7,-13 7,15,10 7,17,-40 8,8,-42 8,25,11 9,29,-5 10,3,-36 10,27,-48 11,13,-27 11,26,-27 11,21,14 11,16,-2 14,20,-44 14,14,43 14,12,26 15,28,-11 16,30,-40 16,24,20 19,19,7 20,12,-29 20,1,22 22,24,20 22,23,-9 23,18,18 23,27,28 24,6,-24 25,17,23 27,6,-50 28,21,28 28,13,-13 >>> random.seed(20) >>> engine.gen_using(csv_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':False, 'direct':True, 'self_loop':True, 'multigraph':False}) 137 >>> file=open('testfile3.csv','r') >>> print(file.read()) 1,34,30 3,76,15 3,5,23 4,13,13 4,21,20 4,67,28 5,60,16 5,32,20 5,92,20 6,64,12 6,94,26 7,62,12 7,36,28 7,42,11 8,20,12 9,47,19 10,49,15 10,27,10 11,48,17 11,51,11 13,58,14 13,70,29 14,37,30 14,61,27 14,87,15 15,84,13 16,83,28 17,45,17 17,24,29 17,18,26 18,59,15 19,98,12 21,2,30 21,99,20 22,69,26 22,96,11 22,88,15 24,79,20 24,12,12 24,82,13 26,50,30 26,30,19 29,52,26 31,25,26 32,68,14 33,65,13 33,78,13 33,55,17 34,63,13 35,44,27 35,57,14 37,74,10 37,41,16 37,100,30 38,72,13 38,56,16 39,91,19 39,43,13 41,28,22 41,81,19 42,90,13 42,46,28 42,97,16 45,86,10 45,53,18 46,85,13 46,23,11 47,71,29 48,95,12 48,77,19 48,93,11 49,75,22 50,73,18 50,40,24 50,54,28 51,80,17 51,66,19 51,89,20 52,58,29 52,16,21 52,43,12 53,8,13 53,98,17 54,55,10 56,62,26 56,27,10 57,70,26 58,44,22 59,90,27 59,91,19 59,78,29 60,87,12 60,92,25 61,69,14 61,79,17 62,25,21 63,97,27 63,29,30 65,9,26 65,64,21 66,67,27 66,95,19 66,93,30 68,30,18 70,83,12 70,99,15 71,31,17 71,89,20 73,36,18 75,72,12 76,2,26 76,12,25 76,86,22 78,23,19 78,100,27 79,40,24 80,84,26 80,80,14 81,20,16 82,15,16 82,88,22 83,19,19 84,85,13 84,28,16 85,77,16 85,94,23 86,1,21 87,74,15 87,96,19 90,93,22 92,49,14 95,98,26 95,55,11 97,38,28 99,19,29 99,89,24 100,40,11 >>> random.seed(20) >>> engine.gen_using(csv_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':0, 'direct':0, 'self_loop':1, 'multigraph':1}) 131 >>> random.seed(2) >>> engine.gen_using(csv_maker, 'testfile4', {'min_weight':0.0, 'max_weight':200.22, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 5 >>> file = open("testfile4.csv") >>> print(file.read()) 4,3,-50.37 6,1,200.16 6,9,-160.91 7,7,-100.52 10,10,-181.75 >>> random.seed(2) >>> engine.gen_using(csv_maker, 'testfile4', {'min_weight':0.0, 'max_weight':200.222, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 5 >>> file = open("testfile4.csv") >>> print(file.read()) 4,3,-50.373 6,1,200.166 6,9,-160.912 7,7,-100.525 10,10,-181.752 >>> #################### gdf_maker #################### >>> random.seed(2) >>> engine.gen_using(gdf_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.gdf','r') >>> print(file.read()) nodedef>name VARCHAR,label VARCHAR 1,Node1 2,Node2 3,Node3 4,Node4 5,Node5 6,Node6 7,Node7 8,Node8 9,Node9 10,Node10 edgedef>node1 VARCHAR,node2 VARCHAR,weight DOUBLE 4,3,-64 5,6,148 5,9,110 6,10,-139 7,7,7 8,2,-97 9,1,60 >>> random.seed(4) >>> engine.gen_using(gdf_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 35 >>> random.seed(20) >>> engine.gen_using(gdf_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':0, 'direct':1, 'self_loop':1, 'multigraph':0}) 137 >>> random.seed(20) >>> engine.gen_using(gdf_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':0, 'direct':0, 'self_loop':1, 'multigraph':1}) 131 >>> #################### gl_maker #################### >>> random.seed(2) >>> engine.gen_using(gl_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':1, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.gl','r') >>> print(file.read()) 1 2:92 3 7:155 9:110 4 10:-139 8:-9 5 6:-81 6 9:143 >>> random.seed(4) >>> engine.gen_using(gl_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':2, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 44 >>> file=open('testfile2.gl','r') >>> print(file.read()) 1 10:46 14:-9 2 4:25 22:-48 3 12:-17 9:16 4 5:-17 5 15:-18 6 23:38 21:-32 18:15 30:-5 7 29:0 16:-48 25:26 20:-27 8 13:19 24:5 8:-40 9 27:-44 19:43 10 11:-12 11 28:-17 17:-27 26:20 12 13:17 13 21:21 19:-29 14 14:-44 15 20:-1 16 23:-9 30:-39 17 18:-39 25:-18 22:-24 18 26:-36 24:-2 19 27:-50 20 29:28 22 28:3 25 10:38 2:-37 27 1:33 28 23:30 >>> random.seed(20) >>> engine.gen_using(gl_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':3, 'max_edge':4, 'sign':0, 'direct':1, 'self_loop':1, 'multigraph':0}) 178 >>> file=open('testfile3.gl','r') >>> print(file.read()) 1 34:30 13:20 76:15 2 56:23 11:13 20:20 3 83:24 60:16 31:20 92:20 4 65:12 95:26 74:22 16:16 5 9:16 22:12 37:18 6 54:18 33:29 27:10 51:17 7 48:11 8:30 62:18 8 69:29 88:14 9 86:15 41:22 32:14 10 75:17 21:29 15:26 30:23 11 35:12 25:19 12 94:30 96:20 82:22 13 70:11 85:15 28:24 14 14:12 79:13 26:20 15 91:12 97:19 98:11 16 44:17 77:26 17 42:10 81:14 57:14 18 55:13 68:13 49:17 47:17 19 66:14 80:14 71:12 20 61:10 39:16 100:30 21 58:13 50:16 59:29 22 38:13 23:18 29:22 23 64:22 87:13 40:28 24 53:10 43:27 78:20 90:10 25 63:19 93:13 26 36:16 67:29 27 46:28 99:21 72:24 28 52:29 89:27 29 73:18 45:24 84:28 30 70:17 55:19 89:20 31 58:29 37:21 49:12 32 33:13 67:17 73:14 33 91:10 43:21 34 75:14 35:17 68:26 35 54:22 66:27 36 80:29 92:19 88:12 37 60:21 47:24 38 83:14 71:20 39 99:27 48:18 40 94:16 78:22 41 98:26 74:25 42 56:14 76:10 43 97:15 44 59:17 93:20 46:14 45 63:13 53:19 51:25 46 87:11 47 86:22 95:13 48 77:26 49 64:24 96:26 50 90:14 57:16 62:19 51 69:24 52 84:12 79:30 61:16 53 100:19 54 85:19 55 82:13 72:26 56 65:27 57 75:14 80:22 58 81:26 59 93:12 60 95:26 61 68:18 62 67:27 77:29 63 82:23 100:11 64 98:15 65 86:29 66 73:17 79:17 69 89:20 81:27 70 97:11 71 74:26 84:10 72 99:21 85:19 73 78:21 76 87:17 78 91:11 81 94:27 82 83:19 83 92:20 85 88:14 88 90:16 91 96:13 94 68:30 95 89:18 96 87:29 98 7:10 100 28:14 >>> #################### mtx_maker #################### >>> from scipy.io import mmread >>> random.seed(2) >>> engine.gen_using(mtx_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> g = mmread("testfile.mtx") >>> print(g.data.tolist()) [-64.0, 148.0, 110.0, -139.0, 7.0, -97.0, 60.0] >>> random.seed(4) >>> engine.gen_using(mtx_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 35 >>> g = mmread("testfile2.mtx") >>> print(int(sum(g.data.tolist()))) -179 >>> random.seed(20) >>> engine.gen_using(mtx_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':0, 'direct':1, 'self_loop':1, 'multigraph':0}) 137 >>> g = mmread("testfile3.mtx") >>> print(int(sum(g.data.tolist()))) 2644 >>> random.seed(20) >>> engine.gen_using(mtx_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':0, 'direct':0, 'self_loop':1, 'multigraph':1}) 131 >>> #################### tsv_maker #################### >>> random.seed(2) >>> engine.gen_using(tsv_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.tsv','r') >>> print(file.read()) 4 3 -64 5 6 148 5 9 110 6 10 -139 7 7 7 8 2 -97 9 1 60 >>> random.seed(4) >>> engine.gen_using(tsv_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 35 >>> random.seed(20) >>> engine.gen_using(tsv_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':0, 'direct':1, 'self_loop':1, 'multigraph':0}) 137 >>> random.seed(20) >>> engine.gen_using(tsv_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':0, 'direct':0, 'self_loop':1, 'multigraph':1}) 131 >>> #################### wel_maker #################### >>> random.seed(2) >>> engine.gen_using(wel_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.wel','r') >>> print(file.read()) 4 3 -64 5 6 148 5 9 110 6 10 -139 7 7 7 8 2 -97 9 1 60 >>> random.seed(4) >>> engine.gen_using(wel_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 35 >>> file=open('testfile2.wel','r') >>> print(file.read()) 1 10 46 2 18 5 2 4 25 2 22 -48 4 23 -17 5 7 -13 7 15 10 7 17 -40 8 8 -42 8 25 11 9 29 -5 10 3 -36 10 27 -48 11 13 -27 11 26 -27 11 21 14 11 16 -2 14 20 -44 14 14 43 14 12 26 15 28 -11 16 30 -40 16 24 20 19 19 7 20 12 -29 20 1 22 22 24 20 22 23 -9 23 18 18 23 27 28 24 6 -24 25 17 23 27 6 -50 28 21 28 28 13 -13 >>> random.seed(20) >>> engine.gen_using(wel_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':0, 'direct':1, 'self_loop':1, 'multigraph':0}) 137 >>> file=open('testfile3.wel','r') >>> print(file.read()) 1 34 30 3 76 15 3 5 23 4 13 13 4 21 20 4 67 28 5 60 16 5 32 20 5 92 20 6 64 12 6 94 26 7 62 12 7 36 28 7 42 11 8 20 12 9 47 19 10 49 15 10 27 10 11 48 17 11 51 11 13 58 14 13 70 29 14 37 30 14 61 27 14 87 15 15 84 13 16 83 28 17 45 17 17 24 29 17 18 26 18 59 15 19 98 12 21 2 30 21 99 20 22 69 26 22 96 11 22 88 15 24 79 20 24 12 12 24 82 13 26 50 30 26 30 19 29 52 26 31 25 26 32 68 14 33 65 13 33 78 13 33 55 17 34 63 13 35 44 27 35 57 14 37 74 10 37 41 16 37 100 30 38 72 13 38 56 16 39 91 19 39 43 13 41 28 22 41 81 19 42 90 13 42 46 28 42 97 16 45 86 10 45 53 18 46 85 13 46 23 11 47 71 29 48 95 12 48 77 19 48 93 11 49 75 22 50 73 18 50 40 24 50 54 28 51 80 17 51 66 19 51 89 20 52 58 29 52 16 21 52 43 12 53 8 13 53 98 17 54 55 10 56 62 26 56 27 10 57 70 26 58 44 22 59 90 27 59 91 19 59 78 29 60 87 12 60 92 25 61 69 14 61 79 17 62 25 21 63 97 27 63 29 30 65 9 26 65 64 21 66 67 27 66 95 19 66 93 30 68 30 18 70 83 12 70 99 15 71 31 17 71 89 20 73 36 18 75 72 12 76 2 26 76 12 25 76 86 22 78 23 19 78 100 27 79 40 24 80 84 26 80 80 14 81 20 16 82 15 16 82 88 22 83 19 19 84 85 13 84 28 16 85 77 16 85 94 23 86 1 21 87 74 15 87 96 19 90 93 22 92 49 14 95 98 26 95 55 11 97 38 28 99 19 29 99 89 24 100 40 11 >>> random.seed(20) >>> engine.gen_using(wel_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':0, 'direct':0, 'self_loop':1, 'multigraph':1}) 131 >>> #################### lp_maker #################### >>> random.seed(2) >>> engine.gen_using(lp_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.lp','r') >>> print(file.read()) node(1). node(2). node(3). node(4). node(5). node(6). node(7). node(8). node(9). node(10). edge(4,3,-64). edge(5,6,148). edge(5,9,110). edge(6,10,-139). edge(7,7,7). edge(8,2,-97). edge(9,1,60). >>> random.seed(4) >>> engine.gen_using(lp_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 35 >>> file=open('testfile2.lp','r') >>> print(file.read()) node(1). node(2). node(3). node(4). node(5). node(6). node(7). node(8). node(9). node(10). node(11). node(12). node(13). node(14). node(15). node(16). node(17). node(18). node(19). node(20). node(21). node(22). node(23). node(24). node(25). node(26). node(27). node(28). node(29). node(30). edge(1,10,46). edge(2,18,5). edge(2,4,25). edge(2,22,-48). edge(4,23,-17). edge(5,7,-13). edge(7,15,10). edge(7,17,-40). edge(8,8,-42). edge(8,25,11). edge(9,29,-5). edge(10,3,-36). edge(10,27,-48). edge(11,13,-27). edge(11,26,-27). edge(11,21,14). edge(11,16,-2). edge(14,20,-44). edge(14,14,43). edge(14,12,26). edge(15,28,-11). edge(16,30,-40). edge(16,24,20). edge(19,19,7). edge(20,12,-29). edge(20,1,22). edge(22,24,20). edge(22,23,-9). edge(23,18,18). edge(23,27,28). edge(24,6,-24). edge(25,17,23). edge(27,6,-50). edge(28,21,28). edge(28,13,-13). >>> #################### tgf_maker #################### >>> random.seed(2) >>> engine.gen_using(tgf_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.tgf','r') >>> print(file.read()) 1 2 3 4 5 6 7 8 9 10 # 4 3 -64 5 6 148 5 9 110 6 10 -139 7 7 7 8 2 -97 9 1 60 >>> random.seed(4) >>> engine.gen_using(tgf_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 35 >>> file=open('testfile2.tgf','r') >>> print(file.read()) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 # 1 10 46 2 18 5 2 4 25 2 22 -48 4 23 -17 5 7 -13 7 15 10 7 17 -40 8 8 -42 8 25 11 9 29 -5 10 3 -36 10 27 -48 11 13 -27 11 26 -27 11 21 14 11 16 -2 14 20 -44 14 14 43 14 12 26 15 28 -11 16 30 -40 16 24 20 19 19 7 20 12 -29 20 1 22 22 24 20 22 23 -9 23 18 18 23 27 28 24 6 -24 25 17 23 27 6 -50 28 21 28 28 13 -13 >>> #################### dl_maker #################### >>> random.seed(2) >>> engine.gen_using(dl_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.dl','r') >>> print(file.read()) dl format=edgelist1 n=10 data: 4 3 -64 5 6 148 5 9 110 6 10 -139 7 7 7 8 2 -97 9 1 60 >>> random.seed(4) >>> engine.gen_using(dl_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 35 >>> file=open('testfile2.dl','r') >>> print(file.read()) dl format=edgelist1 n=30 data: 1 10 46 2 18 5 2 4 25 2 22 -48 4 23 -17 5 7 -13 7 15 10 7 17 -40 8 8 -42 8 25 11 9 29 -5 10 3 -36 10 27 -48 11 13 -27 11 26 -27 11 21 14 11 16 -2 14 20 -44 14 14 43 14 12 26 15 28 -11 16 30 -40 16 24 20 19 19 7 20 12 -29 20 1 22 22 24 20 22 23 -9 23 18 18 23 27 28 24 6 -24 25 17 23 27 6 -50 28 21 28 28 13 -13 >>> #################### gml_maker #################### >>> from networkx.readwrite.gml import read_gml >>> random.seed(2) >>> engine.gen_using(gml_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> gml1 = read_gml("testfile.gml") >>> type(gml1) >>> random.seed(4) >>> engine.gen_using(gml_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':1}) 38 >>> gml2 = read_gml("testfile2.gml") >>> type(gml2) >>> random.seed(20) >>> engine.gen_using(gml_maker, 'testfile3', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':0, 'self_loop':1, 'multigraph':1}) 35 >>> gml3 = read_gml("testfile3.gml") >>> type(gml3) >>> random.seed(120) >>> engine.gen_using(gml_maker, 'testfile4', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':0, 'self_loop':1, 'multigraph':0}) 35 >>> gml4 = read_gml("testfile4.gml") >>> type(gml4) >>> #################### gexf_maker #################### >>> from networkx.readwrite.gexf import read_gexf >>> random.seed(2) >>> engine.gen_using(gexf_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> gexf1 = read_gexf("testfile.gexf") >>> type(gexf1) >>> random.seed(8) >>> engine.gen_using(gexf_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':1}) 35 >>> gexf2 = read_gexf("testfile2.gexf") >>> type(gexf2) >>> random.seed(20) >>> engine.gen_using(gexf_maker, 'testfile3', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':0, 'self_loop':1, 'multigraph':1}) 35 >>> gexf3 = read_gexf("testfile3.gexf") >>> type(gexf3) >>> random.seed(120) >>> engine.gen_using(gexf_maker, 'testfile4', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':0, 'self_loop':1, 'multigraph':0}) 35 >>> gexf4 = read_gexf("testfile4.gexf") >>> type(gexf4) >>> random.seed(120) >>> engine.gen_using(gexf_maker, 'testfile5', {'min_weight':0, 'max_weight':50.2, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':0, 'self_loop':1, 'multigraph':0}) 40 >>> gexf5 = read_gexf("testfile5.gexf") >>> type(gexf5) >>> #################### dot_maker #################### >>> import pydot >>> random.seed(2) >>> engine.gen_using(dot_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 7 >>> file=open('testfile.gv','r') >>> g1 = pydot.graph_from_dot_data(file.read()) >>> g1[0].get_type() 'digraph' >>> len(g1[0].get_edge_list()) 7 >>> random.seed(4) >>> engine.gen_using(dot_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':1, 'direct':1, 'self_loop':1, 'multigraph':0}) 35 >>> file=open('testfile2.gv','r') >>> g2 = pydot.graph_from_dot_data(file.read()) >>> g2[0].get_type() 'digraph' >>> len(g2[0].get_edge_list()) 35 >>> random.seed(20) >>> engine.gen_using(dot_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':0, 'direct':0, 'self_loop':1, 'multigraph':1}) 131 >>> file=open('testfile3.gv','r') >>> g3 = pydot.graph_from_dot_data(file.read()) >>> g3[0].get_type() 'graph' >>> len(g3[0].get_edge_list()) 131 >>> file.close() >>> os.remove('testfile.gr') >>> os.remove('testfile2.gr') >>> os.remove('testfile3.gr') >>> os.remove('testfile4.gr') >>> os.remove('testfile.json') >>> os.remove('testfile2.json') >>> os.remove('testfile3.json') >>> os.remove('testfile.csv') >>> os.remove('testfile2.csv') >>> os.remove('testfile3.csv') >>> os.remove('testfile4.csv') >>> os.remove('testfile.gdf') >>> os.remove('testfile2.gdf') >>> os.remove('testfile3.gdf') >>> os.remove('testfile.gl') >>> os.remove('testfile2.gl') >>> os.remove('testfile3.gl') >>> os.remove('testfile.mtx') >>> os.remove('testfile2.mtx') >>> os.remove('testfile3.mtx') >>> os.remove('testfile.tsv') >>> os.remove('testfile2.tsv') >>> os.remove('testfile3.tsv') >>> os.remove('testfile.wel') >>> os.remove('testfile2.wel') >>> os.remove('testfile3.wel') >>> os.remove('testfile.lp') >>> os.remove('testfile2.lp') >>> os.remove('testfile.tgf') >>> os.remove('testfile2.tgf') >>> os.remove('testfile.dl') >>> os.remove('testfile2.dl') >>> os.remove('testfile.gml') >>> os.remove('testfile2.gml') >>> os.remove('testfile3.gml') >>> os.remove('testfile4.gml') >>> os.remove('testfile.gexf') >>> os.remove('testfile2.gexf') >>> os.remove('testfile3.gexf') >>> os.remove('testfile4.gexf') >>> os.remove('testfile5.gexf') >>> os.remove('testfile.gv') >>> os.remove('testfile2.gv') >>> os.remove('testfile3.gv') >>> os.remove('logfile.log') """ pyrgg-1.6/test/functions_test.py000066400000000000000000000375231471451651000171260ustar00rootroot00000000000000# -*- coding: utf-8 -*- """ >>> from pyrgg.functions import * >>> import pyrgg.params >>> import random >>> import os >>> os.environ["PYRGG_TEST_MODE"] = "1" >>> description_print() Webpage : https://www.pyrgg.site Repository : https://github.com/sepandhaghighi/pyrgg Paper : https://doi.org/10.21105/joss.00331 * If you use PyRGG in your research, please cite our paper ######################################## PyRGG is a user-friendly synthetic random graph generator that is written in Python and supports multiple graph file formats, such as DIMACS-Graph files. It can generate graphs of various sizes and is specifically designed to create input files for a wide range of graph-based research applications, including testing, benchmarking, and performance analysis of graph processing frameworks. PyRGG is aimed at computer scientists who are studying graph algorithms and graph processing frameworks. ######################################## >>> result = input_filter({"file_name": "test","vertices": 5,"max_weight": 1000,"min_weight":455,"min_edge": -45,"max_edge": -11,"sign": False,"output_format": 1, "direct": False,"self_loop": True,"multigraph":False,"number_of_files":2,"engine":1}) >>> result == {'output_format': 1, 'min_weight': 455, 'min_edge': 5, 'max_edge': 5, 'file_name': 'test', 'vertices': 5, 'max_weight': 1000, 'sign': False, "direct": False,"self_loop": True,"multigraph":False,"number_of_files":2,"engine":1} True >>> result = input_filter({"file_name": "test","vertices": 5,"max_weight": 1000,"min_weight":455,"min_edge": -45,"max_edge": -11,"sign": False,"output_format": 1, "direct": False,"self_loop": False,"multigraph":False,"number_of_files":10,"engine":1}) >>> result == {'output_format': 1, 'min_weight': 455, 'min_edge': 4, 'max_edge': 4, 'file_name': 'test', 'vertices': 5, 'max_weight': 1000, 'sign': False, "direct": False,"self_loop": False,"multigraph":False,"number_of_files":10,"engine":1} True >>> result = input_filter({"file_name": "test","vertices": -5,"max_weight": 1000,"min_weight":455,"min_edge": -45,"max_edge": -11,"sign": False,"output_format": 1, "direct": False,"self_loop": False,"multigraph":True,"number_of_files":1,"engine":1}) >>> result == {'output_format': 1, 'min_weight': 455, 'min_edge': 11, 'max_edge': 45, 'file_name': 'test', 'vertices': 5, 'max_weight': 1000, 'sign': False, "direct": False,"self_loop": False,"multigraph":True,"number_of_files":1,"engine":1} True >>> result = input_filter({"file_name": "test","vertices": -5,"max_weight": 1000,"min_weight":455,"min_edge": -45,"max_edge": -11,"sign": False,"output_format": 1, "direct": False,"self_loop": False,"multigraph":True,"number_of_files":1,"engine":1}) >>> result == {'output_format': 1, 'min_weight': 455, 'min_edge': 11, 'max_edge': 45, 'file_name': 'test', 'vertices': 5, 'max_weight': 1000, 'sign': False, "direct": False,"self_loop": False,"multigraph":True,"number_of_files":1,"engine":1} True >>> result = input_filter({"file_name": "test2","vertices": 23,"max_weight": 2,"min_weight": 80,"min_edge": 23,"max_edge": 1,"sign": True,"output_format": 1, "direct": False,"self_loop": True,"multigraph":False,"number_of_files":2,"engine":1}) >>> result == {'min_weight': 2, 'vertices': 23, 'file_name': 'test2', 'max_edge': 23, 'min_edge': 1, 'max_weight': 80, 'output_format': 1, 'sign': True, "direct": False,"self_loop": True,"multigraph":False,"number_of_files":2,"engine":1} True >>> convert_bytes(200) '200.0 bytes' >>> convert_bytes(6000) '5.9 KB' >>> convert_bytes(80000) '78.1 KB' >>> time_convert(33) '00 days, 00 hours, 00 minutes, 33 seconds' >>> time_convert(15000) '00 days, 04 hours, 10 minutes, 00 seconds' >>> time_convert(1) '00 days, 00 hours, 00 minutes, 01 second' >>> time_convert(60) '00 days, 00 hours, 01 minute, 00 seconds' >>> time_convert(60*60) '00 days, 01 hour, 00 minutes, 00 seconds' >>> time_convert(60*60*24) '01 day, 00 hours, 00 minutes, 00 seconds' >>> time_convert(60*60*24 + 60*60 + 60 + 1) '01 day, 01 hour, 01 minute, 01 second' >>> time_convert(0) '00 days, 00 hours, 00 minutes, 00 seconds' >>> time_convert('sadasdasd') Traceback (most recent call last): ... ValueError: could not convert string to float: 'sadasdasd' >>> line(12,"*") ************ >>> is_weighted(0,0,False) False >>> is_weighted(0,0,True) False >>> is_weighted(20,20,False) True >>> is_weighted(1,1,False) False >>> is_weighted(1,1,True) True >>> get_precision(2) 0 >>> get_precision(2.2) 1 >>> get_precision(2.22) 2 >>> get_precision(2.223) 3 >>> handle_str_to_number("20") 20 >>> handle_str_to_number("20.2") 20.2 >>> handle_str_to_bool("1") True >>> handle_str_to_bool("3") Traceback (most recent call last): ... ValueError >>> handle_str_to_bool("0") False >>> handle_str_prob("0.2") 0.2 >>> handle_str_prob("-0.2") Traceback (most recent call last): ... ValueError >>> handle_str_prob("1.2") Traceback (most recent call last): ... ValueError >>> is_float(10) False >>> is_float(10.2) True >>> is_float(None) False >>> prev_item = "" >>> input_func_dict = {"vertices":"120","max_weight":"110","min_weight":"0","min_edge":"1","max_edge":"1000","sign":"1","direct":"1","self_loop":"1","multigraph":"0","file_name":"File 1","output_format":"2","weight":"1","error":"120","number_of_files":"3","config":"0","engine":"1"} >>> def input_func_test(input_data): ... global prev_item ... for index in pyrgg.params.MENU_ITEMS: ... item1, item2 = pyrgg.params.MENU_ITEMS[index] ... if input_data == item2: ... if item1 != prev_item: ... prev_item = item1 ... return input_func_dict[item1] ... else: ... return input_func_dict["error"] ... for index in pyrgg.params.PYRGG_ENGINE_PARAMS: ... item1, item2 = pyrgg.params.PYRGG_ENGINE_PARAMS[index] ... if input_data == item2: ... if item1 != prev_item : ... prev_item = item1 ... return input_func_dict[item1] ... else: ... return input_func_dict["error"] ... for index in pyrgg.params.ERG_ENGINE_PARAMS: ... item1, item2 = pyrgg.params.ERG_ENGINE_PARAMS[index] ... if input_data == item2: ... if item1 != prev_item : ... prev_item = item1 ... return input_func_dict[item1] ... else: ... return input_func_dict["error"] ... for index in pyrgg.params.ER_ENGINE_PARAMS: ... item1, item2 = pyrgg.params.ER_ENGINE_PARAMS[index] ... if input_data == item2: ... if item1 != prev_item : ... prev_item = item1 ... return input_func_dict[item1] ... else: ... return input_func_dict["error"] >>> def input_func_conf_test1(input_data): ... return "1" >>> def input_func_conf_test2(input_data): ... return "2" >>> input_data = get_input(input_func_test) >>> input_data["vertices"] 120 >>> input_data["max_weight"] 110 >>> input_data["min_weight"] 0 >>> input_data["min_edge"] 1 >>> input_data["max_edge"] 120 >>> input_data["number_of_files"] 3 >>> input_data["sign"] True >>> input_data["weight"] True >>> input_data["engine"] 1 >>> prev_item = "" >>> input_func_dict = {"vertices":"120","max_weight":"110","min_weight":"1.2","min_edge":"10000","max_edge":"2","sign":"1","direct":"1","self_loop":"1","multigraph":"0","file_name":"File 1","output_format":"2","weight":"1","error":"120","number_of_files":"1","config":"1","engine":"1"} >>> input_data = get_input(input_func_test) >>> input_data["vertices"] 120 >>> input_data["max_weight"] 110 >>> input_data["number_of_files"] 1 >>> input_data["min_weight"] 1.2 >>> input_data["min_edge"] 2 >>> input_data["max_edge"] 120 >>> input_data["sign"] True >>> input_data["weight"] True >>> input_data["engine"] 1 >>> loaded_config = check_for_config(input_func_conf_test1) >>> input_data["config"] True >>> input_data_ = input_data.copy() >>> config_path = save_config(input_data) >>> loaded_config = load_config(config_path) >>> loaded_config["vertices"] == input_data_["vertices"] True >>> loaded_config["number_of_files"] == input_data_["number_of_files"] True >>> loaded_config["output_format"] == input_data_["output_format"] True >>> save_config("test") [Error] Failed to save config file! >>> load_config("test123456789") [Error] Failed to load config file! >>> loaded_config = check_for_config(input_func_conf_test1) Config files detected in the current directory are listed below: [1] - ... >>> loaded_config["vertices"] == input_data_["vertices"] True >>> loaded_config["number_of_files"] == input_data_["number_of_files"] True >>> loaded_config["output_format"] == input_data_["output_format"] True >>> loaded_config = check_for_config(input_func_conf_test2) Config files detected in the current directory are listed below: [1] - ... >>> loaded_config == None True >>> input_func_dict = {"vertices":"120","max_weight":"110.45","min_weight":"test","min_edge":"10000","max_edge":"2","sign":"1","direct":"1","self_loop":"0","multigraph":"0","file_name":"File 2","output_format":"1","weight":"0","number_of_files":"1","error":"120","config":"0","engine":"1"} >>> input_data = get_input(input_func_test) >>> input_data["vertices"] 120 >>> input_data["min_weight"] 1 >>> input_data["max_edge"] 119 >>> input_data["max_weight"] 1 >>> input_data["weight"] False >>> input_data["sign"] True >>> input_data["direct"] True >>> input_data["multigraph"] False >>> prev_item = "" >>> input_func_dict = {"vertices":"wrong vertices","max_weight":"110.45","min_weight":"2","min_edge":"10000","max_edge":"2","sign":"1","direct":"1","self_loop":"1","multigraph":"1","file_name":"File 2","output_format":"1","weight":"1","error":"1200","number_of_files":"2","config":"0","engine":"1"} >>> input_data = get_input(input_func_test) [Error] Bad input! >>> input_data["vertices"] 1200 >>> prev_item = "" >>> input_func_dict = {"vertices":"1200","max_weight":"wrong max_weight","min_weight":"2","min_edge":"10000","max_edge":"2","sign":"1","direct":"1","self_loop":"1","multigraph":"1","file_name":"File 2","output_format":"1","weight":"1","error":"400","number_of_files":"2","config":"0","engine":"1"} >>> input_data = get_input(input_func_test) [Error] Bad input! >>> input_data["max_weight"] 400 >>> prev_item = "" >>> input_func_dict = {"vertices":"1200","max_weight":"400","min_weight":"wrong min_weight","min_edge":"10000","max_edge":"2","sign":"1","direct":"1","self_loop":"1","multigraph":"1","file_name":"File 2","output_format":"1","weight":"1","error":"2","number_of_files":"2","config":"0","engine":"1"} >>> input_data = get_input(input_func_test) [Error] Bad input! >>> input_data["min_weight"] 2 >>> prev_item = "" >>> input_func_dict = {"vertices":"1200","max_weight":"400","min_weight":"2","min_edge":"wrong min_edge","max_edge":"2","sign":"1","direct":"1","self_loop":"1","multigraph":"1","file_name":"File 2","output_format":"1","weight":"1","error":"0","number_of_files":"2","config":"0","engine":"1"} >>> input_data = get_input(input_func_test) [Error] Bad input! >>> input_data["min_edge"] 0 >>> prev_item = "" >>> input_func_dict = {"vertices":"1200","max_weight":"400","min_weight":"2","min_edge":"0","max_edge":"wrong max_edge","sign":"1","direct":"1","self_loop":"1","multigraph":"1","file_name":"File 2","output_format":"1","weight":"1","error":"2000","number_of_files":"2","config":"0","engine":"1"} >>> input_data = get_input(input_func_test) [Error] Bad input! >>> input_data["max_edge"] 2000 >>> prev_item = "" >>> input_func_dict = {"vertices":"1200","max_weight":"400","min_weight":"2","min_edge":"0","max_edge":"2000","sign":"400","direct":"1","self_loop":"1","multigraph":"1","file_name":"File 2","output_format":"1","weight":"1","error":"1","number_of_files":"2","config":"0","engine":"1"} >>> input_data = get_input(input_func_test) [Error] Bad input! >>> input_data["sign"] True >>> prev_item = "" >>> input_func_dict = {"vertices":"1200","max_weight":"400","min_weight":"2","min_edge":"0","max_edge":"2000","sign":"1","direct":"4000","self_loop":"1","multigraph":"1","file_name":"File 2","output_format":"1","weight":"1","error":"1","number_of_files":"2","config":"0","engine":"1"} >>> input_data = get_input(input_func_test) [Error] Bad input! >>> input_data["direct"] True >>> prev_item = "" >>> input_func_dict = {"vertices":"1200","max_weight":"400","min_weight":"2","min_edge":"0","max_edge":"2000","sign":"1","direct":"1","self_loop":"4000","multigraph":"1","file_name":"File 2","output_format":"1","weight":"1","error":"0","number_of_files":"2","config":"0","engine":"1"} >>> input_data = get_input(input_func_test) [Error] Bad input! >>> input_data["self_loop"] False >>> prev_item = "" >>> input_func_dict = {"vertices":"1200","max_weight":"400","min_weight":"2","min_edge":"0","max_edge":"2000","sign":"1","direct":"1","self_loop":"0","multigraph":"40000","file_name":"File 2","output_format":"1","weight":"1","error":"0","number_of_files":"2","config":"0","engine":"1"} >>> input_data = get_input(input_func_test) [Error] Bad input! >>> input_data["multigraph"] False >>> prev_item = "" >>> input_func_dict = {"vertices":"1200","max_weight":"400","min_weight":"2","min_edge":"0","max_edge":"2000","sign":"1","direct":"1","self_loop":"0","multigraph":"0","file_name":"","output_format":"1","weight":"1","error":"file1","number_of_files":"2","config":"0","engine":"1"} >>> input_data = get_input(input_func_test) [Error] Bad input! >>> input_data["file_name"] 'file1' >>> prev_item = "" >>> input_func_dict = {"vertices":"1200","max_weight":"400","min_weight":"2","min_edge":"0","max_edge":"2000","sign":"1","direct":"1","self_loop":"0","multigraph":"0","file_name":"file1","output_format":"4000","weight":"1","error":"1","number_of_files":"2","config":"0","engine":"1"} >>> input_data = get_input(input_func_test) [Error] Bad input! >>> input_data["output_format"] 1 >>> prev_item = "" >>> input_func_dict = {"vertices":"1200","max_weight":"400","min_weight":"2","min_edge":"0","max_edge":"2000","sign":"1","direct":"1","self_loop":"0","multigraph":"0","file_name":"file1","output_format":"1","weight":"4000","error":"0","number_of_files":"2","config":"0","engine":"1"} >>> input_data = get_input(input_func_test) [Error] Bad input! >>> input_data["weight"] False >>> prev_item = "" >>> input_func_dict = {"vertices":"1200","max_weight":"400","min_weight":"2","min_edge":"0","max_edge":"2000","sign":"1","direct":"1","self_loop":"0","multigraph":"0","file_name":"file1","output_format":"1","weight":"0","error":"1","number_of_files":"-5","config":"0","engine":"1"} >>> input_data = get_input(input_func_test) [Error] Bad input! >>> input_data["number_of_files"] 1 >>> prev_item = "" >>> input_func_dict = {"vertices":"1200","max_weight":"400","min_weight":"2","min_edge":"0","max_edge":"2000","sign":"1","direct":"1","self_loop":"0","multigraph":"0","file_name":"file1","output_format":"1","weight":"0","error":"0","number_of_files":"1","config":"4000","engine":"1"} >>> input_data = get_input(input_func_test) [Error] Bad input! >>> input_data["config"] False >>> prev_item = "" >>> input_func_dict = {"vertices":"1200","max_weight":"400","min_weight":"2","min_edge":"0","max_edge":"2000","sign":"1","direct":"1","self_loop":"0","multigraph":"0","file_name":"file1","output_format":"1","weight":"0","error":"1","number_of_files":"1","config":"0","engine":"100000"} >>> input_data = get_input(input_func_test) [Error] Bad input! >>> input_data["engine"] 1 >>> handle_string("2") '2' >>> handle_string("") Traceback (most recent call last): ... ValueError >>> handle_pos_int(1) 1 >>> handle_pos_int(-1) Traceback (most recent call last): ... ValueError >>> handle_output_format("1") 1 >>> handle_output_format("-14") Traceback (most recent call last): ... ValueError >>> handle_output_format("10000000000") Traceback (most recent call last): ... ValueError >>> handle_engine("1") 1 >>> handle_engine(-4) Traceback (most recent call last): ... ValueError >>> handle_engine("10000000000") Traceback (most recent call last): ... ValueError >>> os.remove('File 1.pyrgg.config.json') """ pyrgg-1.6/test/graph_gen_test.py000066400000000000000000000114111471451651000170340ustar00rootroot00000000000000# -*- coding: utf-8 -*- """ >>> from pyrgg import * >>> import pyrgg.params >>> import pyrgg.engines.pyrgg as engine >>> import random >>> import os >>> import json >>> import yaml >>> import pickle >>> os.environ["PYRGG_TEST_MODE"] = "1" >>> dimacs_maker({}, {}) Traceback (most recent call last): ... TypeError: dimacs_maker() missing 1 required positional argument: 'mdata' >>> random.seed(2) >>> engine.gen_using(json_maker, 'testfile', {'min_weight':0, 'max_weight':200, 'vertices':10, 'min_edge':0, 'max_edge':2, 'sign':True, 'direct':True, 'self_loop':True, 'multigraph':False}) 7 >>> json_to_yaml('testfile') >>> file=open('testfile.yaml','r') >>> testfile_1_yaml=yaml.safe_load(file) >>> testfile_1_yaml['graph']['edges'][1]['source'] 5 >>> testfile_1_yaml['graph']['edges'][1]['target'] 6 >>> testfile_1_yaml['graph']['edges'][1]['weight'] 148 >>> testfile_1_yaml['properties']['directed'] True >>> testfile_1_yaml['properties']['multigraph'] False >>> testfile_1_yaml['properties']['weighted'] True >>> json_to_pickle('testfile') >>> testfile_1_p=pickle.load( open( 'testfile.p', 'rb' ) ) >>> testfile_1_p['graph']['edges'][1]['source'] 5 >>> testfile_1_p['graph']['edges'][1]['target'] 6 >>> testfile_1_p['graph']['edges'][1]['weight'] 148 >>> testfile_1_p['properties']['directed'] True >>> testfile_1_p['properties']['multigraph'] False >>> testfile_1_p['properties']['weighted'] True >>> random.seed(4) >>> engine.gen_using(json_maker, 'testfile2', {'min_weight':0, 'max_weight':50, 'vertices':30, 'min_edge':0, 'max_edge':4, 'sign':True, 'direct':True, 'self_loop':True, 'multigraph':False}) 35 >>> json_to_yaml('testfile2') >>> file=open('testfile2.yaml','r') >>> testfile_2_yaml=yaml.safe_load(file) >>> testfile_2_yaml['graph']['nodes'][1] {'id': 2} >>> testfile_2_yaml['graph']['edges'][1]['source'] 2 >>> testfile_2_yaml['graph']['edges'][1]['target'] 18 >>> testfile_2_yaml['graph']['edges'][1]['weight'] 5 >>> testfile_2_yaml['properties']['directed'] True >>> testfile_2_yaml['properties']['multigraph'] False >>> testfile_2_yaml['properties']['weighted'] True >>> json_to_pickle('testfile2') >>> testfile_2_p=pickle.load( open( 'testfile2.p', 'rb' ) ) >>> testfile_2_p['graph']['edges'][1]['source'] 2 >>> testfile_2_p['graph']['edges'][1]['target'] 18 >>> testfile_2_p['graph']['edges'][1]['weight'] 5 >>> testfile_2_p['properties']['directed'] True >>> testfile_2_p['properties']['multigraph'] False >>> testfile_2_p['properties']['weighted'] True >>> random.seed(20) >>> engine.gen_using(json_maker, 'testfile3', {'min_weight':10, 'max_weight':30, 'vertices':100, 'min_edge':0, 'max_edge':4, 'sign':False, 'direct':True, 'self_loop':True, 'multigraph':False}) 137 >>> json_to_yaml('testfile3') >>> file=open('testfile3.yaml','r') >>> testfile_3_yaml=yaml.safe_load(file) >>> testfile_3_yaml['graph']['nodes'][1] {'id': 2} >>> testfile_3_yaml['graph']['edges'][1]['source'] 3 >>> testfile_3_yaml['graph']['edges'][1]['target'] 76 >>> testfile_3_yaml['graph']['edges'][1]['weight'] 15 >>> testfile_3_yaml['properties']['directed'] True >>> testfile_3_yaml['properties']['multigraph'] False >>> testfile_3_yaml['properties']['weighted'] True >>> json_to_yaml('testfile24') [Error] Failed to generate YAML file! >>> json_to_pickle('testfile24') [Error] Failed to generate Pickle file! >>> json_maker({}, {}) Traceback (most recent call last): ... TypeError: json_maker() missing 1 required positional argument: 'mdata' >>> json_to_pickle('testfile3') >>> testfile_3_p=pickle.load( open( 'testfile3.p', 'rb' ) ) >>> testfile_3_p['graph']['edges'][1]['source'] 3 >>> testfile_3_p['graph']['edges'][1]['target'] 76 >>> testfile_3_p['graph']['edges'][1]['weight'] 15 >>> testfile_3_p['properties']['directed'] True >>> testfile_3_p['properties']['multigraph'] False >>> testfile_3_p['properties']['weighted'] True >>> gl_maker({}) Traceback (most recent call last): ... TypeError: gl_maker() missing 2 required positional arguments: 'weight_dic' and 'mdata' >>> csv_maker({}, {}) Traceback (most recent call last): ... TypeError: csv_maker() missing 1 required positional argument: 'mdata' >>> gdf_maker({}) Traceback (most recent call last): ... TypeError: gdf_maker() missing 2 required positional arguments: 'weight_dic' and 'mdata' >>> tsv_maker({}, {}) Traceback (most recent call last): ... TypeError: tsv_maker() missing 1 required positional argument: 'mdata' >>> wel_maker({}, {}) Traceback (most recent call last): ... TypeError: wel_maker() missing 1 required positional argument: 'mdata' >>> file.close() >>> os.remove('testfile.json') >>> os.remove('testfile.p') >>> os.remove('testfile.yaml') >>> os.remove('testfile2.json') >>> os.remove('testfile2.p') >>> os.remove('testfile2.yaml') >>> os.remove('testfile3.json') >>> os.remove('testfile3.p') >>> os.remove('testfile3.yaml') """ pyrgg-1.6/tox.ini000066400000000000000000000003121471451651000140230ustar00rootroot00000000000000[tox] envlist = py35,py36,py37,py38,flake8 [testenv] deps = -r dev-requirements.txt commands = pytest --cov=pyrgg/ test/ [testenv:flake8] deps = -r dev-requirements.txt commands = flake8 pyrgg/ test/