pax_global_header00006660000000000000000000000064147574034460014530gustar00rootroot0000000000000052 comment=8db0b3812e2032544c1fc00d02d4256cab043f3d mir_eval-0.8.2/000077500000000000000000000000001475740344600133355ustar00rootroot00000000000000mir_eval-0.8.2/.codespell_ignore_list000066400000000000000000000000321475740344600177010ustar00rootroot00000000000000nce fpr shepard dum theis mir_eval-0.8.2/.github/000077500000000000000000000000001475740344600146755ustar00rootroot00000000000000mir_eval-0.8.2/.github/environment-docs.yml000066400000000000000000000002251475740344600207110ustar00rootroot00000000000000name: docs channels: - conda-forge - defaults dependencies: - pip - numpy >=1.15.4 - scipy >=1.4.0 - matplotlib-base>=3.3.0 - numpydoc mir_eval-0.8.2/.github/environment-lint.yml000066400000000000000000000004021475740344600207240ustar00rootroot00000000000000name: lint channels: - conda-forge - defaults dependencies: # required - pip - bandit - codespell - flake8 - pytest - pydocstyle # Dependencies for velin - numpydoc>=1.1.0 - sphinx>=5.1.0 - pygments - black - pip: - velin mir_eval-0.8.2/.github/environment-minimal.yml000066400000000000000000000002611475740344600214070ustar00rootroot00000000000000name: test channels: - conda-forge - defaults dependencies: - pip - numpy ==1.15.4 - scipy ==1.4.0 - matplotlib-base==3.3.0 - pytest - pytest-cov - pytest-mpl mir_eval-0.8.2/.github/environment.yml000066400000000000000000000002611475740344600177630ustar00rootroot00000000000000name: test channels: - conda-forge - defaults dependencies: - pip - numpy >=1.15.4 - scipy >=1.4.0 - matplotlib-base>=3.3.0 - pytest - pytest-cov - pytest-mpl mir_eval-0.8.2/.github/workflows/000077500000000000000000000000001475740344600167325ustar00rootroot00000000000000mir_eval-0.8.2/.github/workflows/docs-ci.yml000066400000000000000000000041031475740344600207740ustar00rootroot00000000000000name: CI Docs on: push: branches: - main pull_request: branches: - main concurrency: group: ${{ github.workflow }}-${{ github.ref }} cancel-in-progress: True jobs: setup: name: "Doc environment setup" runs-on: ${{ matrix.os }} strategy: fail-fast: true matrix: include: - os: ubuntu-latest python-version: "3.8" channel-priority: "flexible" envfile: ".github/environment-docs.yml" steps: - uses: actions/checkout@v4 with: fetch-depth: 0 - name: Cache conda uses: actions/cache@v4 env: # Increase this value to reset cache if etc/example-environment.yml has not changed CACHE_NUMBER: 0 with: path: ~/conda_pkgs_dir key: ${{ runner.os }}-${{ matrix.python-version }}-conda-${{ env.CACHE_NUMBER }}-${{ hashFiles( matrix.envfile ) }} - name: Install Conda environment uses: conda-incubator/setup-miniconda@v3 with: auto-update-conda: false python-version: ${{ matrix.python-version }} add-pip-as-python-dependency: true auto-activate-base: false activate-environment: docs channel-priority: ${{ matrix.channel-priority }} environment-file: ${{ matrix.envfile }} use-only-tar-bz2: false # IMPORTANT: This needs to be set for caching to work properly! - name: Conda info shell: bash -l {0} run: | conda info -a conda list - name: Install mir_eval shell: bash -l {0} run: python -m pip install --upgrade-strategy only-if-needed -e .[docs] - name: Build docs shell: bash -l {0} working-directory: docs run: make html - name: Link checking id: linkcheck shell: bash -l {0} working-directory: docs run: make linkcheck mir_eval-0.8.2/.github/workflows/lint_python.yml000066400000000000000000000036761475740344600220400ustar00rootroot00000000000000name: lint_python on: [pull_request, push] jobs: lint_python: name: "Lint and code analysis" runs-on: ubuntu-latest strategy: fail-fast: true matrix: include: - os: ubuntu-latest python-version: "3.11" channel-priority: "flexible" envfile: ".github/environment-lint.yml" steps: - uses: actions/checkout@v4 with: fetch-depth: 0 - name: Cache conda uses: actions/cache@v4 env: CACHE_NUMBER: 0 with: path: ~/conda_pkgs_dir key: ${{ runner.os }}-${{ matrix.python-version }}-conda-${{ env.CACHE_NUMBER }}-${{ hashFiles( matrix.envfile ) }} - name: Install conda environmnent uses: conda-incubator/setup-miniconda@v3 with: auto-update-conda: false python-version: ${{ matrix.python-version }} add-pip-as-python-dependency: true auto-activate-base: false activate-environment: lint # mamba-version: "*" channel-priority: ${{ matrix.channel-priority }} environment-file: ${{ matrix.envfile }} use-only-tar-bz2: false - name: Conda info shell: bash -l {0} run: | conda info -a conda list - name: Spell check package shell: bash -l {0} run: codespell --ignore-words .codespell_ignore_list mir_eval - name: Security check shell: bash -l {0} run: bandit --recursive --skip B101,B110 . - name: Style check package shell: bash -l {0} run: python -m flake8 mir_eval - name: Format check package shell: bash -l {0} run: python -m black --check mir_eval - name: Format check tests shell: bash -l {0} run: python -m black --check tests - name: Docstring check shell: bash -l {0} run: python -m velin --check mir_eval - name: Docstring style check shell: bash -l {0} run: python -m pydocstyle mir_eval mir_eval-0.8.2/.github/workflows/release.yml000066400000000000000000000016471475740344600211050ustar00rootroot00000000000000name: Publish Python 🐍 distributions 📦 to PyPI on: release: types: [created] jobs: pypi-publish: name: Upload release to PyPI runs-on: ubuntu-latest environment: name: pypi url: https://pypi.org/p/mir_eval permissions: id-token: write # IMPORTANT: this permission is mandatory for trusted publishing steps: - uses: actions/checkout@v4 - name: Set up Python 3.12 uses: actions/setup-python@v5 with: python-version: 3.12 - name: Install pypa/build run: >- python -m pip install build --user - name: Build a binary wheel and a source tarball run: >- python -m build --sdist --wheel --outdir dist/ . - name: Publish package distributions to PyPI if: startsWith(github.ref, 'refs/tags') uses: pypa/gh-action-pypi-publish@release/v1 mir_eval-0.8.2/.github/workflows/test.yml000066400000000000000000000052631475740344600204420ustar00rootroot00000000000000name: Test Python code on: pull_request: branches: - main push: branches: - main concurrency: group: ${{ github.workflow }}-${{ github.ref }} cancel-in-progress: True jobs: test: strategy: fail-fast: false matrix: os: [ubuntu-latest] python-version: ["3.8", "3.10", "3.11", "3.12"] channel-priority: [strict] envfile: [".github/environment.yml"] include: - python-version: "3.13" os: macos-latest - python-version: "3.13" os: windows-latest - python-version: "3.13" os: ubuntu-latest channel-priority: flexible - os: ubuntu-latest python-version: "3.7" envfile: ".github/environment-minimal.yml" channel-priority: "flexible" name: "Minimal dependencies" runs-on: ${{ matrix.os }} steps: - uses: actions/checkout@v4 - name: Cache conda packages uses: actions/cache@v4 with: path: ~/conda_pkgs_dir key: ${{ runner.os }}-${{ matrix.python-version }}-${{ hashFiles( matrix.envfile ) }} - name: Create conda environment uses: conda-incubator/setup-miniconda@v3 with: python-version: ${{ matrix.python-version }} auto-activate-base: false channel-priority: ${{ matrix.channel-priority }} environment-file: ${{ matrix.envfile }} # Disabling bz2 to get more recent dependencies. # NOTE: this breaks cache support, so CI will be slower. use-only-tar-bz2: False # IMPORTANT: This needs to be set for caching to work properly! - name: Install package in development mode shell: bash -l {0} run: python -m pip install --upgrade-strategy=only-if-needed -e .[display,tests] - name: Log installed packages for debugging shell: bash -l {0} run: | conda info -a conda list - name: Show libraries in the system on which NumPy was built shell: bash -l {0} run: python -c "import numpy; numpy.show_config()" - name: Show libraries in the system on which SciPy was built shell: bash -l {0} run: python -c "import scipy; scipy.show_config()" - name: Run unit tests shell: bash -l {0} run: pytest working-directory: tests - name: Upload coverage to Codecov uses: codecov/codecov-action@v5 with: token: ${{ secrets.CODECOV_TOKEN }} files: ./coverage.xml flags: unittests env_vars: OS,PYTHON name: codecov-umbrella fail_ci_if_error: true verbose: true mir_eval-0.8.2/.gitignore000066400000000000000000000007021475740344600153240ustar00rootroot00000000000000*.py[co] # Packages *.egg *.egg-info dist build eggs parts bin var sdist develop-eggs .installed.cfg # Installer logs pip-log.txt # Unit test / coverage reports .coverage .tox #Translations *.mo #Mr Developer .mr.developer.cfg # OS generated files # .DS_Store .DS_Store? ._* .Spotlight-V100 .Trashes ehthumbs.db Thumbs.db # Vim *.swp # pycharm .idea/* # docs docs/_build/* # matplotlib tests tests/result_images/* # coverage coverage.xml mir_eval-0.8.2/.readthedocs.yaml000066400000000000000000000011541475740344600165650ustar00rootroot00000000000000# Read the Docs configuration file # See https://docs.readthedocs.io/en/stable/config-file/v2.html for details # Required version: 2 # Set the OS, Python version, and other tools you might need build: os: ubuntu-24.04 tools: python: "3.12" # Build documentation in the "docs/" directory with Sphinx sphinx: configuration: docs/conf.py # Optionally, but recommended, # declare the Python requirements required to build your documentation # See https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html python: install: - method: pip path: . extra_requirements: - docs mir_eval-0.8.2/LICENSE.txt000066400000000000000000000020671475740344600151650ustar00rootroot00000000000000The MIT License (MIT) Copyright (c) 2014 Colin Raffel Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. mir_eval-0.8.2/README.rst000066400000000000000000000026751475740344600150360ustar00rootroot00000000000000.. image:: https://anaconda.org/conda-forge/mir_eval/badges/version.svg :target: https://anaconda.org/conda-forge/mir_eval .. image:: https://img.shields.io/pypi/v/mir_eval.svg :target: https://pypi.python.org/pypi/mir_eval .. image:: https://github.com/mir-evaluation/mir_eval/actions/workflows/test.yml/badge.svg :target: https://github.com/mir-evaluation/mir_eval/actions/workflows/test.yml .. image:: https://codecov.io/gh/mir-evaluation/mir_eval/graph/badge.svg?token=OzRL3aW7TX :target: https://codecov.io/gh/mir-evaluation/mir_eval .. image:: https://img.shields.io/pypi/l/mir_eval.svg :target: https://github.com/mir-evaluation/mir_eval/blob/main/LICENSE.txt mir_eval ======== Python library for computing common heuristic accuracy scores for various music/audio information retrieval/signal processing tasks. Documentation, including installation and usage information: https://mir-evaluation.github.io/mir_eval/ Dependencies: * `Scipy/Numpy `_ * `decorator `_ If you use mir_eval in a research project, please cite the following paper: Colin Raffel, Brian McFee, Eric J. Humphrey, Justin Salamon, Oriol Nieto, Dawen Liang, and Daniel P. W. Ellis, "`mir_eval: A Transparent Implementation of Common MIR Metrics `_", Proceedings of the 15th International Conference on Music Information Retrieval, 2014. mir_eval-0.8.2/docs/000077500000000000000000000000001475740344600142655ustar00rootroot00000000000000mir_eval-0.8.2/docs/Makefile000066400000000000000000000151621475740344600157320ustar00rootroot00000000000000# Makefile for Sphinx documentation # # You can set these variables from the command line. SPHINXOPTS = SPHINXBUILD = sphinx-build PAPER = BUILDDIR = _build # User-friendly check for sphinx-build ifeq ($(shell which $(SPHINXBUILD) >/dev/null 2>&1; echo $$?), 1) $(error The '$(SPHINXBUILD)' command was not found. Make sure you have Sphinx installed, then set the SPHINXBUILD environment variable to point to the full path of the '$(SPHINXBUILD)' executable. Alternatively you can add the directory with the executable to your PATH. If you don't have Sphinx installed, grab it from http://sphinx-doc.org/) endif # Internal variables. PAPEROPT_a4 = -D latex_paper_size=a4 PAPEROPT_letter = -D latex_paper_size=letter ALLSPHINXOPTS = -d $(BUILDDIR)/doctrees $(PAPEROPT_$(PAPER)) $(SPHINXOPTS) . # the i18n builder cannot share the environment and doctrees with the others I18NSPHINXOPTS = $(PAPEROPT_$(PAPER)) $(SPHINXOPTS) . .PHONY: help clean html dirhtml singlehtml pickle json htmlhelp qthelp devhelp epub latex latexpdf text man changes linkcheck doctest gettext help: @echo "Please use \`make ' where is one of" @echo " html to make standalone HTML files" @echo " dirhtml to make HTML files named index.html in directories" @echo " singlehtml to make a single large HTML file" @echo " pickle to make pickle files" @echo " json to make JSON files" @echo " htmlhelp to make HTML files and a HTML help project" @echo " qthelp to make HTML files and a qthelp project" @echo " devhelp to make HTML files and a Devhelp project" @echo " epub to make an epub" @echo " latex to make LaTeX files, you can set PAPER=a4 or PAPER=letter" @echo " latexpdf to make LaTeX files and run them through pdflatex" @echo " latexpdfja to make LaTeX files and run them through platex/dvipdfmx" @echo " text to make text files" @echo " man to make manual pages" @echo " texinfo to make Texinfo files" @echo " info to make Texinfo files and run them through makeinfo" @echo " gettext to make PO message catalogs" @echo " changes to make an overview of all changed/added/deprecated items" @echo " xml to make Docutils-native XML files" @echo " pseudoxml to make pseudoxml-XML files for display purposes" @echo " linkcheck to check all external links for integrity" @echo " doctest to run all doctests embedded in the documentation (if enabled)" clean: rm -rf $(BUILDDIR)/* html: $(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html @echo @echo "Build finished. The HTML pages are in $(BUILDDIR)/html." dirhtml: $(SPHINXBUILD) -b dirhtml $(ALLSPHINXOPTS) $(BUILDDIR)/dirhtml @echo @echo "Build finished. The HTML pages are in $(BUILDDIR)/dirhtml." singlehtml: $(SPHINXBUILD) -b singlehtml $(ALLSPHINXOPTS) $(BUILDDIR)/singlehtml @echo @echo "Build finished. The HTML page is in $(BUILDDIR)/singlehtml." pickle: $(SPHINXBUILD) -b pickle $(ALLSPHINXOPTS) $(BUILDDIR)/pickle @echo @echo "Build finished; now you can process the pickle files." json: $(SPHINXBUILD) -b json $(ALLSPHINXOPTS) $(BUILDDIR)/json @echo @echo "Build finished; now you can process the JSON files." htmlhelp: $(SPHINXBUILD) -b htmlhelp $(ALLSPHINXOPTS) $(BUILDDIR)/htmlhelp @echo @echo "Build finished; now you can run HTML Help Workshop with the" \ ".hhp project file in $(BUILDDIR)/htmlhelp." qthelp: $(SPHINXBUILD) -b qthelp $(ALLSPHINXOPTS) $(BUILDDIR)/qthelp @echo @echo "Build finished; now you can run "qcollectiongenerator" with the" \ ".qhcp project file in $(BUILDDIR)/qthelp, like this:" @echo "# qcollectiongenerator $(BUILDDIR)/qthelp/mir_eval.qhcp" @echo "To view the help file:" @echo "# assistant -collectionFile $(BUILDDIR)/qthelp/mir_eval.qhc" devhelp: $(SPHINXBUILD) -b devhelp $(ALLSPHINXOPTS) $(BUILDDIR)/devhelp @echo @echo "Build finished." @echo "To view the help file:" @echo "# mkdir -p $$HOME/.local/share/devhelp/mir_eval" @echo "# ln -s $(BUILDDIR)/devhelp $$HOME/.local/share/devhelp/mir_eval" @echo "# devhelp" epub: $(SPHINXBUILD) -b epub $(ALLSPHINXOPTS) $(BUILDDIR)/epub @echo @echo "Build finished. The epub file is in $(BUILDDIR)/epub." latex: $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex @echo @echo "Build finished; the LaTeX files are in $(BUILDDIR)/latex." @echo "Run \`make' in that directory to run these through (pdf)latex" \ "(use \`make latexpdf' here to do that automatically)." latexpdf: $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex @echo "Running LaTeX files through pdflatex..." $(MAKE) -C $(BUILDDIR)/latex all-pdf @echo "pdflatex finished; the PDF files are in $(BUILDDIR)/latex." latexpdfja: $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex @echo "Running LaTeX files through platex and dvipdfmx..." $(MAKE) -C $(BUILDDIR)/latex all-pdf-ja @echo "pdflatex finished; the PDF files are in $(BUILDDIR)/latex." text: $(SPHINXBUILD) -b text $(ALLSPHINXOPTS) $(BUILDDIR)/text @echo @echo "Build finished. The text files are in $(BUILDDIR)/text." man: $(SPHINXBUILD) -b man $(ALLSPHINXOPTS) $(BUILDDIR)/man @echo @echo "Build finished. The manual pages are in $(BUILDDIR)/man." texinfo: $(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) $(BUILDDIR)/texinfo @echo @echo "Build finished. The Texinfo files are in $(BUILDDIR)/texinfo." @echo "Run \`make' in that directory to run these through makeinfo" \ "(use \`make info' here to do that automatically)." info: $(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) $(BUILDDIR)/texinfo @echo "Running Texinfo files through makeinfo..." make -C $(BUILDDIR)/texinfo info @echo "makeinfo finished; the Info files are in $(BUILDDIR)/texinfo." gettext: $(SPHINXBUILD) -b gettext $(I18NSPHINXOPTS) $(BUILDDIR)/locale @echo @echo "Build finished. The message catalogs are in $(BUILDDIR)/locale." changes: $(SPHINXBUILD) -b changes $(ALLSPHINXOPTS) $(BUILDDIR)/changes @echo @echo "The overview file is in $(BUILDDIR)/changes." linkcheck: $(SPHINXBUILD) -b linkcheck $(ALLSPHINXOPTS) $(BUILDDIR)/linkcheck @echo @echo "Link check complete; look for any errors in the above output " \ "or in $(BUILDDIR)/linkcheck/output.txt." doctest: $(SPHINXBUILD) -b doctest $(ALLSPHINXOPTS) $(BUILDDIR)/doctest @echo "Testing of doctests in the sources finished, look at the " \ "results in $(BUILDDIR)/doctest/output.txt." xml: $(SPHINXBUILD) -b xml $(ALLSPHINXOPTS) $(BUILDDIR)/xml @echo @echo "Build finished. The XML files are in $(BUILDDIR)/xml." pseudoxml: $(SPHINXBUILD) -b pseudoxml $(ALLSPHINXOPTS) $(BUILDDIR)/pseudoxml @echo @echo "Build finished. The pseudo-XML files are in $(BUILDDIR)/pseudoxml." mir_eval-0.8.2/docs/api/000077500000000000000000000000001475740344600150365ustar00rootroot00000000000000mir_eval-0.8.2/docs/api/alignment.rst000066400000000000000000000002341475740344600175450ustar00rootroot00000000000000mir_eval.alignment ================== .. automodule:: mir_eval.alignment :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/beat.rst000066400000000000000000000002151475740344600165010ustar00rootroot00000000000000mir_eval.beat ============= .. automodule:: mir_eval.beat :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/chord.rst000066400000000000000000000002201475740344600166610ustar00rootroot00000000000000mir_eval.chord ============== .. automodule:: mir_eval.chord :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/display.rst000066400000000000000000000002251475740344600172340ustar00rootroot00000000000000mir_eval.display ================ .. automodule:: mir_eval.display :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/hierarchy.rst000066400000000000000000000002341475740344600175450ustar00rootroot00000000000000mir_eval.hierarchy ================== .. automodule:: mir_eval.hierarchy :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/index.rst000066400000000000000000000005401475740344600166760ustar00rootroot00000000000000API Reference ============= Below is the reference documentation for all **mir_eval** submodules: .. toctree:: :maxdepth: 2 :titlesonly: alignment beat chord melody multipitch onset pattern segment hierarchy separation tempo transcription transcription_velocity key util io sonify display mir_eval-0.8.2/docs/api/io.rst000066400000000000000000000002071475740344600161760ustar00rootroot00000000000000mir_eval.io =========== .. automodule:: mir_eval.io :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/key.rst000066400000000000000000000002121475740344600163530ustar00rootroot00000000000000mir_eval.key ============ .. automodule:: mir_eval.key :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/melody.rst000066400000000000000000000002231475740344600170560ustar00rootroot00000000000000mir_eval.melody =============== .. automodule:: mir_eval.melody :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/multipitch.rst000066400000000000000000000002371475740344600177540ustar00rootroot00000000000000mir_eval.multipitch =================== .. automodule:: mir_eval.multipitch :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/onset.rst000066400000000000000000000002201475740344600167120ustar00rootroot00000000000000mir_eval.onset ============== .. automodule:: mir_eval.onset :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/pattern.rst000066400000000000000000000002261475740344600172450ustar00rootroot00000000000000mir_eval.pattern ================ .. automodule:: mir_eval.pattern :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/segment.rst000066400000000000000000000002261475740344600172320ustar00rootroot00000000000000mir_eval.segment ================ .. automodule:: mir_eval.segment :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/separation.rst000066400000000000000000000002371475740344600177370ustar00rootroot00000000000000mir_eval.separation =================== .. automodule:: mir_eval.separation :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/sonify.rst000066400000000000000000000002231475740344600170740ustar00rootroot00000000000000mir_eval.sonify =============== .. automodule:: mir_eval.sonify :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/tempo.rst000066400000000000000000000002201475740344600167060ustar00rootroot00000000000000mir_eval.tempo ============== .. automodule:: mir_eval.tempo :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/transcription.rst000066400000000000000000000002501475740344600204640ustar00rootroot00000000000000mir_eval.transcription ====================== .. automodule:: mir_eval.transcription :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/transcription_velocity.rst000066400000000000000000000003031475740344600224010ustar00rootroot00000000000000mir_eval.transcription_velocity =============================== .. automodule:: mir_eval.transcription_velocity :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/api/util.rst000066400000000000000000000002151475740344600165430ustar00rootroot00000000000000mir_eval.util ============= .. automodule:: mir_eval.util :members: :undoc-members: :show-inheritance: :member-order: bysource mir_eval-0.8.2/docs/changes.rst000066400000000000000000000236271475740344600164410ustar00rootroot00000000000000Changes ======= v0.8.2 ------ - `#418`_: Fixed a bug in time-frequency sonification with single-interval inputs. .. _#418: https://github.com/mir-evaluation/mir_eval/pull/418 v0.8.1 ------ - `#410`_: Fixed several errors with time-frequency sonification - `#412`_: Removed unused import of deprecated scipy submodule - `#416`_: `mir_eval.io` routines now support `pathlib.Path` (and generally `os.Pathlike`) inputs as well as strings or open file descriptors. - `#416`_: `mir_eval.io.load_wav` is deprecated and will be removed in v0.9.' .. _#410: https://github.com/mir-evaluation/mir_eval/pull/410 .. _#412: https://github.com/mir-evaluation/mir_eval/pull/412 .. _#416: https://github.com/mir-evaluation/mir_eval/pull/416 v0.8 ---- - `#397`_: Removed invalid chord types from `chord.QUALITIES` - `#390`_: Migrate from personal to organization account - `#388`_: Update to packaging workflow - `#387`_: Various modernizations - `#385`_: Fixed import error - `#384`_: Rename `testing` to `tests` - `#382`_: Deprecated the source separation module - `#380`_: Matplotlib support modernization - `#379`_: Support nans in pitch contour sonification - `#378`_: Improved efficiency in chord validation - `#374`_: Fixed length calculation error in `sonify.time_frequency` - `#370`_: Test and CI modernization - `#367`_: Added interpolation method to docs for `resample_multipitch` - `#361`_: Added PyPI package release workflow - `#360`_: Fixed broken link - `#359`_: Remove support for python 2 - `#356`_, `#357`_, `#358`_: Migrate testing to github actions - `#355`_: Optimize and fix sonification - `#353`_: Set numerical precision, fix support for modern numpy .. _#397: https://github.com/mir-evaluation/mir_eval/pull/397 .. _#390: https://github.com/mir-evaluation/mir_eval/pull/390 .. _#388: https://github.com/mir-evaluation/mir_eval/pull/388 .. _#387: https://github.com/mir-evaluation/mir_eval/pull/387 .. _#385: https://github.com/mir-evaluation/mir_eval/pull/385 .. _#384: https://github.com/mir-evaluation/mir_eval/pull/384 .. _#382: https://github.com/mir-evaluation/mir_eval/pull/382 .. _#380: https://github.com/mir-evaluation/mir_eval/pull/380 .. _#379: https://github.com/mir-evaluation/mir_eval/pull/379 .. _#378: https://github.com/mir-evaluation/mir_eval/pull/378 .. _#374: https://github.com/mir-evaluation/mir_eval/pull/374 .. _#370: https://github.com/mir-evaluation/mir_eval/pull/370 .. _#367: https://github.com/mir-evaluation/mir_eval/pull/367 .. _#361: https://github.com/mir-evaluation/mir_eval/pull/361 .. _#360: https://github.com/mir-evaluation/mir_eval/pull/360 .. _#359: https://github.com/mir-evaluation/mir_eval/pull/359 .. _#356: https://github.com/mir-evaluation/mir_eval/pull/356 .. _#357: https://github.com/mir-evaluation/mir_eval/pull/357 .. _#358: https://github.com/mir-evaluation/mir_eval/pull/358 .. _#355: https://github.com/mir-evaluation/mir_eval/pull/355 .. _#353: https://github.com/mir-evaluation/mir_eval/pull/353 v0.7 ---- - `#334`_: Support notation for unknown/ambiguous key or mode - `#343`_: Add suite of alignment metrics .. _#334: https://github.com/mir-evaluation/mir_eval/pull/334 .. _#343: https://github.com/mir-evaluation/mir_eval/pull/343 v0.6 ---- - `#297`_: Return 0 when no overlap in transcription_velocity - `#299`_: Allow one reference tempo and both estimate tempi to be zero - `#301`_: Allow zero tolerance in tempo, but issue a warning - `#302`_: Loosen separation test tolerance - `#305`_: Use toarray instead of todense for sparse matrices - `#307`_: Use tuple index in chord.rotate_bitmap_to_root - `#309`_: Require matplotlib <3 for testing - `#312`_: Fix raw chroma accuracy for unvoiced estimates - `#320`_: Add comment support to io methods - `#323`_: Fix interpolation in sonify.time_frequency - `#324`_: Add generalized melody metrics - `#327`_: Stop testing 2.7 - `#328`_: Cast n_voiced to int in display.multipitch .. _#297: https://github.com/mir-evaluation/mir_eval/pull/297 .. _#299: https://github.com/mir-evaluation/mir_eval/pull/299 .. _#301: https://github.com/mir-evaluation/mir_eval/pull/301 .. _#302: https://github.com/mir-evaluation/mir_eval/pull/302 .. _#305: https://github.com/mir-evaluation/mir_eval/pull/305 .. _#307: https://github.com/mir-evaluation/mir_eval/pull/307 .. _#309: https://github.com/mir-evaluation/mir_eval/pull/309 .. _#312: https://github.com/mir-evaluation/mir_eval/pull/312 .. _#320: https://github.com/mir-evaluation/mir_eval/pull/320 .. _#323: https://github.com/mir-evaluation/mir_eval/pull/323 .. _#324: https://github.com/mir-evaluation/mir_eval/pull/324 .. _#327: https://github.com/mir-evaluation/mir_eval/pull/327 .. _#328: https://github.com/mir-evaluation/mir_eval/pull/328 v0.5 ---- - `#222`_: added int cast for inferred length in sonify.clicks - `#225`_: improved t-measures and l-measures - `#227`_: added marginal flag to segment.nce - `#234`_: update display to use matplotlib 2 - `#236`_: force integer division in beat.pscore - `#240`_: fix unit tests for source separation - `#242`_: use regexp in chord label validation - `#245`_: add labeled interval formatter to display - `#247`_: do not sonify negative amplitudes in time_frequency - `#249`_: support gaps in util.interpolate_intervals - `#252`_: add modulo and length arguments to chord.scale_degree_to_bitmap - `#254`_: fix bss_eval_images single-frame fallback documentation - `#255`_: fix crackle in sonify.time_frequency - `#258`_: make util.match_events faster - `#259`_: run pep8 check after nosetests - `#263`_: add measures for chord over- and under-segmentation - `#266`_: add amplitude parameter to sonify.pitch_contour - `#268`_: update display tests to support mpl2.1 - `#277`_: update requirements and fix deprecations - `#279`_: isolate matplotlib side effects - `#282`_: remove evaluator scripts - `#283`_: add transcription eval with velocity .. _#222: https://github.com/mir-evaluation/mir_eval/pull/222 .. _#225: https://github.com/mir-evaluation/mir_eval/pull/225 .. _#227: https://github.com/mir-evaluation/mir_eval/pull/227 .. _#234: https://github.com/mir-evaluation/mir_eval/pull/234 .. _#236: https://github.com/mir-evaluation/mir_eval/pull/236 .. _#240: https://github.com/mir-evaluation/mir_eval/pull/240 .. _#242: https://github.com/mir-evaluation/mir_eval/pull/242 .. _#245: https://github.com/mir-evaluation/mir_eval/pull/245 .. _#247: https://github.com/mir-evaluation/mir_eval/pull/247 .. _#249: https://github.com/mir-evaluation/mir_eval/pull/249 .. _#252: https://github.com/mir-evaluation/mir_eval/pull/252 .. _#254: https://github.com/mir-evaluation/mir_eval/pull/254 .. _#255: https://github.com/mir-evaluation/mir_eval/pull/255 .. _#258: https://github.com/mir-evaluation/mir_eval/pull/258 .. _#259: https://github.com/mir-evaluation/mir_eval/pull/259 .. _#263: https://github.com/mir-evaluation/mir_eval/pull/263 .. _#266: https://github.com/mir-evaluation/mir_eval/pull/266 .. _#268: https://github.com/mir-evaluation/mir_eval/pull/268 .. _#277: https://github.com/mir-evaluation/mir_eval/pull/277 .. _#279: https://github.com/mir-evaluation/mir_eval/pull/279 .. _#282: https://github.com/mir-evaluation/mir_eval/pull/282 .. _#283: https://github.com/mir-evaluation/mir_eval/pull/283 v0.4 ---- - `#189`_: expanded transcription metrics - `#195`_: added pitch contour sonification - `#196`_: added the `display` submodule - `#203`_: support unsorted segment intervals - `#205`_: correction in documentation for `sonify.time_frequency` - `#208`_: refactored file/buffer loading - `#210`_: added `io.load_tempo` - `#212`_: added frame-wise blind-source separation evaluation - `#218`_: speed up `melody.resample_melody_series` when times are equivalent .. _#189: https://github.com/mir-evaluation/mir_eval/issues/189 .. _#195: https://github.com/mir-evaluation/mir_eval/issues/195 .. _#196: https://github.com/mir-evaluation/mir_eval/issues/196 .. _#203: https://github.com/mir-evaluation/mir_eval/issues/203 .. _#205: https://github.com/mir-evaluation/mir_eval/issues/205 .. _#208: https://github.com/mir-evaluation/mir_eval/issues/208 .. _#210: https://github.com/mir-evaluation/mir_eval/issues/210 .. _#212: https://github.com/mir-evaluation/mir_eval/issues/212 .. _#218: https://github.com/mir-evaluation/mir_eval/pull/218 v0.3 ---- - `#170`_: implemented transcription metrics - `#173`_: fixed a bug in chord sonification - `#175`_: filter_kwargs passes through `**kwargs` - `#181`_: added key detection metrics .. _#170: https://github.com/mir-evaluation/mir_eval/issues/170 .. _#173: https://github.com/mir-evaluation/mir_eval/issues/173 .. _#175: https://github.com/mir-evaluation/mir_eval/issues/175 .. _#181: https://github.com/mir-evaluation/mir_eval/issues/181 v0.2 ---- - `#103`_: incomplete files passed to `melody.evaluate` should warn - `#109`_: `STRICT_BASS_INTERVALS` is now an argument to `chord.encode` - `#122`_: improved handling of corner cases in beat tracking - `#136`_: improved test coverage - `#138`_: PEP8 compliance - `#139`_: converted documentation to numpydoc style - `#147`_: fixed a rounding error in segment intervals - `#150`_: `sonify.chroma` and `sonify.chords` pass `kwargs` to `time_frequecy` - `#151`_: removed `labels` support from `util.boundaries_to_intervals` - `#159`_: fixed documentation error in `chord.tetrads` - `#160`_: fixed documentation error in `util.intervals_to_samples` .. _#103: https://github.com/mir-evaluation/mir_eval/issues/103 .. _#109: https://github.com/mir-evaluation/mir_eval/issues/109 .. _#122: https://github.com/mir-evaluation/mir_eval/issues/122 .. _#136: https://github.com/mir-evaluation/mir_eval/issues/136 .. _#138: https://github.com/mir-evaluation/mir_eval/issues/138 .. _#139: https://github.com/mir-evaluation/mir_eval/issues/139 .. _#147: https://github.com/mir-evaluation/mir_eval/issues/147 .. _#150: https://github.com/mir-evaluation/mir_eval/issues/150 .. _#151: https://github.com/mir-evaluation/mir_eval/issues/151 .. _#159: https://github.com/mir-evaluation/mir_eval/issues/159 .. _#160: https://github.com/mir-evaluation/mir_eval/issues/160 v0.1 ---- - Initial public release. mir_eval-0.8.2/docs/conf.py000066400000000000000000000217231475740344600155710ustar00rootroot00000000000000# # mir_eval documentation build configuration file, created by # sphinx-quickstart on Thu May 8 15:55:45 2014. # # This file is execfile()d with the current directory set to its # containing dir. # # Note that not all possible configuration values are present in this # autogenerated file. # # All configuration values have a default; values that are commented out # serve to show the default. import sys import os sys.path.insert(0, os.path.abspath("..")) from mir_eval import __version__ as release version = release # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. # sys.path.insert(0, os.path.abspath('.')) # -- General configuration ------------------------------------------------ # If your documentation needs a minimal Sphinx version, state it here. # needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = [ "sphinx.ext.autodoc", "sphinx.ext.imgmath", "numpydoc", ] # Add any paths that contain templates here, relative to this directory. templates_path = ["_templates"] # The suffix of source filenames. source_suffix = ".rst" # The encoding of source files. # source_encoding = 'utf-8-sig' # The master toctree document. master_doc = "index" # General information about the project. project = "mir_eval" copyright = "2014, Colin Raffel et al." # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the # built documents. # # The short X.Y version. #version = "0.7" # The full version, including alpha/beta/rc tags. #release = "0.7" # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. # language = None # There are two options for replacing |today|: either, you set today to some # non-false value, then it is used: # today = '' # Else, today_fmt is used as the format for a strftime call. # today_fmt = '%B %d, %Y' # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. exclude_patterns = ["_build"] # The reST default role (used for this markup: `text`) to use for all # documents. # default_role = None # If true, '()' will be appended to :func: etc. cross-reference text. # add_function_parentheses = True # If true, the current module name will be prepended to all description # unit titles (such as .. function::). # add_module_names = True # If true, sectionauthor and moduleauthor directives will be shown in the # output. They are ignored by default. # show_authors = False # The name of the Pygments (syntax highlighting) style to use. pygments_style = "sphinx" # A list of ignored prefixes for module index sorting. # modindex_common_prefix = [] # If true, keep warnings as "system message" paragraphs in the built documents. # keep_warnings = False # -- Options for HTML output ---------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. #html_theme = "default" html_theme = "sphinx_rtd_theme" # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. html_theme_options = { "navigation_depth": 4, "collapse_navigation": False, } # Add any paths that contain custom themes here, relative to this directory. # html_theme_path = [] # The name for this set of Sphinx documents. If None, it defaults to # " v documentation". # html_title = None # A shorter title for the navigation bar. Default is the same as html_title. # html_short_title = None # The name of an image file (relative to this directory) to place at the top # of the sidebar. # html_logo = None # The name of an image file (within the static path) to use as favicon of the # docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 # pixels large. # html_favicon = None # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". # html_static_path = ["_static"] # Add any extra paths that contain custom files (such as robots.txt or # .htaccess) here, relative to this directory. These files are copied # directly to the root of the documentation. # html_extra_path = [] # If not '', a 'Last updated on:' timestamp is inserted at every page bottom, # using the given strftime format. # html_last_updated_fmt = '%b %d, %Y' # If true, SmartyPants will be used to convert quotes and dashes to # typographically correct entities. # html_use_smartypants = True # Custom sidebar templates, maps document names to template names. # html_sidebars = {} html_sidebars = { '**': [ 'globaltoc.html', # shows the full, global TOC from the master toctree 'localtoc.html', # also shows the local toctree (optional) 'relations.html', 'sourcelink.html', 'searchbox.html', ] } # Additional templates that should be rendered to pages, maps page names to # template names. # html_additional_pages = {} # If false, no module index is generated. html_domain_indices = True # If false, no index is generated. # html_use_index = True # If true, the index is split into individual pages for each letter. # html_split_index = False # If true, links to the reST sources are added to the pages. # html_show_sourcelink = True # If true, "Created using Sphinx" is shown in the HTML footer. Default is True. # html_show_sphinx = True # If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. # html_show_copyright = True # If true, an OpenSearch description file will be output, and all pages will # contain a tag referring to it. The value of this option must be the # base URL from which the finished HTML is served. # html_use_opensearch = '' # This is the file name suffix for HTML files (e.g. ".xhtml"). # html_file_suffix = None # Output file base name for HTML help builder. htmlhelp_basename = "mir_evaldoc" # -- Options for LaTeX output --------------------------------------------- latex_elements = { # The paper size ('letterpaper' or 'a4paper'). # 'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). # 'pointsize': '10pt', # Additional stuff for the LaTeX preamble. # 'preamble': '', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ ( "index", "mir_eval.tex", "mir\\_eval Documentation", "Colin Raffel et al.", "manual", ), ] # The name of an image file (relative to this directory) to place at the top of # the title page. # latex_logo = None # For "manual" documents, if this is true, then toplevel headings are parts, # not chapters. # latex_use_parts = False # If true, show page references after internal links. # latex_show_pagerefs = False # If true, show URL addresses after external links. # latex_show_urls = False # Documents to append as an appendix to all manuals. # latex_appendices = [] # If false, no module index is generated. # latex_domain_indices = True # -- Options for manual page output --------------------------------------- # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ ("index", "mir_eval", "mir_eval Documentation", ["Colin Raffel et al."], 1) ] # If true, show URL addresses after external links. # man_show_urls = False # -- Options for Texinfo output ------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ ( "index", "mir_eval", "mir_eval Documentation", "Colin Raffel et al.", "mir_eval", "One line description of project.", "Miscellaneous", ), ] # Documents to append as an appendix to all manuals. # texinfo_appendices = [] # If false, no module index is generated. # texinfo_domain_indices = True # How to display URL addresses: 'footnote', 'no', or 'inline'. # texinfo_show_urls = 'footnote' # If true, do not generate a @detailmenu in the "Top" node's menu. # texinfo_no_detailmenu = False autodoc_member_order = "bysource" linkcheck_allow_unauthorized = True linkcheck_ignore = [ # Sphinx has problems with the anchor on this one, but it does work 'http://www.music-ir.org/mirex/wiki/2015:Multiple_Fundamental_Frequency_Estimation_%26_Tracking_Results_-_MIREX_Dataset#Task_2:Note_Tracking_.28NT.29' ] mir_eval-0.8.2/docs/index.rst000066400000000000000000000100751475740344600161310ustar00rootroot00000000000000.. mir_eval documentation master file mir_eval Documentation ====================== **mir_eval** is a Python library which provides a transparent, standardized, and straightforward way to evaluate Music Information Retrieval systems. If you use **mir_eval** in a research project, please cite the following paper: C. Raffel, B. McFee, E. J. Humphrey, J. Salamon, O. Nieto, D. Liang, and D. P. W. Ellis, `"mir_eval: A Transparent Implementation of Common MIR Metrics" `_, Proceedings of the 15th International Conference on Music Information Retrieval, 2014. Installation ============ The simplest way to install **mir_eval** is via ``pip``: .. code-block:: console python -m pip install mir_eval If you use `conda` packages, **mir_eval** is available on conda-forge: .. code-block:: console conda install -c conda-forge mir_eval Alternatively, you can install from source: .. code-block:: console python setup.py install If you don't use Python and want to get started as quickly as possible, you might consider using `Anaconda `_ which makes it easy to install a Python environment which can run **mir_eval**. Using mir_eval ============== Once installed, you can import **mir_eval** in your code: .. code-block:: python import mir_eval For example, to evaluate beat tracking: .. code-block:: python reference_beats = mir_eval.io.load_events('reference_beats.txt') estimated_beats = mir_eval.io.load_events('estimated_beats.txt') scores = mir_eval.beat.evaluate(reference_beats, estimated_beats) At the end of execution, ``scores`` will be a dict containing scores for all of the metrics implemented in `mir_eval.beat`. The keys are metric names and values are the scores achieved. You can also load in the data, do some preprocessing, and call specific metric functions from the appropriate submodule like so: .. code-block:: python reference_beats = mir_eval.io.load_events('reference_beats.txt') estimated_beats = mir_eval.io.load_events('estimated_beats.txt') # Crop out beats before 5s, a common preprocessing step reference_beats = mir_eval.beat.trim_beats(reference_beats) estimated_beats = mir_eval.beat.trim_beats(estimated_beats) # Compute the F-measure metric and store it in f_measure f_measure = mir_eval.beat.f_measure(reference_beats, estimated_beats) Alternatively, you can use the evaluator scripts which allow you to run evaluation from the command line, without writing any code. These scripts are are available here: https://github.com/craffel/mir_evaluators API Reference ============= The structure of the **mir_eval** Python module is as follows: Each MIR task for which evaluation metrics are included in **mir_eval** is given its own submodule, and each metric is defined as a separate function in each submodule. Every metric function includes detailed documentation, example usage, input validation, and references to the original paper which defined the metric (see the subsections below). The task submodules also all contain a function ``evaluate()``, which takes as input reference and estimated annotations and returns a dictionary of scores for all of the metrics implemented (for casual users, this is the place to start). Finally, each task submodule also includes functions for common data pre-processing steps. **mir_eval** also includes the following additional submodules: * :mod:`mir_eval.io` which contains convenience functions for loading in task-specific data from common file formats * :mod:`mir_eval.util` which includes miscellaneous functionality shared across the submodules * :mod:`mir_eval.sonify` which implements some simple methods for synthesizing annotations of various formats for "evaluation by ear". * :mod:`mir_eval.display` which provides functions for plotting annotations for various tasks. Detailed API documentation for each submodule is available in the API Reference section. See the :doc:`API Reference ` for full details. .. toctree:: :caption: mir_eval :maxdepth: 2 api/index changes mir_eval-0.8.2/mir_eval/000077500000000000000000000000001475740344600151335ustar00rootroot00000000000000mir_eval-0.8.2/mir_eval/__init__.py000066400000000000000000000007701475740344600172500ustar00rootroot00000000000000#!/usr/bin/env python """Top-level module for mir_eval""" # Import all submodules (for each task) from . import alignment from . import beat from . import chord from . import io from . import onset from . import segment from . import separation from . import util from . import sonify from . import melody from . import multipitch from . import pattern from . import tempo from . import hierarchy from . import transcription from . import transcription_velocity from . import key __version__ = "0.8.2" mir_eval-0.8.2/mir_eval/alignment.py000066400000000000000000000341111475740344600174630ustar00rootroot00000000000000""" Alignment models are given a sequence of events along with a piece of audio, and then return a sequence of timestamps, with one timestamp for each event, indicating the position of this event in the audio. The events are listed in order of occurrence in the audio, so that output timestamps have to be monotonically increasing. Evaluation usually involves taking the series of predicted and ground truth timestamps and comparing their distance, usually on a pair-wise basis, e.g. taking the median absolute error in seconds. Conventions ----------- Timestamps should be provided in the form of a 1-dimensional array of onset times in seconds in increasing order. Metrics ------- * :func:`mir_eval.alignment.absolute_error`: Median absolute error and average absolute error * :func:`mir_eval.alignment.percentage_correct`: Percentage of correct timestamps, where a timestamp is counted as correct if it lies within a certain tolerance window around the ground truth timestamp * :func:`mir_eval.alignment.pcs`: Percentage of correct segments: Percentage of overlap between predicted segments and ground truth segments, where segments are defined by (start time, end time) pairs * :func:`mir_eval.alignment.perceptual_metric`: metric based on human synchronicity perception as measured in the paper "User-centered evaluation of lyrics to audio alignment", N. Lizé-Masclef, A. Vaglio, M. Moussallam, ISMIR 2021 References ---------- .. [#lizemasclef2021] N. Lizé-Masclef, A. Vaglio, M. Moussallam. "User-centered evaluation of lyrics to audio alignment", International Society for Music Information Retrieval (ISMIR) conference, 2021. .. [#mauch2010] M. Mauch, F: Hiromasa, M. Goto. "Lyrics-to-audio alignment and phrase-level segmentation using incomplete internet-style chord annotations", Frontiers in Proceedings of the Sound Music Computing Conference (SMC), 2010. .. [#dzhambazov2017] G. Dzhambazov. "Knowledge-Based Probabilistic Modeling For Tracking Lyrics In Music Audio Signals", PhD Thesis, 2017. .. [#fujihara2011] H. Fujihara, M. Goto, J. Ogata, H. Okuno. "LyricSynchronizer: Automatic synchronization system between musical audio signals and lyrics", IEEE Journal of Selected Topics in Signal Processing, VOL. 5, NO. 6, 2011 """ import collections from typing import Optional import numpy as np from scipy.stats import skewnorm from mir_eval.util import filter_kwargs def validate(reference_timestamps: np.ndarray, estimated_timestamps: np.ndarray): """Check that the input annotations to a metric look like valid onset time arrays, and throws helpful errors if not. Parameters ---------- reference_timestamps : np.ndarray reference timestamp locations, in seconds estimated_timestamps : np.ndarray estimated timestamp locations, in seconds """ # We need to have 1D numpy arrays if not isinstance(reference_timestamps, np.ndarray): raise ValueError( "Reference timestamps need to be a numpy array, but got" f" {type(reference_timestamps)}" ) if not isinstance(estimated_timestamps, np.ndarray): raise ValueError( "Estimated timestamps need to be a numpy array, but got" f" {type(estimated_timestamps)}" ) if reference_timestamps.ndim != 1: raise ValueError( "Reference timestamps need to be a one-dimensional vector, but got" f" {reference_timestamps.ndim} dimensions" ) if estimated_timestamps.ndim != 1: raise ValueError( "Estimated timestamps need to be a one-dimensional vector, but got" f" {estimated_timestamps.ndim} dimensions" ) # If reference or estimated timestamps are empty, cannot compute metric if reference_timestamps.size == 0: raise ValueError("Reference timestamps are empty.") if estimated_timestamps.size != reference_timestamps.size: raise ValueError( "Number of timestamps must be the same in prediction and ground" f" truth, but found {estimated_timestamps.size} in prediction and" f" {reference_timestamps.size} in ground truth" ) # Check monotonicity if not np.all(reference_timestamps[1:] - reference_timestamps[:-1] >= 0): raise ValueError("Reference timestamps are not monotonically increasing!") if not np.all(estimated_timestamps[1:] - estimated_timestamps[:-1] >= 0): raise ValueError("Estimated timestamps are not monotonically increasing!") # Check positivity (need for correct PCS metric calculation) if not np.all(reference_timestamps >= 0): raise ValueError("Reference timestamps can not be below 0!") if not np.all(estimated_timestamps >= 0): raise ValueError("Estimated timestamps can not be below 0!") def absolute_error(reference_timestamps, estimated_timestamps): """Compute the absolute deviations between estimated and reference timestamps, and then returns the median and average over all events Examples -------- >>> reference_timestamps = mir_eval.io.load_events('reference.txt') >>> estimated_timestamps = mir_eval.io.load_events('estimated.txt') >>> mae, aae = mir_eval.align.absolute_error(reference_onsets, estimated_timestamps) Parameters ---------- reference_timestamps : np.ndarray reference timestamps, in seconds estimated_timestamps : np.ndarray estimated timestamps, in seconds Returns ------- mae : float Median absolute error aae: float Average absolute error """ validate(reference_timestamps, estimated_timestamps) deviations = np.abs(reference_timestamps - estimated_timestamps) return np.median(deviations), np.mean(deviations) def percentage_correct(reference_timestamps, estimated_timestamps, window=0.3): """Compute the percentage of correctly predicted timestamps. A timestamp is predicted correctly if its position doesn't deviate more than the window parameter from the ground truth timestamp. Examples -------- >>> reference_timestamps = mir_eval.io.load_events('reference.txt') >>> estimated_timestamps = mir_eval.io.load_events('estimated.txt') >>> pc = mir_eval.align.percentage_correct(reference_onsets, estimated_timestamps, window=0.2) Parameters ---------- reference_timestamps : np.ndarray reference timestamps, in seconds estimated_timestamps : np.ndarray estimated timestamps, in seconds window : float Window size, in seconds (Default value = .3) Returns ------- pc : float Percentage of correct timestamps """ validate(reference_timestamps, estimated_timestamps) deviations = np.abs(reference_timestamps - estimated_timestamps) return np.mean(deviations <= window) def percentage_correct_segments( reference_timestamps, estimated_timestamps, duration: Optional[float] = None ): """Calculate the percentage of correct segments (PCS) metric. It constructs segments out of predicted and estimated timestamps separately out of each given timestamp vector and calculates the percentage of overlap between correct segments compared to the total duration. WARNING: This metrics behaves differently depending on whether "duration" is given! If duration is not given (default case), the computation follows the MIREX lyrics alignment challenge 2020. For a timestamp vector with entries (t1,t2, ... tN), segments with the following (start, end) boundaries are created: (t1, t2), ... (tN-1, tN). After the segments are created, the overlap between the reference and estimated segments is determined and divided by the total duration, which is the distance between the first and last timestamp in the reference. If duration is given, the segment boundaries are instead (0, t1), (t1, t2), ... (tN, duration). The overlap is computed in the same way, but then divided by the duration parameter given to this function. This method follows the original paper [#fujihara2011] more closely, where the metric was proposed. As a result, this variant of the metrics punishes cases where the first estimated timestamp is too early or the last estimated timestamp is too late, whereas the MIREX variant does not. On the other hand, the MIREX metric is invariant to how long the eventless beginning and end parts of the audio are, which might be a desirable property. Examples -------- >>> reference_timestamps = mir_eval.io.load_events('reference.txt') >>> estimated_timestamps = mir_eval.io.load_events('estimated.txt') >>> pcs = mir_eval.align.percentage_correct_segments(reference_timestamps, estimated_timestamps) Parameters ---------- reference_timestamps : np.ndarray reference timestamps, in seconds estimated_timestamps : np.ndarray estimated timestamps, in seconds duration : float Optional. Total duration of audio (seconds). WARNING: Metric is computed differently depending on whether this is provided or not - see documentation above! Returns ------- pcs : float Percentage of time where ground truth and predicted segments overlap """ validate(reference_timestamps, estimated_timestamps) if duration is not None: duration = float(duration) if duration <= 0: raise ValueError( f"Positive duration needs to be provided, but got {duration}" ) if np.max(reference_timestamps) > duration: raise ValueError( "Expected largest reference timestamp" f"{np.max(reference_timestamps)} to not be " f"larger than duration {duration}" ) if np.max(estimated_timestamps) > duration: raise ValueError( "Expected largest estimated timestamp " f"{np.max(estimated_timestamps)} to not be " f"larger than duration {duration}" ) ref_starts = np.concatenate([[0], reference_timestamps]) ref_ends = np.concatenate([reference_timestamps, [duration]]) est_starts = np.concatenate([[0], estimated_timestamps]) est_ends = np.concatenate([estimated_timestamps, [duration]]) else: # MIREX lyrics alignment 2020 style: # Ignore regions before start and after end reference timestamp duration = reference_timestamps[-1] - reference_timestamps[0] if duration <= 0: raise ValueError( f"Reference timestamps are all identical, can not compute PCS" f" metric!" ) ref_starts = reference_timestamps[:-1] ref_ends = reference_timestamps[1:] est_starts = estimated_timestamps[:-1] est_ends = estimated_timestamps[1:] overlap_starts = np.maximum(ref_starts, est_starts) overlap_ends = np.minimum(ref_ends, est_ends) overlap_duration = np.sum(np.maximum(overlap_ends - overlap_starts, 0)) return overlap_duration / duration def karaoke_perceptual_metric(reference_timestamps, estimated_timestamps): """Metric based on human synchronicity perception as measured in the paper "User-centered evaluation of lyrics to audio alignment" [#lizemasclef2021] The parameters of this function were tuned on data collected through a user Karaoke-like experiment It reflects human judgment of how "synchronous" lyrics and audio stimuli are perceived in that setup. Beware that this metric is non-symmetrical and by construction it is also not equal to 1 at 0. Examples -------- >>> reference_timestamps = mir_eval.io.load_events('reference.txt') >>> estimated_timestamps = mir_eval.io.load_events('estimated.txt') >>> score = mir_eval.align.karaoke_perceptual_metric(reference_onsets, estimated_timestamps) Parameters ---------- reference_timestamps : np.ndarray reference timestamps, in seconds estimated_timestamps : np.ndarray estimated timestamps, in seconds Returns ------- perceptual_score : float Perceptual score, averaged over all timestamps """ validate(reference_timestamps, estimated_timestamps) offsets = estimated_timestamps - reference_timestamps # Score offsets using a certain skewed normal distribution skewness = 1.12244251 localisation = -0.22270315 scale = 0.29779424 normalisation_factor = 1.6857 perceptual_scores = (1.0 / normalisation_factor) * skewnorm.pdf( offsets, skewness, loc=localisation, scale=scale ) return np.mean(perceptual_scores) def evaluate(reference_timestamps, estimated_timestamps, **kwargs): """Compute all metrics for the given reference and estimated annotations. Examples -------- >>> reference_timestamps = mir_eval.io.load_events('reference.txt') >>> estimated_timestamps = mir_eval.io.load_events('estimated.txt') >>> duration = max(np.max(reference_timestamps), np.max(estimated_timestamps)) + 10 >>> scores = mir_eval.align.evaluate(reference_onsets, estimated_timestamps, duration) Parameters ---------- reference_timestamps : np.ndarray reference timestamp locations, in seconds estimated_timestamps : np.ndarray estimated timestamp locations, in seconds **kwargs Additional keyword arguments which will be passed to the appropriate metric or preprocessing functions. Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. """ # Compute all metrics scores = collections.OrderedDict() scores["pc"] = filter_kwargs( percentage_correct, reference_timestamps, estimated_timestamps, **kwargs ) scores["mae"], scores["aae"] = absolute_error( reference_timestamps, estimated_timestamps ) scores["pcs"] = filter_kwargs( percentage_correct_segments, reference_timestamps, estimated_timestamps, **kwargs, ) scores["perceptual"] = karaoke_perceptual_metric( reference_timestamps, estimated_timestamps ) return scores mir_eval-0.8.2/mir_eval/beat.py000066400000000000000000000746601475740344600164350ustar00rootroot00000000000000r""" The aim of a beat detection algorithm is to report the times at which a typical human listener might tap their foot to a piece of music. As a result, most metrics for evaluating the performance of beat tracking systems involve computing the error between the estimated beat times and some reference list of beat locations. Many metrics additionally compare the beat sequences at different metric levels in order to deal with the ambiguity of tempo. Based on the methods described in: Matthew E. P. Davies, Norberto Degara, and Mark D. Plumbley. "Evaluation Methods for Musical Audio Beat Tracking Algorithms", Queen Mary University of London Technical Report C4DM-TR-09-06 London, United Kingdom, 8 October 2009. See also the Beat Evaluation Toolbox: https://code.soundsoftware.ac.uk/projects/beat-evaluation/ Conventions ----------- Beat times should be provided in the form of a 1-dimensional array of beat times in seconds in increasing order. Typically, any beats which occur before 5s are ignored; this can be accomplished using :func:`mir_eval.beat.trim_beats()`. Metrics ------- * :func:`mir_eval.beat.f_measure`: The F-measure of the beat sequence, where an estimated beat is considered correct if it is sufficiently close to a reference beat * :func:`mir_eval.beat.cemgil`: Cemgil's score, which computes the sum of Gaussian errors for each beat * :func:`mir_eval.beat.goto`: Goto's score, a binary score which is 1 when at least 25\% of the estimated beat sequence closely matches the reference beat sequence * :func:`mir_eval.beat.p_score`: McKinney's P-score, which computes the cross-correlation of the estimated and reference beat sequences represented as impulse trains * :func:`mir_eval.beat.continuity`: Continuity-based scores which compute the proportion of the beat sequence which is continuously correct * :func:`mir_eval.beat.information_gain`: The Information Gain of a normalized beat error histogram over a uniform distribution """ import numpy as np import collections from . import util import warnings # The maximum allowable beat time MAX_TIME = 30000.0 def trim_beats(beats, min_beat_time=5.0): """Remove beats before min_beat_time. A common preprocessing step. Parameters ---------- beats : np.ndarray Array of beat times in seconds. min_beat_time : float Minimum beat time to allow (Default value = 5.) Returns ------- beats_trimmed : np.ndarray Trimmed beat array. """ # Remove beats before min_beat_time return beats[beats >= min_beat_time] def validate(reference_beats, estimated_beats): """Check that the input annotations to a metric look like valid beat time arrays, and throws helpful errors if not. Parameters ---------- reference_beats : np.ndarray reference beat times, in seconds estimated_beats : np.ndarray estimated beat times, in seconds """ # If reference or estimated beats are empty, # warn because metric will be 0 if reference_beats.size == 0: warnings.warn("Reference beats are empty.") if estimated_beats.size == 0: warnings.warn("Estimated beats are empty.") for beats in [reference_beats, estimated_beats]: util.validate_events(beats, MAX_TIME) def _get_reference_beat_variations(reference_beats): """Return metric variations of the reference beats Parameters ---------- reference_beats : np.ndarray beat locations in seconds Returns ------- reference_beats : np.ndarray Original beat locations off_beat : np.ndarray 180 degrees out of phase from the original beat locations double : np.ndarray Beats at 2x the original tempo half_odd : np.ndarray Half tempo, odd beats half_even : np.ndarray Half tempo, even beats """ # Create annotations at twice the metric level interpolated_indices = np.arange(0, reference_beats.shape[0] - 0.5, 0.5) original_indices = np.arange(0, reference_beats.shape[0]) double_reference_beats = np.interp( interpolated_indices, original_indices, reference_beats ) # Return metric variations: # True, off-beat, double tempo, half tempo odd, and half tempo even return ( reference_beats, double_reference_beats[1::2], double_reference_beats, reference_beats[::2], reference_beats[1::2], ) def f_measure(reference_beats, estimated_beats, f_measure_threshold=0.07): """Compute the F-measure of correct vs incorrectly predicted beats. "Correctness" is determined over a small window. Examples -------- >>> reference_beats = mir_eval.io.load_events('reference.txt') >>> reference_beats = mir_eval.beat.trim_beats(reference_beats) >>> estimated_beats = mir_eval.io.load_events('estimated.txt') >>> estimated_beats = mir_eval.beat.trim_beats(estimated_beats) >>> f_measure = mir_eval.beat.f_measure(reference_beats, estimated_beats) Parameters ---------- reference_beats : np.ndarray reference beat times, in seconds estimated_beats : np.ndarray estimated beat times, in seconds f_measure_threshold : float Window size, in seconds (Default value = 0.07) Returns ------- f_score : float The computed F-measure score """ validate(reference_beats, estimated_beats) # When estimated beats are empty, no beats are correct; metric is 0 if estimated_beats.size == 0 or reference_beats.size == 0: return 0.0 # Compute the best-case matching between reference and estimated locations matching = util.match_events(reference_beats, estimated_beats, f_measure_threshold) precision = float(len(matching)) / len(estimated_beats) recall = float(len(matching)) / len(reference_beats) return util.f_measure(precision, recall) def cemgil(reference_beats, estimated_beats, cemgil_sigma=0.04): """Cemgil's score, computes a gaussian error of each estimated beat. Compares against the original beat times and all metrical variations. Examples -------- >>> reference_beats = mir_eval.io.load_events('reference.txt') >>> reference_beats = mir_eval.beat.trim_beats(reference_beats) >>> estimated_beats = mir_eval.io.load_events('estimated.txt') >>> estimated_beats = mir_eval.beat.trim_beats(estimated_beats) >>> cemgil_score, cemgil_max = mir_eval.beat.cemgil(reference_beats, estimated_beats) Parameters ---------- reference_beats : np.ndarray reference beat times, in seconds estimated_beats : np.ndarray query beat times, in seconds cemgil_sigma : float Sigma parameter of gaussian error windows (Default value = 0.04) Returns ------- cemgil_score : float Cemgil's score for the original reference beats cemgil_max : float The best Cemgil score for all metrical variations """ validate(reference_beats, estimated_beats) # When estimated beats are empty, no beats are correct; metric is 0 if estimated_beats.size == 0 or reference_beats.size == 0: return 0.0, 0.0 # We'll compute Cemgil's accuracy for each variation accuracies = [] for reference_beats in _get_reference_beat_variations(reference_beats): accuracy = 0 # Cycle through beats for beat in reference_beats: # Find the error for the closest beat to the reference beat beat_diff = np.min(np.abs(beat - estimated_beats)) # Add gaussian error into the accuracy accuracy += np.exp(-(beat_diff**2) / (2.0 * cemgil_sigma**2)) # Normalize the accuracy accuracy /= 0.5 * (estimated_beats.shape[0] + reference_beats.shape[0]) # Add it to our list of accuracy scores accuracies.append(accuracy) # Return raw accuracy with non-varied annotations # and maximal accuracy across all variations return accuracies[0], np.max(accuracies) def goto( reference_beats, estimated_beats, goto_threshold=0.35, goto_mu=0.2, goto_sigma=0.2 ): """Calculate Goto's score, a binary 1 or 0 depending on some specific heuristic criteria Examples -------- >>> reference_beats = mir_eval.io.load_events('reference.txt') >>> reference_beats = mir_eval.beat.trim_beats(reference_beats) >>> estimated_beats = mir_eval.io.load_events('estimated.txt') >>> estimated_beats = mir_eval.beat.trim_beats(estimated_beats) >>> goto_score = mir_eval.beat.goto(reference_beats, estimated_beats) Parameters ---------- reference_beats : np.ndarray reference beat times, in seconds estimated_beats : np.ndarray query beat times, in seconds goto_threshold : float Threshold of beat error for a beat to be "correct" (Default value = 0.35) goto_mu : float The mean of the beat errors in the continuously correct track must be less than this (Default value = 0.2) goto_sigma : float The std of the beat errors in the continuously correct track must be less than this (Default value = 0.2) Returns ------- goto_score : float Either 1.0 or 0.0 if some specific criteria are met """ validate(reference_beats, estimated_beats) # When estimated beats are empty, no beats are correct; metric is 0 if estimated_beats.size == 0 or reference_beats.size == 0: return 0.0 # Error for each beat beat_error = np.ones(reference_beats.shape[0]) # Flag for whether the reference and estimated beats are paired paired = np.zeros(reference_beats.shape[0]) # Keep track of Goto's three criteria goto_criteria = 0 for n in range(1, reference_beats.shape[0] - 1): # Get previous inner-reference-beat-interval previous_interval = 0.5 * (reference_beats[n] - reference_beats[n - 1]) # Window start - in the middle of the current beat and the previous window_min = reference_beats[n] - previous_interval # Next inter-reference-beat-interval next_interval = 0.5 * (reference_beats[n + 1] - reference_beats[n]) # Window end - in the middle of the current beat and the next window_max = reference_beats[n] + next_interval # Get estimated beats in the window beats_in_window = np.logical_and( (estimated_beats >= window_min), (estimated_beats < window_max) ) # False negative/positive if beats_in_window.sum() == 0 or beats_in_window.sum() > 1: paired[n] = 0 beat_error[n] = 1 else: # Single beat is paired! paired[n] = 1 # Get offset of the estimated beat and the reference beat offset = estimated_beats[beats_in_window] - reference_beats[n] # Scale by previous or next interval if offset < 0: beat_error[n] = offset[0] / previous_interval else: beat_error[n] = offset[0] / next_interval # Get indices of incorrect beats incorrect_beats = np.flatnonzero(np.abs(beat_error) > goto_threshold) # All beats are correct (first and last will be 0 so always correct) if incorrect_beats.shape[0] < 3: # Get the track of correct beats track = beat_error[incorrect_beats[0] + 1 : incorrect_beats[-1] - 1] goto_criteria = 1 else: # Get the track of maximal length track_len = np.max(np.diff(incorrect_beats)) track_start = np.flatnonzero(np.diff(incorrect_beats) == track_len)[0] # Is the track length at least 25% of the song? if track_len - 1 > 0.25 * (reference_beats.shape[0] - 2): goto_criteria = 1 start_beat = incorrect_beats[track_start] end_beat = incorrect_beats[track_start + 1] track = beat_error[start_beat : end_beat + 1] # If we have a track if goto_criteria: # Are mean and std of the track less than the required thresholds? if np.mean(np.abs(track)) < goto_mu and np.std(track, ddof=1) < goto_sigma: goto_criteria = 3 # If all criteria are met, score is 100%! return 1.0 * (goto_criteria == 3) def p_score(reference_beats, estimated_beats, p_score_threshold=0.2): """Get McKinney's P-score. Based on the autocorrelation of the reference and estimated beats Examples -------- >>> reference_beats = mir_eval.io.load_events('reference.txt') >>> reference_beats = mir_eval.beat.trim_beats(reference_beats) >>> estimated_beats = mir_eval.io.load_events('estimated.txt') >>> estimated_beats = mir_eval.beat.trim_beats(estimated_beats) >>> p_score = mir_eval.beat.p_score(reference_beats, estimated_beats) Parameters ---------- reference_beats : np.ndarray reference beat times, in seconds estimated_beats : np.ndarray query beat times, in seconds p_score_threshold : float Window size will be ``p_score_threshold*np.median(inter_annotation_intervals)``, (Default value = 0.2) Returns ------- correlation : float McKinney's P-score """ validate(reference_beats, estimated_beats) # Warn when only one beat is provided for either estimated or reference, # report a warning if reference_beats.size == 1: warnings.warn( "Only one reference beat was provided, so beat intervals" " cannot be computed." ) if estimated_beats.size == 1: warnings.warn( "Only one estimated beat was provided, so beat intervals" " cannot be computed." ) # When estimated or reference beats have <= 1 beats, can't compute the # metric, so return 0 if estimated_beats.size <= 1 or reference_beats.size <= 1: return 0.0 # Quantize beats to 10ms sampling_rate = int(1.0 / 0.010) # Shift beats so that the minimum in either sequence is zero offset = min(estimated_beats.min(), reference_beats.min()) estimated_beats = np.array(estimated_beats - offset) reference_beats = np.array(reference_beats - offset) # Get the largest time index end_point = np.int64( np.ceil(np.max([np.max(estimated_beats), np.max(reference_beats)])) ) # Make impulse trains with impulses at beat locations reference_train = np.zeros(end_point * sampling_rate + 1) beat_indices = np.ceil(reference_beats * sampling_rate).astype(np.int64) reference_train[beat_indices] = 1.0 estimated_train = np.zeros(end_point * sampling_rate + 1) beat_indices = np.ceil(estimated_beats * sampling_rate).astype(np.int64) estimated_train[beat_indices] = 1.0 # Window size to take the correlation over # defined as .2*median(inter-annotation-intervals) annotation_intervals = np.diff(np.flatnonzero(reference_train)) win_size = int(np.round(p_score_threshold * np.median(annotation_intervals))) # Get full correlation train_correlation = np.correlate(reference_train, estimated_train, "full") # Get the middle element - note we are rounding down on purpose here middle_lag = train_correlation.shape[0] // 2 # Truncate to only valid lags (those corresponding to the window) start = middle_lag - win_size end = middle_lag + win_size + 1 train_correlation = train_correlation[start:end] # Compute and return the P-score n_beats = np.max([estimated_beats.shape[0], reference_beats.shape[0]]) return np.sum(train_correlation) / n_beats def continuity( reference_beats, estimated_beats, continuity_phase_threshold=0.175, continuity_period_threshold=0.175, ): """Get metrics based on how much of the estimated beat sequence is continually correct. Examples -------- >>> reference_beats = mir_eval.io.load_events('reference.txt') >>> reference_beats = mir_eval.beat.trim_beats(reference_beats) >>> estimated_beats = mir_eval.io.load_events('estimated.txt') >>> estimated_beats = mir_eval.beat.trim_beats(estimated_beats) >>> CMLc, CMLt, AMLc, AMLt = mir_eval.beat.continuity(reference_beats, estimated_beats) Parameters ---------- reference_beats : np.ndarray reference beat times, in seconds estimated_beats : np.ndarray query beat times, in seconds continuity_phase_threshold : float Allowable ratio of how far is the estimated beat can be from the reference beat (Default value = 0.175) continuity_period_threshold : float Allowable distance between the inter-beat-interval and the inter-annotation-interval (Default value = 0.175) Returns ------- CMLc : float Correct metric level, continuous accuracy CMLt : float Correct metric level, total accuracy (continuity not required) AMLc : float Any metric level, continuous accuracy AMLt : float Any metric level, total accuracy (continuity not required) """ validate(reference_beats, estimated_beats) # Warn when only one beat is provided for either estimated or reference, # report a warning if reference_beats.size == 1: warnings.warn( "Only one reference beat was provided, so beat intervals" " cannot be computed." ) if estimated_beats.size == 1: warnings.warn( "Only one estimated beat was provided, so beat intervals" " cannot be computed." ) # When estimated or reference beats have <= 1 beats, can't compute the # metric, so return 0 if estimated_beats.size <= 1 or reference_beats.size <= 1: return 0.0, 0.0, 0.0, 0.0 # Accuracies for each variation continuous_accuracies = [] total_accuracies = [] # Get accuracy for each variation for reference_beats in _get_reference_beat_variations(reference_beats): # Annotations that have been used n_annotations = np.max([reference_beats.shape[0], estimated_beats.shape[0]]) used_annotations = np.zeros(n_annotations) # Whether or not we are continuous at any given point beat_successes = np.zeros(n_annotations) for m in range(estimated_beats.shape[0]): # Is this beat correct? beat_success = 0 # Get differences for this beat beat_differences = np.abs(estimated_beats[m] - reference_beats) # Get nearest annotation index nearest = np.argmin(beat_differences) min_difference = beat_differences[nearest] # Have we already used this annotation? if used_annotations[nearest] == 0: # Is this the first beat or first annotation? # If so, look forward. if m == 0 or nearest == 0: # How far is the estimated beat from the reference beat, # relative to the inter-annotation-interval? if nearest + 1 < reference_beats.shape[0]: reference_interval = ( reference_beats[nearest + 1] - reference_beats[nearest] ) else: # Special case when nearest + 1 is too large - use the # previous interval instead reference_interval = ( reference_beats[nearest] - reference_beats[nearest - 1] ) # Handle this special case when beats are not unique if reference_interval == 0: if min_difference == 0: phase = 1 else: phase = np.inf else: phase = np.abs(min_difference / reference_interval) # How close is the inter-beat-interval # to the inter-annotation-interval? if m + 1 < estimated_beats.shape[0]: estimated_interval = estimated_beats[m + 1] - estimated_beats[m] else: # Special case when m + 1 is too large - use the # previous interval estimated_interval = estimated_beats[m] - estimated_beats[m - 1] # Handle this special case when beats are not unique if reference_interval == 0: if estimated_interval == 0: period = 0 else: period = np.inf else: period = np.abs(1 - estimated_interval / reference_interval) if ( phase < continuity_phase_threshold and period < continuity_period_threshold ): # Set this annotation as used used_annotations[nearest] = 1 # This beat is matched beat_success = 1 # This beat/annotation is not the first else: # How far is the estimated beat from the reference beat, # relative to the inter-annotation-interval? reference_interval = ( reference_beats[nearest] - reference_beats[nearest - 1] ) phase = np.abs(min_difference / reference_interval) # How close is the inter-beat-interval # to the inter-annotation-interval? estimated_interval = estimated_beats[m] - estimated_beats[m - 1] reference_interval = ( reference_beats[nearest] - reference_beats[nearest - 1] ) period = np.abs(1 - estimated_interval / reference_interval) if ( phase < continuity_phase_threshold and period < continuity_period_threshold ): # Set this annotation as used used_annotations[nearest] = 1 # This beat is matched beat_success = 1 # Set whether this beat is matched or not beat_successes[m] = beat_success # Add 0s at the begnning and end # so that we at least find the beginning/end of the estimated beats beat_successes = np.append(np.append(0, beat_successes), 0) # Where is the beat not a match? beat_failures = np.nonzero(beat_successes == 0)[0] # Take out those zeros we added beat_successes = beat_successes[1:-1] # Get the continuous accuracy as the longest track of successful beats longest_track = np.max(np.diff(beat_failures)) - 1 continuous_accuracy = longest_track / (1.0 * beat_successes.shape[0]) continuous_accuracies.append(continuous_accuracy) # Get the total accuracy - all sequences total_accuracy = np.sum(beat_successes) / (1.0 * beat_successes.shape[0]) total_accuracies.append(total_accuracy) # Grab accuracy scores return ( continuous_accuracies[0], total_accuracies[0], np.max(continuous_accuracies), np.max(total_accuracies), ) def information_gain(reference_beats, estimated_beats, bins=41): """Get the information gain - K-L divergence of the beat error histogram to a uniform histogram Examples -------- >>> reference_beats = mir_eval.io.load_events('reference.txt') >>> reference_beats = mir_eval.beat.trim_beats(reference_beats) >>> estimated_beats = mir_eval.io.load_events('estimated.txt') >>> estimated_beats = mir_eval.beat.trim_beats(estimated_beats) >>> information_gain = mir_eval.beat.information_gain(reference_beats, estimated_beats) Parameters ---------- reference_beats : np.ndarray reference beat times, in seconds estimated_beats : np.ndarray query beat times, in seconds bins : int Number of bins in the beat error histogram (Default value = 41) Returns ------- information_gain_score : float Entropy of beat error histogram """ validate(reference_beats, estimated_beats) # If an even number of bins is provided, # there will be no bin centered at zero, so warn the user. if not bins % 2: warnings.warn( "bins parameter is even, " "so there will not be a bin centered at zero." ) # Warn when only one beat is provided for either estimated or reference, # report a warning if reference_beats.size == 1: warnings.warn( "Only one reference beat was provided, so beat intervals" " cannot be computed." ) if estimated_beats.size == 1: warnings.warn( "Only one estimated beat was provided, so beat intervals" " cannot be computed." ) # When estimated or reference beats have <= 1 beats, can't compute the # metric, so return 0 if estimated_beats.size <= 1 or reference_beats.size <= 1: return 0.0 # Get entropy for reference beats->estimated beats # and estimated beats->reference beats forward_entropy = _get_entropy(reference_beats, estimated_beats, bins) backward_entropy = _get_entropy(estimated_beats, reference_beats, bins) # Pick the larger of the entropies norm = np.log2(bins) if forward_entropy > backward_entropy: # Note that the beat evaluation toolbox does not normalize information_gain_score = (norm - forward_entropy) / norm else: information_gain_score = (norm - backward_entropy) / norm return information_gain_score def _get_entropy(reference_beats, estimated_beats, bins): """Compute the entropy of the beat error histogram. This is a helper function for the information gain metric, and needs to be run twice: once backwards, once forwards. Parameters ---------- reference_beats : np.ndarray reference beat times, in seconds estimated_beats : np.ndarray query beat times, in seconds bins : int Number of bins in the beat error histogram Returns ------- entropy : float Entropy of beat error histogram """ beat_error = np.zeros(estimated_beats.shape[0]) for n in range(estimated_beats.shape[0]): # Get index of closest annotation to this beat beat_distances = estimated_beats[n] - reference_beats closest_beat = np.argmin(np.abs(beat_distances)) absolute_error = beat_distances[closest_beat] # If the first annotation is closest... if closest_beat == 0: # Inter-annotation interval - space between first two beats interval = 0.5 * (reference_beats[1] - reference_beats[0]) # If last annotation is closest... if closest_beat == (reference_beats.shape[0] - 1): interval = 0.5 * (reference_beats[-1] - reference_beats[-2]) else: if absolute_error < 0: # Closest annotation is the one before the current beat # so look at previous inner-annotation-interval start = reference_beats[closest_beat] end = reference_beats[closest_beat - 1] interval = 0.5 * (start - end) else: # Closest annotation is the one after the current beat # so look at next inner-annotation-interval start = reference_beats[closest_beat + 1] end = reference_beats[closest_beat] interval = 0.5 * (start - end) # The actual error of this beat beat_error[n] = 0.5 * absolute_error / interval # Put beat errors in range (-.5, .5) beat_error = np.mod(beat_error + 0.5, -1) + 0.5 # Note these are slightly different the beat evaluation toolbox # (they are uniform) histogram_bin_edges = np.linspace(-0.5, 0.5, bins + 1) # Get the histogram raw_bin_values = np.histogram(beat_error, histogram_bin_edges)[0] # Turn into a proper probability distribution raw_bin_values = raw_bin_values / (1.0 * np.sum(raw_bin_values)) # Set zero-valued bins to 1 to make the entropy calculation well-behaved raw_bin_values[raw_bin_values == 0] = 1 # Calculate entropy return -np.sum(raw_bin_values * np.log2(raw_bin_values)) def evaluate(reference_beats, estimated_beats, **kwargs): """Compute all metrics for the given reference and estimated annotations. Examples -------- >>> reference_beats = mir_eval.io.load_events('reference.txt') >>> estimated_beats = mir_eval.io.load_events('estimated.txt') >>> scores = mir_eval.beat.evaluate(reference_beats, estimated_beats) Parameters ---------- reference_beats : np.ndarray Reference beat times, in seconds estimated_beats : np.ndarray Query beat times, in seconds **kwargs Additional keyword arguments which will be passed to the appropriate metric or preprocessing functions. Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. """ # Trim beat times at the beginning of the annotations reference_beats = util.filter_kwargs(trim_beats, reference_beats, **kwargs) estimated_beats = util.filter_kwargs(trim_beats, estimated_beats, **kwargs) # Now compute all the metrics scores = collections.OrderedDict() # F-Measure scores["F-measure"] = util.filter_kwargs( f_measure, reference_beats, estimated_beats, **kwargs ) # Cemgil scores["Cemgil"], scores["Cemgil Best Metric Level"] = util.filter_kwargs( cemgil, reference_beats, estimated_beats, **kwargs ) # Goto scores["Goto"] = util.filter_kwargs( goto, reference_beats, estimated_beats, **kwargs ) # P-Score scores["P-score"] = util.filter_kwargs( p_score, reference_beats, estimated_beats, **kwargs ) # Continuity metrics ( scores["Correct Metric Level Continuous"], scores["Correct Metric Level Total"], scores["Any Metric Level Continuous"], scores["Any Metric Level Total"], ) = util.filter_kwargs(continuity, reference_beats, estimated_beats, **kwargs) # Information gain scores["Information gain"] = util.filter_kwargs( information_gain, reference_beats, estimated_beats, **kwargs ) return scores mir_eval-0.8.2/mir_eval/chord.py000066400000000000000000001620401475740344600166070ustar00rootroot00000000000000r""" Chord estimation algorithms produce a list of intervals and labels which denote the chord being played over each timespan. They are evaluated by comparing the estimated chord labels to some reference, usually using a mapping to a chord subalphabet (e.g. minor and major chords only, all triads, etc.). There is no single 'right' way to compare two sequences of chord labels. Embracing this reality, every conventional comparison rule is provided. Comparisons are made over the different components of each chord (e.g. G:maj(6)/5): the root (G), the root-invariant active semitones as determined by the quality shorthand (maj) and scale degrees (6), and the bass interval (5). This submodule provides functions both for comparing a sequences of chord labels according to some chord subalphabet mapping and for using these comparisons to score a sequence of estimated chords against a reference. Conventions ----------- A sequence of chord labels is represented as a list of strings, where each label is the chord name based on the syntax of [#harte2010towards]_. Reference and estimated chord label sequences should be of the same length for comparison functions. When converting the chord string into its constituent parts, * Pitch class counting starts at C, e.g. C:0, D:2, E:4, F:5, etc. * Scale degree is represented as a string of the diatonic interval, relative to the root note, e.g. 'b6', '#5', or '7' * Bass intervals are represented as strings * Chord bitmaps are positional binary vectors indicating active pitch classes and may be absolute or relative depending on context in the code. If no chord is present at a given point in time, it should have the label 'N', which is defined in the variable ``mir_eval.chord.NO_CHORD``. Metrics ------- * :func:`mir_eval.chord.root`: Only compares the root of the chords. * :func:`mir_eval.chord.majmin`: Only compares major, minor, and "no chord" labels. * :func:`mir_eval.chord.majmin_inv`: Compares major/minor chords, with inversions. The bass note must exist in the triad. * :func:`mir_eval.chord.mirex`: A estimated chord is considered correct if it shares *at least* three pitch classes in common. * :func:`mir_eval.chord.thirds`: Chords are compared at the level of major or minor thirds (root and third), For example, both ('A:7', 'A:maj') and ('A:min', 'A:dim') are equivalent, as the third is major and minor in quality, respectively. * :func:`mir_eval.chord.thirds_inv`: Same as above, with inversions (bass relationships). * :func:`mir_eval.chord.triads`: Chords are considered at the level of triads (major, minor, augmented, diminished, suspended), meaning that, in addition to the root, the quality is only considered through #5th scale degree (for augmented chords). For example, ('A:7', 'A:maj') are equivalent, while ('A:min', 'A:dim') and ('A:aug', 'A:maj') are not. * :func:`mir_eval.chord.triads_inv`: Same as above, with inversions (bass relationships). * :func:`mir_eval.chord.tetrads`: Chords are considered at the level of the entire quality in closed voicing, i.e. spanning only a single octave; extended chords (9's, 11's and 13's) are rolled into a single octave with any upper voices included as extensions. For example, ('A:7', 'A:9') are equivalent but ('A:7', 'A:maj7') are not. * :func:`mir_eval.chord.tetrads_inv`: Same as above, with inversions (bass relationships). * :func:`mir_eval.chord.sevenths`: Compares according to MIREX "sevenths" rules; that is, only major, major seventh, seventh, minor, minor seventh and no chord labels are compared. * :func:`mir_eval.chord.sevenths_inv`: Same as above, with inversions (bass relationships). * :func:`mir_eval.chord.overseg`: Computes the level of over-segmentation between estimated and reference intervals. * :func:`mir_eval.chord.underseg`: Computes the level of under-segmentation between estimated and reference intervals. * :func:`mir_eval.chord.seg`: Computes the minimum of over- and under-segmentation between estimated and reference intervals. References ---------- .. [#harte2010towards] C. Harte. Towards Automatic Extraction of Harmony Information from Music Signals. PhD thesis, Queen Mary University of London, August 2010. """ import numpy as np import warnings import collections import re from mir_eval import util BITMAP_LENGTH = 12 NO_CHORD = "N" NO_CHORD_ENCODED = -1, np.array([0] * BITMAP_LENGTH), -1 X_CHORD = "X" X_CHORD_ENCODED = -1, np.array([-1] * BITMAP_LENGTH), -1 class InvalidChordException(Exception): r"""Exception class for suspect / invalid chord labels""" def __init__(self, message="", chord_label=None): self.message = message self.chord_label = chord_label self.name = self.__class__.__name__ super().__init__(message) # --- Chord Primitives --- def _pitch_classes(): r"""Map from pitch class (str) to semitone (int).""" pitch_classes = ["C", "D", "E", "F", "G", "A", "B"] semitones = [0, 2, 4, 5, 7, 9, 11] return {c: s for c, s in zip(pitch_classes, semitones)} def _scale_degrees(): r"""Map scale degrees (str) to semitones (int).""" degrees = ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13"] semitones = [0, 2, 4, 5, 7, 9, 11, 12, 14, 16, 17, 19, 21] return {d: s for d, s in zip(degrees, semitones)} # Maps pitch classes (strings) to semitone indexes (ints). PITCH_CLASSES = _pitch_classes() def pitch_class_to_semitone(pitch_class): r"""Convert a pitch class to semitone. Parameters ---------- pitch_class : str Spelling of a given pitch class, e.g. 'C#', 'Gbb' Returns ------- semitone : int Semitone value of the pitch class. """ semitone = 0 for idx, char in enumerate(pitch_class): if char == "#" and idx > 0: semitone += 1 elif char == "b" and idx > 0: semitone -= 1 elif idx == 0: semitone = PITCH_CLASSES.get(char) else: raise InvalidChordException( "Pitch class improperly formed: %s" % pitch_class ) return semitone % 12 # Maps scale degrees (strings) to semitone indexes (ints). SCALE_DEGREES = _scale_degrees() def scale_degree_to_semitone(scale_degree): r"""Convert a scale degree to semitone. Parameters ---------- scale_degree : str Spelling of a relative scale degree, e.g. 'b3', '7', '#5' Returns ------- semitone : int Relative semitone of the scale degree, wrapped to a single octave Raises ------ InvalidChordException if `scale_degree` is invalid. """ semitone = 0 offset = 0 if scale_degree.startswith("#"): offset = scale_degree.count("#") scale_degree = scale_degree.strip("#") elif scale_degree.startswith("b"): offset = -1 * scale_degree.count("b") scale_degree = scale_degree.strip("b") semitone = SCALE_DEGREES.get(scale_degree, None) if semitone is None: raise InvalidChordException( "Scale degree improperly formed: {}, expected one of {}.".format( scale_degree, list(SCALE_DEGREES.keys()) ) ) return semitone + offset def scale_degree_to_bitmap(scale_degree, modulo=False, length=BITMAP_LENGTH): """Create a bitmap representation of a scale degree. Note that values in the bitmap may be negative, indicating that the semitone is to be removed. Parameters ---------- scale_degree : str Spelling of a relative scale degree, e.g. 'b3', '7', '#5' modulo : bool, default=True If a scale degree exceeds the length of the bit-vector, modulo the scale degree back into the bit-vector; otherwise it is discarded. length : int, default=12 Length of the bit-vector to produce Returns ------- bitmap : np.ndarray, in [-1, 0, 1], len=`length` Bitmap representation of this scale degree. """ sign = 1 if scale_degree.startswith("*"): sign = -1 scale_degree = scale_degree.strip("*") edit_map = [0] * length sd_idx = scale_degree_to_semitone(scale_degree) if sd_idx < length or modulo: edit_map[sd_idx % length] = sign return np.array(edit_map) # Maps quality strings to bitmaps, corresponding to relative pitch class # semitones, i.e. vector[0] is the tonic. QUALITIES = { # 1 2 3 4 5 6 7 "maj": [1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0], "min": [1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0], "aug": [1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0], "dim": [1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0], "sus4": [1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0], "sus2": [1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0], "7": [1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0], "maj7": [1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1], "min7": [1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0], "minmaj7": [1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1], "maj6": [1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0], "min6": [1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0], "dim7": [1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0], "hdim7": [1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0], "maj9": [1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1], "min9": [1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0], "9": [1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0], "min11": [1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0], "11": [1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0], "maj13": [1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1], "min13": [1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0], "13": [1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0], "1": [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], "5": [1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0], "": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], } def quality_to_bitmap(quality): """Return the bitmap for a given quality. Parameters ---------- quality : str Chord quality name. Returns ------- bitmap : np.ndarray Bitmap representation of this quality (12-dim). """ if quality not in QUALITIES: raise InvalidChordException( "Unsupported chord quality shorthand: '%s' " "Did you mean to reduce extended chords?" % quality ) return np.array(QUALITIES[quality]) # Maps extended chord qualities to the subset above, translating additional # voicings to extensions as a set of scale degrees (strings). # TODO(ejhumphrey): Revisit how minmaj7's are mapped. This is how TMC did it, # but MMV handles it like a separate quality (rather than an add7). EXTENDED_QUALITY_REDUX = { "minmaj7": ("min", {"7"}), "maj9": ("maj7", {"9"}), "min9": ("min7", {"9"}), "9": ("7", {"9"}), "b9": ("7", {"b9"}), "#9": ("7", {"#9"}), "11": ("7", {"9", "11"}), "#11": ("7", {"9", "#11"}), "13": ("7", {"9", "11", "13"}), "b13": ("7", {"9", "11", "b13"}), "min11": ("min7", {"9", "11"}), "maj13": ("maj7", {"9", "11", "13"}), "min13": ("min7", {"9", "11", "13"}), } def reduce_extended_quality(quality): """Map an extended chord quality to a simpler one, moving upper voices to a set of scale degree extensions. Parameters ---------- quality : str Extended chord quality to reduce. Returns ------- base_quality : str New chord quality. extensions : set Scale degrees extensions for the quality. """ return EXTENDED_QUALITY_REDUX.get(quality, (quality, set())) # --- Chord Label Parsing --- # This monster regexp is pulled from the JAMS chord namespace, # which is in turn derived from the context-free grammar of # Harte et al., 2005. CHORD_RE = re.compile( r"""^((N|X)|(([A-G](b*|#*))((:(maj|min|dim|aug|1|5|sus2|sus4|maj6|min6|7|maj7|min7|dim7|hdim7|minmaj7|aug7|9|maj9|min9|11|maj11|min11|13|maj13|min13)(\((\*?((b*|#*)([1-9]|1[0-3]?))(,\*?((b*|#*)([1-9]|1[0-3]?)))*)\))?)|(:\((\*?((b*|#*)([1-9]|1[0-3]?))(,\*?((b*|#*)([1-9]|1[0-3]?)))*)\)))?((/((b*|#*)([1-9]|1[0-3]?)))?)?))$""" ) # nopep8 def validate_chord_label(chord_label): """Test for well-formedness of a chord label. Parameters ---------- chord_label : str Chord label to validate. """ if not CHORD_RE.match(chord_label): raise InvalidChordException("Invalid chord label: " "{}".format(chord_label)) pass def split(chord_label, reduce_extended_chords=False): """Parse a chord label into its four constituent parts: - root - quality shorthand - scale degrees - bass Note: Chords lacking quality AND interval information are major. - If a quality is specified, it is returned. - If an interval is specified WITHOUT a quality, the quality field is empty. Some examples:: 'C' -> ['C', 'maj', {}, '1'] 'G#:min(*b3,*5)/5' -> ['G#', 'min', {'*b3', '*5'}, '5'] 'A:(3)/6' -> ['A', '', {'3'}, '6'] Parameters ---------- chord_label : str A chord label. reduce_extended_chords : bool Whether to map the upper voicings of extended chords (9's, 11's, 13's) to semitone extensions. (Default value = False) Returns ------- chord_parts : list Split version of the chord label. """ chord_label = str(chord_label) validate_chord_label(chord_label) if chord_label == NO_CHORD: return [chord_label, "", set(), ""] bass = "1" if "/" in chord_label: chord_label, bass = chord_label.split("/") scale_degrees = set() omission = False if "(" in chord_label: chord_label, scale_degrees = chord_label.split("(") omission = "*" in scale_degrees scale_degrees = scale_degrees.strip(")") scale_degrees = {i.strip() for i in scale_degrees.split(",")} # Note: Chords lacking quality AND added interval information are major. # If a quality shorthand is specified, it is returned. # If an interval is specified WITHOUT a quality, the quality field is # empty. # Intervals specifying omissions MUST have a quality. if omission and ":" not in chord_label: raise InvalidChordException( "Intervals specifying omissions MUST have a quality." ) quality = "" if scale_degrees else "maj" if ":" in chord_label: chord_root, quality_name = chord_label.split(":") # Extended chords (with ":"s) may not explicitly have Major qualities, # so only overwrite the default if the string is not empty. if quality_name: quality = quality_name.lower() else: chord_root = chord_label if reduce_extended_chords: quality, addl_scale_degrees = reduce_extended_quality(quality) scale_degrees.update(addl_scale_degrees) return [chord_root, quality, scale_degrees, bass] def join(chord_root, quality="", extensions=None, bass=""): r"""Join the parts of a chord into a complete chord label. Parameters ---------- chord_root : str Root pitch class of the chord, e.g. 'C', 'Eb' quality : str Quality of the chord, e.g. 'maj', 'hdim7' (Default value = '') extensions : list Any added or absent scaled degrees for this chord, e.g. ['4', '\*3'] (Default value = None) bass : str Scale degree of the bass note, e.g. '5'. (Default value = '') Returns ------- chord_label : str A complete chord label. """ chord_label = chord_root if quality or extensions: chord_label += ":%s" % quality if extensions: chord_label += "(%s)" % ",".join(extensions) if bass and bass != "1": chord_label += "/%s" % bass validate_chord_label(chord_label) return chord_label # --- Chords to Numerical Representations --- def encode(chord_label, reduce_extended_chords=False, strict_bass_intervals=False): """Translate a chord label to numerical representations for evaluation. Parameters ---------- chord_label : str Chord label to encode. reduce_extended_chords : bool Whether to map the upper voicings of extended chords (9's, 11's, 13's) to semitone extensions. (Default value = False) strict_bass_intervals : bool Whether to require that the bass scale degree is present in the chord. (Default value = False) Returns ------- root_number : int Absolute semitone of the chord's root. semitone_bitmap : np.ndarray, dtype=int 12-dim vector of relative semitones in the chord spelling. bass_number : int Relative semitone of the chord's bass note, e.g. 0=root, 7=fifth, etc. """ if chord_label == NO_CHORD: return NO_CHORD_ENCODED if chord_label == X_CHORD: return X_CHORD_ENCODED chord_root, quality, scale_degrees, bass = split( chord_label, reduce_extended_chords=reduce_extended_chords ) root_number = pitch_class_to_semitone(chord_root) bass_number = scale_degree_to_semitone(bass) % 12 semitone_bitmap = quality_to_bitmap(quality) semitone_bitmap[0] = 1 for scale_degree in scale_degrees: semitone_bitmap += scale_degree_to_bitmap(scale_degree, reduce_extended_chords) semitone_bitmap = (semitone_bitmap > 0).astype(np.int64) if not semitone_bitmap[bass_number] and strict_bass_intervals: raise InvalidChordException( "Given bass scale degree is absent from this chord: " "%s" % chord_label, chord_label, ) else: semitone_bitmap[bass_number] = 1 return root_number, semitone_bitmap, bass_number def encode_many(chord_labels, reduce_extended_chords=False): """Translate a set of chord labels to numerical representations for sane evaluation. Parameters ---------- chord_labels : list Set of chord labels to encode. reduce_extended_chords : bool Whether to map the upper voicings of extended chords (9's, 11's, 13's) to semitone extensions. (Default value = False) Returns ------- root_number : np.ndarray, dtype=int Absolute semitone of the chord's root. interval_bitmap : np.ndarray, dtype=int 12-dim vector of relative semitones in the given chord quality. bass_number : np.ndarray, dtype=int Relative semitones of the chord's bass notes. """ num_items = len(chord_labels) roots, basses = np.zeros([2, num_items], dtype=np.int64) semitones = np.zeros([num_items, 12], dtype=np.int64) local_cache = dict() for i, label in enumerate(chord_labels): result = local_cache.get(label, None) if result is None: result = encode(label, reduce_extended_chords) local_cache[label] = result roots[i], semitones[i], basses[i] = result return roots, semitones, basses def rotate_bitmap_to_root(bitmap, chord_root): """Circularly shift a relative bitmap to its absolute pitch classes. For clarity, the best explanation is an example. Given 'G:Maj', the root and quality map are as follows:: root=5 quality=[1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0] # Relative chord shape After rotating to the root, the resulting bitmap becomes:: abs_quality = [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1] # G, B, and D Parameters ---------- bitmap : np.ndarray, shape=(12,) Bitmap of active notes, relative to the given root. chord_root : int Absolute pitch class number. Returns ------- bitmap : np.ndarray, shape=(12,) Absolute bitmap of active pitch classes. """ bitmap = np.asarray(bitmap) assert bitmap.ndim == 1, "Currently only 1D bitmaps are supported." idxs = list(np.nonzero(bitmap)) idxs[-1] = (idxs[-1] + chord_root) % 12 abs_bitmap = np.zeros_like(bitmap) abs_bitmap[tuple(idxs)] = 1 return abs_bitmap def rotate_bitmaps_to_roots(bitmaps, roots): """Circularly shift a relative bitmaps to absolute pitch classes. See :func:`rotate_bitmap_to_root` for more information. Parameters ---------- bitmaps : np.ndarray, shape=(N, 12) Bitmap of active notes, relative to the given root. roots : np.ndarray, shape=(N,) Absolute pitch class number. Returns ------- bitmap : np.ndarray, shape=(N, 12) Absolute bitmaps of active pitch classes. """ abs_bitmaps = [] for bitmap, chord_root in zip(bitmaps, roots): abs_bitmaps.append(rotate_bitmap_to_root(bitmap, chord_root)) return np.asarray(abs_bitmaps) # --- Comparison Routines --- def validate(reference_labels, estimated_labels): """Check that the input annotations to a comparison function look like valid chord labels. Parameters ---------- reference_labels : list, len=n Reference chord labels to score against. estimated_labels : list, len=n Estimated chord labels to score against. """ N = len(reference_labels) M = len(estimated_labels) if N != M: raise ValueError( "Chord comparison received different length lists: " "len(reference)=%d\tlen(estimates)=%d" % (N, M) ) for labels in [reference_labels, estimated_labels]: for chord_label in labels: validate_chord_label(chord_label) # When either label list is empty, warn the user if len(reference_labels) == 0: warnings.warn("Reference labels are empty") if len(estimated_labels) == 0: warnings.warn("Estimated labels are empty") def weighted_accuracy(comparisons, weights): """Compute the weighted accuracy of a list of chord comparisons. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> est_intervals, est_labels = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, ref_intervals.min(), ... ref_intervals.max(), mir_eval.chord.NO_CHORD, ... mir_eval.chord.NO_CHORD) >>> (intervals, ... ref_labels, ... est_labels) = mir_eval.util.merge_labeled_intervals( ... ref_intervals, ref_labels, est_intervals, est_labels) >>> durations = mir_eval.util.intervals_to_durations(intervals) >>> # Here, we're using the "thirds" function to compare labels >>> # but any of the comparison functions would work. >>> comparisons = mir_eval.chord.thirds(ref_labels, est_labels) >>> score = mir_eval.chord.weighted_accuracy(comparisons, durations) Parameters ---------- comparisons : np.ndarray List of chord comparison scores, in [0, 1] or -1 weights : np.ndarray Weights (not necessarily normalized) for each comparison. This can be a list of interval durations Returns ------- score : float Weighted accuracy """ N = len(comparisons) # There should be as many weights as comparisons if weights.shape[0] != N: raise ValueError( "weights and comparisons should be of the same" " length. len(weights) = {} but len(comparisons)" " = {}".format(weights.shape[0], N) ) if (weights < 0).any(): raise ValueError("Weights should all be positive.") if np.sum(weights) == 0: warnings.warn("No nonzero weights, returning 0") return 0 # Find all comparison scores which are valid valid_idx = comparisons >= 0 # If no comparable chords were provided, warn and return 0 if valid_idx.sum() == 0: warnings.warn( "No reference chords were comparable " "to estimated chords, returning 0." ) return 0 # Remove any uncomparable labels comparisons = comparisons[valid_idx] weights = weights[valid_idx] # Normalize the weights total_weight = float(np.sum(weights)) normalized_weights = np.asarray(weights, dtype=float) / total_weight # Score is the sum of all weighted comparisons return np.sum(comparisons * normalized_weights) def thirds(reference_labels, estimated_labels): """Compare chords along root & third relationships. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> est_intervals, est_labels = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, ref_intervals.min(), ... ref_intervals.max(), mir_eval.chord.NO_CHORD, ... mir_eval.chord.NO_CHORD) >>> (intervals, ... ref_labels, ... est_labels) = mir_eval.util.merge_labeled_intervals( ... ref_intervals, ref_labels, est_intervals, est_labels) >>> durations = mir_eval.util.intervals_to_durations(intervals) >>> comparisons = mir_eval.chord.thirds(ref_labels, est_labels) >>> score = mir_eval.chord.weighted_accuracy(comparisons, durations) Parameters ---------- reference_labels : list, len=n Reference chord labels to score against. estimated_labels : list, len=n Estimated chord labels to score against. Returns ------- comparison_scores : np.ndarray, shape=(n,), dtype=float Comparison scores, in [0.0, 1.0] """ validate(reference_labels, estimated_labels) ref_roots, ref_semitones = encode_many(reference_labels, False)[:2] est_roots, est_semitones = encode_many(estimated_labels, False)[:2] eq_roots = ref_roots == est_roots eq_thirds = ref_semitones[:, 3] == est_semitones[:, 3] comparison_scores = (eq_roots * eq_thirds).astype(np.float64) # Ignore 'X' chords comparison_scores[np.any(ref_semitones < 0, axis=1)] = -1.0 return comparison_scores def thirds_inv(reference_labels, estimated_labels): """Score chords along root, third, & bass relationships. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> est_intervals, est_labels = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, ref_intervals.min(), ... ref_intervals.max(), mir_eval.chord.NO_CHORD, ... mir_eval.chord.NO_CHORD) >>> (intervals, ... ref_labels, ... est_labels) = mir_eval.util.merge_labeled_intervals( ... ref_intervals, ref_labels, est_intervals, est_labels) >>> durations = mir_eval.util.intervals_to_durations(intervals) >>> comparisons = mir_eval.chord.thirds_inv(ref_labels, est_labels) >>> score = mir_eval.chord.weighted_accuracy(comparisons, durations) Parameters ---------- reference_labels : list, len=n Reference chord labels to score against. estimated_labels : list, len=n Estimated chord labels to score against. Returns ------- scores : np.ndarray, shape=(n,), dtype=float Comparison scores, in [0.0, 1.0] """ validate(reference_labels, estimated_labels) ref_roots, ref_semitones, ref_bass = encode_many(reference_labels, False) est_roots, est_semitones, est_bass = encode_many(estimated_labels, False) eq_root = ref_roots == est_roots eq_bass = ref_bass == est_bass eq_third = ref_semitones[:, 3] == est_semitones[:, 3] comparison_scores = (eq_root * eq_third * eq_bass).astype(np.float64) # Ignore 'X' chords comparison_scores[np.any(ref_semitones < 0, axis=1)] = -1.0 return comparison_scores def triads(reference_labels, estimated_labels): """Compare chords along triad (root & quality to #5) relationships. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> est_intervals, est_labels = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, ref_intervals.min(), ... ref_intervals.max(), mir_eval.chord.NO_CHORD, ... mir_eval.chord.NO_CHORD) >>> (intervals, ... ref_labels, ... est_labels) = mir_eval.util.merge_labeled_intervals( ... ref_intervals, ref_labels, est_intervals, est_labels) >>> durations = mir_eval.util.intervals_to_durations(intervals) >>> comparisons = mir_eval.chord.triads(ref_labels, est_labels) >>> score = mir_eval.chord.weighted_accuracy(comparisons, durations) Parameters ---------- reference_labels : list, len=n Reference chord labels to score against. estimated_labels : list, len=n Estimated chord labels to score against. Returns ------- comparison_scores : np.ndarray, shape=(n,), dtype=float Comparison scores, in [0.0, 1.0] """ validate(reference_labels, estimated_labels) ref_roots, ref_semitones = encode_many(reference_labels, False)[:2] est_roots, est_semitones = encode_many(estimated_labels, False)[:2] eq_roots = ref_roots == est_roots eq_semitones = np.all(np.equal(ref_semitones[:, :8], est_semitones[:, :8]), axis=1) comparison_scores = (eq_roots * eq_semitones).astype(np.float64) # Ignore 'X' chords comparison_scores[np.any(ref_semitones < 0, axis=1)] = -1.0 return comparison_scores def triads_inv(reference_labels, estimated_labels): """Score chords along triad (root, quality to #5, & bass) relationships. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> est_intervals, est_labels = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, ref_intervals.min(), ... ref_intervals.max(), mir_eval.chord.NO_CHORD, ... mir_eval.chord.NO_CHORD) >>> (intervals, ... ref_labels, ... est_labels) = mir_eval.util.merge_labeled_intervals( ... ref_intervals, ref_labels, est_intervals, est_labels) >>> durations = mir_eval.util.intervals_to_durations(intervals) >>> comparisons = mir_eval.chord.triads_inv(ref_labels, est_labels) >>> score = mir_eval.chord.weighted_accuracy(comparisons, durations) Parameters ---------- reference_labels : list, len=n Reference chord labels to score against. estimated_labels : list, len=n Estimated chord labels to score against. Returns ------- scores : np.ndarray, shape=(n,), dtype=float Comparison scores, in [0.0, 1.0] """ validate(reference_labels, estimated_labels) ref_roots, ref_semitones, ref_bass = encode_many(reference_labels, False) est_roots, est_semitones, est_bass = encode_many(estimated_labels, False) eq_roots = ref_roots == est_roots eq_basses = ref_bass == est_bass eq_semitones = np.all(np.equal(ref_semitones[:, :8], est_semitones[:, :8]), axis=1) comparison_scores = (eq_roots * eq_semitones * eq_basses).astype(np.float64) # Ignore 'X' chords comparison_scores[np.any(ref_semitones < 0, axis=1)] = -1.0 return comparison_scores def tetrads(reference_labels, estimated_labels): """Compare chords along tetrad (root & full quality) relationships. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> est_intervals, est_labels = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, ref_intervals.min(), ... ref_intervals.max(), mir_eval.chord.NO_CHORD, ... mir_eval.chord.NO_CHORD) >>> (intervals, ... ref_labels, ... est_labels) = mir_eval.util.merge_labeled_intervals( ... ref_intervals, ref_labels, est_intervals, est_labels) >>> durations = mir_eval.util.intervals_to_durations(intervals) >>> comparisons = mir_eval.chord.tetrads(ref_labels, est_labels) >>> score = mir_eval.chord.weighted_accuracy(comparisons, durations) Parameters ---------- reference_labels : list, len=n Reference chord labels to score against. estimated_labels : list, len=n Estimated chord labels to score against. Returns ------- comparison_scores : np.ndarray, shape=(n,), dtype=float Comparison scores, in [0.0, 1.0] """ validate(reference_labels, estimated_labels) ref_roots, ref_semitones = encode_many(reference_labels, False)[:2] est_roots, est_semitones = encode_many(estimated_labels, False)[:2] eq_roots = ref_roots == est_roots eq_semitones = np.all(np.equal(ref_semitones, est_semitones), axis=1) comparison_scores = (eq_roots * eq_semitones).astype(np.float64) # Ignore 'X' chords comparison_scores[np.any(ref_semitones < 0, axis=1)] = -1.0 return comparison_scores def tetrads_inv(reference_labels, estimated_labels): """Compare chords along tetrad (root, full quality, & bass) relationships. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> est_intervals, est_labels = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, ref_intervals.min(), ... ref_intervals.max(), mir_eval.chord.NO_CHORD, ... mir_eval.chord.NO_CHORD) >>> (intervals, ... ref_labels, ... est_labels) = mir_eval.util.merge_labeled_intervals( ... ref_intervals, ref_labels, est_intervals, est_labels) >>> durations = mir_eval.util.intervals_to_durations(intervals) >>> comparisons = mir_eval.chord.tetrads_inv(ref_labels, est_labels) >>> score = mir_eval.chord.weighted_accuracy(comparisons, durations) Parameters ---------- reference_labels : list, len=n Reference chord labels to score against. estimated_labels : list, len=n Estimated chord labels to score against. Returns ------- comparison_scores : np.ndarray, shape=(n,), dtype=float Comparison scores, in [0.0, 1.0] """ validate(reference_labels, estimated_labels) ref_roots, ref_semitones, ref_bass = encode_many(reference_labels, False) est_roots, est_semitones, est_bass = encode_many(estimated_labels, False) eq_roots = ref_roots == est_roots eq_basses = ref_bass == est_bass eq_semitones = np.all(np.equal(ref_semitones, est_semitones), axis=1) comparison_scores = (eq_roots * eq_semitones * eq_basses).astype(np.float64) # Ignore 'X' chords comparison_scores[np.any(ref_semitones < 0, axis=1)] = -1.0 return comparison_scores def root(reference_labels, estimated_labels): """Compare chords according to roots. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> est_intervals, est_labels = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, ref_intervals.min(), ... ref_intervals.max(), mir_eval.chord.NO_CHORD, ... mir_eval.chord.NO_CHORD) >>> (intervals, ... ref_labels, ... est_labels) = mir_eval.util.merge_labeled_intervals( ... ref_intervals, ref_labels, est_intervals, est_labels) >>> durations = mir_eval.util.intervals_to_durations(intervals) >>> comparisons = mir_eval.chord.root(ref_labels, est_labels) >>> score = mir_eval.chord.weighted_accuracy(comparisons, durations) Parameters ---------- reference_labels : list, len=n Reference chord labels to score against. estimated_labels : list, len=n Estimated chord labels to score against. Returns ------- comparison_scores : np.ndarray, shape=(n,), dtype=float Comparison scores, in [0.0, 1.0], or -1 if the comparison is out of gamut. """ validate(reference_labels, estimated_labels) ref_roots, ref_semitones = encode_many(reference_labels, False)[:2] est_roots = encode_many(estimated_labels, False)[0] comparison_scores = (ref_roots == est_roots).astype(np.float64) # Ignore 'X' chords comparison_scores[np.any(ref_semitones < 0, axis=1)] = -1.0 return comparison_scores def mirex(reference_labels, estimated_labels): """Compare chords along MIREX rules. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> est_intervals, est_labels = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, ref_intervals.min(), ... ref_intervals.max(), mir_eval.chord.NO_CHORD, ... mir_eval.chord.NO_CHORD) >>> (intervals, ... ref_labels, ... est_labels) = mir_eval.util.merge_labeled_intervals( ... ref_intervals, ref_labels, est_intervals, est_labels) >>> durations = mir_eval.util.intervals_to_durations(intervals) >>> comparisons = mir_eval.chord.mirex(ref_labels, est_labels) >>> score = mir_eval.chord.weighted_accuracy(comparisons, durations) Parameters ---------- reference_labels : list, len=n Reference chord labels to score against. estimated_labels : list, len=n Estimated chord labels to score against. Returns ------- comparison_scores : np.ndarray, shape=(n,), dtype=float Comparison scores, in [0.0, 1.0] """ validate(reference_labels, estimated_labels) # TODO(?): Should this be an argument? min_intersection = 3 ref_data = encode_many(reference_labels, False) ref_chroma = rotate_bitmaps_to_roots(ref_data[1], ref_data[0]) est_data = encode_many(estimated_labels, False) est_chroma = rotate_bitmaps_to_roots(est_data[1], est_data[0]) eq_chroma = (ref_chroma * est_chroma).sum(axis=-1) # Chroma matching for set bits comparison_scores = (eq_chroma >= min_intersection).astype(np.float64) # No-chord matching; match -1 roots, SKIP_CHORDS dropped next no_root = np.logical_and(ref_data[0] == -1, est_data[0] == -1) comparison_scores[no_root] = 1.0 # Skip chords where the number of active semitones `n` is # 0 < n < `min_intersection`. ref_semitone_count = (ref_data[1] > 0).sum(axis=1) skip_idx = np.logical_and( ref_semitone_count > 0, ref_semitone_count < min_intersection ) # Also ignore 'X' chords. np.logical_or(skip_idx, np.any(ref_data[1] < 0, axis=1), skip_idx) comparison_scores[skip_idx] = -1.0 return comparison_scores def majmin(reference_labels, estimated_labels): """Compare chords along major-minor rules. Chords with qualities outside Major/minor/no-chord are ignored. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> est_intervals, est_labels = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, ref_intervals.min(), ... ref_intervals.max(), mir_eval.chord.NO_CHORD, ... mir_eval.chord.NO_CHORD) >>> (intervals, ... ref_labels, ... est_labels) = mir_eval.util.merge_labeled_intervals( ... ref_intervals, ref_labels, est_intervals, est_labels) >>> durations = mir_eval.util.intervals_to_durations(intervals) >>> comparisons = mir_eval.chord.majmin(ref_labels, est_labels) >>> score = mir_eval.chord.weighted_accuracy(comparisons, durations) Parameters ---------- reference_labels : list, len=n Reference chord labels to score against. estimated_labels : list, len=n Estimated chord labels to score against. Returns ------- comparison_scores : np.ndarray, shape=(n,), dtype=float Comparison scores, in [0.0, 1.0], or -1 if the comparison is out of gamut. """ validate(reference_labels, estimated_labels) maj_semitones = np.array(QUALITIES["maj"][:8]) min_semitones = np.array(QUALITIES["min"][:8]) ref_roots, ref_semitones, _ = encode_many(reference_labels, False) est_roots, est_semitones, _ = encode_many(estimated_labels, False) eq_root = ref_roots == est_roots eq_quality = np.all(np.equal(ref_semitones[:, :8], est_semitones[:, :8]), axis=1) comparison_scores = (eq_root * eq_quality).astype(np.float64) # Test for Major / Minor / No-chord is_maj = np.all(np.equal(ref_semitones[:, :8], maj_semitones), axis=1) is_min = np.all(np.equal(ref_semitones[:, :8], min_semitones), axis=1) is_none = np.logical_and(ref_roots < 0, np.all(ref_semitones == 0, axis=1)) # Only keep majors, minors, and Nones (NOR) comparison_scores[(is_maj + is_min + is_none) == 0] = -1 # Disable chords that disrupt this quality (apparently) # ref_voicing = np.all(np.equal(ref_qualities[:, :8], # ref_notes[:, :8]), axis=1) # comparison_scores[ref_voicing == 0] = -1 # est_voicing = np.all(np.equal(est_qualities[:, :8], # est_notes[:, :8]), axis=1) # comparison_scores[est_voicing == 0] = -1 return comparison_scores def majmin_inv(reference_labels, estimated_labels): """Compare chords along major-minor rules, with inversions. Chords with qualities outside Major/minor/no-chord are ignored, and the bass note must exist in the triad (bass in [1, 3, 5]). Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> est_intervals, est_labels = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, ref_intervals.min(), ... ref_intervals.max(), mir_eval.chord.NO_CHORD, ... mir_eval.chord.NO_CHORD) >>> (intervals, ... ref_labels, ... est_labels) = mir_eval.util.merge_labeled_intervals( ... ref_intervals, ref_labels, est_intervals, est_labels) >>> durations = mir_eval.util.intervals_to_durations(intervals) >>> comparisons = mir_eval.chord.majmin_inv(ref_labels, est_labels) >>> score = mir_eval.chord.weighted_accuracy(comparisons, durations) Parameters ---------- reference_labels : list, len=n Reference chord labels to score against. estimated_labels : list, len=n Estimated chord labels to score against. Returns ------- comparison_scores : np.ndarray, shape=(n,), dtype=float Comparison scores, in [0.0, 1.0], or -1 if the comparison is out of gamut. """ validate(reference_labels, estimated_labels) maj_semitones = np.array(QUALITIES["maj"][:8]) min_semitones = np.array(QUALITIES["min"][:8]) ref_roots, ref_semitones, ref_bass = encode_many(reference_labels, False) est_roots, est_semitones, est_bass = encode_many(estimated_labels, False) eq_root_bass = (ref_roots == est_roots) * (ref_bass == est_bass) eq_semitones = np.all(np.equal(ref_semitones[:, :8], est_semitones[:, :8]), axis=1) comparison_scores = (eq_root_bass * eq_semitones).astype(np.float64) # Test for Major / Minor / No-chord is_maj = np.all(np.equal(ref_semitones[:, :8], maj_semitones), axis=1) is_min = np.all(np.equal(ref_semitones[:, :8], min_semitones), axis=1) is_none = np.logical_and(ref_roots < 0, np.all(ref_semitones == 0, axis=1)) # Only keep majors, minors, and Nones (NOR) comparison_scores[(is_maj + is_min + is_none) == 0] = -1 # Disable inversions that are not part of the quality valid_inversion = np.ones(ref_bass.shape, dtype=bool) bass_idx = ref_bass >= 0 valid_inversion[bass_idx] = ref_semitones[bass_idx, ref_bass[bass_idx]] comparison_scores[valid_inversion == 0] = -1 return comparison_scores def sevenths(reference_labels, estimated_labels): """Compare chords along MIREX 'sevenths' rules. Chords with qualities outside [maj, maj7, 7, min, min7, N] are ignored. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> est_intervals, est_labels = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, ref_intervals.min(), ... ref_intervals.max(), mir_eval.chord.NO_CHORD, ... mir_eval.chord.NO_CHORD) >>> (intervals, ... ref_labels, ... est_labels) = mir_eval.util.merge_labeled_intervals( ... ref_intervals, ref_labels, est_intervals, est_labels) >>> durations = mir_eval.util.intervals_to_durations(intervals) >>> comparisons = mir_eval.chord.sevenths(ref_labels, est_labels) >>> score = mir_eval.chord.weighted_accuracy(comparisons, durations) Parameters ---------- reference_labels : list, len=n Reference chord labels to score against. estimated_labels : list, len=n Estimated chord labels to score against. Returns ------- comparison_scores : np.ndarray, shape=(n,), dtype=float Comparison scores, in [0.0, 1.0], or -1 if the comparison is out of gamut. """ validate(reference_labels, estimated_labels) seventh_qualities = ["maj", "min", "maj7", "7", "min7", ""] valid_semitones = np.array([QUALITIES[name] for name in seventh_qualities]) ref_roots, ref_semitones = encode_many(reference_labels, False)[:2] est_roots, est_semitones = encode_many(estimated_labels, False)[:2] eq_root = ref_roots == est_roots eq_semitones = np.all(np.equal(ref_semitones, est_semitones), axis=1) comparison_scores = (eq_root * eq_semitones).astype(np.float64) # Test for reference chord inclusion is_valid = np.array( [ np.all(np.equal(ref_semitones, semitones), axis=1) for semitones in valid_semitones ] ) # Drop if NOR comparison_scores[np.sum(is_valid, axis=0) == 0] = -1 return comparison_scores def sevenths_inv(reference_labels, estimated_labels): """Compare chords along MIREX 'sevenths' rules. Chords with qualities outside [maj, maj7, 7, min, min7, N] are ignored. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> est_intervals, est_labels = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, ref_intervals.min(), ... ref_intervals.max(), mir_eval.chord.NO_CHORD, ... mir_eval.chord.NO_CHORD) >>> (intervals, ... ref_labels, ... est_labels) = mir_eval.util.merge_labeled_intervals( ... ref_intervals, ref_labels, est_intervals, est_labels) >>> durations = mir_eval.util.intervals_to_durations(intervals) >>> comparisons = mir_eval.chord.sevenths_inv(ref_labels, est_labels) >>> score = mir_eval.chord.weighted_accuracy(comparisons, durations) Parameters ---------- reference_labels : list, len=n Reference chord labels to score against. estimated_labels : list, len=n Estimated chord labels to score against. Returns ------- comparison_scores : np.ndarray, shape=(n,), dtype=float Comparison scores, in [0.0, 1.0], or -1 if the comparison is out of gamut. """ validate(reference_labels, estimated_labels) seventh_qualities = ["maj", "min", "maj7", "7", "min7", ""] valid_semitones = np.array([QUALITIES[name] for name in seventh_qualities]) ref_roots, ref_semitones, ref_basses = encode_many(reference_labels, False) est_roots, est_semitones, est_basses = encode_many(estimated_labels, False) eq_roots_basses = (ref_roots == est_roots) * (ref_basses == est_basses) eq_semitones = np.all(np.equal(ref_semitones, est_semitones), axis=1) comparison_scores = (eq_roots_basses * eq_semitones).astype(np.float64) # Test for Major / Minor / No-chord is_valid = np.array( [ np.all(np.equal(ref_semitones, semitones), axis=1) for semitones in valid_semitones ] ) comparison_scores[np.sum(is_valid, axis=0) == 0] = -1 # Disable inversions that are not part of the quality valid_inversion = np.ones(ref_basses.shape, dtype=bool) bass_idx = ref_basses >= 0 valid_inversion[bass_idx] = ref_semitones[bass_idx, ref_basses[bass_idx]] comparison_scores[valid_inversion == 0] = -1 return comparison_scores def directional_hamming_distance(reference_intervals, estimated_intervals): """Compute the directional hamming distance between reference and estimated intervals as defined by [#harte2010towards]_ and used for MIREX 'OverSeg', 'UnderSeg' and 'MeanSeg' measures. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> overseg = 1 - mir_eval.chord.directional_hamming_distance( ... ref_intervals, est_intervals) >>> underseg = 1 - mir_eval.chord.directional_hamming_distance( ... est_intervals, ref_intervals) >>> seg = min(overseg, underseg) Parameters ---------- reference_intervals : np.ndarray, shape=(n, 2), dtype=float Reference chord intervals to score against. estimated_intervals : np.ndarray, shape=(m, 2), dtype=float Estimated chord intervals to score against. Returns ------- directional hamming distance : float directional hamming distance between reference intervals and estimated intervals. """ util.validate_intervals(estimated_intervals) util.validate_intervals(reference_intervals) # make sure chord intervals do not overlap if ( len(reference_intervals) > 1 and (reference_intervals[:-1, 1] > reference_intervals[1:, 0]).any() ): raise ValueError("Chord Intervals must not overlap") est_ts = np.unique(estimated_intervals.flatten()) seg = 0.0 for start, end in reference_intervals: dur = end - start between_start_end = est_ts[(est_ts >= start) & (est_ts < end)] seg_ts = np.hstack([start, between_start_end, end]) seg += dur - np.diff(seg_ts).max() return seg / (reference_intervals[-1, 1] - reference_intervals[0, 0]) def overseg(reference_intervals, estimated_intervals): """Compute the MIREX 'OverSeg' score. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> score = mir_eval.chord.overseg(ref_intervals, est_intervals) Parameters ---------- reference_intervals : np.ndarray, shape=(n, 2), dtype=float Reference chord intervals to score against. estimated_intervals : np.ndarray, shape=(m, 2), dtype=float Estimated chord intervals to score against. Returns ------- oversegmentation score : float Comparison score, in [0.0, 1.0], where 1.0 means no oversegmentation. """ return 1 - directional_hamming_distance(reference_intervals, estimated_intervals) def underseg(reference_intervals, estimated_intervals): """Compute the MIREX 'UnderSeg' score. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> score = mir_eval.chord.underseg(ref_intervals, est_intervals) Parameters ---------- reference_intervals : np.ndarray, shape=(n, 2), dtype=float Reference chord intervals to score against. estimated_intervals : np.ndarray, shape=(m, 2), dtype=float Estimated chord intervals to score against. Returns ------- undersegmentation score : float Comparison score, in [0.0, 1.0], where 1.0 means no undersegmentation. """ return 1 - directional_hamming_distance(estimated_intervals, reference_intervals) def seg(reference_intervals, estimated_intervals): """Compute the MIREX 'MeanSeg' score. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> score = mir_eval.chord.seg(ref_intervals, est_intervals) Parameters ---------- reference_intervals : np.ndarray, shape=(n, 2), dtype=float Reference chord intervals to score against. estimated_intervals : np.ndarray, shape=(m, 2), dtype=float Estimated chord intervals to score against. Returns ------- segmentation score : float Comparison score, in [0.0, 1.0], where 1.0 means perfect segmentation. """ return min( underseg(reference_intervals, estimated_intervals), overseg(reference_intervals, estimated_intervals), ) def merge_chord_intervals(intervals, labels): """ Merge consecutive chord intervals if they represent the same chord. Parameters ---------- intervals : np.ndarray, shape=(n, 2), dtype=float Chord intervals to be merged, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. labels : list, shape=(n,) Chord labels to be merged, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. Returns ------- merged_ivs : np.ndarray, shape=(k, 2), dtype=float Merged chord intervals, k <= n """ roots, semitones, basses = encode_many(labels, True) merged_ivs = [] prev_rt = None prev_st = None prev_ba = None for s, e, rt, st, ba in zip( intervals[:, 0], intervals[:, 1], roots, semitones, basses ): if rt != prev_rt or (st != prev_st).any() or ba != prev_ba: prev_rt, prev_st, prev_ba = rt, st, ba merged_ivs.append([s, e]) else: merged_ivs[-1][-1] = e return np.array(merged_ivs) def evaluate(ref_intervals, ref_labels, est_intervals, est_labels, **kwargs): """Compute weighted accuracy for all comparison functions for the given reference and estimated annotations. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> scores = mir_eval.chord.evaluate(ref_intervals, ref_labels, ... est_intervals, est_labels) Parameters ---------- ref_intervals : np.ndarray, shape=(n, 2) Reference chord intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. ref_labels : list, shape=(n,) reference chord labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. est_intervals : np.ndarray, shape=(m, 2) estimated chord intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. est_labels : list, shape=(m,) estimated chord labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. **kwargs Additional keyword arguments which will be passed to the appropriate metric or preprocessing functions. Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. """ # Append or crop estimated intervals so their span is the same as reference est_intervals, est_labels = util.adjust_intervals( est_intervals, est_labels, ref_intervals.min(), ref_intervals.max(), NO_CHORD, NO_CHORD, ) # use merged intervals for segmentation evaluation merged_ref_intervals = merge_chord_intervals(ref_intervals, ref_labels) merged_est_intervals = merge_chord_intervals(est_intervals, est_labels) # Adjust the labels so that they span the same intervals intervals, ref_labels, est_labels = util.merge_labeled_intervals( ref_intervals, ref_labels, est_intervals, est_labels ) # Convert intervals to durations (used as weights) durations = util.intervals_to_durations(intervals) # Store scores for each comparison function scores = collections.OrderedDict() scores["thirds"] = weighted_accuracy(thirds(ref_labels, est_labels), durations) scores["thirds_inv"] = weighted_accuracy( thirds_inv(ref_labels, est_labels), durations ) scores["triads"] = weighted_accuracy(triads(ref_labels, est_labels), durations) scores["triads_inv"] = weighted_accuracy( triads_inv(ref_labels, est_labels), durations ) scores["tetrads"] = weighted_accuracy(tetrads(ref_labels, est_labels), durations) scores["tetrads_inv"] = weighted_accuracy( tetrads_inv(ref_labels, est_labels), durations ) scores["root"] = weighted_accuracy(root(ref_labels, est_labels), durations) scores["mirex"] = weighted_accuracy(mirex(ref_labels, est_labels), durations) scores["majmin"] = weighted_accuracy(majmin(ref_labels, est_labels), durations) scores["majmin_inv"] = weighted_accuracy( majmin_inv(ref_labels, est_labels), durations ) scores["sevenths"] = weighted_accuracy(sevenths(ref_labels, est_labels), durations) scores["sevenths_inv"] = weighted_accuracy( sevenths_inv(ref_labels, est_labels), durations ) scores["underseg"] = underseg(merged_ref_intervals, merged_est_intervals) scores["overseg"] = overseg(merged_ref_intervals, merged_est_intervals) scores["seg"] = min(scores["overseg"], scores["underseg"]) return scores mir_eval-0.8.2/mir_eval/display.py000066400000000000000000000740461475740344600171650ustar00rootroot00000000000000"""Display functions""" from collections import defaultdict from weakref import WeakKeyDictionary import numpy as np from scipy.signal import spectrogram import matplotlib as mpl from matplotlib.patches import Rectangle from matplotlib.ticker import FuncFormatter, MultipleLocator from matplotlib.ticker import Formatter from matplotlib.colors import LinearSegmentedColormap, LogNorm, ColorConverter from matplotlib.transforms import Bbox, TransformedBbox from .melody import freq_to_voicing from .util import midi_to_hz, hz_to_midi # This dictionary is used to track mir_eval-specific attributes # attached to matplotlib axes __AXMAP = WeakKeyDictionary() def __get_axes(ax=None, fig=None): """Get or construct the target axes object for a new plot. Parameters ---------- ax : matplotlib.pyplot.axes, optional If provided, return this axes object directly. fig : matplotlib.figure.Figure, optional The figure to query for axes. By default, uses the current figure `plt.gcf()`. Returns ------- ax : matplotlib.pyplot.axes An axis handle on which to draw the segmentation. If none is provided, a new set of axes is created. new_axes : bool If `True`, the axis object was newly constructed. If `False`, the axis object already existed. """ new_axes = False if ax is None: if fig is None: import matplotlib.pyplot as plt fig = plt.gcf() if not fig.get_axes(): new_axes = True ax = fig.gca() # Create a storage bucket for this axes in case we need it if ax not in __AXMAP: __AXMAP[ax] = dict() return ax, new_axes def segments( intervals, labels, base=None, height=None, text=False, text_kw=None, ax=None, prop_cycle=None, **kwargs, ): """Plot a segmentation as a set of disjoint rectangles. Parameters ---------- intervals : np.ndarray, shape=(n, 2) segment intervals, in the format returned by :func:`mir_eval.io.load_intervals` or :func:`mir_eval.io.load_labeled_intervals`. labels : list, shape=(n,) reference segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. base : number The vertical position of the base of the rectangles. By default, this will be the bottom of the plot. height : number The height of the rectangles. By default, this will be the top of the plot (minus ``base``). .. note:: If either `base` or `height` are provided, both must be provided. text : bool If true, each segment's label is displayed in its upper-left corner text_kw : dict If ``text == True``, the properties of the text object can be specified here. See ``matplotlib.pyplot.Text`` for valid parameters ax : matplotlib.pyplot.axes An axis handle on which to draw the segmentation. If none is provided, a new set of axes is created. prop_cycle : cycle.Cycler An optional property cycle object to specify style properties. If not provided, the default property cycler will be retrieved from matplotlib. **kwargs Additional keyword arguments to pass to ``matplotlib.patches.Rectangle``. Returns ------- ax : matplotlib.pyplot.axes._subplots.AxesSubplot A handle to the (possibly constructed) plot axes """ if text_kw is None: text_kw = dict() text_kw.setdefault("va", "top") text_kw.setdefault("clip_on", True) text_kw.setdefault("bbox", dict(boxstyle="round", facecolor="white")) # Make sure we have a numpy array intervals = np.atleast_2d(intervals) seg_def_style = dict(linewidth=1) ax, new_axes = __get_axes(ax=ax) if prop_cycle is None: __AXMAP[ax].setdefault("prop_cycle", mpl.rcParams["axes.prop_cycle"]) __AXMAP[ax].setdefault("prop_iter", iter(mpl.rcParams["axes.prop_cycle"])) elif "prop_iter" not in __AXMAP[ax]: __AXMAP[ax]["prop_cycle"] = prop_cycle __AXMAP[ax]["prop_iter"] = iter(prop_cycle) prop_cycle = __AXMAP[ax]["prop_cycle"] prop_iter = __AXMAP[ax]["prop_iter"] if new_axes: ax.set_yticks([]) if base is None and height is None: # If neither are provided, we'll use axes coordinates to span the figure base, height = 0, 1 transform = ax.get_xaxis_transform() elif base is not None and height is not None: # If both are provided, we'll use data coordinates transform = None else: raise ValueError("When specifying base or height, both must be provided.") seg_map = dict() for lab in labels: if lab in seg_map: continue try: properties = next(prop_iter) except StopIteration: prop_iter = iter(prop_cycle) __AXMAP[ax]["prop_iter"] = prop_iter properties = next(prop_iter) style = { k: v for k, v in properties.items() if k in ["color", "facecolor", "edgecolor", "linewidth"] } # Swap color -> facecolor here so we preserve edgecolor on rects style.setdefault("facecolor", style["color"]) style.pop("color", None) seg_map[lab] = seg_def_style.copy() seg_map[lab].update(style) seg_map[lab].update(kwargs) seg_map[lab]["label"] = lab for ival, lab in zip(intervals, labels): rect = ax.axvspan(ival[0], ival[1], ymin=base, ymax=height, **seg_map[lab]) seg_map[lab].pop("label", None) if text: ann = ax.annotate( lab, xy=(ival[0], height), xycoords=transform, xytext=(8, -10), textcoords="offset points", **text_kw, ) ann.set_clip_path(rect) return ax def labeled_intervals( intervals, labels, label_set=None, base=None, height=None, extend_labels=True, ax=None, tick=True, prop_cycle=None, **kwargs, ): """Plot labeled intervals with each label on its own row. Parameters ---------- intervals : np.ndarray, shape=(n, 2) segment intervals, in the format returned by :func:`mir_eval.io.load_intervals` or :func:`mir_eval.io.load_labeled_intervals`. labels : list, shape=(n,) reference segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. label_set : list An (ordered) list of labels to determine the plotting order. If not provided, the labels will be inferred from ``ax.get_yticklabels()``. If no ``yticklabels`` exist, then the sorted set of unique values in ``labels`` is taken as the label set. base : np.ndarray, shape=(n,), optional Vertical positions of each label. By default, labels are positioned at integers ``np.arange(len(labels))``. height : scalar or np.ndarray, shape=(n,), optional Height for each label. If scalar, the same value is applied to all labels. By default, each label has ``height=1``. extend_labels : bool If ``False``, only values of ``labels`` that also exist in ``label_set`` will be shown. If ``True``, all labels are shown, with those in `labels` but not in `label_set` appended to the top of the plot. A horizontal line is drawn to indicate the separation between values in or out of ``label_set``. ax : matplotlib.pyplot.axes An axis handle on which to draw the intervals. If none is provided, a new set of axes is created. tick : bool If ``True``, sets tick positions and labels on the y-axis. prop_cycle : cycle.Cycler An optional property cycle object to specify style properties. If not provided, the default property cycler will be retrieved from matplotlib. **kwargs Additional keyword arguments to pass to `matplotlib.collection.PolyCollection`. Returns ------- ax : matplotlib.pyplot.axes._subplots.AxesSubplot A handle to the (possibly constructed) plot axes """ # Get the axes handle ax, new_axes = __get_axes(ax=ax) if prop_cycle is None: __AXMAP[ax].setdefault("prop_cycle", mpl.rcParams["axes.prop_cycle"]) __AXMAP[ax].setdefault("prop_iter", iter(mpl.rcParams["axes.prop_cycle"])) elif "prop_iter" not in __AXMAP[ax]: __AXMAP[ax]["prop_cycle"] = prop_cycle __AXMAP[ax]["prop_iter"] = iter(prop_cycle) prop_cycle = __AXMAP[ax]["prop_cycle"] prop_iter = __AXMAP[ax]["prop_iter"] # Make sure we have a numpy array intervals = np.atleast_2d(intervals) if label_set is None: # If we have non-empty pre-existing tick labels, use them # If none of the label strings have content, treat it as empty label_set = __AXMAP[ax].get("labels", []) else: label_set = list(label_set) # Put additional labels at the end, in order extended = False if extend_labels: ticks = label_set + sorted(set(labels) - set(label_set)) if ticks != label_set and len(label_set) > 0: extended = True elif label_set: ticks = label_set else: ticks = sorted(set(labels)) # Push the ticks up into the axmap __AXMAP[ax]["labels"] = ticks style = dict(linewidth=1) try: properties = next(prop_iter) except StopIteration: prop_iter = iter(prop_cycle) __AXMAP[ax]["prop_iter"] = prop_iter properties = next(prop_iter) style = { k: v for k, v in properties.items() if k in ["color", "facecolor", "edgecolor", "linewidth"] } # Swap color -> facecolor here so we preserve edgecolor on rects style.setdefault("facecolor", style["color"]) style.pop("color", None) style.update(kwargs) if base is None: base = np.arange(len(ticks)) if height is None: height = 1 if np.isscalar(height): height = height * np.ones_like(base) seg_y = dict() for ybase, yheight, lab in zip(base, height, ticks): seg_y[lab] = (ybase, yheight) xvals = defaultdict(list) for ival, lab in zip(intervals, labels): if lab not in seg_y: continue xvals[lab].append((ival[0], ival[1] - ival[0])) for lab in seg_y: ax.broken_barh(xvals[lab], seg_y[lab], **style) # Pop the label after the first time we see it, so we only get # one legend entry style.pop("label", None) # Draw a line separating the new labels from pre-existing labels if extended: ax.axhline(len(label_set), color="k", alpha=0.5) if tick: ax.grid(True, axis="y") ax.set_yticks([]) ax.set_yticks(base) ax.set_yticklabels(ticks, va="bottom") ax.yaxis.set_major_formatter(IntervalFormatter(base, ticks)) return ax class IntervalFormatter(Formatter): """Ticker formatter for labeled interval plots. Parameters ---------- base : array-like of int The base positions of each label ticks : array-like of string The labels for the ticks """ def __init__(self, base, ticks): self._map = {int(k): v for k, v in zip(base, ticks)} def __call__(self, x, pos=None): """Map the input position to its corresponding interval label""" return self._map.get(int(x), "") def hierarchy(intervals_hier, labels_hier, levels=None, ax=None, **kwargs): """Plot a hierarchical segmentation Parameters ---------- intervals_hier : list of np.ndarray A list of segmentation intervals. Each element should be an n-by-2 array of segment intervals, in the format returned by :func:`mir_eval.io.load_intervals` or :func:`mir_eval.io.load_labeled_intervals`. Segmentations should be ordered by increasing specificity. labels_hier : list of list-like A list of segmentation labels. Each element should be a list of labels for the corresponding element in `intervals_hier`. levels : list of string Each element ``levels[i]`` is a label for the ```i`` th segmentation. This is used in the legend to denote the levels in a segment hierarchy. ax : matplotlib.pyplot.axes An axis handle on which to draw the intervals. If none is provided, a new set of axes is created. **kwargs Additional keyword arguments to `labeled_intervals`. Returns ------- ax : matplotlib.pyplot.axes._subplots.AxesSubplot A handle to the (possibly constructed) plot axes """ # This will break if a segment label exists in multiple levels if levels is None: levels = list(range(len(intervals_hier))) # Get the axes handle ax, _ = __get_axes(ax=ax) # Count the pre-existing patches n_patches = len(ax.patches) for ints, labs, key in zip(intervals_hier[::-1], labels_hier[::-1], levels[::-1]): labeled_intervals(ints, labs, label=key, ax=ax, **kwargs) return ax def events( times, labels=None, base=None, height=None, ax=None, text_kw=None, prop_cycle=None, **kwargs, ): """Plot event times as a set of vertical lines Parameters ---------- times : np.ndarray, shape=(n,) event times, in the format returned by :func:`mir_eval.io.load_events` or :func:`mir_eval.io.load_labeled_events`. labels : list, shape=(n,), optional event labels, in the format returned by :func:`mir_eval.io.load_labeled_events`. base : number The vertical position of the base of the line. By default, this will be the bottom of the plot. height : number The height of the lines. By default, this will be the top of the plot (minus `base`). .. note:: If either `base` or `height` are provided, both must be provided. ax : matplotlib.pyplot.axes An axis handle on which to draw the segmentation. If none is provided, a new set of axes is created. text_kw : dict If `labels` is provided, the properties of the text objects can be specified here. See `matplotlib.pyplot.Text` for valid parameters prop_cycle : cycle.Cycler An optional property cycle object to specify style properties. If not provided, the default property cycler will be retrieved from matplotlib. **kwargs Additional keyword arguments to pass to `matplotlib.pyplot.vlines`. Returns ------- ax : matplotlib.pyplot.axes._subplots.AxesSubplot A handle to the (possibly constructed) plot axes """ if text_kw is None: text_kw = dict() text_kw.setdefault("va", "top") text_kw.setdefault("clip_on", True) text_kw.setdefault("bbox", dict(boxstyle="round", facecolor="white")) # make sure we have an array for times times = np.asarray(times) # Get the axes handle ax, new_axes = __get_axes(ax=ax) if prop_cycle is None: __AXMAP[ax].setdefault("prop_cycle", mpl.rcParams["axes.prop_cycle"]) __AXMAP[ax].setdefault("prop_iter", iter(mpl.rcParams["axes.prop_cycle"])) elif "prop_iter" not in __AXMAP[ax]: __AXMAP[ax]["prop_cycle"] = prop_cycle __AXMAP[ax]["prop_iter"] = iter(prop_cycle) prop_cycle = __AXMAP[ax]["prop_cycle"] prop_iter = __AXMAP[ax]["prop_iter"] if base is None and height is None: # If neither are provided, we'll use axes coordinates to span the figure base, height = 0, 1 transform = ax.get_xaxis_transform() elif base is not None and height is not None: # If both are provided, we'll use data coordinates transform = None else: raise ValueError("When specifying base or height, both must be provided.") # Advance the property iterator if we can, restart it if we must try: properties = next(prop_iter) except StopIteration: prop_iter = iter(prop_cycle) __AXMAP[ax]["prop_iter"] = prop_iter properties = next(prop_iter) style = { k: v for k, v in properties.items() if k in ["color", "linestyle", "linewidth"] } style.update(kwargs) # If the user provided 'colors', don't override it with 'color' if "colors" in style: style.pop("color", None) lines = ax.vlines(times, base, base + height, transform=transform, **style) if labels: for path, lab in zip(lines.get_paths(), labels): ax.annotate( lab, xy=(path.vertices[0][0], height), xycoords=transform, xytext=(8, -10), textcoords="offset points", **text_kw, ) if new_axes: ax.set_yticks([]) return ax def pitch( times, frequencies, midi=False, unvoiced=False, ax=None, prop_cycle=None, **kwargs ): """Visualize pitch contours Parameters ---------- times : np.ndarray, shape=(n,) Sample times of frequencies frequencies : np.ndarray, shape=(n,) frequencies (in Hz) of the pitch contours. Voicing is indicated by sign (positive for voiced, non-positive for non-voiced). midi : bool If `True`, plot on a MIDI-numbered vertical axis. Otherwise, plot on a linear frequency axis. unvoiced : bool If `True`, unvoiced pitch contours are plotted and indicated by transparency. Otherwise, unvoiced pitch contours are omitted from the display. ax : matplotlib.pyplot.axes An axis handle on which to draw the pitch contours. If none is provided, a new set of axes is created. prop_cycle : cycle.Cycler An optional property cycle object to specify style properties. If not provided, the default property cycler will be retrieved from matplotlib. **kwargs Additional keyword arguments to `matplotlib.pyplot.plot`. Returns ------- ax : matplotlib.pyplot.axes._subplots.AxesSubplot A handle to the (possibly constructed) plot axes """ ax, _ = __get_axes(ax=ax) if prop_cycle is None: __AXMAP[ax].setdefault("prop_cycle", mpl.rcParams["axes.prop_cycle"]) __AXMAP[ax].setdefault("prop_iter", iter(mpl.rcParams["axes.prop_cycle"])) elif "prop_iter" not in __AXMAP[ax]: __AXMAP[ax]["prop_cycle"] = prop_cycle __AXMAP[ax]["prop_iter"] = iter(prop_cycle) prop_cycle = __AXMAP[ax]["prop_cycle"] prop_iter = __AXMAP[ax]["prop_iter"] times = np.asarray(times) # First, segment into contiguously voiced contours frequencies, voicings = freq_to_voicing(np.asarray(frequencies, dtype=np.float64)) voicings = voicings.astype(bool) # Here are all the change-points v_changes = 1 + np.flatnonzero(voicings[1:] != voicings[:-1]) v_changes = np.unique(np.concatenate([[0], v_changes, [len(voicings)]])) # Set up arrays of slices for voiced and unvoiced regions v_slices, u_slices = [], [] for start, end in zip(v_changes, v_changes[1:]): idx = slice(start, end) # A region is voiced if its starting sample is voiced # It's unvoiced if none of the samples in the region are voiced. if voicings[start]: v_slices.append(idx) elif frequencies[idx].all(): u_slices.append(idx) # Now we just need to plot the contour try: style = next(prop_iter) except StopIteration: prop_iter = iter(prop_cycle) __AXMAP[ax]["prop_iter"] = prop_iter style = next(prop_iter) style.update(kwargs) if midi: idx = frequencies > 0 frequencies[idx] = hz_to_midi(frequencies[idx]) # Tick at integer midi notes ax.yaxis.set_minor_locator(MultipleLocator(1)) for idx in v_slices: ax.plot(times[idx], frequencies[idx], **style) style.pop("label", None) # Plot the unvoiced portions if unvoiced: style["alpha"] = style.get("alpha", 1.0) * 0.5 for idx in u_slices: ax.plot(times[idx], frequencies[idx], **style) return ax def multipitch( times, frequencies, midi=False, unvoiced=False, ax=None, prop_cycle=None, **kwargs ): """Visualize multiple f0 measurements Parameters ---------- times : np.ndarray, shape=(n,) Sample times of frequencies frequencies : list of np.ndarray frequencies (in Hz) of the pitch measurements. Voicing is indicated by sign (positive for voiced, non-positive for non-voiced). `times` and `frequencies` should be in the format produced by :func:`mir_eval.io.load_ragged_time_series` midi : bool If `True`, plot on a MIDI-numbered vertical axis. Otherwise, plot on a linear frequency axis. unvoiced : bool If `True`, unvoiced pitches are plotted and indicated by transparency. Otherwise, unvoiced pitches are omitted from the display. ax : matplotlib.pyplot.axes An axis handle on which to draw the pitch contours. If none is provided, a new set of axes is created. prop_cycle : cycle.Cycler An optional property cycle object to specify style properties. If not provided, the default property cycler will be retrieved from matplotlib. **kwargs Additional keyword arguments to `plt.scatter`. Returns ------- ax : matplotlib.pyplot.axes._subplots.AxesSubplot A handle to the (possibly constructed) plot axes """ # Get the axes handle ax, _ = __get_axes(ax=ax) if prop_cycle is None: __AXMAP[ax].setdefault("prop_cycle", mpl.rcParams["axes.prop_cycle"]) __AXMAP[ax].setdefault("prop_iter", iter(mpl.rcParams["axes.prop_cycle"])) elif "prop_iter" not in __AXMAP[ax]: __AXMAP[ax]["prop_cycle"] = prop_cycle __AXMAP[ax]["prop_iter"] = iter(prop_cycle) prop_cycle = __AXMAP[ax]["prop_cycle"] prop_iter = __AXMAP[ax]["prop_iter"] # Set up a style for the plot try: style_voiced = next(prop_iter) except StopIteration: prop_iter = iter(prop_cycle) __AXMAP[ax]["prop_iter"] = prop_iter style_voiced = next(prop_iter) style_voiced.update(kwargs) style_unvoiced = style_voiced.copy() style_unvoiced.pop("label", None) style_unvoiced["alpha"] = style_unvoiced.get("alpha", 1.0) * 0.5 # We'll collect all times and frequencies first, then plot them voiced_times = [] voiced_freqs = [] unvoiced_times = [] unvoiced_freqs = [] for t, freqs in zip(times, frequencies): if not len(freqs): continue freqs, voicings = freq_to_voicing(np.asarray(freqs, dtype=np.float64)) # Discard all 0-frequency measurements idx = freqs > 0 freqs = freqs[idx] voicings = voicings[idx].astype(bool) if midi: freqs = hz_to_midi(freqs) n_voiced = sum(voicings) voiced_times.extend([t] * int(n_voiced)) voiced_freqs.extend(freqs[voicings]) unvoiced_times.extend([t] * (len(freqs) - n_voiced)) unvoiced_freqs.extend(freqs[~voicings]) # Plot the voiced frequencies ax.scatter(voiced_times, voiced_freqs, **style_voiced) # Plot the unvoiced frequencies if unvoiced: ax.scatter(unvoiced_times, unvoiced_freqs, **style_unvoiced) # Tick at integer midi notes if midi: ax.yaxis.set_minor_locator(MultipleLocator(1)) return ax def piano_roll(intervals, pitches=None, midi=None, ax=None, **kwargs): """Plot a quantized piano roll as intervals Parameters ---------- intervals : np.ndarray, shape=(n, 2) timing intervals for notes pitches : np.ndarray, shape=(n,), optional pitches of notes (in Hz). midi : np.ndarray, shape=(n,), optional pitches of notes (in MIDI numbers). At least one of ``pitches`` or ``midi`` must be provided. ax : matplotlib.pyplot.axes An axis handle on which to draw the intervals. If none is provided, a new set of axes is created. **kwargs Additional keyword arguments to :func:`labeled_intervals`. Returns ------- ax : matplotlib.pyplot.axes._subplots.AxesSubplot A handle to the (possibly constructed) plot axes """ if midi is None: if pitches is None: raise ValueError("At least one of `midi` or `pitches` " "must be provided.") midi = hz_to_midi(pitches) scale = np.arange(128) ax = labeled_intervals( intervals, np.round(midi).astype(int), label_set=scale, tick=False, ax=ax, **kwargs, ) # Minor tick at each semitone ax.yaxis.set_minor_locator(MultipleLocator(1)) return ax def separation( sources, fs=22050, labels=None, alpha=0.75, ax=None, rasterized=True, edgecolors="None", shading="gouraud", prop_cycle=None, **kwargs, ): """Source-separation visualization Parameters ---------- sources : np.ndarray, shape=(nsrc, nsampl) A list of waveform buffers corresponding to each source fs : number > 0 The sampling rate labels : list of strings An optional list of descriptors corresponding to each source alpha : float in [0, 1] Maximum alpha (opacity) of spectrogram values. ax : matplotlib.pyplot.axes An axis handle on which to draw the spectrograms. If none is provided, a new set of axes is created. rasterized : bool If `True`, the spectrogram is rasterized. edgecolors : str or None The color of the edges of the spectrogram patches. Set to "None" (default) to disable edge coloring. shading : str The shading method to use for the spectrogram. See `matplotlib.pyplot.pcolormesh` for valid options. prop_cycle : cycle.Cycler An optional property cycle object to specify colors for each signal. If not provided, the default property cycler will be retrieved from matplotlib. **kwargs Additional keyword arguments to ``scipy.signal.spectrogram`` Returns ------- ax The axis handle for this plot """ # Get the axes handle ax, new_axes = __get_axes(ax=ax) # Make sure we have at least two dimensions sources = np.atleast_2d(sources) if labels is None: labels = [f"Source {_:d}" for _ in range(len(sources))] kwargs.setdefault("scaling", "spectrum") # The cumulative spectrogram across sources # is used to establish the reference power # for each individual source cumspec = None specs = [] for i, src in enumerate(sources): freqs, times, spec = spectrogram(src, fs=fs, **kwargs) specs.append(spec) if cumspec is None: cumspec = spec.copy() else: cumspec += spec ref_max = cumspec.max() ref_min = ref_max * 1e-6 color_conv = ColorConverter() if prop_cycle is None: __AXMAP[ax].setdefault("prop_cycle", mpl.rcParams["axes.prop_cycle"]) __AXMAP[ax].setdefault("prop_iter", iter(mpl.rcParams["axes.prop_cycle"])) elif "prop_iter" not in __AXMAP[ax]: __AXMAP[ax]["prop_cycle"] = prop_cycle __AXMAP[ax]["prop_iter"] = iter(prop_cycle) prop_cycle = __AXMAP[ax]["prop_cycle"] prop_iter = __AXMAP[ax]["prop_iter"] for i, spec in enumerate(specs): # For each source, grab a new color from the cycler # Then construct a colormap that interpolates from # [transparent white -> new color] # Advance the property iterator if we can, restart it if we must try: properties = next(prop_iter) except StopIteration: prop_iter = iter(prop_cycle) __AXMAP[ax]["prop_iter"] = prop_iter properties = next(prop_iter) color = color_conv.to_rgba(properties["color"], alpha=alpha) cmap = LinearSegmentedColormap.from_list( labels[i], [(1.0, 1.0, 1.0, 0.0), color] ) ax.pcolormesh( times, freqs, spec, cmap=cmap, norm=LogNorm(vmin=ref_min, vmax=ref_max), rasterized=rasterized, edgecolors=edgecolors, shading=shading, ) # Attach a 0x0 rect to the axis with the corresponding label # This way, it will show up in the legend ax.add_patch( Rectangle((times.min(), freqs.min()), 0, 0, color=color, label=labels[i]) ) return ax def __ticker_midi_note(x, pos): """Format midi notes for ticker decoration. Inputs x are interpreted as midi numbers, and converted to [NOTE][OCTAVE]+[cents]. """ NOTES = ["C", "C#", "D", "D#", "E", "F", "F#", "G", "G#", "A", "A#", "B"] cents = float(np.mod(x, 1.0)) if cents >= 0.5: cents = cents - 1.0 x = x + 0.5 idx = int(x % 12) octave = int(x / 12) - 1 if cents == 0: return f"{NOTES[idx]:s}{octave:2d}" return f"{NOTES[idx]:s}{octave:2d}{int(cents * 100):+02d}" def __ticker_midi_hz(x, pos): """Format midi pitches for ticker decoration. Inputs x are interpreted as midi numbers, and converted to Hz. """ return f"{midi_to_hz(x):g}" def ticker_notes(ax=None): """Set the y-axis of the given axes to MIDI notes Parameters ---------- ax : matplotlib.pyplot.axes The axes handle to apply the ticker. By default, uses the current axes handle. """ ax, _ = __get_axes(ax=ax) ax.yaxis.set_major_formatter(FMT_MIDI_NOTE) # Get the tick labels and reset the vertical alignment for tick in ax.yaxis.get_ticklabels(): tick.set_verticalalignment("baseline") def ticker_pitch(ax=None): """Set the y-axis of the given axes to MIDI frequencies Parameters ---------- ax : matplotlib.pyplot.axes The axes handle to apply the ticker. By default, uses the current axes handle. """ ax, _ = __get_axes(ax=ax) ax.yaxis.set_major_formatter(FMT_MIDI_HZ) # Instantiate ticker objects; we don't need more than one of each FMT_MIDI_NOTE = FuncFormatter(__ticker_midi_note) FMT_MIDI_HZ = FuncFormatter(__ticker_midi_hz) mir_eval-0.8.2/mir_eval/hierarchy.py000066400000000000000000000563721475740344600175000ustar00rootroot00000000000000# CREATED:2015-09-16 14:46:47 by Brian McFee """Evaluation criteria for hierarchical structure analysis. Hierarchical structure analysis seeks to annotate a track with a nested decomposition of the temporal elements of the piece, effectively providing a kind of "parse tree" of the composition. Unlike the flat segmentation metrics defined in :mod:`mir_eval.segment`, which can only encode one level of analysis, hierarchical annotations expose the relationships between short segments and the larger compositional elements to which they belong. Conventions ----------- Annotations are assumed to take the form of an ordered list of segmentations. As in the :mod:`mir_eval.segment` metrics, each segmentation itself consists of an n-by-2 array of interval times, so that the ``i`` th segment spans time ``intervals[i, 0]`` to ``intervals[i, 1]``. Hierarchical annotations are ordered by increasing specificity, so that the first segmentation should contain the fewest segments, and the last segmentation contains the most. Metrics ------- * :func:`mir_eval.hierarchy.tmeasure`: Precision, recall, and F-measure of triplet-based frame accuracy for boundary detection. * :func:`mir_eval.hierarchy.lmeasure`: Precision, recall, and F-measure of triplet-based frame accuracy for segment labeling. References ---------- .. [#mcfee2015] Brian McFee, Oriol Nieto, and Juan P. Bello. "Hierarchical evaluation of segment boundary detection", International Society for Music Information Retrieval (ISMIR) conference, 2015. .. [#mcfee2017] Brian McFee, Oriol Nieto, Morwaread Farbood, and Juan P. Bello. "Evaluating hierarchical structure in music annotations", Frontiers in Psychology, 2017. """ import collections import itertools import warnings import numpy as np import scipy.sparse from . import util from .segment import validate_structure def _round(t, frame_size): """Round a time-stamp to a specified resolution. Equivalent to ``t - np.mod(t, frame_size)``. Examples -------- >>> _round(53.279, 0.1) 53.2 >>> _round(53.279, 0.25) 53.25 Parameters ---------- t : number or ndarray The time-stamp to round frame_size : number > 0 The resolution to round to Returns ------- t_round : number The rounded time-stamp """ return t - np.mod(t, float(frame_size)) def _hierarchy_bounds(intervals_hier): """Compute the covered time range of a hierarchical segmentation. Parameters ---------- intervals_hier : list of ndarray A hierarchical segmentation, encoded as a list of arrays of segment intervals. Returns ------- t_min : float t_max : float The minimum and maximum times spanned by the annotation """ boundaries = list(itertools.chain(*list(itertools.chain(*intervals_hier)))) return min(boundaries), max(boundaries) def _align_intervals(int_hier, lab_hier, t_min=0.0, t_max=None): """Align a hierarchical annotation to span a fixed start and end time. Parameters ---------- int_hier : list of list of intervals lab_hier : list of list of str Hierarchical segment annotations, encoded as a list of list of intervals (int_hier) and list of list of strings (lab_hier) t_min : None or number >= 0 The minimum time value for the segmentation t_max : None or number >= t_min The maximum time value for the segmentation Returns ------- intervals_hier : list of list of intervals labels_hier : list of list of str `int_hier` `lab_hier` aligned to span `[t_min, t_max]`. """ return [ list(_) for _ in zip( *[ util.adjust_intervals( np.asarray(ival), labels=lab, t_min=t_min, t_max=t_max ) for ival, lab in zip(int_hier, lab_hier) ] ) ] def _lca(intervals_hier, frame_size): """Compute the (sparse) least-common-ancestor (LCA) matrix for a hierarchical segmentation. For any pair of frames ``(s, t)``, the LCA is the deepest level in the hierarchy such that ``(s, t)`` are contained within a single segment at that level. Parameters ---------- intervals_hier : list of ndarray An ordered list of segment interval arrays. The list is assumed to be ordered by increasing specificity (depth). frame_size : number The length of the sample frames (in seconds) Returns ------- lca_matrix : scipy.sparse.csr_matrix A sparse matrix such that ``lca_matrix[i, j]`` contains the depth of the deepest segment containing frames ``i`` and ``j``. """ frame_size = float(frame_size) # Figure out how many frames we need n_start, n_end = _hierarchy_bounds(intervals_hier) n = int((_round(n_end, frame_size) - _round(n_start, frame_size)) / frame_size) # Initialize the LCA matrix lca_matrix = scipy.sparse.lil_matrix((n, n), dtype=np.uint8) for level, intervals in enumerate(intervals_hier, 1): for ival in (_round(np.asarray(intervals), frame_size) / frame_size).astype( int ): idx = slice(ival[0], ival[1]) lca_matrix[idx, idx] = level return lca_matrix.tocsr() def _meet(intervals_hier, labels_hier, frame_size): """Compute the (sparse) least-common-ancestor (LCA) matrix for a hierarchical segmentation. For any pair of frames ``(s, t)``, the LCA is the deepest level in the hierarchy such that ``(s, t)`` are contained within a single segment at that level. Parameters ---------- intervals_hier : list of ndarray An ordered list of segment interval arrays. The list is assumed to be ordered by increasing specificity (depth). labels_hier : list of list of str ``labels_hier[i]`` contains the segment labels for the ``i``th layer of the annotations frame_size : number The length of the sample frames (in seconds) Returns ------- meet_matrix : scipy.sparse.csr_matrix A sparse matrix such that ``meet_matrix[i, j]`` contains the depth of the deepest segment label containing both ``i`` and ``j``. """ frame_size = float(frame_size) # Figure out how many frames we need n_start, n_end = _hierarchy_bounds(intervals_hier) n = int((_round(n_end, frame_size) - _round(n_start, frame_size)) / frame_size) # Initialize the meet matrix meet_matrix = scipy.sparse.lil_matrix((n, n), dtype=np.uint8) for level, (intervals, labels) in enumerate(zip(intervals_hier, labels_hier), 1): # Encode the labels at this level lab_enc = util.index_labels(labels)[0] # Find unique agreements int_agree = np.triu(np.equal.outer(lab_enc, lab_enc)) # Map intervals to frame indices int_frames = (_round(intervals, frame_size) / frame_size).astype(int) # For each intervals i, j where labels agree, update the meet matrix for seg_i, seg_j in zip(*np.where(int_agree)): idx_i = slice(*list(int_frames[seg_i])) idx_j = slice(*list(int_frames[seg_j])) meet_matrix[idx_i, idx_j] = level if seg_i != seg_j: meet_matrix[idx_j, idx_i] = level return scipy.sparse.csr_matrix(meet_matrix) def _gauc(ref_lca, est_lca, transitive, window): """Generalized area under the curve (GAUC) This function computes the normalized recall score for correctly ordering triples ``(q, i, j)`` where frames ``(q, i)`` are closer than ``(q, j)`` in the reference annotation. Parameters ---------- ref_lca : scipy.sparse est_lca : scipy.sparse The least common ancestor matrices for the reference and estimated annotations transitive : bool If True, then transitive comparisons are counted, meaning that ``(q, i)`` and ``(q, j)`` can differ by any number of levels. If False, then ``(q, i)`` and ``(q, j)`` can differ by exactly one level. window : number or None The maximum number of frames to consider for each query. If `None`, then all frames are considered. Returns ------- score : number [0, 1] The percentage of reference triples correctly ordered by the estimation. Raises ------ ValueError If ``ref_lca`` and ``est_lca`` have different shapes """ # Make sure we have the right number of frames if ref_lca.shape != est_lca.shape: raise ValueError( "Estimated and reference hierarchies " "must have the same shape." ) # How many frames? n = ref_lca.shape[0] # By default, the window covers the entire track if window is None: window = n # Initialize the score score = 0.0 # Iterate over query frames num_frames = 0 for query in range(n): # Find all pairs i,j such that ref_lca[q, i] > ref_lca[q, j] results = slice(max(0, query - window), min(n, query + window)) ref_score = ref_lca[query, results] est_score = est_lca[query, results] # Densify the results ref_score = ref_score.toarray().squeeze() est_score = est_score.toarray().squeeze() # Don't count the query as a result # when query < window, query itself is the index within the slice # otherwise, query is located at the center of the slice, window # (this also holds when the slice goes off the end of the array.) idx = min(query, window) ref_score = np.concatenate((ref_score[:idx], ref_score[idx + 1 :])) est_score = np.concatenate((est_score[:idx], est_score[idx + 1 :])) inversions, normalizer = _compare_frame_rankings( ref_score, est_score, transitive=transitive ) if normalizer: score += 1.0 - inversions / float(normalizer) num_frames += 1 # Normalize by the number of frames counted. # If no frames are counted, take the convention 0/0 -> 0 if num_frames: score /= float(num_frames) else: score = 0.0 return score def _count_inversions(a, b): """Count the number of inversions in two numpy arrays: # points i, j where a[i] >= b[j] Parameters ---------- a, b : np.ndarray, shape=(n,) (m,) The arrays to be compared. This implementation is optimized for arrays with many repeated values. Returns ------- inversions : int The number of detected inversions """ a, a_counts = np.unique(a, return_counts=True) b, b_counts = np.unique(b, return_counts=True) inversions = 0 i = 0 j = 0 while i < len(a) and j < len(b): if a[i] < b[j]: i += 1 elif a[i] >= b[j]: inversions += np.sum(a_counts[i:]) * b_counts[j] j += 1 return inversions def _compare_frame_rankings(ref, est, transitive=False): """Compute the number of ranking disagreements in two lists. Parameters ---------- ref : np.ndarray, shape=(n,) est : np.ndarray, shape=(n,) Reference and estimate ranked lists. `ref[i]` is the relevance score for point `i`. transitive : bool If true, all pairs of reference levels are compared. If false, only adjacent pairs of reference levels are compared. Returns ------- inversions : int The number of pairs of indices `i, j` where `ref[i] < ref[j]` but `est[i] >= est[j]`. normalizer : float The total number of pairs (i, j) under consideration. If transitive=True, then this is |{(i,j) : ref[i] < ref[j]}| If transitive=False, then this is |{i,j) : ref[i] +1 = ref[j]}| """ idx = np.argsort(ref) ref_sorted = ref[idx] est_sorted = est[idx] # Find the break-points in ref_sorted levels, positions, counts = np.unique( ref_sorted, return_index=True, return_counts=True ) positions = list(positions) positions.append(len(ref_sorted)) index = collections.defaultdict(lambda: slice(0)) ref_map = collections.defaultdict(lambda: 0) for level, cnt, start, end in zip(levels, counts, positions[:-1], positions[1:]): index[level] = slice(start, end) ref_map[level] = cnt # Now that we have values sorted, apply the inversion-counter to # pairs of reference values if transitive: level_pairs = itertools.combinations(levels, 2) else: level_pairs = [(i, i + 1) for i in levels] level_pairs, lcounter = itertools.tee(level_pairs) normalizer = float(sum([ref_map[i] * ref_map[j] for (i, j) in lcounter])) if normalizer == 0: return 0, 0.0 inversions = 0 for level_1, level_2 in level_pairs: inversions += _count_inversions( est_sorted[index[level_1]], est_sorted[index[level_2]] ) return inversions, float(normalizer) def validate_hier_intervals(intervals_hier): """Validate a hierarchical segment annotation. Parameters ---------- intervals_hier : ordered list of segmentations Raises ------ ValueError If any segmentation does not span the full duration of the top-level segmentation. If any segmentation does not start at 0. """ # Synthesize a label array for the top layer. label_top = util.generate_labels(intervals_hier[0]) boundaries = set(util.intervals_to_boundaries(intervals_hier[0])) for level, intervals in enumerate(intervals_hier[1:], 1): # Make sure this level is consistent with the root label_current = util.generate_labels(intervals) validate_structure(intervals_hier[0], label_top, intervals, label_current) # Make sure all previous boundaries are accounted for new_bounds = set(util.intervals_to_boundaries(intervals)) if boundaries - new_bounds: warnings.warn( "Segment hierarchy is inconsistent " "at level {:d}".format(level) ) boundaries |= new_bounds def tmeasure( reference_intervals_hier, estimated_intervals_hier, transitive=False, window=15.0, frame_size=0.1, beta=1.0, ): """Compute the tree measures for hierarchical segment annotations. Parameters ---------- reference_intervals_hier : list of ndarray ``reference_intervals_hier[i]`` contains the segment intervals (in seconds) for the ``i`` th layer of the annotations. Layers are ordered from top to bottom, so that the last list of intervals should be the most specific. estimated_intervals_hier : list of ndarray Like ``reference_intervals_hier`` but for the estimated annotation transitive : bool whether to compute the t-measures using transitivity or not. window : float > 0 size of the window (in seconds). For each query frame q, result frames are only counted within q +- window. frame_size : float > 0 length (in seconds) of frames. The frame size cannot be longer than the window. beta : float > 0 beta parameter for the F-measure. Returns ------- t_precision : number [0, 1] T-measure Precision t_recall : number [0, 1] T-measure Recall t_measure : number [0, 1] F-beta measure for ``(t_precision, t_recall)`` Raises ------ ValueError If either of the input hierarchies are inconsistent If the input hierarchies have different time durations If ``frame_size > window`` or ``frame_size <= 0`` """ # Compute the number of frames in the window if frame_size <= 0: raise ValueError( "frame_size ({:.2f}) must be a positive " "number.".format(frame_size) ) if window is None: window_frames = None else: if frame_size > window: raise ValueError( "frame_size ({:.2f}) cannot exceed " "window ({:.2f})".format(frame_size, window) ) window_frames = int(_round(window, frame_size) / frame_size) # Validate the hierarchical segmentations validate_hier_intervals(reference_intervals_hier) validate_hier_intervals(estimated_intervals_hier) # Build the least common ancestor matrices ref_lca = _lca(reference_intervals_hier, frame_size) est_lca = _lca(estimated_intervals_hier, frame_size) # Compute precision and recall t_recall = _gauc(ref_lca, est_lca, transitive, window_frames) t_precision = _gauc(est_lca, ref_lca, transitive, window_frames) t_measure = util.f_measure(t_precision, t_recall, beta=beta) return t_precision, t_recall, t_measure def lmeasure( reference_intervals_hier, reference_labels_hier, estimated_intervals_hier, estimated_labels_hier, frame_size=0.1, beta=1.0, ): """Compute the tree measures for hierarchical segment annotations. Parameters ---------- reference_intervals_hier : list of ndarray ``reference_intervals_hier[i]`` contains the segment intervals (in seconds) for the ``i`` th layer of the annotations. Layers are ordered from top to bottom, so that the last list of intervals should be the most specific. reference_labels_hier : list of list of str ``reference_labels_hier[i]`` contains the segment labels for the ``i`` th layer of the annotations estimated_intervals_hier : list of ndarray estimated_labels_hier : list of ndarray Like ``reference_intervals_hier`` and ``reference_labels_hier`` but for the estimated annotation frame_size : float > 0 length (in seconds) of frames. The frame size cannot be longer than the window. beta : float > 0 beta parameter for the F-measure. Returns ------- l_precision : number [0, 1] L-measure Precision l_recall : number [0, 1] L-measure Recall l_measure : number [0, 1] F-beta measure for ``(l_precision, l_recall)`` Raises ------ ValueError If either of the input hierarchies are inconsistent If the input hierarchies have different time durations If ``frame_size > window`` or ``frame_size <= 0`` """ # Compute the number of frames in the window if frame_size <= 0: raise ValueError( "frame_size ({:.2f}) must be a positive " "number.".format(frame_size) ) # Validate the hierarchical segmentations validate_hier_intervals(reference_intervals_hier) validate_hier_intervals(estimated_intervals_hier) # Build the least common ancestor matrices ref_meet = _meet(reference_intervals_hier, reference_labels_hier, frame_size) est_meet = _meet(estimated_intervals_hier, estimated_labels_hier, frame_size) # Compute precision and recall l_recall = _gauc(ref_meet, est_meet, True, None) l_precision = _gauc(est_meet, ref_meet, True, None) l_measure = util.f_measure(l_precision, l_recall, beta=beta) return l_precision, l_recall, l_measure def evaluate( ref_intervals_hier, ref_labels_hier, est_intervals_hier, est_labels_hier, **kwargs ): r"""Compute all hierarchical structure metrics for the given reference and estimated annotations. Examples -------- A toy example with two two-layer annotations >>> ref_i = [[[0, 30], [30, 60]], [[0, 15], [15, 30], [30, 45], [45, 60]]] >>> est_i = [[[0, 45], [45, 60]], [[0, 15], [15, 30], [30, 45], [45, 60]]] >>> ref_l = [ ['A', 'B'], ['a', 'b', 'a', 'c'] ] >>> est_l = [ ['A', 'B'], ['a', 'a', 'b', 'b'] ] >>> scores = mir_eval.hierarchy.evaluate(ref_i, ref_l, est_i, est_l) >>> dict(scores) {'T-Measure full': 0.94822745804853459, 'T-Measure reduced': 0.8732458222764804, 'T-Precision full': 0.96569179094693058, 'T-Precision reduced': 0.89939075137018787, 'T-Recall full': 0.93138358189386117, 'T-Recall reduced': 0.84857799953694923} A more realistic example, using SALAMI pre-parsed annotations >>> def load_salami(filename): ... "load SALAMI event format as labeled intervals" ... events, labels = mir_eval.io.load_labeled_events(filename) ... intervals = mir_eval.util.boundaries_to_intervals(events)[0] ... return intervals, labels[:len(intervals)] >>> ref_files = ['data/10/parsed/textfile1_uppercase.txt', ... 'data/10/parsed/textfile1_lowercase.txt'] >>> est_files = ['data/10/parsed/textfile2_uppercase.txt', ... 'data/10/parsed/textfile2_lowercase.txt'] >>> ref = [load_salami(fname) for fname in ref_files] >>> ref_int = [seg[0] for seg in ref] >>> ref_lab = [seg[1] for seg in ref] >>> est = [load_salami(fname) for fname in est_files] >>> est_int = [seg[0] for seg in est] >>> est_lab = [seg[1] for seg in est] >>> scores = mir_eval.hierarchy.evaluate(ref_int, ref_lab, ... est_hier, est_lab) >>> dict(scores) {'T-Measure full': 0.66029225561405358, 'T-Measure reduced': 0.62001868041578034, 'T-Precision full': 0.66844764668949885, 'T-Precision reduced': 0.63252297209957919, 'T-Recall full': 0.6523334654992341, 'T-Recall reduced': 0.60799919710921635} Parameters ---------- ref_intervals_hier : list of list-like ref_labels_hier : list of list of str est_intervals_hier : list of list-like est_labels_hier : list of list of str Hierarchical annotations are encoded as an ordered list of segmentations. Each segmentation itself is a list (or list-like) of intervals (\*_intervals_hier) and a list of lists of labels (\*_labels_hier). **kwargs additional keyword arguments to the evaluation metrics. Returns ------- scores : OrderedDict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. T-measures are computed in both the "full" (``transitive=True``) and "reduced" (``transitive=False``) modes. Raises ------ ValueError Thrown when the provided annotations are not valid. """ # First, find the maximum length of the reference _, t_end = _hierarchy_bounds(ref_intervals_hier) # Pre-process the intervals to match the range of the reference, # and start at 0 ref_intervals_hier, ref_labels_hier = _align_intervals( ref_intervals_hier, ref_labels_hier, t_min=0.0, t_max=None ) est_intervals_hier, est_labels_hier = _align_intervals( est_intervals_hier, est_labels_hier, t_min=0.0, t_max=t_end ) scores = collections.OrderedDict() # Force the transitivity setting kwargs["transitive"] = False ( scores["T-Precision reduced"], scores["T-Recall reduced"], scores["T-Measure reduced"], ) = util.filter_kwargs(tmeasure, ref_intervals_hier, est_intervals_hier, **kwargs) kwargs["transitive"] = True ( scores["T-Precision full"], scores["T-Recall full"], scores["T-Measure full"], ) = util.filter_kwargs(tmeasure, ref_intervals_hier, est_intervals_hier, **kwargs) ( scores["L-Precision"], scores["L-Recall"], scores["L-Measure"], ) = util.filter_kwargs( lmeasure, ref_intervals_hier, ref_labels_hier, est_intervals_hier, est_labels_hier, **kwargs ) return scores mir_eval-0.8.2/mir_eval/io.py000066400000000000000000000544671475740344600161340ustar00rootroot00000000000000"""Functions for loading annotations from files in different formats.""" import contextlib import numpy as np import re import warnings import scipy.io.wavfile from . import util from . import key from . import tempo @contextlib.contextmanager def _open(file_or_path, **kwargs): """Either open a file handle, or use an existing file-like object. If `file_or_path` has the `read` attribute, it will return `file_or_path`. Otherwise, it will attempt to open the file at the specified location. """ if hasattr(file_or_path, "read"): yield file_or_path else: try: with open(file_or_path, **kwargs) as file_desc: yield file_desc except TypeError as exc: raise IOError(f"Invalid file-or-path object: {file_or_path}") from exc def load_delimited(filename, converters, delimiter=r"\s+", comment="#"): r"""Load data from an annotation file where columns are delimited. The number of columns is inferred from the length of the provided converters list. Examples -------- >>> # Load in a one-column list of event times (floats) >>> load_delimited('events.txt', [float]) >>> # Load in a list of labeled events, separated by commas >>> load_delimited('labeled_events.csv', [float, str], ',') Parameters ---------- filename : str or `os.Pathlike` Path to the annotation file converters : list of functions Each entry in column ``n`` of the file will be cast by the function ``converters[n]``. delimiter : str Separator regular expression. By default, lines will be split by any amount of whitespace. comment : str or None Comment regular expression. Any lines beginning with this string or pattern will be ignored. Setting to `None` disables comments. Returns ------- columns : tuple of lists Each list in this tuple corresponds to values in one of the columns in the file. """ # Initialize list of empty lists n_columns = len(converters) columns = tuple(list() for _ in range(n_columns)) # Create re object for splitting lines splitter = re.compile(delimiter) # And one for comments if comment is None: commenter = None else: commenter = re.compile(f"^{comment}") # Note: we do io manually here for two reasons. # 1. The csv module has difficulties with unicode, which may lead # to failures on certain annotation strings # # 2. numpy's text loader does not handle non-numeric data # with _open(filename, mode="r") as input_file: for row, line in enumerate(input_file, 1): # Skip commented lines if comment is not None and commenter.match(line): continue # Split each line using the supplied delimiter data = splitter.split(line.strip(), n_columns - 1) # Throw a helpful error if we got an unexpected # of columns if n_columns != len(data): raise ValueError( "Expected {} columns, got {} at " "{}:{:d}:\n\t{}".format(n_columns, len(data), filename, row, line) ) for value, column, converter in zip(data, columns, converters): # Try converting the value, throw a helpful error on failure try: converted_value = converter(value) except: raise ValueError( "Couldn't convert value {} using {} " "found at {}:{:d}:\n\t{}".format( value, converter.__name__, filename, row, line ) ) column.append(converted_value) # Sane output if n_columns == 1: return columns[0] else: return columns def load_events(filename, delimiter=r"\s+", comment="#"): r"""Import time-stamp events from an annotation file. The file should consist of a single column of numeric values corresponding to the event times. This is primarily useful for processing events which lack duration, such as beats or onsets. Parameters ---------- filename : str or `os.Pathlike` Path to the annotation file delimiter : str Separator regular expression. By default, lines will be split by any amount of whitespace. comment : str or None Comment regular expression. Any lines beginning with this string or pattern will be ignored. Setting to `None` disables comments. Returns ------- event_times : np.ndarray array of event times (float) """ # Use our universal function to load in the events events = load_delimited(filename, [float], delimiter=delimiter, comment=comment) events = np.array(events) # Validate them, but throw a warning in place of an error try: util.validate_events(events) except ValueError as error: warnings.warn(error.args[0]) return events def load_labeled_events(filename, delimiter=r"\s+", comment="#"): r"""Import labeled time-stamp events from an annotation file. The file should consist of two columns; the first having numeric values corresponding to the event times and the second having string labels for each event. This is primarily useful for processing labeled events which lack duration, such as beats with metric beat number or onsets with an instrument label. Parameters ---------- filename : str or `os.Pathlike` Path to the annotation file delimiter : str Separator regular expression. By default, lines will be split by any amount of whitespace. comment : str or None Comment regular expression. Any lines beginning with this string or pattern will be ignored. Setting to `None` disables comments. Returns ------- event_times : np.ndarray array of event times (float) labels : list of str list of labels """ # Use our universal function to load in the events events, labels = load_delimited( filename, [float, str], delimiter=delimiter, comment=comment ) events = np.array(events) # Validate them, but throw a warning in place of an error try: util.validate_events(events) except ValueError as error: warnings.warn(error.args[0]) return events, labels def load_intervals(filename, delimiter=r"\s+", comment="#"): r"""Import intervals from an annotation file. The file should consist of two columns of numeric values corresponding to start and end time of each interval. This is primarily useful for processing events which span a duration, such as segmentation, chords, or instrument activation. Parameters ---------- filename : str or `os.Pathlike` Path to the annotation file delimiter : str Separator regular expression. By default, lines will be split by any amount of whitespace. comment : str or None Comment regular expression. Any lines beginning with this string or pattern will be ignored. Setting to `None` disables comments. Returns ------- intervals : np.ndarray, shape=(n_events, 2) array of event start and end times """ # Use our universal function to load in the events starts, ends = load_delimited( filename, [float, float], delimiter=delimiter, comment=comment ) # Stack into an interval matrix intervals = np.array([starts, ends]).T # Validate them, but throw a warning in place of an error try: util.validate_intervals(intervals) except ValueError as error: warnings.warn(error.args[0]) return intervals def load_labeled_intervals(filename, delimiter=r"\s+", comment="#"): r"""Import labeled intervals from an annotation file. The file should consist of three columns: Two consisting of numeric values corresponding to start and end time of each interval and a third corresponding to the label of each interval. This is primarily useful for processing events which span a duration, such as segmentation, chords, or instrument activation. Parameters ---------- filename : str or `os.Pathlike` Path to the annotation file delimiter : str Separator regular expression. By default, lines will be split by any amount of whitespace. comment : str or None Comment regular expression. Any lines beginning with this string or pattern will be ignored. Setting to `None` disables comments. Returns ------- intervals : np.ndarray, shape=(n_events, 2) array of event start and end time labels : list of str list of labels """ # Use our universal function to load in the events starts, ends, labels = load_delimited( filename, [float, float, str], delimiter=delimiter, comment=comment ) # Stack into an interval matrix intervals = np.array([starts, ends]).T # Validate them, but throw a warning in place of an error try: util.validate_intervals(intervals) except ValueError as error: warnings.warn(error.args[0]) return intervals, labels def load_time_series(filename, delimiter=r"\s+", comment="#"): r"""Import a time series from an annotation file. The file should consist of two columns of numeric values corresponding to the time and value of each sample of the time series. Parameters ---------- filename : str or `os.Pathlike` Path to the annotation file delimiter : str Separator regular expression. By default, lines will be split by any amount of whitespace. comment : str or None Comment regular expression. Any lines beginning with this string or pattern will be ignored. Setting to `None` disables comments. Returns ------- times : np.ndarray array of timestamps (float) values : np.ndarray array of corresponding numeric values (float) """ # Use our universal function to load in the events times, values = load_delimited( filename, [float, float], delimiter=delimiter, comment=comment ) times = np.array(times) values = np.array(values) return times, values def load_patterns(filename): """Load the patterns contained in the filename and puts them into a list of patterns, each pattern being a list of occurrence, and each occurrence being a list of (onset, midi) pairs. The input file must be formatted as described in MIREX 2013: http://www.music-ir.org/mirex/wiki/2013:Discovery_of_Repeated_Themes_%26_Sections Parameters ---------- filename : str or `os.Pathlike` The input file path containing the patterns of a given piece using the MIREX 2013 format. Returns ------- pattern_list : list The list of patterns, containing all their occurrences, using the following format:: onset_midi = (onset_time, midi_number) occurrence = [onset_midi1, ..., onset_midiO] pattern = [occurrence1, ..., occurrenceM] pattern_list = [pattern1, ..., patternN] where ``N`` is the number of patterns, ``M[i]`` is the number of occurrences of the ``i`` th pattern, and ``O[j]`` is the number of onsets in the ``j``'th occurrence. E.g.:: occ1 = [(0.5, 67.0), (1.0, 67.0), (1.5, 67.0), (2.0, 64.0)] occ2 = [(4.5, 65.0), (5.0, 65.0), (5.5, 65.0), (6.0, 62.0)] pattern1 = [occ1, occ2] occ1 = [(10.5, 67.0), (11.0, 67.0), (11.5, 67.0), (12.0, 64.0), (12.5, 69.0), (13.0, 69.0), (13.5, 69.0), (14.0, 67.0), (14.5, 76.0), (15.0, 76.0), (15.5, 76.0), (16.0, 72.0)] occ2 = [(18.5, 67.0), (19.0, 67.0), (19.5, 67.0), (20.0, 62.0), (20.5, 69.0), (21.0, 69.0), (21.5, 69.0), (22.0, 67.0), (22.5, 77.0), (23.0, 77.0), (23.5, 77.0), (24.0, 74.0)] pattern2 = [occ1, occ2] pattern_list = [pattern1, pattern2] """ # List with all the patterns pattern_list = [] # Current pattern, which will contain all occs pattern = [] # Current occurrence, containing (onset, midi) occurrence = [] with _open(filename, mode="r") as input_file: for line in input_file.readlines(): if "pattern" in line: if occurrence != []: pattern.append(occurrence) if pattern != []: pattern_list.append(pattern) occurrence = [] pattern = [] continue if "occurrence" in line: if occurrence != []: pattern.append(occurrence) occurrence = [] continue string_values = line.split(",") onset_midi = (float(string_values[0]), float(string_values[1])) occurrence.append(onset_midi) # Add last occurrence and pattern to pattern_list if occurrence != []: pattern.append(occurrence) if pattern != []: pattern_list.append(pattern) return pattern_list @util.deprecated(version="0.8.1", version_removed="0.9.0") def load_wav(path, mono=True): """Load a .wav file as a numpy array using ``scipy.io.wavfile``. .. warning:: This function is deprecatred in mir_eval 0.8.1 and will be removed in 0.9.0. We recommend using a dedicated audio IO library such as `soundfile` instead. Parameters ---------- path : str or `os.Pathlike` Path to a .wav file mono : bool If the provided .wav has more than one channel, it will be converted to mono if ``mono=True``. (Default value = True) Returns ------- audio_data : np.ndarray Array of audio samples, normalized to the range [-1., 1.] fs : int Sampling rate of the audio data """ fs, audio_data = scipy.io.wavfile.read(path) # Make float in range [-1, 1] if audio_data.dtype == "int8": audio_data = audio_data / float(2**8) elif audio_data.dtype == "int16": audio_data = audio_data / float(2**16) elif audio_data.dtype == "int32": audio_data = audio_data / float(2**24) else: raise ValueError("Got unexpected .wav data type " "{}".format(audio_data.dtype)) # Optionally convert to mono if mono and audio_data.ndim != 1: audio_data = audio_data.mean(axis=1) return audio_data, fs def load_valued_intervals(filename, delimiter=r"\s+", comment="#"): r"""Import valued intervals from an annotation file. The file should consist of three columns: Two consisting of numeric values corresponding to start and end time of each interval and a third, also of numeric values, corresponding to the value of each interval. This is primarily useful for processing events which span a duration and have a numeric value, such as piano-roll notes which have an onset, offset, and a pitch value. Parameters ---------- filename : str or `os.Pathlike` Path to the annotation file delimiter : str Separator regular expression. By default, lines will be split by any amount of whitespace. comment : str or None Comment regular expression. Any lines beginning with this string or pattern will be ignored. Setting to `None` disables comments. Returns ------- intervals : np.ndarray, shape=(n_events, 2) Array of event start and end times values : np.ndarray, shape=(n_events,) Array of values """ # Use our universal function to load in the events starts, ends, values = load_delimited( filename, [float, float, float], delimiter=delimiter, comment=comment ) # Stack into an interval matrix intervals = np.array([starts, ends]).T # Validate them, but throw a warning in place of an error try: util.validate_intervals(intervals) except ValueError as error: warnings.warn(error.args[0]) # return values as np.ndarray values = np.array(values) return intervals, values def load_key(filename, delimiter=r"\s+", comment="#"): r"""Load key labels from an annotation file. The file should consist of two string columns: One denoting the key scale degree (semitone), and the other denoting the mode (major or minor). The file should contain only one row. Parameters ---------- filename : str or `os.Pathlike` Path to the annotation file delimiter : str Separator regular expression. By default, lines will be split by any amount of whitespace. comment : str or None Comment regular expression. Any lines beginning with this string or pattern will be ignored. Setting to `None` disables comments. Returns ------- key : str Key label, in the form ``'(key) (mode)'`` """ # Use our universal function to load the key and mode strings scale, mode = load_delimited( filename, [str, str], delimiter=delimiter, comment=comment ) if len(scale) != 1: raise ValueError("Key file should contain only one line.") scale, mode = scale[0], mode[0] # Join with a space key_string = f"{scale} {mode}" # Validate them, but throw a warning in place of an error try: key.validate_key(key_string) except ValueError as error: warnings.warn(error.args[0]) return key_string def load_tempo(filename, delimiter=r"\s+", comment="#"): r"""Load tempo estimates from an annotation file in MIREX format. The file should consist of three numeric columns: the first two correspond to tempo estimates (in beats-per-minute), and the third denotes the relative confidence of the first value compared to the second (in the range [0, 1]). The file should contain only one row. Parameters ---------- filename : str or `os.Pathlike` Path to the annotation file delimiter : str Separator regular expression. By default, lines will be split by any amount of whitespace. comment : str or None Comment regular expression. Any lines beginning with this string or pattern will be ignored. Setting to `None` disables comments. Returns ------- tempi : np.ndarray, non-negative The two tempo estimates weight : float [0, 1] The relative importance of ``tempi[0]`` compared to ``tempi[1]`` """ # Use our universal function to load the key and mode strings t1, t2, weight = load_delimited( filename, [float, float, float], delimiter=delimiter, comment=comment ) weight = weight[0] tempi = np.concatenate([t1, t2]) if len(t1) != 1: raise ValueError("Tempo file should contain only one line.") # Validate them, but throw a warning in place of an error try: tempo.validate_tempi(tempi) except ValueError as error: warnings.warn(error.args[0]) if not 0 <= weight <= 1: raise ValueError(f"Invalid weight: {weight}") return tempi, weight def load_ragged_time_series( filename, dtype=float, delimiter=r"\s+", header=False, comment="#" ): r"""Load data from a delimited time series annotation file with a variable number of columns. This function assumes that column 0 contains time stamps and columns 1 through n contain values. n may be variable from time stamp to time stamp. Examples -------- >>> # Load a ragged list of tab-delimited multi-f0 midi notes >>> times, vals = load_ragged_time_series('multif0.txt', dtype=int, delimiter='\t') >>> # Load a raggled list of space delimited multi-f0 values with a header >>> times, vals = load_ragged_time_series('labeled_events.csv', header=True) Parameters ---------- filename : str or `os.Pathlike` Path to the annotation file dtype : function Data type to apply to values columns. delimiter : str Separator regular expression. By default, lines will be split by any amount of whitespace. header : bool Indicates whether a header row is present or not. By default, assumes no header is present. comment : str or None Comment regular expression. Any lines beginning with this string or pattern will be ignored. Setting to `None` disables comments. Returns ------- times : np.ndarray array of timestamps (float) values : list of np.ndarray list of arrays of corresponding values """ # Initialize empty lists times = [] values = [] # Create re object for splitting lines splitter = re.compile(delimiter) # And one for comments if comment is None: commenter = None else: commenter = re.compile(f"^{comment}") if header: start_row = 1 else: start_row = 0 with _open(filename, mode="r") as input_file: for row, line in enumerate(input_file, start_row): # If this is a comment line, skip it if comment is not None and commenter.match(line): continue # Split each line using the supplied delimiter data = splitter.split(line.strip()) try: converted_time = float(data[0]) except (TypeError, ValueError) as exe: raise ValueError( "Couldn't convert value {} using {} " "found at {}:{:d}:\n\t{}".format( data[0], float.__name__, filename, row, line ) ) from exe times.append(converted_time) # cast values to a numpy array. time stamps with no values are cast # to an empty array. try: converted_value = np.array(data[1:], dtype=dtype) except (TypeError, ValueError) as exe: raise ValueError( "Couldn't convert value {} using {} " "found at {}:{:d}:\n\t{}".format( data[1:], dtype.__name__, filename, row, line ) ) from exe values.append(converted_value) return np.array(times), values mir_eval-0.8.2/mir_eval/key.py000066400000000000000000000153551475740344600163060ustar00rootroot00000000000000""" Key Detection involves determining the underlying key (distribution of notes and note transitions) in a piece of music. Key detection algorithms are evaluated by comparing their estimated key to a ground-truth reference key and reporting a score according to the relationship of the keys. Conventions ----------- Keys are represented as strings of the form ``'(key) (mode)'``, e.g. ``'C# major'`` or ``'Fb minor'``. The case of the key is ignored. Note that certain key strings are equivalent, e.g. ``'C# major'`` and ``'Db major'``. The mode may only be specified as either ``'major'`` or ``'minor'``, no other mode strings will be accepted. Metrics ------- * :func:`mir_eval.key.weighted_score`: Heuristic scoring of the relation of two keys. """ import collections from . import util KEY_TO_SEMITONE = { "c": 0, "c#": 1, "db": 1, "d": 2, "d#": 3, "eb": 3, "e": 4, "f": 5, "f#": 6, "gb": 6, "g": 7, "g#": 8, "ab": 8, "a": 9, "a#": 10, "bb": 10, "b": 11, "x": None, } def validate_key(key): """Check that a key is well-formatted, e.g. in the form ``'C# major'``. The Key can be 'X' if it is not possible to categorize the Key and mode can be 'other' if it can't be categorized as major or minor. Parameters ---------- key : str Key to verify """ if len(key.split()) != 2 and not (len(key.split()) and key.lower() == "x"): raise ValueError("'{}' is not in the form '(key) (mode)' " "or 'X'".format(key)) if key.lower() != "x": key, mode = key.split() if key.lower() == "x": raise ValueError( "Mode {} is invalid; 'X' (Uncategorized) " "doesn't have mode".format(mode) ) if key.lower() not in KEY_TO_SEMITONE: raise ValueError( "Key {} is invalid; should be e.g. D or C# or Eb or " "X (Uncategorized)".format(key) ) if mode not in ["major", "minor", "other"]: raise ValueError( f"Mode '{mode}' is invalid; must be 'major', 'minor' or 'other'" ) def validate(reference_key, estimated_key): """Check that the input annotations to a metric are valid key strings and throws helpful errors if not. Parameters ---------- reference_key : str Reference key string. estimated_key : str Estimated key string. """ for key in [reference_key, estimated_key]: validate_key(key) def split_key_string(key): """Split a key string (of the form, e.g. ``'C# major'``), into a tuple of ``(key, mode)`` where ``key`` is is an integer representing the semitone distance from C. Parameters ---------- key : str String representing a key. Returns ------- key : int Number of semitones above C. mode : str String representing the mode. """ if key.lower() != "x": key, mode = key.split() else: mode = None return KEY_TO_SEMITONE[key.lower()], mode def weighted_score(reference_key, estimated_key): """Compute a heuristic score which is weighted according to the relationship of the reference and estimated key, as follows: +------------------------------------------------------+-------+ | Relationship | Score | +------------------------------------------------------+-------+ | Same key and mode | 1.0 | +------------------------------------------------------+-------+ | Estimated key is a perfect fifth above reference key | 0.5 | +------------------------------------------------------+-------+ | Relative major/minor (same key signature) | 0.3 | +------------------------------------------------------+-------+ | Parallel major/minor (same key) | 0.2 | +------------------------------------------------------+-------+ | Other | 0.0 | +------------------------------------------------------+-------+ Examples -------- >>> ref_key = mir_eval.io.load_key('ref.txt') >>> est_key = mir_eval.io.load_key('est.txt') >>> score = mir_eval.key.weighted_score(ref_key, est_key) Parameters ---------- reference_key : str Reference key string. estimated_key : str Estimated key string. Returns ------- score : float Score representing how closely related the keys are. """ validate(reference_key, estimated_key) reference_key, reference_mode = split_key_string(reference_key) estimated_key, estimated_mode = split_key_string(estimated_key) # If keys are the same, return 1. if reference_key == estimated_key and reference_mode == estimated_mode: return 1.0 # If reference or estimated key are x and they are not the same key # then the result is 'Other'. if reference_key is None or estimated_key is None: return 0.0 # If keys are the same mode and a perfect fifth (differ by 7 semitones) if estimated_mode == reference_mode and (estimated_key - reference_key) % 12 == 7: return 0.5 # Estimated key is relative minor of reference key (9 semitones) if ( estimated_mode != reference_mode == "major" and (estimated_key - reference_key) % 12 == 9 ): return 0.3 # Estimated key is relative major of reference key (3 semitones) if ( estimated_mode != reference_mode == "minor" and (estimated_key - reference_key) % 12 == 3 ): return 0.3 # If keys are in different modes and parallel (same key name) if estimated_mode != reference_mode and reference_key == estimated_key: return 0.2 # Otherwise return 0 return 0.0 def evaluate(reference_key, estimated_key, **kwargs): """Compute all metrics for the given reference and estimated annotations. Examples -------- >>> ref_key = mir_eval.io.load_key('reference.txt') >>> est_key = mir_eval.io.load_key('estimated.txt') >>> scores = mir_eval.key.evaluate(ref_key, est_key) Parameters ---------- reference_key : str Reference key string. estimated_key : str Estimated key string. **kwargs Additional keyword arguments which will be passed to the appropriate metric or preprocessing functions. Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. """ # Compute all metrics scores = collections.OrderedDict() scores["Weighted Score"] = util.filter_kwargs( weighted_score, reference_key, estimated_key ) return scores mir_eval-0.8.2/mir_eval/melody.py000066400000000000000000000755461475740344600170170ustar00rootroot00000000000000# CREATED:2014-03-07 by Justin Salamon """ Melody extraction algorithms aim to produce a sequence of frequency values corresponding to the pitch of the dominant melody from a musical recording. For evaluation, an estimated pitch series is evaluated against a reference based on whether the voicing (melody present or not) and the pitch is correct (within some tolerance). For a detailed explanation of the measures please refer to: J. Salamon, E. Gomez, D. P. W. Ellis and G. Richard, "Melody Extraction from Polyphonic Music Signals: Approaches, Applications and Challenges", IEEE Signal Processing Magazine, 31(2):118-134, Mar. 2014. and: G. E. Poliner, D. P. W. Ellis, A. F. Ehmann, E. Gomez, S. Streich, and B. Ong. "Melody transcription from music audio: Approaches and evaluation", IEEE Transactions on Audio, Speech, and Language Processing, 15(4):1247-1256, 2007. For an explanation of the generalized measures (using non-binary voicings), please refer to: R. Bittner and J. Bosch, "Generalized Metrics for Single-F0 Estimation Evaluation", International Society for Music Information Retrieval Conference (ISMIR), 2019. Conventions ----------- Melody annotations are assumed to be given in the format of a 1d array of frequency values which are accompanied by a 1d array of times denoting when each frequency value occurs. In a reference melody time series, a frequency value of 0 denotes "unvoiced". In a estimated melody time series, unvoiced frames can be indicated either by 0 Hz or by a negative Hz value - negative values represent the algorithm's pitch estimate for frames it has determined as unvoiced, in case they are in fact voiced. Metrics are computed using a sequence of reference and estimated pitches in cents and voicing arrays, both of which are sampled to the same timebase. The function :func:`mir_eval.melody.to_cent_voicing` can be used to convert a sequence of estimated and reference times and frequency values in Hz to voicing arrays and frequency arrays in the format required by the metric functions. By default, the convention is to resample the estimated melody time series to the reference melody time series' timebase. Metrics ------- * :func:`mir_eval.melody.voicing_measures`: Voicing measures, including the recall rate (proportion of frames labeled as melody frames in the reference that are estimated as melody frames) and the false alarm rate (proportion of frames labeled as non-melody in the reference that are mistakenly estimated as melody frames) * :func:`mir_eval.melody.raw_pitch_accuracy`: Raw Pitch Accuracy, which computes the proportion of melody frames in the reference for which the frequency is considered correct (i.e. within half a semitone of the reference frequency) * :func:`mir_eval.melody.raw_chroma_accuracy`: Raw Chroma Accuracy, where the estimated and reference frequency sequences are mapped onto a single octave before computing the raw pitch accuracy * :func:`mir_eval.melody.overall_accuracy`: Overall Accuracy, which computes the proportion of all frames correctly estimated by the algorithm, including whether non-melody frames where labeled by the algorithm as non-melody """ import numpy as np import scipy.interpolate import collections import warnings from . import util def validate_voicing(ref_voicing, est_voicing): """Check that voicing inputs to a metric are in the correct format. Parameters ---------- ref_voicing : np.ndarray Reference voicing array est_voicing : np.ndarray Estimated voicing array """ if ref_voicing.size == 0: warnings.warn("Reference voicing array is empty.") if est_voicing.size == 0: warnings.warn("Estimated voicing array is empty.") if ref_voicing.sum() == 0: warnings.warn("Reference melody has no voiced frames.") if est_voicing.sum() == 0: warnings.warn("Estimated melody has no voiced frames.") # Make sure they're the same length if ref_voicing.shape[0] != est_voicing.shape[0]: raise ValueError( "Reference and estimated voicing arrays should " "be the same length." ) for voicing in [ref_voicing, est_voicing]: # Make sure voicing is between 0 and 1 if np.logical_or(voicing < 0, voicing > 1).any(): raise ValueError("Voicing arrays must be between 0 and 1.") def validate(ref_voicing, ref_cent, est_voicing, est_cent): """Check that voicing and frequency arrays are well-formed. To be used in conjunction with :func:`mir_eval.melody.validate_voicing` Parameters ---------- ref_voicing : np.ndarray Reference voicing array ref_cent : np.ndarray Reference pitch sequence in cents est_voicing : np.ndarray Estimated voicing array est_cent : np.ndarray Estimate pitch sequence in cents """ if ref_cent.size == 0: warnings.warn("Reference frequency array is empty.") if est_cent.size == 0: warnings.warn("Estimated frequency array is empty.") # Make sure they're the same length if ( ref_voicing.shape[0] != ref_cent.shape[0] or est_voicing.shape[0] != est_cent.shape[0] or ref_cent.shape[0] != est_cent.shape[0] ): raise ValueError( "All voicing and frequency arrays must have the " "same length." ) def hz2cents(freq_hz, base_frequency=10.0): """Convert an array of frequency values in Hz to cents. 0 values are left in place. Parameters ---------- freq_hz : np.ndarray Array of frequencies in Hz. base_frequency : float Base frequency for conversion. (Default value = 10.0) """ freq_cent = np.zeros(freq_hz.shape[0]) freq_nonz_ind = np.flatnonzero(freq_hz) normalized_frequency = np.abs(freq_hz[freq_nonz_ind]) / base_frequency freq_cent[freq_nonz_ind] = 1200.0 * np.log2(normalized_frequency) return freq_cent def freq_to_voicing(frequencies, voicing=None): """Convert from an array of frequency values to frequency array + voice/unvoiced array Parameters ---------- frequencies : np.ndarray Array of frequencies. A frequency <= 0 indicates "unvoiced". voicing : np.ndarray Array of voicing values. (Default value = None) Default None, which means the voicing is inferred from `frequencies`: - frames with frequency <= 0.0 are considered "unvoiced" - frames with frequency > 0.0 are considered "voiced" If specified, `voicing` is used as the voicing array, but frequencies with value 0 are forced to have 0 voicing. - Voicing inferred by negative frequency values is ignored. Returns ------- frequencies : np.ndarray Array of frequencies, all >= 0. voiced : np.ndarray Array of voicings between 0 and 1, same length as frequencies, which indicates voiced or unvoiced """ if voicing is not None: voicing[frequencies == 0] = 0 else: voicing = (frequencies > 0).astype(float) return np.abs(frequencies), voicing def constant_hop_timebase(hop, end_time): """Generate a time series from 0 to ``end_time`` with times spaced ``hop`` apart Parameters ---------- hop : float Spacing of samples in the time series end_time : float Time series will span ``[0, end_time]`` Returns ------- times : np.ndarray Generated timebase """ # Compute new timebase. Rounding/linspace is to avoid float problems. end_time = np.round(end_time, 10) times = np.linspace( 0, hop * int(np.floor(end_time / hop)), int(np.floor(end_time / hop)) + 1 ) times = np.round(times, 10) return times def resample_melody_series(times, frequencies, voicing, times_new, kind="linear"): """Resamples frequency and voicing time series to a new timescale. Maintains any zero ("unvoiced") values in frequencies. If ``times`` and ``times_new`` are equivalent, no resampling will be performed. Parameters ---------- times : np.ndarray Times of each frequency value frequencies : np.ndarray Array of frequency values, >= 0 voicing : np.ndarray Array which indicates voiced or unvoiced. This array may be binary or have continuous values between 0 and 1. times_new : np.ndarray Times to resample frequency and voicing sequences to kind : str kind parameter to pass to scipy.interpolate.interp1d. (Default value = 'linear') Returns ------- frequencies_resampled : np.ndarray Frequency array resampled to new timebase voicing_resampled : np.ndarray Voicing array resampled to new timebase """ # If the timebases are already the same, no need to interpolate if times.shape == times_new.shape and np.allclose(times, times_new): return frequencies, voicing # Warn when the delta between the original times is not constant, # unless times[0] == 0. and frequencies[0] == frequencies[1] (see logic at # the beginning of to_cent_voicing) if not ( np.allclose(np.diff(times), np.diff(times).mean()) or ( np.allclose(np.diff(times[1:]), np.diff(times[1:]).mean()) and frequencies[0] == frequencies[1] ) ): warnings.warn( "Non-uniform timescale passed to resample_melody_series. Pitch " "will be linearly interpolated, which will result in undesirable " "behavior if silences are indicated by missing values. Silences " "should be indicated by nonpositive frequency values." ) # Round to avoid floating point problems times = np.round(times, 10) times_new = np.round(times_new, 10) # Add in an additional sample if we'll be asking for a time too large if times_new.max() > times.max(): times = np.append(times, times_new.max()) frequencies = np.append(frequencies, 0) voicing = np.append(voicing, 0) # We need to fix zero transitions if interpolation is not zero or nearest if kind != "zero" and kind != "nearest": # Fill in zero values with the last reported frequency # to avoid erroneous values when resampling frequencies_held = np.array(frequencies) for n, frequency in enumerate(frequencies[1:]): if frequency == 0: frequencies_held[n + 1] = frequencies_held[n] # Linearly interpolate frequencies frequencies_resampled = scipy.interpolate.interp1d( times, frequencies_held, kind )(times_new) # Retain zeros frequency_mask = scipy.interpolate.interp1d(times, frequencies, "zero")( times_new ) frequencies_resampled *= frequency_mask != 0 else: frequencies_resampled = scipy.interpolate.interp1d(times, frequencies, kind)( times_new ) # Use nearest-neighbor for voicing if it was used for frequencies # if voicing is not binary, use linear interpolation is_binary_voicing = np.all( np.logical_or(np.equal(voicing, 0), np.equal(voicing, 1)) ) if kind == "nearest" or (kind == "linear" and not is_binary_voicing): voicing_resampled = scipy.interpolate.interp1d(times, voicing, kind)(times_new) # otherwise, always use zeroth order else: voicing_resampled = scipy.interpolate.interp1d(times, voicing, "zero")( times_new ) return frequencies_resampled, voicing_resampled def to_cent_voicing( ref_time, ref_freq, est_time, est_freq, est_voicing=None, ref_reward=None, base_frequency=10.0, hop=None, kind="linear", ): """Convert reference and estimated time/frequency (Hz) annotations to sampled frequency (cent)/voicing arrays. A zero frequency indicates "unvoiced". If est_voicing is not provided, a negative frequency indicates: "Predicted as unvoiced, but if it's voiced, this is the frequency estimate". If it is provided, negative frequency values are ignored, and the voicing from est_voicing is directly used. Parameters ---------- ref_time : np.ndarray Time of each reference frequency value ref_freq : np.ndarray Array of reference frequency values est_time : np.ndarray Time of each estimated frequency value est_freq : np.ndarray Array of estimated frequency values est_voicing : np.ndarray Estimate voicing confidence. Default None, which means the voicing is inferred from est_freq: - frames with frequency <= 0.0 are considered "unvoiced" - frames with frequency > 0.0 are considered "voiced" ref_reward : np.ndarray Reference voicing reward. Default None, which means all frames are weighted equally. base_frequency : float Base frequency in Hz for conversion to cents (Default value = 10.) hop : float Hop size, in seconds, to resample, default None which means use ref_time kind : str kind parameter to pass to scipy.interpolate.interp1d. (Default value = 'linear') Returns ------- ref_voicing : np.ndarray Resampled reference voicing array ref_cent : np.ndarray Resampled reference frequency (cent) array est_voicing : np.ndarray Resampled estimated voicing array est_cent : np.ndarray Resampled estimated frequency (cent) array """ # Check if missing sample at time 0 and if so add one if ref_time[0] > 0: ref_time = np.insert(ref_time, 0, 0) ref_freq = np.insert(ref_freq, 0, ref_freq[0]) if ref_reward is not None: ref_reward = np.insert(ref_reward, 0, ref_reward[0]) if est_time[0] > 0: est_time = np.insert(est_time, 0, 0) est_freq = np.insert(est_freq, 0, est_freq[0]) if est_voicing is not None: est_voicing = np.insert(est_voicing, 0, est_voicing[0]) # Get separated frequency array and voicing array ref_freq, ref_voicing = freq_to_voicing(ref_freq, ref_reward) est_freq, est_voicing = freq_to_voicing(est_freq, est_voicing) # convert both sequences to cents ref_cent = hz2cents(ref_freq, base_frequency) est_cent = hz2cents(est_freq, base_frequency) # If we received a hop, use it to resample both if hop is not None: # Resample to common time base ref_cent, ref_voicing = resample_melody_series( ref_time, ref_cent, ref_voicing, constant_hop_timebase(hop, ref_time.max()), kind, ) est_cent, est_voicing = resample_melody_series( est_time, est_cent, est_voicing, constant_hop_timebase(hop, est_time.max()), kind, ) # Otherwise, only resample estimated to the reference time base else: est_cent, est_voicing = resample_melody_series( est_time, est_cent, est_voicing, ref_time, kind ) # ensure the estimated sequence is the same length as the reference len_diff = ref_cent.shape[0] - est_cent.shape[0] if len_diff >= 0: est_cent = np.append(est_cent, np.zeros(len_diff)) est_voicing = np.append(est_voicing, np.zeros(len_diff)) else: est_cent = est_cent[: ref_cent.shape[0]] est_voicing = est_voicing[: ref_voicing.shape[0]] return (ref_voicing, ref_cent, est_voicing, est_cent) def voicing_recall(ref_voicing, est_voicing): """Compute the voicing recall given two voicing indicator sequences, one as reference (truth) and the other as the estimate (prediction). The sequences must be of the same length. Examples -------- >>> ref_time, ref_freq = mir_eval.io.load_time_series('ref.txt') >>> est_time, est_freq = mir_eval.io.load_time_series('est.txt') >>> (ref_v, ref_c, ... est_v, est_c) = mir_eval.melody.to_cent_voicing(ref_time, ... ref_freq, ... est_time, ... est_freq) >>> recall = mir_eval.melody.voicing_recall(ref_v, est_v) Parameters ---------- ref_voicing : np.ndarray Reference boolean voicing array est_voicing : np.ndarray Estimated boolean voicing array Returns ------- vx_recall : float Voicing recall rate, the fraction of voiced frames in ref indicated as voiced in est """ if ref_voicing.size == 0 or est_voicing.size == 0: return 0.0 ref_indicator = (ref_voicing > 0).astype(float) if np.sum(ref_indicator) == 0: return 1 return np.sum(est_voicing * ref_indicator) / np.sum(ref_indicator) def voicing_false_alarm(ref_voicing, est_voicing): """Compute the voicing false alarm rates given two voicing indicator sequences, one as reference (truth) and the other as the estimate (prediction). The sequences must be of the same length. Examples -------- >>> ref_time, ref_freq = mir_eval.io.load_time_series('ref.txt') >>> est_time, est_freq = mir_eval.io.load_time_series('est.txt') >>> (ref_v, ref_c, ... est_v, est_c) = mir_eval.melody.to_cent_voicing(ref_time, ... ref_freq, ... est_time, ... est_freq) >>> false_alarm = mir_eval.melody.voicing_false_alarm(ref_v, est_v) Parameters ---------- ref_voicing : np.ndarray Reference boolean voicing array est_voicing : np.ndarray Estimated boolean voicing array Returns ------- vx_false_alarm : float Voicing false alarm rate, the fraction of unvoiced frames in ref indicated as voiced in est """ if ref_voicing.size == 0 or est_voicing.size == 0: return 0.0 ref_indicator = (ref_voicing == 0).astype(float) if np.sum(ref_indicator) == 0: return 0 return np.sum(est_voicing * ref_indicator) / np.sum(ref_indicator) def voicing_measures(ref_voicing, est_voicing): """Compute the voicing recall and false alarm rates given two voicing indicator sequences, one as reference (truth) and the other as the estimate (prediction). The sequences must be of the same length. Examples -------- >>> ref_time, ref_freq = mir_eval.io.load_time_series('ref.txt') >>> est_time, est_freq = mir_eval.io.load_time_series('est.txt') >>> (ref_v, ref_c, ... est_v, est_c) = mir_eval.melody.to_cent_voicing(ref_time, ... ref_freq, ... est_time, ... est_freq) >>> recall, false_alarm = mir_eval.melody.voicing_measures(ref_v, ... est_v) Parameters ---------- ref_voicing : np.ndarray Reference boolean voicing array est_voicing : np.ndarray Estimated boolean voicing array Returns ------- vx_recall : float Voicing recall rate, the fraction of voiced frames in ref indicated as voiced in est vx_false_alarm : float Voicing false alarm rate, the fraction of unvoiced frames in ref indicated as voiced in est """ validate_voicing(ref_voicing, est_voicing) vx_recall = voicing_recall(ref_voicing, est_voicing) vx_false_alm = voicing_false_alarm(ref_voicing, est_voicing) return vx_recall, vx_false_alm def raw_pitch_accuracy(ref_voicing, ref_cent, est_voicing, est_cent, cent_tolerance=50): """Compute the raw pitch accuracy given two pitch (frequency) sequences in cents and matching voicing indicator sequences. The first pitch and voicing arrays are treated as the reference (truth), and the second two as the estimate (prediction). All 4 sequences must be of the same length. Examples -------- >>> ref_time, ref_freq = mir_eval.io.load_time_series('ref.txt') >>> est_time, est_freq = mir_eval.io.load_time_series('est.txt') >>> (ref_v, ref_c, ... est_v, est_c) = mir_eval.melody.to_cent_voicing(ref_time, ... ref_freq, ... est_time, ... est_freq) >>> raw_pitch = mir_eval.melody.raw_pitch_accuracy(ref_v, ref_c, ... est_v, est_c) Parameters ---------- ref_voicing : np.ndarray Reference voicing array. When this array is non-binary, it is treated as a 'reference reward', as in (Bittner & Bosch, 2019) ref_cent : np.ndarray Reference pitch sequence in cents est_voicing : np.ndarray Estimated voicing array est_cent : np.ndarray Estimate pitch sequence in cents cent_tolerance : float Maximum absolute deviation in cents for a frequency value to be considered correct (Default value = 50) Returns ------- raw_pitch : float Raw pitch accuracy, the fraction of voiced frames in ref_cent for which est_cent provides a correct frequency values (within cent_tolerance cents). """ validate_voicing(ref_voicing, est_voicing) validate(ref_voicing, ref_cent, est_voicing, est_cent) # When input arrays are empty, return 0 by special case # If there are no voiced frames in reference, metric is 0 if ( ref_voicing.size == 0 or ref_voicing.sum() == 0 or ref_cent.size == 0 or est_cent.size == 0 ): return 0.0 # Raw pitch = the number of voiced frames in the reference for which the # estimate provides a correct frequency value (within cent_tolerance cents) # NB: voicing estimation is ignored in this measure nonzero_freqs = np.logical_and(est_cent != 0, ref_cent != 0) if sum(nonzero_freqs) == 0: return 0.0 freq_diff_cents = np.abs(ref_cent - est_cent)[nonzero_freqs] correct_frequencies = freq_diff_cents < cent_tolerance rpa = np.sum(ref_voicing[nonzero_freqs] * correct_frequencies) / np.sum(ref_voicing) return rpa def raw_chroma_accuracy( ref_voicing, ref_cent, est_voicing, est_cent, cent_tolerance=50 ): """Compute the raw chroma accuracy given two pitch (frequency) sequences in cents and matching voicing indicator sequences. The first pitch and voicing arrays are treated as the reference (truth), and the second two as the estimate (prediction). All 4 sequences must be of the same length. Examples -------- >>> ref_time, ref_freq = mir_eval.io.load_time_series('ref.txt') >>> est_time, est_freq = mir_eval.io.load_time_series('est.txt') >>> (ref_v, ref_c, ... est_v, est_c) = mir_eval.melody.to_cent_voicing(ref_time, ... ref_freq, ... est_time, ... est_freq) >>> raw_chroma = mir_eval.melody.raw_chroma_accuracy(ref_v, ref_c, ... est_v, est_c) Parameters ---------- ref_voicing : np.ndarray Reference voicing array. When this array is non-binary, it is treated as a 'reference reward', as in (Bittner & Bosch, 2019) ref_cent : np.ndarray Reference pitch sequence in cents est_voicing : np.ndarray Estimated voicing array est_cent : np.ndarray Estimate pitch sequence in cents cent_tolerance : float Maximum absolute deviation in cents for a frequency value to be considered correct (Default value = 50) Returns ------- raw_chroma : float Raw chroma accuracy, the fraction of voiced frames in ref_cent for which est_cent provides a correct frequency values (within cent_tolerance cents), ignoring octave errors """ validate_voicing(ref_voicing, est_voicing) validate(ref_voicing, ref_cent, est_voicing, est_cent) # When input arrays are empty, return 0 by special case # If there are no voiced frames in reference, metric is 0 if ( ref_voicing.size == 0 or ref_voicing.sum() == 0 or ref_cent.size == 0 or est_cent.size == 0 ): return 0.0 # # Raw chroma = same as raw pitch except that octave errors are ignored. nonzero_freqs = np.logical_and(est_cent != 0, ref_cent != 0) if sum(nonzero_freqs) == 0: return 0.0 freq_diff_cents = np.abs(ref_cent - est_cent)[nonzero_freqs] octave = 1200.0 * np.floor(freq_diff_cents / 1200 + 0.5) correct_chroma = np.abs(freq_diff_cents - octave) < cent_tolerance rca = np.sum(ref_voicing[nonzero_freqs] * correct_chroma) / np.sum(ref_voicing) return rca def overall_accuracy(ref_voicing, ref_cent, est_voicing, est_cent, cent_tolerance=50): """Compute the overall accuracy given two pitch (frequency) sequences in cents and matching voicing indicator sequences. The first pitch and voicing arrays are treated as the reference (truth), and the second two as the estimate (prediction). All 4 sequences must be of the same length. Examples -------- >>> ref_time, ref_freq = mir_eval.io.load_time_series('ref.txt') >>> est_time, est_freq = mir_eval.io.load_time_series('est.txt') >>> (ref_v, ref_c, ... est_v, est_c) = mir_eval.melody.to_cent_voicing(ref_time, ... ref_freq, ... est_time, ... est_freq) >>> overall_accuracy = mir_eval.melody.overall_accuracy(ref_v, ref_c, ... est_v, est_c) Parameters ---------- ref_voicing : np.ndarray Reference voicing array. When this array is non-binary, it is treated as a 'reference reward', as in (Bittner & Bosch, 2019) ref_cent : np.ndarray Reference pitch sequence in cents est_voicing : np.ndarray Estimated voicing array est_cent : np.ndarray Estimate pitch sequence in cents cent_tolerance : float Maximum absolute deviation in cents for a frequency value to be considered correct (Default value = 50) Returns ------- overall_accuracy : float Overall accuracy, the total fraction of correctly estimates frames, where provides a correct frequency values (within cent_tolerance). """ validate_voicing(ref_voicing, est_voicing) validate(ref_voicing, ref_cent, est_voicing, est_cent) # When input arrays are empty, return 0 by special case if ( ref_voicing.size == 0 or est_voicing.size == 0 or ref_cent.size == 0 or est_cent.size == 0 ): return 0.0 nonzero_freqs = np.logical_and(est_cent != 0, ref_cent != 0) freq_diff_cents = np.abs(ref_cent - est_cent)[nonzero_freqs] correct_frequencies = freq_diff_cents < cent_tolerance ref_binary = (ref_voicing > 0).astype(float) n_frames = float(len(ref_voicing)) if np.sum(ref_voicing) == 0: ratio = 0.0 else: ratio = np.sum(ref_binary) / np.sum(ref_voicing) accuracy = ( ( ratio * np.sum( ref_voicing[nonzero_freqs] * est_voicing[nonzero_freqs] * correct_frequencies ) ) + np.sum((1.0 - ref_binary) * (1.0 - est_voicing)) ) / n_frames return accuracy def evaluate( ref_time, ref_freq, est_time, est_freq, est_voicing=None, ref_reward=None, **kwargs ): """Evaluate two melody (predominant f0) transcriptions, where the first is treated as the reference (ground truth) and the second as the estimate to be evaluated (prediction). Examples -------- >>> ref_time, ref_freq = mir_eval.io.load_time_series('ref.txt') >>> est_time, est_freq = mir_eval.io.load_time_series('est.txt') >>> scores = mir_eval.melody.evaluate(ref_time, ref_freq, ... est_time, est_freq) Parameters ---------- ref_time : np.ndarray Time of each reference frequency value ref_freq : np.ndarray Array of reference frequency values est_time : np.ndarray Time of each estimated frequency value est_freq : np.ndarray Array of estimated frequency values est_voicing : np.ndarray Estimate voicing confidence. Default None, which means the voicing is inferred from est_freq: - frames with frequency <= 0.0 are considered "unvoiced" - frames with frequency > 0.0 are considered "voiced" ref_reward : np.ndarray Reference pitch estimation reward. Default None, which means all frames are weighted equally. **kwargs Additional keyword arguments which will be passed to the appropriate metric or preprocessing functions. Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. References ---------- .. [#] J. Salamon, E. Gomez, D. P. W. Ellis and G. Richard, "Melody Extraction from Polyphonic Music Signals: Approaches, Applications and Challenges", IEEE Signal Processing Magazine, 31(2):118-134, Mar. 2014. .. [#] G. E. Poliner, D. P. W. Ellis, A. F. Ehmann, E. Gomez, S. Streich, and B. Ong. "Melody transcription from music audio: Approaches and evaluation", IEEE Transactions on Audio, Speech, and Language Processing, 15(4):1247-1256, 2007. .. [#] R. Bittner and J. Bosch, "Generalized Metrics for Single-F0 Estimation Evaluation", International Society for Music Information Retrieval Conference (ISMIR), 2019. """ # Convert to reference/estimated voicing/frequency (cent) arrays (ref_voicing, ref_cent, est_voicing, est_cent) = util.filter_kwargs( to_cent_voicing, ref_time, ref_freq, est_time, est_freq, est_voicing, ref_reward, **kwargs ) # Compute metrics scores = collections.OrderedDict() scores["Voicing Recall"] = util.filter_kwargs( voicing_recall, ref_voicing, est_voicing, **kwargs ) scores["Voicing False Alarm"] = util.filter_kwargs( voicing_false_alarm, ref_voicing, est_voicing, **kwargs ) scores["Raw Pitch Accuracy"] = util.filter_kwargs( raw_pitch_accuracy, ref_voicing, ref_cent, est_voicing, est_cent, **kwargs ) scores["Raw Chroma Accuracy"] = util.filter_kwargs( raw_chroma_accuracy, ref_voicing, ref_cent, est_voicing, est_cent, **kwargs ) scores["Overall Accuracy"] = util.filter_kwargs( overall_accuracy, ref_voicing, ref_cent, est_voicing, est_cent, **kwargs ) return scores mir_eval-0.8.2/mir_eval/multipitch.py000066400000000000000000000411451475740344600176740ustar00rootroot00000000000000""" The goal of multiple f0 (multipitch) estimation and tracking is to identify all of the active fundamental frequencies in each time frame in a complex music signal. Conventions ----------- Multipitch estimates are represented by a timebase and a corresponding list of arrays of frequency estimates. Frequency estimates may have any number of frequency values, including 0 (represented by an empty array). Time values are in units of seconds and frequency estimates are in units of Hz. The timebase of the estimate time series should ideally match the timebase of the reference time series, but if this is not the case, the estimate time series is resampled using a nearest neighbor interpolation to match the estimate. Time values in the estimate time series that are outside of the range of the reference time series are given null (empty array) frequencies. By default, a frequency is "correct" if it is within 0.5 semitones of a reference frequency. Frequency values are compared by first mapping them to log-2 semitone space, where the distance between semitones is constant. Chroma-wrapped frequency values are computed by taking the log-2 frequency values modulo 12 to map them down to a single octave. A chroma-wrapped frequency estimate is correct if it's single-octave value is within 0.5 semitones of the single-octave reference frequency. The metrics are based on those described in [#poliner2007]_ and [#bay2009]_. Metrics ------- * :func:`mir_eval.multipitch.metrics`: Precision, Recall, Accuracy, Substitution, Miss, False Alarm, and Total Error scores based both on raw frequency values and values mapped to a single octave (chroma). References ---------- .. [#poliner2007] G. E. Poliner, and D. P. W. Ellis, "A Discriminative Model for Polyphonic Piano Transription", EURASIP Journal on Advances in Signal Processing, 2007(1):154-163, Jan. 2007. .. [#bay2009] Bay, M., Ehmann, A. F., & Downie, J. S. (2009). Evaluation of Multiple-F0 Estimation and Tracking Systems. In ISMIR (pp. 315-320). """ import numpy as np import collections import scipy.interpolate from . import util import warnings MAX_TIME = 30000.0 # The maximum allowable time stamp (seconds) MAX_FREQ = 5000.0 # The maximum allowable frequency (Hz) MIN_FREQ = 20.0 # The minimum allowable frequency (Hz) def validate(ref_time, ref_freqs, est_time, est_freqs): """Check that the time and frequency inputs are well-formed. Parameters ---------- ref_time : np.ndarray reference time stamps in seconds ref_freqs : list of np.ndarray reference frequencies in Hz est_time : np.ndarray estimate time stamps in seconds est_freqs : list of np.ndarray estimated frequencies in Hz """ util.validate_events(ref_time, max_time=MAX_TIME) util.validate_events(est_time, max_time=MAX_TIME) if ref_time.size == 0: warnings.warn("Reference times are empty.") if ref_time.ndim != 1: raise ValueError("Reference times have invalid dimension") if len(ref_freqs) == 0: warnings.warn("Reference frequencies are empty.") if est_time.size == 0: warnings.warn("Estimated times are empty.") if est_time.ndim != 1: raise ValueError("Estimated times have invalid dimension") if len(est_freqs) == 0: warnings.warn("Estimated frequencies are empty.") if ref_time.size != len(ref_freqs): raise ValueError("Reference times and frequencies have unequal " "lengths.") if est_time.size != len(est_freqs): raise ValueError("Estimate times and frequencies have unequal " "lengths.") for freq in ref_freqs: util.validate_frequencies( freq, max_freq=MAX_FREQ, min_freq=MIN_FREQ, allow_negatives=False ) for freq in est_freqs: util.validate_frequencies( freq, max_freq=MAX_FREQ, min_freq=MIN_FREQ, allow_negatives=False ) def resample_multipitch(times, frequencies, target_times): """Resamples multipitch time series to a new timescale using nearest neighbor interpolation. Values in ``target_times`` outside the range of ``times`` return no pitch estimate. Parameters ---------- times : np.ndarray Array of time stamps frequencies : list of np.ndarray List of np.ndarrays of frequency values target_times : np.ndarray Array of target time stamps Returns ------- frequencies_resampled : list of numpy arrays Frequency list of lists resampled to new timebase """ if target_times.size == 0: return [] if times.size == 0: return [np.array([])] * len(target_times) n_times = len(frequencies) # scipy's interpolate doesn't handle ragged arrays. Instead, we interpolate # the frequency index and then map back to the frequency values. # This only works because we're using a nearest neighbor interpolator! frequency_index = np.arange(0, n_times) # times are already ordered so assume_sorted=True for efficiency # since we're interpolating the index, fill_value is set to the first index # that is out of range. We handle this in the next line. new_frequency_index = scipy.interpolate.interp1d( times, frequency_index, kind="nearest", bounds_error=False, assume_sorted=True, fill_value=n_times, )(target_times) # create array of frequencies plus additional empty element at the end for # target time stamps that are out of the interpolation range freq_vals = frequencies + [np.array([])] # map interpolated indices back to frequency values frequencies_resampled = [freq_vals[i] for i in new_frequency_index.astype(int)] return frequencies_resampled def frequencies_to_midi(frequencies, ref_frequency=440.0): """Convert frequencies to continuous MIDI values. Parameters ---------- frequencies : list of np.ndarray Original frequency values ref_frequency : float reference frequency in Hz. Returns ------- frequencies_midi : list of np.ndarray Continuous MIDI frequency values. """ return [69.0 + 12.0 * np.log2(freqs / ref_frequency) for freqs in frequencies] def midi_to_chroma(frequencies_midi): """Wrap MIDI frequencies to a single octave (chroma). Parameters ---------- frequencies_midi : list of np.ndarray Continuous MIDI note frequency values. Returns ------- frequencies_chroma : list of np.ndarray Midi values wrapped to one octave. """ return [np.mod(freqs, 12) for freqs in frequencies_midi] def compute_num_freqs(frequencies): """Compute the number of frequencies for each time point. Parameters ---------- frequencies : list of np.ndarray Frequency values Returns ------- num_freqs : np.ndarray Number of frequencies at each time point. """ return np.array([f.size for f in frequencies]) def compute_num_true_positives(ref_freqs, est_freqs, window=0.5, chroma=False): """Compute the number of true positives in an estimate given a reference. A frequency is correct if it is within a quartertone of the correct frequency. Parameters ---------- ref_freqs : list of np.ndarray reference frequencies (MIDI) est_freqs : list of np.ndarray estimated frequencies (MIDI) window : float Window size, in semitones chroma : bool If True, computes distances modulo n. If True, ``ref_freqs`` and ``est_freqs`` should be wrapped modulo n. Returns ------- true_positives : np.ndarray Array the same length as ref_freqs containing the number of true positives. """ n_frames = len(ref_freqs) true_positives = np.zeros((n_frames,)) for i, (ref_frame, est_frame) in enumerate(zip(ref_freqs, est_freqs)): if chroma: # match chroma-wrapped frequency events matching = util.match_events( ref_frame, est_frame, window, distance=util._outer_distance_mod_n ) else: # match frequency events within tolerance window in semitones matching = util.match_events(ref_frame, est_frame, window) true_positives[i] = len(matching) return true_positives def compute_accuracy(true_positives, n_ref, n_est): """Compute accuracy metrics. Parameters ---------- true_positives : np.ndarray Array containing the number of true positives at each time point. n_ref : np.ndarray Array containing the number of reference frequencies at each time point. n_est : np.ndarray Array containing the number of estimate frequencies at each time point. Returns ------- precision : float ``sum(true_positives)/sum(n_est)`` recall : float ``sum(true_positives)/sum(n_ref)`` acc : float ``sum(true_positives)/sum(n_est + n_ref - true_positives)`` """ true_positive_sum = float(true_positives.sum()) n_est_sum = n_est.sum() if n_est_sum > 0: precision = true_positive_sum / n_est.sum() else: warnings.warn("Estimate frequencies are all empty.") precision = 0.0 n_ref_sum = n_ref.sum() if n_ref_sum > 0: recall = true_positive_sum / n_ref.sum() else: warnings.warn("Reference frequencies are all empty.") recall = 0.0 acc_denom = (n_est + n_ref - true_positives).sum() if acc_denom > 0: acc = true_positive_sum / acc_denom else: acc = 0.0 return precision, recall, acc def compute_err_score(true_positives, n_ref, n_est): """Compute error score metrics. Parameters ---------- true_positives : np.ndarray Array containing the number of true positives at each time point. n_ref : np.ndarray Array containing the number of reference frequencies at each time point. n_est : np.ndarray Array containing the number of estimate frequencies at each time point. Returns ------- e_sub : float Substitution error e_miss : float Miss error e_fa : float False alarm error e_tot : float Total error """ n_ref_sum = float(n_ref.sum()) if n_ref_sum == 0: warnings.warn("Reference frequencies are all empty.") return 0.0, 0.0, 0.0, 0.0 # Substitution error e_sub = (np.min([n_ref, n_est], axis=0) - true_positives).sum() / n_ref_sum # compute the max of (n_ref - n_est) and 0 e_miss_numerator = n_ref - n_est e_miss_numerator[e_miss_numerator < 0] = 0 # Miss error e_miss = e_miss_numerator.sum() / n_ref_sum # compute the max of (n_est - n_ref) and 0 e_fa_numerator = n_est - n_ref e_fa_numerator[e_fa_numerator < 0] = 0 # False alarm error e_fa = e_fa_numerator.sum() / n_ref_sum # total error e_tot = (np.max([n_ref, n_est], axis=0) - true_positives).sum() / n_ref_sum return e_sub, e_miss, e_fa, e_tot def metrics(ref_time, ref_freqs, est_time, est_freqs, **kwargs): """Compute multipitch metrics. All metrics are computed at the 'macro' level such that the frame true positive/false positive/false negative rates are summed across time and the metrics are computed on the combined values. Examples -------- >>> ref_time, ref_freqs = mir_eval.io.load_ragged_time_series( ... 'reference.txt') >>> est_time, est_freqs = mir_eval.io.load_ragged_time_series( ... 'estimated.txt') >>> metris_tuple = mir_eval.multipitch.metrics( ... ref_time, ref_freqs, est_time, est_freqs) Parameters ---------- ref_time : np.ndarray Time of each reference frequency value ref_freqs : list of np.ndarray List of np.ndarrays of reference frequency values est_time : np.ndarray Time of each estimated frequency value est_freqs : list of np.ndarray List of np.ndarrays of estimate frequency values **kwargs Additional keyword arguments which will be passed to the appropriate metric or preprocessing functions. Returns ------- precision : float Precision (TP/(TP + FP)) recall : float Recall (TP/(TP + FN)) accuracy : float Accuracy (TP/(TP + FP + FN)) e_sub : float Substitution error e_miss : float Miss error e_fa : float False alarm error e_tot : float Total error precision_chroma : float Chroma precision recall_chroma : float Chroma recall accuracy_chroma : float Chroma accuracy e_sub_chroma : float Chroma substitution error e_miss_chroma : float Chroma miss error e_fa_chroma : float Chroma false alarm error e_tot_chroma : float Chroma total error """ validate(ref_time, ref_freqs, est_time, est_freqs) # resample est_freqs if est_times is different from ref_times if est_time.size != ref_time.size or not np.allclose(est_time, ref_time): warnings.warn( "Estimate times not equal to reference times. " "Resampling to common time base." ) est_freqs = resample_multipitch(est_time, est_freqs, ref_time) # convert frequencies from Hz to continuous midi note number ref_freqs_midi = frequencies_to_midi(ref_freqs) est_freqs_midi = frequencies_to_midi(est_freqs) # compute chroma wrapped midi number ref_freqs_chroma = midi_to_chroma(ref_freqs_midi) est_freqs_chroma = midi_to_chroma(est_freqs_midi) # count number of occurrences n_ref = compute_num_freqs(ref_freqs_midi) n_est = compute_num_freqs(est_freqs_midi) # compute the number of true positives true_positives = util.filter_kwargs( compute_num_true_positives, ref_freqs_midi, est_freqs_midi, **kwargs ) # compute the number of true positives ignoring octave mistakes true_positives_chroma = util.filter_kwargs( compute_num_true_positives, ref_freqs_chroma, est_freqs_chroma, chroma=True, **kwargs ) # compute accuracy metrics precision, recall, accuracy = compute_accuracy(true_positives, n_ref, n_est) # compute error metrics e_sub, e_miss, e_fa, e_tot = compute_err_score(true_positives, n_ref, n_est) # compute accuracy metrics ignoring octave mistakes precision_chroma, recall_chroma, accuracy_chroma = compute_accuracy( true_positives_chroma, n_ref, n_est ) # compute error metrics ignoring octave mistakes e_sub_chroma, e_miss_chroma, e_fa_chroma, e_tot_chroma = compute_err_score( true_positives_chroma, n_ref, n_est ) return ( precision, recall, accuracy, e_sub, e_miss, e_fa, e_tot, precision_chroma, recall_chroma, accuracy_chroma, e_sub_chroma, e_miss_chroma, e_fa_chroma, e_tot_chroma, ) def evaluate(ref_time, ref_freqs, est_time, est_freqs, **kwargs): """Evaluate two multipitch (multi-f0) transcriptions, where the first is treated as the reference (ground truth) and the second as the estimate to be evaluated (prediction). Examples -------- >>> ref_time, ref_freq = mir_eval.io.load_ragged_time_series('ref.txt') >>> est_time, est_freq = mir_eval.io.load_ragged_time_series('est.txt') >>> scores = mir_eval.multipitch.evaluate(ref_time, ref_freq, ... est_time, est_freq) Parameters ---------- ref_time : np.ndarray Time of each reference frequency value ref_freqs : list of np.ndarray List of np.ndarrays of reference frequency values est_time : np.ndarray Time of each estimated frequency value est_freqs : list of np.ndarray List of np.ndarrays of estimate frequency values **kwargs Additional keyword arguments which will be passed to the appropriate metric or preprocessing functions. Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. """ scores = collections.OrderedDict() ( scores["Precision"], scores["Recall"], scores["Accuracy"], scores["Substitution Error"], scores["Miss Error"], scores["False Alarm Error"], scores["Total Error"], scores["Chroma Precision"], scores["Chroma Recall"], scores["Chroma Accuracy"], scores["Chroma Substitution Error"], scores["Chroma Miss Error"], scores["Chroma False Alarm Error"], scores["Chroma Total Error"], ) = util.filter_kwargs(metrics, ref_time, ref_freqs, est_time, est_freqs, **kwargs) return scores mir_eval-0.8.2/mir_eval/onset.py000066400000000000000000000104211475740344600166330ustar00rootroot00000000000000""" The goal of an onset detection algorithm is to automatically determine when notes are played in a piece of music. The primary method used to evaluate onset detectors is to first determine which estimated onsets are "correct", where correctness is defined as being within a small window of a reference onset. Based in part on this script: https://github.com/CPJKU/onset_detection/blob/master/onset_evaluation.py Conventions ----------- Onsets should be provided in the form of a 1-dimensional array of onset times in seconds in increasing order. Metrics ------- * :func:`mir_eval.onset.f_measure`: Precision, Recall, and F-measure scores based on the number of estimated onsets which are sufficiently close to reference onsets. """ import collections from . import util import warnings # The maximum allowable beat time MAX_TIME = 30000.0 def validate(reference_onsets, estimated_onsets): """Check that the input annotations to a metric look like valid onset time arrays, and throws helpful errors if not. Parameters ---------- reference_onsets : np.ndarray reference onset locations, in seconds estimated_onsets : np.ndarray estimated onset locations, in seconds """ # If reference or estimated onsets are empty, warn because metric will be 0 if reference_onsets.size == 0: warnings.warn("Reference onsets are empty.") if estimated_onsets.size == 0: warnings.warn("Estimated onsets are empty.") for onsets in [reference_onsets, estimated_onsets]: util.validate_events(onsets, MAX_TIME) def f_measure(reference_onsets, estimated_onsets, window=0.05): """Compute the F-measure of correct vs incorrectly predicted onsets. "Correctness" is determined over a small window. Examples -------- >>> reference_onsets = mir_eval.io.load_events('reference.txt') >>> estimated_onsets = mir_eval.io.load_events('estimated.txt') >>> F, P, R = mir_eval.onset.f_measure(reference_onsets, ... estimated_onsets) Parameters ---------- reference_onsets : np.ndarray reference onset locations, in seconds estimated_onsets : np.ndarray estimated onset locations, in seconds window : float Window size, in seconds (Default value = .05) Returns ------- f_measure : float 2*precision*recall/(precision + recall) precision : float (# true positives)/(# true positives + # false positives) recall : float (# true positives)/(# true positives + # false negatives) """ validate(reference_onsets, estimated_onsets) # If either list is empty, return 0s if reference_onsets.size == 0 or estimated_onsets.size == 0: return 0.0, 0.0, 0.0 # Compute the best-case matching between reference and estimated onset # locations matching = util.match_events(reference_onsets, estimated_onsets, window) precision = float(len(matching)) / len(estimated_onsets) recall = float(len(matching)) / len(reference_onsets) # Compute F-measure and return all statistics return util.f_measure(precision, recall), precision, recall def evaluate(reference_onsets, estimated_onsets, **kwargs): """Compute all metrics for the given reference and estimated annotations. Examples -------- >>> reference_onsets = mir_eval.io.load_events('reference.txt') >>> estimated_onsets = mir_eval.io.load_events('estimated.txt') >>> scores = mir_eval.onset.evaluate(reference_onsets, ... estimated_onsets) Parameters ---------- reference_onsets : np.ndarray reference onset locations, in seconds estimated_onsets : np.ndarray estimated onset locations, in seconds **kwargs Additional keyword arguments which will be passed to the appropriate metric or preprocessing functions. Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. """ # Compute all metrics scores = collections.OrderedDict() (scores["F-measure"], scores["Precision"], scores["Recall"]) = util.filter_kwargs( f_measure, reference_onsets, estimated_onsets, **kwargs ) return scores mir_eval-0.8.2/mir_eval/pattern.py000066400000000000000000000552251475740344600171730ustar00rootroot00000000000000""" Pattern discovery involves the identification of musical patterns (i.e. short fragments or melodic ideas that repeat at least twice) both from audio and symbolic representations. The metrics used to evaluate pattern discovery systems attempt to quantify the ability of the algorithm to not only determine the present patterns in a piece, but also to find all of their occurrences. Based on the methods described here: T. Collins. MIREX task: Discovery of repeated themes & sections. http://www.music-ir.org/mirex/wiki/2013:Discovery_of_Repeated_Themes_&_Sections, 2013. Conventions ----------- The input format can be automatically generated by calling :func:`mir_eval.io.load_patterns`. This format is a list of a list of tuples. The first list collections patterns, each of which is a list of occurrences, and each occurrence is a list of MIDI onset tuples of ``(onset_time, mid_note)`` A pattern is a list of occurrences. The first occurrence must be the prototype of that pattern (i.e. the most representative of all the occurrences). An occurrence is a list of tuples containing the onset time and the midi note number. Metrics ------- * :func:`mir_eval.pattern.standard_FPR`: Strict metric in order to find the possibly transposed patterns of exact length. This is the only metric that considers transposed patterns. * :func:`mir_eval.pattern.establishment_FPR`: Evaluates the amount of patterns that were successfully identified by the estimated results, no matter how many occurrences they found. In other words, this metric captures how the algorithm successfully *established* that a pattern repeated at least twice, and this pattern is also found in the reference annotation. * :func:`mir_eval.pattern.occurrence_FPR`: Evaluation of how well an estimation can effectively identify all the occurrences of the found patterns, independently of how many patterns have been discovered. This metric has a threshold parameter that indicates how similar two occurrences must be in order to be considered equal. In MIREX, this evaluation is run twice, with thresholds .75 and .5. * :func:`mir_eval.pattern.three_layer_FPR`: Aims to evaluate the general similarity between the reference and the estimations, combining both the establishment of patterns and the retrieval of its occurrences in a single F1 score. * :func:`mir_eval.pattern.first_n_three_layer_P`: Computes the three-layer precision for the first N patterns only in order to measure the ability of the algorithm to sort the identified patterns based on their relevance. * :func:`mir_eval.pattern.first_n_target_proportion_R`: Computes the target proportion recall for the first N patterns only in order to measure the ability of the algorithm to sort the identified patterns based on their relevance. """ import numpy as np from . import util import warnings import collections def _n_onset_midi(patterns): """Compute the number of onset_midi objects in a pattern Parameters ---------- patterns A list of patterns using the format returned by :func:`mir_eval.io.load_patterns()` Returns ------- n_onsets : int Number of onsets within the pattern. """ return len([o_m for pat in patterns for occ in pat for o_m in occ]) def validate(reference_patterns, estimated_patterns): """Check that the input annotations to a metric look like valid pattern lists, and throws helpful errors if not. Parameters ---------- reference_patterns : list The reference patterns using the format returned by :func:`mir_eval.io.load_patterns()` estimated_patterns : list The estimated patterns in the same format """ # Warn if pattern lists are empty if _n_onset_midi(reference_patterns) == 0: warnings.warn("Reference patterns are empty.") if _n_onset_midi(estimated_patterns) == 0: warnings.warn("Estimated patterns are empty.") for patterns in [reference_patterns, estimated_patterns]: for pattern in patterns: if len(pattern) <= 0: raise ValueError( "Each pattern must contain at least one " "occurrence." ) for occurrence in pattern: for onset_midi in occurrence: if len(onset_midi) != 2: raise ValueError( "The (onset, midi) tuple must " "contain exactly 2 elements." ) def _occurrence_intersection(occ_P, occ_Q): """Compute the intersection between two occurrences. Parameters ---------- occ_P : list of tuples (onset, midi) pairs representing the reference occurrence. occ_Q : list second list of (onset, midi) tuples Returns ------- S : set Set of the intersection between occ_P and occ_Q. """ set_P = {tuple(onset_midi) for onset_midi in occ_P} set_Q = {tuple(onset_midi) for onset_midi in occ_Q} return set_P & set_Q # Return the intersection def _compute_score_matrix(P, Q, similarity_metric="cardinality_score"): """Compute the score matrix between the patterns P and Q. Parameters ---------- P : list Pattern containing a list of occurrences. Q : list Pattern containing a list of occurrences. similarity_metric : str A string representing the metric to be used when computing the similarity matrix. Accepted values: - "cardinality_score": Count of the intersection between occurrences. (Default value = "cardinality_score") Returns ------- sm : np.array The score matrix between P and Q using the similarity_metric. """ sm = np.zeros((len(P), len(Q))) # The score matrix for iP, occ_P in enumerate(P): for iQ, occ_Q in enumerate(Q): if similarity_metric == "cardinality_score": denom = float(np.max([len(occ_P), len(occ_Q)])) # Compute the score sm[iP, iQ] = len(_occurrence_intersection(occ_P, occ_Q)) / denom # TODO: More scores: 'normalised matching socre' else: raise ValueError( "The similarity metric (%s) can only be: " "'cardinality_score'." ) return sm def standard_FPR(reference_patterns, estimated_patterns, tol=1e-5): """Compute the standard F1 Score, Precision and Recall. This metric checks if the prototype patterns of the reference match possible translated patterns in the prototype patterns of the estimations. Since the sizes of these prototypes must be equal, this metric is quite restrictive and it tends to be 0 in most of 2013 MIREX results. Examples -------- >>> ref_patterns = mir_eval.io.load_patterns("ref_pattern.txt") >>> est_patterns = mir_eval.io.load_patterns("est_pattern.txt") >>> F, P, R = mir_eval.pattern.standard_FPR(ref_patterns, est_patterns) Parameters ---------- reference_patterns : list The reference patterns using the format returned by :func:`mir_eval.io.load_patterns()` estimated_patterns : list The estimated patterns in the same format tol : float Tolerance level when comparing reference against estimation. Default parameter is the one found in the original matlab code by Tom Collins used for MIREX 2013. (Default value = 1e-5) Returns ------- f_measure : float The standard F1 Score precision : float The standard Precision recall : float The standard Recall """ validate(reference_patterns, estimated_patterns) nP = len(reference_patterns) # Number of patterns in the reference nQ = len(estimated_patterns) # Number of patterns in the estimation k = 0 # Number of patterns that match # If no patterns were provided, metric is zero if _n_onset_midi(reference_patterns) == 0 or _n_onset_midi(estimated_patterns) == 0: return 0.0, 0.0, 0.0 # Find matches of the prototype patterns for ref_pattern in reference_patterns: P = np.asarray(ref_pattern[0]) # Get reference prototype for est_pattern in estimated_patterns: Q = np.asarray(est_pattern[0]) # Get estimation prototype if len(P) != len(Q): continue # Check transposition given a certain tolerance if len(P) == len(Q) == 1 or np.max(np.abs(np.diff(P - Q, axis=0))) < tol: k += 1 break # Compute the standard measures precision = k / float(nQ) recall = k / float(nP) f_measure = util.f_measure(precision, recall) return f_measure, precision, recall def establishment_FPR( reference_patterns, estimated_patterns, similarity_metric="cardinality_score" ): """Compute the establishment F1 Score, Precision and Recall. Examples -------- >>> ref_patterns = mir_eval.io.load_patterns("ref_pattern.txt") >>> est_patterns = mir_eval.io.load_patterns("est_pattern.txt") >>> F, P, R = mir_eval.pattern.establishment_FPR(ref_patterns, ... est_patterns) Parameters ---------- reference_patterns : list The reference patterns in the format returned by :func:`mir_eval.io.load_patterns()` estimated_patterns : list The estimated patterns in the same format similarity_metric : str A string representing the metric to be used when computing the similarity matrix. Accepted values: - "cardinality_score": Count of the intersection between occurrences. (Default value = "cardinality_score") Returns ------- f_measure : float The establishment F1 Score precision : float The establishment Precision recall : float The establishment Recall """ validate(reference_patterns, estimated_patterns) nP = len(reference_patterns) # Number of elements in reference nQ = len(estimated_patterns) # Number of elements in estimation S = np.zeros((nP, nQ)) # Establishment matrix # If no patterns were provided, metric is zero if _n_onset_midi(reference_patterns) == 0 or _n_onset_midi(estimated_patterns) == 0: return 0.0, 0.0, 0.0 for iP, ref_pattern in enumerate(reference_patterns): for iQ, est_pattern in enumerate(estimated_patterns): s = _compute_score_matrix(ref_pattern, est_pattern, similarity_metric) S[iP, iQ] = np.max(s) # Compute scores precision = np.mean(np.max(S, axis=0)) recall = np.mean(np.max(S, axis=1)) f_measure = util.f_measure(precision, recall) return f_measure, precision, recall def occurrence_FPR( reference_patterns, estimated_patterns, thres=0.75, similarity_metric="cardinality_score", ): """Compute the occurrence F1 Score, Precision and Recall. Examples -------- >>> ref_patterns = mir_eval.io.load_patterns("ref_pattern.txt") >>> est_patterns = mir_eval.io.load_patterns("est_pattern.txt") >>> F, P, R = mir_eval.pattern.occurrence_FPR(ref_patterns, ... est_patterns) Parameters ---------- reference_patterns : list The reference patterns in the format returned by :func:`mir_eval.io.load_patterns()` estimated_patterns : list The estimated patterns in the same format thres : float How similar two occurrences must be in order to be considered equal (Default value = .75) similarity_metric : str A string representing the metric to be used when computing the similarity matrix. Accepted values: - "cardinality_score": Count of the intersection between occurrences. (Default value = "cardinality_score") Returns ------- f_measure : float The occurrence F1 Score precision : float The occurrence Precision recall : float The occurrence Recall """ validate(reference_patterns, estimated_patterns) # Number of elements in reference nP = len(reference_patterns) # Number of elements in estimation nQ = len(estimated_patterns) # Occurrence matrix with Precision and recall in its last dimension O_PR = np.zeros((nP, nQ, 2)) # Index of the values that are greater than the specified threshold rel_idx = np.empty((0, 2), dtype=int) # If no patterns were provided, metric is zero if _n_onset_midi(reference_patterns) == 0 or _n_onset_midi(estimated_patterns) == 0: return 0.0, 0.0, 0.0 for iP, ref_pattern in enumerate(reference_patterns): for iQ, est_pattern in enumerate(estimated_patterns): s = _compute_score_matrix(ref_pattern, est_pattern, similarity_metric) if np.max(s) >= thres: O_PR[iP, iQ, 0] = np.mean(np.max(s, axis=0)) O_PR[iP, iQ, 1] = np.mean(np.max(s, axis=1)) rel_idx = np.vstack((rel_idx, [iP, iQ])) # Compute the scores if len(rel_idx) == 0: precision = 0 recall = 0 else: P = O_PR[:, :, 0] precision = np.mean(np.max(P[np.ix_(rel_idx[:, 0], rel_idx[:, 1])], axis=0)) R = O_PR[:, :, 1] recall = np.mean(np.max(R[np.ix_(rel_idx[:, 0], rel_idx[:, 1])], axis=1)) f_measure = util.f_measure(precision, recall) return f_measure, precision, recall def three_layer_FPR(reference_patterns, estimated_patterns): """Three Layer F1 Score, Precision and Recall. As described by Meridith. Examples -------- >>> ref_patterns = mir_eval.io.load_patterns("ref_pattern.txt") >>> est_patterns = mir_eval.io.load_patterns("est_pattern.txt") >>> F, P, R = mir_eval.pattern.three_layer_FPR(ref_patterns, ... est_patterns) Parameters ---------- reference_patterns : list The reference patterns in the format returned by :func:`mir_eval.io.load_patterns()` estimated_patterns : list The estimated patterns in the same format Returns ------- f_measure : float The three-layer F1 Score precision : float The three-layer Precision recall : float The three-layer Recall """ validate(reference_patterns, estimated_patterns) def compute_first_layer_PR(ref_occs, est_occs): """Compute the first layer Precision and Recall values given the set of occurrences in the reference and the set of occurrences in the estimation. Parameters ---------- ref_occs est_occs Returns ------- precision recall """ # Find the length of the intersection between reference and estimation s = len(_occurrence_intersection(ref_occs, est_occs)) # Compute the first layer scores precision = s / float(len(ref_occs)) recall = s / float(len(est_occs)) return precision, recall def compute_second_layer_PR(ref_pattern, est_pattern): """Compute the second layer Precision and Recall values given the set of occurrences in the reference and the set of occurrences in the estimation. Parameters ---------- ref_pattern est_pattern Returns ------- precision recall """ # Compute the first layer scores F_1 = compute_layer(ref_pattern, est_pattern) # Compute the second layer scores precision = np.mean(np.max(F_1, axis=0)) recall = np.mean(np.max(F_1, axis=1)) return precision, recall def compute_layer(ref_elements, est_elements, layer=1): """Compute the F-measure matrix for a given layer. The reference and estimated elements can be either patterns or occurrences, depending on the layer. For layer 1, the elements must be occurrences. For layer 2, the elements must be patterns. Parameters ---------- ref_elements est_elements layer (Default value = 1) Returns ------- F : F-measure for the given layer """ if layer != 1 and layer != 2: raise ValueError("Layer (%d) must be an integer between 1 and 2" % layer) nP = len(ref_elements) # Number of elements in reference nQ = len(est_elements) # Number of elements in estimation F = np.zeros((nP, nQ)) # F-measure matrix for the given layer for iP in range(nP): for iQ in range(nQ): if layer == 1: func = compute_first_layer_PR elif layer == 2: func = compute_second_layer_PR # Compute layer scores precision, recall = func(ref_elements[iP], est_elements[iQ]) F[iP, iQ] = util.f_measure(precision, recall) return F # If no patterns were provided, metric is zero if _n_onset_midi(reference_patterns) == 0 or _n_onset_midi(estimated_patterns) == 0: return 0.0, 0.0, 0.0 # Compute the second layer (it includes the first layer) F_2 = compute_layer(reference_patterns, estimated_patterns, layer=2) # Compute the final scores (third layer) precision_3 = np.mean(np.max(F_2, axis=0)) recall_3 = np.mean(np.max(F_2, axis=1)) f_measure_3 = util.f_measure(precision_3, recall_3) return f_measure_3, precision_3, recall_3 def first_n_three_layer_P(reference_patterns, estimated_patterns, n=5): """First n three-layer precision. This metric is basically the same as the three-layer FPR but it is only applied to the first n estimated patterns, and it only returns the precision. In MIREX and typically, n = 5. Examples -------- >>> ref_patterns = mir_eval.io.load_patterns("ref_pattern.txt") >>> est_patterns = mir_eval.io.load_patterns("est_pattern.txt") >>> P = mir_eval.pattern.first_n_three_layer_P(ref_patterns, ... est_patterns, n=5) Parameters ---------- reference_patterns : list The reference patterns in the format returned by :func:`mir_eval.io.load_patterns()` estimated_patterns : list The estimated patterns in the same format n : int Number of patterns to consider from the estimated results, in the order they appear in the matrix (Default value = 5) Returns ------- precision : float The first n three-layer Precision """ validate(reference_patterns, estimated_patterns) # If no patterns were provided, metric is zero if _n_onset_midi(reference_patterns) == 0 or _n_onset_midi(estimated_patterns) == 0: return 0.0, 0.0, 0.0 # Get only the first n patterns from the estimated results fn_est_patterns = estimated_patterns[: min(len(estimated_patterns), n)] # Compute the three-layer scores for the first n estimated patterns F, P, R = three_layer_FPR(reference_patterns, fn_est_patterns) return P # Return the precision only def first_n_target_proportion_R(reference_patterns, estimated_patterns, n=5): """First n target proportion establishment recall metric. This metric is similar is similar to the establishment FPR score, but it only takes into account the first n estimated patterns and it only outputs the Recall value of it. Examples -------- >>> ref_patterns = mir_eval.io.load_patterns("ref_pattern.txt") >>> est_patterns = mir_eval.io.load_patterns("est_pattern.txt") >>> R = mir_eval.pattern.first_n_target_proportion_R( ... ref_patterns, est_patterns, n=5) Parameters ---------- reference_patterns : list The reference patterns in the format returned by :func:`mir_eval.io.load_patterns()` estimated_patterns : list The estimated patterns in the same format n : int Number of patterns to consider from the estimated results, in the order they appear in the matrix. (Default value = 5) Returns ------- recall : float The first n target proportion Recall. """ validate(reference_patterns, estimated_patterns) # If no patterns were provided, metric is zero if _n_onset_midi(reference_patterns) == 0 or _n_onset_midi(estimated_patterns) == 0: return 0.0, 0.0, 0.0 # Get only the first n patterns from the estimated results fn_est_patterns = estimated_patterns[: min(len(estimated_patterns), n)] F, P, R = establishment_FPR(reference_patterns, fn_est_patterns) return R def evaluate(ref_patterns, est_patterns, **kwargs): """Load data and perform the evaluation. Examples -------- >>> ref_patterns = mir_eval.io.load_patterns("ref_pattern.txt") >>> est_patterns = mir_eval.io.load_patterns("est_pattern.txt") >>> scores = mir_eval.pattern.evaluate(ref_patterns, est_patterns) Parameters ---------- ref_patterns : list The reference patterns in the format returned by :func:`mir_eval.io.load_patterns()` est_patterns : list The estimated patterns in the same format **kwargs Additional keyword arguments which will be passed to the appropriate metric or preprocessing functions. Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. """ # Compute all the metrics scores = collections.OrderedDict() # Standard scores scores["F"], scores["P"], scores["R"] = util.filter_kwargs( standard_FPR, ref_patterns, est_patterns, **kwargs ) # Establishment scores scores["F_est"], scores["P_est"], scores["R_est"] = util.filter_kwargs( establishment_FPR, ref_patterns, est_patterns, **kwargs ) # Occurrence scores # Force these values for thresh kwargs["thresh"] = 0.5 scores["F_occ.5"], scores["P_occ.5"], scores["R_occ.5"] = util.filter_kwargs( occurrence_FPR, ref_patterns, est_patterns, **kwargs ) kwargs["thresh"] = 0.75 scores["F_occ.75"], scores["P_occ.75"], scores["R_occ.75"] = util.filter_kwargs( occurrence_FPR, ref_patterns, est_patterns, **kwargs ) # Three-layer scores scores["F_3"], scores["P_3"], scores["R_3"] = util.filter_kwargs( three_layer_FPR, ref_patterns, est_patterns, **kwargs ) # First Five Patterns scores # Set default value of n if "n" not in kwargs: kwargs["n"] = 5 scores["FFP"] = util.filter_kwargs( first_n_three_layer_P, ref_patterns, est_patterns, **kwargs ) scores["FFTP_est"] = util.filter_kwargs( first_n_target_proportion_R, ref_patterns, est_patterns, **kwargs ) return scores mir_eval-0.8.2/mir_eval/segment.py000066400000000000000000001333261475740344600171570ustar00rootroot00000000000000# CREATED:2013-08-13 12:02:42 by Brian McFee """ Evaluation criteria for structural segmentation fall into two categories: boundary annotation and structural annotation. Boundary annotation is the task of predicting the times at which structural changes occur, such as when a verse transitions to a refrain. Metrics for boundary annotation compare estimated segment boundaries to reference boundaries. Structural annotation is the task of assigning labels to detected segments. The estimated labels may be arbitrary strings - such as A, B, C, - and they need not describe functional concepts. Metrics for structural annotation are similar to those used for clustering data. Conventions ----------- Both boundary and structural annotation metrics require two dimensional arrays with two columns, one for boundary start times and one for boundary end times. Structural annotation further require lists of reference and estimated segment labels which must have a length which is equal to the number of rows in the corresponding list of boundary edges. In both tasks, we assume that annotations express a partitioning of the track into intervals. The function :func:`mir_eval.util.adjust_intervals` can be used to pad or crop the segment boundaries to span the duration of the entire track. Metrics ------- * :func:`mir_eval.segment.detection`: An estimated boundary is considered correct if it falls within a window around a reference boundary [#turnbull2007]_ * :func:`mir_eval.segment.deviation`: Computes the median absolute time difference from a reference boundary to its nearest estimated boundary, and vice versa [#turnbull2007]_ * :func:`mir_eval.segment.pairwise`: For classifying pairs of sampled time instants as belonging to the same structural component [#levy2008]_ * :func:`mir_eval.segment.rand_index`: Clusters reference and estimated annotations and compares them by the Rand Index * :func:`mir_eval.segment.ari`: Computes the Rand index, adjusted for chance * :func:`mir_eval.segment.nce`: Interprets sampled reference and estimated labels as samples of random variables :math:`Y_R, Y_E` from which the conditional entropy of :math:`Y_R` given :math:`Y_E` (Under-Segmentation) and :math:`Y_E` given :math:`Y_R` (Over-Segmentation) are estimated [#lukashevich2008]_ * :func:`mir_eval.segment.mutual_information`: Computes the standard, normalized, and adjusted mutual information of sampled reference and estimated segments * :func:`mir_eval.segment.vmeasure`: Computes the V-Measure, which is similar to the conditional entropy metrics, but uses the marginal distributions as normalization rather than the maximum entropy distribution [#rosenberg2007]_ References ---------- .. [#turnbull2007] Turnbull, D., Lanckriet, G. R., Pampalk, E., & Goto, M. A Supervised Approach for Detecting Boundaries in Music Using Difference Features and Boosting. In ISMIR (pp. 51-54). .. [#levy2008] Levy, M., & Sandler, M. Structural segmentation of musical audio by constrained clustering. IEEE transactions on audio, speech, and language processing, 16(2), 318-326. .. [#lukashevich2008] Lukashevich, H. M. Towards Quantitative Measures of Evaluating Song Segmentation. In ISMIR (pp. 375-380). .. [#rosenberg2007] Rosenberg, A., & Hirschberg, J. V-Measure: A Conditional Entropy-Based External Cluster Evaluation Measure. In EMNLP-CoNLL (Vol. 7, pp. 410-420). """ import collections import warnings import numpy as np import scipy.stats import scipy.sparse import scipy.special from . import util def validate_boundary(reference_intervals, estimated_intervals, trim): """Check that the input annotations to a segment boundary estimation metric (i.e. one that only takes in segment intervals) look like valid segment times, and throws helpful errors if not. Parameters ---------- reference_intervals : np.ndarray, shape=(n, 2) reference segment intervals, in the format returned by :func:`mir_eval.io.load_intervals` or :func:`mir_eval.io.load_labeled_intervals`. estimated_intervals : np.ndarray, shape=(m, 2) estimated segment intervals, in the format returned by :func:`mir_eval.io.load_intervals` or :func:`mir_eval.io.load_labeled_intervals`. trim : bool will the start and end events be trimmed? """ if trim: # If we're trimming, then we need at least 2 intervals min_size = 2 else: # If we're not trimming, then we only need one interval min_size = 1 if len(reference_intervals) < min_size: warnings.warn("Reference intervals are empty.") if len(estimated_intervals) < min_size: warnings.warn("Estimated intervals are empty.") for intervals in [reference_intervals, estimated_intervals]: util.validate_intervals(intervals) def validate_structure( reference_intervals, reference_labels, estimated_intervals, estimated_labels ): """Check that the input annotations to a structure estimation metric (i.e. one that takes in both segment boundaries and their labels) look like valid segment times and labels, and throws helpful errors if not. Parameters ---------- reference_intervals : np.ndarray, shape=(n, 2) reference segment intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. reference_labels : list, shape=(n,) reference segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. estimated_intervals : np.ndarray, shape=(m, 2) estimated segment intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. estimated_labels : list, shape=(m,) estimated segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. """ for intervals, labels in [ (reference_intervals, reference_labels), (estimated_intervals, estimated_labels), ]: util.validate_intervals(intervals) if intervals.shape[0] != len(labels): raise ValueError("Number of intervals does not match number " "of labels") # Check only when intervals are non-empty if intervals.size > 0: # Make sure intervals start at 0 if not np.allclose(intervals.min(), 0.0): raise ValueError("Segment intervals do not start at 0") if reference_intervals.size == 0: warnings.warn("Reference intervals are empty.") if estimated_intervals.size == 0: warnings.warn("Estimated intervals are empty.") # Check only when intervals are non-empty if reference_intervals.size > 0 and estimated_intervals.size > 0: if not np.allclose(reference_intervals.max(), estimated_intervals.max()): raise ValueError("End times do not match") def detection( reference_intervals, estimated_intervals, window=0.5, beta=1.0, trim=False ): """Boundary detection hit-rate. A hit is counted whenever an reference boundary is within ``window`` of a estimated boundary. Note that each boundary is matched at most once: this is achieved by computing the size of a maximal matching between reference and estimated boundary points, subject to the window constraint. Examples -------- >>> ref_intervals, _ = mir_eval.io.load_labeled_intervals('ref.lab') >>> est_intervals, _ = mir_eval.io.load_labeled_intervals('est.lab') >>> # With 0.5s windowing >>> P05, R05, F05 = mir_eval.segment.detection(ref_intervals, ... est_intervals, ... window=0.5) >>> # With 3s windowing >>> P3, R3, F3 = mir_eval.segment.detection(ref_intervals, ... est_intervals, ... window=3) >>> # Ignoring hits for the beginning and end of track >>> P, R, F = mir_eval.segment.detection(ref_intervals, ... est_intervals, ... window=0.5, ... trim=True) Parameters ---------- reference_intervals : np.ndarray, shape=(n, 2) reference segment intervals, in the format returned by :func:`mir_eval.io.load_intervals` or :func:`mir_eval.io.load_labeled_intervals`. estimated_intervals : np.ndarray, shape=(m, 2) estimated segment intervals, in the format returned by :func:`mir_eval.io.load_intervals` or :func:`mir_eval.io.load_labeled_intervals`. window : float > 0 size of the window of 'correctness' around ground-truth beats (in seconds) (Default value = 0.5) beta : float > 0 weighting constant for F-measure. (Default value = 1.0) trim : boolean if ``True``, the first and last boundary times are ignored. Typically, these denote start (0) and end-markers. (Default value = False) Returns ------- precision : float precision of estimated predictions recall : float recall of reference reference boundaries f_measure : float F-measure (weighted harmonic mean of ``precision`` and ``recall``) """ validate_boundary(reference_intervals, estimated_intervals, trim) # Convert intervals to boundaries reference_boundaries = util.intervals_to_boundaries(reference_intervals) estimated_boundaries = util.intervals_to_boundaries(estimated_intervals) # Suppress the first and last intervals if trim: reference_boundaries = reference_boundaries[1:-1] estimated_boundaries = estimated_boundaries[1:-1] # If we have no boundaries, we get no score. if len(reference_boundaries) == 0 or len(estimated_boundaries) == 0: return 0.0, 0.0, 0.0 matching = util.match_events(reference_boundaries, estimated_boundaries, window) precision = float(len(matching)) / len(estimated_boundaries) recall = float(len(matching)) / len(reference_boundaries) f_measure = util.f_measure(precision, recall, beta=beta) return precision, recall, f_measure def deviation(reference_intervals, estimated_intervals, trim=False): """Compute the median deviations between reference and estimated boundary times. Examples -------- >>> ref_intervals, _ = mir_eval.io.load_labeled_intervals('ref.lab') >>> est_intervals, _ = mir_eval.io.load_labeled_intervals('est.lab') >>> r_to_e, e_to_r = mir_eval.boundary.deviation(ref_intervals, ... est_intervals) Parameters ---------- reference_intervals : np.ndarray, shape=(n, 2) reference segment intervals, in the format returned by :func:`mir_eval.io.load_intervals` or :func:`mir_eval.io.load_labeled_intervals`. estimated_intervals : np.ndarray, shape=(m, 2) estimated segment intervals, in the format returned by :func:`mir_eval.io.load_intervals` or :func:`mir_eval.io.load_labeled_intervals`. trim : boolean if ``True``, the first and last intervals are ignored. Typically, these denote start (0.0) and end-of-track markers. (Default value = False) Returns ------- reference_to_estimated : float median time from each reference boundary to the closest estimated boundary estimated_to_reference : float median time from each estimated boundary to the closest reference boundary """ validate_boundary(reference_intervals, estimated_intervals, trim) # Convert intervals to boundaries reference_boundaries = util.intervals_to_boundaries(reference_intervals) estimated_boundaries = util.intervals_to_boundaries(estimated_intervals) # Suppress the first and last intervals if trim: reference_boundaries = reference_boundaries[1:-1] estimated_boundaries = estimated_boundaries[1:-1] # If we have no boundaries, we get no score. if len(reference_boundaries) == 0 or len(estimated_boundaries) == 0: return np.nan, np.nan dist = np.abs(np.subtract.outer(reference_boundaries, estimated_boundaries)) estimated_to_reference = np.median(dist.min(axis=0)) reference_to_estimated = np.median(dist.min(axis=1)) return reference_to_estimated, estimated_to_reference def pairwise( reference_intervals, reference_labels, estimated_intervals, estimated_labels, frame_size=0.1, beta=1.0, ): """Frame-clustering segmentation evaluation by pair-wise agreement. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> # Trim or pad the estimate to match reference timing >>> (ref_intervals, ... ref_labels) = mir_eval.util.adjust_intervals(ref_intervals, ... ref_labels, ... t_min=0) >>> (est_intervals, ... est_labels) = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, t_min=0, t_max=ref_intervals.max()) >>> precision, recall, f = mir_eval.structure.pairwise(ref_intervals, ... ref_labels, ... est_intervals, ... est_labels) Parameters ---------- reference_intervals : np.ndarray, shape=(n, 2) reference segment intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. reference_labels : list, shape=(n,) reference segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. estimated_intervals : np.ndarray, shape=(m, 2) estimated segment intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. estimated_labels : list, shape=(m,) estimated segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. frame_size : float > 0 length (in seconds) of frames for clustering (Default value = 0.1) beta : float > 0 beta value for F-measure (Default value = 1.0) Returns ------- precision : float > 0 Precision of detecting whether frames belong in the same cluster recall : float > 0 Recall of detecting whether frames belong in the same cluster f : float > 0 F-measure of detecting whether frames belong in the same cluster """ validate_structure( reference_intervals, reference_labels, estimated_intervals, estimated_labels ) # Check for empty annotations. Don't need to check labels because # validate_structure makes sure they're the same size as intervals if reference_intervals.size == 0 or estimated_intervals.size == 0: return 0.0, 0.0, 0.0 # Generate the cluster labels y_ref = util.intervals_to_samples( reference_intervals, reference_labels, sample_size=frame_size )[-1] y_ref = util.index_labels(y_ref)[0] # Map to index space y_est = util.intervals_to_samples( estimated_intervals, estimated_labels, sample_size=frame_size )[-1] y_est = util.index_labels(y_est)[0] # Build the reference label agreement matrix agree_ref = np.equal.outer(y_ref, y_ref) # Count the unique pairs n_agree_ref = (agree_ref.sum() - len(y_ref)) / 2.0 # Repeat for estimate agree_est = np.equal.outer(y_est, y_est) n_agree_est = (agree_est.sum() - len(y_est)) / 2.0 # Find where they agree matches = np.logical_and(agree_ref, agree_est) n_matches = (matches.sum() - len(y_ref)) / 2.0 precision = n_matches / n_agree_est recall = n_matches / n_agree_ref f_measure = util.f_measure(precision, recall, beta=beta) return precision, recall, f_measure def rand_index( reference_intervals, reference_labels, estimated_intervals, estimated_labels, frame_size=0.1, beta=1.0, ): """(Non-adjusted) Rand index. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> # Trim or pad the estimate to match reference timing >>> (ref_intervals, ... ref_labels) = mir_eval.util.adjust_intervals(ref_intervals, ... ref_labels, ... t_min=0) >>> (est_intervals, ... est_labels) = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, t_min=0, t_max=ref_intervals.max()) >>> rand_index = mir_eval.structure.rand_index(ref_intervals, ... ref_labels, ... est_intervals, ... est_labels) Parameters ---------- reference_intervals : np.ndarray, shape=(n, 2) reference segment intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. reference_labels : list, shape=(n,) reference segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. estimated_intervals : np.ndarray, shape=(m, 2) estimated segment intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. estimated_labels : list, shape=(m,) estimated segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. frame_size : float > 0 length (in seconds) of frames for clustering (Default value = 0.1) beta : float > 0 beta value for F-measure (Default value = 1.0) Returns ------- rand_index : float > 0 Rand index """ validate_structure( reference_intervals, reference_labels, estimated_intervals, estimated_labels ) # Check for empty annotations. Don't need to check labels because # validate_structure makes sure they're the same size as intervals if reference_intervals.size == 0 or estimated_intervals.size == 0: return 0.0, 0.0, 0.0 # Generate the cluster labels y_ref = util.intervals_to_samples( reference_intervals, reference_labels, sample_size=frame_size )[-1] y_ref = util.index_labels(y_ref)[0] # Map to index space y_est = util.intervals_to_samples( estimated_intervals, estimated_labels, sample_size=frame_size )[-1] y_est = util.index_labels(y_est)[0] # Build the reference label agreement matrix agree_ref = np.equal.outer(y_ref, y_ref) # Repeat for estimate agree_est = np.equal.outer(y_est, y_est) # Find where they agree matches_pos = np.logical_and(agree_ref, agree_est) # Find where they disagree matches_neg = np.logical_and(~agree_ref, ~agree_est) n_pairs = len(y_ref) * (len(y_ref) - 1) / 2.0 n_matches_pos = (matches_pos.sum() - len(y_ref)) / 2.0 n_matches_neg = matches_neg.sum() / 2.0 rand = (n_matches_pos + n_matches_neg) / n_pairs return rand def _contingency_matrix(reference_indices, estimated_indices): """Compute the contingency matrix of a true labeling vs an estimated one. Parameters ---------- reference_indices : np.ndarray Array of reference indices estimated_indices : np.ndarray Array of estimated indices Returns ------- contingency_matrix : np.ndarray Contingency matrix, shape=(#reference indices, #estimated indices) .. note:: Based on sklearn.metrics.cluster.contingency_matrix """ ref_classes, ref_class_idx = np.unique(reference_indices, return_inverse=True) est_classes, est_class_idx = np.unique(estimated_indices, return_inverse=True) n_ref_classes = ref_classes.shape[0] n_est_classes = est_classes.shape[0] # Using coo_matrix is faster than histogram2d return scipy.sparse.coo_matrix( (np.ones(ref_class_idx.shape[0]), (ref_class_idx, est_class_idx)), shape=(n_ref_classes, n_est_classes), dtype=np.int64, ).toarray() def _adjusted_rand_index(reference_indices, estimated_indices): """Compute the Rand index, adjusted for change. Parameters ---------- reference_indices : np.ndarray Array of reference indices estimated_indices : np.ndarray Array of estimated indices Returns ------- ari : float Adjusted Rand index .. note:: Based on sklearn.metrics.cluster.adjusted_rand_score """ n_samples = len(reference_indices) ref_classes = np.unique(reference_indices) est_classes = np.unique(estimated_indices) # Special limit cases: no clustering since the data is not split; # or trivial clustering where each document is assigned a unique cluster. # These are perfect matches hence return 1.0. if ( ref_classes.shape[0] == est_classes.shape[0] == 1 or ref_classes.shape[0] == est_classes.shape[0] == 0 or (ref_classes.shape[0] == est_classes.shape[0] == len(reference_indices)) ): return 1.0 contingency = _contingency_matrix(reference_indices, estimated_indices) # Compute the ARI using the contingency data sum_comb_c = sum( scipy.special.comb(n_c, 2, exact=1) for n_c in contingency.sum(axis=1) ) sum_comb_k = sum( scipy.special.comb(n_k, 2, exact=1) for n_k in contingency.sum(axis=0) ) sum_comb = sum( scipy.special.comb(n_ij, 2, exact=1) for n_ij in contingency.flatten() ) prod_comb = (sum_comb_c * sum_comb_k) / float(scipy.special.comb(n_samples, 2)) mean_comb = (sum_comb_k + sum_comb_c) / 2.0 return (sum_comb - prod_comb) / (mean_comb - prod_comb) def ari( reference_intervals, reference_labels, estimated_intervals, estimated_labels, frame_size=0.1, ): """Compute the Adjusted Rand Index (ARI) for frame clustering segmentation evaluation. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> # Trim or pad the estimate to match reference timing >>> (ref_intervals, ... ref_labels) = mir_eval.util.adjust_intervals(ref_intervals, ... ref_labels, ... t_min=0) >>> (est_intervals, ... est_labels) = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, t_min=0, t_max=ref_intervals.max()) >>> ari_score = mir_eval.structure.ari(ref_intervals, ref_labels, ... est_intervals, est_labels) Parameters ---------- reference_intervals : np.ndarray, shape=(n, 2) reference segment intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. reference_labels : list, shape=(n,) reference segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. estimated_intervals : np.ndarray, shape=(m, 2) estimated segment intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. estimated_labels : list, shape=(m,) estimated segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. frame_size : float > 0 length (in seconds) of frames for clustering (Default value = 0.1) Returns ------- ari_score : float > 0 Adjusted Rand index between segmentations. """ validate_structure( reference_intervals, reference_labels, estimated_intervals, estimated_labels ) # Check for empty annotations. Don't need to check labels because # validate_structure makes sure they're the same size as intervals if reference_intervals.size == 0 or estimated_intervals.size == 0: return 0.0, 0.0, 0.0 # Generate the cluster labels y_ref = util.intervals_to_samples( reference_intervals, reference_labels, sample_size=frame_size )[-1] y_ref = util.index_labels(y_ref)[0] # Map to index space y_est = util.intervals_to_samples( estimated_intervals, estimated_labels, sample_size=frame_size )[-1] y_est = util.index_labels(y_est)[0] return _adjusted_rand_index(y_ref, y_est) def _mutual_info_score(reference_indices, estimated_indices, contingency=None): """Compute the mutual information between two sequence labelings. Parameters ---------- reference_indices : np.ndarray Array of reference indices estimated_indices : np.ndarray Array of estimated indices contingency : np.ndarray Pre-computed contingency matrix. If None, one will be computed. (Default value = None) Returns ------- mi : float Mutual information .. note:: Based on sklearn.metrics.cluster.mutual_info_score """ if contingency is None: contingency = _contingency_matrix(reference_indices, estimated_indices).astype( float ) contingency_sum = np.sum(contingency) pi = np.sum(contingency, axis=1) pj = np.sum(contingency, axis=0) outer = np.outer(pi, pj) nnz = contingency != 0.0 # normalized contingency contingency_nm = contingency[nnz] log_contingency_nm = np.log(contingency_nm) contingency_nm /= contingency_sum # log(a / b) should be calculated as log(a) - log(b) for # possible loss of precision log_outer = -np.log(outer[nnz]) + np.log(pi.sum()) + np.log(pj.sum()) mi = ( contingency_nm * (log_contingency_nm - np.log(contingency_sum)) + contingency_nm * log_outer ) return mi.sum() def _entropy(labels): """Calculate the entropy for a labeling. Parameters ---------- labels : list-like List of labels. Returns ------- entropy : float Entropy of the labeling. .. note:: Based on sklearn.metrics.cluster.entropy """ if len(labels) == 0: return 1.0 label_idx = np.unique(labels, return_inverse=True)[1] pi = np.bincount(label_idx).astype(np.float64) pi = pi[pi > 0] pi_sum = np.sum(pi) # log(a / b) should be calculated as log(a) - log(b) for # possible loss of precision return -np.sum((pi / pi_sum) * (np.log(pi) - np.log(pi_sum))) def _adjusted_mutual_info_score(reference_indices, estimated_indices): """Compute the mutual information between two sequence labelings, adjusted for chance. Parameters ---------- reference_indices : np.ndarray Array of reference indices estimated_indices : np.ndarray Array of estimated indices Returns ------- ami : float <= 1.0 Mutual information .. note:: Based on sklearn.metrics.cluster.adjusted_mutual_info_score and sklearn.metrics.cluster.expected_mutual_info_score """ n_samples = len(reference_indices) ref_classes = np.unique(reference_indices) est_classes = np.unique(estimated_indices) # Special limit cases: no clustering since the data is not split. # This is a perfect match hence return 1.0. if ( ref_classes.shape[0] == est_classes.shape[0] == 1 or ref_classes.shape[0] == est_classes.shape[0] == 0 ): return 1.0 contingency = _contingency_matrix(reference_indices, estimated_indices).astype( float ) # Calculate the MI for the two clusterings mi = _mutual_info_score( reference_indices, estimated_indices, contingency=contingency ) # The following code is based on # sklearn.metrics.cluster.expected_mutual_information R, C = contingency.shape N = float(n_samples) a = np.sum(contingency, axis=1).astype(np.int32) b = np.sum(contingency, axis=0).astype(np.int32) # There are three major terms to the EMI equation, which are multiplied to # and then summed over varying nij values. # While nijs[0] will never be used, having it simplifies the indexing. nijs = np.arange(0, max(np.max(a), np.max(b)) + 1, dtype="float") # Stops divide by zero warnings. As its not used, no issue. nijs[0] = 1 # term1 is nij / N term1 = nijs / N # term2 is log((N*nij) / (a * b)) == log(N * nij) - log(a * b) # term2 uses the outer product log_ab_outer = np.log(np.outer(a, b)) # term2 uses N * nij log_Nnij = np.log(N * nijs) # term3 is large, and involved many factorials. Calculate these in log # space to stop overflows. gln_a = scipy.special.gammaln(a + 1) gln_b = scipy.special.gammaln(b + 1) gln_Na = scipy.special.gammaln(N - a + 1) gln_Nb = scipy.special.gammaln(N - b + 1) gln_N = scipy.special.gammaln(N + 1) gln_nij = scipy.special.gammaln(nijs + 1) # start and end values for nij terms for each summation. start = np.array([[v - N + w for w in b] for v in a], dtype="int") start = np.maximum(start, 1) end = np.minimum(np.resize(a, (C, R)).T, np.resize(b, (R, C))) + 1 # emi itself is a summation over the various values. emi = 0 for i in range(R): for j in range(C): for nij in range(start[i, j], end[i, j]): term2 = log_Nnij[nij] - log_ab_outer[i, j] # Numerators are positive, denominators are negative. gln = ( gln_a[i] + gln_b[j] + gln_Na[i] + gln_Nb[j] - gln_N - gln_nij[nij] - scipy.special.gammaln(a[i] - nij + 1) - scipy.special.gammaln(b[j] - nij + 1) - scipy.special.gammaln(N - a[i] - b[j] + nij + 1) ) term3 = np.exp(gln) emi += term1[nij] * term2 * term3 # Calculate entropy for each labeling h_true, h_pred = _entropy(reference_indices), _entropy(estimated_indices) ami = (mi - emi) / (max(h_true, h_pred) - emi) return ami def _normalized_mutual_info_score(reference_indices, estimated_indices): """Compute the mutual information between two sequence labelings, adjusted for chance. Parameters ---------- reference_indices : np.ndarray Array of reference indices estimated_indices : np.ndarray Array of estimated indices Returns ------- nmi : float <= 1.0 Normalized mutual information .. note:: Based on sklearn.metrics.cluster.normalized_mutual_info_score """ ref_classes = np.unique(reference_indices) est_classes = np.unique(estimated_indices) # Special limit cases: no clustering since the data is not split. # This is a perfect match hence return 1.0. if ( ref_classes.shape[0] == est_classes.shape[0] == 1 or ref_classes.shape[0] == est_classes.shape[0] == 0 ): return 1.0 contingency = _contingency_matrix(reference_indices, estimated_indices).astype( float ) contingency = np.array(contingency, dtype="float") # Calculate the MI for the two clusterings mi = _mutual_info_score( reference_indices, estimated_indices, contingency=contingency ) # Calculate the expected value for the mutual information # Calculate entropy for each labeling h_true, h_pred = _entropy(reference_indices), _entropy(estimated_indices) nmi = mi / max(np.sqrt(h_true * h_pred), 1e-10) return nmi def mutual_information( reference_intervals, reference_labels, estimated_intervals, estimated_labels, frame_size=0.1, ): """Frame-clustering segmentation: mutual information metrics. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> # Trim or pad the estimate to match reference timing >>> (ref_intervals, ... ref_labels) = mir_eval.util.adjust_intervals(ref_intervals, ... ref_labels, ... t_min=0) >>> (est_intervals, ... est_labels) = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, t_min=0, t_max=ref_intervals.max()) >>> mi, ami, nmi = mir_eval.structure.mutual_information(ref_intervals, ... ref_labels, ... est_intervals, ... est_labels) Parameters ---------- reference_intervals : np.ndarray, shape=(n, 2) reference segment intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. reference_labels : list, shape=(n,) reference segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. estimated_intervals : np.ndarray, shape=(m, 2) estimated segment intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. estimated_labels : list, shape=(m,) estimated segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. frame_size : float > 0 length (in seconds) of frames for clustering (Default value = 0.1) Returns ------- MI : float > 0 Mutual information between segmentations AMI : float Adjusted mutual information between segmentations. NMI : float > 0 Normalize mutual information between segmentations """ validate_structure( reference_intervals, reference_labels, estimated_intervals, estimated_labels ) # Check for empty annotations. Don't need to check labels because # validate_structure makes sure they're the same size as intervals if reference_intervals.size == 0 or estimated_intervals.size == 0: return 0.0, 0.0, 0.0 # Generate the cluster labels y_ref = util.intervals_to_samples( reference_intervals, reference_labels, sample_size=frame_size )[-1] y_ref = util.index_labels(y_ref)[0] # Map to index space y_est = util.intervals_to_samples( estimated_intervals, estimated_labels, sample_size=frame_size )[-1] y_est = util.index_labels(y_est)[0] # Mutual information mutual_info = _mutual_info_score(y_ref, y_est) # Adjusted mutual information adj_mutual_info = _adjusted_mutual_info_score(y_ref, y_est) # Normalized mutual information norm_mutual_info = _normalized_mutual_info_score(y_ref, y_est) return mutual_info, adj_mutual_info, norm_mutual_info def nce( reference_intervals, reference_labels, estimated_intervals, estimated_labels, frame_size=0.1, beta=1.0, marginal=False, ): """Frame-clustering segmentation: normalized conditional entropy Computes cross-entropy of cluster assignment, normalized by the max-entropy. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> # Trim or pad the estimate to match reference timing >>> (ref_intervals, ... ref_labels) = mir_eval.util.adjust_intervals(ref_intervals, ... ref_labels, ... t_min=0) >>> (est_intervals, ... est_labels) = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, t_min=0, t_max=ref_intervals.max()) >>> S_over, S_under, S_F = mir_eval.structure.nce(ref_intervals, ... ref_labels, ... est_intervals, ... est_labels) Parameters ---------- reference_intervals : np.ndarray, shape=(n, 2) reference segment intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. reference_labels : list, shape=(n,) reference segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. estimated_intervals : np.ndarray, shape=(m, 2) estimated segment intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. estimated_labels : list, shape=(m,) estimated segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. frame_size : float > 0 length (in seconds) of frames for clustering (Default value = 0.1) beta : float > 0 beta for F-measure (Default value = 1.0) marginal : bool If `False`, normalize conditional entropy by uniform entropy. If `True`, normalize conditional entropy by the marginal entropy. (Default value = False) Returns ------- S_over Over-clustering score: - For `marginal=False`, ``1 - H(y_est | y_ref) / log(|y_est|)`` - For `marginal=True`, ``1 - H(y_est | y_ref) / H(y_est)`` If `|y_est|==1`, then `S_over` will be 0. S_under Under-clustering score: - For `marginal=False`, ``1 - H(y_ref | y_est) / log(|y_ref|)`` - For `marginal=True`, ``1 - H(y_ref | y_est) / H(y_ref)`` If `|y_ref|==1`, then `S_under` will be 0. S_F F-measure for (S_over, S_under) """ validate_structure( reference_intervals, reference_labels, estimated_intervals, estimated_labels ) # Check for empty annotations. Don't need to check labels because # validate_structure makes sure they're the same size as intervals if reference_intervals.size == 0 or estimated_intervals.size == 0: return 0.0, 0.0, 0.0 # Generate the cluster labels y_ref = util.intervals_to_samples( reference_intervals, reference_labels, sample_size=frame_size )[-1] y_ref = util.index_labels(y_ref)[0] # Map to index space y_est = util.intervals_to_samples( estimated_intervals, estimated_labels, sample_size=frame_size )[-1] y_est = util.index_labels(y_est)[0] # Make the contingency table: shape = (n_ref, n_est) contingency = _contingency_matrix(y_ref, y_est).astype(float) # Normalize by the number of frames contingency = contingency / len(y_ref) # Compute the marginals p_est = contingency.sum(axis=0) p_ref = contingency.sum(axis=1) # H(true | prediction) = sum_j P[estimated = j] * # sum_i P[true = i | estimated = j] log P[true = i | estimated = j] # entropy sums over axis=0, which is true labels true_given_est = p_est.dot(scipy.stats.entropy(contingency, base=2)) pred_given_ref = p_ref.dot(scipy.stats.entropy(contingency.T, base=2)) if marginal: # Normalize conditional entropy by marginal entropy z_ref = scipy.stats.entropy(p_ref, base=2) z_est = scipy.stats.entropy(p_est, base=2) else: z_ref = np.log2(contingency.shape[0]) z_est = np.log2(contingency.shape[1]) score_under = 0.0 if z_ref > 0: score_under = 1.0 - true_given_est / z_ref score_over = 0.0 if z_est > 0: score_over = 1.0 - pred_given_ref / z_est f_measure = util.f_measure(score_over, score_under, beta=beta) return score_over, score_under, f_measure def vmeasure( reference_intervals, reference_labels, estimated_intervals, estimated_labels, frame_size=0.1, beta=1.0, ): """Frame-clustering segmentation: v-measure Computes cross-entropy of cluster assignment, normalized by the marginal-entropy. This is equivalent to `nce(..., marginal=True)`. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> # Trim or pad the estimate to match reference timing >>> (ref_intervals, ... ref_labels) = mir_eval.util.adjust_intervals(ref_intervals, ... ref_labels, ... t_min=0) >>> (est_intervals, ... est_labels) = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, t_min=0, t_max=ref_intervals.max()) >>> V_precision, V_recall, V_F = mir_eval.structure.vmeasure(ref_intervals, ... ref_labels, ... est_intervals, ... est_labels) Parameters ---------- reference_intervals : np.ndarray, shape=(n, 2) reference segment intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. reference_labels : list, shape=(n,) reference segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. estimated_intervals : np.ndarray, shape=(m, 2) estimated segment intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. estimated_labels : list, shape=(m,) estimated segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. frame_size : float > 0 length (in seconds) of frames for clustering (Default value = 0.1) beta : float > 0 beta for F-measure (Default value = 1.0) Returns ------- V_precision Over-clustering score: ``1 - H(y_est | y_ref) / H(y_est)`` If `|y_est|==1`, then `V_precision` will be 0. V_recall Under-clustering score: ``1 - H(y_ref | y_est) / H(y_ref)`` If `|y_ref|==1`, then `V_recall` will be 0. V_F F-measure for (V_precision, V_recall) """ return nce( reference_intervals, reference_labels, estimated_intervals, estimated_labels, frame_size=frame_size, beta=beta, marginal=True, ) def evaluate(ref_intervals, ref_labels, est_intervals, est_labels, **kwargs): """Compute all metrics for the given reference and estimated annotations. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> scores = mir_eval.segment.evaluate(ref_intervals, ref_labels, ... est_intervals, est_labels) Parameters ---------- ref_intervals : np.ndarray, shape=(n, 2) reference segment intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. ref_labels : list, shape=(n,) reference segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. est_intervals : np.ndarray, shape=(m, 2) estimated segment intervals, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. est_labels : list, shape=(m,) estimated segment labels, in the format returned by :func:`mir_eval.io.load_labeled_intervals`. **kwargs Additional keyword arguments which will be passed to the appropriate metric or preprocessing functions. Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. """ # Adjust timespan of estimations relative to ground truth ref_intervals, ref_labels = util.adjust_intervals( ref_intervals, labels=ref_labels, t_min=0.0 ) est_intervals, est_labels = util.adjust_intervals( est_intervals, labels=est_labels, t_min=0.0, t_max=ref_intervals.max() ) # Now compute all the metrics scores = collections.OrderedDict() # Boundary detection # Force these values for window kwargs["window"] = 0.5 ( scores["Precision@0.5"], scores["Recall@0.5"], scores["F-measure@0.5"], ) = util.filter_kwargs(detection, ref_intervals, est_intervals, **kwargs) kwargs["window"] = 3.0 ( scores["Precision@3.0"], scores["Recall@3.0"], scores["F-measure@3.0"], ) = util.filter_kwargs(detection, ref_intervals, est_intervals, **kwargs) # Boundary deviation scores["Ref-to-est deviation"], scores["Est-to-ref deviation"] = util.filter_kwargs( deviation, ref_intervals, est_intervals, **kwargs ) # Pairwise clustering ( scores["Pairwise Precision"], scores["Pairwise Recall"], scores["Pairwise F-measure"], ) = util.filter_kwargs( pairwise, ref_intervals, ref_labels, est_intervals, est_labels, **kwargs ) # Rand index scores["Rand Index"] = util.filter_kwargs( rand_index, ref_intervals, ref_labels, est_intervals, est_labels, **kwargs ) # Adjusted rand index scores["Adjusted Rand Index"] = util.filter_kwargs( ari, ref_intervals, ref_labels, est_intervals, est_labels, **kwargs ) # Mutual information metrics ( scores["Mutual Information"], scores["Adjusted Mutual Information"], scores["Normalized Mutual Information"], ) = util.filter_kwargs( mutual_information, ref_intervals, ref_labels, est_intervals, est_labels, **kwargs ) # Conditional entropy metrics ( scores["NCE Over"], scores["NCE Under"], scores["NCE F-measure"], ) = util.filter_kwargs( nce, ref_intervals, ref_labels, est_intervals, est_labels, **kwargs ) # V-measure metrics scores["V Precision"], scores["V Recall"], scores["V-measure"] = util.filter_kwargs( vmeasure, ref_intervals, ref_labels, est_intervals, est_labels, **kwargs ) return scores mir_eval-0.8.2/mir_eval/separation.py000066400000000000000000001124111475740344600176520ustar00rootroot00000000000000""" .. warning:: The mir_eval.separation module is deprecated in mir_eval version 0.8, and will be removed. We recommend that you migrate your code to use an alternative package such as sigsep-museval https://sigsep.github.io/sigsep-mus-eval/ Source separation algorithms attempt to extract recordings of individual sources from a recording of a mixture of sources. Evaluation methods for source separation compare the extracted sources from reference sources and attempt to measure the perceptual quality of the separation. See also the bss_eval MATLAB toolbox: http://bass-db.gforge.inria.fr/bss_eval/ Conventions ----------- An audio signal is expected to be in the format of a 1-dimensional array where the entries are the samples of the audio signal. When providing a group of estimated or reference sources, they should be provided in a 2-dimensional array, where the first dimension corresponds to the source number and the second corresponds to the samples. Metrics ------- * :func:`mir_eval.separation.bss_eval_sources`: Computes the bss_eval_sources metrics from bss_eval, which optionally optimally match the estimated sources to the reference sources and measure the distortion and artifacts present in the estimated sources as well as the interference between them. * :func:`mir_eval.separation.bss_eval_sources_framewise`: Computes the bss_eval_sources metrics on a frame-by-frame basis. * :func:`mir_eval.separation.bss_eval_images`: Computes the bss_eval_images metrics from bss_eval, which includes the metrics in :func:`mir_eval.separation.bss_eval_sources` plus the image to spatial distortion ratio. * :func:`mir_eval.separation.bss_eval_images_framewise`: Computes the bss_eval_images metrics on a frame-by-frame basis. References ---------- .. [#vincent2006performance] Emmanuel Vincent, Rémi Gribonval, and Cédric Févotte, "Performance measurement in blind audio source separation," IEEE Trans. on Audio, Speech and Language Processing, 14(4):1462-1469, 2006. """ import numpy as np import scipy.fftpack from scipy.linalg import toeplitz from scipy.signal import fftconvolve import collections import itertools import warnings from . import util # The maximum allowable number of sources (prevents insane computational load) MAX_SOURCES = 100 def validate(reference_sources, estimated_sources): """Check that the input data to a metric are valid, and throws helpful errors if not. Parameters ---------- reference_sources : np.ndarray, shape=(nsrc, nsampl) matrix containing true sources estimated_sources : np.ndarray, shape=(nsrc, nsampl) matrix containing estimated sources """ if reference_sources.shape != estimated_sources.shape: raise ValueError( "The shape of estimated sources and the true " "sources should match. reference_sources.shape " "= {}, estimated_sources.shape " "= {}".format(reference_sources.shape, estimated_sources.shape) ) if reference_sources.ndim > 3 or estimated_sources.ndim > 3: raise ValueError( "The number of dimensions is too high (must be less " "than 3). reference_sources.ndim = {}, " "estimated_sources.ndim " "= {}".format(reference_sources.ndim, estimated_sources.ndim) ) if reference_sources.size == 0: warnings.warn( "reference_sources is empty, should be of size " "(nsrc, nsample). sdr, sir, sar, and perm will all " "be empty np.ndarrays" ) elif _any_source_silent(reference_sources): raise ValueError( "All the reference sources should be non-silent (not " "all-zeros), but at least one of the reference " "sources is all 0s, which introduces ambiguity to the" " evaluation. (Otherwise we can add infinitely many " "all-zero sources.)" ) if estimated_sources.size == 0: warnings.warn( "estimated_sources is empty, should be of size " "(nsrc, nsample). sdr, sir, sar, and perm will all " "be empty np.ndarrays" ) elif _any_source_silent(estimated_sources): raise ValueError( "All the estimated sources should be non-silent (not " "all-zeros), but at least one of the estimated " "sources is all 0s. Since we require each reference " "source to be non-silent, having a silent estimated " "source will result in an underdetermined system." ) if ( estimated_sources.shape[0] > MAX_SOURCES or reference_sources.shape[0] > MAX_SOURCES ): raise ValueError( "The supplied matrices should be of shape (nsrc," " nsampl) but reference_sources.shape[0] = {} and " "estimated_sources.shape[0] = {} which is greater " "than mir_eval.separation.MAX_SOURCES = {}. To " "override this check, set " "mir_eval.separation.MAX_SOURCES to a " "larger value.".format( reference_sources.shape[0], estimated_sources.shape[0], MAX_SOURCES ) ) def _any_source_silent(sources): """Return true if the parameter sources has any silent first dimensions""" return np.any( np.all(np.sum(sources, axis=tuple(range(2, sources.ndim))) == 0, axis=1) ) @util.deprecated(version="0.8", version_removed="0.9") def bss_eval_sources(reference_sources, estimated_sources, compute_permutation=True): """ Ordering and measurement of the separation quality for estimated source signals in terms of filtered true source, interference and artifacts. The decomposition allows a time-invariant filter distortion of length 512, as described in Section III.B of [#vincent2006performance]_. Passing ``False`` for ``compute_permutation`` will improve the computation performance of the evaluation; however, it is not always appropriate and is not the way that the BSS_EVAL Matlab toolbox computes bss_eval_sources. Examples -------- >>> # reference_sources[n] should be an ndarray of samples of the >>> # n'th reference source >>> # estimated_sources[n] should be the same for the n'th estimated >>> # source >>> (sdr, sir, sar, ... perm) = mir_eval.separation.bss_eval_sources(reference_sources, ... estimated_sources) Parameters ---------- reference_sources : np.ndarray, shape=(nsrc, nsampl) matrix containing true sources (must have same shape as estimated_sources) estimated_sources : np.ndarray, shape=(nsrc, nsampl) matrix containing estimated sources (must have same shape as reference_sources) compute_permutation : bool, optional compute permutation of estimate/source combinations (True by default) Returns ------- sdr : np.ndarray, shape=(nsrc,) vector of Signal to Distortion Ratios (SDR) sir : np.ndarray, shape=(nsrc,) vector of Source to Interference Ratios (SIR) sar : np.ndarray, shape=(nsrc,) vector of Sources to Artifacts Ratios (SAR) perm : np.ndarray, shape=(nsrc,) vector containing the best ordering of estimated sources in the mean SIR sense (estimated source number ``perm[j]`` corresponds to true source number ``j``). Note: ``perm`` will be ``[0, 1, ..., nsrc-1]`` if ``compute_permutation`` is ``False``. References ---------- .. [#] Emmanuel Vincent, Shoko Araki, Fabian J. Theis, Guido Nolte, Pau Bofill, Hiroshi Sawada, Alexey Ozerov, B. Vikrham Gowreesunker, Dominik Lutter and Ngoc Q.K. Duong, "The Signal Separation Evaluation Campaign (2007-2010): Achievements and remaining challenges", Signal Processing, 92, pp. 1928-1936, 2012. """ # make sure the input is of shape (nsrc, nsampl) if estimated_sources.ndim == 1: estimated_sources = estimated_sources[np.newaxis, :] if reference_sources.ndim == 1: reference_sources = reference_sources[np.newaxis, :] validate(reference_sources, estimated_sources) # If empty matrices were supplied, return empty lists (special case) if reference_sources.size == 0 or estimated_sources.size == 0: return np.array([]), np.array([]), np.array([]), np.array([]) nsrc = estimated_sources.shape[0] # does user desire permutations? if compute_permutation: # compute criteria for all possible pair matches sdr = np.empty((nsrc, nsrc)) sir = np.empty((nsrc, nsrc)) sar = np.empty((nsrc, nsrc)) for jest in range(nsrc): for jtrue in range(nsrc): s_true, e_spat, e_interf, e_artif = _bss_decomp_mtifilt( reference_sources, estimated_sources[jest], jtrue, 512 ) sdr[jest, jtrue], sir[jest, jtrue], sar[jest, jtrue] = _bss_source_crit( s_true, e_spat, e_interf, e_artif ) # select the best ordering perms = list(itertools.permutations(list(range(nsrc)))) mean_sir = np.empty(len(perms)) dum = np.arange(nsrc) for i, perm in enumerate(perms): mean_sir[i] = np.mean(sir[perm, dum]) popt = perms[np.argmax(mean_sir)] idx = (popt, dum) return (sdr[idx], sir[idx], sar[idx], np.asarray(popt)) else: # compute criteria for only the simple correspondence # (estimate 1 is estimate corresponding to reference source 1, etc.) sdr = np.empty(nsrc) sir = np.empty(nsrc) sar = np.empty(nsrc) for j in range(nsrc): s_true, e_spat, e_interf, e_artif = _bss_decomp_mtifilt( reference_sources, estimated_sources[j], j, 512 ) sdr[j], sir[j], sar[j] = _bss_source_crit(s_true, e_spat, e_interf, e_artif) # return the default permutation for compatibility popt = np.arange(nsrc) return (sdr, sir, sar, popt) @util.deprecated(version="0.8", version_removed="0.9") def bss_eval_sources_framewise( reference_sources, estimated_sources, window=30 * 44100, hop=15 * 44100, compute_permutation=False, ): """Framewise computation of bss_eval_sources Please be aware that this function does not compute permutations (by default) on the possible relations between reference_sources and estimated_sources due to the dangers of a changing permutation. Therefore (by default), it assumes that ``reference_sources[i]`` corresponds to ``estimated_sources[i]``. To enable computing permutations please set ``compute_permutation`` to be ``True`` and check that the returned ``perm`` is identical for all windows. NOTE: if ``reference_sources`` and ``estimated_sources`` would be evaluated using only a single window or are shorter than the window length, the result of :func:`mir_eval.separation.bss_eval_sources` called on ``reference_sources`` and ``estimated_sources`` (with the ``compute_permutation`` parameter passed to :func:`mir_eval.separation.bss_eval_sources`) is returned. Examples -------- >>> # reference_sources[n] should be an ndarray of samples of the >>> # n'th reference source >>> # estimated_sources[n] should be the same for the n'th estimated >>> # source >>> (sdr, sir, sar, ... perm) = mir_eval.separation.bss_eval_sources_framewise( reference_sources, ... estimated_sources) Parameters ---------- reference_sources : np.ndarray, shape=(nsrc, nsampl) matrix containing true sources (must have the same shape as ``estimated_sources``) estimated_sources : np.ndarray, shape=(nsrc, nsampl) matrix containing estimated sources (must have the same shape as ``reference_sources``) window : int, optional Window length for framewise evaluation (default value is 30s at a sample rate of 44.1kHz) hop : int, optional Hop size for framewise evaluation (default value is 15s at a sample rate of 44.1kHz) compute_permutation : bool, optional compute permutation of estimate/source combinations for all windows (False by default) Returns ------- sdr : np.ndarray, shape=(nsrc, nframes) vector of Signal to Distortion Ratios (SDR) sir : np.ndarray, shape=(nsrc, nframes) vector of Source to Interference Ratios (SIR) sar : np.ndarray, shape=(nsrc, nframes) vector of Sources to Artifacts Ratios (SAR) perm : np.ndarray, shape=(nsrc, nframes) vector containing the best ordering of estimated sources in the mean SIR sense (estimated source number ``perm[j]`` corresponds to true source number ``j``). Note: ``perm`` will be ``range(nsrc)`` for all windows if ``compute_permutation`` is ``False`` """ # make sure the input is of shape (nsrc, nsampl) if estimated_sources.ndim == 1: estimated_sources = estimated_sources[np.newaxis, :] if reference_sources.ndim == 1: reference_sources = reference_sources[np.newaxis, :] validate(reference_sources, estimated_sources) # If empty matrices were supplied, return empty lists (special case) if reference_sources.size == 0 or estimated_sources.size == 0: return np.array([]), np.array([]), np.array([]), np.array([]) nsrc = reference_sources.shape[0] nwin = int(np.floor((reference_sources.shape[1] - window + hop) / hop)) # if fewer than 2 windows would be evaluated, return the sources result if nwin < 2: result = bss_eval_sources( reference_sources, estimated_sources, compute_permutation ) return [np.expand_dims(score, -1) for score in result] # compute the criteria across all windows sdr = np.empty((nsrc, nwin)) sir = np.empty((nsrc, nwin)) sar = np.empty((nsrc, nwin)) perm = np.empty((nsrc, nwin)) # k iterates across all the windows for k in range(nwin): win_slice = slice(k * hop, k * hop + window) ref_slice = reference_sources[:, win_slice] est_slice = estimated_sources[:, win_slice] # check for a silent frame if not _any_source_silent(ref_slice) and not _any_source_silent(est_slice): sdr[:, k], sir[:, k], sar[:, k], perm[:, k] = bss_eval_sources( ref_slice, est_slice, compute_permutation ) else: # if we have a silent frame set results as np.nan sdr[:, k] = sir[:, k] = sar[:, k] = perm[:, k] = np.nan return sdr, sir, sar, perm @util.deprecated(version="0.8", version_removed="0.9") def bss_eval_images(reference_sources, estimated_sources, compute_permutation=True): """Compute the bss_eval_images function from the BSS_EVAL Matlab toolbox. Ordering and measurement of the separation quality for estimated source signals in terms of filtered true source, interference and artifacts. This method also provides the ISR measure. The decomposition allows a time-invariant filter distortion of length 512, as described in Section III.B of [#vincent2006performance]_. Passing ``False`` for ``compute_permutation`` will improve the computation performance of the evaluation; however, it is not always appropriate and is not the way that the BSS_EVAL Matlab toolbox computes bss_eval_images. Examples -------- >>> # reference_sources[n] should be an ndarray of samples of the >>> # n'th reference source >>> # estimated_sources[n] should be the same for the n'th estimated >>> # source >>> (sdr, isr, sir, sar, ... perm) = mir_eval.separation.bss_eval_images(reference_sources, ... estimated_sources) Parameters ---------- reference_sources : np.ndarray, shape=(nsrc, nsampl, nchan) matrix containing true sources estimated_sources : np.ndarray, shape=(nsrc, nsampl, nchan) matrix containing estimated sources compute_permutation : bool, optional compute permutation of estimate/source combinations (True by default) Returns ------- sdr : np.ndarray, shape=(nsrc,) vector of Signal to Distortion Ratios (SDR) isr : np.ndarray, shape=(nsrc,) vector of source Image to Spatial distortion Ratios (ISR) sir : np.ndarray, shape=(nsrc,) vector of Source to Interference Ratios (SIR) sar : np.ndarray, shape=(nsrc,) vector of Sources to Artifacts Ratios (SAR) perm : np.ndarray, shape=(nsrc,) vector containing the best ordering of estimated sources in the mean SIR sense (estimated source number ``perm[j]`` corresponds to true source number ``j``). Note: ``perm`` will be ``(1,2,...,nsrc)`` if ``compute_permutation`` is ``False``. References ---------- .. [#] Emmanuel Vincent, Shoko Araki, Fabian J. Theis, Guido Nolte, Pau Bofill, Hiroshi Sawada, Alexey Ozerov, B. Vikrham Gowreesunker, Dominik Lutter and Ngoc Q.K. Duong, "The Signal Separation Evaluation Campaign (2007-2010): Achievements and remaining challenges", Signal Processing, 92, pp. 1928-1936, 2012. """ # make sure the input has 3 dimensions # assuming input is in shape (nsampl) or (nsrc, nsampl) estimated_sources = np.atleast_3d(estimated_sources) reference_sources = np.atleast_3d(reference_sources) # we will ensure input doesn't have more than 3 dimensions in validate validate(reference_sources, estimated_sources) # If empty matrices were supplied, return empty lists (special case) if reference_sources.size == 0 or estimated_sources.size == 0: return np.array([]), np.array([]), np.array([]), np.array([]), np.array([]) # determine size parameters nsrc = estimated_sources.shape[0] nsampl = estimated_sources.shape[1] nchan = estimated_sources.shape[2] # does the user desire permutation? if compute_permutation: # compute criteria for all possible pair matches sdr = np.empty((nsrc, nsrc)) isr = np.empty((nsrc, nsrc)) sir = np.empty((nsrc, nsrc)) sar = np.empty((nsrc, nsrc)) for jest in range(nsrc): for jtrue in range(nsrc): s_true, e_spat, e_interf, e_artif = _bss_decomp_mtifilt_images( reference_sources, np.reshape(estimated_sources[jest], (nsampl, nchan), order="F"), jtrue, 512, ) ( sdr[jest, jtrue], isr[jest, jtrue], sir[jest, jtrue], sar[jest, jtrue], ) = _bss_image_crit(s_true, e_spat, e_interf, e_artif) # select the best ordering perms = list(itertools.permutations(list(range(nsrc)))) mean_sir = np.empty(len(perms)) dum = np.arange(nsrc) for i, perm in enumerate(perms): mean_sir[i] = np.mean(sir[perm, dum]) popt = perms[np.argmax(mean_sir)] idx = (popt, dum) return (sdr[idx], isr[idx], sir[idx], sar[idx], np.asarray(popt)) else: # compute criteria for only the simple correspondence # (estimate 1 is estimate corresponding to reference source 1, etc.) sdr = np.empty(nsrc) isr = np.empty(nsrc) sir = np.empty(nsrc) sar = np.empty(nsrc) Gj = [0] * nsrc # prepare G matrices with zeroes G = np.zeros(1) for j in range(nsrc): # save G matrix to avoid recomputing it every call s_true, e_spat, e_interf, e_artif, Gj_temp, G = _bss_decomp_mtifilt_images( reference_sources, np.reshape(estimated_sources[j], (nsampl, nchan), order="F"), j, 512, Gj[j], G, ) Gj[j] = Gj_temp sdr[j], isr[j], sir[j], sar[j] = _bss_image_crit( s_true, e_spat, e_interf, e_artif ) # return the default permutation for compatibility popt = np.arange(nsrc) return (sdr, isr, sir, sar, popt) @util.deprecated(version="0.8", version_removed="0.9") def bss_eval_images_framewise( reference_sources, estimated_sources, window=30 * 44100, hop=15 * 44100, compute_permutation=False, ): """Framewise computation of bss_eval_images Please be aware that this function does not compute permutations (by default) on the possible relations between ``reference_sources`` and ``estimated_sources`` due to the dangers of a changing permutation. Therefore (by default), it assumes that ``reference_sources[i]`` corresponds to ``estimated_sources[i]``. To enable computing permutations please set ``compute_permutation`` to be ``True`` and check that the returned ``perm`` is identical for all windows. NOTE: if ``reference_sources`` and ``estimated_sources`` would be evaluated using only a single window or are shorter than the window length, the result of ``bss_eval_images`` called on ``reference_sources`` and ``estimated_sources`` (with the ``compute_permutation`` parameter passed to ``bss_eval_images``) is returned Examples -------- >>> # reference_sources[n] should be an ndarray of samples of the >>> # n'th reference source >>> # estimated_sources[n] should be the same for the n'th estimated >>> # source >>> (sdr, isr, sir, sar, ... perm) = mir_eval.separation.bss_eval_images_framewise( reference_sources, ... estimated_sources, window, .... hop) Parameters ---------- reference_sources : np.ndarray, shape=(nsrc, nsampl, nchan) matrix containing true sources (must have the same shape as ``estimated_sources``) estimated_sources : np.ndarray, shape=(nsrc, nsampl, nchan) matrix containing estimated sources (must have the same shape as ``reference_sources``) window : int Window length for framewise evaluation hop : int Hop size for framewise evaluation compute_permutation : bool, optional compute permutation of estimate/source combinations for all windows (False by default) Returns ------- sdr : np.ndarray, shape=(nsrc, nframes) vector of Signal to Distortion Ratios (SDR) isr : np.ndarray, shape=(nsrc, nframes) vector of source Image to Spatial distortion Ratios (ISR) sir : np.ndarray, shape=(nsrc, nframes) vector of Source to Interference Ratios (SIR) sar : np.ndarray, shape=(nsrc, nframes) vector of Sources to Artifacts Ratios (SAR) perm : np.ndarray, shape=(nsrc, nframes) vector containing the best ordering of estimated sources in the mean SIR sense (estimated source number perm[j] corresponds to true source number j) Note: perm will be range(nsrc) for all windows if compute_permutation is False """ # make sure the input has 3 dimensions # assuming input is in shape (nsampl) or (nsrc, nsampl) estimated_sources = np.atleast_3d(estimated_sources) reference_sources = np.atleast_3d(reference_sources) # we will ensure input doesn't have more than 3 dimensions in validate validate(reference_sources, estimated_sources) # If empty matrices were supplied, return empty lists (special case) if reference_sources.size == 0 or estimated_sources.size == 0: return np.array([]), np.array([]), np.array([]), np.array([]) nsrc = reference_sources.shape[0] nwin = int(np.floor((reference_sources.shape[1] - window + hop) / hop)) # if fewer than 2 windows would be evaluated, return the images result if nwin < 2: result = bss_eval_images( reference_sources, estimated_sources, compute_permutation ) return [np.expand_dims(score, -1) for score in result] # compute the criteria across all windows sdr = np.empty((nsrc, nwin)) isr = np.empty((nsrc, nwin)) sir = np.empty((nsrc, nwin)) sar = np.empty((nsrc, nwin)) perm = np.empty((nsrc, nwin)) # k iterates across all the windows for k in range(nwin): win_slice = slice(k * hop, k * hop + window) ref_slice = reference_sources[:, win_slice, :] est_slice = estimated_sources[:, win_slice, :] # check for a silent frame if not _any_source_silent(ref_slice) and not _any_source_silent(est_slice): sdr[:, k], isr[:, k], sir[:, k], sar[:, k], perm[:, k] = bss_eval_images( ref_slice, est_slice, compute_permutation ) else: # if we have a silent frame set results as np.nan sdr[:, k] = sir[:, k] = sar[:, k] = perm[:, k] = np.nan return sdr, isr, sir, sar, perm def _bss_decomp_mtifilt(reference_sources, estimated_source, j, flen): """Decomposition of an estimated source image into four components representing respectively the true source image, spatial (or filtering) distortion, interference and artifacts, derived from the true source images using multichannel time-invariant filters. """ nsampl = estimated_source.size # decomposition # true source image s_true = np.hstack((reference_sources[j], np.zeros(flen - 1))) # spatial (or filtering) distortion e_spat = ( _project(reference_sources[j, np.newaxis, :], estimated_source, flen) - s_true ) # interference e_interf = _project(reference_sources, estimated_source, flen) - s_true - e_spat # artifacts e_artif = -s_true - e_spat - e_interf e_artif[:nsampl] += estimated_source return (s_true, e_spat, e_interf, e_artif) def _bss_decomp_mtifilt_images( reference_sources, estimated_source, j, flen, Gj=None, G=None ): """Decomposition of an estimated source image into four components representing respectively the true source image, spatial (or filtering) distortion, interference and artifacts, derived from the true source images using multichannel time-invariant filters. Adapted version to work with multichannel sources. Improved performance can be gained by passing Gj and G parameters initially as all zeros. These parameters store the results from the computation of the G matrix in _project_images and then return them for subsequent calls to this function. This only works when not computing permutations. """ nsampl = np.shape(estimated_source)[0] nchan = np.shape(estimated_source)[1] # are we saving the Gj and G parameters? saveg = Gj is not None and G is not None # decomposition # true source image s_true = np.hstack( ( np.reshape(reference_sources[j], (nsampl, nchan), order="F").transpose(), np.zeros((nchan, flen - 1)), ) ) # spatial (or filtering) distortion if saveg: e_spat, Gj = _project_images( reference_sources[j, np.newaxis, :], estimated_source, flen, Gj ) else: e_spat = _project_images( reference_sources[j, np.newaxis, :], estimated_source, flen ) e_spat = e_spat - s_true # interference if saveg: e_interf, G = _project_images(reference_sources, estimated_source, flen, G) else: e_interf = _project_images(reference_sources, estimated_source, flen) e_interf = e_interf - s_true - e_spat # artifacts e_artif = -s_true - e_spat - e_interf e_artif[:, :nsampl] += estimated_source.transpose() # return Gj and G only if they were passed in if saveg: return (s_true, e_spat, e_interf, e_artif, Gj, G) else: return (s_true, e_spat, e_interf, e_artif) def _project(reference_sources, estimated_source, flen): """Least-squares projection of estimated source on the subspace spanned by delayed versions of reference sources, with delays between 0 and flen-1 """ nsrc = reference_sources.shape[0] nsampl = reference_sources.shape[1] # computing coefficients of least squares problem via FFT ## # zero padding and FFT of input data reference_sources = np.hstack((reference_sources, np.zeros((nsrc, flen - 1)))) estimated_source = np.hstack((estimated_source, np.zeros(flen - 1))) n_fft = int(2 ** np.ceil(np.log2(nsampl + flen - 1.0))) sf = scipy.fftpack.fft(reference_sources, n=n_fft, axis=1) sef = scipy.fftpack.fft(estimated_source, n=n_fft) # inner products between delayed versions of reference_sources G = np.zeros((nsrc * flen, nsrc * flen)) for i in range(nsrc): for j in range(nsrc): ssf = sf[i] * np.conj(sf[j]) ssf = np.real(scipy.fftpack.ifft(ssf)) ss = toeplitz(np.hstack((ssf[0], ssf[-1:-flen:-1])), r=ssf[:flen]) G[i * flen : (i + 1) * flen, j * flen : (j + 1) * flen] = ss G[j * flen : (j + 1) * flen, i * flen : (i + 1) * flen] = ss.T # inner products between estimated_source and delayed versions of # reference_sources D = np.zeros(nsrc * flen) for i in range(nsrc): ssef = sf[i] * np.conj(sef) ssef = np.real(scipy.fftpack.ifft(ssef)) D[i * flen : (i + 1) * flen] = np.hstack((ssef[0], ssef[-1:-flen:-1])) # Computing projection # Distortion filters try: C = np.linalg.solve(G, D).reshape(flen, nsrc, order="F") except np.linalg.linalg.LinAlgError: C = np.linalg.lstsq(G, D)[0].reshape(flen, nsrc, order="F") # Filtering sproj = np.zeros(nsampl + flen - 1) for i in range(nsrc): sproj += fftconvolve(C[:, i], reference_sources[i])[: nsampl + flen - 1] return sproj def _project_images(reference_sources, estimated_source, flen, G=None): """Least-squares projection of estimated source on the subspace spanned by delayed versions of reference sources, with delays between 0 and flen-1. Passing G as all zeros will populate the G matrix and return it so it can be passed into the next call to avoid recomputing G (this will only works if not computing permutations). """ nsrc = reference_sources.shape[0] nsampl = reference_sources.shape[1] nchan = reference_sources.shape[2] reference_sources = np.reshape( np.transpose(reference_sources, (2, 0, 1)), (nchan * nsrc, nsampl), order="F" ) # computing coefficients of least squares problem via FFT ## # zero padding and FFT of input data reference_sources = np.hstack( (reference_sources, np.zeros((nchan * nsrc, flen - 1))) ) estimated_source = np.hstack( (estimated_source.transpose(), np.zeros((nchan, flen - 1))) ) n_fft = int(2 ** np.ceil(np.log2(nsampl + flen - 1.0))) sf = scipy.fftpack.fft(reference_sources, n=n_fft, axis=1) sef = scipy.fftpack.fft(estimated_source, n=n_fft) # inner products between delayed versions of reference_sources if G is None: saveg = False G = np.zeros((nchan * nsrc * flen, nchan * nsrc * flen)) for i in range(nchan * nsrc): for j in range(i + 1): ssf = sf[i] * np.conj(sf[j]) ssf = np.real(scipy.fftpack.ifft(ssf)) ss = toeplitz(np.hstack((ssf[0], ssf[-1:-flen:-1])), r=ssf[:flen]) G[i * flen : (i + 1) * flen, j * flen : (j + 1) * flen] = ss G[j * flen : (j + 1) * flen, i * flen : (i + 1) * flen] = ss.T else: # avoid recomputing G (only works if no permutation is desired) saveg = True # return G if np.all(G == 0): # only compute G if passed as 0 G = np.zeros((nchan * nsrc * flen, nchan * nsrc * flen)) for i in range(nchan * nsrc): for j in range(i + 1): ssf = sf[i] * np.conj(sf[j]) ssf = np.real(scipy.fftpack.ifft(ssf)) ss = toeplitz(np.hstack((ssf[0], ssf[-1:-flen:-1])), r=ssf[:flen]) G[i * flen : (i + 1) * flen, j * flen : (j + 1) * flen] = ss G[j * flen : (j + 1) * flen, i * flen : (i + 1) * flen] = ss.T # inner products between estimated_source and delayed versions of # reference_sources D = np.zeros((nchan * nsrc * flen, nchan)) for k in range(nchan * nsrc): for i in range(nchan): ssef = sf[k] * np.conj(sef[i]) ssef = np.real(scipy.fftpack.ifft(ssef)) D[k * flen : (k + 1) * flen, i] = np.hstack( (ssef[0], ssef[-1:-flen:-1]) ).transpose() # Computing projection # Distortion filters try: C = np.linalg.solve(G, D).reshape(flen, nchan * nsrc, nchan, order="F") except np.linalg.linalg.LinAlgError: C = np.linalg.lstsq(G, D)[0].reshape(flen, nchan * nsrc, nchan, order="F") # Filtering sproj = np.zeros((nchan, nsampl + flen - 1)) for k in range(nchan * nsrc): for i in range(nchan): sproj[i] += fftconvolve(C[:, k, i].transpose(), reference_sources[k])[ : nsampl + flen - 1 ] # return G only if it was passed in if saveg: return sproj, G else: return sproj def _bss_source_crit(s_true, e_spat, e_interf, e_artif): """Measurement of the separation quality for a given source in terms of filtered true source, interference and artifacts. """ # energy ratios s_filt = s_true + e_spat sdr = _safe_db(np.sum(s_filt**2), np.sum((e_interf + e_artif) ** 2)) sir = _safe_db(np.sum(s_filt**2), np.sum(e_interf**2)) sar = _safe_db(np.sum((s_filt + e_interf) ** 2), np.sum(e_artif**2)) return (sdr, sir, sar) def _bss_image_crit(s_true, e_spat, e_interf, e_artif): """Measurement of the separation quality for a given image in terms of filtered true source, spatial error, interference and artifacts. """ # energy ratios sdr = _safe_db(np.sum(s_true**2), np.sum((e_spat + e_interf + e_artif) ** 2)) isr = _safe_db(np.sum(s_true**2), np.sum(e_spat**2)) sir = _safe_db(np.sum((s_true + e_spat) ** 2), np.sum(e_interf**2)) sar = _safe_db(np.sum((s_true + e_spat + e_interf) ** 2), np.sum(e_artif**2)) return (sdr, isr, sir, sar) def _safe_db(num, den): """Properly handle the potential +Inf db SIR, instead of raising a RuntimeWarning. Only denominator is checked because the numerator can never be 0. """ if den == 0: return np.inf return 10 * np.log10(num / den) @util.deprecated(version="0.8", version_removed="0.9") def evaluate(reference_sources, estimated_sources, **kwargs): """Compute all metrics for the given reference and estimated signals. NOTE: This will always compute :func:`mir_eval.separation.bss_eval_images` for any valid input and will additionally compute :func:`mir_eval.separation.bss_eval_sources` for valid input with fewer than 3 dimensions. Examples -------- >>> # reference_sources[n] should be an ndarray of samples of the >>> # n'th reference source >>> # estimated_sources[n] should be the same for the n'th estimated source >>> scores = mir_eval.separation.evaluate(reference_sources, ... estimated_sources) Parameters ---------- reference_sources : np.ndarray, shape=(nsrc, nsampl[, nchan]) matrix containing true sources estimated_sources : np.ndarray, shape=(nsrc, nsampl[, nchan]) matrix containing estimated sources **kwargs Additional keyword arguments which will be passed to the appropriate metric or preprocessing functions. Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. """ # Compute all the metrics scores = collections.OrderedDict() sdr, isr, sir, sar, perm = util.filter_kwargs( bss_eval_images, reference_sources, estimated_sources, **kwargs ) scores["Images - Source to Distortion"] = sdr.tolist() scores["Images - Image to Spatial"] = isr.tolist() scores["Images - Source to Interference"] = sir.tolist() scores["Images - Source to Artifact"] = sar.tolist() scores["Images - Source permutation"] = perm.tolist() sdr, isr, sir, sar, perm = util.filter_kwargs( bss_eval_images_framewise, reference_sources, estimated_sources, **kwargs ) scores["Images Frames - Source to Distortion"] = sdr.tolist() scores["Images Frames - Image to Spatial"] = isr.tolist() scores["Images Frames - Source to Interference"] = sir.tolist() scores["Images Frames - Source to Artifact"] = sar.tolist() scores["Images Frames - Source permutation"] = perm.tolist() # Verify we can compute sources on this input if reference_sources.ndim < 3 and estimated_sources.ndim < 3: sdr, sir, sar, perm = util.filter_kwargs( bss_eval_sources_framewise, reference_sources, estimated_sources, **kwargs ) scores["Sources Frames - Source to Distortion"] = sdr.tolist() scores["Sources Frames - Source to Interference"] = sir.tolist() scores["Sources Frames - Source to Artifact"] = sar.tolist() scores["Sources Frames - Source permutation"] = perm.tolist() sdr, sir, sar, perm = util.filter_kwargs( bss_eval_sources, reference_sources, estimated_sources, **kwargs ) scores["Sources - Source to Distortion"] = sdr.tolist() scores["Sources - Source to Interference"] = sir.tolist() scores["Sources - Source to Artifact"] = sar.tolist() scores["Sources - Source permutation"] = perm.tolist() return scores mir_eval-0.8.2/mir_eval/sonify.py000066400000000000000000000310151475740344600170140ustar00rootroot00000000000000""" Methods which sonify annotations for "evaluation by ear". All functions return a raw signal at the specified sampling rate. """ import numpy as np import scipy.signal from numpy.lib.stride_tricks import as_strided from scipy.interpolate import interp1d from . import util from . import chord def clicks(times, fs, click=None, length=None): """Return a signal with the signal 'click' placed at each specified time Parameters ---------- times : np.ndarray times to place clicks, in seconds fs : int desired sampling rate of the output signal click : np.ndarray click signal, defaults to a 1 kHz blip length : int desired number of samples in the output signal, defaults to ``times.max()*fs + click.shape[0] + 1`` Returns ------- click_signal : np.ndarray Synthesized click signal """ # Create default click signal if click is None: # 1 kHz tone, 100ms click = np.sin(2 * np.pi * np.arange(fs * 0.1) * 1000 / (1.0 * fs)) # Exponential decay click *= np.exp(-np.arange(fs * 0.1) / (fs * 0.01)) # Set default length if length is None: length = int(times.max() * fs + click.shape[0] + 1) # Pre-allocate click signal click_signal = np.zeros(length) # Place clicks for time in times: # Compute the boundaries of the click start = int(time * fs) end = start + click.shape[0] # Make sure we don't try to output past the end of the signal if start >= length: break if end >= length: click_signal[start:] = click[: length - start] break # Normally, just add a click here click_signal[start:end] = click return click_signal def time_frequency( gram, frequencies, times, fs, function=np.sin, length=None, n_dec=1, threshold=0.01 ): r"""Reverse synthesis of a time-frequency representation of a signal Parameters ---------- gram : np.ndarray ``gram[n, m]`` is the magnitude of ``frequencies[n]`` from ``times[m]`` to ``times[m + 1]`` Non-positive magnitudes are interpreted as silence. frequencies : np.ndarray array of size ``gram.shape[0]`` denoting the frequency (in Hz) of each row of gram times : np.ndarray, shape= ``(gram.shape[1],)`` or ``(gram.shape[1], 2)`` Either the start time (in seconds) of each column in the gram, or the time interval (in seconds) corresponding to each column. fs : int desired sampling rate of the output signal function : function function to use to synthesize notes, should be :math:`2\pi`-periodic length : int desired number of samples in the output signal, defaults to ``times[-1]*fs`` n_dec : int the number of decimals used to approximate each sonfied frequency. Defaults to 1 decimal place. Higher precision will be slower. threshold : float optimizes synthesis to only occur for frequencies that have a linear magnitude of at least one element in gram above the given threshold. Returns ------- output : np.ndarray synthesized version of the piano roll """ # Convert times to intervals if necessary time_converted = False if times.ndim == 1: # Convert to intervals times = np.hstack((times[:-1, np.newaxis], times[1:, np.newaxis])) # We'll need this to keep track of whether we should pad an interval on time_converted = True # Default value for length if length is None: length = int(np.max(times) * fs) last_time_in_secs = float(length) / fs if time_converted and times.shape[0] != gram.shape[1]: times = np.vstack((times, [np.max(times), last_time_in_secs])) if times.shape[0] != gram.shape[1]: raise ValueError( f"times.shape={times.shape} is incompatible with gram.shape={gram.shape}" ) if frequencies.shape[0] != gram.shape[0]: raise ValueError( f"frequencies.shape={frequencies.shape} is incompatible with gram.shape={gram.shape}" ) padding = [0, 0] stacking = [] if times.min() > 0: # We need to pad a silence column on to gram at the beginning padding[0] = 1 stacking.append([0, times.min()]) stacking.append(times) if times.max() < last_time_in_secs: # We need to pad a silence column onto gram at the end padding[1] = 1 stacking.append([times.max(), last_time_in_secs]) gram = np.pad(gram, ((0, 0), padding), mode="constant") times = np.vstack(stacking) # Identify the time intervals that have some overlap with the duration idx = np.logical_and(times[:, 1] >= 0, times[:, 0] <= last_time_in_secs) gram = gram[:, idx] times = np.clip(times[idx], 0, last_time_in_secs) n_times = times.shape[0] # Threshold the tfgram to remove negative values gram = np.maximum(gram, 0) # Pre-allocate output signal output = np.zeros(length) if gram.shape[1] == 0: # There are no time intervals to process, so return # the empty signal. return output # Discard frequencies below threshold freq_keep = np.max(gram, axis=1) >= threshold gram = gram[freq_keep, :] frequencies = frequencies[freq_keep] # Interpolate the values in gram over the time grid. if n_times > 1: interpolator = interp1d( times[:, 0] * fs, gram[:, :n_times], kind="previous", bounds_error=False, fill_value=(gram[:, 0], gram[:, -1]), ) signal = interpolator(np.arange(length)) else: # NOTE: This is a special case where there is only one time interval. # scipy 1.10 and above handle this case directly with the interp1d above, # but older scipy's do not. This is a workaround for that. # # In the 0.9 release, we can bump the minimum scipy to 1.10 and remove this signal = np.tile(gram[:, 0], (1, length)) for n, frequency in enumerate(frequencies): # Get a waveform of length samples at this frequency wave = _fast_synthesize(frequency, n_dec, fs, function, length) # Use a two-cycle ramp to smooth over transients period = 2 * int(fs / frequency) filter = np.ones(period) / period signal_n = scipy.signal.convolve(signal[n], filter, mode="same") # Mix the signal into the output output[:] += wave[: len(signal_n)] * signal_n # Normalize, but only if there's non-zero values norm = np.abs(output).max() if norm >= np.finfo(output.dtype).tiny: output /= norm return output def _fast_synthesize(frequency, n_dec, fs, function, length): """Efficiently synthesize a signal. Generate one cycle, and simulate arbitrary repetitions using array indexing tricks. """ # hack so that we can ensure an integer number of periods and samples # rounds frequency to 1st decimal, s.t. 10 * frequency will be an int frequency = np.round(frequency, n_dec) # Generate 10*frequency periods at this frequency # Equivalent to n_samples = int(n_periods * fs / frequency) # n_periods = 10*frequency is the smallest integer that guarantees # that n_samples will be an integer, since assuming 10*frequency # is an integer n_samples = int(10.0**n_dec * fs) short_signal = function(2.0 * np.pi * np.arange(n_samples) * frequency / fs) # Calculate the number of loops we need to fill the duration n_repeats = int(np.ceil(length / float(short_signal.shape[0]))) # Simulate tiling the short buffer by using stride tricks long_signal = as_strided( short_signal, shape=(n_repeats, len(short_signal)), strides=(0, short_signal.itemsize), ) # Use a flatiter to simulate a long 1D buffer return long_signal.flat def pitch_contour( times, frequencies, fs, amplitudes=None, function=np.sin, length=None, kind="linear" ): r"""Sonify a pitch contour. Parameters ---------- times : np.ndarray time indices for each frequency measurement, in seconds frequencies : np.ndarray frequency measurements, in Hz. Non-positive measurements or NaNs will be interpreted as un-voiced samples. fs : int desired sampling rate of the output signal amplitudes : np.ndarray amplitude measurements, nonnegative defaults to ``np.ones((length,))`` function : function function to use to synthesize notes, should be :math:`2\pi`-periodic length : int desired number of samples in the output signal, defaults to ``max(times)*fs`` kind : str Interpolation mode for the frequency and amplitude values. See: ``scipy.interpolate.interp1d`` for valid settings. Returns ------- output : np.ndarray synthesized version of the pitch contour """ fs = float(fs) if length is None: length = int(times.max() * fs) # Squash the negative frequencies. # wave(0) = 0, so clipping here will un-voice the corresponding instants frequencies = np.maximum(frequencies, 0.0) # Convert nans to zeros to unvoice frequencies = np.nan_to_num(frequencies, copy=False) # Build a frequency interpolator f_interp = interp1d( times * fs, 2 * np.pi * frequencies / fs, kind=kind, fill_value=0.0, bounds_error=False, copy=False, ) # Estimate frequency at sample points f_est = f_interp(np.arange(length)) if amplitudes is None: a_est = np.ones((length,)) else: # build an amplitude interpolator a_interp = interp1d( times * fs, amplitudes, kind=kind, fill_value=0.0, bounds_error=False, copy=False, ) a_est = a_interp(np.arange(length)) # Sonify the waveform return a_est * function(np.cumsum(f_est)) def chroma(chromagram, times, fs, **kwargs): """Reverse synthesis of a chromagram (semitone matrix) Parameters ---------- chromagram : np.ndarray, shape=(12, times.shape[0]) Chromagram matrix, where each row represents a semitone [C->Bb] i.e., ``chromagram[3, j]`` is the magnitude of D# from ``times[j]`` to ``times[j + 1]`` times : np.ndarray, shape=(len(chord_labels),) or (len(chord_labels), 2) Either the start time of each column in the chromagram, or the time interval corresponding to each column. fs : int Sampling rate to synthesize audio data at **kwargs Additional keyword arguments to pass to :func:`mir_eval.sonify.time_frequency` Returns ------- output : np.ndarray Synthesized chromagram """ # We'll just use time_frequency with a Shepard tone-gram # To create the Shepard tone-gram, we copy the chromagram across 7 octaves n_octaves = 7 # starting from C2 base_note = 24 # and weight each octave by a normal distribution # The normal distribution has mean 72 (one octave above middle C) # and std 6 (one half octave) mean = 72 std = 6 notes = np.arange(12 * n_octaves) + base_note shepard_weight = np.exp(-((notes - mean) ** 2.0) / (2.0 * std**2.0)) # Copy the chromagram matrix vertically n_octaves times gram = np.tile(chromagram.T, n_octaves).T # This fixes issues if the supplied chromagram is int type gram = gram.astype(float) # Apply Sheppard weighting gram *= shepard_weight.reshape(-1, 1) # Compute frequencies frequencies = 440.0 * (2.0 ** ((notes - 69) / 12.0)) return time_frequency(gram, frequencies, times, fs, **kwargs) def chords(chord_labels, intervals, fs, **kwargs): """Synthesizes chord labels Parameters ---------- chord_labels : list of str List of chord label strings. intervals : np.ndarray, shape=(len(chord_labels), 2) Start and end times of each chord label fs : int Sampling rate to synthesize at **kwargs Additional keyword arguments to pass to :func:`mir_eval.sonify.time_frequency` Returns ------- output : np.ndarray Synthesized chord labels """ util.validate_intervals(intervals) # Convert from labels to chroma roots, interval_bitmaps, _ = chord.encode_many(chord_labels) chromagram = np.array( [ np.roll(interval_bitmap, root) for (interval_bitmap, root) in zip(interval_bitmaps, roots) ] ).T return chroma(chromagram, intervals, fs, **kwargs) mir_eval-0.8.2/mir_eval/tempo.py000066400000000000000000000121021475740344600166250ustar00rootroot00000000000000""" The goal of a tempo estimation algorithm is to automatically detect the tempo of a piece of music, measured in beats per minute (BPM). See http://www.music-ir.org/mirex/wiki/2014:Audio_Tempo_Estimation for a description of the task and evaluation criteria. Conventions ----------- Reference and estimated tempi should be positive, and provided in ascending order as a numpy array of length 2. The weighting value from the reference must be a float in the range [0, 1]. Metrics ------- * :func:`mir_eval.tempo.detection`: Relative error, hits, and weighted precision of tempo estimation. """ import warnings import numpy as np import collections from . import util def validate_tempi(tempi, reference=True): """Check that there are two non-negative tempi. For a reference value, at least one tempo has to be greater than zero. Parameters ---------- tempi : np.ndarray length-2 array of tempo, in bpm reference : bool indicates a reference value """ if tempi.size != 2: raise ValueError("tempi must have exactly two values") if not np.all(np.isfinite(tempi)) or np.any(tempi < 0): raise ValueError(f"tempi={tempi} must be non-negative numbers") if reference and np.all(tempi == 0): raise ValueError( "reference tempi={} must have one" " value greater than zero".format(tempi) ) def validate(reference_tempi, reference_weight, estimated_tempi): """Check that the input annotations to a metric look like valid tempo annotations. Parameters ---------- reference_tempi : np.ndarray reference tempo values, in bpm reference_weight : float perceptual weight of slow vs fast in reference estimated_tempi : np.ndarray estimated tempo values, in bpm """ validate_tempi(reference_tempi, reference=True) validate_tempi(estimated_tempi, reference=False) if reference_weight < 0 or reference_weight > 1: raise ValueError("Reference weight must lie in range [0, 1]") def detection(reference_tempi, reference_weight, estimated_tempi, tol=0.08): """Compute the tempo detection accuracy metric. Parameters ---------- reference_tempi : np.ndarray, shape=(2,) Two non-negative reference tempi reference_weight : float > 0 The relative strength of ``reference_tempi[0]`` vs ``reference_tempi[1]``. estimated_tempi : np.ndarray, shape=(2,) Two non-negative estimated tempi. tol : float in [0, 1]: The maximum allowable deviation from a reference tempo to count as a hit. ``|est_t - ref_t| <= tol * ref_t`` (Default value = 0.08) Returns ------- p_score : float in [0, 1] Weighted average of recalls: ``reference_weight * hits[0] + (1 - reference_weight) * hits[1]`` one_correct : bool True if at least one reference tempo was correctly estimated both_correct : bool True if both reference tempi were correctly estimated Raises ------ ValueError If the input tempi are ill-formed If the reference weight is not in the range [0, 1] If ``tol < 0`` or ``tol > 1``. """ validate(reference_tempi, reference_weight, estimated_tempi) if tol < 0 or tol > 1: raise ValueError( "invalid tolerance {}: must lie in the range " "[0, 1]".format(tol) ) if tol == 0.0: warnings.warn("A tolerance of 0.0 may not " "lead to the results you expect.") hits = [False, False] for i, ref_t in enumerate(reference_tempi): if ref_t > 0: # Compute the relative error for this reference tempo f_ref_t = float(ref_t) relative_error = np.min(np.abs(ref_t - estimated_tempi) / f_ref_t) # Count the hits hits[i] = relative_error <= tol p_score = reference_weight * hits[0] + (1.0 - reference_weight) * hits[1] one_correct = bool(np.max(hits)) both_correct = bool(np.min(hits)) return p_score, one_correct, both_correct def evaluate(reference_tempi, reference_weight, estimated_tempi, **kwargs): """Compute all metrics for the given reference and estimated annotations. Parameters ---------- reference_tempi : np.ndarray, shape=(2,) Two non-negative reference tempi reference_weight : float > 0 The relative strength of ``reference_tempi[0]`` vs ``reference_tempi[1]``. estimated_tempi : np.ndarray, shape=(2,) Two non-negative estimated tempi. **kwargs Additional keyword arguments which will be passed to the appropriate metric or preprocessing functions. Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. """ # Compute all metrics scores = collections.OrderedDict() ( scores["P-score"], scores["One-correct"], scores["Both-correct"], ) = util.filter_kwargs( detection, reference_tempi, reference_weight, estimated_tempi, **kwargs ) return scores mir_eval-0.8.2/mir_eval/transcription.py000066400000000000000000001071511475740344600204110ustar00rootroot00000000000000""" The aim of a transcription algorithm is to produce a symbolic representation of a recorded piece of music in the form of a set of discrete notes. There are different ways to represent notes symbolically. Here we use the piano-roll convention, meaning each note has a start time, a duration (or end time), and a single, constant, pitch value. Pitch values can be quantized (e.g. to a semitone grid tuned to 440 Hz), but do not have to be. Also, the transcription can contain the notes of a single instrument or voice (for example the melody), or the notes of all instruments/voices in the recording. This module is instrument agnostic: all notes in the estimate are compared against all notes in the reference. There are many metrics for evaluating transcription algorithms. Here we limit ourselves to the most simple and commonly used: given two sets of notes, we count how many estimated notes match the reference, and how many do not. Based on these counts we compute the precision, recall, f-measure and overlap ratio of the estimate given the reference. The default criteria for considering two notes to be a match are adopted from the `MIREX Multiple fundamental frequency estimation and tracking, Note Tracking subtask (task 2) `_: "This subtask is evaluated in two different ways. In the first setup , a returned note is assumed correct if its onset is within +-50ms of a reference note and its F0 is within +- quarter tone of the corresponding reference note, ignoring the returned offset values. In the second setup, on top of the above requirements, a correct returned note is required to have an offset value within 20% of the reference note's duration around the reference note's offset, or within 50ms whichever is larger." In short, we compute precision, recall, f-measure and overlap ratio, once without taking offsets into account, and the second time with. For further details see Salamon, 2013 (page 186), and references therein: Salamon, J. (2013). Melody Extraction from Polyphonic Music Signals. Ph.D. thesis, Universitat Pompeu Fabra, Barcelona, Spain, 2013. IMPORTANT NOTE: the evaluation code in ``mir_eval`` contains several important differences with respect to the code used in MIREX 2015 for the Note Tracking subtask on the Su dataset (henceforth "MIREX"): 1. ``mir_eval`` uses bipartite graph matching to find the optimal pairing of reference notes to estimated notes. MIREX uses a greedy matching algorithm, which can produce sub-optimal note matching. This will result in ``mir_eval``'s metrics being slightly higher compared to MIREX. 2. MIREX rounds down the onset and offset times of each note to 2 decimal points using ``new_time = 0.01 * floor(time*100)``. ``mir_eval`` rounds down the note onset and offset times to 4 decinal points. This will bring our metrics down a notch compared to the MIREX results. 3. In the MIREX wiki, the criterion for matching offsets is that they must be within ``0.2 * ref_duration`` **or 0.05 seconds from each other, whichever is greater** (i.e. ``offset_dif <= max(0.2 * ref_duration, 0.05)``. The MIREX code however only uses a threshold of ``0.2 * ref_duration``, without the 0.05 second minimum. Since ``mir_eval`` does include this minimum, it might produce slightly higher results compared to MIREX. This means that differences 1 and 3 bring ``mir_eval``'s metrics up compared to MIREX, whilst 2 brings them down. Based on internal testing, overall the effect of these three differences is that the Precision, Recall and F-measure returned by ``mir_eval`` will be higher compared to MIREX by about 1%-2%. Finally, note that different evaluation scripts have been used for the Multi-F0 Note Tracking task in MIREX over the years. In particular, some scripts used ``<`` for matching onsets, offsets, and pitch values, whilst the others used ``<=`` for these checks. ``mir_eval`` provides both options: by default the latter (``<=``) is used, but you can set ``strict=True`` when calling :func:`mir_eval.transcription.precision_recall_f1_overlap()` in which case ``<`` will be used. The default value (``strict=False``) is the same as that used in MIREX 2015 for the Note Tracking subtask on the Su dataset. Conventions ----------- Notes should be provided in the form of an interval array and a pitch array. The interval array contains two columns, one for note onsets and the second for note offsets (each row represents a single note). The pitch array contains one column with the corresponding note pitch values (one value per note), represented by their fundamental frequency (f0) in Hertz. Metrics ------- * :func:`mir_eval.transcription.precision_recall_f1_overlap`: The precision, recall, F-measure, and Average Overlap Ratio of the note transcription, where an estimated note is considered correct if its pitch, onset and (optionally) offset are sufficiently close to a reference note. * :func:`mir_eval.transcription.onset_precision_recall_f1`: The precision, recall and F-measure of the note transcription, where an estimated note is considered correct if its onset is sufficiently close to a reference note's onset. That is, these metrics are computed taking only note onsets into account, meaning two notes could be matched even if they have very different pitch values. * :func:`mir_eval.transcription.offset_precision_recall_f1`: The precision, recall and F-measure of the note transcription, where an estimated note is considered correct if its offset is sufficiently close to a reference note's offset. That is, these metrics are computed taking only note offsets into account, meaning two notes could be matched even if they have very different pitch values. """ import numpy as np import collections from . import util import warnings # The number of decimals to keep for onset/offset threshold checks N_DECIMALS = 4 def validate(ref_intervals, ref_pitches, est_intervals, est_pitches): """Check that the input annotations to a metric look like time intervals and a pitch list, and throws helpful errors if not. Parameters ---------- ref_intervals : np.ndarray, shape=(n,2) Array of reference notes time intervals (onset and offset times) ref_pitches : np.ndarray, shape=(n,) Array of reference pitch values in Hertz est_intervals : np.ndarray, shape=(m,2) Array of estimated notes time intervals (onset and offset times) est_pitches : np.ndarray, shape=(m,) Array of estimated pitch values in Hertz """ # Validate intervals validate_intervals(ref_intervals, est_intervals) # Make sure intervals and pitches match in length if not ref_intervals.shape[0] == ref_pitches.shape[0]: raise ValueError("Reference intervals and pitches have different " "lengths.") if not est_intervals.shape[0] == est_pitches.shape[0]: raise ValueError("Estimated intervals and pitches have different " "lengths.") # Make sure all pitch values are positive if ref_pitches.size > 0 and np.min(ref_pitches) <= 0: raise ValueError("Reference contains at least one non-positive pitch " "value") if est_pitches.size > 0 and np.min(est_pitches) <= 0: raise ValueError("Estimate contains at least one non-positive pitch " "value") def validate_intervals(ref_intervals, est_intervals): """Check that the input annotations to a metric look like time intervals, and throws helpful errors if not. Parameters ---------- ref_intervals : np.ndarray, shape=(n,2) Array of reference notes time intervals (onset and offset times) est_intervals : np.ndarray, shape=(m,2) Array of estimated notes time intervals (onset and offset times) """ # If reference or estimated notes are empty, warn if ref_intervals.size == 0: warnings.warn("Reference notes are empty.") if est_intervals.size == 0: warnings.warn("Estimated notes are empty.") # Validate intervals util.validate_intervals(ref_intervals) util.validate_intervals(est_intervals) def match_note_offsets( ref_intervals, est_intervals, offset_ratio=0.2, offset_min_tolerance=0.05, strict=False, ): """Compute a maximum matching between reference and estimated notes, only taking note offsets into account. Given two note sequences represented by ``ref_intervals`` and ``est_intervals`` (see :func:`mir_eval.io.load_valued_intervals`), we seek the largest set of correspondences ``(i, j)`` such that the offset of reference note ``i`` has to be within ``offset_tolerance`` of the offset of estimated note ``j``, where ``offset_tolerance`` is equal to ``offset_ratio`` times the reference note's duration, i.e. ``offset_ratio * ref_duration[i]`` where ``ref_duration[i] = ref_intervals[i, 1] - ref_intervals[i, 0]``. If the resulting ``offset_tolerance`` is less than ``offset_min_tolerance`` (50 ms by default) then ``offset_min_tolerance`` is used instead. Every reference note is matched against at most one estimated note. Note there are separate functions :func:`match_note_onsets` and :func:`match_notes` for matching notes based on onsets only or based on onset, offset, and pitch, respectively. This is because the rules for matching note onsets and matching note offsets are different. Parameters ---------- ref_intervals : np.ndarray, shape=(n,2) Array of reference notes time intervals (onset and offset times) est_intervals : np.ndarray, shape=(m,2) Array of estimated notes time intervals (onset and offset times) offset_ratio : float > 0 The ratio of the reference note's duration used to define the ``offset_tolerance``. Default is 0.2 (20%), meaning the ``offset_tolerance`` will equal the ``ref_duration * 0.2``, or 0.05 (50 ms), whichever is greater. offset_min_tolerance : float > 0 The minimum tolerance for offset matching. See ``offset_ratio`` description for an explanation of how the offset tolerance is determined. strict : bool If ``strict=False`` (the default), threshold checks for offset matching are performed using ``<=`` (less than or equal). If ``strict=True``, the threshold checks are performed using ``<`` (less than). Returns ------- matching : list of tuples A list of matched reference and estimated notes. ``matching[i] == (i, j)`` where reference note ``i`` matches estimated note ``j``. """ # set the comparison function if strict: cmp_func = np.less else: cmp_func = np.less_equal # check for offset matches offset_distances = np.abs( np.subtract.outer(ref_intervals[:, 1], est_intervals[:, 1]) ) # Round distances to a target precision to avoid the situation where # if the distance is exactly 50ms (and strict=False) it erroneously # doesn't match the notes because of precision issues. offset_distances = np.around(offset_distances, decimals=N_DECIMALS) ref_durations = util.intervals_to_durations(ref_intervals) offset_tolerances = np.maximum(offset_ratio * ref_durations, offset_min_tolerance) offset_hit_matrix = cmp_func(offset_distances, offset_tolerances.reshape(-1, 1)) # check for hits hits = np.where(offset_hit_matrix) # Construct the graph input # Flip graph so that 'matching' is a list of tuples where the first item # in each tuple is the reference note index, and the second item is the # estimated note index. G = {} for ref_i, est_i in zip(*hits): if est_i not in G: G[est_i] = [] G[est_i].append(ref_i) # Compute the maximum matching matching = sorted(util._bipartite_match(G).items()) return matching def match_note_onsets(ref_intervals, est_intervals, onset_tolerance=0.05, strict=False): """Compute a maximum matching between reference and estimated notes, only taking note onsets into account. Given two note sequences represented by ``ref_intervals`` and ``est_intervals`` (see :func:`mir_eval.io.load_valued_intervals`), we see the largest set of correspondences ``(i,j)`` such that the onset of reference note ``i`` is within ``onset_tolerance`` of the onset of estimated note ``j``. Every reference note is matched against at most one estimated note. Note there are separate functions :func:`match_note_offsets` and :func:`match_notes` for matching notes based on offsets only or based on onset, offset, and pitch, respectively. This is because the rules for matching note onsets and matching note offsets are different. Parameters ---------- ref_intervals : np.ndarray, shape=(n,2) Array of reference notes time intervals (onset and offset times) est_intervals : np.ndarray, shape=(m,2) Array of estimated notes time intervals (onset and offset times) onset_tolerance : float > 0 The tolerance for an estimated note's onset deviating from the reference note's onset, in seconds. Default is 0.05 (50 ms). strict : bool If ``strict=False`` (the default), threshold checks for onset matching are performed using ``<=`` (less than or equal). If ``strict=True``, the threshold checks are performed using ``<`` (less than). Returns ------- matching : list of tuples A list of matched reference and estimated notes. ``matching[i] == (i, j)`` where reference note ``i`` matches estimated note ``j``. """ # set the comparison function if strict: cmp_func = np.less else: cmp_func = np.less_equal # check for onset matches onset_distances = np.abs( np.subtract.outer(ref_intervals[:, 0], est_intervals[:, 0]) ) # Round distances to a target precision to avoid the situation where # if the distance is exactly 50ms (and strict=False) it erroneously # doesn't match the notes because of precision issues. onset_distances = np.around(onset_distances, decimals=N_DECIMALS) onset_hit_matrix = cmp_func(onset_distances, onset_tolerance) # find hits hits = np.where(onset_hit_matrix) # Construct the graph input # Flip graph so that 'matching' is a list of tuples where the first item # in each tuple is the reference note index, and the second item is the # estimated note index. G = {} for ref_i, est_i in zip(*hits): if est_i not in G: G[est_i] = [] G[est_i].append(ref_i) # Compute the maximum matching matching = sorted(util._bipartite_match(G).items()) return matching def match_notes( ref_intervals, ref_pitches, est_intervals, est_pitches, onset_tolerance=0.05, pitch_tolerance=50.0, offset_ratio=0.2, offset_min_tolerance=0.05, strict=False, ): """Compute a maximum matching between reference and estimated notes, subject to onset, pitch and (optionally) offset constraints. Given two note sequences represented by ``ref_intervals``, ``ref_pitches``, ``est_intervals`` and ``est_pitches`` (see :func:`mir_eval.io.load_valued_intervals`), we seek the largest set of correspondences ``(i, j)`` such that: 1. The onset of reference note ``i`` is within ``onset_tolerance`` of the onset of estimated note ``j``. 2. The pitch of reference note ``i`` is within ``pitch_tolerance`` of the pitch of estimated note ``j``. 3. If ``offset_ratio`` is not ``None``, the offset of reference note ``i`` has to be within ``offset_tolerance`` of the offset of estimated note ``j``, where ``offset_tolerance`` is equal to ``offset_ratio`` times the reference note's duration, i.e. ``offset_ratio * ref_duration[i]`` where ``ref_duration[i] = ref_intervals[i, 1] - ref_intervals[i, 0]``. If the resulting ``offset_tolerance`` is less than 0.05 (50 ms), 0.05 is used instead. 4. If ``offset_ratio`` is ``None``, note offsets are ignored, and only criteria 1 and 2 are taken into consideration. Every reference note is matched against at most one estimated note. This is useful for computing precision/recall metrics for note transcription. Note there are separate functions :func:`match_note_onsets` and :func:`match_note_offsets` for matching notes based on onsets only or based on offsets only, respectively. Parameters ---------- ref_intervals : np.ndarray, shape=(n,2) Array of reference notes time intervals (onset and offset times) ref_pitches : np.ndarray, shape=(n,) Array of reference pitch values in Hertz est_intervals : np.ndarray, shape=(m,2) Array of estimated notes time intervals (onset and offset times) est_pitches : np.ndarray, shape=(m,) Array of estimated pitch values in Hertz onset_tolerance : float > 0 The tolerance for an estimated note's onset deviating from the reference note's onset, in seconds. Default is 0.05 (50 ms). pitch_tolerance : float > 0 The tolerance for an estimated note's pitch deviating from the reference note's pitch, in cents. Default is 50.0 (50 cents). offset_ratio : float > 0 or None The ratio of the reference note's duration used to define the offset_tolerance. Default is 0.2 (20%), meaning the ``offset_tolerance`` will equal the ``ref_duration * 0.2``, or 0.05 (50 ms), whichever is greater. If ``offset_ratio`` is set to ``None``, offsets are ignored in the matching. offset_min_tolerance : float > 0 The minimum tolerance for offset matching. See offset_ratio description for an explanation of how the offset tolerance is determined. Note: this parameter only influences the results if ``offset_ratio`` is not ``None``. strict : bool If ``strict=False`` (the default), threshold checks for onset, offset, and pitch matching are performed using ``<=`` (less than or equal). If ``strict=True``, the threshold checks are performed using ``<`` (less than). Returns ------- matching : list of tuples A list of matched reference and estimated notes. ``matching[i] == (i, j)`` where reference note ``i`` matches estimated note ``j``. """ # set the comparison function if strict: cmp_func = np.less else: cmp_func = np.less_equal # check for onset matches onset_distances = np.abs( np.subtract.outer(ref_intervals[:, 0], est_intervals[:, 0]) ) # Round distances to a target precision to avoid the situation where # if the distance is exactly 50ms (and strict=False) it erroneously # doesn't match the notes because of precision issues. onset_distances = np.around(onset_distances, decimals=N_DECIMALS) onset_hit_matrix = cmp_func(onset_distances, onset_tolerance) # check for pitch matches pitch_distances = np.abs( 1200 * np.subtract.outer(np.log2(ref_pitches), np.log2(est_pitches)) ) pitch_hit_matrix = cmp_func(pitch_distances, pitch_tolerance) # check for offset matches if offset_ratio is not None if offset_ratio is not None: offset_distances = np.abs( np.subtract.outer(ref_intervals[:, 1], est_intervals[:, 1]) ) # Round distances to a target precision to avoid the situation where # if the distance is exactly 50ms (and strict=False) it erroneously # doesn't match the notes because of precision issues. offset_distances = np.around(offset_distances, decimals=N_DECIMALS) ref_durations = util.intervals_to_durations(ref_intervals) offset_tolerances = np.maximum( offset_ratio * ref_durations, offset_min_tolerance ) offset_hit_matrix = cmp_func(offset_distances, offset_tolerances.reshape(-1, 1)) else: offset_hit_matrix = True # check for overall matches note_hit_matrix = onset_hit_matrix * pitch_hit_matrix * offset_hit_matrix hits = np.where(note_hit_matrix) # Construct the graph input # Flip graph so that 'matching' is a list of tuples where the first item # in each tuple is the reference note index, and the second item is the # estimated note index. G = {} for ref_i, est_i in zip(*hits): if est_i not in G: G[est_i] = [] G[est_i].append(ref_i) # Compute the maximum matching matching = sorted(util._bipartite_match(G).items()) return matching def precision_recall_f1_overlap( ref_intervals, ref_pitches, est_intervals, est_pitches, onset_tolerance=0.05, pitch_tolerance=50.0, offset_ratio=0.2, offset_min_tolerance=0.05, strict=False, beta=1.0, ): """Compute the Precision, Recall and F-measure of correct vs incorrectly transcribed notes, and the Average Overlap Ratio for correctly transcribed notes (see :func:`average_overlap_ratio`). "Correctness" is determined based on note onset, pitch and (optionally) offset: an estimated note is assumed correct if its onset is within +-50ms of a reference note and its pitch (F0) is within +- quarter tone (50 cents) of the corresponding reference note. If ``offset_ratio`` is ``None``, note offsets are ignored in the comparison. Otherwise, on top of the above requirements, a correct returned note is required to have an offset value within 20% (by default, adjustable via the ``offset_ratio`` parameter) of the reference note's duration around the reference note's offset, or within ``offset_min_tolerance`` (50 ms by default), whichever is larger. Examples -------- >>> ref_intervals, ref_pitches = mir_eval.io.load_valued_intervals( ... 'reference.txt') >>> est_intervals, est_pitches = mir_eval.io.load_valued_intervals( ... 'estimated.txt') >>> (precision, ... recall, ... f_measure) = mir_eval.transcription.precision_recall_f1_overlap( ... ref_intervals, ref_pitches, est_intervals, est_pitches) >>> (precision_no_offset, ... recall_no_offset, ... f_measure_no_offset) = ( ... mir_eval.transcription.precision_recall_f1_overlap( ... ref_intervals, ref_pitches, est_intervals, est_pitches, ... offset_ratio=None)) Parameters ---------- ref_intervals : np.ndarray, shape=(n,2) Array of reference notes time intervals (onset and offset times) ref_pitches : np.ndarray, shape=(n,) Array of reference pitch values in Hertz est_intervals : np.ndarray, shape=(m,2) Array of estimated notes time intervals (onset and offset times) est_pitches : np.ndarray, shape=(m,) Array of estimated pitch values in Hertz onset_tolerance : float > 0 The tolerance for an estimated note's onset deviating from the reference note's onset, in seconds. Default is 0.05 (50 ms). pitch_tolerance : float > 0 The tolerance for an estimated note's pitch deviating from the reference note's pitch, in cents. Default is 50.0 (50 cents). offset_ratio : float > 0 or None The ratio of the reference note's duration used to define the offset_tolerance. Default is 0.2 (20%), meaning the ``offset_tolerance`` will equal the ``ref_duration * 0.2``, or ``offset_min_tolerance`` (0.05 by default, i.e. 50 ms), whichever is greater. If ``offset_ratio`` is set to ``None``, offsets are ignored in the evaluation. offset_min_tolerance : float > 0 The minimum tolerance for offset matching. See ``offset_ratio`` description for an explanation of how the offset tolerance is determined. Note: this parameter only influences the results if ``offset_ratio`` is not ``None``. strict : bool If ``strict=False`` (the default), threshold checks for onset, offset, and pitch matching are performed using ``<=`` (less than or equal). If ``strict=True``, the threshold checks are performed using ``<`` (less than). beta : float > 0 Weighting factor for f-measure (default value = 1.0). Returns ------- precision : float The computed precision score recall : float The computed recall score f_measure : float The computed F-measure score avg_overlap_ratio : float The computed Average Overlap Ratio score """ validate(ref_intervals, ref_pitches, est_intervals, est_pitches) # When reference notes are empty, metrics are undefined, return 0's if len(ref_pitches) == 0 or len(est_pitches) == 0: return 0.0, 0.0, 0.0, 0.0 matching = match_notes( ref_intervals, ref_pitches, est_intervals, est_pitches, onset_tolerance=onset_tolerance, pitch_tolerance=pitch_tolerance, offset_ratio=offset_ratio, offset_min_tolerance=offset_min_tolerance, strict=strict, ) precision = float(len(matching)) / len(est_pitches) recall = float(len(matching)) / len(ref_pitches) f_measure = util.f_measure(precision, recall, beta=beta) avg_overlap_ratio = average_overlap_ratio(ref_intervals, est_intervals, matching) return precision, recall, f_measure, avg_overlap_ratio def average_overlap_ratio(ref_intervals, est_intervals, matching): """Compute the Average Overlap Ratio between a reference and estimated note transcription. Given a reference and corresponding estimated note, their overlap ratio (OR) is defined as the ratio between the duration of the time segment in which the two notes overlap and the time segment spanned by the two notes combined (earliest onset to latest offset): >>> OR = ((min(ref_offset, est_offset) - max(ref_onset, est_onset)) / ... (max(ref_offset, est_offset) - min(ref_onset, est_onset))) The Average Overlap Ratio (AOR) is given by the mean OR computed over all matching reference and estimated notes. The metric goes from 0 (worst) to 1 (best). Note: this function assumes the matching of reference and estimated notes (see :func:`match_notes`) has already been performed and is provided by the ``matching`` parameter. Furthermore, it is highly recommended to validate the intervals (see :func:`validate_intervals`) before calling this function, otherwise it is possible (though unlikely) for this function to attempt a divide-by-zero operation. Parameters ---------- ref_intervals : np.ndarray, shape=(n,2) Array of reference notes time intervals (onset and offset times) est_intervals : np.ndarray, shape=(m,2) Array of estimated notes time intervals (onset and offset times) matching : list of tuples A list of matched reference and estimated notes. ``matching[i] == (i, j)`` where reference note ``i`` matches estimated note ``j``. Returns ------- avg_overlap_ratio : float The computed Average Overlap Ratio score """ ratios = [] for match in matching: ref_int = ref_intervals[match[0]] est_int = est_intervals[match[1]] overlap_ratio = (min(ref_int[1], est_int[1]) - max(ref_int[0], est_int[0])) / ( max(ref_int[1], est_int[1]) - min(ref_int[0], est_int[0]) ) ratios.append(overlap_ratio) if len(ratios) == 0: return 0 else: return np.mean(ratios) def onset_precision_recall_f1( ref_intervals, est_intervals, onset_tolerance=0.05, strict=False, beta=1.0 ): """Compute the Precision, Recall and F-measure of note onsets: an estimated onset is considered correct if it is within +-50ms of a reference onset. Note that this metric completely ignores note offset and note pitch. This means an estimated onset will be considered correct if it matches a reference onset, even if the onsets come from notes with completely different pitches (i.e. notes that would not match with :func:`match_notes`). Examples -------- >>> ref_intervals, _ = mir_eval.io.load_valued_intervals( ... 'reference.txt') >>> est_intervals, _ = mir_eval.io.load_valued_intervals( ... 'estimated.txt') >>> (onset_precision, ... onset_recall, ... onset_f_measure) = mir_eval.transcription.onset_precision_recall_f1( ... ref_intervals, est_intervals) Parameters ---------- ref_intervals : np.ndarray, shape=(n,2) Array of reference notes time intervals (onset and offset times) est_intervals : np.ndarray, shape=(m,2) Array of estimated notes time intervals (onset and offset times) onset_tolerance : float > 0 The tolerance for an estimated note's onset deviating from the reference note's onset, in seconds. Default is 0.05 (50 ms). strict : bool If ``strict=False`` (the default), threshold checks for onset matching are performed using ``<=`` (less than or equal). If ``strict=True``, the threshold checks are performed using ``<`` (less than). beta : float > 0 Weighting factor for f-measure (default value = 1.0). Returns ------- precision : float The computed precision score recall : float The computed recall score f_measure : float The computed F-measure score """ validate_intervals(ref_intervals, est_intervals) # When reference notes are empty, metrics are undefined, return 0's if len(ref_intervals) == 0 or len(est_intervals) == 0: return 0.0, 0.0, 0.0 matching = match_note_onsets( ref_intervals, est_intervals, onset_tolerance=onset_tolerance, strict=strict ) onset_precision = float(len(matching)) / len(est_intervals) onset_recall = float(len(matching)) / len(ref_intervals) onset_f_measure = util.f_measure(onset_precision, onset_recall, beta=beta) return onset_precision, onset_recall, onset_f_measure def offset_precision_recall_f1( ref_intervals, est_intervals, offset_ratio=0.2, offset_min_tolerance=0.05, strict=False, beta=1.0, ): """Compute the Precision, Recall and F-measure of note offsets: an estimated offset is considered correct if it is within +-50ms (or 20% of the ref note duration, which ever is greater) of a reference offset. Note that this metric completely ignores note onsets and note pitch. This means an estimated offset will be considered correct if it matches a reference offset, even if the offsets come from notes with completely different pitches (i.e. notes that would not match with :func:`match_notes`). Examples -------- >>> ref_intervals, _ = mir_eval.io.load_valued_intervals( ... 'reference.txt') >>> est_intervals, _ = mir_eval.io.load_valued_intervals( ... 'estimated.txt') >>> (offset_precision, ... offset_recall, ... offset_f_measure) = mir_eval.transcription.offset_precision_recall_f1( ... ref_intervals, est_intervals) Parameters ---------- ref_intervals : np.ndarray, shape=(n,2) Array of reference notes time intervals (onset and offset times) est_intervals : np.ndarray, shape=(m,2) Array of estimated notes time intervals (onset and offset times) offset_ratio : float > 0 or None The ratio of the reference note's duration used to define the offset_tolerance. Default is 0.2 (20%), meaning the ``offset_tolerance`` will equal the ``ref_duration * 0.2``, or ``offset_min_tolerance`` (0.05 by default, i.e. 50 ms), whichever is greater. offset_min_tolerance : float > 0 The minimum tolerance for offset matching. See ``offset_ratio`` description for an explanation of how the offset tolerance is determined. strict : bool If ``strict=False`` (the default), threshold checks for onset matching are performed using ``<=`` (less than or equal). If ``strict=True``, the threshold checks are performed using ``<`` (less than). beta : float > 0 Weighting factor for f-measure (default value = 1.0). Returns ------- precision : float The computed precision score recall : float The computed recall score f_measure : float The computed F-measure score """ validate_intervals(ref_intervals, est_intervals) # When reference notes are empty, metrics are undefined, return 0's if len(ref_intervals) == 0 or len(est_intervals) == 0: return 0.0, 0.0, 0.0 matching = match_note_offsets( ref_intervals, est_intervals, offset_ratio=offset_ratio, offset_min_tolerance=offset_min_tolerance, strict=strict, ) offset_precision = float(len(matching)) / len(est_intervals) offset_recall = float(len(matching)) / len(ref_intervals) offset_f_measure = util.f_measure(offset_precision, offset_recall, beta=beta) return offset_precision, offset_recall, offset_f_measure def evaluate(ref_intervals, ref_pitches, est_intervals, est_pitches, **kwargs): """Compute all metrics for the given reference and estimated annotations. Examples -------- >>> ref_intervals, ref_pitches = mir_eval.io.load_valued_intervals( ... 'reference.txt') >>> est_intervals, est_pitches = mir_eval.io.load_valued_intervals( ... 'estimate.txt') >>> scores = mir_eval.transcription.evaluate(ref_intervals, ref_pitches, ... est_intervals, est_pitches) Parameters ---------- ref_intervals : np.ndarray, shape=(n,2) Array of reference notes time intervals (onset and offset times) ref_pitches : np.ndarray, shape=(n,) Array of reference pitch values in Hertz est_intervals : np.ndarray, shape=(m,2) Array of estimated notes time intervals (onset and offset times) est_pitches : np.ndarray, shape=(m,) Array of estimated pitch values in Hertz **kwargs Additional keyword arguments which will be passed to the appropriate metric or preprocessing functions. Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. """ # Compute all the metrics scores = collections.OrderedDict() # Precision, recall and f-measure taking note offsets into account kwargs.setdefault("offset_ratio", 0.2) orig_offset_ratio = kwargs["offset_ratio"] if kwargs["offset_ratio"] is not None: ( scores["Precision"], scores["Recall"], scores["F-measure"], scores["Average_Overlap_Ratio"], ) = util.filter_kwargs( precision_recall_f1_overlap, ref_intervals, ref_pitches, est_intervals, est_pitches, **kwargs ) # Precision, recall and f-measure NOT taking note offsets into account kwargs["offset_ratio"] = None ( scores["Precision_no_offset"], scores["Recall_no_offset"], scores["F-measure_no_offset"], scores["Average_Overlap_Ratio_no_offset"], ) = util.filter_kwargs( precision_recall_f1_overlap, ref_intervals, ref_pitches, est_intervals, est_pitches, **kwargs ) # onset-only metrics ( scores["Onset_Precision"], scores["Onset_Recall"], scores["Onset_F-measure"], ) = util.filter_kwargs( onset_precision_recall_f1, ref_intervals, est_intervals, **kwargs ) # offset-only metrics kwargs["offset_ratio"] = orig_offset_ratio if kwargs["offset_ratio"] is not None: ( scores["Offset_Precision"], scores["Offset_Recall"], scores["Offset_F-measure"], ) = util.filter_kwargs( offset_precision_recall_f1, ref_intervals, est_intervals, **kwargs ) return scores mir_eval-0.8.2/mir_eval/transcription_velocity.py000066400000000000000000000413771475740344600223360ustar00rootroot00000000000000""" Transcription evaluation, as defined in :mod:`mir_eval.transcription`, does not take into account the velocities of reference and estimated notes. This submodule implements a variant of :func:`mir_eval.transcription.precision_recall_f1_overlap` which additionally considers note velocity when determining whether a note is correctly transcribed. This is done by defining a new function :func:`mir_eval.transcription_velocity.match_notes` which first calls :func:`mir_eval.transcription.match_notes` to get a note matching based on onset, offset, and pitch. Then, we follow the evaluation procedure described in [#hawthorne2018onsets]_ to test whether an estimated note should be considered correct: 1. Reference velocities are re-scaled to the range [0, 1]. 2. A linear regression is performed to estimate global scale and offset parameters which minimize the L2 distance between matched estimated and (rescaled) reference notes. 3. The scale and offset parameters are used to rescale estimated velocities. 4. An estimated/reference note pair which has been matched according to the onset, offset, and pitch is further only considered correct if the rescaled velocities are within a predefined threshold, defaulting to 0.1. :func:`mir_eval.transcription_velocity.match_notes` is used to define a new variant :func:`mir_eval.transcription_velocity.precision_recall_f1_overlap` which considers velocity. Conventions ----------- This submodule follows the conventions of :mod:`mir_eval.transcription` and additionally requires velocities to be provided as MIDI velocities in the range [0, 127]. Metrics ------- * :func:`mir_eval.transcription_velocity.precision_recall_f1_overlap`: The precision, recall, F-measure, and Average Overlap Ratio of the note transcription, where an estimated note is considered correct if its pitch, onset, velocity and (optionally) offset are sufficiently close to a reference note. References ---------- .. [#hawthorne2018onsets] Curtis Hawthorne, Erich Elsen, Jialin Song, Adam Roberts, Ian Simon, Colin Raffel, Jesse Engel, Sageev Oore, and Douglas Eck, "Onsets and Frames: Dual-Objective Piano Transcription", Proceedings of the 19th International Society for Music Information Retrieval Conference, 2018. """ import collections import numpy as np from . import transcription from . import util def validate( ref_intervals, ref_pitches, ref_velocities, est_intervals, est_pitches, est_velocities, ): """Check that the input annotations have valid time intervals, pitches, and velocities, and throws helpful errors if not. Parameters ---------- ref_intervals : np.ndarray, shape=(n,2) Array of reference notes time intervals (onset and offset times) ref_pitches : np.ndarray, shape=(n,) Array of reference pitch values in Hertz ref_velocities : np.ndarray, shape=(n,) Array of MIDI velocities (i.e. between 0 and 127) of reference notes est_intervals : np.ndarray, shape=(m,2) Array of estimated notes time intervals (onset and offset times) est_pitches : np.ndarray, shape=(m,) Array of estimated pitch values in Hertz est_velocities : np.ndarray, shape=(m,) Array of MIDI velocities (i.e. between 0 and 127) of estimated notes """ transcription.validate(ref_intervals, ref_pitches, est_intervals, est_pitches) # Check that velocities have the same length as intervals/pitches if not ref_velocities.shape[0] == ref_pitches.shape[0]: raise ValueError( "Reference velocities must have the same length as " "pitches and intervals." ) if not est_velocities.shape[0] == est_pitches.shape[0]: raise ValueError( "Estimated velocities must have the same length as " "pitches and intervals." ) # Check that the velocities are positive if ref_velocities.size > 0 and np.min(ref_velocities) < 0: raise ValueError("Reference velocities must be positive.") if est_velocities.size > 0 and np.min(est_velocities) < 0: raise ValueError("Estimated velocities must be positive.") def match_notes( ref_intervals, ref_pitches, ref_velocities, est_intervals, est_pitches, est_velocities, onset_tolerance=0.05, pitch_tolerance=50.0, offset_ratio=0.2, offset_min_tolerance=0.05, strict=False, velocity_tolerance=0.1, ): """Match notes, taking note velocity into consideration. This function first calls :func:`mir_eval.transcription.match_notes` to match notes according to the supplied intervals, pitches, onset, offset, and pitch tolerances. The velocities of the matched notes are then used to estimate a slope and intercept which can rescale the estimated velocities so that they are as close as possible (in L2 sense) to their matched reference velocities. Velocities are then normalized to the range [0, 1]. A estimated note is then further only considered correct if its velocity is within ``velocity_tolerance`` of its matched (according to pitch and timing) reference note. Parameters ---------- ref_intervals : np.ndarray, shape=(n,2) Array of reference notes time intervals (onset and offset times) ref_pitches : np.ndarray, shape=(n,) Array of reference pitch values in Hertz ref_velocities : np.ndarray, shape=(n,) Array of MIDI velocities (i.e. between 0 and 127) of reference notes est_intervals : np.ndarray, shape=(m,2) Array of estimated notes time intervals (onset and offset times) est_pitches : np.ndarray, shape=(m,) Array of estimated pitch values in Hertz est_velocities : np.ndarray, shape=(m,) Array of MIDI velocities (i.e. between 0 and 127) of estimated notes onset_tolerance : float > 0 The tolerance for an estimated note's onset deviating from the reference note's onset, in seconds. Default is 0.05 (50 ms). pitch_tolerance : float > 0 The tolerance for an estimated note's pitch deviating from the reference note's pitch, in cents. Default is 50.0 (50 cents). offset_ratio : float > 0 or None The ratio of the reference note's duration used to define the offset_tolerance. Default is 0.2 (20%), meaning the ``offset_tolerance`` will equal the ``ref_duration * 0.2``, or 0.05 (50 ms), whichever is greater. If ``offset_ratio`` is set to ``None``, offsets are ignored in the matching. offset_min_tolerance : float > 0 The minimum tolerance for offset matching. See offset_ratio description for an explanation of how the offset tolerance is determined. Note: this parameter only influences the results if ``offset_ratio`` is not ``None``. strict : bool If ``strict=False`` (the default), threshold checks for onset, offset, and pitch matching are performed using ``<=`` (less than or equal). If ``strict=True``, the threshold checks are performed using ``<`` (less than). velocity_tolerance : float > 0 Estimated notes are considered correct if, after rescaling and normalization to [0, 1], they are within ``velocity_tolerance`` of a matched reference note. Returns ------- matching : list of tuples A list of matched reference and estimated notes. ``matching[i] == (i, j)`` where reference note ``i`` matches estimated note ``j``. """ # Compute note matching as usual using standard transcription function matching = transcription.match_notes( ref_intervals, ref_pitches, est_intervals, est_pitches, onset_tolerance, pitch_tolerance, offset_ratio, offset_min_tolerance, strict, ) # Rescale reference velocities to the range [0, 1] min_velocity, max_velocity = np.min(ref_velocities), np.max(ref_velocities) # Make the smallest possible range 1 to avoid divide by zero velocity_range = max(1, max_velocity - min_velocity) ref_velocities = (ref_velocities - min_velocity) / float(velocity_range) # Convert matching list-of-tuples to array for fancy indexing matching = np.array(matching) # When there is no matching, return an empty list if matching.size == 0: return [] # Grab velocities for matched notes ref_matched_velocities = ref_velocities[matching[:, 0]] est_matched_velocities = est_velocities[matching[:, 1]] # Find slope and intercept of line which produces best least-squares fit # between matched est and ref velocities slope, intercept = np.linalg.lstsq( np.vstack([est_matched_velocities, np.ones(len(est_matched_velocities))]).T, ref_matched_velocities, rcond=None, )[0] # Re-scale est velocities to match ref est_matched_velocities = slope * est_matched_velocities + intercept # Compute the absolute error of (rescaled) estimated velocities vs. # normalized reference velocities. Error will be in [0, 1] velocity_diff = np.abs(est_matched_velocities - ref_matched_velocities) # Check whether each error is within the provided tolerance velocity_within_tolerance = velocity_diff < velocity_tolerance # Only keep matches whose velocity was within the provided tolerance matching = matching[velocity_within_tolerance] # Convert back to list-of-tuple format matching = [tuple(_) for _ in matching] return matching def precision_recall_f1_overlap( ref_intervals, ref_pitches, ref_velocities, est_intervals, est_pitches, est_velocities, onset_tolerance=0.05, pitch_tolerance=50.0, offset_ratio=0.2, offset_min_tolerance=0.05, strict=False, velocity_tolerance=0.1, beta=1.0, ): """Compute the Precision, Recall and F-measure of correct vs incorrectly transcribed notes, and the Average Overlap Ratio for correctly transcribed notes (see :func:`mir_eval.transcription.average_overlap_ratio`). "Correctness" is determined based on note onset, velocity, pitch and (optionally) offset. An estimated note is considered correct if 1. Its onset is within ``onset_tolerance`` (default +-50ms) of a reference note 2. Its pitch (F0) is within +/- ``pitch_tolerance`` (default one quarter tone, 50 cents) of the corresponding reference note 3. Its velocity, after normalizing reference velocities to the range [0, 1] and globally rescaling estimated velocities to minimize L2 distance between matched reference notes, is within ``velocity_tolerance`` (default 0.1) the corresponding reference note 4. If ``offset_ratio`` is ``None``, note offsets are ignored in the comparison. Otherwise, on top of the above requirements, a correct returned note is required to have an offset value within `offset_ratio`` (default 20%) of the reference note's duration around the reference note's offset, or within ``offset_min_tolerance`` (default 50 ms), whichever is larger. Parameters ---------- ref_intervals : np.ndarray, shape=(n,2) Array of reference notes time intervals (onset and offset times) ref_pitches : np.ndarray, shape=(n,) Array of reference pitch values in Hertz ref_velocities : np.ndarray, shape=(n,) Array of MIDI velocities (i.e. between 0 and 127) of reference notes est_intervals : np.ndarray, shape=(m,2) Array of estimated notes time intervals (onset and offset times) est_pitches : np.ndarray, shape=(m,) Array of estimated pitch values in Hertz est_velocities : np.ndarray, shape=(n,) Array of MIDI velocities (i.e. between 0 and 127) of estimated notes onset_tolerance : float > 0 The tolerance for an estimated note's onset deviating from the reference note's onset, in seconds. Default is 0.05 (50 ms). pitch_tolerance : float > 0 The tolerance for an estimated note's pitch deviating from the reference note's pitch, in cents. Default is 50.0 (50 cents). offset_ratio : float > 0 or None The ratio of the reference note's duration used to define the offset_tolerance. Default is 0.2 (20%), meaning the ``offset_tolerance`` will equal the ``ref_duration * 0.2``, or ``offset_min_tolerance`` (0.05 by default, i.e. 50 ms), whichever is greater. If ``offset_ratio`` is set to ``None``, offsets are ignored in the evaluation. offset_min_tolerance : float > 0 The minimum tolerance for offset matching. See ``offset_ratio`` description for an explanation of how the offset tolerance is determined. Note: this parameter only influences the results if ``offset_ratio`` is not ``None``. strict : bool If ``strict=False`` (the default), threshold checks for onset, offset, and pitch matching are performed using ``<=`` (less than or equal). If ``strict=True``, the threshold checks are performed using ``<`` (less than). velocity_tolerance : float > 0 Estimated notes are considered correct if, after rescaling and normalization to [0, 1], they are within ``velocity_tolerance`` of a matched reference note. beta : float > 0 Weighting factor for f-measure (default value = 1.0). Returns ------- precision : float The computed precision score recall : float The computed recall score f_measure : float The computed F-measure score avg_overlap_ratio : float The computed Average Overlap Ratio score """ validate( ref_intervals, ref_pitches, ref_velocities, est_intervals, est_pitches, est_velocities, ) # When reference notes are empty, metrics are undefined, return 0's if len(ref_pitches) == 0 or len(est_pitches) == 0: return 0.0, 0.0, 0.0, 0.0 matching = match_notes( ref_intervals, ref_pitches, ref_velocities, est_intervals, est_pitches, est_velocities, onset_tolerance, pitch_tolerance, offset_ratio, offset_min_tolerance, strict, velocity_tolerance, ) precision = float(len(matching)) / len(est_pitches) recall = float(len(matching)) / len(ref_pitches) f_measure = util.f_measure(precision, recall, beta=beta) avg_overlap_ratio = transcription.average_overlap_ratio( ref_intervals, est_intervals, matching ) return precision, recall, f_measure, avg_overlap_ratio def evaluate( ref_intervals, ref_pitches, ref_velocities, est_intervals, est_pitches, est_velocities, **kwargs ): """Compute all metrics for the given reference and estimated annotations. Parameters ---------- ref_intervals : np.ndarray, shape=(n,2) Array of reference notes time intervals (onset and offset times) ref_pitches : np.ndarray, shape=(n,) Array of reference pitch values in Hertz ref_velocities : np.ndarray, shape=(n,) Array of MIDI velocities (i.e. between 0 and 127) of reference notes est_intervals : np.ndarray, shape=(m,2) Array of estimated notes time intervals (onset and offset times) est_pitches : np.ndarray, shape=(m,) Array of estimated pitch values in Hertz est_velocities : np.ndarray, shape=(n,) Array of MIDI velocities (i.e. between 0 and 127) of estimated notes **kwargs Additional keyword arguments which will be passed to the appropriate metric or preprocessing functions. Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. """ # Compute all the metrics scores = collections.OrderedDict() # Precision, recall and f-measure taking note offsets into account kwargs.setdefault("offset_ratio", 0.2) if kwargs["offset_ratio"] is not None: ( scores["Precision"], scores["Recall"], scores["F-measure"], scores["Average_Overlap_Ratio"], ) = util.filter_kwargs( precision_recall_f1_overlap, ref_intervals, ref_pitches, ref_velocities, est_intervals, est_pitches, est_velocities, **kwargs ) # Precision, recall and f-measure NOT taking note offsets into account kwargs["offset_ratio"] = None ( scores["Precision_no_offset"], scores["Recall_no_offset"], scores["F-measure_no_offset"], scores["Average_Overlap_Ratio_no_offset"], ) = util.filter_kwargs( precision_recall_f1_overlap, ref_intervals, ref_pitches, ref_velocities, est_intervals, est_pitches, est_velocities, **kwargs ) return scores mir_eval-0.8.2/mir_eval/util.py000066400000000000000000000720271475740344600164720ustar00rootroot00000000000000""" Useful functionality required across the task submodules, such as preprocessing, validation, and common computations. """ import os import inspect import warnings from decorator import decorator import numpy as np def index_labels(labels, case_sensitive=False): """Convert a list of string identifiers into numerical indices. Parameters ---------- labels : list of strings, shape=(n,) A list of annotations, e.g., segment or chord labels from an annotation file. case_sensitive : bool Set to True to enable case-sensitive label indexing (Default value = False) Returns ------- indices : list, shape=(n,) Numerical representation of ``labels`` index_to_label : dict Mapping to convert numerical indices back to labels. ``labels[i] == index_to_label[indices[i]]`` """ label_to_index = {} index_to_label = {} # If we're not case-sensitive, if not case_sensitive: labels = [str(s).lower() for s in labels] # First, build the unique label mapping for index, s in enumerate(sorted(set(labels))): label_to_index[s] = index index_to_label[index] = s # Remap the labels to indices indices = [label_to_index[s] for s in labels] # Return the converted labels, and the inverse mapping return indices, index_to_label def generate_labels(items, prefix="__"): """Given an array of items (e.g. events, intervals), create a synthetic label for each event of the form '(label prefix)(item number)' Parameters ---------- items : list-like A list or array of events or intervals prefix : str This prefix will be prepended to all synthetically generated labels (Default value = '__') Returns ------- labels : list of str Synthetically generated labels """ return [f"{prefix}{n}" for n in range(len(items))] def intervals_to_samples(intervals, labels, offset=0, sample_size=0.1, fill_value=None): """Convert an array of labeled time intervals to annotated samples. Parameters ---------- intervals : np.ndarray, shape=(n, d) An array of time intervals, as returned by :func:`mir_eval.io.load_intervals()` or :func:`mir_eval.io.load_labeled_intervals()`. The ``i`` th interval spans time ``intervals[i, 0]`` to ``intervals[i, 1]``. labels : list, shape=(n,) The annotation for each interval offset : float > 0 Phase offset of the sampled time grid (in seconds) (Default value = 0) sample_size : float > 0 duration of each sample to be generated (in seconds) (Default value = 0.1) fill_value : type(labels[0]) Object to use for the label with out-of-range time points. (Default value = None) Returns ------- sample_times : list list of sample times sample_labels : list array of labels for each generated sample Notes ----- Intervals will be rounded down to the nearest multiple of ``sample_size``. """ # Round intervals to the sample size num_samples = int(np.floor(intervals.max() / sample_size)) sample_indices = np.arange(num_samples, dtype=np.float32) sample_times = (sample_indices * sample_size + offset).tolist() sampled_labels = interpolate_intervals(intervals, labels, sample_times, fill_value) return sample_times, sampled_labels def interpolate_intervals(intervals, labels, time_points, fill_value=None): """Assign labels to a set of points in time given a set of intervals. Time points that do not lie within an interval are mapped to `fill_value`. Parameters ---------- intervals : np.ndarray, shape=(n, 2) An array of time intervals, as returned by :func:`mir_eval.io.load_intervals()`. The ``i`` th interval spans time ``intervals[i, 0]`` to ``intervals[i, 1]``. Intervals are assumed to be disjoint. labels : list, shape=(n,) The annotation for each interval time_points : array_like, shape=(m,) Points in time to assign labels. These must be in non-decreasing order. fill_value : type(labels[0]) Object to use for the label with out-of-range time points. (Default value = None) Returns ------- aligned_labels : list Labels corresponding to the given time points. Raises ------ ValueError If `time_points` is not in non-decreasing order. """ # Verify that time_points is sorted time_points = np.asarray(time_points) if np.any(time_points[1:] < time_points[:-1]): raise ValueError("time_points must be in non-decreasing order") aligned_labels = [fill_value] * len(time_points) starts = np.searchsorted(time_points, intervals[:, 0], side="left") ends = np.searchsorted(time_points, intervals[:, 1], side="right") for start, end, lab in zip(starts, ends, labels): aligned_labels[start:end] = [lab] * (end - start) return aligned_labels def sort_labeled_intervals(intervals, labels=None): """Sort intervals, and optionally, their corresponding labels according to start time. Parameters ---------- intervals : np.ndarray, shape=(n, 2) The input intervals labels : list, optional Labels for each interval Returns ------- intervals_sorted or (intervals_sorted, labels_sorted) Labels are only returned if provided as input """ idx = np.argsort(intervals[:, 0]) intervals_sorted = intervals[idx] if labels is None: return intervals_sorted else: return intervals_sorted, [labels[_] for _ in idx] def f_measure(precision, recall, beta=1.0): """Compute the f-measure from precision and recall scores. Parameters ---------- precision : float in (0, 1] Precision recall : float in (0, 1] Recall beta : float > 0 Weighting factor for f-measure (Default value = 1.0) Returns ------- f_measure : float The weighted f-measure """ if precision == 0 and recall == 0: return 0.0 return (1 + beta**2) * precision * recall / ((beta**2) * precision + recall) def intervals_to_boundaries(intervals, q=5): """Convert interval times into boundaries. Parameters ---------- intervals : np.ndarray, shape=(n_events, 2) Array of interval start and end-times q : int Number of decimals to round to. (Default value = 5) Returns ------- boundaries : np.ndarray Interval boundary times, including the end of the final interval """ return np.unique(np.ravel(np.round(intervals, decimals=q))) def boundaries_to_intervals(boundaries): """Convert an array of event times into intervals Parameters ---------- boundaries : list-like List-like of event times. These are assumed to be unique timestamps in ascending order. Returns ------- intervals : np.ndarray, shape=(n_intervals, 2) Start and end time for each interval """ if not np.allclose(boundaries, np.unique(boundaries)): raise ValueError("Boundary times are not unique or not ascending.") intervals = np.asarray(list(zip(boundaries[:-1], boundaries[1:]))) return intervals def adjust_intervals( intervals, labels=None, t_min=0.0, t_max=None, start_label="__T_MIN", end_label="__T_MAX", ): """Adjust a list of time intervals to span the range ``[t_min, t_max]``. Any intervals lying completely outside the specified range will be removed. Any intervals lying partially outside the specified range will be cropped. If the specified range exceeds the span of the provided data in either direction, additional intervals will be appended. If an interval is appended at the beginning, it will be given the label ``start_label``; if an interval is appended at the end, it will be given the label ``end_label``. Parameters ---------- intervals : np.ndarray, shape=(n_events, 2) Array of interval start and end-times labels : list, len=n_events or None List of labels (Default value = None) t_min : float or None Minimum interval start time. (Default value = 0.0) t_max : float or None Maximum interval end time. (Default value = None) start_label : str or float or int Label to give any intervals appended at the beginning (Default value = '__T_MIN') end_label : str or float or int Label to give any intervals appended at the end (Default value = '__T_MAX') Returns ------- new_intervals : np.ndarray Intervals spanning ``[t_min, t_max]`` new_labels : list List of labels for ``new_labels`` """ # When supplied intervals are empty and t_max and t_min are supplied, # create one interval from t_min to t_max with the label start_label if t_min is not None and t_max is not None and intervals.size == 0: return np.array([[t_min, t_max]]), [start_label] # When intervals are empty and either t_min or t_max are not supplied, # we can't append new intervals elif (t_min is None or t_max is None) and intervals.size == 0: raise ValueError("Supplied intervals are empty, can't append new" " intervals") if t_min is not None: # Find the intervals that end at or after t_min first_idx = np.argwhere(intervals[:, 1] >= t_min) if len(first_idx) > 0: # If we have events below t_min, crop them out if labels is not None: labels = labels[first_idx[0, 0] :] # Clip to the range (t_min, +inf) intervals = intervals[first_idx[0, 0] :] intervals = np.maximum(t_min, intervals) if intervals.min() > t_min: # Lowest boundary is higher than t_min: # add a new boundary and label intervals = np.vstack(([t_min, intervals.min()], intervals)) if labels is not None: labels.insert(0, start_label) if t_max is not None: # Find the intervals that begin after t_max last_idx = np.argwhere(intervals[:, 0] > t_max) if len(last_idx) > 0: # We have boundaries above t_max. # Trim to only boundaries <= t_max if labels is not None: labels = labels[: last_idx[0, 0]] # Clip to the range (-inf, t_max) intervals = intervals[: last_idx[0, 0]] intervals = np.minimum(t_max, intervals) if intervals.max() < t_max: # Last boundary is below t_max: add a new boundary and label intervals = np.vstack((intervals, [intervals.max(), t_max])) if labels is not None: labels.append(end_label) return intervals, labels def adjust_events(events, labels=None, t_min=0.0, t_max=None, label_prefix="__"): """Adjust the given list of event times to span the range ``[t_min, t_max]``. Any event times outside of the specified range will be removed. If the times do not span ``[t_min, t_max]``, additional events will be added with the prefix ``label_prefix``. Parameters ---------- events : np.ndarray Array of event times (seconds) labels : list or None List of labels (Default value = None) t_min : float or None Minimum valid event time. (Default value = 0.0) t_max : float or None Maximum valid event time. (Default value = None) label_prefix : str Prefix string to use for synthetic labels (Default value = '__') Returns ------- new_times : np.ndarray Event times corrected to the given range. """ if t_min is not None: first_idx = np.argwhere(events >= t_min) if len(first_idx) > 0: # We have events below t_min # Crop them out if labels is not None: labels = labels[first_idx[0, 0] :] events = events[first_idx[0, 0] :] if events[0] > t_min: # Lowest boundary is higher than t_min: # add a new boundary and label events = np.concatenate(([t_min], events)) if labels is not None: labels.insert(0, "%sT_MIN" % label_prefix) if t_max is not None: last_idx = np.argwhere(events > t_max) if len(last_idx) > 0: # We have boundaries above t_max. # Trim to only boundaries <= t_max if labels is not None: labels = labels[: last_idx[0, 0]] events = events[: last_idx[0, 0]] if events[-1] < t_max: # Last boundary is below t_max: add a new boundary and label events = np.concatenate((events, [t_max])) if labels is not None: labels.append("%sT_MAX" % label_prefix) return events, labels def intersect_files(flist1, flist2): """Return the intersection of two sets of filepaths, based on the file name (after the final '/') and ignoring the file extension. Examples -------- >>> flist1 = ['/a/b/abc.lab', '/c/d/123.lab', '/e/f/xyz.lab'] >>> flist2 = ['/g/h/xyz.npy', '/i/j/123.txt', '/k/l/456.lab'] >>> sublist1, sublist2 = mir_eval.util.intersect_files(flist1, flist2) >>> print sublist1 ['/e/f/xyz.lab', '/c/d/123.lab'] >>> print sublist2 ['/g/h/xyz.npy', '/i/j/123.txt'] Parameters ---------- flist1 : list first list of filepaths flist2 : list second list of filepaths Returns ------- sublist1 : list subset of filepaths with matching stems from ``flist1`` sublist2 : list corresponding filepaths from ``flist2`` """ def fname(abs_path): """Return the filename given an absolute path. Parameters ---------- abs_path Returns ------- filename """ return os.path.splitext(os.path.split(abs_path)[-1])[0] fmap = {fname(f): f for f in flist1} pairs = [list(), list()] for f in flist2: if fname(f) in fmap: pairs[0].append(fmap[fname(f)]) pairs[1].append(f) return pairs def merge_labeled_intervals(x_intervals, x_labels, y_intervals, y_labels): r"""Merge the time intervals of two sequences. Parameters ---------- x_intervals : np.ndarray Array of interval times (seconds) x_labels : list or None List of labels y_intervals : np.ndarray Array of interval times (seconds) y_labels : list or None List of labels Returns ------- new_intervals : np.ndarray New interval times of the merged sequences. new_x_labels : list New labels for the sequence ``x`` new_y_labels : list New labels for the sequence ``y`` """ align_check = [ x_intervals[0, 0] == y_intervals[0, 0], x_intervals[-1, 1] == y_intervals[-1, 1], ] if False in align_check: raise ValueError( "Time intervals do not align; did you mean to call " "'adjust_intervals()' first?" ) time_boundaries = np.unique(np.concatenate([x_intervals, y_intervals], axis=0)) output_intervals = np.array([time_boundaries[:-1], time_boundaries[1:]]).T x_labels_out, y_labels_out = [], [] x_label_range = np.arange(len(x_labels)) y_label_range = np.arange(len(y_labels)) for t0, _ in output_intervals: x_idx = x_label_range[(t0 >= x_intervals[:, 0])] x_labels_out.append(x_labels[x_idx[-1]]) y_idx = y_label_range[(t0 >= y_intervals[:, 0])] y_labels_out.append(y_labels[y_idx[-1]]) return output_intervals, x_labels_out, y_labels_out def _bipartite_match(graph): """Find maximum cardinality matching of a bipartite graph (U,V,E). The input format is a dictionary mapping members of U to a list of their neighbors in V. The output is a dict M mapping members of V to their matches in U. Parameters ---------- graph : dictionary : left-vertex -> list of right vertices The input bipartite graph. Each edge need only be specified once. Returns ------- matching : dictionary : right-vertex -> left vertex A maximal bipartite matching. """ # Adapted from: # # Hopcroft-Karp bipartite max-cardinality matching and max independent set # David Eppstein, UC Irvine, 27 Apr 2002 # initialize greedy matching (redundant, but faster than full search) matching = {} for u in graph: for v in graph[u]: if v not in matching: matching[v] = u break while True: # structure residual graph into layers # pred[u] gives the neighbor in the previous layer for u in U # preds[v] gives a list of neighbors in the previous layer for v in V # unmatched gives a list of unmatched vertices in final layer of V, # and is also used as a flag value for pred[u] when u is in the first # layer preds = {} unmatched = [] pred = {u: unmatched for u in graph} for v in matching: del pred[matching[v]] layer = list(pred) # repeatedly extend layering structure by another pair of layers while layer and not unmatched: new_layer = {} for u in layer: for v in graph[u]: if v not in preds: new_layer.setdefault(v, []).append(u) layer = [] for v in new_layer: preds[v] = new_layer[v] if v in matching: layer.append(matching[v]) pred[matching[v]] = v else: unmatched.append(v) # did we finish layering without finding any alternating paths? if not unmatched: unlayered = {} for u in graph: for v in graph[u]: if v not in preds: unlayered[v] = None return matching def recurse(v): """Recursively search backward through layers to find alternating paths. recursion returns true if found path, false otherwise """ if v in preds: L = preds[v] del preds[v] for u in L: if u in pred: pu = pred[u] del pred[u] if pu is unmatched or recurse(pu): matching[v] = u return True return False for v in unmatched: recurse(v) def _outer_distance_mod_n(ref, est, modulus=12): """Compute the absolute outer distance modulo n. Using this distance, d(11, 0) = 1 (modulo 12) Parameters ---------- ref : np.ndarray, shape=(n,) Array of reference values. est : np.ndarray, shape=(m,) Array of estimated values. modulus : int The modulus. 12 by default for octave equivalence. Returns ------- outer_distance : np.ndarray, shape=(n, m) The outer circular distance modulo n. """ ref_mod_n = np.mod(ref, modulus) est_mod_n = np.mod(est, modulus) abs_diff = np.abs(np.subtract.outer(ref_mod_n, est_mod_n)) return np.minimum(abs_diff, modulus - abs_diff) def match_events(ref, est, window, distance=None): """Compute a maximum matching between reference and estimated event times, subject to a window constraint. Given two lists of event times ``ref`` and ``est``, we seek the largest set of correspondences ``(ref[i], est[j])`` such that ``distance(ref[i], est[j]) <= window``, and each ``ref[i]`` and ``est[j]`` is matched at most once. This is useful for computing precision/recall metrics in beat tracking, onset detection, and segmentation. Parameters ---------- ref : np.ndarray, shape=(n,) Array of reference values est : np.ndarray, shape=(m,) Array of estimated values window : float > 0 Size of the window. distance : function function that computes the outer distance of ref and est. By default uses ``|ref[i] - est[j]|`` Returns ------- matching : list of tuples A list of matched reference and event numbers. ``matching[i] == (i, j)`` where ``ref[i]`` matches ``est[j]``. """ if distance is not None: # Compute the indices of feasible pairings hits = np.where(distance(ref, est) <= window) else: hits = _fast_hit_windows(ref, est, window) # Construct the graph input G = {} for ref_i, est_i in zip(*hits): if est_i not in G: G[est_i] = [] G[est_i].append(ref_i) # Compute the maximum matching matching = sorted(_bipartite_match(G).items()) return matching def _fast_hit_windows(ref, est, window): """Fast calculation of windowed hits for time events. Given two lists of event times ``ref`` and ``est``, and a tolerance window, computes a list of pairings ``(i, j)`` where ``|ref[i] - est[j]| <= window``. This is equivalent to, but more efficient than the following: >>> hit_ref, hit_est = np.where(np.abs(np.subtract.outer(ref, est)) ... <= window) Parameters ---------- ref : np.ndarray, shape=(n,) Array of reference values est : np.ndarray, shape=(m,) Array of estimated values window : float >= 0 Size of the tolerance window Returns ------- hit_ref : np.ndarray hit_est : np.ndarray indices such that ``|hit_ref[i] - hit_est[i]| <= window`` """ ref = np.asarray(ref) est = np.asarray(est) ref_idx = np.argsort(ref) ref_sorted = ref[ref_idx] left_idx = np.searchsorted(ref_sorted, est - window, side="left") right_idx = np.searchsorted(ref_sorted, est + window, side="right") hit_ref, hit_est = [], [] for j, (start, end) in enumerate(zip(left_idx, right_idx)): hit_ref.extend(ref_idx[start:end]) hit_est.extend([j] * (end - start)) return hit_ref, hit_est def validate_intervals(intervals): """Check that an (n, 2) interval ndarray is well-formed, and raises errors if not. Parameters ---------- intervals : np.ndarray, shape=(n, 2) Array of interval start/end locations. """ # Validate interval shape if intervals.ndim != 2 or intervals.shape[1] != 2: raise ValueError( "Intervals should be n-by-2 numpy ndarray, " "but shape={}".format(intervals.shape) ) # Make sure no times are negative if (intervals < 0).any(): raise ValueError("Negative interval times found") # Make sure all intervals have strictly positive duration if (intervals[:, 1] <= intervals[:, 0]).any(): raise ValueError("All interval durations must be strictly positive") def validate_events(events, max_time=30000.0): """Check that a 1-d event location ndarray is well-formed, and raises errors if not. Parameters ---------- events : np.ndarray, shape=(n,) Array of event times max_time : float If an event is found above this time, a ValueError will be raised. (Default value = 30000.) """ # Make sure no event times are huge if (events > max_time).any(): raise ValueError( "An event at time {} was found which is greater than " "the maximum allowable time of max_time = {} (did you" " supply event times in " "seconds?)".format(events.max(), max_time) ) # Make sure event locations are 1-d np ndarrays if events.ndim != 1: raise ValueError( "Event times should be 1-d numpy ndarray, " "but shape={}".format(events.shape) ) # Make sure event times are increasing if (np.diff(events) < 0).any(): raise ValueError("Events should be in increasing order.") def validate_frequencies(frequencies, max_freq, min_freq, allow_negatives=False): """Check that a 1-d frequency ndarray is well-formed, and raises errors if not. Parameters ---------- frequencies : np.ndarray, shape=(n,) Array of frequency values max_freq : float If a frequency is found above this pitch, a ValueError will be raised. (Default value = 5000.) min_freq : float If a frequency is found below this pitch, a ValueError will be raised. (Default value = 20.) allow_negatives : bool Whether or not to allow negative frequency values. """ # If flag is true, map frequencies to their absolute value. if allow_negatives: frequencies = np.abs(frequencies) # Make sure no frequency values are huge if (np.abs(frequencies) > max_freq).any(): raise ValueError( "A frequency of {} was found which is greater than " "the maximum allowable value of max_freq = {} (did " "you supply frequency values in " "Hz?)".format(frequencies.max(), max_freq) ) # Make sure no frequency values are tiny if (np.abs(frequencies) < min_freq).any(): raise ValueError( "A frequency of {} was found which is less than the " "minimum allowable value of min_freq = {} (did you " "supply frequency values in " "Hz?)".format(frequencies.min(), min_freq) ) # Make sure frequency values are 1-d np ndarrays if frequencies.ndim != 1: raise ValueError( "Frequencies should be 1-d numpy ndarray, " "but shape={}".format(frequencies.shape) ) def has_kwargs(function): r"""Determine whether a function has \*\*kwargs. Parameters ---------- function : callable The function to test Returns ------- True if function accepts arbitrary keyword arguments. False otherwise. """ sig = inspect.signature(function) for param in list(sig.parameters.values()): if param.kind == param.VAR_KEYWORD: return True return False def filter_kwargs(_function, *args, **kwargs): r"""Given a function and args and keyword args to pass to it, call the function but using only the keyword arguments which it accepts. This is equivalent to redefining the function with an additional \*\*kwargs to accept slop keyword args. If the target function already accepts \*\*kwargs parameters, no filtering is performed. Parameters ---------- _function : callable Function to call. Can take in any number of args or kwargs *args **kwargs Arguments and keyword arguments to _function. """ if has_kwargs(_function): return _function(*args, **kwargs) # Get the list of function arguments func_code = _function.__code__ function_args = func_code.co_varnames[: func_code.co_argcount] # Construct a dict of those kwargs which appear in the function filtered_kwargs = {} for kwarg, value in list(kwargs.items()): if kwarg in function_args: filtered_kwargs[kwarg] = value # Call the function with the supplied args and the filtered kwarg dict return _function(*args, **filtered_kwargs) def intervals_to_durations(intervals): """Convert an array of n intervals to their n durations. Parameters ---------- intervals : np.ndarray, shape=(n, 2) An array of time intervals, as returned by :func:`mir_eval.io.load_intervals()`. The ``i`` th interval spans time ``intervals[i, 0]`` to ``intervals[i, 1]``. Returns ------- durations : np.ndarray, shape=(n,) Array of the duration of each interval. """ validate_intervals(intervals) return np.abs(np.diff(intervals, axis=-1)).flatten() def hz_to_midi(freqs): """Convert Hz to MIDI numbers Parameters ---------- freqs : number or ndarray Frequency/frequencies in Hz Returns ------- midi : number or ndarray MIDI note numbers corresponding to input frequencies. Note that these may be fractional. """ return 12.0 * (np.log2(freqs) - np.log2(440.0)) + 69.0 def midi_to_hz(midi): """Convert MIDI numbers to Hz Parameters ---------- midi : number or ndarray MIDI notes Returns ------- freqs : number or ndarray Frequency/frequencies in Hz corresponding to `midi` """ return 440.0 * (2.0 ** ((midi - 69.0) / 12.0)) def deprecated(*, version, version_removed): """Mark a function as deprecated. Using the decorated (old) function will result in a warning. """ def __wrapper(func, *args, **kwargs): """Warn the user, and then proceed.""" warnings.warn( f"{func.__module__}.{func.__name__}\n\tDeprecated as of mir_eval version {version}." f"\n\tIt will be removed in mir_eval version {version_removed}.", category=FutureWarning, stacklevel=3, # Would be 2, but the decorator adds a level ) return func(*args, **kwargs) return decorator(__wrapper) mir_eval-0.8.2/setup.cfg000066400000000000000000000033311475740344600151560ustar00rootroot00000000000000[tool:pytest] addopts = --cov-report term-missing --cov mir_eval --cov-report=xml --mpl --mpl-baseline-path=baseline_images/test_display [coverage:report] show_missing = True [coverage:run] omit = mir_eval/separation.py [pydocstyle] # convention = numpy # Below is equivalent to numpy convention + D400 and D205 ignore = D107,D203,D205,D212,D213,D400,D402,D413,D415,D416,D417 [flake8] count = True statistics = True show_source = True select = E9, F63, F7, F82 [metadata] name = mir_eval version = attr: mir_eval.__version__ description = Common metrics for common audio/music processing tasks. author = Colin Raffel author_email = craffel@gmail.com url = https://github.com/mir-evaluation/mir_eval long_description = file: README.rst long_description_content_type = text/x-rst; charset=UTF-8 license = MIT python_requires = ">=3.7" classifiers = License :: OSI Approved :: MIT License Programming Language :: Python Development Status :: 5 - Production/Stable Intended Audience :: Developers Topic :: Multimedia :: Sound/Audio :: Analysis Programming Language :: Python :: 3 Programming Language :: Python :: 3.7 Programming Language :: Python :: 3.8 Programming Language :: Python :: 3.9 Programming Language :: Python :: 3.10 Programming Language :: Python :: 3.11 Programming Language :: Python :: 3.12 Programming Language :: Python :: 3.13 [options] packages = find: keywords = audio music mir dsp install_requires = numpy >= 1.15.4 scipy >= 1.4.0 decorator [options.extras_require] display = matplotlib >= 3.3.0 docs = numpydoc sphinx_rtd_theme matplotlib >= 3.3.0 tests = matplotlib >= 3.3.0 pytest pytest-cov pytest-mpl mir_eval-0.8.2/setup.py000066400000000000000000000001051475740344600150430ustar00rootroot00000000000000from setuptools import setup if __name__ == "__main__": setup() mir_eval-0.8.2/tests/000077500000000000000000000000001475740344600144775ustar00rootroot00000000000000mir_eval-0.8.2/tests/baseline_images/000077500000000000000000000000001475740344600176065ustar00rootroot00000000000000mir_eval-0.8.2/tests/baseline_images/test_display/000077500000000000000000000000001475740344600223125ustar00rootroot00000000000000mir_eval-0.8.2/tests/baseline_images/test_display/test_display_events.png000066400000000000000000000220031475740344600271050ustar00rootroot00000000000000PNG  IHDR5 pHYsaa?i#IDATx{u0̀ "*EIP6;h5;lyT|x˰aj=FM5Ғo߾vm gLVfm>Kmv£Iήy_Vk]]&]|s߼o^ϝYkε͛Ç/=^"|ڷo߾ GS%:w]Yk5Mo<=߷ DdM}zjl$YXm}mHs֤o4iag%IC߾g?okYjۆ}WkGWפkIW~6\W{];3d{u?]J~VO|LFk`)MuY`AzT $}:>bHϞY,??=*+{ `',}/H*7|g׽WչP___*jmrygcEP$$IrFu`*ˋY]Yy|®ޫ\Kݻw N-$y~Ǔ3| 3bİ4ԯ :* $*l:%=V]ic5~:W:>y…gy&F*ÞWF@ESmꛞW^+zTSI]WYin\uf{u?] zJϞ=f…innHbH7GVεPV? nw#|#.@(̭ޚqם٬ ܰG]@X,\h<2dHƍAǃj/^g%'`6a„9餓2p}cO9N>}2xL4)/r裏 '9s椮!⋳fW^aӟt~f̘vmˮikë!wیӻOKƍ'Xin)cǎMsss=yy .̩78lAvu̘1c-^?+Ѷp-mQ%gwަkꫯNCCC~}߽K'dO~6;C~[o_tAI.,w^ ~<_$IW2}\qyG3eʔq{ש Zfj;o璳Nmr1,9oĉΝwܞ]r?׿ε^ٳgSToOJm{m+9.\;}[lE.ҞVv~L;%>|x|liiiI}}}Z[[kmo~+wuWvm$fm?w{.y睗;yiv֝qsmsgܜ??rH=܎+agt<]8?|$9Sr뭷f6mZ/ Ǝg~XqG?sagꩧfyꩧr{r%IK r'eʔ)T*?~|͛x }QG꺷;쳳^{e7! Sptr~9#s%d̘1ys]weG?5J%`=2u9d}͂ 2bĈ~+_= ܚ . ӿN򗿼uu&L믿>_Wso߾cKΟ>}zO /dvk@:>of䆟tiəxȟB/w÷8;w/TpGr7},,_~SV⋳kݲGO$~hҫW5*ӧOO|$ɘ}M]}C&Ld'LN8!'O 24W]z>}gҒ7#G}eђ9\}eƌI^x!{Z޷Ѡp_yVfk~]iO$.u†G݊/3k7gyfn\3{ͬqh\yr-dyꩧ|̤I2gΜ;J%Æ O~ }yS![9$rJ̛7oInikkˇHvy李u|mo2{466vayVf].nkG.^˥^+Kl6bX|ͫ1cdرIM7tڍ6(I2}ښ_~vayI/~z. |_|sMz笳W\ٳg`zs=cq=#'~4CI>}ҫW,XcokңG|g.i&ӧOO3cƌ>~xga=Xϟ޻j%Ip3&sN>Of֬Yg}rfܸqoI>/oŒ$;wӮ|ϳ>^E;t?3gSO=-wPj駟ܼ3+ҞIG+#RI]7z kVS|7|s6Қwi;Çϳ>o9կ^{7NgϞ|]WW |G:%rJLՀ{eرcF׿uz{gܝM6nϞm{9昼۷oW::.'xbN<'Nzg=Xw>%'~ey޼iKL>#^*KಷLFo_rZ[[se-st/FFFFF@,V}UJ @HRդ8i_\QmmŽ>4,Gzwik럞 +J{ѥJeaW;f3^g׽Wչ_[[[ΝgIR͐ygӣnqV$[oj*KC[ʚϫMIj>autu?^W ohrιiG%upӲ ӫq%R;f{ޫw]^OWzCϞ== ^MҼ8ў\/OSsʚOsSؼzwv{u?]M ij$7o^^nũ,h[rًW}3ue,踝2o^k3?V}dkݾm+tjMK[V}vv?k{i{ۤm޼,ԭzھ}ڶm޼>we5mҕ7׵/h[}W̬r5Y^OWZMo~x%z3|Zts=aÆzkR_LKKKzDb޼y>|x{۷oݶ>|l[9jW^y%CMeSkG+C߾}?k[-q|:Я_ZPSef/@ @aZԔ>;MMMep|cKߺ^M  @a @a @a @a`7w#G9;sZ-.|HKKK <0O ՍVt|?|u71o~];|#d…9sfgeNg}hGd 7$|#[tM;vl>OeРA3fLzn3~yy'$sh'~w.;rM7ΰaj=N9sfΝw9 ihh=ܓMCCCk=2dHveNfm֋7(%ԩSsCoI&eʔ)壹I,Z(tPyqͣw_ΝM6d}ͳ>O>9ni[cLCCz}ݤ1;seN;2nܸM}j?p 뮻2rZԭk#<俱c#-=O>dFQW[[[zX~9rdZ[[Ypa&y+?WU P둺ͤI2{ekSnxk1I'I&eرmrUWeΜ99ck=;(?Ҳч~W^5n͵,z 6  X/^8eʔ7.ӦMA|0W]uUZ->&l.?p.s1K^}֣5T/~jSSSu뭷^uƯ7/~&TmY3Ψ.X֣uw?oGuTZ(>Zmjj?Vv|< oZZVuݺ10s|^b-vءz7n`Q]Zk # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # oz}IENDB`mir_eval-0.8.2/tests/baseline_images/test_display/test_display_hierarchy_label.png000066400000000000000000000311001475740344600307140ustar00rootroot00000000000000PNG  IHDR5 pHYsaa?i1IDATx{tTա$&1 !KPTPj"k (jR+Z/E[eDւ<("//AJ&3$a1 9gy>8ֈ3E 2@P,C 2@P,C 2@P,C 2@P,C 2@P,C 2@P,C 2@P,C 2@P,C 2@P,C 2@P,C 2@P,C 2@P,C 2@P,C 2@$МUWWJMM1ԃ8*--Uvv\ (aj߾FPOBjjo o8 `0@ 9ۈx=)436|',F 2CQeeLG)JHH5~?***RYY(1)))IYYYjѢ($ QV]]ݻw+>>^jѢUMqUTT/ݻյkWk?D(DYEEd:Niٲ^ݫ %&&tʡ`+Sw{bv,C3ɓo?WVԳgO)77ׅpСC5o}hĉoW=f͚+))Ig}O>Q\ڵ+vu]v)%%E^xVXaj7@<奙N@DJJRRRh"Bݣ>ÇkӦM޽ _8q>IҘ1c"?rM+Vƍ5p@ 2Ds}lEsj޼yJOO_I&飏>qgO:K&LО={t뭷j:u}0r={z衮]jʔ)ԩ^(=(ކ_UXX^ziܹۜwyn׮$G5 %IGՃ>s9GJIIYt4Hbb*7{ァ#GG\z#}+$?^{1^Z6mR=TQQݱs9GGmW^#GnP=={4]@z/uM7iԨQ:󔚚>@SNu]ҥ.\!ChɑA%%%E?5}tڵKpX@@G֤IӧOרQԷo_eddh„ q!`047Ҥ\Qڽ{:vDqb҉~Ǯ^` e(|e]f:"k|p߾}UTTTk_םwީ@*谲hB5ƶmۦkҤI馛 %pOÇuK/գ>j:/6l?)ʧ7i$oڵk0H` +zJ/V׮]M k M4j(=8p8|Q^ÿntȑ:|-Zy5Vb]߿n6rߒqj۶~.r}26XYG!qgϞ=#駟֖-[4oz)Iھ}VXu .$ 5ޜj*m޼Y$=SZh?; `B!B`0(ۃ97%7`T88VuuudБ#GԦMo'ԙZ(+>>u `(??e˔dI?.effȑ#G9DZêu}i~ &UVz5vX}WRyyUZZ_YYY$oVyyʔ/򤥥չo者uǶi3 `L8Qr0T ЀiϢf\WJJh̹*!!}wءJ=ӑ"oJRSS(S*++k.['DՔ)S3<^9ղeKׯ17PE^{p<+k m?1(ٶQ0G}Tc]v3 PnnnF=֭8%K믏vxeffJN?tK]t ͝;W? 'p+uճgO-\tP{ڳg~8x|>_q+k \W]n:;8^kyb{cy-_ټ :@P,C 2@P,C;v:u$ϧ@ !Chʕoٳg.bkԩ:[o{MGpڵk?s5j(eS_}.]{F;&==='qut:#Ix<Dk׮x<ڶm(QgelݺgyFGuÇ J,ϪJ}ѫ;wj۶mz駕k:k;jÆ zHvz3gk $eeeiƌ1c(QcSzBBPr0$aaSসD ZSγsotrΖ<αS~~~ ())@"Peee6lJJJM1u[{I ڛNNpjչfF  au)||ƽ^^Dr c%Vyn>>74M X` e(X` e-#GiF G}d:-4h H+WTBBl:.>Oԏ~#M0A_|a:k.;rϟ.]M6&tx H=,euӹ˴i&mڴI5`]}ڻwhz099Y]t\ݻkʔ)x<7|c: k^ B:x$믿֌3t 2p2X].],IRjjwUppܹ;wQk,c `cB!B`0(I æbh:{l׺\3M#FOq!<_` $ UVVaÆD~t#( P ` Pqq{PA{w)Mt- *##S j{^y^w6Z]6%vnFxe(X` e(X` {ァx 4tΙ3Gcǎ՚5ko>q\gu;]S6G5z;\n+ `(??]zh!Χz۫P WUU5Wʏ2@P,C 2@P,C 2={߿h"<+R3 =xeffJu+77Wyyyfxo]Z|v( ?M2EK.ڵkj:k(^}U՛oΝ;* -[4|pM0A{<(IjѢZnm8@ӳn|4eeeeE~nF\a}9rǩSXXh:+/5   "$)+7|+ 8R@Ɨ-[&>Ғ%KqYYYyqLh.Z *..7 ꖓVԶ%o`Զ`0 X{f|>|>_q+k Xm U` e(X` e(X` e.[,M>]׸qLGp_WZ|V^ 6L)--ռy`]q_|QنO?TpX}􉌥[nS8$9-;wڵk#c`P;w4 }־055U#FպukmVـ\pJ=<_` $ UVVaÆD~t#( P ` Pqqu-y8 D_0TFFzzjGq[flD 2@P,C 28;C[ѦMLGhr|q.]s窰P:uh(ٵkԷo_Q\C#Gj޼y$ǣ:hϞ=fCOԹsg=sZnMGpҔxeff ` e(X` qƍgG PHP(r9 JᰩX@Fݏ@,2 `(??e˔d 8S4~K,i `@YYyiRZ *..7 n{tWlh:)%VYy÷:~222TRRb||ƽ^^Dp[c:+8^kyb{cy-X/` e(X` e(X` e/hԩԩZl={X_k…9svw}WvN;4]z饦49 ѣG5m4͕$uIk֬ѬY( &Y]?c몫1^QQ?P*wY]%I/駟^:g".s|>ӽVTW/KUWWK.Q0{ァ1tD&guG}Tm۶UAA>SW^4ihz<{コ{MG ?6֯6D(R(\p8p8l*\wLGpkM:Rlu,qzS~~~ ())@"Peee6lJJJM1u[{5VN[ߖb{0̳Y}"ڂ222.<>zz5_*Osis<'c7X` e(X` e(ѿ7t P,Cѣ>|RRRw#8~xZJ-[B_t,W%`ʑ#G4{lKꪫ$IS 'p+vREErss#c[Vn pqvE^W~d믿?gkSRRtkjӦڵk~Xqqvb` k $=:r䈮ZPIIX?FƏo0x2V6T(R(\p8p8l*Voܻ{/agDqHC<_` $ UVVaÆD~t#( P ` Pqq$lmPsa\AeddX]y |>|>_q+k ѩ!Ti}j̶Nf{Ɖ0gh.8xu(X` e(X` e(VWW'P.]tg3 5ĉkKTTT۷ `ii?hƌ1b$sκK 'pOo۶MPHW\q(QculٲQguڵZl+W5V011Q&LЃ>-Z/_|[o7V@I]/XI0@ ӧ[nڼyOѣG W/"y<\ܹSUUUS` _r׮]o(/߯;vLpo>|G;vӱ\cu,,,̙3"+   "$)+U/>dr*;?A _k|ٲeJJJ2nSDw{K,8 eee#qzk0X~ߕmlBbC0TFFJJJ\;Xl'WkPone pM ֡X` e(X` e(XtR]r%JOOW6m4x`ڵt,X_=_֭ʕ+nAզ"tӆZٳնm[}1 =֯ڵKÆ SNձcGIҾ} 'p+C Q ?lUWW+''G_j۶m5k~H֬Yc8.ZR6ms)++KC=d:~ `\\^~e_^999/'|t,WY(IW^y>cJ>Wld `CB!B`0(I îlH 8OR@Ɨ-[$W9Odɒ@(++38 ꭮@ b~@}Aedd7+ j{^y^@CqM ֡X` e(X` e(X` e(I09sG  'u}molcc[,8*--Uvv|5+'!..N۷wu~?fmolcc[+Y{,F #olccl_[&˰` e(Xx zgձcG%&&wZzHM@^xRSSնm[]ڱcGی9RE]d(˫/Q^^ղeK_[n5y晵{wՐ!C-ǣEո> 4vXedd(99Y^{>(Eh&L=z(99Y>|8P1_ko(IT߲ѓO>Ms_F<ż+7n~amܸQ?OtWk߾}wyGs}-_\0`=Zv RQQQgɒ%s=ƾl޼9rԩS5m4͘1C֭SffwL77֭˗/$tM4=zz3fy}}sܸqz/k͚5:rhFhʴaM~zVNNNLyII<kϟ?_:s_ٮpK'>~cy~?s-^X~{bi~m`:XUUUj׮]vRqKuM7Cڽ{&O/\ׯovBX/:,}2e[F泮޻wMjѢE:|FբE jժmwyyz! 6L~?2~뭷cǎԖ-[4qD}ᇑ4'?tΛ7Okڈx :~D,}w3f>#Y7]pС/^\SW_=z(77W;wּy"/չ={jeggGbinOc泹y8-ܢj=5=ztsrrԵkW]pڰaz'os_I3gnV%&&OB222_:Tke9;v^uZJ۷?mԡCܹ3Jܓ=zhΝw\ݻW+V.>󙙙 }{&?vޭ˗XK^zcbο{Jիcǎ{bk~m@_~߯($tW(Ҷm۔y;_T۶mu5לv4޽{ָMQQl,X۹sVX6m}nݪp8s7ٳgwٳ6 ߀:ˎufϞ|θqdgϞ=IKKs OYY8SZZ<{޽Yj~N04xOq@3cT]]BF<V(CԽ{w1I_@ B(Ӿ@/roQCp 1:uJuuu"==]Nl(8V媩WYYY*((Pff(mG׫L*,,TfffʭcT[[O?Teee۷|&@Q[[zB!eeeَ+ UvlGjs8ƅ1\ cx 7^qwٳe^رc V@w 8Pͳ%%ڼQFiԨQc V۲⎶Dp 1@Pû@wq}ᇱeeeھ}:w /bDmo[]y啱ӦM$M0A/*yQ@̑hÇ1vkCp 1N+|ϗ_d j|%\F㯿w}R$033S vޭӧG7l)| ;c+ГO>i;/7n_B@v$_9=mڴIꫯ?/_}ڎ۷;O?뮻v*Un=fϞr 0@?Ouerk+++5vX >\~***|駶#xW5uT͜9S۶me]QF%'W/_*((ht}=_kΜ94iNIOSZJWiit &??ږZmٲE#Fh0>bmܸRdɥRuuu֭[nݺRS-DDb$)*I~<.IhT׫u^{<=^}}1FJOOop/$CCiiJJJ^ZYYY/H+V|?~\ ,Q+33S*++ӀbtjkkwѩS\WSS)"`1C$VC*++imSim둏-ɓ'u!}Pv\y RãqgС4h}XQQƌlpۓ'Oj B5+//OUUUΞYyw}c$=>1@PCp 1@w@8qDF?#G Vw]*ȇ>79r-Z`o ٥SN:r$)++K@reQMM9N:)==v6ym !NNTթS'g|%@@ڵѨ87P͘1C=D/==0 W^7ܹ4sfggO>c$"W#***edd(//R"9_W\c|`)~ x24TtpO#(.aIR4M%n[DMKiiJJJ^ZYYYY |!qZ"qAMM1vd `(Reerss-&Tڽe{a婪7+qѣGԩSٯpXyyyr `<ϓyƃD]I Pγs/trM Ρ8 c(8 c.2ez% tkڵoٿ.RuIf__(jժU؎ g }ݧ@ M6);;;6>`qɧO+Wߠ֩SćH' ~(co; @9Y1@ `9 @9Y@ ݻwێpNΝ;ӳ>'N4رc N@IzTWW!C藿ݫݻwgСCmӳgOmݺU?яC\ێg $h޼y7o( Srz0^HDH$v9KѨѨXSZ; Pγs/trΖᬊURRh|ҥʲīFƍSUUrssmDZVC*++=$Im'#Nж\3ϭ# sp<ϓyƃDmDI 6%Uyn>>7?M 8 c(8 c-'NT tE#G{|l#G\Zv2224zh۱|tS|tǏ_V>}ԥKq|a;Mo:t I:q o(-^ RM+۵}v7ш#4j(8pv48>}.>7? cɢX%%%Ɨ.], @jjj4n8UUU)77v+(qhj0 ҿ?ۚv-+//Sq휝D(qD"D"pX4k,yF7'm'پ|.w0*))i4o>A6z5k;FmG.`x[5 tajm{lD?.. *,,TUU/d `hp=zlGH?5ί#(.aIR4U4 >ҍxm(UYJNy:~S~X%%%Ɨ.], @jjj4n8UUU)77v+(qhj0 W~;KOagDa9]y 85`P`B ~-wN'0̳]~"8vxs(8 c(8ÇԩSm 1@8]O8ǫC*((O~ۑ|t>}֭[^{MWe۱|a;-Ǐׂ K/k$-YDݻw _ή۷O:thlsׯTsclGاOA{GTs5:tФI4}tuEݺu̙3l'pJٳuq3F999z衇TUUe;.:ts?M>b"|'c^W$Q$]Òh4h4j+VR[.;'z{dk.~?h;Ry(V\\FK.UVVD ^5557nk;84 TYY$IEūsbq&E8V^^y}<]xя~d;o.GyD/ΝaÆ\|XqVWWg?͛ &HzaÆYN޽{"jQؾ}{طo_o^k׮ a~ `v4c ?233u饗O?ծ]4i$|t{LÇ@sXqi̙9s( k\ `<""Hr8$EQEQ[MiWKu.CC5΄9CƘ:X%%%Ɨ.], @jjj4n8UUU)77v+(qhj0 M@Eū%t{p8< Os 2D2en۱|t\~}ϟo/@90k^W$Q$]Òh4h4j+V#^zbɤ-;gyR4_z,$jڬ!ފ+AAMM _|lMB!UVV*77חm>;! !+//OUUU:Vy77o /)w_BWjp}s3hʔ)Svvƌ?8{|gh43f袋.Rvv 5~x>|c >ќz ޓ96Mr ٳcIEc6W_ԩS5sLm۶M]vFڎv~mzf:uJ#FЉ'nȑ*//XRs7`cǎufҜ9s4o|MUW]`,Y_` Ֆ-[4bĈ#Fƍ-OUU$s ׯ_].9rFVw^gϞ[GITQQ`=W\s][[_;b4_֜ܲeh(%漪J@@:uj0/+//O ]|~'Z|&MT_d?T]]u`[nM6MÆ SQQQl|ԨQգGUW]-[$ݧ_^z%}'|zJ\rvϦ6ⶪ_W:v&NKgEE233uy5M~p|Myg]*ms3??_:z&DQʴf͚M4h`JWT_IzwgϞ>K5.!`06ڹsgRw^ҥYk.Eє6-X@zT_'X| +`0h,X`}3uTmo;9{MǎMyyy짦cLuuy衇ƍMYYYn:t L8>~=Y~裏{gFmrrrbsO;e˖;v3Iՙ /̘1x*muuٶmٶmd̙cm{ks{1ݻw7oٺuꪫͩSl:FQ3fӽ{w}ϑHċ~hJJJ͛MYYY|߿ַt7U*eϟ6h=쳦G&33 4Ǥ$3IM,ZcLMM1b9M04^x0a9x-t- Maaͮ]bכ_nva1[jd`<vݺuM&L04o>?s3ydӹsgӾ}{3z6op-++uc9xMΝMffݻyg}fwǾƙoi?i߾9vX'168 c(8 c(8 c(8 c(8 c(8 c(8 c(8 cd$hIENDB`mir_eval-0.8.2/tests/baseline_images/test_display/test_display_labeled_events.png000066400000000000000000000220641475740344600305640ustar00rootroot00000000000000PNG  IHDR5 pHYsaa?i#IDATxyygXfDP@d$,BT-D1. QkK\0\h*`Irx\VDPE À30Dfaw~91{߼wνޒ,˲ K$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$F$MXxqGIII eYTVVF=U4_ [aQQQ@,\0z[<">uرٮwU8'#"OcKo35l%QG}uZ:6״bŊX<⿕h۾;vllS6Zְb_GQk(i)ZSʻo7@ @b @b @b @bPČ3bɒ%Q[[şmݺuTTTmfoJJJsqGSOŲe"˲/߿p{${>lTVVm۶~\P멩~:/^\mm۶ѧO8C oV̞=;VZk۶m7>yC1cƌxt?ҥKyѡC4aϟs̉իWڵ>8z&kw}7fΜ+W{ƁXP߆XzuL>=>è[y#N:8aa*Q~ӟ_|I.׵kט8qbfF[nhϏI&E֭pMP[[]vY_K_Ry}N8|I1"NňݜbСh4iR\wu1eʔ>|.\vZÿۿ3gwK,zʕ+cڴi^{I'>l;/SO=5^|V\ӧO/N9xꩧr2:XxqӘ7o^|ߏg1zcȐ!G?˖-PSSK.z(2dH㷹]69wuW{[Geee<ѧO6lX̞=;יb„ 1~W^O?sofp qwDž^ȅ%ɖ/_ED|fު5YYU.0`@vꩧfuuu=w[CN;IkȲ,0aBVVV/dgolu^:իW6r^eƌYDd=X:0`@vgn[T:kfnc555N;9Fݬ4+;3{/Twٷ&_qve+WQ7mpwf%%%ٛo٤׳ޭu[?ED6cƌzkY޽ .`[`i͚5Y׮]QF5nuه~eٶ{.&^,2Nk1bĈ&QRR~z̜93>m0a~xכ#FDuuuL6ykiӦEMMM1їacԩ`ƛ:ujt֭o??亞 īX۶mfk:ujx1`|!74o޼x뭷Oou1"V^+SNA5y_=3>ܷԩS^B{<"s̉K61wĈQ[[[[)Efٲe~VMn>Yfj-aȐ!q{ְtf( jsl=u=[=">&˗/5k4Xt/?˲ sQRR/RD|6e6>/AsO0UUU1z5kV<ѪU8 s=ѦMx[o[n%~_=V?StM ^yxb]w{&3fLGy${챘6mZ̙3'k+Ls΍+"<̘>}zޣ5ȤIn={ƒ%Kt~=:yo~?x̘1`NPsOo>я~7pC">ۇ))N{F{nWboƚ5kCYN:(P>ih<0Ç;GQWWGKRv~w]_YYY#%ghSkӣgKJJjW ` lٲxWk>:kN5fΜsς:ECѮ]x'e/ڶm_q{」,,X֜۷om6?ފ+b޼y9N ` ;G.]oݻǂ ~c5… c1rxg?YQmYꪫ4?cܹqy=^t!;3fLt%vu;vlO]++"bbŊxgCd)//>;ƌ;wnݺŸqUVMd ` ҪUx衇K/ƀ[o!C=ZuYz8Cu1jԨѦMXxqt=.袼jDZr7}c?>u'N7|3vi8k{d|qEŰaâcǎqUW… cv{4Hla9xW6^1[gN2%AQVbر1vؼGj:t__rƌDWRR^zi\zyd_~yQ<_WUU__4m3}>*RonѡC(x -‹/>`̟??^x83""Oy2ڵkW^{.g)x^`xע4<1c48⨣*l'Xd$5[wټvo kԆkjӦwڂZ֞s66: \[7ӠO~\ۍ]G!\ݾĪU2ŰoȬ wiul.]ej5+KD4 ,(,Zhy\׳ce;um/K_`Atҥ c}?o6Tֱp^HG_d#^%h^z^{w_?;iիW|_n""(+++# eeeq}5V_1tm0Y :4>xǚtO?4?#TTT{XMMM-ZԠϻ^jUW}p.41֭[1'+.BW^yewyqyE] U5kܹs[o?oi?$8XhQ<1a„5jToֲ|OZnӷo+u?veFww!C4h>}dMgn~ӟf]ti|̘1~ސ,X s}lYNve_|qf_϶z.&^,R_|q\x1sxw_M6QQQʅK.#Gs=/w %%%ѵk8s{E`KZj?Ob3ҥKWYYY?XpбcxGcҥ1sXbE)--~_0i4_W b =z?hѢ3gNTUU}g .,.xbɒ%nVZgiWTTČ3b…1gΜ-dΎ;tPs;L0;sw> KKKhsJJJk1cij>F\RR;wGs0 "֦M|xc48ꨣ8 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1meY+Vh]U6WŷZ6ԒRR(# >:-ekZy)|Qa}A @b @b @b @b MSOãGQRR>h#W'N>8ˣ[nqI'kXl`ʔ)~?yA}c&N%%%q= uuEIIFvm**&?&O(lbq%̙3kqUUUy_3_%fϞgώq'ܹsM̚5+noM>dɒ^~G**> &:th :41،Sn]wݺu9sGTlh}}7Ɣ)Sb̙>4ZreqqwĄ Miƫ~[+-_<"":w$lNmmmկ~g}vL>] e]=Xyfl Ҿ }=Gq!5jT7z*z8l4tP̚5+&Mv[Γ1gΜ\xꩧbQ]][qB6վ}w}c޼yyR4 0YŨQGiӦE޽Ȳ,8?wD_ꫯ:^}׾(EC$+W7xcoVKѹsc=rK.$x(//{/"":uڵy:"":thTTTDeee?lK.-W^ye >g}v}9MEg'2dF߿뮻s9~|ߎ%KDNbSƱhP-Z~z,]4ve8Cc̙ѫWG+%Yey<?eohIENDB`mir_eval-0.8.2/tests/baseline_images/test_display/test_display_labeled_intervals.png000066400000000000000000000174721475740344600312760ustar00rootroot00000000000000PNG  IHDR5 pHYsaa?iIDATx}U}TXYR+5P" ƨAQ&LZMƇqv"3Ҫ J"icp1Q `!PA@T`Ee#?nY@Xyfvf{YK("HC'@@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$өhofDTt("vѡCkax7>M6E~*=@MMMD޽{gDCCCՕg$?}ov]@Ƿr HF$#@d @2 HF$#tho}c?vÙo?$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#IӦMRgn6GTЬZGܹs}ݱuJOU qE>}⮻TZUرc|ߎ/^JOդ /~q9ĝwYqw_TZE袋s\~핞 @T fϞsN :S8_8cԩq}Uz*ǝo64o? 0 >֟ @+s W?hll,nhhhjj:W%}<BKeGF ?b1k֬yڵkf]vŔ)Sbѽ{JO"Q8زe wY dmʟ;72S-=-9vm2-9NGfX6{N> Q]]}xUUUTUUU`FqOS8ps TKAK][8LKӑ7MgVO~  HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @25pԏ;k_Z;vlxGkllNJ+>..~L^hqo??~}cǎX󨯯aÆEnSNq?_:o--f͚xg/믿>i]v=̛7/F_hѢf,Z(~_9Y&-[o~6SNK+rThk: :47tS,_=ѳgx'STt5عsg̟??rJ̜93S~܁oJx衇_bt5 O:uj̜93̙u|8䓣s1gΜXpaݻ6gyflذG ;du]X׮]cРAgqF 80N>fca_ʟw-jjjʏy#"sm6lӧOsFMMM̝;7O,.(JۣGu5{;/իWs=^zi\uU͵K.k׮ .JۻwQ?Ͼ"u8""zqƵteݺu /!Cļyn+oU+۶m4~gРAѽ{xy%K9~/,_< ;v*"]6=ܣ4@aݺu+ĽGn-֟L1nܸXlQ=nӦMqM7ū?n!""v~{,_<6n+Wӧ믿W^yeYti?ӈ#NQFܹs#"bkUdB__j|;߉Z\s5\;v3guǎWU̟??lz|3t>|x9+oW\qq/Eߴibڴi룾;7j|3όG}4="-/`׹sxǎp,9cВcז9-ӒtmeS~A8e9>f͚u#UWWGuuAUUU}C84?\=plۇpصeC˴8i}c.#%/HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@dR T*ի+=V.pڴiQ*zK/4^|JO eFD\z饱yؼys?N:ĉ+=-kX]]}>}9rKlڴ)~ߔկ~cƌΝ;cɒ%0@+i{/~W^o}[q7ǪUb̘11iҤxw+8SO>'|r|QSSOOǜ9sb֭|RSh6y۷oDDİa'?I;66lgώ;VZ ޽{Wp_ ~8~ᏼQEDD\}խ4+Cw㥱1˷"")*5-8E}c>XsǠ%Ǯ-sZ%Hu9b{Q}}}̚5Gy$vZGk׮]1eʔؾ}{t޽өxu.lْ!z:|񪪪{_HG$#@d @2 HF$#@d:UzmYQP- O`ǎQWWWGkǎѣGJO"JEofDT:uuuiӦ޽1}}α9>爜(رcGF9OCѯ_ݻwo_Lǒ}#~<2w[Wə @d :ΨTZ}#~<2w}n@2$#@d {^uYѹs5jT,]S:fg>555qǟǫliӦETjqVhƟ\}}AӧOEQD}}}F.]bرK/UpR_}Duϸˢ6JRl\|Xpa|1~عsg.ؼys駟ЌÇ7۟5k֔wsO /D>}OOt[ /4 FDĕW^YަΝ;cȑq7?OclٲxbĉgϞڍv޵kW\2XreZi͛7(J/}vmiS)8\p׿fcÆ +n zw(}ص^[| _ܤ;S9r!ۻwoѧOb>ѣGOO4q 7 *[E[(~ӟodmmVTUU ,(oo:t(yV'q~/""7>7pqr}>׺%/|Kun\<޽;VXǏo6>~x*4kqꩧ6_dI~1tиwީuEmmmuY1yׯzٚWWWg?vw|+Q*mג]bE4555ۦ6FѮQ*gϞE޽co~_>ߎz*կt_{[S'ٲeKٳ'8fgqF[SEtM1bĈ +;K.$VX&:thww1f̘x饗z5߸qc%{\bĈ2dHr8Z{=ZߏSFΝunO|ݻwt|w͜93xXxq7 ֭k_ݺu>;֭[Wm7nE]{[疬m>}bݱu֏ܦjjj*֯_ .lvP;Hj7ܞzҥꫯk_{EQlmbƌũZtҥ8q ׯȯŋEQZqEzjqI' */xw+cq}nHwQrH $u]g=3|93f!Xb,`1@!X bC ,`1@!X bC ,`1@!X bC ,`1@!X bC ,`1@!X bC ,`1@!X bC ,`1@!X bC/ pg/fv9 Ѕ .k #ނQfnɓ'U~}0K 0Pp[\@X[ּ `a@!X XaS~~٥xzzҟ rrrlKAQXXUfv)`I:v<==jժqƨ 0 C999u1Xa!,)''G ըQC:~rrrTzuKtKP~-[bXuwzjӦ堂@1{ [3nR> Zt$9oby5uTլYD˘4i|}}u7w﮴4j…?#G#Gt]waÆ rrrnG v~֭O?%KԬY3U^]?5ͦ;vl6%I?ﯚ5k*88X=RSSkڴi W&MJ/QF)779{EDDn+&&F-rw֭\eUKfô?|TGڵk-IZ`&Mym۶ڵk.___=JKKS׮]ս{w=Svvuw/^~eu]{q>Py кudFmذAaaaڰa>M6>|$iȐ!9su:v3॥{5k,]tI&Lc=?܄-իWO|$i֬Y)SW^Q>}$I5w}_]O|X./_֑#G-[tzkѢ<==aaaڻw$iԽ{6lP*G! nWђ9s(>>^'Oѣ%rowsuVAAڷo~kkvYry ͦI|sGq ԫW/͘1kaaaET&MR=SO^z:z\ڵӊ+TN{lRڸq?Hyy]wPtE-ZԩSiӦ<{jɒ%e C=M6رcڸq~i}ejz'4tP\RǎSJJ}]IҨQtY 8P۶mѣG駟jС/݆$ UƸq`ZpղeK{JNNVFG_|4h>}Yf:t.]T왽w$O#GTll,IRxxl٢|O?@& 0.]eff*00P7}ڻx ˗/رcjԨWnv9(c_S޿+b3,`1@!X bC d]*Pk7M|ugBB.]Zڵkcjرζ(uc.޽,YfojY5jP5ʢ, ._%55U6Mw6eSfMIRbb4h ݮp$K.:~yl6l6I/'&&M6Zx4h ???=S̙3:uOKMfR˖-뫈9R/^$跿222NLL$ի'___~JII) hqSN駟VttWuꮻ7eggWh-JKKS\\\kzu!\R-[$}_?*--Miii]Α#GKk׮;Cŋ7jƌzuVg͙3G|.]?\%I;w֫纟}YIo[mٲE˗/מ={裏{:tP9n)k3ѣGuw*((HSNU˖-j W޽+OOOVYWKۄ PuUjР:v(IU<==-^Xj޼uYFjڴf̘qFiʔ)zꩧ4|UVMl.>ry} $=Zv,YS5L=8rHyyy믿c=f͚e˖۷>cի~WNU^ZM6맬,-]TYƌ|gzK:tp ӧs .{nQFGեKԸqc >\~JH;֭͛å 6׿ի' 2DgΜQVVu׳sN&MqF9rudL;x}駚:u|}}gyl͙3G˗/ׅ ԧOGAAAZf=}ꮻR%)SiӦ:}y%$$h͚5>^ʒ תUKкugiȑ7ۻ˿v^Vd[AA$z4bM2Ej͛5l0^w=Ԏ;ڵg8QvL ajڴK{HH._,I5jf̘0vEnn%Iׯ|MOsްa3:ٿqƚ3g:v쨋/r5jwݻFXݻWڵSj\ZyyyzWg }]yZw۶mӧO.P4s,۶mSAA,!I6|||O4tddK]ݻwٳPy 5o޼L@yr8:uKV^|~ћo5jaÆ~_h )zsW^ڲe/jjݺ|||ԤI -ͦ7nX7|QiOMgee[n[o۷?˥aڵks]w)((H ,НwީVZi?`IG***Jk.zڴiYfiƌo]NΝ5b_k̙3%IK,ѐ!C4~x5mT{W_}2laf׷~`.]ԦM꫅$D\?^+WԎ;ԡC8qy@[zǵk.iFjԨsF233 &(>&,Vre;vL5R.ekw%c]W^^:t+Vh߾}:pz-߿aЉ'jȐ! Zj;w=UViʔ)e1 bjҮ]ԵkWM8Q[V4w\=΀'NҺj׮d{j޼O/e1 b%աCZ\%ઍK3*gW@@:U鏁, ;v())Ivy4/~y&aq,SF 3{En*77Waгf drss =`޳+1HL6M'O.駟ǧ<*BlfMX^^^ Յ xXp8t%} /;;ۤ*>X EPzze?C*??_GUڵCqjܸq3 g9X vޥ~EUfMC>>> 0 egg+==]5k,޳ $ Eܿ(,ͦ0թSooB}>>wm۶m#G襗^֭[DFl]k.e+9R6M۶mS~ԤIhBƍ֭[쓜 ^ZM6맬,-]TYƌ|gk/l6-\P<|||UVLej<{֮]QF׷AAAul͙3G˗/ڵk>}h͚5Zf|MzazǴg=3111lڷo_z{{Ll" JpgZjkB?L xWǎCҾ}4guI4qD 2JӟبQ#ܹSӟ4~xvj߾$Iiii:qɕT @闻|͛yzrrtBB\XlT+7\30*V8.s:33S/$5ϭ.V(u_o?1Tjegi}zr+|,CwōF(rRL]{6(:(ɓ'j_l|||LVvv  ])P[B4|{yIi;ecJTHH Knnj.@i!Eǝn7w+^qJ{67XbC ,`1@!X bC ,`1@!X *lڽ{٥JO:1cƨqƲ튈P^~ #""BiiiT$/ HMM՝wީ ͜9SZRnn>5JﯰZ<==Za0gG)ͦm۶_~jҤZhqi֭EINNVPPV^MGSVV.]HլYScƌQ~~[o:_4hN>|K L gϞڵk5j(z=((H.]9shZvRRRԧOYFk֬ћo7xCONNL?Zr;r!@c%Ç0 ;_XX \rss(IR~o꧟~7oxmذA$ :ٿqƚ3g:v쨋/ϯGP9 Ð$lb6mZ6gu*22%խ[]ݻwٳPy 5o.L#ͦ}˴f+JRn秷zK۷oׇ~(KVajU~k*l]WzzO[.gϟ|uQ?t!۷OsQN$I'NԐ!Cni= 4Pj4w\=zTVҔ)SbnبQ#ܹS?~_ZׯWRR$)--M'NԮ][zԼysM>]_bnf\:pbccu!EGGpL*##CP! ox*okq'n]l}Zr&I:}4hP!r vNo^Z`|l.ۻEx9Wy>BhK.9۶n=//O;vPlllE`)zpԩSsi޼yxz^SLL5kٳgܹs.7cW#<ѣGgQpڵ+66VtTI5c ڵKQQQ裏\n8r˳LKa]T``222`v9ekôm+X~.!Ӿ Jpp8333%I5ao6F%U@,iӦiɅ?SPQy*N5k* Xvv%BQg#""nM~vy*WV׎^oק24+]UIh|%۠J]*LX3,.^ۻЃQFl`ھ<軪k]xmS zu[ԍW J*ۥ=@,`1@!X bC ,`1@!X bC ,ƴ*ͦݻwUd]@+ VݵgϞZ-߿xEۊVppk.uY{֙3gGFF*11eY~G}5kճgOլYS_}F#Fɓ>JNNw}Z`fϞ]l5^Z~~~󓿿VZ+V㿫=zf͚)))IZh(,VZ3g6mCiӦ?M8QժUӖ-[}^|EuYիƏw}<P)y㕔$I:{ϟ=zh۶my:ubԡC۷ٶ~BmѢK[Ӟ ӧm^}U>|X/^T^^fn\*::Zر-Z,-X~6׽ _T[AA$i֭0`zիWk׮]zspo@&]tٶuVyyyڱcbcct[lQÆ /Ct\/;:uJt9͛7O/^T^kQf4{l;wNCu_J]3fP֭i&}G.7}9rDTC=gyFGV6m_꥗^er;)0$I|{xm3gj̙.mcǎup8w: Ӿ 29y֬Y-Z] @+vک^zŞ~9Kp8ә\oA2(e}k]xmS|\qe=JF+ w%UmeR-ٌ+aqC?zH~~~jٲkgk/'&&M6z7@ 0@.\(QT+ViӦjڴ~hɒ%2 C*ͦ>g֝wީ]v?!C7vܩh 2Ĺ9rD+WիzjmܸQӧO/ϡT E7${x֯_/IVӦM(&&F?]pAv}Q5iD&Lо}O?]wJNNV\\n=Teh۶m0`$Kŋ%IձcG~Zr^n]IR˖- >}뎌s:,, /3Wh"^z60sΩf͚EvnٮVPPpu_=>PUv0//O+hΟ?jذ~mJL Wֹs4l0ŹO-?Xm۶ͬ2EԵkWzo߾ڽ{~'8p@&TP5ٌ➕beff*00P 0}l:?/@]>r\KsuRq8r8LI̙3e* p?':3i˭X ӦMɓ 9rce'uС_.77LgK33ߞTzS]˺DQoEmp.e!33S|%cۋ+__߲_g6j5JԷ<,Vz//ӿ `1@!X bC ,`1@!X bC ,ƒ0!!A6MӧOwi_rl6IUT K@I^f̘sΙ] @lڵBCC5m4KP :uΝr*e$=#jӦ&Mdv)Pf̘K3 ax=?ov)*ӧM6jҤ٥;˟-[j;w٥;2e 0 rgKɅ6l˗/W|13c37pp8333%I-< ٌ-z( Exl|+DM-RN)Iڲe>3y>3mٲlҤ͛{j͊Tn?;겜M6[ne6+..NkV핔$IJKKӉ'L)w 3gãd_T2d]tI;vƌ|߯K*==]۴i&h¹P~e\׵A_w%$$%&&*11~Q{snT^=XB,vIثU^]| 3k,=sQ pg]7f7P^^^puzg*lf)]uօ\v^|p8\n̔3sss˭a3o<,ʱqm۵mV8J JۡdJn4ϕ61=W6(Rbb&O\}ٲec`l 4H 0SK3JOOچGGvtQmWUe%%vP2%N7J*VffBBB,+%nnj.k21l}&cڶj1^mPm%Styb+M (_@!X bC ,`1@!X bC ,ƒ055U6Mw6 W%`BBl6'88Xݻwמ={. tU2JRݕ4_^^^^ٳe@ݮPM60aN<9չsgU^]-ZPJJyT*vEۊVppk.uY{֙3gLUzjOZjVX!y۷5k$jѢE&V Plݻ{n}W֭zǏ;ԩw///uA3\ evW+00P ,ГO>y~6"0M=x-&]tٶuVyyyڱcbcc(T3CN$;wNŋիW/sVVZnyzIرcjڼy.^={*??Qjō;;;[;wK/;w>ջwB>eQMѾn|<۾јkZZ/^,ͦ}NR T*;v4Fk0uiCqFgO6wUg+رCݺusi֭K*_ZjN:jҤӧOQ^9tըQ# 0@G$;vLNrv]{o999z뭷4tPl6g{UW+ɾݱcrss] W\\\l ri-ZguU}_O5lذBU\Ux]+==][K{ݺuu)*?ahܸq뮻lѣ}Q5lPǎK/O;vp˧~&M觟~/Ν;ouע(\\RϟWBBkdߞ:uJժUS͚5 SU/_?4hVFoF'NG͍窾.]*ǥ窄X ]}D%(]V=Z{͛]=..N:tPÆ ;ѣ-[SNҥK|ѢEѣÝmUm?_۪sss5`h. >{\\bbbԡCܹSڵRoUe_/^XV]ګ~J\ӳпO>],3fVZ 6~ СCT]U˖-u!Uy?~\}|bj$644T999:wuqWzt1[_Qڵk'oo*=޴i8pÿqgwFDU:5n:u٤ʖa=z>}jԨ 9sF'OTXXXTXۧ0祑yNN6nXe%KTN=WsIm2OZZWߡCg)88}[V\U۫u7gf (( ooocѢEw}g;5RSS.Lػw1p@#,,m{|AƄ \ګ~pႱk.c׮]$c֬YƮ]wdߎ1¨_g;w4>uF^^YúƝkۨ_{nsaa>|ؘvu7l`a8q¸{ZjժU35Μ9cQܘKz<۾m5j0Ο?_;g+a)FT*|bC ,`1@!X bC ,`1@!X bC ,`1@!X bC ,`1@_qz2IENDB`mir_eval-0.8.2/tests/baseline_images/test_display/test_display_labeled_intervals_compare_common.png000066400000000000000000000426111475740344600343450ustar00rootroot00000000000000PNG  IHDR5 pHYsaa?iE;IDATx{\e(gTiYҺVfyڌ]{j۶BBB.K#l6պuk 0@Çׇ~|}ɒ%ԩ7n8-\bі-[?YE)))QÇWӦM[nEqɺ[5sLlR:tָ/PHHƏBgáUddl6bcc|M7$鮻Rnnn oUp=y#e6Jc/3߿_Vj$+>},X+B۶m}'???}QGyDWbbO?T>>>z駕yC5k(00PWaUvZEDDhڵڱs%?^qm?w$}8mrf?.taz*''G_>͝;WgϞԩSuw?v|@ZjkUW7T-X)N%%%ZF% KQQQ! @Я_?kƌJII̙3׿Uvء%K8?#XѣG+44Tr֭[O>C=~ǝmH>L&=@i݆S4~x8qB#GԦM~};v @1yd+h"eddK.땑v]t>SiFCUN4vX={3{:ByF I>ܠ*//OԲeKmذAźzHAAAKd1 pwn+((HN60P{Ν;]v~ 5̱UW-KQoO@l0 L`2@! d&C0 &`w:wάu%Nd-]L7ިUVU86**J&MҤImÇM7T:+##C&M{vP1 ())IK,qil&MI&5Q<@6M.?M6$M6ljٲ?J맃bbTpJJwŋM6׃>b͙3GjѢyΝ.]O7nΜ9#IԩS hF-hƜ=:tJaQ4D6|^ۛLeX4k,˗;Do͛^zI{եKI;C֭[rrrs۷Oj*ŋu7~'|ٳg'ƍc4|}7Zt>c$O>z;_ Izh/|uͺmٳpƍ5{lp O)SO߿Vڴi^zI5k&ooo(<<嗔h PΝݻwkʕRǎ5{leeeꫯ$kNO=|A-\P5RPP,Z8?}OBWC>Ғ%K4cƌ\i`w^͜9Ssqw9TKbb\ښ5k<=j߾tM7i[~TT-///G:]V3fw}'ݮ";wNyyy+w=_Fa芫; "UjFՙ6z{{kƌ5j?u. *SLLLf͚iZz>#7N>>Y*/¾ܶIuM7SO=f͚i{TXXx[~]^ kQ= `nMݻw] 5I&2dϟ,}ڱ[4jH5/REEEztWC駟\]T\\cnSej\:Ӟ,5{lp 2eK9L7|}}ꫯI&j۶_/~1bl6BCCkh^aos3g(J,&M^oM0YϤ~X}u"##k>a_~E˗/$رCݻwה)SϪn+((HNR```y#e6Jc].sj׮7nrḺU`E߿=JR.]4zh .SO=U3̔_(ֶm[;wc0STCnK +*xiUwSm Iaa PIIfƨ#K]~)))a*,,)j9sRSS˴)UreY(<<\OVAA1'Z.ٳg駟K^nCa\FFF*77Fnn\u+..ռys=p?~\ǎS˜ 5m`8X 6M6LjW,*zCYV5mT򒯯,U40 +77WM6-u]Uf=JPӂ[ Lb(""B-Z j-s&0T L`2@! d&C0 L`2@! dΖb] @q{>>/uwSNҥnvÇuwo_W /쟗ɓ'kZftmg~pff믿^e>Ӻk$IsM}}aÆiڵ:u$ow-ZSBBBmM ީW011Qiii~~~Є ڵqXX|}}᯴mӦMӓO>7*77yСC@`**)&&J}Vbqy^v+22RZl%$$f*֖ǏkΝz饗Էo_I\{/,X@o/kM6UHH^~eݻW&O\Cxzsssܮl2mٲE zPb"áƍk߿vԩS @M$n;#///ŹZE4}t={Zn}~CnK UXXXu{6%%%Eex "P]5j/3ͭwЋk#{c¶fc۠*Γ*۩>mfs6kv]\&Vjowzظc63SUUvP5UN)m3wg{A jd&C0 L`2@! d&C0 L`2@!L(=OR~iҤI^ڴi-[\r#>}6lPevA ,Ў;~zEEEi:v옳ѣn:ܹZx:(>>^'Oƍ픑`effcǎհaÔK***JM6ĉU\\w%`ŢEnbccb u-[LC q>oӦ^z%7NOָqh"g@"M0A O}R%Gp `pp$)99|͟?_˖-ӪUCjʕZr^}Uz+\ajjN}׺馛4zh8qBtI}7ٳddz-i֭ ֲeԪU+gKG_|ϟyiѢE宿@/ԭ[7zuU<\_P6m\ +B]w +==];w֠AkVd9R1111ci&IeZl?jĈ_tWɓ1b~GgH͛7O;vѣ5qD͛7eWƍ5o<^Z.}Zjʷ+7Μ9S]|}}|(=zvO1gϞ$5n';;[{4{.Aꫯbq>ݻr9:11Q۷og}$yejmҤ+TjuynXm+))rJǔ;y7o.Ik,U-O111W_Xkڴi>'Npr9/_EGG+00P}]gee~W6nܨXy{{_t]ap}7+W4ڳgvܩwޒiӦi̘1u_WkÇ5yd޽[? /衇$ƍuAmݺU{~q.Yn Pc|ԼysCiii:t-{4gyyU3FgϞU^':o@]viҥUHH*[Ne|:uꔆ V+/|. *z߿%''+99٥-%%E)))ߛԅ VZ7ȑ#+]e{ƍwީt9sգ>&MTE/lCݺu?\gp* .u֭MkfOmt?^vu5o޼Ɩ~pܸqX,ڴi :(>>^'Oƍ`effcǎհaÔK***JM6ĉU\\w%`ŢEnbccbŊڞ2[58qBVW`IRrrZ~~ϟe˖iժUСCrJ\R^~e֐;S_n&=Z'N);n {a_DDڴiVXX4]q4l0_^ܹ D]e'''kȑь3M6]+~0 I^̙3˴*::<,,LQQQwi;zhڵ󱟟*z066VE;wXbVRRRT656kL7x^|Ey_~8 x…*..V^K{Ν;5|[4m43͕4 n`vuV=32errrԼysCiii:t͕4 nү]`,XP.ϓҖ egg~'aaa*qپ\2/Z;Vv&х/w;]l}-t\Uy8=iT4QmIۥ6u= ,FyAQi7놊@ukԨQ:u][35nn,saORsEͫXivBCCM\ 6M6Lj-sCiXj&Ǔn7O+j^EJ{6_0 L`2@! d&C0 L`2@! d&C0yeX}vwPkE~'aaaaԉΨ]x|O>f͚uZxs̅dXfSӧv]^9sFbbblG5em۶M}ѐ!CtqQQQJIIqY~I~Ν 4HM6_|x@<>\aM?{9}رcktQL_Zb|Myyw&L߮N:)--MAAAJOOwP6kLWǎ5vXuQziӦQFڰaC=3չsgOg}sFgjCqJKK$8qB .i&g޽{S;wtYr]BdXX<GVX_׮]#""$IGU6m:ESO111=zPPP^y{gX*\j-ӿ*/ttuz@"///={ٶqF㢢"mٲEqqquY@á#GHN< ̙3풤Bao6G)5K@3g*55L~(___7TT&ʕu_5,??%FFF*77״!u߾kvyWλ^lT4>X7RmUUͯ*<}TUuYK=gjrl6l6[vZFԨ!1wMm_En߅.o6,%|*]nl~U̲۠]9޳L`2@! d&C0 L`2@! d&C0lY,m߾]%PppueX?!!!JJJ_][,Ç2j]LJJRNNrrrfhРAK֤IheԺZ 6M W5uT>|Xǎsٵkƍ+>>^YYY.399Yzf̘0+55UEEEzGլY3nZ/v7uTuAj߾|I:_00: 3g+&&F!!!G}TSLѶmԧO 2DǏwe}駟駟jܹJIIѠAԴiS}z1w}zW4o޼Z7@}S033SW@@VX7|S^^] tSNJKKSPPӝGGG+44e͚5ձcG;V;vT~~{1jڴijԨ6lOO>5eK>DIN8 jڴiO޽[z쩝;w:֬YSf.!2,,L ѣGmoyݻWgΜQQQkfV)&&F111իӕW^yq׭Vk嵕H6nܨ#FhԶm㏫f>E^^^:{mƍEEEڲejt6lP۶m㏫gϞktV/;9rDtI-X@gΜ}^|EƪSN7oN1VgWZEDD76oެzKs5kfϞnݺiݺuz\o>^Vr~aM0Aݻwg}'| j `FF222.zTT Ð$9,B;qsќ9s\&M|p8: -Zr] @z+RZYB|n%I.U55.o.wyضhL}`xQt=Uo2vxϖ,FuXT*%%Eex "P]5jN:e{35ڽcm;yymnl;Ovlnv:r l6l6[vZF@}bXK ^^nl;OvlnL`2@! d&C0 L`2@! d&C0 ɘ2fggbh.5, QRRkwv 2JRRRrrr5kG rwYn`fSxxս{wM:Uֱcǜ}vڥ>}qƊWVV # 6̙3zg>)Sh۶mӧ ǏR``ff﯀XBo; &oWN j``bbo߮۷/Ѐ4p@>>ٳvrꌏ -~~~q>ѣ+{8RM=x!"///={ٶqF㢢"mٲEqqq(43CG$-_\'|YfTt$%%%̙3Zf$jcǎusM7bccӧuUW;P4uTܹS?E[RR %$$o߾뮻hwޭM6iĈ$ >\/$jJvR^\u8,,LԥK2mG躣|Qaǝ+OOOWQQZjl3 CVU'OTӦMgZ-EJJJ.?@C3EEE{N۷ow|Wj۶^uwР-fffɓ{3l0T\\6m2t_AAAe^۵}vڽ{P!@d1*W *dSN)00cL.}|u0=޿m`P-`Op8p8v$P* <PMge̙JMM-Y5Ĺ>]W{,|Z;\~Ocjrl6l6[vZ~=/d&C0 L`2@! d&C0 Of$nPUۥfD O$EFFP]OVPPp a{JJJO?) @FmÇ+00F]_1gsY2缙9,sޞ6g0tilR^^4g/Zn] _ĜÌfay{Ҝz比9c/LXOl6M>]6ݥlf7s63یst| d8`2@! d… ծ];5nX=zкu]R9s*E[{n>ɲX,.?W_}*|)))e|0 e˖jҤo֍׌2X,?~?S q}-⾢jӍnݺZIIn̚5v9#((VG֍zȈ6JJJ hxY:We/j5-[?^^^ƪUq˳i&CqAg_osSUԩSf͚geeEС>=z՘={e˖j׮FK8#Gsͦ믿Ak;v,UenٲE.}ZlO:%Ţ`_]#nA[lȻ7wuA?~iG~sNHHPllz쩭[+R/ۥ e_/^XGVƍ]~nH\ۻ̿=Z,8qVXkתuP۶mgϞ:vK.ڳg y}e&LwyGڵkWǏÊ kΝ;4r>/(('|`%KԢE |kh*GZ.}rrr7x/ {G}J|*,,l0㹡k3=zPn*GsPPe˖VHOO7;cҤIjă>hYYYFNN'??0 8}1e>38`]ݻѪU+nK3e#++ؿqFcРAF@@sΚ5 2ycǎȑ#6mSNuio(ƶmیm۶s۶ms~۵*0Znm|G֭[n֭QTTiUyC 1Znml߾pa{5RSS͛70}#..θ++sUgOו߆aN2|}}2=q? zm52J[x:I,Y0 7 `4oܰZF6m8t{ Ç7""" jl:t:_/))1On6͸;vݻw7vr0۳g&L05kf4i4hP=_vaq!35kf4jȈ6?Ǐw*Pќz<{ھ6 x饗&MK񞸟bQP@! d&C0 L`2@! d&C0 L`2@! d&C0 L`2@! d&C0 L9HDM,IENDB`test_display_labeled_intervals_compare_noextend.png000066400000000000000000000254731475740344600346310ustar00rootroot00000000000000mir_eval-0.8.2/tests/baseline_images/test_displayPNG  IHDR5 pHYsaa?i*IDATx{tT@$P.B`F<4T*)?RmB\l rmkZE-AQD5($@ dIZ2=ͻ{qG0#@"!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! YEE>sEGGr{:ɓJNNVPka+%%СCj۶-PLLg|QTTqomߘcǷl `` ` ?0q;wN IppBBBL_m@Y*((Pqqz$5kS$***`%''Yf\1jQii=ӈ#Լyso=eee?̙duܹNwSRR5i$y)))svSNZl={hR֭Xǎjo_\vwżLкu*Iz5sL-ZHW\qvء &(22RcǎUAA WTT뮻NBBB#hڵk_}Uhrrrr.R$0Qo{=]!>up 0aϟ3ghƌk>vZEEE\gϞ$͟?_.Ij߾٣'|RcǎUbbBBBDIKz>{ŊSnn233%IZt'|ݯyZh6>R7 Q7mO~s%#@ZdtR}G2e=C;Ԅ <۟;wNx۶mhgjݻwj`֭{%I{__o[NNN~"HuQpBeddh֬Y}͍2}N>-IJNN֖-[T^^nIݺuԩSH.qO"P)66V}ٻ&| 4g*//O۷gPN=v|1jZ߆fc@c@c@c@c@c@c@c@c@[r= 4OKNΜ{KVVVZUenҺuj7--MӦMӴi{Lw4p@ W{ղ淩q@PII>5kת\W_}"""?Yj׮}5rHn%$$|:tsСCe&--MNR-Wшݢ7y~+螮/:ʾ5Z֭[$^{Ok_W_}U/%IuAuA-[S׼yԭ[7=33맻[c]{E_ 㒅ӨۆُW 8{N8I"ƪP111o.Ի|w@rY} tL9uOEi}w 1 1 1 1 1 4> ib]kFLf~ BY_89rD!YPRvΧBΞc;b9rDqqq }'@Y_D(9uܧ܅uJqqqEU ,˥$jJeee;Wr댋zPՂL04>mƟk81 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1&0++K.Ksr4+a2%),,L=Fe6 D͙3ShTf088Xg?O?h4fPnS3gTyiժUڳg(_nI>(B=KܹsճgOuShpJR5f= @#?,q= g-+WVk׮Ξ=hd\0URR"IRYY*\U\NO6|}NC}/{r7eggk֬YUƟ}YEDDaF5zh*&& cǎ]r/'r>p uk±oW7f592΃o|9OmS9fͅ砱)!!tpn*㡡 Ìupq؅ ,|=@y/究m*ǬL?_000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000A0--M=X{衇t]wm5mڴ:?JJJm۶}An[))):t^}z}wy琫_|*摝.](22R͛7׀[oywݺ5cƌz|@{n[N4iR>x˖-Q}-[}*--Memذk 6h˖->?fΝh"޽[7oVZZ233uQ6cƌѦMi&sJOOӵuj7ZrvZ]veЭުӧOkժUJKKS5e{-`˥K[nQDD:u_|V^aÆyn'ĉuIM8QK.$;wN'OV\\_Jx=z |;JOOUTT]vyW~b%@@8IRVVV[pB^Z֭SnnW^yE?멧p֬Y۵k. }SNZlx6_}y*+'N4֡ChϞ=ޟ[uVuI\㨤kW\QI}>… շo_I<;'huСC>}ݫ/z5uTIӧj֭5~x}駺ۼgӦM̬tM-[T޽dIRAA>L讻ҝwީG}TAA;CgΜUW]`M2j*;vLM6)==o u뭷6q\*B.|TsΗ,legg׸߅Q{gUmLiF=FU%y-\ Ӛ5kj}g?k K r驧VRR=z{u󃹨HSVV֠s+S^F0gk± _YxMz|9w_SmTY~K˩YfUg'k*,,TLL`Tw0%%Eǎ3B`x"cד2:V;v*k|=@y/究m*и`://en[nxhhh7.%>zr7ڶC_@ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCc2<(˥;w{*I`VV\._||]v{j~$PW_UHH i] @ۭD%&&gϞ1c:Gzկ_?)==]0@#ixSNgQǎ~O;vP~4l0}~)@kvZEEE)**Jzs)(yя~]jɒ%ղe8kd0##C;wΝ;[o)33S R~~g}z ѕW^>h4!@CTǎ={X=?~7rcz~d^r)((HgΜmݺsm6uh4M `II>,I:~-ZSNiСmx uI]vՂ tq7_ShM6׭[$IRttt^%IsռycuA?Y4&+Wʕ+49#I5jT# `g&ysHTVV2M )|]ZpՍYxz|9w_SmTqq%S^(jYfUg*..ѣUXXO/: `JJ;f@)**RBB-:prUCCC{6`` ` ` ` ` ` ` ` ` ` ` `L'Ǒ$y&W߷+[D~ 'O$y&NGLLL@T8f;,7lcz寒00Dn͜9SnSi4cq[<@/@c@c@c@cKŋվ}{wڴiTo̙}{VVP{&++K._>}4o/;;$&&zwGJNNVxxߏ3iiiUriҤI::tr /xږhʔ)JHHPdd O?j:2͘1CݻwWdduw?zWY#G6hk]1W߷o[6Ζ{NӦM/KرC]w O>S7nԤIuV_^ΝSffN>UPP+i#==xvGh";JLL}ߚT1_^tmy u>}zEU{/k;m4իyf:uJC QyyycFtھ}z!m߾]k֬G}aÆUv„ ^O6/Jmk-z?ւ-_\.K?я u6%媫rn.]8/4uGqFرcog3gtzQ}Nbb3w\ٳgXc#ͰqL:СSQQ8N[gIwm_ĉNhhzj6}[m\xyIN~~gnpNڰk sm@_k_ovnF@^禎+Rm۶M^㙙z74UXX(IjѢxnnZjΝ;k„ :r?Woۧdo^#Gԁ$Iyyy:|ךnp MjKKK__7n\.g|Ym۶kdu֭Iaa\.Ɵy%$$(==]_//;S}MmOرc*//W֭[nÇiV qM>]^{u4hn6kNyyyz衇t7j۶m)W_}?s/#_~z=Zݚc ^Љ'kj|!_j֬7o^eٳg_BGVLLg|̘1j߾{лQ@S빩UÇ{7unJKWHC±`ڵk6o5>bݺuӕW^v_?.`РAw﮾}CZjě/[L Rrrg7m*_VV#GB/o„ uN:+իWƞv禲˗/ט1c5ֹ)-KHBB#GTL_|Q999j۶m&%%]vڷo_#ͮaEFF{ڷo緁kÆ ?~|5uemUZZǏ6L~~zիBCC_znki&ݻƥ΁4kL{ri|ׯfUɓfkj߾}|:t萒a D|mذA﫬ɬ禺W{=zԺmS[_@A5V^턆:˖-sL6͉t<Ջ{ljurssϿbqɓ}N^^iӦSTT_u8lݺ2dYӹs:Κ5kݻw;FrxW^^:3fo*|IgǎΎ;I;vx~՗m:6lpoxN=sjUq9Æ sڶmܹq?vf͚;N^^/;]tqKk:f__ρֵq gɒ%Uu=Nvf͚9z@'+VpqLe˖Nhh;O;oaĈNRR$'';Çw}̙3Dv;_{n?θt$9{o*뜓SyرgΜq&Oh w rɟ;//;qq>wZh4kСӟ/{`5}}=Zvy'pĉUu8ӠpIg!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!AzIENDB`mir_eval-0.8.2/tests/baseline_images/test_display/test_display_labeled_intervals_noextend.png000066400000000000000000000174721475740344600332020ustar00rootroot00000000000000PNG  IHDR5 pHYsaa?iIDATx}U}TXYR+5P" ƨAQ&LZMƇqv"3Ҫ J"icp1Q `!PA@T`Ee#?nY@Xyfvf{YK("HC'@@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$өhofDTt("vѡCkax7>M6E~*=@MMMD޽{gDCCCՕg$?}ov]@Ƿr HF$#@d @2 HF$#tho}c?vÙo?$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#IӦMRgn6GTЬZGܹs}ݱuJOU qE>}⮻TZUرc|ߎ/^JOդ /~q9ĝwYqw_TZE袋s\~핞 @T fϞsN :S8_8cԩq}Uz*ǝo64o? 0 >֟ @+s W?hll,nhhhjj:W%}<BKeGF ?b1k֬yڵkf]vŔ)Sbѽ{JO"Q8زe wY dmʟ;72S-=-9vm2-9NGfX6{N> Q]]}xUUUTUUU`FqOS8ps TKAK][8LKӑ7MgVO~  HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @25pԏ;k_Z;vlxGkllNJ+>..~L^hqo??~}cǎX󨯯aÆEnSNq?_:o--f͚xg/믿>i]v=̛7/F_hѢf,Z(~_9Y&-[o~6SNK+rThk: :47tS,_=ѳgx'STt5عsg̟??rJ̜93S~܁oJx衇_bt5 O:uj̜93̙u|8䓣s1gΜXpaݻ6gyflذG ;du]X׮]cРAgqF 80N>fca_ʟw-jjjʏy#"sm6lӧOsFMMM̝;7O,.(JۣGu5{;/իWs=^zi\uU͵K.k׮ .JۻwQ?Ͼ"u8""zqƵteݺu /!Cļyn+oU+۶m4~gРAѽ{xy%K9~/,_< ;v*"]6=ܣ4@aݺu+ĽGn-֟L1nܸXlQ=nӦMqM7ū?n!""v~{,_<6n+Wӧ믿W^yeYti?ӈ#NQFܹs#"bkUdB__j|;߉Z\s5\;v3guǎWU̟??lz|3t>|x9+oW\qq/Eߴibڴi룾;7j|3όG}4="-/`׹sxǎp,9cВcז9-ӒtmeS~A8e9>f͚u#UWWGuuAUUU}C84?\=plۇpصeC˴8i}c.#%/HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@d @2 HF$#@dR T*ի+=V.pڴiQ*zK/4^|JO eFD\z饱yؼys?N:ĉ+=-kX]]}>}9rKlڴ)~ߔկ~cƌΝ;cɒ%0@+i{/~W^o}[q7ǪUb̘11iҤxw+8SO>'|r|QSSOOǜ9sb֭|RSh6y۷oDDİa'?I;66lgώ;VZ ޽{Wp_ ~8~ᏼQEDD\}խ4+Cw㥱1˷"")*5-8E}c>XsǠ%Ǯ-sZ%Hu9b{Q}}}̚5Gy$vZGk׮]1eʔؾ}{t޽өxu.lْ!z:|񪪪{_HG$#@d @2 HF$#@d:UzmYQP- O`ǎQWWWGkǎѣGJO"JEofDT:uuuiӦ޽1}}α9>爜(رcGF9OCѯ_ݻwo_Lǒ}#~<2w[Wə @d :ΨTZ}#~<2w}n@2$#@d {^uYѹs5jT,]S:fg>555qǟǫliӦETjqVhƟ\}}AӧOEQD}}}F.]bرK/UpR_}Duϸˢ6JRl\|Xpa|1~عsg.ؼys駟ЌÇ7۟5k֔wsO /D>}OOt[ /4 FDĕW^YަΝ;cȑq7?OclٲxbĉgϞڍv޵kW\2XreZi͛7(J/}vmiS)8\p׿fcÆ +n zw(}ص^[| _ܤ;S9r!ۻwoѧOb>ѣGOO4q 7 *[E[(~ӟodmmVTUU ,(oo:t(yV'q~/""7>7pqr}>׺%/|Kun\<޽;VXǏo6>~x*4kqꩧ6_dI~1tиwީuEmmmuY1yׯzٚWWWg?vw|+Q*mג]bE4555ۦ6FѮQ*gϞE޽co~_>ߎz*կt_{[S'ٲeKٳ'8fgqF[SEtM1bĈ +;K.$VX&:thww1f̘x饗z5߸qc%{\bĈ2dHr8Z{=ZߏSFΝunO|ݻwt|w͜93xXxq7 ֭k_ݺu>;֭[Wm7nE]{[疬m>}bݱu֏ܦjjj*֯_ .lvP;Hj7ܞzҥꫯk_{EQlmbƌũZtҥ8q ׯȯŋEQZqEzjqI' */xw+cq}nHwQٯC&kflgZ0 l#.@xl`3@! f6C l`3@! f6C l`3@! f6C l`3@! f6C l`3@! f6C l`3@! f6C l`3@! f6CHw 566j޽Ȑtw aȑ#W\=ػwzn?޽[ݻwt7" I'Q]]=zxvD off&c[ `c@! f6C D]3g hܸqڶm[6rG7kSWWK]vUN4vXٳYCi„ r:r:0a>QQtwjժU*--U}}JJJtfF}y/^SN… `XB555+ms 7hÆ Zd,Y 6h„ ayĊ5n}:uu.؉Hw paD8p@999*++ӥ^*Çoz˥l+?~o]xF[wZj $IZj >L{n}b'@4pVԸ[]AT72= (lrI*''GzĉUYYڵku xoWQQV\)I裏t:O,m Vß\!Xz/`04m4]r%***>f T^^_9r֮]dUTT())I;wnx$UTT(''iNuuuWWWeuָ}?Ur;!gZbz`)ShƍtUWwo|<0m&-45gө=z~׿`jحW' wu-Z>@ݻwٶ[n*((.I˓֡CTnnOyx۴4}t\.ݻyiD#yuaO Q Д)Sohҥ*,,l>UUUڽ{u&I0`UZZmo>m޼YC$ 2D.KWW,mRrr233d$nL aO Q ;П'ot*55U5559sZuM;vЃ>]vi֭Ȑ$'??͟?_YYY{UUUk*>>^ɹ{?/I4i [o+*mO.9p瞓҈#ԭ[7믿.IצMtWW^իW/}G'I<ƍ뮻N_|[oyß$kӧJJJTRR}W^ k d');Q.1pRԍtt옢 53uƭk[r8L|`Fb~^n n B`3@! f6C l`3@! f6C l`3@! f6C l`3@! f6C l`3@! f6C l`3@! f6C l`3@! f6C l&9s4p@edd(''GƍӶmۚ1 C3gT~~RSS5b}鮻R׮]թS';V{iСC0aNN&LÇ%DT2yZjJKKU__=zW~i͝;Wk֬Q^^uoSj…Z`VX]yjhha-YDK,ц 4a„^psaD8p@999*++ӥ^*0S?}/ɓ'r);;[Ə/IڻwzŋkԨQںuzUViРAUViȐ!t۷j9N\.effMA; G[r\,IRyy***TRRmÇkʕkĉ竨棏>?I].{n3/ Dm뮻h"}޽0@)ĆaNĪj9N\.effF;lK힩ESGK|?IڸZc.c*@ ױ>ß=ժ9^!@_mݯaO@:H!(ߙbmΩ! [.2' 3-Q]=zH3v:`'D}# $@3δD# l`3\Ժ4 z{S J_&UVzR]_^-nQU$Q\>:PYaEmu7 j:XC @Цًn{ +CiG1m+0+MgtI36'M]0ih{`"6&ūwNӓCy7 {( 5女ҁ8 0"݉XU]]-)˥HwKC l`3@! f6C D]\l*p7l[nE]wݥ]SN;vӬ͡C4a9N9NM0A GU~4w6ی=Z,^N jZbjjjtWnІ d-YD6lЄ BEB;Ҙ1c4fm\.^|E+%Iz_F֭[dZJ $͛7OC ѶmtE:5n]JUq+'#I & UVzR5?Ư ;SI Q7bS^ziĉnڵ:qJJJ竨H+W$}Gr:'IJVW^yTgjHw-]۾сկݦ^3ќ["=!1ckiҥzꩧf9Ruuu %%%s oS;''ۦ5uuun*Ձw;P!pڸ 1(_EEEꪫ;hz}0 9ᅴw[mZ3gwшT=!pf8PvĢ>ßǼr7G -uM%Iyyyr:tPvٿ)uoL>].{ @4sS̶%wTFCz *`UUvޭnݺI D~;o>m޼YC$ 2D.KWrmZf?򈹑=bɮC}xWwy=z&N^4i$]y啬4õ'LhzvNն#d7׿ .@\p$iڴi +>>^6mW_^zoV^G)##<ƍ뮻N_|[o)>>^S>}TRRWJ_/ -!Œg_`]C0vA0 Èt'bUuuN\. XӓfFq{>ɗjԣq@͚nsGh0vH AH 70 @Q ӴSOF#wF_hd>:\+W\UvZ8qY|y|Gr:'I (ֺ:KJ@'D][w;wf,I'Lzuyhl@/mb`EE$)77ڹsMRR:w|J+**sx۴NuuuWWWBﲈaڸѐnu~wc.!bjh> m)ԲMk{9sx8Nb5 M=S54F1XS0//ON vСC>߿?p)MM>].{^t-_]CSLB婴{VYY=~JLLlf߾}ڼy͐!Crzjo?X.ۦ5l@u}*AOnQ7F_|ڰaԳgOM:Ug9眣s9GgVZZnImݦ{G]tQVV^G_~$ѣ5qD=I&+4X׳sUia9)! )/}{n=m4I7߬Wmm:tH {ァ }y%$$Smm.2͟?_EzӟԻZxرm#zf*ɺ0+=BDuhG!@3 أcs@p-2L}AqpR]h0[ ']n L `3@0a:vB?~~6]/VVzR{-ױTqL3mLKp V rvVFvz(cN^ 쾑aQq0a^5n UM(ΪZ rizP!bc' Vj:XqNe;j:v"=B([篶V'mG]^qK+jGt!bKs2¿jGt ![.R3~AyZw^Qo9 0Կgg?SOVkrQϕm׳:5FQ&,#efR0_^-oL-2>zd$hQ9e7 @X7R]R} G{5vV0XV 7\/ aLK?No1kD7mDDۮ @鶻53|^;#Ё%t۞IDH>@όٿU~ƪH=@RU;v}gR0+=Icd$h򥅖Tvz @"@3女>C`[u%i͌b!Sp  ABhfe'ָ@;].?3Y2Lٙn@8@%`! f6C lJ@Ts^S^]UeH:/?S/ 9#ݵu7hƛJ56ꙕLVn1B$ع˵qOu+蒪FG55*RbmK7\]Ÿ$'G+Iҁ* c( > p,ESz';7;_P"`RzJHw#"r2_R߂@.*RV9 C^ hW|Ch~EtKR0ISFuno~/- A8 0"݉XU]]-)˥K:5ns˵POWԤHw-$ >MzoMFr& Ν@88Tjܭw40= /QV53ܣq0~$tK&&= /_OԸ5pVi{`g(RZwCz^@[MO/ ~ZyMV+?T1?a5Yy@d]:V^ A &Xk^!<!+=IlSU;vI2>!"QϕmsROޖDgNun|a6U>&!''h%gw;~R[UC|fͽaSRnЌ77u5wHU8}At;X5s?Ԏ'Z}RCcq}L53زOIgvMⰄM&:tU,j=女햂LI7!0P:RHr-z~Y6l1 rvVZO>{_}=S sމ'}Atk^_KV 8H{} ue3玦|']=wW0$BG;Ogo/^f_f5yr} Uh^h8Gc]? ßl_6V66  bͭ Ug+} Ee玦Z{O<EGLN9s}f檢Bd}Q :t :tjkkuegUZG;,o4NagC[kAnhًq}hh :k>1^̮c>]J7m|p玖|ͩVTyR}AO]O]/-T:skǐ7Vi\{+}95(ْ?EuCD@ 7=֖lާ-{5vgy}y~Y>Xp+ҁ{d?W~~ u뫯$B%%%޶>|V<9vZ8qY|y۴N~"i3,sXn(җg_lɟ [=ZC[jOu3WձpРAzj޼yСCUUU>MVTT())I;wnMk̙#ѣG_5I q|iR0F9U`~fҷ{fj-@Us^7Bg9St.:fuAIsلy1ƌkV}_~[K/y8f1 Zjr?wU+z }e+o/(2女B`4;wfe_ u:%[3rlYp[jOIzl\9yIM@ԩ?\ƍtr[n6Q99Yɡy~EoSvFFN Dr'y7 @L/R/ Y9 \ikik}j2/~^_ t۰3[=w4r'/Ѷ#!M! A鬳ҤI_BuKnrrr_R'ORvv^}U]wu}{ZxFeyCUH`[?~2.hh4'4ou k

t_UO.[.QA-\7ofXhh4tK lsztQkO/;S/|U/ڜ Ah{uUWgϞԬYTVVM6@/5g9眣ٳg?lV'?hҽޫ*Ke`Bq[^ mzؓgc[tBS%Ueއ֨t>]ԭvK6Sc+z 7]y̖o; 0FٳG?яtkQRRVZI߯S;Ѕ^Z7I3v0o @:`.}om"M?ۭ?ęuzkƛJ56ꙕL X豿NjY]NŸb=60>Ρ~ݴz%fv_YV@ i=I}Q"K& hjɋh*SF8pͭSԷ{_&Xl`, VsHۀFM,9Q0MДՒT!ǿQ'-2LY~\m3c X1mڑXFnWԔ?dM]TS݃{*˭j߯?ѼU:kۺfk9Vs77LyN%烘ܚ+c ^T.Ol ّXFlWTӭ94NIQDM\yzvCwCj{=8f]ӯtI5d-5=Sm1`CҗSY125)^i~<Ķq5ڔխCU}2`g`%Z&ά󣡕Gܦviig"aIYE/+&o$%XC8)1h}G[FhU ;bi'N gze.S;3+Y_k>6Bk5&ݟ WϮ{k;;:Gw~W{dN˝@₰#MKFۿEv `8azfJ64cSVʍ8>LfG^\{)foX>{| {!uj} gJ\ExQ$;?b4H,߰2zBŸs?”UZ]t=:K1s9T]+}-@u3-=ϼ^3?iKk∥Ur;j4q "ZwfIe۾C҈ssgϖX(|Q/-(Ps^wʾ<MtZZ5*! >%fKwudp 8vB6;E(3:K\պ|Rsޯ?Ba@O;FXط̔xM,MqVTbQ{~gV 0v8~Ec@@묆?h{:\kd-Q"soM7g>;{##yDqH;\nv8K m07קeFQJպRa5oݪoTӝvg8J׳o[~?FB~NF)# y"/*gjbOfv\z9zc݌{ĒO5ԄxM~n@ae&FA rvVeFrԙt8}6k|@>Ӧ#$VW4apO=>fb?+6Im/pQ@DB W׵,ٸZ]RRJ3Db}7Zq wjCq }gjuqIGwtr'x%;ХggyBq9%ș.Q5xrS򝘼gK^6 ge8g}y3i疻s%܂hEwN&{+ v;c:&z6TY.[ -"v-;Nܸ/ط{6V0 E6g.=)u$ Y}#R %~mexk7$}1U$u;-gimڧ%W(|wmz  $PI4;0|e~4oݍ3aex3jxCd0K lMG>c(nk#ItrTyx9ymZ)ThhDY_}R)מꓣ=HIԶcw*Q֗h[19gvGg6pmҒ_ijC8D;:vB{t{+BhǗֿLnfV>pYK 힩' y/ Z|ͩzeQjh4X";=)cŸh&k}ɫ2>OW%h]X/좤q9JvHNмG˥똹?րio';q9PPk<"@ ^{<[

mrg pi\J3E{vNUe#j׿RM!m-I.:=M6@"Ni:Rנ~_=;õDC͍6R߬yk%mH i]Os00C–=Уxfǵ*s2yyԯi[őPuoأsv^Sm}INKMԆGJ:>Yq݊@޿n`@#1Pp vU|7P) Py?[^8:~ݎ.Xr24geǏO.ŸSŽstz*΍s F`E M5!0s<Y`g P32/9iT\jw;`0@~|kb !n͌b!ΉZ7!;=)*:)qOj,҂P0;~g꓇KB<M3GiY9a~-W9GHC=YcLe(o>yD}wH{شv=~ғܠ87csecvzR@f(ֺ*p';+'] kT$8$5Mfk͌vԜhOKQvx7WW ƚ4ۭ"1-U-y\~V2ƙ~}]ܾ_1::=%!(eғT6}TVn]uNgήuMO~wcu QgԀBSNFhV6_-Z9al?`KCuIKO~Y%3S#Ugt17_,T|G5o…!w}cŸCRC3.4yYɈM>gW%š2});t픤/ ::ְ 8ZEȪPafDks"Bx݌⠖5(nYLxc-kG^yreg&<*ceu=F']i$\;+=Von+v̀S3Jwm)F<<灿C s3hQ +7!EfTNysTC7]-R[Cmß-bL̤G݂,TŽ]`יj6ajRn.v;ھTwP}AO]OQ`ڎԼ*MױF>KT`z`[?e=T$K^7YK+z랒蹲roTd=vuQ/Ksu"f'@ܜL~$pt6+ }&ZWm<Wgԧi02gΌH [篶|ً%84' WY7];c=–DXB2S+*NJ56toT~WBt~~^9M54;:ǥЖ9ЌPC {K`2矖e;^m6?Y[u+t 'Jw#'k~f>e3ۖ SR*97[nQŲugvM_-oOX>̮n} +O[YZ` g8!oɗu_o/nvF*;D@\iÖ<5nU`Ϭ|־Zω윹̔muVWb3NJY0K};XLX!kyFt=S)A{="!NpMC aX\\vKiod^ 4I'Q_{r2+Ѻܐ@[*Gb0{:(S2iba^ Wp fHоZ)gTRާN$̮iw?Vз7ESyw+YK$gjOb^^VvT jpgK8쾑EFkΑ[0ihNVV:K/lDoUkOv9'En!"`) zy%چLɱzŸ=R6Da+}-δD5{Z7ViғAiW9{:[)g~ 竬c GjS*靧v׫oJ{̑[3XA,ctK45>i֥;"oB@DX&ūwN/=C؊9:\E3Bhcvqkfk݌b8ؓ/86msn,Rj-Nٙ4^S) i zv%`ݼ`ϬNZ7AYlkgG_VgϮЊ.t7Zee7_s<ғT6=kܦ.)UgfNg?}䢪X:`2女h]?O)qJwNZέ'Ig꓇KTvH 'oψY]RPjb][]=zQa~]9pҷpN^i܍UR8mL֚/ou>E+4G9\qD.QiI85Uw/̮iZ7d #/ڶ>Wb4,tUD`Eӓ1[FS $Y)orf}LOU]w ` /.J5hm| 7\F)Uq.b|/iitQ7~]j::KhwOn aګ[ d$|ӕ"Z4a62w/aܼuaUI ᳍b}E`a咕CY\ %3F3l ]vɗFAܽ%0]BHC*˷ 3-1QX/]|fW7 ;.u!R'ԁJ]bvm-z~YyN oo`@8u7hƛ Y/ۺX 5_/UF9$F W$QϕmsR-L:%:3@=z'o>aÆ/;:X<\)!ޡqErftLm_ԩS/?1ch˖-ٳgQ)+=I/:WQ0# Rsyo;4n8͙3Wn]V%%%n/))ʕϦM"ݥuQOsmկOkܹZfT\\{$i͎ŋѫLwyVZR׫DGkOkMO_iȑ꫽!!uE~{۾<@z;y_~FLd,\F#//x'?~p:~0| 0nfꫯHbMee!(++3 ϪapYѹsg=]; !ۭkת%%%Zrez[>s竰P_Hw)&ٱÇs,Z*''GzĉUYY.E%%IʒgUσϷ-X@GՐ!C8A oF mv{nn***"ԫ1h zw5o}?tWbg4btMMu]Zh>u{;ǟ9mVRR>l]xᅚ3g7w PRR fjСU쪫֭[խ[Hw%*//ٱvUVVƱ觪*޽Q'GTL7xCK.Uaaas:DlM,XHLL4^|Ec˖-ԩSN:;vtע=c|W_}eZʸ+ ޻69rX~~zCOׯ7via<4x cӦMƏ~#[nFuuu{|G1cʕFyyC 1N?t?0~N}y;m׶?M>XlQ^^nlܸx83 `5 $͖mǏ7uf$&&5\c|駑V I|͆a,#yyyFrrq饗6mlرcFIIm$&&={4nfc׮]vTh}dk[{_nV5;;۸˼08|qao@! f6C l`3@! f6C l`3@! f6C l`3@! f6C lh)k /IENDB`mir_eval-0.8.2/tests/baseline_images/test_display/test_display_multipitch_hz_voiced.png000066400000000000000000000534711475740344600320320ustar00rootroot00000000000000PNG  IHDR5 pHYsaa?iVIDATx{|Tս䞐d$ T(BT{ZQ*RE倭Gmj~[XED(AnBt$$>ٯC&kflgZ0 l#.@xl`3@! f6C l`3@! f6C l`3@! f6C l`3@! f6C l`3@! f6C l`3@! f6C l`3@! f6CHw 566j޽Ȑtw aȑ#W\=ػwzn?޽[ݻwt7" I'Q]]=zxvD off&c[ `c@! f6C D]3g hܸqڶm[6rG7kSWWK]vUN4vXٳYCi„ r:r:0a>QQtwjժU*--U}}JJJtfF}y/^SN… `XB555+ms 7hÆ Zd,Y 6h„ ayĊ5n}:uu.؉Hw paD8p@999*++ӥ^*Çoz˥l+?~o]xF[wZj $IZj >L{n}b'@4pVԸ[]AT72= (lrI*''GzĉUYYڵku xoWQQV\)I裏t:O,m Vß\!Xz/`04m4]r%***>f T^^_9r֮]dUTT())I;wnx$UTT(''iNuuuWWWeuָ}?Ur;!gZbz`)ShƍtUWwo|<0m&-45gө=z~׿`jحW' wu-Z>@ݻwٶ[n*((.I˓֡CTnnOyx۴4}t\.ݻyiD#yuaO Q Д)Sohҥ*,,l>UUUڽ{u&I0`UZZmo>m޼YC$ 2D.KWW,mRrr233d$nL aO Q ;П'ot*55U5559sZuM;vЃ>]vi֭Ȑ$'??͟?_YYY{UUUk*>>^ɹ{?/I4i [o+*mO.9p瞓҈#ԭ[7믿.IצMtWW^իW/}G'I<ƍ뮻N_|[oyß$kӧJJJTRR}W^ k d');Q.1pRԍtt옢 53uƭk[r8L|`Fb~^n n B`3@! f6C l`3@! f6C l`3@! f6C l`3@! f6C l`3@! f6C l`3@! f6C l`3@! f6C l&9s4p@edd(''GƍӶmۚ1 C3gT~~RSS5b}鮻R׮]թS';V{iСC0aNN&LÇ%DT2yZjJKKU__=zW~i͝;Wk֬Q^^uoSj…Z`VX]yjhha-YDK,ц 4a„^psaD8p@999*++ӥ^*0S?}/ɓ'r);;[Ə/IڻwzŋkԨQںuzUViРAUViȐ!t۷j9N\.effMA; G[r\,IRyy***TRRmÇkʕkĉ竨棏>?I].{n3/ Dm뮻h"}޽0@)ĆaNĪj9N\.effF;lK힩ESGK|?IڸZc.c*@ ױ>ß=ժ9^!@_mݯaO@:H!(ߙbmΩ! [.2' 3-Q]=zH3v:`'D}# $@3δD# l`3\Ժ4 z{S J_&UVzR]_^-nQU$Q\>:PYaEmu7 j:XC @Цًn{ +CiG1m+0+MgtI36'M]0ih{`"6&ūwNӓCy7 {( 5女ҁ8 0"݉XU]]-)˥HwKC l`3@! f6C D]\l*p7l[nE]wݥ]SN;vӬ͡C4a9N9NM0A GU~4w6ی=Z,^N jZbjjjtWnІ d-YD6lЄ BEB;Ҙ1c4fm\.^|E+%Iz_F֭[dZJ $͛7OC ѶmtE:5n]JUq+'#I & UVzR5?Ư ;SI Q7bS^ziĉnڵ:qJJJ竨H+W$}Gr:'IJVW^yTgjHw-]۾сկݦ^3ќ["=!1ckiҥzꩧf9Ruuu %%%s oS;''ۦ5uuun*Ձw;P!pڸ 1(_EEEꪫ;hz}0 9ᅴw[mZ3gwшT=!pf8PvĢ>ßǼr7G -uM%Iyyyr:tPvٿ)uoL>].{ @4sS̶%wTFCz *`UUvޭnݺI D~;o>m޼YC$ 2D.KWrmZf?򈹑=bɮC}xWwy=z&N^4i$]y啬4õ'LhzvNն#d7׿ .@\p$iڴi +>>^6mW_^zoV^G)##<ƍ뮻N_|[o)>>^S>}TRRWJ_/ -!Œg_`]C0vA0 Èt'bUuuN\. XӓfFq{>ɗjԣq@͚nsGh0vH AH 70 @Q ӴSOF#wF_hd>:\+W\UvZ8qY|y|Gr:'I (ֺ:KJ@'D][w;wf,I'Lzuyhl@/mb`EE$)77ڹsMRR:w|J+**sx۴NuuuWWWBﲈaڸѐnu~wc.!bjh> m)ԲMk{9sx8Nb5 M=S54F1XS0//ON vСC>߿?p)MM>].{^t-_]CSLB婴{VYY=~JLLlf߾}ڼy͐!Crzjo?X.ۦ5l@u}*AOnQ7F_|ڰaԳgOM:Ug9眣s9GgVZZnImݦ{G]tQVV^G_~$ѣ5qD=I&+4X׳sUia9)! )/}{n=m4I7߬Wmm:tH {ァ }y%$$Smm.2͟?_EzӟԻZxرm#zf*ɺ0+=BDuhG!@3 أcs@p-2L}AqpR]h0[ ']n L `3@0a:vB?~~6]/VVzR{-ױTqL3mLKp V rvVFvz(cN^ 쾑aQq0a^5n UM(ΪZ rizP!bc' Vj:XqNe;j:v"=B([篶V'mG]^qK+jGt!bKs2¿jGt ![.R3~AyZw^Qo9 0Կgg?SOVkrQϕm׳:5FQ&,#efR0_^-oL-2>zd$hQ9e7 @X7R]R} G{5vV0XV 7\/ aLK?No1kD7mDDۮ @鶻53|^;#Ё%t۞IDH>@όٿU~ƪH=@RU;v}gR0+=Icd$h򥅖Tvz @"@3女>C`[u%i͌b!Sp  ABhfe'ָ@;].?3Y2Lٙn@8@%`! f6C lJ@Ts^S^]UeH:/?S/ 9#ݵu7hƛJ56ꙕLVn1B$ع˵qOu+蒪FG55*RbmK7\]Ÿ$'G+Iҁ* c( > p,ESz';7;_P"`RzJHw#"r2_R߂@.*RV9 C^ hW|Ch~EtKR0ISFuno~/- A8 0"݉XU]]-)˥K:5ns˵POWԤHw-$ >MzoMFr& Ν@88Tjܭw40= /QV53ܣq0~$tK&&= /_OԸ5pVi{`g(RZwCz^@[MO/ ~ZyMV+?T1?a5Yy@d]:V^ A &Xk^!<!+=IlSU;vI2>!"QϕmsROޖDgNun|a6U>&!''h%gw;~R[UC|fͽaSRnЌ77u5wHU8}At;X5s?Ԏ'Z}RCcq}L53زOIgvMⰄM&:tU,j=女햂LI7!0P:RHr-z~Y6l1 rvVZO>{_}=S sމ'}Atk^_KV 8H{} ue3玦|']=wW0$BG;Ogo/^f_f5yr} Uh^h8Gc]? ßl_6V66  bͭ Ug+} Ee玦Z{O<EGLN9s}f檢Bd}Q :t :tjkkuegUZG;,o4NagC[kAnhًq}hh :k>1^̮c>]J7m|p玖|ͩVTyR}AO]O]/-T:skǐ7Vi\{+}95(ْ?EuCD@ 7=֖lާ-{5vgy}y~Y>Xp+ҁ{d?W~~ u뫯$B%%%޶>|V<9vZ8qY|y۴N~"i3,sXn(җg_lɟ [=ZC[jOu3WձpРAzj޼yСCUUU>MVTT())I;wnMk̙#ѣG_5I q|iR0F9U`~fҷ{fj-@Us^7Bg9St.:fuAIsلy1ƌkV}_~[K/y8f1 Zjr?wU+z }e+o/(2女B`4;wfe_ u:%[3rlYp[jOIzl\9yIM@ԩ?\ƍtr[n6Q99Yɡy~EoSvFFN Dr'y7 @L/R/ Y9 \ikik}j2/~^_ t۰3[=w4r'/Ѷ#!M! A鬳ҤI_BuKnrrr_R'ORvv^}U]wu}{ZxFeyCUH`[?~2.hh4'4ou k

t_UO.[.QA-\7ofXhh4tK lsztQkO/;S/|U/ڜ Ah{uUWgϞԬYTVVM6@/5g9眣ٳg?lV'?hҽޫ*Ke`Bq[^ mzؓgc[tBS%Ueއ֨t>]ԭvK6Sc+z 7]y̖o; 0FٳG?яtkQRRVZI߯S;Ѕ^Z7I3v0o @:`.}om"M?ۭ?ęuzkƛJ56ꙕL X豿NjY]NŸb=60>Ρ~ݴz%fv_YV@ i=I}Q"K& hjɋh*SF8pͭSԷ{_&Xl`, VsHۀFM,9Q0MДՒT!ǿQ'-2LY~\m3c X1mڑXFnWԔ?dM]TS݃{*˭j߯?ѼU:kۺfk9Vs77LyN%烘ܚ+c ^T.Ol ّXFlWTӭ94NIQDM\yzvCwCj{=8f]ӯtI5d-5=Sm1`CҗSY125)^i~<Ķq5ڔխCU}2`g`%Z&ά󣡕Gܦviig"aIYE/+&o$%XC8)1h}G[FhU ;bi'N gze.S;3+Y_k>6Bk5&ݟ WϮ{k;;:Gw~W{dN˝@₰#MKFۿEv `8azfJ64cSVʍ8>LfG^\{)foX>{| {!uj} gJ\ExQ$;?b4H,߰2zBŸs?”UZ]t=:K1s9T]+}-@u3-=ϼ^3?iKk∥Ur;j4q "ZwfIe۾C҈ssgϖX(|Q/-(Ps^wʾ<MtZZ5*! >%fKwudp 8vB6;E(3:K\պ|Rsޯ?Ba@O;FXط̔xM,MqVTbQ{~gV 0v8~Ec@@묆?h{:\kd-Q"soM7g>;{##yDqH;\nv8K m07קeFQJպRa5oݪoTӝvg8J׳o[~?FB~NF)# y"/*gjbOfv\z9zc݌{ĒO5ԄxM~n@ae&FA rvVeFrԙt8}6k|@>Ӧ#$VW4apO=>fb?+6Im/pQ@DB W׵,ٸZ]RRJ3Db}7Zq wjCq }gjuqIGwtr'x%;ХggyBq9%ș.Q5xrS򝘼gK^6 ge8g}y3i疻s%܂hEwN&{+ v;c:&z6TY.[ -"v-;Nܸ/ط{6V0 E6g.=)u$ Y}#R %~mexk7$}1U$u;-gimڧ%W(|wmz  $PI4;0|e~4oݍ3aex3jxCd0K lMG>c(nk#ItrTyx9ymZ)ThhDY_}R)מꓣ=HIԶcw*Q֗h[19gvGg6pmҒ_ijC8D;:vB{t{+BhǗֿLnfV>pYK 힩' y/ Z|ͩzeQjh4X";=)cŸh&k}ɫ2>OW%h]X/좤q9JvHNмG˥똹?րio';q9PPk<"@ ^{<[

mrg pi\J3E{vNUe#j׿RM!m-I.:=M6@"Ni:Rנ~_=;õDC͍6R߬yk%mH i]Os00C–=Уxfǵ*s2yyԯi[őPuoأsv^Sm}INKMԆGJ:>Yq݊@޿n`@#1Pp vU|7P) Py?[^8:~ݎ.Xr24geǏO.ŸSŽstz*΍s F`E M5!0s<Y`g P32/9iT\jw;`0@~|kb !n͌b!ΉZ7!;=)*:)qOj,҂P0;~g꓇KB<M3GiY9a~-W9GHC=YcLe(o>yD}wH{شv=~ғܠ87csecvzR@f(ֺ*p';+'] kT$8$5Mfk͌vԜhOKQvx7WW ƚ4ۭ"1-U-y\~V2ƙ~}]ܾ_1::=%!(eғT6}TVn]uNgήuMO~wcu QgԀBSNFhV6_-Z9al?`KCuIKO~Y%3S#Ugt17_,T|G5o…!w}cŸCRC3.4yYɈM>gW%š2});t픤/ ::ְ 8ZEȪPafDks"Bx݌⠖5(nYLxc-kG^yreg&<*ceu=F']i$\;+=Von+v̀S3Jwm)F<<灿C s3hQ +7!EfTNysTC7]-R[Cmß-bL̤G݂,TŽ]`יj6ajRn.v;ھTwP}AO]OQ`ڎԼ*MױF>KT`z`[?e=T$K^7YK+z랒蹲roTd=vuQ/Ksu"f'@ܜL~$pt6+ }&ZWm<Wgԧi02gΌH [篶|ً%84' WY7];c=–DXB2S+*NJ56toT~WBt~~^9M54;:ǥЖ9ЌPC {K`2矖e;^m6?Y[u+t 'Jw#'k~f>e3ۖ SR*97[nQŲugvM_-oOX>̮n} +O[YZ` g8!oɗu_o/nvF*;D@\iÖ<5nU`Ϭ|־Zω윹̔muVWb3NJY0K};XLX!kyFt=S)A{="!NpMC aX\\vKiod^ 4I'Q_{r2+Ѻܐ@[*Gb0{:(S2iba^ Wp fHоZ)gTRާN$̮iw?Vз7ESyw+YK$gjOb^^VvT jpgK8쾑EFkΑ[0ihNVV:K/lDoUkOv9'En!"`) zy%چLɱzŸ=R6Da+}-δD5{Z7ViғAiW9{:[)g~ 竬c GjS*靧v׫oJ{̑[3XA,ctK45>i֥;"oB@DX&ūwN/=C؊9:\E3Bhcvqkfk݌b8ؓ/86msn,Rj-Nٙ4^S) i zv%`ݼ`ϬNZ7AYlkgG_VgϮЊ.t7Zee7_s<ғT6=kܦ.)UgfNg?}䢪X:`2女h]?O)qJwNZέ'Ig꓇KTvH 'oψY]RPjb][]=zQa~]9pҷpN^i܍UR8mL֚/ou>E+4G9\qD.QiI85Uw/̮iZ7d #/ڶ>Wb4,tUD`Eӓ1[FS $Y)orf}LOU]w ` /.J5hm| 7\F)Uq.b|/iitQ7~]j::KhwOn aګ[ d$|ӕ"Z4a62w/aܼuaUI ᳍b}E`a咕CY\ %3F3l ]vɗFAܽ%0]BHC*˷ 3-1QX/]|fW7 ;.u!R'ԁJ]bvm-z~YyN oo`@8u7hƛ Y/ۺX 5_/UF9$F W$QϕmsR-L:%:3@=z'o>aÆ/;:X<\)!ޡqErftLm_ԩS/?1ch˖-ٳgQ)+=I/:WQ0# Rsyo;4n8͙3Wn]V%%%n/))ʕϦM"ݥuQOsmկOkܹZfT\\{$i͎ŋѫLwyVZR׫DGkOkMO_iȑ꫽!!uE~{۾<@z;y_~FLd,\F#//x'?~p:~0| 0nfꫯHbMee!(++3 ϪapYѹsg=]; !ۭkת%%%Zrez[>s竰P_Hw)&ٱÇs,Z*''GzĉUYY.E%%IʒgUσϷ-X@GՐ!C8A oF mv{nn***"ԫ1h zw5o}?tWbg4btMMu]Zh>u{;ǟ9mVRR>l]xᅚ3g7w PRR fjСU쪫֭[խ[Hw%*//ٱvUVVƱ觪*޽Q'GTL7xCK.Uaaas:DlM,XHLL4^|Ec˖-ԩSN:;vtע=c|W_}eZʸ+ ޻69rX~~zCOׯ7via<4x cӦMƏ~#[nFuuu{|G1cʕFyyC 1N?t?0~N}y;m׶?M>XlQ^^nlܸx83 `5 $͖mǏ7uf$&&5\c|駑V I|͆a,#yyyFrrq饗6mlرcFIIm$&&={4nfc׮]vTh}dk[{_nV5;;۸˼08|qao@! f6C l`3@! f6C l`3@! f6C l`3@! f6C lh)k /IENDB`mir_eval-0.8.2/tests/baseline_images/test_display/test_display_multipitch_midi.png000066400000000000000000001534661475740344600310070ustar00rootroot00000000000000PNG  IHDR5 pHYsaa?iIDATxw|u̖tjB ETQAx"b95r?)x wp ((bC" ]@^C'd.)[f7yNγ>Gu]G!BjE7@!B/ B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!j B!jsE7*4#G(!B:4jU}a#GHMMf!"I&݌ !`L”)Sp8UVJ!FdeeJBBBE7(݈*++D233%B!~KB!D#B!D #B!D #I !p'8΀꺎0L&fYBQeU$+VsQΝM7y^uƎ˴i8s =z`ʔ)tLAA9w7 *< RѣG+Oll, 6jVtSBI@h`nn.]t{/zk_}U&N̙3iӦ /'==ݓ=j(͛'|Bݺu=z4 bL2Q4݋dQFXV1t]fq K֭k$B!*X(zu]QF5z p%''+LׯϬY:t(p~Rkоg޽4k֌`Q)~ZhAtttE7G!D&ݻ  y,**>}rJ֯_n/LFرgo *UO !ʪU,##b'''{jRvmx3~x=RN!DYεZW6c 82joz1xygy#^\~4k֌uzB!aApז ޔUL srrWoƁPQF1n8Ν֭[1b 6 D>F͒%Kظq#ԩ\sMvfoN^_[vxvEJJ M4a :Ey1c۷'::vozS/( cƌ :ڵkSn] ¾}<1nӨQ#ڴiziذ!u%-- Y'|Thݺ5m۶qOrr2w}7'O *UȎo!elCk"VU2\n]tK.<t҅'|QF#Э[7>̢E,/2۷ogܸq\:t`=zqWϊ+矉gz,YYx17ޏ?ݻy9s&3g^uo[oE||}/fݺu,Xcǎqwû+T@3*V$#2OL]G2i XbqaΝmۖŋ{}Yz5 .Rկ_~CY}{MQ45&XtW^)\Æ +Ֆ }peK&@G$!EU"V%g5m6gsm)9(8k}|/]w?07fϞ=u]ڵ+s̡AAu^Q:uB4/_p׮]/h޼9fB~T0q 7m(*R5NexfSŗUx' :0n8ƌyعs'[laƌL8wucȐ!Oݻ˗C}7o=ȑ#ꫯػw/˖-O? --ӧOswfâE9r$N37J!2Z'KWEIHgµg9dqhv8C8+:$G$ğ'xwykӧ3sL:uD>}9s&-Znll,+ViӦr-oߞ#Gr9={WԩSxGh׮</kcǎo#11Qj !nwXZ۾UdAvfc>Cu۷UxtHU#YBQuIZ5H9|6qV3bʽO!Ջ*E!5 pB!a$ AyB! CƶmXvmE7E!"h !B0 !B0 !B0@@BQII ̙3IJJf!#F(Jn޼9&M*СCٹsgZ{B!1R 4<Cb*Ȍ3=Ҷbbb GBXH'`QF̝;eZnwK!$ AZZiiideehl 귃ž4jA8v̇#v;x".., M6{ԩSDBB)))^{GBB^x!W_}5|wJ۶myWXl'5jg-Z~7|Jbb"ݻ9t5; ,`ƌ7.oBQHXez@pbk"҄S{N:2i$._1;7oNBBɘL&"mrr2Ǐdܸql۶,u?6l@uڴiS֭TBBȖ|m_o}ĵ\ѪURשSt/^?#</_b1*1Mؿ?_==׿S?3wv~4Md2~zL&SJp !55Ѯ1QJ?os=o&&&oo4ڵkǖ-[ڵ+V5"c#׭[`„ ^O?2ݥKN'Ǐ+{BH(1v%|O(~X!04ȵ\Q1q:уXf͚ELL ͚nE7oޜ+V?(իlo_x뭷-ӼysrrrXd ]tiӆÇ3atɓ'Yt):uKBD AK* u] Y9\=BAp4lذ_NRR{s,Yyyӽ۷-[R~/fĉ+tؑ>[W^<BT+_ax8{r2 Duu'dFFT R $t:2IEz5OꩁSpJ(@\L& BT]}3&6v7D=$ D!EC[/Z_l-62P!  /6-MB!߃_c.@[篊=ٌ5f͚C^Uu1cШQ#bbbꪫ m[*!D t_᳑`ϯVXk=ϡ˝UAնg֭̚5Fr5װm67n̫ĉ9s&mڴᥗ^`B%}|$d ' X2zAg+yHk5›\=J;wkn|6_̠A׿EF5jO=$''+~$\!j0!?y ?Q=F]_:Z@~W[Itttcbbٻw/ 0\TT}aʕ\!L.)})zZ\ssnH+rʨ`BB={_Gtzj=JFFKNNƆ'/8>Ja9Ӣk9QeTp…,X{xbjڶm˽ދ(5q1w\nʈ#eذat! ӵ0RAD{D$ & +h&E$ql?M`Tk7. ^xk9QeT0334ڵkùYh'|QF#Э[7>̢Ed@!޵7$}Y*t +Nۋ rφCe= 0¥ZiEKܹF#$5V`υp=wibG(1$<;^] ~טUɞ?P2H!Deo~mz #L\B!jK{]Awhw2gI@!FGum`@EJG@!7u{KSQFR젦0SL /K/!Cb饯F % {0y!gEi$2AB!*5{O{ݴ< d]77 `r@!ZyuYGJu/kDőP!f] "^@]Tm95Z! !X>'"4J0AW!$="'*P"BTv'xn~ _=I}3fńZ WHH R!áb16FG!91;.i==[]'/~GSH֎oB^&igPA~KX&r !hK6q2y\݊0\1.P&.,Mh/~rhyőB!%ۏ׏7g=$ɩ䥻~zr l;ĩnCV B!D5phLqMf,u=R2l4--B!D1|v!J{(n6d C+Ee%C YB!*ک\ z8G -kqxp4{>&lZ%B[lܾ =!IKKc۶m]"gDn.1dchY96Ϳ/øưd,,?V+a[xH(BTA]Skӱ Z^p~uH6 S +^{{.,xZP!fnCpYO V:4 О?O6fo6 B*_d޸ b->1)h_<4%b\j98fmB݇Gf g|CCIB~}6K'J> ]Ì+C*t5E37 '/nƌ@i nJ 㜠>Zlܱ/X ,lYź C*$."TgZ9ъ?3VD}8~z<֢g0i_^1íӡkC!~-`!:Oo?Ђ9DIVwOJ5ƬU65M ۿ(F@!iμ50kBXz59q\͡鼳|6F D[V@|$BQ=i6 U#W\U<$PLXnh[αhGFZ}|u{K "4IB\~ih}:(x^ɕqp$2^Ɓ5۷}-@*$ "BbމX/GѪABŒ_{l W7a**vMP˗\BQ'Š_4l:aVG~w gZftMW_y*^ڣhhޅOH(B#UUܽ5_[c޿wpbhf>l<C|A۾W71&Q)\]!؂YTZ !U5|79ql籯6s<+}ye6& ) 8 ^Qq$ $"Z5Hg&ȋ!WQ Z/I|66<9g _$ AZZiiiAB!D(TU}?=Ž!׮G|8}N%mGfƗB!0>unb>8)]=S'`B(XPB!Da67BX׍e}ݽXT 4|[~5uAK"v(d"2$BTCcclfa!jsjOhKF>{4phXGLRt+jW?~KY;wBhNm.>983l∩ZQtf֊-f+i?eU17s}|}Ê*rRM6߁b d! 9iG)ݚ-V NL{istext6)UNN@!"=Gy4V,{:;7,-a#hpdZwE;28?H4jV%DhHB`$؏Qs͂sg3ʾs{>{~nsDgϐ 긖eCROr2XDX8ek&raޒW٫7G7^t8}XrmUO!0U<YYaǷirEU&xfa1R*+>69wGt <'CTT+`e9{ k5ZmCJ<_~MҡC6nĉ9r$;j(ƍG֭iݺ5ƍ#66aÆUpB2+_/=LT'tzFqjҲkԣ xkN+s6okePtl?UNvv6?;w.ǏQFyƻ?osn(AnGvîރF_b< Gt}j]v/Q*U.NT90|̼ubK=7k>}svsF_7Nńِ֏~-`QC84ƬU=Lb/~~pk;B-~[\=bz$7]z]f31k>CsvFl?TGm:6qRLgǘo~9q,}95E$I(j`Mt-߃STVt á1ǝقNn!át}=%و;eK `;A8rto7|~ٜL_X{ в2KRGl6'o.I$kGQ@uo=["r$5N:yE;2xm!o={3l=S!yc2N!{;g<t, jú &'n^,ڑ=h7 6|"R$ $R;h(M̂2o=T v;kB(1d?#O>|I٪a:rFe{Hh@22 0-UiI{Bax`kH0iiiyIгTRogohI6g5S7ΊUU;C Bn!x^s?ŬP7. 2>ʸۺ1KIBCAA(M g5HJ y}^r X8.Qb ڥu@쮩0Bkjm:3"96EZ;Bn@_G~ :@T"tJEH(j`MeVsg>ZQiS/m6Zm?:7daVM.6 ;6Db+;u︌Qc=͝ʼ]dzIp=s}.Sǘ鷌MnL(`)v`D,~@!|Ggoj"w})= hIhG-eٌol?>+q7BDR8>C#,"G@!a ܾr&x8q+hBRu5XqU|A]pgMDxgtDsAo_՞j 8eD@!䦭:Fe(h[MQhV>{[^>Rg8ը _?ք"t`ʔ)\x\z!D P]1E=jpJfq}ϵ90\V-AɰCNm6֮][MBe)_Xۮe3:h+/RF-=jVtpđYdkl₟8_DBQ=ثeDkRV&sq\w尞4MW@I 3mà'g56uS-@i8Pw&: pWau|!rq0q6T} Wۺ<* Jz"*m ,=*|5BQ|s2`ٹ8.C@K)2]aU޻;m].ҟq<~`&E 8baJ7CRKK-$9ZU\lc &Y mhvݾ2Vu)rx\5$LŎSZ[&c2\Ο|ٿH;`!?Kl]C,a~gkr XUԎ.M~Ysl4Y/MI+G>M.~/@V߾J|--2v;vU86%ʿeeӇ/ԳgQ`"܉+Fy- W%G~O´#jkGDQK|,M{A'~[NJ WT} dER׎TL-`TV|쪫 6lϜTEekx[ )Y`:כb`,z* g0aQ:o. @~_8]JF;hz>5]8|YTxVp~LӮ?s-N|Ji w~캘xto>Zԋm`mx3.5tQO~;Ɔ@I13gcURuR34VO*{>ϝ i1]RνrH#!3M2Ms+3W%LR_gW]T1k>m(7iD{Ŭi4 fv &/ńEyv :' n2]8+8koƒ Ɖ7RJr >B pOle~Gk-!^46gH&VmaP΄E\|}ɹWHXeQq0 k(oǣy8~+UpWׯs?2Cә|6[୤|cf-fPWEq.ض/E0t_g8r`/ ЅOk [fwWgw . \cxB}ymCS'~ !8mz{3{aΝ|,-ɹWiHX6wUvqu pv+ 8+UF+_b 0 7%+<Ǣם%~UVWCm]jm :Y`||{ E۽S<΅Gl>Ɇgºms\i⻹^'w3 \6l4܆@.}X9/;s6wrU2?E@*R*YX܎E2S{%I~"E+ z!鐑Yp^j6QOQ3n˨C?f^gx(-RUDlS%ٙl;l<±l'3ԉfpUfphl߹O a`eV9Ǧ&k xUzst/}-FZJgϺS'4?P pD́~qFzZ(yܮ33{]jz9 --4 ҊҤN4)6L`춮ZdJXBQt}UĨ42!1U:nw[F5MB3\ǷBwMDk O[X*ud>;w >Pl3u^ZaWJ} Wŏ0u10Hb/H9E6)lZ6ۙ_٭7.s-K%)6S:z)c&̽u- ]M}RWd:vCDϞ,/@? 篻Vlқfhp:t+@'`0 7%+4Ja@ڔ_s+֭!(V|ضbBJ2`|{y/t .w.<"UEsD%G->pC>WuYOo3% fMKp]P{4VzSg(*~)Ma"FjS֞7r`""C*V|}03y#ٺW P!^Hn#y~R*<CFGyVs\}>! oyKU+{7'64a-WO}ADgrISYYԹaxe+/p͏ggv௨$/{PTߓ}1cIMظ<Kao[/՟Q8?u ym=Z)6q{>_c!|ɶ):AP$ȑ{dAZWF9儞slKmbΐy+#Fi1q}Ly_|aPЖmEp5v8n&ACU9O^tol{~V ue4{/vk)p}zS(iO;`}q)0KHP!AWy߿<SLAuƎ˴i8s =z`ʔ)t`HD?도nUeޢn[Uy]po寮0luY.5uZx+߈1;9d.5`SLa~ݣͨkZ2v0 7S~eu/U۫5!4←Uev 5I*{xk=iaGov\-krQŋxW8q"'Ofڵп}W<JIA5E &%rI :uP{6Q|2Uk,rmWe`Ab2)<ثeP.xy֓Ju~Ö!yg0I,޸wLuXWZ ڢ{[W:"Y'%%7|ZlI>}uI&r-бcG}={vE7] p/VIMHSC '-WL.]@la=^n,j5H FNLw܌pIG}٧Ueݭp//Vxky%i,zOo-{ޒMJv W(.l6>CF(ݻ  Y&**>}r lJ)))wv i&$ ܐú\.\%2Μ \.KxΑqsWw/܉ pWygs؁Kl?c##p[Kq?۟%lN:/ Ϸ-IkޘO٤pA:.b^r7νA6G,Gv `Q~)Æ 4jԈ+Wһwo>LF<=߿ zNAA翐HMMcDp',qL/OqVS *J&$XLk xpt#[ACd1ljU eb}EZ. 8NXXr( &p0y.&,OXKgȟ3}:E]+{2k>^b__&e PͿ2I}lzb19}=U|.3k>yO0TYLTao'[&t.V04\ e,*Wrݡ*`I'"Ҟ@ 鑷4 2v>-}jZ 6D1:43fp=`6EaԨQ7suVFAll,Æ *e!K\X+:hz Bk *sӁ~G~~*O`]ke#I Vg.ΕSY^ '6)?\D*zpy Vr~Qrr}_TUapTRj3\]e6 a3626wn6rW`Ǭ)(8 J9@u%~S4RnЭe{˶Risrڞ@ /Ƕ\}UB/2v~NԮi<8\˰O^ j8p#K:y'5j<ݺu,Z%")Pٯ.c,l -#R^, Mfis6\a$5ZPá5~gD(ɢ=0=VEc% j{vgBc( D+vE;2J=hG7#ZqP8+ ŷ>kRt뉷+^-7VOΟt6pe7ڞ@Lj K_z DӞO6ug<]- Uɀ5QQƌØ1cnRpr^틳Rg1w6?%9lE~[d,9|rmO CiҽK`,(vl.\fN=߹zտؾ9~d딞UBiI{ugd&#WoZJq+^rV#!r(~&n;ӥ+]Oz:>mTocwe.kU0RHKK " &uah ²dufǸs Dzm|9T* Ie[7]gǡfB\ (:)QŲ kvDa!(y[TdCԒ-qROb[oX<\Jb; U2Xr)^85D'6"wC0u|J wA)OCW0va\\*5M`yD%A!njcgM$K23kx/:eU$07t=#ByOK!9h` (yWkJRuM!g]|w71]JKᛨfϘ[Q@kr2r{.=8 kXpb|W P-耎 V~ى3G?ׯN^]z<(`9ysI:&[M|-e#>`W%j5vM;\X渨eFG֣S\JsאsmpY/ x>/ҟ;d5ZMZMwqU_: :@ݽLz|caR8]ACa{?}>@ /c.{J[Ʈ2 K |5H_/hA)*fd@?XNh%$s3)h;ZrPǘ /P:D}wmHX[M^ޭ]:57Pz< ו>~-`!<K!9>'RQyyKZ٠b5N5Q]C^ԇGc3Ou W 1I; lϻ62R HZuK\!]mɥX{W]=@b? (dx_ې^שaog-iELrug^2t{"tTSlAT  %8C{mંy!f{o.j8٬rKX C ]]zcC {\Q$P"ٜ17v bԈm,Q%u1ccK-KqJ} {+'KO?"eUPzecJYkLܰYtD^ vTu=>OCVA5"«:"Q DTwlKRC"ڒveKOʁ6i]鮽EOw|CVc(5(A2},,۲gNJfqQ$ #eH8evs\\K!t ~PϡOa;+I~(`qTW%U ߝ AQ,:Du篂HH R!*'wvv1'nWrX4,8, %B[ztw~ʣ=|!ß\jyԱŠb1c'6} o j|Dt9o[3ϗzn-x5IM@BT>3]ܡ,iG+wܷ[-qE~H4I }>V냮->nEHAupf? :3\g3s߫BjkuJ\U 7&6=_zE뷌BT#RW}\ྥoυOÚ!OUn) k^UOqrxwh vw=Ng/u$[.oѝ͚0j8@%DŐPQ-;l&lo55wa-Uf\_㸗oTW);g$qDA;~ Y.L'74R G8r Y=auʯLalZw15Mg:w6]Uxo@H_ܡ'WQמIkᗻJ62Z\lfOegҕ@Eߒ.~[ a;Z,8LIvDuU;xG2(0ZZ꒍+ѱeI`GtORxe 1RӨT;!H .Pڇ'b[7q0/xag-CE˿e\sV ډI&.7sE :v7Mz}>pg*5/wͥC8+nƸ Cft{f4&EC19KppZzJfs?سCϧ9|}Ti=b.٘ (,X0$bi b? *S(QH`_gs̵;}a^W_b]y* ys.$ ʖ|9-V 6,/NOj%@Sx{YծV7o^V^vl?⬼r[gOu}6} )V9 &Jb֪}k]{SYy{?˘UwQ2Pel'fzC~/wQ'ʖ?͡:|Xyql[wd٪&H6/(b8|߰*;{%:oiϲp1c~abN'd{~6~99@Yu'B%1k>MLILe(cBz$i7p4ˆƵ/4WO P m_nJ#?;?J߲e%{jfu:Vq7%ۜX)p*S-믕* =MfJ x{6gX9MjT%#*9_*`lYI` 7gEFK}E=Vp+mV hY p}iQhN8lgp]]&)(|$ xE,}b,_^e hG X9ti<;=r&I !I fΛ?#o!A.6b&byLWI +Ğ2ٙl;~;JFu[_c_F\9pP_d֔iu؉>9pmhcSC̘)>.fU9caޖRw`Yʖ%kGɵR_5M'x&S@r'ꒉ hX8E"˘j, Qf.JMmi(LI%KURn&k܅'98j lNOi]aRUR1g3\V y:ϞŜy=L1J:ws4C@4MggF^JVPeT4R';xkg buJi}Zryjfu}7qEs<09_Ĭ0.Ae3yc<.4ʑ7/ۘ'r5 WPІ`ñe6W` 5'XGBQ_߅ .-S9/7e߄8 Q*WuZ"YL'I ePNX䥻}UN|9%`Nm5Erʥٹ[hrTR9̫T:bVgf>u2mhFQ:ݙcح7V . N>\ϰ<:|W7{E4$džfǸshYswak7gzҏ\W sQ/ lR[G=!s%FX 7lGK,)|E=;w WM*&L%hU֧K&z-z S}Wu(MD)Nc#E9 |vkϔVx[U~G܃Kw\W&Ij :IӰdWo\lڃ  <(e^XݐLFQ ^=th`~ v27]r㜳99c NnRK}5K*ı1QVc7 cmc֪}amSQg3rCf pH"؄gٙ_$qJx)EIFqӆ嶩ڶ;kބJÂF'~+QJQ #p?2-X#gd1q\~*8ǼG*4YL'`57gÁR9T':ȁބ#6x5&)nPס*zX^xEQ<|CI(IUFu Se%zd13 R|6 {Rɴú:LXzqY#X##:|?5ˏZWF9YV8aֿ,MC} vB(|GZ=A[>?mnWfc p\+ $*y UVxlؤ _g[^HHRa/aheˡK8Α@3xxl'q@ْ6JP(14T _a%YdC>J|6>u9әP&'鹠*f h,q ?S&Fgd̽t:ksoiZW?S }/*p~yzdaIQ֝7!{Cʀ& 2M8X%7G &d QG4 (پϲ kQ$ AZZiiiAYڥh *%%PQDܤN}K ĢsgK7e>l=\b=f#Ox,jV돏6|~zaҒ5@Ғ vg@Y7MJ4>6n?%10UqnDNAMyap'?0Sm%N鵰c"`WoH)˼ooߓE5~>1i۔A y/kHUZ@C{{]9i\^j}}%DJQ-jnhצ~Oӯ#?ȁބH jYin MWVtP ڝ-Lӯ z$m֝zb'Fڵd[uL}(_u> :i +<ثe0[I}z=] [(1R.\':6h01 %%jɋ0k]L=9BLŪ56^-g|vԱDIXEGKVg~2q|}:8UޏEBla=.PZRTt4>w\`6JOzz:PὛmySdh6ǍTq3U]0Uҷ-&p~XJ|vkV']|5:BS>>r#ԑD>tZplj_v 0y_?^:(},QYzXLk@Uu1_d Jt/hM9xTcA٭mr"82t&ܹL$YJ IJLF6+ޘW[9ge K 6%۝ZsU*lƮԋ2 ,?oZ ogO{x4?~WhzctX $ܟk riU8@5+ԉҷ]XnȑL+p*.S~/Sb-XoYgi:$jC}[l.hWJ #o蠸m~X+?dǑ\@B %p=BVpW֊~눺` -kOToE Ҕ/m"<`=KіO~hrѴ^Q`b@t-Wr%#ӭ~p$_I4s\mıC򦇈+,d םU-v,)5K4Y9W8]_‚K^t2(X!6>8㝓64kNn̜ m,N°/R_8Sz!9d<YA@66|1(|4Q JIKEy~z߫|KV)kc3,8ig&=?eLz҆*xy!fMJi<.<8%߳_o܏[-'Ci$:3QXY#E[*+HPlK'~y<(ڲkJz.L b#Lde; QR)t9\?CkئeySzqtÙՊ8ɪe6Vr-`K ~:K.Rѫ(`5}Cy }ჰ5GTm2wR)TU יaoQOE~Px჻l^0 \ $'dga 6ll9` Vv1g-ʓm6֮][MTJ:7>^P\=0g3$SzIjX4 O;|p NkY,:)[:"=fkK2VADT.Ef_In_: MQhUG|Qaݘ2Jl)8o[tP].gktQp%| u+*Mo~C ~Tt截M@6VǮhwt ], Q WX [G~>@UoF!@e>@!{6_C:xꟾ{&n;uK1A2yXb͘~Xn,[JTyv.]wJӭlwz} pM ҷ(p*zDNshh?9^%'+l?ƧË[>vkG,?Cϳxnt/jH|m8N}{E9z}? ?Gٹ[h []IGn*Re~Wj{ ̙3϶mۘ0aIIIe^}U&NɓYv-)))ߟ2WMX5%ۏoi-M|/r0f;OX xZ6/ano>ʣ7x=cs ;=XD o_凒bqf՜Wj/|{P#Bt"SsnuE,~gMU U;mb8 3p߿Fզ ϵ~_eaVWb¢}fUW^!553fн{w7oN~h5nBu&Mij>-Bǎycڼ phL^k՟i)?_t(U@Cbݼ ŏ%'FVf6}N‚~‹/?$/3Vo X[h4> 7tikPq|nY`ephp3w XMstڶ P23~{ ʋ泲G^a ~G~~PxD%VmonݺqӠAt;y~޽ddd0`cQQQӇ+WzfAAYYY* K*3<ۿjasF>Sܦ44~/" 1Ay(yPNu+gCޏ,`2\['`]-pq̃dmmv+zoU٢6|8$''[/99>~xƎi1>jrm88ΑKE*$9Y9|=5.<>Tb`Auar%Riηي~@X/6M㥪,:Oah<T凒T4R~+A1H;Q8 xWCz(z'xc̜(Dcj1c3&D]DŇZ"Ξ i~9y5ORO,۔l;筜y:}HUN`5kE¤[{i2Ov;#i:z*&"ѱ&rto˅% Vr|uÁCgv!m9…QrfցTR=hfޔ\lŸ H'bcǖ'ž`2A!12LSm@M֭ƍK.L:OzܞyxX,RS+~V&uXG8+& n;ST.)>MNwR?L]揈Wlc{kQ^cqf` 1Q ▾ +&P,Rv/] :3Oʰc7ǁ=ă!X㙰(˲<`(E;8;5{6سѳa֡YdjET^)yeR٣5ap/w!5?[wJ;u3Ck`X|LCST[ 6 /,X9p} t;~x^A(jժU2WZ)lhp5S^cNY:aS\0lDna~]MX8'Ei6U)燩y>?E -Q ▾ +^o7a2SeXPvHLXl<o4^$G"L6H)h>*{<ث% /=v?J9j6Ҋ(6ݻ7ſvIf^-Zŋ=l6/_N^ʵegeP熥kh5Yk;PCZb]}9{īzi=3vHE P6 (q>=[ >)~[<G-kxlw'bQ_Ab/ϪGڪ??%ѐ0 -P:ry[/DY~{ 2&Qm^z̝;gy_|-Z0i$.2O>$ΝGLh" *Z 2<+R>^Y@O˹q pNm/O)]t D 'Ԍ_Z5:B&"?26{ߣ9 GWO0+P7{GDVS]J /܉k31J =Tgs.nğ"V=9tKr_E2R-=J lz?M O%>*,+R~8#(5+(+J85tl2)K1պHL ]TP/h+jl-\`((:̈:cĥ@c| W>ޙ`؜ ڢ] o9nH)*QdGIff۝M,mmjSn/A`cgDWWOZO!?tY"SYTU]&~q,@o31o[D|Nwy+z_z4㙼hkw 5-01ر`AŎ5T敥n'@ 5.󣤜|~5NVMI-50Cڔ. -\ϟ79?a7`;z/k7fW;uL\0É`t0 34 $k]+[޹sg|ivXbLظSfՎnR‚5*KE}t23-'˔mPl(9Jb'/zT3VstkH"#L^kv2#%3izwԠ|WlKth!ImT\߈v?WGU+ m`%7?+6aZ9+SOҠ~%>fvMozsL+/I8k+KfaVt4Z;6񿏿䢃q|5? AkUt2!;S,0_tgP[~+BwhjIlJ4MIoygb(kc-1NXq3ۨM&f`C-f/z؉ ZGȾsXI,IcFDS03^V X0Y45糰+B^v.>Lj?D :y8[ z r5]n!SaB@ $ЄELqRWѵ"!L]'ZMoS_6^T>bJpKnM6[~K(VQ;2SVC;aQ:o,p Vf?pxNi֪}n;㝓ԕ=;aQ:=ßK0Gh9GZwyٹ[h_ㅷ~3>0vCm@Q-pY|>?G}|xmO)yto>EyMW֢~b>R%qjXzSQ0w9k%L}RWĕϸLIP\s-KhM6a_4~]U-, bwʭS 0cvY*jc SPc7 So3e^ z+tF뮌ڍZyiGNO#D/JFނ`Ko^~o?j&p~5m,M*SuOU H(I F~ˌ]`.ud94}c׉2 6|,?#lgzXVU* ){VRWN m09Y@]% kHEܽ[#%t'v9fkGss& 9ѾOBk#:ve08KV4Q8бpj]xExL=|HqTPK8ɵ,@#j(]=giY%GwѴ (fT 7nu<`n)@Äji*MՓrD1ĔZ-o/yq fCV,5&+;5LskaDLʱSV}uMosu, Ϣtx'-#+&%ۏ1zowmc{4#Y} 1J{ Z_B{̱YT\8(TBkb6v6́2/85.Yn&v՜1v&8N-4C)vZs@m)8є3\Q_Pk5SexVwUj6kSb ~e*uCMS6ؤ7s"+ɳ7p_%5t{wE5~[K5 Kؕ4"# 8 :¨ _u^QQ_PWQDl",@$dTI=y(]9gG>_$nWrQ&/̨=bO<Ԁ1u]AQc)uUű(8bٝ|U߮OoMjޖ6MΔ-xUh_w4H> EJA\b9Tx~&2%^?RN\yUC^jKXy9<: lˌ8'Y!+,}U?iy1U;(*q-%l}s|n to-F1~XZFG[kwsLXW׶R=@]ûԼ,*njFG[pq7* \oa]ռYW%oǪnWpfʥ^Dz,=&D|=@T|IfNZȺ:eMz/^*:涷ܚ< ?`$>+w7-s=*SLU!/}5be4k ,p|:UlnF㝓&0@ŕa3o|M4i&ӵfNSc =tJ{%`nԁA4ƫPM:Tl/BcxH[p檫V_}RPiGsC+6sA C8Fe-Nx)SBn=J-۷{)^/kR sc!H,+ͺi '=my>^Ե.R $x pb!Nb̂luƉMmƺI|2 oջ|(FJR ץf<2hNrBzbE]t.YGhnFmpH.7f{{|TLN 02#D#]Ma31;w ߛSXexd2f[jϴK:3n~5-|) x1XqsMj` +־t*%>~qGnЎǯ $h]US"eacO;' 0o==~~ pe6A};9~%`i-Z _.$EY>]@WUzZSz:sD0{ݮkG~jgĚ=^ޚvO+1[^P[eDk$'MDٸQ{RێbkO>陿2d1,Nj.u|%H@:8"~0kT㸩{m#gY(`@dE EάYVQ[J"R%)ȱt!.B?ד7 jBDY(|VElyF[|lw~|x;n$#_wՅh4\SYҽz>HOkh}rQ2Z/_&yE6W!"'a2gQvNsu]i{7U˂@G|28:oK-x or-rEx͸nQVta4 7˴j =4qP+F@ᓌ>ӫs6Z[d u1= sud\Mg:*$s7:9 ^k膦q !D$5~hI e ͦ\+rw fpgn.:Vڝon`߉lvWl9Zi Yf?AW z}e&s"s tC6?_8xԱl}:zJsHe/q7Qzv 6 ;xynoZC=VgG0(3z^:o94 {Pߡ$`*K([獋 f[^$As&U?8*ۍ!S%>u.CP)iBZ2dwV7ù)Y;'h5NV:*F)8M4SXmO( gsum@Pzng7 ;xaa5C@Qo}5o{gG0U"lQ LMc;,lP5XՄ oL,CCӠ([Jsc@ -(y*yQ*t4K~<ORn OZ>C o_ N&Z]Fׅ8+ɡҵo_ Msk>eD!ÝS&l4{WmAVEf(H<5!jgⳣ>4S\p%bHJHvJZ.v/WF%hZc7ۘ͜({(hБQIww I$uvZnN}y-tES ppN M{\A{'\g/rO׷Ws߿JV>` 2Iu=\mĢ,0{2Ӌ,RSamL!F?; p0"~h(@ٱ:%Nl 1n.KVb'♩&29cB"n%!JNah|b#vfj^kaz.rLm`)qSHMjRpw6f\Viڔ nc%J>52͜JnbUAKMt=,ώD=!j[ ՅM=Jᶣ2]9Pwh$lTs>0{?eWEnRP]jRq]dEtɨyжGvKE! 8rkv?Lc|pKmc-tsM zQ(ZLlckGМeT|i^Aĺ?.}PE)#7WM(\ZpWi/@1-M1npe==l;'L]f8r؃tf1qh'(hzώ` ǛƱH=:$`#7{ /x.-bm^?f4jSv3GzuKro>b<{Tnu>g>5rbEQjJSؓT{=Sqk|-Nߍ[ؔ:{xPi_L3vt<g@,CnA >u4i&ӵxft)#꽱7ʞ&cfB:o:-#\*&ܹA V'hVb!!J&L+dIJ6L҉!g 陿U(ͤm/w܇Xg9<:o:h4 )%5cwwNlX/T1Du6ame`vIO`l+׿4[./~c@nwL8Zg6K#;OhȤHͤ`#{1f̘Q鶔qmPJ1c ̙CNN ॗ^gO/ar,Y0-L}HM I`0E=u9+c]fJq\LuK@m>ޟ^\Mo%'ıLgnUdb6 _*D{"uE4%_R5&u;R#ZFhN^8EklXt;^3|_}Um-[Oorgo;v)s@50o,进8E{~.3 tz9^-/ vMbޡa;8>x f9Xck-SQ+w\ԅ#a"TC5ؼײeZD4w#_hZIMM-) R̞=~cҫW/ϟOAA . 'l9ZN PNo 1/1>Agw Fp'ws,Or풄@2KLxqnY#Y;k  Ԛ^kgn_c _wE֭ر#7p+{ȑ#9QQQ :k׆k |K7]ZQ\?Jtaw.3 XٰQPP;q-cݜ 4Y GQ Ȧ_8wt3OZFF0 _2w\9._R9[G*ۥZIXP' 0%fsiđk@acьytw),ped2Ƽ[!8˙VNJ+ܴD}o~ߑa6gZk\G"9SfHׅǷ:_玴4\v%Qw 4Ν;3|V%:QJU3gVK,g]H4Q6`zUA)(Q:ϨڋetZߜwSU玴4\6Xf {e\{2~x4Mcڴi<,^[2abcc7n\`ٹO+ڥpz1(K 3}f˲j |ր[H=(Ys~1_玩'HKhr7ҵkWƎngݺuo￟iӦq]wѯ_?:˽(jtӪviY/(`أ0y?۝ $٦ÔaR>%Zk{Ues!4iim!PjZy{͇iR{A KPN}WC|=C~*k/PvN3][ҮfmMLv$?[u +Go%OqNVmDLQ v ؞mjts'\r3' ^|76bjYz^ƤӮysYH'БBD&Pvgqw}F}Z:ۏ8^Ply.kAϜfy[ww=8R˫tPAqnČ[-&kƧ[xۺ)ҮY o>fu;UnZClw19=ʷ6zQV^])Dݓw#,kwV7`LYQGrQ~gcouǮʹܝ3'J44QٿPup,-}[ӦY*{.z+Ӏz&YIgOQlҕB:&:T,s^ٖÜ" dvs˭ZiG1x\+des1 ZQ}i`ݏC0MPk͘s۠ 8^GYWΚ,Fߢkb9ҕB:#C' x*Eddcӵ|Zip+s{M_mǮ1n>SY*֟%^I2|u F~;%])+R@Du<{zD5ζ}O|i%\>R@q.8| /KgUu4a!!Jߴ&?+]['u/t1'r&ip-(l \3fFĊVݷd Zqt*e*JјIFfIOk*E@?L<ɓ'/"٭$D[)>\$SfHBH=<Ύ])qP(+$Qp8,rvkJ|>#ֳfqfs)Ѿ X}TJפ+EcrQv)q,:1aHww߁K"4>W/=)Z Qc}ZlT?ؤ{v{!I VU5-#LKR}~l$J~~agV V4!!ά7zյ@)'6Cy=vyW<]~o)%{/rO6 J`Jf9ŪkLa>Jh4hV]'!F10> #\H>5EHtIN[( !)p㹴0͜ʧ@] Nx^hju_0S9OnPF׋:ߖ\$pB4&W@J8ed/;qv*_t]y #$xKrw6ESX%@gX7!T tW^_kBjՙ0 6WTap hwza {\)4.&ѵ8O+(D̿m@y'6[mBN]Yaݒ˥̟!H'W҆(›VY.I|"Β3k%K,;wFa|(`:[(v(g&hhbjKj4T &jr-8fcؚѬHF̀"TLS -\wo%|bX󂺚} (v1e Cw]%T|Ȥ=7r8c%hMĆFMXfguq̝8&qUPP¬x'OB+Xr;v}&!"ɼ"&-(ikM?HTXQuT;*^efQ})5 %v-ǰ1+Za'D8m{Z@L!د'D7a|~^3h~}IQs;Dl`Ŏ-)NOuH(`@dg<& fYEK-'µS=3SKu:dwV=E7Ajj46/gg{ëZzSf3iyfZAצ4x=i2<0^p'VoOTԇl&"ӵ|O0[˭iieΩ^*uYGL~BfTwQiw +o}3sn?jU!o "w+w6Rਹz-/U 2(7 pwV>NGF7AkzOvq['NsTVSnMn:T}*- PQ5m]C&~^6\(zŮ[?xrQf-W-OyJi[@D2 9w t &X V}L05oLS}|M/>L5*g셭Ys+>ߜ'ekuo8s~_PPxlOV˭߳Ü-tHt2} "Ƀl)G˾tCt F\޴̡[W$h%Am| mnedpT[qv !XR9 7Q%`QgӚҫp T{W"AJC<ƖT<9;+q}}Ϩ(|")=4=/:b3O Z֤kJOGdU=~Mo6ti ,`\su5En8=BY臊I ;w5VPP fqo7qr\mI1HtilY6fsu&Yc%F1.Oz+N P9qn;whԋVIAA O/)^ sVPtϪA|m8Cj)gY(`@dE'N3d)8\ABiݚ/aial#Q{ %hYcF jB[,ۋKρ=9o BT%oY(Wf?q?w!ly.k᧕dB!DE 'S.6TZiR[^ !",*m!oiЩd;3VYBiiYlG웒 “G0MŎS]'C#^S=l!~iC' Yh'iˈ;EӠZA ! )'G#J@ I a|A./Yjh64l@ %k%p+ qP@q'|AnљiJ0O#t1/-|}%8tC6^ QI1okhEQׇ~Lͭ1vv0=WhSL]7+V_IKr`߷ \ \c9bM\ ߦ#䬇;OG! {(5^g4033{˗~ZEJjUr;77,y+plYg~Z)F&:~P[1@ 0mEsp_BWgld>~CO-[Mf yBg1 fI)N(ĐG -?_HJlwuQ^jbZYf ?W \ǥlh77ԠS;yɸb??^u;N©,uģiFfFYuCjh-VCq Y?U@Hz藺IHHX0 3F/h.w D <@ji3 {Ğjm=}/ߝ@? yuģcpzB:s&M0{ؕt,`N _@BE* W =}c7[j :Lᖉ߱y<{a#N~-Ҹق%mŖԊ !k'0Llwq3@FfnPl7ihrrQMA?Cke o0 2 '#ᔹ,P](E+1Wj%N= eOuۏO?9YTT >Eߍt aKnGMBģ`aq%#5Z$R;q. n<>+)[ԖFY_< EH(y`8n/Kq-\t aU;(*FЂۭܞM91}!(D ĥtЏn AiZ/.b@7 '@.=N o; 3.<һ}X} 2hh TY^ׄf"22s8~0W[v2_"~,`!Nr8V={AfK`{yp8h^vdR\zFYM3ojJR>\q Wv[AL|taL<|">|;U.B5[[dcf.3Ȓm>ig'%S}2MK5B᣷cKyRPb2ӟy}工5w=t&[) W nW<Q5EV|l,m22_"B+w lk~p-#Zu<+ѶNf\C Lh(͂>nY:w_~_Cgt j) eD: 9ӆ;zp())4.&ѕW,4G0Ø@DaTuk,wO[NlwgU?k \!k!I BD#}XiU):c=аv1MŎS~b)gomα뉎SYu8I'" $RI\ȳt!.) Тs7Õ}e\;+Yu| *pL۞09$'9~%`!n~Mb #aD;+Z7M h⒟EmBJ@!n]0˪kLکZ=4fdr 6 c MxH>"Bᣛu1=kyttJuC' Yhh\:Uh)4~eB?P!$ "yP?/-(@B`ݼ(3cmGn҉!g^ mtk%8B:'I EB;xen /?[y> RL=|mc̳,_6~BB4*, ;gO^roU9(<{թB)ئubmBH@!h$ ^z_=]l7bg 45=SO{T͑I=@!) x7()22s*%9ykr\m{T&Tc*=:BcIBGr+0LniC+u[҆Yt0k2V QIHd>W]GY7|wlQ Q[. !Dq}z;bT:ޒP!h+_ůGYӅj(h|d B4"GvJ@!D%k kU0:X[@T޹sgDO !PB!9~KB!DđP!"H(Ba$K/D=8=!BIHdB[ !BD B!"B!Fzak-B!v$AHHJWJcѺukbbb袋ضm[x[xw&L63g'!!djvQ>2j;9W+B>}ʋ=4e˖^{.ӦMfƍwcԨQ8p CzÇl!;ۗ_|?S<쳼lذTFA^^^.Js??k֬aɬ[+V`#G$??>2j;sUmۖYf??0l0 O[-;mݺuS_4GU} 0@-^ߦiT5k֬ۊTRRzW0SJǫ*,i(֬Y9狪N)sjڴzdy gp?2rJ9k׆iT î]hݺ5;vn_ {rȑJs/**C_Mrr2g}6'N$+++CWN:@fsȜsth"4h7$ Ǐt:IIIt{JJ G Ө`KΝˑ#G"//OmܸQmܸQgU7nTWJ)5k,>#eu7VZ0o޽{͛C=t]W˗/WJ|K/ڷovJOO/UVfS[VcǎU۶m իW+R>JMMUQQQ /T[l ]AA9rjٲl]vjvXմoG\<;s5ʏ-[TÇ/VM)|B!7Y(Ba$B!0 !BD B!"B!F@!B#B!DP!"H(Ba$B!0 !BD B!"B!F@!B#B!DP!"H(Ba$B!0 !BD B!"B!F@!B#B!DP!"H(Ba$B!0 !BD B!"B!F@!B#B!D=IENDB`mir_eval-0.8.2/tests/baseline_images/test_display/test_display_piano_roll.png000066400000000000000000000273271475740344600277550ustar00rootroot00000000000000PNG  IHDR5 pHYsaa?i.IDATx}tTϐ$HLҤ(['DP.VQ\ຸ2(-"VlU qCZFChISY$w3d$:g;;wp?f{eY1]z0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ hwY*aw9,҉'vէcaH]~va eYE*߯Fiiiv:!hȐ!ϔnw9`Z>MKK#cL|` a heٳjjj%&&jllѣGU__ow)a%\bw)%`ZU]]n]r%˲ب?OVNN͞CnJOO Ę3gΨZÆ Srr堇ȑ#V~B͏@ct(>񺶏` '_~7n堗#γkZ>#,ZH%%% 7ܠ]z饝Zʕ+]@b̙3uQ>|X۶mOSwz*]s56l222"1`? 1tr/W^^Ν]v/..W\~iȑz'9zGp8z%I|ΝK/Tur-7 YFn[]Z!ǣ?<8OCCVX!Ct*''GzM>]_o+11QW̙36P7TZZJKKeYV۽{{n}ᇚ;wƍ%KH,Xr=;vѣ:u,YB>}Z=n6[6G ߿tIRaa$5gIRvv*++@ .Rbb/%IzgէOm۶-X О={'IJIIѶmۂ]zڼy4rHp z7d|>*--յ^+I|[lUW]g}VC DĠӧk˖-׶mtRORMMoG$ٳZzި3gTUU?f̘˫uvQF)!!!x?++K$׿VBBNzv*UUUA)))W"Iz'4}tZJwsO0!d|˿K m4hPv#YC͒ ղٳgkڵmjwYG \Rfҽޫ/}K:tN/UW?ܥˣE\kcƌQssʂÕHt 80m45JzZf]>OWqqq;y睺t7T]]2{|ֆ jzWT]]={_t;C:]vi 3B@<[Ӷm۴}v3FSNە}eokС3g -^XOnwd/ηe}T~~F%KԩS$ۭw}WMMM4zhJOO皿rXe]Djx60@:s挪~I L~ ď!6T [}d0`e1ދz[-RIII]wvÇײe˴lٲഹsr]}v-[L}YԷA3gTqqq4Ѻe!F01tr.RIСCt:v|G4m49rD˗/#`׫qgСCտ{jjjҺur4x`=!5j̘1JIIѐ!C'OJ٣K~?mG?b }K_RJJ&L={Dw@jÆ я~QFVo$I/Ǝ[K,iw=UUUz״sNUUU2ݻW/jĉ>}'U]]|XBO>&O7{<(Im.>|X?яv/k̙ڿrrrE ⡇RJJ\.ZWC__Irf=JMMՕW^ӧ>}_֮]={`fggӽޫ'|R\rp8B]UU,-IzsN'vC M>][l 6p@:uJ7nԗe͜9S_fϞĮL%$$O>!wޭUVV*ٳ:sN:/)˲2A]G}/NJ}&IҾK3r; A-._X>nkw/NNQgǧ͓ g%Iԟ%}V!'+_JUZZ7xC7o߾^:Ӛ%IG_oz4p@;ַ?innVBB}%$$O#rYz+A4]IJ gϞ /ZeeeiѢEwDeYZj~i?~\&LPQQFeshKHHЀTWW'IJNN᰹*teYW]] 8'nڵkSODF/~ u]JOO/IZn }vj՚1c<(]pp\  h+n|7*33Ss@۷o#xkSO=%ϧ\7;C7JU[[2NSSN޽{544?@%$$Q!ȑ#&=;$I̐233uȑ\fVZmZ1ZFdH^oW>ܵ/t;E;~O-Eiz?DOZinnehdQ܇-ǂtؕk~wtm(IR5{Z >.{]9fq+;v藿JJJ_%%%!_˲.%~X~?xZ#.I3f95kh…/BE]]]QNSN3DQ܎۽HHHPss$);;[.KUVVɓ'j)nGgϞ\CըQ_JZxs.[LQNN y\=@mܴi_E=ܣ}{yVXӧO+???z׮]q-n`jj6nl땗_w^^ $TTT&|>;k[8=8@ C0 0@@u@'l(ICT^u,ؤ!Zp% >M|nS"8o/[>iv~ڱZzY˾ x 7l`<*++UQQaw)]F0 0@ C0 0˲,5|>~]VZI#2Iuzko#LԺ_Wuo`Olo}zt^'z&F*گs㭗y?cZO@ 8G # e@ C0 0@ Cb@p} @G!` a!&bQ> >M|n&bk[=h_O^-z/4wW۲lOv:Vzf_H*:f[=tzU^u7&{KZýn#1f]b0G.#` a!`eYEĚ}}>~. R^vP:n2 a!` a`z׫caڷ`iV|Fnh?,zcm(is=.Z{g䶿|-_}z_^K6U߶p_;ɾo^W}eӮuc"=f|u1 # e@ C0 0@ CZ.$>~]ok+lScצ_OPF!ڝ/pj/5{>"x>d0"` a!` aH bo>00q.x$Iev+))IӦMӁl 6VTTѣ[ii$[o$[Nڼy***r4c 8qβ.nArW_}U#FԩSeY6nܨGyDsѣURRzر*n`kŋpZ t:5uTݻihhP ĚD >3-ZHT[[+I /33SGz֬YUVENKC[p'I.asx['\ k^W6۫']]Og kΐY-ǃ=>}ߡ #Fy͚5Kn;doYVi=[MMMT~. tB Pzzo`7p{80q!` a+DK>Uy1IҾK |P uf םy&>IGR{OPT]s.E/:͋AZ[L!t֛5_zn{RlON=}(Zy[ F#xTYY K2 a!` aqXe]Di+--@'}&v7` a!`D E" >M|nSȴIoܽ|6.z[i߂sg\;JLWkiuǣ\c6;6wb`<*++UQQaw)]F0 0@ C0 0˲,5|>~W׫c!"Gl]d[߰kX&o-޵un ?ۈ2 a!` a`.>H bo>00@ C0 0vZ4цR_igPI|9O/ ;}҈ bLu~~hy^ט`<*++UQQaw)]F0 0@ C0 0˲,5|>~]@ tn p#` C0 0@ hwuhP ;}n눆NM=h\uuFg -}Q[g5Mi, '`<*++UQQaw)]F0 0q?222q>nY^n4m48pƊ/n5eW*++~z 0 8ϺuTXX͛7B.K3fЉ'+ Wk׮Ր!CT\\6|ߖeiƍzG4gIRII233cs=]2@'׾[oUuժU^^^pԩSwްlhhP eYEDC~$IDn;w߭#G_oN׫UV'қM&h;;!_vz8$(==w܎677몫RAAƏ{GK,і-[Bs8!-j3?,D~h+2dW\>Hr$I!)333:NBn&n)Sti>OÆ $eggr4xcc4y^7/_ɓ'@v{==z%wٲe*((PNNrrrTPPd͛7'nW__~Y?}Qeggkƍ;XBOV~~? &h׮]JMMr(I7xn >p8zt q@}HEEEjjj3>n p#` C0 0@ W}ԧmp} B5uϏI#2$F0ǣJUTT] @ C0 0@ C0ò,"bM>>O~_iiiv:!(==78=8@ C0 0@$]@,j`KN4"^oT'IZ>#y:Lz~Ssk|QG#x#DWU"^?'2XF0 0@ C0 0}jwt\nP>=} %YG 8aqj+z }}@,#` a!`F>.C0 0@ C0LĢ}eCO2m߂!m_+ūIojgNzU^uܺFdy f`0G.#` ^W#r[%+ۭ$M6MbPFGo>n:jͪҌ3t +r\۠A$۸qy͙3GGVIIc|nuСCj*///8ԩSw A@ keYv 땛?Zz~:xLO>Dn;w߭#G_N׫UVzN Pzz5kn3F^{~IJJJ8e,j3~X~?xNQ|)))3f>ுkkkC橫Sfft:r5wSVVrTZZ|QeeeoRI= >I6l|=MW>}?iDFNkC/~|'׃#x00@ C0 0+W_mw)]Fn7#!` a!XFn7#!` a!&bQQQdw)xXagyZיy:/mK;^W@Qee***.!` a!aYewu@'߯4n @| ` a!` a(**ҕW^R>@!boFC0 0@ C0LĢ"ٳĆɝ  bw 555.nhnnp]N 2djjjmi'bbeĉrop7sIiiil#b}n۶/f^ CmNV\)iw)Fbۋo/}~`F C0 0@^Gr]Vz5{ln9+![%+ۭ$M6M8_hQĉ)6άYFW_}RSS5x`}CaQFѣ.)n:uJcǎ͛>n:jͪҌ3tĉ^4>u%i̙!Xa*++Ѿ}TZZg*//ON =ǿm,\;veI/777[.3gXSO=eCoYpBoY2˲8{߲8 lv+;;[~:dwIFVmmӜNN{XY٣+77WK,Q]]%%/I8p$voo z݄ s_֭[U[[ɓ'رcvfZIRfffcYf^[o׫B7K+e5\ѣGKMoD yf͚{̘14iF=6Vf.r߲6s =zh}k_ӰaLs̱r}鷿y6qG߅?ǿ}RRR4f}vb__?QWWfT#++KÆ Ѓ.]'ڽ{.tq!v ~,K1Nvv\.JKKUVVɓ'X;=,w}z饗[o);;;qh{ٳ5tPi Zpݥť'O? ޯ֯k 8PCղeTPP䨠@ɚ7oUǏzu-(++K??.Xu|x<ڱc[t%%%ppGQGɓv'0ܹs,o߾̙c8pݻ-Imn .,\++WZ.r:__[ﷷ8AY}j-\裏.;.<ò,7'w C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 084Ƙp,IENDB`mir_eval-0.8.2/tests/baseline_images/test_display/test_display_piano_roll_midi.png000066400000000000000000000273271475740344600307570ustar00rootroot00000000000000PNG  IHDR5 pHYsaa?i.IDATx}tTϐ$HLҤ(['DP.VQ\ຸ2(-"VlU qCZFChISY$w3d$:g;;wp?f{eY1]z0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ hwY*aw9,҉'vէcaH]~va eYE*߯Fiiiv:!hȐ!ϔnw9`Z>MKK#cL|` a heٳjjj%&&jllѣGU__ow)a%\bw)%`ZU]]n]r%˲ب?OVNN͞CnJOO Ę3gΨZÆ Srr堇ȑ#V~B͏@ct(>񺶏` '_~7n堗#γkZ>#,ZH%%% 7ܠ]z饝Zʕ+]@b̙3uQ>|X۶mOSwz*]s56l222"1`? 1tr/W^^Ν]v/..W\~iȑz'9zGp8z%I|ΝK/Tur-7 YFn[]Z!ǣ?<8OCCVX!Ct*''GzM>]_o+11QW̙36P7TZZJKKeYV۽{{n}ᇚ;wƍ%KH,Xr=;vѣ:u,YB>}Z=n6[6G ߿tIRaa$5gIRvv*++@ .Rbb/%IzgէOm۶-X О={'IJIIѶmۂ]zڼy4rHp z7d|>*--յ^+I|[lUW]g}VC DĠӧk˖-׶mtRORMMoG$ٳZzި3gTUU?f̘˫uvQF)!!!x?++K$׿VBBNzv*UUUA)))W"Iz'4}tZJwsO0!d|˿K m4hPv#YC͒ ղٳgkڵmjwYG \Rfҽޫ/}K:tN/UW?ܥˣE\kcƌQssʂÕHt 80m45JzZf]>OWqqq;y睺t7T]]2{|ֆ jzWT]]={_t;C:]vi 3B@<[Ӷm۴}v3FSNە}eokС3g -^XOnwd/ηe}T~~F%KԩS$ۭw}WMMM4zhJOO皿rXe]Djx60@:s挪~I L~ ď!6T [}d0`e1ދz[-RIII]wvÇײe˴lٲഹsr]}v-[L}YԷA3gTqqq4Ѻe!F01tr.RIСCt:v|G4m49rD˗/#`׫qgСCտ{jjjҺur4x`=!5j̘1JIIѐ!C'OJ٣K~?mG?b }K_RJJ&L={Dw@jÆ я~QFVo$I/Ǝ[K,iw=UUUz״sNUUU2ݻW/jĉ>}'U]]|XBO>&O7{<(Im.>|X?яv/k̙ڿrrrE ⡇RJJ\.ZWC__Irf=JMMՕW^ӧ>}_֮]={`fggӽޫ'|R\rp8B]UU,-IzsN'vC M>][l 6p@:uJ7nԗe͜9S_fϞĮL%$$O>!wޭUVV*ٳ:sN:/)˲2A]G}/NJ}&IҾK3r; A-._X>nkw/NNQgǧ͓ g%Iԟ%}V!'+_JUZZ7xC7o߾^:Ӛ%IG_oz4p@;ַ?innVBB}%$$O#rYz+A4]IJ gϞ /ZeeeiѢEwDeYZj~i?~\&LPQQFeshKHHЀTWW'IJNN᰹*teYW]] 8'nڵkSODF/~ u]JOO/IZn }vj՚1c<(]pp\  h+n|7*33Ss@۷o#xkSO=%ϧ\7;C7JU[[2NSSN޽{544?@%$$Q!ȑ#&=;$I̐233uȑ\fVZmZ1ZFdH^oW>ܵ/t;E;~O-Eiz?DOZinnehdQ܇-ǂtؕk~wtm(IR5{Z >.{]9fq+;v藿JJJ_%%%!_˲.%~X~?xZ#.I3f95kh…/BE]]]QNSN3DQ܎۽HHHPss$);;[.KUVVɓ'j)nGgϞ\CըQ_JZxs.[LQNN y\=@mܴi_E=ܣ}{yVXӧO+???z׮]q-n`jj6nl땗_w^^ $TTT&|>;k[8=8@ C0 0@@u@'l(ICT^u,ؤ!Zp% >M|nS"8o/[>iv~ڱZzY˾ x 7l`<*++UQQaw)]F0 0@ C0 0˲,5|>~]VZI#2Iuzko#LԺ_Wuo`Olo}zt^'z&F*گs㭗y?cZO@ 8G # e@ C0 0@ Cb@p} @G!` a!&bQ> >M|n&bk[=h_O^-z/4wW۲lOv:Vzf_H*:f[=tzU^u7&{KZýn#1f]b0G.#` a!`eYEĚ}}>~. R^vP:n2 a!` a`z׫caڷ`iV|Fnh?,zcm(is=.Z{g䶿|-_}z_^K6U߶p_;ɾo^W}eӮuc"=f|u1 # e@ C0 0@ CZ.$>~]ok+lScצ_OPF!ڝ/pj/5{>"x>d0"` a!` aH bo>00q.x$Iev+))IӦMӁl 6VTTѣ[ii$[o$[Nڼy***r4c 8qβ.nArW_}U#FԩSeY6nܨGyDsѣURRzر*n`kŋpZ t:5uTݻihhP ĚD >3-ZHT[[+I /33SGz֬YUVENKC[p'I.asx['\ k^W6۫']]Og kΐY-ǃ=>}ߡ #Fy͚5Kn;doYVi=[MMMT~. tB Pzzo`7p{80q!` a+DK>Uy1IҾK |P uf םy&>IGR{OPT]s.E/:͋AZ[L!t֛5_zn{RlON=}(Zy[ F#xTYY K2 a!` aqXe]Di+--@'}&v7` a!`D E" >M|nSȴIoܽ|6.z[i߂sg\;JLWkiuǣ\c6;6wb`<*++UQQaw)]F0 0@ C0 0˲,5|>~W׫c!"Gl]d[߰kX&o-޵un ?ۈ2 a!` a`.>H bo>00@ C0 0vZ4цR_igPI|9O/ ;}҈ bLu~~hy^ט`<*++UQQaw)]F0 0@ C0 0˲,5|>~]@ tn p#` C0 0@ hwuhP ;}n눆NM=h\uuFg -}Q[g5Mi, '`<*++UQQaw)]F0 0q?222q>nY^n4m48pƊ/n5eW*++~z 0 8ϺuTXX͛7B.K3fЉ'+ Wk׮Ր!CT\\6|ߖeiƍzG4gIRII233cs=]2@'׾[oUuժU^^^pԩSwްlhhP eYEDC~$IDn;w߭#G_oN׫UV'қM&h;;!_vz8$(==w܎677몫RAAƏ{GK,і-[Bs8!-j3?,D~h+2dW\>Hr$I!)333:NBn&n)Sti>OÆ $eggr4xcc4y^7/_ɓ'@v{==z%wٲe*((PNNrrrTPPd͛7'nW__~Y?}Qeggkƍ;XBOV~~? &h׮]JMMr(I7xn >p8zt q@}HEEEjjj3>n p#` C0 0@ W}ԧmp} B5uϏI#2$F0ǣJUTT] @ C0 0@ C0ò,"bM>>O~_iiiv:!(==78=8@ C0 0@$]@,j`KN4"^oT'IZ>#y:Lz~Ssk|QG#x#DWU"^?'2XF0 0@ C0 0}jwt\nP>=} %YG 8aqj+z }}@,#` a!`F>.C0 0@ C0LĢ}eCO2m߂!m_+ūIojgNzU^uܺFdy f`0G.#` ^W#r[%+ۭ$M6MbPFGo>n:jͪҌ3t +r\۠A$۸qy͙3GGVIIc|nuСCj*///8ԩSw A@ keYv 땛?Zz~:xLO>Dn;w߭#G_N׫UVzN Pzz5kn3F^{~IJJJ8e,j3~X~?xNQ|)))3f>ுkkkC橫Sfft:r5wSVVrTZZ|QeeeoRI= >I6l|=MW>}?iDFNkC/~|'׃#x00@ C0 0+W_mw)]Fn7#!` a!XFn7#!` a!&bQQQdw)xXagyZיy:/mK;^W@Qee***.!` a!aYewu@'߯4n @| ` a!` a(**ҕW^R>@!boFC0 0@ C0LĢ"ٳĆɝ  bw 555.nhnnp]N 2djjjmi'bbeĉrop7sIiiil#b}n۶/f^ CmNV\)iw)Fbۋo/}~`F C0 0@^Gr]Vz5{ln9+![%+ۭ$M6M8_hQĉ)6άYFW_}RSS5x`}CaQFѣ.)n:uJcǎ͛>n:jͪҌ3tĉ^4>u%i̙!Xa*++Ѿ}TZZg*//ON =ǿm,\;veI/777[.3gXSO=eCoYpBoY2˲8{߲8 lv+;;[~:dwIFVmmӜNN{XY٣+77WK,Q]]%%/I8p$voo z݄ s_֭[U[[ɓ'رcvfZIRfffcYf^[o׫B7K+e5\ѣGKMoD yf͚{̘14iF=6Vf.r߲6s =zh}k_ӰaLs̱r}鷿y6qG߅?ǿ}RRR4f}vb__?QWWfT#++KÆ Ѓ.]'ڽ{.tq!v ~,K1Nvv\.JKKUVVɓ'X;=,w}z饗[o);;;qh{ٳ5tPi Zpݥť'O? ޯ֯k 8PCղeTPP䨠@ɚ7oUǏzu-(++K??.Xu|x<ڱc[t%%%ppGQGɓv'0ܹs,o߾̙c8pݻ-Imn .,\++WZ.r:__[ﷷ8AY}j-\裏.;.<ò,7'w C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 0@ C0 084Ƙp,IENDB`mir_eval-0.8.2/tests/baseline_images/test_display/test_display_pitch_hz.png000066400000000000000000000717461475740344600274330ustar00rootroot00000000000000PNG  IHDR5 pHYsaa?isIDATxyxT%=$"("eqP*jUjVV\mJTDPD@,$̜3d'dbs<̹~64MIHW@DDDDKHQ("""`$"""" FHQ("""`$"""" FHQ("""`$"""" FHQ("""`$"""" FHQ("""`$"""" FHQ("""`$"""" FHQ("""`$"""" FHQ("""`$"""" FHQ("""`$"""" FHQ("""`$"""" FHQ("""`$"""" FHQ("""`$"""" FHQ("""`$"""" FHQ("""`b>;w.a0k֬K.0nGtrUWѹsgҘ6mv sEDDD UVaÆ{n,X 8)))Yfkh":uu]ǙgիZ-:eddd`ᝌi6 /G}ow84oqq1穧bĉ<ٓw}O?Euؽ{7={lIHܹ=zD̙3938qbڵ+:t`ܸqqtիWSUUŤI2d+Wlq233DDD$JJJٳg:b2\h_~%Vj)Spyѻwom-©իq8Dǎ֭tt:KKKT(""cV;wꫯfɒ%$''7XfC ㏧w޼{iM1̝;n1q2bl66+V`x<ͥwlٲ\.EEEA ֭[Ǿ馛(..vپ''"""1N0uֱv /dڵ ݿ?;w$77#F`YtiL~~>ׯgرp{+"""*暀3222dHж4:uĐ!C(++cg?#77۷s7ӹsg~ӟe]u]GNgСQ4MnwIMV͖}GDD$\ʺux'9x r)L0 xp\S^^n)!55zK4M3ҕU%%%deeQ\\\9eV+]t!))I8`&.{x߿N"*"~'F ˅gϞF:ҎRRRرhthE);H,ULDDD$(o=z4{챑ԢPK0 0lՋ/M[IKKcӦM{!H&Ô plܸK/sϵh[rgлw6riL۷K8s;w.yyy 0U 77N:1sLj$N'7p={pпϟx~ƍL:tuE]ľ}UB.+jo4SPiTTE y5k0c ҸgĉL<믿t9S8餓loc|ׁL{Gff&K.4l2rssYl}ӧOceƌ׿O>ca۶m/??q1c ͛GEEӟ8y^­lh{6@ף!IS7H|SFU;a?ƿNjR_t<̛7o{s=}qFsf#==q, =X ]`:t`L4 -cױcGz!V+ 3cƌl޼^xK;##pq1gΜ={y@&Rb@ұm~u_}Dڛ']s"-Pt)#P^^c=͛ꪫػw/;w. dn7YYYիd֭C _nn.֭`ڵXVƍhݖ-[Fzzznݪ0db20[f`Sh9| (ne_Oq[+--#<xSN9n+55*hQz1gys]t :n[nf^bhqYgq]w{.77}EDDb02 M[oeʔ)\~tޝ /wq駟c=… :t(ƍc…x߫T>zŹQGť^JEEEW#<s  Č38tyyy|x<N?t W_MVVM$?MDaJĪ(..TVVm6Krrrj(73@DbCSD􆈈HQ("""`Q EDDD@PDDD$(I0 EDDD@$r .C)z. èw򗿰i&o~Yhyyy,^ɓ'n:./GL-'"O`8UÜݐ֪]^@UOiii0qDv;z'? XV222i^/?8}ќr)lڴ7|뮻X|y 5kV`}rsDVVa{֭}xܭ[7V+%h[aaae˘3g7nMee%"-/4M tҩSVYDD$^( '{/RZZGydlڴKrW+V`[^:e hp`ǎL:?~dggGqeQUUq^/VիWcZI 0ZRRR6mӦMc̙ 4uqqǑic~n@^*б㡰N:%""JN'Al6:QFSO=EJJ {|M|/p8tܹ]ӯ_?n7> gu1׿Ӈ2{=9RSS0`^x!{>|8gСL:]'q@ H40Ҡ~ܠۉ'HxG96lZ?_WoN~ҥKce޼yu] 2gys;v,>}:]t`׿cL6>={[DDDbaJJJʢ̠*++ٶm}%999B5P>;x0rHڈH5uN$"""" FHPDDD$(I0 CLWe CzYDB}mw"""B+jCahXg&ҡCz !%~t!J4I C0 rssڵ+UUUݮ̟4a`Z0H PD6M#" @HQ("""`$"""" FHQ("E$(I0 EDDD@ܹs1 Yfٳ#%%dzaÆN'W]u;w&--iӦk׮0^DDD$b:\j6lXロyCj*rrr8(-- 5k/fѢE|Gqgx}""""a`YY^x!>(;v l7M?Ϝ{ 2'xr}Y?>s'Nd<Ӭ[w}7R$"""1Μ938'm߶mL4)p0n8V\ ի *ǐ!Cet:))) [+-/dժU+(([nAۻuƎ;e2eoܹs"w%yDDbXewW_O?Mrrr:'4m27tŁΝ;[Wyoᑱٿ#]%9 1^BFffb xl6[ W7WXXx.''EQQQep8 ĻJz=ʄ2"8b.0a֭cڵυ^ڵk9#aҥ}\.+V`ر1T&??ʈPY¦]j qG:"">b`FFC ږFNg͚Ŝ9s߿?gΜ9re]u]GNgС$u/Kqps҆s`Kp TTTpWPTTĨQXd 2{/6? &L… ZHfezH3L4#]XURRBVV(_7y\Y~p0ڈH}Ei|U^r ; 7|z7 V7X&P$]O+u|w~~P KܾP$=v^Y̕y,k~ٞvD"(~}Wjl{/=:n'p1l~ GȈֽnׯ۠d{QyHx)(N/~⯘Ɏwg>zd@pOJ'zz{D@e&ޒmKh|&5%M>_~d5Kן漝nls6&`uFyжwv9F3={0 KVD2"1j߾F;Ҳ]1c ?3bM~iQ(*P= z_ishڣkl=}HI @X&`UU Z{ҥ2ZGҚyS/aT5mUS `}USP$Fy!kaPnY̰6ZGo{rxFnj?RPD$)(CֱL<<[,6 _Zx6w*sA`s=Q?"V;`t>]쇚.[XosJR 5:5(KE ЫݏW\&` H|ѱfePߗkgo EbT `Bv440 EDbEboJfJ@pND$q(Q)_h) QPD$)Q @""NHJ` SM""CH,2MTCiHP(5p" w+N!mt-sj3Ôh^a9$/x ))5[Ġ*hڰYtic9:Pwj^R(@ÆƾkY@5HH *辴+"1})܋x Z*~UE czܤ@ AQ(@ o$@iW‘pH 9T@ /uM#j2m>gtKCjx+"N^)A^ o[ㅗVġ&`d@,ĉH)AH|P(*߿H(AM ED- ӿ<PD"k6 ۝.8"])EneE$NY5C]8(A5MIH;~!ln 5":Tâ/L"@(ۏ@D$q(ApMDD$)A}IH)AO%V{Jk"-(!W4 L)A6wGZk"Vo?]<ތtU䆚&A6/hS(R;?~ItOC]pQP$UMQw۱>I= mmߡVF)0oy?t3{׽}`rz%m%[e["]i']m/8X/";t^o˲OI2QSx#XiWI}/"XP$=HI~Ieq@G2i⎂k!gîxPYҴ`mDڗD"Q(jv4I(&en;mY|}~/WZrG> ÷ }=F&A&Tb2|G6ldff2fz\r aFNΝ;ƴiصkWOE'[QAͨҢ=MtdxHN y(мh?_v( , O5טl]u;A^Ѧ[+D& nC.&=zpw__pꩧrgaÆ@ɓ'fNfb,Z>2|8O?4֭w[>Spu8>豫d/oN=(g+KV{۵e廭E;57/{'t{pY ؞|'v\ZF]-DXXzkfWiMy]"콜^l378ͭPGLy<-ZġC3fL`ڵ+ `ƌ[z5UUUL4)-//!Crʰ_[BbTO);^[8|PԈZ +$ex7|+62n:%]wW[}.M•hKMp]8m *-.m׺HWd+Yv28e*\ \];S<?bv%u1f*++IOOg}L2;޽{m6nN=TV^ᠠ$:vݺu&8ӉYӷѲ"- SRCX6nW1C{dQR|ݻw3!Tb#̰֧:款^+snot?JyO 7=Cq+LfƂ)=PSF2qx%e:ǟAAevEn>Y%?|MQ @J:!3aG޶rbϱP8_fӎ @Z=/.ίOD[{$^ `x΢eDbAdڵ~Eߩu#dsq.-cAvU9֚~9 nހ{w |nl: |,p_n.k`772DB!f8#9;w.s esssݻ7[2 999\./t֭ctMn;wldAe?Ǘx2eacck_{Robz\_~\ ,-7mwJw<_ݙ"|Ayk/}/_ z 2q凟2i`B%fL jmܹ\Fngҥ2_c6z z&r8 /3xzd;%7;ueטb nC_at'Ra|sݦkkPGx۫.}TPVHRfo±ꑠmk5KлuOwP@OC-&ofLBϞ=)--eѢE,_~2fϞ~3rssپ};7|3;w?)YYY\ve\wutԉlzĉ#|vH&%ӚGZ63R3 5 < |MXqaOzӲ=fZ]_uMsԊ;zC P <^le k WߓaS-/e 6w26a/\b2ܳg]tdee1l0~mN;4***XnO>$$77SN9;{/6? &L… ZMY}YYس{;"8tp/~Gfri+^l=ñ:uW)l|fc/"IC\wFINWf@1l<n͔+eJ 5=JH3dta~tcO~t׌:6GXhݞwg-s(+u,.%mG2_b2?~ϥ;4<PYk2#-2` ݻE9}g0!{O-x( )eFT"d j K4+&etjd<#"RD XQ-qCH0jLhYq{s9dHA jJP(A@ز `᪹}#]y5rPړ?4 "b$-&5k̦%Ef ן 8k!tlHh[G҈ZPM2.whHxjy-ڼ9Y- ی`ɿȱE"VV"u_,ԔOͺ- -|kW8a+a'BboT*CN{jv*%"5?<^ -eE)H6[+F* Zsӹ=J|P()fM&@ @yP$Rj6zcD M!#ujP$RMnӂͪ~/"QV&0Q()A ,+j0$zZ8t/WHtj@D??˾tU$&h4&(T09 Qh_oK}1;wRi`|nEbw%HA j RWrڽNLJ ^5D?40D(tŗ#rS/F!{(V45 w{$]4PX'k}_~<ٯn`_}ߡKb(T= K&c <,+ E@SHԫx +jNZܻ፯)*?!. Pu*ْeA]7 ؚH(|WX5X@" hŞ7 뱋U=jN\kP4`^v(lxMZMM)F`[jޖf?{6辠M9mJI3@K7O%#T/ Ay5?}_7ѷ% >}3J@?Z+ yH?3EsX_<( %}C[{&6 Y5)*/Gԋ6bҮ PM+G3b +fǃ׹\ccq/^Ʒ7"_֯Qgp݊YwJy`_~LYBN`f.j)TR/,i7XG ^e0B;}]#|+U}oYCgfqȆg\S6kˮeٞsnvbn{X=W%4a}\Q5%pwc9 ;Qz@h:~/4OfO%;IK*9-å `j % [X6zqvÿ3}UX]ms蔦kR4 (dF7t1{#cؠ֟a`q$X}OMmHKd_w9OtdkMpTҝxQKIruu͋tYBR߆t}e-FMa0Jy5x0nr[Z0YL_h(-I :8v<0Kg#8YpZ:̣΂7-(]WTFK 8JMÛ z&x=6䬆QM:pl:qWj.hg2 Cf@Ɵn=^ `EQ&` Jr <=`+P3CO82p%?v=Qw( }: ԔK '\ <[ _Wږig T7҆bQwԭ6*8ZF/j  xhVܶ4UoxX:2q{ˆfP^oC0<f =fg[^O뻟ٽLuVv{~<> i(T@/I/<]SYXi} Kxw̓}eRNiY0 .nk*tB5;1R:¤[v>'^_Bi8μ0p*d#N)3qvAF7ʸ]HMjiI}CM(Utv5 .0sYR0Jt/p#5P{zx%1M(-~23aQ@7'[-v("i\X0|) IR(- `n}ujr*=IOd0~`צml J;] 5Ǖ>&,5*l;'& S73Q,Q+&3<Æ #33Lƌ[ox4MfϞM^^)))? 6䪫sΤ1m4vUPlBeo+Œ]4#f|g}W@5%+ Ϗ-eX};MߏEF2qTdأGN N=T>@ww3o<z!VZENNv5#Ϛ5ŋh">#83xcd.oΩrA[o;XɑhGճgr7qBTn4 Sԉ85ת `<bԩ 0pwΧ~iw}seȐ!<P\\{8q"Ç駟fݺu>;d.~FuhFG  ss[j_:HߛdWuծ0*GM'8 $Ã֒j-EXsv1xXhb̘1l۶&M(p87n+W`TUUcȐ!2 q:B%n?Xln>Uq5 'YOG?~8в9 U@R 81zc=`x~d/sbϑ礦pUUMN7KDճ ֭[Gzz:?,^>ݺح[s$%%ѱcF4dܹdeen={l糪R UN_) 'ˮ Ow6n4}kV}y)/5fX˜.)NJeSlUT=`]nC0 L,xaj.}@p,;='?,uYv-~)_~9_|17n wH*a}oYtK/^׃߯GT$+] Uf. P`W 3QaSH_lđGܹs9c+,, dsrrp\5Z!#0*IzW֜wUyq%Ccݮbt_x06fy ppCd:F[W5ݿ4G,VKi @?K>EgjiMR,|qNׯZl|).[Y-y)gm!žuצ;sSm_AJ 3j}XY'.ݸo} {Y|X<ksE\qFZ47\ZlÜQ=F=TY/ek\^xM MF/؃y8 ̃+.(+-V^Z~צwYp-i]0IhCx ~u]3sC~Dӷo ]] Em>GIVjnf0%:dg."bذaۜvip TTTpWPTTĨQXd 5#^l6>L0 bFǴ"iIm-Kqܕi/6J)7|M/~Zes;²w<8lEtUYMw!oXUr0 kPYk4ܯ)P/(^lQ-TUy(豥l.v(eg)lUI6-8Hti-x3ӭp{4Þ PGNhU?($]ܕSq$ȗ7M^7L}L G /ô&aU_乾CILGW^k*5 ϟa0{lfϞhd|A|v][-|td)X[1] pdy>f(z:n`Ox,7@/M!rMz$ndf^}6hާo.v.;ihŁZk*[j Ts`,qp}38,Ox.^D6@ Ta#3Y`c;PvuU`= 67y#Oݻ䋠TpǠmC{H)y\6߼yrv+߰kohOph):qrnp`nW}Dq/G],f߾BU-`[׆QTꫳ۰ H:n8p#bNu.TU?uEpǾ꫼f3eBAU@񁽾Ǖ%PY«61I3j*Jа.Z;(Y|$"^[WmEr|? e8HYAz;7-1_f麝u~Z0y<>j~"-@iEev 'n}vs]f _j_͝[@xґ"솇ޛ 7o|aw̯p5' 52ׂߵ7}"-q{\/Z6OWnGi|ԳX0&dv98޻%ߟOg듰1] =Cգ-k]xGc=xޤosKl23˾Y" 6\EjX~E h#[g6Y\S~GsK5{_Y/s t.ɮØ^+>'^pG3%kt+5e;-m?D5{oSJu8ggGm㖷~Mi!ݳfZht OJV/i_Zb~ye5ƙ:?2޺Ѳ#|eV0yo[:gAܩ]4odF|mT+lp j6>Iؔ2/|p9W>Foo2>zé)ТcqSu%7V qZ'~My ؒoVVhs}=A>uv4靃aI42[>q\뱧yX;LՖ^bGMn%c Gx3HЅc G>D$ߴ! y~~cG=7uHr7ώ VRP6<6?5ݦotoQJYrAG]3N[!6M/J`Z] ت 9ֽYBaUi {Zμ۠m[Lw}&/d]ʵ@?rHڜIJ9ͺ:\ `G N][8o oJLHʀ|aFyvVkM)w c$ؒ}M$,LcJr~mnڵїؖVoەݟO#{^_CeeEF%}8*7L/7ʷ97'9 ҺBn /KאRIͥy ?r9'`\rB_} \;9> _y1zap͟;.qd}&+&khŗ$kt̆xSg}+lPDrޱY?Qv/5OaVRSӡSpБՍΣqqt]vtw4=m"ٻ&0 'ɑLUbo޲ƞ @XyFڟ#%x-+.՞l'3NdVy"im_Кfa~mi{ ˳fɨslH3*(g.;~f! Vybpx.﷟䓮ò7LC@Z;m$6j:k{MN'&MVbځ_.!;}fgpvTn&o;O<6{Ob$ze2gK!El$lnGC U$’RK- h<בӺsΨ-kڬk58~oy7h b@ `\5K%\X 㨠lHK/FbR`=v戃xҾ'3r(<J&Z}CGO%&_}+nJ%,ܘWFRjU+ԗ1\JLj&6 P"ҿޏR`4H5V(EĤ#\͹VxUbe]@_t?8Pb%<:̩~[kmؽx ߏw+5 9?ߚ zX+5|nhSD MS(1l;;yMCD^ z9YLe"[L}FM}^ dJ2 תU$"xj):y?4J0@HPQĤ/s\tJ?0gZl):"EUPbCM$´c"]@@K@JR/,-=+#&@ӣ 4MH N.ٝ"\zD;5@{R;G".W$g("P@hEC{MJVj H+,^#@`@aZ}WFrF>)io JkQP"ϰjኇdQN$6|XJTXk֤.ݳ=r9 .7/׿H8)v(fł%'ÿ_RZ%rFpK~E.mŵ/|faS$^)(J&(kOHǰQe$JIkKoW`լm3b4xY %"dwzL%ѡvUAbMǗYtyJH16@: wnNiڈWzn/hWP$RY t0)#[!ơ}-#5)9Y064MRܧ:h(LlzCM%v洤k^ @jZ`$Ogp^>nW;T_qɆRlؿ3lNwgF-e{\bNvUq_`hYڊ _ rN3>dd>~qq]S%vB7F8Xe(%Ӕ]1b@Aqboq?0,O}F+J6<򶶙W9sH>Z \nO=V,{}O?0d^LoLٰ֧TI-7ɗ<_I2 1OMt1JxTڑSF:ה CN}%UkQW)-"Tp؎%[Z6ȉAi-[Ǔe;G~Ddh&W^y%/2>}mvsNrss1bvK~zƎk8233n?j2xЊ&3g+賗EJJ eee̞=g}vnf:wO@.뮻N:_СC%T(!ACL<[WrA,X%\jeݺu<L0 bZy:Q5 "j fRRRxw}d|A|İi` }[_?BEDL3P@h bp)VצFD}DAFDL z#A:@P}O$,H4Q .J %52I{  E[jOPuw2 E7 FD>;"~,M %]$50D> GͼPOER(WkD}DB$8ŦvA@h H()hHPQ(x5_2> N>)\?CM:D@ fDeEBIM,I%P5)@eEbR( \+O$ "6D!"%c#!Y~v"P$:(#RIb'N#!Qv"[OS)J}HE@ДyzDAW;P}EB"!etD"˗mNs˙GGB$ !*ډRlxHWCDtOH!jj57D ]EA$657D'( )""=,)؏"" `VPb{r5MToڕjU1dֺ6#mՓTtw lI[/Q((¨Cjvd$eV@rnTo;:]b[sR'{ l}~} xuyj}Oj: &`It9Ȉt-$t#.^s\pŻBS' b_B0M j(..&333HSpx}T~ YaP@4Bo5PsoXUfp4G""3 Y**,""fE9 ED$F5f)XSEPDDb@M"f ED$F՝vi@M@Qu=i)""4 H)d4EPDDbTcA+i@M2}@QFHl40"mPDDbT#@i@M@Q@mZHlD"mܹs9r$tڕs9M61MٳgGJJ ǏgÆ AeN'W]u;w&--iӦk׮p&i WX̙3OYt)nI&qС@ロyCj*rrr8(-- 5k/fѢE|Gqgx"qZ""aib޽tڕ+Vp'c&yyy̚5?O/׭[7.~S\\L.]xꩧ>}:wgϞ曜~, 9H_B1?S~ّD1]c4XWqq1پm(((`ҤI2qƱrJV^MUUUP< (S餤$&""RwEQ1ɵ^ˉ'Ȑ!C((([nAeux$:vhΝKVVVֳg>i5M#Z1^y|, L_VV)))Y3g̙3T.@.뮻N:_СC8qb$OODDZJ ."G`A,X%\ 7@EEW\qEEE5%K(b8󩨨`„ ,\S2X_n5OD:"$.#$"A߼owXC^wȚGf+il!#YlZ"":;,r1jI0 EDDD@PDDD$(I0 EDDD@PDDD$(I0 EDDD@PDDD$(I0HW @IIIk""""-U}ݮ'"={F&"""ZdeeEa&ݻ0HWJJJٳ';w$333 c|9c|s4MRX72bУGHWdff܇tAt!V1Q33I` EDDD@pp뭷p8"]9c|9ƇD8xA """" F@PDDD$(I0 EDDD87w\FIFF]vsaӦMM|r èwoT֙={v4ϊ+1bq_ SmۦO> '3gl|,|guyyyMd呒ٰaCK/qGp88YxqΠyMcUUӟ:t(iii_ݻw7 .l𽭬 4K.WѣG7> a׌%׊xLJ qnŊ̜9O?Kv4ijvM6? 5nuݺuݶmSN夓Nb͚5|䥗^ c[gժUAtR;&СCs1w3o<z!VZENNvZ` |'L>..?>,TѤα/[n/_~͛73mڴf_7333}'999ЬGɓ'7l5c}?8a׍%׊xLJ-$B0WXhe˖YTT[o9ƍʕ+ݯ}Iqq1aСC&˕ѻwozgɚ5kS6Z|9]ve̘1&gx .fFXZx0ɵ^ˉ'Ȑ!C-^z%^~eȄ Xۖ5jO>$>(;7Xnݺm֭n}ʇK.iLu4>U?~'ZTVVr7rhApB^}U{99زeKkrSLg{aժUz8F' ##s=r>6tHdE>W^y%_5}QnjΝ;?'jڔ)Sʘ1cׯO<^{m͜q˨E3e-kacz{ڲOUUU_?dѣG 88xyB]V>}z!C8ݻ7oFAR,?8^xa}}lZ(D `ꪫxWYl=zhG_-СCoNNN_l6:u*َ;xwo}c=T7PwiUUUl۶K6kbaȑ1һw&#~ȦMkE"}&8g&W^y%/2>}mYv]h8NF;f̘(jK,nm`vg}c=۷/999AbŊ;{o'-[i]6fs&kc3b9VkE|&JdƞH\~fVV|r3???p+//͋.({5/^ln޼\~y7K/Euuי˗/7{O?5ZI0 ,X(sƍ <뮻~fǎO<|7_>}kv3//<=I>179?KEQ! """b$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""S\.A"""jQaZA0.(**BNNNADDDPXXp7#, !!(111̭!""ANN|#.}"o㛈HtHgtHgtHgtHgtHgt:ζSnu) SU߄GWs[DDD u9--!"`$tZ@"HHDbmNʗk"" @"ꐷBE7U3E@"wwDu DDHC\._ 4@e=(EDDe`4dQ >}SgGVr vE"V4^yɊV}g!>zz449Vg%!%. PZؕ&Q0iuR%P|%CaE](8.0oӘlDQľ")&bDV`gA%\.cz ,Y%Kt)D>8~YI1ӪC9O7DnXY-zEɉeV|Jn;OUbQ<<+ z.4ڑIDD] .… QSSp7HvCe(ڰ|s6nm'+c(0w5p0,+Q&bor( HC<3r' bo1^yLn2I x{EՍpDV%)-{<Ņcc&"D D!u@lW/GZE޵#(QmI>=]/w3E@" `1 ƭF62EN!)F &us QDa$ 86ƑG^(0i (0ic BD4 Cc"  Fx+ \(1iD'Ņ X^@"HRp('DGq!h"HHf$"D D!g ,`i(0i\4k@#HM4" AKNX$", D!o.`)lr@"Hr0]xN%"a$)YB8P̙DDC ;vٱΝlF}}=pv?ֻ Apuu3 pl1`}=~8 0w\:t4pa߿Qy+ f.`"ؚ/v3gs=cb޼y뮻0{lo;dݻ'|V/"rrr|n%"Md(rDlӧJJJPZZk_Vo#F\ ͮ']8aڝ (RDlua񈎎Ɔ лw6_Wl6l6rMMM#I E˗y̼y0o<ԩSqѠ>ŋhѢN?Q(` $iٙ&'#" NqTWW $" @%{ᖋr#탉HT[T#f568.7GDD] Hk!" kx ""L<[i4 $(21it$"H6h1"" Dpm[Ƴ4ڥ H.`@""j@" +&m<[i#4$""j-4ưHDDH&"`$i0  H@ Q;lAN (hw3H& JqKw61iwDkA0u<[i+Wksup>M ?m [;ڃHlVnܪøn :o+n cKƳʔYQpݷ Z}p+ERE;_k cKf w˶PMlm~MHNʬX^.`R7VT¡+`{AEouUO'm*jK1Tg "9VVsjLBn3x|Vc҅YZVXwf9a0l=Qs6o'ws quM>\X%AleF@R7VTd_Q媆(` :/>ޅª<(X}vTMTxڤTב }'ԱH*H"U# S(jhnpEdO~N6 &ޖ2PVTyF?[ǻ- u@"jڈl8KǗ+ { PĚ3oqPhFŊ8-{ß*kkµwl'Kсv31zR?@"?i>]>ޏ~{w(Pv@p6X { ]71 Q~.WV= X}q0^bwK ߝhihgԍHE+/}sT^@x͡UI Jk7Kt+?~ MN؝.#rsDLXߞ`uKSy⪡5 v<>V֥[uuITD'_'(6] VGP`GDe4`PF:RatGA6;s̃c?wUO`ZذT%y/>%kobJ{ Ʀ|w8TbEy e51v*QWuUVrsAy=N.|w v'l|. zfq~`ӱr=\ҚFvL}n-6wxe`TD z(Y4(j8ˆP'n @K'_ KǭK1e@*Zql;|Ʀq\O@|k)z돜[NeD}; *PqYXQ_{gSm|X:ѲZ.W7:\7|̗mRrrHDy~w%MKJ6*/+d 6 ǏwSHce4ₜdhd%E/9*R-d<)e8gE7ie/~s.y)cӱ_tOÎ D dAiw%5.ׁ;:JkL|p2L%5L56dXGx'H8 $2\=*rNowbаD\9"}Ze$c섅 رcGB#M0y,K|}}S:ΧC ?Oy3C]043o}tvFNV6]e}Š0&79ﲒ/|}j@*$Ҽ1lh|7WsUCSc(OױטMg " )ꕀ+Fd7|[T. $ NO\/$dCz!#1i #qHoe4L aOr>( óܡP uRe4qn?:;9o"=.=N2Sr1FA??Y3po 3?F2@H"a4i:*' f1;`4Ғ'j&\#p}|~9 ˷Aɀ(<<NQDb/2?y=mJû;]92cc6'p'y+l<f ½NNр&+!Uܞ)r_1n(W^S"}I,`R;VT;g2Я'?->+: ۟(wvPKpgGLY}}zSb,&$z&g |L#qqI>ojAұ{ _U#30P_WIc5_' Ǐ?7q9j(|VyITD9' 3M͢1)`w&/+ wu#9׿ˮzQ..R@A__8 021 n3""'{ZwhlT_ q} klA0WBqx핻HvP``HE1FCaꑙ|o|Y-]0(=탂ࢾ=̵a|eV2cvK n\Eag0 HcSF@Tuw((PChHTf+TĩX-ɱQ#IjY@N&EE5óa0ݲ4 %8HE#;0)$tLplhQAL1cnF3jBg4 ;w!c$R e4cHn(Cy:4D*D0[ۆ՚bMZ ;1o}!%/5N9pʀT-冭 Qn&SLZxq"R_ETt ŮӕЯgeя@ 6 E~&R gvĚ0"+'bԁi>3 DRHC83Ԇ@"p8ۿ Dlxtjm%Xմ|lFy;8@R/@"`BIOFz0!B$]H"T)، ԌH%1*GI f8u]ٿٳg.Au]܆3c}|/)hf ٳo\g=(ԩSxG0u`5]:3 GR0R$LX,mN'n6,Z6l@UUUpG:v?(Vp bgyiiiX`AB `(4I4?3~6m²e˰teR ԐH*.3fW_GZ۱tRyDmr1 R(I<:TI30.. hױǏGAAΝ+_SM&>Qgs@ɈXsAj0R(ILjC ޽{}{'aZ/"'''L-s{}qO]7"m/Jy'07 6 %%%>יL]17X%''@Aq#q}Q %-1f VBffuơC1l6l6|[Fɍu) C`v,R( R`˗Cf:/_>c/^$_!/R(q EMPyQ]]-+,, H ~xw/`ƕ1J1 'Lp(X,vm/U+z ˺w07<Ө\di /%6*M L@2@"'N4Wƣ16/%M!$ *$@'8` Qn'P$`A POod0QD^ Ue`t@"m.vPe@}/NH HP䅠H HP>8 H8"4*dBк . !.b<ը A뒼+DM͉xHxQ!VI D /f *]z"I D[g8 1+D`@ *$㇇8 &k3TPY>!y0?IxQ!)p!h}&LѸE@2 \Z T= E@201DP:;Le=vTIL FnIPV|c;n|m 9fQr QDVp UԉuEQsu{<(&H٤p8+k'oR7S@uf!sIuccArxQQׄh/|AxB u&U7?ٜ& >i $lRhmt pwxc;xqFGRY+탇:@"mm5} { s8gY2 *7+)ѤF@ Qd+yz󿪾x!@RV \{w6B@;]!Z'@{BBUCS뺋o& ?m'N^[O<_ )+@WV-QU7T^k>(b醓ƓhjI q"J.pDՆ&o{173u/;/<~~y7or;UȧsCI_ ; VCݟ9'fk [U |>u(S([RfwSupDt%ɉM9X&7HABʓC{+EU]F8wОpW) j|[P]oK n%Y_%/KĚCe8VfWK۝l:ϦjvgתPXQ~ucwϟڇR0kml*/eZ<3j#<X\#i=Gd %6 +cE^*Os?.V>^zE! F^6I1fnNgfcdvbp$JA}g Ls݄=143x9r!|AN`T)),l&'WAN*'{ޤ|D Oh C ,f=Bإ8+Ϧb|^ Iyr6^LOY,6ʄgߤql6w(> 'Ym ^ (d$RuWķ~V@ dmQ|~I $p@}q@] 㞭.? DҧgFDD*bPzB3/5]>]7W %`40,v^[wO^=T]9wQA-Nj @9>gEm'pӸl 8+G$Ř;]07"Lqx{)91O~xV"f NCNذMUZqĻ$L|J7rH]CscK~mTRlP^.3n3O;9syԽUJzCJL2bDVjHICHíE: XJXX!T)A`++_6Pټg*PAz+ixR,.{N.ߝ3BߔA <P.-'E[#NF|7ooK=D sV[X_N"x%v4*!92 cŮnJ8EVFzYԞWo Ep( {I1Tœ7nL: ^H[5N' w.c(q*ҮRak JWbQ10һE;" fwѮ&,Z fϐ3F&p)h]cT)y;Tule\P8 Dzz uRM\DYS,]Z Zv .M1pP0jO8+kv>KTp6;Ǎ1 8lh `w)+r0_cv݆@ުy2X=^~H':f;(Fs$@=3Khsj om)YP/9֮p`TΆx;&olrL~s$ `GXgstk6 xao0Lnm ,w `BA.~ks_E,`vmT*0v=ގ)Si `j|s}ߺꎼ(šcmW )-ÿ7rSY|D!܂h뉊nmSGp_amǧ{n p DQo?އߣaxw⋱oP1ѳwuA 0HOO_7xlB\wuklE>I cK:gŮ38qǙJ#VZgE7I& ?\om9`qMO*EM]$gFqq1 _bƌ9sh{)<#:ujZ~1%tx{it©WNO|=߻~oDKVj1qz Dw`y":otx(fC˓@8P">Z,dddw޸ O?Ɨ_~˗z[Ӊn -B~BvRviFHU}V++skp^}g[FmV/ FQSSnRV(kt5 ~r'ce/bC"CC_$` ^z)F+Wz3<4,X D-k?e[8;pۻ0/9*pPT] [k .cA%g=+w&6.joOzQ Jh`Q~.E0Qw!Coڴ ˖-ҥKCרP(SgÉom.hUIM#*|>xj(nĒ|QV.|vS++ٷ$~(vK{MRPnæ\= X۠%,X4{E?nՊoK.Ejjj[>wOr 騧?1VOYPѬz?P.79l5DQDYM#DQĉsu>g{9ҚFVj8Xt̊֜QNImٮ?jR Rj;ue1A)N-vhœY%Δ EurD߾}(((ܹsY& FC<5wxBC׾ '5~=LցqR0bWeVT6amD$?re5fk8S ˚?RYo;\UUy,)}66h;%ɏ<02K0(مc;R,c.ޮ4ڛҌd5 !uf͚5ػw/|2dsݓO> Պ_|999hfH㽝-~ˉݲG=wT"!=yT|,lNw~Pz<9fގeaEk/ol~οn|X$~}09d[41?& j!SZ~|+~2 Im4{Bu?@Ӆ-'!@K?ˇc0ISݦBl cכTч$Bğml6JJJt:QZZUVaŘ3g㎀ƈ#|KNNfkɿo?A >֋sc6bƓ->G j>;p9TuPYoǁ"w^܃+|p OWaڠ4y]3~ܷZ@ɿ” x=rm;N {Gcݦ \8c@q; *|ƠOJA:. Xh0vW7aۉrܾl S1,+( mǙz~pzA,##-6VBff&L&RRR0zhK;}Jff~Qfm)o>v} scnGɀ_ Ku߾\92f#z'hxg@x'F.WtBQ)leOUގ&MFQP.bҒ@lor򄎼͂=Pje#ʌ翢O (_u/r-$]`wg֖fXwgZm~!@bwP:Ϭ~k)opg?K3w<G5;mteC9ۜ" `X,$&&SGf 9s< bߢ+{.7ƈͫ|e2__LpW$ F"2#ɱfZm8W{o{K9) H2 DCJl>r 4Diwro $ NOy$C)`>=Z<ʺ]БzTnGf\(}<|p|ok5־$ob LšFy]\i|~SI !ǷSJE=Eorcr8\"=ﯻ'asWGp=0gT&>gt;'FOEk ߏp{?I !$W.u[.mvMɸ[xLJJR-r5kc4%X03/}o遐m 5*Kfs }cLb{қǻON(M'IAzl;^Wi .`i\c{wH}> >)HŸnv\;1mUrA#:f呭 (/fg(y`gQq%h-.O#3@"榠',A}Ni Jy:RПaP?EmF 94-/4W<ש;)r `(V(4J/[\z7nq66\Է~;gX(#lQ&1faPqFf{*+&h(^1XhXLFSYWBtbj'w?s~Xe w?o8{EGlut>1fkl6 -N| Ai֎Q&2b}د7;4Jc}Dy\,|5,AQMʑ` aFjEz; `B`A⫮% Suh ~]ܤ]RZ|,/5HaRP\/tiVCr؈]9=_&{ 4kjXVr <˧䤨 z^rlVb|}C 1)94U՝\52ߟƘdBP%u ]xF4~1ƾ/e=b{ɯxֶ E_} SV-*)ol_1QFy UK@xJ2 fXpf0lXw3 0{*> VWVB;y9cHn@_|0j2p|yP -`Lo硙 e.,u ׏jF84:'TI8TR0 MAP{]=*&\>,zyZ0 ݳ+Gu^I5np7 v-oC|ܦo pŢ!%=2]e`>#41 b[ԑYJ1cΨL*bb!y(T@ޘ:(gI E8u@oʴwJ3ނD3R1*9y+&@z!?xiV)m+fRlr XwN ~F @R!'`ղw"0LóE4J&_"?@R'i+ꔓ&HM b+˾Hj$u1:XTg6rQnB:Hͻ`x?x@R#gZZ7) `"Z[I̞Y&=(0~ FH*$U.Q1RD(&`5sAWR!y0+D K,a0~p7Eߝ[;~]ЂHc,`"`섅 رcG{-HƠx JO[;ֆ˻  q0Ehj!Ѱ=6Q{cL{ gQ`YϜDD:!ȅt􈋒oz0ef#' Q7zd&`Ban Q`&.MD D@ZfBZR'o0+DzH DO4r?R1i<+DH HeBDHE.'0兠Y$;V"FT7f&&"VݛHmY.QJDHq]f:;~1uWc$53)f701uDjbR;\ƖQ1u?HjfVTή0/ݍ>E$@._=fZpۣH?.M묺u Q=.Cň:o.h6(pI@V݉:+.6sDHdDR0+DHi1@D<ł̝;|MnB\wum(i+D]񧫂;k֬s={bժU1c.\O:GySN AkIkD w!(z>*Z$6Pm8 kLn@W? ؾ};{:NvmXh6l؀ "{ҁX,,*)WU5;Y1X84_C/ *$,u|tREEVZ ?Irrrg u2$#\muOWW݃U uGKtO\=~Bݎ[Np(]gKQgEtرcEC m7mڄe˖!??Fp "o;|w=7ɏaQ w/߁3 \3: +w\Y }'!-JP)] QDtBѓjߎK"555M#p "ufcXXY-nxu3fNFj|v eFtW[ 8[V9NRP^Qx=>jmn{DzB>SH5{9q5HL9ۈL~HW>kF;=r8 Gcxd`#'%JQT⎕բ&끭'*fmpPk,q.Ee]E冈JYLv{`@ (hj_|=0$3!}=r`crS P^ۄiUYIxQ9]bxASs7!)ƌ ,A@E0G,-0g-Hy|0*; _n f$Wr1$z} g  \@ z7 O3FD~Lo|r ]{C$ƘQ<u* ҧNsvުD"M,OP"-2m⑖XG3qgoVr  ZIV sKiD˓3Wٝd "rX* 7]=gJF-crr{x ;q\+py*yԡ֪Dp\KC^j\eݓsQD;Kb RDٿD]ųQROn{v~(jĐĶ&Rd)"b$ @1Al Q`AՆ+Gd}0i QY=7+;'^䜈(20 =}zY>4 W!"" (v1YDDD(VH@""2ވ,`""2@\.vv1ѝ@"  Qr0 i QLDDZHw `BDD Dp0i Q&""-c$ AFld4((01,`""0@D&"" c$ H;aɒ%6lƏPp0iOopB8p;vwS(HYBDDZH<0 "" @8(:anQ0  i QZHDDHG84ȏKH( \4ȏcHp i $""c$ i VH@BDDZHϧ 8| "" @"?00@"":@"?>cHAGDDZHG?""*@"?@?""*@"?@#""b$#HDDڦyfF̞=c.\'x?sOkhdffb(**r)q iox7nӧ[=v˖-|+V[NKv) hI]]}ر%%%X|9~߶x}0qD\.lٲ/B?=:vn{.YX$""Sm1x`~x7YHNNFff&v;뇔TWWc„ HNNnr(;#I&1g֩6.[ ~;`٨7|s3<|tMX`pB?@~~>󑕕<裈CϞ=qi|A{NY!""Re<|0oߎyL&nf>ǥ"//7o7ߌ<ر_=򐗗^_ؽ{7+Fq*/"Ʃr ep8лwo:Qa6QYY;{^wuشi>Z}TbРA:t(rrruVL81ϑKHDDZ [or7n~~>ك>}w^%??-¤Ig+0`{kcKϋ"w  i*}*++`$%%?!-[ HHHѣGqea3f`m>۱}vL2)))8q~ߢ/i*˖-e], 7܀|ڵKnݺu6m`mʕ+1sL <sFbfCMM? M9ݞ~i,ZHLL C(ƜmDfR4<>3!"nVSS$]UWTp7% ibi{Ś8i+D~Q;Hx#^DDq D~i VH8]@@""&@"?20&@""(@"?$""mc$@#+DDQ D~ DDq D~ DDq D~I F$""b$ i N!""c$I DDu D~HLn\'p7(( JOp7(hLDDD3 DDDD:HDDD3 DDDD:HDDD3 DDDD:HDDD3 DDDD:HDDD3 DDDD:HDDD3 DDDD:HDDD3p7  sKt#NXd ,Y&@NNN[DDDDeZf 9vBQQ B%555Aaa!ݜs|۬[ 4wСs~fmh6ׯرc~^ Qk&///kp€Gkbܹʂ 裏|~/"~idee!&&\r XÆ ba_knGȑ#,q(**j>/_unll i][]wլ&Lh~#u[O59h5 :~z,\[nիp80k,յyÇX7pk{xɓ'qUWaԩؽ{7x g?Ê+Bٱc\z5olvjM0zhs/;v ##_~9Vke|͘?>ك㦛n¶mۂ4ڥZ__]v7 vڅ+Wȑ#kڼD׸x gi_|}F ko@p ޯ^[~tL _c֮]++++CװnSOGnկ!C\w&Ls H|M~|r>+_(&%%ZsM7g+͛m,ESZ<7q,s;kCk/VܢC=zy1c3gbڵnZ8z(зo_̛7'Nh-[`֬Y>]qعs'v{mo{ ɓ())y, O͛7x^nFɭW[[>} ;;sݻC.ZnzA?1Z=^ kii)>s,Xc[~U;@E=L#Fx\ff&cŊXr%3go ak;/[oXt)JJJ0i$<>ץphr裏PUUc"5U*))nۨMcc#{1zHLLl!C`Oј}?o5E on6umܢk`PGx|'Xv-;| &f{aȑ-;##ٷʲ2L&3MSN믿Ə~6^SiFw̿bF-v;n&}H~]`Æ 8|p޻jz][:Iu@EXr%֬Y}v~vލnn]pl6c"qŊx ֭O8!nݺU3g y8qB|AeD, S)抏>hEkjZݻww?{ny>+&%%+W+r-bffXSS#{Li&h4>xAgM&u֐??֞n1;;[yl6>O?-ZJ<~{nM&m۶psZx]%#VUUHx]snUkQx'""""]@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""a$"""@""""|%jIENDB`mir_eval-0.8.2/tests/baseline_images/test_display/test_display_pitch_midi_hz.png000066400000000000000000000714561475740344600304330ustar00rootroot00000000000000PNG  IHDR5 pHYsaa?irIDATxwxSw4])-mmi*{#S@2DpC/+իWŅ *( dMPVݻ8?s2:yxhy]*AbxȹHaHaHaHaHaHaHaHaHaHaHaHaHaHaHaHaHaHaHaHaHaHaHaHaHaHaHaFpg&  JrQ#DEEK0f@LL… va`30h1#Ǖfߠ @"""7[l&"""R0@""""a$"""R@""""a$"""R@""""a$"""R@""""a$"""R@""""a$"""R@""""a$&ny|@ "SX^gVL+DtNfH?_.rQS0{@90)-gy.<""j @""o?2K+(g$"r7 DtE}U?>   1vU?+:PPo}Q40DhF1k:]|Q~LDX$  ʥwͯwk^ۄG2|^9*#=thdW6琉<2gh-= d𯟎B~Yu H&ݭvy~}3f| H+Jؓ^I/""/67ҥKtRFW l].E??S/LzB9 ТڈS9%p`jj{hF3JmF+:yQ06Y0k,Cӹp$l.o>*|-zq7γxidTU7ł @ h5^תQ^mDa9 ;a0);s;3/;c`l[[dUhpBmLJt ךCVY '"r' Dfa} 7 U Ƿ7a>hphj#C}4}]g鲟QDDȃ`o oP_V-F@dV{Ra+=c j Ɓ }'63@"a4 2Gk5}P4RR/C;J#a0|İv:!f0;b$b/k՘+O+GXj#Z  b`lH&`@""H!_/J¬k;7p DDn@<iGkȭ0y _n`˖#MHDV<XSd0{a$bs0q%""H!ʫM. {a$ 3 $"rG D&8 X@""H!&`gr"h""wH!\HD<8`G@  *Ϋ@-HN<+&HD^<Űy  *NlV0허C0lj}9}0yW񂗪fUBD.<Љ@T*HQ0yWLZcHD.<&h+z@""H! F(\P m0y4 '+ DDpٲeӧaÆ~C8p@233š5k l+ F!_g~ ʪ)mbEhSKDT< B F#[aذa0LXnvq!<<C ibJt/uV1 0RQ'ݧJz,ZVyryxѨYUUbDr`Z@X$"r;:S>|mڴ}QY=z@NNJKKxb?;N[n)))C" < QVV~& aÆᥗ^BFFF#KܹSOn Xx1lwܹ>|8Lh"t:_LLL3~{D-z g6r)8""wѬ`ǎxp}رcR)S`ܹׯϟI&a0|ѦMt:aP/ ꪫwywutoooZ  ?1aikbӦMx뭷.XEEEҿ .4F pyut p~隵hVEΝ ݻow߅FA=l޽M3lbb"Ґ F`DDD >>}v )))(++Cqq1"##1}t 8@QQ!C`РAM6!-- 6}뭷kArr}4YɅuu_HZtxAPUUVɓ6"66BCCYNN&OlذZmt:ԩSسg^z%lۻwo,Y7tS,szUNDD jr|g1aĠ~-~zO?ӧcԨQk~z6յ+W{ O`ܹHHH;v,Nٳg6lAӧO駟FBBx>=СC>|O<nf$&&"""СCG"t0DD䞚1c dffBӡO>X~=nԩS|r,ZsABBVZ#GJqI,Xs=sGl"ax"BBBp뭷_Mff&͛lDFF{… TdODDT  oFKW\}8`%H\'{c]}8DD7&UzsGSz""" 4[Ƴԋ@""j DD<[yi%.GR2QRwa5 ec;[ķ\}(D b$A |K76ȁ .>lAX*O>y>j%*sK]vDH ݢ_'q]>j%eЗUT#!jD2SRovGznYcY @H^B_ni aWٺ]8UBG5>l3&X`^IX$j 'J} ({b3=yJ}0lA$#sJm.MIȥj;|; t7rT'P`wVRepё5ddǙ<z 6x? }%swsJQVm3X8%TPas@"9Qdsq+ Tx%I>P c(*Kjs9&kE|I^L&==vpO+$s D2b_5(,o\?"i)85oKźC,hxpVZ{0|~mEyAjzoHNPV\^;:M|խwGRdnha9%hW;(MԿUP2OXs ooA~MG^XJdZMQTwT3؃o9~N$y(4=Ś>?@"?i?_:;_wx*LTٲ+UUz9XPT+pe줼A౯!ȶꙞ[9%v({A~./Y&=_痉5};@=+$o D2b_|S›N8*@ +䚂jq<9%Fܶl*MX*>I1thޓYp%V_;sԦ[R˓Ӥ˪1-6?jzuv<.wHI>1Ɉ4),@Ne0xR$BʚV//HG<ƊjsݝNl3g{&0c.žsXq,IJixSw OwcWz>_gخq"yU);_,}ʡ7Pm0aT荨2Þ6F8%y-/vO29.+w6c[y~-B۰ NC$#b|xSs{{8UJp$ qׇ;7 9'Kph$ 䯳}PM@|9q&>5RR/Kץ^h\jW;=V#./CoW}Y0%aݜnG{t oS98U[meU6wɚ@ʛI6Xu E[m6*/+MtRvVF` _D|U\w6V x,[v@:/ Jz:KU3iAoq &zN⭍'3˰;=&j0k6۝/GVɵKM|WJ}/8k4^*dW"TK=U7` pcH1!&@="0W%v|Ze$clYfرcؽ{<88@{CW)g˫V|n>4Gup1,Nsۖ'OA{hz]?jn.THMeyuˍ Ѡ`E|K6tNHE޹?^x6<;~~|$3mi:AD,!ZVb\hVY*2YzЎ!CB@|՘{}W~1ov GD/}޸rmBFw GhsFw C(s(CึЪ`0 R?l`u wEAB@LI0TL nAG ®bcÐ3uvx䚎P[/`@"1' #-#MwǾJOD.M​CbmnŻNA]xAOQw쏇G\i]n|lzG`?yQQl@^bzE࣭gm:`^bWbt >j/TL@_#ۑLyuiL%IX$cM9 C;C0c;oñٱךʄ\kVD)+>>_HDt[ jgTߡzGb ]>OK@6VcLMJ\߽=:Xe.i BSS `?Yp(m! 65&cHFʐJO_ /Bln1KP\7Asv]l{yjo Am;ZgCRpCH:f(dc*&@yK8<f {QٶtL;VusibgHFD}CI@Um#0!ss/^Z]Wwt TU*ľb4^b@@7yp=C.M _kFXsA2?_k͕R9<ɸjWo!"ؒ] Z+D2"T{5nu3ri4Q+:>/N*fRfPvj)P\ւѐ5l&c$`c*/OeSڂ}쮄J½V PJB@M䮼X$H$#FEmmt!y 0gTT-ɓ8 $Ϯ8ՇHFĩ#Pg rjNY)\orq`Ț|ڌd vjl6, 2+2Ԛpo31N 4>ʯzq몟+Y@=W!ק4YOhUAycֵ]}ey>Jj $c D2a5[KYMNCZwɠIx C*Vmȡ XX&N_Hd¶ظ 8s(Ϋ;czĉǹ0! q  .'f-*Ztuf ľڱˎ>E?Vi 0L`Q[ohkF85u .a6# D$pX'Vd`l* "J-\*}Zܞuc֦c$b$ i+L(|Ѿ5ȃp96H2&"RE˳|RkSJ $g D2!i?:wY ؅B V9g"hJ@j>RRs0@"h(`j;%a$wH$<<șRp $c D2 `oIQ$g D2!V Xly3S $cM˖-C>} 6 @gA޽({Ȱy4L:aaa ´iӐ/]{ڵ?뇽{^Ѿ0c DDD  ?_Q[ 3jzuR`tt4/^={`Ϟ=0e=zطo.\}aHMMɓ!11* 6m_jtM0)((#~ ǎo`hԾ`ƌ8y$֮]Ç[nӱJZLYŕ(*׻Pȉ,@[+Lw865y%n/e˖aǎx衇dsヒϟG_!==GPP`ʕ Mp;﫯\R...NY5oؾ};-[K,}пRZ)ixginc!aé_ș@\| DhRhķ~2 66EEEPTR * >>K}}}六[ֹkbРA? #Gw}|L&|˜1c[XB>Qr&->$g F6mG}k֬A=jmWYY㮻}CE@@y O?4L&2333gl2t6l>9s?w}w}v3gĚ5kЩS:]UUbAS ++-@r&+pر=>;vf^;& t}XX{hӦ t:0`:i20`+߿?fΜGy˖-m]Mظq#كyoÇE111U]sH) +Qr&$w>jѹsgA{nشipYlڴɦHKKCnn.4 :Yؽ{wZ{GAϞ=}Ŗ-[tR,_,XyI[% ~x(e-`ƕ>L> 'jV'XةSyfk׮6mڄZ#v1'O.55]^^mVcgxyD9 13Ytգgń |HNNa0pma߾}_`4 V`۽{wax'0w\$$$H;v,NٳgΝÇW^iӰk.X+VF[nܹ3fΜ_ڵÏ?$/M([^[D&`rM٘1c233ЧO_7pӱvZ@~lyfiɓ'`#..=ΝkD,n&s0qĦJZZrQ%1rV3w$>R!wy[\\\/^/wZM4 &Mj־tRߠ\(j^*z[W);`A, PI5_6`"Ƶ0ʐ(+D2k> 2$Ne1r@">eH+( +D}0'V&Gy$w3 9"YsQp1jdH͉IZ @"&^<$g<+d " /$g 2dJ"A DRg8 1*+DA>eHe1r" p1@G@Y #HN23 A+X-p-`"ƙ0ʐZʼnH"rO;`!NLH,\| D`v XPqHL\Γ WZ]}v^nâV&>DnK;`!Mi+Lk%aȽoaWV7c_2ɛ@5e" sVQe>$ 8.W?I߿?jzdz?+2ԔQT!\Velc'K--Bzۂ E32.T9HfeȺ iFŕz&9z17ݗWY> ˫mo `! Pc[BߒDN r&1TeX*I6PﰐPXQ]뺖`)iy&O`4ayJ^X{E<_ YW $i7𣰜o(w#LG[Ϣ{Wn0 ( sk-g%U6X>n cދu?E|<vnKǻjqЕc! `# YvQ`P9<&f`\P|ux `|M)T..~p. :IRq@yq]ڟ7+-(R@獿 _ZHRR/>g 6=r78'2Kޑ(6"Bqb_(DXtM[N墬ʀƕ3 "g]y'Z}ݑ@Ű0yJ\5o6mhPPa7#?UTOCkݷUs;Nc)sunP&jе}Uڣ!!UsY܄u4aS0R7ҥKtR3zORKe.7KK Uv x* *@Qʺ`e*.C}R̸3#\7S;t lKæ>Om8u0ʔԺڈ϶c[2|p͛o#5 MœSq(Z-B^*!?k08-qR6`^wih3]V9cDs9`w E`d]qu\Eʀlu7ğO_!56˜ 2t 'Iژ}5%\ p@e1@M@^*Lf?D.j@ o0*Ag\h溗nq=#0&! j/^*{J/,ON?o.T*E[L_ęLYuH?EJ}47pT1$0zWb7u,vC~Y5~?g'vMRIͳM=\7ch,f nt0t bTӄ ZeJ!ΰ._{&} oks?1'VWW, %/qWn3u7'FծR}soXt}Ϩ \'c)x2',s)adC-닺40욫蹤EtZ z#L&`9NW?U~xf|7f @H-P7N Z5zE0b7+UzV S&`VozcɔIl 2 ^Yk:b]G[kbplh@N,yT.~Zt]y9Z赯KY\{05k5^Ī,R@lF_**TLZ_1P&` mK60}뽟8U"\י'a#= NĿ)//D΀%Z?=ec) `eөI@#&{VàV`>o5sS* h:˦1ʔ8bAʫRWY-S1<^P8sٮS^*T''1ʔLk@iA)ovф9nߌf[R \=PZ*_NK-id~A~12 o`վK>f1 *2y5Q+m9 \k֫pqec)Ĝn4 ?GyFT.LV;#ؼ XJHfeʾnV}ݽYJb@+x7~vvgMX>Bd`D;1]*\z2f|S4|0s**4%<2Vocg 9%c)2c`l[IӬwgr˰T..fH7[hypXUn gnld@q40Yŕ|9w3[}Jg˪,}Mom0?eʺਮa.<+g4 ryx), FM8ﻃ~TB4H[Gs+jfVÙ+X+Os+ (W݃@PeʺI_+#X$S,re2*-)k\0h`yUONɺBYȠ+U@Ù+)~"Fþ߶3gdmW!i\}u~Y8W--كW.dW`4!2BAy5:7r1osZ7T0T?Z4>ʣrfpWP^SQA6 FbX&ɯZdGBC_9ȥ7j*Q Z^eW"惧RJ,ݜ_eb<Ǻf0PVm䴚޺x}T 1;o7R}/"3a< XzmƳLhx`DAɕza) c{qVT7`ByG.AWB\fmz^C.Dnmա€Y~IrJPRFYVɀV[ͷUVmlTqNW{8`źb~cVe0Tv M6ߙDѤlM>,ZF`` q7ɓ6dggGTT1~x:eہ̙ԩ)Sĉ ҥK{Ю];_~ػw6ǏɓCy1c@R;+iq֧Y.TT1彿0tmv\f_pt[]zk&KկilǩEA ** VJ=R,/-6H) |'l*vDa=MoUoA액R@'̲zT08U5)pj?nX'6i}*_[qDɐ<49`֬Yرc`02\|8s ~'߿m`Xr%? 6@$&&hC#F7~7;v om0rHt 8x .\__ەydffJ>Jd3?BǙ\k<Әowz~ 0s(s%lʪkrMK\XtcӇ>مw7\t,w2s@ZTL8Q4-(F,T ^ss婚P4Mr2)ir--}kTkKoRF$ M>۬_ʕ+{bԨQ8uv؁#GgϞoOz8?A߾}N:9\֞{9L8t]ǎk=?"""ɻ/?N㕩е} sA![y?WlVtgTO栠\/:`Ay5l_E8g qbT0i^v0϶Z@;adPhJ/wUf~@V۝;oF׺OY+J`ksֵRNϷf?HZGe0 \qf`~P{0]6Wc_'vqm>Z81MԷPRAMU\jL&||K7n'Ϸey#Itĵu/x,X҆Ma/Xw8zn0sJqÛ)ubGVaܒ?P^m@Qz w؁<ˇ ]vaΜ9ދbW_}ׯ-܂͛7c񈈈#G`aWVG܋]V;`0CU, >>VΞ=7|#]UV!55!!!Grr2&LvBGJJ tiӦ-&  +c̙xGl2v2e Ν~a4i/_.=#<믿zw܁~7nľ}w(**]pvrRVeĞs6׏ if=m#/*胈 !Z |W :٥RXҙ]\i3a 򥚓c̩4ú !07J[ϳG0a$ׁȒRIto] %zb.Fa5 `@g_Ri-,5IP(@JZ###ѣGw. FwG ooZ#E>>> 'GO*\ZeĈΡ)G==x5ޜW{/kk4\QY [Qa]U11!*}z[D͏/A S0b'F[i,5zG>>lV2]?t(2=QPֲ7؇Б#FԚr&55V׻#G^Gddd'w{ UzYN?nkǭ_`Pmnum#5ME9ŕrWDž`Wz>:* 8!"_V--bK//>bGv ʼn#ZzN~9&mA !&hQ߆^Wap\X{0|lK˃dBxT7<S!1ۡOt0*+K[_->-tjI7_oiX`qU=1A+[6f_~ 27at:+A=СC>|O<nf$&&00\t *0qDi_cǎԩS1{lܹs1|p+6mvڅ+V`Ŋ}~iL>Fµ^Frr241_}&NP;v O=#,ߨܕ$J*HmЪgҶ2oqU[?K E VAؕYdZT25{}҈_YTobm;]&/2l YoXn(0'AJ Zv#qRq땋DΫ;FuB`L_aeBHĵ a A>Gg![7&7/[ EEE3f "##}Mff&f̘nݺaΜ91cM?A___lٲ'NDΝ1m4`۶mMKKKCnec͚5oЫW/Kx뭷pwKL:˗/k޽{㣏>ªU0rߕVq!!!sAbb"6nX; 1%20}d_l믵Y٤k@U\%m>┞iRIa}nt>ZV{!gSX쯕::^\{\њܐ9s`Μ9u_IOOuݤI0iҤztx[LL RRRܷ |M^*D7}IzsZ?\& h@С-kNH3Q^mJ\m]\%ul UY<\WОaP9V:/tl6:tN):⚴?1im`η--F˒Ӱ']T//Ķſ&}Fj JƳҨ策>죂}J#Gіo@ tگC0j(}#|Q#+)k}kUCۘ+h2Rpc?XC9G+];cRHjѽbU{2՚W7JMԺ-ZUAQ语x!R'~ˀm}X:x9䋯 &u=)3XKzG@*񑚀Ej;A&5@h5^X5[MrVT}׍@w.k&%6:3Ņۮ8 XNuY} kSo6nBlLdUkiqV@쇜Sb `-?9JV muL {:?\ؿʾS#qbw UZ&kRo?Z^%BДX!;Θ kc"YRph"~OqVDѾji` UK@XJ2Je@!pRL1`ίVbd?@ b | _h |^^ۭv/_IY=u_{zgh`*$=l'}{-y* TI`pǣ8[XT0a,h6k+ 5֍}" =ڣs W=LvoE="]j]Ln&{kch*F\Vx&ߞ5pߡ- ƞs\$enͿ"%0 F'߷ W9<Xkj%3J=ЎCCe#TX(,KK9y!Cピ3X8T cc:_jGdK*b`t _oHU̪ZI&%cp#ݨM}x \Ѧ/}v*Rc8I}Ĺ9#[4 g$&@5JUg#HƤ>8Ua9eZXd@eUk͔4&@rs-  5콻8ubeZ;%׮9GV0\>zsBW!i0+DK.E=0x`Wwq횠U*@o& M0k,;v wv(^x"|ѵ}tm8]}5e@@"(`rkjkRv8}5MDHn~.9f ID<HZ@HVѝ\x$DuVs1{Gv ]|4Di84`$j40C;]kI,M) Q j#Y$"@`xy1|i84`$j&IXP_HNY$R:vV"jy齭(H4LD5X$j%SخML$7(` [%"eb$j&`3q@HAeWc$9Xf`"ec$jgDc|2DžGBDH }8 əUH"<~-15l&9. + y겫-15}A98:DMH y9bDM·Q3wS DMQ3@VCZ9&a$jZ}y2"r @a$jմA DHԂ9X$jA+r%[\jD66[LWZc:A D#O"77@6G=~]Lx=x`ndVnN7Uj}Pso5<>ܔh9H&S[6q&|0C vKN7L յXF1V_J rg#ɽ덎+kͱ\B #8Qro0ł &r ,ln}t,NdcֵmY$j+&`r3jߨ$ټsJqmH\I@ވU>фJ\,0W; T`^((f;Qz^A3]+2s R&Ea Dxx8nf HNNn_}U`ʕuqqq:III6ywqWС`ܹ3gϟ/mץKF) 2RA–SGle۪XPnhl _o`WZ%l0p"=lMv } gPTFrJldW\ŨKDŬ5I+CCBB& ֭C׮]1n8cȐ!kbРA?lT*T%Ν;Ç}=z4nZcTUUy9@q'\=1qN2;wb7cKIxCxm @U+4Ru21ݭxgs`0p<V9H6Wv4],m9*%l_4KG05M@A0o<9z`XXx1ƏSN-܂f̙3Xlt 6GŜ9s;ܾ]w݅ 1^#]`.\h yK-ô;m}l&wQ;;-;u2q*]p&n`{UdWA¸hxadgs Ƈ &?_ܽ""|ݡOiFቱ]?8֮]͛7#::Z>44=zپ{6"22Q1m4={IIIRO| Wt|>>> GC'W&pxpSZa$w`pXvxvb7s]klj&``p\[rKRA#2Z w?>4쮋mmhbHY-iGNgիi&ܮj1xZSä"661ߩSqFkf8DEETXO\-"U3y԰N>!Qn-5"-"?:M| Dat05K`NvH}DCgK{ې˵ p֬Y/_#00YYYʲC駟w}?O{gߤmp>}pa8p)Ǝ{O+VYvك FQ:j\R* O?4y8}4.\'Nࡇjꯅ<ĝ+vH??426`-u,;3{ۦA#B>@<82]t8_u$XBu.0-"#-U{!*,A1?bBl+ i'ݘ1cl_r%~ԩS|r,ZsABBVZ#GJ/_2֏\K'c͚5X`^|E㭷w x"֮] ׯm޼Y:'|;w.ѷo_$%%S'߆I9J,# 5wY((˿wa `dcKn0k`B>.rmWZQ5=zFڭ}Pe4a\T*<SON1 1mR!֪!am|ू4p@S -Cӡ=+w!e~{_60mK ϳGwHdcYqht_5 ?x5*BmRx޽sn _ ̺3; kFye"킚oLXah̹ź9S*}mnl\[lmQ{{_{qDDX?$""Hdd1ٱ*r@""H DvLHDDc$>DDHDD+DD올*\ < =&`Qka$c;  y@";HDDȎM@&@""@ DvNGDDȎDD}S1y*@";>DD y:@";R@Qka$ y:@";LDDȎ8 ؋@C59.ZF`` q7ɓ6ۼ ֭жm[\عs63gDN燰0L2'Nhp>닁b˖-6bوwe˖IGBBѡC̙3EEEM<\`JJ f͚;v )) (++ڵ+{=>|[nE\\qeibʕ8~86lAX羿;|~)֯_zRHDDJ%f|2ÑQF9ܦ:7nرcns!OFNn3d 0׽{w|XhW^>}:.\(m3p@L8/q= ,>"5=Y^!"w NCBB^]]+V@ӡo߾)++ʕ+:g޽HLL>11۶m.9k׮ťK 6oތT7ԨGd2 y `޼y9r$zes/6mK,ARRBCCmyѦMiׯGRRZ}h4}6׷oYYYwy=z@tt4Z-Ə#Gtyyyx饗0s:gUUm@ȳH={6:om^{-8m۶a6mrrrl~K.6m*++ݧ: \;`ǎXv-݋7x߰qZU\\o=z?_>-ZN'JIkv|DZvZl޼ѵn@Ν1tP|h4mtҥ F~'N5k/44jڦ999RU>,|MtMӧfϞӧ__II Ə6m`͚5.XEEEҿ .4wD$HDDP̞=WƦMUUU5yV"))$ >ej5Lb/+jXv-|}}=.#cjaQDDDf_~ RENeeex1ydDFF"//>.^op|wHLLDXX.]W_}~~~8qcbԩ={6`޼y1c aÆaŊ8<}Q@PPF~~~~EJJ >s̕D/Z_ 9q`I'""(N2fW\j'Ng}\kƖ-[гgO/lقz h߾=Fm۶!<<\z̴4JODDHDDc$A DD0Ӹ_`nC!""j DvD> ""V&`""""a$"""R@""""a$"""R@""""a$"""R@""""a$"""R@""""a$"""R@""""a$"""R@""""Ѹܙ b 5xJK.ҥKQ]] qѕ*))NsaJPrm&Ʉ BRp111p\}8(y|չA@II p6]}-*((?|D|G)sT|ΣʟHH>>>xCiu|G)sT|lBDDD0)  0)  0*E0x`"<<7|3N_Ɯ[\gϞĉq5`xg1gZʉG4wyIIIo5-++C߾}{9^Ûo{wFDDn۷o1c T*z>^Ɯ[JUΞ=,Gƶm_]s}"T*׻]ii)bccI&a9fJNNFxx8vGy999n kvv6֭[zmڟ[~;@ȑ#ѫW:Ċ+j*^ ;v,O'2d>slذ~!0|p9>++ ۷}0 u!]_SkYYY5o~Wzq]w!((uO?k׮7|___1Nr^ &૯¦Mo`ݸPUUU}rٳgСCغuk%$$ !!AüyǾb&,P%MN>cL0QQQun㮯#^^G.z=L&n;tP#FwiCmӧK?  Bll,֭[Wo8r>} Z߹EiWw >6Yuu5RRR0|:W\}@ NƍD8p^gÅ =nw}]E1}^}6tnQf 9c=&t:!99Y̔K̟?_1ctyɒ%š5kTȑ#ªU\3g;v&M$ ~gΜs ǎ>c[\h:t <3ns״Dؿ~o F.^XtիÇ wy)K1c aKPŋǏ /4c??k=W^/LlG}BBB-tMz:߻7o>BV+ ¶mۜ\˅D!,,L:t w}m^W| ^Ɯ[/ϒe+YooWOJ-"},RVV~bŊ~ݯJM۫p^~~~~u3U$$<+`]g0@p N9R?o6pNghћs?>$^ߞ;zVlWOW@h@>^OJVkwiiI$IP|HtjZjG֖eY:zucn-Gԉ'\RKTO?~G ̗gH-'Iza Zm$H=e[IoN҇>$_i4Y:_ǸVnO$U,^_W T2$) (@aNeggk>߬Fw KU:)>VnmzXX*: ѯ'~~e"OޫpG+0(P{wͻ .@|fek˲d](Lxy{~~~+CGuQG[ʮeg\r9E FԺ5tJ;v~W4زC[7n}Vu_3g = (F ҷ՝5T&mfi;SXϪ`mq\.Lp]Bc533SӶ~.  ` a!` a!` H.Rgi4#]Ko]|x]xnYU MU+]q;oy+B ttrݴ\ϟ)/OO:R! n ((<4X_Yt#˯taŇk颥֪j%,%'Unٺ>`2_pAc+R&}>eWT:Mߧ勗yrp+9~ eTD}PJlcjit_9_!a!7{S7O] >SLGs?õh"uECzw_?ׁ{ޒkTPw9 ֒'uNꤻZu1}]Ft~@hjgw=:QNIҰqôfgꝙ荅o5%IQeqF}9<'Bu4cӒ5ԬS?%-IVUHݝv]9ըSCk%I_UVuvOOOUQUݒ$N@qW= ! + ю 7)JCz#5P'DzlN-?N3]aÜyΓy{nfCtZb+ ?8u@`JM[m/^έ;W./">:zE;)YT-V,;~Bt*-]Sgog޻*SNoըjkɇKΟT&OG;ɯ+:6Zc5gNQhֻ/n-t&6YEժ}<>@@t7*]+IPT(3^cjfmྃ$C顶*DyxqAT2^?@US=.wX%l֟o^ߒ )000/;<Sv̗qq{L`WOeUbQJMzٮC!'ƶj٠nu=/ߎOrKhfff*55Uuږ߅+ґGoTAe7ЁC{\=5o!K6]G,˲T!^uTS T:=WO C0 0@ CGZ+>$^;̗K%KTV-|{sWcȸ/]\y?3Ƕoߢւ TFռu:i/NK[o=uV~RĔ-WP\Vx⒤䯓սuw޲_AAKnۢqGkӖ -#C!aU3A㞟R%K1[hg}VsQN@@HP<~sbլV_vVv^L/KVȿ'8NcӎZ4w9KOcm;?  Wޯdg<'Em;R4Zy&4Ua:wl~az wFZ-M%ւϞ;$I7];jܡ1O3IτhXaWF<>BY=xWkej+vf2˱OFzF>1R [ԽMwvK}7mWtQY6Gm:QjUb95Nj;ƇO?wڿ~Z4w$KV%Ij(l?$+uwbhUYVuo}:Nё$˲ԻCo8~BNׂ wSQJ|7ۨj59^v-[L-ڶPXcٮ܄GkIoؠɻˆqΨף}l*}byxx[N9{~=pOFOyZZu𗆫oIR>;=zbŨvڲlplK^=?W?~%">A ~/W.ms3=-]i u_\Mj.Iz:|=?g?Kƪ#}r'Ib˫]Zvl٢N:)22RZquTHկ_n:.#[鍹Ԩ#[ZelM3E]"˲^u`NzRJR!W;߯vwSFz/]*.^.7fPth5mT{vv?h =umU2zvlqㅕS}‹#5`PoLgFV*_F|Qm7yJ+O#Gӑ#8UהМ蹱=*TBu]q/O3 Q- O?uhJܹsCtܱYW؎kJOOWPPI)I| Szc]=Z0#., }ȍjO·.\GTUc`|儜vPh[UREbcc/'33SӶ~.  @zr/ʪ?ӧ_1ڸ @C=r4 unݺF a!` a!@{uHk˲4jPCshpwdbWOx|4દ:Ul4r٪ui V릷ف=\saݝp>CU^o#7N?^{O \h[Z-HVTL*/.H>x_G==[8?)=75Kj^e<<PۻIicqdoMiY׽FtwP!a!UÂ3w5[Z箞Bϰq9ը~#KYD7C1}C~Z4w$%I4y@!֪$iXaߥf2K߮Kvحm+!*A5:٫E;^;Lc*>$^I$]ZܼꗯJݱ:mݸUjvwӏ[q])VP:ד^uv]&U)DMݪ/Vtl5 +ӎmPX 8__FVzF)l^4V;'飏?B4-[zwm+??_mzfZh,xsϕ$׵zjM~uڻgf}8Kޟsgϩ׃yiu=dO;~IjVs 3D}UXDVo[yIΝ=.uѼߐt .I:{P%,K!!-ZTNǼ޻(5k])WQ]xQO~^~~P~>coW\8 {jT~UIUy1U5@mZ> I(]F9]㞟p@dShhX:|v;~_lxU+:Ÿ$ݽWUv?IuK-vie`ff$H"<ށ:n~NzʱwQU8cuj8}v%ت9߷?U~بAC:GU7S ǭלwnn|y]{9 ЪP6J6M;vU?W) ,.=Ylr\pBڲ++(yii*\۩#5rHȲ[j}[kegg;-RzaBCeJh Ѕ5W,1 0S'BT⺫-:w.i۱'ԴuSGp)\B'~>?eΝ=x Ek|ڹmΞ㡏M7C1c.OTlSʮKwiݽW=z |J?RaN}nSʮEQlNUbNm~~ TxXi[۸^*T$*uiu?;o:ss)e`|V~ZAU_C8r-زC6oӨAŰ%竵Չ'q6)a}iϏ{6Ycѽm_YqƫX׀A}tCnԙ꧔=z~m߱U=~LSNe+c'bfΚ4Fth9z~=Ξ#(OVokrsEjES2zU>hޠ]J95Hڲnː^^^2z>x5D:!%]z(? ij^w\na]umҏ:KڱeZ7l'G<ǿ7U)R@4e=N}BCwuEF(0 _x{F~Fת/?;\lyIfNyC{RIDM1nNE]ꮞ}V4m';6W]4e|cJ>ߎ2.n\c]=Z06wxGr/XR'(62D^vWOeYش:{@r&@ύyF0v5\{kffRSS+__€@ fӈ #r .O&Y&W:tHQQQT2e\= v]GQ@@l6[(~xM8QSNw}pu]pw}^{M7tS~)%&&[}vء &x>Z$⋚9sNQǏK/W_}]?sjԨS^v{n8p>#͛7Ok׮o-ZŋUuZgϞƍ5|pmܸQ .ݻղeK~kh"_^9  7uZzrjR5dͨ`?~ܒd}嗖eYníq9dffZAAA̙3]5<<j޼Nvw}ŪSڶmPժUKfrlw%[oݻwKl٢k{.7unذAN}"""Vwiiilpwns4hUc;~rpɉ'tE9رc.U,KOwtҪZS[\\!'wKҠA4do^իWWΝkرܿpeeeԩSWSegg]vJMMՊ+ֿf?~\юדO>eJroDb +VA.U,K}… _(66i{llÝEVVB.mݺU7ovSz!m޼Yʕss|ݻ#ɽҥ?=<zzz:>]nLHHSGj۶mnq.~{ʕ+UT)ZΝ?8РAl2I[ E2͛gy{{[ockVѢE}zjyիW[Gu9{ϸq㬠 k…֭[:XK]8秀-}kONNѣG[{}z}ܵv˲]Z֒%KTk…VppSO9K֦MM6Y'Z6mr<嚛:{e)SZrqFI&V5 .\ZV˖-2eX7ovxykO[V᭽!`MfX>>>VڵN$]ٳ}v5b+<<*RհaCk֭t>kt?c+>>*RUJ^sε[ -___\rְaÜݥUV]x׮]-]Νk,YZha8p}W?55WZ_]. eYVA4=!` a!` a!` a!` a!` a!` a!` a!`P/ IENDB`mir_eval-0.8.2/tests/baseline_images/test_display/test_display_segment_text.png000066400000000000000000000271461475740344600303240ustar00rootroot00000000000000PNG  IHDR5 pHYsaa?i.IDATx}u3sø7ͽnEFH ڭG$m7X*RKKժR)0DfƜan9z>=9\ߙ95\:.q _` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` `LnRRR!pG銏WPbHIIQڵ}= PɪU`1DDDH:"##K|'.+}Jҷ凖~Qv]`.k=!L?|!zEr Jeiii]q"^, P0^&8yGV<#CXJergҤOsu4?Λ֦fUdvz;V.H[hTDw[)OQjbwٟD4Px\@w:|Hgf|Q{OrtǻYYw ь_yn#Ei.B_Bc ~UOͥ8CIKud{コԨQ#Ws^<'1[ceiذaƍn8ЪU4u4,L*- /4ݻVZ&vo>-\P?>AnGzwbs}!G3M7ݤիG#9T-_\>>W&SP瑒RTQ#-ݝŋV޽Kx%~7nBBBظG5E}BiӴpBׯGzqUZUW-Լysˢ=RUWJ*ieW)nݓz\P޺ք4Ż:ԍzuwH}#&&FS֭ըQ#oJWU-_#zjѢEe҉5`%i{SSn}@ժUK頥?ߟTtdzY#+}~rrZ/glPX0tM%82j֬6o'ԣgOs'{JI<d\h9/ \rZi]/I[7ifğA=~F]vϙNbPO?(R9Q\l2rԬYSAAA]Qfj*_d^Ny)::L4IZ*Lu*7qծSQrQ|\߭ZjrkUTt*T(,+ߝQHSGj}lէO[]t9[N.K7n,ҿYRU?rRq9 >r<ĨGoλ~iǎUH<\%ꫯ[n_%~%qVSC⼆UViϞ=g]CZR6m ^:3CЁrJxzq%"tYYYz5aκBX,%''kСWhh4zh/ݻrT:EkըQJ*դI ^zz7o噙Zh?\;vTxxj׮QFرcm֭/SXXbccVZiرJNNÇ=woZ/_^?K`O?jԨ :T'Nxgɓ5jcjРA^h;gyFWxxZl~\$^VJt5x._uWhܹޛTvc_^zI+WԕW^_Mc^SŊ_gO<˗j!!!8p͛'Yz-egge˖޽n}7Zh֮]#Gzgڴij޼5aM>]/֛oNWݺu%7ܠjɒ%JLLT6mtחʝ. -X@ 4PLo;vFm۶{g}ߛo'jꫯYfym3uT-X@sg}4{^}:uٳg{\йsg=}ݻW 6Tr?͛u!I}Y{zu=G¼ >PJ$IǎS\\>3FrKx4d}ݒ/Zb׳ 3fУ>oY4sL-YscsiժU+%:-ڵk/SN%6#+>/ ͛7{z'ꫯ9rF۴i4a=cBuQrr%BUTђ%K_~Y_vؑ;?S 0֢Etwf͚?7׿te˖igEXll Ei֬Y:kueiŊj֬BC;eʕ+˗:Yfz+B6l(y3Cz?7UW]~A~ D͛7O*U׽{wnڵ˳vysJJJRF4j(}GڵK?C_TV}뮻NIIIJJJҗ_~nݺgϞ^/93m۶SSSO?.\mz޺uN8]zl^R 2Dwի=EPʕ5m4O5lPW]uO_=/4h xPBB:tK-z-kN 6Գ>|_;z=xeѣGըQ"͝uΝrGM4i#G_j$:Wall3+Vw5kL͛7ׂ tqj޼y'| `+W\.܅ :T#G7͝;W vujԨQg}ONq+iFv҇~+Vo߾ҥ~mny=JyX4hm۶Ҝ9smƎk+=ǖO>\SLQ&MԽ{ww#(%%Ay]nF$ܹS/}>Zpo߮;vB˖-ݻW_}>w﮵kz]SOf͚ˋ<>?sLeee{OKk׮Y&OٶsΚ9s6nܨJÇ:z ҥKO?)555w*_ oTS\ΙۢTEFF>߳.:S_@IIIjٲev<)ꬋSrn1mܸQ[.~}dСڶb>hŒVEWʕ ь4]y޹?m[+2ۭ&Mo߾z' 7t>8n7sc{KÇg=֭UW]nݺiٲe^mذAǏ׺u8ҩ3YI3gf͚;w*88X۷״iO~wR L9X+[oU˶/SƒzϹ+&N*zϺnϞ=4i.]_~Eӧ&NujJJ.}g׋/^]O<߯kFWuѳN!yf=Z֭+Qڏܞ={<̙3k.~>וW^yֱMyڷon3޽ˆ aÆ=>}O^16nXzҬY裏z.SO=%M:w(?!!@'?Gz}}w{8smKjժBK|.((HSuWkZbEiӦyW/ A9-^ *ƛ\.8uor׮][}YdɂyL ?77W*usx:V\SZ*JeÞ?j߉WR>mAYo>9H\jʏ~Tp nW%ȥ~KB .?p@'O׃rrr}`=r#=T`Gi.@?U]?9?cvT,={O?SE2ge>(\p:+#.PvVyo}ھu"ZD\põ g]!A>OD97|FV6l۶MI %i˴mڴiS) e /wkС>|5jt֧~O|.At]wc{8 ZJ?ZQCӢ/ֱA~9@OM޽{Zjedڷo-Z'|B)EgX|ZEiCu!tM^gq>H{DjV(gZIxB:uR ᄄ򻽷^zu?m9Ec vQ~p/UF \iiiZ|ѪX2UϞӔ)O[n.3BV0/N'}>L7dk':/^Q;Tozw},Yzo{ND`:Xu Sp4vJݐ*ɢ}T`"D*8폗N#IgeC53^s{F u?ǭ(u}9~%E4P*WN#IiSݾMe!ŗ(I;WY)ەpW{I/jP*6XuK/_;<ҲJt%%)KWVВy̓{,Wg*7EPX녟'?ά,ea/C`U(Wg 3s3Ss2zw>A[U0c?ksWdVNFE@_s|fE`HK\U]uI{b{( UЂXؿ\8-<lIXUzH@` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` ` `LǑ$Y4S*Eٕ{S_M2E۷WDDW>}qM4I ׵^-[hĥgʔ)r\3f@uw(&&F*TPV>~I=cWU~}=rݞme|zx\.{^dYYYUjUUXQ7xwgQtNNƎK/T+VT||}/?ݽ+˥^xr!ːEi̘1?~6mڤkF={޽{}=f1B_|/_'O[n:v+gsi̙ڰabccյkWp%kÆ zWԢE uGW_r?֭[׿Uўmu4uTK9smۦgyFӦMӌ3<;-[j̙缾 3f}]-\Pk׮UFFz܋5";333qFM0A7n;C;vo_}{O_~Ϻ_w]v3|p7n<#>q!Gfqv;O?ĉNTTK/j%*==iذ|rSNѣ 칏;СCqngȐ!^r-w8N_z.<=+WYpg;AAAҥK/K™?;={88osj֬|NBB{ ,#nݺy]ޭ[7}>ő*IR$i׮]:x",,L:u ň#t 7K.^/^v[oUպuk͙3s} ]:t蠕+WjǎZk׮~;I?<gbbrrrWg'55U.lx v;C=f͚u} Ͻ p?\ըQ5j>UsGӟԡC5o\<=bϞ=}%m…ڸq6lpu<Qg֟'7NׯרQ%iرJMMUƍ\M^eq. $#G7|kמu] ,5zh}G*_|nڵkzJԺukmٲEg=ܥSΟ?_o5k$3F4hg@2@Yn֬Y.?11Q/6nXy"^.#V9tY)_/Zjy.Y$&&СCj۶BBB5kh /Mz]֤Iϛ.I=yvmKuwД)S$d֑#Go߾ڵk/_yO :tԩ۳g?nݺweXFm۶Z|˗/UW]Qq4rH;Zjիu}z֚5kgqkJJJ׮]; 0@III_~ꫯ>t?;vPBBK}9 L?OAٶm[+Wko E^ܹS+VPLL:;S|_||z!-[LRνLћOp .tʕ+֭[1c8+Vtv롕ωrV^8p_ffg~ډrygN8'--͇#/ qwׯwBBBɓ';;wt,XTP?g@8ΠA5k:|k.wqV<ÞmeΦMM69{ٴi]ÝZj9+Vp6ntiٲsI_M7otjժ$%%yfeeyLg qw,c9 NhhӦMϩQs7w\6nۙ8q넅9;vt6oA30;͛7wœƍ;<4gN:u;wƏ(y4h8ǝ#G:UTqÝ^z9{l |ߵkWg: t׹8xeCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCY=IENDB`mir_eval-0.8.2/tests/baseline_images/test_display/test_display_separation.png000066400000000000000000007366521475740344600277740ustar00rootroot00000000000000PNG  IHDR5 pHYsaa?iIDATx}Y~k}9gfN>gTZLScL?"Ml1 4B`6Db:hPZ JSE4HJ`("1 $D|D;sΙYzg&3'3u~u& \p```````a A.`p```````a A.`p```````a A.`p```````a A.`p```````a A.`p```````a A.`p```````a A.`p```````a A.`p```````a A.`p```````a A.`p```````a A.`p```````a A.`p```````a A.nk|D￿~&"iU¥K?.ve/Õ+Ww}݇Wիj```````mK?~7q~я~gWo{pƍߏ>O o <_ "x'//wݿwUߏ־{??µk|+_k^|v^3 7>{u{v_oܖ/%?G_җ{{g߉Oyͫ^* o^Z-oիW6U Xcg?{~p=,>{gguf?0}ucvvwf/}KADOnܸWUᶴ}q[/W_qrrrvk%"OK|Їnz/կ~} n+>(7J)_(?ԂWn裏V+^ {<#Wz`]?k_×eu]~:^;|/ymEַ _9[ 7W'w{|S7a&|{C=/~9ދk׮>]VI1l[lۃA^`[;7aٕ+Wҗ~~0^ⵯ}->x{ z*~җ/yK~mVJ[x; A]q[g)~=7f__DJ y{pzz_u6|5[~7>я~g```````۲ ׯ_իWqڵx`߷i`p```````a A.`p```````a A.`p```````a A.`p```````a A.`p```````a A.`p```````a A.`p```````a A.`p```````a A.`H "h;":_mg_o]w݅ {/??"Z|-oYcG~G𲗽 W\nb{ w^W?Ł D~0X9fz|_>9|sw}w{{uwx衇'>1~|>1.x ]B)n> x<xq}}s`````vEO,ۚ V~Ԋ8 %/}{~~?8Gv^7~7}}|+xk^O|xߎ??_z|3fg>{?cu{Fuu\z=뮃Wӷ?Nf񁁁"+"K9W[¬) ߮cyn}ڵEmgQJ>1<䓸{;oMǣ>Z<{{gzի7{WVoy[pպLTcNA. W]+X ([-iۆ5rډï)mup[&| _ދ3q?׿wg᛾/} _k|w}>cf_1<~w}y1v;v(QefCDv`aD}4*VuӮڶ qoԧ׿u oxۿM߄;?'smr?6X+|#>ϏM4PvF/BtHg00pk5 n63۳uq 2 @ =-"G #4ra-q[fooƷ#_۾7}7OOx+c-{Gq=my䑃c}_OOڵk_2 $k[|h$1n>С{{$y(-/5f /?7_lLؾ%qD@ `BD$B/wURI"йޥB~^Z3VY\};*/w ,\=/_W7 4ᓟd桇E|w|{ŵkuǵk6ǰnkyL˱؈b!"?[L11Z󱬶" 8hZr_HA"|vnjF8/z``c th$3f[\wGhz|emf b"I|z=q6b{<#s D FBH $*8p>{;~99.3g.IS?Sx;߉׼5q>w~w'OOW?SO^ z*~җ/yK~m߆|˷| w?~W?x׻3pMеnX@tm uz@D7~&Ϗ~ױ:·ЈB[dm37Bj YːKt \TSMިG]ED PP)yp=:m,, z/Lb;Vse\t,RmGyw}x衇pUoPw-*\7Y/rȭ=0rHrA;QڰE[ _T.xQ-_BmwwdvP9G1FPHѻkڏJQ"eH5W ~=$v  #_>y ` d,zSGYS s5qydPxEX. #\:vcev".Ϸ< xWYw7GSE>ROia(-\PP/{'1F$JL[Ȭu7<MeèxZ_urG^ڇ+RxdwϾKu cCݸ??ҋEL'lU8ݹҒtZʵ w|7y 0}1X$@H> g+W&3##hŰ?Iwcئ^@#]vL^^&DO&Z2/PPF &mZ-P@rt51_iRG uTRuD8G{ꚨwsO@yJ ,Js:8 H\!nE2oVoOAoj\ib\ ^Y-Y5MxakA| Gv!DeQωh0!MhۦЦ@0m]9鱄￸n"nG.*t Nߏ%Ff @e+(Xt-w[TU1!62Aa.l7*{Mq!\QPY)(91E ͼY0-Y&:[/;XL  iٱP4BQ?Zqg NX1sAgľ^SBbA.i E~̵y}J\COAjCr_}60p@,Oku9#L+EBGZA sSyƔ1Fs: ^\RI@S3Q.7slM[WCxSJH>;3V-f D8DDݲGXŒa1M&.i0(\0]onvXFGi-YTz{$>5@Rŵ{&jD j $*ܚWzM*X4{Uj݁E&s'.)t ,^\͉'c[-t yWBmR91qS#ג[]H锁~3sse8m};(`jQG]g&q}oBvZsX [b!дtQ`9nUӦ TrzQ G`]2b&ˌwGYp߿Z 9T}Y-p{s BֹǮz=vo}twZo-SP$9mv0sC#?9FZwv/{Ĝ"F{#Ö:T:n)\#D=`V NWVM:,)g.x=V .3 gd{/JvBKUc\0g8a' gI.wyTib i5&4*ā_9HFu5H`!O姐q6pj C d:=VrEiSE-J/HGz<+Hg?xn2vW(EQF쯫x9vMgVJf[Yu;YΙ' BtT2f.3l3'Y}P zZVo?v9c6rПI-=\"5KyuFocQ}`oɭ^olۗr| AoAn~>UJ'78B0z\Ud%8Zb K a=`  .zV?U8P]s (XSZz6 @T_Ժزܥc^J@mWד>{`[9b/d:F gMZOxvM\Q2,,,-3?o=ث_ã|Bg icDP}\^:x'ustIM"&F̫^|~ƒqwVuJS ZU\#,捸"e:S?´ZʶO6617 8&FYkVk(jbZWd$ݶdT"m׬V>zܚkA].1Fp(("ՅR ݟ[RDsPsUQ@HVLUgu+w.3|ѣ0Sk d^c@_2f.`I{V}8N+uM[WN,pakef07s,cyndivN?:K"[ڊҒS=^ ERx" ؂EwbS|>!{7y/4v[3}ЬaƭW=Sz RYM@y^cD0m His . @c&l!aN&MjnCW-x\rTuq}Dq kJ~n\cmA= .;J]D x )9yK|$pYqFnsN\M+K İX\])HQ/ͬv`hj4Z+˙d-Vt܉٦1ZE]0,@Qw7 j?'xwc+Cl~!aC#bu Y%, ٨k?~!T/; ,Th!}ȫEiDshs.⸵dž`Ә:rYݹ2cs,=Pַ׿J2BJE7+Z[t[;tָz_Ȕs]✾o_w*[QfݳMX=ɚ̂ǟ3, g $N43JU.}T@ lc!Rg.1L?1ŃKHCMUc iSXhXee2h5#pdϮnSG^)G&̡pxK@J\ TܕqktyО ̇#s{YtChӶ@Eg R2qݴ"- B@- e+<!(X]d] {rBjVW„)NZkI5cXζeWޤORK3]S#Z;KQP8\Л% 7ziqvTRT3Gm"fY]]z%Q:o"¤\֋]7W,iT؎1 us|wxs?s̚?8±fu$y &W7PXNxQ̀' Jja 3$E JGdC֎4,"Q עmXK=~Q=j1||t@¾5fm8{`Gښq\!;+o+kg<}0-6n .wu{Cvc͑w9vb닇OnЊ[^Ε@%6=_{Rp,_u6yǗųf$;gYHkt?pp>+}XMzGGQ#%gԣu呦A.v,߇'4 z-7L | J듽#W}!SjW( bZTxQbznVD ZRXZ9jœ =\y.R~l}9kއo>@<,*tKRL.`*Z腠sIחa/*=G\ꬮE{@!![FV6%qvvLE-P6M+3V4??Ô6HqB 8!u fYQru Д4CJ|AO3ȒIlV-aBV@5 5C&),c?cXev$}QqKE]uIzN5;k@϶#-ns`/?9#)iXxko8:f)u-XZDR$(V] Z5b]뮺CHf,>,Z#̌>߃&S뙄Q.!֒w>^ٔSaOi[zu8%D,MX,v$o.*#x-W"=sVscmz^[Dۯ"]@ x k >ڡm պxNiAnfF_OA Ŋ +,mTH 2Ǧ*749W"CDHq)VgtEc\[%"cl kYMX\].rL0Qm<ђ/G(rsw$L3-ߛEv}s,\p`;d/{b\vuը@{ 3kYXܡZ<.?^67{fqsxvf]kS>,dAFτ ,aq9M.}vmפVS6-Zk_Wic흸]3^W W_[Z8lDfׄ:U?=z֊ޟOPJG(]3k[}Ll^H;_Zc3Qѳx[^T/X $"%ABGio݁^"zhq=صS,.Q @nVD,((&A78" tbre Y=j gh^>Kϭc L m*aN$RNDlV.R~++b?TsGze{xVcެM۶e1U֎ _\WѲb;/'[2#&Ikz]_Sv[^Mې:(bCחbv3Ϙ=/60}]eݼ`enR`r?d񷖬}} l#~1<5?M Ѻhun&a2ZndZ;2j%ZkXu;`T#z,Q8s+S:MS4(2jB$n[׎CR<lnܜ3r̂)EDBdob-Zf").jJndQ8c挧'1% aí^%KV2 /$.k:wLekW՘~+/. 4)P<ױx43.d틜?/vM@Ѭ5([9/CEW㌄AXbu׿~sf0rV` RO\{:˾<`-7=}r`Hd g S0T, 9c&@"]R[d+)Ҙ='z!Z511u FPKOL9(G l7F*pX5Oj) @]1@hb3mn}JT}O]-T+17Әfٿ(*,WDٜgQE J5WYAƟmӄW悆.!j P Ec9 AD@NNY-Sl\!9*\9d&[pt{<#M$異=mm"#yI?G[.Ξ,@ u1c|׸Jx.d9P[s:ԓِrdG۶:z Pa!,νǺg O 1q(㨱Xf,U{.|Eޗ-J^c!6ԊX_udZ< QoQw#x>WbU52R@z,[ pL҈+jKz KbwAHS=wUVc17J(Ax1V[]a,*EZr.Nj7 ѻ@Ӯn,1XχcjOi}au}#!i‰`D~[&Z.O0MCQf*vJ%{$mՒb{bjIZ3 e)^URHAæ\ Zlރb@ˌ)Xe~7wRTpyDZwecgemc?Yj `) XqYs3 OuܾEP J,z'3s%](T|63҄5^o;-Nl r<$t+ta-jm!l{H.$iLǂ)Ѯ:"d}n] Vxv'6ˡe~,00aJ{dRct1pԂndha!1"+MIgr@bMg@Ѻ{4ۜJ~ qŝdјd^'2Zbi}G˄FZ…b.3rnBeMNDm`qz6m("P^" 'gz "y$\o^fXl1ծ,^t; kj62 x p9]V@{ɊAj 4u5 ѾJm?Y:H&6V$G_'a ->])lUs X ZVrz=Z+P@U;`&BDkB_XwdC +!DB@B6{ҾKRlA`]dԞ'=/bWZA[bXU)![Z:;CL;k[o[)fl~9Rx(1RvjX4N $f ˝[1#mG[Z{#$ (Zr)iePc4~Jc.,xm!5UXkfgFe{1ĭ \ \^*M:k)N0.@IZԽ5D,a!0 C@`| j1.`Ɬ@8Q;%ۑLߦ>1ୀ˸ZTQbFj]LhEx 9wpI޾J~J{)qͅ *W4&-֨P1H`M:Y$ȊUihz}n~G`k`".Y' nt?xk;sDŽ&αc#x\6"C# ۂ'"Phy oŻ{QlK*{7_jρ,Pvv1tbߕUQwy.;\\sj;|;֤"ԡKd"·G} M )/¦B)Eo> ?f/:ª!jb9N#ω5,mb~nGr &CMw"iM=0tI]hRSjۜ䝒읂cH޿J@(%c"xSĭXɔf>W=;3wYa[8 73Zi:hɥ V}ƝZ6Fo3/Ԏ[d"}X , ;ņŬz 1 t;#yJ5w y]1Zl; ؟D&ivVP |5~>&so1kZwgmTU5WbJ k| =P;Qsٕ;%o] ̥?[cq6 F$MD-ffCtbzmrIjǮ"Xuρgׯի_wޡ,]h4Q)PY>åxiQI[ E'l*w:/ֿ_d@HY @vT[t$Εk V(J(d\u3PkƅhnЭ8 \"Hus`#5:٫0Z֩|Z< ։=Zsc%Xg ևnpw_q2]Ppe`.VTr.&-˜ytҬLjس}mA /j1vz,w/,싇lĢ=AXe) uvh!1V *dV*"L`fh_ &O1e`1qۯ! |=v$n%*u\WnnѱqC^}kNG޿ۭ7'v^5LCxA<{]?榴2d>V`v?1_pn_~7֟e S2-&ݠV-o\Nj׮]]wux=x bMR&0Ӽn3ˌQ>1фVXF ͪ>I=j [#=;w?+ @e@wާXpvU &u Tdc]v #4bPji9Qa^!%&kWJIâZ6+B<猍4ˮGgzN0B'GݿvV  Dߪ=~J=-Vۨe"<#T*qSP#ߑb拊'$=12hRXK8qWǷZ-֗j2\^ gYNϲM[OqZZb1 Թ &\9'{ؕa]Ks_L~_&+5K"ˬ^i38,|˱.j˲c*hyOyQ0-u%YTkeP%l>C&n0aҬZPZuD]jc /BF[ z8Wej0͔gd0g  1+'Sr̚yJ1BB(!DEssJ~b -X`͵lsӵ²nZݾ:Q7=q FN<#脵$-y_lG@*fvZ_eb_^XqoU`خZW,Y{5gddθ>@,Sش~fɦ`=w^;d¶>gh [XX]qӶ0R1#D-3xDqu7|MbI^49u,RS$s!+r8ޓ[Y,S,fӵr8Wff%klIw[מ@ d̥ ƈIB;_K^SUm1vMuc׳)0Pc2*t5)L}yhisnkJCw)Ī,ֱ9e7ǭrzhah慲)e̕>!`џZ-j1 qܐ+;@Խ-jvv籪2.4؁}$r,[(R_ #Lю^4 s?\.5uZyRHT'S''ptµV BҹDV~2uu P~zT24c,{F_f`뎀27a($;@?eU ='!L]H;xϧTu5jݸth'k@'CK1wi=UߟI'e#Fkx 94!^XuF,  3l'~,,H$ς^0gk5youS鞭n [}D]2Ayha}Z%'5WƔnJ_bYJnөܩBCK _u.@0˕+]v͵-wN磪֎-xus&϶&x}Ӆnry +zߚtw_OsgϷf-@,%9]*\>ԧulm]~}2n1߸WKڠ~_,C@zr8c.lX,{YǮrZUVY aפҳK"ܓ^&u'oFgڷk'>a& A}pOQ;\t x Onb1CLs?uim{Z3[`oKDXX2Prד.ʀr9Uo}D!ؗذPqKYP-ݕ$^\VbT "9 @JVS;7P n'm%P"z-XDԹ !Xky)X3Jq]@ j?7L%l 3!h@uGDd.(.3%U4?/ bЇ4>NzҢ +Rߞ$;]~1'p+ޒR `oŨSpo0O>[`fFfU.q\%7[m8;}KӖ0;gOl=eL` HD0ܥ ZDwn)h *F\HSr-\#%60TJEl G~/g @Dszfπ_ZN{_Z#f}zަ@g ӱkM@OBmhHī&=ShM\FJG Gfs[4^O%oJ^=CۮdgFY3a?+t_ R`3Y޵!D#)*kHvޝ\GjG2Teg@HW#'2/,T\{eo+ӕm!>H-y:Yi NFQP[lfEROvj--Exq/e[?ͶnawT2 K[ !kX<_\Y$M!Tkgj|5dʯ[ϩX]AgF5AX %u3c/w5\1Q"hmMoYiE'tn:ټ;t;wA_sWXƆ+uf`X$ty UL|.@\qZT_#{⚃ݠWAߏ0#߸/~pN_ʯ O7|'Їkkx7?|~k=n?Apzz_eկ~7xы^5_Y9TL[\NԂ{gE]Yǎw5]q"&zӲzNeUB^K{hG:=ܠ:([0u-`n~ u %B*| .#P%s3Hv@vƲ\M pEd?CJd1m:.SE@R+wu}|FpM'6!gх}B%: h(H=hq+ˈ' itmqѬd'E~~3ABsƟt# ZX#juO0e%RF/jnZKԭ7<ޱU[<5_.Zf`3r1͕C͛dsuEL{'vw;sFS ڠY+/stdnEgw`SՕtĔfR.aIeC ,4ej6F~ `^Gaf䜭gyW"- i-HgxڃBZtR 1R17W2za۠i8"W|s>9|w}{9/>яⳟ,^Wmo{nܸQq8>wwO]z2Ń>x<|Aw}}Bxfc Z :Ti]ob}R5 AXUw6b¶`g¸"Rݎ̾]+5br5M3F4e\v˙Z /  .3S'q:t~g'q6?B:!A)(%c3v|=p찗֙m.bdV %g.{h-|̠8yF{e} .la'sY7mZ  ŸAo:zzv)Z楖'_y}PoRǴA{/;2#U[e-~Jկ&Eaźzm_F}E,p[%,cЇjb1 D1g _n6kοñ:'T՗54뎎cSL*0Y<|fG$ȅ1~̘q{U:bRO2c]3҃!hjU}+>ŵWUP׷GoI;▬F-Xn lzj,}VwZ>:#w7G~%~Օ]'Wk:4W%۞lS'E*"K6BA?ɾ- B4  %/y ~_ Uߏ־{??µk|+_k^|v^3 7>{u{3Z/;@\2f6"$\Y&Yĕ4CSv ۚ$ ZYb25H57 8qml-M=Y-By"{Q @zZ7b"4]}lVBaEbHaBN@! @.#G9klwƈ`dJZ^FźDsE#7JKߔEOш c5۷ct ~cǖtF} mO+B(VQ<ŀf) lwR)2  k^o.=`hzN^yiYyj)[+74CsQZ*_j%XWR. [܎1^%),z~x:vx@T$QD|4RD\:{cJ/wS:v^' 6\f0w(urc нﳛ.fwZC B?9;,|8.<gDɞ.bĮ֗]Jin|{Pջ3t;7~|% ́ Dׯ_Bз-J)/'Ľދ/}Kx==uvħ?i>c6zի7{WVoy[pU|ӟ>v;v-sG|T]!"@:|/R%㴜ZV,l4*jf1 0F{aN]2փ;U֏^3eDQ'1E BdVJ•{M*2޵s#n.`o+HgHh);)2kIy QԺ@ A,qI=3.Zrg*0Z Q gz}֋j ɂ9g&}n();0C "2 kE4t[H)UcM> qJf_K4xI\GP'j(Ju~I5v)%Oa'1buՑ.V6)JM7D!i h g-% dV bIa3tgK;/%D"L@Ԓ[\ъE 5zsR=6S j^fα\ksXV Q aU*E> *Ze^x;,;YF':DUxuQq[/| {qvv;׿sb{gxᇱl`~nswG>|C:X?66e45$"I-Kb~"U*-k8o-JVAlz1Wauu',1.A䠋d-RQ&\fEdtAkn]խ !fS-ۉ-f #OO{HGPݔp@PSC\܈L~h&BܿQ#jQG,w|kb۾U|̣aI@(-뱻ܟY>R4!f43@-%eD3vJTҸYl V.:4?sNbje]2-l>E v?! fQHt^XsNzd1ﭽwX]:더gJ~E8D1E&!T ռtAc=XD~d#tZK1Z7-M{յlPf j`̀µ~"Up~S3q[׽ux~ԧ>U~4t羖O$~G~u5/W._=vy_{nsn6ؾofZ ?sS8[xyKIx|A ɭ`ݒ-t!A'j_ 'WӉ4 <e,DA!!ƈ;Ob$]CDa1Xs)MQB%C2"qH ̚2]uĪ X &t8)n 1LZ*Nϖ졽7ɬ&P,"<Ӻ1X5~=:g1.bcFz͜P ]jDf@(sFsB-@I3 qojUF,ބ#nn~;]lqqiPT|0%p Hqck59J%jZ@M%Ӑ.`eF UO3R$ ov|//ո~|+>h ~c=>#C/dRI"hKZpĐ>rPXóG8;YAr2+!Ƥa>O26Q yV֡%`l&IBJh;6702B@50·E2'B 1u1v`ۏ-6JdWS,&dֹ( 9J{Sg۶="WM k٨Yo'8-,1?U/=!HD0۳k.;lB&My!ĎUݛ&LӴ桇źͽދk׮6k׮m\.i1gxO@ \)$K<]I:Ib6F !W#*x;L+j`)0>[}fgjQ,/dX SMq1xڛ4`s t\Mw;liv<`ehj(6ڮHlN $^ B&1J)fmI,ЅY󌼟-Ufaɥ[r‚}QWwGA~}4+`嗑cv+&[BІA$֐^hqK!Eо֮yp느?MW)~}qlֵbX,tZK.9Q<;ns2!,_šH-1)53")E:dkѸ>g2<"XdIxTEQ 66[<;9F1Ww:hwau2\JKhZI&Y RWVV+}*]cmCsp9دvZc\AbR8peCcp6D8Z;h5 :f4/ &Wm.j [x_Ǩmbt/y;ky1/Ð|슍9"&нkh˧*k,Z"OcB7&,2zXo; OO|'^ƍ><"ߏxk_׾?˗/}/իxއK_R%/?A|۷}--x;ށ_U]z3dɘsl=@)Lč~Z1(R,l) 'ATky,`-&;p-ⵔbEZ - MtlbABچ͊{&pfk֬X-݂""(E]آ&h>  KL$%[D빉7;'-A~0K_K Sur2ʻ7]В*6R_@2d`}4K٭\&B[ I]]#Y NRL2I^lv=);cj) n(>kb@c -¬SHڀ z ]#4傈IVֆ\,9K%EDO~'%= 4@ↀI=4 &" м f8T&"/3EUqVAémҽ>rnVQ%L 4^) D, d14Bɤ%LSjv5{ckq۬zB B/yER"IФ 1@+q$6@qϻzPp֏g\oXq#<>M|~я~]SK1ۄKāֶ+s-6Ƅd ڣ@YuK^,Vv ڄI}N3p-%Acz҅Œ Xf% F%^ݗE8,; TZliYN0c.zRR<1am# @dqdV7rG!hB .yZ'p/"d]"HR4˥ul6weQKJÉ^(u+Q!^L*WRD?*F* Ec`;U"Ѳ)O\@AHfY( ԲLgåEvuVx?Vl.9`6q q"(-(\pLJ#^% Xa)Ȭ]{Ia#Rԅ}2f}JP=fNh$t梵悳qe#gHLJD4b3M%cL*5FY/̀ރ*Z7<ѐRv=9Mu0\~3p.^uoWx//⎻Ь^Ҿn}B5g0۰Y2!NZG\8ٜtf-bf,*0"gg*Zk,ͥ l75I.~R-mZ >E 739ΰ^Z 1ZH-ϊ4+J1tٮ/ #}K'nS uxb2 BlqUGĉPcu.8oz" |CYǠ& l ;LZq3%opq+IoYc"-ATHI@>tKMb&Ѻgg_2BPWZM$|p+Vўg$+E$V]jnAb1 g-|uY E 3`?gLYCk òR? %sƝ'nF%~1PV>c}m-&#^}uדYڎXbt.\A~b2}E%F?,tR,Ug)´ "r(DA@\躰9gKɴQ2%nERo g )պpX9Aku{ue[]<93rF3Y/x"@.wzŷImc|-Kh: 7qylm֔ 2Ѥ?e0R3hrDn [lf~ue)^x\ת M;u6)`C&j`.2m)bׄ +*T<1*Q PŢ>fmRa7 Np, ,VHIC<Ռb פ[ R74A & 8l&TC猥@|X \'< pd?Q\vvըsxH4cZk GXf p9HPȺXrpߛTRŒ ID{#)z-GRs !W¦o&L:G6KZK*fdDQKޟZ γ€b2DW4![̡ %yi]2a4sC[D DA"l6H}f\F#_bcuP/rGNH.7(Źߊf{tؐf+؉BAGu "BWYbZIJV^zD0qLKX -ڳEKCvEb}f;̮ 09i-<_fZxXn0#1߻xwTCĹr-I Ao?}g6 SfKKƥxT{>Tζmjd[w0DX>qT'a%m<Ѵ|/I^%SuEP80-Є{<yށoL #wi ])L[PTqZ͚ A"iepL6gD !O#UF ͉Acsa/uZOOHs [E\X]x1T^h"2[6xjGX-1j.JuiqJHh%5T<鱘,W]û5g˜49+P@P ΢)njYPK(t`IWg 5Ad!f gsrKɘQBUz "=jO%`"ւRQ,̂FHlUe(̖ur!vm/ r\p=/I$֢5J<,36Ӷ&%+N"KYעjQkjT2``sy>|@[6Y.۹k_u Ǻ`[Nfk_7A;L^kZ?Zrnc@) `BЪ ZGkB®WϬm 2Ei]%ybݯ$fڵ u`BDZW!*qC! ac/y`'Jh1ټ!WP FP\_ x ] U~hP]WZl "1Ii&%Y Zi`(m⚭59Z]7˾%'-Bb:!qܓF['DkX1H- ̕f-MP Ӛۃ-^*pҸ?PTC@a&q"Ni hY[&pb^3Bh M,ak@wc?%[xBneY a_\W¦+蟪¶'l.8O"kܬ1upLv" L!T7n-}qIXPueu{ձ#J Q{U"q[v5LCR4%sY9v[4C B&0iM+%UA+FBޒ%D#aD).޾tѭ>$ja;t; vP%:u(Jضcul`I/.0 h[@ͪ Ή8'CVqYlҶޫWű+2*z+l@ }U!P=/xpsR @JNŦ8Y~cftϔFDzoZiB&C>D0R؍7 8~ޣp1nn*aѬ_kT.Jaeoӈմ_'i׮*"2' rk'.W\Tի̻(e$gpށ6'О&#\S$Cڍw7N%vFj8k ==wOWč dU+션ĺ#d.g$%*&CHqSthҠVfF APW03 2N6[|YYfԽIjBWc&c9q3/-ܮxM^Vh&23EDšm ~QDJQn{. J^uB>/E*ak^7g.`v)iL d1u0hi1b"(,HiSCz=ɂZ.JLEҌ^LPa~w"},y$R'Т%E-lf13#K6LpZl?E=t"4!]hݮ2/dݐR [zXJ>-_=fqO9WZ'c*;lTAB0Yz3x|gƉdP%ZV:ve {u/ǩ.2Aݶ k(ksxŚ}4}pc@ YG;ﺳJf`1"RjͦL.:Da-WZV *)$Nf+լ,X2wrTAV/Ȋ9GEK NfTr ]J,X3O30$J0 a:A9*AI!JK[ޟikfX4@ `[k@&m¥\[ZB5na PcUBU{}&K12H]Bٯ5}#B@a _ཱུ] /lʂY|bK"֘AUŐȩ͖@-Eȃ|>W(Zfk<QKo%^c z?[?}7lmjQd>;-&;Jju˧lmP+(JvVF$kl>%J0Boca PY-S j[8<>.bR۱f,p2u=l]߯tZ99 hjՈoٸpFucNGrA`e@`(tcIxHR݊-ȵT螅Bdϔ"mn|'6Z2sc9E,uPUA{rUVQH_& Ȣœ);ZHG-҈mrG Ժ<0wNRǭh4xyn`bk@b H*INb['Sy uƎP."ؗND, ƃL mb343 WȂrJ)2^]gpLmT3WDyE;~ $Cީֹ !dIHNJ3i?wYa6g@ffa0UHAH&t\(2 Ϡ{)2]d7sy=g_F[e. a&%xOOlk]UT4#ٶC}5@[LXZ2_SK%U>KÉ }@][W#'`}Fk9`.^;֑e&WC+_sh(%؈?zNSĈtY^ 9kK\0&\JZE 3r$%Ty֝2@0R[8^%KKY%l`0ut3vZs.@(kvxwS cCkMm%g,n[%k F,HvnU=`1"dJ^,$:>4Bu)>c;1}$S ւ,:vgMF49)hCho<ហCOmgzC3Tw e_vc q&LqM3F5 dY֖%5h%u3dwc&ŻnNDפy6OR2CTڠf@q]g'p1\GwyG]|\>3]MΜ5hx!-k !ĤDF \%,VEJA V]N? xrY${fhEp^;`sܿleSZYA3Ԛyֺ{1uUfpeh{In`γa.b􄴥 6J`Yky1Wce 1:&P9Uk/{"-+KIkK'`&4Uܡ8ĠYźvW3;,5}ra]MS_~4jHWepu{6o^QfH9a<:9Zٌ,EqZqDrX['?? n/uj$$R@Jc5PnrZ:}h lQraĠL~VJ"L[ʆ.\qa~֨Y&<9 zMRG&D4gm::[![k÷ifOz7 jo$pn 2/xkKSh}E3<7'BTE GAⅬxpH&,b dP!x1]CdFL{^vW6Ⱥ Y{62cLJq}d5* V=%l|.R@}ϗ-#vq\fECQ TsтFݒB*v .\\p6%.e 'T=5x?k!Fj!yrOM "V>I!}w0)kߕ$uoFgB)hr2A83;*s>`7)D$R/:^CJgijkZ>f{N@i'@(Y+(:Όd[ڄ``nDcZ^T swyk.)Ot0s)pG¼ݙ3#(t1$WYVOkit%aZ[6q݉d0g(!ZyZރdSDB۪7D+Mew9Q+ k-6i6k6{F̠2幺(5Stbq-Rh *SUm4ilu/vtIQ|㘻[Qu±-y}[d.5%-f-",wp 3^ ,vzR&#,ܽm_s2*\d +lxr_֌Zz_H-0Euob}ֹ4Y2>7i*r<]Ơ(y8Ϛʱ[oU-wu^]C#O\[y+0,J(!դ`@Zbg.ɷ%d֒AlBZ8;*h[CDWd$Ol.rąНpV4#Ǟy(,|1wFPИhs3)d<(|mC=őkb11ڴ&U~dˎLƍ| nTE@`uUX o\NjF/犜3_TM_\#EpXf0NSK-x*m6r|>=EJ{ĨdLSHU%瘟Eg*`;A,J>Y>bdUF:-s1 F\fLPMUByx .%qnrT SHD;zTwnk!xabn[H']iw EovZgb&w.8-$;-:ձ_tiܨ BBuh)ʹhmh5SQbk;ܩf~6jF#"NX9kx1h(׆=NBj5-Y9åbO-},L A2jI\EA-+6pR,fIkzz҄K`R| T@Ĩ*x u5{=j\Z$<0io悶㐪Ee[K3Q4y{.*Y JV `kf={n!ZQX" 0Qp*j+:iS癈bZ0oqҎ1fLWL&B{@N"WV3a)Zd]cgʷ^ ݁!\2-@if&Ck,%)b\p6k^ PW?t&"Uh=-G{~b=vͶ&&nw2Ulb$jte\=ĀZƳհw)QxRf0ŊNMeϛŷZI0\ @V.@L 5"Κe<5:rp? K} wuv0'd5>[eεNV/ Fߚ Da+H!hlgLA4v ur - viP{2RL/!$?-LcF],Wb+qI]!OoN)\ !j6kѲ4 Q+ (\E![i{ aڪ XYS}p TEi0m'lnA xQ3YoYee٫,znnapv)wɢ_ĸbB-S,^dCgcn. 51|g]Lnۋ%p^>=/)y΅q%X6o&Dx^|Ysfeus8D(`JDN 1ΓI=2őRdr1ic.Z%_DK, Z$j$}x? N7~.`=ʑP 0&ywj[jKn*uׯjw+BB- / ?eU Vc )Y% KՈPK`a0#dZ{FRC(*yE6Az\۾pˬ\2j)ưeF)glĺ+Ơ}ۘUQIllx )ia#FxSVB=;Jpp -#O} DEĐjP! @iQ'<\ޜh/@_ai qQr3xJM dorծ0]wJ ,[@G` %:b]^#,k7ܚZcz\#c#}V5Q5--l2*JiO87C$eJl^• "6qh UB[52J6''hR<&\%b{W! 8auY]s`NYD} 1 ̸e} bl䔂YaB]2tƮ 5Ǹ`' X$\G LcVARjM u^a%RLyH),mѯw%cg7VtG0XYz =LAji s.;yJYjL|1XVJ~XhWVDZkuO~zmL;MQ'gB8@P0=ﴦ_ك)XD( xX3HR..^ fŰ6AߛXE$赁ZST< &LVH 1+Rl@ I{&hƔ|4QPJ.$Z)]$E˘e[Dv3'xS*@F-(sAp6l!Fx!=*v9`u_ZK`};Q m"ɳؔh!j}OgD_52]296ya6G-{~FD?[ۜbb8ط@̮K5EdHQ @I%  2̥ K.`)xbBHHA{`("X6a /lɍsD)Ĩ=o &OSt&HZIcc"" 1EI$ }cL2Bΐ ( ][+4bRJ)9Z6Ą \1׿6j"Di&zM8dKGL*R& ETy-_lQn#]΢NE-)z-O݀#%h! Ac([/%S=o[aq["SL#.%c\݋HCzƴC-%b^-DyB]} rŒ$@ͪa+uuphwadŠ#Oec |2 !7 6aɴ'ÓɺP[" jŤ=6w^ @Ii&% 16W,V&Y;}5k׏ qs#)>i \v<=4+NѬ5ۿ. 0qg`ރ%DScڂY?Yfpa-z؀?O^:͍aB^\.FL]h%򸬅D^VML[<2?UZW){-Ɖv-֬R 2X^!J8;*&jMOI H%l0f#2[ P N!`61!7@*JEdSB$x Djae yIK)/6idY4{rAr>.`)HHь@JC@2"RzL-EYUQ6G8uPC*Nkn*.2F s?뮻ԋ>d\OSܹS~)"L!wGD*1I[X)MB V3H`-"'ޫȃ[^h]?OѴ4O"in8r T @ԅIκ#k?:UQ3h2w ءT撝S5Uׂl uliϰ\F i@2 صÞY)MuE_C~ XǦsr1"ꂓ8s VQc vf g$sGs)d8=\@ nC@Ybssr, "QK{PJb-uSj+届y*G?=H 'ux(cCAnT` Eos.0CEK %6-X# sâsXq2OXPM΅ ;L}DçzLre6,(urc' 8EOJ,iβMt!BY`P'ٸxeuIt\ <=}mwynx/sh7(J^k"=<>w?D2H{çAx<$;"xχ8#EfYӝb=Ƃi(M͘xt!.u`$6 I3l.P1l>&85&ӛ Ple˱D~ba7xD2|_up{*!02X(,aq{w QUf`PCF1)4,Uraʷ8iyK<0{d2Qqq9,5HEgQ4DmM e:FJHJج;NŹ~B3H'N%& 4L'/N1Pc@D:i~-*-ϼrV[Kj)l=K }gj d>fDX^re?nW}`Wpm58>}ijWlcå?[pépe~_тחxxĘ-0ea.(ݰnp V<`BuTa#>܍AFPϘn  ,#1* )2'jL ,|*K<< 'JQocO{*e瞗WK{-Ҭ1A_XX@|̚20HXosO08oK?Ф1pW2M4v/sNR'LQ}lNч[rb鸔(WH)KMgI$pZh4܆%`sX; c},g0CcK4 KÝ& E "vXtLR>K<Nc:"%&56chBUٟ ,|)  UY,=&"d;o!rDEܙz㎜@I!“ BP1nD=` fvG7ɇcFݒ(<b|jCNhQKވ~_c)'(聖 ໱s;(Ouq"_eMKBW%rOYPSWةaW2qJˋ4tV4L:H q۶A)xo %Lfi<3wQO:J d&&} =]MT89=y}0oݷ"HeFCumvP:uou7BЬzG&gY Jף(["U*N 3S֍:.[_,TtI3pp 4381}$%>͡%S=^JEtA= ʾa^jq.,r|i5ב7F~&ٝDo9$|gߖohZmÉp%w WqPG ^e5&(OQZprޯE67gb$G.왒pZܕ3nGVQ`(KHdΙ_/ո< ;oXma-N#%T9O0lPwzǎ EY g` A)'dM#HpMihDI4@{ Njf|K&%Jf 8P2XyA "D&}-%;KWnP:[6AJR~3n4|6(#.NFMыCXp0mL_G7w@C/#dmYIRj)=PLӲ-yݜ M)^t@rΘa iK aDMJªK RQ\F r($,3I{JS؃0 K/Dz1o_A{G`Zj 2DɅ($) |pE}ψ.E» ? P$*yC}GmcjZ&1tlW /ާ;" n Xgs'ɟ\F$ XY`0KlF0FC|3Sin4 [RInx~ ocֱbhaa ;z#R6t8  m UF2H0լ1 3ze1QF= DZ͘-J\1c\㆖3$r,>b}[tp,_ҳV8.B{IdZ|@QAgVYB ;:x-=Mo+^k27,EpU{wН49q &7|ӎ~& hq3M&ߓo8Q:-%hiᓖru8y [Zb52$Hk)3+_3N#<2bC.Xr[Vemu 3u򷺍 9%;Ukk/zw%azoʕ(Z;O+M,.A s`z,ԴMޝdtaXj #@`-2Vym2X%>*:Z9NH\T4&G/d0@BDzsv@YnVe 6Qw €,s})Lъ!`%V. mSY"Avp<ݔau b%GF\,"LPP0V,MgQ]>4> *e_Lg#C @b-$7DQ#R%/Q8{>eRu|B jiB0-U#;2m #'.hP-$ƶl47`BFu,ׄ_hrA"Ah̀SDe\D7tm}M ]a Bӡ+dmr{TF::r].DIB*ͶIle55.R N= Z4 pDi)9P;N;${D/R5xқ"v8c0  %| ~stPxnir[f D1*٢+6 8K,(Feg|̲;G;kP)ѷ̀釗DA(qbYea+œEr(BP%~oئGjEP7'Zf54J u8f[8bHz1]nRL6TzGI z":6j,-k|x /K^Xc]K4b Z/k><3 4D[Ψ}m`EV:RsVI-(>>ZWmΣ|>-,u4l@N߿\DJ9(wڣڑ$FF/,g8^mf肄"Xlt.obyvOkѱنhZqWenYmbX`s-Z[9YP &`IAր  $X ؓ_S đi`A"HECtS !RҐ"{SF0z,7/|-xB6;(Hk6n cF ˪T5ӲW9kQR9:-wa!f.1Ѓ'ƕFII)07[ cL4AGC$9<逋F7Ɵ\!BQ_`P@uE9G{ 6sܛAmę>%e3>G8CwŢQe,l>aW4bY(I5=Nv@cF/ зwEdi &HnEANmL)=ei_a'ZX;7t2M"L-HGk R =@dLܐ%'y%#<<&xÚ* zBv:!-Tr! P*m="[_;h@;c<@ Rw776`0Vf@?/XL1 M`'L:2CηYxC#4,x_"mb(l':㗾hj IYtB-e" fObFOw;7lq}.T<;9`) Ο{ҘSvsUe: srG Fk0s`Cj=渖Dlq!l7%B= 1Gl>enADai%}Q89H}@#} ے{\l0٢ˍaGtG#;,G4p^W- i99f%g[@ [8CUQ`R8v`n[za&T@pF(ZDp/N#f1`RQڙbpz{ ZIiI pH%msRx [,TqaJؙ}Wkp zeZ \ܛĶ*րSp,Ր7MSjAъN(29|pC Nr #htd uo4S<.no>+&D2C=1p7lB2ʅ̍j $KT0AT j!lp)Ji| .^'G`yda'P7[7eGΏ+d62U$2:;KܼޚuBdm2[P1BWDq:(O]=#OT$|g@Fgp({5% {ReT<$?Hd㎪ӆ)t o*Cwt5͈ܰ5j)eTx[;,KHS<, ~tO%NսT}Ǽ-¶\&r]?r fg ZĿ1}_ !b"ɚbԹ1`,buWM?Y#QJ.8!!yceT mUA9VWX>W|i@-p](=#;Pc^l+\"S(},K\3)TmH=E`^y3˽Rɋ2͙Vf1p*wGVL ^N -jA2ᭉˠ";i`'S=GNdPaЅB{ 憛Y+Kje2uϝd)sÄg s4o^€{n1O;/5:\ 3ю>q(PZQ4m3rEG {Bac"1/LZ|jl kx:*ѠI<44'wJ6Ž,6qԪ7A,>3{#fCG~>gRƮ+L>cNc,5ڢa^0 ua۰ 5-5wc+κ`iT)XJAu"":mZ0t6L24EOv M t~1pgrci go3(uq⮜OgRu1ەTpEh'%Y7zKD e{s`#&ehvRoeZvLty8o9Hꋸ~ٲ7E]UIxN@{/G 3V "8yh&WFX84g #P+3蟻,&I+j[۵.6ɵϋM 6{d9^kۋ8hea3Ņ#xa6 "zkc6dR%&)d^Xn&I@dȸ#Dh0P䑔sИ#4$><˂I1/k(Zd f\;Bj)ސ@a< hۿ1)h:9; z<ȱ+B_@*Qe unDI`4D٘\zxæd#Q}Ļψpel(QDk(r xv7h,=Y!(cE%D&ވS+~{76pY&g' U>EVn^Q{iP> 0Q|q/cgsN>;kDɳ̲jO!򸯽r ΧM7]Zp!8 s }݉>s$gyk`7}2︶ĪGP 1eAaiK4C:6;iO^D=qWYiusIjk`p`1|O=>DŇ*p^hWtXNsf&[/2,52K4#ҩ|X*8Hy`:C`[R(Ku@rW`PILʓ[!&5<4KC F, Ƃ)4Zmpdl|/Ň9)X0(ElX6 >@F4,p =Tw"eɋajx sϷ?򶼶Gac@[پ>ǡ{\#n @"d=H''1DSpRFSl-1L+.7Ef^*soaU8UE+1 l-bh`hƎu6eRq~;T:H&8$G. w:M QBi9~3♱LHxX$bo ~Ñ$& \_dSy݃Yb:X[]%$FZpm-}Y~ϝ8y@u!rH6s| @΄&hXF0] G-/DjiOߛHurX?+DI"ɿE SG|6暉 nz~M}6Rë,P m ޻vs9\,eIax9m):|j:+Qʕpcyu/@@u ~|ut q Ţ,*MkeI zJ'u<ۜ R@"p"zUKDY/{a:wHi]h%\;Ͱkp5zNDe/ E>YyfJCv%f*?<Lh_jqD*,:u=z_W(c7bю]p꽳Dmlf;|56400yױE)Q C#cgvS5QUEeJ|cn$3AM`Zw vu5<^71Œ\?j\h\G zN~jZܤs2NuXjA:QP)Jð õ dg-GYG7vmx,xvX pJԠ@hJ̙hSm@hlh)aM #8{=P2z mTdw8 Ңl֤4Vu( \}L jXj)Hj98!JrqXد{vm{Gdy.#Zf2OtNAzח~ /;P0^/P[k$.Ɋ[\<rU്$;1q?ޖ?‘%o?wlulld>-:@~ 铳^`pWЊ,~ e|UvTITƍ"?÷}۷/忌_~|w}woͿyoo_W|~/;x||om 5_+c/?;xyOQHܖM7t geg*^81\rq .`NE2ɴʠ"h.nZ`cVI\VKee([JAQVD=ؕP ~,QJ@D&.lphx = eEDY$P xj:ߛc,~){ GJ"&*{Т$AEphՋL4DY>wX[|& 4\ę<Y^}ʋL{\}&Eu+8(.&lt Y9~$G(*s bOQ.0nY2DZ+8u(uס?g,ۿ?'<{l>ߎ^uğaݿwO} OI;/~m????u# p)Њ>_r ;]9w`i( FRɘ;'$cCKuYWdIV'R67X_YWtIb$LXF+>.;<.<><ɏ7~.3HcfֻeF,kir+ODhaʼn)ukeA AT Oٱ;yJ>(Tu#R& J8C]w݋,S-RDl6ЇʞY-*PPE) ׭C+Qjs_ b tXѻ6 >Z֩vvëc)KɎAEb@0:z98W<SZ؟Ω@"{6g븽OqL t3cNqK_u'c.eg[j3ȾLۖY 0f-掇qAcB~ 1_IP/mwJl@JTL3Aјַ1L6uG Gknچt'1%'=b6~+2\*DB:~A| -=ML!MqI"#&I{!}Hgcq>K??|3QW>ǧ?i >OOW_Ƿ|˷~ߊɟAڑ%ųXdžupW$aFx ~7H 9 rX -دS 3;'fTD2*mWj %5!1lE)'x GCìCi)U.1ױoqR mrQa\8ȖBp}$ӶPsa;|ܣ{u%>濹A eTӨ}2XTCIwyR̄Jy~ se]@,a2GE eL6;Q"@LYwv%`gv#! ↜jV pY I hOD  V67/k%rU;ǶxXv&Ͳ_,{:UȒj} >O`C5P08\'9;Ǘ_w<;TUtgְՑ@斪8- ;D]A.Xyz%,l'qF4PTFcLlֱ~d۸#LN(y6x=+{f=?'\?x -}>G~g{7ߌ>/b6||7}7᛿c?c~o xwc?c^W\/_\J4@e*Txob{p&OYt^zy:99/c=}=?nWnP2c7hoDpn>jJ1Qz1;. Z]PK HED>w0` l;nmlqҠSL`(\e/ B}.D=T`TC#xnAJRBaYpYkhowxY^DS"mOM0cZtTg0s:-,<9Nl5o,pB9m_1 2V,@K:}n5 pE(,*f0q\m(}K{KǵKԑ_*F+ŶI9&*h="e8;U{o}} /K$D`& mxWt[j}"q©Q9BT :;dhhh(&Fe p Π TҲS%33(j_!BVU.|=`\+X ^+DN8VTYNuhCPb,t "7tFBwfα 2Pla,J-P}CIsUq78Nvj8[8R gʈM@GUPȣ_mQr`Y*2<:8~vh+U,nrKW`,vp6nc˩ή ES4T2vdpEZQmKI ">oDkѳXP#Xehҙ0ǀ+*ZMA]Z 82pݨ⽮$۟ZŹкن0"$ae"Ɏh GDD`/!Hu M>P°8PsNzRs:tȴ0P4w!quL2!fo8GWc|64`{!6 ;GӴإg8 T*ՈIܛ:+G ,c: K;g=3R@SMǀ@ZeJR7>1 CoʿȠ}DV %]J?v||]1/忼}ukwT=x?==/_?y^|w/W[q.f猊sË"[ ~ 9xw팓.Xʂ4 UkzrѺ"([xP" rG'xuw[!WY*p 'rƀA\x-r{ B7~f^_XT+T% |sQv3)̲j Q4Nr+l@˨Ɗ$ t(X;Eֽ,oa ,rj?d90@"c-yG")XODlX<>[Fy%w0 b&ֱ]hAARA^ԩyzuxo%Z??< ThӤDö|n[IS5D"JYl[Qڬ4U,5ơk7$WԸ*ֆ" Dnw϶3Q==ՀyϴrW 2ZtH1)eP˱dކ[0>Sb]$: A"`&"a lC8~Gޗä`na-aՓv/~UŢ )e(Ll8~쟫aKTp%kIyb-x ≰"Jc%69yVvO0k"ɩ  ˤ&_0n-A Hw@t|Hhcns tk1Kտ3>m!/nv|s߈u]/9|۷}|ϾZ??~> ߿^_VL.lنWqGLv iN&,= cePƫ@:ՎIM2AzE>3(@dEc `7E\/c.AG'  i!p@b;X.X%;(U>f FePنn\g#K(h Oŝ_ݮ V}ũa^ /3D2OvXD `w&v'Ae ⇖P *a2~e+J%F=uK,,Kخ(c`6ܵn :$ i=D?KaxQ *& ){%?] .AeB#4g: Q \;K QFUAIrr?)֊I]@>Ž06x_˟Q&,#P_Q ddeF\qeasO~@M&w̤!gM;6?֞!4TK0wxW,:X.0F;gQ_)tJ5r} Eg#+zZ# q?@www}//}s_k~ Zk?W [[_=_@_eYl aam0é,!3Ll`V'w_;-|D3]过(a__c%bP( (Ip6?JQ+<1 )$*M^IX.|^zjSufضbt_kJac3v%ڗ"K+xl(n̅#nm |(.qOۛ]ڐ4yOQ2<@'?I>wDY?4_\7R a1)·O vC@n6O3`xvYs@JieYL3;YV(;- |hc3᡻RfՄK"C ػ{D9lsK Qz/4D¢'rO=[/U$zbH gاT\B4+4M2 1.:7}SoYqA~vXrs 6׆y9d2_,Ɩ9%3M)QNӠd? *pNgQ<@l:!}\;#??w^z?<~=>_ ̟3iO^`?0?Go${ pc _ L~qWc_qLSg'ϟDՊmlѴ>ZwE~Aһvf)qcrZh fwf+cFJQlWfÝ~}-LenATB ͣ J)x.ZѴtOe-P+Z[oxl>jX` DUΟǍ]*'G Vh*kBbCRT6 $ ΁%3rX@b>3XJ uy,Ys;ߟ:[Cf玙|B0(7v#O1?v㷦g)37bx$9hZA[8 0tcf & p 62@"IAS=n+E~;{µ}oepr~vIי|MR!߇;퍄wC~`Y. $y;ܑw$w|)OQA@أB loΠ_`ael &Ayox%>oXƿ|w}~¿w_W}ſ~>rO?1>>0/Agog/HͲd _~.jAFp}EYDc,6@н#'"7'sd?7H Fx[ {+ˌ : :0v@eO~ooco@Jd3O,9i=&824g{ ^`- I0Y=#GdkqD)D#6ל.QmjU ͋"p@ kFpSQ8dvle,U :i |00(S}.U2l;s'`sLJJ>5Onh!] 5&T,h7KWɮ>EhXF3 I11?-Mjt~s'| Bz1dp ָ'Me#LYVH_7>ٽG'&AG\$G j"X(C#^^ yu0:zx7z z*3*̹ `K1(bD |6*#At6ZB@ؾV$ξiȰ(uo9x58onsFܬ=<@.;nH`tVx8n |_8#,&@3A[Urh5w|O<>3Q^+.Q ~ahpHEOhEkA񹜰TNzB Xa6pE94ܾ[BKK( mB gs TwA' [{,Ao1KԶPءZN$X\mEҧ*6PKTW@jݨ[ 3ڞA^sf/Gh1Cܠ Ў`)oǓޑ QYh*;Hiv}dwTҫO[Q sAU&Z/y[[53Ե&(ӑ4][ù0q]^hEPZE>  z~apT%b)AhP"k XDHsRR ܈VrƠ{+S5'(aD#rhȄ->Ͳ4Z7΋ z3aε PMtZn N$z7Uk$` { ߓfڢ=31ezg{Z;VK!q{Zh:S#;VnWweV])B JܔuYO%sldY6/nRw<,"@7Ҋ H²Uti<bNKՈq7&t(Eltq8JO:w@ƅhkt w|e=QX* TXCV|< Q!Ji"O;~Dnֳ O jY~Nz"q6!ppz i3$JU~џnn Z=gţM7S)UP ]&>F7"V4z!Odp.#TOW;mlnt&'s,8['%62'yfd,>PRV46 Eꡒ=Ri=\c=h=6n$܀m`vSfX;p?|~ h : g?DI(UD;9j:6\mWUK9';zmW,r69c./vǯzWipMzV@;X@;#nl&Li^hG+ Ki!ȍ4x䞽X#1TL{ 򴘵2n6lF3sI -aPA t+`RSn# NK6R'm!%Q dE]9b\Ӛ@=VR 'm0Q~1$5|^m^ oqYFqn? Q8p<2Mm?;RHm@Jx\B_"KQɆp@`D&zi?Rq^?@ȝ4 J^c=hI{3`L" '3,ɺwL{f}=) TvO-b3p>~놫gNZ0.M/=Fsmp\ѷ&7ov(Y&ޅDob(8*:)1lfdYfeg?n}*T}G<7<ʮC, H)1_U#1X~˅}XP8J /^5:!KnwՙTQTMCq`%u,m [z5+,To[c.{ f*u"n/=+HM6` R޶žX"B;P:~ *!i IDAT9D m;H( Vb 9fIseYq?ޖ?‘%xf)^0%ݢ,aLTk"a ;P8=GӊEJD P@%1m joeN!xhq!Z%Ԛ2u1˄Vlֱ]a,uAъ TT<nnG:ђe!Y.G ]ll#渌 =ZpxCB9 o#w# M!L/s|m^33,g;/8t11lR'//ՅI76r6ƠJ!̍'d"يN Xdž"xC0>9069M4\ `Ge3ȉLp:1EnE Df3vH~ eE-(LTA0Pyl *;*ZqvK{`cwܷ*%Ҳ?YJW`#)y!8szaGsorEYN^!-6laϵeF *緅ܱ~@|ӟAoX҅V\~WcoX4ʿ% Ud#wͨTkK % <ǼǾ/y=~+DJc0wڳnW` p$5h3!iI9b=f)[K|{[~{|Y?ҥNhW$/LP͒TeۊWX7<[Ĵ5r(w0c@c96Ŕ BW>hRiT&ME#"LaS9aqo*'>OND0˲DKhxVA3c6@VHwwW놥\$IdZŵuO{b3ػdTI׎&+s#<_l ;C|$3=l1#P<^xΝe z6((apnyn8F\#q(z8\3*Q01p^JΓ1@]0\ xܘtUP΃+emX>-L,"lkvsR]u΄8D,8v*q<`+Pqnkt!$˭}A;rQ?i:T4^d,*˾A539n! ׇ9A5Or< %SKƑ&ilqQMg:΍\:1$8 ~a(XڂZh4j-\BIOx^^,/skn;$D)| }|ϟ4&Nj 9A8XNa}DbZ{_oRp@@[" 3GBD9F+Gt"ͱ42>fkpܵ;yc=-4 jwĤ,e5PP,Ҧ7 sHզE`4SV.f`֡NB[(͒z`6v#-GR:!:I{yQ" "ZRpj Y EC%ti0 -ˀYo-,5 =uIE~cNչ&#rdɓ́T&G3֦D{1]Kll*JүYns1Ƚdi'>W'`B(JeK`D< ҇Q +0T 8f׳ i1xNr 4AWrDw@} ` ]Bʝ-h]2LI Tw,wL:iEQJ.EІc)\7v64,C+S%GjF[peG|lmTJ[sቨKi2j<?nr.qTK܂Dv9;Șl3Oۧ t>-7R* R:\GE >ڰHCLn6HOA* ײ7Ai 꼆gY&?6~8p}>gFp8l@s-#žV"YmP97Jesduu8R ; *~ h;C<~"뉈`Ylq;ޖ?±x7`a^Wx^TOǩ,a<Å8 4y3=j opwx0 6zE 0!;[rO4bխGۯQ:!OҪLaa3zQmc)wRTMg}֊DtnAxޯp:I8_WYꝄVy=$ yl@,:F}يq48NpegDB$P? '˿,@)8QyëK jA+JԽ=pwװ(N5}g)wύQ 5JcPbsB07%7Ʈϋf@ 9yA Af *L(N0)=+n/ryx>e\i_ҍaviʙ.3{V[q.=nl?Og$Sl3(<"=y99Ϟ,}>_B2EsOx8<~0-:4Յ7ƃD8ғ&6Kgߖxz2|8TPPB' s7CH ?bٞ ł( 8s|0!r:^ KၦELBR;  ^p>q"j `[R!Yi kPcUO$Epj`:6hc9SVT)2I1p?Hsd'ef".=ZDK1K pbZ <-&M+QX\ /hGw>,s3sd$ӹ9!N gk.qvP ۆ<>;4hOjt\!T{={a̝S@F5pRcawqwD ng7 _OTijHf.Cۿij܏',Cv`#GTP#!}| nQa2\/zTeZE%nqzmCu͵he*@KLme gR՝C X#uŹ#KaMI"MXF~\+-?ign)9b P95^J(+|o;Ф !7gZ5` HgK4PƄ=>gZHm58T-40$Nawz,'ezl%S4dGA C ?İ Qz=Ǿ'T%qy!.c .RQ$1$[yEOI3@KTuIq6I"@iXbsI곦sgFv[|G9_K B#n{jt΍]&] ?֏-<͒9_qe_$rX>;"h@φd,kكL%x?s,CR'/{:*OLy}=`?=ϝy6921;XTt"NzZ K0Ăs׻la"UɟeAe K0\ո}tǢ, iO hRg[< @BnpuNG)ȹ1/D̀c{pH\ {Ix;6E!M | n2I) PuR{T;(2=4]V(K$$*pDxՃj Ep4U aDT QP% '' 9Ztj;V/fql0!n3q  GqXnF\|n48f-n ȷchq=_KwQ6Uӄ̰n+6z{!d K{jK=cmՂrqtɁCxQqܬCF<|%RؤGG_LNY/@p_a^=^AT-'e}:3[V4EzC"T)@ kX<[-̾`g3`Q׹rG,8q@3HE< nFǠ^asyGVɺŧnn^Oq *~G<98^Awn0҂u9x%'΍۶ :66}༜ ZҤޗv^{7(lȖ(3,q(9i@r~%֓*n#ڄhD3SJ· گqA}3(Ѐekr ;|ë D( 5/Rupnxun+W[]85Źb)ѐZh1r&sYR4qF:u?7fq;V&iOHC7@(A/|Қh~SN^}A46`H`1G7XRb(.pXHq}KXbRK/x@ kyeڞTm K=5`GAvAjE֭ZQd\nNM76diet@z֨2 ك栟`ѹ>VXBN`Eς>ngA%1 E;60g f`bU= UP3ȶ.k6}ӽ*Z1n(-f8v(RZga`uřubc xqiP -"s@&0> T@*Y⓲DGv[0x|4 TBQNiQ@{l4lFX|@!5GkƆiƳTiK`G !߹U`Lj^ o΂$FfV5gA yӂ2q]cQZsgx=SH`Wvb<:>.ۧi2~.Kn,kU<[*-p2@B B||Ow-,! !iLqĸҊfv?Sv}(s-o<'2=FXD#AQÓsO/Gx:&1i"(`w<SijIOc -bg k"{F=MLIjsCYT:'"/gy^5-bx W|Wc#Q sh3tGD6B)@Xv>hGڏ܀5LoYJ$IQ`yl\@G4?bMvx®(٠͆X<3CnaH `av) \Ry1LT>$!b>P;2,Txh0 al4-Vf}t,uAZAX45 ~xQR} FEB=0zGyДr*NbybFAm:"Da;!KHorR 9=/|&%~Py$}'!m15L[DH\QQPK#_mnALrSw^\<ˈ%:NX\>-Tm_\Acex={1ИAYBv9nnX'&P8f\lr {YxөIN a_@f,.7$ ˫1GPC+F){Sk2"orV1Rj+2A2V298\%:$"WP?a|TcK_:Ci#>d"ͨ4/ksh `ϝDP=@ |~ QYn'kI; ~|Z]D6w8yeupwXIEz VQ6a2ttǍ#D6eWB}^_POBG)s0l@)a\f, ̯>^c]WԲ(%Yxl +{cCAэeƽm[l$ؕsipyB-,gfp mg(;Zsw)2@aAA@,^pFZz,lʎ O<!2-YBS6p[yj $gy1Kl02FTREV+e-?^> s pcű4 ",f=6+3n_" ɩl4fph %:J=>h贋fSucۇ:ЇaJɱ (RPk[-l^&z7_lT}3)GCP$f/żN%Q7L6^ gR#9F\cwQf?UrKaZ&&Vò?.1wl? m0.lRPkq>|@ıyRcư/'8e ItQ*cO%\^!: ׉g@ K? &{zt)bm,EBnjXHcqCE72š\ϓkIꨱ]2P`)wUN„Jd1qB.^,,ief pM@.n 74f%M:Ӳ cm2bm"X:[2WQ" UY{Z͎ &`ޫ<>2bO(})JyʓeXf%&R/JalܶBN@L >$Co]v/n@vbwà Ak 1(\cf kZy ΰv!L>f׎"n91ށO(gT(JZb y#:gcLn̡\8`@ε'Fl,2r._Fk(,?lؤN):8{se.}+*ܜžB8vZ((,Q]rϚk/b ԲZK{ñw̻9vSuPo"yձqL806X hю3]!b)beNKse !is")<7LbJWoe+J%XfT3<\q^SHl\ [c+ҠT<)T%K8Un֍xds"{cxxZ\\rW(!pR1 4h9EK.:t;D6::[99̬g 'D6cSp7P }a,'d < P⛛\*w\hkAl{Зh&+"dh(,聯ORM*a+s$y||@[PF(#\8۳|ee{u9{9<ʹ)$Ƃ5u dg t )=}5(`3. w`ma`68S(?4"nlhAåЛlI|`~iO@녍 BXa7Tt mb.4H1왝LkL3|i]6:z逸`gmsV c>.L3{]!RXU,/3sL6<+NUUpE[؀9Gx/Wa5,v|z Q&jUHWk:e+Th\ZO*yy<s[pUy*JG~Xx b&T@_yp VxoecOB:{zβou bM?x~ /_~~2b F"oL%Ej=2N(Aenfsq^a7"kC ukSvN̍[C'`n4fg~+ czZ7K%Xv0 6xZN@] QvjDF =K";}baY>fd ޓ+vsRI&j3ċ/S(NrG6%^L"w |GGB7q3ܰzN%YMQ2}9 6D]vat|?j%4`<숈Meߔ45{U5HI[5JT'j7,?|OF@G0\ [=q(9d_'>c n@|YrWvF&tZrpٖe t54=5R+/KٵW`&{Rrw[3jͻSh!dǚ7Sr4!Cȳ;EXwO3ì9mǾA>hjNkhAm(B50ޛG] ֹwl$R r!ܓƊոc _.m 1B^q>nG8S_)<|Z]d13&,т/P<ջؖmky5f^Z(,SlDXc]bPY~ش+7gP^H9@)t"n~Ck]U,n/[ Mra4^nyO"=KD:o3(FP &s RTeEm8?s#5~Qۀg`sۚ_aG5)}Fn'V&K-: ;\4enl+H`w/}g򷗂 *07n6VF~^qT4-ϗ0G 3b>&Ғd\b{Z)~qӖi7ǽDАOӈD%"!e鸏.T2PA=L2-zậXRkȬ7ʉl9&ԩ0Xq,%l˵5~_<,7X?K$wzC6YCZ'DH*p5F1OCo#Ζ(k\yd%urhMƁ]P’yUPzH  %i,Z(:z 2GU|xVXǦxE}ϝr$@gOBP0 EUj^>ꀔQͻ7q`|X@πuq pF`r'T>c| ژ,KSe8d{8}?\q$7J !S: [p^iZOHhhfD|b(p dDI5HN $+CpG#p} [xh#e_g@(U &| :=DDÀǯfYsz1V~6-X?|,?rʘ AmZ@Ȇun*#}E֧h+T[ȭBޝ)Χf\l|}n߉]H-En;|1FgǏcT p2c,bdc(]so#|4އB}_Asu??cA=ǻ(S{:Ţ[3eȱq.pցa E"VF2OJLs0\Ѱid}..PuzJ'c"/݋^FMbmr \x$>~hf~TH|A61f8=Z dlBNH/Zv=< 8{eoK<*6YQq իgMS]FH*J(Tx4c$ &@D)@.6ȿ(gVY|^?ܽGe<&%-0eQž=$G*,[Je۰Zh%SWt#T"|"9YBX+jdulM$; K66D&m{'Rwܨ=]= drf]t@yp`StCHa؈O%+c]s \#1J~=Y/YFe% U:M$ )疁4J&H _/?@=Tv:E '=_e >ݻ [/,ߎT~_q߸~3vzO9Tr$GeXmKޢ"x>o|[~{|5*-DW[3[g6Opmfqںg6b:w@BFD¥0]WT cfIKa)6(qfh}Bud‰jМ668uׂbos!9"mH+ŢmE+ m]Uj] wrܚq1ʵ ^JՊU"E҉NInKC+.=α0|(ɘ? Ǜ1Yާ+Gy]p(,֎Nn)،zNDRC6|l֡ΗB޹ DKc8P_%z4ց$smށz76b|H^?/tD( %^Y9dVjlw{{ uOAH <nƧ0t³/q9LJZp ݰm589>9)-*%#,*D<-J h@ t)* :$zb(Jk{ōeiyUA/TPD 3q84z6 ,e =B*EEgec?H3ѮA,F-`MR/NUT7e쒁:=h u}",y?SB?2 ~u{ vU:~8OdLi `kc/*M%N0~^:Hm;2 È:/ՠQ&XN*6m lo]*A% ;U%ZIjiZ pT BD-~v;9e _FP9|cnrdÐؘ3qb/J3q.grt_ሮ0-4dw\i2γFٵ0J@ӄ xH(!(P &0gN*YU~:yg{!3q#>~찡O"pkG)X+ w )tF{3_S|5JPJrcw 'N9zTC)nӰXs+KM^@e$$rՎUHF)_%ֲ- E[cqN~̴/~`=+x!AB K0BT !8%UFpŶ1H.\~2әNV?\Üxꑗ:`xuyZ`驐pqÈ.8_%P$/N*D+ Mq&=@§EP3LzXGAQ>%0N$>bie1Mkc 0l>HcԳZQŹ*N0SvEQ0p8/~(8žFp)py8z.91xPތ|! '˓'7L9DH_op<^P S3:\|+ ܫ% sL65j8D JuH=n70Zk!BfXAP߀AD/y%]=\_1'&$ğ /? >Q7Ddg /ls zLQU:,Ӱ"t84ІɰȎFG PcYD b.Po X,9xX%<OiBТhm6E @>-3PQR8::4^ DW7;JI7 ;~=2ƒqa̽'_8x!Ĕj# iTXt /;B8`6:x(Y@,BgzsS=f){&eP۹q8+)" O2k`犥ORqkE z$>*6P5x'F$r&)( 9GE裣j O1զL& قЏƓ Cdu~B15*R$ ָ.4& @@C1->DZdqs4z`Ot{~,=Z' ccO_M85v 0 ۑP`tFz=S :},v0hSY21`a)}m+*>Ccm(ZQJ!hA3Iہuy P'f'ڊ,x:6ۦUL}ÆT$w t+6(+WBEe )1WJ"T3yeb* `wmĜޔ2G "O 8|PD!-71 Æ7}E7*k;c)o B GJUدB>75vi?8,7gi2{*XX"TJ) O(ucNTpWe!_Dq[8A%#ϋyhJ`k7w7 `X (^D%lKf DEY\6 -8 ݢ$s-ޜ󀟄#of#G3.{w+" BØ>*h̎ޑȷRH P FSz v1O1I 4hޢ|\D xk@D@cΨa$"0 qcorysCEo_ȊT;S;$hG-ځC_U8HЧ#ϓ7~&@ "GdS_ @NPk+mv/{ 1=;pdID]UYM13rM!`73X\ WHt>0MuW`\a}X_,QA/BJDl4q3lî1|vOam_qjg7N aLw u)i;Y4~xAXjt:lxp$mw@9aH$/V Km ~}y@KQX_R LF _Z:bdWwX/@"@I}c<@C4ml (J{%D-h*{(B=֚ p#iOa fq/$l/q.";{Y>$sƀigIdJxjTʾ3K'zDs{%>-nh[ӂVl<i wx DYQN^u W/T]!8y&e[A<ձ Rl m D8؃VЪC+. |0-(IUţlb[vIe 8k-EQR, (363 +RpgƸm6qnZqٜ3gh0LKvS" d(o>XLaeLjn? 4q$ p<89@nЛ\F \T2*z ;i?aUaSX  hBPadSD;} `!5v)ՠX,hqV LJx,/a<[#hE0y؆e)HŮf'j/QTP J|dGY<[*8/5:d)ѻ/>,pWɕiIM728R*UTGq@?EXo 8@eR** >E) ϗgT Nd::ad,t#cMd\l̮DFLlx { 'R(u!9 ( {؋Zai|`D"̅cGJ4 PǤ0xD1(r((>Pu3g@QΪcm PQ:Mc\aئtMTFoaF}8`Z#jakT4& Peiag8ZxFZA'ϲ=tf[DRD &c=>Sc=春ܗLh1ey)[PyX&"T@:+S,=b9n;{,s*$; c$ 9(zn+y {p_&f$@ +LTMW~ *zZ5Bsz#Mhlܤ߽8=c{ 'sōw|ר-q$&`iv```6qWQ$[aUdQ cDpn+3 MS)^5ľf8V+DfTc".9&ԈdZH]fQ"z@;^G]Pk6}@rq8w%o$TbQnK{ oc7mxD}G)GG3& & X#`_}*&☬(jR@iRPZOzQda\QJ} /YW6iX}lOTa3f@=aΝ@U; #i{J00'e 0։kh[!`uŹ:3"ՃVj - `` O32DD["s0/v W :ѤM ׷K2qӷwY) i)Ƿvqa"` eH&h_]\c 7|g](_np62s)}9R9g=>xS+; +Nhdl _,qhENiiYߧPb(|[b΅(#)! ]XaP-X)A wqV w rJ<E-ФSh'vX=u K^L4%$ǂ Li4,ǯwX%Kĵn\$oz{~C62\@r*ri CAn kǩH=z#wgP8(1&6>$bڠK嬠<({<՗mA)ޮzf P[>͙fU4!Ds=9%uɮkMQ&ѭc5R%V#Ud@I 1 tf k;t\dqd\01gr2Yv%YTJE SD2;ͼ=_a7Q{,P G=JHջ%"Z*ʙ%08z>sV ΖJx\ZGJ >)R9£MQQe\Dh|m&!(p3S]P4Ȥۍ$a6BB<w8 m_\FԚ R#sf{'( `w+_s܏#CyD 3XOћ!ҚĮByt$b^SN!X&{Z%"iЂ $MQ|AMĭGs/U @Oτ> ),wE2nHߐlZ0#rwCC8@Y;"_ s?(O;~ݟuizy]frh<4[ǰW*db6`#lآ7y % jUrKѧu}RiJ?m`0"Kk+\s'M%M 5 7@C crCP yiPwi=o!1i3y<sO-|}m TsAװnWq߀Th+2ޑelЯ@?49 Ͷc&IvmN]0юVu-)3Q=ͳQ) 80/fpQL'B닍ͥ,0Np 4'A y~i!Z4>&V<ӆv7?'?7qw|?t7}7ٳgo^/ߏ>_W~,Qb2Јa0Vevw7M;8> Hz~UfՆRUE'[+~@j${- EBka :F+B#h1~z(\QE cx^j) ry9:bD0͠iSx&54nt^s.qtEp-Z_;H*e)>ʠ?LN= .=x$gIwE!w߁7&~??/^q|ǧ?iſkk2?__?g̟om ??uk_{7Z+^)~/۞1rA&oD% jD}ƀ8r*=pf w*1-; f~I,p]RU%j}p9p}P7.ErKY8qF$ڊن>h01Ұ肥.anLkn^ϗd\a]&^PȹUɦC62SG/m/ý FN:QC]cQfݮ˗HPbA:9mƆ?}wS9㮜pniSZْ/ɦ5L'>(>HD]9-De>/AᑋߓJ`ӽeQr9">Oa~vHSCsxPBAD|N^`\1:8=,TXmPa rh Ԩ):IU㵯X)pb10D ޺= "&r'~,qDaJ90c m^S6w,"{)b =isZZRI9e*0[0#^][ aJ".蝤 o{ۭQ>%OŎņ_Ǖ]|pL纈p{ /_§c~O}S/?2_s:~s?sض5ߊ{{oͿ??}ϼ5^^/_qu,10yIz`}W-9dr0sFz3̎HΒ:,meXt~n'k>SY, ;1c' x>M91E2be7E&+ zX8* %&fǁa~[P&b{ %_8My@q7B%2p7:MR\XX,v\s1~udt~t OƂm[qj'ddg̠Fw4P\;RCb+"u@D Vl64Ag)\7&"`PZU@. zb& p1;1ّ$˞!j DoGqwÁ39->0O$Yra54pf{`0#.qE TDg_pgJ<;uj- W/dQwotWM

i%lu$aεsr}@ >?/祏:tw0g?ٛ~//,˂O~o&|3o|g>ۏȏo|9QD^.e=}ږ0lMEbB.FhQQ+Xr2®W͐DٓAPK ޳C{SҦuRPj8p ohU:m_^o%̛REP* uq/fѴ^f7 }ZTޥ- JLVA@;@ouvۉ_B|,=2yf=oOxgY" SB(y{0^Çe0vʽoذb+m~ň6e)2-e\8j9Tߙ!|0čcޱ"Iqq49~::fX{ | *A>>6p \zu×^^p ZAipyF20 lݱ/wñr5PNp,a)BzaN-E+'7Е]LpQ= l@={7pؐ̚}aҢU>RuQ ǰ(Xm}!,3\<g FȞ}=iO];#JUWi5՟c1(pB1੄~ك= E-KU(@o-ɑI;2"`+ 2QXwTjYPcoAbd }ð8CqWEЗq{S(3b E>~Eہ;κq3"Y$۶#n>VlE|V3_p7=k0T (!/aMS25dp JLaU /qm{zm1TD||UlW7%<>{2؋HRo/K? "8E ;a'%wg$>+8aJT&GeA9+1o¦hxv ZM0,yOnKTw ߘSl/qc[+Ph;$8IK")mzr}C{ q3hY@؟Y up`w*ߴo-es"x-2/~q簮+/ߠ__7>K_bn wXO_Qv$|`uFк{$%NT` OnŊr`Mcr4oH/XmZi@`qA4n `аE1v+{0hŦJ4 '8p}u@(1݇jDW0#(KC(fxvV Y` -'}QŰNbaCǒ9w:(س&]{'eDEh $ I̠1ޝO8t>c":ώ֗@Fq<0Q$(ݾ걲O'(c&A\K$rvps Y5h0_63f2| ])lUQTp. o#ӷTX*1D -zckoC?C''7ov|sOOw X?S?{ZOO˿#;|~o->$~K_BI>| [, h%l$ -V}%wt#bb ,J,|F<0 ;\襟\0 ` _X mhM“16֠SBiن̰نk߰\@{iPDQ`1Ć:yh!,xsfV]2*V-(E~[䢔YK& q9Kxm}?UE01ix_V.FИ|<#lI >ԹZ+(4võ_qk\S=\p5t2y;: :t 5Ȟf6@}tl2Ie@XghRa仄ط: 1A"(yvm+1 :ѻc01KMq*0,` F`F`]T%%ND22_w n۽&n߾ZuOKQHLP5ۀH|DF#TLR]= O08 qf)7`gpw5,D$G];?h —O" L~ @Rc@Ŵ'f&‹b̦A?XVW!"s;K϶N?'v#xqww60?#?oomO60_ |ǧ>)o/?h[o ~/{T :q9N-&GOAZ12 TC6t\T}{oq},-p$*7jW`pb`d{*Q#,~j^Pp&8Bt!8dq d䒍N"H 3T&aN["6}h- Ki=K%*ML0g8KkcIX! M'߲][ȃ4;p1;h\*qq~l$'m ! $8 'k`=y_tno _3gr߉l%X1$"_?HbN2{Yf?ۀ6O*bɜ;,ƈ:k_w*L==71?/e<>>/]߅ ݿZ+ o?T ? vA$-T*K Ⱥp ǾQCڵ s~][!\\> z<"[/ A*|\ffocú^pO\P sd`%چ*,RY\5 ra{=MӲdъ _`EG` v]@(ѦC"u ҹn+ M+ȉΟXAɞqqLxoޟM9}'yIO=`y<ܙn=> ޡ.>K_[6 oɛ%2KnoNDĀsM oF5otNpAe~3.\&{F7O`i DfXm3moSTv(rtXvlj)̱aBݑwX - J{tZ3kap@a3&{敁 c@Mlt\qn AK3VTldo`rU e:V[mK*mn!X*FzHO6D{b:=tV{#ˍO8G[ΖO7|PsT<{!z8^r=c dm+Jy")h(or?ɫOVjy솗/?g?[?#l_x&-1 bk]SLUYG j,՘ .r | F~E0nj߲*:Kn+f JXaQ}:8m T@R[ZS,E]gpp\<8ixqzFQ&M*6G w2gɏV+ckQ=|T ]+7JksŠ}t` I쨃 HX~*;ug/}I?/3} ۞ͷbrA{/}ųvF6ݛmJ*,X C 0: RϨZP#A!XL\ G+n6HRݯe^DaAbv쨪\o@]p6eV$i8vC-T[r, Pf`N_*c8z_LyD1bnSy@}0êkߗ4ny JhDnGDϟu0 1Y ˗>ӕϸ=n,i~% %\%=2 8Y617tggfiʬ=K=_Sk}%oi}= S̤eA+yܶa[pxɾ R TjL4􌃭p.J;:GP\F7A+^zz, o 6:tu$n+0x(Ħ5M7nO! w5[57'\,g\&OLOMvZMD*GOҶ; 70&I-=b [4Oα$ N84:(HXSCm Lv6*PT8`N/@WG&ؠU0+;jeٙX:h `l_qka ]J>0OE`'ADlx?` u2xiDh%_y1s37hrH7*c,ƽG,ǐ`1pd߃ 碁VB>hEi1Y-Y’87T }9atu-P@τȐa1^@ES-[!w^ ^~"sNIޕCgVcT|S.<,7ˬ8DAGQ})mnE{Wcߜ{ͤl?^1N󤓪ř1ЃiŞ|BQR>TҡR*z 6|&M`\VUbЖGCF BK>}d آuHiܯܱCkAKriXp66w,GjE-n4~Xu),85P`@h0(nX_I ZG5 ZD2LJPPX E k,*[UY9;c T93oίcܪv+p*fO؋}}U%pNSK H&XÞnD2Hc9xLbXf/Rl6NNVl}:6<+R-]஝Rx]=Gmlx M*NEҰDKJmk1"KCy!JܫaK:TRpw JQ@ٺpn$HArߗ&Ձ E.t5?mʷx coobs ͱ;ʁa'RpO'1؆hxģc,x&TЌniZ#coHHnDRpPR50;}𽊢.q`3G|Rq(;Ҭ3(#|'H,9)8c<-摃RFz~V/K󸽵7O ,c24D/EZid#w:*n.y[rWh %TNlcऩ$D"0!elcC L/I@;:A7FP64&Wx3)16 Xg޽ BKȤi)RY {'?_7uv07~g3)ZFnW#'o KbsvOaFPPVvx~996غ  "7˿/8zǶNes7h%'Jdv (r(O%E oxQK8>~Nnj=^\p*whP˂E@5JkSlN0\[aťֺ^-23(>ܠs- "j 2i={|d-|+P}x! ۍ ^v$OG`xu3'sg88?_:oc\c=Yi6  -}wzVT3 :1Wp2gi𮝡a_8 J`01[R`icЗcG:㧁pC*хaxG'^ L'㧾bL<-L1KH{p@&q 4TĶ%9Mo!Ledk3xqA}|ze/ ~Bءų:"@ ;CgġK28"D.g7=$cf Y dS2&,_#8ghZq,šE)nl6N`D"_7^r nY9_irF^ޣv^#Ms]c AvGEd" lM9movwvf!saHTTzqz^{v`t;@,U$C7Dt 8r]Cq!VNOeL: #pʠ 704dua03@lS7=!KD$I^i;/? c@'ia(u\ذ0lv_wg9Q/Xt!@@w/NKX.c`(ydKO,% ٩0=XDk)hUqjV\.FQFFCL_5PHV/[G7[)ZO{#!+͜s4n<`ѶtcS-n6`4gT*N4 ޿,zXPFEnpeGsâ{_?(^b <$)МucgkңE@zb7:~#}lBГ$m]?nۻGزxPA#:d,HnnӴZZ8.1)(;o\q \yI(fiFgˢ@BF]EQ+0KSg D۠'p x)3.:X v э]T-8n1`x6낪 j)QᮟfAnB;}Ͼzj-9"Aa,@xjq>>s,'M' Y[zo @(qO9Ғ瑁g75/}%!H DWc5x 0eDIˎ1 9|?wX.X)=Aէu[7S\[ٌK9&t@ac k([X* b/3@k6Zi)Aȱ+*O? 4euG1qLN$?z ,vb 3 aex#Ҟ1Ap4y!vӽVPPhvy-qQTcxA2Si)tXǰJmb$=@D #&~+q/WlT@{%dFvD_*)KTr,M+@Uv^ZfdBX!Rm@V&*PV (^qZg0ޜb! ރ2@5J$\(eReg*!6e7˕f(9 e[G#9l@[. J#ceL8`9ycT1A"n# c  }Dp_>sNћ b;d"6RJ$ ة D[y`sZ7PhZbu h;hAs$Ph\nFѢVj'5Is ʅnl.*CEjP{-e1Y1cϳG줷8*\Zoq,٫żq>ۻNgs fEix:'DO6rPĈިcۙ-q3j:26?r@*" l hwA W]iStSHn >W̒64h(FOH0`1Qg]L|Tctt7ܱx`f+zm: b Hxw1*% ە4>-d2菽=m Xs?Ё(0 iɛd#q/-@e7D 7It*εur8zD_ױ FWw66lHhty t+-l[F(zH+EZiSHsܕ% UAvy}* B#軥jz:LP {6"3 1&@3TgILKa?@V|}ؿއ Cݠw,ƾe4;|^yf$kML1-j0EnnXjzqz*,)O+s+*!qU~FD|xz2cXsjtx_ikx? &!'yoI!@tXt@#+0߀&Zq΢n= > *ڞ@㺽+-K'| @ + tdqnD2K`}a1a_/nq'&nu>}!d{"g@=ǿE&J]ey R@"lep$\b(H<+۰نWwXi K Y2Ru,Vܵ{M$" J".0_${cJp鲍d|dj=g @~{((+Yʸ~,m@Th+ۖ!'C `>>tvÂ``K1  Y+^\Q Ї=u;u\G'= Z);HG7vqFR,Z6F:F_1QĠA}Ho6ãlbPNHyd$d^}}PUT4ڬX[do b}3DYYHq,o|{(^?&84FkLf&x ^fvphHϠaKw\ruű4@=6sts\Z ΍]_8(2zhmg9fc9vDʒe\;Kر:oKo=Qs-0l)H쬋9{$ow%)wب+`ox%~W~}U 1I1;Q8@c㩧E ?0,ԊRQE6ƀ + k'9ly'Q~AwBDdžzz> U] xRJ [*ns)a$ڏȌEKYPe3춑\]P|!UN`}\{bֹP}vsi|]ډ!3́bWc x| ygѽS|k(ǿsrHjd/8@ՉxPwEBr&3KCTq%Pal lGJ;M!^ RZ^MX-Gnca#yWh- ./ *<32]"76}y*c IEi'<^|SKDO@*! ]S:V@p=DC۱c481@?yq5XHCvcSLHx}p(3f=6<{i@I89&iSi#DÀ>~=y -Jy5R  ׀y$k@$ x<XP♟SNߗ'qnxwwH ny"1Jۃ}zr3qВa峷.lg='x,6b6-& pQ E9&7Fskڥr! ,06c5Q9AŽZ1q ΄X,308 hљr Xt?-JxGg`WЪ-'Բ95rϦbZ1tcхw"]"YZ{驨g/~z@ L|K J;̃FpAƱ e8}`B2YZ :=y }ёٖ3|8L,0OTVVr!; B>8n?۹jC%ʿTz`h CpdGHV,'Z (b)*b yEdCID jeQ%"؆V{a*Z_ek`%uRdS/9\o"8/9wA8~7G)D΢iH#'3?/aD  )dz " _F:B䕓h {BS($8M-$1ihH20߫'@Lo>f(ea|ɇ`>YUe7~  /$W+3R I"c#ʄ>nnt{~kڗȨnp5E!O(Z,E#]#LNȆ έFw !{dDkP΋ryrjî1h}\m[7n#7~ >}ckFX1=|] =jD|PRq ϥr al6 CЇ Or `+-FNZ_! ?>+?CRy:52خ8{rKX\hbUm53藙 \A+'> MYvdHFD)Fq}nZTDST[h(((':\` 8U4 ꃓDkr!\":|Dוb{/.|dnFq,a2qs! e ?Z@\@W#PlՋ6<+Gߣ`$y6W6iYϨZܡ mn$=!WC S2שTjSE7A)5Qst@P `Ne:^]t7.<sJ^Q]E;DF믉 3 P39Sw Yʓ vꎷ9%|}&r'Wbx/4 H-rP |㘦 VbQJFwp|5`].}I^y9*8/iv}.8-e&qM:j f(m̛-;"uGbW6%0e>5DCN)K ֠tR b>T vO.lZX̦" b[JĐkYWr,X [G6&!l(/Jt.NAD&HTc(a$]IGG4N|J° HfۋF'x]ԛq?n^uq"@ 4x~>ǠI 0?6Vz$KGT@$_^Kk6Ww*w7`{XV}\R a.A`H?(pvӈlOarCc=V2PB)$ mSVmо.Zx]6: 8 |nA2`EBmi>p.xWE ݡd',gIc0FGY\'ǕD|ԙ!+K!Raۆmtl%pP86129^RpjJop s0#~9d~LD ɪLgIC)V{۱SY.T?}F$uXLzƁ0xȺ0,Jm w@RUYfBka#q_>}{g~ ѣQ9$,5L Z]X{ &˖EG6tI: ,?6h"n<Ǘ4s D9u! AW73ֱy:6lFo(3?HC$0НUصrIjiZ >1c)D dp ~Gu"6(cյ;SHfZJ b@A ()PP (ѧ@g_Y\#s>X_㓧07#/LnSTضҗ-3hA$\ZK}ކuD'6ѝ|'h.Ky@2r^\Ci P>8c/)|l>`#Θ>~¢HuD؋ZC#?+D',2hOq0NODcI/6,=:OKy=Hio>/R`3}s=#faY]?×/w60ﶏ'Gf;}@d3 ݂S$iÑ$yq,i,hMtTfcӘE6&x> hjO2xLppBts&׋Y~pN;fXE,4[p(ѝ0ܵ;f)Ha͒ŢMÝ=uh48 YF(AHn - XƟ\bR2S o(׋ќ0.Q=Īn{Sd};,QJ=Y(b1r9jPyDLt)^ d1lRׂRaX Є,X2|5֨,4R7*31 +{a+^+>ŦTg^ޯگ`} \ΨJ* $e!lFf+>\Qn#,{awďjxB(,e 3\gwT NK] խ>sTUкUyf^*ౌ3Xat:'7HG|@>*7x;C uersR s@2rI\j"5fZH-@9(thhЅvqJ9X'{wu,;' @e"Ӵ°awEL.G2cGboE 9;he׎K _ Q-7-IɦŐUqʾ\ -8,=ҶFoIی š $zB'ӓ =cvg1ߟQ=:{_ɽpPٝ&B'#'5h0EBu81 ǫ EĜ 1fu0i0`u @jE& 0 B Ȝ[x8O}-j"qò]n6o0]Uw̲q}DăU1BB] #lYҗ~_w"ݘ i`//gK,ZhfҊ[=&\cgslG@сF-T*,D8 mZ4 jXbfav <Մ|" D^o(zBf\CaтS(W=a<=S Kpkpd9( NEQ '_{\Dni((NMqlT;%K%'L0ixZmT@#il_&>1'@T!=R)'a}N<=#B= !,=,ⓜŢmʕzY.es_mQg xalfށ* w{Lu` ,Z E $K) l]eV*JQ.!58{n,#2;.I[vz,斝f'@Jy>(%Brs˹,;&RˮsA@8%b>{؜D89c0ށ6`O4Jka=$8-;fvI*"s`Ge/|m6V [# ST"Q eXe\*NC$69) B,X S9&0mQ,/ mkaC tAcgy8M ꀣ`p!߶+j]́pW(EGn\B!^ه-xz\d.8o_~XD鮱+9"zEy04w( bTdZ)kI9˄}"F] l7"\<ÑNR98K< 0Q>/i[C PRC"'K&3Q4u\\Μ#=ciaxaAܵu?11߀;3D X\ a`)V Y"qH*5lI,mJjC3c+pXDދ Ln X19 ˿4x6J3 )cW \%W*jYhe@D7`ϵS-FA"5Pͱ@Y,ƂFNYU͘pFM>R pla U{l9pr`[L(.uJԉXwـ=r"Dg)V &k.A8Rx#t}{5x ;+ ~YYp/NB 3 G{@6آ /" ``DsAc3P1aP;XeBk`oiD 6@\!PӒn آG(Yaiŗ(ݱ':s f~CgOih4Ohl'DX/)‚.؈ HW|SZ`p<jD5'ñ~Agi@v.*Ɵa}@Dp&#Gw*_1"l{=K*]p|F>c-++B.Ԛm[MOT ]HIbL0Ʒ])Q2 @ 2q1xЉg7!pYq#KqZzz{Na}W~W[/~{? w1ݧt`68!9Kc0sժh!R0s85:'S(!w"QY_CBgWtD 8") RZ]R܍m lڴHtT<ZiU Id*Z9u@:Ir'xׇ%8qTm`놵O爢ɩKn> tkĽnYpg S%8E!FcK8.B_,z!kgZĔ=F K!8RDF 8r-_ǕVG$]#%lp$bZrh+1*+ԟD}p|D9C4aExl{/r)KHvow ։Bpb@ |Dg7׍FE >6XA؀ k?-bh*7C7=_: ͩ`*S ;:{P+ T%셞 yLXLn\ݗcȰ:p(G^l|s[n~ը+Ѥ-$)ͳ?C|oJﶏ6(1Xo$0w6>xX;սF, KcV06v.(QNB|!OÌ;̇z}ò[-KD~ .oWIv3a:Nk@ Ncd& q aϊ/+|P/ l"6PkOǀV/X7V6UP߀N)GDp\̵Zf+qMd܎+Oc.y>]!%cAVM7R?pw3 [W%d+ ȂEЇ(ח ٟ 0OYƌIЇ&kVR:8PA7Gb!zjuHiXB"Ѝ!ȋKcy#3eISrvYAI0y{PRt^1d9l-*Y3`5NfGUw7`ۜ1FT;{w9ðv jWAuTдAn+6N񐲄jb9 CS.4.Kޡ ą-\=C<Rњhzk6hܫ j̮U L=d{0.gk_Uo.rX08$FLᯅ(K!GTy( Jh*H *5<8PK3qI1w.Qd^p{L)#p >.qoC@+^=.{([,F _)Yw+.( q\!|E`oZu[q  *J e3{a|?ÀK*QST\"ʇ>2#ǧs ZՊQ:MIʢL8:fjĬfaki#R!+ Oom268k 23h[IPmsnCHjg fU*'4L/L:2H; 6ĥ{Vx^=-,I`b(c&Y zu08jQ5R4("*W0-f6G7ft{ƙ&<%g0-@#\/sޡ,QL1NĬG'DU0{'Z \J̧XoJ^@[Yr}+mx7#-% Æ'kSѢm+az;|8NC1}w/,i"Yl (.rAThe/4>pW ICӴPU|@qWYobahzRZiXdAZ^_y{Qn6҃aES?\-gK  AR EEUR[QTX oðȽwln#Wa٤14>1',U%M:9][,D^޷'D"TJ޳=S=EX oy=̈B+xI mmj>%R*h}x^a) Z.%Ǿ2V} (P4/ _}tI w\ cFUcrB MV"*ݝ((XEm.'?høBeYJtm[J(%4J8kM}6:|߯Y#D $Z\cD3PJk=$ބ3 *S!J/1EJtK]`Pvp\c1ܴ/Iܗ__QTpHIF*:RhN|'gE:4L@\D"=Z*5yzC=`N:#̸Me`l H7N/dFe5 K-N芍eR+Z1ȚQ𸒀|uu jQ,5ʆ b0 *O3\ ҞWz yUވ܂1lw _NdƴQQAzNrxv|6mx¥_eQ儓,0bX@\q+.푥 U|8۶ƅ?NчaLLc2 3>_կ"  { |ѽ8@Z;K43frx97N+-}Ja> Ro,bOJrt"ʓ8&E@:AZfV O-g!H!pOQO = W-݁5즮=xx"as-ct.a8@٭nVA m(#V-W3c-\=[4pAd 3Tf\#}Z"b "rzLAJoAQ,!} ܬZ QBK9k%b>h wT:qcAMY +N΀{ʱK{.ct@Ғه!0qT1v|nZٵD+F.P!>&0l05V˭³劁rĆ p pIn"{y%^sSx0 ^U[9犴9n!t(%r%zkq]#RG·$ֿQ-9rPy%4NYw([py07#Q WRaA~Q C<ΧGQr(hV"g{ m&&9ɓ8c'e, L:p;:|Ud\6<id!P,医r)V ctA>أ_pǩܷ`)CygB;qR+@ hܤ|: s=wҊT"V+i`"kgy(+˛x5|P#5q^(HG0C`t*P)w x-,gBn붴0i>|ߵ}V6U'r#QJBLAh 77"ꍁ^@H0bBrraLNUT*?y9Gオs|K,:{[ks1֟0-F ԝ X-`Ntϥ@]olE9ZYw9QJ A+ct\s2Cx7QJA-nT^Jå66ymha;+l3e^6L[9x7<WfخP'74lDu7.ւsQ@Yk!+Rp}hТ +'l*~ZQDi-esK/{,~GS#;*8.ᠺ -{ %y?x}|SLE ==Nc,n_ iSڈj(= ON] Tj(aonv&uxe۸ JH?4xu WN~4IZmåQ_TkqR>l'j*ME+n$6vQ *qht.E{%?Z@x_,B aȶW JKA3 mr~Ja 穔Gwq$w|ɧ2(DZ[O ;C-:Hl`>6PQO|XNAKnY0ߣf|R%!c,R!$ܧqoZ XoYu\g7߂>M4râУBƀy,,nnΉt:#Oqp'lMU:ۢԳHщy>cؾlbPaqiSCܸ͎cxeR3lxWP#uHCrN z+=Ȥ" z\]> LP5j p_;PUcK݋Uz~2OW7+ZޕASpVn8w(F T6/A{yaWrYO,XL=n87zy'&⪀xЛ1(WZ!?m;7, VZjZX4EH)ۈEqպj{Uvn|I"mX.Dxo,< ٤@CX;ڌ̷o?cG;`$Qcrw-ސ4DgRW#w0c*;eB`JG/Wr7M'X~CRWf?`vSBs'Ia1^2חJXXrsa!ckiϥΉ.w)?y*͡ eP{7{Oԁ  e Rb)O hJq4]*YߋVEޗ(JLA՚zjx9x-("\-6; t'*jvP9ܟ K-wHUQ"-2ϗV M+P FdB &y ylv2hםp"WQ$.kԽZ*P",r$s.h} S$:Ԅ;ˎ)sG h*"Л:y.wU_rwΠRгK8ܾTHhXO/ )/0/xYzoQ"6IW%G)-PTgz(w"Dk \bi v&Ʉ"/[qw<6m g`!vwMFleC* Ħ-*wXO)]I-l;h:a<ԕ;+qn" & W.ԍEbHbVن3̲@bhM±p" -5Y$ZL2Ek? $E,$[n}cvC\G\Ah &7Σ 8TT2ע ^39-ig(%=‹ғF >CFm@S ps 0-hN1FCVn-RI 7,]}cAZ+amz-Bwv. 9y9Wl1' |Nr]B@^ѡm GZ}܋Vk6`2Pp ;JĕʂBY߬Sb"4N>}8:,RbQx|)Mw*yaMf^Gۙ}3m2P%h-WyŜdN`Z *aQ6IN{}9A& SEic сȩ/@t+o{YRg<^8PS( b H׬E|aeJ#D+Eh ].uOp8 \7ʼn`X-wX\@B1T~ ͩoFIˎj(mzCrE8_ؔU(Y=kwe\ζÑTEqp9:*=syE&cuX"b]0oנ2i]|}IvT)<7Ỷb&R/c%78LӠ-G/) u͒Eًt€EVY;y㆜;y=9v_v???_w~g5Ϳ7ןo  9o~k] >%c{TC:C,͖ @ہM7@890@]'+% PĥD,|ـaBݡ\0/-1q ,>hA\js50#ZϢ͆Mwl赧| ` y6nԹE+n i0wV.JE-uߴWcKaΉ)3LG&Ff]zɖX\RSh}c'&s-KZ}Dj$R"0EiQ5Zsnl+c&ǘ!((5ԆQHA% L DIE/GzcO66ӣ-3g=l1>#ĹsT$c (U?! Ҕ7lm889?%: '_VGRL˚CRѫM;Lۈɝ@ ۋM,Nܩ(/9.$ 4TZZk Ϧb*i Ux@oZsCDS5); \E aT$";SfW""j*PJ;FAYk\u,Ul): p4ّ^Z D-t]\@ %_L^]s)%8| >_?{~?*?]޶#5?c_5O${-~-ȅ@Uնwظ2 ʖhDDe轄*2;9?Pf7<ԍ!3opbb`6')e tdb9P;~b^%YA~uLa\in5BʆC@!QY}LjƶoٰkCU?g7!7 H8DQQ ;l'Hx݁e>\ش.ۤae㘜 -rbU@vas:ؠt|V*>>aB^piT (jqVH\)== 7&Dft`ۉ6#]&z8 T@w:h^Y4hQlQT`E챈wd '|/scTQa''NvžħpZ'lr8~f[a4D ֜򷃂j#HVGc,ÐcӢ>LXaNߙt1 ]?_///2/w~_6k%^/hmE6B'Q5"guogpl6Tp36}6W@h{gԃ,im(Xg6BFQq~u|>tCb*&؄ @U*DD; -T E֡.1'5Dw(Pc|@`" d:,5lR#.\sNO {q``>-ڈr;?8a+X | / ^7̭5[F16PTu]+HpN@Ll'Uя=pѣ ""hA18ڭa11@^^.+.x4fx0lpRŝy+ w?C?CɟDʿ򯬟5_7~ ~*ߊO?o_rXJ]xO䤚( w ACUcxGJb_) 8qE\l)t<3W3״VzUM' q7yLF5-i;8< #6}/JsoT-(T*ӮfFt8{D"ib y52Eш7 ܵH,(&^p _Hjrpus\"⌻%c~YyglYCE3_Y@"9k;)8}tܻQ'K(I~0^܍!'biiG^9@Sx(>yh*ͧ7%"X幙,s&`$6X8>`f+'KEbXh4Ϯ @+7c7&|_}]1& 3Oo϶Ob+>Ɣh (-U3o2, D _5pR7^ @5vEP_ơUm@Efg,L^@@wF o:>}FG75`k(twKhE&;'ׯj?zu'(IEV ;T nN,= M= V &lP-'OvM35[3:j9 bGgWC7Q`P}b(- 2 l]"D aWI,g"=jl#T;*¢dBDƝ|rIxÆ*PMǤ ;ǘ]<^CE*G/2(mQ?|ػc5HMw4Mst4x<5V(iu\Zic"uH@ba#%/hȗ|UzjyVw-;t <ɱ)3 ܳ位cz Dy\Ca[:u\RZ+]G1]kH:hl LEBkh3v)g>^N\lؔE#2QƸ3qajo` a ǜlD 49zƫW#L`~T1!Ҋ VvX{fd]J\ "U+>>E!TZۤZ9 5TM[",4=̴'iߴ #d:am #J#gNpX$%RˆSpt~F|BN5p-`Q`;Ts 0S04K bȐu+Q, BZcZDao-Di`G1ȹ+6hc wnBTUu`zէn"(@(i,d bYœ[iBXD$r$s*l ) ZQÃ! 4.~/Ǘ?&'[×~ǷG8㻒3i JTXs+x2mue;7˧ݵi1Ga=/1Oۓn~WRzFx彻'%QU=mk'2|q e5sD9_\|Z56NXē1NxͲ( d~^ui]Kxb1gzϕm:}_ ^_~_OO+_ 7߈}s?s[o=om _|oͿ?3U$~cw;ԝqTl`3B iJ. "[&->:.A-` n"v eωGW2J\AQz-G?:oF+<@c{ct?$n>& j8 LJZZD7l,6p놣O-t-'g<c朸l2*E-1C&()#݈GN'oRk榦,ѓGaD,`-[%]JA+ YS=>#ėעkMs1q>ЪbD56g͑|`2Slm`MLX\&DBAqF'hcs[L"=3YX2O4x5)T+ M#Ș#4#I~=~%]o ?ǟ|+_ο›7o!7">s? OOgg' |_%dO?ן'ZR^ʶE87&pطFDʓ d *Hb϶զBj NЯD3<񰽊)"|BGs@DvWD2UD*'U>یk\JY}@k7"lSrr%Wlp>:.DyYs窑-4 ZM&Xd,(wu(XRujzyQ'̲aadqZp9bA`؂>Gwn /^mLmk(߮D ,(@#dl& pϣX{maMM-'R,Nd"؄ O 'a 7Ӽz" (z|G~8z^뗈ܙEˉ6S~}Vusbkf 8p{lOɀ%U_•ّ8-0aiiHse&w_<1I8&73Sl{)Ů)m޾?#__??-1ַ|+qWVYZ~[F/J/^j~?:g{<4Lcѧah:6p7D4L!JD{'3'K,ֶ (P!H - h>/Ƀ@Lrjg '6dFw ¨#`%mfJ_{٣M+Ӹ:ez{q DSOk|>Jvlꔟi9(5"ZP-R jO,!gnH 0;wO15.&p怏2o@O_n 3&E" .̃sp@\@)̜ |*Wx~OSWc+2k4S# xt޿ ׂ*A&w,t~ PjcDV%@]X<{$!+щjہ0oKC9:7ڶ+ PVދ|; ?"p! +]Fd[߂xm k:$ckk _Ya_zSVadQ薦7\y' 豸;u>7܌i4zmHl0ptuLs7|rix .YA D\qK+xsiأ>j ?[د/[{E,)Zk;;>'\T&zPp> 1 ﯝF7w+6F%ެ TE^26Y~b۷}~,# 'o9b899n'xzxgrI HD0TC0Qy{ܱ3D"!l'pE mE8Q})@ivfx$3K;/(e+]Gr~d'?AХ"x*K#όK-g`p#^O#D$:ѽB=7Ì?}җ/]ųeL;7XSBtLþ=9KGd:d(߽Ǐ] W :9T"*G`̄Y]tUɨCԩ4O ωK@&A9'S .?K*Bm>l@l+df,;L< ³Ƣ(pv!8v (/%!ѵç/?l ٰLUsEX[ mtퟠ!`WPH(  >'NH|S:qz}t&c\96=?. qvȕŤ8` u1|ڒ7Hn_Y,h,DD $l#tzJ~|//9;ՋZ0Ί#6)Q,znxc/qP/f+>6fըrզx5Z0L0g nj{ ZxwU>D>q,j1([7Md"+ y@0B*hDz$LC|/AFQUR LnΡfQ;nGܮ6-QTތKewuŸcE%6^uHXnvc}t>'RQjaKI>kcfg-aSՇJs4o, eR5W6TI'Z$q8.!=]u<:@_K -EeptCS-/ S٩=JKۖZ7S V 9ZT gdghN[f+ѣM״5:aHGqE&wa+japmFr/i (D+ZhIht͉θlE4,l}x??`&;J(ҠYitZ6+bSb!U|0Mb7|`x\_#pCĘDw>g R-5%'Nb0H9 s=Ovu;idXD@6XkEQ0Բt(X=-SPbQ,UZ0q,y//C?$ʽ#z &lAi<<FFyYXJ$K֘kh,2<7B8`^c{ars9qL[Z-h*Kp*m=StL| x ZBQ`sZ447sʝkQES+GXT1fc"y >lj6'`giC7NP<Šj^ t14G7*sVi@t'༟䲏/-8[?o>gCkR4jkB8~\yCr%H݉dkIõŽK>n݉:D1 ZPylnQ@aw:JD@hQC,yN+eWo+Tܱix55,jXLbNVNe0Cy m Kl)T3b́Kkv{X?Lcf yr!/->RFI&8XCG 7 Et{n(Z?w#o*b>6E eYL/sUϘcula"nBfGU [ZD|q #ȯA0տiN;m`ayDY!%,eV=KEJiBo- ZgkJH{@MBXtx4 }K? |S葧=q+nwc0yYTc]\=E2Oa'⋞2cÜϢs>'paS9z7IoA9Ue WEVvuڵ\nDaB%onʧ|NBC F{K+Ԃil|U?0U3"`ݎaz G@Xvcw5=iلxAp3);jBrwΩ~xЖ<[\mA)ͨ_g~c O+%8>MTa->n8t,@˂OfX'~\\'WzA:6ؓ9zzz! "0Opxܰ}{'@ AkYh<䑭HuÄyt<6=Z˜Pls6qx,y{6 ۅTpU Tr!L?60kpͽDp N0Z@x)0Ea11>U79{v&?Cg<ƼO=8xEۅ+T/@g,c%hK (9y<c^Ai},p=nP(d~EY&swb^ iO ιɻMDlPHá$1bC|GÀ|kp8Yj2V/(ɯy9.5"ӁM6Pq-OAs;%_fE`PCZ̈>5MYt۩j dck}b[ت#=jyO61i"lѦ"*S. #ּs^t (͕"D,lR4NRS]!UbGz`jky/cg`u`{Fie"|*Zh&FF4wC/wE>jmqPL`a1q_`fjișN+]>QMA7NsHu3Bhݝ5Ȣ4\;rQf$n,#cNTQԪ ꖌђ"y|ǚ胭uUrjeJIЀ 9c:9:0`qDZnqES=%.l_Yz(y2r+qt5g6hnvE><7ez Ȥ1X ٓY+Z lkAy{1yjaCd.^3lKmI /ʳpPr*% 0u\n^6gJ$ Oٙɛ??0J JZ ߭aJU]_B,T~f??E0M6 p)Rw"<捯7D׸R,g,DfpB=`pmC1L I Z[Pʆ4c(‡ns'0> GxaL #ZaC^TشԂ=~5NC۰ EPq\!6;_3& ӂ- 7h@f;aj%f瓻 U異ShDK3FPK] `D) a%L/6'>(``H C NAjQmAaT|]^9K)&sbmmPu&nV"QP; lʍGc<lJ{{B$egxĚ@BqHUMbMʟ݌4Oat)8ۘc8͗m5T9^>{ltI^p^u)J5[/ B$p7'gyE[؉D\T(K pq@FfW"*9mE~MQS[]M m͙}I>L} Zm<ݮ)wPh33U#.yFǴNdt F@Ղ>Iec I$#W!m:Pk"4ЭcL 7D!>+Ur18'eI vL'{Zw~1DzL#y% .Wl 8s,ƂN:p;NoOA)lMƦ8!st 0{cD|JATr i;att׃jB(Fc> Пn@U+6 eQv oO*% -7N21oc+9+DꖽBJ!6 B16HFybB9)%>H}HZ)$5$1+Ol68$`K4[3ֻB0 QA8gGƟ;0c?| r|^,JEm=wVsu e#8 }HzڔWU4( h6r(hz]@7 Mi(x> pDb(3v%M 3 B^YJ|K.L M=d@ʕásـ07E9I+\pB!+E`dgttE$h2]=I@лs]}P./E# UDiiq֜ƎVϯJY-3ɟ+9b%Sߍc'lҸyʼncDkf+ݮЮ(nPHݖW ydMrz0v+wXH5ۓbl!TV ;Y2gD66Kx4lð=[Zc\)%)ҺpX,&ܩ9M^&!rBl=.Hl{GH2c=8_< P"Z"Ne`rQHM ̣h!O*_k(b@m1\$i4h!E 93#7lf[솁yN¢R 9[KlSh]j4~s #S%E-92oDRP3g\+'/="kFmz $HQ4W~i)"a2cpElSU\j E`݉íGՀ+w",m j|vpv1'\ PP4 qlTfyf"Z!hpzZÝyV&b۪A0-xUt1pVlEjæFx3zy!~ HPTTwZu@CpѺ (m Ċ8%8uX:֣ 2'BJH ZJCv$/qb| ?>,uU= x|b5U&0'!΂ d{5o~\3p~-bavSO&mǦE- '_>WU-Zۢ n V F80cB+=l+ Vi9T# e"m5[JT >'nGG BW7kIixvE ZKCB,#jY)f:/<;Q9pDCc^-"(Wte>fP{+xHOZP<2uv6Tnvw Ë3<>r#9?OoLPXƕ4y) xFD۝87lh(6`zsws'߁EרS*Y.9 zP)߆0COO1 \J 9Dm!ȥX|ܰF$2 A0gQG'/qE'-w݉:o7UbC%M=EBHM]cK螏!pSm8dec|n9 n:0D>XzA:PMOU&ȩ) ;crB9Qk`َHK$&3Pp?qNBIhp夅=u_j*/Rz^ds,Q__e{|YĽ/ 6_{5[NK XY&"Hq(Ş4d1^ ʖH@ەhI,ؠ,.hJ7V|@@!BcSZVXK10-~Gw@\#B 7mR v ''4KYF ON<\x5k!h{Zst Tf_b΁@׆PkBwq.3VɯߘލRt}t|{b%VueA ҨN0, i\6`v)Xrlv؎;3 yW+?G"J03X s' \pmU Bhٴ\/$T@  NŜ/pN_-L R4srbh|@XwݧPE@0I<ψUb/l`(n^#* 5f'W`>Y_d}u|,e߱-x X@GڥUԹ~n2푑@Ujs,&lF@(8-PÑo6B90}QQOߔi}b|VJ]b7شaDۅX<NjAz"n.&ܱ9[(RJ C-TyKK0Fbl򢽼KqUքTp1Ob]m4lf2 ?t-۱I-pDlXxLᡦ?Df.p415l`*hݰ#v-=>Jy>0m`CjP)"Lk:i8>cPrP&?yM\V4^ Z Өxb{=&nFTSQP sqfi8J{bf^h6^R&\{,.i1|| .5A};G!pds5rv·x"̀9TÐmh51ApP;hlT\ ;JGbh 91G,X(s7msZx8d,KّƻIOUB29[r!6ax:I{Znh`VrbbѺ;jp [rLB (DX^υl,{ G=UnCvnz 5y0WT@u>C8P4 ϛ^@A.5^;93@ 0"E[hFbsYo7938sA_>(!Wne&ts)dלy+ =!~D/h@ߟ{pn-a@e.w$ hr_PQAfY|D FAUMPDžWL'(a 4R7C6:PN* A+;oefNf:Xe7fށ[- O ,P&^ 9j9Q"RJG1)EЖF&;0w_&k, G= [.t*XDww Puz!uGfJĐ2;Y"W,hbyv X磵a+uFx u"$.( Ϩ옇6FpBDpiۨآKAoDЮjP3Pqb"KIY PJ#J\r,EE. &7|׺AR"ܢ [~jRh^i)bpHA!5h?,i@ W[6F"R^D]R@7mU[fy$tzHq}>WwGu,.arao#&x)E"Z1τY+禪- 157^TkӭN?w}Kc(6?C1 O<z>|Xby [ec+Bb|'FV&xh{ ypI;~=>#[O>6d(tb˸D\ I"usDE5w( ytlu' T­Iԍ1eYt;qFY?)(;ޱmhi" KdKZ}Nx @NXi%L *Fi`*f,Y| w8©f[>-D[-%&nE#&M<@)@Mc6pAknӟ1L' .cbh2~l 3.IUKA `IP7h"d6/({L^#gxPKC\M´k:{t`<״zTPGո9g,`\>a 1'ց/Zvw-nlO| x{yReHt\+&/wnw-\]_JhMnǁ :J,&Ryo}nq_<xLZL:f xnpxO/;+c븍[MOעxW<ǽ)Vn(Qd8?}+4r McqYOg Z ^Ys#}G '+$)H!ڗ?ݱom>%@'ۂ2ؙ( #ݰiT;E ~FZ1o7˧\abTIFV k\,R%Z2ʖb{ّ3BѰł-;0Qrֵ.R93V p/DdX-hlL8.F,F^O y.:w;Yr"sߜqIqXHp'ɘ(Jj@{ o,ȁ0!).Et51Ad9i ^ݤa2{dHxd([m'itQvx:NoGZ %9XH~% ա|`  ZIHiceUm}D61 %G1>JŲΈ3 V{EymU}k>{@uL9u0D=.1f_fǜgTX̩F4ƱKeχ_A EdHÀk9.{V1FXd9Y>ǒHdJ{텅Ec a E 5EUςNK. ! AՊqX~QGRՇh_R9$XA0@E10@ ,.vwΖq79JXKVքh; TFsk(>TP+!hߌ'xAɢ/G[0y*q&Cr+6fbE[QqYYE,a\$|%2v@5puLGaM m/#%8jpTAʖ[99Sw`D $Z3_ /юN?9aA&1/޶DB4TZHƤEl}Z;~æE@0s8 i;QJ@Q?>\"цfž2!=DV*t _<$zq"O TBZ+5x qL &쑽]jC (n56I(vn6aޝO[j+bE6; mx" iYǣD[!ByF6;-B3=wXs r.Tam ⏻>`"I#<;C!f8"~N5yq*1w:?wSn}+[x0a8Fm _p԰~pFQ "٨*v4CQxG>?x7lcG:Q¯-PA6j?( Ng+dc^? >《畓~ P ek>&v,EDCZD1>E"bCɼZPP2|H*nCe$k1kỷqEˠOx U*j)aGq&'O8&߼# ʌ@BLTҟy}d@" *תP@O.$b{8nyge C߂j_ 8 >@eXK)wM `01r9"~>d[̣ <8=BcPƒߝSrujE- i D,_Hp(eէ1'116nxq,N^4}pBuU55"[kv@|4ث Z뽢,nߚۢOĥ)ZipSA둖6b*om(92!`jxgfH!/x :bmɨaø1HQ*6Ie Mw_X~V d{+@i]RjՎQ6N0*.X1x^4+J<H*^fxs R.@H*Fp7!ɤ(VTœ4$ɕ@UӔձ)*{1<@P3Y sB@ dn7zp;s.S-Y~܋9 #2H3]qnѦ9dywYҠe^aYo!>wb%fӋ2ei]a``F' У <`="[T*W܏pvrvwlqM*t ?N5kv1WK|~82>.5wu~P$EcROh:V;vgn9+8ĉ -`gƇQpjؚE[WϺ9PP4Pl>C3J_]mp۠+=8ltP(lh}!~̸"vNUi9Aa-%`"4lVJi@[|%[h(NUp,䝉It1\h {,tϹFU bR6gqBR5|5Iy=LD6Vq@X*m sK@^Qn:w@!%ye4y"Y^CB ŗm A@X>Lp_; @ 7;7 vw v &,15ڏ-R_SňD+^6e[Tr]4@Jr\) BxYC VKc*` 0si5 ۱xb]l-"JJ.ږTk*^NED) ىwӒ+#| 1=ѝfDY qM+NTU,[Vq1bwa>sq΍]Zf)EH 0HLȟSPC,"a9 7T\O>_Ce͋!%@t)hE 󥕈ش (Ef ˗4Z87ρ[,%Ъ?~^dr7#'|v4q쾣b7NJYk^??!6TQbb~p{F8PJ dG@ PPb%eAPEDZbKI@L˸}.DLj]W% qmxl?®\ꎭ4lZdC+5 ~4wlMuۼ@(OQbf>{wg\l5->&D OQP7~[qL 3fZ|Fwld *ɌE8qگ؞! µdCK(s@[((>=h]vP2կV1u!*C)݊;Z Ehš/e:`~y<=/P=h3@(S'?F߫9 @Pj]5ٯe5ف*̰+( L)D'—o7\B˶؛..7tRp!ZU@А waa8&a| uطkUU+%?CX|w=T<4lE5ťhQ3g2GcYJx H0|\( TY>}^a(zpړHBn9ft 5pk#ңcvf O"n~?>|GǛO^a諲pq ][?Oh3P#$:?r.BP T+(6RelR`)9Ar]oa,V4rS%v*ߢD|Ώ| HHXF$߇+ 8^zZ\T(a,ax Br*= qtX)ar"/)29aŋ=I ;.]3h2^}#H_$s6,oX7sC5ܡp|xּE.k#1 ]+ %,u2Rjk;'~?߰dAqe_8l#[@7h<|]"LDEY* b nb<lv M5~Řʸ&ƟM2W?5>k,!^ @ZX.KiI)Ip"Hӈ ߓ( >f9FXİ lV<Ч^Y+FthBs"NEJR$sT We hIDoo& ͝4 i.d 393 9NFoH.sK)LOe#`Xb2Uڵa]{kP,D.`ĐEe0+sN|҈3&Ja0w`OĜtݠE7sdQ4X% !ژ>nTFwxΈr|0 H5ڷy [ +J$_`O"0UXƋ* w!5W)\BY,RF񍶳h nXWT99ІKQiM$WZ0YxgNѓ:ۤAtE O&c;ip!Inf'< zOE\t 8Ȇp$|Y(8 (Q?uĜ@{x|q_hŢNS {q&c-r"9mP^Yx>hYbJ{lAtĚ5_wNOR $d:jQ`!%?^9s`xĀUKf>VAjB r -M&qA%J[Zbޙ⎛]Q "H$k[7>P;Vh#B:' *"UB"6+n 7o 85t I-,ID#PU `":V+aA@30q(a^zx:h>}gl5k=V#l>t\ޡjCӊl5Qh͜07lV!NdZ؄C'xз? V6xHِcT`_X}X  ܣ߇yǰf{ +@;5DRn6LWI%9I>nJ3"inyf(Z`5 R6AՈx/L hNdZKptvQ:Cֆoc CN?E1g}!|vxaeD*=7gH=>kxzAkkB_"Vek_r&Y(91s plH#NZȃwpq( ;N91]^muqU9/sλ~w[[ő-o>yi:=| ؾb?!6aHAYn*J[{X ߩ=~^vBKE-ZQa-iGsb @-܉5`U\7-&bKW{ —EA"a~l& YR)qGmEMehRlo+ln\T4*f,_ERi"OM&~=`̉i$}n!Sg>Oش 8䥛̜4* 7Wo'|~$δ8}M%-nV` >)b>iN4 ['WB{g?[^(; y}6Ѳ]z*x?aEܥ}B52Үz)O#Uj7m$%:.ؗx'pԕȝArny Tܡ3nn NAIۗ0&6 V9[t 6E#)jS8x6|X9cΨBQQA+l9{0 _Z$`-`G)c{=ﱭuسBYU 5'8:uײs%:Sv1,D'i:u^0),&H0R*hv1*-~Wc  ұHOhW)np{0 uh$6cڍ+aHXLEZ6&aZ*8NQR+A0'9; (sC-́cR<JNdL$ DqE夻@&y.oﱷKW5Jj5 oc@kW4fpPgGӶ( .ߵxJ ^ Ђ,VXIn㷥܎R-G2;nAX"GQ(ʶ.'7,KLs&Ԍ!P 4T4L,Ё m\PtxWc`~iջ%ҕ␅}M74!(hڢՒQ.g|(wc5hKUW1uyw`+idL-pa(z F\c) {]~N1Jk+A '98*?eÛ % (P;73N>[?mV"sv>DρtpcQ -qo69D|Jsڞuel4| @H&:٦J{4s4DkyJ4Xvfd+R41ٖO6DWw뎡 t9WzzjL3RTn$"[00mdc4A;Bi?u#)"Ltg! Iq|x~;>߃ibY.-JdK6tÇÞ`|+ +6@`6m#!VB9 b><_\;i0AAs-$U(xL'zt*#b-b-o3'>HERR9r@Y<;8iTQC gwBI*▗ =(*kD<*2ܰ Ĥd)  X8]s7=[W6jp`̢qf7qŵޠfZg ~&01p7ڻhCAj_@E*M\q ƽTh-M"76Buv؈]|Wq,W 2?<h]А9Fa]9(Fd|]@s@H8 ^="+`{0U#9S8\ef|kPDcCXCD3͸/-'ƕA4wF J]_)mcGA<# `NQg b?c6\s)q s*r#&Nژsn0orhA#;0rLGx(+5'3f>}қ#LWDϼ 8(+%2qx:ǟjrm08cXvt"x\Ja:wqxcHNi ք Ň <ɥ38 + 41&8ܥI0hdRMa>1BYY2CX oK{B;ZN25"%T@ &8Ep1F(EJ\hy7|N1חקB9cX]k,@eNp;ݜDTT掀>mP%Ϟ?'qON Qg1 D**@ ž.ڿ"8ہ>nP+Jp KC֮Vt8Fa-xJnԪnO8&|NRdƩ҈Wl* .h\JP[Wbޘcb5۲.7eo'/Ue2%X.4n) Y$?BK,xO #BK._Du`٢ڴMee9+ωo5s};2;K2ynk5~տٳ ^H⏤b6-v(dyTFYmʆ>)I,&XUA!"#h% z,loӏ3!zAT6!N QzBcY=`xHq]☹ K;F"/3C29vJ&HIlPzĆ'Sb#pLJPx;%Y,%SK$c类f ;֪9Ƴ}<ͧ6TrQ@Uf\;B)۹$b_!Q F1;}ʿ1c#x\rw[NÜd#}Bn)Pƚ̫bDv/&b# G܋_ŽtY> )2!;vPEKu` 9I2qk/\7yCCj NYcoXԢ(>)؉N}α:͐]AMK8% GgmB3U :6}NJD|?uhѬZ;5 3vbћ8gE36OovlJ<iɊp? &G߮䥟\.2= :#޴F~anR8h4 X )M$V£OanDF*׮B'K<ޚ6 m2a9簔CY )\Y/ _k7XdQ&ܨ`!x؞Y簊./_Vj;ǍF_>'.-iˊxb}D6Wx{pVXޜE>;/߉Č۳,WַB V&NU(*𰕁sspb1 D)˔JD?VC—uNR(L'C7[3 mtjYODtr, :F7ic;oϹț#q=M93m&W@Ka4g& ]#cg_CLߺN2E̵ְ01ODU&(,Nvtv4J-ke"п-= ̦ٲV'ԙY,.GP28 й>ř.\cB1Xb~ޏϷF?IaY;LcC*KiyeA1B(iyg>~ eO#.Z'vxRyc!V8wK .K>S }0ZEsn[/i F+,)IU8[<*%Ǣ@> q$S!l1A;[jE8N >Jd˅IlbP4CG- YiH9-KH)XR' я1 ^K;y\ޯ*,0<9#Y}lgk"sni;&R:C\|4ZJ(# lhuǹr8:eYj̲eКlc˟Hؔ5Y gWPI>\dFxi#K8 ZC9%m0$s}+F(%}HY[-sG洗r&^]N!^{Yj҈q$`x=DB]u=Rp/-Jr M'm&ʌ~wGf_+':³e8>[x+ziq*"c'JQ߾'}}.ݒ .䥒sh7/_ganԲPl!RWJYȹrWR^I))՛&o.+9eR$u› wqmcco EsZX3>Ӟek;cN䅚*5/O,+o_:_ E[{g;m ֢6CyPEZ(hּ(6kID{Xκ߅"1q\Oڪ(-娘4U@ee %E[0T;*&^) :8HsGuDDܠ x`o6%}:,yʚW^q7,:l/F FXʒ.Xvee- n1QHmㇴx>}xw|k~8>.ߜRS>bbul$PʂY+>Gƽbh/py't>`3ӏY?cwS-CcDpz̡/PE8qZ4o7 uUj߹Pꆨ>2H(8jVc)YK!Gxt֤Z]%Ce*FCV́=="v4hR,HWynRղػ7%}&5K6ެwo8=ٲZ8MF3ۯp>'dnBsGFB;޸GW\NeA0 dpFYDL xwcȁOJ·#s 7s"7Q*H+%&-4]D^,_Jʙ%P\BLD&/EYa):3 ?=6V=& Sϯ.a3-k~ '|O0sI8HzNw"@.)4,1w?/Kt¶pz0٭qpI䘋zqO⦶1xi/$rbb5((EX1_0S `N)2餱Ku;Fe4ʲϕdB LdA/ƀ ?IwBFq.T b҇F"mǶGa}UQT,<a`y2ŔjW߳EgG@Q{a[%Zc<D\e4 tH<9Fﯼ'/x1Qێ!&G~[QrX. F+Iq.ѝ~DrnI7ͯ{8,&Wxi o39spu4%2Sl.PWÏ{㳇d&Jpg~4>[B{זq'WϲM9`gvW-k2yLb֟b+R"!P\=6h >|'/@S;d3a6#NGt C5g`{,~$un DQ*LM&M [X]4-1\"g٧uٰqVTZЫ^"j,6Y$YNNO~3s>S\Ĺ3 ej-hLAFϴ11Fu*h詅(!P0B1bm$o AN=̅:}C*2>фC#a?y a4S18X;7,I;͔uo{5Ȳ)(DQe?>B8_{~-B:9Q4>D2e54Mί9Z~q;!-Pm 'ď~=Fawޠg㡹 ,spycWM23ty4n3 &mN9h=ڳ$YdKp3?=όNXm=aep.c:`[.viV\;9W̤X^JmyO<'٬M|=?Nb%JoB!xQ{\EN=$\4)ED ٟy\UDcL:hqfzy1yAfT$YPHS&+qde %p)^Ys>9-@$гլK*%=#`Wj ѷlrדRb<7st>ȩomwL̚jZySVV[6nZ?5ސcyJ1ZִP!Q ?K)vHB(N*f7Rb%X,XX]uU*#^u]&趑+~D[tZ+OXxK_]R.j/PD-`K˷˓_V/*&Er)h4Gy&47%}iℑVv)CzŇ6kO?Hp;7SnJJ,3ϛwf!MJd2S⌆j>̚3S{c;{W{n{o2 %^0KtI\!Z-EolE7ly4!saoPKKxt comk.T+ԒxsIu׍kUγAE*KyP`vo-IyKI,Y[7dTqr Y5O<9ΞEzkjͷ~_UHiW\ / ԟS[G{ ?G/??'$/E޾} ?O?i~ٟوKտu^g /?˻o~Iei|:IhWc"!LQkGkw%;mW׈p7l}$Q*3pݬ0&1So<.8vp#`d8ǝ3ER-@K L)<" ~ c4r)q~TSxKZBPu^Z)l :Ln:syGtm|ȴu| hr=lOޣ@{f's G4Kؠ}bqJzN#x]c*#@૚W,ћD\28mC{B0HKq kn~]6/Uus}v&*sA;P{D޹,YV/E<’|N 94F)Pm[v/fF5;QT2OeHjg%w13"%h`` N3O7hOr=Ơ&)<i 4h$>Q _`?IClD>һ$L*k.lQ3piEܑ(f۲lD09\,6vޙfiQM0cz̢R{:(hfh2ͳ,8XT8XB/)bQܽzOms}hcFF 9ِh[*#г;brO'8Ff/>%Phr,0e{P*9(ȧO.>T/a鱑JU95% \l\w#yz="-PPSRH? CEsz`3٧cZ) 8̡>|%ȏOv#V,fVדp?z:fW19cg@S"D^qdŪŭ{ <77gɱI70crPC(2e25z 81T8^}y)6eZlGsB)^){񝏃P`ݖA}C4#]B9m93 s6bEyR TOEwt&% &0kZ T7sXxBtw!QMdc`86dFL?ǯ9ou]]w3?3ٟYw~O$?3?ݿ?4}Yp]޲'FyN\]EmYK ;jJ0F9]J*ڶcopĽ- -BRVJ)Gr@*B$êEvB|+k'假PX,{܌abdR`^zv6o3x)-=yϔcZ!ÖCYCɚF;1Bd! 9)HC-h.iW 3Mgz˅:smAU"0~`2H T,TUINbQn"(.Cw!H;YC=kS!oIiH̓,ow60%f!Nwƌ| +7J]xX@;ף[p58=k"—LMݛ{9!R3oZ35:ϯ=*-9ZƩY5̥j6\Jf|Dũ%Ssb-K9~Jê(޻OCA6r9֗aRa"x&JIi2pqv)lE-9˷JjV2hV!qУ̠*,G[U7Fg?6q͆Zi|8GNorr7^ia 5@g|癝ܜ5WYd牒%d;;cA5"LAٲb'Vvz5~WO;cZ{kg3Ę\S 'p&&ă_&kI"jNd{}4홫kK~pk~vܸ+K~PD7[xdnڕ]H!;kzdIK@|E(5;hh1Pb%l 绷vFyPNEJXPGq Tgm/쁜.676.;o^HGr?[flD>+)jb2/1ZKYAs="2nxsn:{ԋ^ϛ2M__~IRdW! PgdtިyXߎqo*V p:qޮ0;KІKfzC)Op-tO  HԒ9y>Uѵ5M)seeMrvUTKv"xoW.n=1Mmv6GR}ğK1@=L].,-bs9۠͛jiLʖbV BDOO b ,+=jG k5TS<-b0إcݔA{7U8nw wm<Ͽ+?24F}CrljyhLGbCބ!&Jo%Oi.*:EZ*d|R»3'gm0~hOg R;lRah&%$ki4KD-TRtS{vhCf.Xc~9qb%D)6*ʊUjJ db9BEXllβ,ڞfMyjeCJ l m= :F""QRlzctLY3cN.N: 9tɕ S ][K:99TLP񼷣&3< HݣGFqN9S|nh2bY*b41[홭̉qU^bd*0~5w,3RhUm6XgN_b\:S^7U?_~o}['*?wOPo}[;_y__t/ ?ϝ~=??%]Xsj߃XK51RD5! }N7;7dPdRfFwI!gFٻBSUcuq*e!Lm[h$'`PI @4Y4x {6Z.M,M{cإ m޸LTէL&nMY#%GA d hFЫB"L'tmM{RVj,II5 4ïNh.9pNF֣29c@=m[yz=2j9rZ $+oOwu3;GsmPȤx.%ݪ)ٛ}:S?.l.G?X@3B(KʋJ=wqo|n0Jg QGAb"!T nׇZѕhr;GQ~ ~I)L,|,3 a?0?|W~?׾5~?_=z<>>c}?O_:_wǩ M7 ?O.  yyqFpQ|Rhbcd;]YjW&RxL7z~.d2E 9_%گ㭝cHkYEqkLqhgrc4#T ţa#7`An.sFJɦIq)DRyH\KPfB#UY :/̻tw1H $?WelED(ûF~G:fBΕ1w..fu D4?d-T/ J*Güa8= yw8ҽd g~؏_q7{{\?3_ RF??}zT {#iy3q.B&E:.(E7$K"ez[uyG ]!>^!T(T5GZ6 O2J^jic#9U.El{0 iWtkQGHKY5 W"pJVX:-P^bj"=@(z6}*j6u1-HW1_EoB)Cճm}wRu$fjZA-Kyj0ug9eoDхNC. u8IȞBmWg71_3{viDt D]-c$^XLZK _J TaHiU0rAOmxǣBoqo;p˸3Jl@688y kJ B[C:vqEje&}*Yj.Qڿӆa\]C<āl%S_Bg}lT>S3S:'⋻!qǍݤv,~d~dㆵ+_IF}[v,傗++V/Rr*"G];/o3$im*bTOmIJ'%3xj!^iO)/IWj6 w}pYs' OLi"{Xԩ5JXxX%J1 ۹N%{?E[bp*&.1dD|ִΛ[wyӂ'UpYɩG44pŢZVKy >Z=ڸKzRg||5Tj<kai*GrZ)jR7pY /+ _ 2;2|zS=@ӒIhB"HU(wʀG\xw`4W>-ͭ8|Ww$pӂPKmr|iȠЙs }d/ltl!1>&Z&{ sg zn$ۓS6(KxÊ3ReaTiL9I GesT4̡fcBᲄ53%0Hw,Ngudx|Iz&he`}0Ҡ7]'w>(%l'a!D%y`MPj;߼8yS}%3SabNBfAÔٶ"hCrnjش1^!H=}ŏ(ghtLa27kwOȔ:?Ç1  ̓s7m*n0>TE! NP'XM#4UR"0??L+:lܜq˹Adؘkټ<6lQYtIg~^ycc>Sl@DMBXF/tu"$1 OT6>[0_ ,2ۆ" ayVNySuk2a0v.cD[6.C~v79[ 4@%vٹ<ur({g,xFTsT aq8 g]{;޷C".cm\V;[sW%>[cy/݁d _ŹNS2'PBTbb"}gx*xT_]0);j"'g8966nMFοp0zZ#a%rAPo\ {y~xaI,-[8376ԴPlֈqEJyKT[XSX=rI9yNNSFn/XQ3C>\h`F})[K]y%9ch9.3.!> N+4)Tpp$`kkd!;;-oe ?i? pP)EG[;Vp%pIBStR,:_tLE g0ęCk {UEsRǏ]Qm%8&755ÕP^r ֧[uD{0T$"{ay FLTޘ)nWo ])b$-.G #~+dka}-cW!3ܣ(ϭhenM͹pC)cW;# T"[_6vqpk0 1q+qQHʭ]iʨAM]kE VZS r2ML <h"C&>!3>Y\$``Tg"{3oOfTd ۟Ic ![fF56PL)8_e;[?t2{Ϻw-ZkZ"ȾP‡홚j*tmDcOi B~8>2.)ݕBb0]Qx]H CWj49X))F1?Uۆ ;hW*Xs ;^7?q](ۮS+ ~ܰ_*.QYR ;G4,eZir1ƈC Pip{XN1@l&vR!Ϲ ~grkwʌKL9 JqޘmHtiN#b]|6LO1G|܎H(gӃ{7َӦE^q|Q3$/? +u94֝ȓdijdc_SSQHv: 禁-f0o0FlZy0PH q{=[P*MޯS1"K!Ac1NÇ_r<~c%0;Yv9$ ?pj/XH??P&8vzMrN(VV|b ODe̖G1" U `q/T+qr^f@2Un]ո@X$jI}NNr>9>vj*^A<b.g'>2f΢g=vREL轓Eg7Ν\4!Nâ7CX`cc0['72>@0H"YO!\_YK:p KCmw\/\mpFAE1y^%VdMdʅ}_(69)VHW;RRm³0,X1#6F7PoW-aV PS>TɛcѾOU\#3=b.B8rnlxk>ۋI&_sǂUO:N]I>FQAKD(t(J N|&-t1D_UBb*jaNB8AME/B|1d?gx{䪰yN1ɪg&NO{{۸tsA aYui4)'ڮw<&G*ήj$fg[Ϩ+Da<5`̫;KGضWc'"plr6GX\cL~cv|Y2_lHV€2LQ֏ > q'9!87))=eT+xbek*ܜMV9w o$F5z;g܎Sk3G,Dž(Զ0d؅U[„9ɳof3[cg^a\ygLo|16sk7\8]xS/Ef;w:PXxjLAΔ,;240vȷhV^!{Zk%8,'7%Ct(&Do_(UXxśhs3wD4ش~w_W?Rh#1!KqV6nq֯dLd O6i4R֨Gz!#T~TO WFil^.Q'088r `}|Nz3$dfߋV|p|*cnU@*īsuS#|l}H*^z "F#Zɳy#8#kc6pKDFOb2Ӽ+2fK86H5oSO{i5.pFs":ʼ[L>)ã7 SJ9nj8M񜛵o+@l.{&M38v'u}l?) FOBgb"}#6?+S.R!">?=OoPlXR W;6Yv\YӂZm2k++3؟9nBV"VN 9Wq%Kyz~=&)/v JzBLZw2 䕭mo-||Rs~k_EwCq=|Rp)U~i|@F\<SRI՚BHydzu =d+# u[jWt6g9y1h𶟞sr(o_`|xM'EBx:Fg˜sq 8Hl٨}*ގxߧ;Nܸ3o;EܵBUY%} `).%hT,#1&55lс7Z Ӣ lhw*7n;_/4jRY(]sU;̭o</PA%ֲ]*_X}̂IB냚 ~c+kZ&Pc ne^ dLsm Tg$HѨ#tϾ:q|>zC^t ^pK 9*SVZ(Ӥ7L0ntolm;ռ"POb7B6v㥽>} YHg𘊒@`wFX>^^苲DN Kw=}}*L]R-A%諬X|=n~@nMĸQ 0dwR^iN$l rH?A&%Z9ubd/6Ht(Hx,96_i)*I#,%"ȁt|V/!NZB9_gc~Qu AAI /T,2=>cBcm ZA8P_ًh([>ǀ9ﴱ}62++25˯7xePsܮ*O-G2ex푴48Hs"f9a"NJ'%@e҆q/B@u4Dɕ_)O]nh}ǖ 5QJ 1>Gf:^d#xl@6dO{ 6,^?~|۷OBM KYbǟUtY|4J?n_,g>ەW5PBj3.@H ~=ur-UqS + }.Ԫk;[[~;bpa̺<7m6vd\35yeɊ+>5~_ӼLSq,{.KYyZޜ|=Z5WXancgRN'hsu{H_F-~i5I G:8׻ υAk.W٪i(.m ΗaQ /ݾcymvol}c|Rϩpm_#?mҮ}Xv%>gM,y荣.W9+hxݎ+o6F9 J,60 s'5S{7<d,ߺr۹ hܶƭ5&tQ /WGJJ<.kp[UP BK]Yu~9x,eBq"fC̖Y%/hP"^ͮB;|P1%%>v.+FF fL2%gRR952%lt|S&Bʕv[m\>nYis޽=1KuAE5ƫE+0T6X`c~mǕ>0ݬ2dBP7w{wr}eb%E #޻J%vóȷ/mȋ.@B+9gI<_? Obi[;TF@BRęެohJo ezə3ct+6TC IqS4sMSyX'X8g{\P,{}.oF&4=S~ݢD2-C|n2G{5&LEl 1ӌv;v>x*U׃TьpO Fq֞)<Ӣ,ر*xtf[Ҩ0C*G$ؠX(YlbtkfgEgf}h8Xl͜9i 7 y]J?P3@= ʊw1Wc&-n}'T5|!pҺF)!gȥ-ֆnw/O&ڨfלvg༥L@9!BdG63{>V帟l5WT팚3Xx 0n!iӧAiu$u~S !k}'y\NAcȌTf17.eՆ=Pho;0gutZ(+ )W#t_˒ MK,>>b#>:)8f9*4ltj~.l2*nO~b2XwnǣE1b6!s\˖e 9gRu>քXLP MpeZ6sctp'jΜ(GcdQ!sѼDPz,Jfi(Vl 9-dqˢضPryad`&߫L ,5zP(,RJ[ssJn#ΟnZ6ژ(EmZ;-̎6Mz%‰09vA13!,/ux{+8 ˚>n܎-<-&yҖ-E&AgRjqZ(jd52v 3˕}PaSPAM"BG qr ͌w ItF 6(Sڍ<6x&-1!C}dX x[kgboӜϧeסocbdRNv`Arld<_#i|oAxrGS娆ov1H_i[gkqGs[(wp-#") ؐy]%9po9;|gMf<J0G5j9 7j*㠤’V&(Al96D>nR[㠤ܘh/|H):]]"'z<=39x&^^Ji$oYA|Z!>_"?1GC-4j9P;~H 3_77%݇΂3n_#Rj/p\Am < KW͏b[y6LEbέ=sY"˔Ci~?Db %RyޓRa]ބ&-%G*D^YJ V >+gѾ8IsV.K}e7P )a3ƒuFd: 6w6:J)3[3^}W 8Yg{n]{W\_!Z_יpeǣѶ@Z]X98t6v\+/58~{kR$ڢSZ ٮ|q{Ϗ>c ^ڕko42fa %_(j ܎c(q0f!AI KἿTG?TR5qI⢚ ǡѺ\퐪Ż8wf;%Y$3nÓ k/v+kRJu"I_#mX۱.1v~o`y"_\/HwrGvMTW!P),}@-ADn} )Q-`]2Bݎp# 7R?4G"3v ׵1ݔ&S6*th[M1d?1 ŴZõ7 ;]Xll_?PJ,܎vc7~16RԤVn}p;[-6;%Ur5/|?8_|F]-.N>XE-C!haֱַjRN|1Fƾ=" !n9=k</_TW}hDꃸe.jߞY߂w|ߠ_&}A 9-y?5ew>{ b.~D;s݆|h;3H7Ra gmR^zU"RޠQJ +F}i+ NG,Lu黕ծ52~sm K/I$_Mv)UN˖InYb)%>(B]|6g]0HHvmKɣUkR.SY:w:l &S{5<ڿҜWGGs-K\xi&5 9yc+~za_uqn[w`k;3Y%9"sօ9=8|@DϘH8X@ Rlm>vs6ۊ3d!BaN)2o4Y>ѕI$~Pƍ46؅긱/iO+=I361J1\qsRereL'|惷RVlO\U.ngh,9;+n2gC/,Y>Qr zyWr׽Ijܻڻy;5n,UvW@*JQq,^\ѱ1=k㐲w!Kl|~j=,>_1F%yr;]X`JX]դmRvE]x[?J9qFJrb $7h,?-3{߅5~x~zRCDVBZNp7z߹,(8)A#mp!= |^gx6r(>Jc$F)=OiS.G 7LPCZ} 7=I26e,$ѢU/TZ!qR⠄O !p <[g%$mFEx9ni.[#LH`ȃD1`| M 5'Gr22׎ < w^q{h)Z\^wI˦yAJdPRP'0SEZ' 0rΠ]QN nZQY!8Y3IAJca)3%&Tk/TeS+Jޑ1aR;?-1!żePl*799%e-%is g&dj@,漄<}=z\٭(0żSgS b-SA cMjLLX40Qdqm(QWTf`= ;<z͈k]aTR{9?ǗpLkLJH.cNa ȗ#備tljv0w?P}$~%7hW RNw˻himRn =_$O\`} w^<>orP]MWy yY8ra ClpLJ2.Rb;^Xʣ_\d=!K~H.фpLfŃ"aHLmqp)btS.2:V20Z#ʷlw$OZt+$* yl9W.R}ތ/j٩ܭ&#wuU֫zM7yfI؏ظQlxx\b{Ϗ\1C}(zNBI k^YJ΅o䕇F Ԑ>{j5-\ʒU/|vytz"Z5MԚ)rɷ,~p8Ԓ (fBќ/6qÎgRR `<"˖H.?Ǖ4npHl}(OGl}$J{| [}y-qyB)\Lsaq;:jԿ~X\J$1t .]o*(O x*9څu-yd9|!P76i5T-,V,IM=-&ts r*q=.c:KN[&3(%s=2Trh[[c. }}&%/5nŗoO_}[/G9|#,pI+Ejλ-}4n}ckJXR`1ya+bYTi}#}$EA.ڍoYi>&$ )y!L۞Ie%9WON*;9.yo;kgˉ#E 6ZK3_|oY;J Bei6G▤r- ]^oS7hoJAK["'Hm\Ť7!d*ra䊕 d m=%Fw9\ ƳSZjJ%Բʿ|#0(UHzJ 2sS:c{"g+7ɶ-\wG@ }vIćudR %g,W~xjMLM)&t^/OsYۣRcOW)݉'* oY}mzq 眪O:vFKs҉h >Z4_#-Rv&o܎/UtQHmik*qcFK-QsVe38 bh3i-ZB<Ȩܻ*h(oRRbG;F;1!3i y}';}yW}m1>Ǿ@Uξ~<0J*0.f2)|}$Åd1c`hsWTZ:Wn #t{&-|`Q(>y9<2n&Ȅ5T8EV}1QZןyކ;K^j%l&2:NVT{p_G.V3Ca͜\&W}UcƵ]yK%Tp@7FXi?x)?R(ROncJ{LJ"h!c,$# A[ña+[֢+ZWUi*?O/QBEdi:WEKg펲v;.%p[p-*LFFՙF8 bI*V) Ut(]H18,%on >H#T J k=D%^DNN*<#ь4 ck8\|pt;Ed1x&77|%xt! JVK(ɮ܊bZgDsթJ\QFZ;KOa?yէʊdzxo wf=^O|i54Sh%8<&@7Mė{ g&8LAb=%-ԬjDl*EnJڀYʂrQv?aa) *szz#lRFMP ,.;Vvl zb˃Y〇rn4K,<<BY.x}b#ye, ܇YpuƎUjl ?Csls!-|ݹ!18<juBBbU K|~h@U ?j)R,fdUR1,+G'fV܇SҫG]=3 nv%$DR.$Svc16*e@YWkkh7Г ++.B@#}hawD靺\p$OJ]A*7:) .Jct6$R9`\Ra)%Z\mR7a^%%RPRF9I W+?/?fN!_!q's_D NDhc@I5%lvcJ ؅C;~2@8\#_[JvD;ol](TY%,eX홇r)h!Id*KYmKm;Wm`J&e;m3AYV5q UR GRϯ7Io}#Ϥq+G@ZHu5]V)cڦ+^.ws0nH˳:p"Vx&| JR!7a'59|#̹\{4 sh)9 yZ#R"Kl\c1KsÙ3Kfw | њO +953ҭuGf:5~*w'7JysCZ %`pMEFR1##6SMK.pާW.o;G~Кfhx-LNY((}pYJSR"YA;ǝzZ *.AC^=LW_ Hy"E!0Ơl+*oG 6{m?+-ITJN(9=@-ݜs+ufq3z9yDz+W67t {QʡOwAoZ)*3 UŒq3ڎ{c-6رOo4#Ôar# wEwx)dl4b=M?60_" sךՎ=vomV{wBE0k4"~ FXy lu1I$}{R`ASews[IC[!%)뱱aGt}nSYfaa)^Q;cPv!kadG7j0Api^ٙR1DM-%]΅ 49bR5C]<8pYIQ*$1zGqiOO\9CZ Z h'b)'1^Y&Sqǧ5Ah"Fk&nqFc}$yŇT3AtO5&dI lǕ5?|H,\=Ǩp zȵF[œxO%#P51N=XxPDUgt+RΏIh!+{Gbtܸ  cbSXAoe>~6/FN%-n6}xL>vgOV?% ʽsT~ uGG{pdOf$W9ǐ %tRsdmgXC8b Q8*lv-PNXR=yHkJOC;o/R! tzt'jXRbF)F. 8B R_(.NPVK0oS=l$%: {6 XhqA&=&RYʪ,`l_ۍQS'@Nab<‰2Z!%M !t}Ԓ,6Dd[a)PCG&^i({7mMsbSt5̜T @JZX'*2{[pw_Zy,#ЭP4yAD? "6-R&.}X1\wK X' QWk.9v5jR<^Jl8r urzM|DK&L_c_S|W|Pcif\GG Em ^ǮI|dƃӂp!k!z&aLBŴ+ծ_;;w6o 6\S3geQ%bY(DZjn`gaKؠ(Öf*HU=`5*i+!/@}^ctqcBa)jm.Eƻ9 ˩}<$K% RrLdnrju>.-ޙ:)X|^!-3?5MB=u¬!{xTQYLH έݸ+/|ftέjC]~ZW܎bob+KZ]lp>b SQXuP1N2WNե۩j ԼS{ljK$t D4ٳx!rR|aU_y]*I~PmyaniMD}-4G>.xe# x*y\WrMN63wZWXJ9[Ɖ;8̸=1%̍ OjL.[jϢ_!u7>ԍq39z߆۠D&Rxq4o`napm`nQvsmr+k~5LSNEa;2m?ޕ.2$缰fM_TOTmZ\.e\C=9/B˪3Ǝ`IAsRNy]~pT=bzvB*Pih}pudF]$:2{og9#i |nV,1,9CSe"gW5i| A{p \Mc`},6᤬16|"{ؽ lc4clؔw4 QḲy!F'uXw!?g *F{ lRkt.Bəi}q-2z߅ڷw1\kwUң!9tМ iŋx!* B7J#m9-I|I_k9yy\} UД'w_oc|_4{ӭ/~6%o*];,II&ֳQp!cYIelG`*Rn3sI^"@fʡfTPm<\ċ5v"^~}>~^S(yrotZ ^c$.,s\;)PB 6#wQs} GPcTz)0f,m+bu\pC6 J nm:nC6n";ClMoiIhF sV4NP6@?x$s(oA0y|B\(-N cu1aD/t#H䖯&#PlrMgz[ = ;R$|&Wn觿r̃&y])RS-0ƒ;q -}8m#dyN7TNlFFc˃Ϫ"% @EfUpÎԲ;SJfeXADH. -~GH&*:MIh>匕ӸyBrE!נW:!tneihɍ`ar9%ˌZ]z(iӆp K)jyϯsD#jt q1=rOcnZћh=B%_iѨ]('q1YM+ uxp2v:qеX> lIhw"_M{ wsgP6$PDM 3x|fDPoQLMzb  iG>CsߘJ}1K/&.w x؉X/>ګ8 ΠW=-莜]o+SrHqJr͉tf$!S=tP %Qap6,e/w}}No_N⾡ +S>D?POS᳇oJpN[>NѬ B1 ~2{9иr f$àRi o68^DaW<0>;piՅY5ߨTplC8:%*N5jLRnfJ=8:i \^-e8U;J);"URP pC }Iv1wfCǦ3VqH۠pNM$Rm%m}URIpe,,`p]M6ݢoww+md;"dE5/Szka '$R\IU6&DL y$2~+r?;F:-wX>`y&AO#F2X@oȋۮܞILޒJ#Vsz-d<}oX0`EY_taUD28QRbJ҅ޥg&ѩ]3 0,ݨRas:=?[|{N'v@v#=LR7|8SxlHX2C6¨PFaX… 1<@U\<Լ>so{s}kF2Bc}"5ya-oݚA۠B@M+i2@dHwsypHS_ ?7u^1L̕x8^M; g]{*|:7qmE!a9;Bc /1߶WK s z:ϯ\CfeS !skcPOAKۺ (5q9uZ{qD!P,+H>;`xR #>t-31uW> >YQEz^ eb*Wp]/譣8{NK}r}ull!O4E8Ǘ(S~4%weՇu_Vs]ظq$u_R)qdCwNYk !=*iA}=#P+zBϐRT_N"LMy8Nrfk%'΁EO,hx VJnzqCx "{IK 78`k%"ϐrb[TL:?4":\²4J=8Kf?~Շsl,e+Ԩ!~[,DI9hW/^;ueJMj1?܍ Uy2M?MMY$Z4M$QDbt(yv#F XmW͍+e$֭&_@LKXt4$dm~Yr-Uƺ 6-"ytGM`σ?/tb,hW0/l#wi^u!?M=T5!Qn[?=XN/izqN_I Uٷc1i\[DnaU-]kW\S!Q<*eL%\x! jA\#E LJEpd]yGUoSLF8w@v._!D ew9R0%^Nw Z|̋ E _ჷ? M]W;6%N"FMՃX՝xJK;Ib`>\`.O|8zsy*C<ž-٨e/>PYs FߒhD[BrddF\^| 7$AVo)iCt zj9>[6uo1*@;!D06C7:6V:ǰ$ٷTy>ԶXbr y6UN^ T,y\ڇ,?̮Qicэn[+$G;ɷѹ>f<[̡MϚ(rp-MPdb㮍-Qe 7]_#SM)ε;[JΡeV8eӂC;b#}ݘ?3츶jm*S p{ڮ}GE0QS 7}c`3nw'F?;IzZdK"[bi7R3I Ʌ:tFGc+]"VT~3%c0qmޫ;Fr&*0Rf^g4 *ƗjȎԣD2cqD!oL\ CyF_*!fW-%ܟP+]HҮHF9yF`r*@ e(5u{f}ѡއ:Fu 0.=t?8\sML9>!3,bC|0:Lҕ GV_Wǂ;%jQ^M{ʵitJr#B{KUh}ɁǽבԨS6yD>>K;y媃ޜv7WtvT,HO0+DE"dٿkψ%U,ҔS]$HVP*)}Ue"!õ2 >0H^geωU]] eŲ+Lzf#F=7:ճi%{ڃ[`46.dmp [:1)h*ߢ-݇є"St<ѿw^k׮c{`Iy܅xڞCH?-I{8{B?7.WNv;֋_D)h/&7!\P/5-P7FT-\IR(݌fJCikFe&K%9 |{AKP>M V!"tO paIioRvH-)[<@,bÇز9;RܐFgַ6 MskN4:n@]xiƾڇ+"|[.PAįw}e j#Iu㼭M'1k?L `]cy1Iqwy]>҈ّfg1unq2:X %"wb"1Hy|!FEo*!WׯHwGlysXdΔ~%AQC'W,ezy,=GR C1UF>zFhN\ e|CwM%ҫJH\rmKKl>^nb p!qis)7biᨲ~O8$ #LMjI8MYJGZԢUf!5ɗ|c8I/b/pu9vw_u8!g\Xå1*45j ̈'aJ9o? `xgDdu(Wzrͺ~R"UȆwB d4oE82c"!\kQuCtv8w=&Z@ O_mkC9 +ikϾ6%FCP{cB ڼg;f۴\rٞ9EP 6ԨbHriJdF1z,BP-hmG7D D&@J$9je5n$Hmʌ$T;C PeC0~lA`hfMX̩ Uf촦>8;t4vsJG &nDNM@!&Nf={xb+%j |#d?3Z1AI&d)?suaw1e>&F ##ACfVGw=SSYvǣ$IK{=pbxIP2*_HJ_}4wnivZ|3Vl;!#^c$&W+ޣthد]aMa/ݶ5yEKӭEVO5h+XNg~~8MiĠ?m>ͫ3 :,)g־!RbᨢܮI ѿ5kR=u_FEäfO $ :| en Jf K܎Uo,} ?%L(Y]AaH҂(ɕ17a/e}Ս1kTR7}K'%G}ϨN>hRLso"K"AÄm[C|q`|PL'}$M ߁ק'NU" [tvGl{rDUuQQVk4^ITlqT~&lstcuő)ͥ0{ԑN8sAOZ!IX+) 1u'ϔ| +:zCAeRB\%aHQ.62GTRt){f)K* ,0FJDž)fQF8t1m- ̲!@^cڅSA_Ӄ!L1OTY~| c!8s)!مD ûa 0?(yEpѺg7H(vʈAimlo&Pg@su_#($!׈уbA2q:֛*q51M9;*tueNWa홽-+˸0DA;]N,$SdPWz43gxgBiFDh[uem!jxk⽫HanQoYDl>9.m'ՔiG<"U&hd( Σ#7}(K_uh+#1 Ʋ`JV z:Ĩ*lz|Ƅc-=!9B]lL V =MGiݒ;ͳSrUuKՆ]ver>tBZ,OƳv`)uV. H^nXq}_!=C~3 n Ϥ5K 25n2sҦMX/@>Ofd}ftǀ0̮06+⦁;XypTF_a1{1jg$^($Ss_]f.!p(66ŔOuHbN+p3(=w+06S&ՃD!]áQk74cz %aeȳ^l ,B2<#N8}G3PtBN9k*=c 5SSvF DW{`d׹`1 iAo`~:a9Ē]Pm{z etE%biU0&*r}Rҋ<]cЅ1oʔ&ܝ,ѳX\w<>吔ʑEaleGL$Y{[4K|zm%qCZNL630ne C9"i+=2 fR>]X8s}I6{lba_ءTgmX:CZSk #]v mk$a>Z UclhvXĽhT.v%v0hK|ʜf#aK;v=J#xIG扚)-htV]x}BI9Ws %% s(i F'GH>xs_AW¹٥R|E[d6hٶ &B5V=78\i(]_̷#>?3?{O>>~]W~~1?]կG;L3Kk,caT{C]=j͠шH1 ),=azW~`(!Y[EJ?S{˱ܓD7eՍ ]JfNE࡞XfaE sMHK&Iᐏ^ԯnjɽc&G1j8@Mr5H 1[|>xio1A 擜2Ip6jIYf왍̵L-՝s53T{wCRwHb.%CI̵P"D $bo#p3L8-"7Huh8IDATj'Ln9oʐ=7_ò7o0=m\ʦe:bk o }BZ*s9l̹0 z L )SD,W+7^ [FBW蹐iz ݉h#h+f CljlΤLX`l Cj tQ>gݗخqbkVNzOG(3r"Lt܆C-ce&׉iWϧSWWK)ੈ_ّ ANwuݝ5 Zɸ>} &2T*9U({)%.fI#[_3xiaY P1rі̡>xa_u,gf !&$Lrw,}/ۙe\1tPRaJȩDB7OwӴgʦ :%q|8sxޞ6x]qf \VRa3rq(<_˧/SR2~DbNT9S>0KAμwR'9W2SDj)evFj4$1wȷ1ܬZ ,eLWr|x㨰?7GS$(D RsEr_}NW~___Ϳ7y~~ٟ?ĿW~'~O){=~'?+-?G;Bl;a,\"cOafp6qJx(]=D65$)Ss+ˆD~G2qF6n0U!:X0Ofm 0ʱ^\`3#~o__k_K#\# r= puMXU>*nHxa'5.?19r5 ün.%FLJ9DA"р7lJPri=Ldw$IH=|ѡi`gFvPvZς<3F@XRdę∝8UGem Dra#:#!^0,B{_\%N!9ZIzbtmlƦkhHsZw="6,=cR1t:QʍTm~$6zH4%w-?ցmsBh{-ՈJЪD(WHu.-e}B _ɺr'RB 2!?,Qeu(: R7A9h]:\ND-6͇wv W6:SNq!LFR ]W>\ʦ H\&J`@K:Ŋ3B|@I՘MM_ozi繽e鋟TB?96X"4/M>Jttkh5]93̡̌<ҙSbGL̨)SP/PHT#I]F7X-&d17 TVI}ّ!7k`w|+_ag~wͿ?o;3~~W~Wh}|+_//..\e,,LT8 x3}F0[s SZ2YaaNQ1D)(cusȉ7}ic9QMWXF" ~M9RfO2VֱWu6Pc>p8j=p$)6~66@\&n#%v@ Uhl=ݐ#"۸ J>HI1dJҮ':.\Ǖ"c.rP o{)홧ĵYƕe\H$|U~]azT&>Y>kK/ƹ=snϬs{bXgNī{d~!+DӕY 4s3w}yQ2m\g= `+k_wGzb*w:ۅR3̝KH7ҟ?t}ރ$[pbA\I)g7[}+o|ٟGG_t ׿uiw>f׺Kv#0!,L4lqotS㑥0)$*'dDYr'vVJmq g;u $)\7ji icY *feLiH@Rػ36VRFېٍDܵ"kJVQޱ~F|!~}|} ȏݍc_kp=@OJ)M;"L+#YEԀPĘh%^cxCwz85{j~nM;uV8M^_@6 jL4x7HB#N(_,"Ó#ثM *Q'QP3t̒XEHN>ly]#7 3 = f:) R:R9\vΠ9Ɔ cDՠ%2 >~A̿ۯcI73 *FFR| nU#bРT빘TpH cbtтV G&DA Q'(2 > )bd{"!I$c QAňƅ(njM^[\;*/mO_/ſxߏ|k_kPylOh.TV|vP7^m|XQQ:A2V.˸Ti!4R]yܞx]G8{ՅFiTThS~g _462f&^9)]8@7G#=3s@3[ ;7lϤƕCm"퉺|L y\6c_$MGlyڕv% 3i<Оr@#Ҟ?Žo·㊮W92Ҍo :JAk1_ C Ȼ{~SaPTumWR@ +!"cVJf/T2krL<}w2Zו?_+|+imK_ _"ȏ؏|_c`ccDceW+Ьso)Zq()`}C՘rNfjme5UL܈QE9,D[4 W&ccbg\Z`y9aB=] ǽX^ޟ\aggy||??s?sN'~?g,??{ǻOOC?C7Wo)+ 4 %1S,;%Bs6(EU! ۬aH@%R*91 6)L/fHO!ԌYg`ޏi^44\qSdxg G[Yo9P׈&bvSfXڨR,Ri,"ԇ9L(dIe7 ?8Fa#a<^ODb`Đ$zU{HꠍBWoH&H@%j5;ԝ6(ZCSKxӇ [ IC;j!oH% 䠰͝%߃/Vd|AIb5UNġH{I{ѪCQ*3 ko\BMwzUo:ԘgQ8}`ّXKtwῙ3-Ű]@ i4h#]~aH" tul5خHҝKGF$wೃdFCS$k #$9CrՇ?3db?99`:ƛAv y5Pe1#_smGc+IX]p8y%<^*4d+׶ݮ *1 DۍpQ EgMC"b0Tض *ü Wv,{Ld5wQqQ=wQ$ʜ܄yLhg/$m "i`=u9+97 v$d\,]:4(^W" 49Ɂ,%eϽ5 ^Ә˘pih\ݣ1u\^`x挊W T8P9䙓wr<=X8s.` 1c68JWrዧ/дhoǕvJ2wi!8M}׷±ܱs8flbJzLGz1 /6k=oY*K0SRtFjH,f*ȑRTX@reZ-f#&y$Pxl|FNmMF;dR8ͅWs4Sya p $id|+u;̧ufXhhMY{qiGx*Ô84%&ɼ{kT(1"]&ȥPŇT+ȨFFˆ ՘M#'{7JJÜrP\fltm"Iדdr±Fڮ\ƅ6V^ᘹGwȖD7/W&ָ^ڼ<se⹟QS^MiccՍthG!gr35>~̛`'6. V2"*wR~뙻nė gr9P*^ ֕1V7IiwIm\atԍW2Wgra ʑTKxo}ONtw Է UlE%^%(]ܫ ̢r'P[8,!uLጵ=#T|IDIH$0߶<ݿ 6pfƜ2/,! Ha8i]GLzyS?hh#)Dl΀Ž$9ꦛΦ k)[rƖ?8hYyA؄jdY008ԇΠ lrwIrt!GE)Ib*Jzu*#Su%BWRƕܞI#5ǶH 9c{螯9V2|D%{G=3D Fҕl4) [yzH'Fr?5G6[lr)>wPLk[7֮\`X3XAYp%YihH'$+S|X/B;S4;ǝÎO`vK0{4nr 7e7/5r?CE%ʐFaDf(!D%\jM=ƥ2B-BqF# 6} c`!qp4  0[yW+)N$*Bُ=]33fK/$˷}g\m4D:W6"%ȿ4N xazhsv2JWj1db$Yh!VH|SS׫N±ޮsiT^cf|~cqg wvo4Zfcpi|]R-yEo8L'푻r HaZg8 7ITO/{0܆9F,I $')lx,"o0c7Gޙ^;Kr;-3rބGb| B:S9 L] LEgb_|n$NtP WǙӌgșs$]xK> B A/|h$DJ=qwSvIbNy9Ք 19'"4Sx[?S.N9cn>4*2Tlru@#'uǷ8eSKtqsB)+E]/VXV,>,*0qϙ+4W#Hy T j%ʦ>Xn> .}zԣ *v&XYxYi`ɇ&)l 5ͱX6ePX1EJ8D:%cw1r)gj2ͼ/e/x(F6}NDcK,& [SoQ,5+yfи$>H 78j Y 5 c0fNfAӢG)Nv\f& s~SQֈR]t7}b5~PF4xG65nWـHHX8}]K>]}bƗ6P#Q/b"~>YrodyQFUBtFC^J='_ȭ剌QƂe2gVv7Y+rye+lNx7_Ai\^sjT;DM_3NyX]+Ip*'wG晇^OR:~eQFMwd89WĔ_?wu8tWSQwr9U>ٞ(w7Y7.-fnU8˯W}ЍEW8[D,Gt5ʹ1Lq:c}ОHɩ)ɑnʽԜfD5T9׽õŇcAc4xxj*XJ/w7${$L6:6--얼BrVlڲw 2$)G|n$SɔT([6$P:͋#qC$9yF.ZHe\c#)&"[~xrr=}ՋJJ?SuqQ\vMGzz+H_)v hWr"̖grF Ҍ hCmLoO@KJLuKVkycє#t7eq.#pSIk 6nޢr $p.egN5q60Θ }kI)5yngɡIcܢ{k-;[ޕI16!@Za:#}sd5R}Jgs )/ ˮ~P .\۠J+A 9KBTB nt>_q7dNoNG6kT97[xϫ`*i]; kp.L8 \l%>I|̮©VqJ\&L01끱ڞeB(G3/[vߞ}V1,2!݌V}z*e'_&N0̜q7prGdFgh\d Ǥީ4yINKC ߯VBP\i(b{dups$))S1欼##r61ic+5r+y} HlbHv~It I7&iT fʐZOU2228JNpt`#k>e)˻<ف,60JІ cƢeU>|vʰx?w< rƭƵ+Ü2٩੸##}y^($ƛ1J>arҵa~E[Þ+>68q:f:B6b PlJvspw'|*4}8>yEٙh;|7D! hH ROe{P g`nuJ?'4hn{IjQX '+of4߶4Ck$yz:oz~06[o:>)NV ۸rμ>#w&*,T4ȗOj~̰bFNNU(Nx|bO8}FGRR"LADxixYh˺%y_oʇ/Wc\8@%H8ݝ)ta+F vPN ѽs|LݍFs C5^1ɸ8Wŀ\2Td޸ w37״;))Spz:ɿ'՜o譹foc.UxBgzXl0tDFg+Gvhõ:yvj8"јaJ3srǠ:\)) Œ`_$) J1A8-9Ăq1GR:ĝ%3fzOMnU/ދIʁCԾ*s7?PJel,n *:4S$17l:B@J7ǠZ'7 ȱk8 r*LySS XgnV Rt*" Q6Sr!])A^ݐ戙X 8ys%HIfocP,Ly峋,S)Nʵ= N;RBGO ;&\D$!%P<"|"/Z,F -#>0UWReG9$ #p,G {3TNYDM&1Nf\X@XB2)hC9u!|֨STA,<57x ceڇ@ cG`%OkƆF/g492ҋx]F#> oMdk!ŀ%XܿUfdGsVR "69jN&\3T=+P-Ln,Y|1L\BJ:JX]Wrd5jX}+fh}-c68Js^p)#:S 1T$̥Dߕk<mQRk.Cݓ7fd܇SybhP1P5Tj.ɼ]ysp|oz3Mu)eCS9҆g vuCj@a!bi: ⹓+:5K3%tƨ4'Gi~ygt!Ԯř< 1uXV&_e5:Hƪx%'o)]6^;/=9[R A m/AXß%Q4S >.lq܅YA2 p,&%C0fÃUiܑY2sl7mASp!1.+n(S4T:H"1k(!jJ8%%*aG"w8CO MMhmmu¦SD3aQ|a1<"CF0;*M5,+5.!Kd$7s]|p.|WaoyU_soP.PSJD5gN#[[Hڱtt};GpDdp&SGAчvk - 6yk! 'Iį@NRi;2ZK=r3w/ZUCOY}a 8%8Nͫ:wu X sp<_{$Z&0&6X0)znS3Zg8BbpI] 37vu MuNs;o)2v7G9 3WEjӍ6W{zYP羬.Ғz:͝q%XZOxS xwlR85f|=PP7$A#:ʍi`q7!{Hwʠi]^0'ݻ/ ;s$\sz,_}OS߁^ a嗀Jg%I !3itg"F?p]}:#Ϗ8vɲ['rM]sBcZHR8Q3)QDc86DAA ŵ7t̯ *='ϔψ[lQV8phH#smWJ׽uv͇(vN90Abba&cvkU5&ﹱG0F!A2)t_#~'&N[hpJ0H%%T8oIv]BW,6 IŁ0<8]#$9h=IW yahׯmB5| ()LXa(/ևsctok)1ϓg <4Q-ΜǙ_u iÒDPq` n0Lrr\&̔BHx &Μ#3),YPhYP0X[66N:H(4hDDawY+vxtAç&=Mv ζQ31…#NvFm1=;6逦׆Q>/)kW.M9ΕCIurg|F6>y$]^o(>8޾\_zsݚ4'X,Ź'<p.ɗ==6!r:f׼ MxrFaԢ4ݮG zzۆǵta͓Ȥ\}Z}/~ޢۼ1t egE2dgi Qگ9%`>/$Jcߢ}[:|P`z Nzg]{ܔ45B^IeRm,wlx`@<ݖ?s8((g|O#kt)n;ĘY 7/s 5.m5gyfJ)Mqig^MYҗaSsܸEc=5?(ת9Дn_߱89('ۧ|%?؆Sݫ:ݝ"SϽ3D-ǣ6ܩmb)C4#דض2euC1ӫۀ/dc^J%ZB2jG${b1)Qv\tmTtTIIJ&YhN_#b̞-Gg2"TV d})\!t{1B7;㨂9nϿ nUn|sVev璍׾;m"5RqMyy{TOLDC4>T4线=z~cdu]I,Va9iqK.lgÝ:="NUT{ޜuiCG: 4;TuyBӿB>!CC׽ב kHQ,Iɥ󥇙6mmx/߇6{:)^r1B'r«䱕07 dgI^įKS:;Y<8CuϞl $ CtNsi//lC3G˔Rܧ'^ J-K%Ṡx>khrW_**sVYt6VX:猈0S>DRE|Ev ^#畓kifJ)dt~wߜ6Jk0;JNm+7ţ]d[?6Vdd$%/g/)빽en>:-ۙ(l.834ZtI& rү!\t{.nl҇W!a^5j=sg BMIap| fH$.ۣg~ÊFu]3Ƶ/LڢEDitk8<<'UbCp%9c~ui dlAj$&CJ/?\\m0 $  -4Bj,n%P'34JPyGcT5ֱC,Z!RP`,*n%-*vPP2>%#Gmz[|0vQ|<;a}c+ݴIL63l֌#@T *IpLwd '1zgϜok:v} F.֯\m:4qJ݆jdJ!s CS3FqJ'4ņG.*RHtNN! A޼`%;D5yZ Y7T] AƧAfkX ex*sXNn4oڼ$zw"p*F򀒅,:SA͛<ݹy๷H(\sQ6JP1)}=mn6tE=4F!eFĠGjRg3 {1 i|1֡q}G>0iwU- +d,ntm7&1\Ƭ_./zRjȌ +,cd荋*Tgģ1ˍ5+k5MZV8#K(pS+wcؓBv;ϴ23zcPvHݻ3233#jHQE<+X%R8H0+w%qfސ>Yo+-K}Lɨ)/6WR QB/VC6c[ brv/P%`֌!,3/ҹr^*9s)΋͠Si,B\HL v& E2ZLIZ9zdoW+`Ptn?\a[s.Amut6AY9"qΞ^"̩~R6Д ~fj7W揱PQrg'zs᪖XZ0?ob 7&/^?]Q@}hʘ 3b*+X]!Y7nn-{[ nfk wPW_y˅+ݝ]:I97HiMiBB֙K<6 5juh? OVW~~x-mR)eyL{!=4~ĠQ1,VL̽|`ضplgݸw7veI|ly3Vn^~7U1Da* N;D/otۓfr1bE"*٥c9Q"SR*/VBcz[|у/rĩwim<=wi!؅C]nhxz4sc9r'xC9t\'K3AQWqg0X^]8#5ewLqLj ўMIž]3G]f8gM"NJHG p6_V^LxEk@64 /c_A[}ju"%킩J<ӨN`8^<J1,=#JNFgflF-W<%;gn:{83Ik ƟzK 0϶C"va`僚Q2"ʹ͜X3$m!y6pF TLi{ 9 }”oI#(Q' IŚTMQ]"Q¹Ϝc3Igsd \t0h36,j[> 1(ʲJnXZ3C^U8d*Z]Z- Ym+ Twc[5^9]0-F6 W@)Wq37s7sFnv}NتΜ̰^r16>{2[H{,I &31^ 3fJomGKxMaXl8K1x['b; Z#\p0mԘh@ r$QcBzEZŞ,# FVg()%җAS3@$Bārqt !j em.(s+v̕GbfL9Lқws2ÊvdgH֨Lq๿!tƸR"\͏c%"Ҭ$ %~iOT9UjgfA$nĝjW橘_Fљ:.[m& 'n s;WG q P,Jsnxy~ r%>f/_tQ&%^89uS9yqzџyf ^xal+KVtqdQÅjq Ӊ MR|2ylNPO,H,ZNVE i` q4CH#AP-P yO7I?Z#K#~㰔hhtjuU_]neGwZY̒,sQ:E;7ڈ͸r! w-+΋K/؇CT{7:: rQ^lPV,)j|RCgbBye@<-\ZLs,rn-Dfnj^[7 vD4ِ1UE̕=i*ƽje"+JHb}1ipTUSd/U}hJjS|.ӈuf"M2?[SJXFB.Xj LhN&m ]Cqۀ2w*IdAZܖž]1FKz Z=#oBmJ13S=3G !] K/*2)qe>U}!3K%4dK;Ą*b=]>8#-0BMi6DtZ3U!dcfR+-4~Fc}"LRKcv.RHѽT:s_KmJ )am3fPqV{QqpXCԬ{vl|""A@mXV8,6i 1:kM\Eɭ*Wҙj?s{p7&Sޢ+M hJiJ5GLNVѐT)6%3N#JI@i1^g+;.#c'0\cM6J&d !j߶/_TAl2I4G=$ؤjGS.T̳1XRn4j5NYO6SoÞi9sGvbgNE$tγ'"6Sg.vIHId vK=tqb,Y 0#1dI|x.,p֙.`Q"qG_| k ^ID1 \:]qWҎrK}6ؤtDAF,7s3}!= ͙EO)O*BTk` Hہ3ŷْT'(b L1ÎnK$d^&b#dD3Iv$c}s7nӦe`f)dwҞ<{2>\ݟ̉:D#`[&(zКMhڋ^׆)K5ĩKGw`<@? Nu\N6Qk#FA02tT'n[;:}"pTKcx'U$ưcҁ1?pg1쟳1ا+Cy4BgirTav\+=y~/ Idj3rdT-d1D>831o<鲙J^Fquba<:jYǾUsQ؇LFdu>8B;piWz+HVU. }I!r{{?'Ok%ުYdha.ɺG壌@`_QdQ(Ҹ:t,1E#{lbĸ*9EL jgiɱkeHqKC &\bj/ZMi:ۆ?.C|Jxgߢwb涸qm`.gy/?uF2bvu|txJU=1 Rz1() _m,{Dܿ 1ǒup*,@=F6s%kٙ n4bۂwXޅ82]zX i1w.i;s~yB#=nl$!K04 z%E Dij1nfXRcDžl W5զH)ݢߖj d"dyUڇO.#<^oMMcr$J\:7HG%_@#kf 5B/V8)D"t '9bԋFZg_N N6G4.)n7Um/sM4Au@ &@)U]|,D CS/ E bdBȹrH׮zg]F͉hot|mDKH/B6:I5~)=>{n@@zw[܎K[x@F LdZR>3F"y!B`F xM/ .ڙ T"|/ D4R[] &|"\A"Q: - 1hK8G RDZyiS(ژZaҙIz6Lf@3ٖddW}[yE[()j]9wˤ'[]P#gJO[xt'n:; df(1C݈I7-,<= ؼ[4$Xs?;AݚK*_Zw?C<3KYnrw5W4 ^XK+Uqm)a\MݨM$MO[^.( ̹OSM50H䡪T``9+\g:B7H d\ 7:$5ŝfC=0FozEX$!]h), R,q3v2n-ΚހgOR(^Z#v5th7'H"`:= ?Z).uX|D;5{,i[6&i =xSO%tTە4 T}]ND$,sDD V"UΦZ+)g홱g,_m"ky OadB h8 晠(0ճOU 9k3CN4K%!t[S$Yָ^uK8dr7{.dl",RrMc?:3WVtZίA7޸{ a]sf2s+MIbb/PCr3Û!RۙseGh^FF~dZc0y+e"QlBwW$**Ym;q3g-ΥI`O*d=?tztṄ¤I;MWqd/됹<3ȋ+L!GG[a2iC.`$1]bD?, mO-YMLb%΃9xb։&G:Ll`۱,141j& U&L#CxE #717:LިbSkT07)s;-Dc6PUf,r11Dp]ڠ<+KG jp~΀5]EZkڭ/&=ᰶ<{(Nܖ#rTϜ֌>S<;rʩLsizKՕգA񊫴'K痉{/dRNMFdq2"gY-i:әtR!i"#\T9=:7F, ZA I98" ʉܒc8=sbhCk -lS6B,g2 9cWt5!g-a"{6RiQqb%B2cypؓrTp\ՄSv2\9 a<8$޸1Go&r<}=Pr x\ډ9r5D9sK\3{'{f b7}HJqеwfMim,Zc Ĝ"{y8&r̥2/No"bS))RqTgQPfz{v\so<-䐸]|nYFEIcqEfSo9[~{4p!]1đGK4m<5>KmS5J4,4ˁ̞!8{\kb|<3~9fzo(Hщ]+W(;9r7~xޕ3f ٳ{3vZmw" 5՚FҰCzG#mnQ&7^of&Kӎ0#L8 K) ˍN=sn7Lz˹0#K[x|sӏh$CbF9M:CQ2]VP^&&Qĉn+YvAqI%f -` Q,>+].^agUl®/RXMה3\x4Y$1$Z3;$:{90@z@tt!MU.alt2]f;kk\}z19)@Rk3,BiL%4];aN&ý[^ixUQ0Rbj]%ʹrf s; qdM0#ߗs+V=xck0W]α݁ л߷'- dsjF6/ >}Ei&JR%XӐ^&b P`TkcWb;#[# G{Ft2M`܀Yio/ I1rLO!SӎxKKPlN.b&"]Li8cVoi. $Fg% 0O.fTq? c|jpֶOˎkއuA 6e`X46b;Lσ=l 2zc$qK[&h*tX=w#4$g5{ uZSGx]-@|_`pi)BVOMc;3zF~{CwY G]ܳJF^,fY]K^fW>-j?[1[5b^tg}WʹȶqaX[. kn1TwƳiC*Ɓ蹝d[5G6B)I fǛYR]{޼c񗑠Ӌ RL._T.i!],Y[!3v>\E n0)f&tMֺBro{D_Z1 4xQ4Z:NadM/ݹ> غCc8@!4q gq8SQ #T eՙM:z%UE JYUWGUuXǷf*J fѵBX3QlS1JK&χ^j紘6hBS`1skj4"i"JCg'PohFg kͦ;XwZL&%:c\;sQ&´WLm @{; G^Eqx4m 186g }ܱC8ǜ ? vԎL: Y+BJ؅x.][C<rmr%ڑOm}q Z~qN=}X,:yZXDЙ20Nv}4Ό)q?籚ΣR"sf̑1s]6\xj42x,-E*9(MGGr19i A~+TқJNJJFѪ"5Rip8} gRaGF]3KkH;rKj'/L m!!125'9=5^GzXYt>qjB,nH̥q*'7ON 繲T ڧy%!XZssNe!q=fRrF>mɬd  ݍ;ƜBΘИRNY:ybd?&$/N_S\L|*Vq?AF!GJkΚ3,hh &br 2Rd|DgFÌRj} n+ˇyz|]NeFem {3UDӂRFfDdϘ̃ 5) Ot=#"EihZbYF J* z ;ݰc({bo򄎆ЅԚ%!>a#B_S_lјHXnL!aG;z&#y$ p?Z!%v;#˳hݓ=S;qGJ/4}J(+Af:S{9ͳtM/a(*OWtq'XCȌ!#WښrC(Nn F [ޘ]deML&ͰtbtLdi>G!$()+v&ZSJi߬mGnMnK=$7{ua`!i!8ܣ9=)aW[ܠRX⤙H]zFLUYJ/*)dLw*pM$:]ٻϠcZOLFl+ysf ݋9()tIU(](=x|%f}Ƕ WR0Dc0uwvh0Mh^$ʐޮspQ Eo+Qu&.7-'ɑ#tN<^.^N3>1.|W_ޗG>p"-& l`fơ@c˝Ot]:u2dž0Ke'u4ZVSk`lJR!XZe73(Jrԅ1JJ #=f!<NyMϿA[}juEnr]rL 1^^ލWyz4 J6VБ}aD!`Mሹ7-Ծ3Ps=K#dC9$`8sP`⮍r`Qs]'$ػH7bm7޽pȚ%;5PxZ<..$FL1H$a&V6u]`$&4*Og5QMHSr-fJЛH@2йʇ"6Rb=DBMU|Cb7:K %KnC@C ջ&nmHаH'ni#ٮ!۹=Cn2F˨jٸ?1(QS)dJH T]Y)9Ք6,F!:0mQf_ .mFf++J`2{ s7OAO6v85/n|  1(MȺàόpelCBLUWS@HKٹ4em4FԸrQ E7SA9ܜ 9a*dg2z‡cp Cnj[RETj7Hf $+r`方0Dxy9NX sq,O[1YneQ`d|u_EL n6/ʣ6ڎ;:7'u}"l1"Ch Jf1|뻮r2^ ը|쫱_6#QsNpjjי'8 i 65hA)mkkopسT3zmv%euPmfYo mFH!=IS9q[oyn|K)r 8d0Rt#v6;bn|G7~aȽ7L#6qfPv! :9$zaz,s937ugNDؑyF8kz/@ .LZ8DW! ddLU6Ɲkvmf֙Y&ΘY0x&^ i$x8\bv^m%-Q L$q|.}`Sx6}=:0;5APYfЙ<r%v)ČnSv= _ l/H"b"Z9L"2s08-8vH[hc҂ ?`*<}j3lLL29b'bбL,^ȁ|I`>_#wuEieFd4(7ESh w/zI!r/?mf.+4MB`ve1A]kN'9Wc釈MS_wc0v_@ P1QS?3ՉM<<3u/SIS8c;q\n9#z\$d$ hmnLۨ}1VT+)؟_F.Rkf8+c{ 9}`pDr}Mш+*Խ$[i^8/{fn5a"}Al"m!Lj:EvǁFH~[ 9^%| "1ǮR][?;1/)b aӰ1cڙg Ch! %Wbj1(DTW8vLi bF*v!Bf-NBkOH$z.qjSEɩvRt'?1ABH}K>MT:U۴G^]aQ `TmmoVv\83gb鞛c&M-[w#hYC*]HD.q1[7oZuˋ*`O#lqw{I> `:=S+nxl" FX?G/Ez4?=էV9M65Ww^NJB8>>M"n.A .Ib;}351uݺW=;'cz!"t$WNrL3QFU;AW<{f@,fk.% %I<.$ H2kqM-H+!*F23^h7<-צ;_rKXuN{SYzҸΊ180;R18&a&hpO&Y;H8De=9 f?frUinU8[1(};5tƀ+V|TEQNUq]ln~;$:r¢LltT<~L<ى-n櫔^}0<>Sq\|~{CW//DSuKTo*ʁ|w4-Q&`tQAfàP-Ogݒdyr B @qc5h׉"hV(ɡ [Y,4HM] &xfY֍zFBcpKC_QHhGH"e H2&bWךymz7һ%Z =H0@& hJCm]I`;㤮,gĩê d!ZѫMw?Đ$mL4Nsc7Z^flJD5xblvɞvIi7c`+et6sO0$u?[$1rj6ebażrvk8P~;qi yw"f ԧr"+{\Qqµ}7k -49 9j12;6ί=j(+oq;' ?kkj? ɠK# C Q~C`= -y<sh". rGbHtO<2RgĹM ;1xcb97o9?'DqC3b|KM!Qk{h@Wct`nS936cQJ q+A2οs!M0羰PGc;G .<-B Z5nE$spc3P_:?$hx0BĔc1C(r= ea4.ACj$ ƇdZbM3m2Wn:."CVbd2URq*5kuOGhI!.zꪌquOwtY/maS;[ 69>G3+Mho٦nn(d`J 7E_4Н%LXC̱sNcHh=|}Jn/NJЈ(z6ČHqO M-e!jG1>DĄ!u }{6jA{1:@C%)EIitGt"{ynMTpoLѡR]h !a 3rx=xfsҕ>7=pλi:f nTSPDgN#bR26:f*-$m⺠\6}h\|pqty5w W1#i{@{Z6e_c18{k* =X3! f. H Lџn+H<~̛o >{iGW{fR{Cvi>AH5`&\Qzl"0#z={HQpk Av=mTOMk_0ܭ:\#PMG  ϸI O JH ͔bi !$IyLDFІxBO,({*=O5m0l_,׶MA@Ϯ> @F)nn"+%nQ9Mou66',- gMEEۛ-E'b3;6r<,tfk sM̽%{m.K̥q5dD"J^A`ϫ8,ކ p)etw DWQ$XH]m[Ѓ9\< tt?'jk*LJYq4pvX$ă{\Hm`qh՚F,N7a)S*ߣ4D6rgӎ!8CipV,S-c4AEvWÁ! Ζw\ uj1uOg?w eKDž[wDE)ha!]S{ڦI\g_t' ;r0 W=O/k:wa'Cp 7nQf8hGcڙ.ez:IbWd'ܟK|Zr"Ĵ'e Vm6qJ:y{O@$)lUVp 84 (݁]4=zUAx[ "Rb!J7OҊ_ddHMQhDڋoDp=i !AxMWSl^i^uKu $R@VmÐW]1>QpK2"ipؼ FY3@ɽM #].͢hR*pFOU{I4+ܣQOI"!M?_kRz$ߝH}ZDͮ;|o6(V.Ƙ ".e9BorIQi}]İN"-7}C^8"E#CP܌5gҌѭW/tXNbnA<1H ;XS$UMp_Nv 7 imwQLT"T͌ypq 4hDRLT 5i.jYr! sGxl8a$yy $!Yy0oz;H1q1=TN?%2 5RЫ'6S \_]4LQ`͏yg^Z^2F0%b RN(>5[\;2wpyÏl"`/١:@/]%BZS1&,^A K]&WNl6!\:.,͎Iv& yu 6QLcъ Pb!.TarQ^uM*ݼetԘbⲈ6%Yc- Ub&yD5nO~Wm8r\Ro^殽?,h?덢Bo.g趽H,'"a/&^8<ӄ\vسש}ffG:-59MqTcp}q5͠.F{p*1_: 3c_ܸ~^Pb/!$zM% :g `s!ǟj7lb\j'~s4ZԦT K!s*d4d$^+;Oj Y4ԙ277) E3+n ZlRDt5| eԮD)6FB_U'Fڍ ~! ٧2CYt V6bmFRИ1B ǝ;nLY'E mB3lJ]:mS4wCхrwM(Jkp@Qۑ'0>Writ,𚃃7 ] ?I$bLi}\Ra,_cV+G z3M _|!jm_zOP@p+(b"n) ǏrԐ\Kl®͗z eabYS=qoo8n \-%En)[z"W{D FDV;^rp42³_sUw*6`9|9ڌXB>ٮR> 1 քn19T "셫|,V8J恜29 ܜo' Xo 6Řmq* }y+Qڍt/7b)-}eRj*VV(Ira{qhfk dY/έbPWΏ.ܮD[K#$V"Un#m"Ht7>`VC!s'l 3K+6~|frýZ/&FPX4КVUe%meMQ͊L!!7]Vb͓t{M.lS )54MiGkJ-y0^sBDrJ')J`j7︙f&XS_B086MM,^JuJe')"E/\1V=I)]6]5o"]]d)$O؅OUaW&}5ێAWچET$0BWMV8`:qLtz=W.'yW`2+sx0ާ9j 8$$\P;TpaK)݅w}V(  ' ? |'j ([ S~#ASYVdPp4XCX)Z&IsKL "t XZGryl(h= =Tk&0O7q 灠ЬqJjOs4bu Mr2E J\! L )8@AHdLƍ[wSD%(L<~B'(qv$\8\3)w[+'wcS̭B޴W5ճU*q0+p@ ،)҅ F?My)E>#?B_U=(WÎX|ixYv~Srʤnk3sԬ /{-j!=Mb]X1j "!ҽ m> jbFĨ' Ec!4w4$9_'g.p "ruƭ 0jy]pCA> kE v$Y?]n Hص)Vv^5XXQj ]N6J-WZ46}}4?`D F jL9 ҉.Jy%o=;}2{y"nlQ[T}ZjV6W  `\:k_ѓB`y$w1jpժ)q.ͫԭth1 u^mK?x.jj~y7`/76^[[Pr&dvbx\M+0mb /Wx|TtX*&{jWb­ƹڍ%aHi[STaFuԭ'}ۉA1Ûw]Lԩ.X=+LYzXN 14g)x~2J[XLM+ǰP1i]ع2qF S9h\g~vKö~mĉYzqG&)$!!mjX++ז氘}z0`/<ap:vpm/=ѭKAkVjJi%KFwO4ʱ9.'R dJ\_(uTO̤18@TmO|aNXͲgB\?@Ac1]4S[H@}IZ9GͩU g=ZB:>ks&}!q 7\]U,hBn)ƁsQb(BUkdMmigpiåZH}+q-x7]']-L歁POTsٚ~NN ҈æN4ŧRk'hYt&ZTmF.&z9i"2Y=:Diz ܎R0s|[F?±M#F6٨ Z+EgOL3c;Jhn&KڌG^S?1xV:Ppgmmi2)$B7%d@{g֙]1ĝA̺1jRQ`ݥ2ɺSɭb&!3k?Z!|C]"gШfcuR!Cُ8ji+V]ZnIf:PH[ak昹{ o Pw 7c?cv>p2c6qD.+\TQgۢTLp5\"C,#3NG,eia?\GF'΃oU&S|E3E1(Pxh1$),i)` LC> ^_e 먋n!g}i}_UdivkfrYQ{Wm~]VATn1Յðw{}ԴN+CE٩v]'̀<7t͍qէB;6x3IPWkܵջ͏bpc)gB kpȧ6!7nR,`\ *QEi+컖:mU lLiVL<T{rSB.$C̃Cgf3AUSF&ϔ`yAhʐnnbȕvNBqPZ=~ƜN0U4x6Mu`6 kd`u6};.jXe4Q8؄ Zyn][M;[DG[;mwj_烱{6[ohسl2$Y #GkpAp䢰w ^vALl]9}m\|;{e_eOP 3X0Fw9>O][aA`֭qLj\xIsXܜ_qHEB]W;=vpU0_77VY{P[askܤ}ڻ}^-%k-31&"i48i _,bwͼv[C-i3ŵbƥcus'HbyA_cs%n ,aDAg^۹ y x{.:Gd(YQ2?E>Fߥ=] lXlՂ|aQS1ޔ.+e等r/Q{4Jtt 刁kپ =CR{A¥.0:dkl+< ]i!GD՞C/WFiݖf?)UUT]9=meWP-W/(EMJ=b bl\jvy :jX+g䎶dlu<\&S0tOlJhm!f՟+9P\Otw|'_u_OOͼ \QC of#7WSfj2 |@62>W:SJc 88d.Z𤓥8?&GF7]UW?\~djٕC||i lDe'\|}aSDF0aUǽuΜi,:5S h*Wg&7-hkSF]2`_]BBSWxg|w^_}m|PUW uU:s'i=AeE[V3ann9j6>K]8 -X2j k,깞)p;@;#j.Y,ݸmH{jDlj z&:X#E8a}%@ޑn3+a]A.]^7Z: V#rkYݭ:ǥK'ug/QՊM[ )sZ*HyE1@{o,M1@#Uڋ[:R;)ǹΘ#hjv6]pJJu05MNm$䨟 ۄ'}<-ˆԺ-d{gEP>SZ,: : G2]wY&8:369UM~ꛫFcvlNlj1o4pffE2q,!iz4*N1P1*bJMG{ /ץ"w'fidk˺ܦ}1-St^E b q40=_Οz!++ɟ-o[[x;+G?=jkDu.\>rz5onnf{uW^fF0OFdv1TOD[[.A1+I>O>cm^("֚skVRͤf'D)Z^nk՛$WP?3kIߡ+wo 9^Q\_꺳*nt,ˬ0xUήթIJi_\E/5>.TܚgEdJW=qf?\_v͏]>\௹1pn n6uêpEZ:<+FELtW1]0`M&UgJ6T&Swmv Lٱ:͖3br\ Ε{LJRS5^+/%g Ja-z4eٽ1f=DKyTx}u\ڄlpK) a}G6'&7dִ(yֳSkX׽; `p넹v;ljMe.M} udg{fo0̦lDzIW?tv7?_U;>-];sKҮN9$/JWuWkY2)E:Յ}_LjY] \`\@i "61M}2Õ 7+jn}Z[ƶKTp<7~?, }{oo~y/ nn}ՖO>6}G` sHnbs_xYO /®ztء̢Gn!!1]Gf+j}H2D.;> =ͬlkyRlg&84,u HLB'e6:|y8`!X1dw lA nfeVNnB|d11~ܷй[!&'Plk9AO"v3[\b]>h`"|>u@-M_] ~X6>s (r"4|.*5HJ}2vdQ*cxu6Jgis܎Vc` v )LyDZ ډ)f\J d@/!"Ƈ/JHWQW>fRrXTBF}P~T?Aӓ0)w/WXo혬n(EHkW&11D/I 'vbi߿!َ5E!Tbq>cA[` =#"%4BΥTVz+o!͌L汩^l^hSoӇ'\bloK/3o?kW? ?Ď?k>ݵ]ڮk[ >X= ^:bgя~LǑq?>|ZVϺ@~v}>k>ݵ]׮ZO0 |W}y{>𶷽3tT[mV[mV}=@ۿy[~O?mV[mV[fD7oyQy˿wݼoLVǑ=V]ڮgwmg׺hjj'XV[mV[mՓZ[V[mV[mnV[mV[=a5[mV[mVOXm Vw?GݎW~W_7~7r}koͧhDϫ?HJ?'k{Ox}gg~7͌?4W9+_˼⋟spz׻}?:__77ۿ?y{^?_O?^=zw|wԟ4YoVݿwO4W~~?ا񨟜Dϯ|w}//⻿?GJm60[}|_O--}_e_v~~:'>mm|ɗ| 1FտW}4W_e۾駟tY?|OO?|V[MeYx{7}7}7}k;zl/נ>3?3|_C|듹>_kַ?oKKor>?D's}}wݨ*G_gtVD'l[/5{{ÿx[[_C|듹>w~~__!my-듹>ɯ꯲_%^x_+K>󶷽o;4Qk?OO|:y&[}V|U/w׿:'~ק_KK?]'~~??ٟݦQ}"?u~~/2-~OmV׽ =w]]/"O0D ?g~W*` R7|7|ZIOyFo}[?S_a?A[}v^|E~G//~7o~x?3~ꧨ|~_K?>[}z>׼=[Vy[L}Dw~wrss?7>~VkjjzjnV[mV[=a5[mV[mVOXm V[mV[mV[V[mV[mnV[mV[=a5[mV[mVOXm V[mV[mV[V[mV[mnV[mV[=a5[mV[mVOXm V[mV[mV[V[mV[mnV[mV[=a5[mV[mVOXm V[mV[mV[V[mV[mnV[mV[=a5[mV[mVOXm V[mV[mV[V[mV[mnV[mV[=a5[mV[mVOXm V[mV[mV[V[mV[mnV[mV[=a5[mV[mVOXm V[mV[mV[V[mV[mnV[mV[=a5[mV[mVOXm V[mV[mV?vbzBpCIENDB`mir_eval-0.8.2/tests/baseline_images/test_display/test_display_separation_label.png000066400000000000000000007425621475740344600311300ustar00rootroot00000000000000PNG  IHDR5 pHYsaa?iIDATx{nWY9z}n9D"UkT`A,(P( VBERm~DTBĄM 5!999{s>?s\=?';{w<7bfFCCCCCCCCÎ/E# ; 6444444404а`CCCCCCCC# ; 6444444404а`CCCCCCCC# ; 6444444404а`CCCCCCCC# ; 6444444404а`CCCCCCCC# ; 6444444404а`CCCCCCCC# ; 6444444404а`CCCCCCCC# ; 6444444404а`CCCCCCCC# ; 6444444404а`CCCCCCCC# ; 6444444404а`CCCCCCCC# ; 6444444404а`CCCCCCCC# ; 6444444404а`CCCCCCCC# ; 6444444404а`CCCCCCCC# ; 6444444404аpJ7M "\uU3f .]}}~x+pgcϞ=xֳ|+mnv\yؿ?ߏ+wq}pW /NYO~q%>[ނxߎO8ԧ>wyg檫>\{'>Ç+@1o7x#8oĕW^y_CCCCCCCbf/bÇw_%<ůꯂqફk_Z{xߌe8x w~w= OqM7xz\z믿]v _|v 6NI''?xS2oƭފ=i|'>g1 h .zԣ6ggOxMCCCCCCC7*k?[op>?s/})o3pglcz8sV9maX`XSJ{uY Æ̌;\p;%{򗿌ccccdI۬Xyӛބ׿G=OCCCCCC_?g?n {g1F_wmn wyX.G*m݆|_]9׾u^:Lof|_iv7ﺡġCpb߾}o8d|s}?ov?w>;;7=}#n|[e]S;p 7$|>|>_NkuJ}Qz={ଳʟ_uUx߈.]t7bx ^ؿ?^Uz:,yx_G?98.r%/.K_R\q-<5&^oǥ^??ɸo{ubssO~qW{kW2G ?Y~ky(8tߏ6pCCCCCm~* ߈`fFUnG 644444X.[pȑRa{nfh~DJ 7|3 0͚ruX.׾o]tюM|44p?b\" /w﾿/vBҗry;744444h*E{GG{: ; p /pVηo{W]]|co駟W]u㎓vFN1^۟>;]=ǟ0 ==xSl<=̆FN1ܹpps;{[k9$pV8a[[x+^nk.ڵd\nI@lhhhhh8E1v^$'~'pWꫯv۫~~x }r׼5o&ٳ^z)>ݭlXE# w /_|1~G}{qf?C?G?>O~^{-_a\~{vv n=y~GpG?<) ox}1y }W .W{^ofg|S/u~뷎xxK^ofgu=FNy{B7}7Ϙ}o?G I){~ޏw޻ 6444444Bmʯ <\s G\r >яW1n|ko4pBЇ>o/~?gx{ރmG=O~2[B5y G~G+G?-I@nhhhhh8E6x-tBOySV 7ވ???1~}c'= 7pC{^/ī^*\|xֳn^x ]kzov :8ihhhhxbkk 7|3Їbccȩufnhhhhh8p9?k7h{獐5kh> ; 6444444404а`CCCCCCCC# ; 6444444404а64444485`q;4`)^;hT׾غ;'D_??3?[\r%U6$4paqHȟƱ[ršV/rz_+Wp|NUt@$s>y睇>xk_/׾>'=Iصk:,/ÇW׿sN;4e/rpl4pRpa\s5o6uY8r.rq??Oh~馛xއ|x_?@37444444m|C޽{wu?||Cs\s 677ۿسgo;go~3=\l6ooax#__Vuo=ՆǍ7ވo7px/ᦛncL໿Rc޽;~e|NBSN̜޳g[M~x f=v6 ww\r N;4viGG/zы@D'< c, g={Yz򕯌qWbؿ?Jq-644444<`+_G9M<Ǎ7ވÇ'?I8=,?f޽{?^S>//3 >IOzg//6_~9nxt p>+1Ƽ ^x8p8oW^y}v *"z뭸[qM7x>g>lllE/z>O۟xJs9/~?#~~݋8L|3G o;N\x# ;<)3.Bɟ 㦛npK/qe _. YS)ل&k7444L),j$kD{Zs`4'O;z}C8 .o>|;~~}ߗ~UW;;{n<9[3x򓟌.ߋb?)Gkwu.>1s98'>oxJⳟ,aӞ\G=Q?ggOx~\wu'L 'W5q5pbihhhIXG ³6N[qqq8C%kS.7'~я~ttrW[$>. [[[ػw/>xx~yCp7'=Ig?|[o gq{.nV sNf1F4!{D#bhHߜ[N}4ew+~A_:Zk5cLcUuc6K)S^|Ÿqwc?c?G<x󞗷{ԣ?xC??m{̩侮c-Z 7]X0X .^0@uSf+uUB>S4wS'ڿm|{Vlʲ;kUm<*1&wLqJ┴Gf3|۷}Moz~n{!ypya\opWՕc}k_۬^:Omn/ggqg ؿ?^Uz:,yx_G?9*8.r%/.K_R\q'L`\|mӪ7Y\(cue>_^F۾77_4Ǿ2IF@C} G&tg]z*ǔr@7HQyw2]okPoƥFؾp~+q-`Kpqwwwo߾|m}s'?ɸ\s5x+_goI:K<@Nbnmw]WXH{e6ʃ;tRՑO*; 44ߨIQt2.5H[ӿm|OxfiG 3pNO3%v޻jΧ8tߏ~8nzpx@h6ӟ} *d}Ӕ8A'N "!!ZwuY[7q၈c6<\ޏ6~GP7/~}C!W#ǫ M>wpEtk'2~ms [[[G`;N)>G&$dK\\I9ۘc]޸>?`.#$3L#lypsLWF(mߚPڶwzl7ת9X.Oɠ&b[*m5GD!)V?o6uFj^'60j4bXc:`ZO욶Êդ,< XQ*{-|L 4iڔ+BP7@uh(\L Do j-kh}áŸȱ8Ns:m~~~g:넎q뭷 ox>s9}cqUWO~IކFO'=SqpeUկk&'2n#OO_JJi5ħ&v9'#ĀY? v̩yzVRȬ\CMÉir=ӟYCéV_:>-LN\?YȓIh'#880.bfI'~S,qhygn9=qWOLJ>!<|>Ǘ%~x _38w3\ឣ)'3?S̈2 N;Ժj_=F{Hp5+4j,a}'pJ2(-Yhibt G/FgB 5qޡCv9y(:e(j@#muN6mǛRb*Q%b}"`Y}~jX7oYX7YWFrb߽wK6yϴMIp0hmDM6zk_%ٳg~rLǷ|˷o_r5;#G7 : s^~v^~a=<Ԑu>c9_£MSpySg",q0,^S}b*e0)z۪8{g1ĬM!hmnrlN! ujoW]G&6Lc#GKz=zn Ѱr}89W^CVdtGjq8C'uzq{rIbJ )L~[-lC QfPEN* u?G=UW]~C__OO0 x;ށ<1'?\k^??ߓl@#'FL p[~H1}j_Q׭(O%ȍmT4M骚kNSyULKt p@|,^{#`*?%5_D&wos:6S+n9}sb g]k`H!ֿMT3lExɜՖz$pfQ9GרxDQԅ(csIr7tå^?;묳p㦛n7okǠ# ?t"RUGiî\aM%uɴ-mQV)9=JNxeoD V'1Q&9ĀPq[:tQo30:uʞX#oFa@տh,81.Dn }K____ęgO|x_avv,8_I2.1$iȎhk@$pѝd3emV_"oL?o Ǩ,fs8Hپ.J v,&"%FLiH` Ikw@`8fNB'D2i u/3O&5 i2_o y 1qmw圶" r V'ڡPX1J:COkbVS #$/Zmq9萲85a=y&P%Y*F|u7='R Oer²pB +ʌO–J &!٢R_YAw?ԛ9#[|QSlJ2`eB )$p@.@g5 BqG#WܜOESDdI]`&u85͗vf<|junk^VOۮmb۬d?5嫦>]Cf+}[ݧM:81zSnu|w#2>_WAQac OZN` 9oߞٔ=HI68Q5i59)T^,Z$NHHq@LAߋ}U]WrdS€=YrvƑc컝+ɱv< |w7.R/.||;!:gⓟ$H9%:E3 ,bG x[ߊ7x^ś&/<qW`\{{x5]=s{})Ca{߿3r]bൊUS:U>X 9Z5#! e7 %Q\ _{J+)%Dr  GЩ xj?NK c&ƔD #+@#Η믔+U {Psf|̉8$n8bLOS_uZSoyv6UVk#@ Q%gi!ǝkcg;Q&`&z(:y#FJf q1aHKq"86ZYLƯN\A sȩglRDqUԏ,8|)9BMZjꁍoe#h ;^ Msn]osM!U\-l7=p=?m&[[uG/yB+WjkY{JZn|,:1g:U+j@[Y8,fnJZXmYgȾoE^3Ux~' w~/u}vuˆ]SFQSVkȝǾ5-yxl6k=n4 '&=R< %Fx?S:?:39A|W:%Y~֫o\)wl#a5`z;18`@RqlIKx}c;I6P5ٔ{x}W'vd#~ۙ3[\=s_.ہ0\ xzQ%@̻Dvh}>B彬<#S_mzΔVϹ-;޲"P~ɂ;%k \Iw da:miuQ:Uu!K0z?ⳗ]y~N3]7'VuAB 5]ijcGie g>groG]4qRX&4778< 8:=pX.'#d"!2$k%w_J pP(mSlQy1 @IL b}dMl92G{٧|ns([{fy3kn?hyQw8"]S#*RTO,֫5ڮڶrfr)1ES}#Gx[F_TL.\(m7g]ofaa}]W*iX_1@,Q6s.x#E@{SLI1Ցm#ʸ:xk4}L7? D(i Q JCX.^I "'Ie8]QB3N&Nxw'sZ;mt'c#b.3?U9ԎiȕF&EϕO# YX+rSm_ON#)BbRKb3.cor%P3WEP\s&S8  ۢy+vRٓLɫeH[5y?UU g4܊wwbJq`;uhzisT63QpYAF&v߇sϛ@j&q8Z}wd Bk ޿)Qeyx{Qi04w2tZQYNS,< G <1k4w> 8CdIDۙр]q_NTrRfU%ju:850M HD s^aыaMϰ .w3tGfw}N@)!SReلn%4 p]˻0zrM6*V$yf4iU( "1廾 I>Z*Le\򵕀&- 9(6.PANUrai} `Gw*pPG9sfNk8rn6~'UUFB#'G#E͓Vef⤊ ,ӍLMYʼ .I]VL*0SBL[QL%NT/б9VǮ;/f"bJX-;:8%S7֒KCD"Cz2c@LC 82܅N>L5.QH6&ndG@@H;q)xj md()[^PX|(4䶸$2JT4MrR5Q͔NHj!IaWH<:WrHBFh],5#*焄DĿI`z~;ӍVx9Z`W4 0fY%HbXT C@;xh :GU712hy\F6YEA|5?.ٗ۲ $ RK0gul=D@2>+2uR  0v[&Syj'MOywO FO,eeV 4'1GZ$*aE(GN6\d@N')1MI 0΁p)ɮ^L՟ͲڤB`56Mg{4EJQ|Dz3)sUAdGpn3ɛZ]|˅xtbΤt.YP=mHZ"f¿XQ_ԔI1 #y}98')d؈1,,@@蒴b!^kJCX#yS(w0JH/dD*4yFQhQ5j][Z/`jto#Lͨ[+X!0zG[@&|D(G9"Ԗ z3:@ULRa,[@qm"ھH^4g"g|9̳D3ݪRAԻ1WsQ!H:W3ji[0 r{]=!@Fҏ擾[y5)@#'ym iJ~# @`3YTufn6jL1Q`ťlC?buMpՔ*]:c lIDs8#{!pt jF"5G{zNS 7 &&C$eNva\} ӼgEHQnuz$Kb(6٦_Og:I=!ιZ:igٞojuB`==+V8t{bX@ cԨ6 8$Ѳ 7])_V] $YY IK#Q<9]uQR '9q7QWcIcSTK|ϝZ X)&k^DŽBJJ%oՄɚj Q$_%y7GG|w.( ['^޽eQ7ِ}mUѼ9l zkĞ),՘6SBH|(FA]. 0z$Z-6`,;CQ] ƿO&3[dxk ym0Qw2el8.:tͷތJ Ngj..w$G[a [ wb(E5(Wi>j SY5N:4`)ؤZ;^#4˹CBG 3a#GhKK3y5+jaakV&"{rICzF9yjg510 Ĩ1D:>&^kˑ a2WrLwDJ5GHLL;qlEeJ<#PJ}ζN}hbQ.VEWӷy'f,Opӷ⣗U]ǯeZ-rۭl!,ЂeŘ&Yiĥm!BGf {!ɂMHr\kp(uyݺ6%;-Ϩsv%)bqIۮ Ү˫737K[[Yq ]"I QUe\ ~kY/CsnrICfm.rY{ s@۵ƲLqh*<N[XX]C Yc4/ <%a詇GI,ʪII[:oG,j~zEgH)!ɉ9L2B;wsjv8 <- 8P{0Oy'[KLl^~$rj*V2$dj*r! jjM*dsXXɈ9T;R.E&ۛudN U OT [?0HP ٢G3!3Y@| j@pbL)UQ}>&}P|om&%3]ο+2 ?$T}!, aʹ!c7j@ -DkNİIU)wl~9>;/_C"Q5izp;;n6tz,c)ArkhyOSI!.U4RH/˸z5l!rļcg!9k۪K+Wc퉁tՍ̜79 qBtCNtebR@HXAD{`bVeBNA"O{༨D^͜y-#e_?ރ*sUlWLsJ3D̜i]%9tb^G5XOh5o*VTT1"*89EMM lەF;K怀 wGJ=_UɻB:i ˰ 0\'_g()|l޶gm4tQfhej1/r. Ph2i*RS$KV 5tSEXT׺.%Ud,(5$A $$+r+ψ!Mi& 1{Y];S^ٽN$@@勗l]v-J\<gQ&@&nc&9QBuDweP]|^,g K*BJ7R3CJņ''(}f8]KG̒&oT!`y2[bHb`+K<1 G/FODzb~]ZI:uun?سoL)H>BVy:ס}L<72jZ)$ynyԝr9S(HĞ*{dFf`Kqdw yr0h~19Ap\C|9J*'_WL踘|#KH]{i9 zmSc_ฝ &9ATBJA:QL e+X I ˁ+u{C~fT L6AP% S2RDd14`$YZ(bCҀR/դEV8O5$tLG%qr9Sx Ja]KMF9S}ZybG$/D~Jb3?֔ %y31R;KD%2̓*AEuTrK(*3nnhq įM]aF. iz|>@l4VR~챭XRV2~ #Ng}; T;NE#Hog<4׿xߍo^z)~7~|#1^W}{677'?x;?8os㕯|%>gq駟5o-Qdcw; AŹwH)kXE7EZ3# D,NKJ'jh#S.yI!}$,.){^C'u&֪C*$DPH#Q9n^70KQu:5'/`gÏ$DDU$,[:h`R6GIS)$p]IPWH;δy\ek{)D2I.( Ѣ)BQx$(Y-H3姫D%QNZ GSOW203:3+Y H!=„bcMiuԺBb͵M׻brR9I)N 3Ѧ,B@U>F\#'5YS*AM~'S߉!SjkO#]i Vg2RO$ SBJ4t /"B]l,l5\ڈ)(gX^l-YpJ!hj:!^1 GJ:녧>(D'Uºr 1Bs}6Fi'GY` G{~˿g>|3xғg? [ov|ӟy睇>;1*|^O|8|0 )x ^op7+[l"dН3[JuRS) #hV$$elvLɶ+FTuN@L.6c33J$e$ZN_+R`氅0wak8!B:"18 ƀEH[XR ,y!y I#2栋i@Jb).!Z$qJ 'UASC\b>S@INdbwj.YiI'n?y@*ؽP s4/9? $M>?f~mҦ*YیLq2|lfOq*s{AQJrnUoL N MRUp"2Ӓ4`인>d*i$ Tams2 Q~i %VۆS֚(S>VքQiǺQ!!!ZOc!& IBHץ/UF5Z +J01ȱzsPͬJ$#m_)'X b6HxK5O H,)UhWb{K9J-%R._Dk=U(#>|_yf1Sܰ-LJɢN i 1 RSǾΫw &3<;qફk_Z{xߌe8x w~w= OqM7xz\z믿]v _|q]WN՛w^1`HJ8e?4X#>MPX<{8vZVnԙ ^5pVo=N(B)!)D^"1.t˯'|=;AD=O\"J(>= ùupGoCXF *#RG8 ɲ=P7ed )j7aLq:bт|WB{1Z5utw vu G2TFm ̾eOMB)TQSjt9mUR20s3i#5Zk}l͕`F(jԾN^y.Ǚ~Wr.&fr.&kBEH}-_O-(.T ncW̎l>^%SCemjVGQ>Df!^I \1BJ ;-S}:]m0qh}J9!.9Bνϙ7FBgYohc4LvLmGV SRZw:52KŌ*[wt27b:(TĭnG2"["S1F]w݅. 7|3nVr U0C%3Bye/Њϔ<;#1? #i%LphzV LN!p` !{-ydoX6p\ tA:=ac  2 ]eUcJ> $V[ͦr`n'~$ΡFQr=ipH<. [[[ػw/>x:;sŗ%ފl38ce[o5os9笜s۬Û&_\`7*V0 g5AZKL$Lȃ\L6OH2i}jfBM&>:I XU>Ye%]Vɧ&5"OfuX!(?ވ >PQmbZ(]x* 旕trT6j_7KB\9"  Vc. iN$!tDL x09#Z)5ӱd5yN,*r=m:U;.9Q=Βis?b_EW|c׻Z> Wz.z%!1JȌeHf;BbދjicuN(ǥ'fD^aE2&5u8伥/]By6-eUi +*+(@q7l"κe0Wtq 8% _owq~?c?c)(Eϝq^g~g…^~ރe\bXe:ss;\`N'{$VSHLKl9ܳt]6CY ؄V%P%@&S)_#c9렲3mO Hq9˻n {#y~1? XfwZܼC ׂ1!#F8RZa; w`YI&$S?υ*&ʚ>i$Uiu@U03$4Wm0WaA֐=֍{fqf^r"^UʞN1r8zI4[ {R€;0ߑ- X)D7nner|VGk'¾ 7)KЖNzüSI7r_iwycgLma^'Luyq ѫN9 J 46͒jamדL,m&䲐*뺫8ͷ:HRqRq2YGEdH Ki^$jmH?I:$yiG|l^QDR k͸w:'1l~K<"ݹC"c T\5l.@M.]!MM \D my1\=Z`$ mxO_w뭷vmY<\.qTn ]ߕWrޯ}k+b||-wނi!~sCk#3G܁a3cf}/&dx#RǤA,)1f\GI Ӡbp8ɬ<1i$) Z R  ssfeN iBX&aS8 $Fb3%`t M\ZdrDGtaKM ӑ;{8B^ \1ZAI h>o T)Qñj3_H7(?Fk^Dۣ<֒߳֒RBB,**, 1ĈY߫L>CK,dRH"4iI3cf8bHI?Kq%MrrObj IU<:^̼ rA.RC'iE EfPrlodsޫD9F謖DŽJ^Z?B6OVE^]Q)ds7Q?˶?$E$,!^b 1a!0CDJ=g/Y/- 1 k ̜Ǭ+jy\wJ0Z U٘hzz<2Wg33Anٵ.0'D ,Dw 9pJk)QVXK\-F mS. x}Cqy#Hr?Lǡ6r >m.2Lp>ImRՠs;Vu-ߧ꺐XZD .>S~7awĆ+LϚ< xDzG:'J +QSQ$FHiK,ꠐ9E,?%IÌQ4y* m%#)]Bc (IYN DJޟ}Lj]u3 >gb+JH /^댠h8@o;vu;2fU mF\@>$˞#x('q,vI3@$qIRõͳydmiyXGá'UgSk/"uu B6&TƣquSO9ggg<^x!N\{>pUWo|#."\tEx߈ݻw/x`x_WU8묳pgկ~5G)Oy 8.r%/.K_R\q\㌍3gc !h4 FzL^T r82lbw!}YJ*ћb@'K)ܢHsduy1O]2ňR9 &H`?!ȫOYdAKӼ@ˏԿb>c-,؊MߩzI]M)~R $$^ӻ0l޴P%% T!5:4(e'k23Q=`T X9&l: \q^V=$MvQUG1wf-0Z{'#(Mz?BuPUw(7D#_q@\̮E ":Mk)?Y;$GN!Ѽ7O!A$'lfe$:7O٤E,<뚁XI^/ RnNe8>qv(-i46}sYEGԡO]yL`랮2hEJaainL%v-zAr6xi9:ߐ=P{xM@U-^IgGX!-XLTV!)Yy탺p%YEb'I>[A;]7c|K˄0yu?_x4r_*Jr-ؿ?.8pO}Syk9c߾}o{uDW_}(5\W9ZYz߽k>U՟މ;$]ѵw4PAjTW!`NDNH1bcmBfM;J 2wr!h%Az-8%xR5 N6-H^HMhɆӕn b=a Pk6@~db х&r{!쨇jdqΎa@$O70<: AyU.E[+({=[jr JDLFݤnq]BUR!{7)bV)E zRIc"潴]!%J: *+R|9Xu1cŜi+-k:3{B$f~{q"Qs9!FBJ T`^:tgb#c1$$E{3wL*W};կ.Gj>sY8E!Co;t^i,#H0 Ŭ5J^ÑYE!Rn!HflMEQ\FlaUa#֎kBs1"RoyɻL,Jlxp!m7P&HiK  TQy-#s Aj9a}7zײ,Dj-YO*JoB*L%l-0:X}]/ )L!=c>i_ڂcjQs&gKGO\`" )Pb A8aQCZb(dĒACl])1c txJ Ti!0ح~&գ 4DȾ: Id{敊a AǠ2G=z$0]}•JRjffl%zpVENHb$mwͲkR&?+!>D5+"[CXEZ4%i7I,LAJ I1^Q %J&AE,^+kHhchTj'!Dtsطa72BYޗ\}\LJj'U(1dcIMA~2}1x?礽1(Yѻ~D6EmuR`3XExB2l3!Sl*,RgRWuZB zjs[?yJ nϨjZZ eBcW/|K$۶^?fggZyC63~\SF*HOʠ'bgYewz1K*$sRk0 U28:EPkU5HAR q MvM.U<$BT, QT? X>p6`469- ,fHICX&`cgu/)DLCMcf;'ȰvovuPT>GFl(oJHZF z^<ǘ5ؐe>yr>.@0BQD YiT$>HE)0y0R9kD!D!ϡԕ 1+LQ#sj^w҇-s`L06lå9BXۮA-r\g%U-KtGinF7j=P(HK֊ADp,ReUn*Z]:ߠGNy04R;eEz;y/X1d[']E7([X&t$"f>/FƠDN٪ ێ{Nh4xp>3792bN1`߀wz::UnJ,f;xqdOAF][Z{ Kq iii^Ұ)L#=c4aX|粯įw:(tై~.+T#zѸlI-DMY3K;' $ E&l)`1l ':)QTQ5]1P3/&`EYL)cbt=芣VE0\X$iǐehl5Qc}Fw@>j)%\\M!)c%=O>-)j坴|]=z?Dǵ\w\gz,s7/mVG E/DGL9rˉmY3.M9P?i˔9ٗzX|ĘPpI({ԍI \tiKr~A$@LN@n1zӚ}aRIy~ ТB@@_Y0q牕UMVUF?gdҝ'$Jkjt=d¾Ǭdѿv: 1`߮UkXwc'2`:5"hͯl]_krJDw*Y0Dte1$F̐)psY;: Rrj=rĮm@)ꯜ4 Ar@I ^9 -s)EPQV/ULAqC w3}ϛI -;26om{=qnvl~Oo 4x03 ,jQZDH 3%I"hwe,!FBA;ig-4b9]~gFߒЄ9͑+b&:y5:s'!FjFOtx=i0t妦\G$ bH/tp?ҙepC%ll~$Nᜮee8\Jk%f\qI`}9܍hJ`5T?sQGan:Dg{&l^Y@Tݞ&5YAMjfUwtg*1C\6pd5\$fcs7d0+E#C|6oߖ^lv(pJ]G\2E=LfC/9Y4 ZTjiWr1ʺror>Ua8qt8%"F-RWN|AD͗ZڷloQZQV SyҒ;9Bm3zB꫱cD$:d*68?n)ɋKqVa%z%Ym:G9"[<ƒ'='E8qaFaT&WvY2֖˔tLcwW2de4jJ BA」 ,%b4&22\e- ؊lnDڏ ]]TD6:1 S8"l%y,:u9[]yb\t?),@ HO8r̔9GZ)$ S",ViM08 9ϔ\ ͒$&,X3WӅ$QƢe)A)&? 4L f '1I]+U^ F]V'c5I*3⦤!%]Jtŋb-jbJ HΗ5&։rXȣ4\ ̵ԝ)kjR8&eHf^+ǩ0(acbwSjbin e&f uCIDI ZS8 15I"zDiHJ`ATuly9WI$suc0PY-k#bTшWi ]Z\ȅ%#ܧ b9 :% $UIa@[NRBaR.ubH.6KΣzxRK"5&$F}#VCrJ!le0ƈeXY>bK ifff]IڟJ\.0}/aBSH;6'lpeiZP`L8R˾…(. *fI#,㺡Ä /NG(࿽o}QTsw#bcT)H9KJIҕtcV.FuNy `߫2*+4,2+VT/QU@ɜQ,)^ iyiNt 9!`4!g }&)E ~9`$$epH-I`ۉK! ]%W c앁T-"*)ԐWW(r-gKV\WŞ/*ȿgsĆ`Lj^5ٳIzSQX3rE!͉S if7UțOK]8Q}[)z8s[p=Olv:$-Km2j,sJ)^y@`MT>*PM68犂s h $FΣ l:%yc)9k*<::NR#hf@.ÒLuP.JQ_&'y^}dtah893zIL5&oRi#){.\$Cɴ'UPɔGt oy]HT+IH< MIs`9ԷhṄ͞l͛9"6k`pIT=eŠcudk y]ȱD;_ 0Hl" )UfAeyF-ª$M yU-l.Q~fUvӍnAXib\j./Pl@㑫ڄdV2ҧ>#a 97r:)W= #:}cZg6b!$yr,ʲ][*'Yzi9/&HȦD XţSc%Dn[JìnwDHʉ`_*u7$.&&M !E9-=`I'INFu&'uPX!wDc+,1w]sH~Q+gHEZ1vRԑ:uAqTy)S'+Sz%R).Dsu [rRKŖtn&/?WQa67%R^̒`UNItбA1!4lR%r]g Je&:/Spn.9zSD !vL8"c'YE*2hFRH{d@jA€Mf/TqٷN ':յ&|e92$ψ|>ԤZl5Hڡ+.RŮq\%bt "o.SĬ(1*Jߒ$Z" :I"I9[=rKf{S8㞐%iKI,{\سWb'T_.!;%3kB2LARƒӚZX.LiJrmOL}XLe+UQ2#Rj;euUH$E\,g}H1J]ˀy`I=B@ iiA``v٬ƌ%8ɉC͂QH.E8U ޕ1P%t[++q8Y"ck}ﱫSȁ6yV)80v-wiFI;K} RaXx)mww)՜dqL`A-I Kn4`k&u<lM)s; 5/AN3I AVщZy3J8 '8Ah'.H}[.%P?dg55_F;5Y;at=͔Zk^rs&٥NrA'K#`:hC5cUիAQ:5g+}USaun$jKqJY0HC&Bw׭_/<f9Jڌ(Qq̅ 齃KZd$aZ2<Cb Ƞ<ۘsdtLxPͬP|(|$q=|,DԒc[RB/Կ-Z#L@4&=}IA:cR@Jc4r5$fhvV*NITql !$_C*.i㱡~#KQ4=-B 5^$"Z®N f\V9R0u2NbԩJ\ )$/ %5)҉w]!~pϰBWVhfcަ$)m.R#2ҫQJ%8ʴ1,6vA,3H\J^q6k'q4C=&#e`qWIE@$BѬnqFkR:D(E5A-~9hH&0/ .&y Y&Ihb%!ح5]T>W%,B+B&p*;Ё#tb1n] F5+O kT3lZᛅq1j Ȱks-51|Q"C̼_ ofw$ˉU6O)vvɞ!:zyv@j[ξ81D}ZQƬEp$  p°{`RzL"ȝ9\7CVүA5*n]Lp"GgAJuqh$ =uR f+b 3c+m/ɃG%DAV`\FUqCKH=8HgR7b\H9m 3RD|u&(QtHXKu`jhQļp+@q#bppN=\P 9ˑ( P #!KQR AKk[*DQcHI"(آ!9) nl¬I!sO"Ct{JYɳIhd['k^3 K o]%\FU>-PNlϗDVXA{is:r`/,-9!EKrr^PD!&l $)f\Qk!2QJ{֡=fΡzהC$9EL '2뵪%ӵ1H`ಒRnM#fBX_i` Bf*":6wjQR@QۍRW~\zv0aQ`ef$,WoJsdalb[ay)sT8!(,~A 1'8/ kw{1@Ԑq^X9(N%̢*nj;1o']N9q֛O ).Hc[G Nȡwl^\c. [%}|u3zjJsG$4sj v`"JnJЧNE3 onݷWXu%B jΒƜbbf A!WyX6"t p8ZIR{ KZ"eR\d$~w)0A&3Ql"m&&؄mʧd1 $W(MQ(2Ȧ!ȩ` V?E)O4: 2'8!oTV٤IcfɋWpgzp jI[ɡas]BH`r]N1,җ[<z?aK [aKv:kS=S`D q@`Y%y)%o4H~&f<8)CD S #TQQߙBQ."mTA`R~ )&3hsV̿#N+"^m( :QI\/~V&8MҘl^j2`}=4΋J-[)FRÌzf\QIŽ$.Cğ+&IŨ#y]PJv fB{A"6(JjvįHT]cc%!.0"}릀*&dI2I9)3cSIEV7BD )JwDcaX&"CZ`k=auHB." Сwİ2~,&<- K \Q45A:&B}@%O"WiYa*)ɭɞrWp3eRҷ`V !Sfh&~SSA]ܘ%>NXI"z"+.bGJYD'ךd ,=[>R;z=9ښ3?ލuUF[ !e_s1 cDq1-〔HQNY&:W7+X8e\J~VPgd>;b &,l%@p4=of=mTP ݧsV@+ RșॳZcVM s[AYX|RA]LQ.(`ߐ "'bժ0_w#ALiG9BIwN&%>Sn&&uJE)|rCڼWlH1@ŷyt-AD1 ;tTa#p\V:V@\$pԬ_1(F嶳H`+wVcǤT}({Evd ~&| !y+i0, %,z4,ՊI9e6fUYȁPg<(tݞ5 U) gf6Cuߘ_=3vy [ALϯ#w0;xG}X b/wG9#BNVUB1KkITg%cVWRF64[۩,gqe 'AR3E;M] 8<\LP$ڀ'Ϫ%Y8df,"Ĥvyk77eSmk}<#.r 9nS@A9pD.%0X+编}x.?ibMb`mUHȨMsRҨ7UUP#:LM< ꑯaCOu٩?84(f"v6 & /'UJNۀ(# ΫpG NkDH.k)5q'Gpeue~) <8^cy(e@\"2Gd`3DLNd rK& (ݼu3Dіt@@L1%t]DNA$]0ӢF@ؒ32 y݀:ǣ@#ЉUZ.I/njru\!c#yV9Q 5T4jE˟lr.C!Ft”c A}3-eԉ+-x>+.^'.VUBJ2 J]Yς$f~sm.%}WluHbP> \Xgdi#llx*TRr!#Pb, wS.ċEX @RBҶkFe6Xp4]pv|& QUTKbLۮiҞez.>IHG]\gQN]=Yk5tF \vnAVn阴 34~7 O5Ae/FOrPa{qj= TNZ@bKbw1!^+ HU1 [BhbSũV,np3vw,ɢD"Dݹ<fDrO=to* j/8UѱugR4ۆwܟϰ>!,ՆR j-(Uj/+Zk6gpG&(oM !tF IiRߎ?͸ z uǡ;e(,2c@#7=*Mѳrf𔲎W@iԗzag/o;@IӐlcaQDXXRUP$QKcV{ h\X*5h'$͠φA9AтՂNkۈg&-WVa>Hc`E EU@elQ*e0st 3-s= .ztpJzn\>[ G8Rwy'^}T$łH7v ?Q((RPb"ɑ8F74z"ZMIlrg8;g;`?+{ҿ<$`uÀ푝@Ҳdv p@]F1|!D9/!(@vڡ!IIo6ЖxOfm |ؒ`.X{h k Y$ Ĺ#ٮ)̖G#pxr|{o:r6Rp^)zc>Qk}p!iLȓW"2XmC w?꼍G>>4,jkUTfɂD~Xw/q"ʄta)@+Z-RXUDS/ 2*zX"omF+lж˔Yc[DαO`8\,p4{^!RUޝ7Veyi%BS`5u߈ahsZ%TYbe\7sǵ~Wb} ToTm;⺚[:mʣμi'zAf[`^@"W8ПgюBcz}b"|9ǝ()}RN"$ܸ@?m!)s32?0ElDe >N ̓zF󠜜9 [ `킄:<*cZ: Y5wM #\ι  -a/Ux.(iRj|@}yĂC2.79"o7+2c+a>g@S}=a(zR 5:iG BtO+qAFw?'E$=7$s1gz8Gɋv>&1OssM!$=|`ӋNѼ#'|3Y`Қ1LԌGWP6L2)jp?fp惾`Sdza/T[b9O,Fp@0W1@@M6U,*,Qaq{w *@3@TC*|9 0[G4~%LZ2uq(y88c J$ Yv%q:GCwCQ@%lV@'\om?eQ3cO-a3J/MA$iN]c\u0Ə[<ɶ>q鳰M,)4X5 v"q3ayw)}]1Y_}}Lqw] n zI}) D ^^_ ְNn * jYv[yy^0 _Bk{in ZDelPKƬEcV M 8~-' RRP;ұ} ⰦRHD EPw cwP]av﹀+ЍkF.4'*ܱ"8{XdށEFCB?9Ա-a&5(df QiaE|.RUCwq̓i*RO{Gv]8T{/Knwzv \:ϪVPNN턦 M+96جc0(RhEӂV C4YnstifK&wDN5h?p&eN'&, ~808w jw^v:imaWm Ze%zE+ *QEs;T* YZ)N?gR ǬT= eL5<44e^3 zH*Ԝc򐒊 \Vhcϐ,;"  !CEJ56j$ uZ0Ly%@/O|Widn΢(sD^դ`B6붢6R哊8uR#4}wh،] 9W ^gJ@+4 *Lb/z a]1ȻEv0}?ujg!;j% jt̀$q#r=txP0i`wFFwKLT{T6(huB :Mu8rh)i``ލ;ܩlEq P*xnZB*Qҡ>f:N5_W BSZ^jt`AYض N1ǃ-KMj<3wQO:JFAHw1LMT{Dqsl{2'ٯa4oE2#CB#"C1fW u S\w#(ͪ }tlq"?-q=I?gmReu͘a9 ٺYeX%J:ecb&v20ijç94[>SX)7KQ =$85^ף#K-߅E1:򡑰ߧwv'~3'K˗ԧ>~{|ݣiey'vIq.'H_AJ=V XDռ %/X">JNL({\Vw匛>pt0v`KHPTkٯո< ;oXma-N#%T9O0lPwzǎ EY 'G+TxCP sFsq'>GF4@{Njf|K&%J&(G{[߼ ~z">%;+7n!P-p ) F7>Kwv 'Rš ,m8UMGmLЯ#؍ߛ;Q/#dmYIB*^(&iQn΄ A: rGW9g0Q4% q0@ &% ªK RAk.#c9R ^=)x^_A@6t}̇/GhC{G`Zj 2D橅dQHJ>5ҫ ].v/E w>V3f@g}1tw9YMD<揳B-*UB9j@ 鎀j4Rxn1x$qKÈ$ؕk* x f͈4gYd#! c`iEԳ8=1Rh0v~<o=a+ֱ.V]`Q7Y9@ c܆z BV*s}@6&!xF =&pgߴa裲b=;X+f vrDC\G_9\+VI=kN"j/ _4V.tZXiFk7CN^ DOJDamW̍(. =hONf28.0!ߴfGIbZU&7(IKE9b:֊s- Dv\/'ɑ<2bC.Xr[Vemu 3u귺 9*J5pܵw{;NJ؅^E[r% vp@ӊD{E:iR%~LAE5mw'cZ:Р`1+p X[+붰2X%>V<91wu}7sQq- hL:,YX5$# $mаJ1[M%D=+3gaV ٷ<;,=p 0JMeFùVvSfձW+5E5溰e dzD55 iR4x=X9>&"gauX""$12![ /ւLbqy/+@:<b-u06XSXIyChf&Df@oYE6 ^zHN 0<*NKŹb5d@Kf1bSL$l@o:6Z+",+ke@^ Kmk)AQjJWhsx~r>wrV40k)(?W;.?3I<_ˡ@P|ܻ`J1"9vnVYN`u;63\zx`""83`pWhB۞"5W: DE}hnwϭ(sVc%9K8Ig䋤ԳXdbc+tȻk=o&>T!BP2'OD1&:,3\^-h'Ο}{FT n @m 6+DdJ7B*tu Yw#hA`B ' 7̠,{P,OV>,Ľie8,K#p˼.d7T,@cq.XϘQ2"키h!@j\aJ]vZ23;EMr: @8( -4Ć¢rPLcCU\h7[J+QB*=;dFsqb7X~n^y߻?Ho~9:+")-`3xg 聚Q,|c7?[tƬNjXyE>~&-Q>NTqq~j-3`e5QkƸt"YV#pz~&g8^mf肄"Xl:F_V|܏x}lCjKU4+wX2{ZCA61dhGVuқV C5tXkKE  N`쩯)đi`A"Ȋ>) !RҐ"{SF0fpYn2_Z5mv2Qd3pJ~m0!Fx3KM'? `̪3*{МUz ]^'6@ Re^;Iut^G!(De tL7w"E6[R=Bݥ_޺٩Ɔ@ ͩ*Vl*0;BXݐF%PHh- Y`UFS+Si@dҿq<@ákVWС glPm%%r>2J;a4~S?yTc0*՞lyK& gwgqp*B E7@!z II*+{Ǵls%ZT*7Vdz.,,%zhĸԠ4d+jvp _&h7Ǖ 0p1h=DX(bW9>t0PXNAj捽aD9)BM6ę>%%KR-X?M*Ќ_SuG=_N\󶾡~Na m Jxt QTr&D;u:l QjIsy}9vVvМ"bnNEƩuLXahDp9Ѭ=(o,h f!hs(٨C3cֱ7ܘLF'0k,}e=|7icKsyF+ U(4Gd0?jd59I96Q)녺B[U"r"5, AG6놭;|af5RKQjSEia@;#zS;Vf ;`Åׇ(+q'coeݤ(1 ЖsK/ F:n8Ӱ"I6\1/_ħ>Mo)G;>Ӹ?cBfQHmnqUu +4z~`Ȇk/"Kc010tDrc,(0v"ncҳ,#yMA{҈6'2"-jB#3sCRP .i1~ k e鄴PrFIdRiAk؈!3荎/d qL2ytf eB|m(n;`ґrMʆ= Ұ}hlSWHTQ(rT_e @XPcH ,j)3hY0i,~>E @PDT A* Ο{ҘSQ=he `ˀu倏@ܧ`;-4GueZb!؇P'z xcl}inA-b)@qJQc Q}aYݖ,O܃xzd]n ;[8܁ 4p^W- e99f%g[@ [eqx" 2qp9&zM$㩀(GnQtxq_F?b3-@iI CpH%ms?1XXM;"*ag>^q*'9*Ԃz4pqoBR*TXNQim̭FZ(RO(7yp"p@ 0V@wA.PWxFcok9s2ֹ"{`B$,3 g-T(RBԡRZ $E%Y&bj1=Z-nzA413u}JNJECIc i_Ulv(V/c`u8!xxūu`^t0,DA<.p m +K]+8BB>:J֭4 (å*޽?a)1ͧi[/l=; {!¤BmcaV]%T#0)ǔfDBZ jSXؑaC](OzMهa6;tMs&%n”14Ƃ]-fKF .lV`YFD #~9{ oXNJ.X*K)N_DM IFi ~/1Lm`/YZqEܽeYt5geN_Qۂݮ%twH8n4x,p|^lb$4_^uD+ vm_ȝ ).1C )^i$ XPZyaqGԉam3#%17F2iH1}3x<҂b:^l#PdM\;BjY!$= hۿ1)h:9; z:ȱ+B_@V,,H2Vܷ,H0$gu:ll>{c$o>GWf{QA U%X"׀gztm]>ZT1|V抟 -eDE ]~)ʶrzޫFp@X`JcԴx,>cv\%(2ikfg)46 ti4Ɨ2u|J/u'h}>7\y|I4YEgo"eqmU`c VB-q.ш^IؠO=>DŇUZ>^$LH _ +ʰ`/ьTHg(HŲݒB!,T$7Z}F+iIy } ;"=gF{yT C`JVa",^RQ*̘c 2!'J VdsM { #A XE8ƈf|*e;2RFh5AW?yK|Xd}gc *XLDi% ͈ꉅn$%Y ұ_,XnmN+h|E-Xsz#XdDXf âBLb) ;RϢi3MzM*{荕\<3LpΔG?t(@)݆:I%F (n(RfQ5T03nY!.J`E $|Jƪr1DՂ7C$Jvo<l~f8gIc)?3_ǎ.؆wډEDŽTiQm`ecLppQ{7s[8&q< ]g?nxny$54[@a*49Zsn@t`^}x4t=&+q3M| ?Wq X&e92Rkh-Tj=st F@$D;%!LwoC JՓ:ik6%FUN|i^ھ79 -<_T}I~$W!In$7::LT4WO|-t|};ɟI۾_įb>滾_y޷|˷翯+{o-<>>߂W ~/e1_G~o~{[_??obC/\Jj)"0?:x\gvr0A-m QԹq2 в:|{Ŭ+\MՉM Wҹ8Ae.ܝ36Ҳ¯PwHR\pXo@ %JkAz Ȝ (b5(TU f. qjSÔazlM!6|V,x5n|HT 7F+>.ء;<^y|ynS nO + ]^g̬ւFjWxYu:ԭ% j$  S4`胅JnDʤ`IBDQ;PKRA)k 6zeOqf x 9jAv0p:reUmkDAn+zw|pfq9|AֱuV^ڱdG "1}=̜_+ǩN-OtTfd=u'8w}Z:Dѱm8ʥ/:HXa4֝qٗ w2 !1eŻa\PXPHDfuDK@7(-R(3LP4m g)MݑBĚܢo )͵ ŀ & ;Qe3h7,Y=|H`$&I{!Mw1x8_3 ~G7D?7~?y _+?o[[?7W;/g<{~ulXNJ] qE vk![s?OE=PlA<+wEc' `b0f@8!5 ͠}J Ģ&D8(btuuh<":mZ J%&}:-AjA@N;7 Rm_PG2m+:7E`5`#GY{N̛cEfS7|Ó@=Ji4n vh.9Aܐ3T\mʴn" Elۆooo&|73~~ ߁/}u.~~zz~%+_tiL踌GBV6KY" ua[&} insp!=4.H ^e#|"FɣJ1Vul=]Si tf"lk~}Mke W褩}lnlS>/2C_ĊvH}|6h'>;w0` l;nmlqFjЌpYL`(\e/ \ɫD=FS/qs3!Pb씪8mf7~·+E<\pGwZTn%pns/~V- s?5NGy92% N/ËϙzVa+&EM`$bZ ,܇;)t#WJ4-ATg+-΢2e 6uv#%y\;DqMmBk+Ql2iӌ! l_YcL^eo9o$wV,4 Ҙ&oY4Y2 qgnNQ +<4ҞR(36V'ۊu;{z|7w~wwߍ/| )?goEN'|K_²,'>qzg/} /}i3|ܟ_n/a UK2a\mū5 zF N,!#@CCC1A5Vf!hH+4n.P2(Qﹺ;3S ZV 7hr X__J`Z!r@N:աllp8APXfO7! |Cla*$+ig>zT9qY-l]4ڂ <2Cz iu*ljqN gKGV (ܠ(yt55J ," 3ͣA>S] gzTmG[YN*wÀ [22 =ñ R/:.͢!̠#K(*8׊l3XJZ1py;]$g}DbAQ`j۩33`WVThk4\ui*"ucu*΍tr@fˆ&d,(+ DHvD_-g88 LdKMv D=cX^Y %9ᔇ 5aCO7L UMHs^D+Cb6>}9h\~[5A+"Y-pHw(acTu?Go?I77W_/| wU_X'||yyܽW\muDE0;gT^aZp P(`pngtR,TNZ&vPuEQַB^"5{ND|_eq+WyssXhy k@93|EBW ŢZ(aHaҪ%hRiX]Bt+l@˨Ɗt{ o,X;E֝0c|@\渱4ƚ(vZ}w)x6e  iOE[n'Yré(lBokT+-((XBzE0W[1`[HﭤU W0҂V t[{6e`*XHTiB="iƿJSRcKVf!5 LTeDbk5`^XQg&]-:dd1Ԇ)eP˱dކ[0>Sb]$: A"+U3LEؤq/I’ Zª'<7^ERmQp?WÖKS/:64CIMaZB*:ܑ NJ@=tk1˪A)g|܏C?CgT>/| ?_ s?soٟk<>Ͼ}NNӇ~z}[1v;?c{f^G+_1y);}6{\ʠ$WuV;$4N |M EϐT b!>Bڂ,gھY4>^tt"HlDAu*v\ b+N6j x'BY| 佴"ox{Gw3> .k@H#wTld>i+ʊK {ꆗחX IKخ(Sc`6ܵn :$ i=D?KR0<\I;Dw B q `WKoTh]}xX$S4 jM:0b3 N c8Ў2a-zOBmk[ O&%+3+u +%%枛|6 l6c& ?smrY`#}n# gŸXswŢSM<|obƈVOQvl,pN$m }!be_2>vg#FAgU};{9W3 ZMhcNmffv8 h18ףm`^_Ds= IV UL65##ֆ'jzj}47w΢)yo=YufضbtP_kD 3v%ڗ")]+R#nm |t/qOۛ]ڐ4yOQ2<@>)>w-,:׍aصs̨dqH'\U 7iyJHa <;,9 4ʒLD/w҃Uvޢϐ<9>q9>WUdM$2H"G`S]bD؟~t6'=Q|xz&<zYL.&, TvRВ0K  ~xd;BD-{KM{,, ?;Get,m9ùkk< wXgcR릔4)eُECJDL<؊|/?% ցY'uWS^Ÿw.|sO O)O4~'~/^wO~ߋ__N _h/|&~qWc_qLSg'ϟDՊmlѴ>ivƢ J|o Ơi];5f *TKclzeEѻR 8lӯ:g)m' ==cVm&p|^846m-vjQԆkq^cǴs,R}YN߻00N:7R&:q"ha#Md-.k2fmsv>ikqhA+6!Dz'=CKAlBn i 8h}`)9inATB ͣ J)x.ZѴutZVε*-3cl9 |jX`UΟǍ]dUnON)j\ AØG1$ "چ!tԠBs z) mh7V"0ТXϠo≯-Z?aRIF0_$e|nl A;f |.nF$+ xM5=K ٬nQ(VDS8gM+c Gn l_raNu@7!PD8)hJme_cp-}[e"u߃]ufE}jy&kӐF;Ls}q!?{,Tm;fc;맨ʠOK0P=Π_`tAMm26RMϠԼ7|7~|w};~7_W}7&?~>rO?1>>?d__6_?^%?;O?%_|>_1'7>ǧ4>g,9i=&824g{ ^`- RIeYzI#8T"uqޑsckNv|i[ZpՠyQ#p3m:+S VMiH n^ԣAէHtHԌa1?O/=*@ <d }Q4ɿ P9}Vy29HkM XJoRWɮ>EhH# TXG1?-Mj$)N2b,vF@4^qOlGds`DޣI9{쉉ŀUN ݣ}\GZv.#CA5,DYNw/ؾVE Tg4YdX Cuo9x58onsFܬ=<@.wܠdx8n Rc / DJdGI&@,g˷͓'Жk x|g^+.A?0T4mohk'Q5`񹜰TNzB Xa6pwm_v-Zs6HFW YNó]9FVwAS' [{,!o1KԶC+ (68ڴ=`=utU,0tߐ>UٶɥEtAuE ԯ:)twFw6V:t< "][5{4RGlv$O7=/3ࡅ&4h*Hiv}Y YK>m%bGպ_0HI炪L*_7jgTFHIYLGҐvm 9Zv!4{עAiI68S+AnðY̖h(A,`J -sƠ{+S5h}[rߓ)WH0g"{{{o9wpdjhfAM:u"Lsm8иNS­`cD uէ 8AC~`ohEO 2Lu vp^VNUR(/yܞegfY#;VnWwe2Ix†K@nh]Y{96͋n{]D B@7ʊ H²Uti<bNKՈq7&t(Eldp|Qo:w;o u~Bڊ5:\;|2Zp*'t x)V7Yu\Co~'čZZ0+ ѣtC x9N6t1 Su+W$VIDATJkU"GgoC KVH6h/>Q,}Rh!ppz i3$JU~џnn Z=gţM7S)UP ]&>F7"Vt_{'w8UOW;mlnt&'k,4[$62 NzX}=;ĥd46  2#գJzH ئGp}0ڸ'lJ7ځKEkU9W2<7,'HBYuLlcVl}xcگ{wQ`iCF1r}G25%ٿOtgwRSÝZ ֶ+p P P9li`@W=pMz _@k l H76e4/_~oozK=>JRFYލU<ԞX#1-Z! i1k::d7mM '9'e@1: 2mX^'brYڭ$l!U}6QY9jك,a ؕ!:)LdA*P &"kc+`am!`>}nd*L& #|DÃ~BE?D0n{78%6޷ @ ! DFi;' d"| Џ:V#b1,usEw x) īcV˹1#L} ("hF#3hwhƪaEIjlM!Tt[[9Xly`i doeB2a #;!&Ȱv[f`kۦ҇Nۑ˵H)=hG6+5*ja2㚀}ZPU9YHm@Ix\B_"KQɆp@`D& J=̴{T8y[NPѤ{3`L" '3d][wZǍ 3>ttp*1zdjʅKU0jt'Hm58.a+K-C?_; <[#XNJn+ʄH]b3VBw'J -0P@h :*Hsmc"n5|QU Yb}a+\;w# w ~"Ej9@+M8~/F)Z(_#[ٙ0 ;&|Uzi-Z256Xb^1͜aB)aP/`yn̎=>c4)#: ׸I|?c )ƅ6V7Օ]U~NzpXkk:$| PEua!G W={g>٘mL$^[ J$+DLGDPf0COo#*X1:{ iޫ*hMCǿsG=p>~놫fNZ0.M/=Fsmp\ѷ&7ov(IDo,ًQaH_a 477;8 29PJDxdD+C+.Rb;WU#1X~>,  /^5:!cj;(8 :6\Dž-@CoMf39,g¹:iD K/=+HM6` R޶žX"v'<':~ 5D m;HD XiTD9fIseYq?RH 5{Ii1$[fxXpnHa&6ishZHC) $5D-@ɑE ,ym\(V{jMȺ4aul6`WK]P-*6O }V-Z':Zv 2t9ؤq.tE2.hE=^nT ;~H T34A܍04M0̩xžOΤ`2)X:w6+8t11lR./ S0nmlz*z&37g+:`TZhAa}н9069M4\C `Ge3ȉLp:1Enf֑@ˊZha#Av&*ʠgXyl *;*Zqc>l76koK-hUPKTKdyT:0Bh=sK! ̄,;$Rhy!"<9RoA;b*Lgc; <={S+r i1ĵa {,Sם6VP9-kP W0\hŵ_q|e}?E3HLT]lvY2KXH_J?Jxy}%^jzwW``gQ8bpK>Zp~?t@ԠLv"%؊(bT˗g?~{|Y?ҥNhW/L nxhRiL\e9*F E.*rUNh}\-7R* D:Q蔥h:r<,JtPֆEerAy r@}p-KC֠k{eèh=BO;췝}3E\˄g` *gjfRIl3g"_*@\wuGPA3޻`u7Mtz3w ,Hm]?n[ #;;/ieF :6c / iv8%̝gc( <Jф7N`8;2[H<rUTS*gRiǮ 䎯Lz}Kpu=쏤9g2\K]ٜuՆ5vP ۆ<>;4hNjt\!0zÖ;ϧqpKi1BM38q_%pV%P# RP2H1:*.p_n,wyܣ0h1X",-` Dz]p^÷[n^2xV/Z?U|#(31W)/ׂ秨TijHf.Cۿij܏'!}NPG4FB: ܢ9e&=^4`eZТN[^sh+ws-ily ;@[j*ÙTu'{k$U8s\sYySyHERèk'1M- qhq1Y^_ skQ1RWrNw)Bo$5Z5`ΖhBmō {|δ!'w{Xٰށ{-{ @uszUD>4>NQ Kۄcx`i=GkuV;Xd$"zfi$PHHTxjh҆/Rpn0L`Uj^K|~J,|EaՉbwͦfP>7ΠqPHJ0kHk_ yFcbp|;:m58n}lS ?M8 bCNxla sO-; uhܗ38:dtH㏇`W-MV)|ظ3) vo@ݳK6HYUˉjY0`xM&^r^U1%Vϖ{VfIl,:IwĂ 1T$Tp3:}ݏ*khΞ %;JDM->u>wCvzZP`'ggfP;XiA ^OкRVmۆud}`>p^N-iRD@s=7(lQ-A3֤8AD4 9?bHJdq^mB4U)ŀ [WEvh@mIښaxRaXN wWׁ6pŹܵSSk)R5ר6Z\\eRy;.Xs]-av#mlEɱ1o@~B¾B zUD7 4:y4.v zۀ#ݰbNHKZfa[ .c)-)Z>^o6[Ȇk-f%o΃i{J5"1 P,4 ]?[ G8R/@` 3PYq9C m]6YX,"lD51lmlmc7ź1 b9j1=r<ص~?ۼ`gm5S=M4>lnNlaA;407^ HjChY%))>U'w8ۂ͊ǧH Beky.,17M='mH=3q4dq 0x6Q "{"mb hZaѽQwm5g1~Yce#UY`޴L$Bxܨ}/ұ @8sK5F 16j7K* ؂*O*XVQ|n4 ®?uxvj8T@S()3x`=%5V49Ȟ6[DIW w|nc(Y}"3ouK41<5׉KracPV9(vw0x6i?qY dmwTd货ߗ|<8yt{tIq߈#@pa>!=P &,,p`RXHbxc]äE@l@ \d;4A)$7u oI#K?D8a{hsXcpRM+k}qE aU qs3J?N?>1Հ1bS.Oj1rLb&&,D}%w(,@0Wc\ TWRvϳQoiԬb?[p_AdZ1S @r=/~ Epي07Orsh `ϝDH=@ |~ QI75fGbl>.T";yۼOZ`+/hRфނUkbFEb+>qMA٭>+dFW{vPAzn< (%#,ɀ5uE-RH#8a0N3mb#^9 ~'RPA83se;{@LтNݥpOo*tZQIlt¦d0Mϳ:(mnSA<Lj.5Bڎ`dDYIqZL; Ve@0n:^_KxAhRYq@ (j*f -_W$@\I'-tbsv1ڌz*vC":n p0^p5L)9vsa;TA zP9c߳жhFFXyj`-"@5vCXlݯlビ0vD9Y!&L\#jgvK- )̬!Am&pq#v@U(W0[f2XL^c6*aYlUMSXg>^5U*RٱDb{Xb@, eAո>RdfiIˤ89X`"简Dcu:dV؈C>Ь.~}pӭ bx Z)h:FktMkY&ccA;'HviӞCkۍ c$Ÿ;f!U:".qQڭ6g3F;)q~nJESSKt43ϱ|DS?{ Iͅjd?\{b"s.e :,ycV;,`+=,ҧK)MYؓ,c7%h:-"@-Z`>{Xμi7_&WLwɄc-008D>trRcmx~QA{BX1nիW7~-hcD FTge%XfTé3<\qP^SHl\ [QޱiP*<)J qqVssZ"[7x(\u'w#rœ-B@knA)2]jHС VJ lbP3-tmsǦniQ*HN21xonsq nc *+AS/?07M2"dhXX07у^ Y>jR :@(aߨe eR g{Ͼlz0g/糞6 {"~<}كB cO_ @* !ȥ&qm@6lpϼ=Z9tBRRM6c`p0^B1AVM;+:C6F 3GC?>{f'Z# gyӴk\wR0XAh3q9+1i&=ͮ)DsK ?S S=kp p 0E 4,ŎO}pUlꁯBD\Y"ww~kBCB%9/xڞa`1OeZ) /|]!RbZݔ +/A O rYƠ?޽Ԧ-NA_io/OF*6`$򖕩DB 8\ 4TQL}.+FDqmhQڔS]˭ ,BiF94lW|{  .oP`&ؼj9u!JR*DٍB1f,='}Ld S+vsRX9mS,L6g>V/]8ٴ 5-v:3%4oI|x le.^"̄sbA=8LS͢4}9 6D]vat|?j4R0vDDu`ŦoJ@M͞s@ RBV Ki8["cvc's@&$rl (Ot1)weg53(؄UQK07m\^@AWCCF%=KJ6vx DUuOJnqkXy5~cIMZ=ʢ>ͥ%lHuuݑB; eY wIc#c5XKQ^}:|܎G8/?>.rL ;K)w.eel5]3T KZ-,P"2LYsdXcv tsD5u!Ͽ6`}| BB=(B}hMv j4f>8+pnD@!.l0NUnd*ғ]Pt'yGP-<0XTv$p"\}{o{=f>ytOs>#@9 Q3HQiflύ<}Dn$5Îռftwvzi<=2Xj ip9餹U ݍNsT`nVl ,K,yQB дD?_&'5̈T웜CHKثrveЖC)M{CپiKq/24; 4">Q(gZWz'闿'.<J{ګu))61.sQ8bdž֨Ӛ@ YgNA0]QjfwC &:[=Bigh)?S}GWRNzz.]fBa[ϥ7ZD[ 4>}DBJ긏.T2PA=L2-zậXRRkȬ7+ rM4#S=aH%l˵5~_<,7 ]itx&~2_;"6A{AU^J\6x}QG1ۀ!숳%}~yFs rE'cqjԲ23*[:w\Z]UE EG_/\;uX'k =6,s~ X6蝖#:i?A PZ>HW1Tռ{|(Zޜdƛ vC7"<}=7E➰"Wac'=,A~/pp~pnIm&ߕBtd xBӆ 63- |-r`"@8 ;rH SqIW]!CpG #p} [,G) ~WQ$U0yfց!we/y%K8Xٴ`~8oY} \ݕ16p5V>lDjȟD6sS}-> E[aEEU_8~ػ /W|=B_Bw"j&aKGcD1*^ l1A D1zdcٷxcٳc+qC덴KQDPBLd"륁Yؒ(T`Y޸ "&N9.CpßnO6M;$n3Z<7e'0>s>;/ Jip 6p}ðծ:?+ YF(jBcۨ#c.(ݭwYt\e#qJgY9:&(2S=޳w8Q!A7 PJam֤LW/ڶDr{c5^Ru/H-0MB}:~./~ۃz{aQ& "kNPg rfJȱE \7<k ²Dd#L`aA5;%*랦 u1|xW])\"t/R~{")7-4s{E=DțEQU"Q:x|q z"P(¿`cNH/Zv=< 8{%o)p$~;YftD(i܂lgj}gYdk{.F$+JTh HqcMe1rAzfe)(|{,Q;dcؠڂҢL Sa @'5RaR .ۆ%6N6HB[.< :uE7Oe!7,R#z,ZQ#WUcHl"yO,4i(ͺdcxODm1w"F Hv-n@Ox > Iu>!'P>=-4P>օ{ZB}$F3':)7UIf 7i"Q@hM9 w Ɂ4IFb0z),Z=NaG2l`slc7T0l쎭ISJw8Aa~BKZ>LrĐp(&Ca>2] #G'e >QygQԩ/nkD+'j"0|xͰp-kR86.cEՂSMO"V*ʀ0*+2#VfZ (90 ?%ֶ- E[D}ؙ̹/~`=+x!A(\*(aaa !* PABPqJ(m!c\|'=!#?;gs#^E1;4p=N\9>zhZ.o4*)_8.[cP7Vzav\/[OW׍@=CiZYJWYsWZ;aIX[T/^'sJ\B akf׾rZ_ú;"5!.W[,FLtH}ЈQ]r늪}ZPtD BZ_P}mwHUVhNsiLkA1CU6Kdс˶®hba0RTקEy4}ÃRq.8/ip4Us19rxkx{Kt%#zuE+ ?g @ؽDxx@D2P; ޜf(!KPFi+>mPgy*@Lc#YzKk*0.GKV!L!@r[Tg K9M@{-,ĪotME`H!+̓.\NsҮ\;9n¸HDjE*"lwD$i pxAcX@Dފn=1"x|}8åoDVF O938ɣϚXla3˖X@b""mG\=PaQ4ʄIc0_~u QHF۵TѺS>Dc>)S-UQK]4N@>nW}*x _k [" IƳ:C'~|,J? kǫXȞ*NTKSUчrpeXDsFu%3gVIo̙c_ۃDn"ߍ`1r\+)B$"}#&h.҃Q !zܰKM7tg@V Ecwh(kxnxv>%}Zpn@k4}ԂFVUe(ϕ*U*hDw6DrVҗD<&u^B1w(QH9Y8]=4 !T^Y- (OpYz x")&q`1#V4߸FCl_e<{4"3ImFVfp^9 , @U[xj6e2i~<<9Nۚ=n`Ppjs?}WOf mx ̠/Hcثr3,@UQc\Z*6Yv<;yWR o06_q yP57/ |t 0UJ܌HQJD,|'Qtx7% iX)8&1GF{4>ۻ#Z;h7 =}Qf7)DT48lGB Lm" XL5tkaL8|\Oeiǀɦ =@JU llXTfv;JٷhE) "wrԊ'k@ McȀ:94K=V,e)Da6+w(6iRk8Sswѱ6bJ6<"ѽS[Fna EY*,gMO,ZFT{(}T]g8;n#gΠDE I0Ń[$9e? G>Gg]8iWD1}!S)SJeU#o;"y0 a`-{d S~lc+ڙ$}!kj];nAJZFV9Dy3_x91כT.T&Rx j0s}J$2 a>(JUqjK)h*a>~"@;g9p}"`c`e;La‘V/a"<[%,AX1` ?5Z]",`]`22\Jvɠӥ ڸBpy L1 ^x֞mEi;❈PcTZ$)l @1ESs-2.Iv`/tc"0 ,Y0Q Zw{f)Dq/^g˷+>ִ61,|^9QpT7sf,-o UWN^EdaGib{a@ul,aD7zTBB$Udv+L .sRU(֡]7vRY +@KAT+K{%̆ 1.}MV)y6' Z Œ9G#۲O6,y'rXDOMD;d2 #9-?;94N=-'s&m;c9U4=NOfp|kUsd)uC5ڥa`D)ٔ>=n|p6hHEJ5f=;ZC>8%Kmi{V,r@aY ~ىKu2<EC?󖾼 K'lJ.K~;˟63Urr%,iu&&d3Aq@ahϼq#}n7{D *KM!r:?̑<`omCJ;ɶph(o"|U%P^E;i3'"X\ll)6=wX8 3fݑ^qÖ*7)>a,NP#-[@e a8D HRgeE}R,ڭ`ge[;ޒ$zGrZd!'ECC2x%R#Q @{~ ebH~ѺTQNtZzؠW KaU($x9Y<҄Mݳ=Q޽s6b2rܗ)^[ՁnӎȞ1-2Pˮ$1ÓhHyu 4ӅcϳմP2\\u Ac&%T|69:@/ G;ߣS+-K߀e*y5н·7ZH n'/E6ptx<",OQJ9<15o˯{,^ wT_~EziYLzq25`Zڤk uw.Zњ%K7ilaZFd8'XcScd,1 JYޮ'}v,5Obw&2y޷P9i}@3%o|d\1`b^@%D,s ۆ;=d+!*A_7ymEyi"%CcKطc vBj(41 _QuL%D,ABl#WB9JAhG jqY..䍙䴖QL:}spϠ?}\ Hy<8C(c$37x6!Ġ us:1lbZ=Ac)Q`}ʎ-5x1 7F W8 B*{slForREL ~Œ\b<\QJ;Sv T׋qe;q,`ϑpYP;LX.Vؠ-T)pRb!:xnp3C$IpE13@I4|D|&R5 ^_7,Ұ Oʓ'Uj/.|B?1Nu$ݧb"ꀒf/6 .Q Z7L@1uz#;ZR]C)Ka*9-1+o70* c0̹Jcc>y$?mU &@&qNJ.pK<*zH<}_B7@9>!I;3uU-pl nJP9D= NhI:+}f, :Qw v+8B6|WD|WzJ T iVhc+Z.Ŏ D'iX}u޷#R6n"+E7-8.L,a? k˱{ f=|# Ҳ űM.Ԇ|^|.%ѽotq>G*G2єgrjta L>V|v} )f '!\:%Řrx`x}=g Pz ` ^i"qA M:vb 9cZDHM5a8Dvh ( Bk3 AAAZzeG&m n$InIh4ּ3K=G9s4_I~||.g#J|L$vbȣ# Ru 92ߋE /IT&i fo"n=:匘{ S+xt=r|K QN E2ptٻugkŀs,נ'OSVcf܄}aS.r:fY1A<1LF%hT~m`j݁(@o}'B M7rkg [PCP# b/h;ifP>6xzB*\N@#4 D0 6f -"#ʂU1_e@`/-x5^a+V[={dzOcz77``xNعeyACΠDn&"p\c2:678>g"1v /X'72I& Eh!Q.*/h h>L ެu tp\%V 5.vulFaǥ8;, %\zX`/6,C ["3W4-9BKMPtriŋ!qjSlV-R=?4ܵF)˸1"}C"mhc e5~-hc>SW>uf:-blvFrjҘnQB3G ^%8^ـ)c+.cK,qV-FFVH+dԃNÈ,.Epk^BG4 @41p0 ܀9us0]A-橦5:KB!FK`$#>`p @̑>=0P*q]F _}{~۩J ~Wd#' 3'_~hr(i3AmL(vŹa&XZ e Sfzn=Ã7g'Rp.ar&V<цg v7<=? u/K`V м`ScR}sQ/MRqR'㸨R. "z%* (T4iXu $$=%IL!S-gT8=t;qg;'JDgX Z*P0yfP5H%L@8 3lB4 !D\] ؍AԑG%?R\9xYS$aߠ#Lq}6 P}ۣ1fS͛c/_ECyLGe1Y)^^U1\gG;@WP#hh!<= : X6[\`b3L}h2#.oVw 8 V;"c|NԣS-ƮkY˸T0yq3 8Y !Gac1 cfZ;<11Gb|6NG`g_\gva78V {,*chCE}A؏뻾 Ϟ=g>?'KK7qwmm~?t|˷ɓ'~ʯk{_o%JS[>5ƪiggZi_OŒ6P #~kEُUHPs${/xP]e!QԖ7(W(0t-,D_(RZ`Eh-Ư5C5@UڹRaPګT->TN8/gBS炰AL~(4 z o@W5Ԥ1f]Fխyy%3nQ.WY|_7߱l2Gg G ,7I(t\ w\}7\r}sa_FP d)#H%jũpθkg OkiYpj*ZQ,JoRWܝ'ӓ|Tuspt@EJo$W}֭G7õa`* $( ÄĻc]&8j.sAv6&5 ) o=`@ ǢP%%- Mei|'|{i̿hZ9CĘ@;#uW̯Z*N3) RH  SWKA ְV+-Oja+Zu#W M4z-zWkN:=Ss-+!sFt7hܓN'Z=>t|G{0@pb!flhlJBIXtot*?ԟS._?gÝJLc}( \xTmU9e\Ω4>`(YuzeJp`},8#[MmElCy=0KiXtRWWPq57l˳Y2.0.j`/zJdf!JxLOMyf#J?(CenW+$(BK~6lc ;}wS9㮜pniSCoo_ D>C?CxGO? _U|;>_㻿??//wum| xgr#Zf`0xcrx8Cl|txwΝ TCR K"e9n} GvT/_+sŸn@"3־ i Tx)+%p.,F`8i PZWEѝ9 HG+[e ٴ dbxP9Gȸ%y#(1J.G'>c6ishN(! "vV>S'/08={ r*,}(€0F94R jW,~$a0,̄ו~ka;3 Q < %ZSmw "XZlD`jH@Y$5.5I}L zc|au{DL:O6Y>mwÄr=a?\pۼmkXjER&"{I!(9lID:HsT,ǹa`G~BC׷&äE\;.;I0X[|)J\  +R>֙ uF+^|O:O}S_+/?:_s:~ ض5m߆oͿ{7?Ͻ5^^/^qu,10yIz`}W-9dr0sFz3̎HΒ:,meXt~n'k>SY, ;1c' x>M91E2be7E&+ zX8* %&fǁa~[P&b{ & bݓ+q7 ,0nJeoux82,!Xܹcc -۶N~ A-v5h:k_QKeGv:nqWBEJQ8D:mhR<3 ޿nh-MD](LAcvb럁#I*=C1 ߎ4ǿ?ѭb=$V1n1ggs,[}`1H~ khBaF]6ޏϾ୕x.w{7[8\&[u_2>ޣ?@\!`)9̛&y}J٬'ɣIÜk $ #*<}~^K:tw(Ng?ٛ~//,˂O~o&|3o|g>ۏ؏o| >ǜP(Un"/~Ų> mK@rX!P\#樨,9tNfnaKfHf"m G!)iSQ)(5gKsr^p ohU:m_^m/%̛REP* uq/fOѴ^f7 }ZTޥ- JLVA@;@ouvۉB|,=2yf=oOxgY" SB(y{z aj y {߰aVۆmJ_Rd[d#蹀m[q'r:޳3CtaнcEH_irutͰz1P72pe+ _zqœs}+xr*keEC>3|VY=VdB0T1ߌr L\G4$&r:q5JY`~<)9m}2 d0E5`0غc5`]^]:c7-,jyԙ :{+GHZ IPM*Dkg‘D;yST!Y|-b?O؞ q0VFEni'A$<ìB cBy;8̠msIJ'@pEPլVoz_xܟs_VdGmGG/^xzz ,U&T˂Z5Jvũ,!<`i4Gv(=>Np,a)BzaN-E+'7Е]LpQ= l@={7k5!`Ey!q]}ť,o}aQ9B*ZYpgx,>=[޵{< rvFNf#N3\ j? b(Q>bnS g{[=QD߲71Z#veE\-$WFK d DղJJ ;a!qL'=/gS(3b E>~Eہ;κq3"I$۶S G "@>y^X /}[4|*{O̗)D28l %azBk ncuA=cw"\>Q*Qk=Ed$)ʈ%sW~|AqP"S]0 jY) NIxY}JL .ZdV3L,KrţےK_bn wXO_Qv$|`uFՇк{$%NT` OnŊr`Mcr4oH/XmZi@`qA4n `аE1v+{0hŦJ4 '8}u@(1݇jDW0#(KC(fxvV Y` -'}QŰNbaCǒ9w:(س&]oxGeDEh $ I̠1ޝO8tDPu/} /x^l^D&Xkt҆N=+~g~??~~ ?Gw=߃;[3HFWk,} %$&bTTn06*X э+TX($ ^pa~vsS6%`_/~ay.@;CA%Z6yOpXL(XN}06 fg:3f}z*NkڻHj%b 6l!tȣHEa`30D2VjA)rJ%̪]R0/^#uo,FoWWɭ.9I0;r!4e XLj |`HbfZDGxµ83ZQH'/ٽcû`CaJ9PZjfSG& (! Ty uv-FK\}-׎RXmE=Ƽ7D'zwu`>`RcSJA+ 3ȱ;Xeh qAp `A<bvo{0ɩ۷U]psT%=*A6G<<_'<>T0zzO8!!N~Yʍ:8/ܝs 6<ѰxWΫ4πkD!g0{odǓ!u@Ss'Р{P1-}fQ"i|qPGVUҳm}өn~?wo~_ԧ>~7~ __?m`~omi_/gHi`wMb~D,QAJc.YA5dNYENJgNCεDX /BB@Zi o# }`gP#,|UqKbm\\c_Q\w~vf8LY2}Tͳvf{ mXNJmlXUD1z{O>lv-Kr~'mh5<`x':) ǍU`y> gco z:h1 ΀]N+==@vܷB>;dc`䇵j$R 0<9ISHM7mRyRIJ`~/$9z#}T>9nnBS,'fזdA 6͎b4|ƅJ\8 px8} |kɚ~}bv{mAק4}ƾ[B̙w"}/f Vk#wُ6o2N31bNǚ~ i{???4/忌0໿տݿwQk|mj{7}mc(S1,1@#vgfGՆs"L i2wmsq|vH+lJ44!$F(q zI>q!B1ϑGٖj\(Je]r]( cc۫i%Ves.>:6cBI6YVwEt[NhZ rz,z5KpB۾ &x!f=*ُ^l- 5mneC(gWJL޻:j .// UJ+ P.(nBDg`^8\+ym=6\omTE䋑ћnj42o:G.jsP4>mx*j6',<9sSpK3y SY>#. )"<WT=^^3;݁;ӍLJy;}|~f^}͗ާJeG ))He6~F&Ip'e>  G5j >cg^0a 4ęmFR4H9CkHe (Fʩ^,W0 >Xv Xc޿4Б* KR"sAj4J'1p*Jmӛ-m_H'O>Cm%7jqKzTeltg:^v,c;e*D+c]?@}\x JL -P]HmjeOYmFtqxծsXiW/wD xx 4("޵FP%?Zz(Eo p1OS'v%̟(ok}LOH +E#$r;dβ(l"a%eKΐ%l{6߂FYOjTwo*Q*T`)/p.'#|*K=jJCgu`!3p]78T ۺC"i"Jum_tx,OFܬ4z<բ(|~@9[̸p 9hiJ^yЋ `U׿/j>:%v#-:}#3=ގ?2awcϝs/O}c~ӕϸ=l,i~% %\%=2 8Y617tggfiʬ=K=_Sk}%oi}5 S̤eA+xܶa[pxɾ R TjL4􌃭p.J;:GP\F7A㫗^zz, o 6:tu$n+0x(Ħ5M7nO! w5[57'\,g\&LMvZMD*GOҶ; 70&I-=b [4Oα$ N84:(HXSCm Lv6*PT8`N/@WG&ؠU0+;jeٙX:h `l_aka ]J>0OE`'ADlx?` u2xiDh%_y1s37hr`hpI=fJi!́-&.)" jl=`Y=n Jm$Bna!9>(3wv|S4q;nrc L7D=%NẌa#-Tr$;wm'Z82;hpDG!K`D1ޣDc] AՆs@c!SEHURᘬ,aIV>c0s\:W:xgBdd Cư}舖-;/JG?M?9$!3˱Y*)eC" J(6xy7wt =oNkfRp'yIU 4bO>!I(frly)`Y*AP)t=C>&*Lhg\p&qi;tp΀iFËn'˞dۼo&m"iso4u;d]lNp_Ȧe4Uv(Z?rX;E>`\VUbЖGCF BK>}d آuHiܯܱCkAKriXp66w,GjE-n4~Xu),85P`@@l 7,/$}VAOEh~Z(,Y5apJ*,؜1I™Տ71nՈNPiE>ABP'Ʃ%$ piaOTsSE_7"d3\nСXc!3pRp}WQA02%lhQqИO6eWu`~&e$TQ%g g g@cˀusP66xXŸZD&MKulZs> 차}V"^k FA5C.x*.)Rp}4CIˁ㷎F%r& ,Xd!Tf9O 3εB*VAv\\j %>"3BpO Z> (̱Ap(nh!&؃(G6·7< 7Fx kGt6|{\<2|665Ü1lξ n*=^oߗ}meI5@su'x,l v?$ %E ,!X9}9nz$3=~7٬2]wzLz>~(on~I D'&XNjowwۇ 4T` =⽳L>>rJ* (wրBLjddYyIH&=14R.Ri*Ђnh$3#g'A{4E1 OMb%P46 !U7㽯*._9ѱw`d`; `@C59Kl;1[42aQ.A6  ѧϧW_0_*Zf(u@6.n5s^*RZHV4ʽZ#{AA MZ\7w--߾N4x/9Wq ?x%e*x=2\3sv=l$94C'>_e R`CZ@Wk$g9J I٢Lm8ERoz[w3P"qy9m9t &HT wiu3%/X_F-Wiy%~=j0@~15V`DoWxTDk !bd?<.{ܵ3;['g{@w'FDtCY_iynvF'*N j} "shW`tx%0(/ gh]EVla+M7aR,i 3z%g6.P%{Tڈ޳[ߩT((eZ&:7$2^ ( r} -hdI?n4-;TM![ g _'"OHy Y~ >T:9M \Eq07\džm4DPer4r]=\1R~fxŢ Z@<`3{¼R̉:GO>?mo O7?Ղ>hFCq&HEɩTK(ཻ{; A: nTY@-]{I1WO;,{kRൡ, ϳ|"TDYXWe9NLp2m)%P "TMP<~9-D4-XȺD(4||Ag&IMҜor!.;'q[o$셼 PTn>lGKnvLé` ;- ׅ@v[w @*m1oz.X|Ҍ9BēFu};;pFYM羶BrTED!U^Z H_P P ^ n iM*Y҆ Fa#&J:ۚ ?[΀jV;P:{Vo]A, .f@26a֢\zBYCwg{RWғ0k:%&"T!4y,t$Fs&".PŹ6 NG:6rZ!S(J"x<Ɔ(NU?o4nmEiehC+ wJy.セ}aД91.OECPh}TUm`t[VJa9PwOf]dt&X!Dhs&j⬞:i`iуX>,*co|u67dz9t0ΓӚؗl61%-DX`Є 5~^^~RN_Kac`F.C(%ܽA“.[݆F\,Z\gTx2ZgdlE8>o muG;-TLtDNDix<@e*􉞀UC+BQ%t{/cǎiqc|˱==kXϑeI})ls|zG,Pf6{0ly.Ҁ>Z+a1"prbMP Ӧ~uNK]+G&ć}&"2{@Z&;k2AA3HրHfy80 3?/O<4 17CaTqDEbV(mG%C7Rg% 'o]lg='x,6b6-& pQ E9&7Fskڥr! ,06c5Q9AŽZ1q ΄X,308 hљr Xt?-JxGg`WЪ-'Բ95rϦbZ1tcхw"]"YZ{驨g/~z@ L|K J;̃FpAƱ e8}`B2YZ :=y }ёٖ3|8L,0OTVVr!;B>8n?۹jC%ʿTz`h CpdGHV,'Z (b)*b yEdCID jeQ%"؆V{a*Z_ek`%uRdc/9\o"8/9wA8~7G)D΢iH#'3?/1" Lj/K#` gAQ=)ۂ~c_44Ck$dqz@o>f(ea|ɇ`>YUe7~  g$W+3R I"c#ʄ>nnt{~۵ڗȨnl6+e? w%=vF#qmxwz'j|RT c:xq_Q[Gt\(\팦gZI"lo':61K-ѷu |wF!)W_c+[ vxn"'0T rTUalXK\0 zܲĄqj-9yS̄fvB 9tP^*NzӋ.":F! rsJ;ǘ׹HC ÌƄ\+ѯމgXWϔP/M#px`Q,p|hEъ`) gr2F6 `un5m8# | R_Sp^cvȣ-Pv />A*Knylۺ^wt?p 8Xp9[3@'+]66 } Wq U$⛥ JSx.W83 `>,\|3T_q'm42/8 etj,zig 8?Y ԉ痨vũޓ[*wxB>L<KP-vn7DT Z)8U_y |:ش0eGtoJkܷ; 59( KřN4EErJc ̀SmN9o bA>8 YIVa)-SGl@|]Y 搻q#[v0g Ý Y.!т@.⚨TtPO'(m`^Ixx::Ηx9#۴1MzFՂjm 0` vH>q(>p?0 C:`qH6Y}s`RCe?\HgV*T5&a@I+<<5~h_h5Q@dJs4g@nA7Kyrn@<_ 2GADS1QϤbQ;<cC ݕzb"߼V $#DJ,0"@)Р܈ zkOUp9)+]_dǕ^\Pz05e NJÁǑJ3Q01eOl* eD iu}%G̎hQud`"†DO!DDZd3'WۼQvjlJ% DHTpR)X};Pa@fD$ws˅` ! *& A@vL,Z`NOaAL 9,`beS07"€0Yx aa,\&8vH{,lɫr.2{`pO<ܸ^Utm2>&aJ=,N''R*oN>'E%CKXeia@˱I:TYsy,8 &HA\P"DCH sD8%mN _?^LDKɃ+y,bAűWpDq 20m^oD<"Ɖ@bڕq{J#g`D>qx ! +$0iYkKyyANYUp+ Bw}s ڞ`@ cicGDD2*5ͱ$f3yuJ{~~m% !KJW#*~g7݁6A+71<3N;jE(%BB6Em>Zeׅa_qQ lp7VaX V$Ԗ킇qxxW/pߞg=a r"Dd^o/1"%zB -%"cn\=[+ N KpޱuP'@ٽ 5L8:ֱ᥽}7^QSWi(`1^§sWςOX@:zu8&g8*#M ,ie&D=@!pd,Vc'] r|[p$m82"1.%ʹI>0r0,p,^y?[dak4 tCiRI.Pnz10 ܏Ωcs] R@虅f VB#_c%vǬ:9)켠Y2XvgM9"IM9˜asKLʓ\bj-zq3JX5 ~C7`좲o JGT)ndY6.nBktCԢnnB:BUz$K0FA4]L0Lq+.E4H-Jx|9  Gx8P}(#X%ῲ5]St]x fTwcwrV6C\&SA n5hbA1?)O ж8Osj%T 4{M8I>W1Vz qq M+SuT~ׁ]5MBMquY58["ؤϴ1rfy!S"?: e3{n ,PBsZcwc1%qq&59<|y?ۻ#u`Ѓ%"=!~c8^d_DNaY6,ZpR* k0^KB՟RJFe4|eOV7cŋ~ ؔkV\/QUi[AA,m4lJmEsW!L1N?Q"]rra6Tji)kDa Z2k^H̀%"R Ps%6Fg t]w@!։}]0.`@%! $'P4e0l5]A'- 9ؑ[hoZٵ#"/8|ׂ{T 0GK=pi1n(:(jFoG'C &KQ[6#6E$=CvId;n7Iu9(@ꘝ'2p4AǺr'T*ׄ9=gr/Tvgb;P|F E?'z gl/2vcm lanQ,1gw3aL,LX8Z#((?L8CGF(2S|zKhܰl懱ۇMdp&qy3F11zW՝"!{``2=,`xP}8q}{W[_gNU3a6-2̔dp8[ 1LVZc'8kl(T(:PԨ%Jt} .Nict4?4 i;fXcO5!B2W*УY8e@T*Jhzq}[`0Þ) %wa_Q2ǜpri(V|nA+:nD"x'qž{s֞p{`WvINb6BJ,29/Qg xalfށ* wŋs:0@-Тm{6ւV2q+(Ze=7 ˤ?-;d=[s H'Hoؼ}彷7cx#B,bvQSDbFP"iTQe`(Ghګdd21j(g 钎Ù|+ \x Q <!bǹ\}{keWĹf 1Djir|lNZ"CC1rLhT@'y5fhޖ_3;$9m`g] 6+)*(2,p2g .UE!P\uaũԶtp闗0x!f ֠Tֱm<&~luQH0Uo. ?+#~B z7.BhC ~N0'm8nI^q1;qCAﵜ4J_ R@^ɹjQvXT.m}[pY.HAv˜_f8y%nZ%r ^1c`9W4??fA^6m (P-(De !%(e:q.g΋hVƱasPƴ0<0܁p:B6G`Fp8/>Gv?zsn@/H4>mkDA|S3My>(,7ޓU :#o.FAEaW`Q :((EËH,D‡0X7XA\ 7T*up̯}el5FZ;8[( W4Դd*q(#9.AE&(hXZA%JwI4uvj\Bjw. -t= {ୋ*?6"D`B%R7B<k8~ 5JXDl 4 ;H@c> M^"bEYtY;{PE 6UÞ%T.t>GE#`1^'wLWj6q-䈦' x .Xy[$$e1F[zv(f P<ijS8 xRMpY%׏8==`=m'++-K/~Oλ S:0U+7<;!9Kc0sժh!R0s85:'S(!w"QY_ABgWtD 8") RZ] R܍m lڴHtT< ZiU Id*Z9uӶ@:Ir'xׇ%8qTm`놵O爢ɩKn> tkĽnˬd 83l"YFD[%`QP!A}no=c3-bZ#إG) GiJD 68 JTW-vtla9a E׳hcp">D8u"!v0 ΢ <6p9rI%$;Qҷ;fDB81i pc>@[ޛF#t lf1R~uǷ<]: ͩ`*S ;:{P+ T%셞 yLXLn\ݗcȰ:p(G^l|s[n~ը+Ѥ-$)ͳ?|oJ6(1Xo$0w6w{Xj2al\P cByw e~Z`C PQ6\Biү(ӽ\f uh$WyӶnIG.Pa3$&4= G6 e\Pϕ,8زld.x-3oq Aw9e(`.dE.P!b$ 0DIa_fX0Zbõ>: A+(uDٗ5)@ksex<t[mx9>^c tt@T@bubiwpK.\&,CmcE[pX{LT$<+%=+4`Q@AGd9^];Dl@~{?YZIb`[TQC}B;" :q"2jڮM7>?qs;sS?%ߏ[g`x ezTPb[GLZ5HP8>Pͬ.l_fPz Ncw <(ڃ@"  B_].0g^3.qo!V'{]2 Q@CY%ARB(V4]PpBtE`Cy<<Tn2f˝~U 裦rE}se` fG>O_7 >dţt JE7U+dqu̾jĬ„F$_KN3Gd,2￷ʀ7෯ݏ&̠-*n1&@͹ P#ɞ3LK"WӼ^r00Gw D" (,!RXmzA0G$rxAPg5EqHKѠh^l{lp(٬ELAxAg0.ʶ7p fdXΑ{@LD18 "OcVhqt/p)1c!)yރmf]!/铧R"ߌX/૯7<=ݟ_ _m[ cvqZA軣}aO Y~`,@f[pE!uaژEۀ. '~okbHGz|3CJ" .Т O8vc_ +"5l>YZXXxZj((JފmRP~ը@cs &5?'8Qej4u/i: =("b7l//$#W翅?>!R)X,^(-~{gaF Z%N]mvnVۨv-aRAm \O0v{r̮/ KiТxyy`(?b+-_AjEExQpObu\?o72[ZmhxQy~w&+bp^*eSSc{" B sZe)ѽm)>x*X5;pG˿_G"1HJghHi;{ H gTB^c&$1!>0,vǺ ωe< aw1=?pX-D`Q ȗjH'ǒaM>pO:+̸L2yh<Xl(3q 憓| Ud)c+ix5~ŷw-wWwEٖ0$PTaXw" ib.Av:*` İ1`mPeoaog@Pf:Dv؍iԉB+P,-[qΈ |+T\Jr&!LXu9& -IkxtU6'rQ0A AlQZprThlUZ֊#kDme'6 (,*EhV :daT0 f@ dy{'o, !/D$D 3 L+̘VR<5*HO҉ZgYu b( p*6YaŰGB\q;va+He`[oKNчaLL#<7x|!_1Y݁+;Ne_n֊566jmFQkie\ng W*=&a,x`L/ӊq 'px7Wd*MINJ:^>ND{AQ O-uOZrCB {=-p3f;:\:DhOwrsĆQ@g*N@~Fw::._Ł7EBa-p&(ps,, qj3"YvAlaU DiCxµ87,&3>z 2J8{"Eh{Lθt FmE )q͹اjXrYM"-\-vq*F:S{;i7Eb rzLAJoAю,!} ݬZ"B&04Vr@EqA?{/h(@i\hKrX 2;;UOFzˏι"-G_SHt׾KKdk9pF%ISVOiEG6|SxG(k;p A 1r>fq=6=xJ*,/*A{y:(}v+y)}+ֲ,3B;8 { Y4f^ⴝK|{opn!,,N[F؋ tlozfxRݣ5qZ)HjaMRܞsڻX^|`f}FpCJ,|J0'INs)P*m+[Q[=v:N uw>J .g ױ1!}7\ m4YPSPW*_]OXʂS]Ǝw통nxXac++bxǗnc2nWFخP'7ujYʆYE ^l/(G[ DZ ̥~J&墅On_ iS܈j(= O=?(D,ثm)ֱ7õ19Yǥu!l.Z|vRNJ9i7Q=Qq =:(|?^|~Uo]4l&s2! ڈoDGhR?v%%0D܃{}xub" +~%"lfl_sB`hxXaE۩E&:T<0G)j6"8>T]qZkaGXϴ ︍۸/JA7] c <]U(N~ªh.LG*nS39C]KDlezAttK%P iCBˆy||#h)d~h FdXjam@=M1Rz5_V0<|mD+A.@El3wuùnq0vplT)@-XeVw"Dj ba 6̐[8ՍI3{.iiUt^ 8}t8 =_)3o[a 9F҅j$QBu1'H4#2-126~-M17z05x]Y6d1@D&"J`=O7q*V,D'C) >c63˂%Z2ߺa<[XDF#x}ۘ^Y57ynzRm46"U䆰"MKsR G⨜̙ qQ8Pa~$<5s%=杛 D@kz@CbN9LfAe19LJ&PbïBjԾZ_ő-'#}k Y"m>pگXu݉xܵFи͛ n r‚XU Ɂw跷P]!r^ \kt_rwtiҭM`[NDeBKz$g=B xJ "|L8 D^hx7M+,9QvqW/֗XˆsٰT.W[JyJrh&?h)d;AG+ SW w L1l3`lOn;#[]!o~8JPWG"Yd0 _ Y .МcE-5Y$ZL2Eak $E,$[nmtƎ}hm{A+QMnlɹGp穨iEifsZ<(%=‹ғF ^ eٶh )R9:4c\w!Vn-RI 7,]GmeAZ3am|.Bwv. 9x9Wl> OrB@ޠ>qOd׬ähW@3Q넺м2;xFuxL:`*iՌ~~X?&Ԛ(^Dnݨ8 sTBenv(+pαafJ9j^Sz zogߵ_q*+91'¸膥aA106o –Šz)o\Y2Sϛ@ 4µL/`ՇYΥ+dΕ ;d׈v+Y&(HoʂDNf(pGHE5R4npUa)*,T9b}mg\<̴˔CX̣D^aXksB8i)(v۱JIrkc$ 2Q}- ]N;&oYZ xx DKb%?@TķɁBQlAYܽC~iyU*cS6fGlYqZ&h;IQw)N AQTEG;ϨD{lb4֐[8K_S|3NeJDG6nX‰dG:_YZRA FGu̕,1 S $вZ v"o0ӊ%U748mY*˸GYTC` .S ֊ϱ<؎Pa2չE+nˉ-`#I74K`NWx^c)ԩ~<[ c `:,RLr^%<&Z{@6_aTO蚭DQFV K{ Vp7~BfKmp*l'S࡚vQQp^O+;w:L_\ V]ʶ{C=R-Xb8lu Pz5 h&hVh:^=69 FE6B *`n 'JxN*z\-<0L4|ʰQm9fa)%΍@",>@rQx.#L0)MyֆS3!ze!9n%q$!*̴?$*ʹ| ]Q>yaBOM,O@snJeI~ٴYLT9u 57Ad:oY2#,p 0PZJ^@".3ev%b-rX̶,H:( y7m QG&;rSsT2QKƽs2C{WPk)DW㳔~\[_~~;ߞ???G__?'~]??~~ ?? #?EW׏ '.UiV(м4n+[LxxK5q+m'$C{~@G;l \c*r03M2v\o[<n׶h[eżJp".&qC1$w !eŢ+C@!QY{ƶoYZ n]nMOX EFE,L u'Xxr]Ёlrfo |^^@.~hTMar^a(ǢFl>_(EAH'"-}rb[k^$Q`:#oV?e -T Dcr[c^5#<0ȉUtNNcrkxdBpZNP}c7"=K! [px 4,6ܘ)Áu#ڌȾv%(C~ḱkQze@b"3bEC S8x;?,fzw ;9p¼}$>eBR{-+A'C+ƞܯlo1 J 7"EKXI iT(w0=JDy͙FX Ca5, YwkF'U S::+D 8\r #뼷r,߹iAN93o;Kc#DC] J'2bY9}c(_r>9|s>f6|7W?o-o_⻿c?ca(;7w~wk~ͯE}歞HS!&@ 9*"{ź>|6es'_tA_^Q`d z9%qfNtAn$ɫ*'W{{nhp,bMXYQb JT:!BLPda /=ݸDOpAr"@%ΑP,`7 qAO"s"xӀ7%/hF<Dar~^A,R=fH:n@1kE) @ް,`8|moQs,A!8ڭha1A^VN83&x3]fXíL8)geA++/|e2Q8Ļ&z ~Bv4}vQTtydbz<7<>yX͕ş%;v)űqxJMB| w`r'=>KTK^a 9<;=N>lz@=N|=pom">9zb"d*aΖK>}/W_߂?5;o6ȏ{~{=ȏ/,Ny'rrRKG`AU{CJb) 8qE\l)4\ 8-ZQ+ӪTcՅ7haNCSdfхjZ`pNxX1uc{{}W]-ڤ`Y fA^N>|VN44LTQC ~3PDN.4:'3ʹAvl ]K ΤI -%M ɺrI7-+r%z$ɧ(]f#9 ݸ/'6-KH=ar'=EJ4bO"8/WL ^F 1b P| 8?6ڨة =6}/XU7T7,U *׾Je+6i11^K"Eс41?޽w'K(I~0܍!biiG9`bQyMB~% 2G;na:wBq\MLQn e\O&`8д<5BR42=')O&07w9b޷q#ĘuSюQG5?23 Mxh,1lwix+?ߋ~/O?[+>c6| _'o&| _| _1_nnW^>|!bTNiE)+1~n>yc8c[  -+ve[vtPhˆVNPfqڽ\#DJXED@O5Sm vū[=?/Tܵ[8?ƇWc*LЍEu\:io#Ձv|xo$N<Lpk;6zusw@0juNŢBͤtP#eh wB?AX9(vW`YK"Mh/DvDAt"PMe Htx$]X' ?<0yG׏Q U䍮!zΥf#RTގ w H|_g[w7h @E ŗhA/&ʎjt8:jq|A7=b).Ev.aü]lhְzJVŒUhYGDL{8U;I @r3x u`, ^ *@b+aEA  gy&hO +FLˏ0[ΎT{ہ̍N>a)Zd1Qt9rkf{b4gQdSRI憫#\ kKu'ZpsAn{GhnΙŝp3òPALdž6V->6(0/ JU<~ynf{- c@K8އ3`s)'SEb{kgWJ@c v);~m߆~>{~/lc Mn=?<_>c+>:h (-U ۶1o2, D _5pTWc;ڸ @5vEPơUvƲq#&/ vx|=QьhxD#'ؖ3 =n)Xzi"sGWu{! aGr"UNFU(0<_N׺&UpAqx'ld;嚭\:j9 bGgW1C (0U>0 "D agI,g"=j6l#T*¢dmBDƝ|pIxŊ*P}(o ;G>]<<@ۗE*zO2Ϻ(ˤ(|uػc5HU7,*FoX|z sQ0%%E 58- K#DzK| E X-y2Gݷ@|W%ꮅ?r| Ǔ s^6Y{CCCxB/?4[>W|O _җ?s?|~k<雾|?'$W^[[QkR81 m!QHcrp-m8t+X4phmd@&w&N W- A߭|>x>Pd4 @L Ydzݶc&0 ?CZirb-z,-3c.X "UWBI2'szjˡ6'DYhzi! Ҿi5Ffy"FiGL70< :nDzNEQbRmL\.%Ղ!WQ F+ƴfh[@TS;cb" X7ܱ QTq ԑATh(Šf%̂,!0Y4&zw0DZGi* [BJ‚Vs`}@ikw od(_eEy9βLD:Tq* ޣw[Dx>pZ4HA0񗘧{ISe7+dNd=#FÉ]c.2|q e5sD1|Z56NXē1Nxʹ(d~^ui]˂bv35+RgXJ[Bt}SPxކO˾?g>ov,˂/3?3?/N|w7?EW:mö}yFHe 9 ! 1D*"R.)@?^eTԲ ECz61c)Wh=~ed ^G\-hUW[kpEW 'wLҜ(@C\da+o;jY%b >%dA~[3m`[Ãc,RFh%"f') \eףqXJ.Dtgl?"xcyHDr 9`@wTc@?,ϢV%3W@*Ʊ> [ǐ,?bֲ {-\ l..m`Y\k,<7GdL%Y LUuZ3҃*N:۹[L"=3YX2 4nx6(T+ M#H=4#A@޼y3_뻾 |>?gg>S W؏^x|~s~o g?$_'ZR^ʶE87&pօ'A6AUĞm)(4MT4v'?7_!f/8Ϣ`;;<Q,e=+"*E\"ou@mDrRu.s笂6X-7"lSrr%Whp DyYs窑-h% 4x$i"r}\lL#C3d. %"Xd,(wu(XRulzyQ8'̲maadqZpcA`؂>Gsn ֺM^mLmk(ܮD ,(GG =dl& pX[]8[ NNݩ&Y<.D *OnT7y'.D@"QBn{0":(pxq"rG*F-,?YY9>s1E' >"/=%T*ftO WbfG(~8wÀ!=?+#0y/A >1b:yEvwRԌ'|umxyZ'Esk nVЈV us,ET nma+Kp0ʁXJ̕Z b.AQ#tZIDAT0W OQ$Mкc+eU#e"08⾍WUwI =뻾k-? _?ݿ>g]]_˨>QS-==O}f6{<00X"fp =[Q&qC7qMo7vN\[EJP%-42+ڤc@~W_|L>Yco?_F^pM\d.&e痜cEtDA~ GhxHa nrt.B`F0%8g)Ӱl4waxov| \}cy%a"X{'3'J( (PzaZp(5۱i(SǠ+H׈[ʊlRP`'G 9BϺ"3~'_Zw!<$ָwȸ <~]G D!஁g0s5T*2-{-z7|V\YA^-p\y+\ 1-[Y04TZ1ՅY(Eta'q. "!FK}q2X #;D*spq˲ 8Y8&"_dzC_?SN9AwYˈLrXg+uc<Ih:.}:'z{['YXz Yi ׋#/8[D!5=w{vep3]!=K B>pkfxyZpZ ΋xR {8-/N hnOZbkļS^Q2KCCB|TZXX/ɡP9}$"wTzNFENE0}Z;| jg7~̉<JHtYFo]ZPh{ƬGe^y㘔 38dةDdrN>W5-wGC}̶AN& #T\X,Dƾ|d4V̢r!bil)HWΆ;\!@!(47tP؞Z~ x~ HJD~ mBXةfs'>?C].`-Nfc 6Қ'DE h:uE؜nD{6"eYE7PAw~#B-kUǩQM>- h3\)؂oJ'NqSD+Ǧg>=Nڮ=b;="w[퓓4͖(--Swx`3ݸ*_>KF>iA"'Wf#Yp&%E s 6j=lg>9FA5\a}6:\ tH!݀n>^ztp"-Qws:Z on϶J[9x#P)p(:ѽ&Ʊ Ia z';KvPQ#EdnTyv22ҟsFf8MKm$7Rhwtݩ}XFQi"ai8_zD**C- x#ipm=v`%8lpJ٣@cƍE J3Ix$TD3'Et:gܱ1[bkId&njlZ5PrT Dc4*G{Ci۲dsehuoT0'4H%UtbփYDJh5oN P\QI,]u06prR9{wڴIE\} ie-$݆qs3(f5 [}G;ތR7u"J(@ R!,VŦ0ŸCaLĮ{G1_FP>.6omH,+[jKOa2͑sas_covu=hdXD@6XkEQ02t(X=-SPbQ,UZ0q,yOOCymdo=@4## w|,,fwG%%sP,,2<7B؛eP0ɽ߰ 9nҦIR,*Sp*^_(xӢx KŶӅihn樕;עEHlFaB[Pazю-SNڜ0_X4;2B;;yM/ZܧhhnKZe;t'BEi<޵h x M(Hi۽Zl prfcFl`J"o:-)֒s{|n݁:D1 ZPylnQ@aw8JD@hQC,yN+eWn*Tܱiи55,jX bNVNe0Cy m Kl)T3ӲyN2a 'h+35@Cr[|쐩 7Mp8n$L7@SPmd"U}Fm(ʴ^R:}X# fuhe mW-liNsz "T9fYa ;| dy}B{@ M,JL[uX@H ԤL5yZyOgNAS` )#6y/JcV%}5C&d @sXUpU.,lBѮz74#U *y }}g;> !H 1 XڻS-X xč\L B1]b8;*y@6a%'^/Ej\L}TZv8/P-`KֶfT޼~oy~w|u| O aUXh$o`cvS!, ˂OFX#hxB}L+=٠LQ\GɜRuh=<bQGnuĶH ӚE&18yd&Dx0a } 2'""+G b;Kޞuy=q JUQ.yax.Qhnw43FKoZ<!>F";rPP&GڎD7 t4Σ+sBKpLgt9cHdm6%'ςv92π)`p El(hD5-Q ssH@v4:>x)BtXl[ ScXz%l Ie;óQh%Zd؀'Hއc'Jz#@L]+Mny 8ƉX(nfQ%՛iT{AQdܘϽN@Ǣ S#h523kv蘹;{;L+L V'hf䨎a E+uE  6fx}mQij:UE]yKpfp z oy"Rvwb^ xiO <ιMDlPHá$cC|G݀[|sx{Qњ-"8B i.p0#hͲ]NU [n{ۂ|(ZQ|4hTާu{(m*<@ښw “2@#2MT@\)kqK9DHOC,]mq;|4vˏ3,F\fk3̇1bipW܈nȶ`@ |9~654trX(kڶr,ShwXc9$ں!JΚJdYXD(I3RH7P^_ԁs>(jUTuKhM@?\;\,^-hjx|:w-OٳgD@Γm_h\S9 X&sW^D zzq^8qiYL: - Α`Fan4ѭ68Dj5"϶Jh < g%NQPXp, $(yct>S2'IxȎL|.9ܜhUjMTjnu8U*(2bR=͹hZ|3dB]!u#3|t`qCHyK "@=g!21$Ô)^cgH"n`&߂RVDpFO}u#ﳏyd RT\o7I#G8uȋ Z|vwBqbcNe;҈|r@|25@Tmhiƨ*~LY8e!Rzur֞; 6 ?|@Z.6*+KP%縷{vJk{=[C$eGǚ@BqHU/ur}?,&-g7# GX;cJb"Ni6t#g?,tA^cwu)JoZo?jiozIc5D".*Y% T wX!a]+l6#(۩KM mՙ}I>L}tZm<ޮ)wf;F|]raA捖  H{8$HFB.pEh=ѺYl(AnXBV$b+%H]z+'1d{.j]2!]R oLk20G_}3`/X`Ƀ( >8?kmSؚMCq BFoN%a<`8ł*+P52l\wM;QlXavv tUCx,ڜ*ȗEޑ1vR ?ot>PQPM*anTy{ڻ<0m{IO!E*25 .7Ca)HuJ;.<޷qL @$(N c:nƷ]V֪QukC(b6rX|IΙ mP:8g¹u lZqX֦rݝ߭W=:N Yt!py{ŧxW~ qDi WG0kVDi69}:J29 `C DFI5\{ɬ+#]=C;ƴan&ߋ3rg3 BWx xdgttEuYV`v'% H"53C>srty.f(% Ȓ6Gjh<~.Pr h)LHH>28L}7V8HZ(N=Z4[iv6Eq@:ոR#KE8_hc؄a6 [S$Bҝٖ|@f aP]LZY4$9ɱE q흛":T*~AA=0ȇeck\ ڃÏ s5:, ( sn+ cF5J۹‚n$j9~1zOyy+Cc_`irLؼ+c.t$br<oC'w_^/@^-[B 7I)/k^(Rc&gɟ̍aL:CtLX$!y ycxH$7 ]9$"^ŋކa8NOaG^ !օÚG1 Ṉm2 bCqtuEb;BGI||ڎwXt'DDDyb)Z0j[<&m @A]*Fow ENFKBY332}Fƺn$, `mf8ZAZ1\L_8ˆPw rQ` g>͆/&ѢT|.(#Z't9.!$HQ4W~i)"eEe'- ٦N㉳@e(s[<kW!DX-ڒ Guj`p-`BCAPh.%JYs;DV,ub'ݠwl,ݰ3Ϸ@l*8/lf#ڛ93nkQ,u+օ~lciBd}GAܡnXj 4Q뙆u:P5+ZP־C‚wFy 9RBRʺQWD|*+WĠvh3w>(U($pmQɧmQ3VSU-`m`cnoS"YϜ⛹5h;_Ag, T]'j |Y6c"ՓO䫉*[-mRCy PTUE{.* rF}[@-Dj((o'"m :-O("x V\vn֞ Mҳl-*7O -B=;hґndγG<4"[pUn@3;Z}eA-4#ShgC6lw/??D8/ ]"0CauWNsP.70M:\:=0"ZLƱ1gCCXke&7wzN|>zxxn8g(|/FRpTZJ 6y|0)x<,Q1K%6<9 TۺIc?~u`FuG+Jx?jd2jAZہJԑC$c! 7!Ì-R܏+yD+' i#%7 vO{>0AkNqr9nDG!F7u<Ё!D 䁛s^~o;=j(xp zDMN<ӝ(u*".( SSwc&A۳ $.њt/B,KQ&F@2 }$Kiݑ& zL.woW6 nE+`#T^,>- PQ>{_xAm{9NK XY&"HyQ;\5=aȖc@-_6Ӏѷ+ђP-3n/YAY"`Q 4 r3/ڱ9jBut5" .~E hrpB4seD=gk8')r@ڼh=hQ@;BmѸ l9*8Tpnf)t"pޚ1M~n;~ '_-/ * DfP*D cQsVH9YhC Fkow]Q;\l!6ݎs3Sp/Hҁ}B9}$3ځI0w`έ Dh5-년X`uAg1 g˴!SԽ|>+sx=_])TQ@:tP$g*qV0~A3`h+ c0,/T q6e ^B(V#v)DuhE["f c{d*P;9ik6"A R(Ec7H騨ЕƧ/J@0tkh>mY b>MVT%.\t6v 2UO(qy6/"K1pq4br} ?xc$&a&Ok?WYeNSy.4-Fc3YpsَLj#gòCe 5h,$:9I3S:@<`BAѥT*UKa+E,JZn>{u0ǀX5ovnDj!*mם#2MiՂVB+o^/8ѻ/T.8,8rbfvh.<>;$  BVY\jق(1|C55x7B]j ljw4(:CL@k7/PEs!۠7"#jcp{vGpP:h+T;*Z7x\V*"R$;3(\%xmzRJ`3^n]/wms\nt6j,W8nyDnVJsZbue{r]xynn8EZlUTU&|tZC,@dyv8OלW"%x:0E',PZKl8-ZB}({[7UY(f0wQpZ_ő-{/gĶe NA;T'@ul@:W`4,eۅ mNġ V( nۜ >T6nSl 8>_QTQC“OrGp 8G\^X4(eV=u6.a3} %,ay2>ƣ|\5TٺWI[ݬyyt\0XQ2'S ^ZQO6cA!F$R}VA6hp:t{PuZV,eledRHו%-{ [yk֥OE4VlYQDj1 x;oQ}"Z!uaQB# ӳ}-+J`Rap7H};56rcy<O )w>mF!Qh+p{+OD ] b] m__Xzaň-U0f ḱa>m̄4)Ft}"=Ko!z}8/ܴ- !(1o-"y؊F+Ws 2nw>a]  #KQ,Htu)ӻ~Sw˿ LcnXI=DRx_ի~~~w|uG{MqsǞ ]'4>z=yx@ ؙ+*: 3GƤFT׆R7%B3 e~Ŋ"z(?)-P %) (vl-Xr{hœPGxINlC` @u=l ڗ!oX c!Bo gàQh|iab Z8&i‘GD؞$>&Q 2ctY3Y@YBKA`ѭ༝€hz&ʩUCȍr3-@fvkl%ׂ-E+I]bpTefM kR1qKVʊqedDA%FjXl9FGǛyC  5` t +pyn]тrFO5/}F'75Pא{ph=aNxPLHS4#,WFP@BEJfy+7qk2Z q 9n k0D^K>vSMzy9 YO^.y,FY>%gζlD5&Ļn"ڪܷHi >K&q~vW7 GuL.arao#&n|kRpZʅ7⼲@}H*KųV-[U|Q|[Q (,uyD1` OuT;|(`ggQ']B l?zkG_~@]] a}J Dr7t7H!c#! кA֍]rGs> 5Ȳ?L̃xxk}%⚞8͎c7,w%.E+DX ް-,R 7 Q7Ɣ!fХnHg>,SP(2qwa]CъD:Kd 1ZuNx l@NXi%L *Fi`*f,Y| w8©f[774UgRXHnm6h>]Vq^ E-ejE&3NւBn!ۿi,.q=Wk XwlHd1c n_G*WߴTʵ 6+] !ԧ`[\;dw,7R ?}Z#t{\nbTIdlFK@7dH-Uw ŭ9!w%f;ۉa' $'VDˉ[羻H*+SGX1ѻ?Y]aE`ТINav3␻ _z=(dYPӉq~srO'=kguB;N<ѹ8l,*XX5n0h{p2w$IұWh6EðF^|(p?Xu#C\,$DE k|>@:lY@A+ ) FlYՅ6>HXI"J{#ERπR#" %ηw)!s .`r݀yRrmOÓ,,U8cS1vk;^g;{lXr2XA+73Ӄ+*9v]+J0QWshC=7j'̌(- ; Qa> ͳ#"_';/{eg)k1ZЧ6X \gWF9u0D*c4b{TX̩F4Ʊ-4_4A EdHÀk9N[V1FXd9Y>ƒHdJ{텅Ewa E .4!^\,B@&(Zuy@]KV>S:} J夓`B;E4гX)(9[vpTh*a-k^=$P9PAY@F>mJx >ڪ1S6'CZ5mFfeݓ9cADXSrc< sBh|O!0fw.@t.lək# %`& \~vt 2~-@G% "'i9"!qjUl g& G*>f,Efw>EV7 ͘=d CzT~VH%|$B%ƭ@< +P iĠ(he`e% Tt&< k d0-5L1"Ic6~WD,lzl ͭlaP8oxl`[N畛*s>І Vf?,ϊ7NKPo͹ST y).w˓ϗ@5d>g"pTHH6?P/yplzf^Qwϻ358.oHg?J ԉX]pˎ>t"HLX`c+;;P1rү+DT]25Cj TQ!H`P"n1vRdMZ8 {o: A 'X&bhǎ[#0ߕh% Bљȍ #uY0ցDhRuq^UWh-$\掶O2jwج׽j" xl@s0}[d9]8}u=fP{7c9am~Hc9man6x{*%jAAI+ゞT3zJI..pY} ޱ+ZX5ĥ+t,(RQK ;@5 ?|15PTf*Ze~(f8RCŽ*w;K{dv }$qO/7^~+d\ #tfk)"cjC}[c- V~O{njsA17ߠؒg_ 9-7  X<!<(q*C+j9 PHk'rɁ7Rf}JZX@c`;n˕C`-xw؍?~mǫj&a]lus{cRp^ oKIrl1 l>Eq^ mE o79'p+,S<}kCHTUS+3ͼGy7@slkKFp|u3utNpW!tD=F{@1>ǻkp,J) 5*%XmXV: FŒ' Jym(h~EúčP sm$7힠++b4 'p#LbEEY<x9`:VB`{#jg"8 [ax|N vM[\wN|Get%={19a$Di0x|mZ|&잰5.6C@hYz@3L;_3Ļ.\c ~xQl8+ L]a]}8mkY@ي]RYn=CN,4e"_}Jeu*E ENXED׭ϨAe}ATIPP8j lMu t ZVQR71sy4HoC=Q,+p}Dy m c)+Z .lb6 P w D4PO> .9~%,8yB/%P;;A@Ē|4w,ZnPV ց@~TYl')lhƼYTo}ȋ GYNpZ_.ջ|=l)Ro֨x.c3fj/ŷ|{DžNn^Ns2U}3NCxxm?^cf8Q@ԛ|w,pp< TX [Ww"J^7 *uۛ༝ß $hg~]EֈYѪJޙDAN ۍg"J3(J!_@ƈ0QHO4')OiP, zBMb>>WNăW~sHvG#" d.bЃD9ղ`  F[1 󴀂:l4XtFd.6xFRg%G%mK9nakOy|"qqD@ϫϪݒ3# 1=ѝfDY qM+TUL[Vq1bwa>sC;R(`摘ȟC{!E7ȌksWpi'w̶5øy1.KQ|ZJDlSB"KQ-86ρ[,%Ъ߽B.fr]'/plDo(%͢〢wwϻ358>~YHM$saXlx=Q@(N#/2YB}x-3WԺ4ĵ~=&f `Y1-x'#=C@k F1KVG 5` .`.Bd0#٨4] w@Y xbqހ$n+9I8h" 9l |YG]m{V$ A㇭Fd7]:fI 8`JXc^;7?G` tYB:(1^ͱ.P y^[V غʔBtq |νu|T'ZŶrN'n8[ eZ 1., 5,[.{[}DRkU <ޡ*xy^(ND8HE9I<"c JM$1C[^QhIzLBG=4+ƞcaDǠ9QӷF>r|\ztT,AD Wq O;^|"fʄ%#tjomZ+[> dCz:wkHx˹AقPDzƢHq& ,IQ>v,i6>܏bE#7Ub'o-Z${*ZhjolԫiM)}}xjBNEױ R P,-9_`GyB!G +4I_]qYAOx* 98Բk:c mhpqּE.k=>ct+,(aRpGuK!IX WF1 [|dw)5 ڼ\Ǝ))NʄH-PEbt"vkY!sf;J'TZ~,,,P h^:7q(+7HB}=x_Fdzz,| ޮ-Қr!^OKJI*dA"F^|@961Bn%Mg>~{ ǽW i0ܕE>9H c!В(6_" M;qZ4h3 [ໄ^-0xǀ;ks /g[#ExJh-h43 uݧ ?ӄIK]Kѵ>-ws p'HĂR]3YVtFhfjwsuؖ!6,_1Jt Eׯ^ ̻;HgZ0Ga<- > ~GE2"c8ufEr:@qDi6 Y.t3nT(F,JDjz M#4-$;cVVqhXA@-T,G>cB#v$yPvVV L(VSDw+cqNa\`_wG [b ">sbh8\1R!ک流<! A:tT^yn_Gx1wԣ5D (NQnY:Aml޴BV-f̹8g-Ll)2 ;H]r٢Ep gPr$?։~9B9' @ [ zJJ-;2Qł1#7 EK卯ID" f8wYG t ;vNU qF*DZK!K7ƈq/85t I-,IvDv#PU `":f+aN@=FV,VU&t{}8` WR=P& ?B7럆InJʆ4ul[XcVΰzX  ܣބcn79o6sB/[C4BL_XcC¸ԝ1wȀ#Ev0&Ä^Cm۱_uLt؍Ƿlè9xrs U%^_޵ߵ#['/^>ðn ݂Svl_YpibC NE+J 廬.繠Z*@nЊ kJ-=xkp=:j9s' WVVr/1]'l?.qL, 1tcS7qWX ΂ELэ;µ3n`L3Tw"5EE3bBaU$*(&BD^ȣ=I q$l#.GJw<&c2Yv&ȑl3dǍ O#8DrTGX%b/$/@3JO3;!"#Dӧ7قRqTF1-:m_(`/^#[XMsm-n3MbxP9cΨBQQRBɫ%rv0 _Z$R5ZR{z\c g jƽf-ns.O$orFu.9eJy [Nt:gAÛ`8SX `MVUhŨWw-wWw\#a4ڟѮЎ;S:[aBhImǰo8W#L,٘jDD89DfK`{@olY~>'/UerlBlaJB ,-$ē%02U9(dRW5*ZŪln۩܎ЩZdG펱7ǫ9`Y^P|͕L&犤B,hVپ7k*9UM@N`H[{X7jC1P}0l#!s$HK }(MBwp냔^Kf9툑hcyVr Ũ&x2r O3= KZB!&m⟌@hO$@ˆ@ƜfT<ݭw[ӤD %x5qq. E%(-R`'J$Be-߳: Uw{@L1eVac GգwvZol~c;6:[d*9_(L}ctnlvKѸBNjzZƢFE.>kq#W gӮO._d#Znmiz\`9$Tph.ګZg>FcVc؞±ڝ-qoN@~?i#esdžr݅"MRY)LU7vyNsgQ _l:G7?8F01*9~c6\J#"~cx*:G8L]pzl}Я)SE/>!KqtmZwr9Gq:?G7%2'Lψ::8_s,{L\(u5LV5s=0mvD9r41S7xg _yHkǹHvo>W1 sr9Fs!grJBm<.o]9عPhɊ0꣫CRS PV!lYE@L[߸Nj)QP=Lh؇Zk3((~g{gM[CAgX]7{R^å$7wsDTT<*y`&'[g1 Ѿƻ aO_LO]4^Z1(K~ʪeWkE{ĎJ"|pm7.O4}WJn*}մT~^-N{EüAqdk)ގ6v)\ *\>"x|;ޜؔy<ngԲ SY/uo$vޞs7G9Gz\! !rfPM-流,iM60Fѝ7nl/N u)dka{'alc$M(QYBqLhkZD[{6;Me!%/}O3X<],d ps}3]ĹNJb654Bͩo Ǘ±~,˓%Qv ZUBҴ6IÃbP4A7|˞"iG8\*QN$h?6B"pjc\v1i,$r}` pvwķ*r_WVXR;qx3TUJ*tE|Yhk8mI46}Դřeύ,5y?6?F?6)k*>ױ}ܹȌSӆGp8tχWӼ3UEhOh'}}.ݒ .䥒sh7/_ganԲPl!RWJYȹrWR^I))՛&o.+9eR$u› wqmcco EsZX3>Ӟek;cN䅚*5/O,+o__ E[{g;m ֢6CyPEZ(hּ(6{ID{Xκ߅"1q\Oڪ(-娘4U@ee %E[0T;*&^) :8HsGuDDܠ 03xSHwmJu}'YBɕ5ul;[; F FXʒ.Xvee- n1QHmㇴx>}xw|k~8>.ߜRS߾b~&Hޱ4' VWR}'W5+{^йϰ?cO?"dmx9^,R?[!e÷Y7`3e 'Nwwg C}? h&7KPԊvoDu=6&`p+jr #kCӓ`}r.Sעy%]RΥ>0R7D7 EzEᡔ5.7qL6ʥhc{=y^N^,iƐ@I2?_Km),r;gLwWKUjY %/ϔZNDmRdۚ;>Ns/n}?XjcB0[*>%9,!;BkyLϰ|aΧ33gďT˫j鄟'3zb1W#˓),W }ﷰ(:<? *ļ%*sH]ip`;ݠDɩ^76z%8Q~[]%5v1=%rdHh0\LZp&l?$#Zs3~Oi~Ie6{LNcxΙK-bs2u~?D, 4Q;<ٚۻK=zEm;[紻nY-SesFFlLfTK@q;G6$_r<~M$̈́85 ՜nIhyCh׹5|h(['e ǿCeZ 8DV*#Ԉr+P&RکZ>[6"PdEM44E+ċ}dJp9/,Ih̒W&'R\gj6Mo*Mp2$JiD *4sxΆjׂ^ju=QdW'=r:M?ygQ|OqFΘ f(KI1=Nr4Pl{PcȪ@]L MLjŷS&#+:\8B3d$gATD2G,6i%b{qd7wnXw)k^3I1eSXAMaQ<Ɵ}p'p"TZtrFhr[}:Vek8hP;hF 6y&T߇PB1׼5H6>7>ca˃*lKp!T/;-RRwphώ>d)-ED<3:mcd)nQO¹Ex [È A]cbC9Gz)"͛!x֩rӠSڃp@-$p8t 3EK)=~_~_E?ݝ?G(O S?Som#!땿7~;wC1~_+__{W#OB|fVȩBJcH.ٵ}cx[c.,ѮpL`¢5<*Zi]}#\hҬw3rIZiПxOYz~&2K*r߄B.p0zR3zHkhRT?oRFmh7)eZ L-c32kʢϴN퍥Vz]ţk^큾$Tz,F&qY [;xn8hH ]^Xc|&l`΋w {d/Z ]£/[H{k;Q,|5o'^$L:>孄%uH8I˳0h7xxy׮\[\B-{,S-g6auvwۡߠ7/_p^gLt|U%zӘ R1}bM^sOZv;iy<1Naï楻 1xnqϮDc.h``h;%ꥈGXr $Gv(-X`̨f'*Sf`􃵬I9^$.pFdG.t[MhwwEѹTfqvָwg]({5n#ك1ooο+??;ο7 ??Ȼww ?7?S?S[ֿݿֿJHmp),n@Ը$>%h`` N3O7hOr=Ơ&)<i 4h$>Q _`?IClD>һ$L*{.lQ3piEܑ(f۲lD09\,6vޙfiQM0cz̢R{:(hfh2ͳ,8XT8XB/)`QܽzOms}hcFF 9ِh[*#г;brO'8Ff/>%Phr,0e{P*9(ȧO.>T/a鱑JU95% \l\w#yz="-PPSRH? CEsz`3٧cZ) 8̡>|%ȏOv#V,fVדp?z:fW19cg@S"D^qdŪŭ{ <77gɱI70crPC(2e25z 81T8^}y)6eZlGsB)^){񝏃P`ݖA}C4#]B9m93 s6bEyR TOEwt&% &0kZ T7sXxBtw!QMdc`86dFL?ǯyo=u]??9w~O$??}/wu>1CmwrJ.jZJرPTo1v=UJUѶ Gx~E olQ4Wn-RJ>R"V-+v\Y;q,<wbwf K$}Kb׻|1;L9lq{OBINM,54\ M% I=IAjEsIbi:X.v֙&mɛ-^[jmYYkPŕG%5:[85&֚BPK 8djN%q)2O)|yX{t(ȦB.g6Lj<,PD))M.nwŧ gV)R`JM*$zAŒh:}\9&NbQP+͕/ȣuMWp\0-̖<ӂӽ*뀬 iH/b~s?"fjQl=(OxyEڴXLlRkpH;އvܟ m_FT%UeĆis)8}?7j^5-c[|g+\ Cl:$Gpq|tm wr='j\tYY):|]U8yۥKCr eS۹Ѡ~k$R̻#Pϭ)Skw0KlD˹iNc6h}c&Zvڸ0S%!U<?Dq-SSX'$ Jڑfxv :Of )vh7eߞ?~ U]gݿ}[f / y"`ia!Ө%7dF RuGO1rp88%q䝵Bj I+,ڀCV֮,76=Ig+LB\#=!>C7w~x8ݺmNVu{A(b.ѱTAu IY:OIqS aѢ 3(Y4_=LcY m= :F""QRlzctLY3cN.N: 9tɕ S ][K:99TLP񼷣&3< HݣGFqN9S|nh2bY*b41[홭̉qU^bd*0~5w,3RhUm6XgN_b\:S^7T?_~o}['*?wOPo}[{_y__t3 ?O=??%]Xsj߃XK51RD5! }N7;7dPdRfF8B$wJ-D )+4Ic-Tx&* 5p2tŹ z s< Kx֢Ӈ<:=_)%"ۗcׯ>l)d>gP"tƥ6ƴj`&kwipuMJś vг,Τ`uNvZfK$x9(%@`IL?;מl׿nv-Dy.U%hέ߸u12-Mȥ]Ȗ5vozllF/Qf2V *F\x(F;DZ(%ӬJ k,9IC# ~ߓId2=9c1"ǥUd)Zn  8lMfi"H-7 * #87l\ [e@]<}8D`qVyfSwɐX~l1yRxizn9..i9-Q&8_u^ Ŧx//8jk(yX&VGUNsE!|>_ms,ZW%A!GLB/EfE-c-2*%BB a Q'XkV;8rFg -c U koB^(f+{`:Oݧf"?( ʔt0-ӯ Յdjs"%E8'9f/ԇCm3H*Y濙O?}?8QkO?__/ſȿ/yy?ǻw"뺆-CXW) } m'i?q!@zgfElvX)eMVN7\WݬVOPuZ<$J:Esdp2hQiۥE]ݘD`j<}fI آg<$R!3 R|Бewsk[ s9I%).U›coܮ7s=^̏ԴRL<ؒ k]q>*Z;w/[W5.5=39NVL"~ Sq"eFz(}nI}zB1$<7YVܫ,LݾC:^v#="<0Y>[m{BJ\d:ahRѦsk,0:Kf]3kJMB'x*˘d+&#왵Xa]Fk U\^`vWٺAA=$_<(R.8}d9m=*< 3߶u#V#,OIٽtW7c߻,Ps4LR٭[ .K =>Fq/@q 4#tn=sgF;K}d}%yt$(,BHFp}H]&cp4`ǝ´:b^0PQc×-_sǏ/y_ |k_7?O?Ϳ7o?#?#a}?G򷜪~(o[P>#/8.!U [\SLPvc5~c+ U$A F7U؅ٝܟlZh\b~ Dut<^` 2U~c-K({!8n \Cz LR3cxq4awx\1q| Xл[K2jA~\.B yirTv80~R/HU˽4.ݝ~ Rr rυUY7[s%Q1$seǝ#KYݤ;9).ƁG5 i08ql#63vO'>3qW1Ih\IcM+%7,L!ڌBtG,i֯Bld;#ǣVܣaްFtA-ZjJoϤt/E }a9 ˏ@ڌ7k8ȣ[?3?3?z'?O_eJ)?N#9=?tkڿ{N呴<8}!v"LJLJ^p"қTR kqP%|2<#/yX*ee*nX{#N-'g%/hNLX *"p=Ty h:pڵ(#LsfFGb8%],ˇA /1{Ika rC=Ss>_b5U:$꫘/"ao7!ٶD'w@L4 LiU4#bǢ%58D0gJ㌑ו|a01qU8Y1o5?m!1CyV25%ݟz */[yOsX=3s+kRg|XMjMGG68nXn۷eR.xYb"ݑ-"rD1ou<|T~qǏ+#˃IUq ޔP4<]&r/ uUD>Ͽ!ӟYpVCv%5lx(sSm4hkU7o*`t>'wVS)CBw"S\=y;mg.jQ.V7>:/mU٨YV0+ksRsrzv2 :c^js;:}XpySłb cD׺msQ3娩]yio.˘c rd,VXJ/_B0`%kp-Vv!D>?ڪ.#Zj HIj$,?`K2{LpDΆMe8xs gi$HeXS!%6L.E<<YdSLHSmr6__?WA26WznKR:I.qh6U RLJ)8xI(]4VY ˚cg=Q~]ffJNٛŢN݄L@OUš*!TΝw*QST,# `W1}4q1!#Ksp\ҽh͛h=څHN>>ǯ_l+ OԲH\ʓPpoтoq]ғ <3|j> f'uy:h'UR;tnI} ^V@<0ew2+?.$e8c#{ʁ%w˓ ф>}5D =P* q#s h6|Z[MqbHO BY,V vg1bw"Bg.EK &[Y?ѱĈ;z؛h%c7Y0X0> u[3d*|깩hoONhHyR);멀-,)Qr Nu1v.Z x+am1mfťt.q&[O:Li5tUJ@&Ϣ,9 +HZƖ)&Rs 2L&=RFd-R G05 q4|(4hh+?'lWC)3؎/ _c?܃S ^I6-hp|F.)(C;.WvD+ ,E{{Y'~>'#ԣ]gMD`9%!em@ ǽ==7H%Crrw8 [gLVpejpi(xrRLd#ݱ8[}C HriOIj7g l''іT7ƚI.\P/s&^ohC ˤP4!Dg,샑:sA)a=F@ ! *3mj40Pšϛ+--(@]sD4 "̟}ȶy5FamȎ%P"7H7-Hx+3 ~(wD7s{cQUQP P*}YAx$ y~pq9gM`#~̈ qM4YSB⸣ ?Lf Tq=fy2B6s঍W |($Ai$՚JJg]:|E,Oer\~?n Ii'|@Tro7>YX!wF͂gM;ױIEs rV!ڕ?}/]1(2fh% Eq;~%Y+<.CIqb4yQK^rTpj+hǴ;l6?c8Ƀv QτJJLlBñ3XO/*ks?2&vG]Da ''#ƭFSQk$,DN> k{a;oQT/,ŷłukw7qF-S1Q40Tc6~cIj k*'R.;)')tS1*{fs؇ l}ܨo/\]ϾpUȫ,bEi8Zբ=^RӏϤ#TW{COI,yѥNn`C-$ȳsx</੐s!RFcVl]jܕ'ekK^<ټ;`֞cr -'rXߴe?%})Qx&e $lmcYa-g>o>$hd#I ϧ0yg^P⭒:g!nSQt*hkj>IaxNJEb+vΗ8cH7ta ؜hNk3Ja?_&a*<\KX}i} !UNtx CH"w.oDIq&ڕR*F"{p: LAgϢe*d{幕̭ɼ9q(%bjgDtQ}[|k>nF=&Ny%9 \+;?@1IKwֺ(aJ\|4@N&)5iaMdc$] u' Pd6`lʃl]baa37)w2D`z q̨f5){?xzg.0@FbY?c`s r/Դa{慚|3]A'0јkZGEmg!aDKJdw%cxW^8HЕMbV fQL&=~Ua}Îk'2ĕ+V}Î͏*x_!eʂ7l}# Ke"K~~_1btyi#ThF;3ַD4Ɂmj+Am)sB٦]2Ssx!7D,wڱDt߯ }S:=#5YM㴩9G)|_} .O|aŠG]ug-",WT{t熮Ni`!`V&T/Hg^J}TsLȿ;Rek5BvF;gb=?/9_?رV,fsd|wG x, @ܟvASb;o&T]j9'e + >VJn 2f٣PQ*0J8Yw89/3P}xÎ[C*7jqy v f$K|ؾ a' ql~c;5j/ƠRSQ|IP戳ljt3Fbg3q)l&LIˢVKLNN.aћ!^U,0N1-cmP | `egR.ů,%8܄U.yU.68bTKBY|v`!1z0kmTc [@JpA YuX㠦"W>qpٳ|=SrUX<d3MBLmZ:i ۴JǔmYcHMF#wgvcBWgsBc0Owm0՝mqNKM QShl۫RCj 86t9G܋#,tA1&?CHxa;,w|50 ({m#Hþ$2 nI~yH-cMJʾ3|xb%E ^XĚ 7,Bkbr+1ɴhMN;/T&q!8- - ?vqՖ0aNV@c;1v>~iv1Wjda&`wnƒo(Y"lNJ QM)ՙҽs{GM+d_kgUDfd1%Є(R%ъ,_W)69swNDMk-wus!u AyP</jn^7n‡ˆQ+cV=͆668icF!T1Y4"Nku55;QʍOh/:::d1q}4 ~\I{rA1x}P 9nbܬw~[f3Gvgwݻ5qoC8XcAN1 }2?;^0}p >}?Ǘ--oyzbÚЬ8䈕Rڱʚmm~0Y[ ^7uZ, %Gvj^ȹҏ+)X #4Ny!%g?^Xhdl)'(nȴ:u,}K^6ƭB ɧXaɗ(*5~_=:; 8{ȥHzN㫗7 @MBּHBʫp ӫK`!\QcRcxe{A8ɋDE|D }{]=s4 i/sn1T jexTgk{;}~L8Ksv>ϼ-&^HT*iḋ9p| Ey^6aQcfl㙯,_QkH4 *_B"Xy`˝4RQhYIVk帽hxaG {x}S }$78G. tEv2#V`eŏ+ED[VR.xQO t},8<ց >AWH>=/ib4l'ْŐ{șe=G볨Z+mt>Oݞ))s)k6MAqš3*vK~=hFzP,qj6ºjn r=h!}vF+|hHh@fmsYeer7 !+\"fŠL! e%. ~hs8sMw~c8&nE(E5;4 u0F{=q#b E*(O(19/1ċXj[ 0rWrsS,xݱ0㔀{cLoo`NdCAWw$h /gan0ÛlE,IF5؞=_Ļ=5ɸGo rds-\qkG0=J`${B->).%hT,#1:fI/ N##F3;7w塚NY$ 8[yhqPRB"{WxO KR*z q;Nv Kx}&g-Ub!s 1z`lFާ)DYJ[wZgB ߐAjo"ME%-vfرKLMYO"\C?:e)<; Þ|'K>Gvi>7 '?c e 2ƊBprΆx'$=:Fk[AvZ.gw7n~Hʙs.9S-Zz䔨{&{w@Vӡ 1llf;UV'#Ӻel?!:P eYB|Nь.2a#H@p~ %j4luķ]*AyI$1-%džń+Tu9z#L[(>6w_ ^xs9P];&TGglN <~#̤;mH1#箵?0PX۰`h!%p~N9 z28؎Ɓ^D@r189|/I^I^閩I^~-6#,vUyj9P.>.knGOpW=6[ wuR=)*6S|V0'J,zN}"r3E;Hb4-PRdqhq0=2"%s>g!{!)fp/2o> 5 ړ/e_9jhە~MY=X&w϶}+jP2DYg\^I\/i}#{c?[+,WL]>Sl=lm6F؊erVI‡fuydo\mlɸ:gjZYʒWr~7wycۙY/\Rs T9 Ct5z\yRp ԯqگZ,r `@azk7Ґ/Y<-OX>.oy3$%mN;b}<#cn$&CiDN͇ 0 !ϼu&3sf OxMQ1@͖bg#+#dhhjK-j}XusYѸm[klMf@L_;׏x\ඪ4AAN)5V% uYʄE͠-K^ѠEQ]ﳅ:v;9fQcJJ|<]VH9;Z>vW5eJΤ"rkdKXjLʅ+%B) y⎆CEkg h.AeqO?+~9UҺ>||oC"D,%)z85PGT~`}qЏWhg 54sI&@wlgT^~e._'<)n Rq Ig>x)%*]W'gz؎7ә\PU-$yMA5Obo?9+u=͂GVodr\L3\gon.-ZL$3В>w&}4G][ aZ+6þ1hcYz 9c13GrZt;6[/ؐUq@fH蝒 e;T΢{ ̰ȴ ׬#k2_͵3'AF ߰KJ{AYew"x"Nڟ $^ج s}:x^G('Cxs`8"hff/[ Sׂ ظ抪;Q{ -y#7m_s 1 ,9ƥڐj8bmcƀ>1ڹn@ WY?be!{"kY2#!i)Gl}G',CƜQ-'¡o,`,0-&uixv@UP2KǢdHbƠXѢMV,m %9`F fd1@Ό^Gjo"/ ѽ<;G+<XFMkٱ{|3ܦ9@D83WuQ&R8.(9Fq5N:ctEǺ!z:yYSǍ۱V҂$/"|Bڲ$>AJ-8N Vm"ctE)E ݣK~PggF2oZ#kP9M~Z KT>hO>$ZǕK8&(X~]-_"sp߯uwq+_DYb(?"֏HZTo~[ʳ),e¥V/ڽ˗h/- wnYj~pN#![(y% &|w0n!(9R!ʒWj^R_Y>!NP, %WHrtL_,oL +5k6"nPQJ9ujZ:sJxݳMr iδ@(<5~rvy(%ʵ]y7["*Ov=?c1xiWw|Ȑ%8|ʷo_͟/s;q8ġ˜6%-,2v㫏RPKzār$j.GrCBo$ܙч \d̸}OBnh7Pڕ2JC\D+ֱ'PamF^|yr_ߑ.q?7aR]B-Jd9>Z"pGiwTu;( ~H ̸RD۽2\xvS3NqK,Hm?omp4Nǐy2F~kW, ~tc-"*cs\ɲ&jJ|q@)p;v^ڍ;HjSZ5WGl>`TY%_x6ēwg. =n~ۤngDAۣ0T1oGPW(uӪW.h %kYw+]kdlvG6,*^HR*x2-3x aʑF 5G@t\Y5t&uA%0Mkxգ95 W􇓏Z`h$ҾSM$kTϥszWVsܽ헿 Yܜl}vgKrD (ޭ 9_s{"qF>d*K%d1ql}l@'{3fBg5"YYS|e ޶/hd|+Iil =j/qc_>+VzV (gmcxd?8֯C}b,报0'ʘ N o/ٞ\48Xr+wVe ( _`U X|F ~Jo'8󮌻c7{`#ww[ FwZkZgY쮀TXãccs{!eC$V`,zX|}c 1spC@ytUfc}+auUrI}ru~m+*%f'*(2fΈ~*z>!I aYcj!;}粬pत?m& q>14`y{>#TZ2q;`+0|dPjEK>&{nȓ.lQD3{#"^ƀ14m&֜nkL_;6\4<8P >˯zwW/߳GKѪE"]0LN\6ͣR">b5^.z:Y3trEuZpԊ2 UM1moΚI RT Kq|L/1O^}-ZQ}!ti]ejFdAV9/Y $Q}ˤ1}]$"jI ɸ#Vc$>9s$ntg[7"S_ftr7JNBpѭ{|q̓4,g}4;Ù=:q:jƦe'}ٌyQ.-3"g3EtgP l,/k(IÔ4I0<3ȸ7!6Pb94%}x]xnE9E)浠:#Rhh O34Hwnf,Tg:= g"X߄"xX('Chh@-5#EYqApՓ|0mxnF\jv B ̉=Dc"_<=>Duv [(E\/,\cUP' ؗ5#+A}hTP>r¿W^>&0ErtRy`xeF+E!Ty^ -F "`=nj'ˤ$R*)%ㅥb#)W;sl}`) ġ r2 ΅|P [G7%eh ֺr+f/nykJ79KKRR 8ƛ3'ޡw혫&]eQ.\rlN7> Ax6xJkB-TIZVo IY RRqnJglQl?7rӣ..QP,}l>mJpRK'j ma3nϤ,5 %'45GcBtwx/&*sBm8m콳)VBvZ^!..a)@kO}/I`5S;䩚&̹1neh;0Xx}u7J P]u?Qjn\ە/QBw yc6o;OBzrScRW1G yxe$)?m C\:u^кO܏NS;?~ /[ GI %qNa`h_I.;N︔In0AeWgr4]T+' -#^jrXA(Tmҝ΢t!`pͺ ' !Pf*(1{-;;`O@F3(sqNcaPAHۗ9Ed$(Y-D'r+g֊i} [ #U*sEk,?yׇMG2O(+46%-z?YՄLE͖4&{ć_I(N,x2 ?[P~/L)kzg) E!ڹ*|u9( 荄Iq;<6C-6gx tXUyM'akC_J/fv^W򂧻D/T e1穲|.2pf;V-* A9GTXx9t(@eP Wu*,JYo>|7V-1vJ WI <blce잘SQLj֣{XsNI-vqP6MەIg ZnJI%yCsa0w#xv /.©@-쑝.mp'/K>dǒ=jnKUmr ^(X-ñbn5FGHz(F- wއ mQT7M# )a?,y|xb~E/9WV.7%>p"ն/ IqP+eyKCQoVct\J0>|~.O3ڍwD|&&Y9 f._ծ1 უD@O&XPJJ [p2yPouJͲwrQ$>)[Wt$9rP4,+m ېH%#$rIhqe>xQr Kg;߄yd K1֒CIpr$-\}Fpf ;O[0&|N8cǝh}5898=[cu%@8+q(%wc\jpoX|m*EtUPReb/gʥ,w#',f.U?zcwd_ +UeY5TWr;H*23%J |C'mR?ơb.Piy"oB`tY FjFJxQt¸} ]d.‰[!\)*Iޜ%0#jr83\v.biYK\/q-|,QgL.),Y$Dkz><%fHօm,dޝެ+݇敦klYs5IŌ8NF6.(7y_QgcsAk~YᙇRomg<M;+KBBɚ_hxdG%/•RYovq;HYӣZCVgœ7䣟j,TKUB} jRJݯ}uD[<%u+2EډZ|pܹ5|45tz5؀'"i) Y#o ZۼvT 0lwҒTL 9 K1׿BXif>S{{aZy,Kq%hshA0.y~}t֩520].̸NPh:7ֲjk`qJO9bl~0L)*!(7ʌpWtg;:B6X aof>H+0m%p,A^=wYh`Ewh/Z ANS8 `aK*V^K ' 4]v7>zRk}I6q9efES=6Ma hIFyT^| #Y敝I(s@Dr_҅\B(Js#-f.UqSk&x(R}g<fd\ذb`%d҉G%  *]A%yj ـD3ɞsOCT>RqԪ(=iTsөU8.#x5cC"FfQ1hMqpݏ#.*Y,%#i6͙̘SXX)PwzhFMmxsfu'ו26;NoW߰PoT ^dF$ZHƘo ~V%*6΃w.mR=zpR斔8Ր u;mr\jB "Z BGGG~FΉ%%lbH 3! !aI e.e%H6ÖI*M\!P ii#0ptk"a"~z5U*K3quٙmĉը ubPyOK17-R]KR"%82?.%oI[oMELQSF]g~Ǝ+nJ>J+{w9]ܬv(QNratyxeź(Дϝzˣԑ9D"+5ÅQB-P$߅v]oyk~MU)*mӭCQŃ@<@0Q4E@D0P(DiBbmx"X-Z4~֚yk>~.݆)k?kw|)Zi@lˈ1H#"L$qy_pP=Xz6U^%9& P4c^bіxO;]uޞհs6bDǪ.*},;t_YH-XѭZUED>@?+_ؔF=npgxk̯$izjX#vQm161Zy硙;hLM}aD9\D9зx*p:5ß37|~u91"Ȓ.#V"l6e,TR#x$ \IzEyarɁ֒q3GTrl |X*H~e997zh˖Gzoa3E> 跹s7u\9gDFw"^c]q7&EEV]i2.zQ'n(S%Z]pb.#,ܫK5#4} *n,{ t܁p3"e~ e^if9aƟ|]6Q -X`匵Ȱv5N8)a|fu `]>PA# ؜}8J\r|myu{;enQUW[ a{[K +H-d h63oaV9PC|N!L@ "cەCᚡ%S94pwghᤏ\Ϧ_b?rPci3T*+%=K217=L*~=*C03rYp #+H9Q.4zk`y!_QWgg>~_S_~כs=55g5<9] FUp%XE e͍nJ[ dTDQ]jC{tB#A4ʼ @fKma-k1 F0!8%nW޴s8B {R4LNst J\*rRyY&0!k#D8ݕ}=:i4ВWƑ(9Z  9 52U{E*+_I5(N"ŘT-<#>q/+s->$];oϼ;}C-!H:%QT̩4FsL{A54QT'67j}@hc0w4kc3 ],{Sn5hhID!TҊ|>]߼sݹ J/㷓HĀR&&n$"ƩŰg A-ۂjJlтLA}rLcy(~,pVE1Ies qyPȬ xqWA ;,~'.;Z3?N=^XC,n,̼-21Pdf,h9~MdFkûb!IORGo7Ɏ^{mu\8%l&3]+hf_YG,II&֋HQpE6кP);9{Z5J(8YD5D8Qc'"Qzί߄ע ,AO$"j®R)+ZR䚰#MɌ/<)\Nq u KYg=x@ sӘ5Ebs^i[a64Z8B+f)Ǣ'xtn6C w c)V;¦w$4GSpߊfԉ9ΘIH(4.j@#3Au *PZ#c2b^sD=_M4"P| MWzn7PgBAG$D5cRx$|%WgJ΃.G]HS-f}p4s:nt P8*C}`>;>;>(^:}Jd_&*(tlBvb^Ѩ&%]Z+&:Ȑ$9B>{$@Q]*;MQJCиeAJΟ#>t/1DΎ0>KjD/aKWY-YW+^3FHK6$ΠGV#.p+;3pdŜp+>Uk#Fc6Î|VNq]ާ@%b{\|eQ:64`#d"YBPƩ°~gt"+#BG=ZjEj\F"wscgPI6ʊҴ0>{ ̌=:6K]sIO|G!=ײDty;Km4tɌE%6D AOGG5]'j=RJm#cu#tTn>:NQÜ(ILi jK#tiP %#Qi 6,j(w ^̻w #cCp;53xsWr~Fr+E!naᘚN{>A9ӽ{7 N%s@e0WFƉJ堹'MvB"T*G9?NHX%_˝-I#yCj0Sr.O4 eVJ*IBSrC3tHk=P1Z *xxT"U5)#p&x8Nc@ܳkk'w/pz 'p&U{vR{ھZ} "q7n^?׭ޣoWv)~F(j8_p֘LjTP[QYiR4GF -N1E,Ndx'ؑy+m^9m_P 3^gT1†%'E^~E26F{lg3jAGÂ"v-' Lah(} O煪ʢxR3}Z&rhF#w;U0}gSs#ؒ+o>r:I5&a⯖Ù·k%Ɉs>3j}Vu.]ę= ̌%L=3֏Cw8ק|zh/49רS6GOݨeohĽ=Y=f#;%I< 16~azw:"b99L̕|84^M;@3=F_!L\3pwJ߰vFP@G-%].₩~dO')C4uIG]+fyIȧ!ՁEUZ"rfߏJ,1-,B\a=0lg$IvC+ '=;Jc{ch.Ϻ<Ҵq{ [^h"Ic|7Z~|[LlZFDZsmN?'OА1ty")d.IWGu85َm=ԦD3вN42(ʑeER8*x pL$ܠ a[,9pź e)U4 gΤ\xoK cwt#g.Ξx4Ùc"#kyAqvBcIݏ+[[Tx>g.Xj罍C-j+R!)  Ջ]>~ؒN2~!/߉D+Ζ=5Q|ҰY?z =4|\1 B jXNN",xs^~u; Lf|% \I +竞XH'z86B-1$ {,w=ڼ#<'&%gBzp5O+hQ gd 3D=E&nNҘ#Feܯa\"r+-+blc'T=ʏn?[ᶷqei鉦wp87q?g'#o5~!ii@r,8ݸ1Pz6]T\ vjYÈ7c۵ywJ)m " A<@_\6J=N%{$ϑ uo}?;OZ@ &U{ՠpdK+jdg )A! tQh8J ;7f*_;fu* slr׎ 3PZxp%=nEC_ȿ҂ <^t<~JSP14,*@fÕqGQzl0Lx2%;bAJpEGZ Q!8^Ї:NmcNc^eЯ\vqwtj"ñ)iuqbp\;cCbJ$hf"9:EWm߫Cq8搪; +5l866|"s@Qs̡U$uB;!Dp;"NjHC({|Ga#Ēu)W!!e9T*AxDęzLr CzP_]8W$ b fn$WRgaAy#INcG0pen\Vf4`C3`ưJ{ӹ4XC}KOO4:5l9.m;M4m–bǔlH Q#B"Q t <7e-P; *$+C|Ͱ=Zdq_\':zUAkRǿ MC^J&ȉ@<4ǕVmz@ܙLt ֑ÒؾR1}ai}DZt:oTEFƜCVf,߭syib$17ޏpU >k)4Iyu^9z /;Mac=50ܭaF7ji?^`ȉ36-8m ^q+a'U[O̅1wXj3?J,h靦{0N8tFlOݡz%N(q*w̘Kzr廍4]#ȹ0=P>llscXr{oW(?LJF..{hhG%t&(4oc";v5 J\Λq/Lˊi\&)f7{j u|5??9A =p"BP>)Q杞fF!$.Џ2ΰ-ӋüW]6 q>J<ԫD=nPwN:T’\J Nwc5b+R>9͟Q|GAKR1] ()"Hȏ paQJ T3l{;6<22j!t׻CKEn[^q! )Anqfkv yXmH=е8aKx|cF6oa to?M}}6-e/ex\J>0u⁥ưqIj=ꢀf̎辈s6Q's J߉JDM62.eąB Wk!緑7_Dܣ0I,R -t!SQC^;!gshg5O⡨Y0XiZ-TxM>Z=оj*ꬦ jtʁ͑&z׮(f*1~KhS`c2dKcڅiܨLZ#="f<2R KfdFXe;^ιh0i`4$BhƟ"\BӲ6/DX FRx:PRރ33*Q RI&ll,!4IW18I2A.0${3-"h׆pu[Qj;b{xMC[e|5_~>6t/IzRJiqLzP qh m^ROQlT#ʘnF>-Gk&,9heN@goʜ&h M4O9% Aq核Ɓ"5k5Qa$̀ 6yeNevw*6R2-tca5A\J[&q0`bSwnTGA3DvZAjd_E(5uN`m;ui%QH f~$cǗ;d_o5u(0ܔ33ڬ{;b/>\bYʧJˁoAr<:_G!;|C+8KThp8H x+5Z"N8NAăfV;Fw  Gq;a-3*Kf3r zBs꼅0TqAǕq{e( VcltD/LY"SKĽآZFmdqZ žM;XL %B=!8*52vo 7 *%_wEѴ=kGE1fԽ{RQ%#\<*77w:F߮[Rpz܄]ndr/H٢5usfx3 ! _+}"W=P qԝeH>esVP\1;4TJMrx'&" G%,)6fUK PN39N S}U=YaU’K-f 'veF喈s8~fEB />9B)Ppjj`!{uxˠP=w3qy2^YsgNIOFTYhl{薞tHK-<8ةB#UBq PN>|)LOF7܏fu+/\M)39!բ*qϜi>s>JO)c>\8ɤbxs︕'z}b5$jGt69-sK8cTbhqhڷ1yTj oQ#8OI=!?`94ipQpOƳchIt"!탉0d5H64Ӭ$U2i:6^~ZQ3}xFwI3373k0`L7 .) Ed.WyF j)\l措Tnlѱg-kωhRD[9ܩ>)%+/xcrX`ȼ8CV4,pPj KwLVC,J ?T_kAÙ1"reLz-!)`)>TρYԲo>PO CWplƲ!ވ -XJ) EW.#kHcdUPNHV%Q p<03@z̝mA,ɚhP~-,퉑o#Lp]YKp=2W)TnTGmkf9}Zh #44wN-7cfdƫGTYk p:&> 1!+*,5AEͿ=teÍ{/5G󊴇q#486h-Ѡ"Im_x= > j {|~p>(##j4}D KemniOtYmCGQpRy6R)*̙fՂ"W]kĆaof-:Gc3-6wdv'80<4G^֨F+ !>AlǍ2.Wj!!K_*̏oe;uXF!ېЅ>b5)z֒7 $0Է SBm+PC/"5~}+AϤUR5vs$j}.!}R-AyF+Oh[5{&2!X$%"B{Z>cd|TtM7rd7v36:AY?޿Ie+}h;Wo{O=&~wGϯ@5rTNuaKsx<0:`iTWNeIP=%?δoj^Nr`ٕӻ`,0_ H=)i .A~;=~3ZD8{gqO͎L0S!5۵.˿>>21ҝP z:H\W955uwoTߢw2^6=X EyT351Q^lT^(m9 x8s\B+qKD0uaN%_}iPnFFKZi-`s!~2IDATJY\8LR'øݨ7G|OL:av+VWe?:IJ>Np{*! X(֑x/9ulD<{}@R7It3HҴ3;mT $ff}~y40UN90ϝ۸&Q=?E WTd4L" +|fJ^G&dSWHNw0>"+Y{cx\Qm+^x@ ?W>-x?DžчNj])1uyZ@΢T*5RSBާuPba]0{` H[{ێl;3zf "k^q{#6vrNifpӢ sHr!o!x ҘcgHfA16QG.C(_$C|3P:> &77UUCWnIQFlWn,mXR2>B_C nZƆ>Sac(^lB&<#Ac GxPPpQGCBἿjS4b Ң8:7cΈ,΍xKR' ݿNFG/ ^M,%~ؽ10L Y&!6aYNiB27.ufT}##q6vguw@%{gṭS3\IzILj%biIH'c Z bPf3R"h #́ *W6. 0bh)GPd|qaɌ! ]֨Hy $׫zq~/98s3v=%IcQa>&2 _^;kUZ"©p9ݝN{=:J)!fD۠c,m-KOgn,n㈭4Ҧ_% r{ %TSHB.|ԠLF  !e[6 .Wr0)F.U{H8܉XGSp/ 2zC''_`At\(sgLie?3~ mިO*ٞv"/? )', 6ӫkX%R%`0Cq:GBwg}KBfjPE/8=#uYQAK) tf~_4n\}>BjJMC)mɞIVU3&*e߽#d(߿E۸q^ yaδIʢ'NC{` ~o븲ۍ郚8k9P9ֲ?3}s۸=oU+kYyu6OԇsIН8zB_\#}Վ|.DeٔT8/ͳ 븆Q%rG(x})k, 1_f=oөFxq-$h Z$ L=]yA7ϰMѠg|a,Υ\JPDኔD/x]W5$ A'QA4n ՈxJԦiEJy2;>"πSIp-+Nh-6q{ƮGǎZ.X]Ӎ;ѹFd|]zV1`o cxaEVN=^b94^Ml7gaxV^ * pP0n狁JdYP.Ղ4NsƯTNKI2mԢNw9rڲ[7]sk vV!ޙsgp6g>U94",4V2n\GlU;[Ti<1{~ fC~DSɡ.y8\]%mlS|B eMA1T~q1v|q3Bn\ƍ-WScH8}^pzeDz+ZR1x0s_wEт2K 8O1dlq`<=-;Zwww7 _' |w] /C/E~2ΰ2>0L"72#i4}d(,DHq0}(QXD Dϡ袚AG\If8jezhh$)-)N vi$\Z]81LܼsZQϾ[ FE"{C4 AKgFڱZ"Dsh;lGGx{,\`4}PN$L !hgPԹL#pUS$ldr6$mV!75@3#΍@y *cd4XWD^ ad :-"!Q0=ёBǸfKb?B8J m6;m!-Ik-,~ NIí1<ZJDwҬgTs<3,@Ѷy!->z@WZ1 U-mKOS@ǕbZ-= a ?,Xddu(^Nh[ڒIDa@EiԦpuiulZ`)L-;`Ֆ.>\"sԣY}^% yJjCci sJFlUƜwmޜYuW]q!_uA<[ $MpF dGY"۸J0Bb|jT SgW;]6x﹍[`F.]z|?V0CNe^aR ,+&U$bui i/PPLݞHZȠ0ˠT6eIMG,O&xgy^p fv}W~KK{o}{#?ru]__?ίʯ{ ~?˿w<M;7˸p7nvc=.`YhT\_;џ4 蠃j"+>/7V}C7LvSI[Cy+/9겲j;9s؅CI=?}<}(͝gF;vTΜˉs{Ck'. *vfm\cϝ=KL-á_0`OL#[\^VrFdaWI-24ЎUU Loi\VHKDG@!گ;= "13Z#=z ki[*kdʩj %79v<EYO$?ISg`bnep^*]זSÐn]_%"h=qPF;H2oƍ˸JC%Z>(\{o02n]RΜT~`+ˉ1z+7pYJ 6Hq<>Avg^Ks4[DiR#M+!ju7| S7D*F[Ѣ?>~z~÷ J/1HtOoxm<} u(%?ue3JCx ]f /\z9Qʹ--i?l>CyD5"bNk XkӈP94})]#p iGj{uUgeƘ= l3FRh5rhQ)27ȿA& g9Rީ7w9ݶL$o'J)C]xX+\G^ ۼpW4O8NWw?ܟ?r/ۼ(k9|c}.|qao=|}v^3/m^y>Xĩ/:oۿ=}eYO9ڶm{jԲfȤd|n{DqQ8ҐХ&ƭ a*#"P[J3ɇɎ T _"pD@\oPGuv̾U}=耲"XNlm*rZXP\(lDۀ9~>C_x)Lm@` k<+%YGaҭ0椔`ر hMW./ٌ}ApzRxXTP1ƌPؐ[J;4#JQl2%/m ZpT: ,вa4&F`@1h6G|f%k/t6=} 7s=(CKh]?r nE%RƄ*3ڝ# xr9iD m6h7>7/6q? wg#61q [ ]A2wۏ|>ҊG"A~. x^l2 ^>`u)Saۜ`Їn |^J o0k R k 'Z)G4U7m#l} ^ FdiPӝ1ѳբfXEk=#|ƹm#9X3%c-b/|L#QvlB0{ K60 U߈H9 :6S߸?;^u)o+ƞm^x|c/D Y)MW۸o=GEmp/qdO4mpbaɰ2|hVuVlٞHdcOx_d m`+8QJ0J2>^0߾v?3?ß?:ܘ^>_W|q`GKlnmyf\教~"J-y{.TqV0Zɸ%xhH`Ґ{OP^6|惍7%j ȊsπϤ#bL\)@ <|r򤊌O̎v 7-dM@Aݙ2p`yŬg1lG]g 7 3J= hFDDv_Չ >*,pw599g463KWu,abqO,b`08$] ߫g+aI7r1=5 BzǤ>'*v1ӠD(I– 2U4O,ƃ`_d3% @XvdN$+ٸpjZbBU۽.3)8\#D"@8,ͅ˨Yf@6-dލ|`͔f,!Nإ[q$*=:Zz=4YBLRj=>}F`҉AȖ$F 't }4>T$ʗ1$?DMk_ '.xzOСӜs}V *G_TѶ`-z,L&j#`*%fwSJ ꡹=jxЫ93)( eGRd!VZIj {2K21cy ޑ9Q 14$Zjm-9w_?@|w?w/7?~_?|OOOzj|y\慫],.剳.;?=fV7 n)Nree+l^>`<ʉ K;_,Ay!fTʉparҙ2eݘT7n/|(*7j,v[轰 R;EB*Ge b.T}T+BEQdeߩ+,qn kZi퓥 K 1Wv!ƗJYN<@mPs`ҠEXp=3얕i9n3.Ĺ=ab <1g,U;JӕEtՕ G0c=)#*CPZ>1!3oR+A[ӛ_~Cm"#ct(ݼg=Mt9㷏x~ۯh|A̬'=26'CpyŶ+793uEjׅAw.Bo}r'i,>,rZJd\+}iC*>#\ Kki}|i<<ô3"O&R2h!${:}kؘl>c0F DbpRA4Z 9>g6~D3³haqi}ǴuB c|a@M=D +Mnc㥿n#dmqOX^6pWm(+'}Tx~g/AڕCf+og<XUoI>7>tr ՜4z\*gY9Ia \ N"ឿ)8sFX4Z9GJ[- csCz m s1$Bi͸ʛo9sn7 F(0mH] d m?3??3Kҿw]O?|[_Wջ &/Eگ?S?5G ?,knݙmnl0ve.=5`C+ $ݨR*ҴpԤPCs#NDnL']{Q͝ nb6|xK0r҅UKsM'&"t&6/>Iq◨xEa\@Z@=*C F 0]fETRyU xdC^}D`|ݪR*|I&O OKô&,EBP&##p1It@;z2DOmN\R(ܸ!F/RPBc-wQYGo83 @?=ZYDM*%Q yDa2)!:w➲r;JKW=&-߷Q7~ Xm?bև('s͌Pz@8D/5F(jyÔ3[͸6}?L]]llG4l=L KQj6̀輟%pBӲU˫V7ZYMU{B9zFO#v q-(_-:iʈŮe>i8p2 {fx2>2=5(^ 1,:{TͨEHTjK D@25i* "*K8%;59#q_8S2K w7,C-Q{- U .\nÑ[\DYsA$~s|?OSO ~~ٟgg_%'wO4OI>s>3~~N^Q.I]yhdJ-RQ1D۬̌P`b)R:VNp.%QB+nJA;pCf|j::ߋpuh)}ahcsuIeóJeJ@pR0ohtY@#_og :>Ȉz2C!f>+âC S 0Zq+A-MGwj9-j48h0cpS["!:!i@:5POy֜r Pһ;pj:T'_ m$ꍵ MS],rUMVѹzU،o:FMjEg?R9}%XWă)IUs،h v-AlGSl z|\#:IWFpHMu)#2|ګ>`vLD=_dl!ɵ )ɉ WvdJtc]*RimL4!q\pG+kk k4cI&f84cCr9f8L}Fb.g0oҕ^!r3U LS.2#.j.b&=mGYR9Zp͇ompv+ڙ&uMya9G}n+!,!g=U.y{qq2#T qH6.L&&)Qx9SƘ7*%I=V;hDL{3l8Z+kxX+|iMO tGȱjlR|HW𜹝6n9t*jF>Ԣ`gFaDݜr<=PXp;/79@3|PYC=9;}Nl,f27stȼFmli[D|`B/H;G*ӟ!+ڟrzǵb|@;wΨ;r@heS퉹<򈔕EPHJuNg+paeАFڨ`& nOiܺq/wl:RSRNq.eiExsnlcq{RӢjaYE /)<#F<н *VĐuGȌJalHR\7gK6lLE"XKk9G复=2m6{w9q.^W)ۉs=ε_ }n|c屜![.w&޹+#y MOuevyG;ccN. r _iZ|rzδ (RDVM>K464#Tbyp(cRa̹IFH5lLng冼6cp T6\gF꧿bIPz?3,@c0P7zFܲe|(;!5&Y(=xW?ܐGS:cf0qI$VdCwnYЈ5Κ` N&8*E#fIs{=,'N2ƕܜH{g0ie'V e*+%sȭV3ddR+ s`[3n'`ujܔE#6C8w[*& JHß:@Ǝܾ[ЂtSfU]\O,D|,H)T Y 44L7nl#~tMZnǃȖ=/e60ICHc =0h+ʧNy[2)TSfFu\iJWJF@("|q0sDP&u0M D3EsA-^DG{dD Fyz J8op3N G-6`6p~2YZiD,U.܇qy'Kǝ[FR"HH0+MK<Җ֫PKaMsTfqs8 avq03fh3b^t܂ՠpyIKi|E%ƔNeff(nZny}2Gc G8g0:M"¢=Vlz*؂Z~14D/^ώ0Y> X[}IMwC2J鑻IǸ"w4ѹ&PflCؕ6>2eaj,4up@r >>__ׯ~Nk ctƃwXܶ.<\N-V#no8enOL*5*n1Xwaҙ1 ڷgBP&UoeCtnxC5*3tCRQ J+2\ܺuci4dVWNp^*"e9 4]BSg=DMfu <pjںJƖ\x]b5nxc{aoyȴ$?HM78ՖCbZ^sNjaZAx2Ub} 0g!Eqm|Z>-B-L~!"Mcl@++cQ+anSʹs7?5%eŚX@  :cc^P d)gJ )mA3+ VZ)uofs>t^6lOy!o8ӪDœDxU OzP78=sF4I5S⪁w'7D%MOM Kj(O͝m@GOu8hP>D+Llmٴk8ze¢5_ |"q& Ѳ [٣^ft )3Ag).MNxNSQeF6HD&=.ǥr^+Rsz'=ZTΉUCDfҔwNI>Z6ZR q7gܢ3Hk?,;%[pۢ+T9# g460əiDv4LZ 59Kis'=AaMF6IԴ0`$They{{ k ;.=cْ䱕)9d{@:L1ˆNJF+R)P'!" 'dL ݞC3(%/]"[.O_kA8=>p^"\aeO*$dA%$pCx[tpw{I|=ܼ<}܃x9 %>M6|rfƆ a #͍=AnA']X$:-*8(`4\aG٬” *v4<+ƔZO3 9FQx7.gr /e}5 Sm873. [:@q! mGj\vY KpG}d,/3YZO&BD {8_g2-s+s3w #>S;'\Ne@& ^MQ<>W-`./7"ӄn@ luB_";pЂ0D 23Ƃ{+1'uyǓgjDGVkOʅta1I5xֆ҉1dl'ŜbPtFиewZ#~[~=?`T J_/XYn{QЖGT+(ʇׯ-eoip։FxBwŻ\vy&/ U?n+wwtFD^|Ș%o7R3-B)Xšb{7[vq!+:J1 +aPrҕd=( t_o>4ɨd Kĸ,yJFeKGvwua+FZ*/S})ca 5CH}<1s q@M=ZmT)lV8g*aiz8 KPf+tR|GO}%H1zͺQ{Ǫ].p "Ϭ">as.XT{|᩽ 9edc+VV `$()I!‚r\iDKGuROxY ͑)7;u|@ΔCIN$imŹzŤ1K4(`ۨޱ;Dw%4# g*C ޮShuՔ>-Cҫ6wޝSMZ a<.‡y<>l:o>9Ueªc%FWZQ2u1Xs"O|עhĢ0F!=6's11<)u)vLt80 E,ItyX<^ ESTTGg+-VՔH:x=6ͮ*KT1?FXѤQp7fN\'' mnl-t}H8)KW'oManQa<}+Mq}CԹs~`4|mUN*'](MԠpkU#DXE}Nˉhe)̛ZRg23LRDbP*d]J-R*rqF C6{ f.I)Y[%IhcP=LyK,K4 '+kLFaȃ@ERU|vy L !Q"5Q<"|"Z,fM-#10NͶ2cǔ+rL"1ChFYZJs^)mD+HeZUFeX4r7v_{Ő$qhƌ"}T{Y hZC4 U.JJ'pٹͶ9qYp,/<3}F0 .| vm-;:=XPݩx٨'IDY=qEVdԮm6<9 )avK,`;x=46QrRQIhevZ)e~ A/DrYJd?5;}gQ*_ c1q휳i0[:_ݻIdޚ5ĥ&r[ޜ}F]G QߴJa x> prc<@,; s0DʃCHj+R%c83|/6I7tʀ|1b(KDyđfiZ 족aTֲFj=(ȋG!bAɽ;ЊTg)F-R9xG4p cp[1{}]it]Ԝpa]ZhjtƅZ:sz˼)jYj9:܅>f!gvQ Pݼg8Qe$@ gRiLNG@ hG ~ǃNIINנM&KiQ1TVT4, wβ?ycӅ5h]&ME}{×veV^qʠ2,Bڇ 9ݜ>p#4ftKQing'yD\4r4k9l NN,GìĽ&H Ǝ:©EOeStloKܫA7*T,_Ա͹svO\;ͅJˡ<"'Y@ʛաGE=2_"}AlĹQs}µ"Ulx8 +兿?1__f} x;a0- T*?|>=|жFq 0jmsϼY߱N`$mL 4v]x1o'4˼6(p9akYQ/|cl#5BQ$[$(k0z)|8lK U?pMǞ4K NvGRE.؛s{,(%ҒIw۸7xort'M99DT7ޝr@i@i%DM9=j()jR/6(vQ!㧁Fa34 ]+ÏC(ݺd4C.#'b-<#1,i_{o@E[[Ql?|´@pǃ,%Fe\83kmwqǁ 3w%* ]89 uJR{4jn3K;P##Cߥ0%C]/_"wM@m&EO?\СRS|m/B $X:\J"~aGlyǐF?13+C{Ԫ:_naGoVRxX2GRf_uTuLV3Oo^TGkCapG7{犅>V$庳.-ϜhHERUV66ޜO+hh ^d8e{O-U[E|R J,r.|?ny{_vs{[4y'um^CZA'}XSK#>i D{wl2<-fb;?|ޑ< 9(Z2:*icldq0DH0 ZW.#`׆VМ\n^GN.Q}6*A ;5CvgrE9HeF[ЍqHH]|?uF!)y@N1+Z# QnE1J-.V$h4@xx5cC,=vlsGģ'BbC*h"",M#(ڢ.16%b$<]dҤφUM}gɍ?hcWVM$dWAş|eN#M|Kh{\UzOܘ)آ)~q?h_ zgX3к'@?GگT]vԽv=(vђDYxx[}+*=7Ƞ($HLSu<0wj0#H9IMeRzV9C˳#ʡcVpicn5}4"T0V(IcijGuX( i|> q擇}ph^.j omQ[rka>1fƀĵT4P&Dž7KA,3+7=\P"L R㜫v qI4JV%*BR0g#M^鸾c%j1̅f1KL6$ n= Gx }7)Š2^Ѵq{He{F\tW J9@ 2 ~?s 'Q9puGD6#xGsyP2BjA)}ˌXs/$ iB*<3!L3Gc aqshj!(۽30n>h-BJ+$#ڠ`oTVmA w\YU9SitEoCkY8ϝj$s(y wоSaV(wLMy9 y R(a ,NDl!A|E[=,mLޞZ痚^z%Ռ`ۗɣ gؘ=9aKd <4'Pa[EcLe7?Mi5bu2(R8qz ǽ1,4,TY)DgFM.U#ٳ%"yPlY0Wh,9-AMT_+I1֌.k#N#ns%ixa22$; ; ;߸pfR1i-{4t0; 7}d'Lk\rDA_qƏ^qiPyg36XrjzC6zyƞ kX<ቀDvX`܄(՟Y BK1p p?v 9i]`/ɏ@bkܸLD@AKKJkxdynδ-)B.n=eF۸JW.ʓ{?Mi\~Cn،Aђ94>;郹Z~qS!Ҵly+" xh%v#Ƶ<{ok'xOY xcctqi!d(_[C}BKl[@lͅSYYœ;ۼFܸ)5o*pc8(YԪФ\OʚpK8fPݛݭl' Rs %sTT dtDq|CyC43דܶ$e8lp7/ d-%b^-!e6om?;1u{wwSZ_x QHhxC DCBH'OA_(74QSZ=cƼwEnK׸bw17=ELCU9#Uef4K6~CȄ )(sV" bdŲG +gpl'8/p 3g+) k36UPr?ߧ(r(kv5߶f+rbDqr!bSϫvOɌaxSU6+8C_k j @CէΠHh8\\bb92 mnߣn_+bPUMi+z#>vV]h/1Q7p͊5&V%M'+YRA>{}%۬9S`>n(yM+)z ~|̶'̥uA%Y`yQ R;Cm1f[BuHL8vلOdi" 1?T f:xmCS9̦u{ ]+M !s*2l)_xK)}L%J! <9K9mV*2c]ԖD땫ᚥ̭0ՉM3a;sGN/óps;q;#CH !!2#wO\/ٗEw}1^B:\m1kt;tCz꒏FN+ D$nOG?p? u[1k Yǧ0[=!^py5djSS{';5F@iy̬.LrnRN4m&U@z7Xh})tiH}"b1XSvj}^Y<'kv삎i9]-&Rf\:T1P3Sv$0P9&tbEI P#wf2޹K7*h%4FЖ)7&vEƾлQġLԈt5 vm4=h͚FU\xpyTbq)P;!4BU,a$6HQҙJe(֨Y)Q3<qFq#䐬n6[UmH0uYEjB#P,NLDlÒ4^;5H]mc[^^dOttuwz{ŠD^_"p/^. 5F;z\dfL6\|е]Z)D dGَ͸*ﭛgZ2,$hRdG8l)9+E>w-j)?*h4A^lㄭ6H3(jU@b&ЃЖfk? "W lY_+f\lȉgNzsvG"`~P./WcoxImw$u! 3¬Eg~2EhR?޸LQ@7(1$F*6C8J3M;g9[DMa%icjDrcBTQ k59yi]W$IXϾg/ [T S_d8lY/̊{sbH̕(,C @SӞmkI)%+D 9f*4QBS 9ZR.P۠febK6vnG 1ArrLqQ̱xɹ{wUffzSP9g d1^  `Ρd2Ό?'m}e/1 eFjCj!BR?#zflDXN֎ѠpSӁvVCš16D@u|^>WK%G3q1\|3yqz*\(s 9).d{!HC띩;I+GuST ]sel.B +lkҥ4M&3 Z;5+5TwR95QئzLs=]5CDoNT#\kVM,kV5OY@z^~f_YLzph0 #$Fͭe8BbkalMJ}V0opr ]'I6I>;M\u_:Swgtۦ!@S"]mmyIx j''f*Rfǔ{nN{gJAI %q3i m v܍zwch]G1he7k{SCd`CTxa~ϻ~۞6ۍ/9Wq.ȩŝ"\-ⶦnw]4hkj4.,&ݚb1z/FhZ'M$![\AH̔-2 Yn`Xdq{KTR 6gI*yieͤK*~8,t3#r0|7E:C L=#ß)˽^ksJV DWag;:dݚQ"Lg꜂EM(ϥpo-aW~v3s?1m\}F3H"J*=׫ zơ)$ڳ)]سK{0ȹްKQI=QA h0*ڋ vMچ`00!r=+6xORb]0_gÉs9zKG^)O%gDTI p̬Qztj;c$0R{­Y{~&Irͱ$3S?sSo ƐQUv|C. t7JFD9skfĹ-$h$)mO::QE[CZ!k|%`nlk+ ЦT!H7 5.uwf.vЭ/[5ՙs˒_=0&'vOFzPv% d"[ZA}\Lihy) k@ vr>g){$\a'VkěKMMAX0߂$jLHHؓܛ%āv e6eD2Q;hjT1D8P.9NN!@c6q0cn\ "v9Iz3nNFX< 60<7WJ @q,TBۣDD5$T3/[5EIvn /#Xι g,.JS54̋S70*-GlfkPXfȼ:LmIG05\p;ФޫO/Ϸ)+d ı̢ĢQ촙xoϘZX$QPhXFG3`I:Кtjk? uLd u؎&h4YDk@@S r(C?"B̒Ÿf4`韋6)ڹFlƕ8l,4^)t^դFXza> Hu$'x9 XTاؗ"b\dHQ5:K(i8fcTvk),$0#`Dw H/8'{'$[FkWRZDs٘F3|UoٚRLR4Rr`u R L`Bs2lSv& PI(' dƸ1ZMw+Xh1x3/H`oSꙩx<\y]XzqWqUN @+KJ ufW^,/![GA &PQ̬ŹiahJ˵!Ӛ )'Sk5Ziq13s^Ig0\:/+Su0@j֙ZjTbpH] o)0Kڌd(HoBfӴ;=pgcm ʐjXR,d)/IY;nJ-JnUVF ^rñsL+${|71+-&*t>!"$29 .ZECkP8h8}('mrx5>n'6q0no0@p!y6(cHm2ZPhr~z|RQ 3`$`ޫM麀VR1R;HbJ1ќK۫mԤC;n= OV~{̱ۉ9[]~}.ĹmFƃadީN̷:MᚩL\O>ݫIa.8c$G/|)m\ˍc?gcܱOW\+4hz7&Nĩ1.}5!W\{! -ןGfNT황Zb}\+qdignc|xe35ٕőx>myupϳ}s械`|qv|HV:!(& \)CO45@ W WKU\2u @`_QdQ(Ҹ:t,1E#{lbĸ*9EL jgiɱkeHqKC &\bj/ZMi:ۆ?.C|Jxgߢwb涸qm`.gy/?uF2bvu|txJU=1 Rz1() _m,{Dܿ 1ǒup*,@=F6s%kٙ n4bۂwXޅ82]zX i1w.i;s~yB#=nl$!K04 z%E Dij1nfXR#Džl W5զH)ݢߖj d"dyMڇO.#<xoMMcr$J\:7HG%_@#kf 5B/V8)D"t '9bԋFZg_N N6+ TDDg g GlܶW8&j FP씪.Fn"!|a"rT2P\o9kW V^3U.SsD7tk,ed5ūAp ly:=:=G~`2(h`E6|q!u~ǤC|׾n7P,/ֹ~n=-/Q5C+*楖+Dm?2Hvcr^H@7Qu;0^f ‚)v&oUH62KBC.V|4 W}dHTq y (gqlG6Vtf҅ lg>L%"ln!Vo^gJZWk2-iקi#Ea'Hғ݉ہ J 3=Ez7"`Mu O>6o ##ɧ%\5BPr&k%Ofn]od8Myj GU~lJWSdv7wI5?bb窮)f JC{2sTS7%.yŮ%U5?"yg+F<m3NIJ n@E$**I͸'dqgaِ`ϩ:+|>;+uIhH?c6bKTKmLfhr[&7S+H&af 9]'614 Bj@D47N |e.1KĬIwxDCv71^TS .v%E(FU_/ *QGUHvJ kE5yt{f~ȚdީAlSXA&UmWdDvDxHaƹ?fUqrM 9ena&/XCb@p5&vKR֘geH2 R BkSD80ֶwO%2ՉrXΜs=Ӛއ^~gwr]N<s^9s=s3Moiz4h>^qĐx Qvyp]yI,;C0s\^ ;K3Mg:3BT3N*$Mdvc*GZCY@g<ވeAK5$)"{_1A9[rb/3gWm|ha%3[mfB]L!!0{,0\C&|%Wa\*5J5NZHf#{Rμ+v*Nk#3> ěw;yf")ǹ0͍ea`#WC3Whjy=A{5ScCv7DR@Ζ6kJkci֊c~H ~#1cd.tz"HaGL-#7:D'6ӻس{hI'p [vO45*Hb \x`{wN͇/0z˱2#0م+!gĵsO-]Biq-c02Ħ FFlPvWyGMCRo$|s [nVXn"Kc4Z='ṉfoVk /̺.\8Mr1\ plgFO`coP[>!3({VIϻ"5hՋL"0k5k˘VrӧEg+f|3WO+0j1.k˅d-ƛjx6mhTW8=ӛlаFZh =@`x3vq>PRvЛw~"2yzQ@A])b*!-35R1kk5d· 5z"ބαQXZWCmﶝkzB+ Aٙ/FKǩ" 4;'[wh (/usՠC~6.琺??`* ʠy$ :sIGYO4dzjpU45 jvn~sk4LcREi~16vW+vf< Pm FQ)][c)KSfAMh:fnտZ 2C$PD=rb2l$*u MHL]pq~1r4tW+N֤Dukg.B֕S$bŚψ?'a7M4O~vB|YSB!,h|S UntD"𯃞z+;jR%$mhhti(վDXL>;""oB՛Yp;J[7z㶞)'pWa^ ȇ!-<'nlQ3#0r?.-(gN}f$؟{\ qDZYtsh}1^?B3e`8hˇx,$4tNTiDّ@ {ft`S9sUm-: }GXa`?drrS~0c5UcGE̘#Wc0l<ћhdYZg{W%#9x ~hnZm<,[ČDpŵXq˙rfyr^ew\afƳ7R{f9q'N1ULԑ ;xxCU%}[TrP$cs'6+n"B!&rWbSB!tE57 U)E8k0pm7I冱utS8{,ኚ!-?62m&+c$לxWHH#HSJcfQĩ ճcLw#!1Ʃ7^Tx-R.h"Wc.srC&xj`iR8ΕWΝ;Y!Z~~HI>-oh B&)xS4v7sf* ]:cBcZKi:;eL1 45xcLs1Zbc`;)q\ W;kΌ~bXXҚ!=ܖ[TCs_hM JAi :ed=c2Gӫ\פ(>8sebޢUnXkyf-(U 0hdvÎ쉽:CRkDݎ }YhO}Ec#a%3[#?=隰0l j?_YF힔ډs?RzDWzE] 2әڋGyNohFkzA EUi;$w.Bf A,/ԔS/BFQv=uc6oآhB'+wh•`•@0IoU.3`t a4+^Y;%YwJ$rb9`Ug"WB;dّ%0μ|gx 1$Fd FFWڷud4{`Z]#0 5@ B 2Ov2EXiu+rK-z %DjVuTN,mwc$sk/\wng:Y"A?eד\D}d Ce/si ΥC砣gR'KFp9 %9lEID6W]ɵ;7!кTOcefm+U?r[l"tk\A'L셬  I 9YdH # *0G'LD&b+4teR:xTIш cSgKmf&!ޝ7x2}f2b?\ɛ0~x\ͬ^_<AI3DHBB+1l;UҕZ쟏n!L[EmF$Q vS2X0(|[ >W3)td o>yOkur!MwIyvG hEu)R11{xSz!hc{7N^(v*$mXAG:3}:8G5#ߴP C. imi0C^R6nʑE͡wMDg(cn xA xbڎ^c!kfcԔJiZ𸸐e0 ɓ̆UX1(;w)cXTj< DP7!MA!:,)Co"@*. Jc%Z:C 5UJ ,,/n Jg7DT^LMp yB" {f n~ qz&5Zw],eԒ7ƸFJNJ)C#1PuAfWSrJ²HE=-R|7Wsa`*EA<?tSSw۝Ž㰳׼1$lƠ4#c?3m|Ab W E2U]iFbcNM]#U,#fҔ}TY*PEvcLops.a󪐓 BE . 9qnctKSU"BGMZZ糮Nȁ[zHfoŞ q'BR[8a)0yS"0rpHv)vadGlv&3!yhoC{oai3SGmUBAusHY"=6sgnıϜ01#\q#_#wuEieFd4(7ESh w/zI!r/?mf.+4MB`ve1A]kN'9Wc釈MS_wc0v_@ P1QS?3ՉM<<3u/SIS8c;q\n9#z\$d$ hmnLۨ}1VT+)؟_F.Rkf8+c{ 9}`pDr}Mш+*Խ$[i^8/{fn5a"}Al"m!Lj:EvǁFH~[ 9^%| "1ǮR][?;1/)b aӰ1cڙg Ch! %Wbj1(DT>qڡZ;kgT}$B ZޅܟԹ=DKH\%,[tSN~b|tj~Vi)4~L â$0aYsTUHx(qpx;gBs=7LZFXT}Y]l-bn&/?(m`!3^U0F`3: |Zo)0 bի)һqb6Pvj )!W<*ةr5&پ+vHu7Eqbaߩx9=SH!cys[W)$%Cay|voy2T_@_ꖨU) $2#1hZL #n͢7A[JϺ%ʝ54j\E218fQC wn^Y3iܑ(4jMగ@XюD2dLĮ!5)^JES$451nwK X5{aMDN єK/bںxwv)<I]YΈS%U1ɨ1BW;!Iۘhn2*H!XM[%{F%Uƞצ݌CA p^=\ =ln O˙M \g"fg٭tF@!i| ǥ1Ŋ̚I3lRʉdDIrEm ׮m<{7Z[i$s\1rtTc66 e^wmJ_{jQV·v!Ocz6~j? ɠK# C Q~C`= -y<sh". rGbHtO<2RgĹM ;1xcb97o9?'DqC3b|KM!Qk{h@Wct`nS936cQJ q+A2ο˛q!M0羰PGc;G .<-B Z5nE$spc3P_:?$hx0BĔc1C(r= ea4.ACj$ ƇdZbM3m2Wn:."CVbd2URq*5kuOGhI!.zꪌquOwtY/maS;[ 69>G3+Mho٦nn(d`J 7%߈4Н%LXC̱sNcHh=|}Jn/NJЈ(z6ČHqO M-e!jG1>DĄ!u }{6jA{1:@C%)EIitGt"{ynMTpoLѡRyum'`!c½Ma[=_8M J,հ&;WVmr7_~Y-h1+n;2Rma|3A;I !2$ۭ}Bqc琱y&>}|$2e FD}~Bs9Lgv1z Y8+#6}T55ioP{x(C)OrS Z4xE%gyz X n6$DurMKG/P{3Q您^gzTLmbѸq$ }537{ƥQ ;x%ȗpCfHe^k F6dWY1ًqv%7 1؄R ZE,ek~NoE K2SH  -A7B4|V~gtemUָm3f|7kz=hREnpƘ=.s/Zʹ[MG10,id;=xCVK{\e&&} `м7t7@H.&].z55xFYBh>λi:f nTSPDgN#bR26:f*-$m⺠\6}h\|pqty5w W1#i{@{Z6e_c18{k* =X3! f. H Lџn+H<~[o >{iGW{fR{Cvi>AH5`&\Qz}7hb/HpVXT2YzOuNMc$H71!&7öfzrzHdQvq4_R'~ӥ t/Ta09%B*ErH$ZS* g'Cҳ"ambilPKwk,+aUX*cL͖hiM=i.o>l"0#z={HQpk Av=mTOMk_0ܭ:\#PMG * ϸI O JH ͔bi !$IyLDFІxBO,({*=O5m0l_,׶MA@Ϯ> @F)nn"+%nQ9Mou66',- gMEEۛ-E'b3;6r<,tfk sM̽%{m.K̥q5dD"J^A`ϫ8,ކ p)etw DWQ$XH]m[Ѓ9\< tt?+jk? R&8n[;X,Z^^L={Tm68jM\ћ0KȔT)rQAS]9lir!Ӵrogf+1";֫vigKg.:T'Uس;L 2ޥѿ\̭;ۢc0. ٩N=m$] ./RaC~9M텫ͧnuY𻰓!gA8{HK(3[G1LA2T\Motr+b %>-R9ETTbړ2a|68tTNd<'E tY[cp*+8@.dMު <-dhM)DvCei· 22&( C4"y7"olNcn)6{^/:)F HaHiɫE(Ex[ 48lBަ.kqGfQ]4Kj)8ϧ*A@L$\y (ѧ$烈I/5)E=N@>b fWLַSLQ+@cLF`F7N|}bXB @ʖLӛ>!}T/f`S`ގ!(npAiziFB dH+R̗gToz'i1fg $B]ѩlT̪&8/' v4{fл(x|&J~df<^ D bRr4G")&*4,}ŹQq 6sٍ<^hl̐<7DLTS=͇ 8 Ƙޞ?'՟vF @wՓZ WWC'"6 SoTj,XcjޙMLBrOWή\`#69,Krv(N`yw@ T 55W1tkfS9 DD!&'棷΢ Kcq҅C9HFbD^s+MX5/l 7U\TīW]ӆJ7/Bx5,"MIVE pIsvS{1U9Ʒ\! }|ᄡkofw:$%kzЛ-˲418m/I3rH O/:4!)uj-1NDi tMkSg\_}M'q3袋Jb ΃|7HBl57n߽)e؋v1ghSIdu*e0@f7񧼫Ad7XW@} G!FzƜ  >EW 6Do>u͍mQՎW\.\!:!9D"ίፗ\zqM1up~s9_62аmTM(5"~@+{*߷4 5> y L7b7[#h1f[nw_r gv#݋/ qFwKef}%pDJRoj^w;Y5w֋sh:4#vy q1HiCj5>MO&t4P1[A .?pDDpo֋r3V.od<}f-rI[YacSG1dD~yb-AHHtWU%X$ݞkSr 8<0ej MSkplњR c޹- Wd\ѧs5I *p̓2;n{ Vyԗ Nzc|.˦',,lrDJ;2=1ƻk ,DLn&jvuRJcFk͛5Hׯn넄@ A|:vF1q=xeI_lͶcЕ!z ̵P15ӿ5:N?/qϟ畋C9ؤ=\'+D-g`k})3ɣe3/Ԧ5wXR awG]gi} noon7P!DMe :vǶNC¸gM)f⪽-У?Iǯww7h*j kH> QkVc$֡>inI}B>KH;M2Gjfx9<45NIm1a bFN!B)VNw(u|3[ #[CQ9$ppIP!EH"ɸqknb E'SSWqV脕E0Ύ RKc3Eu+~zbUћV#ڳ{Xz]  S5f.D;E@B)z60eg$4/]k3Jju0k/ͽ/oxCN-QCump5t5EOt/E2DBgZC #A=AC]A$D7ͧ!@M@̈h6dq^Nƚ$ .A"\ܸ#zFX9+@np7"'SaҎ;'-6*+k+JXmIWRV%J@3Fϗ&3pgxHD:qTBD:Z)8DgOf/|Pč;JqK[OKƾ `Kg Uc4zRH9Oњ.A Z51Υy fΫm)gEqL/ϐXlh] x>>53%˄rlZIms_xR1Wn,6>n, CO {0n=N<> H]޼ eN\uXDzq]D]g+rb]]9H)]+QRgjhZ9|OsLΕT7^ʑE+:\s,?8_3un'N4̺Ћ <`\4L!/ kTNX9]6L[{/4h#x)8n=G\^] 2]RSH+q^2:@v;ҠWq9BvnO ';>U2B zb.g&'(h7h{ sgj=C0E  JGܺD[O9jN%Z8͐J֩P4YkD7S [WHr?f֎6Яb]D\.(tK0CM F@ůb]3 kBhK;6$K.PFj7[)Eh:j6f2o Tozrsp3wZ5wF6u)>Z;A~36:l3*wQ&6iooNHͦ&@L{L[_(vp֐#2Wfm⬷5xF]Z):8|gJa\WFw36Xf_'=/O/s/_s6buݕƑYlaf= ,5f1'HpL? uװ)p<3Fznw3!3fGYꂈEuv,1-*yMu)*W=_h%B;42R0CpRõqTi| ȓOqC*1\W}(>)thz7u5O>][!7r&piVGO|:nr列-BM, ՐUn9ܿϾkY&H]\lo 잯͔m5/P Kg*x\<%a_Nr9^=<8dyf6T5haL  )^*Ƌ\i ZN)<;qծskɸS!Jk3ڄq^ Mmiά1m &LF?X`SاC̬VIkNUIc` e+M5gMUhj8޴S[IEx3H{}>;wZ+.h5!6=f) @Zz:rA. xG}?mݕ>7~?ww?<__? >ktԵjjݚwȅ!٘45_K),H4\ !$hە|cW c:ez iE:a9MڧrQ2c2[ ~!2v{nAC,vGi(54286S\+f\Z 9VW8w$*~Z =6`Pri" FD}qf!赝[=(ܙW07KKpJ<sN։Up.Y.m]CإŦ]-mg%(?KM Z{ޚ].GNH\Л˰8T*E w$\ ,Cv³@h.~u"n{~IY9TrEm4Ѹfmi;V=ߣ֯7ɦеg9vwF#zzFls./G҅q'q[CcgSg99XʊYj^ PE+LŮM[՚UQeo*Z躻7Ŧs{W8Qoh.SH8d8x2&mMXal Ѝ(歸zB|Zn@NReQ%XNڕsa ӶZ&Ix%.{|r\Ԥ ( "VUm,A`&z&AhkHVO:1l]õ?i_l:J;:VO^ֆN(m^rHA EQx>D7~^w_O$M~>?U٭H3vzh-4<6qSO/[>f6rs5p)}ai,sg) hc~+I\:z34Ƙ C6iYQeO:YH_cr48`tCUue{JG]y<đͧjΗ&L ªK4Q氘xE<1ȧ+_>Oaoh1[LhV5/|[̙ʢ3ZMN1`rjk~ӂFmz1Um%5%T\,4zawƧHpuA忯ꝱꪲ~aUg$Ͷ06r *=|rf# խ-gYg 6K[mPr}mE=3n#CH{gD<5˞e6uiς^- MTͿSCDkD'/]; b2?cf%Kr#Uxҥ˽Fv_DqCjD.~-K7[4bN,%ʝZIu띹AY:vNKeW)xt4o(h7cw)b>Hњ`J{wkBXj68Wsdp_A1ΦP])TI~۩헄s;aPDzpu_Z7X^% {O⬻9AwJޙZ'|P`aH.KGv&ݹ* ُU}shLn83捦6ތҌrQ&}1D7M&X)Jѝ"f@C\LizZWYhRT$,lmY74/27e+s}A>!nfGUO4_|W|??q//᛿y;+ KE҈Ⱥg.v>777O齺+O/j3#'ZY#wyNn}K;Jd'w"-נ$ I[/jk͹@5+)RfR3"-/Mli+(C5C8WPjVv{fM9\q+^vm6!rSnG)nuy%oGU; WCU v5Q b<`T=$xٕV}|/(/xmYٿ7t:eV&gTO bٴ/HR|*nͳm2zTګ8/sǮL.@z胘MQNx]]8{yI7X:aUh"Z-C iNыA"VeE+Ԙ.0n` ^d3vWX*MM)n6;QQXEhKfΙA~1 9vNnʽ]vve)or ɒ3RK%=V\^be3r*ںO.mB6%LհdY2kM /I&Ύά. p{0[D qe&>JV5>Vs-c[%{[j*DC8̛`Z}|G7~7++<ϗv77>aRjsO>2tep?9X$1X/l '^pJwSaW=:Pef#Ɛ.#oXվA@Pi"օfV_5<)3|vKkj:$zv N2LXCf<}A;MH iF32UQ]+'K}|c !Hv>x?[ܭqr5GK J'WExЮDB`4oNW>:u FHT~\޹Mp_BS9M S^zQ$Ub>wX ;ώi ~1}<:dGF ZƴrVn1~_0؄"hĔLJ3.s{2ztDWv%$S+Ĩ@JVE3q)9,wFW>[u?PM͟ BICcSvLy7T+fm$P14VlǚbvH1qA8쎱-PR΄NpHm| E!kR*]WƷɐ]YyfxT/Y6/_7Cڱ^|Bd/4mh?sE ݻ>`+o !Bfڐv<#319H/ m*]c"D6~$רՍmӤε睿=C?gbB䋙sq9>vv=\^L'(I'|is}?s|C~|'??{~ _cjj^{`6{mͿ7˿yygǏyyo;L|fv}>k>o*777|~P>m6ox1i /{k8{>|qgݿ[ ?k>ٵ]ڮWOo' {+}{yi:jj׿ }mmmokk[[|wжjj^zwKȏ?<_e_{ַ~mGX~όڮgvm3]OV[mV[mՓXO,pjIjjzjkjjjj'pz׻CnW~WKK??xg>_5_ÿSxO^}, c='>33??[Vq '|ɫ,__pMoz/E^zOnV[gl{{~W㛾 =}{q̟3ȟXZ=ۿO|ɬ|˷| [~~_ ??#SxON}ov;__~?]]#곥6>c뫿 ~'~{_%_77ww|~)x;0xϷ~E_E_kk}c>ȷ~<ӟC}"c>]~'~|q~~V]MeYx7~7~7~#+;zl/ס>?|~^C|>_+c?co拿s>?Ds}~=*gTVD'l[/"5{{}Cx[[^C|>7__"my=>//_/__xxv~gwLD?g,??8> kn]"Qg?x^y~//T_{GDٟY꫾?}~g~fN\տWA߷>ڶ[}Fbg7 /]X~N~~?'yOl}_CUI)oͿ?%$Moo~3<ޗ|ɗ|䋾^c~>|;گZ?GQ7ǽgWm>#k+}{yƍyc>?̯گ]~}w7a~~TQ_.B-oyzOZ}˿o{>]_a?A[};^z%~G~//=yo}[x?3''==||_ ̧?c>[}jc>׼6y[t}Xw|wpss?>oVkjjzjnV[mV[=a5[mV[mVOXm V[mV[mV[V[mV[mnV[mV[=a5[mV[mVOXm V[mV[mV[V[mV[mnV[mV[=a5[mV[mVOXm V[mV[mV[V[mV[mnV[mV[=a5[mV[mVOXm V[mV[mV[V[mV[mnV[mV[=a5[mV[mVOXm V[mV[mV[V[mV[mnV[mV[=a5[mV[mVOXm V[mV[mV[V[mV[mnV[mV[=a5[mV[mVOXm V[mV[mV[V[mV[mnV[mV[=a5[mV[mVOXm V[mV[mV?V?XmIENDB`mir_eval-0.8.2/tests/baseline_images/test_display/test_display_ticker_midi_zoom.png000066400000000000000000000527701475740344600311460ustar00rootroot00000000000000PNG  IHDR5 pHYsaa?iUIDATxy\ea; + J"hiNjf,liR,۔\V6DͥeD--')n) "ι἟up{\}d 7G """"KPDDD(@("""bEDDD\Qq1 """".FPDDD(@("""bEDDD\Qq1 """".FPDDD(@("""bEDDD\Qq1 """".FPDDD(@("""bEDDD\Qq1 """".FPDDD(@("""bEDDD\Qq1 """".FPDDD(@("""bEDDD\Qq1 """".FPDDD(@("""bEDDD\Qq1.v;FÆ 1L.GDDD*0 hٲ%nn9x;FHH*8r[vtx6lwp5"""R"봯q˷\s[DDDą)@p̘1L&L&4k֌~{a/ӉAN""""uS@n,222Xj}a„ |e˱_oXVVkr~~~tBDDDIlv&KtGV)C*2l Cd3+4 H)q<ߊÍwD3M@56xc>\ԗ#kތ( """R+N 8qy~X4 GjEDD}{$[8Yhӝu䞮]Rc^7ޏa@f~Gd.ͥ)H8_D4?ׅܐh|\(H۰&.pL1^xW'viSjSjW׶gX›92-@rϑ(mxx{jʷQLh;gK3{ݝܹ˒KP*+ye^xN3:}\\TgH.cC۠(EDD橥/*ۃp[.K*HPDDD*ΌUm1!KHP&("""y,hSpspeRY """rE+wfe;(W]T\RQ_kF9*>L\ԡgHX|&k|\SSqQ0' q3wKn&G&5LPDDG?vQTb'Ǝ.Mj );r ޑMxcd\&@X>S9x n&ߎ7^|]N=fL&& OOO5kF~xvӠA+tJ-K.,\6ۯ={T"""ua|a'"c7G(Z{mFVVZ>}0aLii%+..f<>ܹ͛3˗/gǎ|޽{jժr?OIIa̘1$::l}i߾}rϞ=9r8%ˑ\%r9>>~a 믿%%/?BJKKEADDQr3iv֦`Ptwg5+Vkjf^3f0xˎeffCff&6 @DD~~~&%%o &pw}://Af͚Ehh(|r/_^!0>9cyExy6+zjZh5"&&$|A.}3>|P /͂ 8{,3f`ƌeo&RRR4i?3>>>DGG_2hРKbZZe麈H tWf7k˜ѱD pti$La.YL2칄*WsʓKiɋwuF~~>.X  q_ =Ln!.K@:f7n?o~Àv;:f ] """u"&,N㻃9”;rwpeR(K,:SL/w^b[9,EDDf獵׶gX›^De#qQ8 o?wSSRsEDDdL%=xN e Pe%6;б?sFPEGOe42sEaД@Z]]EDDRQfL4*LEDDKNeOv&xhW0@*Zzg>6y.lDHPDDܧX(4f.kWH%;^@T(c-]H)Ta,(~#E%v}o,=iD*MPDD XKy8gzG6ፑ]hgvpe"U(""rY$,L3دt n'(""ra5隸NsouA.M)NAQ [/vdЧ}S^х _/W&R=EDD~ǟJƩxmypMJ("")m9/)iCҨXmD]|N͘1c0LL&<==i֬n_vӧO  222ʎۯիWkav튷7[U8s%<0>EN2?j o6`ժUӇ &0x`JKK/]qq1ÇG1׮]KVVV-RC1h zMZZO?4,_JH.Īt7sWz?jm l6ӼysZjE\\=zo߾,XGyM: T7.;[iӆYfp?ꫯrwWX""\ o3xiU:%6 挊#&$ѥԸZ[nVXQ#;W^,[϶lB˭0`?%%%5R g㿶) ؜/V@رcGϏ_^zg}ȑ#ΦYfk֬ò>::ÇлwoVZE&Mx't֍ӧO3s̲\pq""vw65{ B7`8: pti"0==0MƤI*ʕ+˦l}||.ٮGor.ĉxxxи>[D>9Sď,!1-yΎ4tpe"_sNx >ڶm[viiiu{^Ϳou놧C/!qQE=ܘrG4^qiV+l6?ի1cv䐙fbE$66777>sxڌ;9s0qD?e}]-ZTǰ a7 /sGqm G&pW^M-QFĐă>ۥoF~gʖcccX~=7|%{8|0k׎{aaa\'xsҲeK.Պj-[ϯHEDR`eG6? ]x~XG|IN0 W4eʔV^^RD.I&,KoO7ڑB]!`%\l0$$ĥDD ͯn?v5c8"5ttiR(ցll6; ELXlaS֚wtM ""6'X8YXL/wّ;c[;,:MPDDRάrÀ 8iz'D);DŽEf06<;ޞ@q*`GN-:1$q* ""Jlv^]7c+挊#+q> ""R{ɩf0&> )_P:Ǚt;yJh+t涎-\Iťv^^w9@L挎#$+q~ ""R9˸TmQxy\EEDNYcO-AAQ)>:<~9,zEPDDkL-kțhD@qg(73{<5+REDġ>~I _/^C.K^S(*1$ @ F< ""R~.dq}"7M @UbMxcdzG6utY".EPDDjŹb}#pፙ}o5+RED?^c S &d-]KRcKONӆffۅk84(""5⌵|#+~wdم&~fW&" ""RҳOOoϣ7]|E@6ah~ k${XKPjQPTۏЧ}S^х _/W&"(""WǟJƩxxj@{;\S"uTa|a"bV>$kF.MD.CPDD$\ [;f:3 4+R)Hm?˸E9^Lq ""Raa޷*AHsFDEDBrԲ|8;6祻;Dܮ ;;l&$$!Cnݺ .]x[ïX@QQcƌSNxxx0lذwf̘u]GÆ fذaݻ\1c`2}㪏-"Rfojqݘ64ySqRȠW^2sL:wLII k֬!!!={kez7|Sl6|||HLLd*zʔ)ddd`|Æ $$$puQZZwݻ-kwm-{ye߲ K q挎cG&"Wd2ur)::z7ofx____ϟ5ͭLzr>l۶ollyW}<(L1n='ӒHCo8KNzjʅ_L`` lݺ￟@V\ɤI $99:Pyyy(i׮9q#sàٛz nxg''RO\rATTewpwڵk5k_|;v`رl޼&MToՕ`'Nncǎei۶-r ۶ml6;^G o׿ڇnԗ㸶Kjth營 :P.\ȠA -6::ÇлwoVZU"7m˖1 e˖{y/vܸqرo#G}߱cGuF۶m/뮻*TH}rK,lb[gudd$&KޙIwzxx0{lV+nnn,^z +WRRRO֭l9))_~lwƏg}ƍiݺeѢE ڶm+\H}SLXƉ+ޞnLڑ]["%`PP `ܹ$&&^p`nn.-[bpqbfѥK6mDPP6h۶m!""\ma??®xSNqZhQEDnIZ~C5tti"R.ya޽;˗/gDϞ= ""#GpũS{DDD|"vލb!''<,KJHH?$99 Mvv6ΝI&e222HIIaȐ!4i҄;Sq&' |ѭ5AO\Ž0RSS>}:O>$YYY4mڔ]=MU6lPQ+1hРkbcc^XYv7[3fٹs'׿ͥEӇ%KаZXֲ*'"h?K8YXL/w^֑.&)M2S^>//TH]Uj3k~0 yC挎#"ѥԚ|\[.6ҿ@"zBPD9c-ȊԟلGtiC+DPDؓOT~ n&x{4+"LPD `0]XK4&iT,Â]S ""Th-;l1nnߔGt!H}(" ?ǸT2N_珽5+"5NPD/).27Gѵm#G&".BPD0yVk6Д@Zh.9^Lڥ("R o3*AF>GLHK("RΖԲ{qnnt&+S!iϹrwrSfv{(m܀*ѥ ""b\`p̸ 5+"uH5!#+Í)C=DS"R9Kf񄇇c6 aȐ![K.%>>o+1cЩS'<<<6lXuwAD\n0wFYyE7ӄ^ŸIur0##^z̙3ܹ3%%%YS-[ի|Mc!11˗H?D;YheGٸm :ku4>cL&n݊ohz o޼ɓ'~c2|annn/".㻃H\Ɖ+ޞnLڑ][kOD:7իIHH(~@rr2uV~Yr%&M"00Z^D\n0{~F;NX q70PF8aDEE]wA||@DK)S:uM9:{Eip4lӃըH=O@@K+VFCBB\H>Y~'n'l |OgujD))l6c6]TR;3W9@LG \HPv$,a9 C˜<0 /:yHPfW6O-N~Q):<]HSc-1cl M ou#MkPr%<|c8]S":Ee|#wP`-QO^-Q]HSz _2.Ibiפ("_ IHN#=+ ("֧yzNh#pc.KDE9WlcX#b4vpe""u+N0 0 HFfrti""u˶ȹM= M]H("Nlq)dSpCDم ""("Nmov-O㱛#pӔ%)S2 %9sZj{c>KEZK;r 514ӔHE(Su,iӵ5'" UȠW^2sL:wLII k֬!!!={kez7|Sl6|||HLLd-%%QF73gΤڵVZfڵe>T̷N2aV|KOD0 ˶;gڵ̚5/;v0vX6o @&MRBL [D+yy|o+9gŸ/{+AUd2~;s333Сpn^fϞj͍ŋs}[orJJJJP-[b-~W__dڵtSN߿B:{Eip4hooOX%"RU)1`ΝKbb斅Ǐӷo_, 6.]i&G>m۶{xqџ+ Ynݺ]q_Vtz]:D\{3-ك̠N-]\F8oIVVM6k׮enذaC5h >\ :ċ7os=?sL2G2j(N+vrFc_/^م5utY""RE8?;],z1X{_aKq6 "$,LcL&K$Ffrti""RE\mGy9WbvWDG%""5HPE-.OwlQzE4捑]n)_NP. !9' q3>q ".0 >~ kfffKƎ.MDDj(;r 514@X>S9x n&&oϟo MS"".IP3 g2i͛bDDāEb'_oT0+GSvcܢT:x0L&MHblŕ{(iÜѱĶiDDQ'ΖY8;4{bhDDQ2O3~QGOݍE`||EDEa!^ZRAG.MDD0@'uL1ngݞީ3|EDEж9ONX^^n<;|EDBEnƃaM|3:薚Sq Lh;.-~g':EDr!?xiϷbpchFt єTHf[7n5M}oѥS~) 8 qy~X4 tڊ;H큓LXldOw֑{vtY""RO(!6uyo֐%"XS""R}EELXws+j6f񄇇c6 aȐ![K.%>>o+1cЩS'<<<6lXZ`&邯r͛GXXtڕM6Uh"mþ_4{˝v᥻;+H`FFz"003gҹsgJJJXf ٳ\-[ЫW/曲/fCbb"˗/T}ݻ:oo,Y?μyիo6dݴiӦRR׿Ǽ?sGH}Vca2غu+e룣y衇.hyf&O ~󣆹d2ѼyK_G`֬YY3cƌ GΑ(dmxx{jODDjVsrrXz5 ߯HNN&00@nO`` +WdҤI|UBڶmK֭#ڵkǛoYno>ZKjg7&>eTZWHL&闼3733:`XVXx1wo+W ѲeK,KrPPE۹quױ~}'N`TP:ٕSK_T3ᶎFUDD&U)1`ΝKbb斅Ǐӷo_, 6.]i&/ۦm۶/Ã+3 BNk׮|Wye+Z:D.ΌUm1!KHP&"".wϛ7xwδiܹ3|W̟?t"""뉊bƍӽ{ gCAAAو_.].ԩSѣ瓔baܹem&NOnٳ';$"d:˸E8{Ԁ(<"""W0,,TOΓO>IVVM6k׮enHIIo`Æ eWԠA8|prll,/&77?Odgg@ll,7n,+vrF.KDDEBQb#t "Xx_aKQ' IXL0O}#Дq "U|QGΕhgf.Yk(""RE*lq)~eێMcfۅ(RA0' q3㷶#Onhq. "W`p>EQffKk;4*QBk)|O,]S^C?=HDD%>ϸT<'c)_qr "c[3nK&iT,ׅ94j(E%L^/wdpKT0 +> "Σy[Sgp3ۢx0MH(.0 >؜+Pl*Ї7GצK Εe;X+=14tpe"""5GP\H.S9z&t-cC14+""0xCjv6A 3:έ]HP{IK6:5祻;)_q 2a|rp;pm4+"".GP=Mye^lv&KtG&"" R*;bZ]3W_DD\)q<ߊÍwD3MSzf7o݇݀k2qD5wti"""u+XyboஸVx4h@``Uװb GӦMgϞY\ `2.***K*ٙ2YN-c+ŸHUkȠk׮|̜9;wzjCBB%+..f<:NJJ ƍׯ+Wd۶mӇ!CV?YYY徼+TԎ2- cCYh|PZ֯_7\:~mJKKIHH(|Q3O";;bccٸq#ݻw~V+Vl9??ҵ)ߩfL4*zHm0޽!W4eʔgV^^8QȸTd`2>L|ED pGy9[loBȦ.KDD\`5Owf2RtK م`M8Ԩ} HX`Bv%wK?/RDDDj0XQGJ743Xz^ѥ<@vg<ɏ|3#.4H](j|%rLL׎Go7M R- yk&S?Mq޼9:B]\b'_O6 A^LDDD.FPʏ?瑐Sgp3 J _[3tmvZ4*m94@s%uVk6Д3PJe\r*GO^ dҔP 1 w9˫Pb3 aΨ8bB]T\Qb&- ؜L+Pv8i+ݍ zՔS tWf7m܀9*ѥUR *!1-yΎ4֔H}(l=EϷbpc{]|EDD@OK9_n@xS_掎.MDDDKYش$wŶa5CDD>;|$Xӆvdx֚]nn?I_0 2؏y#YCG&"""5L/bb [`DL#>^LDDDjٸXbԙbx3ΎeH-Rt6;oǼ0 jސ9sti"""R]@V9&,5#׷Ԕ+R9ď,>[كwubHLKG%"""XO켺f/oo<@VGh_W&"""X{ɩf`϶<}=4+""" W3ivΕۃwwf`.KDDDzK޷iq5ppe"""R׸9꒝ l6!CXn%>}:4hЀ+96ocx?z1A^ d̙tܙ֬YCBB{v >={rc,|ExuhDDDd2uV|}{ktt4=%:u* ,]QW-kHҨXZ7Ҩ\V^˅_9d1`ΝKbbLps}v#gm4⍑]eCHfѽ{w/_IOO'))={^rL, l6, ZIVVM6k׮̟?=|e˱_oVZ_}} HXL0o$o9T. )S=;$.Jh{Mj۷' ߿`%\l0$$ΖmQ4mh ԓ)b61k>48n""""5^"""""("""bEDDD\Qq1 """".FPDDD(@("""bEDDD\Qq1.@~~+}qWx  qp%"""RY8 0nرc4lT'$$#G_ ?W9G à-[Wi*Ѻu=<9G>U#r+"""EDDD\`e6y0͎.FίQs~\ """"b4("""bEDDD\Qq1 d޼yM׮]ٴieoذ]Mxx8om/_N0tЁ?ʿoŊ׏MOϞ=YfM6 ,d2]UTTT]1%%ٳ\;g} njsEGGKƍ2d-[d2'\qg:+?g<+Gg;+?g;g̘u]GÆ fذaݻ9ylk%KxNZZ{fdff^C4h{&--~D/_^f˖-9￟۷s3bVoƍ׏+Wm6Ð!CHKK+ߟr_޵ѥ Tڻwo###~̯ٳȑ#1|rkxbbb3gN;9X99X>Y 6w}W_}Eii)̙3CcH޽1vr뢢ɓ'__#**ܺ?F=ʖGavm 0{ꊫl.CԩS˖}# Jj 8}%Y^Ï?0LFFFFٺ 0>˶qs*ҿoUvVU^Cg: 0N8aƆ .ƙCgV\\̶m߿gf˖-0`?%%%ms}֔v;[_XXH۶miݺ5`t\MccciѢ}e~V^w}[omۖ[_W^rs:sj89Xw\#n˶usss_WѣGkh?^^^mװrVz^ g;Ǐg}iݺeۺy( 5ˋ]W_[W_mzyAt OO˶>kJUGƌCrr2~c-Z\u͕U>^ZZZ5w8p~qkXYtV3եWYA07n+V믿&,,۸yP{ωkZxiݻ-[k_F 'xؽ{Ʋe|K/K/dxxx}]_rra̝;*-k3ecO?d?cxxx}0*7x㏍}?1yd0/_^ƙ__w}_}֥װHKK3 x׍4Æa89X99X>:9XYG}0RRRΝ={F̝;h۶eŕ4nrSRRX 5ϟ>.]jo4V*ӿn.z5\cx{{52n/`a>>>;sեG\w:9x_Cgc2E]("""bEDDD\Qq1 """".FPDDD(@("""bEDDD\Qq1 """".FPDDD(@("""bEDDD\Qq1 """".FPDDD(@("""bEDDD\Qq1 """".FPDDD(cQv^sIENDB`mir_eval-0.8.2/tests/data/000077500000000000000000000000001475740344600154105ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/alignment/000077500000000000000000000000001475740344600173665ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/alignment/est00.txt000066400000000000000000000000531475740344600210600ustar00rootroot000000000000000.0 1.0 2.0 3.0 8.0 9.0 10.0 15.0 16.0 17.0mir_eval-0.8.2/tests/data/alignment/est01.txt000066400000000000000000000000531475740344600210610ustar00rootroot000000000000000.5 1.5 2.5 3.5 8.5 9.5 10.5 15.5 16.5 17.5mir_eval-0.8.2/tests/data/alignment/est02.txt000066400000000000000000000000601475740344600210600ustar00rootroot000000000000000.1 1.2 2.3 3.4 8.5 9.6 10.7 15.8 16.9 18.0 35.0mir_eval-0.8.2/tests/data/alignment/est03_mirex.txt000066400000000000000000000000641475740344600222710ustar00rootroot000000000000002.17454162309 2.57454162309 5.20 6.20 6.20 11.911836mir_eval-0.8.2/tests/data/alignment/est04_mirex.txt000066400000000000000000000000271475740344600222710ustar00rootroot000000000000002.17454162309 5.20 6.20mir_eval-0.8.2/tests/data/alignment/output00.json000066400000000000000000000001211475740344600217530ustar00rootroot00000000000000{"pc": 1.0, "mae": 0.0, "aae": 0.0, "pcs": 1.0, "perceptual": 0.9606239680360235}mir_eval-0.8.2/tests/data/alignment/output01.json000066400000000000000000000001401475740344600217550ustar00rootroot00000000000000{"pc": 0.0, "mae": 0.5, "aae": 0.5, "pcs": 0.7352941176470589, "perceptual": 0.0833538912522229}mir_eval-0.8.2/tests/data/alignment/output02.json000066400000000000000000000002161475740344600217620ustar00rootroot00000000000000{"pc": 0.2727272727272727, "mae": 0.5999999999999996, "aae": 1.8636363636363635, "pcs": 0.7250000000000001, "perceptual": 0.17994453887587472}mir_eval-0.8.2/tests/data/alignment/output03_mirex.json000066400000000000000000000002131475740344600231640ustar00rootroot00000000000000{"pc": 0.16666666666666666, "mae": 0.7999999999999998, "aae": 0.9625763961515, "pcs": 0.5591983153121662, "perceptual": 0.1679578367769917}mir_eval-0.8.2/tests/data/alignment/output04_mirex.json000066400000000000000000000001761475740344600231750ustar00rootroot00000000000000{"pc": 0, "mae": 0.7999999999999998, "aae": 0.9784861256363334, "pcs": 0.5395690469032295, "perceptual": 0.014511670347043502}mir_eval-0.8.2/tests/data/alignment/ref00.txt000077500000000000000000000000531475740344600210440ustar00rootroot000000000000000.0 1.0 2.0 3.0 8.0 9.0 10.0 15.0 16.0 17.0mir_eval-0.8.2/tests/data/alignment/ref01.txt000077500000000000000000000000531475740344600210450ustar00rootroot000000000000000.0 1.0 2.0 3.0 8.0 9.0 10.0 15.0 16.0 17.0mir_eval-0.8.2/tests/data/alignment/ref02.txt000077500000000000000000000000601475740344600210440ustar00rootroot000000000000000.0 1.0 2.0 3.0 8.0 9.0 10.0 15.0 16.0 17.0 20.0mir_eval-0.8.2/tests/data/alignment/ref03_mirex.txt000077500000000000000000000000741475740344600222560ustar00rootroot000000000000000.624541623091 4.61454162309 4.61454162309 7.0 7.0 11.911836mir_eval-0.8.2/tests/data/alignment/ref04_mirex.txt000077500000000000000000000000401475740344600222500ustar00rootroot000000000000000.624541623091 4.61454162309 7.0mir_eval-0.8.2/tests/data/beat/000077500000000000000000000000001475740344600163235ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/beat/est00.txt000066400000000000000000000314061475740344600200230ustar00rootroot00000000000000# A comment 3.572970521541950273e+00 4.040272108843537602e+00 4.495963718820862098e+00 4.879092970521542227e+00 5.311564625850340171e+00 5.770158730158730265e+00 6.217142857142857082e+00 6.649614512471655026e+00 7.093696145124716246e+00 7.648072562358276372e+00 8.199546485260771789e+00 8.588480725623583112e+00 8.997732426303855391e+00 9.441814058956916611e+00 9.894603174603174622e+00 1.029804988662131571e+01 1.076535147392290170e+01 1.122975056689342388e+01 1.181024943310657527e+01 1.231238095238095198e+01 1.275936507936507880e+01 1.311927437641723415e+01 1.351691609977324227e+01 1.398421768707483004e+01 1.443120181405895686e+01 1.491301587301587261e+01 1.537160997732426360e+01 1.583891156462584959e+01 1.628299319727891259e+01 1.672997732426303941e+01 1.715374149659863789e+01 1.771392290249433188e+01 1.816380952380952252e+01 1.866013605442176981e+01 1.911002267573696045e+01 1.949605442176870795e+01 1.992272108843537382e+01 2.038131519274376302e+01 2.078766439909297148e+01 2.121142857142856997e+01 2.167292517006802655e+01 2.221859410430839077e+01 2.278458049886621239e+01 2.324897959183673635e+01 2.369596371882086316e+01 2.414004535147392261e+01 2.457251700680271966e+01 2.503981859410430744e+01 2.537650793650793801e+01 2.582349206349206483e+01 2.628498866213151786e+01 2.673777777777777942e+01 2.731247165532879961e+01 2.781170068027210718e+01 2.828190476190476232e+01 2.875791383219954511e+01 2.923392290249433145e+01 2.959963718820861800e+01 3.002049886621315267e+01 3.040943310657596399e+01 3.088834467120181415e+01 3.135564625850340192e+01 3.176199546485260683e+01 3.221188208616779747e+01 3.269950113378684620e+01 3.322775510204081684e+01 3.364861678004535150e+01 3.417977324263038241e+01 3.464707482993197374e+01 3.508825396825396581e+01 3.554394557823129475e+01 3.598802721088435419e+01 3.644371882086167602e+01 3.687328798185941281e+01 3.732317460317459989e+01 3.783111111111111313e+01 3.831292517006802711e+01 3.877151927437641632e+01 3.921850340136054314e+01 3.970031746031745712e+01 4.023147392290249513e+01 4.069587301587301909e+01 4.116897959183673805e+01 4.165659863945577968e+01 4.208616780045351646e+01 4.253315192743764328e+01 4.298594104308389774e+01 4.334294784580498572e+01 4.373768707482993534e+01 4.424852607709750885e+01 4.474195011337868522e+01 4.519764172335600705e+01 4.565623582766439625e+01 4.611773242630385283e+01 4.657342403628118177e+01 4.716263038548753173e+01 4.767346938775510523e+01 4.819301587301587375e+01 4.864870748299319558e+01 4.908408163265306001e+01 4.944399092970521536e+01 4.986485260770975003e+01 5.032054421768707186e+01 5.073560090702947889e+01 5.120000000000000284e+01 5.174276643990929614e+01 5.230585034013605394e+01 5.276734693877551052e+01 5.318240362811791044e+01 5.358875283446712245e+01 5.400380952380952237e+01 5.447401360544217397e+01 5.492680272108843553e+01 5.534766439909297020e+01 5.579755102040816439e+01 5.622131519274376643e+01 5.669732426303854567e+01 5.715301587301587460e+01 5.761160997732426381e+01 5.805569160997732325e+01 5.852009070294784721e+01 5.901931972789115832e+01 5.948662131519274254e+01 6.007582766439909250e+01 6.058086167800453836e+01 6.100752834467120067e+01 6.150675736961451179e+01 6.194213151927437622e+01 6.240653061224490017e+01 6.289414965986394890e+01 6.333823129251700834e+01 6.381424036281179468e+01 6.428444444444444628e+01 6.475174603174603760e+01 6.519873015873015731e+01 6.565442176870747915e+01 6.611301587301586835e+01 6.658321995464852705e+01 6.701569160997732411e+01 6.745977324263039065e+01 6.791546485260771249e+01 6.834213151927437480e+01 6.882394557823128878e+01 6.929995464852608222e+01 6.974984126984126931e+01 7.021424036281179326e+01 7.066412698412698035e+01 7.113723356009070642e+01 7.156680272108843610e+01 7.206022675736961958e+01 7.251011337868480666e+01 7.297741496598639799e+01 7.342730158730158507e+01 7.389750566893424377e+01 7.435029478458049823e+01 7.481469387755102218e+01 7.526748299319727664e+01 7.570866213151927582e+01 7.617306122448979977e+01 7.652716553287982038e+01 7.694802721088434794e+01 7.737469387755102446e+01 7.781877551020407680e+01 7.828317460317460075e+01 7.876498866213151473e+01 7.922068027210883656e+01 7.968217687074829314e+01 8.009433106575963279e+01 8.055582766439908937e+01 8.100571428571429067e+01 8.149623582766439256e+01 8.191709750566893433e+01 8.236408163265306825e+01 8.281977324263039009e+01 8.327836734693877929e+01 8.372244897959183163e+01 8.415201814058957552e+01 8.461641723356008526e+01 8.507501133786847447e+01 8.552199546485260839e+01 8.600671201814058975e+01 8.644789115646258892e+01 8.690648526077097813e+01 8.735056689342403047e+01 8.781786848072562179e+01 8.837514739229024485e+01 8.882793650793651352e+01 8.927782312925170061e+01 8.973641723356008981e+01 9.018920634920634427e+01 9.063909297052154557e+01 9.110639455782312268e+01 9.158820861678005087e+01 9.204390022675737271e+01 9.249959183673469454e+01 9.291174603174603419e+01 9.331229024943310435e+01 9.377378684807256093e+01 9.421786848072562748e+01 9.470548752834467621e+01 9.519310657596372494e+01 9.568072562358275945e+01 9.613931972789116287e+01 9.662113378684807685e+01 9.706521541950112919e+01 9.753251700680272052e+01 9.797369614512471969e+01 9.841777777777777203e+01 9.888507936507936336e+01 9.934947845804988731e+01 9.979646258503400702e+01 1.002782766439909352e+02 1.007310657596371897e+02 1.011896598639455789e+02 1.016453514739229007e+02 1.021097505668934247e+02 1.025683446712018139e+02 1.030559637188208626e+02 1.035203628117913865e+02 1.039557369614512510e+02 1.043998185941043033e+02 1.048468027210884372e+02 1.052850793650793690e+02 1.057494784580498930e+02 1.062341950113378743e+02 1.067392290249433131e+02 1.072994104308390035e+02 1.077551020408163254e+02 1.082398185941043067e+02 1.087013151927437633e+02 1.091657142857142873e+02 1.096388208616779991e+02 1.100945124716553352e+02 1.105589115646258449e+02 1.110262131519274362e+02 1.114848072562358254e+02 1.118853514739228956e+02 1.123062131519274374e+02 1.127415873015873018e+02 1.132146938775510137e+02 1.136878004535147397e+02 1.141405895691609942e+02 1.145788662131519260e+02 1.150461678004535173e+02 1.155628117913832256e+02 1.160359183673469374e+02 1.164364625850340076e+02 1.169269841269841237e+02 1.173681632653061229e+02 1.178499773242630368e+02 1.183056689342403587e+02 1.187497505668934252e+02 1.191996371882086123e+02 1.196495238095238136e+02 1.201545578231292524e+02 1.205812244897959147e+02 1.211559183673469420e+02 1.216116099773242638e+02 1.220992290249433125e+02 1.224765532879818579e+02 1.229206349206349245e+02 1.233705215419501116e+02 1.238407256235827703e+02 1.242848072562358226e+02 1.247753287981859387e+02 1.252716553287981895e+02 1.257360544217687135e+02 1.262381859410430849e+02 1.267199999999999989e+02 1.271814965986394554e+02 1.276487981859410468e+02 1.281160997732426381e+02 1.285659863945578252e+02 1.290013605442176754e+02 1.294628571428571320e+02 1.299272562358276559e+02 1.304061678004535167e+02 1.309024943310657534e+02 1.313639909297052100e+02 1.318341950113378687e+02 1.323014965986394600e+02 1.327658956916099839e+02 1.332883446712018269e+02 1.337730612244897941e+02 1.342287528344671159e+02 1.346989569160997746e+02 1.351720634920635007e+02 1.356248526077097551e+02 1.360805442176870770e+02 1.365536507936508031e+02 1.370151473922902596e+02 1.374650340136054467e+02 1.379787755102040876e+02 1.384751020408163242e+02 1.389772335600906956e+02 1.395577324263038577e+02 1.400047165532879774e+02 1.405010430839002140e+02 1.409886621315192770e+02 1.413282539682539607e+02 1.417955555555555520e+02 1.423209070294784624e+02 1.427591836734693800e+02 1.431945578231292586e+02 1.436705668934240236e+02 1.442162358276644056e+02 1.446806349206349296e+02 1.450550566893423934e+02 1.455455782312925237e+02 1.460273922902494235e+02 1.464801814058956779e+02 1.469968253968253862e+02 1.474699319727891123e+02 1.479401360544217710e+02 1.483958276643990928e+02 1.488515192743764146e+02 1.493217233560090733e+02 1.497745124716553278e+02 1.502214965986394475e+02 1.507004081632653083e+02 1.511822222222222081e+02 1.517017687074829837e+02 1.521574603174603055e+02 1.526682993197278790e+02 1.531297959183673356e+02 1.536116099773242638e+02 1.540614965986394509e+02 1.544649433106575884e+02 1.549206349206349103e+02 1.554111564625850406e+02 1.558639455782312950e+02 1.563660770975056664e+02 1.568420861678004599e+02 1.573093877551020512e+02 1.577563718820861709e+02 1.581888435374149537e+02 1.586590476190476124e+02 1.591321541950113385e+02 1.595849433106575930e+02 1.600754648526077233e+02 1.605572789115646231e+02 1.611145578231292461e+02 1.615528344671201921e+02 1.620288435374149572e+02 1.625629024943310696e+02 1.630418140589569020e+02 1.635149206349206281e+02 1.639764172335600847e+02 1.644292063492063392e+02 1.648326530612244767e+02 1.652825396825396922e+02 1.658688435374149606e+02 1.663651700680271972e+02 1.668324716553287885e+02 1.672881632653061104e+02 1.677032199546485174e+02 1.681676190476190413e+02 1.686610430839002390e+02 1.691051247165532914e+02 1.695927437641723259e+02 1.700687528344671193e+02 1.705215419501133738e+02 1.710207709750566778e+02 1.714880725623582691e+02 1.719408616780045236e+02 1.724110657596371823e+02 1.728870748299319757e+02 1.734762811791383115e+02 1.739784126984127113e+02 1.744834467120181500e+02 1.749130158730158655e+02 1.752990476190476272e+02 1.757605442176870838e+02 1.762249433106576078e+02 1.767096598639455749e+02 1.771740589569160989e+02 1.776471655328798249e+02 1.781028571428571468e+02 1.785672562358276707e+02 1.790519727891156379e+02 1.795395918367347008e+02 1.800330158730158701e+02 1.804799999999999898e+02 1.809647165532879853e+02 1.814407256235827788e+02 1.819341496598639480e+02 1.823898412698412699e+02 1.829035827664399108e+02 1.833970068027210800e+02 1.838468934240362671e+02 1.843519274376417343e+02 1.848482539682539709e+02 1.852865306122448885e+02 1.857248072562358345e+02 1.862327437641723407e+02 1.867058503401360667e+02 1.871528344671201864e+02 1.875911111111111040e+02 1.880787301587301670e+02 1.885286167800453541e+02 1.890510657596371971e+02 1.895183673469387884e+02 1.899537414965986386e+02 1.904674829931972795e+02 1.909405895691610056e+02 1.914165986394557706e+02 1.918664852607709861e+02 1.923482993197278859e+02 1.928649433106575941e+02 1.933264399092970507e+02 1.937705215419501030e+02 1.942233106575963859e+02 1.947080272108843531e+02 1.951608163265306075e+02 1.956339229024943336e+02 1.960896145124716554e+02 1.965511111111111120e+02 1.970242176870748381e+02 1.974682993197278904e+02 1.979326984126984144e+02 1.984116099773242752e+02 1.988760090702947707e+02 1.993607256235827663e+02 1.998222222222222229e+02 2.002924263038548816e+02 2.007771428571428487e+02 2.012560544217687095e+02 2.017494784580498788e+02 2.022167800453514701e+02 2.027102040816326394e+02 2.031310657596371811e+02 2.036157823129251767e+02 2.041121088435374133e+02 2.045707029478458026e+02 2.050438095238095286e+02 2.055111111111111200e+02 2.059551927437641723e+02 2.064224943310657636e+02 2.068897959183673549e+02 2.073512925170068115e+02 2.078185941043084028e+02 2.083004081632653026e+02 2.087880272108843656e+02 2.092582312925169958e+02 2.097023129251700766e+02 2.102073469387755154e+02 2.106920634920634825e+02 2.111593650793650738e+02 2.116150566893423957e+02 2.121433106575963734e+02 2.126251247165533016e+02 2.130924263038548645e+02 2.136061678004535054e+02 2.140792743764172315e+02 2.145146485260771101e+02 2.150080725623582794e+02 2.155014965986394486e+02 2.159600907029478378e+02 2.164419047619047660e+02 2.169179138321995595e+02 2.173823129251700550e+02 2.178496145124716463e+02 2.183111111111111029e+02 2.187697052154194921e+02 2.192457142857142856e+02 2.196868934240362705e+02 2.201309750566893513e+02 2.206302040816326553e+02 2.210975056689342466e+02 2.215590022675737032e+02 2.220437188208616703e+02 2.225168253968253964e+02 2.229725170068027182e+02 2.234485260770975117e+02 2.239013151927437661e+02 2.243686167800453575e+02 2.248272108843537467e+02 2.253351473922902528e+02 2.257531065759637272e+02 2.261971882086167795e+02 2.266499773242630340e+02 2.271230839002267601e+02 2.276136054421768620e+02 2.281012244897959249e+02 2.285801360544217573e+02 2.290445351473922813e+02 2.295147392290249400e+02 2.299791383219954639e+02 2.304232199546485163e+02 2.308760090702947707e+02 2.313694331065759684e+02 2.318686621315192724e+02 2.323882086167800480e+02 2.328148752834467246e+02 2.332444444444444400e+02 2.337030385487528292e+02 2.342806349206349239e+02 2.347479365079365152e+02 2.352210430839002129e+02 2.356128798185941093e+02 2.360105215419501121e+02 2.365097505668934161e+02 2.370089795918367486e+02 2.374385487528344640e+02 2.378942403628117859e+02 2.383673469387755119e+02 2.388520634920634791e+02 2.393425850340136094e+02 2.398040816326530660e+02 2.402626757369614552e+02 2.407125623582766423e+02 2.411479365079365209e+02 2.416181405895691512e+02 2.421318820861677921e+02 2.425933786848072486e+02 2.430780952380952442e+02 2.435453968253968355e+02 2.440301133786848027e+02 2.444829024943310571e+02 2.449414965986394463e+02 2.453971882086167682e+02 2.458760997732426290e+02 mir_eval-0.8.2/tests/data/beat/est01.txt000066400000000000000000000366371475740344600200370ustar00rootroot000000000000003.909659863945578184e+00 4.382766439909296707e+00 4.876190476190476630e+00 5.355102040816326792e+00 5.744036281179138115e+00 6.156190476190475991e+00 6.603174603174602808e+00 7.140136054421768463e+00 7.642267573696145178e+00 8.080544217687075204e+00 8.544943310657595603e+00 9.023854875283447541e+00 9.584036281179137973e+00 1.000489795918367264e+01 1.045768707482993243e+01 1.097142857142857153e+01 1.143873015873015930e+01 1.188571428571428612e+01 1.231528344671201758e+01 1.278258503401360535e+01 1.323247165532879777e+01 1.374040816326530567e+01 1.420770975056689345e+01 1.474467120181405910e+01 1.524680272108843582e+01 1.569378684807256263e+01 1.618721088435374256e+01 1.667192743764172391e+01 1.713342403628118049e+01 1.757170068027210874e+01 1.806802721088435248e+01 1.853823129251700763e+01 1.899972789115646421e+01 1.947573696145124700e+01 1.992272108843537382e+01 2.039002267573696159e+01 2.101405895691609871e+01 2.149587301587301624e+01 2.198349206349206497e+01 2.245079365079364919e+01 2.291519274376417314e+01 2.335346938775510139e+01 2.383238095238095156e+01 2.428517006802720957e+01 2.479891156462585045e+01 2.524589569160997726e+01 2.569868480725623527e+01 2.614857142857142946e+01 2.660716553287981867e+01 2.706866213151927525e+01 2.751274376417233469e+01 2.785814058956916028e+01 2.827609977324263113e+01 2.874630385487528272e+01 2.922521541950113289e+01 2.970702947845805042e+01 3.013369614512471628e+01 3.071999999999999886e+01 3.117569160997732425e+01 3.152689342403628103e+01 3.196807256235827666e+01 3.253986394557823303e+01 3.300426303854874988e+01 3.347156462585034120e+01 3.381696145124716679e+01 3.424943310657596385e+01 3.469641723356009066e+01 3.514920634920635223e+01 3.554104308390022737e+01 3.604897959183673350e+01 3.665269841269841322e+01 3.711999999999999744e+01 3.759600907029478378e+01 3.796172335600906678e+01 3.838258503401360855e+01 3.884117913832199775e+01 3.929977324263038696e+01 3.979609977324263070e+01 4.033306122448979636e+01 4.084390022675736986e+01 4.130539682539682644e+01 4.174367346938775825e+01 4.210938775510204124e+01 4.253895691609977092e+01 4.300625850340136225e+01 4.347936507936508121e+01 4.389732426303854851e+01 4.438784580498866461e+01 4.485804988662131620e+01 4.532825396825396780e+01 4.577523809523809462e+01 4.626285714285714334e+01 4.673596371882086231e+01 4.717424036281179411e+01 4.776344671201814407e+01 4.822494331065759354e+01 4.870095238095237988e+01 4.915083900226757407e+01 4.961523809523809803e+01 5.008834467120181699e+01 5.058176870748299336e+01 5.105487528344671233e+01 5.151346938775510154e+01 5.198657596371882050e+01 5.247419501133786923e+01 5.291827664399092868e+01 5.337396825396825051e+01 5.388190476190476375e+01 5.432018140589568844e+01 5.475845804988662024e+01 5.520834467120181444e+01 5.566984126984127101e+01 5.614004535147392261e+01 5.659283446712018417e+01 5.708916099773242792e+01 5.759419501133786667e+01 5.804117913832199349e+01 5.847655328798185792e+01 5.895546485260771163e+01 5.942857142857143060e+01 5.987845804988662479e+01 6.033124716553287925e+01 6.080725623582766559e+01 6.126294784580498742e+01 6.173315192743763902e+01 6.218594104308390058e+01 6.266195011337868692e+01 6.314956916099773565e+01 6.361396825396825250e+01 6.406675736961450696e+01 6.452535147392289616e+01 6.492879818594104790e+01 6.532063492063491594e+01 6.578213151927437252e+01 6.628426303854875812e+01 6.676607709750567210e+01 6.726240362811790874e+01 6.773260770975056744e+01 6.821732426303854879e+01 6.869043083900226065e+01 6.913451247165532720e+01 6.961052154195010644e+01 7.009814058956915517e+01 7.057995464852608336e+01 7.105886621315192997e+01 7.154068027210884395e+01 7.201668934240362319e+01 7.249269841269841663e+01 7.294839002267573846e+01 7.342439909297051770e+01 7.392072562358276855e+01 7.438222222222222513e+01 7.487564625850339439e+01 7.534004535147391834e+01 7.582476190476189970e+01 7.629496598639455840e+01 7.676226757369614973e+01 7.721795918367347156e+01 7.768816326530611605e+01 7.813224489795918259e+01 7.859374149659863917e+01 7.904362811791382626e+01 7.949351473922902755e+01 7.992888888888889198e+01 8.039038548752834856e+01 8.088671201814058520e+01 8.135981859410431127e+01 8.184163265306122526e+01 8.231473922902493712e+01 8.278494331065759582e+01 8.326095238095237505e+01 8.375727891156462590e+01 8.421006802721088036e+01 8.466866213151926956e+01 8.513306122448979352e+01 8.562648526077097699e+01 8.606766439909297617e+01 8.654947845804989015e+01 8.699356009070294249e+01 8.743183673469387429e+01 8.787591836734694084e+01 8.836063492063492220e+01 8.881342403628117665e+01 8.927782312925170061e+01 8.972190476190476716e+01 9.020081632653061376e+01 9.065941043083900297e+01 9.111510204081632480e+01 9.155047619047618923e+01 9.198585034013605366e+01 9.247056689342403502e+01 9.295528344671201637e+01 9.341678004535147295e+01 9.387827664399092953e+01 9.435138321995465560e+01 9.481578231292516534e+01 9.525405895691609715e+01 9.574167800453514587e+01 9.624671201814058463e+01 9.669659863945578593e+01 9.715229024943310776e+01 9.761378684807256434e+01 9.809850340136054569e+01 9.856870748299319018e+01 9.903310657596371414e+01 9.948009070294784806e+01 9.993578231292516989e+01 1.003943764172335591e+02 1.008645804988662178e+02 1.013492970521541992e+02 1.017788662131519288e+02 1.022751927437641655e+02 1.027512018140589589e+02 1.031807709750566886e+02 1.036567800453514678e+02 1.041182766439909244e+02 1.045826757369614484e+02 1.050412698412698376e+02 1.055085714285714289e+02 1.060223129251700698e+02 1.065012244897959164e+02 1.069511111111111177e+02 1.074416326530612196e+02 1.080192290249433142e+02 1.084923356009070261e+02 1.089596371882086174e+02 1.094095238095238045e+02 1.098448979591836689e+02 1.103296145124716503e+02 1.107911111111111069e+02 1.112642176870748330e+02 1.117431292517006796e+02 1.121843083900226787e+02 1.126312925170067984e+02 1.130724716553287976e+02 1.135310657596371868e+02 1.139954648526077108e+02 1.144424489795918305e+02 1.149213605442176913e+02 1.153799546485260805e+02 1.158443537414966045e+02 1.163087528344671142e+02 1.167586394557823155e+02 1.172201360544217721e+02 1.176932426303854839e+02 1.181344217687074831e+02 1.186162358276643971e+02 1.191038548752834458e+02 1.195537414965986329e+02 1.199949206349206321e+02 1.204593197278911560e+02 1.209295238095238147e+02 1.213939229024943245e+02 1.218583219954648484e+02 1.223140136054421703e+02 1.227842176870748290e+02 1.232544217687074877e+02 1.237043083900226748e+02 1.241396825396825392e+02 1.245750566893424036e+02 1.250452607709750623e+02 1.255067573696145189e+02 1.259914739229025002e+02 1.264616780045351447e+02 1.269463945578231261e+02 1.274165986394557848e+02 1.278780952380952414e+02 1.283570068027210880e+02 1.288068934240362751e+02 1.292712925170067990e+02 1.297095691609977450e+02 1.301768707482993079e+02 1.306267573696145234e+02 1.310853514739229126e+02 1.315526530612245040e+02 1.319909297052154216e+02 1.324263038548752718e+02 1.329139229024943347e+02 1.333696145124716566e+02 1.338253061224489784e+02 1.342955102040816371e+02 1.346641269841269946e+02 1.350849886621315079e+02 1.355464852607709645e+02 1.360108843537414884e+02 1.364607709750566755e+02 1.369425850340136037e+02 1.373953741496598582e+02 1.378597732426303821e+02 1.382951473922902608e+02 1.387885714285714300e+02 1.392907029478458014e+02 1.398073469387755097e+02 1.402949659863945442e+02 1.407593650793650681e+02 1.412382766439909290e+02 1.416852607709750487e+02 1.421583673469387747e+02 1.426198639455782313e+02 1.430842630385487553e+02 1.435457596371882119e+02 1.440072562358276684e+02 1.444484353741496534e+02 1.449128344671201774e+02 1.452321088435374179e+02 1.456616780045351334e+02 1.461057596371882141e+02 1.465527437641723338e+02 1.470287528344671273e+02 1.476063492063491935e+02 1.480736507936507849e+02 1.485119274376417309e+02 1.489763265306122548e+02 1.494262131519274419e+02 1.498993197278911680e+02 1.503404988662131530e+02 1.507990929705215422e+02 1.512315646258503534e+02 1.516698412698412710e+02 1.521284353741496602e+02 1.525696145124716452e+02 1.529092063492063573e+02 1.533184580498866296e+02 1.537567346938775472e+02 1.541804988662131564e+02 1.547406802721088468e+02 1.552166893424036402e+02 1.556839909297052031e+02 1.561338775510204187e+02 1.565866666666666731e+02 1.570162358276643886e+02 1.574516099773242672e+02 1.578898866213151848e+02 1.582991383219954571e+02 1.587722448979591832e+02 1.592308390022675724e+02 1.596981405895691637e+02 1.601393197278911487e+02 1.606037188208616726e+02 1.610594104308389944e+02 1.615034920634920752e+02 1.619620861678004644e+02 1.624148752834467189e+02 1.628734693877551081e+02 1.633262585034013625e+02 1.637935600907029539e+02 1.642608616780045452e+02 1.647397732426303776e+02 1.651838548752834583e+02 1.655205442176870747e+02 1.659385034013605491e+02 1.663622675736961583e+02 1.668673015873015970e+02 1.672939682539682451e+02 1.677409523809523932e+02 1.681995464852607824e+02 1.686117006802721221e+02 1.690993197278911566e+02 1.696565986394557797e+02 1.701993650793650659e+02 1.706724716553287919e+02 1.711310657596371811e+02 1.715693424036281272e+02 1.719321541950113499e+02 1.723762358276644022e+02 1.728406349206349262e+02 1.733224489795918259e+02 1.737868480725623499e+02 1.742251247165532959e+02 1.746779138321995504e+02 1.751336054421768722e+02 1.755980045351473962e+02 1.760304761904761790e+02 1.765093877551020398e+02 1.769679818594104290e+02 1.774178684807256161e+02 1.778648526077097642e+02 1.783379591836734619e+02 1.787704308390022732e+02 1.792145124716553255e+02 1.796673015873015800e+02 1.800852607709750544e+02 1.805641723356009152e+02 1.809966439909296980e+02 1.814407256235827788e+02 1.818731972789115616e+02 1.823404988662131530e+02 1.827816780045351379e+02 1.832199546485260839e+02 1.836785487528344731e+02 1.842648526077097415e+02 1.847408616780045350e+02 1.851268934240362682e+02 1.855216326530612321e+02 1.859453968253968128e+02 1.864243083900226736e+02 1.868858049886621302e+02 1.873298866213151825e+02 1.877971882086167739e+02 1.882615873015872978e+02 1.887201814058956870e+02 1.891729705215419415e+02 1.896315646258503307e+02 1.900756462585034114e+02 1.906300226757369671e+02 1.910973242630385585e+02 1.915675283446711887e+02 1.920348299319727801e+02 1.924992290249433040e+02 1.929346031746031827e+02 1.933148299319727812e+02 1.937327891156462556e+02 1.942000907029478469e+02 1.946557823129251688e+02 1.950679365079365084e+02 1.955091156462584934e+02 1.959357823129251699e+02 1.963624489795918464e+02 1.969139229024943347e+02 1.973551020408163197e+02 1.978282086167800458e+02 1.983013151927437718e+02 1.987657142857142958e+02 1.992156009070294829e+02 1.996074376417233509e+02 1.999847619047619105e+02 2.004607709750566755e+02 2.008932426303854868e+02 2.013518367346938760e+02 2.018510657596371800e+02 2.023764172335600904e+02 2.028030839002267669e+02 2.032907029478458014e+02 2.037318820861677864e+02 2.041875736961451366e+02 2.046200453514739195e+02 2.050409070294784613e+02 2.054995011337868505e+02 2.059580952380952397e+02 2.063412244897959056e+02 2.067272562358276673e+02 2.071713378684807196e+02 2.076299319727891088e+02 2.080769160997732286e+02 2.085180952380952419e+02 2.089912018140589680e+02 2.094556009070294920e+02 2.099025850340136117e+02 2.103582766439909335e+02 2.107965532879818511e+02 2.113480272108843678e+02 2.118037188208616897e+02 2.122419954648526073e+02 2.126918820861677943e+02 2.131533786848072509e+02 2.136293877551020444e+02 2.141053968253968378e+02 2.145581859410430923e+02 2.150051700680272120e+02 2.154753741496598707e+02 2.158904308390022777e+02 2.163345124716553300e+02 2.167989115646258540e+02 2.171878458049886547e+02 2.176232199546485333e+02 2.180702040816326530e+02 2.185317006802721096e+02 2.189815873015872967e+02 2.194692063492063596e+02 2.198987755102040751e+02 2.203747845804988685e+02 2.208362811791383251e+02 2.213209977324262923e+02 2.217505668934240362e+02 2.222120634920634927e+02 2.226619501133786798e+02 2.231205442176870690e+02 2.235791383219954582e+02 2.240116099773242695e+02 2.244295691609977439e+02 2.248330158730158814e+02 2.252625850340135969e+02 2.256921541950113408e+02 2.262320181405895596e+02 2.266906122448979488e+02 2.271259863945578275e+02 2.275700680272108798e+02 2.280373696145124711e+02 2.284959637188208603e+02 2.289226303854875368e+02 2.292564172335600858e+02 2.297150113378684750e+02 2.301910204081632685e+02 2.306438095238095229e+02 2.311517460317460291e+02 2.315987301587301488e+02 2.320631292517006727e+02 2.325014058956916188e+02 2.328874376417233520e+02 2.333547392290249434e+02 2.337901133786847936e+02 2.342370975056689417e+02 2.346985941043083983e+02 2.351629931972789223e+02 2.356244897959183788e+02 2.360685714285714312e+02 2.364894331065759729e+02 2.369219047619047558e+02 2.373601814058957018e+02 2.377955555555555520e+02 2.382744671201814128e+02 2.387504761904761779e+02 2.391858503401360565e+02 2.396328344671201762e+02 2.401785034013605582e+02 2.406399999999999864e+02 2.409795918367346985e+02 2.414468934240362898e+02 2.419112925170068138e+02 2.423727891156462704e+02 2.428458956916099680e+02 2.432986848072562225e+02 2.437543764172335727e+02 2.442071655328798272e+02 2.446947845804988617e+02 2.451127437641723361e+02 2.455510204081632537e+02 2.459892970521541997e+02 2.464478911564625889e+02 2.469151927437641802e+02 2.473970068027210800e+02 2.478643083900226713e+02 2.482938775510204152e+02 2.487466666666666697e+02 2.491878458049886547e+02 2.496464399092970439e+02 2.501253514739229047e+02 2.505810430839002265e+02 2.510570521541950200e+02 2.515069387755102071e+02 2.519539229024943268e+02 2.524038095238095138e+02 2.528624036281179031e+02 2.534109750566893524e+02 2.538869841269841174e+02 2.542643083900226770e+02 2.547229024943310662e+02 2.551698866213151859e+02 2.556255782312925078e+02 2.560551473922902233e+02 2.565195464852607756e+02 2.569781405895691364e+02 2.574106122448979477e+02 2.578430839002267589e+02 2.582784580498866376e+02 2.587312471655328636e+02 2.591956462585034160e+02 2.596542403628117768e+02 2.601128344671201944e+02 2.605424036281179383e+02 2.610213151927437707e+02 2.614770068027210641e+02 2.620429931972789177e+02 2.624841723356009311e+02 2.629630839002267635e+02 2.634100680272109116e+02 2.638628571428571377e+02 2.642634013605442078e+02 2.646697505668934127e+02 2.651080272108843587e+02 2.655521088435374395e+02 2.660252154195011371e+02 2.664605895691610158e+02 2.669191836734693766e+02 2.673980952380952658e+02 2.678682993197278961e+02 2.683268934240362569e+02 2.687651700680272029e+02 2.692382766439909574e+02 2.696881632653061160e+02 2.700683900226757146e+02 2.705124716553287954e+02 2.709971882086167625e+02 2.714819047619047865e+02 2.719114739229024735e+02 2.723439455782312848e+02 2.727967346938775677e+02 2.732524263038548611e+02 2.736994104308390092e+02 2.741609070294784374e+02 2.746456235827664614e+02 2.752406349206349319e+02 2.757050340136054274e+02 2.761607256235827776e+02 2.765931972789115889e+02 2.769385941043083790e+02 2.773623582766439881e+02 2.778383673469387531e+02 2.782737414965986318e+02 2.787961904761904748e+02 2.792809070294784419e+02 2.797075736961451184e+02 2.802619501133787026e+02 2.807350566893424002e+02 2.811704308390022788e+02 2.816609523809523807e+02 2.820818140589569225e+02 2.825084807256235990e+02 2.829612698412698251e+02 2.833734240362811647e+02 2.838291156462585150e+02 2.843109297052154147e+02 2.847985487528344493e+02 2.853674376417233702e+02 2.858637641723356069e+02 2.863542857142857088e+02 2.868012698412698569e+02 2.872859863945578240e+02 2.876691156462584900e+02 2.880580498866212906e+02 2.884237641723356091e+02 2.887807709750566687e+02 2.892509750566893558e+02 2.897298866213151882e+02 2.901942857142857406e+02 2.906731972789115730e+02 2.911404988662131359e+02 2.916048979591836883e+02 2.920867120181405880e+02 2.925395011337868709e+02 2.930561451247165792e+02 mir_eval-0.8.2/tests/data/beat/est02.txt000066400000000000000000000275041475740344600200310ustar00rootroot000000000000002.345215419501133880e+00 2.757369614512471756e+00 3.123083900226757414e+00 3.549750566893424164e+00 3.941587301587301528e+00 4.324716553287982101e+00 4.707845804988662231e+00 5.032925170068026866e+00 5.358004535147392389e+00 5.700498866213151494e+00 6.086530612244898109e+00 6.481269841269841514e+00 6.873106575963718434e+00 7.270748299319728325e+00 7.650975056689341969e+00 8.054421768707483054e+00 8.434648526077097586e+00 8.809070294784580923e+00 9.290884353741496682e+00 9.688526077097504796e+00 1.007455782312925230e+01 1.043736961451247147e+01 1.084662131519274375e+01 1.125006802721088484e+01 1.163319727891156496e+01 1.195827664399092960e+01 1.230367346938775519e+01 1.267519274376417293e+01 1.308734693877551081e+01 1.350530612244897988e+01 1.389133786848072560e+01 1.429478458049886669e+01 1.467501133786848122e+01 1.511909297052154244e+01 1.560671201814058939e+01 1.600145124716553369e+01 1.641070294784580597e+01 1.681705215419501087e+01 1.720888888888888957e+01 1.762394557823129304e+01 1.802448979591836675e+01 1.841052154195011425e+01 1.881396825396825534e+01 1.919999999999999929e+01 1.960054421768707655e+01 2.000979591836734528e+01 2.039292517006802896e+01 2.077315192743764172e+01 2.108952380952380778e+01 2.147845804988662266e+01 2.187609977324262900e+01 2.223020408163265316e+01 2.262204081632653185e+01 2.303419501133786795e+01 2.344054421768707641e+01 2.383818594104308275e+01 2.428517006802720957e+01 2.475827664399092853e+01 2.518204081632653057e+01 2.559709750566893405e+01 2.599764172335600776e+01 2.640399092970521622e+01 2.681904761904761969e+01 2.722829931972789197e+01 2.761723356009070329e+01 2.800326530612244724e+01 2.841832199546485427e+01 2.883047619047619037e+01 2.923102040816326408e+01 2.961414965986394421e+01 2.993052154195011383e+01 3.031945578231292515e+01 3.072580498866213006e+01 3.112634920634920732e+01 3.154140589569161079e+01 3.192453514739229092e+01 3.234829931972789296e+01 3.275174603174603050e+01 3.314358276643991275e+01 3.352380952380952550e+01 3.390113378684807088e+01 3.430458049886621552e+01 3.472544217687075019e+01 3.512888888888888772e+01 3.553233560090703236e+01 3.590095238095238273e+01 3.628408163265306285e+01 3.671945578231292728e+01 3.713451247165532720e+01 3.754376417233559948e+01 3.792979591836734699e+01 3.833034013605442425e+01 3.871637188208616465e+01 3.915174603174602908e+01 3.952036281179138655e+01 3.991219954648526169e+01 4.046367346938775711e+01 4.089614512471655416e+01 4.129959183673469170e+01 4.166530612244898180e+01 4.203392290249433216e+01 4.245768707482993420e+01 4.284662131519274197e+01 4.327619047619047876e+01 4.366512471655328653e+01 4.410630385487528571e+01 4.446911564625850133e+01 4.488997732426303600e+01 4.529052154195011326e+01 4.570557823129252029e+01 4.607419501133787065e+01 4.649795918367347269e+01 4.690721088435374497e+01 4.730485260770974776e+01 4.773732426303855192e+01 4.812916099773242706e+01 4.856453514739229149e+01 4.896798185941042902e+01 4.937433106575963393e+01 4.976036281179138143e+01 5.019573696145124586e+01 5.060208616780045077e+01 5.101424036281179042e+01 5.143510204081632509e+01 5.183564625850340235e+01 5.225070294784580227e+01 5.273251700680272336e+01 5.316498866213152041e+01 5.360326530612245222e+01 5.403573696145124927e+01 5.445079365079364919e+01 5.486585034013605622e+01 5.528090702947845614e+01 5.569306122448979579e+01 5.610521541950113544e+01 5.652027210884353536e+01 5.693242630385487502e+01 5.735038548752834231e+01 5.777124716553287698e+01 5.816308390022675923e+01 5.856072562358276912e+01 5.895546485260771163e+01 5.936181405895691654e+01 5.976816326530612145e+01 6.017741496598639372e+01 6.057505668934240362e+01 6.090013605442177180e+01 6.125714285714285978e+01 6.169541950113378448e+01 6.211918367346938652e+01 6.249360544217687163e+01 6.291156462585033893e+01 6.331501133786848357e+01 6.378231292517006779e+01 6.422639455782312723e+01 6.465596371882085691e+01 6.505941043083900865e+01 6.541061224489796189e+01 6.575891156462584775e+01 6.616526077097505265e+01 6.658902494331066180e+01 6.694893424036281715e+01 6.738430839002268158e+01 6.778485260770975174e+01 6.816507936507936449e+01 6.857723356009070415e+01 6.897487528344670693e+01 6.938412698412697921e+01 6.980498866213152098e+01 7.020263038548752377e+01 7.062058956916099817e+01 7.104145124716553994e+01 7.145941043083900013e+01 7.190058956916099930e+01 7.231854875283447370e+01 7.283809523809523512e+01 7.325895691609977689e+01 7.361886621315193224e+01 7.402811791383220452e+01 7.446058956916100158e+01 7.487854875283446177e+01 7.528489795918366667e+01 7.571446712018141056e+01 7.612662131519275022e+01 7.652716553287982038e+01 7.691609977324263525e+01 7.732535147392290753e+01 7.773750566893424718e+01 7.815256235827664000e+01 7.856181405895691228e+01 7.895945578231292927e+01 7.938031746031745683e+01 7.979247165532879649e+01 8.019301587301586665e+01 8.060807256235827367e+01 8.101151927437641120e+01 8.142947845804988560e+01 8.181551020408163311e+01 8.215219954648526368e+01 8.258467120181406074e+01 8.295038548752835084e+01 8.341188208616780742e+01 8.382403628117913286e+01 8.421006802721088036e+01 8.459900226757369524e+01 8.505759637188208444e+01 8.547265306122449147e+01 8.588190476190476375e+01 8.627374149659864599e+01 8.667428571428571615e+01 8.708934240362812318e+01 8.749278911564626071e+01 8.792235827664399039e+01 8.830839002267573790e+01 8.871764172335601017e+01 8.912399092970521508e+01 8.951873015873016470e+01 8.990476190476189799e+01 9.025886621315193281e+01 9.070294784580498515e+01 9.110929705215419006e+01 9.150693877551020705e+01 9.186975056689342978e+01 9.224417233560090779e+01 9.267374149659863747e+01 9.311492063492063664e+01 9.350675736961451889e+01 9.390730158730158905e+01 9.426430839002267703e+01 9.465614512471655928e+01 9.504217687074829257e+01 9.541659863945578479e+01 9.578811791383219543e+01 9.621478458049887195e+01 9.662693877551019739e+01 9.701587301587301226e+01 9.740190476190475977e+01 9.782566893424036891e+01 9.822621315192743907e+01 9.863256235827664398e+01 9.902730158730159360e+01 9.953233560090703236e+01 9.994448979591837201e+01 1.002956916099773252e+02 1.006672108843537359e+02 1.010648526077097529e+02 1.014828117913832131e+02 1.018891609977324322e+02 1.023042176870748250e+02 1.027337868480725689e+02 1.031314285714285717e+02 1.035522902494331134e+02 1.039528344671201836e+02 1.043562811791383211e+02 1.047626303854875260e+02 1.051660770975056636e+02 1.055608163265306132e+02 1.059584580498866160e+02 1.063590022675737004e+02 1.067769614512471605e+02 1.071746031746031775e+02 1.075693424036281129e+02 1.079727891156462647e+02 1.083791383219954696e+02 1.087709750566893376e+02 1.091802267573696099e+02 1.095778684807256269e+02 1.099871201814058992e+02 1.103847619047619020e+02 1.107736961451247168e+02 1.111800453514739218e+02 1.116125170068027188e+02 1.119985487528344663e+02 1.124048979591836712e+02 1.128489795918367378e+02 1.132524263038548753e+02 1.136471655328798249e+02 1.140390022675736930e+02 1.144105215419501178e+02 1.148226757369614575e+02 1.152174149659863929e+02 1.156440816326530552e+02 1.160649433106575970e+02 1.164683900226757345e+02 1.168718367346938720e+02 1.172694784580498890e+02 1.176555102040816365e+02 1.180647619047619088e+02 1.184362811791383194e+02 1.188455328798185917e+02 1.192489795918367292e+02 1.196698412698412710e+02 1.200616780045351533e+02 1.204767346938775461e+02 1.208859863945578184e+02 1.213039455782312928e+02 1.217044897959183629e+02 1.220992290249433125e+02 1.225142857142857196e+02 1.229119274376417223e+02 1.233066666666666720e+02 1.237217233560090648e+02 1.241425850340136066e+02 1.245605442176870810e+02 1.249523809523809490e+02 1.253558276643990865e+02 1.257447619047619014e+02 1.261627210884353758e+02 1.265603628117913786e+02 1.269609070294784630e+02 1.273643537414966005e+02 1.277939229024943302e+02 1.282205895691610067e+02 1.286995011337868391e+02 1.290826303854875334e+02 1.295063945578231426e+02 1.298053514739229115e+02 1.302058956916099817e+02 1.305890249433106476e+02 1.310011791383219872e+02 1.314655782312925112e+02 1.318487074829932055e+02 1.322695691609977189e+02 1.326846258503401259e+02 1.330909750566893308e+02 1.335205442176870747e+02 1.339385034013605491e+02 1.343477551020408214e+02 1.347715192743764305e+02 1.351633560090702986e+02 1.355261678004535213e+02 1.359586394557823041e+02 1.363475736961451332e+02 1.367858503401360508e+02 1.371718820861678125e+02 1.375898412698412585e+02 1.380107029478458003e+02 1.384199546485260726e+02 1.388292063492063448e+02 1.392529705215419540e+02 1.396738321995464958e+02 1.400453514739228922e+02 1.404517006802720971e+02 1.408783673469387736e+02 1.413166439909296912e+02 1.417317006802720982e+02 1.421438548752834379e+02 1.425356916099773343e+02 1.429507482993197414e+02 1.433658049886621200e+02 1.437663492063492185e+02 1.441843083900226645e+02 1.446080725623582737e+02 1.450463492063492197e+02 1.454497959183673572e+02 1.458474376417233600e+02 1.462508843537414975e+02 1.466543310657596351e+02 1.470577777777777726e+02 1.474728344671201796e+02 1.478675736961451150e+02 1.482478004535147420e+02 1.486454421768707448e+02 1.490401814058956802e+02 1.494378231292517114e+02 1.498499773242630511e+02 1.502737414965986318e+02 1.506800907029478367e+02 1.510951473922902437e+02 1.515189115646258529e+02 1.519194557823129230e+02 1.523490249433106669e+02 1.527640816326530739e+02 1.531733333333333462e+02 1.535564625850340121e+02 1.539744217687074865e+02 1.543865759637188262e+02 1.548161451247165417e+02 1.552021768707483034e+02 1.556172335600907104e+02 1.560322902494331174e+02 1.564241269841269855e+02 1.568333786848072577e+02 1.572571428571428669e+02 1.577650793650793730e+02 1.582294784580498970e+02 1.586416326530612366e+02 1.590160544217687004e+02 1.593846712018140579e+02 1.597794104308389933e+02 1.602060770975056698e+02 1.606443537414965874e+02 1.610652154195011292e+02 1.614918820861678057e+02 1.618750113378684716e+02 1.622842630385487439e+02 1.627080272108843531e+02 1.631404988662131643e+02 1.635207256235827629e+02 1.639357823129251699e+02 1.643508390022675769e+02 1.647513832199546471e+02 1.651838548752834583e+02 1.656018140589569043e+02 1.660110657596371766e+02 1.664261224489795836e+02 1.668382766439909233e+02 1.672591383219954650e+02 1.676945124716553153e+02 1.681066666666666549e+02 1.685333333333333314e+02 1.689483900226757385e+02 1.693721541950113476e+02 1.697726984126984178e+02 1.703183673469387713e+02 1.707479365079365152e+02 1.711862131519274328e+02 1.716215873015873115e+02 1.720424489795918248e+02 1.724865306122449056e+02 1.729190022675736884e+02 1.733311564625850281e+02 1.737229931972789245e+02 1.740654875283446756e+02 1.744834467120181500e+02 1.748985034013605571e+02 1.753222675736961378e+02 1.757315192743764101e+02 1.761552834467120192e+02 1.765732426303854936e+02 1.770115192743764112e+02 1.774207709750566835e+02 1.778126077097505799e+02 1.782682993197279018e+02 1.786804535147392414e+02 1.790897052154195137e+02 1.795337868480725660e+02 1.799314285714285688e+02 1.803232653061224369e+02 1.807760544217687197e+02 1.812056235827664352e+02 1.816932426303854982e+02 1.821257142857142810e+02 1.825639909297052270e+02 1.829703401360544319e+02 1.833302494331065873e+02 1.836698412698412710e+02 1.840994104308390149e+02 1.845144671201813935e+02 1.849004988662131552e+02 1.853184580498866296e+02 1.857422222222222103e+02 1.861369614512471742e+02 1.865491156462585138e+02 1.869670748299319598e+02 1.873879365079365016e+02 1.878058956916099760e+02 1.882064399092970461e+02 1.886360090702947900e+02 1.890858956916099771e+02 1.895154648526077210e+02 1.898956916099773196e+02 1.902991383219954571e+02 1.907229024943310662e+02 1.911437641723356080e+02 1.915530158730158803e+02 1.921015873015873012e+02 1.925630839002267578e+02 1.930100680272108775e+02 1.934512471655328909e+02 1.938982312925170106e+02 1.942436281179138291e+02 1.945832199546485128e+02 1.949228117913832250e+02 1.952536961451247066e+02 1.956919727891156526e+02 1.961215419501133681e+02 1.965191836734693993e+02 1.969052154195011326e+02 1.973028571428571354e+02 1.977092063492063403e+02 1.981068480725623715e+02 1.985073922902494417e+02 1.989079365079365118e+02 mir_eval-0.8.2/tests/data/beat/est03.txt000066400000000000000000000250271475740344600200300ustar00rootroot000000000000006.443537414965986310e-01 1.131972789115646361e+00 1.622494331065759576e+00 2.130430839002267707e+00 2.679002267573696194e+00 3.210158730158730211e+00 3.720997732426303717e+00 4.237641723356008860e+00 4.789115646258503389e+00 5.334784580498865836e+00 5.863038548752834700e+00 6.400000000000000355e+00 6.820861678004535023e+00 7.238820861678004093e+00 7.810612244897959577e+00 8.379501133786847689e+00 8.913560090702947747e+00 9.462131519274375790e+00 9.990385487528344655e+00 1.052154195011337912e+01 1.105850340136054477e+01 1.165351473922902414e+01 1.217886621315192741e+01 1.275646258503401320e+01 1.334857142857142875e+01 1.390875283446712096e+01 1.442249433106576006e+01 1.500009070294784586e+01 1.558349206349206284e+01 1.610594104308389873e+01 1.663419501133786937e+01 1.717986394557823004e+01 1.777777777777777857e+01 1.832054421768707542e+01 1.882848072562358155e+01 1.928707482993197431e+01 1.976018140589569327e+01 2.030875283446712132e+01 2.085151927437641817e+01 2.136235827664399167e+01 2.189351473922902613e+01 2.236081632653061391e+01 2.289487528344671219e+01 2.342022675736961546e+01 2.394848072562358254e+01 2.451736961451247154e+01 2.506303854875283577e+01 2.557968253968254047e+01 2.612244897959183731e+01 2.665941043083900297e+01 2.706866213151927525e+01 2.747210884353741633e+01 2.804099773242630533e+01 2.855183673469387884e+01 2.906267573696145234e+01 2.962285714285714278e+01 3.020335600907029416e+01 3.067936507936508050e+01 3.119310657596371783e+01 3.172426303854875229e+01 3.224090702947845699e+01 3.277496598639455527e+01 3.328000000000000114e+01 3.380244897959183703e+01 3.437133786848072248e+01 3.487637188208616834e+01 3.542494331065759638e+01 3.594739229024943228e+01 3.647854875283447029e+01 3.701551020408163595e+01 3.754086167800453211e+01 3.808072562358276514e+01 3.860897959183673578e+01 3.913433106575963905e+01 3.963936507936507780e+01 4.013569160997732155e+01 4.062040816326530290e+01 4.118929705215419546e+01 4.174077097505669087e+01 4.226321995464852677e+01 4.278857142857143003e+01 4.334294784580498572e+01 4.390022675736961588e+01 4.445750566893423894e+01 4.497414965986394719e+01 4.545886621315192855e+01 4.601034013605442397e+01 4.652408163265305774e+01 4.710167800453514531e+01 4.759510204081632878e+01 4.807401360544217539e+01 4.854712018140589436e+01 4.900861678004535094e+01 4.950494331065759468e+01 5.001868480725623556e+01 5.050920634920635166e+01 5.111582766439909165e+01 5.166730158730158706e+01 5.216072562358276343e+01 5.255836734693877332e+01 5.295310657596371584e+01 5.355682539682539556e+01 5.406476190476190169e+01 5.458721088435374469e+01 5.512417233560091034e+01 5.563791383219954412e+01 5.615165532879818500e+01 5.664798185941042874e+01 5.719945578231292416e+01 5.771029478458049766e+01 5.826467120181406045e+01 5.882775510204081826e+01 5.937052154195011155e+01 5.992780045351474172e+01 6.048798185941043215e+01 6.102494331065759781e+01 6.152707482993197630e+01 6.206693877551020222e+01 6.261260770975057000e+01 6.311764172335600875e+01 6.369233560090702895e+01 6.423219954648526198e+01 6.474013605442176811e+01 6.524807256235827424e+01 6.578793650793650727e+01 6.629006802721087865e+01 6.678349206349206213e+01 6.726530612244897611e+01 6.772099773242629794e+01 6.824344671201814094e+01 6.873687074829932442e+01 6.922448979591837315e+01 6.973823129251699982e+01 7.021714285714286063e+01 7.068734693877550512e+01 7.125043083900226293e+01 7.178739229024942858e+01 7.228952380952381418e+01 7.275682539682539129e+01 7.333732426303855334e+01 7.391492063492063380e+01 7.440544217687074990e+01 7.493369614512471344e+01 7.551999999999999602e+01 7.604535147392290639e+01 7.657650793650793730e+01 7.712217687074830508e+01 7.764462585034013387e+01 7.817868480725623215e+01 7.871564625850339780e+01 7.921777777777778340e+01 7.978666666666666174e+01 8.031782312925170686e+01 8.089251700680271995e+01 8.144689342403627563e+01 8.194902494331066123e+01 8.250049886621314954e+01 8.303455782312924782e+01 8.355120181405895607e+01 8.409687074829932385e+01 8.462512471655328739e+01 8.513886621315192826e+01 8.568743764172334920e+01 8.619537414965986954e+01 8.670911564625851042e+01 8.732444444444443832e+01 8.787591836734694084e+01 8.831709750566894002e+01 8.885986394557822621e+01 8.936780045351473234e+01 8.989024943310657534e+01 9.048235827664399267e+01 9.104834467120181785e+01 9.150113378684807230e+01 9.185814058956916028e+01 9.237768707482993591e+01 9.292916099773242422e+01 9.342258503401360770e+01 9.390149659863945431e+01 9.437750566893423354e+01 9.487383219954648439e+01 9.539918367346939476e+01 9.582875283446712444e+01 9.638603174603174750e+01 9.695201814058957268e+01 9.749768707482992625e+01 9.805786848072561668e+01 9.861514739229025395e+01 9.913179138321994799e+01 9.965714285714285836e+01 1.001970068027210914e+02 1.007775056689342392e+02 1.013231746031746070e+02 1.018456235827664358e+02 1.023680725623582788e+02 1.028702040816326502e+02 1.033781405895691563e+02 1.038802721088435419e+02 1.043940136054421828e+02 1.049396825396825363e+02 1.053576417233560107e+02 1.057785034013605383e+02 1.062138775510204027e+02 1.066753741496598593e+02 1.072094331065759576e+02 1.077376870748299353e+02 1.082717460317460336e+02 1.087999999999999972e+02 1.092789115646258438e+02 1.097723356009070272e+02 1.102657596371882107e+02 1.107417687074829900e+02 1.113280725623582725e+02 1.118214965986394560e+02 1.123120181405895721e+02 1.128344671201814009e+02 1.133249886621315170e+02 1.138300226757369558e+02 1.143147392290249371e+02 1.148487981859410496e+02 1.154931519274376370e+02 1.159836734693877531e+02 1.165438548752834436e+02 1.171011337868480666e+02 1.177629024943310725e+02 1.182534240362811744e+02 1.187236281179138331e+02 1.191560997732426301e+02 1.195885714285714272e+02 1.200123356009070363e+02 1.205028571428571382e+02 1.210049886621315238e+02 1.214868027210884378e+02 1.219366893424036249e+02 1.225287981859410422e+02 1.230889795918367327e+02 1.235417687074829871e+02 1.241222675736961492e+02 1.246243990929705205e+02 1.251294331065759593e+02 1.256518820861678023e+02 1.261743310657596311e+02 1.267316099773242684e+02 1.273237188208616715e+02 1.278258503401360571e+02 1.283192743764172405e+02 1.287111111111111086e+02 1.291203628117913809e+02 1.296253968253968196e+02 1.300926984126984109e+02 1.305890249433106476e+02 1.311056689342403558e+02 1.316455328798186031e+02 1.321679818594104177e+02 1.325772335600906899e+02 1.331664399092970541e+02 1.337585487528344572e+02 1.342606802721088570e+02 1.347686167800453632e+02 1.353113832199546493e+02 1.358048072562358186e+02 1.363824036281179133e+02 1.368526077097505720e+02 1.373431292517006739e+02 1.378394557823129389e+02 1.383502947845805124e+02 1.388582312925170186e+02 1.392645804988662235e+02 1.397667120181405949e+02 1.403036734693877463e+02 1.408377324263038588e+02 1.414124263038548861e+02 1.419290702947845944e+02 1.424050793650793594e+02 1.428985034013605571e+02 1.434499773242630454e+02 1.440130612244898032e+02 1.445616326530612241e+02 1.451073015873015777e+02 1.456065306122449101e+02 1.461144671201814162e+02 1.466369160997732308e+02 1.471854875283446802e+02 1.477485714285714380e+02 1.483348752834467064e+02 1.487905668934240282e+02 1.493507482993197186e+02 1.498325623582766468e+02 1.503346938775510182e+02 1.508977777777777760e+02 1.514057142857142821e+02 1.519223582766439904e+02 1.525521995464852694e+02 1.530253061224489670e+02 1.534809977324263173e+02 1.538728344671201853e+02 1.543662585034013546e+02 1.548799999999999955e+02 1.554924263038548702e+02 1.560555102040816280e+02 1.566156916099773184e+02 1.571062131519274487e+02 1.576344671201813981e+02 1.581598185941043084e+02 1.586503401360544103e+02 1.591931065759637249e+02 1.597097505668934332e+02 1.604702040816326587e+02 1.608910657596372005e+02 1.614599546485260646e+02 1.620114285714285813e+02 1.624874376417233464e+02 1.630127891156462567e+02 1.635787755102040819e+02 1.640692970521541838e+02 1.645801360544217573e+02 1.650967800453514656e+02 1.656105215419501064e+02 1.661358730158730168e+02 1.666583219954648598e+02 1.671720634920635007e+02 1.678193197278911555e+02 1.683591836734693743e+02 1.689396825396825363e+02 1.694766439909297162e+02 1.700165079365079350e+02 1.705592743764172212e+02 1.710004535147392346e+02 1.715374149659863861e+02 1.720279365079365164e+02 1.725590929705215331e+02 1.730960544217687129e+02 1.736417233560090665e+02 1.741090249433106578e+02 1.746750113378684830e+02 1.752264852607709713e+02 1.757663492063492185e+02 1.762946031746031679e+02 1.768228571428571456e+02 1.773482086167800560e+02 1.778677551020408032e+02 1.784221315192743873e+02 1.790926077097505811e+02 1.795773242630385482e+02 1.800736507936507849e+02 1.805728798185941173e+02 1.810721088435374213e+02 1.815742403628117927e+02 1.821141043083900115e+02 1.826713832199546346e+02 1.831677097505668996e+02 1.836611337868480689e+02 1.842329251700680288e+02 1.847582766439909392e+02 1.852720181405895801e+02 1.858031746031745968e+02 1.862559637188208512e+02 1.867464852607709815e+02 1.873211791383220088e+02 1.879307029478458162e+02 1.884589569160997655e+02 1.889610884353741369e+02 1.893413151927437639e+02 1.897824943310657488e+02 1.903600907029478435e+02 1.908186848072562327e+02 1.912714739229024872e+02 1.917213605442176743e+02 1.923047619047619037e+02 1.928765532879818636e+02 1.934773696145124688e+02 1.939940136054421771e+02 1.944729251700680379e+02 1.948908843537414839e+02 1.953146485260770930e+02 1.958138775510203970e+02 1.963392290249433074e+02 1.968529705215419483e+02 1.974421768707483125e+02 1.980139682539682440e+02 1.986031746031746081e+02 1.991662585034013659e+02 1.997148299319727869e+02 2.002227664399092930e+02 2.007190929705215297e+02 2.011022222222222240e+02 2.015114739229024963e+02 2.020455328798185803e+02 2.025592743764172212e+02 2.030788208616779968e+02 2.035635374149659924e+02 2.040946938775510091e+02 2.046229478458049869e+02 2.051366893424036277e+02 2.056272108843537296e+02 2.062425396825396717e+02 2.067127437641723304e+02 2.074499773242630454e+02 2.080275736961451116e+02 2.085964625850340042e+02 2.091769614512471662e+02 2.097545578231292609e+02 2.102131519274376501e+02 2.108023582766439858e+02 2.113044897959183572e+02 2.118211337868480655e+02 2.122652154195011462e+02 2.126976870748299291e+02 2.131272562358276730e+02 2.135829478458049948e+02 2.140183219954648450e+02 2.144769160997732342e+02 2.149239002267573824e+02 2.154840816326530728e+02 2.160500680272108980e+02 2.165696145124716452e+02 2.171356009070294704e+02 2.177393197278911430e+02 2.183227210884353724e+02 2.187900226757369637e+02 2.192921541950113351e+02 2.198058956916099760e+02 2.203138321995464821e+02 2.208595011337868357e+02 2.214051700680272177e+02 2.219305215419500996e+02 2.224645804988662121e+02 2.229725170068027182e+02 2.234688435374149549e+02 2.239506575963718831e+02 2.244498866213151871e+02 mir_eval-0.8.2/tests/data/beat/est04.txt000066400000000000000000000346671475740344600200430ustar00rootroot000000000000006.907936507936508486e-01 1.111655328798185849e+00 1.523809523809523725e+00 1.924353741496598547e+00 2.321995464852607771e+00 2.760272108843537353e+00 3.192743764172335741e+00 3.619410430839002046e+00 3.993832199546485384e+00 4.414693877551020051e+00 4.826848072562357927e+00 5.250612244897959080e+00 5.665668934240362553e+00 6.086530612244898109e+00 6.545124716553288202e+00 6.960181405895691675e+00 7.421678004535147366e+00 7.868662131519274183e+00 8.309841269841269806e+00 8.724897959183673279e+00 9.119637188208617573e+00 9.557913832199545823e+00 1.001941043083900240e+01 1.044317460317460267e+01 1.089886621315192805e+01 1.145614512471655289e+01 1.188861678004535172e+01 1.233269841269841294e+01 1.272743764172335545e+01 1.306702947845804985e+01 1.346757369614512534e+01 1.389714285714285680e+01 1.435573696145124778e+01 1.475918367346938709e+01 1.520616780045351391e+01 1.565315192743764250e+01 1.603628117913832085e+01 1.646294784580499027e+01 1.682866213151927326e+01 1.730467120181405960e+01 1.778938775510204096e+01 1.821605442176870682e+01 1.865433106575963862e+01 1.908390022675736830e+01 1.953668934240362987e+01 1.997786848072562194e+01 2.039873015873016016e+01 2.083990929705215578e+01 2.127818594104308403e+01 2.172807256235827822e+01 2.218956916099773125e+01 2.261913832199546448e+01 2.304870748299319771e+01 2.351020408163265429e+01 2.391074829931972801e+01 2.434612244897959243e+01 2.483374149659864116e+01 2.526911564625850204e+01 2.569287981859410408e+01 2.614566893424036209e+01 2.658104308390022652e+01 2.702802721088435334e+01 2.745179138321995538e+01 2.786104308390022766e+01 2.833414965986394662e+01 2.875501133786848129e+01 2.921070294784580668e+01 2.966058956916099731e+01 3.010757369614512413e+01 3.053424036281178999e+01 3.098412698412698418e+01 3.144562358276644076e+01 3.192163265306122355e+01 3.237151927437641774e+01 3.282430839002267220e+01 3.328000000000000114e+01 3.372408163265306058e+01 3.426684807256236098e+01 3.460353741496598445e+01 3.507664399092970342e+01 3.553814058956916000e+01 3.602285714285714135e+01 3.647274376417233555e+01 3.690521541950113260e+01 3.734639455782313178e+01 3.777886621315192883e+01 3.835936507936507667e+01 3.884408163265305802e+01 3.929106575963718484e+01 3.974095238095237903e+01 4.019374149659864059e+01 4.062331065759637028e+01 4.101514739229025253e+01 4.144471655328798221e+01 4.189460317460317640e+01 4.235029478458049823e+01 4.284952380952380935e+01 4.342712018140589691e+01 4.387700680272109111e+01 4.433560090702948031e+01 4.465197278911564638e+01 4.508444444444444343e+01 4.553142857142857025e+01 4.597841269841269707e+01 4.646312925170067842e+01 4.694784580498865978e+01 4.741804988662131848e+01 4.780988662131519362e+01 4.830040816326530262e+01 4.874448979591836917e+01 4.919147392290249599e+01 4.966167800453514758e+01 5.009705215419501201e+01 5.054693877551020620e+01 5.109551020408163424e+01 5.152798185941043130e+01 5.194013605442177095e+01 5.235229024943310350e+01 5.282539682539682246e+01 5.324916099773242451e+01 5.371646258503401583e+01 5.417505668934240504e+01 5.473233560090702809e+01 5.519383219954648467e+01 5.563210884353741648e+01 5.607328798185940855e+01 5.641868480725623414e+01 5.687147392290249570e+01 5.731265306122448777e+01 5.776834467120181671e+01 5.822984126984127329e+01 5.867102040816326536e+01 5.913541950113378931e+01 5.966077097505669258e+01 6.011356009070294704e+01 6.056344671201814123e+01 6.095818594104308374e+01 6.136743764172335602e+01 6.179700680272108571e+01 6.226430839002267703e+01 6.273160997732426125e+01 6.319891156462585258e+01 6.363138321995464963e+01 6.407836734693877645e+01 6.455147392290248831e+01 6.502167800453514701e+01 6.545124716553287669e+01 6.591564625850340065e+01 6.636843537414965510e+01 6.680090702947845216e+01 6.724498866213151871e+01 6.761360544217687618e+01 6.805768707482992852e+01 6.852208616780045247e+01 6.897487528344670693e+01 6.943346938775509614e+01 6.988045351473923006e+01 7.033034013605441714e+01 7.080054421768707584e+01 7.125623582766439768e+01 7.170321995464853160e+01 7.214439909297051656e+01 7.258267573696144837e+01 7.304997732426303969e+01 7.347664399092970200e+01 7.391492063492063380e+01 7.433868480725622874e+01 7.479147392290249741e+01 7.523555555555554974e+01 7.567092970521541417e+01 7.614113378684807287e+01 7.659102040816325996e+01 7.695963718820861743e+01 7.735147392290249968e+01 7.779845804988661939e+01 7.823963718820861857e+01 7.868081632653061774e+01 7.916553287981859910e+01 7.962412698412698830e+01 8.012045351473922494e+01 8.056743764172335887e+01 8.100861678004535804e+01 8.144108843537415510e+01 8.189387755102040956e+01 8.232344671201813924e+01 8.275882086167800367e+01 8.321741496598639287e+01 8.367600907029478208e+01 8.410848072562357913e+01 8.456707482993196834e+01 8.501115646258503489e+01 8.542331065759637454e+01 8.582095238095237733e+01 8.619247165532880217e+01 8.659882086167800708e+01 8.704870748299319416e+01 8.753632653061224289e+01 8.795428571428571729e+01 8.842739229024942915e+01 8.886857142857142833e+01 8.929523809523809064e+01 8.972480725623583453e+01 9.017179138321995424e+01 9.059555555555554918e+01 9.104253968253968310e+01 9.147791383219954753e+01 9.191619047619047933e+01 9.233414965986393952e+01 9.281886621315192087e+01 9.322231292517007262e+01 9.367800453514739445e+01 9.414240362811791840e+01 9.457777777777778283e+01 9.502766439909296992e+01 9.548335600907029175e+01 9.606385487528345379e+01 9.651374149659864088e+01 9.694621315192743793e+01 9.738739229024943711e+01 9.783727891156462420e+01 9.827265306122448862e+01 9.872544217687074308e+01 9.916371882086167489e+01 9.959619047619047194e+01 1.000460770975056732e+02 1.004611337868480661e+02 1.009023129251700652e+02 1.013376870748299297e+02 1.017933786848072515e+02 1.022113378684807259e+02 1.026699319727891151e+02 1.031111111111111143e+02 1.035406802721088440e+02 1.038860770975056624e+02 1.043185487528344737e+02 1.047771428571428629e+02 1.051863945578231352e+02 1.056536961451247123e+02 1.060803628117913888e+02 1.065070294784580511e+02 1.069453061224489829e+02 1.074039002267573721e+02 1.078624943310657613e+02 1.083036734693877605e+02 1.087216326530612207e+02 1.091424943310657625e+02 1.095981859410430843e+02 1.100567800453514735e+02 1.104921541950113379e+02 1.109246258503401350e+02 1.113745124716553221e+02 1.118331065759637255e+02 1.122684807256235757e+02 1.127212698412698444e+02 1.131392290249433046e+02 1.136007256235827612e+02 1.140448072562358277e+02 1.144598639455782347e+02 1.149358730158730140e+02 1.153538321995464884e+02 1.158066213151927428e+02 1.162478004535147420e+02 1.167034920634920638e+02 1.171417687074829956e+02 1.175974603174603175e+02 1.180183219954648592e+02 1.185030385487528406e+02 1.189355102040816377e+02 1.193737868480725695e+02 1.198149659863945544e+02 1.202300226757369614e+02 1.206799092970521485e+02 1.211152834467120130e+02 1.215535600907029448e+02 1.220092517006802666e+02 1.224359183673469431e+02 1.228625850340136054e+02 1.233211791383219946e+02 1.237855782312925186e+02 1.241832199546485214e+02 1.246098866213151979e+02 1.250771882086167750e+02 1.255299773242630437e+02 1.259885714285714329e+02 1.264181405895691626e+02 1.268593197278911617e+02 1.272830839002267567e+02 1.277300680272108906e+02 1.282089795918367372e+02 1.287024036281179065e+02 1.290768253968253987e+02 1.294831746031746036e+02 1.299069387755102127e+02 1.303626303854875346e+02 1.308444444444444343e+02 1.312711111111111109e+02 1.317239002267573653e+02 1.322028117913832261e+02 1.326672108843537501e+02 1.331229024943310719e+02 1.335553741496598548e+02 1.340023582766440029e+02 1.344435374149659879e+02 1.348789115646258381e+02 1.353113832199546493e+02 1.357641723356009038e+02 1.362227664399092930e+02 1.366668480725623454e+02 1.371167346938775609e+02 1.375811337868480848e+02 1.380223129251700698e+02 1.384692970521541895e+02 1.388756462585033944e+02 1.393342403628117836e+02 1.397492970521541906e+02 1.402195011337868493e+02 1.406897052154195080e+02 1.411279818594104256e+02 1.415691609977324390e+02 1.420335600907029345e+02 1.424486167800453416e+02 1.428752834467120181e+02 1.433309750566893399e+02 1.437837641723355944e+02 1.441901133786847993e+02 1.446690249433106601e+02 1.451276190476190493e+02 1.455717006802721016e+02 1.460099773242630476e+02 1.464540589569161000e+02 1.468923356009070176e+02 1.473451247165533005e+02 1.478182312925169981e+02 1.482942403628117916e+02 1.487238095238095354e+02 1.491475736961451162e+02 1.496003628117913706e+02 1.500386394557823166e+02 1.505146485260771101e+02 1.509442176870748256e+02 1.513941043083900126e+02 1.518614058956916040e+02 1.522996825396825500e+02 1.527437641723356023e+02 1.531762358276643852e+02 1.536232199546485333e+02 1.540556916099773161e+02 1.544823582766439927e+02 1.549206349206349103e+02 1.553676190476190584e+02 1.558175056689342455e+02 1.562557823129251631e+02 1.566824489795918396e+02 1.571555555555555657e+02 1.575909297052154159e+02 1.580379138321995356e+02 1.584790929705215490e+02 1.589173696145124666e+02 1.594049886621315295e+02 1.599332426303854788e+02 1.603860317460317333e+02 1.608301133786848141e+02 1.611842176870748347e+02 1.616079818594104438e+02 1.620462585034013614e+02 1.624816326530612116e+02 1.629082993197278881e+02 1.633726984126984121e+02 1.637993650793650886e+02 1.642492517006802757e+02 1.647020408163265301e+02 1.651519274376417172e+02 1.655873015873015959e+02 1.660284807256235808e+02 1.664551473922902574e+02 1.668789115646258381e+02 1.673491156462584968e+02 1.678367346938775597e+02 1.682750113378684773e+02 1.687074829931972886e+02 1.691254421768707346e+02 1.695869387755101911e+02 1.700368253968254066e+02 1.704286621315192747e+02 1.708872562358276639e+02 1.713081179138322057e+02 1.717667120181405949e+02 1.722253061224489841e+02 1.726577777777777669e+02 1.731076643990929824e+02 1.735546485260771021e+02 1.739697052154195092e+02 1.743876643990929836e+02 1.748317460317460359e+02 1.752613151927437514e+02 1.757431292517006796e+02 1.761814058956915972e+02 1.766167800453514758e+02 1.770608616780045281e+02 1.775049433106576089e+02 1.779432199546485265e+02 1.783902040816326462e+02 1.788487981859410354e+02 1.792638548752834424e+02 1.797253514739228990e+02 1.801781405895691535e+02 1.806251247165533016e+02 1.810663038548752866e+02 1.814900680272108957e+02 1.819283446712018133e+02 1.823521088435374224e+02 1.827874829931972727e+02 1.832489795918367292e+02 1.837191836734693879e+02 1.841603628117913729e+02 1.845928344671201842e+02 1.850485260770975060e+02 1.855158276643990973e+02 1.859570068027210823e+02 1.864097959183673368e+02 1.868277551020408112e+02 1.873095691609977393e+02 1.877362358276643874e+02 1.881803174603174682e+02 1.886156916099773184e+02 1.890539682539682644e+02 1.895357823129251642e+02 1.899827664399092839e+02 1.903949206349206236e+02 1.907983673469387895e+02 1.912772789115646219e+02 1.917155555555555679e+02 1.921770521541950245e+02 1.926269387755102116e+02 1.931406802721088525e+02 1.935876643990929722e+02 1.940317460317460245e+02 1.944555102040816337e+02 1.948908843537414839e+02 1.953233560090702952e+02 1.957790476190476170e+02 1.962376417233560062e+02 1.967107482993197323e+02 1.971548299319727846e+02 1.976047165532879717e+02 1.980604081632652935e+02 1.985044897959183743e+02 1.989543764172335614e+02 1.993955555555555463e+02 1.998367346938775597e+02 2.002750113378684773e+02 2.007045804988662212e+02 2.011544671201814083e+02 2.016130612244897975e+02 2.020629478458049846e+02 2.025012244897959306e+02 2.029307936507936461e+02 2.033719727891156595e+02 2.038102494331065770e+02 2.042514285714285620e+02 2.046809977324263059e+02 2.050873469387755108e+02 2.055343310657596305e+02 2.059697052154195092e+02 2.063963718820861573e+02 2.068317460317460359e+02 2.071916553287981912e+02 2.076009070294784635e+02 2.080188662131519379e+02 2.084687528344671250e+02 2.088925170068027342e+02 2.092872562358276696e+02 2.097400453514739240e+02 2.101928344671201785e+02 2.106427210884353656e+02 2.110751927437641768e+02 2.115047619047618923e+02 2.119459410430839057e+02 2.123784126984126885e+02 2.128021768707482977e+02 2.132172335600907047e+02 2.136351927437641791e+02 2.140821768707482988e+02 2.145291609977324185e+02 2.149964625850340099e+02 2.154347392290249559e+02 2.159049433106575862e+02 2.163025850340136174e+02 2.167553741496598718e+02 2.171907482993197220e+02 2.176319274376417354e+02 2.180498866213151814e+02 2.184968707482993295e+02 2.189148299319727755e+02 2.193443990929705194e+02 2.197681632653061286e+02 2.201803174603174682e+02 2.206243990929705205e+02 2.210539682539682644e+02 2.215067573696145189e+02 2.219479365079365039e+02 2.224036281179138257e+02 2.228273922902494348e+02 2.232772789115646219e+02 2.237155555555555679e+02 2.241683446712018224e+02 2.246066213151927400e+02 2.250855328798186008e+02 2.255325170068027205e+02 2.259707936507936381e+02 2.263945578231292473e+02 2.268183219954648564e+02 2.272827210884353804e+02 2.276832653061224505e+02 2.281302494331065702e+02 2.286120634920634984e+02 2.290503401360544160e+02 2.294828117913832273e+02 2.299152834467120101e+02 2.303825850340136014e+02 2.308179591836734801e+02 2.312272108843537524e+02 2.315842176870748403e+02 2.321356916099773287e+02 2.326755555555555475e+02 2.331631746031746104e+02 2.336014512471655280e+02 2.340571428571428498e+02 2.344954195011337958e+02 2.349453061224489829e+02 2.354097052154195069e+02 2.358537868480725592e+02 2.362920634920635052e+02 2.366084353741496500e+02 2.370409070294784613e+02 2.374762811791383115e+02 2.379348752834467007e+02 2.383905668934240225e+02 2.388607709750566812e+02 2.392932426303854925e+02 2.397634467120181512e+02 2.401959183673469340e+02 2.406341950113378800e+02 2.410492517006802586e+02 2.415281632653061195e+02 2.419925623582766434e+02 2.424308390022675610e+02 2.428836281179138439e+02 2.433248072562358288e+02 2.437398639455782359e+02 2.442129705215419619e+02 2.446396371882086100e+02 2.451098412698412687e+02 2.455568253968253885e+02 2.460009070294784692e+02 2.464536961451247237e+02 2.468803628117913718e+02 2.473418594104308283e+02 2.477975510204081502e+02 2.482474376417233657e+02 2.486886167800453507e+02 2.491414058956916051e+02 2.495941950113378596e+02 2.500266666666666708e+02 2.504620408163265211e+02 2.508974149659863997e+02 2.513502040816326542e+02 2.518204081632653129e+02 2.522470748299319609e+02 2.527114739229024849e+02 2.531265306122448919e+02 2.535764172335600790e+02 2.540175963718820924e+02 2.544529705215419426e+02 2.549289795918367361e+02 2.553701587301587210e+02 2.557997278911564649e+02 2.562002721088435351e+02 2.567227210884353781e+02 2.571464852607709872e+02 2.574802721088435646e+02 2.579040362811791169e+02 2.583161904761904566e+02 2.587312471655328636e+02 2.591782312925170118e+02 2.596513378684807094e+02 2.601186394557823292e+02 2.605424036281179383e+02 2.609458503401360758e+02 2.613725170068026955e+02 2.618049886621315068e+02 mir_eval-0.8.2/tests/data/beat/est05.txt000066400000000000000000000162041475740344600200270ustar00rootroot000000000000002.052063492063492145e+00 2.586122448979591759e+00 3.123083900226757414e+00 3.703582766439909246e+00 4.272471655328797802e+00 4.803628117913832263e+00 5.381224489795918053e+00 5.909478458049886918e+00 6.458049886621314961e+00 6.974693877551020549e+00 7.534875283446711869e+00 8.063129251700679845e+00 8.597188208616779903e+00 9.157369614512472111e+00 9.682721088435373602e+00 1.019936507936508008e+01 1.073922902494331133e+01 1.126748299319727842e+01 1.180154195011337848e+01 1.234140589569160973e+01 1.291029478458049873e+01 1.344725623582766438e+01 1.398131519274376444e+01 1.451827664399093010e+01 1.505814058956916135e+01 1.562122448979591915e+01 1.614947845804988802e+01 1.669514739229024869e+01 1.724662131519274411e+01 1.779809523809523952e+01 1.834956916099773139e+01 1.890104308390022680e+01 1.946122448979591724e+01 2.000108843537415027e+01 2.051773242630385496e+01 2.108952380952380778e+01 2.163809523809523938e+01 2.219537414965986244e+01 2.273814058956915929e+01 2.328671201814059089e+01 2.383238095238095156e+01 2.437804988662131578e+01 2.491501133786848143e+01 2.546938775510204067e+01 2.602666666666666728e+01 2.656943310657596413e+01 2.710639455782312979e+01 2.764335600907029544e+01 2.818902494331065611e+01 2.875501133786848129e+01 2.930938775510204053e+01 2.986376417233559977e+01 3.041814058956916256e+01 3.096671201814059060e+01 3.151818594104308247e+01 3.206965986394558144e+01 3.261823129251700948e+01 3.317260770975056516e+01 3.371247165532879819e+01 3.424943310657596385e+01 3.480090702947845926e+01 3.534657596371881993e+01 3.588643990929705296e+01 3.638566893424036408e+01 3.691682539682539499e+01 3.744798185941043300e+01 3.797333333333333627e+01 3.848707482993197004e+01 3.909369614512471713e+01 3.960163265306122327e+01 4.019083900226757322e+01 4.074811791383219628e+01 4.129959183673469170e+01 4.184526077097505947e+01 4.240253968253968253e+01 4.294240362811791556e+01 4.349678004535147124e+01 4.403374149659863690e+01 4.456199546485260754e+01 4.514539682539682275e+01 4.565043083900226861e+01 4.614675736961451236e+01 4.670113378684807515e+01 4.725841269841269821e+01 4.778956916099772911e+01 4.833523809523809689e+01 4.888961451247165257e+01 4.942947845804988560e+01 4.996934240362811863e+01 5.053532879818594381e+01 5.106648526077097472e+01 5.161505668934240276e+01 5.214040816326530603e+01 5.268607709750566670e+01 5.321433106575963734e+01 5.374839002267573562e+01 5.429405895691609629e+01 5.484843537414965908e+01 5.535056689342403757e+01 5.597460317460317469e+01 5.650285714285714533e+01 5.700789115646258409e+01 5.758839002267573903e+01 5.816308390022675923e+01 5.870004535147392488e+01 5.926893424036281033e+01 5.977977324263038383e+01 6.032544217687075161e+01 6.089142857142856968e+01 6.142839002267573534e+01 6.195954648526077335e+01 6.252843537414965880e+01 6.304507936507936705e+01 6.354430839002267817e+01 6.408126984126984382e+01 6.462113378684807685e+01 6.514068027210883827e+01 6.569795918367347554e+01 6.625814058956916597e+01 6.679510204081633162e+01 6.735528344671202206e+01 6.790675736961451037e+01 6.845532879818594552e+01 6.899229024943311117e+01 6.953505668934239736e+01 7.007492063492063039e+01 7.059156462585033864e+01 7.114013605442177379e+01 7.167129251700680470e+01 7.219374149659863349e+01 7.272199546485261124e+01 7.322993197278911737e+01 7.376399092970521565e+01 7.427773242630385653e+01 7.486984126984127386e+01 7.538648526077098211e+01 7.594956916099772570e+01 7.647201814058956870e+01 7.704380952380952863e+01 7.757206349206349216e+01 7.819609977324263639e+01 7.867501133786848300e+01 7.927002267573696770e+01 7.979827664399093123e+01 8.034104308390023164e+01 8.090122448979592207e+01 8.144108843537415510e+01 8.198095238095237391e+01 8.252081632653060694e+01 8.308680272108843212e+01 8.361505668934240987e+01 8.416072562358276343e+01 8.468607709750567381e+01 8.525786848072561952e+01 8.581514739229024258e+01 8.634920634920635507e+01 8.688616780045352073e+01 8.745795918367346644e+01 8.802104308390022425e+01 8.856090702947845728e+01 8.912979591836734983e+01 8.967256235827665023e+01 9.021532879818593642e+01 9.076390022675737157e+01 9.131247165532879251e+01 9.186104308390022766e+01 9.240961451247164860e+01 9.296689342403628586e+01 9.348934240362811465e+01 9.404952380952380508e+01 9.456907029478458071e+01 9.510022675736961162e+01 9.573587301587301113e+01 9.626412698412698887e+01 9.684172335600906933e+01 9.738739229024943711e+01 9.791564625850340065e+01 9.848163265306122582e+01 9.903310657596371414e+01 9.958167800453514928e+01 1.001505668934240418e+02 1.007339682539682570e+02 1.012448072562358306e+02 1.018049886621315210e+02 1.023100226757369597e+02 1.028963265306122423e+02 1.034507029478457980e+02 1.039847619047619105e+02 1.045275283446711967e+02 1.050790022675736992e+02 1.056275736961451202e+02 1.061935600907029453e+02 1.067566439909297031e+02 1.073313378684807304e+02 1.078828117913832187e+02 1.084313832199546539e+02 1.089741496598639401e+02 1.095169160997732405e+02 1.100712925170067962e+02 1.105908390022675718e+02 1.111365079365079396e+02 1.116676643990929705e+02 1.121697959183673419e+02 1.128141496598639435e+02 1.133307936507936518e+02 1.138938775510204096e+02 1.144453514739228979e+02 1.150200453514739252e+02 1.155337868480725660e+02 1.160736507936507991e+02 1.166077097505668974e+02 1.171562811791383183e+02 1.176903401360544166e+02 1.182331065759637170e+02 1.187671655328798153e+02 1.193244444444444383e+02 1.198526984126984161e+02 1.203867573696145143e+02 1.209440362811791374e+02 1.215042176870748278e+02 1.220063492063492134e+02 1.226100680272108860e+02 1.231731519274376438e+02 1.237188208616780116e+02 1.242673922902494326e+02 1.248043537414965982e+02 1.253442176870748312e+02 1.258666666666666600e+02 1.263949206349206378e+02 1.269405895691609913e+02 1.274630385487528343e+02 1.279854875283446773e+02 1.285079365079365061e+02 1.290419954648526186e+02 1.295644444444444332e+02 1.301855782312925101e+02 1.306993197278911509e+02 1.312595011337868414e+02 1.318109750566893297e+02 1.323653514739229138e+02 1.328907029478457957e+02 1.334450793650793514e+02 1.339733333333333292e+02 1.345219047619047501e+02 1.350559637188208626e+02 1.356045351473922835e+02 1.361502040816326655e+02 1.366726530612244801e+02 1.372009070294784578e+02 1.377378684807256377e+02 1.383386848072562429e+02 1.388350113378684796e+02 1.393777777777777658e+02 1.399408616780045236e+02 1.404865306122449056e+02 1.410380045351473939e+02 1.415662585034013716e+02 1.421061224489795904e+02 1.426285714285714334e+02 1.431858503401360565e+02 1.437402267573696122e+02 1.442771882086167921e+02 1.448025396825396740e+02 1.453307936507936518e+02 1.458532426303854947e+02 1.463989115646258483e+02 1.469590929705215387e+02 1.475192743764172292e+02 1.480939682539682565e+02 1.486367346938775427e+02 1.491911111111110984e+02 1.497774149659863951e+02 1.503492063492063551e+02 1.509064852607709781e+02 1.514550566893423991e+02 1.520123356009070221e+02 1.525609070294784715e+02 1.531152834467120272e+02 1.536493424036281112e+02 1.541921088435374259e+02 1.547232653061224426e+02 1.552747392290249309e+02 1.558291156462585150e+02 1.564038095238095138e+02 1.569494784580498958e+02 1.575067573696145189e+02 1.580466213151927377e+02 1.585893877551020523e+02 1.591263492063492038e+02 1.596546031746031815e+02 1.602031746031746025e+02 1.607952834467120056e+02 mir_eval-0.8.2/tests/data/beat/est06.txt000066400000000000000000000207121475740344600200270ustar00rootroot000000000000001.219047619047619047e-01 6.211337868480725222e-01 1.149387755102040831e+00 1.732789115646258482e+00 2.290068027210884427e+00 2.885079365079365132e+00 3.453968253968254132e+00 4.057687074829932072e+00 4.652698412698412334e+00 5.215782312925170139e+00 5.688888888888889106e+00 6.069115646258503638e+00 6.591564625850340420e+00 7.160453514739229419e+00 7.648072562358276372e+00 8.138594104308390698e+00 8.669750566893423382e+00 9.206712018140589038e+00 9.729160997732426708e+00 1.023129251700680342e+01 1.076244897959183611e+01 1.129360544217687057e+01 1.182476190476190503e+01 1.230947845804988638e+01 1.302058956916099852e+01 1.356335600907029537e+01 1.409160997732426246e+01 1.462276643990929692e+01 1.513360544217687043e+01 1.564734693877550953e+01 1.616108843537415041e+01 1.668353741496598630e+01 1.718857142857142861e+01 1.776036281179138498e+01 1.823056689342403658e+01 1.875301587301587247e+01 1.924934240362811622e+01 1.975727891156462590e+01 2.025360544217686964e+01 2.075863945578231196e+01 2.127238095238095283e+01 2.178321995464852634e+01 2.231437641723356080e+01 2.281070294784580454e+01 2.331573696145124686e+01 2.382657596371882036e+01 2.433451247165533005e+01 2.486857142857142833e+01 2.535619047619047706e+01 2.587283446712018176e+01 2.635464852607709574e+01 2.689451247165532877e+01 2.741115646258503347e+01 2.791328798185941196e+01 2.844154195011337904e+01 2.902204081632653043e+01 2.958222222222222086e+01 3.013369614512471628e+01 3.064163265306122597e+01 3.118730158730158664e+01 3.168653061224489775e+01 3.219446712018140744e+01 3.274013605442176811e+01 3.325968253968253663e+01 3.377052154195011013e+01 3.428716553287981839e+01 3.479800453514739189e+01 3.530884353741496540e+01 3.582258503401360628e+01 3.633922902494330742e+01 3.683845804988661854e+01 3.735800453514739417e+01 3.786884353741496767e+01 3.837968253968254118e+01 3.891664399092970683e+01 3.943328798185940798e+01 3.994702947845804886e+01 4.045786848072562236e+01 4.100063492063492276e+01 4.150566893424036152e+01 4.200489795918367264e+01 4.252154195011338089e+01 4.304399092970521679e+01 4.356063492063491793e+01 4.405986394557822905e+01 4.458231292517006494e+01 4.507863945578231579e+01 4.558367346938775455e+01 4.608870748299320041e+01 4.661405895691609658e+01 4.713070294784580483e+01 4.765895691609977547e+01 4.815238095238095184e+01 4.865451247165533033e+01 4.918566893424036124e+01 4.972843537414966164e+01 5.022476190476190538e+01 5.070947845804988674e+01 5.122321995464852762e+01 5.174566893424036351e+01 5.225360544217686964e+01 5.275863945578231551e+01 5.328399092970521878e+01 5.378031746031746252e+01 5.429986394557823104e+01 5.484553287981859171e+01 5.537088435374149498e+01 5.588752834467120323e+01 5.640126984126984411e+01 5.692662131519274027e+01 5.744907029478458327e+01 5.798312925170068155e+01 5.849106575963718768e+01 5.900190476190476119e+01 5.950984126984126732e+01 6.004099773242630533e+01 6.054022675736961645e+01 6.106557823129251972e+01 6.157931972789115349e+01 6.206693877551020222e+01 6.258648526077097785e+01 6.312634920634920377e+01 6.364589569160997939e+01 6.414802721088435078e+01 6.465886621315192428e+01 6.519873015873015731e+01 6.570956916099773082e+01 6.620879818594104904e+01 6.673124716553287783e+01 6.723337868480724921e+01 6.776453514739229433e+01 6.829569160997732524e+01 6.880943310657596612e+01 6.935510204081631969e+01 6.987755102040816269e+01 7.037968253968253407e+01 7.088181405895691967e+01 7.141006802721088320e+01 7.192380952380952408e+01 7.243755102040816496e+01 7.295419501133787321e+01 7.345922902494331197e+01 7.392072562358276855e+01 7.448961451247166110e+01 7.501786848072562464e+01 7.555192743764172292e+01 7.609179138321995595e+01 7.660843537414966420e+01 7.711927437641723770e+01 7.762721088435374384e+01 7.814385487528345209e+01 7.870403628117914252e+01 7.921197278911564865e+01 7.975764172335600222e+01 8.027718820861677784e+01 8.079673469387755347e+01 8.129306122448979011e+01 8.179519274376417570e+01 8.236117913832200088e+01 8.286040816326530489e+01 8.339156462585033580e+01 8.391981859410431355e+01 8.444517006802720971e+01 8.495891156462585059e+01 8.547265306122449147e+01 8.598929705215419972e+01 8.649142857142857110e+01 8.700517006802721198e+01 8.752181405895692023e+01 8.807619047619047592e+01 8.858122448979591468e+01 8.906303854875282866e+01 8.957968253968253691e+01 9.015147392290249684e+01 9.064780045351473348e+01 9.117315192743764385e+01 9.165496598639455783e+01 9.215129251700680868e+01 9.269115646258502750e+01 9.321360544217687050e+01 9.373315192743764612e+01 9.421206349206349273e+01 9.475773242630386051e+01 9.526276643990929927e+01 9.583455782312924498e+01 9.635410430839002061e+01 9.677786848072562975e+01 9.717841269841269991e+01 9.765732426303854652e+01 9.816816326530612002e+01 9.869641723356009777e+01 9.920435374149660390e+01 9.970938775510204266e+01 1.002579591836734636e+02 1.007629931972789166e+02 1.012738321995464901e+02 1.017904761904761841e+02 1.025393197278911543e+02 1.030559637188208626e+02 1.035755102040816382e+02 1.040718367346938749e+02 1.045565532879818562e+02 1.051109297052154261e+02 1.055985487528344606e+02 1.061035827664399136e+02 1.065824943310657602e+02 1.071049433106576032e+02 1.076157823129251767e+02 1.081063038548752786e+02 1.086113378684807316e+02 1.091279818594104256e+02 1.096359183673469317e+02 1.101090249433106578e+02 1.106401814058956887e+02 1.111248979591836701e+02 1.116676643990929705e+02 1.121814058956916114e+02 1.127386848072562344e+02 1.132785487528344675e+02 1.137922902494331083e+02 1.143002267573696145e+02 1.148081632653061206e+02 1.153277097505668962e+02 1.158385487528344697e+02 1.163551927437641780e+02 1.168805442176870741e+02 1.173942857142857150e+02 1.179254421768707459e+02 1.184275736961451315e+02 1.189442176870748256e+02 1.194434467120181438e+02 1.199194557823129230e+02 1.204128798185941065e+02 1.209004988662131552e+02 1.214461678004535088e+02 1.219686167800453518e+02 1.224649433106576026e+02 1.229728798185941088e+02 1.234808163265306149e+02 1.240032653061224437e+02 1.245199092970521519e+02 1.250278458049886581e+02 1.255531972789115684e+02 1.260611337868480746e+02 1.265864852607709707e+02 1.271060317460317464e+02 1.276081632653061178e+02 1.281364172335600813e+02 1.286791836734693959e+02 1.292306575963718842e+02 1.297327891156462556e+02 1.302697505668934355e+02 1.307776870748299416e+02 1.313030385487528235e+02 1.318022675736961560e+02 1.323102040816326621e+02 1.328268480725623704e+02 1.333347845804988765e+02 1.338862585034013648e+02 1.343738775510203993e+02 1.348818140589569055e+02 1.353984580498866137e+02 1.359092970521541872e+02 1.364607709750566755e+02 1.369541950113378732e+02 1.374795464852607836e+02 1.379729705215419528e+02 1.384896145124716611e+02 1.390033560090703020e+02 1.395054875283446734e+02 1.400018140589569100e+02 1.405416780045351572e+02 1.410525170068027307e+02 1.415546485260771021e+02 1.421003174603174557e+02 1.426082539682539618e+02 1.431394104308390069e+02 1.436386394557823110e+02 1.441930158730158666e+02 1.447677097505668939e+02 1.453104761904761801e+02 1.458097052154195126e+02 1.463466666666666640e+02 1.468633106575963723e+02 1.473741496598639458e+02 1.478965986394557888e+02 1.484248526077097381e+02 1.489385941043083790e+02 1.494552380952380872e+02 1.499747845804988629e+02 1.504769160997732342e+02 1.509819501133786730e+02 1.514782766439909381e+02 1.519920181405895789e+02 1.524883446712018156e+02 1.530165986394557933e+02 1.535448526077097426e+02 1.540556916099773161e+02 1.545636281179138223e+02 1.550657596371882221e+02 1.555678911564625935e+02 1.560787301587301670e+02 1.566243990929705205e+02 1.571555555555555657e+02 1.576576870748299370e+02 1.581714285714285779e+02 1.586503401360544103e+02 1.592192290249433029e+02 1.597590929705215501e+02 1.602525170068027194e+02 1.607778684807256298e+02 1.612887074829932033e+02 1.618140589569161136e+02 1.623684353741496693e+02 1.628908843537414839e+02 1.633988208616780184e+02 1.639067573696145246e+02 1.644175963718820981e+02 1.649226303854875368e+02 1.654044444444444366e+02 1.659181859410430775e+02 1.664348299319727857e+02 1.670472562358276605e+02 1.675290702947845887e+02 1.679644444444444389e+02 1.684810884353741471e+02 1.690151473922902596e+02 1.695346938775510068e+02 1.700194104308390024e+02 1.705157369614512390e+02 1.710294784580498799e+02 1.715345124716553187e+02 1.720424489795918248e+02 1.725445804988662246e+02 1.730757369614512413e+02 1.735952834467120169e+02 1.740916099773242536e+02 1.746343764172335682e+02 1.751742403628117870e+02 1.756937868480725626e+02 1.762278458049886751e+02 1.767648072562358266e+02 1.773336961451247191e+02 1.779083900226757464e+02 1.784569614512471674e+02 1.789852154195011451e+02 mir_eval-0.8.2/tests/data/beat/est07.txt000066400000000000000000000222061475740344600200300ustar00rootroot000000000000004.144761904761904425e+00 4.704943310657596633e+00 5.302857142857142492e+00 5.839818594104308147e+00 6.359365079365079332e+00 6.919546485260770652e+00 7.441995464852607434e+00 7.973151927437641895e+00 8.498503401360544274e+00 9.038367346938775526e+00 9.560816326530611420e+00 1.009197278911564588e+01 1.062312925170068034e+01 1.115718820861678040e+01 1.169414965986394606e+01 1.226884353741496625e+01 1.276226757369614440e+01 1.329052154195011326e+01 1.382458049886621332e+01 1.433251700680272123e+01 1.486657596371882128e+01 1.538321995464852598e+01 1.592018140589569164e+01 1.642811791383219955e+01 1.692444444444444329e+01 1.744399092970521536e+01 1.797804988662131365e+01 1.850340136054421691e+01 1.903455782312925137e+01 1.955120181405895607e+01 2.007655328798185934e+01 2.060190476190476261e+01 2.112145124716553113e+01 2.164970521541950177e+01 2.218666666666666742e+01 2.273233560090702809e+01 2.325188208616780017e+01 2.377723356009070343e+01 2.430548752834467052e+01 2.483083900226757379e+01 2.533877551020407992e+01 2.586993197278911438e+01 2.638367346938775526e+01 2.690031746031745996e+01 2.742857142857142705e+01 2.793070294784580554e+01 2.844734693877551024e+01 2.897560090702947733e+01 2.948934240362811821e+01 3.001179138321995410e+01 3.054004535147392119e+01 3.106829931972789183e+01 3.159365079365079509e+01 3.212190476190475863e+01 3.264435374149660163e+01 3.315519274376417513e+01 3.367764172335601103e+01 3.418557823129251716e+01 3.471963718820861544e+01 3.524208616780045134e+01 3.574712018140589720e+01 3.626956916099773309e+01 3.679201814058956899e+01 3.728544217687074536e+01 3.779918367346938624e+01 3.832743764172335688e+01 3.887891156462585229e+01 3.941297052154195057e+01 3.991800453514738933e+01 4.044625850340135997e+01 4.097160997732426324e+01 4.149696145124716651e+01 4.201650793650793503e+01 4.253895691609977092e+01 4.307011337868480894e+01 4.358385487528344981e+01 4.410630385487528571e+01 4.462875283446712160e+01 4.516281179138321988e+01 4.568816326530612315e+01 4.620770975056689167e+01 4.673306122448979494e+01 4.726421768707483295e+01 4.779247165532879649e+01 4.830621315192743737e+01 4.883736961451246827e+01 4.936562358276643891e+01 4.988807256235827481e+01 5.040471655328798306e+01 5.093297052154194660e+01 5.146412698412698461e+01 5.200399092970521764e+01 5.251773242630385141e+01 5.306049886621315181e+01 5.360616780045351248e+01 5.410539682539682360e+01 5.459591836734693970e+01 5.515900226757369751e+01 5.571047619047619293e+01 5.624163265306122383e+01 5.676117913832199235e+01 5.729523809523809774e+01 5.782349206349206128e+01 5.834884353741496454e+01 5.888290249433106283e+01 5.940535147392290583e+01 5.992780045351474172e+01 6.045315192743764499e+01 6.098721088435374327e+01 6.151256235827664653e+01 6.202340136054422004e+01 6.255746031746031832e+01 6.307410430839001947e+01 6.359074829931972772e+01 6.410739229024943597e+01 6.463274376417233213e+01 6.514358276643990564e+01 6.567473922902493655e+01 6.620299319727891429e+01 6.671963718820862255e+01 6.722757369614512868e+01 6.776163265306122696e+01 6.830439909297052736e+01 6.883265306122449090e+01 6.934349206349206440e+01 6.988045351473923006e+01 7.040000000000000568e+01 7.092535147392290185e+01 7.142458049886622007e+01 7.194412698412698148e+01 7.251011337868480666e+01 7.303836734693877020e+01 7.356371882086168057e+01 7.409487528344671148e+01 7.460281179138321761e+01 7.513396825396824852e+01 7.564770975056688940e+01 7.616725623582766502e+01 7.668680272108844065e+01 7.720925170068026944e+01 7.772009070294784294e+01 7.825124716553287385e+01 7.876789115646258210e+01 7.928743764172335773e+01 7.980117913832199861e+01 8.031492063492063949e+01 8.082575963718821299e+01 8.135981859410431127e+01 8.187356009070295215e+01 8.240471655328798306e+01 8.292716553287981185e+01 8.344671201814058747e+01 8.390530612244897668e+01 8.448580498866212452e+01 8.501405895691610226e+01 8.553650793650793105e+01 8.605605442176870667e+01 8.657269841269841493e+01 8.708934240362812318e+01 8.759727891156462931e+01 8.812553287981859285e+01 8.864798185941043585e+01 8.919655328798185678e+01 8.972770975056688769e+01 9.024435374149659594e+01 9.074938775510203470e+01 9.126893424036281033e+01 9.178557823129251858e+01 9.229641723356009209e+01 9.281015873015873296e+01 9.332390022675737384e+01 9.383183673469387998e+01 9.435428571428570876e+01 9.487092970521541702e+01 9.539337868480726002e+01 9.590131519274376615e+01 9.642086167800454177e+01 9.693460317460316844e+01 9.744834467120180932e+01 9.797369614512471969e+01 9.849034013605442794e+01 9.900698412698412199e+01 9.952362811791383024e+01 1.000518820861677938e+02 1.005685260770975020e+02 1.010967800453514798e+02 1.016279365079365107e+02 1.021358730158730168e+02 1.026438095238095229e+02 1.031633560090702986e+02 1.036683900226757373e+02 1.041792290249433108e+02 1.047074829931972744e+02 1.052270294784580500e+02 1.057697959183673504e+02 1.063038548752834487e+02 1.068234013605442243e+02 1.073400453514739183e+02 1.078886167800453535e+02 1.084052607709750617e+02 1.089160997732426353e+02 1.094472562358276662e+02 1.100016326530612218e+02 1.105356916099773201e+02 1.110494331065759610e+02 1.115776870748299388e+02 1.121117460317460370e+02 1.126516099773242701e+02 1.131392290249433046e+02 1.136732879818594171e+02 1.142189569160997706e+02 1.147472108843537484e+02 1.152609523809523751e+02 1.157863038548752854e+02 1.163116553287981816e+02 1.168224943310657551e+02 1.173478458049886655e+02 1.178760997732426290e+02 1.183985487528344720e+02 1.189151927437641660e+02 1.194318367346938743e+02 1.199687981859410399e+02 1.204767346938775461e+02 1.209672562358276622e+02 1.214780952380952357e+02 1.219831292517006744e+02 1.225491156462584996e+02 1.230657596371882079e+02 1.235678911564625793e+02 1.240845351473922875e+02 1.246127891156462653e+02 1.251323356009070267e+02 1.256402721088435328e+02 1.261511111111111063e+02 1.266996825396825415e+02 1.272018140589569128e+02 1.277271655328798232e+02 1.282438095238095173e+02 1.287546485260770908e+02 1.292770975056689338e+02 1.297937414965986420e+02 1.302871655328798113e+02 1.308299319727891259e+02 1.313407709750566994e+02 1.318545124716553403e+02 1.323624489795918464e+02 1.328761904761904873e+02 1.334015419501133692e+02 1.339123809523809427e+02 1.344203174603174489e+02 1.349398639455782245e+02 1.354565079365079328e+02 1.359760544217687084e+02 1.364781859410430798e+02 1.369948299319727880e+02 1.375085714285714289e+02 1.380194104308390024e+02 1.385215419501133738e+02 1.390585034013605537e+02 1.396041723356009072e+02 1.401034013605442112e+02 1.406171428571428521e+02 1.411599092970521667e+02 1.416794557823129139e+02 1.421757823129251790e+02 1.427040362811791283e+02 1.432439002267573755e+02 1.437518367346938817e+02 1.442742857142857247e+02 1.447590022675736918e+02 1.452698412698412653e+02 1.457893877551020410e+02 1.463060317460317492e+02 1.468226757369614575e+02 1.473393197278911657e+02 1.478733786848072498e+02 1.484016326530612275e+02 1.489182766439909358e+02 1.494436281179138462e+02 1.499602721088435260e+02 1.504856235827664364e+02 1.510022675736961446e+02 1.515334240362811897e+02 1.520703854875283412e+02 1.525812244897959147e+02 1.531007709750566903e+02 1.536203174603174659e+02 1.540876190476190573e+02 1.545839455782312939e+02 1.550918820861678000e+02 1.556433560090702883e+02 1.561658049886621313e+02 1.566650340136054353e+02 1.571903854875283457e+02 1.577418594104308340e+02 1.582556009070294749e+02 1.587693424036281158e+02 1.592801814058956893e+02 1.597939229024943302e+02 1.603018594104308363e+02 1.608039909297052077e+02 1.612945124716553380e+02 1.618372789115646242e+02 1.623452154195011303e+02 1.628647619047619060e+02 1.633930158730158837e+02 1.639183673469387656e+02 1.644408163265306086e+02 1.649574603174603169e+02 1.654857142857142946e+02 1.660081632653061092e+02 1.665306122448979522e+02 1.670327437641723236e+02 1.675871201814059077e+02 1.680950566893424138e+02 1.685971882086167852e+02 1.691283446712018019e+02 1.696246712018140670e+02 1.701384126984127079e+02 1.706724716553287919e+02 1.711629931972789223e+02 1.717144671201814106e+02 1.722311111111111188e+02 1.727535600907029618e+02 1.732643990929705353e+02 1.737810430839002152e+02 1.743151020408163276e+02 1.748201360544217664e+02 1.753338775510204073e+02 1.758331065759637113e+02 1.763497505668934195e+02 1.768518820861677909e+02 1.773511111111111234e+02 1.778619501133786969e+02 1.783785941043083767e+02 1.788952380952380850e+02 1.794060770975056585e+02 1.799140136054421646e+02 1.804306575963718728e+02 1.809414965986394463e+02 1.814552380952380872e+02 1.819660770975056607e+02 1.824711111111110995e+02 1.829935600907029425e+02 1.834956916099773139e+02 1.840094331065759548e+02 1.845144671201813935e+02 1.850369160997732365e+02 1.855506575963718774e+02 1.860643990929705183e+02 1.865723356009070244e+02 1.870889795918367327e+02 1.875940136054421714e+02 1.880961451247165428e+02 1.886214965986394532e+02 1.891352380952380940e+02 1.896489795918367349e+02 1.901656235827664432e+02 1.906851700680272188e+02 1.911960090702947923e+02 1.917097505668934332e+02 1.922205895691610067e+02 1.927430385487528213e+02 1.932422675736961537e+02 1.937531065759637272e+02 1.942523356009070312e+02 1.947544671201814026e+02 1.952798185941043130e+02 1.958138775510203970e+02 1.963363265306122400e+02 1.968558730158730157e+02 1.973725170068027239e+02 1.978891609977324322e+02 1.984464399092970552e+02 mir_eval-0.8.2/tests/data/beat/est08.txt000066400000000000000000000154771475740344600200450ustar00rootroot000000000000003.453968253968254243e-01 8.852607709750567322e-01 1.465759637188208675e+00 1.999818594104308289e+00 2.545487528344671180e+00 3.059229024943310726e+00 3.578775510204081467e+00 4.109931972789115484e+00 4.815238095238095539e+00 5.433469387755102353e+00 6.034285714285714697e+00 6.667029478458049496e+00 7.262040816326530646e+00 7.903492063492063124e+00 8.542040816326530006e+00 9.122539682539683170e+00 9.685623582766439199e+00 1.031256235827664369e+01 1.090467120181405924e+01 1.150839002267573719e+01 1.207727891156462618e+01 1.265197278911564638e+01 1.327891156462585087e+01 1.385941043083900226e+01 1.446603174603174580e+01 1.504943310657596456e+01 1.566185941043083929e+01 1.621043083900226733e+01 1.679383219954648609e+01 1.735981859410430772e+01 1.792870748299319672e+01 1.858757369614512456e+01 1.917968253968253833e+01 1.975147392290249471e+01 2.032616780045351490e+01 2.092408163265305987e+01 2.150748299319727863e+01 2.210539682539682715e+01 2.269170068027210974e+01 2.325768707482993136e+01 2.384108843537415012e+01 2.441287981859410294e+01 2.502530612244898123e+01 2.561741496598639500e+01 2.621823129251700735e+01 2.677260770975056658e+01 2.736181405895691654e+01 2.798004535147392247e+01 2.854893424036281147e+01 2.913814058956916142e+01 2.975346938775510353e+01 3.030494331065759539e+01 3.090866213151927511e+01 3.147464852607709673e+01 3.204643990929704955e+01 3.265015873015872927e+01 3.322775510204081684e+01 3.379083900226757464e+01 3.438294784580499197e+01 3.496054421768707243e+01 3.555555555555555713e+01 3.617668934240362688e+01 3.675138321995464707e+01 3.730866213151927724e+01 3.788916099773242507e+01 3.846675736961451264e+01 3.901532879818594068e+01 3.962195011337868777e+01 4.021115646258503062e+01 4.076553287981859341e+01 4.135764172335601074e+01 4.188879818594104165e+01 4.249251700680272137e+01 4.310204081632652873e+01 4.369124716553287868e+01 4.425433106575963649e+01 4.487256235827664597e+01 4.544435374149659879e+01 4.600163265306122184e+01 4.665179138321995111e+01 4.722068027210884367e+01 4.779247165532879649e+01 4.840199546485261095e+01 4.897959183673469141e+01 4.958911564625850588e+01 5.019283446712017849e+01 5.079655328798185820e+01 5.134802721088435362e+01 5.194884353741496597e+01 5.252643990929705353e+01 5.310693877551020137e+01 5.370195011337868607e+01 5.429696145124716367e+01 5.486004535147392147e+01 5.548117913832199832e+01 5.605877551020407878e+01 5.664798185941042874e+01 5.726621315192743822e+01 5.785541950113378817e+01 5.841850340136054598e+01 5.901061224489795620e+01 5.958530612244897640e+01 6.013387755102041154e+01 6.075501133786848129e+01 6.137614512471655104e+01 6.193922902494330884e+01 6.254585034013605593e+01 6.310022675736961162e+01 6.368362811791383393e+01 6.431346938775510580e+01 6.485043083900227145e+01 6.546285714285714619e+01 6.609850340136054569e+01 6.664707482993196663e+01 6.723628117913831659e+01 6.784000000000000341e+01 6.842630385487528599e+01 6.899809523809523171e+01 6.957278911564625901e+01 7.013587301587301681e+01 7.075120181405895892e+01 7.137233560090703577e+01 7.193541950113379357e+01 7.247818594104307977e+01 7.305287981859410706e+01 7.364498866213152439e+01 7.420226757369614745e+01 7.479147392290249741e+01 7.537487528344671261e+01 7.594666666666667254e+01 7.652426303854875300e+01 7.708154195011337606e+01 7.762430839002267646e+01 7.823092970521541645e+01 7.879401360544217425e+01 7.938321995464852421e+01 7.995210884353741676e+01 8.052390022675737669e+01 8.109278911564625503e+01 8.173424036281178928e+01 8.229151927437641234e+01 8.286331065759637227e+01 8.344671201814058747e+01 8.399818594104309000e+01 8.459609977324262786e+01 8.514176870748299564e+01 8.577160997732426040e+01 8.638113378684806776e+01 8.697324263038548509e+01 8.758566893424035982e+01 8.820099773242630192e+01 8.874376417233560232e+01 8.936489795918367918e+01 8.998603174603174182e+01 9.055492063492063437e+01 9.116734693877550910e+01 9.176235827664399380e+01 9.238639455782312382e+01 9.292625850340135685e+01 9.350675736961451889e+01 9.411047619047619150e+01 9.470839002267574358e+01 9.525696145124716452e+01 9.586938775510203925e+01 9.643537414965986443e+01 9.698975056689342011e+01 9.754412698412699001e+01 9.812172335600907047e+01 9.872834467120181046e+01 9.923918367346938396e+01 9.984290249433107078e+01 1.003914739229024917e+02 1.008674829931972852e+02 1.014247619047619082e+02 1.020284807256235808e+02 1.026002721088435408e+02 1.031923809523809581e+02 1.037496598639455812e+02 1.043156462585034063e+02 1.048903401360544194e+02 1.054534240362811772e+02 1.060629478458049846e+02 1.065941043083900297e+02 1.071746031746031775e+02 1.077405895691610027e+02 1.083123809523809484e+02 1.088580498866213162e+02 1.094443537414965988e+02 1.099726077097505623e+02 1.105356916099773201e+02 1.111161904761904822e+02 1.116937868480725626e+02 1.122684807256235757e+02 1.128780045351473973e+02 1.134236734693877509e+02 1.139838548752834413e+02 1.145556462585034012e+02 1.151158276643990916e+02 1.156934240362811721e+02 1.162913378684807242e+02 1.168399092970521593e+02 1.174000907029478498e+02 1.180009070294784550e+02 1.185610884353741454e+02 1.191212698412698359e+02 1.196959637188208632e+02 1.202706575963718763e+02 1.208511564625850383e+02 1.214258503401360514e+02 1.219453968253968270e+02 1.225113832199546522e+02 1.230918820861678000e+02 1.236694784580498805e+02 1.242180498866213156e+02 1.247724263038548713e+02 1.253151927437641717e+02 1.258898866213151990e+02 1.264878004535147369e+02 1.270450793650793599e+02 1.275849433106575930e+02 1.281712471655328898e+02 1.287285260770975128e+02 1.293090249433106464e+02 1.299011337868480780e+02 1.304526077097505663e+02 1.310447165532879694e+02 1.316252154195011315e+02 1.322231292517006693e+02 1.328036281179138314e+02 1.333580045351473871e+02 1.339297959183673470e+02 1.345015873015873069e+02 1.350820861678004405e+02 1.357090249433106521e+02 1.362430839002267646e+02 1.368032653061224551e+02 1.373692517006802802e+02 1.379236281179138359e+02 1.384925170068027285e+02 1.390643083900226884e+02 1.396360997732426199e+02 1.401875736961451366e+02 1.407477551020408271e+02 1.413195464852607586e+02 1.418971428571428532e+02 1.424486167800453416e+02 1.430175056689342341e+02 1.436589569160997826e+02 1.442104308390022709e+02 1.447938321995464719e+02 1.453859410430839034e+02 1.459025850340136117e+02 1.464946938775510148e+02 1.470693877551020421e+02 1.476585941043083778e+02 1.482245804988662030e+02 1.488195918367347019e+02 1.493681632653061229e+02 1.499544671201814197e+02 1.505407709750566880e+02 1.511125623582766480e+02 1.516698412698412710e+02 1.522300226757369614e+02 1.527960090702947866e+02 1.533939229024943245e+02 1.539657142857142844e+02 1.545955555555555634e+02 1.551557369614512538e+02 1.557420408163265222e+02 1.563921995464852728e+02 1.569697959183673390e+02 1.575938321995464833e+02 1.582323809523809643e+02 1.589028571428571297e+02 1.595472108843537455e+02 1.602147845804988719e+02 1.608068934240362751e+02 1.614077097505668803e+02 1.620375510204081593e+02 mir_eval-0.8.2/tests/data/beat/est09.txt000066400000000000000000000372001475740344600200320ustar00rootroot000000000000002.349886621315195323e-01 8.068707482993203728e-01 1.378934240362813091e+00 1.950498866213153493e+00 2.522244897959184939e+00 3.093786848072563433e+00 3.665532879818595102e+00 4.237210884353743268e+00 4.808866213151929969e+00 5.380385487528348776e+00 5.952335600907034063e+00 6.524263038548758331e+00 7.095396825396830920e+00 7.666145124716559067e+00 8.237142857142863761e+00 8.808117913832207435e+00 9.379387755102049695e+00 9.951088435374158436e+00 1.052269841269842310e+01 1.109433106575963990e+01 1.166603174603173976e+01 1.223770975056687682e+01 1.280950113378682076e+01 1.338129251700676647e+01 1.395294784580494252e+01 1.452455782312919474e+01 1.509616780045344697e+01 1.566755102040808723e+01 1.623868480725614916e+01 1.680963718820851938e+01 1.738090702947835098e+01 1.795195011337856883e+01 1.852335600907016655e+01 1.909519274376404852e+01 1.966700680272097301e+01 2.023852607709740425e+01 2.081036281179129332e+01 2.138190476190468203e+01 2.195371882086161008e+01 2.252519274376411573e+01 2.309678004535143003e+01 2.366850340136051400e+01 2.424045351473920817e+01 2.481201814058956145e+01 2.538312925170068368e+01 2.595390022675738351e+01 2.652498866213154471e+01 2.709605442176874490e+01 2.766750566893428953e+01 2.823922902494337350e+01 2.881081632653068425e+01 2.938240362811799855e+01 2.995433106575973525e+01 3.052587301587312396e+01 3.109752834467132132e+01 3.166931972789128835e+01 3.224092970521555657e+01 3.281231292517021814e+01 3.338403628117929856e+01 3.395546485260788216e+01 3.452662131519293354e+01 3.509757369614529665e+01 3.566886621315207151e+01 3.623993197278922906e+01 3.680988662131527178e+01 3.737943310657600904e+01 3.794925170068028564e+01 3.851929705215417954e+01 3.908975056689337180e+01 3.966077097505660731e+01 4.023210884353730421e+01 4.080335600907014992e+01 4.137487528344653498e+01 4.194632653061203342e+01 4.251795918367322713e+01 4.308943310657569015e+01 4.366156462585003339e+01 4.423333333333300033e+01 4.480526077097469084e+01 4.537675736961411133e+01 4.594841269841226961e+01 4.651977324262991687e+01 4.709133786848023107e+01 4.766272108843484290e+01 4.823380952380896503e+01 4.880476190476131393e+01 4.937600907029415964e+01 4.994725623582700536e+01 5.051891156462516363e+01 5.109038548752762665e+01 5.166210884353666444e+01 5.223356009070216288e+01 5.280557823129169748e+01 5.337727891156377780e+01 5.394922902494242578e+01 5.452074829931881794e+01 5.509208616779950773e+01 5.566321995464755190e+01 5.623442176870647558e+01 5.680551020408059060e+01 5.737668934240255680e+01 5.794825396825286390e+01 5.852013605442063238e+01 5.909188208616663474e+01 5.966369614512351660e+01 6.023512471655205758e+01 6.080684807256109536e+01 6.137791383219824581e+01 6.194925170067894271e+01 6.252061224489659708e+01 6.309201814058818059e+01 6.366344671201671446e+01 6.423512471655183731e+01 6.480653061224342082e+01 6.537791383219803265e+01 6.594945578231137517e+01 6.652056689342245477e+01 6.709208616779885404e+01 6.766399092970358708e+01 6.823589569160830592e+01 6.880780045351303897e+01 6.937925170067853742e+01 6.995086167800276655e+01 7.052199546485081783e+01 7.109317460317276982e+01 7.166455782312739586e+01 7.223603174602985177e+01 7.280730158729966206e+01 7.337922902494135258e+01 7.395018140589370148e+01 7.452156462584831331e+01 7.509353741496393297e+01 7.566517006802513379e+01 7.623598639455570947e+01 7.680653061224275291e+01 7.737845804988444343e+01 7.794999999999778595e+01 7.852108843537190808e+01 7.909315192743537182e+01 7.966537414965755204e+01 8.023705215419266779e+01 8.080800453514501669e+01 8.137986394557583480e+01 8.195133786847829072e+01 8.252328798185693870e+01 8.309380952380702468e+01 8.366591836734440335e+01 8.423770975056433485e+01 8.480929705215160652e+01 8.537995464852345151e+01 8.595015873015607610e+01 8.652251700680002955e+01 8.709412698412425868e+01 8.766492063491787690e+01 8.823700680271829810e+01 8.880886621314910201e+01 8.938065759636903351e+01 8.995299319727602949e+01 9.052489795918076254e+01 9.109569160997438075e+01 9.167272108843239664e+01 9.224537414965685400e+01 9.281764172335296337e+01 9.338909297051846181e+01 9.396102040816015233e+01 9.453224489795604768e+01 9.510424036280862481e+01 9.567564625850019411e+01 9.624761904761581377e+01 9.681888888888562406e+01 9.739083900226427204e+01 9.796183673469055009e+01 9.853335600906693514e+01 9.910403628117573760e+01 9.967555555555212266e+01 1.002463945578196700e+02 1.008182539682504739e+02 1.013899092970486322e+02 1.019618367346903227e+02 1.025330612244862039e+02 1.031049886621278944e+02 1.036761904761868180e+02 1.042481859410393952e+02 1.048196371882049078e+02 1.053916099773205133e+02 1.059629024943272810e+02 1.065345578231254393e+02 1.071058276643952496e+02 1.076775736961412520e+02 1.082482993197239836e+02 1.088199773242590993e+02 1.093908843537375191e+02 1.099625850340096065e+02 1.105338321995424451e+02 1.111058956916059088e+02 1.116771655328757191e+02 1.122490929705174096e+02 1.128202947845763333e+02 1.133922222222180238e+02 1.139637188208574514e+02 1.145355555555512979e+02 1.151070294784537538e+02 1.156789342403584868e+02 1.162501133786804530e+02 1.168216099773198806e+02 1.173922448979547681e+02 1.179636281179093800e+02 1.185346258503356580e+02 1.191063945578186178e+02 1.196778684807210738e+02 1.202499773242584524e+02 1.208212471655282627e+02 1.213930839002221092e+02 1.219641723355962313e+02 1.225360997732379218e+02 1.231075283446664628e+02 1.236793877550972667e+02 1.242506349206301195e+02 1.248225396825348383e+02 1.253938321995416203e+02 1.259656009070245801e+02 1.265363265306073117e+02 1.271078231292467393e+02 1.276785487528294709e+02 1.282506122448929204e+02 1.288225396825345967e+02 1.293943310657545283e+02 1.299665079365028078e+02 1.305383900226705691e+02 1.311096598639403794e+02 1.316811791383167645e+02 1.322527437641670929e+02 1.328241043083847330e+02 1.333957823129198630e+02 1.339674149659810496e+02 1.345387755101986897e+02 1.351101587301533300e+02 1.356814285714231119e+02 1.362527891156407804e+02 1.368240136054366758e+02 1.373957596371826639e+02 1.379675283446656238e+02 1.385391383219898671e+02 1.391107029478401671e+02 1.396823129251644104e+02 1.402535827664342207e+02 1.408251473922845207e+02 1.413965986394500192e+02 1.419679365079307161e+02 1.425395464852549310e+02 1.431111564625791743e+02 1.436824263038489846e+02 1.442538775510144831e+02 1.448251473922842933e+02 1.453966439909237067e+02 1.459680272108783470e+02 1.465394104308329588e+02 1.471093424036220370e+02 1.476796825396764348e+02 1.482487301587240154e+02 1.488185034013543770e+02 1.493886394557760866e+02 1.499595691609914923e+02 1.505321088435311481e+02 1.511043310657533141e+02 1.516748072562294851e+02 1.522465306122385300e+02 1.528178004535083403e+02 1.533897505668869883e+02 1.539608390022611104e+02 1.545330385487463332e+02 1.551044217687009450e+02 1.556766666666601111e+02 1.562467120181339908e+02 1.568172562358210484e+02 1.573895691609910727e+02 1.579610884353674578e+02 1.585323582766372681e+02 1.591039909296984547e+02 1.596760770974988759e+02 1.602484353741428436e+02 1.608187755101972414e+02 1.613904081632584280e+02 1.619619954648456996e+02 1.625341269841200358e+02 1.631066893423966349e+02 1.636783673469317648e+02 1.642487301587231059e+02 1.648250793650722983e+02 1.653974149659792943e+02 1.659699999999928650e+02 1.665412244897887319e+02 1.671128571428499470e+02 1.676840362811718990e+02 1.682559863945505469e+02 1.688275283446639037e+02 1.693995238095164666e+02 1.699710430838928517e+02 1.705431972789041595e+02 1.711144217687000548e+02 1.716860090702873265e+02 1.722566666666591857e+02 1.728280045351398542e+02 1.733986848072486850e+02 1.739704081632577299e+02 1.745417460317383984e+02 1.751138775510127630e+02 1.756851020408086299e+02 1.762570068027133630e+02 1.768283673469310315e+02 1.774002494330987929e+02 1.779716780045273481e+02 1.785435374149581378e+02 1.791148979591758064e+02 1.796867120181326811e+02 1.802577551020328883e+02 1.808292970521462166e+02 1.814001133786767923e+02 1.819717006802640640e+02 1.825425623582685830e+02 1.831145578231211459e+02 1.836859863945497011e+02 1.842579591836652924e+02 1.848291156462503011e+02 1.854008843537332609e+02 1.859721541950030712e+02 1.865441723355926058e+02 1.871159183673386224e+02 1.876880045351390436e+02 1.882592970521457971e+02 1.888312925169983885e+02 1.894029931972704617e+02 1.899743764172250735e+02 1.905449433106490744e+02 1.911161451247079981e+02 1.916867120181319990e+02 1.922584126984040722e+02 1.928298412698326274e+02 1.934019274376330486e+02 1.939733106575876604e+02 1.945451020408075919e+02 1.951161904761817141e+02 1.956880725623494754e+02 1.962596371881997754e+02 1.968315192743675368e+02 1.974029478457960920e+02 1.979748752834377683e+02 1.985458049886531740e+02 1.991173922902404456e+02 1.996881632652971064e+02 2.002597052154104347e+02 2.008306802720997553e+02 2.014020408163173954e+02 2.019724036281087649e+02 2.025419047618955801e+02 2.031091383219862507e+02 2.036769160997639858e+02 2.042482086167707678e+02 2.048197052154101812e+02 2.053910884353647930e+02 2.059625850340042348e+02 2.065340136054327616e+02 2.071055328798091466e+02 2.076770294784485600e+02 2.082485714285619167e+02 2.088200907029383018e+02 2.093916326530516585e+02 2.099631065759541002e+02 2.105346485260674569e+02 2.111061678004438420e+02 2.116776643990832838e+02 2.122491836734596689e+02 2.128205668934142807e+02 2.133919954648428075e+02 2.139635147392191925e+02 2.145350566893325492e+02 2.151065759637089343e+02 2.156780952380853194e+02 2.162496145124617044e+02 2.168211111111011178e+02 2.173925623582666162e+02 2.179640589569060580e+02 2.185355555555454714e+02 2.191070294784479415e+02 2.196839229024841700e+02 2.202573922902392383e+02 2.208298639455680075e+02 2.214022448979489468e+02 2.219763718820758811e+02 2.225448752834363972e+02 2.231157596371778595e+02 2.236867573696041234e+02 2.242601360544113618e+02 2.248305668934135895e+02 2.254028798185836422e+02 2.259742176870643391e+02 2.265487755101935363e+02 2.271182312925064366e+02 2.276913832199440435e+02 2.282607256235721422e+02 2.288342176870641822e+02 2.294049206349099279e+02 2.299770294784473208e+02 2.305470975056581722e+02 2.311212471655220781e+02 2.316877777777669678e+02 2.322602040816217936e+02 2.328303628117805033e+02 2.334029251700571024e+02 2.339736734693767914e+02 2.345467800453404834e+02 2.351179591836624638e+02 2.356925396825286327e+02 2.362626530612133990e+02 2.368350793650682533e+02 2.374043990929593804e+02 2.379769160997620645e+02 2.385479138321883283e+02 2.391198185940930614e+02 2.396904988662018923e+02 2.402642857142744219e+02 2.408319727891042987e+02 2.414036961451133436e+02 2.419743310657482311e+02 2.425474376417119231e+02 2.431175963718706328e+02 2.436904081632538066e+02 2.442622675736846247e+02 2.448349886621199687e+02 2.454054875283330830e+02 2.459771428571312413e+02 2.465469160997615745e+02 2.471193877550903437e+02 2.476917460317343114e+02 2.482647845804871167e+02 2.488356009070176924e+02 2.494099999999881732e+02 2.499775056689223902e+02 2.505478231292398164e+02 2.511180045351354693e+02 2.516914058956796794e+02 2.522617006802601338e+02 2.528343083900106762e+02 2.534056235827544015e+02 2.539796145124595910e+02 2.545496145124595557e+02 2.551212018140468274e+02 2.556908843537293308e+02 2.562589569160875840e+02 2.568301587301465361e+02 2.574002040816204158e+02 2.579728344671079299e+02 2.585449659863822376e+02 2.591186848072440512e+02 2.596905442176752672e+02 2.602628571428456326e+02 2.608354875283334877e+02 2.614089569160889255e+02 2.619826077097400230e+02 2.625559863945475740e+02 2.631278231292417900e+02 2.636982993197182736e+02 2.642819501133694189e+02 2.648570068027121351e+02 2.654055102040729821e+02 2.659745124716470173e+02 2.665441269841189751e+02 2.671166439909220003e+02 2.676881632652987264e+02 2.682608390022605249e+02 2.688327664399025707e+02 2.694062358276579516e+02 2.699768480725562654e+02 2.705484580498808214e+02 2.711198639455727744e+02 2.716920634920583097e+02 2.722635147392242061e+02 2.728358730158685148e+02 2.734057596371840191e+02 2.739770521541911421e+02 2.745469160997697031e+02 2.751185714285682025e+02 2.756885487528315366e+02 2.762609523809497887e+02 2.768331972789092674e+02 2.774064172335581020e+02 2.779778231292500550e+02 2.785507936507922864e+02 2.791235600907019148e+02 2.796972108843530691e+02 2.802704081632649036e+02 2.808435147392289650e+02 2.814163718820864233e+02 2.819880272108849226e+02 2.825747165532888516e+02 2.831501814058968876e+02 2.836935600907044659e+02 2.842622675736979545e+02 2.848319274376438557e+02 2.854047619047643707e+02 2.859774376417261692e+02 2.865503628117944572e+02 2.871218367346972968e+02 2.876950340136091882e+02 2.882648752834507491e+02 2.888365759637231918e+02 2.894078458049933715e+02 2.899804761904812267e+02 2.905524036281232156e+02 2.911248299319784678e+02 2.916936734693937296e+02 2.922661224489858682e+02 2.928471655328864358e+02 2.934194331065829147e+02 2.939914739229097336e+02 2.945625623582841968e+02 2.951337641723434899e+02 2.957040589569243139e+02 2.962755782313010400e+02 2.968460317460405804e+02 2.974176870748390797e+02 2.979891836734788626e+02 2.985611111111209084e+02 2.991320861678105416e+02 2.997046031746135668e+02 3.002764625850447828e+02 3.008489115646369214e+02 3.014206122449093073e+02 3.019925623582883532e+02 3.025637641723475895e+02 3.031355328798309188e+02 3.037065532879944953e+02 3.042778231292646751e+02 3.048480272108976123e+02 3.054195918367482818e+02 3.059902721088574822e+02 3.065622448979734145e+02 3.071337188208761972e+02 3.077056462585182999e+02 3.082770975056841394e+02 3.088492290249587882e+02 3.094209070294942876e+02 3.099930158730319931e+02 3.105644897959348327e+02 3.111363265306290486e+02 3.117076190476361717e+02 3.122795238095412174e+02 3.128506349206526806e+02 3.134219501133967469e+02 3.139921768707666843e+02 3.145633786848259206e+02 3.151339455782502910e+02 3.157056009070487903e+02 3.162769841270037432e+02 3.168487981859610159e+02 3.174197959183875923e+02 3.179923582766645609e+02 3.185640816326740037e+02 3.191365079365291422e+02 3.197082993197494147e+02 3.202802947846023471e+02 3.208515419501355836e+02 3.214233786848297427e+02 3.219945351474150925e+02 3.225658049886852723e+02 3.231361451247399827e+02 3.237075056689579924e+02 3.242781179138563061e+02 3.248501360544461818e+02 3.254217233560337945e+02 3.259937188208867269e+02 3.265650566893677365e+02 3.271370521542206689e+02 3.277086621315452817e+02 3.282809070295047604e+02 3.288524716553554299e+02 3.294238095238364394e+02 3.299948979592109595e+02 3.305663492063767990e+02 3.311375056689621488e+02 3.317082539682821789e+02 3.322789795918652658e+02 3.328500000000288424e+02 3.334215646258795118e+02 3.339931972789410679e+02 3.345646031746329641e+02 3.351361678004836335e+02 3.357077777778082464e+02 3.362794784580806322e+02 3.368510430839313017e+02 3.374229251700994041e+02 3.379950113379001664e+02 3.385668253968574390e+02 3.391383900227081085e+02 3.397102494331392677e+02 3.402816326530942206e+02 3.408526077097838538e+02 3.414232879818930542e+02 3.419939909297391409e+02 3.425655555555898104e+02 3.431375056689687995e+02 3.437092290249781854e+02 3.442808163265657981e+02 3.448527437642078439e+02 3.454243310657954567e+02 3.459957823129612962e+02 3.465674829932337389e+02 3.471396145125084445e+02 3.477114058957287170e+02 3.482829705215793865e+02 3.488547619047996591e+02 3.494263492063872718e+02 3.499975283447095649e+02 3.505680725623969920e+02 3.511387755102430788e+02 3.517101360544610884e+02 3.522818367347335311e+02 3.528534013605842006e+02 3.534251247165935865e+02 3.539965986394964261e+02 3.545682766440318687e+02 3.551397732426716516e+02 3.557113832199962076e+02 3.562833106576382534e+02 3.568548752834889228e+02 3.574264625850765356e+02 3.579981405896119782e+02 3.585698639456213641e+02 3.591412698413133171e+02 3.597122675737399504e+02 3.602831292517448105e+02 3.608544897959627633e+02 3.614262131519722061e+02 3.619977097506119321e+02 3.625695011338322047e+02 3.631413151927894205e+02 3.637126303855335436e+02 3.642839002268037234e+02 3.648555555556021659e+02 3.654267573696614591e+02 mir_eval-0.8.2/tests/data/beat/output00.json000066400000000000000000000006261475740344600207220ustar00rootroot00000000000000{"F-measure": 0.6216216216216216, "Cemgil": 0.36267669947376407, "Cemgil Best Metric Level": 0.36267669947376407, "Goto": 0.0, "P-score": 0.8281853281853282, "Correct Metric Level Continuous": 0.032818532818532815, "Correct Metric Level Total": 0.65444015444015446, "Any Metric Level Continuous": 0.032818532818532815, "Any Metric Level Total": 0.65444015444015446, "Information gain": 0.20492902479030584}mir_eval-0.8.2/tests/data/beat/output01.json000066400000000000000000000006261475740344600207230ustar00rootroot00000000000000{"F-measure": 0.5714285714285714, "Cemgil": 0.37930967713752983, "Cemgil Best Metric Level": 0.37930967713752983, "Goto": 0.0, "P-score": 0.7786624203821656, "Correct Metric Level Continuous": 0.065286624203821655, "Correct Metric Level Total": 0.59235668789808915, "Any Metric Level Continuous": 0.065286624203821655, "Any Metric Level Total": 0.59235668789808915, "Information gain": 0.18165289235165968}mir_eval-0.8.2/tests/data/beat/output02.json000066400000000000000000000006241475740344600207220ustar00rootroot00000000000000{"F-measure": 0.710691823899371, "Cemgil": 0.5142812021968689, "Cemgil Best Metric Level": 0.5142812021968689, "Goto": 0.0, "P-score": 0.78616352201257866, "Correct Metric Level Continuous": 0.069182389937106917, "Correct Metric Level Total": 0.70230607966457026, "Any Metric Level Continuous": 0.069182389937106917, "Any Metric Level Total": 0.70230607966457026, "Information gain": 0.16915072749280333}mir_eval-0.8.2/tests/data/beat/output03.json000066400000000000000000000006351475740344600207250ustar00rootroot00000000000000{"F-measure": 0.15827338129496404, "Cemgil": 0.10490347511815068, "Cemgil Best Metric Level": 0.20035411158345875, "Goto": 0.0, "P-score": 0.40521327014218012, "Correct Metric Level Continuous": 0.0023696682464454978, "Correct Metric Level Total": 0.0047393364928909956, "Any Metric Level Continuous": 0.003669724770642202, "Any Metric Level Total": 0.012844036697247707, "Information gain": 0.034733860498019208}mir_eval-0.8.2/tests/data/beat/output04.json000066400000000000000000000006271475740344600207270ustar00rootroot00000000000000{"F-measure": 0.5517241379310345, "Cemgil": 0.36213884390750961, "Cemgil Best Metric Level": 0.36213884390750961, "Goto": 0.0, "P-score": 0.80689655172413788, "Correct Metric Level Continuous": 0.043103448275862072, "Correct Metric Level Total": 0.61896551724137927, "Any Metric Level Continuous": 0.043103448275862072, "Any Metric Level Total": 0.61896551724137927, "Information gain": 0.17432052000795428}mir_eval-0.8.2/tests/data/beat/output05.json000066400000000000000000000006241475740344600207250ustar00rootroot00000000000000{"F-measure": 0.2191304347826087, "Cemgil": 0.12313752600283781, "Cemgil Best Metric Level": 0.12313752600283781, "Goto": 0.0, "P-score": 0.6470588235294118, "Correct Metric Level Continuous": 0.02768166089965398, "Correct Metric Level Total": 0.42560553633217996, "Any Metric Level Continuous": 0.02768166089965398, "Any Metric Level Total": 0.42560553633217996, "Information gain": 0.37609621063532095}mir_eval-0.8.2/tests/data/beat/output06.json000066400000000000000000000006301475740344600207230ustar00rootroot00000000000000{"F-measure": 0.38995568685376664, "Cemgil": 0.22357721675815428, "Cemgil Best Metric Level": 0.22357721675815428, "Goto": 0.0, "P-score": 0.74117647058823533, "Correct Metric Level Continuous": 0.041176470588235294, "Correct Metric Level Total": 0.57647058823529407, "Any Metric Level Continuous": 0.041176470588235294, "Any Metric Level Total": 0.57647058823529407, "Information gain": 0.29985845720926313}mir_eval-0.8.2/tests/data/beat/output07.json000066400000000000000000000006301475740344600207240ustar00rootroot00000000000000{"F-measure": 0.41231593038821956, "Cemgil": 0.22720728663021972, "Cemgil Best Metric Level": 0.22720728663021972, "Goto": 0.0, "P-score": 0.89333333333333331, "Correct Metric Level Continuous": 0.090666666666666673, "Correct Metric Level Total": 0.72533333333333339, "Any Metric Level Continuous": 0.090666666666666673, "Any Metric Level Total": 0.72533333333333339, "Information gain": 0.45951853335878939}mir_eval-0.8.2/tests/data/beat/output08.json000066400000000000000000000006301475740344600207250ustar00rootroot00000000000000{"F-measure": 0.17100371747211895, "Cemgil": 0.10601534783891264, "Cemgil Best Metric Level": 0.10601534783891264, "Goto": 0.0, "P-score": 0.64814814814814814, "Correct Metric Level Continuous": 0.022222222222222223, "Correct Metric Level Total": 0.45555555555555555, "Any Metric Level Continuous": 0.022222222222222223, "Any Metric Level Total": 0.45555555555555555, "Information gain": 0.36848147577387486}mir_eval-0.8.2/tests/data/beat/output09.json000066400000000000000000000006211475740344600207260ustar00rootroot00000000000000{"F-measure": 0.9992082343626286, "Cemgil": 0.983071489454861, "Cemgil Best Metric Level": 0.983071489454861, "Goto": 1.0, "P-score": 0.99841772151898733, "Correct Metric Level Continuous": 0.99841772151898733, "Correct Metric Level Total": 0.99841772151898733, "Any Metric Level Continuous": 0.99841772151898733, "Any Metric Level Total": 0.99841772151898733, "Information gain": 0.77527393651396859}mir_eval-0.8.2/tests/data/beat/ref00.txt000066400000000000000000000316201475740344600200020ustar00rootroot000000000000005.980385487528344646e-01 1.067329707070142186e+00 1.573276643990929591e+00 2.059759083819572734e+00 2.532891156462584892e+00 2.997290249433106624e+00 3.461689342403627911e+00 3.926088435374149643e+00 4.406111111111111533e+00 4.916950113378685039e+00 5.381349206349207215e+00 5.892188208616780720e+00 6.310147392290249790e+00 6.728106575963718861e+00 7.146065759637188819e+00 7.656904761904762324e+00 8.121303854875284500e+00 8.632142857142858006e+00 9.096541950113378405e+00 9.560941043083900581e+00 9.932460317460318322e+00 1.039685941043083872e+01 1.081481859410430957e+01 1.127921768707482997e+01 1.174361678004535214e+01 1.220801587301587432e+01 1.271885487528344783e+01 1.318325396825396822e+01 1.360121315192743729e+01 1.406561224489795947e+01 1.448357142857142854e+01 1.494797052154195072e+01 1.541236961451247289e+01 1.587676870748299507e+01 1.634116780045351547e+01 1.680556689342403587e+01 1.722352607709750671e+01 1.768792517006802711e+01 1.815232426303854751e+01 1.861672335600907147e+01 1.903468253968253876e+01 1.954552154195011227e+01 2.000992063492063622e+01 2.042787981859410351e+01 2.089227891156462746e+01 2.131023809523809476e+01 2.172819727891156560e+01 2.219259637188208600e+01 2.270343537414965951e+01 2.316783446712018346e+01 2.363223356009070386e+01 2.409663265306122426e+01 2.451459183673469511e+01 2.497899092970521551e+01 2.544339002267573591e+01 2.590778911564625986e+01 2.632574829931972715e+01 2.683658730158730066e+01 2.725454648526077150e+01 2.771894557823129190e+01 2.818334467120181586e+01 2.864774376417233626e+01 2.911214285714285666e+01 2.957654195011338061e+01 3.008738095238095411e+01 3.059821995464852762e+01 3.101617913832199491e+01 3.143413832199546576e+01 3.185209750566893305e+01 3.227005668934240390e+01 3.278089569160997740e+01 3.329173469387755091e+01 3.375613378684806776e+01 3.422053287981859171e+01 3.468493197278911566e+01 3.514933106575963251e+01 3.561373015873015646e+01 3.607812925170068041e+01 3.654252834467119726e+01 3.696048752834466455e+01 3.742488662131518851e+01 3.788928571428571246e+01 3.835368480725622931e+01 3.881808390022675326e+01 3.928248299319727721e+01 3.974688208616779406e+01 4.016484126984126846e+01 4.062924036281178530e+01 4.109363945578230926e+01 4.155803854875283321e+01 4.206887755102040671e+01 4.248683673469387401e+01 4.290479591836734130e+01 4.336919501133786525e+01 4.383359410430838921e+01 4.429799319727890605e+01 4.476239229024943000e+01 4.527323129251700351e+01 4.573763038548752746e+01 4.620202947845804431e+01 4.666642857142856826e+01 4.713082766439909221e+01 4.759522675736960906e+01 4.805962585034013301e+01 4.852402494331065697e+01 4.903486394557823047e+01 4.949926303854874732e+01 4.996366213151927127e+01 5.038162131519273856e+01 5.084602040816326252e+01 5.126397959183672981e+01 5.172837868480725376e+01 5.219277777777777771e+01 5.270361678004535122e+01 5.316801587301586807e+01 5.363241496598639202e+01 5.409681405895691597e+01 5.456121315192743282e+01 5.497917233560090722e+01 5.539713151927437451e+01 5.586153061224489136e+01 5.632592970521541531e+01 5.674388888888888260e+01 5.725472789115645611e+01 5.771912698412698006e+01 5.813708616780044736e+01 5.860148526077097131e+01 5.901944444444443860e+01 5.953028344671201211e+01 6.004112244897958561e+01 6.045908163265306001e+01 6.092348072562357686e+01 6.138787981859410081e+01 6.180583900226756811e+01 6.227023809523809206e+01 6.273463718820861601e+01 6.324547619047618952e+01 6.375631519274376302e+01 6.417427437641724453e+01 6.468511337868481803e+01 6.510307256235827822e+01 6.561391156462585172e+01 6.603187074829932612e+01 6.649626984126985008e+01 6.696066893424035982e+01 6.737862811791383422e+01 6.784302721088435817e+01 6.830742630385488212e+01 6.877182539682540607e+01 6.923622448979591582e+01 6.970062358276643977e+01 7.016502267573696372e+01 7.062942176870748767e+01 7.109382086167801162e+01 7.151178004535147181e+01 7.197617913832199577e+01 7.244057823129251972e+01 7.285853741496599412e+01 7.336937641723356762e+01 7.383377551020409157e+01 7.429817460317460132e+01 7.471613378684807572e+01 7.518053287981859967e+01 7.564493197278912362e+01 7.610933106575964757e+01 7.657373015873015731e+01 7.703812925170068127e+01 7.745608843537415567e+01 7.787404761904763006e+01 7.833844671201813981e+01 7.880284580498866376e+01 7.926724489795918771e+01 7.973164399092971166e+01 8.019604308390023562e+01 8.061400226757369580e+01 8.107840136054421976e+01 8.154280045351474371e+01 8.196075963718821811e+01 8.242515873015872785e+01 8.288955782312925180e+01 8.335395691609977575e+01 8.381835600907029971e+01 8.423631519274377411e+01 8.470071428571428385e+01 8.511867346938775825e+01 8.558307256235828220e+01 8.604747165532880615e+01 8.651187074829933010e+01 8.692982993197279029e+01 8.744066893424036380e+01 8.785862811791383820e+01 8.827658730158731260e+01 8.874098639455782234e+01 8.920538548752834629e+01 8.971622448979591979e+01 9.013418367346939419e+01 9.059858276643991815e+01 9.106298185941042789e+01 9.152738095238095184e+01 9.199178004535147579e+01 9.240973922902495019e+01 9.292057823129252370e+01 9.338497732426304765e+01 9.384937641723355739e+01 9.431377551020408134e+01 9.473173469387755574e+01 9.519613378684807969e+01 9.566053287981860365e+01 9.612493197278911339e+01 9.663577097505668689e+01 9.710017006802721085e+01 9.756456916099773480e+01 9.807540816326530830e+01 9.849336734693878270e+01 9.895776643990930665e+01 9.937572562358276684e+01 9.984012471655329080e+01 1.003045238095238147e+02 1.007689229024943387e+02 1.012333219954648627e+02 1.017441609977324362e+02 1.022085600907029459e+02 1.026265192743764203e+02 1.030444784580498947e+02 1.035088775510204187e+02 1.039732766439909284e+02 1.044376757369614523e+02 1.049020748299319763e+02 1.053200340136054507e+02 1.057844331065759746e+02 1.062952721088435482e+02 1.067596712018140579e+02 1.071776303854875323e+02 1.076884693877551058e+02 1.081528684807256298e+02 1.085708276643990899e+02 1.090352267573696139e+02 1.095460657596371874e+02 1.100104648526077114e+02 1.104748639455782353e+02 1.109392630385487593e+02 1.114036621315192832e+02 1.118680612244897929e+02 1.123324603174603169e+02 1.128432993197278904e+02 1.133541383219954639e+02 1.137720975056689383e+02 1.141900566893424127e+02 1.146080158730158729e+02 1.150724149659863969e+02 1.155832539682539704e+02 1.160476530612244943e+02 1.165120521541950183e+02 1.169300113378684784e+02 1.174408503401360520e+02 1.179052494331065759e+02 1.183232086167800503e+02 1.188340476190476238e+02 1.192520068027210982e+02 1.197164058956916080e+02 1.201808049886621319e+02 1.206452040816326559e+02 1.211096031746031798e+02 1.215275623582766542e+02 1.219919614512471640e+02 1.225028004535147375e+02 1.229671995464852614e+02 1.234315986394557854e+02 1.238959977324263093e+02 1.243139569160997837e+02 1.248247959183673572e+02 1.252891950113378670e+02 1.258000340136054405e+02 1.263108730158730140e+02 1.267752721088435379e+02 1.272396712018140619e+02 1.277040702947845858e+02 1.281684693877550956e+02 1.285864285714285700e+02 1.290972675736961435e+02 1.295152267573696179e+02 1.299796258503401134e+02 1.304440249433106374e+02 1.309548639455782109e+02 1.314192630385487348e+02 1.318836621315192588e+02 1.323480612244897827e+02 1.328124603174603067e+02 1.333232993197278802e+02 1.337876984126984041e+02 1.342520975056689281e+02 1.347629365079365016e+02 1.352273356009070255e+02 1.356917346938775495e+02 1.362025736961451230e+02 1.366205328798185974e+02 1.370849319727890929e+02 1.375493310657596169e+02 1.380601700680271904e+02 1.385245691609977143e+02 1.390354081632652878e+02 1.394533673469387622e+02 1.399642063492063357e+02 1.404286054421768597e+02 1.408930045351473836e+02 1.413574036281179076e+02 1.418682426303854811e+02 1.423790816326530546e+02 1.428434807256235786e+02 1.433078798185941025e+02 1.437722789115646265e+02 1.441902380952380724e+02 1.446081972789115468e+02 1.450725963718820708e+02 1.455834353741496443e+02 1.460478344671201683e+02 1.465586734693877418e+02 1.470230725623582657e+02 1.475339115646258392e+02 1.479983106575963632e+02 1.484627097505668871e+02 1.489271088435374111e+02 1.493450680272108855e+02 1.498094671201814094e+02 1.503203061224489829e+02 1.507382653061224289e+02 1.512491043083900024e+02 1.517599433106575759e+02 1.521779024943310503e+02 1.526887414965986238e+02 1.531531405895691478e+02 1.536175396825396717e+02 1.541283786848072452e+02 1.545927777777777692e+02 1.550571768707482931e+02 1.555215759637188171e+02 1.559859750566893410e+02 1.564039342403628154e+02 1.568683333333333110e+02 1.573791723356008845e+02 1.577971315192743589e+02 1.582615306122448828e+02 1.587259297052154068e+02 1.591903287981859307e+02 1.596547278911564547e+02 1.601191269841269786e+02 1.605835260770975026e+02 1.610479251700680265e+02 1.615123242630385505e+02 1.619767233560090460e+02 1.624411224489795700e+02 1.629055215419500939e+02 1.633699206349206179e+02 1.638807596371881914e+02 1.643915986394557649e+02 1.648559977324262888e+02 1.653668367346938624e+02 1.658312358276643863e+02 1.662491950113378607e+02 1.667135941043083847e+02 1.672244331065759582e+02 1.677352721088435317e+02 1.682461111111111052e+02 1.687105102040816291e+02 1.691749092970521531e+02 1.696393083900226770e+02 1.701501473922902505e+02 1.706145464852607745e+02 1.710789455782312700e+02 1.715433446712017940e+02 1.720077437641723179e+02 1.724721428571428419e+02 1.729365419501133658e+02 1.734009410430838898e+02 1.739117800453514633e+02 1.743761791383219872e+02 1.748405782312925112e+02 1.753514172335600847e+02 1.758158163265306086e+02 1.762802154195011326e+02 1.767910544217687061e+02 1.772090136054421805e+02 1.776734126984126760e+02 1.781842517006802495e+02 1.786950907029478230e+02 1.791130498866212974e+02 1.796238888888888710e+02 1.801347278911564445e+02 1.805991269841269684e+02 1.810170861678004428e+02 1.814814852607709668e+02 1.819923242630385403e+02 1.824567233560090642e+02 1.829675623582766377e+02 1.834319614512471617e+02 1.838963605442176856e+02 1.843607596371882096e+02 1.848715986394557831e+02 1.853359977324263070e+02 1.857539569160997530e+02 1.862647959183673265e+02 1.867291950113378505e+02 1.872400340136054240e+02 1.877044331065759479e+02 1.881688321995464719e+02 1.885867913832199463e+02 1.890976303854875198e+02 1.895620294784580437e+02 1.900264285714285677e+02 1.905372675736961412e+02 1.910016666666666652e+02 1.914660657596371891e+02 1.919304648526077131e+02 1.923948639455782086e+02 1.928592630385487325e+02 1.933701020408163060e+02 1.938345011337868300e+02 1.942989002267573539e+02 1.948097392290249275e+02 1.952276984126984019e+02 1.956920975056689258e+02 1.961564965986394498e+02 1.966208956916099737e+02 1.970388548752834481e+02 1.975032539682539721e+02 1.980140929705215456e+02 1.984784920634920411e+02 1.989428911564625650e+02 1.994537301587301386e+02 1.999181292517006625e+02 2.003825283446711865e+02 2.008933673469387600e+02 2.014042063492063335e+02 2.018221655328798079e+02 2.022865646258503318e+02 2.027974036281179053e+02 2.032618027210884293e+02 2.037262018140589532e+02 2.041441609977324276e+02 2.046550000000000011e+02 2.051193990929705251e+02 2.055837981859410206e+02 2.060481972789115446e+02 2.064661564625850190e+02 2.069305555555555429e+02 2.073949546485260669e+02 2.078593537414965908e+02 2.083701927437641643e+02 2.088810317460317378e+02 2.093454308390022618e+02 2.097633900226757362e+02 2.102277891156462601e+02 2.107386281179138336e+02 2.112494671201814072e+02 2.117138662131519311e+02 2.121782653061224266e+02 2.126426643990929506e+02 2.131535034013605241e+02 2.136643424036280976e+02 2.141287414965986216e+02 2.145931405895691455e+02 2.151039795918367190e+02 2.155219387755101934e+02 2.160327777777777669e+02 2.164971768707482909e+02 2.169615759637188148e+02 2.174259750566893388e+02 2.178439342403628132e+02 2.183547732426303867e+02 2.188191723356009106e+02 2.192835714285714062e+02 2.197479705215419301e+02 2.202123696145124541e+02 2.206767687074829780e+02 2.210947278911564524e+02 2.216055668934240259e+02 2.220699659863945499e+02 2.225808049886621234e+02 2.230452040816326473e+02 2.235096031746031713e+02 2.239740022675736952e+02 2.244384013605442192e+02 2.248563605442176652e+02 2.253207596371881891e+02 2.258315986394557626e+02 2.262495578231292370e+02 2.267139569160997610e+02 2.271783560090702849e+02 2.276891950113378584e+02 2.281535941043083824e+02 2.286179931972789063e+02 2.290359523809523807e+02 2.295467913832199542e+02 2.300576303854875277e+02 2.304755895691609737e+02 2.309399886621314977e+02 2.314043877551020216e+02 2.319152267573695951e+02 2.323796258503401191e+02 2.328440249433106430e+02 2.333084240362811670e+02 2.337728231292516909e+02 2.342372222222222149e+02 2.347016213151927388e+02 2.351660204081632628e+02 2.356304195011337868e+02 2.360948185941043107e+02 2.365592176870748062e+02 2.370236167800453302e+02 2.374880158730158541e+02 2.379524149659863781e+02 2.384632539682539516e+02 2.389740929705215251e+02 2.393920521541949995e+02 2.399493310657596226e+02 2.404137301587301465e+02 2.408316893424036209e+02 2.412496485260770953e+02 2.416676077097505697e+02 2.421784467120181432e+02 2.426428458049886387e+02 2.431536848072562123e+02 2.436645238095237858e+02 2.441753628117913593e+02 2.446862018140589328e+02 2.451970408163265063e+02 2.456614399092970302e+02 2.461258390022675542e+02 mir_eval-0.8.2/tests/data/beat/ref01.txt000066400000000000000000000370031475740344600200040ustar00rootroot000000000000004.587188208616780338e-01 9.695578231292516502e-01 1.480396825396825378e+00 1.944795918367347110e+00 2.409195011337868397e+00 2.827154195011337912e+00 3.337993197278911417e+00 3.802392290249433149e+00 4.220351473922902663e+00 4.731190476190477057e+00 5.195589569160998344e+00 5.706428571428571850e+00 6.217267573696145355e+00 6.635226757369615314e+00 7.146065759637188819e+00 7.656904761904762324e+00 8.121303854875284500e+00 8.585702947845804900e+00 9.050102040816327076e+00 9.514501133786849252e+00 1.002534013605442276e+01 1.048973922902494316e+01 1.100057823129251666e+01 1.141853741496598751e+01 1.192937641723356101e+01 1.234733560090703008e+01 1.285817460317460359e+01 1.332257369614512577e+01 1.378697278911564617e+01 1.429781179138321967e+01 1.471577097505669052e+01 1.518017006802721092e+01 1.569100907029478442e+01 1.620184807256235970e+01 1.666624716553288010e+01 1.713064625850340050e+01 1.764148526077097401e+01 1.805944444444444485e+01 1.857028344671201836e+01 1.908112244897959187e+01 1.954552154195011227e+01 1.996348072562358311e+01 2.047431972789115662e+01 2.089227891156462746e+01 2.135667800453514786e+01 2.182107709750566826e+01 2.228547619047619222e+01 2.279631519274376572e+01 2.326071428571428612e+01 2.372511337868480652e+01 2.418951247165533047e+01 2.465391156462585087e+01 2.516475056689342438e+01 2.558270975056689522e+01 2.604710884353741562e+01 2.651150793650793602e+01 2.697590702947845998e+01 2.744030612244898037e+01 2.790470521541950077e+01 2.832266439909297162e+01 2.878706349206349202e+01 2.920502267573696287e+01 2.966942176870748327e+01 3.018026077097505677e+01 3.064465986394557717e+01 3.106261904761904802e+01 3.152701814058956842e+01 3.199141723356008882e+01 3.245581632653060922e+01 3.292021541950113317e+01 3.333817460317460046e+01 3.384901360544217397e+01 3.431341269841269792e+01 3.473137188208616521e+01 3.514933106575963251e+01 3.561373015873015646e+01 3.603168934240362375e+01 3.654252834467119726e+01 3.700692743764172121e+01 3.747132653061224516e+01 3.793572562358276201e+01 3.840012471655328596e+01 3.886452380952380992e+01 3.932892290249432676e+01 3.979332199546485072e+01 4.021128117913831801e+01 4.067568027210884196e+01 4.114007936507935881e+01 4.165091836734693231e+01 4.206887755102040671e+01 4.253327664399092356e+01 4.304411564625849707e+01 4.346207482993197146e+01 4.392647392290248831e+01 4.443731292517006182e+01 4.485527210884353622e+01 4.536611111111110972e+01 4.583051020408162657e+01 4.629490929705215052e+01 4.675930839002267447e+01 4.717726757369614177e+01 4.759522675736960906e+01 4.810606575963718257e+01 4.857046485260770652e+01 4.903486394557823047e+01 4.949926303854874732e+01 4.996366213151927127e+01 5.047450113378684478e+01 5.093890022675736873e+01 5.140329931972788557e+01 5.186769841269840953e+01 5.233209750566893348e+01 5.279649659863945033e+01 5.330733560090702383e+01 5.377173469387754778e+01 5.418969387755101508e+01 5.465409297052153903e+01 5.511849206349206298e+01 5.558289115646257983e+01 5.604729024943310378e+01 5.651168934240362773e+01 5.697608843537414458e+01 5.748692743764171809e+01 5.795132653061224204e+01 5.836928571428570933e+01 5.883368480725623328e+01 5.925164399092970058e+01 5.976248299319727408e+01 6.027332199546484759e+01 6.073772108843537154e+01 6.120212018140589549e+01 6.162007936507936279e+01 6.213091836734693629e+01 6.254887755102040359e+01 6.301327664399092754e+01 6.347767573696145149e+01 6.394207482993197544e+01 6.440647392290249229e+01 6.487087301587301624e+01 6.533527210884354020e+01 6.584611111111111370e+01 6.626407029478458810e+01 6.677490929705216161e+01 6.728574829931973511e+01 6.775014739229025906e+01 6.826098639455783257e+01 6.872538548752834231e+01 6.918978458049886626e+01 6.970062358276643977e+01 7.011858276643991417e+01 7.062942176870748767e+01 7.109382086167801162e+01 7.160465986394558513e+01 7.206905895691610908e+01 7.253345804988661882e+01 7.299785714285714278e+01 7.350869614512471628e+01 7.397309523809524023e+01 7.443749433106576419e+01 7.490189342403628814e+01 7.536629251700681209e+01 7.583069160997732183e+01 7.634153061224489534e+01 7.680592970521541929e+01 7.727032879818594324e+01 7.773472789115646719e+01 7.819912698412699115e+01 7.861708616780045134e+01 7.908148526077097529e+01 7.954588435374149924e+01 8.001028344671202319e+01 8.042824263038549759e+01 8.089264172335600733e+01 8.140348072562358084e+01 8.186787981859410479e+01 8.233227891156462874e+01 8.279667800453515270e+01 8.335395691609977575e+01 8.377191609977325015e+01 8.428275510204082366e+01 8.474715419501134761e+01 8.516511337868480780e+01 8.567595238095238130e+01 8.609391156462585570e+01 8.655831065759637966e+01 8.702270975056690361e+01 8.748710884353741335e+01 8.795150793650793730e+01 8.841590702947846125e+01 8.883386621315193565e+01 8.934470521541950916e+01 8.976266439909296935e+01 9.022706349206349330e+01 9.073790249433106680e+01 9.115586167800454120e+01 9.162026077097506516e+01 9.203821995464852534e+01 9.254905895691609885e+01 9.296701814058957325e+01 9.343141723356009720e+01 9.389581632653062115e+01 9.436021541950113090e+01 9.487105442176870440e+01 9.528901360544217880e+01 9.575341269841270275e+01 9.621781179138322670e+01 9.668221088435375066e+01 9.719304988662132416e+01 9.765744897959183390e+01 9.812184807256235786e+01 9.863268707482993136e+01 9.905064625850340576e+01 9.951504535147392971e+01 9.993300453514738990e+01 1.004438435374149634e+02 1.008618027210884378e+02 1.013726417233560113e+02 1.018370408163265353e+02 1.023478798185941088e+02 1.028122789115646327e+02 1.032766780045351567e+02 1.036946371882086169e+02 1.041590362811791408e+02 1.046698752834467143e+02 1.050878344671201887e+02 1.055986734693877622e+02 1.060630725623582862e+02 1.065274716553287959e+02 1.069918707482993199e+02 1.074562698412698438e+02 1.079671088435374173e+02 1.083850680272108917e+02 1.088494671201814157e+02 1.093138662131519254e+02 1.097782653061224494e+02 1.102426643990929733e+02 1.107070634920634973e+02 1.111714625850340212e+02 1.116358616780045452e+02 1.121002607709750549e+02 1.125646598639455789e+02 1.129826190476190533e+02 1.134470181405895772e+02 1.139114172335601012e+02 1.143293764172335614e+02 1.147937755102040853e+02 1.152581746031746093e+02 1.157225736961451332e+02 1.161869727891156572e+02 1.166513718820861669e+02 1.170693310657596413e+02 1.175337301587301653e+02 1.179981292517006892e+02 1.185089682539682627e+02 1.189733673469387725e+02 1.193913265306122469e+02 1.199021655328798204e+02 1.203665646258503443e+02 1.208309637188208683e+02 1.212953628117913922e+02 1.217597619047619020e+02 1.222241609977324259e+02 1.226885600907029499e+02 1.231529591836734738e+02 1.236173582766439978e+02 1.240817573696145217e+02 1.244997165532879819e+02 1.250105555555555554e+02 1.254285147392290298e+02 1.258929138321995538e+02 1.263573129251700777e+02 1.268681519274376512e+02 1.273325510204081610e+02 1.277969501133786849e+02 1.282613492063491947e+02 1.287257482993197186e+02 1.291901473922902426e+02 1.296081065759637170e+02 1.300725056689342409e+02 1.305369047619047649e+02 1.310013038548752604e+02 1.314657029478457844e+02 1.319301020408163083e+02 1.323945011337868323e+02 1.328124603174603067e+02 1.332768594104308306e+02 1.337412585034013546e+02 1.342056575963718785e+02 1.346700566893424025e+02 1.350880158730158769e+02 1.355988548752834504e+02 1.360632539682539459e+02 1.365276530612244699e+02 1.369920521541949938e+02 1.374564512471655178e+02 1.379208503401360417e+02 1.383388095238095161e+02 1.388032086167800401e+02 1.392676077097505640e+02 1.397320068027210880e+02 1.401964058956916119e+02 1.406608049886621075e+02 1.411716439909296810e+02 1.415896031746031554e+02 1.421004421768707289e+02 1.425184013605442033e+02 1.429828004535147272e+02 1.434471995464852512e+02 1.439115986394557751e+02 1.443759977324262991e+02 1.447939569160997735e+02 1.452583560090702974e+02 1.457227551020407930e+02 1.461871541950113169e+02 1.466515532879818409e+02 1.470695124716553153e+02 1.475339115646258392e+02 1.479983106575963632e+02 1.484627097505668871e+02 1.488806689342403615e+02 1.493450680272108855e+02 1.497630272108843315e+02 1.502274263038548554e+02 1.506918253968253794e+02 1.511562244897959033e+02 1.516206235827664273e+02 1.520385827664399017e+02 1.524565419501133761e+02 1.529673809523809496e+02 1.533389002267573460e+02 1.538032993197278699e+02 1.542676984126983939e+02 1.546856575963718683e+02 1.551500566893423922e+02 1.555680158730158666e+02 1.560324149659863906e+02 1.564968140589569146e+02 1.569612131519274385e+02 1.573791723356008845e+02 1.577971315192743589e+02 1.582615306122448828e+02 1.586794897959183572e+02 1.591438888888888812e+02 1.595618480725623556e+02 1.600262471655328795e+02 1.604442063492063255e+02 1.609550453514738990e+02 1.614194444444444230e+02 1.618374036281178974e+02 1.623018027210884213e+02 1.627662018140589453e+02 1.632306009070294692e+02 1.636949999999999932e+02 1.641593990929705171e+02 1.646237981859410411e+02 1.650881972789115650e+02 1.655990362811791385e+02 1.660169954648525845e+02 1.664813945578231085e+02 1.668993537414965829e+02 1.673173129251700573e+02 1.677817120181405812e+02 1.682461111111111052e+02 1.686640702947845796e+02 1.691284693877551035e+02 1.696393083900226770e+02 1.701037074829932010e+02 1.705681065759636965e+02 1.710325056689342205e+02 1.714969047619047444e+02 1.719613038548752684e+02 1.724721428571428419e+02 1.728901020408163163e+02 1.734009410430838898e+02 1.738653401360544137e+02 1.742832993197278881e+02 1.747476984126984121e+02 1.752120975056689360e+02 1.756764965986394316e+02 1.760944557823129060e+02 1.765588548752834299e+02 1.770232539682539539e+02 1.774876530612244778e+02 1.779520521541950018e+02 1.784164512471655257e+02 1.788344104308390001e+02 1.792523696145124745e+02 1.796703287981859205e+02 1.801347278911564445e+02 1.806455668934240180e+02 1.810635260770974924e+02 1.814814852607709668e+02 1.819458843537414907e+02 1.824102834467120147e+02 1.828282426303854891e+02 1.832462018140589350e+02 1.837106009070294590e+02 1.841749999999999829e+02 1.846393990929705069e+02 1.851037981859410309e+02 1.855681972789115548e+02 1.859861564625850292e+02 1.864505555555555532e+02 1.868685147392290276e+02 1.873793537414966011e+02 1.878437528344670966e+02 1.883545918367346701e+02 1.887725510204081445e+02 1.892369501133786684e+02 1.897013492063491924e+02 1.901657482993197164e+02 1.905837074829931908e+02 1.910481065759637147e+02 1.914660657596371891e+02 1.919304648526077131e+02 1.923484240362811590e+02 1.928592630385487325e+02 1.933236621315192565e+02 1.937880612244897804e+02 1.942060204081632548e+02 1.947168594104308283e+02 1.951348185941043027e+02 1.955527777777777771e+02 1.959707369614512231e+02 1.963886961451246975e+02 1.968530952380952215e+02 1.972710544217686959e+02 1.976890136054421703e+02 1.981998526077097438e+02 1.986642517006802677e+02 1.991286507936507917e+02 1.995930498866213156e+02 2.000574489795918396e+02 2.005218480725623351e+02 2.009862471655328591e+02 2.014042063492063335e+02 2.018221655328798079e+02 2.022865646258503318e+02 2.027509637188208558e+02 2.032153628117913797e+02 2.036797619047619037e+02 2.040977210884353781e+02 2.045156802721088241e+02 2.049336394557822985e+02 2.053980385487528224e+02 2.058159977324262968e+02 2.063268367346938703e+02 2.067912358276643943e+02 2.072091950113378687e+02 2.076735941043083926e+02 2.080915532879818386e+02 2.085559523809523625e+02 2.089739115646258369e+02 2.094383106575963609e+02 2.099491496598639344e+02 2.104135487528344584e+02 2.108779478458049823e+02 2.112959070294784567e+02 2.117603061224489807e+02 2.121782653061224266e+02 2.125962244897959010e+02 2.130606235827664250e+02 2.135250226757369489e+02 2.139894217687074729e+02 2.144538208616779968e+02 2.148717800453514712e+02 2.153826190476190447e+02 2.158005782312925191e+02 2.162649773242630147e+02 2.167293764172335386e+02 2.171937755102040626e+02 2.176581746031745865e+02 2.181225736961451105e+02 2.185869727891156344e+02 2.190513718820861584e+02 2.194693310657596328e+02 2.199801700680272063e+02 2.203981292517006807e+02 2.208625283446712046e+02 2.213269274376417002e+02 2.217913265306122241e+02 2.222557256235827481e+02 2.227201247165532720e+02 2.231380839002267464e+02 2.236024829931972704e+02 2.241133219954648439e+02 2.244848412698412687e+02 2.249492403628117927e+02 2.253671995464852387e+02 2.257851587301587131e+02 2.262031179138321875e+02 2.266210770975056619e+02 2.270390362811791363e+02 2.275034353741496602e+02 2.279678344671201842e+02 2.284322335600906797e+02 2.288966326530612037e+02 2.293145918367346781e+02 2.297789909297052020e+02 2.301969501133786764e+02 2.306613492063492004e+02 2.311721882086167739e+02 2.316365873015872978e+02 2.321009863945578218e+02 2.325653854875283457e+02 2.329833446712017917e+02 2.334013038548752661e+02 2.338192630385487405e+02 2.342836621315192644e+02 2.347945011337868380e+02 2.352589002267573619e+02 2.356768594104308363e+02 2.361412585034013603e+02 2.365592176870748062e+02 2.369771768707482806e+02 2.373951360544217550e+02 2.378595351473922790e+02 2.383239342403628029e+02 2.387883333333333269e+02 2.392062925170068013e+02 2.397171315192743748e+02 2.401350907029478492e+02 2.405994897959183447e+02 2.410174489795918191e+02 2.414818480725623431e+02 2.419462471655328670e+02 2.424106462585033910e+02 2.429214852607709645e+02 2.433394444444444389e+02 2.438038435374149628e+02 2.442218027210884372e+02 2.446862018140589328e+02 2.451041609977324072e+02 2.455685600907029311e+02 2.460329591836734551e+02 2.464973582766439790e+02 2.469617573696145030e+02 2.474261564625850269e+02 2.478905555555555509e+02 2.483085147392290253e+02 2.488193537414965988e+02 2.492837528344671227e+02 2.497481519274376183e+02 2.502125510204081422e+02 2.506769501133786662e+02 2.511413492063491901e+02 2.516057482993197141e+02 2.520237074829931885e+02 2.524416666666666629e+02 2.529060657596371868e+02 2.533704648526077108e+02 2.537884240362811568e+02 2.542528231292516807e+02 2.547172222222222047e+02 2.552280612244897782e+02 2.556924603174603021e+02 2.561104195011338334e+02 2.565748185941043289e+02 2.570392176870748244e+02 2.574571768707482988e+02 2.578751360544217732e+02 2.583395351473923256e+02 2.588039342403628211e+02 2.592218934240362955e+02 2.596862925170068479e+02 2.601971315192744214e+02 2.606150907029478390e+02 2.610330498866213134e+02 2.615438888888888869e+02 2.620082879818594392e+02 2.624262471655329136e+02 2.628442063492063880e+02 2.633086054421768836e+02 2.637730045351474359e+02 2.642374036281179315e+02 2.647018027210884270e+02 2.651662018140589794e+02 2.656306009070294749e+02 2.660950000000000273e+02 2.665129591836735017e+02 2.669773582766439972e+02 2.674417573696145496e+02 2.679061564625850451e+02 2.683705555555555975e+02 2.689278344671201921e+02 2.692993537414965886e+02 2.697173129251700630e+02 2.701352721088435374e+02 2.705532312925170118e+02 2.710640702947845853e+02 2.714820294784580597e+02 2.719464285714286120e+02 2.724108276643991076e+02 2.728287868480725820e+02 2.732931859410430775e+02 2.737111451247165519e+02 2.741755442176871043e+02 2.746399433106575998e+02 2.751507823129251733e+02 2.755687414965986477e+02 2.760795804988662212e+02 2.765439795918367736e+02 2.769619387755102480e+02 2.773798979591836655e+02 2.778442970521542179e+02 2.783551360544217914e+02 2.788195351473922869e+02 2.792839342403628393e+02 2.797483333333333348e+02 2.802127324263038872e+02 2.806306916099773616e+02 2.810950907029478572e+02 2.815594897959184095e+02 2.820238888888889051e+02 2.824882879818594006e+02 2.829991269841269741e+02 2.834635260770975265e+02 2.839279251700680220e+02 2.843923242630385744e+02 2.848567233560090699e+02 2.853211224489796223e+02 2.857855215419501178e+02 2.862499206349206702e+02 2.867143197278911657e+02 2.871787188208617181e+02 2.876895578231292916e+02 2.881539569160997871e+02 2.886183560090703395e+02 2.891756349206349341e+02 2.896400340136054865e+02 2.901508730158730600e+02 2.906152721088435555e+02 2.910796712018140511e+02 2.915905102040816246e+02 2.920084693877550990e+02 mir_eval-0.8.2/tests/data/beat/ref02.txt000066400000000000000000000274531475740344600200150ustar00rootroot000000000000003.041167758511563068e+00 3.434229024943310726e+00 3.852188208616780241e+00 4.223707482993197537e+00 4.595226757369615278e+00 4.966746031746032131e+00 5.384705215419501201e+00 5.756224489795918942e+00 6.127743764172335794e+00 6.499263038548753535e+00 6.917222222222222605e+00 7.288741496598639458e+00 7.706700680272109416e+00 8.078219954648526269e+00 8.449739229024944009e+00 8.821258503401361750e+00 9.192777777777777715e+00 9.564297052154195455e+00 9.982256235827664526e+00 1.035377551020408227e+01 1.077173469387755134e+01 1.114325396825396908e+01 1.156121315192743815e+01 1.193273242630385589e+01 1.230425170068027185e+01 1.272221088435374270e+01 1.314017006802721177e+01 1.351168934240362773e+01 1.388320861678004547e+01 1.430116780045351454e+01 1.471912698412698539e+01 1.509064625850340136e+01 1.550860544217687043e+01 1.588012471655328994e+01 1.629808390022675724e+01 1.671604308390022808e+01 1.713400226757369538e+01 1.750552154195011312e+01 1.792348072562358396e+01 1.829500000000000171e+01 1.871295918367346900e+01 1.908447845804988674e+01 1.945599773242630448e+01 1.987395691609977533e+01 2.029191609977324262e+01 2.070987528344671347e+01 2.108139455782313121e+01 2.149935374149659850e+01 2.187087301587301624e+01 2.224239229024943398e+01 2.266035147392290128e+01 2.303187074829931902e+01 2.349626984126984297e+01 2.386778911564625716e+01 2.428574829931972801e+01 2.465726757369614575e+01 2.502878684807256349e+01 2.544674603174603078e+01 2.586470521541950163e+01 2.628266439909297247e+01 2.670062358276643977e+01 2.711858276643991061e+01 2.753654195011337791e+01 2.790806122448979565e+01 2.832602040816326650e+01 2.869753968253968424e+01 2.911549886621315153e+01 2.953345804988662238e+01 2.990497732426304012e+01 3.032293650793650741e+01 3.074089569160997826e+01 3.111241496598639600e+01 3.153037414965986329e+01 3.194833333333333414e+01 3.236629251700679788e+01 3.273781179138321562e+01 3.315577097505668291e+01 3.352729024943310066e+01 3.394524943310657505e+01 3.436320861678004235e+01 3.473472789115646009e+01 3.515268707482992738e+01 3.552420634920634512e+01 3.594216553287981242e+01 3.636012471655328682e+01 3.673164399092970456e+01 3.714960317460317185e+01 3.756756235827663915e+01 3.798552154195011354e+01 3.840348072562358084e+01 3.877499999999999858e+01 3.919295918367346587e+01 3.956447845804988361e+01 3.993599773242630135e+01 4.035395691609976865e+01 4.077191609977324305e+01 4.114343537414965368e+01 4.160783446712017764e+01 4.207223356009070159e+01 4.249019274376416888e+01 4.290815192743763618e+01 4.332611111111111057e+01 4.369763038548752832e+01 4.411558956916099561e+01 4.448710884353741335e+01 4.490506802721088064e+01 4.532302721088434794e+01 4.574098639455782234e+01 4.615894557823128963e+01 4.653046485260770737e+01 4.694842403628117466e+01 4.731994331065759241e+01 4.773790249433105970e+01 4.815586167800453410e+01 4.857382086167800139e+01 4.899178004535146869e+01 4.940973922902494309e+01 4.978125850340136083e+01 5.019921768707482812e+01 5.061717687074829541e+01 5.103513605442176271e+01 5.145309523809523711e+01 5.187105442176870440e+01 5.224257369614512214e+01 5.266053287981858944e+01 5.303205215419500718e+01 5.349645124716553113e+01 5.386797052154194887e+01 5.433236961451246572e+01 5.470388888888888346e+01 5.512184807256235786e+01 5.553980725623582515e+01 5.595776643990929244e+01 5.642216553287981640e+01 5.684012471655328369e+01 5.721164399092970143e+01 5.762960317460316872e+01 5.804756235827664312e+01 5.846552154195011042e+01 5.888348072562357771e+01 5.930143990929705211e+01 5.967295918367346275e+01 6.009091836734693715e+01 6.046243764172335489e+01 6.088039682539682218e+01 6.129835600907028947e+01 6.166987528344670721e+01 6.213427437641723117e+01 6.255223356009069846e+01 6.297019274376416575e+01 6.334171201814058350e+01 6.375967120181405789e+01 6.408475056689343319e+01 6.450270975056689338e+01 6.492066893424036778e+01 6.538506802721089173e+01 6.580302721088435192e+01 6.617454648526077676e+01 6.659250566893425116e+01 6.701046485260771135e+01 6.738198412698413620e+01 6.779994331065759638e+01 6.821790249433107078e+01 6.863586167800454518e+01 6.905382086167800537e+01 6.942534013605443022e+01 6.979685941043084085e+01 7.021481859410431525e+01 7.063277777777777544e+01 7.105073696145124984e+01 7.142225623582767469e+01 7.188665532879818443e+01 7.230461451247165883e+01 7.272257369614513323e+01 7.314053287981859341e+01 7.355849206349206781e+01 7.397645124716554221e+01 7.439441043083900240e+01 7.481236961451247680e+01 7.518388888888888744e+01 7.555540816326531228e+01 7.601980725623583623e+01 7.639132653061224687e+01 7.680928571428572127e+01 7.722724489795918146e+01 7.764520408163265586e+01 7.806316326530613026e+01 7.848112244897959044e+01 7.889908163265306484e+01 7.927060090702947548e+01 7.968856009070294988e+01 8.010651927437642428e+01 8.047803854875283491e+01 8.089599773242630931e+01 8.131395691609978371e+01 8.173191609977324390e+01 8.210343537414966875e+01 8.256783446712017849e+01 8.298579365079365289e+01 8.335731292517007773e+01 8.377527210884353792e+01 8.414679138321996277e+01 8.456475056689342296e+01 8.498270975056689736e+01 8.540066893424037175e+01 8.581862811791383194e+01 8.623658730158730634e+01 8.660810657596371698e+01 8.702606575963719138e+01 8.739758503401361622e+01 8.781554421768707641e+01 8.823350340136055081e+01 8.860502267573696145e+01 8.906942176870748540e+01 8.944094104308391024e+01 8.990534013605441999e+01 9.027685941043084483e+01 9.064837868480725547e+01 9.101989795918368031e+01 9.143785714285714050e+01 9.185581632653061490e+01 9.222733560090703975e+01 9.264529478458049994e+01 9.301681405895692478e+01 9.348121315192743452e+01 9.385273242630385937e+01 9.422425170068027001e+01 9.464221088435374440e+01 9.501373015873016925e+01 9.543168934240362944e+01 9.584964852607710384e+01 9.622116780045351447e+01 9.663912698412698887e+01 9.701064625850339951e+01 9.742860544217687391e+01 9.784656462585034831e+01 9.821808390022675894e+01 9.863604308390023334e+01 9.905400226757369353e+01 9.942552154195011838e+01 9.984348072562359278e+01 1.002614399092970530e+02 1.006793990929705274e+02 1.010973582766440018e+02 1.015153174603174620e+02 1.019332766439909363e+02 1.023512358276643965e+02 1.027691950113378709e+02 1.031407142857142958e+02 1.035586734693877560e+02 1.039766326530612304e+02 1.043945918367347048e+02 1.047661111111111154e+02 1.051840702947845898e+02 1.056020294784580500e+02 1.060199886621315244e+02 1.064379478458049988e+02 1.068094671201814094e+02 1.072274263038548838e+02 1.075989455782312945e+02 1.079704648526077193e+02 1.083419841269841299e+02 1.087599433106576043e+02 1.091779024943310645e+02 1.095958616780045389e+02 1.100138208616780133e+02 1.103853401360544240e+02 1.108032993197278984e+02 1.112212585034013586e+02 1.116392176870748330e+02 1.120571768707483074e+02 1.124286961451247180e+02 1.128466553287981924e+02 1.132646145124716526e+02 1.136825736961451270e+02 1.140540929705215518e+02 1.144256122448979625e+02 1.148435714285714369e+02 1.152615306122448970e+02 1.156794897959183714e+02 1.160510090702947821e+02 1.164689682539682565e+02 1.168869274376417309e+02 1.173048866213151911e+02 1.176764058956916159e+02 1.180943650793650903e+02 1.184658843537415009e+02 1.188838435374149753e+02 1.193018027210884355e+02 1.197197619047619099e+02 1.201377210884353843e+02 1.205092403628117950e+02 1.209271995464852694e+02 1.212987188208616800e+02 1.217166780045351544e+02 1.221346371882086146e+02 1.225061564625850394e+02 1.229241156462585138e+02 1.233420748299319740e+02 1.237600340136054484e+02 1.241779931972789086e+02 1.245959523809523830e+02 1.249674716553288079e+02 1.253854308390022680e+02 1.257569501133786929e+02 1.261749092970521531e+02 1.265464285714285779e+02 1.269643877551020381e+02 1.273823469387755125e+02 1.278003061224489869e+02 1.281718253968253975e+02 1.285897845804988435e+02 1.290077437641723179e+02 1.293792630385487428e+02 1.297972222222222172e+02 1.302151814058956916e+02 1.306795804988662155e+02 1.310975396825396615e+02 1.315154988662131359e+02 1.318870181405895607e+02 1.323049773242630351e+02 1.327229365079365095e+02 1.331408956916099555e+02 1.335124149659863804e+02 1.339768140589569043e+02 1.343947732426303787e+02 1.348127324263038531e+02 1.352306916099773275e+02 1.356022108843537239e+02 1.360201700680271983e+02 1.364381292517006727e+02 1.368096485260770976e+02 1.372740476190476215e+02 1.376455668934240180e+02 1.380635260770974924e+02 1.384814852607709668e+02 1.388530045351473916e+02 1.392709637188208376e+02 1.396889229024943120e+02 1.401068820861677864e+02 1.405248412698412608e+02 1.408963605442176856e+02 1.413607596371882096e+02 1.417787188208616556e+02 1.421966780045351300e+02 1.425681972789115548e+02 1.430325963718820788e+02 1.434041156462585036e+02 1.438220748299319496e+02 1.441935941043083744e+02 1.446579931972788984e+02 1.450295124716553232e+02 1.454474716553287976e+02 1.458654308390022436e+02 1.462833900226757180e+02 1.466549092970521428e+02 1.470728684807256172e+02 1.474908276643990916e+02 1.479087868480725660e+02 1.482803061224489625e+02 1.486518253968253873e+02 1.490697845804988617e+02 1.494877437641723361e+02 1.499057029478457821e+02 1.502772222222222069e+02 1.506951814058956813e+02 1.511131405895691557e+02 1.514846598639455806e+02 1.519954988662131541e+02 1.523670181405895505e+02 1.527849773242630249e+02 1.532029365079364993e+02 1.536208956916099737e+02 1.540388548752834481e+02 1.544568140589568941e+02 1.548747732426303685e+02 1.552927324263038429e+02 1.557106916099773173e+02 1.560822108843537421e+02 1.565001700680271881e+02 1.569181292517006625e+02 1.572896485260770874e+02 1.577540476190476113e+02 1.582184467120181353e+02 1.585899659863945601e+02 1.590543650793650556e+02 1.594258843537414805e+02 1.598438435374149549e+02 1.602618027210884293e+02 1.606797619047619037e+02 1.610977210884353781e+02 1.614692403628117745e+02 1.619336394557822985e+02 1.623515986394557729e+02 1.627695578231292473e+02 1.631875170068027217e+02 1.636054761904761676e+02 1.640234353741496420e+02 1.644413945578231164e+02 1.648129138321995413e+02 1.652308730158730157e+02 1.656488321995464617e+02 1.660667913832199361e+02 1.664847505668934105e+02 1.669027097505668848e+02 1.673206689342403592e+02 1.677386281179138336e+02 1.681565873015872796e+02 1.685745464852607540e+02 1.689925056689342284e+02 1.694104648526077028e+02 1.698748639455782268e+02 1.702463832199546516e+02 1.706643424036280976e+02 1.711287414965986216e+02 1.715002607709750464e+02 1.719182199546485208e+02 1.723826190476190447e+02 1.728470181405895687e+02 1.732649773242630147e+02 1.736829365079364891e+02 1.740544557823129139e+02 1.745188548752834379e+02 1.749368140589569123e+02 1.753547732426303867e+02 1.757727324263038327e+02 1.761906916099773071e+02 1.766550907029478310e+02 1.770730498866213054e+02 1.774910090702947798e+02 1.778625283446712046e+02 1.782804875283446506e+02 1.787448866213151746e+02 1.791628458049886490e+02 1.795808049886621234e+02 1.799987641723355978e+02 1.803702834467119942e+02 1.807882426303854686e+02 1.812062018140589430e+02 1.816706009070294670e+02 1.820421201814058918e+02 1.824600793650793662e+02 1.829244784580498902e+02 1.833424376417233361e+02 1.837139569160997610e+02 1.841319160997732354e+02 1.845498752834467098e+02 1.849678344671201842e+02 1.853857936507936301e+02 1.858037528344671045e+02 1.861752721088435294e+02 1.865932312925170038e+02 1.870111904761904782e+02 1.874291496598639242e+02 1.878006689342403490e+02 1.882650680272108730e+02 1.886830272108843474e+02 1.891009863945578218e+02 1.895189455782312962e+02 1.899369047619047421e+02 1.903548639455782165e+02 1.907728231292516909e+02 1.911907823129251653e+02 1.915623015873015902e+02 1.919802607709750362e+02 1.923982199546485106e+02 1.928626190476190345e+02 1.933270181405895585e+02 1.936985374149659833e+02 1.941629365079365073e+02 1.946273356009070312e+02 1.950452947845804772e+02 1.955561337868480507e+02 1.960205328798185747e+02 1.964849319727890986e+02 1.969028911564625730e+02 1.973208503401360474e+02 1.977852494331065714e+02 1.981567687074829962e+02 1.986211678004534917e+02 1.990391269841269661e+02 1.995035260770974901e+02 1.998750453514739149e+02 mir_eval-0.8.2/tests/data/beat/ref03.txt000066400000000000000000000155301475740344600200070ustar00rootroot000000000000005.718592400307472845e-01 1.248197278911564512e+00 1.898356009070294892e+00 2.594954648526077268e+00 3.313383751582585024e+00 4.034591836734694681e+00 4.731190476190477057e+00 5.520668934240362979e+00 6.263707482993197573e+00 6.960306122448979949e+00 7.796224489795918977e+00 8.539263038548753570e+00 9.282301587301587276e+00 1.002534013605442276e+01 1.081481859410430957e+01 1.155785714285714327e+01 1.234733560090703008e+01 1.309037414965986379e+01 1.387985260770975060e+01 1.457645124716553298e+01 1.536592970521541979e+01 1.610896825396825349e+01 1.694488662131519163e+01 1.773436507936508022e+01 1.852384353741496525e+01 1.922044217687074763e+01 2.005636054421768577e+01 2.089227891156462746e+01 2.168175736961451250e+01 2.247123582766440109e+01 2.330715419501133923e+01 2.409663265306122426e+01 2.493255102040816240e+01 2.567558956916099788e+01 2.651150793650793602e+01 2.730098639455782461e+01 2.809046485260770964e+01 2.887994331065759823e+01 2.966942176870748327e+01 3.045890022675736830e+01 3.124837868480725689e+01 3.203785714285714192e+01 3.278089569160997740e+01 3.361681405895691199e+01 3.440629251700679703e+01 3.519577097505668917e+01 3.603168934240362375e+01 3.691404761904761500e+01 3.765708616780045048e+01 3.835368480725622931e+01 3.918960317460317100e+01 3.997908163265305603e+01 4.076856009070294817e+01 4.151159863945577655e+01 4.234751700680271824e+01 4.313699546485260328e+01 4.392647392290248831e+01 4.480883219954647956e+01 4.555187074829931504e+01 4.634134920634920007e+01 4.713082766439909221e+01 4.787386621315192770e+01 4.875622448979591184e+01 4.949926303854874732e+01 5.028874149659863946e+01 5.107821995464852449e+01 5.196057823129251574e+01 5.275005668934240077e+01 5.349309523809523625e+01 5.432901360544217084e+01 5.525781179138321875e+01 5.604729024943310378e+01 5.674388888888888260e+01 5.748692743764171809e+01 5.832284580498865978e+01 5.915876417233559437e+01 6.004112244897958561e+01 6.092348072562357686e+01 6.171295918367346900e+01 6.254887755102040359e+01 6.338479591836734528e+01 6.426715419501134363e+01 6.510307256235827822e+01 6.603187074829932612e+01 6.654270975056689963e+01 6.728574829931973511e+01 6.812166666666666970e+01 6.891114512471655473e+01 6.974706349206348932e+01 7.058298185941043812e+01 7.137246031746032315e+01 7.211549886621315864e+01 7.295141723356009322e+01 7.369445578231292870e+01 7.457681405895692706e+01 7.541273242630386164e+01 7.620221088435374668e+01 7.689880952380953261e+01 7.773472789115646719e+01 7.852420634920635223e+01 7.936012471655328682e+01 8.019604308390023562e+01 8.098552154195012065e+01 8.177500000000000568e+01 8.256447845804989072e+01 8.335395691609977575e+01 8.418987528344671034e+01 8.502579365079365914e+01 8.572239229024943086e+01 8.651187074829933010e+01 8.734778911564626469e+01 8.818370748299319928e+01 8.892674603174603476e+01 8.971622448979591979e+01 9.055214285714285438e+01 9.134162131519275363e+01 9.213109977324263866e+01 9.296701814058957325e+01 9.371005668934240873e+01 9.445309523809524421e+01 9.519613378684807969e+01 9.603205215419501428e+01 9.686797052154194887e+01 9.765744897959183390e+01 9.840048752834466939e+01 9.923640589569161818e+01 1.000723242630385528e+02 1.008618027210884378e+02 1.016512811791383228e+02 1.024407596371882079e+02 1.031837981859410434e+02 1.040197165532879922e+02 1.047163151927437639e+02 1.056451133786848118e+02 1.063881519274376473e+02 1.072705102040816314e+02 1.080135487528344669e+02 1.088959070294784652e+02 1.096853854875283503e+02 1.104748639455782353e+02 1.113572222222222194e+02 1.121467006802721187e+02 1.129361791383220037e+02 1.137720975056689383e+02 1.146080158730158729e+02 1.153046145124716588e+02 1.161405328798185934e+02 1.169764512471655422e+02 1.178123696145124768e+02 1.186018480725623618e+02 1.193913265306122469e+02 1.201808049886621319e+02 1.210167233560090807e+02 1.218062018140589657e+02 1.225956802721088508e+02 1.233387188208616863e+02 1.241746371882086208e+02 1.249641156462585059e+02 1.258000340136054405e+02 1.265895124716553397e+02 1.273789909297052247e+02 1.282149092970521451e+02 1.289579478458049664e+02 1.297938662131519152e+02 1.305369047619047649e+02 1.312799433106575862e+02 1.320229818594104074e+02 1.327660204081632571e+02 1.335090589569160784e+02 1.343449773242630272e+02 1.351344557823129264e+02 1.358774943310657477e+02 1.367134126984126965e+02 1.375493310657596169e+02 1.383388095238095161e+02 1.391282879818593869e+02 1.398713265306122366e+02 1.407536848072562350e+02 1.415431632653061058e+02 1.422862018140589555e+02 1.430292403628117768e+02 1.438651587301587256e+02 1.446081972789115468e+02 1.454441156462584956e+02 1.462335941043083665e+02 1.470695124716553153e+02 1.478589909297052145e+02 1.486020294784580358e+02 1.493915079365079350e+02 1.502274263038548554e+02 1.510169047619047547e+02 1.518063832199546255e+02 1.525494217687074752e+02 1.534317800453514735e+02 1.541748185941042948e+02 1.549178571428571445e+02 1.557073356009070153e+02 1.565896938775510137e+02 1.573327324263038349e+02 1.580293310657596351e+02 1.587723696145124563e+02 1.595618480725623556e+02 1.603513265306122264e+02 1.610943650793650761e+02 1.618838435374149469e+02 1.626733219954648462e+02 1.634163605442176674e+02 1.642522789115646162e+02 1.649953174603174375e+02 1.657847959183673368e+02 1.665278344671201580e+02 1.673173129251700573e+02 1.681067913832199565e+02 1.690355895691609760e+02 1.697786281179138257e+02 1.705681065759636965e+02 1.713111451247165462e+02 1.721470634920634950e+02 1.729365419501133658e+02 1.737260204081632651e+02 1.744226190476190368e+02 1.753049773242630351e+02 1.760480158730158564e+02 1.769768140589569043e+02 1.777198526077097540e+02 1.785093310657596248e+02 1.792523696145124745e+02 1.800882879818593949e+02 1.808777664399092941e+02 1.816672448979591650e+02 1.825031632653061138e+02 1.833390816326530626e+02 1.840821201814058838e+02 1.848715986394557831e+02 1.856610770975056539e+02 1.864505555555555532e+02 1.871471541950113249e+02 1.879366326530612241e+02 1.888189909297051940e+02 1.895620294784580437e+02 1.903979478458049925e+02 1.911874263038548634e+02 1.918840249433106351e+02 1.927199433106575839e+02 1.935094217687074831e+02 1.943453401360544035e+02 1.950883786848072532e+02 1.958778571428571240e+02 1.966673356009070233e+02 1.975032539682539721e+02 1.982462925170067933e+02 1.990357709750566926e+02 1.997788095238095138e+02 2.006147278911564626e+02 2.013577664399092839e+02 2.021472448979591832e+02 2.028902834467120044e+02 2.037262018140589532e+02 2.045156802721088241e+02 2.053515986394557729e+02 2.060017573696144950e+02 2.068841156462584934e+02 2.076271541950113146e+02 2.084630725623582634e+02 2.092525510204081627e+02 2.100420294784580335e+02 2.108779478458049823e+02 2.116674263038548531e+02 2.125033446712018019e+02 2.133392630385487507e+02 2.142216213151927207e+02 2.151504195011337686e+02 2.163578571428571422e+02 2.174259750566893388e+02 2.184476530612244858e+02 2.194228911564625832e+02 2.202588095238095036e+02 2.211876077097505515e+02 2.220699659863945499e+02 2.229058843537414987e+02 mir_eval-0.8.2/tests/data/beat/ref04.txt000066400000000000000000000347201475740344600200120ustar00rootroot000000000000002.729591836734693855e-01 6.444784580498865711e-01 1.015997732426303868e+00 1.387517006802721165e+00 1.805476190476190457e+00 2.223435374149659971e+00 2.641394557823129041e+00 3.059353741496598555e+00 3.477312925170068070e+00 3.941712018140589802e+00 4.406111111111111533e+00 4.824070294784580604e+00 5.242029478458050562e+00 5.706428571428571850e+00 6.124387755102040920e+00 6.542346938775510878e+00 6.960306122448979949e+00 7.424705215419501236e+00 7.889104308390022524e+00 8.260623582766440265e+00 8.725022675736962441e+00 9.142981859410431511e+00 9.560941043083900581e+00 9.978900226757369651e+00 1.044329931972789183e+01 1.086125850340136090e+01 1.132565759637188307e+01 1.179005668934240347e+01 1.220801587301587432e+01 1.262597505668934339e+01 1.304393424036281246e+01 1.346189342403628153e+01 1.387985260770975060e+01 1.434425170068027278e+01 1.480865079365079495e+01 1.522660997732426402e+01 1.564456916099773309e+01 1.606252834467120394e+01 1.648048752834467123e+01 1.689844671201814208e+01 1.726996598639455982e+01 1.773436507936508022e+01 1.819876417233560062e+01 1.861672335600907147e+01 1.912756235827664497e+01 1.954552154195011227e+01 2.000992063492063622e+01 2.042787981859410351e+01 2.089227891156462746e+01 2.131023809523809476e+01 2.177463718820861871e+01 2.219259637188208600e+01 2.265699546485260640e+01 2.307495464852607725e+01 2.349291383219954810e+01 2.391087301587301539e+01 2.437527210884353934e+01 2.483967120181405974e+01 2.530407029478458014e+01 2.572202947845805099e+01 2.613998866213151828e+01 2.660438775510204223e+01 2.706878684807256263e+01 2.748674603174603348e+01 2.790470521541950077e+01 2.832266439909297162e+01 2.883350340136054513e+01 2.920502267573696287e+01 2.971586167800453637e+01 3.013382086167800367e+01 3.059821995464852762e+01 3.101617913832199491e+01 3.143413832199546576e+01 3.194497732426303926e+01 3.236293650793650301e+01 3.282733560090702696e+01 3.329173469387755091e+01 3.370969387755101820e+01 3.417409297052154216e+01 3.459205215419500945e+01 3.510289115646258296e+01 3.556729024943310691e+01 3.598524943310657420e+01 3.644964852607709105e+01 3.686760770975056545e+01 3.737844671201813895e+01 3.779640589569160625e+01 3.826080498866213020e+01 3.867876417233559749e+01 3.918960317460317100e+01 3.960756235827663829e+01 4.007196145124716224e+01 4.053636054421768620e+01 4.100075963718820304e+01 4.146515873015872700e+01 4.192955782312925095e+01 4.239395691609976780e+01 4.285835600907029175e+01 4.327631519274375904e+01 4.374071428571428299e+01 4.420511337868480695e+01 4.466951247165532379e+01 4.513391156462584775e+01 4.555187074829931504e+01 4.606270975056688854e+01 4.648066893424036294e+01 4.694506802721087979e+01 4.740946712018140374e+01 4.782742630385487104e+01 4.833826530612244454e+01 4.880266439909296849e+01 4.922062358276643579e+01 4.968502267573695974e+01 5.014942176870747659e+01 5.056738095238095099e+01 5.103178004535146783e+01 5.149617913832199179e+01 5.196057823129251574e+01 5.242497732426303259e+01 5.284293650793650698e+01 5.326089569160997428e+01 5.372529478458049823e+01 5.418969387755101508e+01 5.465409297052153903e+01 5.511849206349206298e+01 5.558289115646257983e+01 5.600085034013605423e+01 5.646524943310657108e+01 5.692964852607709503e+01 5.739404761904761898e+01 5.781200680272108627e+01 5.827640589569161023e+01 5.874080498866212707e+01 5.920520408163265103e+01 5.962316326530611832e+01 6.004112244897958561e+01 6.045908163265306001e+01 6.092348072562357686e+01 6.143431972789115036e+01 6.185227891156462476e+01 6.231667800453514161e+01 6.278107709750566556e+01 6.324547619047618952e+01 6.366343537414965681e+01 6.412783446712018076e+01 6.459223356009070471e+01 6.505663265306122867e+01 6.552103174603175262e+01 6.593899092970521281e+01 6.640339002267573676e+01 6.691422902494331026e+01 6.737862811791383422e+01 6.793590702947845728e+01 6.844674603174603078e+01 6.886470521541950518e+01 6.932910430839002913e+01 6.979350340136055308e+01 7.025790249433106283e+01 7.067586167800453723e+01 7.114026077097506118e+01 7.160465986394558513e+01 7.206905895691610908e+01 7.253345804988661882e+01 7.290497732426304367e+01 7.336937641723356762e+01 7.378733560090702781e+01 7.429817460317460132e+01 7.476257369614512527e+01 7.518053287981859967e+01 7.559849206349207407e+01 7.601645124716553426e+01 7.648085034013605821e+01 7.694524943310658216e+01 7.740964852607710611e+01 7.782760770975056630e+01 7.829200680272109025e+01 7.870996598639456465e+01 7.917436507936508860e+01 7.959232426303854879e+01 8.005672335600907275e+01 8.047468253968254714e+01 8.089264172335600733e+01 8.131060090702948173e+01 8.182143990929705524e+01 8.223939909297052964e+01 8.265735827664398983e+01 8.312175736961451378e+01 8.358615646258503773e+01 8.405055555555556168e+01 8.446851473922902187e+01 8.493291383219954582e+01 8.539731292517006978e+01 8.581527210884354417e+01 8.623323129251700436e+01 8.669763038548752832e+01 8.711558956916100271e+01 8.762642857142857622e+01 8.804438775510205062e+01 8.850878684807256036e+01 8.888030612244898521e+01 8.934470521541950916e+01 8.976266439909296935e+01 9.018062358276644375e+01 9.064502267573696770e+01 9.110942176870749165e+01 9.152738095238095184e+01 9.199178004535147579e+01 9.245617913832199974e+01 9.287413832199547414e+01 9.329209750566893433e+01 9.375649659863945828e+01 9.422089569160998224e+01 9.463885487528345664e+01 9.510325396825396638e+01 9.556765306122449033e+01 9.598561224489796473e+01 9.640357142857143913e+01 9.686797052154194887e+01 9.733236961451247282e+01 9.775032879818594722e+01 9.821472789115647117e+01 9.867912698412699513e+01 9.909708616780045531e+01 9.951504535147392971e+01 9.997944444444445367e+01 1.004438435374149634e+02 1.008618027210884378e+02 1.012797619047619122e+02 1.016977210884353724e+02 1.021156802721088468e+02 1.026265192743764203e+02 1.029980385487528451e+02 1.034624376417233549e+02 1.039268367346938788e+02 1.043447959183673532e+02 1.047627551020408134e+02 1.052735941043083869e+02 1.056915532879818613e+02 1.061559523809523853e+02 1.065739115646258597e+02 1.070383106575963694e+02 1.075027097505668934e+02 1.079206689342403678e+02 1.083850680272108917e+02 1.088030272108843519e+02 1.092209863945578263e+02 1.096853854875283503e+02 1.101033446712018247e+02 1.105677437641723344e+02 1.109392630385487593e+02 1.114501020408163328e+02 1.119145011337868567e+02 1.123789002267573807e+02 1.127968594104308409e+02 1.132148185941043153e+02 1.136792176870748392e+02 1.140971768707482994e+02 1.145151360544217738e+02 1.149795351473922977e+02 1.154439342403628217e+02 1.159083333333333314e+02 1.163262925170068058e+02 1.167442517006802802e+02 1.172086507936508042e+02 1.176730498866213139e+02 1.180910090702947883e+02 1.185554081632653123e+02 1.189733673469387725e+02 1.194377664399092964e+02 1.198557256235827708e+02 1.202736848072562452e+02 1.207380839002267550e+02 1.212024829931972789e+02 1.216204421768707533e+02 1.220384013605442277e+02 1.225028004535147375e+02 1.229207596371882119e+02 1.233851587301587358e+02 1.238031179138322102e+02 1.242675170068027199e+02 1.246854761904761943e+02 1.251034353741496687e+02 1.255678344671201785e+02 1.260322335600907024e+02 1.264966326530612264e+02 1.269610317460317503e+02 1.273325510204081610e+02 1.277969501133786849e+02 1.282613492063491947e+02 1.287257482993197186e+02 1.291437074829931930e+02 1.296081065759637170e+02 1.300260657596371914e+02 1.304440249433106374e+02 1.309084240362811613e+02 1.313263832199546357e+02 1.317907823129251597e+02 1.322551814058956836e+02 1.327195804988662076e+02 1.331375396825396820e+02 1.336019387755102059e+02 1.340663378684807014e+02 1.345307369614512254e+02 1.349486961451246998e+02 1.353666553287981742e+02 1.358310544217686981e+02 1.362954535147392221e+02 1.367134126984126965e+02 1.371778117913832205e+02 1.375957709750566664e+02 1.380601700680271904e+02 1.384781292517006648e+02 1.389425283446711887e+02 1.394069274376417127e+02 1.398248866213151871e+02 1.402892857142857110e+02 1.407536848072562350e+02 1.412645238095238085e+02 1.416824829931972545e+02 1.420540022675736793e+02 1.425184013605442033e+02 1.429828004535147272e+02 1.434007596371882016e+02 1.438187188208616760e+02 1.442831179138322000e+02 1.447475170068027239e+02 1.452119160997732195e+02 1.456763151927437434e+02 1.461407142857142674e+02 1.465586734693877418e+02 1.470230725623582657e+02 1.474410317460317401e+02 1.479054308390022641e+02 1.483698299319727880e+02 1.488342290249433120e+02 1.492521882086167579e+02 1.497165873015872819e+02 1.501345464852607563e+02 1.505525056689342307e+02 1.510169047619047547e+02 1.514348639455782290e+02 1.518992630385487530e+02 1.523636621315192770e+02 1.527816213151927229e+02 1.532460204081632469e+02 1.537104195011337708e+02 1.540819387755101957e+02 1.545463378684807196e+02 1.550107369614512436e+02 1.554286961451247180e+02 1.558930952380952419e+02 1.563110544217686879e+02 1.567754535147392119e+02 1.571934126984126863e+02 1.576578117913832102e+02 1.581222108843537342e+02 1.585401700680272086e+02 1.590045691609977325e+02 1.594225283446711785e+02 1.598404875283446529e+02 1.603513265306122264e+02 1.607692857142857008e+02 1.611872448979591752e+02 1.616516439909296992e+02 1.621160430839002231e+02 1.625804421768707471e+02 1.629984013605442215e+02 1.634163605442176674e+02 1.638807596371881914e+02 1.643451587301587153e+02 1.647631179138321897e+02 1.651810770975056641e+02 1.656454761904761881e+02 1.661098752834467120e+02 1.665278344671201580e+02 1.669922335600906820e+02 1.674101927437641564e+02 1.678745918367346803e+02 1.682925510204081547e+02 1.687569501133786787e+02 1.691749092970521531e+02 1.696393083900226770e+02 1.700572675736961230e+02 1.705216666666666470e+02 1.709396258503401214e+02 1.714040249433106453e+02 1.718684240362811693e+02 1.722863832199546437e+02 1.727507823129251676e+02 1.731687414965986420e+02 1.736331405895691375e+02 1.740975396825396615e+02 1.745154988662131359e+02 1.749334580498866103e+02 1.753514172335600847e+02 1.758158163265306086e+02 1.762337755102040830e+02 1.766981746031746070e+02 1.771625736961451025e+02 1.775805328798185769e+02 1.779984920634920513e+02 1.784628911564625753e+02 1.789272902494330992e+02 1.793452494331065736e+02 1.798096485260770976e+02 1.802740476190476215e+02 1.807384467120181171e+02 1.811564058956915915e+02 1.815743650793650659e+02 1.819923242630385403e+02 1.825031632653061138e+02 1.828746825396825386e+02 1.833390816326530626e+02 1.837570408163265085e+02 1.842214399092970325e+02 1.846858390022675565e+02 1.851037981859410309e+02 1.855681972789115548e+02 1.860325963718820788e+02 1.864505555555555532e+02 1.869149546485260771e+02 1.873329138321995231e+02 1.877973129251700470e+02 1.882617120181405710e+02 1.886796712018140454e+02 1.890976303854875198e+02 1.895620294784580437e+02 1.900264285714285677e+02 1.904908276643990916e+02 1.909087868480725660e+02 1.913267460317460120e+02 1.917911451247165360e+02 1.922555442176870599e+02 1.926735034013605343e+02 1.931843424036281078e+02 1.935558616780045327e+02 1.939738208616780071e+02 1.943917800453514531e+02 1.948561791383219770e+02 1.952276984126984019e+02 1.956920975056689258e+02 1.961564965986394498e+02 1.965744557823129242e+02 1.970388548752834481e+02 1.975032539682539721e+02 1.980140929705215456e+02 1.984320521541949915e+02 1.988964512471655155e+02 1.993144104308389899e+02 1.997788095238095138e+02 2.001967687074829882e+02 2.006611678004535122e+02 2.010791269841269866e+02 2.015435260770974821e+02 2.019614852607709565e+02 2.024258843537414805e+02 2.028438435374149549e+02 2.033082426303854788e+02 2.037262018140589532e+02 2.041906009070294772e+02 2.046085600907029516e+02 2.050729591836734471e+02 2.054909183673469215e+02 2.059088775510203959e+02 2.063268367346938703e+02 2.067912358276643943e+02 2.072091950113378687e+02 2.076735941043083926e+02 2.080915532879818386e+02 2.085095124716553130e+02 2.089274716553287874e+02 2.093918707482993113e+02 2.098098299319727857e+02 2.102277891156462601e+02 2.106457482993197061e+02 2.111101473922902301e+02 2.115281065759637045e+02 2.119925056689342284e+02 2.124569047619047524e+02 2.128748639455782268e+02 2.132928231292517012e+02 2.137107823129251472e+02 2.141751814058956711e+02 2.146395804988661951e+02 2.150575396825396695e+02 2.155219387755101934e+02 2.159863378684807174e+02 2.163578571428571422e+02 2.167758163265305882e+02 2.172866553287981617e+02 2.177046145124716361e+02 2.181225736961451105e+02 2.185405328798185849e+02 2.190049319727891088e+02 2.194228911564625832e+02 2.198408503401360576e+02 2.202588095238095036e+02 2.206767687074829780e+02 2.210947278911564524e+02 2.215591269841269764e+02 2.220235260770975003e+02 2.224879251700680243e+02 2.229058843537414987e+02 2.233238435374149446e+02 2.237882426303854686e+02 2.242526417233559926e+02 2.246706009070294670e+02 2.251349999999999909e+02 2.255993990929705149e+02 2.260173582766439893e+02 2.264817573696145132e+02 2.268997165532879592e+02 2.273176757369614336e+02 2.277820748299319575e+02 2.282000340136054319e+02 2.286644331065759559e+02 2.291288321995464798e+02 2.295467913832199542e+02 2.300111904761904782e+02 2.304291496598639242e+02 2.308935487528344481e+02 2.313579478458049721e+02 2.317759070294784465e+02 2.322403061224489704e+02 2.326582653061224448e+02 2.331226643990929688e+02 2.334941836734693652e+02 2.339585827664398892e+02 2.344229818594104131e+02 2.348873809523809371e+02 2.353517800453514610e+02 2.358161791383219850e+02 2.362341383219954594e+02 2.366520975056689338e+02 2.371164965986394577e+02 2.375344557823129037e+02 2.379988548752834276e+02 2.384168140589569020e+02 2.389276530612244756e+02 2.393920521541949995e+02 2.398100113378684739e+02 2.402744104308389979e+02 2.407388095238095218e+02 2.411567687074829962e+02 2.416211678004534917e+02 2.420391269841269661e+02 2.425035260770974901e+02 2.429679251700680140e+02 2.433858843537414884e+02 2.438502834467120124e+02 2.443146825396825363e+02 2.447326417233560107e+02 2.451970408163265063e+02 2.456614399092970302e+02 2.460793990929705046e+02 2.465437981859410286e+02 2.469617573696145030e+02 2.473797165532879774e+02 2.478905555555555509e+02 2.483549546485260748e+02 2.487729138321995492e+02 2.492373129251700448e+02 2.496552721088435192e+02 2.501196712018140431e+02 2.505840702947845671e+02 2.510484693877550910e+02 2.514664285714285654e+02 2.518843877551020398e+02 2.523487868480725638e+02 2.528131859410430877e+02 2.532311451247165337e+02 2.536491043083900081e+02 2.541599433106575816e+02 2.545779024943310560e+02 2.549958616780045304e+02 2.554602607709750544e+02 2.559246598639455499e+02 2.563426190476190527e+02 2.567605782312925271e+02 2.571320975056689804e+02 2.575500566893423979e+02 2.580144557823129503e+02 2.584788548752834458e+02 2.588968140589569202e+02 2.593612131519274726e+02 2.597791723356009470e+02 2.602435714285714425e+02 2.606615306122449169e+02 2.611259297052154125e+02 2.615438888888888869e+02 2.619154081632653401e+02 2.623333673469388145e+02 mir_eval-0.8.2/tests/data/beat/ref05.txt000066400000000000000000000164321475740344600200130ustar00rootroot000000000000003.678897818412698584e-01 8.766780045351474371e-01 1.394420947301587166e+00 1.916587089269841115e+00 2.521825117460317234e+00 2.966473922902494120e+00 3.570192743764172505e+00 4.127471655328798228e+00 4.731190476190477057e+00 5.242029478458050562e+00 5.799308390022676285e+00 6.356587301587302008e+00 6.867426303854875513e+00 7.378265306122449019e+00 7.935544217687075630e+00 8.492823129251700465e+00 9.003662131519273970e+00 9.560941043083900581e+00 1.007178004535147409e+01 1.062905895691610070e+01 1.113989795918367420e+01 1.169717687074829904e+01 1.220801587301587432e+01 1.276529478458049915e+01 1.327613378684807266e+01 1.383341269841269927e+01 1.439069160997732411e+01 1.494797052154195072e+01 1.545880952380952422e+01 1.601608843537415083e+01 1.657336734693877744e+01 1.713064625850340050e+01 1.768792517006802711e+01 1.819876417233560062e+01 1.875604308390022723e+01 1.931332199546485384e+01 1.991704081632653001e+01 2.047431972789115662e+01 2.098515873015873012e+01 2.149599773242630363e+01 2.205327664399093024e+01 2.256411564625850374e+01 2.315761795579123827e+01 2.370671335183441286e+01 2.428239229024943313e+01 2.483967120181405974e+01 2.535051020408163325e+01 2.590778911564625986e+01 2.646506802721088647e+01 2.702234693877550953e+01 2.757962585034013614e+01 2.809046485260770964e+01 2.864774376417233626e+01 2.920502267573696287e+01 2.976230158730158948e+01 3.031958049886621254e+01 3.087685941043083915e+01 3.138769841269841265e+01 3.194497732426303926e+01 3.254869614512471543e+01 3.305953514739228893e+01 3.361681405895691199e+01 3.417409297052154216e+01 3.473137188208616521e+01 3.524221088435373872e+01 3.579948979591836178e+01 3.635676870748299194e+01 3.686760770975056545e+01 3.737844671201813895e+01 3.788928571428571246e+01 3.844656462585033552e+01 3.895740362811790902e+01 3.951468253968253919e+01 4.002552154195011269e+01 4.062924036281178530e+01 4.118651927437641547e+01 4.169735827664398897e+01 4.225463718820861203e+01 4.281191609977324219e+01 4.336919501133786525e+01 4.392647392290248831e+01 4.448375283446711848e+01 4.499459183673469198e+01 4.555187074829931504e+01 4.610914965986394520e+01 4.661998866213151871e+01 4.713082766439909221e+01 4.764166666666666572e+01 4.824538548752833833e+01 4.875622448979591184e+01 4.931350340136054200e+01 4.987078231292516506e+01 5.042806122448979522e+01 5.093890022675736873e+01 5.149617913832199179e+01 5.200701814058956529e+01 5.256429705215418835e+01 5.316801587301586807e+01 5.367885487528344157e+01 5.423613378684807174e+01 5.474697278911564524e+01 5.525781179138321875e+01 5.581509070294784181e+01 5.637236961451247197e+01 5.692964852607709503e+01 5.748692743764171809e+01 5.804420634920634825e+01 5.860148526077097131e+01 5.915876417233559437e+01 5.971604308390022453e+01 6.027332199546484759e+01 6.083060090702947775e+01 6.134143990929705126e+01 6.185227891156462476e+01 6.240955782312924782e+01 6.296683673469387088e+01 6.352411564625850104e+01 6.403495464852608166e+01 6.454579365079365516e+01 6.510307256235827822e+01 6.566035147392290128e+01 6.617119047619047478e+01 6.672846938775511205e+01 6.723930839002268556e+01 6.779658730158730862e+01 6.835386621315193167e+01 6.891114512471655473e+01 6.942198412698412824e+01 6.997926303854875130e+01 7.049010204081632480e+01 7.104738095238096207e+01 7.155821995464853558e+01 7.211549886621315864e+01 7.262633786848073214e+01 7.318361678004535520e+01 7.364801587301587915e+01 7.415885487528345266e+01 7.471613378684807572e+01 7.527341269841269877e+01 7.583069160997732183e+01 7.634153061224489534e+01 7.689880952380953261e+01 7.745608843537415567e+01 7.801336734693877872e+01 7.861708616780045134e+01 7.912792517006802484e+01 7.968520408163266211e+01 8.024248299319728517e+01 8.075332199546485867e+01 8.131060090702948173e+01 8.186787981859410479e+01 8.237871882086167830e+01 8.293599773242630135e+01 8.349327664399093862e+01 8.405055555555556168e+01 8.460783446712018474e+01 8.511867346938775825e+01 8.567595238095238130e+01 8.623323129251700436e+01 8.679051020408164163e+01 8.730134920634921514e+01 8.785862811791383820e+01 8.846234693877551081e+01 8.901962585034013387e+01 8.957690476190477114e+01 9.013418367346939419e+01 9.069146258503401725e+01 9.124874149659864031e+01 9.175958049886621382e+01 9.227041950113378732e+01 9.287413832199547414e+01 9.343141723356009720e+01 9.394225623582767071e+01 9.449953514739229377e+01 9.505681405895691682e+01 9.561409297052153988e+01 9.612493197278911339e+01 9.668221088435375066e+01 9.728592970521542327e+01 9.784320861678004633e+01 9.835404761904761983e+01 9.895776643990930665e+01 9.946860544217688016e+01 1.000258843537415032e+02 1.005831632653061263e+02 1.011868820861677989e+02 1.017441609977324362e+02 1.023014399092970592e+02 1.028122789115646327e+02 1.033231179138322062e+02 1.038803968253968293e+02 1.043912358276644028e+02 1.049485147392290258e+02 1.055057936507936489e+02 1.060630725623582862e+02 1.065739115646258597e+02 1.072240702947845818e+02 1.078277891156462687e+02 1.083386281179138422e+02 1.088494671201814157e+02 1.094531859410430883e+02 1.100104648526077114e+02 1.105213038548752849e+02 1.110785827664399079e+02 1.116358616780045452e+02 1.121467006802721187e+02 1.127039795918367417e+02 1.132148185941043153e+02 1.137720975056689383e+02 1.143758163265306109e+02 1.149330952380952482e+02 1.154903741496598713e+02 1.160012131519274448e+02 1.165120521541950183e+02 1.170693310657596413e+02 1.176266099773242644e+02 1.181374489795918379e+02 1.186482879818594114e+02 1.192055668934240344e+02 1.197628458049886717e+02 1.203201247165532948e+02 1.208774036281179178e+02 1.214346825396825409e+02 1.219455215419501144e+02 1.225028004535147375e+02 1.230600793650793747e+02 1.236173582766439978e+02 1.241746371882086208e+02 1.246854761904761943e+02 1.252427551020408174e+02 1.257535941043083909e+02 1.263108730158730140e+02 1.268681519274376512e+02 1.273789909297052247e+02 1.279362698412698336e+02 1.284471088435373929e+02 1.289579478458049664e+02 1.295152267573696179e+02 1.300725056689342409e+02 1.306297845804988640e+02 1.311406235827664375e+02 1.316514625850340110e+02 1.323016213151927332e+02 1.328124603174603067e+02 1.333697392290249297e+02 1.338805782312925032e+02 1.344842970521541758e+02 1.349951360544217493e+02 1.355059750566893229e+02 1.360632539682539459e+02 1.366205328798185974e+02 1.371313718820861709e+02 1.376886507936507940e+02 1.381994897959183675e+02 1.387567687074829905e+02 1.393140476190476136e+02 1.398713265306122366e+02 1.403821655328798101e+02 1.409394444444444332e+02 1.414967233560090563e+02 1.420540022675736793e+02 1.426112811791383024e+02 1.431221201814058759e+02 1.436329591836734494e+02 1.441902380952380724e+02 1.447475170068027239e+02 1.452583560090702974e+02 1.457691950113378709e+02 1.463264739229024940e+02 1.468837528344671171e+02 1.473945918367346906e+02 1.479518707482993136e+02 1.485555895691609862e+02 1.491128684807256093e+02 1.496701473922902323e+02 1.501809863945578059e+02 1.507847052154194785e+02 1.513884240362811795e+02 1.519457029478458026e+02 1.524565419501133761e+02 1.530138208616779991e+02 1.535710997732426222e+02 1.541283786848072452e+02 1.546392176870748187e+02 1.551964965986394418e+02 1.557537755102040649e+02 1.563110544217686879e+02 1.568218934240362614e+02 1.574256122448979625e+02 1.579364512471655360e+02 1.584472902494331095e+02 1.589581292517006830e+02 1.595154081632653060e+02 1.601191269841269786e+02 1.606764058956916017e+02 1.612801247165532743e+02 1.617909637188208478e+02 1.623018027210884213e+02 mir_eval-0.8.2/tests/data/beat/ref06.txt000066400000000000000000000207741475740344600200200ustar00rootroot000000000000005.051587301587301404e-01 1.015997732426303868e+00 1.526836734693877595e+00 2.176995464852607753e+00 2.734274376417233476e+00 3.337993197278911417e+00 3.941712018140589802e+00 4.498990929705215969e+00 5.102709750566893909e+00 5.706428571428571850e+00 6.263707482993197573e+00 6.774546485260771078e+00 7.331825396825397689e+00 7.842664399092971195e+00 8.353503401360544700e+00 8.864342403628118205e+00 9.375181405895691711e+00 9.886020408163265216e+00 1.035041950113378739e+01 1.090769841269841400e+01 1.141853741496598751e+01 1.197581632653061234e+01 1.248665532879818585e+01 1.304393424036281246e+01 1.350833333333333464e+01 1.401917233560090814e+01 1.453001133786848165e+01 1.508729024943310648e+01 1.559812925170067999e+01 1.610896825396825349e+01 1.661980725623582700e+01 1.717708616780045361e+01 1.768792517006802711e+01 1.819876417233560062e+01 1.866316326530612457e+01 1.917400226757369808e+01 1.968484126984127158e+01 2.019568027210884509e+01 2.070651927437641859e+01 2.121735827664399210e+01 2.172819727891156560e+01 2.228547619047619222e+01 2.274987528344671261e+01 2.326071428571428612e+01 2.377155328798185963e+01 2.428239229024943313e+01 2.474679138321995353e+01 2.530407029478458014e+01 2.581490929705215365e+01 2.632574829931972715e+01 2.679014739229025110e+01 2.734742630385487416e+01 2.790470521541950077e+01 2.836910430839002473e+01 2.892638321995464779e+01 2.948366213151927440e+01 2.999450113378684790e+01 3.055178004535147451e+01 3.106261904761904802e+01 3.161989795918367463e+01 3.213073696145124103e+01 3.268801587301587119e+01 3.319885487528344470e+01 3.370969387755101820e+01 3.426697278911564126e+01 3.477781179138321477e+01 3.528865079365078827e+01 3.575304988662131223e+01 3.631032879818593528e+01 3.682116780045350879e+01 3.728556689342403274e+01 3.779640589569160625e+01 3.830724489795917975e+01 3.881808390022675326e+01 3.937536281179138342e+01 3.988620181405895693e+01 4.039704081632653043e+01 4.090787981859410394e+01 4.146515873015872700e+01 4.197599773242630050e+01 4.248683673469387401e+01 4.299767573696144751e+01 4.346207482993197146e+01 4.397291383219954497e+01 4.448375283446711848e+01 4.499459183673469198e+01 4.550543083900226549e+01 4.606270975056688854e+01 4.657354875283446205e+01 4.708438775510203556e+01 4.759522675736960906e+01 4.815250566893423922e+01 4.861690476190475607e+01 4.908130385487528002e+01 4.959214285714285353e+01 5.014942176870747659e+01 5.066026077097505009e+01 5.117109977324263070e+01 5.168193877551020421e+01 5.223921768707482727e+01 5.270361678004535122e+01 5.321445578231292473e+01 5.372529478458049823e+01 5.423613378684807174e+01 5.479341269841269479e+01 5.530425170068026830e+01 5.581509070294784181e+01 5.632592970521541531e+01 5.683676870748298882e+01 5.730116780045351277e+01 5.785844671201813583e+01 5.841572562358276599e+01 5.892656462585033950e+01 5.943740362811791300e+01 5.994824263038548651e+01 6.050552154195010957e+01 6.101636054421768307e+01 6.152719954648525658e+01 6.203803854875283008e+01 6.250243764172335403e+01 6.305971655328797709e+01 6.357055555555555060e+01 6.408139455782313121e+01 6.459223356009070471e+01 6.510307256235827822e+01 6.566035147392290128e+01 6.617119047619047478e+01 6.663558956916099874e+01 6.714642857142857224e+01 6.770370748299319530e+01 6.816810657596371925e+01 6.872538548752834231e+01 6.923622448979591582e+01 6.979350340136055308e+01 7.030434240362812659e+01 7.081518140589570010e+01 7.132602040816327360e+01 7.188329931972789666e+01 7.234769841269842061e+01 7.285853741496599412e+01 7.341581632653061718e+01 7.392665532879819068e+01 7.443749433106576419e+01 7.490189342403628814e+01 7.545917233560091120e+01 7.597001133786848470e+01 7.652729024943310776e+01 7.708456916099773082e+01 7.759540816326530432e+01 7.810624716553287783e+01 7.861708616780045134e+01 7.912792517006802484e+01 7.968520408163266211e+01 8.019604308390023562e+01 8.070688208616780912e+01 8.121772108843538263e+01 8.172856009070295613e+01 8.223939909297052964e+01 8.279667800453515270e+01 8.330751700680272620e+01 8.381835600907029971e+01 8.437563492063492276e+01 8.488647392290249627e+01 8.539731292517006978e+01 8.590815192743764328e+01 8.646543083900226634e+01 8.697626984126983984e+01 8.748710884353741335e+01 8.799794784580498686e+01 8.850878684807256036e+01 8.901962585034013387e+01 8.953046485260770737e+01 9.004130385487528088e+01 9.050570294784580483e+01 9.106298185941042789e+01 9.157382086167801560e+01 9.208465986394558911e+01 9.259549886621316261e+01 9.315277777777778567e+01 9.366361678004535918e+01 9.417445578231293268e+01 9.468529478458050619e+01 9.519613378684807969e+01 9.575341269841270275e+01 9.631069160997732581e+01 9.686797052154194887e+01 9.733236961451247282e+01 9.784320861678004633e+01 9.830760770975057028e+01 9.881844671201814378e+01 9.937572562358276684e+01 9.988656462585034035e+01 1.003974036281179139e+02 1.009082426303854874e+02 1.014190816326530609e+02 1.019299206349206344e+02 1.024407596371882079e+02 1.029515986394557814e+02 1.034624376417233549e+02 1.039732766439909284e+02 1.044841156462585019e+02 1.049949546485260754e+02 1.055057936507936489e+02 1.060166326530612224e+02 1.065274716553287959e+02 1.069918707482993199e+02 1.075027097505668934e+02 1.080135487528344669e+02 1.085243877551020404e+02 1.090352267573696139e+02 1.095460657596371874e+02 1.100569047619047609e+02 1.105677437641723344e+02 1.110785827664399079e+02 1.115894217687074814e+02 1.121002607709750549e+02 1.126110997732426284e+02 1.131683786848072657e+02 1.137256575963718888e+02 1.141900566893424127e+02 1.147473356009070358e+02 1.152581746031746093e+02 1.157690136054421828e+02 1.162798526077097563e+02 1.167906916099773298e+02 1.173015306122449033e+02 1.178123696145124768e+02 1.183232086167800503e+02 1.188340476190476238e+02 1.193448866213151973e+02 1.198557256235827708e+02 1.203665646258503443e+02 1.208774036281179178e+02 1.213882426303854913e+02 1.218526417233560153e+02 1.224099206349206383e+02 1.229207596371882119e+02 1.233851587301587358e+02 1.239424376417233589e+02 1.244532766439909324e+02 1.249641156462585059e+02 1.254285147392290298e+02 1.259393537414966033e+02 1.264501927437641768e+02 1.270074716553287999e+02 1.275183106575963734e+02 1.280755895691609965e+02 1.285864285714285700e+02 1.290972675736961435e+02 1.296081065759637170e+02 1.301189455782312905e+02 1.306762244897959135e+02 1.312335034013605366e+02 1.317443424036281101e+02 1.322551814058956836e+02 1.327660204081632571e+02 1.332768594104308306e+02 1.337876984126984041e+02 1.342520975056689281e+02 1.348093764172335511e+02 1.353202154195011246e+02 1.358310544217686981e+02 1.363418934240362717e+02 1.368527324263038452e+02 1.373635714285714187e+02 1.378744104308389922e+02 1.383852494331065657e+02 1.388960884353741392e+02 1.394069274376417127e+02 1.399177664399092862e+02 1.404286054421768597e+02 1.409858843537414828e+02 1.414967233560090563e+02 1.420075623582766298e+02 1.425184013605442033e+02 1.430292403628117768e+02 1.435865192743763998e+02 1.440973582766439733e+02 1.446546371882085964e+02 1.451654761904761699e+02 1.457227551020407930e+02 1.462800340136054444e+02 1.467908730158730179e+02 1.473017120181405915e+02 1.478125510204081650e+02 1.483233900226757385e+02 1.488342290249433120e+02 1.493915079365079350e+02 1.499023469387755085e+02 1.504131859410430820e+02 1.508775850340136060e+02 1.514348639455782290e+02 1.518992630385487530e+02 1.524565419501133761e+02 1.529209410430839000e+02 1.534782199546485231e+02 1.539890589569160966e+02 1.544998979591836701e+02 1.550107369614512436e+02 1.555215759637188171e+02 1.560324149659863906e+02 1.565432539682539641e+02 1.570540929705215376e+02 1.575649319727891111e+02 1.580757709750566846e+02 1.585866099773242581e+02 1.590974489795918316e+02 1.596082879818594051e+02 1.601655668934240282e+02 1.606764058956916017e+02 1.612336848072562248e+02 1.617445238095237983e+02 1.622553628117913718e+02 1.628126417233559948e+02 1.633234807256235683e+02 1.638343197278911418e+02 1.643451587301587153e+02 1.649024376417233384e+02 1.653668367346938624e+02 1.658776757369614359e+02 1.663420748299319598e+02 1.668993537414965829e+02 1.674101927437641564e+02 1.678745918367346803e+02 1.683854308390022538e+02 1.688962698412698273e+02 1.694071088435374008e+02 1.698715079365079248e+02 1.703823469387754983e+02 1.708931859410430718e+02 1.714504648526076949e+02 1.719148639455782188e+02 1.724257029478457923e+02 1.729365419501133658e+02 1.734473809523809393e+02 1.740046598639455624e+02 1.745154988662131359e+02 1.750727777777777590e+02 1.756300566893423820e+02 1.761408956916099555e+02 1.766517346938775290e+02 1.772090136054421805e+02 1.777662925170068036e+02 1.782771315192743771e+02 1.787879705215419506e+02 1.792523696145124745e+02 1.797632086167800480e+02 1.802276077097505436e+02 mir_eval-0.8.2/tests/data/beat/ref07.txt000066400000000000000000000226001475740344600200070ustar00rootroot000000000000001.395192857232350758e-01 6.557406428992047509e-01 1.201757369614512516e+00 1.712596371882086244e+00 2.269875283446712189e+00 2.827154195011337912e+00 3.430873015873015852e+00 4.034591836734694681e+00 4.591870748299320404e+00 5.149149659863946127e+00 5.706428571428571850e+00 6.263707482993197573e+00 6.820986394557823296e+00 7.331825396825397689e+00 7.889104308390022524e+00 8.399943310657596030e+00 8.957222222222222641e+00 9.514501133786849252e+00 1.002534013605442276e+01 1.053617913832199626e+01 1.109345804988662110e+01 1.160429705215419460e+01 1.216157596371882121e+01 1.271885487528344783e+01 1.322969387755102133e+01 1.374053287981859484e+01 1.429781179138321967e+01 1.480865079365079495e+01 1.531948979591836846e+01 1.583032879818594196e+01 1.634116780045351547e+01 1.685200680272108897e+01 1.736284580498866248e+01 1.787368480725623598e+01 1.843096371882086260e+01 1.894180272108843610e+01 1.945264172335600961e+01 2.000992063492063622e+01 2.052075963718820972e+01 2.103159863945578323e+01 2.154243764172335673e+01 2.209971655328798334e+01 2.261055555555555685e+01 2.316783446712018346e+01 2.367867346938775697e+01 2.423595238095238003e+01 2.474679138321995353e+01 2.530407029478458014e+01 2.576846938775510409e+01 2.627930839002267760e+01 2.683658730158730066e+01 2.734742630385487416e+01 2.785826530612244767e+01 2.836910430839002473e+01 2.892638321995464779e+01 2.943722222222222129e+01 2.994806122448979480e+01 3.045890022675736830e+01 3.096973922902494536e+01 3.152701814058956842e+01 3.203785714285714192e+01 3.254869614512471543e+01 3.305953514739228893e+01 3.357037414965986244e+01 3.408121315192743594e+01 3.463849206349205900e+01 3.514933106575963251e+01 3.566017006802720601e+01 3.617100907029477952e+01 3.668184807256235302e+01 3.723912698412698319e+01 3.770352607709750004e+01 3.821436507936507354e+01 3.877164399092970370e+01 3.932892290249432676e+01 3.983976190476190027e+01 4.035060090702947377e+01 4.086143990929704728e+01 4.141871882086167744e+01 4.192955782312925095e+01 4.248683673469387401e+01 4.299767573696144751e+01 4.350851473922902102e+01 4.401935374149659452e+01 4.453019274376416803e+01 4.508747165532879819e+01 4.559831065759637170e+01 4.610914965986394520e+01 4.661998866213151871e+01 4.717726757369614177e+01 4.768810657596371527e+01 4.824538548752833833e+01 4.870978458049886228e+01 4.926706349206349245e+01 4.982434240362811551e+01 5.033518140589568901e+01 5.089246031746031207e+01 5.140329931972788557e+01 5.191413832199545908e+01 5.242497732426303259e+01 5.293581632653060609e+01 5.353953514739228581e+01 5.409681405895691597e+01 5.456121315192743282e+01 5.507205215419500632e+01 5.558289115646257983e+01 5.614017006802720999e+01 5.665100907029478350e+01 5.720828798185940656e+01 5.771912698412698006e+01 5.827640589569161023e+01 5.883368480725623328e+01 5.934452380952380679e+01 5.985536281179138030e+01 6.036620181405895380e+01 6.092348072562357686e+01 6.138787981859410081e+01 6.194515873015872387e+01 6.250243764172335403e+01 6.296683673469387088e+01 6.352411564625850104e+01 6.403495464852608166e+01 6.454579365079365516e+01 6.510307256235827822e+01 6.561391156462585172e+01 6.612475056689342523e+01 6.668202947845804829e+01 6.719286848072562179e+01 6.770370748299319530e+01 6.816810657596371925e+01 6.872538548752834231e+01 6.928266439909297958e+01 6.979350340136055308e+01 7.030434240362812659e+01 7.086162131519274965e+01 7.137246031746032315e+01 7.188329931972789666e+01 7.239413832199547016e+01 7.295141723356009322e+01 7.346225623582766673e+01 7.397309523809524023e+01 7.453037414965986329e+01 7.504121315192743680e+01 7.559849206349207407e+01 7.610933106575964757e+01 7.657373015873015731e+01 7.713100907029479458e+01 7.764184807256236809e+01 7.815268707482994159e+01 7.870996598639456465e+01 7.922080498866213816e+01 7.973164399092971166e+01 8.024248299319728517e+01 8.075332199546485867e+01 8.126416099773243218e+01 8.182143990929705524e+01 8.233227891156462874e+01 8.284311791383220225e+01 8.335395691609977575e+01 8.391123582766439881e+01 8.437563492063492276e+01 8.493291383219954582e+01 8.544375283446711933e+01 8.600103174603175660e+01 8.651187074829933010e+01 8.702270975056690361e+01 8.753354875283447711e+01 8.804438775510205062e+01 8.860166666666667368e+01 8.911250566893424718e+01 8.962334467120182069e+01 9.013418367346939419e+01 9.069146258503401725e+01 9.115586167800454120e+01 9.171314058956916426e+01 9.222397959183673777e+01 9.273481859410431127e+01 9.324565759637188478e+01 9.375649659863945828e+01 9.426733560090703179e+01 9.477817460317460529e+01 9.528901360544217880e+01 9.584629251700680186e+01 9.635713151927437536e+01 9.686797052154194887e+01 9.737880952380952237e+01 9.793608843537415964e+01 9.840048752834466939e+01 9.895776643990930665e+01 9.946860544217688016e+01 9.997944444444445367e+01 1.004902834467120272e+02 1.010011224489796007e+02 1.015584013605442237e+02 1.020692403628117972e+02 1.025800793650793707e+02 1.030909183673469443e+02 1.036017573696145178e+02 1.041125963718820913e+02 1.046234353741496648e+02 1.051342743764172383e+02 1.056915532879818613e+02 1.062488321995464844e+02 1.067596712018140579e+02 1.072705102040816314e+02 1.078277891156462687e+02 1.083850680272108917e+02 1.088494671201814157e+02 1.093603061224489892e+02 1.099175850340136122e+02 1.104284240362811857e+02 1.109857029478458088e+02 1.114965419501133823e+02 1.120073809523809558e+02 1.125646598639455789e+02 1.131219387755102019e+02 1.135863378684807259e+02 1.141436167800453489e+02 1.146544557823129225e+02 1.152117346938775597e+02 1.157225736961451332e+02 1.162334126984127067e+02 1.167442517006802802e+02 1.172550907029478537e+02 1.177659297052154272e+02 1.183232086167800503e+02 1.188804875283446734e+02 1.193913265306122469e+02 1.199021655328798204e+02 1.204130045351473939e+02 1.209702834467120169e+02 1.214346825396825409e+02 1.219455215419501144e+02 1.224563605442176879e+02 1.230136394557823110e+02 1.235244784580498845e+02 1.240353174603174580e+02 1.245461564625850315e+02 1.251034353741496687e+02 1.255678344671201785e+02 1.260786734693877520e+02 1.265895124716553397e+02 1.271467913832199628e+02 1.276576303854875363e+02 1.281684693877550956e+02 1.286793083900226691e+02 1.291901473922902426e+02 1.297009863945578161e+02 1.302118253968253896e+02 1.307691043083900126e+02 1.312799433106575862e+02 1.317907823129251597e+02 1.323016213151927332e+02 1.328124603174603067e+02 1.333232993197278802e+02 1.338341383219954537e+02 1.343449773242630272e+02 1.348558163265306007e+02 1.354130952380952237e+02 1.359239342403627973e+02 1.364347732426303708e+02 1.368991723356008947e+02 1.374564512471655178e+02 1.379672902494330913e+02 1.384781292517006648e+02 1.389889682539682383e+02 1.395462471655328613e+02 1.400570861678004349e+02 1.405679251700680084e+02 1.410787641723355819e+02 1.415896031746031554e+02 1.421468820861677784e+02 1.426577210884353519e+02 1.431685600907029254e+02 1.436793990929704989e+02 1.441902380952380724e+02 1.447010770975056460e+02 1.452119160997732195e+02 1.457227551020407930e+02 1.462335941043083665e+02 1.467444331065759400e+02 1.472552721088435135e+02 1.477661111111110870e+02 1.483233900226757385e+02 1.488342290249433120e+02 1.493915079365079350e+02 1.499023469387755085e+02 1.504131859410430820e+02 1.509240249433106555e+02 1.514813038548752786e+02 1.519921428571428521e+02 1.525029818594104256e+02 1.530602607709750487e+02 1.535710997732426222e+02 1.540354988662131461e+02 1.544998979591836701e+02 1.550107369614512436e+02 1.555680158730158666e+02 1.561252947845804897e+02 1.566361337868480632e+02 1.571469727891156367e+02 1.576578117913832102e+02 1.581686507936507837e+02 1.586794897959183572e+02 1.591903287981859307e+02 1.597011678004535042e+02 1.602120068027210777e+02 1.607228458049886513e+02 1.612801247165532743e+02 1.617445238095237983e+02 1.622553628117913718e+02 1.627662018140589453e+02 1.633234807256235683e+02 1.638343197278911418e+02 1.643451587301587153e+02 1.648559977324262888e+02 1.654132766439909119e+02 1.659241156462584854e+02 1.664813945578231085e+02 1.669922335600906820e+02 1.674566326530612059e+02 1.680139115646258290e+02 1.685247505668934025e+02 1.690355895691609760e+02 1.695928684807256275e+02 1.701037074829932010e+02 1.705681065759636965e+02 1.710789455782312700e+02 1.715897845804988435e+02 1.721006235827664170e+02 1.726579024943310685e+02 1.732151814058956916e+02 1.737260204081632651e+02 1.742368594104308386e+02 1.747476984126984121e+02 1.752585374149659856e+02 1.757693764172335591e+02 1.762802154195011326e+02 1.767910544217687061e+02 1.773018934240362796e+02 1.778127324263038531e+02 1.783235714285714266e+02 1.788344104308390001e+02 1.793452494331065736e+02 1.798560884353741471e+02 1.803669274376417206e+02 1.808777664399092941e+02 1.813886054421768677e+02 1.818994444444444412e+02 1.824102834467120147e+02 1.829211224489795882e+02 1.834319614512471617e+02 1.839428004535147352e+02 1.844536394557823087e+02 1.849644784580498822e+02 1.854753174603174557e+02 1.859861564625850292e+02 1.864969954648526027e+02 1.870078344671201762e+02 1.875186734693877497e+02 1.880295124716553232e+02 1.885403514739228967e+02 1.890511904761904702e+02 1.895620294784580437e+02 1.900728684807256172e+02 1.905837074829931908e+02 1.911409863945578138e+02 1.916518253968253873e+02 1.921162244897959113e+02 1.926735034013605343e+02 1.931843424036281078e+02 1.936951814058956813e+02 1.942060204081632548e+02 1.947168594104308283e+02 1.952276984126984019e+02 1.957385374149659754e+02 1.962493764172335489e+02 1.967602154195011224e+02 1.973174943310657454e+02 1.978283333333333189e+02 1.983391723356008924e+02 1.988500113378684659e+02 1.993608503401360394e+02 1.999181292517006625e+02 mir_eval-0.8.2/tests/data/beat/ref08.txt000066400000000000000000000153641475740344600200210ustar00rootroot000000000000008.719954648526079266e-02 6.909183673469387887e-01 1.294637188208616729e+00 1.991235827664398883e+00 2.594954648526077268e+00 3.245113378684807426e+00 3.941712018140589802e+00 4.638310657596372621e+00 5.334909297052154997e+00 5.938628117913832938e+00 6.542346938775510878e+00 7.099625850340136601e+00 7.749784580498866760e+00 8.399943310657596030e+00 8.957222222222222641e+00 9.560941043083900581e+00 1.016465986394557852e+01 1.076837868480725646e+01 1.137209750566893440e+01 1.197581632653061234e+01 1.253309523809523895e+01 1.309037414965986379e+01 1.364765306122449040e+01 1.429781179138321967e+01 1.490153061224489761e+01 1.550524943310657555e+01 1.606252834467120394e+01 1.666624716553288010e+01 1.722352607709750671e+01 1.782724489795918288e+01 1.838452380952380949e+01 1.898824263038548921e+01 1.959196145124716537e+01 2.024212018140589464e+01 2.079939909297052125e+01 2.135667800453514786e+01 2.191395691609977447e+01 2.251767573696145064e+01 2.312139455782313036e+01 2.367867346938775697e+01 2.423595238095238003e+01 2.479323129251700664e+01 2.544339002267573591e+01 2.609354875283446873e+01 2.669726757369614489e+01 2.720810657596371840e+01 2.781182539682539812e+01 2.836910430839002473e+01 2.897282312925170089e+01 2.957654195011338061e+01 3.018026077097505677e+01 3.073753968253968338e+01 3.134125850340135955e+01 3.189853741496598971e+01 3.245581632653060922e+01 3.305953514739228893e+01 3.366325396825396865e+01 3.422053287981859171e+01 3.482425170068027143e+01 3.538153061224489448e+01 3.598524943310657420e+01 3.663540816326530347e+01 3.719268707482992653e+01 3.774996598639455669e+01 3.840012471655328596e+01 3.895740362811790902e+01 3.951468253968253919e+01 4.011840136054421180e+01 4.072212018140589151e+01 4.123295918367346502e+01 4.183667800453514474e+01 4.239395691609976780e+01 4.295123582766439796e+01 4.360139455782312723e+01 4.420511337868480695e+01 4.476239229024943000e+01 4.536611111111110972e+01 4.592339002267573278e+01 4.652710884353741250e+01 4.717726757369614177e+01 4.773454648526076483e+01 4.829182539682539499e+01 4.889554421768707471e+01 4.945282312925169776e+01 5.005654195011337748e+01 5.066026077097505009e+01 5.126397959183672981e+01 5.182125850340135997e+01 5.242497732426303259e+01 5.302869614512471230e+01 5.358597505668934247e+01 5.418969387755101508e+01 5.479341269841269479e+01 5.535069160997731785e+01 5.595441043083899757e+01 5.651168934240362773e+01 5.711540816326530035e+01 5.771912698412698006e+01 5.836928571428570933e+01 5.892656462585033950e+01 5.948384353741496255e+01 6.004112244897958561e+01 6.069128117913832199e+01 6.124856009070294505e+01 6.189871882086167432e+01 6.245599773242629738e+01 6.305971655328797709e+01 6.361699546485260726e+01 6.417427437641724453e+01 6.477799319727891714e+01 6.538171201814058975e+01 6.593899092970521281e+01 6.649626984126985008e+01 6.709998866213152269e+01 6.770370748299319530e+01 6.830742630385488212e+01 6.891114512471655473e+01 6.946842403628117779e+01 7.007214285714286461e+01 7.067586167800453723e+01 7.123314058956916028e+01 7.183685941043084711e+01 7.239413832199547016e+01 7.299785714285714278e+01 7.350869614512471628e+01 7.411241496598640310e+01 7.471613378684807572e+01 7.527341269841269877e+01 7.587713151927438560e+01 7.643441043083900865e+01 7.699168934240363171e+01 7.750252834467120522e+01 7.810624716553287783e+01 7.870996598639456465e+01 7.931368480725623726e+01 7.982452380952381077e+01 8.042824263038549759e+01 8.103196145124717020e+01 8.158924036281179326e+01 8.219295918367348008e+01 8.275023809523810314e+01 8.335395691609977575e+01 8.391123582766439881e+01 8.451495464852608563e+01 8.511867346938775825e+01 8.567595238095238130e+01 8.623323129251700436e+01 8.683695011337869119e+01 8.744066893424036380e+01 8.804438775510205062e+01 8.864810657596372323e+01 8.920538548752834629e+01 8.985554421768708266e+01 9.045926303854875528e+01 9.106298185941042789e+01 9.166670068027211471e+01 9.227041950113378732e+01 9.287413832199547414e+01 9.343141723356009720e+01 9.398869614512472026e+01 9.459241496598639287e+01 9.519613378684807969e+01 9.575341269841270275e+01 9.635713151927437536e+01 9.691441043083901263e+01 9.742524943310658614e+01 9.802896825396825875e+01 9.863268707482993136e+01 9.918996598639456863e+01 9.974724489795919169e+01 1.002580839002267652e+02 1.008618027210884378e+02 1.014190816326530609e+02 1.019299206349206344e+02 1.025336394557823212e+02 1.031373582766439938e+02 1.036481972789115673e+02 1.042519160997732399e+02 1.048091950113378772e+02 1.053664739229025002e+02 1.059701927437641729e+02 1.065274716553287959e+02 1.070847505668934332e+02 1.076420294784580562e+02 1.082457482993197289e+02 1.087565873015873024e+02 1.093603061224489892e+02 1.098711451247165627e+02 1.104748639455782353e+02 1.110321428571428584e+02 1.116358616780045452e+02 1.121467006802721187e+02 1.127504195011337913e+02 1.133541383219954639e+02 1.138649773242630374e+02 1.144686961451247242e+02 1.150259750566893473e+02 1.155368140589569208e+02 1.161405328798185934e+02 1.167442517006802802e+02 1.173015306122449033e+02 1.179052494331065759e+02 1.184625283446711990e+02 1.190198072562358362e+02 1.196235260770975088e+02 1.201808049886621319e+02 1.207845238095238187e+02 1.212953628117913922e+02 1.218990816326530648e+02 1.223634807256235888e+02 1.229671995464852614e+02 1.235709183673469482e+02 1.241281972789115713e+02 1.246854761904761943e+02 1.252427551020408174e+02 1.257535941043083909e+02 1.263573129251700777e+02 1.269145918367347008e+02 1.275183106575963734e+02 1.280291496598639469e+02 1.286328684807256195e+02 1.291901473922902426e+02 1.297938662131519152e+02 1.303511451247165382e+02 1.309084240362811613e+02 1.315121428571428339e+02 1.321158616780045350e+02 1.326731405895691580e+02 1.332768594104308306e+02 1.338341383219954537e+02 1.343914172335600767e+02 1.349486961451246998e+02 1.355524149659863724e+02 1.361561337868480734e+02 1.367598526077097461e+02 1.372706916099773196e+02 1.378279705215419426e+02 1.383852494331065657e+02 1.389425283446711887e+02 1.395462471655328613e+02 1.401035260770974844e+02 1.407072448979591854e+02 1.412645238095238085e+02 1.417753628117913820e+02 1.423790816326530546e+02 1.429363605442176777e+02 1.435400793650793503e+02 1.441437981859410229e+02 1.447010770975056460e+02 1.452583560090702974e+02 1.458620748299319700e+02 1.464193537414965931e+02 1.469766326530612162e+02 1.475339115646258392e+02 1.480911904761904623e+02 1.487413492063491844e+02 1.493450680272108855e+02 1.498559070294784590e+02 1.504596258503401316e+02 1.510169047619047547e+02 1.516206235827664273e+02 1.521779024943310503e+02 1.526887414965986238e+02 1.532924603174602964e+02 1.538497392290249195e+02 1.544534580498866205e+02 1.551036167800453427e+02 1.556608956916099658e+02 1.562181746031745888e+02 1.568683333333333110e+02 1.575184920634920616e+02 1.581222108843537342e+02 1.587259297052154068e+02 1.593760884353741289e+02 1.599798072562358300e+02 1.607692857142857008e+02 mir_eval-0.8.2/tests/data/beat/ref09.txt000066400000000000000000000372311475740344600200170ustar00rootroot000000000000002.359049919500000037e-01 8.073879903307981110e-01 1.378870988711596413e+00 1.950353987092394936e+00 2.521836985473192794e+00 3.093319983853990873e+00 3.664802982234789397e+00 4.236285980615586588e+00 4.807768978996384668e+00 5.379251977377182747e+00 5.950734975757980827e+00 6.522217974138778906e+00 7.093700972519577874e+00 7.665183970900375954e+00 8.236666969281174033e+00 8.808149967661972113e+00 9.379632966042770192e+00 9.951115964423568272e+00 1.052259896280436635e+01 1.109408196118516443e+01 1.166556495956596251e+01 1.223704795794676059e+01 1.280853095632755867e+01 1.338001395470835675e+01 1.395149695308915661e+01 1.452297995146995468e+01 1.509446294985075276e+01 1.566594594823155084e+01 1.623742894661234715e+01 1.680891194499314878e+01 1.738039494337394331e+01 1.795187794175474494e+01 1.852336094013553947e+01 1.909484393851634110e+01 1.966632693689713562e+01 2.023780993527793726e+01 2.080929293365873178e+01 2.138077593203953342e+01 2.195225893042032794e+01 2.252374192880112957e+01 2.309522492718192410e+01 2.366670792556272573e+01 2.423819092394352026e+01 2.480967392232432189e+01 2.538115692070511642e+01 2.595263991908591805e+01 2.652412291746671258e+01 2.709560591584751421e+01 2.766708891422831584e+01 2.823857191260911037e+01 2.881005491098991200e+01 2.938153790937070653e+01 2.995302090775150816e+01 3.052450390613230269e+01 3.109598690451310432e+01 3.166746990289389885e+01 3.223895290127470048e+01 3.281043589965549501e+01 3.338191889803629664e+01 3.395340189641709117e+01 3.452488489479789280e+01 3.509636789317868732e+01 3.566785089155948896e+01 3.623933388994028348e+01 3.681081688832108512e+01 3.738229988670188675e+01 3.795378288508268128e+01 3.852526588346348291e+01 3.909674888184427743e+01 3.966823188022507907e+01 4.023971487860587359e+01 4.081119787698667523e+01 4.138268087536746975e+01 4.195416387374827139e+01 4.252564687212906591e+01 4.309712987050986754e+01 4.366861286889066207e+01 4.424009586727146370e+01 4.481157886565225823e+01 4.538306186403305986e+01 4.595454486241385439e+01 4.652602786079465602e+01 4.709751085917545055e+01 4.766899385755625218e+01 4.824047685593704671e+01 4.881195985431784834e+01 4.938344285269864287e+01 4.995492585107944450e+01 5.052640884946023903e+01 5.109789184784104066e+01 5.166937484622183518e+01 5.224085784460263682e+01 5.281234084298343134e+01 5.338382384136423298e+01 5.395530683974502750e+01 5.452678983812582914e+01 5.509827283650663077e+01 5.566975583488742529e+01 5.624123883326822693e+01 5.681272183164902145e+01 5.738420483002982309e+01 5.795568782841061761e+01 5.852717082679141924e+01 5.909865382517221377e+01 5.967013682355301540e+01 6.024161982193380993e+01 6.081310282031461156e+01 6.138458581869540609e+01 6.195606881707620772e+01 6.252755181545700225e+01 6.309903481383780388e+01 6.367051781221859841e+01 6.424200081059940715e+01 6.481348380898020878e+01 6.538496680736099620e+01 6.595644980574179783e+01 6.652793280412259946e+01 6.709941580250340110e+01 6.767089880088418852e+01 6.824238179926499015e+01 6.881386479764579178e+01 6.938534779602659341e+01 6.995683079440738084e+01 7.052831379278818247e+01 7.109979679116898410e+01 7.167127978954978573e+01 7.224276278793057315e+01 7.281424578631137479e+01 7.338572878469217642e+01 7.395721178307297805e+01 7.452869478145377968e+01 7.510017777983456710e+01 7.567166077821536874e+01 7.624314377659617037e+01 7.681462677497697200e+01 7.738610977335775942e+01 7.795759277173856105e+01 7.852907577011936269e+01 7.910055876850016432e+01 7.967204176688095174e+01 8.024352476526175337e+01 8.081500776364255501e+01 8.138649076202335664e+01 8.195797376040414406e+01 8.252945675878494569e+01 8.310093975716574732e+01 8.367242275554654896e+01 8.424390575392733638e+01 8.481538875230813801e+01 8.538687175068893964e+01 8.595835474906974127e+01 8.652983774745052870e+01 8.710132074583133033e+01 8.767280374421213196e+01 8.824428674259293359e+01 8.881576974097372101e+01 8.938725273935452265e+01 8.995873573773532428e+01 9.053021873611612591e+01 9.110170173449691333e+01 9.167318473287771496e+01 9.224466773125851660e+01 9.281615072963931823e+01 9.338763372802011986e+01 9.395911672640090728e+01 9.453059972478170891e+01 9.510208272316251055e+01 9.567356572154331218e+01 9.624504871992409960e+01 9.681653171830490123e+01 9.738801471668570287e+01 9.795949771506650450e+01 9.853098071344729192e+01 9.910246371182809355e+01 9.967394671020889518e+01 1.002454297085896968e+02 1.008169127069704842e+02 1.013883957053512859e+02 1.019598787037320875e+02 1.025313617021128891e+02 1.031028447004936766e+02 1.036743276988744782e+02 1.042458106972552798e+02 1.048172936956360815e+02 1.053887766940168689e+02 1.059602596923976705e+02 1.065317426907784721e+02 1.071032256891592738e+02 1.076747086875400612e+02 1.082461916859208628e+02 1.088176746843016645e+02 1.093891576826824661e+02 1.099606406810632677e+02 1.105321236794440551e+02 1.111036066778248568e+02 1.116750896762056584e+02 1.122465726745864600e+02 1.128180556729672475e+02 1.133895386713480491e+02 1.139610216697288507e+02 1.145325046681096524e+02 1.151039876664904398e+02 1.156754706648712414e+02 1.162469536632520430e+02 1.168184366616328447e+02 1.173899196600136321e+02 1.179614026583944337e+02 1.185328856567752354e+02 1.191043686551560370e+02 1.196758516535368244e+02 1.202473346519176260e+02 1.208188176502984277e+02 1.213903006486792293e+02 1.219617836470600167e+02 1.225332666454408184e+02 1.231047496438216200e+02 1.236762326422024216e+02 1.242477156405832091e+02 1.248191986389640107e+02 1.253906816373448123e+02 1.259621646357256139e+02 1.265336476341064014e+02 1.271051306324872030e+02 1.276766136308680046e+02 1.282480966292488347e+02 1.288195796276296221e+02 1.293910626260104380e+02 1.299625456243912254e+02 1.305340286227720128e+02 1.311055116211528286e+02 1.316769946195336161e+02 1.322484776179144319e+02 1.328199606162952193e+02 1.333914436146760067e+02 1.339629266130568226e+02 1.345344096114376100e+02 1.351058926098183974e+02 1.356773756081992133e+02 1.362488586065800007e+02 1.368203416049608165e+02 1.373918246033416040e+02 1.379633076017223914e+02 1.385347906001032072e+02 1.391062735984839946e+02 1.396777565968647821e+02 1.402492395952455979e+02 1.408207225936263853e+02 1.413922055920072012e+02 1.419636885903879886e+02 1.425351715887687760e+02 1.431066545871495919e+02 1.436781375855303793e+02 1.442496205839111667e+02 1.448211035822919825e+02 1.453925865806727700e+02 1.459640695790535858e+02 1.465355525774343732e+02 1.471070355758151607e+02 1.476785185741959765e+02 1.482500015725767639e+02 1.488214845709575798e+02 1.493929675693383672e+02 1.499644505677191546e+02 1.505359335660999704e+02 1.511074165644807579e+02 1.516788995628615453e+02 1.522503825612423611e+02 1.528218655596231486e+02 1.533933485580039644e+02 1.539648315563847518e+02 1.545363145547655392e+02 1.551077975531463551e+02 1.556792805515271425e+02 1.562507635499079299e+02 1.568222465482887458e+02 1.573937295466695332e+02 1.579652125450503490e+02 1.585366955434311365e+02 1.591081785418119239e+02 1.596796615401927397e+02 1.602511445385735271e+02 1.608226275369543146e+02 1.613941105353351304e+02 1.619655935337159178e+02 1.625370765320967337e+02 1.631085595304775211e+02 1.636800425288583085e+02 1.642515255272391244e+02 1.648230085256199118e+02 1.653944915240007276e+02 1.659659745223815150e+02 1.665374575207623025e+02 1.671089405191431183e+02 1.676804235175239057e+02 1.682519065159046932e+02 1.688233895142855090e+02 1.693948725126662964e+02 1.699663555110471123e+02 1.705378385094278997e+02 1.711093215078086871e+02 1.716808045061895029e+02 1.722522875045702904e+02 1.728237705029510778e+02 1.733952535013318936e+02 1.739667364997126811e+02 1.745382194980934969e+02 1.751097024964742843e+02 1.756811854948550717e+02 1.762526684932358876e+02 1.768241514916166750e+02 1.773956344899974624e+02 1.779671174883782783e+02 1.785386004867590657e+02 1.791100834851398815e+02 1.796815664835206690e+02 1.802530494819014564e+02 1.808245324802822722e+02 1.813960154786630596e+02 1.819674984770438471e+02 1.825389814754246629e+02 1.831104644738054503e+02 1.836819474721862662e+02 1.842534304705670536e+02 1.848249134689478410e+02 1.853963964673286569e+02 1.859678794657094443e+02 1.865393624640902601e+02 1.871108454624710475e+02 1.876823284608518350e+02 1.882538114592326508e+02 1.888252944576134382e+02 1.893967774559942256e+02 1.899682604543750415e+02 1.905397434527558289e+02 1.911112264511366448e+02 1.916827094495174322e+02 1.922541924478982196e+02 1.928256754462790354e+02 1.933971584446598229e+02 1.939686414430406103e+02 1.945401244414214261e+02 1.951116074398022135e+02 1.956830904381830294e+02 1.962545734365638168e+02 1.968260564349446042e+02 1.973975394333254201e+02 1.979690224317062075e+02 1.985405054300869949e+02 1.991119884284678108e+02 1.996834714268485982e+02 2.002549544252294140e+02 2.008264374236102014e+02 2.013979204219909889e+02 2.019694034203718047e+02 2.025408864187525921e+02 2.031123694171334080e+02 2.036838524155141954e+02 2.042553354138949828e+02 2.048268184122757987e+02 2.053983014106565861e+02 2.059697844090373735e+02 2.065412674074181894e+02 2.071127504057989768e+02 2.076842334041797926e+02 2.082557164025605800e+02 2.088271994009413675e+02 2.093986823993221833e+02 2.099701653977029707e+02 2.105416483960837581e+02 2.111131313944645740e+02 2.116846143928453614e+02 2.122560973912261773e+02 2.128275803896069647e+02 2.133990633879877521e+02 2.139705463863685679e+02 2.145420293847493554e+02 2.151135123831301428e+02 2.156849953815109586e+02 2.162564783798917460e+02 2.168279613782725619e+02 2.173994443766533493e+02 2.179709273750341367e+02 2.185424103734149526e+02 2.191138933717957400e+02 2.196853763701765558e+02 2.202568593685573433e+02 2.208283423669381307e+02 2.213998253653189465e+02 2.219713083636997339e+02 2.225427913620805214e+02 2.231142743604613372e+02 2.236857573588421246e+02 2.242572403572229405e+02 2.248287233556037279e+02 2.254002063539845153e+02 2.259716893523653312e+02 2.265431723507461186e+02 2.271146553491269060e+02 2.276861383475077218e+02 2.282576213458885093e+02 2.288291043442693251e+02 2.294005873426501125e+02 2.299720703410309000e+02 2.305435533394117158e+02 2.311150363377925032e+02 2.316865193361732906e+02 2.322580023345541065e+02 2.328294853329348939e+02 2.334009683313157097e+02 2.339724513296964972e+02 2.345439343280772846e+02 2.351154173264581004e+02 2.356869003248388879e+02 2.362583833232196753e+02 2.368298663216004911e+02 2.374013493199812785e+02 2.379728323183620944e+02 2.385443153167428818e+02 2.391157983151236692e+02 2.396872813135044851e+02 2.402587643118852725e+02 2.408302473102660883e+02 2.414017303086468758e+02 2.419732133070276632e+02 2.425446963054084790e+02 2.431161793037892664e+02 2.436876623021700539e+02 2.442591453005508697e+02 2.448306282989316571e+02 2.454021112973124730e+02 2.459735942956932604e+02 2.465450772940740478e+02 2.471165602924548637e+02 2.476880432908356511e+02 2.482595262892164385e+02 2.488310092875972543e+02 2.494024922859780418e+02 2.499739752843588576e+02 2.505454582827396450e+02 2.511169412811204324e+02 2.516884242795012483e+02 2.522599072778820357e+02 2.528313902762628231e+02 2.534028732746436390e+02 2.539743562730244264e+02 2.545458392714052422e+02 2.551173222697860297e+02 2.556888052681668171e+02 2.562602882665475477e+02 2.568317712649283635e+02 2.574032542633091225e+02 2.579747372616899384e+02 2.585462202600707542e+02 2.591177032584515132e+02 2.596891862568323290e+02 2.602606692552131449e+02 2.608321522535939039e+02 2.614036352519747197e+02 2.619751182503555356e+02 2.625466012487362946e+02 2.631180842471171104e+02 2.636895672454979263e+02 2.642610502438787421e+02 2.648325332422595011e+02 2.654040162406403169e+02 2.659754992390211328e+02 2.665469822374018918e+02 2.671184652357827076e+02 2.676899482341635235e+02 2.682614312325442825e+02 2.688329142309250983e+02 2.694043972293059142e+02 2.699758802276866732e+02 2.705473632260674890e+02 2.711188462244483048e+02 2.716903292228290638e+02 2.722618122212098797e+02 2.728332952195906955e+02 2.734047782179715114e+02 2.739762612163522704e+02 2.745477442147330862e+02 2.751192272131139021e+02 2.756907102114946611e+02 2.762621932098754769e+02 2.768336762082562927e+02 2.774051592066370517e+02 2.779766422050178676e+02 2.785481252033986834e+02 2.791196082017794424e+02 2.796910912001602583e+02 2.802625741985410741e+02 2.808340571969218900e+02 2.814055401953026490e+02 2.819770231936834648e+02 2.825485061920642806e+02 2.831199891904450396e+02 2.836914721888258555e+02 2.842629551872066713e+02 2.848344381855874303e+02 2.854059211839682462e+02 2.859774041823490620e+02 2.865488871807298210e+02 2.871203701791106369e+02 2.876918531774914527e+02 2.882633361758722117e+02 2.888348191742530275e+02 2.894063021726338434e+02 2.899777851710146592e+02 2.905492681693954182e+02 2.911207511677762341e+02 2.916922341661570499e+02 2.922637171645378089e+02 2.928352001629186248e+02 2.934066831612994406e+02 2.939781661596801996e+02 2.945496491580610154e+02 2.951211321564418313e+02 2.956926151548225903e+02 2.962640981532034061e+02 2.968355811515842220e+02 2.974070641499650378e+02 2.979785471483457968e+02 2.985500301467266127e+02 2.991215131451074285e+02 2.996929961434881875e+02 3.002644791418690033e+02 3.008359621402498192e+02 3.014074451386305782e+02 3.019789281370113940e+02 3.025504111353922099e+02 3.031218941337729689e+02 3.036933771321537847e+02 3.042648601305346006e+02 3.048363431289153596e+02 3.054078261272961754e+02 3.059793091256769912e+02 3.065507921240578071e+02 3.071222751224385661e+02 3.076937581208193819e+02 3.082652411192001978e+02 3.088367241175809568e+02 3.094082071159617726e+02 3.099796901143425885e+02 3.105511731127233475e+02 3.111226561111041633e+02 3.116941391094849791e+02 3.122656221078657381e+02 3.128371051062465540e+02 3.134085881046273698e+02 3.139800711030081857e+02 3.145515541013889447e+02 3.151230370997697605e+02 3.156945200981505764e+02 3.162660030965313354e+02 3.168374860949121512e+02 3.174089690932929670e+02 3.179804520916737260e+02 3.185519350900545419e+02 3.191234180884353577e+02 3.196949010868161167e+02 3.202663840851969326e+02 3.208378670835777484e+02 3.214093500819585074e+02 3.219808330803393233e+02 3.225523160787201391e+02 3.231237990771009549e+02 3.236952820754817139e+02 3.242667650738625298e+02 3.248382480722433456e+02 3.254097310706241046e+02 3.259812140690049205e+02 3.265526970673857363e+02 3.271241800657664953e+02 3.276956630641473112e+02 3.282671460625281270e+02 3.288386290609088860e+02 3.294101120592897018e+02 3.299815950576705177e+02 3.305530780560513335e+02 3.311245610544320925e+02 3.316960440528129084e+02 3.322675270511937242e+02 3.328390100495744832e+02 3.334104930479552991e+02 3.339819760463361149e+02 3.345534590447168739e+02 3.351249420430976897e+02 3.356964250414785056e+02 3.362679080398592646e+02 3.368393910382400804e+02 3.374108740366208963e+02 3.379823570350016553e+02 3.385538400333824711e+02 3.391253230317632870e+02 3.396968060301441028e+02 3.402682890285248618e+02 3.408397720269056776e+02 3.414112550252864935e+02 3.419827380236672525e+02 3.425542210220480683e+02 3.431257040204288842e+02 3.436971870188096432e+02 3.442686700171904590e+02 3.448401530155712749e+02 3.454116360139520339e+02 3.459831190123328497e+02 3.465546020107136655e+02 3.471260850090944245e+02 3.476975680074752404e+02 3.482690510058560562e+02 3.488405340042368721e+02 3.494120170026176311e+02 3.499835000009984469e+02 3.505549829993792628e+02 3.511264659977600218e+02 3.516979489961408376e+02 3.522694319945216535e+02 3.528409149929024125e+02 3.534123979912832283e+02 3.539838809896640441e+02 3.545553639880448031e+02 3.551268469864256190e+02 3.556983299848064348e+02 3.562698129831872507e+02 3.568412959815680097e+02 3.574127789799488255e+02 3.579842619783296414e+02 3.585557449767104004e+02 3.591272279750912162e+02 3.596987109734720320e+02 3.602701939718527910e+02 3.608416769702336069e+02 3.614131599686144227e+02 3.619846429669951817e+02 3.625561259653759976e+02 3.631276089637568134e+02 3.636990919621375724e+02 3.642705749605183883e+02 3.648420579588992041e+02 3.654135409572800199e+02 3.659850239556607789e+02 mir_eval-0.8.2/tests/data/chord/000077500000000000000000000000001475740344600165075ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/chord/est00.lab000066400000000000000000000157171475740344600201350ustar00rootroot00000000000000# Another comment 0.256 0.718 B:min 0.718 1.186 G:maj 1.186 1.633 G:maj 1.633 2.089 D:maj 2.089 2.542 D:maj 2.542 2.989 G:maj 2.989 3.415 G:maj 3.415 3.895 D:maj 3.895 4.369 D:maj 4.369 4.831 G:maj 4.831 5.284 G:maj 5.284 5.746 D:maj 5.746 6.199 G:maj 6.199 6.667 G:maj 6.667 7.123 G:maj 7.123 7.585 D:maj 7.585 8.071 D:maj 8.071 8.506 G:maj 8.506 8.953 G:maj 8.953 9.415 D:maj 9.415 9.883 D:maj 9.883 10.327 G:maj 10.327 10.777 G:maj 10.777 11.233 D:maj 11.233 11.695 A:min 11.695 12.166 G:maj 12.166 12.595 G:maj 12.595 13.081 D:maj 13.081 13.552 G:maj 13.552 13.999 G:maj 13.999 14.467 G:maj 14.467 14.932 D:maj 14.932 15.397 A:min 15.397 15.841 G:maj 15.841 16.306 G:maj 16.306 16.756 D:maj 16.756 17.233 G:maj 17.233 17.689 C:maj 17.689 18.142 E:min 18.142 18.589 E:maj 18.589 19.075 A:min 19.075 19.546 C:maj 19.546 20.014 C:maj 20.014 20.482 C:maj 20.482 20.947 D:maj 20.947 21.4 D:maj 21.4 21.871 D:maj 21.871 22.327 D:maj 22.327 22.78 G:maj 22.78 23.251 G:maj 23.251 23.701 G:maj 23.701 24.166 D:maj 24.166 24.628 G:maj 24.628 25.087 G:maj 25.087 25.546 G:maj 25.546 26.005 D:maj 26.005 26.482 D:maj 26.482 26.923 G:maj 26.923 27.382 G:maj 27.382 27.841 D:maj 27.841 28.303 D:maj 28.303 28.777 G:maj 28.777 29.218 G:maj 29.218 29.683 D:maj 29.683 30.133 A:min 30.133 30.592 G:maj 30.592 31.03 G:maj 31.03 31.534 D:maj 31.534 32.002 G:maj 32.002 32.431 G:maj 32.431 32.893 G:maj 32.893 33.352 D:maj 33.352 33.802 A:min 33.802 34.267 G:maj 34.267 34.714 G:maj 34.714 35.188 D:maj 35.188 35.635 G:maj 35.635 36.109 E:min 36.109 36.562 E:min 36.562 37.015 E:min 37.015 37.471 A:min 37.471 37.942 C:maj 37.942 38.41 C:maj 38.41 38.875 C:maj 38.875 39.349 A:maj 39.349 39.811 B:maj 39.811 40.27 B:maj 40.27 40.726 B:maj 40.726 41.188 B:maj 41.188 41.668 E:min 41.668 42.133 E:maj 42.133 42.595 E:min 42.595 43.048 E:min 43.048 43.531 C:maj 43.531 43.999 C:maj 43.999 44.461 C:maj 44.461 44.908 C:maj 44.908 45.376 G:maj 45.376 45.835 G:maj 45.835 46.297 G:maj 46.297 46.777 G:min 46.777 47.218 B:maj 47.218 47.683 B:maj 47.683 48.136 B:maj 48.136 48.589 B:maj 48.589 49.054 E:min 49.054 49.513 E:min 49.513 49.984 E:min 49.984 50.461 E:min 50.461 50.911 E:min 50.911 51.361 E:min 51.361 51.826 E:min 51.826 52.264 E:min 52.264 52.75 G:maj 52.75 53.212 G:maj 53.212 53.671 G:maj 53.671 54.136 G:maj 54.136 54.604 G:maj 54.604 55.066 G:maj 55.066 55.528 G:min 55.528 55.957 E:maj 55.957 56.446 C:maj 56.446 56.917 C:maj 56.917 57.373 A:min 57.373 57.835 E:min 57.835 58.303 D:maj 58.303 58.768 D:maj 58.768 59.233 D:maj 59.233 59.707 G:min 59.707 60.172 G:maj 60.172 60.625 G:maj 60.625 61.096 G:maj 61.096 61.558 G:maj 61.558 62.017 E:min 62.017 62.47 E:min 62.47 62.932 E:min 62.932 63.37 E:min 63.37 63.856 C:maj 63.856 64.321 C:maj 64.321 64.798 E:min 64.798 65.257 B:min 65.257 65.725 D:maj 65.725 66.184 D:maj 66.184 66.634 D:maj 66.634 67.093 A:min 67.093 67.573 G:maj 67.573 68.035 G:maj 68.035 68.491 D:maj 68.491 68.965 G:maj 68.965 69.433 G:maj 69.433 69.91 G:maj 69.91 70.369 D:maj 70.369 70.846 D:maj 70.846 71.305 G:maj 71.305 71.779 G:maj 71.779 72.238 D:maj 72.238 72.682 G:maj 72.682 73.162 G:maj 73.162 73.606 G:maj 73.606 74.083 D:maj 74.083 74.53 D:maj 74.53 75.001 G:maj 75.001 75.454 G:maj 75.454 75.916 D:maj 75.916 76.378 G:maj 76.378 76.84 G:maj 76.84 77.308 G:maj 77.308 77.758 D:maj 77.758 78.223 A:min 78.223 78.679 G:maj 78.679 79.132 G:maj 79.132 79.597 D:maj 79.597 80.05 E:min 80.05 80.518 E:min 80.518 80.983 E:min 80.983 81.436 E:maj 81.436 81.883 E:maj 81.883 82.357 C:maj 82.357 82.825 C:maj 82.825 83.287 C:maj 83.287 83.752 D:maj 83.752 84.217 D:maj 84.217 84.685 D:maj 84.685 85.135 D:min 85.135 85.633 E:min 85.633 86.068 G:maj 86.068 86.518 G:maj 86.518 86.98 D:maj 86.98 87.451 G:maj 87.451 87.907 G:maj 87.907 88.372 G:maj 88.372 88.831 D:maj 88.831 89.305 D:maj 89.305 89.761 G:maj 89.761 90.223 G:maj 90.223 90.688 D:maj 90.688 91.153 G:maj 91.153 91.603 G:maj 91.603 92.068 G:maj 92.068 92.527 G:maj 92.527 92.998 D:maj 92.998 93.436 G:maj 93.436 93.907 G:maj 93.907 94.36 D:maj 94.36 94.819 G:maj 94.819 95.284 G:maj 95.284 95.734 G:maj 95.734 96.208 D:maj 96.208 96.679 G:maj 96.679 97.138 G:maj 97.138 97.603 G:maj 97.603 98.065 D:maj 98.065 98.521 G:maj 98.521 98.977 E:min 98.977 99.442 E:min 99.442 99.901 E:min 99.901 100.372 A:min 100.372 100.816 C:maj 100.816 101.278 C:maj 101.278 101.737 C:maj 101.737 102.199 C:maj 102.199 102.649 D:maj 102.649 103.114 D:maj 103.114 103.561 D:maj 103.561 104.041 G:maj 104.041 104.494 G:maj 104.494 104.962 G:maj 104.962 105.418 D:maj 105.418 105.871 G:maj 105.871 106.333 G:maj 106.333 106.789 G:maj 106.789 107.254 D:maj 107.254 107.716 D:maj 107.716 108.181 G:maj 108.181 108.631 G:maj 108.631 109.084 D:maj 109.084 109.543 D:maj 109.543 110.011 G:maj 110.011 110.458 G:maj 110.458 110.917 D:maj 110.917 111.367 A:min 111.367 111.811 G:maj 111.811 112.267 G:maj 112.267 112.756 D:maj 112.756 113.218 G:maj 113.218 113.677 G:maj 113.677 114.142 G:maj 114.142 114.595 D:maj 114.595 115.054 A:min 115.054 115.516 G:maj 115.516 115.96 G:maj 115.96 116.431 D:maj 116.431 116.884 E:min 116.884 117.355 E:min 117.355 117.826 G:maj 117.826 118.285 E:maj 118.285 118.756 E:min 118.756 119.215 C:maj 119.215 119.692 C:maj 119.692 120.151 C:maj 120.151 120.625 B:maj 120.625 121.081 B:maj 121.081 121.525 B:maj 121.525 121.984 B:maj 121.984 122.455 B:maj 122.455 122.932 E:min 122.932 123.4 E:min 123.4 123.853 E:maj 123.853 124.324 D:maj 124.324 124.792 C:maj 124.792 125.263 C:maj 125.263 125.728 C:maj 125.728 126.187 C:maj 126.187 126.643 G:maj 126.643 127.105 G:maj 127.105 127.558 G:maj 127.558 128.041 G:min 128.041 128.497 B:maj 128.497 128.962 B:maj 128.962 129.415 B:maj 129.415 129.868 F:maj 129.868 130.345 E:min 130.345 130.81 E:min 130.81 131.269 E:min 131.269 131.728 E:min 131.728 132.211 E:min 132.211 132.682 E:min 132.682 133.153 E:min 133.153 133.621 N 133.621 134.083 G:maj 134.083 134.563 G:maj 134.563 135.01 G:maj 135.01 135.481 G:min 135.481 135.934 G:maj 135.934 136.399 F:maj 136.399 136.852 G:min 136.852 137.275 G:min 137.275 137.764 C:maj 137.764 138.241 C:maj 138.241 138.706 A:min 138.706 139.144 E:min 139.144 139.621 D:maj 139.621 140.113 D:maj 140.113 140.581 D:maj 140.581 141.064 N 141.064 141.526 G:maj 141.526 141.979 G:maj 141.979 142.441 G:maj 142.441 142.903 G:maj 142.903 143.362 E:min 143.362 143.821 E:min 143.821 144.289 E:maj 144.289 144.73 E:min 144.73 145.228 C:maj 145.228 145.693 C:maj 145.693 146.173 E:min 146.173 146.659 C:maj 146.659 147.106 D:maj 147.106 147.565 D:maj 147.565 148.024 D:maj 148.024 148.51 A:min 148.51 148.99 G:maj 148.99 149.437 G:maj 149.437 149.911 D:maj 149.911 150.376 A:min 150.376 150.853 G:maj 150.853 151.333 G:maj 151.333 151.783 D:maj 151.783 152.23 A:min 152.23 152.713 G:maj 152.713 153.166 G:maj 153.166 153.643 D:maj 153.643 154.12 D:maj 154.12 154.573 G:maj 154.573 155.044 G:maj 155.044 155.509 D:maj 155.509 156.004 D:maj 156.004 156.451 G:maj 156.451 156.922 G:maj 156.922 157.372 D:maj 157.372 157.843 G:maj 157.843 158.311 G:maj 158.311 158.788 G:maj 158.788 159.259 D:maj 159.259 159.733 D:maj 159.733 160.183 G:maj 160.183 160.283 Eb:maj mir_eval-0.8.2/tests/data/chord/est01.lab000066400000000000000000000015141475740344600201240ustar00rootroot000000000000000.000000 2.212063 N 2.212063 6.452063 G:maj 6.452063 12.884082 C:min 12.884082 14.680000 Bb:min 14.680000 26.776054 C:min 26.776054 27.284082 Bb:maj 27.284082 34.932063 C:min 34.932063 37.320000 Bb:maj 37.320000 51.128073 C:min 51.128073 59.996009 C:maj 59.996009 60.244082 F:maj 60.244082 61.556009 Bb:maj 61.556009 63.842086 C:maj 63.842086 66.956009 Bb:maj 66.956009 74.924082 C:min 74.924082 76.376054 A:min 76.376054 81.388027 C:min 81.388027 82.460045 A:min 82.460045 83.020045 Bb:maj 83.020045 87.832018 C:maj 87.832018 90.360000 C:min 90.360000 93.372063 Bb:maj 93.372063 94.124082 C:min 94.124082 97.468027 Bb:maj 97.468027 117.280000 C:min 117.280000 124.094059 Bb:maj 124.094059 141.666032 C:min 141.666032 144.364082 C:maj 144.364082 147.748027 C:min 147.748027 152.658050 Bb:maj 152.658050 179.452063 C:min 179.452063 183.576961 N mir_eval-0.8.2/tests/data/chord/est02.lab000066400000000000000000000245571475740344600201410ustar00rootroot000000000000000.481 0.814 B:min 0.814 1.126 B:min 1.126 1.453 D:maj 1.453 1.756 B:min 1.756 2.053 B:min 2.053 2.35 B:min 2.35 2.668 B:maj 2.668 3.007 E:maj 3.007 3.343 E:maj 3.343 3.634 A:maj 3.634 3.961 D:maj 3.961 4.267 G:maj 4.267 4.546 G:maj 4.546 4.852 D:min 4.852 5.17 B:maj 5.17 5.479 D:min 5.479 5.806 Eb:maj 5.806 6.121 E:maj 6.121 6.445 E:maj 6.445 6.766 B:maj 6.766 7.09 A:maj 7.09 7.417 C#:min 7.417 7.741 A:maj 7.741 8.059 Ab:min 8.059 8.365 B:maj 8.365 8.686 A:maj 8.686 9.016 A:maj 9.016 9.325 E:maj 9.325 9.655 B:min 9.655 9.964 B:maj 9.964 10.297 B:min 10.297 10.618 B:maj 10.618 10.945 B:maj 10.945 11.272 E:maj 11.272 11.602 E:maj 11.602 11.923 B:maj 11.923 12.262 E:maj 12.262 12.595 E:maj 12.595 12.925 E:maj 12.925 13.252 E:maj 13.252 13.579 E:maj 13.579 13.921 C#:min 13.921 14.257 C#:min 14.257 14.587 C#:maj 14.587 14.911 C#:maj 14.911 15.229 C#:min 15.229 15.577 C#:min 15.577 15.904 B:min 15.904 16.231 F:maj 16.231 16.546 A:maj 16.546 16.891 A:maj 16.891 17.224 E:maj 17.224 17.551 A:maj 17.551 17.878 A:maj 17.878 18.202 A:maj 18.202 18.523 A:maj 18.523 18.85 A:maj 18.85 19.198 B:maj 19.198 19.537 B:maj 19.537 19.864 B:maj 19.864 20.173 B:maj 20.173 20.5 B:maj 20.5 20.824 B:min 20.824 21.151 B:maj 21.151 21.472 C#:min 21.472 21.799 E:maj 21.799 22.129 E:maj 22.129 22.456 B:maj 22.456 22.786 E:maj 22.786 23.113 E:maj 23.113 23.446 E:maj 23.446 23.77 E:maj 23.77 24.097 E:maj 24.097 24.409 C#:min 24.409 24.76 C#:maj 24.76 25.09 Ab:maj 25.09 25.414 A:maj 25.414 25.744 C#:min 25.744 26.071 C#:min 26.071 26.395 B:maj 26.395 26.731 A:maj 26.731 27.055 A:maj 27.055 27.406 A:maj 27.406 27.736 E:maj 27.736 28.063 A:maj 28.063 28.393 A:maj 28.393 28.723 A:maj 28.723 29.038 A:maj 29.038 29.365 A:maj 29.365 29.707 B:min 29.707 30.043 B:maj 30.043 30.361 B:maj 30.361 30.676 B:maj 30.676 30.994 B:min 30.994 31.321 B:maj 31.321 31.642 B:maj 31.642 31.921 Eb:maj 31.921 32.275 C#:maj 32.275 32.608 C#:min 32.608 32.929 C#:min 32.929 33.256 C#:min 33.256 33.589 C#:min 33.589 33.919 C#:maj 33.919 34.219 C#:maj 34.219 34.555 C#:min 34.555 34.888 C#:maj 34.888 35.206 C#:maj 35.206 35.521 Eb:min 35.521 35.893 C#:maj 35.893 36.229 C#:min 36.229 36.565 C#:min 36.565 36.904 B:maj 36.904 37.231 B:maj 37.231 37.567 A:maj 37.567 37.888 A:maj 37.888 38.221 A:maj 38.221 38.539 A:maj 38.539 38.866 A:maj 38.866 39.196 A:maj 39.196 39.529 A:maj 39.529 39.835 B:maj 39.835 40.177 B:maj 40.177 40.495 B:maj 40.495 40.807 B:maj 40.807 41.152 B:maj 41.152 41.479 B:maj 41.479 41.815 B:maj 41.815 42.127 C#:min 42.127 42.448 Eb:maj 42.448 42.778 E:maj 42.778 43.108 E:maj 43.108 43.435 E:maj 43.435 43.753 E:maj 43.753 44.071 E:maj 44.071 44.392 E:maj 44.392 44.719 E:maj 44.719 45.04 A:maj 45.04 45.367 C#:min 45.367 45.697 C#:min 45.697 46.018 C#:min 46.018 46.33 C#:min 46.33 46.651 C#:min 46.651 46.984 C#:maj 46.984 47.302 C#:min 47.302 47.629 B:min 47.629 47.965 A:maj 47.965 48.316 A:maj 48.316 48.631 A:maj 48.631 48.946 A:maj 48.946 49.267 B:maj 49.267 49.603 B:maj 49.603 49.924 C#:maj 49.924 50.257 Eb:maj 50.257 50.578 E:maj 50.578 50.902 E:maj 50.902 51.229 E:maj 51.229 51.547 E:maj 51.547 51.862 E:maj 51.862 52.186 E:maj 52.186 52.519 E:maj 52.519 52.837 E:maj 52.837 53.158 E:maj 53.158 53.491 E:maj 53.491 53.821 E:maj 53.821 54.148 E:maj 54.148 54.484 E:maj 54.484 54.817 E:maj 54.817 55.147 B:maj 55.147 55.462 E:maj 55.462 55.789 C#:min 55.789 56.137 C#:min 56.137 56.473 Ab:maj 56.473 56.8 C#:maj 56.8 57.133 C#:min 57.133 57.451 C#:min 57.451 57.778 B:maj 57.778 58.105 B:min 58.105 58.444 A:maj 58.444 58.783 A:maj 58.783 59.101 A:maj 59.101 59.44 A:maj 59.44 59.773 A:maj 59.773 60.1 A:maj 60.1 60.415 A:maj 60.415 60.754 A:maj 60.754 61.093 B:min 61.093 61.423 B:min 61.423 61.741 Gb:maj 61.741 62.062 B:maj 62.062 62.377 B:maj 62.377 62.707 C#:min 62.707 63.031 E:maj 63.031 63.358 B:maj 63.358 63.688 E:maj 63.688 64.012 E:maj 64.012 64.345 E:maj 64.345 64.669 E:maj 64.669 65.008 E:maj 65.008 65.332 E:maj 65.332 65.656 E:maj 65.656 65.965 E:maj 65.965 66.31 C#:min 66.31 66.637 C#:min 66.637 66.967 Ab:maj 66.967 67.297 C#:maj 67.297 67.633 C#:min 67.633 67.963 C#:min 67.963 68.278 B:maj 68.278 68.605 G:maj 68.605 68.941 A:maj 68.941 69.277 A:maj 69.277 69.598 A:maj 69.598 69.916 A:maj 69.916 70.24 A:maj 70.24 70.567 A:maj 70.567 70.882 C#:min 70.882 71.203 E:maj 71.203 71.542 B:maj 71.542 71.866 B:maj 71.866 72.178 B:maj 72.178 72.484 C#:min 72.484 72.802 Eb:maj 72.802 73.12 Eb:maj 73.12 73.441 B:maj 73.441 73.762 A:maj 73.762 74.095 C#:min 74.095 74.431 C#:min 74.431 74.758 C#:min 74.758 75.085 C#:min 75.085 75.427 C#:maj 75.427 75.751 C#:maj 75.751 76.069 C#:maj 76.069 76.393 C:min 76.393 76.726 C#:maj 76.726 77.053 C#:maj 77.053 77.38 Eb:min 77.38 77.71 C#:maj 77.71 78.043 C#:min 78.043 78.376 C#:min 78.376 78.697 B:maj 78.697 79.024 B:maj 79.024 79.345 A:maj 79.345 79.672 A:maj 79.672 79.996 A:maj 79.996 80.326 A:maj 80.326 80.644 A:maj 80.644 80.974 A:maj 80.974 81.295 A:maj 81.295 81.613 A:maj 81.613 81.943 B:maj 81.943 82.27 B:maj 82.27 82.603 B:maj 82.603 82.936 B:maj 82.936 83.254 Eb:min 83.254 83.584 B:maj 83.584 83.893 C#:min 83.893 84.214 Eb:maj 84.214 84.55 E:maj 84.55 84.877 E:maj 84.877 85.195 E:maj 85.195 85.51 E:maj 85.51 85.828 E:maj 85.828 86.149 E:maj 86.149 86.47 E:maj 86.47 86.803 E:maj 86.803 87.139 C#:min 87.139 87.475 C#:min 87.475 87.796 C#:maj 87.796 88.102 C#:min 88.102 88.417 C#:min 88.417 88.75 C#:maj 88.75 89.068 B:maj 89.068 89.386 Bb:maj 89.386 89.734 A:maj 89.734 90.073 A:maj 90.073 90.391 E:maj 90.391 90.709 Eb:maj 90.709 91.033 B:min 91.033 91.36 B:min 91.36 91.681 Eb:maj 91.681 91.996 B:maj 91.996 92.323 E:maj 92.323 92.647 E:maj 92.647 92.959 E:maj 92.959 93.28 E:maj 93.28 93.625 E:maj 93.625 93.937 E:maj 93.937 94.258 E:maj 94.258 94.597 E:min 94.597 94.933 A:maj 94.933 95.257 A:maj 95.257 95.575 E:maj 95.575 95.905 E:maj 95.905 96.235 A:maj 96.235 96.544 A:maj 96.544 96.865 E:maj 96.865 97.177 B:maj 97.177 97.501 Gb:maj 97.501 97.822 Gb:maj 97.822 98.137 C#:min 98.137 98.461 Gb:maj 98.461 98.779 Gb:maj 98.779 99.109 Eb:min 99.109 99.439 Eb:min 99.439 99.757 B:maj 99.757 100.081 D:maj 100.081 100.405 D:maj 100.405 100.717 A:maj 100.717 101.056 C#:maj 101.056 101.374 D:min 101.374 101.689 D:maj 101.689 102.007 A:maj 102.007 102.331 B:min 102.331 102.646 E:min 102.646 102.97 E:maj 102.97 103.294 E:min 103.294 103.612 E:min 103.612 103.933 E:maj 103.933 104.242 C#:min 104.242 104.563 E:maj 104.563 104.89 E:min 104.89 105.223 A:maj 105.223 105.553 A:maj 105.553 105.874 E:maj 105.874 106.195 A:maj 106.195 106.507 A:maj 106.507 106.825 A:maj 106.825 107.14 E:maj 107.14 107.47 A:maj 107.47 107.797 Gb:maj 107.797 108.112 Gb:maj 108.112 108.424 C#:min 108.424 108.742 Gb:maj 108.742 109.06 Gb:maj 109.06 109.378 Gb:maj 109.378 109.696 E:maj 109.696 110.002 N 110.002 110.314 D:min 110.314 110.659 D:maj 110.659 110.992 D:maj 110.992 111.307 D:min 111.307 111.631 E:maj 111.631 111.946 E:maj 111.946 112.276 E:min 112.276 112.597 B:maj 112.597 112.909 A:maj 112.909 113.23 A:maj 113.23 113.536 A:maj 113.536 113.857 A:maj 113.857 114.172 B:maj 114.172 114.49 B:maj 114.49 114.808 B:min 114.808 115.144 B:maj 115.144 115.474 E:maj 115.474 115.798 E:min 115.798 116.143 B:maj 116.143 116.464 E:maj 116.464 116.794 E:maj 116.794 117.115 E:maj 117.115 117.442 E:maj 117.442 117.76 A:maj 117.76 118.096 C#:min 118.096 118.423 C#:min 118.423 118.756 Ab:maj 118.756 119.074 C#:min 119.074 119.41 C#:min 119.41 119.737 C#:min 119.737 120.067 Ab:min 120.067 120.382 B:min 120.382 120.727 A:maj 120.727 121.054 A:maj 121.054 121.363 A:maj 121.363 121.699 A:maj 121.699 122.026 A:maj 122.026 122.356 A:maj 122.356 122.677 E:maj 122.677 122.989 A:maj 122.989 123.325 B:min 123.325 123.658 B:maj 123.658 123.97 C#:min 123.97 124.273 C#:maj 124.273 124.597 Eb:maj 124.597 124.939 B:maj 124.939 125.26 C#:min 125.26 125.584 Eb:maj 125.584 125.92 E:maj 125.92 126.247 E:maj 126.247 126.571 E:maj 126.571 126.889 E:maj 126.889 127.222 E:maj 127.222 127.543 E:maj 127.543 127.867 E:maj 127.867 128.188 Eb:maj 128.188 128.521 C#:min 128.521 128.854 C#:min 128.854 129.184 Ab:maj 129.184 129.505 C#:maj 129.505 129.841 C#:min 129.841 130.153 C#:min 130.153 130.471 B:maj 130.471 130.786 A:maj 130.786 131.122 A:maj 131.122 131.452 A:maj 131.452 131.773 A:maj 131.773 132.1 A:maj 132.1 132.427 A:maj 132.427 132.748 A:maj 132.748 133.069 A:maj 133.069 133.387 C#:min 133.387 133.723 B:maj 133.723 134.053 B:maj 134.053 134.368 Gb:maj 134.368 134.68 B:maj 134.68 134.989 B:maj 134.989 135.343 B:maj 135.343 135.652 C#:min 135.652 135.97 B:maj 135.97 136.288 C#:min 136.288 136.618 C#:min 136.618 136.951 C#:min 136.951 137.281 C#:min 137.281 137.608 C#:min 137.608 137.923 C#:maj 137.923 138.262 C#:maj 138.262 138.589 C:min 138.589 138.907 C#:min 138.907 139.225 C#:min 139.225 139.555 C#:min 139.555 139.873 C#:maj 139.873 140.218 C#:maj 140.218 140.554 C#:min 140.554 140.875 B:maj 140.875 141.223 B:maj 141.223 141.553 A:maj 141.553 141.88 A:maj 141.88 142.21 A:maj 142.21 142.537 A:maj 142.537 142.855 A:maj 142.855 143.167 A:maj 143.167 143.491 A:maj 143.491 143.866 B:min 143.866 144.175 B:maj 144.175 144.484 B:maj 144.484 144.805 B:maj 144.805 145.132 B:maj 145.132 145.447 B:maj 145.447 145.768 B:maj 145.768 146.083 D:min 146.083 146.407 Eb:maj 146.407 146.734 E:maj 146.734 147.061 E:min 147.061 147.385 B:maj 147.385 147.7 E:maj 147.7 148.015 E:maj 148.015 148.348 E:maj 148.348 148.669 Eb:maj 148.669 148.993 A:maj 148.993 149.317 C#:min 149.317 149.65 C#:min 149.65 149.971 C#:maj 149.971 150.286 C#:maj 150.286 150.601 C#:min 150.601 150.928 C#:maj 150.928 151.249 Eb:min 151.249 151.57 B:min 151.57 151.9 A:maj 151.9 152.23 A:maj 152.23 152.542 A:maj 152.542 152.866 A:maj 152.866 153.202 B:maj 153.202 153.529 B:maj 153.529 153.847 B:min 153.847 154.156 B:maj 154.156 154.456 E:maj 154.456 154.792 C#:min 154.792 155.092 Eb:min 155.092 155.422 C#:min 155.422 155.731 C#:min 155.731 156.037 C#:min 156.037 156.343 B:maj 156.343 156.67 B:min 156.67 157.009 A:maj 157.009 157.336 A:maj 157.336 157.657 C#:min 157.657 157.975 E:maj 157.975 158.278 B:min 158.278 158.605 B:maj 158.605 158.92 B:maj 158.92 159.232 B:maj 159.232 159.544 C#:min 159.544 159.856 C#:min 159.856 160.18 C#:min 160.18 160.495 C#:min 160.495 160.807 C#:min 160.807 161.128 Eb:min 161.128 161.437 B:maj 161.437 161.761 B:maj 161.761 162.088 A:maj 162.088 162.418 A:maj 162.418 162.739 C#:min 162.739 163.054 A:maj 163.054 163.378 B:maj 163.378 163.714 B:maj 163.714 164.032 B:maj 164.032 164.35 E:maj 164.35 164.701 E:maj 164.701 165.019 E:maj 165.019 165.34 E:maj 165.34 165.658 E:maj 165.658 165.976 E:min 165.976 166.076 C#:maj mir_eval-0.8.2/tests/data/chord/est03.lab000066400000000000000000000173251475740344600201350ustar00rootroot000000000000000.000000 1.368073 N 1.368073 2.408073 D:maj 2.408073 3.730068 D:min 3.730068 4.568073 F:maj 4.568073 5.080000 G:min 5.080000 5.832018 D:min 5.832018 6.892063 E:maj 6.892063 7.664036 D:min 7.664036 8.236009 B:min 8.236009 10.328073 Bb:maj 10.328073 14.324082 A:maj 14.324082 16.364082 N 16.364082 17.432018 A:min 17.432018 20.080000 N 20.080000 23.232018 A:min 23.232018 25.560000 N 25.560000 30.024036 A:min 30.024036 31.088073 D:min 31.088073 32.120000 F:maj 32.120000 32.664036 G:min 32.664036 35.998005 A:min 35.998005 36.554014 A:maj 36.554014 50.696054 D:min 50.696054 51.712018 F:maj 51.712018 52.740045 C:maj 52.740045 53.848073 Bb:maj 53.848073 54.484082 D#:maj 54.484082 65.988027 E:maj 65.988027 81.064036 A:min 81.064036 82.076009 D:min 82.076009 83.104036 F:maj 83.104036 83.616054 G:maj 83.616054 87.466032 A:min 87.466032 101.492063 D:min 101.492063 102.492063 F:maj 102.492063 103.008073 C:maj 103.008073 103.524082 F:maj 103.524082 104.552018 Bb:maj 104.552018 105.208073 D#:maj 105.208073 111.310023 E:maj 111.310023 112.636009 F:min 112.636009 115.784036 E:maj 115.784036 117.656054 N 117.656054 118.950023 D:maj 118.950023 120.240000 D:min 120.240000 121.320000 F:maj 121.320000 122.764082 D:min 122.764082 124.028027 E:maj 124.028027 124.816054 C:maj 124.816054 125.220045 B:maj 125.220045 127.732063 Bb:maj 127.732063 130.288073 A:maj 130.288073 131.312018 D:maj 131.312018 132.644082 D:min 132.644082 133.464036 F:maj 133.464036 135.160000 D:min 135.160000 136.780045 E:maj 136.780045 137.160000 C:maj 137.160000 137.572063 B:maj 137.572063 140.032018 Bb:maj 140.032018 145.424036 A:maj 145.424036 147.144036 A:min 147.144036 148.022041 G:maj 148.022041 149.456054 A:min 149.456054 150.278005 G:maj 150.278005 160.276009 A:min 160.276009 161.300045 C:maj 161.300045 162.368073 D:maj 162.368073 163.396009 F:maj 163.396009 163.956009 D:min 163.956009 164.464036 C:maj 164.464036 167.940045 A:min 167.940045 182.620045 D:min 182.620045 184.712018 F:maj 184.712018 185.792018 Bb:maj 185.792018 186.392018 D#:maj 186.392018 197.472018 E:maj 197.472018 199.200000 N 199.200000 200.574059 D:maj 200.574059 201.662041 D:min 201.662041 203.012063 F:maj 203.012063 203.930068 G:min 203.930068 204.220045 D:min 204.220045 205.576054 E:maj 205.576054 206.674014 F:min 206.674014 209.140045 Bb:maj 209.140045 211.228027 A:maj 211.228027 214.156009 D:min 214.156009 215.004082 F:maj 215.004082 216.664036 D:min 216.664036 217.828027 E:maj 217.828027 218.592018 D:min 218.592018 219.138050 B:min 219.138050 221.592018 Bb:maj 221.592018 225.392018 A:maj 225.392018 227.580045 A:min 227.580045 228.366077 G:maj 228.366077 240.024036 A:min 240.024036 241.052063 C:maj 241.052063 242.072018 D:min 242.072018 243.088073 F:maj 243.088073 243.872018 D:maj 243.872018 246.970068 A:min 246.970068 247.428027 A:maj 247.428027 261.528073 D:min 261.528073 262.548027 F:maj 262.548027 263.588027 C:maj 263.588027 264.372063 Bb:maj 264.372063 265.124082 D:min 265.124082 276.228027 E:maj 276.228027 277.920000 A:min 277.920000 279.148027 D:maj 279.148027 280.560000 D:min 280.560000 281.772063 F:maj 281.772063 282.400000 G:min 282.400000 282.992018 D:min 282.992018 284.590023 E:maj 284.590023 285.170068 C:maj 285.170068 285.440000 B:maj 285.440000 287.072018 Bb:maj 287.072018 287.500045 C:maj 287.500045 287.920000 D:min 287.920000 290.412063 A:maj 290.412063 292.908027 D:min 292.908027 294.056054 F:maj 294.056054 294.988027 G:maj 294.988027 295.400000 A:maj 295.400000 296.972063 E:maj 296.972063 297.554014 C:maj 297.554014 297.844082 B:maj 297.844082 299.536054 Bb:maj 299.536054 299.952018 C:maj 299.952018 300.360000 D:min 300.360000 302.856054 A:maj 302.856054 304.200000 D:maj 304.200000 305.450068 E:maj 305.450068 306.812063 F:maj 306.812063 307.638005 G:maj 307.638005 307.912018 A:maj 307.912018 309.512018 E:maj 309.512018 310.004082 C:maj 310.004082 310.408073 B:min 310.408073 312.072018 Bb:maj 312.072018 312.496054 C:maj 312.496054 312.912018 D:min 312.912018 315.344036 A:maj 315.344036 316.870023 D:min 316.870023 317.872018 E:maj 317.872018 319.220045 F:maj 319.220045 320.058050 G:maj 320.058050 320.340045 A:maj 320.340045 321.956009 E:maj 321.956009 322.404082 C:maj 322.404082 322.828027 B:maj 322.828027 324.464036 Bb:maj 324.464036 324.888073 C:maj 324.888073 325.332063 D:min 325.332063 327.836009 A:maj 327.836009 329.148027 D:maj 329.148027 330.268027 E:maj 330.268027 331.704036 F:maj 331.704036 332.526077 G:maj 332.526077 332.828027 A:maj 332.828027 334.572063 E:maj 334.572063 334.946032 C:maj 334.946032 335.320000 B:maj 335.320000 337.036009 Bb:maj 337.036009 337.544036 C:maj 337.544036 337.828027 D:min 337.828027 340.372063 A:maj 340.372063 341.664036 D:maj 341.664036 342.902041 E:maj 342.902041 344.000000 F:maj 344.000000 344.844082 G:maj 344.844082 345.404082 D:min 345.404082 347.080000 E:maj 347.080000 347.484082 C:maj 347.484082 348.028027 B:maj 348.028027 350.044082 Bb:maj 350.044082 350.492063 D:min 350.492063 353.012063 A:maj 353.012063 354.408073 D:maj 354.408073 355.476009 E:min 355.476009 356.690068 F:maj 356.690068 357.536054 G:maj 357.536054 358.012063 A:maj 358.012063 359.198005 E:maj 359.198005 359.740045 D:min 359.740045 360.016054 C:maj 360.016054 360.464036 B:maj 360.464036 362.140045 Bb:maj 362.140045 362.458050 C:maj 362.458050 363.026032 D:min 363.026032 365.602086 A:maj 365.602086 366.808073 D:maj 366.808073 367.832018 D:min 367.832018 369.284082 F:maj 369.284082 370.472018 G:maj 370.472018 371.972063 E:maj 371.972063 372.572063 C:maj 372.572063 372.996009 B:min 372.996009 374.704036 Bb:maj 374.704036 374.982041 C:maj 374.982041 375.544036 D:min 375.544036 378.096054 A:maj 378.096054 379.312018 D:maj 379.312018 380.492063 E:maj 380.492063 381.884082 F:maj 381.884082 382.586032 G:maj 382.586032 383.070023 D:min 383.070023 384.788027 E:maj 384.788027 385.280000 C:maj 385.280000 385.716009 B:maj 385.716009 387.408073 Bb:maj 387.408073 388.044082 C:maj 388.044082 390.600000 A:maj 390.600000 392.284082 D:min 392.284082 393.372063 E:maj 393.372063 394.652063 F:maj 394.652063 395.472018 G:maj 395.472018 395.956009 D:min 395.956009 397.572063 E:maj 397.572063 397.988027 C:maj 397.988027 398.408073 B:maj 398.408073 400.948027 Bb:maj 400.948027 403.288073 A:maj 403.288073 404.748027 D:min 404.748027 406.004082 E:maj 406.004082 407.276009 F:maj 407.276009 408.372063 G:maj 408.372063 410.190023 E:maj 410.190023 410.736054 C:maj 410.736054 411.008073 B:maj 411.008073 412.656054 Bb:maj 412.656054 413.160000 C:maj 413.160000 413.576054 D:min 413.576054 416.152018 A:maj 416.152018 417.306032 D:maj 417.306032 418.740045 D:min 418.740045 420.086077 F:maj 420.086077 420.872018 G:maj 420.872018 421.336054 D:min 421.336054 423.012063 E:maj 423.012063 423.532063 C:maj 423.532063 423.830023 B:maj 423.830023 425.576054 Bb:maj 425.576054 425.992018 C:maj 425.992018 426.436009 D:min 426.436009 428.968073 A:maj 428.968073 430.300045 D:min 430.300045 431.508027 E:maj 431.508027 432.866032 F:maj 432.866032 433.584036 G:min 433.584036 434.104036 D:min 434.104036 435.640000 E:maj 435.640000 436.124082 C:maj 436.124082 436.584036 B:min 436.584036 438.260045 Bb:maj 438.260045 438.526077 C:maj 438.526077 439.090068 D:min 439.090068 440.816054 A:maj 440.816054 442.968073 D:min 442.968073 444.092063 E:maj 444.092063 445.484082 F:maj 445.484082 446.276009 G:min 446.276009 446.814059 A:maj 446.814059 448.288073 E:maj 448.288073 449.072018 E:min 449.072018 449.322086 B:maj 449.322086 451.244082 Bb:maj 451.244082 451.836009 D:min 451.836009 454.404082 A:maj 454.404082 455.818050 D:min 455.818050 456.846077 E:maj 456.846077 458.212063 F:maj 458.212063 459.020045 G:maj 459.020045 459.550023 D:min 459.550023 461.128073 E:maj 461.128073 461.660045 C:maj 461.660045 462.226032 B:min 462.226032 463.824036 Bb:maj 463.824036 464.240000 C:maj 464.240000 464.632018 D:min 464.632018 465.366077 A:maj 465.366077 469.182404 N mir_eval-0.8.2/tests/data/chord/est04.lab000066400000000000000000000016121475740344600201260ustar00rootroot000000000000000.000000 0.996009 N 0.996009 5.220045 F:maj 5.220045 8.168073 C:maj 8.168073 24.356009 G:maj 24.356009 39.532063 C:maj 39.532063 41.548027 F:maj 41.548027 61.232018 G:maj 61.232018 65.144036 C:maj 65.144036 67.136054 G:maj 67.136054 68.648073 F:maj 68.648073 73.064036 C:maj 73.064036 75.016054 E:min7 75.016054 80.936054 F:maj7 80.936054 84.868027 C:maj 84.868027 86.828027 G:maj 86.828027 88.320000 F:maj 88.320000 91.284082 C:maj 91.284082 92.764082 F:maj 92.764082 94.736054 G:maj 94.736054 96.720000 F:maj 96.720000 117.712018 G:maj 117.712018 124.216054 C:maj 124.216054 125.544036 F:maj 125.544036 130.156009 C:maj 130.156009 132.104036 E:min7 132.104036 136.516009 F:maj7 136.516009 141.904036 C:maj 141.904036 143.884082 G:maj 143.884082 145.348027 F:maj 145.348027 149.800091 C:maj 149.800091 151.768073 E:min7 151.768073 156.208073 F:maj7 156.208073 163.628027 C:maj 163.628027 168.437551 B:aug mir_eval-0.8.2/tests/data/chord/est05.lab000066400000000000000000000102411475740344600201250ustar00rootroot000000000000000.331 1.198 Ab:maj 1.198 1.891 Ab:maj 1.891 2.704 Eb:maj 2.704 3.394 Ab:maj 3.394 4.09 Ab:maj 4.09 4.768 Ab:maj 4.768 5.449 Bb:min 5.449 6.139 Ab:maj 6.139 6.826 Ab:maj 6.826 7.513 Ab:maj 7.513 8.233 C#:maj 8.233 8.947 Bb:min 8.947 9.652 Bb:min 9.652 10.342 Bb:maj 10.342 11.029 C#:maj 11.029 11.74 Eb:maj 11.74 12.424 Eb:maj 12.424 13.117 Ab:maj 13.117 13.813 C#:min 13.813 14.521 Bb:maj 14.521 15.22 Bb:maj 15.22 15.919 Bb:maj 15.919 16.627 F:min 16.627 17.335 Eb:maj 17.335 18.037 Eb:maj 18.037 18.757 Eb:maj 18.757 19.465 F:min 19.465 20.167 Bb:min 20.167 20.842 Bb:min 20.842 21.55 Ab:maj 21.55 22.24 Ab:maj 22.24 22.942 Eb:maj 22.942 23.635 Eb:maj 23.635 24.331 Ab:maj 24.331 25.027 Ab:maj 25.027 25.729 F:min 25.729 26.413 Bb:min 26.413 27.106 Bb:min 27.106 27.805 C#:maj 27.805 28.507 Ab:maj 28.507 29.206 Ab:maj 29.206 29.902 Ab:maj 29.902 30.598 Ab:maj 30.598 31.297 Ab:maj 31.297 31.987 Ab:maj 31.987 32.686 Ab:maj 32.686 33.37 C#:maj 33.37 34.087 F:min 34.087 34.774 Bb:min 34.774 35.467 Bb:maj 35.467 36.163 F:min 36.163 36.862 Eb:maj 36.862 37.561 Eb:maj 37.561 38.257 Ab:maj 38.257 38.965 C#:maj 38.965 39.673 Bb:min 39.673 40.36 Bb:min 40.36 41.053 F:maj 41.053 41.746 F:min 41.746 42.457 Eb:maj 42.457 43.144 Eb:maj 43.144 43.846 Ab:maj 43.846 44.536 F:min 44.536 45.247 Ab:maj 45.247 45.937 Bb:maj 45.937 46.648 Ab:maj 46.648 47.347 Ab:maj 47.347 48.046 Eb:maj 48.046 48.754 Eb:maj 48.754 49.462 Ab:maj 49.462 50.158 Ab:maj 50.158 50.875 Bb:maj 50.875 51.58 Bb:min 51.58 52.276 Bb:min 52.276 52.975 C#:maj 52.975 53.677 Ab:maj 53.677 54.379 Ab:maj 54.379 55.081 Ab:maj 55.081 55.801 C#:maj 55.801 56.497 Ab:maj 56.497 57.199 Ab:maj 57.199 57.895 Ab:maj 57.895 58.594 Ab:maj 58.594 59.308 Ab:maj 59.308 60.019 Ab:maj 60.019 60.733 F:min 60.733 61.435 C#:maj 61.435 62.143 Ab:maj 62.143 62.833 Ab:maj 62.833 63.553 Ab:maj 63.553 64.249 Ab:maj 64.249 64.945 Ab:maj 64.945 65.635 C#:maj 65.635 66.346 C:maj 66.346 67.051 Ab:maj 67.051 67.759 Ab:maj 67.759 68.452 Ab:maj 68.452 69.163 Eb:maj 69.163 69.862 Eb:maj 69.862 70.567 Ab:maj 70.567 71.278 C#:maj 71.278 71.989 Bb:maj 71.989 72.688 Bb:maj 72.688 73.402 Bb:maj 73.402 74.098 F:maj 74.098 74.812 Eb:maj 74.812 75.517 Eb:maj 75.517 76.231 Ab:maj 76.231 76.936 C#:min 76.936 77.656 Bb:min 77.656 78.355 Bb:min 78.355 79.06 Bb:maj 79.06 79.741 F:maj 79.741 80.464 Eb:maj 80.464 81.166 Eb:maj 81.166 81.874 F:maj 81.874 82.573 F:min 82.573 83.302 Ab:maj 83.302 84.004 Bb:min 84.004 84.727 Ab:maj 84.727 85.426 Ab:maj 85.426 86.131 Eb:maj 86.131 86.827 Eb:maj 86.827 87.529 Ab:maj 87.529 88.234 Ab:maj 88.234 88.951 Bb:min 88.951 89.65 Bb:maj 89.65 90.361 Bb:min 90.361 91.069 C#:maj 91.069 91.78 Ab:maj 91.78 92.476 Ab:maj 92.476 93.178 Ab:maj 93.178 93.892 Ab:maj 93.892 94.576 Ab:maj 94.576 95.293 Ab:maj 95.293 96.004 Ab:maj 96.004 96.706 Ab:maj 96.706 97.417 C#:maj 97.417 98.116 Ab:maj 98.116 98.824 C#:maj 98.824 99.526 C#:maj 99.526 100.24 Ab:maj 100.24 100.927 Ab:maj 100.927 101.632 Ab:maj 101.632 102.328 Ab:maj 102.328 103.039 N 103.039 103.732 C#:maj 103.732 104.431 C#:maj 104.431 105.121 C#:maj 105.121 105.817 Eb:maj 105.817 106.513 Ab:maj 106.513 107.215 Eb:maj 107.215 107.914 Eb:maj 107.914 108.613 Ab:maj 108.613 109.321 C#:maj 109.321 110.035 Bb:maj 110.035 110.734 Bb:min 110.734 111.43 Bb:min 111.43 112.12 F:min 112.12 112.834 Eb:maj 112.834 113.521 Eb:maj 113.521 114.226 Ab:maj 114.226 114.925 C#:min 114.925 115.636 Bb:maj 115.636 116.332 Bb:min 116.332 117.019 Bb:maj 117.019 117.733 F:min 117.733 118.432 Eb:maj 118.432 119.125 Eb:maj 119.125 119.839 Eb:maj 119.839 120.547 F:min 120.547 121.258 Ab:maj 121.258 121.966 Bb:min 121.966 122.671 Ab:maj 122.671 123.361 Ab:maj 123.361 124.072 Eb:maj 124.072 124.771 Eb:maj 124.771 125.476 Ab:maj 125.476 126.202 Ab:maj 126.202 126.913 F:min 126.913 127.612 Bb:maj 127.612 128.311 Bb:min 128.311 129.022 C#:maj 129.022 129.721 Ab:maj 129.721 130.426 Ab:maj 130.426 131.146 Ab:maj 131.146 131.836 C#:maj 131.836 132.538 Ab:maj 132.538 133.243 Ab:maj 133.243 133.954 Ab:maj 133.954 134.65 Ab:maj 134.65 135.358 Ab:maj 135.358 136.054 C#:maj 136.054 136.759 Ab:maj 136.759 137.452 C#:maj 137.452 138.166 Ab:maj 138.166 138.859 Ab:maj 138.859 139.567 Ab:maj 139.567 140.272 Ab:maj 140.272 140.98 Ab:maj 140.98 141.08 Eb:maj mir_eval-0.8.2/tests/data/chord/est06.lab000066400000000000000000000055611475740344600201370ustar00rootroot000000000000000.000000 0.024036 N 0.024036 2.164082 D:min7 2.164082 3.844082 F:maj 3.844082 5.708027 C:maj 5.708027 7.888073 G:maj 7.888073 9.316009 D:min 9.316009 11.464036 G:maj 11.464036 15.300045 C:maj 15.300045 16.976054 D:min 16.976054 18.888073 G:maj 18.888073 19.852063 C:maj 19.852063 20.324082 F:maj 20.324082 23.192018 C:maj 23.192018 24.628027 D:min 24.628027 27.028027 G:7 27.028027 30.636009 C:maj 30.636009 32.540045 D:min 32.540045 34.452063 Bb:maj 34.452063 34.680000 F:maj 34.680000 37.544036 G:maj 37.544036 40.176054 D:min7 40.176054 42.132063 F:maj 42.132063 43.788027 C:maj 43.788027 45.440000 G:maj 45.440000 46.228027 C:maj 46.228027 47.840000 D:min7 47.840000 49.760000 F:maj7 49.760000 51.184036 C:maj 51.184036 51.660045 D:min7 51.660045 53.796009 G:maj 53.796009 55.488073 D:min7 55.488073 57.408073 F:maj7 57.408073 57.656054 D:min7 57.656054 59.328073 C:maj 59.328073 60.980045 G:maj 60.980045 63.236009 D:min7 63.236009 65.048073 Bb:maj 65.048073 65.284082 F:maj 65.284082 68.904036 G:maj 68.904036 70.796009 D:min7 70.796009 72.956009 G:maj 72.956009 76.808073 C:maj 76.808073 78.496054 D:min 78.496054 80.416054 G:maj 80.416054 84.432018 C:maj 84.432018 86.128073 D:min 86.128073 88.028027 G:maj 88.028027 92.136054 C:maj 92.136054 93.568073 D:min 93.568073 95.684082 Bb:maj 95.684082 99.508027 G:maj 99.508027 99.740045 C:maj 99.740045 101.400000 D:min7 101.400000 103.320000 F:maj7 103.320000 105.216054 C:maj 105.216054 107.364082 G:maj 107.364082 108.808073 D:min 108.808073 110.932063 F:maj7 110.932063 112.396009 C:maj 112.396009 112.884082 D:min7 112.884082 114.500045 G:maj 114.500045 117.164082 D:min7 117.164082 118.092063 F:maj7 118.092063 118.564082 D:min7 118.564082 120.492063 C:maj 120.492063 122.616054 G:maj 122.616054 124.048073 D:min 124.048073 124.288073 C:maj 124.288073 126.480000 Bb:maj 126.480000 130.232018 G:maj 130.232018 131.676009 D:min 131.676009 134.060045 G:maj 134.060045 137.896054 C:maj 137.896054 139.332063 D:min 139.332063 141.476009 G:maj 141.476009 145.304036 C:maj 145.304036 147.228027 D:min7 147.228027 149.128073 G:maj 149.128073 149.844082 C:maj 149.844082 151.028027 A:min7 151.028027 152.488073 C:maj 152.488073 153.200000 A:min 153.200000 154.868027 D:min 154.868027 156.764082 Bb:maj 156.764082 160.364082 G:maj 160.364082 162.528073 D:min7 162.528073 164.416054 F:maj7 164.416054 165.852063 C:maj 165.852063 166.092063 D:min7 166.092063 167.764082 G:maj 167.764082 168.468027 C:maj 168.468027 170.132063 D:min7 170.132063 172.284082 F:maj7 172.284082 173.488073 C:maj 173.488073 173.716009 D:min 173.716009 176.084082 G:maj 176.084082 177.784036 D:min7 177.784036 179.748027 F:maj 179.748027 181.420045 C:maj 181.420045 183.276009 G:maj 183.276009 185.412063 D:min7 185.412063 187.544036 Bb:maj 187.544036 191.100045 G:maj 191.100045 191.348027 C:maj 191.348027 193.036009 D:min 193.036009 194.712018 Bb:maj 194.712018 204.848073 F:maj 204.848073 204.939320 N mir_eval-0.8.2/tests/data/chord/est07.lab000066400000000000000000000073051475740344600201360ustar00rootroot000000000000000.000000 0.116009 N 0.116009 1.928073 D#:maj 1.928073 3.572063 Ab:maj 3.572063 5.692063 D#:maj 5.692063 7.572063 Ab:maj 7.572063 8.280000 D#:maj 8.280000 10.304036 F:min 10.304036 11.268027 Ab:maj7 11.268027 12.608073 D:min7 12.608073 14.840000 Bb:maj6 14.840000 16.628027 C:min 16.628027 16.880000 F:maj 16.880000 17.112018 D#:maj 17.112018 18.472018 C:min7 18.472018 18.920091 A:min7 18.920091 19.352018 C:min7 19.352018 20.308027 F:7 20.308027 21.156009 Ab:maj7 21.156009 22.044082 Ab:maj6 22.044082 23.912018 D#:maj 23.912018 26.120000 Bb:7 26.120000 27.432018 G:7 27.432018 28.500045 C:min 28.500045 29.196009 Bb:maj 29.196009 30.956009 D#:maj 30.956009 32.748027 F:min 32.748027 34.060045 Ab:maj 34.060045 34.488073 Ab:maj6 34.488073 35.136054 D:min7 35.136054 36.668027 Bb:maj 36.668027 38.036009 D:dim 38.036009 40.120000 D#:maj 40.120000 41.740045 Ab:maj7 41.740045 42.860045 D:min7 42.860045 43.528073 Bb:maj6 43.528073 45.084082 G:maj 45.084082 50.068027 C:min 50.068027 50.744036 F:maj 50.744036 51.208073 F:7 51.208073 51.860045 Ab:maj7 51.860045 52.608073 Ab:maj 52.608073 54.484082 D#:maj 54.484082 56.060045 Bb:maj 56.060045 57.796009 G:maj 57.796009 59.116009 C:min 59.116009 59.604082 Bb:maj 59.604082 61.368073 D#:maj 61.368073 62.480000 F:min 62.480000 64.040091 Ab:maj6 64.040091 64.956009 Ab:maj 64.956009 66.764082 D#:maj 66.764082 67.192018 Ab:maj 67.192018 68.816054 D#:maj 68.816054 70.580045 Bb:maj 70.580045 72.172063 C:min 72.172063 73.784036 Ab:maj6 73.784036 75.784036 Ab:maj 75.784036 77.628027 Bb:maj 77.628027 78.844082 C:min 78.844082 81.168073 F:min 81.168073 83.156009 Ab:maj 83.156009 86.328073 C:min 86.328073 88.312018 F:7 88.312018 91.664036 Ab:maj6 91.664036 91.860045 C#:maj 91.860045 93.656054 D#:maj 93.656054 97.360000 Ab:maj6 97.360000 98.924082 Bb:maj 98.924082 100.712018 Bb:7 100.712018 102.476009 D#:maj 102.476009 104.016054 Ab:maj 104.016054 106.016054 D#:maj 106.016054 107.596009 Ab:maj 107.596009 109.628027 D#:maj 109.628027 111.404082 Ab:maj7 111.404082 112.772063 Bb:maj 112.772063 115.064036 Bb:maj6 115.064036 116.172063 C:min 116.172063 116.872018 F:7 116.872018 118.712018 Bb:maj 118.712018 119.848073 A:min 119.848073 120.736054 F:7 120.736054 122.340045 Ab:maj6 122.340045 124.156009 D#:maj 124.156009 125.956009 Bb:maj 125.956009 127.740045 G:maj 127.740045 129.552018 C:min 129.552018 131.316009 D#:maj 131.316009 133.128073 Ab:maj6 133.128073 134.944036 Ab:maj 134.944036 138.556009 Bb:maj 138.556009 140.404082 D#:maj 140.404082 142.200000 Ab:maj 142.200000 143.760000 Bb:maj 143.760000 145.812063 G:min 145.812063 147.596009 C:min 147.596009 148.500045 Bb:maj 148.500045 150.492063 C:min7 150.492063 152.992018 Ab:maj6 152.992018 154.764082 D#:maj 154.764082 156.572063 Bb:maj 156.572063 158.344036 G:maj 158.344036 160.148027 C:min 160.148027 161.924082 D#:maj 161.924082 164.156009 Ab:maj6 164.156009 165.696054 Ab:maj 165.696054 169.060045 D#:maj 169.060045 170.872018 Bb:maj 170.872018 172.628027 C:min 172.628027 174.416054 F:min 174.416054 176.224036 Ab:maj 176.224036 177.988027 Bb:maj 177.988027 179.800091 C:min 179.800091 181.556009 F:min 181.556009 183.372063 Ab:maj 183.372063 185.108027 C:min 185.108027 186.968073 Bb:maj 186.968073 188.760000 A:min 188.760000 191.984036 Ab:maj6 191.984036 192.484082 Ab:maj 192.484082 193.996009 D#:maj 193.996009 195.904036 Ab:maj6 195.904036 197.632018 Ab:maj 197.632018 201.156009 Bb:maj 201.156009 202.964082 C:min 202.964082 204.688073 Bb:maj 204.688073 206.504036 F:maj 206.504036 210.008073 Ab:maj6 210.008073 211.820045 D#:maj 211.820045 212.916009 Ab:maj7 212.916009 214.804082 Ab:maj 214.804082 217.076009 D#:maj 217.076009 218.632018 Ab:maj 218.632018 220.660045 D#:maj 220.660045 222.760000 Ab:maj 222.760000 228.996009 D#:maj 228.996009 244.970522 N mir_eval-0.8.2/tests/data/chord/est08.lab000066400000000000000000000441301475740344600201340ustar00rootroot000000000000007.76117913832 8.08743764172 E:maj 8.08743764172 8.44063492063 E:maj 8.44063492063 8.79083900227 C#:min 8.79083900227 9.13804988662 E:min 9.13804988662 9.48526077098 Gb:maj 9.48526077098 9.82349206349 N 9.82349206349 10.1766893424 N 10.1766893424 10.526893424 C#:maj 10.526893424 10.8711111111 N 10.8711111111 11.2213151927 Bb:min 11.2213151927 11.5655328798 Ab:min 11.5655328798 11.9097505669 Ab:maj 11.9097505669 12.2599546485 Ab:maj 12.2599546485 12.6071655329 Ab:min 12.6071655329 12.9603628118 Eb:min 12.9603628118 13.3075736961 Ab:maj 13.3075736961 13.6517913832 Ab:min 13.6517913832 13.9990022676 Ab:maj 13.9990022676 14.3462131519 Ab:maj 14.3462131519 14.6934240363 Ab:maj 14.6934240363 15.0406349206 Ab:maj 15.0406349206 15.3908390023 Ab:min 15.3908390023 15.7380498866 Ab:maj 15.7380498866 16.085260771 Ab:maj 16.085260771 16.4324716553 Ab:maj 16.4324716553 16.7796825397 N 16.7796825397 17.126893424 Ab:min 17.126893424 17.4741043084 Ab:maj 17.4741043084 17.82430839 Ab:maj 17.82430839 18.1715192744 Ab:min 18.1715192744 18.5247165533 C#:maj 18.5247165533 18.8719274376 Ab:maj 18.8719274376 19.2161451247 C#:maj 19.2161451247 19.5633560091 C#:maj 19.5633560091 19.9075736961 Ab:maj 19.9075736961 20.2547845805 Ab:maj 20.2547845805 20.6049886621 Ab:maj 20.6049886621 20.9521995465 Ab:min 20.9521995465 21.3024036281 Eb:min 21.3024036281 21.6526077098 Ab:maj 21.6526077098 21.9938321995 Ab:maj 21.9938321995 22.3350566893 N 22.3350566893 22.6912471655 Ab:maj 22.6912471655 23.0384580499 Ab:maj 23.0384580499 23.3856689342 Ab:maj 23.3856689342 23.7358730159 Ab:min 23.7358730159 24.0830839002 Bb:min 24.0830839002 24.4302947846 C#:maj 24.4302947846 24.7775056689 C#:maj 24.7775056689 25.121723356 Ab:maj 25.121723356 25.4719274376 B:maj 25.4719274376 25.819138322 Ab:maj 25.819138322 26.1663492063 Ab:maj 26.1663492063 26.516553288 Ab:min 26.516553288 26.8667573696 D:min 26.8667573696 27.2109750567 Ab:maj 27.2109750567 27.558185941 C#:maj 27.558185941 27.9083900227 C#:maj 27.9083900227 28.2526077098 Ab:min 28.2526077098 28.6028117914 Ab:maj 28.6028117914 28.9500226757 Ab:maj 28.9500226757 29.2972335601 Ab:min 29.2972335601 29.6474376417 Ab:maj 29.6474376417 29.9976417234 C#:maj 29.9976417234 30.3388662132 C#:maj 30.3388662132 30.6860770975 C#:maj 30.6860770975 31.0362811791 Ab:maj 31.0362811791 31.3834920635 C#:min 31.3834920635 31.7277097506 C#:min 31.7277097506 32.0809070295 Eb:maj 32.0809070295 32.4281179138 Bb:min 32.4281179138 32.7783219955 E:maj 32.7783219955 33.1225396825 E:maj 33.1225396825 33.4757369615 Gb:maj 33.4757369615 33.8169614512 Gb:maj 33.8169614512 34.1671655329 Ab:min 34.1671655329 34.5143764172 Ab:maj 34.5143764172 34.8585941043 Ab:min 34.8585941043 35.2147845805 Ab:min 35.2147845805 35.5590022676 C#:maj 35.5590022676 35.9032199546 Ab:min 35.9032199546 36.2534240363 C#:maj 36.2534240363 36.5976417234 Ab:min 36.5976417234 36.9448526077 Ab:maj 36.9448526077 37.2920634921 Ab:maj 37.2920634921 37.6422675737 Ab:min 37.6422675737 37.9924716553 Ab:min 37.9924716553 38.342675737 C#:maj 38.342675737 38.6839002268 C#:maj 38.6839002268 39.0341043084 C#:maj 39.0341043084 39.3813151927 B:maj 39.3813151927 39.7285260771 Ab:maj 39.7285260771 40.0757369615 Ab:maj 40.0757369615 40.4229478458 Ab:maj 40.4229478458 40.7761451247 Ab:min 40.7761451247 41.1233560091 C#:maj 41.1233560091 41.4615873016 C#:maj 41.4615873016 41.8117913832 C#:maj 41.8117913832 42.1590022676 Ab:maj 42.1590022676 42.5092063492 C#:min 42.5092063492 42.8564172336 C#:min 42.8564172336 43.2066213152 Eb:maj 43.2066213152 43.5538321995 Bb:min 43.5538321995 43.9040362812 E:maj 43.9040362812 44.2482539683 E:maj 44.2482539683 44.6014512472 Ab:min 44.6014512472 44.9456689342 Gb:maj 44.9456689342 45.2898866213 E:maj 45.2898866213 45.6400907029 E:maj 45.6400907029 45.9873015873 Eb:min 45.9873015873 46.3404988662 E:maj 46.3404988662 46.6847165533 E:maj 46.6847165533 47.0319274376 E:maj 47.0319274376 47.3761451247 E:maj 47.3761451247 47.7233560091 E:maj 47.7233560091 48.0735600907 Gb:maj 48.0735600907 48.4207709751 Gb:maj 48.4207709751 48.7679818594 Gb:maj 48.7679818594 49.1211791383 Gb:maj 49.1211791383 49.4653968254 Gb:maj 49.4653968254 49.8096145125 B:maj 49.8096145125 50.1628117914 Gb:maj 50.1628117914 50.5070294785 Ab:min 50.5070294785 50.8542403628 E:maj 50.8542403628 51.1984580499 E:maj 51.1984580499 51.5516553288 E:maj 51.5516553288 51.9018594104 E:maj 51.9018594104 52.2520634921 E:maj 52.2520634921 52.5932879819 E:maj 52.5932879819 52.9404988662 E:maj 52.9404988662 53.2847165533 E:maj 53.2847165533 53.6349206349 Bb:min 53.6349206349 53.9851247166 B:maj 53.9851247166 54.3383219955 Bb:min 54.3383219955 54.6825396825 Ab:min 54.6825396825 55.0327437642 Eb:maj 55.0327437642 55.3769614512 Eb:maj 55.3769614512 55.7241723356 Bb:min 55.7241723356 56.07138322 Ab:min 56.07138322 56.4185941043 Ab:min 56.4185941043 56.7658049887 Ab:min 56.7658049887 57.113015873 Ab:min 57.113015873 57.4662131519 Ab:min 57.4662131519 57.810430839 Ab:min 57.810430839 58.1576417234 Ab:min 58.1576417234 58.5048526077 Ab:min 58.5048526077 58.8490702948 Ab:min 58.8490702948 59.1992743764 Gb:maj 59.1992743764 59.5464852608 Gb:maj 59.5464852608 59.8966893424 Gb:maj 59.8966893424 60.246893424 Gb:maj 60.246893424 60.5941043084 Gb:maj 60.5941043084 60.9383219955 Gb:maj 60.9383219955 61.2885260771 Gb:maj 61.2885260771 61.6357369615 Gb:maj 61.6357369615 61.9829478458 E:maj 61.9829478458 62.3301587302 E:maj 62.3301587302 62.6773696145 E:maj 62.6773696145 63.0275736961 E:maj 63.0275736961 63.3717913832 E:maj 63.3717913832 63.7190022676 E:maj 63.7190022676 64.0692063492 E:maj 64.0692063492 64.4134240363 E:maj 64.4134240363 64.7666213152 Eb:min 64.7666213152 65.1108390023 Eb:maj 65.1108390023 65.4580498866 Eb:maj 65.4580498866 65.8082539683 Ab:min 65.8082539683 66.1554648526 Eb:maj 66.1554648526 66.502675737 Eb:maj 66.502675737 66.8558730159 Eb:maj 66.8558730159 67.2000907029 Ab:min 67.2000907029 67.5473015873 Ab:min 67.5473015873 67.8915192744 Ab:min 67.8915192744 68.2387301587 Ab:min 68.2387301587 68.5919274376 Ab:min 68.5919274376 68.9331519274 Ab:min 68.9331519274 69.2833560091 Ab:min 69.2833560091 69.6335600907 Ab:min 69.6335600907 69.9747845805 Ab:min 69.9747845805 70.3279818594 Gb:maj 70.3279818594 70.6751927438 Gb:maj 70.6751927438 71.0224036281 Gb:maj 71.0224036281 71.3726077098 Gb:maj 71.3726077098 71.7198185941 Gb:maj 71.7198185941 72.0670294785 Gb:maj 72.0670294785 72.4142403628 Gb:maj 72.4142403628 72.7584580499 Gb:maj 72.7584580499 73.1086621315 E:maj 73.1086621315 73.4558730159 E:maj 73.4558730159 73.8060770975 E:maj 73.8060770975 74.1562811791 E:maj 74.1562811791 74.5064852608 E:maj 74.5064852608 74.8477097506 E:maj 74.8477097506 75.1979138322 E:maj 75.1979138322 75.5451247166 C#:min 75.5451247166 75.8893424036 C#:min 75.8893424036 76.236553288 Eb:maj 76.236553288 76.5867573696 Eb:maj 76.5867573696 76.933968254 N 76.933968254 77.278185941 E:maj 77.278185941 77.6283900227 E:maj 77.6283900227 77.975600907 Gb:maj 77.975600907 78.3258049887 Gb:maj 78.3258049887 78.6700226757 Ab:min 78.6700226757 79.0202267574 Ab:maj 79.0202267574 79.3674376417 Ab:min 79.3674376417 79.7146485261 Ab:maj 79.7146485261 80.0648526077 Ab:maj 80.0648526077 80.4090702948 N 80.4090702948 80.7742403628 N 80.7742403628 81.109478458 Ab:maj 81.109478458 81.4596825397 Ab:maj 81.4596825397 81.806893424 Ab:maj 81.806893424 82.1570975057 Ab:maj 82.1570975057 82.4953287982 C#:maj 82.4953287982 82.8455328798 Bb:min 82.8455328798 83.1897505669 C#:maj 83.1897505669 83.533968254 C#:maj 83.533968254 83.8871655329 Ab:min 83.8871655329 84.2343764172 Ab:maj 84.2343764172 84.5845804989 Ab:maj 84.5845804989 84.9258049887 Ab:maj 84.9258049887 85.2700226757 N 85.2700226757 85.6262131519 C#:maj 85.6262131519 85.9734240363 Ab:min 85.9734240363 86.3116553288 Bb:min 86.3116553288 86.667845805 C#:maj 86.667845805 87.0150566893 Ab:maj 87.0150566893 87.3622675737 Ab:maj 87.3622675737 87.7124716553 A:maj 87.7124716553 88.0596825397 N 88.0596825397 88.4128798186 Ab:maj 88.4128798186 88.7541043084 C#:maj 88.7541043084 89.0953287982 C#:maj 89.0953287982 89.4515192744 Ab:maj 89.4515192744 89.7987301587 C#:min 89.7987301587 90.1459410431 C#:min 90.1459410431 90.4961451247 Eb:maj 90.4961451247 90.8403628118 Eb:maj 90.8403628118 91.1845804989 B:maj 91.1845804989 91.5287981859 Gb:maj 91.5287981859 91.8819954649 B:maj 91.8819954649 92.2321995465 C#:min 92.2321995465 92.5794104308 C#:maj 92.5794104308 92.9296145125 Ab:maj 92.9296145125 93.2768253968 Ab:min 93.2768253968 93.6270294785 Ab:min 93.6270294785 93.9712471655 Ab:min 93.9712471655 94.3214512472 C#:maj 94.3214512472 94.6686621315 C#:maj 94.6686621315 95.0128798186 B:maj 95.0128798186 95.3600907029 Ab:maj 95.3600907029 95.7073015873 Ab:maj 95.7073015873 96.0575056689 Ab:maj 96.0575056689 96.4077097506 Ab:min 96.4077097506 96.7579138322 C#:maj 96.7579138322 97.0961451247 A:min 97.0961451247 97.4463492063 Ab:maj 97.4463492063 97.796553288 Ab:maj 97.796553288 98.1437641723 Ab:min 98.1437641723 98.4879818594 Ab:maj 98.4879818594 98.838185941 Ab:min 98.838185941 99.19138322 Ab:min 99.19138322 99.535600907 C#:maj 99.535600907 99.8828117914 Ab:min 99.8828117914 100.230022676 C#:maj 100.230022676 100.57723356 Ab:maj 100.57723356 100.924444444 C#:min 100.924444444 101.271655329 C#:min 101.271655329 101.618866213 Ab:min 101.618866213 101.972063492 Eb:maj 101.972063492 102.316281179 E:maj 102.316281179 102.663492063 E:maj 102.663492063 103.010702948 Ab:min 103.010702948 103.360907029 Gb:maj 103.360907029 103.705124717 E:maj 103.705124717 104.049342404 E:maj 104.049342404 104.402539683 E:maj 104.402539683 104.752743764 E:maj 104.752743764 105.102947846 E:maj 105.102947846 105.444172336 E:maj 105.444172336 105.794376417 E:maj 105.794376417 106.138594104 E:maj 106.138594104 106.485804989 Gb:maj 106.485804989 106.83600907 Gb:maj 106.83600907 107.183219955 Gb:maj 107.183219955 107.536417234 Gb:maj 107.536417234 107.883628118 Gb:maj 107.883628118 108.227845805 Ab:min 108.227845805 108.578049887 Gb:maj 108.578049887 108.922267574 Ab:min 108.922267574 109.269478458 E:maj 109.269478458 109.610702948 E:maj 109.610702948 109.963900227 E:maj 109.963900227 110.314104308 E:maj 110.314104308 110.658321995 E:maj 110.658321995 111.008526077 E:maj 111.008526077 111.358730159 E:maj 111.358730159 111.702947846 E:maj 111.702947846 112.05015873 Bb:min 112.05015873 112.400362812 Eb:maj 112.400362812 112.744580499 Bb:min 112.744580499 113.097777778 Ab:min 113.097777778 113.441995465 Eb:maj 113.441995465 113.792199546 Ab:min 113.792199546 114.139410431 Eb:maj 114.139410431 114.486621315 Gb:maj 114.486621315 114.836825397 Ab:maj 114.836825397 115.184036281 Ab:min 115.184036281 115.531247166 Ab:min 115.531247166 115.87845805 Ab:min 115.87845805 116.225668934 Ab:min 116.225668934 116.572879819 Ab:min 116.572879819 116.920090703 Ab:min 116.920090703 117.267301587 Ab:min 117.267301587 117.614512472 Gb:maj 117.614512472 117.958730159 Gb:maj 117.958730159 118.30893424 Gb:maj 118.30893424 118.662131519 Gb:maj 118.662131519 119.009342404 Gb:maj 119.009342404 119.353560091 Gb:maj 119.353560091 119.703764172 Gb:maj 119.703764172 120.050975057 Gb:maj 120.050975057 120.398185941 E:maj 120.398185941 120.745396825 E:maj 120.745396825 121.095600907 E:maj 121.095600907 121.442811791 E:maj 121.442811791 121.787029478 E:maj 121.787029478 122.134240363 E:maj 122.134240363 122.487437642 E:maj 122.487437642 122.828662132 E:maj 122.828662132 123.178866213 Eb:maj 123.178866213 123.526077098 Eb:maj 123.526077098 123.873287982 Eb:maj 123.873287982 124.223492063 Ab:min 124.223492063 124.570702948 Eb:maj 124.570702948 124.917913832 Eb:maj 124.917913832 125.271111111 Eb:maj 125.271111111 125.612335601 Ab:min 125.612335601 125.962539683 Ab:min 125.962539683 126.309750567 Ab:min 126.309750567 126.656961451 Ab:min 126.656961451 127.01015873 Ab:maj 127.01015873 127.348390023 Ab:min 127.348390023 127.698594104 Ab:min 127.698594104 128.048798186 Ab:min 128.048798186 128.390022676 Ab:min 128.390022676 128.743219955 Gb:maj 128.743219955 129.087437642 Gb:maj 129.087437642 129.440634921 Gb:maj 129.440634921 129.7938322 Gb:maj 129.7938322 130.141043084 Gb:maj 130.141043084 130.482267574 Gb:maj 130.482267574 130.832471655 Gb:maj 130.832471655 131.17968254 Gb:maj 131.17968254 131.526893424 E:maj 131.526893424 131.871111111 E:maj 131.871111111 132.218321995 E:maj 132.218321995 132.568526077 E:maj 132.568526077 132.918730159 E:maj 132.918730159 133.262947846 E:maj 133.262947846 133.619138322 E:maj 133.619138322 133.960362812 C#:min 133.960362812 134.304580499 E:maj 134.304580499 134.65478458 Eb:maj 134.65478458 135.004988662 Eb:maj 135.004988662 135.349206349 Ab:min 135.349206349 135.696417234 E:maj 135.696417234 136.040634921 E:maj 136.040634921 136.390839002 Gb:maj 136.390839002 136.738049887 B:maj 136.738049887 137.085260771 C#:maj 137.085260771 137.435464853 Ab:min 137.435464853 137.782675737 Ab:min 137.782675737 138.135873016 Ab:min 138.135873016 138.480090703 C#:maj 138.480090703 138.827301587 N 138.827301587 139.174512472 C#:maj 139.174512472 139.524716553 Ab:maj 139.524716553 139.871927438 Ab:maj 139.871927438 140.213151927 Ab:maj 140.213151927 140.563356009 Ab:min 140.563356009 140.916553288 Ab:maj 140.916553288 141.257777778 Ab:min 141.257777778 141.607981859 Ab:min 141.607981859 141.949206349 F:min 141.949206349 142.302403628 Ab:min 142.302403628 142.649614512 Ab:min 142.649614512 142.999818594 Ab:min 142.999818594 143.347029478 Ab:min 143.347029478 143.694240363 Ab:min 143.694240363 144.041451247 Ab:min 144.041451247 144.388662132 Ab:min 144.388662132 144.735873016 N 144.735873016 145.086077098 Ab:maj 145.086077098 145.433287982 Ab:maj 145.433287982 145.777505669 Ab:maj 145.777505669 146.127709751 Ab:min 146.127709751 146.483900227 Ab:min 146.483900227 146.828117914 Ab:min 146.828117914 147.169342404 Ab:min 147.169342404 147.510566893 N 147.510566893 147.86675737 Ab:min 147.86675737 148.210975057 Ab:min 148.210975057 148.561179138 Ab:min 148.561179138 148.908390023 Ab:min 148.908390023 149.258594104 C#:min 149.258594104 149.608798186 Ab:min 149.608798186 149.953015873 C#:min 149.953015873 150.300226757 N 150.300226757 150.653424036 C#:maj 150.653424036 151.000634921 F:min 151.000634921 151.344852608 E:maj 151.344852608 151.692063492 C#:maj 151.692063492 152.051247166 C#:min 152.051247166 152.39845805 Ab:maj 152.39845805 152.742675737 Ab:maj 152.742675737 153.104852608 C#:min 153.104852608 153.4430839 C#:min 153.4430839 153.793287982 Gb:maj 153.793287982 154.137505669 Gb:maj 154.137505669 154.481723356 Gb:maj 154.481723356 154.82893424 Gb:maj 154.82893424 155.173151927 Gb:maj 155.173151927 155.529342404 Gb:maj 155.529342404 155.870566893 Gb:maj 155.870566893 156.211791383 Gb:maj 156.211791383 156.559002268 Gb:maj 156.559002268 156.909206349 Gb:maj 156.909206349 157.259410431 E:maj 157.259410431 157.606621315 E:maj 157.606621315 157.950839002 E:maj 157.950839002 158.301043084 E:maj 158.301043084 158.642267574 E:maj 158.642267574 158.992471655 E:maj 158.992471655 159.33968254 Eb:maj 159.33968254 159.683900227 Gb:maj 159.683900227 160.037097506 C#:maj 160.037097506 160.381315193 C#:maj 160.381315193 160.734512472 Eb:maj 160.734512472 161.078730159 N 161.078730159 161.425941043 B:maj 161.425941043 161.773151927 Eb:min 161.773151927 162.123356009 Ab:min 162.123356009 162.473560091 Ab:maj 162.473560091 162.817777778 Ab:min 162.817777778 163.164988662 Ab:maj 163.164988662 163.518185941 Ab:min 163.518185941 163.859410431 Ab:min 163.859410431 164.209614512 Ab:min 164.209614512 164.5538322 Ab:min 164.5538322 164.907029478 Gb:maj 164.907029478 165.251247166 Gb:maj 165.251247166 165.601451247 Gb:maj 165.601451247 165.954648526 Gb:maj 165.954648526 166.298866213 Gb:maj 166.298866213 166.6430839 Gb:maj 166.6430839 166.996281179 Gb:maj 166.996281179 167.337505669 Gb:maj 167.337505669 167.687709751 E:maj 167.687709751 168.034920635 E:maj 168.034920635 168.379138322 E:maj 168.379138322 168.732335601 E:maj 168.732335601 169.076553288 E:maj 169.076553288 169.423764172 E:maj 169.423764172 169.776961451 E:maj 169.776961451 170.127165533 E:maj 170.127165533 170.477369615 Eb:maj 170.477369615 170.827573696 E:maj 170.827573696 171.171791383 E:maj 171.171791383 171.527981859 E:maj 171.527981859 171.863219955 Bb:min 171.863219955 172.213424036 Bb:min 172.213424036 172.563628118 C#:maj 172.563628118 172.907845805 C#:maj 172.907845805 173.255056689 Ab:min 173.255056689 173.599274376 Ab:maj 173.599274376 173.946485261 Ab:min 173.946485261 174.296689342 Ab:min 174.296689342 174.643900227 Ab:min 174.643900227 174.991111111 Ab:min 174.991111111 175.338321995 Ab:min 175.338321995 175.679546485 Ab:min 175.679546485 176.029750567 Gb:maj 176.029750567 176.376961451 Gb:maj 176.376961451 176.727165533 Gb:maj 176.727165533 177.080362812 Gb:maj 177.080362812 177.427573696 Gb:maj 177.427573696 177.768798186 Gb:maj 177.768798186 178.119002268 Gb:maj 178.119002268 178.466213152 Gb:maj 178.466213152 178.816417234 E:maj 178.816417234 179.163628118 E:maj 179.163628118 179.510839002 E:maj 179.510839002 179.861043084 E:maj 179.861043084 180.205260771 E:maj 180.205260771 180.552471655 E:maj 180.552471655 180.89968254 E:maj 180.89968254 181.246893424 E:maj 181.246893424 181.594104308 Eb:maj 181.594104308 181.941315193 Eb:maj 181.941315193 182.291519274 Eb:maj 182.291519274 182.638730159 Eb:maj 182.638730159 182.98893424 C#:min 182.98893424 183.333151927 Eb:maj 183.333151927 183.686349206 Eb:maj 183.686349206 184.030566893 Ab:min 184.030566893 184.377777778 Ab:min 184.377777778 184.724988662 Ab:min 184.724988662 185.072199546 Ab:min 185.072199546 185.422403628 Ab:min 185.422403628 185.766621315 Ab:min 185.766621315 186.1138322 Ab:min 186.1138322 186.464036281 Ab:maj 186.464036281 186.808253968 Ab:min 186.808253968 187.15845805 Gb:maj 187.15845805 187.505668934 Gb:maj 187.505668934 187.855873016 Gb:maj 187.855873016 188.209070295 Gb:maj 188.209070295 188.550294785 Gb:maj 188.550294785 188.897505669 Gb:maj 188.897505669 189.244716553 Gb:maj 189.244716553 189.591927438 Gb:maj 189.591927438 189.939138322 E:maj 189.939138322 190.289342404 E:maj 190.289342404 190.633560091 E:maj 190.633560091 190.98675737 E:maj 190.98675737 191.333968254 E:maj 191.333968254 191.678185941 E:maj 191.678185941 192.034376417 E:maj 192.034376417 192.378594104 C#:min 192.378594104 192.722811791 C#:min 192.722811791 193.073015873 Eb:maj 193.073015873 193.423219955 Eb:maj 193.423219955 193.761451247 Eb:maj 193.761451247 194.111655329 E:maj 194.111655329 194.458866213 E:maj 194.458866213 194.558866213 C:min mir_eval-0.8.2/tests/data/chord/est09.lab000066400000000000000000000674521475740344600201510ustar00rootroot000000000000000.236281179138 0.712199546485 Ab:min 0.712199546485 1.17015873016 Bb:min 1.17015873016 1.64009070295 N 1.64009070295 2.09505668934 C#:maj 2.09505668934 2.57396825397 C#:maj 2.57396825397 3.0379138322 C#:maj 3.0379138322 3.50185941043 Bb:min 3.50185941043 3.97179138322 G:maj 3.97179138322 4.44172335601 G:maj 4.44172335601 4.90566893424 C#:maj 4.90566893424 5.37260770975 Eb:maj 5.37260770975 5.84253968254 C#:maj 5.84253968254 6.31845804989 G:min 6.31845804989 6.7853968254 G:min 6.7853968254 7.25233560091 G:min 7.25233560091 7.72526077098 C#:maj 7.72526077098 8.19219954649 N 8.19219954649 8.66512471655 E:maj 8.66512471655 9.14403628118 E:maj 9.14403628118 9.60498866213 D:maj 9.60498866213 10.0719274376 G:min 10.0719274376 10.5328798186 G:min 10.5328798186 11.0028117914 G:min 11.0028117914 11.4697505669 E:maj 11.4697505669 11.9456689342 E:maj 11.9456689342 12.4185941043 D:maj 12.4185941043 12.8855328798 D:maj 12.8855328798 13.3554648526 D:maj 13.3554648526 13.8224036281 D:maj 13.8224036281 14.30430839 E:maj 14.30430839 14.7682539683 B:maj 14.7682539683 15.2292063492 D:maj 15.2292063492 15.6901587302 D:maj 15.6901587302 16.1570975057 E:maj 16.1570975057 16.6180498866 B:maj 16.6180498866 17.0790022676 D:maj 17.0790022676 17.5429478458 E:maj 17.5429478458 18.0158730159 E:maj 18.0158730159 18.4738321995 B:maj 18.4738321995 18.9407709751 D:maj 18.9407709751 19.4047165533 E:maj 19.4047165533 19.8686621315 E:maj 19.8686621315 20.335600907 Ab:maj 20.335600907 20.796553288 D:maj 20.796553288 21.2724716553 F#:min 21.2724716553 21.730430839 A:maj 21.730430839 22.2003628118 A:maj 22.2003628118 22.6553287982 A:maj 22.6553287982 23.1192743764 A:maj 23.1192743764 23.5832199546 F#:min 23.5832199546 24.0531519274 F#:min 24.0531519274 24.5260770975 F#:min 24.5260770975 24.993015873 F#:min 24.993015873 25.4659410431 A:maj 25.4659410431 25.9358730159 A:maj 25.9358730159 26.4147845805 A:maj 26.4147845805 26.8727437642 Bb:min 26.8727437642 27.3366893424 F#:min 27.3366893424 27.7946485261 F#:min 27.7946485261 28.2585941043 F#:min 28.2585941043 28.7315192744 E:maj 28.7315192744 29.2044444444 G:maj 29.2044444444 29.67138322 D:maj 29.67138322 30.1473015873 D:maj 30.1473015873 30.6172335601 D:maj 30.6172335601 31.0931519274 D:maj 31.0931519274 31.5660770975 D:maj 31.5660770975 32.0479818594 E:maj 32.0479818594 32.5119274376 E:maj 32.5119274376 32.9818594104 E:maj 32.9818594104 33.4248526077 E:maj 33.4248526077 33.9097505669 E:maj 33.9097505669 34.3856689342 E:maj 34.3856689342 34.855600907 E:maj 34.855600907 35.316553288 B:min 35.316553288 35.7685260771 E:maj 35.7685260771 36.2324716553 E:maj 36.2324716553 36.6994104308 E:maj 36.6994104308 37.1663492063 E:maj 37.1663492063 37.6332879819 E:maj 37.6332879819 38.1032199546 E:maj 38.1032199546 38.5671655329 E:maj 38.5671655329 39.0251247166 E:maj 39.0251247166 39.4920634921 E:maj 39.4920634921 39.9560090703 B:maj 39.9560090703 40.4289342404 F#:min 40.4289342404 40.8988662132 D:maj 40.8988662132 41.3568253968 E:maj 41.3568253968 41.8297505669 B:maj 41.8297505669 42.2996825397 D:maj 42.2996825397 42.7666213152 E:maj 42.7666213152 43.2455328798 E:maj 43.2455328798 43.7214512472 B:maj 43.7214512472 44.1824036281 D:maj 44.1824036281 44.6493424036 D:maj 44.6493424036 45.1132879819 E:maj 45.1132879819 45.5682539683 E:maj 45.5682539683 46.0262131519 F#:min 46.0262131519 46.4961451247 E:maj 46.4961451247 46.9660770975 A:maj 46.9660770975 47.4449886621 A:maj 47.4449886621 47.9089342404 A:maj 47.9089342404 48.3788662132 A:maj 48.3788662132 48.8458049887 F#:min 48.8458049887 49.321723356 F#:min 49.321723356 49.7946485261 F#:min 49.7946485261 50.2645804989 D:maj 50.2645804989 50.7434920635 A:maj 50.7434920635 51.2194104308 A:maj 51.2194104308 51.6803628118 A:maj 51.6803628118 52.1592743764 Bb:min 52.1592743764 52.6292063492 Gb:maj 52.6292063492 53.1051247166 F#:min 53.1051247166 53.5660770975 F#:min 53.5660770975 54.0449886621 F#:min 54.0449886621 54.5179138322 D:maj 54.5179138322 54.987845805 D:maj 54.987845805 55.4577777778 D:maj 55.4577777778 55.9277097506 D:maj 55.9277097506 56.3946485261 D:maj 56.3946485261 56.8735600907 D:maj 56.8735600907 57.3404988662 E:maj 57.3404988662 57.8014512472 E:maj 57.8014512472 58.2803628118 E:maj 58.2803628118 58.7413151927 E:maj 58.7413151927 59.2142403628 E:maj 59.2142403628 59.6751927438 E:maj 59.6751927438 60.1331519274 E:maj 60.1331519274 60.6120634921 E:maj 60.6120634921 61.0879818594 E:maj 61.0879818594 61.5549206349 E:maj 61.5549206349 62.0308390023 E:maj 62.0308390023 62.4917913832 E:maj 62.4917913832 62.9467573696 E:maj 62.9467573696 63.4166893424 E:maj 63.4166893424 63.8836281179 E:maj 63.8836281179 64.3445804989 E:maj 64.3445804989 64.8145124717 E:maj 64.8145124717 65.2814512472 E:maj 65.2814512472 65.7483900227 D:maj 65.7483900227 66.22430839 E:maj 66.22430839 66.6942403628 E:maj 66.6942403628 67.1551927438 B:min 67.1551927438 67.6161451247 C#:maj 67.6161451247 68.0800907029 E:maj 68.0800907029 68.5470294785 E:maj 68.5470294785 69.013968254 E:maj 69.013968254 69.4809070295 F#:min 69.4809070295 69.9418594104 E:maj 69.9418594104 70.3938321995 E:maj 70.3938321995 70.8487981859 E:maj 70.8487981859 71.3037641723 E:maj 71.3037641723 71.7527437642 E:maj 71.7527437642 72.2256689342 D:maj 72.2256689342 72.6896145125 D:min 72.6896145125 73.1685260771 F:maj 73.1685260771 73.629478458 A:maj 73.629478458 74.0994104308 G:maj 74.0994104308 74.5663492063 F:maj 74.5663492063 75.0183219955 C:maj 75.0183219955 75.4762811791 G:maj 75.4762811791 75.9611791383 C:maj 75.9611791383 76.4251247166 C:maj 76.4251247166 76.8920634921 C:maj 76.8920634921 77.353015873 C:maj 77.353015873 77.8199546485 A:min 77.8199546485 78.2839002268 C:maj 78.2839002268 78.7388662132 C:maj 78.7388662132 79.1818594104 D:min 79.1818594104 79.6637641723 D:min 79.6637641723 80.121723356 D:min 80.121723356 80.5886621315 D:min 80.5886621315 81.0436281179 A:min 81.0436281179 81.5075736961 C:maj 81.5075736961 81.9655328798 G:maj 81.9655328798 82.4234920635 N 82.4234920635 82.8754648526 D:min 82.8754648526 83.3483900227 C:maj 83.3483900227 83.8153287982 C:maj 83.8153287982 84.2792743764 C:maj 84.2792743764 84.7432199546 C:maj 84.7432199546 85.1951927438 C:maj 85.1951927438 85.659138322 C:maj 85.659138322 86.1081179138 E:maj 86.1081179138 86.5511111111 E:maj 86.5511111111 87.0240362812 D:maj 87.0240362812 87.4969614512 D:min 87.4969614512 87.9519274376 F:maj 87.9519274376 88.4218594104 A:min 88.4218594104 88.8828117914 G:maj 88.8828117914 89.3317913832 G:maj 89.3317913832 89.7837641723 E:min 89.7837641723 90.2387301587 G:maj 90.2387301587 90.7146485261 C:maj 90.7146485261 91.175600907 C:maj 91.175600907 91.6275736961 C:maj 91.6275736961 92.0855328798 G:maj 92.0855328798 92.5345124717 A:min 92.5345124717 92.9984580499 C:maj 92.9984580499 93.4354648526 Eb:min 93.4354648526 93.8934240363 A:min 93.8934240363 94.3693424036 D:maj 94.3693424036 94.8362811791 D:maj 94.8362811791 95.2912471655 D:min 95.2912471655 95.7492063492 A:min 95.7492063492 96.2101587302 C:maj 96.2101587302 96.6711111111 G:maj 96.6711111111 97.1200907029 E:min 97.1200907029 97.5780498866 G:maj 97.5780498866 98.0270294785 C:maj 98.0270294785 98.4879818594 C:maj 98.4879818594 98.9459410431 C:maj 98.9459410431 99.4009070295 C:maj 99.4009070295 99.8588662132 A:maj 99.8588662132 100.304852608 A:maj 100.304852608 100.759818594 A:maj 100.759818594 101.229750567 A:maj 101.229750567 101.69968254 F#:min 101.69968254 102.17260771 F#:min 102.17260771 102.642539683 F#:min 102.642539683 103.094512472 F#:min 103.094512472 103.549478458 D:maj 103.549478458 104.010430839 D:maj 104.010430839 104.474376417 D:min 104.474376417 104.941315193 D:maj 104.941315193 105.390294785 E:maj 105.390294785 105.860226757 E:maj 105.860226757 106.309206349 F#:min 106.309206349 106.773151927 E:maj 106.773151927 107.231111111 A:maj 107.231111111 107.698049887 C#:min 107.698049887 108.161995465 E:maj 108.161995465 108.625941043 A:maj 108.625941043 109.092879819 F#:min 109.092879819 109.544852608 F#:min 109.544852608 110.01478458 Gb:maj 110.01478458 110.46675737 D:maj 110.46675737 110.936689342 D:maj 110.936689342 111.403628118 D:min 111.403628118 111.855600907 D:min 111.855600907 112.313560091 F:maj 112.313560091 112.780498866 E:maj 112.780498866 113.235464853 E:maj 113.235464853 113.693424036 F#:min 113.693424036 114.157369615 E:maj 114.157369615 114.618321995 E:maj 114.618321995 115.09723356 B:maj 115.09723356 115.561179138 Ab:min 115.561179138 116.016145125 E:maj 116.016145125 116.462131519 E:maj 116.462131519 116.917097506 E:maj 116.917097506 117.369070295 F#:min 117.369070295 117.821043084 E:maj 117.821043084 118.279002268 E:maj 118.279002268 118.739954649 E:maj 118.739954649 119.203900227 D:maj 119.203900227 119.667845805 E:maj 119.667845805 120.131791383 A:maj 120.131791383 120.595736961 A:maj 120.595736961 121.053696145 A:maj 121.053696145 121.511655329 A:maj 121.511655329 121.97260771 F#:min 121.97260771 122.439546485 F#:min 122.439546485 122.909478458 F#:min 122.909478458 123.370430839 F#:min 123.370430839 123.828390023 A:maj 123.828390023 124.301315193 A:maj 124.301315193 124.762267574 A:maj 124.762267574 125.229206349 D:maj 125.229206349 125.69015873 F#:min 125.69015873 126.157097506 F#:min 126.157097506 126.615056689 F#:min 126.615056689 127.07600907 C:maj 127.07600907 127.545941043 D:maj 127.545941043 128.006893424 D:maj 128.006893424 128.467845805 D:maj 128.467845805 128.93478458 D:maj 128.93478458 129.392743764 D:maj 129.392743764 129.862675737 D:maj 129.862675737 130.33260771 E:maj 130.33260771 130.784580499 E:maj 130.784580499 131.242539683 E:maj 131.242539683 131.709478458 E:maj 131.709478458 132.170430839 E:maj 132.170430839 132.625396825 E:maj 132.625396825 133.092335601 E:maj 133.092335601 133.553287982 E:maj 133.553287982 134.002267574 E:maj 134.002267574 134.45723356 E:maj 134.45723356 134.918185941 E:maj 134.918185941 135.373151927 E:maj 135.373151927 135.834104308 E:maj 135.834104308 136.295056689 E:maj 136.295056689 136.764988662 E:maj 136.764988662 137.222947846 E:maj 137.222947846 137.680907029 E:maj 137.680907029 138.132879819 E:maj 138.132879819 138.587845805 E:maj 138.587845805 139.060770975 E:maj 139.060770975 139.515736961 E:maj 139.515736961 139.973696145 F:min 139.973696145 140.425668934 E:maj 140.425668934 140.874648526 E:maj 140.874648526 141.326621315 E:maj 141.326621315 141.781587302 E:maj 141.781587302 142.236553288 E:maj 142.236553288 142.697505669 E:maj 142.697505669 143.143492063 E:maj 143.143492063 143.601451247 E:maj 143.601451247 144.053424036 E:maj 144.053424036 144.499410431 E:maj 144.499410431 144.963356009 E:maj 144.963356009 145.418321995 E:maj 145.418321995 145.86430839 E:maj 145.86430839 146.322267574 E:maj 146.322267574 146.77723356 E:maj 146.77723356 147.238185941 E:maj 147.238185941 147.696145125 E:maj 147.696145125 148.151111111 E:maj 148.151111111 148.615056689 E:maj 148.615056689 149.070022676 E:maj 149.070022676 149.530975057 E:maj 149.530975057 149.985941043 E:maj 149.985941043 150.446893424 E:maj 150.446893424 150.90185941 E:maj 150.90185941 151.356825397 E:maj 151.356825397 151.817777778 E:maj 151.817777778 152.275736961 E:maj 152.275736961 152.736689342 E:maj 152.736689342 153.188662132 E:maj 153.188662132 153.643628118 E:maj 153.643628118 154.104580499 E:maj 154.104580499 154.562539683 E:maj 154.562539683 155.014512472 E:maj 155.014512472 155.466485261 E:maj 155.466485261 155.936417234 E:maj 155.936417234 156.397369615 E:maj 156.397369615 156.846349206 E:maj 156.846349206 157.30430839 E:maj 157.30430839 157.771247166 E:maj 157.771247166 158.21723356 E:maj 158.21723356 158.663219955 E:maj 158.663219955 159.118185941 E:maj 159.118185941 159.573151927 E:maj 159.573151927 160.025124717 E:maj 160.025124717 160.474104308 E:maj 160.474104308 160.9230839 E:maj 160.9230839 161.381043084 E:maj 161.381043084 161.839002268 E:maj 161.839002268 162.293968254 E:maj 162.293968254 162.754920635 E:maj 162.754920635 163.215873016 E:maj 163.215873016 163.676825397 E:maj 163.676825397 164.128798186 E:maj 164.128798186 164.580770975 E:maj 164.580770975 165.038730159 E:maj 165.038730159 165.49968254 E:maj 165.49968254 165.951655329 E:maj 165.951655329 166.41260771 E:maj 166.41260771 166.879546485 E:maj 166.879546485 167.334512472 E:maj 167.334512472 167.777505669 G:maj 167.777505669 168.241451247 E:maj 168.241451247 168.702403628 E:maj 168.702403628 169.163356009 E:maj 169.163356009 169.621315193 E:maj 169.621315193 170.082267574 E:maj 170.082267574 170.534240363 E:maj 170.534240363 170.998185941 E:maj 170.998185941 171.459138322 E:maj 171.459138322 171.917097506 E:maj 171.917097506 172.387029478 E:maj 172.387029478 172.847981859 B:min 172.847981859 173.302947846 E:maj 173.302947846 173.763900227 E:maj 173.763900227 174.227845805 E:maj 174.227845805 174.685804989 E:maj 174.685804989 175.14675737 E:maj 175.14675737 175.607709751 E:maj 175.607709751 176.074648526 E:maj 176.074648526 176.529614512 E:maj 176.529614512 176.993560091 E:maj 176.993560091 177.463492063 E:maj 177.463492063 177.91845805 E:maj 177.91845805 178.379410431 E:maj 178.379410431 178.840362812 E:maj 178.840362812 179.307301587 E:maj 179.307301587 179.771247166 E:maj 179.771247166 180.235192744 E:maj 180.235192744 180.696145125 E:maj 180.696145125 181.1630839 E:maj 181.1630839 181.621043084 E:maj 181.621043084 182.079002268 E:maj 182.079002268 182.539954649 A:maj 182.539954649 183.000907029 E:maj 183.000907029 183.458866213 E:maj 183.458866213 183.919818594 E:maj 183.919818594 184.377777778 E:maj 184.377777778 184.835736961 E:maj 184.835736961 185.290702948 E:maj 185.290702948 185.748662132 E:maj 185.748662132 186.215600907 E:maj 186.215600907 186.676553288 E:maj 186.676553288 187.131519274 E:maj 187.131519274 187.592471655 E:maj 187.592471655 188.047437642 E:maj 188.047437642 188.51138322 E:maj 188.51138322 188.972335601 E:maj 188.972335601 189.436281179 E:maj 189.436281179 189.89723356 E:maj 189.89723356 190.358185941 E:maj 190.358185941 190.819138322 E:maj 190.819138322 191.277097506 E:maj 191.277097506 191.735056689 E:maj 191.735056689 192.193015873 E:maj 192.193015873 192.659954649 E:maj 192.659954649 193.123900227 E:maj 193.123900227 193.587845805 E:maj 193.587845805 194.045804989 E:maj 194.045804989 194.50675737 E:maj 194.50675737 194.964716553 E:maj 194.964716553 195.425668934 E:maj 195.425668934 195.889614512 E:maj 195.889614512 196.33260771 E:maj 196.33260771 196.796553288 E:maj 196.796553288 197.254512472 E:maj 197.254512472 197.712471655 E:maj 197.712471655 198.167437642 E:maj 198.167437642 198.628390023 E:maj 198.628390023 199.086349206 E:maj 199.086349206 199.547301587 E:maj 199.547301587 200.014240363 E:maj 200.014240363 200.475192744 E:maj 200.475192744 200.936145125 E:maj 200.936145125 201.4030839 E:maj 201.4030839 201.852063492 E:maj 201.852063492 202.31600907 E:maj 202.31600907 202.773968254 E:maj 202.773968254 203.240907029 E:maj 203.240907029 203.698866213 E:maj 203.698866213 204.159818594 E:maj 204.159818594 204.611791383 E:maj 204.611791383 205.072743764 E:maj 205.072743764 205.530702948 E:maj 205.530702948 205.991655329 E:maj 205.991655329 206.449614512 E:maj 206.449614512 206.910566893 E:maj 206.910566893 207.371519274 E:maj 207.371519274 207.829478458 E:maj 207.829478458 208.290430839 E:maj 208.290430839 208.754376417 E:maj 208.754376417 209.218321995 E:maj 209.218321995 209.676281179 E:maj 209.676281179 210.125260771 D:maj 210.125260771 210.574240363 E:maj 210.574240363 211.029206349 E:maj 211.029206349 211.484172336 E:maj 211.484172336 211.936145125 E:maj 211.936145125 212.397097506 E:maj 212.397097506 212.852063492 E:maj 212.852063492 213.310022676 E:maj 213.310022676 213.75600907 E:maj 213.75600907 214.210975057 E:maj 214.210975057 214.671927438 E:maj 214.671927438 215.126893424 E:maj 215.126893424 215.5938322 E:maj 215.5938322 216.051791383 E:maj 216.051791383 216.512743764 E:maj 216.512743764 216.967709751 E:maj 216.967709751 217.413696145 D:maj 217.413696145 217.865668934 E:maj 217.865668934 218.311655329 E:maj 218.311655329 218.769614512 E:maj 218.769614512 219.230566893 D:maj 219.230566893 219.697505669 E:maj 219.697505669 220.152471655 E:maj 220.152471655 220.607437642 E:maj 220.607437642 221.065396825 D:maj 221.065396825 221.517369615 E:maj 221.517369615 221.978321995 E:maj 221.978321995 222.454240363 E:maj 222.454240363 222.912199546 E:maj 222.912199546 223.373151927 E:maj 223.373151927 223.834104308 E:maj 223.834104308 224.292063492 E:maj 224.292063492 224.747029478 E:maj 224.747029478 225.199002268 E:maj 225.199002268 225.653968254 E:maj 225.653968254 226.105941043 E:maj 226.105941043 226.557913832 E:maj 226.557913832 227.024852608 E:maj 227.024852608 227.4738322 E:maj 227.4738322 227.931791383 E:maj 227.931791383 228.389750567 E:maj 228.389750567 228.856689342 E:maj 228.856689342 229.311655329 E:maj 229.311655329 229.778594104 E:maj 229.778594104 230.233560091 E:maj 230.233560091 230.68553288 C#:min 230.68553288 231.146485261 E:maj 231.146485261 231.607437642 E:maj 231.607437642 232.065396825 E:maj 232.065396825 232.529342404 E:maj 232.529342404 232.975328798 E:maj 232.975328798 233.436281179 E:maj 233.436281179 233.891247166 E:maj 233.891247166 234.352199546 E:maj 234.352199546 234.81015873 E:maj 234.81015873 235.274104308 E:maj 235.274104308 235.732063492 E:maj 235.732063492 236.190022676 E:maj 236.190022676 236.653968254 E:maj 236.653968254 237.10893424 E:maj 237.10893424 237.563900227 E:maj 237.563900227 238.018866213 E:maj 238.018866213 238.482811791 E:maj 238.482811791 238.937777778 E:maj 238.937777778 239.38675737 E:maj 239.38675737 239.853696145 E:maj 239.853696145 240.305668934 E:maj 240.305668934 240.763628118 E:maj 240.763628118 241.218594104 E:maj 241.218594104 241.673560091 E:maj 241.673560091 242.134512472 E:maj 242.134512472 242.592471655 E:maj 242.592471655 243.047437642 Gb:maj 243.047437642 243.51138322 E:maj 243.51138322 243.972335601 E:maj 243.972335601 244.430294785 E:maj 244.430294785 244.888253968 E:maj 244.888253968 245.358185941 E:maj 245.358185941 245.816145125 E:maj 245.816145125 246.277097506 E:maj 246.277097506 246.735056689 E:maj 246.735056689 247.201995465 E:maj 247.201995465 247.659954649 E:maj 247.659954649 248.120907029 E:maj 248.120907029 248.575873016 E:maj 248.575873016 249.036825397 E:maj 249.036825397 249.491791383 E:maj 249.491791383 249.964716553 E:maj 249.964716553 250.431655329 E:maj 250.431655329 250.886621315 E:maj 250.886621315 251.338594104 E:maj 251.338594104 251.793560091 E:maj 251.793560091 252.251519274 E:maj 252.251519274 252.715464853 E:maj 252.715464853 253.152471655 E:maj 253.152471655 253.607437642 E:maj 253.607437642 254.07138322 E:maj 254.07138322 254.523356009 E:maj 254.523356009 254.975328798 E:maj 254.975328798 255.430294785 E:maj 255.430294785 255.900226757 E:maj 255.900226757 256.358185941 E:maj 256.358185941 256.816145125 E:maj 256.816145125 257.274104308 E:maj 257.274104308 257.732063492 E:maj 257.732063492 258.193015873 E:maj 258.193015873 258.650975057 E:maj 258.650975057 259.114920635 E:maj 259.114920635 259.572879819 E:maj 259.572879819 260.039818594 E:maj 260.039818594 260.50675737 E:maj 260.50675737 260.964716553 E:maj 260.964716553 261.41968254 E:maj 261.41968254 261.877641723 E:maj 261.877641723 262.329614512 E:maj 262.329614512 262.784580499 E:maj 262.784580499 263.239546485 E:maj 263.239546485 263.68553288 E:maj 263.68553288 264.149478458 E:maj 264.149478458 264.610430839 E:maj 264.610430839 265.059410431 E:maj 265.059410431 265.526349206 E:maj 265.526349206 265.981315193 E:maj 265.981315193 266.442267574 E:maj 266.442267574 266.89723356 E:maj 266.89723356 267.352199546 E:maj 267.352199546 267.816145125 E:maj 267.816145125 268.274104308 E:maj 268.274104308 268.732063492 G:maj 268.732063492 269.19600907 E:maj 269.19600907 269.650975057 E:maj 269.650975057 270.114920635 E:maj 270.114920635 270.575873016 E:maj 270.575873016 271.039818594 E:maj 271.039818594 271.500770975 E:maj 271.500770975 271.955736961 E:maj 271.955736961 272.407709751 E:maj 272.407709751 272.868662132 E:maj 272.868662132 273.329614512 E:maj 273.329614512 273.787573696 E:maj 273.787573696 274.242539683 F#:min 274.242539683 274.706485261 E:maj 274.706485261 275.164444444 E:maj 275.164444444 275.625396825 E:maj 275.625396825 276.080362812 E:maj 276.080362812 276.535328798 E:maj 276.535328798 276.993287982 E:maj 276.993287982 277.454240363 E:maj 277.454240363 277.912199546 E:maj 277.912199546 278.364172336 E:maj 278.364172336 278.825124717 E:maj 278.825124717 279.280090703 E:maj 279.280090703 279.744036281 E:maj 279.744036281 280.204988662 E:maj 280.204988662 280.662947846 E:maj 280.662947846 281.117913832 E:maj 281.117913832 281.575873016 E:maj 281.575873016 282.036825397 C#:min 282.036825397 282.497777778 E:maj 282.497777778 282.958730159 E:maj 282.958730159 283.413696145 E:maj 283.413696145 283.865668934 E:maj 283.865668934 284.326621315 E:maj 284.326621315 284.775600907 E:maj 284.775600907 285.230566893 F#:min 285.230566893 285.688526077 E:maj 285.688526077 286.137505669 E:maj 286.137505669 286.589478458 E:maj 286.589478458 287.056417234 E:maj 287.056417234 287.520362812 E:maj 287.520362812 287.981315193 E:maj 287.981315193 288.433287982 E:maj 288.433287982 288.894240363 E:maj 288.894240363 289.343219955 E:maj 289.343219955 289.801179138 E:maj 289.801179138 290.256145125 E:maj 290.256145125 290.714104308 E:maj 290.714104308 291.172063492 E:maj 291.172063492 291.630022676 E:maj 291.630022676 292.07600907 E:maj 292.07600907 292.530975057 E:maj 292.530975057 292.985941043 E:maj 292.985941043 293.446893424 E:maj 293.446893424 293.895873016 E:maj 293.895873016 294.3538322 E:maj 294.3538322 294.805804989 E:maj 294.805804989 295.263764172 E:maj 295.263764172 295.724716553 E:maj 295.724716553 296.173696145 E:maj 296.173696145 296.634648526 E:maj 296.634648526 297.089614512 E:maj 297.089614512 297.550566893 E:maj 297.550566893 298.011519274 E:maj 298.011519274 298.475464853 E:maj 298.475464853 298.942403628 E:maj 298.942403628 299.406349206 E:maj 299.406349206 299.867301587 E:maj 299.867301587 300.33723356 E:maj 300.33723356 300.795192744 E:maj 300.795192744 301.259138322 E:maj 301.259138322 301.7230839 E:maj 301.7230839 302.193015873 E:maj 302.193015873 302.644988662 E:maj 302.644988662 303.10893424 E:maj 303.10893424 303.560907029 F#:min 303.560907029 304.02185941 E:maj 304.02185941 304.4738322 E:maj 304.4738322 304.928798186 E:maj 304.928798186 305.38675737 Gb:maj 305.38675737 305.841723356 E:maj 305.841723356 306.302675737 E:maj 306.302675737 306.754648526 E:maj 306.754648526 307.206621315 E:maj 307.206621315 307.667573696 E:maj 307.667573696 308.119546485 E:maj 308.119546485 308.580498866 E:maj 308.580498866 309.03845805 D:maj 309.03845805 309.496417234 E:maj 309.496417234 309.960362812 E:maj 309.960362812 310.418321995 E:maj 310.418321995 310.876281179 B:min 310.876281179 311.340226757 E:maj 311.340226757 311.789206349 E:maj 311.789206349 312.25015873 G:maj 312.25015873 312.714104308 E:maj 312.714104308 313.178049887 E:maj 313.178049887 313.630022676 E:maj 313.630022676 314.087981859 E:maj 314.087981859 314.54893424 E:maj 314.54893424 315.000907029 E:maj 315.000907029 315.449886621 E:maj 315.449886621 315.910839002 E:maj 315.910839002 316.362811791 E:maj 316.362811791 316.82675737 E:maj 316.82675737 317.275736961 E:maj 317.275736961 317.730702948 E:maj 317.730702948 318.188662132 E:maj 318.188662132 318.649614512 E:maj 318.649614512 319.104580499 E:maj 319.104580499 319.562539683 E:maj 319.562539683 320.023492063 E:maj 320.023492063 320.481451247 E:maj 320.481451247 320.933424036 E:maj 320.933424036 321.385396825 E:maj 321.385396825 321.840362812 F#:min 321.840362812 322.307301587 E:maj 322.307301587 322.750294785 E:maj 322.750294785 323.205260771 E:maj 323.205260771 323.660226757 E:maj 323.660226757 324.115192744 E:maj 324.115192744 324.564172336 E:maj 324.564172336 325.022131519 E:maj 325.022131519 325.474104308 C#:maj 325.474104308 325.932063492 F:min 325.932063492 326.390022676 N 326.390022676 326.844988662 N 326.844988662 327.299954649 N 327.299954649 327.751927438 F:min 327.751927438 328.206893424 E:maj 328.206893424 328.664852608 E:maj 328.664852608 329.1138322 E:maj 329.1138322 329.57478458 E:maj 329.57478458 330.032743764 E:maj 330.032743764 330.490702948 E:maj 330.490702948 330.960634921 E:maj 330.960634921 331.418594104 E:maj 331.418594104 331.870566893 D:maj 331.870566893 332.32553288 D:maj 332.32553288 332.777505669 D:min 332.777505669 333.256417234 C:maj 333.256417234 333.714376417 E:maj 333.714376417 334.172335601 B:min 334.172335601 334.627301587 F#:min 334.627301587 335.106213152 E:maj 335.106213152 335.576145125 E:maj 335.576145125 336.040090703 E:maj 336.040090703 336.477097506 F#:min 336.477097506 336.944036281 E:maj 336.944036281 337.404988662 E:maj 337.404988662 337.862947846 B:maj 337.862947846 338.326893424 D:maj 338.326893424 338.7938322 E:maj 338.7938322 339.25478458 E:maj 339.25478458 339.718730159 E:maj 339.718730159 340.17968254 Gb:maj 340.17968254 340.640634921 E:maj 340.640634921 341.095600907 E:maj 341.095600907 341.556553288 B:min 341.556553288 342.011519274 B:maj 342.011519274 342.487437642 E:maj 342.487437642 342.945396825 E:maj 342.945396825 343.406349206 E:maj 343.406349206 343.867301587 F#:min 343.867301587 344.313287982 E:maj 344.313287982 344.765260771 E:maj 344.765260771 345.235192744 Ab:min 345.235192744 345.696145125 D:maj 345.696145125 346.160090703 E:maj 346.160090703 346.630022676 E:maj 346.630022676 347.087981859 E:maj 347.087981859 347.527981859 F#:min 347.527981859 347.973968254 E:maj 347.973968254 348.434920635 E:maj 348.434920635 348.889886621 B:min 348.889886621 349.335873016 B:min 349.335873016 349.81478458 E:maj 349.81478458 350.33260771 A:maj 350.33260771 350.823492063 A:maj 350.823492063 351.314376417 N 351.314376417 351.78430839 N 351.78430839 352.269206349 N 352.269206349 352.757097506 G:min 352.757097506 353.224036281 N 353.224036281 353.723900227 Eb:maj 353.723900227 354.208798186 N 354.208798186 354.708662132 N 354.708662132 355.184580499 N 355.184580499 355.64553288 N 355.64553288 356.112471655 N 356.112471655 356.576417234 E:maj 356.576417234 357.025396825 F:min 357.025396825 357.47138322 N 357.47138322 357.932335601 N 357.932335601 358.399274376 N 358.399274376 358.863219955 N 358.863219955 359.300226757 N 359.300226757 359.776145125 N 359.776145125 360.246077098 N 360.246077098 360.692063492 N 360.692063492 361.15600907 N 361.15600907 361.634920635 Eb:maj 361.634920635 362.14675737 N 362.14675737 362.61968254 N 362.61968254 363.09260771 N 363.09260771 363.568526077 Eb:maj 363.568526077 364.035464853 N 364.035464853 364.493424036 C#:maj 364.493424036 364.960362812 Eb:min 364.960362812 365.412335601 N 365.412335601 365.870294785 D:maj 365.870294785 366.331247166 N 366.331247166 366.813151927 N 366.813151927 367.292063492 N 367.292063492 367.761995465 N 367.761995465 368.225941043 C#:maj 368.225941043 368.719818594 N 368.719818594 369.195736961 E:maj 369.195736961 369.701587302 N 369.701587302 370.168526077 N 370.168526077 370.63845805 N 370.63845805 371.11138322 Eb:maj 371.11138322 371.563356009 N 371.563356009 372.039274376 N 372.039274376 372.491247166 E:maj 372.491247166 372.946213152 N 372.946213152 373.404172336 N 373.404172336 373.880090703 N 373.880090703 374.373968254 Eb:maj 374.373968254 374.852879819 N 374.852879819 375.376689342 N 375.376689342 375.840634921 B:maj 375.840634921 376.340498866 N 376.340498866 376.807437642 N 376.807437642 377.286349206 E:maj 377.286349206 377.783219955 F:min 377.783219955 378.259138322 N 378.259138322 378.761995465 E:maj 378.761995465 379.26185941 N 379.26185941 379.764716553 N 379.764716553 380.237641723 Eb:maj 380.237641723 380.701587302 Eb:maj 380.701587302 381.177505669 N 381.177505669 381.641451247 Eb:maj 381.641451247 382.099410431 Eb:maj 382.099410431 382.563356009 N 382.563356009 383.030294785 N 383.030294785 383.494240363 N 383.494240363 383.967165533 N 383.967165533 384.455056689 Eb:min 384.455056689 384.907029478 N 384.907029478 385.376961451 N 385.376961451 385.837913832 N 385.837913832 386.322811791 N 386.322811791 386.777777778 Eb:maj 386.777777778 387.262675737 E:maj 387.262675737 387.711655329 Eb:maj 387.711655329 388.199546485 E:maj 388.199546485 388.684444444 N 388.684444444 389.154376417 N 389.154376417 389.621315193 C:maj 389.621315193 390.100226757 N 390.100226757 390.582131519 N 390.582131519 391.093968254 N 391.093968254 391.611791383 D:maj 391.611791383 391.711791383 Eb:maj mir_eval-0.8.2/tests/data/chord/output00.json000066400000000000000000000007321475740344600211040ustar00rootroot00000000000000{"thirds": 0.76314050772927455, "thirds_inv": 0.74084785691131028, "triads": 0.76314050772927455, "triads_inv": 0.74084785691131028, "tetrads": 0.74350305483862278, "tetrads_inv": 0.72121040402065839, "root": 0.80276927493052763, "mirex": 0.76314050772927455, "majmin": 0.76314050772927455, "majmin_inv": 0.74084785691131028, "sevenths": 0.74350305483862278, "sevenths_inv": 0.72121040402065839, "underseg": 0.900273562098, "overseg": 0.780828010977, "seg": 0.780828010977} mir_eval-0.8.2/tests/data/chord/output01.json000066400000000000000000000007261475740344600211100ustar00rootroot00000000000000{"thirds": 0.2257723638759061, "thirds_inv": 0.2257723638759061, "triads": 0.13168315063682912, "triads_inv": 0.13168315063682912, "tetrads": 0.13168315063682912, "tetrads_inv": 0.13168315063682912, "root": 0.88297902097902081, "mirex": 0.73392446544143686, "majmin": 0.73392446544143686, "majmin_inv": 0.73392446544143686, "sevenths": 0.73392446544143686, "sevenths_inv": 0.73392446544143686, "underseg": 0.897004020503, "overseg": 0.64457485294, "seg": 0.64457485294} mir_eval-0.8.2/tests/data/chord/output02.json000066400000000000000000000007271475740344600211120ustar00rootroot00000000000000{"thirds": 0.62235241230972749, "thirds_inv": 0.5999746953382874, "triads": 0.62235241230972749, "triads_inv": 0.5999746953382874, "tetrads": 0.59832989232691602, "tetrads_inv": 0.59832989232691602, "root": 0.73874627645401281, "mirex": 0.62235241230972749, "majmin": 0.62235241230972749, "majmin_inv": 0.5999746953382874, "sevenths": 0.59832989232691602, "sevenths_inv": 0.59832989232691602, "underseg": 0.947849657658, "overseg": 0.586538153191, "seg": 0.586538153191} mir_eval-0.8.2/tests/data/chord/output03.json000066400000000000000000000007251475740344600211110ustar00rootroot00000000000000{"thirds": 0.72013661910808879, "thirds_inv": 0.6752525345964725, "triads": 0.551201950767642, "triads_inv": 0.53919658590025954, "tetrads": 0.3184048214587859, "tetrads_inv": 0.30639945659140355, "root": 0.77169647053595714, "mirex": 0.60518026902732736, "majmin": 0.74138825567913169, "majmin_inv": 0.72524056878247878, "sevenths": 0.42826698064547669, "sevenths_inv": 0.41211929374882367, "underseg": 0.92753387865, "overseg": 0.858606159941, "seg": 0.858606159941} mir_eval-0.8.2/tests/data/chord/output04.json000066400000000000000000000007321475740344600211100ustar00rootroot00000000000000{"thirds": 0.61377316975360119, "thirds_inv": 0.54760240590439091, "triads": 0.61377316975360119, "triads_inv": 0.54760240590439091, "tetrads": 0.54216401269552861, "tetrads_inv": 0.48493654010175835, "root": 0.61377316975360119, "mirex": 0.70954975432509093, "majmin": 0.74187242134913767, "majmin_inv": 0.66189130256050943, "sevenths": 0.67437894070820537, "sevenths_inv": 0.60319567984343858, "underseg": 0.551395407985, "overseg": 0.942801858904, "seg": 0.551395407985} mir_eval-0.8.2/tests/data/chord/output05.json000066400000000000000000000007261475740344600211140ustar00rootroot00000000000000{"thirds": 0.54805508051922081, "thirds_inv": 0.53908937896741549, "triads": 0.5411086020794218, "triads_inv": 0.53214290052761659, "tetrads": 0.5411086020794218, "tetrads_inv": 0.53214290052761659, "root": 0.61754483525649884, "mirex": 0.5411086020794218, "majmin": 0.55139366172919813, "majmin_inv": 0.54225754563416062, "sevenths": 0.55139366172919813, "sevenths_inv": 0.54225754563416062, "underseg": 0.623182058069, "overseg": 0.71294165444, "seg": 0.623182058069} mir_eval-0.8.2/tests/data/chord/output06.json000066400000000000000000000007321475740344600211120ustar00rootroot00000000000000{"thirds": 0.86233665785350588, "thirds_inv": 0.85200037700744258, "triads": 0.86233665785350588, "triads_inv": 0.85200037700744258, "tetrads": 0.68752442224833576, "tetrads_inv": 0.67718814140227235, "root": 0.86233665785350588, "mirex": 0.87498407755581697, "majmin": 0.86233665785350588, "majmin_inv": 0.85200037700744258, "sevenths": 0.68752442224833576, "sevenths_inv": 0.67718814140227235, "underseg": 0.887955983157, "overseg": 0.878630816686, "seg": 0.878630816686} mir_eval-0.8.2/tests/data/chord/output07.json000066400000000000000000000007311475740344600211120ustar00rootroot00000000000000{"thirds": 0.79412682857142791, "thirds_inv": 0.58257699999999979, "triads": 0.7869349918367341, "triads_inv": 0.57538516326530587, "tetrads": 0.65067331836734621, "tetrads_inv": 0.47650731020408149, "root": 0.80047788571428513, "mirex": 0.84289421224489736, "majmin": 0.81069326801782837, "majmin_inv": 0.59275655958287776, "sevenths": 0.69772853045224192, "sevenths_inv": 0.49373832106319904, "underseg": 0.902303669388, "overseg": 0.900598579592, "seg": 0.900598579592} mir_eval-0.8.2/tests/data/chord/output08.json000066400000000000000000000007321475740344600211140ustar00rootroot00000000000000{"thirds": 0.58387551023364859, "thirds_inv": 0.58387551023364859, "triads": 0.51898833336814898, "triads_inv": 0.51898833336814898, "tetrads": 0.46432900228964935, "tetrads_inv": 0.46432900228964935, "root": 0.70902490931479811, "mirex": 0.61737654673925113, "majmin": 0.61737654673925113, "majmin_inv": 0.61737654673925113, "sevenths": 0.55235506764487585, "sevenths_inv": 0.55235506764487585, "underseg": 0.943561201816, "overseg": 0.554632653078, "seg": 0.554632653078} mir_eval-0.8.2/tests/data/chord/output09.json000066400000000000000000000007231475740344600211150ustar00rootroot00000000000000{"thirds": 0.7962928556965031, "thirds_inv": 0.7962928556965031, "triads": 0.7962928556965031, "triads_inv": 0.7962928556965031, "tetrads": 0.23258851286870402, "tetrads_inv": 0.23258851286870402, "root": 0.80729838398181941, "mirex": 0.7962928556965031, "majmin": 0.7962928556965031, "majmin_inv": 0.7962928556965031, "sevenths": 0.23258851286870402, "sevenths_inv": 0.23258851286870402, "underseg": 0.985101943227, "overseg": 0.269990550826, "seg": 0.269990550826} mir_eval-0.8.2/tests/data/chord/ref00.lab000066400000000000000000000050631475740344600201070ustar00rootroot000000000000000.0000 0.7353 N 0.7353 1.6222 G 1.6222 2.5039 D 2.5039 3.4158 G 3.4158 4.3394 D 4.3394 5.2630 G 5.2630 6.1983 D 6.1983 7.1336 G 7.1336 8.1394 D 8.1394 9.0071 G 9.0071 9.8811 D 9.8811 10.8047 G 10.8047 11.7049 D 11.7049 12.6285 G 12.6285 13.5755 D 13.5755 14.4874 G 14.4874 15.4227 D 15.4227 16.3463 G 16.3463 17.2789 D 17.2789 18.1936 E:min/b3 18.1936 19.1172 E:min 19.1172 20.9617 C 20.9617 22.8116 D 22.8116 23.7352 G 23.7352 24.6588 D 24.6588 25.5941 G 25.5941 26.5411 D 26.5411 27.4180 G 27.4180 28.3182 D 28.3182 29.2535 G 29.2535 30.1771 D 30.1771 31.0890 G 31.0890 32.0486 D 32.0486 32.9163 G 32.9163 33.8364 D 33.8364 34.7367 G 34.7367 35.6929 D 35.6929 36.5593 E:min/b3 36.5593 37.4958 E:min 37.4958 39.3080 C 39.3080 41.2136 B 41.2136 43.0842 E:min 43.0842 44.9081 C 44.9081 46.7991 G 46.7991 48.6142 B 48.6142 52.3137 E:min 52.3137 54.1441 G 54.1441 56.0543 G:7 56.0543 57.8503 C 57.8503 59.7371 D 59.7371 61.5447 G 61.5447 63.4153 E:min 63.4153 65.2902 C 65.2902 67.0864 D 67.0864 68.0567 G 68.0567 69.0037 D 69.0037 69.9273 G 69.9273 70.8860 D 70.8860 71.7979 G 71.7979 72.7098 D 72.7098 73.6335 G 73.6335 74.5571 D 74.5571 75.4456 G 75.4456 76.3809 D 76.3809 77.3279 G 77.3279 78.2632 D 78.2632 79.1751 G 79.1751 80.0753 D 80.0753 81.0106 E:min/b3 81.0106 81.9459 E:min 81.9459 83.7698 C 83.7698 85.6053 D 85.6053 86.5289 G 86.5289 87.4759 D 87.4759 88.4112 G 88.4112 89.3348 D 89.3348 90.2701 G 90.2701 91.1586 D 91.1586 92.0822 G 92.0822 92.9942 D 92.9942 93.9061 G 93.9061 94.8414 D 94.8414 95.7884 G 95.7884 96.6886 D 96.6886 97.6473 G 97.6473 98.5592 D 98.5592 99.5067 E:min/b3 99.5067 100.3596 E:min 100.3596 102.1952 C 102.1952 104.0656 D 104.0656 105.0011 G 105.0011 105.9364 D 105.9364 106.8132 G 106.8132 107.7602 D 107.7602 108.6254 G 108.6254 109.5723 D 109.5723 110.5193 G 110.5193 111.4196 D 111.4196 112.3549 G 112.3549 113.2434 D 113.2434 114.1670 G 114.1670 115.1023 D 115.1023 116.0142 G 116.0142 116.9261 D 116.9261 117.8497 E:min/b3 117.8497 118.7734 E:min 118.7734 120.6556 C 120.6556 122.5146 B:7 122.5146 124.3501 E:min 124.3501 126.1739 C 126.1739 128.0328 G 128.0328 129.8917 B 129.8917 131.7974 E:min 131.7974 133.5979 E:min 133.5979 135.4801 G 135.4801 137.3157 G:7 137.3157 139.1863 C 139.1863 141.0686 D 141.0686 142.9041 G 142.9041 144.7396 E:min 144.7396 146.6336 C 146.6336 148.5159 D 148.5159 149.4395 G 149.4395 150.4099 D 150.4099 151.3335 G 151.3335 152.2922 D 152.2922 153.2041 G 153.2041 154.1745 D 154.1745 155.0981 G 155.0981 156.0296 D 156.0296 156.9336 G 156.9336 157.8806 D 157.8806 158.7925 G 158.7925 159.7629 D 159.7629 160.7099 G 160.7099 161.6452 D mir_eval-0.8.2/tests/data/chord/ref01.lab000066400000000000000000000015521475740344600201070ustar00rootroot000000000000000.0000 1.7350 N 1.7350 6.2900 N 6.2900 37.4125 C:min(*b3) 37.4125 60.0224 C:min(*b3) 60.0224 61.4902 Bb 61.4902 62.0114 C:min(*b3) 62.0114 63.3928 Bb 63.3928 63.9312 C:min(*b3) 63.9312 65.2770 Bb 65.2770 65.7802 C:min(*b3) 65.7802 67.1846 Bb 67.1846 90.2743 C:min(*b3) 90.2743 91.7255 Bb 91.7255 92.3136 C:min(*b3) 92.3136 93.6330 Bb 93.6330 94.1714 C:min(*b3) 94.1714 95.5172 Bb 95.5172 96.0672 C:min(*b3) 96.0672 97.4248 Bb 97.4248 117.1151 C:min(*b3) 117.1151 118.5601 Bb 118.5601 119.1101 C:min(*b3) 119.1101 120.4911 Bb 120.4911 121.0411 C:min(*b3) 121.0411 122.4221 Bb 122.4221 122.9487 C:min(*b3) 122.9487 124.2711 Bb 124.2711 147.1664 C:min(*b3) 147.1664 148.6950 Bb 148.6950 149.2450 C:min(*b3) 149.2450 150.5791 Bb 150.5791 151.0941 C:min(*b3) 151.0941 152.4750 Bb 152.4750 152.9665 C:min(*b3) 152.9665 154.4060 Bb 154.4060 179.3023 C:min(*b3) 179.3023 183.6835 N mir_eval-0.8.2/tests/data/chord/ref02.lab000066400000000000000000000040361475740344600201100ustar00rootroot000000000000000.0000 0.8622 N 0.8622 2.3859 E 2.3859 2.6761 B:9 2.6761 4.8816 E 4.8816 5.1950 E/5 5.1950 5.4852 D 5.4852 5.8334 D# 5.8334 7.0986 E 7.0986 8.3755 C#:min 8.3755 9.6407 A 9.6407 10.9408 B 10.9408 12.9373 E 12.9373 13.5873 E/7 13.5873 15.5606 C#:min 15.5606 16.2338 C#:min/b7 16.2338 18.8572 A 18.8572 21.5037 B 21.5037 23.4654 E 23.4654 24.1038 E/7 24.1038 26.1004 C#:min 26.1004 26.7504 C#:min/b7 26.7504 29.3737 A 29.3737 32.0086 B 32.0086 36.5588 C#:min 36.5588 37.2205 C#:min/b7 37.2205 39.8670 A 39.8670 42.4671 B 42.4671 44.4288 E 44.4288 45.0440 E/7 45.0440 46.9709 C#:min 46.9709 47.6093 C#:min/b7 47.6093 48.9558 A 48.9558 50.2095 B 50.2095 52.8908 E 52.8908 54.8177 E 54.8177 55.4561 E/7 55.4561 57.4642 C#:min 57.4642 58.0910 C#:min/b7 58.0910 60.7608 A 60.7608 63.3609 B 63.3609 65.3458 E 65.3458 65.9726 E/7 65.9726 67.9995 C#:min 67.9995 68.6076 C#:min/b7 68.6076 71.2309 A 71.2309 73.7962 B 73.7962 78.3812 C#:min 78.3812 79.0197 C#:min/b7 79.0197 81.6314 A 81.6314 84.2431 B 84.2431 86.1468 E 86.1468 86.8200 E/7 86.8200 88.7701 C#:min 88.7701 89.3853 C#:min/b7 89.3853 90.7318 A 90.7318 91.9738 B 91.9738 94.5971 E 94.5971 97.2088 A 97.2088 99.7625 F#:min 99.7625 102.3510 D 102.3510 104.9047 E 104.9047 107.4468 A 107.4468 110.0237 F#:min 110.0237 111.3121 D 111.3121 112.6122 E 112.6122 113.9007 A 113.9007 115.1659 B 115.1659 117.7776 E 117.7776 120.0514 C#:min 120.0514 120.3893 C#:min/b7 120.3893 123.0011 A 123.0011 125.5896 B 125.5896 127.5558 E 127.5558 128.2129 E/7 128.2129 130.1402 C#:min 130.1402 130.8014 C#:min/b7 130.8014 133.3899 A 133.3899 136.0132 B 136.0132 140.5286 C#:min 140.5286 141.1786 C#:min/b7 141.1786 143.8600 A 143.8600 146.4369 B 146.4369 148.3651 E 148.3651 149.0254 E/7 149.0254 150.8729 C#:min 150.8729 151.6139 C#:min/b7 151.6139 152.8792 A 152.8792 154.1444 B 154.1444 156.0417 C#:min 156.0417 156.6981 C#:min/b7 156.6981 157.9981 A 157.9981 159.2518 B 159.2518 161.1438 C#:min 161.1438 161.7822 C#:min/b7 161.7822 163.0707 A 163.0707 164.3475 B 164.3475 165.9842 E 165.9842 166.3673 B 166.3673 168.7149 E 168.7149 171.5099 N mir_eval-0.8.2/tests/data/chord/ref03.lab000066400000000000000000000141721475740344600201130ustar00rootroot000000000000000.0000 1.4231 N 1.4231 2.5480 D:min 2.5480 3.6972 D:min/2 3.6972 4.7651 D:min/b3 4.7651 5.4698 D:min/4 5.4698 5.8098 D:min/5 5.8098 8.0268 E:9 8.0268 10.3368 Bb:7 10.3368 14.5504 A:aug 14.5504 27.8875 A:min 27.8875 28.9710 A:min 28.9710 30.0117 C 30.0117 31.0959 D:min7(2,*b3,4) 31.0959 32.1359 F 32.1359 32.6351 G 32.6351 33.2039 G#:aug 33.2039 36.1690 A:min 36.1690 37.3942 A 37.3942 49.7099 D:min 49.7099 50.6734 D:min 50.6734 51.7065 F 51.7065 52.7279 C 52.7279 53.7610 Bb 53.7610 54.1208 D:(1,4) 54.1208 54.4691 D#:(1,4) 54.4691 54.8289 E:(1,4) 54.8289 66.7152 E:9 66.7152 79.0425 A:min 79.0425 80.0524 A:min 80.0524 81.0738 C 81.0738 82.0953 D:min7(2,*b3,4) 82.0953 83.1400 F 83.1400 83.5927 G 83.5927 84.0918 G#:aug 84.0918 86.9958 A:min 86.9958 88.1893 A 88.1893 100.4470 D:min 100.4470 101.4801 D:min 101.4801 102.4783 F 102.4783 103.5230 C 103.5230 104.5677 Bb 104.5677 104.8811 D:(1,4) 104.8811 105.1829 D#:(1,4) 105.1829 105.5892 E:(1,4) 105.5892 117.6844 E:9 117.6844 118.9960 D:min 118.9960 120.2497 D:min/2 120.2497 121.5149 D:min/b3 121.5149 122.3652 D:min/4 122.3652 122.8033 D:min/5 122.8033 125.2990 E:9 125.2990 127.7366 Bb:7 127.7366 130.2322 A:aug 130.2322 131.5051 D:min 131.5051 132.7047 D:min/2 132.7047 133.9351 D:min/b3 133.9351 134.7698 D:min/4 134.7698 135.1655 D:min/5 135.1655 137.6147 E:9 137.6147 140.0871 Bb:7 140.0871 145.2120 A:aug 145.2120 159.1701 A:min 159.1701 160.2612 A:min 160.2612 161.3408 C 161.3408 162.4435 D:min7(2,*b3,4) 162.4435 163.4534 F 163.4534 163.9525 G 163.9525 164.5213 G#:aug 164.5213 166.6339 A:min 166.6339 168.7464 A 168.7464 181.5497 D:min 181.5497 182.6408 D:min 182.6408 183.7203 F 183.7203 184.7650 C 184.7650 185.8329 Bb 185.8329 186.1695 D:(1,4) 186.1695 186.4713 D#:(1,4) 186.4713 186.8544 E:(1,4) 186.8544 199.1975 E:9 199.1975 200.4702 D:min 200.4702 201.7818 D:min/2 201.7818 203.0122 D:min/b3 203.0122 203.8132 D:min/4 203.8132 204.3007 D:min/5 204.3007 206.7499 E:9 206.7499 209.1527 Bb:7 209.1527 211.6599 A:aug 211.6599 212.9484 D:min 212.9484 214.1324 D:min/2 214.1324 215.4092 D:min/b3 215.4092 216.2101 D:min/4 216.2101 216.6977 D:min/5 216.6977 219.1353 E:9 219.1353 221.6425 Bb:7 221.6425 226.6454 A:aug 226.6454 239.0076 A:min 239.0076 240.0407 A:min 240.0407 241.0621 C 241.0621 242.0836 D:min7(2,*b3,4) 242.0836 243.1283 F 243.1283 243.6274 G 243.6274 244.1382 G#:aug 244.1382 248.1776 A:min 248.1776 260.5050 D:min 260.5050 261.5148 D:min 261.5148 262.5711 F 262.5711 263.6506 C 263.6506 264.6489 Bb 264.6489 264.9971 D:(1,4) 264.9971 265.2989 D#:(1,4) 265.2989 265.6264 E:(1,4) 265.6264 277.9550 E:9 277.9550 279.1585 D:min 279.1585 280.5282 D:min/2 280.5282 281.7818 D:min/b3 281.7818 283.0238 D:min/4 283.0238 284.7097 E:9 284.7097 285.0891 C:(1) 285.0891 285.4846 B:(1) 285.4846 287.9338 Bb:7 287.9338 290.4179 A:aug 290.4179 291.6483 D:min 291.6483 292.9019 D:min/2 292.9019 294.1091 D:min/b3 294.1091 294.9913 D:min/4 294.9913 295.4440 D:min/5 295.4440 297.0943 E:9 297.0943 297.4835 C:(1) 297.4835 297.8700 B:(1) 297.8700 300.3773 Bb:7 300.3773 302.8845 A:aug 302.8845 304.1149 D:min 304.1149 305.4034 D:min/2 305.4034 306.7034 D:min/b3 306.7034 307.5392 D:min/4 307.5392 307.9687 D:min/5 307.9687 309.6346 E:9 309.6346 310.0335 C:(1) 310.0335 310.4643 B:(1) 310.4643 312.9251 Bb:7 312.9251 315.4324 A:aug 315.4324 316.6280 D:min 316.6280 317.8816 D:min/2 317.8816 319.1933 D:min/b3 319.1933 319.9826 D:min/4 319.9826 320.3889 D:min/5 320.3889 322.0387 E:9 322.0387 322.4375 C:(1) 322.4375 322.8381 B:(1) 322.8381 325.3453 Bb:7 325.3453 327.8526 A:aug 327.8526 329.0830 D:min 329.0830 330.3482 D:min/2 330.3482 331.5902 D:min/b3 331.5902 332.3912 D:min/4 332.3912 332.8787 D:min/5 332.8787 334.5498 E:9 334.5498 334.9389 C:(1) 334.9389 335.3279 B:(1) 335.3279 337.8584 Bb:7 337.8584 340.4121 A:aug 340.4121 341.5960 D:min 341.5960 342.9193 D:min/2 342.9193 344.1729 D:min/b3 344.1729 344.9855 D:min/4 344.9855 345.4382 D:min/5 345.4382 347.1095 E:9 347.1095 347.4987 C:(1) 347.4987 347.9222 B:(1) 347.9222 350.4527 Bb:7 350.4527 353.0412 A:aug 353.0412 354.2484 D:min 354.2484 355.6413 D:min/2 355.6413 356.8137 D:min/b3 356.8137 357.6378 D:min/4 357.6378 358.0325 D:min/5 358.0325 359.6401 E:9 359.6401 360.0584 C:(1) 360.0584 360.4469 B:(1) 360.4469 362.9541 Bb:7 362.9541 365.4962 A:aug 365.4962 366.7498 D:min 366.7498 368.0383 D:min/2 368.0383 369.2571 D:min/b3 369.2571 370.0812 D:min/4 370.0812 370.5107 D:min/5 370.5107 372.1998 E:9 372.1998 372.5792 C:(1) 372.5792 373.0064 B:(1) 373.0064 375.4788 Bb:7 375.4788 378.1137 A:aug 378.1137 379.3325 D:min 379.3325 380.6210 D:min/2 380.6210 381.8978 D:min/b3 381.8978 382.6987 D:min/4 382.6987 383.1863 D:min/5 383.1863 384.8957 E:9 384.8957 385.3238 C:(1) 385.3238 385.7400 B:(1) 385.7400 388.2356 Bb:7 388.2356 390.7312 A:aug 390.7312 392.0893 D:min 392.0893 393.3314 D:min/2 393.3314 394.6082 D:min/b3 394.6082 395.4788 D:min/4 395.4788 395.9547 D:min/5 395.9547 397.5625 E:9 397.5625 398.0100 C:(1) 398.0100 398.3807 B:(1) 398.3807 400.8647 Bb:7 400.8647 403.4416 A:aug 403.4416 404.6720 D:min 404.6720 405.9837 D:min/2 405.9837 407.2141 D:min/b3 407.2141 408.0753 D:min/4 408.0753 408.4561 D:min/5 408.4561 410.2098 E:9 410.2098 410.6087 C:(1) 410.6087 410.9982 B:(1) 410.9982 413.5751 Bb:7 413.5751 416.1404 A:aug 416.1404 417.3592 D:min 417.3592 418.6941 D:min/2 418.6941 419.9477 D:min/b3 419.9477 420.8299 D:min/4 420.8299 421.2826 D:min/5 421.2826 423.0225 E:9 423.0225 423.4408 C:(1) 423.4408 423.8479 B:(1) 423.8479 426.3784 Bb:7 426.3784 428.9553 A:aug 428.9553 430.2205 D:min 430.2205 431.4973 D:min/2 431.4973 432.7510 D:min/b3 432.7510 433.5287 D:min/4 433.5287 433.9698 D:min/5 433.9698 435.7184 E:9 435.7184 436.1368 C:(1) 436.1368 436.5583 B:(1) 436.5583 439.1352 Bb:7 439.1352 441.6308 A:aug 441.6308 442.8960 D:min 442.8960 444.1613 D:min/2 444.1613 445.4962 D:min/b3 445.4962 446.2971 D:min/4 446.2971 446.7498 D:min/5 446.7498 448.3852 E:9 448.3852 448.8522 C:(1) 448.8522 449.2919 B:(1) 449.2919 451.7875 Bb:7 451.7875 454.3760 A:aug 454.3760 455.6645 D:min 455.6645 456.9761 D:min/2 456.9761 458.2065 D:min/b3 458.2065 459.0771 D:min/4 459.0771 459.5530 D:min/5 459.5530 461.2562 E:9 461.2562 461.6454 C:(1) 461.6454 462.0603 B:(1) 462.0603 464.5791 Bb:7 464.5791 465.0175 A 465.0175 468.0824 N mir_eval-0.8.2/tests/data/chord/ref04.lab000066400000000000000000000042141475740344600201100ustar00rootroot000000000000000.0000 0.9834 N 0.9834 5.2007 F:maj(9)/5 5.2007 7.2649 C 7.2649 9.3524 F:maj(9)/5 9.3524 12.6900 G 12.6900 13.4356 C/5 13.4356 16.7909 G 16.7909 17.4707 C/5 17.4707 18.7865 G 18.7865 19.4882 C/5 19.4882 20.8259 G 20.8259 21.5057 C/5 21.5057 24.8609 G 24.8609 25.4930 C/5 25.4930 27.4989 C 27.4989 29.4814 D:min7(4)/5 29.4814 31.4990 E:min7 31.4990 33.5049 F:maj(9)/6 33.5049 35.5458 C 35.5458 37.4934 D:min7(4)/5 37.4934 39.5226 E:min7 39.5226 41.5168 F:maj(9) 41.5168 44.8388 G 44.8388 45.5186 C/5 45.5186 46.7905 G 46.7905 47.4923 C/5 47.4923 48.8080 G 48.8080 49.4221 C/5 49.4221 50.7378 G 50.7378 51.4177 C/5 51.4177 52.7115 G 52.7115 53.3913 C/5 53.3913 54.6194 G 54.6194 55.3430 C/5 55.3430 56.6150 G 56.6150 57.2948 C/5 57.2948 58.6105 G 58.6105 59.2904 C/5 59.2904 60.5623 G 60.5623 61.2377 C/5 61.2377 63.2202 C 63.2202 65.2145 D:min7(4)/b7 65.2145 67.1271 E:min7 67.1271 69.0747 F:maj(9)/6 69.0747 71.1739 C 71.1739 73.0398 D:min7(4)/b7 73.0398 74.9991 E:min7 74.9991 77.0167 F:maj(9) 77.0167 77.4715 F 77.4715 77.9963 C/3 77.9963 78.4511 F 78.4511 78.9572 C/3 78.9572 79.4307 F 79.4307 79.9205 C/3 79.9205 80.4220 F 80.4220 80.9235 C/4 80.9235 82.9294 C 82.9294 84.8770 D:min7(4)/b7 84.8770 86.8362 E:min7/b3 86.8362 88.7955 F:maj(9) 88.7955 90.7548 C 90.7548 92.7607 D:min7(4)/b7 92.7607 94.7316 E:min7/b3 94.7316 96.7141 F:maj(9) 96.7141 118.3826 G 118.3826 120.2905 C 120.2905 122.2544 D:min7(4)/b7 122.2544 124.2487 E:min7/b3 124.2487 126.1729 F:maj(9) 126.1729 128.1672 C 128.1672 130.1148 D:min7(4)/b7 130.1148 132.1090 E:min7/b3 132.1090 134.0799 F:maj(9) 134.0799 134.5910 F 134.5910 135.0813 C/3 135.0813 135.5429 F 135.5429 136.0622 C/3 136.0622 136.5215 F 136.5215 137.0239 C/5 137.0239 137.5086 F/3 137.5086 138.0626 G/3 138.0626 139.9693 C 139.9693 141.9286 D:min7(4)/b7 141.9286 143.8878 E:min7/b3 143.8878 145.8704 F:maj(9) 145.8704 147.8530 C 147.8530 149.8706 D:min7(4)/b7 149.8706 151.8065 E:min7/b3 151.8065 153.7891 F:maj(9) 153.7891 154.1972 F 154.1972 154.7570 C/3 154.7570 155.2352 F 155.2352 155.7483 C/3 155.7483 156.1915 F 156.1915 156.6930 C/3 156.6930 157.2194 F 157.2194 157.6842 G/3 157.6842 159.2389 C 159.2389 168.2981 G:(1) 168.2981 169.0674 N mir_eval-0.8.2/tests/data/chord/ref05.lab000066400000000000000000000052611475740344600201140ustar00rootroot000000000000000.0000 0.3450 N 0.3450 1.6735 Ab/5 1.6735 3.0846 Eb 3.0846 3.7610 Ab 3.7610 4.4258 Db 4.4258 5.1372 Ab 5.1372 5.7902 Db 5.7902 6.5016 Ab 6.5016 7.1664 Db 7.1664 7.9011 Ab 7.9011 8.5775 Db 8.5775 10.0003 Bb:min 10.0003 11.3881 F:min 11.3881 12.7642 Eb 12.7642 13.4816 Ab 13.4816 14.1987 Db 14.1987 15.5982 Bb:min 15.5982 16.9860 F:min 16.9860 18.3854 Eb 18.3854 19.8082 F:min 19.8082 21.2194 Bb:min 21.2194 21.9191 Ab 21.9191 22.5955 Db 22.5955 23.9950 Eb 23.9950 24.6830 Ab 24.6830 25.4061 Db 25.4061 26.7939 Bb:min 26.7939 28.1700 Db 28.1700 28.8581 Ab 28.8581 29.5695 Db 29.5695 30.2809 Ab 30.2809 30.9573 Db 30.9573 31.6570 Ab 31.6570 32.3568 Db 32.3568 33.0039 Ab 33.0039 33.6771 Db 33.6771 35.1557 Bb:min 35.1557 36.5668 F:min 36.5668 37.9197 Eb 37.9197 38.6427 Ab 38.6427 39.3308 Db 39.3308 40.7419 Bb:min 40.7419 42.1064 F:min 42.1064 43.5292 Eb 43.5292 44.8937 F:min 44.8937 46.3165 Bb:min 46.3165 46.9929 Ab 46.9929 47.7159 Db 47.7159 49.1504 Eb 49.1504 49.8501 Ab 49.8501 50.5382 Db 50.5382 51.9260 Bb:min 51.9260 53.3371 Db 53.3371 54.0368 Ab 54.0368 54.7599 Db 54.7599 55.4596 Ab 55.4596 56.1594 Db 56.1594 56.8708 Ab 56.8708 57.5588 Db 57.5588 58.9700 Ab 58.9700 61.8039 Db 61.8039 64.6261 Ab 64.6261 67.4134 Db 67.4134 68.8012 Eb:sus4 68.8012 70.2124 Eb 70.2124 70.9587 Ab 70.9587 71.6701 Db 71.6701 73.0696 Bb:min 73.0696 74.4574 F:min 74.4574 75.8802 Eb 75.8802 76.6616 Ab 76.6616 77.3263 Db 77.3263 78.7258 Bb:min 78.7258 80.1252 F:min 80.1252 81.5364 Eb 81.5364 82.9475 F:min 82.9475 84.3820 Bb:min 84.3820 85.0933 Ab 85.0933 85.7814 Db 85.7814 87.1809 Eb 87.1809 87.9039 Ab 87.9039 88.5920 Db 88.5920 90.0031 Bb:min 90.0031 91.4376 Db 91.4376 92.1257 Ab 92.1257 92.8837 Db 92.8837 93.5718 Ab 93.5718 94.2948 Db 94.2948 94.9712 Ab 94.9712 95.6710 Db 95.6710 97.1171 Ab 97.1171 99.8927 Db 99.8927 102.6800 Ab 102.6800 105.4906 Db 105.4906 106.8667 Eb:sus4 106.8667 108.2545 Eb 108.2545 108.9776 Ab 108.9776 109.6890 Db 109.6890 111.1118 Bb:min 111.1118 112.4996 F:min 112.4996 113.8757 Eb 113.8757 114.5988 Ab 114.5988 115.3102 Db 115.3102 116.6746 Bb:min 116.6746 118.0974 F:min 118.0974 119.5319 Eb 119.5319 120.9314 F:min 120.9314 122.3308 Bb:min 122.3308 123.0655 Ab 123.0655 123.7536 Db 123.7536 125.1181 Eb 125.1181 125.8645 Ab 125.8645 126.5759 Db 126.5759 127.9637 Bb:min 127.9637 129.3748 Db 129.3748 130.1095 Ab 130.1095 130.8442 Db 130.8442 131.5323 Ab 131.5323 132.2320 Db 132.2320 132.9085 Ab 132.9085 133.6548 Db 133.6548 134.3546 Ab 134.3546 135.0776 Db 135.0776 135.7540 Ab 135.7540 136.4188 Db 136.4188 137.1418 Ab 137.1418 137.8299 Db 137.8299 138.5646 Ab 138.5646 139.2644 Db 139.2644 139.9874 Ab 139.9874 140.6638 Db 140.6638 141.3986 Ab 141.3986 142.0633 Db 142.0633 142.7864 Ab 142.7864 148.1758 N mir_eval-0.8.2/tests/data/chord/ref06.lab000066400000000000000000000040031475740344600201060ustar00rootroot000000000000000.000 0.310 N 0.310 1.968 D:min 1.968 4.090 F:maj/5 4.090 5.762 C:maj 5.762 7.945 G:maj 7.945 9.839 D:min 9.839 11.758 G:maj 11.758 14.169 C:maj 14.169 14.866 F:maj/5 14.866 15.598 C:maj 15.598 17.490 D:min 17.490 19.435 G:maj 19.435 19.893 C:maj 19.893 20.633 F:maj/5 20.633 21.823 C:maj 21.823 22.568 F:maj/5 22.568 23.252 C:maj 23.252 25.177 D:min 25.177 27.069 G:maj 27.069 29.476 C:maj 29.476 30.189 F:maj/5 30.189 30.935 C:maj 30.935 32.805 D:min 32.805 34.723 Bb:maj 34.723 38.525 G:maj 38.525 40.200 D:min 40.200 42.386 F:maj 42.386 44.055 C:maj 44.055 46.171 G:maj 46.171 47.893 D:min 47.893 50.007 F:maj 50.007 51.661 C:maj 51.661 53.838 G:maj 53.838 55.520 D:min 55.520 57.692 F:maj 57.692 59.340 C:maj 59.340 61.472 G:maj 61.472 63.188 D:min 63.188 65.301 Bb:maj 65.301 69.121 G:maj 69.121 71.064 D:min 71.064 72.936 G:maj 72.936 75.432 C:maj 75.432 76.874 F:maj/5 76.874 78.776 D:min 78.776 80.622 G:maj 80.622 84.473 C:maj 84.473 86.388 D:min 86.388 88.312 G:maj 88.312 92.141 C:maj 92.141 94.019 D:min 94.019 95.938 Bb:maj 95.938 99.779 G:maj 99.779 101.433 D:min 101.433 103.570 F:maj 103.570 105.260 C:maj 105.260 107.386 G:maj 107.386 109.076 D:min 109.076 111.256 F:maj 111.256 112.825 C:maj 112.825 115.028 G:maj 115.028 116.681 D:min 116.681 118.839 F:maj 118.839 120.500 C:maj 120.500 122.629 G:maj 122.629 124.323 D:min 124.323 126.451 Bb:maj 126.451 130.272 G:maj 130.272 132.201 D:min 132.201 134.093 G:maj 134.093 137.964 C:maj 137.964 139.831 D:min 139.831 141.742 G:maj 141.742 145.564 C:maj 145.564 147.523 D:min 147.523 149.379 G:maj 149.379 153.236 C:maj 153.236 155.123 D:min 155.123 157.003 Bb:maj 157.003 160.842 G:maj 160.842 162.568 D:min 162.568 164.689 F:maj 164.689 166.337 C:maj 166.337 168.512 G:maj 168.512 170.200 D:min 170.200 172.293 F:maj 172.293 174.016 C:maj 174.016 176.142 G:maj 176.142 177.866 D:min 177.866 179.987 F:maj 179.987 181.648 C:maj 181.648 183.766 G:maj 183.766 185.430 D:min 185.430 187.603 Bb:maj 187.603 191.407 G:maj 191.407 193.078 D:min 193.078 195.247 Bb:maj 195.247 204.240 F:maj mir_eval-0.8.2/tests/data/chord/ref07.lab000066400000000000000000000055471475740344600201250ustar00rootroot000000000000000.000 0.105 N 0.105 1.923 Eb:maj 1.923 3.826 Ab:maj/5 3.826 5.667 Bb:maj(4)/4 5.667 7.545 Ab:maj/5 7.545 9.467 Eb:maj 9.467 11.282 Ab:maj7 11.282 13.146 Bb:maj/3 13.146 14.858 G:min 14.858 16.658 C:min 16.658 18.458 C:min7/b7 18.458 20.274 C:min(6)/6 20.274 22.106 Ab:maj 22.106 23.906 Eb:maj/5 23.906 25.746 Bb:maj 25.746 27.482 G:maj/3 27.482 28.506 C:min 28.506 29.170 Bb:maj/3 29.170 30.970 Eb:maj 30.970 32.746 F:min7 32.746 34.522 Ab:maj 34.522 38.074 Bb:maj/3 38.074 39.882 Eb:maj 39.882 41.706 Ab:maj7 41.706 43.516 Bb:maj/3 43.516 45.346 G:min 45.346 47.139 C:min 47.139 48.907 C:min7/b7 48.907 50.762 C:min(6)/6 50.762 52.546 Ab:maj 52.546 54.330 Eb:maj/5 54.330 56.106 Bb:maj 56.106 57.819 G:maj/3 57.819 58.906 C:min 58.906 59.560 Bb:maj/3 59.560 61.386 Eb:maj 61.386 63.162 F:min7 63.162 64.938 Ab:maj 64.938 66.286 Eb:maj 66.286 67.650 Ab:maj/5 67.650 68.554 Eb:maj 68.554 70.382 Bb:maj/3 70.382 72.203 C:min 72.203 73.978 F:min7 73.978 75.762 Ab:maj 75.762 77.627 Bb:maj/3 77.627 79.379 C:min 79.379 81.197 F:min7 81.197 82.940 Ab:maj 82.940 84.685 C:min 84.685 86.540 C:min7/b7 86.540 88.346 C:min(6)/6 88.346 91.859 Ab:maj6 91.859 93.675 Eb:maj/3 93.675 95.411 Ab:maj6 95.411 97.187 Ab:maj 97.187 98.955 Bb:maj 98.955 99.818 Bb:sus4 99.818 100.707 Bb:maj 100.707 102.475 Eb:maj 102.475 104.233 Ab:maj/5 104.233 106.001 Bb:maj(4)/4 106.001 107.827 Ab:maj/5 107.827 109.643 Eb:maj 109.643 111.427 Ab:maj7 111.427 113.230 Bb:maj/3 113.230 115.065 G:min 115.065 116.880 C:min 116.880 118.726 C:min7/b7 118.726 120.518 C:min(6)/6 120.518 122.344 Ab:maj 122.344 124.134 Eb:maj/5 124.134 125.980 Bb:maj 125.980 127.751 G:maj/3 127.751 128.863 C:min 128.863 129.519 Bb:maj/3 129.519 131.326 Eb:maj 131.326 133.119 F:min7 133.119 134.958 Ab:maj 134.958 138.567 Bb:maj 138.567 140.400 Eb:maj 140.400 142.182 Ab:maj7 142.182 144.014 Bb:maj/3 144.014 145.774 G:min 145.774 147.582 C:min 147.582 149.383 C:min7/b7 149.383 151.187 C:min(6)/6 151.187 152.990 Ab:maj 152.990 154.758 Eb:maj/5 154.758 156.591 Bb:maj 156.591 158.382 G:maj/3 158.382 159.478 C:min 159.478 160.134 Bb:maj/3 160.134 161.958 Eb:maj 161.958 163.737 F:min7 163.737 165.454 Ab:maj 165.454 169.046 Eb:maj 169.046 170.854 Bb:maj/3 170.854 172.662 C:min 172.662 174.406 F:min7 174.406 176.247 Ab:maj 176.247 177.991 Bb:maj/3 177.991 179.830 C:min 179.830 181.606 F:min7 181.606 183.414 Ab:maj 183.414 185.118 C:min 185.118 186.998 C:min7/b7 186.998 188.774 C:min(6)/6 188.774 192.399 Ab:maj6 192.399 194.166 Eb:maj/3 194.166 195.862 Ab:maj6 195.862 197.590 Ab:maj 197.590 199.391 Bb:maj 199.391 200.290 Bb:sus4 200.290 201.142 Bb:maj 201.142 202.910 C:min 202.910 204.673 C:min7/b7 204.673 206.446 C:min(6)/6 206.446 210.046 Ab:maj6 210.046 211.774 Eb:maj/3 211.774 213.622 Ab:maj6 213.622 215.318 Ab:maj 215.318 217.130 Eb:maj 217.130 218.862 Ab:maj/5 218.862 220.671 Bb:maj(4)/4 220.671 222.850 Ab:maj/5 222.850 228.785 Eb:maj 228.785 245.000 N mir_eval-0.8.2/tests/data/chord/ref08.lab000066400000000000000000000031211475740344600201100ustar00rootroot000000000000000.000 0.620 N 0.620 3.322 G#:min(*b3,*5) 3.322 6.071 F#:maj(*3) 6.071 8.834 E:maj 8.834 11.607 N 11.607 31.086 G#:min 31.086 31.799 C#:min(*b3) 31.799 32.472 D#:min(*b3) 32.472 33.191 E:maj(*3) 33.191 33.912 F#:maj(*3) 33.912 42.219 G#:min 42.219 42.893 C#:min(*b3) 42.893 43.608 D#:min(*b3) 43.608 44.294 E:maj(*3) 44.294 44.980 F#:maj(*3) 44.980 47.763 E:maj 47.763 50.555 F#:maj 50.555 53.363 E:maj 53.363 56.114 D#:7 56.114 58.915 G#:min 58.915 61.667 F#:maj 61.667 64.451 E:maj 64.451 67.251 D#:7 67.251 69.995 G#:min 69.995 72.827 F#:maj 72.827 75.611 E:maj 75.611 76.985 D#:7 76.985 77.665 E:maj(*3) 77.665 78.385 F#:maj(*3) 78.385 89.510 G#:min(*b3) 89.510 90.185 C#:min(*b3) 90.185 90.887 D#:min(*b3) 90.887 92.231 F#:maj(*3) 92.231 100.620 G#:min 100.620 101.299 C#:min(*b3) 101.299 102.031 D#:min(*b3) 102.031 102.682 E:maj(*3) 102.682 103.404 F#:maj(*3) 103.404 106.167 E:maj 106.167 108.963 F#:maj 108.963 111.747 E:maj 111.747 114.539 D#:7 114.539 117.314 G#:min 117.314 120.103 F#:maj 120.103 122.873 E:maj 122.873 125.691 D#:7 125.691 128.429 G#:min 128.429 131.237 F#:maj 131.237 134.008 E:maj 134.008 135.380 D#:7 135.380 136.099 E:maj(*3) 136.099 136.780 F#:maj(*3) 136.780 153.536 G#:min 153.536 156.267 F#:maj 156.267 159.048 E:maj 159.048 161.851 D#:7 161.851 164.604 G#:min 164.604 167.403 F#:maj 167.403 170.171 E:maj 170.171 172.946 D#:7 172.946 175.714 G#:min 175.714 178.525 F#:maj 178.525 181.315 E:maj 181.315 184.083 D#:7 184.083 186.829 G#:min 186.829 189.619 F#:maj 189.619 192.424 E:maj 192.424 193.803 D#:7 193.803 194.490 E:maj(*3) 194.490 195.208 F#:maj(*3) 195.208 200.000 G#:min mir_eval-0.8.2/tests/data/chord/ref09.lab000066400000000000000000000017541475740344600201230ustar00rootroot000000000000000.000 8.230 N 8.230 13.893 E:7 13.893 21.350 E:9 21.350 23.188 A:maj 23.188 25.058 F#:min 25.058 26.898 A:maj 26.898 28.773 F#:min 28.773 31.660 D:maj 31.660 39.078 E:maj 39.078 46.567 E:9 46.567 48.433 A:maj 48.433 50.344 F#:min 50.344 52.192 A:maj 52.192 54.093 F#:min 54.093 56.943 D:maj 56.943 64.435 E:maj 64.435 71.796 E:9 71.796 73.675 D:min 73.675 75.567 G:7 75.567 77.399 C:maj 77.399 79.246 A:min 79.246 81.103 D:min 81.103 82.935 G:7 82.935 86.625 C:maj 86.625 88.438 D:min 88.438 90.290 G:7 90.290 92.119 C:maj 92.119 93.951 A:min 93.951 95.809 D:min 95.809 97.631 G:7 97.631 99.455 C:maj 99.455 101.320 A:7 101.320 103.142 F#:min 103.142 105.028 D:min 105.028 106.831 E:maj 106.831 108.655 A:maj 108.655 110.546 F#:min 110.546 112.370 D:min 112.370 119.726 E:9 119.726 121.614 A:maj 121.614 123.472 F#:min 123.472 125.304 A:maj 125.304 127.093 F#:min 127.093 129.922 D:maj 129.922 324.196 E:7 324.196 327.795 N 327.795 333.281 E:7 333.281 349.861 E:9 349.861 350.288 A:maj 350.288 395.000 N mir_eval-0.8.2/tests/data/hierarchy/000077500000000000000000000000001475740344600173665ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/hierarchy/est00.lab000066400000000000000000000004671475740344600210100ustar00rootroot00000000000000# A comment 0.000 0.469 Z 0.469 6.170 A 6.170 17.610 A 17.610 28.988 A 28.988 40.409 A 40.409 51.674 B 51.674 63.138 B 63.138 68.826 C 68.826 80.204 A 80.204 91.586 A 91.586 103.002 B 103.002 114.332 B 114.332 125.722 D 125.722 137.082 A 137.082 148.490 B 148.490 182.886 B 182.886 187.787 Z' mir_eval-0.8.2/tests/data/hierarchy/est01.lab000066400000000000000000000011351475740344600210020ustar00rootroot000000000000000.000 0.469 z 0.469 6.170 b 6.170 11.923 c 11.923 17.610 c 17.610 23.312 d 23.312 28.988 d 28.988 34.638 e 34.638 40.409 e 40.409 46.066 f 46.066 51.674 f 51.674 57.410 g 57.410 63.138 g 63.138 68.826 h 68.826 74.498 i 74.498 80.204 i 80.204 85.904 j 85.904 91.586 j 91.586 97.266 k 97.266 103.002 k 103.002 108.668 l 108.668 114.332 l 114.332 120.042 m 120.042 125.722 m 125.722 131.378 n 131.378 137.082 o 137.082 142.818 p 142.818 148.490 p 148.490 154.196 q 154.196 159.890 q 159.890 165.554 q 165.554 171.226 q 171.226 176.970 q 176.970 182.886 r 182.886 187.787 z' mir_eval-0.8.2/tests/data/hierarchy/output_w=05.json000066400000000000000000000005201475740344600224060ustar00rootroot00000000000000{"T-Precision reduced": 0.9037379015435819, "T-Recall reduced": 0.9645859626864335, "T-Measure reduced": 0.9331710743157444, "T-Precision full": 0.914103820262725, "T-Recall full": 0.9695550559527968, "T-Measure full": 0.9410132501083357, "L-Precision": 0.76637322676449, "L-Recall": 0.8816707087885174, "L-Measure": 0.8199888503715905}mir_eval-0.8.2/tests/data/hierarchy/output_w=15.json000066400000000000000000000005201475740344600224070ustar00rootroot00000000000000{"T-Precision reduced": 0.7484596791031685, "T-Recall reduced": 0.7564831451158136, "T-Measure reduced": 0.7524500239192489, "T-Precision full": 0.8377303685813188, "T-Recall full": 0.8044189667273323, "T-Measure full": 0.820736802677731, "L-Precision": 0.76637322676449, "L-Recall": 0.8816707087885174, "L-Measure": 0.8199888503715905}mir_eval-0.8.2/tests/data/hierarchy/output_w=30.json000066400000000000000000000005201475740344600224040ustar00rootroot00000000000000{"T-Precision reduced": 0.8258236282977253, "T-Recall reduced": 0.6179435977681829, "T-Measure reduced": 0.7069178670620068, "T-Precision full": 0.8897226874011187, "T-Recall full": 0.705521675534329, "T-Measure full": 0.7869874431288547, "L-Precision": 0.76637322676449, "L-Recall": 0.8816707087885174, "L-Measure": 0.8199888503715905}mir_eval-0.8.2/tests/data/hierarchy/ref00.lab000066400000000000000000000003011475740344600207540ustar00rootroot000000000000000.000 0.441 Z 0.441 17.512 A 17.512 40.445 B 40.445 63.101 C 63.101 68.797 D 68.797 91.580 B 91.580 114.351 C 114.351 125.636 E 125.636 137.074 B 137.074 148.451 C 148.451 187.779 C mir_eval-0.8.2/tests/data/hierarchy/ref01.lab000066400000000000000000000011111475740344600207550ustar00rootroot000000000000000.000 0.441 z 0.441 6.172 a 6.172 11.861 b 11.861 17.512 b 17.512 23.244 c 23.244 28.875 d 28.875 34.667 c 34.667 40.445 d 40.445 46.071 e 46.071 51.768 e 51.768 57.360 e 57.360 63.101 e 63.101 68.797 f 68.797 74.457 c 74.457 80.170 d 80.170 85.774 c 85.774 91.580 d 91.580 97.311 e 97.311 103.029 e 103.029 108.627 e 108.627 114.351 e 114.351 120.031 g 120.031 125.636 g 125.636 131.424 c 131.424 137.074 d 137.074 142.860 e 142.860 148.451 e 148.451 154.212 e 154.212 159.832 e 159.832 165.571 e 165.571 171.200 e 171.200 177.041 e 177.041 187.779 e mir_eval-0.8.2/tests/data/key/000077500000000000000000000000001475740344600162005ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/key/est00.txt000066400000000000000000000000241475740344600176700ustar00rootroot00000000000000# A comment C major mir_eval-0.8.2/tests/data/key/est01.txt000066400000000000000000000000071475740344600176720ustar00rootroot00000000000000G minormir_eval-0.8.2/tests/data/key/est02.txt000066400000000000000000000000111475740344600176660ustar00rootroot00000000000000Ab minor mir_eval-0.8.2/tests/data/key/est03.txt000066400000000000000000000000071475740344600176740ustar00rootroot00000000000000D majormir_eval-0.8.2/tests/data/key/est04.txt000066400000000000000000000000101475740344600176670ustar00rootroot00000000000000F# minormir_eval-0.8.2/tests/data/key/est05.txt000066400000000000000000000000101475740344600176700ustar00rootroot00000000000000A major mir_eval-0.8.2/tests/data/key/est06.txt000066400000000000000000000000101475740344600176710ustar00rootroot00000000000000Gb minormir_eval-0.8.2/tests/data/key/est07.txt000066400000000000000000000000071475740344600177000ustar00rootroot00000000000000G majormir_eval-0.8.2/tests/data/key/est08.txt000066400000000000000000000000071475740344600177010ustar00rootroot00000000000000C majormir_eval-0.8.2/tests/data/key/est09.txt000066400000000000000000000000071475740344600177020ustar00rootroot00000000000000C minormir_eval-0.8.2/tests/data/key/output00.json000066400000000000000000000000271475740344600205720ustar00rootroot00000000000000{"Weighted Score": 1.0}mir_eval-0.8.2/tests/data/key/output01.json000066400000000000000000000000271475740344600205730ustar00rootroot00000000000000{"Weighted Score": 1.0}mir_eval-0.8.2/tests/data/key/output02.json000066400000000000000000000000271475740344600205740ustar00rootroot00000000000000{"Weighted Score": 0.5}mir_eval-0.8.2/tests/data/key/output03.json000066400000000000000000000000271475740344600205750ustar00rootroot00000000000000{"Weighted Score": 0.0}mir_eval-0.8.2/tests/data/key/output04.json000066400000000000000000000000271475740344600205760ustar00rootroot00000000000000{"Weighted Score": 0.3}mir_eval-0.8.2/tests/data/key/output05.json000066400000000000000000000000271475740344600205770ustar00rootroot00000000000000{"Weighted Score": 0.3}mir_eval-0.8.2/tests/data/key/output06.json000066400000000000000000000000271475740344600206000ustar00rootroot00000000000000{"Weighted Score": 0.2}mir_eval-0.8.2/tests/data/key/output07.json000066400000000000000000000000271475740344600206010ustar00rootroot00000000000000{"Weighted Score": 0.2}mir_eval-0.8.2/tests/data/key/output08.json000066400000000000000000000000271475740344600206020ustar00rootroot00000000000000{"Weighted Score": 0.0}mir_eval-0.8.2/tests/data/key/output09.json000066400000000000000000000000271475740344600206030ustar00rootroot00000000000000{"Weighted Score": 0.0}mir_eval-0.8.2/tests/data/key/ref00.txt000066400000000000000000000000071475740344600176520ustar00rootroot00000000000000C majormir_eval-0.8.2/tests/data/key/ref01.txt000066400000000000000000000000071475740344600176530ustar00rootroot00000000000000G minormir_eval-0.8.2/tests/data/key/ref02.txt000066400000000000000000000000101475740344600176460ustar00rootroot00000000000000Db minormir_eval-0.8.2/tests/data/key/ref03.txt000066400000000000000000000000071475740344600176550ustar00rootroot00000000000000A minormir_eval-0.8.2/tests/data/key/ref04.txt000066400000000000000000000000071475740344600176560ustar00rootroot00000000000000A majormir_eval-0.8.2/tests/data/key/ref05.txt000066400000000000000000000000111475740344600176520ustar00rootroot00000000000000F# minor mir_eval-0.8.2/tests/data/key/ref06.txt000066400000000000000000000000101475740344600176520ustar00rootroot00000000000000Gb majormir_eval-0.8.2/tests/data/key/ref07.txt000066400000000000000000000000071475740344600176610ustar00rootroot00000000000000G minormir_eval-0.8.2/tests/data/key/ref08.txt000066400000000000000000000000071475740344600176620ustar00rootroot00000000000000G majormir_eval-0.8.2/tests/data/key/ref09.txt000066400000000000000000000000071475740344600176630ustar00rootroot00000000000000A minormir_eval-0.8.2/tests/data/melody/000077500000000000000000000000001475740344600167015ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/melody/est00.txt000077500000000000000000000710541475740344600204070ustar00rootroot00000000000000# A comment 0 0 0.01 0 0.02 -220 0.03 -220 0.04 -220 0.05 -220 0.06 -220 0.07 -220 0.08 -220 0.09 -220 0.1 -220 0.11 -220 0.12 -220 0.13 -220 0.14 -220 0.15 -220 0.16 -220 0.17 -220 0.18 -220 0.19 -220 0.2 -220 0.21 -220 0.22 -220 0.23 -220 0.24 -220 0.25 -220 0.26 -220 0.27 -220 0.28 -220 0.29 -220 0.3 -220 0.31 -220 0.32 -220 0.33 -220 0.34 -220 0.35 -220 0.36 -220 0.37 -220 0.38 -220 0.39 -220 0.4 -220 0.41 -220 0.42 -220 0.43 -220 0.44 -220 0.45 -220 0.46 -220 0.47 -220 0.48 -220 0.49 -220 0.5 -220 0.51 -220 0.52 -220 0.53 -220 0.54 -220 0.55 -220 0.56 -220 0.57 -220 0.58 -220 0.59 -220 0.6 -220 0.61 -220 0.62 -220 0.63 -220 0.64 -220 0.65 -220 0.66 -220 0.67 -220 0.68 -220 0.69 -220 0.7 -220 0.71 -220 0.72 -220 0.73 -220 0.74 -220 0.75 -220 0.76 -220 0.77 -220 0.78 -220 0.79 -220 0.8 -220 0.81 -220 0.82 -220 0.83 -220 0.84 -220 0.85 -220 0.86 -220 0.87 -220 0.88 -220 0.89 -220 0.9 -220 0.91 -220 0.92 -220 0.93 -220 0.94 -220 0.95 -220 0.96 -220 0.97 -220 0.98 -220 0.99 -220 1 -220 1.01 -220 1.02 -220 1.03 -220 1.04 -220 1.05 -220 1.06 -220 1.07 -220 1.08 -220 1.09 -220 1.1 -220 1.11 -220 1.12 -220 1.13 -220 1.14 -220 1.15 -220 1.16 -220 1.17 -220 1.18 -220 1.19 -220 1.2 -220 1.21 -220 1.22 -220 1.23 -220 1.24 -220 1.25 -220 1.26 -220 1.27 -220 1.28 -220 1.29 -220 1.3 -220 1.31 -220 1.32 -220 1.33 -220 1.34 -220 1.35 -220 1.36 -220 1.37 298.798 1.38 297.077 1.39 300.529 1.4 302.27 1.41 304.021 1.42 304.021 1.43 304.021 1.44 305.782 1.45 304.021 1.46 304.021 1.47 304.021 1.48 305.782 1.49 304.021 1.5 305.782 1.51 307.553 1.52 307.553 1.53 307.553 1.54 305.782 1.55 307.553 1.56 307.553 1.57 307.553 1.58 307.553 1.59 305.782 1.6 307.553 1.61 307.553 1.62 307.553 1.63 309.335 1.64 309.335 1.65 307.553 1.66 309.335 1.67 307.553 1.68 307.553 1.69 307.553 1.7 309.335 1.71 309.335 1.72 307.553 1.73 309.335 1.74 309.335 1.75 309.335 1.76 312.929 1.77 311.127 1.78 309.335 1.79 311.127 1.8 309.335 1.81 312.929 1.82 311.127 1.83 311.127 1.84 314.742 1.85 312.929 1.86 314.742 1.87 318.399 1.88 316.565 1.89 316.565 1.9 316.565 1.91 312.929 1.92 312.929 1.93 309.335 1.94 305.782 1.95 288.62 1.96 290.292 1.97 298.798 1.98 297.077 1.99 293.665 2 295.366 2.01 295.366 2.02 291.973 2.03 290.292 2.04 288.62 2.05 286.957 2.06 286.957 2.07 286.957 2.08 286.957 2.09 286.957 2.1 288.62 2.11 290.292 2.12 290.292 2.13 290.292 2.14 290.292 2.15 291.973 2.16 293.665 2.17 293.665 2.18 291.973 2.19 291.973 2.2 293.665 2.21 293.665 2.22 293.665 2.23 293.665 2.24 293.665 2.25 291.973 2.26 293.665 2.27 293.665 2.28 293.665 2.29 293.665 2.3 291.973 2.31 291.973 2.32 291.973 2.33 291.973 2.34 291.973 2.35 293.665 2.36 293.665 2.37 293.665 2.38 293.665 2.39 293.665 2.4 293.665 2.41 293.665 2.42 293.665 2.43 293.665 2.44 293.665 2.45 293.665 2.46 293.665 2.47 293.665 2.48 293.665 2.49 293.665 2.5 293.665 2.51 293.665 2.52 293.665 2.53 293.665 2.54 293.665 2.55 293.665 2.56 293.665 2.57 293.665 2.58 293.665 2.59 293.665 2.6 293.665 2.61 293.665 2.62 295.366 2.63 293.665 2.64 293.665 2.65 293.665 2.66 295.366 2.67 293.665 2.68 293.665 2.69 293.665 2.7 293.665 2.71 293.665 2.72 293.665 2.73 293.665 2.74 293.665 2.75 293.665 2.76 293.665 2.77 293.665 2.78 293.665 2.79 295.366 2.8 295.366 2.81 295.366 2.82 295.366 2.83 295.366 2.84 295.366 2.85 295.366 2.86 295.366 2.87 293.665 2.88 293.665 2.89 293.665 2.9 293.665 2.91 295.366 2.92 293.665 2.93 293.665 2.94 293.665 2.95 291.973 2.96 291.973 2.97 293.665 2.98 295.366 2.99 295.366 3 295.366 3.01 295.366 3.02 295.366 3.03 295.366 3.04 293.665 3.05 293.665 3.06 291.973 3.07 291.973 3.08 291.973 3.09 291.973 3.1 293.665 3.11 293.665 3.12 293.665 3.13 293.665 3.14 295.366 3.15 295.366 3.16 295.366 3.17 295.366 3.18 295.366 3.19 295.366 3.2 295.366 3.21 295.366 3.22 295.366 3.23 293.665 3.24 291.973 3.25 291.973 3.26 291.973 3.27 290.292 3.28 291.973 3.29 291.973 3.3 291.973 3.31 291.973 3.32 293.665 3.33 295.366 3.34 295.366 3.35 297.077 3.36 297.077 3.37 297.077 3.38 297.077 3.39 295.366 3.4 295.366 3.41 295.366 3.42 293.665 3.43 293.665 3.44 293.665 3.45 291.973 3.46 290.292 3.47 288.62 3.48 288.62 3.49 288.62 3.5 288.62 3.51 288.62 3.52 291.973 3.53 291.973 3.54 293.665 3.55 295.366 3.56 295.366 3.57 297.077 3.58 297.077 3.59 297.077 3.6 295.366 3.61 295.366 3.62 293.665 3.63 293.665 3.64 291.973 3.65 291.973 3.66 290.292 3.67 290.292 3.68 290.292 3.69 291.973 3.7 291.973 3.71 291.973 3.72 293.665 3.73 295.366 3.74 295.366 3.75 295.366 3.76 295.366 3.77 295.366 3.78 295.366 3.79 293.665 3.8 293.665 3.81 293.665 3.82 293.665 3.83 291.973 3.84 291.973 3.85 290.292 3.86 290.292 3.87 288.62 3.88 290.292 3.89 290.292 3.9 291.973 3.91 291.973 3.92 293.665 3.93 293.665 3.94 293.665 3.95 291.973 3.96 291.973 3.97 291.973 3.98 291.973 3.99 291.973 4 291.973 4.01 293.665 4.02 291.973 4.03 291.973 4.04 291.973 4.05 291.973 4.06 293.665 4.07 293.665 4.08 293.665 4.09 293.665 4.1 293.665 4.11 293.665 4.12 293.665 4.13 291.973 4.14 290.292 4.15 290.292 4.16 288.62 4.17 290.292 4.18 290.292 4.19 290.292 4.2 290.292 4.21 291.973 4.22 291.973 4.23 293.665 4.24 295.366 4.25 297.077 4.26 298.798 4.27 298.798 4.28 297.077 4.29 295.366 4.3 295.366 4.31 293.665 4.32 293.665 4.33 291.973 4.34 290.292 4.35 290.292 4.36 290.292 4.37 290.292 4.38 290.292 4.39 291.973 4.4 293.665 4.41 293.665 4.42 297.077 4.43 298.798 4.44 298.798 4.45 297.077 4.46 295.366 4.47 295.366 4.48 293.665 4.49 293.665 4.5 291.973 4.51 291.973 4.52 291.973 4.53 291.973 4.54 291.973 4.55 288.62 4.56 291.973 4.57 291.973 4.58 291.973 4.59 -293.665 4.6 -293.665 4.61 -293.665 4.62 -295.366 4.63 -295.366 4.64 -297.077 4.65 -295.366 4.66 -295.366 4.67 -293.665 4.68 -291.973 4.69 -293.665 4.7 -293.665 4.71 -295.366 4.72 -293.665 4.73 -291.973 4.74 -293.665 4.75 -293.665 4.76 -295.366 4.77 -297.077 4.78 -297.077 4.79 -297.077 4.8 -297.077 4.81 -295.366 4.82 -293.665 4.83 -293.665 4.84 -291.973 4.85 -291.973 4.86 -291.973 4.87 -291.973 4.88 -291.973 4.89 -293.665 4.9 -293.665 4.91 -298.798 4.92 -295.366 4.93 -293.665 4.94 -293.665 4.95 -293.665 4.96 -293.665 4.97 -293.665 4.98 -295.366 4.99 -295.366 5 -297.077 5.01 -297.077 5.02 -293.665 5.03 -291.973 5.04 -291.973 5.05 -293.665 5.06 -293.665 5.07 -295.366 5.08 -295.366 5.09 -291.973 5.1 -291.973 5.11 -291.973 5.12 -295.366 5.13 -295.366 5.14 -297.077 5.15 -297.077 5.16 -295.366 5.17 -295.366 5.18 -295.366 5.19 -295.366 5.2 -293.665 5.21 -293.665 5.22 -293.665 5.23 -293.665 5.24 -293.665 5.25 -295.366 5.26 -295.366 5.27 -295.366 5.28 -297.077 5.29 -220 5.3 -220 5.31 -220 5.32 -220 5.33 -220 5.34 -220 5.35 -220 5.36 258.621 5.37 260.119 5.38 260.119 5.39 260.119 5.4 258.621 5.41 260.119 5.42 260.119 5.43 260.119 5.44 260.119 5.45 260.119 5.46 260.119 5.47 260.119 5.48 260.119 5.49 260.119 5.5 260.119 5.51 261.626 5.52 261.626 5.53 261.626 5.54 260.119 5.55 260.119 5.56 260.119 5.57 260.119 5.58 261.626 5.59 260.119 5.6 261.626 5.61 260.119 5.62 261.626 5.63 261.626 5.64 260.119 5.65 260.119 5.66 260.119 5.67 260.119 5.68 261.626 5.69 261.626 5.7 261.626 5.71 261.626 5.72 261.626 5.73 260.119 5.74 261.626 5.75 261.626 5.76 261.626 5.77 261.626 5.78 261.626 5.79 263.141 5.8 263.141 5.81 261.626 5.82 261.626 5.83 263.141 5.84 264.666 5.85 264.666 5.86 263.141 5.87 263.141 5.88 263.141 5.89 263.141 5.9 263.141 5.91 263.141 5.92 263.141 5.93 263.141 5.94 266.199 5.95 267.741 5.96 269.292 5.97 273.999 5.98 273.999 5.99 278.788 6 286.957 6.01 286.957 6.02 288.62 6.03 293.665 6.04 297.077 6.05 298.798 6.06 297.077 6.07 297.077 6.08 298.798 6.09 298.798 6.1 297.077 6.11 295.366 6.12 293.665 6.13 293.665 6.14 293.665 6.15 291.973 6.16 291.973 6.17 291.973 6.18 293.665 6.19 293.665 6.2 293.665 6.21 293.665 6.22 293.665 6.23 293.665 6.24 293.665 6.25 293.665 6.26 293.665 6.27 293.665 6.28 291.973 6.29 293.665 6.3 293.665 6.31 291.973 6.32 291.973 6.33 291.973 6.34 291.973 6.35 291.973 6.36 293.665 6.37 293.665 6.38 293.665 6.39 293.665 6.4 293.665 6.41 293.665 6.42 293.665 6.43 293.665 6.44 293.665 6.45 293.665 6.46 295.366 6.47 293.665 6.48 293.665 6.49 293.665 6.5 293.665 6.51 293.665 6.52 293.665 6.53 291.973 6.54 291.973 6.55 290.292 6.56 290.292 6.57 288.62 6.58 290.292 6.59 290.292 6.6 291.973 6.61 293.665 6.62 300.529 6.63 309.335 6.64 316.565 6.65 322.099 6.66 337.332 6.67 343.229 6.68 349.228 6.69 351.251 6.7 351.251 6.71 353.286 6.72 353.286 6.73 355.333 6.74 355.333 6.75 353.286 6.76 351.251 6.77 349.228 6.78 349.228 6.79 349.228 6.8 347.217 6.81 347.217 6.82 345.217 6.83 345.217 6.84 345.217 6.85 345.217 6.86 347.217 6.87 347.217 6.88 349.228 6.89 351.251 6.9 351.251 6.91 349.228 6.92 349.228 6.93 349.228 6.94 349.228 6.95 347.217 6.96 347.217 6.97 347.217 6.98 347.217 6.99 347.217 7 347.217 7.01 347.217 7.02 347.217 7.03 347.217 7.04 347.217 7.05 347.217 7.06 347.217 7.07 347.217 7.08 347.217 7.09 347.217 7.1 349.228 7.11 349.228 7.12 347.217 7.13 347.217 7.14 345.217 7.15 345.217 7.16 345.217 7.17 347.217 7.18 345.217 7.19 343.229 7.2 341.252 7.21 337.332 7.22 339.286 7.23 341.252 7.24 343.229 7.25 347.217 7.26 349.228 7.27 351.251 7.28 355.333 7.29 359.461 7.3 367.863 7.31 374.294 7.32 380.836 7.33 383.042 7.34 385.261 7.35 387.493 7.36 389.738 7.37 391.995 7.38 391.995 7.39 391.995 7.4 391.995 7.41 391.995 7.42 389.738 7.43 391.995 7.44 391.995 7.45 389.738 7.46 389.738 7.47 389.738 7.48 389.738 7.49 389.738 7.5 387.493 7.51 387.493 7.52 389.738 7.53 389.738 7.54 385.261 7.55 389.738 7.56 389.738 7.57 389.738 7.58 389.738 7.59 389.738 7.6 389.738 7.61 389.738 7.62 389.738 7.63 389.738 7.64 389.738 7.65 389.738 7.66 391.995 7.67 391.995 7.68 391.995 7.69 391.995 7.7 391.995 7.71 391.995 7.72 389.738 7.73 391.995 7.74 389.738 7.75 389.738 7.76 389.738 7.77 389.738 7.78 389.738 7.79 389.738 7.8 389.738 7.81 389.738 7.82 391.995 7.83 391.995 7.84 391.995 7.85 394.266 7.86 394.266 7.87 391.995 7.88 391.995 7.89 391.995 7.9 387.493 7.91 387.493 7.92 389.738 7.93 387.493 7.94 389.738 7.95 387.493 7.96 387.493 7.97 389.738 7.98 389.738 7.99 389.738 8 391.995 8.01 387.493 8.02 389.738 8.03 389.738 8.04 387.493 8.05 387.493 8.06 391.995 8.07 389.738 8.08 389.738 8.09 389.738 8.1 391.995 8.11 391.995 8.12 391.995 8.13 389.738 8.14 389.738 8.15 389.738 8.16 389.738 8.17 389.738 8.18 391.995 8.19 391.995 8.2 391.995 8.21 389.738 8.22 394.266 8.23 394.266 8.24 394.266 8.25 391.995 8.26 391.995 8.27 389.738 8.28 389.738 8.29 387.493 8.3 389.738 8.31 387.493 8.32 389.738 8.33 389.738 8.34 387.493 8.35 394.266 8.36 394.266 8.37 391.995 8.38 394.266 8.39 396.55 8.4 396.55 8.41 396.55 8.42 394.266 8.43 394.266 8.44 396.55 8.45 391.995 8.46 394.266 8.47 394.266 8.48 396.55 8.49 396.55 8.5 396.55 8.51 394.266 8.52 394.266 8.53 396.55 8.54 398.847 8.55 391.995 8.56 391.995 8.57 391.995 8.58 398.847 8.59 396.55 8.6 398.847 8.61 398.847 8.62 396.55 8.63 -440 8.64 -440 8.65 -440 8.66 347.217 8.67 343.229 8.68 339.286 8.69 343.229 8.7 343.229 8.71 343.229 8.72 343.229 8.73 343.229 8.74 345.217 8.75 345.217 8.76 347.217 8.77 347.217 8.78 347.217 8.79 347.217 8.8 347.217 8.81 347.217 8.82 347.217 8.83 347.217 8.84 347.217 8.85 347.217 8.86 349.228 8.87 347.217 8.88 349.228 8.89 347.217 8.9 347.217 8.91 347.217 8.92 347.217 8.93 347.217 8.94 347.217 8.95 347.217 8.96 347.217 8.97 347.217 8.98 347.217 8.99 347.217 9 349.228 9.01 349.228 9.02 349.228 9.03 349.228 9.04 349.228 9.05 349.228 9.06 347.217 9.07 345.217 9.08 347.217 9.09 347.217 9.1 349.228 9.11 347.217 9.12 347.217 9.13 347.217 9.14 349.228 9.15 347.217 9.16 347.217 9.17 347.217 9.18 349.228 9.19 349.228 9.2 349.228 9.21 349.228 9.22 349.228 9.23 349.228 9.24 349.228 9.25 349.228 9.26 347.217 9.27 349.228 9.28 349.228 9.29 349.228 9.3 349.228 9.31 347.217 9.32 347.217 9.33 347.217 9.34 347.217 9.35 347.217 9.36 349.228 9.37 349.228 9.38 349.228 9.39 349.228 9.4 349.228 9.41 349.228 9.42 349.228 9.43 349.228 9.44 347.217 9.45 347.217 9.46 347.217 9.47 349.228 9.48 347.217 9.49 347.217 9.5 347.217 9.51 347.217 9.52 347.217 9.53 347.217 9.54 347.217 9.55 347.217 9.56 349.228 9.57 349.228 9.58 351.251 9.59 349.228 9.6 349.228 9.61 349.228 9.62 351.251 9.63 349.228 9.64 349.228 9.65 349.228 9.66 347.217 9.67 345.217 9.68 345.217 9.69 347.217 9.7 345.217 9.71 345.217 9.72 345.217 9.73 345.217 9.74 347.217 9.75 347.217 9.76 349.228 9.77 349.228 9.78 349.228 9.79 349.228 9.8 349.228 9.81 351.251 9.82 349.228 9.83 349.228 9.84 349.228 9.85 349.228 9.86 349.228 9.87 347.217 9.88 347.217 9.89 347.217 9.9 345.217 9.91 345.217 9.92 347.217 9.93 347.217 9.94 345.217 9.95 345.217 9.96 347.217 9.97 349.228 9.98 349.228 9.99 349.228 10 349.228 10.01 351.251 10.02 349.228 10.03 351.251 10.04 349.228 10.05 349.228 10.06 347.217 10.07 347.217 10.08 345.217 10.09 345.217 10.1 343.229 10.11 343.229 10.12 345.217 10.13 345.217 10.14 345.217 10.15 345.217 10.16 347.217 10.17 349.228 10.18 351.251 10.19 351.251 10.2 351.251 10.21 351.251 10.22 351.251 10.23 349.228 10.24 351.251 10.25 349.228 10.26 349.228 10.27 347.217 10.28 345.217 10.29 345.217 10.3 345.217 10.31 347.217 10.32 349.228 10.33 349.228 10.34 349.228 10.35 349.228 10.36 -440 10.37 -440 10.38 -440 10.39 -440 10.4 -440 10.41 -440 10.42 -440 10.43 -440 10.44 -440 10.45 -440 10.46 -440 10.47 -440 10.48 -440 10.49 -440 10.5 -440 10.51 -440 10.52 -440 10.53 -440 10.54 -440 10.55 -440 10.56 -440 10.57 -440 10.58 -440 10.59 -440 10.6 -440 10.61 -440 10.62 -440 10.63 -440 10.64 -440 10.65 -440 10.66 -440 10.67 -440 10.68 -440 10.69 -440 10.7 -440 10.71 -440 10.72 -440 10.73 -440 10.74 -440 10.75 -440 10.76 -440 10.77 -440 10.78 -440 10.79 -440 10.8 -440 10.81 -440 10.82 -440 10.83 -440 10.84 -440 10.85 -440 10.86 -440 10.87 -440 10.88 -440 10.89 -440 10.9 -440 10.91 -440 10.92 -440 10.93 -440 10.94 -440 10.95 -440 10.96 -440 10.97 -440 10.98 -440 10.99 -440 11 -440 11.01 -220 11.02 -220 11.03 -220 11.04 -220 11.05 -220 11.06 -220 11.07 -220 11.08 -220 11.09 -220 11.1 -220 11.11 -220 11.12 -220 11.13 -220 11.14 -220 11.15 -220 11.16 -220 11.17 -220 11.18 -220 11.19 -220 11.2 -220 11.21 347.217 11.22 347.217 11.23 349.228 11.24 349.228 11.25 349.228 11.26 349.228 11.27 347.217 11.28 347.217 11.29 347.217 11.3 347.217 11.31 347.217 11.32 347.217 11.33 347.217 11.34 347.217 11.35 349.228 11.36 349.228 11.37 349.228 11.38 347.217 11.39 347.217 11.4 347.217 11.41 345.217 11.42 345.217 11.43 345.217 11.44 345.217 11.45 347.217 11.46 349.228 11.47 351.251 11.48 349.228 11.49 349.228 11.5 349.228 11.51 349.228 11.52 349.228 11.53 347.217 11.54 347.217 11.55 347.217 11.56 347.217 11.57 347.217 11.58 345.217 11.59 345.217 11.6 345.217 11.61 347.217 11.62 347.217 11.63 347.217 11.64 347.217 11.65 345.217 11.66 345.217 11.67 345.217 11.68 347.217 11.69 349.228 11.7 347.217 11.71 349.228 11.72 351.251 11.73 353.286 11.74 353.286 11.75 351.251 11.76 347.217 11.77 -220 11.78 -220 11.79 -220 11.8 -220 11.81 -220 11.82 -220 11.83 -220 11.84 -220 11.85 -220 11.86 -220 11.87 -220 11.88 -220 11.89 -220 11.9 295.366 11.91 290.292 11.92 286.957 11.93 286.957 11.94 285.305 11.95 285.305 11.96 286.957 11.97 286.957 11.98 288.62 11.99 290.292 12 291.973 12.01 293.665 12.02 291.973 12.03 291.973 12.04 291.973 12.05 291.973 12.06 291.973 12.07 291.973 12.08 291.973 12.09 291.973 12.1 291.973 12.11 293.665 12.12 293.665 12.13 293.665 12.14 293.665 12.15 293.665 12.16 291.973 12.17 291.973 12.18 291.973 12.19 291.973 12.2 293.665 12.21 293.665 12.22 293.665 12.23 293.665 12.24 291.973 12.25 291.973 12.26 291.973 12.27 291.973 12.28 291.973 12.29 291.973 12.3 291.973 12.31 291.973 12.32 291.973 12.33 293.665 12.34 293.665 12.35 293.665 12.36 293.665 12.37 291.973 12.38 291.973 12.39 291.973 12.4 295.366 12.41 295.366 12.42 293.665 12.43 293.665 12.44 293.665 12.45 293.665 12.46 291.973 12.47 293.665 12.48 293.665 12.49 293.665 12.5 293.665 12.51 293.665 12.52 293.665 12.53 293.665 12.54 293.665 12.55 293.665 12.56 293.665 12.57 291.973 12.58 291.973 12.59 293.665 12.6 293.665 12.61 293.665 12.62 293.665 12.63 293.665 12.64 293.665 12.65 293.665 12.66 293.665 12.67 293.665 12.68 293.665 12.69 293.665 12.7 293.665 12.71 293.665 12.72 291.973 12.73 293.665 12.74 293.665 12.75 293.665 12.76 293.665 12.77 293.665 12.78 293.665 12.79 293.665 12.8 293.665 12.81 293.665 12.82 293.665 12.83 293.665 12.84 293.665 12.85 293.665 12.86 293.665 12.87 293.665 12.88 291.973 12.89 293.665 12.9 293.665 12.91 293.665 12.92 293.665 12.93 291.973 12.94 293.665 12.95 293.665 12.96 293.665 12.97 293.665 12.98 293.665 12.99 293.665 13 293.665 13.01 293.665 13.02 291.973 13.03 293.665 13.04 293.665 13.05 293.665 13.06 295.366 13.07 297.077 13.08 297.077 13.09 297.077 13.1 297.077 13.11 293.665 13.12 291.973 13.13 290.292 13.14 286.957 13.15 282.028 13.16 272.421 13.17 264.666 13.18 264.666 13.19 266.199 13.2 270.852 13.21 267.741 13.22 255.65 13.23 255.65 13.24 258.621 13.25 258.621 13.26 257.131 13.27 258.621 13.28 260.119 13.29 260.119 13.3 260.119 13.31 263.141 13.32 261.626 13.33 257.131 13.34 258.621 13.35 260.119 13.36 260.119 13.37 260.119 13.38 261.626 13.39 263.141 13.4 260.119 13.41 260.119 13.42 260.119 13.43 260.119 13.44 257.131 13.45 260.119 13.46 261.626 13.47 258.621 13.48 258.621 13.49 260.119 13.5 260.119 13.51 255.65 13.52 255.65 13.53 260.119 13.54 261.626 13.55 258.621 13.56 258.621 13.57 261.626 13.58 260.119 13.59 260.119 13.6 261.626 13.61 263.141 13.62 260.119 13.63 261.626 13.64 260.119 13.65 260.119 13.66 258.621 13.67 260.119 13.68 260.119 13.69 260.119 13.7 258.621 13.71 261.626 13.72 260.119 13.73 260.119 13.74 260.119 13.75 261.626 13.76 260.119 13.77 260.119 13.78 260.119 13.79 261.626 13.8 260.119 13.81 260.119 13.82 260.119 13.83 261.626 13.84 260.119 13.85 260.119 13.86 260.119 13.87 260.119 13.88 260.119 13.89 260.119 13.9 260.119 13.91 258.621 13.92 258.621 13.93 260.119 13.94 260.119 13.95 260.119 13.96 260.119 13.97 260.119 13.98 260.119 13.99 260.119 14 260.119 14.01 260.119 14.02 258.621 14.03 258.621 14.04 260.119 14.05 260.119 14.06 260.119 14.07 260.119 14.08 260.119 14.09 260.119 14.1 260.119 14.11 261.626 14.12 263.141 14.13 261.626 14.14 263.141 14.15 263.141 14.16 261.626 14.17 261.626 14.18 261.626 14.19 261.626 14.2 260.119 14.21 260.119 14.22 260.119 14.23 258.621 14.24 258.621 14.25 260.119 14.26 258.621 14.27 260.119 14.28 260.119 14.29 261.626 14.3 261.626 14.31 263.141 14.32 263.141 14.33 263.141 14.34 263.141 14.35 263.141 14.36 263.141 14.37 261.626 14.38 261.626 14.39 263.141 14.4 260.119 14.41 260.119 14.42 260.119 14.43 260.119 14.44 258.621 14.45 260.119 14.46 258.621 14.47 258.621 14.48 260.119 14.49 260.119 14.5 261.626 14.51 261.626 14.52 261.626 14.53 263.141 14.54 263.141 14.55 261.626 14.56 261.626 14.57 263.141 14.58 260.119 14.59 260.119 14.6 261.626 14.61 258.621 14.62 257.131 14.63 260.119 14.64 260.119 14.65 257.131 14.66 255.65 14.67 260.119 14.68 260.119 14.69 258.621 14.7 260.119 14.71 264.666 14.72 263.141 14.73 261.626 14.74 263.141 14.75 264.666 14.76 261.626 14.77 263.141 14.78 263.141 14.79 260.119 14.8 258.621 14.81 261.626 14.82 260.119 14.83 255.65 14.84 257.131 14.85 260.119 14.86 258.621 14.87 257.131 14.88 260.119 14.89 261.626 14.9 260.119 14.91 261.626 14.92 263.141 14.93 264.666 14.94 263.141 14.95 263.141 14.96 263.141 14.97 261.626 14.98 261.626 14.99 263.141 15 260.119 15.01 258.621 15.02 260.119 15.03 260.119 15.04 257.131 15.05 258.621 15.06 260.119 15.07 260.119 15.08 260.119 15.09 261.626 15.1 261.626 15.11 261.626 15.12 261.626 15.13 263.141 15.14 261.626 15.15 261.626 15.16 263.141 15.17 261.626 15.18 260.119 15.19 260.119 15.2 260.119 15.21 258.621 15.22 257.131 15.23 260.119 15.24 260.119 15.25 258.621 15.26 260.119 15.27 263.141 15.28 -263.141 15.29 -261.626 15.3 -263.141 15.31 -220 15.32 -220 15.33 -220 15.34 -220 15.35 -220 15.36 -220 15.37 -220 15.38 -220 15.39 -220 15.4 -220 15.41 -220 15.42 -220 15.43 -220 15.44 -220 15.45 -220 15.46 -220 15.47 -220 15.48 -220 15.49 -220 15.5 -220 15.51 -220 15.52 -220 15.53 -220 15.54 -220 15.55 -220 15.56 -220 15.57 -220 15.58 -220 15.59 -220 15.6 -220 15.61 -220 15.62 -220 15.63 -220 15.64 -220 15.65 -220 15.66 -220 15.67 -220 15.68 -220 15.69 -220 15.7 -220 15.71 -220 15.72 -220 15.73 -220 15.74 -220 15.75 -220 15.76 -220 15.77 -220 15.78 -220 15.79 -195.998 15.8 -195.998 15.81 -194.869 15.82 -195.998 15.83 -195.998 15.84 -195.998 15.85 -195.998 15.86 -195.998 15.87 -195.998 15.88 -195.998 15.89 -195.998 15.9 -195.998 15.91 -195.998 15.92 -195.998 15.93 -194.869 15.94 -194.869 15.95 -195.998 15.96 -220 15.97 -220 15.98 -220 15.99 -220 16 -220 16.01 -220 16.02 -220 16.03 -220 16.04 -220 16.05 -220 16.06 -220 16.07 -220 16.08 -220 16.09 -220 16.1 -220 16.11 -220 16.12 -220 16.13 -220 16.14 -220 16.15 -220 16.16 -220 16.17 -220 16.18 -220 16.19 -220 16.2 -220 16.21 -220 16.22 -220 16.23 -220 16.24 -220 16.25 -220 16.26 -220 16.27 -220 16.28 -220 16.29 -220 16.3 -220 16.31 -220 16.32 -220 16.33 -220 16.34 -220 16.35 349.228 16.36 349.228 16.37 347.217 16.38 351.251 16.39 349.228 16.4 347.217 16.41 347.217 16.42 347.217 16.43 347.217 16.44 349.228 16.45 347.217 16.46 347.217 16.47 347.217 16.48 347.217 16.49 349.228 16.5 349.228 16.51 349.228 16.52 349.228 16.53 349.228 16.54 347.217 16.55 347.217 16.56 347.217 16.57 349.228 16.58 347.217 16.59 349.228 16.6 347.217 16.61 347.217 16.62 347.217 16.63 347.217 16.64 345.217 16.65 347.217 16.66 347.217 16.67 349.228 16.68 349.228 16.69 349.228 16.7 347.217 16.71 347.217 16.72 349.228 16.73 347.217 16.74 347.217 16.75 349.228 16.76 347.217 16.77 349.228 16.78 349.228 16.79 347.217 16.8 349.228 16.81 349.228 16.82 349.228 16.83 351.251 16.84 349.228 16.85 351.251 16.86 353.286 16.87 353.286 16.88 355.333 16.89 355.333 16.9 357.391 16.91 355.333 16.92 355.333 16.93 353.286 16.94 351.251 16.95 345.217 16.96 323.965 16.97 311.127 16.98 307.553 16.99 311.127 17 311.127 17.01 309.335 17.02 311.127 17.03 314.742 17.04 305.782 17.05 295.366 17.06 290.292 17.07 288.62 17.08 288.62 17.09 291.973 17.1 293.665 17.11 290.292 17.12 290.292 17.13 291.973 17.14 293.665 17.15 295.366 17.16 291.973 17.17 290.292 17.18 291.973 17.19 295.366 17.2 295.366 17.21 295.366 17.22 293.665 17.23 291.973 17.24 293.665 17.25 295.366 17.26 293.665 17.27 291.973 17.28 291.973 17.29 293.665 17.3 293.665 17.31 293.665 17.32 293.665 17.33 291.973 17.34 293.665 17.35 293.665 17.36 295.366 17.37 293.665 17.38 293.665 17.39 293.665 17.4 293.665 17.41 295.366 17.42 295.366 17.43 293.665 17.44 293.665 17.45 293.665 17.46 293.665 17.47 293.665 17.48 293.665 17.49 293.665 17.5 293.665 17.51 293.665 17.52 293.665 17.53 293.665 17.54 291.973 17.55 288.62 17.56 -297.077 17.57 -297.077 17.58 -297.077 17.59 -297.077 17.6 -297.077 17.61 -297.077 17.62 -297.077 17.63 -297.077 17.64 -295.366 17.65 -293.665 17.66 -293.665 17.67 -295.366 17.68 297.077 17.69 293.665 17.7 291.973 17.71 293.665 17.72 295.366 17.73 291.973 17.74 291.973 17.75 293.665 17.76 293.665 17.77 293.665 17.78 293.665 17.79 293.665 17.8 291.973 17.81 293.665 17.82 293.665 17.83 293.665 17.84 295.366 17.85 295.366 17.86 295.366 17.87 293.665 17.88 293.665 17.89 293.665 17.9 293.665 17.91 293.665 17.92 293.665 17.93 293.665 17.94 293.665 17.95 293.665 17.96 293.665 17.97 293.665 17.98 293.665 17.99 291.973 18 293.665 18.01 293.665 18.02 293.665 18.03 293.665 18.04 291.973 18.05 291.973 18.06 291.973 18.07 293.665 18.08 293.665 18.09 293.665 18.1 293.665 18.11 293.665 18.12 293.665 18.13 293.665 18.14 293.665 18.15 291.973 18.16 293.665 18.17 291.973 18.18 291.973 18.19 291.973 18.2 290.292 18.21 290.292 18.22 290.292 18.23 290.292 18.24 290.292 18.25 290.292 18.26 291.973 18.27 295.366 18.28 295.366 18.29 297.077 18.3 298.798 18.31 298.798 18.32 293.665 18.33 290.292 18.34 297.077 18.35 311.127 18.36 314.742 18.37 316.565 18.38 312.929 18.39 314.742 18.4 312.929 18.41 311.127 18.42 309.335 18.43 307.553 18.44 304.021 18.45 295.366 18.46 295.366 18.47 298.798 18.48 -440 18.49 -440 18.5 -440 18.51 -440 18.52 -440 18.53 -440 18.54 -440 18.55 -440 18.56 -440 18.57 -440 18.58 -440 18.59 -440 18.6 -440 18.61 -440 18.62 -440 18.63 -440 18.64 -440 18.65 -440 18.66 -440 18.67 -440 18.68 300.529 18.69 304.021 18.7 307.553 18.71 309.335 18.72 309.335 18.73 311.127 18.74 311.127 18.75 311.127 18.76 311.127 18.77 309.335 18.78 309.335 18.79 307.553 18.8 307.553 18.81 309.335 18.82 309.335 18.83 309.335 18.84 309.335 18.85 309.335 18.86 309.335 18.87 309.335 18.88 309.335 18.89 309.335 18.9 309.335 18.91 309.335 18.92 309.335 18.93 309.335 18.94 309.335 18.95 311.127 18.96 309.335 18.97 309.335 18.98 309.335 18.99 309.335 19 309.335 19.01 309.335 19.02 309.335 19.03 307.553 19.04 307.553 19.05 309.335 19.06 309.335 19.07 309.335 19.08 309.335 19.09 309.335 19.1 309.335 19.11 309.335 19.12 311.127 19.13 311.127 19.14 311.127 19.15 311.127 19.16 309.335 19.17 311.127 19.18 311.127 19.19 311.127 19.2 312.929 19.21 311.127 19.22 311.127 19.23 311.127 19.24 311.127 19.25 311.127 19.26 311.127 19.27 311.127 19.28 311.127 19.29 311.127 19.3 309.335 19.31 309.335 19.32 311.127 19.33 311.127 19.34 309.335 19.35 309.335 19.36 311.127 19.37 311.127 19.38 311.127 19.39 311.127 19.4 309.335 19.41 309.335 19.42 311.127 19.43 311.127 19.44 311.127 19.45 311.127 19.46 309.335 19.47 311.127 19.48 311.127 19.49 311.127 19.5 309.335 19.51 309.335 19.52 309.335 19.53 309.335 19.54 311.127 19.55 309.335 19.56 309.335 19.57 309.335 19.58 307.553 19.59 309.335 19.6 311.127 19.61 312.929 19.62 312.929 19.63 312.929 19.64 312.929 19.65 312.929 19.66 312.929 19.67 311.127 19.68 311.127 19.69 311.127 19.7 309.335 19.71 311.127 19.72 311.127 19.73 309.335 19.74 309.335 19.75 309.335 19.76 309.335 19.77 309.335 19.78 309.335 19.79 311.127 19.8 309.335 19.81 309.335 19.82 307.553 19.83 309.335 19.84 311.127 19.85 312.929 19.86 312.929 19.87 311.127 19.88 311.127 19.89 311.127 19.9 311.127 19.91 311.127 19.92 311.127 19.93 309.335 19.94 311.127 19.95 309.335 19.96 311.127 19.97 309.335 19.98 307.553 19.99 307.553 20 309.335 20.01 311.127 20.02 309.335 20.03 309.335 20.04 311.127 20.05 311.127 20.06 312.929 20.07 312.929 20.08 311.127 20.09 309.335 20.1 311.127 20.11 311.127 20.12 312.929 20.13 312.929 20.14 311.127 20.15 309.335 20.16 309.335 20.17 309.335 20.18 312.929 20.19 309.335 20.2 309.335 20.21 307.553 20.22 307.553 20.23 309.335 20.24 311.127 20.25 309.335 20.26 311.127 20.27 307.553 20.28 307.553 20.29 309.335 20.3 312.929 20.31 312.929 20.32 311.127 20.33 309.335 20.34 309.335 20.35 309.335 20.36 311.127 20.37 311.127 20.38 309.335 20.39 307.553 20.4 -220 20.41 -220 20.42 -220 20.43 -220 20.44 -220 20.45 -220 20.46 -220 20.47 -220 20.48 -220 20.49 -220 20.5 -220 20.51 -220 20.52 -220 20.53 -220 20.54 -220 20.55 -220 20.56 -220 20.57 -220 20.58 -220 20.59 -220 20.6 -220 20.61 -220 20.62 -220 20.63 -220 20.64 -220 20.65 -220 20.66 -220 20.67 -220 20.68 -220 20.69 -220 20.7 -220 20.71 -220 20.72 -220 20.73 -220 20.74 -220 20.75 -220 20.76 -220 20.77 -220 20.78 -220 20.79 -220 20.8 -220 20.81 -220 20.82 -374.294 20.83 -374.294 20.84 -372.138 20.85 -372.138 20.86 -372.138 20.87 -372.138 20.88 -369.994 20.89 -367.863 20.9 -363.638 20.91 -363.638 20.92 -365.745 20.93 -369.994 20.94 -369.994 20.95 -369.994 20.96 -372.138 20.97 -374.294 20.98 -374.294 20.99 -372.138 21 -220 21.01 -220 21.02 -220 21.03 -220 21.04 -220 21.05 -220 mir_eval-0.8.2/tests/data/melody/est01.txt000077500000000000000000000731321475740344600204070ustar00rootroot000000000000000 0 0.01 0 0.02 -220 0.03 -220 0.04 -220 0.05 -220 0.06 -220 0.07 -220 0.08 -220 0.09 -220 0.1 -220 0.11 -220 0.12 -220 0.13 -220 0.14 -220 0.15 -220 0.16 -220 0.17 -220 0.18 -220 0.19 -220 0.2 -220 0.21 -220 0.22 -220 0.23 -220 0.24 -220 0.25 -220 0.26 -220 0.27 -220 0.28 -220 0.29 -220 0.3 -220 0.31 -220 0.32 -220 0.33 -220 0.34 -220 0.35 -220 0.36 -220 0.37 -220 0.38 -220 0.39 -220 0.4 -220 0.41 -220 0.42 -220 0.43 -220 0.44 -220 0.45 -220 0.46 -220 0.47 -220 0.48 -220 0.49 -220 0.5 -220 0.51 -220 0.52 -220 0.53 -220 0.54 -220 0.55 -220 0.56 -220 0.57 -220 0.58 295.366 0.59 293.665 0.6 290.292 0.61 290.292 0.62 290.292 0.63 291.973 0.64 291.973 0.65 291.973 0.66 291.973 0.67 291.973 0.68 291.973 0.69 291.973 0.7 291.973 0.71 291.973 0.72 291.973 0.73 291.973 0.74 291.973 0.75 293.665 0.76 295.366 0.77 295.366 0.78 295.366 0.79 295.366 0.8 295.366 0.81 295.366 0.82 295.366 0.83 293.665 0.84 293.665 0.85 293.665 0.86 293.665 0.87 293.665 0.88 293.665 0.89 295.366 0.9 295.366 0.91 293.665 0.92 293.665 0.93 293.665 0.94 293.665 0.95 295.366 0.96 295.366 0.97 295.366 0.98 293.665 0.99 293.665 1 295.366 1.01 295.366 1.02 295.366 1.03 295.366 1.04 295.366 1.05 295.366 1.06 297.077 1.07 298.798 1.08 300.529 1.09 302.27 1.1 300.529 1.11 300.529 1.12 298.798 1.13 297.077 1.14 295.366 1.15 293.665 1.16 290.292 1.17 288.62 1.18 273.999 1.19 273.999 1.2 275.586 1.21 270.852 1.22 266.199 1.23 264.666 1.24 261.626 1.25 255.65 1.26 255.65 1.27 255.65 1.28 254.178 1.29 252.714 1.3 255.65 1.31 255.65 1.32 258.621 1.33 258.621 1.34 258.621 1.35 260.119 1.36 261.626 1.37 261.626 1.38 261.626 1.39 261.626 1.4 261.626 1.41 260.119 1.42 260.119 1.43 260.119 1.44 260.119 1.45 260.119 1.46 260.119 1.47 260.119 1.48 261.626 1.49 260.119 1.5 260.119 1.51 260.119 1.52 260.119 1.53 260.119 1.54 261.626 1.55 261.626 1.56 260.119 1.57 260.119 1.58 261.626 1.59 260.119 1.6 260.119 1.61 261.626 1.62 263.141 1.63 260.119 1.64 260.119 1.65 261.626 1.66 261.626 1.67 257.131 1.68 260.119 1.69 260.119 1.7 260.119 1.71 258.621 1.72 260.119 1.73 260.119 1.74 260.119 1.75 260.119 1.76 261.626 1.77 261.626 1.78 260.119 1.79 258.621 1.8 258.621 1.81 257.131 1.82 257.131 1.83 260.119 1.84 260.119 1.85 260.119 1.86 258.621 1.87 261.626 1.88 266.199 1.89 264.666 1.9 261.626 1.91 261.626 1.92 260.119 1.93 260.119 1.94 260.119 1.95 260.119 1.96 258.621 1.97 260.119 1.98 260.119 1.99 260.119 2 258.621 2.01 260.119 2.02 261.626 2.03 260.119 2.04 260.119 2.05 260.119 2.06 260.119 2.07 260.119 2.08 261.626 2.09 261.626 2.1 261.626 2.11 260.119 2.12 260.119 2.13 261.626 2.14 260.119 2.15 260.119 2.16 260.119 2.17 260.119 2.18 258.621 2.19 260.119 2.2 258.621 2.21 258.621 2.22 260.119 2.23 261.626 2.24 261.626 2.25 261.626 2.26 263.141 2.27 261.626 2.28 261.626 2.29 261.626 2.3 261.626 2.31 261.626 2.32 261.626 2.33 260.119 2.34 261.626 2.35 260.119 2.36 260.119 2.37 261.626 2.38 260.119 2.39 260.119 2.4 260.119 2.41 261.626 2.42 260.119 2.43 261.626 2.44 261.626 2.45 261.626 2.46 261.626 2.47 261.626 2.48 261.626 2.49 261.626 2.5 261.626 2.51 261.626 2.52 263.141 2.53 264.666 2.54 264.666 2.55 264.666 2.56 264.666 2.57 264.666 2.58 264.666 2.59 263.141 2.6 261.626 2.61 258.621 2.62 255.65 2.63 251.258 2.64 246.942 2.65 241.301 2.66 237.156 2.67 -220 2.68 -220 2.69 -220 2.7 -220 2.71 -220 2.72 217.473 2.73 216.221 2.74 216.221 2.75 216.221 2.76 216.221 2.77 216.221 2.78 217.473 2.79 217.473 2.8 220 2.81 218.733 2.82 218.733 2.83 218.733 2.84 218.733 2.85 218.733 2.86 220 2.87 217.473 2.88 218.733 2.89 218.733 2.9 218.733 2.91 218.733 2.92 218.733 2.93 218.733 2.94 218.733 2.95 218.733 2.96 218.733 2.97 218.733 2.98 218.733 2.99 216.221 3 217.473 3.01 217.473 3.02 217.473 3.03 216.221 3.04 216.221 3.05 216.221 3.06 216.221 3.07 216.221 3.08 216.221 3.09 214.975 3.1 214.975 3.11 213.737 3.12 216.221 3.13 217.473 3.14 220 3.15 223.846 3.16 225.142 3.17 226.446 3.18 230.405 3.19 231.739 3.2 234.432 3.21 234.432 3.22 237.156 3.23 237.156 3.24 235.79 3.25 234.432 3.26 234.432 3.27 234.432 3.28 234.432 3.29 234.432 3.3 233.082 3.31 231.739 3.32 230.405 3.33 231.739 3.34 230.405 3.35 230.405 3.36 231.739 3.37 231.739 3.38 231.739 3.39 231.739 3.4 230.405 3.41 231.739 3.42 233.082 3.43 233.082 3.44 233.082 3.45 233.082 3.46 233.082 3.47 230.405 3.48 231.739 3.49 231.739 3.5 230.405 3.51 231.739 3.52 231.739 3.53 233.082 3.54 231.739 3.55 231.739 3.56 227.758 3.57 227.758 3.58 229.078 3.59 231.739 3.6 231.739 3.61 231.739 3.62 233.082 3.63 231.739 3.64 230.405 3.65 230.405 3.66 230.405 3.67 230.405 3.68 -220 3.69 -220 3.7 -220 3.71 -220 3.72 -220 3.73 -220 3.74 -220 3.75 -220 3.76 -220 3.77 -220 3.78 -220 3.79 -220 3.8 -220 3.81 -220 3.82 -220 3.83 -220 3.84 -220 3.85 -220 3.86 -220 3.87 -220 3.88 -220 3.89 -220 3.9 -220 3.91 -220 3.92 -220 3.93 -220 3.94 -220 3.95 -220 3.96 -220 3.97 -220 3.98 -220 3.99 -220 4 -220 4.01 -220 4.02 -220 4.03 -220 4.04 -220 4.05 -220 4.06 -220 4.07 -220 4.08 -220 4.09 -220 4.1 -220 4.11 -220 4.12 -220 4.13 -220 4.14 -220 4.15 -220 4.16 -220 4.17 -220 4.18 -220 4.19 -220 4.2 -220 4.21 -220 4.22 -220 4.23 -220 4.24 -220 4.25 266.199 4.26 261.626 4.27 260.119 4.28 260.119 4.29 258.621 4.3 258.621 4.31 260.119 4.32 260.119 4.33 260.119 4.34 260.119 4.35 260.119 4.36 260.119 4.37 260.119 4.38 260.119 4.39 260.119 4.4 261.626 4.41 263.141 4.42 263.141 4.43 263.141 4.44 263.141 4.45 263.141 4.46 261.626 4.47 261.626 4.48 263.141 4.49 263.141 4.5 261.626 4.51 260.119 4.52 258.621 4.53 252.714 4.54 245.519 4.55 241.301 4.56 237.156 4.57 229.078 4.58 226.446 4.59 226.446 4.6 226.446 4.61 227.758 4.62 227.758 4.63 226.446 4.64 227.758 4.65 227.758 4.66 229.078 4.67 230.405 4.68 230.405 4.69 231.739 4.7 231.739 4.71 231.739 4.72 231.739 4.73 231.739 4.74 231.739 4.75 231.739 4.76 233.082 4.77 231.739 4.78 231.739 4.79 231.739 4.8 231.739 4.81 231.739 4.82 231.739 4.83 231.739 4.84 231.739 4.85 231.739 4.86 231.739 4.87 231.739 4.88 231.739 4.89 233.082 4.9 233.082 4.91 233.082 4.92 231.739 4.93 231.739 4.94 231.739 4.95 231.739 4.96 230.405 4.97 230.405 4.98 231.739 4.99 231.739 5 231.739 5.01 230.405 5.02 229.078 5.03 229.078 5.04 229.078 5.05 227.758 5.06 227.758 5.07 227.758 5.08 227.758 5.09 227.758 5.1 229.078 5.11 231.739 5.12 -220 5.13 -220 5.14 -220 5.15 -220 5.16 -220 5.17 -220 5.18 264.666 5.19 261.626 5.2 266.199 5.21 266.199 5.22 266.199 5.23 266.199 5.24 264.666 5.25 264.666 5.26 264.666 5.27 263.141 5.28 263.141 5.29 261.626 5.3 261.626 5.31 261.626 5.32 260.119 5.33 260.119 5.34 261.626 5.35 261.626 5.36 261.626 5.37 263.141 5.38 263.141 5.39 261.626 5.4 261.626 5.41 261.626 5.42 261.626 5.43 261.626 5.44 260.119 5.45 261.626 5.46 261.626 5.47 260.119 5.48 258.621 5.49 260.119 5.5 261.626 5.51 260.119 5.52 260.119 5.53 260.119 5.54 260.119 5.55 258.621 5.56 260.119 5.57 261.626 5.58 258.621 5.59 254.178 5.6 -234.432 5.61 -234.432 5.62 -234.432 5.63 -234.432 5.64 -234.432 5.65 -233.082 5.66 -234.432 5.67 -234.432 5.68 -234.432 5.69 -234.432 5.7 -235.79 5.71 -235.79 5.72 -234.432 5.73 -233.082 5.74 -220 5.75 269.292 5.76 277.183 5.77 280.403 5.78 285.305 5.79 290.292 5.8 293.665 5.81 295.366 5.82 295.366 5.83 295.366 5.84 295.366 5.85 295.366 5.86 295.366 5.87 295.366 5.88 295.366 5.89 293.665 5.9 293.665 5.91 293.665 5.92 293.665 5.93 293.665 5.94 293.665 5.95 293.665 5.96 293.665 5.97 291.973 5.98 291.973 5.99 291.973 6 291.973 6.01 293.665 6.02 293.665 6.03 293.665 6.04 293.665 6.05 293.665 6.06 293.665 6.07 293.665 6.08 293.665 6.09 293.665 6.1 293.665 6.11 293.665 6.12 293.665 6.13 293.665 6.14 291.973 6.15 291.973 6.16 291.973 6.17 291.973 6.18 291.973 6.19 293.665 6.2 293.665 6.21 293.665 6.22 293.665 6.23 293.665 6.24 293.665 6.25 293.665 6.26 293.665 6.27 291.973 6.28 291.973 6.29 290.292 6.3 290.292 6.31 288.62 6.32 288.62 6.33 285.305 6.34 286.957 6.35 288.62 6.36 291.973 6.37 295.366 6.38 302.27 6.39 307.553 6.4 302.27 6.41 297.077 6.42 -220 6.43 -220 6.44 -220 6.45 -220 6.46 396.55 6.47 398.847 6.48 398.847 6.49 398.847 6.5 398.847 6.51 396.55 6.52 396.55 6.53 396.55 6.54 394.266 6.55 394.266 6.56 394.266 6.57 391.995 6.58 391.995 6.59 391.995 6.6 391.995 6.61 389.738 6.62 389.738 6.63 391.995 6.64 391.995 6.65 391.995 6.66 391.995 6.67 391.995 6.68 391.995 6.69 391.995 6.7 391.995 6.71 394.266 6.72 391.995 6.73 391.995 6.74 389.738 6.75 389.738 6.76 389.738 6.77 389.738 6.78 389.738 6.79 391.995 6.8 391.995 6.81 391.995 6.82 394.266 6.83 394.266 6.84 394.266 6.85 394.266 6.86 394.266 6.87 394.266 6.88 394.266 6.89 391.995 6.9 391.995 6.91 391.995 6.92 391.995 6.93 391.995 6.94 394.266 6.95 396.55 6.96 396.55 6.97 398.847 6.98 -220 6.99 -220 7 -220 7.01 -220 7.02 -440 7.03 -440 7.04 349.228 7.05 347.217 7.06 347.217 7.07 347.217 7.08 349.228 7.09 349.228 7.1 347.217 7.11 347.217 7.12 349.228 7.13 349.228 7.14 347.217 7.15 347.217 7.16 347.217 7.17 347.217 7.18 347.217 7.19 347.217 7.2 347.217 7.21 347.217 7.22 347.217 7.23 347.217 7.24 347.217 7.25 347.217 7.26 347.217 7.27 347.217 7.28 347.217 7.29 347.217 7.3 347.217 7.31 347.217 7.32 347.217 7.33 347.217 7.34 347.217 7.35 347.217 7.36 349.228 7.37 349.228 7.38 347.217 7.39 347.217 7.4 347.217 7.41 347.217 7.42 347.217 7.43 347.217 7.44 345.217 7.45 345.217 7.46 347.217 7.47 347.217 7.48 345.217 7.49 345.217 7.5 345.217 7.51 345.217 7.52 347.217 7.53 347.217 7.54 347.217 7.55 347.217 7.56 345.217 7.57 347.217 7.58 347.217 7.59 347.217 7.6 347.217 7.61 347.217 7.62 349.228 7.63 349.228 7.64 349.228 7.65 349.228 7.66 349.228 7.67 349.228 7.68 349.228 7.69 347.217 7.7 347.217 7.71 347.217 7.72 349.228 7.73 349.228 7.74 349.228 7.75 349.228 7.76 349.228 7.77 349.228 7.78 349.228 7.79 349.228 7.8 349.228 7.81 349.228 7.82 349.228 7.83 349.228 7.84 349.228 7.85 347.217 7.86 347.217 7.87 347.217 7.88 349.228 7.89 349.228 7.9 349.228 7.91 347.217 7.92 347.217 7.93 347.217 7.94 347.217 7.95 347.217 7.96 347.217 7.97 347.217 7.98 347.217 7.99 347.217 8 347.217 8.01 347.217 8.02 347.217 8.03 347.217 8.04 347.217 8.05 347.217 8.06 347.217 8.07 345.217 8.08 345.217 8.09 347.217 8.1 345.217 8.11 347.217 8.12 345.217 8.13 347.217 8.14 349.228 8.15 339.286 8.16 345.217 8.17 347.217 8.18 -440 8.19 -440 8.2 -440 8.21 -440 8.22 -440 8.23 -440 8.24 -440 8.25 -440 8.26 -440 8.27 -440 8.28 -440 8.29 -440 8.3 -440 8.31 -440 8.32 -440 8.33 -440 8.34 -440 8.35 -440 8.36 -440 8.37 -440 8.38 -440 8.39 -440 8.4 -440 8.41 -440 8.42 -440 8.43 -440 8.44 -440 8.45 -440 8.46 -440 8.47 -440 8.48 -440 8.49 -440 8.5 -440 8.51 -440 8.52 -440 8.53 -440 8.54 -440 8.55 -440 8.56 -440 8.57 -440 8.58 -440 8.59 -440 8.6 -440 8.61 -440 8.62 -440 8.63 -440 8.64 -440 8.65 -440 8.66 -440 8.67 -440 8.68 -440 8.69 -440 8.7 -440 8.71 -440 8.72 -440 8.73 -440 8.74 -440 8.75 -440 8.76 -440 8.77 -440 8.78 -440 8.79 -440 8.8 -440 8.81 -440 8.82 -440 8.83 -440 8.84 -440 8.85 -440 8.86 -440 8.87 -440 8.88 -440 8.89 -440 8.9 -440 8.91 -440 8.92 -440 8.93 -440 8.94 -440 8.95 -440 8.96 -440 8.97 -440 8.98 -440 8.99 316.565 9 312.929 9.01 311.127 9.02 307.553 9.03 309.335 9.04 309.335 9.05 309.335 9.06 311.127 9.07 309.335 9.08 309.335 9.09 309.335 9.1 311.127 9.11 311.127 9.12 311.127 9.13 309.335 9.14 309.335 9.15 309.335 9.16 309.335 9.17 309.335 9.18 309.335 9.19 309.335 9.2 309.335 9.21 311.127 9.22 309.335 9.23 309.335 9.24 309.335 9.25 309.335 9.26 309.335 9.27 309.335 9.28 309.335 9.29 311.127 9.3 309.335 9.31 309.335 9.32 311.127 9.33 311.127 9.34 311.127 9.35 311.127 9.36 311.127 9.37 311.127 9.38 309.335 9.39 309.335 9.4 309.335 9.41 309.335 9.42 309.335 9.43 309.335 9.44 309.335 9.45 309.335 9.46 307.553 9.47 307.553 9.48 307.553 9.49 307.553 9.5 304.021 9.51 302.27 9.52 305.782 9.53 307.553 9.54 311.127 9.55 312.929 9.56 314.742 9.57 -440 9.58 -440 9.59 -440 9.6 -440 9.61 -440 9.62 -440 9.63 -440 9.64 349.228 9.65 349.228 9.66 351.251 9.67 351.251 9.68 353.286 9.69 353.286 9.7 351.251 9.71 351.251 9.72 351.251 9.73 349.228 9.74 349.228 9.75 349.228 9.76 347.217 9.77 347.217 9.78 347.217 9.79 347.217 9.8 345.217 9.81 347.217 9.82 347.217 9.83 347.217 9.84 347.217 9.85 347.217 9.86 347.217 9.87 347.217 9.88 347.217 9.89 347.217 9.9 347.217 9.91 347.217 9.92 347.217 9.93 347.217 9.94 347.217 9.95 349.228 9.96 347.217 9.97 347.217 9.98 347.217 9.99 347.217 10 347.217 10.01 349.228 10.02 347.217 10.03 347.217 10.04 347.217 10.05 345.217 10.06 345.217 10.07 349.228 10.08 347.217 10.09 347.217 10.1 347.217 10.11 349.228 10.12 349.228 10.13 351.251 10.14 351.251 10.15 353.286 10.16 353.286 10.17 353.286 10.18 353.286 10.19 349.228 10.2 347.217 10.21 345.217 10.22 341.252 10.23 335.389 10.24 327.729 10.25 323.965 10.26 316.565 10.27 312.929 10.28 312.929 10.29 312.929 10.3 307.553 10.31 305.782 10.32 304.021 10.33 302.27 10.34 302.27 10.35 302.27 10.36 304.021 10.37 305.782 10.38 305.782 10.39 307.553 10.4 309.335 10.41 309.335 10.42 309.335 10.43 309.335 10.44 309.335 10.45 309.335 10.46 309.335 10.47 309.335 10.48 307.553 10.49 309.335 10.5 309.335 10.51 309.335 10.52 309.335 10.53 311.127 10.54 311.127 10.55 311.127 10.56 311.127 10.57 311.127 10.58 311.127 10.59 311.127 10.6 309.335 10.61 309.335 10.62 309.335 10.63 309.335 10.64 309.335 10.65 309.335 10.66 309.335 10.67 311.127 10.68 311.127 10.69 309.335 10.7 311.127 10.71 311.127 10.72 311.127 10.73 311.127 10.74 311.127 10.75 311.127 10.76 311.127 10.77 311.127 10.78 311.127 10.79 312.929 10.8 314.742 10.81 316.565 10.82 316.565 10.83 316.565 10.84 314.742 10.85 312.929 10.86 305.782 10.87 304.021 10.88 302.27 10.89 302.27 10.9 300.529 10.91 298.798 10.92 297.077 10.93 293.665 10.94 291.973 10.95 291.973 10.96 293.665 10.97 290.292 10.98 288.62 10.99 286.957 11 290.292 11.01 290.292 11.02 288.62 11.03 286.957 11.04 290.292 11.05 293.665 11.06 293.665 11.07 291.973 11.08 291.973 11.09 291.973 11.1 293.665 11.11 291.973 11.12 291.973 11.13 290.292 11.14 290.292 11.15 293.665 11.16 293.665 11.17 291.973 11.18 291.973 11.19 293.665 11.2 293.665 11.21 293.665 11.22 293.665 11.23 293.665 11.24 293.665 11.25 293.665 11.26 291.973 11.27 291.973 11.28 291.973 11.29 295.366 11.3 295.366 11.31 293.665 11.32 291.973 11.33 291.973 11.34 293.665 11.35 295.366 11.36 295.366 11.37 293.665 11.38 293.665 11.39 295.366 11.4 297.077 11.41 297.077 11.42 293.665 11.43 290.292 11.44 290.292 11.45 295.366 11.46 297.077 11.47 295.366 11.48 293.665 11.49 293.665 11.5 295.366 11.51 297.077 11.52 297.077 11.53 295.366 11.54 291.973 11.55 291.973 11.56 297.077 11.57 298.798 11.58 300.529 11.59 300.529 11.6 300.529 11.61 300.529 11.62 297.077 11.63 293.665 11.64 297.077 11.65 297.077 11.66 297.077 11.67 304.021 11.68 298.798 11.69 293.665 11.7 -263.141 11.71 -261.626 11.72 263.141 11.73 264.666 11.74 260.119 11.75 263.141 11.76 260.119 11.77 257.131 11.78 255.65 11.79 255.65 11.8 255.65 11.81 257.131 11.82 255.65 11.83 258.621 11.84 260.119 11.85 260.119 11.86 258.621 11.87 260.119 11.88 260.119 11.89 260.119 11.9 260.119 11.91 261.626 11.92 260.119 11.93 260.119 11.94 261.626 11.95 261.626 11.96 261.626 11.97 261.626 11.98 261.626 11.99 261.626 12 261.626 12.01 260.119 12.02 260.119 12.03 260.119 12.04 260.119 12.05 260.119 12.06 260.119 12.07 258.621 12.08 260.119 12.09 260.119 12.1 258.621 12.11 258.621 12.12 257.131 12.13 257.131 12.14 252.714 12.15 249.811 12.16 255.65 12.17 258.621 12.18 263.141 12.19 266.199 12.2 270.852 12.21 278.788 12.22 286.957 12.23 291.973 12.24 291.973 12.25 293.665 12.26 297.077 12.27 295.366 12.28 295.366 12.29 295.366 12.3 295.366 12.31 297.077 12.32 297.077 12.33 293.665 12.34 291.973 12.35 291.973 12.36 293.665 12.37 293.665 12.38 293.665 12.39 291.973 12.4 291.973 12.41 291.973 12.42 291.973 12.43 291.973 12.44 291.973 12.45 291.973 12.46 291.973 12.47 291.973 12.48 291.973 12.49 291.973 12.5 291.973 12.51 291.973 12.52 291.973 12.53 293.665 12.54 293.665 12.55 293.665 12.56 293.665 12.57 293.665 12.58 293.665 12.59 293.665 12.6 291.973 12.61 291.973 12.62 291.973 12.63 291.973 12.64 291.973 12.65 291.973 12.66 290.292 12.67 290.292 12.68 290.292 12.69 291.973 12.7 291.973 12.71 290.292 12.72 291.973 12.73 291.973 12.74 291.973 12.75 291.973 12.76 291.973 12.77 291.973 12.78 291.973 12.79 291.973 12.8 290.292 12.81 291.973 12.82 290.292 12.83 291.973 12.84 291.973 12.85 293.665 12.86 295.366 12.87 293.665 12.88 293.665 12.89 291.973 12.9 291.973 12.91 291.973 12.92 293.665 12.93 293.665 12.94 293.665 12.95 291.973 12.96 293.665 12.97 293.665 12.98 293.665 12.99 293.665 13 293.665 13.01 293.665 13.02 293.665 13.03 293.665 13.04 293.665 13.05 293.665 13.06 293.665 13.07 293.665 13.08 293.665 13.09 293.665 13.1 293.665 13.11 291.973 13.12 293.665 13.13 291.973 13.14 293.665 13.15 291.973 13.16 290.292 13.17 291.973 13.18 293.665 13.19 293.665 13.2 293.665 13.21 291.973 13.22 290.292 13.23 291.973 13.24 295.366 13.25 297.077 13.26 295.366 13.27 291.973 13.28 291.973 13.29 293.665 13.3 295.366 13.31 293.665 13.32 291.973 13.33 290.292 13.34 293.665 13.35 295.366 13.36 295.366 13.37 293.665 13.38 290.292 13.39 290.292 13.4 293.665 13.41 293.665 13.42 291.973 13.43 291.973 13.44 291.973 13.45 291.973 13.46 291.973 13.47 293.665 13.48 291.973 13.49 290.292 13.5 290.292 13.51 293.665 13.52 293.665 13.53 291.973 13.54 288.62 13.55 290.292 13.56 291.973 13.57 293.665 13.58 293.665 13.59 291.973 13.6 293.665 13.61 293.665 13.62 293.665 13.63 291.973 13.64 290.292 13.65 288.62 13.66 290.292 13.67 291.973 13.68 291.973 13.69 295.366 13.7 298.798 13.71 298.798 13.72 297.077 13.73 297.077 13.74 298.798 13.75 297.077 13.76 -220 13.77 -220 13.78 -220 13.79 -220 13.8 -220 13.81 -220 13.82 -220 13.83 -220 13.84 -220 13.85 -220 13.86 -220 13.87 -220 13.88 -220 13.89 -220 13.9 -220 13.91 -220 13.92 -220 13.93 -220 13.94 -220 13.95 -220 13.96 -220 13.97 -220 13.98 -220 13.99 -220 14 -220 14.01 -220 14.02 -220 14.03 -220 14.04 -220 14.05 -220 14.06 -220 14.07 -220 14.08 -220 14.09 -220 14.1 -220 14.11 -220 14.12 -220 14.13 -220 14.14 -220 14.15 -220 14.16 -220 14.17 -220 14.18 -220 14.19 -220 14.2 -221.274 14.21 -222.556 14.22 -218.733 14.23 -217.473 14.24 -218.733 14.25 -217.473 14.26 -218.733 14.27 -218.733 14.28 -218.733 14.29 -218.733 14.3 -220 14.31 -218.733 14.32 -218.733 14.33 -217.473 14.34 -217.473 14.35 -217.473 14.36 -217.473 14.37 -217.473 14.38 -218.733 14.39 -218.733 14.4 -220 14.41 -220 14.42 -220 14.43 -220 14.44 -218.733 14.45 -218.733 14.46 -220 14.47 -220 14.48 -220 14.49 -220 14.5 -218.733 14.51 -218.733 14.52 -218.733 14.53 -218.733 14.54 -218.733 14.55 -218.733 14.56 -218.733 14.57 -218.733 14.58 -218.733 14.59 -218.733 14.6 -218.733 14.61 -218.733 14.62 -218.733 14.63 -217.473 14.64 -216.221 14.65 -220 14.66 -220 14.67 -220 14.68 -220 14.69 -220 14.7 -220 14.71 -220 14.72 -220 14.73 -220 14.74 -220 14.75 -220 14.76 -220 14.77 -220 14.78 -220 14.79 -220 14.8 -220 14.81 246.942 14.82 245.519 14.83 248.372 14.84 258.621 14.85 261.626 14.86 263.141 14.87 264.666 14.88 263.141 14.89 264.666 14.9 264.666 14.91 264.666 14.92 263.141 14.93 263.141 14.94 263.141 14.95 263.141 14.96 261.626 14.97 261.626 14.98 261.626 14.99 260.119 15 260.119 15.01 260.119 15.02 260.119 15.03 261.626 15.04 261.626 15.05 261.626 15.06 261.626 15.07 261.626 15.08 261.626 15.09 261.626 15.1 261.626 15.11 260.119 15.12 260.119 15.13 260.119 15.14 260.119 15.15 258.621 15.16 260.119 15.17 260.119 15.18 260.119 15.19 260.119 15.2 260.119 15.21 260.119 15.22 260.119 15.23 260.119 15.24 261.626 15.25 261.626 15.26 260.119 15.27 261.626 15.28 261.626 15.29 260.119 15.3 260.119 15.31 260.119 15.32 260.119 15.33 260.119 15.34 260.119 15.35 258.621 15.36 260.119 15.37 260.119 15.38 261.626 15.39 263.141 15.4 261.626 15.41 261.626 15.42 261.626 15.43 261.626 15.44 261.626 15.45 263.141 15.46 263.141 15.47 263.141 15.48 263.141 15.49 264.666 15.5 264.666 15.51 264.666 15.52 264.666 15.53 264.666 15.54 264.666 15.55 264.666 15.56 263.141 15.57 257.131 15.58 -220 15.59 -220 15.6 -220 15.61 -220 15.62 -220 15.63 -220 15.64 -220 15.65 -220 15.66 -220 15.67 -220 15.68 233.082 15.69 231.739 15.7 231.739 15.71 230.405 15.72 231.739 15.73 231.739 15.74 231.739 15.75 231.739 15.76 231.739 15.77 231.739 15.78 231.739 15.79 230.405 15.8 233.082 15.81 233.082 15.82 231.739 15.83 233.082 15.84 231.739 15.85 233.082 15.86 231.739 15.87 230.405 15.88 231.739 15.89 231.739 15.9 230.405 15.91 229.078 15.92 227.758 15.93 229.078 15.94 230.405 15.95 231.739 15.96 231.739 15.97 231.739 15.98 231.739 15.99 231.739 16 231.739 16.01 231.739 16.02 233.082 16.03 233.082 16.04 233.082 16.05 233.082 16.06 233.082 16.07 231.739 16.08 230.405 16.09 225.142 16.1 225.142 16.11 225.142 16.12 221.274 16.13 222.556 16.14 220 16.15 222.556 16.16 223.846 16.17 220 16.18 216.221 16.19 214.975 16.2 213.737 16.21 213.737 16.22 213.737 16.23 216.221 16.24 217.473 16.25 217.473 16.26 217.473 16.27 217.473 16.28 218.733 16.29 217.473 16.3 220 16.31 220 16.32 220 16.33 220 16.34 220 16.35 218.733 16.36 217.473 16.37 218.733 16.38 218.733 16.39 218.733 16.4 220 16.41 220 16.42 218.733 16.43 217.473 16.44 217.473 16.45 220 16.46 220 16.47 218.733 16.48 220 16.49 220 16.5 220 16.51 220 16.52 220 16.53 218.733 16.54 220 16.55 220 16.56 218.733 16.57 218.733 16.58 218.733 16.59 218.733 16.6 220 16.61 218.733 16.62 220 16.63 220 16.64 220 16.65 220 16.66 220 16.67 220 16.68 217.473 16.69 217.473 16.7 221.274 16.71 221.274 16.72 218.733 16.73 218.733 16.74 220 16.75 221.274 16.76 220 16.77 217.473 16.78 218.733 16.79 220 16.8 220 16.81 218.733 16.82 218.733 16.83 218.733 16.84 218.733 16.85 218.733 16.86 217.473 16.87 217.473 16.88 218.733 16.89 220 16.9 220 16.91 220 16.92 -220 16.93 -220 16.94 -220 16.95 -220 16.96 -220 16.97 -220 16.98 -220 16.99 -220 17 -220 17.01 -220 17.02 -220 17.03 -220 17.04 -220 17.05 -237.156 17.06 -235.79 17.07 -234.432 17.08 -233.082 17.09 -230.405 17.1 -229.078 17.11 -230.405 17.12 -230.405 17.13 -230.405 17.14 -230.405 17.15 -231.739 17.16 -231.739 17.17 -233.082 17.18 -233.082 17.19 -231.739 17.2 -233.082 17.21 -233.082 17.22 -231.739 17.23 -231.739 17.24 -231.739 17.25 -230.405 17.26 -231.739 17.27 -231.739 17.28 -231.739 17.29 -231.739 17.3 -231.739 17.31 -231.739 17.32 -231.739 17.33 -230.405 17.34 -230.405 17.35 -229.078 17.36 -229.078 17.37 -227.758 17.38 -220 17.39 -220 17.4 -220 17.41 -220 17.42 -220 17.43 -220 17.44 -220 17.45 -220 17.46 -220 17.47 269.292 17.48 267.741 17.49 266.199 17.5 264.666 17.51 263.141 17.52 263.141 17.53 263.141 17.54 263.141 17.55 263.141 17.56 263.141 17.57 261.626 17.58 261.626 17.59 260.119 17.6 261.626 17.61 260.119 17.62 260.119 17.63 260.119 17.64 260.119 17.65 260.119 17.66 260.119 17.67 260.119 17.68 260.119 17.69 258.621 17.7 260.119 17.71 260.119 17.72 260.119 17.73 260.119 17.74 260.119 17.75 260.119 17.76 260.119 17.77 261.626 17.78 260.119 17.79 261.626 17.8 261.626 17.81 261.626 17.82 260.119 17.83 260.119 17.84 260.119 17.85 260.119 17.86 260.119 17.87 260.119 17.88 260.119 17.89 258.621 17.9 260.119 17.91 260.119 17.92 260.119 17.93 260.119 17.94 260.119 17.95 260.119 17.96 260.119 17.97 260.119 17.98 260.119 17.99 260.119 18 258.621 18.01 260.119 18.02 260.119 18.03 258.621 18.04 258.621 18.05 260.119 18.06 261.626 18.07 260.119 18.08 260.119 18.09 261.626 18.1 261.626 18.11 261.626 18.12 261.626 18.13 261.626 18.14 260.119 18.15 258.621 18.16 261.626 18.17 261.626 18.18 260.119 18.19 261.626 18.2 261.626 18.21 261.626 18.22 260.119 18.23 261.626 18.24 261.626 18.25 260.119 18.26 260.119 18.27 263.141 18.28 261.626 18.29 260.119 18.3 261.626 18.31 261.626 18.32 260.119 18.33 261.626 18.34 261.626 18.35 261.626 18.36 260.119 18.37 261.626 18.38 261.626 18.39 260.119 18.4 260.119 18.41 260.119 18.42 260.119 18.43 260.119 18.44 260.119 18.45 260.119 18.46 260.119 18.47 260.119 18.48 261.626 18.49 261.626 18.5 261.626 18.51 260.119 18.52 260.119 18.53 260.119 18.54 260.119 18.55 260.119 18.56 261.626 18.57 260.119 18.58 261.626 18.59 261.626 18.6 260.119 18.61 258.621 18.62 260.119 18.63 260.119 18.64 258.621 18.65 258.621 18.66 261.626 18.67 261.626 18.68 261.626 18.69 261.626 18.7 263.141 18.71 261.626 18.72 261.626 18.73 261.626 18.74 260.119 18.75 260.119 18.76 260.119 18.77 260.119 18.78 260.119 18.79 260.119 18.8 261.626 18.81 260.119 18.82 260.119 18.83 260.119 18.84 261.626 18.85 260.119 18.86 260.119 18.87 260.119 18.88 261.626 18.89 261.626 18.9 261.626 18.91 261.626 18.92 260.119 18.93 260.119 18.94 260.119 18.95 260.119 18.96 260.119 18.97 260.119 18.98 260.119 18.99 260.119 19 260.119 19.01 260.119 19.02 261.626 19.03 261.626 19.04 261.626 19.05 261.626 19.06 261.626 19.07 261.626 19.08 260.119 19.09 260.119 19.1 260.119 19.11 260.119 19.12 260.119 19.13 260.119 19.14 260.119 19.15 260.119 19.16 260.119 19.17 260.119 19.18 260.119 19.19 260.119 19.2 260.119 19.21 260.119 19.22 260.119 19.23 260.119 19.24 261.626 19.25 261.626 19.26 261.626 19.27 260.119 19.28 260.119 19.29 260.119 19.3 260.119 19.31 260.119 19.32 261.626 19.33 261.626 19.34 261.626 19.35 261.626 19.36 261.626 19.37 260.119 19.38 260.119 19.39 260.119 19.4 260.119 19.41 260.119 19.42 258.621 19.43 258.621 19.44 260.119 19.45 260.119 19.46 260.119 19.47 260.119 19.48 260.119 19.49 260.119 19.5 260.119 19.51 261.626 19.52 261.626 19.53 260.119 19.54 261.626 19.55 261.626 19.56 261.626 19.57 261.626 19.58 261.626 19.59 263.141 19.6 261.626 19.61 260.119 19.62 260.119 19.63 260.119 19.64 260.119 19.65 260.119 19.66 260.119 19.67 260.119 19.68 260.119 19.69 260.119 19.7 260.119 19.71 258.621 19.72 260.119 19.73 260.119 19.74 260.119 19.75 260.119 19.76 261.626 19.77 261.626 19.78 263.141 19.79 263.141 19.8 261.626 19.81 261.626 19.82 260.119 19.83 260.119 19.84 260.119 19.85 258.621 19.86 258.621 19.87 258.621 19.88 258.621 19.89 257.131 19.9 258.621 19.91 260.119 19.92 260.119 19.93 260.119 19.94 260.119 19.95 260.119 19.96 261.626 19.97 261.626 19.98 261.626 19.99 263.141 20 264.666 20.01 263.141 20.02 263.141 20.03 261.626 20.04 260.119 20.05 260.119 20.06 260.119 20.07 258.621 20.08 257.131 20.09 257.131 20.1 257.131 20.11 258.621 20.12 258.621 20.13 260.119 20.14 260.119 20.15 261.626 20.16 261.626 20.17 261.626 20.18 261.626 20.19 263.141 20.2 263.141 20.21 263.141 20.22 263.141 20.23 261.626 20.24 261.626 20.25 260.119 20.26 261.626 20.27 258.621 20.28 258.621 20.29 258.621 20.3 258.621 20.31 257.131 20.32 257.131 20.33 258.621 20.34 260.119 20.35 260.119 20.36 260.119 20.37 261.626 20.38 261.626 20.39 261.626 20.4 263.141 20.41 263.141 20.42 263.141 20.43 263.141 20.44 261.626 20.45 261.626 20.46 260.119 20.47 260.119 20.48 260.119 20.49 258.621 20.5 260.119 20.51 260.119 20.52 260.119 20.53 260.119 20.54 260.119 20.55 260.119 20.56 260.119 20.57 261.626 20.58 261.626 20.59 261.626 20.6 263.141 20.61 261.626 20.62 261.626 20.63 260.119 20.64 260.119 20.65 260.119 20.66 260.119 20.67 260.119 20.68 258.621 20.69 258.621 20.7 257.131 20.71 255.65 20.72 258.621 20.73 258.621 20.74 258.621 20.75 258.621 20.76 260.119 20.77 260.119 20.78 260.119 20.79 260.119 20.8 260.119 20.81 260.119 20.82 261.626 20.83 261.626 20.84 263.141 20.85 263.141 20.86 261.626 20.87 260.119 20.88 -220 20.89 -220 20.9 -220 20.91 -220 20.92 -220 20.93 -220 20.94 -220 20.95 -220 20.96 -220 20.97 -220 20.98 -220 20.99 -220 21 -220 21.01 -220 21.02 -220 21.03 -220 21.04 -220 21.05 -220 21.06 -220 21.07 -220 21.08 -220 21.09 -220 21.1 -220 21.11 -220 21.12 -220 21.13 -220 21.14 -220 21.15 -220 21.16 -220 21.17 -220 21.18 -220 21.19 -220 21.2 -220 21.21 -220 21.22 -220 21.23 -220 21.24 -220 21.25 -220 21.26 -220 21.27 -220 21.28 -220 21.29 -220 21.3 -220 21.31 -220 21.32 -220 21.33 -220 21.34 -220 21.35 -220 21.36 -220 21.37 -220 21.38 -220 21.39 -220 21.4 -220 21.41 -220 21.42 -220 21.43 -220 21.44 -220 21.45 -220 21.46 -220 21.47 -220 21.48 -220 21.49 -220 21.5 -220 21.51 -220 21.52 -220 21.53 -220 21.54 -220 21.55 -220 21.56 -220 21.57 -220 21.58 -220 21.59 -220 21.6 -220 21.61 -220 21.62 -220 21.63 -220 21.64 -220 21.65 -220 21.66 -220 21.67 -220 21.68 -220 21.69 -220 21.7 -220 21.71 -220 21.72 -220 21.73 -220 21.74 -220 21.75 -220 21.76 -220 21.77 -220 21.78 -220 21.79 -220 21.8 -220 21.81 -220 21.82 -220 21.83 -220 21.84 -220 21.85 -220 21.86 -220 21.87 -220 21.88 -220 21.89 -220 21.9 -220 21.91 -220 21.92 -220 21.93 -220 21.94 -220 21.95 -220 21.96 -220 21.97 -220 mir_eval-0.8.2/tests/data/melody/est02.txt000077500000000000000000000513311475740344600204050ustar00rootroot000000000000000 0 0.01 0 0.02 -220 0.03 -220 0.04 300.529 0.05 298.798 0.06 298.798 0.07 298.798 0.08 295.366 0.09 293.665 0.1 297.077 0.11 300.529 0.12 298.798 0.13 295.366 0.14 298.798 0.15 302.27 0.16 302.27 0.17 298.798 0.18 302.27 0.19 307.553 0.2 307.553 0.21 305.782 0.22 309.335 0.23 311.127 0.24 307.553 0.25 311.127 0.26 309.335 0.27 307.553 0.28 312.929 0.29 311.127 0.3 309.335 0.31 311.127 0.32 309.335 0.33 309.335 0.34 311.127 0.35 309.335 0.36 309.335 0.37 311.127 0.38 309.335 0.39 309.335 0.4 309.335 0.41 309.335 0.42 309.335 0.43 309.335 0.44 311.127 0.45 311.127 0.46 311.127 0.47 311.127 0.48 309.335 0.49 309.335 0.5 309.335 0.51 309.335 0.52 309.335 0.53 309.335 0.54 309.335 0.55 309.335 0.56 309.335 0.57 307.553 0.58 312.929 0.59 312.929 0.6 305.782 0.61 309.335 0.62 311.127 0.63 305.782 0.64 311.127 0.65 309.335 0.66 305.782 0.67 309.335 0.68 311.127 0.69 305.782 0.7 309.335 0.71 311.127 0.72 307.553 0.73 309.335 0.74 311.127 0.75 307.553 0.76 307.553 0.77 311.127 0.78 305.782 0.79 309.335 0.8 311.127 0.81 305.782 0.82 283.661 0.83 275.586 0.84 270.852 0.85 275.586 0.86 277.183 0.87 275.586 0.88 277.183 0.89 275.586 0.9 277.183 0.91 275.586 0.92 275.586 0.93 275.586 0.94 275.586 0.95 275.586 0.96 275.586 0.97 275.586 0.98 275.586 0.99 275.586 1 275.586 1.01 275.586 1.02 275.586 1.03 275.586 1.04 275.586 1.05 275.586 1.06 273.999 1.07 267.741 1.08 263.141 1.09 261.626 1.1 261.626 1.11 260.119 1.12 264.666 1.13 263.141 1.14 257.131 1.15 260.119 1.16 258.621 1.17 258.621 1.18 261.626 1.19 258.621 1.2 257.131 1.21 260.119 1.22 258.621 1.23 258.621 1.24 263.141 1.25 258.621 1.26 258.621 1.27 261.626 1.28 260.119 1.29 257.131 1.3 261.626 1.31 260.119 1.32 260.119 1.33 261.626 1.34 260.119 1.35 260.119 1.36 261.626 1.37 260.119 1.38 258.621 1.39 261.626 1.4 260.119 1.41 258.621 1.42 261.626 1.43 258.621 1.44 258.621 1.45 257.131 1.46 241.301 1.47 234.432 1.48 231.739 1.49 231.739 1.5 231.739 1.51 231.739 1.52 231.739 1.53 231.739 1.54 230.405 1.55 231.739 1.56 231.739 1.57 231.739 1.58 231.739 1.59 231.739 1.6 231.739 1.61 231.739 1.62 231.739 1.63 231.739 1.64 231.739 1.65 231.739 1.66 231.739 1.67 231.739 1.68 231.739 1.69 231.739 1.7 231.739 1.71 231.739 1.72 231.739 1.73 231.739 1.74 231.739 1.75 231.739 1.76 230.405 1.77 230.405 1.78 230.405 1.79 -220 1.8 -220 1.81 -220 1.82 -220 1.83 -220 1.84 -220 1.85 -220 1.86 -220 1.87 -220 1.88 -220 1.89 -220 1.9 147.683 1.91 139.394 1.92 138.591 1.93 138.591 1.94 137.793 1.95 138.591 1.96 137.793 1.97 137.793 1.98 137.793 1.99 137.793 2 137.793 2.01 137.793 2.02 138.591 2.03 137.793 2.04 137.793 2.05 137.793 2.06 138.591 2.07 137.793 2.08 137.793 2.09 137.793 2.1 137.793 2.11 137.793 2.12 137.793 2.13 138.591 2.14 137.793 2.15 138.591 2.16 138.591 2.17 138.591 2.18 138.591 2.19 137.793 2.2 138.591 2.21 137.793 2.22 137.793 2.23 138.591 2.24 138.591 2.25 137.793 2.26 138.591 2.27 138.591 2.28 -355.333 2.29 -220 2.3 -220 2.31 -220 2.32 -220 2.33 -220 2.34 -220 2.35 -220 2.36 -220 2.37 -220 2.38 -220 2.39 -220 2.4 -220 2.41 206.456 2.42 205.267 2.43 205.267 2.44 205.267 2.45 205.267 2.46 205.267 2.47 205.267 2.48 205.267 2.49 205.267 2.5 205.267 2.51 205.267 2.52 205.267 2.53 206.456 2.54 206.456 2.55 205.267 2.56 206.456 2.57 206.456 2.58 206.456 2.59 206.456 2.6 206.456 2.61 206.456 2.62 206.456 2.63 206.456 2.64 206.456 2.65 205.267 2.66 206.456 2.67 205.267 2.68 206.456 2.69 206.456 2.7 205.267 2.71 205.267 2.72 206.456 2.73 206.456 2.74 206.456 2.75 206.456 2.76 206.456 2.77 206.456 2.78 206.456 2.79 205.267 2.8 206.456 2.81 206.456 2.82 205.267 2.83 205.267 2.84 205.267 2.85 206.456 2.86 206.456 2.87 206.456 2.88 205.267 2.89 206.456 2.9 206.456 2.91 206.456 2.92 206.456 2.93 206.456 2.94 206.456 2.95 207.652 2.96 211.282 2.97 206.456 2.98 204.085 2.99 212.506 3 211.282 3.01 205.267 3.02 202.91 3.03 210.065 3.04 210.065 3.05 206.456 3.06 205.267 3.07 206.456 3.08 206.456 3.09 206.456 3.1 206.456 3.11 207.652 3.12 206.456 3.13 206.456 3.14 207.652 3.15 206.456 3.16 -220 3.17 -220 3.18 -220 3.19 -220 3.2 -220 3.21 -220 3.22 -220 3.23 -220 3.24 -172.609 3.25 -171.614 3.26 -176.643 3.27 -176.643 3.28 -174.614 3.29 -172.609 3.3 -173.608 3.31 -177.666 3.32 -177.666 3.33 -174.614 3.34 -172.609 3.35 -179.731 3.36 -178.696 3.37 -220 3.38 -220 3.39 -220 3.4 -220 3.41 -220 3.42 -220 3.43 -220 3.44 -220 3.45 -220 3.46 -220 3.47 -220 3.48 -220 3.49 -220 3.5 -220 3.51 -220 3.52 -220 3.53 -220 3.54 -220 3.55 -220 3.56 -220 3.57 -220 3.58 -220 3.59 -220 3.6 -220 3.61 -220 3.62 -220 3.63 -220 3.64 -220 3.65 -220 3.66 -220 3.67 -220 3.68 -220 3.69 -220 3.7 -220 3.71 -220 3.72 -220 3.73 -220 3.74 -220 3.75 -263.141 3.76 -261.626 3.77 -261.626 3.78 -261.626 3.79 -263.141 3.8 -263.141 3.81 -261.626 3.82 -261.626 3.83 -263.141 3.84 -263.141 3.85 -261.626 3.86 -261.626 3.87 -261.626 3.88 -263.141 3.89 -261.626 3.9 -261.626 3.91 -261.626 3.92 -261.626 3.93 -261.626 3.94 -261.626 3.95 -261.626 3.96 -261.626 3.97 -261.626 3.98 -261.626 3.99 -260.119 4 -261.626 4.01 175.626 4.02 180.772 4.03 179.731 4.04 178.696 4.05 178.696 4.06 181.819 4.07 181.819 4.08 179.731 4.09 178.696 4.1 177.666 4.11 176.643 4.12 177.666 4.13 180.772 4.14 -261.626 4.15 -220 4.16 -220 4.17 -220 4.18 -220 4.19 -220 4.2 -220 4.21 -220 4.22 -220 4.23 -220 4.24 -220 4.25 -220 4.26 -220 4.27 180.772 4.28 182.872 4.29 180.772 4.3 179.731 4.31 179.731 4.32 180.772 4.33 180.772 4.34 180.772 4.35 180.772 4.36 179.731 4.37 178.696 4.38 179.731 4.39 180.772 4.4 181.819 4.41 180.772 4.42 179.731 4.43 180.772 4.44 179.731 4.45 179.731 4.46 180.772 4.47 181.819 4.48 180.772 4.49 179.731 4.5 180.772 4.51 180.772 4.52 180.772 4.53 180.772 4.54 181.819 4.55 180.772 4.56 179.731 4.57 179.731 4.58 180.772 4.59 180.772 4.6 180.772 4.61 180.772 4.62 180.772 4.63 180.772 4.64 179.731 4.65 178.696 4.66 177.666 4.67 175.626 4.68 174.614 4.69 172.609 4.7 172.609 4.71 173.608 4.72 172.609 4.73 173.608 4.74 173.608 4.75 173.608 4.76 173.608 4.77 173.608 4.78 173.608 4.79 173.608 4.8 173.608 4.81 172.609 4.82 173.608 4.83 173.608 4.84 173.608 4.85 173.608 4.86 173.608 4.87 173.608 4.88 173.608 4.89 173.608 4.9 174.614 4.91 -220 4.92 -220 4.93 -220 4.94 -220 4.95 -220 4.96 -220 4.97 -220 4.98 -220 4.99 -220 5 -220 5.01 -220 5.02 -220 5.03 -220 5.04 -220 5.05 -220 5.06 -220 5.07 231.739 5.08 229.078 5.09 229.078 5.1 230.405 5.11 229.078 5.12 229.078 5.13 230.405 5.14 230.405 5.15 230.405 5.16 230.405 5.17 230.405 5.18 229.078 5.19 230.405 5.2 231.739 5.21 231.739 5.22 231.739 5.23 231.739 5.24 230.405 5.25 230.405 5.26 231.739 5.27 231.739 5.28 230.405 5.29 230.405 5.3 230.405 5.31 230.405 5.32 231.739 5.33 231.739 5.34 231.739 5.35 230.405 5.36 230.405 5.37 230.405 5.38 230.405 5.39 231.739 5.4 231.739 5.41 230.405 5.42 230.405 5.43 230.405 5.44 230.405 5.45 230.405 5.46 231.739 5.47 230.405 5.48 230.405 5.49 230.405 5.5 231.739 5.51 230.405 5.52 230.405 5.53 231.739 5.54 230.405 5.55 230.405 5.56 231.739 5.57 230.405 5.58 230.405 5.59 231.739 5.6 231.739 5.61 229.078 5.62 230.405 5.63 231.739 5.64 230.405 5.65 230.405 5.66 231.739 5.67 231.739 5.68 230.405 5.69 230.405 5.7 230.405 5.71 230.405 5.72 230.405 5.73 231.739 5.74 230.405 5.75 230.405 5.76 231.739 5.77 231.739 5.78 229.078 5.79 221.274 5.8 211.282 5.81 206.456 5.82 206.456 5.83 205.267 5.84 205.267 5.85 206.456 5.86 207.652 5.87 206.456 5.88 206.456 5.89 206.456 5.9 205.267 5.91 205.267 5.92 205.267 5.93 206.456 5.94 205.267 5.95 205.267 5.96 205.267 5.97 205.267 5.98 205.267 5.99 205.267 6 206.456 6.01 205.267 6.02 206.456 6.03 206.456 6.04 206.456 6.05 207.652 6.06 206.456 6.07 202.91 6.08 202.91 6.09 204.085 6.1 198.275 6.11 198.275 6.12 198.275 6.13 200.579 6.14 202.91 6.15 205.267 6.16 206.456 6.17 206.456 6.18 206.456 6.19 205.267 6.2 206.456 6.21 206.456 6.22 206.456 6.23 206.456 6.24 206.456 6.25 206.456 6.26 206.456 6.27 206.456 6.28 206.456 6.29 206.456 6.3 206.456 6.31 206.456 6.32 206.456 6.33 206.456 6.34 205.267 6.35 206.456 6.36 206.456 6.37 206.456 6.38 206.456 6.39 206.456 6.4 206.456 6.41 206.456 6.42 206.456 6.43 206.456 6.44 206.456 6.45 206.456 6.46 206.456 6.47 206.456 6.48 206.456 6.49 206.456 6.5 206.456 6.51 206.456 6.52 206.456 6.53 206.456 6.54 206.456 6.55 206.456 6.56 206.456 6.57 206.456 6.58 206.456 6.59 206.456 6.6 206.456 6.61 206.456 6.62 206.456 6.63 206.456 6.64 206.456 6.65 206.456 6.66 206.456 6.67 206.456 6.68 206.456 6.69 206.456 6.7 206.456 6.71 206.456 6.72 206.456 6.73 206.456 6.74 206.456 6.75 206.456 6.76 206.456 6.77 206.456 6.78 206.456 6.79 206.456 6.8 206.456 6.81 206.456 6.82 206.456 6.83 206.456 6.84 206.456 6.85 206.456 6.86 207.652 6.87 208.855 6.88 207.652 6.89 205.267 6.9 206.456 6.91 206.456 6.92 206.456 6.93 206.456 6.94 206.456 6.95 206.456 6.96 206.456 6.97 206.456 6.98 206.456 6.99 205.267 7 206.456 7.01 206.456 7.02 206.456 7.03 206.456 7.04 207.652 7.05 207.652 7.06 207.652 7.07 206.456 7.08 206.456 7.09 206.456 7.1 206.456 7.11 206.456 7.12 207.652 7.13 206.456 7.14 204.085 7.15 204.085 7.16 205.267 7.17 205.267 7.18 206.456 7.19 206.456 7.2 206.456 7.21 206.456 7.22 206.456 7.23 206.456 7.24 206.456 7.25 206.456 7.26 206.456 7.27 -220 7.28 -220 7.29 -220 7.3 -220 7.31 -220 7.32 -220 7.33 -220 7.34 -220 7.35 -220 7.36 -220 7.37 -220 7.38 -220 7.39 -220 7.4 -220 7.41 -263.141 7.42 -261.626 7.43 -264.666 7.44 -263.141 7.45 -263.141 7.46 -264.666 7.47 -263.141 7.48 -261.626 7.49 -261.626 7.5 -263.141 7.51 -257.131 7.52 -261.626 7.53 -261.626 7.54 -261.626 7.55 -258.621 7.56 -220 7.57 -220 7.58 -220 7.59 -220 7.6 -220 7.61 -220 7.62 -220 7.63 -220 7.64 323.965 7.65 311.127 7.66 311.127 7.67 311.127 7.68 311.127 7.69 311.127 7.7 311.127 7.71 311.127 7.72 312.929 7.73 311.127 7.74 311.127 7.75 311.127 7.76 311.127 7.77 312.929 7.78 311.127 7.79 311.127 7.8 312.929 7.81 311.127 7.82 311.127 7.83 311.127 7.84 311.127 7.85 312.929 7.86 311.127 7.87 311.127 7.88 341.252 7.89 347.217 7.9 347.217 7.91 347.217 7.92 349.228 7.93 347.217 7.94 349.228 7.95 349.228 7.96 347.217 7.97 349.228 7.98 347.217 7.99 347.217 8 349.228 8.01 345.217 8.02 349.228 8.03 349.228 8.04 347.217 8.05 347.217 8.06 349.228 8.07 345.217 8.08 349.228 8.09 347.217 8.1 347.217 8.11 349.228 8.12 347.217 8.13 349.228 8.14 347.217 8.15 347.217 8.16 351.251 8.17 337.332 8.18 345.217 8.19 -155.563 8.2 -155.563 8.21 -155.563 8.22 -159.2 8.23 -155.563 8.24 -154.668 8.25 -161.049 8.26 -156.465 8.27 -154.668 8.28 -155.563 8.29 -154.668 8.3 -156.465 8.31 -154.668 8.32 -174.614 8.33 -170.626 8.34 -173.608 8.35 -173.608 8.36 -220 8.37 -220 8.38 -220 8.39 -220 8.4 -220 8.41 -220 8.42 -220 8.43 206.456 8.44 205.267 8.45 202.91 8.46 204.085 8.47 205.267 8.48 205.267 8.49 205.267 8.5 204.085 8.51 202.91 8.52 204.085 8.53 206.456 8.54 207.652 8.55 206.456 8.56 205.267 8.57 206.456 8.58 206.456 8.59 206.456 8.6 205.267 8.61 205.267 8.62 207.652 8.63 207.652 8.64 204.085 8.65 202.91 8.66 202.91 8.67 205.267 8.68 207.652 8.69 -220 8.7 -220 8.71 -220 8.72 -220 8.73 -220 8.74 -220 8.75 -220 8.76 -220 8.77 -220 8.78 -220 8.79 -220 8.8 -220 8.81 -220 8.82 -220 8.83 -220 8.84 -220 8.85 -220 8.86 -220 8.87 -220 8.88 -220 8.89 -220 8.9 -220 8.91 193.746 8.92 194.869 8.93 194.869 8.94 195.998 8.95 194.869 8.96 194.869 8.97 195.998 8.98 195.998 8.99 194.869 9 193.746 9.01 193.746 9.02 194.869 9.03 194.869 9.04 195.998 9.05 194.869 9.06 194.869 9.07 194.869 9.08 194.869 9.09 194.869 9.1 195.998 9.11 194.869 9.12 194.869 9.13 195.998 9.14 195.998 9.15 195.998 9.16 195.998 9.17 195.998 9.18 195.998 9.19 195.998 9.2 197.133 9.21 195.998 9.22 197.133 9.23 198.275 9.24 198.275 9.25 199.424 9.26 204.085 9.27 -220 9.28 229.078 9.29 231.739 9.3 231.739 9.31 230.405 9.32 229.078 9.33 231.739 9.34 231.739 9.35 230.405 9.36 230.405 9.37 233.082 9.38 233.082 9.39 230.405 9.4 231.739 9.41 231.739 9.42 231.739 9.43 230.405 9.44 231.739 9.45 233.082 9.46 233.082 9.47 230.405 9.48 229.078 9.49 231.739 9.5 233.082 9.51 231.739 9.52 229.078 9.53 231.739 9.54 233.082 9.55 231.739 9.56 230.405 9.57 233.082 9.58 233.082 9.59 230.405 9.6 230.405 9.61 233.082 9.62 233.082 9.63 229.078 9.64 231.739 9.65 233.082 9.66 231.739 9.67 229.078 9.68 231.739 9.69 233.082 9.7 231.739 9.71 229.078 9.72 231.739 9.73 233.082 9.74 230.405 9.75 230.405 9.76 231.739 9.77 231.739 9.78 230.405 9.79 230.405 9.8 233.082 9.81 231.739 9.82 230.405 9.83 233.082 9.84 233.082 9.85 231.739 9.86 231.739 9.87 233.082 9.88 231.739 9.89 231.739 9.9 231.739 9.91 231.739 9.92 231.739 9.93 231.739 9.94 231.739 9.95 231.739 9.96 231.739 9.97 233.082 9.98 231.739 9.99 231.739 10 231.739 10.01 231.739 10.02 231.739 10.03 231.739 10.04 231.739 10.05 233.082 10.06 231.739 10.07 231.739 10.08 233.082 10.09 231.739 10.1 231.739 10.11 233.082 10.12 233.082 10.13 230.405 10.14 229.078 10.15 220 10.16 211.282 10.17 206.456 10.18 207.652 10.19 207.652 10.2 206.456 10.21 207.652 10.22 207.652 10.23 207.652 10.24 205.267 10.25 206.456 10.26 206.456 10.27 205.267 10.28 206.456 10.29 207.652 10.3 206.456 10.31 204.085 10.32 204.085 10.33 205.267 10.34 205.267 10.35 206.456 10.36 205.267 10.37 205.267 10.38 206.456 10.39 206.456 10.4 205.267 10.41 204.085 10.42 205.267 10.43 206.456 10.44 207.652 10.45 204.085 10.46 200.579 10.47 201.741 10.48 198.275 10.49 199.424 10.5 198.275 10.51 197.133 10.52 197.133 10.53 200.579 10.54 204.085 10.55 206.456 10.56 205.267 10.57 205.267 10.58 204.085 10.59 205.267 10.6 206.456 10.61 206.456 10.62 205.267 10.63 204.085 10.64 205.267 10.65 206.456 10.66 206.456 10.67 205.267 10.68 205.267 10.69 206.456 10.7 206.456 10.71 206.456 10.72 205.267 10.73 205.267 10.74 205.267 10.75 206.456 10.76 206.456 10.77 205.267 10.78 205.267 10.79 206.456 10.8 206.456 10.81 205.267 10.82 204.085 10.83 205.267 10.84 206.456 10.85 206.456 10.86 205.267 10.87 205.267 10.88 205.267 10.89 205.267 10.9 202.91 10.91 195.998 10.92 194.869 10.93 194.869 10.94 194.869 10.95 194.869 10.96 194.869 10.97 194.869 10.98 194.869 10.99 194.869 11 194.869 11.01 194.869 11.02 194.869 11.03 194.869 11.04 194.869 11.05 194.869 11.06 194.869 11.07 193.746 11.08 194.869 11.09 194.869 11.1 194.869 11.11 194.869 11.12 194.869 11.13 194.869 11.14 192.631 11.15 192.631 11.16 192.631 11.17 -220 11.18 -220 11.19 -220 11.2 -220 11.21 -220 11.22 -220 11.23 -220 11.24 -220 11.25 -220 11.26 -220 11.27 -220 11.28 -220 11.29 -220 11.3 -220 11.31 229.078 11.32 231.739 11.33 230.405 11.34 227.758 11.35 227.758 11.36 229.078 11.37 229.078 11.38 230.405 11.39 229.078 11.4 229.078 11.41 230.405 11.42 230.405 11.43 230.405 11.44 230.405 11.45 231.739 11.46 230.405 11.47 230.405 11.48 231.739 11.49 230.405 11.5 230.405 11.51 230.405 11.52 230.405 11.53 230.405 11.54 231.739 11.55 231.739 11.56 230.405 11.57 231.739 11.58 231.739 11.59 230.405 11.6 230.405 11.61 230.405 11.62 231.739 11.63 230.405 11.64 230.405 11.65 231.739 11.66 230.405 11.67 229.078 11.68 230.405 11.69 233.082 11.7 231.739 11.71 229.078 11.72 229.078 11.73 231.739 11.74 231.739 11.75 230.405 11.76 231.739 11.77 231.739 11.78 230.405 11.79 229.078 11.8 230.405 11.81 231.739 11.82 231.739 11.83 230.405 11.84 230.405 11.85 231.739 11.86 231.739 11.87 229.078 11.88 230.405 11.89 231.739 11.9 230.405 11.91 230.405 11.92 230.405 11.93 231.739 11.94 231.739 11.95 231.739 11.96 230.405 11.97 231.739 11.98 231.739 11.99 230.405 12 230.405 12.01 230.405 12.02 231.739 12.03 227.758 12.04 216.221 12.05 207.652 12.06 206.456 12.07 206.456 12.08 205.267 12.09 205.267 12.1 206.456 12.11 206.456 12.12 205.267 12.13 205.267 12.14 206.456 12.15 206.456 12.16 206.456 12.17 206.456 12.18 205.267 12.19 205.267 12.2 206.456 12.21 206.456 12.22 205.267 12.23 205.267 12.24 205.267 12.25 205.267 12.26 206.456 12.27 206.456 12.28 205.267 12.29 205.267 12.3 205.267 12.31 206.456 12.32 205.267 12.33 205.267 12.34 206.456 12.35 206.456 12.36 205.267 12.37 202.91 12.38 200.579 12.39 195.998 12.4 194.869 12.41 193.746 12.42 193.746 12.43 194.869 12.44 194.869 12.45 194.869 12.46 194.869 12.47 194.869 12.48 193.746 12.49 193.746 12.5 194.869 12.51 193.746 12.52 193.746 12.53 193.746 12.54 193.746 12.55 193.746 12.56 194.869 12.57 194.869 12.58 194.869 12.59 193.746 12.6 193.746 12.61 195.998 12.62 195.998 12.63 194.869 12.64 193.746 12.65 194.869 12.66 195.998 12.67 194.869 12.68 194.869 12.69 194.869 12.7 194.869 12.71 194.869 12.72 194.869 12.73 194.869 12.74 194.869 12.75 195.998 12.76 194.869 12.77 195.998 12.78 194.869 12.79 195.998 12.8 195.998 12.81 194.869 12.82 194.869 12.83 195.998 12.84 195.998 12.85 195.998 12.86 194.869 12.87 195.998 12.88 195.998 12.89 194.869 12.9 194.869 12.91 195.998 12.92 194.869 12.93 194.869 12.94 194.869 12.95 194.869 12.96 195.998 12.97 195.998 12.98 195.998 12.99 195.998 13 195.998 13.01 195.998 13.02 195.998 13.03 194.869 13.04 194.869 13.05 194.869 13.06 194.869 13.07 194.869 13.08 194.869 13.09 194.869 13.1 194.869 13.11 194.869 13.12 194.869 13.13 194.869 13.14 195.998 13.15 195.998 13.16 195.998 13.17 195.998 13.18 194.869 13.19 194.869 13.2 194.869 13.21 195.998 13.22 194.869 13.23 194.869 13.24 194.869 13.25 194.869 13.26 194.869 13.27 194.869 13.28 194.869 13.29 194.869 13.3 195.998 13.31 195.998 13.32 195.998 13.33 195.998 13.34 195.998 13.35 195.998 13.36 195.998 13.37 194.869 13.38 194.869 13.39 195.998 13.4 195.998 13.41 194.869 13.42 193.746 13.43 193.746 13.44 194.869 13.45 194.869 13.46 194.869 13.47 197.133 13.48 194.869 13.49 195.998 13.5 195.998 13.51 194.869 13.52 197.133 13.53 195.998 13.54 194.869 13.55 195.998 13.56 193.746 13.57 193.746 13.58 195.998 13.59 194.869 13.6 195.998 13.61 194.869 13.62 194.869 13.63 194.869 13.64 194.869 13.65 193.746 13.66 194.869 13.67 194.869 13.68 197.133 13.69 197.133 13.7 197.133 13.71 197.133 13.72 195.998 13.73 194.869 13.74 194.869 13.75 194.869 13.76 194.869 13.77 194.869 13.78 194.869 13.79 194.869 13.8 194.869 13.81 194.869 13.82 194.869 13.83 194.869 13.84 194.869 13.85 195.998 13.86 195.998 13.87 195.998 13.88 195.998 13.89 195.998 13.9 195.998 13.91 195.998 13.92 194.869 13.93 194.869 13.94 194.869 13.95 194.869 13.96 194.869 13.97 194.869 13.98 193.746 13.99 194.869 14 194.869 14.01 195.998 14.02 195.998 14.03 195.998 14.04 195.998 14.05 195.998 14.06 195.998 14.07 -220 14.08 -220 14.09 -220 14.1 -220 14.11 -220 14.12 -220 14.13 -220 14.14 -220 14.15 -220 14.16 -220 14.17 -220 14.18 -220 14.19 -220 14.2 -220 14.21 -220 14.22 -220 14.23 -220 14.24 -220 14.25 -220 14.26 -220 14.27 -220 14.28 -220 14.29 -220 14.3 -220 14.31 -220 14.32 -220 14.33 -220 14.34 -220 14.35 -220 14.36 -220 14.37 -220 14.38 -220 14.39 -220 14.4 -220 14.41 -220 14.42 -220 14.43 -220 14.44 -220 14.45 -220 14.46 -220 14.47 -145.146 14.48 -145.146 14.49 -146.832 14.5 -146.832 14.51 -146.832 14.52 -145.146 14.53 -145.146 14.54 -145.146 14.55 -145.987 14.56 -146.832 14.57 -146.832 14.58 -145.987 14.59 -220 14.6 -220 14.61 -220 14.62 -220 14.63 -220 14.64 -220 14.65 -220 14.66 -220 14.67 -220 14.68 -220 14.69 -220 14.7 -220 14.71 -220 14.72 -220 14.73 -210.065 14.74 -205.267 14.75 -204.085 14.76 -210.065 14.77 -210.065 14.78 -205.267 14.79 -206.456 14.8 -208.855 14.81 -206.456 14.82 -205.267 14.83 -205.267 14.84 -206.456 14.85 -210.065 14.86 -208.855 14.87 -206.456 14.88 -204.085 14.89 -220 14.9 -220 14.91 -220 14.92 -220 14.93 -220 14.94 -220 14.95 -220 14.96 -220 14.97 -220 14.98 -220 14.99 -220 15 -220 15.01 -220 15.02 -220 15.03 -220 15.04 -220 15.05 -220 15.06 -220 15.07 -220 15.08 -220 15.09 -220 15.1 -220 15.11 -220 15.12 -220 15.13 -220 15.14 -220 15.15 -220 15.16 -220 15.17 -220 15.18 -220 15.19 -220 15.2 -220 15.21 -220 15.22 -220 15.23 -220 15.24 -220 15.25 -220 15.26 -220 15.27 -220 15.28 -220 15.29 -220 15.3 -220 15.31 -220 15.32 -220 15.33 -220 15.34 -220 15.35 -220 15.36 -220 15.37 -220 15.38 -220 15.39 -220 15.4 -220 15.41 -220 15.42 -220 mir_eval-0.8.2/tests/data/melody/est03.txt000077500000000000000000000326561475740344600204170ustar00rootroot000000000000000 0 0.01 0 0.02 -220 0.03 258.621 0.04 261.626 0.05 260.119 0.06 260.119 0.07 260.119 0.08 260.119 0.09 258.621 0.1 258.621 0.11 260.119 0.12 261.626 0.13 260.119 0.14 261.626 0.15 261.626 0.16 260.119 0.17 260.119 0.18 261.626 0.19 261.626 0.2 261.626 0.21 261.626 0.22 260.119 0.23 260.119 0.24 261.626 0.25 263.141 0.26 263.141 0.27 261.626 0.28 261.626 0.29 263.141 0.3 267.741 0.31 295.366 0.32 309.335 0.33 309.335 0.34 309.335 0.35 309.335 0.36 309.335 0.37 309.335 0.38 309.335 0.39 309.335 0.4 309.335 0.41 309.335 0.42 311.127 0.43 309.335 0.44 307.553 0.45 307.553 0.46 309.335 0.47 311.127 0.48 307.553 0.49 305.782 0.5 311.127 0.51 314.742 0.52 311.127 0.53 -220 0.54 -220 0.55 -220 0.56 -220 0.57 -220 0.58 -220 0.59 -220 0.6 254.178 0.61 260.119 0.62 261.626 0.63 260.119 0.64 258.621 0.65 260.119 0.66 261.626 0.67 263.141 0.68 261.626 0.69 260.119 0.7 261.626 0.71 260.119 0.72 261.626 0.73 263.141 0.74 263.141 0.75 261.626 0.76 261.626 0.77 260.119 0.78 261.626 0.79 263.141 0.8 264.666 0.81 263.141 0.82 260.119 0.83 260.119 0.84 260.119 0.85 261.626 0.86 264.666 0.87 278.788 0.88 -220 0.89 307.553 0.9 307.553 0.91 307.553 0.92 309.335 0.93 305.782 0.94 307.553 0.95 309.335 0.96 307.553 0.97 307.553 0.98 309.335 0.99 307.553 1 305.782 1.01 309.335 1.02 311.127 1.03 -220 1.04 -220 1.05 -220 1.06 -220 1.07 -220 1.08 -220 1.09 -220 1.1 -220 1.11 -220 1.12 -220 1.13 -167.695 1.14 -171.614 1.15 -173.608 1.16 173.608 1.17 172.609 1.18 172.609 1.19 172.609 1.2 173.608 1.21 173.608 1.22 174.614 1.23 173.608 1.24 173.608 1.25 174.614 1.26 174.614 1.27 173.608 1.28 173.608 1.29 175.626 1.3 175.626 1.31 176.643 1.32 175.626 1.33 175.626 1.34 173.608 1.35 174.614 1.36 173.608 1.37 174.614 1.38 173.608 1.39 172.609 1.4 173.608 1.41 -145.987 1.42 -147.683 1.43 -147.683 1.44 -146.832 1.45 -147.683 1.46 -148.538 1.47 -146.832 1.48 -147.683 1.49 -146.832 1.5 -147.683 1.51 -146.832 1.52 -146.832 1.53 -147.683 1.54 -146.832 1.55 -146.832 1.56 -146.832 1.57 -147.683 1.58 -146.832 1.59 -146.832 1.6 -146.832 1.61 -147.683 1.62 -147.683 1.63 -146.832 1.64 -146.832 1.65 -147.683 1.66 -147.683 1.67 -148.538 1.68 -147.683 1.69 -146.832 1.7 -148.538 1.71 -149.399 1.72 -147.683 1.73 -220 1.74 -220 1.75 -220 1.76 -220 1.77 -220 1.78 -220 1.79 -220 1.8 -220 1.81 -220 1.82 -220 1.83 -220 1.84 -220 1.85 -220 1.86 -220 1.87 -220 1.88 -220 1.89 -220 1.9 -220 1.91 -220 1.92 -220 1.93 -220 1.94 -220 1.95 -220 1.96 -220 1.97 172.609 1.98 173.608 1.99 172.609 2 174.614 2.01 174.614 2.02 174.614 2.03 173.608 2.04 174.614 2.05 174.614 2.06 173.608 2.07 173.608 2.08 174.614 2.09 174.614 2.1 173.608 2.11 172.609 2.12 174.614 2.13 173.608 2.14 174.614 2.15 174.614 2.16 174.614 2.17 173.608 2.18 172.609 2.19 175.626 2.2 174.614 2.21 174.614 2.22 173.608 2.23 174.614 2.24 172.609 2.25 174.614 2.26 174.614 2.27 175.626 2.28 171.614 2.29 174.614 2.3 173.608 2.31 174.614 2.32 174.614 2.33 172.609 2.34 173.608 2.35 173.608 2.36 174.614 2.37 174.614 2.38 175.626 2.39 174.614 2.4 173.608 2.41 175.626 2.42 175.626 2.43 174.614 2.44 173.608 2.45 173.608 2.46 173.608 2.47 172.609 2.48 173.608 2.49 174.614 2.5 172.609 2.51 172.609 2.52 174.614 2.53 174.614 2.54 171.614 2.55 174.614 2.56 175.626 2.57 174.614 2.58 173.608 2.59 173.608 2.6 175.626 2.61 173.608 2.62 172.609 2.63 173.608 2.64 174.614 2.65 172.609 2.66 173.608 2.67 174.614 2.68 173.608 2.69 172.609 2.7 174.614 2.71 174.614 2.72 172.609 2.73 173.608 2.74 175.626 2.75 175.626 2.76 173.608 2.77 174.614 2.78 174.614 2.79 172.609 2.8 179.731 2.81 178.696 2.82 178.696 2.83 177.666 2.84 177.666 2.85 177.666 2.86 176.643 2.87 175.626 2.88 174.614 2.89 175.626 2.9 175.626 2.91 175.626 2.92 175.626 2.93 176.643 2.94 175.626 2.95 174.614 2.96 174.614 2.97 174.614 2.98 173.608 2.99 173.608 3 174.614 3.01 174.614 3.02 174.614 3.03 175.626 3.04 175.626 3.05 173.608 3.06 173.608 3.07 175.626 3.08 174.614 3.09 173.608 3.1 173.608 3.11 174.614 3.12 174.614 3.13 175.626 3.14 175.626 3.15 175.626 3.16 173.608 3.17 173.608 3.18 174.614 3.19 174.614 3.2 173.608 3.21 174.614 3.22 175.626 3.23 174.614 3.24 174.614 3.25 173.608 3.26 174.614 3.27 174.614 3.28 174.614 3.29 173.608 3.3 173.608 3.31 173.608 3.32 176.643 3.33 175.626 3.34 173.608 3.35 174.614 3.36 173.608 3.37 174.614 3.38 174.614 3.39 173.608 3.4 174.614 3.41 174.614 3.42 174.614 3.43 174.614 3.44 174.614 3.45 174.614 3.46 174.614 3.47 175.626 3.48 174.614 3.49 173.608 3.5 173.608 3.51 174.614 3.52 176.643 3.53 174.614 3.54 173.608 3.55 173.608 3.56 174.614 3.57 175.626 3.58 175.626 3.59 175.626 3.6 174.614 3.61 173.608 3.62 175.626 3.63 174.614 3.64 175.626 3.65 174.614 3.66 -143.479 3.67 -150.264 3.68 -149.399 3.69 -145.146 3.7 -146.832 3.71 -153.777 3.72 -146.832 3.73 -144.31 3.74 -149.399 3.75 -152.01 3.76 -145.987 3.77 -145.146 3.78 -152.891 3.79 -148.538 3.8 -145.146 3.81 -148.538 3.82 -153.777 3.83 -147.683 3.84 -145.146 3.85 -148.538 3.86 -155.563 3.87 -152.01 3.88 -147.683 3.89 -147.683 3.9 -220 3.91 -220 3.92 -220 3.93 -220 3.94 -220 3.95 -220 3.96 -220 3.97 -220 3.98 -220 3.99 -220 4 -220 4.01 -220 4.02 -220 4.03 -220 4.04 -220 4.05 -220 4.06 -220 4.07 -220 4.08 -220 4.09 -220 4.1 -220 4.11 -220 4.12 -220 4.13 -220 4.14 -220 4.15 -175.626 4.16 -175.626 4.17 -175.626 4.18 -175.626 4.19 263.141 4.2 263.141 4.21 260.119 4.22 261.626 4.23 261.626 4.24 266.199 4.25 264.666 4.26 261.626 4.27 261.626 4.28 263.141 4.29 261.626 4.3 260.119 4.31 263.141 4.32 261.626 4.33 261.626 4.34 266.199 4.35 261.626 4.36 260.119 4.37 269.292 4.38 264.666 4.39 261.626 4.4 257.131 4.41 258.621 4.42 258.621 4.43 258.621 4.44 258.621 4.45 258.621 4.46 260.119 4.47 260.119 4.48 258.621 4.49 260.119 4.5 260.119 4.51 260.119 4.52 260.119 4.53 260.119 4.54 260.119 4.55 260.119 4.56 261.626 4.57 260.119 4.58 260.119 4.59 261.626 4.6 261.626 4.61 260.119 4.62 261.626 4.63 261.626 4.64 263.141 4.65 273.999 4.66 307.553 4.67 309.335 4.68 309.335 4.69 309.335 4.7 307.553 4.71 309.335 4.72 311.127 4.73 311.127 4.74 309.335 4.75 307.553 4.76 309.335 4.77 311.127 4.78 311.127 4.79 309.335 4.8 309.335 4.81 311.127 4.82 309.335 4.83 307.553 4.84 305.782 4.85 302.27 4.86 -220 4.87 -220 4.88 -220 4.89 -220 4.9 -220 4.91 -220 4.92 -220 4.93 -220 4.94 -220 4.95 -220 4.96 261.626 4.97 263.141 4.98 261.626 4.99 260.119 5 258.621 5.01 260.119 5.02 261.626 5.03 261.626 5.04 261.626 5.05 260.119 5.06 261.626 5.07 261.626 5.08 261.626 5.09 261.626 5.1 261.626 5.11 261.626 5.12 261.626 5.13 261.626 5.14 261.626 5.15 261.626 5.16 261.626 5.17 261.626 5.18 261.626 5.19 261.626 5.2 261.626 5.21 263.141 5.22 275.586 5.23 302.27 5.24 307.553 5.25 309.335 5.26 307.553 5.27 309.335 5.28 309.335 5.29 307.553 5.3 307.553 5.31 309.335 5.32 309.335 5.33 309.335 5.34 307.553 5.35 307.553 5.36 309.335 5.37 307.553 5.38 305.782 5.39 305.782 5.4 307.553 5.41 309.335 5.42 307.553 5.43 -220 5.44 -220 5.45 -220 5.46 -220 5.47 -220 5.48 -220 5.49 -220 5.5 -168.666 5.51 -170.626 5.52 -172.609 5.53 -173.608 5.54 -172.609 5.55 -172.609 5.56 -172.609 5.57 -173.608 5.58 -173.608 5.59 -173.608 5.6 -172.609 5.61 -173.608 5.62 -173.608 5.63 -173.608 5.64 -173.608 5.65 -173.608 5.66 -174.614 5.67 -173.608 5.68 -175.626 5.69 -173.608 5.7 -173.608 5.71 -172.609 5.72 -172.609 5.73 -173.608 5.74 -173.608 5.75 -172.609 5.76 -174.614 5.77 -174.614 5.78 -174.614 5.79 -173.608 5.8 -174.614 5.81 -174.614 5.82 -174.614 5.83 -173.608 5.84 -173.608 5.85 -173.608 5.86 -147.683 5.87 -147.683 5.88 -146.832 5.89 -147.683 5.9 -146.832 5.91 -146.832 5.92 -145.987 5.93 -146.832 5.94 -148.538 5.95 -146.832 5.96 -146.832 5.97 -148.538 5.98 -145.146 5.99 -146.832 6 -147.683 6.01 -145.987 6.02 -145.146 6.03 -146.832 6.04 -145.987 6.05 -144.31 6.06 -147.683 6.07 -148.538 6.08 -148.538 6.09 -146.832 6.1 -220 6.11 -220 6.12 -220 6.13 -220 6.14 -220 6.15 -220 6.16 -220 6.17 -220 6.18 -220 6.19 -220 6.2 -220 6.21 -220 6.22 -220 6.23 -220 6.24 -220 6.25 -220 6.26 -220 6.27 -220 6.28 -220 6.29 -220 6.3 -220 6.31 -220 6.32 -220 6.33 -167.695 6.34 172.609 6.35 173.608 6.36 173.608 6.37 173.608 6.38 173.608 6.39 174.614 6.4 173.608 6.41 173.608 6.42 174.614 6.43 174.614 6.44 172.609 6.45 173.608 6.46 174.614 6.47 174.614 6.48 171.614 6.49 170.626 6.5 173.608 6.51 174.614 6.52 174.614 6.53 174.614 6.54 173.608 6.55 171.614 6.56 173.608 6.57 175.626 6.58 175.626 6.59 171.614 6.6 171.614 6.61 175.626 6.62 175.626 6.63 173.608 6.64 172.609 6.65 174.614 6.66 173.608 6.67 171.614 6.68 173.608 6.69 174.614 6.7 173.608 6.71 173.608 6.72 175.626 6.73 174.614 6.74 172.609 6.75 174.614 6.76 175.626 6.77 175.626 6.78 171.614 6.79 173.608 6.8 175.626 6.81 174.614 6.82 172.609 6.83 173.608 6.84 174.614 6.85 172.609 6.86 173.608 6.87 174.614 6.88 174.614 6.89 171.614 6.9 172.609 6.91 175.626 6.92 173.608 6.93 173.608 6.94 175.626 6.95 174.614 6.96 171.614 6.97 172.609 6.98 175.626 6.99 174.614 7 172.609 7.01 173.608 7.02 174.614 7.03 174.614 7.04 173.608 7.05 174.614 7.06 173.608 7.07 173.608 7.08 173.608 7.09 174.614 7.1 173.608 7.11 172.609 7.12 174.614 7.13 174.614 7.14 173.608 7.15 174.614 7.16 177.666 7.17 177.666 7.18 178.696 7.19 173.608 7.2 173.608 7.21 173.608 7.22 174.614 7.23 175.626 7.24 176.643 7.25 176.643 7.26 175.626 7.27 176.643 7.28 175.626 7.29 173.608 7.3 173.608 7.31 173.608 7.32 173.608 7.33 174.614 7.34 175.626 7.35 175.626 7.36 175.626 7.37 175.626 7.38 174.614 7.39 173.608 7.4 173.608 7.41 174.614 7.42 175.626 7.43 174.614 7.44 174.614 7.45 175.626 7.46 175.626 7.47 175.626 7.48 174.614 7.49 173.608 7.5 173.608 7.51 174.614 7.52 174.614 7.53 174.614 7.54 174.614 7.55 174.614 7.56 174.614 7.57 175.626 7.58 174.614 7.59 174.614 7.6 174.614 7.61 174.614 7.62 174.614 7.63 174.614 7.64 173.608 7.65 174.614 7.66 175.626 7.67 171.614 7.68 174.614 7.69 175.626 7.7 174.614 7.71 173.608 7.72 173.608 7.73 174.614 7.74 176.643 7.75 172.609 7.76 173.608 7.77 173.608 7.78 174.614 7.79 175.626 7.8 174.614 7.81 174.614 7.82 173.608 7.83 174.614 7.84 174.614 7.85 175.626 7.86 174.614 7.87 174.614 7.88 174.614 7.89 176.643 7.9 174.614 7.91 174.614 7.92 174.614 7.93 176.643 7.94 175.626 7.95 175.626 7.96 174.614 7.97 174.614 7.98 177.666 7.99 176.643 8 175.626 8.01 172.609 8.02 173.608 8.03 177.666 8.04 173.608 8.05 176.643 8.06 173.608 8.07 174.614 8.08 174.614 8.09 172.609 8.1 176.643 8.11 173.608 8.12 172.609 8.13 175.626 8.14 177.666 8.15 173.608 8.16 173.608 8.17 175.626 8.18 176.643 8.19 173.608 8.2 172.609 8.21 174.614 8.22 173.608 8.23 173.608 8.24 173.608 8.25 173.608 8.26 174.614 8.27 175.626 8.28 175.626 8.29 175.626 8.3 173.608 8.31 174.614 8.32 175.626 8.33 175.626 8.34 174.614 8.35 173.608 8.36 174.614 8.37 175.626 8.38 175.626 8.39 174.614 8.4 174.614 8.41 175.626 8.42 175.626 8.43 175.626 8.44 175.626 8.45 174.614 8.46 175.626 8.47 174.614 8.48 170.626 8.49 -220 8.5 -220 8.51 -220 8.52 -220 8.53 -220 8.54 -173.608 8.55 -175.626 8.56 -176.643 8.57 -175.626 8.58 -173.608 8.59 -173.608 8.6 -175.626 8.61 -174.614 8.62 -176.643 8.63 -174.614 8.64 -172.609 8.65 -174.614 8.66 -173.608 8.67 -174.614 8.68 -173.608 8.69 -173.608 8.7 -176.643 8.71 -173.608 8.72 -174.614 8.73 -174.614 8.74 -172.609 8.75 -174.614 8.76 -175.626 8.77 -173.608 8.78 -173.608 8.79 -174.614 8.8 -175.626 8.81 -175.626 8.82 -176.643 8.83 -168.666 8.84 -170.626 8.85 -172.609 8.86 -174.614 8.87 -173.608 8.88 -173.608 8.89 -170.626 8.9 -172.609 8.91 -147.683 8.92 -147.683 8.93 -146.832 8.94 -146.832 8.95 -146.832 8.96 -147.683 8.97 -147.683 8.98 -148.538 8.99 -147.683 9 -146.832 9.01 -145.987 9.02 -145.987 9.03 -146.832 9.04 -147.683 9.05 -145.987 9.06 -147.683 9.07 -156.465 9.08 -166.729 9.09 -257.131 9.1 -258.621 9.11 -260.119 9.12 -264.666 9.13 -244.105 9.14 -239.912 9.15 -257.131 9.16 -264.666 9.17 -260.119 9.18 -260.119 9.19 -254.178 9.2 -266.199 9.21 -264.666 9.22 -263.141 9.23 -261.626 9.24 -266.199 9.25 -267.741 9.26 -263.141 9.27 -260.119 9.28 -260.119 9.29 -270.852 9.3 351.251 9.31 347.217 9.32 349.228 9.33 351.251 9.34 351.251 9.35 351.251 9.36 349.228 9.37 351.251 9.38 355.333 9.39 353.286 9.4 351.251 9.41 351.251 9.42 351.251 9.43 351.251 9.44 351.251 9.45 351.251 9.46 351.251 9.47 353.286 9.48 353.286 9.49 351.251 9.5 351.251 9.51 353.286 9.52 353.286 9.53 353.286 9.54 353.286 9.55 353.286 9.56 353.286 9.57 353.286 9.58 355.333 9.59 355.333 9.6 353.286 9.61 349.228 9.62 351.251 9.63 351.251 9.64 351.251 9.65 351.251 9.66 351.251 9.67 351.251 9.68 351.251 9.69 351.251 9.7 351.251 9.71 351.251 9.72 351.251 9.73 353.286 9.74 353.286 9.75 353.286 9.76 353.286 9.77 355.333 9.78 355.333 9.79 355.333 9.8 357.391 9.81 357.391 9.82 -220 9.83 -220 9.84 -220 9.85 -220 9.86 -220 9.87 -220 9.88 -179.731 9.89 -176.643 9.9 -171.614 9.91 -172.609 9.92 -173.608 9.93 -174.614 9.94 -171.614 9.95 -176.643 9.96 -174.614 9.97 -173.608 9.98 -220 9.99 -220 10 -220 10.01 -220 10.02 -220 mir_eval-0.8.2/tests/data/melody/est04.txt000077500000000000000000000651461475740344600204200ustar00rootroot000000000000000 0 0.01 0 0.02 233.082 0.03 225.142 0.04 231.739 0.05 349.228 0.06 347.217 0.07 347.217 0.08 349.228 0.09 349.228 0.1 349.228 0.11 347.217 0.12 347.217 0.13 347.217 0.14 347.217 0.15 347.217 0.16 345.217 0.17 351.251 0.18 349.228 0.19 349.228 0.2 347.217 0.21 347.217 0.22 349.228 0.23 347.217 0.24 347.217 0.25 349.228 0.26 349.228 0.27 349.228 0.28 349.228 0.29 349.228 0.3 349.228 0.31 349.228 0.32 349.228 0.33 349.228 0.34 351.251 0.35 349.228 0.36 343.229 0.37 349.228 0.38 349.228 0.39 345.217 0.4 349.228 0.41 349.228 0.42 349.228 0.43 349.228 0.44 351.251 0.45 351.251 0.46 351.251 0.47 349.228 0.48 351.251 0.49 349.228 0.5 349.228 0.51 349.228 0.52 347.217 0.53 349.228 0.54 -463.479 0.55 -468.864 0.56 -466.164 0.57 -463.479 0.58 -463.479 0.59 -463.479 0.6 -466.164 0.61 -460.809 0.62 -468.864 0.63 -463.479 0.64 -460.809 0.65 -463.479 0.66 -460.809 0.67 523.251 0.68 523.251 0.69 520.237 0.7 520.237 0.71 520.237 0.72 520.237 0.73 520.237 0.74 520.237 0.75 520.237 0.76 517.241 0.77 517.241 0.78 517.241 0.79 520.237 0.8 520.237 0.81 520.237 0.82 520.237 0.83 520.237 0.84 520.237 0.85 -440 0.86 -440 0.87 -440 0.88 -440 0.89 -440 0.9 -440 0.91 -440 0.92 -440 0.93 -440 0.94 231.739 0.95 233.082 0.96 229.078 0.97 231.739 0.98 231.739 0.99 233.082 1 231.739 1.01 230.405 1.02 230.405 1.03 231.739 1.04 231.739 1.05 230.405 1.06 233.082 1.07 233.082 1.08 231.739 1.09 -460.809 1.1 349.228 1.11 347.217 1.12 347.217 1.13 347.217 1.14 347.217 1.15 349.228 1.16 347.217 1.17 349.228 1.18 347.217 1.19 347.217 1.2 347.217 1.21 347.217 1.22 347.217 1.23 347.217 1.24 343.229 1.25 349.228 1.26 349.228 1.27 345.217 1.28 347.217 1.29 349.228 1.3 347.217 1.31 349.228 1.32 349.228 1.33 349.228 1.34 349.228 1.35 349.228 1.36 349.228 1.37 349.228 1.38 349.228 1.39 351.251 1.4 351.251 1.41 347.217 1.42 349.228 1.43 349.228 1.44 -468.864 1.45 -460.809 1.46 -463.479 1.47 -466.164 1.48 -468.864 1.49 -460.809 1.5 -463.479 1.51 -466.164 1.52 -466.164 1.53 -468.864 1.54 -463.479 1.55 -463.479 1.56 -458.155 1.57 -463.479 1.58 -466.164 1.59 -463.479 1.6 -466.164 1.61 -463.479 1.62 -466.164 1.63 -463.479 1.64 -460.809 1.65 -463.479 1.66 -460.809 1.67 -463.479 1.68 -466.164 1.69 -471.58 1.7 -463.479 1.71 -463.479 1.72 349.228 1.73 347.217 1.74 347.217 1.75 349.228 1.76 349.228 1.77 349.228 1.78 349.228 1.79 349.228 1.8 349.228 1.81 349.228 1.82 351.251 1.83 347.217 1.84 347.217 1.85 347.217 1.86 347.217 1.87 347.217 1.88 351.251 1.89 347.217 1.9 349.228 1.91 349.228 1.92 349.228 1.93 349.228 1.94 349.228 1.95 349.228 1.96 349.228 1.97 347.217 1.98 351.251 1.99 347.217 2 347.217 2.01 347.217 2.02 347.217 2.03 347.217 2.04 349.228 2.05 349.228 2.06 347.217 2.07 347.217 2.08 347.217 2.09 347.217 2.1 347.217 2.11 347.217 2.12 347.217 2.13 347.217 2.14 -482.603 2.15 -463.479 2.16 -458.155 2.17 -471.58 2.18 -471.58 2.19 -463.479 2.2 -460.809 2.21 -466.164 2.22 -466.164 2.23 -466.164 2.24 -463.479 2.25 -463.479 2.26 -463.479 2.27 -463.479 2.28 -479.823 2.29 -440 2.3 -440 2.31 -440 2.32 -440 2.33 -440 2.34 -440 2.35 -440 2.36 -440 2.37 -440 2.38 -440 2.39 -440 2.4 -440 2.41 -440 2.42 -440 2.43 -440 2.44 -440 2.45 -440 2.46 -615.107 2.47 -618.67 2.48 -622.254 2.49 -618.67 2.5 -618.67 2.51 -618.67 2.52 -611.564 2.53 -611.564 2.54 -615.107 2.55 -622.254 2.56 -618.67 2.57 -618.67 2.58 -611.564 2.59 -615.107 2.6 -622.254 2.61 -615.107 2.62 -615.107 2.63 -618.67 2.64 -618.67 2.65 -618.67 2.66 -611.564 2.67 -615.107 2.68 -618.67 2.69 -618.67 2.7 -615.107 2.71 -615.107 2.72 -618.67 2.73 -618.67 2.74 -618.67 2.75 -618.67 2.76 -618.67 2.77 -618.67 2.78 -622.254 2.79 -618.67 2.8 -618.67 2.81 -622.254 2.82 -622.254 2.83 -615.107 2.84 -618.67 2.85 -618.67 2.86 -618.67 2.87 -611.564 2.88 -594.154 2.89 -611.564 2.9 394.266 2.91 389.738 2.92 389.738 2.93 391.995 2.94 391.995 2.95 391.995 2.96 391.995 2.97 389.738 2.98 389.738 2.99 389.738 3 389.738 3.01 389.738 3.02 389.738 3.03 389.738 3.04 391.995 3.05 387.493 3.06 583.947 3.07 587.33 3.08 587.33 3.09 583.947 3.1 583.947 3.11 583.947 3.12 580.583 3.13 583.947 3.14 583.947 3.15 583.947 3.16 580.583 3.17 580.583 3.18 583.947 3.19 583.947 3.2 583.947 3.21 583.947 3.22 583.947 3.23 520.237 3.24 520.237 3.25 520.237 3.26 520.237 3.27 520.237 3.28 517.241 3.29 520.237 3.3 520.237 3.31 520.237 3.32 517.241 3.33 517.241 3.34 520.237 3.35 520.237 3.36 520.237 3.37 520.237 3.38 466.164 3.39 466.164 3.4 466.164 3.41 466.164 3.42 466.164 3.43 463.479 3.44 463.479 3.45 466.164 3.46 463.479 3.47 463.479 3.48 463.479 3.49 466.164 3.5 466.164 3.51 466.164 3.52 466.164 3.53 466.164 3.54 -463.479 3.55 -466.164 3.56 -466.164 3.57 -463.479 3.58 -466.164 3.59 -463.479 3.6 -440 3.61 -440 3.62 -440 3.63 -440 3.64 -440 3.65 -440 3.66 -440 3.67 -625.859 3.68 -622.254 3.69 -611.564 3.7 -611.564 3.71 -622.254 3.72 -618.67 3.73 -611.564 3.74 -615.107 3.75 -618.67 3.76 -622.254 3.77 -618.67 3.78 -611.564 3.79 -615.107 3.8 -615.107 3.81 -622.254 3.82 -618.67 3.83 -618.67 3.84 -618.67 3.85 -618.67 3.86 -618.67 3.87 -618.67 3.88 -618.67 3.89 -622.254 3.9 -618.67 3.91 -618.67 3.92 -618.67 3.93 -622.254 3.94 -618.67 3.95 -611.564 3.96 -615.107 3.97 -618.67 3.98 -625.859 3.99 -625.859 4 -618.67 4.01 -618.67 4.02 -880 4.03 -880 4.04 -880 4.05 -880 4.06 -880 4.07 -880 4.08 -880 4.09 -880 4.1 -880 4.11 -880 4.12 -880 4.13 -880 4.14 -880 4.15 -880 4.16 -880 4.17 -880 4.18 -880 4.19 -880 4.2 -880 4.21 -880 4.22 -880 4.23 -880 4.24 -880 4.25 -880 4.26 -880 4.27 -880 4.28 -880 4.29 -880 4.3 -880 4.31 -880 4.32 -880 4.33 -880 4.34 -880 4.35 -880 4.36 -880 4.37 -880 4.38 -880 4.39 -880 4.4 -880 4.41 -880 4.42 -880 4.43 -880 4.44 -880 4.45 -880 4.46 -880 4.47 -880 4.48 -880 4.49 -880 4.5 -880 4.51 -880 4.52 -880 4.53 -880 4.54 880 4.55 874.932 4.56 874.932 4.57 874.932 4.58 880 4.59 874.932 4.6 874.932 4.61 880 4.62 880 4.63 880 4.64 -926.958 4.65 -890.225 4.66 -916.311 4.67 -921.619 4.68 -905.786 4.69 -921.619 4.7 926.958 4.71 926.958 4.72 926.958 4.73 926.958 4.74 926.958 4.75 926.958 4.76 932.328 4.77 932.328 4.78 932.328 4.79 932.328 4.8 932.328 4.81 932.328 4.82 926.958 4.83 926.958 4.84 937.728 4.85 921.619 4.86 926.958 4.87 932.328 4.88 926.958 4.89 926.958 4.9 926.958 4.91 932.328 4.92 926.958 4.93 932.328 4.94 932.328 4.95 932.328 4.96 932.328 4.97 932.328 4.98 932.328 4.99 932.328 5 932.328 5.01 926.958 5.02 932.328 5.03 926.958 5.04 926.958 5.05 932.328 5.06 932.328 5.07 926.958 5.08 932.328 5.09 932.328 5.1 932.328 5.11 932.328 5.12 932.328 5.13 932.328 5.14 932.328 5.15 -926.958 5.16 698.456 5.17 694.434 5.18 694.434 5.19 694.434 5.2 690.434 5.21 694.434 5.22 694.434 5.23 690.434 5.24 690.434 5.25 694.434 5.26 694.434 5.27 694.434 5.28 694.434 5.29 702.503 5.3 698.456 5.31 698.456 5.32 694.434 5.33 698.456 5.34 694.434 5.35 694.434 5.36 694.434 5.37 694.434 5.38 694.434 5.39 694.434 5.4 694.434 5.41 694.434 5.42 694.434 5.43 694.434 5.44 686.457 5.45 694.434 5.46 698.456 5.47 690.434 5.48 694.434 5.49 -926.958 5.5 -926.958 5.51 -926.958 5.52 -932.328 5.53 -932.328 5.54 -926.958 5.55 -926.958 5.56 -921.619 5.57 -926.958 5.58 -932.328 5.59 -926.958 5.6 -921.619 5.61 -880 5.62 -880 5.63 -880 5.64 -880 5.65 -880 5.66 -880 5.67 -880 5.68 -880 5.69 -880 5.7 -880 5.71 -880 5.72 -880 5.73 -880 5.74 -880 5.75 -880 5.76 -880 5.77 -880 5.78 -880 5.79 -880 5.8 -880 5.81 -880 5.82 -880 5.83 -880 5.84 -880 5.85 -880 5.86 -880 5.87 -880 5.88 -880 5.89 625.859 5.9 618.67 5.91 622.254 5.92 618.67 5.93 618.67 5.94 615.107 5.95 615.107 5.96 618.67 5.97 618.67 5.98 618.67 5.99 615.107 6 615.107 6.01 618.67 6.02 622.254 6.03 618.67 6.04 -880 6.05 -880 6.06 -880 6.07 694.434 6.08 698.456 6.09 694.434 6.1 694.434 6.11 694.434 6.12 694.434 6.13 694.434 6.14 690.434 6.15 694.434 6.16 694.434 6.17 694.434 6.18 694.434 6.19 702.503 6.2 702.503 6.21 694.434 6.22 690.434 6.23 698.456 6.24 698.456 6.25 694.434 6.26 690.434 6.27 694.434 6.28 694.434 6.29 694.434 6.3 694.434 6.31 694.434 6.32 694.434 6.33 698.456 6.34 779.475 6.35 779.475 6.36 779.475 6.37 779.475 6.38 783.991 6.39 779.475 6.4 783.991 6.41 783.991 6.42 783.991 6.43 783.991 6.44 783.991 6.45 779.475 6.46 783.991 6.47 783.991 6.48 779.475 6.49 783.991 6.5 783.991 6.51 783.991 6.52 783.991 6.53 788.532 6.54 783.991 6.55 783.991 6.56 779.475 6.57 783.991 6.58 783.991 6.59 783.991 6.6 783.991 6.61 783.991 6.62 783.991 6.63 779.475 6.64 774.986 6.65 793.1 6.66 622.254 6.67 622.254 6.68 618.67 6.69 618.67 6.7 618.67 6.71 615.107 6.72 618.67 6.73 618.67 6.74 618.67 6.75 615.107 6.76 615.107 6.77 618.67 6.78 622.254 6.79 618.67 6.8 622.254 6.81 618.67 6.82 618.67 6.83 618.67 6.84 618.67 6.85 622.254 6.86 618.67 6.87 618.67 6.88 618.67 6.89 622.254 6.9 618.67 6.91 618.67 6.92 618.67 6.93 615.107 6.94 615.107 6.95 618.67 6.96 601.058 6.97 583.947 6.98 583.947 6.99 583.947 7 583.947 7.01 583.947 7.02 583.947 7.03 583.947 7.04 580.583 7.05 580.583 7.06 580.583 7.07 583.947 7.08 583.947 7.09 583.947 7.1 583.947 7.11 583.947 7.12 583.947 7.13 583.947 7.14 583.947 7.15 583.947 7.16 583.947 7.17 587.33 7.18 583.947 7.19 583.947 7.2 583.947 7.21 583.947 7.22 583.947 7.23 583.947 7.24 583.947 7.25 -580.583 7.26 -590.732 7.27 -611.564 7.28 -622.254 7.29 618.67 7.3 618.67 7.31 615.107 7.32 618.67 7.33 618.67 7.34 618.67 7.35 615.107 7.36 615.107 7.37 618.67 7.38 618.67 7.39 618.67 7.4 618.67 7.41 622.254 7.42 622.254 7.43 618.67 7.44 618.67 7.45 618.67 7.46 625.859 7.47 618.67 7.48 618.67 7.49 622.254 7.5 618.67 7.51 618.67 7.52 618.67 7.53 622.254 7.54 618.67 7.55 622.254 7.56 618.67 7.57 622.254 7.58 611.564 7.59 618.67 7.6 618.67 7.61 618.67 7.62 618.67 7.63 618.67 7.64 618.67 7.65 618.67 7.66 618.67 7.67 618.67 7.68 622.254 7.69 622.254 7.7 622.254 7.71 622.254 7.72 618.67 7.73 622.254 7.74 622.254 7.75 618.67 7.76 618.67 7.77 622.254 7.78 618.67 7.79 615.107 7.8 618.67 7.81 618.67 7.82 618.67 7.83 618.67 7.84 625.859 7.85 706.572 7.86 698.456 7.87 694.434 7.88 698.456 7.89 694.434 7.9 690.434 7.91 694.434 7.92 694.434 7.93 694.434 7.94 690.434 7.95 690.434 7.96 694.434 7.97 694.434 7.98 694.434 7.99 694.434 8 698.456 8.01 694.434 8.02 -880 8.03 -880 8.04 -880 8.05 -880 8.06 -880 8.07 -880 8.08 -880 8.09 -880 8.1 -880 8.11 -880 8.12 -880 8.13 -880 8.14 -523.251 8.15 -523.251 8.16 -523.251 8.17 -517.241 8.18 -517.241 8.19 -520.237 8.2 -520.237 8.21 -514.262 8.22 -514.262 8.23 -520.237 8.24 -517.241 8.25 -514.262 8.26 -517.241 8.27 -520.237 8.28 -520.237 8.29 -514.262 8.3 -520.237 8.31 -523.251 8.32 -517.241 8.33 -517.241 8.34 -517.241 8.35 -520.237 8.36 -517.241 8.37 -520.237 8.38 -523.251 8.39 -520.237 8.4 -520.237 8.41 -520.237 8.42 -523.251 8.43 -502.516 8.44 -710.665 8.45 -694.434 8.46 -655.458 8.47 -647.93 8.48 -663.074 8.49 -678.573 8.5 -686.457 8.51 -682.504 8.52 -686.457 8.53 -698.456 8.54 -702.503 8.55 -694.434 8.56 -690.434 8.57 -690.434 8.58 -694.434 8.59 -698.456 8.6 -698.456 8.61 -694.434 8.62 -690.434 8.63 -694.434 8.64 -694.434 8.65 -694.434 8.66 -694.434 8.67 -698.456 8.68 -698.456 8.69 -690.434 8.7 -690.434 8.71 -694.434 8.72 -694.434 8.73 -694.434 8.74 -690.434 8.75 -690.434 8.76 -694.434 8.77 -698.456 8.78 -698.456 8.79 -698.456 8.8 -694.434 8.81 -694.434 8.82 -694.434 8.83 -694.434 8.84 -690.434 8.85 -694.434 8.86 -698.456 8.87 -698.456 8.88 -698.456 8.89 -698.456 8.9 -694.434 8.91 -698.456 8.92 -690.434 8.93 -690.434 8.94 -690.434 8.95 -694.434 8.96 -694.434 8.97 -694.434 8.98 -698.456 8.99 -698.456 9 -694.434 9.01 -694.434 9.02 -694.434 9.03 -706.572 9.04 -690.434 9.05 -674.664 9.06 -682.504 9.07 -647.93 9.08 -647.93 9.09 -674.664 9.1 -682.504 9.11 -682.504 9.12 -682.504 9.13 -690.434 9.14 -698.456 9.15 -702.503 9.16 -698.456 9.17 -694.434 9.18 -678.573 9.19 -880 9.2 -880 9.21 -880 9.22 -880 9.23 -880 9.24 -880 9.25 -880 9.26 -880 9.27 -880 9.28 -880 9.29 -880 9.3 -880 9.31 -880 9.32 -880 9.33 -880 9.34 -714.782 9.35 -682.504 9.36 -647.93 9.37 -647.93 9.38 -666.915 9.39 -678.573 9.4 -686.457 9.41 -686.457 9.42 -690.434 9.43 -698.456 9.44 -698.456 9.45 -698.456 9.46 -694.434 9.47 -694.434 9.48 -698.456 9.49 -694.434 9.5 -694.434 9.51 -690.434 9.52 -690.434 9.53 -690.434 9.54 -690.434 9.55 -694.434 9.56 -698.456 9.57 -698.456 9.58 -694.434 9.59 -694.434 9.6 -694.434 9.61 -694.434 9.62 -690.434 9.63 -659.255 9.64 -880 9.65 -880 9.66 -880 9.67 -880 9.68 -880 9.69 -943.161 9.7 -921.619 9.71 -911.033 9.72 -932.328 9.73 -937.728 9.74 -921.619 9.75 -900.569 9.76 -916.311 9.77 -916.311 9.78 -926.958 9.79 -937.728 9.8 -937.728 9.81 -921.619 9.82 -937.728 9.83 -932.328 9.84 -921.619 9.85 -926.958 9.86 -916.311 9.87 -932.328 9.88 -926.958 9.89 -932.328 9.9 -926.958 9.91 -916.311 9.92 -926.958 9.93 -880 9.94 -880 9.95 -880 9.96 783.991 9.97 779.475 9.98 779.475 9.99 779.475 10 783.991 10.01 783.991 10.02 783.991 10.03 783.991 10.04 783.991 10.05 783.991 10.06 783.991 10.07 783.991 10.08 783.991 10.09 779.475 10.1 779.475 10.11 779.475 10.12 783.991 10.13 783.991 10.14 783.991 10.15 783.991 10.16 783.991 10.17 779.475 10.18 783.991 10.19 783.991 10.2 783.991 10.21 783.991 10.22 779.475 10.23 779.475 10.24 779.475 10.25 788.532 10.26 783.991 10.27 783.991 10.28 783.991 10.29 783.991 10.3 783.991 10.31 788.532 10.32 783.991 10.33 783.991 10.34 783.991 10.35 779.475 10.36 783.991 10.37 783.991 10.38 779.475 10.39 783.991 10.4 783.991 10.41 779.475 10.42 779.475 10.43 783.991 10.44 783.991 10.45 783.991 10.46 783.991 10.47 783.991 10.48 783.991 10.49 783.991 10.5 783.991 10.51 783.991 10.52 788.532 10.53 788.532 10.54 797.695 10.55 770.522 10.56 783.991 10.57 783.991 10.58 698.456 10.59 690.434 10.6 690.434 10.61 694.434 10.62 694.434 10.63 690.434 10.64 690.434 10.65 694.434 10.66 694.434 10.67 -880 10.68 -880 10.69 -880 10.7 -880 10.71 -880 10.72 -880 10.73 -880 10.74 -880 10.75 -880 10.76 -880 10.77 -880 10.78 -880 10.79 -880 10.8 -880 10.81 -880 10.82 -880 10.83 -880 10.84 -880 10.85 -880 10.86 -880 10.87 -880 10.88 -880 10.89 -690.434 10.9 -731.489 10.91 -766.084 10.92 -788.532 10.93 -779.475 10.94 -735.727 10.95 -748.587 10.96 -774.986 10.97 -783.991 10.98 -770.522 10.99 -770.522 11 -788.532 11.01 -774.986 11.02 -779.475 11.03 -783.991 11.04 -783.991 11.05 -774.986 11.06 -770.522 11.07 -770.522 11.08 -779.475 11.09 -783.991 11.1 -770.522 11.11 -774.986 11.12 583.947 11.13 583.947 11.14 583.947 11.15 583.947 11.16 583.947 11.17 583.947 11.18 583.947 11.19 583.947 11.2 580.583 11.21 580.583 11.22 583.947 11.23 583.947 11.24 583.947 11.25 583.947 11.26 583.947 11.27 587.33 11.28 587.33 11.29 583.947 11.3 587.33 11.31 587.33 11.32 587.33 11.33 587.33 11.34 587.33 11.35 587.33 11.36 587.33 11.37 583.947 11.38 583.947 11.39 583.947 11.4 583.947 11.41 583.947 11.42 583.947 11.43 583.947 11.44 583.947 11.45 577.24 11.46 580.583 11.47 -788.532 11.48 -783.991 11.49 -770.522 11.5 -783.991 11.51 -770.522 11.52 -779.475 11.53 -779.475 11.54 -783.991 11.55 -779.475 11.56 -779.475 11.57 -774.986 11.58 -793.1 11.59 -766.084 11.6 -779.475 11.61 -779.475 11.62 -788.532 11.63 -779.475 11.64 -783.991 11.65 -774.986 11.66 -779.475 11.67 -774.986 11.68 -783.991 11.69 -779.475 11.7 -779.475 11.71 -779.475 11.72 -788.532 11.73 -821.069 11.74 -825.825 11.75 -779.475 11.76 -710.665 11.77 -682.504 11.78 -670.779 11.79 -466.164 11.8 -466.164 11.81 -466.164 11.82 -466.164 11.83 -466.164 11.84 -466.164 11.85 -466.164 11.86 -466.164 11.87 -466.164 11.88 -468.864 11.89 -466.164 11.9 -466.164 11.91 -466.164 11.92 -880 11.93 -880 11.94 -880 11.95 -880 11.96 -880 11.97 -880 11.98 -880 11.99 -880 12 -880 12.01 -880 12.02 -880 12.03 -880 12.04 -880 12.05 -880 12.06 -880 12.07 520.237 12.08 523.251 12.09 520.237 12.1 520.237 12.11 520.237 12.12 520.237 12.13 520.237 12.14 520.237 12.15 520.237 12.16 517.241 12.17 517.241 12.18 514.262 12.19 520.237 12.2 520.237 12.21 520.237 12.22 520.237 12.23 520.237 12.24 -864.882 12.25 -869.892 12.26 -880 12.27 -869.892 12.28 -864.882 12.29 -864.882 12.3 -880 12.31 -864.882 12.32 -874.932 12.33 -854.948 12.34 523.251 12.35 520.237 12.36 520.237 12.37 520.237 12.38 520.237 12.39 523.251 12.4 520.237 12.41 523.251 12.42 523.251 12.43 520.237 12.44 517.241 12.45 517.241 12.46 517.241 12.47 520.237 12.48 520.237 12.49 520.237 12.5 520.237 12.51 523.251 12.52 523.251 12.53 520.237 12.54 523.251 12.55 523.251 12.56 523.251 12.57 523.251 12.58 523.251 12.59 523.251 12.6 526.282 12.61 526.282 12.62 526.282 12.63 532.397 12.64 -859.901 12.65 -450.285 12.66 -452.893 12.67 -447.691 12.68 -434.946 12.69 -434.946 12.7 -440 12.71 -437.466 12.72 -440 12.73 -434.946 12.74 -440 12.75 -440 12.76 -440 12.77 -437.466 12.78 -440 12.79 -440 12.8 -440 12.81 -440 12.82 -440 12.83 -440 12.84 -440 12.85 -440 12.86 -440 12.87 -440 12.88 -440 12.89 -440 12.9 -440 12.91 -440 12.92 -440 12.93 547.998 12.94 551.172 12.95 554.365 12.96 551.172 12.97 547.998 12.98 554.365 12.99 547.998 13 583.947 13.01 577.24 13.02 587.33 13.03 583.947 13.04 580.583 13.05 583.947 13.06 583.947 13.07 580.583 13.08 583.947 13.09 577.24 13.1 583.947 13.11 583.947 13.12 583.947 13.13 583.947 13.14 583.947 13.15 583.947 13.16 583.947 13.17 583.947 13.18 583.947 13.19 587.33 13.2 587.33 13.21 583.947 13.22 583.947 13.23 583.947 13.24 583.947 13.25 583.947 13.26 583.947 13.27 583.947 13.28 583.947 13.29 583.947 13.3 583.947 13.31 587.33 13.32 583.947 13.33 577.24 13.34 580.583 13.35 583.947 13.36 583.947 13.37 587.33 13.38 583.947 13.39 587.33 13.4 587.33 13.41 587.33 13.42 583.947 13.43 587.33 13.44 587.33 13.45 583.947 13.46 587.33 13.47 587.33 13.48 587.33 13.49 583.947 13.5 587.33 13.51 583.947 13.52 583.947 13.53 583.947 13.54 587.33 13.55 580.583 13.56 580.583 13.57 583.947 13.58 583.947 13.59 293.665 13.6 290.292 13.61 290.292 13.62 291.973 13.63 291.973 13.64 293.665 13.65 291.973 13.66 291.973 13.67 293.665 13.68 293.665 13.69 290.292 13.7 291.973 13.71 295.366 13.72 293.665 13.73 293.665 13.74 293.665 13.75 291.973 13.76 293.665 13.77 293.665 13.78 -590.732 13.79 -580.583 13.8 -580.583 13.81 -587.33 13.82 -590.732 13.83 -455.517 13.84 -455.517 13.85 -432.441 13.86 554.365 13.87 551.172 13.88 554.365 13.89 554.365 13.9 551.172 13.91 544.842 13.92 538.584 13.93 547.998 13.94 523.251 13.95 523.251 13.96 520.237 13.97 520.237 13.98 520.237 13.99 517.241 14 463.479 14.01 463.479 14.02 463.479 14.03 466.164 14.04 466.164 14.05 463.479 14.06 463.479 14.07 463.479 14.08 460.809 14.09 460.809 14.1 463.479 14.11 463.479 14.12 466.164 14.13 463.479 14.14 463.479 14.15 460.809 14.16 468.864 14.17 466.164 14.18 -442.549 14.19 -437.466 14.2 -437.466 14.21 -437.466 14.22 -434.946 14.23 -434.946 14.24 -434.946 14.25 -434.946 14.26 -434.946 14.27 -434.946 14.28 -434.946 14.29 -437.466 14.3 -437.466 14.31 -434.946 14.32 -434.946 14.33 -437.466 14.34 -440 14.35 -434.946 14.36 -434.946 14.37 -437.466 14.38 -437.466 14.39 -437.466 14.4 -437.466 14.41 -437.466 14.42 -434.946 14.43 -440 14.44 -429.95 14.45 -779.475 14.46 -401.158 14.47 -398.847 14.48 -396.55 14.49 -391.995 14.5 -779.475 14.51 -748.587 14.52 -391.995 14.53 -396.55 14.54 -770.522 14.55 -739.989 14.56 -761.672 14.57 -389.738 14.58 -770.522 14.59 -774.986 14.6 -766.084 14.61 -389.738 14.62 -774.986 14.63 -391.995 14.64 -391.995 14.65 -391.995 14.66 -766.084 14.67 -770.522 14.68 -389.738 14.69 -394.266 14.7 -770.522 14.71 -387.493 14.72 -770.522 14.73 -394.266 14.74 -394.266 14.75 -394.266 14.76 -766.084 14.77 -387.493 14.78 -389.738 14.79 -391.995 14.8 -391.995 14.81 -389.738 14.82 -770.522 14.83 -389.738 14.84 -389.738 14.85 -389.738 14.86 -387.493 14.87 -387.493 14.88 -389.738 14.89 -389.738 14.9 -396.55 14.91 -389.738 14.92 -391.995 14.93 -389.738 14.94 -394.266 14.95 -389.738 14.96 -389.738 14.97 -385.261 14.98 -389.738 14.99 -391.995 15 -394.266 15.01 -387.493 15.02 -387.493 15.03 -389.738 15.04 -394.266 15.05 -761.672 15.06 -387.493 15.07 -391.995 15.08 -391.995 15.09 -391.995 15.1 -389.738 15.11 -391.995 15.12 -391.995 15.13 -391.995 15.14 -391.995 15.15 -391.995 15.16 -391.995 15.17 -394.266 15.18 -394.266 15.19 -391.995 15.2 -440 15.21 -440 15.22 -440 15.23 -440 15.24 -440 15.25 -440 15.26 -440 15.27 -440 15.28 -440 15.29 -440 15.3 -440 15.31 -440 15.32 -440 15.33 -440 15.34 -440 15.35 -440 15.36 -440 15.37 -440 15.38 -440 15.39 -710.665 15.4 -748.587 15.41 -766.084 15.42 -394.266 15.43 -391.995 15.44 -744.276 15.45 -757.285 15.46 -389.738 15.47 -394.266 15.48 -389.738 15.49 -385.261 15.5 -385.261 15.51 -389.738 15.52 -389.738 15.53 -389.738 15.54 -391.995 15.55 -389.738 15.56 -387.493 15.57 -387.493 15.58 -389.738 15.59 -389.738 15.6 -387.493 15.61 -387.493 15.62 -385.261 15.63 -420.13 15.64 -405.819 15.65 -440 15.66 -440 15.67 -587.33 15.68 -590.732 15.69 -583.947 15.7 -580.583 15.71 -587.33 15.72 -580.583 15.73 -583.947 15.74 293.665 15.75 291.973 15.76 290.292 15.77 291.973 15.78 305.782 15.79 316.565 15.8 316.565 15.81 311.127 15.82 304.021 15.83 300.529 15.84 -440 15.85 -440 15.86 -440 15.87 -440 15.88 -440 15.89 -440 15.9 -440 15.91 -440 15.92 -440 15.93 -440 15.94 -440 15.95 -440 15.96 -587.33 15.97 -590.732 15.98 -594.154 15.99 -577.24 16 -573.915 16.01 -583.947 16.02 -580.583 16.03 -577.24 16.04 -583.947 16.05 -587.33 16.06 -583.947 16.07 -577.24 16.08 -587.33 16.09 -594.154 16.1 -587.33 16.11 -580.583 16.12 -580.583 16.13 -577.24 16.14 -580.583 16.15 -587.33 16.16 -590.732 16.17 -580.583 16.18 -580.583 16.19 -587.33 16.2 -583.947 16.21 -580.583 16.22 -583.947 16.23 -597.596 16.24 -440 16.25 -440 16.26 -440 16.27 -466.164 16.28 -458.155 16.29 -458.155 16.3 -463.479 16.31 -466.164 16.32 -466.164 16.33 -466.164 16.34 -463.479 16.35 -463.479 16.36 -463.479 16.37 -466.164 16.38 -466.164 16.39 -468.864 16.4 523.251 16.41 520.237 16.42 523.251 16.43 523.251 16.44 523.251 16.45 520.237 16.46 520.237 16.47 520.237 16.48 520.237 16.49 520.237 16.5 520.237 16.51 520.237 16.52 517.241 16.53 517.241 16.54 520.237 16.55 520.237 16.56 520.237 16.57 520.237 16.58 -594.154 16.59 -594.154 16.6 -580.583 16.61 -577.24 16.62 -583.947 16.63 -587.33 16.64 -580.583 16.65 -587.33 16.66 -583.947 16.67 -580.583 16.68 -573.915 16.69 -583.947 16.7 -597.596 16.71 -594.154 16.72 -583.947 16.73 -580.583 16.74 -577.24 16.75 -580.583 16.76 -590.732 16.77 -590.732 16.78 -580.583 16.79 -577.24 16.8 -587.33 16.81 -587.33 16.82 -580.583 16.83 -590.732 16.84 -597.596 16.85 520.237 16.86 520.237 16.87 523.251 16.88 520.237 16.89 520.237 16.9 520.237 16.91 520.237 16.92 520.237 16.93 520.237 16.94 520.237 16.95 520.237 16.96 520.237 16.97 517.241 16.98 517.241 16.99 520.237 17 520.237 17.01 520.237 17.02 520.237 17.03 520.237 17.04 520.237 17.05 523.251 17.06 520.237 17.07 520.237 17.08 520.237 17.09 523.251 17.1 520.237 17.11 523.251 17.12 520.237 17.13 520.237 17.14 523.251 17.15 523.251 17.16 520.237 17.17 520.237 17.18 520.237 17.19 520.237 17.2 520.237 17.21 520.237 17.22 520.237 17.23 520.237 17.24 517.241 17.25 514.262 17.26 520.237 17.27 520.237 17.28 520.237 17.29 520.237 17.3 520.237 17.31 523.251 17.32 523.251 17.33 523.251 17.34 523.251 17.35 523.251 17.36 523.251 17.37 523.251 17.38 523.251 17.39 523.251 17.4 526.282 17.41 526.282 17.42 526.282 17.43 532.397 17.44 523.251 17.45 514.262 17.46 520.237 17.47 523.251 17.48 523.251 17.49 520.237 17.5 520.237 17.51 520.237 17.52 520.237 17.53 520.237 17.54 523.251 17.55 523.251 17.56 520.237 17.57 520.237 17.58 523.251 17.59 523.251 17.6 520.237 17.61 520.237 17.62 520.237 17.63 523.251 17.64 520.237 17.65 523.251 17.66 520.237 17.67 -440 17.68 -440 17.69 -440 17.7 -440 17.71 -440 17.72 -440 17.73 -440 17.74 -440 17.75 -440 17.76 -440 17.77 -440 17.78 -408.17 17.79 -440 17.8 -442.549 17.81 -437.466 17.82 -432.441 17.83 -429.95 17.84 583.947 17.85 583.947 17.86 583.947 17.87 583.947 17.88 583.947 17.89 583.947 17.9 580.583 17.91 580.583 17.92 583.947 17.93 583.947 17.94 583.947 17.95 583.947 17.96 583.947 17.97 583.947 17.98 583.947 17.99 583.947 18 587.33 18.01 587.33 18.02 587.33 18.03 583.947 18.04 583.947 18.05 583.947 18.06 288.62 18.07 291.973 18.08 293.665 18.09 291.973 18.1 291.973 18.11 291.973 18.12 290.292 18.13 291.973 18.14 291.973 18.15 290.292 18.16 291.973 18.17 291.973 18.18 285.305 18.19 293.665 18.2 298.798 18.21 298.798 18.22 298.798 18.23 587.33 18.24 583.947 18.25 587.33 18.26 587.33 18.27 587.33 18.28 587.33 18.29 587.33 18.3 587.33 18.31 587.33 18.32 587.33 18.33 583.947 18.34 583.947 18.35 583.947 18.36 291.973 18.37 293.665 18.38 293.665 18.39 291.973 18.4 291.973 18.41 293.665 18.42 293.665 18.43 291.973 18.44 291.973 18.45 293.665 18.46 291.973 18.47 293.665 18.48 293.665 18.49 293.665 18.5 291.973 18.51 291.973 18.52 293.665 18.53 293.665 18.54 293.665 18.55 291.973 18.56 291.973 18.57 293.665 18.58 293.665 18.59 293.665 18.6 291.973 18.61 291.973 18.62 291.973 18.63 293.665 18.64 291.973 18.65 290.292 18.66 297.077 18.67 291.973 18.68 288.62 18.69 295.366 18.7 295.366 18.71 291.973 18.72 291.973 18.73 293.665 18.74 293.665 18.75 291.973 18.76 293.665 18.77 293.665 18.78 290.292 18.79 291.973 18.8 295.366 18.81 293.665 18.82 291.973 18.83 293.665 18.84 293.665 18.85 291.973 18.86 293.665 18.87 291.973 18.88 -583.947 18.89 -580.583 18.9 -583.947 18.91 -583.947 18.92 -587.33 18.93 -583.947 18.94 -583.947 18.95 -580.583 18.96 -583.947 18.97 -587.33 18.98 -463.479 18.99 -463.479 19 -460.809 19.01 -466.164 19.02 -460.809 19.03 -460.809 19.04 -460.809 19.05 -463.479 19.06 -463.479 19.07 -463.479 19.08 -463.479 19.09 -463.479 19.1 -463.479 19.11 -463.479 19.12 -463.479 19.13 -463.479 19.14 -463.479 19.15 -463.479 19.16 -466.164 19.17 -463.479 19.18 -460.809 19.19 -463.479 19.2 -463.479 mir_eval-0.8.2/tests/data/melody/est05.txt000077500000000000000000000644651475740344600204240ustar00rootroot000000000000000 0 0.01 0 0.02 -880 0.03 -880 0.04 -880 0.05 -880 0.06 -655.458 0.07 -718.923 0.08 -748.587 0.09 -774.986 0.1 -788.532 0.11 -774.986 0.12 -744.276 0.13 -761.672 0.14 -779.475 0.15 -783.991 0.16 -779.475 0.17 -774.986 0.18 -779.475 0.19 -779.475 0.2 -779.475 0.21 -783.991 0.22 -783.991 0.23 -774.986 0.24 -774.986 0.25 -774.986 0.26 -783.991 0.27 -779.475 0.28 -774.986 0.29 -774.986 0.3 -774.986 0.31 -788.532 0.32 -793.1 0.33 -774.986 0.34 -761.672 0.35 -774.986 0.36 -774.986 0.37 -788.532 0.38 -779.475 0.39 -779.475 0.4 -770.522 0.41 -779.475 0.42 -779.475 0.43 -788.532 0.44 -774.986 0.45 -779.475 0.46 -770.522 0.47 -788.532 0.48 -788.532 0.49 -783.991 0.5 -770.522 0.51 -783.991 0.52 -774.986 0.53 -783.991 0.54 -774.986 0.55 -774.986 0.56 -779.475 0.57 -788.532 0.58 -779.475 0.59 -783.991 0.6 -783.991 0.61 -783.991 0.62 921.619 0.63 926.958 0.64 926.958 0.65 932.328 0.66 926.958 0.67 932.328 0.68 932.328 0.69 932.328 0.7 932.328 0.71 926.958 0.72 932.328 0.73 932.328 0.74 926.958 0.75 926.958 0.76 932.328 0.77 932.328 0.78 932.328 0.79 932.328 0.8 926.958 0.81 932.328 0.82 932.328 0.83 926.958 0.84 926.958 0.85 932.328 0.86 932.328 0.87 932.328 0.88 932.328 0.89 937.728 0.9 911.033 0.91 869.892 0.92 880 0.93 874.932 0.94 874.932 0.95 885.098 0.96 880 0.97 880 0.98 880 0.99 880 1 880 1.01 880 1.02 880 1.03 880 1.04 880 1.05 -880 1.06 -880 1.07 -880 1.08 -880 1.09 -880 1.1 -880 1.11 -880 1.12 -880 1.13 -880 1.14 -880 1.15 -880 1.16 -880 1.17 -880 1.18 -880 1.19 -880 1.2 -880 1.21 -880 1.22 -880 1.23 -880 1.24 779.475 1.25 779.475 1.26 779.475 1.27 779.475 1.28 783.991 1.29 783.991 1.3 783.991 1.31 783.991 1.32 783.991 1.33 783.991 1.34 783.991 1.35 783.991 1.36 779.475 1.37 779.475 1.38 779.475 1.39 783.991 1.4 783.991 1.41 783.991 1.42 783.991 1.43 783.991 1.44 779.475 1.45 783.991 1.46 783.991 1.47 779.475 1.48 783.991 1.49 779.475 1.5 783.991 1.51 783.991 1.52 783.991 1.53 583.947 1.54 587.33 1.55 583.947 1.56 583.947 1.57 583.947 1.58 580.583 1.59 583.947 1.6 583.947 1.61 580.583 1.62 583.947 1.63 580.583 1.64 583.947 1.65 583.947 1.66 583.947 1.67 583.947 1.68 587.33 1.69 583.947 1.7 583.947 1.71 583.947 1.72 587.33 1.73 587.33 1.74 587.33 1.75 587.33 1.76 587.33 1.77 587.33 1.78 583.947 1.79 583.947 1.8 583.947 1.81 580.583 1.82 587.33 1.83 590.732 1.84 587.33 1.85 583.947 1.86 583.947 1.87 580.583 1.88 583.947 1.89 587.33 1.9 583.947 1.91 587.33 1.92 587.33 1.93 587.33 1.94 583.947 1.95 583.947 1.96 583.947 1.97 587.33 1.98 587.33 1.99 587.33 2 587.33 2.01 587.33 2.02 587.33 2.03 587.33 2.04 583.947 2.05 583.947 2.06 583.947 2.07 583.947 2.08 583.947 2.09 580.583 2.1 583.947 2.11 583.947 2.12 523.251 2.13 520.237 2.14 523.251 2.15 520.237 2.16 520.237 2.17 520.237 2.18 520.237 2.19 517.241 2.2 520.237 2.21 520.237 2.22 520.237 2.23 517.241 2.24 517.241 2.25 517.241 2.26 520.237 2.27 520.237 2.28 520.237 2.29 520.237 2.3 -440 2.31 -440 2.32 -440 2.33 -440 2.34 -440 2.35 -440 2.36 -440 2.37 -440 2.38 -440 2.39 -440 2.4 -440 2.41 -440 2.42 -440 2.43 -440 2.44 -440 2.45 -440 2.46 -674.664 2.47 -727.276 2.48 -748.587 2.49 -774.986 2.5 -788.532 2.51 -770.522 2.52 -748.587 2.53 -766.084 2.54 -783.991 2.55 -779.475 2.56 -770.522 2.57 520.237 2.58 520.237 2.59 520.237 2.6 520.237 2.61 520.237 2.62 520.237 2.63 520.237 2.64 523.251 2.65 520.237 2.66 523.251 2.67 523.251 2.68 520.237 2.69 520.237 2.7 523.251 2.71 523.251 2.72 520.237 2.73 523.251 2.74 520.237 2.75 523.251 2.76 520.237 2.77 520.237 2.78 523.251 2.79 520.237 2.8 520.237 2.81 520.237 2.82 514.262 2.83 517.241 2.84 520.237 2.85 523.251 2.86 523.251 2.87 523.251 2.88 520.237 2.89 523.251 2.9 523.251 2.91 523.251 2.92 523.251 2.93 523.251 2.94 523.251 2.95 523.251 2.96 523.251 2.97 -779.475 2.98 -774.986 2.99 -783.991 3 -788.532 3.01 -783.991 3.02 -774.986 3.03 -788.532 3.04 463.479 3.05 463.479 3.06 463.479 3.07 466.164 3.08 463.479 3.09 466.164 3.1 466.164 3.11 466.164 3.12 463.479 3.13 463.479 3.14 466.164 3.15 466.164 3.16 -779.475 3.17 -770.522 3.18 -440 3.19 -440 3.2 -440 3.21 -440 3.22 -440 3.23 -440 3.24 -440 3.25 -440 3.26 -440 3.27 -440 3.28 -440 3.29 -440 3.3 -440 3.31 520.237 3.32 523.251 3.33 523.251 3.34 520.237 3.35 520.237 3.36 520.237 3.37 520.237 3.38 517.241 3.39 520.237 3.4 520.237 3.41 520.237 3.42 520.237 3.43 517.241 3.44 514.262 3.45 520.237 3.46 520.237 3.47 520.237 3.48 520.237 3.49 520.237 3.5 520.237 3.51 520.237 3.52 520.237 3.53 523.251 3.54 520.237 3.55 520.237 3.56 523.251 3.57 523.251 3.58 520.237 3.59 523.251 3.6 523.251 3.61 520.237 3.62 523.251 3.63 523.251 3.64 520.237 3.65 523.251 3.66 520.237 3.67 520.237 3.68 520.237 3.69 520.237 3.7 514.262 3.71 514.262 3.72 517.241 3.73 520.237 3.74 520.237 3.75 520.237 3.76 520.237 3.77 520.237 3.78 520.237 3.79 520.237 3.8 523.251 3.81 523.251 3.82 523.251 3.83 523.251 3.84 526.282 3.85 526.282 3.86 -774.986 3.87 -770.522 3.88 -779.475 3.89 -779.475 3.9 -797.695 3.91 -770.522 3.92 583.947 3.93 587.33 3.94 587.33 3.95 583.947 3.96 583.947 3.97 583.947 3.98 583.947 3.99 583.947 4 583.947 4.01 583.947 4.02 583.947 4.03 580.583 4.04 583.947 4.05 583.947 4.06 583.947 4.07 583.947 4.08 583.947 4.09 583.947 4.1 583.947 4.11 583.947 4.12 583.947 4.13 583.947 4.14 587.33 4.15 587.33 4.16 583.947 4.17 583.947 4.18 583.947 4.19 583.947 4.2 587.33 4.21 587.33 4.22 577.24 4.23 580.583 4.24 583.947 4.25 587.33 4.26 580.583 4.27 580.583 4.28 580.583 4.29 583.947 4.3 583.947 4.31 583.947 4.32 583.947 4.33 587.33 4.34 587.33 4.35 583.947 4.36 587.33 4.37 587.33 4.38 583.947 4.39 587.33 4.4 587.33 4.41 587.33 4.42 587.33 4.43 583.947 4.44 583.947 4.45 583.947 4.46 583.947 4.47 587.33 4.48 583.947 4.49 583.947 4.5 583.947 4.51 583.947 4.52 -880 4.53 -880 4.54 -880 4.55 -880 4.56 -880 4.57 -880 4.58 -880 4.59 -880 4.6 -880 4.61 -880 4.62 -880 4.63 -880 4.64 -880 4.65 -880 4.66 -880 4.67 -880 4.68 -880 4.69 -880 4.7 -880 4.71 -880 4.72 -880 4.73 -880 4.74 -880 4.75 -880 4.76 -880 4.77 -880 4.78 -880 4.79 -880 4.8 -880 4.81 -880 4.82 -880 4.83 -880 4.84 -880 4.85 -880 4.86 -880 4.87 -731.489 4.88 -761.672 4.89 -779.475 4.9 -788.532 4.91 -770.522 4.92 -748.587 4.93 -766.084 4.94 -783.991 4.95 -783.991 4.96 -774.986 4.97 -766.084 4.98 -779.475 4.99 -779.475 5 -783.991 5.01 -783.991 5.02 -783.991 5.03 -774.986 5.04 -774.986 5.05 -779.475 5.06 -783.991 5.07 -774.986 5.08 -774.986 5.09 -774.986 5.1 -779.475 5.11 -797.695 5.12 -788.532 5.13 -766.084 5.14 -766.084 5.15 -770.522 5.16 -774.986 5.17 -779.475 5.18 -774.986 5.19 -779.475 5.2 -774.986 5.21 -774.986 5.22 -774.986 5.23 -779.475 5.24 -774.986 5.25 -774.986 5.26 -770.522 5.27 -788.532 5.28 -793.1 5.29 -783.991 5.3 -770.522 5.31 -783.991 5.32 -774.986 5.33 -783.991 5.34 -774.986 5.35 -783.991 5.36 -779.475 5.37 -783.991 5.38 -774.986 5.39 -779.475 5.4 -779.475 5.41 -779.475 5.42 779.475 5.43 779.475 5.44 779.475 5.45 783.991 5.46 783.991 5.47 779.475 5.48 779.475 5.49 783.991 5.5 783.991 5.51 783.991 5.52 783.991 5.53 783.991 5.54 783.991 5.55 783.991 5.56 779.475 5.57 779.475 5.58 783.991 5.59 783.991 5.6 783.991 5.61 -880 5.62 -880 5.63 -880 5.64 -880 5.65 -880 5.66 -880 5.67 -880 5.68 -880 5.69 -880 5.7 880 5.71 874.932 5.72 874.932 5.73 874.932 5.74 880 5.75 880 5.76 880 5.77 880 5.78 880 5.79 880 5.8 880 5.81 880 5.82 880 5.83 880 5.84 874.932 5.85 880 5.86 880 5.87 -880 5.88 -880 5.89 -880 5.9 -880 5.91 -880 5.92 -880 5.93 -880 5.94 -880 5.95 -880 5.96 -880 5.97 -880 5.98 -880 5.99 -880 6 -880 6.01 921.619 6.02 926.958 6.03 926.958 6.04 926.958 6.05 932.328 6.06 932.328 6.07 926.958 6.08 932.328 6.09 932.328 6.1 932.328 6.11 932.328 6.12 932.328 6.13 932.328 6.14 932.328 6.15 932.328 6.16 932.328 6.17 932.328 6.18 932.328 6.19 926.958 6.2 926.958 6.21 932.328 6.22 932.328 6.23 932.328 6.24 937.728 6.25 932.328 6.26 932.328 6.27 932.328 6.28 -880 6.29 -880 6.3 1046.5 6.31 1040.47 6.32 1040.47 6.33 1046.5 6.34 1046.5 6.35 1046.5 6.36 1046.5 6.37 1046.5 6.38 1046.5 6.39 1046.5 6.4 1046.5 6.41 1046.5 6.42 1046.5 6.43 1046.5 6.44 1046.5 6.45 1046.5 6.46 1040.47 6.47 1040.47 6.48 1046.5 6.49 1046.5 6.5 1046.5 6.51 1046.5 6.52 1046.5 6.53 1046.5 6.54 1046.5 6.55 1046.5 6.56 1046.5 6.57 1046.5 6.58 1046.5 6.59 1046.5 6.6 1046.5 6.61 1040.47 6.62 874.932 6.63 880 6.64 874.932 6.65 874.932 6.66 874.932 6.67 874.932 6.68 874.932 6.69 880 6.7 880 6.71 880 6.72 880 6.73 880 6.74 880 6.75 880 6.76 880 6.77 880 6.78 880 6.79 880 6.8 880 6.81 880 6.82 779.475 6.83 779.475 6.84 779.475 6.85 779.475 6.86 783.991 6.87 779.475 6.88 779.475 6.89 783.991 6.9 783.991 6.91 779.475 6.92 783.991 6.93 779.475 6.94 783.991 6.95 783.991 6.96 779.475 6.97 779.475 6.98 783.991 6.99 783.991 7 783.991 7.01 788.532 7.02 783.991 7.03 783.991 7.04 779.475 7.05 779.475 7.06 779.475 7.07 774.986 7.08 774.986 7.09 779.475 7.1 783.991 7.11 783.991 7.12 783.991 7.13 783.991 7.14 783.991 7.15 783.991 7.16 783.991 7.17 788.532 7.18 788.532 7.19 783.991 7.2 783.991 7.21 -766.084 7.22 -731.489 7.23 -698.456 7.24 -690.434 7.25 -714.782 7.26 -766.084 7.27 -774.986 7.28 -788.532 7.29 -757.285 7.3 -770.522 7.31 -783.991 7.32 -788.532 7.33 -774.986 7.34 -774.986 7.35 -774.986 7.36 -779.475 7.37 -783.991 7.38 -779.475 7.39 -779.475 7.4 -779.475 7.41 -779.475 7.42 -779.475 7.43 -783.991 7.44 -779.475 7.45 -779.475 7.46 -779.475 7.47 -783.991 7.48 -779.475 7.49 -779.475 7.5 -779.475 7.51 -774.986 7.52 -779.475 7.53 -788.532 7.54 -788.532 7.55 -793.1 7.56 -783.991 7.57 -766.084 7.58 -779.475 7.59 -783.991 7.6 -783.991 7.61 -774.986 7.62 -779.475 7.63 -783.991 7.64 -779.475 7.65 -779.475 7.66 -783.991 7.67 -779.475 7.68 -779.475 7.69 -779.475 7.7 -783.991 7.71 -783.991 7.72 -783.991 7.73 -779.475 7.74 -779.475 7.75 -779.475 7.76 -783.991 7.77 -783.991 7.78 -783.991 7.79 -779.475 7.8 -783.991 7.81 -770.522 7.82 -779.475 7.83 -783.991 7.84 -788.532 7.85 -779.475 7.86 -779.475 7.87 -783.991 7.88 -783.991 7.89 -779.475 7.9 -783.991 7.91 -779.475 7.92 -779.475 7.93 -783.991 7.94 -779.475 7.95 -779.475 7.96 -783.991 7.97 -779.475 7.98 -779.475 7.99 -779.475 8 -779.475 8.01 -779.475 8.02 -779.475 8.03 -779.475 8.04 -779.475 8.05 -779.475 8.06 -779.475 8.07 -779.475 8.08 -779.475 8.09 -779.475 8.1 -779.475 8.11 -770.522 8.12 -774.986 8.13 -702.503 8.14 -678.573 8.15 -655.458 8.16 -779.475 8.17 -779.475 8.18 -779.475 8.19 -779.475 8.2 -774.986 8.21 -783.991 8.22 -779.475 8.23 -774.986 8.24 -774.986 8.25 -783.991 8.26 -783.991 8.27 -779.475 8.28 -779.475 8.29 -779.475 8.3 -779.475 8.31 -783.991 8.32 -783.991 8.33 -783.991 8.34 -779.475 8.35 -779.475 8.36 -779.475 8.37 -779.475 8.38 -774.986 8.39 -770.522 8.4 -880 8.41 -880 8.42 -880 8.43 -880 8.44 -880 8.45 -880 8.46 -766.084 8.47 -779.475 8.48 -783.991 8.49 -774.986 8.5 -779.475 8.51 -788.532 8.52 -788.532 8.53 -766.084 8.54 -770.522 8.55 -779.475 8.56 -779.475 8.57 -783.991 8.58 -783.991 8.59 -774.986 8.6 -774.986 8.61 -779.475 8.62 -783.991 8.63 -783.991 8.64 -779.475 8.65 -774.986 8.66 -779.475 8.67 -783.991 8.68 -783.991 8.69 -779.475 8.7 -774.986 8.71 -779.475 8.72 -783.991 8.73 -783.991 8.74 -779.475 8.75 -779.475 8.76 -779.475 8.77 -779.475 8.78 -779.475 8.79 -779.475 8.8 -779.475 8.81 -779.475 8.82 -779.475 8.83 -779.475 8.84 -779.475 8.85 -779.475 8.86 -779.475 8.87 -783.991 8.88 -783.991 8.89 -779.475 8.9 -779.475 8.91 -779.475 8.92 -779.475 8.93 -783.991 8.94 -779.475 8.95 -779.475 8.96 -779.475 8.97 -779.475 8.98 -783.991 8.99 -779.475 9 -774.986 9.01 -761.672 9.02 -774.986 9.03 -783.991 9.04 -793.1 9.05 -783.991 9.06 -779.475 9.07 -766.084 9.08 -783.991 9.09 -788.532 9.1 -779.475 9.11 -770.522 9.12 -783.991 9.13 -788.532 9.14 -779.475 9.15 -779.475 9.16 -779.475 9.17 -779.475 9.18 -779.475 9.19 -783.991 9.2 -779.475 9.21 -779.475 9.22 -779.475 9.23 -779.475 9.24 -783.991 9.25 -779.475 9.26 -779.475 9.27 -779.475 9.28 -779.475 9.29 -779.475 9.3 -783.991 9.31 -793.1 9.32 -880 9.33 -880 9.34 -587.33 9.35 -601.058 9.36 -590.732 9.37 -580.583 9.38 -580.583 9.39 -583.947 9.4 -587.33 9.41 -580.583 9.42 -583.947 9.43 -587.33 9.44 -583.947 9.45 -583.947 9.46 -594.154 9.47 -880 9.48 -880 9.49 -880 9.5 -880 9.51 -880 9.52 -880 9.53 -880 9.54 -880 9.55 -880 9.56 -880 9.57 -880 9.58 -880 9.59 -880 9.6 -880 9.61 -880 9.62 -880 9.63 -880 9.64 -880 9.65 -880 9.66 -880 9.67 -880 9.68 -880 9.69 -880 9.7 -880 9.71 -880 9.72 -880 9.73 -880 9.74 -880 9.75 -880 9.76 -880 9.77 -880 9.78 -880 9.79 -880 9.8 -880 9.81 -880 9.82 -880 9.83 -880 9.84 -880 9.85 -880 9.86 -880 9.87 -880 9.88 -880 9.89 -880 9.9 -880 9.91 -880 9.92 -880 9.93 -880 9.94 -880 9.95 -880 9.96 -880 9.97 -880 9.98 -880 9.99 -880 10 -880 10.01 -880 10.02 -880 10.03 -880 10.04 -880 10.05 -880 10.06 -880 10.07 -880 10.08 -880 10.09 -880 10.1 -880 10.11 -880 10.12 -880 10.13 -880 10.14 -880 10.15 -880 10.16 -880 10.17 -880 10.18 -880 10.19 -880 10.2 -880 10.21 -880 10.22 -880 10.23 -880 10.24 -880 10.25 -880 10.26 -880 10.27 -880 10.28 -880 10.29 -880 10.3 -880 10.31 -880 10.32 -880 10.33 -880 10.34 -880 10.35 -880 10.36 -880 10.37 625.859 10.38 618.67 10.39 622.254 10.4 622.254 10.41 618.67 10.42 618.67 10.43 615.107 10.44 615.107 10.45 618.67 10.46 618.67 10.47 618.67 10.48 618.67 10.49 618.67 10.5 622.254 10.51 622.254 10.52 -880 10.53 -880 10.54 698.456 10.55 694.434 10.56 694.434 10.57 694.434 10.58 694.434 10.59 694.434 10.6 694.434 10.61 694.434 10.62 690.434 10.63 690.434 10.64 694.434 10.65 694.434 10.66 694.434 10.67 694.434 10.68 779.475 10.69 779.475 10.7 783.991 10.71 783.991 10.72 779.475 10.73 779.475 10.74 783.991 10.75 783.991 10.76 783.991 10.77 783.991 10.78 783.991 10.79 783.991 10.8 783.991 10.81 783.991 10.82 779.475 10.83 783.991 10.84 779.475 10.85 783.991 10.86 788.532 10.87 783.991 10.88 779.475 10.89 783.991 10.9 783.991 10.91 783.991 10.92 779.475 10.93 779.475 10.94 779.475 10.95 779.475 10.96 783.991 10.97 779.475 10.98 783.991 10.99 783.991 11 783.991 11.01 783.991 11.02 783.991 11.03 788.532 11.04 788.532 11.05 783.991 11.06 783.991 11.07 783.991 11.08 783.991 11.09 -880 11.1 -880 11.11 874.932 11.12 874.932 11.13 874.932 11.14 874.932 11.15 880 11.16 874.932 11.17 874.932 11.18 880 11.19 880 11.2 880 11.21 874.932 11.22 880 11.23 880 11.24 880 11.25 874.932 11.26 880 11.27 880 11.28 880 11.29 -880 11.3 -880 11.31 -880 11.32 -880 11.33 -880 11.34 -880 11.35 -880 11.36 -880 11.37 -880 11.38 -880 11.39 -880 11.4 -880 11.41 -880 11.42 -880 11.43 926.958 11.44 932.328 11.45 932.328 11.46 932.328 11.47 932.328 11.48 932.328 11.49 932.328 11.5 932.328 11.51 932.328 11.52 932.328 11.53 932.328 11.54 932.328 11.55 932.328 11.56 932.328 11.57 932.328 11.58 932.328 11.59 932.328 11.6 926.958 11.61 932.328 11.62 932.328 11.63 932.328 11.64 932.328 11.65 932.328 11.66 926.958 11.67 932.328 11.68 932.328 11.69 -880 11.7 -880 11.71 -880 11.72 1040.47 11.73 1040.47 11.74 1040.47 11.75 1046.5 11.76 1046.5 11.77 1046.5 11.78 1046.5 11.79 1046.5 11.8 1040.47 11.81 1046.5 11.82 1046.5 11.83 1046.5 11.84 1046.5 11.85 1046.5 11.86 1046.5 11.87 1040.47 11.88 1040.47 11.89 1040.47 11.9 1040.47 11.91 1046.5 11.92 1046.5 11.93 1046.5 11.94 1046.5 11.95 1046.5 11.96 1046.5 11.97 -880 11.98 -880 11.99 -880 12 -880 12.01 -932.328 12.02 -921.619 12.03 926.958 12.04 926.958 12.05 926.958 12.06 932.328 12.07 926.958 12.08 932.328 12.09 926.958 12.1 932.328 12.11 932.328 12.12 932.328 12.13 926.958 12.14 932.328 12.15 932.328 12.16 932.328 12.17 932.328 12.18 932.328 12.19 932.328 12.2 926.958 12.21 926.958 12.22 926.958 12.23 932.328 12.24 932.328 12.25 932.328 12.26 932.328 12.27 932.328 12.28 932.328 12.29 932.328 12.3 926.958 12.31 932.328 12.32 943.161 12.33 926.958 12.34 932.328 12.35 932.328 12.36 932.328 12.37 -932.328 12.38 -943.161 12.39 -926.958 12.4 -926.958 12.41 -937.728 12.42 -921.619 12.43 -926.958 12.44 -926.958 12.45 -943.161 12.46 -937.728 12.47 -921.619 12.48 -926.958 12.49 -932.328 12.5 -926.958 12.51 -921.619 12.52 -932.328 12.53 -932.328 12.54 -926.958 12.55 -926.958 12.56 -926.958 12.57 -926.958 12.58 -921.619 12.59 -932.328 12.6 -932.328 12.61 -937.728 12.62 -937.728 12.63 -926.958 12.64 -932.328 12.65 -932.328 12.66 -932.328 12.67 -932.328 12.68 -932.328 12.69 -932.328 12.7 -932.328 12.71 -926.958 12.72 -926.958 12.73 -926.958 12.74 -926.958 12.75 -932.328 12.76 -932.328 12.77 -932.328 12.78 -932.328 12.79 -937.728 12.8 -932.328 12.81 -937.728 12.82 -932.328 12.83 -932.328 12.84 -932.328 12.85 -932.328 12.86 -932.328 12.87 -926.958 12.88 -880 12.89 -880 12.9 -880 12.91 -880 12.92 694.434 12.93 698.456 12.94 698.456 12.95 694.434 12.96 694.434 12.97 690.434 12.98 694.434 12.99 694.434 13 694.434 13.01 690.434 13.02 694.434 13.03 694.434 13.04 694.434 13.05 694.434 13.06 694.434 13.07 694.434 13.08 694.434 13.09 698.456 13.1 694.434 13.11 698.456 13.12 694.434 13.13 694.434 13.14 694.434 13.15 694.434 13.16 694.434 13.17 694.434 13.18 694.434 13.19 694.434 13.2 694.434 13.21 690.434 13.22 690.434 13.23 686.457 13.24 694.434 13.25 694.434 13.26 694.434 13.27 698.456 13.28 698.456 13.29 694.434 13.3 698.456 13.31 694.434 13.32 694.434 13.33 698.456 13.34 698.456 13.35 698.456 13.36 698.456 13.37 690.434 13.38 698.456 13.39 698.456 13.4 690.434 13.41 690.434 13.42 694.434 13.43 694.434 13.44 694.434 13.45 694.434 13.46 694.434 13.47 694.434 13.48 694.434 13.49 -926.958 13.5 -921.619 13.51 583.947 13.52 583.947 13.53 583.947 13.54 587.33 13.55 583.947 13.56 583.947 13.57 583.947 13.58 583.947 13.59 583.947 13.6 583.947 13.61 580.583 13.62 580.583 13.63 583.947 13.64 583.947 13.65 583.947 13.66 583.947 13.67 587.33 13.68 583.947 13.69 583.947 13.7 583.947 13.71 583.947 13.72 583.947 13.73 587.33 13.74 587.33 13.75 587.33 13.76 583.947 13.77 587.33 13.78 583.947 13.79 583.947 13.8 580.583 13.81 583.947 13.82 580.583 13.83 583.947 13.84 583.947 13.85 587.33 13.86 583.947 13.87 580.583 13.88 583.947 13.89 583.947 13.9 583.947 13.91 583.947 13.92 587.33 13.93 587.33 13.94 583.947 13.95 583.947 13.96 587.33 13.97 587.33 13.98 583.947 13.99 587.33 14 -932.328 14.01 -932.328 14.02 -926.958 14.03 -932.328 14.04 -926.958 14.05 -926.958 14.06 -926.958 14.07 -926.958 14.08 -926.958 14.09 -926.958 14.1 -932.328 14.11 -954.12 14.12 -926.958 14.13 -916.311 14.14 -937.728 14.15 -948.624 14.16 -932.328 14.17 -926.958 14.18 -937.728 14.19 -932.328 14.2 -926.958 14.21 -932.328 14.22 -937.728 14.23 -932.328 14.24 -932.328 14.25 -926.958 14.26 -932.328 14.27 -937.728 14.28 -937.728 14.29 -937.728 14.3 -937.728 14.31 -937.728 14.32 -932.328 14.33 -932.328 14.34 -932.328 14.35 -880 14.36 -880 14.37 -880 14.38 -880 14.39 -880 14.4 -880 14.41 -880 14.42 774.986 14.43 779.475 14.44 779.475 14.45 779.475 14.46 779.475 14.47 783.991 14.48 783.991 14.49 779.475 14.5 783.991 14.51 783.991 14.52 783.991 14.53 783.991 14.54 783.991 14.55 783.991 14.56 783.991 14.57 779.475 14.58 779.475 14.59 783.991 14.6 783.991 14.61 783.991 14.62 783.991 14.63 783.991 14.64 783.991 14.65 783.991 14.66 779.475 14.67 779.475 14.68 779.475 14.69 779.475 14.7 779.475 14.71 779.475 14.72 783.991 14.73 783.991 14.74 783.991 14.75 783.991 14.76 783.991 14.77 783.991 14.78 783.991 14.79 783.991 14.8 783.991 14.81 783.991 14.82 783.991 14.83 783.991 14.84 783.991 14.85 783.991 14.86 779.475 14.87 774.986 14.88 783.991 14.89 779.475 14.9 783.991 14.91 783.991 14.92 783.991 14.93 783.991 14.94 783.991 14.95 783.991 14.96 783.991 14.97 -523.251 14.98 -523.251 14.99 -520.237 15 -529.331 15.01 -538.584 15.02 -825.825 15.03 -811.638 15.04 -761.672 15.05 -774.986 15.06 -783.991 15.07 -783.991 15.08 -779.475 15.09 -783.991 15.1 -783.991 15.11 -779.475 15.12 -779.475 15.13 -880 15.14 -880 15.15 -880 15.16 -880 15.17 -880 15.18 -880 15.19 -880 15.2 -880 15.21 -880 15.22 -880 15.23 -880 15.24 -880 15.25 -880 15.26 -880 15.27 -880 15.28 -880 15.29 -880 15.3 -880 15.31 -880 15.32 -880 15.33 -880 15.34 -880 15.35 -880 15.36 -880 15.37 -880 15.38 -880 15.39 -880 15.4 -880 15.41 -880 15.42 -880 15.43 -880 15.44 -880 15.45 -880 15.46 -880 15.47 583.947 15.48 583.947 15.49 587.33 15.5 587.33 15.51 583.947 15.52 583.947 15.53 583.947 15.54 580.583 15.55 583.947 15.56 583.947 15.57 583.947 15.58 580.583 15.59 580.583 15.6 583.947 15.61 -880 15.62 -880 15.63 779.475 15.64 779.475 15.65 779.475 15.66 779.475 15.67 783.991 15.68 783.991 15.69 779.475 15.7 783.991 15.71 783.991 15.72 783.991 15.73 783.991 15.74 783.991 15.75 779.475 15.76 783.991 15.77 783.991 15.78 779.475 15.79 783.991 15.8 783.991 15.81 779.475 15.82 783.991 15.83 783.991 15.84 783.991 15.85 783.991 15.86 779.475 15.87 779.475 15.88 779.475 15.89 779.475 15.9 779.475 15.91 783.991 15.92 779.475 15.93 783.991 15.94 783.991 15.95 698.456 15.96 694.434 15.97 690.434 15.98 694.434 15.99 694.434 16 690.434 16.01 690.434 16.02 694.434 16.03 694.434 16.04 694.434 16.05 698.456 16.06 698.456 16.07 694.434 16.08 694.434 16.09 694.434 16.1 694.434 16.11 698.456 16.12 694.434 16.13 694.434 16.14 694.434 16.15 694.434 16.16 694.434 16.17 694.434 16.18 694.434 16.19 694.434 16.2 694.434 16.21 -580.583 16.22 -570.609 16.23 -690.434 16.24 -694.434 16.25 -694.434 16.26 -694.434 16.27 -694.434 16.28 -698.456 16.29 -698.456 16.3 -694.434 16.31 -694.434 16.32 -698.456 16.33 -698.456 16.34 -698.456 16.35 -702.503 16.36 -690.434 16.37 -694.434 16.38 -694.434 16.39 -694.434 16.4 -694.434 16.41 -694.434 16.42 -694.434 16.43 -694.434 16.44 -694.434 16.45 -690.434 16.46 -694.434 16.47 -694.434 16.48 -694.434 16.49 -698.456 16.5 -698.456 16.51 -694.434 16.52 -698.456 16.53 -718.923 16.54 -710.665 16.55 -694.434 16.56 -698.456 16.57 -698.456 16.58 -698.456 16.59 -698.456 16.6 -597.596 16.61 -583.947 16.62 -594.154 16.63 -583.947 16.64 -570.609 16.65 -587.33 16.66 -594.154 16.67 -604.54 16.68 583.947 16.69 583.947 16.7 587.33 16.71 583.947 16.72 583.947 16.73 583.947 16.74 583.947 16.75 583.947 16.76 583.947 16.77 583.947 16.78 -880 16.79 -880 16.8 -880 16.81 -880 16.82 -880 16.83 -880 16.84 -880 16.85 779.475 16.86 779.475 16.87 783.991 16.88 783.991 16.89 779.475 16.9 783.991 16.91 783.991 16.92 783.991 16.93 783.991 16.94 783.991 16.95 788.532 16.96 779.475 16.97 779.475 16.98 779.475 16.99 783.991 17 783.991 17.01 783.991 17.02 783.991 17.03 779.475 17.04 -520.237 17.05 -520.237 17.06 -517.241 17.07 -520.237 17.08 -517.241 17.09 -526.282 17.1 -526.282 17.11 -987.767 17.12 -505.427 17.13 -514.262 17.14 -520.237 17.15 -517.241 17.16 -520.237 17.17 -520.237 17.18 -517.241 17.19 -517.241 17.2 -523.251 17.21 -520.237 17.22 -520.237 17.23 -517.241 17.24 -520.237 17.25 -514.262 17.26 -517.241 17.27 -520.237 17.28 -520.237 17.29 -520.237 17.3 -520.237 17.31 -520.237 17.32 -520.237 17.33 -523.251 17.34 -523.251 17.35 -517.241 17.36 -520.237 17.37 -523.251 17.38 -520.237 17.39 -517.241 17.4 -499.622 17.41 -880 17.42 -880 17.43 698.456 17.44 694.434 17.45 694.434 17.46 694.434 17.47 694.434 17.48 690.434 17.49 694.434 17.5 694.434 17.51 690.434 17.52 690.434 17.53 694.434 17.54 694.434 17.55 698.456 17.56 694.434 17.57 694.434 17.58 694.434 17.59 694.434 17.6 694.434 17.61 698.456 17.62 698.456 17.63 694.434 17.64 694.434 17.65 694.434 17.66 694.434 17.67 694.434 17.68 694.434 17.69 694.434 17.7 694.434 17.71 694.434 17.72 -880 17.73 -508.355 17.74 -517.241 17.75 -520.237 17.76 -520.237 17.77 -520.237 17.78 -511.3 17.79 -517.241 17.8 -517.241 17.81 -511.3 17.82 -517.241 17.83 -520.237 17.84 -517.241 17.85 -520.237 17.86 -520.237 17.87 -520.237 17.88 -520.237 17.89 -517.241 17.9 -517.241 17.91 698.456 17.92 694.434 17.93 694.434 17.94 694.434 17.95 694.434 17.96 690.434 17.97 690.434 17.98 694.434 17.99 694.434 18 694.434 18.01 -761.672 18.02 -739.989 18.03 -674.664 18.04 -655.458 18.05 -682.504 18.06 -714.782 18.07 -723.087 18.08 -718.923 18.09 -714.782 18.1 -706.572 18.11 -686.457 18.12 -678.573 18.13 -682.504 18.14 -694.434 18.15 -694.434 18.16 -690.434 18.17 -690.434 18.18 -690.434 18.19 -694.434 18.2 -694.434 18.21 -694.434 18.22 -694.434 18.23 -698.456 18.24 -694.434 18.25 -686.457 18.26 -686.457 18.27 -694.434 18.28 -698.456 18.29 -690.434 18.3 -682.504 18.31 -682.504 18.32 -690.434 18.33 -694.434 18.34 -694.434 18.35 -694.434 18.36 -694.434 18.37 -698.456 18.38 -690.434 18.39 -690.434 18.4 -690.434 18.41 -694.434 18.42 -694.434 18.43 -694.434 18.44 -690.434 18.45 -694.434 18.46 -694.434 18.47 -690.434 18.48 -686.457 18.49 -686.457 18.5 -690.434 18.51 -694.434 18.52 -694.434 18.53 -694.434 18.54 -698.456 18.55 -698.456 18.56 -694.434 18.57 -690.434 18.58 -686.457 18.59 -694.434 18.6 -698.456 18.61 -686.457 18.62 -682.504 18.63 -682.504 18.64 -698.456 18.65 -694.434 18.66 -686.457 18.67 -694.434 18.68 -698.456 18.69 -698.456 18.7 -690.434 18.71 -690.434 18.72 -694.434 18.73 -694.434 18.74 -694.434 18.75 -702.503 18.76 -698.456 18.77 -682.504 18.78 -674.664 18.79 -880 18.8 -880 18.81 -880 18.82 -880 18.83 -880 18.84 -880 18.85 -880 18.86 -880 18.87 -880 18.88 -880 18.89 -880 18.9 -880 18.91 -880 18.92 -880 18.93 -698.456 18.94 -678.573 18.95 -678.573 18.96 -694.434 18.97 -718.923 18.98 -710.665 18.99 -714.782 19 -710.665 19.01 -698.456 19.02 -686.457 19.03 -682.504 19.04 -678.573 19.05 -678.573 19.06 -694.434 19.07 -678.573 19.08 -880 19.09 -880 19.1 -880 19.11 -880 19.12 -880 19.13 -880 19.14 -880 19.15 -880 19.16 -880 19.17 -880 19.18 -880 mir_eval-0.8.2/tests/data/melody/est06.txt000077500000000000000000000533341475740344600204160ustar00rootroot000000000000000 0 0.01 0 0.02 -663.074 0.03 -663.074 0.04 -663.074 0.05 -663.074 0.06 -663.074 0.07 -663.074 0.08 -659.255 0.09 -663.074 0.1 -659.255 0.11 -655.458 0.12 -659.255 0.13 -647.93 0.14 -640.487 0.15 -655.458 0.16 -655.458 0.17 -655.458 0.18 -651.683 0.19 -651.683 0.2 -655.458 0.21 -663.074 0.22 666.915 0.23 670.779 0.24 666.915 0.25 663.074 0.26 644.198 0.27 618.67 0.28 597.596 0.29 580.583 0.3 577.24 0.31 583.947 0.32 594.154 0.33 625.859 0.34 651.683 0.35 674.664 0.36 682.504 0.37 678.573 0.38 663.074 0.39 655.458 0.4 629.484 0.41 -663.074 0.42 -666.915 0.43 -666.915 0.44 -663.074 0.45 -666.915 0.46 -666.915 0.47 -663.074 0.48 -663.074 0.49 -670.779 0.5 -666.915 0.51 -880 0.52 577.24 0.53 597.596 0.54 618.67 0.55 625.859 0.56 636.798 0.57 633.131 0.58 622.254 0.59 608.042 0.6 583.947 0.61 567.323 0.62 557.577 0.63 554.365 0.64 564.055 0.65 573.915 0.66 590.732 0.67 611.564 0.68 629.484 0.69 647.93 0.7 659.255 0.71 659.255 0.72 651.683 0.73 636.798 0.74 618.67 0.75 601.058 0.76 577.24 0.77 570.609 0.78 564.055 0.79 570.609 0.8 587.33 0.81 608.042 0.82 636.798 0.83 666.915 0.84 686.457 0.85 694.434 0.86 698.456 0.87 686.457 0.88 678.573 0.89 659.255 0.9 640.487 0.91 618.67 0.92 611.564 0.93 608.042 0.94 611.564 0.95 625.859 0.96 644.198 0.97 674.664 0.98 698.456 0.99 702.503 1 690.434 1.01 -440 1.02 -440 1.03 -666.915 1.04 -629.484 1.05 -666.915 1.06 -678.573 1.07 -666.915 1.08 -670.779 1.09 -666.915 1.1 -659.255 1.11 -659.255 1.12 -659.255 1.13 -670.779 1.14 -440 1.15 -440 1.16 -440 1.17 -440 1.18 761.672 1.19 748.587 1.2 723.087 1.21 714.782 1.22 698.456 1.23 698.456 1.24 698.456 1.25 702.503 1.26 710.665 1.27 735.727 1.28 766.084 1.29 783.991 1.3 793.1 1.31 788.532 1.32 766.084 1.33 744.276 1.34 706.572 1.35 690.434 1.36 663.074 1.37 655.458 1.38 659.255 1.39 666.915 1.4 674.664 1.41 694.434 1.42 714.782 1.43 731.489 1.44 735.727 1.45 735.727 1.46 718.923 1.47 710.665 1.48 666.915 1.49 625.859 1.5 594.154 1.51 590.732 1.52 594.154 1.53 611.564 1.54 636.798 1.55 647.93 1.56 666.915 1.57 674.664 1.58 682.504 1.59 682.504 1.6 674.664 1.61 651.683 1.62 633.131 1.63 608.042 1.64 597.596 1.65 594.154 1.66 604.54 1.67 618.67 1.68 644.198 1.69 663.074 1.7 670.779 1.71 670.779 1.72 659.255 1.73 636.798 1.74 625.859 1.75 -440 1.76 698.456 1.77 655.458 1.78 670.779 1.79 670.779 1.8 647.93 1.81 622.254 1.82 611.564 1.83 615.107 1.84 640.487 1.85 647.93 1.86 644.198 1.87 644.198 1.88 629.484 1.89 618.67 1.9 594.154 1.91 577.24 1.92 567.323 1.93 560.807 1.94 564.055 1.95 573.915 1.96 587.33 1.97 601.058 1.98 618.67 1.99 636.798 2 644.198 2.01 651.683 2.02 644.198 2.03 633.131 2.04 615.107 2.05 -440 2.06 -440 2.07 -440 2.08 597.596 2.09 611.564 2.1 633.131 2.11 659.255 2.12 682.504 2.13 694.434 2.14 698.456 2.15 690.434 2.16 666.915 2.17 659.255 2.18 636.798 2.19 -440 2.2 -440 2.21 -440 2.22 -440 2.23 -440 2.24 -440 2.25 -440 2.26 -440 2.27 -440 2.28 -440 2.29 -440 2.3 -440 2.31 -440 2.32 -440 2.33 -440 2.34 -440 2.35 -440 2.36 -440 2.37 608.042 2.38 608.042 2.39 615.107 2.4 622.254 2.41 622.254 2.42 625.859 2.43 622.254 2.44 608.042 2.45 590.732 2.46 573.915 2.47 560.807 2.48 551.172 2.49 547.998 2.5 554.365 2.51 567.323 2.52 583.947 2.53 597.596 2.54 604.54 2.55 611.564 2.56 615.107 2.57 611.564 2.58 594.154 2.59 573.915 2.6 544.842 2.61 -440 2.62 -440 2.63 -440 2.64 415.305 2.65 437.466 2.66 463.479 2.67 488.211 2.68 493.883 2.69 502.516 2.7 505.427 2.71 505.427 2.72 499.622 2.73 493.883 2.74 485.399 2.75 477.06 2.76 471.58 2.77 468.864 2.78 474.312 2.79 477.06 2.8 488.211 2.81 496.744 2.82 508.355 2.83 511.3 2.84 514.262 2.85 514.262 2.86 505.427 2.87 491.039 2.88 482.603 2.89 -440 2.9 -440 2.91 -440 2.92 -440 2.93 -440 2.94 -440 2.95 -440 2.96 -440 2.97 557.577 2.98 570.609 2.99 577.24 3 580.583 3.01 573.915 3.02 570.609 3.03 557.577 3.04 544.842 3.05 532.397 3.06 529.331 3.07 526.282 3.08 526.282 3.09 532.397 3.1 544.842 3.11 560.807 3.12 577.24 3.13 587.33 3.14 590.732 3.15 594.154 3.16 594.154 3.17 583.947 3.18 570.609 3.19 554.365 3.2 535.482 3.21 523.251 3.22 514.262 3.23 517.241 3.24 523.251 3.25 538.584 3.26 557.577 3.27 583.947 3.28 597.596 3.29 611.564 3.3 611.564 3.31 608.042 3.32 590.732 3.33 573.915 3.34 538.584 3.35 541.704 3.36 554.365 3.37 551.172 3.38 551.172 3.39 554.365 3.4 551.172 3.41 554.365 3.42 557.577 3.43 554.365 3.44 551.172 3.45 554.365 3.46 560.807 3.47 557.577 3.48 554.365 3.49 557.577 3.5 557.577 3.51 557.577 3.52 557.577 3.53 554.365 3.54 554.365 3.55 551.172 3.56 554.365 3.57 554.365 3.58 557.577 3.59 554.365 3.6 547.998 3.61 557.577 3.62 567.323 3.63 583.947 3.64 587.33 3.65 580.583 3.66 567.323 3.67 551.172 3.68 538.584 3.69 554.365 3.7 557.577 3.71 557.577 3.72 554.365 3.73 547.998 3.74 538.584 3.75 551.172 3.76 567.323 3.77 590.732 3.78 597.596 3.79 601.058 3.8 601.058 3.81 587.33 3.82 577.24 3.83 554.365 3.84 535.482 3.85 551.172 3.86 554.365 3.87 554.365 3.88 554.365 3.89 544.842 3.9 541.704 3.91 557.577 3.92 583.947 3.93 597.596 3.94 608.042 3.95 611.564 3.96 608.042 3.97 597.596 3.98 567.323 3.99 -666.915 4 -663.074 4.01 -659.255 4.02 -663.074 4.03 -666.915 4.04 -666.915 4.05 -663.074 4.06 -663.074 4.07 -663.074 4.08 -659.255 4.09 -663.074 4.1 -663.074 4.11 -659.255 4.12 -663.074 4.13 -659.255 4.14 -659.255 4.15 -659.255 4.16 -663.074 4.17 -659.255 4.18 -663.074 4.19 -663.074 4.2 -663.074 4.21 -663.074 4.22 -666.915 4.23 -666.915 4.24 -666.915 4.25 -663.074 4.26 -663.074 4.27 -663.074 4.28 -663.074 4.29 -659.255 4.3 -659.255 4.31 -663.074 4.32 -663.074 4.33 -663.074 4.34 -663.074 4.35 -659.255 4.36 -663.074 4.37 -663.074 4.38 -663.074 4.39 -663.074 4.4 -663.074 4.41 -666.915 4.42 -663.074 4.43 -666.915 4.44 -622.254 4.45 -659.255 4.46 -663.074 4.47 -659.255 4.48 -663.074 4.49 -663.074 4.5 -663.074 4.51 -663.074 4.52 -659.255 4.53 -659.255 4.54 -663.074 4.55 -659.255 4.56 -659.255 4.57 -659.255 4.58 -655.458 4.59 -659.255 4.6 -659.255 4.61 -659.255 4.62 -663.074 4.63 -659.255 4.64 -659.255 4.65 -663.074 4.66 -659.255 4.67 -659.255 4.68 -663.074 4.69 -663.074 4.7 -663.074 4.71 -666.915 4.72 -663.074 4.73 -666.915 4.74 -666.915 4.75 -659.255 4.76 -666.915 4.77 -663.074 4.78 -659.255 4.79 -659.255 4.8 -659.255 4.81 -655.458 4.82 -659.255 4.83 -659.255 4.84 -659.255 4.85 -663.074 4.86 -663.074 4.87 -663.074 4.88 -666.915 4.89 -666.915 4.9 -659.255 4.91 -663.074 4.92 -666.915 4.93 -666.915 4.94 -659.255 4.95 -651.683 4.96 -663.074 4.97 -663.074 4.98 -659.255 4.99 -655.458 5 -659.255 5.01 -663.074 5.02 -659.255 5.03 -659.255 5.04 -663.074 5.05 -659.255 5.06 -663.074 5.07 -659.255 5.08 -659.255 5.09 -659.255 5.1 -663.074 5.11 -663.074 5.12 -663.074 5.13 -663.074 5.14 -663.074 5.15 -666.915 5.16 -666.915 5.17 -663.074 5.18 -663.074 5.19 -666.915 5.2 -659.255 5.21 -651.683 5.22 -659.255 5.23 -663.074 5.24 -655.458 5.25 -666.915 5.26 -663.074 5.27 -670.779 5.28 -670.779 5.29 -655.458 5.3 -670.779 5.31 -670.779 5.32 -659.255 5.33 -666.915 5.34 -666.915 5.35 -666.915 5.36 -659.255 5.37 -659.255 5.38 -659.255 5.39 -655.458 5.4 -659.255 5.41 -659.255 5.42 -655.458 5.43 -663.074 5.44 -663.074 5.45 -659.255 5.46 640.487 5.47 647.93 5.48 655.458 5.49 651.683 5.5 647.93 5.51 647.93 5.52 651.683 5.53 647.93 5.54 647.93 5.55 651.683 5.56 651.683 5.57 655.458 5.58 655.458 5.59 659.255 5.6 659.255 5.61 655.458 5.62 647.93 5.63 644.198 5.64 644.198 5.65 644.198 5.66 647.93 5.67 647.93 5.68 655.458 5.69 659.255 5.7 670.779 5.71 674.664 5.72 682.504 5.73 682.504 5.74 678.573 5.75 674.664 5.76 655.458 5.77 640.487 5.78 629.484 5.79 615.107 5.8 611.564 5.81 618.67 5.82 625.859 5.83 640.487 5.84 666.915 5.85 686.457 5.86 702.503 5.87 714.782 5.88 718.923 5.89 718.923 5.9 710.665 5.91 694.434 5.92 659.255 5.93 625.859 5.94 597.596 5.95 587.33 5.96 587.33 5.97 601.058 5.98 622.254 5.99 659.255 6 678.573 6.01 698.456 6.02 710.665 6.03 706.572 6.04 698.456 6.05 698.456 6.06 706.572 6.07 710.665 6.08 659.255 6.09 706.572 6.1 718.923 6.11 710.665 6.12 702.503 6.13 690.434 6.14 655.458 6.15 -880 6.16 690.434 6.17 690.434 6.18 666.915 6.19 659.255 6.2 666.915 6.21 674.664 6.22 670.779 6.23 659.255 6.24 644.198 6.25 615.107 6.26 597.596 6.27 594.154 6.28 594.154 6.29 601.058 6.3 622.254 6.31 640.487 6.32 663.074 6.33 682.504 6.34 694.434 6.35 694.434 6.36 682.504 6.37 678.573 6.38 674.664 6.39 663.074 6.4 647.93 6.41 647.93 6.42 644.198 6.43 647.93 6.44 655.458 6.45 666.915 6.46 682.504 6.47 686.457 6.48 690.434 6.49 686.457 6.5 674.664 6.51 663.074 6.52 659.255 6.53 640.487 6.54 629.484 6.55 674.664 6.56 690.434 6.57 678.573 6.58 651.683 6.59 659.255 6.6 674.664 6.61 678.573 6.62 682.504 6.63 678.573 6.64 666.915 6.65 682.504 6.66 694.434 6.67 670.779 6.68 -880 6.69 -880 6.7 -880 6.71 -880 6.72 -880 6.73 629.484 6.74 629.484 6.75 633.131 6.76 636.798 6.77 640.487 6.78 625.859 6.79 615.107 6.8 597.596 6.81 587.33 6.82 577.24 6.83 577.24 6.84 580.583 6.85 590.732 6.86 597.596 6.87 615.107 6.88 629.484 6.89 640.487 6.9 655.458 6.91 659.255 6.92 663.074 6.93 655.458 6.94 640.487 6.95 625.859 6.96 601.058 6.97 583.947 6.98 577.24 6.99 577.24 7 580.583 7.01 590.732 7.02 608.042 7.03 629.484 7.04 651.683 7.05 666.915 7.06 674.664 7.07 682.504 7.08 682.504 7.09 678.573 7.1 666.915 7.11 651.683 7.12 633.131 7.13 625.859 7.14 622.254 7.15 618.67 7.16 629.484 7.17 640.487 7.18 644.198 7.19 611.564 7.2 608.042 7.21 629.484 7.22 -659.255 7.23 -659.255 7.24 -663.074 7.25 -666.915 7.26 -663.074 7.27 587.33 7.28 590.732 7.29 580.583 7.3 583.947 7.31 583.947 7.32 583.947 7.33 604.54 7.34 594.154 7.35 580.583 7.36 583.947 7.37 590.732 7.38 594.154 7.39 594.154 7.4 594.154 7.41 590.732 7.42 587.33 7.43 587.33 7.44 583.947 7.45 573.915 7.46 560.807 7.47 554.365 7.48 573.915 7.49 583.947 7.5 594.154 7.51 601.058 7.52 611.564 7.53 611.564 7.54 611.564 7.55 608.042 7.56 597.596 7.57 587.33 7.58 570.609 7.59 557.577 7.6 554.365 7.61 554.365 7.62 560.807 7.63 590.732 7.64 604.54 7.65 625.859 7.66 644.198 7.67 663.074 7.68 670.779 7.69 674.664 7.7 674.664 7.71 674.664 7.72 663.074 7.73 651.683 7.74 629.484 7.75 615.107 7.76 604.54 7.77 597.596 7.78 597.596 7.79 611.564 7.8 633.131 7.81 651.683 7.82 670.779 7.83 674.664 7.84 678.573 7.85 655.458 7.86 -440 7.87 -440 7.88 -663.074 7.89 -655.458 7.9 -663.074 7.91 -659.255 7.92 -659.255 7.93 -663.074 7.94 -663.074 7.95 -663.074 7.96 -670.779 7.97 -666.915 7.98 -666.915 7.99 -666.915 8 -663.074 8.01 -663.074 8.02 -663.074 8.03 678.573 8.04 682.504 8.05 686.457 8.06 694.434 8.07 690.434 8.08 666.915 8.09 640.487 8.1 608.042 8.11 590.732 8.12 577.24 8.13 573.915 8.14 583.947 8.15 601.058 8.16 625.859 8.17 659.255 8.18 686.457 8.19 710.665 8.2 718.923 8.21 723.087 8.22 718.923 8.23 710.665 8.24 682.504 8.25 655.458 8.26 618.67 8.27 597.596 8.28 577.24 8.29 570.609 8.3 577.24 8.31 594.154 8.32 622.254 8.33 644.198 8.34 663.074 8.35 678.573 8.36 682.504 8.37 674.664 8.38 655.458 8.39 615.107 8.4 594.154 8.41 -659.255 8.42 452.893 8.43 447.691 8.44 468.864 8.45 502.516 8.46 532.397 8.47 551.172 8.48 564.055 8.49 567.323 8.5 570.609 8.51 580.583 8.52 560.807 8.53 554.365 8.54 560.807 8.55 554.365 8.56 538.584 8.57 538.584 8.58 547.998 8.59 560.807 8.6 560.807 8.61 560.807 8.62 554.365 8.63 544.842 8.64 554.365 8.65 554.365 8.66 535.482 8.67 554.365 8.68 551.172 8.69 557.577 8.7 564.055 8.71 554.365 8.72 557.577 8.73 560.807 8.74 564.055 8.75 557.577 8.76 544.842 8.77 526.282 8.78 505.427 8.79 485.399 8.8 -440 8.81 -440 8.82 -440 8.83 -440 8.84 -440 8.85 -440 8.86 -440 8.87 -440 8.88 -440 8.89 -440 8.9 -440 8.91 -440 8.92 -440 8.93 -440 8.94 -440 8.95 -440 8.96 -440 8.97 -440 8.98 -440 8.99 -440 9 -440 9.01 -440 9.02 -440 9.03 -440 9.04 -440 9.05 -440 9.06 -440 9.07 -597.596 9.08 -601.058 9.09 -594.154 9.1 -580.583 9.11 -544.842 9.12 -532.397 9.13 -517.241 9.14 -517.241 9.15 -529.331 9.16 -547.998 9.17 -560.807 9.18 -573.915 9.19 -583.947 9.2 -587.33 9.21 -583.947 9.22 -580.583 9.23 -440 9.24 -440 9.25 -440 9.26 -440 9.27 -440 9.28 -440 9.29 -440 9.3 -440 9.31 -440 9.32 -440 9.33 -440 9.34 -440 9.35 -440 9.36 -440 9.37 -440 9.38 -440 9.39 -440 9.4 -440 9.41 508.355 9.42 511.3 9.43 520.237 9.44 523.251 9.45 526.282 9.46 523.251 9.47 508.355 9.48 493.883 9.49 474.312 9.5 468.864 9.51 468.864 9.52 477.06 9.53 485.399 9.54 499.622 9.55 511.3 9.56 532.397 9.57 541.704 9.58 547.998 9.59 551.172 9.6 544.842 9.61 532.397 9.62 523.251 9.63 505.427 9.64 493.883 9.65 477.06 9.66 477.06 9.67 488.211 9.68 502.516 9.69 523.251 9.7 547.998 9.71 573.915 9.72 594.154 9.73 597.596 9.74 597.596 9.75 594.154 9.76 577.24 9.77 567.323 9.78 538.584 9.79 523.251 9.8 514.262 9.81 508.355 9.82 505.427 9.83 511.3 9.84 508.355 9.85 493.883 9.86 493.883 9.87 499.622 9.88 502.516 9.89 493.883 9.9 496.744 9.91 505.427 9.92 505.427 9.93 502.516 9.94 499.622 9.95 496.744 9.96 493.883 9.97 496.744 9.98 496.744 9.99 496.744 10 496.744 10.01 420.13 10.02 445.113 10.03 460.809 10.04 477.06 10.05 493.883 10.06 505.427 10.07 508.355 10.08 508.355 10.09 505.427 10.1 496.744 10.11 491.039 10.12 479.823 10.13 468.864 10.14 463.479 10.15 463.479 10.16 471.58 10.17 482.603 10.18 491.039 10.19 502.516 10.2 511.3 10.21 520.237 10.22 526.282 10.23 526.282 10.24 523.251 10.25 520.237 10.26 505.427 10.27 496.744 10.28 477.06 10.29 460.809 10.3 474.312 10.31 485.399 10.32 499.622 10.33 517.241 10.34 538.584 10.35 560.807 10.36 577.24 10.37 583.947 10.38 587.33 10.39 583.947 10.4 580.583 10.41 554.365 10.42 541.704 10.43 526.282 10.44 511.3 10.45 505.427 10.46 505.427 10.47 511.3 10.48 535.482 10.49 551.172 10.5 573.915 10.51 580.583 10.52 580.583 10.53 580.583 10.54 -351.251 10.55 -351.251 10.56 -351.251 10.57 -351.251 10.58 -351.251 10.59 -353.286 10.6 -351.251 10.61 -351.251 10.62 -353.286 10.63 -351.251 10.64 -351.251 10.65 -353.286 10.66 -353.286 10.67 -351.251 10.68 -353.286 10.69 -351.251 10.7 -351.251 10.71 557.577 10.72 570.609 10.73 580.583 10.74 580.583 10.75 573.915 10.76 564.055 10.77 544.842 10.78 535.482 10.79 523.251 10.8 505.427 10.81 505.427 10.82 508.355 10.83 523.251 10.84 541.704 10.85 554.365 10.86 580.583 10.87 587.33 10.88 594.154 10.89 597.596 10.9 594.154 10.91 583.947 10.92 570.609 10.93 544.842 10.94 529.331 10.95 505.427 10.96 499.622 10.97 502.516 10.98 511.3 10.99 526.282 11 544.842 11.01 560.807 11.02 577.24 11.03 580.583 11.04 573.915 11.05 567.323 11.06 547.998 11.07 502.516 11.08 445.113 11.09 422.564 11.1 405.819 11.11 401.158 11.12 412.913 11.13 427.474 11.14 437.466 11.15 442.549 11.16 445.113 11.17 442.549 11.18 445.113 11.19 447.691 11.2 427.474 11.21 403.482 11.22 410.535 11.23 415.305 11.24 408.17 11.25 410.535 11.26 432.441 11.27 445.113 11.28 450.285 11.29 463.479 11.3 466.164 11.31 460.809 11.32 447.691 11.33 445.113 11.34 442.549 11.35 445.113 11.36 445.113 11.37 440 11.38 442.549 11.39 445.113 11.4 440 11.41 420.13 11.42 429.95 11.43 442.549 11.44 455.517 11.45 466.164 11.46 468.864 11.47 458.155 11.48 442.549 11.49 420.13 11.5 398.847 11.51 -440 11.52 -440 11.53 -440 11.54 -440 11.55 -440 11.56 -440 11.57 -440 11.58 -440 11.59 -440 11.6 -440 11.61 -440 11.62 -440 11.63 -440 11.64 -440 11.65 -440 11.66 -440 11.67 -440 11.68 -440 11.69 -440 11.7 -440 11.71 -440 11.72 -440 11.73 -440 11.74 -440 11.75 -440 11.76 -440 11.77 -440 11.78 -440 11.79 -440 11.8 -440 11.81 -398.847 11.82 -412.913 11.83 -437.466 11.84 -452.893 11.85 -460.809 11.86 -458.155 11.87 -445.113 11.88 -440 11.89 -437.466 11.9 -440 11.91 -442.549 11.92 -450.285 11.93 -460.809 11.94 -479.823 11.95 -485.399 11.96 -491.039 11.97 -488.211 11.98 -482.603 11.99 -468.864 12 -460.809 12.01 -450.285 12.02 -437.466 12.03 -440 12.04 -440 12.05 -440 12.06 -440 12.07 -440 12.08 -440 12.09 -440 12.1 -440 12.11 -440 12.12 -440 12.13 -440 12.14 -440 12.15 -440 12.16 -440 12.17 -440 12.18 -440 12.19 -440 12.2 -440 12.21 -440 12.22 -440 12.23 -440 12.24 405.819 12.25 412.913 12.26 417.711 12.27 422.564 12.28 420.13 12.29 410.535 12.3 398.847 12.31 385.261 12.32 374.294 12.33 365.745 12.34 363.638 12.35 369.994 12.36 380.836 12.37 394.266 12.38 408.17 12.39 427.474 12.4 437.466 12.41 442.549 12.42 440 12.43 432.441 12.44 420.13 12.45 408.17 12.46 394.266 12.47 380.836 12.48 367.863 12.49 363.638 12.5 369.994 12.51 378.643 12.52 396.55 12.53 408.17 12.54 425.012 12.55 445.113 12.56 460.809 12.57 471.58 12.58 471.58 12.59 463.479 12.6 458.155 12.61 442.549 12.62 427.474 12.63 415.305 12.64 401.158 12.65 398.847 12.66 403.482 12.67 408.17 12.68 417.711 12.69 432.441 12.7 445.113 12.71 447.691 12.72 442.549 12.73 434.946 12.74 437.466 12.75 450.285 12.76 445.113 12.77 440 12.78 432.441 12.79 408.17 12.8 405.819 12.81 417.711 12.82 408.17 12.83 403.482 12.84 389.738 12.85 391.995 12.86 394.266 12.87 394.266 12.88 396.55 12.89 394.266 12.9 396.55 12.91 391.995 12.92 389.738 12.93 387.493 12.94 387.493 12.95 387.493 12.96 389.738 12.97 391.995 12.98 394.266 12.99 396.55 13 398.847 13.01 403.482 13.02 403.482 13.03 398.847 13.04 394.266 13.05 391.995 13.06 387.493 13.07 385.261 13.08 385.261 13.09 380.836 13.1 380.836 13.11 385.261 13.12 387.493 13.13 389.738 13.14 391.995 13.15 396.55 13.16 398.847 13.17 403.482 13.18 405.819 13.19 408.17 13.2 401.158 13.21 398.847 13.22 387.493 13.23 394.266 13.24 396.55 13.25 396.55 13.26 389.738 13.27 387.493 13.28 385.261 13.29 394.266 13.3 396.55 13.31 391.995 13.32 389.738 13.33 394.266 13.34 455.517 13.35 445.113 13.36 437.466 13.37 408.17 13.38 408.17 13.39 425.012 13.4 403.482 13.41 408.17 13.42 437.466 13.43 442.549 13.44 450.285 13.45 460.809 13.46 466.164 13.47 455.517 13.48 447.691 13.49 445.113 13.5 440 13.51 440 13.52 440 13.53 442.549 13.54 440 13.55 440 13.56 440 13.57 440 13.58 442.549 13.59 440 13.6 442.549 13.61 440 13.62 442.549 13.63 440 13.64 440 13.65 442.549 13.66 442.549 13.67 440 13.68 440 13.69 442.549 13.7 442.549 13.71 445.113 13.72 445.113 13.73 445.113 13.74 442.549 13.75 440 13.76 437.466 13.77 432.441 13.78 432.441 13.79 440 13.8 445.113 13.81 437.466 13.82 440 13.83 442.549 13.84 445.113 13.85 437.466 13.86 442.549 13.87 445.113 13.88 440 13.89 442.549 13.9 447.691 13.91 445.113 13.92 437.466 13.93 432.441 13.94 442.549 13.95 445.113 13.96 425.012 13.97 410.535 13.98 429.95 13.99 437.466 14 442.549 14.01 447.691 14.02 450.285 14.03 450.285 14.04 445.113 14.05 440 14.06 432.441 14.07 415.305 14.08 408.17 14.09 398.847 14.1 385.261 14.11 376.462 14.12 369.994 14.13 361.544 14.14 -440 14.15 -437.466 14.16 -437.466 14.17 -442.549 14.18 -345.217 14.19 -361.544 14.2 -367.863 14.21 -376.462 14.22 -442.549 14.23 -442.549 14.24 -442.549 14.25 -440 14.26 -442.549 14.27 -440 14.28 -442.549 14.29 -442.549 14.3 -442.549 14.31 -442.549 14.32 -442.549 14.33 -440 14.34 -442.549 14.35 -440 14.36 -442.549 14.37 -440 14.38 -442.549 14.39 -442.549 14.4 -440 14.41 -440 14.42 -440 14.43 -440 14.44 -440 14.45 -440 14.46 -440 14.47 -440 14.48 -440 14.49 -440 14.5 -440 14.51 -440 14.52 -440 14.53 -440 14.54 -440 14.55 -440 14.56 -440 14.57 -440 14.58 -440 14.59 -440 14.6 372.138 14.61 376.462 14.62 378.643 14.63 376.462 14.64 372.138 14.65 369.994 14.66 363.638 14.67 357.391 14.68 357.391 14.69 361.544 14.7 363.638 14.71 365.745 14.72 372.138 14.73 374.294 14.74 378.643 14.75 380.836 14.76 385.261 14.77 383.042 14.78 383.042 14.79 378.643 14.8 369.994 14.81 359.461 14.82 351.251 14.83 345.217 14.84 347.217 14.85 343.229 14.86 343.229 14.87 349.228 14.88 359.461 14.89 372.138 14.9 385.261 14.91 385.261 14.92 389.738 14.93 391.995 14.94 391.995 14.95 387.493 14.96 376.462 14.97 369.994 14.98 351.251 14.99 351.251 15 343.229 15.01 339.286 15.02 341.252 15.03 365.745 15.04 367.863 15.05 372.138 15.06 376.462 15.07 383.042 15.08 396.55 15.09 396.55 15.1 389.738 15.11 378.643 15.12 372.138 15.13 363.638 15.14 -442.549 15.15 -440 15.16 -437.466 15.17 -440 15.18 -440 15.19 -440 15.2 -440 15.21 -442.549 15.22 -442.549 15.23 -440 15.24 -442.549 15.25 -447.691 15.26 -440 15.27 -440 15.28 -442.549 15.29 -455.517 15.3 -442.549 15.31 -440 15.32 -440 15.33 -440 15.34 -440 15.35 -440 15.36 -440 15.37 -440 15.38 -440 15.39 -440 15.4 -440 15.41 -440 15.42 -440 15.43 -440 15.44 -440 15.45 -440 15.46 -440 15.47 -440 15.48 -440 15.49 -440 15.5 -440 15.51 -440 15.52 -440 15.53 -440 15.54 -440 15.55 -440 15.56 -440 15.57 -440 15.58 -440 15.59 -440 15.6 -440 15.61 -440 15.62 -440 15.63 -440 15.64 -440 15.65 -440 15.66 -440 15.67 -440 15.68 -440 15.69 -440 15.7 -440 15.71 -440 15.72 -440 15.73 -440 15.74 -440 15.75 -440 15.76 -440 15.77 -440 15.78 -440 15.79 -440 15.8 -440 15.81 -440 15.82 -440 15.83 -440 15.84 -440 15.85 -440 15.86 -440 15.87 -440 15.88 -440 15.89 -440 15.9 -440 15.91 -440 15.92 -440 15.93 -440 15.94 -440 15.95 -440 15.96 -440 15.97 -440 15.98 -440 15.99 -440 16 -440 16.01 -440 16.02 -440 16.03 -440 16.04 -440 16.05 -440 16.06 -440 16.07 -440 16.08 -440 mir_eval-0.8.2/tests/data/melody/est07.txt000077500000000000000000000657321475740344600204240ustar00rootroot000000000000000 0 0.01 0 0.02 -220 0.03 -218.733 0.04 -220 0.05 -220 0.06 -220 0.07 -220 0.08 -221.274 0.09 -221.274 0.1 -221.274 0.11 -221.274 0.12 -220 0.13 -220 0.14 -220 0.15 -220 0.16 -220 0.17 -218.733 0.18 -218.733 0.19 -220 0.2 -221.274 0.21 -220 0.22 -220 0.23 -220 0.24 -221.274 0.25 -218.733 0.26 -223.846 0.27 -221.274 0.28 -217.473 0.29 -214.975 0.3 -214.975 0.31 -214.975 0.32 -218.733 0.33 -220 0.34 -220 0.35 -220 0.36 -220 0.37 -220 0.38 -220 0.39 -221.274 0.4 -221.274 0.41 -254.178 0.42 -246.942 0.43 -242.699 0.44 -242.699 0.45 -233.082 0.46 -229.078 0.47 -222.556 0.48 -217.473 0.49 -217.473 0.5 -221.274 0.51 -222.556 0.52 -218.733 0.53 -221.274 0.54 -222.556 0.55 -222.556 0.56 -222.556 0.57 -222.556 0.58 -222.556 0.59 -222.556 0.6 -218.733 0.61 -207.652 0.62 -201.741 0.63 -200.579 0.64 -200.579 0.65 -201.741 0.66 -204.085 0.67 -220 0.68 -220 0.69 -220 0.7 -220 0.71 -220 0.72 -220 0.73 -220 0.74 -220 0.75 -220 0.76 -220 0.77 -220 0.78 -220 0.79 -220 0.8 -220 0.81 -220 0.82 -220 0.83 -220 0.84 -220 0.85 -220 0.86 -220 0.87 -220 0.88 -220 0.89 -220 0.9 -220 0.91 -220 0.92 -220 0.93 -220 0.94 -220 0.95 -220 0.96 -269.292 0.97 -261.626 0.98 -255.65 0.99 -252.714 1 -251.258 1.01 -249.811 1.02 -246.942 1.03 -244.105 1.04 -241.301 1.05 -239.912 1.06 -239.912 1.07 -220 1.08 -220 1.09 -220 1.1 -220 1.11 -220 1.12 -220 1.13 -220 1.14 -220 1.15 -220 1.16 322.099 1.17 305.782 1.18 295.366 1.19 290.292 1.2 286.957 1.21 282.028 1.22 280.403 1.23 280.403 1.24 280.403 1.25 282.028 1.26 282.028 1.27 -220 1.28 -220 1.29 -220 1.3 -220 1.31 -220 1.32 -220 1.33 -220 1.34 -220 1.35 343.229 1.36 331.537 1.37 327.729 1.38 322.099 1.39 316.565 1.4 312.929 1.41 305.782 1.42 302.27 1.43 297.077 1.44 295.366 1.45 295.366 1.46 297.077 1.47 297.077 1.48 297.077 1.49 295.366 1.5 293.665 1.51 291.973 1.52 290.292 1.53 272.421 1.54 263.141 1.55 263.141 1.56 261.626 1.57 272.421 1.58 277.183 1.59 275.586 1.6 277.183 1.61 282.028 1.62 283.661 1.63 283.661 1.64 -220 1.65 -220 1.66 -220 1.67 -220 1.68 -220 1.69 -220 1.7 -220 1.71 -220 1.72 -220 1.73 -220 1.74 -220 1.75 235.79 1.76 231.739 1.77 227.758 1.78 234.432 1.79 249.811 1.8 254.178 1.81 248.372 1.82 242.699 1.83 229.078 1.84 220 1.85 208.855 1.86 197.133 1.87 191.521 1.88 183.932 1.89 179.731 1.9 180.772 1.91 188.231 1.92 200.579 1.93 211.282 1.94 220 1.95 226.446 1.96 227.758 1.97 227.758 1.98 223.846 1.99 217.473 2 210.065 2.01 202.91 2.02 197.133 2.03 198.275 2.04 201.741 2.05 206.456 2.06 205.267 2.07 207.652 2.08 213.737 2.09 217.473 2.1 220 2.11 221.274 2.12 220 2.13 214.975 2.14 211.282 2.15 210.065 2.16 208.855 2.17 207.652 2.18 210.065 2.19 213.737 2.2 214.975 2.21 212.506 2.22 207.652 2.23 200.579 2.24 192.631 2.25 186.069 2.26 -220 2.27 -220 2.28 -220 2.29 -220 2.3 -327.729 2.31 -335.389 2.32 -173.608 2.33 -181.819 2.34 -182.872 2.35 -178.696 2.36 -335.389 2.37 -325.841 2.38 -327.729 2.39 -331.537 2.4 -329.628 2.41 -329.628 2.42 -331.537 2.43 -333.458 2.44 -220 2.45 -220 2.46 -220 2.47 -220 2.48 -220 2.49 -220 2.5 -220 2.51 -220 2.52 -220 2.53 -220 2.54 -220 2.55 -220 2.56 -220 2.57 -220 2.58 -220 2.59 -220 2.6 -220 2.61 -220 2.62 -220 2.63 -220 2.64 -220 2.65 -220 2.66 -220 2.67 -220 2.68 -220 2.69 -220 2.7 -220 2.71 -220 2.72 -220 2.73 -220 2.74 -220 2.75 -220 2.76 -331.537 2.77 -333.458 2.78 -331.537 2.79 -329.628 2.8 -331.537 2.81 -331.537 2.82 -331.537 2.83 -331.537 2.84 -167.695 2.85 -168.666 2.86 -327.729 2.87 -323.965 2.88 -331.537 2.89 -331.537 2.9 -220 2.91 -220 2.92 -220 2.93 -220 2.94 -218.733 2.95 -225.142 2.96 -227.758 2.97 -223.846 2.98 -221.274 2.99 -214.975 3 -218.733 3.01 -220 3.02 -220 3.03 -220 3.04 -221.274 3.05 -221.274 3.06 -221.274 3.07 -221.274 3.08 -220 3.09 -218.733 3.1 -220 3.11 -222.556 3.12 -218.733 3.13 -216.221 3.14 -217.473 3.15 -220 3.16 -221.274 3.17 -221.274 3.18 -222.556 3.19 -221.274 3.2 -221.274 3.21 -221.274 3.22 -222.556 3.23 -218.733 3.24 -220 3.25 -221.274 3.26 -220 3.27 -221.274 3.28 -218.733 3.29 -220 3.3 -221.274 3.31 -220 3.32 -221.274 3.33 -220 3.34 -220 3.35 -221.274 3.36 -221.274 3.37 -220 3.38 -220 3.39 -220 3.4 -220 3.41 -220 3.42 -220 3.43 -220 3.44 -220 3.45 -220 3.46 -220 3.47 -220 3.48 -220 3.49 -220 3.5 -220 3.51 -220 3.52 -220 3.53 -220 3.54 -220 3.55 -220 3.56 -220 3.57 -220 3.58 -220 3.59 -220 3.6 -220 3.61 -220 3.62 -220 3.63 -220 3.64 -220 3.65 -220 3.66 -220 3.67 -220 3.68 -220 3.69 -220 3.7 -220 3.71 -220 3.72 -220 3.73 -220 3.74 -220 3.75 -220 3.76 -220 3.77 -220 3.78 -220 3.79 -220 3.8 -220 3.81 -220 3.82 -220 3.83 -220 3.84 -220 3.85 -220 3.86 -220 3.87 -220 3.88 -220 3.89 -220 3.9 -220 3.91 -220 3.92 -220 3.93 -220 3.94 -220 3.95 -220 3.96 280.403 3.97 277.183 3.98 272.421 3.99 269.292 4 261.626 4.01 251.258 4.02 238.53 4.03 231.739 4.04 225.142 4.05 223.846 4.06 229.078 4.07 234.432 4.08 246.942 4.09 254.178 4.1 260.119 4.11 -260.119 4.12 -260.119 4.13 -220 4.14 -220 4.15 280.403 4.16 275.586 4.17 267.741 4.18 263.141 4.19 255.65 4.2 251.258 4.21 248.372 4.22 245.519 4.23 246.942 4.24 251.258 4.25 257.131 4.26 -220 4.27 -220 4.28 -220 4.29 -220 4.3 -220 4.31 323.965 4.32 327.729 4.33 333.458 4.34 335.389 4.35 333.458 4.36 325.841 4.37 314.742 4.38 305.782 4.39 295.366 4.4 288.62 4.41 286.957 4.42 290.292 4.43 295.366 4.44 302.27 4.45 309.335 4.46 314.742 4.47 311.127 4.48 -297.077 4.49 -297.077 4.5 -298.798 4.51 -297.077 4.52 -293.665 4.53 -293.665 4.54 -295.366 4.55 -298.798 4.56 -297.077 4.57 -293.665 4.58 -283.661 4.59 -298.798 4.6 -297.077 4.61 -293.665 4.62 -280.403 4.63 -277.183 4.64 -282.028 4.65 -285.305 4.66 -288.62 4.67 -290.292 4.68 -220 4.69 -220 4.7 -220 4.71 -220 4.72 -220 4.73 -220 4.74 -220 4.75 -220 4.76 -220 4.77 -220 4.78 -220 4.79 -220 4.8 -220 4.81 -220 4.82 -220 4.83 -220 4.84 -220 4.85 -220 4.86 -220 4.87 -220 4.88 -220 4.89 -220 4.9 -220 4.91 -220 4.92 -220 4.93 -220 4.94 -440 4.95 -440 4.96 221.274 4.97 220 4.98 222.556 4.99 225.142 5 230.405 5.01 230.405 5.02 227.758 5.03 220 5.04 218.733 5.05 218.733 5.06 212.506 5.07 214.975 5.08 220 5.09 220 5.1 214.975 5.11 212.506 5.12 214.975 5.13 218.733 5.14 226.446 5.15 234.432 5.16 242.699 5.17 242.699 5.18 238.53 5.19 230.405 5.2 218.733 5.21 206.456 5.22 197.133 5.23 189.321 5.24 186.069 5.25 186.069 5.26 189.321 5.27 195.998 5.28 205.267 5.29 225.142 5.3 233.082 5.31 235.79 5.32 231.739 5.33 229.078 5.34 -440 5.35 -440 5.36 -440 5.37 -440 5.38 -331.537 5.39 -333.458 5.4 -335.389 5.41 -345.217 5.42 -339.286 5.43 -329.628 5.44 -325.841 5.45 -327.729 5.46 -329.628 5.47 -331.537 5.48 -331.537 5.49 -327.729 5.5 -335.389 5.51 -339.286 5.52 -341.252 5.53 -337.332 5.54 -339.286 5.55 -335.389 5.56 -333.458 5.57 -331.537 5.58 -331.537 5.59 -331.537 5.6 -329.628 5.61 -331.537 5.62 -440 5.63 -440 5.64 -440 5.65 -440 5.66 -440 5.67 -440 5.68 -440 5.69 -440 5.7 -440 5.71 -440 5.72 -440 5.73 -440 5.74 -440 5.75 -440 5.76 -440 5.77 -440 5.78 -440 5.79 -440 5.8 -440 5.81 -440 5.82 -440 5.83 -440 5.84 -440 5.85 -440 5.86 -440 5.87 -440 5.88 -440 5.89 -440 5.9 -440 5.91 -440 5.92 -440 5.93 -440 5.94 -440 5.95 -440 5.96 -440 5.97 -440 5.98 -440 5.99 -440 6 -440 6.01 -440 6.02 -440 6.03 -440 6.04 -440 6.05 -440 6.06 -440 6.07 -440 6.08 -440 6.09 -440 6.1 -440 6.11 -440 6.12 -440 6.13 -440 6.14 -440 6.15 -440 6.16 -440 6.17 -440 6.18 -440 6.19 -440 6.2 -440 6.21 -440 6.22 -440 6.23 -440 6.24 -440 6.25 -440 6.26 -440 6.27 -440 6.28 -440 6.29 -349.228 6.3 -349.228 6.31 -353.286 6.32 -357.391 6.33 -351.251 6.34 -345.217 6.35 -335.389 6.36 -329.628 6.37 -325.841 6.38 -322.099 6.39 -440 6.4 -440 6.41 -440 6.42 -440 6.43 -380.836 6.44 -387.493 6.45 -389.738 6.46 -391.995 6.47 -394.266 6.48 -394.266 6.49 -394.266 6.5 -391.995 6.51 -383.042 6.52 -378.643 6.53 -378.643 6.54 -380.836 6.55 -385.261 6.56 -387.493 6.57 -389.738 6.58 -387.493 6.59 -440 6.6 -440 6.61 -440 6.62 -440 6.63 412.913 6.64 422.564 6.65 420.13 6.66 415.305 6.67 412.913 6.68 415.305 6.69 415.305 6.7 415.305 6.71 415.305 6.72 417.711 6.73 415.305 6.74 410.535 6.75 408.17 6.76 415.305 6.77 417.711 6.78 429.95 6.79 434.946 6.8 440 6.81 440 6.82 447.691 6.83 455.517 6.84 471.58 6.85 474.312 6.86 477.06 6.87 471.58 6.88 468.864 6.89 460.809 6.9 452.893 6.91 445.113 6.92 442.549 6.93 440 6.94 440 6.95 440 6.96 422.564 6.97 427.474 6.98 442.549 6.99 442.549 7 442.549 7.01 252.714 7.02 252.714 7.03 251.258 7.04 249.811 7.05 248.372 7.06 246.942 7.07 246.942 7.08 246.942 7.09 245.519 7.1 245.519 7.11 245.519 7.12 245.519 7.13 246.942 7.14 248.372 7.15 251.258 7.16 257.131 7.17 269.292 7.18 277.183 7.19 282.028 7.2 286.957 7.21 288.62 7.22 290.292 7.23 290.292 7.24 290.292 7.25 -245.519 7.26 -248.372 7.27 -251.258 7.28 -248.372 7.29 -251.258 7.3 -244.105 7.31 -239.912 7.32 -241.301 7.33 -300.529 7.34 -304.021 7.35 -302.27 7.36 -304.021 7.37 -305.782 7.38 -309.335 7.39 -309.335 7.4 -307.553 7.41 -304.021 7.42 -302.27 7.43 601.058 7.44 601.058 7.45 594.154 7.46 590.732 7.47 583.947 7.48 583.947 7.49 583.947 7.5 583.947 7.51 587.33 7.52 590.732 7.53 594.154 7.54 597.596 7.55 597.596 7.56 597.596 7.57 594.154 7.58 590.732 7.59 587.33 7.6 587.33 7.61 590.732 7.62 583.947 7.63 580.583 7.64 587.33 7.65 587.33 7.66 583.947 7.67 580.583 7.68 577.24 7.69 -323.965 7.7 -323.965 7.71 -327.729 7.72 -327.729 7.73 -329.628 7.74 -327.729 7.75 -329.628 7.76 -327.729 7.77 -325.841 7.78 -323.965 7.79 305.782 7.8 305.782 7.81 309.335 7.82 307.553 7.83 305.782 7.84 302.27 7.85 305.782 7.86 304.021 7.87 302.27 7.88 305.782 7.89 307.553 7.9 325.841 7.91 327.729 7.92 329.628 7.93 329.628 7.94 331.537 7.95 331.537 7.96 327.729 7.97 311.127 7.98 300.529 7.99 298.798 8 307.553 8.01 295.366 8.02 290.292 8.03 288.62 8.04 285.305 8.05 282.028 8.06 -323.965 8.07 -327.729 8.08 -327.729 8.09 -327.729 8.1 -329.628 8.11 -329.628 8.12 -327.729 8.13 -325.841 8.14 -323.965 8.15 -283.661 8.16 -282.028 8.17 -285.305 8.18 -288.62 8.19 590.732 8.2 594.154 8.21 597.596 8.22 594.154 8.23 594.154 8.24 594.154 8.25 594.154 8.26 590.732 8.27 594.154 8.28 601.058 8.29 604.54 8.3 604.54 8.31 604.54 8.32 594.154 8.33 590.732 8.34 597.596 8.35 597.596 8.36 601.058 8.37 590.732 8.38 587.33 8.39 590.732 8.4 590.732 8.41 587.33 8.42 611.564 8.43 587.33 8.44 587.33 8.45 590.732 8.46 590.732 8.47 590.732 8.48 590.732 8.49 590.732 8.5 587.33 8.51 583.947 8.52 580.583 8.53 -333.458 8.54 -333.458 8.55 -329.628 8.56 -327.729 8.57 -329.628 8.58 -331.537 8.59 -323.965 8.6 -322.099 8.61 -329.628 8.62 -331.537 8.63 -329.628 8.64 -331.537 8.65 -331.537 8.66 -331.537 8.67 -331.537 8.68 -329.628 8.69 -329.628 8.7 -331.537 8.71 -331.537 8.72 -331.537 8.73 -331.537 8.74 -331.537 8.75 283.661 8.76 283.661 8.77 285.305 8.78 283.661 8.79 283.661 8.8 283.661 8.81 285.305 8.82 285.305 8.83 285.305 8.84 283.661 8.85 280.403 8.86 280.403 8.87 282.028 8.88 282.028 8.89 285.305 8.9 286.957 8.91 283.661 8.92 280.403 8.93 282.028 8.94 278.788 8.95 267.741 8.96 270.852 8.97 275.586 8.98 290.292 8.99 304.021 9 314.742 9.01 323.965 9.02 329.628 9.03 327.729 9.04 323.965 9.05 311.127 9.06 300.529 9.07 288.62 9.08 283.661 9.09 277.183 9.1 275.586 9.11 278.788 9.12 282.028 9.13 291.973 9.14 300.529 9.15 311.127 9.16 323.965 9.17 329.628 9.18 331.537 9.19 329.628 9.2 323.965 9.21 312.929 9.22 300.529 9.23 295.366 9.24 290.292 9.25 288.62 9.26 286.957 9.27 286.957 9.28 290.292 9.29 293.665 9.3 293.665 9.31 288.62 9.32 282.028 9.33 264.666 9.34 -440 9.35 -440 9.36 -440 9.37 -440 9.38 -440 9.39 -440 9.4 -440 9.41 -440 9.42 -440 9.43 -440 9.44 -440 9.45 -440 9.46 -440 9.47 -440 9.48 -440 9.49 -440 9.5 -440 9.51 -440 9.52 -440 9.53 -440 9.54 -440 9.55 -333.458 9.56 -331.537 9.57 -331.537 9.58 -331.537 9.59 -331.537 9.6 -331.537 9.61 -329.628 9.62 -329.628 9.63 -329.628 9.64 -329.628 9.65 -329.628 9.66 -329.628 9.67 -440 9.68 -440 9.69 -440 9.7 -440 9.71 -440 9.72 -440 9.73 -440 9.74 -440 9.75 -440 9.76 -440 9.77 -440 9.78 -440 9.79 -440 9.8 -440 9.81 -440 9.82 -440 9.83 -440 9.84 -440 9.85 -440 9.86 -440 9.87 -440 9.88 -440 9.89 -440 9.9 -440 9.91 -440 9.92 -458.155 9.93 -458.155 9.94 471.58 9.95 485.399 9.96 523.251 9.97 541.704 9.98 554.365 9.99 557.577 10 551.172 10.01 538.584 10.02 526.282 10.03 499.622 10.04 485.399 10.05 468.864 10.06 460.809 10.07 458.155 10.08 458.155 10.09 466.164 10.1 474.312 10.11 479.823 10.12 496.744 10.13 514.262 10.14 532.397 10.15 544.842 10.16 554.365 10.17 557.577 10.18 551.172 10.19 535.482 10.2 517.241 10.21 496.744 10.22 479.823 10.23 460.809 10.24 447.691 10.25 450.285 10.26 463.479 10.27 471.58 10.28 488.211 10.29 502.516 10.3 523.251 10.31 535.482 10.32 547.998 10.33 554.365 10.34 551.172 10.35 541.704 10.36 526.282 10.37 505.427 10.38 488.211 10.39 471.58 10.4 458.155 10.41 455.517 10.42 460.809 10.43 468.864 10.44 491.039 10.45 508.355 10.46 523.251 10.47 538.584 10.48 551.172 10.49 551.172 10.5 541.704 10.51 532.397 10.52 -508.355 10.53 -485.399 10.54 -468.864 10.55 -458.155 10.56 -452.893 10.57 -455.517 10.58 -463.479 10.59 -474.312 10.6 -485.399 10.61 -493.883 10.62 -499.622 10.63 -505.427 10.64 -502.516 10.65 -331.537 10.66 -333.458 10.67 -333.458 10.68 -329.628 10.69 -331.537 10.7 -331.537 10.71 -333.458 10.72 -333.458 10.73 -331.537 10.74 -329.628 10.75 460.809 10.76 474.312 10.77 491.039 10.78 514.262 10.79 535.482 10.8 551.172 10.81 557.577 10.82 554.365 10.83 551.172 10.84 541.704 10.85 532.397 10.86 520.237 10.87 514.262 10.88 511.3 10.89 514.262 10.9 517.241 10.91 529.331 10.92 541.704 10.93 570.609 10.94 587.33 10.95 604.54 10.96 611.564 10.97 625.859 10.98 618.67 10.99 615.107 11 604.54 11.01 594.154 11.02 580.583 11.03 564.055 11.04 535.482 11.05 526.282 11.06 517.241 11.07 514.262 11.08 520.237 11.09 529.331 11.1 541.704 11.11 570.609 11.12 583.947 11.13 601.058 11.14 615.107 11.15 633.131 11.16 640.487 11.17 629.484 11.18 615.107 11.19 601.058 11.2 573.915 11.21 547.998 11.22 526.282 11.23 517.241 11.24 511.3 11.25 514.262 11.26 520.237 11.27 538.584 11.28 567.323 11.29 583.947 11.3 594.154 11.31 604.54 11.32 604.54 11.33 -307.553 11.34 -323.965 11.35 -309.335 11.36 -577.24 11.37 -573.915 11.38 266.199 11.39 275.586 11.4 275.586 11.41 273.999 11.42 273.999 11.43 277.183 11.44 278.788 11.45 275.586 11.46 261.626 11.47 248.372 11.48 242.699 11.49 231.739 11.5 213.737 11.51 197.133 11.52 189.321 11.53 186.069 11.54 188.231 11.55 192.631 11.56 204.085 11.57 629.484 11.58 655.458 11.59 666.915 11.6 670.779 11.61 670.779 11.62 659.255 11.63 640.487 11.64 625.859 11.65 611.564 11.66 604.54 11.67 594.154 11.68 590.732 11.69 594.154 11.7 601.058 11.71 615.107 11.72 640.487 11.73 666.915 11.74 690.434 11.75 710.665 11.76 727.276 11.77 727.276 11.78 710.665 11.79 690.434 11.8 678.573 11.81 640.487 11.82 618.67 11.83 597.596 11.84 583.947 11.85 573.915 11.86 573.915 11.87 590.732 11.88 604.54 11.89 629.484 11.9 698.456 11.91 718.923 11.92 493.883 11.93 496.744 11.94 493.883 11.95 488.211 11.96 471.58 11.97 452.893 11.98 437.466 11.99 401.158 12 391.995 12.01 385.261 12.02 387.493 12.03 394.266 12.04 410.535 12.05 437.466 12.06 455.517 12.07 468.864 12.08 479.823 12.09 482.603 12.1 479.823 12.11 477.06 12.12 466.164 12.13 458.155 12.14 445.113 12.15 434.946 12.16 427.474 12.17 425.012 12.18 427.474 12.19 432.441 12.2 440 12.21 445.113 12.22 468.864 12.23 482.603 12.24 493.883 12.25 493.883 12.26 471.58 12.27 460.809 12.28 442.549 12.29 445.113 12.3 452.893 12.31 450.285 12.32 434.946 12.33 427.474 12.34 432.441 12.35 440 12.36 450.285 12.37 466.164 12.38 479.823 12.39 482.603 12.4 479.823 12.41 471.58 12.42 463.479 12.43 450.285 12.44 442.549 12.45 432.441 12.46 417.711 12.47 412.913 12.48 405.819 12.49 405.819 12.5 408.17 12.51 415.305 12.52 422.564 12.53 434.946 12.54 445.113 12.55 460.809 12.56 474.312 12.57 482.603 12.58 488.211 12.59 491.039 12.6 485.399 12.61 474.312 12.62 463.479 12.63 452.893 12.64 432.441 12.65 422.564 12.66 405.819 12.67 403.482 12.68 403.482 12.69 405.819 12.7 417.711 12.71 432.441 12.72 450.285 12.73 474.312 12.74 491.039 12.75 511.3 12.76 514.262 12.77 511.3 12.78 493.883 12.79 477.06 12.8 463.479 12.81 450.285 12.82 427.474 12.83 417.711 12.84 410.535 12.85 408.17 12.86 412.913 12.87 422.564 12.88 437.466 12.89 447.691 12.9 463.479 12.91 471.58 12.92 479.823 12.93 485.399 12.94 482.603 12.95 463.479 12.96 -288.62 12.97 -560.807 12.98 -560.807 12.99 -560.807 13 -283.661 13.01 -288.62 13.02 -297.077 13.03 -305.782 13.04 -322.099 13.05 -335.389 13.06 -355.333 13.07 544.842 13.08 551.172 13.09 544.842 13.1 532.397 13.11 508.355 13.12 496.744 13.13 482.603 13.14 474.312 13.15 450.285 13.16 445.113 13.17 442.549 13.18 440 13.19 442.549 13.2 450.285 13.21 460.809 13.22 482.603 13.23 -333.458 13.24 -331.537 13.25 -331.537 13.26 331.537 13.27 331.537 13.28 333.458 13.29 333.458 13.3 333.458 13.31 331.537 13.32 329.628 13.33 329.628 13.34 329.628 13.35 329.628 13.36 329.628 13.37 329.628 13.38 329.628 13.39 325.841 13.4 327.729 13.41 329.628 13.42 325.841 13.43 327.729 13.44 329.628 13.45 331.537 13.46 329.628 13.47 329.628 13.48 329.628 13.49 329.628 13.5 325.841 13.51 327.729 13.52 329.628 13.53 327.729 13.54 327.729 13.55 331.537 13.56 333.458 13.57 331.537 13.58 329.628 13.59 325.841 13.6 329.628 13.61 333.458 13.62 329.628 13.63 329.628 13.64 327.729 13.65 331.537 13.66 325.841 13.67 327.729 13.68 329.628 13.69 325.841 13.7 327.729 13.71 331.537 13.72 333.458 13.73 331.537 13.74 347.217 13.75 359.461 13.76 337.332 13.77 331.537 13.78 331.537 13.79 331.537 13.8 331.537 13.81 331.537 13.82 496.744 13.83 491.039 13.84 488.211 13.85 479.823 13.86 -322.099 13.87 -437.466 13.88 -437.466 13.89 597.596 13.9 618.67 13.91 212.506 13.92 212.506 13.93 208.855 13.94 192.631 13.95 184.997 13.96 171.614 13.97 168.666 13.98 164.814 13.99 164.814 14 165.769 14.01 169.643 14.02 174.614 14.03 186.069 14.04 191.521 14.05 200.579 14.06 205.267 14.07 206.456 14.08 205.267 14.09 201.741 14.1 193.746 14.11 184.997 14.12 175.626 14.13 171.614 14.14 168.666 14.15 168.666 14.16 173.608 14.17 176.643 14.18 181.819 14.19 191.521 14.2 197.133 14.21 202.91 14.22 205.267 14.23 200.579 14.24 195.998 14.25 184.997 14.26 179.731 14.27 177.666 14.28 177.666 14.29 179.731 14.3 183.932 14.31 187.147 14.32 187.147 14.33 187.147 14.34 -220 14.35 -220 14.36 -220 14.37 -220 14.38 -220 14.39 -220 14.4 -220 14.41 -220 14.42 -220 14.43 -220 14.44 -220 14.45 -220 14.46 -220 14.47 -220 14.48 -220 14.49 -220 14.5 -220 14.51 -220 14.52 -220 14.53 -220 14.54 -220 14.55 -220 14.56 -220 14.57 -220 14.58 -220 14.59 -220 14.6 -220 14.61 314.742 14.62 312.929 14.63 316.565 14.64 320.244 14.65 323.965 14.66 323.965 14.67 322.099 14.68 320.244 14.69 318.399 14.7 312.929 14.71 311.127 14.72 316.565 14.73 320.244 14.74 323.965 14.75 323.965 14.76 325.841 14.77 325.841 14.78 325.841 14.79 323.965 14.8 320.244 14.81 316.565 14.82 314.742 14.83 312.929 14.84 312.929 14.85 311.127 14.86 309.335 14.87 314.742 14.88 322.099 14.89 323.965 14.9 329.628 14.91 335.389 14.92 343.229 14.93 347.217 14.94 345.217 14.95 343.229 14.96 339.286 14.97 331.537 14.98 323.965 14.99 320.244 15 314.742 15.01 312.929 15.02 309.335 15.03 312.929 15.04 320.244 15.05 323.965 15.06 329.628 15.07 337.332 15.08 351.251 15.09 355.333 15.1 355.333 15.11 353.286 15.12 345.217 15.13 337.332 15.14 333.458 15.15 325.841 15.16 318.399 15.17 298.798 15.18 288.62 15.19 290.292 15.2 309.335 15.21 314.742 15.22 316.565 15.23 322.099 15.24 333.458 15.25 337.332 15.26 343.229 15.27 347.217 15.28 353.286 15.29 357.391 15.3 361.544 15.31 361.544 15.32 355.333 15.33 341.252 15.34 333.458 15.35 331.537 15.36 335.389 15.37 351.251 15.38 -220 15.39 -220 15.4 -220 15.41 -220 15.42 238.53 15.43 237.156 15.44 242.699 15.45 255.65 15.46 272.421 15.47 288.62 15.48 298.798 15.49 311.127 15.5 320.244 15.51 325.841 15.52 322.099 15.53 316.565 15.54 307.553 15.55 298.798 15.56 288.62 15.57 280.403 15.58 266.199 15.59 261.626 15.6 258.621 15.61 258.621 15.62 263.141 15.63 267.741 15.64 277.183 15.65 288.62 15.66 298.798 15.67 311.127 15.68 316.565 15.69 318.399 15.7 320.244 15.71 312.929 15.72 305.782 15.73 300.529 15.74 290.292 15.75 280.403 15.76 269.292 15.77 263.141 15.78 260.119 15.79 258.621 15.8 260.119 15.81 263.141 15.82 266.199 15.83 275.586 15.84 282.028 15.85 288.62 15.86 293.665 15.87 297.077 15.88 298.798 15.89 293.665 15.9 288.62 15.91 282.028 15.92 269.292 15.93 263.141 15.94 257.131 15.95 252.714 15.96 249.811 15.97 246.942 15.98 245.519 15.99 244.105 16 246.942 16.01 252.714 16.02 260.119 16.03 264.666 16.04 263.141 16.05 244.105 16.06 246.942 16.07 252.714 16.08 245.519 16.09 229.078 16.1 223.846 16.11 221.274 16.12 217.473 16.13 216.221 16.14 216.221 16.15 218.733 16.16 222.556 16.17 225.142 16.18 229.078 16.19 229.078 16.2 226.446 16.21 226.446 16.22 223.846 16.23 220 16.24 220 16.25 220 16.26 221.274 16.27 217.473 16.28 217.473 16.29 218.733 16.3 220 16.31 220 16.32 220 16.33 220 16.34 218.733 16.35 218.733 16.36 216.221 16.37 213.737 16.38 210.065 16.39 205.267 16.4 201.741 16.41 199.424 16.42 198.275 16.43 200.579 16.44 205.267 16.45 213.737 16.46 223.846 16.47 230.405 16.48 235.79 16.49 237.156 16.5 235.79 16.51 235.79 16.52 231.739 16.53 227.758 16.54 221.274 16.55 216.221 16.56 212.506 16.57 208.855 16.58 208.855 16.59 208.855 16.6 210.065 16.61 214.975 16.62 220 16.63 226.446 16.64 230.405 16.65 234.432 16.66 237.156 16.67 237.156 16.68 237.156 16.69 234.432 16.7 230.405 16.71 226.446 16.72 220 16.73 216.221 16.74 213.737 16.75 213.737 16.76 213.737 16.77 217.473 16.78 221.274 16.79 226.446 16.8 230.405 16.81 -234.432 16.82 -235.79 16.83 -237.156 16.84 -238.53 16.85 -237.156 16.86 -234.432 16.87 -231.739 16.88 -226.446 16.89 -225.142 16.9 -226.446 16.91 -220 16.92 -220 16.93 -220 16.94 -220 16.95 -220 16.96 305.782 16.97 302.27 16.98 309.335 16.99 314.742 17 318.399 17.01 318.399 17.02 316.565 17.03 314.742 17.04 305.782 17.05 298.798 17.06 291.973 17.07 286.957 17.08 283.661 17.09 282.028 17.1 282.028 17.11 285.305 17.12 288.62 17.13 300.529 17.14 311.127 17.15 323.965 17.16 331.537 17.17 337.332 17.18 337.332 17.19 331.537 17.2 320.244 17.21 311.127 17.22 295.366 17.23 288.62 17.24 280.403 17.25 277.183 17.26 273.999 17.27 275.586 17.28 280.403 17.29 286.957 17.3 290.292 17.31 297.077 17.32 300.529 17.33 305.782 17.34 307.553 17.35 309.335 17.36 311.127 17.37 316.565 17.38 316.565 17.39 314.742 17.4 311.127 17.41 307.553 17.42 297.077 17.43 291.973 17.44 286.957 17.45 282.028 17.46 280.403 17.47 286.957 17.48 288.62 17.49 290.292 17.5 291.973 17.51 293.665 17.52 297.077 17.53 298.798 17.54 304.021 17.55 307.553 17.56 305.782 17.57 304.021 17.58 302.27 17.59 297.077 17.6 293.665 17.61 291.973 17.62 288.62 17.63 288.62 17.64 288.62 17.65 290.292 17.66 291.973 17.67 295.366 17.68 298.798 17.69 311.127 17.7 320.244 17.71 320.244 17.72 295.366 17.73 293.665 17.74 291.973 17.75 293.665 17.76 291.973 17.77 290.292 17.78 291.973 17.79 298.798 17.8 304.021 17.81 311.127 17.82 322.099 17.83 331.537 17.84 337.332 17.85 341.252 17.86 341.252 17.87 339.286 17.88 337.332 17.89 335.389 17.9 331.537 17.91 327.729 17.92 323.965 17.93 322.099 17.94 316.565 17.95 314.742 17.96 320.244 17.97 325.841 17.98 327.729 17.99 331.537 18 333.458 18.01 335.389 18.02 337.332 18.03 335.389 18.04 335.389 18.05 333.458 18.06 331.537 18.07 327.729 18.08 323.965 18.09 318.399 18.1 314.742 18.11 316.565 18.12 318.399 18.13 322.099 18.14 325.841 18.15 329.628 18.16 337.332 18.17 341.252 18.18 347.217 18.19 349.228 18.2 353.286 18.21 353.286 18.22 347.217 18.23 337.332 18.24 329.628 18.25 322.099 18.26 312.929 18.27 305.782 18.28 302.27 18.29 305.782 18.3 309.335 18.31 312.929 18.32 322.099 18.33 327.729 18.34 335.389 18.35 339.286 18.36 343.229 18.37 343.229 18.38 345.217 18.39 339.286 18.4 335.389 18.41 333.458 18.42 331.537 18.43 329.628 18.44 327.729 18.45 327.729 18.46 325.841 18.47 320.244 18.48 331.537 18.49 335.389 18.5 331.537 18.51 335.389 18.52 333.458 18.53 331.537 18.54 327.729 18.55 329.628 18.56 331.537 18.57 329.628 18.58 331.537 18.59 331.537 18.6 327.729 18.61 335.389 18.62 331.537 18.63 333.458 18.64 227.758 18.65 237.156 18.66 239.912 18.67 239.912 18.68 231.739 18.69 226.446 18.7 217.473 18.71 211.282 18.72 204.085 18.73 200.579 18.74 200.579 18.75 200.579 18.76 200.579 18.77 205.267 18.78 208.855 18.79 214.975 18.8 221.274 18.81 229.078 18.82 237.156 18.83 242.699 18.84 245.519 18.85 245.519 18.86 244.105 18.87 241.301 18.88 233.082 18.89 227.758 18.9 218.733 18.91 211.282 18.92 201.741 18.93 197.133 18.94 194.869 18.95 195.998 18.96 200.579 18.97 206.456 18.98 214.975 18.99 225.142 19 231.739 19.01 238.53 19.02 242.699 19.03 245.519 19.04 245.519 19.05 245.519 19.06 242.699 19.07 237.156 19.08 233.082 19.09 229.078 19.1 222.556 19.11 217.473 19.12 212.506 19.13 206.456 19.14 205.267 19.15 205.267 19.16 206.456 19.17 210.065 19.18 216.221 19.19 222.556 19.2 227.758 19.21 231.739 19.22 235.79 19.23 239.912 19.24 242.699 19.25 242.699 19.26 242.699 19.27 239.912 19.28 235.79 19.29 233.082 19.3 227.758 19.31 222.556 19.32 218.733 19.33 214.975 19.34 211.282 19.35 211.282 19.36 212.506 19.37 216.221 19.38 218.733 19.39 222.556 19.4 226.446 19.41 230.405 19.42 231.739 19.43 231.739 19.44 231.739 19.45 230.405 19.46 226.446 19.47 221.274 19.48 218.733 19.49 220 19.5 220 19.51 220 19.52 218.733 19.53 220 19.54 218.733 19.55 218.733 19.56 220 19.57 221.274 19.58 220 19.59 220 19.6 220 19.61 218.733 19.62 220 19.63 220 19.64 220 19.65 220 19.66 218.733 19.67 221.274 19.68 218.733 19.69 218.733 19.7 -220 19.71 -220 19.72 -220 19.73 -220 19.74 -220 19.75 -220 19.76 -220 19.77 -220 19.78 -220 19.79 -220 19.8 -220 19.81 -220 19.82 -222.556 19.83 -222.556 19.84 -221.274 19.85 -221.274 19.86 -221.274 19.87 -222.556 19.88 -222.556 19.89 -222.556 19.9 -221.274 19.91 -221.274 19.92 -220 19.93 -220 19.94 -221.274 19.95 -221.274 19.96 -221.274 19.97 -221.274 mir_eval-0.8.2/tests/data/melody/est08.txt000077500000000000000000000740401475740344600204150ustar00rootroot000000000000000 0 0.01 0 0.02 -220 0.03 -220 0.04 -220 0.05 -220 0.06 -220 0.07 -220 0.08 -220 0.09 -220 0.1 -220 0.11 -220 0.12 -220 0.13 -220 0.14 -220 0.15 -220 0.16 -220 0.17 -220 0.18 -220 0.19 -220 0.2 -220 0.21 -220 0.22 -220 0.23 -220 0.24 -220 0.25 -220 0.26 -220 0.27 -220 0.28 -220 0.29 -220 0.3 -220 0.31 -220 0.32 -220 0.33 -220 0.34 -220 0.35 -220 0.36 -220 0.37 -220 0.38 -220 0.39 -220 0.4 -220 0.41 -220 0.42 -220 0.43 -220 0.44 -220 0.45 -220 0.46 -220 0.47 -220 0.48 -220 0.49 -220 0.5 -220 0.51 -220 0.52 -220 0.53 -220 0.54 -220 0.55 -220 0.56 187.147 0.57 187.147 0.58 184.997 0.59 183.932 0.6 181.819 0.61 182.872 0.62 181.819 0.63 182.872 0.64 183.932 0.65 183.932 0.66 183.932 0.67 183.932 0.68 183.932 0.69 183.932 0.7 184.997 0.71 186.069 0.72 187.147 0.73 187.147 0.74 187.147 0.75 187.147 0.76 186.069 0.77 186.069 0.78 184.997 0.79 182.872 0.8 180.772 0.81 178.696 0.82 177.666 0.83 178.696 0.84 180.772 0.85 181.819 0.86 181.819 0.87 184.997 0.88 188.231 0.89 191.521 0.9 194.869 0.91 197.133 0.92 197.133 0.93 197.133 0.94 194.869 0.95 191.521 0.96 186.069 0.97 181.819 0.98 176.643 0.99 173.608 1 171.614 1.01 170.626 1.02 170.626 1.03 172.609 1.04 176.643 1.05 182.872 1.06 188.231 1.07 193.746 1.08 198.275 1.09 202.91 1.1 205.267 1.11 205.267 1.12 202.91 1.13 199.424 1.14 192.631 1.15 186.069 1.16 175.626 1.17 171.614 1.18 169.643 1.19 168.666 1.2 168.666 1.21 172.609 1.22 177.666 1.23 187.147 1.24 191.521 1.25 199.424 1.26 202.91 1.27 204.085 1.28 201.741 1.29 199.424 1.3 192.631 1.31 189.321 1.32 187.147 1.33 183.932 1.34 180.772 1.35 178.696 1.36 178.696 1.37 180.772 1.38 182.872 1.39 186.069 1.4 188.231 1.41 190.418 1.42 190.418 1.43 190.418 1.44 190.418 1.45 188.231 1.46 187.147 1.47 186.069 1.48 182.872 1.49 180.772 1.5 177.666 1.51 177.666 1.52 177.666 1.53 178.696 1.54 180.772 1.55 181.819 1.56 183.932 1.57 186.069 1.58 187.147 1.59 187.147 1.6 188.231 1.61 187.147 1.62 187.147 1.63 184.997 1.64 182.872 1.65 180.772 1.66 180.772 1.67 179.731 1.68 178.696 1.69 178.696 1.7 177.666 1.71 178.696 1.72 179.731 1.73 180.772 1.74 180.772 1.75 180.772 1.76 181.819 1.77 182.872 1.78 184.997 1.79 184.997 1.8 184.997 1.81 184.997 1.82 184.997 1.83 184.997 1.84 184.997 1.85 184.997 1.86 184.997 1.87 184.997 1.88 187.147 1.89 188.231 1.9 190.418 1.91 190.418 1.92 190.418 1.93 189.321 1.94 188.231 1.95 188.231 1.96 187.147 1.97 187.147 1.98 187.147 1.99 183.932 2 182.872 2.01 194.869 2.02 199.424 2.03 201.741 2.04 202.91 2.05 202.91 2.06 199.424 2.07 197.133 2.08 -220 2.09 -220 2.1 195.998 2.11 194.869 2.12 193.746 2.13 190.418 2.14 194.869 2.15 202.91 2.16 204.085 2.17 206.456 2.18 210.065 2.19 213.737 2.2 213.737 2.21 211.282 2.22 204.085 2.23 197.133 2.24 189.321 2.25 182.872 2.26 174.614 2.27 170.626 2.28 168.666 2.29 169.643 2.3 173.608 2.31 186.069 2.32 194.869 2.33 207.652 2.34 216.221 2.35 221.274 2.36 222.556 2.37 220 2.38 214.975 2.39 208.855 2.4 195.998 2.41 186.069 2.42 173.608 2.43 168.666 2.44 167.695 2.45 170.626 2.46 180.772 2.47 191.521 2.48 197.133 2.49 206.456 2.5 211.282 2.51 214.975 2.52 214.975 2.53 212.506 2.54 205.267 2.55 -220 2.56 -220 2.57 -220 2.58 -220 2.59 -220 2.6 -220 2.61 -220 2.62 -220 2.63 -220 2.64 -220 2.65 -220 2.66 -220 2.67 -220 2.68 -220 2.69 -220 2.7 -220 2.71 -220 2.72 -220 2.73 -220 2.74 -220 2.75 -220 2.76 -220 2.77 -220 2.78 -220 2.79 -220 2.8 -220 2.81 -220 2.82 -220 2.83 -220 2.84 -220 2.85 -174.614 2.86 -176.643 2.87 -177.666 2.88 -175.626 2.89 -168.666 2.9 -161.982 2.91 -152.891 2.92 -149.399 2.93 -145.987 2.94 -143.479 2.95 -142.652 2.96 -145.146 2.97 -147.683 2.98 -152.891 2.99 -160.122 3 -171.614 3.01 -180.772 3.02 -183.932 3.03 -188.231 3.04 -188.231 3.05 -184.997 3.06 -173.608 3.07 -163.865 3.08 -220 3.09 -220 3.1 -220 3.11 -220 3.12 -220 3.13 -220 3.14 -220 3.15 -220 3.16 -220 3.17 -220 3.18 -220 3.19 -220 3.2 -220 3.21 -220 3.22 -220 3.23 -220 3.24 -220 3.25 -220 3.26 -220 3.27 -220 3.28 -220 3.29 -220 3.3 -220 3.31 -220 3.32 -220 3.33 -220 3.34 -220 3.35 -220 3.36 -220 3.37 -220 3.38 -220 3.39 -220 3.4 -220 3.41 -220 3.42 -220 3.43 -220 3.44 -220 3.45 -220 3.46 -220 3.47 -220 3.48 -220 3.49 -220 3.5 -220 3.51 -220 3.52 -220 3.53 -220 3.54 -220 3.55 -220 3.56 -220 3.57 -220 3.58 -220 3.59 -220 3.6 -220 3.61 -220 3.62 -220 3.63 -220 3.64 -220 3.65 -220 3.66 -220 3.67 -220 3.68 -220 3.69 -220 3.7 -220 3.71 -220 3.72 -220 3.73 -220 3.74 -220 3.75 -220 3.76 -220 3.77 -220 3.78 -220 3.79 -220 3.8 -220 3.81 -220 3.82 -220 3.83 -220 3.84 -220 3.85 -220 3.86 -220 3.87 -220 3.88 -220 3.89 -220 3.9 -220 3.91 -220 3.92 -220 3.93 -220 3.94 -220 3.95 -220 3.96 -220 3.97 -220 3.98 -220 3.99 -220 4 -220 4.01 -220 4.02 -220 4.03 -220 4.04 -220 4.05 -220 4.06 -220 4.07 -220 4.08 -220 4.09 -220 4.1 -220 4.11 -220 4.12 -220 4.13 -220 4.14 -220 4.15 -220 4.16 -220 4.17 -220 4.18 -220 4.19 -220 4.2 -220 4.21 -220 4.22 -220 4.23 -220 4.24 -220 4.25 -220 4.26 -220 4.27 -220 4.28 -220 4.29 -220 4.3 -220 4.31 -220 4.32 -220 4.33 -220 4.34 190.418 4.35 191.521 4.36 192.631 4.37 193.746 4.38 194.869 4.39 194.869 4.4 195.998 4.41 197.133 4.42 199.424 4.43 199.424 4.44 198.275 4.45 197.133 4.46 194.869 4.47 193.746 4.48 192.631 4.49 191.521 4.5 192.631 4.51 193.746 4.52 193.746 4.53 194.869 4.54 194.869 4.55 194.869 4.56 194.869 4.57 197.133 4.58 195.998 4.59 195.998 4.6 195.998 4.61 195.998 4.62 194.869 4.63 194.869 4.64 195.998 4.65 195.998 4.66 195.998 4.67 195.998 4.68 195.998 4.69 197.133 4.7 197.133 4.71 198.275 4.72 198.275 4.73 197.133 4.74 197.133 4.75 195.998 4.76 195.998 4.77 194.869 4.78 194.869 4.79 193.746 4.8 192.631 4.81 191.521 4.82 191.521 4.83 191.521 4.84 190.418 4.85 191.521 4.86 192.631 4.87 195.998 4.88 198.275 4.89 201.741 4.9 204.085 4.91 206.456 4.92 207.652 4.93 206.456 4.94 205.267 4.95 202.91 4.96 197.133 4.97 193.746 4.98 188.231 4.99 184.997 5 180.772 5.01 180.772 5.02 181.819 5.03 184.997 5.04 186.069 5.05 189.321 5.06 192.631 5.07 199.424 5.08 204.085 5.09 207.652 5.1 208.855 5.11 210.065 5.12 210.065 5.13 207.652 5.14 202.91 5.15 199.424 5.16 195.998 5.17 193.746 5.18 190.418 5.19 186.069 5.2 182.872 5.21 182.872 5.22 183.932 5.23 186.069 5.24 188.231 5.25 192.631 5.26 197.133 5.27 201.741 5.28 204.085 5.29 205.267 5.3 206.456 5.31 205.267 5.32 202.91 5.33 201.741 5.34 198.275 5.35 194.869 5.36 190.418 5.37 187.147 5.38 182.872 5.39 178.696 5.4 177.666 5.41 178.696 5.42 179.731 5.43 184.997 5.44 188.231 5.45 191.521 5.46 192.631 5.47 198.275 5.48 202.91 5.49 204.085 5.5 204.085 5.51 202.91 5.52 201.741 5.53 199.424 5.54 194.869 5.55 190.418 5.56 186.069 5.57 182.872 5.58 179.731 5.59 178.696 5.6 179.731 5.61 182.872 5.62 184.997 5.63 191.521 5.64 193.746 5.65 197.133 5.66 200.579 5.67 202.91 5.68 204.085 5.69 202.91 5.7 199.424 5.71 197.133 5.72 192.631 5.73 189.321 5.74 184.997 5.75 182.872 5.76 181.819 5.77 182.872 5.78 184.997 5.79 188.231 5.8 191.521 5.81 193.746 5.82 195.998 5.83 198.275 5.84 198.275 5.85 197.133 5.86 195.998 5.87 194.869 5.88 193.746 5.89 192.631 5.9 190.418 5.91 189.321 5.92 190.418 5.93 191.521 5.94 193.746 5.95 195.998 5.96 198.275 5.97 200.579 5.98 200.579 5.99 199.424 6 198.275 6.01 197.133 6.02 197.133 6.03 197.133 6.04 195.998 6.05 197.133 6.06 197.133 6.07 197.133 6.08 198.275 6.09 198.275 6.1 198.275 6.11 198.275 6.12 197.133 6.13 194.869 6.14 191.521 6.15 188.231 6.16 -220 6.17 -220 6.18 -220 6.19 -220 6.2 -220 6.21 -220 6.22 -220 6.23 -220 6.24 -220 6.25 -220 6.26 -220 6.27 -220 6.28 -220 6.29 -220 6.3 -220 6.31 -220 6.32 -220 6.33 -220 6.34 -220 6.35 -220 6.36 -220 6.37 -220 6.38 -220 6.39 -220 6.4 -220 6.41 -220 6.42 -220 6.43 -220 6.44 -220 6.45 -220 6.46 216.221 6.47 217.473 6.48 222.556 6.49 227.758 6.5 233.082 6.51 234.432 6.52 231.739 6.53 223.846 6.54 213.737 6.55 202.91 6.56 197.133 6.57 192.631 6.58 191.521 6.59 191.521 6.6 195.998 6.61 202.91 6.62 216.221 6.63 227.758 6.64 241.301 6.65 246.942 6.66 249.811 6.67 248.372 6.68 244.105 6.69 235.79 6.7 227.758 6.71 217.473 6.72 210.065 6.73 204.085 6.74 201.741 6.75 200.579 6.76 201.741 6.77 204.085 6.78 208.855 6.79 217.473 6.8 237.156 6.81 244.105 6.82 249.811 6.83 251.258 6.84 249.811 6.85 246.942 6.86 242.699 6.87 231.739 6.88 222.556 6.89 214.975 6.9 208.855 6.91 202.91 6.92 201.741 6.93 204.085 6.94 208.855 6.95 216.221 6.96 225.142 6.97 233.082 6.98 241.301 6.99 244.105 7 244.105 7.01 239.912 7.02 234.432 7.03 229.078 7.04 222.556 7.05 218.733 7.06 217.473 7.07 217.473 7.08 145.987 7.09 146.832 7.1 146.832 7.11 146.832 7.12 146.832 7.13 147.683 7.14 146.832 7.15 149.399 7.16 155.563 7.17 156.465 7.18 160.122 7.19 163.865 7.2 171.614 7.21 179.731 7.22 189.321 7.23 193.746 7.24 194.869 7.25 193.746 7.26 190.418 7.27 183.932 7.28 172.609 7.29 161.982 7.3 153.777 7.31 149.399 7.32 146.832 7.33 146.832 7.34 149.399 7.35 153.777 7.36 165.769 7.37 176.643 7.38 190.418 7.39 198.275 7.4 202.91 7.41 202.91 7.42 201.741 7.43 194.869 7.44 189.321 7.45 176.643 7.46 170.626 7.47 163.865 7.48 161.982 7.49 163.865 7.5 164.814 7.51 167.695 7.52 174.614 7.53 181.819 7.54 193.746 7.55 197.133 7.56 201.741 7.57 198.275 7.58 -220 7.59 -220 7.6 -220 7.61 -220 7.62 -220 7.63 -220 7.64 -220 7.65 -220 7.66 -220 7.67 -220 7.68 -220 7.69 -220 7.7 -220 7.71 -220 7.72 -220 7.73 -220 7.74 -220 7.75 -220 7.76 -220 7.77 -220 7.78 -220 7.79 -220 7.8 -220 7.81 -220 7.82 -220 7.83 -220 7.84 -295.366 7.85 -297.077 7.86 -297.077 7.87 -295.366 7.88 -295.366 7.89 -295.366 7.9 -295.366 7.91 -297.077 7.92 -295.366 7.93 -295.366 7.94 -295.366 7.95 -295.366 7.96 -295.366 7.97 -295.366 7.98 -293.665 7.99 -295.366 8 -293.665 8.01 -293.665 8.02 -295.366 8.03 -293.665 8.04 -293.665 8.05 -293.665 8.06 -295.366 8.07 -295.366 8.08 -295.366 8.09 -295.366 8.1 -295.366 8.11 -295.366 8.12 -295.366 8.13 -295.366 8.14 -295.366 8.15 -295.366 8.16 -295.366 8.17 -295.366 8.18 -295.366 8.19 -295.366 8.2 -295.366 8.21 -295.366 8.22 -295.366 8.23 -295.366 8.24 -295.366 8.25 -295.366 8.26 -295.366 8.27 -295.366 8.28 -295.366 8.29 -297.077 8.3 -295.366 8.31 -295.366 8.32 -295.366 8.33 -295.366 8.34 -295.366 8.35 -295.366 8.36 -295.366 8.37 -297.077 8.38 -295.366 8.39 -295.366 8.4 -295.366 8.41 -295.366 8.42 -293.665 8.43 -293.665 8.44 -295.366 8.45 -295.366 8.46 -295.366 8.47 -295.366 8.48 -295.366 8.49 -295.366 8.5 -295.366 8.51 -295.366 8.52 -297.077 8.53 -297.077 8.54 -298.798 8.55 -297.077 8.56 -297.077 8.57 -293.665 8.58 -295.366 8.59 -293.665 8.6 -293.665 8.61 -295.366 8.62 -295.366 8.63 -295.366 8.64 -295.366 8.65 -295.366 8.66 -293.665 8.67 -295.366 8.68 -293.665 8.69 -293.665 8.7 -295.366 8.71 -295.366 8.72 -293.665 8.73 -293.665 8.74 -293.665 8.75 195.998 8.76 197.133 8.77 199.424 8.78 200.579 8.79 201.741 8.8 202.91 8.81 204.085 8.82 207.652 8.83 210.065 8.84 210.065 8.85 211.282 8.86 214.975 8.87 214.975 8.88 216.221 8.89 217.473 8.9 218.733 8.91 218.733 8.92 220 8.93 220 8.94 221.274 8.95 220 8.96 221.274 8.97 221.274 8.98 221.274 8.99 221.274 9 222.556 9.01 222.556 9.02 222.556 9.03 222.556 9.04 221.274 9.05 221.274 9.06 221.274 9.07 221.274 9.08 221.274 9.09 221.274 9.1 221.274 9.11 221.274 9.12 222.556 9.13 222.556 9.14 222.556 9.15 222.556 9.16 222.556 9.17 221.274 9.18 220 9.19 220 9.2 220 9.21 220 9.22 220 9.23 221.274 9.24 221.274 9.25 223.846 9.26 225.142 9.27 227.758 9.28 227.758 9.29 227.758 9.3 227.758 9.31 226.446 9.32 225.142 9.33 225.142 9.34 222.556 9.35 221.274 9.36 218.733 9.37 218.733 9.38 218.733 9.39 217.473 9.4 217.473 9.41 221.274 9.42 225.142 9.43 230.405 9.44 231.739 9.45 234.432 9.46 237.156 9.47 238.53 9.48 238.53 9.49 237.156 9.5 234.432 9.51 230.405 9.52 226.446 9.53 220 9.54 214.975 9.55 211.282 9.56 207.652 9.57 207.652 9.58 210.065 9.59 214.975 9.6 218.733 9.61 225.142 9.62 229.078 9.63 234.432 9.64 237.156 9.65 239.912 9.66 241.301 9.67 241.301 9.68 238.53 9.69 233.082 9.7 229.078 9.71 223.846 9.72 213.737 9.73 208.855 9.74 205.267 9.75 204.085 9.76 205.267 9.77 208.855 9.78 214.975 9.79 218.733 9.8 223.846 9.81 227.758 9.82 230.405 9.83 234.432 9.84 234.432 9.85 234.432 9.86 233.082 9.87 230.405 9.88 226.446 9.89 222.556 9.9 216.221 9.91 213.737 9.92 210.065 9.93 210.065 9.94 211.282 9.95 216.221 9.96 220 9.97 223.846 9.98 227.758 9.99 231.739 10 234.432 10.01 235.79 10.02 235.79 10.03 233.082 10.04 230.405 10.05 225.142 10.06 223.846 10.07 222.556 10.08 222.556 10.09 221.274 10.1 220 10.11 218.733 10.12 217.473 10.13 217.473 10.14 214.975 10.15 216.221 10.16 216.221 10.17 216.221 10.18 214.975 10.19 213.737 10.2 212.506 10.21 216.221 10.22 220 10.23 221.274 10.24 221.274 10.25 221.274 10.26 221.274 10.27 220 10.28 220 10.29 220 10.3 221.274 10.31 220 10.32 221.274 10.33 221.274 10.34 221.274 10.35 221.274 10.36 222.556 10.37 222.556 10.38 222.556 10.39 223.846 10.4 223.846 10.41 223.846 10.42 223.846 10.43 223.846 10.44 223.846 10.45 222.556 10.46 222.556 10.47 223.846 10.48 223.846 10.49 222.556 10.5 222.556 10.51 221.274 10.52 221.274 10.53 220 10.54 218.733 10.55 218.733 10.56 217.473 10.57 217.473 10.58 218.733 10.59 218.733 10.6 218.733 10.61 218.733 10.62 218.733 10.63 220 10.64 221.274 10.65 222.556 10.66 223.846 10.67 225.142 10.68 225.142 10.69 226.446 10.7 225.142 10.71 222.556 10.72 220 10.73 220 10.74 220 10.75 220 10.76 225.142 10.77 226.446 10.78 227.758 10.79 238.53 10.8 252.714 10.81 255.65 10.82 257.131 10.83 255.65 10.84 254.178 10.85 249.811 10.86 -440 10.87 -440 10.88 -248.372 10.89 -248.372 10.9 -246.942 10.91 -246.942 10.92 -246.942 10.93 -249.811 10.94 -251.258 10.95 502.516 10.96 499.622 10.97 499.622 10.98 496.744 10.99 496.744 11 496.744 11.01 496.744 11.02 493.883 11.03 491.039 11.04 491.039 11.05 488.211 11.06 491.039 11.07 491.039 11.08 493.883 11.09 493.883 11.1 493.883 11.11 496.744 11.12 496.744 11.13 496.744 11.14 496.744 11.15 493.883 11.16 493.883 11.17 491.039 11.18 488.211 11.19 488.211 11.2 485.399 11.21 485.399 11.22 485.399 11.23 485.399 11.24 488.211 11.25 491.039 11.26 493.883 11.27 496.744 11.28 499.622 11.29 505.427 11.3 505.427 11.31 505.427 11.32 502.516 11.33 496.744 11.34 493.883 11.35 491.039 11.36 485.399 11.37 482.603 11.38 479.823 11.39 477.06 11.4 477.06 11.41 479.823 11.42 488.211 11.43 493.883 11.44 505.427 11.45 517.241 11.46 523.251 11.47 526.282 11.48 526.282 11.49 526.282 11.5 523.251 11.51 520.237 11.52 517.241 11.53 511.3 11.54 496.744 11.55 488.211 11.56 471.58 11.57 460.809 11.58 455.517 11.59 455.517 11.6 463.479 11.61 471.58 11.62 482.603 11.63 496.744 11.64 508.355 11.65 526.282 11.66 532.397 11.67 541.704 11.68 544.842 11.69 544.842 11.7 541.704 11.71 535.482 11.72 529.331 11.73 523.251 11.74 511.3 11.75 499.622 11.76 488.211 11.77 477.06 11.78 463.479 11.79 460.809 11.8 463.479 11.81 468.864 11.82 477.06 11.83 493.883 11.84 505.427 11.85 523.251 11.86 529.331 11.87 538.584 11.88 541.704 11.89 541.704 11.9 535.482 11.91 529.331 11.92 523.251 11.93 511.3 11.94 496.744 11.95 479.823 11.96 463.479 11.97 455.517 11.98 450.285 11.99 452.893 12 458.155 12.01 477.06 12.02 488.211 12.03 505.427 12.04 517.241 12.05 529.331 12.06 535.482 12.07 538.584 12.08 538.584 12.09 532.397 12.1 520.237 12.11 508.355 12.12 485.399 12.13 468.864 12.14 458.155 12.15 455.517 12.16 458.155 12.17 463.479 12.18 477.06 12.19 -248.372 12.2 -251.258 12.21 -254.178 12.22 -260.119 12.23 -254.178 12.24 -251.258 12.25 -251.258 12.26 -249.811 12.27 -246.942 12.28 -245.519 12.29 -244.105 12.3 -242.699 12.31 -479.823 12.32 -242.699 12.33 -242.699 12.34 -244.105 12.35 -244.105 12.36 -242.699 12.37 -440 12.38 -440 12.39 -440 12.4 -440 12.41 -241.301 12.42 -474.312 12.43 479.823 12.44 485.399 12.45 496.744 12.46 514.262 12.47 529.331 12.48 544.842 12.49 547.998 12.5 544.842 12.51 538.584 12.52 523.251 12.53 508.355 12.54 491.039 12.55 474.312 12.56 460.809 12.57 450.285 12.58 445.113 12.59 447.691 12.6 458.155 12.61 471.58 12.62 479.823 12.63 496.744 12.64 551.172 12.65 564.055 12.66 570.609 12.67 570.609 12.68 567.323 12.69 554.365 12.7 529.331 12.71 511.3 12.72 488.211 12.73 471.58 12.74 463.479 12.75 458.155 12.76 460.809 12.77 468.864 12.78 477.06 12.79 505.427 12.8 532.397 12.81 538.584 12.82 535.482 12.83 523.251 12.84 499.622 12.85 479.823 12.86 -440 12.87 -440 12.88 -440 12.89 -440 12.9 -440 12.91 -440 12.92 -440 12.93 -440 12.94 -440 12.95 -440 12.96 -440 12.97 -440 12.98 -440 12.99 -440 13 -440 13.01 -440 13.02 -440 13.03 -440 13.04 -440 13.05 -440 13.06 -440 13.07 -440 13.08 -440 13.09 -440 13.1 -440 13.11 -440 13.12 -440 13.13 -440 13.14 267.741 13.15 272.421 13.16 283.661 13.17 290.292 13.18 291.973 13.19 291.973 13.2 290.292 13.21 286.957 13.22 280.403 13.23 272.421 13.24 269.292 13.25 267.741 13.26 269.292 13.27 278.788 13.28 282.028 13.29 282.028 13.3 283.661 13.31 280.403 13.32 278.788 13.33 278.788 13.34 280.403 13.35 280.403 13.36 278.788 13.37 277.183 13.38 275.586 13.39 273.999 13.4 273.999 13.41 273.999 13.42 275.586 13.43 275.586 13.44 275.586 13.45 275.586 13.46 277.183 13.47 278.788 13.48 277.183 13.49 277.183 13.5 275.586 13.51 275.586 13.52 275.586 13.53 277.183 13.54 278.788 13.55 278.788 13.56 280.403 13.57 278.788 13.58 280.403 13.59 280.403 13.6 283.661 13.61 283.661 13.62 283.661 13.63 -282.028 13.64 -282.028 13.65 -280.403 13.66 -280.403 13.67 -280.403 13.68 -278.788 13.69 -277.183 13.7 -275.586 13.71 -273.999 13.72 -272.421 13.73 -272.421 13.74 272.421 13.75 272.421 13.76 273.999 13.77 277.183 13.78 278.788 13.79 280.403 13.8 283.661 13.81 285.305 13.82 285.305 13.83 286.957 13.84 286.957 13.85 286.957 13.86 286.957 13.87 283.661 13.88 282.028 13.89 277.183 13.9 273.999 13.91 272.421 13.92 270.852 13.93 270.852 13.94 270.852 13.95 272.421 13.96 277.183 13.97 280.403 13.98 283.661 13.99 286.957 14 288.62 14.01 290.292 14.02 291.973 14.03 291.973 14.04 290.292 14.05 288.62 14.06 286.957 14.07 285.305 14.08 282.028 14.09 -277.183 14.1 -273.999 14.11 -270.852 14.12 -267.741 14.13 -266.199 14.14 -266.199 14.15 -266.199 14.16 -269.292 14.17 -272.421 14.18 -275.586 14.19 282.028 14.2 286.957 14.21 290.292 14.22 291.973 14.23 293.665 14.24 293.665 14.25 293.665 14.26 290.292 14.27 288.62 14.28 286.957 14.29 283.661 14.3 278.788 14.31 273.999 14.32 270.852 14.33 269.292 14.34 269.292 14.35 267.741 14.36 269.292 14.37 272.421 14.38 273.999 14.39 280.403 14.4 285.305 14.41 290.292 14.42 293.665 14.43 298.798 14.44 300.529 14.45 298.798 14.46 297.077 14.47 293.665 14.48 288.62 14.49 283.661 14.5 277.183 14.51 275.586 14.52 270.852 14.53 269.292 14.54 269.292 14.55 269.292 14.56 270.852 14.57 277.183 14.58 283.661 14.59 286.957 14.6 290.292 14.61 293.665 14.62 295.366 14.63 293.665 14.64 288.62 14.65 283.661 14.66 272.421 14.67 266.199 14.68 258.621 14.69 255.65 14.7 255.65 14.71 258.621 14.72 266.199 14.73 273.999 14.74 282.028 14.75 288.62 14.76 290.292 14.77 291.973 14.78 291.973 14.79 288.62 14.8 285.305 14.81 275.586 14.82 272.421 14.83 267.741 14.84 266.199 14.85 264.666 14.86 266.199 14.87 266.199 14.88 269.292 14.89 273.999 14.9 282.028 14.91 285.305 14.92 288.62 14.93 290.292 14.94 291.973 14.95 290.292 14.96 288.62 14.97 285.305 14.98 280.403 14.99 277.183 15 275.586 15.01 273.999 15.02 272.421 15.03 275.586 15.04 280.403 15.05 285.305 15.06 290.292 15.07 291.973 15.08 293.665 15.09 293.665 15.1 291.973 15.11 290.292 15.12 291.973 15.13 293.665 15.14 286.957 15.15 -220 15.16 -220 15.17 -220 15.18 -220 15.19 -220 15.2 -220 15.21 -220 15.22 -220 15.23 -220 15.24 -220 15.25 -220 15.26 -220 15.27 -220 15.28 -220 15.29 -220 15.3 -220 15.31 -220 15.32 -220 15.33 -220 15.34 -220 15.35 252.714 15.36 252.714 15.37 254.178 15.38 255.65 15.39 260.119 15.4 278.788 15.41 288.62 15.42 295.366 15.43 297.077 15.44 298.798 15.45 302.27 15.46 307.553 15.47 309.335 15.48 304.021 15.49 297.077 15.5 290.292 15.51 278.788 15.52 273.999 15.53 272.421 15.54 273.999 15.55 275.586 15.56 280.403 15.57 286.957 15.58 291.973 15.59 297.077 15.6 309.335 15.61 314.742 15.62 318.399 15.63 323.965 15.64 323.965 15.65 320.244 15.66 312.929 15.67 305.782 15.68 298.798 15.69 293.665 15.7 288.62 15.71 283.661 15.72 280.403 15.73 278.788 15.74 278.788 15.75 282.028 15.76 285.305 15.77 288.62 15.78 293.665 15.79 298.798 15.8 307.553 15.81 309.335 15.82 311.127 15.83 316.565 15.84 316.565 15.85 314.742 15.86 311.127 15.87 304.021 15.88 298.798 15.89 291.973 15.9 288.62 15.91 285.305 15.92 278.788 15.93 277.183 15.94 280.403 15.95 280.403 15.96 282.028 15.97 286.957 15.98 291.973 15.99 295.366 16 300.529 16.01 305.782 16.02 309.335 16.03 314.742 16.04 314.742 16.05 312.929 16.06 311.127 16.07 305.782 16.08 300.529 16.09 295.366 16.1 290.292 16.11 286.957 16.12 282.028 16.13 280.403 16.14 280.403 16.15 282.028 16.16 282.028 16.17 285.305 16.18 290.292 16.19 291.973 16.2 297.077 16.21 302.27 16.22 307.553 16.23 311.127 16.24 314.742 16.25 314.742 16.26 312.929 16.27 312.929 16.28 309.335 16.29 307.553 16.3 300.529 16.31 295.366 16.32 290.292 16.33 286.957 16.34 283.661 16.35 278.788 16.36 278.788 16.37 280.403 16.38 282.028 16.39 283.661 16.4 288.62 16.41 293.665 16.42 297.077 16.43 304.021 16.44 309.335 16.45 316.565 16.46 318.399 16.47 320.244 16.48 320.244 16.49 318.399 16.5 312.929 16.51 309.335 16.52 300.529 16.53 295.366 16.54 290.292 16.55 286.957 16.56 285.305 16.57 282.028 16.58 282.028 16.59 283.661 16.6 285.305 16.61 288.62 16.62 291.973 16.63 297.077 16.64 300.529 16.65 305.782 16.66 309.335 16.67 312.929 16.68 316.565 16.69 318.399 16.7 320.244 16.71 316.565 16.72 312.929 16.73 307.553 16.74 302.27 16.75 297.077 16.76 291.973 16.77 285.305 16.78 283.661 16.79 282.028 16.8 282.028 16.81 283.661 16.82 285.305 16.83 288.62 16.84 295.366 16.85 298.798 16.86 302.27 16.87 305.782 16.88 307.553 16.89 309.335 16.9 307.553 16.91 307.553 16.92 305.782 16.93 302.27 16.94 300.529 16.95 297.077 16.96 295.366 16.97 291.973 16.98 290.292 16.99 290.292 17 290.292 17.01 288.62 17.02 290.292 17.03 290.292 17.04 291.973 17.05 293.665 17.06 295.366 17.07 297.077 17.08 298.798 17.09 300.529 17.1 304.021 17.11 305.782 17.12 307.553 17.13 307.553 17.14 305.782 17.15 302.27 17.16 297.077 17.17 290.292 17.18 286.957 17.19 285.305 17.2 283.661 17.21 283.661 17.22 283.661 17.23 285.305 17.24 288.62 17.25 291.973 17.26 295.366 17.27 298.798 17.28 304.021 17.29 307.553 17.3 309.335 17.31 312.929 17.32 316.565 17.33 312.929 17.34 311.127 17.35 304.021 17.36 300.529 17.37 295.366 17.38 293.665 17.39 290.292 17.4 285.305 17.41 283.661 17.42 282.028 17.43 283.661 17.44 285.305 17.45 286.957 17.46 288.62 17.47 290.292 17.48 293.665 17.49 298.798 17.5 302.27 17.51 309.335 17.52 312.929 17.53 318.399 17.54 320.244 17.55 314.742 17.56 312.929 17.57 309.335 17.58 304.021 17.59 300.529 17.6 293.665 17.61 291.973 17.62 288.62 17.63 286.957 17.64 285.305 17.65 285.305 17.66 286.957 17.67 290.292 17.68 291.973 17.69 295.366 17.7 298.798 17.71 302.27 17.72 305.782 17.73 309.335 17.74 314.742 17.75 316.565 17.76 316.565 17.77 312.929 17.78 309.335 17.79 307.553 17.8 302.27 17.81 298.798 17.82 293.665 17.83 291.973 17.84 290.292 17.85 288.62 17.86 288.62 17.87 288.62 17.88 288.62 17.89 291.973 17.9 291.973 17.91 295.366 17.92 297.077 17.93 300.529 17.94 302.27 17.95 304.021 17.96 305.782 17.97 309.335 17.98 311.127 17.99 311.127 18 305.782 18.01 302.27 18.02 298.798 18.03 297.077 18.04 295.366 18.05 291.973 18.06 291.973 18.07 290.292 18.08 288.62 18.09 288.62 18.1 290.292 18.11 291.973 18.12 293.665 18.13 297.077 18.14 298.798 18.15 304.021 18.16 309.335 18.17 311.127 18.18 312.929 18.19 312.929 18.2 312.929 18.21 309.335 18.22 307.553 18.23 300.529 18.24 295.366 18.25 293.665 18.26 291.973 18.27 290.292 18.28 288.62 18.29 286.957 18.3 285.305 18.31 286.957 18.32 288.62 18.33 290.292 18.34 293.665 18.35 297.077 18.36 298.798 18.37 304.021 18.38 309.335 18.39 312.929 18.4 316.565 18.41 316.565 18.42 314.742 18.43 312.929 18.44 309.335 18.45 305.782 18.46 300.529 18.47 297.077 18.48 291.973 18.49 291.973 18.5 290.292 18.51 290.292 18.52 288.62 18.53 288.62 18.54 290.292 18.55 293.665 18.56 297.077 18.57 302.27 18.58 304.021 18.59 305.782 18.6 307.553 18.61 309.335 18.62 311.127 18.63 311.127 18.64 311.127 18.65 307.553 18.66 304.021 18.67 300.529 18.68 295.366 18.69 293.665 18.7 290.292 18.71 288.62 18.72 286.957 18.73 285.305 18.74 286.957 18.75 286.957 18.76 288.62 18.77 291.973 18.78 297.077 18.79 302.27 18.8 307.553 18.81 312.929 18.82 316.565 18.83 320.244 18.84 322.099 18.85 322.099 18.86 320.244 18.87 318.399 18.88 311.127 18.89 305.782 18.9 295.366 18.91 290.292 18.92 283.661 18.93 278.788 18.94 278.788 18.95 273.999 18.96 273.999 18.97 275.586 18.98 280.403 18.99 285.305 19 286.957 19.01 293.665 19.02 297.077 19.03 302.27 19.04 311.127 19.05 314.742 19.06 318.399 19.07 318.399 19.08 314.742 19.09 312.929 19.1 305.782 19.11 302.27 19.12 298.798 19.13 291.973 19.14 288.62 19.15 286.957 19.16 285.305 19.17 285.305 19.18 285.305 19.19 286.957 19.2 290.292 19.21 293.665 19.22 298.798 19.23 304.021 19.24 311.127 19.25 314.742 19.26 322.099 19.27 323.965 19.28 323.965 19.29 322.099 19.3 323.965 19.31 316.565 19.32 311.127 19.33 302.27 19.34 297.077 19.35 290.292 19.36 286.957 19.37 282.028 19.38 278.788 19.39 280.403 19.4 286.957 19.41 288.62 19.42 290.292 19.43 293.665 19.44 297.077 19.45 300.529 19.46 305.782 19.47 307.553 19.48 311.127 19.49 311.127 19.5 312.929 19.51 311.127 19.52 309.335 19.53 304.021 19.54 300.529 19.55 297.077 19.56 295.366 19.57 291.973 19.58 291.973 19.59 290.292 19.6 288.62 19.61 286.957 19.62 288.62 19.63 290.292 19.64 291.973 19.65 297.077 19.66 300.529 19.67 305.782 19.68 311.127 19.69 312.929 19.7 314.742 19.71 314.742 19.72 314.742 19.73 312.929 19.74 311.127 19.75 304.021 19.76 300.529 19.77 297.077 19.78 293.665 19.79 290.292 19.8 288.62 19.81 286.957 19.82 286.957 19.83 286.957 19.84 290.292 19.85 293.665 19.86 297.077 19.87 304.021 19.88 311.127 19.89 314.742 19.9 318.399 19.91 318.399 19.92 318.399 19.93 318.399 19.94 314.742 19.95 311.127 19.96 302.27 19.97 297.077 19.98 288.62 19.99 282.028 20 277.183 20.01 275.586 20.02 273.999 20.03 275.586 20.04 278.788 20.05 283.661 20.06 288.62 20.07 293.665 20.08 297.077 20.09 305.782 20.1 311.127 20.11 314.742 20.12 318.399 20.13 316.565 20.14 311.127 20.15 309.335 20.16 304.021 20.17 298.798 20.18 295.366 20.19 291.973 20.2 288.62 20.21 285.305 20.22 285.305 20.23 283.661 20.24 285.305 20.25 288.62 20.26 291.973 20.27 297.077 20.28 298.798 20.29 302.27 20.3 305.782 20.31 312.929 20.32 314.742 20.33 311.127 20.34 309.335 20.35 307.553 20.36 300.529 20.37 297.077 20.38 291.973 20.39 288.62 20.4 286.957 20.41 286.957 20.42 286.957 20.43 290.292 20.44 288.62 20.45 290.292 20.46 291.973 20.47 293.665 20.48 295.366 20.49 298.798 20.5 302.27 20.51 304.021 20.52 304.021 20.53 298.798 20.54 297.077 20.55 295.366 20.56 295.366 20.57 295.366 20.58 295.366 20.59 297.077 20.6 298.798 20.61 302.27 20.62 307.553 20.63 307.553 20.64 305.782 20.65 305.782 20.66 309.335 20.67 307.553 20.68 307.553 20.69 305.782 20.7 300.529 20.71 293.665 20.72 -220 20.73 -220 20.74 -297.077 20.75 -295.366 20.76 -297.077 20.77 -297.077 20.78 -297.077 20.79 -297.077 20.8 -295.366 20.81 -295.366 20.82 -297.077 20.83 -295.366 20.84 -295.366 20.85 -297.077 20.86 -297.077 20.87 -297.077 20.88 -297.077 20.89 -295.366 20.9 -297.077 20.91 -295.366 20.92 -295.366 20.93 -293.665 20.94 -220 20.95 -220 20.96 -220 20.97 -297.077 20.98 -295.366 20.99 -293.665 21 -290.292 21.01 -283.661 21.02 -280.403 21.03 -277.183 21.04 -273.999 21.05 -275.586 21.06 -278.788 21.07 -283.661 21.08 -286.957 21.09 -288.62 21.1 -293.665 21.11 -293.665 21.12 -297.077 21.13 -298.798 21.14 -300.529 21.15 -302.27 21.16 -302.27 21.17 -298.798 21.18 -295.366 21.19 -290.292 21.2 -283.661 21.21 -267.741 21.22 -264.666 21.23 -264.666 21.24 -263.141 21.25 -266.199 21.26 -270.852 21.27 -280.403 21.28 -293.665 21.29 -298.798 21.3 -305.782 21.31 -311.127 21.32 -316.565 21.33 -314.742 21.34 -311.127 21.35 -304.021 21.36 -220 21.37 -220 21.38 -220 21.39 -220 21.4 -220 21.41 -220 21.42 -220 21.43 -220 21.44 -220 21.45 -220 21.46 -220 21.47 -220 21.48 -220 21.49 -220 21.5 -220 21.51 -220 21.52 -220 21.53 -220 21.54 -220 21.55 -220 21.56 -220 21.57 -220 21.58 -220 21.59 -220 21.6 -220 21.61 -220 21.62 -220 21.63 -220 21.64 -220 21.65 -220 21.66 -220 21.67 -220 21.68 -220 21.69 -220 21.7 -220 21.71 -220 21.72 -220 21.73 -220 21.74 -220 21.75 -220 21.76 -220 21.77 -220 21.78 -220 21.79 -220 21.8 -220 21.81 -220 21.82 -220 21.83 -220 21.84 -220 21.85 -220 21.86 -220 21.87 -220 21.88 -220 21.89 -220 21.9 -220 21.91 -220 21.92 -220 21.93 -220 21.94 -220 21.95 -220 21.96 -220 21.97 -220 21.98 -220 21.99 -220 22 -220 22.01 -220 22.02 -220 22.03 -220 22.04 -220 22.05 -220 22.06 -220 22.07 -220 22.08 -220 22.09 -220 22.1 -220 22.11 -220 22.12 -220 22.13 -220 22.14 -220 22.15 -220 mir_eval-0.8.2/tests/data/melody/est09.txt000077500000000000000000000665441475740344600204300ustar00rootroot000000000000000 0 0.01 0 0.02 161.049 0.03 159.2 0.04 153.777 0.05 144.31 0.06 154.668 0.07 157.371 0.08 161.982 0.09 168.666 0.1 172.609 0.11 174.614 0.12 174.614 0.13 172.609 0.14 174.614 0.15 175.626 0.16 174.614 0.17 173.608 0.18 174.614 0.19 175.626 0.2 176.643 0.21 177.666 0.22 177.666 0.23 176.643 0.24 176.643 0.25 176.643 0.26 176.643 0.27 176.643 0.28 178.696 0.29 179.731 0.3 174.614 0.31 175.626 0.32 175.626 0.33 175.626 0.34 175.626 0.35 175.626 0.36 175.626 0.37 175.626 0.38 175.626 0.39 175.626 0.4 175.626 0.41 175.626 0.42 175.626 0.43 175.626 0.44 174.614 0.45 174.614 0.46 174.614 0.47 175.626 0.48 175.626 0.49 176.643 0.5 175.626 0.51 177.666 0.52 177.666 0.53 176.643 0.54 176.643 0.55 177.666 0.56 177.666 0.57 178.696 0.58 178.696 0.59 177.666 0.6 177.666 0.61 176.643 0.62 176.643 0.63 176.643 0.64 176.643 0.65 176.643 0.66 176.643 0.67 177.666 0.68 177.666 0.69 178.696 0.7 178.696 0.71 179.731 0.72 178.696 0.73 179.731 0.74 178.696 0.75 177.666 0.76 177.666 0.77 178.696 0.78 178.696 0.79 178.696 0.8 177.666 0.81 176.643 0.82 176.643 0.83 175.626 0.84 173.608 0.85 172.609 0.86 171.614 0.87 171.614 0.88 177.666 0.89 170.626 0.9 172.609 0.91 169.643 0.92 173.608 0.93 175.626 0.94 168.666 0.95 172.609 0.96 181.819 0.97 187.147 0.98 193.746 0.99 195.998 1 202.91 1.01 202.91 1.02 204.085 1.03 201.741 1.04 199.424 1.05 199.424 1.06 198.275 1.07 194.869 1.08 193.746 1.09 197.133 1.1 198.275 1.11 195.998 1.12 197.133 1.13 198.275 1.14 199.424 1.15 197.133 1.16 197.133 1.17 200.579 1.18 200.579 1.19 199.424 1.2 199.424 1.21 199.424 1.22 199.424 1.23 199.424 1.24 198.275 1.25 199.424 1.26 198.275 1.27 197.133 1.28 198.275 1.29 198.275 1.3 195.998 1.31 195.998 1.32 198.275 1.33 197.133 1.34 187.147 1.35 -220 1.36 -220 1.37 -220 1.38 -220 1.39 -220 1.4 -220 1.41 -220 1.42 -220 1.43 -220 1.44 -220 1.45 -220 1.46 -220 1.47 -220 1.48 202.91 1.49 202.91 1.5 201.741 1.51 201.741 1.52 201.741 1.53 201.741 1.54 202.91 1.55 206.456 1.56 208.855 1.57 208.855 1.58 212.506 1.59 216.221 1.6 218.733 1.61 220 1.62 220 1.63 218.733 1.64 218.733 1.65 217.473 1.66 214.975 1.67 216.221 1.68 214.975 1.69 213.737 1.7 214.975 1.71 216.221 1.72 216.221 1.73 216.221 1.74 216.221 1.75 216.221 1.76 217.473 1.77 217.473 1.78 213.737 1.79 212.506 1.8 214.975 1.81 216.221 1.82 216.221 1.83 212.506 1.84 210.065 1.85 207.652 1.86 204.085 1.87 206.456 1.88 -147.683 1.89 199.424 1.9 198.275 1.91 198.275 1.92 197.133 1.93 197.133 1.94 197.133 1.95 194.869 1.96 194.869 1.97 194.869 1.98 194.869 1.99 197.133 2 199.424 2.01 195.998 2.02 197.133 2.03 195.998 2.04 194.869 2.05 195.998 2.06 194.869 2.07 193.746 2.08 194.869 2.09 195.998 2.1 194.869 2.11 -145.987 2.12 -146.832 2.13 -145.987 2.14 -145.987 2.15 -145.987 2.16 -145.987 2.17 -145.987 2.18 -145.987 2.19 -145.987 2.2 -145.987 2.21 -145.987 2.22 -145.987 2.23 -145.987 2.24 -145.987 2.25 194.869 2.26 195.998 2.27 195.998 2.28 195.998 2.29 195.998 2.3 194.869 2.31 195.998 2.32 195.998 2.33 195.998 2.34 195.998 2.35 195.998 2.36 195.998 2.37 197.133 2.38 197.133 2.39 195.998 2.4 195.998 2.41 194.869 2.42 195.998 2.43 197.133 2.44 197.133 2.45 195.998 2.46 195.998 2.47 195.998 2.48 197.133 2.49 195.998 2.5 194.869 2.51 195.998 2.52 197.133 2.53 197.133 2.54 195.998 2.55 195.998 2.56 197.133 2.57 197.133 2.58 197.133 2.59 195.998 2.6 195.998 2.61 199.424 2.62 199.424 2.63 198.275 2.64 -220 2.65 -220 2.66 -220 2.67 -220 2.68 -220 2.69 -220 2.7 -220 2.71 -220 2.72 -220 2.73 -220 2.74 -220 2.75 -220 2.76 -220 2.77 -220 2.78 -220 2.79 -220 2.8 -220 2.81 -220 2.82 -220 2.83 -220 2.84 -220 2.85 176.643 2.86 177.666 2.87 176.643 2.88 176.643 2.89 176.643 2.9 174.614 2.91 173.608 2.92 174.614 2.93 174.614 2.94 173.608 2.95 173.608 2.96 174.614 2.97 174.614 2.98 173.608 2.99 175.626 3 175.626 3.01 176.643 3.02 176.643 3.03 176.643 3.04 176.643 3.05 175.626 3.06 174.614 3.07 175.626 3.08 175.626 3.09 175.626 3.1 176.643 3.11 176.643 3.12 175.626 3.13 175.626 3.14 175.626 3.15 176.643 3.16 178.696 3.17 179.731 3.18 -220 3.19 -220 3.2 -220 3.21 -220 3.22 -220 3.23 -220 3.24 -220 3.25 -220 3.26 -220 3.27 -220 3.28 -220 3.29 -220 3.3 -220 3.31 -220 3.32 -220 3.33 -220 3.34 -220 3.35 -220 3.36 -220 3.37 -220 3.38 -220 3.39 -220 3.4 -220 3.41 -220 3.42 -220 3.43 -220 3.44 -220 3.45 -220 3.46 -220 3.47 -220 3.48 -220 3.49 -220 3.5 -220 3.51 -220 3.52 -220 3.53 -220 3.54 -220 3.55 -220 3.56 -220 3.57 -220 3.58 -220 3.59 -220 3.6 -220 3.61 -220 3.62 -220 3.63 -220 3.64 -220 3.65 -220 3.66 -220 3.67 -220 3.68 -220 3.69 -220 3.7 -220 3.71 191.521 3.72 189.321 3.73 181.819 3.74 182.872 3.75 184.997 3.76 186.069 3.77 189.321 3.78 190.418 3.79 191.521 3.8 192.631 3.81 194.869 3.82 197.133 3.83 200.579 3.84 201.741 3.85 202.91 3.86 204.085 3.87 204.085 3.88 205.267 3.89 205.267 3.9 204.085 3.91 204.085 3.92 204.085 3.93 202.91 3.94 204.085 3.95 204.085 3.96 205.267 3.97 205.267 3.98 -153.777 3.99 -153.777 4 -153.777 4.01 -154.668 4.02 -154.668 4.03 -153.777 4.04 -153.777 4.05 -153.777 4.06 -152.891 4.07 -152.891 4.08 -153.777 4.09 204.085 4.1 204.085 4.11 204.085 4.12 204.085 4.13 204.085 4.14 205.267 4.15 206.456 4.16 206.456 4.17 206.456 4.18 206.456 4.19 206.456 4.2 206.456 4.21 206.456 4.22 206.456 4.23 207.652 4.24 206.456 4.25 206.456 4.26 206.456 4.27 206.456 4.28 205.267 4.29 205.267 4.3 207.652 4.31 206.456 4.32 205.267 4.33 205.267 4.34 206.456 4.35 205.267 4.36 204.085 4.37 205.267 4.38 204.085 4.39 -220 4.4 -229.078 4.41 -226.446 4.42 -234.432 4.43 -233.082 4.44 206.456 4.45 211.282 4.46 207.652 4.47 204.085 4.48 210.065 4.49 212.506 4.5 208.855 4.51 206.456 4.52 207.652 4.53 211.282 4.54 208.855 4.55 204.085 4.56 202.91 4.57 207.652 4.58 206.456 4.59 199.424 4.6 195.998 4.61 204.085 4.62 222.556 4.63 182.872 4.64 187.147 4.65 187.147 4.66 186.069 4.67 186.069 4.68 187.147 4.69 189.321 4.7 190.418 4.71 192.631 4.72 193.746 4.73 198.275 4.74 200.579 4.75 204.085 4.76 205.267 4.77 205.267 4.78 205.267 4.79 205.267 4.8 204.085 4.81 204.085 4.82 204.085 4.83 204.085 4.84 202.91 4.85 205.267 4.86 204.085 4.87 204.085 4.88 205.267 4.89 205.267 4.9 205.267 4.91 205.267 4.92 205.267 4.93 206.456 4.94 205.267 4.95 204.085 4.96 205.267 4.97 204.085 4.98 204.085 4.99 204.085 5 205.267 5.01 205.267 5.02 205.267 5.03 204.085 5.04 205.267 5.05 205.267 5.06 205.267 5.07 204.085 5.08 205.267 5.09 204.085 5.1 204.085 5.11 205.267 5.12 204.085 5.13 204.085 5.14 206.456 5.15 206.456 5.16 205.267 5.17 205.267 5.18 205.267 5.19 205.267 5.2 205.267 5.21 206.456 5.22 206.456 5.23 206.456 5.24 206.456 5.25 205.267 5.26 204.085 5.27 201.741 5.28 200.579 5.29 199.424 5.3 198.275 5.31 197.133 5.32 195.998 5.33 194.869 5.34 195.998 5.35 197.133 5.36 199.424 5.37 197.133 5.38 198.275 5.39 198.275 5.4 197.133 5.41 195.998 5.42 197.133 5.43 197.133 5.44 198.275 5.45 197.133 5.46 197.133 5.47 198.275 5.48 195.998 5.49 193.746 5.5 198.275 5.51 199.424 5.52 199.424 5.53 201.741 5.54 194.869 5.55 190.418 5.56 197.133 5.57 197.133 5.58 195.998 5.59 195.998 5.6 195.998 5.61 195.998 5.62 197.133 5.63 195.998 5.64 195.998 5.65 197.133 5.66 195.998 5.67 194.869 5.68 197.133 5.69 195.998 5.7 195.998 5.71 195.998 5.72 195.998 5.73 197.133 5.74 195.998 5.75 194.869 5.76 195.998 5.77 194.869 5.78 194.869 5.79 194.869 5.8 195.998 5.81 197.133 5.82 197.133 5.83 197.133 5.84 195.998 5.85 195.998 5.86 195.998 5.87 197.133 5.88 197.133 5.89 197.133 5.9 197.133 5.91 195.998 5.92 198.275 5.93 200.579 5.94 201.741 5.95 204.085 5.96 206.456 5.97 206.456 5.98 210.065 5.99 213.737 6 213.737 6.01 214.975 6.02 213.737 6.03 211.282 6.04 210.065 6.05 207.652 6.06 207.652 6.07 206.456 6.08 206.456 6.09 205.267 6.1 205.267 6.11 205.267 6.12 205.267 6.13 205.267 6.14 205.267 6.15 206.456 6.16 206.456 6.17 205.267 6.18 206.456 6.19 205.267 6.2 207.652 6.21 207.652 6.22 206.456 6.23 194.869 6.24 200.579 6.25 204.085 6.26 208.855 6.27 212.506 6.28 213.737 6.29 211.282 6.3 207.652 6.31 208.855 6.32 211.282 6.33 205.267 6.34 204.085 6.35 206.456 6.36 206.456 6.37 199.424 6.38 195.998 6.39 190.418 6.4 184.997 6.41 182.872 6.42 182.872 6.43 179.731 6.44 170.626 6.45 172.609 6.46 173.608 6.47 174.614 6.48 175.626 6.49 176.643 6.5 178.696 6.51 182.872 6.52 183.932 6.53 188.231 6.54 190.418 6.55 192.631 6.56 195.998 6.57 197.133 6.58 197.133 6.59 198.275 6.6 197.133 6.61 197.133 6.62 197.133 6.63 197.133 6.64 198.275 6.65 198.275 6.66 197.133 6.67 197.133 6.68 197.133 6.69 197.133 6.7 197.133 6.71 197.133 6.72 197.133 6.73 197.133 6.74 197.133 6.75 197.133 6.76 197.133 6.77 198.275 6.78 195.998 6.79 193.746 6.8 191.521 6.81 191.521 6.82 189.321 6.83 187.147 6.84 183.932 6.85 178.696 6.86 172.609 6.87 179.731 6.88 177.666 6.89 170.626 6.9 173.608 6.91 173.608 6.92 173.608 6.93 175.626 6.94 175.626 6.95 174.614 6.96 176.643 6.97 176.643 6.98 176.643 6.99 176.643 7 176.643 7.01 176.643 7.02 176.643 7.03 177.666 7.04 177.666 7.05 177.666 7.06 174.614 7.07 175.626 7.08 178.696 7.09 178.696 7.1 175.626 7.11 176.643 7.12 178.696 7.13 179.731 7.14 177.666 7.15 176.643 7.16 176.643 7.17 176.643 7.18 175.626 7.19 174.614 7.2 175.626 7.21 178.696 7.22 178.696 7.23 177.666 7.24 175.626 7.25 174.614 7.26 177.666 7.27 178.696 7.28 178.696 7.29 177.666 7.3 176.643 7.31 177.666 7.32 177.666 7.33 178.696 7.34 175.626 7.35 178.696 7.36 173.608 7.37 175.626 7.38 178.696 7.39 176.643 7.4 176.643 7.41 176.643 7.42 174.614 7.43 176.643 7.44 177.666 7.45 174.614 7.46 175.626 7.47 177.666 7.48 175.626 7.49 176.643 7.5 176.643 7.51 175.626 7.52 175.626 7.53 174.614 7.54 174.614 7.55 174.614 7.56 139.394 7.57 136.999 7.58 137.793 7.59 139.394 7.6 137.793 7.61 137.793 7.62 138.591 7.63 137.793 7.64 136.999 7.65 140.202 7.66 137.793 7.67 140.202 7.68 138.591 7.69 136.999 7.7 137.793 7.71 138.591 7.72 136.999 7.73 -171.614 7.74 -175.626 7.75 -175.626 7.76 -174.614 7.77 -175.626 7.78 -174.614 7.79 -172.609 7.8 -174.614 7.81 -177.666 7.82 -177.666 7.83 -176.643 7.84 -177.666 7.85 -179.731 7.86 -179.731 7.87 -179.731 7.88 -179.731 7.89 -177.666 7.9 -177.666 7.91 -176.643 7.92 -178.696 7.93 -177.666 7.94 -175.626 7.95 -177.666 7.96 -178.696 7.97 -176.643 7.98 -176.643 7.99 -177.666 8 -176.643 8.01 -175.626 8.02 -174.614 8.03 -175.626 8.04 -176.643 8.05 -175.626 8.06 -175.626 8.07 -175.626 8.08 -176.643 8.09 -176.643 8.1 -175.626 8.11 -176.643 8.12 -177.666 8.13 -175.626 8.14 -177.666 8.15 -177.666 8.16 -176.643 8.17 -176.643 8.18 -177.666 8.19 -175.626 8.2 -174.614 8.21 -175.626 8.22 -177.666 8.23 -178.696 8.24 -179.731 8.25 -176.643 8.26 -175.626 8.27 -181.819 8.28 -176.643 8.29 -174.614 8.3 -180.772 8.31 -178.696 8.32 -177.666 8.33 -178.696 8.34 -179.731 8.35 -177.666 8.36 -177.666 8.37 -179.731 8.38 -176.643 8.39 -175.626 8.4 -177.666 8.41 -175.626 8.42 -174.614 8.43 -176.643 8.44 -177.666 8.45 -175.626 8.46 -176.643 8.47 -179.731 8.48 -172.609 8.49 -139.394 8.5 -136.999 8.51 -138.591 8.52 -138.591 8.53 -136.999 8.54 -140.202 8.55 -137.793 8.56 -137.793 8.57 -138.591 8.58 -138.591 8.59 -138.591 8.6 -137.793 8.61 -137.793 8.62 -139.394 8.63 -137.793 8.64 -137.793 8.65 -137.793 8.66 -137.793 8.67 -138.591 8.68 -138.591 8.69 -138.591 8.7 -141.831 8.71 -220 8.72 -220 8.73 -220 8.74 -220 8.75 -220 8.76 -220 8.77 -220 8.78 -220 8.79 -220 8.8 -220 8.81 -220 8.82 -220 8.83 -220 8.84 -220 8.85 -220 8.86 -220 8.87 -220 8.88 -220 8.89 -220 8.9 -220 8.91 -220 8.92 -220 8.93 -220 8.94 -220 8.95 -220 8.96 -138.591 8.97 -137.793 8.98 -137.793 8.99 -138.591 9 -137.793 9.01 -138.591 9.02 -137.793 9.03 -137.793 9.04 -138.591 9.05 -137.793 9.06 -137.793 9.07 -138.591 9.08 -137.793 9.09 -220 9.1 -220 9.11 -220 9.12 -220 9.13 -220 9.14 -220 9.15 -220 9.16 -220 9.17 -220 9.18 208.855 9.19 225.142 9.2 233.082 9.21 233.082 9.22 233.082 9.23 233.082 9.24 231.739 9.25 233.082 9.26 233.082 9.27 233.082 9.28 231.739 9.29 230.405 9.3 233.082 9.31 233.082 9.32 231.739 9.33 231.739 9.34 231.739 9.35 231.739 9.36 233.082 9.37 231.739 9.38 234.432 9.39 233.082 9.4 233.082 9.41 233.082 9.42 231.739 9.43 231.739 9.44 233.082 9.45 231.739 9.46 233.082 9.47 233.082 9.48 -154.668 9.49 -155.563 9.5 -154.668 9.51 -155.563 9.52 -153.777 9.53 -153.777 9.54 -154.668 9.55 -154.668 9.56 -155.563 9.57 -153.777 9.58 -154.668 9.59 -155.563 9.6 -154.668 9.61 -152.891 9.62 -151.135 9.63 -145.146 9.64 -148.538 9.65 -155.563 9.66 -155.563 9.67 -154.668 9.68 -220 9.69 -220 9.7 -220 9.71 -220 9.72 -220 9.73 -220 9.74 -220 9.75 -220 9.76 -220 9.77 -220 9.78 -220 9.79 -220 9.8 -220 9.81 -220 9.82 -220 9.83 -220 9.84 -220 9.85 -220 9.86 -220 9.87 -220 9.88 -220 9.89 -220 9.9 -220 9.91 -220 9.92 -220 9.93 -220 9.94 -220 9.95 -220 9.96 -220 9.97 -220 9.98 -220 9.99 -220 10 -220 10.01 -220 10.02 -220 10.03 -220 10.04 -220 10.05 -220 10.06 -220 10.07 -220 10.08 -220 10.09 -220 10.1 -220 10.11 -220 10.12 -220 10.13 -220 10.14 -220 10.15 -220 10.16 -220 10.17 -220 10.18 -220 10.19 -220 10.2 -220 10.21 -220 10.22 -220 10.23 -220 10.24 -220 10.25 -220 10.26 -220 10.27 -220 10.28 -220 10.29 -220 10.3 -220 10.31 -220 10.32 -220 10.33 -220 10.34 -220 10.35 -220 10.36 -220 10.37 -220 10.38 -220 10.39 -220 10.4 -220 10.41 -220 10.42 -220 10.43 -220 10.44 -220 10.45 -220 10.46 -220 10.47 -220 10.48 -220 10.49 -220 10.5 -220 10.51 -220 10.52 -220 10.53 -220 10.54 -220 10.55 -220 10.56 -220 10.57 -220 10.58 -220 10.59 -220 10.6 -220 10.61 -220 10.62 -220 10.63 -220 10.64 -220 10.65 -220 10.66 -220 10.67 -220 10.68 -220 10.69 -220 10.7 -220 10.71 -220 10.72 -220 10.73 -220 10.74 -220 10.75 -220 10.76 -220 10.77 -220 10.78 -220 10.79 -220 10.8 -220 10.81 -220 10.82 -220 10.83 -220 10.84 -220 10.85 -220 10.86 -220 10.87 -220 10.88 130.813 10.89 129.31 10.9 130.813 10.91 131.571 10.92 130.813 10.93 130.813 10.94 130.813 10.95 128.565 10.96 120.651 10.97 127.825 10.98 136.999 10.99 133.87 11 134.646 11.01 131.571 11.02 130.059 11.03 154.668 11.04 155.563 11.05 161.982 11.06 160.122 11.07 160.122 11.08 163.865 11.09 163.865 11.1 164.814 11.11 164.814 11.12 167.695 11.13 169.643 11.14 169.643 11.15 170.626 11.16 169.643 11.17 171.614 11.18 173.608 11.19 172.609 11.2 172.609 11.21 171.614 11.22 173.608 11.23 172.609 11.24 172.609 11.25 171.614 11.26 171.614 11.27 170.626 11.28 171.614 11.29 170.626 11.3 171.614 11.31 172.609 11.32 172.609 11.33 172.609 11.34 173.608 11.35 172.609 11.36 173.608 11.37 173.608 11.38 174.614 11.39 174.614 11.4 175.626 11.41 175.626 11.42 177.666 11.43 177.666 11.44 176.643 11.45 175.626 11.46 175.626 11.47 174.614 11.48 172.609 11.49 173.608 11.5 172.609 11.51 172.609 11.52 171.614 11.53 171.614 11.54 170.626 11.55 171.614 11.56 171.614 11.57 173.608 11.58 174.614 11.59 174.614 11.6 173.608 11.61 173.608 11.62 174.614 11.63 175.626 11.64 175.626 11.65 175.626 11.66 174.614 11.67 175.626 11.68 175.626 11.69 173.608 11.7 173.608 11.71 173.608 11.72 174.614 11.73 173.608 11.74 174.614 11.75 174.614 11.76 174.614 11.77 174.614 11.78 175.626 11.79 175.626 11.8 174.614 11.81 174.614 11.82 174.614 11.83 174.614 11.84 175.626 11.85 177.666 11.86 180.772 11.87 186.069 11.88 188.231 11.89 192.631 11.9 189.321 11.91 197.133 11.92 195.998 11.93 195.998 11.94 194.869 11.95 193.746 11.96 190.418 11.97 190.418 11.98 190.418 11.99 190.418 12 191.521 12.01 189.321 12.02 188.231 12.03 190.418 12.04 191.521 12.05 192.631 12.06 192.631 12.07 192.631 12.08 193.746 12.09 194.869 12.1 192.631 12.11 192.631 12.12 191.521 12.13 191.521 12.14 181.819 12.15 179.731 12.16 173.608 12.17 171.614 12.18 177.666 12.19 183.932 12.2 192.631 12.21 199.424 12.22 197.133 12.23 194.869 12.24 198.275 12.25 199.424 12.26 194.869 12.27 189.321 12.28 184.997 12.29 179.731 12.3 -174.614 12.31 -220 12.32 -220 12.33 -220 12.34 -220 12.35 -220 12.36 205.267 12.37 201.741 12.38 200.579 12.39 199.424 12.4 200.579 12.41 201.741 12.42 202.91 12.43 205.267 12.44 206.456 12.45 207.652 12.46 208.855 12.47 210.065 12.48 210.065 12.49 211.282 12.5 213.737 12.51 214.975 12.52 220 12.53 -220 12.54 -220 12.55 -220 12.56 -220 12.57 -171.614 12.58 -172.609 12.59 -173.608 12.6 -173.608 12.61 -173.608 12.62 -173.608 12.63 -173.608 12.64 -172.609 12.65 -173.608 12.66 -173.608 12.67 -173.608 12.68 -173.608 12.69 -172.609 12.7 -173.608 12.71 -173.608 12.72 -174.614 12.73 -173.608 12.74 -172.609 12.75 -172.609 12.76 -174.614 12.77 -170.626 12.78 -171.614 12.79 169.643 12.8 173.608 12.81 208.855 12.82 208.855 12.83 205.267 12.84 201.741 12.85 199.424 12.86 195.998 12.87 195.998 12.88 194.869 12.89 194.869 12.9 194.869 12.91 193.746 12.92 194.869 12.93 193.746 12.94 194.869 12.95 194.869 12.96 194.869 12.97 192.631 12.98 194.869 12.99 195.998 13 194.869 13.01 194.869 13.02 194.869 13.03 195.998 13.04 195.998 13.05 194.869 13.06 194.869 13.07 195.998 13.08 195.998 13.09 194.869 13.1 195.998 13.11 195.998 13.12 195.998 13.13 195.998 13.14 194.869 13.15 194.869 13.16 195.998 13.17 195.998 13.18 195.998 13.19 197.133 13.2 195.998 13.21 197.133 13.22 195.998 13.23 195.998 13.24 193.746 13.25 194.869 13.26 194.869 13.27 194.869 13.28 194.869 13.29 193.746 13.3 191.521 13.31 194.869 13.32 194.869 13.33 193.746 13.34 194.869 13.35 193.746 13.36 197.133 13.37 198.275 13.38 198.275 13.39 197.133 13.4 200.579 13.41 198.275 13.42 193.746 13.43 191.521 13.44 186.069 13.45 178.696 13.46 174.614 13.47 167.695 13.48 153.777 13.49 158.283 13.5 158.283 13.51 156.465 13.52 152.891 13.53 146.832 13.54 148.538 13.55 157.371 13.56 167.695 13.57 172.609 13.58 170.626 13.59 168.666 13.6 173.608 13.61 175.626 13.62 174.614 13.63 176.643 13.64 177.666 13.65 174.614 13.66 169.643 13.67 170.626 13.68 171.614 13.69 173.608 13.7 177.666 13.71 173.608 13.72 172.609 13.73 174.614 13.74 177.666 13.75 177.666 13.76 178.696 13.77 177.666 13.78 175.626 13.79 175.626 13.8 173.608 13.81 173.608 13.82 173.608 13.83 173.608 13.84 173.608 13.85 173.608 13.86 173.608 13.87 175.626 13.88 176.643 13.89 175.626 13.9 176.643 13.91 175.626 13.92 173.608 13.93 173.608 13.94 174.614 13.95 172.609 13.96 173.608 13.97 174.614 13.98 175.626 13.99 171.614 14 171.614 14.01 175.626 14.02 175.626 14.03 169.643 14.04 174.614 14.05 177.666 14.06 174.614 14.07 177.666 14.08 180.772 14.09 178.696 14.1 178.696 14.11 177.666 14.12 174.614 14.13 172.609 14.14 170.626 14.15 178.696 14.16 188.231 14.17 -220 14.18 -220 14.19 -220 14.2 -220 14.21 -220 14.22 -220 14.23 -220 14.24 -220 14.25 -220 14.26 -220 14.27 -220 14.28 -220 14.29 -220 14.3 -220 14.31 -220 14.32 -220 14.33 -220 14.34 -220 14.35 -220 14.36 -220 14.37 -220 14.38 -220 14.39 -220 14.4 -220 14.41 -295.366 14.42 -293.665 14.43 -291.973 14.44 -293.665 14.45 -291.973 14.46 -290.292 14.47 -291.973 14.48 -295.366 14.49 -295.366 14.5 -286.957 14.51 -291.973 14.52 -297.077 14.53 -293.665 14.54 -288.62 14.55 -291.973 14.56 -290.292 14.57 -293.665 14.58 -291.973 14.59 -149.399 14.6 -151.135 14.61 394.266 14.62 383.042 14.63 361.544 14.64 361.544 14.65 363.638 14.66 365.745 14.67 365.745 14.68 367.863 14.69 372.138 14.7 380.836 14.71 383.042 14.72 383.042 14.73 387.493 14.74 391.995 14.75 394.266 14.76 396.55 14.77 398.847 14.78 403.482 14.79 405.819 14.8 408.17 14.81 408.17 14.82 405.819 14.83 405.819 14.84 405.819 14.85 408.17 14.86 408.17 14.87 408.17 14.88 410.535 14.89 412.913 14.9 410.535 14.91 410.535 14.92 412.913 14.93 410.535 14.94 410.535 14.95 410.535 14.96 410.535 14.97 412.913 14.98 412.913 14.99 412.913 15 412.913 15.01 412.913 15.02 412.913 15.03 412.913 15.04 412.913 15.05 412.913 15.06 412.913 15.07 417.711 15.08 410.535 15.09 410.535 15.1 410.535 15.11 410.535 15.12 410.535 15.13 410.535 15.14 408.17 15.15 408.17 15.16 408.17 15.17 410.535 15.18 412.913 15.19 412.913 15.2 410.535 15.21 410.535 15.22 410.535 15.23 410.535 15.24 410.535 15.25 410.535 15.26 412.913 15.27 412.913 15.28 412.913 15.29 415.305 15.3 415.305 15.31 415.305 15.32 417.711 15.33 417.711 15.34 -230.405 15.35 -233.082 15.36 -231.739 15.37 -233.082 15.38 -231.739 15.39 -231.739 15.4 -231.739 15.41 -231.739 15.42 -231.739 15.43 -231.739 15.44 -231.739 15.45 -230.405 15.46 -233.082 15.47 -231.739 15.48 -230.405 15.49 -233.082 15.5 -234.432 15.51 -249.811 15.52 188.231 15.53 194.869 15.54 191.521 15.55 189.321 15.56 187.147 15.57 186.069 15.58 187.147 15.59 189.321 15.6 193.746 15.61 194.869 15.62 195.998 15.63 198.275 15.64 201.741 15.65 204.085 15.66 206.456 15.67 208.855 15.68 208.855 15.69 207.652 15.7 210.065 15.71 210.065 15.72 208.855 15.73 208.855 15.74 211.282 15.75 211.282 15.76 210.065 15.77 208.855 15.78 207.652 15.79 212.506 15.8 212.506 15.81 208.855 15.82 208.855 15.83 210.065 15.84 211.282 15.85 210.065 15.86 207.652 15.87 207.652 15.88 210.065 15.89 208.855 15.9 206.456 15.91 206.456 15.92 210.065 15.93 208.855 15.94 206.456 15.95 206.456 15.96 208.855 15.97 208.855 15.98 206.456 15.99 207.652 16 206.456 16.01 205.267 16.02 210.065 16.03 206.456 16.04 205.267 16.05 210.065 16.06 208.855 16.07 205.267 16.08 206.456 16.09 208.855 16.1 207.652 16.11 207.652 16.12 207.652 16.13 207.652 16.14 210.065 16.15 208.855 16.16 206.456 16.17 207.652 16.18 208.855 16.19 206.456 16.2 202.91 16.21 201.741 16.22 204.085 16.23 199.424 16.24 197.133 16.25 198.275 16.26 198.275 16.27 194.869 16.28 195.998 16.29 195.998 16.3 197.133 16.31 198.275 16.32 195.998 16.33 195.998 16.34 199.424 16.35 198.275 16.36 198.275 16.37 198.275 16.38 198.275 16.39 198.275 16.4 198.275 16.41 197.133 16.42 199.424 16.43 198.275 16.44 198.275 16.45 198.275 16.46 199.424 16.47 198.275 16.48 195.998 16.49 197.133 16.5 195.998 16.51 197.133 16.52 199.424 16.53 199.424 16.54 202.91 16.55 199.424 16.56 197.133 16.57 198.275 16.58 197.133 16.59 195.998 16.6 198.275 16.61 197.133 16.62 197.133 16.63 198.275 16.64 197.133 16.65 197.133 16.66 195.998 16.67 195.998 16.68 194.869 16.69 194.869 16.7 194.869 16.71 197.133 16.72 195.998 16.73 197.133 16.74 195.998 16.75 197.133 16.76 197.133 16.77 195.998 16.78 -220 16.79 -220 16.8 -220 16.81 -220 16.82 -220 16.83 -220 16.84 -220 16.85 -220 16.86 -220 16.87 -220 16.88 -220 16.89 204.085 16.9 202.91 16.91 205.267 16.92 207.652 16.93 207.652 16.94 207.652 16.95 206.456 16.96 205.267 16.97 205.267 16.98 205.267 16.99 205.267 17 205.267 17.01 205.267 17.02 205.267 17.03 205.267 17.04 206.456 17.05 207.652 17.06 207.652 17.07 207.652 17.08 210.065 17.09 -220 17.1 -220 17.11 -220 17.12 -220 17.13 -220 17.14 -220 17.15 -220 17.16 -220 17.17 -220 17.18 -220 17.19 -220 17.2 -220 17.21 -220 17.22 -220 17.23 -220 17.24 -220 17.25 -220 17.26 -220 17.27 -220 17.28 -220 17.29 -220 17.3 -220 17.31 -220 17.32 169.643 17.33 173.608 17.34 174.614 17.35 176.643 17.36 179.731 17.37 179.731 17.38 178.696 17.39 179.731 17.4 180.772 17.41 181.819 17.42 182.872 17.43 186.069 17.44 189.321 17.45 191.521 17.46 194.869 17.47 197.133 17.48 198.275 17.49 200.579 17.5 201.741 17.51 200.579 17.52 199.424 17.53 197.133 17.54 194.869 17.55 194.869 17.56 194.869 17.57 194.869 17.58 194.869 17.59 194.869 17.6 195.998 17.61 197.133 17.62 199.424 17.63 198.275 17.64 -220 17.65 -220 17.66 -220 17.67 -220 17.68 -220 17.69 -220 17.7 -220 17.71 -220 17.72 -220 17.73 -220 17.74 -220 17.75 -220 17.76 -220 17.77 -220 17.78 -220 17.79 173.608 17.8 179.731 17.81 182.872 17.82 183.932 17.83 182.872 17.84 180.772 17.85 178.696 17.86 178.696 17.87 176.643 17.88 176.643 17.89 175.626 17.9 175.626 17.91 175.626 17.92 175.626 17.93 175.626 17.94 174.614 17.95 174.614 17.96 174.614 17.97 175.626 17.98 176.643 17.99 176.643 18 175.626 18.01 175.626 18.02 175.626 18.03 176.643 18.04 177.666 18.05 175.626 18.06 175.626 18.07 174.614 18.08 173.608 18.09 174.614 18.1 175.626 18.11 174.614 18.12 174.614 18.13 174.614 18.14 175.626 18.15 178.696 18.16 177.666 18.17 176.643 18.18 175.626 18.19 174.614 18.2 175.626 18.21 175.626 18.22 175.626 18.23 175.626 18.24 175.626 18.25 176.643 18.26 174.614 18.27 175.626 18.28 174.614 18.29 174.614 18.3 174.614 18.31 173.608 18.32 173.608 18.33 173.608 18.34 174.614 18.35 173.608 18.36 174.614 18.37 174.614 18.38 173.608 18.39 173.608 18.4 174.614 18.41 173.608 18.42 173.608 18.43 174.614 18.44 173.608 18.45 173.608 18.46 174.614 18.47 173.608 18.48 173.608 18.49 174.614 18.5 174.614 18.51 175.626 18.52 176.643 18.53 175.626 18.54 174.614 18.55 175.626 18.56 174.614 18.57 173.608 18.58 174.614 18.59 172.609 18.6 173.608 18.61 175.626 18.62 173.608 18.63 174.614 18.64 174.614 18.65 174.614 18.66 174.614 18.67 174.614 18.68 174.614 18.69 175.626 18.7 174.614 18.71 173.608 18.72 176.643 18.73 175.626 18.74 172.609 18.75 174.614 18.76 174.614 18.77 172.609 18.78 175.626 18.79 174.614 18.8 174.614 18.81 177.666 18.82 174.614 18.83 173.608 18.84 176.643 18.85 175.626 18.86 174.614 18.87 174.614 18.88 176.643 18.89 176.643 18.9 176.643 18.91 176.643 18.92 176.643 18.93 176.643 18.94 177.666 18.95 176.643 18.96 176.643 18.97 175.626 18.98 175.626 18.99 174.614 19 174.614 19.01 174.614 19.02 174.614 19.03 173.608 19.04 174.614 19.05 175.626 19.06 174.614 19.07 173.608 19.08 174.614 19.09 173.608 19.1 172.609 19.11 174.614 19.12 173.608 19.13 175.626 19.14 174.614 19.15 176.643 19.16 175.626 19.17 176.643 19.18 178.696 19.19 175.626 19.2 177.666 19.21 174.614 19.22 175.626 19.23 174.614 19.24 173.608 19.25 174.614 19.26 174.614 19.27 173.608 19.28 173.608 19.29 174.614 19.3 173.608 19.31 175.626 19.32 176.643 19.33 174.614 19.34 175.626 19.35 177.666 19.36 172.609 19.37 -173.608 19.38 -174.614 19.39 -176.643 19.4 -173.608 19.41 -172.609 19.42 -172.609 19.43 -172.609 19.44 -173.608 19.45 -174.614 19.46 -174.614 19.47 -174.614 19.48 -174.614 19.49 -175.626 19.5 -174.614 19.51 -173.608 19.52 -173.608 19.53 -173.608 19.54 -173.608 19.55 -174.614 19.56 -173.608 19.57 -174.614 19.58 -173.608 19.59 -174.614 19.6 -174.614 19.61 -173.608 19.62 -171.614 19.63 -172.609 19.64 -177.666 19.65 -140.202 19.66 -136.21 19.67 -137.793 19.68 -138.591 19.69 -137.793 19.7 -138.591 19.71 -138.591 19.72 -137.793 19.73 -137.793 19.74 -136.999 19.75 -138.591 19.76 -139.394 19.77 -137.793 19.78 -137.793 19.79 -138.591 19.8 -138.591 19.81 -138.591 19.82 -138.591 19.83 -138.591 19.84 -138.591 19.85 -137.793 19.86 -138.591 19.87 -139.394 19.88 -138.591 19.89 -137.793 19.9 -137.793 19.91 -137.793 19.92 -137.793 19.93 -137.793 19.94 -137.793 19.95 -137.793 19.96 -138.591 19.97 -139.394 19.98 -137.793 mir_eval-0.8.2/tests/data/melody/output00.json000066400000000000000000000003231475740344600212720ustar00rootroot00000000000000{"Voicing Recall": 0.97653429602888087, "Voicing False Alarm": 0.03248259860788863, "Raw Pitch Accuracy": 0.96425992779783398, "Raw Chroma Accuracy": 0.96425992779783398, "Overall Accuracy": 0.96393171806167399}mir_eval-0.8.2/tests/data/melody/output01.json000066400000000000000000000003241475740344600212740ustar00rootroot00000000000000{"Voicing Recall": 0.90236220472440942, "Voicing False Alarm": 0.035772357723577237, "Raw Pitch Accuracy": 0.94488188976377951, "Raw Chroma Accuracy": 0.94488188976377951, "Overall Accuracy": 0.90554089709762531}mir_eval-0.8.2/tests/data/melody/output02.json000066400000000000000000000003231475740344600212740ustar00rootroot00000000000000{"Voicing Recall": 0.81715951686797172, "Voicing False Alarm": 0.17938931297709923, "Raw Pitch Accuracy": 0.76343190337359434, "Raw Chroma Accuracy": 0.76343190337359434, "Overall Accuracy": 0.76455125797972212}mir_eval-0.8.2/tests/data/melody/output03.json000066400000000000000000000003241475740344600212760ustar00rootroot00000000000000{"Voicing Recall": 0.83470456245325353, "Voicing False Alarm": 0.083333333333333329, "Raw Pitch Accuracy": 0.89005235602094246, "Raw Chroma Accuracy": 0.89005235602094246, "Overall Accuracy": 0.83958453548759382}mir_eval-0.8.2/tests/data/melody/output04.json000066400000000000000000000003021475740344600212730ustar00rootroot00000000000000{"Voicing Recall": 0.55196674128557721, "Voicing False Alarm": 0.0, "Raw Pitch Accuracy": 0.53118004477134639, "Raw Chroma Accuracy": 0.5890629996802047, "Overall Accuracy": 0.48461074230537116}mir_eval-0.8.2/tests/data/melody/output05.json000066400000000000000000000003241475740344600213000ustar00rootroot00000000000000{"Voicing Recall": 0.58853783982365904, "Voicing False Alarm": 0.039049235993208829, "Raw Pitch Accuracy": 0.69250551065393096, "Raw Chroma Accuracy": 0.71307861866274802, "Overall Accuracy": 0.63726970703714891}mir_eval-0.8.2/tests/data/melody/output06.json000066400000000000000000000003231475740344600213000ustar00rootroot00000000000000{"Voicing Recall": 0.79990757855822547, "Voicing False Alarm": 0.14705882352941177, "Raw Pitch Accuracy": 0.75277264325323479, "Raw Chroma Accuracy": 0.75277264325323479, "Overall Accuracy": 0.72190201729106629}mir_eval-0.8.2/tests/data/melody/output07.json000066400000000000000000000003231475740344600213010ustar00rootroot00000000000000{"Voicing Recall": 0.69313725490196076, "Voicing False Alarm": 0.14507772020725387, "Raw Pitch Accuracy": 0.45392156862745098, "Raw Chroma Accuracy": 0.62287581699346406, "Overall Accuracy": 0.45037724898432968}mir_eval-0.8.2/tests/data/melody/output08.json000066400000000000000000000003231475740344600213020ustar00rootroot00000000000000{"Voicing Recall": 0.81575793888556025, "Voicing False Alarm": 0.018633540372670808, "Raw Pitch Accuracy": 0.7369682444577591, "Raw Chroma Accuracy": 0.84002396644697419, "Overall Accuracy": 0.74038209892698248}mir_eval-0.8.2/tests/data/melody/output09.json000066400000000000000000000003241475740344600213040ustar00rootroot00000000000000{"Voicing Recall": 0.86051660516605166, "Voicing False Alarm": 0.078590785907859076, "Raw Pitch Accuracy": 0.80184501845018452, "Raw Chroma Accuracy": 0.84575645756457563, "Overall Accuracy": 0.78770301624129935}mir_eval-0.8.2/tests/data/melody/ref00.txt000066400000000000000000002071111475740344600203600ustar00rootroot000000000000000.000 0.000 0.006 0.000 0.012 0.000 0.017 0.000 0.023 0.000 0.029 0.000 0.035 0.000 0.041 0.000 0.046 0.000 0.052 0.000 0.058 0.000 0.064 0.000 0.070 0.000 0.075 0.000 0.081 0.000 0.087 0.000 0.093 0.000 0.099 0.000 0.104 0.000 0.110 0.000 0.116 0.000 0.122 0.000 0.128 0.000 0.134 0.000 0.139 0.000 0.145 0.000 0.151 0.000 0.157 0.000 0.163 0.000 0.168 0.000 0.174 0.000 0.180 0.000 0.186 0.000 0.192 0.000 0.197 0.000 0.203 0.000 0.209 0.000 0.215 0.000 0.221 0.000 0.226 0.000 0.232 0.000 0.238 0.000 0.244 0.000 0.250 0.000 0.255 0.000 0.261 0.000 0.267 0.000 0.273 0.000 0.279 0.000 0.284 0.000 0.290 0.000 0.296 0.000 0.302 0.000 0.308 0.000 0.313 0.000 0.319 0.000 0.325 0.000 0.331 0.000 0.337 0.000 0.342 0.000 0.348 0.000 0.354 0.000 0.360 0.000 0.366 0.000 0.372 0.000 0.377 0.000 0.383 0.000 0.389 0.000 0.395 0.000 0.401 0.000 0.406 0.000 0.412 0.000 0.418 0.000 0.424 0.000 0.430 0.000 0.435 0.000 0.441 0.000 0.447 0.000 0.453 0.000 0.459 0.000 0.464 0.000 0.470 0.000 0.476 0.000 0.482 0.000 0.488 0.000 0.493 0.000 0.499 0.000 0.505 0.000 0.511 0.000 0.517 0.000 0.522 0.000 0.528 0.000 0.534 0.000 0.540 0.000 0.546 0.000 0.551 0.000 0.557 0.000 0.563 0.000 0.569 0.000 0.575 0.000 0.580 0.000 0.586 0.000 0.592 0.000 0.598 0.000 0.604 0.000 0.610 0.000 0.615 0.000 0.621 0.000 0.627 0.000 0.633 0.000 0.639 0.000 0.644 0.000 0.650 0.000 0.656 0.000 0.662 0.000 0.668 0.000 0.673 0.000 0.679 0.000 0.685 0.000 0.691 0.000 0.697 0.000 0.702 0.000 0.708 0.000 0.714 0.000 0.720 0.000 0.726 0.000 0.731 0.000 0.737 0.000 0.743 0.000 0.749 0.000 0.755 0.000 0.760 0.000 0.766 0.000 0.772 0.000 0.778 0.000 0.784 0.000 0.789 0.000 0.795 0.000 0.801 0.000 0.807 0.000 0.813 0.000 0.819 0.000 0.824 0.000 0.830 0.000 0.836 0.000 0.842 0.000 0.848 0.000 0.853 0.000 0.859 0.000 0.865 0.000 0.871 0.000 0.877 0.000 0.882 0.000 0.888 0.000 0.894 0.000 0.900 0.000 0.906 0.000 0.911 0.000 0.917 0.000 0.923 0.000 0.929 0.000 0.935 0.000 0.940 0.000 0.946 0.000 0.952 0.000 0.958 0.000 0.964 0.000 0.969 0.000 0.975 0.000 0.981 0.000 0.987 0.000 0.993 0.000 0.998 0.000 1.004 0.000 1.010 0.000 1.016 0.000 1.022 0.000 1.027 0.000 1.033 0.000 1.039 0.000 1.045 0.000 1.051 0.000 1.057 0.000 1.062 0.000 1.068 0.000 1.074 0.000 1.080 0.000 1.086 0.000 1.091 0.000 1.097 0.000 1.103 0.000 1.109 0.000 1.115 0.000 1.120 0.000 1.126 0.000 1.132 0.000 1.138 0.000 1.144 0.000 1.149 0.000 1.155 0.000 1.161 0.000 1.167 0.000 1.173 0.000 1.178 0.000 1.184 0.000 1.190 0.000 1.196 0.000 1.202 0.000 1.207 0.000 1.213 0.000 1.219 0.000 1.225 0.000 1.231 0.000 1.236 0.000 1.242 0.000 1.248 0.000 1.254 0.000 1.260 0.000 1.265 0.000 1.271 0.000 1.277 0.000 1.283 0.000 1.289 0.000 1.295 330.689 1.300 325.321 1.306 320.239 1.312 314.843 1.318 309.768 1.324 309.728 1.329 309.730 1.335 306.681 1.341 303.666 1.347 300.019 1.353 296.872 1.358 296.471 1.364 298.224 1.370 299.099 1.376 299.074 1.382 299.034 1.387 299.553 1.393 300.889 1.399 302.492 1.405 303.547 1.411 303.892 1.416 303.905 1.422 303.915 1.428 304.034 1.434 304.288 1.440 304.696 1.445 305.232 1.451 305.692 1.457 305.906 1.463 305.966 1.469 306.074 1.474 306.268 1.480 306.424 1.486 306.437 1.492 306.410 1.498 306.533 1.503 306.864 1.509 307.256 1.515 307.567 1.521 307.766 1.527 307.948 1.533 308.164 1.538 308.377 1.544 308.511 1.550 308.544 1.556 308.474 1.562 308.373 1.567 308.261 1.573 308.108 1.579 307.903 1.585 307.700 1.591 307.663 1.596 307.883 1.602 308.216 1.608 308.483 1.614 308.649 1.620 308.787 1.625 309.002 1.631 309.219 1.637 309.347 1.643 309.353 1.649 309.260 1.654 309.103 1.660 309.016 1.666 308.995 1.672 308.992 1.678 308.977 1.683 309.030 1.689 309.218 1.695 309.527 1.701 309.787 1.707 309.895 1.712 309.890 1.718 309.861 1.724 309.779 1.730 309.677 1.736 309.672 1.741 309.884 1.747 310.298 1.753 310.770 1.759 311.195 1.765 311.495 1.771 311.671 1.776 311.680 1.782 311.569 1.788 311.394 1.794 311.259 1.800 311.210 1.805 311.272 1.811 311.403 1.817 311.536 1.823 311.699 1.829 312.020 1.834 312.595 1.840 313.312 1.846 313.973 1.852 314.621 1.858 315.436 1.863 316.382 1.869 317.068 1.875 317.224 1.881 317.022 1.887 316.825 1.892 316.694 1.898 316.395 1.904 315.697 1.910 314.672 1.916 313.656 1.921 312.801 1.927 312.032 1.933 311.103 1.939 309.593 1.945 307.257 1.950 302.786 1.956 296.182 1.962 292.944 1.968 293.003 1.974 299.555 1.980 299.057 1.985 295.254 1.991 293.579 1.997 294.322 2.003 295.769 2.009 296.401 2.014 295.804 2.020 294.558 2.026 293.085 2.032 291.644 2.038 290.494 2.043 289.713 2.049 289.109 2.055 288.592 2.061 288.161 2.067 287.878 2.072 287.826 2.078 287.979 2.084 288.234 2.090 288.484 2.096 288.733 2.101 289.052 2.107 289.499 2.113 290.040 2.119 290.601 2.125 291.132 2.130 291.651 2.136 292.123 2.142 292.510 2.148 292.830 2.154 293.121 2.159 293.383 2.165 293.591 2.171 293.727 2.177 293.801 2.183 293.844 2.188 293.860 2.194 293.857 2.200 293.876 2.206 293.960 2.212 294.105 2.218 294.249 2.223 294.348 2.229 294.349 2.235 294.227 2.241 294.015 2.247 293.816 2.252 293.696 2.258 293.632 2.264 293.604 2.270 293.633 2.276 293.699 2.281 293.745 2.287 293.706 2.293 293.603 2.299 293.493 2.305 293.429 2.310 293.414 2.316 293.415 2.322 293.373 2.328 293.269 2.334 293.146 2.339 293.148 2.345 293.313 2.351 293.598 2.357 293.907 2.363 294.194 2.368 294.427 2.374 294.625 2.380 294.777 2.386 294.865 2.392 294.869 2.397 294.804 2.403 294.728 2.409 294.660 2.415 294.568 2.421 294.506 2.426 294.534 2.432 294.661 2.438 294.831 2.444 295.003 2.450 295.147 2.456 295.292 2.461 295.407 2.467 295.469 2.473 295.449 2.479 295.386 2.485 295.368 2.490 295.385 2.496 295.345 2.502 295.243 2.508 295.145 2.514 295.135 2.519 295.188 2.525 295.272 2.531 295.405 2.537 295.528 2.543 295.522 2.548 295.388 2.554 295.218 2.560 295.152 2.566 295.220 2.572 295.279 2.577 295.191 2.583 295.000 2.589 294.846 2.595 294.848 2.601 294.963 2.606 295.093 2.612 295.211 2.618 295.270 2.624 295.196 2.630 295.061 2.635 294.975 2.641 295.012 2.647 295.144 2.653 295.245 2.659 295.249 2.664 295.131 2.670 294.919 2.676 294.724 2.682 294.618 2.688 294.602 2.694 294.634 2.699 294.677 2.705 294.755 2.711 294.893 2.717 295.045 2.723 295.201 2.728 295.307 2.734 295.320 2.740 295.240 2.746 295.104 2.752 294.937 2.757 294.819 2.763 294.763 2.769 294.792 2.775 294.891 2.781 295.026 2.786 295.177 2.792 295.334 2.798 295.416 2.804 295.411 2.810 295.350 2.815 295.267 2.821 295.194 2.827 295.098 2.833 294.964 2.839 294.874 2.844 294.850 2.850 294.898 2.856 294.961 2.862 295.042 2.868 295.171 2.873 295.308 2.879 295.350 2.885 295.362 2.891 295.408 2.897 295.484 2.902 295.514 2.908 295.446 2.914 295.346 2.920 295.247 2.926 295.139 2.932 295.001 2.937 294.839 2.943 294.654 2.949 294.481 2.955 294.297 2.961 294.081 2.966 293.901 2.972 293.928 2.978 294.300 2.984 294.920 2.990 295.381 2.995 295.457 3.001 295.293 3.007 295.155 3.013 295.176 3.019 295.180 3.024 294.989 3.030 294.674 3.036 294.334 3.042 293.955 3.048 293.585 3.053 293.315 3.059 293.257 3.065 293.394 3.071 293.555 3.077 293.607 3.082 293.509 3.088 293.371 3.094 293.359 3.100 293.552 3.106 293.905 3.111 294.313 3.117 294.671 3.123 295.035 3.129 295.443 3.135 295.895 3.140 296.350 3.146 296.726 3.152 296.985 3.158 297.078 3.164 296.998 3.170 296.816 3.175 296.671 3.181 296.611 3.187 296.644 3.193 296.717 3.199 296.800 3.204 296.836 3.210 296.760 3.216 296.427 3.222 295.831 3.228 295.072 3.233 294.306 3.239 293.636 3.245 293.081 3.251 292.627 3.257 292.312 3.262 292.063 3.268 291.834 3.274 291.563 3.280 291.328 3.286 291.298 3.291 291.493 3.297 291.804 3.303 292.213 3.309 292.766 3.315 293.478 3.320 294.313 3.326 295.164 3.332 296.028 3.338 296.807 3.344 297.371 3.349 297.673 3.355 297.817 3.361 297.910 3.367 298.070 3.373 298.304 3.379 298.547 3.384 298.742 3.390 298.869 3.396 298.849 3.402 298.609 3.408 298.188 3.413 297.675 3.419 297.118 3.425 296.411 3.431 295.556 3.437 294.613 3.442 293.668 3.448 292.672 3.454 291.626 3.460 290.569 3.466 289.601 3.471 288.811 3.477 288.277 3.483 287.997 3.489 287.922 3.495 287.952 3.500 288.060 3.506 288.375 3.512 288.959 3.518 289.697 3.524 290.412 3.529 291.104 3.535 291.898 3.541 292.894 3.547 293.990 3.553 295.003 3.558 295.879 3.564 296.627 3.570 297.233 3.576 297.763 3.582 298.225 3.587 298.685 3.593 299.104 3.599 299.266 3.605 298.993 3.611 298.226 3.617 297.105 3.622 295.950 3.628 295.045 3.634 294.415 3.640 293.927 3.646 293.362 3.651 292.701 3.657 292.037 3.663 291.480 3.669 291.024 3.675 290.621 3.680 290.255 3.686 290.010 3.692 290.014 3.698 290.298 3.704 290.676 3.709 290.978 3.715 291.226 3.721 291.539 3.727 292.042 3.733 292.734 3.738 293.501 3.744 294.196 3.750 294.769 3.756 295.200 3.762 295.605 3.767 296.027 3.773 296.433 3.779 296.704 3.785 296.771 3.791 296.585 3.796 296.243 3.802 295.823 3.808 295.373 3.814 294.910 3.820 294.396 3.825 293.885 3.831 293.348 3.837 292.726 3.843 291.946 3.849 291.069 3.855 290.246 3.860 289.592 3.866 289.157 3.872 288.987 3.878 288.941 3.884 288.826 3.889 288.569 3.895 288.280 3.901 288.092 3.907 288.004 3.913 288.020 3.918 288.203 3.924 288.598 3.930 289.135 3.936 289.703 3.942 290.245 3.947 290.698 3.953 291.105 3.959 291.622 3.965 292.267 3.971 292.900 3.976 293.364 3.982 293.591 3.988 293.671 3.994 293.775 4.000 293.931 4.005 294.037 4.011 294.048 4.017 293.921 4.023 293.656 4.029 293.299 4.034 292.995 4.040 292.841 4.046 292.831 4.052 292.731 4.058 292.554 4.063 292.349 4.069 292.156 4.075 291.893 4.081 291.471 4.087 290.848 4.093 290.169 4.098 289.590 4.104 289.168 4.110 288.822 4.116 288.451 4.122 288.055 4.127 287.716 4.133 287.512 4.139 287.461 4.145 287.533 4.151 287.657 4.156 287.770 4.162 287.874 4.168 288.112 4.174 288.552 4.180 289.163 4.185 289.844 4.191 290.558 4.197 291.252 4.203 291.962 4.209 292.642 4.214 293.235 4.220 293.708 4.226 294.168 4.232 294.737 4.238 295.468 4.243 296.280 4.249 297.012 4.255 297.605 4.261 297.992 4.267 298.079 4.272 297.842 4.278 297.398 4.284 296.855 4.290 296.256 4.296 295.468 4.301 294.548 4.307 293.573 4.313 292.723 4.319 292.026 4.325 291.386 4.331 290.608 4.336 289.657 4.342 288.761 4.348 288.264 4.354 288.263 4.360 288.532 4.365 288.869 4.371 289.270 4.377 289.854 4.383 290.598 4.389 291.443 4.394 292.339 4.400 293.322 4.406 294.345 4.412 295.492 4.418 296.844 4.423 298.290 4.429 299.526 4.435 300.275 4.441 300.314 4.447 299.615 4.452 298.568 4.458 298.155 4.464 298.709 4.470 300.623 4.476 303.558 4.481 302.745 4.487 292.602 4.493 285.275 4.499 276.567 4.505 276.656 4.510 0.000 4.516 0.000 4.522 0.000 4.528 0.000 4.534 0.000 4.540 0.000 4.545 0.000 4.551 0.000 4.557 0.000 4.563 0.000 4.569 0.000 4.574 0.000 4.580 0.000 4.586 0.000 4.592 0.000 4.598 0.000 4.603 0.000 4.609 0.000 4.615 0.000 4.621 0.000 4.627 0.000 4.632 0.000 4.638 0.000 4.644 0.000 4.650 0.000 4.656 0.000 4.661 0.000 4.667 0.000 4.673 0.000 4.679 0.000 4.685 0.000 4.690 0.000 4.696 0.000 4.702 0.000 4.708 0.000 4.714 0.000 4.719 0.000 4.725 0.000 4.731 0.000 4.737 0.000 4.743 0.000 4.748 0.000 4.754 0.000 4.760 0.000 4.766 0.000 4.772 0.000 4.778 0.000 4.783 0.000 4.789 0.000 4.795 0.000 4.801 0.000 4.807 0.000 4.812 0.000 4.818 0.000 4.824 0.000 4.830 0.000 4.836 0.000 4.841 0.000 4.847 0.000 4.853 0.000 4.859 0.000 4.865 0.000 4.870 0.000 4.876 0.000 4.882 0.000 4.888 0.000 4.894 0.000 4.899 0.000 4.905 0.000 4.911 0.000 4.917 0.000 4.923 0.000 4.928 0.000 4.934 0.000 4.940 0.000 4.946 0.000 4.952 0.000 4.957 0.000 4.963 0.000 4.969 0.000 4.975 0.000 4.981 0.000 4.986 0.000 4.992 0.000 4.998 0.000 5.004 0.000 5.010 0.000 5.016 0.000 5.021 0.000 5.027 0.000 5.033 0.000 5.039 0.000 5.045 0.000 5.050 0.000 5.056 0.000 5.062 0.000 5.068 0.000 5.074 0.000 5.079 0.000 5.085 0.000 5.091 0.000 5.097 0.000 5.103 0.000 5.108 0.000 5.114 0.000 5.120 0.000 5.126 0.000 5.132 0.000 5.137 0.000 5.143 0.000 5.149 0.000 5.155 0.000 5.161 0.000 5.166 0.000 5.172 0.000 5.178 0.000 5.184 0.000 5.190 0.000 5.195 0.000 5.201 0.000 5.207 0.000 5.213 0.000 5.219 0.000 5.224 0.000 5.230 0.000 5.236 0.000 5.242 0.000 5.248 0.000 5.254 0.000 5.259 0.000 5.265 0.000 5.271 0.000 5.277 0.000 5.283 0.000 5.288 0.000 5.294 0.000 5.300 0.000 5.306 0.000 5.312 0.000 5.317 0.000 5.323 0.000 5.329 0.000 5.335 0.000 5.341 0.000 5.346 0.000 5.352 0.000 5.358 0.000 5.364 0.000 5.370 0.000 5.375 0.000 5.381 226.235 5.387 230.391 5.393 242.717 5.399 247.206 5.404 255.943 5.410 259.470 5.416 259.748 5.422 259.456 5.428 259.552 5.433 259.485 5.439 259.486 5.445 259.623 5.451 259.929 5.457 260.370 5.462 260.727 5.468 260.781 5.474 260.629 5.480 260.590 5.486 260.807 5.492 261.037 5.497 261.065 5.503 261.020 5.509 261.087 5.515 261.261 5.521 261.458 5.526 261.598 5.532 261.683 5.538 261.677 5.544 261.597 5.550 261.529 5.555 261.481 5.561 261.451 5.567 261.489 5.573 261.575 5.579 261.657 5.584 261.679 5.590 261.602 5.596 261.478 5.602 261.323 5.608 261.209 5.613 261.210 5.619 261.298 5.625 261.408 5.631 261.462 5.637 261.375 5.642 261.243 5.648 261.221 5.654 261.300 5.660 261.324 5.666 261.239 5.671 261.170 5.677 261.248 5.683 261.461 5.689 261.642 5.695 261.714 5.700 261.744 5.706 261.780 5.712 261.849 5.718 262.018 5.724 262.203 5.730 262.338 5.735 262.328 5.741 262.211 5.747 262.036 5.753 261.834 5.759 261.600 5.764 261.483 5.770 261.513 5.776 261.605 5.782 261.549 5.788 261.290 5.793 260.955 5.799 260.638 5.805 260.373 5.811 260.206 5.817 260.112 5.822 260.103 5.828 260.370 5.834 261.922 5.840 265.530 5.846 269.432 5.851 271.539 5.857 269.504 5.863 266.779 5.869 262.801 5.875 262.864 5.880 262.492 5.886 264.021 5.892 264.935 5.898 262.583 5.904 259.940 5.909 257.017 5.915 265.696 5.921 269.977 5.927 276.006 5.933 274.651 5.939 279.916 5.944 279.550 5.950 277.484 5.956 275.867 5.962 275.049 5.968 274.724 5.973 274.613 5.979 275.270 5.985 276.229 5.991 277.915 5.997 280.034 6.002 282.006 6.008 283.995 6.014 285.872 6.020 287.856 6.026 290.127 6.031 292.795 6.037 295.672 6.043 298.133 6.049 299.696 6.055 300.477 6.060 300.590 6.066 300.342 6.072 300.199 6.078 300.403 6.084 300.825 6.089 300.986 6.095 300.577 6.101 299.589 6.107 298.161 6.113 296.572 6.118 295.221 6.124 294.413 6.130 294.092 6.136 293.963 6.142 293.802 6.147 293.583 6.153 293.413 6.159 293.362 6.165 293.467 6.171 293.709 6.177 294.043 6.182 294.364 6.188 294.637 6.194 294.814 6.200 294.948 6.206 295.059 6.211 295.150 6.217 295.173 6.223 295.105 6.229 294.929 6.235 294.706 6.240 294.491 6.246 294.313 6.252 294.152 6.258 294.018 6.264 293.997 6.269 294.070 6.275 294.156 6.281 294.151 6.287 294.004 6.293 293.762 6.298 293.489 6.304 293.202 6.310 292.979 6.316 292.880 6.322 292.897 6.327 292.977 6.333 293.029 6.339 292.982 6.345 292.862 6.351 292.829 6.356 292.943 6.362 293.166 6.368 293.428 6.374 293.708 6.380 294.015 6.385 294.261 6.391 294.306 6.397 294.173 6.403 293.971 6.409 293.813 6.415 293.742 6.420 293.747 6.426 293.821 6.432 293.971 6.438 294.147 6.444 294.324 6.449 294.447 6.455 294.528 6.461 294.598 6.467 294.703 6.473 294.798 6.478 294.777 6.484 294.513 6.490 294.037 6.496 293.491 6.502 293.064 6.507 292.875 6.513 292.900 6.519 292.828 6.525 292.341 6.531 291.446 6.536 290.723 6.542 290.462 6.548 290.536 6.554 290.547 6.560 290.323 6.565 290.020 6.571 289.765 6.577 289.640 6.583 289.732 6.589 290.228 6.594 291.254 6.600 292.639 6.606 293.694 6.612 294.428 6.618 296.353 6.623 300.525 6.629 307.814 6.635 313.013 6.641 316.359 6.647 319.773 6.653 323.410 6.658 328.458 6.664 333.538 6.670 339.313 6.676 345.727 6.682 350.440 6.687 352.730 6.693 353.316 6.699 353.485 6.705 353.738 6.711 354.224 6.716 354.761 6.722 355.059 6.728 355.095 6.734 355.105 6.740 355.185 6.745 355.146 6.751 354.562 6.757 353.314 6.763 351.719 6.769 350.517 6.774 350.020 6.780 350.153 6.786 350.409 6.792 350.274 6.798 349.665 6.803 348.831 6.809 348.166 6.815 347.741 6.821 347.438 6.827 347.124 6.832 346.785 6.838 346.578 6.844 346.647 6.850 346.907 6.856 347.248 6.861 347.684 6.867 348.224 6.873 348.877 6.879 349.566 6.885 350.162 6.891 350.652 6.896 350.972 6.902 351.029 6.908 350.851 6.914 350.603 6.920 350.398 6.925 350.210 6.931 349.945 6.937 349.612 6.943 349.334 6.949 349.241 6.954 349.214 6.960 349.152 6.966 349.023 6.972 348.897 6.978 348.802 6.983 348.720 6.989 348.511 6.995 348.196 7.001 347.883 7.007 347.750 7.012 347.747 7.018 347.749 7.024 347.624 7.030 347.365 7.036 347.143 7.041 347.034 7.047 347.055 7.053 347.203 7.059 347.389 7.065 347.515 7.070 347.512 7.076 347.505 7.082 347.689 7.088 348.127 7.094 348.620 7.100 349.000 7.105 349.221 7.111 349.304 7.117 349.180 7.123 348.851 7.129 348.444 7.134 347.909 7.140 346.842 7.146 345.283 7.152 344.096 7.158 344.100 7.163 344.889 7.169 345.341 7.175 345.084 7.181 344.432 7.187 343.474 7.192 342.274 7.198 341.001 7.204 339.963 7.210 339.455 7.216 339.100 7.221 338.419 7.227 337.820 7.233 338.371 7.239 340.536 7.245 343.378 7.250 345.409 7.256 346.730 7.262 348.245 7.268 350.354 7.274 352.645 7.279 354.575 7.285 356.314 7.291 358.391 7.297 361.586 7.303 366.013 7.308 371.061 7.314 374.725 7.320 376.868 7.326 378.820 7.332 381.326 7.338 384.143 7.343 386.268 7.349 388.029 7.355 389.615 7.361 390.748 7.367 391.426 7.372 392.073 7.378 392.915 7.384 393.643 7.390 393.829 7.396 393.520 7.401 393.080 7.407 392.717 7.413 392.375 7.419 391.968 7.425 391.560 7.430 391.322 7.436 391.301 7.442 391.367 7.448 391.271 7.454 390.907 7.459 390.428 7.465 389.972 7.471 389.577 7.477 389.206 7.483 388.865 7.488 388.569 7.494 388.317 7.500 388.078 7.506 387.872 7.512 387.702 7.517 387.604 7.523 387.668 7.529 387.991 7.535 388.555 7.541 389.167 7.546 389.625 7.552 389.888 7.558 390.063 7.564 390.225 7.570 390.409 7.576 390.606 7.581 390.788 7.587 390.934 7.593 391.009 7.599 391.055 7.605 391.094 7.610 391.105 7.616 391.061 7.622 390.975 7.628 390.918 7.634 390.933 7.639 391.004 7.645 391.059 7.651 391.047 7.657 390.985 7.663 390.927 7.668 390.916 7.674 390.991 7.680 391.169 7.686 391.388 7.692 391.539 7.697 391.526 7.703 391.358 7.709 391.106 7.715 390.861 7.721 390.675 7.726 390.544 7.732 390.436 7.738 390.350 7.744 390.296 7.750 390.260 7.755 390.206 7.761 390.116 7.767 390.007 7.773 389.921 7.779 389.882 7.784 389.922 7.790 390.070 7.796 390.330 7.802 390.685 7.808 391.135 7.814 391.627 7.819 392.055 7.825 392.341 7.831 392.487 7.837 392.532 7.843 392.514 7.848 392.424 7.854 392.244 7.860 391.953 7.866 391.550 7.872 391.055 7.877 390.505 7.883 389.940 7.889 389.413 7.895 388.979 7.901 388.701 7.906 388.593 7.912 388.638 7.918 388.750 7.924 388.838 7.930 388.921 7.935 389.036 7.941 389.164 7.947 389.237 7.953 389.240 7.959 389.268 7.964 389.449 7.970 389.780 7.976 390.177 7.982 390.531 7.988 390.735 7.993 390.776 7.999 390.691 8.005 390.500 8.011 390.188 8.017 389.742 8.022 389.278 8.028 388.979 8.034 388.928 8.040 389.069 8.046 389.277 8.052 389.455 8.057 389.642 8.063 389.856 8.069 390.049 8.075 390.168 8.081 390.260 8.086 390.468 8.092 390.842 8.098 391.253 8.104 391.569 8.110 391.758 8.115 391.848 8.121 391.876 8.127 391.829 8.133 391.692 8.139 391.449 8.144 391.093 8.150 390.608 8.156 389.994 8.162 389.474 8.168 389.264 8.173 389.395 8.179 389.663 8.185 389.850 8.191 389.950 8.197 390.185 8.202 390.585 8.208 391.058 8.214 391.481 8.220 391.784 8.226 391.984 8.231 392.074 8.237 392.043 8.243 391.889 8.249 391.623 8.255 391.274 8.260 390.877 8.266 390.430 8.272 389.948 8.278 389.467 8.284 389.022 8.290 388.684 8.295 388.501 8.301 388.493 8.307 388.638 8.313 388.845 8.319 389.026 8.324 389.213 8.330 389.440 8.336 389.650 8.342 389.762 8.348 389.781 8.353 389.834 8.359 390.072 8.365 390.504 8.371 391.008 8.377 391.498 8.382 391.959 8.388 392.436 8.394 392.941 8.400 393.453 8.406 393.912 8.411 394.323 8.417 394.669 8.423 394.961 8.429 395.183 8.435 395.373 8.440 395.525 8.446 395.671 8.452 395.847 8.458 396.084 8.464 396.290 8.469 396.380 8.475 396.430 8.481 396.731 8.487 397.436 8.493 398.165 8.499 398.335 8.504 397.685 8.510 396.415 8.516 394.911 8.522 393.544 8.528 392.707 8.533 392.457 8.539 392.254 8.545 391.013 8.551 388.278 8.557 385.200 8.562 382.981 8.568 381.349 8.574 379.959 8.580 378.229 8.586 376.067 8.591 372.236 8.597 369.793 8.603 0.000 8.609 0.000 8.615 0.000 8.620 0.000 8.626 0.000 8.632 0.000 8.638 352.272 8.644 338.922 8.649 348.568 8.655 349.107 8.661 348.050 8.667 346.566 8.673 345.128 8.678 343.757 8.684 342.500 8.690 341.718 8.696 341.606 8.702 341.499 8.707 341.624 8.713 341.944 8.719 342.401 8.725 342.861 8.731 343.289 8.737 343.733 8.742 344.180 8.748 344.633 8.754 345.240 8.760 346.011 8.766 346.782 8.771 347.454 8.777 348.039 8.783 348.558 8.789 348.959 8.795 349.177 8.800 349.198 8.806 349.041 8.812 348.828 8.818 348.650 8.824 348.473 8.829 348.267 8.835 348.027 8.841 347.876 8.847 347.919 8.853 348.062 8.858 348.176 8.864 348.262 8.870 348.373 8.876 348.575 8.882 348.830 8.887 348.980 8.893 348.944 8.899 348.719 8.905 348.354 8.911 348.041 8.916 347.891 8.922 347.855 8.928 347.831 8.934 347.856 8.940 348.007 8.945 348.297 8.951 348.549 8.957 348.611 8.963 348.525 8.969 348.431 8.975 348.338 8.980 348.246 8.986 348.231 8.992 348.391 8.998 348.701 9.004 349.049 9.009 349.344 9.015 349.569 9.021 349.724 9.027 349.734 9.033 349.585 9.038 349.326 9.044 349.035 9.050 348.754 9.056 348.434 9.062 348.064 9.067 347.680 9.073 347.310 9.079 347.071 9.085 347.080 9.091 347.233 9.096 347.369 9.102 347.395 9.108 347.380 9.114 347.459 9.120 347.634 9.125 347.786 9.131 347.853 9.137 347.888 9.143 347.962 9.149 348.117 9.154 348.336 9.160 348.553 9.166 348.745 9.172 348.949 9.178 349.168 9.183 349.396 9.189 349.623 9.195 349.841 9.201 349.998 9.207 350.021 9.213 349.895 9.218 349.726 9.224 349.663 9.230 349.726 9.236 349.812 9.242 349.753 9.247 349.544 9.253 349.317 9.259 349.206 9.265 349.169 9.271 349.097 9.276 348.878 9.282 348.554 9.288 348.225 9.294 347.971 9.300 347.803 9.305 347.706 9.311 347.726 9.317 347.855 9.323 348.048 9.329 348.291 9.334 348.573 9.340 348.883 9.346 349.133 9.352 349.222 9.358 349.202 9.363 349.286 9.369 349.510 9.375 349.764 9.381 349.893 9.387 349.950 9.392 349.935 9.398 349.843 9.404 349.576 9.410 349.166 9.416 348.726 9.421 348.379 9.427 348.136 9.433 347.961 9.439 347.810 9.445 347.729 9.451 347.708 9.456 347.679 9.462 347.627 9.468 347.640 9.474 347.753 9.480 347.847 9.485 347.810 9.491 347.745 9.497 347.773 9.503 347.855 9.509 347.864 9.514 347.829 9.520 347.862 9.526 348.028 9.532 348.272 9.538 348.499 9.543 348.699 9.549 348.944 9.555 349.209 9.561 349.380 9.567 349.379 9.572 349.300 9.578 349.311 9.584 349.493 9.590 349.773 9.596 350.005 9.601 350.119 9.607 350.148 9.613 350.119 9.619 350.003 9.625 349.804 9.630 349.577 9.636 349.349 9.642 349.059 9.648 348.672 9.654 348.198 9.660 347.753 9.665 347.397 9.671 347.156 9.677 347.032 9.683 347.033 9.689 347.066 9.694 347.045 9.700 346.916 9.706 346.729 9.712 346.641 9.718 346.678 9.723 346.764 9.729 346.827 9.735 346.957 9.741 347.179 9.747 347.446 9.752 347.690 9.758 347.939 9.764 348.228 9.770 348.602 9.776 349.122 9.781 349.821 9.787 350.513 9.793 350.938 9.799 351.094 9.805 351.216 9.810 351.391 9.816 351.466 9.822 351.346 9.828 351.113 9.834 350.920 9.839 350.782 9.845 350.604 9.851 350.341 9.857 350.038 9.863 349.666 9.868 349.222 9.874 348.684 9.880 348.140 9.886 347.730 9.892 347.479 9.898 347.296 9.903 347.039 9.909 346.711 9.915 346.446 9.921 346.370 9.927 346.436 9.932 346.515 9.938 346.509 9.944 346.465 9.950 346.460 9.956 346.574 9.961 346.820 9.967 347.180 9.973 347.693 9.979 348.340 9.985 349.062 9.990 349.852 9.996 350.638 10.002 351.378 10.008 351.934 10.014 352.131 10.019 352.002 10.025 351.784 10.031 351.562 10.037 351.256 10.043 350.771 10.048 350.212 10.054 349.636 10.060 349.065 10.066 348.380 10.072 347.567 10.077 346.736 10.083 346.004 10.089 345.447 10.095 345.066 10.101 344.784 10.106 344.608 10.112 344.533 10.118 344.529 10.124 344.573 10.130 344.720 10.136 345.025 10.141 345.437 10.147 345.907 10.153 346.513 10.159 347.296 10.165 348.140 10.170 348.942 10.176 349.716 10.182 350.506 10.188 351.323 10.194 352.105 10.199 352.702 10.205 353.104 10.211 353.378 10.217 353.501 10.223 353.370 10.228 352.967 10.234 352.355 10.240 351.723 10.246 351.108 10.252 350.507 10.257 349.823 10.263 349.044 10.269 348.225 10.275 347.506 10.281 346.985 10.286 346.583 10.292 346.145 10.298 345.799 10.304 345.869 10.310 346.398 10.315 347.244 10.321 348.047 10.327 348.718 10.333 348.971 10.339 348.150 10.344 345.340 10.350 338.934 10.356 331.683 10.362 327.483 10.368 334.848 10.374 345.473 10.379 0.000 10.385 0.000 10.391 0.000 10.397 0.000 10.403 0.000 10.408 0.000 10.414 0.000 10.420 0.000 10.426 0.000 10.432 0.000 10.437 0.000 10.443 0.000 10.449 0.000 10.455 0.000 10.461 0.000 10.466 0.000 10.472 0.000 10.478 0.000 10.484 0.000 10.490 0.000 10.495 0.000 10.501 0.000 10.507 0.000 10.513 0.000 10.519 0.000 10.524 0.000 10.530 0.000 10.536 0.000 10.542 0.000 10.548 0.000 10.553 0.000 10.559 0.000 10.565 0.000 10.571 0.000 10.577 0.000 10.582 0.000 10.588 0.000 10.594 0.000 10.600 0.000 10.606 0.000 10.612 0.000 10.617 0.000 10.623 0.000 10.629 0.000 10.635 0.000 10.641 0.000 10.646 0.000 10.652 0.000 10.658 0.000 10.664 0.000 10.670 0.000 10.675 0.000 10.681 0.000 10.687 0.000 10.693 0.000 10.699 0.000 10.704 0.000 10.710 0.000 10.716 0.000 10.722 0.000 10.728 0.000 10.733 0.000 10.739 0.000 10.745 0.000 10.751 0.000 10.757 0.000 10.762 0.000 10.768 0.000 10.774 0.000 10.780 0.000 10.786 0.000 10.791 0.000 10.797 0.000 10.803 0.000 10.809 0.000 10.815 0.000 10.820 0.000 10.826 0.000 10.832 0.000 10.838 0.000 10.844 0.000 10.850 0.000 10.855 0.000 10.861 0.000 10.867 0.000 10.873 0.000 10.879 0.000 10.884 0.000 10.890 0.000 10.896 0.000 10.902 0.000 10.908 0.000 10.913 0.000 10.919 0.000 10.925 0.000 10.931 0.000 10.937 0.000 10.942 0.000 10.948 0.000 10.954 0.000 10.960 0.000 10.966 0.000 10.971 0.000 10.977 0.000 10.983 0.000 10.989 0.000 10.995 0.000 11.000 0.000 11.006 0.000 11.012 0.000 11.018 0.000 11.024 0.000 11.029 0.000 11.035 0.000 11.041 0.000 11.047 0.000 11.053 0.000 11.059 0.000 11.064 0.000 11.070 0.000 11.076 0.000 11.082 0.000 11.088 0.000 11.093 0.000 11.099 0.000 11.105 0.000 11.111 0.000 11.117 0.000 11.122 0.000 11.128 0.000 11.134 0.000 11.140 0.000 11.146 0.000 11.151 0.000 11.157 0.000 11.163 0.000 11.169 0.000 11.175 0.000 11.180 0.000 11.186 0.000 11.192 351.286 11.198 350.829 11.204 350.317 11.209 349.814 11.215 349.700 11.221 350.256 11.227 350.754 11.233 350.519 11.238 350.141 11.244 350.036 11.250 349.548 11.256 349.112 11.262 348.757 11.267 348.508 11.273 348.213 11.279 347.810 11.285 347.383 11.291 347.130 11.297 347.056 11.302 347.059 11.308 347.204 11.314 347.504 11.320 347.792 11.326 347.904 11.331 347.931 11.337 348.130 11.343 348.592 11.349 348.980 11.355 349.006 11.360 348.779 11.366 348.493 11.372 348.198 11.378 347.829 11.384 347.409 11.389 347.041 11.395 346.745 11.401 346.439 11.407 346.115 11.413 345.918 11.418 345.987 11.424 346.240 11.430 346.564 11.436 346.993 11.442 347.556 11.447 348.215 11.453 348.887 11.459 349.468 11.465 349.949 11.471 350.274 11.476 350.330 11.482 350.148 11.488 349.898 11.494 349.694 11.500 349.506 11.505 349.245 11.511 348.918 11.517 348.660 11.523 348.549 11.529 348.510 11.535 348.432 11.540 348.314 11.546 348.219 11.552 348.187 11.558 348.160 11.564 347.982 11.569 347.682 11.575 347.380 11.581 347.249 11.587 347.243 11.593 347.247 11.598 347.133 11.604 346.899 11.610 346.697 11.616 346.594 11.622 346.602 11.627 346.726 11.633 346.900 11.639 347.044 11.645 347.055 11.651 346.922 11.656 346.706 11.662 346.462 11.668 346.277 11.674 346.358 11.680 346.813 11.685 347.564 11.691 348.350 11.697 349.023 11.703 349.646 11.709 350.282 11.714 350.932 11.720 351.653 11.726 352.462 11.732 353.322 11.738 354.196 11.743 355.081 11.749 355.922 11.755 356.395 11.761 355.779 11.767 354.211 11.773 349.941 11.778 345.082 11.784 343.294 11.790 0.000 11.796 0.000 11.802 0.000 11.807 0.000 11.813 0.000 11.819 0.000 11.825 0.000 11.831 0.000 11.836 0.000 11.842 0.000 11.848 0.000 11.854 0.000 11.860 0.000 11.865 0.000 11.871 0.000 11.877 0.000 11.883 0.000 11.889 0.000 11.894 0.000 11.900 313.579 11.906 299.501 11.912 292.041 11.918 289.018 11.923 287.884 11.929 287.460 11.935 287.212 11.941 286.864 11.947 286.557 11.952 286.923 11.958 287.384 11.964 287.777 11.970 288.145 11.976 288.609 11.981 289.195 11.987 289.637 11.993 289.889 11.999 290.223 12.005 290.842 12.011 291.720 12.016 292.448 12.022 292.683 12.028 292.515 12.034 292.205 12.040 291.900 12.045 291.625 12.051 291.359 12.057 291.093 12.063 290.924 12.069 290.951 12.074 291.154 12.080 291.427 12.086 291.772 12.092 292.185 12.098 292.699 12.103 293.269 12.109 293.764 12.115 294.151 12.121 294.419 12.127 294.503 12.132 294.413 12.138 294.256 12.144 294.088 12.150 293.906 12.156 293.667 12.161 293.388 12.167 293.178 12.173 293.119 12.179 293.098 12.185 293.016 12.190 292.865 12.196 292.771 12.202 292.765 12.208 292.763 12.214 292.611 12.220 292.339 12.225 292.091 12.231 291.980 12.237 291.954 12.243 291.921 12.249 291.819 12.254 291.655 12.260 291.502 12.266 291.388 12.272 291.352 12.278 291.403 12.283 291.534 12.289 291.665 12.295 291.693 12.301 291.591 12.307 291.461 12.312 291.415 12.318 291.484 12.324 291.822 12.330 292.312 12.336 292.902 12.341 293.324 12.347 293.423 12.353 293.333 12.359 293.346 12.365 293.512 12.370 293.448 12.376 292.595 12.382 291.253 12.388 290.622 12.394 291.433 12.399 292.991 12.405 293.835 12.411 293.786 12.417 293.450 12.423 292.954 12.428 292.360 12.434 291.918 12.440 291.835 12.446 292.052 12.452 292.146 12.458 291.901 12.463 291.676 12.469 291.942 12.475 292.761 12.481 293.667 12.487 294.208 12.492 294.466 12.498 294.689 12.504 294.881 12.510 294.630 12.516 293.957 12.521 293.233 12.527 292.802 12.533 292.724 12.539 292.792 12.545 292.824 12.550 292.933 12.556 293.143 12.562 293.166 12.568 292.925 12.574 292.672 12.579 292.589 12.585 292.617 12.591 292.651 12.597 292.730 12.603 292.876 12.608 292.978 12.614 292.989 12.620 293.066 12.626 293.269 12.632 293.418 12.637 293.284 12.643 292.928 12.649 292.560 12.655 292.413 12.661 292.536 12.666 292.836 12.672 293.078 12.678 293.141 12.684 293.012 12.690 292.798 12.696 292.639 12.701 292.662 12.707 292.857 12.713 293.123 12.719 293.328 12.725 293.490 12.730 293.660 12.736 293.820 12.742 293.864 12.748 293.761 12.754 293.534 12.759 293.313 12.765 293.175 12.771 293.058 12.777 292.900 12.783 292.713 12.788 292.585 12.794 292.610 12.800 292.703 12.806 292.766 12.812 292.808 12.817 292.904 12.823 293.086 12.829 293.321 12.835 293.465 12.841 293.449 12.846 293.241 12.852 292.942 12.858 292.699 12.864 292.607 12.870 292.602 12.875 292.582 12.881 292.574 12.887 292.677 12.893 292.888 12.899 293.087 12.904 293.166 12.910 293.140 12.916 293.068 12.922 292.940 12.928 292.818 12.934 292.814 12.939 292.974 12.945 293.250 12.951 293.536 12.957 293.778 12.963 293.958 12.968 294.070 12.974 294.081 12.980 293.950 12.986 293.734 12.992 293.525 12.997 293.304 13.003 293.133 13.009 292.936 13.015 292.652 13.021 292.402 13.026 292.460 13.032 292.979 13.038 293.759 13.044 294.496 13.050 295.111 13.055 295.740 13.061 296.454 13.067 297.142 13.073 297.698 13.079 298.140 13.084 298.536 13.090 298.796 13.096 298.680 13.102 297.969 13.108 296.799 13.113 295.417 13.119 293.942 13.125 292.057 13.131 290.035 13.137 288.090 13.142 286.253 13.148 284.250 13.154 281.772 13.160 277.891 13.166 272.768 13.172 268.513 13.177 265.966 13.183 265.716 13.189 266.396 13.195 268.194 13.201 269.607 13.206 268.457 13.212 265.015 13.218 260.615 13.224 257.629 13.230 256.413 13.235 256.184 13.241 256.740 13.247 257.601 13.253 258.198 13.259 258.485 13.264 258.783 13.270 259.355 13.276 260.130 13.282 260.798 13.288 261.216 13.293 261.435 13.299 261.592 13.305 261.716 13.311 261.751 13.317 261.700 13.322 261.605 13.328 261.536 13.334 261.520 13.340 261.474 13.346 261.358 13.351 261.173 13.357 261.031 13.363 261.027 13.369 261.126 13.375 261.217 13.380 261.297 13.386 261.382 13.392 261.533 13.398 261.710 13.404 261.831 13.410 261.829 13.415 261.695 13.421 261.372 13.427 260.852 13.433 260.293 13.439 259.953 13.444 259.916 13.450 260.144 13.456 260.470 13.462 260.737 13.468 260.824 13.473 260.635 13.479 260.174 13.485 259.704 13.491 259.419 13.497 259.405 13.502 259.597 13.508 259.682 13.514 259.399 13.520 258.835 13.526 258.397 13.531 258.505 13.537 259.153 13.543 259.833 13.549 259.989 13.555 260.046 13.560 260.294 13.566 260.658 13.572 260.913 13.578 260.883 13.584 260.763 13.589 261.018 13.595 261.676 13.601 262.491 13.607 262.942 13.613 262.789 13.619 262.233 13.624 261.684 13.630 261.321 13.636 261.021 13.642 260.586 13.648 260.186 13.653 259.950 13.659 259.801 13.665 259.669 13.671 259.523 13.677 259.395 13.682 259.376 13.688 259.512 13.694 259.805 13.700 260.224 13.706 260.644 13.711 260.928 13.717 261.062 13.723 261.114 13.729 261.183 13.735 261.280 13.740 261.374 13.746 261.376 13.752 261.334 13.758 261.300 13.764 261.306 13.769 261.304 13.775 261.278 13.781 261.235 13.787 261.231 13.793 261.252 13.798 261.284 13.804 261.315 13.810 261.378 13.816 261.493 13.822 261.634 13.827 261.733 13.833 261.758 13.839 261.664 13.845 261.481 13.851 261.277 13.857 261.130 13.862 261.038 13.868 261.006 13.874 261.049 13.880 261.148 13.886 261.229 13.891 261.213 13.897 261.116 13.903 260.974 13.909 260.870 13.915 260.855 13.920 260.890 13.926 260.878 13.932 260.783 13.938 260.639 13.944 260.609 13.949 260.743 13.955 260.989 13.961 261.207 13.967 261.303 13.973 261.228 13.978 261.070 13.984 260.932 13.990 260.822 13.996 260.701 14.002 260.545 14.007 260.417 14.013 260.305 14.019 260.167 14.025 260.025 14.031 259.978 14.036 260.030 14.042 260.137 14.048 260.230 14.054 260.318 14.060 260.429 14.065 260.565 14.071 260.684 14.077 260.822 14.083 260.971 14.089 261.180 14.095 261.430 14.100 261.694 14.106 261.938 14.112 262.202 14.118 262.491 14.124 262.808 14.129 263.090 14.135 263.357 14.141 263.550 14.147 263.592 14.153 263.450 14.158 263.214 14.164 262.959 14.170 262.730 14.176 262.458 14.182 262.080 14.187 261.605 14.193 261.139 14.199 260.759 14.205 260.491 14.211 260.272 14.216 260.084 14.222 259.933 14.228 259.795 14.234 259.684 14.240 259.638 14.245 259.691 14.251 259.835 14.257 260.044 14.263 260.291 14.269 260.543 14.274 260.757 14.280 260.982 14.286 261.274 14.292 261.652 14.298 262.064 14.303 262.436 14.309 262.780 14.315 263.147 14.321 263.512 14.327 263.845 14.333 264.072 14.338 264.166 14.344 264.145 14.350 264.040 14.356 263.864 14.362 263.643 14.367 263.381 14.373 263.091 14.379 262.809 14.385 262.529 14.391 262.272 14.396 262.012 14.402 261.714 14.408 261.358 14.414 260.992 14.420 260.654 14.425 260.382 14.431 260.152 14.437 259.924 14.443 259.746 14.449 259.654 14.454 259.663 14.460 259.729 14.466 259.843 14.472 260.048 14.478 260.336 14.483 260.612 14.489 260.877 14.495 261.192 14.501 261.582 14.507 262.021 14.512 262.425 14.518 262.810 14.524 263.207 14.530 263.575 14.536 263.876 14.541 264.041 14.547 264.050 14.553 263.911 14.559 263.653 14.565 263.264 14.571 262.783 14.576 262.309 14.582 261.983 14.588 261.833 14.594 261.687 14.600 261.351 14.605 260.849 14.611 260.374 14.617 260.055 14.623 259.885 14.629 259.756 14.634 259.658 14.640 259.588 14.646 259.498 14.652 259.390 14.658 259.338 14.663 259.394 14.669 259.589 14.675 259.876 14.681 260.247 14.687 260.633 14.692 261.015 14.698 261.421 14.704 261.921 14.710 262.488 14.716 263.094 14.721 263.611 14.727 264.073 14.733 264.470 14.739 264.782 14.745 264.956 14.750 264.959 14.756 264.766 14.762 264.434 14.768 264.014 14.774 263.519 14.780 262.987 14.785 262.428 14.791 261.875 14.797 261.356 14.803 260.875 14.809 260.483 14.814 260.156 14.820 259.845 14.826 259.530 14.832 259.254 14.838 259.065 14.843 258.990 14.849 259.008 14.855 259.049 14.861 259.155 14.867 259.342 14.872 259.640 14.878 260.004 14.884 260.431 14.890 260.934 14.896 261.527 14.901 262.097 14.907 262.661 14.913 263.235 14.919 263.806 14.925 264.293 14.930 264.635 14.936 264.856 14.942 265.001 14.948 265.064 14.954 265.000 14.959 264.742 14.965 264.318 14.971 263.836 14.977 263.392 14.983 262.993 14.988 262.580 14.994 262.163 15.000 261.728 15.006 261.213 15.012 260.632 15.018 260.088 15.023 259.652 15.029 259.343 15.035 259.100 15.041 258.875 15.047 258.686 15.052 258.594 15.058 258.648 15.064 258.874 15.070 259.262 15.076 259.803 15.081 260.375 15.087 260.819 15.093 261.065 15.099 261.243 15.105 261.510 15.110 261.920 15.116 262.404 15.122 262.888 15.128 263.298 15.134 263.577 15.139 263.712 15.145 263.724 15.151 263.695 15.157 263.635 15.163 263.510 15.168 263.224 15.174 262.818 15.180 262.391 15.186 261.988 15.192 261.561 15.197 261.055 15.203 260.476 15.209 259.909 15.215 259.444 15.221 259.053 15.226 258.707 15.232 258.405 15.238 258.191 15.244 258.107 15.250 258.303 15.256 258.872 15.261 259.844 15.267 261.016 15.273 262.130 15.279 263.107 15.285 263.968 15.290 264.453 15.296 264.293 15.302 263.443 15.308 262.161 15.314 261.807 15.319 261.514 15.325 263.845 15.331 269.073 15.337 0.000 15.343 0.000 15.348 0.000 15.354 0.000 15.360 0.000 15.366 0.000 15.372 0.000 15.377 0.000 15.383 0.000 15.389 0.000 15.395 0.000 15.401 0.000 15.406 0.000 15.412 0.000 15.418 0.000 15.424 0.000 15.430 0.000 15.435 0.000 15.441 0.000 15.447 0.000 15.453 0.000 15.459 0.000 15.464 0.000 15.470 0.000 15.476 0.000 15.482 0.000 15.488 0.000 15.494 0.000 15.499 0.000 15.505 0.000 15.511 0.000 15.517 0.000 15.523 0.000 15.528 0.000 15.534 0.000 15.540 0.000 15.546 0.000 15.552 0.000 15.557 0.000 15.563 0.000 15.569 0.000 15.575 0.000 15.581 0.000 15.586 0.000 15.592 0.000 15.598 0.000 15.604 0.000 15.610 0.000 15.615 0.000 15.621 0.000 15.627 0.000 15.633 0.000 15.639 0.000 15.644 0.000 15.650 0.000 15.656 0.000 15.662 0.000 15.668 0.000 15.673 0.000 15.679 0.000 15.685 0.000 15.691 0.000 15.697 0.000 15.702 0.000 15.708 0.000 15.714 0.000 15.720 0.000 15.726 0.000 15.732 0.000 15.737 0.000 15.743 0.000 15.749 0.000 15.755 0.000 15.761 0.000 15.766 0.000 15.772 0.000 15.778 0.000 15.784 0.000 15.790 0.000 15.795 0.000 15.801 0.000 15.807 0.000 15.813 0.000 15.819 0.000 15.824 0.000 15.830 0.000 15.836 0.000 15.842 0.000 15.848 0.000 15.853 0.000 15.859 0.000 15.865 0.000 15.871 0.000 15.877 0.000 15.882 0.000 15.888 0.000 15.894 0.000 15.900 0.000 15.906 0.000 15.911 0.000 15.917 0.000 15.923 0.000 15.929 0.000 15.935 0.000 15.940 0.000 15.946 0.000 15.952 0.000 15.958 0.000 15.964 0.000 15.970 0.000 15.975 0.000 15.981 0.000 15.987 0.000 15.993 0.000 15.999 0.000 16.004 0.000 16.010 0.000 16.016 0.000 16.022 0.000 16.028 0.000 16.033 0.000 16.039 0.000 16.045 0.000 16.051 0.000 16.057 0.000 16.062 0.000 16.068 0.000 16.074 0.000 16.080 0.000 16.086 0.000 16.091 0.000 16.097 0.000 16.103 0.000 16.109 0.000 16.115 0.000 16.120 0.000 16.126 0.000 16.132 0.000 16.138 0.000 16.144 0.000 16.149 0.000 16.155 0.000 16.161 0.000 16.167 0.000 16.173 0.000 16.179 0.000 16.184 0.000 16.190 0.000 16.196 0.000 16.202 0.000 16.208 0.000 16.213 0.000 16.219 0.000 16.225 0.000 16.231 0.000 16.237 0.000 16.242 0.000 16.248 0.000 16.254 0.000 16.260 0.000 16.266 0.000 16.271 0.000 16.277 0.000 16.283 0.000 16.289 0.000 16.295 0.000 16.300 0.000 16.306 0.000 16.312 0.000 16.318 0.000 16.324 0.000 16.329 0.000 16.335 0.000 16.341 351.422 16.347 351.680 16.353 351.945 16.358 351.698 16.364 350.419 16.370 349.100 16.376 349.094 16.382 349.527 16.387 349.362 16.393 348.925 16.399 348.603 16.405 348.469 16.411 348.418 16.417 348.439 16.422 348.552 16.428 348.674 16.434 348.725 16.440 348.625 16.446 348.431 16.451 348.263 16.457 348.198 16.463 348.259 16.469 348.509 16.475 348.908 16.480 349.324 16.486 349.670 16.492 349.922 16.498 350.083 16.504 350.192 16.509 350.258 16.515 350.293 16.521 350.261 16.527 350.137 16.533 349.907 16.538 349.646 16.544 349.413 16.550 349.220 16.556 349.038 16.562 348.961 16.567 348.997 16.573 349.087 16.579 349.120 16.585 349.022 16.591 348.791 16.596 348.483 16.602 348.133 16.608 347.812 16.614 347.622 16.620 347.613 16.625 347.715 16.631 347.796 16.637 347.758 16.643 347.608 16.649 347.524 16.655 347.646 16.660 347.906 16.666 348.219 16.672 348.557 16.678 348.927 16.684 349.259 16.689 349.401 16.695 349.295 16.701 349.074 16.707 348.851 16.713 348.748 16.718 348.756 16.724 348.847 16.730 348.996 16.736 349.192 16.742 349.393 16.747 349.573 16.753 349.666 16.759 349.729 16.765 349.827 16.771 349.959 16.776 349.991 16.782 349.853 16.788 349.595 16.794 349.329 16.800 349.141 16.805 349.139 16.811 349.313 16.817 349.576 16.823 349.847 16.829 350.214 16.834 350.758 16.840 351.434 16.846 352.113 16.852 352.703 16.858 353.275 16.863 353.878 16.869 354.524 16.875 355.194 16.881 355.949 16.887 356.777 16.893 357.512 16.898 357.962 16.904 358.038 16.910 357.730 16.916 357.137 16.922 356.379 16.927 355.551 16.933 354.537 16.939 352.975 16.945 350.250 16.951 346.728 16.956 343.225 16.962 339.358 16.968 333.527 16.974 323.461 16.980 316.907 16.985 303.005 16.991 303.958 16.997 297.545 17.003 305.623 17.009 294.971 17.014 0.000 17.020 0.000 17.026 0.000 17.032 0.000 17.038 300.801 17.043 296.964 17.049 294.351 17.055 292.057 17.061 290.239 17.067 289.172 17.072 288.572 17.078 288.134 17.084 287.915 17.090 287.864 17.096 288.105 17.101 288.334 17.107 288.589 17.113 288.948 17.119 289.475 17.125 290.205 17.131 290.886 17.136 291.408 17.142 291.748 17.148 291.961 17.154 292.121 17.160 292.368 17.165 292.686 17.171 293.005 17.177 293.236 17.183 293.379 17.189 293.510 17.194 293.666 17.200 293.777 17.206 293.766 17.212 293.608 17.218 293.381 17.223 293.213 17.229 293.093 17.235 292.950 17.241 292.767 17.247 292.604 17.252 292.581 17.258 292.665 17.264 292.743 17.270 292.778 17.276 292.849 17.281 293.001 17.287 293.237 17.293 293.429 17.299 293.478 17.305 293.339 17.310 293.050 17.316 292.768 17.322 292.623 17.328 292.597 17.334 292.589 17.340 292.559 17.345 292.613 17.351 292.792 17.357 293.020 17.363 293.177 17.369 293.235 17.374 293.243 17.380 293.165 17.386 293.041 17.392 292.984 17.398 293.091 17.403 293.340 17.409 293.638 17.415 293.887 17.421 294.114 17.427 294.251 17.432 294.303 17.438 294.223 17.444 294.047 17.450 293.783 17.456 293.517 17.461 293.233 17.467 292.970 17.473 292.691 17.479 292.475 17.485 292.535 17.490 292.865 17.496 293.155 17.502 293.148 17.508 292.868 17.514 292.618 17.519 292.726 17.525 293.153 17.531 293.525 17.537 293.305 17.543 292.267 17.548 290.433 17.554 288.114 17.560 286.006 17.566 284.362 17.572 281.898 17.578 279.816 17.583 279.499 17.589 286.169 17.595 294.500 17.601 0.000 17.607 0.000 17.612 0.000 17.618 0.000 17.624 0.000 17.630 0.000 17.636 0.000 17.641 0.000 17.647 0.000 17.653 0.000 17.659 0.000 17.665 0.000 17.670 0.000 17.676 0.000 17.682 0.000 17.688 294.267 17.694 295.495 17.699 294.900 17.705 294.428 17.711 294.235 17.717 294.140 17.723 293.724 17.728 292.930 17.734 291.734 17.740 291.037 17.746 291.993 17.752 292.622 17.757 292.915 17.763 292.868 17.769 292.796 17.775 292.861 17.781 292.906 17.786 292.859 17.792 292.795 17.798 292.850 17.804 293.046 17.810 293.361 17.816 293.700 17.821 293.992 17.827 294.202 17.833 294.337 17.839 294.448 17.845 294.541 17.850 294.594 17.856 294.563 17.862 294.427 17.868 294.212 17.874 293.987 17.879 293.797 17.885 293.638 17.891 293.486 17.897 293.416 17.903 293.462 17.908 293.556 17.914 293.602 17.920 293.501 17.926 293.286 17.932 293.021 17.937 292.738 17.943 292.477 17.949 292.329 17.955 292.305 17.961 292.377 17.966 292.448 17.972 292.448 17.978 292.337 17.984 292.253 17.990 292.311 17.995 292.504 18.001 292.771 18.007 293.070 18.013 293.411 18.019 293.747 18.024 293.913 18.030 293.857 18.036 293.681 18.042 293.498 18.048 293.397 18.054 293.380 18.059 293.435 18.065 293.562 18.071 293.731 18.077 293.905 18.083 294.056 18.088 294.143 18.094 294.212 18.100 294.306 18.106 294.411 18.112 294.436 18.117 294.322 18.123 294.081 18.129 293.693 18.135 293.150 18.141 292.587 18.146 292.380 18.152 292.587 18.158 292.888 18.164 292.899 18.170 292.528 18.175 292.000 18.181 291.564 18.187 291.181 18.193 290.675 18.199 290.045 18.204 289.394 18.210 288.922 18.216 288.645 18.222 288.508 18.228 288.499 18.233 288.659 18.239 288.838 18.245 288.958 18.251 289.245 18.257 290.089 18.262 291.806 18.268 294.377 18.274 296.683 18.280 298.011 18.286 298.912 18.292 299.815 18.297 300.931 18.303 302.152 18.309 303.220 18.315 303.081 18.321 300.484 18.326 294.453 18.332 291.025 18.338 295.914 18.344 307.422 18.350 313.219 18.355 315.323 18.361 315.984 18.367 316.230 18.373 316.316 18.379 316.328 18.384 316.245 18.390 315.883 18.396 315.084 18.402 314.004 18.408 312.898 18.413 311.710 18.419 310.390 18.425 309.518 18.431 309.215 18.437 309.054 18.442 308.417 18.448 306.748 18.454 303.692 18.460 299.691 18.466 296.678 18.471 286.981 18.477 0.000 18.483 0.000 18.489 0.000 18.495 0.000 18.500 0.000 18.506 0.000 18.512 0.000 18.518 0.000 18.524 0.000 18.530 0.000 18.535 0.000 18.541 0.000 18.547 0.000 18.553 0.000 18.559 0.000 18.564 0.000 18.570 0.000 18.576 0.000 18.582 0.000 18.588 0.000 18.593 0.000 18.599 0.000 18.605 0.000 18.611 0.000 18.617 0.000 18.622 0.000 18.628 315.256 18.634 285.561 18.640 296.124 18.646 289.566 18.651 297.306 18.657 306.242 18.663 288.685 18.669 291.496 18.675 302.623 18.680 313.376 18.686 312.457 18.692 311.666 18.698 310.609 18.704 309.817 18.709 309.578 18.715 310.325 18.721 311.271 18.727 311.655 18.733 311.285 18.739 310.928 18.744 311.246 18.750 311.923 18.756 312.048 18.762 311.441 18.768 310.722 18.773 310.226 18.779 309.804 18.785 309.420 18.791 309.146 18.797 309.102 18.802 309.170 18.808 309.205 18.814 309.234 18.820 309.445 18.826 309.865 18.831 310.319 18.837 310.583 18.843 310.667 18.849 310.694 18.855 310.748 18.860 310.816 18.866 310.858 18.872 310.858 18.878 310.837 18.884 310.843 18.889 310.879 18.895 310.892 18.901 310.861 18.907 310.813 18.913 310.779 18.918 310.778 18.924 310.803 18.930 310.869 18.936 310.990 18.942 311.141 18.947 311.272 18.953 311.341 18.959 311.301 18.965 311.125 18.971 310.875 18.977 310.679 18.982 310.583 18.988 310.554 18.994 310.562 19.000 310.597 19.006 310.647 19.011 310.672 19.017 310.643 19.023 310.540 19.029 310.412 19.035 310.341 19.040 310.342 19.046 310.344 19.052 310.273 19.058 310.137 19.064 310.051 19.069 310.141 19.075 310.368 19.081 310.669 19.087 310.977 19.093 311.254 19.098 311.473 19.104 311.654 19.110 311.757 19.116 311.794 19.122 311.767 19.127 311.710 19.133 311.659 19.139 311.607 19.145 311.545 19.151 311.530 19.156 311.591 19.162 311.724 19.168 311.882 19.174 312.023 19.180 312.140 19.185 312.267 19.191 312.368 19.197 312.407 19.203 312.369 19.209 312.328 19.215 312.339 19.220 312.351 19.226 312.286 19.232 312.154 19.238 312.025 19.244 311.942 19.249 311.882 19.255 311.877 19.261 311.926 19.267 311.917 19.273 311.792 19.278 311.624 19.284 311.511 19.290 311.530 19.296 311.595 19.302 311.555 19.307 311.385 19.313 311.191 19.319 311.104 19.325 311.184 19.331 311.315 19.336 311.420 19.342 311.500 19.348 311.514 19.354 311.447 19.360 311.388 19.365 311.409 19.371 311.548 19.377 311.714 19.383 311.834 19.389 311.895 19.394 311.869 19.400 311.791 19.406 311.759 19.412 311.832 19.418 312.001 19.423 312.181 19.429 312.324 19.435 312.471 19.441 312.626 19.447 312.775 19.453 312.863 19.458 312.837 19.464 312.703 19.470 312.479 19.476 312.206 19.482 311.928 19.487 311.687 19.493 311.485 19.499 311.361 19.505 311.285 19.511 311.269 19.516 311.277 19.522 311.253 19.528 311.152 19.534 311.024 19.540 310.901 19.545 310.811 19.551 310.723 19.557 310.581 19.563 310.438 19.569 310.402 19.574 310.500 19.580 310.698 19.586 310.921 19.592 311.185 19.598 311.506 19.603 311.817 19.609 312.056 19.615 312.299 19.621 312.579 19.627 312.875 19.632 313.082 19.638 313.190 19.644 313.261 19.650 313.314 19.656 313.320 19.661 313.257 19.667 313.117 19.673 312.923 19.679 312.703 19.685 312.447 19.691 312.145 19.696 311.855 19.702 311.680 19.708 311.731 19.714 311.875 19.720 311.835 19.725 311.523 19.731 311.131 19.737 310.866 19.743 310.801 19.749 310.754 19.754 310.659 19.760 310.557 19.766 310.411 19.772 310.206 19.778 310.040 19.783 309.984 19.789 310.082 19.795 310.238 19.801 310.376 19.807 310.480 19.812 310.515 19.818 310.503 19.824 310.547 19.830 310.716 19.836 311.011 19.841 311.355 19.847 311.697 19.853 312.073 19.859 312.482 19.865 312.917 19.870 313.294 19.876 313.531 19.882 313.601 19.888 313.520 19.894 313.333 19.900 313.098 19.905 312.843 19.911 312.572 19.917 312.337 19.923 312.136 19.929 311.998 19.934 311.888 19.940 311.743 19.946 311.498 19.952 311.201 19.958 310.885 19.963 310.599 19.969 310.354 19.975 310.109 19.981 309.891 19.987 309.751 19.992 309.687 19.998 309.696 20.004 309.746 20.010 309.873 20.016 310.093 20.021 310.347 20.027 310.593 20.033 310.894 20.039 311.260 20.045 311.662 20.050 312.002 20.056 312.272 20.062 312.533 20.068 312.801 20.074 313.080 20.079 313.308 20.085 313.461 20.091 313.547 20.097 313.599 20.103 313.635 20.108 313.651 20.114 313.633 20.120 313.597 20.126 313.486 20.132 313.264 20.138 312.973 20.143 312.670 20.149 312.427 20.155 312.205 20.161 311.882 20.167 311.409 20.172 310.917 20.178 310.531 20.184 310.325 20.190 310.191 20.196 310.071 20.201 309.972 20.207 309.867 20.213 309.729 20.219 309.633 20.225 309.572 20.230 309.501 20.236 309.333 20.242 309.063 20.248 308.852 20.254 308.818 20.259 308.973 20.265 309.271 20.271 309.637 20.277 309.988 20.283 310.279 20.288 310.512 20.294 310.780 20.300 311.121 20.306 311.474 20.312 311.729 20.317 311.863 20.323 311.953 20.329 312.075 20.335 312.192 20.341 312.224 20.346 312.141 20.352 311.973 20.358 311.819 20.364 311.671 20.370 311.484 20.376 311.225 20.381 310.989 20.387 310.812 20.393 310.729 20.399 310.683 20.405 310.703 20.410 310.860 20.416 311.194 20.422 311.591 20.428 311.971 20.434 312.284 20.439 312.292 20.445 311.880 20.451 310.874 20.457 309.697 20.463 308.772 20.468 0.000 20.474 0.000 20.480 0.000 20.486 0.000 20.492 0.000 20.497 0.000 20.503 0.000 20.509 0.000 20.515 0.000 20.521 0.000 20.526 0.000 20.532 0.000 20.538 0.000 20.544 0.000 20.550 0.000 20.555 0.000 20.561 0.000 20.567 0.000 20.573 0.000 20.579 0.000 20.584 0.000 20.590 0.000 20.596 0.000 20.602 0.000 20.608 0.000 20.614 0.000 20.619 0.000 20.625 0.000 20.631 0.000 20.637 0.000 20.643 0.000 20.648 0.000 20.654 0.000 20.660 0.000 20.666 0.000 20.672 0.000 20.677 0.000 20.683 0.000 20.689 0.000 20.695 0.000 20.701 0.000 20.706 0.000 20.712 0.000 20.718 0.000 20.724 0.000 20.730 0.000 20.735 0.000 20.741 0.000 20.747 0.000 20.753 0.000 20.759 0.000 20.764 0.000 20.770 0.000 20.776 0.000 20.782 0.000 20.788 0.000 20.793 0.000 20.799 0.000 20.805 0.000 20.811 0.000 20.817 0.000 20.822 0.000 20.828 0.000 20.834 0.000 20.840 0.000 20.846 0.000 20.852 0.000 20.857 0.000 20.863 0.000 20.869 0.000 20.875 0.000 20.881 0.000 20.886 0.000 20.892 0.000 20.898 0.000 20.904 0.000 20.910 0.000 20.915 0.000 20.921 0.000 20.927 0.000 20.933 0.000 20.939 0.000 20.944 0.000 20.950 0.000 20.956 0.000 20.962 0.000 20.968 0.000 20.973 0.000 20.979 0.000 20.985 0.000 20.991 0.000 20.997 0.000 21.002 0.000 21.008 0.000 21.014 0.000 21.020 0.000 21.026 0.000 21.031 0.000 21.037 0.000 21.043 0.000 21.049 0.000 21.055 0.000 21.060 0.000 21.066 0.000 21.072 0.000 21.078 0.000 mir_eval-0.8.2/tests/data/melody/ref01.txt000066400000000000000000002162171475740344600203700ustar00rootroot000000000000000.000 0.000 0.006 0.000 0.012 0.000 0.017 0.000 0.023 0.000 0.029 0.000 0.035 0.000 0.041 0.000 0.046 0.000 0.052 0.000 0.058 0.000 0.064 0.000 0.070 0.000 0.075 0.000 0.081 0.000 0.087 0.000 0.093 0.000 0.099 0.000 0.104 0.000 0.110 0.000 0.116 0.000 0.122 0.000 0.128 0.000 0.134 0.000 0.139 0.000 0.145 0.000 0.151 0.000 0.157 0.000 0.163 0.000 0.168 0.000 0.174 0.000 0.180 0.000 0.186 0.000 0.192 0.000 0.197 0.000 0.203 0.000 0.209 0.000 0.215 0.000 0.221 0.000 0.226 0.000 0.232 0.000 0.238 0.000 0.244 0.000 0.250 0.000 0.255 0.000 0.261 0.000 0.267 0.000 0.273 0.000 0.279 0.000 0.284 0.000 0.290 0.000 0.296 0.000 0.302 0.000 0.308 0.000 0.313 0.000 0.319 0.000 0.325 0.000 0.331 0.000 0.337 0.000 0.342 0.000 0.348 0.000 0.354 0.000 0.360 0.000 0.366 0.000 0.372 0.000 0.377 0.000 0.383 0.000 0.389 0.000 0.395 0.000 0.401 0.000 0.406 0.000 0.412 0.000 0.418 0.000 0.424 0.000 0.430 0.000 0.435 0.000 0.441 0.000 0.447 0.000 0.453 0.000 0.459 0.000 0.464 0.000 0.470 0.000 0.476 0.000 0.482 0.000 0.488 0.000 0.493 0.000 0.499 0.000 0.505 0.000 0.511 0.000 0.517 0.000 0.522 298.886 0.528 296.296 0.534 296.296 0.540 293.333 0.546 291.385 0.551 289.661 0.557 290.419 0.563 292.297 0.569 293.615 0.575 294.933 0.580 293.289 0.586 291.644 0.592 292.900 0.598 289.713 0.604 288.336 0.610 288.915 0.615 288.981 0.621 289.303 0.627 289.625 0.633 289.948 0.639 290.270 0.644 290.593 0.650 291.246 0.656 290.909 0.662 290.627 0.668 290.662 0.673 291.261 0.679 292.506 0.685 293.089 0.691 293.354 0.697 292.765 0.702 292.696 0.708 292.487 0.714 292.132 0.720 291.861 0.726 291.827 0.731 292.046 0.737 292.522 0.743 293.090 0.749 293.750 0.755 295.053 0.760 295.221 0.766 296.037 0.772 296.529 0.778 297.021 0.784 297.145 0.789 297.131 0.795 296.959 0.801 296.686 0.807 296.413 0.813 296.140 0.819 295.780 0.824 295.463 0.830 295.124 0.836 294.785 0.842 294.553 0.848 294.522 0.853 294.489 0.859 294.592 0.865 294.642 0.871 295.018 0.877 294.801 0.882 294.819 0.888 294.600 0.894 294.988 0.900 294.914 0.906 294.860 0.911 294.771 0.917 294.681 0.923 294.456 0.929 294.298 0.935 294.208 0.940 294.130 0.946 294.115 0.952 294.781 0.958 294.698 0.964 295.189 0.969 295.318 0.975 295.446 0.981 295.252 0.987 295.058 0.993 295.496 0.998 295.242 1.004 295.140 1.010 295.039 1.016 295.359 1.022 295.198 1.027 295.036 1.033 295.655 1.039 295.332 1.045 296.664 1.051 297.675 1.057 298.625 1.062 299.575 1.068 300.339 1.074 301.103 1.080 301.867 1.086 302.549 1.091 302.804 1.097 303.060 1.103 303.316 1.109 303.451 1.115 302.581 1.120 302.107 1.126 300.736 1.132 296.816 1.138 297.112 1.144 295.129 1.149 293.147 1.155 291.164 1.161 288.204 1.167 285.733 1.173 284.598 1.178 282.794 1.184 278.512 1.190 275.469 1.196 272.426 1.202 272.077 1.207 271.728 1.213 270.185 1.219 268.375 1.225 264.031 1.231 263.564 1.236 262.503 1.242 261.441 1.248 257.913 1.254 256.166 1.260 254.797 1.265 254.075 1.271 253.760 1.277 253.475 1.283 254.202 1.289 253.970 1.295 253.952 1.300 254.487 1.306 255.559 1.312 256.539 1.318 257.565 1.324 258.274 1.329 258.900 1.335 259.240 1.341 259.580 1.347 259.920 1.353 260.215 1.358 260.527 1.364 261.019 1.370 261.071 1.376 261.248 1.382 261.403 1.387 261.598 1.393 261.793 1.399 261.802 1.405 261.774 1.411 261.652 1.416 261.439 1.422 261.227 1.428 261.071 1.434 260.875 1.440 260.629 1.445 260.561 1.451 260.575 1.457 260.756 1.463 260.720 1.469 260.841 1.474 260.935 1.480 261.194 1.486 261.360 1.492 261.487 1.498 261.476 1.503 261.220 1.509 260.964 1.515 260.938 1.521 260.732 1.527 260.590 1.533 260.526 1.538 260.557 1.544 260.743 1.550 260.982 1.556 261.221 1.562 261.231 1.567 261.220 1.573 261.088 1.579 260.957 1.585 260.982 1.591 260.919 1.596 261.015 1.602 261.315 1.608 261.605 1.614 261.852 1.620 261.998 1.625 262.126 1.631 262.092 1.637 261.971 1.643 261.748 1.649 261.553 1.654 261.312 1.660 261.063 1.666 260.818 1.672 259.968 1.678 260.876 1.683 260.586 1.689 260.296 1.695 260.479 1.701 259.942 1.707 260.071 1.712 260.133 1.718 260.265 1.724 259.911 1.730 259.713 1.736 259.420 1.741 259.459 1.747 260.031 1.753 260.603 1.759 261.175 1.765 261.741 1.771 261.576 1.776 261.281 1.782 261.031 1.788 260.527 1.794 259.755 1.800 256.526 1.805 255.799 1.811 256.359 1.817 258.804 1.823 261.248 1.829 261.056 1.834 259.791 1.840 261.653 1.846 260.640 1.852 260.351 1.858 260.318 1.863 260.157 1.869 260.060 1.875 262.530 1.881 265.027 1.887 267.524 1.892 266.684 1.898 264.918 1.904 262.764 1.910 261.349 1.916 260.692 1.921 260.421 1.927 260.532 1.933 261.056 1.939 261.329 1.945 261.139 1.950 260.417 1.956 259.961 1.962 259.890 1.968 260.238 1.974 260.629 1.980 261.020 1.985 261.177 1.991 261.157 1.997 261.105 2.003 261.069 2.009 261.046 2.014 261.202 2.020 261.357 2.026 261.513 2.032 261.669 2.038 261.316 2.043 260.673 2.049 260.520 2.055 260.168 2.061 260.140 2.067 260.073 2.072 260.104 2.078 260.350 2.084 260.644 2.090 260.875 2.096 260.990 2.101 260.791 2.107 260.876 2.113 260.777 2.119 260.811 2.125 260.845 2.130 260.879 2.136 261.094 2.142 261.219 2.148 261.292 2.154 261.391 2.159 261.490 2.165 261.589 2.171 261.688 2.177 261.588 2.183 261.321 2.188 261.027 2.194 260.825 2.200 260.737 2.206 260.709 2.212 260.652 2.218 260.594 2.223 260.649 2.229 260.768 2.235 260.855 2.241 260.958 2.247 261.061 2.252 261.164 2.258 261.337 2.264 261.509 2.270 261.465 2.276 261.319 2.281 261.173 2.287 260.986 2.293 260.922 2.299 260.858 2.305 260.824 2.310 260.934 2.316 261.248 2.322 261.563 2.328 261.708 2.334 261.853 2.339 261.998 2.345 262.091 2.351 262.061 2.357 261.870 2.363 261.680 2.368 261.437 2.374 261.233 2.380 261.123 2.386 261.071 2.392 261.078 2.397 261.123 2.403 261.172 2.409 261.256 2.415 261.322 2.421 261.422 2.426 261.658 2.432 261.781 2.438 261.904 2.444 262.027 2.450 262.147 2.456 262.149 2.461 262.059 2.467 261.925 2.473 261.792 2.479 261.658 2.485 261.524 2.490 261.608 2.496 261.781 2.502 262.459 2.508 262.461 2.514 263.029 2.519 263.634 2.525 264.202 2.531 264.769 2.537 265.337 2.543 265.904 2.548 266.472 2.554 266.728 2.560 266.984 2.566 266.595 2.572 266.752 2.577 265.928 2.583 266.185 2.589 265.577 2.595 264.603 2.601 263.248 2.606 261.588 2.612 259.860 2.618 258.133 2.624 256.181 2.630 254.341 2.635 251.138 2.641 248.616 2.647 245.487 2.653 243.675 2.659 241.205 2.664 239.064 2.670 238.062 2.676 236.491 2.682 0.000 2.688 0.000 2.694 0.000 2.699 0.000 2.705 217.805 2.711 215.627 2.717 215.627 2.723 215.627 2.728 215.627 2.734 215.627 2.740 215.337 2.746 215.047 2.752 214.758 2.757 215.622 2.763 216.267 2.769 216.686 2.775 216.829 2.781 216.972 2.786 217.115 2.792 218.144 2.798 218.709 2.804 219.273 2.810 219.005 2.815 218.738 2.821 219.142 2.827 219.446 2.833 219.559 2.839 219.612 2.844 219.575 2.850 219.538 2.856 219.501 2.862 219.564 2.868 219.550 2.873 219.520 2.879 219.595 2.885 219.559 2.891 219.686 2.897 219.621 2.902 219.622 2.908 219.801 2.914 219.764 2.920 219.755 2.926 219.796 2.932 219.844 2.937 219.892 2.943 219.792 2.949 219.693 2.955 219.615 2.961 219.685 2.966 219.678 2.972 219.490 2.978 219.129 2.984 218.528 2.990 217.928 2.995 217.747 3.001 217.566 3.007 217.945 3.013 218.165 3.019 218.158 3.024 218.015 3.030 217.806 3.036 217.597 3.042 217.061 3.048 216.688 3.053 216.177 3.059 216.021 3.065 216.172 3.071 216.931 3.077 216.632 3.082 216.584 3.088 216.536 3.094 216.488 3.100 216.439 3.106 216.391 3.111 216.343 3.117 218.458 3.123 219.376 3.129 218.861 3.135 219.759 3.140 220.658 3.146 221.687 3.152 223.100 3.158 224.322 3.164 225.543 3.170 226.764 3.175 227.985 3.181 229.514 3.187 231.292 3.193 233.071 3.199 233.689 3.204 234.430 3.210 235.171 3.216 235.912 3.222 236.430 3.228 236.707 3.233 236.984 3.239 236.980 3.245 236.899 3.251 236.818 3.257 236.648 3.262 235.170 3.268 235.974 3.274 235.620 3.280 234.018 3.286 233.553 3.291 233.207 3.297 233.285 3.303 233.679 3.309 233.910 3.315 233.382 3.320 233.629 3.326 232.595 3.332 232.407 3.338 231.795 3.344 231.395 3.349 231.709 3.355 231.378 3.361 231.129 3.367 230.947 3.373 231.057 3.379 231.167 3.384 231.196 3.390 231.592 3.396 231.987 3.402 232.411 3.408 232.821 3.413 233.290 3.419 233.471 3.425 233.694 3.431 233.916 3.437 233.572 3.442 233.480 3.448 233.426 3.454 233.222 3.460 232.998 3.466 232.772 3.471 232.642 3.477 232.687 3.483 232.732 3.489 232.463 3.495 232.611 3.500 232.193 3.506 232.112 3.512 232.194 3.518 232.327 3.524 232.484 3.529 232.640 3.535 232.481 3.541 232.530 3.547 232.578 3.553 232.452 3.558 232.325 3.564 232.199 3.570 229.752 3.576 230.749 3.582 230.278 3.587 231.987 3.593 231.103 3.599 232.650 3.605 232.380 3.611 233.156 3.617 232.771 3.622 232.769 3.628 231.962 3.634 232.564 3.640 232.898 3.646 232.617 3.651 232.336 3.657 232.575 3.663 232.527 3.669 232.995 3.675 232.270 3.680 232.715 3.686 232.665 3.692 232.616 3.698 232.567 3.704 232.517 3.709 232.468 3.715 232.382 3.721 232.315 3.727 232.073 3.733 236.556 3.738 238.617 3.744 239.471 3.750 238.519 3.756 241.223 3.762 244.684 3.767 248.145 3.773 236.636 3.779 247.174 3.785 232.089 3.791 0.000 3.796 0.000 3.802 0.000 3.808 0.000 3.814 0.000 3.820 0.000 3.825 0.000 3.831 0.000 3.837 0.000 3.843 0.000 3.849 0.000 3.855 0.000 3.860 0.000 3.866 0.000 3.872 0.000 3.878 0.000 3.884 0.000 3.889 0.000 3.895 0.000 3.901 0.000 3.907 0.000 3.913 0.000 3.918 0.000 3.924 0.000 3.930 0.000 3.936 0.000 3.942 0.000 3.947 0.000 3.953 0.000 3.959 0.000 3.965 0.000 3.971 0.000 3.976 0.000 3.982 0.000 3.988 0.000 3.994 0.000 4.000 0.000 4.005 0.000 4.011 0.000 4.017 0.000 4.023 0.000 4.029 0.000 4.034 0.000 4.040 0.000 4.046 0.000 4.052 0.000 4.058 0.000 4.063 0.000 4.069 0.000 4.075 0.000 4.081 0.000 4.087 0.000 4.093 0.000 4.098 0.000 4.104 0.000 4.110 0.000 4.116 0.000 4.122 0.000 4.127 0.000 4.133 0.000 4.139 0.000 4.145 0.000 4.151 0.000 4.156 0.000 4.162 0.000 4.168 0.000 4.174 0.000 4.180 0.000 4.185 0.000 4.191 0.000 4.197 0.000 4.203 0.000 4.209 0.000 4.214 0.000 4.220 0.000 4.226 0.000 4.232 270.094 4.238 277.771 4.243 272.215 4.249 264.049 4.255 259.815 4.261 261.223 4.267 262.631 4.272 261.928 4.278 261.212 4.284 260.235 4.290 259.695 4.296 259.732 4.301 259.769 4.307 260.357 4.313 260.498 4.319 260.487 4.325 260.394 4.331 260.300 4.336 261.340 4.342 260.557 4.348 260.892 4.354 260.696 4.360 260.538 4.365 260.380 4.371 260.221 4.377 259.950 4.383 260.063 4.389 260.373 4.394 260.682 4.400 260.992 4.406 261.301 4.412 262.724 4.418 263.405 4.423 264.086 4.429 264.543 4.435 264.947 4.441 265.163 4.447 265.091 4.452 264.669 4.458 264.068 4.464 263.581 4.470 263.722 4.476 263.459 4.481 263.197 4.487 262.934 4.493 262.672 4.499 262.409 4.505 261.681 4.510 260.953 4.516 259.221 4.522 257.489 4.528 254.542 4.534 251.595 4.540 248.581 4.545 245.600 4.551 242.619 4.557 240.333 4.563 236.812 4.569 233.291 4.574 229.771 4.580 226.250 4.586 227.010 4.592 226.600 4.598 226.189 4.603 226.920 4.609 227.651 4.615 228.382 4.621 227.563 4.627 227.835 4.632 227.877 4.638 227.919 4.644 228.299 4.650 228.679 4.656 229.060 4.661 229.440 4.667 229.821 4.673 230.202 4.679 230.582 4.685 231.399 4.690 232.216 4.696 232.727 4.702 232.878 4.708 232.741 4.714 232.658 4.719 232.604 4.725 232.579 4.731 232.571 4.737 232.554 4.743 232.542 4.748 232.766 4.754 232.636 4.760 232.694 4.766 232.545 4.772 232.354 4.778 232.257 4.783 232.154 4.789 232.364 4.795 232.382 4.801 232.399 4.807 232.383 4.812 232.368 4.818 232.352 4.824 232.336 4.830 232.321 4.836 232.441 4.841 232.165 4.847 232.294 4.853 232.504 4.859 232.720 4.865 232.867 4.870 232.860 4.876 232.854 4.882 232.933 4.888 233.011 4.894 233.382 4.899 233.569 4.905 233.568 4.911 233.454 4.917 232.750 4.923 233.070 4.928 232.974 4.934 232.879 4.940 232.783 4.946 232.687 4.952 232.591 4.957 232.322 4.963 232.140 4.969 231.893 4.975 231.824 4.981 231.873 4.986 231.922 4.992 231.897 4.998 231.911 5.004 231.456 5.010 231.235 5.016 230.786 5.021 230.327 5.027 229.658 5.033 229.378 5.039 229.639 5.045 229.566 5.050 229.043 5.056 228.328 5.062 227.879 5.068 228.045 5.074 228.421 5.079 228.594 5.085 228.211 5.091 227.692 5.097 227.884 5.103 229.038 5.108 230.192 5.114 233.285 5.120 235.409 5.126 237.532 5.132 239.655 5.137 242.329 5.143 244.455 5.149 246.485 5.155 248.563 5.161 250.617 5.166 255.787 5.172 260.956 5.178 263.465 5.184 261.958 5.190 264.731 5.195 263.794 5.201 263.524 5.207 265.550 5.213 266.912 5.219 268.273 5.224 266.938 5.230 267.331 5.236 267.496 5.242 266.930 5.248 266.365 5.254 265.800 5.259 265.234 5.265 264.669 5.271 263.981 5.277 263.619 5.283 263.093 5.288 262.649 5.294 262.205 5.300 261.761 5.306 261.502 5.312 261.427 5.317 261.260 5.323 261.014 5.329 260.768 5.335 260.756 5.341 260.996 5.346 261.237 5.352 261.478 5.358 261.719 5.364 261.960 5.370 261.694 5.375 261.781 5.381 261.766 5.387 261.641 5.393 261.484 5.399 261.327 5.404 261.146 5.410 260.976 5.416 260.807 5.422 261.186 5.428 261.076 5.433 261.057 5.439 261.129 5.445 261.206 5.451 261.316 5.457 261.432 5.462 261.581 5.468 261.730 5.474 261.678 5.480 261.555 5.486 261.290 5.492 261.096 5.497 261.071 5.503 261.047 5.509 261.022 5.515 261.153 5.521 261.225 5.526 261.298 5.532 261.371 5.538 261.444 5.544 260.891 5.550 261.300 5.555 261.238 5.561 261.377 5.567 261.516 5.573 261.655 5.579 261.794 5.584 260.431 5.590 260.157 5.596 259.339 5.602 257.328 5.608 258.473 5.613 260.973 5.619 270.679 5.625 274.015 5.631 272.120 5.637 256.057 5.642 0.000 5.648 0.000 5.654 0.000 5.660 0.000 5.666 0.000 5.671 0.000 5.677 0.000 5.683 0.000 5.689 0.000 5.695 0.000 5.700 0.000 5.706 0.000 5.712 0.000 5.718 0.000 5.724 0.000 5.730 269.268 5.735 263.882 5.741 263.882 5.747 266.521 5.753 266.521 5.759 272.062 5.764 274.273 5.770 277.083 5.776 280.180 5.782 283.087 5.788 286.089 5.793 291.934 5.799 296.358 5.805 298.477 5.811 295.713 5.817 294.982 5.822 296.067 5.828 297.070 5.834 297.590 5.840 297.892 5.846 298.081 5.851 298.269 5.857 298.455 5.863 298.225 5.869 297.633 5.875 297.041 5.880 296.449 5.886 295.857 5.892 295.872 5.898 295.419 5.904 294.965 5.909 294.663 5.915 294.360 5.921 294.057 5.927 293.919 5.933 293.953 5.939 294.076 5.944 294.010 5.950 294.012 5.956 293.697 5.962 293.616 5.968 293.463 5.973 293.262 5.979 293.110 5.985 292.933 5.991 292.768 5.997 292.604 6.002 292.651 6.008 292.871 6.014 293.090 6.020 293.310 6.026 293.398 6.031 293.483 6.037 293.724 6.043 293.811 6.049 293.975 6.055 293.998 6.060 294.091 6.066 294.185 6.072 294.278 6.078 293.885 6.084 293.810 6.089 293.648 6.095 293.627 6.101 293.614 6.107 293.718 6.113 293.685 6.118 293.754 6.124 293.565 6.130 293.658 6.136 293.335 6.142 293.396 6.147 293.457 6.153 293.388 6.159 293.448 6.165 293.509 6.171 293.248 6.177 293.074 6.182 292.856 6.188 292.639 6.194 292.422 6.200 292.204 6.206 292.511 6.211 292.392 6.217 292.273 6.223 292.154 6.229 292.035 6.235 291.916 6.240 292.112 6.246 292.030 6.252 291.948 6.258 292.131 6.264 292.211 6.269 292.280 6.275 292.335 6.281 292.389 6.287 291.797 6.293 290.980 6.298 289.629 6.304 288.899 6.310 289.614 6.316 289.404 6.322 288.654 6.327 287.431 6.333 286.208 6.339 286.580 6.345 286.724 6.351 286.868 6.356 287.012 6.362 287.156 6.368 290.173 6.374 291.753 6.380 293.334 6.385 294.914 6.391 299.460 6.397 302.523 6.403 314.702 6.409 317.207 6.415 319.711 6.420 325.438 6.426 0.000 6.432 0.000 6.438 0.000 6.444 0.000 6.449 0.000 6.455 368.052 6.461 386.455 6.467 398.049 6.473 399.876 6.478 399.876 6.484 400.751 6.490 399.797 6.496 400.107 6.502 400.417 6.507 400.704 6.513 400.282 6.519 399.436 6.525 398.477 6.531 397.518 6.536 396.950 6.542 396.131 6.548 395.600 6.554 395.053 6.560 394.577 6.565 394.076 6.571 393.509 6.577 392.848 6.583 392.249 6.589 391.828 6.594 391.561 6.600 391.328 6.606 391.031 6.612 390.746 6.618 390.492 6.623 390.328 6.629 390.332 6.635 390.373 6.641 390.475 6.647 390.610 6.653 390.729 6.658 390.819 6.664 390.819 6.670 390.868 6.676 390.936 6.682 391.087 6.687 391.292 6.693 391.578 6.699 391.882 6.705 392.236 6.711 392.585 6.716 392.844 6.722 392.969 6.728 392.984 6.734 392.874 6.740 392.489 6.745 391.805 6.751 391.073 6.757 391.421 6.763 390.718 6.769 391.349 6.774 391.182 6.780 390.376 6.786 389.890 6.792 389.472 6.798 389.320 6.803 389.552 6.809 389.783 6.815 390.015 6.821 390.247 6.827 390.538 6.832 390.960 6.838 391.015 6.844 391.382 6.850 392.424 6.856 392.321 6.861 392.070 6.867 391.789 6.873 391.117 6.879 389.806 6.885 389.657 6.891 389.679 6.896 390.890 6.902 391.235 6.908 391.372 6.914 390.816 6.920 392.155 6.925 392.495 6.931 392.836 6.937 393.176 6.943 393.517 6.949 393.857 6.954 394.198 6.960 393.638 6.966 393.872 6.972 396.041 6.978 398.210 6.983 400.379 6.989 0.000 6.995 0.000 7.001 0.000 7.007 0.000 7.012 0.000 7.018 0.000 7.024 0.000 7.030 343.464 7.036 343.464 7.041 346.898 7.047 346.898 7.053 348.397 7.059 348.091 7.065 348.120 7.070 348.148 7.076 348.176 7.082 348.205 7.088 348.233 7.094 348.261 7.100 348.289 7.105 348.310 7.111 348.332 7.117 348.353 7.123 348.374 7.129 348.395 7.134 348.416 7.140 348.176 7.146 348.195 7.152 348.654 7.158 348.726 7.163 348.798 7.169 348.680 7.175 348.562 7.181 348.340 7.187 348.170 7.192 348.092 7.198 348.499 7.204 348.596 7.210 348.389 7.216 348.646 7.221 348.538 7.227 348.381 7.233 348.011 7.239 348.015 7.245 348.183 7.250 348.322 7.256 348.461 7.262 348.285 7.268 348.258 7.274 347.927 7.279 347.952 7.285 348.059 7.291 348.165 7.297 347.888 7.303 347.850 7.308 348.056 7.314 348.484 7.320 348.520 7.326 348.576 7.332 348.887 7.338 348.727 7.343 348.889 7.349 349.052 7.355 349.278 7.361 349.241 7.367 349.126 7.372 348.978 7.378 348.846 7.384 348.547 7.390 348.306 7.396 348.235 7.401 348.326 7.407 348.620 7.413 348.411 7.419 347.987 7.425 347.620 7.430 347.242 7.436 346.949 7.442 346.823 7.448 346.897 7.454 347.114 7.459 347.298 7.465 347.346 7.471 347.252 7.477 347.158 7.483 346.847 7.488 346.618 7.494 346.431 7.500 346.377 7.506 346.438 7.512 346.544 7.517 346.678 7.523 346.848 7.529 347.066 7.535 347.198 7.541 347.312 7.546 347.441 7.552 347.332 7.558 347.534 7.564 347.392 7.570 347.125 7.576 347.085 7.581 346.899 7.587 346.730 7.593 346.744 7.599 346.983 7.605 347.392 7.610 347.916 7.616 348.551 7.622 349.239 7.628 349.799 7.634 350.148 7.639 350.329 7.645 350.411 7.651 350.409 7.657 350.300 7.663 350.055 7.668 349.665 7.674 349.161 7.680 348.605 7.686 348.096 7.692 347.810 7.697 347.854 7.703 348.138 7.709 348.427 7.715 348.744 7.721 348.729 7.726 348.924 7.732 349.194 7.738 349.485 7.744 349.763 7.750 349.983 7.755 350.081 7.761 350.031 7.767 349.877 7.773 349.720 7.779 349.629 7.784 349.578 7.790 349.534 7.796 349.528 7.802 349.630 7.808 349.816 7.814 349.987 7.819 350.027 7.825 349.947 7.831 349.820 7.837 349.721 7.843 349.632 7.848 349.491 7.854 349.296 7.860 349.108 7.866 348.950 7.872 348.792 7.877 348.640 7.883 348.556 7.889 348.579 7.895 348.655 7.901 348.705 7.906 348.747 7.912 348.769 7.918 348.780 7.924 348.768 7.930 348.721 7.935 348.653 7.941 348.622 7.947 348.684 7.953 348.847 7.959 349.014 7.964 349.073 7.970 348.990 7.976 348.820 7.982 348.651 7.988 348.527 7.993 348.460 7.999 348.429 8.005 348.380 8.011 348.444 8.017 348.487 8.022 348.469 8.028 348.467 8.034 347.975 8.040 347.554 8.046 347.375 8.052 350.545 8.057 345.210 8.063 347.460 8.069 347.549 8.075 345.232 8.081 346.595 8.086 349.937 8.092 345.244 8.098 347.057 8.104 348.055 8.110 349.054 8.115 346.586 8.121 346.938 8.127 347.467 8.133 348.259 8.139 348.350 8.144 348.442 8.150 348.101 8.156 347.419 8.162 346.906 8.168 346.796 8.173 347.322 8.179 348.234 8.185 349.031 8.191 349.385 8.197 349.303 8.202 348.989 8.208 348.632 8.214 348.333 8.220 348.138 8.226 348.003 8.231 348.196 8.237 347.260 8.243 346.710 8.249 346.386 8.255 346.451 8.260 346.665 8.266 346.879 8.272 347.093 8.278 344.346 8.284 342.771 8.290 341.865 8.295 350.844 8.301 349.186 8.307 350.962 8.313 350.394 8.319 0.000 8.324 0.000 8.330 0.000 8.336 0.000 8.342 0.000 8.348 0.000 8.353 0.000 8.359 0.000 8.365 0.000 8.371 0.000 8.377 0.000 8.382 0.000 8.388 0.000 8.394 0.000 8.400 0.000 8.406 0.000 8.411 0.000 8.417 0.000 8.423 0.000 8.429 0.000 8.435 0.000 8.440 0.000 8.446 0.000 8.452 0.000 8.458 0.000 8.464 0.000 8.469 0.000 8.475 0.000 8.481 0.000 8.487 0.000 8.493 0.000 8.499 0.000 8.504 0.000 8.510 0.000 8.516 0.000 8.522 0.000 8.528 0.000 8.533 0.000 8.539 0.000 8.545 0.000 8.551 0.000 8.557 0.000 8.562 0.000 8.568 0.000 8.574 0.000 8.580 0.000 8.586 0.000 8.591 0.000 8.597 0.000 8.603 0.000 8.609 0.000 8.615 0.000 8.620 0.000 8.626 0.000 8.632 0.000 8.638 0.000 8.644 0.000 8.649 0.000 8.655 0.000 8.661 0.000 8.667 0.000 8.673 0.000 8.678 0.000 8.684 0.000 8.690 0.000 8.696 0.000 8.702 0.000 8.707 0.000 8.713 0.000 8.719 0.000 8.725 0.000 8.731 0.000 8.737 0.000 8.742 0.000 8.748 0.000 8.754 0.000 8.760 0.000 8.766 0.000 8.771 0.000 8.777 0.000 8.783 0.000 8.789 0.000 8.795 0.000 8.800 0.000 8.806 0.000 8.812 0.000 8.818 0.000 8.824 0.000 8.829 0.000 8.835 0.000 8.841 0.000 8.847 0.000 8.853 0.000 8.858 0.000 8.864 0.000 8.870 0.000 8.876 0.000 8.882 0.000 8.887 0.000 8.893 0.000 8.899 0.000 8.905 0.000 8.911 0.000 8.916 0.000 8.922 0.000 8.928 0.000 8.934 0.000 8.940 0.000 8.945 0.000 8.951 0.000 8.957 0.000 8.963 0.000 8.969 0.000 8.975 0.000 8.980 301.613 8.986 310.662 8.992 313.768 8.998 313.768 9.004 313.124 9.009 312.072 9.015 311.224 9.021 310.376 9.027 309.045 9.033 309.529 9.038 310.098 9.044 310.569 9.050 310.760 9.056 310.649 9.062 310.624 9.067 310.255 9.073 310.099 9.079 310.144 9.085 310.310 9.091 310.542 9.096 310.700 9.102 310.979 9.108 311.206 9.114 311.250 9.120 311.289 9.125 311.281 9.131 311.095 9.137 310.837 9.143 310.623 9.149 310.395 9.154 310.104 9.160 309.942 9.166 309.874 9.172 309.973 9.178 310.124 9.183 310.126 9.189 310.263 9.195 310.444 9.201 310.737 9.207 310.947 9.213 310.959 9.218 310.758 9.224 310.642 9.230 310.432 9.236 310.224 9.242 310.034 9.247 309.931 9.253 309.833 9.259 309.893 9.265 310.113 9.271 310.403 9.276 310.655 9.282 310.686 9.288 310.651 9.294 310.427 9.300 310.419 9.305 310.293 9.311 310.358 9.317 310.519 9.323 310.765 9.329 311.043 9.334 311.323 9.340 311.541 9.346 311.711 9.352 311.446 9.358 311.181 9.363 310.917 9.369 310.652 9.375 310.587 9.381 310.270 9.387 309.953 9.392 308.950 9.398 309.885 9.404 309.625 9.410 309.365 9.416 309.450 9.421 309.477 9.427 308.894 9.433 308.710 9.439 308.640 9.445 308.513 9.451 308.225 9.456 307.581 9.462 306.936 9.468 306.292 9.474 305.648 9.480 305.183 9.485 304.961 9.491 305.066 9.497 304.800 9.503 304.534 9.509 304.267 9.514 305.215 9.520 304.996 9.526 304.972 9.532 305.476 9.538 306.642 9.543 308.084 9.549 309.525 9.555 312.157 9.561 314.194 9.567 316.230 9.572 317.838 9.578 319.446 9.584 321.054 9.590 323.674 9.596 0.000 9.601 0.000 9.607 0.000 9.613 0.000 9.619 0.000 9.625 341.607 9.630 345.023 9.636 346.916 9.642 349.119 9.648 349.915 9.654 351.014 9.660 351.911 9.665 352.597 9.671 353.024 9.677 353.180 9.683 353.306 9.689 353.229 9.694 352.857 9.700 352.265 9.706 351.655 9.712 351.044 9.718 351.345 9.723 347.834 9.729 349.850 9.735 350.169 9.741 348.900 9.747 348.844 9.752 349.136 9.758 349.001 9.764 348.724 9.770 348.495 9.776 348.331 9.781 348.185 9.787 348.112 9.793 348.510 9.799 348.605 9.805 348.699 9.810 348.518 9.816 348.598 9.822 348.316 9.828 348.018 9.834 348.094 9.839 348.271 9.845 348.380 9.851 348.386 9.857 348.268 9.863 348.150 9.868 347.929 9.874 347.990 9.880 348.292 9.886 348.364 9.892 347.859 9.898 347.898 9.903 348.161 9.909 348.427 9.915 348.557 9.921 348.602 9.927 349.281 9.932 348.776 9.938 348.960 9.944 349.001 9.950 349.042 9.956 349.216 9.961 349.089 9.967 348.944 9.973 348.755 9.979 348.504 9.985 348.851 9.990 348.318 9.996 348.495 10.002 348.763 10.008 349.032 10.014 345.807 10.019 348.139 10.025 350.470 10.031 349.274 10.037 345.799 10.043 343.464 10.048 346.439 10.054 345.355 10.060 345.113 10.066 347.106 10.072 345.983 10.077 346.059 10.083 349.813 10.089 347.727 10.095 348.112 10.101 348.730 10.106 349.347 10.112 349.538 10.118 350.262 10.124 350.995 10.130 351.540 10.136 352.004 10.141 351.959 10.147 353.245 10.153 354.532 10.159 355.086 10.165 355.037 10.170 355.321 10.176 355.445 10.182 355.649 10.188 355.812 10.194 352.436 10.199 350.869 10.205 349.301 10.211 347.504 10.217 342.363 10.223 340.890 10.228 337.583 10.234 334.275 10.240 330.968 10.246 329.351 10.252 326.415 10.257 323.479 10.263 318.127 10.269 314.266 10.275 312.757 10.281 313.808 10.286 314.860 10.292 312.753 10.298 310.646 10.304 309.044 10.310 307.646 10.315 305.540 10.321 304.573 10.327 303.839 10.333 303.105 10.339 302.478 10.344 303.120 10.350 303.339 10.356 303.558 10.362 304.760 10.368 305.438 10.374 306.038 10.379 306.621 10.385 307.204 10.391 307.788 10.397 308.371 10.403 308.954 10.408 309.537 10.414 310.121 10.420 310.704 10.426 311.285 10.432 310.928 10.437 310.556 10.443 310.184 10.449 309.811 10.455 309.629 10.461 309.493 10.466 309.390 10.472 309.288 10.478 309.185 10.484 309.106 10.490 309.186 10.495 309.489 10.501 309.890 10.507 310.292 10.513 310.482 10.519 310.672 10.524 310.740 10.530 310.868 10.536 310.997 10.542 311.457 10.548 311.682 10.553 311.848 10.559 311.998 10.565 312.096 10.571 312.145 10.577 312.099 10.582 311.983 10.588 311.940 10.594 311.868 10.600 311.711 10.606 311.085 10.612 310.486 10.617 309.503 10.623 309.654 10.629 310.033 10.635 310.298 10.641 310.563 10.646 310.238 10.652 309.425 10.658 308.783 10.664 308.140 10.670 307.498 10.675 309.924 10.681 308.661 10.687 311.778 10.693 304.081 10.699 293.420 10.704 331.887 10.710 321.365 10.716 328.784 10.722 0.000 10.728 0.000 10.733 0.000 10.739 0.000 10.745 0.000 10.751 0.000 10.757 0.000 10.762 0.000 10.768 0.000 10.774 0.000 10.780 0.000 10.786 0.000 10.791 0.000 10.797 0.000 10.803 312.612 10.809 319.273 10.815 322.465 10.820 322.465 10.826 319.240 10.832 317.628 10.838 315.988 10.844 315.118 10.850 314.248 10.855 313.028 10.861 311.497 10.867 309.729 10.873 307.961 10.879 306.193 10.884 304.664 10.890 303.328 10.896 302.235 10.902 300.881 10.908 299.681 10.913 297.674 10.919 296.595 10.925 295.426 10.931 295.618 10.937 295.216 10.942 292.446 10.948 290.860 10.954 291.568 10.960 289.514 10.966 288.402 10.971 287.683 10.977 287.257 10.983 287.058 10.989 286.956 10.995 286.986 11.000 287.049 11.006 287.250 11.012 287.685 11.018 288.146 11.024 288.458 11.029 288.844 11.035 289.382 11.041 289.844 11.047 290.344 11.053 290.915 11.059 291.532 11.064 292.126 11.070 292.720 11.076 292.383 11.082 292.407 11.088 292.431 11.093 292.196 11.099 291.961 11.105 291.803 11.111 291.945 11.117 292.162 11.122 292.380 11.128 292.622 11.134 292.835 11.140 292.696 11.146 292.716 11.151 292.746 11.157 292.770 11.163 292.795 11.169 292.819 11.175 292.844 11.180 293.090 11.186 293.225 11.192 293.361 11.198 293.496 11.204 293.631 11.209 293.767 11.215 293.593 11.221 293.420 11.227 293.098 11.233 292.924 11.238 292.751 11.244 292.671 11.250 292.591 11.256 292.512 11.262 292.432 11.267 292.604 11.273 292.729 11.279 292.853 11.285 292.977 11.291 293.102 11.297 293.226 11.302 293.372 11.308 293.517 11.314 293.519 11.320 293.308 11.326 293.097 11.331 292.863 11.337 292.730 11.343 292.648 11.349 292.719 11.355 292.978 11.360 293.340 11.366 293.666 11.372 293.822 11.378 294.007 11.384 294.178 11.389 294.179 11.395 294.098 11.401 293.877 11.407 293.657 11.413 293.395 11.418 293.153 11.424 293.109 11.430 293.065 11.436 293.061 11.442 293.123 11.447 293.186 11.453 293.248 11.459 293.515 11.465 293.680 11.471 293.896 11.476 294.112 11.482 294.329 11.488 294.545 11.494 294.761 11.500 294.977 11.505 295.072 11.511 294.905 11.517 294.728 11.523 294.546 11.529 294.367 11.535 294.766 11.540 295.107 11.546 294.756 11.552 295.901 11.558 296.433 11.564 296.385 11.569 297.517 11.575 297.795 11.581 298.627 11.587 299.459 11.593 300.087 11.598 300.235 11.604 300.215 11.610 300.114 11.616 299.623 11.622 299.417 11.627 297.926 11.633 297.077 11.639 295.907 11.645 294.738 11.651 293.568 11.656 293.467 11.662 292.832 11.668 289.539 11.674 290.451 11.680 291.363 11.685 289.352 11.691 290.285 11.697 284.094 11.703 281.090 11.709 277.725 11.714 273.755 11.720 269.894 11.726 266.033 11.732 262.172 11.738 263.478 11.743 261.214 11.749 262.181 11.755 259.657 11.761 258.272 11.767 258.882 11.773 256.342 11.778 257.170 11.784 255.918 11.790 255.352 11.796 255.036 11.802 256.068 11.807 256.131 11.813 256.337 11.819 256.691 11.825 257.159 11.831 257.769 11.836 258.594 11.842 259.312 11.848 260.084 11.854 260.683 11.860 261.022 11.865 261.098 11.871 260.982 11.877 260.869 11.883 260.932 11.889 260.928 11.894 260.924 11.900 260.920 11.906 260.915 11.912 260.911 11.918 260.947 11.923 261.120 11.929 261.451 11.935 261.882 11.941 262.376 11.947 262.839 11.952 262.713 11.958 262.650 11.964 262.555 11.970 262.461 11.976 262.366 11.981 262.271 11.987 262.083 11.993 261.888 11.999 261.688 12.005 261.606 12.011 261.512 12.016 261.477 12.022 261.415 12.028 261.776 12.034 261.578 12.040 261.188 12.045 261.881 12.051 261.582 12.057 261.553 12.063 260.789 12.069 260.413 12.074 260.287 12.080 260.397 12.086 260.468 12.092 260.435 12.098 260.151 12.103 259.577 12.109 258.675 12.115 257.774 12.121 256.872 12.127 255.971 12.132 256.821 12.138 255.233 12.144 253.646 12.150 252.058 12.156 252.975 12.161 253.892 12.167 256.613 12.173 259.647 12.179 262.682 12.185 264.840 12.190 266.415 12.196 267.989 12.202 270.783 12.208 274.551 12.214 278.318 12.220 282.235 12.225 287.114 12.231 288.597 12.237 293.670 12.243 293.978 12.249 293.702 12.254 293.953 12.260 295.409 12.266 296.263 12.272 296.163 12.278 295.967 12.283 295.819 12.289 295.671 12.295 295.930 12.301 296.249 12.307 296.568 12.312 296.074 12.318 296.275 12.324 296.475 12.330 296.676 12.336 296.473 12.341 294.443 12.347 294.910 12.353 293.636 12.359 294.260 12.365 294.268 12.370 294.534 12.376 294.418 12.382 293.702 12.388 293.564 12.394 293.287 12.399 293.076 12.405 293.149 12.411 292.681 12.417 292.940 12.423 293.200 12.428 293.269 12.434 293.338 12.440 293.066 12.446 292.903 12.452 292.740 12.458 292.615 12.463 292.720 12.469 292.849 12.475 292.978 12.481 292.832 12.487 292.881 12.492 292.787 12.498 292.611 12.504 292.622 12.510 292.549 12.516 292.590 12.521 292.740 12.527 292.836 12.533 293.125 12.539 293.317 12.545 293.509 12.550 293.398 12.556 293.407 12.562 293.508 12.568 293.650 12.574 293.791 12.579 293.812 12.585 293.751 12.591 293.382 12.597 293.257 12.603 293.132 12.608 293.012 12.614 292.979 12.620 292.902 12.626 293.215 12.632 292.654 12.637 292.404 12.643 291.998 12.649 291.937 12.655 291.746 12.661 291.719 12.666 291.762 12.672 291.898 12.678 292.056 12.684 292.181 12.690 292.033 12.696 291.846 12.701 291.552 12.707 291.398 12.713 291.378 12.719 291.292 12.725 291.556 12.730 291.652 12.736 291.833 12.742 291.971 12.748 291.889 12.754 291.999 12.759 292.194 12.765 292.193 12.771 292.135 12.777 292.019 12.783 292.014 12.788 291.890 12.794 291.739 12.800 291.588 12.806 291.645 12.812 291.703 12.817 291.827 12.823 292.227 12.829 292.730 12.835 293.312 12.841 293.894 12.846 294.284 12.852 294.513 12.858 294.700 12.864 294.728 12.870 294.643 12.875 294.546 12.881 294.323 12.887 293.935 12.893 293.548 12.899 293.019 12.904 292.577 12.910 292.405 12.916 292.553 12.922 292.850 12.928 293.147 12.934 293.443 12.939 293.340 12.945 293.560 12.951 293.736 12.957 293.912 12.963 294.230 12.968 294.435 12.974 294.460 12.980 294.382 12.986 294.219 12.992 294.098 12.997 293.977 13.003 293.944 13.009 293.911 13.015 293.932 13.021 294.047 13.026 294.262 13.032 294.354 13.038 294.426 13.044 294.306 13.050 294.185 13.055 294.065 13.061 293.945 13.067 293.824 13.073 293.704 13.079 293.566 13.084 293.395 13.090 293.223 13.096 293.052 13.102 293.120 13.108 293.189 13.113 293.257 13.119 293.326 13.125 293.394 13.131 293.267 13.137 293.264 13.142 293.262 13.148 293.259 13.154 293.144 13.160 293.084 13.166 293.165 13.172 293.391 13.177 293.544 13.183 293.616 13.189 293.533 13.195 293.283 13.201 293.032 13.206 293.022 13.212 292.912 13.218 292.858 13.224 292.874 13.230 292.881 13.235 293.091 13.241 293.300 13.247 293.510 13.253 293.720 13.259 293.722 13.264 293.594 13.270 293.402 13.276 293.210 13.282 292.939 13.288 292.695 13.293 292.687 13.299 292.679 13.305 292.852 13.311 293.065 13.317 293.258 13.322 293.464 13.328 293.657 13.334 293.857 13.340 294.084 13.346 294.282 13.351 294.428 13.357 294.380 13.363 294.266 13.369 293.692 13.375 293.117 13.380 292.543 13.386 292.496 13.392 292.449 13.398 292.570 13.404 293.046 13.410 292.992 13.415 292.818 13.421 291.959 13.427 291.243 13.433 291.341 13.439 291.870 13.444 292.183 13.450 291.953 13.456 291.422 13.462 291.275 13.468 291.788 13.473 292.458 13.479 292.716 13.485 292.425 13.491 292.040 13.497 291.920 13.502 292.215 13.508 292.510 13.514 292.806 13.520 293.101 13.526 292.992 13.531 292.436 13.537 291.381 13.543 290.815 13.549 290.924 13.555 291.408 13.560 291.874 13.566 291.958 13.572 292.492 13.578 292.801 13.584 292.998 13.589 292.681 13.595 292.315 13.601 292.368 13.607 292.732 13.613 293.096 13.619 293.124 13.624 291.686 13.630 291.516 13.636 291.854 13.642 292.191 13.648 291.180 13.653 291.685 13.659 288.768 13.665 290.367 13.671 290.283 13.677 286.955 13.682 296.659 13.688 297.672 13.694 300.000 13.700 302.328 13.706 313.795 13.711 312.377 13.717 0.000 13.723 0.000 13.729 0.000 13.735 0.000 13.740 0.000 13.746 0.000 13.752 0.000 13.758 0.000 13.764 0.000 13.769 0.000 13.775 0.000 13.781 0.000 13.787 0.000 13.793 0.000 13.798 0.000 13.804 0.000 13.810 0.000 13.816 0.000 13.822 0.000 13.827 0.000 13.833 0.000 13.839 0.000 13.845 0.000 13.851 0.000 13.857 0.000 13.862 0.000 13.868 0.000 13.874 0.000 13.880 0.000 13.886 0.000 13.891 0.000 13.897 0.000 13.903 0.000 13.909 0.000 13.915 0.000 13.920 0.000 13.926 0.000 13.932 0.000 13.938 0.000 13.944 0.000 13.949 0.000 13.955 0.000 13.961 0.000 13.967 0.000 13.973 0.000 13.978 0.000 13.984 0.000 13.990 0.000 13.996 0.000 14.002 0.000 14.007 0.000 14.013 0.000 14.019 0.000 14.025 0.000 14.031 0.000 14.036 0.000 14.042 0.000 14.048 0.000 14.054 0.000 14.060 0.000 14.065 0.000 14.071 0.000 14.077 0.000 14.083 0.000 14.089 0.000 14.095 0.000 14.100 0.000 14.106 0.000 14.112 0.000 14.118 0.000 14.124 0.000 14.129 0.000 14.135 228.837 14.141 231.126 14.147 224.192 14.153 221.950 14.158 217.511 14.164 216.312 14.170 215.628 14.176 214.944 14.182 217.430 14.187 222.628 14.193 224.205 14.199 225.782 14.205 220.539 14.211 220.979 14.216 220.899 14.222 220.236 14.228 219.864 14.234 219.320 14.240 219.165 14.245 218.816 14.251 218.563 14.257 219.009 14.263 219.319 14.269 219.577 14.274 219.538 14.280 219.920 14.286 219.703 14.292 218.861 14.298 219.358 14.303 219.501 14.309 219.409 14.315 219.421 14.321 219.442 14.327 219.299 14.333 219.108 14.338 218.925 14.344 218.663 14.350 218.343 14.356 217.982 14.362 217.813 14.367 217.804 14.373 217.914 14.379 218.122 14.385 218.392 14.391 218.820 14.396 219.346 14.402 219.811 14.408 220.192 14.414 220.489 14.420 220.828 14.425 220.642 14.431 220.547 14.437 220.421 14.443 220.280 14.449 220.082 14.454 219.888 14.460 219.661 14.466 219.575 14.472 219.549 14.478 220.337 14.483 219.477 14.489 219.396 14.495 219.341 14.501 219.286 14.507 219.231 14.512 219.139 14.518 218.866 14.524 218.615 14.530 218.684 14.536 218.718 14.541 218.752 14.547 218.786 14.553 218.820 14.559 218.853 14.565 218.881 14.571 218.864 14.576 218.847 14.582 218.829 14.588 218.812 14.594 219.300 14.600 219.477 14.605 219.653 14.611 219.803 14.617 219.751 14.623 219.360 14.629 219.138 14.634 218.832 14.640 216.383 14.646 215.005 14.652 213.627 14.658 212.249 14.663 210.872 14.669 201.114 14.675 207.279 14.681 202.014 14.687 215.523 14.692 0.000 14.698 0.000 14.704 0.000 14.710 0.000 14.716 0.000 14.721 0.000 14.727 0.000 14.733 0.000 14.739 0.000 14.745 0.000 14.750 0.000 14.756 0.000 14.762 0.000 14.768 0.000 14.774 0.000 14.780 0.000 14.785 0.000 14.791 0.000 14.797 244.012 14.803 246.974 14.809 246.974 14.814 244.905 14.820 244.905 14.826 250.436 14.832 253.202 14.838 254.777 14.843 256.840 14.849 258.908 14.855 260.974 14.861 262.055 14.867 263.137 14.872 263.725 14.878 264.312 14.884 264.677 14.890 264.175 14.896 264.367 14.901 264.559 14.907 264.750 14.913 264.942 14.919 263.709 14.925 263.571 14.930 263.528 14.936 263.515 14.942 263.502 14.948 263.494 14.954 263.298 14.959 263.366 14.965 262.873 14.971 262.529 14.977 262.139 14.983 261.749 14.988 261.358 14.994 261.352 15.000 261.153 15.006 261.185 15.012 261.256 15.018 261.468 15.023 261.726 15.029 262.025 15.035 262.325 15.041 262.451 15.047 262.482 15.052 262.376 15.058 262.180 15.064 261.935 15.070 261.691 15.076 261.447 15.081 261.382 15.087 261.278 15.093 261.173 15.099 261.069 15.105 260.964 15.110 260.860 15.116 260.755 15.122 260.651 15.128 260.546 15.134 260.688 15.139 260.634 15.145 260.581 15.151 260.523 15.157 260.466 15.163 260.409 15.168 260.352 15.174 260.336 15.180 260.418 15.186 260.590 15.192 260.762 15.197 260.934 15.203 261.105 15.209 261.277 15.215 261.239 15.221 261.138 15.226 260.964 15.232 260.888 15.238 260.949 15.244 260.935 15.250 260.925 15.256 260.913 15.261 260.875 15.267 260.740 15.273 260.606 15.279 260.471 15.285 260.534 15.290 260.503 15.296 260.544 15.302 260.634 15.308 260.766 15.314 260.825 15.319 260.828 15.325 260.738 15.331 260.645 15.337 260.459 15.343 260.274 15.348 260.221 15.354 260.354 15.360 260.615 15.366 260.876 15.372 261.228 15.377 261.439 15.383 261.649 15.389 261.860 15.395 262.070 15.401 262.280 15.406 262.491 15.412 262.576 15.418 262.662 15.424 262.632 15.430 262.431 15.435 262.230 15.441 262.029 15.447 261.828 15.453 261.627 15.459 262.335 15.464 262.647 15.470 262.960 15.476 263.729 15.482 264.490 15.488 265.274 15.494 266.046 15.499 265.990 15.505 265.935 15.511 265.782 15.517 265.893 15.523 266.285 15.528 266.068 15.534 266.081 15.540 266.093 15.546 266.106 15.552 263.458 15.557 262.392 15.563 263.141 15.569 263.011 15.575 262.864 15.581 262.718 15.586 259.945 15.592 261.070 15.598 261.227 15.604 254.012 15.610 250.545 15.615 232.944 15.621 217.962 15.627 213.770 15.633 0.000 15.639 0.000 15.644 0.000 15.650 0.000 15.656 0.000 15.662 236.290 15.668 233.891 15.673 231.552 15.679 231.552 15.685 229.237 15.691 230.360 15.697 230.117 15.702 229.874 15.708 229.631 15.714 229.388 15.720 231.426 15.726 230.276 15.732 230.561 15.737 231.130 15.743 231.698 15.749 232.022 15.755 232.237 15.761 232.360 15.766 232.353 15.772 232.320 15.778 232.391 15.784 232.594 15.790 232.673 15.795 232.832 15.801 232.991 15.807 233.694 15.813 233.866 15.819 233.805 15.824 233.740 15.830 233.545 15.836 233.350 15.842 233.156 15.848 232.545 15.853 232.182 15.859 231.696 15.865 231.407 15.871 231.199 15.877 231.245 15.882 231.503 15.888 232.034 15.894 232.565 15.900 233.096 15.906 231.291 15.911 229.893 15.917 228.495 15.923 229.367 15.929 229.263 15.935 229.064 15.940 229.872 15.946 230.680 15.952 231.488 15.958 231.538 15.964 231.588 15.970 231.276 15.975 231.646 15.981 231.517 15.987 231.484 15.993 232.211 15.999 232.389 16.004 232.086 16.010 231.802 16.016 231.538 16.022 231.865 16.028 231.748 16.033 231.631 16.039 231.978 16.045 231.805 16.051 232.178 16.057 233.030 16.062 233.099 16.068 233.559 16.074 231.690 16.080 232.106 16.086 231.748 16.091 231.391 16.097 231.033 16.103 232.983 16.109 229.601 16.115 226.424 16.120 220.914 16.126 220.901 16.132 222.503 16.138 223.761 16.144 225.019 16.149 224.015 16.155 221.998 16.161 220.487 16.167 218.976 16.173 216.464 16.179 214.951 16.184 214.215 16.190 214.138 16.196 214.315 16.202 214.492 16.208 214.668 16.213 214.089 16.219 214.383 16.225 214.678 16.231 214.973 16.237 215.295 16.242 215.963 16.248 216.630 16.254 217.298 16.260 217.966 16.266 217.981 16.271 218.444 16.277 218.682 16.283 218.890 16.289 219.051 16.295 219.183 16.300 219.346 16.306 219.584 16.312 219.822 16.318 219.985 16.324 219.868 16.329 219.624 16.335 219.237 16.341 218.921 16.347 218.997 16.353 218.881 16.358 218.764 16.364 218.926 16.370 219.033 16.376 219.239 16.382 219.395 16.387 219.261 16.393 219.295 16.399 219.315 16.405 219.288 16.411 219.318 16.417 219.347 16.422 219.414 16.428 219.480 16.434 219.546 16.440 219.628 16.446 219.953 16.451 219.875 16.457 219.955 16.463 219.939 16.469 219.829 16.475 219.668 16.480 219.452 16.486 219.386 16.492 219.317 16.498 219.188 16.504 219.146 16.509 219.175 16.515 219.204 16.521 219.277 16.527 219.416 16.533 219.522 16.538 219.628 16.544 219.734 16.550 219.840 16.556 219.946 16.562 219.811 16.567 219.704 16.573 219.606 16.579 219.417 16.585 219.321 16.591 219.279 16.596 219.310 16.602 219.452 16.608 219.781 16.614 219.873 16.620 220.083 16.625 220.234 16.631 220.385 16.637 220.451 16.643 220.415 16.649 220.197 16.655 220.017 16.660 219.813 16.666 219.622 16.672 219.607 16.678 219.592 16.684 219.618 16.689 219.607 16.695 219.596 16.701 219.585 16.707 219.574 16.713 220.236 16.718 220.464 16.724 220.651 16.730 220.303 16.736 220.456 16.742 220.609 16.747 220.761 16.753 220.556 16.759 220.633 16.765 220.496 16.771 220.068 16.776 220.164 16.782 220.166 16.788 220.231 16.794 220.296 16.800 220.323 16.805 220.345 16.811 220.289 16.817 220.077 16.823 219.482 16.829 219.607 16.834 218.957 16.840 218.989 16.846 219.184 16.852 219.727 16.858 219.175 16.863 218.402 16.869 218.015 16.875 218.281 16.881 218.875 16.887 219.470 16.893 220.064 16.898 220.659 16.904 221.253 16.910 221.215 16.916 221.821 16.922 221.469 16.927 223.713 16.933 222.472 16.939 219.360 16.945 216.247 16.951 211.003 16.956 198.552 16.962 0.000 16.968 0.000 16.974 0.000 16.980 0.000 16.985 0.000 16.991 0.000 16.997 0.000 17.003 0.000 17.009 0.000 17.014 0.000 17.020 0.000 17.026 0.000 17.032 0.000 17.038 238.881 17.043 236.751 17.049 236.751 17.055 236.751 17.061 234.495 17.067 234.291 17.072 234.088 17.078 233.801 17.084 233.398 17.090 232.190 17.096 230.981 17.101 230.542 17.107 230.822 17.113 231.101 17.119 231.419 17.125 231.737 17.131 232.054 17.136 232.372 17.142 231.424 17.148 231.742 17.154 232.495 17.160 232.943 17.165 233.064 17.171 233.185 17.177 233.123 17.183 233.256 17.189 233.390 17.194 233.217 17.200 233.062 17.206 232.874 17.212 232.603 17.218 232.612 17.223 232.502 17.229 232.392 17.235 232.283 17.241 232.242 17.247 232.201 17.252 232.318 17.258 232.435 17.264 232.488 17.270 232.542 17.276 232.595 17.281 232.649 17.287 232.625 17.293 232.358 17.299 231.973 17.305 231.823 17.310 232.177 17.316 232.413 17.322 232.164 17.328 231.714 17.334 231.263 17.340 230.994 17.345 230.230 17.351 229.504 17.357 229.007 17.363 229.357 17.369 229.708 17.374 230.058 17.380 232.713 17.386 229.531 17.392 228.337 17.398 221.838 17.403 217.991 17.409 221.729 17.415 0.000 17.421 0.000 17.427 0.000 17.432 0.000 17.438 0.000 17.444 0.000 17.450 0.000 17.456 0.000 17.461 0.000 17.467 273.483 17.473 268.013 17.479 265.333 17.485 265.333 17.490 265.333 17.496 267.051 17.502 266.486 17.508 266.310 17.514 266.133 17.519 265.957 17.525 265.780 17.531 265.604 17.537 265.428 17.543 265.252 17.548 265.075 17.554 264.899 17.560 264.723 17.566 263.349 17.572 262.828 17.578 262.335 17.583 261.939 17.589 261.830 17.595 261.578 17.601 261.397 17.607 261.235 17.612 261.332 17.618 261.322 17.624 261.102 17.630 261.070 17.636 260.943 17.641 261.100 17.647 261.044 17.653 261.031 17.659 261.235 17.665 261.116 17.670 261.126 17.676 261.136 17.682 260.941 17.688 260.745 17.694 260.664 17.699 260.817 17.705 260.970 17.711 260.966 17.717 260.923 17.723 260.879 17.728 260.836 17.734 260.685 17.740 260.959 17.746 260.668 17.752 260.760 17.757 260.792 17.763 260.943 17.769 261.127 17.775 261.310 17.781 261.494 17.786 261.385 17.792 261.430 17.798 261.475 17.804 261.520 17.810 261.624 17.816 261.728 17.821 261.719 17.827 261.576 17.833 261.374 17.839 261.171 17.845 260.969 17.850 261.064 17.856 261.068 17.862 260.964 17.868 260.860 17.874 260.696 17.879 260.334 17.885 259.973 17.891 259.912 17.897 259.870 17.903 259.934 17.908 260.061 17.914 260.242 17.920 260.396 17.926 260.297 17.932 260.166 17.937 259.833 17.943 259.602 17.949 259.590 17.955 259.648 17.961 259.751 17.966 259.855 17.972 259.959 17.978 260.062 17.984 260.166 17.990 260.269 17.995 260.373 18.001 260.316 18.007 260.260 18.013 260.203 18.019 260.108 18.024 260.013 18.030 259.918 18.036 259.811 18.042 259.740 18.048 259.765 18.054 259.957 18.059 260.325 18.065 260.779 18.071 261.294 18.077 261.839 18.083 262.195 18.088 262.415 18.094 262.562 18.100 262.559 18.106 262.556 18.112 262.424 18.117 262.205 18.123 261.817 18.129 261.429 18.135 260.938 18.141 260.652 18.146 260.464 18.152 260.616 18.158 260.879 18.164 261.140 18.170 261.403 18.175 261.386 18.181 261.507 18.187 261.680 18.193 261.909 18.199 262.109 18.204 262.310 18.210 262.309 18.216 262.238 18.222 262.098 18.228 261.972 18.233 261.915 18.239 261.894 18.245 261.874 18.251 261.868 18.257 261.959 18.262 262.109 18.268 262.229 18.274 262.216 18.280 262.104 18.286 261.993 18.292 261.964 18.297 261.936 18.303 261.907 18.309 261.660 18.315 261.522 18.321 261.385 18.326 261.235 18.332 261.156 18.338 261.106 18.344 261.148 18.350 261.254 18.355 261.230 18.361 261.304 18.367 261.266 18.373 261.266 18.379 261.295 18.384 261.269 18.390 261.242 18.396 261.189 18.402 261.218 18.408 261.369 18.413 261.458 18.419 261.477 18.425 261.343 18.431 261.209 18.437 261.074 18.442 260.940 18.448 260.920 18.454 260.899 18.460 260.921 18.466 260.983 18.471 261.106 18.477 261.263 18.483 261.457 18.489 261.651 18.495 261.536 18.500 261.530 18.506 261.373 18.512 261.216 18.518 260.950 18.524 260.784 18.530 260.617 18.535 260.715 18.541 260.817 18.547 260.965 18.553 261.091 18.559 261.317 18.564 261.492 18.570 261.735 18.576 261.979 18.582 262.096 18.588 262.260 18.593 262.149 18.599 261.988 18.605 261.609 18.611 261.230 18.617 260.799 18.622 260.394 18.628 260.415 18.634 260.523 18.640 260.632 18.646 260.741 18.651 260.559 18.657 260.580 18.663 260.448 18.669 260.706 18.675 260.965 18.680 261.223 18.686 261.116 18.692 261.106 18.698 261.114 18.704 261.205 18.709 261.343 18.715 261.457 18.721 261.477 18.727 261.389 18.733 261.271 18.739 261.149 18.744 261.028 18.750 261.010 18.756 260.993 18.762 260.975 18.768 260.958 18.773 261.109 18.779 261.259 18.785 261.461 18.791 261.643 18.797 261.520 18.802 261.396 18.808 261.273 18.814 261.150 18.820 260.914 18.826 260.677 18.831 260.689 18.837 260.790 18.843 260.892 18.849 261.050 18.855 261.210 18.860 261.380 18.866 261.636 18.872 261.893 18.878 262.167 18.884 262.356 18.889 262.498 18.895 262.466 18.901 262.294 18.907 261.977 18.913 261.601 18.918 261.174 18.924 261.045 18.930 261.044 18.936 261.195 18.942 261.347 18.947 260.989 18.953 260.752 18.959 260.573 18.965 260.619 18.971 260.694 18.977 260.770 18.982 260.845 18.988 260.941 18.994 260.921 19.000 260.952 19.006 261.019 19.011 261.068 19.017 260.966 19.023 261.013 19.029 261.059 19.035 261.186 19.040 261.312 19.046 261.439 19.052 261.397 19.058 261.228 19.064 261.068 19.069 260.904 19.075 260.890 19.081 260.876 19.087 260.862 19.093 260.952 19.098 261.046 19.104 261.201 19.110 261.391 19.116 261.542 19.122 261.443 19.127 261.343 19.133 261.219 19.139 261.020 19.145 260.734 19.151 260.448 19.156 260.406 19.162 260.365 19.168 260.362 19.174 260.474 19.180 260.623 19.185 260.734 19.191 260.757 19.197 260.887 19.203 260.964 19.209 260.903 19.215 260.916 19.220 260.974 19.226 261.058 19.232 261.200 19.238 261.377 19.244 261.537 19.249 261.655 19.255 261.415 19.261 261.175 19.267 261.083 19.273 260.852 19.278 260.620 19.284 260.684 19.290 260.705 19.296 260.847 19.302 261.029 19.307 261.273 19.313 261.517 19.319 261.732 19.325 262.014 19.331 262.319 19.336 262.613 19.342 262.808 19.348 262.712 19.354 262.493 19.360 262.068 19.365 261.591 19.371 261.015 19.377 260.719 19.383 260.430 19.389 260.371 19.394 260.311 19.400 260.251 19.406 260.192 19.412 259.901 19.418 259.793 19.423 259.951 19.429 260.109 19.435 260.268 19.441 260.426 19.447 260.400 19.453 260.338 19.458 260.398 19.464 260.513 19.470 260.586 19.476 260.680 19.482 260.691 19.487 260.827 19.493 261.010 19.499 261.327 19.505 261.716 19.511 261.955 19.516 261.903 19.522 261.980 19.528 261.950 19.534 261.954 19.540 262.005 19.545 262.055 19.551 262.189 19.557 262.282 19.563 262.395 19.569 262.514 19.574 262.645 19.580 262.745 19.586 262.505 19.592 262.356 19.598 262.034 19.603 261.669 19.609 261.264 19.615 260.757 19.621 260.678 19.627 260.385 19.632 260.465 19.638 260.408 19.644 260.445 19.650 260.415 19.656 260.385 19.661 260.416 19.667 260.454 19.673 260.656 19.679 260.730 19.685 260.663 19.691 260.568 19.696 260.327 19.702 260.087 19.708 259.847 19.714 259.951 19.720 260.236 19.725 260.634 19.731 260.758 19.737 260.757 19.743 260.721 19.749 260.627 19.754 260.839 19.760 261.145 19.766 261.450 19.772 261.755 19.778 262.060 19.783 262.238 19.789 262.263 19.795 262.211 19.801 262.086 19.807 261.909 19.812 261.618 19.818 261.280 19.824 260.941 19.830 260.603 19.836 260.611 19.841 260.560 19.847 260.331 19.853 260.034 19.859 259.537 19.865 259.263 19.870 258.878 19.876 258.795 19.882 258.561 19.888 258.568 19.894 258.511 19.900 258.656 19.905 258.778 19.911 259.075 19.917 259.285 19.923 259.746 19.929 259.726 19.934 259.929 19.940 260.133 19.946 260.393 19.952 260.625 19.958 261.068 19.963 261.511 19.969 262.044 19.975 262.597 19.981 263.166 19.987 263.552 19.992 263.874 19.998 264.196 20.004 264.396 20.010 264.423 20.016 264.451 20.021 264.192 20.027 263.623 20.033 262.981 20.039 262.218 20.045 261.416 20.050 260.561 20.056 260.147 20.062 259.748 20.068 259.375 20.074 259.051 20.079 258.727 20.085 258.377 20.091 258.189 20.097 258.106 20.103 258.365 20.108 258.527 20.114 258.738 20.120 258.782 20.126 258.980 20.132 259.100 20.138 259.396 20.143 259.604 20.149 259.917 20.155 260.372 20.161 260.917 20.167 261.417 20.172 262.024 20.178 262.448 20.184 262.739 20.190 263.005 20.196 263.271 20.201 263.536 20.207 263.554 20.213 263.571 20.219 263.669 20.225 263.670 20.230 263.563 20.236 263.627 20.242 263.267 20.248 262.907 20.254 262.584 20.259 261.908 20.265 261.129 20.271 260.351 20.277 259.572 20.283 259.194 20.288 258.816 20.294 258.480 20.300 258.397 20.306 258.314 20.312 258.222 20.317 258.311 20.323 258.535 20.329 258.884 20.335 259.234 20.341 259.601 20.346 259.959 20.352 260.169 20.358 260.749 20.364 261.329 20.370 261.909 20.376 262.347 20.381 262.730 20.387 263.141 20.393 263.396 20.399 263.650 20.405 263.836 20.410 264.056 20.416 264.276 20.422 264.225 20.428 264.363 20.434 264.105 20.439 263.738 20.445 263.297 20.451 262.644 20.457 261.979 20.463 261.257 20.468 260.612 20.474 260.201 20.480 259.899 20.486 259.542 20.492 259.170 20.497 259.009 20.503 258.924 20.509 258.950 20.515 259.106 20.521 259.386 20.526 259.604 20.532 259.964 20.538 260.030 20.544 260.096 20.550 260.162 20.555 260.436 20.561 260.711 20.567 261.245 20.573 261.838 20.579 262.432 20.584 262.979 20.590 263.554 20.596 263.912 20.602 263.992 20.608 263.831 20.614 263.671 20.619 263.246 20.625 262.953 20.631 262.646 20.637 262.330 20.643 261.858 20.648 261.464 20.654 261.157 20.660 260.806 20.666 260.414 20.672 259.760 20.677 259.437 20.683 258.949 20.689 258.760 20.695 258.364 20.701 258.071 20.706 257.779 20.712 257.872 20.718 257.904 20.724 257.970 20.730 258.036 20.735 258.103 20.741 258.093 20.747 257.978 20.753 257.916 20.759 258.866 20.764 259.583 20.770 259.846 20.776 259.863 20.782 259.879 20.788 260.240 20.793 261.547 20.799 262.599 20.805 262.986 20.811 262.789 20.817 262.475 20.822 262.536 20.828 262.863 20.834 263.056 20.840 263.190 20.846 262.985 20.852 262.584 20.857 261.982 20.863 260.896 20.869 260.040 20.875 259.616 20.881 259.542 20.886 259.678 20.892 259.632 20.898 259.565 20.904 259.272 20.910 259.004 20.915 258.550 20.921 258.312 20.927 258.070 20.933 258.044 20.939 258.017 20.944 257.991 20.950 256.957 20.956 256.894 20.962 257.013 20.968 257.155 20.973 257.297 20.979 255.881 20.985 256.688 20.991 257.495 20.997 255.719 21.002 266.805 21.008 265.900 21.014 265.748 21.020 267.872 21.026 0.000 21.031 0.000 21.037 0.000 21.043 0.000 21.049 0.000 21.055 0.000 21.060 0.000 21.066 0.000 21.072 0.000 21.078 0.000 21.084 0.000 21.090 0.000 21.095 0.000 21.101 0.000 21.107 0.000 21.113 0.000 21.119 0.000 21.124 0.000 21.130 0.000 21.136 0.000 21.142 0.000 21.148 0.000 21.153 0.000 21.159 0.000 21.165 0.000 21.171 0.000 21.177 0.000 21.182 0.000 21.188 0.000 21.194 0.000 21.200 0.000 21.206 0.000 21.211 0.000 21.217 0.000 21.223 0.000 21.229 0.000 21.235 0.000 21.240 0.000 21.246 0.000 21.252 0.000 21.258 0.000 21.264 0.000 21.269 0.000 21.275 0.000 21.281 0.000 21.287 0.000 21.293 0.000 21.299 0.000 21.304 0.000 21.310 0.000 21.316 0.000 21.322 0.000 21.328 0.000 21.333 0.000 21.339 0.000 21.345 0.000 21.351 0.000 21.357 0.000 21.362 0.000 21.368 0.000 21.374 0.000 21.380 0.000 21.386 0.000 21.391 0.000 21.397 0.000 21.403 0.000 21.409 0.000 21.415 0.000 21.420 0.000 21.426 0.000 21.432 0.000 21.438 0.000 21.444 0.000 21.449 0.000 21.455 0.000 21.461 0.000 21.467 0.000 21.473 0.000 21.478 0.000 21.484 0.000 21.490 0.000 21.496 0.000 21.502 0.000 21.507 0.000 21.513 0.000 21.519 0.000 21.525 0.000 21.531 0.000 21.537 0.000 21.542 0.000 21.548 0.000 21.554 0.000 21.560 0.000 21.566 0.000 21.571 0.000 21.577 0.000 21.583 0.000 21.589 0.000 21.595 0.000 21.600 0.000 21.606 0.000 21.612 0.000 21.618 0.000 21.624 0.000 21.629 0.000 21.635 0.000 21.641 0.000 21.647 0.000 21.653 0.000 21.658 0.000 21.664 0.000 21.670 0.000 21.676 0.000 21.682 0.000 21.687 0.000 21.693 0.000 21.699 0.000 21.705 0.000 21.711 0.000 21.716 0.000 21.722 0.000 21.728 0.000 21.734 0.000 21.740 0.000 21.745 0.000 21.751 0.000 21.757 0.000 21.763 0.000 21.769 0.000 21.775 0.000 21.780 0.000 21.786 0.000 21.792 0.000 21.798 0.000 21.804 0.000 21.809 0.000 21.815 0.000 21.821 0.000 21.827 0.000 21.833 0.000 21.838 0.000 21.844 0.000 21.850 0.000 21.856 0.000 21.862 0.000 21.867 0.000 21.873 0.000 21.879 0.000 21.885 0.000 21.891 0.000 21.896 0.000 21.902 0.000 21.908 0.000 21.914 0.000 21.920 0.000 21.925 0.000 21.931 0.000 21.937 0.000 21.943 0.000 21.949 0.000 21.954 0.000 21.960 0.000 21.966 0.000 21.972 0.000 21.978 0.000 21.983 0.000 21.989 0.000 21.995 0.000 mir_eval-0.8.2/tests/data/melody/ref02.txt000066400000000000000000001435051475740344600203700ustar00rootroot000000000000000.000 0.000 0.006 0.000 0.012 0.000 0.017 0.000 0.023 0.000 0.029 303.097 0.035 303.097 0.041 303.097 0.046 301.422 0.052 299.747 0.058 298.794 0.064 298.409 0.070 298.024 0.075 297.639 0.081 297.562 0.087 297.891 0.093 298.239 0.099 298.588 0.104 298.937 0.110 299.404 0.116 299.629 0.122 299.853 0.128 300.190 0.134 300.410 0.139 300.393 0.145 300.806 0.151 300.885 0.157 301.131 0.163 301.899 0.168 302.406 0.174 303.044 0.180 304.613 0.186 305.640 0.192 306.580 0.197 307.564 0.203 308.526 0.209 307.732 0.215 308.335 0.221 308.961 0.226 309.493 0.232 310.928 0.238 310.205 0.244 310.321 0.250 310.435 0.255 310.530 0.261 310.647 0.267 310.841 0.273 311.025 0.279 311.196 0.284 311.267 0.290 311.197 0.296 311.114 0.302 311.018 0.308 310.987 0.313 311.024 0.319 311.032 0.325 311.090 0.331 311.090 0.337 311.254 0.342 311.055 0.348 311.052 0.354 311.179 0.360 311.104 0.366 311.401 0.372 311.698 0.377 311.119 0.383 311.073 0.389 311.064 0.395 311.056 0.401 311.106 0.406 311.010 0.412 310.997 0.418 311.012 0.424 311.030 0.430 311.117 0.435 311.189 0.441 311.307 0.447 311.436 0.453 311.654 0.459 311.477 0.464 311.432 0.470 311.381 0.476 311.355 0.482 311.273 0.488 311.182 0.493 311.126 0.499 311.051 0.505 311.029 0.511 310.968 0.517 310.893 0.522 310.871 0.528 310.822 0.534 310.874 0.540 310.975 0.546 311.075 0.551 310.973 0.557 310.931 0.563 310.937 0.569 310.908 0.575 310.851 0.580 310.861 0.586 310.787 0.592 310.712 0.598 310.637 0.604 310.620 0.610 310.639 0.615 310.568 0.621 310.498 0.627 310.381 0.633 310.187 0.639 310.099 0.644 310.011 0.650 310.070 0.656 310.061 0.662 310.258 0.668 310.404 0.673 310.468 0.679 310.554 0.685 310.640 0.691 310.500 0.697 310.558 0.702 310.266 0.708 310.244 0.714 310.340 0.720 310.431 0.726 310.552 0.731 310.524 0.737 310.464 0.743 310.420 0.749 310.368 0.755 310.240 0.760 310.175 0.766 310.151 0.772 310.138 0.778 310.060 0.784 310.100 0.789 310.153 0.795 310.262 0.801 310.327 0.807 310.413 0.813 310.489 0.819 310.565 0.824 310.641 0.830 310.717 0.836 307.714 0.842 269.948 0.848 272.397 0.853 275.960 0.859 276.478 0.865 277.294 0.871 276.951 0.877 277.182 0.882 277.460 0.888 277.270 0.894 277.083 0.900 277.041 0.906 276.886 0.911 277.178 0.917 276.835 0.923 276.589 0.929 276.505 0.935 276.609 0.940 276.751 0.946 276.616 0.952 276.531 0.958 276.553 0.964 276.709 0.969 276.908 0.975 276.797 0.981 276.665 0.987 276.610 0.993 276.670 0.998 276.827 1.004 276.756 1.010 276.681 1.016 276.658 1.022 276.682 1.027 276.805 1.033 276.760 1.039 276.725 1.045 276.721 1.051 276.684 1.057 276.647 1.062 276.609 1.068 273.806 1.074 275.110 1.080 265.847 1.086 262.883 1.091 261.737 1.097 261.460 1.103 261.503 1.109 261.550 1.115 261.622 1.120 261.494 1.126 261.306 1.132 260.968 1.138 260.650 1.144 260.231 1.149 259.906 1.155 259.622 1.161 259.489 1.167 259.367 1.173 259.285 1.178 259.217 1.184 259.212 1.190 259.258 1.196 259.321 1.202 259.410 1.207 259.482 1.213 259.563 1.219 259.588 1.225 259.625 1.231 259.656 1.236 259.754 1.242 259.837 1.248 259.915 1.254 259.933 1.260 259.954 1.265 259.960 1.271 259.986 1.277 259.997 1.283 260.024 1.289 260.053 1.295 260.119 1.300 260.181 1.306 260.259 1.312 260.302 1.318 260.355 1.324 260.374 1.329 260.412 1.335 260.435 1.341 260.494 1.347 260.541 1.353 260.593 1.358 260.621 1.364 260.658 1.370 260.677 1.376 260.706 1.382 260.675 1.387 260.677 1.393 260.606 1.399 260.616 1.405 260.574 1.411 260.631 1.416 260.645 1.422 260.706 1.428 260.658 1.434 260.609 1.440 260.230 1.445 259.529 1.451 258.628 1.457 251.695 1.463 242.748 1.469 235.602 1.474 232.107 1.480 233.222 1.486 232.915 1.492 232.233 1.498 231.841 1.503 231.969 1.509 232.569 1.515 232.924 1.521 232.715 1.527 232.285 1.533 231.814 1.538 231.586 1.544 231.688 1.550 231.812 1.556 231.951 1.562 232.122 1.567 232.042 1.573 231.869 1.579 231.819 1.585 231.727 1.591 231.787 1.596 232.008 1.602 232.025 1.608 232.049 1.614 232.116 1.620 232.012 1.625 232.013 1.631 232.090 1.637 232.067 1.643 232.140 1.649 232.180 1.654 232.118 1.660 232.162 1.666 232.181 1.672 232.197 1.678 232.312 1.683 232.334 1.689 232.322 1.695 232.390 1.701 232.353 1.707 232.333 1.712 232.442 1.718 232.424 1.724 232.428 1.730 232.521 1.736 232.433 1.741 232.345 1.747 232.035 1.753 231.822 1.759 231.379 1.765 231.067 1.771 230.825 1.776 230.764 1.782 230.800 1.788 230.767 1.794 230.737 1.800 230.722 1.805 230.700 1.811 229.298 1.817 226.160 1.823 221.651 1.829 218.493 1.834 212.513 1.840 212.103 1.846 206.818 1.852 206.011 1.858 205.204 1.863 208.484 1.869 208.826 1.875 206.424 1.881 204.022 1.887 201.620 1.892 201.211 1.898 203.749 1.904 204.373 1.910 202.813 1.916 204.744 1.921 204.663 1.927 204.581 1.933 206.545 1.939 205.391 1.945 205.510 1.950 205.785 1.956 206.060 1.962 206.335 1.968 205.425 1.974 205.889 1.980 205.884 1.985 205.878 1.991 205.873 1.997 205.868 2.003 205.863 2.009 205.858 2.014 205.853 2.020 205.938 2.026 205.889 2.032 206.014 2.038 205.954 2.043 206.121 2.049 206.191 2.055 206.261 2.061 206.331 2.067 206.401 2.072 206.471 2.078 206.541 2.084 206.611 2.090 206.610 2.096 206.610 2.101 206.626 2.107 206.724 2.113 206.780 2.119 206.789 2.125 206.797 2.130 206.760 2.136 206.766 2.142 206.748 2.148 206.916 2.154 206.931 2.159 206.878 2.165 206.866 2.171 206.791 2.177 206.849 2.183 206.727 2.188 206.562 2.194 206.496 2.200 206.433 2.206 206.590 2.212 206.747 2.218 206.904 2.223 207.061 2.229 206.544 2.235 206.576 2.241 206.471 2.247 206.364 2.252 206.340 2.258 206.627 2.264 206.913 2.270 207.199 2.276 207.485 2.281 206.129 2.287 206.857 2.293 206.035 2.299 205.985 2.305 205.936 2.310 205.954 2.316 208.018 2.322 206.968 2.328 206.979 2.334 207.287 2.339 207.447 2.345 205.604 2.351 204.595 2.357 204.545 2.363 205.000 2.368 203.635 2.374 204.317 2.380 203.970 2.386 206.013 2.392 206.940 2.397 206.341 2.403 206.423 2.409 206.554 2.415 206.684 2.421 206.816 2.426 206.946 2.432 206.162 2.438 206.593 2.444 206.570 2.450 206.455 2.456 206.339 2.461 206.224 2.467 206.109 2.473 205.993 2.479 206.152 2.485 206.091 2.490 206.031 2.496 206.052 2.502 206.074 2.508 206.096 2.514 206.117 2.519 206.139 2.525 206.226 2.531 206.260 2.537 206.295 2.543 206.330 2.548 206.365 2.554 206.415 2.560 206.464 2.566 206.514 2.572 206.564 2.577 206.613 2.583 206.663 2.589 206.712 2.595 206.548 2.601 206.542 2.606 206.537 2.612 206.532 2.618 206.645 2.624 206.622 2.630 206.629 2.635 206.554 2.641 206.542 2.647 206.511 2.653 206.643 2.659 206.626 2.664 206.527 2.670 206.484 2.676 206.418 2.682 206.535 2.688 206.524 2.694 206.453 2.699 206.442 2.705 206.395 2.711 206.530 2.717 206.540 2.723 206.488 2.728 206.497 2.734 206.456 2.740 206.593 2.746 206.595 2.752 206.528 2.757 206.526 2.763 206.481 2.769 206.620 2.775 206.627 2.781 206.558 2.786 206.556 2.792 206.511 2.798 206.651 2.804 206.659 2.810 206.591 2.815 206.589 2.821 206.533 2.827 206.653 2.833 206.650 2.839 206.586 2.844 206.617 2.850 206.601 2.856 206.756 2.862 206.770 2.868 206.694 2.873 206.700 2.879 206.669 2.885 206.815 2.891 206.829 2.897 206.753 2.902 206.754 2.908 206.706 2.914 206.822 2.920 206.806 2.926 206.721 2.932 206.730 2.937 206.694 2.943 206.818 2.949 206.816 2.955 206.744 2.961 206.755 2.966 206.714 2.972 206.824 2.978 206.813 2.984 206.729 2.990 206.738 2.995 206.710 3.001 206.838 3.007 206.847 3.013 206.784 3.019 206.820 3.024 206.822 3.030 206.957 3.036 206.968 3.042 206.912 3.048 206.964 3.053 206.985 3.059 207.116 3.065 207.110 3.071 207.037 3.077 207.070 3.082 207.083 3.088 207.191 3.094 207.162 3.100 207.077 3.106 207.082 3.111 207.073 3.117 207.151 3.123 207.111 3.129 207.047 3.135 207.062 3.140 207.056 3.146 207.110 3.152 207.034 3.158 206.955 3.164 206.958 3.170 206.965 3.175 207.033 3.181 206.969 3.187 206.906 3.193 206.890 3.199 206.861 3.204 206.900 3.210 206.827 3.216 206.779 3.222 206.757 3.228 206.711 3.233 206.728 3.239 206.630 3.245 206.569 3.251 206.552 3.257 206.538 3.262 206.620 3.268 206.576 3.274 206.551 3.280 206.542 3.286 206.493 3.291 206.534 3.297 206.452 3.303 206.408 3.309 206.396 3.315 206.329 3.320 206.392 3.326 208.438 3.332 207.398 3.338 206.632 3.344 203.671 3.349 203.826 3.355 203.981 3.361 203.530 3.367 0.000 3.373 0.000 3.379 0.000 3.384 0.000 3.390 0.000 3.396 0.000 3.402 0.000 3.408 0.000 3.413 0.000 3.419 0.000 3.425 0.000 3.431 0.000 3.437 0.000 3.442 0.000 3.448 0.000 3.454 0.000 3.460 0.000 3.466 0.000 3.471 0.000 3.477 0.000 3.483 0.000 3.489 0.000 3.495 0.000 3.500 0.000 3.506 0.000 3.512 0.000 3.518 0.000 3.524 0.000 3.529 0.000 3.535 0.000 3.541 0.000 3.547 0.000 3.553 0.000 3.558 0.000 3.564 0.000 3.570 0.000 3.576 0.000 3.582 0.000 3.587 0.000 3.593 0.000 3.599 0.000 3.605 0.000 3.611 0.000 3.617 0.000 3.622 0.000 3.628 0.000 3.634 0.000 3.640 0.000 3.646 0.000 3.651 0.000 3.657 0.000 3.663 0.000 3.669 0.000 3.675 0.000 3.680 0.000 3.686 0.000 3.692 0.000 3.698 0.000 3.704 0.000 3.709 0.000 3.715 0.000 3.721 0.000 3.727 0.000 3.733 0.000 3.738 0.000 3.744 177.495 3.750 177.495 3.756 179.270 3.762 179.270 3.767 179.575 3.773 180.223 3.779 181.763 3.785 182.303 3.791 181.561 3.796 181.845 3.802 182.128 3.808 181.916 3.814 182.002 3.820 182.111 3.825 182.235 3.831 182.390 3.837 182.570 3.843 182.711 3.849 182.811 3.855 182.896 3.860 182.974 3.866 183.009 3.872 182.457 3.878 182.653 3.884 182.902 3.889 183.152 3.895 183.401 3.901 185.487 3.907 184.788 3.913 184.582 3.918 184.375 3.924 186.011 3.930 185.092 3.936 183.301 3.942 183.766 3.947 182.184 3.953 182.993 3.959 182.982 3.965 182.076 3.971 181.618 3.976 181.159 3.982 182.508 3.988 181.836 3.994 181.084 4.000 179.780 4.005 180.539 4.011 180.475 4.017 180.410 4.023 181.183 4.029 181.955 4.034 181.512 4.040 181.667 4.046 181.823 4.052 181.979 4.058 182.134 4.063 181.668 4.069 181.901 4.075 181.594 4.081 181.422 4.087 181.158 4.093 180.873 4.098 180.588 4.104 180.303 4.110 180.019 4.116 179.734 4.122 181.243 4.127 181.300 4.133 181.002 4.139 181.038 4.145 181.074 4.151 181.594 4.156 181.686 4.162 181.736 4.168 181.736 4.174 181.692 4.180 181.612 4.185 181.503 4.191 181.363 4.197 181.202 4.203 181.038 4.209 180.877 4.214 180.711 4.220 180.495 4.226 180.162 4.232 179.139 4.238 179.028 4.243 176.676 4.249 177.199 4.255 179.227 4.261 180.502 4.267 181.777 4.272 181.222 4.278 181.392 4.284 181.562 4.290 181.732 4.296 181.903 4.301 181.302 4.307 181.261 4.313 181.321 4.319 181.348 4.325 181.376 4.331 181.403 4.336 181.430 4.342 181.334 4.348 181.318 4.354 181.305 4.360 181.292 4.365 181.279 4.371 181.266 4.377 181.253 4.383 181.240 4.389 181.227 4.394 181.278 4.400 181.288 4.406 181.349 4.412 181.411 4.418 181.360 4.423 181.372 4.429 181.384 4.435 181.396 4.441 181.409 4.447 181.473 4.452 181.467 4.458 181.451 4.464 181.436 4.470 181.420 4.476 181.380 4.481 181.352 4.487 181.369 4.493 181.399 4.499 181.397 4.505 181.395 4.510 181.393 4.516 181.391 4.522 181.406 4.528 181.373 4.534 181.318 4.540 181.275 4.545 181.308 4.551 181.301 4.557 181.404 4.563 181.348 4.569 181.351 4.574 181.298 4.580 181.245 4.586 181.192 4.592 181.169 4.598 181.215 4.603 181.260 4.609 181.305 4.615 181.351 4.621 181.197 4.627 181.201 4.632 181.245 4.638 181.182 4.644 181.061 4.650 180.941 4.656 180.269 4.661 179.282 4.667 177.131 4.673 175.502 4.679 175.348 4.685 174.457 4.690 174.019 4.696 173.416 4.702 173.413 4.708 173.361 4.714 173.274 4.719 173.329 4.725 173.384 4.731 173.439 4.737 173.494 4.743 173.549 4.748 173.507 4.754 173.700 4.760 173.854 4.766 173.961 4.772 174.008 4.778 173.993 4.783 173.949 4.789 173.922 4.795 173.924 4.801 173.930 4.807 173.905 4.812 173.850 4.818 173.796 4.824 173.777 4.830 173.801 4.836 173.842 4.841 173.870 4.847 173.885 4.853 173.913 4.859 173.981 4.865 174.075 4.870 174.164 4.876 174.250 4.882 174.379 4.888 174.541 4.894 174.641 4.899 174.772 4.905 176.637 4.911 175.858 4.917 177.524 4.923 176.758 4.928 176.718 4.934 176.678 4.940 176.637 4.946 175.330 4.952 174.023 4.957 172.715 4.963 173.122 4.969 173.529 4.975 175.169 4.981 175.367 4.986 175.157 4.992 174.947 4.998 174.738 5.004 172.783 5.010 173.417 5.016 175.359 5.021 176.648 5.027 176.480 5.033 173.068 5.039 0.000 5.045 0.000 5.050 230.807 5.056 230.068 5.062 231.008 5.068 231.008 5.074 230.915 5.079 230.718 5.085 230.522 5.091 230.254 5.097 230.219 5.103 230.271 5.108 230.306 5.114 230.432 5.120 230.512 5.126 230.593 5.132 230.652 5.137 230.694 5.143 230.701 5.149 230.779 5.155 230.975 5.161 231.059 5.166 231.111 5.172 231.179 5.178 231.239 5.184 231.303 5.190 231.418 5.195 231.507 5.201 231.596 5.207 231.568 5.213 231.655 5.219 231.653 5.224 231.720 5.230 231.785 5.236 231.739 5.242 231.807 5.248 231.824 5.254 231.738 5.259 231.708 5.265 231.755 5.271 231.651 5.277 231.628 5.283 231.669 5.288 231.575 5.294 231.572 5.300 231.609 5.306 231.546 5.312 231.552 5.317 231.545 5.323 231.471 5.329 231.475 5.335 231.448 5.341 231.392 5.346 231.405 5.352 231.355 5.358 231.330 5.364 231.380 5.370 231.346 5.375 231.346 5.381 231.409 5.387 231.359 5.393 231.345 5.399 231.409 5.404 231.339 5.410 231.317 5.416 231.389 5.422 231.321 5.428 231.332 5.433 231.425 5.439 231.354 5.445 231.349 5.451 231.401 5.457 231.308 5.462 231.301 5.468 231.350 5.474 231.279 5.480 231.295 5.486 231.348 5.492 231.300 5.497 231.315 5.503 231.323 5.509 231.265 5.515 231.287 5.521 231.291 5.526 231.253 5.532 231.271 5.538 231.234 5.544 231.215 5.550 231.270 5.555 231.253 5.561 231.269 5.567 231.333 5.573 231.302 5.579 231.319 5.584 231.388 5.590 231.341 5.596 231.356 5.602 231.435 5.608 231.379 5.613 231.376 5.619 231.422 5.625 231.322 5.631 231.313 5.637 231.391 5.642 231.333 5.648 231.375 5.654 231.474 5.660 231.424 5.666 231.452 5.671 231.514 5.677 231.454 5.683 231.482 5.689 231.529 5.695 231.474 5.700 231.501 5.706 231.518 5.712 231.477 5.718 231.506 5.724 231.492 5.730 231.467 5.735 231.516 5.741 231.491 5.747 231.483 5.753 231.536 5.759 231.498 5.764 231.503 5.770 231.523 5.776 231.362 5.782 230.593 5.788 229.824 5.793 224.474 5.799 212.558 5.805 209.934 5.811 208.566 5.817 206.650 5.822 207.536 5.828 207.579 5.834 207.051 5.840 206.919 5.846 206.787 5.851 206.655 5.857 206.523 5.863 207.473 5.869 206.942 5.875 206.976 5.880 206.402 5.886 206.628 5.892 206.765 5.898 206.823 5.904 206.706 5.909 206.613 5.915 206.452 5.921 206.271 5.927 206.204 5.933 206.178 5.939 206.298 5.944 206.341 5.950 206.299 5.956 206.275 5.962 206.256 5.968 206.358 5.973 206.396 5.979 206.348 5.985 206.310 5.991 206.298 5.997 206.422 6.002 206.511 6.008 206.504 6.014 206.492 6.020 206.482 6.026 206.587 6.031 206.656 6.037 206.651 6.043 206.729 6.049 206.807 6.055 207.852 6.060 208.897 6.066 209.156 6.072 206.605 6.078 204.053 6.084 203.517 6.089 202.981 6.095 202.445 6.101 203.928 6.107 203.199 6.113 201.159 6.118 199.120 6.124 197.865 6.130 199.843 6.136 201.023 6.142 203.694 6.147 205.620 6.153 205.839 6.159 206.058 6.165 206.277 6.171 206.496 6.177 206.715 6.182 206.467 6.188 206.550 6.194 206.779 6.200 206.935 6.206 206.523 6.211 206.723 6.217 206.770 6.223 206.791 6.229 206.825 6.235 206.853 6.240 206.880 6.246 206.908 6.252 206.935 6.258 206.963 6.264 206.990 6.269 207.001 6.275 207.055 6.281 206.978 6.287 206.900 6.293 206.851 6.298 206.939 6.304 206.974 6.310 206.888 6.316 206.818 6.322 206.770 6.327 206.864 6.333 206.902 6.339 206.825 6.345 206.765 6.351 206.714 6.356 206.806 6.362 206.844 6.368 206.768 6.374 206.709 6.380 206.659 6.385 206.756 6.391 206.806 6.397 206.743 6.403 206.693 6.409 206.654 6.415 206.763 6.420 206.831 6.426 206.784 6.432 206.752 6.438 206.720 6.444 206.834 6.449 206.903 6.455 206.857 6.461 206.840 6.467 206.829 6.473 206.958 6.478 207.028 6.484 206.967 6.490 206.955 6.496 206.944 6.502 207.068 6.507 207.128 6.513 207.062 6.519 207.069 6.525 207.062 6.531 207.175 6.536 207.205 6.542 207.112 6.548 207.120 6.554 207.099 6.560 207.199 6.565 207.208 6.571 207.099 6.577 207.102 6.583 207.072 6.589 207.177 6.594 207.186 6.600 207.078 6.606 207.074 6.612 207.028 6.618 207.102 6.623 207.073 6.629 206.953 6.635 206.970 6.641 206.966 6.647 207.079 6.653 207.075 6.658 206.973 6.664 207.003 6.670 207.008 6.676 207.121 6.682 207.118 6.687 207.034 6.693 207.084 6.699 207.116 6.705 207.243 6.711 207.240 6.716 207.170 6.722 207.222 6.728 207.246 6.734 207.335 6.740 207.284 6.745 207.201 6.751 207.235 6.757 207.241 6.763 207.303 6.769 207.237 6.774 207.165 6.780 207.195 6.786 207.215 6.792 207.273 6.798 207.210 6.803 207.136 6.809 207.142 6.815 207.171 6.821 207.228 6.827 207.180 6.832 207.148 6.838 207.194 6.844 207.277 6.850 207.346 6.856 207.282 6.861 207.262 6.867 207.307 6.873 207.387 6.879 207.434 6.885 207.338 6.891 207.329 6.896 207.351 6.902 207.400 6.908 207.411 6.914 207.292 6.920 207.314 6.925 207.315 6.931 207.351 6.937 207.339 6.943 207.203 6.949 207.238 6.954 207.205 6.960 207.226 6.966 207.207 6.972 207.075 6.978 207.135 6.983 207.120 6.989 207.172 6.995 207.180 7.001 207.069 7.007 207.157 7.012 207.192 7.018 207.296 7.024 207.315 7.030 207.212 7.036 207.280 7.041 207.306 7.047 207.391 7.053 207.374 7.059 207.284 7.065 207.352 7.070 207.353 7.076 207.395 7.082 207.417 7.088 207.438 7.094 207.460 7.100 207.267 7.105 207.292 7.111 207.196 7.117 207.114 7.123 207.126 7.129 207.033 7.134 206.994 7.140 206.862 7.146 206.731 7.152 206.599 7.158 206.467 7.163 206.335 7.169 206.203 7.175 206.680 7.181 206.727 7.187 206.748 7.192 206.843 7.198 206.831 7.204 206.829 7.210 206.909 7.216 206.960 7.221 207.048 7.227 207.006 7.233 207.000 7.239 207.080 7.245 207.124 7.250 207.185 7.256 207.108 7.262 207.096 7.268 207.141 7.274 207.133 7.279 207.149 7.285 207.042 7.291 207.042 7.297 207.051 7.303 206.998 7.308 206.973 7.314 206.825 7.320 206.794 7.326 206.741 7.332 206.666 7.338 206.590 7.343 206.514 7.349 206.439 7.355 205.182 7.361 205.516 7.367 206.547 7.372 206.508 7.378 206.558 7.384 206.613 7.390 206.679 7.396 206.772 7.401 206.739 7.407 206.740 7.413 206.778 7.419 206.841 7.425 206.925 7.430 206.885 7.436 206.898 7.442 206.953 7.448 207.016 7.454 207.077 7.459 207.003 7.465 207.029 7.471 207.070 7.477 207.107 7.483 207.137 7.488 207.170 7.494 207.202 7.500 207.048 7.506 207.007 7.512 206.966 7.517 206.799 7.523 206.760 7.529 206.651 7.535 206.541 7.541 204.368 7.546 205.259 7.552 205.376 7.558 204.087 7.564 204.825 7.570 205.563 7.576 206.123 7.581 206.147 7.587 206.187 7.593 206.291 7.599 206.412 7.605 206.407 7.610 206.431 7.616 206.498 7.622 206.610 7.628 206.719 7.634 206.688 7.639 206.700 7.645 206.774 7.651 206.872 7.657 206.957 7.663 206.892 7.668 206.906 7.674 206.924 7.680 206.955 7.686 206.976 7.692 206.861 7.697 206.826 7.703 206.807 7.709 206.774 7.715 206.758 7.721 206.636 7.726 206.621 7.732 206.607 7.738 206.593 7.744 206.610 7.750 206.159 7.755 206.424 7.761 206.120 7.767 205.954 7.773 205.787 7.779 205.538 7.784 205.288 7.790 205.039 7.796 204.789 7.802 205.038 7.808 205.287 7.814 206.458 7.819 206.463 7.825 206.410 7.831 205.344 7.837 205.826 7.843 205.857 7.848 206.860 7.854 206.119 7.860 205.378 7.866 206.241 7.872 203.886 7.877 202.990 7.883 203.378 7.889 203.766 7.895 204.154 7.901 208.633 7.906 211.067 7.912 210.233 7.918 0.000 7.924 0.000 7.930 0.000 7.935 0.000 7.941 0.000 7.947 0.000 7.953 0.000 7.959 0.000 7.964 0.000 7.970 0.000 7.976 0.000 7.982 0.000 7.988 0.000 7.993 0.000 7.999 0.000 8.005 0.000 8.011 0.000 8.017 0.000 8.022 0.000 8.028 0.000 8.034 0.000 8.040 0.000 8.046 0.000 8.052 0.000 8.057 0.000 8.063 0.000 8.069 0.000 8.075 0.000 8.081 0.000 8.086 0.000 8.092 0.000 8.098 0.000 8.104 0.000 8.110 0.000 8.115 0.000 8.121 0.000 8.127 0.000 8.133 0.000 8.139 0.000 8.144 0.000 8.150 0.000 8.156 0.000 8.162 0.000 8.168 0.000 8.173 0.000 8.179 0.000 8.185 0.000 8.191 0.000 8.197 0.000 8.202 0.000 8.208 0.000 8.214 0.000 8.220 0.000 8.226 0.000 8.231 0.000 8.237 0.000 8.243 0.000 8.249 0.000 8.255 0.000 8.260 0.000 8.266 0.000 8.272 0.000 8.278 0.000 8.284 0.000 8.290 0.000 8.295 0.000 8.301 0.000 8.307 0.000 8.313 0.000 8.319 0.000 8.324 0.000 8.330 0.000 8.336 0.000 8.342 0.000 8.348 0.000 8.353 0.000 8.359 0.000 8.365 0.000 8.371 0.000 8.377 0.000 8.382 0.000 8.388 0.000 8.394 0.000 8.400 0.000 8.406 0.000 8.411 202.012 8.417 202.012 8.423 203.259 8.429 207.325 8.435 207.325 8.440 207.325 8.446 207.325 8.452 207.324 8.458 207.324 8.464 207.324 8.469 206.293 8.475 206.251 8.481 206.277 8.487 206.395 8.493 206.560 8.499 206.701 8.504 206.544 8.510 206.896 8.516 206.866 8.522 206.835 8.528 206.919 8.533 206.936 8.539 206.889 8.545 206.912 8.551 206.966 8.557 207.159 8.562 207.259 8.568 207.237 8.574 207.250 8.580 207.238 8.586 207.362 8.591 207.392 8.597 207.322 8.603 207.324 8.609 207.302 8.615 207.427 8.620 207.448 8.626 207.376 8.632 207.397 8.638 207.395 8.644 207.508 8.649 207.389 8.655 207.027 8.661 206.626 8.667 205.211 8.673 205.212 8.678 206.326 8.684 206.481 8.690 206.699 8.696 206.175 8.702 206.872 8.707 206.809 8.713 206.676 8.719 206.543 8.725 204.346 8.731 205.213 8.737 203.299 8.742 204.187 8.748 204.229 8.754 206.741 8.760 208.017 8.766 207.812 8.771 206.041 8.777 207.103 8.783 208.166 8.789 207.136 8.795 207.435 8.800 207.564 8.806 207.694 8.812 206.610 8.818 205.945 8.824 205.953 8.829 205.860 8.835 205.768 8.841 204.716 8.847 203.664 8.853 202.611 8.858 201.559 8.864 204.517 8.870 196.966 8.876 194.591 8.882 192.216 8.887 192.137 8.893 191.459 8.899 192.991 8.905 194.523 8.911 196.055 8.916 195.612 8.922 195.439 8.928 195.877 8.934 196.015 8.940 196.153 8.945 195.715 8.951 195.936 8.957 195.935 8.963 195.869 8.969 195.554 8.975 195.608 8.980 195.662 8.986 195.716 8.992 195.686 8.998 195.656 9.004 195.625 9.009 195.595 9.015 195.564 9.021 195.742 9.027 195.750 9.033 195.728 9.038 195.728 9.044 195.734 9.050 195.842 9.056 195.857 9.062 195.844 9.067 195.832 9.073 195.836 9.079 195.868 9.085 195.875 9.091 195.916 9.096 195.957 9.102 195.999 9.108 195.962 9.114 195.992 9.120 196.052 9.125 196.062 9.131 196.097 9.137 196.189 9.143 196.381 9.149 196.483 9.154 196.529 9.160 196.539 9.166 196.507 9.172 196.523 9.178 196.596 9.183 196.573 9.189 196.579 9.195 196.561 9.201 196.554 9.207 196.546 9.213 196.600 9.218 196.678 9.224 196.744 9.230 196.810 9.236 196.876 9.242 196.993 9.247 197.955 9.253 198.916 9.259 199.878 9.265 198.831 9.271 197.784 9.276 229.122 9.282 230.883 9.288 231.548 9.294 232.158 9.300 232.193 9.305 231.688 9.311 231.295 9.317 231.328 9.323 231.896 9.329 232.131 9.334 232.053 9.340 232.056 9.346 232.146 9.352 232.093 9.358 231.935 9.363 232.092 9.369 232.146 9.375 232.149 9.381 232.177 9.387 232.287 9.392 232.281 9.398 232.288 9.404 232.354 9.410 232.487 9.416 232.487 9.421 232.509 9.427 232.653 9.433 232.611 9.439 232.573 9.445 232.623 9.451 232.561 9.456 232.590 9.462 232.511 9.468 232.523 9.474 232.535 9.480 232.586 9.485 232.589 9.491 232.648 9.497 232.625 9.503 232.584 9.509 232.673 9.514 232.680 9.520 232.656 9.526 232.703 9.532 232.656 9.538 232.649 9.543 232.641 9.549 232.638 9.555 232.608 9.561 232.685 9.567 232.631 9.572 232.661 9.578 232.706 9.584 232.641 9.590 232.687 9.596 232.704 9.601 232.659 9.607 232.702 9.613 232.685 9.619 232.646 9.625 232.684 9.630 232.612 9.636 232.562 9.642 232.617 9.648 232.553 9.654 232.528 9.660 232.593 9.665 232.517 9.671 232.518 9.677 232.583 9.683 232.500 9.689 232.519 9.694 232.552 9.700 232.484 9.706 232.516 9.712 232.510 9.718 232.457 9.723 232.500 9.729 232.487 9.735 232.468 9.741 232.527 9.747 232.475 9.752 232.446 9.758 232.512 9.764 232.456 9.770 232.443 9.776 232.507 9.781 232.426 9.787 232.422 9.793 232.482 9.799 232.393 9.805 232.412 9.810 232.453 9.816 232.389 9.822 232.437 9.828 232.452 9.834 232.419 9.839 232.470 9.845 232.441 9.851 232.394 9.857 232.432 9.863 232.379 9.868 232.368 9.874 232.440 9.880 232.386 9.886 232.378 9.892 232.442 9.898 232.362 9.903 232.359 9.909 232.424 9.915 232.341 9.921 232.356 9.927 232.404 9.932 232.324 9.938 232.343 9.944 232.341 9.950 232.275 9.956 232.330 9.961 232.337 9.967 232.323 9.973 232.396 9.979 232.372 9.985 232.370 9.990 232.443 9.996 232.406 10.002 232.402 10.008 232.472 10.014 232.411 10.019 232.416 10.025 232.491 10.031 232.412 10.037 232.410 10.043 232.463 10.048 232.386 10.054 232.413 10.060 232.447 10.066 232.379 10.072 232.415 10.077 232.407 10.083 232.355 10.089 232.405 10.095 232.381 10.101 232.364 10.106 232.438 10.112 232.412 10.118 232.426 10.124 232.509 10.130 232.452 10.136 232.461 10.141 231.402 10.147 229.714 10.153 226.057 10.159 212.216 10.165 209.571 10.170 208.129 10.176 208.146 10.182 208.163 10.188 208.180 10.194 208.141 10.199 207.872 10.205 207.718 10.211 207.563 10.217 207.409 10.223 208.126 10.228 207.280 10.234 206.849 10.240 206.801 10.246 207.312 10.252 207.020 10.257 206.728 10.263 206.436 10.269 206.577 10.275 206.748 10.281 206.919 10.286 207.090 10.292 207.261 10.298 207.196 10.304 207.132 10.310 207.064 10.315 206.996 10.321 206.927 10.327 206.939 10.333 206.900 10.339 206.837 10.344 206.891 10.350 206.851 10.356 206.748 10.362 206.768 10.368 206.783 10.374 206.916 10.379 206.936 10.385 206.869 10.391 206.890 10.397 206.905 10.403 207.038 10.408 207.067 10.414 207.046 10.420 207.108 10.426 207.067 10.432 207.764 10.437 208.462 10.443 209.295 10.449 212.161 10.455 214.010 10.461 201.438 10.466 202.174 10.472 203.449 10.478 210.588 10.484 204.055 10.490 207.891 10.495 205.474 10.501 203.056 10.507 202.645 10.513 202.234 10.519 205.860 10.524 205.770 10.530 206.784 10.536 206.203 10.542 206.247 10.548 206.395 10.553 206.491 10.559 206.587 10.565 206.683 10.571 205.830 10.577 206.313 10.582 206.031 10.588 206.055 10.594 206.125 10.600 206.173 10.606 206.278 10.612 206.356 10.617 206.431 10.623 206.396 10.629 206.311 10.635 206.300 10.641 206.385 10.646 206.522 10.652 206.546 10.658 206.505 10.664 206.508 10.670 206.571 10.675 206.692 10.681 206.686 10.687 206.620 10.693 206.598 10.699 206.624 10.704 206.718 10.710 206.691 10.716 206.621 10.722 206.602 10.728 206.631 10.733 206.718 10.739 206.676 10.745 206.585 10.751 206.549 10.757 206.551 10.762 206.617 10.768 206.549 10.774 206.423 10.780 206.297 10.786 206.171 10.791 206.044 10.797 206.168 10.803 206.132 10.809 206.117 10.815 206.143 10.820 206.132 10.826 206.131 10.832 206.216 10.838 206.301 10.844 206.386 10.850 206.411 10.855 206.420 10.861 206.428 10.867 206.535 10.873 206.526 10.879 206.499 10.884 206.472 10.890 206.445 10.896 206.418 10.902 202.657 10.908 198.756 10.913 196.847 10.919 195.528 10.925 195.439 10.931 195.349 10.937 195.409 10.942 195.595 10.948 195.719 10.954 195.842 10.960 195.772 10.966 195.703 10.971 195.633 10.977 195.564 10.983 195.706 10.989 195.641 10.995 195.577 11.000 195.513 11.006 195.448 11.012 195.384 11.018 195.636 11.024 195.504 11.029 195.437 11.035 195.436 11.041 195.366 11.047 195.368 11.053 195.371 11.059 195.373 11.064 195.375 11.070 195.535 11.076 195.599 11.082 195.688 11.088 195.743 11.093 195.797 11.099 195.838 11.105 195.872 11.111 195.900 11.117 195.804 11.122 195.660 11.128 195.365 11.134 193.194 11.140 193.880 11.146 194.120 11.151 194.359 11.157 194.423 11.163 194.465 11.169 194.543 11.175 194.656 11.180 194.856 11.186 196.747 11.192 195.815 11.198 195.807 11.204 195.434 11.209 195.560 11.215 195.866 11.221 196.810 11.227 197.891 11.233 198.098 11.238 196.755 11.244 199.474 11.250 198.246 11.256 198.167 11.262 193.563 11.267 195.046 11.273 195.538 11.279 228.095 11.285 226.110 11.291 224.125 11.297 228.804 11.302 228.858 11.308 231.224 11.314 232.435 11.320 231.881 11.326 230.422 11.331 230.268 11.337 229.672 11.343 229.584 11.349 229.497 11.355 229.550 11.360 229.629 11.366 229.579 11.372 229.548 11.378 229.593 11.384 229.654 11.389 230.145 11.395 230.261 11.401 230.231 11.407 230.437 11.413 230.622 11.418 230.724 11.424 230.853 11.430 230.944 11.436 231.034 11.442 231.201 11.447 231.272 11.453 231.316 11.459 231.417 11.465 231.436 11.471 231.472 11.476 231.500 11.482 231.514 11.488 231.503 11.494 231.591 11.500 231.540 11.505 231.522 11.511 231.608 11.517 231.547 11.523 231.575 11.529 231.678 11.535 231.605 11.540 231.606 11.546 231.676 11.552 231.595 11.558 231.599 11.564 231.644 11.569 231.563 11.575 231.587 11.581 231.642 11.587 231.599 11.593 231.621 11.598 231.622 11.604 231.584 11.610 231.634 11.616 231.647 11.622 231.649 11.627 231.719 11.633 231.696 11.639 231.699 11.645 231.776 11.651 231.761 11.656 231.778 11.662 231.857 11.668 231.795 11.674 231.766 11.680 231.828 11.685 231.738 11.691 231.725 11.697 231.776 11.703 231.679 11.709 231.687 11.714 231.767 11.720 231.708 11.726 231.734 11.732 231.782 11.738 231.705 11.743 231.719 11.749 231.739 11.755 231.688 11.761 231.711 11.767 231.705 11.773 231.679 11.778 231.732 11.784 231.714 11.790 231.695 11.796 231.739 11.802 231.697 11.807 231.685 11.813 231.728 11.819 231.671 11.825 231.667 11.831 231.747 11.836 231.691 11.842 231.697 11.848 231.784 11.854 231.715 11.860 231.719 11.865 231.778 11.871 231.675 11.877 231.671 11.883 231.736 11.889 231.672 11.894 231.701 11.900 231.746 11.906 231.679 11.912 231.722 11.918 231.770 11.923 231.742 11.929 231.779 11.935 231.761 11.941 231.721 11.947 231.763 11.952 231.722 11.958 231.695 11.964 231.732 11.970 231.678 11.976 231.667 11.981 231.739 11.987 231.703 11.993 231.696 11.999 231.756 12.005 231.667 12.011 231.655 12.016 231.722 12.022 231.574 12.028 231.426 12.034 229.509 12.040 228.476 12.045 220.191 12.051 209.067 12.057 207.336 12.063 207.151 12.069 206.194 12.074 207.052 12.080 206.899 12.086 206.839 12.092 206.779 12.098 206.719 12.103 206.659 12.109 207.484 12.115 206.720 12.121 206.250 12.127 206.230 12.132 206.409 12.138 206.616 12.144 206.844 12.150 206.928 12.156 206.917 12.161 206.768 12.167 206.559 12.173 206.469 12.179 206.436 12.185 206.499 12.190 206.468 12.196 206.367 12.202 206.371 12.208 206.393 12.214 206.470 12.220 206.405 12.225 206.250 12.231 206.201 12.237 206.176 12.243 206.254 12.249 206.235 12.254 206.158 12.260 206.179 12.266 206.192 12.272 206.292 12.278 206.270 12.283 206.173 12.289 206.162 12.295 206.149 12.301 206.243 12.307 206.221 12.312 206.137 12.318 206.155 12.324 206.179 12.330 206.330 12.336 206.369 12.341 206.332 12.347 206.367 12.353 206.374 12.359 206.446 12.365 206.083 12.370 204.859 12.376 202.957 12.382 199.381 12.388 196.641 12.394 195.418 12.399 195.371 12.405 195.601 12.411 195.477 12.417 195.482 12.423 195.416 12.428 195.454 12.434 195.451 12.440 195.442 12.446 195.277 12.452 195.113 12.458 194.949 12.463 194.784 12.469 194.620 12.475 194.573 12.481 194.468 12.487 194.391 12.492 194.371 12.498 194.438 12.504 194.404 12.510 194.404 12.516 194.466 12.521 194.433 12.527 194.449 12.533 194.485 12.539 194.545 12.545 194.611 12.550 194.695 12.556 194.799 12.562 194.940 12.568 195.021 12.574 195.101 12.579 195.345 12.585 195.444 12.591 195.519 12.597 195.605 12.603 195.686 12.608 195.722 12.614 195.752 12.620 195.717 12.626 195.729 12.632 195.684 12.637 195.639 12.643 195.594 12.649 195.527 12.655 195.516 12.661 195.505 12.666 195.526 12.672 195.576 12.678 195.610 12.684 195.559 12.690 195.507 12.696 195.455 12.701 195.403 12.707 195.418 12.713 195.433 12.719 195.443 12.725 195.520 12.730 195.611 12.736 195.698 12.742 195.784 12.748 195.871 12.754 195.958 12.759 196.045 12.765 196.132 12.771 196.310 12.777 196.349 12.783 196.388 12.788 196.416 12.794 196.449 12.800 196.391 12.806 196.326 12.812 196.264 12.817 196.152 12.823 196.037 12.829 195.916 12.835 195.778 12.841 195.641 12.846 195.503 12.852 195.517 12.858 195.475 12.864 195.496 12.870 195.419 12.875 195.459 12.881 195.458 12.887 195.458 12.893 195.534 12.899 195.611 12.904 195.669 12.910 195.726 12.916 195.783 12.922 195.845 12.928 195.904 12.934 195.964 12.939 196.038 12.945 196.105 12.951 196.176 12.957 196.245 12.963 196.314 12.968 196.383 12.974 196.425 12.980 196.468 12.986 196.427 12.992 196.386 12.997 196.344 13.003 196.302 13.009 196.189 13.015 196.091 13.021 195.986 13.026 195.880 13.032 195.765 13.038 195.651 13.044 195.525 13.050 195.400 13.055 195.333 13.061 195.276 13.067 195.221 13.073 195.237 13.079 195.409 13.084 195.503 13.090 195.521 13.096 195.690 13.102 195.783 13.108 195.914 13.113 196.026 13.119 196.193 13.125 196.308 13.131 196.400 13.137 196.492 13.142 196.562 13.148 196.594 13.154 196.598 13.160 196.546 13.166 196.494 13.172 196.443 13.177 196.391 13.183 196.340 13.189 196.014 13.195 195.826 13.201 195.638 13.206 195.449 13.212 195.647 13.218 195.628 13.224 195.580 13.230 195.684 13.235 195.698 13.241 195.712 13.247 195.725 13.253 195.739 13.259 195.794 13.264 195.826 13.270 195.891 13.276 195.962 13.282 196.031 13.288 196.096 13.293 196.162 13.299 196.210 13.305 196.267 13.311 196.320 13.317 196.373 13.322 196.425 13.328 196.462 13.334 196.473 13.340 196.420 13.346 196.449 13.351 196.252 13.357 196.200 13.363 196.076 13.369 195.936 13.375 195.803 13.380 195.730 13.386 195.656 13.392 195.467 13.398 195.278 13.404 195.181 13.410 195.083 13.415 195.084 13.421 195.118 13.427 195.168 13.433 195.290 13.439 195.394 13.444 195.498 13.450 195.602 13.456 195.706 13.462 195.774 13.468 195.847 13.473 195.925 13.479 196.001 13.485 196.077 13.491 196.158 13.497 196.236 13.502 196.235 13.508 196.212 13.514 196.220 13.520 196.222 13.526 196.227 13.531 196.232 13.537 196.091 13.543 195.950 13.549 195.809 13.555 195.689 13.560 195.558 13.566 195.427 13.572 195.297 13.578 195.384 13.584 195.371 13.589 195.353 13.595 195.341 13.601 195.353 13.607 195.382 13.613 195.402 13.619 195.569 13.624 195.533 13.630 195.614 13.636 195.688 13.642 195.769 13.648 195.847 13.653 195.926 13.659 196.137 13.665 196.261 13.671 196.367 13.677 196.439 13.682 196.469 13.688 196.498 13.694 196.528 13.700 196.557 13.706 196.168 13.711 196.149 13.717 195.945 13.723 195.740 13.729 195.536 13.735 195.332 13.740 195.928 13.746 195.632 13.752 195.631 13.758 195.630 13.764 195.629 13.769 195.248 13.775 194.867 13.781 195.097 13.787 195.803 13.793 196.271 13.798 196.740 13.804 195.703 13.810 195.700 13.816 195.698 13.822 195.703 13.827 195.854 13.833 195.951 13.839 196.074 13.845 196.164 13.851 196.254 13.857 196.441 13.862 196.580 13.868 196.718 13.874 196.834 13.880 196.961 13.886 196.946 13.891 196.917 13.897 196.887 13.903 196.167 13.909 196.156 13.915 195.790 13.920 196.108 13.926 196.017 13.932 195.905 13.938 195.852 13.944 195.817 13.949 195.756 13.955 194.990 13.961 193.796 13.967 194.743 13.973 194.821 13.978 194.899 13.984 194.977 13.990 194.959 13.996 195.058 14.002 195.004 14.007 195.346 14.013 195.157 14.019 194.968 14.025 194.779 14.031 195.755 14.036 195.806 14.042 196.319 14.048 195.933 14.054 196.011 14.060 196.088 14.065 196.973 14.071 196.016 14.077 196.325 14.083 196.427 14.089 196.529 14.095 195.990 14.100 196.283 14.106 195.913 14.112 195.898 14.118 195.769 14.124 195.706 14.129 195.605 14.135 195.491 14.141 195.436 14.147 195.351 14.153 195.266 14.158 195.182 14.164 195.097 14.170 195.012 14.176 194.928 14.182 195.349 14.187 195.122 14.193 195.479 14.199 195.835 14.205 196.192 14.211 196.549 14.216 196.024 14.222 195.699 14.228 195.808 14.234 196.576 14.240 197.014 14.245 196.814 14.251 196.882 14.257 196.885 14.263 196.066 14.269 196.079 14.274 196.040 14.280 196.408 14.286 196.001 14.292 195.593 14.298 195.186 14.303 195.526 14.309 195.444 14.315 195.362 14.321 195.281 14.327 195.199 14.333 195.117 14.338 195.035 14.344 195.185 14.350 195.120 14.356 195.210 14.362 195.300 14.367 195.669 14.373 195.410 14.379 195.151 14.385 194.892 14.391 195.643 14.396 195.658 14.402 195.672 14.408 195.726 14.414 195.727 14.420 195.728 14.425 195.729 14.431 195.730 14.437 195.774 14.443 195.742 14.449 195.730 14.454 195.662 14.460 195.567 14.466 195.580 14.472 195.367 14.478 195.247 14.483 195.128 14.489 195.376 14.495 195.263 14.501 194.920 14.507 194.692 14.512 194.843 14.518 194.995 14.524 195.256 14.530 195.263 14.536 195.398 14.541 195.469 14.547 195.540 14.553 195.782 14.559 195.934 14.565 196.086 14.571 196.202 14.576 196.273 14.582 196.377 14.588 196.444 14.594 196.512 14.600 195.678 14.605 195.627 14.611 195.600 14.617 195.604 14.623 195.641 14.629 197.618 14.634 196.639 14.640 196.633 14.646 196.628 14.652 196.622 14.658 196.616 14.663 194.820 14.669 194.799 14.675 194.758 14.681 194.803 14.687 196.736 14.692 195.748 14.698 195.761 14.704 192.882 14.710 194.165 14.716 194.865 14.721 195.564 14.727 194.912 14.733 195.094 14.739 194.873 14.745 195.171 14.750 195.469 14.756 197.724 14.762 197.011 14.768 198.730 14.774 197.913 14.780 197.888 14.785 197.862 14.791 197.837 14.797 197.812 14.803 197.787 14.809 197.762 14.814 197.737 14.820 193.757 14.826 194.225 14.832 194.692 14.838 194.598 14.843 194.503 14.849 0.000 14.855 0.000 14.861 0.000 14.867 0.000 14.872 0.000 14.878 0.000 14.884 0.000 14.890 0.000 14.896 0.000 14.901 0.000 14.907 0.000 14.913 0.000 14.919 0.000 14.925 0.000 14.930 0.000 14.936 0.000 14.942 0.000 14.948 0.000 14.954 0.000 14.959 0.000 14.965 0.000 14.971 0.000 14.977 0.000 14.983 0.000 14.988 0.000 14.994 0.000 15.000 0.000 15.006 0.000 15.012 0.000 15.018 0.000 15.023 0.000 15.029 0.000 15.035 0.000 15.041 0.000 15.047 0.000 15.052 0.000 15.058 0.000 15.064 0.000 15.070 0.000 15.076 0.000 15.081 0.000 15.087 0.000 15.093 0.000 15.099 0.000 15.105 0.000 15.110 0.000 15.116 0.000 15.122 0.000 15.128 0.000 15.134 0.000 15.139 0.000 15.145 0.000 15.151 0.000 15.157 0.000 15.163 0.000 15.168 0.000 15.174 0.000 15.180 0.000 15.186 0.000 15.192 0.000 15.197 0.000 15.203 0.000 15.209 0.000 15.215 0.000 15.221 0.000 15.226 0.000 15.232 0.000 15.238 0.000 15.244 0.000 15.250 0.000 15.256 0.000 15.261 0.000 15.267 0.000 15.273 0.000 15.279 0.000 15.285 0.000 15.290 0.000 15.296 0.000 15.302 0.000 15.308 0.000 15.314 0.000 15.319 0.000 15.325 0.000 15.331 0.000 15.337 0.000 15.343 0.000 15.348 0.000 15.354 0.000 15.360 0.000 15.366 0.000 15.372 0.000 15.377 0.000 15.383 0.000 15.389 0.000 15.395 0.000 15.401 0.000 15.406 0.000 15.412 0.000 15.418 0.000 15.424 0.000 15.430 0.000 15.435 0.000 15.441 0.000 15.447 0.000 15.453 0.000 mir_eval-0.8.2/tests/data/melody/ref03.txt000066400000000000000000000766211475740344600203750ustar00rootroot000000000000000.000 0.000 0.006 0.000 0.012 0.000 0.017 0.000 0.023 259.483 0.029 260.624 0.035 260.911 0.041 261.199 0.046 261.487 0.052 261.774 0.058 260.521 0.064 260.421 0.070 260.365 0.075 260.389 0.081 260.444 0.087 260.588 0.093 260.731 0.099 260.870 0.104 261.004 0.110 261.132 0.116 261.261 0.122 261.362 0.128 261.474 0.134 261.590 0.139 261.745 0.145 261.861 0.151 261.968 0.157 261.998 0.163 262.047 0.168 262.068 0.174 262.119 0.180 262.150 0.186 262.215 0.192 262.245 0.197 262.283 0.203 262.270 0.209 262.271 0.215 262.243 0.221 262.265 0.226 262.286 0.232 262.363 0.238 262.445 0.244 262.533 0.250 262.595 0.255 262.671 0.261 262.654 0.267 262.659 0.273 262.681 0.279 262.662 0.284 262.667 0.290 262.670 0.296 262.673 0.302 262.676 0.308 265.305 0.313 263.955 0.319 309.230 0.325 310.387 0.331 310.537 0.337 310.688 0.342 309.998 0.348 310.367 0.354 310.353 0.360 310.339 0.366 310.324 0.372 310.310 0.377 310.202 0.383 310.311 0.389 310.472 0.395 310.549 0.401 310.627 0.406 310.630 0.412 310.721 0.418 310.696 0.424 310.615 0.430 310.523 0.435 310.404 0.441 310.176 0.447 309.499 0.453 305.957 0.459 307.507 0.464 308.094 0.470 308.680 0.476 309.266 0.482 313.769 0.488 314.334 0.493 314.603 0.499 311.870 0.505 308.141 0.511 307.959 0.517 306.004 0.522 304.935 0.528 306.457 0.534 305.864 0.540 305.272 0.546 304.679 0.551 0.000 0.557 0.000 0.563 0.000 0.569 0.000 0.575 0.000 0.580 0.000 0.586 0.000 0.592 261.558 0.598 261.558 0.604 261.558 0.610 261.558 0.615 261.012 0.621 260.773 0.627 260.593 0.633 260.414 0.639 260.702 0.644 260.712 0.650 260.800 0.656 260.909 0.662 261.072 0.668 261.209 0.673 261.376 0.679 261.457 0.685 261.557 0.691 261.590 0.697 261.672 0.702 261.705 0.708 261.764 0.714 261.788 0.720 261.866 0.726 261.910 0.731 261.961 0.737 261.968 0.743 262.001 0.749 262.032 0.755 262.073 0.760 262.105 0.766 262.142 0.772 262.177 0.778 262.201 0.784 262.246 0.789 262.280 0.795 262.257 0.801 262.331 0.807 262.326 0.813 262.316 0.819 262.341 0.824 262.342 0.830 262.332 0.836 262.285 0.842 262.263 0.848 262.254 0.853 262.246 0.859 264.859 0.865 263.834 0.871 268.939 0.877 268.845 0.882 305.063 0.888 308.637 0.894 308.276 0.900 308.840 0.906 308.610 0.911 308.681 0.917 308.752 0.923 308.823 0.929 308.709 0.935 308.756 0.940 308.825 0.946 308.790 0.952 308.674 0.958 308.626 0.964 308.578 0.969 308.530 0.975 308.873 0.981 308.606 0.987 308.243 0.993 307.772 0.998 307.284 1.004 306.795 1.010 307.238 1.016 307.682 1.022 308.125 1.027 311.654 1.033 310.504 1.039 309.353 1.045 305.295 1.051 302.691 1.057 299.359 1.062 0.000 1.068 0.000 1.074 0.000 1.080 0.000 1.086 0.000 1.091 0.000 1.097 0.000 1.103 0.000 1.109 0.000 1.115 0.000 1.120 0.000 1.126 171.121 1.132 171.301 1.138 171.301 1.144 171.070 1.149 170.839 1.155 170.608 1.161 170.377 1.167 171.616 1.173 172.651 1.178 172.276 1.184 172.643 1.190 173.091 1.196 173.498 1.202 173.906 1.207 174.313 1.213 174.504 1.219 174.419 1.225 174.257 1.231 174.096 1.236 173.732 1.242 173.805 1.248 173.861 1.254 173.941 1.260 173.913 1.265 173.949 1.271 174.037 1.277 174.145 1.283 174.243 1.289 174.365 1.295 174.508 1.300 174.610 1.306 174.607 1.312 174.211 1.318 174.470 1.324 174.564 1.329 174.808 1.335 175.099 1.341 175.391 1.347 175.682 1.353 175.974 1.358 176.265 1.364 176.083 1.370 175.902 1.376 175.720 1.382 175.139 1.387 174.558 1.393 173.977 1.399 173.396 1.405 172.815 1.411 173.956 1.416 173.446 1.422 172.935 1.428 173.387 1.434 173.838 1.440 174.458 1.445 174.994 1.451 174.274 1.457 174.545 1.463 174.408 1.469 176.153 1.474 177.898 1.480 0.000 1.486 0.000 1.492 0.000 1.498 0.000 1.503 0.000 1.509 0.000 1.515 0.000 1.521 0.000 1.527 0.000 1.533 0.000 1.538 0.000 1.544 0.000 1.550 0.000 1.556 0.000 1.562 0.000 1.567 0.000 1.573 0.000 1.579 0.000 1.585 0.000 1.591 0.000 1.596 0.000 1.602 0.000 1.608 0.000 1.614 0.000 1.620 0.000 1.625 0.000 1.631 0.000 1.637 0.000 1.643 0.000 1.649 0.000 1.654 0.000 1.660 0.000 1.666 0.000 1.672 0.000 1.678 0.000 1.683 0.000 1.689 0.000 1.695 0.000 1.701 0.000 1.707 0.000 1.712 0.000 1.718 0.000 1.724 0.000 1.730 0.000 1.736 0.000 1.741 0.000 1.747 0.000 1.753 0.000 1.759 0.000 1.765 0.000 1.771 0.000 1.776 0.000 1.782 0.000 1.788 0.000 1.794 0.000 1.800 0.000 1.805 0.000 1.811 0.000 1.817 0.000 1.823 0.000 1.829 0.000 1.834 0.000 1.840 0.000 1.846 0.000 1.852 0.000 1.858 0.000 1.863 0.000 1.869 0.000 1.875 0.000 1.881 0.000 1.887 0.000 1.892 0.000 1.898 0.000 1.904 0.000 1.910 0.000 1.916 0.000 1.921 0.000 1.927 0.000 1.933 0.000 1.939 0.000 1.945 0.000 1.950 0.000 1.956 172.028 1.962 172.028 1.968 173.749 1.974 173.749 1.980 173.749 1.985 173.749 1.991 173.552 1.997 173.938 2.003 174.148 2.009 174.278 2.014 173.890 2.020 174.003 2.026 174.052 2.032 174.100 2.038 173.828 2.043 173.882 2.049 173.995 2.055 174.110 2.061 174.166 2.067 174.181 2.072 174.187 2.078 174.204 2.084 174.220 2.090 174.244 2.096 174.305 2.101 174.413 2.107 174.543 2.113 174.653 2.119 174.726 2.125 174.752 2.130 174.743 2.136 174.618 2.142 174.696 2.148 174.687 2.154 174.704 2.159 174.733 2.165 174.753 2.171 174.749 2.177 174.736 2.183 174.727 2.188 174.726 2.194 174.715 2.200 174.691 2.206 174.675 2.212 174.681 2.218 174.695 2.223 174.690 2.229 174.683 2.235 174.673 2.241 174.676 2.247 174.685 2.252 174.699 2.258 174.732 2.264 174.775 2.270 174.808 2.276 174.822 2.281 174.808 2.287 174.781 2.293 174.753 2.299 174.722 2.305 174.679 2.310 174.629 2.316 174.585 2.322 174.592 2.328 174.566 2.334 174.586 2.339 174.630 2.345 174.695 2.351 174.744 2.357 174.763 2.363 174.767 2.368 174.773 2.374 174.799 2.380 174.832 2.386 174.856 2.392 174.880 2.397 174.901 2.403 174.867 2.409 174.885 2.415 174.860 2.421 174.858 2.426 174.884 2.432 174.911 2.438 174.918 2.444 174.906 2.450 174.884 2.456 174.871 2.461 174.879 2.467 174.895 2.473 174.892 2.479 174.852 2.485 174.787 2.490 174.736 2.496 174.715 2.502 174.712 2.508 174.716 2.514 174.724 2.519 174.746 2.525 174.781 2.531 174.820 2.537 174.848 2.543 174.864 2.548 174.878 2.554 174.890 2.560 174.893 2.566 174.885 2.572 174.864 2.577 174.844 2.583 174.826 2.589 174.832 2.595 174.855 2.601 174.878 2.606 174.866 2.612 174.827 2.618 174.781 2.624 174.752 2.630 174.742 2.635 174.752 2.641 174.772 2.647 174.777 2.653 174.762 2.659 174.746 2.664 174.744 2.670 174.753 2.676 174.777 2.682 174.820 2.688 174.857 2.694 174.867 2.699 174.845 2.705 174.821 2.711 174.815 2.717 174.827 2.723 174.839 2.728 174.850 2.734 174.866 2.740 174.876 2.746 174.872 2.752 174.867 2.757 174.868 2.763 174.875 2.769 174.870 2.775 174.853 2.781 174.837 2.786 174.842 2.792 174.862 2.798 174.877 2.804 174.878 2.810 174.884 2.815 174.903 2.821 174.924 2.827 174.921 2.833 174.890 2.839 174.866 2.844 174.879 2.850 174.930 2.856 174.981 2.862 175.005 2.868 175.003 2.873 174.997 2.879 174.986 2.885 174.956 2.891 174.928 2.897 174.934 2.902 174.974 2.908 175.009 2.914 175.008 2.920 174.987 2.926 174.967 2.932 174.957 2.937 174.949 2.943 174.940 2.949 174.932 2.955 174.934 2.961 174.939 2.966 174.936 2.972 174.927 2.978 174.918 2.984 174.922 2.990 174.932 2.995 174.948 3.001 174.967 3.007 174.969 3.013 174.955 3.019 174.948 3.024 174.966 3.030 174.998 3.036 175.025 3.042 175.034 3.048 175.030 3.053 175.016 3.059 174.996 3.065 174.975 3.071 174.963 3.077 174.963 3.082 174.973 3.088 174.980 3.094 174.976 3.100 174.963 3.106 174.955 3.111 174.958 3.117 174.978 3.123 175.018 3.129 175.059 3.135 175.076 3.140 175.068 3.146 175.045 3.152 175.030 3.158 175.029 3.164 175.029 3.170 175.015 3.175 174.993 3.181 174.970 3.187 174.945 3.193 174.922 3.199 174.908 3.204 174.922 3.210 174.958 3.216 174.998 3.222 175.032 3.228 175.056 3.233 175.070 3.239 175.076 3.245 175.078 3.251 175.082 3.257 175.093 3.262 175.105 3.268 175.117 3.274 175.122 3.280 175.121 3.286 175.123 3.291 175.120 3.297 175.107 3.303 175.084 3.309 175.066 3.315 175.062 3.320 175.061 3.326 175.053 3.332 175.042 3.338 175.037 3.344 175.035 3.349 175.034 3.355 175.032 3.361 175.032 3.367 175.046 3.373 175.065 3.379 175.081 3.384 175.086 3.390 175.091 3.396 175.100 3.402 175.113 3.408 175.115 3.413 175.114 3.419 175.120 3.425 175.131 3.431 175.131 3.437 175.120 3.442 175.110 3.448 175.112 3.454 175.127 3.460 175.147 3.466 175.164 3.471 175.177 3.477 175.185 3.483 175.197 3.489 175.212 3.495 175.221 3.500 175.222 3.506 175.226 3.512 175.243 3.518 175.266 3.524 175.291 3.529 175.309 3.535 175.321 3.541 175.329 3.547 175.340 3.553 175.350 3.558 175.354 3.564 175.351 3.570 175.352 3.576 175.358 3.582 175.357 3.587 175.348 3.593 175.335 3.599 175.330 3.605 175.336 3.611 175.352 3.617 175.371 3.622 175.388 3.628 175.391 3.634 175.384 3.640 175.383 3.646 175.395 3.651 175.416 3.657 175.429 3.663 175.428 3.669 175.416 3.675 175.407 3.680 175.415 3.686 175.435 3.692 175.454 3.698 175.465 3.704 175.470 3.709 175.479 3.715 175.490 3.721 175.500 3.727 175.492 3.733 175.471 3.738 175.453 3.744 175.448 3.750 175.459 3.756 175.474 3.762 175.483 3.767 175.485 3.773 175.482 3.779 175.476 3.785 175.481 3.791 175.489 3.796 175.506 3.802 175.521 3.808 175.527 3.814 175.531 3.820 175.536 3.825 175.535 3.831 175.520 3.837 175.499 3.843 175.474 3.849 175.450 3.855 177.180 3.860 177.911 3.866 175.558 3.872 176.578 3.878 175.042 3.884 174.957 3.889 174.938 3.895 175.020 3.901 176.726 3.907 176.008 3.913 175.927 3.918 179.038 3.924 0.000 3.930 0.000 3.936 0.000 3.942 0.000 3.947 0.000 3.953 0.000 3.959 0.000 3.965 0.000 3.971 0.000 3.976 0.000 3.982 0.000 3.988 0.000 3.994 0.000 4.000 0.000 4.005 0.000 4.011 0.000 4.017 0.000 4.023 0.000 4.029 0.000 4.034 0.000 4.040 0.000 4.046 0.000 4.052 0.000 4.058 0.000 4.063 0.000 4.069 0.000 4.075 0.000 4.081 0.000 4.087 0.000 4.093 0.000 4.098 0.000 4.104 0.000 4.110 0.000 4.116 0.000 4.122 0.000 4.127 0.000 4.133 0.000 4.139 0.000 4.145 0.000 4.151 0.000 4.156 0.000 4.162 0.000 4.168 0.000 4.174 0.000 4.180 0.000 4.185 0.000 4.191 0.000 4.197 0.000 4.203 0.000 4.209 0.000 4.214 0.000 4.220 0.000 4.226 0.000 4.232 0.000 4.238 0.000 4.243 0.000 4.249 0.000 4.255 0.000 4.261 0.000 4.267 0.000 4.272 0.000 4.278 0.000 4.284 0.000 4.290 0.000 4.296 0.000 4.301 0.000 4.307 0.000 4.313 0.000 4.319 0.000 4.325 0.000 4.331 0.000 4.336 0.000 4.342 0.000 4.348 0.000 4.354 0.000 4.360 0.000 4.365 0.000 4.371 0.000 4.377 0.000 4.383 249.562 4.389 254.553 4.394 254.553 4.400 257.098 4.406 259.644 4.412 259.151 4.418 259.239 4.423 259.868 4.429 259.983 4.435 259.554 4.441 259.649 4.447 259.639 4.452 259.672 4.458 259.749 4.464 259.837 4.470 259.977 4.476 260.121 4.481 260.285 4.487 260.405 4.493 260.520 4.499 260.600 4.505 260.677 4.510 260.723 4.516 260.787 4.522 260.852 4.528 260.968 4.534 261.091 4.540 261.241 4.545 261.329 4.551 261.404 4.557 261.430 4.563 261.515 4.569 261.574 4.574 261.671 4.580 261.700 4.586 261.760 4.592 261.783 4.598 261.835 4.603 261.843 4.609 261.879 4.615 261.886 4.621 261.917 4.627 261.961 4.632 262.178 4.638 262.309 4.644 262.440 4.650 262.570 4.656 262.701 4.661 262.831 4.667 309.834 4.673 310.605 4.679 310.444 4.685 310.309 4.690 310.219 4.696 310.130 4.702 310.185 4.708 309.976 4.714 310.085 4.719 310.138 4.725 310.218 4.731 310.285 4.737 310.358 4.743 310.481 4.748 310.461 4.754 310.361 4.760 310.530 4.766 310.458 4.772 310.674 4.778 310.730 4.783 310.865 4.789 310.918 4.795 310.938 4.801 311.012 4.807 311.058 4.812 311.173 4.818 310.953 4.824 310.172 4.830 309.160 4.836 308.147 4.841 306.935 4.847 306.332 4.853 308.479 4.859 310.445 4.865 308.307 4.870 309.000 4.876 309.693 4.882 307.283 4.888 311.131 4.894 309.545 4.899 307.959 4.905 306.373 4.911 304.787 4.917 303.201 4.923 266.917 4.928 265.489 4.934 261.431 4.940 258.688 4.946 260.393 4.952 260.193 4.957 261.142 4.963 265.845 4.969 263.298 4.975 261.919 4.981 261.784 4.986 261.543 4.992 261.338 4.998 261.266 5.004 261.292 5.010 261.369 5.016 261.489 5.021 261.638 5.027 261.759 5.033 261.875 5.039 261.980 5.045 262.092 5.050 262.145 5.056 262.070 5.062 262.177 5.068 262.172 5.074 262.156 5.079 262.185 5.085 262.185 5.091 262.190 5.097 262.165 5.103 262.180 5.108 262.200 5.114 262.286 5.120 262.381 5.126 262.499 5.132 262.562 5.137 262.591 5.143 262.580 5.149 262.571 5.155 262.572 5.161 262.582 5.166 262.607 5.172 262.605 5.178 262.623 5.184 262.597 5.190 262.580 5.195 262.547 5.201 262.569 5.207 263.025 5.213 265.897 5.219 264.523 5.224 269.776 5.230 269.707 5.236 309.140 5.242 310.106 5.248 309.790 5.254 309.731 5.259 309.806 5.265 309.881 5.271 309.415 5.277 309.672 5.283 309.658 5.288 309.440 5.294 309.223 5.300 309.342 5.306 309.289 5.312 309.237 5.317 309.327 5.323 309.286 5.329 309.246 5.335 309.205 5.341 309.165 5.346 309.288 5.352 309.415 5.358 309.196 5.364 309.328 5.370 308.895 5.375 308.065 5.381 307.148 5.387 306.231 5.393 305.314 5.399 307.441 5.404 309.430 5.410 308.373 5.416 308.411 5.422 308.448 5.428 302.316 5.433 299.864 5.439 301.484 5.445 316.310 5.451 179.009 5.457 178.867 5.462 175.151 5.468 176.686 5.474 176.880 5.480 175.967 5.486 174.692 5.492 173.008 5.497 172.219 5.503 172.409 5.509 172.532 5.515 172.688 5.521 172.845 5.526 173.001 5.532 172.735 5.538 172.780 5.544 172.833 5.550 172.899 5.555 172.990 5.561 173.100 5.567 173.210 5.573 173.320 5.579 173.430 5.584 173.539 5.590 173.649 5.596 173.608 5.602 173.670 5.608 173.732 5.613 173.794 5.619 173.857 5.625 173.919 5.631 173.981 5.637 174.092 5.642 174.203 5.648 174.314 5.654 174.425 5.660 174.235 5.666 174.316 5.671 173.481 5.677 172.843 5.683 172.206 5.689 173.284 5.695 172.828 5.700 172.778 5.706 174.250 5.712 174.879 5.718 174.171 5.724 173.462 5.730 172.754 5.735 172.045 5.741 173.050 5.747 172.659 5.753 172.592 5.759 174.087 5.764 173.210 5.770 175.021 5.776 174.197 5.782 174.148 5.788 174.099 5.793 174.050 5.799 174.001 5.805 173.952 5.811 175.642 5.817 176.389 5.822 179.384 5.828 0.000 5.834 0.000 5.840 0.000 5.846 0.000 5.851 0.000 5.857 0.000 5.863 0.000 5.869 0.000 5.875 0.000 5.880 0.000 5.886 0.000 5.892 0.000 5.898 0.000 5.904 0.000 5.909 0.000 5.915 0.000 5.921 0.000 5.927 0.000 5.933 0.000 5.939 0.000 5.944 0.000 5.950 0.000 5.956 0.000 5.962 0.000 5.968 0.000 5.973 0.000 5.979 0.000 5.985 0.000 5.991 0.000 5.997 0.000 6.002 0.000 6.008 0.000 6.014 0.000 6.020 0.000 6.026 0.000 6.031 0.000 6.037 0.000 6.043 0.000 6.049 0.000 6.055 0.000 6.060 0.000 6.066 0.000 6.072 0.000 6.078 0.000 6.084 0.000 6.089 0.000 6.095 0.000 6.101 0.000 6.107 0.000 6.113 0.000 6.118 0.000 6.124 0.000 6.130 0.000 6.136 0.000 6.142 0.000 6.147 0.000 6.153 0.000 6.159 0.000 6.165 0.000 6.171 0.000 6.177 0.000 6.182 0.000 6.188 0.000 6.194 0.000 6.200 0.000 6.206 0.000 6.211 0.000 6.217 0.000 6.223 0.000 6.229 0.000 6.235 0.000 6.240 0.000 6.246 0.000 6.252 0.000 6.258 0.000 6.264 0.000 6.269 0.000 6.275 0.000 6.281 0.000 6.287 0.000 6.293 0.000 6.298 0.000 6.304 0.000 6.310 0.000 6.316 0.000 6.322 0.000 6.327 0.000 6.333 171.522 6.339 171.522 6.345 173.237 6.351 173.237 6.356 173.637 6.362 174.037 6.368 174.437 6.374 173.162 6.380 173.545 6.385 173.927 6.391 173.587 6.397 173.485 6.403 173.401 6.409 173.371 6.415 173.402 6.420 173.472 6.426 173.546 6.432 173.613 6.438 173.680 6.444 173.766 6.449 173.851 6.455 173.942 6.461 173.919 6.467 173.918 6.473 173.936 6.478 173.992 6.484 174.089 6.490 174.212 6.496 174.322 6.502 174.352 6.507 174.389 6.513 174.426 6.519 174.495 6.525 174.526 6.531 174.534 6.536 174.600 6.542 174.638 6.548 174.688 6.554 174.722 6.560 174.737 6.565 174.730 6.571 174.687 6.577 174.629 6.583 174.611 6.589 174.668 6.594 174.761 6.600 174.797 6.606 174.803 6.612 174.786 6.618 174.790 6.623 174.812 6.629 174.843 6.635 174.868 6.641 174.891 6.647 174.908 6.653 174.909 6.658 174.895 6.664 174.875 6.670 174.866 6.676 174.885 6.682 174.926 6.687 174.956 6.693 174.926 6.699 174.906 6.705 174.878 6.711 174.874 6.716 174.878 6.722 174.869 6.728 174.845 6.734 174.821 6.740 174.813 6.745 174.848 6.751 174.927 6.757 175.003 6.763 175.027 6.769 175.010 6.774 174.986 6.780 174.978 6.786 174.983 6.792 174.990 6.798 174.985 6.803 174.967 6.809 174.936 6.815 174.906 6.821 174.882 6.827 174.854 6.832 174.818 6.838 174.784 6.844 174.771 6.850 174.778 6.856 174.778 6.861 174.748 6.867 174.717 6.873 174.720 6.879 174.761 6.885 174.800 6.891 174.722 6.896 174.736 6.902 174.696 6.908 174.691 6.914 174.708 6.920 174.719 6.925 174.722 6.931 174.742 6.937 174.710 6.943 174.680 6.949 174.648 6.954 174.636 6.960 174.623 6.966 174.592 6.972 174.550 6.978 174.514 6.983 174.489 6.989 174.469 6.995 174.460 7.001 174.458 7.007 174.467 7.012 174.486 7.018 174.521 7.024 174.571 7.030 174.625 7.036 174.669 7.041 174.694 7.047 174.707 7.053 174.709 7.059 174.694 7.065 174.665 7.070 174.645 7.076 174.651 7.082 174.669 7.088 174.682 7.094 174.668 7.100 174.633 7.105 174.597 7.111 174.580 7.117 174.584 7.123 174.605 7.129 174.654 7.134 174.710 7.140 174.767 7.146 174.764 7.152 174.774 7.158 174.801 7.163 174.822 7.169 174.817 7.175 174.801 7.181 174.799 7.187 174.767 7.192 174.777 7.198 174.740 7.204 174.702 7.210 174.669 7.216 174.645 7.221 174.637 7.227 174.647 7.233 174.656 7.239 174.660 7.245 174.669 7.250 174.687 7.256 174.710 7.262 174.726 7.268 174.742 7.274 174.766 7.279 174.809 7.285 174.856 7.291 174.896 7.297 174.926 7.303 174.945 7.308 174.958 7.314 174.967 7.320 174.970 7.326 174.972 7.332 174.962 7.338 174.939 7.343 174.909 7.349 174.886 7.355 174.874 7.361 174.881 7.367 174.899 7.372 174.911 7.378 174.914 7.384 174.913 7.390 174.931 7.396 174.968 7.401 175.004 7.407 175.030 7.413 175.039 7.419 175.038 7.425 175.038 7.430 175.038 7.436 175.034 7.442 175.030 7.448 175.031 7.454 175.085 7.459 175.025 7.465 175.018 7.471 175.014 7.477 175.009 7.483 174.996 7.488 174.977 7.494 174.975 7.500 174.986 7.506 174.992 7.512 174.970 7.517 174.935 7.523 174.906 7.529 174.895 7.535 174.901 7.541 174.918 7.546 174.934 7.552 174.941 7.558 174.947 7.564 174.963 7.570 174.988 7.576 175.001 7.581 174.994 7.587 174.986 7.593 174.993 7.599 175.005 7.605 175.015 7.610 175.024 7.616 175.038 7.622 175.048 7.628 175.044 7.634 175.032 7.639 175.026 7.645 175.026 7.651 175.034 7.657 175.059 7.663 175.088 7.668 175.099 7.674 175.086 7.680 175.071 7.686 175.072 7.692 175.078 7.697 175.066 7.703 175.031 7.709 174.997 7.715 174.979 7.721 174.978 7.726 174.986 7.732 174.992 7.738 175.005 7.744 175.025 7.750 175.042 7.755 175.044 7.761 175.028 7.767 175.010 7.773 175.017 7.779 175.051 7.784 175.089 7.790 175.104 7.796 175.100 7.802 175.084 7.808 175.073 7.814 175.072 7.819 175.073 7.825 175.069 7.831 175.076 7.837 175.094 7.843 175.107 7.848 175.097 7.854 175.073 7.860 175.058 7.866 175.063 7.872 175.077 7.877 175.084 7.883 175.088 7.889 175.095 7.895 175.112 7.901 175.134 7.906 175.150 7.912 175.156 7.918 175.161 7.924 175.171 7.930 175.184 7.935 175.187 7.941 175.177 7.947 175.156 7.953 175.136 7.959 175.124 7.964 175.119 7.970 175.114 7.976 175.107 7.982 175.100 7.988 175.091 7.993 175.074 7.999 175.055 8.005 175.039 8.011 175.030 8.017 175.031 8.022 175.035 8.028 175.037 8.034 175.029 8.040 175.022 8.046 175.020 8.052 175.020 8.057 175.021 8.063 175.028 8.069 175.037 8.075 175.029 8.081 175.009 8.086 174.995 8.092 174.995 8.098 174.991 8.104 174.980 8.110 174.975 8.115 174.994 8.121 175.025 8.127 175.060 8.133 175.083 8.139 175.104 8.144 175.126 8.150 175.151 8.156 175.166 8.162 175.172 8.168 175.170 8.173 175.171 8.179 175.168 8.185 175.165 8.191 175.165 8.197 175.170 8.202 175.180 8.208 175.189 8.214 175.182 8.220 175.164 8.226 175.145 8.231 175.132 8.237 175.135 8.243 175.147 8.249 175.160 8.255 175.169 8.260 175.178 8.266 175.185 8.272 175.192 8.278 175.203 8.284 175.221 8.290 175.231 8.295 175.230 8.301 175.227 8.307 175.232 8.313 175.245 8.319 175.257 8.324 175.257 8.330 175.263 8.336 175.286 8.342 175.324 8.348 175.359 8.353 175.375 8.359 175.378 8.365 175.385 8.371 175.401 8.377 175.422 8.382 175.436 8.388 175.453 8.394 175.414 8.400 175.398 8.406 175.394 8.411 175.401 8.417 175.409 8.423 175.421 8.429 175.437 8.435 175.454 8.440 175.473 8.446 175.497 8.452 175.521 8.458 175.533 8.464 175.538 8.469 175.543 8.475 175.549 8.481 175.552 8.487 175.553 8.493 175.558 8.499 175.569 8.504 175.578 8.510 175.583 8.516 175.580 8.522 175.576 8.528 175.574 8.533 175.575 8.539 175.569 8.545 175.559 8.551 175.548 8.557 175.549 8.562 175.555 8.568 175.562 8.574 175.572 8.580 175.578 8.586 175.574 8.591 175.565 8.597 175.551 8.603 175.530 8.609 175.503 8.615 175.475 8.620 175.464 8.626 175.470 8.632 177.225 8.638 178.105 8.644 177.628 8.649 177.151 8.655 174.907 8.661 177.018 8.667 174.660 8.673 175.245 8.678 175.241 8.684 176.819 8.690 177.632 8.696 175.693 8.702 175.601 8.707 175.508 8.713 175.485 8.719 175.232 8.725 174.979 8.731 175.517 8.737 176.055 8.742 180.125 8.748 179.967 8.754 0.000 8.760 0.000 8.766 0.000 8.771 0.000 8.777 0.000 8.783 0.000 8.789 0.000 8.795 0.000 8.800 0.000 8.806 0.000 8.812 0.000 8.818 0.000 8.824 0.000 8.829 0.000 8.835 0.000 8.841 0.000 8.847 0.000 8.853 0.000 8.858 0.000 8.864 0.000 8.870 0.000 8.876 0.000 8.882 0.000 8.887 0.000 8.893 0.000 8.899 0.000 8.905 0.000 8.911 0.000 8.916 0.000 8.922 0.000 8.928 0.000 8.934 0.000 8.940 0.000 8.945 0.000 8.951 0.000 8.957 0.000 8.963 0.000 8.969 0.000 8.975 0.000 8.980 0.000 8.986 0.000 8.992 0.000 8.998 0.000 9.004 0.000 9.009 0.000 9.015 0.000 9.021 0.000 9.027 0.000 9.033 0.000 9.038 0.000 9.044 0.000 9.050 0.000 9.056 0.000 9.062 0.000 9.067 0.000 9.073 0.000 9.079 0.000 9.085 0.000 9.091 0.000 9.096 0.000 9.102 0.000 9.108 0.000 9.114 0.000 9.120 0.000 9.125 0.000 9.131 0.000 9.137 0.000 9.143 0.000 9.149 0.000 9.154 0.000 9.160 0.000 9.166 0.000 9.172 0.000 9.178 0.000 9.183 0.000 9.189 0.000 9.195 0.000 9.201 0.000 9.207 0.000 9.213 0.000 9.218 0.000 9.224 0.000 9.230 0.000 9.236 0.000 9.242 0.000 9.247 0.000 9.253 0.000 9.259 0.000 9.265 0.000 9.271 0.000 9.276 0.000 9.282 0.000 9.288 0.000 9.294 0.000 9.300 355.917 9.305 352.358 9.311 351.624 9.317 350.890 9.323 352.053 9.329 351.576 9.334 352.613 9.340 352.777 9.346 353.047 9.352 352.590 9.358 353.244 9.363 353.275 9.369 353.294 9.375 353.315 9.381 353.346 9.387 353.403 9.392 353.455 9.398 353.393 9.404 353.322 9.410 353.147 9.416 352.979 9.421 352.847 9.427 352.758 9.433 352.726 9.439 352.778 9.445 352.911 9.451 353.100 9.456 353.288 9.462 353.423 9.468 353.528 9.474 353.596 9.480 353.624 9.485 353.616 9.491 353.602 9.497 353.615 9.503 353.666 9.509 353.717 9.514 353.764 9.520 353.820 9.526 353.887 9.532 353.949 9.538 353.998 9.543 354.055 9.549 354.138 9.555 354.279 9.561 354.529 9.567 354.897 9.572 355.293 9.578 355.219 9.584 355.372 9.590 355.524 9.596 355.677 9.601 355.829 9.607 352.422 9.613 352.588 9.619 350.403 9.625 351.707 9.630 351.721 9.636 351.796 9.642 351.887 9.648 351.997 9.654 352.075 9.660 352.100 9.665 352.106 9.671 352.135 9.677 352.193 9.683 352.275 9.689 352.364 9.694 352.448 9.700 352.526 9.706 352.596 9.712 352.660 9.718 352.719 9.723 352.785 9.729 352.896 9.735 353.060 9.741 353.248 9.747 353.430 9.752 353.585 9.758 353.763 9.764 354.062 9.770 354.576 9.776 355.329 9.781 355.157 9.787 354.986 9.793 354.814 9.799 354.643 9.805 354.471 9.810 354.300 9.816 357.670 9.822 355.699 9.828 358.554 9.834 357.433 9.839 357.249 9.845 356.597 9.851 355.944 9.857 355.291 9.863 354.639 9.868 361.066 9.874 0.000 9.880 0.000 9.886 0.000 9.892 0.000 9.898 0.000 9.903 0.000 9.909 0.000 9.915 0.000 9.921 0.000 9.927 0.000 9.932 0.000 9.938 0.000 9.944 0.000 9.950 0.000 9.956 0.000 9.961 0.000 9.967 0.000 9.973 0.000 9.979 0.000 9.985 0.000 9.990 0.000 9.996 0.000 10.002 0.000 10.008 0.000 10.014 0.000 10.019 0.000 10.025 0.000 10.031 0.000 10.037 0.000 10.043 0.000 10.048 0.000 10.054 0.000 mir_eval-0.8.2/tests/data/melody/ref04.txt000066400000000000000000001752671475740344600204040ustar00rootroot000000000000000.000 0.000 0.006 0.000 0.012 0.000 0.017 0.000 0.023 350.008 0.029 348.980 0.035 348.583 0.041 348.536 0.046 348.900 0.052 348.903 0.058 349.000 0.064 349.015 0.070 349.120 0.075 349.482 0.081 349.419 0.087 349.280 0.093 349.227 0.099 349.251 0.104 349.320 0.110 349.353 0.116 349.389 0.122 349.332 0.128 349.173 0.134 349.085 0.139 348.917 0.145 348.685 0.151 348.467 0.157 348.424 0.163 348.544 0.168 348.803 0.174 348.933 0.180 348.907 0.186 348.806 0.192 348.682 0.197 348.583 0.203 348.556 0.209 348.607 0.215 348.779 0.221 349.029 0.226 349.249 0.232 349.419 0.238 349.543 0.244 349.587 0.250 349.644 0.255 349.765 0.261 349.922 0.267 350.040 0.273 350.161 0.279 350.255 0.284 350.377 0.290 350.540 0.296 350.674 0.302 350.781 0.308 350.869 0.313 350.881 0.319 350.816 0.325 350.658 0.331 350.463 0.337 350.258 0.342 350.060 0.348 349.855 0.354 349.695 0.360 349.546 0.366 349.392 0.372 349.154 0.377 349.030 0.383 349.055 0.389 349.283 0.395 349.489 0.401 349.657 0.406 349.844 0.412 350.038 0.418 350.244 0.424 350.421 0.430 350.566 0.435 350.723 0.441 350.903 0.447 350.850 0.453 350.681 0.459 350.456 0.464 350.298 0.470 350.235 0.476 350.298 0.482 350.019 0.488 350.002 0.493 349.942 0.499 349.835 0.505 349.759 0.511 349.734 0.517 349.729 0.522 349.763 0.528 349.841 0.534 349.984 0.540 350.211 0.546 350.425 0.551 350.542 0.557 350.538 0.563 350.448 0.569 350.258 0.575 350.054 0.580 349.902 0.586 349.763 0.592 349.591 0.598 349.377 0.604 349.097 0.610 348.594 0.615 347.822 0.621 346.865 0.627 346.443 0.633 346.792 0.639 347.628 0.644 348.175 0.650 348.557 0.656 348.941 0.662 319.328 0.668 317.728 0.673 318.234 0.679 319.082 0.685 355.356 0.691 323.637 0.697 397.528 0.702 392.324 0.708 385.883 0.714 383.842 0.720 378.476 0.726 333.245 0.731 334.738 0.737 336.702 0.743 520.753 0.749 520.913 0.755 521.022 0.760 521.010 0.766 520.800 0.772 520.242 0.778 519.470 0.784 519.090 0.789 519.351 0.795 520.280 0.801 521.418 0.807 522.034 0.813 522.332 0.819 522.481 0.824 522.591 0.830 522.591 0.836 522.582 0.842 522.554 0.848 522.581 0.853 522.319 0.859 522.123 0.865 522.130 0.871 522.136 0.877 522.440 0.882 522.706 0.888 522.523 0.894 522.725 0.900 522.966 0.906 522.664 0.911 522.550 0.917 523.722 0.923 518.965 0.929 474.977 0.935 465.298 0.940 465.582 0.946 465.790 0.952 465.920 0.958 465.876 0.964 466.332 0.969 466.355 0.975 466.287 0.981 466.163 0.987 466.092 0.993 466.239 0.998 466.200 1.004 465.825 1.010 465.736 1.016 465.615 1.022 465.435 1.027 465.459 1.033 465.619 1.039 465.862 1.045 465.998 1.051 466.125 1.057 466.201 1.062 466.207 1.068 466.227 1.074 466.217 1.080 466.269 1.086 466.359 1.091 466.601 1.097 466.240 1.103 444.607 1.109 435.293 1.115 380.829 1.120 341.674 1.126 343.585 1.132 344.762 1.138 349.102 1.144 349.237 1.149 349.545 1.155 349.576 1.161 349.430 1.167 349.283 1.173 349.240 1.178 349.314 1.184 349.320 1.190 349.360 1.196 349.361 1.202 349.350 1.207 349.255 1.213 349.081 1.219 348.859 1.225 348.614 1.231 348.440 1.236 348.463 1.242 348.676 1.248 348.874 1.254 348.938 1.260 348.837 1.265 348.730 1.271 348.647 1.277 348.570 1.283 348.581 1.289 348.696 1.295 348.915 1.300 349.188 1.306 349.441 1.312 349.524 1.318 349.568 1.324 349.650 1.329 349.734 1.335 349.850 1.341 350.024 1.347 350.090 1.353 350.184 1.358 350.306 1.364 350.457 1.370 350.617 1.376 350.744 1.382 350.841 1.387 350.879 1.393 350.856 1.399 350.753 1.405 350.568 1.411 350.363 1.416 350.160 1.422 349.935 1.428 349.750 1.434 349.594 1.440 349.456 1.445 349.299 1.451 349.074 1.457 349.042 1.463 349.154 1.469 349.425 1.474 349.565 1.480 349.759 1.486 349.946 1.492 350.141 1.498 350.317 1.503 350.492 1.509 350.639 1.515 350.836 1.521 350.873 1.527 350.767 1.533 350.544 1.538 350.356 1.544 350.255 1.550 350.318 1.556 350.071 1.562 349.975 1.567 349.986 1.573 349.878 1.579 349.797 1.585 349.760 1.591 349.737 1.596 349.756 1.602 349.811 1.608 349.921 1.614 350.104 1.620 350.333 1.625 350.509 1.631 350.555 1.637 350.425 1.643 350.318 1.649 350.136 1.654 349.963 1.660 349.828 1.666 349.695 1.672 349.517 1.678 349.259 1.683 348.915 1.689 348.242 1.695 347.355 1.701 346.540 1.707 346.572 1.712 347.278 1.718 348.244 1.724 348.669 1.730 348.973 1.736 349.140 1.741 349.208 1.747 349.242 1.753 349.257 1.759 349.292 1.765 349.321 1.771 349.391 1.776 349.448 1.782 349.496 1.788 349.557 1.794 349.646 1.800 349.784 1.805 349.958 1.811 350.120 1.817 350.239 1.823 350.305 1.829 350.299 1.834 350.238 1.840 350.153 1.846 350.096 1.852 350.082 1.858 350.085 1.863 350.089 1.869 350.103 1.875 350.134 1.881 350.193 1.887 350.335 1.892 350.567 1.898 350.887 1.904 351.168 1.910 351.225 1.916 351.143 1.921 351.003 1.927 350.899 1.933 350.793 1.939 350.684 1.945 350.597 1.950 350.531 1.956 350.445 1.962 350.282 1.968 350.285 1.974 350.247 1.980 350.083 1.985 349.763 1.991 349.393 1.997 349.037 2.003 348.835 2.009 348.761 2.014 348.788 2.020 348.879 2.026 349.000 2.032 349.041 2.038 349.017 2.043 348.983 2.049 348.995 2.055 348.948 2.061 348.826 2.067 348.608 2.072 348.306 2.078 347.919 2.084 347.943 2.090 348.188 2.096 348.462 2.101 348.591 2.107 348.618 2.113 348.632 2.119 348.679 2.125 348.780 2.130 348.898 2.136 349.013 2.142 349.118 2.148 349.251 2.154 349.458 2.159 349.751 2.165 350.080 2.171 350.321 2.177 350.378 2.183 350.257 2.188 350.044 2.194 349.911 2.200 349.860 2.206 349.833 2.212 349.811 2.218 349.802 2.223 349.799 2.229 349.815 2.235 349.820 2.241 349.811 2.247 349.811 2.252 349.894 2.258 350.147 2.264 350.767 2.270 351.103 2.276 351.075 2.281 350.616 2.287 350.139 2.293 349.976 2.299 349.878 2.305 349.815 2.310 349.717 2.316 349.589 2.322 349.451 2.328 349.202 2.334 348.863 2.339 348.606 2.345 348.644 2.351 349.011 2.357 349.548 2.363 349.888 2.368 350.071 2.374 350.191 2.380 350.297 2.386 350.373 2.392 350.429 2.397 350.475 2.403 350.526 2.409 350.468 2.415 350.349 2.421 350.201 2.426 350.195 2.432 350.310 2.438 350.220 2.444 350.115 2.450 350.014 2.456 349.843 2.461 349.687 2.467 349.621 2.473 349.641 2.479 349.794 2.485 350.013 2.490 350.170 2.496 350.188 2.502 350.042 2.508 349.907 2.514 349.864 2.519 349.868 2.525 349.885 2.531 349.890 2.537 349.846 2.543 349.810 2.548 349.775 2.554 349.726 2.560 349.666 2.566 349.564 2.572 349.489 2.577 349.397 2.583 349.230 2.589 349.050 2.595 349.164 2.601 349.458 2.606 349.708 2.612 349.568 2.618 349.587 2.624 349.534 2.630 349.476 2.635 349.361 2.641 349.295 2.647 349.233 2.653 349.214 2.659 349.244 2.664 349.275 2.670 349.304 2.676 349.336 2.682 349.385 2.688 349.436 2.694 349.455 2.699 349.414 2.705 349.232 2.711 349.144 2.717 349.227 2.723 349.475 2.728 349.700 2.734 349.770 2.740 349.812 2.746 349.846 2.752 349.893 2.757 349.993 2.763 350.123 2.769 350.283 2.775 350.480 2.781 350.676 2.786 350.939 2.792 351.008 2.798 350.972 2.804 350.838 2.810 350.761 2.815 350.741 2.821 350.718 2.827 350.695 2.833 350.654 2.839 350.632 2.844 350.499 2.850 350.512 2.856 350.579 2.862 350.614 2.868 350.508 2.873 350.362 2.879 350.421 2.885 350.643 2.891 346.636 2.897 346.949 2.902 378.915 2.908 391.871 2.914 390.818 2.920 391.267 2.926 391.591 2.932 391.678 2.937 391.584 2.943 392.099 2.949 392.213 2.955 392.182 2.961 391.938 2.966 391.927 2.972 392.101 2.978 392.163 2.984 392.107 2.990 391.977 2.995 391.844 3.001 391.769 3.007 391.552 3.013 391.113 3.019 390.998 3.024 391.175 3.030 391.391 3.036 391.460 3.042 391.436 3.048 416.835 3.053 368.341 3.059 362.207 3.065 359.617 3.071 389.377 3.077 356.017 3.082 587.515 3.088 587.333 3.094 586.879 3.100 586.561 3.106 586.284 3.111 585.771 3.117 584.919 3.123 584.577 3.129 584.297 3.135 584.414 3.140 584.604 3.146 584.841 3.152 584.918 3.158 584.618 3.164 583.774 3.170 583.034 3.175 583.105 3.181 583.945 3.187 585.191 3.193 586.235 3.199 586.880 3.204 587.059 3.210 586.883 3.216 577.417 3.222 574.697 3.228 571.657 3.233 565.915 3.239 562.903 3.245 530.992 3.251 529.570 3.257 521.801 3.262 521.505 3.268 521.295 3.274 520.987 3.280 520.487 3.286 520.329 3.291 520.403 3.297 520.811 3.303 520.961 3.309 521.037 3.315 520.749 3.320 520.423 3.326 519.662 3.332 519.190 3.338 519.048 3.344 519.669 3.349 521.021 3.355 521.713 3.361 521.690 3.367 513.318 3.373 511.783 3.379 510.317 3.384 504.786 3.390 505.958 3.396 467.623 3.402 465.475 3.408 465.617 3.413 465.686 3.419 465.691 3.425 462.560 3.431 462.691 3.437 462.699 3.442 462.745 3.448 465.099 3.454 465.019 3.460 465.542 3.466 465.677 3.471 466.012 3.477 465.794 3.483 466.163 3.489 466.051 3.495 465.843 3.500 465.993 3.506 458.330 3.512 456.789 3.518 455.938 3.524 451.470 3.529 449.911 3.535 447.364 3.541 445.474 3.547 443.159 3.553 449.719 3.558 413.080 3.564 412.238 3.570 423.683 3.576 392.221 3.582 392.235 3.587 392.104 3.593 392.121 3.599 392.009 3.605 391.863 3.611 391.486 3.617 391.316 3.622 391.291 3.628 391.469 3.634 391.619 3.640 391.632 3.646 391.585 3.651 391.499 3.657 391.545 3.663 391.599 3.669 391.681 3.675 391.692 3.680 391.760 3.686 391.826 3.692 392.010 3.698 392.250 3.704 392.537 3.709 392.779 3.715 392.988 3.721 393.233 3.727 393.362 3.733 393.475 3.738 393.735 3.744 393.967 3.750 394.008 3.756 393.989 3.762 393.889 3.767 393.682 3.773 393.392 3.779 393.089 3.785 392.857 3.791 392.710 3.796 392.585 3.802 392.406 3.808 392.150 3.814 391.868 3.820 391.609 3.825 391.818 3.831 392.079 3.837 392.487 3.843 392.689 3.849 393.006 3.855 393.268 3.860 393.422 3.866 393.607 3.872 393.769 3.878 393.691 3.884 393.498 3.889 393.226 3.895 393.047 3.901 392.956 3.907 392.818 3.913 392.691 3.918 392.587 3.924 392.535 3.930 392.527 3.936 392.566 3.942 392.711 3.947 392.807 3.953 393.023 3.959 393.299 3.965 393.489 3.971 393.556 3.976 393.414 3.982 393.219 3.988 392.916 3.994 392.730 4.000 392.536 4.005 392.528 4.011 392.267 4.017 391.902 4.023 391.288 4.029 390.275 4.034 389.180 4.040 388.839 4.046 389.226 4.052 390.130 4.058 390.860 4.063 391.401 4.069 391.659 4.075 391.816 4.081 391.839 4.087 391.905 4.093 391.963 4.098 392.047 4.104 392.172 4.110 392.297 4.116 392.449 4.122 392.654 4.127 392.873 4.133 392.968 4.139 392.989 4.145 392.936 4.151 392.835 4.156 392.773 4.162 392.749 4.168 392.769 4.174 392.773 4.180 392.821 4.185 392.906 4.191 393.013 4.197 393.135 4.203 393.321 4.209 393.509 4.214 393.788 4.220 393.824 4.226 393.619 4.232 393.676 4.238 393.650 4.243 393.621 4.249 393.578 4.255 393.533 4.261 393.423 4.267 393.206 4.272 393.092 4.278 392.922 4.284 392.657 4.290 392.352 4.296 392.000 4.301 391.615 4.307 391.367 4.313 391.291 4.319 391.364 4.325 391.515 4.331 391.546 4.336 391.523 4.342 391.404 4.348 391.337 4.354 391.139 4.360 390.917 4.365 390.547 4.371 390.280 4.377 390.315 4.383 390.524 4.389 390.791 4.394 390.960 4.400 391.051 4.406 391.132 4.412 391.276 4.418 391.447 4.423 391.638 4.429 391.877 4.435 392.196 4.441 392.616 4.447 393.010 4.452 393.217 4.458 393.169 4.464 392.933 4.470 392.734 4.476 392.659 4.481 392.658 4.487 392.662 4.493 392.649 4.499 392.624 4.505 392.610 4.510 392.574 4.516 391.725 4.522 391.187 4.528 879.515 4.534 879.378 4.540 878.914 4.545 878.810 4.551 877.932 4.557 878.280 4.563 879.356 4.569 879.745 4.574 879.682 4.580 880.013 4.586 880.127 4.592 880.466 4.598 880.833 4.603 880.966 4.609 881.043 4.615 881.087 4.621 881.252 4.627 881.378 4.632 881.445 4.638 881.435 4.644 881.551 4.650 881.867 4.656 881.902 4.661 882.068 4.667 882.075 4.673 882.217 4.679 881.915 4.685 881.140 4.690 882.810 4.696 910.247 4.702 931.482 4.708 931.117 4.714 931.274 4.719 930.135 4.725 930.520 4.731 931.538 4.737 932.081 4.743 931.891 4.748 932.260 4.754 932.544 4.760 933.080 4.766 933.553 4.772 933.399 4.778 933.379 4.783 933.468 4.789 933.565 4.795 933.622 4.801 933.636 4.807 933.661 4.812 934.002 4.818 934.424 4.824 934.112 4.830 934.217 4.836 933.560 4.841 932.482 4.847 930.281 4.853 928.469 4.859 929.341 4.865 929.181 4.870 928.772 4.876 929.921 4.882 931.185 4.888 931.515 4.894 931.828 4.899 932.112 4.905 932.546 4.911 932.944 4.917 933.344 4.923 933.411 4.928 933.462 4.934 933.526 4.940 933.491 4.946 933.535 4.952 933.599 4.957 933.895 4.963 934.208 4.969 934.433 4.975 933.813 4.981 933.897 4.986 933.423 4.992 933.751 4.998 934.683 5.004 935.372 5.010 935.717 5.016 935.211 5.021 934.705 5.027 933.701 5.033 932.732 5.039 932.057 5.045 931.883 5.050 932.203 5.056 932.927 5.062 933.719 5.068 934.079 5.074 931.962 5.079 930.588 5.085 930.850 5.091 932.946 5.097 933.408 5.103 933.574 5.108 933.817 5.114 934.128 5.120 934.554 5.126 935.396 5.132 938.773 5.137 934.577 5.143 933.775 5.149 933.896 5.155 933.289 5.161 931.207 5.166 931.207 5.172 818.349 5.178 705.613 5.184 705.613 5.190 705.613 5.195 705.613 5.201 703.287 5.207 703.287 5.213 700.968 5.219 698.657 5.224 698.657 5.230 696.353 5.236 694.592 5.242 696.290 5.248 697.359 5.254 697.895 5.259 698.086 5.265 698.159 5.271 698.136 5.277 697.794 5.283 697.436 5.288 697.090 5.294 696.920 5.300 697.067 5.306 696.565 5.312 696.928 5.317 697.537 5.323 697.679 5.329 697.322 5.335 696.805 5.341 696.418 5.346 696.742 5.352 697.186 5.358 697.421 5.364 697.438 5.370 697.196 5.375 696.739 5.381 696.291 5.387 696.140 5.393 696.314 5.399 696.782 5.404 697.071 5.410 697.132 5.416 696.765 5.422 695.465 5.428 693.755 5.433 692.379 5.439 692.426 5.445 694.039 5.451 695.611 5.457 696.691 5.462 697.342 5.468 697.682 5.474 697.801 5.480 697.782 5.486 697.646 5.492 697.445 5.497 697.217 5.503 697.231 5.509 697.607 5.515 698.069 5.521 698.589 5.526 695.878 5.532 695.557 5.538 695.128 5.544 694.362 5.550 693.634 5.555 693.186 5.561 693.032 5.567 0.000 5.573 0.000 5.579 0.000 5.584 0.000 5.590 0.000 5.596 0.000 5.602 0.000 5.608 0.000 5.613 0.000 5.619 0.000 5.625 0.000 5.631 0.000 5.637 0.000 5.642 0.000 5.648 0.000 5.654 0.000 5.660 0.000 5.666 0.000 5.671 0.000 5.677 0.000 5.683 0.000 5.689 0.000 5.695 0.000 5.700 0.000 5.706 0.000 5.712 0.000 5.718 0.000 5.724 0.000 5.730 585.574 5.735 586.409 5.741 586.559 5.747 586.720 5.753 587.017 5.759 587.322 5.764 587.127 5.770 586.726 5.776 586.478 5.782 586.187 5.788 585.685 5.793 584.828 5.799 584.497 5.805 584.308 5.811 584.443 5.817 584.629 5.822 584.820 5.828 584.904 5.834 584.595 5.840 583.731 5.846 583.013 5.851 583.098 5.857 583.977 5.863 585.296 5.869 586.342 5.875 586.817 5.880 585.229 5.886 595.068 5.892 607.691 5.898 616.231 5.904 621.215 5.909 621.459 5.915 622.015 5.921 622.165 5.927 621.979 5.933 621.334 5.939 620.996 5.944 620.498 5.950 619.697 5.956 619.381 5.962 619.151 5.968 619.198 5.973 619.329 5.979 619.477 5.985 619.547 5.991 619.203 5.997 618.233 6.002 617.732 6.008 618.002 6.014 619.168 6.020 620.520 6.026 621.184 6.031 621.701 6.037 621.780 6.043 622.402 6.049 622.584 6.055 658.188 6.060 676.932 6.066 697.791 6.072 698.136 6.078 698.211 6.084 698.054 6.089 697.499 6.095 697.176 6.101 696.532 6.107 695.518 6.113 695.151 6.118 694.966 6.124 695.048 6.130 695.251 6.136 695.294 6.142 694.866 6.147 693.760 6.153 693.444 6.159 694.203 6.165 695.899 6.171 697.117 6.177 697.766 6.182 698.023 6.188 698.103 6.194 698.085 6.200 697.826 6.206 697.487 6.211 697.112 6.217 696.934 6.223 696.949 6.229 697.268 6.235 696.801 6.240 697.263 6.246 697.675 6.252 697.623 6.258 697.310 6.264 696.812 6.269 696.689 6.275 697.091 6.281 697.401 6.287 697.407 6.293 697.261 6.298 696.880 6.304 696.472 6.310 696.264 6.316 696.440 6.322 696.133 6.327 695.235 6.333 700.582 6.339 726.372 6.345 730.676 6.351 729.740 6.356 785.075 6.362 785.263 6.368 785.742 6.374 783.479 6.380 767.671 6.385 766.551 6.391 765.719 6.397 765.912 6.403 766.959 6.409 768.417 6.415 769.956 6.420 771.797 6.426 773.516 6.432 785.081 6.438 784.970 6.444 785.221 6.449 785.199 6.455 785.359 6.461 785.600 6.467 785.573 6.473 785.312 6.478 784.820 6.484 783.700 6.490 783.941 6.496 784.575 6.502 785.250 6.507 785.792 6.513 786.337 6.519 786.673 6.525 786.990 6.531 786.982 6.536 786.487 6.542 785.656 6.548 785.035 6.554 784.479 6.560 784.016 6.565 783.880 6.571 784.033 6.577 784.502 6.583 784.730 6.589 783.896 6.594 782.685 6.600 782.254 6.606 782.844 6.612 783.816 6.618 784.362 6.623 784.548 6.629 784.811 6.635 785.068 6.641 785.253 6.647 785.025 6.653 783.965 6.658 785.200 6.664 784.962 6.670 743.583 6.676 728.825 6.682 656.104 6.687 622.265 6.693 613.557 6.699 614.267 6.705 614.582 6.711 614.740 6.716 614.865 6.722 619.118 6.728 619.118 6.734 619.294 6.740 619.534 6.745 619.649 6.751 619.392 6.757 618.397 6.763 617.674 6.769 617.910 6.774 619.049 6.780 620.491 6.786 621.133 6.792 621.691 6.798 621.883 6.803 621.946 6.809 621.965 6.815 621.882 6.821 621.552 6.827 621.138 6.832 620.711 6.838 620.433 6.844 620.351 6.850 620.493 6.856 620.967 6.861 621.463 6.867 621.887 6.873 621.880 6.879 621.628 6.885 621.068 6.891 620.534 6.896 620.679 6.902 621.056 6.908 621.363 6.914 621.282 6.920 620.722 6.925 619.935 6.931 617.241 6.937 617.036 6.943 616.201 6.949 612.935 6.954 611.743 6.960 608.135 6.966 605.918 6.972 603.624 6.978 586.704 6.983 586.615 6.989 584.061 6.995 585.654 7.001 585.265 7.007 584.244 7.012 584.119 7.018 584.519 7.024 585.606 7.030 588.085 7.036 588.635 7.041 588.252 7.047 586.996 7.053 584.835 7.059 584.632 7.065 585.358 7.070 586.045 7.076 586.863 7.082 587.331 7.088 587.068 7.094 586.868 7.100 586.933 7.105 587.069 7.111 586.838 7.117 586.160 7.123 585.505 7.129 585.435 7.134 586.082 7.140 586.296 7.146 586.587 7.152 586.682 7.158 586.611 7.163 586.660 7.169 586.889 7.175 586.713 7.181 586.093 7.187 585.731 7.192 585.767 7.198 586.214 7.204 586.616 7.210 586.721 7.216 586.528 7.221 586.118 7.227 585.698 7.233 585.443 7.239 585.570 7.245 585.480 7.250 586.657 7.256 590.459 7.262 606.490 7.268 606.447 7.274 607.654 7.279 620.105 7.285 620.753 7.291 620.790 7.297 621.536 7.303 621.230 7.308 620.066 7.314 619.024 7.320 618.423 7.326 619.012 7.332 619.550 7.338 619.661 7.343 619.150 7.349 618.612 7.355 618.326 7.361 618.166 7.367 618.139 7.372 618.542 7.378 619.625 7.384 620.784 7.390 621.535 7.396 621.914 7.401 621.901 7.407 621.877 7.413 621.911 7.419 621.764 7.425 621.389 7.430 620.915 7.436 620.641 7.442 620.497 7.448 620.332 7.454 620.617 7.459 621.138 7.465 621.845 7.471 622.037 7.477 621.948 7.483 621.496 7.488 620.881 7.494 620.405 7.500 620.715 7.506 621.064 7.512 621.378 7.517 621.413 7.523 621.152 7.529 620.814 7.535 620.414 7.541 620.201 7.546 620.344 7.552 620.733 7.558 621.049 7.564 621.173 7.570 621.086 7.576 620.805 7.581 619.947 7.587 618.222 7.593 616.380 7.599 615.968 7.605 617.149 7.610 619.028 7.616 620.332 7.622 621.157 7.628 621.628 7.634 621.828 7.639 621.834 7.645 621.800 7.651 621.780 7.657 621.709 7.663 621.524 7.668 621.380 7.674 621.481 7.680 621.873 7.686 622.308 7.692 622.694 7.697 623.027 7.703 623.413 7.709 623.665 7.715 623.852 7.721 623.904 7.726 623.796 7.732 623.503 7.738 623.102 7.744 622.647 7.750 622.207 7.755 621.773 7.761 621.511 7.767 621.438 7.773 621.475 7.779 621.258 7.784 620.961 7.790 620.566 7.796 620.179 7.802 619.724 7.808 619.545 7.814 619.588 7.819 619.756 7.825 619.892 7.831 619.918 7.837 619.918 7.843 619.877 7.848 615.287 7.854 650.379 7.860 675.662 7.866 697.742 7.872 698.084 7.877 698.222 7.883 698.045 7.889 697.801 7.895 697.195 7.901 693.168 7.906 693.081 7.912 695.168 7.918 694.975 7.924 695.014 7.930 695.249 7.935 695.279 7.941 694.856 7.947 693.772 7.953 693.432 7.959 694.222 7.964 695.896 7.970 697.128 7.976 697.767 7.982 698.036 7.988 698.100 7.993 698.092 7.999 697.864 8.005 697.533 8.011 697.186 8.017 697.030 8.022 696.981 8.028 697.251 8.034 697.690 8.040 697.873 8.046 697.766 8.052 697.703 8.057 697.296 8.063 696.472 8.069 696.582 8.075 696.956 8.081 697.422 8.086 697.731 8.092 697.794 8.098 0.000 8.104 0.000 8.110 0.000 8.115 0.000 8.121 0.000 8.127 0.000 8.133 522.984 8.139 515.758 8.144 516.350 8.150 522.947 8.156 522.928 8.162 523.159 8.168 522.823 8.173 522.662 8.179 522.508 8.185 522.293 8.191 522.077 8.197 520.128 8.202 519.604 8.208 520.844 8.214 520.731 8.220 520.806 8.226 520.938 8.231 521.101 8.237 521.076 8.243 520.793 8.249 520.208 8.255 519.420 8.260 519.057 8.266 519.369 8.272 520.346 8.278 521.486 8.284 522.153 8.290 522.338 8.295 522.483 8.301 522.583 8.307 522.604 8.313 522.592 8.319 522.631 8.324 522.701 8.330 522.654 8.336 522.379 8.342 522.114 8.348 522.067 8.353 522.222 8.359 522.290 8.365 522.504 8.371 522.789 8.377 523.168 8.382 523.228 8.388 523.077 8.394 522.926 8.400 522.935 8.406 522.917 8.411 522.980 8.417 523.075 8.423 523.137 8.429 523.232 8.435 523.201 8.440 523.014 8.446 522.705 8.452 522.395 8.458 522.005 8.464 521.800 8.469 521.775 8.475 522.017 8.481 522.490 8.487 522.842 8.493 523.036 8.499 523.005 8.504 522.831 8.510 522.471 8.516 521.735 8.522 520.346 8.528 518.500 8.533 517.855 8.539 518.410 8.545 519.967 8.551 521.360 8.557 522.031 8.562 522.319 8.568 522.469 8.574 522.638 8.580 522.726 8.586 522.776 8.591 522.707 8.597 522.544 8.603 522.279 8.609 522.155 8.615 522.302 8.620 522.624 8.626 523.055 8.632 523.288 8.638 523.412 8.644 523.569 8.649 523.777 8.655 524.039 8.661 524.498 8.667 525.107 8.673 525.665 8.678 526.001 8.684 526.351 8.690 526.546 8.696 526.559 8.702 526.481 8.707 526.498 8.713 526.296 8.719 526.018 8.725 525.546 8.731 525.065 8.737 524.697 8.742 524.281 8.748 523.978 8.754 523.750 8.760 523.438 8.766 522.955 8.771 522.426 8.777 522.324 8.783 522.255 8.789 522.376 8.795 522.424 8.800 522.369 8.806 522.204 8.812 522.179 8.818 522.393 8.824 523.022 8.829 524.044 8.835 524.455 8.841 524.227 8.847 523.449 8.853 523.118 8.858 523.087 8.864 523.188 8.870 523.322 8.876 523.409 8.882 523.462 8.887 523.497 8.893 523.528 8.899 522.623 8.905 521.910 8.911 522.057 8.916 523.279 8.922 523.889 8.928 523.823 8.934 523.651 8.940 523.391 8.945 523.008 8.951 522.317 8.957 521.951 8.963 522.091 8.969 522.885 8.975 523.581 8.980 524.004 8.986 524.304 8.992 524.490 8.998 524.621 9.004 524.646 9.009 524.841 9.015 525.379 9.021 526.026 9.027 525.844 9.033 525.236 9.038 524.605 9.044 524.436 9.050 524.480 9.056 524.660 9.062 524.880 9.067 525.108 9.073 525.228 9.079 525.222 9.085 525.031 9.091 524.814 9.096 524.575 9.102 524.311 9.108 523.951 9.114 523.478 9.120 522.807 9.125 522.731 9.131 523.082 9.137 523.724 9.143 523.602 9.149 523.564 9.154 523.545 9.160 523.604 9.166 523.645 9.172 523.745 9.178 523.879 9.183 524.119 9.189 524.750 9.195 525.011 9.201 525.033 9.207 524.527 9.213 524.211 9.218 523.936 9.224 523.618 9.230 523.306 9.236 522.983 9.242 522.570 9.247 522.546 9.253 523.306 9.259 523.531 9.265 522.737 9.271 522.495 9.276 522.534 9.282 522.870 9.288 523.255 9.294 523.586 9.300 523.906 9.305 524.146 9.311 524.638 9.317 0.000 9.323 0.000 9.329 0.000 9.334 0.000 9.340 0.000 9.346 0.000 9.352 0.000 9.358 0.000 9.363 0.000 9.369 0.000 9.375 0.000 9.381 0.000 9.387 0.000 9.392 0.000 9.398 0.000 9.404 0.000 9.410 0.000 9.416 0.000 9.421 0.000 9.427 0.000 9.433 0.000 9.439 0.000 9.445 0.000 9.451 0.000 9.456 0.000 9.462 0.000 9.468 0.000 9.474 0.000 9.480 0.000 9.485 0.000 9.491 0.000 9.497 0.000 9.503 0.000 9.509 0.000 9.514 0.000 9.520 0.000 9.526 0.000 9.532 0.000 9.538 0.000 9.543 0.000 9.549 0.000 9.555 0.000 9.561 0.000 9.567 0.000 9.572 0.000 9.578 0.000 9.584 0.000 9.590 0.000 9.596 0.000 9.601 0.000 9.607 0.000 9.613 0.000 9.619 0.000 9.625 0.000 9.630 0.000 9.636 0.000 9.642 0.000 9.648 0.000 9.654 0.000 9.660 0.000 9.665 0.000 9.671 0.000 9.677 0.000 9.683 0.000 9.689 0.000 9.694 0.000 9.700 0.000 9.706 0.000 9.712 0.000 9.718 0.000 9.723 0.000 9.729 0.000 9.735 0.000 9.741 0.000 9.747 0.000 9.752 0.000 9.758 0.000 9.764 0.000 9.770 0.000 9.776 0.000 9.781 0.000 9.787 0.000 9.793 0.000 9.799 0.000 9.805 0.000 9.810 0.000 9.816 0.000 9.822 0.000 9.828 0.000 9.834 0.000 9.839 0.000 9.845 0.000 9.851 0.000 9.857 0.000 9.863 0.000 9.868 0.000 9.874 0.000 9.880 0.000 9.886 0.000 9.892 0.000 9.898 0.000 9.903 0.000 9.909 0.000 9.915 0.000 9.921 697.547 9.927 697.583 9.932 697.719 9.938 698.050 9.944 698.401 9.950 697.418 9.956 697.038 9.961 697.625 9.967 724.006 9.973 731.897 9.979 724.320 9.985 725.968 9.990 726.394 9.996 760.605 10.002 760.007 10.008 759.373 10.014 758.515 10.019 763.462 10.025 788.035 10.031 788.194 10.037 787.928 10.043 784.862 10.048 784.779 10.054 784.810 10.060 785.051 10.066 784.953 10.072 785.186 10.077 785.189 10.083 785.281 10.089 785.570 10.095 785.624 10.101 785.355 10.106 784.902 10.112 784.702 10.118 783.883 10.124 784.443 10.130 785.121 10.136 785.661 10.141 786.212 10.147 786.585 10.153 786.932 10.159 787.012 10.165 786.636 10.170 785.924 10.176 785.209 10.182 784.606 10.188 784.099 10.194 783.869 10.199 783.997 10.205 784.417 10.211 784.805 10.217 784.167 10.223 782.954 10.228 782.187 10.234 782.553 10.240 783.501 10.246 784.280 10.252 784.491 10.257 784.756 10.263 785.012 10.269 785.302 10.275 785.676 10.281 786.071 10.286 786.283 10.292 786.274 10.298 786.228 10.304 786.378 10.310 787.032 10.315 787.831 10.321 788.408 10.327 788.589 10.333 788.254 10.339 787.747 10.344 786.851 10.350 785.747 10.356 784.808 10.362 784.238 10.368 783.940 10.374 784.025 10.379 784.400 10.385 785.887 10.391 787.410 10.397 787.338 10.403 785.862 10.408 783.756 10.414 783.148 10.420 783.030 10.426 783.395 10.432 784.937 10.437 786.655 10.443 787.480 10.449 787.098 10.455 785.852 10.461 785.123 10.466 784.037 10.472 783.375 10.478 783.552 10.484 784.588 10.490 785.468 10.495 785.731 10.501 786.031 10.507 787.430 10.513 788.263 10.519 788.203 10.524 789.574 10.530 783.956 10.536 749.635 10.542 713.363 10.548 698.165 10.553 697.412 10.559 697.106 10.565 732.303 10.571 731.745 10.577 729.968 10.582 727.833 10.588 724.510 10.594 716.473 10.600 712.496 10.606 708.504 10.612 704.788 10.617 701.969 10.623 693.851 10.629 693.442 10.635 694.286 10.641 695.892 10.646 697.160 10.652 707.684 10.658 708.349 10.664 709.358 10.670 711.055 10.675 713.446 10.681 716.033 10.687 718.525 10.693 720.021 10.699 720.438 10.704 720.486 10.710 720.323 10.716 720.749 10.722 720.903 10.728 0.000 10.733 0.000 10.739 0.000 10.745 0.000 10.751 0.000 10.757 0.000 10.762 0.000 10.768 0.000 10.774 0.000 10.780 0.000 10.786 0.000 10.791 0.000 10.797 0.000 10.803 0.000 10.809 0.000 10.815 0.000 10.820 0.000 10.826 0.000 10.832 0.000 10.838 0.000 10.844 0.000 10.850 0.000 10.855 586.793 10.861 586.526 10.867 586.544 10.873 586.771 10.879 587.067 10.884 587.335 10.890 587.056 10.896 586.578 10.902 586.237 10.908 586.087 10.913 585.195 10.919 584.761 10.925 584.417 10.931 584.318 10.937 584.475 10.942 584.678 10.948 584.827 10.954 584.866 10.960 584.428 10.966 583.524 10.971 582.940 10.977 583.244 10.983 584.288 10.989 585.675 10.995 586.349 11.000 586.703 11.006 586.996 11.012 587.032 11.018 587.049 11.024 587.022 11.029 586.849 11.035 586.593 11.041 586.254 11.047 585.948 11.053 585.642 11.059 585.435 11.064 585.701 11.070 586.242 11.076 586.906 11.082 587.215 11.088 587.150 11.093 586.732 11.099 585.846 11.105 585.328 11.111 585.616 11.117 586.043 11.122 586.505 11.128 586.644 11.134 586.559 11.140 586.402 11.146 586.124 11.151 585.771 11.157 585.525 11.163 585.479 11.169 585.652 11.175 586.016 11.180 586.343 11.186 586.439 11.192 586.358 11.198 586.035 11.204 585.183 11.209 583.456 11.215 581.970 11.221 581.500 11.227 582.804 11.233 584.267 11.238 585.526 11.244 586.094 11.250 586.561 11.256 586.805 11.262 586.951 11.267 587.026 11.273 587.018 11.279 586.995 11.285 586.842 11.291 586.617 11.297 586.449 11.302 586.593 11.308 586.946 11.314 587.383 11.320 587.595 11.326 587.882 11.331 588.335 11.337 588.233 11.343 588.395 11.349 588.590 11.355 588.577 11.360 588.414 11.366 588.140 11.372 587.802 11.378 587.277 11.384 586.762 11.389 586.359 11.395 586.294 11.401 586.427 11.407 586.440 11.413 586.355 11.418 586.141 11.424 585.927 11.430 585.412 11.436 585.101 11.442 584.559 11.447 584.752 11.453 585.084 11.459 585.357 11.465 585.582 11.471 585.777 11.476 585.951 11.482 585.918 11.488 583.618 11.494 582.557 11.500 589.100 11.505 586.803 11.511 587.207 11.517 587.468 11.523 587.645 11.529 587.819 11.535 587.995 11.540 588.200 11.546 588.620 11.552 589.302 11.558 589.995 11.564 590.308 11.569 590.032 11.575 589.491 11.581 589.110 11.587 588.705 11.593 589.634 11.598 590.143 11.604 590.652 11.610 590.506 11.616 590.752 11.622 590.847 11.627 590.774 11.633 589.989 11.639 589.469 11.645 588.992 11.651 588.629 11.656 588.271 11.662 587.887 11.668 587.402 11.674 586.931 11.680 586.786 11.685 586.933 11.691 587.370 11.697 587.858 11.703 588.046 11.709 588.059 11.714 587.934 11.720 587.699 11.726 587.144 11.732 589.707 11.738 0.000 11.743 0.000 11.749 465.354 11.755 465.469 11.761 465.591 11.767 465.779 11.773 465.759 11.778 466.192 11.784 466.400 11.790 466.375 11.796 466.256 11.802 466.164 11.807 466.154 11.813 466.254 11.819 466.160 11.825 465.810 11.831 465.731 11.836 465.582 11.842 465.436 11.848 465.490 11.854 465.646 11.860 465.914 11.865 466.051 11.871 466.138 11.877 466.204 11.883 466.203 11.889 466.203 11.894 466.223 11.900 466.287 11.906 466.336 11.912 466.375 11.918 466.401 11.923 466.439 11.929 466.508 11.935 466.649 11.941 466.938 11.947 467.401 11.952 467.902 11.958 468.272 11.964 468.349 11.970 468.301 11.976 468.248 11.981 468.333 11.987 468.377 11.993 0.000 11.999 0.000 12.005 0.000 12.011 0.000 12.016 0.000 12.022 0.000 12.028 0.000 12.034 0.000 12.040 0.000 12.045 525.977 12.051 523.770 12.057 522.681 12.063 522.522 12.069 522.695 12.074 523.033 12.080 522.905 12.086 523.352 12.092 523.133 12.098 522.668 12.103 522.676 12.109 522.312 12.115 521.980 12.121 521.278 12.127 520.958 12.132 520.716 12.138 520.731 12.144 520.829 12.150 520.930 12.156 521.020 12.161 520.959 12.167 520.675 12.173 519.977 12.179 519.238 12.185 519.039 12.190 519.532 12.196 520.621 12.202 521.656 12.208 522.158 12.214 522.392 12.220 522.520 12.225 522.616 12.231 522.605 12.237 522.603 12.243 522.672 12.249 522.732 12.254 522.643 12.260 522.370 12.266 522.092 12.272 522.020 12.278 522.244 12.283 522.286 12.289 522.550 12.295 522.811 12.301 523.225 12.307 523.167 12.312 522.996 12.318 522.913 12.324 522.940 12.330 522.721 12.336 523.060 12.341 523.089 12.347 523.145 12.353 523.224 12.359 523.173 12.365 522.972 12.370 522.678 12.376 522.306 12.382 521.895 12.388 521.793 12.394 521.818 12.399 522.118 12.405 522.604 12.411 522.939 12.417 523.055 12.423 522.986 12.428 522.775 12.434 522.325 12.440 521.453 12.446 519.868 12.452 518.227 12.458 517.898 12.463 518.771 12.469 520.406 12.475 521.584 12.481 522.143 12.487 522.371 12.492 522.536 12.498 522.671 12.504 522.745 12.510 522.766 12.516 522.686 12.521 522.490 12.527 522.240 12.533 522.160 12.539 522.368 12.545 522.763 12.550 523.133 12.556 523.320 12.562 523.455 12.568 523.618 12.574 523.833 12.579 524.105 12.585 524.627 12.591 525.239 12.597 525.800 12.603 526.073 12.608 526.395 12.614 526.571 12.620 526.465 12.626 526.091 12.632 526.050 12.637 524.263 12.643 523.074 12.649 522.068 12.655 515.116 12.661 512.134 12.666 512.602 12.672 509.459 12.678 505.511 12.684 501.277 12.690 500.862 12.696 500.307 12.701 480.208 12.707 481.158 12.713 480.491 12.719 479.055 12.725 479.095 12.730 478.719 12.736 489.737 12.742 487.776 12.748 477.608 12.754 477.191 12.759 476.589 12.765 475.684 12.771 475.300 12.777 474.940 12.783 474.624 12.788 474.708 12.794 474.696 12.800 474.859 12.806 475.240 12.812 474.921 12.817 475.175 12.823 475.929 12.829 476.712 12.835 478.264 12.841 480.174 12.846 0.000 12.852 0.000 12.858 524.227 12.864 528.271 12.870 525.199 12.875 525.374 12.881 525.278 12.887 525.746 12.893 525.670 12.899 525.306 12.904 521.115 12.910 535.237 12.916 542.818 12.922 553.107 12.928 554.200 12.934 554.879 12.939 554.836 12.945 554.509 12.951 553.788 12.957 553.956 12.963 554.639 12.968 554.443 12.974 559.767 12.980 563.336 12.986 563.067 12.992 562.198 12.997 563.518 13.003 567.866 13.009 569.330 13.015 581.733 13.021 583.366 13.026 583.173 13.032 583.585 13.038 584.478 13.044 583.980 13.050 584.081 13.055 584.478 13.061 584.997 13.067 585.139 13.073 584.546 13.079 583.263 13.084 582.460 13.090 583.037 13.096 584.410 13.102 585.838 13.108 586.417 13.113 586.641 13.119 586.824 13.125 586.909 13.131 587.073 13.137 587.169 13.142 587.023 13.148 586.630 13.154 586.009 13.160 585.533 13.166 585.488 13.172 585.539 13.177 585.798 13.183 586.145 13.189 586.731 13.195 587.153 13.201 587.231 13.206 586.858 13.212 586.094 13.218 585.245 13.224 585.633 13.230 586.044 13.235 586.538 13.241 586.704 13.247 586.566 13.253 586.332 13.259 586.017 13.264 585.761 13.270 585.637 13.276 585.579 13.282 585.625 13.288 585.945 13.293 586.249 13.299 586.389 13.305 586.381 13.311 586.096 13.317 585.313 13.322 583.547 13.328 582.018 13.334 581.455 13.340 582.742 13.346 584.207 13.351 585.465 13.357 586.079 13.363 586.560 13.369 586.824 13.375 586.996 13.380 587.052 13.386 587.000 13.392 586.933 13.398 586.820 13.404 586.632 13.410 586.560 13.415 586.624 13.421 586.835 13.427 587.291 13.433 587.554 13.439 587.876 13.444 588.068 13.450 588.237 13.456 588.370 13.462 588.562 13.468 588.559 13.473 588.426 13.479 588.125 13.485 587.800 13.491 587.247 13.497 586.730 13.502 586.344 13.508 586.308 13.514 586.459 13.520 586.477 13.526 586.353 13.531 586.115 13.537 585.890 13.543 585.399 13.549 585.130 13.555 584.599 13.560 584.785 13.566 585.085 13.572 585.322 13.578 585.548 13.584 585.775 13.589 585.972 13.595 585.952 13.601 583.686 13.607 582.570 13.613 589.064 13.619 586.751 13.624 587.177 13.630 587.476 13.636 587.678 13.642 587.829 13.648 587.968 13.653 588.181 13.659 588.584 13.665 589.312 13.671 590.064 13.677 590.360 13.682 590.004 13.688 589.445 13.694 589.065 13.700 588.702 13.706 589.689 13.711 590.152 13.717 590.511 13.723 590.345 13.729 590.603 13.735 590.774 13.740 590.658 13.746 589.908 13.752 589.381 13.758 588.987 13.764 588.676 13.769 588.333 13.775 587.911 13.781 587.360 13.787 586.819 13.793 586.690 13.798 586.949 13.804 587.439 13.810 587.892 13.816 588.050 13.822 587.044 13.827 582.405 13.833 569.009 13.839 554.045 13.845 554.151 13.851 554.042 13.857 554.137 13.862 554.376 13.868 554.208 13.874 553.974 13.880 553.638 13.886 553.757 13.891 553.173 13.897 551.939 13.903 551.120 13.909 550.347 13.915 548.774 13.920 546.602 13.926 546.622 13.932 546.887 13.938 547.670 13.944 545.822 13.949 542.136 13.955 539.338 13.961 535.749 13.967 536.673 13.973 538.605 13.978 539.572 13.984 539.038 13.990 535.465 13.996 512.818 14.002 482.770 14.007 465.585 14.013 465.943 14.019 465.971 14.025 465.867 14.031 465.482 14.036 466.395 14.042 466.297 14.048 466.185 14.054 466.181 14.060 466.204 14.065 466.169 14.071 467.020 14.077 465.744 14.083 465.651 14.089 465.494 14.095 465.442 14.100 465.574 14.106 465.841 14.112 466.007 14.118 466.112 14.124 466.184 14.129 466.197 14.135 466.216 14.141 466.223 14.147 466.298 14.153 466.336 14.158 466.377 14.164 466.411 14.170 466.466 14.176 466.547 14.182 466.725 14.187 467.020 14.193 467.553 14.199 468.101 14.205 468.358 14.211 468.336 14.216 468.248 14.222 468.046 14.228 467.794 14.234 467.617 14.240 467.372 14.245 467.059 14.251 466.627 14.257 466.093 14.263 465.949 14.269 466.146 14.274 466.594 14.280 466.923 14.286 467.289 14.292 467.638 14.298 467.895 14.303 468.175 14.309 468.288 14.315 468.231 14.321 468.078 14.327 467.876 14.333 467.813 14.338 467.796 14.344 467.789 14.350 467.770 14.356 467.759 14.362 467.605 14.367 467.513 14.373 467.484 14.379 467.411 14.385 467.504 14.391 0.000 14.396 0.000 14.402 0.000 14.408 0.000 14.414 0.000 14.420 0.000 14.425 0.000 14.431 0.000 14.437 0.000 14.443 0.000 14.449 398.871 14.454 391.774 14.460 391.350 14.466 391.167 14.472 391.489 14.478 391.493 14.483 391.666 14.489 391.706 14.495 391.947 14.501 392.238 14.507 392.087 14.512 391.999 14.518 392.029 14.524 392.076 14.530 392.107 14.536 392.123 14.541 391.825 14.547 391.826 14.553 391.705 14.559 391.549 14.565 391.163 14.571 391.035 14.576 391.134 14.582 391.342 14.588 391.470 14.594 391.475 14.600 391.431 14.605 391.421 14.611 391.458 14.617 391.490 14.623 391.529 14.629 391.550 14.634 391.613 14.640 391.717 14.646 391.987 14.652 392.243 14.658 392.522 14.663 392.753 14.669 392.928 14.675 393.068 14.681 393.203 14.687 393.358 14.692 393.550 14.698 393.780 14.704 393.883 14.710 393.779 14.716 393.598 14.721 393.326 14.727 393.053 14.733 392.839 14.739 392.658 14.745 392.540 14.750 392.413 14.756 392.230 14.762 391.952 14.768 391.814 14.774 391.861 14.780 392.105 14.785 392.265 14.791 392.498 14.797 392.792 14.803 393.107 14.809 393.401 14.814 393.645 14.820 393.863 14.826 393.999 14.832 393.863 14.838 393.598 14.843 393.304 14.849 393.108 14.855 393.016 14.861 392.902 14.867 392.753 14.872 392.612 14.878 392.566 14.884 392.556 14.890 392.586 14.896 392.658 14.901 392.796 14.907 392.975 14.913 393.199 14.919 393.323 14.925 393.317 14.930 393.200 14.936 393.017 14.942 392.854 14.948 392.668 14.954 392.466 14.959 392.251 14.965 391.953 14.971 391.589 14.977 390.892 14.983 389.783 14.988 388.790 14.994 388.588 15.000 389.190 15.006 390.250 15.012 390.987 15.018 391.446 15.023 391.680 15.029 391.781 15.035 391.845 15.041 391.919 15.047 391.984 15.052 392.084 15.058 392.188 15.064 392.326 15.070 392.488 15.076 392.703 15.081 392.879 15.087 392.937 15.093 392.927 15.099 392.883 15.105 392.817 15.110 392.781 15.116 392.763 15.122 392.786 15.128 392.781 15.134 392.823 15.139 392.906 15.145 393.006 15.151 393.151 15.157 393.334 15.163 393.506 15.168 393.546 15.174 393.556 15.180 393.595 15.186 393.644 15.192 393.637 15.197 393.602 15.203 393.559 15.209 393.513 15.215 393.318 15.221 393.199 15.226 393.065 15.232 392.882 15.238 392.600 15.244 392.275 15.250 391.878 15.256 391.541 15.261 391.350 15.267 391.319 15.273 391.425 15.279 391.547 15.285 391.525 15.290 391.486 15.296 391.370 15.302 391.302 15.308 391.086 15.314 390.858 15.319 390.502 15.325 390.284 15.331 390.364 15.337 390.624 15.343 390.850 15.348 391.001 15.354 391.079 15.360 391.191 15.366 391.327 15.372 391.497 15.377 391.699 15.383 391.960 15.389 392.305 15.395 392.711 15.401 393.069 15.406 393.224 15.412 393.129 15.418 392.878 15.424 392.705 15.430 392.653 15.435 392.660 15.441 392.667 15.447 392.653 15.453 392.637 15.459 392.645 15.464 392.670 15.470 392.700 15.476 392.786 15.482 392.996 15.488 393.550 15.494 394.233 15.499 394.446 15.505 394.116 15.511 393.302 15.517 392.938 15.523 392.685 15.528 392.466 15.534 392.167 15.540 391.836 15.546 391.489 15.552 391.039 15.557 390.936 15.563 391.182 15.569 391.781 15.575 392.228 15.581 392.593 15.586 392.835 15.592 393.026 15.598 393.192 15.604 393.355 15.610 393.551 15.615 393.633 15.621 393.602 15.627 393.538 15.633 393.484 15.639 393.507 15.644 393.530 15.650 393.367 15.656 393.093 15.662 392.739 15.668 392.452 15.673 392.216 15.679 392.017 15.685 391.797 15.691 391.633 15.697 391.565 15.702 391.624 15.708 391.780 15.714 391.996 15.720 392.179 15.726 392.299 15.732 392.372 15.737 392.428 15.743 392.456 15.749 392.447 15.755 392.376 15.761 392.319 15.766 392.309 15.772 392.316 15.778 391.929 15.784 391.806 15.790 391.852 15.795 392.049 15.801 392.065 15.807 392.056 15.813 392.011 15.819 391.995 15.824 391.968 15.830 391.965 15.836 391.946 15.842 391.966 15.848 391.971 15.853 391.966 15.859 391.949 15.865 391.923 15.871 391.896 15.877 391.985 15.882 392.384 15.888 392.533 15.894 392.315 15.900 391.716 15.906 397.511 15.911 399.285 15.917 395.772 15.923 392.136 15.929 391.491 15.935 391.446 15.940 391.529 15.946 391.484 15.952 391.559 15.958 391.819 15.964 392.297 15.970 392.129 15.975 392.073 15.981 391.979 15.987 392.019 15.993 392.088 15.999 392.116 16.004 392.101 16.010 391.820 16.016 391.796 16.022 391.647 16.028 391.437 16.033 391.136 16.039 391.056 16.045 391.184 16.051 391.374 16.057 391.396 16.062 391.333 16.068 391.300 16.074 391.347 16.080 391.407 16.086 391.435 16.091 391.465 16.097 391.543 16.103 391.620 16.109 391.706 16.115 391.770 16.120 391.772 16.126 391.663 16.132 391.522 16.138 391.339 16.144 391.321 16.149 391.470 16.155 391.651 16.161 391.679 16.167 391.523 16.173 391.365 16.179 391.669 16.184 392.007 16.190 391.819 16.196 391.401 16.202 391.105 16.208 390.979 16.213 391.088 16.219 391.182 16.225 391.080 16.231 390.829 16.237 390.278 16.242 390.803 16.248 410.748 16.254 413.240 16.260 465.487 16.266 465.616 16.271 465.798 16.277 465.807 16.283 466.011 16.289 466.395 16.295 466.353 16.300 466.245 16.306 466.156 16.312 466.142 16.318 466.255 16.324 466.165 16.329 465.825 16.335 465.745 16.341 465.605 16.347 465.449 16.353 465.470 16.358 465.611 16.364 465.909 16.370 466.064 16.376 466.159 16.382 466.217 16.387 466.253 16.393 467.082 16.399 468.572 16.405 480.914 16.411 489.195 16.417 509.526 16.422 509.171 16.428 522.779 16.434 523.175 16.440 523.303 16.446 523.071 16.451 522.614 16.457 522.587 16.463 522.218 16.469 521.856 16.475 521.222 16.480 520.895 16.486 520.675 16.492 520.748 16.498 520.840 16.504 520.962 16.509 521.104 16.515 520.921 16.521 520.566 16.527 519.778 16.533 519.124 16.538 519.085 16.544 519.748 16.550 520.946 16.556 521.831 16.562 522.222 16.567 522.431 16.573 522.549 16.579 522.605 16.585 522.610 16.591 522.608 16.596 522.688 16.602 522.707 16.608 522.600 16.614 522.259 16.620 522.081 16.625 522.034 16.631 522.344 16.637 522.348 16.643 522.650 16.649 522.966 16.655 523.224 16.660 523.125 16.666 522.963 16.672 522.924 16.678 522.963 16.684 523.039 16.689 523.098 16.695 523.172 16.701 523.246 16.707 523.335 16.713 523.285 16.718 523.111 16.724 522.836 16.730 522.407 16.736 521.905 16.742 521.823 16.747 522.021 16.753 522.622 16.759 523.280 16.765 523.560 16.771 523.632 16.776 523.569 16.782 523.284 16.788 522.995 16.794 522.574 16.800 522.232 16.805 522.185 16.811 522.382 16.817 522.245 16.823 521.920 16.829 521.850 16.834 522.159 16.840 522.205 16.846 522.405 16.852 522.959 16.858 522.552 16.863 522.523 16.869 522.506 16.875 522.562 16.881 522.780 16.887 522.793 16.893 522.653 16.898 522.530 16.904 522.622 16.910 522.283 16.916 521.953 16.922 521.509 16.927 520.988 16.933 520.776 16.939 520.683 16.945 520.762 16.951 520.859 16.956 520.958 16.962 520.910 16.968 520.663 16.974 519.996 16.980 519.302 16.985 519.099 16.991 519.560 16.997 520.608 17.003 521.637 17.009 522.153 17.014 522.397 17.020 522.528 17.026 522.624 17.032 522.614 17.038 522.602 17.043 522.679 17.049 522.731 17.055 522.678 17.061 522.447 17.067 522.151 17.072 522.034 17.078 522.248 17.084 522.253 17.090 522.502 17.096 522.815 17.101 523.179 17.107 523.140 17.113 523.006 17.119 522.946 17.125 522.921 17.131 522.760 17.136 523.072 17.142 523.108 17.148 523.171 17.154 523.238 17.160 523.180 17.165 522.973 17.171 522.682 17.177 522.305 17.183 521.900 17.189 521.800 17.194 521.827 17.200 522.123 17.206 522.569 17.212 522.929 17.218 523.054 17.223 522.990 17.229 522.761 17.235 522.309 17.241 521.433 17.247 519.846 17.252 518.210 17.258 517.890 17.264 518.788 17.270 520.426 17.276 521.594 17.281 522.148 17.287 522.366 17.293 522.524 17.299 522.649 17.305 522.733 17.310 522.754 17.316 522.682 17.322 522.486 17.328 522.228 17.334 522.155 17.340 522.372 17.345 522.703 17.351 523.106 17.357 523.294 17.363 523.428 17.369 523.587 17.374 523.797 17.380 524.061 17.386 524.576 17.392 525.191 17.398 525.751 17.403 526.064 17.409 526.419 17.415 526.609 17.421 526.547 17.427 526.502 17.432 526.471 17.438 526.225 17.444 525.849 17.450 525.398 17.456 524.971 17.461 524.595 17.467 524.182 17.473 523.927 17.479 523.679 17.485 523.337 17.490 522.790 17.496 522.371 17.502 522.307 17.508 522.281 17.514 522.424 17.519 522.395 17.525 522.323 17.531 522.229 17.537 522.241 17.543 522.474 17.548 523.247 17.554 524.213 17.560 524.477 17.566 523.941 17.572 523.255 17.578 523.035 17.583 523.066 17.589 523.191 17.595 523.333 17.601 523.410 17.607 523.451 17.612 523.484 17.618 523.466 17.624 522.308 17.630 521.874 17.636 522.205 17.641 523.629 17.647 523.850 17.653 523.768 17.659 523.579 17.665 523.290 17.670 522.904 17.676 522.266 17.682 522.048 17.688 522.373 17.694 523.264 17.699 523.956 17.705 524.395 17.711 524.647 17.717 525.895 17.723 533.047 17.728 545.159 17.734 555.943 17.740 555.538 17.746 555.111 17.752 554.323 17.757 553.512 17.763 552.939 17.769 553.234 17.775 554.247 17.781 554.655 17.786 553.337 17.792 552.069 17.798 557.049 17.804 567.687 17.810 573.697 17.816 576.010 17.821 585.814 17.827 585.980 17.833 585.961 17.839 585.764 17.845 586.433 17.850 585.835 17.856 584.977 17.862 584.747 17.868 584.631 17.874 584.541 17.879 584.544 17.885 584.547 17.891 584.590 17.897 584.734 17.903 584.441 17.908 583.678 17.914 583.114 17.920 583.240 17.926 584.137 17.932 585.482 17.937 586.260 17.943 586.754 17.949 587.117 17.955 587.103 17.961 586.992 17.966 586.862 17.972 586.742 17.978 586.620 17.984 586.278 17.990 585.882 17.995 585.573 18.001 585.700 18.007 585.737 18.013 586.319 18.019 586.951 18.024 587.183 18.030 587.112 18.036 586.701 18.042 586.134 18.048 585.392 18.054 585.674 18.059 586.017 18.065 586.395 18.071 586.570 18.077 586.594 18.083 586.487 18.088 586.171 18.094 585.779 18.100 585.471 18.106 585.418 18.112 585.692 18.117 586.063 18.123 586.396 18.129 586.449 18.135 586.334 18.141 585.973 18.146 585.124 18.152 583.394 18.158 581.947 18.164 581.508 18.170 582.826 18.175 584.293 18.181 585.552 18.187 586.123 18.193 586.554 18.199 586.771 18.204 586.929 18.210 587.024 18.216 587.050 18.222 587.029 18.228 586.857 18.233 586.512 18.239 586.389 18.245 586.588 18.251 586.965 18.257 587.391 18.262 587.588 18.268 587.847 18.274 588.312 18.280 588.234 18.286 588.420 18.292 588.595 18.297 588.547 18.303 588.384 18.309 588.085 18.315 587.784 18.321 587.299 18.326 586.796 18.332 586.373 18.338 586.302 18.344 586.408 18.350 586.423 18.355 586.364 18.361 586.153 18.367 585.946 18.373 585.415 18.379 585.067 18.384 584.523 18.390 584.741 18.396 585.098 18.402 585.394 18.408 585.600 18.413 585.781 18.419 585.923 18.425 585.861 18.431 583.599 18.437 582.572 18.442 589.170 18.448 586.842 18.454 587.210 18.460 587.433 18.466 587.605 18.471 587.796 18.477 588.011 18.483 588.220 18.489 588.628 18.495 589.244 18.500 589.981 18.506 590.285 18.512 590.054 18.518 589.537 18.524 589.129 18.530 588.648 18.535 589.609 18.541 590.135 18.547 590.553 18.553 590.306 18.559 590.482 18.564 590.564 18.570 590.379 18.576 589.615 18.582 589.134 18.588 588.707 18.593 588.427 18.599 588.116 18.605 587.747 18.611 587.248 18.617 586.671 18.622 586.413 18.628 586.452 18.634 586.861 18.640 587.305 18.646 587.501 18.651 587.489 18.657 587.267 18.663 586.781 18.669 585.652 18.675 582.890 18.680 580.882 18.686 581.067 18.692 583.605 18.698 585.834 18.704 586.520 18.709 586.810 18.715 586.890 18.721 586.957 18.727 587.039 18.733 587.077 18.739 587.081 18.744 586.860 18.750 586.659 18.756 586.779 18.762 587.148 18.768 587.724 18.773 588.008 18.779 588.199 18.785 588.437 18.791 588.787 18.797 589.184 18.802 589.409 18.808 589.749 18.814 590.031 18.820 590.298 18.826 590.303 18.831 590.256 18.837 590.185 18.843 589.870 18.849 588.593 18.855 587.655 18.860 587.167 18.866 587.414 18.872 587.439 18.878 587.432 18.884 587.184 18.889 586.718 18.895 585.971 18.901 585.560 18.907 585.319 18.913 584.752 18.918 585.307 18.924 585.569 18.930 585.824 18.936 586.028 18.942 586.342 18.947 587.545 18.953 588.942 18.959 589.223 18.965 588.215 18.971 587.279 18.977 587.228 18.982 587.387 18.988 587.514 18.994 587.574 19.000 587.641 19.006 587.801 19.011 588.159 19.017 590.540 19.023 590.894 19.029 587.524 19.035 588.429 19.040 588.190 19.046 587.898 19.052 587.360 19.058 586.610 19.064 586.421 19.069 586.738 19.075 587.817 19.081 588.580 19.087 588.980 19.093 589.269 19.098 589.308 19.104 589.030 19.110 589.071 19.116 589.091 19.122 589.061 19.127 588.875 19.133 588.727 19.139 588.818 19.145 588.902 19.151 588.890 19.156 588.621 19.162 588.480 19.168 588.471 19.174 588.448 19.180 588.385 19.185 588.153 19.191 587.611 19.197 585.867 19.203 582.881 19.209 581.440 19.215 582.961 19.220 585.673 19.226 586.763 19.232 587.138 mir_eval-0.8.2/tests/data/melody/ref05.txt000066400000000000000000001737011475740344600203740ustar00rootroot000000000000000.000 0.000 0.006 0.000 0.012 0.000 0.017 0.000 0.023 0.000 0.029 0.000 0.035 0.000 0.041 0.000 0.046 0.000 0.052 0.000 0.058 0.000 0.064 0.000 0.070 0.000 0.075 0.000 0.081 0.000 0.087 0.000 0.093 0.000 0.099 0.000 0.104 0.000 0.110 0.000 0.116 0.000 0.122 0.000 0.128 0.000 0.134 0.000 0.139 0.000 0.145 0.000 0.151 0.000 0.157 0.000 0.163 0.000 0.168 0.000 0.174 0.000 0.180 0.000 0.186 0.000 0.192 0.000 0.197 0.000 0.203 0.000 0.209 0.000 0.215 0.000 0.221 0.000 0.226 0.000 0.232 0.000 0.238 0.000 0.244 0.000 0.250 0.000 0.255 0.000 0.261 0.000 0.267 0.000 0.273 0.000 0.279 0.000 0.284 0.000 0.290 0.000 0.296 0.000 0.302 0.000 0.308 0.000 0.313 0.000 0.319 0.000 0.325 0.000 0.331 0.000 0.337 0.000 0.342 0.000 0.348 0.000 0.354 0.000 0.360 0.000 0.366 0.000 0.372 0.000 0.377 0.000 0.383 0.000 0.389 0.000 0.395 0.000 0.401 0.000 0.406 0.000 0.412 0.000 0.418 0.000 0.424 0.000 0.430 0.000 0.435 0.000 0.441 0.000 0.447 0.000 0.453 0.000 0.459 0.000 0.464 0.000 0.470 0.000 0.476 0.000 0.482 0.000 0.488 0.000 0.493 0.000 0.499 0.000 0.505 0.000 0.511 0.000 0.517 0.000 0.522 0.000 0.528 0.000 0.534 0.000 0.540 0.000 0.546 0.000 0.551 0.000 0.557 0.000 0.563 0.000 0.569 0.000 0.575 0.000 0.580 0.000 0.586 0.000 0.592 0.000 0.598 0.000 0.604 0.000 0.610 0.000 0.615 931.692 0.621 932.285 0.627 932.044 0.633 929.744 0.639 929.543 0.644 931.548 0.650 932.037 0.656 932.137 0.662 932.410 0.668 932.459 0.673 932.877 0.679 933.320 0.685 933.401 0.691 933.407 0.697 933.469 0.702 933.558 0.708 933.617 0.714 933.636 0.720 933.684 0.726 933.924 0.731 934.287 0.737 934.010 0.743 934.051 0.749 933.447 0.755 933.645 0.760 934.423 0.766 935.087 0.772 935.483 0.778 935.141 0.784 934.823 0.789 933.902 0.795 932.872 0.801 932.076 0.807 931.830 0.813 932.114 0.819 932.856 0.824 933.696 0.830 934.305 0.836 932.162 0.842 931.146 0.848 931.239 0.853 933.083 0.859 933.398 0.865 933.442 0.871 933.682 0.877 934.107 0.882 934.935 0.888 932.409 0.894 925.989 0.900 920.154 0.906 902.324 0.911 896.660 0.917 877.829 0.923 878.678 0.929 879.857 0.935 879.531 0.940 879.658 0.946 880.134 0.952 880.219 0.958 880.616 0.964 881.072 0.969 880.966 0.975 881.117 0.981 881.223 0.987 881.316 0.993 881.482 0.998 881.457 1.004 881.395 1.010 881.719 1.016 882.070 1.022 881.715 1.027 881.388 1.033 881.812 1.039 881.337 1.045 881.539 1.051 881.549 1.057 881.756 1.062 882.800 1.068 883.365 1.074 882.342 1.080 882.233 1.086 882.238 1.091 881.965 1.097 880.751 1.103 879.781 1.109 880.410 1.115 895.451 1.120 0.000 1.126 0.000 1.132 0.000 1.138 0.000 1.144 0.000 1.149 0.000 1.155 0.000 1.161 0.000 1.167 0.000 1.173 0.000 1.178 0.000 1.184 0.000 1.190 0.000 1.196 0.000 1.202 0.000 1.207 0.000 1.213 0.000 1.219 0.000 1.225 782.074 1.231 783.961 1.236 784.388 1.242 782.486 1.248 781.637 1.254 782.197 1.260 783.593 1.265 783.819 1.271 783.841 1.277 784.091 1.283 784.092 1.289 784.138 1.295 784.410 1.300 784.760 1.306 784.832 1.312 784.859 1.318 784.752 1.324 784.888 1.329 784.914 1.335 784.978 1.341 785.016 1.347 785.212 1.353 785.412 1.358 785.635 1.364 785.500 1.370 785.128 1.376 784.819 1.382 783.643 1.387 784.008 1.393 784.698 1.399 785.349 1.405 785.883 1.411 786.445 1.416 786.740 1.422 787.009 1.428 786.914 1.434 786.357 1.440 785.542 1.445 784.943 1.451 784.383 1.457 783.945 1.463 783.871 1.469 784.070 1.474 784.559 1.480 784.683 1.486 783.709 1.492 782.603 1.498 782.999 1.503 0.000 1.509 0.000 1.515 0.000 1.521 0.000 1.527 0.000 1.533 0.000 1.538 0.000 1.544 0.000 1.550 0.000 1.556 0.000 1.562 0.000 1.567 0.000 1.573 580.682 1.579 581.311 1.585 584.464 1.591 584.685 1.596 584.816 1.602 584.847 1.608 584.413 1.614 583.506 1.620 582.858 1.625 583.093 1.631 584.099 1.637 585.452 1.643 586.238 1.649 586.646 1.654 586.967 1.660 587.018 1.666 587.040 1.672 587.030 1.678 586.883 1.683 586.611 1.689 586.215 1.695 585.738 1.701 585.656 1.707 585.479 1.712 585.650 1.718 586.162 1.724 586.764 1.730 587.161 1.736 587.177 1.741 586.813 1.747 586.205 1.753 585.382 1.759 585.577 1.765 586.040 1.771 586.528 1.776 586.680 1.782 586.596 1.788 586.414 1.794 586.149 1.800 585.808 1.805 585.544 1.811 585.476 1.817 585.632 1.823 586.000 1.829 586.338 1.834 586.449 1.840 586.373 1.846 586.066 1.852 585.287 1.858 583.595 1.863 582.067 1.869 581.463 1.875 582.647 1.881 583.774 1.887 585.165 1.892 585.992 1.898 586.523 1.904 586.796 1.910 586.958 1.916 587.041 1.921 587.013 1.927 586.990 1.933 586.881 1.939 586.627 1.945 586.436 1.950 586.512 1.956 586.901 1.962 587.311 1.968 587.575 1.974 587.856 1.980 588.277 1.985 588.545 1.991 588.655 1.997 588.593 2.003 588.565 2.009 588.430 2.014 588.143 2.020 587.816 2.026 587.322 2.032 586.801 2.038 586.361 2.043 586.279 2.049 586.405 2.055 586.460 2.061 586.382 2.067 586.170 2.072 585.960 2.078 585.472 2.084 585.160 2.090 585.318 2.096 584.289 2.101 580.861 2.107 562.163 2.113 558.318 2.119 555.432 2.125 522.936 2.130 523.149 2.136 523.329 2.142 523.075 2.148 522.645 2.154 522.674 2.159 522.249 2.165 521.921 2.171 523.084 2.177 520.911 2.183 520.710 2.188 520.724 2.194 520.841 2.200 520.965 2.206 521.025 2.212 520.935 2.218 520.596 2.223 519.845 2.229 519.174 2.235 519.062 2.241 519.664 2.247 520.781 2.252 521.744 2.258 522.186 2.264 522.407 2.270 522.528 2.276 522.354 2.281 521.848 2.287 522.398 2.293 510.391 2.299 498.437 2.305 480.986 2.310 465.899 2.316 465.601 2.322 465.697 2.328 465.824 2.334 465.717 2.339 465.681 2.345 465.834 2.351 465.811 2.357 465.492 2.363 465.478 2.368 465.351 2.374 465.219 2.380 465.456 2.386 465.491 2.392 465.803 2.397 465.960 2.403 465.720 2.409 465.790 2.415 466.311 2.421 475.713 2.426 483.322 2.432 491.542 2.438 511.985 2.444 512.601 2.450 522.983 2.456 523.242 2.461 523.326 2.467 523.146 2.473 522.655 2.479 522.420 2.485 522.167 2.490 521.782 2.496 521.344 2.502 520.942 2.508 520.685 2.514 520.700 2.519 520.831 2.525 521.019 2.531 521.108 2.537 520.977 2.543 520.628 2.548 519.825 2.554 519.210 2.560 519.161 2.566 519.836 2.572 521.041 2.577 521.927 2.583 522.267 2.589 522.476 2.595 522.584 2.601 522.649 2.606 522.640 2.612 522.647 2.618 522.756 2.624 522.759 2.630 522.624 2.635 522.196 2.641 521.995 2.647 522.062 2.653 522.232 2.659 522.353 2.664 522.667 2.670 523.070 2.676 523.298 2.682 523.123 2.688 522.940 2.694 522.945 2.699 522.889 2.705 522.914 2.711 522.998 2.717 523.073 2.723 523.200 2.728 523.215 2.734 523.078 2.740 522.868 2.746 522.530 2.752 522.147 2.757 521.884 2.763 521.803 2.769 521.921 2.775 522.350 2.781 522.731 2.786 523.007 2.792 523.029 2.798 522.927 2.804 522.614 2.810 522.017 2.815 520.858 2.821 518.973 2.827 517.863 2.833 518.097 2.839 519.456 2.844 521.053 2.850 521.884 2.856 522.280 2.862 522.419 2.868 522.595 2.873 522.704 2.879 522.761 2.885 522.743 2.891 522.625 2.897 522.367 2.902 522.166 2.908 522.203 2.914 522.494 2.920 522.912 2.926 523.212 2.932 523.367 2.937 523.524 2.943 523.708 2.949 523.954 2.955 524.274 2.961 524.902 2.966 525.495 2.972 525.939 2.978 526.184 2.984 526.445 2.990 526.566 2.995 526.513 3.001 526.635 3.007 526.814 3.013 526.505 3.019 524.066 3.024 507.286 3.030 464.483 3.036 465.644 3.042 465.701 3.048 465.733 3.053 465.869 3.059 466.311 3.065 466.334 3.071 466.352 3.077 466.199 3.082 466.080 3.088 466.204 3.094 466.251 3.100 466.055 3.106 465.787 3.111 465.695 3.117 465.431 3.123 465.467 3.129 465.575 3.135 465.692 3.140 466.003 3.146 466.074 3.152 466.134 3.158 466.238 3.164 466.173 3.170 466.183 3.175 466.254 3.181 466.219 3.187 466.321 3.193 466.384 3.199 466.282 3.204 466.352 3.210 466.426 3.216 466.233 3.222 466.769 3.228 467.066 3.233 467.224 3.239 467.484 3.245 0.000 3.251 0.000 3.257 0.000 3.262 486.017 3.268 483.965 3.274 0.000 3.280 0.000 3.286 0.000 3.291 0.000 3.297 0.000 3.303 533.453 3.309 522.980 3.315 522.660 3.320 522.657 3.326 522.888 3.332 522.907 3.338 523.328 3.344 522.788 3.349 522.689 3.355 522.286 3.361 522.229 3.367 521.867 3.373 521.251 3.379 520.958 3.384 520.853 3.390 520.857 3.396 520.964 3.402 521.066 3.408 521.081 3.413 520.908 3.419 520.425 3.425 519.554 3.431 518.950 3.437 519.040 3.442 519.860 3.448 521.104 3.454 521.899 3.460 522.205 3.466 522.393 3.471 522.498 3.477 522.563 3.483 522.550 3.489 522.554 3.495 522.635 3.500 522.598 3.506 522.472 3.512 522.154 3.518 522.003 3.524 522.137 3.529 522.326 3.535 522.369 3.541 522.640 3.547 523.000 3.553 523.164 3.558 523.064 3.564 522.906 3.570 522.873 3.576 522.883 3.582 523.000 3.587 523.047 3.593 523.075 3.599 523.179 3.605 523.198 3.611 523.065 3.617 522.812 3.622 522.506 3.628 522.108 3.634 521.822 3.640 521.768 3.646 521.900 3.651 522.329 3.657 522.745 3.663 523.018 3.669 523.042 3.675 522.924 3.680 522.588 3.686 521.968 3.692 520.779 3.698 519.006 3.704 517.896 3.709 518.178 3.715 519.524 3.721 521.064 3.727 521.887 3.733 522.290 3.738 522.412 3.744 522.592 3.750 522.694 3.756 522.752 3.762 522.737 3.767 522.627 3.773 522.355 3.779 522.178 3.785 522.219 3.791 522.516 3.796 522.947 3.802 523.233 3.808 523.384 3.814 523.533 3.820 523.708 3.825 523.950 3.831 524.276 3.837 524.933 3.843 525.537 3.849 525.977 3.855 526.231 3.860 526.471 3.866 526.547 3.872 526.468 3.878 526.489 3.884 526.380 3.889 526.233 3.895 526.193 3.901 524.552 3.907 522.756 3.913 546.561 3.918 558.491 3.924 561.588 3.930 564.800 3.936 567.674 3.942 568.116 3.947 568.128 3.953 565.944 3.959 562.819 3.965 561.193 3.971 560.160 3.976 582.829 3.982 582.843 3.988 582.504 3.994 582.477 4.000 582.451 4.005 582.128 4.011 581.579 4.017 581.205 4.023 581.801 4.029 583.128 4.034 585.538 4.040 586.701 4.046 587.232 4.052 587.429 4.058 587.396 4.063 587.482 4.069 587.380 4.075 587.214 4.081 586.902 4.087 586.532 4.093 586.279 4.098 585.993 4.104 585.945 4.110 586.289 4.116 586.879 4.122 587.607 4.127 587.977 4.133 588.066 4.139 587.917 4.145 587.383 4.151 586.840 4.156 586.643 4.162 586.796 4.168 587.185 4.174 587.345 4.180 587.189 4.185 587.005 4.191 586.755 4.197 586.380 4.203 586.107 4.209 585.931 4.214 585.873 4.220 585.999 4.226 586.236 4.232 586.309 4.238 586.303 4.243 585.994 4.249 585.353 4.255 583.648 4.261 581.344 4.267 580.183 4.272 581.362 4.278 583.396 4.284 585.113 4.290 586.092 4.296 586.626 4.301 586.860 4.307 587.116 4.313 587.181 4.319 587.168 4.325 587.177 4.331 587.092 4.336 586.880 4.342 586.787 4.348 586.779 4.354 587.002 4.360 587.553 4.365 587.889 4.371 588.170 4.377 588.463 4.383 588.750 4.389 589.017 4.394 589.188 4.400 589.274 4.406 589.290 4.412 589.071 4.418 588.651 4.423 588.049 4.429 587.321 4.435 586.744 4.441 586.500 4.447 586.623 4.452 586.826 4.458 586.836 4.464 586.688 4.470 586.400 4.476 585.937 4.481 585.510 4.487 585.179 4.493 585.123 4.499 585.309 4.505 585.571 4.510 585.720 4.516 585.831 4.522 585.948 4.528 586.177 4.534 587.284 4.540 589.305 4.545 589.604 4.551 588.372 4.557 587.751 4.563 587.954 4.569 588.116 4.574 588.267 4.580 588.530 4.586 588.761 4.592 588.923 4.598 589.362 4.603 589.936 4.609 590.237 4.615 590.306 4.621 590.223 4.627 590.235 4.632 590.839 4.638 591.715 4.644 592.513 4.650 592.746 4.656 592.548 4.661 592.440 4.667 592.412 4.673 592.056 4.679 591.503 4.685 590.780 4.690 590.080 4.696 589.522 4.702 589.138 4.708 588.871 4.714 588.454 4.719 587.917 4.725 587.652 4.731 587.524 4.737 587.659 4.743 588.054 4.748 588.270 4.754 588.389 4.760 588.448 4.766 588.516 4.772 589.394 4.778 0.000 4.783 0.000 4.789 0.000 4.795 0.000 4.801 0.000 4.807 0.000 4.812 0.000 4.818 0.000 4.824 0.000 4.830 0.000 4.836 0.000 4.841 0.000 4.847 0.000 4.853 0.000 4.859 0.000 4.865 0.000 4.870 0.000 4.876 0.000 4.882 0.000 4.888 0.000 4.894 0.000 4.899 0.000 4.905 0.000 4.911 0.000 4.917 0.000 4.923 0.000 4.928 0.000 4.934 0.000 4.940 0.000 4.946 0.000 4.952 0.000 4.957 0.000 4.963 0.000 4.969 0.000 4.975 0.000 4.981 0.000 4.986 0.000 4.992 0.000 4.998 0.000 5.004 0.000 5.010 0.000 5.016 0.000 5.021 0.000 5.027 0.000 5.033 0.000 5.039 0.000 5.045 0.000 5.050 0.000 5.056 0.000 5.062 0.000 5.068 0.000 5.074 0.000 5.079 0.000 5.085 0.000 5.091 0.000 5.097 0.000 5.103 0.000 5.108 0.000 5.114 0.000 5.120 0.000 5.126 0.000 5.132 0.000 5.137 0.000 5.143 0.000 5.149 0.000 5.155 0.000 5.161 0.000 5.166 0.000 5.172 0.000 5.178 0.000 5.184 0.000 5.190 0.000 5.195 0.000 5.201 0.000 5.207 0.000 5.213 0.000 5.219 0.000 5.224 0.000 5.230 0.000 5.236 0.000 5.242 0.000 5.248 0.000 5.254 0.000 5.259 0.000 5.265 0.000 5.271 0.000 5.277 586.533 5.283 586.397 5.288 586.364 5.294 586.784 5.300 587.127 5.306 587.296 5.312 586.496 5.317 586.573 5.323 586.023 5.329 585.930 5.335 585.019 5.341 584.644 5.346 584.347 5.352 584.384 5.358 584.555 5.364 584.768 5.370 584.900 5.375 584.770 5.381 584.206 5.387 583.304 5.393 582.944 5.399 583.396 5.404 584.707 5.410 628.149 5.416 641.397 5.422 642.780 5.428 634.734 5.433 629.275 5.439 782.122 5.445 782.383 5.451 783.194 5.457 783.745 5.462 783.589 5.468 783.942 5.474 784.103 5.480 784.162 5.486 784.421 5.492 784.735 5.497 784.828 5.503 784.856 5.509 784.769 5.515 784.887 5.521 785.091 5.526 784.982 5.532 785.194 5.538 785.216 5.544 785.416 5.550 785.638 5.555 785.499 5.561 785.131 5.567 784.804 5.573 783.655 5.579 783.973 5.584 784.629 5.590 785.253 5.596 785.736 5.602 786.238 5.608 786.531 5.613 786.918 5.619 787.009 5.625 786.371 5.631 785.492 5.637 784.517 5.642 783.448 5.648 782.628 5.654 781.919 5.660 781.449 5.666 781.708 5.671 782.597 5.677 778.880 5.683 877.057 5.689 880.162 5.695 879.520 5.700 879.053 5.706 878.875 5.712 877.833 5.718 878.241 5.724 879.122 5.730 879.654 5.735 879.625 5.741 879.885 5.747 880.090 5.753 880.315 5.759 880.724 5.764 880.904 5.770 881.026 5.776 881.084 5.782 881.289 5.788 881.365 5.793 881.440 5.799 881.459 5.805 881.554 5.811 881.788 5.817 881.911 5.822 881.494 5.828 881.436 5.834 882.015 5.840 881.005 5.846 881.660 5.851 882.146 5.857 882.221 5.863 882.314 5.869 882.401 5.875 882.408 5.880 882.215 5.886 881.750 5.892 881.139 5.898 880.548 5.904 880.049 5.909 879.884 5.915 880.988 5.921 0.000 5.927 0.000 5.933 0.000 5.939 0.000 5.944 0.000 5.950 0.000 5.956 0.000 5.962 0.000 5.968 0.000 5.973 0.000 5.979 0.000 5.985 0.000 5.991 879.965 5.997 879.761 6.002 879.802 6.008 879.202 6.014 909.228 6.020 932.318 6.026 932.415 6.031 930.132 6.037 929.183 6.043 931.037 6.049 931.810 6.055 931.671 6.060 931.986 6.066 932.474 6.072 932.777 6.078 933.219 6.084 933.513 6.089 933.416 6.095 933.431 6.101 933.547 6.107 933.594 6.113 933.638 6.118 933.684 6.124 933.846 6.130 934.223 6.136 933.844 6.142 934.043 6.147 934.593 6.153 933.522 6.159 934.208 6.165 934.934 6.171 935.441 6.177 935.171 6.182 934.940 6.188 934.374 6.194 933.204 6.200 932.229 6.206 931.862 6.211 932.007 6.217 932.659 6.223 933.461 6.229 934.255 6.235 933.526 6.240 931.265 6.246 931.126 6.252 932.675 6.258 933.329 6.264 933.441 6.269 933.605 6.275 933.930 6.281 933.466 6.287 935.915 6.293 945.770 6.298 976.382 6.304 1045.154 6.310 1044.184 6.316 1044.735 6.322 1045.795 6.327 1045.736 6.333 1046.316 6.339 1046.858 6.345 1047.274 6.351 1047.796 6.356 1047.861 6.362 1047.907 6.368 1048.103 6.374 1048.079 6.380 1048.017 6.385 1047.949 6.391 1048.189 6.397 1048.623 6.403 1049.132 6.409 1050.049 6.415 1048.853 6.420 1049.152 6.426 1049.653 6.432 1049.977 6.438 1049.521 6.444 1048.553 6.449 1047.834 6.455 1046.809 6.461 1045.857 6.467 1045.669 6.473 1046.148 6.478 1046.875 6.484 1047.071 6.490 1045.632 6.496 1045.419 6.502 1045.895 6.507 1047.631 6.513 1047.842 6.519 1047.855 6.525 1047.947 6.531 1048.168 6.536 1048.444 6.542 1048.656 6.548 1048.978 6.554 1049.550 6.560 1050.377 6.565 1051.434 6.571 1052.335 6.577 1052.444 6.583 1051.841 6.589 1050.260 6.594 1049.066 6.600 1048.387 6.606 0.000 6.612 0.000 6.618 0.000 6.623 0.000 6.629 438.904 6.635 878.377 6.641 879.461 6.647 879.355 6.653 879.732 6.658 880.040 6.664 880.147 6.670 880.509 6.676 880.875 6.682 880.983 6.687 881.053 6.693 881.181 6.699 881.301 6.705 881.384 6.711 881.490 6.716 881.490 6.722 881.649 6.728 881.856 6.734 881.616 6.740 881.468 6.745 882.048 6.751 880.841 6.757 881.417 6.763 882.064 6.769 882.551 6.774 882.506 6.780 882.402 6.786 882.098 6.792 881.759 6.798 881.000 6.803 878.347 6.809 878.493 6.815 870.032 6.821 782.759 6.827 782.221 6.832 782.172 6.838 782.457 6.844 783.528 6.850 783.833 6.856 783.877 6.861 784.045 6.867 784.116 6.873 798.145 6.879 798.802 6.885 798.587 6.891 797.171 6.896 784.814 6.902 784.788 6.908 784.957 6.914 785.136 6.920 785.226 6.925 785.202 6.931 785.288 6.937 785.539 6.943 785.660 6.949 785.367 6.954 784.935 6.960 784.709 6.966 783.879 6.972 784.401 6.978 785.060 6.983 785.608 6.989 786.161 6.995 786.530 7.001 786.902 7.007 787.033 7.012 786.670 7.018 785.925 7.024 785.241 7.030 784.649 7.036 784.159 7.041 783.879 7.047 783.963 7.053 784.370 7.059 784.745 7.065 784.207 7.070 783.056 7.076 782.248 7.082 782.533 7.088 783.460 7.094 784.271 7.100 784.481 7.105 784.689 7.111 784.991 7.117 785.277 7.123 785.644 7.129 786.043 7.134 786.275 7.140 786.286 7.146 786.236 7.152 786.354 7.158 786.945 7.163 787.782 7.169 788.398 7.175 788.579 7.181 788.316 7.187 787.798 7.192 786.932 7.198 785.811 7.204 784.884 7.210 784.187 7.216 784.010 7.221 785.920 7.227 787.907 7.233 856.009 7.239 878.372 7.245 877.991 7.250 878.043 7.256 878.866 7.262 879.522 7.268 879.400 7.274 879.775 7.279 880.051 7.285 880.251 7.291 880.680 7.297 881.027 7.303 880.993 7.308 880.988 7.314 881.173 7.320 881.265 7.326 881.317 7.332 881.373 7.338 881.457 7.343 881.704 7.349 881.896 7.355 881.563 7.361 881.472 7.367 881.956 7.372 880.903 7.378 881.592 7.384 882.200 7.390 882.393 7.396 882.529 7.401 882.359 7.407 882.017 7.413 881.395 7.419 880.961 7.425 880.643 7.430 880.368 7.436 880.299 7.442 880.373 7.448 880.788 7.454 880.431 7.459 878.861 7.465 878.281 7.471 878.539 7.477 879.917 7.483 880.546 7.488 880.723 7.494 880.933 7.500 881.200 7.506 881.520 7.512 881.919 7.517 882.262 7.523 882.388 7.529 882.371 7.535 882.509 7.541 882.809 7.546 883.401 7.552 884.175 7.558 884.770 7.564 884.683 7.570 883.896 7.576 882.532 7.581 881.347 7.587 880.487 7.593 880.178 7.599 880.482 7.605 881.576 7.610 883.066 7.616 883.241 7.622 882.359 7.628 880.284 7.634 879.153 7.639 878.618 7.645 878.304 7.651 877.617 7.657 875.255 7.663 882.783 7.668 883.337 7.674 884.099 7.680 884.842 7.686 884.565 7.692 882.452 7.697 882.366 7.703 882.370 7.709 882.567 7.715 883.271 7.721 884.106 7.726 887.068 7.732 888.041 7.738 886.810 7.744 883.060 7.750 881.236 7.755 880.180 7.761 880.597 7.767 881.533 7.773 882.061 7.779 882.404 7.784 882.537 7.790 882.425 7.796 882.127 7.802 881.599 7.808 880.105 7.814 877.478 7.819 878.109 7.825 880.421 7.831 881.681 7.837 880.695 7.843 880.247 7.848 879.976 7.854 879.470 7.860 879.620 7.866 880.103 7.872 881.166 7.877 881.771 7.883 882.247 7.889 882.880 7.895 883.568 7.901 884.218 7.906 884.332 7.912 884.621 7.918 884.375 7.924 883.751 7.930 883.377 7.935 884.104 7.941 883.618 7.947 882.179 7.953 879.901 7.959 879.209 7.964 878.727 7.970 878.119 7.976 877.583 7.982 878.044 7.988 879.029 7.993 880.493 7.999 881.737 8.005 882.381 8.011 882.299 8.017 882.128 8.022 882.134 8.028 882.459 8.034 883.246 8.040 884.529 8.046 885.210 8.052 884.756 8.057 883.076 8.063 881.447 8.069 881.325 8.075 880.885 8.081 882.210 8.086 883.351 8.092 884.003 8.098 884.193 8.104 883.825 8.110 883.387 8.115 882.483 8.121 881.667 8.127 880.414 8.133 879.636 8.139 879.572 8.144 880.104 8.150 880.776 8.156 881.084 8.162 879.628 8.168 878.341 8.173 878.540 8.179 879.998 8.185 880.556 8.191 880.570 8.197 880.627 8.202 880.868 8.208 881.251 8.214 881.985 8.220 882.367 8.226 882.447 8.231 882.473 8.237 882.685 8.243 883.504 8.249 884.434 8.255 885.236 8.260 885.561 8.266 885.553 8.272 884.455 8.278 882.445 8.284 880.880 8.290 880.258 8.295 880.360 8.301 880.281 8.307 880.094 8.313 879.226 8.319 877.882 8.324 876.660 8.330 876.866 8.336 878.086 8.342 878.661 8.348 880.555 8.353 881.723 8.359 882.263 8.365 881.816 8.371 881.701 8.377 882.367 8.382 884.011 8.388 885.326 8.394 885.653 8.400 884.795 8.406 882.993 8.411 881.732 8.417 881.084 8.423 879.942 8.429 880.539 8.435 882.181 8.440 883.591 8.446 884.906 8.452 884.859 8.458 883.985 8.464 882.839 8.469 882.191 8.475 882.208 8.481 882.585 8.487 882.888 8.493 882.848 8.499 882.296 8.504 881.273 8.510 879.192 8.516 873.355 8.522 870.468 8.528 872.617 8.533 877.994 8.539 879.696 8.545 880.205 8.551 880.655 8.557 881.445 8.562 882.031 8.568 882.291 8.574 882.259 8.580 882.120 8.586 882.371 8.591 882.905 8.597 883.633 8.603 884.279 8.609 884.723 8.615 884.675 8.620 884.291 8.626 883.404 8.632 881.936 8.638 880.230 8.644 879.417 8.649 879.294 8.655 879.309 8.661 878.862 8.667 878.336 8.673 877.866 8.678 877.601 8.684 878.245 8.690 879.099 8.696 880.148 8.702 881.533 8.707 882.431 8.713 882.577 8.719 882.308 8.725 881.974 8.731 882.045 8.737 882.568 8.742 883.958 8.748 885.272 8.754 885.306 8.760 881.274 8.766 880.938 8.771 880.917 8.777 880.481 8.783 882.181 8.789 883.369 8.795 883.877 8.800 883.895 8.806 883.545 8.812 883.290 8.818 882.716 8.824 881.734 8.829 880.343 8.835 879.768 8.841 879.939 8.847 880.515 8.853 881.185 8.858 881.272 8.864 880.360 8.870 878.913 8.876 878.831 8.882 880.344 8.887 880.358 8.893 880.440 8.899 880.505 8.905 880.614 8.911 880.803 8.916 881.257 8.922 882.081 8.928 882.305 8.934 882.382 8.940 882.554 8.945 883.327 8.951 884.188 8.957 884.908 8.963 885.332 8.969 885.533 8.975 885.727 8.980 886.203 8.986 880.945 8.992 880.376 8.998 880.940 9.004 880.577 9.009 880.280 9.015 879.919 9.021 878.468 9.027 876.860 9.033 876.346 9.038 876.783 9.044 878.357 9.050 880.163 9.056 881.331 9.062 881.660 9.067 881.060 9.073 881.536 9.079 882.330 9.085 883.619 9.091 884.954 9.096 885.424 9.102 884.837 9.108 883.418 9.114 882.085 9.120 881.316 9.125 881.157 9.131 880.717 9.137 882.248 9.143 883.817 9.149 885.096 9.154 884.875 9.160 884.010 9.166 883.169 9.172 882.359 9.178 882.042 9.183 882.414 9.189 882.857 9.195 883.024 9.201 882.704 9.207 881.389 9.213 878.800 9.218 872.814 9.224 870.524 9.230 871.889 9.236 877.192 9.242 879.456 9.247 880.229 9.253 880.791 9.259 881.429 9.265 882.065 9.271 882.367 9.276 882.440 9.282 882.285 9.288 882.368 9.294 882.752 9.300 883.480 9.305 884.193 9.311 884.759 9.317 884.785 9.323 884.403 9.329 883.446 9.334 882.121 9.340 880.651 9.346 879.717 9.352 879.369 9.358 879.248 9.363 878.861 9.369 878.254 9.375 877.953 9.381 878.181 9.387 878.760 9.392 879.418 9.398 880.176 9.404 881.065 9.410 881.094 9.416 880.827 9.421 880.208 9.427 880.409 9.433 879.931 9.439 879.318 9.445 879.100 9.451 879.060 9.456 879.386 9.462 879.683 9.468 880.223 9.474 880.514 9.480 880.448 9.485 881.183 9.491 881.946 9.497 882.394 9.503 882.625 9.509 882.186 9.514 881.595 9.520 881.683 9.526 882.470 9.532 883.553 9.538 884.318 9.543 884.379 9.549 884.565 9.555 883.674 9.561 883.016 9.567 881.680 9.572 881.105 9.578 880.941 9.584 0.000 9.590 0.000 9.596 0.000 9.601 0.000 9.607 0.000 9.613 0.000 9.619 0.000 9.625 0.000 9.630 0.000 9.636 0.000 9.642 0.000 9.648 0.000 9.654 0.000 9.660 0.000 9.665 0.000 9.671 0.000 9.677 0.000 9.683 0.000 9.689 0.000 9.694 0.000 9.700 0.000 9.706 0.000 9.712 0.000 9.718 0.000 9.723 0.000 9.729 0.000 9.735 0.000 9.741 0.000 9.747 0.000 9.752 0.000 9.758 0.000 9.764 0.000 9.770 0.000 9.776 0.000 9.781 0.000 9.787 0.000 9.793 0.000 9.799 0.000 9.805 0.000 9.810 0.000 9.816 0.000 9.822 0.000 9.828 0.000 9.834 0.000 9.839 0.000 9.845 0.000 9.851 0.000 9.857 0.000 9.863 0.000 9.868 0.000 9.874 0.000 9.880 0.000 9.886 0.000 9.892 0.000 9.898 0.000 9.903 0.000 9.909 0.000 9.915 0.000 9.921 0.000 9.927 0.000 9.932 0.000 9.938 0.000 9.944 0.000 9.950 0.000 9.956 0.000 9.961 0.000 9.967 0.000 9.973 0.000 9.979 0.000 9.985 0.000 9.990 0.000 9.996 0.000 10.002 0.000 10.008 0.000 10.014 0.000 10.019 0.000 10.025 0.000 10.031 0.000 10.037 0.000 10.043 0.000 10.048 0.000 10.054 0.000 10.060 0.000 10.066 0.000 10.072 0.000 10.077 0.000 10.083 0.000 10.089 0.000 10.095 0.000 10.101 0.000 10.106 0.000 10.112 0.000 10.118 0.000 10.124 0.000 10.130 0.000 10.136 0.000 10.141 0.000 10.147 0.000 10.153 0.000 10.159 0.000 10.165 0.000 10.170 0.000 10.176 0.000 10.182 0.000 10.188 0.000 10.194 0.000 10.199 0.000 10.205 0.000 10.211 0.000 10.217 0.000 10.223 0.000 10.228 0.000 10.234 0.000 10.240 0.000 10.246 0.000 10.252 0.000 10.257 0.000 10.263 0.000 10.269 0.000 10.275 0.000 10.281 0.000 10.286 0.000 10.292 0.000 10.298 0.000 10.304 0.000 10.310 0.000 10.315 0.000 10.321 0.000 10.327 0.000 10.333 0.000 10.339 0.000 10.344 0.000 10.350 0.000 10.356 0.000 10.362 0.000 10.368 0.000 10.374 0.000 10.379 621.916 10.385 621.411 10.391 621.424 10.397 621.772 10.403 621.811 10.408 622.409 10.414 621.687 10.420 621.600 10.426 621.073 10.432 620.830 10.437 619.745 10.443 619.364 10.449 619.101 10.455 619.130 10.461 619.293 10.466 619.512 10.472 619.557 10.478 619.415 10.484 618.500 10.490 617.766 10.495 617.932 10.501 618.935 10.507 620.198 10.513 620.972 10.519 621.636 10.524 621.274 10.530 637.202 10.536 676.647 10.542 697.592 10.548 697.969 10.553 698.248 10.559 698.191 10.565 697.729 10.571 697.354 10.577 696.777 10.582 695.737 10.588 695.277 10.594 694.960 10.600 695.032 10.606 695.178 10.612 695.341 10.617 695.064 10.623 694.115 10.629 693.447 10.635 693.839 10.641 695.351 10.646 696.797 10.652 697.596 10.658 697.839 10.664 697.994 10.670 698.168 10.675 698.161 10.681 727.209 10.687 738.636 10.693 760.637 10.699 763.464 10.704 770.743 10.710 771.112 10.716 755.953 10.722 783.892 10.728 784.027 10.733 784.143 10.739 784.236 10.745 784.593 10.751 784.805 10.757 784.827 10.762 784.830 10.768 784.779 10.774 785.016 10.780 784.931 10.786 785.194 10.791 785.183 10.797 785.282 10.803 785.518 10.809 785.644 10.815 785.282 10.820 784.953 10.826 784.701 10.832 783.868 10.838 784.370 10.844 785.058 10.850 785.615 10.855 786.183 10.861 786.533 10.867 786.927 10.873 787.033 10.879 786.683 10.884 786.004 10.890 785.259 10.896 784.651 10.902 784.150 10.908 783.886 10.913 783.963 10.919 784.328 10.925 784.692 10.931 784.224 10.937 783.061 10.942 782.249 10.948 782.549 10.954 783.470 10.960 784.271 10.966 784.477 10.971 784.700 10.977 784.987 10.983 785.267 10.989 785.655 10.995 786.053 11.000 786.271 11.006 786.282 11.012 786.227 11.018 786.345 11.024 786.934 11.029 787.772 11.035 788.404 11.041 788.590 11.047 788.266 11.053 787.494 11.059 786.972 11.064 785.839 11.070 784.862 11.076 784.269 11.082 783.955 11.088 783.784 11.093 784.034 11.099 787.909 11.105 801.065 11.111 856.246 11.117 878.895 11.122 877.808 11.128 878.241 11.134 879.112 11.140 879.640 11.146 879.617 11.151 879.874 11.157 880.082 11.163 880.315 11.169 880.743 11.175 880.909 11.180 881.036 11.186 881.087 11.192 881.287 11.198 881.364 11.204 881.433 11.209 881.460 11.215 881.559 11.221 881.795 11.227 881.662 11.233 881.477 11.238 881.411 11.244 880.820 11.250 881.041 11.256 881.722 11.262 882.238 11.267 882.388 11.273 882.444 11.279 882.362 11.285 882.178 11.291 881.833 11.297 881.291 11.302 880.934 11.308 880.582 11.314 880.405 11.320 880.545 11.326 881.054 11.331 0.000 11.337 0.000 11.343 0.000 11.349 0.000 11.355 0.000 11.360 0.000 11.366 0.000 11.372 0.000 11.378 0.000 11.384 0.000 11.389 0.000 11.395 0.000 11.401 0.000 11.407 0.000 11.413 0.000 11.418 0.000 11.424 887.447 11.430 930.653 11.436 932.518 11.442 930.212 11.447 929.008 11.453 931.048 11.459 932.344 11.465 931.775 11.471 932.115 11.476 932.771 11.482 932.801 11.488 933.200 11.494 933.355 11.500 933.419 11.505 933.443 11.511 933.551 11.517 933.596 11.523 933.643 11.529 933.688 11.535 933.840 11.540 934.223 11.546 933.846 11.552 934.046 11.558 934.598 11.564 933.517 11.569 934.203 11.575 934.933 11.581 935.442 11.587 935.173 11.593 934.932 11.598 934.370 11.604 933.204 11.610 932.229 11.616 931.852 11.622 932.013 11.627 932.664 11.633 933.467 11.639 934.248 11.645 933.594 11.651 931.262 11.656 931.104 11.662 932.674 11.668 933.356 11.674 933.425 11.680 933.616 11.685 933.921 11.691 934.440 11.697 938.051 11.703 950.946 11.709 1045.451 11.714 1045.240 11.720 1044.234 11.726 1044.938 11.732 1045.938 11.738 1045.831 11.743 1046.449 11.749 1046.923 11.755 1047.367 11.761 1047.860 11.767 1047.872 11.773 1047.975 11.778 1048.084 11.784 1048.080 11.790 1048.003 11.796 1047.949 11.802 1048.324 11.807 1048.786 11.813 1049.320 11.819 1050.086 11.825 1048.893 11.831 1049.301 11.836 1049.822 11.842 1049.970 11.848 1049.467 11.854 1048.401 11.860 1047.578 11.865 1046.526 11.871 1045.736 11.877 1045.689 11.883 1046.306 11.889 1047.093 11.894 1046.539 11.900 1045.522 11.906 1045.458 11.912 1046.227 11.918 1047.736 11.923 1047.834 11.929 1047.861 11.935 1048.004 11.941 1048.240 11.947 1048.498 11.952 1048.700 11.958 1049.012 11.964 1049.531 11.970 1050.388 11.976 1051.325 11.981 1052.029 11.987 1052.041 11.993 1051.497 11.999 1050.057 12.005 1048.790 12.011 1048.193 12.016 1046.430 12.022 979.080 12.028 931.659 12.034 931.021 12.040 930.516 12.045 930.130 12.051 930.623 12.057 931.642 12.063 931.597 12.069 931.940 12.074 932.414 12.080 932.688 12.086 933.129 12.092 933.504 12.098 933.400 12.103 933.391 12.109 933.470 12.115 933.578 12.121 933.633 12.127 933.667 12.132 933.734 12.138 934.101 12.144 933.992 12.150 934.056 12.156 934.719 12.161 933.473 12.167 933.975 12.173 934.756 12.179 935.290 12.185 935.487 12.190 935.012 12.196 934.547 12.202 933.440 12.208 932.424 12.214 931.886 12.220 931.910 12.225 932.451 12.231 933.270 12.237 934.080 12.243 933.783 12.249 931.309 12.254 931.049 12.260 932.166 12.266 933.262 12.272 933.374 12.278 933.536 12.283 933.848 12.289 934.204 12.295 934.544 12.301 934.827 12.307 934.993 12.312 935.191 12.318 935.602 12.324 936.265 12.330 937.170 12.336 937.866 12.341 937.718 12.347 936.718 12.353 935.421 12.359 934.080 12.365 933.139 12.370 932.606 12.376 932.627 12.382 933.524 12.388 934.750 12.394 935.048 12.399 934.419 12.405 932.757 12.411 931.235 12.417 930.298 12.423 929.080 12.428 927.504 12.434 927.933 12.440 929.655 12.446 930.406 12.452 936.681 12.458 937.398 12.463 936.087 12.469 935.357 12.475 935.268 12.481 935.557 12.487 936.324 12.492 936.756 12.498 938.822 12.504 939.544 12.510 938.242 12.516 935.579 12.521 934.583 12.527 934.186 12.533 934.637 12.539 935.091 12.545 935.331 12.550 935.449 12.556 935.503 12.562 935.105 12.568 934.546 12.574 933.767 12.579 928.816 12.585 923.781 12.591 924.117 12.597 930.528 12.603 933.064 12.608 933.480 12.614 934.125 12.620 934.454 12.626 934.603 12.632 934.471 12.637 934.662 12.643 935.114 12.649 935.546 12.655 936.142 12.661 936.260 12.666 936.561 12.672 936.694 12.678 936.305 12.684 935.665 12.690 934.804 12.696 932.650 12.701 931.722 12.707 931.518 12.713 931.917 12.719 931.384 12.725 930.267 12.730 929.884 12.736 929.950 12.742 930.560 12.748 932.199 12.754 933.373 12.759 934.216 12.765 934.491 12.771 934.493 12.777 934.412 12.783 934.794 12.788 935.637 12.794 936.936 12.800 937.760 12.806 937.492 12.812 935.828 12.817 934.849 12.823 934.040 12.829 934.897 12.835 936.046 12.841 936.797 12.846 936.941 12.852 936.890 12.858 936.400 12.864 935.420 12.870 934.294 12.875 933.159 12.881 932.640 12.887 932.687 12.893 933.579 12.899 935.409 12.904 944.131 12.910 845.308 12.916 686.563 12.922 688.507 12.928 697.747 12.934 697.721 12.939 689.476 12.945 691.255 12.951 692.444 12.957 693.383 12.963 695.479 12.968 695.087 12.974 694.959 12.980 695.054 12.986 695.292 12.992 695.252 12.997 694.646 13.003 693.619 13.009 693.500 13.015 694.421 13.021 696.141 13.026 697.263 13.032 697.835 13.038 698.049 13.044 698.117 13.050 698.066 13.055 697.763 13.061 697.416 13.067 697.069 13.073 696.864 13.079 697.007 13.084 696.523 13.090 696.890 13.096 697.433 13.102 697.674 13.108 697.587 13.113 696.857 13.119 696.471 13.125 696.712 13.131 697.162 13.137 697.427 13.142 697.372 13.148 697.221 13.154 696.833 13.160 696.423 13.166 696.230 13.172 696.390 13.177 696.807 13.183 697.029 13.189 697.136 13.195 696.799 13.201 695.642 13.206 693.956 13.212 692.438 13.218 692.298 13.224 693.852 13.230 695.492 13.235 696.652 13.241 697.306 13.247 697.668 13.253 697.788 13.259 697.771 13.264 697.615 13.270 697.409 13.276 697.208 13.282 697.274 13.288 697.680 13.293 698.157 13.299 698.669 13.305 699.004 13.311 699.364 13.317 699.656 13.322 699.836 13.328 699.709 13.334 699.387 13.340 699.068 13.346 698.529 13.351 698.044 13.357 697.702 13.363 697.508 13.369 697.493 13.375 697.434 13.380 697.115 13.386 696.592 13.392 696.117 13.398 695.735 13.404 695.346 13.410 695.591 13.415 695.800 13.421 695.911 13.427 695.854 13.433 695.332 13.439 693.602 13.444 692.963 13.450 693.746 13.456 696.172 13.462 697.688 13.468 698.305 13.473 698.698 13.479 698.838 13.485 698.694 13.491 697.764 13.497 696.961 13.502 664.925 13.508 639.909 13.514 586.652 13.520 586.716 13.526 587.146 13.531 587.269 13.537 587.123 13.543 586.621 13.549 586.556 13.555 586.106 13.560 585.571 13.566 584.785 13.572 584.459 13.578 584.321 13.584 584.462 13.589 584.662 13.595 584.825 13.601 584.876 13.607 584.472 13.613 583.581 13.619 582.945 13.624 583.185 13.630 584.177 13.636 585.554 13.642 586.291 13.648 586.668 13.653 586.984 13.659 587.012 13.665 587.031 13.671 587.020 13.677 586.879 13.682 586.609 13.688 586.290 13.694 585.889 13.700 585.649 13.706 585.459 13.711 585.653 13.717 586.182 13.723 586.854 13.729 587.181 13.735 587.169 13.740 586.807 13.746 586.178 13.752 585.346 13.758 585.598 13.764 586.002 13.769 586.477 13.775 586.644 13.781 586.577 13.787 586.445 13.793 586.180 13.798 585.803 13.804 585.526 13.810 585.415 13.816 585.629 13.822 585.971 13.827 586.324 13.833 586.431 13.839 586.367 13.845 586.056 13.851 585.299 13.857 583.593 13.862 582.061 13.868 581.475 13.874 582.683 13.880 584.154 13.886 585.444 13.891 586.043 13.897 586.534 13.903 586.797 13.909 586.953 13.915 587.030 13.920 587.005 13.926 586.986 13.932 586.875 13.938 586.632 13.944 586.450 13.949 586.569 13.955 586.816 13.961 587.315 13.967 587.497 13.973 587.724 13.978 588.249 13.984 589.668 13.990 590.388 13.996 588.172 14.002 549.787 14.007 504.313 14.013 498.968 14.019 495.252 14.025 495.459 14.031 499.323 14.036 458.346 14.042 466.307 14.048 458.359 14.054 457.553 14.060 456.459 14.065 455.527 14.071 454.965 14.077 455.074 14.083 455.656 14.089 465.873 14.095 466.016 14.100 466.113 14.106 466.192 14.112 466.199 14.118 466.195 14.124 466.204 14.129 466.272 14.135 466.349 14.141 466.393 14.147 466.426 14.153 466.478 14.158 466.407 14.164 466.602 14.170 466.957 14.176 467.457 14.182 467.883 14.187 468.189 14.193 468.325 14.199 468.184 14.205 467.976 14.211 467.756 14.216 467.837 14.222 467.557 14.228 467.004 14.234 466.600 14.240 466.062 14.245 466.052 14.251 466.309 14.257 466.719 14.263 467.078 14.269 467.364 14.274 467.541 14.280 467.846 14.286 468.216 14.292 468.263 14.298 468.124 14.303 467.880 14.309 467.666 14.315 467.624 14.321 467.526 14.327 467.416 14.333 467.253 14.338 467.108 14.344 467.004 14.350 466.965 14.356 466.964 14.362 467.022 14.367 467.240 14.373 467.553 14.379 467.721 14.385 467.656 14.391 467.364 14.396 467.082 14.402 466.777 14.408 0.000 14.414 0.000 14.420 0.000 14.425 390.642 14.431 783.547 14.437 783.094 14.443 782.907 14.449 782.357 14.454 782.389 14.460 783.210 14.466 783.746 14.472 783.571 14.478 783.939 14.483 784.093 14.489 784.143 14.495 784.410 14.501 784.756 14.507 784.820 14.512 784.846 14.518 784.757 14.524 784.745 14.530 785.080 14.536 784.975 14.541 785.223 14.547 785.214 14.553 785.412 14.559 785.636 14.565 785.496 14.571 785.142 14.576 784.815 14.582 783.663 14.588 784.003 14.594 784.703 14.600 785.357 14.605 785.891 14.611 786.452 14.617 786.751 14.623 787.005 14.629 786.908 14.634 786.348 14.640 785.539 14.646 784.945 14.652 784.379 14.658 783.997 14.663 783.875 14.669 784.091 14.675 784.583 14.681 784.700 14.687 783.743 14.692 782.492 14.698 782.248 14.704 783.004 14.710 783.941 14.716 784.405 14.721 784.573 14.727 784.858 14.733 785.129 14.739 785.446 14.745 785.847 14.750 786.211 14.756 786.298 14.762 786.254 14.768 786.247 14.774 786.573 14.780 787.343 14.785 788.097 14.791 788.562 14.797 788.428 14.803 787.928 14.809 787.438 14.814 786.384 14.820 785.319 14.826 784.521 14.832 784.132 14.838 783.959 14.843 784.156 14.849 784.740 14.855 786.823 14.861 787.544 14.867 786.952 14.872 784.509 14.878 783.438 14.884 783.019 14.890 783.114 14.896 783.765 14.901 785.702 14.907 787.139 14.913 787.459 14.919 786.691 14.925 785.548 14.930 784.735 14.936 783.570 14.942 783.371 14.948 783.799 14.954 785.038 14.959 785.573 14.965 785.746 14.971 786.094 14.977 787.918 14.983 788.060 14.988 788.099 14.994 787.144 15.000 786.476 15.006 785.970 15.012 753.793 15.018 697.481 15.023 697.745 15.029 697.782 15.035 698.131 15.041 698.232 15.047 698.086 15.052 697.579 15.058 697.256 15.064 696.691 15.070 695.726 15.076 695.324 15.081 695.102 15.087 695.046 15.093 695.207 15.099 695.339 15.105 695.048 15.110 694.123 15.116 693.489 15.122 693.878 15.128 706.159 15.134 707.524 15.139 708.375 15.145 709.222 15.151 710.293 15.157 697.788 15.163 697.831 15.168 0.000 15.174 0.000 15.180 0.000 15.186 0.000 15.192 0.000 15.197 0.000 15.203 0.000 15.209 0.000 15.215 0.000 15.221 0.000 15.226 0.000 15.232 0.000 15.238 0.000 15.244 0.000 15.250 0.000 15.256 0.000 15.261 0.000 15.267 0.000 15.273 0.000 15.279 0.000 15.285 0.000 15.290 0.000 15.296 0.000 15.302 0.000 15.308 0.000 15.314 0.000 15.319 0.000 15.325 0.000 15.331 0.000 15.337 0.000 15.343 0.000 15.348 0.000 15.354 0.000 15.360 0.000 15.366 0.000 15.372 0.000 15.377 0.000 15.383 0.000 15.389 0.000 15.395 0.000 15.401 0.000 15.406 0.000 15.412 0.000 15.418 0.000 15.424 0.000 15.430 0.000 15.435 0.000 15.441 0.000 15.447 0.000 15.453 0.000 15.459 0.000 15.464 0.000 15.470 603.329 15.476 586.720 15.482 586.364 15.488 586.395 15.494 586.771 15.499 586.719 15.505 587.373 15.511 586.590 15.517 586.519 15.523 586.135 15.528 585.968 15.534 585.112 15.540 584.704 15.546 584.383 15.552 584.336 15.557 584.511 15.563 584.717 15.569 584.850 15.575 584.873 15.581 584.438 15.586 583.593 15.592 583.015 15.598 583.301 15.604 584.302 15.610 585.499 15.615 586.264 15.621 0.000 15.627 0.000 15.633 0.000 15.639 0.000 15.644 0.000 15.650 782.179 15.656 782.348 15.662 783.402 15.668 783.830 15.673 783.656 15.679 784.013 15.685 784.083 15.691 784.169 15.697 784.487 15.702 784.793 15.708 784.839 15.714 784.839 15.720 784.755 15.726 784.977 15.732 784.916 15.737 784.993 15.743 785.199 15.749 785.235 15.755 785.482 15.761 785.670 15.766 785.424 15.772 785.061 15.778 784.757 15.784 783.870 15.790 784.248 15.795 784.895 15.801 785.496 15.807 786.047 15.813 786.574 15.819 786.825 15.824 787.020 15.830 786.800 15.836 786.166 15.842 785.376 15.848 784.784 15.853 784.252 15.859 783.890 15.865 783.924 15.871 784.205 15.877 784.672 15.882 784.508 15.888 783.606 15.894 782.791 15.900 783.104 15.906 777.585 15.911 777.404 15.917 777.311 15.923 782.582 15.929 776.787 15.935 777.602 15.940 748.820 15.946 749.079 15.952 746.955 15.958 744.191 15.964 739.177 15.970 742.524 15.975 739.072 15.981 712.950 15.987 711.181 15.993 709.607 15.999 708.040 16.004 706.560 16.010 694.401 16.016 696.155 16.022 697.250 16.028 697.838 16.033 698.045 16.039 698.109 16.045 698.037 16.051 697.782 16.057 697.431 16.062 697.100 16.068 696.860 16.074 697.034 16.080 696.548 16.086 696.873 16.091 697.435 16.097 697.652 16.103 697.478 16.109 697.060 16.115 696.628 16.120 696.690 16.126 697.148 16.132 697.412 16.138 697.382 16.144 697.162 16.149 696.817 16.155 696.411 16.161 696.215 16.167 696.396 16.173 696.814 16.179 697.115 16.184 697.129 16.190 696.784 16.196 695.599 16.202 693.938 16.208 692.422 16.213 692.307 16.219 693.845 16.225 695.501 16.231 696.631 16.237 697.289 16.242 697.645 16.248 697.783 16.254 697.764 16.260 697.614 16.266 697.414 16.271 697.209 16.277 697.265 16.283 697.677 16.289 698.157 16.295 698.659 16.300 699.007 16.306 699.351 16.312 699.616 16.318 699.840 16.324 699.709 16.329 699.404 16.335 699.054 16.341 698.543 16.347 698.050 16.353 697.706 16.358 697.521 16.364 697.497 16.370 697.453 16.376 697.111 16.382 696.589 16.387 696.102 16.393 695.743 16.399 695.351 16.405 695.602 16.411 695.796 16.417 695.906 16.422 695.852 16.428 695.358 16.434 693.643 16.440 692.995 16.446 693.726 16.451 696.178 16.457 697.690 16.463 698.303 16.469 698.708 16.475 698.833 16.480 698.811 16.486 698.428 16.492 697.392 16.498 697.299 16.504 697.885 16.509 699.021 16.515 699.473 16.521 699.567 16.527 698.284 16.533 698.545 16.538 699.352 16.544 700.242 16.550 701.062 16.556 700.919 16.562 700.296 16.567 699.935 16.573 699.645 16.579 699.068 16.585 698.388 16.591 697.696 16.596 697.321 16.602 697.414 16.608 697.863 16.614 698.284 16.620 698.395 16.625 698.119 16.631 697.424 16.637 695.774 16.643 693.117 16.649 691.653 16.655 692.483 16.660 695.031 16.666 696.600 16.672 696.177 16.678 703.459 16.684 666.380 16.689 640.209 16.695 586.584 16.701 586.688 16.707 587.135 16.713 587.242 16.718 587.068 16.724 586.622 16.730 586.550 16.736 586.094 16.742 585.567 16.747 584.784 16.753 584.476 16.759 584.332 16.765 584.479 16.771 584.645 16.776 584.821 16.782 584.904 16.788 584.602 16.794 583.801 16.800 583.114 16.805 583.209 16.811 584.073 16.817 0.000 16.823 0.000 16.829 0.000 16.834 0.000 16.840 0.000 16.846 0.000 16.852 0.000 16.858 0.000 16.863 783.529 16.869 783.853 16.875 783.869 16.881 784.059 16.887 784.115 16.893 784.255 16.898 784.594 16.904 784.896 16.910 784.835 16.916 784.812 16.922 784.786 16.927 785.012 16.933 784.949 16.939 785.219 16.945 785.206 16.951 785.287 16.956 785.551 16.962 785.657 16.968 785.370 16.974 784.930 16.980 784.717 16.985 783.861 16.991 784.380 16.997 785.075 17.003 785.626 17.009 786.182 17.014 786.680 17.020 786.902 17.026 787.058 17.032 786.715 17.038 786.041 17.043 785.293 17.049 784.671 17.055 784.096 17.061 783.684 17.067 783.594 17.072 783.732 17.078 784.305 17.084 784.286 17.090 785.266 17.096 776.847 17.101 747.648 17.107 733.335 17.113 697.692 17.119 697.853 17.125 698.198 17.131 698.090 17.136 698.054 17.142 697.309 17.148 696.795 17.154 695.716 17.160 695.281 17.165 694.965 17.171 695.008 17.177 695.148 17.183 695.334 17.189 695.119 17.194 694.195 17.200 693.441 17.206 693.777 17.212 695.141 17.218 696.682 17.223 697.547 17.229 697.937 17.235 698.040 17.241 697.995 17.247 697.815 17.252 697.505 17.258 697.309 17.264 0.000 17.270 0.000 17.276 0.000 17.281 0.000 17.287 0.000 17.293 0.000 17.299 0.000 17.305 0.000 17.310 0.000 17.316 0.000 17.322 0.000 17.328 0.000 17.334 0.000 17.340 0.000 17.345 0.000 17.351 0.000 17.357 0.000 17.363 0.000 17.369 0.000 17.374 0.000 17.380 0.000 17.386 0.000 17.392 0.000 17.398 0.000 17.403 0.000 17.409 0.000 17.415 0.000 17.421 699.952 17.427 700.504 17.432 697.495 17.438 697.782 17.444 698.060 17.450 698.538 17.456 698.177 17.461 697.582 17.467 697.211 17.473 696.843 17.479 695.621 17.485 695.178 17.490 694.962 17.496 695.034 17.502 695.199 17.508 695.278 17.514 694.906 17.519 693.812 17.525 693.482 17.531 694.149 17.537 695.812 17.543 697.070 17.548 697.743 17.554 698.031 17.560 698.101 17.566 698.100 17.572 697.879 17.578 697.544 17.583 697.166 17.589 696.978 17.595 696.940 17.601 697.254 17.607 696.785 17.612 697.222 17.618 697.651 17.624 697.605 17.630 696.971 17.636 696.298 17.641 696.631 17.647 697.047 17.653 697.391 17.659 697.430 17.665 697.299 17.670 696.922 17.676 696.505 17.682 696.247 17.688 696.281 17.694 696.645 17.699 697.030 17.705 697.161 17.711 696.911 17.717 696.300 17.723 694.914 17.728 0.000 17.734 0.000 17.740 0.000 17.746 0.000 17.752 0.000 17.757 0.000 17.763 0.000 17.769 0.000 17.775 0.000 17.781 0.000 17.786 0.000 17.792 0.000 17.798 0.000 17.804 0.000 17.810 0.000 17.816 0.000 17.821 0.000 17.827 0.000 17.833 0.000 17.839 0.000 17.845 0.000 17.850 0.000 17.856 0.000 17.862 0.000 17.868 0.000 17.874 699.363 17.879 697.860 17.885 697.223 17.891 697.473 17.897 697.842 17.903 697.362 17.908 697.579 17.914 697.104 17.920 696.621 17.926 695.664 17.932 695.228 17.937 694.963 17.943 694.961 17.949 695.136 17.955 695.366 17.961 695.143 17.966 694.317 17.972 693.581 17.978 693.901 17.984 695.205 17.990 696.641 17.995 697.475 18.001 697.937 18.007 698.043 18.013 698.080 18.019 697.902 18.024 697.572 18.030 697.188 18.036 696.942 18.042 696.827 18.048 697.084 18.054 696.656 18.059 697.051 18.065 697.583 18.071 697.644 18.077 697.111 18.083 696.673 18.088 696.508 18.094 696.872 18.100 697.257 18.106 697.419 18.112 697.333 18.117 697.011 18.123 696.609 18.129 696.300 18.135 696.265 18.141 696.606 18.146 696.908 18.152 697.129 18.158 697.007 18.164 696.213 18.170 694.738 18.175 693.073 18.181 692.015 18.187 692.842 18.193 694.680 18.199 696.179 18.204 697.069 18.210 697.580 18.216 697.785 18.222 697.825 18.228 697.737 18.233 697.554 18.239 697.362 18.245 697.249 18.251 697.539 18.257 697.970 18.262 698.469 18.268 698.903 18.274 699.245 18.280 699.589 18.286 699.851 18.292 699.899 18.297 699.668 18.303 699.338 18.309 698.903 18.315 698.339 18.321 697.914 18.326 697.612 18.332 697.545 18.338 697.546 18.344 697.347 18.350 696.899 18.355 696.259 18.361 695.883 18.367 695.274 18.373 695.399 18.379 695.687 18.384 695.872 18.390 695.928 18.396 695.766 18.402 694.788 18.408 693.083 18.413 693.191 18.419 694.810 18.425 697.109 18.431 698.111 18.437 698.553 18.442 698.846 18.448 698.905 18.454 698.795 18.460 698.130 18.466 697.303 18.471 697.586 18.477 698.535 18.483 699.349 18.489 699.684 18.495 698.595 18.500 698.283 18.506 699.024 18.512 699.829 18.518 700.821 18.524 701.197 18.530 700.782 18.535 700.159 18.541 699.819 18.547 699.541 18.553 698.811 18.559 698.053 18.564 697.464 18.570 697.311 18.576 697.579 18.582 698.106 18.588 698.370 18.593 698.293 18.599 697.799 18.605 696.597 18.611 693.899 18.617 691.644 18.622 691.760 18.628 694.185 18.634 696.424 18.640 697.435 18.646 697.751 18.651 697.830 18.657 697.822 18.663 697.681 18.669 697.445 18.675 697.299 18.680 697.575 18.686 698.033 18.692 698.545 18.698 698.911 18.704 699.126 18.709 699.450 18.715 699.800 18.721 700.242 18.727 700.781 18.733 701.358 18.739 702.089 18.744 702.648 18.750 703.154 18.756 702.838 18.762 702.457 18.768 700.061 18.773 698.967 18.779 698.249 18.785 697.564 18.791 696.702 18.797 696.052 18.802 695.909 18.808 696.061 18.814 0.000 18.820 0.000 18.826 0.000 18.831 0.000 18.837 0.000 18.843 0.000 18.849 0.000 18.855 0.000 18.860 0.000 18.866 0.000 18.872 0.000 18.878 0.000 18.884 0.000 18.889 0.000 18.895 0.000 18.901 0.000 18.907 0.000 18.913 0.000 18.918 0.000 18.924 0.000 18.930 0.000 18.936 0.000 18.942 0.000 18.947 0.000 18.953 0.000 18.959 0.000 18.965 0.000 18.971 0.000 18.977 0.000 18.982 0.000 18.988 0.000 18.994 0.000 19.000 0.000 19.006 0.000 19.011 0.000 19.017 0.000 19.023 0.000 19.029 0.000 19.035 0.000 19.040 0.000 19.046 0.000 19.052 0.000 19.058 0.000 19.064 0.000 19.069 0.000 19.075 0.000 19.081 0.000 19.087 0.000 19.093 0.000 19.098 0.000 19.104 0.000 19.110 0.000 19.116 0.000 19.122 0.000 19.127 0.000 19.133 0.000 19.139 0.000 19.145 0.000 19.151 0.000 19.156 0.000 19.162 0.000 19.168 0.000 19.174 0.000 19.180 0.000 19.185 0.000 19.191 0.000 19.197 0.000 19.203 0.000 19.209 0.000 19.215 0.000 mir_eval-0.8.2/tests/data/melody/ref06.txt000066400000000000000000001465331475740344600204000ustar00rootroot000000000000000.000 0.000 0.006 0.000 0.012 0.000 0.017 0.000 0.023 0.000 0.029 0.000 0.035 0.000 0.041 0.000 0.046 0.000 0.052 0.000 0.058 576.320 0.064 606.502 0.070 637.346 0.075 655.822 0.081 666.976 0.087 674.818 0.093 677.506 0.099 676.962 0.104 674.369 0.110 669.799 0.116 663.701 0.122 657.244 0.128 651.575 0.134 645.313 0.139 638.909 0.145 634.276 0.151 630.951 0.157 627.830 0.163 625.400 0.168 624.327 0.174 625.078 0.180 627.619 0.186 630.929 0.192 633.800 0.197 637.129 0.203 651.438 0.209 665.015 0.215 667.401 0.221 668.249 0.226 669.001 0.232 669.737 0.238 669.828 0.244 668.711 0.250 666.133 0.255 661.282 0.261 652.909 0.267 639.384 0.273 624.479 0.279 608.993 0.284 593.117 0.290 584.796 0.296 580.200 0.302 578.526 0.308 579.048 0.313 581.572 0.319 586.534 0.325 594.283 0.331 606.730 0.337 627.955 0.342 647.922 0.348 660.954 0.354 674.040 0.360 680.127 0.366 682.205 0.372 681.230 0.377 677.701 0.383 671.768 0.389 665.481 0.395 658.964 0.401 653.275 0.406 630.557 0.412 620.415 0.418 614.510 0.424 619.963 0.430 631.101 0.435 630.818 0.441 634.794 0.447 655.478 0.453 660.156 0.459 665.397 0.464 666.227 0.470 661.840 0.476 661.673 0.482 662.006 0.488 665.055 0.493 668.183 0.499 649.823 0.505 643.263 0.511 561.110 0.517 571.228 0.522 575.607 0.528 582.497 0.534 589.260 0.540 609.509 0.546 619.865 0.551 626.337 0.557 633.088 0.563 636.502 0.569 636.590 0.575 634.660 0.580 630.563 0.586 623.880 0.592 614.673 0.598 607.215 0.604 598.116 0.610 578.606 0.615 568.585 0.621 560.326 0.627 556.667 0.633 556.150 0.639 558.231 0.644 562.462 0.650 569.033 0.656 577.487 0.662 586.000 0.668 596.314 0.673 606.386 0.679 619.551 0.685 632.096 0.691 643.902 0.697 655.226 0.702 659.894 0.708 661.595 0.714 660.951 0.720 658.160 0.726 652.910 0.731 645.551 0.737 635.567 0.743 624.836 0.749 615.250 0.755 605.975 0.760 586.886 0.766 578.128 0.772 571.664 0.778 567.012 0.784 565.282 0.789 566.593 0.795 571.551 0.801 579.606 0.807 589.424 0.813 599.185 0.819 613.369 0.824 632.417 0.830 654.146 0.836 671.563 0.842 682.396 0.848 690.696 0.853 695.257 0.859 697.761 0.865 697.904 0.871 695.454 0.877 689.476 0.882 680.526 0.888 672.622 0.894 663.993 0.900 652.571 0.906 638.354 0.911 627.774 0.917 620.476 0.923 615.245 0.929 611.327 0.935 609.734 0.940 611.035 0.946 615.311 0.952 621.406 0.958 628.980 0.964 638.910 0.969 656.999 0.975 678.256 0.981 690.899 0.987 699.427 0.993 702.130 0.998 702.024 1.004 700.120 1.010 695.788 1.016 683.325 1.022 668.207 1.027 670.610 1.033 675.992 1.039 672.163 1.045 665.488 1.051 665.023 1.057 666.931 1.062 672.679 1.068 680.447 1.074 681.708 1.080 665.438 1.086 663.022 1.091 668.943 1.097 665.793 1.103 661.375 1.109 663.831 1.115 619.057 1.120 0.000 1.126 0.000 1.132 0.000 1.138 0.000 1.144 0.000 1.149 0.000 1.155 0.000 1.161 0.000 1.167 0.000 1.173 0.000 1.178 0.000 1.184 691.845 1.190 728.971 1.196 714.611 1.202 718.058 1.207 709.479 1.213 708.840 1.219 702.440 1.225 697.365 1.231 702.966 1.236 702.185 1.242 703.383 1.248 704.441 1.254 706.203 1.260 709.389 1.265 714.812 1.271 722.208 1.277 738.383 1.283 765.755 1.289 778.508 1.295 786.374 1.300 791.035 1.306 792.234 1.312 789.966 1.318 783.433 1.324 773.654 1.329 760.780 1.335 739.384 1.341 721.589 1.347 708.496 1.353 692.036 1.358 678.210 1.364 668.273 1.370 662.775 1.376 660.278 1.382 660.487 1.387 662.596 1.393 666.258 1.399 671.764 1.405 678.431 1.411 689.912 1.416 701.447 1.422 711.519 1.428 721.369 1.434 728.917 1.440 734.357 1.445 737.046 1.451 736.689 1.457 732.946 1.463 726.324 1.469 717.922 1.474 710.004 1.480 694.902 1.486 679.993 1.492 666.511 1.498 619.162 1.503 599.404 1.509 592.120 1.515 590.217 1.521 592.000 1.527 598.065 1.533 610.025 1.538 626.182 1.544 635.077 1.550 644.484 1.556 655.728 1.562 664.512 1.567 670.928 1.573 678.162 1.579 682.154 1.585 684.806 1.591 685.129 1.596 682.576 1.602 677.683 1.608 669.429 1.614 656.222 1.620 642.495 1.625 629.036 1.631 618.604 1.637 606.816 1.643 600.481 1.649 597.947 1.654 598.029 1.660 600.775 1.666 606.719 1.672 617.704 1.678 627.809 1.683 640.274 1.689 655.494 1.695 665.677 1.701 670.706 1.707 672.690 1.712 672.001 1.718 669.234 1.724 664.553 1.730 658.141 1.736 644.654 1.741 631.635 1.747 628.839 1.753 689.089 1.759 698.238 1.765 653.443 1.771 662.709 1.776 665.214 1.782 665.892 1.788 667.986 1.794 671.109 1.800 667.191 1.805 663.305 1.811 653.547 1.817 618.936 1.823 615.091 1.829 613.506 1.834 619.579 1.840 630.047 1.846 641.440 1.852 646.161 1.858 647.457 1.863 646.981 1.869 645.197 1.875 641.958 1.881 637.065 1.887 631.357 1.892 624.540 1.898 615.284 1.904 603.654 1.910 591.284 1.916 577.357 1.921 570.492 1.927 564.768 1.933 562.411 1.939 562.584 1.945 565.611 1.950 570.820 1.956 576.674 1.962 584.342 1.968 593.069 1.974 602.167 1.980 612.766 1.985 622.747 1.991 631.711 1.997 638.773 2.003 646.036 2.009 650.992 2.014 652.460 2.020 650.490 2.026 644.641 2.032 637.017 2.038 629.288 2.043 621.671 2.049 616.601 2.055 611.405 2.061 539.559 2.067 526.205 2.072 536.828 2.078 582.867 2.084 606.838 2.090 610.773 2.096 616.454 2.101 625.283 2.107 635.225 2.113 646.828 2.119 660.791 2.125 682.156 2.130 691.595 2.136 697.248 2.142 700.276 2.148 699.316 2.154 695.097 2.159 687.720 2.165 675.910 2.171 667.324 2.177 664.618 2.183 656.516 2.188 651.003 2.194 647.333 2.200 647.217 2.206 649.499 2.212 650.204 2.218 649.777 2.223 645.694 2.229 642.689 2.235 646.915 2.241 658.625 2.247 669.995 2.252 672.753 2.258 673.717 2.264 673.556 2.270 672.962 2.276 671.841 2.281 670.746 2.287 668.655 2.293 663.523 2.299 657.525 2.305 648.463 2.310 646.593 2.316 641.453 2.322 605.460 2.328 603.822 2.334 596.589 2.339 637.532 2.345 641.819 2.351 643.147 2.357 642.947 2.363 602.670 2.368 606.624 2.374 608.269 2.380 610.122 2.386 612.433 2.392 615.672 2.397 619.733 2.403 623.368 2.409 625.546 2.415 626.502 2.421 626.379 2.426 625.187 2.432 622.813 2.438 618.448 2.444 612.222 2.450 604.044 2.456 593.958 2.461 582.565 2.467 573.023 2.473 563.688 2.479 556.223 2.485 551.959 2.490 550.461 2.496 551.325 2.502 554.046 2.508 558.863 2.514 566.052 2.519 576.576 2.525 587.885 2.531 594.488 2.537 600.381 2.543 605.602 2.548 610.297 2.554 613.756 2.560 615.563 2.566 615.443 2.572 613.227 2.577 608.093 2.583 601.300 2.589 594.475 2.595 590.355 2.601 574.836 2.606 575.319 2.612 585.250 2.618 613.823 2.624 612.389 2.630 608.214 2.635 611.609 2.641 492.950 2.647 502.112 2.653 395.557 2.659 447.956 2.664 456.808 2.670 479.561 2.676 490.503 2.682 495.611 2.688 499.755 2.694 503.467 2.699 505.862 2.705 506.898 2.711 506.836 2.717 505.733 2.723 503.620 2.728 500.747 2.734 497.429 2.740 492.896 2.746 487.613 2.752 482.761 2.757 477.214 2.763 464.345 2.769 461.804 2.775 461.406 2.781 463.712 2.786 474.835 2.792 478.779 2.798 483.468 2.804 488.156 2.810 493.618 2.815 499.747 2.821 505.079 2.827 509.533 2.833 513.218 2.839 516.637 2.844 518.581 2.850 518.374 2.856 515.742 2.862 510.528 2.868 504.744 2.873 498.178 2.879 491.645 2.885 478.431 2.891 0.000 2.897 0.000 2.902 0.000 2.908 0.000 2.914 0.000 2.920 0.000 2.926 0.000 2.932 509.939 2.937 510.781 2.943 514.312 2.949 518.110 2.955 527.219 2.961 522.760 2.966 527.501 2.972 555.586 2.978 561.013 2.984 568.178 2.990 575.903 2.995 582.096 3.001 584.112 3.007 583.284 3.013 580.535 3.019 576.619 3.024 571.896 3.030 565.007 3.036 556.856 3.042 549.037 3.048 542.112 3.053 537.268 3.059 533.801 3.065 530.470 3.071 527.925 3.077 526.818 3.082 527.439 3.088 529.853 3.094 533.741 3.100 538.842 3.106 546.714 3.111 556.947 3.117 565.991 3.123 573.604 3.129 581.898 3.135 587.731 3.140 591.371 3.146 593.541 3.152 595.019 3.158 595.746 3.164 594.964 3.170 592.319 3.175 587.857 3.181 580.870 3.187 573.019 3.193 556.302 3.199 544.777 3.204 538.259 3.210 531.692 3.216 523.316 3.222 517.228 3.228 515.443 3.233 516.422 3.239 519.957 3.245 525.465 3.251 535.066 3.257 544.643 3.262 557.116 3.268 568.083 3.274 577.230 3.280 588.085 3.286 601.882 3.291 607.545 3.297 611.704 3.303 613.385 3.309 612.599 3.315 608.778 3.320 602.139 3.326 594.566 3.332 588.469 3.338 581.630 3.344 552.050 3.349 541.643 3.355 530.115 3.361 528.202 3.367 605.871 3.373 602.361 3.379 601.174 3.384 600.220 3.390 601.870 3.396 604.063 3.402 602.795 3.408 596.545 3.413 592.731 3.419 596.773 3.425 572.200 3.431 578.190 3.437 589.835 3.442 592.289 3.448 593.796 3.454 597.186 3.460 594.299 3.466 600.150 3.471 602.825 3.477 602.255 3.483 604.501 3.489 552.359 3.495 551.831 3.500 550.612 3.506 552.982 3.512 602.267 3.518 602.214 3.524 602.734 3.529 601.823 3.535 600.590 3.541 0.000 3.547 0.000 3.553 0.000 3.558 0.000 3.564 0.000 3.570 0.000 3.576 0.000 3.582 0.000 3.587 0.000 3.593 0.000 3.599 0.000 3.605 579.408 3.611 567.897 3.617 571.928 3.622 576.143 3.628 581.224 3.634 585.715 3.640 587.745 3.646 587.747 3.651 585.834 3.657 581.731 3.663 575.599 3.669 566.000 3.675 554.683 3.680 539.017 3.686 523.017 3.692 506.075 3.698 499.842 3.704 495.312 3.709 493.630 3.715 494.234 3.721 496.656 3.727 502.273 3.733 508.208 3.738 518.160 3.744 534.074 3.750 546.928 3.756 561.242 3.762 570.787 3.767 580.456 3.773 590.101 3.779 595.818 3.785 599.954 3.791 602.831 3.796 604.061 3.802 603.466 3.808 600.658 3.814 595.198 3.820 588.448 3.825 579.768 3.831 572.940 3.837 570.789 3.843 542.503 3.849 522.807 3.855 498.407 3.860 489.786 3.866 485.671 3.872 485.225 3.878 487.812 3.884 493.423 3.889 501.134 3.895 513.559 3.901 527.843 3.907 544.740 3.913 559.848 3.918 576.823 3.924 587.038 3.930 596.044 3.936 602.440 3.942 607.989 3.947 612.468 3.953 614.660 3.959 614.650 3.965 612.395 3.971 608.141 3.976 601.203 3.982 592.353 3.988 580.972 3.994 582.327 4.000 577.626 4.005 614.221 4.011 616.855 4.017 615.431 4.023 610.919 4.029 608.866 4.034 608.060 4.040 603.403 4.046 601.649 4.052 600.447 4.058 601.069 4.063 602.568 4.069 602.333 4.075 602.873 4.081 607.865 4.087 605.330 4.093 602.442 4.098 600.593 4.104 0.000 4.110 0.000 4.116 0.000 4.122 0.000 4.127 0.000 4.133 0.000 4.139 0.000 4.145 0.000 4.151 0.000 4.156 0.000 4.162 0.000 4.168 0.000 4.174 0.000 4.180 0.000 4.185 0.000 4.191 0.000 4.197 0.000 4.203 0.000 4.209 0.000 4.214 0.000 4.220 0.000 4.226 0.000 4.232 0.000 4.238 0.000 4.243 0.000 4.249 0.000 4.255 0.000 4.261 0.000 4.267 0.000 4.272 0.000 4.278 0.000 4.284 0.000 4.290 0.000 4.296 0.000 4.301 0.000 4.307 0.000 4.313 0.000 4.319 0.000 4.325 0.000 4.331 0.000 4.336 0.000 4.342 0.000 4.348 0.000 4.354 0.000 4.360 0.000 4.365 0.000 4.371 0.000 4.377 0.000 4.383 0.000 4.389 0.000 4.394 0.000 4.400 0.000 4.406 0.000 4.412 0.000 4.418 0.000 4.423 0.000 4.429 0.000 4.435 0.000 4.441 0.000 4.447 0.000 4.452 0.000 4.458 0.000 4.464 0.000 4.470 0.000 4.476 0.000 4.481 0.000 4.487 0.000 4.493 0.000 4.499 0.000 4.505 0.000 4.510 0.000 4.516 0.000 4.522 0.000 4.528 0.000 4.534 0.000 4.540 0.000 4.545 0.000 4.551 0.000 4.557 0.000 4.563 0.000 4.569 0.000 4.574 0.000 4.580 0.000 4.586 0.000 4.592 0.000 4.598 0.000 4.603 0.000 4.609 0.000 4.615 0.000 4.621 0.000 4.627 0.000 4.632 0.000 4.638 0.000 4.644 0.000 4.650 0.000 4.656 0.000 4.661 0.000 4.667 0.000 4.673 0.000 4.679 0.000 4.685 0.000 4.690 0.000 4.696 0.000 4.702 0.000 4.708 0.000 4.714 0.000 4.719 0.000 4.725 0.000 4.731 0.000 4.737 0.000 4.743 0.000 4.748 0.000 4.754 0.000 4.760 0.000 4.766 0.000 4.772 0.000 4.778 0.000 4.783 0.000 4.789 0.000 4.795 0.000 4.801 0.000 4.807 0.000 4.812 0.000 4.818 0.000 4.824 0.000 4.830 0.000 4.836 0.000 4.841 0.000 4.847 0.000 4.853 0.000 4.859 0.000 4.865 0.000 4.870 0.000 4.876 0.000 4.882 0.000 4.888 0.000 4.894 0.000 4.899 0.000 4.905 0.000 4.911 0.000 4.917 0.000 4.923 0.000 4.928 0.000 4.934 0.000 4.940 0.000 4.946 0.000 4.952 0.000 4.957 0.000 4.963 0.000 4.969 0.000 4.975 0.000 4.981 0.000 4.986 0.000 4.992 0.000 4.998 0.000 5.004 0.000 5.010 0.000 5.016 0.000 5.021 0.000 5.027 0.000 5.033 0.000 5.039 0.000 5.045 0.000 5.050 0.000 5.056 0.000 5.062 0.000 5.068 0.000 5.074 0.000 5.079 0.000 5.085 0.000 5.091 0.000 5.097 0.000 5.103 0.000 5.108 0.000 5.114 0.000 5.120 0.000 5.126 0.000 5.132 0.000 5.137 0.000 5.143 0.000 5.149 0.000 5.155 0.000 5.161 0.000 5.166 0.000 5.172 0.000 5.178 0.000 5.184 0.000 5.190 0.000 5.195 0.000 5.201 651.298 5.207 644.947 5.213 639.019 5.219 634.612 5.224 628.436 5.230 624.665 5.236 633.616 5.242 644.069 5.248 634.625 5.254 623.070 5.259 625.564 5.265 628.440 5.271 637.318 5.277 627.034 5.283 627.687 5.288 632.358 5.294 637.998 5.300 638.463 5.306 628.934 5.312 626.483 5.317 629.344 5.323 635.376 5.329 638.551 5.335 630.163 5.341 656.574 5.346 660.102 5.352 661.857 5.358 656.472 5.364 652.084 5.370 646.309 5.375 652.879 5.381 654.509 5.387 653.626 5.393 649.726 5.399 645.973 5.404 634.032 5.410 664.839 5.416 664.105 5.422 656.973 5.428 651.919 5.433 652.755 5.439 655.634 5.445 657.391 5.451 654.693 5.457 650.165 5.462 648.841 5.468 648.854 5.474 650.398 5.480 652.559 5.486 653.301 5.492 652.639 5.497 651.413 5.503 650.408 5.509 650.206 5.515 650.674 5.521 651.287 5.526 651.625 5.532 651.629 5.538 651.498 5.544 651.560 5.550 651.995 5.555 652.783 5.561 653.808 5.567 655.023 5.573 656.351 5.579 657.681 5.584 658.865 5.590 659.676 5.596 659.877 5.602 659.363 5.608 658.165 5.613 656.375 5.619 654.063 5.625 651.321 5.631 648.967 5.637 647.443 5.642 646.731 5.648 646.550 5.654 646.728 5.660 647.266 5.666 648.303 5.671 649.990 5.677 652.460 5.683 655.523 5.689 659.299 5.695 663.948 5.700 668.365 5.706 672.577 5.712 676.528 5.718 679.609 5.724 681.904 5.730 683.236 5.735 683.465 5.741 682.364 5.747 679.768 5.753 675.338 5.759 668.363 5.764 659.839 5.770 649.148 5.776 639.148 5.782 631.384 5.788 624.455 5.793 618.988 5.799 615.070 5.805 613.846 5.811 615.480 5.817 619.873 5.822 624.670 5.828 630.698 5.834 637.645 5.840 654.090 5.846 669.777 5.851 680.508 5.857 692.806 5.863 703.064 5.869 711.966 5.875 717.501 5.880 720.738 5.886 721.674 5.892 720.672 5.898 717.584 5.904 711.652 5.909 701.968 5.915 689.732 5.921 674.791 5.927 659.307 5.933 635.326 5.939 619.307 5.944 605.270 5.950 594.227 5.956 589.589 5.962 588.796 5.968 591.555 5.973 598.074 5.979 609.251 5.985 626.908 5.991 643.023 5.997 667.562 6.002 680.076 6.008 688.949 6.014 696.956 6.020 703.833 6.026 708.491 6.031 710.095 6.037 709.226 6.043 705.744 6.049 697.829 6.055 688.056 6.060 682.073 6.066 679.988 6.072 691.564 6.078 670.404 6.084 673.149 6.089 678.332 6.095 0.000 6.101 0.000 6.107 0.000 6.113 722.882 6.118 632.113 6.124 694.792 6.130 692.897 6.136 682.530 6.142 665.272 6.147 645.022 6.153 634.460 6.159 630.675 6.165 684.057 6.171 681.635 6.177 676.507 6.182 664.673 6.188 660.340 6.194 662.749 6.200 665.922 6.206 669.161 6.211 672.236 6.217 673.177 6.223 672.112 6.229 668.786 6.235 663.755 6.240 655.167 6.246 636.456 6.252 621.836 6.258 609.912 6.264 602.397 6.269 597.212 6.275 594.753 6.281 594.618 6.287 596.949 6.293 601.738 6.298 608.734 6.304 617.567 6.310 628.191 6.316 639.867 6.322 655.334 6.327 675.686 6.333 684.856 6.339 691.291 6.345 694.988 6.351 695.373 6.356 693.099 6.362 689.041 6.368 684.198 6.374 681.156 6.380 678.572 6.385 674.994 6.391 668.624 6.397 660.980 6.403 654.015 6.409 649.734 6.415 647.228 6.420 646.079 6.426 646.584 6.432 648.754 6.438 652.660 6.444 657.040 6.449 661.999 6.455 669.197 6.461 677.597 6.467 686.775 6.473 690.150 6.478 691.750 6.484 691.480 6.490 689.489 6.496 685.853 6.502 680.617 6.507 674.674 6.513 669.489 6.519 663.664 6.525 656.838 6.531 649.472 6.536 661.119 6.542 637.764 6.548 659.679 6.554 661.168 6.560 660.627 6.565 664.008 6.571 0.000 6.577 0.000 6.583 0.000 6.589 0.000 6.594 0.000 6.600 0.000 6.606 0.000 6.612 0.000 6.618 0.000 6.623 0.000 6.629 0.000 6.635 0.000 6.641 0.000 6.647 0.000 6.653 0.000 6.658 0.000 6.664 0.000 6.670 0.000 6.676 0.000 6.682 0.000 6.687 0.000 6.693 0.000 6.699 0.000 6.705 0.000 6.711 0.000 6.716 0.000 6.722 0.000 6.728 622.303 6.734 628.524 6.740 631.038 6.745 632.792 6.751 634.571 6.757 636.032 6.763 638.059 6.769 639.900 6.774 638.304 6.780 633.695 6.786 626.987 6.792 618.537 6.798 609.471 6.803 600.654 6.809 592.467 6.815 586.244 6.821 581.950 6.827 579.617 6.832 578.815 6.838 579.545 6.844 581.852 6.850 586.119 6.856 591.930 6.861 598.038 6.867 605.007 6.873 613.465 6.879 622.801 6.885 631.171 6.891 639.455 6.896 647.902 6.902 655.084 6.908 659.452 6.914 661.916 6.920 662.785 6.925 662.300 6.931 659.940 6.937 655.018 6.943 645.913 6.949 635.188 6.954 625.404 6.960 612.289 6.966 599.682 6.972 590.078 6.978 582.099 6.983 578.481 6.989 577.223 6.995 577.507 7.001 579.768 7.007 583.552 7.012 590.266 7.018 598.421 7.024 607.468 7.030 618.132 7.036 631.452 7.041 645.583 7.047 656.657 7.053 665.291 7.059 672.132 7.065 678.022 7.070 681.610 7.076 683.322 7.082 683.381 7.088 681.753 7.094 679.010 7.100 674.592 7.105 668.184 7.111 660.542 7.117 650.348 7.123 639.861 7.129 631.495 7.134 626.960 7.140 623.895 7.146 621.906 7.152 621.553 7.158 623.332 7.163 627.405 7.169 632.639 7.175 637.429 7.181 640.465 7.187 641.139 7.192 631.413 7.198 616.060 7.204 611.629 7.210 614.154 7.216 615.935 7.221 619.319 7.227 619.119 7.233 621.816 7.239 621.977 7.245 618.459 7.250 617.070 7.256 656.093 7.262 660.653 7.268 659.594 7.274 656.955 7.279 649.695 7.285 651.240 7.291 617.650 7.297 629.075 7.303 639.307 7.308 635.103 7.314 637.683 7.320 641.641 7.326 627.824 7.332 625.668 7.338 626.418 7.343 637.635 7.349 634.805 7.355 633.610 7.361 591.603 7.367 589.432 7.372 591.507 7.378 594.418 7.384 600.878 7.390 607.934 7.396 607.956 7.401 607.412 7.407 605.335 7.413 598.472 7.419 595.886 7.425 595.196 7.430 595.466 7.436 587.600 7.442 575.134 7.448 565.984 7.454 559.629 7.459 557.065 7.465 556.395 7.471 557.362 7.477 560.776 7.483 566.803 7.488 575.984 7.494 582.257 7.500 588.576 7.506 593.855 7.512 600.256 7.517 605.433 7.523 610.203 7.529 613.084 7.535 614.913 7.541 615.798 7.546 615.288 7.552 612.949 7.558 608.220 7.564 601.508 7.570 593.478 7.576 586.135 7.581 578.445 7.587 570.378 7.593 561.830 7.599 556.342 7.605 554.250 7.610 555.061 7.616 557.901 7.622 562.738 7.628 570.109 7.634 578.321 7.639 588.444 7.645 602.158 7.651 612.789 7.657 627.553 7.663 641.505 7.668 644.051 7.674 651.932 7.680 658.314 7.686 663.613 7.692 667.448 7.697 669.601 7.703 670.982 7.709 676.806 7.715 674.350 7.721 670.054 7.726 663.453 7.732 654.951 7.738 645.796 7.744 635.480 7.750 623.810 7.755 615.176 7.761 608.089 7.767 603.932 7.773 602.047 7.779 601.779 7.784 603.546 7.790 607.917 7.796 615.395 7.802 629.287 7.808 638.149 7.814 649.095 7.819 663.503 7.825 670.297 7.831 674.748 7.837 676.551 7.843 675.821 7.848 672.856 7.854 668.788 7.860 663.107 7.866 659.713 7.872 658.902 7.877 659.798 7.883 652.575 7.889 654.851 7.895 662.455 7.901 656.968 7.906 656.318 7.912 655.916 7.918 653.763 7.924 654.469 7.930 655.578 7.935 656.735 7.941 658.021 7.947 651.670 7.953 646.498 7.959 644.374 7.964 643.617 7.970 642.994 7.976 641.435 7.982 0.000 7.988 0.000 7.993 638.379 7.999 629.479 8.005 634.046 8.011 640.641 8.017 651.939 8.022 678.782 8.028 681.980 8.034 682.279 8.040 683.115 8.046 685.406 8.052 688.607 8.057 691.973 8.063 693.588 8.069 692.539 8.075 688.565 8.081 679.897 8.086 665.533 8.092 645.134 8.098 628.316 8.104 614.282 8.110 600.096 8.115 589.422 8.121 581.868 8.127 578.417 8.133 577.618 8.139 579.169 8.144 583.405 8.150 590.701 8.156 603.321 8.162 620.988 8.168 640.860 8.173 656.960 8.179 676.117 8.185 690.162 8.191 703.934 8.197 713.404 8.202 720.076 8.208 723.956 8.214 725.491 8.220 724.675 8.226 721.246 8.231 713.856 8.237 704.553 8.243 693.062 8.249 676.295 8.255 655.724 8.260 632.518 8.266 614.350 8.272 600.188 8.278 588.462 8.284 578.991 8.290 575.216 8.295 573.452 8.301 574.292 8.307 577.943 8.313 588.202 8.319 602.754 8.324 616.825 8.330 633.495 8.336 647.180 8.342 664.609 8.348 672.140 8.353 678.171 8.359 680.811 8.365 681.099 8.371 679.089 8.377 673.973 8.382 662.610 8.388 645.442 8.394 627.384 8.400 612.374 8.406 603.804 8.411 595.869 8.417 519.856 8.423 502.855 8.429 500.667 8.435 494.595 8.440 403.760 8.446 483.518 8.452 491.877 8.458 520.958 8.464 532.804 8.469 544.858 8.475 553.900 8.481 561.095 8.487 566.262 8.493 568.765 8.499 570.428 8.504 575.061 8.510 577.805 8.516 574.644 8.522 563.892 8.528 562.220 8.533 560.137 8.539 560.182 8.545 557.128 8.551 553.861 8.557 542.930 8.562 539.006 8.568 537.220 8.574 539.537 8.580 541.849 8.586 557.592 8.591 559.819 8.597 561.667 8.603 562.150 8.609 562.495 8.615 562.516 8.620 561.187 8.626 557.583 8.632 553.376 8.638 562.156 8.644 566.492 8.649 567.947 8.655 562.326 8.661 552.128 8.667 550.223 8.673 545.429 8.678 548.920 8.684 553.224 8.690 559.747 8.696 566.120 8.702 562.880 8.707 556.476 8.713 556.938 8.719 558.124 8.725 560.062 8.731 562.583 8.737 564.966 8.742 565.579 8.748 564.389 8.754 561.139 8.760 555.198 8.766 547.820 8.771 539.682 8.777 530.997 8.783 517.555 8.789 504.446 8.795 490.427 8.800 464.424 8.806 557.766 8.812 558.867 8.818 559.742 8.824 560.900 8.829 562.125 8.835 563.632 8.841 564.925 8.847 572.906 8.853 555.875 8.858 0.000 8.864 85.508 8.870 0.000 8.876 0.000 8.882 0.000 8.887 0.000 8.893 0.000 8.899 0.000 8.905 0.000 8.911 0.000 8.916 0.000 8.922 0.000 8.928 0.000 8.934 0.000 8.940 0.000 8.945 0.000 8.951 0.000 8.957 0.000 8.963 0.000 8.969 0.000 8.975 0.000 8.980 0.000 8.986 0.000 8.992 0.000 8.998 0.000 9.004 0.000 9.009 0.000 9.015 0.000 9.021 553.772 9.027 535.175 9.033 531.336 9.038 545.493 9.044 549.780 9.050 555.970 9.056 551.727 9.062 577.888 9.067 586.811 9.073 596.802 9.079 602.568 9.085 603.325 9.091 601.624 9.096 596.595 9.102 589.740 9.108 573.105 9.114 565.921 9.120 558.233 9.125 533.074 9.131 526.189 9.137 520.700 9.143 519.241 9.149 522.904 9.154 534.629 9.160 543.839 9.166 551.198 9.172 560.596 9.178 568.793 9.183 573.802 9.189 581.106 9.195 586.472 9.201 589.126 9.207 589.667 9.213 588.337 9.218 585.870 9.224 583.840 9.230 582.085 9.236 581.137 9.242 577.807 9.247 0.000 9.253 0.000 9.259 0.000 9.265 0.000 9.271 0.000 9.276 0.000 9.282 0.000 9.288 0.000 9.294 0.000 9.300 0.000 9.305 0.000 9.311 0.000 9.317 0.000 9.323 0.000 9.329 0.000 9.334 0.000 9.340 0.000 9.346 0.000 9.352 0.000 9.358 0.000 9.363 0.000 9.369 0.000 9.375 0.000 9.381 0.000 9.387 0.000 9.392 0.000 9.398 0.000 9.404 0.000 9.410 0.000 9.416 507.325 9.421 511.331 9.427 515.433 9.433 520.196 9.439 524.349 9.445 526.971 9.451 527.970 9.456 527.310 9.462 524.906 9.468 520.317 9.474 513.903 9.480 504.819 9.485 495.261 9.491 485.528 9.497 476.264 9.503 469.966 9.509 467.794 9.514 469.104 9.520 474.235 9.526 480.448 9.532 486.495 9.538 492.572 9.543 499.199 9.549 507.223 9.555 515.445 9.561 525.233 9.567 533.416 9.572 540.479 9.578 546.226 9.584 549.672 9.590 550.606 9.596 549.373 9.601 546.092 9.607 541.179 9.613 536.183 9.619 530.246 9.625 522.657 9.630 514.591 9.636 507.476 9.642 500.775 9.648 493.687 9.654 480.132 9.660 477.264 9.665 478.654 9.671 484.329 9.677 491.889 9.683 502.497 9.689 511.187 9.694 518.861 9.700 531.513 9.706 545.594 9.712 560.789 9.718 575.819 9.723 593.572 9.729 598.210 9.735 601.435 9.741 602.311 9.747 600.886 9.752 596.554 9.758 589.872 9.764 581.781 9.770 573.414 9.776 564.956 9.781 543.802 9.787 534.738 9.793 527.595 9.799 520.956 9.805 515.284 9.810 511.794 9.816 510.661 9.822 511.131 9.828 513.088 9.834 517.128 9.839 521.347 9.845 523.312 9.851 524.996 9.857 527.013 9.863 532.528 9.868 553.809 9.874 555.344 9.880 555.959 9.886 558.220 9.892 560.881 9.898 556.079 9.903 556.252 9.909 549.960 9.915 535.485 9.921 533.669 9.927 533.601 9.932 533.636 9.938 537.570 9.944 523.516 9.950 513.545 9.956 509.028 9.961 549.424 9.967 0.000 9.973 118.243 9.979 0.000 9.985 0.000 9.990 0.000 9.996 0.000 10.002 0.000 10.008 0.000 10.014 523.550 10.019 444.250 10.025 448.964 10.031 456.020 10.037 463.767 10.043 473.923 10.048 484.511 10.054 494.543 10.060 501.992 10.066 506.763 10.072 508.695 10.077 509.868 10.083 510.219 10.089 509.686 10.095 507.877 10.101 504.493 10.106 498.690 10.112 492.480 10.118 486.001 10.124 480.424 10.130 473.429 10.136 467.871 10.141 464.444 10.147 463.413 10.153 464.596 10.159 468.257 10.165 473.102 10.170 478.791 10.176 484.553 10.182 490.517 10.188 496.871 10.194 502.755 10.199 507.603 10.205 512.663 10.211 517.533 10.217 522.052 10.223 525.766 10.228 527.244 10.234 527.548 10.240 526.882 10.246 524.747 10.252 520.776 10.257 515.685 10.263 508.961 10.269 502.188 10.275 494.726 10.281 487.825 10.286 481.534 10.292 475.316 10.298 463.451 10.304 472.684 10.310 478.329 10.315 488.666 10.321 497.962 10.327 505.168 10.333 511.491 10.339 519.287 10.344 537.149 10.350 547.701 10.356 561.525 10.362 574.511 10.368 572.415 10.374 575.002 10.379 578.440 10.385 579.724 10.391 588.219 10.397 586.039 10.403 581.681 10.408 575.191 10.414 563.224 10.420 549.314 10.426 537.809 10.432 528.972 10.437 521.518 10.443 514.314 10.449 509.604 10.455 507.206 10.461 507.090 10.466 509.416 10.472 513.739 10.478 521.550 10.484 530.900 10.490 539.737 10.495 551.353 10.501 561.638 10.507 578.330 10.513 583.253 10.519 584.707 10.524 584.188 10.530 582.714 10.536 581.917 10.542 585.185 10.548 571.917 10.553 564.743 10.559 513.658 10.565 512.595 10.571 515.191 10.577 0.000 10.582 0.000 10.588 0.000 10.594 0.000 10.600 0.000 10.606 0.000 10.612 0.000 10.617 0.000 10.623 0.000 10.629 0.000 10.635 0.000 10.641 0.000 10.646 0.000 10.652 0.000 10.658 0.000 10.664 0.000 10.670 0.000 10.675 0.000 10.681 0.000 10.687 0.000 10.693 63.072 10.699 508.242 10.704 553.453 10.710 556.187 10.716 561.522 10.722 568.323 10.728 575.605 10.733 580.519 10.739 582.040 10.745 581.219 10.751 578.476 10.757 573.645 10.762 567.203 10.768 558.679 10.774 549.792 10.780 541.704 10.786 535.275 10.791 529.062 10.797 523.363 10.803 509.819 10.809 507.103 10.815 506.860 10.820 508.802 10.826 512.852 10.832 520.704 10.838 530.116 10.844 538.132 10.850 546.757 10.855 554.330 10.861 566.988 10.867 578.307 10.873 589.027 10.879 593.605 10.884 596.641 10.890 598.661 10.896 598.962 10.902 597.059 10.908 592.936 10.913 586.930 10.919 579.239 10.925 570.758 10.931 554.821 10.937 542.807 10.942 535.960 10.948 527.031 10.954 518.951 10.960 502.963 10.966 500.723 10.971 501.504 10.977 504.426 10.983 509.952 10.989 520.162 10.995 531.785 11.000 540.030 11.006 549.258 11.012 558.262 11.018 567.633 11.024 575.091 11.029 579.173 11.035 580.397 11.041 579.224 11.047 575.597 11.053 570.281 11.059 563.292 11.064 557.223 11.070 546.547 11.076 525.757 11.082 512.895 11.088 478.338 11.093 519.667 11.099 416.366 11.105 404.807 11.111 403.605 11.117 405.308 11.122 409.602 11.128 418.209 11.134 425.116 11.140 431.325 11.146 438.121 11.151 442.136 11.157 445.070 11.163 446.456 11.169 446.630 11.175 446.887 11.180 437.494 11.186 432.821 11.192 429.293 11.198 424.388 11.204 426.479 11.209 430.213 11.215 408.917 11.221 403.613 11.227 411.029 11.233 412.788 11.238 409.406 11.244 405.470 11.250 407.797 11.256 409.846 11.262 428.374 11.267 434.155 11.273 438.130 11.279 442.885 11.285 453.412 11.291 459.521 11.297 464.305 11.302 466.899 11.308 466.954 11.314 464.814 11.320 460.770 11.326 456.400 11.331 440.174 11.337 428.031 11.343 0.000 11.349 0.000 11.355 0.000 11.360 0.000 11.366 0.000 11.372 0.000 11.378 0.000 11.384 0.000 11.389 0.000 11.395 0.000 11.401 0.000 11.407 406.084 11.413 407.292 11.418 415.188 11.424 425.317 11.430 435.493 11.436 446.131 11.442 455.438 11.447 462.572 11.453 468.291 11.459 470.922 11.465 468.641 11.471 465.221 11.476 459.380 11.482 452.061 11.488 443.457 11.494 431.992 11.500 415.936 11.505 401.419 11.511 391.176 11.517 367.240 11.523 360.569 11.529 348.972 11.535 385.833 11.540 424.817 11.546 469.490 11.552 0.000 11.558 0.000 11.564 0.000 11.569 0.000 11.575 0.000 11.581 0.000 11.587 0.000 11.593 0.000 11.598 0.000 11.604 0.000 11.610 0.000 11.616 0.000 11.622 0.000 11.627 0.000 11.633 0.000 11.639 0.000 11.645 0.000 11.651 0.000 11.656 0.000 11.662 0.000 11.668 0.000 11.674 0.000 11.680 0.000 11.685 0.000 11.691 0.000 11.697 0.000 11.703 0.000 11.709 0.000 11.714 0.000 11.720 0.000 11.726 0.000 11.732 0.000 11.738 0.000 11.743 0.000 11.749 0.000 11.755 0.000 11.761 0.000 11.767 0.000 11.773 0.000 11.778 0.000 11.784 0.000 11.790 0.000 11.796 0.000 11.802 0.000 11.807 0.000 11.813 386.957 11.819 399.754 11.825 413.987 11.831 427.471 11.836 441.461 11.842 453.098 11.848 459.905 11.854 461.944 11.860 461.649 11.865 458.498 11.871 452.403 11.877 446.786 11.883 443.103 11.889 440.938 11.894 439.850 11.900 439.462 11.906 440.108 11.912 441.927 11.918 445.399 11.923 449.109 11.929 454.133 11.935 461.042 11.941 470.654 11.947 482.637 11.952 486.708 11.958 489.891 11.964 491.584 11.970 491.826 11.976 490.363 11.981 486.996 11.987 482.487 11.993 475.390 11.999 467.133 12.005 461.078 12.011 456.005 12.016 450.869 12.022 443.057 12.028 436.472 12.034 408.034 12.040 397.171 12.045 0.000 12.051 0.000 12.057 0.000 12.063 0.000 12.069 0.000 12.074 0.000 12.080 0.000 12.086 0.000 12.092 0.000 12.098 0.000 12.103 0.000 12.109 0.000 12.115 0.000 12.121 0.000 12.127 0.000 12.132 0.000 12.138 0.000 12.144 0.000 12.150 0.000 12.156 0.000 12.161 0.000 12.167 0.000 12.173 0.000 12.179 0.000 12.185 0.000 12.190 0.000 12.196 0.000 12.202 0.000 12.208 0.000 12.214 0.000 12.220 0.000 12.225 0.000 12.231 0.000 12.237 395.870 12.243 404.059 12.249 408.809 12.254 411.955 12.260 416.248 12.266 421.058 12.272 423.872 12.278 424.290 12.283 422.521 12.289 418.231 12.295 412.147 12.301 405.906 12.307 398.155 12.312 390.530 12.318 382.524 12.324 374.780 12.330 369.691 12.336 366.563 12.341 365.652 12.347 366.488 12.353 369.476 12.359 374.395 12.365 380.065 12.370 387.487 12.376 397.177 12.382 406.073 12.388 415.726 12.394 425.165 12.399 432.337 12.405 438.611 12.411 441.661 12.417 442.675 12.423 442.039 12.428 439.784 12.434 435.469 12.440 430.569 12.446 423.185 12.452 412.611 12.458 404.903 12.463 396.141 12.469 388.230 12.475 378.489 12.481 372.016 12.487 367.306 12.492 365.218 12.498 364.998 12.504 366.933 12.510 371.954 12.516 379.523 12.521 389.742 12.527 398.200 12.533 408.415 12.539 420.531 12.545 429.443 12.550 438.351 12.556 447.632 12.562 456.850 12.568 466.003 12.574 471.385 12.579 473.577 12.585 473.378 12.591 470.632 12.597 465.476 12.603 460.165 12.608 454.158 12.614 446.063 12.620 436.838 12.626 431.238 12.632 421.686 12.637 410.633 12.643 404.048 12.649 400.987 12.655 400.345 12.661 401.294 12.666 403.461 12.672 407.449 12.678 411.349 12.684 417.198 12.690 423.742 12.696 432.488 12.701 439.697 12.707 444.557 12.713 450.001 12.719 453.122 12.725 455.264 12.730 460.290 12.736 464.569 12.742 466.666 12.748 464.750 12.754 460.788 12.759 455.811 12.765 450.255 12.771 443.855 12.777 438.476 12.783 431.782 12.788 423.554 12.794 419.141 12.800 415.069 12.806 416.441 12.812 410.996 12.817 412.772 12.823 413.348 12.829 411.360 12.835 408.689 12.841 401.871 12.846 396.095 12.852 393.594 12.858 391.157 12.864 0.000 12.870 0.000 12.875 0.000 12.881 0.000 12.887 0.000 12.893 0.000 12.899 0.000 12.904 0.000 12.910 0.000 12.916 368.062 12.922 377.305 12.928 380.519 12.934 385.805 12.939 388.424 12.945 388.897 12.951 388.684 12.957 389.265 12.963 390.806 12.968 392.497 12.974 394.035 12.980 395.483 12.986 396.886 12.992 398.369 12.997 399.888 13.003 401.450 13.009 402.727 13.015 403.325 13.021 403.160 13.026 402.434 13.032 401.249 13.038 399.520 13.044 397.239 13.050 394.545 13.055 391.803 13.061 389.621 13.067 388.025 13.073 386.586 13.079 385.184 13.084 383.826 13.090 382.736 13.096 382.081 13.102 382.123 13.108 382.972 13.113 384.477 13.119 386.022 13.125 387.295 13.131 388.448 13.137 390.006 13.142 392.158 13.148 394.912 13.154 397.795 13.160 400.523 13.166 402.908 13.172 404.745 13.177 405.870 13.183 406.516 13.189 406.772 13.195 406.507 13.201 405.434 13.206 403.201 13.212 399.901 13.218 395.964 13.224 391.038 13.230 387.288 13.235 382.389 13.241 376.978 13.247 372.466 13.253 353.416 13.259 333.817 13.264 345.443 13.270 329.548 13.276 352.399 13.282 363.076 13.288 401.624 13.293 415.503 13.299 430.748 13.305 441.616 13.311 448.238 13.317 454.365 13.322 458.782 13.328 461.521 13.334 462.334 13.340 460.870 13.346 457.227 13.351 451.441 13.357 444.738 13.363 437.960 13.369 430.596 13.375 422.592 13.380 412.614 13.386 407.930 13.392 405.701 13.398 405.240 13.404 406.524 13.410 409.771 13.415 416.456 13.421 426.120 13.427 434.344 13.433 443.141 13.439 450.551 13.444 456.483 13.450 460.919 13.456 463.147 13.462 463.074 13.468 460.787 13.473 456.287 13.479 451.072 13.485 445.177 13.491 440.344 13.497 426.201 13.502 0.000 13.508 0.000 13.514 0.000 13.520 0.000 13.526 0.000 13.531 0.000 13.537 0.000 13.543 0.000 13.549 0.000 13.555 0.000 13.560 0.000 13.566 0.000 13.572 0.000 13.578 0.000 13.584 0.000 13.589 0.000 13.595 0.000 13.601 0.000 13.607 0.000 13.613 0.000 13.619 0.000 13.624 0.000 13.630 0.000 13.636 0.000 13.642 0.000 13.648 0.000 13.653 0.000 13.659 0.000 13.665 0.000 13.671 465.645 13.677 457.439 13.682 460.437 13.688 458.575 13.694 458.302 13.700 458.476 13.706 460.551 13.711 453.949 13.717 450.187 13.723 449.465 13.729 450.170 13.735 449.970 13.740 448.875 13.746 446.711 13.752 443.833 13.758 439.904 13.764 435.293 13.769 430.178 13.775 424.707 13.781 420.458 13.787 418.373 13.793 417.936 13.798 418.984 13.804 421.150 13.810 424.523 13.816 429.056 13.822 434.749 13.827 440.290 13.833 445.897 13.839 451.310 13.845 457.588 13.851 464.174 13.857 470.024 13.862 474.012 13.868 476.083 13.874 476.577 13.880 476.015 13.886 474.563 13.891 471.650 13.897 466.822 13.903 461.399 13.909 454.882 13.915 448.328 13.920 440.454 13.926 433.997 13.932 426.649 13.938 417.254 13.944 412.084 13.949 409.466 13.955 408.592 13.961 408.938 13.967 410.214 13.973 412.892 13.978 416.996 13.984 422.771 13.990 428.676 13.996 434.463 14.002 441.006 14.007 445.147 14.013 448.035 14.019 450.188 14.025 451.667 14.031 452.073 14.036 451.394 14.042 449.600 14.048 446.875 14.054 443.219 14.060 437.932 14.065 431.734 14.071 425.998 14.077 417.471 14.083 409.671 14.089 404.295 14.095 399.007 14.100 392.844 14.106 384.171 14.112 378.374 14.118 373.874 14.124 369.520 14.129 364.895 14.135 358.707 14.141 353.299 14.147 348.374 14.153 339.861 14.158 336.544 14.164 335.472 14.170 336.493 14.176 340.785 14.182 348.991 14.187 354.678 14.193 360.699 14.199 365.157 14.205 369.520 14.211 373.249 14.216 376.427 14.222 379.154 14.228 381.275 14.234 382.831 14.240 383.819 14.245 384.302 14.251 384.490 14.257 384.469 14.263 384.184 14.269 383.446 14.274 382.221 14.280 380.527 14.286 378.705 14.292 377.052 14.298 376.324 14.303 376.305 14.309 376.466 14.315 376.327 14.321 376.495 14.327 378.802 14.333 380.050 14.338 380.661 14.344 380.520 14.350 381.105 14.356 382.068 14.362 384.016 14.367 386.115 14.373 386.365 14.379 387.617 14.385 386.530 14.391 386.070 14.396 384.633 14.402 379.916 14.408 375.623 14.414 374.414 14.420 375.456 14.425 376.732 14.431 377.059 14.437 376.636 14.443 375.770 14.449 374.718 14.454 373.416 14.460 372.602 14.466 372.060 14.472 371.915 14.478 372.874 14.483 374.630 14.489 379.077 14.495 379.205 14.501 377.176 14.507 376.758 14.512 379.155 14.518 380.578 14.524 379.950 14.530 0.000 14.536 0.000 14.541 371.256 14.547 374.444 14.553 373.277 14.559 371.012 14.565 352.997 14.571 345.622 14.576 349.397 14.582 355.635 14.588 361.324 14.594 365.995 14.600 370.550 14.605 373.638 14.611 375.537 14.617 376.528 14.623 376.807 14.629 376.574 14.634 375.884 14.640 374.515 14.646 372.476 14.652 369.645 14.658 366.614 14.663 363.815 14.669 361.546 14.675 360.324 14.681 359.753 14.687 359.517 14.692 359.631 14.698 360.362 14.704 361.968 14.710 364.191 14.716 366.776 14.721 369.854 14.727 372.942 14.733 375.973 14.739 378.933 14.745 381.402 14.750 383.046 14.756 384.134 14.762 384.983 14.768 385.429 14.774 385.387 14.780 384.664 14.785 383.204 14.791 380.748 14.797 377.441 14.803 372.945 14.809 366.667 14.814 361.061 14.820 355.699 14.826 351.290 14.832 347.678 14.838 345.361 14.843 344.157 14.849 343.520 14.855 343.302 14.861 343.772 14.867 345.398 14.872 348.789 14.878 353.705 14.884 358.547 14.890 365.731 14.896 374.389 14.901 380.134 14.907 384.331 14.913 388.057 14.919 391.134 14.925 393.236 14.930 394.213 14.936 394.189 14.942 393.323 14.948 391.301 14.954 387.767 14.959 382.180 14.965 375.993 14.971 369.591 14.977 362.373 14.983 356.476 14.988 351.122 14.994 346.954 15.000 343.555 15.006 342.646 15.012 342.844 15.018 343.889 15.023 345.610 15.029 348.366 15.035 352.779 15.041 358.003 15.047 363.457 15.052 370.556 15.058 377.007 15.064 383.013 15.070 388.197 15.076 392.959 15.081 395.759 15.087 397.045 15.093 397.107 15.099 396.180 15.105 394.116 15.110 389.895 15.116 382.899 15.122 375.911 15.128 370.157 15.134 363.591 15.139 355.294 15.145 348.114 15.151 343.516 15.157 341.910 15.163 341.710 15.168 341.852 15.174 342.948 15.180 346.118 15.186 350.851 15.192 355.778 15.197 361.442 15.203 368.164 15.209 375.135 15.215 380.327 15.221 383.349 15.226 385.651 15.232 387.493 15.238 388.254 15.244 387.420 15.250 384.820 15.256 380.760 15.261 376.052 15.267 371.072 15.273 359.817 15.279 349.767 15.285 343.526 15.290 343.752 15.296 351.522 15.302 0.000 15.308 0.000 15.314 0.000 15.319 0.000 15.325 0.000 15.331 0.000 15.337 0.000 15.343 0.000 15.348 0.000 15.354 0.000 15.360 0.000 15.366 0.000 15.372 0.000 15.377 0.000 15.383 0.000 15.389 0.000 15.395 0.000 15.401 0.000 15.406 0.000 15.412 0.000 15.418 0.000 15.424 0.000 15.430 0.000 15.435 0.000 15.441 0.000 15.447 0.000 15.453 0.000 15.459 0.000 15.464 0.000 15.470 0.000 15.476 0.000 15.482 0.000 15.488 0.000 15.494 0.000 15.499 0.000 15.505 0.000 15.511 0.000 15.517 0.000 15.523 0.000 15.528 0.000 15.534 0.000 15.540 0.000 15.546 0.000 15.552 0.000 15.557 0.000 15.563 0.000 15.569 0.000 15.575 0.000 15.581 0.000 15.586 0.000 15.592 0.000 15.598 0.000 15.604 0.000 15.610 0.000 15.615 0.000 15.621 0.000 15.627 0.000 15.633 0.000 15.639 0.000 15.644 0.000 15.650 0.000 15.656 0.000 15.662 0.000 15.668 0.000 15.673 0.000 15.679 0.000 15.685 0.000 15.691 0.000 15.697 0.000 15.702 0.000 15.708 0.000 15.714 0.000 15.720 0.000 15.726 0.000 15.732 0.000 15.737 0.000 15.743 0.000 15.749 0.000 15.755 0.000 15.761 0.000 15.766 0.000 15.772 0.000 15.778 0.000 15.784 0.000 15.790 0.000 15.795 0.000 15.801 0.000 15.807 0.000 15.813 0.000 15.819 0.000 15.824 0.000 15.830 0.000 15.836 0.000 15.842 0.000 15.848 0.000 15.853 0.000 15.859 0.000 15.865 0.000 15.871 0.000 15.877 0.000 15.882 0.000 15.888 0.000 15.894 0.000 15.900 0.000 15.906 0.000 15.911 0.000 15.917 0.000 15.923 0.000 15.929 0.000 15.935 0.000 15.940 0.000 15.946 0.000 15.952 0.000 15.958 0.000 15.964 0.000 15.970 0.000 15.975 0.000 15.981 0.000 15.987 0.000 15.993 0.000 15.999 0.000 16.004 0.000 16.010 0.000 16.016 0.000 16.022 0.000 16.028 0.000 16.033 0.000 16.039 0.000 16.045 0.000 16.051 0.000 16.057 0.000 16.062 0.000 16.068 0.000 16.074 0.000 16.080 0.000 16.086 0.000 16.091 0.000 16.097 0.000 16.103 0.000 16.109 0.000 mir_eval-0.8.2/tests/data/melody/ref07.txt000066400000000000000000002015621475740344600203730ustar00rootroot000000000000000.000 0.000 0.006 0.000 0.012 0.000 0.017 0.000 0.023 0.000 0.029 0.000 0.035 0.000 0.041 0.000 0.046 0.000 0.052 0.000 0.058 0.000 0.064 0.000 0.070 0.000 0.075 0.000 0.081 0.000 0.087 0.000 0.093 0.000 0.099 0.000 0.104 0.000 0.110 0.000 0.116 0.000 0.122 0.000 0.128 0.000 0.134 0.000 0.139 0.000 0.145 0.000 0.151 0.000 0.157 0.000 0.163 0.000 0.168 0.000 0.174 0.000 0.180 0.000 0.186 0.000 0.192 0.000 0.197 0.000 0.203 0.000 0.209 0.000 0.215 215.280 0.221 210.109 0.226 205.196 0.232 202.619 0.238 196.916 0.244 195.828 0.250 0.000 0.255 0.000 0.261 226.656 0.267 226.740 0.273 222.924 0.279 220.110 0.284 217.052 0.290 214.739 0.296 213.539 0.302 213.181 0.308 213.350 0.313 213.413 0.319 212.809 0.325 209.401 0.331 205.583 0.337 204.026 0.342 207.893 0.348 211.193 0.354 213.792 0.360 215.774 0.366 216.061 0.372 216.099 0.377 216.713 0.383 216.860 0.389 216.210 0.395 213.757 0.401 0.000 0.406 0.000 0.412 262.101 0.418 254.440 0.424 247.103 0.430 242.376 0.435 239.972 0.441 237.707 0.447 238.341 0.453 235.503 0.459 232.620 0.464 229.707 0.470 226.012 0.476 222.723 0.482 219.936 0.488 216.022 0.493 212.222 0.499 199.957 0.505 193.687 0.511 195.902 0.517 199.831 0.522 215.019 0.528 223.830 0.534 232.721 0.540 230.696 0.546 226.027 0.551 219.566 0.557 218.646 0.563 222.125 0.569 228.106 0.575 223.137 0.580 222.662 0.586 223.512 0.592 228.053 0.598 226.907 0.604 224.748 0.610 217.405 0.615 206.954 0.621 203.230 0.627 202.076 0.633 201.401 0.639 201.284 0.644 201.696 0.650 202.698 0.656 204.548 0.662 204.899 0.668 202.613 0.673 201.617 0.679 201.331 0.685 0.000 0.691 0.000 0.697 0.000 0.702 0.000 0.708 0.000 0.714 0.000 0.720 0.000 0.726 0.000 0.731 0.000 0.737 0.000 0.743 0.000 0.749 204.920 0.755 210.973 0.760 206.101 0.766 212.197 0.772 214.356 0.778 0.000 0.784 0.000 0.789 237.478 0.795 229.969 0.801 224.697 0.807 221.900 0.813 213.402 0.819 211.378 0.824 210.862 0.830 210.351 0.836 221.161 0.842 221.238 0.848 220.286 0.853 214.717 0.859 0.000 0.865 0.000 0.871 217.149 0.877 220.418 0.882 220.779 0.888 0.000 0.894 0.000 0.900 216.569 0.906 215.891 0.911 69.744 0.917 213.809 0.923 213.934 0.929 0.000 0.935 0.000 0.940 0.000 0.946 0.000 0.952 259.048 0.958 280.483 0.964 274.659 0.969 266.789 0.975 262.093 0.981 258.375 0.987 255.750 0.993 254.850 0.998 254.302 1.004 253.001 1.010 251.656 1.016 250.393 1.022 249.207 1.027 248.002 1.033 245.873 1.039 244.205 1.045 242.907 1.051 242.087 1.057 241.891 1.062 242.141 1.068 242.251 1.074 241.987 1.080 241.062 1.086 236.116 1.091 233.776 1.097 234.692 1.103 0.000 1.109 0.000 1.115 0.000 1.120 341.779 1.126 284.633 1.132 270.245 1.138 258.212 1.144 254.917 1.149 263.822 1.155 273.684 1.161 342.249 1.167 328.922 1.173 310.825 1.178 301.753 1.184 297.493 1.190 293.943 1.196 291.036 1.202 288.437 1.207 286.218 1.213 284.407 1.219 282.783 1.225 281.492 1.231 280.776 1.236 280.633 1.242 280.861 1.248 281.305 1.254 281.925 1.260 282.523 1.265 283.004 1.271 282.064 1.277 279.237 1.283 271.893 1.289 267.591 1.295 265.174 1.300 263.463 1.306 263.805 1.312 265.040 1.318 268.956 1.324 270.230 1.329 270.973 1.335 272.614 1.341 0.000 1.347 0.000 1.353 0.000 1.358 331.612 1.364 330.817 1.370 328.781 1.376 326.382 1.382 323.896 1.387 318.659 1.393 318.138 1.399 315.364 1.405 312.819 1.411 309.997 1.416 306.600 1.422 303.548 1.428 301.222 1.434 299.405 1.440 298.098 1.445 297.117 1.451 296.447 1.457 296.247 1.463 296.517 1.469 297.008 1.474 297.508 1.480 297.813 1.486 297.759 1.492 297.066 1.498 295.807 1.503 294.308 1.509 293.231 1.515 292.745 1.521 292.416 1.527 291.807 1.533 286.309 1.538 280.574 1.544 276.475 1.550 266.791 1.556 266.624 1.562 264.009 1.567 261.768 1.573 262.422 1.579 267.169 1.585 271.625 1.591 276.263 1.596 277.785 1.602 278.860 1.608 280.571 1.614 282.583 1.620 284.466 1.625 285.733 1.631 285.977 1.637 285.500 1.643 284.465 1.649 280.352 1.654 275.785 1.660 290.223 1.666 288.373 1.672 286.587 1.678 287.467 1.683 287.531 1.689 287.086 1.695 287.542 1.701 286.329 1.707 286.593 1.712 287.479 1.718 288.841 1.724 0.000 1.730 0.000 1.736 0.000 1.741 0.000 1.747 0.000 1.753 237.709 1.759 236.413 1.765 232.934 1.771 228.408 1.776 228.074 1.782 232.050 1.788 239.666 1.794 249.937 1.800 255.494 1.805 257.651 1.811 256.091 1.817 253.152 1.823 247.983 1.829 239.955 1.834 235.860 1.840 230.262 1.846 216.725 1.852 213.062 1.858 205.926 1.863 201.653 1.869 192.959 1.875 190.031 1.881 187.988 1.887 179.374 1.892 177.097 1.898 178.287 1.904 178.228 1.910 182.559 1.916 187.493 1.921 196.461 1.927 202.472 1.933 213.046 1.939 218.087 1.945 221.893 1.950 225.053 1.956 227.497 1.962 228.900 1.968 229.421 1.974 228.872 1.980 227.332 1.985 225.365 1.991 222.613 1.997 218.733 2.003 214.610 2.009 210.698 2.014 206.700 2.020 207.511 2.026 204.926 2.032 209.946 2.038 204.879 2.043 207.317 2.049 211.298 2.055 211.882 2.061 211.871 2.067 211.204 2.072 210.692 2.078 211.523 2.084 214.878 2.090 217.021 2.096 217.971 2.101 218.155 2.107 218.143 2.113 218.370 2.119 218.550 2.125 218.137 2.130 216.903 2.136 214.756 2.142 212.081 2.148 209.073 2.154 207.872 2.159 207.225 2.165 206.789 2.171 206.521 2.177 206.909 2.183 208.858 2.188 211.910 2.194 214.357 2.200 215.344 2.206 215.450 2.212 214.693 2.218 212.884 2.223 210.295 2.229 206.093 2.235 201.198 2.241 196.347 2.247 191.224 2.252 189.504 2.258 189.362 2.264 191.128 2.270 193.010 2.276 162.526 2.281 153.843 2.287 153.413 2.293 153.235 2.299 153.879 2.305 156.108 2.310 160.118 2.316 169.144 2.322 174.462 2.328 177.451 2.334 180.523 2.339 182.871 2.345 183.992 2.351 183.976 2.357 183.389 2.363 182.505 2.368 182.269 2.374 183.852 2.380 195.153 2.386 186.694 2.392 199.013 2.397 198.797 2.403 195.392 2.409 193.823 2.415 191.266 2.421 205.475 2.426 194.859 2.432 191.849 2.438 0.000 2.444 0.000 2.450 0.000 2.456 0.000 2.461 0.000 2.467 0.000 2.473 0.000 2.479 0.000 2.485 0.000 2.490 0.000 2.496 155.685 2.502 149.402 2.508 145.547 2.514 144.207 2.519 145.116 2.525 148.343 2.531 150.456 2.537 153.205 2.543 153.226 2.548 149.992 2.554 146.925 2.560 135.653 2.566 132.344 2.572 133.373 2.577 117.110 2.583 0.000 2.589 0.000 2.595 0.000 2.601 0.000 2.606 0.000 2.612 0.000 2.618 0.000 2.624 0.000 2.630 0.000 2.635 0.000 2.641 0.000 2.647 0.000 2.653 0.000 2.659 143.585 2.664 140.101 2.670 128.844 2.676 126.931 2.682 126.292 2.688 127.319 2.694 131.453 2.699 133.690 2.705 138.333 2.711 142.954 2.717 146.479 2.723 148.777 2.728 149.817 2.734 150.139 2.740 149.768 2.746 148.946 2.752 147.790 2.757 146.263 2.763 144.886 2.769 140.730 2.775 127.649 2.781 114.739 2.786 113.731 2.792 111.206 2.798 106.542 2.804 105.183 2.810 104.170 2.815 104.627 2.821 103.951 2.827 92.097 2.833 93.397 2.839 101.224 2.844 105.059 2.850 107.950 2.856 109.760 2.862 113.966 2.868 117.090 2.873 121.226 2.879 125.805 2.885 128.725 2.891 133.470 2.897 138.866 2.902 140.355 2.908 141.921 2.914 142.398 2.920 142.101 2.926 141.124 2.932 139.540 2.937 136.361 2.943 132.945 2.949 129.734 2.955 128.493 2.961 123.297 2.966 119.409 2.972 116.321 2.978 114.448 2.984 113.915 2.990 114.526 2.995 115.876 3.001 118.696 3.007 121.420 3.013 125.839 3.019 130.286 3.024 135.788 3.030 138.603 3.036 143.103 3.042 145.198 3.048 149.941 3.053 152.553 3.059 154.157 3.065 154.383 3.071 153.788 3.077 154.273 3.082 149.540 3.088 146.746 3.094 143.621 3.100 138.815 3.106 130.005 3.111 127.702 3.117 124.783 3.123 123.591 3.129 122.835 3.135 122.504 3.140 121.599 3.146 119.598 3.152 118.789 3.158 119.549 3.164 122.886 3.170 121.804 3.175 131.953 3.181 133.780 3.187 134.337 3.193 134.089 3.199 133.189 3.204 132.444 3.210 131.375 3.216 129.456 3.222 140.566 3.228 160.662 3.233 159.098 3.239 157.399 3.245 155.649 3.251 153.228 3.257 150.685 3.262 148.463 3.268 146.622 3.274 145.179 3.280 144.505 3.286 144.304 3.291 148.702 3.297 151.444 3.303 152.653 3.309 152.396 3.315 150.687 3.320 145.562 3.326 136.734 3.332 138.119 3.338 136.482 3.344 115.660 3.349 90.212 3.355 74.107 3.361 149.022 3.367 149.851 3.373 148.914 3.379 143.853 3.384 116.853 3.390 112.054 3.396 211.394 3.402 207.864 3.408 205.039 3.413 202.856 3.419 200.656 3.425 198.612 3.431 196.471 3.437 193.331 3.442 190.263 3.448 187.682 3.454 187.296 3.460 187.345 3.466 185.787 3.471 179.106 3.477 156.139 3.483 152.216 3.489 154.443 3.495 0.000 3.500 0.000 3.506 203.236 3.512 202.514 3.518 201.549 3.524 201.381 3.529 201.907 3.535 200.810 3.541 202.291 3.547 204.991 3.553 205.124 3.558 205.596 3.564 213.969 3.570 237.940 3.576 237.368 3.582 235.874 3.587 227.229 3.593 221.486 3.599 217.446 3.605 209.264 3.611 207.642 3.617 204.502 3.622 201.974 3.628 198.973 3.634 196.218 3.640 193.263 3.646 189.619 3.651 185.499 3.657 181.953 3.663 192.547 3.669 0.000 3.675 0.000 3.680 209.612 3.686 209.915 3.692 211.131 3.698 202.836 3.704 204.170 3.709 206.034 3.715 204.030 3.721 202.125 3.727 201.351 3.733 201.798 3.738 203.140 3.744 204.627 3.750 207.856 3.756 209.593 3.762 209.269 3.767 206.302 3.773 204.682 3.779 206.496 3.785 0.000 3.791 246.097 3.796 240.924 3.802 237.687 3.808 234.433 3.814 232.048 3.820 229.687 3.825 227.883 3.831 226.290 3.837 225.041 3.843 224.089 3.849 223.483 3.855 223.411 3.860 223.931 3.866 224.870 3.872 227.231 3.878 228.473 3.884 219.342 3.889 210.567 3.895 210.559 3.901 207.174 3.907 214.074 3.913 214.326 3.918 214.516 3.924 216.200 3.930 216.376 3.936 217.433 3.942 218.100 3.947 219.375 3.953 213.388 3.959 217.714 3.965 210.871 3.971 279.330 3.976 277.346 3.982 275.088 3.988 272.550 3.994 269.986 4.000 266.962 4.005 263.758 4.011 259.042 4.017 253.752 4.023 244.810 4.029 233.314 4.034 230.943 4.040 227.473 4.046 225.285 4.052 224.917 4.058 225.571 4.063 227.670 4.069 230.795 4.075 234.508 4.081 239.005 4.087 244.965 4.093 252.268 4.098 257.924 4.104 261.567 4.110 263.051 4.116 263.331 4.122 263.023 4.127 263.857 4.133 271.595 4.139 277.217 4.145 283.815 4.151 282.188 4.156 280.852 4.162 278.267 4.168 274.804 4.174 271.183 4.180 267.831 4.185 263.881 4.191 259.761 4.197 255.962 4.203 252.692 4.209 249.980 4.214 247.870 4.220 246.828 4.226 246.534 4.232 247.045 4.238 249.231 4.243 251.844 4.249 255.240 4.255 258.914 4.261 261.881 4.267 263.567 4.272 263.433 4.278 262.461 4.284 264.293 4.290 267.236 4.296 275.123 4.301 285.267 4.307 307.513 4.313 326.599 4.319 329.041 4.325 330.511 4.331 331.979 4.336 333.908 4.342 334.966 4.348 334.995 4.354 334.151 4.360 332.032 4.365 328.024 4.371 321.894 4.377 314.426 4.383 307.679 4.389 301.731 4.394 296.842 4.400 291.368 4.406 288.796 4.412 287.834 4.418 288.030 4.423 289.216 4.429 291.810 4.435 295.680 4.441 299.058 4.447 304.141 4.452 309.793 4.458 312.844 4.464 313.920 4.470 313.681 4.476 311.644 4.481 307.938 4.487 303.013 4.493 296.266 4.499 276.637 4.505 0.000 4.510 0.000 4.516 0.000 4.522 0.000 4.528 0.000 4.534 0.000 4.540 0.000 4.545 0.000 4.551 0.000 4.557 0.000 4.563 0.000 4.569 0.000 4.574 0.000 4.580 0.000 4.586 0.000 4.592 0.000 4.598 0.000 4.603 0.000 4.609 0.000 4.615 0.000 4.621 319.013 4.627 298.554 4.632 289.451 4.638 285.242 4.644 283.947 4.650 285.201 4.656 287.279 4.661 288.543 4.667 289.180 4.673 289.316 4.679 289.526 4.685 290.232 4.690 275.717 4.696 265.106 4.702 254.177 4.708 258.190 4.714 255.780 4.719 250.910 4.725 246.251 4.731 241.773 4.737 238.669 4.743 206.285 4.748 220.397 4.754 231.214 4.760 236.019 4.766 240.127 4.772 244.248 4.778 250.328 4.783 254.038 4.789 257.167 4.795 257.897 4.801 257.440 4.807 255.776 4.812 253.317 4.818 248.189 4.824 245.718 4.830 250.271 4.836 250.793 4.841 249.525 4.847 247.727 4.853 239.600 4.859 243.281 4.865 237.354 4.870 241.749 4.876 254.881 4.882 255.068 4.888 256.838 4.894 257.884 4.899 0.000 4.905 0.000 4.911 258.426 4.917 253.414 4.923 251.256 4.928 250.806 4.934 0.000 4.940 0.000 4.946 226.776 4.952 225.041 4.957 223.321 4.963 221.168 4.969 220.343 4.975 220.228 4.981 220.777 4.986 222.757 4.992 225.597 4.998 228.411 5.004 230.686 5.010 231.681 5.016 231.821 5.021 231.000 5.027 228.925 5.033 226.113 5.039 220.265 5.045 0.000 5.050 0.000 5.056 0.000 5.062 0.000 5.068 0.000 5.074 0.000 5.079 0.000 5.085 0.000 5.091 227.100 5.097 0.000 5.103 0.000 5.108 0.000 5.114 199.615 5.120 208.025 5.126 212.787 5.132 217.679 5.137 220.852 5.143 225.370 5.149 228.590 5.155 235.983 5.161 240.827 5.166 243.170 5.172 243.775 5.178 243.030 5.184 240.556 5.190 235.939 5.195 231.717 5.201 225.891 5.207 220.037 5.213 209.411 5.219 204.168 5.224 198.703 5.230 193.224 5.236 189.635 5.242 187.233 5.248 186.048 5.254 186.033 5.259 187.311 5.265 189.956 5.271 192.370 5.277 195.460 5.283 202.003 5.288 206.251 5.294 216.748 5.300 229.906 5.306 234.013 5.312 235.414 5.317 235.652 5.323 234.800 5.329 233.066 5.335 231.050 5.341 228.240 5.346 224.704 5.352 213.846 5.358 190.427 5.364 178.974 5.370 176.282 5.375 172.262 5.381 167.089 5.387 165.771 5.393 166.654 5.399 168.551 5.404 170.204 5.410 172.096 5.416 174.306 5.422 176.620 5.428 177.464 5.433 179.192 5.439 197.068 5.445 187.042 5.451 193.664 5.457 0.000 5.462 0.000 5.468 0.000 5.474 0.000 5.480 0.000 5.486 200.972 5.492 183.758 5.497 194.348 5.503 196.988 5.509 188.453 5.515 183.339 5.521 178.775 5.526 173.046 5.532 171.929 5.538 174.748 5.544 171.668 5.550 167.764 5.555 167.549 5.561 167.280 5.567 167.004 5.573 166.986 5.579 167.276 5.584 167.475 5.590 167.212 5.596 166.450 5.602 165.381 5.608 164.426 5.613 164.037 5.619 164.200 5.625 164.019 5.631 163.743 5.637 161.992 5.642 159.065 5.648 154.842 5.654 149.013 5.660 143.677 5.666 129.100 5.671 122.987 5.677 0.000 5.683 0.000 5.689 0.000 5.695 0.000 5.700 0.000 5.706 0.000 5.712 0.000 5.718 0.000 5.724 0.000 5.730 0.000 5.735 0.000 5.741 0.000 5.747 137.687 5.753 138.491 5.759 138.471 5.764 139.098 5.770 140.588 5.776 142.275 5.782 143.194 5.788 143.833 5.793 144.078 5.799 143.734 5.805 143.200 5.811 142.745 5.817 142.158 5.822 129.735 5.828 106.572 5.834 0.000 5.840 283.051 5.846 199.343 5.851 0.000 5.857 0.000 5.863 0.000 5.869 0.000 5.875 0.000 5.880 0.000 5.886 137.609 5.892 146.087 5.898 139.128 5.904 137.523 5.909 135.669 5.915 134.350 5.921 133.950 5.927 134.406 5.933 135.017 5.939 135.589 5.944 136.333 5.950 137.181 5.956 138.299 5.962 139.363 5.968 140.020 5.973 138.240 5.979 134.818 5.985 130.892 5.991 0.000 5.997 0.000 6.002 136.395 6.008 136.896 6.014 136.682 6.020 136.752 6.026 136.602 6.031 136.343 6.037 136.195 6.043 135.614 6.049 135.292 6.055 134.907 6.060 134.731 6.066 135.016 6.072 138.622 6.078 135.646 6.084 59.478 6.089 92.504 6.095 0.000 6.101 0.000 6.107 152.237 6.113 151.302 6.118 150.770 6.124 150.343 6.130 149.968 6.136 149.609 6.142 149.237 6.147 148.620 6.153 147.723 6.159 146.423 6.165 144.993 6.171 143.626 6.177 144.184 6.182 142.749 6.188 146.565 6.194 141.931 6.200 150.988 6.206 161.110 6.211 166.321 6.217 169.042 6.223 194.970 6.229 199.596 6.235 201.784 6.240 203.927 6.246 205.129 6.252 0.000 6.258 0.000 6.264 0.000 6.269 0.000 6.275 163.600 6.281 187.502 6.287 179.521 6.293 175.152 6.298 173.982 6.304 174.651 6.310 176.276 6.316 177.742 6.322 178.566 6.327 178.431 6.333 177.158 6.339 175.376 6.345 173.145 6.351 170.471 6.356 168.807 6.362 166.940 6.368 164.829 6.374 162.646 6.380 161.719 6.385 160.810 6.391 159.280 6.397 157.301 6.403 150.785 6.409 131.414 6.415 123.023 6.420 125.235 6.426 127.654 6.432 187.321 6.438 192.200 6.444 193.789 6.449 194.662 6.455 195.149 6.461 195.690 6.467 196.435 6.473 197.345 6.478 198.108 6.484 198.512 6.490 198.499 6.496 198.122 6.502 197.419 6.507 196.319 6.513 194.176 6.519 192.117 6.525 191.320 6.531 192.795 6.536 193.154 6.542 192.749 6.548 193.257 6.554 193.970 6.560 194.638 6.565 195.376 6.571 196.011 6.577 196.337 6.583 196.186 6.589 195.308 6.594 193.607 6.600 190.944 6.606 187.088 6.612 175.479 6.618 169.502 6.623 196.218 6.629 201.132 6.635 205.717 6.641 209.010 6.647 208.958 6.653 208.828 6.658 208.521 6.664 208.272 6.670 208.346 6.676 208.111 6.682 207.832 6.687 207.529 6.693 207.351 6.699 207.377 6.705 207.611 6.711 208.053 6.716 208.643 6.722 209.294 6.728 209.829 6.734 209.810 6.740 208.565 6.745 206.799 6.751 206.060 6.757 207.391 6.763 211.697 6.769 213.874 6.774 215.135 6.780 217.051 6.786 218.147 6.792 219.525 6.798 221.294 6.803 222.347 6.809 223.462 6.815 223.992 6.821 223.720 6.827 230.287 6.832 232.726 6.838 234.705 6.844 236.306 6.850 236.940 6.856 237.504 6.861 237.806 6.867 237.790 6.873 237.349 6.879 236.503 6.885 235.281 6.891 233.710 6.896 232.028 6.902 229.931 6.908 227.258 6.914 225.097 6.920 223.653 6.925 222.901 6.931 222.752 6.937 223.462 6.943 222.695 6.949 218.420 6.954 216.206 6.960 212.229 6.966 209.194 6.972 210.580 6.978 214.408 6.983 215.488 6.989 220.154 6.995 236.107 7.001 249.383 7.007 250.938 7.012 252.535 7.018 253.323 7.024 253.210 7.030 252.459 7.036 251.225 7.041 249.992 7.047 249.146 7.053 248.531 7.059 248.280 7.065 248.072 7.070 247.823 7.076 247.466 7.082 247.159 7.088 246.786 7.094 246.466 7.100 246.353 7.105 246.971 7.111 247.976 7.117 248.307 7.123 247.808 7.129 246.864 7.134 247.465 7.140 248.879 7.146 250.495 7.152 252.492 7.158 254.772 7.163 258.282 7.169 265.173 7.175 270.435 7.181 274.386 7.187 274.529 7.192 276.064 7.198 278.089 7.204 280.802 7.210 282.398 7.216 284.050 7.221 285.239 7.227 286.159 7.233 286.625 7.239 286.455 7.245 285.441 7.250 284.164 7.256 283.048 7.262 263.893 7.268 246.722 7.274 232.147 7.279 230.274 7.285 222.901 7.291 222.419 7.297 221.614 7.303 225.783 7.308 227.981 7.314 245.680 7.320 283.178 7.326 298.801 7.332 301.560 7.338 303.989 7.343 304.505 7.349 304.477 7.355 304.266 7.361 304.067 7.367 303.953 7.372 304.956 7.378 306.886 7.384 307.489 7.390 309.245 7.396 308.071 7.401 308.238 7.407 306.758 7.413 305.127 7.419 303.758 7.425 302.908 7.430 302.203 7.436 301.428 7.442 300.600 7.448 299.579 7.454 298.020 7.459 296.087 7.465 294.296 7.471 292.831 7.477 291.904 7.483 291.574 7.488 291.705 7.494 292.109 7.500 292.645 7.506 293.206 7.512 293.759 7.517 294.343 7.523 295.070 7.529 296.127 7.535 297.618 7.541 299.157 7.546 300.333 7.552 300.861 7.558 300.715 7.564 300.072 7.570 299.320 7.576 298.745 7.581 298.752 7.587 299.473 7.593 294.457 7.599 291.936 7.605 292.333 7.610 292.965 7.616 292.876 7.622 292.634 7.628 293.177 7.634 306.416 7.639 303.859 7.645 302.608 7.651 297.349 7.657 294.945 7.663 293.246 7.668 292.085 7.674 291.098 7.680 290.150 7.686 289.360 7.692 288.972 7.697 288.918 7.703 288.966 7.709 288.961 7.715 289.060 7.721 289.614 7.726 290.893 7.732 292.471 7.738 294.479 7.744 296.205 7.750 298.061 7.755 287.760 7.761 284.893 7.767 282.356 7.773 283.689 7.779 291.786 7.784 315.771 7.790 314.396 7.796 312.471 7.802 310.497 7.808 308.361 7.814 307.515 7.819 306.834 7.825 306.151 7.831 305.668 7.837 305.352 7.843 305.151 7.848 304.795 7.854 304.201 7.860 303.548 7.866 303.104 7.872 303.137 7.877 303.736 7.883 304.579 7.889 304.863 7.895 304.088 7.901 301.521 7.906 295.711 7.912 290.603 7.918 287.038 7.924 285.914 7.930 289.540 7.935 290.492 7.941 289.885 7.947 293.634 7.953 295.936 7.959 298.105 7.964 299.528 7.970 300.241 7.976 300.625 7.982 301.441 7.988 302.585 7.993 303.452 7.999 303.202 8.005 301.856 8.011 298.614 8.017 293.234 8.022 291.117 8.028 289.984 8.034 289.133 8.040 287.996 8.046 286.158 8.052 284.136 8.057 282.073 8.063 280.120 8.069 275.190 8.075 271.257 8.081 277.359 8.086 269.824 8.092 293.590 8.098 292.055 8.104 289.952 8.110 289.219 8.115 289.153 8.121 290.492 8.127 0.000 8.133 0.000 8.139 0.000 8.144 299.630 8.150 287.641 8.156 282.731 8.162 281.164 8.168 282.028 8.173 284.415 8.179 287.291 8.185 290.474 8.191 293.509 8.197 296.299 8.202 298.222 8.208 299.295 8.214 299.333 8.220 298.579 8.226 297.991 8.231 297.803 8.237 297.921 8.243 297.967 8.249 297.657 8.255 297.050 8.260 296.542 8.266 296.613 8.272 297.458 8.278 299.216 8.284 300.959 8.290 302.296 8.295 303.288 8.301 304.154 8.307 304.798 8.313 305.269 8.319 306.366 8.324 307.261 8.330 297.667 8.336 307.260 8.342 305.780 8.348 303.935 8.353 302.703 8.359 301.591 8.365 300.694 8.371 299.366 8.377 295.915 8.382 291.247 8.388 287.434 8.394 285.627 8.400 286.794 8.406 286.811 8.411 284.493 8.417 287.371 8.423 294.200 8.429 296.480 8.435 295.837 8.440 295.108 8.446 294.534 8.452 294.467 8.458 294.683 8.464 294.964 8.469 295.342 8.475 295.767 8.481 296.195 8.487 296.547 8.493 296.651 8.499 296.333 8.504 295.565 8.510 294.507 8.516 293.523 8.522 293.601 8.528 291.366 8.533 289.227 8.539 287.670 8.545 287.703 8.551 288.041 8.557 289.842 8.562 306.692 8.568 305.337 8.574 307.634 8.580 305.222 8.586 303.700 8.591 301.238 8.597 299.631 8.603 298.505 8.609 297.608 8.615 296.875 8.620 296.346 8.626 296.037 8.632 295.878 8.638 295.853 8.644 295.950 8.649 296.176 8.655 296.273 8.661 295.844 8.667 294.210 8.673 290.484 8.678 284.561 8.684 279.569 8.690 272.663 8.696 273.206 8.702 273.259 8.707 275.258 8.713 276.364 8.719 278.815 8.725 279.158 8.731 282.658 8.737 281.651 8.742 281.315 8.748 281.110 8.754 281.847 8.760 282.850 8.766 284.060 8.771 284.546 8.777 284.642 8.783 284.563 8.789 284.306 8.795 284.221 8.800 284.373 8.806 284.837 8.812 285.412 8.818 285.710 8.824 285.761 8.829 285.694 8.835 285.493 8.841 284.843 8.847 283.590 8.853 281.939 8.858 278.838 8.864 275.505 8.870 269.543 8.876 268.463 8.882 285.295 8.887 285.802 8.893 285.992 8.899 286.599 8.905 287.213 8.911 287.996 8.916 288.735 8.922 288.909 8.928 0.000 8.934 0.000 8.940 0.000 8.945 0.000 8.951 283.278 8.957 273.872 8.963 269.669 8.969 269.663 8.975 274.705 8.980 282.240 8.986 289.827 8.992 296.922 8.998 303.530 9.004 312.528 9.009 319.057 9.015 325.948 9.021 328.752 9.027 329.863 9.033 329.550 9.038 328.090 9.044 325.266 9.050 320.381 9.056 315.189 9.062 310.780 9.067 304.717 9.073 291.779 9.079 286.581 9.085 282.857 9.091 279.762 9.096 277.803 9.102 276.823 9.108 276.927 9.114 278.038 9.120 279.978 9.125 283.327 9.131 287.786 9.137 293.975 9.143 300.079 9.149 305.774 9.154 311.400 9.160 317.593 9.166 323.844 9.172 329.429 9.178 331.644 9.183 331.888 9.189 331.615 9.195 330.009 9.201 327.539 9.207 323.315 9.213 317.272 9.218 311.323 9.224 305.243 9.230 299.404 9.236 295.451 9.242 292.499 9.247 290.514 9.253 289.240 9.259 288.252 9.265 287.708 9.271 287.767 9.276 288.730 9.282 290.469 9.288 293.152 9.294 295.104 9.300 295.700 9.305 295.162 9.311 292.700 9.317 289.765 9.323 285.745 9.329 277.762 9.334 270.112 9.340 263.289 9.346 251.794 9.352 263.437 9.358 266.072 9.363 264.189 9.369 0.000 9.375 0.000 9.381 0.000 9.387 0.000 9.392 0.000 9.398 0.000 9.404 0.000 9.410 0.000 9.416 0.000 9.421 0.000 9.427 0.000 9.433 0.000 9.439 0.000 9.445 0.000 9.451 0.000 9.456 0.000 9.462 0.000 9.468 0.000 9.474 0.000 9.480 0.000 9.485 0.000 9.491 0.000 9.497 0.000 9.503 0.000 9.509 0.000 9.514 0.000 9.520 0.000 9.526 0.000 9.532 0.000 9.538 0.000 9.543 0.000 9.549 0.000 9.555 0.000 9.561 0.000 9.567 0.000 9.572 0.000 9.578 0.000 9.584 0.000 9.590 0.000 9.596 0.000 9.601 0.000 9.607 0.000 9.613 0.000 9.619 0.000 9.625 0.000 9.630 0.000 9.636 0.000 9.642 0.000 9.648 0.000 9.654 0.000 9.660 0.000 9.665 0.000 9.671 0.000 9.677 0.000 9.683 0.000 9.689 0.000 9.694 0.000 9.700 0.000 9.706 0.000 9.712 0.000 9.718 0.000 9.723 0.000 9.729 0.000 9.735 0.000 9.741 0.000 9.747 0.000 9.752 0.000 9.758 0.000 9.764 0.000 9.770 0.000 9.776 0.000 9.781 0.000 9.787 0.000 9.793 0.000 9.799 0.000 9.805 0.000 9.810 0.000 9.816 0.000 9.822 0.000 9.828 0.000 9.834 0.000 9.839 0.000 9.845 0.000 9.851 0.000 9.857 0.000 9.863 0.000 9.868 0.000 9.874 0.000 9.880 0.000 9.886 0.000 9.892 0.000 9.898 0.000 9.903 0.000 9.909 0.000 9.915 0.000 9.921 232.727 9.927 229.457 9.932 229.684 9.938 230.250 9.944 234.973 9.950 241.421 9.956 246.087 9.961 253.637 9.967 261.130 9.973 267.909 9.979 272.439 9.985 279.455 9.990 280.099 9.996 279.928 10.002 278.290 10.008 275.627 10.014 272.150 10.019 267.654 10.025 261.543 10.031 255.800 10.037 250.007 10.043 244.367 10.048 239.577 10.054 235.868 10.060 232.963 10.066 230.607 10.072 229.194 10.077 228.888 10.083 229.679 10.089 231.208 10.095 233.082 10.101 235.217 10.106 237.372 10.112 240.192 10.118 243.381 10.124 246.696 10.130 250.345 10.136 254.714 10.141 264.212 10.147 269.144 10.153 273.287 10.159 276.385 10.165 279.363 10.170 280.457 10.176 280.556 10.182 279.238 10.188 276.407 10.194 269.008 10.199 265.658 10.205 259.473 10.211 253.318 10.217 247.089 10.223 241.855 10.228 236.257 10.234 232.838 10.240 228.873 10.246 226.785 10.252 224.964 10.257 226.927 10.263 230.060 10.269 233.282 10.275 236.743 10.281 239.869 10.286 243.516 10.292 247.316 10.298 251.869 10.304 257.729 10.310 263.138 10.315 267.498 10.321 274.934 10.327 277.104 10.333 278.359 10.339 279.050 10.344 278.523 10.350 276.681 10.356 273.325 10.362 264.885 10.368 261.601 10.374 255.262 10.379 248.563 10.385 242.926 10.391 238.382 10.397 235.102 10.403 231.500 10.408 229.382 10.414 227.520 10.420 228.436 10.426 230.673 10.432 233.181 10.437 237.314 10.443 242.904 10.449 248.037 10.455 255.301 10.461 258.975 10.466 263.529 10.472 269.046 10.478 273.441 10.484 276.349 10.490 277.563 10.495 277.676 10.501 276.875 10.507 274.034 10.513 268.623 10.519 263.038 10.524 257.603 10.530 254.424 10.536 243.218 10.542 240.107 10.548 234.280 10.553 231.174 10.559 228.872 10.565 227.918 10.571 228.309 10.577 228.699 10.582 231.287 10.588 234.300 10.594 237.216 10.600 240.054 10.606 243.733 10.612 247.213 10.617 250.021 10.623 251.607 10.629 252.806 10.635 253.549 10.641 253.568 10.646 252.668 10.652 250.430 10.658 244.971 10.664 236.593 10.670 228.552 10.675 223.861 10.681 222.355 10.687 0.000 10.693 0.000 10.699 232.759 10.704 0.000 10.710 0.000 10.716 0.000 10.722 0.000 10.728 0.000 10.733 0.000 10.739 229.222 10.745 230.972 10.751 227.758 10.757 231.229 10.762 233.548 10.768 236.870 10.774 242.249 10.780 249.171 10.786 255.855 10.791 263.230 10.797 269.726 10.803 275.428 10.809 278.126 10.815 279.236 10.820 279.194 10.826 278.265 10.832 276.913 10.838 275.317 10.844 273.297 10.850 270.316 10.855 266.697 10.861 263.026 10.867 260.253 10.873 258.359 10.879 257.294 10.884 256.768 10.890 256.773 10.896 257.349 10.902 258.627 10.908 260.964 10.913 264.418 10.919 268.373 10.925 273.623 10.931 279.402 10.937 285.356 10.942 291.433 10.948 296.999 10.954 301.859 10.960 305.531 10.966 308.161 10.971 310.297 10.977 311.287 10.983 311.207 10.989 309.968 10.995 307.765 11.000 305.429 11.006 302.856 11.012 299.952 11.018 295.682 11.024 291.297 11.029 286.492 11.035 280.778 11.041 274.302 11.047 268.949 11.053 264.627 11.059 261.217 11.064 259.459 11.070 258.638 11.076 258.655 11.082 259.520 11.088 261.434 11.093 264.041 11.099 267.507 11.105 272.636 11.111 280.546 11.117 285.422 11.122 289.987 11.128 295.368 11.134 300.364 11.140 304.876 11.146 309.170 11.151 313.174 11.157 315.536 11.163 316.390 11.169 316.005 11.175 314.642 11.180 311.896 11.186 307.831 11.192 303.246 11.198 296.223 11.204 290.708 11.209 284.387 11.215 273.976 11.221 267.037 11.227 262.362 11.233 258.952 11.238 257.257 11.244 256.414 11.250 256.675 11.256 258.011 11.262 260.401 11.267 263.834 11.273 268.269 11.279 275.900 11.285 283.502 11.291 288.976 11.297 293.093 11.302 296.800 11.308 300.314 11.314 302.532 11.320 303.897 11.326 304.642 11.331 306.472 11.337 301.438 11.343 297.420 11.349 298.057 11.355 293.587 11.360 289.730 11.366 287.755 11.372 287.350 11.378 276.530 11.384 267.193 11.389 272.997 11.395 274.627 11.401 274.890 11.407 274.631 11.413 273.664 11.418 273.005 11.424 273.330 11.430 274.844 11.436 276.764 11.442 277.847 11.447 278.015 11.453 276.841 11.459 273.656 11.465 267.843 11.471 258.348 11.476 251.973 11.482 248.205 11.488 241.346 11.494 238.403 11.500 229.298 11.505 207.417 11.511 199.750 11.517 193.189 11.523 189.814 11.529 188.123 11.535 187.318 11.540 187.587 11.546 188.707 11.552 190.933 11.558 195.547 11.564 199.832 11.569 205.566 11.575 211.998 11.581 216.225 11.587 219.406 11.593 222.017 11.598 223.167 11.604 223.735 11.610 223.634 11.616 222.843 11.622 221.057 11.627 218.287 11.633 215.012 11.639 211.557 11.645 208.270 11.651 205.303 11.656 203.370 11.662 201.734 11.668 200.366 11.674 199.188 11.680 198.232 11.685 197.690 11.691 197.684 11.697 198.274 11.703 199.505 11.709 201.096 11.714 204.060 11.720 210.155 11.726 214.722 11.732 220.267 11.738 228.193 11.743 232.445 11.749 235.807 11.755 238.570 11.761 240.785 11.767 242.072 11.773 242.343 11.778 241.549 11.784 239.597 11.790 236.493 11.796 232.395 11.802 228.731 11.807 223.113 11.813 215.591 11.819 209.166 11.825 206.340 11.831 201.712 11.836 198.707 11.842 195.796 11.848 193.426 11.854 192.024 11.860 191.678 11.865 192.326 11.871 193.838 11.877 196.379 11.883 199.938 11.889 204.267 11.894 210.561 11.900 220.913 11.906 234.909 11.912 240.182 11.918 243.646 11.923 246.619 11.929 248.538 11.935 249.615 11.941 249.659 11.947 248.583 11.952 246.404 11.958 242.662 11.964 238.479 11.970 233.240 11.976 227.595 11.981 219.218 11.987 209.172 11.993 202.704 11.999 198.168 12.005 195.667 12.011 193.991 12.016 193.336 12.022 193.398 12.028 194.486 12.034 195.584 12.040 198.513 12.045 201.397 12.051 210.335 12.057 220.673 12.063 224.991 12.069 232.487 12.074 236.441 12.080 239.158 12.086 241.224 12.092 242.250 12.098 242.479 12.103 241.911 12.109 240.584 12.115 238.477 12.121 236.211 12.127 232.368 12.132 229.932 12.138 227.750 12.144 224.598 12.150 220.581 12.156 217.480 12.161 215.359 12.167 214.184 12.173 213.848 12.179 214.101 12.185 214.762 12.190 215.806 12.196 217.281 12.202 218.993 12.208 221.048 12.214 223.819 12.220 231.292 12.225 236.936 12.231 239.427 12.237 239.102 12.243 234.478 12.249 218.922 12.254 204.277 12.260 170.983 12.266 155.878 12.272 128.969 12.278 236.027 12.283 207.934 12.289 144.206 12.295 143.597 12.301 145.136 12.307 145.944 12.312 145.475 12.318 144.617 12.324 143.422 12.330 142.307 12.336 141.951 12.341 142.556 12.347 144.043 12.353 145.928 12.359 148.219 12.365 150.466 12.370 153.627 12.376 156.854 12.382 158.892 12.388 160.217 12.394 160.785 12.399 160.746 12.405 159.777 12.411 158.534 12.417 156.815 12.423 154.934 12.428 153.197 12.434 151.325 12.440 149.453 12.446 147.055 12.452 144.495 12.458 142.192 12.463 140.439 12.469 139.045 12.475 137.595 12.481 136.311 12.487 135.568 12.492 135.349 12.498 135.538 12.504 136.073 12.510 137.039 12.516 138.357 12.521 139.832 12.527 141.655 12.533 144.069 12.539 146.920 12.545 149.384 12.550 151.703 12.556 154.548 12.562 157.250 12.568 159.575 12.574 161.581 12.579 163.049 12.585 163.967 12.591 164.059 12.597 163.411 12.603 162.175 12.608 160.571 12.614 158.646 12.620 156.513 12.626 153.829 12.632 151.113 12.637 148.542 12.643 145.268 12.649 142.190 12.655 139.958 12.661 138.111 12.666 136.357 12.672 135.041 12.678 134.301 12.684 134.256 12.690 134.791 12.696 135.702 12.701 137.159 12.707 139.416 12.713 142.893 12.719 146.882 12.725 151.007 12.730 155.075 12.736 158.748 12.742 163.093 12.748 168.254 12.754 171.190 12.759 172.820 12.765 173.410 12.771 172.829 12.777 171.281 12.783 167.264 12.788 163.483 12.794 160.022 12.800 157.056 12.806 153.909 12.812 150.713 12.817 147.521 12.823 143.663 12.829 140.969 12.835 139.155 12.841 137.667 12.846 136.742 12.852 136.276 12.858 136.380 12.864 137.057 12.870 138.256 12.875 139.962 12.881 142.817 12.887 145.826 12.893 149.039 12.899 151.885 12.904 154.137 12.910 156.863 12.916 159.170 12.922 160.829 12.928 162.225 12.934 162.496 12.939 161.573 12.945 160.081 12.951 157.570 12.957 153.483 12.963 147.376 12.968 142.935 12.974 141.809 12.980 140.496 12.986 140.460 12.992 139.969 12.997 139.649 13.003 140.235 13.009 142.647 13.015 143.814 13.021 145.932 13.026 150.031 13.032 151.106 13.038 156.279 13.044 158.755 13.050 166.279 13.055 171.023 13.061 175.040 13.067 178.738 13.073 181.829 13.079 183.838 13.084 184.265 13.090 183.809 13.096 182.731 13.102 180.688 13.108 174.466 13.113 171.550 13.119 168.940 13.125 165.418 13.131 161.897 13.137 160.107 13.142 156.781 13.148 153.563 13.154 151.436 13.160 150.041 13.166 148.784 13.172 147.861 13.177 147.309 13.183 147.193 13.189 147.470 13.195 148.069 13.201 149.077 13.206 150.553 13.212 153.554 13.218 155.907 13.224 161.606 13.230 165.848 13.235 170.709 13.241 179.849 13.247 182.976 13.253 186.131 13.259 188.462 13.264 189.751 13.270 190.002 13.276 189.546 13.282 188.151 13.288 185.404 13.293 180.466 13.299 175.479 13.305 170.492 13.311 166.498 13.317 163.779 13.322 159.499 13.328 157.526 13.334 152.621 13.340 150.624 13.346 149.077 13.351 147.849 13.357 146.967 13.363 146.569 13.369 146.691 13.375 147.332 13.380 148.404 13.386 149.876 13.392 151.827 13.398 154.830 13.404 157.822 13.410 164.371 13.415 166.497 13.421 171.505 13.427 175.498 13.433 178.699 13.439 180.008 13.444 180.298 13.450 179.904 13.456 178.843 13.462 176.905 13.468 173.431 13.473 169.788 13.479 166.383 13.485 164.438 13.491 160.285 13.497 158.119 13.502 154.476 13.508 152.189 13.514 150.226 13.520 148.785 13.526 147.872 13.531 147.541 13.537 147.722 13.543 148.364 13.549 149.358 13.555 150.683 13.560 152.349 13.566 155.350 13.572 157.445 13.578 158.212 13.584 163.478 13.589 172.637 13.595 176.535 13.601 179.615 13.607 180.612 13.613 180.758 13.619 180.112 13.624 178.320 13.630 175.012 13.636 171.614 13.642 164.402 13.648 161.567 13.653 159.370 13.659 155.261 13.665 151.645 13.671 149.746 13.677 148.313 13.682 147.043 13.688 146.329 13.694 146.107 13.700 146.515 13.706 147.563 13.711 149.069 13.717 151.655 13.723 155.003 13.729 162.576 13.735 165.785 13.740 168.829 13.746 171.505 13.752 174.959 13.758 175.870 13.764 174.372 13.769 173.050 13.775 163.048 13.781 162.490 13.787 155.133 13.793 150.711 13.798 139.222 13.804 116.619 13.810 0.000 13.816 0.000 13.822 128.015 13.827 0.000 13.833 161.444 13.839 160.498 13.845 159.520 13.851 159.222 13.857 159.352 13.862 160.123 13.868 161.697 13.874 165.433 13.880 175.455 13.886 184.725 13.891 193.213 13.897 196.509 13.903 203.503 13.909 209.103 13.915 210.846 13.920 211.320 13.926 210.393 13.932 207.347 13.938 203.083 13.944 198.706 13.949 193.297 13.955 183.988 13.961 174.052 13.967 173.485 13.973 169.954 13.978 167.201 13.984 166.048 13.990 165.397 13.996 165.371 14.002 166.007 14.007 167.222 14.013 168.815 14.019 170.810 14.025 174.734 14.031 179.647 14.036 187.027 14.042 192.858 14.048 196.417 14.054 199.721 14.060 203.618 14.065 206.314 14.071 207.299 14.077 207.316 14.083 206.275 14.089 204.435 14.095 201.576 14.100 198.205 14.106 194.708 14.112 189.852 14.118 184.253 14.124 177.941 14.129 174.906 14.135 171.701 14.141 170.326 14.147 169.699 14.153 169.435 14.158 169.911 14.164 171.199 14.170 173.176 14.176 175.793 14.182 180.446 14.187 185.284 14.193 190.222 14.199 194.577 14.205 198.328 14.211 201.164 14.216 205.034 14.222 205.678 14.228 205.186 14.234 203.374 14.240 200.484 14.245 196.577 14.251 191.626 14.257 186.478 14.263 181.675 14.269 178.726 14.274 177.758 14.280 177.884 14.286 178.068 14.292 178.970 14.298 180.845 14.303 183.452 14.309 186.207 14.315 187.600 14.321 188.759 14.327 189.218 14.333 189.254 14.338 189.133 14.344 188.862 14.350 186.482 14.356 183.156 14.362 183.582 14.367 184.880 14.373 183.592 14.379 182.916 14.385 185.470 14.391 183.156 14.396 183.127 14.402 182.926 14.408 177.881 14.414 175.806 14.420 185.993 14.425 186.406 14.431 185.523 14.437 184.221 14.443 204.035 14.449 191.378 14.454 182.289 14.460 170.593 14.466 150.883 14.472 181.543 14.478 185.148 14.483 185.265 14.489 185.447 14.495 186.632 14.501 189.242 14.507 188.393 14.512 0.000 14.518 0.000 14.524 0.000 14.530 0.000 14.536 0.000 14.541 0.000 14.547 0.000 14.553 0.000 14.559 0.000 14.565 0.000 14.571 0.000 14.576 0.000 14.582 0.000 14.588 0.000 14.594 0.000 14.600 0.000 14.605 322.803 14.611 363.462 14.617 357.509 14.623 312.664 14.629 314.417 14.634 317.931 14.640 321.594 14.646 323.678 14.652 324.748 14.658 325.704 14.663 325.182 14.669 324.233 14.675 322.798 14.681 321.210 14.687 319.503 14.692 317.670 14.698 315.655 14.704 314.095 14.710 313.447 14.716 313.865 14.721 315.286 14.727 317.255 14.733 319.742 14.739 322.047 14.745 324.040 14.750 325.153 14.756 325.854 14.762 326.237 14.768 326.488 14.774 326.553 14.780 326.326 14.785 325.698 14.791 324.654 14.797 323.296 14.803 321.926 14.809 320.405 14.814 318.597 14.820 316.581 14.826 314.800 14.832 313.318 14.838 311.797 14.843 310.664 14.849 310.200 14.855 310.313 14.861 310.979 14.867 312.019 14.872 313.681 14.878 316.099 14.884 318.795 14.890 321.889 14.896 325.111 14.901 328.319 14.907 331.213 14.913 333.887 14.919 341.452 14.925 344.472 14.930 346.071 14.936 346.914 14.942 347.269 14.948 347.223 14.954 346.279 14.959 344.178 14.965 340.679 14.971 335.842 14.977 331.128 14.983 327.236 14.988 323.261 14.994 319.323 15.000 315.584 15.006 312.731 15.012 311.180 15.018 310.379 15.023 310.423 15.029 311.119 15.035 312.560 15.041 314.561 15.047 317.006 15.052 320.962 15.058 325.624 15.064 329.466 15.070 334.047 15.076 343.004 15.081 347.852 15.087 351.428 15.093 354.500 15.099 356.393 15.105 357.139 15.110 356.742 15.116 354.487 15.122 350.271 15.128 345.474 15.134 341.063 15.139 337.432 15.145 334.040 15.151 330.731 15.157 326.895 15.163 323.104 15.168 321.877 15.174 315.503 15.180 299.493 15.186 295.247 15.192 295.765 15.197 295.879 15.203 311.095 15.209 309.711 15.215 309.238 15.221 314.972 15.226 318.288 15.232 330.017 15.238 334.598 15.244 337.898 15.250 340.554 15.256 343.300 15.261 345.712 15.267 346.701 15.273 348.973 15.279 351.683 15.285 353.376 15.290 355.171 15.296 357.789 15.302 361.283 15.308 362.422 15.314 360.786 15.319 358.290 15.325 356.579 15.331 352.855 15.337 345.468 15.343 339.990 15.348 338.306 15.354 358.835 15.360 359.877 15.366 357.916 15.372 354.614 15.377 352.338 15.383 351.109 15.389 348.194 15.395 348.243 15.401 348.608 15.406 350.215 15.412 350.146 15.418 350.469 15.424 414.087 15.430 434.553 15.435 441.344 15.441 446.662 15.447 452.692 15.453 249.563 15.459 261.313 15.464 271.842 15.470 283.710 15.476 290.345 15.482 295.695 15.488 301.802 15.494 309.181 15.499 316.582 15.505 322.297 15.511 325.076 15.517 325.518 15.523 324.400 15.528 322.152 15.534 318.972 15.540 315.113 15.546 310.182 15.552 304.125 15.557 298.208 15.563 292.307 15.569 286.802 15.575 280.935 15.581 272.515 15.586 266.785 15.592 262.969 15.598 260.943 15.604 259.798 15.610 259.462 15.615 259.977 15.621 261.369 15.627 263.659 15.633 265.777 15.639 269.578 15.644 276.561 15.650 288.010 15.656 290.859 15.662 297.295 15.668 304.263 15.673 311.331 15.679 315.690 15.685 318.433 15.691 319.914 15.697 320.347 15.702 319.835 15.708 318.416 15.714 315.835 15.720 312.902 15.726 309.282 15.732 304.667 15.737 299.401 15.743 293.551 15.749 288.498 15.755 283.285 15.761 277.481 15.766 267.722 15.772 264.868 15.778 262.347 15.784 260.811 15.790 259.958 15.795 259.839 15.801 260.424 15.807 261.801 15.813 262.655 15.819 264.659 15.824 267.468 15.830 271.635 15.836 277.475 15.842 281.836 15.848 285.623 15.853 288.681 15.859 291.744 15.865 295.542 15.871 297.827 15.877 299.372 15.882 299.583 15.888 298.333 15.894 295.824 15.900 292.336 15.906 289.137 15.911 285.073 15.917 280.397 15.923 275.034 15.929 269.500 15.935 263.653 15.940 260.217 15.946 257.623 15.952 254.943 15.958 251.671 15.964 250.383 15.970 248.787 15.975 247.706 15.981 246.952 15.987 246.515 15.993 246.116 15.999 246.194 16.004 247.262 16.010 250.032 16.016 254.579 16.022 258.939 16.028 262.173 16.033 264.039 16.039 264.473 16.045 260.973 16.051 256.958 16.057 248.756 16.062 250.832 16.068 255.486 16.074 253.708 16.080 252.035 16.086 249.937 16.091 237.822 16.097 232.190 16.103 219.011 16.109 221.177 16.115 220.060 16.120 218.564 16.126 215.698 16.132 215.821 16.138 215.522 16.144 216.190 16.149 217.945 16.155 219.704 16.161 221.933 16.167 223.426 16.173 226.141 16.179 228.293 16.184 229.885 16.190 230.722 16.196 231.045 16.202 229.991 16.208 229.080 16.213 228.819 16.219 227.600 16.225 228.665 16.231 227.696 16.237 227.033 16.242 218.295 16.248 217.029 16.254 216.695 16.260 219.952 16.266 218.306 16.271 217.692 16.277 217.467 16.283 217.696 16.289 218.181 16.295 218.808 16.300 219.521 16.306 220.051 16.312 220.287 16.318 220.269 16.324 220.130 16.329 220.052 16.335 220.035 16.341 219.970 16.347 219.754 16.353 219.001 16.358 218.186 16.364 216.998 16.370 215.153 16.376 213.040 16.382 210.976 16.387 208.946 16.393 206.754 16.399 204.565 16.405 202.813 16.411 201.081 16.417 199.842 16.422 199.227 16.428 199.321 16.434 200.242 16.440 201.895 16.446 204.526 16.451 207.955 16.457 215.256 16.463 221.208 16.469 225.820 16.475 231.120 16.480 234.401 16.486 236.405 16.492 237.323 16.498 237.407 16.504 237.084 16.509 236.219 16.515 235.140 16.521 233.453 16.527 231.527 16.533 229.170 16.538 226.555 16.544 223.772 16.550 220.152 16.556 216.865 16.562 214.210 16.567 211.906 16.573 210.270 16.579 209.151 16.585 208.502 16.591 208.376 16.596 208.889 16.602 210.124 16.608 212.146 16.614 215.000 16.620 218.102 16.625 220.862 16.631 223.789 16.637 227.032 16.643 230.416 16.649 233.252 16.655 235.275 16.660 236.836 16.666 237.864 16.672 238.414 16.678 238.415 16.684 237.994 16.689 237.007 16.695 235.441 16.701 233.471 16.707 231.081 16.713 228.324 16.718 225.122 16.724 221.969 16.730 218.419 16.736 215.830 16.742 214.530 16.747 214.015 16.753 214.033 16.759 214.435 16.765 215.240 16.771 216.638 16.776 218.812 16.782 221.111 16.788 223.697 16.794 226.248 16.800 229.242 16.805 231.818 16.811 233.933 16.817 235.728 16.823 236.971 16.829 237.879 16.834 238.471 16.840 238.721 16.846 238.631 16.852 238.197 16.858 237.498 16.863 236.585 16.869 235.270 16.875 233.482 16.881 231.420 16.887 229.582 16.893 228.571 16.898 228.891 16.904 228.017 16.910 229.438 16.916 228.527 16.922 224.567 16.927 215.943 16.933 220.750 16.939 222.196 16.945 228.492 16.951 234.981 16.956 237.206 16.962 240.199 16.968 304.397 16.974 303.432 16.980 304.313 16.985 306.834 16.991 311.174 16.997 314.987 17.003 318.668 17.009 319.758 17.014 320.055 17.020 319.506 17.026 318.161 17.032 315.875 17.038 312.674 17.043 308.202 17.049 303.926 17.055 299.961 17.061 295.682 17.067 291.724 17.072 288.102 17.078 285.101 17.084 282.885 17.090 281.434 17.096 281.209 17.101 281.816 17.107 283.354 17.113 285.562 17.119 288.102 17.125 291.441 17.131 295.481 17.136 302.222 17.142 309.968 17.148 316.523 17.154 321.390 17.160 328.299 17.165 331.975 17.171 334.783 17.177 336.675 17.183 337.950 17.189 335.579 17.194 332.183 17.200 326.453 17.206 321.117 17.212 316.394 17.218 311.990 17.223 306.944 17.229 299.105 17.235 292.672 17.241 286.384 17.247 282.780 17.252 274.526 17.258 272.869 17.264 272.118 17.270 273.226 17.276 273.725 17.281 276.499 17.287 283.798 17.293 285.839 17.299 289.562 17.305 290.157 17.310 294.899 17.316 299.718 17.322 303.322 17.328 306.338 17.334 308.788 17.340 310.873 17.345 312.079 17.351 312.487 17.357 312.653 17.363 313.189 17.369 314.599 17.374 316.698 17.380 318.179 17.386 318.636 17.392 317.926 17.398 315.973 17.403 313.530 17.409 310.986 17.415 308.335 17.421 305.531 17.427 297.475 17.432 292.040 17.438 288.826 17.444 286.447 17.450 287.824 17.456 286.498 17.461 285.829 17.467 286.164 17.473 286.530 17.479 287.304 17.485 285.630 17.490 287.516 17.496 289.202 17.502 290.670 17.508 292.323 17.514 294.391 17.519 296.551 17.525 298.592 17.531 300.367 17.537 302.285 17.543 304.923 17.548 307.050 17.554 308.002 17.560 308.036 17.566 307.577 17.572 307.066 17.578 306.369 17.583 305.166 17.589 303.392 17.595 300.674 17.601 298.289 17.607 296.342 17.612 294.667 17.618 293.114 17.624 290.397 17.630 289.664 17.636 289.102 17.641 288.747 17.647 288.698 17.653 289.080 17.659 289.820 17.665 290.737 17.670 292.282 17.676 294.858 17.682 299.629 17.688 304.326 17.694 311.713 17.699 317.154 17.705 319.992 17.711 321.013 17.717 320.591 17.723 315.156 17.728 293.733 17.734 297.841 17.740 299.562 17.746 299.170 17.752 299.491 17.757 298.929 17.763 296.199 17.769 293.931 17.775 290.158 17.781 290.150 17.786 291.507 17.792 293.351 17.798 296.842 17.804 302.090 17.810 311.866 17.816 317.543 17.821 322.380 17.827 326.002 17.833 330.380 17.839 334.127 17.845 338.183 17.850 341.601 17.856 343.478 17.862 344.354 17.868 344.396 17.874 343.705 17.879 342.487 17.885 340.885 17.891 338.826 17.897 336.580 17.903 334.367 17.908 331.897 17.914 329.040 17.920 325.372 17.926 321.834 17.932 319.120 17.937 317.291 17.943 316.116 17.949 315.646 17.955 315.975 17.961 317.154 17.966 319.465 17.972 323.184 17.978 325.922 17.984 328.157 17.990 330.302 17.995 332.350 18.001 334.314 18.007 336.395 18.013 338.283 18.019 339.678 18.024 340.346 18.030 340.350 18.036 339.772 18.042 338.799 18.048 337.586 18.054 336.158 18.059 334.447 18.065 332.195 18.071 329.350 18.077 326.713 18.083 324.323 18.088 321.500 18.094 318.294 18.100 316.404 18.106 315.510 18.112 315.282 18.117 315.642 18.123 316.486 18.129 317.945 18.135 320.489 18.141 323.571 18.146 326.792 18.152 330.430 18.158 334.950 18.164 338.649 18.170 341.967 18.175 344.677 18.181 347.223 18.187 349.867 18.193 352.205 18.199 353.667 18.204 354.209 18.210 353.893 18.216 352.675 18.222 350.509 18.228 347.749 18.233 342.285 18.239 336.251 18.245 331.616 18.251 328.018 18.257 322.292 18.262 317.602 18.268 310.862 18.274 307.722 18.280 305.631 18.286 304.643 18.292 304.595 18.297 305.522 18.303 307.413 18.309 310.318 18.315 313.890 18.321 318.276 18.326 322.706 18.332 326.587 18.338 330.080 18.344 334.616 18.350 338.435 18.355 342.919 18.361 345.280 18.367 346.845 18.373 347.546 18.379 347.379 18.384 346.339 18.390 344.416 18.396 341.669 18.402 338.431 18.408 336.115 18.413 334.376 18.419 333.010 18.425 331.760 18.431 330.494 18.437 329.222 18.442 328.319 18.448 328.041 18.454 328.149 18.460 327.985 18.466 327.108 18.471 325.576 18.477 324.167 18.483 321.967 18.489 325.574 18.495 333.815 18.500 333.793 18.506 333.285 18.512 331.976 18.518 332.506 18.524 332.970 18.530 334.112 18.535 336.681 18.541 338.811 18.547 341.563 18.553 340.859 18.559 339.226 18.564 337.842 18.570 335.927 18.576 162.534 18.582 156.649 18.588 150.281 18.593 150.546 18.599 152.242 18.605 158.643 18.611 172.774 18.617 178.863 18.622 181.811 18.628 187.852 18.634 200.739 18.640 204.124 18.646 218.088 18.651 235.636 18.657 238.712 18.663 240.296 18.669 240.504 18.675 239.553 18.680 237.179 18.686 232.868 18.692 228.532 18.698 224.182 18.704 218.666 18.709 213.622 18.715 209.983 18.721 207.387 18.727 204.923 18.733 202.682 18.739 201.460 18.744 200.838 18.750 200.587 18.756 200.682 18.762 201.163 18.768 202.168 18.773 203.925 18.779 206.126 18.785 209.011 18.791 212.655 18.797 216.021 18.802 220.127 18.808 223.426 18.814 227.030 18.820 232.610 18.826 238.748 18.831 241.917 18.837 244.661 18.843 246.563 18.849 247.055 18.855 246.874 18.860 246.008 18.866 244.542 18.872 242.437 18.878 239.928 18.884 236.595 18.889 232.409 18.895 227.083 18.901 223.030 18.907 218.671 18.913 212.854 18.918 207.419 18.924 203.733 18.930 200.828 18.936 197.241 18.942 195.850 18.947 195.389 18.953 195.921 18.959 197.712 18.965 200.553 18.971 203.653 18.977 206.965 18.982 211.828 18.988 218.607 18.994 224.114 19.000 227.979 19.006 232.572 19.011 237.019 19.017 239.720 19.023 242.259 19.029 244.073 19.035 245.407 19.040 246.034 19.046 246.157 19.052 245.799 19.058 244.902 19.064 243.369 19.069 241.269 19.075 238.976 19.081 236.655 19.087 233.855 19.093 230.951 19.098 228.214 19.104 223.262 19.110 220.169 19.116 216.461 19.122 213.127 19.127 210.307 19.133 207.647 19.139 206.328 19.145 205.450 19.151 205.194 19.156 205.515 19.162 206.390 19.168 207.778 19.174 209.654 19.180 212.825 19.185 216.660 19.191 220.243 19.197 223.682 19.203 226.790 19.209 229.932 19.215 233.361 19.220 235.713 19.226 237.654 19.232 239.575 19.238 241.296 19.244 242.704 19.249 243.610 19.255 244.000 19.261 243.759 19.267 242.927 19.273 241.651 19.278 239.964 19.284 237.657 19.290 235.646 19.296 232.880 19.302 230.090 19.307 227.077 19.313 223.931 19.319 221.576 19.325 219.058 19.331 216.452 19.336 214.381 19.342 212.964 19.348 212.325 19.354 212.324 19.360 212.819 19.365 213.862 19.371 215.281 19.377 217.004 19.383 219.059 19.389 221.671 19.394 223.902 19.400 226.053 19.406 227.953 19.412 229.944 19.418 231.586 19.423 232.811 19.429 233.558 19.435 233.883 19.441 233.810 19.447 233.369 19.453 232.545 19.458 231.284 19.464 229.424 19.470 227.148 19.476 223.868 19.482 215.157 19.487 0.000 19.493 0.000 19.499 0.000 19.505 0.000 19.511 0.000 19.516 0.000 19.522 0.000 19.528 0.000 19.534 0.000 19.540 0.000 19.545 0.000 19.551 0.000 19.557 0.000 19.563 0.000 19.569 0.000 19.574 0.000 19.580 0.000 19.586 0.000 19.592 0.000 19.598 0.000 19.603 0.000 19.609 0.000 19.615 0.000 19.621 0.000 19.627 0.000 19.632 0.000 19.638 0.000 19.644 0.000 19.650 0.000 19.656 0.000 19.661 0.000 19.667 0.000 19.673 0.000 19.679 0.000 19.685 0.000 19.691 0.000 19.696 0.000 19.702 0.000 19.708 0.000 19.714 0.000 19.720 0.000 19.725 0.000 19.731 0.000 19.737 0.000 19.743 0.000 19.749 0.000 19.754 0.000 19.760 0.000 19.766 0.000 19.772 0.000 19.778 0.000 19.783 0.000 19.789 0.000 19.795 0.000 19.801 0.000 19.807 0.000 19.812 0.000 19.818 0.000 19.824 0.000 19.830 0.000 19.836 0.000 19.841 0.000 19.847 0.000 19.853 0.000 19.859 0.000 19.865 0.000 19.870 0.000 19.876 0.000 19.882 0.000 19.888 0.000 19.894 0.000 19.900 0.000 19.905 0.000 19.911 0.000 19.917 0.000 19.923 0.000 19.929 0.000 19.934 0.000 19.940 0.000 19.946 0.000 19.952 0.000 19.958 0.000 19.963 0.000 19.969 0.000 19.975 0.000 19.981 0.000 19.987 0.000 19.992 0.000 19.998 0.000 mir_eval-0.8.2/tests/data/melody/ref08.txt000066400000000000000000002177751475740344600204110ustar00rootroot000000000000000.000 0.000 0.006 0.000 0.012 0.000 0.017 192.662 0.023 183.918 0.029 173.222 0.035 173.423 0.041 173.895 0.046 174.300 0.052 174.274 0.058 174.260 0.064 174.195 0.070 174.063 0.075 173.910 0.081 173.739 0.087 173.568 0.093 173.394 0.099 173.229 0.104 173.073 0.110 172.943 0.116 172.859 0.122 172.823 0.128 172.837 0.134 172.924 0.139 173.058 0.145 173.258 0.151 173.583 0.157 174.075 0.163 174.800 0.168 175.722 0.174 176.780 0.180 178.147 0.186 179.640 0.192 180.961 0.197 182.087 0.203 182.804 0.209 183.253 0.215 183.383 0.221 183.320 0.226 183.162 0.232 183.125 0.238 183.119 0.244 183.131 0.250 183.063 0.255 182.998 0.261 182.954 0.267 182.907 0.273 182.724 0.279 182.461 0.284 182.173 0.290 181.921 0.296 181.831 0.302 181.946 0.308 182.182 0.313 182.421 0.319 182.603 0.325 182.768 0.331 183.008 0.337 183.363 0.342 183.875 0.348 184.445 0.354 184.967 0.360 185.436 0.366 185.770 0.372 185.966 0.377 186.122 0.383 186.259 0.389 186.357 0.395 186.408 0.401 186.412 0.406 186.363 0.412 186.150 0.418 185.701 0.424 185.095 0.430 184.524 0.435 183.977 0.441 183.343 0.447 182.679 0.453 182.171 0.459 181.980 0.464 182.110 0.470 182.417 0.476 182.785 0.482 183.183 0.488 183.573 0.493 183.919 0.499 184.148 0.505 184.245 0.511 184.324 0.517 184.538 0.522 184.956 0.528 185.504 0.534 186.023 0.540 186.527 0.546 187.051 0.551 187.500 0.557 187.705 0.563 187.613 0.569 187.271 0.575 186.761 0.580 186.074 0.586 185.219 0.592 184.335 0.598 183.564 0.604 182.985 0.610 182.620 0.615 182.470 0.621 182.578 0.627 182.946 0.633 183.501 0.639 184.081 0.644 184.503 0.650 184.737 0.656 184.824 0.662 184.786 0.668 184.677 0.673 184.562 0.679 184.468 0.685 184.470 0.691 184.613 0.697 184.898 0.702 185.323 0.708 185.911 0.714 186.639 0.720 187.423 0.726 188.034 0.731 188.313 0.737 188.307 0.743 188.118 0.749 187.830 0.755 187.513 0.760 187.185 0.766 186.880 0.772 186.606 0.778 186.276 0.784 185.745 0.789 184.878 0.795 183.761 0.801 182.537 0.807 181.306 0.813 180.077 0.819 179.199 0.824 178.874 0.830 179.064 0.836 179.562 0.842 180.095 0.848 180.566 0.853 181.111 0.859 181.833 0.865 182.714 0.871 183.858 0.877 185.473 0.882 187.542 0.888 189.618 0.894 191.426 0.900 193.172 0.906 194.952 0.911 196.523 0.917 197.830 0.923 198.420 0.929 198.219 0.935 197.338 0.940 195.919 0.946 194.204 0.952 192.362 0.958 190.175 0.964 187.612 0.969 185.098 0.975 182.236 0.981 179.457 0.987 176.448 0.993 174.493 0.998 172.951 1.004 171.908 1.010 171.069 1.016 170.546 1.022 170.588 1.027 171.241 1.033 172.427 1.039 174.282 1.045 176.642 1.051 180.050 1.057 183.116 1.062 187.228 1.068 190.371 1.074 193.612 1.080 195.807 1.086 199.074 1.091 202.078 1.097 204.482 1.103 205.948 1.109 206.425 1.115 205.900 1.120 204.585 1.126 202.697 1.132 200.180 1.138 197.684 1.144 194.844 1.149 191.367 1.155 188.084 1.161 181.452 1.167 175.912 1.173 172.752 1.178 171.327 1.184 170.235 1.190 169.471 1.196 168.994 1.202 169.136 1.207 170.056 1.213 171.914 1.219 174.603 1.225 178.418 1.231 183.307 1.236 187.921 1.242 191.456 1.248 194.598 1.254 199.061 1.260 201.795 1.265 203.873 1.271 204.826 1.277 204.881 1.283 204.101 1.289 202.589 1.295 200.333 1.300 196.768 1.306 193.092 1.312 191.406 1.318 190.219 1.324 188.715 1.329 186.387 1.335 183.399 1.341 181.673 1.347 180.441 1.353 179.438 1.358 178.994 1.364 179.093 1.370 179.730 1.376 180.911 1.382 182.204 1.387 183.841 1.393 185.712 1.399 187.029 1.405 188.288 1.411 189.598 1.416 190.712 1.422 191.431 1.428 191.628 1.434 191.408 1.440 190.899 1.445 190.176 1.451 189.314 1.457 188.268 1.463 187.080 1.469 186.234 1.474 185.481 1.480 184.503 1.486 182.852 1.492 181.029 1.498 179.715 1.503 178.965 1.509 178.491 1.515 178.235 1.521 178.165 1.527 178.378 1.533 178.884 1.538 179.658 1.544 180.639 1.550 181.776 1.556 182.843 1.562 184.004 1.567 185.317 1.573 186.435 1.579 187.256 1.585 187.786 1.591 188.075 1.596 188.189 1.602 188.241 1.608 188.255 1.614 188.095 1.620 187.695 1.625 187.053 1.631 186.187 1.637 185.162 1.643 184.091 1.649 183.083 1.654 182.112 1.660 181.341 1.666 180.779 1.672 180.367 1.678 180.050 1.683 179.737 1.689 179.439 1.695 179.125 1.701 178.798 1.707 178.543 1.712 178.561 1.718 178.986 1.724 179.748 1.730 180.520 1.736 181.026 1.741 181.270 1.747 181.333 1.753 181.407 1.759 181.716 1.765 182.341 1.771 183.220 1.776 184.138 1.782 184.827 1.788 185.237 1.794 185.380 1.800 185.363 1.805 185.302 1.811 185.291 1.817 185.372 1.823 185.500 1.829 185.635 1.834 185.754 1.840 185.831 1.846 185.810 1.852 185.707 1.858 185.593 1.863 185.578 1.869 185.777 1.875 186.268 1.881 187.033 1.887 187.925 1.892 188.857 1.898 189.732 1.904 190.572 1.910 191.385 1.916 191.985 1.921 192.125 1.927 191.687 1.933 190.849 1.939 189.825 1.945 188.828 1.950 187.403 1.956 185.399 1.962 182.768 1.968 179.305 1.974 178.836 1.980 178.603 1.985 179.080 1.991 180.928 1.997 181.306 2.003 182.096 2.009 186.289 2.014 193.107 2.020 196.829 2.026 199.551 2.032 201.746 2.038 203.097 2.043 203.644 2.049 203.498 2.055 202.690 2.061 201.341 2.067 200.005 2.072 198.386 2.078 196.455 2.084 192.158 2.090 194.497 2.096 195.511 2.101 195.140 2.107 195.771 2.113 195.382 2.119 194.620 2.125 193.412 2.130 191.452 2.136 190.551 2.142 193.213 2.148 198.926 2.154 202.315 2.159 204.049 2.165 204.861 2.171 205.619 2.177 206.986 2.183 209.068 2.188 211.509 2.194 213.710 2.200 214.482 2.206 213.960 2.212 212.406 2.218 209.778 2.223 206.750 2.229 203.404 2.235 197.885 2.241 193.159 2.247 189.907 2.252 186.091 2.258 179.997 2.264 175.900 2.270 173.298 2.276 170.924 2.281 169.608 2.287 169.151 2.293 169.404 2.299 170.613 2.305 173.100 2.310 178.760 2.316 187.613 2.322 192.667 2.328 196.830 2.334 204.070 2.339 211.834 2.345 216.166 2.351 220.433 2.357 221.981 2.363 222.522 2.368 222.246 2.374 221.052 2.380 218.654 2.386 215.468 2.392 211.552 2.397 206.619 2.403 200.009 2.409 193.001 2.415 187.132 2.421 178.750 2.426 173.501 2.432 170.711 2.438 168.970 2.444 168.601 2.450 169.380 2.456 171.361 2.461 174.333 2.467 180.827 2.473 188.142 2.479 193.941 2.485 197.230 2.490 202.622 2.496 207.598 2.502 210.648 2.508 213.371 2.514 215.149 2.519 215.716 2.525 215.446 2.531 214.247 2.537 212.078 2.543 207.701 2.548 201.860 2.554 198.023 2.560 195.016 2.566 192.401 2.572 184.352 2.577 185.619 2.583 185.708 2.589 185.385 2.595 185.114 2.601 185.641 2.606 186.887 2.612 186.759 2.618 190.338 2.624 194.263 2.630 197.705 2.635 198.906 2.641 200.999 2.647 200.649 2.653 201.461 2.659 200.857 2.664 200.331 2.670 200.340 2.676 201.114 2.682 205.009 2.688 205.429 2.694 204.876 2.699 201.956 2.705 199.795 2.711 197.690 2.717 194.350 2.723 189.383 2.728 186.847 2.734 180.413 2.740 172.981 2.746 166.097 2.752 155.598 2.757 142.509 2.763 140.633 2.769 139.436 2.775 140.616 2.781 141.623 2.786 142.088 2.792 142.742 2.798 143.334 2.804 144.162 2.810 145.773 2.815 148.331 2.821 151.434 2.827 155.739 2.833 160.742 2.839 166.269 2.844 171.267 2.850 173.942 2.856 176.299 2.862 177.658 2.868 178.385 2.873 178.319 2.879 177.425 2.885 175.567 2.891 173.098 2.897 169.608 2.902 164.152 2.908 160.293 2.914 157.304 2.920 153.193 2.926 149.560 2.932 146.479 2.937 144.205 2.943 142.957 2.949 142.498 2.955 142.744 2.961 143.594 2.966 145.077 2.972 147.381 2.978 149.921 2.984 153.197 2.990 159.390 2.995 162.450 3.001 170.325 3.007 174.198 3.013 180.258 3.019 183.573 3.024 185.710 3.030 187.377 3.036 187.868 3.042 187.682 3.048 186.875 3.053 184.818 3.059 181.777 3.065 180.070 3.071 170.536 3.077 166.131 3.082 161.279 3.088 156.837 3.094 153.344 3.100 151.327 3.106 150.084 3.111 149.746 3.117 150.098 3.123 151.085 3.129 153.074 3.135 155.788 3.140 159.588 3.146 162.094 3.152 168.662 3.158 171.643 3.164 174.878 3.170 177.480 3.175 178.408 3.181 178.065 3.187 176.117 3.193 172.997 3.199 168.921 3.204 161.515 3.210 157.129 3.216 149.305 3.222 150.019 3.228 130.584 3.233 124.462 3.239 118.489 3.245 117.930 3.251 119.868 3.257 113.782 3.262 115.253 3.268 90.788 3.274 92.050 3.280 116.049 3.286 88.923 3.291 87.422 3.297 0.000 3.303 0.000 3.309 0.000 3.315 0.000 3.320 0.000 3.326 0.000 3.332 0.000 3.338 0.000 3.344 0.000 3.349 0.000 3.355 0.000 3.361 0.000 3.367 0.000 3.373 0.000 3.379 0.000 3.384 0.000 3.390 0.000 3.396 0.000 3.402 0.000 3.408 0.000 3.413 0.000 3.419 0.000 3.425 0.000 3.431 0.000 3.437 0.000 3.442 0.000 3.448 0.000 3.454 0.000 3.460 0.000 3.466 0.000 3.471 0.000 3.477 0.000 3.483 0.000 3.489 0.000 3.495 0.000 3.500 0.000 3.506 0.000 3.512 0.000 3.518 0.000 3.524 0.000 3.529 0.000 3.535 0.000 3.541 0.000 3.547 0.000 3.553 0.000 3.558 0.000 3.564 0.000 3.570 0.000 3.576 0.000 3.582 0.000 3.587 0.000 3.593 0.000 3.599 0.000 3.605 0.000 3.611 0.000 3.617 0.000 3.622 0.000 3.628 0.000 3.634 0.000 3.640 0.000 3.646 0.000 3.651 0.000 3.657 0.000 3.663 0.000 3.669 0.000 3.675 0.000 3.680 0.000 3.686 0.000 3.692 0.000 3.698 0.000 3.704 0.000 3.709 0.000 3.715 0.000 3.721 0.000 3.727 0.000 3.733 0.000 3.738 0.000 3.744 0.000 3.750 0.000 3.756 0.000 3.762 0.000 3.767 0.000 3.773 0.000 3.779 0.000 3.785 0.000 3.791 0.000 3.796 0.000 3.802 0.000 3.808 0.000 3.814 0.000 3.820 0.000 3.825 0.000 3.831 0.000 3.837 0.000 3.843 0.000 3.849 0.000 3.855 0.000 3.860 0.000 3.866 0.000 3.872 0.000 3.878 0.000 3.884 0.000 3.889 0.000 3.895 0.000 3.901 0.000 3.907 0.000 3.913 0.000 3.918 0.000 3.924 0.000 3.930 0.000 3.936 0.000 3.942 0.000 3.947 0.000 3.953 0.000 3.959 0.000 3.965 0.000 3.971 0.000 3.976 0.000 3.982 0.000 3.988 0.000 3.994 0.000 4.000 0.000 4.005 0.000 4.011 0.000 4.017 0.000 4.023 0.000 4.029 0.000 4.034 0.000 4.040 0.000 4.046 0.000 4.052 0.000 4.058 0.000 4.063 0.000 4.069 0.000 4.075 0.000 4.081 0.000 4.087 0.000 4.093 0.000 4.098 0.000 4.104 0.000 4.110 0.000 4.116 0.000 4.122 0.000 4.127 0.000 4.133 0.000 4.139 0.000 4.145 0.000 4.151 0.000 4.156 0.000 4.162 0.000 4.168 0.000 4.174 0.000 4.180 0.000 4.185 0.000 4.191 0.000 4.197 0.000 4.203 208.148 4.209 202.041 4.214 196.047 4.220 193.140 4.226 192.497 4.232 192.701 4.238 192.665 4.243 192.559 4.249 192.650 4.255 192.692 4.261 192.498 4.267 192.340 4.272 192.217 4.278 192.088 4.284 191.866 4.290 191.431 4.296 190.865 4.301 190.281 4.307 189.680 4.313 189.009 4.319 188.852 4.325 189.485 4.331 190.225 4.336 190.624 4.342 190.701 4.348 191.066 4.354 191.642 4.360 192.377 4.365 193.057 4.371 193.651 4.377 194.251 4.383 194.869 4.389 195.503 4.394 196.120 4.400 196.722 4.406 197.331 4.412 197.990 4.418 198.668 4.423 199.261 4.429 199.640 4.435 199.741 4.441 199.503 4.447 198.859 4.452 197.891 4.458 196.857 4.464 195.859 4.470 194.904 4.476 194.084 4.481 193.491 4.487 193.188 4.493 193.201 4.499 193.417 4.505 193.693 4.510 193.932 4.516 194.103 4.522 194.257 4.528 194.407 4.534 194.564 4.540 194.730 4.545 194.925 4.551 195.126 4.557 195.400 4.563 195.789 4.569 196.311 4.574 196.884 4.580 197.275 4.586 197.370 4.592 197.223 4.598 196.913 4.603 196.540 4.609 196.161 4.615 195.841 4.621 195.680 4.627 195.677 4.632 195.815 4.638 196.000 4.644 196.185 4.650 196.368 4.656 196.576 4.661 196.741 4.667 196.734 4.673 196.631 4.679 196.629 4.685 196.898 4.690 197.348 4.696 197.706 4.702 197.909 4.708 198.070 4.714 198.191 4.719 198.308 4.725 198.308 4.731 198.175 4.737 197.983 4.743 197.738 4.748 197.487 4.754 197.189 4.760 196.746 4.766 196.251 4.772 195.710 4.778 195.189 4.783 194.784 4.789 194.420 4.795 194.048 4.801 193.638 4.807 193.142 4.812 192.603 4.818 192.026 4.824 191.600 4.830 191.419 4.836 191.435 4.841 191.518 4.847 191.637 4.853 191.962 4.859 192.629 4.865 193.622 4.870 194.985 4.876 196.597 4.882 198.314 4.888 199.938 4.894 201.943 4.899 203.319 4.905 204.507 4.911 205.775 4.917 207.293 4.923 208.414 4.928 208.830 4.934 208.520 4.940 207.378 4.946 205.510 4.952 203.495 4.957 201.213 4.963 198.988 4.969 196.499 4.975 193.168 4.981 190.703 4.986 188.278 4.992 185.838 4.998 183.505 5.004 181.752 5.010 180.802 5.016 180.855 5.021 181.661 5.027 182.801 5.033 183.888 5.039 185.358 5.045 187.161 5.050 188.803 5.056 190.460 5.062 192.871 5.068 195.230 5.074 198.014 5.079 201.124 5.085 203.986 5.091 206.687 5.097 208.406 5.103 209.599 5.108 210.556 5.114 211.083 5.120 211.090 5.126 210.482 5.132 209.130 5.137 207.075 5.143 204.760 5.149 202.411 5.155 200.082 5.161 198.073 5.166 196.255 5.172 194.561 5.178 192.994 5.184 191.025 5.190 188.931 5.195 186.759 5.201 184.940 5.207 183.872 5.213 183.390 5.219 183.504 5.224 184.142 5.230 185.219 5.236 186.568 5.242 188.291 5.248 190.581 5.254 192.921 5.259 194.976 5.265 197.168 5.271 199.610 5.277 201.883 5.283 204.643 5.288 205.929 5.294 206.631 5.300 206.824 5.306 206.666 5.312 206.190 5.317 205.457 5.323 204.481 5.329 203.124 5.335 201.461 5.341 199.783 5.346 198.104 5.352 196.219 5.358 194.055 5.364 191.713 5.370 189.608 5.375 187.618 5.381 185.289 5.387 182.800 5.393 180.347 5.399 178.786 5.404 178.210 5.410 178.392 5.416 179.104 5.422 180.219 5.428 181.604 5.433 183.570 5.439 186.181 5.445 188.670 5.451 190.417 5.457 191.794 5.462 193.186 5.468 195.103 5.474 197.750 5.480 200.638 5.486 202.828 5.492 204.651 5.497 205.181 5.503 205.127 5.509 204.705 5.515 203.986 5.521 202.996 5.526 201.753 5.532 200.186 5.538 198.189 5.544 196.121 5.550 193.754 5.555 191.322 5.561 188.494 5.567 186.289 5.573 184.101 5.579 182.067 5.584 180.250 5.590 179.260 5.596 179.158 5.602 179.732 5.608 180.947 5.613 182.671 5.619 184.474 5.625 186.699 5.631 188.972 5.637 191.566 5.642 193.743 5.648 195.365 5.654 197.323 5.660 199.305 5.666 201.319 5.671 203.435 5.677 204.207 5.683 204.365 5.689 204.082 5.695 203.341 5.700 202.120 5.706 200.526 5.712 198.601 5.718 196.389 5.724 194.192 5.730 191.825 5.735 189.487 5.741 187.046 5.747 184.798 5.753 183.344 5.759 182.606 5.764 182.370 5.770 182.605 5.776 183.360 5.782 184.685 5.788 186.514 5.793 188.302 5.799 189.993 5.805 191.634 5.811 193.509 5.817 195.183 5.822 196.758 5.828 197.947 5.834 198.609 5.840 198.767 5.846 198.459 5.851 197.799 5.857 197.039 5.863 196.290 5.869 195.575 5.875 194.907 5.880 194.239 5.886 193.524 5.892 192.699 5.898 191.756 5.904 190.792 5.909 190.086 5.915 189.853 5.921 190.090 5.927 190.735 5.933 191.721 5.939 192.883 5.944 194.239 5.950 195.698 5.956 197.332 5.962 198.786 5.968 199.743 5.973 200.254 5.979 200.445 5.985 200.367 5.991 200.013 5.997 199.464 6.002 198.893 6.008 198.465 6.014 198.234 6.020 198.059 6.026 197.817 6.031 197.519 6.037 197.286 6.043 197.227 6.049 197.342 6.055 197.526 6.060 197.722 6.066 197.951 6.072 198.179 6.078 198.353 6.084 198.426 6.089 198.412 6.095 198.375 6.101 198.409 6.107 198.550 6.113 198.756 6.118 198.800 6.124 198.407 6.130 197.223 6.136 195.427 6.142 193.392 6.147 191.223 6.153 189.370 6.159 188.263 6.165 187.238 6.171 0.000 6.177 0.000 6.182 65.892 6.188 188.687 6.194 193.118 6.200 192.900 6.206 193.932 6.211 196.060 6.217 196.717 6.223 196.457 6.229 196.283 6.235 195.928 6.240 195.922 6.246 196.439 6.252 196.541 6.258 196.596 6.264 196.427 6.269 197.519 6.275 198.118 6.281 199.197 6.287 198.879 6.293 197.289 6.298 196.749 6.304 196.686 6.310 197.010 6.316 196.889 6.322 196.990 6.327 196.975 6.333 196.840 6.339 196.487 6.345 196.413 6.351 196.125 6.356 196.194 6.362 197.426 6.368 197.245 6.374 196.155 6.380 195.480 6.385 195.860 6.391 196.084 6.397 196.596 6.403 197.803 6.409 198.265 6.415 0.000 6.420 0.000 6.426 198.456 6.432 196.326 6.438 77.684 6.444 0.000 6.449 207.833 6.455 214.365 6.461 215.982 6.467 216.475 6.473 217.475 6.478 219.155 6.484 221.939 6.490 226.068 6.496 230.062 6.502 233.944 6.507 235.886 6.513 236.235 6.519 235.036 6.525 232.425 6.531 228.988 6.536 223.140 6.542 215.282 6.548 209.095 6.554 204.464 6.560 200.021 6.565 196.864 6.571 194.364 6.577 192.842 6.583 192.066 6.589 192.068 6.594 192.863 6.600 194.490 6.606 197.062 6.612 200.041 6.618 204.568 6.623 210.559 6.629 218.625 6.635 229.256 6.641 237.949 6.647 243.928 6.653 247.960 6.658 250.268 6.664 250.935 6.670 250.323 6.676 248.732 6.682 246.374 6.687 243.180 6.693 238.532 6.699 233.247 6.705 227.276 6.711 222.198 6.716 216.859 6.722 212.369 6.728 208.213 6.734 205.202 6.740 202.801 6.745 201.336 6.751 200.740 6.757 200.843 6.763 201.509 6.769 202.618 6.774 204.157 6.780 206.311 6.786 209.570 6.792 214.020 6.798 222.449 6.803 234.960 6.809 240.647 6.815 245.070 6.821 248.904 6.827 251.346 6.832 252.572 6.838 252.572 6.844 251.884 6.850 250.607 6.856 248.188 6.861 245.013 6.867 240.808 6.873 235.785 6.879 229.800 6.885 221.875 6.891 216.651 6.896 213.154 6.902 209.876 6.908 206.626 6.914 203.988 6.920 202.566 6.925 202.462 6.931 203.579 6.937 205.538 6.943 208.198 6.949 211.287 6.954 216.225 6.960 222.653 6.966 227.237 6.972 231.852 6.978 236.280 6.983 240.847 6.989 244.014 6.995 245.763 7.001 245.663 7.007 244.358 7.012 242.411 7.018 239.857 7.024 237.019 7.030 233.473 7.036 229.736 7.041 226.408 7.047 222.487 7.053 220.497 7.059 219.449 7.065 219.135 7.070 219.015 7.076 217.722 7.082 214.998 7.088 210.150 7.094 207.669 7.100 207.184 7.105 0.000 7.111 0.000 7.117 0.000 7.123 0.000 7.129 0.000 7.134 0.000 7.140 161.292 7.146 163.560 7.152 164.580 7.158 162.110 7.163 158.706 7.169 157.010 7.175 156.928 7.181 157.880 7.187 159.859 7.192 163.125 7.198 166.941 7.204 170.628 7.210 174.085 7.216 179.702 7.221 184.097 7.227 190.775 7.233 193.223 7.239 194.504 7.245 195.061 7.250 194.827 7.256 193.996 7.262 192.239 7.268 189.734 7.274 186.394 7.279 180.262 7.285 172.536 7.291 166.895 7.297 161.300 7.303 157.150 7.308 153.073 7.314 150.011 7.320 148.302 7.326 147.133 7.332 146.686 7.338 147.114 7.343 148.554 7.349 151.318 7.355 155.547 7.361 160.654 7.367 165.199 7.372 174.025 7.378 180.648 7.384 187.753 7.390 193.841 7.396 198.175 7.401 201.927 7.407 203.402 7.413 203.988 7.419 203.616 7.425 202.147 7.430 199.195 7.436 195.918 7.442 190.939 7.448 187.479 7.454 181.432 7.459 175.173 7.465 170.471 7.471 166.996 7.477 164.568 7.483 163.410 7.488 162.896 7.494 163.089 7.500 163.988 7.506 165.356 7.512 167.690 7.517 170.078 7.523 173.788 7.529 177.808 7.535 181.788 7.541 189.322 7.546 192.957 7.552 197.094 7.558 200.200 7.564 201.399 7.570 201.290 7.576 199.301 7.581 195.259 7.587 190.146 7.593 186.964 7.599 179.661 7.605 163.257 7.610 147.409 7.616 141.950 7.622 135.422 7.628 130.388 7.634 118.848 7.639 102.635 7.645 103.664 7.651 102.839 7.657 103.867 7.663 112.473 7.668 116.720 7.674 0.000 7.680 0.000 7.686 0.000 7.692 0.000 7.697 0.000 7.703 0.000 7.709 0.000 7.715 0.000 7.721 0.000 7.726 0.000 7.732 0.000 7.738 0.000 7.744 0.000 7.750 0.000 7.755 0.000 7.761 0.000 7.767 0.000 7.773 0.000 7.779 0.000 7.784 0.000 7.790 0.000 7.796 0.000 7.802 0.000 7.808 0.000 7.814 0.000 7.819 0.000 7.825 0.000 7.831 0.000 7.837 0.000 7.843 0.000 7.848 0.000 7.854 0.000 7.860 0.000 7.866 0.000 7.872 0.000 7.877 0.000 7.883 0.000 7.889 0.000 7.895 0.000 7.901 0.000 7.906 0.000 7.912 0.000 7.918 0.000 7.924 0.000 7.930 0.000 7.935 0.000 7.941 0.000 7.947 0.000 7.953 0.000 7.959 0.000 7.964 0.000 7.970 0.000 7.976 0.000 7.982 0.000 7.988 0.000 7.993 0.000 7.999 0.000 8.005 0.000 8.011 0.000 8.017 0.000 8.022 0.000 8.028 0.000 8.034 0.000 8.040 0.000 8.046 0.000 8.052 0.000 8.057 0.000 8.063 0.000 8.069 0.000 8.075 0.000 8.081 0.000 8.086 0.000 8.092 0.000 8.098 0.000 8.104 0.000 8.110 0.000 8.115 0.000 8.121 0.000 8.127 0.000 8.133 0.000 8.139 0.000 8.144 0.000 8.150 0.000 8.156 0.000 8.162 0.000 8.168 0.000 8.173 0.000 8.179 0.000 8.185 0.000 8.191 0.000 8.197 0.000 8.202 0.000 8.208 0.000 8.214 0.000 8.220 0.000 8.226 0.000 8.231 0.000 8.237 0.000 8.243 0.000 8.249 0.000 8.255 0.000 8.260 0.000 8.266 0.000 8.272 0.000 8.278 0.000 8.284 0.000 8.290 0.000 8.295 0.000 8.301 0.000 8.307 0.000 8.313 0.000 8.319 0.000 8.324 0.000 8.330 0.000 8.336 0.000 8.342 0.000 8.348 0.000 8.353 0.000 8.359 0.000 8.365 0.000 8.371 0.000 8.377 0.000 8.382 0.000 8.388 0.000 8.394 0.000 8.400 0.000 8.406 0.000 8.411 0.000 8.417 0.000 8.423 0.000 8.429 0.000 8.435 0.000 8.440 0.000 8.446 0.000 8.452 0.000 8.458 0.000 8.464 0.000 8.469 0.000 8.475 0.000 8.481 0.000 8.487 0.000 8.493 0.000 8.499 0.000 8.504 0.000 8.510 0.000 8.516 0.000 8.522 0.000 8.528 0.000 8.533 0.000 8.539 0.000 8.545 0.000 8.551 0.000 8.557 0.000 8.562 0.000 8.568 0.000 8.574 0.000 8.580 0.000 8.586 0.000 8.591 0.000 8.597 0.000 8.603 0.000 8.609 0.000 8.615 0.000 8.620 0.000 8.626 0.000 8.632 0.000 8.638 0.000 8.644 0.000 8.649 0.000 8.655 0.000 8.661 0.000 8.667 0.000 8.673 0.000 8.678 0.000 8.684 0.000 8.690 0.000 8.696 0.000 8.702 0.000 8.707 0.000 8.713 0.000 8.719 222.278 8.725 212.154 8.731 200.548 8.737 197.530 8.742 196.912 8.748 196.268 8.754 196.003 8.760 196.385 8.766 198.042 8.771 199.446 8.777 200.456 8.783 201.492 8.789 202.449 8.795 203.683 8.800 204.431 8.806 205.121 8.812 205.944 8.818 206.865 8.824 207.841 8.829 208.729 8.835 209.546 8.841 210.367 8.847 211.191 8.853 212.080 8.858 213.104 8.864 214.127 8.870 215.046 8.876 215.717 8.882 216.234 8.887 216.851 8.893 217.666 8.899 218.562 8.905 219.150 8.911 219.375 8.916 219.508 8.922 219.746 8.928 220.282 8.934 220.825 8.940 221.124 8.945 221.125 8.951 220.796 8.957 220.896 8.963 221.194 8.969 221.510 8.975 222.239 8.980 222.249 8.986 222.148 8.992 222.173 8.998 222.474 9.004 222.663 9.009 223.073 9.015 223.318 9.021 223.293 9.027 222.982 9.033 222.482 9.038 221.992 9.044 221.677 9.050 221.521 9.056 221.456 9.062 221.444 9.067 221.478 9.073 221.568 9.079 221.666 9.085 221.654 9.091 221.527 9.096 221.476 9.102 221.623 9.108 221.945 9.114 222.320 9.120 222.688 9.125 223.071 9.131 223.457 9.137 223.704 9.143 223.720 9.149 223.566 9.154 223.371 9.160 223.187 9.166 222.907 9.172 222.428 9.178 221.820 9.183 221.273 9.189 220.867 9.195 220.614 9.201 220.479 9.207 220.403 9.213 220.455 9.218 220.651 9.224 220.920 9.230 221.223 9.236 221.607 9.242 222.140 9.247 222.914 9.253 223.969 9.259 225.119 9.265 226.203 9.271 227.158 9.276 227.902 9.282 228.323 9.288 228.407 9.294 228.238 9.300 227.958 9.305 227.623 9.311 227.219 9.317 226.761 9.323 226.261 9.329 225.679 9.334 224.942 9.340 223.994 9.346 222.900 9.352 221.823 9.358 220.822 9.363 219.956 9.369 219.327 9.375 218.869 9.381 218.513 9.387 218.236 9.392 218.089 9.398 218.201 9.404 218.788 9.410 220.031 9.416 221.953 9.421 224.542 9.427 227.112 9.433 229.617 9.439 231.543 9.445 233.133 9.451 234.593 9.456 235.996 9.462 237.347 9.468 238.444 9.474 239.069 9.480 239.121 9.485 238.693 9.491 237.964 9.497 236.912 9.503 235.382 9.509 233.207 9.514 231.082 9.520 228.953 9.526 226.376 9.532 223.299 9.538 219.562 9.543 215.862 9.549 213.200 9.555 211.003 9.561 209.589 9.567 208.625 9.572 208.179 9.578 208.601 9.584 210.088 9.590 212.472 9.596 215.232 9.601 218.274 9.607 221.221 9.613 223.781 9.619 226.816 9.625 230.308 9.630 232.896 9.636 235.240 9.642 237.166 9.648 239.213 9.654 240.875 9.660 241.981 9.665 242.469 9.671 242.284 9.677 241.409 9.683 239.681 9.689 237.229 9.694 234.721 9.700 232.179 9.706 229.128 9.712 225.831 9.718 222.117 9.723 217.562 9.729 212.519 9.735 208.735 9.741 206.379 9.747 205.399 9.752 205.009 9.758 205.089 9.764 205.848 9.770 207.270 9.776 208.968 9.781 211.180 9.787 213.997 9.793 218.169 9.799 222.363 9.805 224.795 9.810 226.582 9.816 228.859 9.822 231.127 9.828 233.141 9.834 234.681 9.839 235.523 9.845 235.742 9.851 235.494 9.857 234.925 9.863 234.054 9.868 232.762 9.874 231.281 9.880 229.436 9.886 227.445 9.892 225.217 9.898 222.426 9.903 218.145 9.909 215.262 9.915 213.182 9.921 211.877 9.927 211.034 9.932 210.676 9.938 210.915 9.944 211.950 9.950 213.737 9.956 215.938 9.961 218.423 9.967 220.758 9.973 223.246 9.979 225.596 9.985 228.063 9.990 230.720 9.996 232.938 10.002 234.661 10.008 235.933 10.014 236.690 10.019 236.973 10.025 236.715 10.031 235.818 10.037 234.173 10.043 232.103 10.048 229.739 10.054 227.428 10.060 225.726 10.066 224.788 10.072 224.225 10.077 223.334 10.083 222.520 10.089 222.063 10.095 221.642 10.101 220.976 10.106 220.285 10.112 219.739 10.118 219.270 10.124 218.621 10.130 217.692 10.136 216.896 10.141 216.557 10.147 216.564 10.153 216.694 10.159 216.788 10.165 216.806 10.170 216.652 10.176 216.153 10.182 215.428 10.188 214.740 10.194 214.124 10.199 213.460 10.205 213.155 10.211 213.953 10.217 216.291 10.223 219.538 10.228 221.665 10.234 221.843 10.240 221.689 10.246 221.767 10.252 221.976 10.257 222.008 10.263 221.789 10.269 221.492 10.275 221.274 10.281 221.191 10.286 221.211 10.292 221.303 10.298 221.386 10.304 221.392 10.310 221.337 10.315 221.331 10.321 221.444 10.327 221.722 10.333 222.048 10.339 222.226 10.344 222.231 10.350 222.200 10.356 222.260 10.362 222.486 10.368 222.793 10.374 223.058 10.379 223.272 10.385 223.493 10.391 223.738 10.397 224.039 10.403 224.360 10.408 224.637 10.414 224.808 10.420 224.829 10.426 224.728 10.432 224.559 10.437 224.348 10.443 224.131 10.449 223.963 10.455 223.867 10.461 223.860 10.466 223.944 10.472 224.086 10.478 224.219 10.484 224.235 10.490 224.040 10.495 223.634 10.501 223.066 10.507 222.450 10.513 221.959 10.519 221.598 10.524 221.258 10.530 220.826 10.536 220.318 10.542 219.812 10.548 219.401 10.553 219.027 10.559 218.708 10.565 218.518 10.571 218.531 10.577 218.734 10.582 219.040 10.588 219.285 10.594 219.364 10.600 219.238 10.606 219.032 10.612 218.943 10.617 219.083 10.623 219.516 10.629 220.184 10.635 220.928 10.641 221.631 10.646 222.304 10.652 222.939 10.658 223.608 10.664 224.303 10.670 224.985 10.675 225.612 10.681 226.135 10.687 226.529 10.693 226.755 10.699 226.677 10.704 226.198 10.710 225.176 10.716 223.912 10.722 222.485 10.728 220.888 10.733 218.958 10.739 216.455 10.745 213.271 10.751 211.390 10.757 211.645 10.762 200.397 10.768 193.432 10.774 201.344 10.780 211.070 10.786 224.584 10.791 231.666 10.797 245.434 10.803 250.589 10.809 257.049 10.815 258.285 10.820 258.515 10.826 257.310 10.832 256.179 10.838 255.499 10.844 254.728 10.850 253.313 10.855 249.664 10.861 245.929 10.867 244.414 10.873 235.599 10.879 247.232 10.884 248.772 10.890 248.811 10.896 248.682 10.902 247.672 10.908 246.849 10.913 246.734 10.919 247.326 10.925 248.468 10.931 249.806 10.937 250.915 10.942 251.573 10.948 251.772 10.954 251.621 10.960 251.193 10.966 250.120 10.971 249.325 10.977 248.663 10.983 248.230 10.989 248.089 10.995 248.401 11.000 248.439 11.006 248.404 11.012 248.130 11.018 247.616 11.024 246.950 11.029 246.296 11.035 245.741 11.041 245.311 11.047 245.020 11.053 244.895 11.059 244.954 11.064 245.210 11.070 245.662 11.076 246.260 11.082 246.867 11.088 247.390 11.093 247.784 11.099 248.100 11.105 248.373 11.111 248.613 11.117 248.809 11.122 248.944 11.128 249.010 11.134 249.016 11.140 248.965 11.146 248.828 11.151 248.541 11.157 248.106 11.163 247.574 11.169 246.995 11.175 246.384 11.180 245.719 11.186 245.029 11.192 244.360 11.198 243.799 11.204 243.431 11.209 243.303 11.215 243.331 11.221 243.459 11.227 243.633 11.233 243.881 11.238 244.230 11.244 244.715 11.250 245.366 11.256 246.110 11.262 246.948 11.267 247.850 11.273 248.802 11.279 249.846 11.285 250.915 11.291 251.938 11.297 252.972 11.302 253.670 11.308 253.913 11.314 253.580 11.320 252.851 11.326 251.894 11.331 250.766 11.337 249.528 11.343 248.309 11.349 247.163 11.355 245.973 11.360 244.667 11.366 243.474 11.372 242.389 11.378 241.466 11.384 240.660 11.389 239.954 11.395 239.440 11.401 239.170 11.407 239.366 11.413 240.166 11.418 241.588 11.424 243.588 11.430 245.990 11.436 248.383 11.442 251.388 11.447 254.256 11.453 257.102 11.459 259.514 11.465 261.217 11.471 262.208 11.476 264.190 11.482 264.640 11.488 264.956 11.494 264.729 11.500 263.823 11.505 262.558 11.511 261.348 11.517 260.220 11.523 259.078 11.529 257.505 11.535 255.092 11.540 251.946 11.546 248.206 11.552 245.318 11.558 242.646 11.564 239.034 11.569 235.290 11.575 232.193 11.581 230.094 11.587 228.134 11.593 228.392 11.598 229.304 11.604 230.744 11.610 233.418 11.616 236.784 11.622 240.237 11.627 244.058 11.633 247.732 11.639 251.721 11.645 255.144 11.651 258.761 11.656 264.124 11.662 267.239 11.668 269.050 11.674 270.832 11.680 273.724 11.685 274.762 11.691 275.060 11.697 274.548 11.703 271.967 11.709 270.696 11.714 268.910 11.720 267.038 11.726 264.997 11.732 262.994 11.738 260.557 11.743 257.428 11.749 253.584 11.755 250.021 11.761 246.952 11.767 243.703 11.773 240.585 11.778 237.606 11.784 234.938 11.790 231.995 11.796 231.536 11.802 231.878 11.807 232.873 11.813 234.572 11.819 237.329 11.825 240.595 11.831 244.444 11.836 247.508 11.842 250.964 11.848 254.785 11.854 258.933 11.860 262.912 11.865 266.740 11.871 269.014 11.877 270.270 11.883 271.264 11.889 273.292 11.894 271.320 11.900 270.324 11.906 268.604 11.912 266.757 11.918 264.885 11.923 262.848 11.929 260.064 11.935 255.982 11.941 251.569 11.947 247.959 11.952 243.746 11.958 238.324 11.964 234.008 11.970 230.693 11.976 228.144 11.981 225.779 11.987 225.870 11.993 226.492 11.999 227.834 12.005 230.422 12.011 234.064 12.016 237.931 12.022 243.325 12.028 247.456 12.034 250.941 12.040 254.558 12.045 259.752 12.051 263.577 12.057 266.348 12.063 268.925 12.069 269.561 12.074 270.071 12.080 270.039 12.086 269.437 12.092 267.998 12.098 265.361 12.103 262.395 12.109 259.116 12.115 255.281 12.121 250.390 12.127 241.470 12.132 235.519 12.138 233.613 12.144 231.069 12.150 229.821 12.156 229.392 12.161 229.697 12.167 230.931 12.173 232.740 12.179 236.077 12.185 238.465 12.190 240.793 12.196 249.974 12.202 253.312 12.208 256.322 12.214 257.870 12.220 258.473 12.225 258.727 12.231 257.986 12.237 255.334 12.243 254.064 12.249 253.291 12.254 252.820 12.260 251.867 12.266 250.086 12.272 248.663 12.278 247.170 12.283 245.640 12.289 244.812 12.295 243.915 12.301 243.110 12.307 242.122 12.312 241.540 12.318 241.330 12.324 241.590 12.330 241.772 12.336 242.544 12.341 243.324 12.347 243.943 12.353 244.331 12.359 244.076 12.365 242.713 12.370 240.201 12.376 236.472 12.382 232.246 12.388 231.211 12.394 226.886 12.399 219.923 12.405 233.384 12.411 239.579 12.417 236.095 12.423 235.927 12.428 237.542 12.434 239.115 12.440 240.972 12.446 243.400 12.452 246.561 12.458 250.854 12.463 255.813 12.469 260.773 12.475 266.147 12.481 270.280 12.487 273.296 12.492 274.529 12.498 275.158 12.504 274.932 12.510 273.613 12.516 270.886 12.521 266.697 12.527 261.065 12.533 254.554 12.539 249.322 12.545 245.285 12.550 241.594 12.556 237.735 12.562 232.679 12.568 228.556 12.574 225.552 12.579 224.088 12.585 223.501 12.591 223.908 12.597 225.290 12.603 227.650 12.608 231.235 12.614 234.561 12.620 238.519 12.626 243.065 12.632 247.893 12.637 253.111 12.643 264.973 12.649 277.779 12.655 282.064 12.661 284.590 12.666 285.809 12.672 286.409 12.678 286.275 12.684 284.936 12.690 281.878 12.696 277.537 12.701 272.745 12.707 267.877 12.713 261.708 12.719 256.472 12.725 244.274 12.730 238.997 12.736 235.494 12.742 232.267 12.748 230.671 12.754 230.116 12.759 230.431 12.765 231.329 12.771 232.598 12.777 234.672 12.783 237.545 12.788 242.542 12.794 246.447 12.800 257.204 12.806 268.269 12.812 270.850 12.817 271.444 12.823 270.345 12.829 267.316 12.835 261.305 12.841 255.441 12.846 248.671 12.852 242.697 12.858 239.497 12.864 237.580 12.870 225.994 12.875 241.846 12.881 256.046 12.887 269.078 12.893 269.867 12.899 268.064 12.904 265.041 12.910 265.098 12.916 261.533 12.922 260.880 12.928 261.008 12.934 252.852 12.939 249.257 12.945 250.683 12.951 253.558 12.957 256.217 12.963 258.621 12.968 235.988 12.974 241.671 12.980 243.608 12.986 254.746 12.992 251.256 12.997 250.256 13.003 248.392 13.009 247.799 13.015 238.686 13.021 238.888 13.026 248.050 13.032 242.921 13.038 246.241 13.044 250.153 13.050 233.020 13.055 252.256 13.061 249.770 13.067 249.269 13.073 241.575 13.079 244.792 13.084 242.261 13.090 238.870 13.096 0.000 13.102 467.093 13.108 215.426 13.113 169.915 13.119 270.838 13.125 270.034 13.131 271.023 13.137 269.785 13.142 270.641 13.148 272.350 13.154 276.704 13.160 280.730 13.166 283.805 13.172 286.933 13.177 289.495 13.183 291.283 13.189 292.163 13.195 291.873 13.201 290.670 13.206 288.884 13.212 286.586 13.218 283.435 13.224 279.984 13.230 276.331 13.235 273.020 13.241 270.457 13.247 268.697 13.253 267.555 13.259 267.925 13.264 270.086 13.270 274.638 13.276 280.108 13.282 281.536 13.288 281.500 13.293 281.139 13.299 280.730 13.305 280.373 13.311 280.088 13.317 279.884 13.322 279.788 13.328 279.767 13.334 279.767 13.340 279.682 13.346 279.445 13.351 279.007 13.357 278.381 13.363 277.634 13.369 276.959 13.375 276.551 13.380 276.391 13.386 276.294 13.392 276.107 13.398 275.781 13.404 275.449 13.410 275.266 13.415 275.254 13.421 275.353 13.427 275.436 13.433 275.437 13.439 275.472 13.444 275.663 13.450 276.169 13.456 277.015 13.462 277.953 13.468 278.647 13.473 278.916 13.479 278.767 13.485 278.384 13.491 277.972 13.497 277.625 13.502 277.293 13.508 276.963 13.514 276.735 13.520 276.671 13.526 276.791 13.531 277.049 13.537 277.388 13.543 277.824 13.549 278.322 13.555 278.838 13.560 279.310 13.566 279.657 13.572 279.920 13.578 280.208 13.584 280.603 13.589 281.138 13.595 281.792 13.601 282.572 13.607 283.373 13.613 284.051 13.619 284.436 13.624 284.418 13.630 284.035 13.636 283.466 13.642 282.856 13.648 282.333 13.653 281.969 13.659 281.705 13.665 281.445 13.671 281.095 13.677 280.593 13.682 279.956 13.688 279.239 13.694 278.428 13.700 277.528 13.706 276.642 13.711 275.836 13.717 275.128 13.723 274.601 13.729 274.274 13.735 274.035 13.740 273.799 13.746 273.611 13.752 273.634 13.758 274.039 13.764 274.865 13.769 275.983 13.775 277.353 13.781 278.734 13.787 280.002 13.793 281.171 13.798 282.265 13.804 283.352 13.810 284.436 13.816 285.495 13.822 286.351 13.827 286.932 13.833 287.582 13.839 288.103 13.845 288.410 13.851 288.223 13.857 287.517 13.862 286.558 13.868 285.631 13.874 284.703 13.880 283.497 13.886 281.855 13.891 280.015 13.897 278.032 13.903 275.743 13.909 273.603 13.915 271.965 13.920 271.122 13.926 270.961 13.932 271.081 13.938 271.262 13.944 271.449 13.949 272.068 13.955 273.131 13.961 274.600 13.967 276.653 13.973 279.080 13.978 281.640 13.984 283.656 13.990 285.512 13.996 287.255 14.002 289.310 14.007 290.522 14.013 291.269 14.019 292.186 14.025 293.257 14.031 293.423 14.036 292.564 14.042 291.153 14.048 290.255 14.054 289.845 14.060 289.200 14.065 288.071 14.071 286.650 14.077 285.252 14.083 283.261 14.089 280.469 14.095 277.831 14.100 275.388 14.106 273.349 14.112 271.368 14.118 269.916 14.124 269.087 14.129 268.515 14.135 267.681 14.141 266.782 14.147 266.532 14.153 267.034 14.158 268.375 14.164 269.881 14.170 271.368 14.176 273.227 14.182 275.431 14.187 277.790 14.193 280.430 14.199 283.836 14.205 286.375 14.211 287.844 14.216 289.897 14.222 291.864 14.228 293.249 14.234 294.025 14.240 294.290 14.245 294.161 14.251 293.741 14.257 292.957 14.263 291.887 14.269 290.887 14.274 289.989 14.280 288.457 14.286 286.993 14.292 285.490 14.298 283.256 14.303 280.249 14.309 277.505 14.315 274.829 14.321 272.548 14.327 270.784 14.333 269.804 14.338 269.443 14.344 269.407 14.350 269.255 14.356 269.109 14.362 269.394 14.367 270.276 14.373 271.710 14.379 273.292 14.385 275.179 14.391 277.926 14.396 281.174 14.402 284.421 14.408 286.895 14.414 289.380 14.420 291.794 14.425 294.373 14.431 297.024 14.437 299.746 14.443 301.388 14.449 301.578 14.454 301.239 14.460 300.332 14.466 298.401 14.472 295.226 14.478 292.097 14.483 289.845 14.489 287.603 14.495 285.440 14.501 282.152 14.507 279.189 14.512 276.344 14.518 273.933 14.524 271.965 14.530 270.535 14.536 269.831 14.541 269.653 14.547 269.689 14.553 269.840 14.559 270.353 14.565 271.730 14.571 274.573 14.576 278.391 14.582 282.399 14.588 285.477 14.594 287.716 14.600 289.896 14.605 291.995 14.611 293.627 14.617 294.988 14.623 295.929 14.629 295.920 14.634 294.584 14.640 291.252 14.646 287.671 14.652 284.697 14.658 281.195 14.663 276.747 14.669 271.718 14.675 266.099 14.681 261.041 14.687 257.582 14.692 255.897 14.698 255.258 14.704 255.789 14.710 257.479 14.716 260.141 14.721 263.434 14.727 267.454 14.733 271.679 14.739 277.323 14.745 282.773 14.750 285.770 14.756 288.332 14.762 290.780 14.768 292.610 14.774 293.717 14.780 293.791 14.785 293.080 14.791 291.372 14.797 288.944 14.803 285.391 14.809 281.503 14.814 277.900 14.820 274.700 14.826 271.810 14.832 269.185 14.838 267.494 14.843 266.567 14.849 266.236 14.855 266.233 14.861 266.369 14.867 266.677 14.872 267.335 14.878 268.481 14.884 269.971 14.890 271.975 14.896 274.679 14.901 278.661 14.907 282.928 14.913 286.209 14.919 288.318 14.925 289.697 14.930 290.919 14.936 292.134 14.942 292.511 14.948 292.069 14.954 291.180 14.959 290.450 14.965 289.506 14.971 287.773 14.977 285.119 14.983 282.732 14.988 280.820 14.994 279.136 15.000 277.531 15.006 276.039 15.012 274.821 15.018 273.991 15.023 273.899 15.029 274.888 15.035 277.425 15.041 280.576 15.047 283.128 15.052 285.122 15.058 287.266 15.064 289.858 15.070 291.915 15.076 293.545 15.081 294.735 15.087 295.219 15.093 294.912 15.099 293.774 15.105 291.667 15.110 288.927 15.116 285.596 15.122 275.782 15.128 267.495 15.134 0.000 15.139 0.000 15.145 0.000 15.151 0.000 15.157 0.000 15.163 0.000 15.168 0.000 15.174 0.000 15.180 0.000 15.186 0.000 15.192 0.000 15.197 0.000 15.203 0.000 15.209 0.000 15.215 0.000 15.221 0.000 15.226 0.000 15.232 0.000 15.238 0.000 15.244 0.000 15.250 0.000 15.256 0.000 15.261 0.000 15.267 0.000 15.273 0.000 15.279 0.000 15.285 0.000 15.290 0.000 15.296 0.000 15.302 0.000 15.308 0.000 15.314 0.000 15.319 0.000 15.325 0.000 15.331 0.000 15.337 0.000 15.343 0.000 15.348 0.000 15.354 274.162 15.360 261.915 15.366 258.841 15.372 255.211 15.377 253.483 15.383 254.097 15.389 257.731 15.395 263.462 15.401 270.808 15.406 278.994 15.412 286.590 15.418 292.183 15.424 295.717 15.430 297.741 15.435 298.997 15.441 299.744 15.447 300.395 15.453 301.670 15.459 304.940 15.464 308.520 15.470 310.846 15.476 310.318 15.482 307.337 15.488 303.202 15.494 299.662 15.499 296.126 15.505 291.057 15.511 285.664 15.517 280.052 15.523 276.171 15.528 273.401 15.534 272.774 15.540 273.362 15.546 274.456 15.552 275.968 15.557 278.044 15.563 280.216 15.569 282.417 15.575 285.440 15.581 288.870 15.586 292.908 15.592 297.369 15.598 303.505 15.604 308.372 15.610 313.261 15.615 317.062 15.621 320.287 15.627 322.813 15.633 324.226 15.639 324.658 15.644 324.206 15.650 322.990 15.656 321.014 15.662 318.030 15.668 314.857 15.673 311.687 15.679 308.459 15.685 304.134 15.691 297.343 15.697 292.237 15.702 288.708 15.708 285.999 15.714 283.411 15.720 282.111 15.726 280.535 15.732 279.748 15.737 279.828 15.743 280.616 15.749 281.749 15.755 283.009 15.761 284.528 15.766 286.319 15.772 288.381 15.778 290.815 15.784 293.322 15.790 296.503 15.795 300.311 15.801 303.516 15.807 306.757 15.813 309.846 15.819 312.395 15.824 314.298 15.830 315.768 15.836 316.569 15.842 316.951 15.848 316.812 15.853 315.829 15.859 314.227 15.865 312.045 15.871 309.155 15.877 306.388 15.882 303.024 15.888 297.711 15.894 295.413 15.900 292.168 15.906 288.705 15.911 285.883 15.917 283.859 15.923 282.172 15.929 280.956 15.935 280.293 15.940 280.194 15.946 280.274 15.952 280.374 15.958 280.566 15.964 281.985 15.970 284.327 15.975 286.862 15.981 289.575 15.987 291.922 15.993 294.511 15.999 297.549 16.004 300.649 16.010 303.439 16.016 306.706 16.022 310.344 16.028 312.866 16.033 314.412 16.039 315.270 16.045 315.523 16.051 315.268 16.057 314.424 16.062 312.912 16.068 310.807 16.074 307.962 16.080 304.965 16.086 301.612 16.091 298.758 16.097 295.604 16.103 292.609 16.109 290.254 16.115 289.214 16.120 287.438 16.126 285.536 16.132 283.768 16.138 282.793 16.144 282.452 16.149 282.455 16.155 282.411 16.161 282.580 16.167 282.952 16.173 284.577 16.179 286.819 16.184 289.242 16.190 291.537 16.196 294.143 16.202 297.223 16.208 301.014 16.213 304.057 16.219 307.046 16.225 309.842 16.231 311.972 16.237 313.329 16.242 314.252 16.248 314.891 16.254 315.312 16.260 315.431 16.266 315.120 16.271 314.392 16.277 313.362 16.283 312.122 16.289 310.680 16.295 308.572 16.300 305.817 16.306 301.778 16.312 296.614 16.318 293.763 16.324 291.281 16.329 289.828 16.335 288.050 16.341 286.083 16.347 283.997 16.353 282.495 16.358 281.626 16.364 281.293 16.370 281.246 16.376 280.841 16.382 281.662 16.387 282.819 16.393 284.309 16.399 286.181 16.405 288.733 16.411 291.243 16.417 293.938 16.422 297.532 16.428 300.694 16.434 303.425 16.440 306.867 16.446 310.972 16.451 314.314 16.457 317.257 16.463 319.255 16.469 320.530 16.475 321.149 16.480 321.074 16.486 320.344 16.492 319.150 16.498 317.650 16.504 315.788 16.509 313.700 16.515 310.942 16.521 308.208 16.527 304.608 16.533 300.338 16.538 297.096 16.544 294.515 16.550 292.242 16.556 290.210 16.562 288.453 16.567 286.859 16.573 285.609 16.579 285.011 16.585 285.172 16.591 285.826 16.596 286.527 16.602 287.154 16.608 286.966 16.614 288.547 16.620 290.196 16.625 292.188 16.631 294.865 16.637 298.127 16.643 301.215 16.649 303.163 16.655 305.993 16.660 308.964 16.666 311.567 16.672 313.585 16.678 315.675 16.684 317.522 16.689 319.068 16.695 320.090 16.701 320.343 16.707 319.873 16.713 318.776 16.718 317.122 16.724 315.048 16.730 312.669 16.736 309.998 16.742 306.506 16.747 303.912 16.753 301.075 16.759 296.544 16.765 293.107 16.771 290.441 16.776 288.418 16.782 286.880 16.788 285.546 16.794 284.655 16.800 284.354 16.805 284.690 16.811 285.403 16.817 286.221 16.823 287.168 16.829 288.029 16.834 290.376 16.840 292.887 16.846 295.760 16.852 298.443 16.858 301.073 16.863 302.613 16.869 304.948 16.875 307.361 16.881 309.044 16.887 309.808 16.893 309.955 16.898 309.901 16.904 309.662 16.910 309.052 16.916 308.071 16.922 306.961 16.927 305.857 16.933 304.519 16.939 302.999 16.945 300.700 16.951 299.395 16.956 297.956 16.962 296.372 16.968 294.726 16.974 293.143 16.980 291.875 16.985 290.896 16.991 290.073 16.997 289.378 17.003 288.883 17.009 288.575 17.014 288.381 17.020 288.304 17.026 288.521 17.032 289.165 17.038 290.224 17.043 291.495 17.049 292.942 17.055 294.389 17.061 295.492 17.067 296.353 17.072 297.207 17.078 298.310 17.084 300.004 17.090 302.014 17.096 304.283 17.101 306.437 17.107 307.758 17.113 308.465 17.119 308.860 17.125 309.090 17.131 309.101 17.136 308.751 17.142 307.973 17.148 306.757 17.154 304.799 17.160 301.974 17.165 297.539 17.171 294.174 17.177 291.291 17.183 288.982 17.189 287.061 17.194 285.164 17.200 284.950 17.206 284.477 17.212 284.282 17.218 284.350 17.223 284.688 17.229 284.950 17.235 286.045 17.241 287.529 17.247 289.306 17.252 291.169 17.258 293.445 17.264 296.122 17.270 298.609 17.276 300.556 17.281 302.288 17.287 304.606 17.293 307.241 17.299 309.494 17.305 311.396 17.310 312.916 17.316 314.275 17.322 315.305 17.328 315.769 17.334 315.403 17.340 314.111 17.345 311.919 17.351 308.638 17.357 305.487 17.363 302.699 17.369 299.801 17.374 297.354 17.380 295.278 17.386 293.168 17.392 291.155 17.398 290.438 17.403 288.849 17.409 287.136 17.415 285.651 17.421 284.577 17.427 284.199 17.432 284.321 17.438 284.455 17.444 284.229 17.450 284.868 17.456 285.961 17.461 287.515 17.467 289.235 17.473 290.929 17.479 293.002 17.485 295.964 17.490 298.660 17.496 300.840 17.502 302.990 17.508 306.323 17.514 310.272 17.519 313.131 17.525 315.168 17.531 317.157 17.537 318.450 17.543 319.055 17.548 318.755 17.554 317.605 17.560 316.009 17.566 314.192 17.572 312.375 17.578 310.193 17.583 307.439 17.589 304.722 17.595 301.152 17.601 298.064 17.607 295.663 17.612 292.377 17.618 292.406 17.624 291.499 17.630 290.768 17.636 290.003 17.641 289.150 17.647 288.538 17.653 288.222 17.659 288.328 17.665 288.050 17.670 289.293 17.676 290.776 17.682 292.401 17.688 294.175 17.694 295.951 17.699 297.753 17.705 299.493 17.711 301.233 17.717 303.389 17.723 306.470 17.728 309.398 17.734 311.881 17.740 313.671 17.746 315.341 17.752 316.530 17.757 317.189 17.763 317.138 17.769 316.343 17.775 314.862 17.781 313.078 17.786 311.440 17.792 309.757 17.798 307.723 17.804 305.333 17.810 302.617 17.816 298.246 17.821 295.521 17.827 293.772 17.833 292.513 17.839 292.852 17.845 292.397 17.850 291.790 17.856 290.925 17.862 290.005 17.868 289.269 17.874 288.182 17.879 288.701 17.885 289.457 17.891 290.363 17.897 291.421 17.903 292.656 17.908 294.113 17.914 295.555 17.920 297.012 17.926 298.506 17.932 300.251 17.937 302.233 17.943 304.543 17.949 306.732 17.955 308.439 17.961 309.897 17.966 311.033 17.972 311.793 17.978 312.231 17.984 312.348 17.990 312.133 17.995 311.527 18.001 310.387 18.007 308.685 18.013 306.696 18.019 304.762 18.024 302.421 18.030 300.478 18.036 298.382 18.042 296.290 18.048 294.559 18.054 293.199 18.059 292.262 18.065 291.584 18.071 290.882 18.077 290.158 18.083 289.636 18.088 289.489 18.094 289.724 18.100 290.233 18.106 290.892 18.112 291.772 18.117 293.000 18.123 294.555 18.129 296.253 18.135 297.935 18.141 299.557 18.146 301.376 18.152 303.860 18.158 306.654 18.164 308.676 18.170 310.310 18.175 311.802 18.181 313.146 18.187 314.191 18.193 314.697 18.199 314.560 18.204 313.851 18.210 312.654 18.216 310.955 18.222 308.495 18.228 305.774 18.233 302.852 18.239 299.117 18.245 296.781 18.251 295.251 18.257 293.957 18.262 292.648 18.268 291.468 18.274 290.475 18.280 290.820 18.286 289.927 18.292 289.100 18.297 287.606 18.303 287.633 18.309 287.802 18.315 287.970 18.321 288.298 18.326 288.991 18.332 290.139 18.338 291.758 18.344 293.729 18.350 295.599 18.355 297.151 18.361 298.662 18.367 300.716 18.373 303.504 18.379 307.239 18.384 310.807 18.390 313.583 18.396 315.725 18.402 317.266 18.408 317.991 18.413 318.054 18.419 317.355 18.425 316.001 18.431 314.511 18.437 313.046 18.442 311.436 18.448 309.476 18.454 307.273 18.460 305.088 18.466 302.761 18.471 298.059 18.477 295.442 18.483 293.831 18.489 294.525 18.495 293.975 18.500 293.557 18.506 292.916 18.512 292.060 18.518 291.091 18.524 289.182 18.530 289.169 18.535 289.563 18.541 290.307 18.547 291.402 18.553 293.115 18.559 295.471 18.564 298.147 18.570 300.348 18.576 301.848 18.582 303.216 18.588 304.835 18.593 306.540 18.599 308.094 18.605 309.385 18.611 310.641 18.617 311.772 18.622 312.657 18.628 313.138 18.634 313.115 18.640 312.580 18.646 311.559 18.651 310.080 18.657 308.207 18.663 305.995 18.669 303.657 18.675 301.655 18.680 298.045 18.686 296.252 18.692 294.642 18.698 293.025 18.704 291.623 18.709 290.518 18.715 289.438 18.721 289.543 18.727 288.584 18.733 288.007 18.739 286.730 18.744 286.952 18.750 287.232 18.756 287.656 18.762 288.467 18.768 289.803 18.773 291.915 18.779 294.735 18.785 297.936 18.791 301.229 18.797 303.823 18.802 306.980 18.808 310.316 18.814 313.180 18.820 315.792 18.826 317.941 18.831 320.118 18.837 321.649 18.843 322.778 18.849 323.316 18.855 323.276 18.860 322.708 18.866 321.577 18.872 319.810 18.878 317.597 18.884 314.941 18.889 311.762 18.895 307.959 18.901 303.710 18.907 299.302 18.913 295.059 18.918 291.821 18.924 288.283 18.930 284.674 18.936 281.758 18.942 279.682 18.947 278.375 18.953 277.762 18.959 277.580 18.965 277.862 18.971 278.490 18.977 279.536 18.982 281.010 18.988 282.655 18.994 284.682 19.000 285.448 19.006 288.391 19.011 291.161 19.017 294.312 19.023 297.631 19.029 301.069 19.035 304.899 19.040 309.425 19.046 312.650 19.052 314.794 19.058 316.522 19.064 317.664 19.069 318.268 19.075 318.286 19.081 317.595 19.087 316.187 19.093 314.357 19.098 312.142 19.104 309.432 19.110 306.511 19.116 302.785 19.122 299.719 19.127 296.855 19.133 293.912 19.139 291.250 19.145 291.321 19.151 290.179 19.156 289.244 19.162 288.293 19.168 287.406 19.174 286.925 19.180 286.971 19.185 286.168 19.191 287.269 19.197 288.616 19.203 290.055 19.209 291.718 19.215 294.152 19.220 297.371 19.226 300.905 19.232 304.068 19.238 308.371 19.244 312.696 19.249 315.741 19.255 318.215 19.261 320.521 19.267 322.463 19.273 324.115 19.278 325.107 19.284 325.517 19.290 325.414 19.296 324.831 19.302 323.699 19.307 321.884 19.313 319.352 19.319 316.462 19.325 313.348 19.331 309.898 19.336 305.974 19.342 302.028 19.348 295.383 19.354 291.092 19.360 287.329 19.365 284.009 19.371 281.753 19.377 280.473 19.383 279.915 19.389 280.960 19.394 281.755 19.400 283.265 19.406 285.188 19.412 286.862 19.418 288.339 19.423 288.443 19.429 290.548 19.435 293.025 19.441 296.128 19.447 298.771 19.453 301.298 19.458 303.667 19.464 306.688 19.470 309.368 19.476 311.216 19.482 312.189 19.487 312.723 19.493 313.057 19.499 313.247 19.505 313.253 19.511 312.975 19.516 312.345 19.522 311.203 19.528 309.340 19.534 307.045 19.540 304.420 19.545 301.992 19.551 298.704 19.557 296.934 19.563 295.779 19.569 294.830 19.574 293.888 19.580 292.793 19.586 291.611 19.592 290.434 19.598 289.264 19.603 288.314 19.609 287.680 19.615 287.404 19.621 287.495 19.627 287.949 19.632 288.906 19.638 290.369 19.644 292.145 19.650 294.542 19.656 297.507 19.661 300.542 19.667 303.718 19.673 307.636 19.679 310.866 19.685 312.791 19.691 314.087 19.696 315.184 19.702 315.985 19.708 316.430 19.714 316.402 19.720 315.904 19.725 315.097 19.731 314.037 19.737 312.644 19.743 310.930 19.749 308.865 19.754 306.547 19.760 303.846 19.766 301.306 19.772 299.031 19.778 296.588 19.783 294.400 19.789 292.554 19.795 293.123 19.801 292.199 19.807 291.046 19.812 289.609 19.818 288.385 19.824 286.296 19.830 286.675 19.836 287.586 19.841 288.919 19.847 290.661 19.853 293.025 19.859 295.599 19.865 298.868 19.870 302.091 19.876 306.420 19.882 310.982 19.888 313.836 19.894 315.652 19.900 317.097 19.905 318.299 19.911 319.292 19.917 319.812 19.923 319.793 19.929 319.421 19.934 318.794 19.940 317.812 19.946 316.296 19.952 314.333 19.958 311.766 19.963 309.053 19.969 305.564 19.975 300.859 19.981 296.613 19.987 293.622 19.992 289.934 19.998 287.014 20.004 284.752 20.010 282.782 20.016 281.477 20.021 280.918 20.027 280.925 20.033 281.269 20.039 281.815 20.045 282.639 20.050 283.938 20.056 285.877 20.062 286.574 20.068 289.359 20.074 292.453 20.079 296.177 20.085 300.361 20.091 304.371 20.097 308.384 20.103 312.151 20.108 314.496 20.114 316.217 20.120 317.037 20.126 317.253 20.132 316.967 20.138 316.199 20.143 314.946 20.149 313.384 20.155 311.417 20.161 309.272 20.167 306.927 20.172 304.883 20.178 302.078 20.184 296.941 20.190 293.408 20.196 290.255 20.201 290.219 20.207 288.540 20.213 287.278 20.219 285.997 20.225 285.110 20.230 284.971 20.236 285.560 20.242 286.472 20.248 287.285 20.254 287.053 20.259 288.809 20.265 290.944 20.271 293.638 20.277 296.243 20.283 298.579 20.288 300.794 20.294 302.993 20.300 306.313 20.306 309.865 20.312 312.340 20.317 313.811 20.323 314.811 20.329 315.267 20.335 315.231 20.341 314.485 20.346 313.030 20.352 310.892 20.358 307.834 20.364 304.840 20.370 300.719 20.376 297.017 20.381 293.878 20.387 291.362 20.393 289.310 20.399 287.068 20.405 287.004 20.410 285.385 20.416 284.269 20.422 284.011 20.428 284.419 20.434 285.108 20.439 284.612 20.445 285.835 20.451 287.284 20.457 288.754 20.463 290.019 20.468 291.190 20.474 292.401 20.480 293.860 20.486 295.369 20.492 297.139 20.497 299.290 20.503 301.585 20.509 303.957 20.515 305.753 20.521 306.361 20.526 305.634 20.532 303.182 20.538 300.742 20.544 298.658 20.550 297.196 20.555 296.304 20.561 295.663 20.567 295.231 20.573 295.069 20.579 295.376 20.584 296.256 20.590 297.605 20.596 299.242 20.602 300.903 20.608 302.749 20.614 304.872 20.619 306.527 20.625 307.392 20.631 307.662 20.637 307.745 20.643 308.095 20.648 308.886 20.654 309.923 20.660 310.776 20.666 311.233 20.672 311.216 20.677 310.752 20.683 309.882 20.689 308.581 20.695 306.937 20.701 305.304 20.706 303.536 20.712 301.483 20.718 299.321 20.724 294.108 20.730 288.954 20.735 284.405 20.741 255.538 20.747 222.293 20.753 208.778 20.759 201.513 20.764 194.402 20.770 0.000 20.776 0.000 20.782 0.000 20.788 0.000 20.793 0.000 20.799 0.000 20.805 0.000 20.811 0.000 20.817 0.000 20.822 0.000 20.828 125.355 20.834 123.131 20.840 120.100 20.846 120.375 20.852 121.201 20.857 122.907 20.863 124.408 20.869 124.859 20.875 125.793 20.881 127.418 20.886 128.486 20.892 129.346 20.898 130.474 20.904 131.693 20.910 133.166 20.915 134.417 20.921 136.046 20.927 137.103 20.933 138.872 20.939 139.782 20.944 141.588 20.950 142.624 20.956 144.626 20.962 146.071 20.968 147.175 20.973 147.860 20.979 148.140 20.985 147.899 20.991 147.153 20.997 146.063 21.002 144.751 21.008 143.357 21.014 142.075 21.020 140.685 21.026 139.229 21.031 137.982 21.037 137.401 21.043 137.327 21.049 137.577 21.055 138.033 21.060 138.611 21.066 139.352 21.072 140.095 21.078 140.721 21.084 141.373 21.090 142.171 21.095 143.227 21.101 144.641 21.107 145.984 21.113 147.060 21.119 148.041 21.124 149.095 21.130 150.132 21.136 151.021 21.142 151.910 21.148 152.657 21.153 153.041 21.159 152.998 21.165 152.494 21.171 151.651 21.177 150.555 21.182 149.010 21.188 147.241 21.194 145.223 21.200 142.970 21.206 139.872 21.211 136.808 21.217 134.680 21.223 133.394 21.229 132.789 21.235 131.981 21.240 131.904 21.246 132.108 21.252 132.670 21.258 133.641 21.264 135.340 21.269 137.218 21.275 139.542 21.281 142.396 21.287 145.568 21.293 148.736 21.299 151.836 21.304 153.350 21.310 155.232 21.316 156.848 21.322 157.795 21.328 158.236 21.333 158.201 21.339 157.650 21.345 156.508 21.351 154.965 21.357 152.663 21.362 150.606 21.368 148.130 21.374 145.552 21.380 143.333 21.386 141.234 21.391 139.128 21.397 137.188 21.403 135.959 21.409 135.354 21.415 135.397 21.420 135.436 21.426 136.950 21.432 138.672 21.438 141.193 21.444 144.270 21.449 147.661 21.455 151.172 21.461 152.825 21.467 154.951 21.473 156.637 21.478 157.885 21.484 158.440 21.490 158.230 21.496 157.208 21.502 155.137 21.507 152.943 21.513 150.535 21.519 147.921 21.525 145.493 21.531 143.581 21.537 142.251 21.542 141.636 21.548 141.787 21.554 142.428 21.560 143.569 21.566 145.446 21.571 147.202 21.577 148.657 21.583 150.057 21.589 151.394 21.595 152.708 21.600 153.732 21.606 154.484 21.612 155.181 21.618 154.169 21.624 154.202 21.629 151.787 21.635 146.212 21.641 0.000 21.647 0.000 21.653 143.846 21.658 150.342 21.664 0.000 21.670 0.000 21.676 147.144 21.682 146.117 21.687 145.231 21.693 145.492 21.699 149.144 21.705 0.000 21.711 0.000 21.716 0.000 21.722 0.000 21.728 0.000 21.734 0.000 21.740 0.000 21.745 0.000 21.751 0.000 21.757 0.000 21.763 0.000 21.769 0.000 21.775 0.000 21.780 0.000 21.786 0.000 21.792 0.000 21.798 0.000 21.804 0.000 21.809 146.871 21.815 145.911 21.821 0.000 21.827 0.000 21.833 0.000 21.838 0.000 21.844 0.000 21.850 0.000 21.856 0.000 21.862 0.000 21.867 0.000 21.873 0.000 21.879 0.000 21.885 0.000 21.891 0.000 21.896 0.000 21.902 0.000 21.908 0.000 21.914 0.000 21.920 0.000 21.925 0.000 21.931 0.000 21.937 0.000 21.943 0.000 21.949 0.000 21.954 0.000 21.960 0.000 21.966 0.000 21.972 0.000 21.978 0.000 21.983 0.000 21.989 0.000 21.995 0.000 22.001 0.000 22.007 0.000 22.013 0.000 22.018 0.000 22.024 0.000 22.030 0.000 22.036 0.000 22.042 0.000 22.047 0.000 22.053 0.000 22.059 0.000 22.065 0.000 22.071 0.000 22.076 0.000 22.082 0.000 22.088 0.000 22.094 0.000 22.100 0.000 22.105 0.000 22.111 0.000 22.117 0.000 22.123 0.000 22.129 0.000 22.134 0.000 22.140 0.000 22.146 0.000 22.152 0.000 22.158 0.000 22.163 0.000 22.169 0.000 22.175 0.000 mir_eval-0.8.2/tests/data/melody/ref09.txt000066400000000000000000002003131475740344600203660ustar00rootroot000000000000000.000 120.607 0.006 121.814 0.012 123.229 0.017 124.053 0.023 124.569 0.029 123.986 0.035 125.423 0.041 128.111 0.046 130.314 0.052 131.194 0.058 146.946 0.064 158.367 0.070 158.101 0.075 157.931 0.081 159.494 0.087 163.366 0.093 166.066 0.099 167.659 0.104 171.503 0.110 172.480 0.116 173.456 0.122 174.432 0.128 175.409 0.134 175.634 0.139 175.898 0.145 175.745 0.151 175.297 0.157 174.849 0.163 174.401 0.168 174.349 0.174 174.978 0.180 175.608 0.186 176.237 0.192 177.123 0.197 177.881 0.203 178.639 0.209 178.796 0.215 179.254 0.221 179.711 0.226 179.868 0.232 180.013 0.238 180.011 0.244 179.869 0.250 179.797 0.255 179.689 0.261 179.681 0.267 179.649 0.273 179.629 0.279 179.724 0.284 179.673 0.290 179.675 0.296 179.689 0.302 179.766 0.308 179.874 0.313 179.982 0.319 180.090 0.325 179.928 0.331 179.766 0.337 179.604 0.342 179.163 0.348 178.885 0.354 178.636 0.360 178.444 0.366 178.330 0.372 178.255 0.377 178.185 0.383 178.086 0.389 177.986 0.395 177.826 0.401 177.665 0.406 177.372 0.412 177.339 0.418 177.295 0.424 177.166 0.430 176.954 0.435 176.692 0.441 176.408 0.447 176.123 0.453 175.838 0.459 175.878 0.464 175.903 0.470 175.929 0.476 176.183 0.482 176.417 0.488 176.651 0.493 176.886 0.499 177.114 0.505 177.345 0.511 177.575 0.517 177.322 0.522 177.405 0.528 177.569 0.534 177.744 0.540 178.060 0.546 178.377 0.551 178.695 0.557 179.013 0.563 179.332 0.569 179.305 0.575 179.344 0.580 179.329 0.586 179.140 0.592 178.861 0.598 178.411 0.604 177.961 0.610 177.511 0.615 177.061 0.621 177.142 0.627 177.120 0.633 177.236 0.639 177.382 0.644 177.561 0.650 177.746 0.656 177.875 0.662 178.004 0.668 178.247 0.673 178.490 0.679 178.733 0.685 178.976 0.691 179.315 0.697 179.543 0.702 179.649 0.708 179.604 0.714 179.457 0.720 179.452 0.726 179.210 0.731 178.969 0.737 179.254 0.743 179.315 0.749 179.377 0.755 179.438 0.760 179.499 0.766 179.560 0.772 180.240 0.778 180.486 0.784 180.710 0.789 180.878 0.795 180.962 0.801 180.937 0.807 180.811 0.813 180.615 0.819 180.418 0.824 180.222 0.830 179.926 0.836 178.557 0.842 177.725 0.848 176.624 0.853 175.524 0.859 174.046 0.865 172.757 0.871 171.468 0.877 168.477 0.882 168.000 0.888 166.266 0.894 163.509 0.900 161.264 0.906 157.175 0.911 154.008 0.917 149.222 0.923 147.462 0.929 145.702 0.935 145.381 0.940 147.228 0.946 149.140 0.952 154.040 0.958 162.170 0.964 168.684 0.969 174.247 0.975 182.088 0.981 186.902 0.987 189.365 0.993 196.156 0.998 200.782 1.004 201.768 1.010 203.475 1.016 204.461 1.022 203.749 1.027 203.881 1.033 203.865 1.039 202.958 1.045 201.905 1.051 200.924 1.057 199.907 1.062 198.909 1.068 197.980 1.074 197.514 1.080 197.258 1.086 197.128 1.091 197.089 1.097 197.300 1.103 197.511 1.109 197.936 1.115 198.255 1.120 198.573 1.126 198.891 1.132 199.060 1.138 199.125 1.144 199.176 1.149 199.226 1.155 199.277 1.161 199.688 1.167 199.919 1.173 200.149 1.178 200.380 1.184 200.324 1.190 200.288 1.196 200.242 1.202 200.197 1.207 200.151 1.213 200.094 1.219 199.909 1.225 199.678 1.231 199.218 1.236 199.043 1.242 199.032 1.248 198.939 1.254 198.846 1.260 198.753 1.265 198.660 1.271 198.567 1.277 198.821 1.283 198.696 1.289 198.572 1.295 198.553 1.300 198.296 1.306 198.159 1.312 198.021 1.318 199.017 1.324 199.023 1.329 199.029 1.335 197.973 1.341 198.604 1.347 196.557 1.353 194.509 1.358 192.461 1.364 188.510 1.370 184.558 1.376 180.606 1.382 180.188 1.387 172.662 1.393 171.046 1.399 168.860 1.405 167.096 1.411 166.772 1.416 164.071 1.422 164.185 1.428 164.298 1.434 167.699 1.440 174.541 1.445 176.069 1.451 183.858 1.457 186.632 1.463 189.406 1.469 194.101 1.474 195.858 1.480 197.614 1.486 199.370 1.492 201.127 1.498 200.854 1.503 202.496 1.509 201.592 1.515 201.642 1.521 201.691 1.527 201.741 1.533 201.497 1.538 201.254 1.544 202.248 1.550 203.046 1.556 203.844 1.562 205.210 1.567 206.577 1.573 207.943 1.579 209.726 1.585 211.509 1.591 213.442 1.596 215.375 1.602 217.128 1.608 218.652 1.614 219.835 1.620 220.447 1.625 220.695 1.631 220.476 1.637 220.104 1.643 219.555 1.649 218.947 1.654 218.340 1.660 217.897 1.666 217.371 1.672 216.941 1.678 216.514 1.683 216.097 1.689 215.839 1.695 215.664 1.701 215.729 1.707 215.919 1.712 216.413 1.718 216.886 1.724 217.188 1.730 217.288 1.736 217.195 1.741 217.009 1.747 216.869 1.753 216.883 1.759 216.917 1.765 217.322 1.771 217.542 1.776 217.761 1.782 217.817 1.788 217.955 1.794 217.861 1.800 215.697 1.805 214.569 1.811 217.181 1.817 216.727 1.823 217.202 1.829 217.053 1.834 215.705 1.840 214.520 1.846 213.098 1.852 211.542 1.858 209.698 1.863 208.111 1.869 206.920 1.875 205.721 1.881 204.987 1.887 201.980 1.892 200.109 1.898 199.648 1.904 199.186 1.910 199.461 1.916 199.157 1.921 198.824 1.927 198.491 1.933 198.158 1.939 197.825 1.945 197.493 1.950 197.160 1.956 196.827 1.962 196.494 1.968 195.878 1.974 195.262 1.980 195.198 1.985 195.275 1.991 195.560 1.997 195.987 2.003 196.524 2.009 197.094 2.014 197.665 2.020 197.832 2.026 197.795 2.032 197.471 2.038 196.934 2.043 196.330 2.049 195.726 2.055 195.539 2.061 195.351 2.067 195.448 2.072 195.446 2.078 195.444 2.084 195.442 2.090 195.441 2.096 195.439 2.101 195.385 2.107 195.269 2.113 195.150 2.119 195.032 2.125 194.993 2.130 195.032 2.136 195.095 2.142 195.107 2.148 195.031 2.154 194.926 2.159 194.822 2.165 194.899 2.171 195.028 2.177 195.254 2.183 195.481 2.188 195.568 2.194 195.496 2.200 195.319 2.206 195.131 2.212 194.949 2.218 195.000 2.223 195.046 2.229 195.111 2.235 195.188 2.241 195.299 2.247 195.447 2.252 195.622 2.258 195.803 2.264 195.985 2.270 196.105 2.276 196.179 2.281 196.247 2.287 196.318 2.293 196.447 2.299 196.522 2.305 196.586 2.310 196.627 2.316 196.680 2.322 196.732 2.328 196.785 2.334 196.776 2.339 196.720 2.345 196.665 2.351 196.624 2.357 196.638 2.363 196.709 2.368 196.788 2.374 196.863 2.380 196.820 2.386 196.823 2.392 196.806 2.397 196.748 2.403 196.663 2.409 196.560 2.415 196.446 2.421 196.378 2.426 196.455 2.432 196.662 2.438 196.868 2.444 197.075 2.450 197.187 2.456 197.231 2.461 197.244 2.467 197.223 2.473 197.147 2.479 197.018 2.485 196.890 2.490 196.761 2.496 196.819 2.502 196.823 2.508 196.984 2.514 197.174 2.519 197.388 2.525 197.606 2.531 197.787 2.537 197.905 2.543 197.986 2.548 198.049 2.554 198.052 2.560 197.953 2.566 197.769 2.572 197.567 2.577 197.364 2.583 197.161 2.589 197.302 2.595 197.357 2.601 197.455 2.606 197.580 2.612 197.762 2.618 198.002 2.624 200.093 2.630 200.755 2.635 200.936 2.641 201.117 2.647 201.298 2.653 199.465 2.659 194.495 2.664 191.094 2.670 186.908 2.676 183.115 2.682 0.000 2.688 0.000 2.694 0.000 2.699 0.000 2.705 0.000 2.711 0.000 2.717 0.000 2.723 0.000 2.728 0.000 2.734 0.000 2.740 0.000 2.746 0.000 2.752 0.000 2.757 0.000 2.763 0.000 2.769 0.000 2.775 0.000 2.781 0.000 2.786 0.000 2.792 0.000 2.798 0.000 2.804 0.000 2.810 0.000 2.815 0.000 2.821 0.000 2.827 0.000 2.833 0.000 2.839 187.979 2.844 182.340 2.850 179.240 2.856 177.448 2.862 177.812 2.868 178.177 2.873 178.542 2.879 178.252 2.885 178.316 2.891 177.829 2.897 177.117 2.902 176.425 2.908 175.829 2.914 175.394 2.920 175.171 2.926 175.158 2.932 175.224 2.937 175.100 2.943 174.885 2.949 174.613 2.955 174.342 2.961 174.071 2.966 174.090 2.972 174.110 2.978 174.291 2.984 174.581 2.990 174.870 2.995 175.159 3.001 175.634 3.007 175.940 3.013 176.245 3.019 176.550 3.024 176.856 3.030 176.934 3.036 177.126 3.042 176.997 3.048 176.864 3.053 176.623 3.059 176.383 3.065 176.143 3.071 175.903 3.077 175.862 3.082 175.937 3.088 176.011 3.094 176.086 3.100 176.166 3.106 176.435 3.111 176.610 3.117 176.833 3.123 177.031 3.129 177.043 3.135 176.978 3.140 176.914 3.146 176.850 3.152 176.785 3.158 177.132 3.164 177.782 3.170 178.524 3.175 179.266 3.181 180.008 3.187 180.750 3.193 179.677 3.199 176.496 3.204 172.626 3.210 165.183 3.216 162.718 3.222 160.919 3.228 163.582 3.233 169.025 3.239 173.078 3.245 0.000 3.251 0.000 3.257 0.000 3.262 0.000 3.268 0.000 3.274 0.000 3.280 0.000 3.286 0.000 3.291 0.000 3.297 0.000 3.303 0.000 3.309 0.000 3.315 0.000 3.320 0.000 3.326 0.000 3.332 0.000 3.338 0.000 3.344 0.000 3.349 0.000 3.355 0.000 3.361 0.000 3.367 0.000 3.373 0.000 3.379 0.000 3.384 0.000 3.390 0.000 3.396 0.000 3.402 0.000 3.408 0.000 3.413 0.000 3.419 0.000 3.425 0.000 3.431 0.000 3.437 0.000 3.442 0.000 3.448 0.000 3.454 0.000 3.460 0.000 3.466 0.000 3.471 0.000 3.477 0.000 3.483 0.000 3.489 0.000 3.495 0.000 3.500 0.000 3.506 0.000 3.512 0.000 3.518 0.000 3.524 0.000 3.529 0.000 3.535 0.000 3.541 0.000 3.547 0.000 3.553 0.000 3.558 0.000 3.564 0.000 3.570 0.000 3.576 0.000 3.582 0.000 3.587 0.000 3.593 0.000 3.599 0.000 3.605 0.000 3.611 0.000 3.617 0.000 3.622 0.000 3.628 0.000 3.634 0.000 3.640 0.000 3.646 0.000 3.651 0.000 3.657 0.000 3.663 0.000 3.669 0.000 3.675 0.000 3.680 0.000 3.686 0.000 3.692 0.000 3.698 0.000 3.704 0.000 3.709 0.000 3.715 0.000 3.721 0.000 3.727 177.949 3.733 177.948 3.738 177.948 3.744 180.336 3.750 181.909 3.756 183.481 3.762 185.054 3.767 186.626 3.773 188.199 3.779 188.156 3.785 189.587 3.791 190.629 3.796 191.069 3.802 191.814 3.808 192.407 3.814 193.076 3.820 194.037 3.825 195.071 3.831 196.425 3.837 197.992 3.843 199.558 3.849 200.690 3.855 201.694 3.860 202.477 3.866 203.260 3.872 203.757 3.878 204.408 3.884 205.060 3.889 205.306 3.895 205.454 3.901 205.457 3.907 205.375 3.913 205.208 3.918 204.976 3.924 204.693 3.930 204.410 3.936 204.126 3.942 204.285 3.947 204.475 3.953 204.754 3.959 205.036 3.965 205.316 3.971 205.487 3.976 205.609 3.982 205.670 3.988 205.675 3.994 205.681 4.000 205.782 4.005 205.884 4.011 205.985 4.017 206.087 4.023 206.338 4.029 206.515 4.034 206.092 4.040 206.293 4.046 206.299 4.052 206.003 4.058 205.916 4.063 205.502 4.069 205.251 4.075 205.200 4.081 205.148 4.087 205.115 4.093 205.089 4.098 205.062 4.104 205.046 4.110 205.055 4.116 205.071 4.122 205.086 4.127 205.102 4.133 204.996 4.139 204.988 4.145 204.980 4.151 205.090 4.156 205.450 4.162 205.912 4.168 206.391 4.174 206.889 4.180 207.387 4.185 207.884 4.191 207.767 4.197 207.716 4.203 207.664 4.209 207.301 4.214 207.160 4.220 207.165 4.226 207.301 4.232 207.442 4.238 207.437 4.243 207.317 4.249 207.118 4.255 206.958 4.261 206.799 4.267 206.639 4.272 206.480 4.278 206.320 4.284 206.220 4.290 206.089 4.296 206.177 4.301 206.264 4.307 206.428 4.313 206.687 4.319 206.946 4.325 207.009 4.331 206.949 4.336 206.732 4.342 206.408 4.348 206.085 4.354 205.761 4.360 205.731 4.365 205.554 4.371 205.492 4.377 205.430 4.383 205.368 4.389 205.456 4.394 205.545 4.400 205.543 4.406 203.462 4.412 204.445 4.418 198.345 4.423 203.727 4.429 204.304 4.435 204.722 4.441 205.141 4.447 205.559 4.452 206.329 4.458 206.979 4.464 207.426 4.470 207.719 4.476 207.877 4.481 207.814 4.487 207.740 4.493 207.593 4.499 207.635 4.505 207.857 4.510 208.135 4.516 208.434 4.522 208.533 4.528 208.607 4.534 208.549 4.540 208.423 4.545 208.331 4.551 207.776 4.557 207.417 4.563 206.908 4.569 206.415 4.574 205.915 4.580 205.414 4.586 204.913 4.592 204.412 4.598 203.911 4.603 201.376 4.609 199.858 4.615 197.832 4.621 196.060 4.627 194.987 4.632 193.565 4.638 186.548 4.644 185.975 4.650 185.823 4.656 187.315 4.661 187.943 4.667 187.113 4.673 187.147 4.679 187.181 4.685 187.215 4.690 187.249 4.696 187.606 4.702 188.517 4.708 189.427 4.714 191.025 4.719 192.256 4.725 193.487 4.731 194.718 4.737 196.282 4.743 198.198 4.748 199.937 4.754 201.677 4.760 202.860 4.766 204.074 4.772 204.986 4.778 205.651 4.783 206.025 4.789 206.145 4.795 206.114 4.801 206.019 4.807 205.845 4.812 205.611 4.818 205.347 4.824 205.160 4.830 205.098 4.836 205.079 4.841 205.060 4.847 205.040 4.853 205.021 4.859 205.002 4.865 204.982 4.870 204.963 4.876 204.943 4.882 205.092 4.888 205.426 4.894 205.760 4.899 206.094 4.905 206.066 4.911 206.056 4.917 206.046 4.923 206.036 4.928 206.026 4.934 206.025 4.940 206.045 4.946 205.989 4.952 205.809 4.957 205.501 4.963 205.188 4.969 204.877 4.975 204.866 4.981 204.870 4.986 204.882 4.992 204.901 4.998 204.920 5.004 204.940 5.010 205.022 5.016 205.172 5.021 205.399 5.027 205.633 5.033 205.867 5.039 205.900 5.045 205.877 5.050 205.776 5.056 205.676 5.062 205.575 5.068 205.639 5.074 205.631 5.079 205.617 5.085 205.602 5.091 205.541 5.097 205.356 5.103 205.115 5.108 204.874 5.114 204.750 5.120 204.690 5.126 204.736 5.132 204.933 5.137 205.225 5.143 205.561 5.149 205.875 5.155 205.890 5.161 205.892 5.166 205.799 5.172 205.696 5.178 205.594 5.184 205.581 5.190 205.641 5.195 205.735 5.201 205.848 5.207 205.961 5.213 206.075 5.219 206.208 5.224 206.403 5.230 206.633 5.236 206.863 5.242 207.093 5.248 206.897 5.254 206.700 5.259 206.215 5.265 205.594 5.271 204.835 5.277 204.008 5.283 203.084 5.288 202.139 5.294 201.195 5.300 200.256 5.306 199.315 5.312 198.375 5.317 197.658 5.323 197.249 5.329 197.009 5.335 196.917 5.341 196.957 5.346 197.159 5.352 197.485 5.358 197.898 5.364 198.331 5.370 198.764 5.375 199.197 5.381 198.815 5.387 198.603 5.393 198.304 5.399 197.986 5.404 197.669 5.410 197.351 5.416 197.457 5.422 197.563 5.428 197.864 5.433 198.221 5.439 198.578 5.445 198.935 5.451 199.149 5.457 199.218 5.462 199.287 5.468 199.356 5.474 199.425 5.480 198.352 5.486 198.322 5.492 197.771 5.497 193.530 5.503 198.780 5.509 198.871 5.515 198.963 5.521 198.663 5.526 198.457 5.532 198.062 5.538 197.884 5.544 197.597 5.550 197.821 5.555 197.772 5.561 197.734 5.567 195.714 5.573 200.526 5.579 198.154 5.584 197.136 5.590 197.395 5.596 197.655 5.602 197.291 5.608 197.020 5.613 197.117 5.619 196.977 5.625 196.778 5.631 196.578 5.637 196.424 5.642 196.371 5.648 196.394 5.654 196.448 5.660 196.486 5.666 196.514 5.671 196.532 5.677 196.554 5.683 196.594 5.689 196.702 5.695 196.870 5.700 197.038 5.706 197.067 5.712 196.997 5.718 196.846 5.724 196.668 5.730 196.491 5.735 196.592 5.741 196.584 5.747 196.804 5.753 196.820 5.759 196.756 5.764 196.623 5.770 196.490 5.776 196.286 5.782 196.204 5.788 196.264 5.793 196.457 5.799 196.730 5.805 196.963 5.811 197.197 5.817 197.409 5.822 197.567 5.828 197.713 5.834 197.859 5.840 197.982 5.846 197.964 5.851 197.826 5.857 197.506 5.863 197.318 5.869 197.248 5.875 197.177 5.880 197.505 5.886 197.832 5.892 198.160 5.898 198.800 5.904 199.284 5.909 199.768 5.915 196.941 5.921 197.109 5.927 198.518 5.933 200.311 5.939 201.358 5.944 201.916 5.950 202.694 5.956 203.197 5.962 203.699 5.968 205.131 5.973 206.284 5.979 207.436 5.985 209.735 5.991 209.346 5.997 212.677 6.002 210.795 6.008 213.034 6.014 212.256 6.020 214.172 6.026 213.256 6.031 213.231 6.037 213.205 6.043 213.180 6.049 212.817 6.055 210.496 6.060 210.577 6.066 209.112 6.072 207.867 6.078 208.017 6.084 207.406 6.089 206.796 6.095 206.600 6.101 206.403 6.107 206.546 6.113 206.706 6.118 206.872 6.124 207.030 6.130 207.058 6.136 207.086 6.142 206.925 6.147 206.840 6.153 206.764 6.159 206.748 6.165 206.798 6.171 206.848 6.177 206.694 6.182 206.771 6.188 206.771 6.194 206.771 6.200 206.809 6.206 207.039 6.211 207.269 6.217 207.499 6.223 209.806 6.229 208.964 6.235 208.777 6.240 209.051 6.246 206.854 6.252 208.090 6.258 208.007 6.264 209.685 6.269 210.394 6.275 210.800 6.281 211.122 6.287 211.311 6.293 211.398 6.298 211.390 6.304 211.303 6.310 211.212 6.316 211.190 6.322 211.168 6.327 210.658 6.333 210.094 6.339 209.371 6.345 208.566 6.351 207.787 6.356 206.845 6.362 205.917 6.368 204.820 6.374 203.486 6.380 202.152 6.385 200.819 6.391 197.749 6.397 195.547 6.403 194.840 6.409 191.452 6.415 189.404 6.420 186.686 6.426 182.461 6.432 180.779 6.438 174.268 6.444 170.172 6.449 171.464 6.455 171.918 6.461 172.356 6.467 172.802 6.473 173.303 6.478 173.950 6.484 174.596 6.490 175.243 6.496 175.890 6.502 177.921 6.507 178.918 6.513 179.915 6.519 180.912 6.525 182.558 6.531 183.880 6.536 185.363 6.542 187.716 6.548 189.295 6.554 190.874 6.560 192.896 6.565 193.943 6.571 195.477 6.577 196.438 6.583 197.284 6.589 197.850 6.594 198.220 6.600 198.479 6.606 198.593 6.612 198.559 6.618 198.336 6.623 198.026 6.629 197.775 6.635 197.607 6.641 197.567 6.647 197.648 6.653 197.784 6.658 197.920 6.664 198.055 6.670 197.838 6.676 197.725 6.682 197.560 6.687 197.394 6.693 197.229 6.699 197.170 6.705 197.252 6.711 197.487 6.716 197.769 6.722 198.052 6.728 198.080 6.734 198.108 6.740 198.136 6.745 197.859 6.751 198.017 6.757 198.005 6.763 197.965 6.769 197.939 6.774 197.913 6.780 198.666 6.786 199.419 6.792 198.171 6.798 198.694 6.803 194.779 6.809 193.032 6.815 190.201 6.821 191.669 6.827 193.138 6.832 190.729 6.838 189.038 6.844 187.523 6.850 187.779 6.856 184.393 6.861 182.620 6.867 180.041 6.873 179.339 6.879 178.637 6.885 177.935 6.891 177.233 6.896 174.765 6.902 173.180 6.908 172.866 6.914 173.797 6.920 174.191 6.925 174.596 6.931 174.996 6.937 175.395 6.943 175.795 6.949 176.179 6.954 176.474 6.960 176.578 6.966 176.683 6.972 176.787 6.978 176.846 6.983 176.905 6.989 176.915 6.995 176.926 7.001 176.936 7.007 177.103 7.012 177.191 7.018 177.318 7.024 177.416 7.030 177.425 7.036 177.429 7.041 177.307 7.047 177.185 7.053 177.063 7.059 176.989 7.065 177.021 7.070 177.192 7.076 177.426 7.082 177.633 7.088 177.690 7.094 177.655 7.100 177.671 7.105 177.759 7.111 177.844 7.117 177.907 7.123 177.980 7.129 178.311 7.134 178.625 7.140 178.915 7.146 179.051 7.152 179.082 7.158 178.997 7.163 178.760 7.169 178.523 7.175 177.893 7.181 177.460 7.187 177.027 7.192 176.599 7.198 176.497 7.204 176.695 7.210 177.086 7.216 177.380 7.221 177.675 7.227 177.716 7.233 177.711 7.239 177.600 7.245 177.414 7.250 177.229 7.256 177.043 7.262 177.041 7.268 177.138 7.274 177.377 7.279 177.711 7.285 178.108 7.291 178.371 7.297 178.530 7.303 178.610 7.308 178.591 7.314 178.415 7.320 178.437 7.326 178.571 7.332 178.783 7.338 178.957 7.343 178.990 7.349 178.867 7.355 178.743 7.361 178.545 7.367 178.462 7.372 178.402 7.378 178.331 7.384 178.265 7.390 178.137 7.396 178.135 7.401 178.172 7.407 178.195 7.413 178.172 7.419 178.149 7.425 178.000 7.430 177.914 7.436 177.888 7.442 177.882 7.448 177.875 7.454 177.869 7.459 177.863 7.465 177.856 7.471 177.850 7.477 177.749 7.483 177.696 7.488 177.603 7.494 177.511 7.500 177.475 7.506 177.516 7.512 177.557 7.517 177.664 7.523 177.647 7.529 177.540 7.535 177.310 7.541 177.052 7.546 176.865 7.552 176.833 7.558 176.958 7.564 177.196 7.570 177.487 7.576 177.751 7.581 177.931 7.587 178.001 7.593 177.994 7.599 177.987 7.605 178.034 7.610 178.193 7.616 178.416 7.622 178.639 7.628 178.672 7.634 178.648 7.639 178.624 7.645 178.600 7.651 178.599 7.657 178.625 7.663 178.650 7.668 178.611 7.674 178.572 7.680 178.469 7.686 178.308 7.692 178.099 7.697 177.726 7.703 177.310 7.709 176.916 7.715 176.542 7.721 176.205 7.726 175.930 7.732 175.767 7.738 175.743 7.744 175.814 7.750 175.863 7.755 175.913 7.761 175.963 7.767 176.013 7.773 176.256 7.779 176.395 7.784 176.550 7.790 176.696 7.796 176.810 7.802 176.923 7.808 177.036 7.814 177.158 7.819 177.305 7.825 177.565 7.831 177.961 7.837 178.412 7.843 178.863 7.848 179.176 7.854 179.366 7.860 179.555 7.866 179.703 7.872 179.759 7.877 179.713 7.883 179.582 7.889 179.380 7.895 179.136 7.901 178.893 7.906 178.650 7.912 178.497 7.918 178.299 7.924 178.100 7.930 177.902 7.935 177.650 7.941 177.518 7.947 177.385 7.953 177.416 7.959 177.447 7.964 177.581 7.970 177.861 7.976 178.001 7.982 178.149 7.988 178.230 7.993 178.209 7.999 178.099 8.005 177.881 8.011 177.610 8.017 177.383 8.022 177.200 8.028 177.035 8.034 176.904 8.040 176.827 8.046 176.808 8.052 176.809 8.057 176.814 8.063 176.782 8.069 176.751 8.075 176.719 8.081 176.758 8.086 176.796 8.092 176.931 8.098 177.006 8.104 177.052 8.110 177.098 8.115 177.145 8.121 177.191 8.127 177.347 8.133 177.581 8.139 177.814 8.144 178.048 8.150 178.282 8.156 178.516 8.162 177.976 8.168 178.230 8.173 178.239 8.179 178.249 8.185 178.259 8.191 178.269 8.197 178.278 8.202 176.505 8.208 175.790 8.214 174.819 8.220 175.716 8.226 176.441 8.231 176.938 8.237 177.286 8.243 177.628 8.249 177.856 8.255 178.015 8.260 178.137 8.266 178.211 8.272 178.235 8.278 178.241 8.284 178.237 8.290 178.235 8.295 178.257 8.301 178.344 8.307 178.527 8.313 178.771 8.319 179.010 8.324 179.194 8.330 179.327 8.336 179.406 8.342 179.440 8.348 179.458 8.353 179.497 8.359 179.522 8.365 179.480 8.371 179.338 8.377 179.084 8.382 178.735 8.388 178.273 8.394 177.704 8.400 177.118 8.406 176.634 8.411 176.322 8.417 176.194 8.423 176.178 8.429 176.162 8.435 176.145 8.440 176.129 8.446 177.390 8.452 177.800 8.458 178.209 8.464 178.419 8.469 178.109 8.475 177.302 8.481 176.743 8.487 176.185 8.493 175.199 8.499 174.214 8.504 173.229 8.510 173.647 8.516 173.376 8.522 171.679 8.528 167.281 8.533 165.876 8.539 164.605 8.545 164.899 8.551 165.104 8.557 164.876 8.562 160.003 8.568 157.452 8.574 0.000 8.580 0.000 8.586 0.000 8.591 0.000 8.597 0.000 8.603 0.000 8.609 0.000 8.615 0.000 8.620 0.000 8.626 0.000 8.632 0.000 8.638 0.000 8.644 0.000 8.649 0.000 8.655 0.000 8.661 0.000 8.667 0.000 8.673 0.000 8.678 0.000 8.684 0.000 8.690 0.000 8.696 0.000 8.702 0.000 8.707 0.000 8.713 0.000 8.719 0.000 8.725 0.000 8.731 0.000 8.737 0.000 8.742 0.000 8.748 0.000 8.754 0.000 8.760 0.000 8.766 0.000 8.771 0.000 8.777 0.000 8.783 0.000 8.789 0.000 8.795 0.000 8.800 0.000 8.806 0.000 8.812 0.000 8.818 0.000 8.824 0.000 8.829 0.000 8.835 0.000 8.841 0.000 8.847 0.000 8.853 0.000 8.858 0.000 8.864 0.000 8.870 0.000 8.876 0.000 8.882 0.000 8.887 0.000 8.893 0.000 8.899 0.000 8.905 0.000 8.911 0.000 8.916 0.000 8.922 0.000 8.928 0.000 8.934 0.000 8.940 0.000 8.945 0.000 8.951 0.000 8.957 0.000 8.963 0.000 8.969 0.000 8.975 0.000 8.980 0.000 8.986 0.000 8.992 0.000 8.998 0.000 9.004 0.000 9.009 0.000 9.015 0.000 9.021 0.000 9.027 0.000 9.033 0.000 9.038 0.000 9.044 0.000 9.050 0.000 9.056 0.000 9.062 0.000 9.067 0.000 9.073 0.000 9.079 0.000 9.085 0.000 9.091 0.000 9.096 0.000 9.102 0.000 9.108 0.000 9.114 0.000 9.120 0.000 9.125 0.000 9.131 0.000 9.137 0.000 9.143 0.000 9.149 0.000 9.154 0.000 9.160 0.000 9.166 0.000 9.172 0.000 9.178 0.000 9.183 0.000 9.189 0.000 9.195 0.000 9.201 0.000 9.207 0.000 9.213 0.000 9.218 0.000 9.224 0.000 9.230 0.000 9.236 0.000 9.242 0.000 9.247 0.000 9.253 0.000 9.259 0.000 9.265 0.000 9.271 0.000 9.276 0.000 9.282 0.000 9.288 0.000 9.294 0.000 9.300 0.000 9.305 0.000 9.311 0.000 9.317 0.000 9.323 0.000 9.329 0.000 9.334 0.000 9.340 0.000 9.346 0.000 9.352 0.000 9.358 0.000 9.363 0.000 9.369 0.000 9.375 0.000 9.381 0.000 9.387 0.000 9.392 0.000 9.398 0.000 9.404 0.000 9.410 0.000 9.416 0.000 9.421 0.000 9.427 0.000 9.433 0.000 9.439 0.000 9.445 0.000 9.451 0.000 9.456 0.000 9.462 0.000 9.468 0.000 9.474 0.000 9.480 0.000 9.485 0.000 9.491 0.000 9.497 0.000 9.503 0.000 9.509 0.000 9.514 0.000 9.520 0.000 9.526 0.000 9.532 0.000 9.538 0.000 9.543 0.000 9.549 0.000 9.555 0.000 9.561 0.000 9.567 0.000 9.572 0.000 9.578 0.000 9.584 0.000 9.590 0.000 9.596 0.000 9.601 0.000 9.607 0.000 9.613 0.000 9.619 0.000 9.625 0.000 9.630 0.000 9.636 0.000 9.642 0.000 9.648 0.000 9.654 0.000 9.660 0.000 9.665 0.000 9.671 0.000 9.677 0.000 9.683 0.000 9.689 0.000 9.694 0.000 9.700 0.000 9.706 0.000 9.712 0.000 9.718 0.000 9.723 0.000 9.729 0.000 9.735 0.000 9.741 0.000 9.747 0.000 9.752 0.000 9.758 0.000 9.764 0.000 9.770 0.000 9.776 0.000 9.781 0.000 9.787 0.000 9.793 0.000 9.799 0.000 9.805 0.000 9.810 0.000 9.816 0.000 9.822 0.000 9.828 0.000 9.834 0.000 9.839 0.000 9.845 0.000 9.851 0.000 9.857 0.000 9.863 0.000 9.868 0.000 9.874 0.000 9.880 0.000 9.886 0.000 9.892 0.000 9.898 0.000 9.903 0.000 9.909 0.000 9.915 0.000 9.921 0.000 9.927 0.000 9.932 0.000 9.938 0.000 9.944 0.000 9.950 0.000 9.956 0.000 9.961 0.000 9.967 0.000 9.973 0.000 9.979 0.000 9.985 0.000 9.990 0.000 9.996 0.000 10.002 0.000 10.008 0.000 10.014 0.000 10.019 0.000 10.025 0.000 10.031 0.000 10.037 0.000 10.043 0.000 10.048 0.000 10.054 0.000 10.060 0.000 10.066 0.000 10.072 0.000 10.077 0.000 10.083 0.000 10.089 0.000 10.095 0.000 10.101 0.000 10.106 0.000 10.112 0.000 10.118 0.000 10.124 0.000 10.130 0.000 10.136 0.000 10.141 0.000 10.147 0.000 10.153 0.000 10.159 0.000 10.165 0.000 10.170 0.000 10.176 0.000 10.182 0.000 10.188 0.000 10.194 0.000 10.199 0.000 10.205 0.000 10.211 0.000 10.217 0.000 10.223 0.000 10.228 0.000 10.234 0.000 10.240 0.000 10.246 0.000 10.252 0.000 10.257 0.000 10.263 0.000 10.269 0.000 10.275 0.000 10.281 0.000 10.286 0.000 10.292 0.000 10.298 0.000 10.304 0.000 10.310 0.000 10.315 0.000 10.321 0.000 10.327 0.000 10.333 0.000 10.339 0.000 10.344 0.000 10.350 0.000 10.356 0.000 10.362 0.000 10.368 0.000 10.374 0.000 10.379 0.000 10.385 0.000 10.391 0.000 10.397 0.000 10.403 0.000 10.408 0.000 10.414 0.000 10.420 0.000 10.426 0.000 10.432 0.000 10.437 0.000 10.443 0.000 10.449 0.000 10.455 0.000 10.461 0.000 10.466 0.000 10.472 0.000 10.478 0.000 10.484 0.000 10.490 0.000 10.495 0.000 10.501 0.000 10.507 0.000 10.513 0.000 10.519 0.000 10.524 0.000 10.530 0.000 10.536 0.000 10.542 0.000 10.548 0.000 10.553 0.000 10.559 0.000 10.565 0.000 10.571 0.000 10.577 0.000 10.582 0.000 10.588 0.000 10.594 0.000 10.600 0.000 10.606 0.000 10.612 0.000 10.617 0.000 10.623 0.000 10.629 0.000 10.635 0.000 10.641 0.000 10.646 0.000 10.652 0.000 10.658 0.000 10.664 0.000 10.670 0.000 10.675 0.000 10.681 0.000 10.687 0.000 10.693 0.000 10.699 0.000 10.704 0.000 10.710 0.000 10.716 0.000 10.722 0.000 10.728 0.000 10.733 0.000 10.739 0.000 10.745 0.000 10.751 0.000 10.757 0.000 10.762 0.000 10.768 0.000 10.774 0.000 10.780 0.000 10.786 0.000 10.791 0.000 10.797 0.000 10.803 0.000 10.809 0.000 10.815 0.000 10.820 0.000 10.826 0.000 10.832 0.000 10.838 0.000 10.844 0.000 10.850 0.000 10.855 48.258 10.861 96.052 10.867 99.249 10.873 101.286 10.879 101.834 10.884 102.095 10.890 99.554 10.896 99.287 10.902 96.109 10.908 91.917 10.913 90.637 10.919 92.506 10.925 93.655 10.931 94.405 10.937 96.493 10.942 99.474 10.948 101.807 10.954 102.374 10.960 106.010 10.966 108.112 10.971 114.273 10.977 118.528 10.983 118.787 10.989 128.403 10.995 128.985 11.000 136.766 11.006 139.538 11.012 143.366 11.018 146.667 11.024 147.878 11.029 150.134 11.035 151.871 11.041 153.609 11.047 155.332 11.053 156.414 11.059 157.497 11.064 158.645 11.070 159.760 11.076 160.892 11.082 161.419 11.088 161.994 11.093 162.220 11.099 162.446 11.105 162.673 11.111 163.033 11.117 164.009 11.122 165.239 11.128 165.890 11.134 166.830 11.140 167.626 11.146 168.421 11.151 169.217 11.157 170.012 11.163 170.808 11.169 171.320 11.175 171.587 11.180 172.047 11.186 172.626 11.192 173.206 11.198 173.710 11.204 174.185 11.209 174.432 11.215 174.316 11.221 173.980 11.227 173.510 11.233 172.999 11.238 172.456 11.244 171.912 11.250 171.369 11.256 170.950 11.262 170.658 11.267 170.488 11.273 170.399 11.279 170.347 11.285 170.277 11.291 170.216 11.297 170.372 11.302 170.529 11.308 170.792 11.314 171.002 11.320 171.238 11.326 171.475 11.331 171.711 11.337 171.948 11.343 172.185 11.349 172.421 11.355 172.658 11.360 172.894 11.366 173.131 11.372 173.367 11.378 173.604 11.384 174.295 11.389 174.672 11.395 175.012 11.401 175.351 11.407 175.691 11.413 176.030 11.418 176.250 11.424 176.577 11.430 176.904 11.436 177.153 11.442 177.333 11.447 177.417 11.453 177.370 11.459 177.124 11.465 176.625 11.471 175.932 11.476 175.151 11.482 174.421 11.488 173.838 11.494 173.443 11.500 173.047 11.505 172.652 11.511 173.076 11.517 172.940 11.523 172.804 11.529 172.513 11.535 172.221 11.540 171.929 11.546 171.638 11.552 171.721 11.558 171.722 11.564 171.765 11.569 172.253 11.575 172.741 11.581 173.549 11.587 174.110 11.593 174.588 11.598 174.776 11.604 174.693 11.610 174.485 11.616 174.277 11.622 174.069 11.627 174.509 11.633 174.308 11.639 175.208 11.645 175.677 11.651 176.126 11.656 176.474 11.662 176.667 11.668 176.694 11.674 176.557 11.680 176.285 11.685 175.865 11.691 175.431 11.697 175.048 11.703 174.748 11.709 174.538 11.714 174.413 11.720 174.245 11.726 174.099 11.732 173.952 11.738 173.876 11.743 174.882 11.749 174.301 11.755 174.348 11.761 174.395 11.767 174.441 11.773 174.488 11.778 175.170 11.784 175.535 11.790 175.899 11.796 176.217 11.802 176.133 11.807 176.118 11.813 176.000 11.819 175.836 11.825 175.661 11.831 175.486 11.836 175.311 11.842 175.136 11.848 175.509 11.854 175.883 11.860 176.808 11.865 177.734 11.871 179.066 11.877 181.331 11.883 183.596 11.889 186.937 11.894 189.253 11.900 192.081 11.906 193.046 11.912 194.943 11.918 195.842 11.923 196.736 11.929 197.630 11.935 196.539 11.941 195.447 11.947 196.300 11.952 194.155 11.958 194.818 11.964 193.920 11.970 193.023 11.976 192.643 11.981 192.004 11.987 191.365 11.993 191.031 11.999 190.544 12.005 190.570 12.011 190.596 12.016 190.919 12.022 191.092 12.028 191.183 12.034 191.249 12.040 191.327 12.045 191.592 12.051 191.911 12.057 192.323 12.063 192.790 12.069 193.258 12.074 193.726 12.080 194.194 12.086 194.662 12.092 195.129 12.098 195.597 12.103 194.104 12.109 194.860 12.115 194.028 12.121 194.301 12.127 194.387 12.132 194.473 12.138 194.559 12.144 190.752 12.150 191.080 12.156 192.025 12.161 195.439 12.167 196.011 12.173 196.024 12.179 197.112 12.185 197.560 12.190 197.808 12.196 198.056 12.202 198.113 12.208 198.169 12.214 198.226 12.220 198.282 12.225 198.339 12.231 199.524 12.237 199.882 12.243 200.240 12.249 200.598 12.254 200.957 12.260 199.433 12.266 200.240 12.272 198.211 12.278 197.194 12.283 196.178 12.289 195.161 12.295 194.145 12.301 189.266 12.307 186.318 12.312 183.371 12.318 178.619 12.324 176.517 12.330 178.282 12.336 181.411 12.341 189.373 12.347 197.336 12.353 199.140 12.359 199.943 12.365 200.745 12.370 201.548 12.376 200.328 12.382 200.819 12.388 200.890 12.394 199.160 12.399 200.177 12.405 200.086 12.411 199.995 12.417 199.904 12.423 201.811 12.428 202.701 12.434 203.591 12.440 204.481 12.446 205.371 12.452 206.261 12.458 207.151 12.463 208.041 12.469 208.748 12.475 209.288 12.481 209.912 12.487 210.535 12.492 211.159 12.498 211.782 12.504 212.406 12.510 213.029 12.516 213.653 12.521 214.277 12.527 215.014 12.533 220.698 12.539 221.669 12.545 222.640 12.550 221.376 12.556 219.625 12.562 217.874 12.568 216.123 12.574 218.659 12.579 216.085 12.585 216.869 12.591 217.953 12.597 217.999 12.603 0.000 12.608 0.000 12.614 0.000 12.620 0.000 12.626 0.000 12.632 0.000 12.637 0.000 12.643 0.000 12.649 0.000 12.655 0.000 12.661 0.000 12.666 0.000 12.672 0.000 12.678 0.000 12.684 0.000 12.690 0.000 12.696 0.000 12.701 0.000 12.707 0.000 12.713 0.000 12.719 0.000 12.725 0.000 12.730 0.000 12.736 0.000 12.742 0.000 12.748 0.000 12.754 0.000 12.759 0.000 12.765 0.000 12.771 0.000 12.777 0.000 12.783 0.000 12.788 0.000 12.794 0.000 12.800 0.000 12.806 198.281 12.812 199.369 12.817 201.363 12.823 205.390 12.829 205.390 12.835 205.391 12.841 205.391 12.846 203.337 12.852 202.523 12.858 201.090 12.864 199.656 12.870 198.222 12.875 196.789 12.881 196.553 12.887 196.072 12.893 195.590 12.899 195.423 12.904 195.326 12.910 195.422 12.916 195.608 12.922 195.730 12.928 195.738 12.934 195.638 12.939 195.514 12.945 195.391 12.951 195.291 12.957 195.214 12.963 195.191 12.968 195.169 12.974 195.042 12.980 194.967 12.986 194.988 12.992 195.203 12.997 195.508 13.003 195.839 13.009 195.974 13.015 195.957 13.021 195.810 13.026 195.710 13.032 195.676 13.038 195.721 13.044 195.861 13.050 196.028 13.055 196.194 13.061 196.361 13.067 196.349 13.073 196.353 13.079 196.356 13.084 196.360 13.090 196.364 13.096 196.205 13.102 196.299 13.108 196.290 13.113 196.267 13.119 196.251 13.125 196.236 13.131 196.220 13.137 196.078 13.142 195.924 13.148 195.786 13.154 195.797 13.160 195.938 13.166 196.148 13.172 196.372 13.177 196.601 13.183 196.804 13.189 196.965 13.195 197.091 13.201 197.177 13.206 197.229 13.212 197.281 13.218 197.195 13.224 197.052 13.230 196.815 13.235 196.520 13.241 196.184 13.247 195.847 13.253 195.652 13.259 195.492 13.264 195.383 13.270 195.310 13.276 195.335 13.282 195.342 13.288 195.332 13.293 195.215 13.299 195.099 13.305 195.025 13.311 194.980 13.317 194.942 13.322 194.901 13.328 194.861 13.334 194.922 13.340 194.897 13.346 194.894 13.351 195.023 13.357 195.347 13.363 195.800 13.369 196.531 13.375 197.332 13.380 198.132 13.386 198.933 13.392 198.942 13.398 199.346 13.404 199.553 13.410 199.760 13.415 198.733 13.421 199.287 13.427 197.372 13.433 196.371 13.439 195.371 13.444 194.371 13.450 191.437 13.456 187.575 13.462 187.861 13.468 177.184 13.473 174.329 13.479 171.474 13.485 166.775 13.491 162.998 13.497 160.687 13.502 158.608 13.508 157.208 13.514 156.458 13.520 156.312 13.526 156.705 13.531 157.690 13.537 158.675 13.543 160.026 13.549 161.607 13.555 163.215 13.560 164.799 13.566 166.334 13.572 167.802 13.578 168.572 13.584 169.690 13.589 170.635 13.595 171.579 13.601 172.418 13.607 172.779 13.613 173.432 13.619 174.085 13.624 174.738 13.630 176.948 13.636 177.140 13.642 177.346 13.648 177.552 13.653 177.758 13.659 177.132 13.665 176.506 13.671 175.880 13.677 173.594 13.682 172.141 13.688 170.550 13.694 169.143 13.700 171.517 13.706 172.220 13.711 173.758 13.717 171.381 13.723 174.069 13.729 175.324 13.735 176.578 13.740 177.833 13.746 178.323 13.752 178.420 13.758 178.391 13.764 178.380 13.769 178.359 13.775 177.907 13.781 177.670 13.787 177.434 13.793 176.575 13.798 176.027 13.804 175.479 13.810 174.932 13.816 174.136 13.822 173.813 13.827 173.489 13.833 173.569 13.839 173.465 13.845 173.503 13.851 173.971 13.857 174.197 13.862 174.513 13.868 174.937 13.874 175.456 13.880 176.036 13.886 176.615 13.891 177.018 13.897 177.236 13.903 177.281 13.909 177.202 13.915 176.959 13.920 176.583 13.926 176.140 13.932 175.674 13.938 175.085 13.944 174.769 13.949 174.452 13.955 174.197 13.961 174.129 13.967 174.645 13.973 174.773 13.978 175.085 13.984 175.398 13.990 175.710 13.996 176.022 14.002 175.509 14.007 175.723 14.013 175.749 14.019 175.774 14.025 175.800 14.031 174.670 14.036 175.123 14.042 175.190 14.048 175.450 14.054 176.023 14.060 176.450 14.065 176.932 14.071 177.409 14.077 177.903 14.083 178.371 14.089 178.748 14.095 179.002 14.100 179.125 14.106 179.116 14.112 178.961 14.118 178.656 14.124 178.273 14.129 177.704 14.135 176.647 14.141 175.591 14.147 172.823 14.153 170.907 14.158 168.565 14.164 166.436 14.170 165.842 14.176 161.191 14.182 155.398 14.187 151.677 14.193 152.797 14.199 153.917 14.205 158.138 14.211 0.000 14.216 0.000 14.222 0.000 14.228 0.000 14.234 0.000 14.240 0.000 14.245 0.000 14.251 0.000 14.257 0.000 14.263 0.000 14.269 0.000 14.274 0.000 14.280 0.000 14.286 0.000 14.292 0.000 14.298 0.000 14.303 0.000 14.309 0.000 14.315 0.000 14.321 0.000 14.327 0.000 14.333 0.000 14.338 0.000 14.344 0.000 14.350 0.000 14.356 0.000 14.362 0.000 14.367 0.000 14.373 0.000 14.379 0.000 14.385 0.000 14.391 0.000 14.396 0.000 14.402 0.000 14.408 0.000 14.414 0.000 14.420 0.000 14.425 0.000 14.431 0.000 14.437 0.000 14.443 0.000 14.449 0.000 14.454 0.000 14.460 0.000 14.466 0.000 14.472 0.000 14.478 0.000 14.483 0.000 14.489 0.000 14.495 0.000 14.501 0.000 14.507 0.000 14.512 0.000 14.518 0.000 14.524 0.000 14.530 0.000 14.536 0.000 14.541 0.000 14.547 0.000 14.553 0.000 14.559 0.000 14.565 0.000 14.571 0.000 14.576 0.000 14.582 0.000 14.588 0.000 14.594 0.000 14.600 0.000 14.605 0.000 14.611 0.000 14.617 0.000 14.623 0.000 14.629 200.414 14.634 186.445 14.640 184.581 14.646 183.630 14.652 182.221 14.658 181.665 14.663 181.531 14.669 181.878 14.675 182.090 14.681 183.004 14.687 183.919 14.692 184.833 14.698 187.605 14.704 188.069 14.710 189.687 14.716 190.381 14.721 191.075 14.727 191.769 14.733 192.463 14.739 193.266 14.745 194.199 14.750 195.752 14.756 196.360 14.762 197.418 14.768 198.252 14.774 199.027 14.780 199.802 14.785 200.578 14.791 201.353 14.797 202.138 14.803 203.152 14.809 204.051 14.814 204.743 14.820 204.938 14.826 204.724 14.832 203.846 14.838 203.338 14.843 203.340 14.849 203.113 14.855 203.046 14.861 203.106 14.867 203.265 14.872 203.523 14.878 203.864 14.884 204.293 14.890 204.798 14.896 205.304 14.901 205.688 14.907 205.801 14.913 205.870 14.919 205.883 14.925 205.895 14.930 206.006 14.936 206.067 14.942 206.129 14.948 205.931 14.954 205.976 14.959 206.008 14.965 206.047 14.971 206.332 14.977 206.494 14.983 206.718 14.988 206.911 14.994 207.104 15.000 207.155 15.006 207.247 15.012 207.267 15.018 207.168 15.023 207.069 15.029 207.097 15.035 207.110 15.041 207.139 15.047 207.175 15.052 207.211 15.058 207.058 15.064 207.139 15.070 207.094 15.076 207.097 15.081 206.907 15.087 206.810 15.093 206.666 15.099 206.546 15.105 206.436 15.110 206.327 15.116 206.217 15.122 205.860 15.128 205.776 15.134 205.621 15.139 205.501 15.145 205.465 15.151 205.204 15.157 205.055 15.163 204.906 15.168 204.877 15.174 205.155 15.180 205.544 15.186 205.877 15.192 206.210 15.197 206.437 15.203 206.524 15.209 206.009 15.215 205.877 15.221 205.514 15.226 205.266 15.232 205.019 15.238 205.108 15.244 205.198 15.250 205.604 15.256 205.792 15.261 205.981 15.267 206.434 15.273 206.886 15.279 207.339 15.285 207.791 15.290 207.830 15.296 208.076 15.302 208.218 15.308 208.412 15.314 208.358 15.319 208.332 15.325 208.645 15.331 208.886 15.337 209.163 15.343 209.440 15.348 209.717 15.354 207.894 15.360 208.905 15.366 198.403 15.372 194.181 15.377 190.555 15.383 186.631 15.389 182.707 15.395 180.571 15.401 177.541 15.406 174.511 15.412 170.222 15.418 168.229 15.424 165.088 15.430 164.145 15.435 163.201 15.441 161.598 15.447 159.458 15.453 157.150 15.459 155.119 15.464 153.848 15.470 153.118 15.476 153.639 15.482 155.081 15.488 159.169 15.494 161.935 15.499 167.015 15.505 176.001 15.511 181.203 15.517 186.406 15.523 187.568 15.528 189.205 15.534 190.369 15.540 191.020 15.546 190.008 15.552 189.839 15.557 188.438 15.563 187.653 15.569 186.868 15.575 186.932 15.581 187.537 15.586 187.872 15.592 188.341 15.598 188.991 15.604 189.859 15.610 191.034 15.615 192.210 15.621 193.385 15.627 194.792 15.633 196.225 15.639 198.969 15.644 199.905 15.650 201.662 15.656 203.008 15.662 204.681 15.668 205.699 15.673 206.897 15.679 207.949 15.685 208.798 15.691 209.403 15.697 209.817 15.702 209.857 15.708 209.897 15.714 209.934 15.720 209.971 15.726 209.997 15.732 210.120 15.737 210.332 15.743 210.502 15.749 210.505 15.755 210.347 15.761 210.189 15.766 209.960 15.772 209.731 15.778 209.502 15.784 209.731 15.790 209.662 15.795 210.071 15.801 210.270 15.807 210.409 15.813 210.438 15.819 210.271 15.824 210.103 15.830 209.936 15.836 210.087 15.842 210.072 15.848 209.755 15.853 209.437 15.859 209.120 15.865 208.803 15.871 208.485 15.877 208.538 15.882 208.531 15.888 208.410 15.894 208.288 15.900 208.166 15.906 208.119 15.911 208.073 15.917 208.026 15.923 207.979 15.929 207.827 15.935 207.886 15.940 207.896 15.946 207.907 15.952 207.917 15.958 207.898 15.964 207.906 15.970 207.915 15.975 208.134 15.981 208.032 15.987 208.028 15.993 207.960 15.999 207.924 16.004 207.888 16.010 208.066 16.016 208.015 16.022 208.205 16.028 208.190 16.033 208.121 16.039 208.052 16.045 208.031 16.051 208.011 16.057 208.015 16.062 208.056 16.068 208.078 16.074 208.101 16.080 208.123 16.086 208.146 16.091 208.168 16.097 208.234 16.103 208.419 16.109 208.544 16.115 208.699 16.120 208.967 16.126 209.026 16.132 208.873 16.138 208.803 16.144 208.691 16.149 208.787 16.155 208.883 16.161 208.833 16.167 208.693 16.173 208.543 16.179 208.404 16.184 208.266 16.190 207.906 16.196 207.529 16.202 207.042 16.208 206.357 16.213 205.634 16.219 204.848 16.225 203.995 16.231 203.044 16.237 202.021 16.242 200.997 16.248 199.973 16.254 198.984 16.260 198.183 16.266 197.546 16.271 196.995 16.277 196.767 16.283 196.540 16.289 196.313 16.295 196.786 16.300 196.571 16.306 197.300 16.312 197.551 16.318 197.801 16.324 198.052 16.329 198.131 16.335 198.210 16.341 198.289 16.347 198.100 16.353 198.189 16.358 198.367 16.364 198.603 16.370 198.840 16.376 199.076 16.382 199.312 16.387 199.548 16.393 199.784 16.399 200.020 16.405 198.317 16.411 197.987 16.417 197.976 16.422 198.357 16.428 198.737 16.434 198.895 16.440 199.053 16.446 199.170 16.451 198.527 16.457 198.544 16.463 198.726 16.469 198.691 16.475 198.658 16.480 198.624 16.486 196.604 16.492 197.534 16.498 197.582 16.504 197.630 16.509 197.679 16.515 197.727 16.521 197.775 16.527 199.802 16.533 200.364 16.538 200.640 16.544 200.712 16.550 200.593 16.556 200.339 16.562 200.005 16.567 199.711 16.573 199.397 16.579 199.082 16.585 198.488 16.591 198.155 16.596 197.891 16.602 197.716 16.608 197.711 16.614 197.813 16.620 197.915 16.625 198.069 16.631 198.224 16.637 198.378 16.643 198.313 16.649 198.247 16.655 197.920 16.660 197.592 16.666 197.045 16.672 196.650 16.678 196.288 16.684 195.910 16.689 195.539 16.695 195.328 16.701 195.252 16.707 195.396 16.713 195.789 16.718 196.182 16.724 196.783 16.730 197.279 16.736 197.057 16.742 197.041 16.747 197.166 16.753 197.291 16.759 197.416 16.765 197.540 16.771 197.665 16.776 197.790 16.782 198.100 16.788 198.317 16.794 196.595 16.800 191.636 16.805 180.764 16.811 178.034 16.817 178.082 16.823 177.083 16.829 176.085 16.834 175.086 16.840 174.087 16.846 173.089 16.852 172.713 16.858 172.764 16.863 172.867 16.869 173.364 16.875 174.571 16.881 176.476 16.887 178.914 16.893 182.896 16.898 188.972 16.904 192.060 16.910 200.372 16.916 202.485 16.922 205.620 16.927 207.766 16.933 207.921 16.939 208.076 16.945 207.243 16.951 207.385 16.956 207.485 16.962 207.411 16.968 207.308 16.974 207.205 16.980 207.092 16.985 206.918 16.991 206.745 16.997 206.572 17.003 206.399 17.009 206.338 17.014 206.200 17.020 206.101 17.026 206.034 17.032 206.097 17.038 206.378 17.043 206.915 17.049 207.606 17.055 208.297 17.061 208.988 17.067 209.678 17.072 210.369 17.078 211.060 17.084 209.634 17.090 210.282 17.096 212.424 17.101 211.682 17.107 211.485 17.113 211.015 17.119 206.468 17.125 205.999 17.131 169.877 17.136 163.890 17.142 0.000 17.148 0.000 17.154 0.000 17.160 0.000 17.165 0.000 17.171 0.000 17.177 0.000 17.183 0.000 17.189 0.000 17.194 0.000 17.200 0.000 17.206 0.000 17.212 0.000 17.218 0.000 17.223 0.000 17.229 0.000 17.235 0.000 17.241 0.000 17.247 0.000 17.252 0.000 17.258 84.778 17.264 88.737 17.270 87.281 17.276 88.383 17.281 88.751 17.287 89.486 17.293 88.849 17.299 88.212 17.305 83.701 17.310 169.456 17.316 170.694 17.322 173.712 17.328 177.598 17.334 175.619 17.340 174.254 17.345 174.308 17.351 175.287 17.357 176.395 17.363 177.315 17.369 178.235 17.374 178.859 17.380 179.197 17.386 179.390 17.392 179.497 17.398 179.604 17.403 179.913 17.409 180.296 17.415 180.748 17.421 181.295 17.427 182.040 17.432 183.029 17.438 184.935 17.444 186.383 17.450 188.060 17.456 189.737 17.461 191.660 17.467 193.582 17.473 195.505 17.479 196.477 17.485 197.924 17.490 199.134 17.496 200.344 17.502 200.725 17.508 201.520 17.514 201.584 17.519 201.647 17.525 200.732 17.531 199.816 17.537 198.683 17.543 197.658 17.548 196.635 17.554 195.836 17.560 195.370 17.566 195.131 17.572 195.026 17.578 195.111 17.583 195.197 17.589 195.310 17.595 195.452 17.601 195.652 17.607 195.852 17.612 198.013 17.618 197.202 17.624 199.011 17.630 200.820 17.636 202.629 17.641 202.393 17.647 200.053 17.653 198.766 17.659 196.952 17.665 187.585 17.670 185.635 17.676 183.576 17.682 178.838 17.688 174.101 17.694 169.364 17.699 166.273 17.705 161.694 17.711 157.859 17.717 150.579 17.723 146.472 17.728 145.001 17.734 0.000 17.740 0.000 17.746 0.000 17.752 0.000 17.757 0.000 17.763 0.000 17.769 0.000 17.775 0.000 17.781 0.000 17.786 172.187 17.792 172.187 17.798 173.909 17.804 176.012 17.810 177.622 17.816 179.479 17.821 180.121 17.827 181.370 17.833 182.315 17.839 182.048 17.845 181.991 17.850 181.829 17.856 179.902 17.862 178.858 17.868 177.814 17.874 176.769 17.879 177.444 17.885 176.792 17.891 176.139 17.897 176.160 17.903 176.012 17.908 175.865 17.914 175.717 17.920 175.569 17.926 175.288 17.932 175.074 17.937 174.827 17.943 174.596 17.949 174.628 17.955 174.714 17.961 174.832 17.966 174.950 17.972 175.068 17.978 175.187 17.984 175.743 17.990 176.000 17.995 176.197 18.001 176.294 18.007 176.293 18.013 176.254 18.019 176.215 18.024 176.175 18.030 176.414 18.036 176.507 18.042 176.628 18.048 176.666 18.054 176.616 18.059 176.453 18.065 176.196 18.071 175.903 18.077 175.610 18.083 175.317 18.088 175.024 18.094 175.054 18.100 174.959 18.106 174.863 18.112 174.768 18.117 174.672 18.123 174.779 18.129 174.838 18.135 175.102 18.141 175.426 18.146 175.896 18.152 176.444 18.158 176.997 18.164 177.550 18.170 177.642 18.175 177.702 18.181 177.524 18.187 176.960 18.193 176.545 18.199 176.055 18.204 175.603 18.210 175.582 18.216 175.525 18.222 175.617 18.228 176.019 18.233 176.266 18.239 176.503 18.245 176.625 18.251 176.748 18.257 176.711 18.262 176.776 18.268 176.871 18.274 176.966 18.280 176.974 18.286 176.838 18.292 176.610 18.297 176.289 18.303 175.896 18.309 175.466 18.315 175.036 18.321 174.606 18.326 174.514 18.332 174.301 18.338 174.262 18.344 174.278 18.350 174.378 18.355 174.528 18.361 174.685 18.367 174.842 18.373 174.899 18.379 174.957 18.384 174.996 18.390 174.997 18.396 174.965 18.402 174.923 18.408 174.879 18.413 174.791 18.419 174.643 18.425 174.525 18.431 174.493 18.437 174.563 18.442 174.655 18.448 174.736 18.454 174.745 18.460 174.791 18.466 174.837 18.471 174.809 18.477 174.706 18.483 174.533 18.489 174.340 18.495 174.192 18.500 174.198 18.506 174.355 18.512 174.727 18.518 175.220 18.524 175.713 18.530 176.206 18.535 176.254 18.541 176.336 18.547 176.253 18.553 176.123 18.559 175.888 18.564 175.653 18.570 175.529 18.576 175.431 18.582 175.338 18.588 175.283 18.593 175.297 18.599 175.342 18.605 175.363 18.611 175.356 18.617 175.367 18.622 175.416 18.628 175.477 18.634 175.538 18.640 175.598 18.646 175.424 18.651 175.303 18.657 175.231 18.663 175.253 18.669 175.344 18.675 175.451 18.680 175.559 18.686 175.667 18.692 175.775 18.698 175.882 18.704 175.990 18.709 176.098 18.715 175.981 18.721 176.019 18.727 175.793 18.733 175.582 18.739 175.313 18.744 174.971 18.750 174.716 18.756 174.534 18.762 174.453 18.768 174.474 18.773 174.546 18.779 174.618 18.785 174.690 18.791 174.769 18.797 175.016 18.802 175.364 18.808 175.780 18.814 176.197 18.820 176.613 18.826 176.563 18.831 176.343 18.837 176.035 18.843 175.645 18.849 175.255 18.855 174.939 18.860 174.811 18.866 174.895 18.872 175.185 18.878 175.476 18.884 176.012 18.889 176.409 18.895 176.796 18.901 177.177 18.907 177.534 18.913 177.837 18.918 178.066 18.924 178.181 18.930 178.146 18.936 177.986 18.942 177.889 18.947 177.760 18.953 177.647 18.959 177.576 18.965 177.526 18.971 177.477 18.977 177.309 18.982 177.136 18.988 176.933 18.994 176.666 19.000 176.262 19.006 175.987 19.011 175.792 19.017 175.640 19.023 175.530 19.029 175.453 19.035 175.434 19.040 175.414 19.046 175.323 19.052 175.200 19.058 175.125 19.064 175.110 19.069 175.134 19.075 175.159 19.081 175.183 19.087 175.040 19.093 175.025 19.098 175.011 19.104 174.930 19.110 174.849 19.116 174.798 19.122 174.794 19.127 174.791 19.133 174.838 19.139 174.842 19.145 174.887 19.151 175.059 19.156 175.383 19.162 175.783 19.168 176.119 19.174 176.313 19.180 176.377 19.185 176.441 19.191 176.347 19.197 176.384 19.203 176.422 19.209 176.459 19.215 176.556 19.220 176.652 19.226 176.657 19.232 176.662 19.238 176.244 19.244 175.916 19.249 175.588 19.255 175.261 19.261 174.933 19.267 174.605 19.273 174.488 19.278 174.371 19.284 174.341 19.290 174.588 19.296 174.883 19.302 175.178 19.307 175.439 19.313 175.615 19.319 175.834 19.325 176.053 19.331 176.314 19.336 176.596 19.342 176.878 19.348 177.160 19.354 177.418 19.360 177.424 19.365 176.672 19.371 175.920 19.377 171.665 19.383 169.162 19.389 169.098 19.394 169.493 19.400 169.275 19.406 167.595 19.412 164.979 19.418 159.622 19.423 155.636 19.429 152.474 19.435 149.970 19.441 0.000 19.447 0.000 19.453 0.000 19.458 0.000 19.464 0.000 19.470 0.000 19.476 0.000 19.482 0.000 19.487 0.000 19.493 0.000 19.499 0.000 19.505 0.000 19.511 0.000 19.516 0.000 19.522 0.000 19.528 0.000 19.534 0.000 19.540 0.000 19.545 0.000 19.551 0.000 19.557 0.000 19.563 0.000 19.569 0.000 19.574 0.000 19.580 0.000 19.586 0.000 19.592 0.000 19.598 0.000 19.603 0.000 19.609 0.000 19.615 0.000 19.621 0.000 19.627 0.000 19.632 0.000 19.638 0.000 19.644 0.000 19.650 0.000 19.656 0.000 19.661 0.000 19.667 0.000 19.673 0.000 19.679 0.000 19.685 0.000 19.691 0.000 19.696 0.000 19.702 0.000 19.708 0.000 19.714 0.000 19.720 0.000 19.725 0.000 19.731 0.000 19.737 0.000 19.743 0.000 19.749 0.000 19.754 0.000 19.760 0.000 19.766 0.000 19.772 0.000 19.778 0.000 19.783 0.000 19.789 0.000 19.795 0.000 19.801 0.000 19.807 0.000 19.812 0.000 19.818 0.000 19.824 0.000 19.830 0.000 19.836 0.000 19.841 0.000 19.847 0.000 19.853 0.000 19.859 0.000 19.865 0.000 19.870 0.000 19.876 0.000 19.882 0.000 19.888 0.000 19.894 0.000 19.900 0.000 19.905 0.000 19.911 0.000 19.917 0.000 19.923 0.000 19.929 0.000 19.934 0.000 19.940 0.000 19.946 0.000 19.952 0.000 19.958 0.000 19.963 0.000 19.969 0.000 19.975 0.000 19.981 0.000 19.987 0.000 19.992 0.000 19.998 0.000 20.004 0.000 20.010 0.000 mir_eval-0.8.2/tests/data/melody/reward00.txt000066400000000000000000001207541475740344600210770ustar00rootroot000000000000000.0 0.0 0.006 0.0 0.012 0.0 0.017 0.0 0.023 0.0 0.029 0.0 0.035 0.0 0.041 0.0 0.046 0.0 0.052 0.0 0.058 0.0 0.064 0.0 0.07 0.0 0.075 0.0 0.081 0.0 0.087 0.0 0.093 0.0 0.099 0.0 0.104 0.0 0.11 0.0 0.116 0.0 0.122 0.0 0.128 0.0 0.134 0.0 0.139 0.0 0.145 0.0 0.151 0.0 0.157 0.0 0.163 0.0 0.168 0.0 0.174 0.0 0.18 0.0 0.186 0.0 0.192 0.0 0.197 0.0 0.203 0.0 0.209 0.0 0.215 0.0 0.221 0.0 0.226 0.0 0.232 0.0 0.238 0.0 0.244 0.0 0.25 0.0 0.255 0.0 0.261 0.0 0.267 0.0 0.273 0.0 0.279 0.0 0.284 0.0 0.29 0.0 0.296 0.0 0.302 0.0 0.308 0.0 0.313 0.0 0.319 0.0 0.325 0.0 0.331 0.0 0.337 0.0 0.342 0.0 0.348 0.0 0.354 0.0 0.36 0.0 0.366 0.0 0.372 0.0 0.377 0.0 0.383 0.0 0.389 0.0 0.395 0.0 0.401 0.0 0.406 0.0 0.412 0.0 0.418 0.0 0.424 0.0 0.43 0.0 0.435 0.0 0.441 0.0 0.447 0.0 0.453 0.0 0.459 0.0 0.464 0.0 0.47 0.0 0.476 0.0 0.482 0.0 0.488 0.0 0.493 0.0 0.499 0.0 0.505 0.0 0.511 0.0 0.517 0.0 0.522 0.0 0.528 0.0 0.534 0.0 0.54 0.0 0.546 0.0 0.551 0.0 0.557 0.0 0.563 0.0 0.569 0.0 0.575 0.0 0.58 0.0 0.586 0.0 0.592 0.0 0.598 0.0 0.604 0.0 0.61 0.0 0.615 0.0 0.621 0.0 0.627 0.0 0.633 0.0 0.639 0.0 0.644 0.0 0.65 0.0 0.656 0.0 0.662 0.0 0.668 0.0 0.673 0.0 0.679 0.0 0.685 0.0 0.691 0.0 0.697 0.0 0.702 0.0 0.708 0.0 0.714 0.0 0.72 0.0 0.726 0.0 0.731 0.0 0.737 0.0 0.743 0.0 0.749 0.0 0.755 0.0 0.76 0.0 0.766 0.0 0.772 0.0 0.778 0.0 0.784 0.0 0.789 0.0 0.795 0.0 0.801 0.0 0.807 0.0 0.813 0.0 0.819 0.0 0.824 0.0 0.83 0.0 0.836 0.0 0.842 0.0 0.848 0.0 0.853 0.0 0.859 0.0 0.865 0.0 0.871 0.0 0.877 0.0 0.882 0.0 0.888 0.0 0.894 0.0 0.9 0.0 0.906 0.0 0.911 0.0 0.917 0.0 0.923 0.0 0.929 0.0 0.935 0.0 0.94 0.0 0.946 0.0 0.952 0.0 0.958 0.0 0.964 0.0 0.969 0.0 0.975 0.0 0.981 0.0 0.987 0.0 0.993 0.0 0.998 0.0 1.004 0.0 1.01 0.0 1.016 0.0 1.022 0.0 1.027 0.0 1.033 0.0 1.039 0.0 1.045 0.0 1.051 0.0 1.057 0.0 1.062 0.0 1.068 0.0 1.074 0.0 1.08 0.0 1.086 0.0 1.091 0.0 1.097 0.0 1.103 0.0 1.109 0.0 1.115 0.0 1.12 0.0 1.126 0.0 1.132 0.0 1.138 0.0 1.144 0.0 1.149 0.0 1.155 0.0 1.161 0.0 1.167 0.0 1.173 0.0 1.178 0.0 1.184 0.0 1.19 0.0 1.196 0.0 1.202 0.0 1.207 0.0 1.213 0.0 1.219 0.0 1.225 0.0 1.231 0.0 1.236 0.0 1.242 0.0 1.248 0.0 1.254 0.0 1.26 0.0 1.265 0.0 1.271 0.0 1.277 0.0 1.283 0.0 1.289 0.0 1.295 1.0 1.3 0.3 1.306 0.9 1.312 0.3 1.318 0.7 1.324 0.2 1.329 0.6 1.335 0.1 1.341 1.0 1.347 0.8 1.353 0.4 1.358 0.6 1.364 0.8 1.37 0.1 1.376 1.0 1.382 0.1 1.387 0.7 1.393 0.5 1.399 0.2 1.405 0.5 1.411 0.3 1.416 0.2 1.422 0.5 1.428 0.5 1.434 0.5 1.44 0.5 1.445 0.7 1.451 0.1 1.457 0.6 1.463 0.4 1.469 1.0 1.474 0.3 1.48 0.9 1.486 1.0 1.492 0.1 1.498 1.0 1.503 1.0 1.509 0.4 1.515 0.4 1.521 0.8 1.527 0.8 1.533 0.8 1.538 0.2 1.544 1.0 1.55 0.6 1.556 0.2 1.562 0.4 1.567 0.1 1.573 0.8 1.579 0.6 1.585 0.8 1.591 0.9 1.596 0.5 1.602 0.6 1.608 0.9 1.614 0.7 1.62 0.3 1.625 0.4 1.631 0.9 1.637 0.4 1.643 0.4 1.649 0.5 1.654 0.3 1.66 0.2 1.666 0.1 1.672 0.7 1.678 0.9 1.683 0.2 1.689 0.6 1.695 0.1 1.701 0.4 1.707 1.0 1.712 0.9 1.718 0.3 1.724 0.5 1.73 0.8 1.736 0.1 1.741 0.9 1.747 0.6 1.753 0.8 1.759 0.7 1.765 1.0 1.771 0.3 1.776 0.2 1.782 0.3 1.788 0.3 1.794 0.2 1.8 0.2 1.805 0.2 1.811 0.6 1.817 0.9 1.823 0.7 1.829 0.7 1.834 0.4 1.84 1.0 1.846 0.5 1.852 0.9 1.858 0.3 1.863 0.1 1.869 0.2 1.875 0.9 1.881 1.0 1.887 0.8 1.892 1.0 1.898 1.0 1.904 0.2 1.91 0.8 1.916 0.7 1.921 0.1 1.927 0.6 1.933 0.3 1.939 0.7 1.945 0.7 1.95 0.9 1.956 0.8 1.962 0.8 1.968 0.8 1.974 0.9 1.98 0.5 1.985 0.6 1.991 0.3 1.997 0.4 2.003 0.4 2.009 0.1 2.014 0.3 2.02 0.5 2.026 0.1 2.032 0.5 2.038 0.3 2.043 0.4 2.049 0.9 2.055 0.9 2.061 0.8 2.067 0.9 2.072 0.8 2.078 0.4 2.084 0.1 2.09 0.2 2.096 0.5 2.101 0.8 2.107 0.1 2.113 0.4 2.119 0.5 2.125 0.7 2.13 0.3 2.136 0.3 2.142 0.1 2.148 0.9 2.154 0.4 2.159 0.3 2.165 0.4 2.171 0.9 2.177 1.0 2.183 0.9 2.188 0.7 2.194 0.3 2.2 0.8 2.206 0.5 2.212 0.9 2.218 0.6 2.223 0.7 2.229 1.0 2.235 0.1 2.241 0.4 2.247 0.3 2.252 0.8 2.258 0.4 2.264 0.2 2.27 0.8 2.276 1.0 2.281 1.0 2.287 0.3 2.293 0.5 2.299 0.3 2.305 0.2 2.31 0.5 2.316 0.4 2.322 0.3 2.328 0.9 2.334 0.3 2.339 0.8 2.345 0.2 2.351 0.5 2.357 0.1 2.363 0.4 2.368 0.1 2.374 0.8 2.38 0.1 2.386 0.9 2.392 0.9 2.397 0.7 2.403 0.8 2.409 1.0 2.415 1.0 2.421 1.0 2.426 0.8 2.432 0.5 2.438 0.8 2.444 0.1 2.45 0.6 2.456 0.5 2.461 0.2 2.467 0.4 2.473 0.1 2.479 0.1 2.485 1.0 2.49 0.3 2.496 0.2 2.502 0.3 2.508 0.4 2.514 0.2 2.519 0.2 2.525 0.4 2.531 0.9 2.537 0.7 2.543 0.6 2.548 0.1 2.554 0.5 2.56 0.4 2.566 0.5 2.572 0.6 2.577 0.5 2.583 0.8 2.589 0.2 2.595 0.1 2.601 0.1 2.606 0.5 2.612 0.7 2.618 0.9 2.624 0.1 2.63 1.0 2.635 0.8 2.641 0.3 2.647 0.7 2.653 0.9 2.659 0.3 2.664 0.8 2.67 0.2 2.676 0.5 2.682 0.2 2.688 1.0 2.694 0.6 2.699 0.7 2.705 0.4 2.711 0.4 2.717 1.0 2.723 0.3 2.728 0.6 2.734 0.7 2.74 0.9 2.746 1.0 2.752 1.0 2.757 0.9 2.763 0.4 2.769 0.7 2.775 0.3 2.781 0.3 2.786 0.6 2.792 0.5 2.798 1.0 2.804 1.0 2.81 0.5 2.815 0.7 2.821 0.7 2.827 0.6 2.833 0.3 2.839 0.7 2.844 0.5 2.85 0.4 2.856 0.6 2.862 0.5 2.868 0.5 2.873 0.1 2.879 0.9 2.885 0.2 2.891 0.2 2.897 0.2 2.902 0.2 2.908 0.6 2.914 0.3 2.92 0.3 2.926 0.7 2.932 0.2 2.937 0.7 2.943 0.9 2.949 0.9 2.955 0.7 2.961 0.2 2.966 0.7 2.972 0.9 2.978 0.8 2.984 0.7 2.99 0.7 2.995 0.7 3.001 0.3 3.007 0.1 3.013 0.7 3.019 0.6 3.024 0.5 3.03 0.5 3.036 0.1 3.042 0.9 3.048 0.9 3.053 0.9 3.059 0.6 3.065 0.9 3.071 0.3 3.077 0.4 3.082 0.6 3.088 0.9 3.094 0.8 3.1 1.0 3.106 0.7 3.111 0.6 3.117 0.5 3.123 0.1 3.129 0.6 3.135 0.4 3.14 0.4 3.146 0.9 3.152 1.0 3.158 0.9 3.164 0.8 3.17 0.4 3.175 0.3 3.181 0.8 3.187 0.9 3.193 0.6 3.199 0.4 3.204 0.7 3.21 0.7 3.216 1.0 3.222 0.7 3.228 0.4 3.233 1.0 3.239 0.8 3.245 0.2 3.251 1.0 3.257 0.4 3.262 0.5 3.268 0.1 3.274 0.4 3.28 0.6 3.286 0.9 3.291 0.1 3.297 0.1 3.303 0.3 3.309 0.5 3.315 1.0 3.32 0.7 3.326 0.2 3.332 1.0 3.338 0.3 3.344 0.9 3.349 0.1 3.355 0.9 3.361 0.8 3.367 0.6 3.373 0.7 3.379 0.3 3.384 0.9 3.39 0.7 3.396 0.3 3.402 0.5 3.408 0.1 3.413 0.9 3.419 0.9 3.425 0.6 3.431 1.0 3.437 0.5 3.442 0.7 3.448 0.1 3.454 0.5 3.46 0.3 3.466 0.3 3.471 0.7 3.477 0.1 3.483 0.6 3.489 0.6 3.495 0.1 3.5 0.6 3.506 0.7 3.512 0.1 3.518 0.1 3.524 0.9 3.529 0.6 3.535 0.5 3.541 0.9 3.547 1.0 3.553 0.6 3.558 0.3 3.564 0.6 3.57 0.6 3.576 0.4 3.582 1.0 3.587 0.5 3.593 0.6 3.599 0.7 3.605 0.8 3.611 0.4 3.617 0.6 3.622 0.1 3.628 0.8 3.634 0.3 3.64 1.0 3.646 0.3 3.651 0.7 3.657 0.1 3.663 0.8 3.669 0.5 3.675 0.6 3.68 0.3 3.686 0.6 3.692 0.3 3.698 0.5 3.704 1.0 3.709 0.2 3.715 0.5 3.721 0.1 3.727 0.1 3.733 0.3 3.738 1.0 3.744 0.3 3.75 0.5 3.756 0.3 3.762 0.9 3.767 0.2 3.773 0.3 3.779 0.2 3.785 0.5 3.791 0.3 3.796 0.5 3.802 1.0 3.808 0.8 3.814 0.2 3.82 0.2 3.825 0.2 3.831 0.7 3.837 0.1 3.843 1.0 3.849 1.0 3.855 1.0 3.86 0.8 3.866 0.9 3.872 1.0 3.878 0.4 3.884 0.3 3.889 0.7 3.895 0.8 3.901 0.4 3.907 0.3 3.913 1.0 3.918 0.6 3.924 0.4 3.93 0.9 3.936 0.4 3.942 0.3 3.947 0.7 3.953 1.0 3.959 0.5 3.965 1.0 3.971 0.4 3.976 0.9 3.982 0.1 3.988 0.2 3.994 0.2 4.0 0.8 4.005 0.8 4.011 0.3 4.017 0.6 4.023 0.1 4.029 0.1 4.034 0.4 4.04 0.7 4.046 0.9 4.052 0.5 4.058 0.2 4.063 0.1 4.069 0.9 4.075 0.1 4.081 0.7 4.087 0.3 4.093 1.0 4.098 0.5 4.104 0.4 4.11 1.0 4.116 0.8 4.122 0.7 4.127 0.2 4.133 0.9 4.139 0.7 4.145 0.5 4.151 0.8 4.156 0.2 4.162 1.0 4.168 0.3 4.174 0.1 4.18 0.8 4.185 0.9 4.191 1.0 4.197 0.6 4.203 0.9 4.209 0.6 4.214 0.1 4.22 0.8 4.226 0.5 4.232 0.6 4.238 0.7 4.243 0.6 4.249 0.8 4.255 1.0 4.261 0.9 4.267 0.2 4.272 0.5 4.278 0.3 4.284 0.7 4.29 0.1 4.296 0.3 4.301 0.1 4.307 0.7 4.313 0.6 4.319 0.6 4.325 1.0 4.331 0.1 4.336 0.5 4.342 0.8 4.348 1.0 4.354 1.0 4.36 0.9 4.365 0.7 4.371 0.5 4.377 1.0 4.383 0.5 4.389 1.0 4.394 0.7 4.4 1.0 4.406 0.6 4.412 0.7 4.418 0.6 4.423 0.6 4.429 0.8 4.435 0.7 4.441 0.9 4.447 0.6 4.452 0.5 4.458 0.4 4.464 0.9 4.47 0.6 4.476 0.6 4.481 0.9 4.487 0.5 4.493 0.5 4.499 1.0 4.505 0.6 4.51 0.0 4.516 0.0 4.522 0.0 4.528 0.0 4.534 0.0 4.54 0.0 4.545 0.0 4.551 0.0 4.557 0.0 4.563 0.0 4.569 0.0 4.574 0.0 4.58 0.0 4.586 0.0 4.592 0.0 4.598 0.0 4.603 0.0 4.609 0.0 4.615 0.0 4.621 0.0 4.627 0.0 4.632 0.0 4.638 0.0 4.644 0.0 4.65 0.0 4.656 0.0 4.661 0.0 4.667 0.0 4.673 0.0 4.679 0.0 4.685 0.0 4.69 0.0 4.696 0.0 4.702 0.0 4.708 0.0 4.714 0.0 4.719 0.0 4.725 0.0 4.731 0.0 4.737 0.0 4.743 0.0 4.748 0.0 4.754 0.0 4.76 0.0 4.766 0.0 4.772 0.0 4.778 0.0 4.783 0.0 4.789 0.0 4.795 0.0 4.801 0.0 4.807 0.0 4.812 0.0 4.818 0.0 4.824 0.0 4.83 0.0 4.836 0.0 4.841 0.0 4.847 0.0 4.853 0.0 4.859 0.0 4.865 0.0 4.87 0.0 4.876 0.0 4.882 0.0 4.888 0.0 4.894 0.0 4.899 0.0 4.905 0.0 4.911 0.0 4.917 0.0 4.923 0.0 4.928 0.0 4.934 0.0 4.94 0.0 4.946 0.0 4.952 0.0 4.957 0.0 4.963 0.0 4.969 0.0 4.975 0.0 4.981 0.0 4.986 0.0 4.992 0.0 4.998 0.0 5.004 0.0 5.01 0.0 5.016 0.0 5.021 0.0 5.027 0.0 5.033 0.0 5.039 0.0 5.045 0.0 5.05 0.0 5.056 0.0 5.062 0.0 5.068 0.0 5.074 0.0 5.079 0.0 5.085 0.0 5.091 0.0 5.097 0.0 5.103 0.0 5.108 0.0 5.114 0.0 5.12 0.0 5.126 0.0 5.132 0.0 5.137 0.0 5.143 0.0 5.149 0.0 5.155 0.0 5.161 0.0 5.166 0.0 5.172 0.0 5.178 0.0 5.184 0.0 5.19 0.0 5.195 0.0 5.201 0.0 5.207 0.0 5.213 0.0 5.219 0.0 5.224 0.0 5.23 0.0 5.236 0.0 5.242 0.0 5.248 0.0 5.254 0.0 5.259 0.0 5.265 0.0 5.271 0.0 5.277 0.0 5.283 0.0 5.288 0.0 5.294 0.0 5.3 0.0 5.306 0.0 5.312 0.0 5.317 0.0 5.323 0.0 5.329 0.0 5.335 0.0 5.341 0.0 5.346 0.0 5.352 0.0 5.358 0.0 5.364 0.0 5.37 0.0 5.375 0.0 5.381 0.1 5.387 0.9 5.393 0.6 5.399 0.1 5.404 0.2 5.41 0.5 5.416 0.4 5.422 0.2 5.428 0.3 5.433 0.6 5.439 0.5 5.445 0.1 5.451 0.1 5.457 0.5 5.462 0.3 5.468 0.9 5.474 0.2 5.48 0.6 5.486 0.8 5.492 0.2 5.497 0.4 5.503 0.2 5.509 0.8 5.515 0.4 5.521 0.6 5.526 0.6 5.532 0.2 5.538 0.4 5.544 0.6 5.55 0.8 5.555 0.5 5.561 0.6 5.567 1.0 5.573 0.6 5.579 0.8 5.584 0.5 5.59 0.6 5.596 0.5 5.602 0.8 5.608 0.5 5.613 0.4 5.619 0.9 5.625 0.6 5.631 1.0 5.637 0.4 5.642 0.7 5.648 0.7 5.654 0.2 5.66 1.0 5.666 0.1 5.671 0.8 5.677 1.0 5.683 0.2 5.689 0.8 5.695 0.5 5.7 0.6 5.706 0.2 5.712 0.8 5.718 0.2 5.724 0.1 5.73 0.8 5.735 0.4 5.741 0.4 5.747 0.9 5.753 0.4 5.759 0.1 5.764 1.0 5.77 1.0 5.776 0.9 5.782 0.3 5.788 0.3 5.793 0.4 5.799 0.4 5.805 0.7 5.811 0.6 5.817 0.9 5.822 0.8 5.828 0.2 5.834 0.6 5.84 1.0 5.846 0.7 5.851 1.0 5.857 1.0 5.863 1.0 5.869 0.7 5.875 0.9 5.88 0.9 5.886 0.7 5.892 0.2 5.898 0.2 5.904 0.1 5.909 0.8 5.915 0.4 5.921 0.2 5.927 0.9 5.933 0.7 5.939 0.1 5.944 0.7 5.95 0.2 5.956 1.0 5.962 0.1 5.968 0.2 5.973 0.3 5.979 0.4 5.985 0.3 5.991 0.6 5.997 0.5 6.002 0.1 6.008 0.6 6.014 0.5 6.02 0.9 6.026 0.3 6.031 0.1 6.037 0.1 6.043 0.7 6.049 0.1 6.055 1.0 6.06 0.1 6.066 0.2 6.072 0.5 6.078 0.7 6.084 0.2 6.089 0.7 6.095 0.6 6.101 1.0 6.107 0.9 6.113 0.1 6.118 0.5 6.124 1.0 6.13 0.3 6.136 1.0 6.142 0.1 6.147 0.7 6.153 0.7 6.159 0.1 6.165 0.9 6.171 0.6 6.177 0.4 6.182 0.5 6.188 0.5 6.194 0.1 6.2 0.7 6.206 0.3 6.211 0.1 6.217 0.5 6.223 0.5 6.229 0.8 6.235 0.7 6.24 0.3 6.246 0.5 6.252 0.2 6.258 0.4 6.264 0.2 6.269 1.0 6.275 0.9 6.281 0.5 6.287 0.6 6.293 0.6 6.298 0.5 6.304 0.4 6.31 0.4 6.316 0.3 6.322 0.9 6.327 0.2 6.333 0.8 6.339 0.1 6.345 1.0 6.351 0.5 6.356 0.8 6.362 0.1 6.368 0.2 6.374 0.5 6.38 0.6 6.385 0.4 6.391 0.6 6.397 0.9 6.403 0.9 6.409 0.7 6.415 0.2 6.42 0.7 6.426 0.5 6.432 0.5 6.438 0.6 6.444 0.9 6.449 0.3 6.455 0.8 6.461 0.1 6.467 0.1 6.473 0.9 6.478 0.4 6.484 0.2 6.49 0.4 6.496 0.3 6.502 0.2 6.507 0.7 6.513 0.7 6.519 0.9 6.525 0.7 6.531 0.5 6.536 0.9 6.542 0.1 6.548 0.5 6.554 0.6 6.56 0.7 6.565 0.5 6.571 0.8 6.577 0.7 6.583 1.0 6.589 0.5 6.594 0.3 6.6 0.9 6.606 0.4 6.612 0.7 6.618 0.3 6.623 0.1 6.629 0.3 6.635 0.8 6.641 0.8 6.647 0.7 6.653 1.0 6.658 0.6 6.664 0.9 6.67 0.6 6.676 0.9 6.682 0.4 6.687 0.7 6.693 0.6 6.699 0.3 6.705 0.3 6.711 0.2 6.716 1.0 6.722 0.3 6.728 0.8 6.734 0.4 6.74 0.5 6.745 0.7 6.751 0.3 6.757 0.2 6.763 0.2 6.769 0.5 6.774 0.4 6.78 0.9 6.786 0.6 6.792 0.6 6.798 0.5 6.803 0.6 6.809 0.1 6.815 0.3 6.821 0.5 6.827 0.8 6.832 0.1 6.838 0.6 6.844 0.5 6.85 1.0 6.856 1.0 6.861 0.1 6.867 0.4 6.873 0.5 6.879 0.5 6.885 0.2 6.891 0.9 6.896 1.0 6.902 0.4 6.908 0.3 6.914 0.9 6.92 0.8 6.925 0.4 6.931 0.7 6.937 0.1 6.943 0.9 6.949 0.6 6.954 0.6 6.96 0.3 6.966 0.1 6.972 1.0 6.978 0.2 6.983 0.4 6.989 0.2 6.995 0.2 7.001 0.2 7.007 1.0 7.012 0.9 7.018 1.0 7.024 0.8 7.03 1.0 7.036 0.5 7.041 0.3 7.047 0.3 7.053 0.5 7.059 0.5 7.065 0.6 7.07 0.9 7.076 0.5 7.082 0.7 7.088 0.5 7.094 0.7 7.1 1.0 7.105 0.3 7.111 0.6 7.117 0.6 7.123 0.8 7.129 0.6 7.134 0.2 7.14 0.8 7.146 1.0 7.152 0.8 7.158 0.9 7.163 0.9 7.169 0.6 7.175 0.3 7.181 0.8 7.187 0.8 7.192 0.8 7.198 1.0 7.204 0.1 7.21 0.5 7.216 0.7 7.221 0.3 7.227 0.1 7.233 1.0 7.239 1.0 7.245 0.4 7.25 0.6 7.256 0.1 7.262 1.0 7.268 0.1 7.274 0.3 7.279 0.9 7.285 0.4 7.291 0.5 7.297 0.9 7.303 0.2 7.308 0.1 7.314 0.5 7.32 0.8 7.326 0.3 7.332 0.1 7.338 1.0 7.343 0.1 7.349 1.0 7.355 0.7 7.361 0.7 7.367 0.3 7.372 0.8 7.378 0.2 7.384 0.6 7.39 0.9 7.396 0.2 7.401 0.5 7.407 0.8 7.413 0.4 7.419 0.1 7.425 0.2 7.43 0.6 7.436 0.3 7.442 0.1 7.448 0.2 7.454 0.8 7.459 0.5 7.465 1.0 7.471 0.1 7.477 0.2 7.483 0.4 7.488 0.4 7.494 0.5 7.5 0.4 7.506 0.5 7.512 0.7 7.517 0.9 7.523 0.2 7.529 1.0 7.535 0.8 7.541 0.8 7.546 0.8 7.552 0.8 7.558 0.5 7.564 0.9 7.57 0.4 7.576 0.5 7.581 0.2 7.587 0.4 7.593 1.0 7.599 0.1 7.605 0.1 7.61 0.6 7.616 0.9 7.622 0.5 7.628 0.5 7.634 0.8 7.639 0.6 7.645 0.2 7.651 0.4 7.657 0.3 7.663 0.4 7.668 0.3 7.674 1.0 7.68 0.9 7.686 0.3 7.692 0.4 7.697 1.0 7.703 0.1 7.709 0.7 7.715 0.9 7.721 1.0 7.726 0.7 7.732 0.2 7.738 0.6 7.744 0.8 7.75 0.6 7.755 1.0 7.761 0.1 7.767 1.0 7.773 0.3 7.779 0.9 7.784 0.4 7.79 0.8 7.796 0.6 7.802 0.8 7.808 0.7 7.814 0.3 7.819 0.7 7.825 1.0 7.831 0.8 7.837 0.8 7.843 0.1 7.848 0.3 7.854 0.8 7.86 0.7 7.866 0.4 7.872 0.1 7.877 0.8 7.883 0.5 7.889 0.3 7.895 0.5 7.901 0.1 7.906 0.4 7.912 0.5 7.918 0.5 7.924 0.2 7.93 0.5 7.935 0.1 7.941 1.0 7.947 0.6 7.953 0.5 7.959 0.4 7.964 0.2 7.97 0.9 7.976 0.2 7.982 0.9 7.988 0.6 7.993 0.4 7.999 0.3 8.005 0.7 8.011 0.7 8.017 0.8 8.022 0.3 8.028 0.3 8.034 0.2 8.04 0.8 8.046 0.7 8.052 0.9 8.057 0.5 8.063 0.7 8.069 0.3 8.075 0.7 8.081 0.6 8.086 0.3 8.092 0.4 8.098 0.7 8.104 0.8 8.11 0.8 8.115 0.6 8.121 0.3 8.127 0.7 8.133 0.7 8.139 0.5 8.144 0.4 8.15 0.4 8.156 0.2 8.162 0.9 8.168 0.4 8.173 0.2 8.179 0.9 8.185 0.7 8.191 0.1 8.197 0.6 8.202 1.0 8.208 0.3 8.214 0.9 8.22 0.4 8.226 0.9 8.231 0.6 8.237 0.3 8.243 0.1 8.249 0.7 8.255 0.7 8.26 0.4 8.266 0.8 8.272 0.7 8.278 0.3 8.284 0.5 8.29 0.9 8.295 0.9 8.301 0.5 8.307 0.1 8.313 0.9 8.319 0.3 8.324 0.9 8.33 0.8 8.336 0.1 8.342 1.0 8.348 0.8 8.353 0.6 8.359 0.8 8.365 0.2 8.371 0.8 8.377 0.6 8.382 0.6 8.388 0.2 8.394 0.8 8.4 0.1 8.406 0.9 8.411 0.4 8.417 0.2 8.423 1.0 8.429 0.6 8.435 0.8 8.44 0.8 8.446 0.4 8.452 0.4 8.458 0.1 8.464 0.6 8.469 0.9 8.475 0.7 8.481 0.5 8.487 0.2 8.493 0.7 8.499 0.1 8.504 0.8 8.51 0.8 8.516 0.2 8.522 0.3 8.528 0.4 8.533 0.8 8.539 0.9 8.545 0.8 8.551 0.5 8.557 0.2 8.562 0.3 8.568 0.7 8.574 0.4 8.58 0.6 8.586 0.9 8.591 0.1 8.597 0.8 8.603 0.0 8.609 0.0 8.615 0.0 8.62 0.0 8.626 0.0 8.632 0.0 8.638 0.8 8.644 0.6 8.649 0.6 8.655 0.2 8.661 0.2 8.667 0.2 8.673 0.5 8.678 0.3 8.684 0.1 8.69 0.1 8.696 1.0 8.702 0.3 8.707 0.7 8.713 0.3 8.719 0.1 8.725 0.1 8.731 0.1 8.737 0.9 8.742 0.3 8.748 0.6 8.754 0.5 8.76 0.4 8.766 0.4 8.771 0.1 8.777 0.5 8.783 0.6 8.789 0.4 8.795 0.4 8.8 1.0 8.806 0.5 8.812 0.7 8.818 0.7 8.824 0.8 8.829 0.8 8.835 0.6 8.841 0.2 8.847 0.6 8.853 0.6 8.858 0.8 8.864 0.6 8.87 0.3 8.876 0.7 8.882 0.8 8.887 0.4 8.893 0.3 8.899 0.1 8.905 0.7 8.911 0.2 8.916 0.3 8.922 0.1 8.928 0.1 8.934 0.4 8.94 0.1 8.945 0.1 8.951 0.2 8.957 0.7 8.963 0.3 8.969 1.0 8.975 0.2 8.98 0.7 8.986 0.9 8.992 0.8 8.998 0.6 9.004 0.9 9.009 0.5 9.015 0.5 9.021 0.2 9.027 0.8 9.033 0.1 9.038 1.0 9.044 0.3 9.05 0.2 9.056 0.8 9.062 0.6 9.067 0.1 9.073 0.8 9.079 0.5 9.085 0.3 9.091 0.2 9.096 0.5 9.102 0.4 9.108 0.9 9.114 1.0 9.12 0.6 9.125 0.2 9.131 0.7 9.137 0.1 9.143 0.2 9.149 0.8 9.154 0.8 9.16 0.7 9.166 0.4 9.172 0.2 9.178 0.9 9.183 0.7 9.189 0.9 9.195 0.8 9.201 0.9 9.207 1.0 9.213 0.2 9.218 0.1 9.224 0.8 9.23 0.4 9.236 0.2 9.242 0.1 9.247 0.3 9.253 0.5 9.259 0.8 9.265 1.0 9.271 0.4 9.276 0.2 9.282 1.0 9.288 0.7 9.294 0.5 9.3 0.9 9.305 0.1 9.311 0.5 9.317 0.3 9.323 0.8 9.329 0.8 9.334 0.7 9.34 0.8 9.346 0.6 9.352 0.7 9.358 0.3 9.363 0.3 9.369 0.4 9.375 0.1 9.381 0.7 9.387 1.0 9.392 0.9 9.398 0.5 9.404 0.1 9.41 0.1 9.416 0.5 9.421 0.9 9.427 0.6 9.433 1.0 9.439 0.1 9.445 0.4 9.451 0.7 9.456 0.3 9.462 0.5 9.468 0.9 9.474 1.0 9.48 0.7 9.485 0.7 9.491 0.4 9.497 0.1 9.503 0.9 9.509 0.4 9.514 0.6 9.52 0.6 9.526 0.7 9.532 0.1 9.538 0.9 9.543 0.6 9.549 0.5 9.555 0.4 9.561 0.1 9.567 0.6 9.572 0.2 9.578 0.3 9.584 0.8 9.59 0.1 9.596 0.6 9.601 0.9 9.607 0.5 9.613 0.9 9.619 1.0 9.625 0.3 9.63 1.0 9.636 0.4 9.642 0.6 9.648 1.0 9.654 0.9 9.66 0.7 9.665 0.8 9.671 0.7 9.677 0.9 9.683 0.7 9.689 0.1 9.694 0.9 9.7 0.7 9.706 0.4 9.712 0.3 9.718 0.2 9.723 0.6 9.729 0.1 9.735 0.8 9.741 0.9 9.747 0.3 9.752 0.1 9.758 0.8 9.764 0.1 9.77 0.4 9.776 0.3 9.781 0.1 9.787 0.7 9.793 0.8 9.799 0.8 9.805 0.7 9.81 0.1 9.816 0.6 9.822 0.8 9.828 1.0 9.834 0.8 9.839 0.6 9.845 0.4 9.851 0.6 9.857 0.7 9.863 0.1 9.868 0.5 9.874 1.0 9.88 0.5 9.886 0.2 9.892 0.8 9.898 1.0 9.903 0.2 9.909 0.8 9.915 0.7 9.921 0.3 9.927 1.0 9.932 0.8 9.938 0.4 9.944 0.5 9.95 0.9 9.956 0.7 9.961 0.3 9.967 0.5 9.973 0.2 9.979 0.2 9.985 0.8 9.99 0.1 9.996 0.4 10.002 0.9 10.008 0.1 10.014 0.3 10.019 0.9 10.025 0.9 10.031 1.0 10.037 0.3 10.043 0.1 10.048 0.9 10.054 0.7 10.06 0.2 10.066 0.9 10.072 1.0 10.077 0.7 10.083 0.7 10.089 1.0 10.095 0.2 10.101 0.4 10.106 0.3 10.112 0.1 10.118 0.6 10.124 0.3 10.13 0.7 10.136 0.9 10.141 0.4 10.147 0.6 10.153 0.9 10.159 0.5 10.165 0.2 10.17 0.2 10.176 0.1 10.182 0.9 10.188 0.9 10.194 0.7 10.199 1.0 10.205 1.0 10.211 0.6 10.217 0.5 10.223 0.9 10.228 0.9 10.234 0.6 10.24 0.2 10.246 0.7 10.252 0.9 10.257 0.3 10.263 0.8 10.269 0.7 10.275 0.9 10.281 0.2 10.286 0.4 10.292 0.9 10.298 0.3 10.304 0.4 10.31 0.7 10.315 0.1 10.321 0.4 10.327 0.8 10.333 0.1 10.339 0.7 10.344 0.8 10.35 0.6 10.356 0.5 10.362 0.3 10.368 1.0 10.374 0.6 10.379 0.0 10.385 0.0 10.391 0.0 10.397 0.0 10.403 0.0 10.408 0.0 10.414 0.0 10.42 0.0 10.426 0.0 10.432 0.0 10.437 0.0 10.443 0.0 10.449 0.0 10.455 0.0 10.461 0.0 10.466 0.0 10.472 0.0 10.478 0.0 10.484 0.0 10.49 0.0 10.495 0.0 10.501 0.0 10.507 0.0 10.513 0.0 10.519 0.0 10.524 0.0 10.53 0.0 10.536 0.0 10.542 0.0 10.548 0.0 10.553 0.0 10.559 0.0 10.565 0.0 10.571 0.0 10.577 0.0 10.582 0.0 10.588 0.0 10.594 0.0 10.6 0.0 10.606 0.0 10.612 0.0 10.617 0.0 10.623 0.0 10.629 0.0 10.635 0.0 10.641 0.0 10.646 0.0 10.652 0.0 10.658 0.0 10.664 0.0 10.67 0.0 10.675 0.0 10.681 0.0 10.687 0.0 10.693 0.0 10.699 0.0 10.704 0.0 10.71 0.0 10.716 0.0 10.722 0.0 10.728 0.0 10.733 0.0 10.739 0.0 10.745 0.0 10.751 0.0 10.757 0.0 10.762 0.0 10.768 0.0 10.774 0.0 10.78 0.0 10.786 0.0 10.791 0.0 10.797 0.0 10.803 0.0 10.809 0.0 10.815 0.0 10.82 0.0 10.826 0.0 10.832 0.0 10.838 0.0 10.844 0.0 10.85 0.0 10.855 0.0 10.861 0.0 10.867 0.0 10.873 0.0 10.879 0.0 10.884 0.0 10.89 0.0 10.896 0.0 10.902 0.0 10.908 0.0 10.913 0.0 10.919 0.0 10.925 0.0 10.931 0.0 10.937 0.0 10.942 0.0 10.948 0.0 10.954 0.0 10.96 0.0 10.966 0.0 10.971 0.0 10.977 0.0 10.983 0.0 10.989 0.0 10.995 0.0 11.0 0.0 11.006 0.0 11.012 0.0 11.018 0.0 11.024 0.0 11.029 0.0 11.035 0.0 11.041 0.0 11.047 0.0 11.053 0.0 11.059 0.0 11.064 0.0 11.07 0.0 11.076 0.0 11.082 0.0 11.088 0.0 11.093 0.0 11.099 0.0 11.105 0.0 11.111 0.0 11.117 0.0 11.122 0.0 11.128 0.0 11.134 0.0 11.14 0.0 11.146 0.0 11.151 0.0 11.157 0.0 11.163 0.0 11.169 0.0 11.175 0.0 11.18 0.0 11.186 0.0 11.192 0.5 11.198 0.1 11.204 0.8 11.209 0.7 11.215 0.3 11.221 1.0 11.227 0.4 11.233 0.7 11.238 0.1 11.244 0.6 11.25 0.4 11.256 0.6 11.262 0.9 11.267 0.6 11.273 1.0 11.279 0.1 11.285 0.1 11.291 0.6 11.297 0.7 11.302 0.4 11.308 0.1 11.314 0.5 11.32 0.1 11.326 0.5 11.331 0.4 11.337 0.5 11.343 0.8 11.349 0.7 11.355 1.0 11.36 0.1 11.366 0.4 11.372 0.7 11.378 0.8 11.384 0.1 11.389 0.2 11.395 0.2 11.401 0.5 11.407 0.9 11.413 0.4 11.418 0.5 11.424 0.8 11.43 0.1 11.436 0.9 11.442 0.6 11.447 0.6 11.453 0.4 11.459 1.0 11.465 0.3 11.471 0.6 11.476 0.8 11.482 0.2 11.488 0.9 11.494 0.5 11.5 0.4 11.505 0.8 11.511 0.5 11.517 0.6 11.523 0.9 11.529 0.2 11.535 0.1 11.54 0.8 11.546 1.0 11.552 0.3 11.558 0.3 11.564 1.0 11.569 0.4 11.575 0.4 11.581 0.2 11.587 0.9 11.593 0.3 11.598 0.1 11.604 0.9 11.61 0.3 11.616 0.4 11.622 0.4 11.627 0.4 11.633 0.9 11.639 0.4 11.645 0.7 11.651 0.9 11.656 0.2 11.662 0.7 11.668 0.5 11.674 0.5 11.68 0.8 11.685 0.8 11.691 0.9 11.697 1.0 11.703 0.7 11.709 0.3 11.714 0.1 11.72 0.8 11.726 1.0 11.732 0.2 11.738 0.1 11.743 0.6 11.749 0.9 11.755 0.7 11.761 0.9 11.767 0.8 11.773 0.7 11.778 0.2 11.784 0.7 11.79 0.0 11.796 0.0 11.802 0.0 11.807 0.0 11.813 0.0 11.819 0.0 11.825 0.0 11.831 0.0 11.836 0.0 11.842 0.0 11.848 0.0 11.854 0.0 11.86 0.0 11.865 0.0 11.871 0.0 11.877 0.0 11.883 0.0 11.889 0.0 11.894 0.0 11.9 0.7 11.906 1.0 11.912 1.0 11.918 1.0 11.923 0.7 11.929 0.7 11.935 0.7 11.941 0.2 11.947 1.0 11.952 0.9 11.958 0.3 11.964 0.8 11.97 0.4 11.976 1.0 11.981 0.9 11.987 0.8 11.993 0.4 11.999 0.9 12.005 0.3 12.011 0.4 12.016 0.8 12.022 0.1 12.028 0.7 12.034 0.4 12.04 0.3 12.045 0.1 12.051 1.0 12.057 0.4 12.063 0.1 12.069 0.9 12.074 0.6 12.08 0.2 12.086 0.5 12.092 0.2 12.098 0.2 12.103 0.6 12.109 0.6 12.115 0.9 12.121 0.8 12.127 0.5 12.132 0.2 12.138 0.7 12.144 0.6 12.15 0.1 12.156 0.7 12.161 0.4 12.167 0.9 12.173 0.8 12.179 0.7 12.185 0.8 12.19 0.5 12.196 0.7 12.202 0.9 12.208 0.5 12.214 0.2 12.22 0.9 12.225 0.1 12.231 0.3 12.237 0.2 12.243 0.7 12.249 0.6 12.254 0.2 12.26 0.8 12.266 0.6 12.272 0.9 12.278 0.3 12.283 0.7 12.289 0.2 12.295 0.5 12.301 0.2 12.307 0.6 12.312 0.2 12.318 0.2 12.324 0.3 12.33 0.8 12.336 0.2 12.341 0.6 12.347 0.3 12.353 0.4 12.359 0.3 12.365 0.5 12.37 0.2 12.376 1.0 12.382 0.5 12.388 0.9 12.394 0.9 12.399 0.1 12.405 0.2 12.411 0.6 12.417 0.4 12.423 1.0 12.428 0.1 12.434 0.7 12.44 0.8 12.446 1.0 12.452 1.0 12.458 0.4 12.463 0.3 12.469 0.1 12.475 0.1 12.481 0.2 12.487 0.7 12.492 0.9 12.498 0.9 12.504 0.9 12.51 0.9 12.516 0.4 12.521 0.2 12.527 0.1 12.533 0.2 12.539 0.8 12.545 0.3 12.55 0.8 12.556 0.5 12.562 0.8 12.568 0.1 12.574 0.1 12.579 0.4 12.585 0.3 12.591 0.7 12.597 0.3 12.603 0.6 12.608 0.6 12.614 0.2 12.62 0.1 12.626 0.8 12.632 0.4 12.637 0.8 12.643 0.6 12.649 0.9 12.655 0.3 12.661 0.6 12.666 0.4 12.672 0.3 12.678 0.4 12.684 0.8 12.69 0.2 12.696 0.4 12.701 0.9 12.707 0.3 12.713 0.5 12.719 0.5 12.725 1.0 12.73 0.8 12.736 0.6 12.742 0.3 12.748 0.8 12.754 0.4 12.759 0.8 12.765 0.1 12.771 0.9 12.777 0.9 12.783 0.8 12.788 0.6 12.794 0.7 12.8 0.3 12.806 0.3 12.812 0.1 12.817 0.5 12.823 0.6 12.829 0.6 12.835 1.0 12.841 0.4 12.846 0.4 12.852 0.2 12.858 0.8 12.864 0.8 12.87 0.9 12.875 0.2 12.881 0.1 12.887 0.2 12.893 1.0 12.899 0.8 12.904 0.5 12.91 0.1 12.916 1.0 12.922 0.1 12.928 0.7 12.934 0.5 12.939 0.6 12.945 0.8 12.951 0.1 12.957 0.4 12.963 0.7 12.968 0.7 12.974 0.3 12.98 0.4 12.986 1.0 12.992 0.2 12.997 0.4 13.003 0.5 13.009 0.7 13.015 0.2 13.021 0.8 13.026 0.6 13.032 0.5 13.038 0.5 13.044 0.6 13.05 0.5 13.055 0.7 13.061 0.5 13.067 0.3 13.073 0.3 13.079 0.1 13.084 0.3 13.09 0.7 13.096 0.2 13.102 0.4 13.108 1.0 13.113 0.6 13.119 0.2 13.125 0.2 13.131 0.7 13.137 0.6 13.142 0.2 13.148 1.0 13.154 0.8 13.16 0.5 13.166 0.5 13.172 0.2 13.177 0.9 13.183 0.1 13.189 0.7 13.195 0.2 13.201 0.8 13.206 0.4 13.212 0.5 13.218 0.4 13.224 0.7 13.23 0.8 13.235 0.7 13.241 0.6 13.247 0.8 13.253 0.9 13.259 0.5 13.264 0.7 13.27 0.7 13.276 0.9 13.282 0.1 13.288 0.1 13.293 0.1 13.299 1.0 13.305 0.1 13.311 0.2 13.317 0.3 13.322 0.1 13.328 0.6 13.334 1.0 13.34 0.8 13.346 1.0 13.351 0.3 13.357 0.3 13.363 0.2 13.369 0.1 13.375 0.8 13.38 0.6 13.386 0.3 13.392 0.5 13.398 0.2 13.404 0.4 13.41 0.4 13.415 0.8 13.421 0.4 13.427 0.1 13.433 0.6 13.439 1.0 13.444 0.3 13.45 0.7 13.456 0.6 13.462 0.5 13.468 0.5 13.473 0.3 13.479 0.3 13.485 0.8 13.491 0.8 13.497 0.1 13.502 0.3 13.508 1.0 13.514 0.4 13.52 0.2 13.526 1.0 13.531 0.6 13.537 0.8 13.543 0.7 13.549 0.4 13.555 0.4 13.56 0.8 13.566 0.3 13.572 0.8 13.578 0.2 13.584 0.1 13.589 0.5 13.595 0.9 13.601 0.8 13.607 0.4 13.613 0.8 13.619 0.9 13.624 0.7 13.63 0.2 13.636 0.1 13.642 0.4 13.648 0.5 13.653 0.5 13.659 0.8 13.665 0.5 13.671 0.7 13.677 0.7 13.682 0.4 13.688 0.2 13.694 0.1 13.7 0.1 13.706 0.4 13.711 0.7 13.717 0.3 13.723 0.8 13.729 0.1 13.735 0.4 13.74 0.6 13.746 0.2 13.752 0.1 13.758 0.8 13.764 0.6 13.769 0.9 13.775 0.4 13.781 0.1 13.787 1.0 13.793 0.7 13.798 0.3 13.804 0.6 13.81 0.2 13.816 0.7 13.822 0.2 13.827 0.8 13.833 0.1 13.839 0.1 13.845 0.7 13.851 0.7 13.857 1.0 13.862 0.1 13.868 0.7 13.874 0.9 13.88 0.8 13.886 0.8 13.891 0.3 13.897 0.8 13.903 0.7 13.909 0.5 13.915 0.4 13.92 1.0 13.926 0.9 13.932 1.0 13.938 0.2 13.944 0.9 13.949 0.6 13.955 0.1 13.961 1.0 13.967 0.2 13.973 0.8 13.978 0.7 13.984 0.8 13.99 0.6 13.996 0.9 14.002 0.1 14.007 0.4 14.013 0.8 14.019 0.5 14.025 0.7 14.031 0.1 14.036 0.2 14.042 0.5 14.048 0.4 14.054 0.1 14.06 0.7 14.065 0.3 14.071 1.0 14.077 0.2 14.083 1.0 14.089 0.5 14.095 0.2 14.1 0.1 14.106 0.1 14.112 1.0 14.118 0.7 14.124 0.8 14.129 0.2 14.135 0.9 14.141 0.4 14.147 0.9 14.153 0.2 14.158 0.4 14.164 0.7 14.17 0.8 14.176 0.2 14.182 0.6 14.187 0.7 14.193 1.0 14.199 0.1 14.205 0.5 14.211 0.1 14.216 0.5 14.222 0.8 14.228 0.2 14.234 0.9 14.24 0.4 14.245 0.4 14.251 0.4 14.257 0.7 14.263 0.5 14.269 0.1 14.274 0.4 14.28 0.9 14.286 0.3 14.292 1.0 14.298 0.7 14.303 0.7 14.309 0.5 14.315 0.8 14.321 1.0 14.327 0.1 14.333 0.7 14.338 0.2 14.344 0.8 14.35 0.3 14.356 0.5 14.362 0.5 14.367 0.6 14.373 0.9 14.379 0.2 14.385 0.9 14.391 0.3 14.396 0.5 14.402 0.3 14.408 0.8 14.414 0.3 14.42 1.0 14.425 0.9 14.431 0.5 14.437 0.9 14.443 0.2 14.449 0.6 14.454 1.0 14.46 0.4 14.466 0.9 14.472 0.5 14.478 0.5 14.483 0.5 14.489 0.2 14.495 0.9 14.501 0.8 14.507 0.4 14.512 0.1 14.518 0.8 14.524 0.6 14.53 1.0 14.536 0.3 14.541 0.3 14.547 0.6 14.553 0.1 14.559 0.2 14.565 0.9 14.571 0.3 14.576 0.5 14.582 0.7 14.588 0.6 14.594 0.4 14.6 0.3 14.605 0.3 14.611 0.9 14.617 0.8 14.623 1.0 14.629 0.7 14.634 1.0 14.64 0.3 14.646 1.0 14.652 0.1 14.658 0.6 14.663 0.8 14.669 0.4 14.675 0.1 14.681 0.4 14.687 0.6 14.692 0.6 14.698 0.3 14.704 0.2 14.71 0.2 14.716 0.1 14.721 0.5 14.727 0.5 14.733 0.7 14.739 0.9 14.745 0.6 14.75 0.9 14.756 0.4 14.762 0.7 14.768 0.7 14.774 0.8 14.78 1.0 14.785 0.9 14.791 0.8 14.797 0.6 14.803 0.7 14.809 0.7 14.814 1.0 14.82 0.2 14.826 0.5 14.832 0.2 14.838 1.0 14.843 0.9 14.849 0.3 14.855 0.7 14.861 0.1 14.867 0.7 14.872 1.0 14.878 0.6 14.884 0.2 14.89 0.1 14.896 1.0 14.901 0.4 14.907 0.7 14.913 0.3 14.919 0.7 14.925 0.2 14.93 1.0 14.936 0.3 14.942 0.6 14.948 0.5 14.954 0.9 14.959 0.9 14.965 0.5 14.971 1.0 14.977 0.6 14.983 0.2 14.988 1.0 14.994 1.0 15.0 0.1 15.006 0.4 15.012 0.7 15.018 0.9 15.023 0.1 15.029 0.3 15.035 0.8 15.041 0.3 15.047 0.2 15.052 0.9 15.058 0.2 15.064 0.9 15.07 0.5 15.076 0.6 15.081 0.1 15.087 0.7 15.093 0.6 15.099 0.4 15.105 0.5 15.11 0.6 15.116 0.6 15.122 0.1 15.128 0.2 15.134 0.1 15.139 0.6 15.145 0.5 15.151 0.2 15.157 0.2 15.163 0.3 15.168 0.2 15.174 0.9 15.18 0.1 15.186 0.1 15.192 0.8 15.197 0.8 15.203 0.9 15.209 1.0 15.215 0.6 15.221 0.9 15.226 0.3 15.232 0.3 15.238 0.3 15.244 0.5 15.25 0.9 15.256 0.7 15.261 0.5 15.267 1.0 15.273 0.1 15.279 0.6 15.285 0.8 15.29 0.2 15.296 0.9 15.302 0.6 15.308 0.2 15.314 0.8 15.319 0.3 15.325 0.5 15.331 0.9 15.337 0.0 15.343 0.0 15.348 0.0 15.354 0.0 15.36 0.0 15.366 0.0 15.372 0.0 15.377 0.0 15.383 0.0 15.389 0.0 15.395 0.0 15.401 0.0 15.406 0.0 15.412 0.0 15.418 0.0 15.424 0.0 15.43 0.0 15.435 0.0 15.441 0.0 15.447 0.0 15.453 0.0 15.459 0.0 15.464 0.0 15.47 0.0 15.476 0.0 15.482 0.0 15.488 0.0 15.494 0.0 15.499 0.0 15.505 0.0 15.511 0.0 15.517 0.0 15.523 0.0 15.528 0.0 15.534 0.0 15.54 0.0 15.546 0.0 15.552 0.0 15.557 0.0 15.563 0.0 15.569 0.0 15.575 0.0 15.581 0.0 15.586 0.0 15.592 0.0 15.598 0.0 15.604 0.0 15.61 0.0 15.615 0.0 15.621 0.0 15.627 0.0 15.633 0.0 15.639 0.0 15.644 0.0 15.65 0.0 15.656 0.0 15.662 0.0 15.668 0.0 15.673 0.0 15.679 0.0 15.685 0.0 15.691 0.0 15.697 0.0 15.702 0.0 15.708 0.0 15.714 0.0 15.72 0.0 15.726 0.0 15.732 0.0 15.737 0.0 15.743 0.0 15.749 0.0 15.755 0.0 15.761 0.0 15.766 0.0 15.772 0.0 15.778 0.0 15.784 0.0 15.79 0.0 15.795 0.0 15.801 0.0 15.807 0.0 15.813 0.0 15.819 0.0 15.824 0.0 15.83 0.0 15.836 0.0 15.842 0.0 15.848 0.0 15.853 0.0 15.859 0.0 15.865 0.0 15.871 0.0 15.877 0.0 15.882 0.0 15.888 0.0 15.894 0.0 15.9 0.0 15.906 0.0 15.911 0.0 15.917 0.0 15.923 0.0 15.929 0.0 15.935 0.0 15.94 0.0 15.946 0.0 15.952 0.0 15.958 0.0 15.964 0.0 15.97 0.0 15.975 0.0 15.981 0.0 15.987 0.0 15.993 0.0 15.999 0.0 16.004 0.0 16.01 0.0 16.016 0.0 16.022 0.0 16.028 0.0 16.033 0.0 16.039 0.0 16.045 0.0 16.051 0.0 16.057 0.0 16.062 0.0 16.068 0.0 16.074 0.0 16.08 0.0 16.086 0.0 16.091 0.0 16.097 0.0 16.103 0.0 16.109 0.0 16.115 0.0 16.12 0.0 16.126 0.0 16.132 0.0 16.138 0.0 16.144 0.0 16.149 0.0 16.155 0.0 16.161 0.0 16.167 0.0 16.173 0.0 16.179 0.0 16.184 0.0 16.19 0.0 16.196 0.0 16.202 0.0 16.208 0.0 16.213 0.0 16.219 0.0 16.225 0.0 16.231 0.0 16.237 0.0 16.242 0.0 16.248 0.0 16.254 0.0 16.26 0.0 16.266 0.0 16.271 0.0 16.277 0.0 16.283 0.0 16.289 0.0 16.295 0.0 16.3 0.0 16.306 0.0 16.312 0.0 16.318 0.0 16.324 0.0 16.329 0.0 16.335 0.0 16.341 0.8 16.347 0.7 16.353 0.8 16.358 0.6 16.364 0.3 16.37 0.2 16.376 0.3 16.382 0.9 16.387 0.2 16.393 0.6 16.399 0.6 16.405 0.4 16.411 0.4 16.417 0.6 16.422 0.1 16.428 0.8 16.434 0.9 16.44 0.9 16.446 0.5 16.451 0.8 16.457 0.1 16.463 0.7 16.469 0.5 16.475 0.6 16.48 0.2 16.486 0.8 16.492 0.5 16.498 0.3 16.504 1.0 16.509 1.0 16.515 0.9 16.521 1.0 16.527 0.6 16.533 0.7 16.538 0.4 16.544 0.7 16.55 0.4 16.556 0.2 16.562 1.0 16.567 1.0 16.573 0.2 16.579 0.9 16.585 0.4 16.591 0.6 16.596 0.5 16.602 0.1 16.608 0.1 16.614 0.7 16.62 0.9 16.625 0.2 16.631 0.4 16.637 0.3 16.643 0.5 16.649 0.9 16.655 0.9 16.66 0.6 16.666 0.9 16.672 0.1 16.678 0.2 16.684 0.2 16.689 0.3 16.695 0.8 16.701 0.7 16.707 0.1 16.713 0.3 16.718 0.5 16.724 0.5 16.73 0.2 16.736 1.0 16.742 0.5 16.747 0.4 16.753 0.7 16.759 0.2 16.765 0.5 16.771 0.3 16.776 0.8 16.782 0.5 16.788 0.4 16.794 0.7 16.8 0.6 16.805 0.7 16.811 0.9 16.817 0.2 16.823 0.2 16.829 0.2 16.834 0.1 16.84 0.4 16.846 0.9 16.852 0.3 16.858 0.4 16.863 0.1 16.869 0.2 16.875 0.6 16.881 0.8 16.887 0.6 16.893 0.5 16.898 0.9 16.904 0.1 16.91 0.6 16.916 0.5 16.922 0.3 16.927 0.3 16.933 0.3 16.939 0.5 16.945 1.0 16.951 0.6 16.956 0.1 16.962 0.6 16.968 1.0 16.974 0.4 16.98 0.2 16.985 0.3 16.991 1.0 16.997 0.4 17.003 0.3 17.009 0.8 17.014 0.0 17.02 0.0 17.026 0.0 17.032 0.0 17.038 0.4 17.043 0.4 17.049 0.8 17.055 0.7 17.061 0.2 17.067 0.6 17.072 0.1 17.078 0.5 17.084 0.1 17.09 0.1 17.096 0.1 17.101 0.7 17.107 0.2 17.113 0.1 17.119 0.6 17.125 0.1 17.131 1.0 17.136 0.6 17.142 0.2 17.148 0.3 17.154 0.2 17.16 0.3 17.165 0.1 17.171 0.9 17.177 0.5 17.183 0.1 17.189 0.6 17.194 0.9 17.2 0.8 17.206 0.1 17.212 0.3 17.218 0.8 17.223 0.4 17.229 0.1 17.235 0.4 17.241 0.2 17.247 0.4 17.252 0.2 17.258 0.3 17.264 1.0 17.27 0.8 17.276 1.0 17.281 0.9 17.287 0.2 17.293 0.2 17.299 0.8 17.305 0.8 17.31 1.0 17.316 0.2 17.322 0.6 17.328 0.9 17.334 0.2 17.34 0.2 17.345 0.9 17.351 0.4 17.357 1.0 17.363 0.4 17.369 1.0 17.374 0.5 17.38 1.0 17.386 0.5 17.392 0.7 17.398 0.1 17.403 0.1 17.409 0.6 17.415 0.1 17.421 0.8 17.427 0.8 17.432 1.0 17.438 0.1 17.444 0.6 17.45 0.3 17.456 0.2 17.461 0.5 17.467 1.0 17.473 0.8 17.479 0.2 17.485 0.5 17.49 0.2 17.496 0.8 17.502 0.4 17.508 0.4 17.514 0.1 17.519 0.3 17.525 0.1 17.531 0.3 17.537 0.2 17.543 0.7 17.548 0.6 17.554 0.8 17.56 0.2 17.566 0.4 17.572 0.7 17.578 0.9 17.583 0.3 17.589 0.6 17.595 1.0 17.601 0.0 17.607 0.0 17.612 0.0 17.618 0.0 17.624 0.0 17.63 0.0 17.636 0.0 17.641 0.0 17.647 0.0 17.653 0.0 17.659 0.0 17.665 0.0 17.67 0.0 17.676 0.0 17.682 0.0 17.688 0.1 17.694 0.1 17.699 1.0 17.705 0.6 17.711 0.4 17.717 0.6 17.723 0.5 17.728 0.8 17.734 0.6 17.74 0.2 17.746 0.6 17.752 0.4 17.757 0.8 17.763 0.1 17.769 0.4 17.775 0.9 17.781 0.9 17.786 1.0 17.792 0.6 17.798 0.8 17.804 0.4 17.81 0.5 17.816 0.4 17.821 1.0 17.827 0.7 17.833 0.5 17.839 0.5 17.845 0.6 17.85 0.7 17.856 0.2 17.862 0.5 17.868 0.2 17.874 0.6 17.879 0.4 17.885 0.3 17.891 0.3 17.897 0.7 17.903 0.7 17.908 0.1 17.914 0.3 17.92 0.5 17.926 0.6 17.932 0.5 17.937 0.8 17.943 0.3 17.949 0.7 17.955 0.1 17.961 0.5 17.966 0.3 17.972 0.3 17.978 0.1 17.984 0.2 17.99 0.6 17.995 0.5 18.001 0.7 18.007 0.5 18.013 0.5 18.019 0.3 18.024 1.0 18.03 1.0 18.036 0.6 18.042 0.3 18.048 0.5 18.054 1.0 18.059 0.5 18.065 0.1 18.071 0.3 18.077 0.8 18.083 0.3 18.088 0.2 18.094 0.7 18.1 0.9 18.106 0.6 18.112 0.1 18.117 0.5 18.123 0.9 18.129 0.2 18.135 0.9 18.141 0.7 18.146 0.1 18.152 0.2 18.158 0.6 18.164 0.1 18.17 0.3 18.175 0.9 18.181 0.6 18.187 0.4 18.193 0.1 18.199 0.4 18.204 0.3 18.21 0.9 18.216 0.8 18.222 0.4 18.228 0.5 18.233 0.6 18.239 1.0 18.245 0.4 18.251 1.0 18.257 0.3 18.262 0.1 18.268 0.7 18.274 0.3 18.28 0.2 18.286 0.9 18.292 0.6 18.297 0.7 18.303 0.4 18.309 0.6 18.315 0.7 18.321 0.2 18.326 0.2 18.332 0.6 18.338 1.0 18.344 0.7 18.35 0.8 18.355 1.0 18.361 0.3 18.367 0.6 18.373 0.9 18.379 0.1 18.384 0.4 18.39 0.9 18.396 0.7 18.402 0.1 18.408 0.4 18.413 1.0 18.419 0.2 18.425 0.4 18.431 0.5 18.437 0.8 18.442 0.9 18.448 0.5 18.454 0.9 18.46 0.2 18.466 0.9 18.471 0.1 18.477 0.0 18.483 0.0 18.489 0.0 18.495 0.0 18.5 0.0 18.506 0.0 18.512 0.0 18.518 0.0 18.524 0.0 18.53 0.0 18.535 0.0 18.541 0.0 18.547 0.0 18.553 0.0 18.559 0.0 18.564 0.0 18.57 0.0 18.576 0.0 18.582 0.0 18.588 0.0 18.593 0.0 18.599 0.0 18.605 0.0 18.611 0.0 18.617 0.0 18.622 0.0 18.628 0.2 18.634 0.7 18.64 1.0 18.646 0.5 18.651 0.5 18.657 0.8 18.663 0.9 18.669 0.8 18.675 0.7 18.68 0.1 18.686 0.1 18.692 0.4 18.698 0.3 18.704 0.3 18.709 1.0 18.715 0.6 18.721 0.3 18.727 0.2 18.733 1.0 18.739 0.5 18.744 0.4 18.75 0.1 18.756 0.8 18.762 0.3 18.768 0.8 18.773 0.6 18.779 1.0 18.785 0.3 18.791 0.7 18.797 0.2 18.802 0.2 18.808 0.5 18.814 0.1 18.82 0.2 18.826 1.0 18.831 1.0 18.837 0.1 18.843 0.5 18.849 0.4 18.855 0.9 18.86 1.0 18.866 0.5 18.872 0.3 18.878 0.4 18.884 0.9 18.889 1.0 18.895 0.1 18.901 0.1 18.907 0.5 18.913 0.2 18.918 0.3 18.924 0.2 18.93 0.8 18.936 0.9 18.942 0.9 18.947 0.5 18.953 0.4 18.959 0.3 18.965 1.0 18.971 0.3 18.977 0.9 18.982 1.0 18.988 0.2 18.994 0.6 19.0 0.2 19.006 0.7 19.011 0.5 19.017 0.6 19.023 0.6 19.029 1.0 19.035 0.1 19.04 0.9 19.046 0.6 19.052 1.0 19.058 0.9 19.064 1.0 19.069 0.9 19.075 0.6 19.081 0.1 19.087 0.2 19.093 1.0 19.098 0.8 19.104 1.0 19.11 0.9 19.116 0.3 19.122 0.2 19.127 0.6 19.133 0.7 19.139 1.0 19.145 0.1 19.151 0.3 19.156 0.1 19.162 0.2 19.168 0.8 19.174 0.8 19.18 0.3 19.185 0.7 19.191 1.0 19.197 1.0 19.203 0.9 19.209 0.9 19.215 0.4 19.22 0.7 19.226 0.9 19.232 1.0 19.238 0.4 19.244 1.0 19.249 0.5 19.255 0.8 19.261 0.6 19.267 1.0 19.273 0.3 19.278 0.2 19.284 0.5 19.29 1.0 19.296 0.7 19.302 1.0 19.307 0.8 19.313 0.3 19.319 0.3 19.325 0.7 19.331 0.5 19.336 0.6 19.342 0.3 19.348 0.6 19.354 0.1 19.36 0.1 19.365 0.4 19.371 0.4 19.377 0.4 19.383 0.7 19.389 0.4 19.394 0.2 19.4 0.3 19.406 0.3 19.412 0.4 19.418 0.9 19.423 0.5 19.429 0.4 19.435 0.6 19.441 0.8 19.447 0.2 19.453 0.8 19.458 0.2 19.464 0.9 19.47 1.0 19.476 0.2 19.482 0.6 19.487 0.2 19.493 0.6 19.499 0.4 19.505 0.5 19.511 0.3 19.516 0.1 19.522 1.0 19.528 0.2 19.534 0.7 19.54 0.8 19.545 0.5 19.551 0.3 19.557 0.4 19.563 0.2 19.569 0.1 19.574 0.1 19.58 1.0 19.586 0.5 19.592 0.6 19.598 0.4 19.603 0.1 19.609 0.1 19.615 0.9 19.621 0.5 19.627 0.3 19.632 0.7 19.638 0.3 19.644 0.1 19.65 1.0 19.656 0.5 19.661 0.1 19.667 0.1 19.673 0.3 19.679 0.2 19.685 0.3 19.691 0.2 19.696 0.7 19.702 0.9 19.708 0.9 19.714 0.3 19.72 0.1 19.725 0.6 19.731 0.6 19.737 0.3 19.743 0.4 19.749 0.2 19.754 0.6 19.76 0.7 19.766 0.8 19.772 0.1 19.778 0.8 19.783 0.4 19.789 0.5 19.795 0.1 19.801 0.6 19.807 0.9 19.812 0.1 19.818 0.7 19.824 0.1 19.83 0.2 19.836 0.6 19.841 0.7 19.847 0.6 19.853 0.7 19.859 0.4 19.865 0.2 19.87 0.3 19.876 0.9 19.882 0.5 19.888 0.2 19.894 0.8 19.9 0.6 19.905 0.4 19.911 0.6 19.917 0.7 19.923 1.0 19.929 1.0 19.934 0.4 19.94 0.8 19.946 1.0 19.952 0.9 19.958 0.6 19.963 0.8 19.969 0.6 19.975 0.4 19.981 0.2 19.987 0.1 19.992 0.1 19.998 0.3 20.004 0.1 20.01 0.1 20.016 0.8 20.021 0.8 20.027 0.2 20.033 0.2 20.039 0.6 20.045 1.0 20.05 0.5 20.056 0.4 20.062 0.6 20.068 0.4 20.074 0.9 20.079 0.7 20.085 0.8 20.091 0.7 20.097 0.1 20.103 0.2 20.108 0.8 20.114 0.3 20.12 0.6 20.126 0.4 20.132 0.4 20.138 0.4 20.143 0.2 20.149 0.6 20.155 0.1 20.161 0.5 20.167 0.6 20.172 0.3 20.178 0.4 20.184 0.1 20.19 0.4 20.196 0.5 20.201 0.3 20.207 0.7 20.213 0.4 20.219 0.8 20.225 0.8 20.23 0.3 20.236 0.6 20.242 0.2 20.248 0.7 20.254 0.6 20.259 0.4 20.265 1.0 20.271 0.7 20.277 0.7 20.283 1.0 20.288 0.1 20.294 0.4 20.3 0.1 20.306 0.4 20.312 1.0 20.317 0.5 20.323 0.7 20.329 1.0 20.335 0.5 20.341 0.1 20.346 0.9 20.352 0.4 20.358 0.6 20.364 0.6 20.37 0.6 20.376 0.2 20.381 0.4 20.387 1.0 20.393 0.9 20.399 1.0 20.405 0.4 20.41 1.0 20.416 0.6 20.422 0.4 20.428 0.4 20.434 1.0 20.439 0.5 20.445 0.9 20.451 0.2 20.457 0.9 20.463 0.6 20.468 0.0 20.474 0.0 20.48 0.0 20.486 0.0 20.492 0.0 20.497 0.0 20.503 0.0 20.509 0.0 20.515 0.0 20.521 0.0 20.526 0.0 20.532 0.0 20.538 0.0 20.544 0.0 20.55 0.0 20.555 0.0 20.561 0.0 20.567 0.0 20.573 0.0 20.579 0.0 20.584 0.0 20.59 0.0 20.596 0.0 20.602 0.0 20.608 0.0 20.614 0.0 20.619 0.0 20.625 0.0 20.631 0.0 20.637 0.0 20.643 0.0 20.648 0.0 20.654 0.0 20.66 0.0 20.666 0.0 20.672 0.0 20.677 0.0 20.683 0.0 20.689 0.0 20.695 0.0 20.701 0.0 20.706 0.0 20.712 0.0 20.718 0.0 20.724 0.0 20.73 0.0 20.735 0.0 20.741 0.0 20.747 0.0 20.753 0.0 20.759 0.0 20.764 0.0 20.77 0.0 20.776 0.0 20.782 0.0 20.788 0.0 20.793 0.0 20.799 0.0 20.805 0.0 20.811 0.0 20.817 0.0 20.822 0.0 20.828 0.0 20.834 0.0 20.84 0.0 20.846 0.0 20.852 0.0 20.857 0.0 20.863 0.0 20.869 0.0 20.875 0.0 20.881 0.0 20.886 0.0 20.892 0.0 20.898 0.0 20.904 0.0 20.91 0.0 20.915 0.0 20.921 0.0 20.927 0.0 20.933 0.0 20.939 0.0 20.944 0.0 20.95 0.0 20.956 0.0 20.962 0.0 20.968 0.0 20.973 0.0 20.979 0.0 20.985 0.0 20.991 0.0 20.997 0.0 21.002 0.0 21.008 0.0 21.014 0.0 21.02 0.0 21.026 0.0 21.031 0.0 21.037 0.0 21.043 0.0 21.049 0.0 21.055 0.0 21.06 0.0 21.066 0.0 21.072 0.0 21.078 0.0 mir_eval-0.8.2/tests/data/melody/voicingest00.txt000066400000000000000000000604041475740344600217600ustar00rootroot00000000000000# A comment 0 0.0 0.01 0.0 0.02 0.2 0.03 0.2 0.04 0.2 0.05 0.2 0.06 0.2 0.07 0.2 0.08 0.2 0.09 0.2 0.1 0.2 0.11 0.2 0.12 0.2 0.13 0.2 0.14 0.2 0.15 0.2 0.16 0.2 0.17 0.2 0.18 0.2 0.19 0.2 0.2 0.2 0.21 0.2 0.22 0.2 0.23 0.2 0.24 0.2 0.25 0.2 0.26 0.2 0.27 0.2 0.28 0.2 0.29 0.2 0.3 0.2 0.31 0.2 0.32 0.2 0.33 0.2 0.34 0.2 0.35 0.2 0.36 0.2 0.37 0.2 0.38 0.2 0.39 0.2 0.4 0.2 0.41 0.2 0.42 0.2 0.43 0.2 0.44 0.2 0.45 0.2 0.46 0.2 0.47 0.2 0.48 0.2 0.49 0.2 0.5 0.2 0.51 0.2 0.52 0.2 0.53 0.2 0.54 0.2 0.55 0.2 0.56 0.2 0.57 0.2 0.58 0.2 0.59 0.2 0.6 0.2 0.61 0.2 0.62 0.2 0.63 0.2 0.64 0.2 0.65 0.2 0.66 0.2 0.67 0.2 0.68 0.2 0.69 0.2 0.7 0.2 0.71 0.2 0.72 0.2 0.73 0.2 0.74 0.2 0.75 0.2 0.76 0.2 0.77 0.2 0.78 0.2 0.79 0.2 0.8 0.2 0.81 0.2 0.82 0.2 0.83 0.2 0.84 0.2 0.85 0.2 0.86 0.2 0.87 0.2 0.88 0.2 0.89 0.2 0.9 0.2 0.91 0.2 0.92 0.2 0.93 0.2 0.94 0.2 0.95 0.2 0.96 0.2 0.97 0.2 0.98 0.2 0.99 0.2 1 0.2 1.01 0.2 1.02 0.2 1.03 0.2 1.04 0.2 1.05 0.2 1.06 0.2 1.07 0.2 1.08 0.2 1.09 0.2 1.1 0.2 1.11 0.2 1.12 0.2 1.13 0.2 1.14 0.2 1.15 0.2 1.16 0.2 1.17 0.2 1.18 0.2 1.19 0.2 1.2 0.2 1.21 0.2 1.22 0.2 1.23 0.2 1.24 0.2 1.25 0.2 1.26 0.2 1.27 0.2 1.28 0.2 1.29 0.2 1.3 0.2 1.31 0.2 1.32 0.2 1.33 0.2 1.34 0.2 1.35 0.2 1.36 0.2 1.37 0.8 1.38 0.8 1.39 0.8 1.4 0.8 1.41 0.8 1.42 0.8 1.43 0.8 1.44 0.7 1.45 0.8 1.46 0.8 1.47 0.8 1.48 0.7 1.49 0.8 1.5 0.7 1.51 0.7 1.52 0.7 1.53 0.7 1.54 0.7 1.55 0.7 1.56 0.7 1.57 0.7 1.58 0.7 1.59 0.7 1.6 0.7 1.61 0.7 1.62 0.7 1.63 0.8 1.64 0.8 1.65 0.7 1.66 0.8 1.67 0.7 1.68 0.7 1.69 0.7 1.7 0.8 1.71 0.8 1.72 0.7 1.73 0.8 1.74 0.8 1.75 0.8 1.76 1.0 1.77 0.9 1.78 0.8 1.79 0.9 1.8 0.8 1.81 1.0 1.82 0.9 1.83 0.9 1.84 1.0 1.85 1.0 1.86 1.0 1.87 0.9 1.88 0.9 1.89 0.9 1.9 0.9 1.91 1.0 1.92 1.0 1.93 0.8 1.94 0.7 1.95 0.6 1.96 1.0 1.97 0.9 1.98 0.8 1.99 0.6 2 0.5 2.01 0.5 2.02 0.7 2.03 1.0 2.04 0.6 2.05 0.9 2.06 0.9 2.07 0.9 2.08 0.9 2.09 0.9 2.1 0.6 2.11 1.0 2.12 1.0 2.13 1.0 2.14 1.0 2.15 0.7 2.16 0.6 2.17 0.6 2.18 0.7 2.19 0.7 2.2 0.6 2.21 0.6 2.22 0.6 2.23 0.6 2.24 0.6 2.25 0.7 2.26 0.6 2.27 0.6 2.28 0.6 2.29 0.6 2.3 0.7 2.31 0.7 2.32 0.7 2.33 0.7 2.34 0.7 2.35 0.6 2.36 0.6 2.37 0.6 2.38 0.6 2.39 0.6 2.4 0.6 2.41 0.6 2.42 0.6 2.43 0.6 2.44 0.6 2.45 0.6 2.46 0.6 2.47 0.6 2.48 0.6 2.49 0.6 2.5 0.6 2.51 0.6 2.52 0.6 2.53 0.6 2.54 0.6 2.55 0.6 2.56 0.6 2.57 0.6 2.58 0.6 2.59 0.6 2.6 0.6 2.61 0.6 2.62 0.5 2.63 0.6 2.64 0.6 2.65 0.6 2.66 0.5 2.67 0.6 2.68 0.6 2.69 0.6 2.7 0.6 2.71 0.6 2.72 0.6 2.73 0.6 2.74 0.6 2.75 0.6 2.76 0.6 2.77 0.6 2.78 0.6 2.79 0.5 2.8 0.5 2.81 0.5 2.82 0.5 2.83 0.5 2.84 0.5 2.85 0.5 2.86 0.5 2.87 0.6 2.88 0.6 2.89 0.6 2.9 0.6 2.91 0.5 2.92 0.6 2.93 0.6 2.94 0.6 2.95 0.7 2.96 0.7 2.97 0.6 2.98 0.5 2.99 0.5 3 0.5 3.01 0.5 3.02 0.5 3.03 0.5 3.04 0.6 3.05 0.6 3.06 0.7 3.07 0.7 3.08 0.7 3.09 0.7 3.1 0.6 3.11 0.6 3.12 0.6 3.13 0.6 3.14 0.5 3.15 0.5 3.16 0.5 3.17 0.5 3.18 0.5 3.19 0.5 3.2 0.5 3.21 0.5 3.22 0.5 3.23 0.6 3.24 0.7 3.25 0.7 3.26 0.7 3.27 1.0 3.28 0.7 3.29 0.7 3.3 0.7 3.31 0.7 3.32 0.6 3.33 0.5 3.34 0.5 3.35 0.8 3.36 0.8 3.37 0.8 3.38 0.8 3.39 0.5 3.4 0.5 3.41 0.5 3.42 0.6 3.43 0.6 3.44 0.6 3.45 0.7 3.46 1.0 3.47 0.6 3.48 0.6 3.49 0.6 3.5 0.6 3.51 0.6 3.52 0.7 3.53 0.7 3.54 0.6 3.55 0.5 3.56 0.5 3.57 0.8 3.58 0.8 3.59 0.8 3.6 0.5 3.61 0.5 3.62 0.6 3.63 0.6 3.64 0.7 3.65 0.7 3.66 1.0 3.67 1.0 3.68 1.0 3.69 0.7 3.7 0.7 3.71 0.7 3.72 0.6 3.73 0.5 3.74 0.5 3.75 0.5 3.76 0.5 3.77 0.5 3.78 0.5 3.79 0.6 3.8 0.6 3.81 0.6 3.82 0.6 3.83 0.7 3.84 0.7 3.85 1.0 3.86 1.0 3.87 0.6 3.88 1.0 3.89 1.0 3.9 0.7 3.91 0.7 3.92 0.6 3.93 0.6 3.94 0.6 3.95 0.7 3.96 0.7 3.97 0.7 3.98 0.7 3.99 0.7 4 0.7 4.01 0.6 4.02 0.7 4.03 0.7 4.04 0.7 4.05 0.7 4.06 0.6 4.07 0.6 4.08 0.6 4.09 0.6 4.1 0.6 4.11 0.6 4.12 0.6 4.13 0.7 4.14 1.0 4.15 1.0 4.16 0.6 4.17 1.0 4.18 1.0 4.19 1.0 4.2 1.0 4.21 0.7 4.22 0.7 4.23 0.6 4.24 0.5 4.25 0.8 4.26 0.9 4.27 0.9 4.28 0.8 4.29 0.5 4.3 0.5 4.31 0.6 4.32 0.6 4.33 0.7 4.34 1.0 4.35 1.0 4.36 1.0 4.37 1.0 4.38 1.0 4.39 0.7 4.4 0.6 4.41 0.6 4.42 0.8 4.43 0.9 4.44 0.9 4.45 0.8 4.46 0.5 4.47 0.5 4.48 0.6 4.49 0.6 4.5 0.7 4.51 0.7 4.52 0.7 4.53 0.7 4.54 0.7 4.55 0.6 4.56 0.7 4.57 0.7 4.58 0.7 4.59 0.3 4.6 0.3 4.61 0.3 4.62 0.1 4.63 0.1 4.64 0.2 4.65 0.1 4.66 0.1 4.67 0.3 4.68 0.1 4.69 0.3 4.7 0.3 4.71 0.1 4.72 0.3 4.73 0.1 4.74 0.3 4.75 0.3 4.76 0.1 4.77 0.2 4.78 0.2 4.79 0.2 4.8 0.2 4.81 0.1 4.82 0.3 4.83 0.3 4.84 0.1 4.85 0.1 4.86 0.1 4.87 0.1 4.88 0.1 4.89 0.3 4.9 0.3 4.91 0.2 4.92 0.1 4.93 0.3 4.94 0.3 4.95 0.3 4.96 0.3 4.97 0.3 4.98 0.1 4.99 0.1 5 0.2 5.01 0.2 5.02 0.3 5.03 0.1 5.04 0.1 5.05 0.3 5.06 0.3 5.07 0.1 5.08 0.1 5.09 0.1 5.1 0.1 5.11 0.1 5.12 0.1 5.13 0.1 5.14 0.2 5.15 0.2 5.16 0.1 5.17 0.1 5.18 0.1 5.19 0.1 5.2 0.3 5.21 0.3 5.22 0.3 5.23 0.3 5.24 0.3 5.25 0.1 5.26 0.1 5.27 0.1 5.28 0.2 5.29 0.2 5.3 0.2 5.31 0.2 5.32 0.2 5.33 0.2 5.34 0.2 5.35 0.2 5.36 0.7 5.37 0.7 5.38 0.7 5.39 0.7 5.4 0.7 5.41 0.7 5.42 0.7 5.43 0.7 5.44 0.7 5.45 0.7 5.46 0.7 5.47 0.7 5.48 0.7 5.49 0.7 5.5 0.7 5.51 0.7 5.52 0.7 5.53 0.7 5.54 0.7 5.55 0.7 5.56 0.7 5.57 0.7 5.58 0.7 5.59 0.7 5.6 0.7 5.61 0.7 5.62 0.7 5.63 0.7 5.64 0.7 5.65 0.7 5.66 0.7 5.67 0.7 5.68 0.7 5.69 0.7 5.7 0.7 5.71 0.7 5.72 0.7 5.73 0.7 5.74 0.7 5.75 0.7 5.76 0.7 5.77 0.7 5.78 0.7 5.79 0.7 5.8 0.7 5.81 0.7 5.82 0.7 5.83 0.7 5.84 0.7 5.85 0.7 5.86 0.7 5.87 0.7 5.88 0.7 5.89 0.7 5.9 0.7 5.91 0.7 5.92 0.7 5.93 0.7 5.94 0.7 5.95 0.8 5.96 0.7 5.97 0.7 5.98 0.7 5.99 0.8 6 0.9 6.01 0.9 6.02 0.6 6.03 0.6 6.04 0.8 6.05 0.9 6.06 0.8 6.07 0.8 6.08 0.9 6.09 0.9 6.1 0.8 6.11 0.5 6.12 0.6 6.13 0.6 6.14 0.6 6.15 0.7 6.16 0.7 6.17 0.7 6.18 0.6 6.19 0.6 6.2 0.6 6.21 0.6 6.22 0.6 6.23 0.6 6.24 0.6 6.25 0.6 6.26 0.6 6.27 0.6 6.28 0.7 6.29 0.6 6.3 0.6 6.31 0.7 6.32 0.7 6.33 0.7 6.34 0.7 6.35 0.7 6.36 0.6 6.37 0.6 6.38 0.6 6.39 0.6 6.4 0.6 6.41 0.6 6.42 0.6 6.43 0.6 6.44 0.6 6.45 0.6 6.46 0.5 6.47 0.6 6.48 0.6 6.49 0.6 6.5 0.6 6.51 0.6 6.52 0.6 6.53 0.7 6.54 0.7 6.55 1.0 6.56 1.0 6.57 0.6 6.58 1.0 6.59 1.0 6.6 0.7 6.61 0.6 6.62 0.8 6.63 0.8 6.64 0.9 6.65 0.8 6.66 0.6 6.67 0.6 6.68 0.7 6.69 0.6 6.7 0.6 6.71 0.7 6.72 0.7 6.73 0.7 6.74 0.7 6.75 0.7 6.76 0.6 6.77 0.7 6.78 0.7 6.79 0.7 6.8 0.8 6.81 0.8 6.82 0.9 6.83 0.9 6.84 0.9 6.85 0.9 6.86 0.8 6.87 0.8 6.88 0.7 6.89 0.6 6.9 0.6 6.91 0.7 6.92 0.7 6.93 0.7 6.94 0.7 6.95 0.8 6.96 0.8 6.97 0.8 6.98 0.8 6.99 0.8 7 0.8 7.01 0.8 7.02 0.8 7.03 0.8 7.04 0.8 7.05 0.8 7.06 0.8 7.07 0.8 7.08 0.8 7.09 0.8 7.1 0.7 7.11 0.7 7.12 0.8 7.13 0.8 7.14 0.9 7.15 0.9 7.16 0.9 7.17 0.8 7.18 0.9 7.19 0.6 7.2 0.6 7.21 0.6 7.22 0.7 7.23 0.6 7.24 0.6 7.25 0.8 7.26 0.7 7.27 0.6 7.28 0.7 7.29 0.8 7.3 0.8 7.31 0.8 7.32 0.8 7.33 0.8 7.34 0.8 7.35 0.8 7.36 0.8 7.37 0.9 7.38 0.9 7.39 0.9 7.4 0.9 7.41 0.9 7.42 0.8 7.43 0.9 7.44 0.9 7.45 0.8 7.46 0.8 7.47 0.8 7.48 0.8 7.49 0.8 7.5 0.8 7.51 0.8 7.52 0.8 7.53 0.8 7.54 0.8 7.55 0.8 7.56 0.8 7.57 0.8 7.58 0.8 7.59 0.8 7.6 0.8 7.61 0.8 7.62 0.8 7.63 0.8 7.64 0.8 7.65 0.8 7.66 0.9 7.67 0.9 7.68 0.9 7.69 0.9 7.7 0.9 7.71 0.9 7.72 0.8 7.73 0.9 7.74 0.8 7.75 0.8 7.76 0.8 7.77 0.8 7.78 0.8 7.79 0.8 7.8 0.8 7.81 0.8 7.82 0.9 7.83 0.9 7.84 0.9 7.85 0.9 7.86 0.9 7.87 0.9 7.88 0.9 7.89 0.9 7.9 0.8 7.91 0.8 7.92 0.8 7.93 0.8 7.94 0.8 7.95 0.8 7.96 0.8 7.97 0.8 7.98 0.8 7.99 0.8 8 0.9 8.01 0.8 8.02 0.8 8.03 0.8 8.04 0.8 8.05 0.8 8.06 0.9 8.07 0.8 8.08 0.8 8.09 0.8 8.1 0.9 8.11 0.9 8.12 0.9 8.13 0.8 8.14 0.8 8.15 0.8 8.16 0.8 8.17 0.8 8.18 0.9 8.19 0.9 8.2 0.9 8.21 0.8 8.22 0.9 8.23 0.9 8.24 0.9 8.25 0.9 8.26 0.9 8.27 0.8 8.28 0.8 8.29 0.8 8.3 0.8 8.31 0.8 8.32 0.8 8.33 0.8 8.34 0.8 8.35 0.9 8.36 0.9 8.37 0.9 8.38 0.9 8.39 0.9 8.4 0.9 8.41 0.9 8.42 0.9 8.43 0.9 8.44 0.9 8.45 0.9 8.46 0.9 8.47 0.9 8.48 0.9 8.49 0.9 8.5 0.9 8.51 0.9 8.52 0.9 8.53 0.9 8.54 0.9 8.55 0.9 8.56 0.9 8.57 0.9 8.58 0.9 8.59 0.9 8.6 0.9 8.61 0.9 8.62 0.9 8.63 0.3 8.64 0.3 8.65 0.3 8.66 0.8 8.67 0.6 8.68 0.7 8.69 0.6 8.7 0.6 8.71 0.6 8.72 0.6 8.73 0.6 8.74 0.9 8.75 0.9 8.76 0.8 8.77 0.8 8.78 0.8 8.79 0.8 8.8 0.8 8.81 0.8 8.82 0.8 8.83 0.8 8.84 0.8 8.85 0.8 8.86 0.7 8.87 0.8 8.88 0.7 8.89 0.8 8.9 0.8 8.91 0.8 8.92 0.8 8.93 0.8 8.94 0.8 8.95 0.8 8.96 0.8 8.97 0.8 8.98 0.8 8.99 0.8 9 0.7 9.01 0.7 9.02 0.7 9.03 0.7 9.04 0.7 9.05 0.7 9.06 0.8 9.07 0.9 9.08 0.8 9.09 0.8 9.1 0.7 9.11 0.8 9.12 0.8 9.13 0.8 9.14 0.7 9.15 0.8 9.16 0.8 9.17 0.8 9.18 0.7 9.19 0.7 9.2 0.7 9.21 0.7 9.22 0.7 9.23 0.7 9.24 0.7 9.25 0.7 9.26 0.8 9.27 0.7 9.28 0.7 9.29 0.7 9.3 0.7 9.31 0.8 9.32 0.8 9.33 0.8 9.34 0.8 9.35 0.8 9.36 0.7 9.37 0.7 9.38 0.7 9.39 0.7 9.4 0.7 9.41 0.7 9.42 0.7 9.43 0.7 9.44 0.8 9.45 0.8 9.46 0.8 9.47 0.7 9.48 0.8 9.49 0.8 9.5 0.8 9.51 0.8 9.52 0.8 9.53 0.8 9.54 0.8 9.55 0.8 9.56 0.7 9.57 0.7 9.58 0.6 9.59 0.7 9.6 0.7 9.61 0.7 9.62 0.6 9.63 0.7 9.64 0.7 9.65 0.7 9.66 0.8 9.67 0.9 9.68 0.9 9.69 0.8 9.7 0.9 9.71 0.9 9.72 0.9 9.73 0.9 9.74 0.8 9.75 0.8 9.76 0.7 9.77 0.7 9.78 0.7 9.79 0.7 9.8 0.7 9.81 0.6 9.82 0.7 9.83 0.7 9.84 0.7 9.85 0.7 9.86 0.7 9.87 0.8 9.88 0.8 9.89 0.8 9.9 0.9 9.91 0.9 9.92 0.8 9.93 0.8 9.94 0.9 9.95 0.9 9.96 0.8 9.97 0.7 9.98 0.7 9.99 0.7 10 0.7 10.01 0.6 10.02 0.7 10.03 0.6 10.04 0.7 10.05 0.7 10.06 0.8 10.07 0.8 10.08 0.9 10.09 0.9 10.1 0.6 10.11 0.6 10.12 0.9 10.13 0.9 10.14 0.9 10.15 0.9 10.16 0.8 10.17 0.7 10.18 0.6 10.19 0.6 10.2 0.6 10.21 0.6 10.22 0.6 10.23 0.7 10.24 0.6 10.25 0.7 10.26 0.7 10.27 0.8 10.28 0.9 10.29 0.9 10.3 0.9 10.31 0.8 10.32 0.7 10.33 0.7 10.34 0.7 10.35 0.7 10.36 0.3 10.37 0.3 10.38 0.3 10.39 0.3 10.4 0.3 10.41 0.3 10.42 0.3 10.43 0.3 10.44 0.3 10.45 0.3 10.46 0.3 10.47 0.3 10.48 0.3 10.49 0.3 10.5 0.3 10.51 0.3 10.52 0.3 10.53 0.3 10.54 0.3 10.55 0.3 10.56 0.3 10.57 0.3 10.58 0.3 10.59 0.3 10.6 0.3 10.61 0.3 10.62 0.3 10.63 0.3 10.64 0.3 10.65 0.3 10.66 0.3 10.67 0.3 10.68 0.3 10.69 0.3 10.7 0.3 10.71 0.3 10.72 0.3 10.73 0.3 10.74 0.3 10.75 0.3 10.76 0.3 10.77 0.3 10.78 0.3 10.79 0.3 10.8 0.3 10.81 0.3 10.82 0.3 10.83 0.3 10.84 0.3 10.85 0.3 10.86 0.3 10.87 0.3 10.88 0.3 10.89 0.3 10.9 0.3 10.91 0.3 10.92 0.3 10.93 0.3 10.94 0.3 10.95 0.3 10.96 0.3 10.97 0.3 10.98 0.3 10.99 0.3 11 0.3 11.01 0.2 11.02 0.2 11.03 0.2 11.04 0.2 11.05 0.2 11.06 0.2 11.07 0.2 11.08 0.2 11.09 0.2 11.1 0.2 11.11 0.2 11.12 0.2 11.13 0.2 11.14 0.2 11.15 0.2 11.16 0.2 11.17 0.2 11.18 0.2 11.19 0.2 11.2 0.2 11.21 0.8 11.22 0.8 11.23 0.7 11.24 0.7 11.25 0.7 11.26 0.7 11.27 0.8 11.28 0.8 11.29 0.8 11.3 0.8 11.31 0.8 11.32 0.8 11.33 0.8 11.34 0.8 11.35 0.7 11.36 0.7 11.37 0.7 11.38 0.8 11.39 0.8 11.4 0.8 11.41 0.9 11.42 0.9 11.43 0.9 11.44 0.9 11.45 0.8 11.46 0.7 11.47 0.6 11.48 0.7 11.49 0.7 11.5 0.7 11.51 0.7 11.52 0.7 11.53 0.8 11.54 0.8 11.55 0.8 11.56 0.8 11.57 0.8 11.58 0.9 11.59 0.9 11.6 0.9 11.61 0.8 11.62 0.8 11.63 0.8 11.64 0.8 11.65 0.9 11.66 0.9 11.67 0.9 11.68 0.8 11.69 0.7 11.7 0.8 11.71 0.7 11.72 0.6 11.73 0.7 11.74 0.7 11.75 0.6 11.76 0.8 11.77 0.2 11.78 0.2 11.79 0.2 11.8 0.2 11.81 0.2 11.82 0.2 11.83 0.2 11.84 0.2 11.85 0.2 11.86 0.2 11.87 0.2 11.88 0.2 11.89 0.2 11.9 0.5 11.91 1.0 11.92 0.9 11.93 0.9 11.94 0.9 11.95 0.9 11.96 0.9 11.97 0.9 11.98 0.6 11.99 1.0 12 0.7 12.01 0.6 12.02 0.7 12.03 0.7 12.04 0.7 12.05 0.7 12.06 0.7 12.07 0.7 12.08 0.7 12.09 0.7 12.1 0.7 12.11 0.6 12.12 0.6 12.13 0.6 12.14 0.6 12.15 0.6 12.16 0.7 12.17 0.7 12.18 0.7 12.19 0.7 12.2 0.6 12.21 0.6 12.22 0.6 12.23 0.6 12.24 0.7 12.25 0.7 12.26 0.7 12.27 0.7 12.28 0.7 12.29 0.7 12.3 0.7 12.31 0.7 12.32 0.7 12.33 0.6 12.34 0.6 12.35 0.6 12.36 0.6 12.37 0.7 12.38 0.7 12.39 0.7 12.4 0.5 12.41 0.5 12.42 0.6 12.43 0.6 12.44 0.6 12.45 0.6 12.46 0.7 12.47 0.6 12.48 0.6 12.49 0.6 12.5 0.6 12.51 0.6 12.52 0.6 12.53 0.6 12.54 0.6 12.55 0.6 12.56 0.6 12.57 0.7 12.58 0.7 12.59 0.6 12.6 0.6 12.61 0.6 12.62 0.6 12.63 0.6 12.64 0.6 12.65 0.6 12.66 0.6 12.67 0.6 12.68 0.6 12.69 0.6 12.7 0.6 12.71 0.6 12.72 0.7 12.73 0.6 12.74 0.6 12.75 0.6 12.76 0.6 12.77 0.6 12.78 0.6 12.79 0.6 12.8 0.6 12.81 0.6 12.82 0.6 12.83 0.6 12.84 0.6 12.85 0.6 12.86 0.6 12.87 0.6 12.88 0.7 12.89 0.6 12.9 0.6 12.91 0.6 12.92 0.6 12.93 0.7 12.94 0.6 12.95 0.6 12.96 0.6 12.97 0.6 12.98 0.6 12.99 0.6 13 0.6 13.01 0.6 13.02 0.7 13.03 0.6 13.04 0.6 13.05 0.6 13.06 0.5 13.07 0.8 13.08 0.8 13.09 0.8 13.1 0.8 13.11 0.6 13.12 0.7 13.13 1.0 13.14 0.9 13.15 0.8 13.16 0.7 13.17 0.7 13.18 0.7 13.19 0.7 13.2 0.7 13.21 0.8 13.22 0.8 13.23 0.8 13.24 0.7 13.25 0.7 13.26 0.8 13.27 0.7 13.28 0.7 13.29 0.7 13.3 0.7 13.31 0.7 13.32 0.7 13.33 0.8 13.34 0.7 13.35 0.7 13.36 0.7 13.37 0.7 13.38 0.7 13.39 0.7 13.4 0.7 13.41 0.7 13.42 0.7 13.43 0.7 13.44 0.8 13.45 0.7 13.46 0.7 13.47 0.7 13.48 0.7 13.49 0.7 13.5 0.7 13.51 0.8 13.52 0.8 13.53 0.7 13.54 0.7 13.55 0.7 13.56 0.7 13.57 0.7 13.58 0.7 13.59 0.7 13.6 0.7 13.61 0.7 13.62 0.7 13.63 0.7 13.64 0.7 13.65 0.7 13.66 0.7 13.67 0.7 13.68 0.7 13.69 0.7 13.7 0.7 13.71 0.7 13.72 0.7 13.73 0.7 13.74 0.7 13.75 0.7 13.76 0.7 13.77 0.7 13.78 0.7 13.79 0.7 13.8 0.7 13.81 0.7 13.82 0.7 13.83 0.7 13.84 0.7 13.85 0.7 13.86 0.7 13.87 0.7 13.88 0.7 13.89 0.7 13.9 0.7 13.91 0.7 13.92 0.7 13.93 0.7 13.94 0.7 13.95 0.7 13.96 0.7 13.97 0.7 13.98 0.7 13.99 0.7 14 0.7 14.01 0.7 14.02 0.7 14.03 0.7 14.04 0.7 14.05 0.7 14.06 0.7 14.07 0.7 14.08 0.7 14.09 0.7 14.1 0.7 14.11 0.7 14.12 0.7 14.13 0.7 14.14 0.7 14.15 0.7 14.16 0.7 14.17 0.7 14.18 0.7 14.19 0.7 14.2 0.7 14.21 0.7 14.22 0.7 14.23 0.7 14.24 0.7 14.25 0.7 14.26 0.7 14.27 0.7 14.28 0.7 14.29 0.7 14.3 0.7 14.31 0.7 14.32 0.7 14.33 0.7 14.34 0.7 14.35 0.7 14.36 0.7 14.37 0.7 14.38 0.7 14.39 0.7 14.4 0.7 14.41 0.7 14.42 0.7 14.43 0.7 14.44 0.7 14.45 0.7 14.46 0.7 14.47 0.7 14.48 0.7 14.49 0.7 14.5 0.7 14.51 0.7 14.52 0.7 14.53 0.7 14.54 0.7 14.55 0.7 14.56 0.7 14.57 0.7 14.58 0.7 14.59 0.7 14.6 0.7 14.61 0.7 14.62 0.8 14.63 0.7 14.64 0.7 14.65 0.8 14.66 0.8 14.67 0.7 14.68 0.7 14.69 0.7 14.7 0.7 14.71 0.7 14.72 0.7 14.73 0.7 14.74 0.7 14.75 0.7 14.76 0.7 14.77 0.7 14.78 0.7 14.79 0.7 14.8 0.7 14.81 0.7 14.82 0.7 14.83 0.8 14.84 0.8 14.85 0.7 14.86 0.7 14.87 0.8 14.88 0.7 14.89 0.7 14.9 0.7 14.91 0.7 14.92 0.7 14.93 0.7 14.94 0.7 14.95 0.7 14.96 0.7 14.97 0.7 14.98 0.7 14.99 0.7 15 0.7 15.01 0.7 15.02 0.7 15.03 0.7 15.04 0.8 15.05 0.7 15.06 0.7 15.07 0.7 15.08 0.7 15.09 0.7 15.1 0.7 15.11 0.7 15.12 0.7 15.13 0.7 15.14 0.7 15.15 0.7 15.16 0.7 15.17 0.7 15.18 0.7 15.19 0.7 15.2 0.7 15.21 0.7 15.22 0.8 15.23 0.7 15.24 0.7 15.25 0.7 15.26 0.7 15.27 0.7 15.28 0.3 15.29 0.3 15.3 0.3 15.31 0.2 15.32 0.2 15.33 0.2 15.34 0.2 15.35 0.2 15.36 0.2 15.37 0.2 15.38 0.2 15.39 0.2 15.4 0.2 15.41 0.2 15.42 0.2 15.43 0.2 15.44 0.2 15.45 0.2 15.46 0.2 15.47 0.2 15.48 0.2 15.49 0.2 15.5 0.2 15.51 0.2 15.52 0.2 15.53 0.2 15.54 0.2 15.55 0.2 15.56 0.2 15.57 0.2 15.58 0.2 15.59 0.2 15.6 0.2 15.61 0.2 15.62 0.2 15.63 0.2 15.64 0.2 15.65 0.2 15.66 0.2 15.67 0.2 15.68 0.2 15.69 0.2 15.7 0.2 15.71 0.2 15.72 0.2 15.73 0.2 15.74 0.2 15.75 0.2 15.76 0.2 15.77 0.2 15.78 0.2 15.79 0.1 15.8 0.1 15.81 0.1 15.82 0.1 15.83 0.1 15.84 0.1 15.85 0.1 15.86 0.1 15.87 0.1 15.88 0.1 15.89 0.1 15.9 0.1 15.91 0.1 15.92 0.1 15.93 0.1 15.94 0.1 15.95 0.1 15.96 0.2 15.97 0.2 15.98 0.2 15.99 0.2 16 0.2 16.01 0.2 16.02 0.2 16.03 0.2 16.04 0.2 16.05 0.2 16.06 0.2 16.07 0.2 16.08 0.2 16.09 0.2 16.1 0.2 16.11 0.2 16.12 0.2 16.13 0.2 16.14 0.2 16.15 0.2 16.16 0.2 16.17 0.2 16.18 0.2 16.19 0.2 16.2 0.2 16.21 0.2 16.22 0.2 16.23 0.2 16.24 0.2 16.25 0.2 16.26 0.2 16.27 0.2 16.28 0.2 16.29 0.2 16.3 0.2 16.31 0.2 16.32 0.2 16.33 0.2 16.34 0.2 16.35 0.7 16.36 0.7 16.37 0.8 16.38 0.6 16.39 0.7 16.4 0.8 16.41 0.8 16.42 0.8 16.43 0.8 16.44 0.7 16.45 0.8 16.46 0.8 16.47 0.8 16.48 0.8 16.49 0.7 16.5 0.7 16.51 0.7 16.52 0.7 16.53 0.7 16.54 0.8 16.55 0.8 16.56 0.8 16.57 0.7 16.58 0.8 16.59 0.7 16.6 0.8 16.61 0.8 16.62 0.8 16.63 0.8 16.64 0.9 16.65 0.8 16.66 0.8 16.67 0.7 16.68 0.7 16.69 0.7 16.7 0.8 16.71 0.8 16.72 0.7 16.73 0.8 16.74 0.8 16.75 0.7 16.76 0.8 16.77 0.7 16.78 0.7 16.79 0.8 16.8 0.7 16.81 0.7 16.82 0.7 16.83 0.6 16.84 0.7 16.85 0.6 16.86 0.7 16.87 0.7 16.88 0.7 16.89 0.7 16.9 0.8 16.91 0.7 16.92 0.7 16.93 0.7 16.94 0.6 16.95 0.9 16.96 0.9 16.97 0.9 16.98 0.7 16.99 0.9 17 0.9 17.01 0.8 17.02 0.9 17.03 1.0 17.04 0.7 17.05 0.5 17.06 1.0 17.07 0.6 17.08 0.6 17.09 0.7 17.1 0.6 17.11 1.0 17.12 1.0 17.13 0.7 17.14 0.6 17.15 0.5 17.16 0.7 17.17 1.0 17.18 0.7 17.19 0.5 17.2 0.5 17.21 0.5 17.22 0.6 17.23 0.7 17.24 0.6 17.25 0.5 17.26 0.6 17.27 0.7 17.28 0.7 17.29 0.6 17.3 0.6 17.31 0.6 17.32 0.6 17.33 0.7 17.34 0.6 17.35 0.6 17.36 0.5 17.37 0.6 17.38 0.6 17.39 0.6 17.4 0.6 17.41 0.5 17.42 0.5 17.43 0.6 17.44 0.6 17.45 0.6 17.46 0.6 17.47 0.6 17.48 0.6 17.49 0.6 17.5 0.6 17.51 0.6 17.52 0.6 17.53 0.6 17.54 0.7 17.55 0.6 17.56 0.2 17.57 0.2 17.58 0.2 17.59 0.2 17.6 0.2 17.61 0.2 17.62 0.2 17.63 0.2 17.64 0.1 17.65 0.3 17.66 0.3 17.67 0.1 17.68 0.8 17.69 0.6 17.7 0.7 17.71 0.6 17.72 0.5 17.73 0.7 17.74 0.7 17.75 0.6 17.76 0.6 17.77 0.6 17.78 0.6 17.79 0.6 17.8 0.7 17.81 0.6 17.82 0.6 17.83 0.6 17.84 0.5 17.85 0.5 17.86 0.5 17.87 0.6 17.88 0.6 17.89 0.6 17.9 0.6 17.91 0.6 17.92 0.6 17.93 0.6 17.94 0.6 17.95 0.6 17.96 0.6 17.97 0.6 17.98 0.6 17.99 0.7 18 0.6 18.01 0.6 18.02 0.6 18.03 0.6 18.04 0.7 18.05 0.7 18.06 0.7 18.07 0.6 18.08 0.6 18.09 0.6 18.1 0.6 18.11 0.6 18.12 0.6 18.13 0.6 18.14 0.6 18.15 0.7 18.16 0.6 18.17 0.7 18.18 0.7 18.19 0.7 18.2 1.0 18.21 1.0 18.22 1.0 18.23 1.0 18.24 1.0 18.25 1.0 18.26 0.7 18.27 0.5 18.28 0.5 18.29 0.8 18.3 0.9 18.31 0.9 18.32 0.6 18.33 1.0 18.34 0.8 18.35 0.9 18.36 1.0 18.37 0.9 18.38 1.0 18.39 1.0 18.4 1.0 18.41 0.9 18.42 0.8 18.43 0.7 18.44 0.8 18.45 0.8 18.46 0.8 18.47 0.8 18.48 0.3 18.49 0.3 18.5 0.3 18.51 0.3 18.52 0.3 18.53 0.3 18.54 0.3 18.55 0.3 18.56 0.3 18.57 0.3 18.58 0.3 18.59 0.3 18.6 0.3 18.61 0.3 18.62 0.3 18.63 0.3 18.64 0.3 18.65 0.3 18.66 0.3 18.67 0.3 18.68 0.8 18.69 0.8 18.7 0.8 18.71 0.9 18.72 0.9 18.73 0.8 18.74 0.8 18.75 0.8 18.76 0.8 18.77 0.8 18.78 0.8 18.79 0.7 18.8 0.7 18.81 0.8 18.82 0.8 18.83 0.8 18.84 0.8 18.85 0.8 18.86 0.8 18.87 0.8 18.88 0.8 18.89 0.8 18.9 0.8 18.91 0.8 18.92 0.8 18.93 0.8 18.94 0.8 18.95 0.9 18.96 0.8 18.97 0.8 18.98 0.8 18.99 0.8 19 0.8 19.01 0.8 19.02 0.8 19.03 0.7 19.04 0.7 19.05 0.8 19.06 0.8 19.07 0.8 19.08 0.8 19.09 0.8 19.1 0.8 19.11 0.8 19.12 0.9 19.13 0.9 19.14 0.9 19.15 0.9 19.16 0.8 19.17 0.9 19.18 0.9 19.19 0.9 19.2 1.0 19.21 0.9 19.22 0.9 19.23 0.9 19.24 0.9 19.25 0.9 19.26 0.9 19.27 0.9 19.28 0.9 19.29 0.9 19.3 0.8 19.31 0.8 19.32 0.9 19.33 0.9 19.34 0.8 19.35 0.8 19.36 0.9 19.37 0.9 19.38 0.9 19.39 0.9 19.4 0.8 19.41 0.8 19.42 0.9 19.43 0.9 19.44 0.9 19.45 0.9 19.46 0.8 19.47 0.9 19.48 0.9 19.49 0.9 19.5 0.8 19.51 0.8 19.52 0.8 19.53 0.8 19.54 0.9 19.55 0.8 19.56 0.8 19.57 0.8 19.58 0.7 19.59 0.8 19.6 0.9 19.61 1.0 19.62 1.0 19.63 1.0 19.64 1.0 19.65 1.0 19.66 1.0 19.67 0.9 19.68 0.9 19.69 0.9 19.7 0.8 19.71 0.9 19.72 0.9 19.73 0.8 19.74 0.8 19.75 0.8 19.76 0.8 19.77 0.8 19.78 0.8 19.79 0.9 19.8 0.8 19.81 0.8 19.82 0.7 19.83 0.8 19.84 0.9 19.85 1.0 19.86 1.0 19.87 0.9 19.88 0.9 19.89 0.9 19.9 0.9 19.91 0.9 19.92 0.9 19.93 0.8 19.94 0.9 19.95 0.8 19.96 0.9 19.97 0.8 19.98 0.7 19.99 0.7 20 0.8 20.01 0.9 20.02 0.8 20.03 0.8 20.04 0.9 20.05 0.9 20.06 1.0 20.07 1.0 20.08 0.9 20.09 0.8 20.1 0.9 20.11 0.9 20.12 1.0 20.13 1.0 20.14 0.9 20.15 0.8 20.16 0.8 20.17 0.8 20.18 1.0 20.19 0.8 20.2 0.8 20.21 0.7 20.22 0.7 20.23 0.8 20.24 0.9 20.25 0.8 20.26 0.9 20.27 0.7 20.28 0.7 20.29 0.8 20.3 1.0 20.31 1.0 20.32 0.9 20.33 0.8 20.34 0.8 20.35 0.8 20.36 0.9 20.37 0.9 20.38 0.8 20.39 0.7 20.4 0.2 20.41 0.2 20.42 0.2 20.43 0.2 20.44 0.2 20.45 0.2 20.46 0.2 20.47 0.2 20.48 0.2 20.49 0.2 20.5 0.2 20.51 0.2 20.52 0.2 20.53 0.2 20.54 0.2 20.55 0.2 20.56 0.2 20.57 0.2 20.58 0.2 20.59 0.2 20.6 0.2 20.61 0.2 20.62 0.2 20.63 0.2 20.64 0.2 20.65 0.2 20.66 0.2 20.67 0.2 20.68 0.2 20.69 0.2 20.7 0.2 20.71 0.2 20.72 0.2 20.73 0.2 20.74 0.2 20.75 0.2 20.76 0.2 20.77 0.2 20.78 0.2 20.79 0.2 20.8 0.2 20.81 0.2 20.82 0.0 20.83 0.0 20.84 0.1 20.85 0.1 20.86 0.1 20.87 0.1 20.88 0.1 20.89 0.2 20.9 0.3 20.91 0.3 20.92 0.3 20.93 0.1 20.94 0.1 20.95 0.1 20.96 0.1 20.97 0.0 20.98 0.0 20.99 0.1 21 0.2 21.01 0.2 21.02 0.2 21.03 0.2 21.04 0.2 21.05 0.2 mir_eval-0.8.2/tests/data/multipitch/000077500000000000000000000000001475740344600175725ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/multipitch/est00.txt000066400000000000000000002727031475740344600213010ustar00rootroot00000000000000# A comment 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.30 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.40 0.41 0.42 0.43 0.44 0.45 0.46 0.47 0.48 0.49 0.50 0.51 0.52 0.53 0.54 0.55 0.56 0.57 0.58 0.59 415.30 0.60 415.30 0.61 415.30 0.62 415.30 0.63 415.30 0.64 415.30 0.65 415.30 0.66 415.30 0.67 415.30 0.68 415.30 0.69 415.30 0.70 415.30 0.71 415.30 0.72 415.30 0.73 415.30 0.74 415.30 0.75 415.30 0.76 415.30 0.77 415.30 0.78 415.30 0.79 415.30 0.80 415.30 0.81 415.30 0.82 415.30 0.83 415.30 0.84 415.30 0.85 415.30 0.86 415.30 493.88 0.87 415.30 493.88 0.88 415.30 493.88 0.89 415.30 493.88 0.90 415.30 493.88 0.91 415.30 493.88 0.92 415.30 493.88 0.93 415.30 493.88 0.94 415.30 493.88 0.95 415.30 493.88 0.96 415.30 493.88 0.97 415.30 493.88 0.98 415.30 493.88 0.99 415.30 493.88 1.00 415.30 493.88 1.01 415.30 493.88 1.02 415.30 493.88 1.03 415.30 493.88 1.04 415.30 493.88 1.05 415.30 493.88 1.06 415.30 493.88 1.07 415.30 1.08 415.30 1.09 415.30 1.10 329.63 415.30 1.11 329.63 415.30 1.12 329.63 415.30 1.13 329.63 415.30 1.14 329.63 415.30 1.15 329.63 415.30 1.16 329.63 1.17 329.63 1.18 329.63 1.19 329.63 1.20 329.63 1.21 329.63 1.22 329.63 1.23 329.63 1.24 329.63 1.25 329.63 1.26 329.63 1.27 329.63 1.28 329.63 1.29 329.63 1.30 329.63 1.31 329.63 1.32 329.63 1.33 329.63 415.30 1.34 329.63 415.30 1.35 329.63 415.30 1.36 329.63 415.30 1.37 329.63 415.30 1.38 329.63 415.30 1.39 329.63 415.30 1.40 329.63 415.30 1.41 329.63 415.30 1.42 329.63 415.30 1.43 329.63 415.30 1.44 329.63 415.30 1.45 329.63 415.30 1.46 329.63 1.47 329.63 1.48 329.63 1.49 329.63 1.50 329.63 1.51 329.63 1.52 329.63 1.53 329.63 1.54 329.63 415.30 1.55 329.63 415.30 1.56 415.30 1.57 415.30 1.58 415.30 1.59 415.30 1.60 415.30 1.61 415.30 1.62 415.30 1.63 329.63 415.30 1.64 329.63 415.30 1.65 329.63 415.30 1.66 329.63 415.30 1.67 329.63 415.30 1.68 329.63 415.30 1.69 329.63 415.30 1.70 329.63 415.30 1.71 329.63 415.30 1.72 329.63 415.30 1.73 329.63 415.30 1.74 415.30 1.75 415.30 1.76 415.30 1.77 415.30 1.78 415.30 1.79 415.30 1.80 415.30 1.81 415.30 1.82 329.63 415.30 1.83 329.63 415.30 1.84 329.63 415.30 1.85 329.63 415.30 1.86 329.63 415.30 1.87 329.63 415.30 1.88 329.63 415.30 1.89 329.63 415.30 1.90 329.63 415.30 1.91 329.63 415.30 1.92 329.63 415.30 1.93 329.63 415.30 1.94 329.63 415.30 1.95 329.63 415.30 1.96 329.63 415.30 1.97 329.63 415.30 1.98 329.63 415.30 1.99 329.63 415.30 2.00 329.63 415.30 2.01 329.63 415.30 2.02 415.30 2.03 415.30 2.04 415.30 2.05 415.30 2.06 415.30 2.07 415.30 2.08 415.30 2.09 415.30 2.10 415.30 2.11 415.30 2.12 415.30 2.13 415.30 2.14 415.30 2.15 415.30 2.16 415.30 2.17 415.30 2.18 415.30 2.19 415.30 2.20 415.30 2.21 415.30 2.22 415.30 2.23 415.30 2.24 415.30 2.25 415.30 2.26 415.30 2.27 415.30 2.28 415.30 2.29 415.30 2.30 415.30 2.31 415.30 2.32 415.30 2.33 415.30 2.34 415.30 2.35 415.30 2.36 415.30 2.37 415.30 2.38 415.30 2.39 415.30 2.40 415.30 2.41 415.30 2.42 415.30 2.43 415.30 2.44 311.13 415.30 2.45 311.13 415.30 2.46 311.13 415.30 2.47 311.13 415.30 2.48 311.13 415.30 2.49 311.13 415.30 2.50 311.13 415.30 2.51 311.13 415.30 2.52 311.13 415.30 2.53 311.13 415.30 2.54 311.13 415.30 2.55 311.13 415.30 2.56 311.13 415.30 2.57 311.13 415.30 2.58 311.13 2.59 311.13 2.60 311.13 2.61 311.13 415.30 2.62 311.13 415.30 2.63 311.13 415.30 2.64 311.13 415.30 2.65 311.13 415.30 2.66 311.13 415.30 2.67 311.13 415.30 2.68 311.13 415.30 2.69 311.13 415.30 2.70 311.13 415.30 2.71 311.13 415.30 2.72 311.13 415.30 2.73 311.13 415.30 2.74 311.13 415.30 2.75 311.13 415.30 2.76 311.13 415.30 2.77 311.13 415.30 2.78 311.13 415.30 2.79 311.13 415.30 2.80 311.13 415.30 2.81 311.13 415.30 2.82 311.13 415.30 2.83 311.13 415.30 2.84 311.13 415.30 2.85 311.13 415.30 2.86 311.13 415.30 2.87 311.13 415.30 2.88 311.13 415.30 2.89 311.13 415.30 2.90 415.30 2.91 415.30 2.92 415.30 2.93 415.30 2.94 415.30 2.95 415.30 2.96 415.30 2.97 415.30 2.98 311.13 415.30 2.99 311.13 415.30 3.00 246.94 311.13 415.30 3.01 246.94 311.13 415.30 3.02 246.94 311.13 415.30 3.03 246.94 311.13 415.30 3.04 246.94 415.30 3.05 246.94 415.30 3.06 246.94 415.30 3.07 246.94 415.30 3.08 246.94 415.30 3.09 246.94 415.30 3.10 246.94 415.30 3.11 246.94 415.30 3.12 246.94 415.30 3.13 246.94 415.30 3.14 246.94 415.30 3.15 246.94 415.30 3.16 246.94 415.30 3.17 246.94 415.30 3.18 246.94 415.30 3.19 246.94 415.30 3.20 246.94 415.30 3.21 246.94 3.22 246.94 3.23 246.94 3.24 246.94 3.25 246.94 3.26 246.94 3.27 246.94 3.28 246.94 3.29 246.94 3.30 246.94 3.31 246.94 3.32 246.94 3.33 246.94 3.34 246.94 3.35 246.94 3.36 246.94 3.37 246.94 3.38 246.94 3.39 246.94 3.40 246.94 3.41 246.94 3.42 246.94 3.43 246.94 3.44 246.94 3.45 246.94 3.46 246.94 493.88 3.47 246.94 493.88 3.48 246.94 493.88 3.49 246.94 493.88 3.50 246.94 493.88 3.51 246.94 493.88 3.52 246.94 493.88 3.53 246.94 3.54 246.94 3.55 3.56 3.57 3.58 3.59 3.60 3.61 3.62 3.63 3.64 3.65 311.13 493.88 3.66 311.13 493.88 3.67 311.13 493.88 3.68 311.13 493.88 3.69 311.13 493.88 3.70 311.13 493.88 3.71 311.13 493.88 3.72 311.13 493.88 3.73 311.13 493.88 3.74 311.13 493.88 739.99 3.75 311.13 493.88 739.99 3.76 493.88 739.99 3.77 493.88 739.99 987.77 3.78 493.88 739.99 987.77 3.79 493.88 739.99 987.77 3.80 493.88 739.99 987.77 3.81 493.88 739.99 987.77 3.82 493.88 739.99 987.77 3.83 493.88 739.99 987.77 3.84 493.88 739.99 987.77 3.85 493.88 739.99 987.77 3.86 493.88 739.99 3.87 493.88 739.99 3.88 311.13 493.88 739.99 3.89 311.13 493.88 739.99 3.90 311.13 493.88 739.99 3.91 311.13 493.88 739.99 3.92 311.13 493.88 739.99 3.93 311.13 493.88 739.99 3.94 311.13 493.88 739.99 3.95 311.13 493.88 739.99 3.96 311.13 493.88 739.99 3.97 311.13 3.98 311.13 3.99 311.13 4.00 4.01 4.02 4.03 4.04 4.05 4.06 4.07 4.08 4.09 4.10 4.11 4.12 4.13 4.14 311.13 4.15 311.13 4.16 207.65 311.13 4.17 207.65 311.13 4.18 207.65 311.13 4.19 207.65 311.13 4.20 207.65 311.13 4.21 207.65 311.13 4.22 207.65 311.13 4.23 207.65 4.24 207.65 4.25 207.65 4.26 207.65 4.27 207.65 4.28 207.65 311.13 4.29 207.65 311.13 4.30 207.65 311.13 4.31 207.65 311.13 4.32 207.65 311.13 4.33 207.65 311.13 4.34 207.65 311.13 4.35 207.65 311.13 932.33 4.36 207.65 311.13 932.33 4.37 207.65 311.13 932.33 4.38 207.65 311.13 932.33 4.39 207.65 311.13 932.33 4.40 207.65 311.13 932.33 4.41 207.65 311.13 4.42 207.65 311.13 4.43 207.65 311.13 4.44 207.65 311.13 4.45 207.65 311.13 4.46 207.65 311.13 932.33 4.47 207.65 311.13 932.33 4.48 207.65 311.13 932.33 4.49 207.65 311.13 932.33 4.50 207.65 311.13 932.33 4.51 207.65 311.13 932.33 4.52 207.65 311.13 932.33 4.53 311.13 932.33 4.54 311.13 932.33 4.55 311.13 932.33 4.56 311.13 932.33 4.57 311.13 932.33 4.58 311.13 932.33 4.59 311.13 932.33 4.60 207.65 246.94 311.13 932.33 4.61 207.65 246.94 311.13 932.33 4.62 207.65 246.94 311.13 932.33 4.63 207.65 246.94 311.13 932.33 4.64 207.65 246.94 311.13 932.33 4.65 207.65 246.94 311.13 932.33 4.66 207.65 246.94 311.13 932.33 4.67 311.13 932.33 4.68 311.13 932.33 4.69 311.13 932.33 4.70 311.13 932.33 4.71 311.13 932.33 4.72 311.13 932.33 4.73 311.13 932.33 4.74 311.13 932.33 4.75 311.13 932.33 4.76 311.13 932.33 4.77 311.13 932.33 4.78 311.13 932.33 4.79 311.13 932.33 4.80 311.13 932.33 4.81 311.13 932.33 4.82 311.13 932.33 4.83 311.13 932.33 4.84 311.13 932.33 4.85 311.13 932.33 4.86 311.13 932.33 4.87 311.13 932.33 4.88 311.13 932.33 4.89 311.13 932.33 4.90 311.13 932.33 4.91 311.13 932.33 4.92 311.13 932.33 4.93 311.13 932.33 4.94 311.13 932.33 4.95 311.13 932.33 4.96 311.13 932.33 4.97 311.13 932.33 4.98 311.13 932.33 4.99 311.13 5.00 311.13 5.01 311.13 5.02 932.33 5.03 932.33 5.04 932.33 5.05 932.33 5.06 932.33 5.07 932.33 5.08 932.33 5.09 932.33 5.10 932.33 5.11 138.59 5.12 138.59 5.13 138.59 5.14 138.59 5.15 138.59 5.16 138.59 5.17 138.59 5.18 5.19 5.20 5.21 5.22 5.23 5.24 5.25 5.26 5.27 5.28 5.29 5.30 5.31 5.32 5.33 5.34 5.35 5.36 5.37 5.38 5.39 5.40 5.41 5.42 5.43 5.44 5.45 5.46 5.47 5.48 5.49 5.50 5.51 5.52 5.53 5.54 5.55 5.56 5.57 5.58 5.59 5.60 5.61 5.62 5.63 5.64 5.65 5.66 5.67 5.68 5.69 5.70 5.71 5.72 5.73 5.74 5.75 5.76 5.77 5.78 5.79 5.80 5.81 5.82 5.83 5.84 5.85 5.86 5.87 5.88 5.89 5.90 5.91 5.92 5.93 5.94 5.95 5.96 5.97 5.98 5.99 6.00 6.01 6.02 6.03 6.04 6.05 6.06 6.07 6.08 6.09 246.94 6.10 246.94 6.11 246.94 6.12 246.94 6.13 246.94 6.14 246.94 6.15 246.94 6.16 246.94 6.17 246.94 6.18 246.94 6.19 246.94 6.20 246.94 6.21 246.94 6.22 246.94 6.23 246.94 6.24 246.94 6.25 246.94 6.26 246.94 6.27 246.94 6.28 246.94 6.29 246.94 6.30 246.94 6.31 246.94 6.32 6.33 6.34 6.35 6.36 6.37 6.38 6.39 6.40 6.41 6.42 6.43 6.44 6.45 6.46 6.47 6.48 6.49 6.50 6.51 6.52 6.53 6.54 6.55 6.56 6.57 6.58 6.59 6.60 6.61 6.62 6.63 6.64 6.65 659.26 6.66 659.26 6.67 659.26 6.68 659.26 6.69 659.26 6.70 659.26 6.71 659.26 6.72 659.26 6.73 659.26 6.74 659.26 6.75 659.26 6.76 6.77 6.78 6.79 6.80 6.81 493.88 659.26 6.82 493.88 659.26 6.83 493.88 659.26 6.84 493.88 659.26 6.85 493.88 659.26 6.86 493.88 659.26 6.87 493.88 659.26 6.88 493.88 659.26 6.89 493.88 659.26 6.90 138.59 659.26 6.91 138.59 659.26 6.92 138.59 6.93 138.59 6.94 138.59 6.95 138.59 493.88 659.26 6.96 138.59 493.88 659.26 6.97 138.59 493.88 659.26 6.98 138.59 493.88 659.26 6.99 493.88 659.26 7.00 493.88 659.26 7.01 493.88 659.26 7.02 493.88 659.26 7.03 493.88 659.26 7.04 155.56 7.05 155.56 7.06 155.56 7.07 155.56 7.08 155.56 7.09 155.56 7.10 155.56 7.11 155.56 220.00 7.12 155.56 220.00 7.13 155.56 220.00 7.14 155.56 220.00 7.15 155.56 220.00 7.16 155.56 220.00 7.17 155.56 220.00 7.18 155.56 220.00 7.19 155.56 220.00 7.20 155.56 220.00 7.21 155.56 220.00 7.22 155.56 7.23 155.56 7.24 155.56 7.25 155.56 7.26 155.56 7.27 155.56 739.99 7.28 155.56 739.99 7.29 155.56 739.99 7.30 155.56 739.99 7.31 155.56 739.99 7.32 155.56 739.99 7.33 155.56 739.99 7.34 155.56 739.99 7.35 155.56 739.99 7.36 155.56 739.99 7.37 155.56 220.00 739.99 7.38 155.56 220.00 739.99 7.39 155.56 220.00 739.99 7.40 155.56 220.00 739.99 7.41 155.56 220.00 739.99 7.42 155.56 220.00 739.99 7.43 155.56 739.99 7.44 155.56 739.99 7.45 155.56 739.99 7.46 155.56 440.00 739.99 7.47 155.56 440.00 739.99 7.48 155.56 440.00 739.99 7.49 155.56 440.00 739.99 7.50 155.56 440.00 739.99 7.51 155.56 369.99 440.00 739.99 7.52 155.56 369.99 440.00 739.99 7.53 155.56 369.99 440.00 7.54 155.56 369.99 440.00 7.55 155.56 369.99 440.00 7.56 155.56 369.99 440.00 7.57 155.56 369.99 440.00 7.58 155.56 369.99 440.00 7.59 155.56 369.99 440.00 7.60 155.56 369.99 440.00 7.61 155.56 369.99 440.00 7.62 155.56 369.99 739.99 7.63 155.56 369.99 739.99 7.64 155.56 369.99 739.99 7.65 155.56 369.99 739.99 7.66 155.56 369.99 739.99 7.67 155.56 369.99 440.00 739.99 7.68 155.56 369.99 440.00 739.99 7.69 155.56 369.99 440.00 739.99 7.70 155.56 369.99 440.00 739.99 7.71 155.56 369.99 440.00 739.99 7.72 155.56 369.99 440.00 739.99 7.73 155.56 369.99 440.00 7.74 155.56 369.99 440.00 7.75 155.56 369.99 440.00 7.76 155.56 369.99 440.00 7.77 155.56 369.99 440.00 7.78 155.56 369.99 440.00 739.99 7.79 155.56 369.99 440.00 739.99 7.80 155.56 369.99 440.00 739.99 7.81 155.56 369.99 440.00 739.99 7.82 155.56 369.99 440.00 739.99 7.83 155.56 369.99 440.00 739.99 7.84 155.56 369.99 440.00 739.99 7.85 155.56 369.99 440.00 739.99 7.86 155.56 369.99 440.00 739.99 7.87 155.56 369.99 440.00 739.99 7.88 155.56 369.99 440.00 739.99 7.89 155.56 369.99 440.00 739.99 7.90 155.56 369.99 440.00 739.99 7.91 155.56 369.99 440.00 739.99 7.92 155.56 369.99 440.00 7.93 155.56 369.99 440.00 7.94 155.56 369.99 440.00 7.95 155.56 369.99 440.00 7.96 155.56 369.99 440.00 7.97 155.56 369.99 440.00 7.98 155.56 369.99 440.00 7.99 155.56 164.81 369.99 554.37 8.00 155.56 164.81 369.99 554.37 8.01 155.56 164.81 554.37 8.02 155.56 164.81 554.37 8.03 155.56 164.81 554.37 8.04 164.81 554.37 8.05 164.81 554.37 8.06 164.81 554.37 8.07 164.81 554.37 8.08 164.81 554.37 8.09 164.81 554.37 8.10 164.81 554.37 8.11 164.81 554.37 8.12 164.81 554.37 8.13 164.81 554.37 8.14 164.81 554.37 8.15 164.81 554.37 8.16 164.81 554.37 8.17 164.81 554.37 8.18 164.81 554.37 8.19 164.81 554.37 8.20 164.81 220.00 554.37 8.21 164.81 220.00 554.37 8.22 164.81 220.00 554.37 8.23 164.81 220.00 554.37 8.24 164.81 220.00 554.37 8.25 164.81 220.00 554.37 8.26 164.81 220.00 554.37 8.27 164.81 554.37 8.28 164.81 554.37 8.29 164.81 554.37 8.30 164.81 554.37 8.31 164.81 554.37 8.32 164.81 554.37 8.33 164.81 554.37 8.34 164.81 415.30 554.37 8.35 164.81 415.30 554.37 8.36 164.81 415.30 554.37 8.37 164.81 415.30 554.37 8.38 164.81 415.30 554.37 8.39 164.81 415.30 554.37 8.40 164.81 415.30 554.37 8.41 164.81 415.30 554.37 8.42 164.81 415.30 554.37 8.43 164.81 415.30 554.37 8.44 164.81 415.30 554.37 8.45 164.81 415.30 554.37 8.46 164.81 415.30 554.37 8.47 164.81 415.30 554.37 8.48 164.81 415.30 554.37 8.49 164.81 415.30 554.37 8.50 164.81 415.30 554.37 8.51 164.81 415.30 554.37 8.52 415.30 554.37 8.53 415.30 554.37 8.54 415.30 554.37 8.55 415.30 554.37 8.56 415.30 554.37 8.57 415.30 554.37 8.58 415.30 554.37 8.59 415.30 554.37 8.60 415.30 554.37 8.61 415.30 554.37 8.62 415.30 554.37 8.63 415.30 554.37 8.64 415.30 554.37 8.65 415.30 554.37 8.66 415.30 554.37 8.67 164.81 415.30 554.37 8.68 164.81 415.30 554.37 8.69 164.81 415.30 554.37 8.70 164.81 415.30 554.37 8.71 164.81 415.30 554.37 8.72 164.81 415.30 554.37 8.73 164.81 415.30 554.37 8.74 164.81 415.30 554.37 8.75 164.81 415.30 554.37 8.76 164.81 415.30 554.37 8.77 164.81 415.30 554.37 8.78 164.81 415.30 554.37 8.79 164.81 415.30 554.37 8.80 164.81 415.30 554.37 8.81 164.81 415.30 554.37 8.82 164.81 415.30 554.37 8.83 164.81 415.30 554.37 8.84 164.81 415.30 554.37 8.85 415.30 554.37 8.86 415.30 554.37 8.87 415.30 554.37 8.88 415.30 554.37 8.89 415.30 554.37 8.90 164.81 415.30 554.37 8.91 164.81 415.30 554.37 8.92 164.81 415.30 554.37 8.93 164.81 415.30 554.37 8.94 164.81 277.18 415.30 8.95 164.81 277.18 415.30 8.96 164.81 277.18 415.30 8.97 164.81 277.18 415.30 8.98 164.81 277.18 415.30 8.99 164.81 277.18 415.30 9.00 164.81 277.18 415.30 9.01 164.81 277.18 415.30 9.02 164.81 277.18 415.30 9.03 164.81 277.18 415.30 9.04 164.81 277.18 415.30 9.05 164.81 277.18 415.30 9.06 164.81 277.18 9.07 164.81 277.18 9.08 164.81 277.18 9.09 164.81 277.18 9.10 164.81 277.18 9.11 164.81 277.18 9.12 164.81 277.18 9.13 164.81 277.18 415.30 9.14 164.81 277.18 415.30 9.15 164.81 277.18 415.30 9.16 164.81 277.18 415.30 9.17 164.81 277.18 415.30 9.18 164.81 277.18 415.30 9.19 164.81 277.18 415.30 9.20 277.18 415.30 9.21 277.18 415.30 9.22 164.81 277.18 415.30 9.23 164.81 277.18 415.30 9.24 164.81 277.18 415.30 9.25 164.81 277.18 415.30 9.26 164.81 277.18 415.30 9.27 164.81 277.18 415.30 9.28 164.81 277.18 415.30 9.29 164.81 277.18 415.30 9.30 164.81 277.18 415.30 9.31 164.81 415.30 9.32 164.81 415.30 9.33 164.81 415.30 9.34 164.81 415.30 9.35 164.81 415.30 9.36 415.30 659.26 9.37 415.30 659.26 9.38 415.30 659.26 9.39 415.30 659.26 9.40 415.30 659.26 9.41 415.30 659.26 9.42 415.30 659.26 9.43 415.30 9.44 415.30 9.45 415.30 9.46 415.30 9.47 415.30 9.48 415.30 9.49 415.30 9.50 415.30 9.51 415.30 9.52 415.30 9.53 415.30 9.54 415.30 9.55 415.30 9.56 415.30 9.57 415.30 659.26 9.58 415.30 659.26 9.59 415.30 659.26 9.60 415.30 659.26 9.61 415.30 659.26 9.62 164.81 415.30 659.26 9.63 164.81 415.30 659.26 9.64 164.81 415.30 659.26 9.65 164.81 415.30 659.26 9.66 164.81 415.30 9.67 164.81 415.30 9.68 164.81 415.30 9.69 164.81 207.65 415.30 9.70 164.81 207.65 415.30 9.71 164.81 207.65 415.30 659.26 9.72 164.81 207.65 415.30 659.26 9.73 164.81 207.65 415.30 659.26 9.74 164.81 207.65 415.30 659.26 9.75 164.81 207.65 415.30 659.26 9.76 164.81 207.65 415.30 659.26 9.77 164.81 207.65 415.30 659.26 9.78 164.81 207.65 415.30 659.26 9.79 164.81 207.65 415.30 659.26 9.80 164.81 207.65 415.30 9.81 164.81 207.65 415.30 9.82 164.81 207.65 415.30 9.83 164.81 207.65 415.30 493.88 9.84 164.81 207.65 415.30 493.88 9.85 155.56 164.81 207.65 415.30 493.88 9.86 155.56 164.81 207.65 415.30 493.88 9.87 155.56 164.81 207.65 415.30 493.88 9.88 155.56 164.81 207.65 415.30 493.88 9.89 155.56 164.81 415.30 493.88 9.90 155.56 164.81 415.30 493.88 9.91 155.56 164.81 415.30 493.88 9.92 155.56 415.30 493.88 9.93 155.56 415.30 493.88 9.94 155.56 246.94 415.30 493.88 9.95 155.56 246.94 415.30 493.88 9.96 155.56 246.94 415.30 9.97 155.56 246.94 415.30 9.98 155.56 246.94 415.30 9.99 155.56 246.94 415.30 10.00 155.56 246.94 415.30 10.01 155.56 246.94 415.30 10.02 155.56 246.94 415.30 10.03 155.56 246.94 415.30 10.04 155.56 246.94 415.30 10.05 155.56 246.94 415.30 10.06 155.56 246.94 415.30 10.07 155.56 246.94 415.30 10.08 155.56 246.94 10.09 155.56 246.94 10.10 155.56 246.94 10.11 155.56 246.94 10.12 155.56 246.94 10.13 155.56 246.94 415.30 10.14 155.56 246.94 415.30 10.15 155.56 246.94 415.30 10.16 155.56 246.94 415.30 10.17 155.56 246.94 415.30 10.18 155.56 246.94 415.30 10.19 155.56 246.94 415.30 10.20 155.56 246.94 415.30 10.21 155.56 246.94 415.30 10.22 155.56 246.94 415.30 10.23 155.56 246.94 415.30 10.24 155.56 246.94 415.30 10.25 155.56 246.94 415.30 10.26 155.56 246.94 415.30 10.27 155.56 246.94 415.30 10.28 155.56 246.94 415.30 10.29 155.56 246.94 415.30 10.30 155.56 246.94 415.30 10.31 155.56 246.94 415.30 10.32 155.56 246.94 415.30 10.33 155.56 246.94 10.34 155.56 246.94 10.35 155.56 246.94 10.36 155.56 246.94 659.26 10.37 155.56 246.94 659.26 10.38 155.56 246.94 659.26 10.39 155.56 246.94 659.26 10.40 155.56 246.94 659.26 10.41 155.56 246.94 659.26 10.42 155.56 246.94 659.26 10.43 155.56 246.94 659.26 10.44 155.56 246.94 659.26 10.45 155.56 246.94 659.26 10.46 155.56 246.94 659.26 10.47 155.56 246.94 659.26 10.48 155.56 246.94 659.26 10.49 155.56 246.94 659.26 10.50 155.56 246.94 659.26 10.51 155.56 246.94 659.26 10.52 155.56 246.94 659.26 10.53 155.56 246.94 659.26 10.54 155.56 246.94 659.26 10.55 155.56 246.94 659.26 10.56 155.56 246.94 659.26 10.57 155.56 246.94 659.26 10.58 155.56 246.94 659.26 10.59 155.56 246.94 659.26 10.60 155.56 246.94 659.26 10.61 155.56 246.94 659.26 10.62 155.56 246.94 659.26 10.63 155.56 246.94 659.26 10.64 155.56 246.94 659.26 10.65 155.56 246.94 659.26 10.66 155.56 246.94 659.26 10.67 155.56 246.94 659.26 10.68 155.56 246.94 659.26 10.69 155.56 246.94 659.26 10.70 155.56 246.94 659.26 10.71 155.56 246.94 659.26 10.72 155.56 246.94 659.26 10.73 155.56 246.94 659.26 10.74 155.56 246.94 659.26 10.75 155.56 246.94 659.26 10.76 155.56 246.94 659.26 10.77 155.56 246.94 659.26 10.78 155.56 246.94 659.26 10.79 155.56 246.94 659.26 10.80 155.56 246.94 659.26 10.81 155.56 246.94 659.26 10.82 155.56 246.94 659.26 10.83 138.59 155.56 246.94 659.26 10.84 138.59 155.56 246.94 659.26 10.85 138.59 155.56 246.94 659.26 10.86 138.59 155.56 246.94 659.26 10.87 138.59 155.56 233.08 246.94 659.26 10.88 138.59 155.56 233.08 246.94 659.26 10.89 138.59 155.56 233.08 246.94 659.26 10.90 138.59 155.56 233.08 246.94 659.26 10.91 138.59 155.56 233.08 246.94 659.26 10.92 138.59 233.08 246.94 659.26 10.93 138.59 233.08 246.94 659.26 10.94 138.59 233.08 246.94 659.26 10.95 138.59 233.08 246.94 659.26 10.96 138.59 233.08 246.94 659.26 10.97 138.59 233.08 246.94 659.26 10.98 138.59 233.08 246.94 659.26 10.99 138.59 233.08 246.94 659.26 11.00 138.59 233.08 246.94 659.26 11.01 233.08 246.94 659.26 11.02 233.08 246.94 659.26 11.03 233.08 246.94 659.26 11.04 233.08 246.94 659.26 11.05 233.08 246.94 659.26 11.06 233.08 246.94 659.26 11.07 233.08 246.94 659.26 11.08 155.56 233.08 246.94 659.26 11.09 155.56 233.08 246.94 659.26 11.10 155.56 233.08 246.94 659.26 11.11 155.56 233.08 246.94 659.26 11.12 155.56 233.08 246.94 659.26 11.13 155.56 220.00 233.08 246.94 277.18 659.26 11.14 155.56 220.00 233.08 246.94 277.18 659.26 11.15 155.56 220.00 233.08 246.94 277.18 659.26 1975.53 11.16 155.56 220.00 233.08 246.94 277.18 659.26 1975.53 11.17 220.00 233.08 277.18 659.26 1975.53 11.18 220.00 233.08 277.18 659.26 1975.53 11.19 233.08 277.18 659.26 1975.53 11.20 233.08 277.18 659.26 1975.53 11.21 233.08 277.18 659.26 1975.53 11.22 233.08 277.18 659.26 1975.53 11.23 233.08 277.18 659.26 1975.53 11.24 233.08 277.18 659.26 11.25 233.08 277.18 659.26 11.26 233.08 659.26 11.27 233.08 659.26 11.28 233.08 659.26 11.29 233.08 659.26 1975.53 11.30 233.08 659.26 1975.53 11.31 233.08 659.26 1975.53 11.32 233.08 659.26 1975.53 11.33 233.08 659.26 1975.53 11.34 233.08 466.16 659.26 1975.53 11.35 233.08 466.16 659.26 1975.53 11.36 233.08 466.16 659.26 1975.53 11.37 233.08 466.16 659.26 1975.53 11.38 233.08 466.16 659.26 11.39 233.08 466.16 659.26 11.40 233.08 466.16 659.26 11.41 233.08 466.16 659.26 11.42 233.08 466.16 659.26 11.43 233.08 466.16 659.26 11.44 233.08 466.16 659.26 11.45 233.08 466.16 659.26 1975.53 11.46 233.08 466.16 659.26 1975.53 11.47 233.08 466.16 1975.53 11.48 233.08 466.16 1975.53 11.49 233.08 466.16 1975.53 11.50 233.08 466.16 1975.53 11.51 233.08 466.16 1975.53 11.52 233.08 11.53 233.08 11.54 233.08 11.55 233.08 659.26 11.56 233.08 659.26 11.57 233.08 659.26 11.58 233.08 659.26 11.59 233.08 659.26 11.60 233.08 659.26 11.61 233.08 659.26 11.62 233.08 659.26 11.63 233.08 11.64 233.08 11.65 233.08 11.66 233.08 11.67 233.08 11.68 233.08 11.69 233.08 11.70 233.08 11.71 233.08 11.72 233.08 11.73 233.08 11.74 233.08 11.75 233.08 11.76 233.08 11.77 233.08 11.78 233.08 11.79 233.08 11.80 233.08 11.81 233.08 11.82 233.08 11.83 233.08 11.84 233.08 11.85 233.08 11.86 233.08 11.87 233.08 415.30 11.88 233.08 415.30 11.89 138.59 233.08 415.30 11.90 138.59 233.08 415.30 11.91 138.59 233.08 415.30 11.92 138.59 233.08 415.30 11.93 138.59 233.08 415.30 11.94 138.59 233.08 329.63 415.30 11.95 138.59 233.08 329.63 415.30 11.96 233.08 329.63 415.30 11.97 233.08 329.63 415.30 11.98 233.08 329.63 415.30 11.99 233.08 329.63 415.30 12.00 233.08 329.63 415.30 12.01 138.59 329.63 415.30 12.02 138.59 329.63 415.30 12.03 138.59 329.63 415.30 12.04 138.59 329.63 415.30 12.05 138.59 329.63 415.30 12.06 138.59 329.63 415.30 12.07 138.59 329.63 415.30 12.08 138.59 329.63 415.30 12.09 138.59 329.63 415.30 12.10 138.59 329.63 415.30 12.11 138.59 329.63 415.30 12.12 138.59 329.63 415.30 12.13 138.59 329.63 415.30 12.14 138.59 329.63 415.30 12.15 138.59 329.63 415.30 12.16 138.59 329.63 415.30 12.17 138.59 329.63 415.30 12.18 138.59 329.63 415.30 12.19 138.59 329.63 415.30 12.20 138.59 329.63 415.30 12.21 138.59 329.63 415.30 12.22 329.63 415.30 830.61 12.23 329.63 415.30 830.61 12.24 329.63 415.30 830.61 12.25 329.63 415.30 830.61 12.26 329.63 415.30 830.61 12.27 138.59 329.63 415.30 830.61 12.28 138.59 329.63 415.30 830.61 12.29 138.59 311.13 329.63 415.30 830.61 12.30 138.59 311.13 329.63 415.30 830.61 12.31 138.59 311.13 329.63 415.30 830.61 12.32 138.59 311.13 329.63 415.30 830.61 12.33 138.59 311.13 329.63 415.30 830.61 12.34 138.59 311.13 329.63 415.30 830.61 12.35 138.59 311.13 329.63 415.30 830.61 12.36 138.59 311.13 329.63 415.30 830.61 12.37 138.59 311.13 329.63 415.30 830.61 12.38 138.59 329.63 415.30 830.61 12.39 138.59 329.63 415.30 830.61 12.40 138.59 329.63 415.30 830.61 12.41 138.59 329.63 415.30 830.61 12.42 138.59 329.63 415.30 830.61 12.43 138.59 329.63 415.30 830.61 12.44 138.59 329.63 415.30 830.61 12.45 138.59 329.63 415.30 830.61 12.46 138.59 329.63 415.30 830.61 12.47 138.59 329.63 415.30 830.61 12.48 138.59 329.63 415.30 830.61 12.49 138.59 329.63 415.30 830.61 12.50 138.59 329.63 415.30 830.61 12.51 138.59 329.63 415.30 830.61 12.52 138.59 329.63 415.30 830.61 12.53 138.59 329.63 415.30 830.61 12.54 329.63 415.30 830.61 12.55 329.63 415.30 830.61 12.56 329.63 415.30 830.61 12.57 329.63 415.30 830.61 12.58 329.63 415.30 830.61 12.59 329.63 415.30 830.61 12.60 329.63 415.30 830.61 12.61 329.63 415.30 830.61 12.62 329.63 415.30 830.61 12.63 329.63 415.30 830.61 12.64 329.63 415.30 830.61 12.65 329.63 415.30 830.61 12.66 329.63 415.30 830.61 12.67 329.63 415.30 830.61 12.68 69.30 138.59 329.63 415.30 830.61 12.69 69.30 138.59 329.63 415.30 830.61 12.70 69.30 138.59 329.63 415.30 830.61 12.71 69.30 138.59 329.63 415.30 830.61 12.72 69.30 138.59 329.63 415.30 830.61 12.73 69.30 138.59 329.63 415.30 830.61 12.74 69.30 138.59 329.63 415.30 830.61 12.75 69.30 138.59 329.63 415.30 466.16 830.61 12.76 69.30 138.59 329.63 415.30 466.16 830.61 12.77 69.30 138.59 329.63 415.30 466.16 830.61 12.78 69.30 138.59 329.63 415.30 466.16 830.61 12.79 69.30 138.59 329.63 415.30 466.16 830.61 12.80 69.30 329.63 415.30 466.16 830.61 12.81 69.30 329.63 415.30 466.16 830.61 12.82 69.30 329.63 415.30 466.16 12.83 69.30 329.63 415.30 466.16 12.84 69.30 329.63 415.30 466.16 12.85 69.30 329.63 415.30 466.16 12.86 69.30 329.63 415.30 466.16 12.87 69.30 329.63 415.30 466.16 12.88 69.30 329.63 415.30 466.16 12.89 69.30 329.63 466.16 12.90 69.30 329.63 466.16 12.91 69.30 329.63 466.16 12.92 69.30 329.63 466.16 12.93 69.30 329.63 466.16 12.94 69.30 329.63 415.30 466.16 932.33 12.95 69.30 329.63 415.30 466.16 932.33 12.96 69.30 329.63 415.30 466.16 932.33 12.97 69.30 329.63 415.30 466.16 932.33 12.98 69.30 329.63 415.30 466.16 932.33 12.99 69.30 329.63 415.30 466.16 932.33 13.00 69.30 329.63 466.16 932.33 13.01 69.30 329.63 466.16 932.33 13.02 69.30 329.63 466.16 932.33 13.03 69.30 329.63 466.16 932.33 13.04 69.30 329.63 466.16 932.33 13.05 69.30 329.63 466.16 932.33 13.06 69.30 329.63 466.16 932.33 13.07 69.30 329.63 466.16 932.33 13.08 69.30 329.63 466.16 932.33 13.09 69.30 329.63 466.16 932.33 13.10 69.30 329.63 466.16 932.33 13.11 69.30 329.63 466.16 932.33 13.12 69.30 329.63 466.16 932.33 13.13 69.30 329.63 466.16 932.33 13.14 69.30 329.63 466.16 932.33 13.15 69.30 329.63 466.16 932.33 13.16 69.30 329.63 466.16 932.33 13.17 69.30 329.63 466.16 932.33 13.18 69.30 329.63 466.16 932.33 13.19 69.30 329.63 466.16 932.33 13.20 69.30 329.63 466.16 932.33 13.21 69.30 329.63 466.16 13.22 69.30 329.63 466.16 13.23 69.30 329.63 466.16 13.24 69.30 311.13 329.63 466.16 13.25 69.30 311.13 329.63 466.16 13.26 69.30 164.81 311.13 329.63 466.16 932.33 13.27 69.30 164.81 311.13 329.63 466.16 932.33 13.28 69.30 164.81 311.13 329.63 466.16 932.33 13.29 69.30 164.81 311.13 329.63 466.16 932.33 13.30 69.30 164.81 311.13 329.63 466.16 932.33 13.31 69.30 164.81 329.63 466.16 932.33 13.32 69.30 164.81 329.63 466.16 932.33 13.33 69.30 329.63 466.16 932.33 13.34 69.30 329.63 466.16 932.33 13.35 69.30 329.63 466.16 932.33 13.36 69.30 329.63 466.16 932.33 13.37 69.30 329.63 466.16 932.33 13.38 69.30 164.81 329.63 466.16 932.33 13.39 69.30 164.81 329.63 466.16 932.33 13.40 69.30 164.81 329.63 466.16 932.33 13.41 69.30 164.81 329.63 466.16 932.33 13.42 69.30 164.81 329.63 466.16 932.33 13.43 69.30 164.81 329.63 466.16 932.33 13.44 69.30 164.81 329.63 466.16 932.33 13.45 69.30 164.81 329.63 466.16 932.33 13.46 69.30 164.81 329.63 466.16 932.33 13.47 69.30 164.81 329.63 466.16 932.33 13.48 69.30 164.81 329.63 466.16 932.33 13.49 69.30 164.81 329.63 466.16 932.33 13.50 69.30 164.81 329.63 466.16 932.33 13.51 69.30 164.81 329.63 466.16 932.33 13.52 69.30 164.81 329.63 466.16 932.33 13.53 69.30 164.81 329.63 466.16 932.33 13.54 69.30 164.81 329.63 466.16 932.33 13.55 69.30 164.81 329.63 466.16 932.33 13.56 69.30 164.81 329.63 466.16 932.33 13.57 69.30 164.81 329.63 466.16 932.33 13.58 69.30 164.81 329.63 466.16 932.33 13.59 69.30 164.81 329.63 466.16 659.26 932.33 13.60 69.30 164.81 329.63 466.16 659.26 932.33 13.61 69.30 329.63 466.16 659.26 932.33 13.62 69.30 329.63 466.16 659.26 932.33 13.63 69.30 466.16 659.26 932.33 13.64 69.30 466.16 493.88 659.26 932.33 13.65 69.30 466.16 493.88 659.26 932.33 13.66 69.30 77.78 466.16 493.88 739.99 932.33 13.67 69.30 77.78 466.16 493.88 739.99 932.33 13.68 69.30 77.78 466.16 493.88 739.99 932.33 13.69 69.30 77.78 466.16 493.88 739.99 932.33 13.70 69.30 77.78 493.88 739.99 932.33 13.71 69.30 77.78 493.88 739.99 932.33 13.72 77.78 493.88 739.99 13.73 77.78 369.99 493.88 739.99 13.74 77.78 369.99 493.88 739.99 13.75 77.78 369.99 493.88 739.99 13.76 77.78 369.99 493.88 739.99 13.77 77.78 369.99 493.88 739.99 13.78 77.78 369.99 493.88 739.99 13.79 77.78 369.99 493.88 739.99 13.80 77.78 369.99 493.88 739.99 2217.46 13.81 77.78 369.99 493.88 739.99 2217.46 13.82 77.78 155.56 369.99 493.88 739.99 2217.46 13.83 77.78 155.56 369.99 493.88 739.99 2217.46 13.84 77.78 155.56 369.99 493.88 739.99 2217.46 13.85 77.78 155.56 369.99 493.88 739.99 2217.46 13.86 77.78 155.56 493.88 739.99 13.87 77.78 155.56 493.88 739.99 13.88 77.78 155.56 493.88 739.99 13.89 77.78 493.88 739.99 13.90 77.78 493.88 739.99 13.91 77.78 369.99 493.88 739.99 13.92 77.78 369.99 493.88 739.99 13.93 77.78 369.99 493.88 739.99 13.94 77.78 233.08 369.99 493.88 739.99 2217.46 13.95 77.78 233.08 369.99 493.88 739.99 2217.46 13.96 77.78 155.56 233.08 369.99 493.88 2217.46 13.97 77.78 155.56 233.08 369.99 493.88 2217.46 13.98 77.78 155.56 233.08 369.99 493.88 2217.46 13.99 77.78 155.56 233.08 369.99 493.88 2217.46 14.00 77.78 155.56 233.08 369.99 493.88 2217.46 14.01 77.78 155.56 233.08 369.99 493.88 2217.46 14.02 77.78 155.56 233.08 369.99 493.88 2217.46 14.03 77.78 155.56 233.08 246.94 369.99 739.99 2217.46 14.04 77.78 155.56 233.08 246.94 369.99 739.99 2217.46 14.05 77.78 155.56 233.08 246.94 369.99 739.99 14.06 77.78 155.56 233.08 246.94 369.99 739.99 14.07 77.78 155.56 233.08 246.94 369.99 739.99 14.08 77.78 155.56 233.08 246.94 369.99 739.99 14.09 77.78 155.56 233.08 246.94 369.99 739.99 14.10 77.78 155.56 233.08 246.94 369.99 739.99 2217.46 14.11 77.78 155.56 233.08 246.94 369.99 739.99 2217.46 14.12 77.78 155.56 233.08 246.94 369.99 739.99 2217.46 14.13 77.78 155.56 233.08 246.94 369.99 739.99 2217.46 14.14 77.78 155.56 246.94 369.99 739.99 2217.46 14.15 77.78 155.56 246.94 369.99 739.99 2217.46 14.16 77.78 155.56 246.94 369.99 739.99 2217.46 14.17 77.78 155.56 246.94 369.99 739.99 2217.46 14.18 77.78 155.56 246.94 369.99 739.99 2217.46 14.19 77.78 155.56 246.94 369.99 739.99 2217.46 14.20 77.78 155.56 246.94 369.99 739.99 2217.46 14.21 77.78 155.56 246.94 369.99 739.99 2217.46 14.22 77.78 155.56 246.94 369.99 739.99 2217.46 14.23 77.78 155.56 246.94 369.99 739.99 2217.46 14.24 77.78 155.56 246.94 369.99 739.99 14.25 77.78 155.56 246.94 369.99 739.99 14.26 77.78 155.56 246.94 369.99 739.99 14.27 77.78 155.56 246.94 369.99 739.99 14.28 77.78 246.94 369.99 739.99 14.29 77.78 246.94 369.99 739.99 14.30 77.78 246.94 369.99 739.99 14.31 77.78 246.94 369.99 739.99 2217.46 14.32 77.78 246.94 369.99 739.99 2217.46 14.33 77.78 246.94 369.99 739.99 2217.46 14.34 77.78 246.94 369.99 739.99 2217.46 14.35 77.78 246.94 369.99 739.99 2217.46 14.36 77.78 246.94 369.99 739.99 2217.46 14.37 77.78 246.94 369.99 739.99 2217.46 14.38 77.78 246.94 369.99 739.99 2217.46 14.39 77.78 246.94 369.99 739.99 2217.46 14.40 77.78 246.94 369.99 739.99 14.41 77.78 246.94 369.99 739.99 14.42 77.78 246.94 369.99 739.99 14.43 77.78 246.94 369.99 739.99 14.44 77.78 246.94 369.99 739.99 14.45 77.78 246.94 369.99 739.99 14.46 77.78 246.94 369.99 739.99 14.47 77.78 246.94 369.99 739.99 2217.46 14.48 77.78 246.94 369.99 739.99 2217.46 14.49 77.78 246.94 369.99 739.99 2217.46 14.50 77.78 246.94 369.99 739.99 2217.46 14.51 77.78 246.94 369.99 739.99 2217.46 14.52 77.78 246.94 369.99 739.99 2217.46 14.53 77.78 246.94 369.99 739.99 2217.46 14.54 77.78 246.94 369.99 739.99 2217.46 14.55 77.78 246.94 369.99 739.99 2217.46 14.56 77.78 246.94 369.99 739.99 14.57 77.78 246.94 369.99 739.99 14.58 246.94 369.99 739.99 14.59 246.94 369.99 739.99 14.60 246.94 369.99 739.99 14.61 246.94 369.99 739.99 14.62 246.94 369.99 739.99 14.63 246.94 369.99 739.99 14.64 246.94 369.99 739.99 14.65 246.94 369.99 14.66 246.94 369.99 14.67 246.94 369.99 14.68 246.94 369.99 14.69 246.94 369.99 14.70 246.94 369.99 14.71 246.94 369.99 14.72 246.94 369.99 14.73 246.94 369.99 14.74 246.94 369.99 14.75 77.78 246.94 369.99 932.33 14.76 77.78 246.94 369.99 932.33 14.77 77.78 246.94 369.99 932.33 14.78 77.78 246.94 369.99 932.33 14.79 77.78 246.94 369.99 932.33 14.80 77.78 246.94 369.99 932.33 14.81 77.78 246.94 369.99 932.33 14.82 77.78 246.94 369.99 466.16 932.33 14.83 77.78 246.94 369.99 466.16 932.33 14.84 77.78 246.94 369.99 466.16 932.33 14.85 77.78 246.94 369.99 466.16 932.33 14.86 77.78 246.94 369.99 466.16 932.33 14.87 77.78 246.94 369.99 466.16 932.33 14.88 77.78 246.94 369.99 466.16 932.33 14.89 77.78 155.56 246.94 369.99 466.16 932.33 14.90 77.78 155.56 246.94 369.99 466.16 932.33 14.91 155.56 246.94 369.99 466.16 932.33 14.92 155.56 246.94 369.99 466.16 932.33 14.93 155.56 246.94 369.99 466.16 932.33 14.94 155.56 246.94 369.99 466.16 932.33 14.95 155.56 246.94 369.99 466.16 932.33 14.96 155.56 246.94 369.99 466.16 932.33 14.97 155.56 246.94 369.99 466.16 932.33 14.98 155.56 246.94 369.99 466.16 932.33 14.99 155.56 246.94 369.99 466.16 932.33 15.00 155.56 246.94 369.99 466.16 932.33 15.01 155.56 246.94 369.99 466.16 932.33 15.02 155.56 246.94 369.99 466.16 932.33 15.03 155.56 246.94 369.99 466.16 932.33 15.04 155.56 246.94 369.99 466.16 932.33 15.05 155.56 369.99 466.16 932.33 15.06 155.56 369.99 466.16 932.33 15.07 155.56 369.99 466.16 932.33 15.08 155.56 369.99 466.16 932.33 15.09 369.99 466.16 932.33 15.10 246.94 369.99 466.16 932.33 15.11 246.94 369.99 466.16 932.33 15.12 155.56 246.94 369.99 466.16 932.33 987.77 15.13 155.56 246.94 369.99 466.16 932.33 987.77 15.14 155.56 246.94 369.99 466.16 932.33 987.77 15.15 155.56 246.94 369.99 466.16 932.33 987.77 15.16 155.56 246.94 369.99 466.16 932.33 987.77 15.17 155.56 246.94 369.99 466.16 932.33 987.77 15.18 155.56 246.94 369.99 466.16 932.33 987.77 15.19 155.56 246.94 369.99 466.16 932.33 987.77 15.20 155.56 246.94 369.99 466.16 932.33 987.77 15.21 155.56 246.94 369.99 466.16 932.33 15.22 155.56 246.94 369.99 466.16 932.33 15.23 155.56 246.94 369.99 466.16 932.33 15.24 155.56 246.94 369.99 466.16 932.33 15.25 155.56 246.94 369.99 466.16 932.33 15.26 155.56 246.94 369.99 466.16 932.33 15.27 155.56 246.94 369.99 466.16 932.33 15.28 155.56 246.94 369.99 466.16 932.33 987.77 15.29 155.56 246.94 369.99 466.16 932.33 987.77 15.30 155.56 246.94 369.99 466.16 932.33 987.77 15.31 155.56 246.94 369.99 466.16 932.33 987.77 15.32 155.56 246.94 369.99 466.16 932.33 987.77 15.33 155.56 246.94 369.99 466.16 932.33 987.77 15.34 155.56 246.94 369.99 466.16 932.33 987.77 15.35 155.56 246.94 369.99 466.16 932.33 15.36 155.56 246.94 369.99 466.16 932.33 15.37 155.56 246.94 369.99 932.33 15.38 155.56 246.94 369.99 466.16 932.33 15.39 155.56 246.94 369.99 466.16 932.33 15.40 155.56 246.94 369.99 466.16 932.33 15.41 155.56 246.94 369.99 466.16 932.33 15.42 155.56 246.94 369.99 466.16 932.33 15.43 155.56 246.94 369.99 466.16 932.33 15.44 155.56 246.94 369.99 466.16 932.33 15.45 155.56 246.94 369.99 466.16 932.33 15.46 155.56 246.94 369.99 466.16 932.33 15.47 155.56 246.94 369.99 466.16 932.33 15.48 155.56 246.94 369.99 466.16 932.33 15.49 155.56 246.94 369.99 466.16 932.33 15.50 155.56 246.94 369.99 466.16 932.33 15.51 155.56 246.94 369.99 466.16 932.33 15.52 123.47 155.56 246.94 369.99 466.16 932.33 15.53 123.47 155.56 246.94 369.99 466.16 932.33 15.54 123.47 155.56 369.99 466.16 932.33 15.55 123.47 155.56 369.99 466.16 932.33 15.56 123.47 155.56 369.99 466.16 932.33 15.57 123.47 155.56 369.99 466.16 932.33 15.58 123.47 155.56 369.99 466.16 932.33 15.59 123.47 155.56 369.99 466.16 932.33 15.60 123.47 155.56 369.99 466.16 932.33 15.61 123.47 466.16 932.33 15.62 123.47 466.16 932.33 15.63 123.47 466.16 932.33 15.64 123.47 466.16 932.33 15.65 123.47 466.16 932.33 15.66 123.47 466.16 932.33 15.67 123.47 466.16 932.33 15.68 61.74 123.47 466.16 932.33 15.69 61.74 123.47 466.16 932.33 15.70 61.74 123.47 466.16 932.33 15.71 61.74 123.47 466.16 932.33 15.72 61.74 123.47 466.16 932.33 15.73 61.74 123.47 466.16 932.33 15.74 61.74 123.47 466.16 932.33 15.75 61.74 123.47 311.13 466.16 932.33 15.76 61.74 123.47 311.13 466.16 932.33 15.77 61.74 123.47 311.13 466.16 932.33 15.78 61.74 123.47 311.13 466.16 932.33 15.79 61.74 123.47 311.13 466.16 932.33 15.80 61.74 123.47 311.13 466.16 932.33 15.81 61.74 123.47 311.13 466.16 932.33 15.82 61.74 123.47 311.13 466.16 932.33 15.83 61.74 123.47 311.13 466.16 932.33 15.84 61.74 123.47 311.13 466.16 932.33 15.85 61.74 123.47 311.13 466.16 932.33 15.86 61.74 123.47 311.13 466.16 15.87 61.74 123.47 311.13 466.16 15.88 61.74 123.47 311.13 466.16 15.89 61.74 123.47 311.13 466.16 15.90 61.74 123.47 311.13 466.16 15.91 61.74 123.47 311.13 466.16 15.92 61.74 123.47 311.13 466.16 15.93 61.74 123.47 311.13 466.16 932.33 15.94 61.74 123.47 311.13 466.16 932.33 15.95 61.74 123.47 311.13 466.16 932.33 15.96 61.74 123.47 311.13 466.16 932.33 15.97 61.74 123.47 311.13 466.16 932.33 15.98 61.74 123.47 311.13 466.16 932.33 15.99 61.74 123.47 311.13 466.16 932.33 16.00 61.74 123.47 311.13 466.16 932.33 16.01 61.74 123.47 311.13 466.16 932.33 16.02 61.74 123.47 311.13 16.03 61.74 123.47 246.94 311.13 16.04 61.74 123.47 246.94 311.13 16.05 61.74 123.47 246.94 311.13 16.06 61.74 123.47 246.94 311.13 16.07 61.74 123.47 246.94 311.13 16.08 61.74 123.47 246.94 311.13 16.09 61.74 123.47 246.94 311.13 16.10 61.74 123.47 246.94 311.13 16.11 61.74 123.47 246.94 311.13 16.12 61.74 123.47 246.94 311.13 16.13 61.74 123.47 246.94 311.13 16.14 61.74 123.47 246.94 311.13 16.15 61.74 123.47 246.94 311.13 16.16 61.74 123.47 246.94 311.13 16.17 61.74 123.47 246.94 311.13 16.18 61.74 123.47 246.94 311.13 16.19 61.74 123.47 246.94 311.13 16.20 61.74 123.47 246.94 311.13 16.21 61.74 123.47 246.94 311.13 16.22 61.74 123.47 246.94 311.13 16.23 61.74 123.47 246.94 311.13 16.24 61.74 123.47 246.94 311.13 16.25 61.74 123.47 246.94 311.13 16.26 61.74 123.47 246.94 311.13 16.27 61.74 123.47 246.94 311.13 16.28 123.47 246.94 311.13 16.29 123.47 246.94 311.13 16.30 123.47 246.94 311.13 16.31 123.47 246.94 311.13 16.32 123.47 246.94 311.13 16.33 123.47 246.94 311.13 415.30 830.61 16.34 123.47 246.94 311.13 415.30 830.61 16.35 123.47 311.13 415.30 830.61 16.36 123.47 311.13 415.30 830.61 16.37 123.47 311.13 415.30 830.61 16.38 123.47 311.13 415.30 830.61 16.39 123.47 311.13 415.30 830.61 16.40 123.47 311.13 415.30 830.61 16.41 123.47 311.13 415.30 830.61 16.42 123.47 311.13 415.30 830.61 16.43 123.47 311.13 415.30 830.61 16.44 123.47 311.13 415.30 830.61 16.45 123.47 311.13 415.30 830.61 16.46 123.47 311.13 415.30 830.61 16.47 123.47 311.13 415.30 830.61 16.48 123.47 311.13 415.30 830.61 16.49 123.47 311.13 415.30 830.61 16.50 123.47 311.13 415.30 830.61 16.51 123.47 311.13 415.30 830.61 16.52 123.47 311.13 415.30 830.61 16.53 123.47 311.13 830.61 16.54 82.41 123.47 311.13 830.61 16.55 82.41 123.47 311.13 830.61 16.56 82.41 123.47 311.13 830.61 16.57 82.41 123.47 311.13 830.61 16.58 82.41 123.47 311.13 415.30 830.61 16.59 82.41 123.47 311.13 415.30 830.61 16.60 82.41 123.47 415.30 16.61 82.41 123.47 415.30 16.62 82.41 123.47 415.30 16.63 82.41 123.47 415.30 16.64 82.41 123.47 415.30 16.65 82.41 415.30 16.66 82.41 415.30 16.67 82.41 415.30 16.68 82.41 415.30 830.61 16.69 82.41 415.30 830.61 16.70 82.41 415.30 830.61 16.71 82.41 415.30 830.61 16.72 82.41 329.63 415.30 830.61 16.73 82.41 329.63 415.30 830.61 16.74 82.41 329.63 415.30 830.61 16.75 82.41 329.63 415.30 830.61 16.76 82.41 329.63 415.30 830.61 16.77 82.41 329.63 415.30 830.61 16.78 82.41 329.63 415.30 830.61 16.79 82.41 329.63 415.30 830.61 16.80 82.41 329.63 415.30 830.61 16.81 82.41 329.63 415.30 830.61 16.82 82.41 329.63 415.30 830.61 16.83 82.41 329.63 415.30 830.61 16.84 82.41 329.63 415.30 830.61 1661.22 16.85 82.41 329.63 415.30 830.61 1661.22 16.86 82.41 164.81 329.63 415.30 830.61 1661.22 16.87 82.41 164.81 329.63 415.30 830.61 1661.22 16.88 82.41 164.81 415.30 830.61 1661.22 16.89 82.41 164.81 415.30 830.61 1661.22 16.90 82.41 164.81 415.30 830.61 1661.22 16.91 82.41 164.81 415.30 830.61 16.92 82.41 164.81 415.30 830.61 16.93 82.41 164.81 415.30 830.61 16.94 82.41 164.81 415.30 830.61 16.95 82.41 164.81 415.30 830.61 16.96 82.41 164.81 415.30 830.61 16.97 82.41 164.81 415.30 830.61 16.98 82.41 164.81 415.30 830.61 16.99 82.41 164.81 415.30 830.61 17.00 82.41 164.81 415.30 830.61 1661.22 17.01 82.41 164.81 415.30 830.61 1661.22 17.02 164.81 415.30 830.61 1661.22 17.03 164.81 415.30 830.61 1661.22 17.04 164.81 415.30 830.61 1661.22 17.05 82.41 164.81 415.30 830.61 1661.22 17.06 82.41 164.81 415.30 830.61 1661.22 17.07 82.41 164.81 246.94 415.30 830.61 1661.22 17.08 82.41 164.81 246.94 415.30 830.61 1661.22 17.09 82.41 164.81 246.94 415.30 830.61 1661.22 17.10 82.41 164.81 246.94 415.30 830.61 1661.22 17.11 82.41 164.81 246.94 415.30 830.61 17.12 82.41 164.81 246.94 415.30 830.61 17.13 82.41 164.81 246.94 415.30 830.61 17.14 82.41 246.94 415.30 830.61 17.15 82.41 246.94 415.30 830.61 17.16 82.41 246.94 415.30 830.61 1661.22 17.17 82.41 246.94 415.30 830.61 1661.22 17.18 82.41 246.94 415.30 830.61 1661.22 17.19 82.41 164.81 246.94 415.30 830.61 1661.22 17.20 82.41 164.81 246.94 415.30 830.61 1661.22 17.21 82.41 164.81 246.94 415.30 830.61 1661.22 17.22 82.41 164.81 246.94 415.30 830.61 1661.22 17.23 82.41 164.81 246.94 415.30 830.61 17.24 82.41 164.81 246.94 415.30 830.61 17.25 82.41 164.81 246.94 415.30 830.61 17.26 82.41 164.81 246.94 415.30 830.61 17.27 82.41 164.81 246.94 415.30 830.61 17.28 82.41 164.81 246.94 415.30 830.61 17.29 82.41 164.81 246.94 415.30 830.61 17.30 82.41 164.81 246.94 415.30 493.88 830.61 17.31 82.41 164.81 246.94 415.30 493.88 830.61 17.32 82.41 164.81 246.94 415.30 493.88 830.61 17.33 82.41 164.81 246.94 415.30 493.88 830.61 1661.22 17.34 82.41 164.81 246.94 415.30 493.88 830.61 1661.22 17.35 82.41 164.81 415.30 493.88 830.61 1661.22 17.36 82.41 164.81 415.30 493.88 830.61 1661.22 17.37 82.41 164.81 415.30 493.88 830.61 1661.22 17.38 82.41 164.81 415.30 493.88 830.61 1661.22 17.39 82.41 164.81 415.30 493.88 830.61 1661.22 17.40 82.41 164.81 246.94 415.30 493.88 830.61 1661.22 17.41 82.41 164.81 246.94 415.30 493.88 830.61 1661.22 17.42 82.41 164.81 246.94 415.30 493.88 830.61 17.43 82.41 164.81 246.94 415.30 493.88 830.61 17.44 82.41 164.81 246.94 415.30 493.88 659.26 830.61 1479.98 17.45 82.41 164.81 246.94 415.30 493.88 659.26 830.61 1479.98 17.46 82.41 246.94 659.26 830.61 1479.98 17.47 82.41 246.94 659.26 830.61 1479.98 17.48 82.41 246.94 659.26 830.61 1479.98 17.49 82.41 246.94 659.26 830.61 1479.98 17.50 82.41 246.94 659.26 830.61 1479.98 17.51 82.41 246.94 369.99 659.26 830.61 17.52 82.41 246.94 369.99 659.26 830.61 17.53 82.41 369.99 830.61 17.54 82.41 369.99 830.61 17.55 82.41 369.99 830.61 17.56 82.41 155.56 369.99 830.61 17.57 82.41 155.56 369.99 830.61 17.58 77.78 82.41 155.56 369.99 415.30 17.59 77.78 82.41 155.56 369.99 415.30 17.60 77.78 82.41 155.56 369.99 415.30 17.61 77.78 82.41 155.56 369.99 415.30 17.62 77.78 82.41 155.56 369.99 415.30 17.63 77.78 82.41 155.56 369.99 415.30 2217.46 17.64 77.78 82.41 155.56 369.99 415.30 2217.46 17.65 77.78 369.99 2217.46 17.66 77.78 369.99 2217.46 17.67 77.78 369.99 2217.46 17.68 77.78 369.99 2217.46 17.69 77.78 369.99 2217.46 17.70 77.78 369.99 739.99 2217.46 17.71 77.78 369.99 739.99 2217.46 17.72 77.78 369.99 739.99 17.73 77.78 369.99 739.99 17.74 77.78 369.99 739.99 17.75 77.78 369.99 739.99 17.76 77.78 369.99 739.99 17.77 77.78 369.99 739.99 2217.46 17.78 77.78 369.99 739.99 2217.46 17.79 77.78 246.94 369.99 739.99 2217.46 17.80 77.78 246.94 369.99 739.99 2217.46 17.81 77.78 246.94 369.99 2217.46 17.82 77.78 246.94 369.99 2217.46 17.83 77.78 246.94 369.99 2217.46 17.84 77.78 246.94 369.99 2217.46 17.85 77.78 246.94 369.99 2217.46 17.86 77.78 246.94 369.99 739.99 2217.46 17.87 77.78 246.94 369.99 739.99 2217.46 17.88 77.78 246.94 369.99 739.99 17.89 77.78 246.94 369.99 739.99 17.90 77.78 369.99 739.99 17.91 77.78 369.99 739.99 17.92 77.78 369.99 739.99 17.93 77.78 369.99 415.30 739.99 17.94 77.78 369.99 415.30 739.99 17.95 77.78 369.99 415.30 2217.46 17.96 77.78 369.99 415.30 2217.46 17.97 77.78 369.99 415.30 2217.46 17.98 77.78 246.94 369.99 415.30 2217.46 17.99 77.78 246.94 369.99 415.30 2217.46 18.00 77.78 246.94 369.99 415.30 2217.46 18.01 77.78 246.94 369.99 415.30 2217.46 18.02 77.78 246.94 369.99 739.99 2217.46 18.03 77.78 246.94 369.99 739.99 2217.46 18.04 77.78 246.94 369.99 739.99 18.05 77.78 246.94 369.99 739.99 18.06 77.78 246.94 369.99 739.99 18.07 77.78 246.94 369.99 739.99 18.08 77.78 246.94 369.99 739.99 18.09 77.78 246.94 369.99 739.99 18.10 77.78 246.94 369.99 739.99 18.11 77.78 246.94 369.99 739.99 18.12 77.78 246.94 369.99 739.99 2217.46 18.13 77.78 246.94 369.99 739.99 2217.46 18.14 77.78 246.94 369.99 1479.98 2217.46 18.15 77.78 246.94 369.99 1479.98 2217.46 18.16 77.78 246.94 369.99 1479.98 2217.46 18.17 77.78 246.94 369.99 1479.98 2217.46 18.18 77.78 246.94 369.99 1479.98 2217.46 18.19 77.78 246.94 369.99 1479.98 2217.46 18.20 77.78 246.94 369.99 1479.98 2217.46 18.21 77.78 246.94 369.99 18.22 77.78 246.94 369.99 18.23 77.78 246.94 369.99 18.24 77.78 246.94 369.99 18.25 77.78 246.94 369.99 18.26 77.78 246.94 369.99 18.27 77.78 246.94 369.99 18.28 77.78 246.94 369.99 1479.98 2217.46 18.29 77.78 246.94 369.99 1479.98 2217.46 18.30 77.78 246.94 369.99 1479.98 2217.46 18.31 77.78 246.94 369.99 1479.98 2217.46 18.32 77.78 246.94 369.99 1479.98 2217.46 18.33 77.78 246.94 369.99 1479.98 2217.46 18.34 77.78 246.94 369.99 1479.98 2217.46 18.35 77.78 246.94 369.99 2217.46 18.36 77.78 246.94 369.99 2217.46 18.37 77.78 246.94 369.99 2217.46 18.38 77.78 246.94 369.99 2217.46 18.39 77.78 246.94 369.99 18.40 77.78 246.94 369.99 18.41 77.78 246.94 369.99 18.42 77.78 246.94 369.99 18.43 77.78 246.94 369.99 18.44 246.94 369.99 18.45 246.94 369.99 18.46 123.47 246.94 369.99 18.47 123.47 246.94 369.99 18.48 123.47 246.94 369.99 18.49 123.47 246.94 311.13 369.99 18.50 123.47 246.94 311.13 369.99 18.51 123.47 246.94 311.13 830.61 18.52 123.47 246.94 311.13 830.61 18.53 123.47 246.94 311.13 830.61 18.54 123.47 246.94 311.13 830.61 18.55 123.47 246.94 311.13 830.61 18.56 123.47 246.94 311.13 830.61 18.57 123.47 246.94 311.13 830.61 18.58 123.47 246.94 311.13 415.30 830.61 18.59 123.47 246.94 311.13 415.30 830.61 18.60 123.47 311.13 415.30 830.61 18.61 123.47 311.13 415.30 830.61 18.62 123.47 311.13 415.30 18.63 123.47 311.13 415.30 18.64 123.47 311.13 415.30 18.65 123.47 311.13 415.30 18.66 123.47 311.13 415.30 18.67 123.47 311.13 415.30 18.68 123.47 311.13 415.30 18.69 123.47 311.13 415.30 18.70 123.47 311.13 415.30 830.61 18.71 123.47 311.13 415.30 830.61 18.72 123.47 311.13 415.30 830.61 18.73 123.47 311.13 415.30 830.61 18.74 123.47 311.13 415.30 830.61 18.75 123.47 311.13 415.30 830.61 18.76 123.47 311.13 415.30 830.61 18.77 123.47 311.13 415.30 830.61 18.78 123.47 311.13 415.30 830.61 18.79 123.47 311.13 415.30 830.61 18.80 123.47 311.13 415.30 830.61 18.81 123.47 311.13 415.30 18.82 123.47 311.13 415.30 18.83 123.47 311.13 415.30 18.84 123.47 311.13 415.30 18.85 123.47 311.13 415.30 18.86 123.47 311.13 415.30 18.87 123.47 311.13 415.30 18.88 123.47 311.13 415.30 18.89 123.47 311.13 415.30 18.90 123.47 311.13 415.30 18.91 123.47 311.13 415.30 18.92 123.47 311.13 415.30 18.93 123.47 311.13 415.30 18.94 123.47 311.13 415.30 18.95 123.47 246.94 311.13 415.30 18.96 123.47 246.94 311.13 415.30 18.97 123.47 246.94 311.13 415.30 18.98 123.47 246.94 311.13 415.30 18.99 123.47 246.94 311.13 415.30 19.00 123.47 246.94 311.13 415.30 19.01 123.47 246.94 311.13 415.30 19.02 123.47 246.94 311.13 369.99 415.30 19.03 123.47 246.94 311.13 369.99 415.30 19.04 123.47 246.94 311.13 369.99 415.30 19.05 123.47 246.94 311.13 369.99 415.30 830.61 19.06 123.47 246.94 311.13 369.99 415.30 830.61 19.07 123.47 246.94 311.13 369.99 415.30 830.61 19.08 123.47 246.94 311.13 369.99 415.30 830.61 19.09 123.47 246.94 311.13 369.99 415.30 830.61 19.10 123.47 246.94 311.13 369.99 415.30 830.61 19.11 123.47 246.94 311.13 415.30 830.61 19.12 123.47 246.94 311.13 415.30 830.61 19.13 123.47 246.94 311.13 415.30 830.61 19.14 123.47 246.94 311.13 415.30 19.15 123.47 246.94 311.13 415.30 19.16 123.47 246.94 311.13 415.30 19.17 123.47 246.94 311.13 415.30 19.18 123.47 311.13 415.30 19.19 123.47 311.13 415.30 19.20 123.47 311.13 415.30 19.21 123.47 311.13 415.30 19.22 123.47 311.13 415.30 19.23 123.47 311.13 19.24 123.47 311.13 19.25 123.47 830.61 19.26 123.47 830.61 19.27 123.47 830.61 19.28 123.47 830.61 19.29 123.47 830.61 19.30 123.47 415.30 830.61 19.31 123.47 415.30 830.61 19.32 123.47 415.30 830.61 19.33 123.47 415.30 830.61 19.34 123.47 415.30 19.35 123.47 415.30 19.36 123.47 415.30 19.37 123.47 415.30 19.38 123.47 415.30 19.39 123.47 415.30 19.40 123.47 415.30 19.41 123.47 415.30 19.42 123.47 138.59 415.30 19.43 123.47 138.59 415.30 19.44 123.47 138.59 19.45 123.47 138.59 19.46 123.47 138.59 19.47 123.47 138.59 19.48 123.47 138.59 19.49 123.47 138.59 19.50 123.47 138.59 19.51 123.47 138.59 415.30 19.52 123.47 138.59 415.30 19.53 123.47 138.59 329.63 415.30 19.54 123.47 138.59 329.63 415.30 19.55 123.47 138.59 329.63 415.30 19.56 123.47 138.59 329.63 415.30 19.57 123.47 138.59 329.63 415.30 19.58 123.47 138.59 329.63 415.30 19.59 123.47 138.59 329.63 415.30 19.60 123.47 138.59 329.63 415.30 19.61 123.47 138.59 329.63 415.30 19.62 123.47 329.63 415.30 19.63 123.47 329.63 415.30 659.26 19.64 123.47 329.63 415.30 659.26 19.65 123.47 329.63 415.30 659.26 19.66 123.47 329.63 415.30 659.26 19.67 277.18 329.63 415.30 659.26 1975.53 19.68 277.18 329.63 415.30 659.26 1975.53 19.69 277.18 329.63 415.30 659.26 1975.53 19.70 207.65 277.18 329.63 415.30 659.26 1975.53 19.71 207.65 277.18 329.63 415.30 659.26 1975.53 19.72 138.59 207.65 277.18 329.63 415.30 1975.53 19.73 138.59 207.65 277.18 329.63 415.30 1975.53 19.74 138.59 207.65 329.63 415.30 659.26 19.75 138.59 207.65 329.63 415.30 659.26 19.76 138.59 329.63 415.30 659.26 19.77 138.59 329.63 415.30 659.26 19.78 138.59 329.63 415.30 659.26 19.79 138.59 329.63 415.30 659.26 987.77 19.80 138.59 329.63 415.30 659.26 987.77 19.81 207.65 329.63 415.30 659.26 987.77 19.82 207.65 329.63 415.30 659.26 987.77 19.83 207.65 329.63 415.30 659.26 987.77 19.84 207.65 329.63 415.30 659.26 987.77 19.85 207.65 329.63 415.30 659.26 987.77 19.86 207.65 329.63 415.30 659.26 987.77 19.87 207.65 329.63 415.30 659.26 987.77 19.88 207.65 246.94 329.63 415.30 659.26 987.77 19.89 207.65 246.94 329.63 415.30 659.26 987.77 19.90 207.65 246.94 329.63 415.30 659.26 987.77 19.91 207.65 246.94 329.63 415.30 659.26 987.77 19.92 246.94 329.63 415.30 659.26 19.93 246.94 329.63 415.30 659.26 19.94 246.94 329.63 415.30 659.26 19.95 246.94 329.63 415.30 659.26 19.96 246.94 329.63 415.30 659.26 19.97 207.65 246.94 329.63 415.30 659.26 1318.51 19.98 207.65 246.94 329.63 415.30 659.26 1318.51 19.99 207.65 246.94 329.63 415.30 659.26 1318.51 20.00 207.65 246.94 329.63 415.30 659.26 1318.51 20.01 207.65 246.94 329.63 415.30 659.26 1318.51 20.02 207.65 246.94 329.63 415.30 659.26 1318.51 20.03 207.65 246.94 329.63 415.30 659.26 1318.51 20.04 138.59 207.65 246.94 329.63 415.30 659.26 1318.51 20.05 138.59 207.65 246.94 329.63 415.30 659.26 1318.51 20.06 138.59 207.65 246.94 329.63 415.30 659.26 20.07 138.59 207.65 246.94 329.63 415.30 659.26 20.08 138.59 207.65 246.94 329.63 415.30 659.26 20.09 138.59 207.65 246.94 329.63 415.30 659.26 20.10 138.59 207.65 246.94 329.63 415.30 659.26 20.11 207.65 246.94 329.63 415.30 659.26 20.12 207.65 246.94 329.63 415.30 659.26 20.13 207.65 246.94 329.63 415.30 659.26 20.14 207.65 246.94 329.63 415.30 659.26 20.15 207.65 246.94 329.63 415.30 659.26 20.16 207.65 246.94 329.63 415.30 659.26 20.17 207.65 246.94 329.63 415.30 659.26 20.18 207.65 246.94 329.63 415.30 659.26 20.19 207.65 246.94 329.63 415.30 659.26 20.20 207.65 246.94 329.63 415.30 659.26 20.21 207.65 246.94 329.63 415.30 659.26 1318.51 20.22 207.65 246.94 329.63 415.30 659.26 1318.51 20.23 207.65 246.94 329.63 415.30 659.26 1318.51 20.24 207.65 246.94 329.63 415.30 659.26 1318.51 20.25 207.65 246.94 329.63 415.30 659.26 1318.51 20.26 207.65 246.94 329.63 415.30 659.26 1318.51 20.27 207.65 246.94 329.63 415.30 659.26 1318.51 20.28 207.65 246.94 329.63 415.30 659.26 1318.51 20.29 207.65 246.94 329.63 415.30 659.26 1318.51 20.30 207.65 246.94 329.63 415.30 659.26 1318.51 20.31 207.65 246.94 329.63 415.30 659.26 1318.51 20.32 207.65 246.94 329.63 415.30 659.26 1318.51 20.33 207.65 246.94 329.63 415.30 659.26 1318.51 20.34 207.65 246.94 329.63 415.30 659.26 1318.51 20.35 207.65 246.94 329.63 415.30 659.26 1318.51 20.36 207.65 246.94 329.63 415.30 659.26 1318.51 20.37 207.65 246.94 329.63 415.30 659.26 1318.51 20.38 207.65 246.94 329.63 415.30 659.26 1318.51 20.39 116.54 246.94 329.63 415.30 659.26 1318.51 20.40 116.54 246.94 329.63 415.30 659.26 1318.51 20.41 116.54 415.30 659.26 1318.51 20.42 116.54 415.30 659.26 1318.51 20.43 116.54 415.30 659.26 1318.51 20.44 116.54 415.30 659.26 20.45 116.54 415.30 659.26 20.46 116.54 174.61 415.30 20.47 116.54 174.61 415.30 20.48 116.54 174.61 415.30 20.49 116.54 174.61 233.08 415.30 20.50 116.54 174.61 233.08 415.30 20.51 174.61 233.08 415.30 20.52 174.61 233.08 415.30 20.53 174.61 233.08 415.30 20.54 174.61 233.08 415.30 20.55 174.61 233.08 415.30 20.56 174.61 233.08 415.30 20.57 174.61 233.08 415.30 20.58 174.61 233.08 349.23 415.30 20.59 174.61 233.08 349.23 415.30 20.60 174.61 233.08 349.23 415.30 659.26 20.61 174.61 233.08 349.23 415.30 659.26 20.62 174.61 233.08 349.23 415.30 659.26 830.61 20.63 174.61 233.08 349.23 415.30 659.26 830.61 20.64 174.61 233.08 415.30 659.26 830.61 20.65 174.61 233.08 415.30 659.26 830.61 20.66 174.61 233.08 415.30 659.26 830.61 20.67 174.61 415.30 830.61 20.68 174.61 415.30 830.61 20.69 174.61 415.30 830.61 20.70 174.61 415.30 830.61 20.71 174.61 415.30 830.61 20.72 174.61 415.30 830.61 20.73 174.61 415.30 830.61 20.74 116.54 174.61 415.30 830.61 20.75 116.54 174.61 415.30 830.61 20.76 116.54 174.61 415.30 830.61 20.77 116.54 174.61 415.30 830.61 20.78 116.54 174.61 415.30 830.61 20.79 116.54 174.61 415.30 830.61 20.80 116.54 174.61 415.30 830.61 20.81 116.54 415.30 830.61 20.82 116.54 415.30 830.61 20.83 116.54 415.30 830.61 20.84 116.54 415.30 830.61 20.85 116.54 415.30 830.61 20.86 116.54 415.30 830.61 20.87 116.54 415.30 830.61 20.88 116.54 277.18 415.30 830.61 20.89 116.54 277.18 415.30 830.61 20.90 116.54 277.18 415.30 830.61 20.91 116.54 277.18 415.30 830.61 20.92 116.54 277.18 415.30 830.61 20.93 116.54 277.18 415.30 830.61 20.94 116.54 277.18 415.30 830.61 20.95 116.54 277.18 415.30 830.61 20.96 116.54 277.18 415.30 830.61 20.97 116.54 277.18 415.30 830.61 20.98 116.54 277.18 415.30 830.61 20.99 116.54 277.18 415.30 21.00 116.54 277.18 415.30 21.01 116.54 277.18 415.30 21.02 116.54 277.18 415.30 21.03 116.54 277.18 415.30 21.04 116.54 277.18 415.30 21.05 116.54 277.18 415.30 21.06 116.54 277.18 415.30 21.07 116.54 277.18 415.30 21.08 116.54 277.18 415.30 21.09 116.54 277.18 415.30 21.10 116.54 277.18 415.30 21.11 116.54 277.18 415.30 21.12 116.54 277.18 415.30 21.13 116.54 277.18 415.30 21.14 116.54 277.18 415.30 21.15 116.54 277.18 415.30 21.16 116.54 277.18 415.30 21.17 116.54 277.18 415.30 21.18 116.54 277.18 415.30 21.19 116.54 277.18 415.30 21.20 116.54 277.18 415.30 21.21 116.54 277.18 415.30 21.22 116.54 277.18 415.30 21.23 116.54 277.18 415.30 21.24 116.54 277.18 415.30 21.25 116.54 277.18 415.30 21.26 116.54 277.18 415.30 21.27 116.54 277.18 415.30 21.28 116.54 277.18 415.30 21.29 116.54 277.18 415.30 21.30 116.54 277.18 415.30 21.31 116.54 277.18 415.30 21.32 116.54 277.18 415.30 21.33 116.54 277.18 415.30 21.34 116.54 277.18 415.30 21.35 116.54 277.18 415.30 21.36 116.54 277.18 415.30 21.37 116.54 277.18 415.30 21.38 116.54 277.18 415.30 21.39 116.54 164.81 233.08 277.18 415.30 21.40 116.54 164.81 233.08 277.18 415.30 21.41 82.41 116.54 164.81 233.08 277.18 415.30 21.42 82.41 116.54 164.81 233.08 277.18 415.30 21.43 82.41 116.54 164.81 233.08 415.30 21.44 82.41 116.54 164.81 233.08 415.30 830.61 21.45 82.41 116.54 164.81 233.08 415.30 830.61 21.46 82.41 116.54 164.81 233.08 277.18 830.61 21.47 82.41 116.54 164.81 233.08 277.18 830.61 21.48 82.41 116.54 164.81 233.08 277.18 830.61 21.49 82.41 116.54 164.81 233.08 277.18 830.61 21.50 82.41 116.54 164.81 233.08 277.18 21.51 82.41 116.54 164.81 233.08 277.18 21.52 82.41 116.54 164.81 233.08 277.18 21.53 164.81 233.08 277.18 21.54 164.81 233.08 277.18 21.55 164.81 233.08 277.18 21.56 164.81 233.08 277.18 21.57 164.81 233.08 277.18 21.58 164.81 233.08 277.18 415.30 21.59 164.81 233.08 277.18 415.30 21.60 82.41 164.81 233.08 277.18 415.30 21.61 82.41 164.81 233.08 277.18 415.30 21.62 82.41 164.81 233.08 277.18 415.30 21.63 82.41 164.81 233.08 277.18 415.30 21.64 82.41 164.81 233.08 277.18 415.30 21.65 82.41 164.81 233.08 277.18 415.30 21.66 82.41 164.81 233.08 277.18 415.30 21.67 164.81 233.08 277.18 415.30 21.68 164.81 233.08 277.18 415.30 21.69 164.81 233.08 277.18 415.30 21.70 164.81 233.08 277.18 415.30 21.71 164.81 233.08 277.18 415.30 21.72 164.81 233.08 277.18 415.30 21.73 164.81 233.08 277.18 415.30 21.74 164.81 233.08 277.18 21.75 164.81 233.08 277.18 21.76 164.81 233.08 277.18 415.30 21.77 164.81 233.08 277.18 415.30 21.78 164.81 233.08 277.18 415.30 21.79 164.81 233.08 277.18 415.30 21.80 164.81 233.08 277.18 415.30 21.81 82.41 164.81 233.08 277.18 415.30 21.82 82.41 164.81 233.08 277.18 415.30 21.83 82.41 164.81 233.08 277.18 415.30 21.84 82.41 164.81 233.08 277.18 415.30 21.85 82.41 164.81 233.08 277.18 415.30 21.86 82.41 164.81 233.08 277.18 415.30 21.87 82.41 164.81 233.08 277.18 415.30 21.88 82.41 164.81 233.08 277.18 369.99 415.30 21.89 82.41 164.81 233.08 277.18 369.99 415.30 21.90 82.41 164.81 233.08 369.99 415.30 21.91 82.41 164.81 233.08 369.99 415.30 21.92 82.41 164.81 233.08 369.99 415.30 21.93 82.41 164.81 233.08 369.99 415.30 21.94 82.41 164.81 233.08 369.99 21.95 82.41 164.81 233.08 369.99 21.96 82.41 164.81 233.08 369.99 21.97 82.41 164.81 233.08 369.99 21.98 82.41 164.81 233.08 369.99 21.99 82.41 164.81 233.08 369.99 739.99 22.00 82.41 164.81 233.08 369.99 739.99 22.01 233.08 369.99 739.99 22.02 233.08 369.99 739.99 22.03 233.08 369.99 739.99 22.04 233.08 369.99 739.99 22.05 233.08 369.99 739.99 22.06 82.41 233.08 369.99 739.99 22.07 82.41 233.08 369.99 739.99 22.08 82.41 233.08 369.99 739.99 22.09 82.41 233.08 369.99 739.99 22.10 82.41 233.08 369.99 739.99 22.11 82.41 233.08 369.99 22.12 82.41 233.08 369.99 22.13 82.41 233.08 369.99 22.14 82.41 233.08 369.99 22.15 233.08 369.99 22.16 233.08 369.99 739.99 22.17 233.08 369.99 739.99 22.18 164.81 233.08 369.99 739.99 22.19 164.81 233.08 369.99 739.99 22.20 164.81 233.08 369.99 739.99 22.21 164.81 233.08 369.99 739.99 22.22 164.81 233.08 369.99 739.99 22.23 82.41 164.81 233.08 369.99 659.26 739.99 22.24 82.41 164.81 233.08 369.99 659.26 739.99 22.25 82.41 164.81 233.08 369.99 659.26 739.99 22.26 82.41 164.81 233.08 369.99 659.26 739.99 22.27 82.41 233.08 369.99 659.26 739.99 22.28 82.41 233.08 369.99 659.26 739.99 22.29 82.41 233.08 369.99 22.30 82.41 233.08 369.99 2217.46 22.31 82.41 233.08 369.99 2217.46 22.32 82.41 233.08 369.99 2217.46 22.33 82.41 233.08 369.99 2217.46 22.34 82.41 233.08 369.99 2217.46 22.35 82.41 233.08 369.99 2217.46 22.36 82.41 233.08 369.99 2217.46 22.37 82.41 233.08 311.13 369.99 2217.46 22.38 82.41 233.08 311.13 369.99 2217.46 22.39 82.41 233.08 311.13 369.99 22.40 82.41 233.08 311.13 369.99 22.41 82.41 233.08 311.13 369.99 22.42 82.41 233.08 311.13 369.99 22.43 233.08 311.13 369.99 22.44 233.08 311.13 369.99 1108.73 22.45 233.08 311.13 369.99 1108.73 22.46 77.78 233.08 311.13 1108.73 22.47 77.78 233.08 311.13 1108.73 22.48 77.78 233.08 369.99 1108.73 22.49 77.78 233.08 369.99 1108.73 22.50 77.78 233.08 369.99 22.51 77.78 233.08 369.99 22.52 77.78 233.08 369.99 22.53 77.78 369.99 22.54 77.78 369.99 22.55 77.78 369.99 739.99 22.56 77.78 369.99 739.99 22.57 77.78 369.99 739.99 22.58 77.78 369.99 739.99 22.59 77.78 369.99 739.99 22.60 77.78 311.13 369.99 739.99 22.61 77.78 311.13 369.99 739.99 22.62 77.78 311.13 369.99 22.63 77.78 311.13 369.99 22.64 77.78 311.13 369.99 739.99 22.65 77.78 311.13 369.99 739.99 22.66 77.78 311.13 369.99 739.99 22.67 77.78 311.13 369.99 739.99 22.68 77.78 311.13 369.99 739.99 22.69 77.78 311.13 369.99 739.99 22.70 77.78 311.13 369.99 739.99 22.71 77.78 155.56 246.94 311.13 369.99 739.99 22.72 77.78 155.56 246.94 311.13 369.99 739.99 22.73 77.78 155.56 246.94 311.13 369.99 739.99 22.74 77.78 155.56 246.94 311.13 369.99 739.99 22.75 77.78 155.56 246.94 311.13 369.99 739.99 22.76 77.78 155.56 246.94 369.99 739.99 22.77 77.78 155.56 246.94 369.99 739.99 22.78 77.78 155.56 246.94 369.99 739.99 22.79 77.78 155.56 246.94 369.99 739.99 22.80 77.78 155.56 246.94 369.99 739.99 22.81 77.78 155.56 246.94 311.13 369.99 739.99 22.82 77.78 155.56 246.94 311.13 369.99 739.99 22.83 77.78 155.56 246.94 311.13 369.99 739.99 22.84 77.78 155.56 246.94 311.13 369.99 739.99 22.85 77.78 155.56 246.94 311.13 369.99 739.99 22.86 77.78 155.56 246.94 311.13 369.99 739.99 22.87 77.78 155.56 246.94 311.13 369.99 739.99 22.88 77.78 155.56 246.94 311.13 369.99 739.99 22.89 77.78 155.56 246.94 311.13 369.99 739.99 22.90 77.78 155.56 246.94 311.13 369.99 739.99 22.91 77.78 155.56 246.94 311.13 369.99 739.99 22.92 77.78 155.56 246.94 311.13 369.99 739.99 22.93 77.78 155.56 246.94 311.13 369.99 739.99 22.94 77.78 155.56 246.94 311.13 369.99 739.99 22.95 77.78 155.56 246.94 311.13 369.99 739.99 22.96 77.78 155.56 246.94 311.13 369.99 739.99 22.97 77.78 155.56 246.94 369.99 739.99 22.98 77.78 155.56 246.94 369.99 739.99 22.99 77.78 155.56 246.94 369.99 739.99 2217.46 23.00 77.78 155.56 246.94 369.99 739.99 2217.46 23.01 77.78 155.56 246.94 369.99 2217.46 23.02 77.78 155.56 246.94 369.99 2217.46 23.03 77.78 155.56 246.94 369.99 2217.46 23.04 77.78 155.56 246.94 369.99 2217.46 23.05 77.78 155.56 246.94 369.99 2217.46 23.06 77.78 155.56 246.94 369.99 2217.46 23.07 77.78 155.56 246.94 369.99 2217.46 23.08 77.78 155.56 246.94 369.99 2217.46 23.09 77.78 155.56 246.94 369.99 739.99 2217.46 23.10 77.78 155.56 246.94 369.99 739.99 2217.46 23.11 155.56 246.94 369.99 739.99 2217.46 23.12 155.56 246.94 369.99 739.99 2217.46 23.13 77.78 155.56 246.94 369.99 739.99 2217.46 23.14 77.78 155.56 246.94 369.99 739.99 2217.46 23.15 77.78 155.56 246.94 369.99 739.99 2217.46 23.16 77.78 155.56 246.94 369.99 739.99 2217.46 23.17 77.78 155.56 246.94 369.99 739.99 2217.46 23.18 77.78 155.56 246.94 369.99 739.99 2217.46 23.19 77.78 155.56 246.94 369.99 739.99 2217.46 23.20 77.78 123.47 155.56 246.94 369.99 739.99 2217.46 23.21 77.78 123.47 155.56 246.94 369.99 739.99 2217.46 23.22 77.78 123.47 369.99 739.99 2217.46 23.23 77.78 123.47 369.99 739.99 2217.46 23.24 77.78 123.47 369.99 739.99 2217.46 23.25 77.78 123.47 369.99 739.99 2217.46 23.26 77.78 123.47 369.99 739.99 2217.46 23.27 77.78 123.47 369.99 739.99 2217.46 23.28 77.78 123.47 369.99 739.99 2217.46 23.29 77.78 369.99 739.99 2217.46 23.30 77.78 369.99 739.99 2217.46 23.31 77.78 369.99 739.99 2217.46 23.32 77.78 246.94 369.99 739.99 2217.46 23.33 77.78 246.94 369.99 739.99 2217.46 23.34 77.78 246.94 369.99 2217.46 23.35 77.78 246.94 369.99 2217.46 23.36 77.78 246.94 369.99 2217.46 23.37 77.78 246.94 369.99 2217.46 23.38 77.78 246.94 369.99 2217.46 23.39 77.78 246.94 369.99 2217.46 23.40 77.78 246.94 369.99 2217.46 23.41 77.78 246.94 369.99 2217.46 23.42 77.78 246.94 369.99 2217.46 23.43 77.78 246.94 369.99 2217.46 23.44 77.78 246.94 369.99 2217.46 23.45 246.94 369.99 23.46 246.94 369.99 23.47 246.94 369.99 23.48 246.94 311.13 23.49 246.94 311.13 23.50 246.94 311.13 23.51 246.94 311.13 23.52 246.94 311.13 23.53 123.47 246.94 311.13 23.54 123.47 246.94 311.13 23.55 123.47 311.13 622.25 23.56 123.47 311.13 622.25 23.57 123.47 311.13 622.25 23.58 123.47 311.13 622.25 23.59 123.47 311.13 622.25 23.60 123.47 311.13 622.25 23.61 123.47 311.13 622.25 23.62 123.47 311.13 622.25 23.63 123.47 311.13 622.25 23.64 123.47 311.13 23.65 123.47 311.13 23.66 123.47 311.13 23.67 123.47 311.13 23.68 123.47 311.13 23.69 123.47 311.13 622.25 23.70 123.47 311.13 622.25 23.71 123.47 311.13 622.25 23.72 123.47 311.13 622.25 23.73 123.47 311.13 622.25 23.74 123.47 311.13 622.25 1244.51 23.75 123.47 311.13 622.25 1244.51 23.76 123.47 311.13 622.25 1244.51 23.77 123.47 311.13 622.25 1244.51 23.78 123.47 311.13 622.25 1244.51 23.79 123.47 311.13 622.25 1244.51 23.80 123.47 311.13 622.25 1244.51 23.81 123.47 311.13 622.25 659.26 1244.51 23.82 123.47 311.13 622.25 659.26 1244.51 23.83 123.47 311.13 659.26 1244.51 23.84 123.47 311.13 659.26 1244.51 23.85 123.47 311.13 659.26 1244.51 23.86 123.47 311.13 659.26 1244.51 23.87 123.47 311.13 659.26 1244.51 23.88 123.47 311.13 622.25 659.26 1244.51 23.89 123.47 311.13 622.25 659.26 1244.51 23.90 123.47 311.13 622.25 1244.51 23.91 123.47 311.13 622.25 1244.51 23.92 123.47 311.13 622.25 1244.51 23.93 123.47 311.13 622.25 1244.51 23.94 123.47 311.13 622.25 1244.51 23.95 123.47 311.13 622.25 1244.51 23.96 123.47 311.13 622.25 1244.51 23.97 123.47 311.13 622.25 1244.51 23.98 123.47 311.13 622.25 1244.51 23.99 123.47 246.94 311.13 659.26 1244.51 24.00 123.47 246.94 311.13 659.26 1244.51 24.01 123.47 246.94 311.13 659.26 1244.51 24.02 123.47 246.94 311.13 659.26 1244.51 24.03 123.47 246.94 311.13 659.26 24.04 123.47 246.94 311.13 659.26 24.05 123.47 246.94 311.13 659.26 24.06 123.47 246.94 311.13 493.88 659.26 24.07 123.47 246.94 311.13 493.88 659.26 24.08 123.47 311.13 493.88 622.25 24.09 123.47 311.13 493.88 622.25 24.10 123.47 311.13 493.88 622.25 24.11 123.47 311.13 493.88 622.25 24.12 123.47 311.13 493.88 622.25 24.13 123.47 311.13 493.88 622.25 659.26 932.33 24.14 123.47 311.13 493.88 622.25 659.26 932.33 24.15 123.47 311.13 493.88 622.25 659.26 932.33 24.16 123.47 311.13 493.88 622.25 659.26 932.33 24.17 123.47 311.13 622.25 659.26 932.33 24.18 123.47 246.94 311.13 622.25 659.26 932.33 24.19 123.47 246.94 311.13 622.25 659.26 932.33 24.20 123.47 246.94 311.13 659.26 24.21 123.47 246.94 311.13 659.26 24.22 123.47 246.94 311.13 659.26 24.23 123.47 246.94 311.13 659.26 24.24 123.47 246.94 311.13 659.26 24.25 123.47 246.94 311.13 622.25 659.26 24.26 123.47 246.94 311.13 622.25 659.26 24.27 123.47 246.94 311.13 622.25 987.77 24.28 123.47 246.94 311.13 622.25 987.77 24.29 123.47 246.94 311.13 622.25 987.77 24.30 123.47 246.94 311.13 622.25 987.77 24.31 123.47 246.94 311.13 622.25 987.77 24.32 123.47 246.94 311.13 622.25 932.33 987.77 24.33 123.47 246.94 311.13 622.25 932.33 987.77 24.34 246.94 311.13 622.25 659.26 932.33 24.35 246.94 311.13 622.25 659.26 932.33 24.36 246.94 311.13 622.25 659.26 932.33 24.37 246.94 311.13 622.25 659.26 932.33 24.38 246.94 311.13 622.25 659.26 932.33 24.39 246.94 311.13 622.25 659.26 932.33 24.40 246.94 311.13 622.25 659.26 932.33 24.41 246.94 311.13 622.25 659.26 932.33 24.42 246.94 311.13 622.25 659.26 932.33 24.43 246.94 311.13 622.25 659.26 932.33 24.44 246.94 311.13 622.25 659.26 932.33 24.45 246.94 311.13 622.25 659.26 932.33 24.46 246.94 311.13 622.25 659.26 932.33 24.47 246.94 311.13 622.25 659.26 932.33 24.48 246.94 311.13 659.26 932.33 24.49 246.94 311.13 659.26 932.33 24.50 123.47 246.94 311.13 659.26 932.33 24.51 123.47 246.94 311.13 659.26 932.33 24.52 123.47 311.13 659.26 24.53 123.47 311.13 329.63 659.26 24.54 123.47 311.13 329.63 659.26 24.55 123.47 329.63 659.26 24.56 123.47 329.63 659.26 24.57 103.83 123.47 329.63 659.26 24.58 103.83 123.47 329.63 659.26 24.59 103.83 329.63 659.26 24.60 103.83 329.63 659.26 24.61 103.83 329.63 659.26 24.62 103.83 329.63 659.26 24.63 103.83 329.63 659.26 24.64 103.83 329.63 24.65 103.83 329.63 24.66 103.83 329.63 24.67 103.83 329.63 24.68 103.83 329.63 24.69 103.83 329.63 24.70 103.83 329.63 24.71 103.83 329.63 659.26 24.72 103.83 329.63 659.26 24.73 103.83 311.13 329.63 659.26 24.74 103.83 311.13 329.63 659.26 24.75 103.83 311.13 329.63 659.26 24.76 103.83 311.13 329.63 659.26 24.77 103.83 311.13 329.63 659.26 24.78 103.83 311.13 329.63 24.79 103.83 311.13 329.63 24.80 103.83 311.13 329.63 24.81 103.83 311.13 329.63 24.82 103.83 311.13 329.63 24.83 51.91 103.83 311.13 329.63 24.84 51.91 103.83 311.13 329.63 24.85 51.91 103.83 311.13 329.63 24.86 51.91 103.83 311.13 329.63 24.87 51.91 103.83 329.63 24.88 51.91 103.83 329.63 24.89 103.83 329.63 24.90 103.83 311.13 329.63 659.26 24.91 103.83 311.13 329.63 659.26 24.92 103.83 311.13 329.63 659.26 24.93 103.83 311.13 329.63 659.26 24.94 103.83 311.13 329.63 659.26 24.95 103.83 311.13 329.63 659.26 24.96 311.13 329.63 659.26 24.97 246.94 311.13 329.63 659.26 24.98 246.94 311.13 329.63 659.26 24.99 246.94 311.13 329.63 25.00 246.94 311.13 329.63 25.01 246.94 311.13 329.63 25.02 246.94 311.13 329.63 25.03 246.94 311.13 329.63 25.04 246.94 311.13 329.63 25.05 246.94 311.13 329.63 25.06 246.94 311.13 329.63 25.07 246.94 311.13 329.63 25.08 246.94 311.13 329.63 25.09 246.94 311.13 329.63 25.10 246.94 311.13 329.63 25.11 246.94 311.13 329.63 25.12 246.94 311.13 329.63 25.13 246.94 311.13 329.63 25.14 246.94 311.13 329.63 25.15 246.94 311.13 329.63 25.16 246.94 311.13 329.63 25.17 246.94 311.13 329.63 25.18 246.94 311.13 329.63 25.19 246.94 311.13 329.63 25.20 246.94 311.13 329.63 25.21 246.94 311.13 329.63 25.22 246.94 311.13 329.63 25.23 246.94 311.13 329.63 25.24 246.94 311.13 329.63 25.25 246.94 311.13 329.63 25.26 246.94 311.13 329.63 25.27 246.94 311.13 329.63 25.28 246.94 311.13 329.63 25.29 246.94 311.13 329.63 659.26 25.30 246.94 311.13 329.63 659.26 25.31 246.94 311.13 329.63 659.26 25.32 246.94 311.13 329.63 659.26 25.33 246.94 311.13 329.63 659.26 25.34 246.94 311.13 329.63 659.26 25.35 246.94 311.13 329.63 659.26 25.36 246.94 311.13 329.63 659.26 25.37 246.94 311.13 329.63 659.26 25.38 103.83 246.94 311.13 329.63 659.26 25.39 103.83 246.94 311.13 329.63 659.26 25.40 103.83 246.94 311.13 329.63 659.26 25.41 103.83 246.94 311.13 329.63 659.26 25.42 103.83 246.94 311.13 329.63 659.26 25.43 103.83 246.94 311.13 329.63 25.44 103.83 246.94 311.13 329.63 25.45 103.83 246.94 329.63 25.46 103.83 246.94 329.63 25.47 103.83 246.94 329.63 25.48 103.83 246.94 329.63 25.49 103.83 246.94 329.63 25.50 246.94 329.63 554.37 25.51 246.94 329.63 554.37 25.52 246.94 277.18 329.63 554.37 25.53 246.94 277.18 329.63 554.37 25.54 277.18 329.63 554.37 25.55 116.54 277.18 329.63 554.37 25.56 116.54 277.18 329.63 554.37 25.57 116.54 277.18 329.63 25.58 116.54 277.18 329.63 25.59 116.54 277.18 329.63 25.60 116.54 277.18 329.63 25.61 116.54 277.18 329.63 25.62 116.54 277.18 329.63 25.63 116.54 277.18 329.63 25.64 116.54 277.18 329.63 25.65 116.54 277.18 329.63 25.66 116.54 277.18 329.63 25.67 116.54 277.18 329.63 25.68 116.54 277.18 329.63 25.69 116.54 277.18 329.63 25.70 116.54 277.18 329.63 25.71 116.54 277.18 329.63 25.72 116.54 277.18 329.63 25.73 116.54 277.18 329.63 25.74 116.54 277.18 329.63 25.75 116.54 277.18 329.63 25.76 116.54 277.18 329.63 25.77 116.54 277.18 329.63 25.78 116.54 277.18 329.63 25.79 116.54 277.18 329.63 25.80 116.54 277.18 329.63 25.81 116.54 277.18 329.63 25.82 116.54 277.18 329.63 25.83 116.54 277.18 329.63 554.37 25.84 116.54 277.18 329.63 554.37 25.85 116.54 277.18 329.63 554.37 25.86 116.54 277.18 329.63 554.37 25.87 116.54 277.18 329.63 554.37 25.88 116.54 277.18 329.63 554.37 25.89 116.54 277.18 329.63 554.37 25.90 116.54 277.18 329.63 554.37 25.91 116.54 277.18 329.63 554.37 25.92 116.54 277.18 329.63 554.37 25.93 116.54 277.18 329.63 554.37 25.94 116.54 277.18 329.63 554.37 25.95 116.54 277.18 329.63 554.37 25.96 116.54 277.18 329.63 554.37 25.97 116.54 277.18 329.63 554.37 25.98 116.54 277.18 329.63 554.37 25.99 116.54 277.18 329.63 554.37 26.00 116.54 277.18 329.63 554.37 26.01 116.54 277.18 329.63 554.37 26.02 116.54 277.18 329.63 554.37 26.03 116.54 277.18 329.63 554.37 26.04 116.54 277.18 329.63 554.37 26.05 116.54 277.18 329.63 554.37 26.06 116.54 277.18 329.63 554.37 26.07 116.54 277.18 329.63 554.37 26.08 116.54 164.81 277.18 329.63 554.37 26.09 116.54 164.81 277.18 329.63 554.37 26.10 116.54 164.81 277.18 554.37 26.11 116.54 164.81 277.18 554.37 26.12 116.54 164.81 277.18 554.37 26.13 116.54 164.81 277.18 554.37 26.14 116.54 164.81 277.18 554.37 26.15 116.54 164.81 277.18 554.37 26.16 116.54 164.81 277.18 554.37 26.17 116.54 164.81 277.18 554.37 26.18 116.54 164.81 277.18 554.37 26.19 116.54 164.81 277.18 554.37 26.20 116.54 164.81 277.18 554.37 26.21 116.54 164.81 277.18 554.37 26.22 116.54 164.81 277.18 554.37 26.23 116.54 164.81 277.18 554.37 26.24 116.54 164.81 277.18 329.63 554.37 26.25 116.54 164.81 277.18 329.63 554.37 26.26 116.54 164.81 277.18 329.63 554.37 26.27 116.54 164.81 277.18 329.63 554.37 26.28 116.54 164.81 277.18 329.63 554.37 26.29 116.54 164.81 277.18 329.63 554.37 26.30 116.54 164.81 277.18 329.63 554.37 26.31 116.54 164.81 277.18 329.63 554.37 26.32 116.54 164.81 277.18 329.63 554.37 26.33 116.54 164.81 277.18 329.63 554.37 26.34 116.54 164.81 277.18 329.63 554.37 26.35 116.54 164.81 277.18 329.63 554.37 26.36 116.54 164.81 277.18 329.63 554.37 26.37 116.54 164.81 277.18 329.63 554.37 26.38 116.54 164.81 277.18 329.63 554.37 26.39 116.54 164.81 277.18 329.63 554.37 26.40 116.54 164.81 277.18 329.63 554.37 26.41 116.54 164.81 277.18 329.63 554.37 26.42 116.54 164.81 277.18 329.63 554.37 26.43 116.54 164.81 277.18 329.63 554.37 2217.46 26.44 116.54 164.81 277.18 329.63 554.37 2217.46 26.45 116.54 164.81 277.18 329.63 554.37 2217.46 26.46 116.54 164.81 277.18 329.63 554.37 2217.46 26.47 116.54 164.81 277.18 329.63 554.37 2217.46 26.48 116.54 164.81 277.18 329.63 554.37 2217.46 26.49 116.54 164.81 277.18 329.63 554.37 2217.46 26.50 116.54 164.81 277.18 329.63 554.37 26.51 116.54 164.81 277.18 329.63 554.37 26.52 116.54 164.81 277.18 329.63 554.37 26.53 116.54 164.81 277.18 329.63 554.37 26.54 277.18 329.63 554.37 26.55 277.18 329.63 554.37 26.56 277.18 329.63 554.37 26.57 277.18 329.63 554.37 26.58 277.18 329.63 554.37 26.59 103.83 277.18 329.63 26.60 103.83 277.18 329.63 26.61 103.83 277.18 329.63 26.62 103.83 277.18 329.63 26.63 103.83 277.18 329.63 26.64 103.83 277.18 329.63 26.65 103.83 277.18 329.63 26.66 103.83 277.18 329.63 26.67 103.83 277.18 329.63 26.68 103.83 277.18 311.13 329.63 26.69 103.83 277.18 311.13 329.63 26.70 103.83 277.18 311.13 329.63 26.71 103.83 277.18 311.13 329.63 26.72 103.83 277.18 311.13 329.63 26.73 103.83 277.18 311.13 26.74 103.83 277.18 311.13 26.75 103.83 246.94 311.13 26.76 103.83 246.94 311.13 26.77 103.83 246.94 311.13 26.78 103.83 246.94 311.13 659.26 26.79 103.83 246.94 311.13 659.26 26.80 103.83 246.94 311.13 659.26 26.81 103.83 246.94 311.13 659.26 26.82 103.83 246.94 277.18 311.13 329.63 659.26 26.83 103.83 246.94 277.18 311.13 329.63 659.26 26.84 103.83 246.94 277.18 311.13 329.63 659.26 26.85 103.83 246.94 277.18 311.13 329.63 659.26 26.86 103.83 246.94 277.18 311.13 329.63 659.26 26.87 103.83 246.94 277.18 311.13 329.63 659.26 26.88 103.83 246.94 277.18 311.13 329.63 659.26 26.89 103.83 311.13 329.63 659.26 26.90 103.83 311.13 329.63 659.26 26.91 103.83 311.13 329.63 26.92 103.83 311.13 329.63 26.93 103.83 311.13 329.63 26.94 103.83 311.13 329.63 26.95 103.83 311.13 329.63 26.96 103.83 311.13 329.63 659.26 26.97 103.83 311.13 329.63 659.26 26.98 103.83 311.13 329.63 659.26 26.99 103.83 246.94 311.13 329.63 659.26 27.00 103.83 246.94 311.13 329.63 659.26 27.01 103.83 246.94 311.13 329.63 659.26 27.02 103.83 246.94 311.13 329.63 659.26 27.03 246.94 311.13 329.63 659.26 27.04 246.94 311.13 329.63 659.26 27.05 246.94 311.13 329.63 27.06 246.94 311.13 329.63 659.26 27.07 246.94 311.13 329.63 659.26 27.08 246.94 311.13 329.63 659.26 27.09 246.94 311.13 329.63 659.26 27.10 246.94 311.13 329.63 659.26 27.11 246.94 311.13 329.63 659.26 27.12 246.94 311.13 329.63 659.26 27.13 246.94 311.13 329.63 659.26 27.14 246.94 311.13 329.63 659.26 27.15 246.94 311.13 329.63 659.26 27.16 246.94 311.13 329.63 659.26 27.17 246.94 311.13 329.63 659.26 27.18 246.94 311.13 329.63 659.26 27.19 246.94 311.13 329.63 659.26 27.20 246.94 311.13 329.63 659.26 27.21 246.94 311.13 329.63 659.26 27.22 246.94 311.13 329.63 659.26 27.23 246.94 311.13 329.63 659.26 27.24 246.94 311.13 329.63 659.26 27.25 246.94 311.13 329.63 659.26 27.26 246.94 311.13 329.63 659.26 27.27 246.94 311.13 329.63 659.26 27.28 246.94 311.13 329.63 659.26 27.29 246.94 311.13 329.63 659.26 27.30 246.94 311.13 329.63 659.26 27.31 246.94 311.13 329.63 659.26 27.32 246.94 311.13 329.63 659.26 27.33 246.94 311.13 329.63 659.26 27.34 246.94 311.13 329.63 659.26 27.35 246.94 311.13 329.63 659.26 27.36 103.83 246.94 311.13 329.63 659.26 27.37 103.83 246.94 311.13 329.63 659.26 27.38 103.83 246.94 311.13 329.63 659.26 27.39 103.83 246.94 311.13 329.63 659.26 27.40 103.83 246.94 311.13 329.63 659.26 27.41 103.83 246.94 311.13 329.63 659.26 27.42 103.83 246.94 311.13 329.63 659.26 27.43 103.83 246.94 311.13 329.63 659.26 27.44 103.83 246.94 311.13 329.63 659.26 27.45 103.83 246.94 311.13 329.63 659.26 27.46 103.83 246.94 311.13 329.63 659.26 27.47 103.83 246.94 311.13 329.63 659.26 27.48 103.83 246.94 311.13 329.63 659.26 27.49 103.83 246.94 311.13 329.63 27.50 103.83 246.94 311.13 329.63 27.51 103.83 246.94 311.13 329.63 27.52 103.83 246.94 311.13 329.63 27.53 103.83 246.94 311.13 329.63 27.54 98.00 103.83 246.94 311.13 329.63 27.55 98.00 103.83 246.94 311.13 329.63 27.56 98.00 103.83 246.94 329.63 27.57 98.00 103.83 233.08 246.94 329.63 27.58 98.00 103.83 233.08 246.94 329.63 27.59 98.00 233.08 246.94 329.63 27.60 98.00 233.08 246.94 329.63 27.61 98.00 233.08 329.63 27.62 98.00 233.08 329.63 27.63 98.00 233.08 329.63 27.64 98.00 233.08 329.63 27.65 98.00 233.08 329.63 27.66 49.00 98.00 329.63 27.67 49.00 98.00 329.63 27.68 49.00 98.00 329.63 659.26 27.69 49.00 98.00 329.63 659.26 27.70 49.00 98.00 329.63 659.26 27.71 49.00 98.00 329.63 659.26 27.72 49.00 98.00 329.63 659.26 27.73 49.00 98.00 329.63 659.26 27.74 49.00 98.00 329.63 659.26 27.75 49.00 98.00 329.63 27.76 49.00 98.00 329.63 27.77 49.00 98.00 27.78 49.00 98.00 233.08 27.79 49.00 98.00 233.08 27.80 49.00 98.00 233.08 27.81 49.00 98.00 233.08 27.82 49.00 98.00 233.08 27.83 49.00 98.00 233.08 27.84 49.00 98.00 233.08 27.85 49.00 98.00 233.08 329.63 27.86 49.00 98.00 233.08 329.63 27.87 49.00 233.08 329.63 27.88 49.00 233.08 329.63 27.89 49.00 233.08 329.63 27.90 49.00 233.08 329.63 27.91 49.00 233.08 329.63 27.92 49.00 233.08 329.63 27.93 49.00 233.08 329.63 27.94 49.00 27.95 49.00 27.96 49.00 329.63 27.97 49.00 329.63 27.98 49.00 329.63 27.99 49.00 329.63 28.00 49.00 329.63 28.01 49.00 329.63 28.02 49.00 329.63 28.03 49.00 233.08 329.63 28.04 49.00 233.08 329.63 28.05 49.00 233.08 329.63 28.06 49.00 233.08 329.63 28.07 49.00 233.08 329.63 28.08 49.00 98.00 233.08 329.63 622.25 28.09 49.00 98.00 233.08 329.63 622.25 28.10 49.00 98.00 233.08 622.25 28.11 49.00 98.00 233.08 622.25 28.12 49.00 98.00 233.08 622.25 28.13 49.00 98.00 233.08 622.25 28.14 49.00 98.00 233.08 622.25 28.15 49.00 98.00 233.08 622.25 28.16 49.00 98.00 233.08 622.25 28.17 49.00 98.00 233.08 622.25 28.18 49.00 98.00 233.08 622.25 28.19 49.00 98.00 233.08 28.20 49.00 98.00 233.08 28.21 49.00 98.00 233.08 28.22 49.00 98.00 233.08 622.25 28.23 49.00 98.00 233.08 622.25 28.24 49.00 98.00 233.08 622.25 28.25 49.00 98.00 233.08 622.25 28.26 49.00 98.00 233.08 622.25 28.27 49.00 98.00 233.08 622.25 28.28 49.00 98.00 233.08 622.25 28.29 49.00 98.00 233.08 622.25 28.30 49.00 98.00 233.08 622.25 28.31 49.00 98.00 233.08 622.25 28.32 49.00 98.00 233.08 622.25 28.33 49.00 98.00 233.08 622.25 28.34 49.00 98.00 233.08 622.25 28.35 49.00 98.00 233.08 622.25 28.36 49.00 98.00 233.08 622.25 28.37 49.00 98.00 233.08 622.25 28.38 49.00 98.00 233.08 622.25 28.39 49.00 98.00 233.08 622.25 28.40 98.00 233.08 622.25 28.41 98.00 233.08 622.25 28.42 98.00 233.08 622.25 28.43 98.00 233.08 622.25 28.44 98.00 233.08 622.25 28.45 98.00 233.08 311.13 622.25 28.46 98.00 233.08 311.13 622.25 28.47 49.00 98.00 233.08 311.13 622.25 28.48 49.00 98.00 233.08 311.13 622.25 28.49 49.00 98.00 233.08 311.13 622.25 28.50 49.00 98.00 233.08 311.13 622.25 28.51 49.00 98.00 233.08 311.13 622.25 28.52 49.00 98.00 233.08 311.13 622.25 28.53 49.00 98.00 233.08 311.13 622.25 28.54 49.00 98.00 311.13 622.25 28.55 49.00 98.00 311.13 622.25 28.56 49.00 98.00 311.13 622.25 28.57 49.00 98.00 311.13 622.25 28.58 49.00 98.00 311.13 622.25 28.59 49.00 98.00 28.60 49.00 98.00 28.61 49.00 98.00 28.62 49.00 98.00 28.63 98.00 28.64 98.00 622.25 28.65 98.00 622.25 28.66 622.25 28.67 622.25 28.68 246.94 622.25 28.69 246.94 622.25 28.70 103.83 246.94 622.25 28.71 103.83 246.94 622.25 28.72 103.83 246.94 622.25 28.73 103.83 246.94 622.25 28.74 103.83 246.94 622.25 28.75 103.83 246.94 622.25 28.76 103.83 246.94 622.25 28.77 103.83 622.25 28.78 103.83 622.25 28.79 103.83 622.25 28.80 103.83 246.94 622.25 28.81 103.83 246.94 622.25 28.82 103.83 246.94 622.25 28.83 103.83 246.94 622.25 28.84 103.83 246.94 622.25 28.85 103.83 246.94 622.25 28.86 103.83 246.94 622.25 28.87 103.83 246.94 622.25 28.88 103.83 246.94 622.25 28.89 103.83 246.94 311.13 622.25 28.90 103.83 246.94 311.13 622.25 28.91 103.83 246.94 311.13 622.25 28.92 103.83 246.94 311.13 622.25 28.93 103.83 311.13 622.25 28.94 103.83 311.13 622.25 28.95 103.83 311.13 622.25 28.96 103.83 311.13 622.25 28.97 103.83 311.13 622.25 28.98 103.83 311.13 622.25 28.99 103.83 311.13 622.25 29.00 103.83 311.13 622.25 29.01 103.83 311.13 622.25 29.02 103.83 311.13 622.25 29.03 103.83 622.25 29.04 103.83 622.25 29.05 103.83 622.25 1244.51 29.06 103.83 622.25 1244.51 29.07 103.83 622.25 1244.51 29.08 103.83 311.13 622.25 932.33 1244.51 29.09 103.83 311.13 622.25 932.33 1244.51 29.10 103.83 311.13 622.25 932.33 1244.51 29.11 103.83 311.13 622.25 932.33 1244.51 29.12 103.83 311.13 622.25 932.33 29.13 103.83 311.13 622.25 932.33 29.14 103.83 311.13 622.25 932.33 29.15 103.83 311.13 622.25 932.33 29.16 103.83 311.13 622.25 932.33 29.17 103.83 311.13 622.25 932.33 29.18 103.83 311.13 622.25 932.33 29.19 103.83 311.13 622.25 29.20 103.83 311.13 622.25 29.21 103.83 311.13 622.25 29.22 103.83 311.13 622.25 29.23 103.83 311.13 622.25 29.24 103.83 311.13 622.25 29.25 103.83 311.13 622.25 29.26 103.83 311.13 622.25 29.27 103.83 311.13 622.25 29.28 311.13 29.29 311.13 1244.51 29.30 311.13 1244.51 29.31 311.13 622.25 1244.51 29.32 311.13 622.25 1244.51 29.33 311.13 622.25 1244.51 29.34 311.13 622.25 1244.51 29.35 311.13 622.25 29.36 311.13 622.25 29.37 311.13 622.25 29.38 311.13 622.25 29.39 311.13 622.25 29.40 622.25 29.41 622.25 29.42 622.25 29.43 622.25 29.44 622.25 29.45 311.13 622.25 29.46 311.13 622.25 29.47 311.13 622.25 29.48 311.13 622.25 29.49 311.13 622.25 29.50 311.13 622.25 29.51 311.13 622.25 29.52 311.13 622.25 29.53 311.13 622.25 29.54 311.13 622.25 29.55 311.13 622.25 29.56 622.25 29.57 622.25 29.58 29.59 29.60 29.61 29.62 29.63 29.64 29.65 29.66 29.67 29.68 29.69 29.70 29.71 29.72 29.73 29.74 29.75 29.76 29.77 29.78 29.79 29.80 92.50 29.81 92.50 29.82 92.50 29.83 92.50 29.84 92.50 29.85 92.50 29.86 92.50 29.87 92.50 29.88 92.50 29.89 92.50 29.90 92.50 29.91 92.50 185.00 29.92 92.50 185.00 29.93 185.00 29.94 185.00 523.25 29.95 185.00 523.25 29.96 185.00 523.25 29.97 185.00 523.25 29.98 92.50 185.00 523.25 29.99 92.50 185.00 523.25 30.00 92.50 523.25 30.01 92.50 523.25 1046.50 30.02 92.50 523.25 1046.50 30.03 92.50 523.25 1046.50 30.04 92.50 523.25 1046.50 30.05 92.50 523.25 1046.50 30.06 92.50 523.25 1046.50 30.07 523.25 1046.50 30.08 523.25 1046.50 30.09 523.25 1046.50 30.10 523.25 1046.50 30.11 523.25 1046.50 30.12 523.25 1046.50 30.13 523.25 1046.50 30.14 185.00 523.25 30.15 185.00 523.25 30.16 185.00 523.25 30.17 185.00 523.25 30.18 185.00 523.25 30.19 185.00 523.25 1046.50 30.20 185.00 523.25 1046.50 30.21 185.00 220.00 523.25 1046.50 30.22 185.00 220.00 523.25 1046.50 30.23 185.00 220.00 523.25 1046.50 30.24 185.00 220.00 523.25 1046.50 30.25 185.00 220.00 523.25 1046.50 30.26 185.00 220.00 523.25 1046.50 30.27 185.00 220.00 523.25 1046.50 30.28 185.00 220.00 523.25 1046.50 30.29 185.00 220.00 523.25 1046.50 30.30 185.00 220.00 523.25 1046.50 30.31 185.00 220.00 523.25 1046.50 30.32 185.00 220.00 523.25 1046.50 30.33 220.00 523.25 1046.50 30.34 220.00 523.25 1046.50 30.35 185.00 220.00 523.25 1046.50 30.36 185.00 220.00 523.25 1046.50 30.37 185.00 220.00 523.25 1046.50 30.38 185.00 220.00 523.25 1046.50 30.39 185.00 220.00 523.25 1046.50 30.40 185.00 220.00 523.25 1046.50 30.41 185.00 220.00 523.25 1046.50 30.42 185.00 220.00 523.25 1046.50 30.43 185.00 220.00 523.25 1046.50 30.44 185.00 220.00 523.25 1046.50 30.45 185.00 220.00 523.25 1046.50 30.46 185.00 220.00 523.25 1046.50 30.47 185.00 220.00 523.25 1046.50 30.48 185.00 220.00 523.25 1046.50 30.49 220.00 369.99 523.25 1046.50 30.50 220.00 369.99 523.25 1046.50 30.51 220.00 369.99 523.25 1046.50 30.52 220.00 369.99 523.25 1046.50 30.53 220.00 369.99 523.25 1046.50 30.54 220.00 369.99 523.25 1046.50 30.55 220.00 369.99 523.25 1046.50 30.56 220.00 369.99 523.25 1046.50 30.57 220.00 369.99 523.25 1046.50 30.58 220.00 369.99 523.25 1046.50 30.59 185.00 220.00 369.99 523.25 1046.50 30.60 185.00 220.00 369.99 523.25 1046.50 30.61 185.00 220.00 369.99 523.25 1046.50 30.62 185.00 220.00 369.99 523.25 1046.50 30.63 185.00 220.00 369.99 523.25 1046.50 30.64 185.00 220.00 369.99 523.25 1046.50 30.65 185.00 220.00 523.25 1046.50 30.66 185.00 220.00 523.25 1046.50 30.67 185.00 220.00 523.25 1046.50 30.68 185.00 220.00 523.25 1046.50 30.69 185.00 220.00 523.25 1046.50 30.70 185.00 369.99 523.25 1046.50 30.71 185.00 369.99 523.25 1046.50 30.72 185.00 369.99 523.25 1046.50 30.73 185.00 369.99 523.25 1046.50 30.74 185.00 369.99 523.25 1046.50 30.75 185.00 369.99 415.30 523.25 1046.50 30.76 185.00 369.99 415.30 523.25 1046.50 30.77 185.00 415.30 523.25 1046.50 30.78 185.00 415.30 523.25 1046.50 30.79 164.81 415.30 523.25 1046.50 30.80 164.81 415.30 523.25 1046.50 30.81 164.81 415.30 523.25 1046.50 30.82 164.81 415.30 523.25 554.37 1046.50 30.83 164.81 415.30 523.25 554.37 1046.50 30.84 164.81 415.30 523.25 554.37 1046.50 30.85 164.81 415.30 523.25 554.37 1046.50 30.86 164.81 415.30 554.37 30.87 164.81 415.30 554.37 30.88 164.81 415.30 554.37 30.89 82.41 164.81 415.30 554.37 30.90 82.41 164.81 415.30 554.37 30.91 82.41 415.30 554.37 30.92 82.41 415.30 554.37 30.93 82.41 415.30 554.37 30.94 82.41 415.30 554.37 30.95 82.41 415.30 554.37 30.96 82.41 415.30 523.25 554.37 30.97 82.41 415.30 523.25 554.37 30.98 164.81 277.18 415.30 523.25 554.37 30.99 164.81 277.18 415.30 523.25 554.37 31.00 164.81 277.18 415.30 523.25 554.37 31.01 164.81 277.18 415.30 523.25 554.37 31.02 164.81 277.18 415.30 523.25 554.37 31.03 164.81 277.18 415.30 523.25 554.37 31.04 164.81 277.18 415.30 523.25 554.37 31.05 164.81 277.18 415.30 554.37 31.06 164.81 277.18 415.30 554.37 31.07 164.81 277.18 415.30 554.37 31.08 164.81 277.18 415.30 554.37 31.09 164.81 277.18 415.30 554.37 31.10 164.81 277.18 415.30 554.37 31.11 164.81 277.18 415.30 554.37 31.12 164.81 415.30 554.37 31.13 164.81 415.30 554.37 31.14 164.81 415.30 554.37 31.15 164.81 415.30 554.37 31.16 554.37 31.17 82.41 277.18 554.37 31.18 82.41 277.18 554.37 31.19 82.41 277.18 415.30 554.37 31.20 82.41 277.18 415.30 554.37 31.21 82.41 277.18 415.30 554.37 31.22 82.41 277.18 415.30 554.37 31.23 82.41 277.18 415.30 554.37 31.24 82.41 277.18 415.30 554.37 31.25 82.41 277.18 415.30 554.37 31.26 277.18 415.30 554.37 31.27 277.18 415.30 554.37 31.28 277.18 415.30 554.37 31.29 277.18 415.30 554.37 31.30 277.18 415.30 554.37 31.31 207.65 277.18 415.30 554.37 31.32 207.65 277.18 415.30 554.37 31.33 207.65 277.18 415.30 554.37 31.34 207.65 277.18 415.30 554.37 31.35 207.65 277.18 415.30 554.37 31.36 207.65 277.18 415.30 554.37 31.37 207.65 277.18 415.30 554.37 31.38 207.65 277.18 415.30 554.37 31.39 207.65 277.18 415.30 554.37 31.40 207.65 277.18 415.30 554.37 31.41 207.65 277.18 415.30 554.37 31.42 207.65 277.18 415.30 31.43 207.65 277.18 415.30 31.44 207.65 277.18 415.30 554.37 31.45 207.65 277.18 415.30 554.37 31.46 207.65 277.18 415.30 554.37 31.47 207.65 277.18 415.30 554.37 31.48 207.65 277.18 415.30 554.37 31.49 277.18 415.30 554.37 31.50 277.18 415.30 554.37 31.51 277.18 415.30 554.37 31.52 277.18 415.30 554.37 31.53 277.18 415.30 554.37 31.54 277.18 415.30 554.37 31.55 277.18 415.30 554.37 31.56 277.18 415.30 31.57 277.18 415.30 31.58 277.18 415.30 31.59 277.18 415.30 31.60 277.18 415.30 31.61 277.18 415.30 554.37 31.62 277.18 415.30 554.37 31.63 277.18 415.30 554.37 31.64 277.18 415.30 554.37 31.65 82.41 277.18 415.30 554.37 31.66 82.41 277.18 415.30 554.37 31.67 82.41 277.18 554.37 31.68 82.41 207.65 277.18 554.37 31.69 82.41 207.65 277.18 554.37 31.70 82.41 207.65 277.18 554.37 31.71 82.41 207.65 277.18 554.37 31.72 82.41 207.65 277.18 554.37 31.73 82.41 207.65 277.18 554.37 31.74 82.41 207.65 277.18 554.37 31.75 82.41 207.65 277.18 554.37 31.76 82.41 207.65 277.18 554.37 31.77 82.41 277.18 31.78 82.41 277.18 31.79 277.18 31.80 277.18 31.81 277.18 31.82 277.18 369.99 31.83 277.18 369.99 31.84 155.56 277.18 369.99 31.85 155.56 277.18 369.99 31.86 155.56 277.18 369.99 31.87 155.56 277.18 369.99 31.88 155.56 277.18 369.99 31.89 155.56 277.18 369.99 31.90 155.56 277.18 369.99 31.91 277.18 369.99 31.92 277.18 369.99 31.93 277.18 369.99 31.94 277.18 369.99 31.95 277.18 369.99 31.96 277.18 369.99 31.97 277.18 369.99 31.98 277.18 369.99 31.99 277.18 369.99 32.00 277.18 369.99 32.01 277.18 369.99 32.02 277.18 369.99 32.03 277.18 369.99 32.04 277.18 369.99 32.05 220.00 277.18 369.99 32.06 220.00 277.18 369.99 32.07 77.78 220.00 277.18 369.99 32.08 77.78 220.00 277.18 369.99 32.09 77.78 220.00 277.18 369.99 32.10 77.78 220.00 277.18 369.99 32.11 77.78 220.00 277.18 369.99 32.12 77.78 220.00 277.18 369.99 32.13 77.78 220.00 277.18 369.99 32.14 77.78 220.00 277.18 369.99 32.15 77.78 220.00 277.18 369.99 32.16 77.78 155.56 220.00 277.18 369.99 32.17 77.78 155.56 220.00 277.18 369.99 32.18 155.56 220.00 277.18 369.99 32.19 155.56 220.00 277.18 369.99 32.20 155.56 220.00 277.18 369.99 32.21 155.56 220.00 277.18 369.99 32.22 155.56 220.00 277.18 369.99 32.23 155.56 220.00 277.18 369.99 32.24 155.56 220.00 277.18 369.99 32.25 155.56 220.00 277.18 369.99 32.26 77.78 155.56 220.00 277.18 369.99 32.27 77.78 155.56 220.00 277.18 369.99 32.28 77.78 220.00 277.18 369.99 32.29 77.78 220.00 277.18 369.99 32.30 77.78 220.00 369.99 32.31 77.78 220.00 369.99 32.32 77.78 220.00 32.33 77.78 185.00 220.00 32.34 77.78 185.00 220.00 32.35 77.78 185.00 220.00 32.36 77.78 185.00 220.00 32.37 77.78 185.00 220.00 32.38 77.78 185.00 220.00 32.39 77.78 185.00 220.00 32.40 77.78 185.00 220.00 32.41 77.78 185.00 220.00 32.42 155.56 185.00 220.00 32.43 155.56 185.00 220.00 32.44 155.56 185.00 220.00 369.99 32.45 155.56 185.00 220.00 369.99 32.46 155.56 185.00 220.00 369.99 32.47 155.56 185.00 220.00 369.99 32.48 155.56 185.00 220.00 369.99 32.49 155.56 185.00 220.00 369.99 32.50 155.56 185.00 220.00 369.99 32.51 185.00 220.00 369.99 32.52 185.00 220.00 369.99 32.53 185.00 220.00 32.54 185.00 220.00 32.55 185.00 220.00 32.56 185.00 220.00 32.57 185.00 220.00 32.58 185.00 220.00 32.59 185.00 220.00 32.60 220.00 32.61 155.56 220.00 369.99 32.62 155.56 220.00 369.99 32.63 155.56 220.00 369.99 32.64 155.56 220.00 369.99 32.65 155.56 220.00 277.18 369.99 32.66 155.56 220.00 277.18 369.99 32.67 220.00 277.18 369.99 32.68 220.00 277.18 369.99 32.69 220.00 277.18 369.99 32.70 220.00 277.18 369.99 32.71 220.00 277.18 369.99 32.72 220.00 277.18 32.73 220.00 277.18 32.74 220.00 277.18 32.75 220.00 277.18 32.76 220.00 277.18 32.77 220.00 277.18 32.78 220.00 277.18 32.79 220.00 277.18 32.80 220.00 277.18 32.81 220.00 32.82 220.00 32.83 220.00 32.84 220.00 32.85 220.00 32.86 220.00 277.18 32.87 220.00 277.18 32.88 220.00 277.18 32.89 220.00 277.18 32.90 277.18 32.91 277.18 440.00 32.92 277.18 440.00 32.93 277.18 440.00 32.94 277.18 440.00 32.95 277.18 329.63 440.00 32.96 277.18 329.63 440.00 32.97 329.63 440.00 32.98 329.63 440.00 32.99 329.63 440.00 33.00 329.63 440.00 33.01 329.63 440.00 33.02 329.63 440.00 33.03 329.63 440.00 33.04 329.63 440.00 33.05 329.63 440.00 33.06 329.63 440.00 33.07 329.63 440.00 33.08 329.63 440.00 33.09 329.63 440.00 33.10 329.63 440.00 33.11 329.63 440.00 33.12 329.63 440.00 33.13 329.63 440.00 33.14 329.63 440.00 33.15 329.63 440.00 33.16 329.63 440.00 33.17 329.63 440.00 33.18 329.63 440.00 33.19 329.63 440.00 33.20 329.63 440.00 33.21 329.63 440.00 33.22 329.63 440.00 33.23 440.00 33.24 440.00 33.25 440.00 33.26 329.63 440.00 33.27 329.63 440.00 33.28 329.63 440.00 33.29 329.63 440.00 33.30 329.63 440.00 33.31 329.63 440.00 33.32 329.63 440.00 33.33 329.63 440.00 33.34 329.63 440.00 33.35 329.63 440.00 33.36 329.63 440.00 33.37 329.63 440.00 33.38 329.63 440.00 33.39 329.63 440.00 33.40 329.63 440.00 33.41 329.63 440.00 33.42 329.63 33.43 329.63 33.44 329.63 33.45 329.63 33.46 329.63 33.47 329.63 440.00 33.48 329.63 440.00 33.49 329.63 440.00 33.50 329.63 440.00 33.51 329.63 440.00 33.52 329.63 440.00 33.53 329.63 440.00 33.54 329.63 440.00 33.55 329.63 440.00 33.56 329.63 440.00 33.57 329.63 440.00 33.58 329.63 440.00 33.59 329.63 440.00 33.60 329.63 440.00 33.61 329.63 440.00 33.62 329.63 440.00 33.63 329.63 440.00 33.64 329.63 440.00 33.65 329.63 440.00 33.66 329.63 440.00 33.67 329.63 33.68 329.63 33.69 329.63 33.70 329.63 33.71 329.63 33.72 329.63 33.73 329.63 33.74 329.63 33.75 329.63 33.76 329.63 33.77 329.63 33.78 329.63 33.79 329.63 33.80 329.63 33.81 329.63 33.82 329.63 33.83 329.63 33.84 329.63 33.85 329.63 33.86 65.41 329.63 33.87 65.41 329.63 33.88 65.41 329.63 33.89 65.41 329.63 33.90 65.41 329.63 33.91 65.41 329.63 33.92 65.41 329.63 33.93 65.41 33.94 65.41 33.95 65.41 33.96 65.41 33.97 65.41 33.98 65.41 33.99 65.41 34.00 34.01 34.02 34.03 34.04 34.05 65.41 34.06 65.41 34.07 65.41 34.08 65.41 34.09 65.41 34.10 65.41 34.11 65.41 34.12 65.41 34.13 65.41 34.14 65.41 34.15 65.41 34.16 65.41 34.17 65.41 34.18 65.41 34.19 65.41 34.20 65.41 34.21 65.41 311.13 34.22 65.41 311.13 34.23 65.41 311.13 34.24 65.41 311.13 34.25 65.41 311.13 34.26 65.41 311.13 34.27 65.41 311.13 34.28 65.41 311.13 34.29 65.41 311.13 34.30 65.41 311.13 34.31 65.41 311.13 34.32 65.41 34.33 65.41 34.34 65.41 34.35 65.41 34.36 65.41 34.37 65.41 34.38 65.41 34.39 34.40 34.41 34.42 34.43 34.44 34.45 34.46 34.47 34.48 34.49 34.50 34.51 34.52 34.53 34.54 34.55 34.56 34.57 34.58 34.59 34.60 34.61 34.62 34.63 34.64 34.65 34.66 34.67 34.68 34.69 34.70 34.71 34.72 34.73 34.74 34.75 34.76 34.77 34.78 34.79 34.80 34.81 34.82 34.83 34.84 34.85 34.86 34.87 34.88 34.89 34.90 34.91 34.92 34.93 34.94 34.95 415.30 34.96 415.30 34.97 415.30 34.98 415.30 34.99 415.30 35.00 415.30 35.01 415.30 35.02 35.03 35.04 35.05 35.06 35.07 35.08 35.09 138.59 35.10 138.59 35.11 138.59 35.12 138.59 35.13 138.59 35.14 138.59 415.30 35.15 138.59 415.30 35.16 138.59 415.30 35.17 138.59 415.30 35.18 415.30 35.19 415.30 35.20 415.30 35.21 415.30 35.22 415.30 35.23 415.30 35.24 415.30 35.25 415.30 35.26 415.30 35.27 415.30 35.28 415.30 35.29 415.30 35.30 415.30 35.31 415.30 35.32 415.30 35.33 415.30 35.34 415.30 35.35 415.30 35.36 415.30 35.37 415.30 35.38 415.30 35.39 415.30 35.40 415.30 35.41 415.30 35.42 415.30 35.43 415.30 35.44 35.45 35.46 35.47 35.48 35.49 415.30 35.50 415.30 35.51 415.30 35.52 415.30 35.53 415.30 35.54 415.30 35.55 415.30 35.56 415.30 35.57 415.30 35.58 415.30 35.59 415.30 35.60 35.61 35.62 35.63 35.64 35.65 35.66 35.67 415.30 35.68 415.30 35.69 415.30 35.70 415.30 35.71 415.30 35.72 415.30 35.73 415.30 35.74 415.30 35.75 415.30 35.76 415.30 35.77 415.30 35.78 415.30 35.79 415.30 35.80 415.30 35.81 415.30 35.82 415.30 35.83 415.30 35.84 415.30 35.85 35.86 35.87 35.88 415.30 35.89 415.30 35.90 415.30 35.91 415.30 35.92 415.30 35.93 415.30 35.94 415.30 35.95 415.30 35.96 415.30 35.97 415.30 35.98 415.30 35.99 415.30 36.00 415.30 36.01 415.30 36.02 415.30 36.03 415.30 36.04 36.05 36.06 36.07 36.08 36.09 36.10 36.11 36.12 36.13 36.14 36.15 36.16 36.17 36.18 36.19 36.20 36.21 36.22 36.23 36.24 36.25 36.26 36.27 36.28 36.29 36.30 36.31 36.32 36.33 36.34 36.35 36.36 36.37 36.38 36.39 36.40 36.41 36.42 36.43 36.44 36.45 36.46 36.47 36.48 36.49 36.50 36.51 36.52 36.53 36.54 36.55 36.56 36.57 36.58 36.59 36.60 36.61 36.62 36.63 36.64 36.65 36.66 36.67 36.68 36.69 36.70 36.71 36.72 36.73 36.74 36.75 36.76 36.77 36.78 36.79 36.80 36.81 36.82 36.83 36.84 36.85 36.86 36.87 36.88 36.89 36.90 36.91 36.92 36.93 36.94 36.95 36.96 36.97 36.98 36.99 37.00 37.01 37.02 mir_eval-0.8.2/tests/data/multipitch/est01.txt000066400000000000000000001570321475740344600212770ustar00rootroot000000000000000.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.30 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.40 0.41 0.42 0.43 0.44 0.45 0.46 0.47 0.48 0.49 0.50 0.51 0.52 0.53 0.54 0.55 0.56 0.57 0.58 0.59 0.60 0.61 0.62 0.63 0.64 0.65 0.66 0.67 0.68 0.69 0.70 0.71 0.72 0.73 0.74 0.75 440.00 0.76 440.00 0.77 440.00 0.78 440.00 0.79 440.00 0.80 440.00 0.81 440.00 0.82 440.00 0.83 440.00 0.84 440.00 0.85 440.00 0.86 440.00 0.87 440.00 0.88 440.00 0.89 440.00 0.90 440.00 0.91 440.00 0.92 440.00 0.93 440.00 0.94 440.00 0.95 440.00 0.96 220.00 440.00 0.97 220.00 440.00 0.98 220.00 440.00 0.99 220.00 440.00 1.00 220.00 440.00 1.01 220.00 440.00 1.02 220.00 1.03 220.00 1.04 220.00 1.05 220.00 1.06 220.00 1.07 220.00 440.00 1.08 220.00 440.00 1.09 220.00 440.00 1.10 220.00 440.00 1.11 220.00 440.00 1.12 440.00 1.13 440.00 1.14 220.00 440.00 1.15 220.00 440.00 1.16 220.00 440.00 1.17 220.00 440.00 1.18 220.00 440.00 1.19 220.00 440.00 1.20 220.00 440.00 1.21 220.00 440.00 1.22 220.00 440.00 1.23 220.00 440.00 1.24 220.00 440.00 1.25 220.00 440.00 1.26 220.00 440.00 1.27 220.00 440.00 1.28 220.00 440.00 1.29 220.00 440.00 1.30 220.00 440.00 1.31 220.00 440.00 1.32 220.00 440.00 1.33 440.00 1.34 440.00 1.35 1.36 1.37 1.38 1.39 1.40 1.41 1.42 1.43 1.44 1.45 1.46 1.47 1.48 1.49 1.50 1.51 1.52 1.53 1.54 1.55 1.56 1.57 1.58 261.63 1.59 261.63 1.60 261.63 1.61 261.63 523.25 1.62 261.63 523.25 1.63 261.63 523.25 1.64 261.63 523.25 1.65 261.63 523.25 1.66 261.63 523.25 1.67 261.63 523.25 1.68 261.63 523.25 1.69 261.63 523.25 1.70 261.63 523.25 1.71 261.63 523.25 1.72 261.63 523.25 1.73 261.63 523.25 1.74 523.25 1.75 523.25 1.76 523.25 1.77 1.78 1.79 1.80 1.81 1.82 1.83 1.84 1.85 1.86 1.87 1.88 1.89 1.90 1.91 1.92 1.93 1.94 1.95 1.96 329.63 1.97 329.63 1.98 329.63 1.99 329.63 2.00 329.63 2.01 329.63 2.02 329.63 2.03 329.63 2.04 329.63 2.05 329.63 2.06 329.63 2.07 329.63 2.08 329.63 2.09 329.63 2.10 329.63 2.11 329.63 2.12 329.63 2.13 329.63 2.14 329.63 2.15 329.63 2.16 329.63 2.17 329.63 2.18 329.63 2.19 329.63 2.20 329.63 2.21 329.63 2.22 329.63 2.23 329.63 2.24 329.63 2.25 329.63 2.26 329.63 2.27 329.63 2.28 329.63 2.29 329.63 2.30 329.63 2.31 329.63 2.32 329.63 2.33 329.63 2.34 329.63 2.35 329.63 2.36 329.63 2.37 329.63 2.38 329.63 2.39 329.63 2.40 329.63 2.41 329.63 2.42 329.63 2.43 329.63 2.44 164.81 329.63 2.45 164.81 329.63 2.46 164.81 329.63 2.47 164.81 329.63 2.48 164.81 329.63 2.49 164.81 329.63 2.50 164.81 329.63 2.51 164.81 329.63 2.52 164.81 329.63 2.53 329.63 2.54 329.63 2.55 329.63 2.56 329.63 2.57 329.63 2.58 329.63 2.59 329.63 2.60 2.61 2.62 2.63 2.64 2.65 2.66 2.67 2.68 2.69 2.70 2.71 2.72 2.73 2.74 2.75 2.76 2.77 2.78 2.79 2.80 2.81 2.82 2.83 2.84 2.85 2.86 2.87 2.88 2.89 2.90 2.91 2.92 2.93 2.94 2.95 2.96 2.97 2.98 2.99 3.00 329.63 3.01 329.63 3.02 329.63 3.03 329.63 3.04 329.63 3.05 329.63 3.06 329.63 3.07 329.63 3.08 329.63 3.09 329.63 349.23 3.10 329.63 349.23 3.11 349.23 3.12 349.23 3.13 349.23 3.14 349.23 3.15 349.23 3.16 174.61 349.23 3.17 174.61 349.23 3.18 174.61 349.23 3.19 174.61 349.23 3.20 174.61 349.23 3.21 174.61 349.23 3.22 174.61 349.23 3.23 174.61 349.23 3.24 174.61 349.23 3.25 174.61 349.23 3.26 174.61 349.23 3.27 174.61 349.23 3.28 174.61 349.23 3.29 174.61 349.23 3.30 174.61 349.23 3.31 174.61 349.23 3.32 174.61 349.23 3.33 174.61 349.23 3.34 174.61 349.23 3.35 174.61 3.36 174.61 3.37 329.63 3.38 329.63 3.39 329.63 3.40 329.63 3.41 329.63 3.42 329.63 3.43 329.63 3.44 329.63 3.45 329.63 3.46 329.63 3.47 329.63 3.48 329.63 3.49 329.63 3.50 329.63 3.51 3.52 3.53 146.83 3.54 146.83 3.55 146.83 3.56 146.83 3.57 146.83 3.58 146.83 3.59 146.83 3.60 146.83 3.61 146.83 3.62 146.83 3.63 146.83 293.66 3.64 146.83 293.66 3.65 293.66 3.66 293.66 3.67 293.66 3.68 293.66 3.69 293.66 3.70 293.66 3.71 293.66 3.72 261.63 3.73 261.63 3.74 261.63 3.75 261.63 3.76 261.63 3.77 261.63 3.78 261.63 3.79 261.63 3.80 261.63 3.81 261.63 3.82 261.63 3.83 261.63 3.84 261.63 3.85 261.63 3.86 261.63 3.87 261.63 3.88 261.63 3.89 261.63 3.90 261.63 3.91 261.63 3.92 261.63 3.93 261.63 3.94 261.63 3.95 261.63 3.96 261.63 3.97 261.63 3.98 261.63 3.99 261.63 4.00 261.63 4.01 261.63 4.02 4.03 4.04 4.05 4.06 4.07 4.08 4.09 4.10 4.11 4.12 4.13 4.14 4.15 4.16 220.00 4.17 220.00 4.18 220.00 4.19 220.00 4.20 220.00 4.21 220.00 4.22 220.00 4.23 220.00 4.24 220.00 4.25 220.00 4.26 220.00 4.27 220.00 4.28 220.00 4.29 220.00 4.30 220.00 4.31 220.00 4.32 220.00 4.33 220.00 4.34 220.00 4.35 220.00 4.36 220.00 4.37 220.00 4.38 220.00 4.39 220.00 4.40 220.00 4.41 220.00 4.42 110.00 220.00 4.43 110.00 220.00 4.44 110.00 4.45 110.00 4.46 110.00 4.47 110.00 4.48 110.00 4.49 110.00 220.00 4.50 110.00 220.00 4.51 220.00 4.52 220.00 4.53 220.00 4.54 220.00 4.55 220.00 4.56 220.00 4.57 220.00 4.58 220.00 4.59 220.00 4.60 220.00 4.61 220.00 4.62 220.00 4.63 220.00 4.64 220.00 4.65 220.00 4.66 220.00 4.67 220.00 4.68 220.00 4.69 220.00 4.70 220.00 4.71 220.00 4.72 220.00 4.73 220.00 4.74 220.00 4.75 220.00 4.76 220.00 4.77 110.00 220.00 4.78 110.00 220.00 4.79 110.00 220.00 4.80 110.00 220.00 4.81 110.00 220.00 4.82 110.00 220.00 4.83 110.00 220.00 4.84 110.00 220.00 4.85 110.00 220.00 4.86 110.00 220.00 4.87 110.00 220.00 4.88 220.00 4.89 220.00 4.90 110.00 220.00 4.91 110.00 220.00 4.92 110.00 220.00 4.93 110.00 220.00 4.94 110.00 220.00 4.95 110.00 220.00 4.96 110.00 220.00 4.97 110.00 220.00 4.98 110.00 220.00 4.99 110.00 220.00 5.00 110.00 220.00 5.01 110.00 220.00 5.02 220.00 5.03 220.00 5.04 110.00 220.00 5.05 110.00 220.00 5.06 110.00 220.00 5.07 110.00 220.00 5.08 110.00 220.00 5.09 110.00 220.00 5.10 110.00 220.00 5.11 110.00 220.00 5.12 110.00 220.00 5.13 220.00 5.14 220.00 5.15 220.00 5.16 220.00 5.17 220.00 5.18 220.00 5.19 220.00 5.20 220.00 5.21 220.00 5.22 220.00 5.23 220.00 5.24 220.00 5.25 5.26 5.27 5.28 5.29 5.30 220.00 5.31 220.00 5.32 220.00 5.33 220.00 5.34 220.00 5.35 220.00 5.36 220.00 5.37 220.00 5.38 220.00 5.39 5.40 5.41 5.42 5.43 5.44 5.45 5.46 5.47 5.48 5.49 5.50 5.51 5.52 5.53 5.54 5.55 5.56 5.57 5.58 5.59 5.60 5.61 5.62 5.63 5.64 5.65 5.66 5.67 82.41 5.68 82.41 5.69 82.41 5.70 82.41 5.71 82.41 5.72 82.41 5.73 82.41 5.74 82.41 5.75 82.41 5.76 82.41 5.77 82.41 5.78 82.41 5.79 82.41 5.80 82.41 5.81 82.41 5.82 82.41 5.83 82.41 5.84 82.41 5.85 82.41 5.86 82.41 5.87 82.41 5.88 82.41 5.89 82.41 5.90 82.41 5.91 82.41 5.92 82.41 5.93 82.41 5.94 82.41 5.95 82.41 5.96 82.41 5.97 82.41 5.98 82.41 5.99 82.41 6.00 82.41 6.01 82.41 6.02 82.41 6.03 82.41 6.04 82.41 6.05 82.41 6.06 82.41 6.07 82.41 6.08 82.41 6.09 82.41 6.10 82.41 6.11 82.41 6.12 82.41 6.13 82.41 6.14 82.41 6.15 82.41 6.16 82.41 6.17 82.41 6.18 82.41 6.19 82.41 6.20 82.41 6.21 82.41 6.22 82.41 6.23 82.41 6.24 82.41 6.25 82.41 6.26 82.41 6.27 82.41 6.28 82.41 6.29 82.41 6.30 82.41 6.31 82.41 6.32 82.41 6.33 82.41 6.34 82.41 6.35 82.41 6.36 82.41 6.37 82.41 6.38 82.41 6.39 82.41 6.40 82.41 6.41 82.41 6.42 82.41 6.43 82.41 6.44 82.41 6.45 82.41 6.46 82.41 6.47 82.41 6.48 82.41 6.49 82.41 6.50 82.41 6.51 82.41 6.52 82.41 6.53 82.41 6.54 82.41 6.55 82.41 6.56 82.41 6.57 82.41 6.58 82.41 6.59 82.41 6.60 82.41 6.61 82.41 6.62 82.41 6.63 82.41 6.64 82.41 6.65 82.41 6.66 82.41 6.67 82.41 6.68 82.41 6.69 82.41 6.70 82.41 6.71 82.41 6.72 82.41 6.73 82.41 6.74 82.41 6.75 82.41 6.76 82.41 6.77 82.41 6.78 82.41 6.79 82.41 6.80 82.41 6.81 82.41 6.82 82.41 6.83 82.41 92.50 6.84 82.41 92.50 6.85 82.41 92.50 6.86 82.41 92.50 6.87 82.41 92.50 6.88 82.41 92.50 6.89 82.41 92.50 6.90 82.41 92.50 6.91 82.41 92.50 6.92 82.41 92.50 6.93 82.41 92.50 6.94 92.50 6.95 92.50 6.96 92.50 6.97 92.50 6.98 92.50 6.99 92.50 7.00 92.50 7.01 92.50 7.02 92.50 7.03 92.50 7.04 92.50 164.81 7.05 92.50 164.81 7.06 92.50 164.81 7.07 92.50 164.81 7.08 92.50 164.81 7.09 92.50 164.81 7.10 92.50 164.81 7.11 92.50 164.81 7.12 92.50 164.81 7.13 92.50 164.81 7.14 92.50 164.81 7.15 92.50 164.81 7.16 92.50 164.81 7.17 92.50 164.81 7.18 92.50 7.19 92.50 7.20 92.50 7.21 92.50 7.22 92.50 7.23 92.50 220.00 7.24 92.50 220.00 7.25 92.50 220.00 7.26 92.50 220.00 7.27 92.50 220.00 7.28 92.50 220.00 7.29 92.50 220.00 7.30 92.50 220.00 7.31 92.50 220.00 7.32 92.50 220.00 7.33 92.50 220.00 7.34 92.50 220.00 7.35 92.50 220.00 7.36 92.50 220.00 7.37 92.50 220.00 7.38 92.50 220.00 7.39 92.50 220.00 7.40 92.50 220.00 7.41 220.00 7.42 220.00 7.43 220.00 7.44 220.00 7.45 220.00 7.46 185.00 220.00 7.47 185.00 220.00 7.48 185.00 220.00 7.49 185.00 220.00 7.50 185.00 220.00 7.51 185.00 220.00 7.52 185.00 220.00 7.53 7.54 7.55 92.50 7.56 92.50 7.57 92.50 7.58 92.50 7.59 92.50 7.60 92.50 7.61 92.50 7.62 92.50 164.81 7.63 92.50 164.81 7.64 92.50 164.81 7.65 92.50 164.81 7.66 92.50 164.81 7.67 92.50 164.81 7.68 92.50 164.81 7.69 92.50 164.81 7.70 92.50 164.81 7.71 92.50 7.72 92.50 7.73 92.50 7.74 92.50 7.75 92.50 7.76 92.50 7.77 92.50 7.78 92.50 7.79 92.50 7.80 92.50 7.81 92.50 329.63 7.82 92.50 329.63 7.83 92.50 329.63 7.84 92.50 329.63 7.85 92.50 329.63 7.86 92.50 329.63 7.87 92.50 7.88 92.50 7.89 92.50 7.90 92.50 7.91 92.50 7.92 92.50 7.93 92.50 7.94 92.50 7.95 92.50 7.96 92.50 7.97 103.83 7.98 103.83 7.99 103.83 8.00 103.83 8.01 103.83 8.02 103.83 8.03 103.83 8.04 103.83 8.05 103.83 8.06 103.83 8.07 103.83 8.08 103.83 8.09 103.83 8.10 103.83 8.11 103.83 8.12 103.83 8.13 103.83 8.14 103.83 8.15 103.83 8.16 103.83 8.17 103.83 8.18 103.83 8.19 103.83 8.20 103.83 8.21 103.83 8.22 103.83 8.23 103.83 8.24 103.83 8.25 103.83 8.26 103.83 8.27 103.83 8.28 103.83 8.29 103.83 8.30 103.83 8.31 103.83 8.32 103.83 8.33 103.83 8.34 103.83 8.35 103.83 8.36 103.83 246.94 8.37 103.83 246.94 8.38 103.83 246.94 8.39 103.83 246.94 8.40 103.83 246.94 8.41 103.83 246.94 8.42 103.83 246.94 8.43 103.83 207.65 246.94 8.44 103.83 207.65 246.94 8.45 103.83 207.65 246.94 8.46 103.83 207.65 246.94 8.47 103.83 207.65 246.94 8.48 103.83 207.65 246.94 8.49 103.83 207.65 246.94 8.50 207.65 246.94 8.51 207.65 246.94 8.52 207.65 246.94 8.53 207.65 246.94 8.54 207.65 246.94 8.55 207.65 246.94 8.56 207.65 246.94 8.57 207.65 246.94 8.58 207.65 246.94 8.59 207.65 246.94 8.60 207.65 246.94 8.61 207.65 246.94 8.62 207.65 246.94 8.63 207.65 246.94 8.64 207.65 246.94 8.65 207.65 246.94 8.66 207.65 246.94 8.67 207.65 246.94 8.68 207.65 246.94 8.69 103.83 207.65 246.94 8.70 103.83 207.65 246.94 8.71 103.83 246.94 8.72 103.83 246.94 8.73 103.83 246.94 8.74 103.83 246.94 8.75 103.83 246.94 8.76 103.83 164.81 246.94 8.77 103.83 164.81 246.94 8.78 103.83 164.81 246.94 8.79 103.83 164.81 246.94 8.80 103.83 164.81 246.94 8.81 103.83 164.81 246.94 8.82 103.83 164.81 246.94 8.83 103.83 164.81 246.94 8.84 103.83 164.81 246.94 8.85 103.83 164.81 246.94 8.86 103.83 164.81 246.94 8.87 103.83 246.94 8.88 103.83 246.94 8.89 103.83 246.94 8.90 103.83 246.94 8.91 103.83 246.94 8.92 103.83 246.94 8.93 103.83 246.94 8.94 103.83 8.95 103.83 8.96 103.83 8.97 103.83 8.98 103.83 8.99 103.83 9.00 103.83 9.01 103.83 9.02 103.83 9.03 103.83 9.04 103.83 9.05 103.83 9.06 103.83 9.07 103.83 9.08 103.83 9.09 103.83 9.10 103.83 9.11 103.83 9.12 103.83 9.13 103.83 9.14 103.83 9.15 103.83 110.00 9.16 103.83 110.00 9.17 103.83 110.00 9.18 103.83 110.00 9.19 103.83 110.00 9.20 103.83 110.00 9.21 103.83 110.00 9.22 103.83 110.00 9.23 103.83 110.00 9.24 103.83 110.00 9.25 103.83 110.00 9.26 103.83 110.00 9.27 110.00 9.28 110.00 9.29 110.00 329.63 523.25 9.30 110.00 329.63 523.25 9.31 110.00 329.63 523.25 9.32 110.00 329.63 523.25 9.33 110.00 329.63 523.25 9.34 110.00 329.63 523.25 9.35 110.00 329.63 523.25 9.36 220.00 329.63 523.25 9.37 220.00 329.63 523.25 9.38 220.00 329.63 523.25 9.39 220.00 329.63 523.25 9.40 220.00 329.63 523.25 9.41 220.00 329.63 523.25 9.42 220.00 329.63 523.25 9.43 220.00 329.63 523.25 9.44 220.00 329.63 523.25 9.45 220.00 523.25 9.46 220.00 523.25 9.47 220.00 523.25 9.48 220.00 329.63 523.25 9.49 220.00 329.63 523.25 9.50 220.00 261.63 329.63 523.25 9.51 220.00 261.63 329.63 523.25 9.52 220.00 261.63 329.63 523.25 9.53 220.00 261.63 329.63 523.25 9.54 220.00 261.63 329.63 523.25 9.55 220.00 261.63 329.63 523.25 9.56 220.00 261.63 329.63 523.25 9.57 220.00 261.63 329.63 523.25 9.58 220.00 261.63 329.63 523.25 9.59 220.00 261.63 329.63 523.25 9.60 220.00 261.63 329.63 523.25 9.61 220.00 261.63 9.62 220.00 261.63 9.63 220.00 261.63 9.64 220.00 261.63 523.25 9.65 220.00 261.63 523.25 9.66 220.00 261.63 523.25 9.67 220.00 261.63 523.25 9.68 220.00 261.63 523.25 9.69 220.00 261.63 523.25 9.70 220.00 261.63 523.25 9.71 220.00 261.63 329.63 523.25 9.72 220.00 261.63 329.63 523.25 9.73 220.00 261.63 329.63 9.74 220.00 261.63 329.63 9.75 220.00 261.63 329.63 9.76 220.00 261.63 329.63 9.77 220.00 261.63 329.63 9.78 110.00 261.63 329.63 9.79 110.00 261.63 329.63 9.80 110.00 261.63 329.63 9.81 110.00 261.63 329.63 9.82 110.00 261.63 329.63 9.83 110.00 246.94 261.63 329.63 9.84 110.00 246.94 261.63 329.63 9.85 110.00 246.94 261.63 329.63 9.86 110.00 246.94 261.63 329.63 9.87 246.94 261.63 9.88 246.94 261.63 9.89 246.94 261.63 9.90 246.94 261.63 9.91 246.94 261.63 9.92 246.94 261.63 9.93 246.94 261.63 9.94 164.81 261.63 9.95 164.81 261.63 9.96 164.81 261.63 9.97 164.81 261.63 9.98 164.81 261.63 9.99 164.81 261.63 10.00 164.81 261.63 10.01 164.81 261.63 10.02 164.81 261.63 10.03 164.81 261.63 10.04 164.81 261.63 10.05 164.81 261.63 10.06 164.81 261.63 10.07 164.81 261.63 10.08 164.81 261.63 10.09 164.81 261.63 10.10 164.81 261.63 10.11 164.81 261.63 10.12 164.81 261.63 10.13 164.81 261.63 10.14 164.81 261.63 10.15 164.81 261.63 10.16 164.81 261.63 10.17 164.81 10.18 164.81 10.19 164.81 10.20 164.81 10.21 164.81 10.22 164.81 10.23 164.81 10.24 164.81 10.25 164.81 10.26 164.81 10.27 164.81 10.28 164.81 10.29 164.81 10.30 164.81 10.31 164.81 10.32 164.81 10.33 164.81 10.34 164.81 10.35 164.81 10.36 164.81 10.37 164.81 10.38 174.61 10.39 174.61 10.40 174.61 10.41 164.81 174.61 10.42 164.81 174.61 10.43 164.81 174.61 10.44 164.81 174.61 10.45 164.81 174.61 10.46 164.81 174.61 10.47 164.81 174.61 10.48 164.81 174.61 10.49 164.81 174.61 10.50 164.81 174.61 10.51 164.81 174.61 10.52 87.31 164.81 174.61 10.53 87.31 164.81 174.61 10.54 87.31 164.81 174.61 10.55 87.31 164.81 174.61 10.56 87.31 164.81 174.61 10.57 87.31 164.81 349.23 10.58 87.31 164.81 349.23 10.59 87.31 349.23 10.60 87.31 349.23 10.61 87.31 349.23 10.62 87.31 349.23 10.63 87.31 349.23 10.64 87.31 174.61 349.23 10.65 87.31 174.61 349.23 10.66 87.31 174.61 349.23 10.67 87.31 174.61 349.23 10.68 87.31 174.61 349.23 10.69 87.31 174.61 349.23 10.70 87.31 174.61 349.23 10.71 87.31 174.61 349.23 10.72 87.31 174.61 349.23 10.73 87.31 174.61 349.23 10.74 87.31 174.61 349.23 10.75 87.31 174.61 349.23 10.76 87.31 174.61 349.23 10.77 87.31 174.61 349.23 10.78 87.31 174.61 349.23 10.79 87.31 174.61 349.23 10.80 87.31 174.61 349.23 10.81 87.31 174.61 349.23 10.82 87.31 174.61 349.23 10.83 87.31 174.61 349.23 10.84 87.31 174.61 349.23 10.85 87.31 174.61 349.23 10.86 87.31 174.61 349.23 10.87 87.31 174.61 349.23 10.88 87.31 174.61 349.23 10.89 87.31 174.61 349.23 10.90 87.31 174.61 349.23 10.91 87.31 174.61 349.23 10.92 87.31 174.61 349.23 10.93 87.31 174.61 349.23 10.94 87.31 174.61 10.95 87.31 174.61 10.96 87.31 174.61 10.97 87.31 174.61 10.98 87.31 174.61 10.99 87.31 110.00 174.61 11.00 87.31 110.00 174.61 11.01 87.31 110.00 174.61 11.02 87.31 110.00 174.61 11.03 110.00 11.04 110.00 11.05 110.00 11.06 110.00 11.07 110.00 11.08 110.00 440.00 11.09 110.00 440.00 11.10 110.00 440.00 11.11 110.00 440.00 11.12 110.00 440.00 11.13 110.00 440.00 11.14 110.00 440.00 11.15 110.00 440.00 11.16 110.00 440.00 11.17 110.00 261.63 440.00 11.18 110.00 261.63 440.00 11.19 261.63 440.00 11.20 261.63 440.00 11.21 261.63 440.00 11.22 261.63 11.23 261.63 11.24 261.63 11.25 261.63 11.26 261.63 11.27 261.63 11.28 261.63 11.29 261.63 11.30 261.63 11.31 261.63 11.32 261.63 11.33 261.63 11.34 130.81 261.63 11.35 130.81 261.63 11.36 130.81 261.63 11.37 130.81 261.63 11.38 130.81 261.63 11.39 130.81 261.63 11.40 130.81 261.63 11.41 130.81 261.63 11.42 130.81 261.63 11.43 130.81 261.63 11.44 130.81 261.63 11.45 130.81 261.63 11.46 130.81 261.63 11.47 130.81 261.63 11.48 130.81 261.63 523.25 11.49 130.81 261.63 523.25 11.50 130.81 261.63 523.25 11.51 130.81 261.63 523.25 11.52 130.81 261.63 523.25 11.53 130.81 261.63 523.25 11.54 130.81 261.63 523.25 11.55 130.81 261.63 523.25 11.56 130.81 261.63 523.25 11.57 130.81 261.63 11.58 130.81 261.63 11.59 130.81 261.63 11.60 130.81 261.63 11.61 82.41 261.63 11.62 82.41 261.63 11.63 82.41 261.63 11.64 82.41 261.63 11.65 82.41 261.63 11.66 82.41 261.63 329.63 11.67 82.41 261.63 329.63 11.68 82.41 261.63 329.63 11.69 82.41 261.63 329.63 11.70 82.41 329.63 11.71 82.41 329.63 11.72 82.41 329.63 11.73 82.41 329.63 11.74 82.41 329.63 11.75 82.41 329.63 11.76 82.41 329.63 11.77 82.41 329.63 11.78 82.41 329.63 11.79 82.41 329.63 11.80 82.41 329.63 11.81 82.41 329.63 11.82 82.41 329.63 11.83 82.41 329.63 11.84 82.41 329.63 11.85 82.41 329.63 11.86 82.41 329.63 11.87 82.41 329.63 11.88 82.41 329.63 11.89 82.41 329.63 11.90 82.41 329.63 11.91 82.41 329.63 11.92 82.41 329.63 11.93 82.41 329.63 11.94 82.41 329.63 11.95 82.41 329.63 11.96 82.41 11.97 82.41 11.98 82.41 11.99 82.41 12.00 82.41 12.01 82.41 12.02 82.41 12.03 82.41 12.04 82.41 12.05 82.41 12.06 82.41 12.07 82.41 12.08 82.41 12.09 82.41 12.10 82.41 12.11 82.41 12.12 82.41 12.13 82.41 12.14 82.41 12.15 82.41 12.16 82.41 12.17 82.41 220.00 12.18 82.41 220.00 12.19 82.41 220.00 12.20 82.41 220.00 12.21 82.41 220.00 12.22 82.41 220.00 12.23 82.41 220.00 12.24 82.41 110.00 220.00 12.25 82.41 110.00 220.00 12.26 110.00 220.00 12.27 110.00 220.00 12.28 110.00 220.00 12.29 110.00 220.00 12.30 110.00 220.00 12.31 110.00 12.32 110.00 12.33 110.00 12.34 110.00 12.35 12.36 261.63 12.37 261.63 12.38 261.63 12.39 261.63 12.40 130.81 261.63 12.41 130.81 261.63 12.42 130.81 261.63 12.43 130.81 261.63 12.44 130.81 261.63 12.45 130.81 261.63 12.46 130.81 261.63 12.47 130.81 261.63 12.48 130.81 261.63 12.49 130.81 261.63 12.50 130.81 220.00 261.63 12.51 130.81 220.00 261.63 12.52 130.81 220.00 261.63 12.53 130.81 220.00 261.63 12.54 130.81 220.00 261.63 12.55 130.81 220.00 261.63 12.56 130.81 261.63 12.57 130.81 261.63 12.58 130.81 261.63 12.59 130.81 261.63 12.60 130.81 261.63 12.61 130.81 261.63 12.62 130.81 261.63 12.63 130.81 261.63 12.64 130.81 261.63 12.65 130.81 261.63 12.66 130.81 261.63 12.67 130.81 261.63 12.68 130.81 261.63 12.69 130.81 261.63 12.70 130.81 261.63 12.71 130.81 261.63 12.72 130.81 261.63 12.73 130.81 261.63 12.74 130.81 261.63 12.75 130.81 261.63 12.76 130.81 261.63 12.77 130.81 12.78 130.81 12.79 130.81 12.80 130.81 155.56 12.81 130.81 155.56 12.82 77.78 130.81 155.56 12.83 77.78 130.81 155.56 12.84 77.78 130.81 155.56 12.85 77.78 130.81 155.56 12.86 77.78 130.81 155.56 12.87 77.78 155.56 12.88 77.78 155.56 12.89 77.78 155.56 12.90 77.78 155.56 12.91 77.78 155.56 12.92 77.78 155.56 12.93 77.78 155.56 12.94 77.78 155.56 311.13 12.95 77.78 155.56 311.13 12.96 155.56 311.13 12.97 155.56 311.13 12.98 77.78 155.56 311.13 12.99 77.78 155.56 311.13 13.00 77.78 155.56 311.13 13.01 77.78 155.56 311.13 13.02 77.78 155.56 311.13 13.03 77.78 155.56 311.13 13.04 77.78 155.56 311.13 13.05 77.78 311.13 13.06 77.78 311.13 13.07 77.78 311.13 13.08 77.78 311.13 13.09 77.78 311.13 13.10 77.78 311.13 13.11 77.78 311.13 13.12 77.78 311.13 13.13 77.78 311.13 13.14 77.78 311.13 13.15 77.78 311.13 13.16 77.78 311.13 13.17 77.78 311.13 13.18 77.78 311.13 13.19 77.78 311.13 13.20 77.78 311.13 13.21 77.78 311.13 13.22 77.78 311.13 13.23 77.78 311.13 13.24 77.78 311.13 13.25 77.78 311.13 13.26 77.78 311.13 13.27 77.78 311.13 13.28 77.78 311.13 13.29 77.78 311.13 13.30 77.78 311.13 13.31 77.78 311.13 13.32 77.78 311.13 13.33 77.78 311.13 13.34 77.78 311.13 13.35 77.78 311.13 13.36 77.78 311.13 13.37 77.78 311.13 13.38 77.78 311.13 13.39 77.78 311.13 13.40 77.78 311.13 13.41 77.78 311.13 13.42 77.78 311.13 13.43 77.78 311.13 13.44 77.78 311.13 13.45 77.78 311.13 13.46 77.78 311.13 13.47 77.78 311.13 13.48 77.78 311.13 13.49 77.78 311.13 13.50 77.78 311.13 13.51 77.78 311.13 13.52 77.78 311.13 13.53 77.78 311.13 13.54 77.78 311.13 13.55 77.78 311.13 13.56 77.78 13.57 77.78 523.25 13.58 77.78 523.25 13.59 77.78 523.25 13.60 77.78 523.25 13.61 77.78 523.25 13.62 77.78 523.25 13.63 77.78 523.25 13.64 77.78 523.25 13.65 77.78 523.25 13.66 77.78 523.25 13.67 77.78 523.25 13.68 77.78 523.25 13.69 77.78 523.25 13.70 77.78 523.25 13.71 77.78 523.25 13.72 77.78 523.25 13.73 77.78 246.94 369.99 523.25 13.74 77.78 246.94 369.99 523.25 13.75 77.78 246.94 369.99 523.25 13.76 77.78 246.94 369.99 523.25 13.77 77.78 246.94 369.99 13.78 77.78 246.94 369.99 13.79 77.78 246.94 369.99 13.80 77.78 246.94 369.99 13.81 77.78 246.94 369.99 13.82 77.78 246.94 369.99 13.83 77.78 246.94 369.99 13.84 77.78 220.00 246.94 369.99 13.85 77.78 220.00 246.94 369.99 13.86 77.78 220.00 246.94 369.99 13.87 77.78 220.00 246.94 369.99 13.88 77.78 220.00 246.94 369.99 13.89 77.78 220.00 246.94 369.99 13.90 77.78 220.00 246.94 369.99 13.91 77.78 220.00 246.94 369.99 13.92 77.78 220.00 246.94 369.99 13.93 77.78 220.00 246.94 369.99 13.94 77.78 220.00 246.94 369.99 13.95 77.78 220.00 246.94 369.99 13.96 77.78 220.00 246.94 369.99 13.97 77.78 220.00 246.94 369.99 13.98 220.00 246.94 13.99 220.00 246.94 14.00 220.00 246.94 14.01 220.00 246.94 440.00 14.02 220.00 246.94 440.00 14.03 220.00 246.94 440.00 14.04 220.00 246.94 440.00 14.05 220.00 246.94 440.00 14.06 220.00 246.94 440.00 14.07 220.00 246.94 440.00 14.08 220.00 246.94 440.00 14.09 220.00 246.94 440.00 14.10 220.00 246.94 440.00 14.11 220.00 246.94 440.00 14.12 220.00 246.94 440.00 14.13 220.00 246.94 440.00 14.14 220.00 246.94 440.00 14.15 220.00 246.94 440.00 14.16 220.00 246.94 440.00 14.17 220.00 246.94 440.00 14.18 220.00 246.94 440.00 14.19 220.00 246.94 440.00 14.20 220.00 246.94 440.00 14.21 220.00 246.94 14.22 220.00 246.94 14.23 220.00 246.94 14.24 220.00 246.94 14.25 220.00 246.94 14.26 220.00 246.94 440.00 14.27 220.00 246.94 440.00 14.28 220.00 246.94 440.00 14.29 220.00 246.94 440.00 14.30 220.00 246.94 440.00 14.31 220.00 246.94 440.00 14.32 220.00 246.94 440.00 14.33 220.00 246.94 440.00 14.34 220.00 246.94 440.00 14.35 220.00 246.94 14.36 220.00 246.94 14.37 220.00 246.94 14.38 220.00 246.94 14.39 220.00 246.94 14.40 220.00 246.94 440.00 14.41 220.00 246.94 440.00 14.42 220.00 246.94 440.00 14.43 220.00 246.94 440.00 14.44 220.00 246.94 440.00 14.45 220.00 246.94 440.00 14.46 220.00 246.94 440.00 14.47 220.00 246.94 440.00 14.48 220.00 246.94 440.00 14.49 220.00 246.94 440.00 14.50 220.00 246.94 440.00 14.51 220.00 246.94 440.00 14.52 220.00 246.94 440.00 14.53 220.00 246.94 440.00 14.54 220.00 246.94 440.00 14.55 220.00 246.94 440.00 14.56 220.00 246.94 440.00 14.57 220.00 246.94 440.00 14.58 220.00 246.94 440.00 14.59 220.00 246.94 440.00 14.60 220.00 246.94 440.00 14.61 220.00 246.94 440.00 14.62 220.00 246.94 440.00 14.63 220.00 246.94 440.00 14.64 220.00 246.94 440.00 14.65 220.00 246.94 440.00 14.66 220.00 246.94 440.00 14.67 220.00 246.94 440.00 14.68 220.00 246.94 440.00 14.69 220.00 246.94 440.00 14.70 220.00 246.94 440.00 14.71 220.00 246.94 440.00 14.72 220.00 246.94 440.00 14.73 220.00 246.94 440.00 14.74 220.00 246.94 440.00 14.75 220.00 246.94 440.00 14.76 220.00 246.94 440.00 14.77 220.00 246.94 440.00 14.78 220.00 246.94 440.00 14.79 220.00 246.94 440.00 14.80 220.00 246.94 440.00 14.81 220.00 246.94 440.00 14.82 220.00 246.94 440.00 14.83 220.00 246.94 440.00 14.84 220.00 246.94 14.85 220.00 246.94 14.86 220.00 246.94 14.87 220.00 246.94 14.88 220.00 246.94 14.89 220.00 14.90 220.00 14.91 220.00 14.92 220.00 14.93 220.00 14.94 220.00 246.94 14.95 220.00 246.94 14.96 220.00 246.94 14.97 220.00 246.94 14.98 220.00 246.94 14.99 220.00 246.94 15.00 220.00 246.94 15.01 220.00 246.94 15.02 220.00 246.94 15.03 220.00 246.94 15.04 220.00 246.94 15.05 220.00 246.94 15.06 220.00 246.94 15.07 220.00 246.94 15.08 220.00 246.94 15.09 246.94 15.10 246.94 15.11 246.94 15.12 246.94 15.13 246.94 15.14 246.94 15.15 246.94 15.16 15.17 15.18 15.19 15.20 15.21 15.22 15.23 15.24 15.25 15.26 15.27 15.28 15.29 15.30 15.31 15.32 15.33 415.30 15.34 415.30 15.35 415.30 15.36 415.30 15.37 415.30 15.38 415.30 15.39 415.30 15.40 415.30 15.41 415.30 15.42 15.43 15.44 15.45 15.46 15.47 15.48 15.49 15.50 15.51 15.52 15.53 15.54 15.55 15.56 15.57 15.58 15.59 15.60 15.61 15.62 15.63 15.64 15.65 15.66 207.65 15.67 207.65 15.68 207.65 15.69 207.65 15.70 207.65 15.71 207.65 15.72 207.65 15.73 207.65 15.74 207.65 15.75 207.65 220.00 15.76 207.65 220.00 15.77 220.00 15.78 220.00 15.79 220.00 15.80 220.00 15.81 220.00 15.82 220.00 15.83 220.00 15.84 220.00 15.85 220.00 15.86 220.00 15.87 220.00 15.88 220.00 15.89 220.00 15.90 220.00 15.91 220.00 15.92 220.00 15.93 220.00 15.94 220.00 15.95 220.00 15.96 220.00 15.97 220.00 15.98 220.00 15.99 220.00 16.00 220.00 392.00 16.01 220.00 392.00 16.02 220.00 392.00 16.03 220.00 392.00 16.04 220.00 392.00 16.05 392.00 16.06 392.00 16.07 392.00 16.08 392.00 16.09 16.10 16.11 16.12 16.13 16.14 16.15 16.16 16.17 16.18 16.19 466.16 16.20 466.16 16.21 466.16 16.22 466.16 16.23 466.16 16.24 466.16 16.25 466.16 16.26 466.16 16.27 466.16 16.28 466.16 16.29 466.16 16.30 466.16 16.31 466.16 16.32 466.16 16.33 440.00 16.34 440.00 16.35 440.00 16.36 440.00 16.37 440.00 16.38 440.00 16.39 440.00 16.40 440.00 16.41 440.00 16.42 440.00 16.43 440.00 16.44 440.00 16.45 440.00 16.46 440.00 16.47 440.00 16.48 440.00 16.49 16.50 16.51 392.00 16.52 392.00 16.53 392.00 16.54 392.00 16.55 392.00 16.56 220.00 392.00 16.57 220.00 392.00 16.58 220.00 392.00 16.59 220.00 392.00 16.60 220.00 392.00 16.61 220.00 392.00 16.62 220.00 392.00 16.63 220.00 392.00 16.64 220.00 392.00 16.65 220.00 392.00 16.66 220.00 392.00 16.67 220.00 16.68 220.00 16.69 220.00 16.70 220.00 16.71 220.00 16.72 220.00 392.00 16.73 220.00 392.00 16.74 220.00 392.00 16.75 146.83 220.00 392.00 16.76 146.83 220.00 392.00 16.77 146.83 392.00 16.78 146.83 392.00 16.79 146.83 392.00 16.80 146.83 392.00 16.81 146.83 392.00 16.82 146.83 392.00 16.83 146.83 392.00 16.84 146.83 392.00 16.85 146.83 392.00 16.86 146.83 392.00 16.87 146.83 392.00 16.88 146.83 392.00 16.89 146.83 369.99 392.00 16.90 146.83 369.99 392.00 16.91 146.83 369.99 16.92 146.83 369.99 16.93 146.83 220.00 293.66 369.99 16.94 146.83 220.00 293.66 369.99 16.95 220.00 293.66 16.96 220.00 293.66 16.97 220.00 293.66 16.98 73.42 220.00 293.66 16.99 73.42 220.00 293.66 17.00 73.42 220.00 293.66 17.01 73.42 220.00 293.66 17.02 73.42 220.00 293.66 17.03 73.42 220.00 293.66 17.04 73.42 220.00 293.66 17.05 73.42 220.00 293.66 17.06 73.42 220.00 293.66 17.07 73.42 220.00 293.66 17.08 73.42 220.00 293.66 17.09 73.42 220.00 293.66 17.10 73.42 220.00 293.66 17.11 220.00 293.66 17.12 220.00 293.66 17.13 220.00 293.66 17.14 220.00 293.66 17.15 220.00 293.66 17.16 220.00 293.66 17.17 220.00 293.66 17.18 293.66 17.19 293.66 17.20 293.66 17.21 293.66 17.22 293.66 17.23 293.66 17.24 293.66 17.25 293.66 17.26 293.66 17.27 293.66 17.28 293.66 17.29 293.66 17.30 293.66 369.99 17.31 293.66 369.99 17.32 293.66 369.99 17.33 293.66 369.99 17.34 293.66 369.99 17.35 293.66 369.99 17.36 293.66 369.99 17.37 293.66 369.99 17.38 293.66 369.99 17.39 293.66 369.99 17.40 293.66 369.99 17.41 293.66 369.99 17.42 293.66 369.99 17.43 293.66 369.99 17.44 369.99 17.45 369.99 17.46 369.99 17.47 293.66 369.99 17.48 293.66 369.99 17.49 293.66 369.99 17.50 293.66 369.99 17.51 293.66 369.99 17.52 293.66 369.99 17.53 293.66 369.99 17.54 293.66 369.99 440.00 17.55 293.66 369.99 440.00 17.56 369.99 440.00 17.57 369.99 440.00 17.58 369.99 440.00 17.59 369.99 440.00 17.60 17.61 17.62 17.63 17.64 17.65 17.66 17.67 17.68 17.69 17.70 220.00 17.71 220.00 17.72 220.00 17.73 220.00 17.74 220.00 17.75 220.00 17.76 220.00 17.77 220.00 17.78 220.00 17.79 220.00 17.80 220.00 17.81 220.00 17.82 220.00 17.83 220.00 17.84 220.00 17.85 220.00 17.86 220.00 17.87 220.00 17.88 220.00 17.89 220.00 17.90 220.00 17.91 220.00 17.92 220.00 17.93 246.94 17.94 246.94 17.95 246.94 17.96 246.94 17.97 246.94 17.98 246.94 17.99 246.94 18.00 246.94 18.01 246.94 18.02 246.94 18.03 246.94 18.04 246.94 18.05 123.47 246.94 18.06 123.47 246.94 18.07 123.47 246.94 18.08 123.47 246.94 18.09 123.47 246.94 18.10 123.47 246.94 18.11 123.47 18.12 123.47 18.13 123.47 18.14 123.47 18.15 123.47 18.16 123.47 18.17 123.47 18.18 123.47 18.19 123.47 18.20 123.47 18.21 123.47 18.22 123.47 18.23 123.47 18.24 123.47 18.25 123.47 18.26 123.47 18.27 123.47 18.28 123.47 18.29 123.47 18.30 123.47 18.31 123.47 18.32 123.47 18.33 123.47 18.34 123.47 18.35 18.36 18.37 293.66 18.38 293.66 18.39 293.66 18.40 293.66 18.41 293.66 18.42 123.47 293.66 18.43 123.47 293.66 18.44 123.47 293.66 18.45 123.47 293.66 18.46 123.47 293.66 18.47 123.47 293.66 18.48 123.47 293.66 18.49 123.47 293.66 18.50 123.47 293.66 18.51 18.52 18.53 123.47 18.54 123.47 18.55 123.47 18.56 123.47 18.57 123.47 18.58 123.47 18.59 123.47 18.60 123.47 18.61 123.47 18.62 123.47 18.63 123.47 18.64 123.47 18.65 123.47 18.66 123.47 18.67 123.47 18.68 123.47 18.69 123.47 18.70 123.47 18.71 123.47 18.72 123.47 392.00 18.73 123.47 392.00 18.74 123.47 392.00 18.75 123.47 392.00 18.76 123.47 392.00 18.77 123.47 392.00 18.78 123.47 392.00 18.79 123.47 392.00 18.80 123.47 392.00 18.81 123.47 392.00 18.82 123.47 392.00 18.83 123.47 392.00 18.84 123.47 392.00 18.85 123.47 392.00 18.86 123.47 18.87 123.47 18.88 123.47 18.89 123.47 18.90 18.91 349.23 18.92 349.23 18.93 349.23 18.94 349.23 18.95 349.23 18.96 349.23 18.97 349.23 18.98 349.23 18.99 349.23 19.00 349.23 19.01 349.23 19.02 349.23 19.03 349.23 19.04 349.23 19.05 349.23 19.06 349.23 19.07 349.23 19.08 349.23 19.09 19.10 19.11 19.12 19.13 19.14 130.81 19.15 130.81 19.16 130.81 19.17 130.81 19.18 130.81 19.19 130.81 19.20 130.81 19.21 130.81 19.22 130.81 19.23 130.81 19.24 130.81 19.25 130.81 19.26 130.81 19.27 130.81 19.28 130.81 19.29 130.81 19.30 130.81 19.31 130.81 19.32 19.33 19.34 19.35 19.36 19.37 65.41 19.38 65.41 19.39 65.41 19.40 65.41 19.41 65.41 19.42 65.41 19.43 65.41 19.44 65.41 19.45 65.41 19.46 19.47 19.48 19.49 261.63 19.50 261.63 19.51 261.63 19.52 261.63 19.53 261.63 19.54 261.63 19.55 261.63 19.56 261.63 19.57 261.63 19.58 261.63 19.59 261.63 19.60 261.63 19.61 261.63 19.62 261.63 19.63 261.63 19.64 261.63 19.65 261.63 19.66 261.63 19.67 261.63 19.68 261.63 19.69 261.63 19.70 261.63 19.71 261.63 19.72 261.63 19.73 261.63 19.74 261.63 19.75 261.63 19.76 261.63 19.77 261.63 19.78 261.63 19.79 261.63 19.80 261.63 19.81 261.63 19.82 261.63 19.83 261.63 19.84 261.63 19.85 261.63 19.86 261.63 19.87 261.63 19.88 261.63 19.89 261.63 19.90 19.91 19.92 19.93 19.94 19.95 19.96 19.97 19.98 19.99 20.00 20.01 20.02 20.03 20.04 20.05 20.06 20.07 20.08 20.09 20.10 20.11 20.12 20.13 20.14 20.15 20.16 196.00 20.17 196.00 20.18 196.00 20.19 196.00 20.20 196.00 20.21 196.00 20.22 196.00 20.23 196.00 20.24 196.00 20.25 20.26 20.27 20.28 20.29 20.30 20.31 20.32 103.83 20.33 103.83 20.34 103.83 20.35 103.83 20.36 103.83 20.37 103.83 20.38 103.83 20.39 103.83 20.40 103.83 20.41 103.83 20.42 103.83 20.43 103.83 20.44 103.83 20.45 103.83 20.46 103.83 20.47 103.83 20.48 103.83 20.49 103.83 20.50 103.83 20.51 103.83 20.52 103.83 20.53 103.83 20.54 103.83 20.55 103.83 246.94 20.56 103.83 246.94 20.57 103.83 246.94 20.58 103.83 246.94 20.59 103.83 246.94 20.60 103.83 246.94 20.61 103.83 246.94 20.62 246.94 20.63 246.94 20.64 246.94 20.65 246.94 349.23 20.66 246.94 349.23 20.67 246.94 349.23 20.68 246.94 349.23 20.69 246.94 349.23 20.70 246.94 349.23 20.71 246.94 20.72 246.94 20.73 246.94 20.74 246.94 20.75 246.94 20.76 246.94 329.63 20.77 246.94 329.63 20.78 246.94 329.63 20.79 246.94 293.66 329.63 20.80 246.94 293.66 329.63 20.81 246.94 293.66 329.63 20.82 246.94 293.66 329.63 20.83 246.94 293.66 329.63 20.84 246.94 293.66 329.63 20.85 246.94 293.66 329.63 20.86 246.94 293.66 329.63 20.87 246.94 293.66 329.63 20.88 246.94 293.66 329.63 20.89 246.94 293.66 329.63 20.90 246.94 293.66 329.63 20.91 246.94 293.66 329.63 20.92 246.94 293.66 20.93 246.94 293.66 349.23 20.94 246.94 293.66 349.23 20.95 246.94 349.23 20.96 246.94 349.23 20.97 246.94 349.23 20.98 246.94 349.23 20.99 246.94 349.23 21.00 246.94 349.23 21.01 246.94 349.23 21.02 349.23 21.03 349.23 21.04 349.23 21.05 349.23 21.06 349.23 21.07 349.23 21.08 349.23 21.09 349.23 21.10 349.23 21.11 246.94 349.23 21.12 246.94 349.23 21.13 246.94 349.23 21.14 246.94 349.23 21.15 246.94 349.23 21.16 246.94 349.23 21.17 246.94 349.23 21.18 246.94 349.23 21.19 246.94 349.23 21.20 246.94 349.23 21.21 246.94 349.23 21.22 349.23 21.23 349.23 21.24 349.23 21.25 349.23 21.26 349.23 21.27 246.94 349.23 21.28 246.94 349.23 21.29 246.94 349.23 21.30 246.94 349.23 21.31 246.94 349.23 21.32 246.94 349.23 21.33 246.94 349.23 21.34 246.94 21.35 246.94 21.36 246.94 21.37 246.94 21.38 246.94 21.39 246.94 21.40 246.94 21.41 246.94 21.42 246.94 21.43 246.94 21.44 246.94 21.45 246.94 21.46 246.94 21.47 246.94 21.48 246.94 21.49 246.94 21.50 246.94 21.51 246.94 21.52 246.94 21.53 246.94 21.54 246.94 21.55 246.94 21.56 246.94 21.57 246.94 21.58 246.94 21.59 246.94 21.60 246.94 21.61 246.94 21.62 110.00 246.94 21.63 110.00 246.94 21.64 110.00 246.94 21.65 110.00 246.94 21.66 110.00 246.94 21.67 110.00 246.94 21.68 110.00 246.94 21.69 246.94 21.70 246.94 21.71 21.72 261.63 21.73 261.63 21.74 261.63 21.75 261.63 21.76 261.63 21.77 261.63 21.78 261.63 21.79 261.63 21.80 261.63 21.81 110.00 261.63 21.82 110.00 261.63 21.83 110.00 261.63 21.84 110.00 261.63 21.85 110.00 261.63 21.86 110.00 261.63 21.87 110.00 261.63 21.88 110.00 261.63 21.89 110.00 261.63 21.90 110.00 261.63 21.91 110.00 261.63 21.92 110.00 261.63 21.93 110.00 261.63 21.94 261.63 21.95 261.63 21.96 261.63 21.97 261.63 21.98 261.63 21.99 261.63 22.00 261.63 22.01 261.63 22.02 261.63 22.03 261.63 22.04 261.63 22.05 261.63 22.06 22.07 22.08 22.09 440.00 22.10 440.00 22.11 440.00 22.12 440.00 22.13 415.30 440.00 22.14 415.30 440.00 22.15 415.30 440.00 22.16 415.30 440.00 22.17 415.30 440.00 22.18 415.30 440.00 22.19 415.30 440.00 22.20 415.30 440.00 22.21 415.30 440.00 22.22 415.30 440.00 22.23 415.30 440.00 22.24 415.30 440.00 22.25 415.30 440.00 523.25 22.26 415.30 440.00 523.25 22.27 440.00 523.25 22.28 440.00 523.25 22.29 440.00 523.25 22.30 440.00 523.25 22.31 440.00 523.25 22.32 440.00 523.25 22.33 440.00 523.25 22.34 440.00 523.25 22.35 440.00 523.25 22.36 440.00 523.25 22.37 440.00 523.25 22.38 440.00 523.25 22.39 440.00 523.25 22.40 440.00 523.25 22.41 440.00 523.25 22.42 440.00 523.25 22.43 440.00 523.25 22.44 440.00 523.25 22.45 440.00 523.25 22.46 261.63 440.00 523.25 22.47 261.63 440.00 523.25 22.48 261.63 523.25 22.49 261.63 523.25 22.50 261.63 523.25 22.51 261.63 523.25 22.52 261.63 523.25 22.53 261.63 523.25 22.54 261.63 523.25 22.55 261.63 523.25 22.56 261.63 523.25 22.57 261.63 523.25 22.58 261.63 523.25 22.59 261.63 523.25 22.60 261.63 523.25 22.61 261.63 523.25 22.62 261.63 523.25 22.63 261.63 523.25 22.64 103.83 261.63 523.25 22.65 103.83 261.63 523.25 22.66 103.83 261.63 22.67 103.83 261.63 22.68 103.83 261.63 22.69 103.83 261.63 22.70 103.83 261.63 22.71 103.83 261.63 22.72 103.83 261.63 22.73 103.83 261.63 22.74 103.83 261.63 22.75 103.83 261.63 22.76 103.83 22.77 103.83 22.78 103.83 22.79 103.83 22.80 103.83 22.81 103.83 207.65 22.82 103.83 207.65 22.83 103.83 207.65 22.84 103.83 207.65 22.85 103.83 207.65 22.86 103.83 207.65 22.87 103.83 207.65 22.88 103.83 207.65 246.94 22.89 103.83 207.65 246.94 22.90 103.83 207.65 246.94 22.91 103.83 207.65 246.94 22.92 103.83 207.65 246.94 22.93 103.83 207.65 246.94 22.94 103.83 246.94 22.95 103.83 246.94 22.96 103.83 246.94 22.97 103.83 207.65 246.94 22.98 103.83 207.65 246.94 22.99 103.83 207.65 246.94 23.00 103.83 207.65 246.94 23.01 103.83 207.65 246.94 23.02 103.83 207.65 246.94 23.03 103.83 207.65 246.94 23.04 103.83 207.65 246.94 23.05 103.83 207.65 246.94 23.06 103.83 207.65 246.94 293.66 23.07 103.83 207.65 246.94 293.66 23.08 103.83 207.65 246.94 293.66 23.09 103.83 207.65 246.94 293.66 23.10 103.83 207.65 246.94 293.66 23.11 103.83 246.94 293.66 23.12 103.83 246.94 293.66 23.13 103.83 246.94 293.66 23.14 103.83 246.94 293.66 23.15 103.83 246.94 293.66 23.16 103.83 207.65 246.94 293.66 23.17 103.83 207.65 246.94 293.66 23.18 103.83 207.65 246.94 293.66 23.19 103.83 207.65 246.94 293.66 23.20 103.83 207.65 246.94 293.66 23.21 103.83 207.65 246.94 293.66 23.22 103.83 207.65 246.94 293.66 23.23 103.83 207.65 246.94 293.66 23.24 103.83 246.94 293.66 23.25 103.83 246.94 293.66 23.26 103.83 246.94 293.66 23.27 103.83 246.94 329.63 23.28 103.83 246.94 329.63 23.29 103.83 246.94 329.63 23.30 103.83 246.94 329.63 23.31 246.94 329.63 23.32 246.94 329.63 1479.98 23.33 246.94 329.63 1479.98 23.34 207.65 246.94 329.63 698.46 1479.98 23.35 207.65 246.94 329.63 698.46 1479.98 23.36 207.65 246.94 329.63 698.46 1479.98 23.37 207.65 246.94 329.63 698.46 1479.98 23.38 207.65 246.94 698.46 23.39 207.65 246.94 698.46 23.40 207.65 246.94 698.46 23.41 207.65 246.94 698.46 23.42 207.65 246.94 698.46 23.43 207.65 246.94 493.88 23.44 207.65 246.94 493.88 23.45 246.94 493.88 23.46 246.94 493.88 23.47 246.94 493.88 23.48 246.94 493.88 23.49 246.94 493.88 23.50 207.65 246.94 493.88 23.51 207.65 246.94 493.88 23.52 207.65 246.94 493.88 23.53 207.65 246.94 493.88 23.54 207.65 246.94 493.88 23.55 207.65 246.94 493.88 23.56 207.65 246.94 493.88 23.57 207.65 246.94 493.88 23.58 207.65 246.94 493.88 23.59 246.94 493.88 23.60 246.94 493.88 23.61 246.94 493.88 23.62 246.94 493.88 23.63 246.94 493.88 23.64 246.94 493.88 23.65 246.94 493.88 23.66 246.94 493.88 23.67 246.94 493.88 23.68 246.94 493.88 23.69 246.94 493.88 587.33 23.70 246.94 493.88 587.33 23.71 246.94 493.88 587.33 23.72 246.94 493.88 587.33 23.73 246.94 587.33 23.74 246.94 587.33 23.75 246.94 587.33 23.76 246.94 587.33 23.77 246.94 587.33 23.78 246.94 23.79 246.94 23.80 246.94 23.81 110.00 246.94 23.82 110.00 246.94 23.83 110.00 246.94 23.84 110.00 246.94 23.85 110.00 246.94 23.86 110.00 246.94 23.87 110.00 246.94 23.88 110.00 246.94 23.89 110.00 246.94 23.90 110.00 246.94 23.91 110.00 246.94 23.92 110.00 246.94 23.93 110.00 246.94 23.94 110.00 246.94 23.95 110.00 246.94 23.96 110.00 246.94 23.97 110.00 246.94 23.98 110.00 246.94 23.99 110.00 246.94 261.63 24.00 110.00 246.94 261.63 24.01 110.00 246.94 261.63 24.02 110.00 246.94 261.63 24.03 110.00 246.94 261.63 24.04 110.00 220.00 246.94 261.63 24.05 110.00 220.00 246.94 261.63 24.06 110.00 220.00 261.63 24.07 110.00 220.00 261.63 24.08 110.00 220.00 261.63 24.09 110.00 220.00 261.63 24.10 110.00 220.00 261.63 24.11 110.00 220.00 261.63 24.12 110.00 220.00 261.63 24.13 110.00 261.63 24.14 110.00 261.63 24.15 110.00 261.63 24.16 110.00 261.63 24.17 110.00 261.63 24.18 110.00 220.00 261.63 24.19 110.00 220.00 261.63 24.20 110.00 220.00 261.63 329.63 24.21 110.00 220.00 261.63 329.63 24.22 110.00 220.00 261.63 329.63 24.23 110.00 220.00 261.63 329.63 24.24 110.00 220.00 261.63 329.63 24.25 110.00 220.00 261.63 329.63 24.26 110.00 220.00 261.63 329.63 24.27 110.00 220.00 261.63 329.63 24.28 110.00 220.00 261.63 329.63 24.29 110.00 220.00 261.63 329.63 24.30 110.00 220.00 261.63 329.63 24.31 110.00 261.63 329.63 24.32 110.00 220.00 261.63 329.63 24.33 110.00 220.00 261.63 329.63 24.34 110.00 220.00 261.63 329.63 24.35 110.00 220.00 261.63 329.63 24.36 110.00 220.00 261.63 24.37 110.00 220.00 261.63 24.38 110.00 220.00 261.63 24.39 110.00 220.00 261.63 880.00 24.40 110.00 220.00 261.63 880.00 24.41 220.00 261.63 880.00 24.42 220.00 261.63 880.00 24.43 220.00 261.63 880.00 24.44 220.00 261.63 880.00 24.45 220.00 261.63 880.00 24.46 220.00 261.63 880.00 24.47 220.00 261.63 880.00 24.48 220.00 261.63 880.00 24.49 220.00 261.63 880.00 24.50 220.00 261.63 880.00 24.51 220.00 261.63 880.00 24.52 220.00 261.63 880.00 24.53 220.00 261.63 880.00 24.54 220.00 261.63 880.00 24.55 220.00 261.63 880.00 24.56 220.00 261.63 880.00 24.57 110.00 220.00 261.63 523.25 1046.50 24.58 110.00 220.00 261.63 523.25 1046.50 24.59 110.00 220.00 261.63 523.25 1046.50 24.60 110.00 220.00 261.63 523.25 1046.50 24.61 110.00 220.00 261.63 523.25 1046.50 24.62 110.00 220.00 261.63 523.25 1046.50 24.63 110.00 220.00 261.63 523.25 1046.50 24.64 110.00 220.00 261.63 523.25 1046.50 24.65 110.00 220.00 261.63 523.25 1046.50 24.66 110.00 220.00 261.63 329.63 523.25 24.67 110.00 220.00 261.63 329.63 523.25 24.68 220.00 261.63 329.63 523.25 24.69 220.00 261.63 329.63 523.25 24.70 220.00 261.63 329.63 523.25 24.71 220.00 261.63 329.63 523.25 24.72 220.00 261.63 329.63 523.25 24.73 220.00 261.63 329.63 523.25 1046.50 24.74 220.00 261.63 329.63 523.25 1046.50 24.75 220.00 261.63 329.63 1046.50 24.76 220.00 261.63 329.63 1046.50 24.77 220.00 261.63 329.63 1046.50 24.78 261.63 329.63 1046.50 24.79 261.63 329.63 1046.50 24.80 261.63 329.63 1046.50 24.81 261.63 329.63 1046.50 24.82 261.63 329.63 1046.50 24.83 261.63 329.63 1046.50 24.84 261.63 329.63 1046.50 24.85 261.63 329.63 1046.50 24.86 261.63 329.63 1046.50 24.87 261.63 329.63 440.00 24.88 261.63 329.63 440.00 24.89 261.63 329.63 440.00 24.90 261.63 329.63 440.00 1046.50 24.91 261.63 329.63 440.00 1046.50 24.92 261.63 329.63 440.00 1046.50 24.93 261.63 329.63 440.00 1046.50 24.94 146.83 261.63 440.00 1046.50 24.95 146.83 261.63 440.00 1046.50 24.96 146.83 261.63 440.00 1046.50 24.97 146.83 261.63 349.23 440.00 1046.50 24.98 146.83 261.63 349.23 440.00 1046.50 24.99 73.42 146.83 261.63 349.23 1046.50 25.00 73.42 146.83 261.63 349.23 1046.50 25.01 73.42 146.83 261.63 349.23 1046.50 25.02 73.42 146.83 261.63 349.23 1046.50 25.03 73.42 146.83 261.63 349.23 1046.50 25.04 73.42 146.83 261.63 349.23 1046.50 25.05 73.42 146.83 261.63 349.23 1046.50 25.06 73.42 146.83 261.63 349.23 1046.50 25.07 73.42 146.83 261.63 349.23 1046.50 25.08 73.42 146.83 261.63 349.23 1046.50 25.09 73.42 146.83 261.63 349.23 1046.50 25.10 73.42 146.83 349.23 1046.50 25.11 73.42 146.83 220.00 349.23 1046.50 25.12 73.42 146.83 220.00 349.23 1046.50 25.13 73.42 146.83 220.00 349.23 1046.50 25.14 73.42 146.83 220.00 349.23 1046.50 25.15 73.42 146.83 220.00 349.23 1046.50 25.16 73.42 146.83 220.00 349.23 1046.50 25.17 73.42 146.83 220.00 349.23 1046.50 25.18 73.42 146.83 220.00 349.23 1046.50 25.19 73.42 146.83 220.00 349.23 1046.50 25.20 73.42 146.83 220.00 349.23 1046.50 25.21 73.42 146.83 220.00 349.23 1046.50 25.22 73.42 146.83 220.00 349.23 1046.50 25.23 73.42 146.83 220.00 349.23 1046.50 25.24 73.42 146.83 220.00 349.23 1046.50 25.25 73.42 146.83 220.00 349.23 1046.50 25.26 73.42 146.83 220.00 349.23 1046.50 25.27 73.42 146.83 220.00 349.23 1046.50 25.28 73.42 146.83 220.00 349.23 1046.50 25.29 73.42 146.83 220.00 349.23 1046.50 25.30 73.42 146.83 220.00 349.23 1046.50 25.31 73.42 146.83 220.00 349.23 493.88 1046.50 25.32 73.42 146.83 220.00 349.23 493.88 1046.50 25.33 73.42 146.83 220.00 349.23 493.88 1046.50 25.34 73.42 146.83 220.00 349.23 493.88 1046.50 25.35 73.42 146.83 220.00 349.23 493.88 1046.50 25.36 73.42 146.83 220.00 349.23 493.88 1046.50 25.37 73.42 146.83 220.00 349.23 493.88 1046.50 25.38 73.42 146.83 220.00 349.23 493.88 1046.50 25.39 73.42 146.83 220.00 349.23 493.88 1046.50 25.40 73.42 146.83 349.23 493.88 1046.50 25.41 73.42 146.83 349.23 493.88 1046.50 25.42 73.42 146.83 349.23 493.88 1046.50 25.43 73.42 146.83 293.66 349.23 493.88 1046.50 25.44 73.42 146.83 293.66 349.23 493.88 1046.50 25.45 73.42 293.66 349.23 493.88 1046.50 25.46 73.42 293.66 349.23 493.88 1046.50 25.47 73.42 293.66 349.23 493.88 1046.50 25.48 73.42 293.66 349.23 493.88 1046.50 25.49 73.42 293.66 349.23 493.88 1046.50 25.50 73.42 293.66 349.23 493.88 1046.50 25.51 73.42 293.66 349.23 493.88 1046.50 25.52 73.42 293.66 493.88 1046.50 25.53 73.42 293.66 493.88 1046.50 25.54 73.42 293.66 493.88 25.55 73.42 293.66 493.88 25.56 73.42 293.66 493.88 25.57 73.42 293.66 493.88 25.58 73.42 293.66 493.88 25.59 73.42 293.66 349.23 493.88 25.60 73.42 293.66 349.23 493.88 25.61 73.42 293.66 349.23 493.88 25.62 73.42 293.66 349.23 493.88 25.63 73.42 293.66 349.23 493.88 25.64 73.42 146.83 293.66 349.23 493.88 25.65 73.42 146.83 293.66 349.23 493.88 25.66 73.42 146.83 293.66 349.23 493.88 25.67 73.42 146.83 293.66 349.23 493.88 25.68 73.42 146.83 293.66 349.23 493.88 25.69 73.42 146.83 220.00 293.66 349.23 493.88 25.70 73.42 146.83 220.00 293.66 349.23 493.88 25.71 73.42 146.83 220.00 293.66 349.23 493.88 25.72 73.42 146.83 220.00 293.66 349.23 493.88 25.73 73.42 146.83 220.00 293.66 349.23 493.88 25.74 73.42 146.83 220.00 293.66 349.23 493.88 25.75 73.42 146.83 220.00 293.66 349.23 493.88 25.76 73.42 146.83 220.00 293.66 349.23 493.88 25.77 73.42 146.83 220.00 293.66 349.23 493.88 25.78 146.83 220.00 293.66 349.23 493.88 25.79 146.83 220.00 293.66 349.23 493.88 25.80 146.83 220.00 293.66 349.23 493.88 25.81 146.83 220.00 293.66 349.23 493.88 25.82 146.83 220.00 293.66 349.23 493.88 25.83 146.83 220.00 293.66 349.23 493.88 25.84 146.83 220.00 293.66 349.23 493.88 25.85 146.83 220.00 293.66 349.23 493.88 25.86 146.83 220.00 293.66 349.23 493.88 25.87 146.83 220.00 349.23 493.88 1396.91 25.88 146.83 220.00 349.23 493.88 1396.91 25.89 146.83 220.00 349.23 493.88 1396.91 25.90 73.42 146.83 220.00 349.23 493.88 1396.91 25.91 73.42 146.83 220.00 349.23 493.88 1396.91 25.92 73.42 146.83 220.00 349.23 493.88 1396.91 25.93 73.42 146.83 220.00 349.23 493.88 1396.91 25.94 73.42 146.83 220.00 349.23 493.88 1396.91 25.95 73.42 146.83 220.00 349.23 493.88 1396.91 25.96 73.42 146.83 220.00 349.23 493.88 1396.91 25.97 73.42 146.83 220.00 349.23 493.88 1396.91 25.98 73.42 146.83 220.00 349.23 493.88 1396.91 25.99 73.42 146.83 220.00 349.23 493.88 1396.91 26.00 73.42 146.83 220.00 349.23 493.88 1396.91 26.01 73.42 146.83 220.00 349.23 493.88 1396.91 26.02 73.42 146.83 220.00 349.23 493.88 1396.91 26.03 73.42 146.83 349.23 1396.91 26.04 73.42 146.83 349.23 1396.91 26.05 146.83 349.23 1396.91 26.06 146.83 164.81 349.23 1396.91 26.07 146.83 164.81 349.23 1396.91 26.08 164.81 246.94 349.23 1396.91 26.09 164.81 246.94 349.23 1396.91 26.10 164.81 246.94 349.23 830.61 1396.91 26.11 164.81 246.94 349.23 830.61 1396.91 26.12 164.81 246.94 349.23 830.61 1396.91 26.13 82.41 164.81 246.94 349.23 830.61 1396.91 26.14 82.41 164.81 246.94 349.23 830.61 1396.91 26.15 82.41 164.81 246.94 349.23 830.61 1396.91 26.16 82.41 164.81 246.94 349.23 830.61 1396.91 26.17 82.41 164.81 246.94 349.23 1396.91 26.18 82.41 164.81 246.94 349.23 1396.91 26.19 82.41 164.81 246.94 349.23 1396.91 26.20 82.41 164.81 246.94 349.23 1396.91 26.21 82.41 164.81 246.94 349.23 1396.91 26.22 82.41 164.81 246.94 26.23 82.41 164.81 246.94 26.24 82.41 164.81 246.94 26.25 82.41 164.81 246.94 26.26 82.41 164.81 246.94 26.27 82.41 164.81 246.94 1318.51 26.28 82.41 164.81 246.94 1318.51 26.29 82.41 164.81 246.94 1318.51 26.30 82.41 164.81 246.94 1318.51 26.31 82.41 164.81 1318.51 26.32 82.41 164.81 1318.51 26.33 82.41 164.81 1318.51 26.34 82.41 164.81 349.23 1318.51 26.35 82.41 164.81 349.23 1318.51 26.36 82.41 164.81 349.23 1318.51 26.37 82.41 164.81 349.23 1318.51 26.38 82.41 164.81 349.23 1318.51 26.39 82.41 164.81 349.23 1318.51 26.40 82.41 164.81 349.23 26.41 82.41 164.81 349.23 26.42 82.41 164.81 349.23 26.43 82.41 87.31 164.81 440.00 26.44 82.41 87.31 164.81 440.00 26.45 82.41 87.31 164.81 246.94 440.00 1174.66 26.46 82.41 87.31 164.81 246.94 440.00 1174.66 26.47 82.41 87.31 164.81 246.94 440.00 1174.66 26.48 82.41 87.31 164.81 246.94 440.00 1174.66 26.49 82.41 87.31 164.81 246.94 440.00 1174.66 26.50 82.41 87.31 164.81 246.94 440.00 1174.66 26.51 82.41 87.31 164.81 246.94 440.00 1174.66 26.52 82.41 164.81 246.94 440.00 1174.66 26.53 82.41 164.81 246.94 440.00 1174.66 26.54 82.41 164.81 246.94 440.00 26.55 82.41 164.81 246.94 440.00 26.56 82.41 164.81 246.94 440.00 26.57 82.41 164.81 440.00 26.58 82.41 164.81 440.00 26.59 82.41 164.81 440.00 26.60 82.41 164.81 440.00 26.61 82.41 164.81 440.00 26.62 82.41 164.81 440.00 523.25 26.63 82.41 164.81 440.00 523.25 26.64 82.41 164.81 440.00 523.25 26.65 82.41 164.81 440.00 523.25 26.66 82.41 164.81 440.00 523.25 26.67 82.41 164.81 440.00 523.25 26.68 82.41 164.81 440.00 523.25 26.69 82.41 164.81 440.00 523.25 26.70 82.41 164.81 440.00 523.25 26.71 82.41 164.81 246.94 440.00 523.25 26.72 82.41 164.81 246.94 440.00 523.25 26.73 82.41 164.81 246.94 440.00 523.25 26.74 82.41 164.81 246.94 440.00 523.25 26.75 82.41 164.81 246.94 440.00 523.25 26.76 82.41 164.81 246.94 440.00 523.25 26.77 82.41 164.81 246.94 440.00 523.25 26.78 82.41 164.81 246.94 440.00 523.25 987.77 26.79 82.41 164.81 246.94 440.00 523.25 987.77 26.80 82.41 164.81 329.63 440.00 523.25 987.77 26.81 82.41 164.81 329.63 440.00 523.25 987.77 26.82 82.41 164.81 329.63 440.00 523.25 987.77 26.83 82.41 164.81 329.63 440.00 523.25 987.77 26.84 82.41 164.81 329.63 440.00 523.25 987.77 26.85 82.41 164.81 329.63 440.00 523.25 987.77 26.86 82.41 164.81 329.63 440.00 523.25 987.77 26.87 82.41 246.94 329.63 440.00 523.25 987.77 26.88 82.41 246.94 329.63 440.00 523.25 987.77 26.89 82.41 246.94 329.63 523.25 987.77 26.90 82.41 246.94 329.63 523.25 987.77 26.91 82.41 246.94 523.25 987.77 26.92 82.41 246.94 523.25 987.77 26.93 82.41 246.94 523.25 987.77 26.94 82.41 246.94 523.25 987.77 26.95 82.41 246.94 523.25 987.77 26.96 82.41 164.81 246.94 440.00 523.25 880.00 1760.00 26.97 82.41 164.81 246.94 440.00 523.25 880.00 1760.00 26.98 82.41 164.81 440.00 880.00 1760.00 26.99 82.41 164.81 440.00 880.00 1760.00 27.00 82.41 164.81 440.00 880.00 1760.00 27.01 164.81 440.00 830.61 880.00 1760.00 27.02 164.81 440.00 830.61 880.00 1760.00 27.03 164.81 440.00 830.61 880.00 1760.00 27.04 164.81 440.00 830.61 880.00 1760.00 27.05 164.81 440.00 830.61 880.00 27.06 164.81 440.00 830.61 880.00 27.07 164.81 440.00 830.61 880.00 27.08 82.41 164.81 440.00 830.61 880.00 27.09 82.41 164.81 440.00 830.61 880.00 27.10 82.41 164.81 440.00 830.61 880.00 27.11 82.41 164.81 440.00 830.61 880.00 27.12 82.41 164.81 440.00 830.61 27.13 82.41 164.81 440.00 830.61 27.14 82.41 164.81 440.00 830.61 27.15 82.41 164.81 246.94 329.63 440.00 830.61 27.16 82.41 164.81 246.94 329.63 440.00 830.61 27.17 164.81 246.94 329.63 440.00 830.61 27.18 164.81 246.94 329.63 440.00 830.61 27.19 164.81 246.94 329.63 440.00 830.61 27.20 164.81 246.94 329.63 440.00 830.61 2489.02 27.21 164.81 246.94 329.63 440.00 830.61 2489.02 27.22 82.41 164.81 246.94 329.63 440.00 830.61 2489.02 27.23 82.41 164.81 246.94 329.63 440.00 830.61 2489.02 27.24 82.41 164.81 329.63 440.00 830.61 2489.02 27.25 82.41 164.81 329.63 440.00 830.61 2489.02 27.26 82.41 164.81 329.63 440.00 830.61 2489.02 27.27 82.41 164.81 329.63 440.00 830.61 2489.02 27.28 82.41 164.81 329.63 440.00 830.61 2489.02 27.29 82.41 164.81 329.63 830.61 1479.98 2489.02 27.30 82.41 164.81 329.63 830.61 1479.98 2489.02 27.31 82.41 164.81 329.63 830.61 1479.98 27.32 82.41 164.81 329.63 830.61 1479.98 27.33 82.41 164.81 329.63 415.30 1479.98 27.34 82.41 164.81 329.63 415.30 1479.98 27.35 82.41 164.81 329.63 415.30 27.36 82.41 164.81 329.63 415.30 698.46 1661.22 27.37 82.41 164.81 329.63 415.30 698.46 1661.22 27.38 82.41 164.81 329.63 415.30 698.46 1661.22 27.39 82.41 164.81 329.63 415.30 698.46 1661.22 27.40 82.41 329.63 415.30 698.46 1661.22 27.41 82.41 329.63 415.30 698.46 1661.22 27.42 82.41 329.63 415.30 698.46 1661.22 27.43 82.41 329.63 415.30 698.46 1661.22 27.44 82.41 329.63 415.30 698.46 1661.22 27.45 82.41 329.63 415.30 27.46 82.41 329.63 415.30 27.47 82.41 329.63 415.30 27.48 82.41 329.63 415.30 27.49 82.41 329.63 415.30 27.50 82.41 329.63 415.30 659.26 27.51 82.41 329.63 415.30 659.26 27.52 82.41 329.63 415.30 659.26 27.53 82.41 329.63 415.30 659.26 27.54 82.41 415.30 493.88 659.26 27.55 82.41 415.30 493.88 659.26 27.56 82.41 415.30 493.88 659.26 27.57 82.41 415.30 493.88 659.26 27.58 82.41 415.30 493.88 659.26 27.59 82.41 415.30 493.88 659.26 27.60 82.41 415.30 493.88 659.26 27.61 82.41 415.30 493.88 659.26 27.62 82.41 415.30 493.88 659.26 27.63 82.41 415.30 493.88 659.26 27.64 82.41 415.30 493.88 659.26 27.65 82.41 415.30 493.88 659.26 27.66 82.41 415.30 493.88 27.67 82.41 415.30 493.88 27.68 82.41 415.30 493.88 27.69 82.41 415.30 493.88 27.70 82.41 415.30 493.88 27.71 82.41 415.30 493.88 27.72 82.41 415.30 493.88 27.73 82.41 164.81 415.30 493.88 587.33 27.74 82.41 164.81 415.30 493.88 587.33 27.75 82.41 164.81 415.30 493.88 587.33 659.26 27.76 82.41 164.81 415.30 493.88 587.33 659.26 27.77 82.41 164.81 415.30 493.88 587.33 659.26 27.78 82.41 164.81 415.30 493.88 587.33 659.26 27.79 82.41 164.81 415.30 493.88 587.33 659.26 27.80 82.41 164.81 415.30 493.88 587.33 659.26 27.81 82.41 164.81 415.30 493.88 587.33 659.26 27.82 82.41 164.81 246.94 415.30 493.88 659.26 27.83 82.41 164.81 246.94 415.30 493.88 659.26 27.84 82.41 164.81 246.94 415.30 493.88 659.26 27.85 82.41 164.81 246.94 415.30 493.88 659.26 27.86 82.41 164.81 246.94 415.30 493.88 659.26 27.87 82.41 164.81 246.94 415.30 523.25 659.26 830.61 27.88 82.41 164.81 246.94 415.30 523.25 659.26 830.61 27.89 164.81 246.94 415.30 523.25 659.26 830.61 27.90 164.81 246.94 415.30 523.25 659.26 830.61 27.91 164.81 415.30 523.25 830.61 27.92 164.81 415.30 523.25 830.61 27.93 164.81 415.30 523.25 830.61 27.94 164.81 415.30 523.25 830.61 27.95 164.81 415.30 523.25 830.61 27.96 164.81 415.30 523.25 830.61 27.97 164.81 415.30 523.25 830.61 27.98 164.81 415.30 523.25 830.61 27.99 164.81 415.30 523.25 830.61 28.00 164.81 415.30 523.25 830.61 28.01 164.81 415.30 830.61 28.02 164.81 415.30 830.61 28.03 164.81 415.30 830.61 28.04 164.81 415.30 830.61 28.05 164.81 415.30 830.61 28.06 164.81 415.30 830.61 28.07 164.81 415.30 830.61 28.08 164.81 415.30 830.61 28.09 164.81 415.30 830.61 28.10 164.81 415.30 830.61 28.11 164.81 415.30 830.61 28.12 164.81 415.30 830.61 28.13 164.81 415.30 830.61 28.14 164.81 415.30 830.61 28.15 164.81 415.30 830.61 28.16 164.81 415.30 830.61 28.17 164.81 415.30 830.61 28.18 164.81 415.30 830.61 28.19 164.81 415.30 830.61 28.20 164.81 415.30 830.61 28.21 164.81 415.30 830.61 28.22 164.81 415.30 830.61 28.23 164.81 415.30 830.61 28.24 164.81 415.30 830.61 28.25 164.81 415.30 830.61 28.26 164.81 415.30 830.61 28.27 164.81 415.30 830.61 28.28 164.81 415.30 830.61 28.29 164.81 220.00 415.30 440.00 493.88 830.61 28.30 164.81 220.00 415.30 440.00 493.88 830.61 28.31 110.00 164.81 220.00 415.30 440.00 493.88 830.61 28.32 110.00 164.81 220.00 415.30 440.00 493.88 830.61 28.33 110.00 164.81 220.00 415.30 440.00 493.88 28.34 110.00 164.81 220.00 415.30 440.00 493.88 28.35 110.00 164.81 220.00 415.30 440.00 493.88 28.36 110.00 164.81 220.00 415.30 440.00 493.88 28.37 110.00 164.81 220.00 415.30 440.00 493.88 28.38 110.00 164.81 220.00 440.00 493.88 28.39 110.00 164.81 220.00 440.00 493.88 28.40 110.00 164.81 220.00 440.00 493.88 28.41 110.00 164.81 220.00 440.00 493.88 28.42 110.00 220.00 440.00 493.88 28.43 110.00 220.00 440.00 493.88 28.44 110.00 220.00 440.00 493.88 28.45 110.00 220.00 440.00 28.46 110.00 220.00 440.00 28.47 110.00 220.00 440.00 1108.73 28.48 110.00 220.00 440.00 1108.73 28.49 110.00 220.00 440.00 1108.73 28.50 110.00 220.00 440.00 1108.73 28.51 110.00 220.00 440.00 1108.73 28.52 110.00 440.00 1108.73 28.53 110.00 440.00 1108.73 28.54 110.00 440.00 1108.73 28.55 110.00 440.00 1108.73 28.56 110.00 440.00 1108.73 28.57 110.00 220.00 440.00 1108.73 28.58 110.00 220.00 440.00 1108.73 28.59 110.00 220.00 440.00 1108.73 28.60 110.00 220.00 440.00 1108.73 28.61 110.00 220.00 440.00 1108.73 28.62 110.00 220.00 440.00 1108.73 28.63 110.00 220.00 440.00 1108.73 28.64 110.00 220.00 440.00 1108.73 28.65 110.00 220.00 440.00 1108.73 28.66 110.00 220.00 440.00 28.67 110.00 220.00 440.00 28.68 110.00 220.00 440.00 28.69 110.00 220.00 440.00 28.70 110.00 220.00 440.00 28.71 110.00 220.00 440.00 28.72 110.00 220.00 440.00 28.73 110.00 220.00 440.00 28.74 110.00 220.00 440.00 28.75 110.00 220.00 440.00 28.76 110.00 220.00 440.00 28.77 110.00 440.00 28.78 110.00 440.00 28.79 110.00 440.00 28.80 110.00 440.00 28.81 110.00 440.00 28.82 110.00 440.00 28.83 110.00 440.00 28.84 110.00 440.00 28.85 110.00 440.00 28.86 110.00 440.00 28.87 110.00 220.00 440.00 28.88 110.00 220.00 440.00 28.89 110.00 220.00 440.00 28.90 110.00 220.00 440.00 28.91 110.00 220.00 440.00 28.92 110.00 220.00 440.00 28.93 110.00 220.00 440.00 28.94 110.00 220.00 440.00 28.95 110.00 220.00 440.00 28.96 110.00 220.00 440.00 28.97 110.00 220.00 440.00 28.98 110.00 220.00 440.00 28.99 110.00 220.00 440.00 29.00 110.00 440.00 29.01 110.00 440.00 29.02 29.03 29.04 29.05 29.06 29.07 29.08 29.09 29.10 29.11 29.12 29.13 29.14 29.15 29.16 29.17 29.18 29.19 29.20 29.21 29.22 29.23 29.24 29.25 29.26 29.27 29.28 29.29 29.30 29.31 29.32 29.33 29.34 29.35 29.36 29.37 29.38 29.39 29.40 29.41 29.42 29.43 29.44 29.45 29.46 29.47 29.48 29.49 29.50 29.51 29.52 29.53 29.54 29.55 29.56 29.57 29.58 29.59 29.60 29.61 29.62 29.63 29.64 29.65 29.66 29.67 29.68 29.69 29.70 29.71 29.72 29.73 29.74 29.75 29.76 29.77 29.78 29.79 29.80 29.81 29.82 29.83 29.84 29.85 29.86 29.87 29.88 29.89 29.90 29.91 29.92 29.93 29.94 29.95 29.96 29.97 29.98 mir_eval-0.8.2/tests/data/multipitch/est02.txt000066400000000000000000003513611475740344600213010ustar00rootroot000000000000000.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.30 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.40 0.41 0.42 0.43 0.44 0.45 0.46 0.47 0.48 0.49 0.50 0.51 0.52 0.53 0.54 0.55 0.56 0.57 0.58 0.59 0.60 0.61 0.62 0.63 0.64 0.65 0.66 0.67 0.68 0.69 0.70 0.71 0.72 0.73 0.74 0.75 0.76 0.77 0.78 0.79 0.80 0.81 0.82 0.83 0.84 0.85 0.86 0.87 0.88 0.89 0.90 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1.00 1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.10 1.11 1.12 1.13 1.14 1.15 1.16 1.17 1.18 1.19 1.20 1.21 1.22 1.23 1.24 1.25 1.26 1.27 1.28 1.29 1.30 1.31 1.32 1.33 1.34 1.35 1.36 1.37 1.38 1.39 1.40 1.41 1.42 1.43 1.44 1.45 1.46 1.47 1.48 1.49 1.50 1.51 1.52 1.53 1.54 1.55 1.56 1.57 1.58 1.59 1.60 1.61 1.62 1.63 1.64 1.65 1.66 1.67 1.68 1.69 1.70 1.71 1.72 1.73 1.74 1.75 1.76 1.77 1.78 1.79 1.80 1.81 1.82 1.83 1.84 1.85 1.86 1.87 1.88 1.89 1.90 1.91 1.92 1.93 1.94 1.95 1.96 1.97 1.98 1.99 2.00 2.01 2.02 2.03 2.04 2.05 2.06 2.07 2.08 2.09 2.10 2.11 2.12 2.13 2.14 2.15 2.16 2.17 2.18 2.19 2.20 2.21 2.22 2.23 2.24 2.25 2.26 2.27 2.28 2.29 2.30 2.31 2.32 2.33 2.34 2.35 2.36 2.37 2.38 2.39 2.40 2.41 2.42 2.43 2.44 2.45 2.46 2.47 2.48 2.49 2.50 2.51 2.52 2.53 2.54 2.55 2.56 2.57 2.58 138.59 207.65 2.59 138.59 207.65 2.60 138.59 207.65 2.61 69.30 138.59 207.65 277.18 2.62 69.30 138.59 207.65 277.18 2.63 69.30 138.59 207.65 277.18 2.64 69.30 138.59 207.65 277.18 2.65 69.30 138.59 207.65 277.18 2.66 69.30 138.59 207.65 277.18 2.67 69.30 138.59 207.65 277.18 2.68 69.30 138.59 207.65 277.18 2.69 69.30 138.59 207.65 277.18 2.70 69.30 138.59 207.65 277.18 2.71 69.30 138.59 207.65 277.18 2.72 69.30 138.59 207.65 2.73 69.30 138.59 207.65 2.74 69.30 138.59 207.65 2.75 69.30 138.59 207.65 2.76 69.30 2.77 69.30 2.78 69.30 2.79 69.30 2.80 69.30 2.81 69.30 2.82 69.30 2.83 69.30 2.84 69.30 2.85 69.30 2.86 69.30 277.18 2.87 69.30 277.18 2.88 69.30 277.18 2.89 69.30 277.18 2.90 69.30 277.18 2.91 69.30 277.18 2.92 69.30 277.18 2.93 69.30 277.18 2.94 69.30 277.18 2.95 69.30 277.18 2.96 69.30 277.18 2.97 69.30 277.18 2.98 69.30 277.18 2.99 69.30 277.18 3.00 69.30 277.18 3.01 69.30 277.18 3.02 69.30 277.18 3.03 69.30 277.18 3.04 69.30 277.18 3.05 69.30 277.18 3.06 69.30 277.18 3.07 69.30 277.18 3.08 69.30 277.18 3.09 69.30 277.18 3.10 69.30 277.18 3.11 69.30 277.18 3.12 69.30 277.18 3.13 69.30 277.18 3.14 69.30 277.18 3.15 69.30 277.18 3.16 69.30 277.18 3.17 69.30 277.18 3.18 69.30 277.18 3.19 69.30 277.18 3.20 69.30 277.18 3.21 69.30 277.18 3.22 69.30 277.18 3.23 69.30 277.18 3.24 69.30 277.18 3.25 69.30 277.18 3.26 69.30 277.18 3.27 69.30 277.18 3.28 69.30 277.18 3.29 69.30 277.18 3.30 69.30 277.18 3.31 69.30 277.18 3.32 69.30 277.18 3.33 69.30 277.18 3.34 69.30 277.18 3.35 69.30 277.18 3.36 69.30 277.18 3.37 69.30 277.18 3.38 69.30 277.18 3.39 69.30 277.18 3.40 69.30 277.18 3.41 69.30 277.18 3.42 69.30 277.18 3.43 69.30 277.18 3.44 69.30 277.18 3.45 69.30 277.18 3.46 69.30 3.47 69.30 3.48 69.30 3.49 69.30 3.50 69.30 3.51 69.30 3.52 69.30 3.53 69.30 3.54 69.30 3.55 69.30 3.56 69.30 3.57 69.30 3.58 69.30 3.59 69.30 3.60 69.30 3.61 69.30 3.62 69.30 3.63 69.30 3.64 69.30 3.65 69.30 3.66 69.30 3.67 69.30 3.68 69.30 3.69 69.30 3.70 69.30 329.63 3.71 69.30 329.63 3.72 69.30 329.63 3.73 69.30 329.63 3.74 69.30 329.63 3.75 69.30 329.63 3.76 69.30 329.63 3.77 69.30 329.63 3.78 69.30 329.63 3.79 69.30 329.63 3.80 69.30 329.63 3.81 69.30 329.63 3.82 69.30 329.63 3.83 69.30 329.63 3.84 69.30 329.63 3.85 69.30 329.63 3.86 69.30 329.63 3.87 69.30 329.63 3.88 69.30 329.63 3.89 69.30 329.63 3.90 69.30 329.63 3.91 69.30 329.63 3.92 69.30 329.63 3.93 69.30 329.63 3.94 69.30 329.63 3.95 69.30 329.63 3.96 69.30 329.63 3.97 69.30 329.63 3.98 69.30 329.63 3.99 69.30 329.63 4.00 69.30 329.63 4.01 69.30 329.63 4.02 69.30 329.63 4.03 69.30 329.63 4.04 69.30 329.63 4.05 69.30 329.63 4.06 69.30 329.63 4.07 69.30 329.63 4.08 69.30 329.63 4.09 69.30 329.63 4.10 69.30 329.63 4.11 69.30 329.63 4.12 69.30 329.63 4.13 69.30 4.14 69.30 207.65 4.15 69.30 207.65 4.16 69.30 207.65 4.17 69.30 207.65 4.18 69.30 207.65 4.19 69.30 207.65 4.20 69.30 207.65 4.21 69.30 207.65 4.22 69.30 207.65 4.23 69.30 207.65 4.24 69.30 207.65 4.25 69.30 207.65 4.26 69.30 207.65 4.27 69.30 207.65 4.28 69.30 207.65 4.29 69.30 207.65 4.30 69.30 207.65 4.31 69.30 207.65 4.32 69.30 207.65 4.33 69.30 207.65 4.34 69.30 207.65 4.35 69.30 207.65 4.36 69.30 207.65 4.37 69.30 207.65 4.38 69.30 207.65 4.39 69.30 207.65 4.40 69.30 207.65 4.41 69.30 207.65 4.42 69.30 207.65 4.43 69.30 207.65 4.44 69.30 207.65 4.45 69.30 207.65 4.46 69.30 207.65 4.47 69.30 207.65 4.48 69.30 207.65 4.49 69.30 207.65 4.50 69.30 207.65 4.51 69.30 207.65 4.52 69.30 207.65 4.53 69.30 207.65 4.54 69.30 207.65 4.55 69.30 4.56 69.30 4.57 69.30 4.58 69.30 4.59 69.30 4.60 277.18 4.61 277.18 4.62 277.18 4.63 277.18 4.64 277.18 4.65 277.18 4.66 277.18 4.67 207.65 277.18 4.68 207.65 277.18 4.69 207.65 277.18 4.70 207.65 277.18 4.71 207.65 277.18 4.72 207.65 277.18 4.73 207.65 277.18 4.74 207.65 277.18 4.75 207.65 277.18 4.76 207.65 277.18 4.77 207.65 277.18 4.78 207.65 277.18 4.79 277.18 4.80 277.18 4.81 277.18 4.82 277.18 4.83 277.18 4.84 277.18 4.85 277.18 4.86 277.18 4.87 277.18 4.88 277.18 4.89 277.18 4.90 277.18 4.91 277.18 4.92 277.18 4.93 277.18 4.94 277.18 4.95 277.18 4.96 277.18 4.97 277.18 4.98 277.18 4.99 277.18 5.00 277.18 5.01 277.18 5.02 277.18 5.03 277.18 5.04 277.18 5.05 277.18 5.06 277.18 5.07 277.18 5.08 277.18 5.09 277.18 329.63 5.10 277.18 329.63 5.11 277.18 329.63 5.12 277.18 329.63 5.13 277.18 329.63 5.14 277.18 329.63 5.15 277.18 329.63 5.16 69.30 277.18 329.63 5.17 69.30 277.18 329.63 5.18 69.30 277.18 329.63 5.19 69.30 277.18 329.63 5.20 69.30 329.63 5.21 69.30 329.63 5.22 69.30 329.63 5.23 69.30 329.63 5.24 69.30 329.63 5.25 69.30 329.63 5.26 69.30 329.63 5.27 69.30 329.63 5.28 69.30 329.63 5.29 69.30 329.63 5.30 69.30 329.63 5.31 69.30 329.63 5.32 69.30 329.63 5.33 69.30 329.63 5.34 69.30 329.63 5.35 69.30 329.63 5.36 69.30 329.63 5.37 69.30 329.63 5.38 69.30 329.63 5.39 69.30 329.63 5.40 69.30 329.63 5.41 69.30 329.63 5.42 69.30 277.18 329.63 5.43 69.30 277.18 329.63 5.44 69.30 277.18 329.63 5.45 69.30 277.18 329.63 5.46 69.30 277.18 329.63 5.47 69.30 277.18 329.63 5.48 69.30 277.18 329.63 5.49 69.30 277.18 329.63 5.50 69.30 277.18 329.63 5.51 69.30 277.18 329.63 5.52 69.30 277.18 329.63 5.53 69.30 277.18 329.63 5.54 69.30 277.18 329.63 5.55 69.30 207.65 277.18 329.63 5.56 69.30 207.65 277.18 329.63 5.57 69.30 207.65 329.63 5.58 69.30 207.65 329.63 5.59 69.30 207.65 329.63 5.60 69.30 207.65 277.18 329.63 5.61 69.30 207.65 277.18 329.63 5.62 207.65 277.18 329.63 5.63 207.65 277.18 329.63 5.64 207.65 277.18 5.65 207.65 277.18 5.66 207.65 277.18 5.67 207.65 277.18 5.68 207.65 277.18 5.69 207.65 277.18 5.70 207.65 277.18 5.71 207.65 277.18 5.72 207.65 277.18 5.73 207.65 277.18 5.74 207.65 277.18 5.75 207.65 277.18 5.76 69.30 207.65 277.18 5.77 69.30 207.65 277.18 5.78 69.30 207.65 5.79 69.30 207.65 5.80 69.30 207.65 5.81 207.65 5.82 207.65 5.83 207.65 5.84 207.65 5.85 207.65 5.86 207.65 5.87 207.65 5.88 207.65 5.89 207.65 5.90 207.65 277.18 5.91 207.65 277.18 5.92 207.65 277.18 5.93 207.65 277.18 5.94 207.65 277.18 5.95 207.65 277.18 5.96 207.65 277.18 5.97 207.65 277.18 5.98 207.65 277.18 5.99 207.65 277.18 6.00 207.65 277.18 6.01 207.65 277.18 6.02 207.65 277.18 6.03 207.65 277.18 6.04 277.18 6.05 277.18 6.06 277.18 6.07 277.18 6.08 277.18 6.09 207.65 277.18 6.10 207.65 277.18 6.11 207.65 277.18 6.12 207.65 277.18 6.13 207.65 6.14 207.65 6.15 207.65 6.16 207.65 277.18 6.17 207.65 277.18 6.18 207.65 277.18 6.19 207.65 277.18 6.20 207.65 277.18 6.21 207.65 277.18 6.22 207.65 277.18 6.23 207.65 277.18 6.24 207.65 277.18 6.25 207.65 277.18 6.26 207.65 277.18 6.27 207.65 277.18 6.28 207.65 277.18 6.29 207.65 6.30 207.65 6.31 207.65 6.32 207.65 6.33 207.65 6.34 207.65 6.35 207.65 6.36 207.65 6.37 207.65 6.38 207.65 6.39 207.65 6.40 207.65 6.41 207.65 6.42 207.65 6.43 6.44 6.45 6.46 6.47 6.48 6.49 6.50 6.51 6.52 6.53 329.63 6.54 329.63 6.55 277.18 329.63 6.56 277.18 329.63 6.57 277.18 329.63 6.58 277.18 329.63 6.59 277.18 329.63 6.60 277.18 329.63 6.61 277.18 329.63 6.62 277.18 329.63 6.63 277.18 329.63 6.64 277.18 329.63 6.65 277.18 329.63 6.66 277.18 329.63 6.67 277.18 329.63 6.68 277.18 329.63 6.69 277.18 329.63 6.70 277.18 329.63 6.71 277.18 329.63 6.72 277.18 329.63 6.73 277.18 329.63 6.74 277.18 329.63 6.75 277.18 329.63 6.76 277.18 329.63 6.77 277.18 329.63 6.78 277.18 329.63 6.79 277.18 329.63 6.80 277.18 329.63 6.81 277.18 329.63 6.82 277.18 329.63 6.83 277.18 329.63 6.84 277.18 329.63 6.85 277.18 329.63 6.86 277.18 329.63 6.87 277.18 329.63 6.88 277.18 329.63 6.89 277.18 329.63 6.90 277.18 329.63 6.91 277.18 329.63 6.92 277.18 329.63 6.93 277.18 329.63 6.94 277.18 329.63 6.95 277.18 329.63 6.96 277.18 329.63 6.97 277.18 329.63 6.98 277.18 329.63 6.99 207.65 277.18 329.63 7.00 207.65 277.18 329.63 7.01 207.65 277.18 329.63 7.02 207.65 277.18 329.63 7.03 207.65 277.18 329.63 7.04 207.65 277.18 329.63 7.05 207.65 277.18 329.63 7.06 207.65 277.18 7.07 207.65 277.18 7.08 207.65 277.18 7.09 207.65 277.18 7.10 207.65 277.18 7.11 207.65 277.18 7.12 207.65 277.18 7.13 207.65 277.18 7.14 207.65 277.18 7.15 207.65 277.18 7.16 207.65 277.18 7.17 207.65 277.18 7.18 207.65 277.18 7.19 207.65 277.18 7.20 207.65 277.18 7.21 207.65 277.18 7.22 207.65 7.23 207.65 7.24 207.65 7.25 207.65 7.26 207.65 7.27 207.65 7.28 207.65 7.29 207.65 7.30 207.65 7.31 207.65 7.32 207.65 7.33 207.65 7.34 69.30 207.65 7.35 69.30 207.65 7.36 69.30 207.65 7.37 69.30 207.65 7.38 69.30 207.65 7.39 69.30 207.65 7.40 69.30 207.65 7.41 69.30 207.65 7.42 69.30 207.65 7.43 69.30 207.65 7.44 69.30 207.65 7.45 69.30 207.65 7.46 207.65 7.47 207.65 7.48 207.65 7.49 207.65 7.50 207.65 7.51 207.65 7.52 207.65 7.53 207.65 277.18 7.54 207.65 277.18 7.55 207.65 277.18 7.56 207.65 277.18 7.57 277.18 7.58 277.18 7.59 277.18 7.60 277.18 7.61 277.18 7.62 277.18 7.63 277.18 7.64 277.18 7.65 277.18 7.66 277.18 7.67 277.18 7.68 277.18 7.69 277.18 7.70 277.18 7.71 277.18 7.72 277.18 7.73 277.18 7.74 277.18 7.75 277.18 7.76 277.18 7.77 277.18 7.78 7.79 7.80 7.81 7.82 7.83 277.18 7.84 277.18 7.85 277.18 7.86 277.18 7.87 277.18 7.88 277.18 7.89 277.18 7.90 277.18 7.91 277.18 7.92 277.18 7.93 277.18 7.94 277.18 7.95 277.18 7.96 277.18 7.97 329.63 7.98 329.63 7.99 329.63 8.00 329.63 8.01 329.63 8.02 329.63 8.03 329.63 8.04 329.63 8.05 329.63 8.06 8.07 8.08 8.09 8.10 8.11 329.63 8.12 329.63 8.13 329.63 8.14 329.63 8.15 329.63 8.16 329.63 8.17 329.63 8.18 329.63 8.19 329.63 8.20 329.63 8.21 329.63 8.22 329.63 8.23 329.63 8.24 8.25 8.26 8.27 8.28 8.29 8.30 8.31 8.32 8.33 8.34 8.35 8.36 329.63 8.37 329.63 8.38 329.63 8.39 329.63 8.40 329.63 8.41 329.63 8.42 329.63 8.43 8.44 8.45 8.46 8.47 8.48 8.49 8.50 207.65 8.51 207.65 8.52 207.65 8.53 123.47 207.65 8.54 123.47 207.65 8.55 123.47 207.65 8.56 123.47 207.65 8.57 61.74 123.47 207.65 8.58 61.74 123.47 207.65 8.59 61.74 123.47 207.65 8.60 61.74 123.47 207.65 8.61 61.74 123.47 207.65 8.62 61.74 123.47 207.65 8.63 61.74 123.47 207.65 8.64 61.74 123.47 207.65 8.65 61.74 123.47 207.65 8.66 61.74 123.47 207.65 8.67 61.74 123.47 207.65 8.68 61.74 123.47 207.65 8.69 61.74 123.47 207.65 8.70 61.74 123.47 207.65 8.71 61.74 123.47 207.65 8.72 61.74 123.47 207.65 8.73 61.74 123.47 207.65 8.74 61.74 123.47 207.65 8.75 61.74 123.47 207.65 8.76 61.74 123.47 207.65 8.77 61.74 123.47 207.65 8.78 61.74 123.47 207.65 8.79 61.74 123.47 207.65 8.80 61.74 123.47 207.65 8.81 61.74 123.47 207.65 8.82 61.74 123.47 207.65 8.83 61.74 123.47 207.65 8.84 61.74 123.47 207.65 8.85 61.74 123.47 207.65 8.86 61.74 123.47 207.65 8.87 61.74 123.47 207.65 8.88 61.74 123.47 207.65 8.89 61.74 123.47 207.65 8.90 61.74 123.47 207.65 8.91 61.74 123.47 207.65 8.92 61.74 123.47 207.65 8.93 61.74 123.47 207.65 8.94 61.74 123.47 207.65 8.95 61.74 123.47 207.65 8.96 61.74 123.47 207.65 8.97 61.74 123.47 207.65 8.98 61.74 123.47 207.65 8.99 61.74 123.47 207.65 9.00 61.74 123.47 207.65 9.01 61.74 123.47 207.65 9.02 61.74 123.47 207.65 9.03 61.74 123.47 207.65 9.04 61.74 123.47 207.65 9.05 61.74 123.47 207.65 9.06 61.74 123.47 207.65 9.07 61.74 123.47 207.65 9.08 61.74 123.47 207.65 9.09 61.74 123.47 207.65 9.10 61.74 123.47 9.11 61.74 123.47 9.12 61.74 123.47 9.13 61.74 123.47 9.14 61.74 123.47 9.15 61.74 123.47 9.16 61.74 123.47 9.17 61.74 123.47 9.18 61.74 123.47 9.19 61.74 123.47 9.20 61.74 123.47 9.21 61.74 123.47 9.22 61.74 123.47 9.23 61.74 123.47 9.24 61.74 123.47 9.25 61.74 123.47 9.26 61.74 123.47 9.27 61.74 123.47 277.18 9.28 61.74 123.47 277.18 9.29 61.74 123.47 277.18 9.30 61.74 123.47 277.18 9.31 61.74 123.47 277.18 9.32 61.74 123.47 277.18 9.33 61.74 123.47 277.18 9.34 61.74 123.47 277.18 9.35 61.74 123.47 277.18 9.36 61.74 123.47 277.18 9.37 61.74 123.47 277.18 9.38 61.74 123.47 277.18 9.39 61.74 123.47 277.18 9.40 61.74 123.47 277.18 9.41 61.74 123.47 9.42 61.74 123.47 9.43 61.74 123.47 9.44 61.74 123.47 9.45 61.74 123.47 9.46 61.74 123.47 9.47 61.74 123.47 9.48 61.74 123.47 9.49 61.74 123.47 9.50 61.74 123.47 9.51 61.74 123.47 9.52 61.74 123.47 9.53 61.74 123.47 9.54 61.74 123.47 9.55 61.74 123.47 9.56 61.74 123.47 9.57 61.74 123.47 9.58 61.74 123.47 9.59 61.74 123.47 9.60 61.74 123.47 9.61 61.74 123.47 9.62 61.74 123.47 311.13 9.63 61.74 123.47 311.13 9.64 61.74 123.47 311.13 9.65 61.74 123.47 311.13 9.66 61.74 123.47 311.13 9.67 61.74 123.47 311.13 9.68 61.74 123.47 9.69 61.74 123.47 9.70 61.74 123.47 9.71 61.74 123.47 9.72 61.74 123.47 9.73 61.74 123.47 9.74 61.74 123.47 9.75 61.74 123.47 9.76 61.74 123.47 9.77 61.74 123.47 9.78 61.74 123.47 329.63 9.79 61.74 123.47 329.63 9.80 61.74 123.47 329.63 9.81 61.74 123.47 329.63 9.82 61.74 123.47 329.63 9.83 61.74 123.47 329.63 9.84 61.74 123.47 329.63 9.85 61.74 123.47 9.86 61.74 123.47 9.87 61.74 123.47 9.88 61.74 123.47 9.89 61.74 123.47 9.90 61.74 123.47 9.91 61.74 123.47 9.92 61.74 123.47 9.93 61.74 123.47 9.94 61.74 123.47 9.95 61.74 123.47 9.96 61.74 123.47 9.97 61.74 123.47 9.98 61.74 123.47 9.99 61.74 123.47 10.00 61.74 123.47 10.01 61.74 123.47 10.02 61.74 123.47 10.03 61.74 123.47 10.04 61.74 123.47 10.05 61.74 123.47 10.06 61.74 207.65 10.07 61.74 207.65 10.08 61.74 207.65 10.09 61.74 207.65 10.10 61.74 207.65 10.11 61.74 207.65 10.12 61.74 207.65 10.13 61.74 207.65 10.14 61.74 207.65 10.15 61.74 207.65 10.16 61.74 207.65 10.17 61.74 207.65 10.18 61.74 207.65 10.19 61.74 207.65 10.20 61.74 207.65 10.21 61.74 207.65 10.22 61.74 207.65 10.23 61.74 207.65 10.24 61.74 207.65 10.25 61.74 207.65 10.26 61.74 207.65 10.27 207.65 10.28 207.65 10.29 207.65 10.30 207.65 10.31 61.74 207.65 10.32 61.74 207.65 10.33 61.74 207.65 10.34 61.74 207.65 10.35 61.74 207.65 10.36 61.74 207.65 10.37 61.74 207.65 10.38 61.74 123.47 207.65 10.39 61.74 123.47 207.65 10.40 123.47 207.65 10.41 123.47 207.65 10.42 123.47 207.65 10.43 123.47 207.65 10.44 123.47 207.65 10.45 123.47 207.65 10.46 123.47 207.65 10.47 123.47 207.65 10.48 61.74 123.47 207.65 10.49 61.74 123.47 207.65 10.50 61.74 207.65 10.51 61.74 207.65 10.52 61.74 207.65 10.53 61.74 207.65 10.54 61.74 10.55 61.74 277.18 10.56 61.74 277.18 10.57 61.74 277.18 10.58 61.74 277.18 10.59 61.74 277.18 10.60 61.74 277.18 10.61 61.74 277.18 10.62 61.74 277.18 10.63 61.74 277.18 10.64 61.74 277.18 10.65 61.74 277.18 10.66 61.74 277.18 10.67 61.74 277.18 10.68 61.74 277.18 10.69 61.74 277.18 10.70 61.74 277.18 10.71 61.74 277.18 10.72 61.74 277.18 10.73 61.74 277.18 10.74 61.74 277.18 10.75 61.74 277.18 10.76 61.74 277.18 10.77 61.74 277.18 10.78 61.74 277.18 10.79 61.74 277.18 10.80 61.74 277.18 10.81 61.74 277.18 10.82 61.74 277.18 10.83 61.74 277.18 10.84 61.74 277.18 10.85 61.74 277.18 10.86 61.74 277.18 10.87 61.74 277.18 10.88 61.74 277.18 10.89 61.74 277.18 10.90 61.74 277.18 10.91 61.74 277.18 10.92 61.74 277.18 10.93 61.74 277.18 10.94 61.74 277.18 10.95 61.74 277.18 10.96 61.74 277.18 10.97 61.74 277.18 10.98 61.74 277.18 10.99 61.74 277.18 11.00 61.74 277.18 11.01 61.74 277.18 11.02 61.74 277.18 11.03 61.74 277.18 329.63 11.04 61.74 277.18 329.63 11.05 61.74 277.18 329.63 11.06 61.74 277.18 329.63 11.07 61.74 277.18 329.63 11.08 61.74 277.18 329.63 11.09 61.74 277.18 329.63 11.10 61.74 277.18 329.63 11.11 61.74 277.18 329.63 11.12 61.74 277.18 329.63 11.13 61.74 277.18 329.63 11.14 61.74 277.18 329.63 11.15 61.74 277.18 329.63 11.16 61.74 277.18 329.63 11.17 61.74 277.18 329.63 11.18 61.74 277.18 329.63 11.19 277.18 329.63 11.20 277.18 329.63 11.21 277.18 329.63 11.22 277.18 329.63 11.23 277.18 329.63 11.24 61.74 277.18 329.63 11.25 61.74 277.18 329.63 11.26 61.74 277.18 329.63 11.27 61.74 277.18 329.63 11.28 61.74 277.18 329.63 11.29 61.74 277.18 329.63 11.30 61.74 277.18 329.63 11.31 61.74 277.18 329.63 11.32 61.74 277.18 329.63 11.33 61.74 277.18 329.63 11.34 61.74 277.18 329.63 11.35 61.74 277.18 329.63 11.36 61.74 277.18 329.63 11.37 61.74 277.18 329.63 11.38 61.74 277.18 329.63 11.39 61.74 277.18 329.63 11.40 61.74 277.18 329.63 11.41 61.74 277.18 329.63 11.42 61.74 277.18 329.63 11.43 61.74 277.18 329.63 11.44 61.74 277.18 329.63 11.45 61.74 277.18 329.63 11.46 61.74 277.18 329.63 11.47 61.74 277.18 329.63 11.48 61.74 207.65 277.18 329.63 11.49 61.74 207.65 277.18 329.63 11.50 61.74 207.65 277.18 329.63 11.51 61.74 207.65 277.18 329.63 11.52 61.74 207.65 329.63 11.53 61.74 207.65 329.63 11.54 61.74 207.65 329.63 11.55 61.74 207.65 329.63 11.56 61.74 207.65 329.63 11.57 61.74 207.65 329.63 11.58 61.74 207.65 329.63 11.59 61.74 207.65 11.60 61.74 207.65 11.61 61.74 207.65 11.62 61.74 207.65 11.63 61.74 207.65 11.64 61.74 207.65 11.65 61.74 207.65 11.66 61.74 207.65 11.67 61.74 207.65 11.68 61.74 207.65 11.69 61.74 207.65 11.70 207.65 11.71 207.65 11.72 207.65 11.73 207.65 11.74 207.65 11.75 61.74 207.65 11.76 61.74 207.65 11.77 61.74 207.65 11.78 61.74 207.65 11.79 61.74 207.65 11.80 61.74 207.65 11.81 61.74 207.65 11.82 61.74 207.65 11.83 61.74 207.65 11.84 61.74 207.65 11.85 61.74 207.65 11.86 61.74 207.65 11.87 61.74 207.65 11.88 61.74 207.65 11.89 207.65 11.90 207.65 11.91 207.65 11.92 207.65 11.93 207.65 11.94 207.65 277.18 11.95 207.65 277.18 11.96 207.65 277.18 11.97 207.65 277.18 11.98 207.65 277.18 11.99 207.65 277.18 12.00 207.65 277.18 12.01 207.65 277.18 12.02 207.65 277.18 12.03 207.65 277.18 12.04 207.65 277.18 12.05 207.65 277.18 12.06 207.65 277.18 12.07 207.65 277.18 12.08 207.65 277.18 12.09 207.65 277.18 12.10 207.65 277.18 12.11 207.65 277.18 12.12 207.65 277.18 12.13 207.65 277.18 12.14 207.65 277.18 12.15 277.18 12.16 277.18 12.17 277.18 12.18 277.18 12.19 277.18 12.20 277.18 12.21 277.18 12.22 277.18 12.23 277.18 12.24 207.65 277.18 12.25 207.65 277.18 12.26 207.65 277.18 12.27 207.65 277.18 12.28 207.65 277.18 12.29 207.65 277.18 12.30 207.65 277.18 12.31 207.65 277.18 12.32 207.65 277.18 12.33 207.65 277.18 12.34 207.65 277.18 12.35 277.18 12.36 277.18 12.37 277.18 12.38 277.18 12.39 277.18 12.40 277.18 12.41 277.18 12.42 277.18 12.43 277.18 329.63 12.44 277.18 329.63 12.45 277.18 329.63 12.46 277.18 329.63 12.47 277.18 329.63 12.48 277.18 329.63 12.49 277.18 329.63 12.50 277.18 329.63 12.51 277.18 329.63 12.52 277.18 329.63 12.53 277.18 329.63 12.54 277.18 329.63 12.55 277.18 329.63 12.56 277.18 329.63 12.57 277.18 329.63 12.58 277.18 329.63 12.59 277.18 329.63 12.60 277.18 329.63 12.61 277.18 329.63 12.62 277.18 329.63 12.63 277.18 329.63 12.64 277.18 329.63 12.65 277.18 329.63 12.66 277.18 329.63 12.67 277.18 329.63 12.68 277.18 329.63 12.69 277.18 329.63 12.70 277.18 329.63 12.71 277.18 329.63 12.72 277.18 329.63 12.73 277.18 329.63 12.74 277.18 329.63 12.75 277.18 329.63 12.76 277.18 329.63 12.77 277.18 329.63 12.78 277.18 329.63 12.79 277.18 329.63 12.80 277.18 329.63 12.81 277.18 329.63 12.82 277.18 329.63 12.83 277.18 329.63 12.84 277.18 329.63 12.85 277.18 329.63 12.86 277.18 329.63 12.87 277.18 329.63 12.88 277.18 329.63 12.89 207.65 277.18 12.90 207.65 277.18 12.91 207.65 277.18 12.92 207.65 277.18 12.93 207.65 277.18 12.94 207.65 277.18 12.95 207.65 277.18 12.96 207.65 277.18 12.97 207.65 277.18 12.98 207.65 12.99 207.65 13.00 207.65 13.01 207.65 277.18 13.02 207.65 277.18 13.03 207.65 277.18 13.04 207.65 277.18 13.05 207.65 277.18 13.06 207.65 277.18 13.07 207.65 13.08 207.65 13.09 207.65 13.10 207.65 13.11 207.65 13.12 207.65 13.13 207.65 13.14 207.65 13.15 207.65 13.16 207.65 13.17 207.65 13.18 207.65 13.19 207.65 13.20 207.65 13.21 207.65 13.22 207.65 13.23 207.65 13.24 207.65 13.25 207.65 13.26 207.65 13.27 207.65 13.28 207.65 13.29 207.65 13.30 207.65 13.31 207.65 13.32 207.65 13.33 207.65 13.34 207.65 13.35 207.65 13.36 207.65 13.37 207.65 13.38 207.65 277.18 13.39 207.65 277.18 13.40 207.65 277.18 13.41 207.65 277.18 13.42 277.18 13.43 277.18 13.44 277.18 13.45 277.18 13.46 277.18 13.47 277.18 13.48 277.18 13.49 277.18 13.50 277.18 13.51 277.18 13.52 277.18 13.53 277.18 13.54 277.18 13.55 277.18 13.56 277.18 13.57 277.18 13.58 277.18 13.59 277.18 13.60 277.18 13.61 277.18 13.62 277.18 13.63 277.18 13.64 277.18 13.65 277.18 13.66 207.65 277.18 13.67 207.65 277.18 13.68 207.65 277.18 13.69 207.65 277.18 13.70 207.65 277.18 13.71 207.65 277.18 13.72 207.65 277.18 13.73 207.65 277.18 13.74 207.65 277.18 13.75 207.65 277.18 13.76 207.65 277.18 13.77 207.65 277.18 13.78 207.65 277.18 13.79 277.18 13.80 277.18 13.81 277.18 13.82 277.18 13.83 277.18 13.84 277.18 13.85 277.18 13.86 277.18 13.87 277.18 329.63 13.88 277.18 329.63 13.89 277.18 329.63 13.90 277.18 329.63 13.91 277.18 329.63 13.92 277.18 329.63 13.93 277.18 329.63 13.94 277.18 329.63 13.95 277.18 329.63 13.96 277.18 329.63 13.97 277.18 329.63 13.98 329.63 13.99 329.63 14.00 329.63 14.01 329.63 14.02 329.63 14.03 277.18 329.63 14.04 277.18 329.63 14.05 277.18 329.63 14.06 277.18 329.63 14.07 277.18 329.63 14.08 277.18 329.63 14.09 277.18 329.63 14.10 277.18 329.63 14.11 277.18 329.63 14.12 277.18 329.63 14.13 277.18 329.63 14.14 277.18 329.63 14.15 277.18 329.63 14.16 277.18 329.63 14.17 277.18 329.63 14.18 277.18 329.63 14.19 277.18 329.63 14.20 277.18 329.63 14.21 277.18 329.63 14.22 277.18 329.63 14.23 277.18 329.63 14.24 277.18 329.63 14.25 277.18 329.63 14.26 277.18 329.63 14.27 277.18 329.63 14.28 277.18 329.63 14.29 277.18 329.63 14.30 277.18 329.63 14.31 277.18 329.63 14.32 277.18 329.63 14.33 277.18 329.63 14.34 277.18 329.63 14.35 277.18 14.36 277.18 14.37 277.18 14.38 277.18 14.39 277.18 14.40 277.18 14.41 277.18 14.42 207.65 14.43 207.65 14.44 207.65 14.45 207.65 14.46 207.65 14.47 110.00 207.65 220.00 14.48 110.00 207.65 220.00 14.49 110.00 207.65 220.00 14.50 110.00 207.65 220.00 14.51 110.00 207.65 220.00 14.52 110.00 164.81 207.65 220.00 14.53 110.00 164.81 207.65 220.00 14.54 110.00 164.81 220.00 14.55 110.00 164.81 220.00 14.56 110.00 164.81 220.00 14.57 110.00 164.81 220.00 14.58 110.00 164.81 220.00 14.59 110.00 164.81 220.00 14.60 110.00 164.81 220.00 14.61 110.00 164.81 220.00 14.62 110.00 164.81 220.00 14.63 110.00 164.81 220.00 14.64 110.00 164.81 220.00 14.65 110.00 164.81 220.00 14.66 110.00 164.81 220.00 14.67 110.00 164.81 220.00 14.68 110.00 164.81 220.00 14.69 110.00 164.81 220.00 14.70 110.00 164.81 220.00 14.71 110.00 164.81 220.00 14.72 110.00 164.81 220.00 14.73 55.00 110.00 164.81 220.00 14.74 55.00 110.00 164.81 220.00 14.75 55.00 110.00 220.00 14.76 55.00 110.00 220.00 14.77 55.00 110.00 220.00 14.78 55.00 110.00 220.00 14.79 55.00 110.00 220.00 14.80 55.00 110.00 220.00 14.81 55.00 110.00 220.00 14.82 110.00 164.81 220.00 14.83 110.00 164.81 220.00 14.84 110.00 164.81 220.00 329.63 14.85 110.00 164.81 220.00 329.63 14.86 110.00 164.81 220.00 329.63 14.87 110.00 164.81 220.00 329.63 14.88 110.00 164.81 220.00 329.63 14.89 110.00 164.81 220.00 14.90 110.00 164.81 220.00 14.91 110.00 164.81 14.92 110.00 164.81 14.93 110.00 164.81 14.94 110.00 164.81 14.95 110.00 164.81 14.96 110.00 164.81 14.97 110.00 164.81 14.98 110.00 164.81 14.99 110.00 164.81 15.00 110.00 164.81 15.01 110.00 164.81 15.02 110.00 164.81 15.03 110.00 164.81 15.04 110.00 164.81 15.05 110.00 164.81 277.18 15.06 110.00 164.81 277.18 15.07 110.00 164.81 277.18 15.08 110.00 164.81 277.18 15.09 110.00 164.81 277.18 15.10 110.00 164.81 277.18 15.11 110.00 164.81 277.18 15.12 110.00 164.81 277.18 15.13 110.00 164.81 277.18 15.14 110.00 164.81 277.18 15.15 110.00 164.81 277.18 15.16 110.00 164.81 277.18 15.17 110.00 164.81 277.18 15.18 110.00 164.81 277.18 15.19 110.00 164.81 277.18 15.20 110.00 164.81 277.18 15.21 110.00 164.81 277.18 15.22 110.00 164.81 277.18 15.23 110.00 164.81 277.18 15.24 110.00 164.81 277.18 15.25 110.00 164.81 277.18 15.26 110.00 164.81 277.18 15.27 110.00 164.81 277.18 15.28 110.00 164.81 277.18 15.29 110.00 164.81 277.18 15.30 110.00 164.81 277.18 15.31 110.00 164.81 277.18 15.32 110.00 164.81 277.18 15.33 110.00 164.81 277.18 15.34 110.00 164.81 277.18 15.35 110.00 164.81 277.18 15.36 110.00 164.81 277.18 15.37 110.00 164.81 277.18 15.38 110.00 164.81 277.18 15.39 110.00 164.81 277.18 15.40 110.00 277.18 15.41 110.00 277.18 15.42 110.00 277.18 15.43 110.00 277.18 15.44 110.00 277.18 15.45 110.00 277.18 15.46 110.00 277.18 15.47 110.00 277.18 15.48 110.00 277.18 15.49 110.00 277.18 15.50 110.00 277.18 15.51 110.00 277.18 15.52 110.00 277.18 15.53 110.00 277.18 15.54 110.00 277.18 15.55 110.00 277.18 15.56 110.00 277.18 15.57 110.00 277.18 15.58 110.00 277.18 15.59 110.00 277.18 15.60 110.00 277.18 15.61 110.00 277.18 15.62 110.00 277.18 15.63 110.00 15.64 110.00 15.65 110.00 15.66 110.00 15.67 110.00 15.68 110.00 15.69 110.00 15.70 110.00 15.71 110.00 15.72 110.00 15.73 110.00 15.74 110.00 15.75 110.00 15.76 110.00 15.77 110.00 15.78 110.00 15.79 110.00 15.80 110.00 15.81 110.00 15.82 110.00 277.18 15.83 110.00 277.18 15.84 110.00 277.18 15.85 110.00 277.18 15.86 110.00 277.18 15.87 110.00 277.18 15.88 110.00 277.18 15.89 110.00 277.18 15.90 110.00 277.18 15.91 110.00 277.18 15.92 110.00 277.18 15.93 110.00 277.18 15.94 110.00 277.18 15.95 110.00 277.18 15.96 110.00 277.18 15.97 110.00 277.18 15.98 110.00 15.99 110.00 16.00 110.00 16.01 110.00 16.02 110.00 16.03 110.00 220.00 16.04 110.00 220.00 16.05 110.00 220.00 16.06 110.00 220.00 16.07 110.00 220.00 16.08 110.00 220.00 16.09 110.00 220.00 16.10 110.00 220.00 16.11 110.00 220.00 16.12 110.00 220.00 16.13 110.00 220.00 16.14 110.00 220.00 16.15 110.00 220.00 16.16 110.00 220.00 16.17 110.00 220.00 16.18 110.00 220.00 16.19 110.00 220.00 16.20 110.00 220.00 16.21 110.00 220.00 16.22 110.00 220.00 16.23 110.00 220.00 16.24 110.00 220.00 16.25 110.00 220.00 16.26 110.00 220.00 16.27 110.00 220.00 16.28 110.00 220.00 16.29 110.00 220.00 16.30 110.00 220.00 16.31 110.00 220.00 16.32 110.00 220.00 16.33 110.00 220.00 16.34 110.00 220.00 16.35 110.00 220.00 16.36 110.00 220.00 16.37 110.00 220.00 16.38 110.00 220.00 16.39 110.00 220.00 16.40 110.00 220.00 16.41 110.00 220.00 16.42 110.00 220.00 16.43 110.00 220.00 16.44 110.00 220.00 277.18 16.45 110.00 220.00 277.18 16.46 110.00 220.00 277.18 16.47 110.00 220.00 277.18 16.48 110.00 220.00 277.18 16.49 110.00 220.00 277.18 16.50 110.00 220.00 277.18 16.51 110.00 220.00 277.18 16.52 110.00 220.00 277.18 16.53 110.00 220.00 277.18 16.54 110.00 220.00 277.18 16.55 110.00 220.00 277.18 16.56 110.00 220.00 277.18 329.63 16.57 110.00 220.00 277.18 329.63 16.58 110.00 220.00 277.18 329.63 16.59 110.00 220.00 277.18 329.63 16.60 110.00 220.00 277.18 329.63 16.61 110.00 220.00 277.18 329.63 16.62 110.00 220.00 277.18 329.63 16.63 110.00 220.00 277.18 329.63 16.64 110.00 220.00 277.18 329.63 16.65 110.00 277.18 16.66 110.00 277.18 16.67 110.00 277.18 16.68 110.00 277.18 16.69 110.00 277.18 16.70 110.00 277.18 16.71 110.00 277.18 16.72 110.00 277.18 16.73 110.00 277.18 16.74 110.00 277.18 16.75 110.00 277.18 16.76 110.00 277.18 16.77 110.00 16.78 110.00 16.79 110.00 277.18 16.80 110.00 277.18 16.81 110.00 277.18 16.82 110.00 277.18 16.83 110.00 277.18 16.84 110.00 277.18 16.85 110.00 277.18 16.86 110.00 277.18 16.87 110.00 277.18 16.88 110.00 277.18 16.89 110.00 277.18 16.90 110.00 277.18 16.91 110.00 277.18 16.92 110.00 277.18 16.93 110.00 277.18 329.63 16.94 110.00 277.18 329.63 16.95 110.00 277.18 329.63 16.96 110.00 277.18 329.63 16.97 110.00 277.18 329.63 16.98 110.00 329.63 16.99 110.00 329.63 17.00 110.00 329.63 17.01 110.00 329.63 17.02 110.00 329.63 17.03 110.00 329.63 17.04 110.00 329.63 17.05 110.00 329.63 17.06 110.00 329.63 17.07 110.00 329.63 17.08 110.00 329.63 17.09 110.00 329.63 17.10 110.00 329.63 17.11 110.00 329.63 17.12 110.00 329.63 17.13 110.00 329.63 17.14 110.00 277.18 329.63 17.15 110.00 277.18 329.63 17.16 110.00 277.18 329.63 17.17 110.00 277.18 329.63 17.18 110.00 277.18 329.63 17.19 110.00 277.18 329.63 17.20 110.00 277.18 329.63 17.21 110.00 220.00 277.18 329.63 17.22 110.00 220.00 277.18 329.63 17.23 220.00 277.18 329.63 17.24 220.00 277.18 329.63 17.25 220.00 329.63 17.26 220.00 329.63 17.27 220.00 329.63 17.28 110.00 220.00 277.18 329.63 17.29 110.00 220.00 277.18 329.63 17.30 110.00 220.00 277.18 329.63 17.31 110.00 220.00 277.18 329.63 17.32 110.00 220.00 277.18 329.63 17.33 110.00 220.00 277.18 329.63 17.34 110.00 220.00 277.18 329.63 17.35 110.00 220.00 277.18 329.63 17.36 110.00 220.00 277.18 329.63 17.37 220.00 277.18 329.63 17.38 220.00 277.18 329.63 17.39 220.00 277.18 329.63 17.40 220.00 277.18 329.63 17.41 220.00 277.18 329.63 17.42 220.00 277.18 329.63 17.43 220.00 277.18 329.63 17.44 220.00 277.18 329.63 17.45 220.00 277.18 329.63 17.46 220.00 329.63 17.47 220.00 329.63 17.48 220.00 329.63 17.49 220.00 329.63 17.50 220.00 329.63 17.51 92.50 220.00 277.18 329.63 17.52 92.50 220.00 277.18 329.63 17.53 92.50 220.00 277.18 329.63 17.54 92.50 220.00 277.18 329.63 17.55 92.50 220.00 277.18 329.63 17.56 46.25 92.50 220.00 277.18 17.57 46.25 92.50 220.00 277.18 17.58 46.25 92.50 220.00 277.18 17.59 46.25 92.50 220.00 277.18 17.60 46.25 92.50 220.00 277.18 17.61 46.25 92.50 220.00 277.18 17.62 46.25 92.50 220.00 277.18 17.63 46.25 92.50 220.00 277.18 17.64 46.25 92.50 220.00 277.18 17.65 46.25 92.50 220.00 277.18 17.66 46.25 92.50 220.00 277.18 17.67 46.25 92.50 220.00 277.18 17.68 46.25 92.50 220.00 277.18 17.69 46.25 92.50 220.00 277.18 17.70 46.25 92.50 220.00 277.18 17.71 46.25 92.50 220.00 277.18 17.72 46.25 92.50 220.00 17.73 46.25 92.50 220.00 17.74 46.25 92.50 220.00 17.75 46.25 92.50 220.00 17.76 46.25 92.50 220.00 17.77 46.25 92.50 220.00 17.78 46.25 92.50 220.00 17.79 46.25 92.50 220.00 17.80 46.25 92.50 220.00 17.81 46.25 92.50 220.00 17.82 46.25 92.50 220.00 17.83 46.25 92.50 220.00 17.84 46.25 92.50 220.00 17.85 46.25 92.50 220.00 17.86 46.25 92.50 220.00 17.87 46.25 92.50 220.00 17.88 46.25 92.50 220.00 17.89 46.25 92.50 220.00 17.90 46.25 92.50 220.00 17.91 46.25 92.50 220.00 17.92 46.25 92.50 220.00 17.93 46.25 92.50 220.00 17.94 46.25 92.50 220.00 17.95 46.25 92.50 220.00 17.96 46.25 92.50 220.00 17.97 46.25 92.50 220.00 17.98 46.25 92.50 220.00 17.99 46.25 92.50 220.00 18.00 46.25 92.50 220.00 18.01 46.25 92.50 220.00 18.02 46.25 92.50 220.00 293.66 18.03 46.25 92.50 220.00 293.66 18.04 46.25 92.50 220.00 293.66 18.05 46.25 92.50 220.00 293.66 18.06 46.25 92.50 220.00 293.66 18.07 46.25 92.50 220.00 293.66 18.08 46.25 92.50 220.00 293.66 18.09 46.25 92.50 220.00 293.66 18.10 46.25 92.50 220.00 293.66 18.11 46.25 92.50 220.00 293.66 18.12 46.25 92.50 220.00 293.66 18.13 46.25 92.50 220.00 293.66 18.14 46.25 92.50 220.00 293.66 18.15 46.25 92.50 220.00 293.66 18.16 46.25 92.50 220.00 293.66 18.17 46.25 92.50 220.00 293.66 18.18 46.25 92.50 220.00 293.66 18.19 46.25 92.50 220.00 293.66 18.20 46.25 92.50 220.00 293.66 18.21 46.25 92.50 220.00 293.66 18.22 46.25 92.50 220.00 293.66 18.23 46.25 92.50 220.00 293.66 18.24 46.25 92.50 220.00 293.66 18.25 46.25 92.50 220.00 293.66 18.26 46.25 92.50 220.00 293.66 18.27 46.25 92.50 220.00 293.66 18.28 46.25 92.50 220.00 293.66 18.29 46.25 92.50 220.00 293.66 18.30 46.25 92.50 220.00 293.66 18.31 46.25 92.50 220.00 293.66 18.32 46.25 92.50 220.00 293.66 18.33 46.25 92.50 220.00 293.66 18.34 46.25 92.50 220.00 293.66 18.35 46.25 92.50 220.00 293.66 18.36 46.25 92.50 220.00 293.66 18.37 46.25 92.50 220.00 293.66 18.38 46.25 92.50 220.00 293.66 18.39 46.25 92.50 293.66 18.40 46.25 92.50 293.66 18.41 46.25 92.50 293.66 18.42 46.25 92.50 293.66 18.43 46.25 92.50 293.66 18.44 46.25 92.50 293.66 18.45 46.25 92.50 293.66 18.46 46.25 92.50 293.66 18.47 46.25 92.50 293.66 18.48 46.25 92.50 293.66 18.49 46.25 92.50 293.66 369.99 18.50 46.25 92.50 293.66 369.99 18.51 46.25 92.50 293.66 369.99 18.52 46.25 92.50 293.66 369.99 18.53 92.50 293.66 369.99 18.54 92.50 293.66 369.99 18.55 92.50 293.66 369.99 18.56 92.50 293.66 369.99 18.57 92.50 293.66 369.99 18.58 92.50 293.66 369.99 18.59 92.50 293.66 369.99 18.60 92.50 293.66 369.99 18.61 92.50 293.66 369.99 18.62 92.50 293.66 369.99 18.63 92.50 293.66 369.99 18.64 92.50 293.66 369.99 18.65 92.50 293.66 369.99 18.66 92.50 293.66 369.99 18.67 92.50 293.66 369.99 18.68 92.50 293.66 369.99 18.69 92.50 293.66 369.99 18.70 92.50 293.66 369.99 18.71 92.50 293.66 369.99 18.72 92.50 293.66 18.73 92.50 293.66 18.74 92.50 293.66 18.75 92.50 293.66 18.76 92.50 293.66 18.77 92.50 293.66 18.78 92.50 293.66 18.79 46.25 92.50 293.66 18.80 46.25 92.50 293.66 18.81 46.25 92.50 293.66 18.82 46.25 92.50 293.66 18.83 46.25 92.50 293.66 18.84 46.25 92.50 293.66 18.85 46.25 92.50 293.66 18.86 46.25 92.50 293.66 18.87 46.25 92.50 293.66 18.88 46.25 92.50 185.00 293.66 18.89 46.25 92.50 185.00 293.66 18.90 46.25 92.50 185.00 293.66 18.91 46.25 92.50 185.00 293.66 18.92 46.25 92.50 185.00 293.66 18.93 92.50 185.00 293.66 18.94 92.50 185.00 293.66 18.95 92.50 185.00 293.66 18.96 92.50 185.00 293.66 18.97 92.50 185.00 293.66 18.98 92.50 185.00 220.00 293.66 18.99 92.50 185.00 220.00 293.66 19.00 92.50 220.00 293.66 19.01 92.50 220.00 293.66 19.02 92.50 220.00 293.66 19.03 92.50 220.00 293.66 19.04 92.50 220.00 293.66 19.05 92.50 220.00 293.66 19.06 92.50 220.00 293.66 19.07 92.50 220.00 293.66 19.08 92.50 220.00 293.66 19.09 92.50 220.00 277.18 293.66 19.10 92.50 220.00 277.18 293.66 19.11 92.50 220.00 277.18 293.66 19.12 92.50 220.00 277.18 293.66 19.13 92.50 220.00 277.18 293.66 19.14 92.50 220.00 277.18 293.66 19.15 92.50 220.00 277.18 293.66 19.16 92.50 220.00 277.18 293.66 19.17 92.50 220.00 277.18 293.66 19.18 92.50 220.00 277.18 293.66 19.19 92.50 220.00 277.18 293.66 19.20 92.50 220.00 277.18 293.66 19.21 92.50 220.00 277.18 293.66 19.22 92.50 220.00 277.18 293.66 19.23 92.50 220.00 277.18 293.66 19.24 92.50 220.00 277.18 293.66 19.25 220.00 277.18 293.66 19.26 220.00 277.18 293.66 19.27 220.00 277.18 293.66 19.28 220.00 277.18 293.66 19.29 220.00 277.18 293.66 19.30 220.00 277.18 19.31 220.00 277.18 19.32 220.00 277.18 19.33 220.00 277.18 19.34 220.00 19.35 220.00 19.36 220.00 19.37 220.00 19.38 220.00 19.39 220.00 19.40 220.00 19.41 220.00 19.42 220.00 293.66 19.43 220.00 293.66 19.44 220.00 277.18 293.66 19.45 220.00 277.18 293.66 19.46 220.00 277.18 293.66 369.99 19.47 220.00 277.18 293.66 369.99 19.48 220.00 277.18 293.66 369.99 19.49 220.00 277.18 293.66 369.99 19.50 220.00 277.18 293.66 369.99 19.51 220.00 277.18 293.66 369.99 19.52 220.00 277.18 293.66 369.99 19.53 220.00 293.66 369.99 19.54 220.00 293.66 369.99 19.55 220.00 293.66 19.56 220.00 293.66 19.57 220.00 293.66 19.58 220.00 293.66 19.59 220.00 293.66 19.60 92.50 220.00 293.66 19.61 92.50 220.00 293.66 19.62 92.50 220.00 293.66 19.63 92.50 220.00 293.66 19.64 92.50 220.00 293.66 19.65 92.50 220.00 293.66 19.66 92.50 220.00 293.66 19.67 92.50 220.00 293.66 19.68 92.50 220.00 293.66 19.69 92.50 220.00 293.66 19.70 92.50 220.00 293.66 19.71 92.50 220.00 293.66 19.72 92.50 220.00 293.66 19.73 92.50 220.00 293.66 19.74 92.50 220.00 293.66 19.75 92.50 220.00 293.66 19.76 92.50 220.00 293.66 19.77 92.50 220.00 293.66 19.78 92.50 220.00 293.66 19.79 92.50 220.00 293.66 19.80 92.50 220.00 293.66 19.81 92.50 220.00 293.66 19.82 92.50 220.00 293.66 19.83 92.50 220.00 293.66 19.84 92.50 220.00 293.66 19.85 92.50 220.00 293.66 19.86 92.50 220.00 293.66 19.87 92.50 220.00 293.66 19.88 92.50 220.00 293.66 19.89 92.50 220.00 293.66 19.90 92.50 220.00 293.66 19.91 92.50 220.00 293.66 19.92 92.50 220.00 293.66 19.93 92.50 220.00 293.66 369.99 19.94 92.50 220.00 293.66 369.99 19.95 92.50 220.00 293.66 369.99 19.96 92.50 220.00 293.66 369.99 19.97 92.50 220.00 293.66 369.99 19.98 92.50 220.00 293.66 369.99 19.99 92.50 220.00 293.66 369.99 20.00 92.50 220.00 293.66 369.99 20.01 92.50 220.00 293.66 369.99 20.02 46.25 92.50 220.00 293.66 369.99 20.03 46.25 92.50 220.00 293.66 369.99 20.04 46.25 92.50 220.00 293.66 369.99 20.05 46.25 92.50 220.00 293.66 369.99 20.06 46.25 220.00 293.66 369.99 20.07 46.25 220.00 293.66 369.99 20.08 46.25 220.00 293.66 369.99 20.09 46.25 92.50 220.00 293.66 369.99 20.10 46.25 92.50 220.00 293.66 369.99 20.11 46.25 92.50 220.00 293.66 369.99 20.12 46.25 92.50 220.00 293.66 369.99 20.13 92.50 220.00 293.66 369.99 20.14 92.50 220.00 293.66 369.99 20.15 92.50 220.00 293.66 369.99 20.16 92.50 220.00 293.66 369.99 20.17 92.50 220.00 293.66 369.99 20.18 92.50 220.00 293.66 369.99 20.19 92.50 220.00 293.66 369.99 20.20 92.50 220.00 293.66 369.99 20.21 92.50 220.00 293.66 369.99 20.22 92.50 220.00 293.66 369.99 20.23 92.50 220.00 293.66 369.99 20.24 92.50 220.00 293.66 369.99 20.25 92.50 220.00 293.66 369.99 20.26 92.50 220.00 293.66 369.99 20.27 92.50 220.00 293.66 369.99 20.28 92.50 220.00 293.66 369.99 20.29 92.50 220.00 293.66 369.99 20.30 92.50 220.00 293.66 369.99 20.31 92.50 220.00 293.66 369.99 20.32 92.50 220.00 293.66 369.99 20.33 92.50 220.00 293.66 369.99 20.34 92.50 220.00 293.66 369.99 20.35 92.50 220.00 293.66 369.99 20.36 92.50 220.00 293.66 369.99 20.37 92.50 220.00 293.66 369.99 20.38 92.50 220.00 293.66 369.99 20.39 92.50 220.00 293.66 369.99 20.40 92.50 220.00 293.66 369.99 20.41 92.50 220.00 293.66 369.99 20.42 92.50 220.00 293.66 369.99 20.43 92.50 220.00 293.66 369.99 20.44 92.50 220.00 293.66 369.99 20.45 92.50 220.00 293.66 369.99 20.46 92.50 220.00 293.66 369.99 20.47 92.50 220.00 293.66 369.99 20.48 92.50 220.00 293.66 369.99 20.49 92.50 207.65 220.00 293.66 369.99 20.50 92.50 207.65 220.00 293.66 369.99 20.51 103.83 207.65 293.66 369.99 20.52 103.83 207.65 293.66 369.99 20.53 103.83 207.65 369.99 20.54 103.83 207.65 369.99 20.55 103.83 207.65 20.56 103.83 207.65 20.57 103.83 207.65 20.58 103.83 207.65 20.59 103.83 207.65 20.60 103.83 207.65 293.66 20.61 103.83 207.65 293.66 20.62 103.83 207.65 293.66 20.63 103.83 207.65 293.66 20.64 103.83 207.65 293.66 20.65 103.83 207.65 293.66 20.66 103.83 207.65 293.66 20.67 103.83 207.65 293.66 20.68 103.83 207.65 293.66 20.69 103.83 207.65 20.70 103.83 207.65 20.71 103.83 207.65 20.72 103.83 207.65 20.73 103.83 207.65 20.74 103.83 207.65 20.75 103.83 207.65 20.76 103.83 207.65 20.77 103.83 207.65 20.78 103.83 207.65 20.79 103.83 207.65 20.80 103.83 207.65 20.81 103.83 207.65 20.82 103.83 207.65 20.83 103.83 207.65 20.84 103.83 207.65 20.85 103.83 207.65 20.86 103.83 207.65 20.87 103.83 207.65 20.88 103.83 207.65 20.89 103.83 207.65 20.90 103.83 207.65 20.91 103.83 207.65 20.92 103.83 207.65 20.93 103.83 207.65 20.94 103.83 207.65 20.95 103.83 207.65 20.96 103.83 207.65 20.97 103.83 207.65 20.98 103.83 207.65 20.99 103.83 207.65 21.00 103.83 207.65 21.01 103.83 207.65 21.02 103.83 207.65 21.03 103.83 207.65 21.04 103.83 207.65 21.05 103.83 207.65 21.06 103.83 207.65 21.07 103.83 207.65 261.63 21.08 103.83 207.65 261.63 21.09 103.83 207.65 261.63 21.10 103.83 207.65 261.63 21.11 103.83 207.65 261.63 21.12 103.83 207.65 261.63 21.13 103.83 207.65 261.63 21.14 103.83 207.65 261.63 21.15 103.83 207.65 261.63 21.16 51.91 103.83 207.65 261.63 21.17 51.91 103.83 207.65 261.63 21.18 51.91 103.83 207.65 261.63 21.19 51.91 103.83 207.65 261.63 21.20 51.91 103.83 207.65 261.63 21.21 51.91 103.83 207.65 261.63 21.22 51.91 103.83 207.65 261.63 21.23 51.91 103.83 207.65 261.63 21.24 51.91 103.83 207.65 261.63 21.25 51.91 103.83 207.65 21.26 51.91 103.83 207.65 21.27 51.91 103.83 207.65 21.28 51.91 103.83 207.65 21.29 51.91 103.83 207.65 21.30 51.91 103.83 207.65 261.63 21.31 51.91 103.83 207.65 261.63 21.32 51.91 103.83 261.63 21.33 51.91 103.83 261.63 21.34 51.91 103.83 261.63 21.35 51.91 103.83 261.63 21.36 51.91 103.83 21.37 51.91 103.83 21.38 51.91 103.83 21.39 51.91 103.83 21.40 51.91 103.83 21.41 51.91 103.83 21.42 51.91 103.83 21.43 51.91 103.83 21.44 51.91 103.83 21.45 51.91 103.83 21.46 51.91 103.83 21.47 51.91 103.83 21.48 51.91 103.83 21.49 51.91 103.83 21.50 51.91 103.83 21.51 51.91 103.83 21.52 51.91 103.83 21.53 51.91 103.83 207.65 369.99 21.54 51.91 103.83 207.65 369.99 21.55 51.91 103.83 207.65 369.99 21.56 51.91 103.83 207.65 369.99 21.57 51.91 103.83 207.65 369.99 21.58 51.91 103.83 207.65 261.63 369.99 21.59 51.91 103.83 207.65 261.63 369.99 21.60 51.91 103.83 207.65 261.63 369.99 21.61 51.91 103.83 207.65 261.63 369.99 21.62 103.83 261.63 369.99 21.63 103.83 261.63 369.99 21.64 103.83 369.99 21.65 103.83 369.99 21.66 103.83 369.99 21.67 103.83 207.65 369.99 21.68 103.83 207.65 369.99 21.69 103.83 207.65 369.99 21.70 103.83 207.65 369.99 21.71 103.83 207.65 369.99 21.72 103.83 207.65 261.63 369.99 21.73 103.83 207.65 261.63 369.99 21.74 103.83 207.65 261.63 369.99 21.75 103.83 207.65 261.63 369.99 21.76 103.83 207.65 261.63 369.99 21.77 103.83 207.65 261.63 369.99 21.78 103.83 207.65 261.63 369.99 21.79 103.83 207.65 261.63 369.99 21.80 103.83 207.65 261.63 369.99 21.81 103.83 207.65 261.63 369.99 21.82 103.83 207.65 261.63 369.99 21.83 103.83 207.65 261.63 369.99 21.84 103.83 207.65 261.63 369.99 21.85 103.83 207.65 261.63 369.99 21.86 103.83 207.65 261.63 369.99 21.87 103.83 207.65 261.63 369.99 21.88 103.83 207.65 261.63 369.99 21.89 103.83 207.65 261.63 369.99 21.90 103.83 207.65 369.99 21.91 103.83 207.65 369.99 21.92 103.83 207.65 369.99 21.93 103.83 207.65 369.99 21.94 103.83 207.65 369.99 21.95 103.83 207.65 369.99 21.96 103.83 207.65 369.99 21.97 103.83 207.65 369.99 21.98 103.83 207.65 369.99 21.99 103.83 207.65 369.99 22.00 103.83 207.65 369.99 22.01 103.83 207.65 369.99 22.02 103.83 207.65 369.99 22.03 103.83 207.65 369.99 22.04 103.83 207.65 369.99 22.05 103.83 207.65 369.99 22.06 103.83 207.65 369.99 22.07 103.83 207.65 369.99 22.08 103.83 207.65 369.99 22.09 103.83 207.65 369.99 22.10 103.83 207.65 369.99 22.11 51.91 103.83 207.65 369.99 22.12 51.91 103.83 207.65 369.99 22.13 51.91 103.83 207.65 22.14 51.91 103.83 207.65 22.15 51.91 103.83 207.65 22.16 51.91 103.83 207.65 22.17 51.91 103.83 207.65 22.18 103.83 207.65 22.19 103.83 207.65 22.20 103.83 207.65 22.21 103.83 207.65 22.22 103.83 207.65 22.23 103.83 207.65 22.24 103.83 207.65 22.25 103.83 207.65 22.26 103.83 207.65 22.27 51.91 103.83 207.65 22.28 51.91 103.83 207.65 22.29 51.91 103.83 207.65 22.30 51.91 103.83 207.65 22.31 51.91 103.83 207.65 22.32 51.91 103.83 207.65 22.33 51.91 103.83 207.65 22.34 51.91 103.83 207.65 22.35 51.91 103.83 207.65 22.36 51.91 103.83 207.65 22.37 51.91 103.83 207.65 22.38 51.91 103.83 207.65 22.39 103.83 207.65 22.40 103.83 207.65 22.41 103.83 207.65 22.42 103.83 207.65 22.43 103.83 207.65 22.44 103.83 207.65 22.45 103.83 207.65 22.46 103.83 207.65 22.47 103.83 207.65 22.48 103.83 207.65 22.49 103.83 207.65 22.50 103.83 207.65 22.51 103.83 207.65 277.18 22.52 103.83 207.65 277.18 22.53 103.83 277.18 22.54 103.83 277.18 22.55 103.83 277.18 22.56 103.83 277.18 22.57 103.83 277.18 22.58 103.83 277.18 22.59 103.83 277.18 22.60 103.83 277.18 22.61 103.83 277.18 22.62 103.83 277.18 22.63 103.83 277.18 22.64 103.83 277.18 22.65 103.83 277.18 22.66 103.83 277.18 22.67 103.83 277.18 22.68 103.83 277.18 22.69 103.83 277.18 22.70 103.83 277.18 22.71 103.83 277.18 22.72 103.83 277.18 22.73 277.18 22.74 277.18 22.75 277.18 22.76 277.18 22.77 277.18 22.78 277.18 22.79 277.18 22.80 277.18 22.81 277.18 22.82 277.18 22.83 277.18 22.84 277.18 22.85 277.18 22.86 277.18 22.87 277.18 22.88 277.18 22.89 277.18 22.90 277.18 22.91 277.18 22.92 277.18 22.93 277.18 22.94 277.18 22.95 103.83 277.18 22.96 103.83 277.18 22.97 103.83 277.18 22.98 103.83 277.18 22.99 103.83 277.18 329.63 23.00 103.83 277.18 329.63 23.01 103.83 277.18 329.63 23.02 103.83 277.18 329.63 23.03 103.83 277.18 329.63 23.04 103.83 277.18 329.63 23.05 103.83 277.18 329.63 23.06 103.83 277.18 329.63 23.07 103.83 277.18 329.63 23.08 103.83 277.18 329.63 23.09 103.83 277.18 329.63 23.10 103.83 277.18 329.63 23.11 103.83 277.18 329.63 23.12 103.83 277.18 329.63 23.13 103.83 277.18 329.63 23.14 103.83 277.18 329.63 23.15 103.83 277.18 329.63 23.16 103.83 277.18 329.63 23.17 103.83 277.18 329.63 23.18 103.83 277.18 329.63 23.19 103.83 277.18 329.63 23.20 103.83 277.18 329.63 23.21 103.83 277.18 329.63 23.22 103.83 277.18 329.63 23.23 103.83 277.18 329.63 23.24 103.83 277.18 329.63 23.25 103.83 277.18 329.63 23.26 103.83 277.18 329.63 23.27 103.83 277.18 329.63 23.28 103.83 277.18 329.63 23.29 103.83 277.18 329.63 23.30 103.83 277.18 329.63 23.31 103.83 277.18 329.63 23.32 103.83 277.18 329.63 23.33 103.83 277.18 329.63 23.34 103.83 277.18 329.63 23.35 103.83 277.18 329.63 23.36 103.83 277.18 329.63 23.37 103.83 277.18 329.63 23.38 103.83 277.18 329.63 23.39 103.83 277.18 329.63 23.40 103.83 277.18 329.63 23.41 103.83 277.18 329.63 23.42 103.83 277.18 329.63 23.43 103.83 277.18 329.63 23.44 103.83 277.18 329.63 23.45 103.83 277.18 329.63 23.46 103.83 277.18 329.63 23.47 103.83 277.18 329.63 23.48 103.83 277.18 329.63 23.49 103.83 277.18 329.63 23.50 103.83 277.18 23.51 103.83 277.18 23.52 103.83 277.18 23.53 103.83 277.18 23.54 103.83 277.18 23.55 103.83 277.18 23.56 103.83 277.18 23.57 103.83 277.18 23.58 103.83 277.18 23.59 103.83 277.18 23.60 103.83 277.18 23.61 103.83 277.18 23.62 103.83 23.63 103.83 23.64 103.83 23.65 103.83 23.66 103.83 23.67 103.83 23.68 103.83 23.69 103.83 207.65 23.70 103.83 207.65 23.71 103.83 207.65 23.72 103.83 207.65 23.73 103.83 207.65 23.74 103.83 207.65 23.75 103.83 207.65 23.76 103.83 207.65 23.77 103.83 207.65 23.78 103.83 207.65 23.79 103.83 207.65 23.80 103.83 207.65 23.81 103.83 207.65 23.82 103.83 207.65 23.83 103.83 207.65 23.84 103.83 207.65 23.85 103.83 207.65 23.86 103.83 207.65 23.87 103.83 207.65 23.88 103.83 207.65 23.89 103.83 207.65 23.90 103.83 207.65 23.91 103.83 207.65 23.92 103.83 207.65 23.93 103.83 207.65 23.94 103.83 207.65 23.95 103.83 207.65 23.96 103.83 207.65 23.97 103.83 207.65 23.98 103.83 207.65 23.99 103.83 207.65 24.00 103.83 207.65 24.01 103.83 207.65 24.02 103.83 207.65 24.03 103.83 207.65 24.04 51.91 103.83 207.65 24.05 51.91 103.83 207.65 24.06 51.91 103.83 207.65 24.07 51.91 103.83 207.65 24.08 51.91 103.83 207.65 24.09 51.91 103.83 207.65 24.10 103.83 24.11 103.83 24.12 103.83 24.13 103.83 24.14 103.83 24.15 103.83 277.18 24.16 103.83 277.18 24.17 103.83 277.18 24.18 103.83 277.18 24.19 103.83 277.18 24.20 103.83 277.18 24.21 103.83 277.18 24.22 103.83 277.18 24.23 103.83 277.18 24.24 103.83 277.18 24.25 103.83 277.18 24.26 103.83 277.18 24.27 103.83 277.18 24.28 103.83 277.18 24.29 103.83 277.18 24.30 103.83 277.18 24.31 103.83 277.18 24.32 103.83 277.18 24.33 103.83 277.18 24.34 103.83 277.18 24.35 103.83 277.18 24.36 103.83 24.37 103.83 24.38 103.83 24.39 103.83 24.40 103.83 24.41 103.83 24.42 103.83 24.43 103.83 24.44 103.83 24.45 103.83 24.46 103.83 24.47 103.83 24.48 103.83 24.49 103.83 24.50 103.83 277.18 24.51 103.83 277.18 24.52 103.83 277.18 24.53 103.83 277.18 24.54 103.83 277.18 24.55 103.83 277.18 311.13 24.56 103.83 277.18 311.13 24.57 103.83 311.13 24.58 103.83 311.13 24.59 103.83 311.13 24.60 103.83 311.13 24.61 103.83 311.13 24.62 103.83 311.13 24.63 103.83 311.13 24.64 103.83 311.13 24.65 103.83 311.13 24.66 103.83 311.13 24.67 103.83 311.13 24.68 103.83 311.13 24.69 103.83 311.13 24.70 103.83 311.13 24.71 103.83 311.13 24.72 103.83 311.13 24.73 103.83 311.13 24.74 103.83 311.13 24.75 103.83 311.13 24.76 103.83 311.13 24.77 103.83 311.13 24.78 103.83 311.13 24.79 103.83 311.13 24.80 103.83 311.13 24.81 103.83 311.13 24.82 103.83 311.13 24.83 103.83 311.13 24.84 103.83 311.13 24.85 103.83 311.13 24.86 103.83 311.13 24.87 103.83 311.13 24.88 103.83 311.13 24.89 103.83 311.13 24.90 103.83 311.13 24.91 103.83 311.13 24.92 103.83 311.13 24.93 103.83 311.13 24.94 51.91 103.83 311.13 24.95 51.91 103.83 311.13 24.96 51.91 103.83 311.13 24.97 51.91 103.83 311.13 24.98 51.91 103.83 311.13 24.99 51.91 103.83 311.13 25.00 51.91 103.83 311.13 25.01 51.91 103.83 311.13 25.02 51.91 103.83 311.13 25.03 103.83 311.13 25.04 103.83 185.00 311.13 25.05 103.83 185.00 311.13 25.06 103.83 185.00 25.07 103.83 185.00 25.08 103.83 185.00 25.09 103.83 185.00 25.10 103.83 185.00 25.11 103.83 185.00 25.12 103.83 185.00 25.13 103.83 185.00 25.14 103.83 185.00 25.15 103.83 185.00 25.16 103.83 185.00 25.17 103.83 185.00 25.18 103.83 185.00 25.19 103.83 185.00 25.20 103.83 185.00 25.21 103.83 185.00 25.22 103.83 185.00 25.23 103.83 185.00 25.24 103.83 185.00 25.25 103.83 185.00 25.26 103.83 185.00 25.27 103.83 185.00 25.28 103.83 185.00 25.29 103.83 185.00 25.30 103.83 185.00 25.31 103.83 185.00 25.32 103.83 185.00 25.33 103.83 185.00 25.34 103.83 185.00 25.35 103.83 185.00 25.36 103.83 185.00 25.37 103.83 185.00 25.38 103.83 185.00 25.39 103.83 185.00 25.40 103.83 185.00 25.41 103.83 185.00 25.42 103.83 185.00 25.43 103.83 185.00 25.44 103.83 185.00 25.45 103.83 185.00 25.46 103.83 185.00 25.47 103.83 185.00 25.48 103.83 185.00 25.49 103.83 185.00 25.50 103.83 185.00 25.51 103.83 185.00 25.52 103.83 185.00 25.53 103.83 185.00 25.54 103.83 185.00 25.55 103.83 185.00 25.56 103.83 185.00 25.57 103.83 185.00 207.65 261.63 25.58 103.83 185.00 207.65 261.63 25.59 103.83 185.00 207.65 261.63 25.60 103.83 185.00 207.65 261.63 25.61 103.83 185.00 207.65 261.63 25.62 103.83 185.00 207.65 261.63 25.63 103.83 185.00 207.65 261.63 25.64 103.83 185.00 207.65 261.63 25.65 103.83 185.00 207.65 261.63 25.66 103.83 185.00 261.63 25.67 103.83 185.00 261.63 25.68 103.83 185.00 261.63 25.69 103.83 185.00 261.63 25.70 103.83 185.00 261.63 25.71 103.83 185.00 261.63 25.72 103.83 185.00 261.63 25.73 103.83 185.00 261.63 25.74 103.83 185.00 261.63 25.75 103.83 185.00 261.63 25.76 103.83 185.00 261.63 25.77 103.83 185.00 261.63 25.78 103.83 185.00 261.63 25.79 103.83 185.00 261.63 25.80 103.83 185.00 261.63 25.81 103.83 185.00 261.63 25.82 103.83 185.00 261.63 25.83 103.83 185.00 261.63 25.84 103.83 185.00 261.63 25.85 103.83 185.00 261.63 25.86 103.83 185.00 261.63 25.87 103.83 185.00 261.63 25.88 103.83 185.00 261.63 25.89 103.83 185.00 261.63 25.90 103.83 185.00 261.63 25.91 103.83 185.00 261.63 25.92 103.83 185.00 261.63 25.93 103.83 185.00 261.63 25.94 103.83 185.00 261.63 25.95 103.83 185.00 261.63 25.96 103.83 185.00 261.63 25.97 103.83 185.00 261.63 25.98 103.83 185.00 261.63 25.99 103.83 185.00 261.63 26.00 103.83 185.00 261.63 26.01 103.83 185.00 261.63 26.02 103.83 185.00 261.63 26.03 103.83 185.00 261.63 26.04 103.83 185.00 261.63 26.05 103.83 185.00 261.63 26.06 103.83 185.00 261.63 26.07 103.83 185.00 261.63 26.08 103.83 185.00 261.63 26.09 103.83 185.00 261.63 26.10 103.83 185.00 261.63 26.11 103.83 185.00 261.63 26.12 103.83 185.00 261.63 26.13 103.83 185.00 261.63 311.13 26.14 103.83 185.00 261.63 311.13 26.15 103.83 185.00 261.63 311.13 26.16 103.83 185.00 261.63 311.13 26.17 185.00 261.63 311.13 26.18 185.00 261.63 311.13 26.19 185.00 261.63 311.13 26.20 103.83 185.00 261.63 311.13 26.21 103.83 185.00 261.63 311.13 26.22 103.83 185.00 261.63 311.13 26.23 103.83 185.00 261.63 311.13 26.24 103.83 185.00 261.63 311.13 26.25 103.83 185.00 261.63 311.13 26.26 103.83 185.00 261.63 311.13 26.27 103.83 185.00 261.63 311.13 26.28 103.83 185.00 261.63 311.13 26.29 103.83 185.00 261.63 311.13 26.30 103.83 185.00 261.63 311.13 26.31 103.83 185.00 261.63 311.13 26.32 103.83 185.00 261.63 311.13 26.33 103.83 185.00 261.63 311.13 26.34 103.83 185.00 261.63 311.13 26.35 103.83 185.00 261.63 311.13 26.36 103.83 185.00 261.63 311.13 26.37 103.83 185.00 261.63 311.13 26.38 103.83 185.00 261.63 311.13 26.39 103.83 185.00 261.63 311.13 26.40 103.83 185.00 261.63 311.13 26.41 103.83 185.00 261.63 311.13 26.42 103.83 185.00 261.63 311.13 26.43 103.83 185.00 261.63 311.13 26.44 103.83 185.00 261.63 311.13 26.45 103.83 185.00 261.63 311.13 26.46 103.83 185.00 261.63 311.13 26.47 103.83 185.00 261.63 311.13 26.48 103.83 185.00 261.63 311.13 26.49 103.83 185.00 261.63 311.13 26.50 103.83 185.00 261.63 311.13 26.51 103.83 185.00 261.63 311.13 26.52 103.83 185.00 261.63 311.13 26.53 103.83 185.00 261.63 311.13 26.54 103.83 185.00 261.63 311.13 26.55 103.83 185.00 261.63 311.13 26.56 103.83 185.00 261.63 311.13 26.57 103.83 261.63 311.13 26.58 103.83 261.63 311.13 26.59 103.83 311.13 26.60 103.83 311.13 26.61 103.83 311.13 26.62 103.83 311.13 26.63 103.83 311.13 26.64 103.83 311.13 26.65 103.83 311.13 26.66 103.83 261.63 311.13 26.67 103.83 261.63 311.13 26.68 103.83 261.63 311.13 26.69 103.83 261.63 311.13 26.70 103.83 261.63 311.13 26.71 103.83 261.63 311.13 26.72 103.83 261.63 311.13 26.73 103.83 261.63 311.13 26.74 103.83 261.63 311.13 26.75 103.83 261.63 311.13 26.76 103.83 261.63 311.13 26.77 103.83 261.63 311.13 26.78 103.83 261.63 311.13 26.79 103.83 261.63 311.13 26.80 103.83 261.63 311.13 26.81 103.83 261.63 311.13 26.82 103.83 311.13 26.83 103.83 311.13 26.84 103.83 311.13 26.85 103.83 311.13 26.86 103.83 311.13 26.87 103.83 311.13 26.88 103.83 311.13 26.89 103.83 277.18 311.13 26.90 103.83 277.18 311.13 26.91 103.83 277.18 311.13 26.92 69.30 103.83 277.18 311.13 26.93 69.30 103.83 277.18 311.13 26.94 69.30 103.83 138.59 277.18 26.95 69.30 103.83 138.59 277.18 26.96 69.30 103.83 138.59 164.81 277.18 26.97 69.30 103.83 138.59 164.81 277.18 26.98 69.30 103.83 138.59 164.81 277.18 26.99 69.30 103.83 138.59 164.81 207.65 277.18 27.00 69.30 103.83 138.59 164.81 207.65 277.18 27.01 69.30 103.83 138.59 164.81 207.65 277.18 27.02 69.30 103.83 138.59 164.81 207.65 277.18 27.03 69.30 103.83 138.59 164.81 207.65 277.18 27.04 69.30 103.83 138.59 164.81 207.65 277.18 27.05 69.30 103.83 138.59 164.81 207.65 277.18 27.06 69.30 103.83 138.59 164.81 207.65 277.18 27.07 69.30 103.83 138.59 164.81 207.65 277.18 27.08 69.30 103.83 164.81 207.65 277.18 27.09 69.30 103.83 164.81 207.65 277.18 27.10 69.30 103.83 164.81 207.65 277.18 27.11 69.30 103.83 164.81 207.65 277.18 27.12 69.30 103.83 164.81 207.65 277.18 27.13 69.30 103.83 164.81 207.65 277.18 27.14 69.30 103.83 164.81 207.65 277.18 27.15 69.30 103.83 164.81 207.65 277.18 27.16 69.30 103.83 164.81 207.65 277.18 27.17 69.30 103.83 164.81 207.65 277.18 27.18 69.30 103.83 164.81 207.65 277.18 27.19 69.30 103.83 164.81 207.65 277.18 27.20 69.30 103.83 164.81 207.65 277.18 27.21 69.30 103.83 164.81 207.65 277.18 27.22 69.30 103.83 164.81 207.65 277.18 27.23 69.30 103.83 164.81 207.65 277.18 27.24 69.30 103.83 164.81 207.65 277.18 27.25 69.30 103.83 164.81 207.65 277.18 27.26 69.30 103.83 164.81 207.65 277.18 27.27 69.30 103.83 164.81 207.65 277.18 27.28 69.30 103.83 164.81 207.65 277.18 27.29 69.30 103.83 164.81 207.65 277.18 27.30 69.30 103.83 164.81 207.65 277.18 27.31 69.30 103.83 164.81 207.65 277.18 27.32 69.30 103.83 164.81 207.65 277.18 27.33 69.30 103.83 164.81 207.65 277.18 27.34 69.30 103.83 164.81 207.65 277.18 27.35 69.30 103.83 164.81 207.65 27.36 69.30 103.83 164.81 207.65 27.37 69.30 103.83 164.81 207.65 27.38 69.30 103.83 164.81 207.65 27.39 69.30 103.83 164.81 207.65 27.40 69.30 103.83 164.81 207.65 277.18 27.41 69.30 103.83 164.81 207.65 277.18 27.42 69.30 103.83 164.81 207.65 277.18 27.43 69.30 103.83 164.81 207.65 277.18 27.44 69.30 103.83 164.81 207.65 277.18 27.45 69.30 103.83 164.81 207.65 277.18 27.46 69.30 103.83 164.81 207.65 277.18 27.47 69.30 103.83 164.81 207.65 277.18 27.48 69.30 103.83 164.81 207.65 277.18 27.49 69.30 103.83 164.81 207.65 277.18 27.50 69.30 103.83 164.81 207.65 277.18 27.51 69.30 103.83 164.81 207.65 277.18 27.52 69.30 103.83 164.81 207.65 277.18 27.53 69.30 103.83 164.81 207.65 277.18 27.54 69.30 103.83 164.81 207.65 277.18 27.55 69.30 103.83 164.81 207.65 277.18 27.56 69.30 164.81 207.65 277.18 27.57 69.30 164.81 207.65 277.18 27.58 69.30 164.81 207.65 277.18 27.59 69.30 164.81 207.65 277.18 27.60 69.30 164.81 207.65 277.18 27.61 69.30 103.83 164.81 207.65 277.18 27.62 69.30 103.83 164.81 207.65 277.18 27.63 69.30 103.83 164.81 207.65 277.18 27.64 69.30 103.83 164.81 207.65 277.18 27.65 69.30 103.83 164.81 207.65 277.18 27.66 69.30 103.83 164.81 207.65 277.18 27.67 69.30 103.83 164.81 207.65 277.18 27.68 69.30 103.83 164.81 207.65 277.18 27.69 69.30 103.83 164.81 207.65 277.18 27.70 69.30 103.83 164.81 207.65 277.18 27.71 69.30 103.83 164.81 207.65 277.18 27.72 69.30 103.83 164.81 207.65 277.18 27.73 69.30 103.83 164.81 207.65 277.18 27.74 69.30 103.83 164.81 207.65 277.18 27.75 69.30 103.83 164.81 207.65 27.76 69.30 103.83 164.81 207.65 27.77 69.30 103.83 164.81 207.65 27.78 69.30 103.83 164.81 207.65 277.18 27.79 69.30 103.83 164.81 207.65 277.18 27.80 69.30 103.83 164.81 207.65 277.18 27.81 69.30 103.83 164.81 207.65 277.18 27.82 69.30 164.81 207.65 277.18 27.83 69.30 164.81 207.65 277.18 27.84 69.30 164.81 207.65 277.18 27.85 69.30 103.83 164.81 207.65 277.18 27.86 69.30 103.83 164.81 207.65 277.18 27.87 69.30 103.83 164.81 207.65 277.18 27.88 69.30 103.83 164.81 207.65 277.18 27.89 69.30 103.83 164.81 207.65 277.18 27.90 69.30 103.83 164.81 207.65 277.18 27.91 69.30 103.83 164.81 207.65 277.18 27.92 69.30 103.83 164.81 207.65 277.18 27.93 69.30 103.83 164.81 207.65 277.18 27.94 69.30 103.83 164.81 207.65 277.18 27.95 69.30 103.83 164.81 207.65 277.18 27.96 69.30 103.83 164.81 207.65 277.18 27.97 69.30 103.83 164.81 207.65 277.18 27.98 69.30 164.81 207.65 277.18 27.99 69.30 164.81 207.65 277.18 28.00 69.30 164.81 207.65 277.18 28.01 164.81 207.65 277.18 28.02 164.81 207.65 277.18 28.03 164.81 207.65 277.18 28.04 164.81 207.65 277.18 28.05 164.81 207.65 277.18 28.06 164.81 207.65 277.18 28.07 164.81 207.65 277.18 28.08 164.81 207.65 277.18 28.09 164.81 207.65 277.18 28.10 164.81 207.65 277.18 28.11 164.81 207.65 277.18 28.12 103.83 164.81 277.18 28.13 103.83 164.81 277.18 28.14 103.83 164.81 277.18 28.15 103.83 164.81 277.18 28.16 103.83 164.81 277.18 28.17 103.83 164.81 277.18 28.18 103.83 164.81 277.18 28.19 103.83 164.81 277.18 28.20 103.83 164.81 277.18 28.21 164.81 277.18 28.22 164.81 277.18 28.23 164.81 277.18 28.24 164.81 277.18 28.25 164.81 277.18 28.26 164.81 277.18 28.27 164.81 277.18 28.28 164.81 277.18 28.29 164.81 277.18 28.30 164.81 277.18 28.31 164.81 277.18 28.32 164.81 277.18 28.33 164.81 277.18 28.34 164.81 277.18 28.35 164.81 277.18 28.36 164.81 277.18 28.37 164.81 277.18 28.38 164.81 277.18 28.39 164.81 277.18 28.40 164.81 277.18 28.41 164.81 277.18 28.42 164.81 277.18 28.43 164.81 277.18 28.44 164.81 277.18 28.45 164.81 277.18 28.46 164.81 277.18 28.47 164.81 207.65 277.18 28.48 164.81 207.65 277.18 28.49 164.81 207.65 277.18 28.50 164.81 207.65 277.18 28.51 164.81 207.65 277.18 28.52 207.65 277.18 28.53 207.65 277.18 28.54 207.65 277.18 28.55 207.65 277.18 28.56 207.65 277.18 28.57 207.65 277.18 28.58 207.65 277.18 28.59 207.65 277.18 28.60 207.65 277.18 28.61 207.65 277.18 28.62 207.65 277.18 28.63 207.65 277.18 28.64 207.65 277.18 28.65 207.65 277.18 28.66 207.65 277.18 28.67 207.65 277.18 28.68 207.65 277.18 28.69 207.65 277.18 28.70 207.65 277.18 28.71 207.65 277.18 28.72 207.65 277.18 28.73 207.65 277.18 28.74 207.65 277.18 28.75 207.65 277.18 28.76 207.65 277.18 28.77 207.65 277.18 28.78 207.65 277.18 28.79 207.65 277.18 28.80 207.65 277.18 28.81 207.65 277.18 28.82 207.65 277.18 28.83 207.65 277.18 28.84 207.65 277.18 28.85 207.65 277.18 28.86 207.65 277.18 28.87 207.65 277.18 28.88 207.65 277.18 28.89 207.65 277.18 415.30 28.90 207.65 277.18 415.30 28.91 207.65 277.18 415.30 28.92 207.65 277.18 415.30 28.93 207.65 277.18 415.30 28.94 103.83 207.65 277.18 415.30 28.95 103.83 207.65 277.18 415.30 28.96 103.83 277.18 415.30 28.97 103.83 277.18 415.30 28.98 103.83 277.18 415.30 28.99 103.83 277.18 415.30 29.00 103.83 277.18 415.30 29.01 103.83 277.18 415.30 29.02 103.83 277.18 415.30 29.03 103.83 207.65 277.18 415.30 29.04 103.83 207.65 277.18 415.30 29.05 103.83 207.65 277.18 29.06 103.83 207.65 277.18 29.07 207.65 277.18 29.08 207.65 277.18 29.09 207.65 277.18 29.10 207.65 277.18 29.11 207.65 277.18 29.12 207.65 277.18 29.13 207.65 277.18 29.14 207.65 277.18 29.15 207.65 277.18 29.16 207.65 277.18 29.17 207.65 277.18 29.18 207.65 277.18 29.19 207.65 277.18 29.20 207.65 277.18 29.21 207.65 277.18 29.22 207.65 277.18 29.23 207.65 277.18 29.24 277.18 29.25 277.18 29.26 277.18 29.27 277.18 29.28 277.18 29.29 277.18 29.30 277.18 29.31 277.18 29.32 277.18 29.33 277.18 29.34 277.18 29.35 277.18 29.36 277.18 29.37 277.18 29.38 277.18 29.39 277.18 29.40 277.18 29.41 277.18 29.42 277.18 29.43 277.18 29.44 277.18 29.45 277.18 29.46 277.18 29.47 277.18 29.48 277.18 29.49 164.81 277.18 29.50 164.81 277.18 29.51 164.81 277.18 29.52 164.81 277.18 29.53 164.81 277.18 29.54 164.81 277.18 29.55 164.81 277.18 29.56 164.81 277.18 29.57 164.81 277.18 29.58 164.81 277.18 29.59 164.81 277.18 29.60 164.81 277.18 29.61 164.81 277.18 29.62 164.81 277.18 29.63 164.81 277.18 29.64 164.81 277.18 29.65 164.81 277.18 29.66 164.81 277.18 29.67 164.81 277.18 29.68 164.81 277.18 29.69 164.81 277.18 29.70 164.81 277.18 29.71 164.81 277.18 29.72 164.81 277.18 29.73 164.81 277.18 29.74 164.81 277.18 29.75 164.81 277.18 29.76 164.81 277.18 29.77 164.81 277.18 29.78 164.81 277.18 29.79 164.81 277.18 29.80 164.81 277.18 29.81 164.81 277.18 29.82 164.81 277.18 29.83 164.81 277.18 29.84 164.81 277.18 29.85 164.81 277.18 29.86 164.81 277.18 29.87 164.81 277.18 29.88 164.81 277.18 29.89 164.81 277.18 29.90 164.81 277.18 29.91 164.81 277.18 29.92 164.81 277.18 29.93 164.81 277.18 29.94 164.81 277.18 29.95 164.81 277.18 29.96 164.81 277.18 29.97 164.81 277.18 29.98 164.81 207.65 277.18 29.99 164.81 207.65 277.18 30.00 164.81 207.65 277.18 30.01 164.81 207.65 277.18 30.02 164.81 207.65 277.18 30.03 207.65 277.18 30.04 207.65 277.18 30.05 207.65 277.18 30.06 207.65 277.18 30.07 207.65 277.18 30.08 207.65 277.18 30.09 207.65 277.18 30.10 207.65 277.18 30.11 207.65 277.18 30.12 207.65 277.18 30.13 207.65 277.18 30.14 207.65 277.18 30.15 207.65 277.18 30.16 207.65 277.18 30.17 207.65 277.18 30.18 207.65 277.18 30.19 207.65 277.18 30.20 207.65 277.18 30.21 207.65 277.18 30.22 207.65 277.18 30.23 207.65 277.18 30.24 207.65 277.18 30.25 207.65 277.18 30.26 207.65 277.18 30.27 207.65 277.18 30.28 207.65 277.18 30.29 207.65 277.18 30.30 207.65 277.18 30.31 207.65 277.18 30.32 207.65 277.18 30.33 207.65 277.18 30.34 207.65 277.18 30.35 207.65 277.18 30.36 207.65 277.18 30.37 207.65 277.18 30.38 207.65 277.18 30.39 207.65 277.18 30.40 207.65 277.18 30.41 207.65 277.18 30.42 207.65 277.18 30.43 207.65 277.18 30.44 207.65 277.18 30.45 207.65 277.18 30.46 207.65 277.18 30.47 207.65 277.18 30.48 207.65 277.18 30.49 207.65 277.18 30.50 207.65 277.18 30.51 207.65 277.18 30.52 207.65 277.18 30.53 207.65 277.18 30.54 207.65 277.18 30.55 207.65 277.18 30.56 164.81 277.18 30.57 164.81 277.18 30.58 164.81 277.18 30.59 164.81 277.18 30.60 164.81 277.18 30.61 164.81 277.18 30.62 164.81 277.18 30.63 164.81 277.18 30.64 164.81 277.18 30.65 164.81 277.18 30.66 164.81 277.18 30.67 164.81 277.18 30.68 164.81 277.18 30.69 164.81 277.18 30.70 164.81 277.18 30.71 164.81 277.18 30.72 164.81 277.18 30.73 164.81 207.65 277.18 30.74 164.81 207.65 277.18 30.75 164.81 207.65 277.18 30.76 164.81 207.65 277.18 30.77 164.81 207.65 277.18 30.78 164.81 207.65 277.18 30.79 164.81 207.65 277.18 30.80 164.81 207.65 277.18 30.81 164.81 207.65 277.18 30.82 164.81 207.65 277.18 30.83 164.81 207.65 277.18 30.84 164.81 207.65 277.18 30.85 164.81 207.65 277.18 30.86 164.81 207.65 277.18 30.87 164.81 207.65 277.18 30.88 164.81 207.65 277.18 30.89 164.81 207.65 277.18 30.90 164.81 207.65 277.18 30.91 164.81 207.65 277.18 30.92 164.81 207.65 277.18 30.93 164.81 207.65 277.18 30.94 164.81 207.65 277.18 30.95 164.81 207.65 277.18 30.96 164.81 207.65 277.18 30.97 164.81 207.65 277.18 30.98 207.65 277.18 30.99 207.65 277.18 31.00 207.65 277.18 31.01 207.65 277.18 31.02 207.65 277.18 31.03 207.65 277.18 31.04 207.65 277.18 31.05 207.65 277.18 31.06 207.65 277.18 31.07 207.65 277.18 31.08 207.65 277.18 31.09 207.65 277.18 31.10 207.65 277.18 31.11 207.65 277.18 31.12 277.18 31.13 277.18 31.14 277.18 31.15 277.18 31.16 277.18 31.17 277.18 31.18 277.18 31.19 277.18 31.20 277.18 31.21 277.18 31.22 277.18 31.23 277.18 31.24 277.18 31.25 277.18 31.26 277.18 31.27 277.18 31.28 277.18 31.29 277.18 31.30 277.18 31.31 277.18 31.32 277.18 31.33 277.18 31.34 277.18 31.35 277.18 31.36 277.18 31.37 277.18 31.38 277.18 31.39 277.18 31.40 277.18 31.41 277.18 31.42 277.18 31.43 277.18 31.44 277.18 415.30 31.45 277.18 415.30 31.46 415.30 31.47 207.65 415.30 31.48 207.65 415.30 31.49 207.65 415.30 31.50 207.65 415.30 31.51 207.65 415.30 31.52 207.65 415.30 31.53 207.65 415.30 31.54 207.65 415.30 31.55 207.65 415.30 31.56 207.65 415.30 31.57 207.65 415.30 31.58 207.65 415.30 31.59 207.65 415.30 31.60 207.65 415.30 31.61 207.65 415.30 31.62 207.65 415.30 31.63 207.65 415.30 31.64 207.65 415.30 31.65 207.65 415.30 31.66 207.65 415.30 31.67 207.65 415.30 31.68 207.65 415.30 31.69 207.65 415.30 31.70 207.65 415.30 31.71 207.65 415.30 31.72 207.65 415.30 31.73 207.65 415.30 31.74 207.65 415.30 31.75 207.65 415.30 31.76 207.65 415.30 31.77 207.65 415.30 31.78 207.65 415.30 31.79 207.65 415.30 31.80 207.65 415.30 31.81 207.65 415.30 31.82 207.65 415.30 31.83 207.65 415.30 31.84 207.65 415.30 31.85 207.65 415.30 31.86 207.65 415.30 31.87 207.65 415.30 31.88 207.65 415.30 31.89 207.65 415.30 31.90 207.65 415.30 31.91 207.65 415.30 31.92 207.65 415.30 31.93 415.30 31.94 415.30 31.95 415.30 31.96 207.65 415.30 31.97 207.65 415.30 31.98 207.65 415.30 31.99 207.65 415.30 32.00 207.65 415.30 32.01 207.65 415.30 32.02 207.65 415.30 32.03 207.65 415.30 32.04 207.65 415.30 32.05 207.65 277.18 415.30 32.06 207.65 277.18 415.30 32.07 207.65 277.18 415.30 32.08 207.65 277.18 415.30 32.09 207.65 277.18 415.30 32.10 207.65 277.18 415.30 32.11 207.65 277.18 415.30 32.12 207.65 277.18 415.30 32.13 207.65 277.18 415.30 32.14 207.65 277.18 415.30 32.15 207.65 277.18 415.30 32.16 207.65 277.18 415.30 32.17 207.65 277.18 415.30 32.18 207.65 277.18 415.30 32.19 207.65 277.18 415.30 32.20 207.65 277.18 415.30 32.21 207.65 277.18 415.30 32.22 207.65 277.18 415.30 32.23 207.65 277.18 415.30 32.24 207.65 277.18 415.30 32.25 207.65 277.18 415.30 32.26 207.65 277.18 415.30 32.27 207.65 277.18 415.30 32.28 277.18 415.30 32.29 277.18 415.30 32.30 277.18 415.30 32.31 277.18 415.30 32.32 415.30 32.33 415.30 32.34 415.30 32.35 415.30 32.36 415.30 32.37 415.30 32.38 415.30 32.39 415.30 32.40 415.30 32.41 415.30 32.42 415.30 32.43 415.30 32.44 415.30 32.45 415.30 32.46 415.30 32.47 415.30 32.48 415.30 32.49 415.30 32.50 415.30 32.51 415.30 32.52 415.30 32.53 415.30 32.54 415.30 32.55 415.30 32.56 329.63 415.30 32.57 329.63 415.30 32.58 329.63 415.30 32.59 329.63 415.30 32.60 329.63 415.30 32.61 329.63 415.30 32.62 329.63 415.30 32.63 329.63 415.30 32.64 329.63 415.30 32.65 329.63 415.30 32.66 329.63 415.30 32.67 329.63 415.30 32.68 329.63 415.30 32.69 329.63 415.30 32.70 329.63 415.30 32.71 329.63 415.30 32.72 329.63 415.30 32.73 329.63 415.30 32.74 329.63 415.30 32.75 329.63 415.30 32.76 329.63 415.30 32.77 329.63 415.30 32.78 329.63 415.30 32.79 415.30 32.80 415.30 32.81 415.30 32.82 415.30 32.83 415.30 32.84 329.63 415.30 32.85 329.63 415.30 32.86 329.63 415.30 32.87 329.63 415.30 32.88 329.63 415.30 32.89 329.63 415.30 32.90 329.63 415.30 32.91 329.63 415.30 32.92 329.63 415.30 32.93 329.63 415.30 32.94 329.63 415.30 32.95 329.63 415.30 32.96 329.63 415.30 32.97 329.63 415.30 32.98 329.63 415.30 32.99 329.63 415.30 33.00 329.63 415.30 33.01 329.63 415.30 33.02 207.65 415.30 33.03 207.65 415.30 33.04 207.65 415.30 33.05 207.65 415.30 33.06 207.65 415.30 33.07 207.65 415.30 33.08 207.65 415.30 33.09 207.65 415.30 33.10 207.65 415.30 33.11 207.65 415.30 33.12 207.65 415.30 33.13 207.65 415.30 33.14 207.65 415.30 33.15 207.65 415.30 33.16 207.65 415.30 33.17 207.65 415.30 33.18 207.65 415.30 33.19 207.65 415.30 33.20 207.65 415.30 33.21 207.65 220.00 415.30 33.22 207.65 220.00 415.30 33.23 207.65 220.00 415.30 33.24 207.65 220.00 415.30 33.25 220.00 415.30 33.26 103.83 220.00 261.63 415.30 33.27 103.83 220.00 261.63 415.30 33.28 103.83 130.81 207.65 261.63 415.30 33.29 103.83 130.81 207.65 261.63 415.30 33.30 65.41 103.83 130.81 207.65 261.63 415.30 33.31 65.41 103.83 130.81 207.65 261.63 415.30 33.32 65.41 103.83 130.81 207.65 261.63 415.30 33.33 65.41 103.83 130.81 207.65 261.63 415.30 33.34 65.41 103.83 130.81 207.65 261.63 415.30 33.35 65.41 103.83 130.81 207.65 261.63 415.30 33.36 65.41 103.83 130.81 207.65 261.63 415.30 33.37 65.41 103.83 130.81 207.65 261.63 415.30 33.38 65.41 103.83 130.81 207.65 261.63 415.30 33.39 65.41 103.83 130.81 207.65 261.63 415.30 33.40 65.41 103.83 130.81 207.65 261.63 415.30 33.41 65.41 103.83 130.81 207.65 261.63 415.30 33.42 65.41 103.83 130.81 207.65 261.63 415.30 33.43 65.41 103.83 130.81 207.65 261.63 415.30 33.44 65.41 103.83 207.65 261.63 415.30 33.45 65.41 103.83 207.65 261.63 415.30 33.46 65.41 103.83 261.63 415.30 33.47 65.41 103.83 261.63 415.30 33.48 65.41 103.83 261.63 415.30 33.49 65.41 103.83 261.63 415.30 33.50 65.41 103.83 261.63 415.30 33.51 65.41 103.83 261.63 415.30 33.52 65.41 103.83 261.63 415.30 33.53 65.41 103.83 261.63 415.30 33.54 65.41 103.83 261.63 415.30 33.55 65.41 103.83 261.63 415.30 33.56 65.41 103.83 207.65 261.63 415.30 33.57 65.41 103.83 207.65 261.63 415.30 33.58 65.41 103.83 207.65 261.63 415.30 33.59 65.41 103.83 207.65 261.63 415.30 33.60 65.41 103.83 207.65 261.63 415.30 33.61 65.41 103.83 207.65 261.63 415.30 33.62 65.41 103.83 207.65 261.63 415.30 33.63 65.41 103.83 207.65 261.63 415.30 33.64 65.41 103.83 207.65 261.63 415.30 33.65 65.41 103.83 207.65 261.63 415.30 33.66 65.41 103.83 207.65 261.63 415.30 33.67 65.41 103.83 207.65 261.63 415.30 33.68 65.41 103.83 207.65 261.63 415.30 33.69 65.41 103.83 207.65 261.63 415.30 33.70 65.41 103.83 207.65 261.63 415.30 33.71 65.41 103.83 207.65 261.63 415.30 33.72 65.41 103.83 207.65 261.63 415.30 33.73 65.41 103.83 207.65 261.63 415.30 33.74 65.41 103.83 207.65 261.63 415.30 33.75 65.41 103.83 207.65 261.63 415.30 33.76 65.41 103.83 207.65 261.63 415.30 33.77 65.41 103.83 207.65 261.63 415.30 33.78 65.41 103.83 207.65 261.63 415.30 33.79 65.41 103.83 207.65 261.63 415.30 33.80 65.41 103.83 207.65 261.63 415.30 33.81 65.41 207.65 261.63 415.30 33.82 65.41 207.65 261.63 415.30 33.83 65.41 207.65 261.63 415.30 33.84 65.41 207.65 261.63 415.30 33.85 65.41 207.65 261.63 415.30 33.86 65.41 207.65 261.63 311.13 415.30 33.87 65.41 207.65 261.63 311.13 415.30 33.88 65.41 207.65 261.63 311.13 415.30 33.89 65.41 207.65 261.63 311.13 415.30 33.90 65.41 207.65 261.63 311.13 415.30 33.91 65.41 103.83 207.65 261.63 311.13 415.30 33.92 65.41 103.83 207.65 261.63 311.13 415.30 33.93 65.41 103.83 207.65 261.63 311.13 415.30 33.94 65.41 103.83 207.65 261.63 311.13 415.30 33.95 65.41 103.83 207.65 261.63 311.13 415.30 33.96 65.41 103.83 207.65 261.63 311.13 415.30 33.97 65.41 103.83 207.65 261.63 311.13 415.30 33.98 65.41 103.83 207.65 261.63 311.13 415.30 33.99 65.41 103.83 207.65 261.63 311.13 415.30 34.00 65.41 103.83 207.65 261.63 311.13 415.30 34.01 65.41 103.83 207.65 261.63 311.13 415.30 34.02 65.41 207.65 261.63 311.13 415.30 34.03 65.41 207.65 261.63 311.13 415.30 34.04 65.41 207.65 261.63 311.13 415.30 34.05 65.41 207.65 261.63 311.13 415.30 34.06 65.41 207.65 261.63 311.13 415.30 34.07 65.41 207.65 261.63 311.13 415.30 34.08 65.41 207.65 261.63 311.13 415.30 34.09 65.41 103.83 207.65 261.63 311.13 415.30 34.10 65.41 103.83 207.65 261.63 311.13 415.30 34.11 65.41 103.83 261.63 311.13 415.30 34.12 65.41 103.83 261.63 311.13 415.30 34.13 65.41 103.83 261.63 311.13 415.30 34.14 65.41 103.83 261.63 311.13 415.30 34.15 65.41 103.83 261.63 311.13 415.30 34.16 65.41 103.83 261.63 311.13 415.30 34.17 65.41 103.83 261.63 311.13 415.30 34.18 65.41 103.83 261.63 311.13 415.30 34.19 65.41 103.83 261.63 311.13 415.30 34.20 65.41 103.83 261.63 311.13 415.30 34.21 65.41 103.83 207.65 261.63 311.13 415.30 34.22 65.41 103.83 207.65 261.63 311.13 415.30 34.23 65.41 103.83 207.65 261.63 311.13 415.30 34.24 65.41 103.83 207.65 261.63 311.13 415.30 34.25 65.41 207.65 261.63 311.13 415.30 34.26 65.41 207.65 261.63 311.13 415.30 34.27 65.41 207.65 261.63 311.13 415.30 34.28 65.41 207.65 261.63 311.13 415.30 34.29 65.41 207.65 261.63 311.13 415.30 34.30 65.41 207.65 261.63 311.13 415.30 34.31 65.41 207.65 261.63 311.13 415.30 34.32 65.41 130.81 207.65 261.63 311.13 415.30 34.33 65.41 130.81 207.65 261.63 311.13 415.30 34.34 65.41 130.81 207.65 261.63 311.13 415.30 34.35 65.41 130.81 207.65 261.63 311.13 415.30 34.36 65.41 130.81 207.65 261.63 311.13 415.30 34.37 65.41 130.81 207.65 261.63 311.13 415.30 34.38 65.41 130.81 207.65 261.63 311.13 415.30 34.39 65.41 130.81 207.65 261.63 311.13 369.99 415.30 34.40 65.41 130.81 207.65 261.63 311.13 369.99 415.30 34.41 65.41 130.81 207.65 261.63 311.13 369.99 415.30 34.42 65.41 130.81 207.65 261.63 311.13 369.99 415.30 34.43 65.41 130.81 207.65 261.63 311.13 369.99 415.30 34.44 65.41 207.65 261.63 311.13 369.99 415.30 34.45 65.41 207.65 261.63 311.13 369.99 415.30 34.46 65.41 207.65 261.63 311.13 369.99 415.30 34.47 65.41 207.65 261.63 311.13 369.99 415.30 34.48 65.41 207.65 261.63 311.13 369.99 415.30 34.49 65.41 207.65 261.63 311.13 369.99 415.30 34.50 65.41 207.65 261.63 311.13 369.99 415.30 34.51 65.41 207.65 261.63 311.13 369.99 34.52 65.41 207.65 261.63 311.13 369.99 34.53 65.41 207.65 261.63 369.99 34.54 65.41 207.65 261.63 369.99 34.55 65.41 207.65 261.63 369.99 34.56 65.41 207.65 261.63 369.99 34.57 65.41 207.65 261.63 369.99 34.58 65.41 207.65 261.63 369.99 34.59 65.41 207.65 261.63 369.99 34.60 65.41 207.65 261.63 369.99 34.61 65.41 207.65 261.63 369.99 34.62 65.41 207.65 261.63 34.63 65.41 207.65 261.63 34.64 65.41 207.65 261.63 34.65 65.41 207.65 261.63 34.66 65.41 207.65 261.63 34.67 65.41 207.65 261.63 34.68 65.41 207.65 261.63 34.69 65.41 207.65 261.63 34.70 65.41 207.65 261.63 369.99 34.71 65.41 207.65 261.63 369.99 34.72 65.41 207.65 261.63 369.99 34.73 65.41 207.65 261.63 369.99 34.74 65.41 207.65 261.63 369.99 34.75 65.41 207.65 261.63 369.99 34.76 65.41 207.65 261.63 369.99 34.77 65.41 207.65 261.63 369.99 34.78 65.41 207.65 261.63 369.99 34.79 65.41 207.65 261.63 369.99 34.80 65.41 207.65 261.63 369.99 34.81 65.41 207.65 261.63 369.99 34.82 65.41 207.65 261.63 369.99 34.83 65.41 207.65 261.63 369.99 34.84 65.41 207.65 261.63 369.99 34.85 65.41 207.65 261.63 369.99 34.86 65.41 207.65 261.63 369.99 34.87 65.41 207.65 261.63 369.99 34.88 65.41 207.65 261.63 34.89 65.41 207.65 261.63 34.90 65.41 207.65 261.63 34.91 65.41 207.65 261.63 34.92 65.41 207.65 261.63 34.93 65.41 207.65 261.63 34.94 65.41 207.65 261.63 34.95 65.41 207.65 261.63 34.96 65.41 207.65 261.63 34.97 65.41 207.65 261.63 34.98 65.41 207.65 261.63 34.99 65.41 207.65 261.63 35.00 65.41 207.65 261.63 35.01 65.41 207.65 261.63 35.02 65.41 207.65 261.63 35.03 65.41 207.65 261.63 35.04 65.41 207.65 261.63 35.05 65.41 207.65 261.63 35.06 65.41 207.65 261.63 35.07 65.41 207.65 261.63 35.08 65.41 207.65 261.63 35.09 65.41 207.65 261.63 35.10 65.41 207.65 261.63 35.11 65.41 207.65 261.63 35.12 65.41 207.65 261.63 35.13 65.41 207.65 261.63 35.14 65.41 207.65 261.63 35.15 65.41 207.65 261.63 35.16 65.41 207.65 261.63 35.17 65.41 207.65 261.63 35.18 65.41 207.65 261.63 35.19 65.41 207.65 261.63 35.20 65.41 207.65 261.63 35.21 65.41 207.65 261.63 35.22 65.41 207.65 261.63 35.23 65.41 207.65 261.63 415.30 35.24 65.41 207.65 261.63 415.30 35.25 65.41 207.65 261.63 415.30 35.26 65.41 207.65 261.63 415.30 35.27 65.41 261.63 415.30 35.28 65.41 261.63 415.30 35.29 65.41 261.63 415.30 35.30 65.41 261.63 415.30 35.31 65.41 261.63 415.30 35.32 65.41 261.63 311.13 415.30 35.33 65.41 261.63 311.13 415.30 35.34 65.41 261.63 311.13 415.30 35.35 65.41 261.63 311.13 415.30 35.36 65.41 261.63 311.13 415.30 35.37 65.41 261.63 311.13 35.38 65.41 261.63 311.13 35.39 130.81 261.63 311.13 35.40 130.81 261.63 311.13 35.41 130.81 261.63 311.13 35.42 130.81 261.63 311.13 35.43 130.81 261.63 311.13 35.44 261.63 311.13 35.45 261.63 311.13 35.46 261.63 311.13 35.47 261.63 311.13 35.48 261.63 311.13 35.49 261.63 311.13 35.50 261.63 311.13 35.51 261.63 311.13 35.52 261.63 311.13 35.53 261.63 311.13 35.54 261.63 311.13 35.55 261.63 311.13 35.56 261.63 311.13 35.57 261.63 311.13 35.58 261.63 311.13 35.59 261.63 311.13 35.60 261.63 311.13 35.61 261.63 311.13 35.62 261.63 311.13 35.63 261.63 311.13 35.64 261.63 311.13 35.65 261.63 311.13 35.66 261.63 311.13 35.67 261.63 311.13 35.68 261.63 311.13 35.69 261.63 311.13 35.70 261.63 311.13 35.71 261.63 311.13 35.72 261.63 311.13 35.73 261.63 311.13 35.74 261.63 311.13 35.75 261.63 311.13 35.76 261.63 311.13 35.77 261.63 311.13 35.78 261.63 311.13 35.79 261.63 311.13 35.80 261.63 311.13 35.81 261.63 311.13 35.82 261.63 311.13 35.83 261.63 311.13 369.99 35.84 261.63 311.13 369.99 35.85 261.63 311.13 369.99 35.86 261.63 311.13 369.99 35.87 261.63 311.13 369.99 35.88 261.63 311.13 369.99 35.89 261.63 311.13 369.99 35.90 261.63 311.13 369.99 35.91 261.63 311.13 369.99 35.92 261.63 311.13 369.99 35.93 261.63 311.13 369.99 35.94 261.63 311.13 369.99 35.95 261.63 311.13 369.99 35.96 261.63 311.13 369.99 35.97 261.63 311.13 369.99 35.98 261.63 311.13 369.99 35.99 261.63 369.99 36.00 261.63 369.99 36.01 261.63 369.99 36.02 261.63 369.99 36.03 261.63 369.99 36.04 261.63 369.99 36.05 261.63 369.99 36.06 261.63 36.07 261.63 36.08 261.63 36.09 261.63 36.10 261.63 36.11 261.63 369.99 36.12 261.63 369.99 36.13 261.63 369.99 36.14 261.63 369.99 415.30 36.15 261.63 369.99 415.30 36.16 261.63 369.99 415.30 36.17 261.63 369.99 415.30 36.18 261.63 369.99 415.30 36.19 261.63 369.99 415.30 36.20 261.63 369.99 415.30 36.21 261.63 369.99 415.30 36.22 261.63 369.99 415.30 36.23 261.63 369.99 415.30 36.24 261.63 369.99 415.30 36.25 261.63 369.99 415.30 36.26 261.63 369.99 415.30 36.27 207.65 261.63 369.99 415.30 36.28 207.65 261.63 369.99 415.30 36.29 207.65 36.30 207.65 36.31 207.65 36.32 207.65 36.33 207.65 36.34 207.65 36.35 207.65 36.36 207.65 36.37 207.65 36.38 207.65 36.39 207.65 36.40 207.65 36.41 207.65 36.42 207.65 36.43 207.65 36.44 207.65 36.45 207.65 36.46 207.65 36.47 207.65 36.48 207.65 36.49 207.65 36.50 207.65 36.51 207.65 36.52 207.65 36.53 207.65 36.54 207.65 36.55 207.65 36.56 207.65 36.57 207.65 36.58 207.65 36.59 207.65 36.60 207.65 36.61 207.65 36.62 207.65 36.63 207.65 36.64 207.65 36.65 207.65 415.30 36.66 207.65 415.30 36.67 207.65 415.30 36.68 207.65 415.30 36.69 207.65 415.30 36.70 207.65 415.30 36.71 207.65 415.30 36.72 207.65 415.30 36.73 207.65 415.30 36.74 311.13 415.30 36.75 311.13 415.30 36.76 311.13 415.30 36.77 311.13 415.30 36.78 311.13 415.30 36.79 311.13 415.30 36.80 311.13 415.30 36.81 311.13 415.30 36.82 311.13 415.30 36.83 311.13 415.30 36.84 311.13 415.30 36.85 311.13 415.30 36.86 311.13 415.30 36.87 311.13 415.30 36.88 311.13 415.30 36.89 311.13 415.30 36.90 311.13 415.30 36.91 311.13 415.30 36.92 311.13 415.30 36.93 311.13 415.30 36.94 311.13 415.30 36.95 311.13 415.30 36.96 311.13 415.30 36.97 311.13 36.98 311.13 36.99 311.13 37.00 311.13 37.01 311.13 37.02 311.13 37.03 311.13 37.04 311.13 37.05 311.13 37.06 311.13 37.07 311.13 37.08 311.13 37.09 311.13 37.10 311.13 37.11 311.13 37.12 311.13 37.13 311.13 37.14 311.13 37.15 311.13 37.16 311.13 37.17 311.13 37.18 311.13 37.19 311.13 37.20 311.13 37.21 311.13 37.22 311.13 37.23 311.13 37.24 311.13 37.25 311.13 369.99 37.26 311.13 369.99 37.27 311.13 369.99 37.28 311.13 369.99 37.29 311.13 369.99 37.30 311.13 369.99 37.31 311.13 369.99 37.32 311.13 369.99 37.33 311.13 369.99 37.34 311.13 369.99 37.35 311.13 369.99 37.36 311.13 369.99 37.37 311.13 369.99 37.38 311.13 369.99 37.39 311.13 369.99 37.40 311.13 369.99 37.41 311.13 369.99 37.42 311.13 369.99 37.43 311.13 369.99 37.44 311.13 369.99 37.45 311.13 369.99 37.46 65.41 311.13 369.99 37.47 65.41 311.13 369.99 37.48 65.41 311.13 369.99 37.49 65.41 311.13 369.99 37.50 65.41 311.13 37.51 65.41 311.13 37.52 65.41 311.13 37.53 65.41 311.13 37.54 65.41 311.13 37.55 65.41 311.13 37.56 65.41 311.13 37.57 65.41 311.13 369.99 415.30 37.58 65.41 311.13 369.99 415.30 37.59 65.41 369.99 415.30 37.60 65.41 369.99 415.30 37.61 65.41 369.99 415.30 37.62 65.41 369.99 37.63 65.41 369.99 37.64 65.41 369.99 37.65 65.41 369.99 37.66 65.41 369.99 37.67 65.41 369.99 37.68 65.41 369.99 37.69 369.99 415.30 37.70 369.99 415.30 37.71 369.99 415.30 37.72 369.99 415.30 37.73 415.30 37.74 415.30 37.75 415.30 37.76 415.30 37.77 415.30 37.78 207.65 415.30 37.79 207.65 415.30 37.80 207.65 415.30 37.81 207.65 415.30 37.82 207.65 415.30 37.83 207.65 415.30 37.84 207.65 415.30 37.85 207.65 415.30 37.86 207.65 415.30 37.87 207.65 415.30 37.88 207.65 415.30 37.89 207.65 415.30 37.90 207.65 415.30 37.91 207.65 415.30 37.92 207.65 415.30 37.93 207.65 415.30 37.94 207.65 415.30 37.95 207.65 415.30 37.96 207.65 415.30 37.97 207.65 415.30 37.98 207.65 415.30 37.99 207.65 415.30 38.00 207.65 415.30 38.01 207.65 415.30 38.02 207.65 415.30 38.03 207.65 415.30 38.04 207.65 415.30 38.05 207.65 415.30 38.06 207.65 415.30 38.07 207.65 415.30 38.08 207.65 415.30 38.09 207.65 415.30 38.10 207.65 415.30 38.11 207.65 415.30 38.12 207.65 415.30 38.13 207.65 415.30 38.14 207.65 415.30 38.15 207.65 415.30 38.16 207.65 415.30 38.17 207.65 415.30 38.18 207.65 415.30 38.19 207.65 415.30 38.20 207.65 415.30 38.21 207.65 415.30 38.22 415.30 38.23 415.30 38.24 415.30 38.25 415.30 38.26 415.30 38.27 311.13 415.30 38.28 311.13 415.30 38.29 311.13 415.30 38.30 311.13 415.30 38.31 311.13 415.30 38.32 311.13 415.30 38.33 311.13 415.30 38.34 207.65 311.13 415.30 38.35 207.65 311.13 415.30 38.36 207.65 311.13 415.30 38.37 207.65 311.13 415.30 38.38 207.65 311.13 415.30 38.39 207.65 311.13 415.30 38.40 207.65 311.13 415.30 38.41 207.65 311.13 415.30 38.42 207.65 311.13 415.30 38.43 207.65 311.13 415.30 38.44 207.65 311.13 415.30 38.45 207.65 311.13 415.30 38.46 207.65 311.13 415.30 38.47 207.65 311.13 415.30 38.48 207.65 311.13 415.30 38.49 207.65 311.13 415.30 38.50 207.65 311.13 415.30 38.51 207.65 311.13 415.30 38.52 311.13 415.30 38.53 311.13 415.30 38.54 311.13 415.30 38.55 311.13 415.30 38.56 311.13 415.30 38.57 311.13 415.30 38.58 311.13 415.30 38.59 311.13 415.30 38.60 311.13 415.30 38.61 311.13 415.30 38.62 311.13 415.30 38.63 311.13 415.30 38.64 311.13 415.30 38.65 311.13 415.30 38.66 311.13 415.30 38.67 311.13 415.30 38.68 311.13 415.30 38.69 311.13 415.30 38.70 311.13 415.30 38.71 311.13 415.30 38.72 311.13 415.30 38.73 311.13 415.30 38.74 311.13 369.99 415.30 38.75 311.13 369.99 415.30 38.76 311.13 369.99 415.30 38.77 311.13 369.99 415.30 38.78 311.13 369.99 415.30 38.79 311.13 369.99 415.30 38.80 311.13 369.99 415.30 38.81 311.13 369.99 415.30 38.82 311.13 369.99 415.30 38.83 311.13 369.99 415.30 38.84 311.13 369.99 415.30 38.85 311.13 369.99 415.30 38.86 311.13 369.99 415.30 38.87 311.13 369.99 415.30 38.88 311.13 369.99 415.30 38.89 311.13 369.99 415.30 38.90 311.13 369.99 415.30 38.91 311.13 369.99 415.30 38.92 369.99 415.30 38.93 369.99 415.30 38.94 369.99 415.30 38.95 369.99 415.30 38.96 369.99 415.30 38.97 369.99 415.30 38.98 369.99 415.30 38.99 369.99 415.30 39.00 369.99 415.30 39.01 369.99 415.30 39.02 369.99 415.30 39.03 415.30 39.04 415.30 39.05 415.30 39.06 369.99 415.30 39.07 369.99 415.30 39.08 369.99 415.30 39.09 369.99 415.30 39.10 369.99 415.30 39.11 369.99 415.30 39.12 369.99 415.30 39.13 369.99 415.30 39.14 369.99 415.30 39.15 369.99 415.30 39.16 369.99 415.30 39.17 369.99 415.30 39.18 369.99 415.30 39.19 369.99 415.30 39.20 369.99 415.30 39.21 369.99 415.30 39.22 369.99 415.30 39.23 369.99 415.30 39.24 369.99 415.30 39.25 369.99 415.30 39.26 369.99 415.30 39.27 369.99 415.30 39.28 369.99 415.30 39.29 369.99 415.30 39.30 369.99 415.30 39.31 369.99 415.30 39.32 369.99 415.30 39.33 369.99 415.30 39.34 369.99 415.30 39.35 369.99 415.30 39.36 415.30 39.37 415.30 39.38 415.30 39.39 415.30 39.40 415.30 39.41 415.30 39.42 415.30 39.43 415.30 39.44 415.30 39.45 415.30 39.46 415.30 39.47 415.30 39.48 69.30 415.30 39.49 69.30 415.30 39.50 69.30 138.59 207.65 415.30 39.51 69.30 138.59 207.65 415.30 39.52 69.30 138.59 207.65 415.30 39.53 69.30 138.59 207.65 415.30 39.54 69.30 138.59 207.65 415.30 39.55 69.30 138.59 207.65 415.30 39.56 69.30 138.59 207.65 415.30 39.57 69.30 138.59 207.65 415.30 39.58 69.30 138.59 207.65 415.30 39.59 69.30 138.59 207.65 415.30 39.60 69.30 138.59 207.65 415.30 39.61 69.30 138.59 207.65 415.30 39.62 69.30 138.59 207.65 415.30 39.63 69.30 138.59 207.65 415.30 39.64 69.30 138.59 207.65 415.30 39.65 69.30 138.59 207.65 415.30 39.66 69.30 138.59 207.65 415.30 39.67 69.30 138.59 207.65 415.30 39.68 69.30 138.59 207.65 415.30 39.69 69.30 138.59 207.65 415.30 39.70 69.30 138.59 207.65 415.30 39.71 69.30 138.59 207.65 415.30 39.72 69.30 138.59 207.65 415.30 39.73 69.30 138.59 207.65 415.30 39.74 69.30 138.59 207.65 415.30 39.75 69.30 138.59 415.30 39.76 69.30 138.59 415.30 39.77 69.30 138.59 415.30 39.78 69.30 138.59 415.30 39.79 69.30 138.59 415.30 39.80 69.30 415.30 39.81 69.30 415.30 39.82 69.30 415.30 39.83 69.30 415.30 39.84 69.30 415.30 39.85 69.30 415.30 39.86 69.30 415.30 39.87 69.30 277.18 415.30 39.88 69.30 277.18 415.30 39.89 69.30 277.18 415.30 39.90 69.30 277.18 415.30 39.91 69.30 277.18 415.30 39.92 69.30 277.18 415.30 39.93 69.30 277.18 415.30 39.94 69.30 415.30 39.95 69.30 415.30 39.96 69.30 415.30 39.97 69.30 415.30 39.98 69.30 415.30 39.99 69.30 415.30 40.00 69.30 415.30 40.01 69.30 415.30 40.02 69.30 415.30 40.03 69.30 415.30 40.04 69.30 138.59 415.30 40.05 69.30 138.59 415.30 40.06 69.30 138.59 415.30 40.07 69.30 138.59 415.30 40.08 69.30 138.59 415.30 40.09 69.30 138.59 415.30 40.10 69.30 138.59 415.30 40.11 69.30 138.59 415.30 40.12 69.30 138.59 415.30 40.13 69.30 138.59 415.30 40.14 69.30 138.59 415.30 40.15 69.30 138.59 415.30 40.16 69.30 138.59 415.30 40.17 69.30 138.59 415.30 40.18 69.30 138.59 277.18 415.30 40.19 69.30 138.59 277.18 415.30 40.20 69.30 138.59 277.18 415.30 40.21 69.30 138.59 277.18 415.30 40.22 69.30 138.59 277.18 415.30 40.23 69.30 138.59 277.18 415.30 40.24 69.30 138.59 277.18 415.30 40.25 69.30 138.59 277.18 415.30 40.26 69.30 138.59 277.18 415.30 40.27 69.30 138.59 277.18 415.30 40.28 69.30 138.59 277.18 415.30 40.29 69.30 277.18 415.30 40.30 69.30 277.18 415.30 40.31 69.30 277.18 415.30 40.32 69.30 277.18 415.30 40.33 69.30 277.18 415.30 40.34 69.30 277.18 415.30 40.35 69.30 277.18 415.30 40.36 69.30 277.18 415.30 40.37 69.30 277.18 415.30 40.38 69.30 277.18 415.30 40.39 69.30 277.18 415.30 40.40 69.30 277.18 415.30 40.41 69.30 277.18 415.30 40.42 69.30 277.18 415.30 40.43 69.30 277.18 415.30 40.44 69.30 277.18 415.30 40.45 69.30 277.18 415.30 40.46 69.30 277.18 415.30 40.47 69.30 277.18 415.30 40.48 69.30 277.18 415.30 40.49 69.30 277.18 415.30 40.50 69.30 277.18 415.30 40.51 69.30 277.18 415.30 40.52 69.30 277.18 415.30 40.53 69.30 277.18 415.30 40.54 69.30 277.18 415.30 40.55 69.30 277.18 415.30 40.56 69.30 277.18 415.30 40.57 69.30 277.18 415.30 40.58 69.30 277.18 415.30 40.59 69.30 277.18 329.63 415.30 40.60 69.30 277.18 329.63 415.30 40.61 69.30 277.18 329.63 415.30 40.62 69.30 277.18 329.63 415.30 40.63 69.30 277.18 329.63 415.30 40.64 69.30 277.18 329.63 415.30 40.65 69.30 277.18 329.63 415.30 40.66 69.30 277.18 329.63 415.30 40.67 69.30 277.18 329.63 415.30 40.68 69.30 277.18 329.63 415.30 40.69 69.30 277.18 329.63 415.30 40.70 69.30 277.18 329.63 415.30 40.71 69.30 277.18 329.63 415.30 40.72 69.30 277.18 329.63 415.30 40.73 69.30 277.18 329.63 415.30 40.74 69.30 277.18 329.63 415.30 40.75 69.30 277.18 329.63 415.30 40.76 69.30 277.18 329.63 415.30 40.77 69.30 277.18 329.63 415.30 40.78 69.30 277.18 329.63 415.30 40.79 69.30 277.18 329.63 415.30 40.80 69.30 277.18 329.63 415.30 40.81 69.30 277.18 329.63 415.30 40.82 69.30 277.18 329.63 415.30 40.83 69.30 277.18 329.63 415.30 40.84 69.30 277.18 329.63 415.30 40.85 277.18 329.63 415.30 40.86 277.18 329.63 415.30 40.87 277.18 329.63 415.30 40.88 277.18 329.63 415.30 40.89 277.18 329.63 415.30 40.90 277.18 329.63 415.30 40.91 277.18 329.63 415.30 40.92 69.30 277.18 329.63 415.30 40.93 69.30 277.18 329.63 415.30 40.94 69.30 277.18 329.63 415.30 40.95 69.30 277.18 329.63 415.30 40.96 69.30 277.18 329.63 415.30 40.97 69.30 277.18 329.63 415.30 40.98 69.30 277.18 329.63 415.30 40.99 69.30 277.18 329.63 415.30 41.00 69.30 277.18 329.63 415.30 41.01 277.18 329.63 415.30 41.02 277.18 329.63 415.30 41.03 207.65 277.18 329.63 415.30 41.04 207.65 277.18 329.63 415.30 41.05 207.65 277.18 415.30 41.06 207.65 277.18 415.30 41.07 207.65 277.18 415.30 41.08 207.65 277.18 41.09 207.65 277.18 41.10 207.65 277.18 41.11 207.65 277.18 41.12 207.65 277.18 41.13 207.65 277.18 41.14 207.65 277.18 41.15 207.65 277.18 41.16 207.65 277.18 41.17 207.65 277.18 41.18 207.65 277.18 41.19 207.65 277.18 41.20 207.65 277.18 41.21 207.65 277.18 41.22 207.65 277.18 41.23 207.65 277.18 41.24 207.65 277.18 41.25 207.65 277.18 41.26 207.65 277.18 41.27 207.65 277.18 41.28 207.65 277.18 41.29 207.65 277.18 41.30 207.65 277.18 41.31 207.65 277.18 41.32 207.65 277.18 41.33 207.65 277.18 41.34 207.65 277.18 41.35 207.65 277.18 41.36 207.65 277.18 41.37 207.65 277.18 41.38 207.65 277.18 41.39 207.65 277.18 41.40 207.65 277.18 41.41 207.65 277.18 41.42 207.65 277.18 41.43 207.65 277.18 41.44 207.65 277.18 41.45 207.65 277.18 41.46 207.65 277.18 41.47 207.65 277.18 41.48 207.65 277.18 41.49 207.65 277.18 41.50 207.65 277.18 41.51 207.65 277.18 41.52 207.65 277.18 41.53 207.65 277.18 41.54 207.65 277.18 41.55 207.65 277.18 41.56 207.65 277.18 41.57 207.65 277.18 41.58 207.65 277.18 41.59 207.65 277.18 41.60 207.65 277.18 41.61 207.65 277.18 41.62 207.65 277.18 41.63 207.65 277.18 41.64 207.65 277.18 41.65 207.65 277.18 41.66 277.18 41.67 277.18 41.68 277.18 41.69 277.18 41.70 277.18 41.71 277.18 41.72 277.18 41.73 277.18 41.74 277.18 41.75 207.65 277.18 41.76 207.65 277.18 41.77 207.65 277.18 41.78 207.65 277.18 41.79 207.65 277.18 41.80 207.65 277.18 41.81 207.65 277.18 41.82 207.65 277.18 41.83 207.65 277.18 41.84 207.65 277.18 41.85 207.65 277.18 41.86 207.65 277.18 41.87 207.65 277.18 41.88 207.65 277.18 41.89 207.65 277.18 41.90 207.65 277.18 41.91 207.65 277.18 41.92 207.65 277.18 41.93 207.65 277.18 41.94 207.65 277.18 41.95 207.65 277.18 41.96 207.65 277.18 41.97 207.65 277.18 41.98 207.65 277.18 41.99 207.65 277.18 42.00 207.65 277.18 42.01 207.65 277.18 329.63 42.02 207.65 277.18 329.63 42.03 207.65 277.18 329.63 42.04 207.65 277.18 329.63 42.05 207.65 277.18 329.63 42.06 207.65 277.18 329.63 42.07 207.65 277.18 329.63 42.08 207.65 277.18 329.63 42.09 207.65 277.18 329.63 42.10 207.65 277.18 329.63 42.11 207.65 277.18 329.63 42.12 207.65 277.18 329.63 42.13 207.65 277.18 329.63 42.14 207.65 277.18 329.63 42.15 207.65 277.18 329.63 42.16 207.65 277.18 329.63 42.17 207.65 277.18 329.63 42.18 207.65 277.18 329.63 42.19 207.65 277.18 329.63 42.20 207.65 277.18 329.63 42.21 207.65 277.18 329.63 42.22 207.65 277.18 329.63 42.23 207.65 277.18 329.63 42.24 207.65 277.18 329.63 42.25 207.65 277.18 329.63 42.26 207.65 277.18 329.63 42.27 207.65 277.18 329.63 42.28 207.65 277.18 329.63 42.29 207.65 277.18 329.63 42.30 207.65 277.18 329.63 42.31 207.65 277.18 329.63 42.32 207.65 277.18 329.63 42.33 207.65 277.18 329.63 42.34 207.65 277.18 329.63 42.35 207.65 277.18 329.63 42.36 207.65 277.18 329.63 42.37 207.65 277.18 329.63 42.38 207.65 277.18 329.63 42.39 207.65 277.18 329.63 42.40 207.65 277.18 329.63 42.41 207.65 277.18 329.63 42.42 207.65 277.18 329.63 42.43 207.65 277.18 329.63 42.44 207.65 277.18 329.63 42.45 207.65 277.18 329.63 42.46 207.65 277.18 329.63 42.47 207.65 277.18 329.63 42.48 207.65 277.18 329.63 42.49 207.65 277.18 329.63 42.50 207.65 277.18 329.63 42.51 207.65 277.18 329.63 42.52 207.65 277.18 329.63 440.00 42.53 207.65 277.18 329.63 440.00 42.54 207.65 277.18 329.63 440.00 42.55 207.65 277.18 329.63 440.00 42.56 207.65 440.00 42.57 207.65 440.00 42.58 207.65 440.00 42.59 207.65 329.63 440.00 42.60 207.65 329.63 440.00 42.61 207.65 220.00 329.63 440.00 42.62 207.65 220.00 329.63 440.00 42.63 207.65 220.00 329.63 440.00 42.64 207.65 220.00 329.63 440.00 42.65 207.65 220.00 329.63 440.00 42.66 92.50 220.00 329.63 440.00 42.67 92.50 220.00 329.63 440.00 42.68 92.50 220.00 440.00 42.69 92.50 220.00 440.00 42.70 92.50 220.00 440.00 42.71 92.50 220.00 329.63 440.00 42.72 92.50 220.00 329.63 440.00 42.73 46.25 92.50 220.00 329.63 440.00 42.74 46.25 92.50 220.00 329.63 440.00 42.75 46.25 92.50 220.00 329.63 440.00 42.76 46.25 92.50 220.00 329.63 440.00 42.77 46.25 92.50 220.00 329.63 440.00 42.78 46.25 92.50 220.00 329.63 440.00 42.79 46.25 92.50 220.00 329.63 440.00 42.80 46.25 92.50 220.00 440.00 42.81 46.25 92.50 220.00 440.00 42.82 46.25 92.50 220.00 440.00 42.83 46.25 92.50 220.00 440.00 42.84 46.25 92.50 220.00 440.00 42.85 46.25 92.50 220.00 440.00 42.86 46.25 92.50 220.00 440.00 42.87 46.25 92.50 220.00 440.00 42.88 46.25 92.50 220.00 440.00 42.89 46.25 92.50 220.00 440.00 42.90 46.25 92.50 220.00 440.00 42.91 46.25 220.00 440.00 42.92 46.25 220.00 440.00 42.93 46.25 220.00 440.00 42.94 46.25 220.00 440.00 42.95 46.25 220.00 440.00 42.96 46.25 220.00 440.00 42.97 46.25 220.00 440.00 42.98 46.25 220.00 440.00 42.99 46.25 220.00 440.00 43.00 46.25 220.00 440.00 43.01 46.25 92.50 220.00 440.00 43.02 46.25 92.50 220.00 440.00 43.03 46.25 92.50 220.00 440.00 43.04 46.25 92.50 220.00 440.00 43.05 46.25 92.50 220.00 440.00 43.06 46.25 92.50 220.00 440.00 43.07 46.25 92.50 220.00 440.00 43.08 46.25 92.50 220.00 440.00 43.09 46.25 92.50 220.00 440.00 43.10 46.25 92.50 220.00 440.00 43.11 46.25 92.50 220.00 440.00 43.12 46.25 92.50 220.00 440.00 43.13 46.25 92.50 220.00 440.00 43.14 46.25 92.50 220.00 440.00 43.15 46.25 92.50 220.00 440.00 43.16 46.25 92.50 220.00 440.00 43.17 46.25 92.50 220.00 277.18 440.00 43.18 46.25 92.50 220.00 277.18 440.00 43.19 46.25 92.50 220.00 277.18 440.00 43.20 46.25 92.50 220.00 277.18 440.00 43.21 46.25 92.50 220.00 277.18 440.00 43.22 46.25 92.50 220.00 277.18 440.00 43.23 46.25 92.50 220.00 277.18 440.00 43.24 46.25 92.50 220.00 277.18 440.00 43.25 46.25 92.50 220.00 277.18 440.00 43.26 46.25 92.50 220.00 277.18 440.00 43.27 46.25 92.50 220.00 277.18 440.00 43.28 46.25 92.50 220.00 277.18 440.00 43.29 46.25 92.50 220.00 277.18 440.00 43.30 46.25 92.50 220.00 277.18 440.00 43.31 46.25 92.50 220.00 277.18 440.00 43.32 46.25 92.50 220.00 277.18 440.00 43.33 46.25 92.50 220.00 277.18 440.00 43.34 46.25 92.50 220.00 277.18 440.00 43.35 46.25 92.50 220.00 277.18 440.00 43.36 46.25 92.50 220.00 277.18 440.00 43.37 46.25 92.50 220.00 277.18 440.00 43.38 46.25 92.50 220.00 277.18 440.00 43.39 46.25 92.50 220.00 277.18 440.00 43.40 46.25 92.50 220.00 277.18 440.00 43.41 46.25 92.50 220.00 277.18 440.00 43.42 46.25 92.50 220.00 440.00 43.43 46.25 92.50 220.00 440.00 43.44 46.25 92.50 220.00 440.00 43.45 46.25 92.50 220.00 440.00 43.46 46.25 92.50 220.00 440.00 43.47 46.25 92.50 440.00 43.48 46.25 92.50 440.00 43.49 46.25 92.50 440.00 43.50 46.25 92.50 440.00 43.51 46.25 92.50 440.00 43.52 46.25 92.50 440.00 43.53 46.25 92.50 440.00 43.54 46.25 92.50 440.00 43.55 46.25 92.50 440.00 43.56 46.25 92.50 440.00 43.57 46.25 92.50 440.00 43.58 46.25 92.50 440.00 43.59 46.25 92.50 440.00 43.60 46.25 92.50 440.00 43.61 46.25 92.50 440.00 43.62 46.25 92.50 440.00 43.63 46.25 92.50 440.00 43.64 46.25 92.50 369.99 440.00 43.65 46.25 92.50 369.99 440.00 43.66 46.25 92.50 369.99 440.00 43.67 46.25 92.50 369.99 440.00 43.68 46.25 92.50 369.99 440.00 43.69 46.25 92.50 369.99 440.00 43.70 46.25 92.50 369.99 440.00 43.71 46.25 92.50 369.99 440.00 43.72 46.25 92.50 369.99 440.00 43.73 46.25 92.50 369.99 440.00 43.74 46.25 92.50 369.99 440.00 43.75 46.25 92.50 369.99 440.00 43.76 46.25 92.50 369.99 440.00 43.77 46.25 92.50 369.99 440.00 43.78 46.25 92.50 369.99 440.00 43.79 46.25 92.50 369.99 440.00 43.80 46.25 92.50 369.99 440.00 43.81 46.25 92.50 369.99 440.00 43.82 46.25 92.50 369.99 440.00 43.83 46.25 92.50 369.99 440.00 43.84 46.25 92.50 277.18 369.99 440.00 43.85 46.25 92.50 277.18 369.99 440.00 43.86 46.25 92.50 277.18 369.99 440.00 43.87 46.25 92.50 277.18 369.99 440.00 43.88 46.25 92.50 277.18 369.99 440.00 43.89 46.25 92.50 277.18 369.99 440.00 43.90 46.25 92.50 277.18 369.99 440.00 43.91 46.25 92.50 277.18 369.99 440.00 43.92 46.25 92.50 277.18 369.99 440.00 43.93 46.25 92.50 277.18 369.99 440.00 43.94 46.25 92.50 277.18 369.99 440.00 43.95 46.25 92.50 277.18 369.99 440.00 43.96 46.25 92.50 277.18 369.99 440.00 43.97 46.25 92.50 277.18 369.99 440.00 43.98 46.25 92.50 277.18 369.99 440.00 43.99 46.25 92.50 277.18 369.99 440.00 44.00 46.25 92.50 277.18 369.99 440.00 44.01 46.25 92.50 277.18 369.99 440.00 44.02 46.25 92.50 277.18 369.99 440.00 44.03 46.25 92.50 277.18 369.99 440.00 44.04 46.25 92.50 277.18 369.99 440.00 44.05 92.50 277.18 369.99 440.00 44.06 92.50 277.18 369.99 440.00 44.07 92.50 277.18 369.99 440.00 44.08 92.50 220.00 277.18 369.99 440.00 44.09 92.50 220.00 277.18 369.99 440.00 44.10 92.50 220.00 277.18 369.99 44.11 92.50 220.00 277.18 369.99 44.12 92.50 220.00 277.18 369.99 44.13 92.50 220.00 277.18 369.99 44.14 92.50 220.00 277.18 369.99 44.15 92.50 220.00 277.18 369.99 44.16 92.50 220.00 277.18 369.99 44.17 92.50 220.00 369.99 44.18 92.50 220.00 369.99 44.19 92.50 220.00 44.20 92.50 220.00 44.21 92.50 220.00 44.22 92.50 220.00 44.23 92.50 220.00 44.24 92.50 220.00 44.25 92.50 220.00 44.26 92.50 220.00 44.27 92.50 220.00 44.28 92.50 220.00 44.29 92.50 220.00 44.30 92.50 220.00 44.31 92.50 220.00 44.32 92.50 220.00 44.33 92.50 220.00 44.34 92.50 220.00 44.35 220.00 44.36 220.00 44.37 220.00 44.38 220.00 44.39 220.00 44.40 220.00 44.41 220.00 44.42 92.50 220.00 44.43 92.50 220.00 44.44 92.50 220.00 44.45 92.50 220.00 44.46 92.50 220.00 44.47 92.50 220.00 44.48 92.50 220.00 44.49 92.50 220.00 44.50 92.50 220.00 44.51 220.00 44.52 220.00 44.53 220.00 44.54 220.00 44.55 220.00 44.56 92.50 220.00 44.57 92.50 220.00 44.58 92.50 220.00 44.59 92.50 220.00 44.60 92.50 220.00 44.61 92.50 220.00 277.18 44.62 92.50 220.00 277.18 44.63 92.50 220.00 277.18 44.64 92.50 220.00 277.18 44.65 92.50 220.00 277.18 44.66 92.50 220.00 277.18 44.67 92.50 220.00 277.18 44.68 92.50 220.00 277.18 44.69 92.50 220.00 277.18 44.70 92.50 220.00 277.18 44.71 92.50 220.00 277.18 44.72 92.50 220.00 277.18 44.73 92.50 220.00 277.18 44.74 92.50 220.00 277.18 44.75 92.50 220.00 277.18 44.76 92.50 220.00 277.18 44.77 92.50 220.00 277.18 44.78 92.50 220.00 277.18 44.79 92.50 220.00 277.18 44.80 92.50 220.00 277.18 44.81 92.50 220.00 277.18 44.82 92.50 220.00 277.18 44.83 92.50 220.00 277.18 44.84 92.50 220.00 277.18 44.85 92.50 220.00 277.18 44.86 92.50 220.00 277.18 44.87 92.50 220.00 277.18 44.88 92.50 220.00 277.18 44.89 92.50 220.00 277.18 44.90 92.50 220.00 277.18 44.91 92.50 220.00 277.18 44.92 92.50 220.00 277.18 44.93 92.50 220.00 277.18 44.94 92.50 220.00 277.18 44.95 92.50 220.00 277.18 44.96 92.50 220.00 277.18 44.97 92.50 220.00 277.18 44.98 92.50 220.00 277.18 44.99 92.50 220.00 277.18 45.00 92.50 220.00 277.18 45.01 92.50 220.00 277.18 45.02 92.50 220.00 277.18 45.03 92.50 220.00 277.18 45.04 92.50 220.00 277.18 45.05 92.50 220.00 277.18 45.06 92.50 220.00 277.18 45.07 92.50 220.00 277.18 45.08 92.50 220.00 277.18 45.09 92.50 220.00 277.18 45.10 92.50 220.00 277.18 369.99 45.11 92.50 220.00 277.18 369.99 45.12 92.50 220.00 369.99 45.13 92.50 220.00 369.99 45.14 92.50 220.00 369.99 45.15 92.50 220.00 369.99 45.16 92.50 220.00 369.99 45.17 92.50 220.00 369.99 45.18 92.50 220.00 369.99 45.19 92.50 220.00 369.99 45.20 92.50 220.00 369.99 45.21 92.50 220.00 369.99 45.22 92.50 220.00 369.99 45.23 92.50 220.00 369.99 45.24 92.50 220.00 369.99 45.25 92.50 220.00 369.99 45.26 92.50 220.00 369.99 45.27 92.50 220.00 369.99 45.28 92.50 220.00 369.99 45.29 92.50 220.00 369.99 45.30 92.50 220.00 45.31 92.50 220.00 45.32 92.50 220.00 45.33 92.50 220.00 45.34 92.50 220.00 45.35 92.50 220.00 45.36 92.50 220.00 45.37 92.50 220.00 45.38 92.50 220.00 45.39 92.50 220.00 45.40 92.50 220.00 45.41 92.50 220.00 45.42 92.50 220.00 45.43 92.50 220.00 45.44 92.50 220.00 45.45 92.50 220.00 45.46 92.50 220.00 45.47 92.50 220.00 45.48 92.50 220.00 45.49 92.50 220.00 45.50 92.50 220.00 45.51 92.50 220.00 45.52 92.50 220.00 45.53 92.50 220.00 45.54 92.50 220.00 45.55 92.50 220.00 45.56 92.50 220.00 45.57 92.50 220.00 45.58 92.50 220.00 45.59 92.50 220.00 45.60 92.50 220.00 45.61 92.50 220.00 415.30 45.62 92.50 220.00 415.30 45.63 92.50 220.00 415.30 45.64 92.50 220.00 415.30 45.65 92.50 415.30 45.66 92.50 415.30 45.67 92.50 415.30 45.68 92.50 207.65 415.30 45.69 92.50 207.65 415.30 45.70 92.50 123.47 207.65 415.30 45.71 92.50 123.47 207.65 415.30 45.72 92.50 123.47 207.65 415.30 45.73 61.74 92.50 123.47 207.65 415.30 45.74 61.74 92.50 123.47 207.65 415.30 45.75 61.74 92.50 123.47 207.65 415.30 45.76 61.74 92.50 123.47 207.65 415.30 45.77 61.74 92.50 123.47 207.65 415.30 45.78 61.74 92.50 123.47 207.65 415.30 45.79 61.74 92.50 123.47 207.65 415.30 45.80 61.74 92.50 123.47 207.65 415.30 45.81 61.74 92.50 123.47 207.65 415.30 45.82 61.74 92.50 123.47 207.65 415.30 45.83 61.74 92.50 123.47 207.65 415.30 45.84 61.74 92.50 123.47 207.65 415.30 45.85 61.74 92.50 123.47 207.65 415.30 45.86 61.74 92.50 123.47 207.65 415.30 45.87 61.74 92.50 123.47 207.65 415.30 45.88 61.74 123.47 207.65 415.30 45.89 61.74 123.47 207.65 415.30 45.90 61.74 123.47 207.65 415.30 45.91 61.74 123.47 207.65 415.30 45.92 61.74 123.47 207.65 415.30 45.93 61.74 123.47 207.65 415.30 45.94 61.74 123.47 207.65 415.30 45.95 61.74 123.47 207.65 415.30 45.96 61.74 123.47 207.65 415.30 45.97 61.74 123.47 207.65 415.30 45.98 61.74 123.47 207.65 415.30 45.99 61.74 123.47 207.65 415.30 46.00 61.74 123.47 207.65 415.30 46.01 61.74 123.47 207.65 415.30 46.02 61.74 123.47 207.65 415.30 46.03 61.74 123.47 207.65 415.30 46.04 61.74 123.47 207.65 415.30 46.05 61.74 123.47 207.65 415.30 46.06 61.74 123.47 207.65 415.30 46.07 123.47 207.65 415.30 46.08 123.47 207.65 415.30 46.09 123.47 207.65 415.30 46.10 61.74 123.47 207.65 415.30 46.11 61.74 123.47 207.65 415.30 46.12 61.74 123.47 207.65 246.94 415.30 46.13 61.74 123.47 207.65 246.94 415.30 46.14 61.74 123.47 207.65 246.94 415.30 46.15 61.74 123.47 207.65 246.94 415.30 46.16 61.74 123.47 207.65 246.94 415.30 46.17 61.74 123.47 207.65 246.94 415.30 46.18 61.74 123.47 207.65 246.94 415.30 46.19 61.74 123.47 207.65 246.94 415.30 46.20 61.74 123.47 207.65 246.94 415.30 46.21 61.74 207.65 246.94 415.30 46.22 61.74 207.65 246.94 415.30 46.23 61.74 207.65 246.94 415.30 46.24 61.74 207.65 246.94 415.30 46.25 61.74 207.65 246.94 415.30 46.26 61.74 246.94 415.30 46.27 61.74 246.94 415.30 46.28 61.74 123.47 246.94 415.30 46.29 61.74 123.47 246.94 415.30 46.30 61.74 123.47 246.94 415.30 46.31 61.74 123.47 246.94 415.30 46.32 61.74 123.47 246.94 415.30 46.33 61.74 123.47 246.94 415.30 46.34 61.74 123.47 246.94 415.30 46.35 61.74 123.47 246.94 415.30 46.36 61.74 123.47 246.94 415.30 46.37 61.74 123.47 246.94 415.30 46.38 61.74 123.47 246.94 415.30 46.39 61.74 123.47 246.94 415.30 46.40 61.74 123.47 246.94 415.30 46.41 61.74 123.47 246.94 415.30 46.42 61.74 123.47 246.94 415.30 46.43 61.74 123.47 246.94 415.30 46.44 61.74 123.47 246.94 415.30 46.45 61.74 123.47 246.94 415.30 46.46 61.74 123.47 246.94 415.30 46.47 61.74 123.47 246.94 415.30 46.48 61.74 123.47 246.94 415.30 46.49 61.74 123.47 415.30 46.50 61.74 123.47 415.30 46.51 61.74 123.47 415.30 46.52 61.74 123.47 415.30 46.53 61.74 123.47 415.30 46.54 61.74 123.47 415.30 46.55 61.74 123.47 415.30 46.56 61.74 123.47 415.30 46.57 61.74 123.47 415.30 46.58 61.74 123.47 246.94 415.30 46.59 61.74 123.47 246.94 415.30 46.60 123.47 246.94 415.30 46.61 123.47 246.94 415.30 46.62 123.47 246.94 415.30 46.63 123.47 246.94 415.30 46.64 123.47 246.94 415.30 46.65 246.94 415.30 46.66 246.94 415.30 46.67 246.94 415.30 46.68 246.94 329.63 415.30 46.69 246.94 329.63 415.30 46.70 246.94 329.63 415.30 46.71 246.94 329.63 415.30 46.72 246.94 329.63 415.30 46.73 246.94 329.63 415.30 46.74 246.94 329.63 415.30 46.75 123.47 246.94 329.63 415.30 46.76 123.47 246.94 329.63 415.30 46.77 123.47 246.94 329.63 415.30 46.78 123.47 246.94 329.63 415.30 46.79 123.47 246.94 329.63 415.30 46.80 123.47 246.94 329.63 415.30 46.81 123.47 329.63 415.30 46.82 123.47 329.63 415.30 46.83 123.47 329.63 415.30 46.84 61.74 123.47 329.63 415.30 46.85 61.74 123.47 329.63 415.30 46.86 61.74 123.47 329.63 415.30 46.87 61.74 123.47 329.63 415.30 46.88 61.74 123.47 329.63 415.30 46.89 61.74 123.47 329.63 415.30 46.90 61.74 123.47 329.63 415.30 46.91 123.47 329.63 415.30 46.92 123.47 329.63 415.30 46.93 123.47 329.63 415.30 46.94 123.47 329.63 415.30 46.95 123.47 329.63 415.30 46.96 123.47 329.63 415.30 46.97 123.47 329.63 415.30 46.98 123.47 329.63 415.30 46.99 123.47 329.63 415.30 47.00 123.47 329.63 415.30 47.01 123.47 329.63 415.30 47.02 123.47 329.63 415.30 47.03 61.74 123.47 329.63 415.30 47.04 61.74 123.47 329.63 415.30 47.05 61.74 123.47 329.63 415.30 47.06 61.74 123.47 329.63 415.30 47.07 61.74 123.47 329.63 47.08 61.74 123.47 329.63 47.09 61.74 123.47 329.63 47.10 61.74 123.47 329.63 47.11 61.74 123.47 329.63 47.12 61.74 207.65 329.63 47.13 61.74 207.65 329.63 47.14 61.74 207.65 329.63 47.15 61.74 207.65 329.63 47.16 207.65 47.17 207.65 47.18 207.65 47.19 207.65 47.20 207.65 47.21 123.47 207.65 47.22 123.47 207.65 47.23 123.47 207.65 47.24 123.47 207.65 47.25 123.47 207.65 47.26 123.47 207.65 47.27 123.47 207.65 47.28 207.65 47.29 207.65 47.30 61.74 207.65 47.31 61.74 207.65 47.32 61.74 207.65 47.33 61.74 207.65 47.34 61.74 207.65 47.35 61.74 207.65 47.36 61.74 207.65 47.37 61.74 207.65 47.38 61.74 207.65 47.39 61.74 207.65 47.40 61.74 207.65 47.41 61.74 207.65 47.42 61.74 207.65 47.43 61.74 207.65 47.44 61.74 207.65 47.45 61.74 207.65 47.46 61.74 207.65 47.47 61.74 207.65 47.48 61.74 207.65 47.49 61.74 207.65 47.50 61.74 207.65 47.51 61.74 207.65 47.52 61.74 207.65 47.53 61.74 207.65 47.54 61.74 207.65 47.55 61.74 207.65 47.56 61.74 207.65 47.57 61.74 207.65 47.58 61.74 207.65 47.59 61.74 207.65 47.60 61.74 207.65 47.61 61.74 207.65 246.94 47.62 61.74 207.65 246.94 47.63 61.74 207.65 246.94 47.64 61.74 207.65 246.94 47.65 61.74 207.65 246.94 47.66 61.74 207.65 246.94 47.67 61.74 207.65 246.94 47.68 61.74 207.65 246.94 47.69 61.74 207.65 246.94 47.70 61.74 207.65 246.94 47.71 61.74 207.65 246.94 47.72 61.74 207.65 246.94 47.73 61.74 207.65 246.94 47.74 61.74 207.65 246.94 47.75 61.74 207.65 246.94 47.76 61.74 207.65 246.94 47.77 61.74 207.65 246.94 47.78 61.74 207.65 246.94 47.79 61.74 207.65 246.94 47.80 61.74 207.65 246.94 47.81 61.74 207.65 246.94 47.82 61.74 207.65 246.94 47.83 207.65 47.84 207.65 47.85 207.65 47.86 207.65 47.87 207.65 47.88 207.65 246.94 47.89 207.65 246.94 47.90 207.65 246.94 47.91 207.65 246.94 47.92 207.65 246.94 47.93 207.65 246.94 47.94 207.65 246.94 47.95 207.65 246.94 47.96 207.65 246.94 47.97 207.65 246.94 47.98 207.65 246.94 47.99 207.65 246.94 48.00 207.65 246.94 48.01 207.65 246.94 48.02 207.65 246.94 48.03 207.65 246.94 48.04 246.94 48.05 246.94 48.06 246.94 48.07 246.94 329.63 48.08 246.94 329.63 48.09 246.94 329.63 48.10 246.94 329.63 48.11 329.63 48.12 329.63 48.13 329.63 48.14 329.63 48.15 329.63 48.16 329.63 48.17 329.63 48.18 329.63 48.19 329.63 48.20 329.63 48.21 329.63 48.22 329.63 48.23 329.63 48.24 329.63 48.25 329.63 48.26 329.63 48.27 329.63 48.28 329.63 48.29 329.63 48.30 329.63 48.31 329.63 48.32 329.63 48.33 329.63 48.34 329.63 48.35 329.63 48.36 329.63 48.37 329.63 48.38 329.63 48.39 329.63 48.40 329.63 48.41 329.63 48.42 329.63 48.43 329.63 48.44 329.63 48.45 329.63 48.46 329.63 48.47 329.63 48.48 329.63 48.49 329.63 48.50 329.63 48.51 329.63 48.52 329.63 48.53 329.63 48.54 329.63 48.55 329.63 48.56 329.63 369.99 48.57 329.63 369.99 48.58 61.74 329.63 369.99 48.59 61.74 329.63 369.99 48.60 61.74 329.63 369.99 48.61 61.74 329.63 369.99 48.62 61.74 329.63 369.99 48.63 61.74 207.65 329.63 369.99 48.64 61.74 207.65 329.63 369.99 48.65 61.74 207.65 329.63 369.99 48.66 61.74 207.65 329.63 369.99 48.67 123.47 207.65 220.00 329.63 369.99 48.68 123.47 207.65 220.00 329.63 369.99 48.69 123.47 220.00 329.63 369.99 48.70 123.47 220.00 329.63 369.99 48.71 123.47 220.00 329.63 369.99 48.72 123.47 220.00 329.63 369.99 48.73 123.47 220.00 329.63 369.99 48.74 123.47 220.00 329.63 369.99 48.75 123.47 220.00 329.63 369.99 48.76 123.47 220.00 329.63 369.99 48.77 123.47 220.00 246.94 329.63 369.99 48.78 123.47 220.00 246.94 329.63 369.99 48.79 123.47 220.00 246.94 329.63 369.99 48.80 123.47 220.00 246.94 329.63 369.99 48.81 123.47 220.00 246.94 329.63 369.99 48.82 123.47 220.00 246.94 329.63 369.99 48.83 123.47 220.00 246.94 329.63 369.99 48.84 123.47 220.00 246.94 329.63 369.99 48.85 123.47 220.00 246.94 329.63 369.99 48.86 123.47 220.00 246.94 369.99 48.87 123.47 220.00 246.94 369.99 48.88 123.47 220.00 369.99 48.89 123.47 220.00 369.99 48.90 123.47 220.00 369.99 48.91 123.47 220.00 369.99 48.92 123.47 220.00 369.99 48.93 123.47 220.00 369.99 48.94 123.47 220.00 369.99 48.95 123.47 220.00 369.99 48.96 123.47 220.00 369.99 48.97 123.47 220.00 369.99 48.98 123.47 220.00 369.99 48.99 123.47 220.00 369.99 49.00 61.74 123.47 220.00 369.99 49.01 61.74 123.47 220.00 369.99 49.02 61.74 123.47 220.00 369.99 49.03 61.74 123.47 220.00 369.99 49.04 61.74 123.47 220.00 369.99 49.05 61.74 123.47 220.00 369.99 49.06 61.74 123.47 220.00 369.99 49.07 61.74 123.47 220.00 369.99 49.08 61.74 123.47 220.00 369.99 49.09 61.74 123.47 220.00 369.99 49.10 61.74 123.47 220.00 369.99 49.11 123.47 220.00 369.99 49.12 123.47 220.00 369.99 49.13 123.47 220.00 369.99 49.14 123.47 220.00 246.94 369.99 49.15 123.47 220.00 246.94 369.99 49.16 123.47 220.00 246.94 369.99 49.17 123.47 220.00 246.94 369.99 49.18 220.00 246.94 369.99 49.19 220.00 246.94 369.99 49.20 220.00 246.94 369.99 49.21 220.00 246.94 369.99 49.22 220.00 246.94 369.99 49.23 220.00 246.94 369.99 49.24 220.00 246.94 369.99 49.25 220.00 246.94 369.99 49.26 220.00 246.94 369.99 49.27 220.00 246.94 369.99 49.28 220.00 246.94 369.99 49.29 220.00 246.94 369.99 49.30 220.00 246.94 369.99 49.31 220.00 246.94 369.99 49.32 220.00 246.94 369.99 49.33 220.00 246.94 369.99 49.34 220.00 246.94 369.99 49.35 220.00 246.94 369.99 49.36 220.00 246.94 369.99 49.37 220.00 369.99 49.38 220.00 369.99 49.39 220.00 369.99 49.40 220.00 369.99 49.41 220.00 369.99 49.42 123.47 220.00 369.99 49.43 123.47 220.00 369.99 49.44 123.47 220.00 369.99 49.45 123.47 220.00 369.99 49.46 123.47 369.99 49.47 123.47 369.99 49.48 369.99 49.49 369.99 49.50 369.99 49.51 369.99 49.52 369.99 49.53 369.99 49.54 369.99 49.55 369.99 49.56 369.99 49.57 369.99 49.58 369.99 49.59 369.99 49.60 311.13 369.99 49.61 311.13 369.99 49.62 311.13 369.99 49.63 311.13 369.99 49.64 311.13 369.99 49.65 311.13 369.99 49.66 311.13 369.99 49.67 311.13 369.99 49.68 311.13 369.99 49.69 311.13 369.99 49.70 311.13 369.99 49.71 311.13 369.99 49.72 311.13 369.99 49.73 311.13 369.99 49.74 311.13 369.99 49.75 311.13 369.99 49.76 311.13 369.99 49.77 311.13 369.99 49.78 311.13 369.99 49.79 311.13 369.99 49.80 311.13 369.99 49.81 311.13 369.99 49.82 311.13 369.99 49.83 311.13 369.99 49.84 311.13 369.99 49.85 311.13 369.99 49.86 311.13 369.99 49.87 311.13 369.99 49.88 61.74 311.13 369.99 49.89 61.74 311.13 369.99 49.90 61.74 311.13 49.91 61.74 311.13 49.92 61.74 311.13 49.93 61.74 311.13 49.94 61.74 311.13 49.95 61.74 311.13 49.96 61.74 311.13 49.97 61.74 311.13 49.98 61.74 311.13 49.99 61.74 311.13 50.00 61.74 311.13 50.01 61.74 311.13 50.02 61.74 311.13 50.03 61.74 311.13 50.04 61.74 311.13 50.05 61.74 311.13 50.06 61.74 311.13 50.07 61.74 311.13 50.08 61.74 311.13 50.09 61.74 311.13 50.10 61.74 311.13 50.11 61.74 311.13 50.12 61.74 311.13 50.13 311.13 50.14 311.13 493.88 50.15 311.13 493.88 50.16 220.00 311.13 493.88 50.17 220.00 311.13 493.88 50.18 220.00 311.13 493.88 50.19 220.00 311.13 493.88 50.20 220.00 311.13 493.88 50.21 220.00 311.13 493.88 50.22 220.00 311.13 493.88 50.23 220.00 311.13 493.88 50.24 220.00 311.13 493.88 50.25 220.00 311.13 493.88 50.26 220.00 311.13 493.88 50.27 220.00 311.13 493.88 50.28 220.00 311.13 493.88 50.29 220.00 311.13 493.88 50.30 220.00 311.13 493.88 50.31 220.00 311.13 493.88 50.32 220.00 311.13 493.88 50.33 220.00 311.13 493.88 50.34 220.00 311.13 493.88 50.35 220.00 311.13 493.88 50.36 220.00 311.13 493.88 50.37 220.00 311.13 493.88 50.38 220.00 311.13 493.88 50.39 220.00 246.94 311.13 493.88 50.40 220.00 246.94 311.13 493.88 50.41 220.00 246.94 50.42 220.00 246.94 50.43 220.00 246.94 50.44 220.00 246.94 50.45 220.00 246.94 50.46 220.00 246.94 311.13 50.47 220.00 246.94 311.13 50.48 220.00 246.94 311.13 50.49 220.00 246.94 311.13 493.88 50.50 220.00 246.94 311.13 493.88 50.51 220.00 246.94 311.13 493.88 50.52 220.00 246.94 311.13 493.88 50.53 220.00 311.13 493.88 50.54 220.00 311.13 493.88 50.55 220.00 246.94 311.13 493.88 50.56 220.00 246.94 311.13 493.88 50.57 220.00 246.94 493.88 50.58 220.00 246.94 493.88 50.59 220.00 246.94 493.88 50.60 220.00 246.94 493.88 50.61 220.00 246.94 493.88 50.62 220.00 246.94 50.63 220.00 246.94 50.64 220.00 246.94 50.65 220.00 246.94 50.66 220.00 246.94 50.67 220.00 246.94 50.68 220.00 246.94 50.69 220.00 246.94 50.70 220.00 246.94 50.71 220.00 246.94 50.72 220.00 246.94 50.73 220.00 246.94 50.74 220.00 246.94 50.75 220.00 246.94 50.76 220.00 246.94 50.77 220.00 246.94 50.78 220.00 246.94 50.79 220.00 246.94 50.80 220.00 246.94 50.81 220.00 246.94 50.82 220.00 246.94 50.83 220.00 246.94 50.84 220.00 246.94 50.85 220.00 246.94 50.86 220.00 246.94 50.87 220.00 246.94 50.88 220.00 246.94 50.89 220.00 246.94 50.90 220.00 246.94 50.91 220.00 246.94 50.92 220.00 246.94 50.93 220.00 246.94 50.94 220.00 246.94 50.95 220.00 246.94 50.96 220.00 246.94 50.97 246.94 50.98 246.94 50.99 246.94 51.00 246.94 51.01 246.94 51.02 246.94 51.03 246.94 51.04 246.94 51.05 246.94 51.06 246.94 51.07 246.94 51.08 246.94 51.09 246.94 51.10 246.94 51.11 246.94 51.12 246.94 51.13 246.94 51.14 246.94 51.15 246.94 51.16 246.94 51.17 246.94 51.18 246.94 51.19 246.94 51.20 246.94 51.21 246.94 311.13 493.88 51.22 246.94 311.13 493.88 51.23 246.94 311.13 493.88 51.24 246.94 311.13 493.88 51.25 311.13 493.88 51.26 311.13 493.88 51.27 311.13 493.88 51.28 311.13 493.88 51.29 311.13 493.88 51.30 246.94 311.13 493.88 51.31 246.94 311.13 493.88 51.32 246.94 311.13 493.88 51.33 246.94 311.13 493.88 51.34 246.94 311.13 51.35 246.94 311.13 51.36 246.94 311.13 51.37 246.94 311.13 51.38 246.94 311.13 51.39 246.94 311.13 51.40 246.94 311.13 51.41 246.94 311.13 51.42 246.94 311.13 51.43 246.94 311.13 51.44 246.94 311.13 51.45 246.94 311.13 51.46 246.94 311.13 51.47 246.94 311.13 51.48 246.94 311.13 51.49 246.94 311.13 51.50 246.94 311.13 51.51 246.94 311.13 51.52 246.94 311.13 51.53 246.94 311.13 51.54 246.94 311.13 51.55 246.94 311.13 51.56 246.94 311.13 51.57 246.94 311.13 51.58 246.94 311.13 51.59 246.94 311.13 51.60 246.94 311.13 51.61 246.94 311.13 51.62 246.94 311.13 51.63 246.94 311.13 51.64 246.94 311.13 51.65 246.94 311.13 51.66 246.94 311.13 51.67 246.94 311.13 51.68 246.94 311.13 51.69 246.94 311.13 51.70 246.94 311.13 51.71 246.94 311.13 51.72 246.94 311.13 51.73 246.94 311.13 51.74 246.94 311.13 51.75 246.94 311.13 51.76 311.13 51.77 311.13 51.78 311.13 51.79 311.13 51.80 311.13 51.81 311.13 51.82 311.13 51.83 311.13 51.84 311.13 51.85 311.13 51.86 311.13 51.87 311.13 51.88 164.81 311.13 51.89 164.81 311.13 51.90 164.81 311.13 329.63 51.91 164.81 311.13 329.63 51.92 164.81 207.65 311.13 329.63 51.93 164.81 207.65 311.13 329.63 51.94 164.81 207.65 329.63 51.95 164.81 207.65 329.63 51.96 164.81 207.65 329.63 51.97 82.41 164.81 207.65 51.98 82.41 164.81 207.65 51.99 82.41 164.81 207.65 52.00 82.41 164.81 207.65 52.01 82.41 164.81 207.65 52.02 82.41 164.81 207.65 329.63 52.03 82.41 164.81 207.65 329.63 52.04 82.41 164.81 207.65 329.63 52.05 82.41 164.81 207.65 329.63 52.06 82.41 207.65 329.63 52.07 82.41 207.65 329.63 52.08 82.41 207.65 329.63 52.09 82.41 207.65 329.63 52.10 82.41 207.65 329.63 52.11 82.41 207.65 329.63 52.12 82.41 207.65 329.63 52.13 82.41 207.65 329.63 52.14 82.41 207.65 329.63 52.15 82.41 207.65 329.63 52.16 82.41 164.81 207.65 329.63 52.17 82.41 164.81 207.65 329.63 52.18 82.41 164.81 207.65 329.63 52.19 82.41 164.81 207.65 329.63 52.20 82.41 164.81 207.65 329.63 52.21 82.41 164.81 207.65 329.63 52.22 82.41 164.81 207.65 329.63 52.23 82.41 164.81 207.65 329.63 52.24 82.41 164.81 207.65 329.63 52.25 82.41 164.81 207.65 329.63 52.26 82.41 164.81 207.65 329.63 52.27 82.41 164.81 207.65 329.63 52.28 82.41 164.81 207.65 329.63 52.29 82.41 164.81 207.65 329.63 52.30 82.41 164.81 207.65 329.63 52.31 82.41 164.81 207.65 329.63 52.32 82.41 164.81 207.65 329.63 52.33 82.41 164.81 207.65 329.63 52.34 82.41 207.65 329.63 52.35 82.41 207.65 329.63 52.36 82.41 207.65 329.63 52.37 82.41 207.65 329.63 52.38 82.41 207.65 329.63 52.39 82.41 207.65 329.63 52.40 82.41 207.65 329.63 52.41 82.41 207.65 329.63 52.42 82.41 207.65 329.63 52.43 82.41 207.65 329.63 52.44 82.41 207.65 329.63 52.45 82.41 207.65 329.63 52.46 82.41 207.65 329.63 52.47 82.41 207.65 329.63 52.48 82.41 329.63 52.49 82.41 329.63 52.50 82.41 329.63 52.51 82.41 329.63 52.52 82.41 329.63 52.53 82.41 329.63 52.54 82.41 329.63 52.55 82.41 329.63 52.56 82.41 329.63 52.57 82.41 329.63 52.58 82.41 329.63 52.59 82.41 329.63 52.60 82.41 329.63 52.61 82.41 329.63 52.62 82.41 329.63 52.63 82.41 329.63 52.64 82.41 329.63 52.65 82.41 329.63 52.66 82.41 329.63 52.67 82.41 329.63 52.68 82.41 329.63 52.69 82.41 329.63 52.70 82.41 329.63 52.71 82.41 52.72 82.41 52.73 82.41 52.74 82.41 52.75 82.41 52.76 82.41 52.77 82.41 52.78 82.41 52.79 82.41 52.80 82.41 52.81 82.41 52.82 82.41 52.83 82.41 52.84 82.41 52.85 82.41 52.86 82.41 52.87 82.41 52.88 82.41 52.89 82.41 52.90 82.41 52.91 82.41 52.92 82.41 52.93 82.41 52.94 82.41 52.95 82.41 52.96 82.41 52.97 82.41 52.98 82.41 52.99 82.41 53.00 82.41 53.01 82.41 53.02 82.41 53.03 82.41 53.04 82.41 53.05 82.41 53.06 82.41 329.63 53.07 82.41 329.63 53.08 82.41 329.63 53.09 82.41 329.63 53.10 82.41 329.63 53.11 82.41 329.63 53.12 82.41 329.63 53.13 82.41 329.63 53.14 82.41 329.63 53.15 82.41 329.63 53.16 82.41 329.63 53.17 82.41 329.63 53.18 82.41 329.63 53.19 82.41 329.63 53.20 82.41 329.63 53.21 82.41 329.63 53.22 82.41 329.63 53.23 82.41 329.63 53.24 82.41 329.63 53.25 82.41 329.63 53.26 82.41 329.63 53.27 82.41 53.28 82.41 53.29 82.41 53.30 82.41 53.31 82.41 53.32 82.41 329.63 53.33 82.41 329.63 53.34 82.41 329.63 53.35 82.41 329.63 53.36 82.41 329.63 53.37 82.41 329.63 53.38 82.41 329.63 53.39 82.41 207.65 329.63 53.40 82.41 207.65 329.63 53.41 82.41 207.65 53.42 82.41 207.65 53.43 82.41 164.81 207.65 53.44 82.41 164.81 207.65 53.45 82.41 164.81 207.65 53.46 82.41 164.81 207.65 53.47 82.41 164.81 207.65 53.48 82.41 164.81 207.65 53.49 82.41 164.81 207.65 53.50 82.41 164.81 207.65 53.51 82.41 164.81 207.65 53.52 164.81 207.65 53.53 164.81 207.65 53.54 164.81 207.65 53.55 53.56 53.57 53.58 53.59 53.60 53.61 53.62 53.63 53.64 53.65 53.66 53.67 53.68 53.69 53.70 53.71 53.72 53.73 53.74 53.75 53.76 53.77 53.78 53.79 53.80 53.81 53.82 53.83 53.84 53.85 53.86 53.87 53.88 53.89 53.90 53.91 53.92 53.93 53.94 53.95 53.96 53.97 53.98 53.99 54.00 54.01 54.02 54.03 54.04 54.05 54.06 54.07 54.08 54.09 54.10 54.11 54.12 54.13 54.14 54.15 54.16 54.17 54.18 54.19 54.20 54.21 54.22 54.23 54.24 54.25 54.26 54.27 54.28 54.29 54.30 54.31 54.32 54.33 54.34 54.35 54.36 54.37 54.38 54.39 54.40 54.41 54.42 54.43 54.44 54.45 54.46 54.47 54.48 54.49 54.50 54.51 54.52 54.53 mir_eval-0.8.2/tests/data/multipitch/est03.txt000066400000000000000000001606561475740344600213070ustar00rootroot000000000000000.0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.2 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.3 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.4 0.41 0.42 0.43 0.44 0.45 0.46 0.47 0.48 0.49 0.5 0.51 0.52 420.13 0.53 420.13 0.54 420.13 0.55 420.13 0.56 420.13 0.57 420.13 0.58 425.012 0.59 425.012 0.6 425.012 0.61 425.012 0.62 425.012 0.63 425.012 0.64 420.13 0.65 420.13 0.66 420.13 0.67 420.13 0.68 420.13 0.69 420.13 0.7 420.13 0.71 420.13 0.72 420.13 493.883 0.73 420.13 493.883 0.74 420.13 493.883 0.75 420.13 493.883 0.76 420.13 493.883 0.77 420.13 493.883 0.78 420.13 505.427 0.79 420.13 505.427 0.8 420.13 1497.17 505.427 0.81 420.13 1497.17 505.427 0.82 420.13 1497.17 505.427 0.83 420.13 1497.17 505.427 0.84 420.13 1497.17 505.427 0.85 420.13 1497.17 505.427 0.86 420.13 499.622 1479.98 0.87 420.13 499.622 1479.98 0.88 420.13 499.622 1479.98 0.89 420.13 499.622 1479.98 0.9 420.13 1479.98 0.91 420.13 1479.98 0.92 420.13 493.883 0.93 420.13 493.883 0.94 420.13 493.883 0.95 420.13 493.883 0.96 420.13 493.883 0.97 420.13 493.883 0.98 420.13 505.427 0.99 420.13 505.427 1.0 420.13 505.427 1.01 420.13 505.427 1.02 420.13 505.427 1.03 420.13 505.427 1.04 420.13 493.883 1.05 420.13 493.883 1.06 420.13 493.883 1.07 420.13 493.883 1.08 420.13 493.883 1.09 420.13 493.883 1.1 420.13 329.628 1.11 420.13 329.628 1.12 420.13 329.628 1.13 420.13 329.628 1.14 420.13 329.628 1.15 420.13 329.628 1.16 420.13 333.458 1.17 420.13 333.458 1.18 420.13 333.458 1.19 420.13 333.458 1.2 420.13 333.458 1.21 420.13 333.458 1.22 333.458 1.23 333.458 1.24 333.458 1.25 333.458 1.26 333.458 1.27 333.458 1.28 420.13 333.458 1.29 420.13 333.458 1.3 420.13 333.458 1.31 420.13 333.458 1.32 420.13 333.458 1.33 420.13 333.458 1.34 420.13 333.458 1.35 420.13 333.458 1.36 420.13 333.458 1.37 420.13 333.458 1.38 333.458 425.012 1.39 333.458 425.012 1.4 333.458 425.012 1.41 333.458 425.012 1.42 333.458 425.012 1.43 333.458 425.012 1.44 420.13 333.458 1.45 420.13 333.458 1.46 420.13 333.458 1.47 420.13 333.458 1.48 420.13 333.458 1.49 420.13 333.458 1.5 420.13 329.628 1.51 420.13 329.628 1.52 329.628 1.53 329.628 1.54 425.012 329.628 1.55 425.012 329.628 1.56 425.012 329.628 1.57 425.012 329.628 1.58 333.458 425.012 1.59 333.458 425.012 1.6 420.13 333.458 1.61 420.13 333.458 1.62 420.13 333.458 560.807 1.63 420.13 333.458 560.807 1.64 420.13 329.628 560.807 1.65 420.13 329.628 560.807 1.66 420.13 329.628 560.807 1.67 420.13 329.628 560.807 1.68 420.13 329.628 560.807 1.69 420.13 329.628 560.807 1.7 420.13 554.365 329.628 1.71 420.13 554.365 329.628 1.72 420.13 554.365 329.628 1.73 420.13 554.365 329.628 1.74 420.13 554.365 329.628 1.75 420.13 554.365 329.628 1.76 420.13 554.365 329.628 1.77 420.13 554.365 329.628 1.78 420.13 554.365 329.628 1.79 420.13 554.365 329.628 1.8 420.13 333.458 560.807 1.81 420.13 333.458 560.807 1.82 420.13 333.458 560.807 1.83 420.13 333.458 560.807 1.84 420.13 333.458 560.807 1.85 420.13 333.458 560.807 1.86 420.13 554.365 329.628 1.87 420.13 554.365 329.628 1.88 420.13 554.365 329.628 1.89 420.13 554.365 329.628 1.9 420.13 554.365 329.628 1.91 420.13 554.365 329.628 1.92 420.13 554.365 329.628 1.93 420.13 554.365 329.628 1.94 420.13 554.365 329.628 1.95 420.13 554.365 329.628 1.96 420.13 329.628 560.807 1.97 420.13 329.628 560.807 1.98 420.13 329.628 560.807 1.99 420.13 329.628 560.807 2.0 420.13 329.628 560.807 2.01 420.13 329.628 560.807 2.02 420.13 554.365 329.628 2.03 420.13 554.365 329.628 2.04 420.13 554.365 2.05 420.13 554.365 2.06 420.13 554.365 2.07 420.13 554.365 2.08 420.13 2.09 420.13 2.1 420.13 2.11 420.13 2.12 420.13 2.13 420.13 2.14 420.13 2.15 420.13 2.16 420.13 2.17 420.13 2.18 420.13 2.19 420.13 2.2 420.13 2.21 420.13 2.22 420.13 2.23 420.13 2.24 420.13 2.25 420.13 2.26 420.13 2.27 420.13 2.28 420.13 2.29 420.13 2.3 415.305 2.31 415.305 2.32 415.305 2.33 415.305 2.34 415.305 2.35 415.305 2.36 415.305 2.37 415.305 2.38 420.13 2.39 420.13 2.4 420.13 2.41 420.13 2.42 420.13 2.43 420.13 2.44 420.13 2.45 420.13 2.46 420.13 2.47 420.13 2.48 420.13 2.49 420.13 2.5 415.305 2.51 415.305 2.52 415.305 2.53 415.305 2.54 415.305 2.55 415.305 2.56 415.305 2.57 415.305 2.58 2.59 2.6 420.13 314.742 2.61 420.13 314.742 2.62 420.13 314.742 2.63 420.13 314.742 2.64 420.13 314.742 2.65 420.13 314.742 2.66 420.13 311.127 2.67 420.13 311.127 2.68 311.127 415.305 2.69 311.127 415.305 2.7 311.127 415.305 2.71 311.127 415.305 2.72 311.127 415.305 2.73 311.127 415.305 2.74 311.127 415.305 2.75 311.127 415.305 2.76 420.13 314.742 2.77 420.13 314.742 2.78 420.13 314.742 2.79 420.13 314.742 2.8 420.13 314.742 2.81 420.13 314.742 2.82 425.012 314.742 2.83 425.012 314.742 2.84 311.127 425.012 2.85 311.127 425.012 2.86 311.127 425.012 2.87 311.127 425.012 2.88 311.127 415.305 2.89 311.127 415.305 2.9 311.127 252.714 415.305 2.91 311.127 252.714 415.305 2.92 252.714 415.305 314.742 2.93 252.714 415.305 314.742 2.94 420.13 252.714 314.742 2.95 420.13 252.714 314.742 2.96 249.811 420.13 314.742 2.97 249.811 420.13 314.742 2.98 249.811 420.13 314.742 2.99 249.811 420.13 314.742 3.0 311.127 249.811 420.13 3.01 311.127 249.811 420.13 3.02 311.127 252.714 420.13 3.03 311.127 252.714 420.13 3.04 311.127 252.714 420.13 3.05 311.127 252.714 420.13 3.06 311.127 252.714 420.13 3.07 311.127 252.714 420.13 3.08 249.811 420.13 314.742 3.09 249.811 420.13 314.742 3.1 249.811 420.13 314.742 3.11 249.811 420.13 314.742 3.12 249.811 420.13 314.742 3.13 249.811 420.13 314.742 3.14 249.811 420.13 3.15 249.811 420.13 3.16 249.811 420.13 3.17 249.811 420.13 3.18 249.811 420.13 3.19 249.811 420.13 3.2 249.811 3.21 249.811 3.22 249.811 3.23 249.811 3.24 249.811 3.25 249.811 3.26 249.811 311.127 3.27 249.811 311.127 3.28 249.811 311.127 3.29 249.811 311.127 3.3 249.811 311.127 3.31 249.811 311.127 3.32 249.811 314.742 3.33 249.811 314.742 3.34 249.811 314.742 3.35 249.811 314.742 3.36 249.811 314.742 3.37 249.811 314.742 3.38 249.811 314.742 3.39 249.811 314.742 3.4 249.811 3.41 249.811 3.42 249.811 499.622 3.43 249.811 499.622 3.44 249.811 499.622 3.45 249.811 499.622 3.46 249.811 499.622 3.47 249.811 499.622 3.48 249.811 493.883 3.49 249.811 493.883 3.5 493.883 3.51 493.883 3.52 493.883 3.53 493.883 3.54 505.427 3.55 505.427 3.56 505.427 3.57 505.427 3.58 505.427 3.59 505.427 3.6 3.61 3.62 499.622 3.63 499.622 3.64 499.622 3.65 499.622 3.66 499.622 3.67 499.622 3.68 488.211 3.69 488.211 3.7 488.211 3.71 488.211 3.72 488.211 3.73 488.211 3.74 505.427 3.75 505.427 3.76 505.427 3.77 505.427 3.78 505.427 3.79 505.427 3.8 499.622 3.81 499.622 3.82 499.622 3.83 499.622 3.84 499.622 3.85 499.622 3.86 493.883 3.87 493.883 3.88 493.883 311.127 3.89 493.883 311.127 3.9 493.883 311.127 3.91 493.883 311.127 3.92 499.622 311.127 3.93 499.622 311.127 3.94 499.622 311.127 3.95 499.622 311.127 3.96 314.742 3.97 314.742 3.98 314.742 3.99 314.742 4.0 4.01 4.02 493.883 4.03 493.883 4.04 493.883 4.05 493.883 4.06 493.883 4.07 493.883 4.08 493.883 4.09 493.883 4.1 499.622 4.11 499.622 4.12 499.622 4.13 499.622 4.14 314.742 4.15 314.742 4.16 314.742 4.17 314.742 4.18 314.742 4.19 314.742 4.2 314.742 4.21 314.742 4.22 311.127 4.23 311.127 4.24 311.127 4.25 311.127 4.26 311.127 4.27 311.127 4.28 314.742 4.29 314.742 4.3 210.065 314.742 4.31 210.065 314.742 4.32 210.065 314.742 4.33 210.065 314.742 4.34 210.065 318.399 4.35 210.065 318.399 4.36 210.065 318.399 4.37 210.065 318.399 4.38 210.065 318.399 4.39 210.065 318.399 4.4 311.127 207.652 4.41 311.127 207.652 4.42 311.127 207.652 4.43 311.127 207.652 4.44 311.127 207.652 4.45 311.127 207.652 4.46 210.065 314.742 4.47 210.065 314.742 4.48 314.742 4.49 314.742 4.5 314.742 4.51 314.742 4.52 318.399 4.53 318.399 4.54 318.399 4.55 318.399 4.56 318.399 4.57 318.399 4.58 311.127 4.59 311.127 4.6 311.127 4.61 311.127 4.62 311.127 4.63 311.127 4.64 314.742 4.65 314.742 4.66 314.742 4.67 314.742 4.68 314.742 4.69 314.742 4.7 314.742 4.71 314.742 4.72 311.127 4.73 311.127 4.74 311.127 4.75 311.127 4.76 311.127 4.77 311.127 4.78 311.127 4.79 311.127 4.8 318.399 4.81 318.399 4.82 318.399 4.83 318.399 4.84 318.399 4.85 318.399 4.86 314.742 4.87 314.742 4.88 314.742 4.89 314.742 4.9 314.742 4.91 314.742 4.92 314.742 4.93 314.742 4.94 314.742 4.95 314.742 4.96 318.399 4.97 318.399 4.98 318.399 4.99 318.399 5.0 318.399 5.01 318.399 5.02 314.742 5.03 314.742 5.04 5.05 5.06 5.07 5.08 5.09 5.1 5.11 5.12 5.13 5.14 5.15 5.16 5.17 5.18 5.19 5.2 5.21 5.22 5.23 5.24 5.25 5.26 5.27 5.28 5.29 5.3 5.31 5.32 5.33 5.34 5.35 5.36 5.37 5.38 5.39 5.4 5.41 5.42 5.43 5.44 5.45 5.46 5.47 5.48 5.49 5.5 5.51 5.52 5.53 5.54 5.55 5.56 5.57 5.58 5.59 5.6 5.61 5.62 5.63 5.64 5.65 5.66 5.67 5.68 5.69 5.7 5.71 5.72 5.73 5.74 5.75 5.76 5.77 5.78 5.79 5.8 5.81 5.82 5.83 5.84 5.85 5.86 5.87 5.88 5.89 5.9 5.91 5.92 5.93 5.94 5.95 5.96 5.97 5.98 5.99 6.0 6.01 6.02 6.03 6.04 6.05 6.06 6.07 6.08 6.09 6.1 249.811 6.11 249.811 6.12 249.811 6.13 249.811 6.14 249.811 6.15 249.811 6.16 249.811 6.17 249.811 6.18 249.811 6.19 249.811 6.2 249.811 6.21 249.811 6.22 249.811 6.23 249.811 6.24 249.811 6.25 249.811 6.26 249.811 6.27 249.811 6.28 249.811 6.29 249.811 6.3 249.811 6.31 249.811 6.32 252.714 6.33 252.714 6.34 6.35 6.36 6.37 6.38 6.39 6.4 6.41 6.42 6.43 6.44 6.45 6.46 6.47 6.48 6.49 6.5 6.51 6.52 6.53 6.54 6.55 6.56 6.57 6.58 6.59 6.6 6.61 6.62 6.63 6.64 493.883 6.65 493.883 6.66 493.883 6.67 493.883 6.68 493.883 333.458 6.69 493.883 333.458 6.7 505.427 333.458 6.71 505.427 333.458 6.72 505.427 333.458 6.73 505.427 333.458 6.74 505.427 333.458 6.75 505.427 333.458 6.76 333.458 493.883 6.77 333.458 493.883 6.78 333.458 493.883 6.79 333.458 493.883 6.8 333.458 493.883 6.81 333.458 493.883 6.82 493.883 329.628 6.83 493.883 329.628 6.84 493.883 329.628 6.85 493.883 329.628 6.86 499.622 329.628 6.87 499.622 329.628 6.88 499.622 333.458 6.89 499.622 333.458 6.9 499.622 333.458 6.91 499.622 333.458 6.92 499.622 690.434 6.93 499.622 690.434 6.94 493.883 690.434 6.95 493.883 690.434 6.96 493.883 690.434 6.97 493.883 690.434 6.98 493.883 690.434 6.99 493.883 690.434 7.0 493.883 690.434 7.01 493.883 690.434 7.02 682.504 488.211 157.371 7.03 682.504 488.211 157.371 7.04 157.371 7.05 157.371 7.06 314.742 157.371 7.07 314.742 157.371 7.08 222.556 314.742 157.371 7.09 222.556 314.742 157.371 7.1 222.556 314.742 157.371 7.11 222.556 314.742 157.371 7.12 222.556 314.742 157.371 7.13 222.556 314.742 157.371 7.14 222.556 314.742 157.371 7.15 222.556 314.742 157.371 7.16 220 157.371 314.742 7.17 220 157.371 314.742 7.18 220 157.371 445.113 7.19 220 157.371 445.113 7.2 220 157.371 445.113 7.21 220 157.371 445.113 7.22 220 311.127 157.371 445.113 7.23 220 311.127 157.371 445.113 7.24 220 311.127 157.371 445.113 7.25 220 311.127 157.371 445.113 7.26 220 311.127 157.371 445.113 7.27 220 311.127 157.371 445.113 7.28 739.989 220 311.127 157.371 445.113 7.29 739.989 220 311.127 157.371 445.113 7.3 739.989 220 311.127 157.371 445.113 7.31 739.989 220 311.127 157.371 445.113 7.32 739.989 220 157.371 445.113 314.742 7.33 739.989 220 157.371 445.113 314.742 7.34 220 748.587 157.371 445.113 314.742 7.35 220 748.587 157.371 445.113 314.742 7.36 748.587 222.556 157.371 445.113 314.742 7.37 748.587 222.556 157.371 445.113 314.742 7.38 748.587 222.556 157.371 445.113 314.742 7.39 748.587 222.556 157.371 445.113 314.742 7.4 222.556 157.371 445.113 314.742 7.41 222.556 157.371 445.113 314.742 7.42 311.127 157.371 445.113 7.43 311.127 157.371 445.113 7.44 311.127 157.371 445.113 7.45 311.127 157.371 445.113 7.46 369.994 311.127 445.113 7.47 369.994 311.127 445.113 7.48 369.994 311.127 440 7.49 369.994 311.127 440 7.5 369.994 440 314.742 7.51 369.994 440 314.742 7.52 374.294 440 157.371 314.742 7.53 374.294 440 157.371 314.742 7.54 374.294 157.371 445.113 314.742 7.55 374.294 157.371 445.113 314.742 7.56 374.294 157.371 445.113 314.742 7.57 374.294 157.371 445.113 314.742 7.58 374.294 157.371 445.113 314.742 7.59 374.294 157.371 445.113 314.742 7.6 450.285 155.563 374.294 311.127 7.61 450.285 155.563 374.294 311.127 7.62 450.285 155.563 374.294 311.127 7.63 450.285 155.563 374.294 311.127 7.64 450.285 155.563 374.294 311.127 7.65 450.285 155.563 374.294 311.127 7.66 374.294 311.127 157.371 7.67 374.294 311.127 157.371 7.68 374.294 311.127 445.113 157.371 7.69 374.294 311.127 445.113 157.371 7.7 374.294 314.742 445.113 157.371 7.71 374.294 314.742 445.113 157.371 7.72 374.294 314.742 445.113 157.371 7.73 374.294 314.742 445.113 157.371 7.74 450.285 374.294 314.742 157.371 7.75 450.285 374.294 314.742 157.371 7.76 450.285 374.294 314.742 157.371 7.77 450.285 374.294 314.742 157.371 7.78 450.285 374.294 314.742 157.371 7.79 450.285 374.294 314.742 157.371 7.8 374.294 311.127 445.113 157.371 7.81 374.294 311.127 445.113 157.371 7.82 374.294 311.127 445.113 157.371 7.83 374.294 311.127 445.113 157.371 7.84 374.294 311.127 445.113 157.371 7.85 374.294 311.127 445.113 157.371 7.86 450.285 155.563 374.294 311.127 7.87 450.285 155.563 374.294 311.127 7.88 450.285 155.563 374.294 311.127 7.89 450.285 155.563 374.294 311.127 7.9 450.285 155.563 374.294 311.127 7.91 450.285 155.563 374.294 311.127 7.92 155.563 374.294 311.127 445.113 7.93 155.563 374.294 311.127 445.113 7.94 155.563 374.294 445.113 7.95 155.563 374.294 445.113 7.96 369.994 445.113 157.371 7.97 369.994 445.113 157.371 7.98 369.994 445.113 554.365 157.371 7.99 369.994 445.113 554.365 157.371 8.0 450.285 369.994 554.365 157.371 8.01 450.285 369.994 554.365 157.371 8.02 369.994 166.729 554.365 157.371 8.03 369.994 166.729 554.365 157.371 8.04 547.998 157.371 210.065 166.729 8.05 547.998 157.371 210.065 166.729 8.06 547.998 157.371 210.065 166.729 8.07 547.998 157.371 210.065 166.729 8.08 547.998 210.065 166.729 8.09 547.998 210.065 166.729 8.1 560.807 210.065 166.729 8.11 560.807 210.065 166.729 8.12 560.807 210.065 166.729 8.13 560.807 210.065 166.729 8.14 560.807 210.065 166.729 8.15 560.807 210.065 166.729 8.16 210.065 166.729 554.365 8.17 210.065 166.729 554.365 8.18 166.729 554.365 8.19 166.729 554.365 8.2 166.729 554.365 8.21 166.729 554.365 8.22 166.729 554.365 8.23 166.729 554.365 8.24 560.807 166.729 8.25 560.807 166.729 8.26 560.807 166.729 8.27 560.807 166.729 8.28 560.807 166.729 8.29 560.807 166.729 8.3 560.807 166.729 8.31 560.807 166.729 8.32 166.729 554.365 8.33 166.729 554.365 8.34 420.13 166.729 554.365 8.35 420.13 166.729 554.365 8.36 420.13 166.729 554.365 8.37 420.13 166.729 554.365 8.38 547.998 420.13 166.729 8.39 547.998 420.13 166.729 8.4 547.998 420.13 8.41 547.998 420.13 8.42 547.998 425.012 8.43 547.998 425.012 8.44 560.807 425.012 8.45 560.807 425.012 8.46 560.807 425.012 8.47 560.807 425.012 8.48 560.807 420.13 8.49 560.807 420.13 8.5 420.13 554.365 8.51 420.13 554.365 8.52 420.13 554.365 8.53 420.13 554.365 8.54 420.13 554.365 8.55 420.13 554.365 8.56 560.807 420.13 8.57 560.807 420.13 8.58 560.807 420.13 8.59 560.807 420.13 8.6 560.807 420.13 8.61 560.807 420.13 8.62 420.13 567.323 8.63 420.13 567.323 8.64 420.13 567.323 8.65 420.13 567.323 8.66 420.13 567.323 8.67 420.13 567.323 8.68 425.012 554.365 8.69 425.012 554.365 8.7 425.012 554.365 8.71 425.012 554.365 8.72 425.012 554.365 8.73 425.012 554.365 8.74 420.13 567.323 8.75 420.13 567.323 8.76 420.13 567.323 8.77 420.13 567.323 8.78 420.13 8.79 420.13 8.8 560.807 420.13 8.81 560.807 420.13 8.82 560.807 420.13 8.83 560.807 420.13 8.84 560.807 420.13 8.85 560.807 420.13 8.86 420.13 567.323 8.87 420.13 567.323 8.88 420.13 567.323 8.89 420.13 567.323 8.9 420.13 567.323 8.91 420.13 567.323 8.92 420.13 8.93 420.13 8.94 280.403 420.13 8.95 280.403 420.13 8.96 280.403 420.13 8.97 280.403 420.13 8.98 280.403 420.13 8.99 280.403 420.13 9.0 280.403 420.13 9.01 280.403 420.13 9.02 280.403 420.13 9.03 280.403 420.13 9.04 280.403 9.05 280.403 9.06 280.403 9.07 280.403 9.08 280.403 9.09 280.403 9.1 280.403 9.11 280.403 9.12 280.403 420.13 9.13 280.403 420.13 9.14 280.403 420.13 9.15 280.403 420.13 9.16 280.403 420.13 9.17 280.403 420.13 9.18 280.403 420.13 9.19 280.403 420.13 9.2 280.403 420.13 9.21 280.403 420.13 9.22 280.403 420.13 9.23 280.403 420.13 9.24 280.403 420.13 9.25 280.403 420.13 9.26 280.403 420.13 9.27 280.403 420.13 9.28 280.403 420.13 9.29 280.403 420.13 9.3 280.403 420.13 9.31 280.403 420.13 9.32 420.13 9.33 420.13 9.34 420.13 9.35 420.13 9.36 9.37 9.38 420.13 9.39 420.13 9.4 420.13 9.41 420.13 9.42 420.13 9.43 420.13 9.44 420.13 9.45 420.13 9.46 420.13 9.47 420.13 9.48 420.13 9.49 420.13 9.5 420.13 9.51 420.13 9.52 420.13 9.53 420.13 9.54 420.13 9.55 420.13 9.56 420.13 9.57 420.13 9.58 420.13 9.59 420.13 9.6 420.13 9.61 420.13 9.62 425.012 9.63 425.012 9.64 425.012 9.65 425.012 9.66 425.012 9.67 425.012 9.68 420.13 9.69 420.13 9.7 420.13 9.71 420.13 9.72 420.13 9.73 420.13 9.74 210.065 420.13 9.75 210.065 420.13 9.76 210.065 420.13 9.77 210.065 420.13 9.78 210.065 420.13 9.79 210.065 420.13 9.8 210.065 420.13 9.81 210.065 420.13 9.82 210.065 420.13 9.83 210.065 420.13 9.84 420.13 212.506 9.85 420.13 212.506 9.86 420.13 9.87 420.13 9.88 314.742 420.13 9.89 314.742 420.13 9.9 314.742 420.13 9.91 314.742 420.13 9.92 314.742 420.13 157.371 9.93 314.742 420.13 157.371 9.94 311.127 249.811 420.13 157.371 9.95 311.127 249.811 420.13 157.371 9.96 311.127 249.811 420.13 157.371 9.97 311.127 249.811 420.13 157.371 9.98 425.012 311.127 249.811 157.371 9.99 425.012 311.127 249.811 157.371 10.0 425.012 249.811 157.371 10.01 425.012 249.811 157.371 10.02 425.012 249.811 157.371 10.03 425.012 249.811 157.371 10.04 249.811 157.371 10.05 249.811 157.371 10.06 249.811 157.371 10.07 249.811 157.371 10.08 249.811 157.371 10.09 249.811 157.371 10.1 249.811 157.371 10.11 249.811 157.371 10.12 249.811 311.127 157.371 10.13 249.811 311.127 157.371 10.14 249.811 311.127 157.371 10.15 249.811 311.127 157.371 10.16 249.811 311.127 157.371 10.17 249.811 311.127 157.371 10.18 249.811 311.127 157.371 10.19 249.811 311.127 157.371 10.2 249.811 311.127 157.371 10.21 249.811 311.127 157.371 10.22 318.399 249.811 157.371 10.23 318.399 249.811 157.371 10.24 249.811 157.371 10.25 249.811 157.371 10.26 246.942 157.371 10.27 246.942 157.371 10.28 246.942 157.371 10.29 246.942 157.371 10.3 246.942 157.371 10.31 246.942 157.371 10.32 252.714 157.371 10.33 252.714 157.371 10.34 252.714 157.371 10.35 252.714 157.371 10.36 252.714 157.371 10.37 252.714 157.371 10.38 249.811 157.371 10.39 249.811 157.371 10.4 249.811 157.371 10.41 249.811 157.371 10.42 249.811 157.371 10.43 249.811 157.371 10.44 314.742 249.811 157.371 10.45 314.742 249.811 157.371 10.46 314.742 249.811 157.371 10.47 314.742 249.811 157.371 10.48 314.742 249.811 157.371 10.49 314.742 249.811 157.371 10.5 249.811 311.127 157.371 10.51 249.811 311.127 157.371 10.52 249.811 311.127 157.371 10.53 249.811 311.127 157.371 10.54 249.811 311.127 157.371 10.55 249.811 311.127 157.371 10.56 249.811 311.127 157.371 10.57 249.811 311.127 157.371 10.58 249.811 311.127 157.371 10.59 249.811 311.127 157.371 10.6 249.811 311.127 157.371 10.61 249.811 311.127 157.371 10.62 314.742 249.811 157.371 10.63 314.742 249.811 157.371 10.64 314.742 249.811 157.371 10.65 314.742 249.811 157.371 10.66 314.742 249.811 157.371 10.67 314.742 249.811 157.371 10.68 314.742 249.811 157.371 10.69 314.742 249.811 157.371 10.7 249.811 311.127 157.371 10.71 249.811 311.127 157.371 10.72 249.811 311.127 157.371 10.73 249.811 311.127 157.371 10.74 249.811 311.127 157.371 10.75 249.811 311.127 157.371 10.76 249.811 311.127 157.371 10.77 249.811 311.127 157.371 10.78 246.942 311.127 157.371 10.79 246.942 311.127 157.371 10.8 246.942 311.127 157.371 10.81 246.942 311.127 157.371 10.82 246.942 311.127 157.371 10.83 246.942 311.127 157.371 10.84 249.811 10.85 249.811 10.86 249.811 10.87 249.811 10.88 659.255 249.811 10.89 659.255 249.811 10.9 659.255 249.811 10.91 659.255 249.811 10.92 659.255 249.811 233.082 10.93 659.255 249.811 233.082 10.94 249.811 666.915 233.082 10.95 249.811 666.915 233.082 10.96 249.811 666.915 233.082 10.97 249.811 666.915 233.082 10.98 249.811 666.915 233.082 10.99 249.811 666.915 233.082 11.0 249.811 233.082 11.01 249.811 233.082 11.02 249.811 233.082 11.03 249.811 233.082 11.04 249.811 233.082 11.05 249.811 233.082 11.06 659.255 249.811 233.082 11.07 659.255 249.811 233.082 11.08 659.255 249.811 230.405 11.09 659.255 249.811 230.405 11.1 659.255 252.714 230.405 11.11 659.255 252.714 230.405 11.12 252.714 666.915 230.405 11.13 252.714 666.915 230.405 11.14 252.714 666.915 230.405 11.15 252.714 666.915 230.405 11.16 666.915 233.082 11.17 666.915 233.082 11.18 233.082 11.19 233.082 11.2 233.082 11.21 233.082 11.22 233.082 11.23 233.082 11.24 233.082 11.25 233.082 11.26 235.79 11.27 235.79 11.28 235.79 11.29 235.79 11.3 235.79 11.31 235.79 11.32 235.79 11.33 235.79 11.34 235.79 11.35 235.79 11.36 235.79 11.37 235.79 11.38 235.79 11.39 235.79 11.4 235.79 11.41 235.79 11.42 235.79 11.43 235.79 11.44 235.79 11.45 235.79 11.46 235.79 11.47 235.79 11.48 235.79 11.49 235.79 11.5 235.79 11.51 235.79 11.52 235.79 11.53 235.79 11.54 235.79 11.55 235.79 11.56 235.79 11.57 235.79 11.58 235.79 11.59 235.79 11.6 233.082 11.61 233.082 11.62 233.082 11.63 233.082 11.64 233.082 11.65 233.082 11.66 233.082 11.67 233.082 11.68 235.79 11.69 235.79 11.7 235.79 11.71 235.79 11.72 235.79 11.73 235.79 11.74 235.79 11.75 235.79 11.76 235.79 11.77 235.79 11.78 235.79 11.79 235.79 11.8 235.79 11.81 235.79 11.82 235.79 11.83 235.79 11.84 235.79 11.85 235.79 11.86 235.79 11.87 235.79 11.88 235.79 11.89 235.79 11.9 235.79 11.91 235.79 11.92 235.79 11.93 235.79 11.94 11.95 11.96 11.97 11.98 11.99 12.0 420.13 12.01 420.13 12.02 420.13 12.03 420.13 12.04 420.13 12.05 420.13 12.06 420.13 12.07 420.13 12.08 325.841 420.13 12.09 325.841 420.13 12.1 325.841 420.13 12.11 325.841 420.13 12.12 325.841 420.13 12.13 325.841 420.13 12.14 325.841 420.13 12.15 325.841 420.13 12.16 325.841 415.305 12.17 325.841 415.305 12.18 333.458 415.305 12.19 333.458 415.305 12.2 333.458 415.305 12.21 333.458 415.305 12.22 333.458 415.305 12.23 333.458 415.305 12.24 329.628 420.13 12.25 329.628 420.13 12.26 329.628 420.13 12.27 329.628 420.13 12.28 329.628 420.13 12.29 329.628 420.13 12.3 325.841 415.305 12.31 325.841 415.305 12.32 325.841 415.305 12.33 325.841 415.305 12.34 325.841 415.305 12.35 325.841 415.305 12.36 333.458 425.012 12.37 333.458 425.012 12.38 333.458 12.39 333.458 12.4 333.458 425.012 12.41 333.458 425.012 12.42 333.458 425.012 12.43 333.458 425.012 12.44 425.012 329.628 12.45 425.012 329.628 12.46 415.305 329.628 12.47 415.305 329.628 12.48 415.305 329.628 12.49 415.305 329.628 12.5 415.305 329.628 12.51 415.305 329.628 12.52 333.458 420.13 12.53 333.458 420.13 12.54 333.458 420.13 830.609 12.55 333.458 420.13 830.609 12.56 333.458 420.13 830.609 12.57 333.458 420.13 830.609 12.58 333.458 425.012 830.609 12.59 333.458 425.012 830.609 12.6 333.458 425.012 840.261 12.61 333.458 425.012 840.261 12.62 333.458 425.012 840.261 12.63 333.458 425.012 840.261 12.64 333.458 420.13 840.261 12.65 333.458 420.13 840.261 12.66 333.458 12.67 333.458 12.68 425.012 329.628 12.69 425.012 329.628 12.7 425.012 329.628 12.71 425.012 329.628 12.72 425.012 70.1008 329.628 12.73 425.012 70.1008 329.628 12.74 70.1008 420.13 329.628 12.75 70.1008 420.13 329.628 12.76 333.458 70.1008 420.13 12.77 333.458 70.1008 420.13 12.78 477.06 70.1008 420.13 12.79 477.06 70.1008 420.13 12.8 70.9154 333.458 425.012 477.06 12.81 70.9154 333.458 425.012 477.06 12.82 70.9154 333.458 425.012 477.06 12.83 70.9154 333.458 425.012 477.06 12.84 70.9154 333.458 471.58 12.85 70.9154 333.458 471.58 12.86 70.9154 333.458 471.58 12.87 70.9154 333.458 471.58 12.88 333.458 70.1008 471.58 12.89 333.458 70.1008 471.58 12.9 333.458 477.06 70.1008 12.91 333.458 477.06 70.1008 12.92 333.458 477.06 70.1008 12.93 333.458 477.06 70.1008 12.94 333.458 70.1008 12.95 333.458 70.1008 12.96 333.458 70.1008 12.97 333.458 70.1008 12.98 333.458 70.1008 12.99 333.458 70.1008 13.0 70.1008 466.164 329.628 13.01 70.1008 466.164 329.628 13.02 70.9154 466.164 329.628 13.03 70.9154 466.164 329.628 13.04 70.9154 466.164 329.628 13.05 70.9154 466.164 329.628 13.06 325.841 70.9154 477.06 13.07 325.841 70.9154 477.06 13.08 325.841 477.06 70.1008 13.09 325.841 477.06 70.1008 13.1 325.841 477.06 13.11 325.841 477.06 13.12 333.458 471.58 13.13 333.458 471.58 13.14 333.458 471.58 13.15 333.458 471.58 13.16 333.458 471.58 13.17 333.458 471.58 13.18 333.458 471.58 13.19 333.458 471.58 13.2 333.458 471.58 13.21 333.458 471.58 13.22 325.841 70.9154 471.58 13.23 325.841 70.9154 471.58 13.24 325.841 70.9154 477.06 13.25 325.841 70.9154 477.06 13.26 325.841 70.9154 477.06 13.27 325.841 70.9154 477.06 13.28 337.332 70.1008 13.29 337.332 70.1008 13.3 337.332 70.1008 13.31 337.332 70.1008 13.32 337.332 70.1008 13.33 337.332 70.1008 13.34 333.458 70.1008 13.35 333.458 70.1008 13.36 333.458 70.1008 13.37 333.458 70.1008 13.38 333.458 70.9154 13.39 333.458 70.9154 13.4 333.458 70.9154 13.41 333.458 70.9154 13.42 333.458 70.9154 13.43 333.458 70.9154 13.44 333.458 70.1008 13.45 333.458 70.1008 13.46 333.458 13.47 333.458 13.48 333.458 13.49 333.458 13.5 333.458 13.51 333.458 13.52 333.458 13.53 333.458 13.54 333.458 13.55 333.458 13.56 329.628 13.57 329.628 13.58 482.603 329.628 13.59 482.603 329.628 13.6 482.603 329.628 13.61 482.603 329.628 13.62 482.603 13.63 482.603 13.64 482.603 13.65 482.603 13.66 499.622 13.67 499.622 13.68 499.622 13.69 499.622 13.7 78.6855 499.622 374.294 13.71 78.6855 499.622 374.294 13.72 78.6855 499.622 374.294 13.73 78.6855 499.622 374.294 13.74 78.6855 493.883 374.294 13.75 78.6855 493.883 374.294 13.76 78.6855 493.883 369.994 13.77 78.6855 493.883 369.994 13.78 78.6855 493.883 369.994 13.79 78.6855 493.883 369.994 13.8 78.6855 493.883 757.285 369.994 13.81 78.6855 493.883 757.285 369.994 13.82 78.6855 499.622 757.285 374.294 13.83 78.6855 499.622 757.285 374.294 13.84 78.6855 499.622 757.285 374.294 13.85 78.6855 499.622 757.285 374.294 13.86 739.989 78.6855 374.294 13.87 739.989 78.6855 374.294 13.88 739.989 78.6855 369.994 13.89 739.989 78.6855 369.994 13.9 739.989 78.6855 13.91 739.989 78.6855 13.92 78.6855 748.587 369.994 13.93 78.6855 748.587 369.994 13.94 78.6855 748.587 369.994 13.95 78.6855 748.587 369.994 13.96 78.6855 748.587 369.994 13.97 78.6855 748.587 369.994 13.98 78.6855 757.285 369.994 13.99 78.6855 757.285 369.994 14.0 78.6855 757.285 369.994 14.01 78.6855 757.285 369.994 14.02 78.6855 757.285 369.994 14.03 78.6855 757.285 369.994 14.04 739.989 78.6855 374.294 14.05 739.989 78.6855 374.294 14.06 78.6855 249.811 374.294 14.07 78.6855 249.811 374.294 14.08 78.6855 748.587 249.811 374.294 14.09 78.6855 748.587 249.811 374.294 14.1 78.6855 365.745 748.587 249.811 14.11 78.6855 365.745 748.587 249.811 14.12 78.6855 365.745 748.587 249.811 14.13 78.6855 365.745 748.587 249.811 14.14 78.6855 365.745 757.285 249.811 14.15 78.6855 365.745 757.285 249.811 14.16 78.6855 757.285 249.811 374.294 14.17 78.6855 757.285 249.811 374.294 14.18 78.6855 757.285 249.811 374.294 14.19 78.6855 757.285 249.811 374.294 14.2 739.989 78.6855 249.811 374.294 14.21 739.989 78.6855 249.811 374.294 14.22 739.989 78.6855 249.811 374.294 14.23 739.989 78.6855 249.811 374.294 14.24 739.989 78.6855 249.811 369.994 14.25 739.989 78.6855 249.811 369.994 14.26 78.6855 249.811 369.994 14.27 78.6855 249.811 369.994 14.28 78.6855 757.285 249.811 369.994 14.29 78.6855 757.285 249.811 369.994 14.3 78.6855 757.285 249.811 369.994 14.31 78.6855 757.285 249.811 369.994 14.32 78.6855 757.285 249.811 374.294 14.33 78.6855 757.285 249.811 374.294 14.34 78.6855 757.285 249.811 374.294 14.35 78.6855 757.285 249.811 374.294 14.36 78.6855 748.587 249.811 374.294 14.37 78.6855 748.587 249.811 374.294 14.38 78.6855 246.942 748.587 374.294 14.39 78.6855 246.942 748.587 374.294 14.4 78.6855 246.942 748.587 369.994 14.41 78.6855 246.942 748.587 369.994 14.42 739.989 78.6855 246.942 369.994 14.43 739.989 78.6855 246.942 369.994 14.44 739.989 78.6855 369.994 249.811 14.45 739.989 78.6855 369.994 249.811 14.46 739.989 78.6855 378.643 249.811 14.47 739.989 78.6855 378.643 249.811 14.48 78.6855 378.643 757.285 249.811 14.49 78.6855 378.643 757.285 249.811 14.5 78.6855 378.643 757.285 249.811 14.51 78.6855 378.643 757.285 249.811 14.52 78.6855 757.285 374.294 249.811 14.53 78.6855 757.285 374.294 249.811 14.54 739.989 78.6855 374.294 249.811 14.55 739.989 78.6855 374.294 249.811 14.56 739.989 78.6855 374.294 249.811 14.57 739.989 78.6855 374.294 249.811 14.58 739.989 78.6855 374.294 249.811 14.59 739.989 78.6855 374.294 249.811 14.6 78.6855 757.285 374.294 249.811 14.61 78.6855 757.285 374.294 249.811 14.62 757.285 374.294 249.811 14.63 757.285 374.294 249.811 14.64 374.294 249.811 14.65 374.294 249.811 14.66 374.294 249.811 14.67 374.294 249.811 14.68 374.294 249.811 14.69 374.294 249.811 14.7 374.294 249.811 14.71 374.294 249.811 14.72 369.994 249.811 14.73 369.994 249.811 14.74 369.994 249.811 14.75 369.994 249.811 14.76 369.994 249.811 14.77 369.994 249.811 14.78 374.294 249.811 14.79 374.294 249.811 14.8 374.294 249.811 14.81 374.294 249.811 14.82 477.06 374.294 249.811 14.83 477.06 374.294 249.811 14.84 477.06 374.294 249.811 14.85 477.06 374.294 249.811 14.86 477.06 374.294 249.811 14.87 477.06 374.294 249.811 14.88 374.294 471.58 14.89 374.294 471.58 14.9 374.294 471.58 14.91 374.294 471.58 14.92 374.294 471.58 14.93 374.294 471.58 14.94 374.294 471.58 14.95 374.294 471.58 14.96 477.06 374.294 14.97 477.06 374.294 14.98 477.06 374.294 14.99 477.06 374.294 15.0 365.745 15.01 365.745 15.02 365.745 15.03 365.745 15.04 365.745 477.06 932.328 15.05 365.745 477.06 932.328 15.06 477.06 932.328 369.994 15.07 477.06 932.328 369.994 15.08 477.06 932.328 369.994 15.09 477.06 932.328 369.994 15.1 954.12 471.58 369.994 15.11 954.12 471.58 369.994 15.12 374.294 954.12 471.58 15.13 374.294 954.12 471.58 15.14 374.294 954.12 249.811 471.58 15.15 374.294 954.12 249.811 471.58 15.16 374.294 249.811 15.17 374.294 249.811 15.18 374.294 249.811 15.19 374.294 249.811 15.2 249.811 471.58 369.994 15.21 249.811 471.58 369.994 15.22 249.811 471.58 369.994 15.23 249.811 471.58 369.994 15.24 249.811 471.58 369.994 15.25 249.811 471.58 369.994 15.26 249.811 311.127 471.58 369.994 15.27 249.811 311.127 471.58 369.994 15.28 249.811 311.127 471.58 369.994 15.29 249.811 311.127 471.58 369.994 15.3 477.06 374.294 252.714 311.127 15.31 477.06 374.294 252.714 311.127 15.32 374.294 252.714 314.742 15.33 374.294 252.714 314.742 15.34 374.294 252.714 314.742 15.35 374.294 252.714 314.742 15.36 249.811 314.742 369.994 15.37 249.811 314.742 369.994 15.38 314.742 369.994 15.39 314.742 369.994 15.4 314.742 369.994 15.41 314.742 369.994 15.42 471.58 314.742 369.994 15.43 471.58 314.742 369.994 15.44 471.58 314.742 369.994 15.45 471.58 314.742 369.994 15.46 471.58 374.294 314.742 15.47 471.58 374.294 314.742 15.48 477.06 124.905 374.294 314.742 15.49 477.06 124.905 374.294 314.742 15.5 477.06 124.905 374.294 314.742 15.51 477.06 124.905 374.294 314.742 15.52 477.06 124.905 374.294 314.742 15.53 477.06 124.905 374.294 314.742 15.54 477.06 124.905 374.294 314.742 15.55 477.06 124.905 374.294 314.742 15.56 124.905 314.742 15.57 124.905 314.742 15.58 124.905 15.59 124.905 15.6 124.905 15.61 124.905 15.62 477.06 124.905 15.63 477.06 124.905 15.64 477.06 124.905 15.65 477.06 124.905 15.66 477.06 124.905 15.67 477.06 124.905 15.68 477.06 124.905 15.69 477.06 124.905 15.7 124.905 471.58 15.71 124.905 471.58 15.72 124.905 471.58 15.73 124.905 471.58 15.74 124.905 311.127 15.75 124.905 311.127 15.76 124.905 311.127 15.77 124.905 311.127 15.78 124.905 311.127 15.79 124.905 311.127 15.8 124.905 314.742 15.81 124.905 314.742 15.82 124.905 314.742 15.83 124.905 314.742 15.84 124.905 314.742 15.85 124.905 314.742 15.86 124.905 314.742 15.87 124.905 314.742 15.88 124.905 15.89 124.905 15.9 124.905 15.91 124.905 15.92 124.905 15.93 124.905 15.94 124.905 15.95 124.905 15.96 124.905 314.742 15.97 124.905 314.742 15.98 124.905 314.742 15.99 124.905 314.742 16.0 124.905 314.742 16.01 124.905 314.742 16.02 124.905 314.742 16.03 124.905 314.742 16.04 126.357 314.742 16.05 126.357 314.742 16.06 126.357 314.742 16.07 126.357 314.742 16.08 126.357 311.127 16.09 126.357 311.127 16.1 124.905 311.127 16.11 124.905 311.127 16.12 124.905 311.127 16.13 124.905 311.127 16.14 124.905 314.742 16.15 124.905 314.742 16.16 124.905 314.742 16.17 124.905 314.742 16.18 124.905 314.742 16.19 124.905 314.742 16.2 124.905 314.742 16.21 124.905 314.742 16.22 124.905 314.742 16.23 124.905 314.742 16.24 124.905 314.742 16.25 124.905 314.742 16.26 124.905 314.742 16.27 124.905 314.742 16.28 124.905 314.742 16.29 124.905 314.742 16.3 124.905 307.553 16.31 124.905 307.553 16.32 124.905 16.33 124.905 16.34 124.905 16.35 124.905 16.36 318.399 124.905 16.37 318.399 124.905 16.38 318.399 124.905 16.39 318.399 124.905 16.4 318.399 124.905 16.41 318.399 124.905 16.42 124.905 314.742 16.43 124.905 314.742 16.44 124.905 314.742 16.45 124.905 314.742 16.46 124.905 314.742 16.47 124.905 314.742 16.48 124.905 314.742 16.49 124.905 314.742 16.5 124.905 314.742 16.51 124.905 314.742 16.52 124.905 314.742 16.53 124.905 314.742 16.54 83.3644 124.905 314.742 16.55 83.3644 124.905 314.742 16.56 83.3644 124.905 314.742 16.57 83.3644 124.905 314.742 16.58 83.3644 124.905 16.59 83.3644 124.905 16.6 83.3644 420.13 16.61 83.3644 420.13 16.62 83.3644 420.13 16.63 83.3644 420.13 16.64 83.3644 420.13 16.65 83.3644 420.13 16.66 83.3644 420.13 16.67 83.3644 420.13 16.68 83.3644 420.13 16.69 83.3644 420.13 16.7 83.3644 425.012 16.71 83.3644 425.012 16.72 83.3644 425.012 16.73 83.3644 425.012 16.74 83.3644 425.012 16.75 83.3644 425.012 16.76 83.3644 420.13 16.77 83.3644 420.13 16.78 83.3644 420.13 16.79 83.3644 420.13 16.8 83.3644 420.13 16.81 83.3644 420.13 16.82 83.3644 420.13 16.83 83.3644 420.13 16.84 83.3644 420.13 16.85 83.3644 420.13 16.86 83.3644 420.13 16.87 83.3644 420.13 16.88 83.3644 420.13 16.89 83.3644 420.13 16.9 83.3644 420.13 16.91 83.3644 420.13 16.92 83.3644 420.13 16.93 83.3644 420.13 16.94 83.3644 420.13 840.261 16.95 83.3644 420.13 840.261 16.96 420.13 840.261 16.97 420.13 840.261 16.98 420.13 840.261 16.99 420.13 840.261 17.0 83.3644 850.024 420.13 17.01 83.3644 850.024 420.13 17.02 83.3644 850.024 420.13 17.03 83.3644 850.024 420.13 17.04 83.3644 850.024 420.13 17.05 83.3644 850.024 420.13 17.06 83.3644 420.13 17.07 83.3644 420.13 17.08 83.3644 420.13 17.09 83.3644 420.13 17.1 83.3644 420.13 840.261 17.11 83.3644 420.13 840.261 17.12 83.3644 420.13 840.261 17.13 83.3644 420.13 840.261 17.14 83.3644 420.13 840.261 17.15 83.3644 420.13 840.261 17.16 83.3644 420.13 840.261 17.17 83.3644 420.13 840.261 17.18 83.3644 830.609 420.13 17.19 83.3644 830.609 420.13 17.2 83.3644 830.609 420.13 17.21 83.3644 830.609 420.13 17.22 83.3644 420.13 17.23 83.3644 420.13 17.24 83.3644 420.13 17.25 83.3644 420.13 17.26 83.3644 420.13 17.27 83.3644 420.13 17.28 83.3644 420.13 17.29 83.3644 420.13 17.3 83.3644 420.13 17.31 83.3644 420.13 17.32 83.3644 420.13 17.33 83.3644 420.13 17.34 83.3644 420.13 17.35 83.3644 420.13 17.36 83.3644 425.012 17.37 83.3644 425.012 17.38 83.3644 425.012 17.39 83.3644 425.012 17.4 83.3644 425.012 840.261 17.41 83.3644 425.012 840.261 17.42 83.3644 425.012 840.261 17.43 83.3644 425.012 840.261 17.44 840.261 17.45 840.261 17.46 850.024 17.47 850.024 17.48 850.024 17.49 850.024 17.5 850.024 17.51 850.024 17.52 17.53 17.54 374.294 17.55 374.294 17.56 374.294 17.57 374.294 17.58 374.294 17.59 374.294 17.6 78.6855 374.294 17.61 78.6855 374.294 17.62 78.6855 374.294 17.63 78.6855 374.294 17.64 78.6855 374.294 17.65 78.6855 374.294 17.66 78.6855 374.294 17.67 78.6855 374.294 17.68 78.6855 374.294 17.69 78.6855 374.294 17.7 78.6855 369.994 17.71 78.6855 369.994 17.72 78.6855 369.994 17.73 78.6855 369.994 17.74 78.6855 369.994 17.75 78.6855 369.994 17.76 78.6855 374.294 17.77 78.6855 374.294 17.78 78.6855 374.294 17.79 78.6855 374.294 17.8 78.6855 374.294 17.81 78.6855 374.294 17.82 78.6855 374.294 17.83 78.6855 374.294 17.84 78.6855 374.294 17.85 78.6855 374.294 17.86 78.6855 369.994 17.87 78.6855 369.994 17.88 78.6855 369.994 17.89 78.6855 369.994 17.9 78.6855 369.994 17.91 78.6855 369.994 17.92 78.6855 17.93 78.6855 17.94 78.6855 374.294 17.95 78.6855 374.294 17.96 78.6855 374.294 17.97 78.6855 374.294 17.98 78.6855 374.294 17.99 78.6855 374.294 18.0 78.6855 374.294 18.01 78.6855 374.294 18.02 78.6855 369.994 18.03 78.6855 369.994 18.04 78.6855 369.994 18.05 78.6855 369.994 18.06 78.6855 369.994 18.07 78.6855 369.994 18.08 78.6855 369.994 18.09 78.6855 369.994 18.1 78.6855 374.294 18.11 78.6855 374.294 18.12 78.6855 374.294 18.13 78.6855 374.294 18.14 374.294 249.811 18.15 374.294 249.811 18.16 374.294 249.811 18.17 374.294 249.811 18.18 374.294 249.811 18.19 374.294 249.811 18.2 249.811 369.994 18.21 249.811 369.994 18.22 249.811 369.994 18.23 249.811 369.994 18.24 249.811 369.994 18.25 249.811 369.994 18.26 374.294 18.27 374.294 18.28 374.294 18.29 374.294 18.3 374.294 18.31 374.294 18.32 374.294 18.33 374.294 18.34 374.294 18.35 374.294 18.36 374.294 18.37 374.294 18.38 374.294 18.39 374.294 18.4 374.294 18.41 374.294 18.42 374.294 18.43 374.294 18.44 124.905 374.294 18.45 124.905 374.294 18.46 124.905 374.294 18.47 124.905 374.294 18.48 378.643 124.905 18.49 378.643 124.905 18.5 124.905 18.51 124.905 18.52 124.905 314.742 18.53 124.905 314.742 18.54 124.905 314.742 18.55 124.905 314.742 18.56 124.905 314.742 18.57 124.905 314.742 18.58 124.905 314.742 18.59 124.905 314.742 18.6 124.905 314.742 18.61 124.905 314.742 18.62 124.905 314.742 18.63 124.905 314.742 18.64 318.399 124.905 18.65 318.399 124.905 18.66 124.905 18.67 124.905 18.68 124.905 18.69 124.905 18.7 124.905 18.71 124.905 18.72 124.905 18.73 124.905 18.74 124.905 18.75 124.905 18.76 124.905 18.77 124.905 18.78 124.905 18.79 124.905 18.8 124.905 18.81 124.905 18.82 124.905 420.13 18.83 124.905 420.13 18.84 420.13 123.471 18.85 420.13 123.471 18.86 420.13 123.471 18.87 420.13 123.471 18.88 420.13 123.471 18.89 420.13 123.471 18.9 124.905 420.13 18.91 124.905 420.13 18.92 124.905 420.13 18.93 124.905 420.13 18.94 124.905 314.742 18.95 124.905 314.742 18.96 124.905 314.742 18.97 124.905 314.742 18.98 314.742 123.471 18.99 314.742 123.471 19.0 314.742 123.471 19.01 314.742 123.471 19.02 314.742 123.471 19.03 314.742 123.471 19.04 314.742 123.471 19.05 314.742 123.471 19.06 311.127 123.471 19.07 311.127 123.471 19.08 124.905 311.127 19.09 124.905 311.127 19.1 124.905 311.127 19.11 124.905 311.127 19.12 124.905 19.13 124.905 19.14 124.905 19.15 124.905 19.16 124.905 19.17 124.905 19.18 124.905 19.19 124.905 19.2 124.905 19.21 124.905 19.22 124.905 19.23 124.905 19.24 124.905 19.25 124.905 19.26 124.905 19.27 124.905 19.28 124.905 19.29 124.905 19.3 124.905 19.31 124.905 19.32 123.471 19.33 123.471 19.34 123.471 19.35 123.471 19.36 123.471 19.37 123.471 19.38 124.905 19.39 124.905 19.4 124.905 19.41 124.905 19.42 19.43 19.44 19.45 19.46 277.183 19.47 277.183 19.48 277.183 19.49 277.183 19.5 277.183 19.51 277.183 19.52 277.183 19.53 277.183 19.54 277.183 19.55 277.183 19.56 283.661 420.13 19.57 283.661 420.13 19.58 420.13 19.59 420.13 19.6 333.458 420.13 19.61 333.458 420.13 19.62 333.458 415.305 19.63 333.458 415.305 19.64 333.458 415.305 19.65 333.458 415.305 19.66 333.458 415.305 19.67 333.458 415.305 19.68 333.458 425.012 19.69 333.458 425.012 19.7 333.458 425.012 19.71 333.458 425.012 19.72 333.458 425.012 19.73 333.458 425.012 19.74 333.458 415.305 19.75 333.458 415.305 19.76 329.628 415.305 19.77 329.628 415.305 19.78 415.305 19.79 415.305 19.8 420.13 19.81 420.13 19.82 420.13 19.83 420.13 19.84 333.458 420.13 19.85 333.458 420.13 19.86 333.458 425.012 19.87 333.458 425.012 19.88 333.458 425.012 19.89 333.458 425.012 19.9 333.458 425.012 19.91 333.458 425.012 19.92 333.458 415.305 19.93 333.458 415.305 19.94 252.714 329.628 415.305 19.95 252.714 329.628 415.305 19.96 252.714 329.628 415.305 19.97 252.714 329.628 415.305 19.98 252.714 329.628 420.13 19.99 252.714 329.628 420.13 20.0 333.458 252.714 420.13 666.915 20.01 333.458 252.714 420.13 666.915 20.02 333.458 252.714 420.13 666.915 20.03 333.458 252.714 420.13 666.915 20.04 249.811 420.13 666.915 20.05 249.811 420.13 666.915 20.06 333.458 651.683 249.811 420.13 20.07 333.458 651.683 249.811 420.13 20.08 333.458 651.683 249.811 420.13 20.09 333.458 651.683 249.811 420.13 20.1 333.458 651.683 249.811 420.13 20.11 333.458 651.683 249.811 420.13 20.12 659.255 333.458 252.714 420.13 20.13 659.255 333.458 252.714 420.13 20.14 659.255 333.458 252.714 420.13 20.15 659.255 333.458 252.714 420.13 20.16 659.255 333.458 420.13 212.506 20.17 659.255 333.458 420.13 212.506 20.18 333.458 425.012 666.915 212.506 20.19 333.458 425.012 666.915 212.506 20.2 333.458 425.012 666.915 212.506 20.21 333.458 425.012 666.915 212.506 20.22 333.458 425.012 210.065 666.915 20.23 333.458 425.012 210.065 666.915 20.24 333.458 210.065 666.915 420.13 20.25 333.458 210.065 666.915 420.13 20.26 333.458 210.065 420.13 20.27 333.458 210.065 420.13 20.28 333.458 420.13 20.29 333.458 420.13 20.3 333.458 420.13 20.31 333.458 420.13 20.32 1333.83 333.458 420.13 20.33 1333.83 333.458 420.13 20.34 1333.83 333.458 420.13 20.35 1333.83 333.458 420.13 20.36 1333.83 333.458 425.012 20.37 1333.83 333.458 425.012 20.38 1333.83 20.39 1333.83 20.4 1333.83 425.012 20.41 1333.83 425.012 20.42 425.012 1349.33 20.43 425.012 1349.33 20.44 425.012 20.45 425.012 20.46 420.13 20.47 420.13 20.48 420.13 20.49 420.13 20.5 420.13 20.51 420.13 20.52 425.012 20.53 425.012 20.54 425.012 20.55 425.012 20.56 425.012 20.57 425.012 20.58 425.012 20.59 425.012 20.6 420.13 20.61 420.13 20.62 420.13 20.63 420.13 20.64 420.13 20.65 420.13 20.66 420.13 20.67 420.13 20.68 425.012 20.69 425.012 20.7 425.012 20.71 425.012 20.72 425.012 20.73 425.012 20.74 420.13 20.75 420.13 20.76 420.13 20.77 420.13 20.78 420.13 20.79 420.13 20.8 420.13 20.81 420.13 20.82 420.13 20.83 420.13 20.84 425.012 20.85 425.012 20.86 425.012 20.87 425.012 20.88 425.012 20.89 425.012 20.9 277.183 420.13 20.91 277.183 420.13 20.92 277.183 420.13 20.93 277.183 420.13 20.94 277.183 420.13 20.95 277.183 420.13 20.96 280.403 420.13 20.97 280.403 420.13 20.98 280.403 420.13 20.99 280.403 420.13 21.0 280.403 420.13 21.01 280.403 420.13 21.02 280.403 420.13 21.03 280.403 420.13 21.04 280.403 420.13 21.05 280.403 420.13 21.06 280.403 21.07 280.403 21.08 280.403 21.09 280.403 21.1 280.403 21.11 280.403 21.12 280.403 21.13 280.403 21.14 280.403 21.15 280.403 21.16 280.403 21.17 280.403 21.18 280.403 21.19 280.403 21.2 280.403 21.21 280.403 21.22 280.403 21.23 280.403 21.24 280.403 21.25 280.403 21.26 280.403 21.27 280.403 21.28 280.403 21.29 280.403 21.3 280.403 420.13 21.31 280.403 420.13 21.32 280.403 420.13 21.33 280.403 420.13 21.34 280.403 420.13 21.35 280.403 420.13 21.36 420.13 21.37 420.13 21.38 420.13 21.39 420.13 21.4 425.012 21.41 425.012 21.42 425.012 21.43 425.012 21.44 21.45 21.46 233.082 21.47 233.082 21.48 233.082 21.49 233.082 21.5 233.082 21.51 233.082 21.52 233.082 21.53 233.082 21.54 233.082 21.55 233.082 21.56 233.082 21.57 233.082 21.58 230.405 21.59 230.405 21.6 230.405 21.61 230.405 21.62 230.405 21.63 230.405 21.64 233.082 21.65 233.082 21.66 233.082 21.67 233.082 21.68 233.082 21.69 233.082 21.7 233.082 21.71 233.082 21.72 233.082 21.73 233.082 21.74 233.082 21.75 233.082 21.76 233.082 21.77 233.082 21.78 233.082 21.79 233.082 21.8 83.3644 233.082 21.81 83.3644 233.082 21.82 83.3644 233.082 21.83 83.3644 233.082 21.84 83.3644 235.79 21.85 83.3644 235.79 21.86 235.79 84.3331 21.87 235.79 84.3331 21.88 235.79 84.3331 21.89 235.79 84.3331 21.9 84.3331 233.082 21.91 84.3331 233.082 21.92 369.994 84.3331 233.082 21.93 369.994 84.3331 233.082 21.94 369.994 84.3331 233.082 21.95 369.994 84.3331 233.082 21.96 369.994 233.082 21.97 369.994 233.082 21.98 369.994 233.082 21.99 369.994 233.082 22.0 374.294 233.082 22.01 374.294 233.082 22.02 374.294 233.082 22.03 374.294 233.082 22.04 374.294 233.082 22.05 374.294 233.082 22.06 374.294 233.082 22.07 374.294 233.082 22.08 369.994 233.082 22.09 369.994 233.082 22.1 369.994 233.082 22.11 369.994 233.082 22.12 369.994 233.082 22.13 369.994 233.082 22.14 374.294 233.082 22.15 374.294 233.082 22.16 374.294 235.79 22.17 374.294 235.79 22.18 374.294 235.79 22.19 374.294 235.79 22.2 374.294 22.21 374.294 22.22 374.294 22.23 374.294 22.24 369.994 233.082 22.25 369.994 233.082 22.26 369.994 233.082 22.27 369.994 233.082 22.28 369.994 233.082 22.29 369.994 233.082 22.3 369.994 233.082 22.31 369.994 233.082 22.32 374.294 233.082 22.33 374.294 233.082 22.34 374.294 233.082 22.35 374.294 233.082 22.36 233.082 22.37 233.082 22.38 233.082 22.39 233.082 22.4 22.41 22.42 22.43 22.44 78.6855 22.45 78.6855 22.46 78.6855 369.994 22.47 78.6855 369.994 22.48 78.6855 369.994 22.49 78.6855 369.994 22.5 78.6855 369.994 22.51 78.6855 369.994 22.52 78.6855 374.294 22.53 78.6855 374.294 22.54 78.6855 374.294 22.55 78.6855 374.294 22.56 78.6855 374.294 22.57 78.6855 374.294 22.58 78.6855 369.994 22.59 78.6855 369.994 22.6 78.6855 369.994 22.61 78.6855 369.994 22.62 78.6855 369.994 22.63 78.6855 369.994 22.64 78.6855 365.745 22.65 78.6855 365.745 22.66 78.6855 365.745 22.67 78.6855 365.745 22.68 78.6855 365.745 22.69 78.6855 365.745 22.7 78.6855 374.294 22.71 78.6855 374.294 22.72 78.6855 374.294 22.73 78.6855 374.294 22.74 78.6855 374.294 22.75 78.6855 374.294 22.76 78.6855 369.994 22.77 78.6855 369.994 22.78 78.6855 369.994 22.79 78.6855 369.994 22.8 78.6855 369.994 22.81 78.6855 369.994 22.82 78.6855 365.745 22.83 78.6855 365.745 22.84 78.6855 365.745 314.742 22.85 78.6855 365.745 314.742 22.86 78.6855 365.745 314.742 22.87 78.6855 365.745 314.742 22.88 78.6855 314.742 374.294 22.89 78.6855 314.742 374.294 22.9 78.6855 314.742 374.294 22.91 78.6855 314.742 374.294 22.92 78.6855 314.742 374.294 22.93 78.6855 314.742 374.294 22.94 314.742 374.294 22.95 314.742 374.294 22.96 369.994 22.97 369.994 22.98 369.994 249.811 22.99 369.994 249.811 23.0 369.994 249.811 23.01 369.994 249.811 23.02 365.745 249.811 23.03 365.745 249.811 23.04 365.745 249.811 23.05 365.745 249.811 23.06 365.745 249.811 23.07 365.745 249.811 23.08 378.643 249.811 23.09 378.643 249.811 23.1 378.643 249.811 23.11 378.643 249.811 23.12 378.643 249.811 23.13 378.643 249.811 23.14 369.994 23.15 369.994 23.16 23.17 23.18 23.19 23.2 23.21 23.22 23.23 23.24 23.25 23.26 23.27 23.28 23.29 23.3 23.31 23.32 23.33 23.34 23.35 23.36 23.37 23.38 23.39 23.4 23.41 23.42 23.43 23.44 23.45 23.46 23.47 23.48 23.49 23.5 23.51 23.52 314.742 23.53 314.742 23.54 124.905 314.742 23.55 124.905 314.742 23.56 124.905 314.742 23.57 124.905 314.742 23.58 124.905 314.742 23.59 124.905 314.742 23.6 124.905 314.742 23.61 124.905 314.742 23.62 124.905 314.742 23.63 124.905 314.742 23.64 124.905 314.742 23.65 124.905 314.742 23.66 124.905 314.742 23.67 124.905 314.742 23.68 124.905 314.742 23.69 124.905 314.742 23.7 124.905 314.742 23.71 124.905 314.742 23.72 124.905 311.127 23.73 124.905 311.127 23.74 124.905 311.127 23.75 124.905 311.127 23.76 124.905 311.127 23.77 124.905 311.127 23.78 124.905 311.127 23.79 124.905 311.127 23.8 318.399 124.905 23.81 318.399 124.905 23.82 318.399 124.905 23.83 318.399 124.905 23.84 318.399 124.905 23.85 318.399 124.905 23.86 124.905 311.127 23.87 124.905 311.127 23.88 124.905 311.127 23.89 124.905 311.127 23.9 124.905 311.127 23.91 124.905 311.127 23.92 124.905 311.127 23.93 124.905 311.127 23.94 124.905 311.127 23.95 124.905 311.127 23.96 124.905 311.127 23.97 124.905 311.127 23.98 124.905 314.742 651.683 23.99 124.905 314.742 651.683 24.0 124.905 314.742 651.683 24.01 124.905 314.742 651.683 24.02 124.905 314.742 651.683 24.03 124.905 314.742 651.683 24.04 644.198 124.905 311.127 24.05 644.198 124.905 311.127 24.06 644.198 124.905 311.127 24.07 644.198 124.905 311.127 24.08 644.198 124.905 311.127 24.09 644.198 124.905 311.127 24.1 318.399 24.11 318.399 24.12 24.13 24.14 24.15 24.16 311.127 24.17 311.127 24.18 311.127 24.19 311.127 24.2 311.127 24.21 311.127 24.22 311.127 24.23 311.127 24.24 629.484 311.127 24.25 629.484 311.127 24.26 629.484 311.127 24.27 629.484 311.127 24.28 629.484 311.127 24.29 629.484 311.127 24.3 311.127 636.799 24.31 311.127 636.799 24.32 314.742 636.799 24.33 314.742 636.799 24.34 314.742 636.799 24.35 314.742 636.799 24.36 314.742 644.198 24.37 314.742 644.198 24.38 318.399 644.198 24.39 318.399 644.198 24.4 318.399 644.198 24.41 318.399 644.198 24.42 644.198 24.43 644.198 24.44 644.198 24.45 644.198 24.46 644.198 24.47 644.198 24.48 666.915 24.49 666.915 24.5 666.915 24.51 666.915 24.52 322.099 24.53 322.099 24.54 322.099 24.55 322.099 24.56 322.099 24.57 322.099 24.58 333.458 24.59 333.458 24.6 333.458 24.61 333.458 24.62 333.458 105.033 24.63 333.458 105.033 24.64 333.458 105.033 24.65 333.458 105.033 24.66 337.332 105.033 24.67 337.332 105.033 24.68 337.332 105.033 24.69 337.332 105.033 24.7 337.332 105.033 24.71 337.332 105.033 24.72 333.458 105.033 24.73 333.458 105.033 24.74 333.458 105.033 24.75 333.458 105.033 24.76 333.458 105.033 24.77 333.458 105.033 24.78 333.458 105.033 24.79 333.458 105.033 24.8 337.332 24.81 337.332 24.82 337.332 24.83 337.332 24.84 337.332 24.85 337.332 24.86 333.458 24.87 333.458 24.88 333.458 24.89 333.458 24.9 333.458 24.91 333.458 24.92 24.93 24.94 24.95 24.96 24.97 24.98 24.99 25.0 25.01 25.02 25.03 25.04 249.811 25.05 249.811 25.06 249.811 25.07 249.811 25.08 249.811 25.09 249.811 25.1 249.811 25.11 249.811 25.12 249.811 25.13 249.811 25.14 249.811 25.15 249.811 25.16 249.811 25.17 249.811 25.18 249.811 25.19 249.811 25.2 249.811 25.21 249.811 25.22 252.714 25.23 252.714 25.24 252.714 25.25 252.714 25.26 252.714 25.27 252.714 25.28 252.714 25.29 252.714 25.3 252.714 25.31 252.714 25.32 252.714 25.33 252.714 25.34 252.714 25.35 252.714 25.36 333.458 252.714 25.37 333.458 252.714 25.38 333.458 252.714 25.39 333.458 252.714 25.4 333.458 252.714 25.41 333.458 252.714 25.42 337.332 252.714 25.43 337.332 252.714 25.44 337.332 252.714 25.45 337.332 252.714 25.46 337.332 25.47 337.332 25.48 333.458 25.49 333.458 25.5 25.51 25.52 25.53 25.54 277.183 25.55 277.183 25.56 277.183 25.57 277.183 25.58 277.183 25.59 277.183 25.6 280.403 25.61 280.403 25.62 280.403 25.63 280.403 25.64 280.403 25.65 280.403 25.66 280.403 25.67 280.403 25.68 280.403 25.69 280.403 25.7 280.403 25.71 280.403 25.72 280.403 25.73 280.403 25.74 280.403 25.75 280.403 25.76 280.403 25.77 280.403 25.78 280.403 25.79 280.403 25.8 280.403 25.81 280.403 25.82 280.403 25.83 280.403 25.84 280.403 25.85 280.403 25.86 280.403 25.87 280.403 25.88 280.403 25.89 280.403 25.9 280.403 25.91 280.403 25.92 277.183 25.93 277.183 25.94 277.183 25.95 277.183 25.96 277.183 25.97 277.183 25.98 547.998 277.183 25.99 547.998 277.183 26.0 547.998 280.403 333.458 26.01 547.998 280.403 333.458 26.02 547.998 280.403 333.458 26.03 547.998 280.403 333.458 26.04 280.403 333.458 554.365 26.05 280.403 333.458 554.365 26.06 280.403 333.458 554.365 26.07 280.403 333.458 554.365 26.08 280.403 333.458 554.365 26.09 280.403 333.458 554.365 26.1 560.807 277.183 333.458 26.11 560.807 277.183 333.458 26.12 337.332 560.807 26.13 337.332 560.807 26.14 337.332 560.807 26.15 337.332 560.807 26.16 337.332 554.365 26.17 337.332 554.365 26.18 333.458 554.365 26.19 333.458 554.365 26.2 333.458 554.365 26.21 333.458 554.365 26.22 333.458 554.365 26.23 333.458 554.365 26.24 333.458 554.365 26.25 333.458 554.365 26.26 117.895 333.458 554.365 26.27 117.895 333.458 554.365 26.28 117.895 333.458 554.365 26.29 117.895 333.458 554.365 26.3 560.807 117.895 333.458 26.31 560.807 117.895 333.458 26.32 560.807 117.895 333.458 280.403 26.33 560.807 117.895 333.458 280.403 26.34 560.807 117.895 333.458 280.403 26.35 560.807 117.895 333.458 280.403 26.36 560.807 117.895 333.458 280.403 26.37 560.807 117.895 333.458 280.403 26.38 560.807 117.895 333.458 280.403 26.39 560.807 117.895 333.458 280.403 26.4 560.807 117.895 333.458 280.403 26.41 560.807 117.895 333.458 280.403 26.42 560.807 117.895 333.458 280.403 26.43 560.807 117.895 333.458 280.403 26.44 560.807 117.895 333.458 280.403 26.45 560.807 117.895 333.458 280.403 26.46 560.807 117.895 333.458 280.403 26.47 560.807 117.895 333.458 280.403 26.48 560.807 117.895 333.458 280.403 26.49 560.807 117.895 333.458 280.403 26.5 560.807 333.458 280.403 26.51 560.807 333.458 280.403 26.52 560.807 333.458 280.403 26.53 560.807 333.458 280.403 26.54 333.458 280.403 26.55 333.458 280.403 26.56 337.332 280.403 26.57 337.332 280.403 26.58 337.332 280.403 26.59 337.332 280.403 26.6 337.332 280.403 26.61 337.332 280.403 26.62 333.458 280.403 26.63 333.458 280.403 26.64 333.458 280.403 26.65 333.458 280.403 26.66 333.458 280.403 26.67 333.458 280.403 26.68 329.628 26.69 329.628 26.7 105.033 26.71 105.033 26.72 105.033 26.73 105.033 26.74 105.033 26.75 105.033 26.76 105.033 26.77 105.033 26.78 105.033 26.79 105.033 26.8 105.033 26.81 105.033 26.82 105.033 26.83 105.033 26.84 105.033 26.85 105.033 26.86 105.033 26.87 105.033 26.88 105.033 26.89 105.033 26.9 26.91 26.92 26.93 26.94 26.95 26.96 26.97 26.98 105.033 26.99 105.033 27.0 105.033 27.01 105.033 27.02 333.458 105.033 27.03 333.458 105.033 27.04 333.458 105.033 27.05 333.458 105.033 27.06 333.458 106.253 27.07 333.458 106.253 27.08 337.332 106.253 27.09 337.332 106.253 27.1 337.332 252.714 106.253 27.11 337.332 252.714 106.253 27.12 337.332 252.714 105.033 27.13 337.332 252.714 105.033 27.14 252.714 105.033 27.15 252.714 105.033 27.16 249.811 105.033 27.17 249.811 105.033 27.18 249.811 105.033 27.19 249.811 105.033 27.2 249.811 105.033 27.21 249.811 105.033 27.22 333.458 249.811 105.033 27.23 333.458 249.811 105.033 27.24 333.458 252.714 27.25 333.458 252.714 27.26 333.458 252.714 27.27 333.458 252.714 27.28 337.332 252.714 27.29 337.332 252.714 27.3 337.332 252.714 27.31 337.332 252.714 27.32 337.332 249.811 105.033 27.33 337.332 249.811 105.033 27.34 333.458 249.811 105.033 27.35 333.458 249.811 105.033 27.36 333.458 249.811 105.033 27.37 333.458 249.811 105.033 27.38 249.811 105.033 27.39 249.811 105.033 27.4 249.811 105.033 27.41 249.811 105.033 27.42 252.714 105.033 27.43 252.714 105.033 27.44 252.714 105.033 27.45 252.714 105.033 27.46 105.033 27.47 105.033 27.48 105.033 27.49 105.033 27.5 27.51 27.52 27.53 27.54 99.1376 27.55 99.1376 27.56 99.1376 27.57 99.1376 27.58 99.1376 27.59 99.1376 27.6 99.1376 27.61 99.1376 27.62 99.1376 27.63 99.1376 27.64 99.1376 27.65 99.1376 27.66 99.1376 27.67 99.1376 27.68 99.1376 27.69 99.1376 27.7 99.1376 27.71 99.1376 27.72 99.1376 27.73 99.1376 27.74 99.1376 27.75 99.1376 27.76 99.1376 27.77 99.1376 27.78 99.1376 27.79 99.1376 27.8 99.1376 27.81 99.1376 27.82 99.1376 27.83 99.1376 27.84 99.1376 27.85 99.1376 27.86 99.1376 27.87 99.1376 27.88 99.1376 27.89 99.1376 27.9 99.1376 27.91 99.1376 27.92 99.1376 27.93 99.1376 27.94 99.1376 27.95 99.1376 27.96 99.1376 27.97 99.1376 27.98 99.1376 27.99 99.1376 28.0 99.1376 28.01 99.1376 28.02 99.1376 28.03 99.1376 28.04 99.1376 28.05 99.1376 28.06 99.1376 28.07 99.1376 28.08 99.1376 28.09 99.1376 28.1 99.1376 28.11 99.1376 28.12 99.1376 28.13 99.1376 28.14 99.1376 235.79 28.15 99.1376 235.79 28.16 99.1376 235.79 28.17 99.1376 235.79 28.18 99.1376 235.79 28.19 99.1376 235.79 28.2 99.1376 235.79 28.21 99.1376 235.79 28.22 99.1376 235.79 28.23 99.1376 235.79 28.24 99.1376 235.79 28.25 99.1376 235.79 28.26 99.1376 235.79 28.27 99.1376 235.79 28.28 99.1376 28.29 99.1376 28.3 99.1376 28.31 99.1376 28.32 99.1376 28.33 99.1376 28.34 99.1376 28.35 99.1376 28.36 99.1376 28.37 99.1376 28.38 99.1376 28.39 99.1376 28.4 99.1376 622.254 28.41 99.1376 622.254 28.42 99.1376 622.254 28.43 99.1376 622.254 28.44 99.1376 622.254 28.45 99.1376 622.254 28.46 99.1376 629.484 28.47 99.1376 629.484 28.48 99.1376 629.484 28.49 99.1376 629.484 28.5 99.1376 629.484 28.51 99.1376 629.484 28.52 99.1376 636.799 28.53 99.1376 636.799 28.54 99.1376 636.799 28.55 99.1376 636.799 28.56 99.1376 28.57 99.1376 28.58 99.1376 28.59 99.1376 28.6 99.1376 28.61 99.1376 28.62 99.1376 28.63 99.1376 28.64 99.1376 28.65 99.1376 28.66 99.1376 28.67 99.1376 28.68 28.69 28.7 28.71 28.72 105.033 28.73 105.033 28.74 105.033 28.75 105.033 28.76 105.033 622.254 28.77 105.033 622.254 28.78 105.033 622.254 28.79 105.033 622.254 28.8 105.033 622.254 28.81 105.033 622.254 28.82 105.033 622.254 28.83 105.033 622.254 28.84 629.484 105.033 28.85 629.484 105.033 28.86 629.484 105.033 28.87 629.484 105.033 28.88 105.033 28.89 105.033 28.9 314.742 105.033 28.91 314.742 105.033 28.92 314.742 105.033 622.254 28.93 314.742 105.033 622.254 28.94 314.742 105.033 622.254 28.95 314.742 105.033 622.254 28.96 314.742 105.033 622.254 28.97 314.742 105.033 622.254 28.98 314.742 105.033 615.107 28.99 314.742 105.033 615.107 29.0 314.742 105.033 615.107 29.01 314.742 105.033 615.107 29.02 615.107 29.03 615.107 29.04 629.484 29.05 629.484 29.06 629.484 29.07 629.484 29.08 629.484 311.127 29.09 629.484 311.127 29.1 311.127 622.254 29.11 311.127 622.254 29.12 311.127 622.254 29.13 311.127 622.254 29.14 311.127 29.15 311.127 29.16 311.127 29.17 311.127 29.18 311.127 29.19 311.127 29.2 311.127 29.21 311.127 29.22 311.127 29.23 311.127 29.24 311.127 29.25 311.127 29.26 314.742 29.27 314.742 29.28 314.742 29.29 314.742 29.3 314.742 29.31 314.742 29.32 314.742 622.254 29.33 314.742 622.254 29.34 314.742 622.254 29.35 314.742 622.254 29.36 622.254 29.37 622.254 29.38 629.484 29.39 629.484 29.4 629.484 29.41 629.484 29.42 629.484 29.43 629.484 29.44 29.45 29.46 29.47 29.48 29.49 29.5 29.51 29.52 29.53 29.54 29.55 29.56 29.57 29.58 29.59 29.6 29.61 29.62 29.63 29.64 29.65 29.66 29.67 29.68 29.69 29.7 29.71 29.72 29.73 29.74 29.75 29.76 29.77 29.78 29.79 29.8 29.81 29.82 29.83 29.84 29.85 29.86 29.87 29.88 29.89 29.9 29.91 29.92 29.93 29.94 29.95 29.96 29.97 29.98 29.99 30.0 30.01 30.02 30.03 30.04 30.05 30.06 30.07 30.08 30.09 30.1 30.11 30.12 529.331 30.13 529.331 30.14 529.331 30.15 529.331 30.16 529.331 30.17 529.331 30.18 529.331 30.19 529.331 mir_eval-0.8.2/tests/data/multipitch/est04.txt000066400000000000000000001731051475740344600213010ustar00rootroot000000000000000.0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.2 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.3 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.4 0.41 0.42 222.556 0.43 222.556 0.44 445.113 222.556 0.45 445.113 222.556 0.46 445.113 222.556 0.47 445.113 222.556 0.48 445.113 222.556 0.49 445.113 222.556 0.5 445.113 222.556 0.51 445.113 222.556 0.52 445.113 222.556 0.53 445.113 222.556 0.54 445.113 220 0.55 445.113 220 0.56 445.113 220 0.57 445.113 220 0.58 445.113 220 0.59 445.113 220 0.6 445.113 222.556 0.61 445.113 222.556 0.62 445.113 222.556 0.63 445.113 222.556 0.64 445.113 222.556 0.65 445.113 222.556 0.66 445.113 222.556 0.67 445.113 222.556 0.68 445.113 222.556 0.69 445.113 222.556 0.7 445.113 222.556 0.71 445.113 222.556 0.72 222.556 450.285 0.73 222.556 450.285 0.74 222.556 450.285 0.75 222.556 450.285 0.76 222.556 450.285 0.77 222.556 450.285 0.78 445.113 222.556 0.79 445.113 222.556 0.8 445.113 220 0.81 445.113 220 0.82 445.113 220 0.83 445.113 220 0.84 445.113 220 0.85 445.113 220 0.86 445.113 222.556 0.87 445.113 222.556 0.88 222.556 450.285 0.89 222.556 450.285 0.9 222.556 450.285 0.91 222.556 450.285 0.92 222.556 450.285 0.93 222.556 450.285 0.94 220 440 0.95 220 440 0.96 220 440 0.97 220 440 0.98 220 440 0.99 220 440 1.0 220 445.113 1.01 220 445.113 1.02 220 445.113 1.03 220 445.113 1.04 220 445.113 1.05 220 445.113 1.06 220 445.113 1.07 220 445.113 1.08 220 445.113 1.09 220 445.113 1.1 220 445.113 1.11 220 445.113 1.12 220 445.113 1.13 220 445.113 1.14 220 445.113 1.15 220 445.113 1.16 220 445.113 1.17 220 445.113 1.18 220 445.113 1.19 220 445.113 1.2 445.113 222.556 1.21 445.113 222.556 1.22 445.113 222.556 1.23 445.113 222.556 1.24 445.113 222.556 1.25 445.113 222.556 1.26 445.113 222.556 1.27 445.113 222.556 1.28 220 450.285 1.29 220 450.285 1.3 220 450.285 1.31 220 450.285 1.32 220 261.626 450.285 1.33 220 261.626 450.285 1.34 220 261.626 535.482 445.113 1.35 220 261.626 535.482 445.113 1.36 220 261.626 535.482 445.113 1.37 220 261.626 535.482 445.113 1.38 220 535.482 264.666 445.113 1.39 220 535.482 264.666 445.113 1.4 529.331 264.666 445.113 1.41 529.331 264.666 445.113 1.42 529.331 264.666 445.113 1.43 529.331 264.666 445.113 1.44 529.331 264.666 445.113 1.45 529.331 264.666 445.113 1.46 529.331 264.666 445.113 1.47 529.331 264.666 445.113 1.48 529.331 264.666 445.113 1.49 529.331 264.666 445.113 1.5 529.331 264.666 445.113 1.51 529.331 264.666 445.113 1.52 529.331 264.666 445.113 1.53 529.331 264.666 445.113 1.54 529.331 264.666 445.113 1.55 529.331 264.666 445.113 1.56 529.331 264.666 1.57 529.331 264.666 1.58 529.331 264.666 1.59 529.331 264.666 1.6 529.331 264.666 1.61 529.331 264.666 1.62 529.331 264.666 1.63 529.331 264.666 1.64 529.331 264.666 1.65 529.331 264.666 1.66 529.331 264.666 1.67 529.331 264.666 1.68 529.331 264.666 1.69 529.331 264.666 1.7 529.331 264.666 1.71 529.331 264.666 1.72 529.331 264.666 1.73 529.331 264.666 1.74 529.331 264.666 1.75 529.331 264.666 1.76 529.331 267.741 1.77 529.331 267.741 1.78 529.331 267.741 333.458 1.79 529.331 267.741 333.458 1.8 267.741 333.458 535.482 1.81 267.741 333.458 535.482 1.82 333.458 264.666 535.482 1.83 333.458 264.666 535.482 1.84 337.332 264.666 1.85 337.332 264.666 1.86 337.332 264.666 1.87 337.332 264.666 1.88 337.332 264.666 1.89 337.332 264.666 1.9 337.332 264.666 1.91 337.332 264.666 1.92 337.332 264.666 1.93 337.332 264.666 1.94 333.458 168.666 264.666 1.95 333.458 168.666 264.666 1.96 168.666 264.666 1.97 168.666 264.666 1.98 333.458 168.666 264.666 1.99 333.458 168.666 264.666 2.0 333.458 168.666 2.01 333.458 168.666 2.02 333.458 168.666 2.03 333.458 168.666 2.04 341.252 337.332 168.666 2.05 341.252 337.332 168.666 2.06 341.252 337.332 168.666 2.07 341.252 337.332 168.666 2.08 341.252 337.332 168.666 2.09 341.252 337.332 168.666 2.1 341.252 166.729 337.332 2.11 341.252 166.729 337.332 2.12 333.458 341.252 166.729 2.13 333.458 341.252 166.729 2.14 333.458 166.729 357.391 2.15 333.458 166.729 357.391 2.16 333.458 168.666 2.17 333.458 168.666 2.18 333.458 168.666 2.19 333.458 168.666 2.2 168.666 337.332 2.21 168.666 337.332 2.22 168.666 337.332 2.23 168.666 337.332 2.24 168.666 337.332 2.25 168.666 337.332 2.26 333.458 168.666 2.27 333.458 168.666 2.28 333.458 168.666 2.29 333.458 168.666 2.3 333.458 168.666 2.31 333.458 168.666 2.32 333.458 166.729 2.33 333.458 166.729 2.34 166.729 337.332 2.35 166.729 337.332 2.36 166.729 337.332 2.37 166.729 337.332 2.38 337.332 168.666 2.39 337.332 168.666 2.4 168.666 2.41 168.666 2.42 333.458 168.666 2.43 333.458 168.666 2.44 333.458 168.666 2.45 333.458 168.666 2.46 166.729 333.458 2.47 166.729 333.458 2.48 166.729 333.458 2.49 166.729 333.458 2.5 166.729 333.458 2.51 166.729 333.458 2.52 333.458 168.666 2.53 333.458 168.666 2.54 333.458 168.666 2.55 333.458 168.666 2.56 333.458 168.666 2.57 333.458 168.666 2.58 333.458 168.666 2.59 333.458 168.666 2.6 333.458 168.666 2.61 333.458 168.666 2.62 333.458 168.666 2.63 333.458 168.666 2.64 333.458 168.666 2.65 333.458 168.666 2.66 333.458 2.67 333.458 2.68 333.458 2.69 333.458 2.7 333.458 2.71 333.458 2.72 337.332 2.73 337.332 2.74 337.332 2.75 337.332 2.76 337.332 2.77 337.332 2.78 329.628 168.666 2.79 329.628 168.666 2.8 329.628 168.666 2.81 329.628 168.666 2.82 329.628 168.666 2.83 329.628 168.666 2.84 333.458 168.666 2.85 333.458 168.666 2.86 333.458 168.666 2.87 333.458 168.666 2.88 333.458 168.666 2.89 333.458 168.666 2.9 337.332 168.666 2.91 337.332 168.666 2.92 168.666 2.93 168.666 2.94 333.458 168.666 2.95 333.458 168.666 2.96 333.458 168.666 2.97 333.458 168.666 2.98 333.458 168.666 2.99 333.458 168.666 3.0 333.458 168.666 3.01 333.458 168.666 3.02 337.332 168.666 3.03 337.332 168.666 3.04 178.696 337.332 168.666 3.05 178.696 337.332 168.666 3.06 178.696 337.332 168.666 3.07 178.696 337.332 168.666 3.08 178.696 333.458 349.228 168.666 3.09 178.696 333.458 349.228 168.666 3.1 178.696 333.458 349.228 168.666 3.11 178.696 333.458 349.228 168.666 3.12 178.696 333.458 349.228 168.666 3.13 178.696 333.458 349.228 168.666 3.14 178.696 168.666 353.286 3.15 178.696 168.666 353.286 3.16 178.696 168.666 353.286 3.17 178.696 168.666 353.286 3.18 178.696 168.666 353.286 3.19 178.696 168.666 353.286 3.2 178.696 168.666 353.286 3.21 178.696 168.666 353.286 3.22 176.643 353.286 3.23 176.643 353.286 3.24 176.643 353.286 3.25 176.643 353.286 3.26 176.643 353.286 3.27 176.643 353.286 3.28 176.643 353.286 3.29 176.643 353.286 3.3 176.643 353.286 3.31 176.643 353.286 3.32 333.458 357.391 176.643 3.33 333.458 357.391 176.643 3.34 333.458 357.391 176.643 3.35 333.458 357.391 176.643 3.36 168.666 333.458 357.391 176.643 3.37 168.666 333.458 357.391 176.643 3.38 178.696 341.252 168.666 337.332 3.39 178.696 341.252 168.666 337.332 3.4 178.696 341.252 168.666 337.332 3.41 178.696 341.252 168.666 337.332 3.42 178.696 341.252 168.666 337.332 3.43 178.696 341.252 168.666 337.332 3.44 178.696 341.252 168.666 337.332 3.45 178.696 341.252 168.666 337.332 3.46 178.696 341.252 168.666 3.47 178.696 341.252 168.666 3.48 178.696 341.252 3.49 178.696 341.252 3.5 170.626 3.51 170.626 3.52 170.626 3.53 170.626 3.54 170.626 297.077 3.55 170.626 297.077 3.56 170.626 297.077 3.57 170.626 297.077 3.58 297.077 3.59 297.077 3.6 300.529 3.61 300.529 3.62 300.529 3.63 300.529 3.64 300.529 3.65 300.529 3.66 297.077 3.67 297.077 3.68 261.626 297.077 3.69 261.626 297.077 3.7 261.626 297.077 3.71 261.626 297.077 3.72 261.626 300.529 3.73 261.626 300.529 3.74 264.666 300.529 3.75 264.666 300.529 3.76 264.666 300.529 3.77 264.666 300.529 3.78 264.666 3.79 264.666 3.8 261.626 535.482 3.81 261.626 535.482 3.82 261.626 535.482 3.83 261.626 535.482 3.84 261.626 535.482 3.85 261.626 535.482 3.86 267.741 529.331 3.87 267.741 529.331 3.88 267.741 529.331 3.89 267.741 529.331 3.9 267.741 529.331 3.91 267.741 529.331 3.92 267.741 529.331 3.93 267.741 529.331 3.94 267.741 529.331 3.95 267.741 529.331 3.96 267.741 529.331 3.97 267.741 529.331 3.98 267.741 529.331 3.99 267.741 529.331 4.0 267.741 4.01 267.741 4.02 267.741 4.03 267.741 4.04 267.741 4.05 267.741 4.06 4.07 4.08 4.09 4.1 220 4.11 220 4.12 220 4.13 220 4.14 220 4.15 220 4.16 445.113 222.556 4.17 445.113 222.556 4.18 445.113 222.556 4.19 445.113 222.556 4.2 445.113 222.556 4.21 445.113 222.556 4.22 445.113 222.556 4.23 445.113 222.556 4.24 445.113 222.556 4.25 445.113 222.556 4.26 222.556 450.285 4.27 222.556 450.285 4.28 222.556 4.29 222.556 4.3 222.556 4.31 222.556 4.32 222.556 4.33 222.556 4.34 445.113 222.556 4.35 445.113 222.556 4.36 445.113 222.556 4.37 445.113 222.556 4.38 445.113 112.571 222.556 4.39 445.113 112.571 222.556 4.4 445.113 112.571 222.556 4.41 445.113 112.571 222.556 4.42 112.571 222.556 450.285 4.43 112.571 222.556 450.285 4.44 111.278 222.556 450.285 4.45 111.278 222.556 450.285 4.46 111.278 222.556 450.285 4.47 111.278 222.556 450.285 4.48 111.278 220 445.113 4.49 111.278 220 445.113 4.5 111.278 220 445.113 4.51 111.278 220 445.113 4.52 220 112.571 445.113 4.53 220 112.571 445.113 4.54 112.571 222.556 445.113 4.55 112.571 222.556 445.113 4.56 112.571 222.556 445.113 4.57 112.571 222.556 445.113 4.58 112.571 222.556 450.285 4.59 112.571 222.556 450.285 4.6 112.571 222.556 450.285 4.61 112.571 222.556 450.285 4.62 111.278 222.556 450.285 4.63 111.278 222.556 450.285 4.64 111.278 440 222.556 4.65 111.278 440 222.556 4.66 111.278 440 222.556 4.67 111.278 440 222.556 4.68 111.278 440 222.556 4.69 111.278 440 222.556 4.7 445.113 112.571 222.556 4.71 445.113 112.571 222.556 4.72 445.113 112.571 222.556 4.73 445.113 112.571 222.556 4.74 445.113 112.571 220 4.75 445.113 112.571 220 4.76 445.113 112.571 220 4.77 445.113 112.571 220 4.78 440 111.278 220 4.79 440 111.278 220 4.8 440 111.278 220 4.81 440 111.278 220 4.82 111.278 222.556 4.83 111.278 222.556 4.84 112.571 222.556 4.85 112.571 222.556 4.86 112.571 222.556 4.87 112.571 222.556 4.88 220 112.571 4.89 220 112.571 4.9 220 112.571 450.285 4.91 220 112.571 450.285 4.92 220 112.571 450.285 4.93 220 112.571 450.285 4.94 220 112.571 450.285 4.95 220 112.571 450.285 4.96 445.113 111.278 222.556 4.97 445.113 111.278 222.556 4.98 445.113 111.278 222.556 4.99 445.113 111.278 222.556 5.0 445.113 111.278 222.556 5.01 445.113 111.278 222.556 5.02 445.113 112.571 222.556 5.03 445.113 112.571 222.556 5.04 445.113 112.571 222.556 5.05 445.113 112.571 222.556 5.06 445.113 112.571 222.556 5.07 445.113 112.571 222.556 5.08 445.113 112.571 222.556 5.09 445.113 112.571 222.556 5.1 445.113 112.571 222.556 5.11 445.113 112.571 222.556 5.12 445.113 112.571 222.556 5.13 445.113 112.571 222.556 5.14 445.113 112.571 222.556 5.15 445.113 112.571 222.556 5.16 445.113 112.571 220 5.17 445.113 112.571 220 5.18 445.113 112.571 220 5.19 445.113 112.571 220 5.2 107.488 220 5.21 107.488 220 5.22 225.142 107.488 5.23 225.142 107.488 5.24 225.142 107.488 5.25 225.142 107.488 5.26 225.142 107.488 5.27 225.142 107.488 5.28 225.142 107.488 5.29 225.142 107.488 5.3 107.488 222.556 5.31 107.488 222.556 5.32 107.488 222.556 5.33 107.488 222.556 5.34 107.488 222.556 5.35 107.488 222.556 5.36 107.488 222.556 5.37 107.488 222.556 5.38 222.556 5.39 222.556 5.4 222.556 5.41 222.556 5.42 222.556 5.43 222.556 5.44 225.142 5.45 225.142 5.46 5.47 5.48 5.49 5.5 425.012 5.51 425.012 5.52 425.012 5.53 425.012 5.54 425.012 5.55 425.012 5.56 425.012 5.57 425.012 5.58 425.012 83.3644 5.59 425.012 83.3644 5.6 425.012 83.3644 5.61 425.012 83.3644 5.62 425.012 83.3644 5.63 425.012 83.3644 5.64 83.3644 5.65 83.3644 5.66 83.3644 5.67 83.3644 5.68 84.3331 252.714 5.69 84.3331 252.714 5.7 84.3331 252.714 5.71 84.3331 252.714 5.72 84.3331 252.714 5.73 84.3331 252.714 5.74 84.3331 252.714 5.75 84.3331 252.714 5.76 84.3331 252.714 5.77 84.3331 252.714 5.78 84.3331 252.714 5.79 84.3331 252.714 5.8 84.3331 5.81 84.3331 5.82 84.3331 5.83 84.3331 5.84 84.3331 5.85 84.3331 5.86 84.3331 5.87 84.3331 5.88 84.3331 5.89 84.3331 5.9 84.3331 5.91 84.3331 5.92 84.3331 5.93 84.3331 5.94 84.3331 5.95 84.3331 5.96 84.3331 5.97 84.3331 5.98 84.3331 5.99 84.3331 6.0 84.3331 6.01 84.3331 6.02 84.3331 6.03 84.3331 6.04 84.3331 6.05 84.3331 6.06 84.3331 6.07 84.3331 6.08 84.3331 6.09 84.3331 6.1 84.3331 6.11 84.3331 6.12 84.3331 6.13 84.3331 6.14 84.3331 6.15 84.3331 6.16 84.3331 6.17 84.3331 6.18 84.3331 6.19 84.3331 6.2 84.3331 6.21 84.3331 6.22 84.3331 6.23 84.3331 6.24 84.3331 6.25 84.3331 6.26 84.3331 6.27 84.3331 6.28 84.3331 6.29 84.3331 6.3 84.3331 6.31 84.3331 6.32 84.3331 6.33 84.3331 6.34 84.3331 6.35 84.3331 6.36 84.3331 6.37 84.3331 6.38 84.3331 6.39 84.3331 6.4 84.3331 6.41 84.3331 6.42 84.3331 6.43 84.3331 6.44 84.3331 6.45 84.3331 6.46 84.3331 6.47 84.3331 6.48 83.3644 6.49 83.3644 6.5 83.3644 6.51 83.3644 6.52 420.13 83.3644 6.53 420.13 83.3644 6.54 420.13 83.3644 252.714 6.55 420.13 83.3644 252.714 6.56 420.13 83.3644 252.714 6.57 420.13 83.3644 252.714 6.58 425.012 83.3644 252.714 6.59 425.012 83.3644 252.714 6.6 425.012 168.666 83.3644 252.714 6.61 425.012 168.666 83.3644 252.714 6.62 425.012 168.666 83.3644 252.714 6.63 425.012 168.666 83.3644 252.714 6.64 168.666 83.3644 252.714 6.65 168.666 83.3644 252.714 6.66 168.666 83.3644 252.714 6.67 168.666 83.3644 252.714 6.68 168.666 83.3644 252.714 6.69 168.666 83.3644 252.714 6.7 168.666 83.3644 252.714 6.71 168.666 83.3644 252.714 6.72 168.666 83.3644 252.714 6.73 168.666 83.3644 252.714 6.74 168.666 83.3644 252.714 6.75 168.666 83.3644 252.714 6.76 168.666 252.714 6.77 168.666 252.714 6.78 168.666 252.714 6.79 168.666 252.714 6.8 93.5734 168.666 252.714 6.81 93.5734 168.666 252.714 6.82 93.5734 168.666 252.714 6.83 93.5734 168.666 252.714 6.84 93.5734 168.666 252.714 6.85 93.5734 168.666 252.714 6.86 94.6607 83.3644 252.714 6.87 94.6607 83.3644 252.714 6.88 94.6607 83.3644 252.714 6.89 94.6607 83.3644 252.714 6.9 94.6607 83.3644 252.714 6.91 94.6607 83.3644 252.714 6.92 93.5734 83.3644 252.714 6.93 93.5734 83.3644 252.714 6.94 93.5734 84.3331 6.95 93.5734 84.3331 6.96 93.5734 84.3331 6.97 93.5734 84.3331 6.98 93.5734 84.3331 6.99 93.5734 84.3331 7.0 93.5734 84.3331 7.01 93.5734 84.3331 7.02 93.5734 7.03 93.5734 7.04 93.5734 168.666 7.05 93.5734 168.666 7.06 93.5734 168.666 7.07 93.5734 168.666 7.08 93.5734 168.666 7.09 93.5734 168.666 7.1 93.5734 168.666 7.11 93.5734 168.666 7.12 93.5734 168.666 7.13 93.5734 168.666 7.14 93.5734 168.666 7.15 93.5734 168.666 7.16 93.5734 168.666 7.17 93.5734 168.666 7.18 93.5734 168.666 7.19 93.5734 168.666 7.2 93.5734 7.21 93.5734 7.22 220 93.5734 7.23 220 93.5734 7.24 220 93.5734 7.25 220 93.5734 7.26 220 93.5734 7.27 220 93.5734 7.28 93.5734 222.556 7.29 93.5734 222.556 7.3 93.5734 222.556 7.31 93.5734 222.556 7.32 93.5734 222.556 7.33 93.5734 222.556 7.34 93.5734 222.556 7.35 93.5734 222.556 7.36 93.5734 222.556 7.37 93.5734 222.556 7.38 189.321 93.5734 222.556 7.39 189.321 93.5734 222.556 7.4 189.321 93.5734 222.556 7.41 189.321 93.5734 222.556 7.42 189.321 93.5734 222.556 7.43 189.321 93.5734 222.556 7.44 189.321 93.5734 222.556 7.45 189.321 93.5734 222.556 7.46 189.321 93.5734 690.434 222.556 7.47 189.321 93.5734 690.434 222.556 7.48 189.321 93.5734 690.434 222.556 7.49 189.321 93.5734 690.434 222.556 7.5 189.321 93.5734 690.434 222.556 7.51 189.321 93.5734 690.434 222.556 7.52 682.504 189.321 93.5734 222.556 7.53 682.504 189.321 93.5734 222.556 7.54 682.504 187.147 7.55 682.504 187.147 7.56 682.504 93.5734 7.57 682.504 93.5734 7.58 93.5734 7.59 93.5734 7.6 93.5734 280.403 7.61 93.5734 280.403 7.62 93.5734 280.403 7.63 93.5734 280.403 7.64 445.113 93.5734 280.403 7.65 445.113 93.5734 280.403 7.66 445.113 93.5734 280.403 7.67 445.113 93.5734 280.403 7.68 445.113 93.5734 333.458 280.403 7.69 445.113 93.5734 333.458 280.403 7.7 445.113 93.5734 333.458 280.403 7.71 445.113 93.5734 333.458 280.403 7.72 445.113 93.5734 333.458 280.403 7.73 445.113 93.5734 333.458 280.403 7.74 445.113 93.5734 333.458 280.403 7.75 445.113 93.5734 333.458 280.403 7.76 445.113 93.5734 333.458 280.403 7.77 445.113 93.5734 333.458 280.403 7.78 445.113 93.5734 333.458 280.403 7.79 445.113 93.5734 333.458 280.403 7.8 445.113 93.5734 333.458 280.403 7.81 445.113 93.5734 333.458 280.403 7.82 93.5734 333.458 280.403 7.83 93.5734 333.458 280.403 7.84 93.5734 333.458 7.85 93.5734 333.458 7.86 93.5734 333.458 7.87 93.5734 333.458 7.88 93.5734 337.332 7.89 93.5734 337.332 7.9 93.5734 337.332 7.91 93.5734 337.332 7.92 93.5734 7.93 93.5734 7.94 93.5734 7.95 93.5734 7.96 93.5734 7.97 93.5734 7.98 93.5734 105.033 7.99 93.5734 105.033 8.0 93.5734 105.033 8.01 93.5734 105.033 8.02 93.5734 105.033 8.03 93.5734 105.033 8.04 210.065 106.253 93.5734 189.321 8.05 210.065 106.253 93.5734 189.321 8.06 210.065 106.253 93.5734 189.321 8.07 210.065 106.253 93.5734 189.321 8.08 210.065 106.253 189.321 8.09 210.065 106.253 189.321 8.1 210.065 106.253 314.742 189.321 8.11 210.065 106.253 314.742 189.321 8.12 210.065 106.253 314.742 189.321 8.13 210.065 106.253 314.742 189.321 8.14 210.065 106.253 314.742 189.321 8.15 210.065 106.253 314.742 189.321 8.16 210.065 106.253 314.742 8.17 210.065 106.253 314.742 8.18 210.065 106.253 314.742 8.19 210.065 106.253 314.742 8.2 210.065 106.253 314.742 8.21 210.065 106.253 314.742 8.22 210.065 106.253 314.742 8.23 210.065 106.253 314.742 8.24 210.065 106.253 314.742 8.25 210.065 106.253 314.742 8.26 210.065 106.253 314.742 8.27 210.065 106.253 314.742 8.28 210.065 106.253 314.742 8.29 210.065 106.253 314.742 8.3 210.065 106.253 314.742 8.31 210.065 106.253 314.742 8.32 210.065 106.253 314.742 8.33 210.065 106.253 314.742 8.34 210.065 106.253 314.742 8.35 210.065 106.253 314.742 8.36 210.065 252.714 8.37 210.065 252.714 8.38 210.065 252.714 8.39 210.065 252.714 8.4 210.065 252.714 8.41 210.065 252.714 8.42 210.065 252.714 8.43 210.065 252.714 8.44 210.065 252.714 8.45 210.065 252.714 8.46 210.065 252.714 8.47 210.065 252.714 8.48 210.065 252.714 8.49 210.065 252.714 8.5 210.065 252.714 8.51 210.065 252.714 8.52 210.065 252.714 8.53 210.065 252.714 8.54 210.065 252.714 8.55 210.065 252.714 8.56 210.065 252.714 8.57 210.065 252.714 8.58 212.506 252.714 8.59 212.506 252.714 8.6 212.506 690.434 252.714 8.61 212.506 690.434 252.714 8.62 212.506 690.434 252.714 8.63 212.506 690.434 252.714 8.64 210.065 690.434 252.714 8.65 210.065 690.434 252.714 8.66 210.065 682.504 252.714 8.67 210.065 682.504 252.714 8.68 210.065 682.504 252.714 8.69 210.065 682.504 252.714 8.7 682.504 212.506 252.714 8.71 682.504 212.506 252.714 8.72 106.253 252.714 8.73 106.253 252.714 8.74 106.253 166.729 252.714 8.75 106.253 166.729 252.714 8.76 106.253 166.729 252.714 8.77 106.253 166.729 252.714 8.78 106.253 166.729 252.714 8.79 106.253 166.729 252.714 8.8 106.253 166.729 337.332 252.714 8.81 106.253 166.729 337.332 252.714 8.82 106.253 166.729 337.332 252.714 8.83 106.253 166.729 337.332 252.714 8.84 106.253 166.729 337.332 252.714 8.85 106.253 166.729 337.332 252.714 8.86 106.253 166.729 337.332 252.714 8.87 106.253 166.729 337.332 252.714 8.88 106.253 166.729 337.332 252.714 8.89 106.253 166.729 337.332 252.714 8.9 106.253 166.729 337.332 252.714 8.91 106.253 166.729 337.332 252.714 8.92 106.253 166.729 337.332 252.714 8.93 106.253 166.729 337.332 252.714 8.94 166.729 337.332 252.714 8.95 166.729 337.332 252.714 8.96 166.729 337.332 252.714 8.97 166.729 337.332 252.714 8.98 166.729 337.332 252.714 8.99 166.729 337.332 252.714 9.0 210.065 252.714 9.01 210.065 252.714 9.02 210.065 107.488 252.714 505.427 9.03 210.065 107.488 252.714 505.427 9.04 210.065 107.488 252.714 505.427 9.05 210.065 107.488 252.714 505.427 9.06 210.065 107.488 252.714 505.427 9.07 210.065 107.488 252.714 505.427 9.08 210.065 107.488 252.714 505.427 9.09 210.065 107.488 252.714 505.427 9.1 210.065 107.488 499.622 9.11 210.065 107.488 499.622 9.12 210.065 107.488 499.622 9.13 210.065 107.488 499.622 9.14 210.065 107.488 9.15 210.065 107.488 9.16 111.278 212.506 9.17 111.278 212.506 9.18 111.278 212.506 9.19 111.278 212.506 9.2 111.278 212.506 9.21 111.278 212.506 9.22 210.065 112.571 9.23 210.065 112.571 9.24 210.065 112.571 9.25 210.065 112.571 9.26 112.571 9.27 112.571 9.28 111.278 529.331 9.29 111.278 529.331 9.3 111.278 529.331 9.31 111.278 529.331 9.32 111.278 529.331 249.811 9.33 111.278 529.331 249.811 9.34 111.278 249.811 517.241 9.35 111.278 249.811 517.241 9.36 111.278 249.811 222.556 517.241 9.37 111.278 249.811 222.556 517.241 9.38 111.278 222.556 517.241 252.714 9.39 111.278 222.556 517.241 252.714 9.4 111.278 529.331 337.332 222.556 252.714 9.41 111.278 529.331 337.332 222.556 252.714 9.42 111.278 529.331 337.332 222.556 252.714 9.43 111.278 529.331 337.332 222.556 252.714 9.44 111.278 529.331 337.332 222.556 9.45 111.278 529.331 337.332 222.556 9.46 111.278 529.331 333.458 222.556 9.47 111.278 529.331 333.458 222.556 9.48 111.278 523.251 333.458 222.556 9.49 111.278 523.251 333.458 222.556 9.5 111.278 523.251 333.458 264.666 222.556 9.51 111.278 523.251 333.458 264.666 222.556 9.52 111.278 523.251 333.458 264.666 222.556 9.53 111.278 523.251 333.458 264.666 222.556 9.54 523.251 333.458 264.666 222.556 9.55 523.251 333.458 264.666 222.556 9.56 529.331 333.458 264.666 222.556 9.57 529.331 333.458 264.666 222.556 9.58 529.331 333.458 264.666 222.556 9.59 529.331 333.458 264.666 222.556 9.6 529.331 333.458 264.666 222.556 9.61 529.331 333.458 264.666 222.556 9.62 529.331 333.458 264.666 222.556 9.63 529.331 333.458 264.666 222.556 9.64 523.251 333.458 264.666 222.556 9.65 523.251 333.458 264.666 222.556 9.66 523.251 264.666 222.556 9.67 523.251 264.666 222.556 9.68 523.251 264.666 222.556 9.69 523.251 264.666 222.556 9.7 523.251 264.666 222.556 9.71 523.251 264.666 222.556 9.72 523.251 264.666 222.556 9.73 523.251 264.666 222.556 9.74 523.251 264.666 222.556 9.75 523.251 264.666 222.556 9.76 523.251 264.666 222.556 9.77 523.251 264.666 222.556 9.78 523.251 264.666 252.714 9.79 523.251 264.666 252.714 9.8 264.666 252.714 9.81 264.666 252.714 9.82 264.666 252.714 9.83 264.666 252.714 9.84 264.666 333.458 252.714 9.85 264.666 333.458 252.714 9.86 267.741 333.458 252.714 9.87 267.741 333.458 252.714 9.88 267.741 333.458 252.714 9.89 267.741 333.458 252.714 9.9 267.741 333.458 252.714 9.91 267.741 333.458 252.714 9.92 264.666 337.332 252.714 9.93 264.666 337.332 252.714 9.94 166.729 264.666 337.332 9.95 166.729 264.666 337.332 9.96 166.729 264.666 9.97 166.729 264.666 9.98 166.729 264.666 9.99 166.729 264.666 10.0 166.729 264.666 10.01 166.729 264.666 10.02 166.729 264.666 10.03 166.729 264.666 10.04 166.729 264.666 10.05 166.729 264.666 10.06 261.626 166.729 10.07 261.626 166.729 10.08 261.626 166.729 10.09 261.626 166.729 10.1 261.626 166.729 10.11 261.626 166.729 10.12 261.626 166.729 10.13 261.626 166.729 10.14 261.626 166.729 10.15 261.626 166.729 10.16 261.626 168.666 10.17 261.626 168.666 10.18 261.626 168.666 10.19 261.626 168.666 10.2 168.666 10.21 168.666 10.22 168.666 10.23 168.666 10.24 168.666 10.25 168.666 10.26 168.666 10.27 168.666 10.28 168.666 10.29 168.666 10.3 168.666 10.31 168.666 10.32 168.666 10.33 168.666 10.34 168.666 10.35 168.666 10.36 168.666 10.37 168.666 10.38 88.3215 168.666 10.39 88.3215 168.666 10.4 88.3215 168.666 10.41 88.3215 168.666 10.42 88.3215 168.666 10.43 88.3215 168.666 10.44 88.3215 168.666 10.45 88.3215 168.666 10.46 88.3215 168.666 10.47 88.3215 168.666 10.48 88.3215 168.666 10.49 88.3215 168.666 10.5 88.3215 10.51 88.3215 10.52 88.3215 353.286 10.53 88.3215 353.286 10.54 88.3215 353.286 10.55 88.3215 353.286 10.56 88.3215 353.286 10.57 88.3215 353.286 10.58 88.3215 353.286 10.59 88.3215 353.286 10.6 88.3215 353.286 10.61 88.3215 353.286 10.62 88.3215 353.286 10.63 88.3215 353.286 10.64 88.3215 176.643 353.286 10.65 88.3215 176.643 353.286 10.66 88.3215 176.643 353.286 10.67 88.3215 176.643 353.286 10.68 88.3215 357.391 176.643 10.69 88.3215 357.391 176.643 10.7 88.3215 357.391 176.643 10.71 88.3215 357.391 176.643 10.72 88.3215 357.391 176.643 10.73 88.3215 357.391 176.643 10.74 88.3215 176.643 353.286 10.75 88.3215 176.643 353.286 10.76 88.3215 176.643 353.286 10.77 88.3215 176.643 353.286 10.78 88.3215 176.643 353.286 10.79 88.3215 176.643 353.286 10.8 88.3215 176.643 353.286 10.81 88.3215 176.643 353.286 10.82 88.3215 176.643 353.286 10.83 88.3215 176.643 353.286 10.84 88.3215 176.643 353.286 10.85 88.3215 176.643 353.286 10.86 88.3215 176.643 353.286 10.87 88.3215 176.643 353.286 10.88 88.3215 176.643 353.286 10.89 88.3215 176.643 353.286 10.9 88.3215 176.643 353.286 10.91 88.3215 176.643 353.286 10.92 88.3215 176.643 353.286 10.93 88.3215 176.643 353.286 10.94 88.3215 176.643 353.286 10.95 88.3215 176.643 353.286 10.96 88.3215 176.643 353.286 10.97 88.3215 176.643 353.286 10.98 112.571 88.3215 176.643 10.99 112.571 88.3215 176.643 11.0 112.571 88.3215 176.643 11.01 112.571 88.3215 176.643 11.02 112.571 88.3215 11.03 112.571 88.3215 11.04 112.571 88.3215 11.05 112.571 88.3215 11.06 112.571 11.07 112.571 11.08 112.571 450.285 11.09 112.571 450.285 11.1 110 450.285 11.11 110 450.285 11.12 110 450.285 11.13 110 450.285 11.14 110 450.285 11.15 110 450.285 11.16 110 450.285 11.17 110 450.285 11.18 445.113 110 11.19 445.113 110 11.2 445.113 264.666 11.21 445.113 264.666 11.22 264.666 11.23 264.666 11.24 264.666 11.25 264.666 11.26 264.666 11.27 264.666 11.28 264.666 11.29 264.666 11.3 264.666 11.31 264.666 11.32 264.666 11.33 264.666 11.34 264.666 11.35 264.666 11.36 264.666 11.37 264.666 11.38 264.666 11.39 264.666 11.4 264.666 11.41 264.666 11.42 264.666 11.43 264.666 11.44 264.666 11.45 264.666 11.46 264.666 535.482 11.47 264.666 535.482 11.48 264.666 535.482 11.49 264.666 535.482 11.5 267.741 535.482 11.51 267.741 535.482 11.52 267.741 529.331 11.53 267.741 529.331 11.54 267.741 529.331 11.55 267.741 529.331 11.56 267.741 529.331 11.57 267.741 529.331 11.58 267.741 83.3644 11.59 267.741 83.3644 11.6 267.741 83.3644 11.61 267.741 83.3644 11.62 267.741 83.3644 11.63 267.741 83.3644 11.64 84.3331 11.65 84.3331 11.66 84.3331 11.67 84.3331 11.68 84.3331 337.332 11.69 84.3331 337.332 11.7 84.3331 337.332 11.71 84.3331 337.332 11.72 84.3331 337.332 11.73 84.3331 337.332 11.74 333.458 84.3331 11.75 333.458 84.3331 11.76 333.458 84.3331 11.77 333.458 84.3331 11.78 333.458 84.3331 11.79 333.458 84.3331 11.8 333.458 84.3331 11.81 333.458 84.3331 11.82 84.3331 337.332 11.83 84.3331 337.332 11.84 84.3331 337.332 11.85 84.3331 337.332 11.86 84.3331 337.332 11.87 84.3331 337.332 11.88 333.458 84.3331 11.89 333.458 84.3331 11.9 333.458 84.3331 11.91 333.458 84.3331 11.92 333.458 84.3331 11.93 333.458 84.3331 11.94 84.3331 11.95 84.3331 11.96 84.3331 11.97 84.3331 11.98 84.3331 11.99 84.3331 12.0 84.3331 12.01 84.3331 12.02 84.3331 12.03 84.3331 12.04 84.3331 12.05 84.3331 12.06 84.3331 12.07 84.3331 12.08 84.3331 12.09 84.3331 12.1 84.3331 12.11 84.3331 12.12 84.3331 12.13 84.3331 12.14 84.3331 12.15 84.3331 12.16 225.142 84.3331 12.17 225.142 84.3331 12.18 225.142 84.3331 12.19 225.142 84.3331 12.2 225.142 84.3331 12.21 225.142 84.3331 12.22 84.3331 222.556 12.23 84.3331 222.556 12.24 84.3331 222.556 12.25 84.3331 222.556 12.26 445.113 84.3331 222.556 12.27 445.113 84.3331 222.556 12.28 445.113 84.3331 222.556 12.29 445.113 84.3331 222.556 12.3 445.113 84.3331 222.556 12.31 445.113 84.3331 222.556 12.32 445.113 222.556 12.33 445.113 222.556 12.34 445.113 267.741 12.35 445.113 267.741 12.36 267.741 450.285 12.37 267.741 450.285 12.38 267.741 12.39 267.741 12.4 264.666 12.41 264.666 12.42 264.666 12.43 264.666 12.44 264.666 12.45 264.666 12.46 264.666 12.47 264.666 12.48 264.666 12.49 264.666 12.5 264.666 12.51 264.666 12.52 264.666 12.53 264.666 12.54 264.666 12.55 264.666 12.56 264.666 12.57 264.666 12.58 264.666 12.59 264.666 12.6 264.666 12.61 264.666 12.62 264.666 12.63 264.666 12.64 264.666 535.482 12.65 264.666 535.482 12.66 264.666 535.482 12.67 264.666 535.482 12.68 264.666 535.482 12.69 264.666 535.482 12.7 264.666 535.482 12.71 264.666 535.482 12.72 529.331 264.666 12.73 529.331 264.666 12.74 529.331 267.741 12.75 529.331 267.741 12.76 529.331 267.741 12.77 529.331 267.741 12.78 267.741 12.79 267.741 12.8 12.81 12.82 12.83 12.84 78.6855 12.85 78.6855 12.86 78.6855 12.87 78.6855 12.88 78.6855 12.89 78.6855 12.9 79.5998 12.91 79.5998 12.92 80.5247 314.742 79.5998 12.93 80.5247 314.742 79.5998 12.94 80.5247 314.742 79.5998 12.95 80.5247 314.742 79.5998 12.96 80.5247 314.742 79.5998 12.97 80.5247 314.742 79.5998 12.98 80.5247 79.5998 311.127 12.99 80.5247 79.5998 311.127 13.0 80.5247 79.5998 311.127 13.01 80.5247 79.5998 311.127 13.02 80.5247 79.5998 311.127 13.03 80.5247 79.5998 311.127 13.04 80.5247 314.742 79.5998 13.05 80.5247 314.742 79.5998 13.06 80.5247 314.742 79.5998 13.07 80.5247 314.742 79.5998 13.08 80.5247 314.742 13.09 80.5247 314.742 13.1 80.5247 314.742 13.11 80.5247 314.742 13.12 80.5247 311.127 13.13 80.5247 311.127 13.14 80.5247 311.127 13.15 80.5247 311.127 13.16 80.5247 311.127 13.17 80.5247 311.127 13.18 80.5247 311.127 13.19 80.5247 311.127 13.2 80.5247 318.399 13.21 80.5247 318.399 13.22 80.5247 318.399 13.23 80.5247 318.399 13.24 80.5247 318.399 13.25 80.5247 318.399 13.26 80.5247 314.742 13.27 80.5247 314.742 13.28 80.5247 314.742 13.29 80.5247 314.742 13.3 80.5247 314.742 13.31 80.5247 314.742 13.32 80.5247 314.742 13.33 80.5247 314.742 13.34 80.5247 314.742 13.35 80.5247 314.742 13.36 80.5247 314.742 13.37 80.5247 314.742 13.38 80.5247 314.742 13.39 80.5247 314.742 13.4 80.5247 314.742 13.41 80.5247 314.742 13.42 80.5247 314.742 13.43 80.5247 314.742 13.44 80.5247 314.742 13.45 80.5247 314.742 13.46 80.5247 314.742 13.47 80.5247 314.742 13.48 80.5247 314.742 13.49 80.5247 314.742 13.5 80.5247 314.742 13.51 80.5247 314.742 13.52 80.5247 311.127 13.53 80.5247 311.127 13.54 80.5247 13.55 80.5247 13.56 80.5247 13.57 80.5247 13.58 80.5247 535.482 13.59 80.5247 535.482 13.6 80.5247 535.482 13.61 80.5247 535.482 13.62 80.5247 535.482 13.63 80.5247 535.482 13.64 535.482 13.65 535.482 13.66 529.331 13.67 529.331 13.68 529.331 13.69 529.331 13.7 529.331 13.71 529.331 13.72 535.482 13.73 535.482 13.74 535.482 374.294 252.714 13.75 535.482 374.294 252.714 13.76 374.294 252.714 13.77 374.294 252.714 13.78 374.294 252.714 13.79 374.294 252.714 13.8 374.294 252.714 13.81 374.294 252.714 13.82 374.294 252.714 13.83 374.294 252.714 13.84 374.294 222.556 252.714 13.85 374.294 222.556 252.714 13.86 374.294 222.556 252.714 13.87 374.294 222.556 252.714 13.88 374.294 222.556 252.714 13.89 374.294 222.556 252.714 13.9 374.294 222.556 252.714 13.91 374.294 222.556 252.714 13.92 374.294 222.556 252.714 13.93 374.294 222.556 252.714 13.94 222.556 252.714 13.95 222.556 252.714 13.96 222.556 252.714 13.97 222.556 252.714 13.98 222.556 252.714 13.99 222.556 252.714 14.0 445.113 222.556 252.714 14.01 445.113 222.556 252.714 14.02 445.113 222.556 252.714 14.03 445.113 222.556 252.714 14.04 445.113 222.556 252.714 14.05 445.113 222.556 252.714 14.06 445.113 222.556 252.714 14.07 445.113 222.556 252.714 14.08 445.113 222.556 252.714 14.09 445.113 222.556 252.714 14.1 445.113 222.556 252.714 14.11 445.113 222.556 252.714 14.12 440 222.556 252.714 14.13 440 222.556 252.714 14.14 440 222.556 252.714 14.15 440 222.556 252.714 14.16 440 222.556 252.714 14.17 440 222.556 252.714 14.18 445.113 222.556 252.714 14.19 445.113 222.556 252.714 14.2 445.113 222.556 252.714 14.21 445.113 222.556 252.714 14.22 445.113 222.556 252.714 14.23 445.113 222.556 252.714 14.24 222.556 450.285 252.714 14.25 222.556 450.285 252.714 14.26 222.556 450.285 252.714 14.27 222.556 450.285 252.714 14.28 222.556 450.285 252.714 14.29 222.556 450.285 252.714 14.3 445.113 222.556 252.714 14.31 445.113 222.556 252.714 14.32 445.113 222.556 252.714 14.33 445.113 222.556 252.714 14.34 445.113 222.556 252.714 14.35 445.113 222.556 252.714 14.36 222.556 450.285 252.714 14.37 222.556 450.285 252.714 14.38 222.556 450.285 252.714 14.39 222.556 450.285 252.714 14.4 222.556 252.714 14.41 222.556 252.714 14.42 445.113 222.556 252.714 14.43 445.113 222.556 252.714 14.44 445.113 222.556 252.714 14.45 445.113 222.556 252.714 14.46 445.113 222.556 252.714 14.47 445.113 222.556 252.714 14.48 440 222.556 252.714 14.49 440 222.556 252.714 14.5 440 222.556 252.714 14.51 440 222.556 252.714 14.52 225.142 440 252.714 14.53 225.142 440 252.714 14.54 225.142 450.285 252.714 14.55 225.142 450.285 252.714 14.56 225.142 252.714 14.57 225.142 252.714 14.58 225.142 252.714 14.59 225.142 252.714 14.6 225.142 440 252.714 14.61 225.142 440 252.714 14.62 440 222.556 252.714 14.63 440 222.556 252.714 14.64 440 222.556 252.714 14.65 440 222.556 252.714 14.66 222.556 450.285 252.714 14.67 222.556 450.285 252.714 14.68 225.142 450.285 252.714 14.69 225.142 450.285 252.714 14.7 225.142 450.285 252.714 14.71 225.142 450.285 252.714 14.72 225.142 450.285 252.714 14.73 225.142 450.285 252.714 14.74 445.113 225.142 252.714 14.75 445.113 225.142 252.714 14.76 445.113 225.142 252.714 14.77 445.113 225.142 252.714 14.78 445.113 222.556 252.714 14.79 445.113 222.556 252.714 14.8 445.113 222.556 252.714 14.81 445.113 222.556 252.714 14.82 222.556 450.285 252.714 14.83 222.556 450.285 252.714 14.84 225.142 450.285 252.714 14.85 225.142 450.285 252.714 14.86 225.142 450.285 252.714 14.87 225.142 450.285 252.714 14.88 225.142 252.714 14.89 225.142 252.714 14.9 225.142 252.714 14.91 225.142 252.714 14.92 225.142 14.93 225.142 14.94 225.142 14.95 225.142 14.96 225.142 14.97 225.142 14.98 225.142 14.99 225.142 15.0 15.01 15.02 15.03 15.04 15.05 15.06 15.07 15.08 15.09 15.1 15.11 15.12 15.13 15.14 15.15 15.16 15.17 15.18 15.19 15.2 15.21 15.22 15.23 15.24 15.25 15.26 15.27 15.28 15.29 15.3 15.31 15.32 15.33 15.34 15.35 15.36 15.37 15.38 15.39 15.4 15.41 15.42 15.43 15.44 15.45 15.46 15.47 15.48 15.49 15.5 15.51 15.52 15.53 15.54 15.55 15.56 15.57 15.58 15.59 15.6 15.61 15.62 15.63 15.64 15.65 15.66 15.67 15.68 15.69 15.7 15.71 15.72 15.73 15.74 15.75 15.76 15.77 15.78 15.79 15.8 15.81 15.82 222.556 15.83 222.556 15.84 222.556 15.85 222.556 15.86 222.556 15.87 222.556 15.88 222.556 15.89 222.556 15.9 222.556 15.91 222.556 15.92 222.556 15.93 222.556 15.94 222.556 15.95 222.556 15.96 222.556 15.97 222.556 15.98 15.99 16.0 16.01 16.02 16.03 16.04 16.05 16.06 16.07 16.08 16.09 16.1 16.11 16.12 16.13 16.14 16.15 16.16 16.17 16.18 16.19 16.2 16.21 16.22 16.23 16.24 16.25 16.26 16.27 16.28 16.29 16.3 16.31 16.32 450.285 16.33 450.285 16.34 450.285 16.35 450.285 16.36 450.285 16.37 450.285 16.38 450.285 16.39 450.285 16.4 450.285 16.41 450.285 16.42 450.285 16.43 450.285 16.44 450.285 16.45 450.285 16.46 450.285 16.47 450.285 16.48 450.285 16.49 450.285 16.5 16.51 16.52 16.53 16.54 396.55 222.556 16.55 396.55 222.556 16.56 396.55 222.556 16.57 396.55 222.556 16.58 396.55 222.556 16.59 396.55 222.556 16.6 396.55 222.556 16.61 396.55 222.556 16.62 396.55 222.556 16.63 396.55 222.556 16.64 396.55 222.556 16.65 396.55 222.556 16.66 222.556 16.67 222.556 16.68 222.556 16.69 222.556 16.7 222.556 75.1322 16.71 222.556 75.1322 16.72 75.1322 16.73 75.1322 16.74 75.1322 16.75 75.1322 16.76 75.1322 16.77 75.1322 16.78 75.1322 16.79 75.1322 16.8 396.55 75.1322 16.81 396.55 75.1322 16.82 396.55 75.1322 16.83 396.55 75.1322 16.84 396.55 75.1322 16.85 396.55 75.1322 16.86 396.55 75.1322 16.87 396.55 75.1322 16.88 383.042 75.1322 16.89 383.042 75.1322 16.9 383.042 75.1322 16.91 383.042 75.1322 16.92 75.1322 16.93 75.1322 16.94 75.1322 16.95 75.1322 16.96 75.1322 16.97 75.1322 16.98 75.1322 16.99 75.1322 17.0 75.1322 17.01 75.1322 17.02 75.1322 17.03 75.1322 17.04 75.1322 17.05 75.1322 17.06 75.1322 17.07 75.1322 17.08 75.1322 17.09 75.1322 17.1 75.1322 17.11 75.1322 17.12 75.1322 297.077 17.13 75.1322 297.077 17.14 75.1322 297.077 17.15 75.1322 297.077 17.16 75.1322 297.077 17.17 75.1322 297.077 17.18 300.529 75.1322 17.19 300.529 75.1322 17.2 300.529 75.1322 17.21 300.529 75.1322 17.22 300.529 75.1322 17.23 300.529 75.1322 17.24 300.529 75.1322 17.25 300.529 75.1322 17.26 300.529 75.1322 17.27 300.529 75.1322 17.28 300.529 75.1322 17.29 300.529 75.1322 17.3 75.1322 297.077 17.31 75.1322 297.077 17.32 75.1322 297.077 17.33 75.1322 297.077 17.34 374.294 75.1322 297.077 17.35 374.294 75.1322 297.077 17.36 374.294 300.529 75.1322 17.37 374.294 300.529 75.1322 17.38 374.294 300.529 75.1322 17.39 374.294 300.529 75.1322 17.4 374.294 300.529 75.1322 17.41 374.294 300.529 75.1322 17.42 374.294 300.529 75.1322 17.43 374.294 300.529 75.1322 17.44 374.294 300.529 75.1322 17.45 374.294 300.529 75.1322 17.46 374.294 75.1322 17.47 374.294 75.1322 17.48 75.1322 17.49 75.1322 17.5 75.1322 17.51 75.1322 17.52 75.1322 17.53 75.1322 17.54 75.1322 17.55 75.1322 17.56 75.1322 17.57 75.1322 17.58 75.1322 17.59 75.1322 17.6 75.1322 17.61 75.1322 17.62 75.1322 17.63 75.1322 17.64 75.1322 17.65 75.1322 17.66 75.1322 17.67 75.1322 17.68 75.1322 17.69 75.1322 17.7 222.556 75.1322 17.71 222.556 75.1322 17.72 222.556 17.73 222.556 17.74 222.556 17.75 222.556 17.76 222.556 17.77 222.556 17.78 222.556 17.79 222.556 17.8 222.556 17.81 222.556 17.82 222.556 17.83 222.556 17.84 222.556 17.85 222.556 17.86 222.556 17.87 222.556 17.88 222.556 17.89 222.556 17.9 126.357 222.556 17.91 126.357 222.556 17.92 126.357 17.93 126.357 17.94 126.357 17.95 126.357 17.96 126.357 17.97 126.357 17.98 126.357 17.99 126.357 18.0 126.357 18.01 126.357 18.02 126.357 18.03 126.357 18.04 126.357 18.05 126.357 18.06 126.357 18.07 126.357 18.08 126.357 18.09 126.357 18.1 126.357 18.11 126.357 18.12 126.357 18.13 126.357 18.14 126.357 18.15 126.357 18.16 126.357 18.17 126.357 18.18 126.357 18.19 126.357 18.2 126.357 18.21 126.357 18.22 126.357 18.23 126.357 18.24 126.357 18.25 126.357 18.26 126.357 18.27 126.357 18.28 126.357 18.29 126.357 18.3 126.357 18.31 126.357 18.32 126.357 18.33 126.357 18.34 126.357 18.35 126.357 18.36 126.357 18.37 126.357 18.38 126.357 297.077 18.39 126.357 297.077 18.4 126.357 297.077 18.41 126.357 297.077 18.42 126.357 297.077 18.43 126.357 297.077 18.44 126.357 297.077 18.45 126.357 297.077 18.46 126.357 297.077 18.47 126.357 297.077 18.48 126.357 300.529 18.49 126.357 300.529 18.5 126.357 300.529 18.51 126.357 300.529 18.52 126.357 300.529 18.53 126.357 300.529 18.54 126.357 300.529 18.55 126.357 300.529 18.56 126.357 300.529 18.57 126.357 300.529 18.58 126.357 353.286 18.59 126.357 353.286 18.6 126.357 353.286 18.61 126.357 353.286 18.62 126.357 353.286 18.63 126.357 353.286 18.64 126.357 353.286 18.65 126.357 353.286 18.66 126.357 353.286 18.67 126.357 353.286 18.68 126.357 353.286 18.69 126.357 353.286 18.7 126.357 353.286 18.71 126.357 353.286 18.72 126.357 353.286 18.73 126.357 353.286 18.74 396.55 126.357 353.286 18.75 396.55 126.357 353.286 18.76 396.55 126.357 353.286 18.77 396.55 126.357 353.286 18.78 396.55 126.357 353.286 18.79 396.55 126.357 353.286 18.8 396.55 126.357 353.286 18.81 396.55 126.357 353.286 18.82 126.357 401.158 353.286 18.83 126.357 401.158 353.286 18.84 126.357 401.158 353.286 18.85 126.357 401.158 353.286 18.86 126.357 353.286 18.87 126.357 353.286 18.88 126.357 353.286 18.89 126.357 353.286 18.9 126.357 353.286 18.91 126.357 353.286 18.92 126.357 353.286 18.93 126.357 353.286 18.94 126.357 353.286 18.95 126.357 353.286 18.96 353.286 18.97 353.286 18.98 353.286 18.99 353.286 19.0 353.286 19.01 353.286 19.02 353.286 19.03 353.286 19.04 353.286 19.05 353.286 19.06 353.286 19.07 353.286 19.08 353.286 19.09 353.286 19.1 19.11 19.12 19.13 19.14 19.15 19.16 132.333 19.17 132.333 19.18 132.333 19.19 132.333 19.2 132.333 19.21 132.333 19.22 132.333 19.23 132.333 19.24 132.333 19.25 132.333 19.26 132.333 19.27 132.333 19.28 132.333 19.29 132.333 19.3 132.333 19.31 132.333 19.32 132.333 19.33 132.333 19.34 132.333 19.35 132.333 19.36 198.275 19.37 198.275 19.38 198.275 19.39 198.275 19.4 198.275 19.41 198.275 19.42 198.275 19.43 198.275 19.44 198.275 19.45 198.275 19.46 198.275 19.47 198.275 19.48 264.666 19.49 264.666 19.5 264.666 19.51 264.666 19.52 264.666 19.53 264.666 19.54 264.666 19.55 264.666 19.56 264.666 19.57 264.666 19.58 264.666 19.59 264.666 19.6 264.666 19.61 264.666 19.62 264.666 19.63 264.666 19.64 264.666 19.65 264.666 19.66 264.666 19.67 264.666 19.68 264.666 19.69 264.666 19.7 264.666 19.71 264.666 19.72 264.666 19.73 264.666 19.74 264.666 19.75 264.666 19.76 264.666 19.77 264.666 19.78 264.666 19.79 264.666 19.8 264.666 19.81 264.666 19.82 264.666 19.83 264.666 19.84 264.666 19.85 264.666 19.86 264.666 19.87 264.666 19.88 264.666 19.89 264.666 19.9 264.666 19.91 264.666 19.92 264.666 19.93 264.666 19.94 264.666 19.95 264.666 19.96 264.666 19.97 264.666 19.98 264.666 19.99 264.666 20.0 264.666 20.01 264.666 20.02 264.666 20.03 264.666 20.04 264.666 20.05 264.666 20.06 264.666 20.07 264.666 20.08 20.09 20.1 20.11 20.12 20.13 20.14 20.15 20.16 200.579 20.17 200.579 20.18 200.579 20.19 200.579 20.2 200.579 20.21 200.579 20.22 198.275 20.23 198.275 20.24 198.275 20.25 198.275 20.26 198.275 20.27 198.275 20.28 20.29 20.3 20.31 20.32 106.253 20.33 106.253 20.34 106.253 20.35 106.253 20.36 106.253 20.37 106.253 20.38 106.253 20.39 106.253 20.4 106.253 20.41 106.253 20.42 106.253 20.43 106.253 20.44 20.45 20.46 20.47 20.48 345.217 20.49 345.217 20.5 345.217 20.51 345.217 20.52 345.217 20.53 345.217 20.54 341.252 252.714 20.55 341.252 252.714 20.56 341.252 252.714 20.57 341.252 252.714 20.58 210.065 341.252 252.714 20.59 210.065 341.252 252.714 20.6 210.065 341.252 252.714 20.61 210.065 341.252 252.714 20.62 210.065 345.217 252.714 20.63 210.065 345.217 252.714 20.64 210.065 345.217 252.714 20.65 210.065 345.217 252.714 20.66 210.065 345.217 252.714 20.67 210.065 345.217 252.714 20.68 210.065 345.217 252.714 20.69 210.065 345.217 252.714 20.7 210.065 341.252 252.714 20.71 210.065 341.252 252.714 20.72 341.252 252.714 20.73 341.252 252.714 20.74 341.252 252.714 20.75 341.252 252.714 20.76 345.217 300.529 252.714 20.77 345.217 300.529 252.714 20.78 345.217 300.529 252.714 20.79 345.217 300.529 252.714 20.8 345.217 300.529 252.714 20.81 345.217 300.529 252.714 20.82 341.252 300.529 252.714 20.83 341.252 300.529 252.714 20.84 341.252 252.714 297.077 20.85 341.252 252.714 297.077 20.86 341.252 252.714 297.077 20.87 341.252 252.714 297.077 20.88 341.252 252.714 297.077 20.89 341.252 252.714 297.077 20.9 341.252 300.529 252.714 20.91 341.252 300.529 252.714 20.92 300.529 353.286 252.714 20.93 300.529 353.286 252.714 20.94 337.332 300.529 353.286 252.714 20.95 337.332 300.529 353.286 252.714 20.96 337.332 300.529 353.286 252.714 20.97 337.332 300.529 353.286 252.714 20.98 337.332 353.286 252.714 20.99 337.332 353.286 252.714 21.0 337.332 353.286 252.714 21.01 337.332 353.286 252.714 21.02 337.332 353.286 252.714 21.03 337.332 353.286 252.714 21.04 337.332 353.286 252.714 21.05 337.332 353.286 252.714 21.06 353.286 252.714 21.07 353.286 252.714 21.08 353.286 252.714 21.09 353.286 252.714 21.1 349.228 21.11 349.228 21.12 349.228 249.811 21.13 349.228 249.811 21.14 349.228 249.811 21.15 349.228 249.811 21.16 349.228 249.811 21.17 349.228 249.811 21.18 349.228 249.811 21.19 349.228 249.811 21.2 349.228 252.714 21.21 349.228 252.714 21.22 353.286 252.714 21.23 353.286 252.714 21.24 353.286 252.714 21.25 353.286 252.714 21.26 249.811 353.286 21.27 249.811 353.286 21.28 249.811 349.228 21.29 249.811 349.228 21.3 249.811 349.228 21.31 249.811 349.228 21.32 349.228 252.714 21.33 349.228 252.714 21.34 353.286 252.714 21.35 353.286 252.714 21.36 353.286 252.714 21.37 353.286 252.714 21.38 353.286 252.714 21.39 353.286 252.714 21.4 341.252 252.714 21.41 341.252 252.714 21.42 341.252 252.714 21.43 341.252 252.714 21.44 252.714 21.45 252.714 21.46 252.714 21.47 252.714 21.48 252.714 21.49 252.714 21.5 252.714 21.51 252.714 21.52 252.714 21.53 252.714 21.54 252.714 21.55 252.714 21.56 252.714 21.57 252.714 21.58 252.714 21.59 252.714 21.6 252.714 21.61 252.714 21.62 252.714 21.63 252.714 21.64 252.714 21.65 252.714 21.66 252.714 21.67 252.714 21.68 252.714 21.69 252.714 21.7 252.714 21.71 252.714 21.72 267.741 252.714 21.73 267.741 252.714 21.74 267.741 249.811 21.75 267.741 249.811 21.76 267.741 21.77 267.741 21.78 264.666 21.79 264.666 21.8 264.666 21.81 264.666 21.82 264.666 21.83 264.666 21.84 264.666 21.85 264.666 21.86 264.666 21.87 264.666 21.88 264.666 21.89 264.666 21.9 264.666 21.91 264.666 21.92 264.666 21.93 264.666 21.94 264.666 21.95 264.666 21.96 264.666 21.97 264.666 21.98 264.666 21.99 264.666 22.0 264.666 22.01 264.666 22.02 264.666 22.03 264.666 22.04 264.666 22.05 264.666 22.06 264.666 22.07 264.666 22.08 264.666 22.09 264.666 22.1 264.666 450.285 22.11 264.666 450.285 22.12 425.012 264.666 450.285 22.13 425.012 264.666 450.285 22.14 425.012 264.666 450.285 22.15 425.012 264.666 450.285 22.16 425.012 264.666 450.285 22.17 425.012 264.666 450.285 22.18 425.012 264.666 450.285 22.19 425.012 264.666 450.285 22.2 425.012 264.666 429.95 22.21 425.012 264.666 429.95 22.22 425.012 429.95 22.23 425.012 429.95 22.24 425.012 429.95 22.25 425.012 429.95 22.26 529.331 450.285 22.27 529.331 450.285 22.28 529.331 450.285 22.29 529.331 450.285 22.3 529.331 450.285 22.31 529.331 450.285 22.32 529.331 450.285 22.33 529.331 450.285 22.34 529.331 450.285 22.35 529.331 450.285 22.36 529.331 450.285 22.37 529.331 450.285 22.38 529.331 450.285 22.39 529.331 450.285 22.4 529.331 450.285 22.41 529.331 450.285 22.42 529.331 267.741 22.43 529.331 267.741 22.44 267.741 22.45 267.741 22.46 529.331 267.741 22.47 529.331 267.741 22.48 529.331 267.741 22.49 529.331 267.741 22.5 529.331 264.666 22.51 529.331 264.666 22.52 529.331 264.666 22.53 529.331 264.666 22.54 529.331 264.666 22.55 529.331 264.666 22.56 529.331 264.666 22.57 529.331 264.666 22.58 529.331 264.666 22.59 529.331 264.666 22.6 529.331 264.666 22.61 529.331 264.666 22.62 529.331 264.666 22.63 529.331 264.666 22.64 529.331 105.033 264.666 22.65 529.331 105.033 264.666 22.66 105.033 264.666 22.67 105.033 264.666 22.68 105.033 264.666 22.69 105.033 264.666 22.7 210.065 106.253 264.666 22.71 210.065 106.253 264.666 22.72 210.065 106.253 264.666 22.73 210.065 106.253 264.666 22.74 210.065 106.253 264.666 22.75 210.065 106.253 264.666 22.76 210.065 106.253 264.666 22.77 210.065 106.253 264.666 22.78 210.065 106.253 264.666 22.79 210.065 106.253 264.666 22.8 210.065 106.253 264.666 22.81 210.065 106.253 264.666 22.82 210.065 267.741 22.83 210.065 267.741 22.84 210.065 267.741 252.714 22.85 210.065 267.741 252.714 22.86 210.065 267.741 252.714 22.87 210.065 267.741 252.714 22.88 210.065 255.65 252.714 22.89 210.065 255.65 252.714 22.9 210.065 255.65 252.714 22.91 210.065 255.65 252.714 22.92 210.065 252.714 22.93 210.065 252.714 22.94 210.065 252.714 22.95 210.065 252.714 22.96 210.065 252.714 22.97 210.065 252.714 22.98 210.065 252.714 22.99 210.065 252.714 23.0 210.065 252.714 23.01 210.065 252.714 23.02 210.065 252.714 23.03 210.065 252.714 23.04 210.065 252.714 23.05 210.065 252.714 23.06 210.065 252.714 23.07 210.065 252.714 23.08 210.065 300.529 252.714 23.09 210.065 300.529 252.714 23.1 210.065 300.529 252.714 23.11 210.065 300.529 252.714 23.12 210.065 493.883 300.529 252.714 23.13 210.065 493.883 300.529 252.714 23.14 210.065 493.883 300.529 252.714 23.15 210.065 493.883 300.529 252.714 23.16 210.065 493.883 300.529 252.714 23.17 210.065 493.883 300.529 252.714 23.18 210.065 300.529 252.714 499.622 23.19 210.065 300.529 252.714 499.622 23.2 210.065 300.529 252.714 499.622 23.21 210.065 300.529 252.714 499.622 23.22 210.065 300.529 252.714 499.622 23.23 210.065 300.529 252.714 499.622 23.24 210.065 297.077 252.714 499.622 23.25 210.065 297.077 252.714 499.622 23.26 210.065 493.883 297.077 252.714 23.27 210.065 493.883 297.077 252.714 23.28 210.065 493.883 337.332 297.077 252.714 23.29 210.065 493.883 337.332 297.077 252.714 23.3 210.065 493.883 337.332 300.529 252.714 23.31 210.065 493.883 337.332 300.529 252.714 23.32 210.065 337.332 300.529 252.714 499.622 23.33 210.065 337.332 300.529 252.714 499.622 23.34 210.065 337.332 300.529 252.714 499.622 23.35 210.065 337.332 300.529 252.714 499.622 23.36 210.065 337.332 300.529 252.714 23.37 210.065 337.332 300.529 252.714 23.38 210.065 337.332 252.714 297.077 23.39 210.065 337.332 252.714 297.077 23.4 210.065 493.883 252.714 297.077 23.41 210.065 493.883 252.714 297.077 23.42 210.065 493.883 297.077 23.43 210.065 493.883 297.077 23.44 210.065 493.883 252.714 297.077 23.45 210.065 493.883 252.714 297.077 23.46 210.065 499.622 252.714 297.077 23.47 210.065 499.622 252.714 297.077 23.48 210.065 499.622 252.714 297.077 23.49 210.065 499.622 252.714 297.077 23.5 210.065 499.622 252.714 23.51 210.065 499.622 252.714 23.52 210.065 252.714 23.53 210.065 252.714 23.54 210.065 252.714 23.55 210.065 252.714 23.56 249.811 23.57 249.811 23.58 249.811 23.59 249.811 23.6 249.811 23.61 249.811 23.62 252.714 23.63 252.714 23.64 252.714 23.65 252.714 23.66 23.67 23.68 252.714 23.69 252.714 23.7 252.714 23.71 252.714 23.72 252.714 23.73 252.714 23.74 252.714 23.75 252.714 23.76 249.811 23.77 249.811 23.78 249.811 23.79 249.811 23.8 249.811 23.81 249.811 23.82 112.571 252.714 23.83 112.571 252.714 23.84 112.571 252.714 23.85 112.571 252.714 23.86 112.571 252.714 23.87 112.571 252.714 23.88 112.571 252.714 23.89 112.571 252.714 23.9 112.571 601.058 252.714 23.91 112.571 601.058 252.714 23.92 112.571 601.058 252.714 23.93 112.571 601.058 252.714 23.94 112.571 601.058 252.714 23.95 112.571 601.058 252.714 23.96 112.571 601.058 252.714 23.97 112.571 601.058 252.714 23.98 594.154 112.571 252.714 23.99 594.154 112.571 252.714 24.0 594.154 112.571 267.741 252.714 24.01 594.154 112.571 267.741 252.714 24.02 112.571 267.741 252.714 24.03 112.571 267.741 252.714 24.04 112.571 267.741 252.714 24.05 112.571 267.741 252.714 24.06 112.571 264.666 252.714 24.07 112.571 264.666 252.714 24.08 112.571 529.331 264.666 24.09 112.571 529.331 264.666 24.1 112.571 529.331 264.666 24.11 112.571 529.331 264.666 24.12 112.571 529.331 264.666 24.13 112.571 529.331 264.666 24.14 112.571 535.482 264.666 24.15 112.571 535.482 264.666 24.16 112.571 535.482 264.666 24.17 112.571 535.482 264.666 24.18 220 112.571 535.482 264.666 24.19 220 112.571 535.482 264.666 24.2 220 529.331 264.666 24.21 220 529.331 264.666 24.22 220 529.331 264.666 24.23 220 529.331 264.666 24.24 529.331 333.458 264.666 222.556 24.25 529.331 333.458 264.666 222.556 24.26 529.331 333.458 264.666 222.556 24.27 529.331 333.458 264.666 222.556 24.28 529.331 333.458 264.666 222.556 24.29 529.331 333.458 264.666 222.556 24.3 529.331 333.458 264.666 222.556 24.31 529.331 333.458 264.666 222.556 24.32 529.331 333.458 264.666 222.556 24.33 529.331 333.458 264.666 222.556 24.34 220 333.458 264.666 24.35 220 333.458 264.666 24.36 220 333.458 264.666 24.37 220 333.458 264.666 24.38 220 333.458 264.666 24.39 220 333.458 264.666 24.4 445.113 333.458 264.666 222.556 890.225 24.41 445.113 333.458 264.666 222.556 890.225 24.42 445.113 264.666 222.556 890.225 24.43 445.113 264.666 222.556 890.225 24.44 445.113 264.666 222.556 890.225 24.45 445.113 264.666 222.556 890.225 24.46 445.113 900.569 264.666 222.556 24.47 445.113 900.569 264.666 222.556 24.48 445.113 900.569 264.666 222.556 24.49 445.113 900.569 264.666 222.556 24.5 900.569 264.666 222.556 450.285 24.51 900.569 264.666 222.556 450.285 24.52 264.666 222.556 450.285 890.225 24.53 264.666 222.556 450.285 890.225 24.54 264.666 222.556 450.285 24.55 264.666 222.556 450.285 24.56 445.113 535.482 264.666 222.556 24.57 445.113 535.482 264.666 222.556 24.58 445.113 535.482 264.666 222.556 24.59 445.113 535.482 264.666 222.556 24.6 445.113 267.741 535.482 222.556 24.61 445.113 267.741 535.482 222.556 24.62 445.113 267.741 529.331 222.556 24.63 445.113 267.741 529.331 222.556 24.64 445.113 267.741 529.331 222.556 24.65 445.113 267.741 529.331 222.556 24.66 267.741 529.331 222.556 24.67 267.741 529.331 222.556 24.68 267.741 529.331 222.556 24.69 267.741 529.331 222.556 24.7 267.741 529.331 222.556 24.71 267.741 529.331 222.556 24.72 267.741 529.331 333.458 222.556 24.73 267.741 529.331 333.458 222.556 24.74 267.741 529.331 333.458 222.556 24.75 267.741 529.331 333.458 222.556 24.76 267.741 535.482 333.458 24.77 267.741 535.482 333.458 24.78 267.741 535.482 333.458 24.79 267.741 535.482 333.458 24.8 535.482 333.458 264.666 24.81 535.482 333.458 264.666 24.82 529.331 333.458 264.666 24.83 529.331 333.458 264.666 24.84 333.458 264.666 24.85 333.458 264.666 24.86 337.332 264.666 24.87 337.332 264.666 24.88 76.0052 337.332 264.666 24.89 76.0052 337.332 264.666 24.9 76.0052 337.332 264.666 24.91 76.0052 337.332 264.666 24.92 76.0052 264.666 1058.66 24.93 76.0052 264.666 1058.66 24.94 445.113 76.0052 264.666 1058.66 24.95 445.113 76.0052 264.666 1058.66 24.96 445.113 76.0052 264.666 353.286 1058.66 24.97 445.113 76.0052 264.666 353.286 1058.66 24.98 445.113 76.0052 1046.5 264.666 353.286 24.99 445.113 76.0052 1046.5 264.666 353.286 25.0 445.113 1046.5 264.666 353.286 75.1322 25.01 445.113 1046.5 264.666 353.286 75.1322 25.02 1046.5 264.666 353.286 75.1322 450.285 25.03 1046.5 264.666 353.286 75.1322 450.285 25.04 264.666 353.286 75.1322 1070.96 450.285 25.05 264.666 353.286 75.1322 1070.96 450.285 25.06 264.666 353.286 75.1322 1070.96 25.07 264.666 353.286 75.1322 1070.96 25.08 353.286 75.1322 1070.96 25.09 353.286 75.1322 1070.96 25.1 1034.48 353.286 75.1322 25.11 1034.48 353.286 75.1322 25.12 1034.48 353.286 75.1322 25.13 1034.48 353.286 75.1322 25.14 1034.48 353.286 75.1322 25.15 1034.48 353.286 75.1322 25.16 353.286 75.1322 1070.96 25.17 353.286 75.1322 1070.96 25.18 353.286 75.1322 25.19 353.286 75.1322 25.2 353.286 75.1322 25.21 353.286 75.1322 25.22 353.286 75.1322 450.285 25.23 353.286 75.1322 450.285 25.24 353.286 75.1322 450.285 25.25 353.286 75.1322 450.285 25.26 353.286 75.1322 450.285 25.27 353.286 75.1322 450.285 25.28 353.286 75.1322 450.285 25.29 353.286 75.1322 450.285 25.3 353.286 75.1322 450.285 25.31 353.286 75.1322 450.285 25.32 74.2692 353.286 450.285 499.622 25.33 74.2692 353.286 450.285 499.622 25.34 74.2692 353.286 499.622 25.35 74.2692 353.286 499.622 25.36 74.2692 353.286 1046.5 499.622 25.37 74.2692 353.286 1046.5 499.622 25.38 74.2692 353.286 1046.5 499.622 25.39 74.2692 353.286 1046.5 499.622 25.4 74.2692 353.286 1046.5 499.622 25.41 74.2692 353.286 1046.5 499.622 25.42 74.2692 353.286 1058.66 499.622 25.43 74.2692 353.286 1058.66 499.622 25.44 74.2692 353.286 1058.66 499.622 25.45 74.2692 353.286 1058.66 499.622 25.46 74.2692 353.286 1058.66 499.622 25.47 74.2692 353.286 1058.66 499.622 25.48 74.2692 353.286 499.622 25.49 74.2692 353.286 499.622 25.5 74.2692 353.286 297.077 499.622 25.51 74.2692 353.286 297.077 499.622 25.52 1479.98 74.2692 357.391 297.077 499.622 25.53 1479.98 74.2692 357.391 297.077 499.622 25.54 1479.98 74.2692 297.077 499.622 25.55 1479.98 74.2692 297.077 499.622 25.56 1479.98 74.2692 297.077 499.622 25.57 1479.98 74.2692 297.077 499.622 25.58 1479.98 74.2692 297.077 499.622 25.59 1479.98 74.2692 297.077 499.622 25.6 1479.98 74.2692 353.286 297.077 499.622 25.61 1479.98 74.2692 353.286 297.077 499.622 25.62 1479.98 74.2692 353.286 297.077 499.622 25.63 1479.98 74.2692 353.286 297.077 499.622 25.64 1479.98 74.2692 353.286 297.077 499.622 25.65 1479.98 74.2692 353.286 297.077 499.622 25.66 74.2692 353.286 297.077 499.622 25.67 74.2692 353.286 297.077 499.622 25.68 74.2692 353.286 297.077 499.622 25.69 74.2692 353.286 297.077 499.622 25.7 74.2692 353.286 297.077 499.622 25.71 74.2692 353.286 297.077 499.622 25.72 74.2692 353.286 297.077 499.622 25.73 74.2692 353.286 297.077 499.622 25.74 74.2692 1202.12 353.286 297.077 499.622 25.75 74.2692 1202.12 353.286 297.077 499.622 25.76 74.2692 1202.12 353.286 297.077 499.622 25.77 74.2692 1202.12 353.286 297.077 499.622 25.78 74.2692 1202.12 353.286 297.077 499.622 25.79 74.2692 1202.12 353.286 297.077 499.622 25.8 74.2692 1202.12 353.286 297.077 499.622 25.81 74.2692 1202.12 353.286 297.077 499.622 25.82 74.2692 1202.12 353.286 297.077 25.83 74.2692 1202.12 353.286 297.077 25.84 74.2692 1202.12 353.286 297.077 25.85 74.2692 1202.12 353.286 297.077 25.86 353.286 25.87 353.286 25.88 353.286 25.89 353.286 25.9 353.286 25.91 353.286 25.92 353.286 25.93 353.286 25.94 353.286 25.95 353.286 25.96 353.286 25.97 353.286 25.98 353.286 25.99 353.286 26.0 353.286 26.01 353.286 26.02 353.286 26.03 353.286 26.04 353.286 26.05 353.286 26.06 353.286 26.07 353.286 26.08 353.286 252.714 168.666 26.09 353.286 252.714 168.666 26.1 353.286 252.714 83.3644 168.666 26.11 353.286 252.714 83.3644 168.666 26.12 353.286 252.714 83.3644 168.666 26.13 353.286 252.714 83.3644 168.666 26.14 166.729 353.286 252.714 83.3644 26.15 166.729 353.286 252.714 83.3644 26.16 84.3331 166.729 353.286 252.714 26.17 84.3331 166.729 353.286 252.714 26.18 84.3331 166.729 357.391 252.714 26.19 84.3331 166.729 357.391 252.714 26.2 84.3331 357.391 252.714 168.666 26.21 84.3331 357.391 252.714 168.666 26.22 84.3331 252.714 168.666 26.23 84.3331 252.714 168.666 26.24 84.3331 252.714 168.666 26.25 84.3331 252.714 168.666 26.26 84.3331 252.714 168.666 26.27 84.3331 252.714 168.666 26.28 84.3331 252.714 26.29 84.3331 252.714 26.3 84.3331 252.714 26.31 84.3331 252.714 26.32 252.714 83.3644 168.666 26.33 252.714 83.3644 168.666 26.34 252.714 83.3644 168.666 26.35 252.714 83.3644 168.666 26.36 252.714 83.3644 168.666 26.37 252.714 83.3644 168.666 26.38 252.714 83.3644 168.666 26.39 252.714 83.3644 168.666 26.4 252.714 83.3644 168.666 26.41 252.714 83.3644 168.666 26.42 252.714 83.3644 168.666 26.43 252.714 83.3644 168.666 26.44 252.714 83.3644 26.45 252.714 83.3644 26.46 252.714 445.113 83.3644 26.47 252.714 445.113 83.3644 26.48 252.714 445.113 83.3644 26.49 252.714 445.113 83.3644 26.5 252.714 445.113 83.3644 26.51 252.714 445.113 83.3644 26.52 252.714 445.113 83.3644 26.53 252.714 445.113 83.3644 26.54 252.714 445.113 83.3644 26.55 252.714 445.113 83.3644 26.56 252.714 445.113 83.3644 26.57 252.714 445.113 83.3644 26.58 252.714 445.113 83.3644 26.59 252.714 445.113 83.3644 26.6 252.714 445.113 83.3644 26.61 252.714 445.113 83.3644 26.62 252.714 445.113 83.3644 26.63 252.714 445.113 83.3644 26.64 529.331 252.714 445.113 83.3644 26.65 529.331 252.714 445.113 83.3644 26.66 529.331 252.714 445.113 83.3644 26.67 529.331 252.714 445.113 83.3644 26.68 529.331 252.714 445.113 83.3644 26.69 529.331 252.714 445.113 83.3644 26.7 529.331 252.714 445.113 83.3644 26.71 529.331 252.714 445.113 83.3644 26.72 529.331 252.714 445.113 83.3644 26.73 529.331 252.714 445.113 83.3644 26.74 529.331 252.714 445.113 83.3644 26.75 529.331 252.714 445.113 83.3644 26.76 529.331 252.714 445.113 83.3644 26.77 529.331 252.714 445.113 83.3644 26.78 529.331 445.113 83.3644 26.79 529.331 445.113 83.3644 26.8 445.113 83.3644 26.81 445.113 83.3644 26.82 445.113 83.3644 26.83 445.113 83.3644 26.84 83.3644 26.85 83.3644 26.86 84.3331 26.87 84.3331 26.88 84.3331 26.89 84.3331 26.9 84.3331 26.91 84.3331 26.92 84.3331 26.93 84.3331 26.94 84.3331 26.95 84.3331 26.96 26.97 26.98 26.99 27.0 168.666 27.01 168.666 27.02 84.3331 168.666 27.03 84.3331 168.666 27.04 84.3331 168.666 27.05 84.3331 168.666 27.06 84.3331 168.666 27.07 84.3331 168.666 27.08 84.3331 168.666 27.09 84.3331 168.666 27.1 84.3331 168.666 27.11 84.3331 168.666 27.12 84.3331 168.666 27.13 84.3331 168.666 27.14 84.3331 850.024 27.15 84.3331 850.024 27.16 84.3331 850.024 27.17 84.3331 850.024 27.18 84.3331 333.458 850.024 27.19 84.3331 333.458 850.024 27.2 84.3331 333.458 850.024 27.21 84.3331 333.458 850.024 27.22 840.261 84.3331 333.458 27.23 840.261 84.3331 333.458 27.24 840.261 84.3331 333.458 27.25 840.261 84.3331 333.458 27.26 840.261 84.3331 333.458 27.27 840.261 84.3331 333.458 27.28 840.261 84.3331 337.332 27.29 840.261 84.3331 337.332 27.3 84.3331 337.332 27.31 84.3331 337.332 27.32 84.3331 337.332 27.33 84.3331 337.332 27.34 84.3331 337.332 27.35 84.3331 337.332 27.36 84.3331 333.458 420.13 27.37 84.3331 333.458 420.13 27.38 84.3331 333.458 420.13 27.39 84.3331 333.458 420.13 27.4 84.3331 333.458 420.13 27.41 84.3331 333.458 420.13 27.42 84.3331 333.458 420.13 27.43 84.3331 333.458 420.13 27.44 84.3331 333.458 420.13 27.45 84.3331 333.458 420.13 27.46 84.3331 333.458 420.13 27.47 84.3331 333.458 420.13 27.48 84.3331 333.458 420.13 27.49 84.3331 333.458 420.13 27.5 84.3331 420.13 27.51 84.3331 420.13 27.52 84.3331 420.13 27.53 84.3331 420.13 27.54 84.3331 420.13 27.55 84.3331 420.13 27.56 84.3331 420.13 499.622 27.57 84.3331 420.13 499.622 27.58 84.3331 420.13 499.622 27.59 84.3331 420.13 499.622 27.6 84.3331 420.13 499.622 27.61 84.3331 420.13 499.622 27.62 84.3331 420.13 499.622 27.63 84.3331 420.13 499.622 27.64 84.3331 420.13 499.622 27.65 84.3331 420.13 499.622 27.66 84.3331 420.13 499.622 27.67 84.3331 420.13 499.622 27.68 84.3331 420.13 499.622 27.69 84.3331 420.13 499.622 27.7 84.3331 499.622 27.71 84.3331 499.622 27.72 83.3644 499.622 27.73 83.3644 499.622 27.74 83.3644 499.622 27.75 83.3644 499.622 27.76 83.3644 499.622 27.77 83.3644 499.622 27.78 83.3644 499.622 27.79 83.3644 499.622 27.8 83.3644 499.622 27.81 83.3644 499.622 27.82 83.3644 27.83 83.3644 27.84 83.3644 27.85 83.3644 27.86 83.3644 27.87 83.3644 27.88 83.3644 27.89 83.3644 27.9 166.729 83.3644 850.024 27.91 166.729 83.3644 850.024 27.92 166.729 850.024 27.93 166.729 850.024 27.94 166.729 850.024 27.95 166.729 850.024 27.96 166.729 420.13 850.024 27.97 166.729 420.13 850.024 27.98 166.729 420.13 850.024 27.99 166.729 420.13 850.024 28.0 420.13 168.666 850.024 28.01 420.13 168.666 850.024 28.02 425.012 168.666 850.024 28.03 425.012 168.666 850.024 28.04 425.012 168.666 850.024 28.05 425.012 168.666 850.024 28.06 425.012 168.666 850.024 28.07 425.012 168.666 850.024 28.08 420.13 168.666 850.024 28.09 420.13 168.666 850.024 28.1 420.13 850.024 28.11 420.13 850.024 28.12 420.13 850.024 28.13 420.13 850.024 28.14 840.261 420.13 28.15 840.261 420.13 28.16 840.261 420.13 28.17 840.261 420.13 28.18 840.261 420.13 28.19 840.261 420.13 28.2 420.13 168.666 850.024 28.21 420.13 168.666 850.024 28.22 420.13 168.666 850.024 28.23 420.13 168.666 850.024 28.24 168.666 850.024 28.25 168.666 850.024 28.26 168.666 28.27 168.666 28.28 222.556 168.666 28.29 222.556 168.666 28.3 222.556 168.666 28.31 222.556 168.666 28.32 111.278 222.556 445.113 28.33 111.278 222.556 445.113 28.34 111.278 222.556 445.113 28.35 111.278 222.556 445.113 28.36 111.278 222.556 445.113 28.37 111.278 222.556 445.113 28.38 111.278 222.556 450.285 28.39 111.278 222.556 450.285 28.4 222.556 112.571 450.285 28.41 222.556 112.571 450.285 28.42 222.556 112.571 450.285 28.43 222.556 112.571 450.285 28.44 222.556 445.113 112.571 28.45 222.556 445.113 112.571 28.46 222.556 445.113 112.571 28.47 222.556 445.113 112.571 28.48 222.556 445.113 28.49 222.556 445.113 28.5 222.556 445.113 28.51 222.556 445.113 28.52 450.285 28.53 450.285 28.54 450.285 28.55 450.285 28.56 222.556 450.285 28.57 222.556 450.285 28.58 222.556 450.285 28.59 222.556 450.285 28.6 222.556 445.113 28.61 222.556 445.113 28.62 222.556 445.113 28.63 222.556 445.113 28.64 222.556 445.113 28.65 222.556 445.113 28.66 222.556 450.285 28.67 222.556 450.285 28.68 225.142 450.285 28.69 225.142 450.285 28.7 225.142 450.285 28.71 225.142 450.285 28.72 450.285 28.73 450.285 28.74 445.113 28.75 445.113 28.76 445.113 28.77 445.113 28.78 445.113 28.79 445.113 28.8 445.113 28.81 445.113 28.82 450.285 28.83 450.285 28.84 450.285 28.85 450.285 28.86 450.285 28.87 450.285 28.88 mir_eval-0.8.2/tests/data/multipitch/est05.txt000066400000000000000000002574761475740344600213200ustar00rootroot000000000000000.0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.2 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.3 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.4 0.41 0.42 0.43 0.44 0.45 0.46 0.47 0.48 0.49 0.5 0.51 0.52 0.53 0.54 0.55 0.56 0.57 0.58 0.59 0.6 0.61 0.62 0.63 0.64 0.65 0.66 0.67 0.68 0.69 0.7 0.71 0.72 0.73 0.74 0.75 0.76 0.77 0.78 0.79 0.8 0.81 0.82 0.83 0.84 0.85 0.86 0.87 0.88 0.89 0.9 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1.0 1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.1 1.11 1.12 1.13 1.14 1.15 1.16 1.17 1.18 1.19 1.2 1.21 1.22 1.23 1.24 1.25 1.26 1.27 1.28 1.29 1.3 1.31 1.32 1.33 1.34 1.35 1.36 1.37 1.38 1.39 1.4 1.41 1.42 1.43 1.44 1.45 1.46 1.47 1.48 1.49 1.5 1.51 1.52 1.53 1.54 1.55 1.56 1.57 1.58 1.59 1.6 1.61 1.62 1.63 1.64 1.65 1.66 1.67 1.68 1.69 1.7 1.71 1.72 1.73 1.74 1.75 1.76 1.77 1.78 1.79 1.8 1.81 1.82 1.83 1.84 1.85 1.86 1.87 1.88 1.89 1.9 1.91 1.92 1.93 1.94 1.95 1.96 1.97 1.98 1.99 2.0 2.01 2.02 2.03 2.04 2.05 2.06 2.07 2.08 2.09 2.1 2.11 2.12 2.13 2.14 2.15 2.16 2.17 2.18 2.19 2.2 2.21 2.22 2.23 2.24 2.25 2.26 2.27 2.28 2.29 2.3 2.31 2.32 2.33 2.34 2.35 2.36 2.37 2.38 2.39 2.4 2.41 2.42 2.43 2.44 2.45 2.46 2.47 2.48 2.49 2.5 2.51 2.52 2.53 2.54 141.831 207.652 2.55 141.831 207.652 2.56 277.183 141.831 207.652 2.57 277.183 141.831 207.652 2.58 277.183 141.831 70.1008 207.652 2.59 277.183 141.831 70.1008 207.652 2.6 277.183 141.831 70.1008 207.652 2.61 277.183 141.831 70.1008 207.652 2.62 280.403 141.831 70.1008 207.652 2.63 280.403 141.831 70.1008 207.652 2.64 280.403 141.831 70.1008 207.652 2.65 280.403 141.831 70.1008 207.652 2.66 280.403 70.1008 207.652 2.67 280.403 70.1008 207.652 2.68 280.403 210.065 70.1008 2.69 280.403 210.065 70.1008 2.7 280.403 210.065 70.1008 2.71 280.403 210.065 70.1008 2.72 280.403 210.065 70.1008 2.73 280.403 210.065 70.1008 2.74 280.403 420.13 70.1008 207.652 2.75 280.403 420.13 70.1008 207.652 2.76 280.403 420.13 70.1008 207.652 2.77 280.403 420.13 70.1008 207.652 2.78 280.403 420.13 70.1008 207.652 2.79 280.403 420.13 70.1008 207.652 2.8 280.403 420.13 70.1008 207.652 2.81 280.403 420.13 70.1008 207.652 2.82 280.403 420.13 70.1008 207.652 2.83 280.403 420.13 70.1008 207.652 2.84 280.403 210.065 420.13 70.1008 2.85 280.403 210.065 420.13 70.1008 2.86 280.403 70.1008 2.87 280.403 70.1008 2.88 280.403 70.1008 2.89 280.403 70.1008 2.9 280.403 70.1008 2.91 280.403 70.1008 2.92 280.403 70.1008 2.93 280.403 70.1008 2.94 280.403 70.1008 2.95 280.403 70.1008 2.96 280.403 70.1008 2.97 280.403 70.1008 2.98 280.403 70.1008 2.99 280.403 70.1008 3.0 280.403 70.1008 3.01 280.403 70.1008 3.02 280.403 70.1008 3.03 280.403 70.1008 3.04 280.403 70.1008 207.652 3.05 280.403 70.1008 207.652 3.06 280.403 70.1008 207.652 3.07 280.403 70.1008 207.652 3.08 280.403 70.1008 207.652 3.09 280.403 70.1008 207.652 3.1 280.403 70.1008 207.652 3.11 280.403 70.1008 207.652 3.12 280.403 70.1008 207.652 3.13 280.403 70.1008 207.652 3.14 280.403 70.1008 207.652 3.15 280.403 70.1008 207.652 3.16 280.403 70.1008 207.652 3.17 280.403 70.1008 207.652 3.18 280.403 70.1008 207.652 3.19 280.403 70.1008 207.652 3.2 280.403 70.1008 207.652 3.21 280.403 70.1008 207.652 3.22 280.403 70.1008 3.23 280.403 70.1008 3.24 280.403 70.1008 3.25 280.403 70.1008 3.26 280.403 70.1008 3.27 280.403 70.1008 3.28 280.403 70.1008 3.29 280.403 70.1008 3.3 280.403 70.1008 3.31 280.403 70.1008 3.32 280.403 70.1008 3.33 280.403 70.1008 3.34 280.403 70.1008 3.35 280.403 70.1008 3.36 280.403 70.1008 3.37 280.403 70.1008 3.38 280.403 70.1008 3.39 280.403 70.1008 3.4 280.403 70.1008 3.41 280.403 70.1008 3.42 280.403 70.1008 3.43 280.403 70.1008 3.44 280.403 70.1008 3.45 280.403 70.1008 3.46 280.403 70.1008 3.47 280.403 70.1008 3.48 280.403 210.065 70.1008 3.49 280.403 210.065 70.1008 3.5 210.065 70.1008 3.51 210.065 70.1008 3.52 210.065 70.1008 3.53 210.065 70.1008 3.54 210.065 70.1008 3.55 210.065 70.1008 3.56 210.065 70.1008 3.57 210.065 70.1008 3.58 280.403 210.065 70.1008 3.59 280.403 210.065 70.1008 3.6 280.403 210.065 70.1008 3.61 280.403 210.065 70.1008 3.62 280.403 210.065 70.1008 3.63 280.403 210.065 70.1008 3.64 280.403 210.065 70.1008 3.65 280.403 210.065 70.1008 3.66 280.403 210.065 70.1008 3.67 280.403 210.065 70.1008 3.68 210.065 333.458 70.1008 283.661 3.69 210.065 333.458 70.1008 283.661 3.7 210.065 333.458 70.1008 3.71 210.065 333.458 70.1008 3.72 210.065 333.458 70.1008 3.73 210.065 333.458 70.1008 3.74 210.065 333.458 70.1008 3.75 210.065 333.458 70.1008 3.76 210.065 333.458 70.1008 3.77 210.065 333.458 70.1008 3.78 210.065 333.458 70.1008 3.79 210.065 333.458 70.1008 3.8 210.065 333.458 70.1008 3.81 210.065 333.458 70.1008 3.82 210.065 333.458 70.1008 3.83 210.065 333.458 70.1008 3.84 210.065 333.458 70.1008 3.85 210.065 333.458 70.1008 3.86 210.065 333.458 70.1008 3.87 210.065 333.458 70.1008 3.88 210.065 333.458 70.1008 3.89 210.065 333.458 70.1008 3.9 333.458 70.1008 3.91 333.458 70.1008 3.92 333.458 70.1008 3.93 333.458 70.1008 3.94 333.458 70.1008 3.95 333.458 70.1008 3.96 333.458 70.1008 3.97 333.458 70.1008 3.98 333.458 70.1008 3.99 333.458 70.1008 4.0 333.458 70.1008 4.01 333.458 70.1008 4.02 333.458 70.1008 4.03 333.458 70.1008 4.04 333.458 70.1008 4.05 333.458 70.1008 4.06 210.065 333.458 70.1008 4.07 210.065 333.458 70.1008 4.08 210.065 333.458 70.1008 4.09 210.065 333.458 70.1008 4.1 210.065 333.458 70.1008 4.11 210.065 333.458 70.1008 4.12 333.458 70.1008 207.652 4.13 333.458 70.1008 207.652 4.14 333.458 70.1008 207.652 4.15 333.458 70.1008 207.652 4.16 333.458 70.1008 207.652 4.17 333.458 70.1008 207.652 4.18 333.458 70.1008 207.652 4.19 333.458 70.1008 207.652 4.2 333.458 70.1008 207.652 4.21 333.458 70.1008 207.652 4.22 333.458 70.1008 207.652 4.23 333.458 70.1008 207.652 4.24 333.458 70.1008 207.652 4.25 333.458 70.1008 207.652 4.26 333.458 70.1008 207.652 4.27 333.458 70.1008 207.652 4.28 333.458 70.1008 207.652 4.29 333.458 70.1008 207.652 4.3 333.458 70.1008 207.652 4.31 333.458 70.1008 207.652 4.32 333.458 70.1008 207.652 4.33 333.458 70.1008 207.652 4.34 333.458 70.1008 207.652 4.35 333.458 70.1008 207.652 4.36 70.1008 207.652 4.37 70.1008 207.652 4.38 70.1008 207.652 4.39 70.1008 207.652 4.4 70.1008 207.652 4.41 70.1008 207.652 4.42 70.1008 207.652 4.43 70.1008 207.652 4.44 70.1008 207.652 4.45 70.1008 207.652 4.46 70.1008 207.652 4.47 70.1008 207.652 4.48 70.1008 207.652 4.49 70.1008 207.652 4.5 70.1008 207.652 4.51 70.1008 207.652 4.52 70.1008 207.652 4.53 70.1008 207.652 4.54 70.1008 207.652 4.55 70.1008 207.652 4.56 70.1008 4.57 70.1008 4.58 70.1008 4.59 70.1008 4.6 273.999 70.1008 4.61 273.999 70.1008 4.62 273.999 70.1008 207.652 4.63 273.999 70.1008 207.652 4.64 273.999 70.1008 207.652 4.65 273.999 70.1008 207.652 4.66 280.403 70.1008 207.652 4.67 280.403 70.1008 207.652 4.68 280.403 207.652 4.69 280.403 207.652 4.7 280.403 207.652 4.71 280.403 207.652 4.72 280.403 207.652 4.73 280.403 207.652 4.74 280.403 207.652 4.75 280.403 207.652 4.76 280.403 207.652 4.77 280.403 207.652 4.78 280.403 207.652 4.79 280.403 207.652 4.8 280.403 207.652 4.81 280.403 207.652 4.82 280.403 207.652 4.83 280.403 207.652 4.84 280.403 210.065 333.458 4.85 280.403 210.065 333.458 4.86 280.403 210.065 333.458 4.87 280.403 210.065 333.458 4.88 280.403 333.458 4.89 280.403 333.458 4.9 280.403 333.458 4.91 280.403 333.458 4.92 280.403 333.458 4.93 280.403 333.458 4.94 280.403 333.458 4.95 280.403 333.458 4.96 333.458 277.183 4.97 333.458 277.183 4.98 333.458 277.183 4.99 333.458 277.183 5.0 333.458 277.183 5.01 333.458 277.183 5.02 333.458 277.183 5.03 333.458 277.183 5.04 280.403 333.458 5.05 280.403 333.458 5.06 280.403 337.332 5.07 280.403 337.332 5.08 280.403 337.332 5.09 280.403 337.332 5.1 280.403 337.332 5.11 280.403 337.332 5.12 280.403 333.458 5.13 280.403 333.458 5.14 280.403 70.1008 333.458 5.15 280.403 70.1008 333.458 5.16 280.403 70.1008 333.458 5.17 280.403 70.1008 333.458 5.18 280.403 70.1008 333.458 5.19 280.403 70.1008 333.458 5.2 280.403 70.1008 333.458 5.21 280.403 70.1008 333.458 5.22 280.403 70.1008 333.458 5.23 280.403 70.1008 333.458 5.24 280.403 70.1008 333.458 5.25 280.403 70.1008 333.458 5.26 280.403 70.1008 333.458 5.27 280.403 70.1008 333.458 5.28 280.403 70.1008 333.458 5.29 280.403 70.1008 333.458 5.3 280.403 70.1008 333.458 5.31 280.403 70.1008 333.458 5.32 280.403 70.1008 333.458 5.33 280.403 70.1008 333.458 5.34 280.403 70.1008 333.458 5.35 280.403 70.1008 333.458 5.36 280.403 70.1008 333.458 5.37 280.403 70.1008 333.458 5.38 280.403 70.1008 333.458 5.39 280.403 70.1008 333.458 5.4 280.403 70.1008 333.458 5.41 280.403 70.1008 333.458 5.42 280.403 70.1008 333.458 5.43 280.403 70.1008 333.458 5.44 280.403 70.1008 333.458 5.45 280.403 70.1008 333.458 5.46 280.403 70.1008 333.458 5.47 280.403 70.1008 333.458 5.48 280.403 70.1008 333.458 5.49 280.403 70.1008 333.458 5.5 280.403 210.065 70.1008 333.458 5.51 280.403 210.065 70.1008 333.458 5.52 280.403 210.065 70.1008 333.458 5.53 280.403 210.065 70.1008 333.458 5.54 280.403 210.065 70.1008 333.458 5.55 280.403 210.065 70.1008 333.458 5.56 280.403 210.065 70.1008 333.458 5.57 280.403 210.065 70.1008 333.458 5.58 280.403 70.1008 333.458 207.652 5.59 280.403 70.1008 333.458 207.652 5.6 280.403 70.1008 333.458 207.652 5.61 280.403 70.1008 333.458 207.652 5.62 280.403 70.1008 333.458 207.652 5.63 280.403 70.1008 333.458 207.652 5.64 280.403 70.1008 333.458 207.652 5.65 280.403 70.1008 333.458 207.652 5.66 280.403 70.1008 333.458 207.652 5.67 280.403 70.1008 333.458 207.652 5.68 280.403 70.1008 333.458 207.652 5.69 280.403 70.1008 333.458 207.652 5.7 280.403 70.1008 333.458 207.652 5.71 280.403 70.1008 333.458 207.652 5.72 280.403 70.1008 333.458 207.652 5.73 280.403 70.1008 333.458 207.652 5.74 280.403 70.1008 333.458 207.652 5.75 280.403 70.1008 333.458 207.652 5.76 280.403 70.1008 333.458 207.652 5.77 280.403 70.1008 333.458 207.652 5.78 280.403 70.1008 333.458 207.652 5.79 280.403 70.1008 333.458 207.652 5.8 280.403 70.1008 207.652 5.81 280.403 70.1008 207.652 5.82 280.403 70.1008 207.652 5.83 280.403 70.1008 207.652 5.84 280.403 70.1008 207.652 5.85 280.403 70.1008 207.652 5.86 280.403 70.1008 207.652 5.87 280.403 70.1008 207.652 5.88 280.403 207.652 5.89 280.403 207.652 5.9 280.403 207.652 5.91 280.403 207.652 5.92 280.403 207.652 5.93 280.403 207.652 5.94 280.403 210.065 5.95 280.403 210.065 5.96 210.065 277.183 5.97 210.065 277.183 5.98 210.065 277.183 5.99 210.065 277.183 6.0 210.065 277.183 6.01 210.065 277.183 6.02 280.403 210.065 6.03 280.403 210.065 6.04 280.403 210.065 6.05 280.403 210.065 6.06 280.403 210.065 6.07 280.403 210.065 6.08 280.403 207.652 6.09 280.403 207.652 6.1 283.661 207.652 6.11 283.661 207.652 6.12 283.661 207.652 6.13 283.661 207.652 6.14 283.661 207.652 6.15 283.661 207.652 6.16 280.403 207.652 6.17 280.403 207.652 6.18 280.403 207.652 6.19 280.403 207.652 6.2 280.403 207.652 6.21 280.403 207.652 6.22 280.403 207.652 6.23 280.403 207.652 6.24 280.403 207.652 6.25 280.403 207.652 6.26 280.403 207.652 6.27 280.403 207.652 6.28 280.403 207.652 6.29 280.403 207.652 6.3 207.652 6.31 207.652 6.32 207.652 6.33 207.652 6.34 210.065 6.35 210.065 6.36 210.065 6.37 210.065 6.38 210.065 6.39 210.065 6.4 210.065 6.41 210.065 6.42 210.065 6.43 210.065 6.44 210.065 6.45 210.065 6.46 6.47 6.48 6.49 6.5 6.51 6.52 6.53 6.54 6.55 6.56 333.458 6.57 333.458 6.58 280.403 333.458 6.59 280.403 333.458 6.6 280.403 333.458 6.61 280.403 333.458 6.62 280.403 333.458 6.63 280.403 333.458 6.64 280.403 333.458 6.65 280.403 333.458 6.66 280.403 333.458 6.67 280.403 333.458 6.68 333.458 277.183 6.69 333.458 277.183 6.7 333.458 277.183 6.71 333.458 277.183 6.72 333.458 277.183 6.73 333.458 277.183 6.74 280.403 333.458 6.75 280.403 333.458 6.76 280.403 333.458 6.77 280.403 333.458 6.78 280.403 333.458 6.79 280.403 333.458 6.8 280.403 333.458 6.81 280.403 333.458 6.82 280.403 333.458 6.83 280.403 333.458 6.84 280.403 333.458 6.85 280.403 333.458 6.86 280.403 333.458 6.87 280.403 333.458 6.88 280.403 333.458 6.89 280.403 333.458 6.9 280.403 333.458 6.91 280.403 333.458 6.92 280.403 333.458 6.93 280.403 333.458 6.94 280.403 333.458 6.95 280.403 333.458 6.96 280.403 333.458 6.97 280.403 333.458 6.98 280.403 210.065 333.458 6.99 280.403 210.065 333.458 7.0 280.403 210.065 333.458 7.01 280.403 210.065 333.458 7.02 280.403 210.065 333.458 7.03 280.403 210.065 333.458 7.04 280.403 333.458 207.652 7.05 280.403 333.458 207.652 7.06 280.403 333.458 207.652 7.07 280.403 333.458 207.652 7.08 280.403 333.458 207.652 7.09 280.403 333.458 207.652 7.1 280.403 333.458 207.652 7.11 280.403 333.458 207.652 7.12 280.403 333.458 207.652 7.13 280.403 333.458 207.652 7.14 280.403 333.458 207.652 7.15 280.403 333.458 207.652 7.16 280.403 207.652 7.17 280.403 207.652 7.18 280.403 207.652 7.19 280.403 207.652 7.2 280.403 207.652 7.21 280.403 207.652 7.22 280.403 207.652 7.23 280.403 207.652 7.24 280.403 207.652 7.25 280.403 207.652 7.26 280.403 207.652 7.27 280.403 207.652 7.28 207.652 277.183 7.29 207.652 277.183 7.3 207.652 277.183 7.31 207.652 277.183 7.32 207.652 277.183 7.33 207.652 277.183 7.34 207.652 7.35 207.652 7.36 207.652 7.37 207.652 7.38 207.652 7.39 207.652 7.4 207.652 7.41 207.652 7.42 207.652 7.43 207.652 7.44 207.652 7.45 207.652 7.46 207.652 7.47 207.652 7.48 207.652 7.49 207.652 7.5 207.652 7.51 207.652 7.52 280.403 207.652 7.53 280.403 207.652 7.54 280.403 207.652 7.55 280.403 207.652 7.56 280.403 207.652 7.57 280.403 207.652 7.58 280.403 207.652 7.59 280.403 207.652 7.6 280.403 7.61 280.403 7.62 280.403 7.63 280.403 7.64 280.403 7.65 280.403 7.66 280.403 7.67 280.403 7.68 280.403 7.69 280.403 7.7 277.183 7.71 277.183 7.72 277.183 7.73 277.183 7.74 277.183 7.75 277.183 7.76 277.183 7.77 277.183 7.78 277.183 7.79 277.183 7.8 280.403 7.81 280.403 7.82 280.403 7.83 280.403 7.84 280.403 7.85 280.403 7.86 280.403 7.87 280.403 7.88 280.403 7.89 280.403 7.9 280.403 7.91 280.403 7.92 280.403 7.93 280.403 7.94 277.183 7.95 277.183 7.96 277.183 7.97 277.183 7.98 7.99 8.0 333.458 8.01 333.458 8.02 333.458 8.03 333.458 8.04 333.458 8.05 333.458 8.06 333.458 8.07 333.458 8.08 333.458 8.09 333.458 8.1 333.458 8.11 333.458 8.12 333.458 8.13 333.458 8.14 333.458 8.15 333.458 8.16 333.458 8.17 333.458 8.18 333.458 8.19 333.458 8.2 333.458 8.21 333.458 8.22 333.458 8.23 333.458 8.24 333.458 8.25 333.458 8.26 8.27 8.28 8.29 8.3 8.31 8.32 8.33 8.34 333.458 8.35 333.458 8.36 333.458 8.37 333.458 8.38 333.458 8.39 333.458 8.4 333.458 8.41 333.458 8.42 333.458 207.652 8.43 333.458 207.652 8.44 333.458 207.652 8.45 333.458 207.652 8.46 207.652 8.47 207.652 8.48 126.357 205.267 8.49 126.357 205.267 8.5 126.357 205.267 8.51 126.357 205.267 8.52 126.357 205.267 8.53 126.357 205.267 8.54 124.905 207.652 8.55 124.905 207.652 8.56 124.905 207.652 8.57 124.905 207.652 8.58 124.905 207.652 8.59 124.905 207.652 8.6 124.905 207.652 311.127 8.61 124.905 207.652 311.127 8.62 124.905 207.652 311.127 8.63 124.905 207.652 311.127 8.64 124.905 207.652 311.127 8.65 124.905 207.652 311.127 8.66 307.553 124.905 207.652 8.67 307.553 124.905 207.652 8.68 307.553 124.905 207.652 8.69 307.553 124.905 207.652 8.7 307.553 124.905 207.652 420.13 8.71 307.553 124.905 207.652 420.13 8.72 63.9125 124.905 207.652 420.13 8.73 63.9125 124.905 207.652 420.13 8.74 63.9125 124.905 207.652 420.13 8.75 63.9125 124.905 207.652 420.13 8.76 63.9125 124.905 207.652 420.13 8.77 63.9125 124.905 207.652 420.13 8.78 187.147 63.9125 124.905 207.652 420.13 8.79 187.147 63.9125 124.905 207.652 420.13 8.8 187.147 63.9125 124.905 207.652 425.012 8.81 187.147 63.9125 124.905 207.652 425.012 8.82 187.147 63.9125 124.905 207.652 8.83 187.147 63.9125 124.905 207.652 8.84 187.147 63.9125 124.905 207.652 8.85 187.147 63.9125 124.905 207.652 8.86 187.147 63.9125 124.905 207.652 8.87 187.147 63.9125 124.905 207.652 8.88 187.147 63.9125 124.905 207.652 8.89 187.147 63.9125 124.905 207.652 8.9 187.147 63.9125 124.905 207.652 8.91 187.147 63.9125 124.905 207.652 8.92 187.147 63.9125 124.905 207.652 8.93 187.147 63.9125 124.905 207.652 8.94 187.147 63.9125 124.905 207.652 8.95 187.147 63.9125 124.905 207.652 8.96 187.147 124.905 207.652 311.127 8.97 187.147 124.905 207.652 311.127 8.98 187.147 124.905 207.652 311.127 8.99 187.147 124.905 207.652 311.127 9.0 187.147 124.905 207.652 311.127 9.01 187.147 124.905 207.652 311.127 9.02 187.147 124.905 207.652 311.127 9.03 187.147 124.905 207.652 311.127 9.04 124.905 207.652 311.127 9.05 124.905 207.652 311.127 9.06 124.905 207.652 311.127 9.07 124.905 207.652 311.127 9.08 124.905 311.127 9.09 124.905 311.127 9.1 124.905 311.127 9.11 124.905 311.127 9.12 124.905 311.127 9.13 124.905 311.127 9.14 124.905 311.127 9.15 124.905 311.127 9.16 187.147 124.905 311.127 9.17 187.147 124.905 311.127 9.18 187.147 124.905 311.127 9.19 187.147 124.905 311.127 9.2 187.147 124.905 311.127 9.21 187.147 124.905 311.127 9.22 187.147 124.905 311.127 9.23 187.147 124.905 311.127 9.24 187.147 124.905 311.127 9.25 187.147 124.905 311.127 9.26 187.147 124.905 311.127 9.27 187.147 124.905 311.127 9.28 187.147 280.403 124.905 311.127 9.29 187.147 280.403 124.905 311.127 9.3 187.147 280.403 124.905 311.127 9.31 187.147 280.403 124.905 311.127 9.32 187.147 280.403 124.905 311.127 9.33 187.147 280.403 124.905 311.127 9.34 187.147 280.403 124.905 311.127 9.35 187.147 280.403 124.905 311.127 9.36 187.147 280.403 124.905 311.127 9.37 187.147 280.403 124.905 311.127 9.38 187.147 280.403 124.905 311.127 9.39 187.147 280.403 124.905 311.127 9.4 187.147 124.905 311.127 9.41 187.147 124.905 311.127 9.42 187.147 124.905 311.127 9.43 187.147 124.905 311.127 9.44 187.147 124.905 311.127 9.45 187.147 124.905 311.127 9.46 187.147 124.905 311.127 9.47 187.147 124.905 311.127 9.48 187.147 124.905 311.127 9.49 187.147 124.905 311.127 9.5 187.147 124.905 311.127 9.51 187.147 124.905 311.127 9.52 187.147 124.905 311.127 9.53 187.147 124.905 311.127 9.54 124.905 311.127 9.55 124.905 311.127 9.56 124.905 311.127 9.57 124.905 311.127 9.58 124.905 311.127 9.59 124.905 311.127 9.6 124.905 311.127 9.61 124.905 311.127 9.62 124.905 311.127 9.63 124.905 311.127 9.64 124.905 311.127 9.65 124.905 311.127 9.66 124.905 9.67 124.905 9.68 124.905 9.69 124.905 9.7 124.905 9.71 124.905 9.72 124.905 9.73 124.905 9.74 124.905 9.75 124.905 9.76 124.905 9.77 124.905 9.78 124.905 9.79 124.905 9.8 124.905 9.81 124.905 9.82 124.905 9.83 124.905 9.84 124.905 9.85 124.905 9.86 124.905 9.87 124.905 9.88 124.905 9.89 124.905 9.9 124.905 9.91 124.905 9.92 124.905 9.93 124.905 9.94 124.905 9.95 124.905 9.96 124.905 9.97 124.905 9.98 124.905 9.99 124.905 10.0 124.905 10.01 124.905 10.02 124.905 10.03 124.905 10.04 210.065 10.05 210.065 10.06 210.065 10.07 210.065 10.08 210.065 10.09 210.065 10.1 207.652 10.11 207.652 10.12 207.652 10.13 207.652 10.14 207.652 10.15 207.652 10.16 207.652 10.17 207.652 10.18 207.652 10.19 207.652 10.2 207.652 10.21 207.652 10.22 207.652 10.23 207.652 10.24 207.652 10.25 207.652 10.26 207.652 10.27 207.652 10.28 207.652 10.29 207.652 10.3 207.652 10.31 207.652 10.32 207.652 10.33 207.652 10.34 207.652 10.35 207.652 10.36 207.652 10.37 207.652 10.38 207.652 10.39 207.652 10.4 207.652 10.41 207.652 10.42 207.652 10.43 207.652 10.44 207.652 10.45 207.652 10.46 207.652 10.47 207.652 10.48 207.652 10.49 207.652 10.5 207.652 10.51 207.652 10.52 10.53 10.54 10.55 10.56 10.57 10.58 10.59 10.6 277.183 10.61 277.183 10.62 277.183 10.63 277.183 10.64 277.183 10.65 277.183 10.66 280.403 10.67 280.403 10.68 280.403 10.69 280.403 10.7 280.403 10.71 280.403 10.72 280.403 10.73 280.403 10.74 280.403 10.75 280.403 10.76 280.403 10.77 280.403 10.78 280.403 10.79 280.403 10.8 280.403 10.81 280.403 10.82 280.403 10.83 280.403 10.84 10.85 10.86 10.87 10.88 10.89 10.9 10.91 10.92 10.93 10.94 10.95 10.96 10.97 10.98 10.99 11.0 11.01 11.02 11.03 11.04 11.05 11.06 333.458 11.07 333.458 11.08 333.458 11.09 333.458 11.1 333.458 11.11 333.458 11.12 333.458 11.13 333.458 11.14 333.458 11.15 333.458 11.16 333.458 11.17 333.458 11.18 333.458 11.19 333.458 11.2 333.458 11.21 333.458 11.22 333.458 11.23 333.458 11.24 333.458 11.25 333.458 11.26 333.458 11.27 333.458 11.28 333.458 11.29 333.458 11.3 333.458 11.31 333.458 11.32 333.458 11.33 333.458 11.34 333.458 11.35 333.458 11.36 333.458 11.37 333.458 11.38 333.458 11.39 333.458 11.4 333.458 11.41 333.458 11.42 333.458 11.43 333.458 11.44 333.458 11.45 333.458 11.46 333.458 11.47 333.458 11.48 333.458 207.652 11.49 333.458 207.652 11.5 207.652 11.51 207.652 11.52 207.652 11.53 207.652 11.54 207.652 11.55 207.652 11.56 207.652 11.57 207.652 11.58 207.652 11.59 207.652 11.6 207.652 11.61 207.652 11.62 207.652 11.63 207.652 11.64 207.652 11.65 207.652 11.66 207.652 11.67 207.652 11.68 207.652 11.69 207.652 11.7 207.652 11.71 207.652 11.72 207.652 11.73 207.652 11.74 207.652 11.75 207.652 11.76 207.652 11.77 207.652 11.78 207.652 11.79 207.652 11.8 207.652 11.81 207.652 11.82 207.652 11.83 207.652 11.84 207.652 11.85 207.652 11.86 207.652 11.87 207.652 11.88 207.652 11.89 207.652 11.9 207.652 11.91 207.652 11.92 207.652 11.93 207.652 11.94 207.652 11.95 207.652 11.96 207.652 11.97 207.652 11.98 11.99 12.0 12.01 12.02 12.03 12.04 280.403 12.05 280.403 12.06 280.403 12.07 280.403 12.08 280.403 12.09 280.403 12.1 280.403 12.11 280.403 12.12 280.403 12.13 280.403 12.14 280.403 12.15 280.403 12.16 280.403 12.17 280.403 12.18 280.403 12.19 280.403 12.2 280.403 12.21 280.403 12.22 280.403 12.23 280.403 12.24 280.403 12.25 280.403 12.26 12.27 12.28 12.29 12.3 12.31 12.32 12.33 12.34 12.35 12.36 12.37 12.38 12.39 12.4 12.41 12.42 12.43 12.44 12.45 12.46 333.458 12.47 333.458 12.48 333.458 12.49 333.458 12.5 333.458 12.51 333.458 12.52 333.458 12.53 333.458 12.54 333.458 12.55 333.458 12.56 333.458 12.57 333.458 12.58 333.458 12.59 333.458 12.6 333.458 12.61 333.458 12.62 333.458 12.63 333.458 12.64 333.458 12.65 333.458 12.66 333.458 12.67 333.458 12.68 333.458 12.69 333.458 12.7 333.458 12.71 333.458 12.72 12.73 12.74 12.75 12.76 12.77 12.78 12.79 12.8 12.81 12.82 12.83 12.84 12.85 12.86 207.652 12.87 207.652 12.88 207.652 12.89 207.652 12.9 207.652 12.91 207.652 12.92 207.652 12.93 207.652 12.94 207.652 12.95 207.652 12.96 207.652 12.97 207.652 12.98 207.652 12.99 207.652 13.0 207.652 13.01 207.652 13.02 207.652 13.03 207.652 13.04 207.652 13.05 207.652 13.06 207.652 13.07 207.652 13.08 207.652 13.09 207.652 13.1 207.652 13.11 207.652 13.12 207.652 13.13 207.652 13.14 207.652 13.15 207.652 13.16 207.652 13.17 207.652 13.18 207.652 13.19 207.652 13.2 207.652 13.21 207.652 13.22 207.652 13.23 207.652 13.24 207.652 13.25 207.652 13.26 207.652 13.27 207.652 13.28 207.652 13.29 207.652 13.3 207.652 13.31 207.652 13.32 207.652 13.33 207.652 13.34 207.652 13.35 207.652 13.36 207.652 13.37 207.652 13.38 207.652 13.39 207.652 13.4 283.661 13.41 283.661 13.42 283.661 13.43 283.661 13.44 283.661 13.45 283.661 13.46 280.403 13.47 280.403 13.48 280.403 13.49 280.403 13.5 280.403 13.51 280.403 13.52 280.403 13.53 280.403 13.54 280.403 13.55 280.403 13.56 280.403 13.57 280.403 13.58 280.403 13.59 280.403 13.6 280.403 13.61 280.403 13.62 280.403 13.63 280.403 13.64 280.403 13.65 280.403 13.66 277.183 13.67 277.183 13.68 277.183 13.69 277.183 13.7 277.183 13.71 277.183 13.72 277.183 13.73 277.183 13.74 277.183 13.75 277.183 13.76 277.183 13.77 277.183 13.78 277.183 13.79 277.183 13.8 277.183 13.81 277.183 13.82 277.183 13.83 277.183 13.84 280.403 13.85 280.403 13.86 280.403 13.87 280.403 13.88 329.628 280.403 13.89 329.628 280.403 13.9 329.628 280.403 13.91 329.628 280.403 13.92 329.628 280.403 13.93 329.628 280.403 13.94 280.403 333.458 13.95 280.403 333.458 13.96 280.403 333.458 13.97 280.403 333.458 13.98 333.458 13.99 333.458 14.0 333.458 14.01 333.458 14.02 333.458 277.183 14.03 333.458 277.183 14.04 333.458 277.183 14.05 333.458 277.183 14.06 333.458 277.183 14.07 333.458 277.183 14.08 280.403 333.458 14.09 280.403 333.458 14.1 280.403 333.458 14.11 280.403 333.458 14.12 280.403 333.458 14.13 280.403 333.458 14.14 329.628 280.403 14.15 329.628 280.403 14.16 329.628 280.403 14.17 329.628 280.403 14.18 329.628 280.403 14.19 329.628 280.403 14.2 280.403 333.458 14.21 280.403 333.458 14.22 280.403 333.458 14.23 280.403 333.458 14.24 280.403 333.458 14.25 280.403 333.458 14.26 329.628 280.403 14.27 329.628 280.403 14.28 329.628 280.403 14.29 329.628 280.403 14.3 329.628 280.403 14.31 329.628 280.403 14.32 280.403 333.458 14.33 280.403 333.458 14.34 280.403 333.458 14.35 280.403 333.458 14.36 280.403 333.458 14.37 280.403 333.458 14.38 280.403 14.39 280.403 14.4 280.403 14.41 280.403 14.42 220 14.43 220 14.44 220 111.278 14.45 220 111.278 14.46 220 111.278 14.47 220 111.278 14.48 220 111.278 14.49 220 111.278 14.5 168.666 220 111.278 14.51 168.666 220 111.278 14.52 168.666 220 111.278 14.53 168.666 220 111.278 14.54 168.666 220 277.183 111.278 14.55 168.666 220 277.183 111.278 14.56 220 277.183 111.278 166.729 14.57 220 277.183 111.278 166.729 14.58 220 277.183 111.278 166.729 14.59 220 277.183 111.278 166.729 14.6 220 277.183 111.278 166.729 14.61 220 277.183 111.278 166.729 14.62 220 277.183 111.278 166.729 14.63 220 277.183 111.278 166.729 14.64 220 277.183 111.278 166.729 14.65 220 277.183 111.278 166.729 14.66 220 277.183 111.278 166.729 14.67 220 277.183 111.278 166.729 14.68 220 277.183 111.278 166.729 14.69 220 277.183 111.278 166.729 14.7 220 277.183 111.278 166.729 14.71 220 277.183 111.278 166.729 14.72 220 277.183 111.278 166.729 14.73 220 277.183 111.278 166.729 14.74 220 277.183 111.278 166.729 14.75 220 277.183 111.278 166.729 14.76 220 277.183 111.278 166.729 14.77 220 277.183 111.278 166.729 14.78 220 111.278 166.729 14.79 220 111.278 166.729 14.8 220 111.278 166.729 14.81 220 111.278 166.729 14.82 220 111.278 166.729 14.83 220 111.278 166.729 14.84 220 111.278 166.729 14.85 220 111.278 166.729 14.86 220 111.278 166.729 14.87 220 111.278 166.729 14.88 220 111.278 166.729 14.89 220 111.278 166.729 14.9 220 111.278 166.729 14.91 220 111.278 166.729 14.92 220 111.278 166.729 14.93 220 111.278 166.729 14.94 220 111.278 166.729 14.95 220 111.278 166.729 14.96 220 111.278 166.729 14.97 220 111.278 166.729 14.98 220 111.278 166.729 14.99 220 111.278 166.729 15.0 111.278 166.729 15.01 111.278 166.729 15.02 111.278 166.729 15.03 111.278 166.729 15.04 277.183 111.278 166.729 15.05 277.183 111.278 166.729 15.06 277.183 111.278 166.729 15.07 277.183 111.278 166.729 15.08 277.183 111.278 166.729 15.09 277.183 111.278 166.729 15.1 277.183 111.278 166.729 15.11 277.183 111.278 166.729 15.12 277.183 111.278 166.729 15.13 277.183 111.278 166.729 15.14 277.183 111.278 166.729 15.15 277.183 111.278 166.729 15.16 280.403 111.278 166.729 15.17 280.403 111.278 166.729 15.18 280.403 111.278 166.729 15.19 280.403 111.278 166.729 15.2 280.403 111.278 166.729 15.21 280.403 111.278 166.729 15.22 280.403 111.278 166.729 15.23 280.403 111.278 166.729 15.24 280.403 111.278 166.729 15.25 280.403 111.278 166.729 15.26 277.183 111.278 166.729 15.27 277.183 111.278 166.729 15.28 277.183 111.278 166.729 15.29 277.183 111.278 166.729 15.3 277.183 111.278 15.31 277.183 111.278 15.32 277.183 111.278 15.33 277.183 111.278 15.34 277.183 111.278 15.35 277.183 111.278 15.36 277.183 111.278 15.37 277.183 111.278 15.38 277.183 111.278 15.39 277.183 111.278 15.4 277.183 111.278 15.41 277.183 111.278 15.42 277.183 111.278 15.43 277.183 111.278 15.44 277.183 111.278 15.45 277.183 111.278 15.46 277.183 111.278 15.47 277.183 111.278 15.48 277.183 111.278 15.49 277.183 111.278 15.5 277.183 111.278 15.51 277.183 111.278 15.52 277.183 111.278 15.53 277.183 111.278 15.54 277.183 111.278 15.55 277.183 111.278 15.56 277.183 111.278 15.57 277.183 111.278 15.58 277.183 111.278 15.59 277.183 111.278 15.6 277.183 111.278 15.61 277.183 111.278 15.62 277.183 111.278 15.63 277.183 111.278 15.64 277.183 111.278 15.65 277.183 111.278 15.66 111.278 15.67 111.278 15.68 111.278 15.69 111.278 15.7 111.278 15.71 111.278 15.72 111.278 15.73 111.278 15.74 111.278 15.75 111.278 15.76 111.278 15.77 111.278 15.78 111.278 15.79 111.278 15.8 111.278 15.81 111.278 15.82 111.278 15.83 111.278 15.84 277.183 111.278 15.85 277.183 111.278 15.86 277.183 111.278 15.87 277.183 111.278 15.88 277.183 111.278 15.89 277.183 111.278 15.9 277.183 111.278 15.91 277.183 111.278 15.92 277.183 111.278 15.93 277.183 111.278 15.94 283.661 111.278 15.95 283.661 111.278 15.96 111.278 15.97 111.278 15.98 220 111.278 15.99 220 111.278 16.0 220 111.278 16.01 220 111.278 16.02 220 111.278 16.03 220 111.278 16.04 220 111.278 16.05 220 111.278 16.06 220 111.278 16.07 220 111.278 16.08 220 111.278 16.09 220 111.278 16.1 220 111.278 16.11 220 111.278 16.12 220 111.278 16.13 220 111.278 16.14 220 111.278 16.15 220 111.278 16.16 220 111.278 16.17 220 111.278 16.18 220 111.278 16.19 220 111.278 16.2 220 111.278 16.21 220 111.278 16.22 220 111.278 16.23 220 111.278 16.24 220 111.278 16.25 220 111.278 16.26 220 111.278 16.27 220 111.278 16.28 220 111.278 16.29 220 111.278 16.3 220 111.278 16.31 220 111.278 16.32 220 111.278 16.33 220 111.278 16.34 220 111.278 16.35 220 111.278 16.36 220 111.278 16.37 220 111.278 16.38 220 111.278 16.39 220 111.278 16.4 220 16.41 220 16.42 220 16.43 220 16.44 220 111.278 16.45 220 111.278 16.46 283.661 111.278 16.47 283.661 111.278 16.48 283.661 111.278 16.49 283.661 111.278 16.5 283.661 111.278 16.51 283.661 111.278 16.52 280.403 111.278 16.53 280.403 111.278 16.54 280.403 111.278 16.55 280.403 111.278 16.56 280.403 111.278 16.57 280.403 111.278 16.58 280.403 111.278 16.59 280.403 111.278 16.6 280.403 16.61 280.403 16.62 280.403 16.63 280.403 16.64 280.403 16.65 280.403 16.66 280.403 16.67 280.403 16.68 280.403 16.69 280.403 16.7 280.403 16.71 280.403 16.72 280.403 16.73 280.403 16.74 16.75 16.76 16.77 16.78 16.79 16.8 16.81 16.82 16.83 16.84 16.85 16.86 16.87 16.88 16.89 16.9 16.91 16.92 16.93 16.94 333.458 16.95 333.458 16.96 333.458 16.97 333.458 16.98 333.458 16.99 333.458 17.0 333.458 17.01 333.458 17.02 333.458 17.03 333.458 17.04 333.458 17.05 333.458 17.06 333.458 111.278 17.07 333.458 111.278 17.08 333.458 111.278 17.09 333.458 111.278 17.1 333.458 111.278 17.11 333.458 111.278 17.12 333.458 111.278 17.13 333.458 111.278 17.14 333.458 111.278 17.15 333.458 111.278 17.16 333.458 111.278 17.17 333.458 111.278 17.18 333.458 17.19 333.458 17.2 333.458 17.21 333.458 17.22 333.458 17.23 333.458 17.24 333.458 17.25 333.458 17.26 17.27 17.28 17.29 17.3 17.31 17.32 17.33 17.34 333.458 17.35 333.458 17.36 333.458 17.37 333.458 17.38 333.458 17.39 333.458 17.4 333.458 17.41 333.458 17.42 333.458 17.43 333.458 17.44 333.458 17.45 333.458 17.46 333.458 17.47 333.458 17.48 220 92.4986 17.49 220 92.4986 17.5 220 92.4986 17.51 220 92.4986 17.52 220 92.4986 17.53 220 92.4986 17.54 280.403 220 92.4986 17.55 280.403 220 92.4986 17.56 280.403 220 92.4986 17.57 280.403 220 92.4986 17.58 280.403 220 92.4986 17.59 280.403 220 92.4986 17.6 280.403 220 92.4986 17.61 280.403 220 92.4986 17.62 280.403 220 92.4986 17.63 280.403 220 92.4986 17.64 280.403 220 92.4986 17.65 280.403 220 92.4986 17.66 220 277.183 92.4986 17.67 220 277.183 92.4986 17.68 220 92.4986 17.69 220 92.4986 17.7 220 92.4986 17.71 220 92.4986 17.72 220 92.4986 17.73 220 92.4986 17.74 220 92.4986 17.75 220 92.4986 17.76 220 92.4986 17.77 220 92.4986 17.78 220 92.4986 17.79 220 92.4986 17.8 220 92.4986 17.81 220 92.4986 17.82 220 92.4986 17.83 220 92.4986 17.84 220 92.4986 17.85 220 92.4986 17.86 220 92.4986 17.87 220 92.4986 17.88 220 92.4986 17.89 220 92.4986 17.9 220 92.4986 17.91 220 92.4986 17.92 220 92.4986 17.93 220 92.4986 17.94 220 92.4986 17.95 220 92.4986 17.96 220 92.4986 17.97 220 92.4986 17.98 220 92.4986 17.99 220 92.4986 18.0 220 92.4986 18.01 220 92.4986 18.02 220 92.4986 18.03 220 92.4986 18.04 297.077 220 92.4986 18.05 297.077 220 92.4986 18.06 297.077 220 92.4986 18.07 297.077 220 92.4986 18.08 297.077 220 92.4986 18.09 297.077 220 92.4986 18.1 297.077 220 92.4986 18.11 297.077 220 92.4986 18.12 297.077 220 92.4986 18.13 297.077 220 92.4986 18.14 297.077 220 92.4986 18.15 297.077 220 92.4986 18.16 297.077 220 92.4986 18.17 297.077 220 92.4986 18.18 297.077 220 92.4986 18.19 297.077 220 92.4986 18.2 297.077 220 92.4986 18.21 297.077 220 92.4986 18.22 297.077 220 92.4986 18.23 297.077 220 92.4986 18.24 297.077 220 92.4986 18.25 297.077 220 92.4986 18.26 297.077 92.4986 18.27 297.077 92.4986 18.28 297.077 92.4986 18.29 297.077 92.4986 18.3 297.077 92.4986 18.31 297.077 92.4986 18.32 92.4986 18.33 92.4986 18.34 92.4986 18.35 92.4986 18.36 92.4986 18.37 92.4986 18.38 92.4986 18.39 92.4986 18.4 92.4986 18.41 92.4986 18.42 92.4986 18.43 92.4986 18.44 92.4986 18.45 92.4986 18.46 92.4986 18.47 92.4986 18.48 92.4986 18.49 92.4986 18.5 92.4986 18.51 92.4986 18.52 92.4986 18.53 92.4986 18.54 92.4986 18.55 92.4986 18.56 92.4986 18.57 92.4986 18.58 92.4986 18.59 92.4986 18.6 92.4986 18.61 92.4986 18.62 92.4986 18.63 92.4986 18.64 92.4986 18.65 92.4986 18.66 92.4986 18.67 92.4986 18.68 92.4986 18.69 92.4986 18.7 92.4986 18.71 92.4986 18.72 92.4986 18.73 92.4986 18.74 92.4986 18.75 92.4986 18.76 92.4986 18.77 92.4986 18.78 92.4986 18.79 92.4986 18.8 92.4986 18.81 92.4986 18.82 92.4986 18.83 92.4986 18.84 92.4986 18.85 92.4986 18.86 92.4986 18.87 92.4986 18.88 92.4986 18.89 92.4986 18.9 92.4986 18.91 92.4986 18.92 92.4986 18.93 92.4986 18.94 92.4986 18.95 92.4986 18.96 92.4986 18.97 92.4986 18.98 220 92.4986 18.99 220 92.4986 19.0 220 92.4986 19.01 220 92.4986 19.02 220 92.4986 19.03 220 92.4986 19.04 220 92.4986 19.05 220 92.4986 19.06 220 92.4986 19.07 220 92.4986 19.08 220 92.4986 19.09 220 92.4986 19.1 220 92.4986 19.11 220 92.4986 19.12 220 92.4986 19.13 220 92.4986 19.14 220 92.4986 19.15 220 92.4986 19.16 220 92.4986 19.17 220 92.4986 19.18 220 92.4986 19.19 220 92.4986 19.2 220 92.4986 19.21 220 92.4986 19.22 220 92.4986 19.23 220 92.4986 19.24 220 92.4986 19.25 220 92.4986 19.26 220 92.4986 19.27 220 92.4986 19.28 220 92.4986 19.29 220 92.4986 19.3 220 92.4986 19.31 220 92.4986 19.32 220 92.4986 19.33 220 92.4986 19.34 220 93.5734 19.35 220 93.5734 19.36 220 93.5734 19.37 220 93.5734 19.38 220 93.5734 19.39 220 93.5734 19.4 220 93.5734 19.41 220 93.5734 19.42 220 93.5734 19.43 220 93.5734 19.44 297.077 220 93.5734 19.45 297.077 220 93.5734 19.46 297.077 220 19.47 297.077 220 19.48 297.077 220 19.49 297.077 220 19.5 297.077 220 93.5734 19.51 297.077 220 93.5734 19.52 297.077 220 93.5734 19.53 297.077 220 93.5734 19.54 297.077 220 93.5734 19.55 297.077 220 93.5734 19.56 297.077 220 93.5734 19.57 297.077 220 93.5734 19.58 297.077 220 93.5734 19.59 297.077 220 93.5734 19.6 297.077 220 93.5734 19.61 297.077 220 93.5734 19.62 297.077 220 92.4986 19.63 297.077 220 92.4986 19.64 297.077 220 92.4986 19.65 297.077 220 92.4986 19.66 297.077 220 92.4986 19.67 297.077 220 92.4986 19.68 297.077 220 92.4986 19.69 297.077 220 92.4986 19.7 297.077 220 92.4986 19.71 297.077 220 92.4986 19.72 297.077 220 92.4986 19.73 297.077 220 92.4986 19.74 297.077 220 92.4986 19.75 297.077 220 92.4986 19.76 297.077 220 92.4986 19.77 297.077 220 92.4986 19.78 297.077 92.4986 19.79 297.077 92.4986 19.8 297.077 92.4986 19.81 297.077 92.4986 19.82 297.077 92.4986 19.83 297.077 92.4986 19.84 297.077 92.4986 19.85 297.077 92.4986 19.86 297.077 92.4986 19.87 297.077 92.4986 19.88 297.077 92.4986 19.89 297.077 92.4986 19.9 297.077 92.4986 19.91 297.077 92.4986 19.92 297.077 92.4986 19.93 297.077 92.4986 19.94 297.077 92.4986 19.95 297.077 92.4986 19.96 297.077 369.994 92.4986 19.97 297.077 369.994 92.4986 19.98 297.077 369.994 92.4986 19.99 297.077 369.994 92.4986 20.0 297.077 369.994 92.4986 20.01 297.077 369.994 92.4986 20.02 297.077 369.994 92.4986 20.03 297.077 369.994 92.4986 20.04 297.077 369.994 92.4986 20.05 297.077 369.994 92.4986 20.06 374.294 297.077 92.4986 20.07 374.294 297.077 92.4986 20.08 297.077 92.4986 20.09 297.077 92.4986 20.1 297.077 92.4986 20.11 297.077 92.4986 20.12 297.077 92.4986 20.13 297.077 92.4986 20.14 297.077 92.4986 20.15 297.077 92.4986 20.16 297.077 92.4986 20.17 297.077 92.4986 20.18 297.077 92.4986 20.19 297.077 92.4986 20.2 297.077 92.4986 20.21 297.077 92.4986 20.22 297.077 92.4986 20.23 297.077 92.4986 20.24 297.077 92.4986 20.25 297.077 92.4986 20.26 297.077 92.4986 20.27 297.077 92.4986 20.28 297.077 92.4986 20.29 297.077 92.4986 20.3 297.077 92.4986 20.31 297.077 92.4986 20.32 297.077 92.4986 20.33 297.077 92.4986 20.34 297.077 92.4986 20.35 297.077 92.4986 20.36 297.077 92.4986 20.37 297.077 92.4986 20.38 297.077 92.4986 20.39 297.077 92.4986 20.4 297.077 92.4986 20.41 297.077 92.4986 20.42 297.077 92.4986 20.43 297.077 92.4986 20.44 20.45 20.46 20.47 20.48 105.033 20.49 105.033 20.5 105.033 210.065 20.51 105.033 210.065 20.52 105.033 210.065 20.53 105.033 210.065 20.54 105.033 210.065 20.55 105.033 210.065 20.56 105.033 210.065 20.57 105.033 210.065 20.58 105.033 210.065 20.59 105.033 210.065 20.6 105.033 210.065 20.61 105.033 210.065 20.62 105.033 210.065 20.63 105.033 210.065 20.64 105.033 210.065 20.65 105.033 210.065 20.66 105.033 210.065 20.67 105.033 210.065 20.68 105.033 210.065 20.69 105.033 210.065 20.7 105.033 210.065 20.71 105.033 210.065 20.72 105.033 207.652 20.73 105.033 207.652 20.74 105.033 207.652 20.75 105.033 207.652 20.76 105.033 207.652 20.77 105.033 207.652 20.78 105.033 207.652 20.79 105.033 207.652 20.8 105.033 207.652 20.81 105.033 207.652 20.82 105.033 207.652 20.83 105.033 207.652 20.84 105.033 207.652 20.85 105.033 207.652 20.86 105.033 207.652 20.87 105.033 207.652 20.88 105.033 207.652 20.89 105.033 207.652 20.9 105.033 207.652 20.91 105.033 207.652 20.92 105.033 207.652 20.93 105.033 207.652 20.94 105.033 207.652 20.95 105.033 207.652 20.96 105.033 207.652 20.97 105.033 207.652 20.98 105.033 207.652 20.99 105.033 207.652 21.0 105.033 207.652 21.01 105.033 207.652 21.02 105.033 207.652 21.03 105.033 207.652 21.04 105.033 207.652 21.05 105.033 207.652 21.06 105.033 207.652 21.07 105.033 207.652 21.08 105.033 207.652 21.09 105.033 207.652 21.1 105.033 207.652 21.11 105.033 207.652 21.12 105.033 207.652 21.13 105.033 207.652 21.14 105.033 207.652 21.15 105.033 207.652 21.16 105.033 210.065 21.17 105.033 210.065 21.18 105.033 210.065 21.19 105.033 210.065 21.2 105.033 210.065 21.21 105.033 210.065 21.22 105.033 210.065 21.23 105.033 210.065 21.24 105.033 207.652 21.25 105.033 207.652 21.26 105.033 207.652 21.27 105.033 207.652 21.28 105.033 207.652 21.29 105.033 207.652 21.3 105.033 207.652 21.31 105.033 207.652 21.32 105.033 207.652 21.33 105.033 207.652 21.34 105.033 207.652 21.35 105.033 207.652 21.36 105.033 207.652 21.37 105.033 207.652 21.38 105.033 207.652 21.39 105.033 207.652 21.4 105.033 21.41 105.033 21.42 105.033 21.43 105.033 21.44 105.033 21.45 105.033 21.46 105.033 21.47 105.033 21.48 105.033 207.652 21.49 105.033 207.652 21.5 105.033 207.652 21.51 105.033 207.652 21.52 105.033 207.652 21.53 105.033 207.652 21.54 105.033 207.652 21.55 105.033 207.652 21.56 105.033 207.652 21.57 105.033 207.652 21.58 105.033 369.994 207.652 21.59 105.033 369.994 207.652 21.6 105.033 369.994 207.652 21.61 105.033 369.994 207.652 21.62 369.994 207.652 21.63 369.994 207.652 21.64 369.994 207.652 21.65 369.994 207.652 21.66 374.294 207.652 21.67 374.294 207.652 21.68 374.294 207.652 21.69 374.294 207.652 21.7 207.652 21.71 207.652 21.72 207.652 21.73 207.652 21.74 207.652 21.75 207.652 21.76 207.652 21.77 207.652 21.78 207.652 21.79 207.652 21.8 207.652 21.81 207.652 21.82 207.652 21.83 207.652 21.84 207.652 21.85 207.652 21.86 207.652 21.87 207.652 21.88 21.89 21.9 21.91 21.92 21.93 21.94 21.95 21.96 21.97 21.98 207.652 21.99 207.652 22.0 207.652 22.01 207.652 22.02 207.652 22.03 207.652 22.04 210.065 22.05 210.065 22.06 210.065 22.07 210.065 22.08 210.065 22.09 210.065 22.1 207.652 22.11 207.652 22.12 207.652 22.13 207.652 22.14 207.652 22.15 207.652 22.16 207.652 22.17 207.652 22.18 207.652 22.19 207.652 22.2 207.652 22.21 207.652 22.22 207.652 22.23 207.652 22.24 207.652 22.25 207.652 22.26 207.652 22.27 207.652 22.28 210.065 22.29 210.065 22.3 210.065 22.31 210.065 22.32 210.065 22.33 210.065 22.34 207.652 22.35 207.652 22.36 207.652 22.37 207.652 22.38 207.652 22.39 207.652 22.4 207.652 22.41 207.652 22.42 207.652 22.43 207.652 22.44 207.652 22.45 207.652 22.46 207.652 22.47 207.652 22.48 207.652 22.49 207.652 22.5 22.51 22.52 22.53 22.54 22.55 22.56 283.661 22.57 283.661 22.58 283.661 22.59 283.661 22.6 283.661 22.61 283.661 22.62 280.403 22.63 280.403 22.64 280.403 22.65 280.403 22.66 280.403 22.67 280.403 22.68 280.403 22.69 280.403 22.7 280.403 22.71 280.403 22.72 280.403 22.73 280.403 22.74 280.403 22.75 280.403 22.76 280.403 22.77 280.403 22.78 280.403 22.79 280.403 22.8 280.403 22.81 280.403 22.82 277.183 22.83 277.183 22.84 277.183 22.85 277.183 22.86 277.183 22.87 277.183 22.88 277.183 22.89 277.183 22.9 277.183 22.91 277.183 22.92 277.183 22.93 277.183 22.94 280.403 22.95 280.403 22.96 280.403 22.97 280.403 22.98 22.99 23.0 23.01 23.02 23.03 23.04 23.05 23.06 23.07 23.08 23.09 23.1 23.11 23.12 23.13 23.14 333.458 23.15 333.458 23.16 333.458 23.17 333.458 23.18 333.458 23.19 333.458 23.2 333.458 23.21 333.458 23.22 333.458 23.23 333.458 23.24 337.332 23.25 337.332 23.26 23.27 23.28 23.29 23.3 23.31 23.32 23.33 23.34 23.35 23.36 23.37 23.38 23.39 23.4 23.41 23.42 23.43 23.44 23.45 23.46 23.47 23.48 23.49 23.5 105.033 23.51 105.033 23.52 105.033 23.53 105.033 23.54 105.033 23.55 105.033 23.56 105.033 23.57 105.033 23.58 105.033 23.59 105.033 23.6 105.033 210.065 23.61 105.033 210.065 23.62 105.033 210.065 23.63 105.033 210.065 23.64 105.033 210.065 23.65 105.033 210.065 23.66 105.033 210.065 23.67 105.033 210.065 23.68 105.033 210.065 23.69 105.033 210.065 23.7 105.033 210.065 23.71 105.033 210.065 23.72 105.033 210.065 23.73 105.033 210.065 23.74 105.033 210.065 23.75 105.033 210.065 23.76 105.033 210.065 23.77 105.033 210.065 23.78 105.033 210.065 23.79 105.033 210.065 23.8 105.033 210.065 23.81 105.033 210.065 23.82 105.033 210.065 23.83 105.033 210.065 23.84 105.033 207.652 23.85 105.033 207.652 23.86 105.033 207.652 23.87 105.033 207.652 23.88 207.652 23.89 207.652 23.9 207.652 23.91 207.652 23.92 105.033 207.652 23.93 105.033 207.652 23.94 105.033 207.652 23.95 105.033 207.652 23.96 105.033 207.652 23.97 105.033 207.652 23.98 105.033 207.652 23.99 105.033 207.652 24.0 105.033 207.652 24.01 105.033 207.652 24.02 105.033 207.652 24.03 105.033 207.652 24.04 105.033 207.652 24.05 105.033 207.652 24.06 105.033 207.652 24.07 105.033 207.652 24.08 105.033 207.652 24.09 105.033 207.652 24.1 105.033 210.065 24.11 105.033 210.065 24.12 105.033 24.13 105.033 24.14 105.033 24.15 105.033 24.16 105.033 24.17 105.033 24.18 280.403 105.033 24.19 280.403 105.033 24.2 280.403 105.033 24.21 280.403 105.033 24.22 280.403 105.033 24.23 280.403 105.033 24.24 280.403 105.033 24.25 280.403 105.033 24.26 280.403 105.033 24.27 280.403 105.033 24.28 280.403 105.033 24.29 280.403 105.033 24.3 105.033 24.31 105.033 24.32 105.033 24.33 105.033 24.34 105.033 24.35 105.033 24.36 105.033 24.37 105.033 24.38 105.033 24.39 105.033 24.4 105.033 24.41 105.033 24.42 105.033 24.43 105.033 24.44 105.033 24.45 105.033 24.46 105.033 24.47 105.033 24.48 105.033 24.49 105.033 24.5 105.033 24.51 105.033 24.52 105.033 24.53 105.033 24.54 105.033 24.55 105.033 24.56 105.033 24.57 105.033 24.58 105.033 24.59 105.033 24.6 105.033 24.61 105.033 24.62 314.742 105.033 24.63 314.742 105.033 24.64 314.742 105.033 24.65 314.742 105.033 24.66 314.742 105.033 24.67 314.742 105.033 24.68 314.742 105.033 24.69 314.742 105.033 24.7 314.742 105.033 24.71 314.742 105.033 24.72 318.399 105.033 24.73 318.399 105.033 24.74 105.033 24.75 105.033 24.76 105.033 24.77 105.033 24.78 105.033 24.79 105.033 24.8 105.033 24.81 105.033 24.82 105.033 24.83 105.033 24.84 105.033 24.85 105.033 24.86 105.033 24.87 105.033 24.88 105.033 24.89 105.033 24.9 105.033 24.91 105.033 24.92 105.033 24.93 105.033 24.94 105.033 24.95 105.033 24.96 105.033 24.97 105.033 24.98 105.033 24.99 105.033 25.0 105.033 25.01 105.033 25.02 105.033 25.03 105.033 25.04 187.147 105.033 25.05 187.147 105.033 25.06 187.147 105.033 25.07 187.147 105.033 25.08 187.147 105.033 25.09 187.147 105.033 25.1 187.147 105.033 25.11 187.147 105.033 25.12 187.147 105.033 25.13 187.147 105.033 25.14 187.147 105.033 25.15 187.147 105.033 25.16 187.147 105.033 25.17 187.147 105.033 25.18 187.147 105.033 25.19 187.147 105.033 25.2 187.147 105.033 25.21 187.147 105.033 25.22 187.147 105.033 25.23 187.147 105.033 25.24 187.147 105.033 25.25 187.147 105.033 25.26 187.147 105.033 25.27 187.147 105.033 25.28 187.147 105.033 25.29 187.147 105.033 25.3 187.147 105.033 25.31 187.147 105.033 25.32 187.147 105.033 25.33 187.147 105.033 25.34 187.147 105.033 25.35 187.147 105.033 25.36 187.147 105.033 25.37 187.147 105.033 25.38 187.147 105.033 25.39 187.147 105.033 25.4 187.147 105.033 25.41 187.147 105.033 25.42 187.147 105.033 25.43 187.147 105.033 25.44 187.147 105.033 25.45 187.147 105.033 25.46 187.147 105.033 25.47 187.147 105.033 25.48 187.147 105.033 25.49 187.147 105.033 25.5 187.147 105.033 25.51 187.147 105.033 25.52 187.147 105.033 25.53 187.147 105.033 25.54 187.147 105.033 25.55 187.147 105.033 25.56 187.147 25.57 187.147 25.58 187.147 261.626 25.59 187.147 261.626 25.6 187.147 261.626 25.61 187.147 261.626 25.62 187.147 261.626 25.63 187.147 261.626 25.64 187.147 261.626 25.65 187.147 261.626 25.66 187.147 261.626 25.67 187.147 261.626 25.68 187.147 261.626 25.69 187.147 261.626 25.7 187.147 264.666 25.71 187.147 264.666 25.72 187.147 25.73 187.147 25.74 187.147 25.75 187.147 25.76 187.147 25.77 187.147 25.78 187.147 25.79 187.147 25.8 187.147 25.81 187.147 25.82 187.147 264.666 25.83 187.147 264.666 25.84 187.147 264.666 25.85 187.147 264.666 25.86 187.147 264.666 25.87 187.147 264.666 25.88 187.147 261.626 25.89 187.147 261.626 25.9 187.147 261.626 25.91 187.147 261.626 25.92 187.147 261.626 25.93 187.147 261.626 25.94 187.147 105.033 264.666 25.95 187.147 105.033 264.666 25.96 187.147 105.033 264.666 25.97 187.147 105.033 264.666 25.98 187.147 105.033 264.666 25.99 187.147 105.033 264.666 26.0 187.147 105.033 264.666 26.01 187.147 105.033 264.666 26.02 187.147 105.033 264.666 26.03 187.147 105.033 264.666 26.04 187.147 105.033 264.666 26.05 187.147 105.033 264.666 26.06 187.147 105.033 264.666 26.07 187.147 105.033 264.666 26.08 187.147 105.033 264.666 26.09 187.147 105.033 264.666 26.1 187.147 105.033 264.666 26.11 187.147 105.033 264.666 26.12 187.147 105.033 26.13 187.147 105.033 26.14 314.742 187.147 105.033 26.15 314.742 187.147 105.033 26.16 314.742 187.147 26.17 314.742 187.147 26.18 314.742 187.147 26.19 314.742 187.147 26.2 314.742 187.147 105.033 26.21 314.742 187.147 105.033 26.22 314.742 187.147 105.033 26.23 314.742 187.147 105.033 26.24 314.742 105.033 26.25 314.742 105.033 26.26 314.742 105.033 26.27 314.742 105.033 26.28 314.742 105.033 26.29 314.742 105.033 26.3 314.742 105.033 26.31 314.742 105.033 26.32 314.742 105.033 26.33 314.742 105.033 26.34 314.742 105.033 26.35 314.742 105.033 26.36 314.742 105.033 26.37 314.742 105.033 26.38 314.742 105.033 26.39 314.742 105.033 26.4 314.742 105.033 26.41 314.742 105.033 26.42 314.742 105.033 26.43 314.742 105.033 26.44 314.742 105.033 26.45 314.742 105.033 26.46 314.742 105.033 26.47 314.742 105.033 26.48 314.742 105.033 26.49 314.742 105.033 26.5 314.742 105.033 26.51 314.742 105.033 26.52 314.742 105.033 26.53 314.742 105.033 26.54 314.742 105.033 26.55 314.742 105.033 26.56 314.742 105.033 26.57 314.742 105.033 26.58 314.742 105.033 26.59 314.742 105.033 26.6 105.033 26.61 105.033 26.62 105.033 26.63 105.033 26.64 105.033 26.65 105.033 26.66 105.033 26.67 105.033 26.68 105.033 26.69 105.033 26.7 105.033 26.71 105.033 26.72 105.033 26.73 105.033 26.74 105.033 26.75 105.033 26.76 105.033 26.77 105.033 26.78 26.79 26.8 26.81 26.82 26.83 26.84 26.85 26.86 26.87 26.88 207.652 26.89 207.652 26.9 105.033 207.652 26.91 105.033 207.652 26.92 280.403 105.033 207.652 26.93 280.403 105.033 207.652 26.94 280.403 105.033 210.065 26.95 280.403 105.033 210.065 26.96 280.403 105.033 210.065 26.97 280.403 105.033 210.065 26.98 280.403 105.033 210.065 26.99 280.403 105.033 210.065 27.0 164.814 280.403 105.033 210.065 27.01 164.814 280.403 105.033 210.065 27.02 164.814 280.403 105.033 210.065 27.03 164.814 280.403 105.033 210.065 27.04 164.814 280.403 105.033 210.065 27.05 164.814 280.403 105.033 210.065 27.06 164.814 280.403 105.033 70.1008 210.065 27.07 164.814 280.403 105.033 70.1008 210.065 27.08 164.814 280.403 105.033 70.1008 210.065 27.09 164.814 280.403 105.033 70.1008 210.065 27.1 164.814 105.033 70.1008 210.065 277.183 27.11 164.814 105.033 70.1008 210.065 277.183 27.12 164.814 105.033 70.1008 210.065 277.183 27.13 164.814 105.033 70.1008 210.065 277.183 27.14 105.033 70.1008 166.729 210.065 277.183 27.15 105.033 70.1008 166.729 210.065 277.183 27.16 280.403 105.033 70.1008 166.729 210.065 27.17 280.403 105.033 70.1008 166.729 210.065 27.18 280.403 105.033 70.1008 166.729 210.065 27.19 280.403 105.033 70.1008 166.729 210.065 27.2 280.403 105.033 70.1008 166.729 210.065 27.21 280.403 105.033 70.1008 166.729 210.065 27.22 280.403 105.033 70.1008 166.729 207.652 27.23 280.403 105.033 70.1008 166.729 207.652 27.24 280.403 105.033 70.1008 166.729 207.652 27.25 280.403 105.033 70.1008 166.729 207.652 27.26 280.403 105.033 70.1008 166.729 207.652 27.27 280.403 105.033 70.1008 166.729 207.652 27.28 105.033 70.1008 166.729 207.652 27.29 105.033 70.1008 166.729 207.652 27.3 105.033 70.1008 166.729 207.652 27.31 105.033 70.1008 166.729 207.652 27.32 105.033 70.1008 166.729 210.065 27.33 105.033 70.1008 166.729 210.065 27.34 105.033 70.1008 166.729 210.065 27.35 105.033 70.1008 166.729 210.065 27.36 105.033 70.1008 166.729 210.065 27.37 105.033 70.1008 166.729 210.065 27.38 105.033 70.1008 166.729 210.065 27.39 105.033 70.1008 166.729 210.065 27.4 105.033 70.1008 166.729 207.652 27.41 105.033 70.1008 166.729 207.652 27.42 70.1008 207.652 27.43 70.1008 207.652 27.44 70.1008 207.652 27.45 70.1008 207.652 27.46 210.065 70.1008 27.47 210.065 70.1008 27.48 210.065 70.1008 27.49 210.065 70.1008 27.5 210.065 70.1008 27.51 210.065 70.1008 27.52 210.065 70.1008 27.53 210.065 70.1008 27.54 210.065 70.1008 27.55 210.065 70.1008 27.56 210.065 70.1008 27.57 210.065 70.1008 27.58 207.652 27.59 207.652 27.6 207.652 27.61 207.652 27.62 207.652 27.63 207.652 27.64 207.652 27.65 207.652 27.66 207.652 27.67 207.652 27.68 210.065 27.69 210.065 27.7 210.065 27.71 210.065 27.72 210.065 27.73 210.065 27.74 210.065 27.75 210.065 27.76 210.065 27.77 210.065 27.78 210.065 27.79 210.065 27.8 210.065 27.81 210.065 27.82 210.065 27.83 210.065 27.84 210.065 27.85 210.065 27.86 207.652 27.87 207.652 27.88 207.652 27.89 207.652 27.9 207.652 27.91 207.652 27.92 207.652 27.93 207.652 27.94 207.652 27.95 207.652 27.96 207.652 27.97 207.652 27.98 207.652 27.99 207.652 28.0 207.652 28.01 207.652 28.02 210.065 277.183 28.03 210.065 277.183 28.04 210.065 277.183 28.05 210.065 277.183 28.06 277.183 28.07 277.183 28.08 280.403 28.09 280.403 28.1 280.403 28.11 280.403 28.12 280.403 28.13 280.403 28.14 280.403 28.15 280.403 28.16 280.403 28.17 280.403 28.18 280.403 28.19 280.403 28.2 280.403 28.21 280.403 28.22 280.403 28.23 280.403 28.24 280.403 28.25 280.403 28.26 280.403 28.27 280.403 28.28 280.403 28.29 280.403 28.3 280.403 28.31 280.403 28.32 280.403 28.33 280.403 28.34 280.403 28.35 280.403 28.36 280.403 28.37 280.403 28.38 277.183 28.39 277.183 28.4 277.183 28.41 277.183 28.42 277.183 28.43 277.183 28.44 280.403 28.45 280.403 28.46 280.403 210.065 28.47 280.403 210.065 28.48 280.403 210.065 28.49 280.403 210.065 28.5 280.403 210.065 28.51 280.403 210.065 28.52 280.403 207.652 28.53 280.403 207.652 28.54 280.403 207.652 28.55 280.403 207.652 28.56 280.403 207.652 28.57 280.403 207.652 28.58 280.403 207.652 28.59 280.403 207.652 28.6 280.403 207.652 28.61 280.403 207.652 28.62 280.403 207.652 28.63 280.403 207.652 28.64 280.403 207.652 28.65 280.403 207.652 28.66 280.403 207.652 28.67 280.403 207.652 28.68 280.403 207.652 28.69 280.403 207.652 28.7 280.403 207.652 28.71 280.403 207.652 28.72 280.403 207.652 28.73 280.403 207.652 28.74 280.403 207.652 28.75 280.403 207.652 28.76 280.403 207.652 28.77 280.403 207.652 28.78 280.403 207.652 28.79 280.403 207.652 28.8 280.403 207.652 28.81 280.403 207.652 28.82 280.403 207.652 28.83 280.403 207.652 28.84 280.403 207.652 28.85 280.403 207.652 28.86 280.403 207.652 28.87 280.403 207.652 28.88 280.403 207.652 28.89 280.403 207.652 28.9 280.403 207.652 28.91 280.403 207.652 28.92 280.403 28.93 280.403 28.94 280.403 28.95 280.403 28.96 280.403 28.97 280.403 28.98 277.183 28.99 277.183 29.0 277.183 29.01 277.183 29.02 277.183 29.03 277.183 29.04 277.183 29.05 277.183 29.06 280.403 29.07 280.403 29.08 280.403 29.09 280.403 29.1 280.403 29.11 280.403 29.12 280.403 29.13 280.403 29.14 280.403 29.15 280.403 29.16 280.403 29.17 280.403 29.18 280.403 29.19 280.403 29.2 280.403 29.21 280.403 29.22 280.403 29.23 280.403 29.24 280.403 29.25 280.403 29.26 280.403 29.27 280.403 29.28 280.403 29.29 280.403 29.3 280.403 29.31 280.403 29.32 277.183 29.33 277.183 29.34 277.183 29.35 277.183 29.36 277.183 29.37 277.183 29.38 277.183 29.39 277.183 29.4 277.183 29.41 277.183 29.42 280.403 29.43 280.403 29.44 280.403 29.45 280.403 29.46 280.403 29.47 280.403 29.48 280.403 29.49 280.403 29.5 280.403 29.51 280.403 29.52 280.403 29.53 280.403 29.54 280.403 29.55 280.403 29.56 280.403 29.57 280.403 29.58 280.403 29.59 280.403 29.6 280.403 29.61 280.403 29.62 280.403 29.63 280.403 29.64 280.403 29.65 280.403 29.66 280.403 29.67 280.403 29.68 280.403 29.69 280.403 29.7 280.403 29.71 280.403 29.72 280.403 29.73 280.403 29.74 280.403 29.75 280.403 29.76 280.403 29.77 280.403 29.78 280.403 29.79 280.403 29.8 280.403 29.81 280.403 29.82 280.403 29.83 280.403 29.84 280.403 29.85 280.403 29.86 280.403 29.87 280.403 29.88 280.403 29.89 280.403 29.9 280.403 29.91 280.403 29.92 280.403 29.93 280.403 29.94 280.403 29.95 280.403 29.96 280.403 29.97 280.403 29.98 280.403 29.99 280.403 30.0 280.403 210.065 30.01 280.403 210.065 30.02 280.403 210.065 30.03 280.403 210.065 30.04 280.403 210.065 30.05 280.403 210.065 30.06 280.403 207.652 30.07 280.403 207.652 30.08 280.403 207.652 30.09 280.403 207.652 30.1 280.403 207.652 30.11 280.403 207.652 30.12 280.403 207.652 30.13 280.403 207.652 30.14 280.403 207.652 30.15 280.403 207.652 30.16 280.403 207.652 30.17 280.403 207.652 30.18 280.403 207.652 30.19 280.403 207.652 30.2 280.403 207.652 30.21 280.403 207.652 30.22 280.403 207.652 30.23 280.403 207.652 30.24 280.403 207.652 30.25 280.403 207.652 30.26 280.403 207.652 30.27 280.403 207.652 30.28 280.403 207.652 30.29 280.403 207.652 30.3 280.403 207.652 30.31 280.403 207.652 30.32 280.403 207.652 30.33 280.403 207.652 30.34 280.403 207.652 30.35 280.403 207.652 30.36 280.403 207.652 30.37 280.403 207.652 30.38 207.652 30.39 207.652 30.4 207.652 30.41 207.652 30.42 207.652 30.43 207.652 30.44 207.652 30.45 207.652 30.46 207.652 30.47 207.652 30.48 280.403 30.49 280.403 30.5 280.403 30.51 280.403 30.52 280.403 30.53 280.403 30.54 280.403 30.55 280.403 30.56 280.403 30.57 280.403 30.58 280.403 30.59 280.403 30.6 280.403 30.61 280.403 30.62 280.403 30.63 280.403 30.64 280.403 30.65 280.403 30.66 280.403 30.67 280.403 30.68 280.403 30.69 280.403 30.7 277.183 30.71 277.183 30.72 277.183 30.73 277.183 30.74 277.183 30.75 277.183 30.76 277.183 30.77 277.183 30.78 280.403 30.79 280.403 30.8 280.403 30.81 280.403 30.82 280.403 30.83 280.403 30.84 280.403 30.85 280.403 30.86 280.403 30.87 280.403 30.88 280.403 30.89 280.403 30.9 280.403 30.91 280.403 30.92 280.403 30.93 280.403 30.94 280.403 30.95 280.403 30.96 280.403 30.97 280.403 30.98 30.99 31.0 31.01 31.02 31.03 31.04 31.05 31.06 31.07 31.08 31.09 31.1 31.11 31.12 31.13 31.14 31.15 31.16 31.17 31.18 31.19 31.2 31.21 31.22 31.23 31.24 31.25 31.26 31.27 31.28 31.29 31.3 31.31 31.32 31.33 31.34 31.35 31.36 31.37 31.38 31.39 31.4 31.41 31.42 31.43 31.44 420.13 31.45 420.13 31.46 207.652 420.13 31.47 207.652 420.13 31.48 207.652 420.13 31.49 207.652 420.13 31.5 207.652 420.13 31.51 207.652 420.13 31.52 207.652 420.13 31.53 207.652 420.13 31.54 207.652 420.13 31.55 207.652 420.13 31.56 207.652 420.13 31.57 207.652 420.13 31.58 207.652 420.13 31.59 207.652 420.13 31.6 207.652 420.13 31.61 207.652 420.13 31.62 207.652 420.13 31.63 207.652 420.13 31.64 207.652 420.13 31.65 207.652 420.13 31.66 207.652 420.13 31.67 207.652 420.13 31.68 207.652 420.13 31.69 207.652 420.13 31.7 210.065 420.13 31.71 210.065 420.13 31.72 210.065 420.13 31.73 210.065 420.13 31.74 210.065 420.13 31.75 210.065 420.13 31.76 210.065 420.13 31.77 210.065 420.13 31.78 210.065 420.13 31.79 210.065 420.13 31.8 210.065 420.13 31.81 210.065 420.13 31.82 210.065 420.13 31.83 210.065 420.13 31.84 207.652 420.13 31.85 207.652 420.13 31.86 207.652 420.13 31.87 207.652 420.13 31.88 207.652 420.13 31.89 207.652 420.13 31.9 420.13 31.91 420.13 31.92 420.13 31.93 420.13 31.94 420.13 31.95 420.13 31.96 420.13 31.97 420.13 31.98 420.13 31.99 420.13 32.0 420.13 32.01 420.13 32.02 420.13 32.03 420.13 32.04 420.13 32.05 420.13 32.06 420.13 32.07 420.13 32.08 420.13 32.09 420.13 32.1 420.13 32.11 420.13 32.12 280.403 420.13 32.13 280.403 420.13 32.14 280.403 420.13 32.15 280.403 420.13 32.16 280.403 420.13 32.17 280.403 420.13 32.18 280.403 420.13 32.19 280.403 420.13 32.2 280.403 420.13 32.21 280.403 420.13 32.22 280.403 420.13 32.23 280.403 420.13 32.24 280.403 420.13 32.25 280.403 420.13 32.26 280.403 420.13 32.27 280.403 420.13 32.28 420.13 32.29 420.13 32.3 420.13 32.31 420.13 32.32 420.13 32.33 420.13 32.34 420.13 32.35 420.13 32.36 420.13 32.37 420.13 32.38 420.13 32.39 420.13 32.4 420.13 32.41 420.13 32.42 420.13 32.43 420.13 32.44 420.13 32.45 420.13 32.46 420.13 32.47 420.13 32.48 420.13 32.49 420.13 32.5 420.13 32.51 420.13 32.52 420.13 32.53 420.13 32.54 420.13 32.55 420.13 32.56 420.13 32.57 420.13 32.58 420.13 32.59 420.13 32.6 420.13 32.61 420.13 32.62 420.13 32.63 420.13 32.64 420.13 32.65 420.13 32.66 420.13 32.67 420.13 32.68 420.13 32.69 420.13 32.7 420.13 32.71 420.13 32.72 420.13 32.73 420.13 32.74 420.13 32.75 420.13 32.76 32.77 32.78 420.13 32.79 420.13 32.8 420.13 32.81 420.13 32.82 420.13 32.83 420.13 32.84 420.13 32.85 420.13 32.86 420.13 32.87 420.13 32.88 420.13 32.89 420.13 32.9 420.13 32.91 420.13 32.92 420.13 32.93 420.13 32.94 420.13 32.95 420.13 32.96 420.13 32.97 420.13 32.98 420.13 32.99 420.13 33.0 420.13 33.01 420.13 33.02 420.13 33.03 420.13 33.04 420.13 33.05 420.13 33.06 420.13 33.07 420.13 33.08 420.13 33.09 420.13 33.1 420.13 33.11 420.13 33.12 420.13 33.13 420.13 33.14 420.13 33.15 420.13 33.16 420.13 33.17 420.13 33.18 425.012 33.19 425.012 33.2 425.012 33.21 425.012 33.22 425.012 33.23 425.012 33.24 420.13 33.25 420.13 33.26 210.065 264.666 420.13 33.27 210.065 264.666 420.13 33.28 210.065 264.666 420.13 33.29 210.065 264.666 420.13 33.3 210.065 264.666 420.13 33.31 210.065 264.666 420.13 33.32 210.065 264.666 420.13 33.33 210.065 264.666 420.13 33.34 210.065 264.666 420.13 33.35 210.065 264.666 420.13 33.36 210.065 264.666 420.13 33.37 210.065 264.666 420.13 33.38 210.065 264.666 420.13 33.39 210.065 264.666 420.13 33.4 210.065 264.666 420.13 33.41 210.065 264.666 420.13 33.42 210.065 264.666 420.13 33.43 210.065 264.666 420.13 33.44 210.065 264.666 105.033 420.13 33.45 210.065 264.666 105.033 420.13 33.46 210.065 264.666 105.033 420.13 33.47 210.065 264.666 105.033 420.13 33.48 264.666 105.033 66.9352 420.13 33.49 264.666 105.033 66.9352 420.13 33.5 264.666 105.033 66.9352 420.13 33.51 264.666 105.033 66.9352 420.13 33.52 264.666 105.033 66.9352 420.13 33.53 264.666 105.033 66.9352 420.13 33.54 264.666 105.033 66.9352 420.13 33.55 264.666 105.033 66.9352 420.13 33.56 264.666 105.033 66.9352 420.13 33.57 264.666 105.033 66.9352 420.13 33.58 264.666 105.033 66.9352 420.13 33.59 264.666 105.033 66.9352 420.13 33.6 264.666 105.033 66.9352 420.13 33.61 264.666 105.033 66.9352 420.13 33.62 210.065 264.666 66.9352 420.13 33.63 210.065 264.666 66.9352 420.13 33.64 210.065 264.666 66.9352 420.13 33.65 210.065 264.666 66.9352 420.13 33.66 210.065 264.666 66.9352 420.13 33.67 210.065 264.666 66.9352 420.13 33.68 210.065 264.666 66.9352 420.13 33.69 210.065 264.666 66.9352 420.13 33.7 210.065 264.666 66.9352 420.13 33.71 210.065 264.666 66.9352 420.13 33.72 210.065 264.666 66.9352 420.13 33.73 210.065 264.666 66.9352 420.13 33.74 210.065 264.666 66.9352 420.13 33.75 210.065 264.666 66.9352 420.13 33.76 210.065 264.666 66.9352 420.13 33.77 210.065 264.666 66.9352 420.13 33.78 210.065 264.666 66.9352 420.13 33.79 210.065 264.666 66.9352 420.13 33.8 210.065 264.666 66.9352 420.13 33.81 210.065 264.666 66.9352 420.13 33.82 210.065 264.666 66.9352 420.13 33.83 210.065 264.666 66.9352 420.13 33.84 210.065 264.666 420.13 33.85 210.065 264.666 420.13 33.86 210.065 264.666 420.13 33.87 210.065 264.666 420.13 33.88 210.065 264.666 420.13 33.89 210.065 264.666 420.13 33.9 210.065 264.666 420.13 33.91 210.065 264.666 420.13 33.92 314.742 210.065 264.666 420.13 33.93 314.742 210.065 264.666 420.13 33.94 314.742 210.065 264.666 420.13 33.95 314.742 210.065 264.666 420.13 33.96 314.742 210.065 264.666 420.13 33.97 314.742 210.065 264.666 420.13 33.98 314.742 210.065 264.666 420.13 33.99 314.742 210.065 264.666 420.13 34.0 314.742 210.065 264.666 420.13 34.01 314.742 210.065 264.666 420.13 34.02 314.742 210.065 264.666 420.13 34.03 314.742 210.065 264.666 420.13 34.04 314.742 210.065 264.666 420.13 34.05 314.742 210.065 264.666 420.13 34.06 314.742 210.065 264.666 420.13 34.07 314.742 210.065 264.666 420.13 34.08 314.742 210.065 264.666 420.13 34.09 314.742 210.065 264.666 420.13 34.1 314.742 264.666 420.13 34.11 314.742 264.666 420.13 34.12 314.742 264.666 420.13 34.13 314.742 264.666 420.13 34.14 314.742 264.666 420.13 34.15 314.742 264.666 420.13 34.16 314.742 264.666 420.13 34.17 314.742 264.666 420.13 34.18 264.666 420.13 34.19 264.666 420.13 34.2 264.666 420.13 34.21 264.666 420.13 34.22 264.666 420.13 34.23 264.666 420.13 34.24 264.666 420.13 34.25 264.666 420.13 34.26 264.666 420.13 34.27 264.666 420.13 34.28 264.666 420.13 34.29 264.666 420.13 34.3 264.666 34.31 264.666 34.32 34.33 34.34 34.35 34.36 34.37 34.38 34.39 34.4 34.41 34.42 34.43 34.44 34.45 34.46 34.47 34.48 34.49 34.5 34.51 34.52 34.53 34.54 34.55 34.56 34.57 34.58 34.59 34.6 34.61 34.62 34.63 34.64 34.65 34.66 34.67 34.68 34.69 34.7 34.71 34.72 34.73 34.74 34.75 34.76 34.77 34.78 34.79 34.8 34.81 34.82 34.83 34.84 34.85 34.86 207.652 34.87 207.652 34.88 207.652 34.89 207.652 34.9 207.652 34.91 207.652 34.92 207.652 34.93 207.652 34.94 207.652 34.95 207.652 34.96 207.652 34.97 207.652 34.98 207.652 34.99 207.652 35.0 207.652 35.01 207.652 35.02 207.652 35.03 207.652 35.04 207.652 35.05 207.652 35.06 210.065 35.07 210.065 35.08 210.065 35.09 210.065 35.1 210.065 35.11 210.065 35.12 207.652 35.13 207.652 35.14 207.652 35.15 207.652 35.16 207.652 35.17 207.652 35.18 35.19 35.2 35.21 35.22 35.23 35.24 35.25 35.26 35.27 35.28 35.29 35.3 35.31 35.32 35.33 35.34 311.127 35.35 311.127 35.36 311.127 35.37 311.127 35.38 311.127 35.39 311.127 35.4 314.742 35.41 314.742 35.42 314.742 35.43 314.742 35.44 314.742 35.45 314.742 35.46 314.742 35.47 314.742 35.48 314.742 35.49 314.742 35.5 314.742 35.51 314.742 35.52 314.742 35.53 314.742 35.54 314.742 35.55 314.742 35.56 314.742 35.57 314.742 35.58 314.742 35.59 314.742 35.6 314.742 35.61 314.742 35.62 314.742 35.63 314.742 35.64 314.742 35.65 314.742 35.66 314.742 35.67 314.742 35.68 314.742 35.69 314.742 35.7 314.742 35.71 314.742 35.72 314.742 35.73 314.742 35.74 35.75 35.76 35.77 35.78 35.79 35.8 35.81 35.82 35.83 35.84 35.85 35.86 35.87 35.88 35.89 35.9 35.91 35.92 35.93 35.94 35.95 35.96 35.97 35.98 35.99 36.0 36.01 36.02 36.03 36.04 36.05 36.06 36.07 36.08 36.09 36.1 36.11 36.12 36.13 36.14 36.15 36.16 36.17 36.18 36.19 36.2 36.21 36.22 36.23 36.24 36.25 36.26 210.065 36.27 210.065 36.28 210.065 36.29 210.065 36.3 210.065 36.31 210.065 36.32 207.652 36.33 207.652 36.34 207.652 36.35 207.652 36.36 207.652 36.37 207.652 36.38 207.652 36.39 207.652 36.4 207.652 36.41 207.652 36.42 207.652 36.43 207.652 36.44 207.652 36.45 207.652 36.46 207.652 36.47 207.652 36.48 207.652 36.49 207.652 36.5 210.065 36.51 210.065 36.52 210.065 36.53 210.065 36.54 210.065 36.55 210.065 36.56 210.065 36.57 210.065 36.58 210.065 36.59 210.065 36.6 207.652 36.61 207.652 36.62 207.652 36.63 207.652 36.64 36.65 36.66 36.67 36.68 36.69 36.7 36.71 36.72 36.73 36.74 36.75 36.76 314.742 36.77 314.742 36.78 314.742 36.79 314.742 36.8 314.742 36.81 314.742 36.82 314.742 36.83 314.742 36.84 314.742 36.85 314.742 36.86 314.742 36.87 314.742 36.88 314.742 36.89 314.742 36.9 314.742 36.91 314.742 36.92 314.742 36.93 314.742 36.94 314.742 36.95 314.742 36.96 314.742 36.97 314.742 36.98 314.742 36.99 314.742 37.0 314.742 37.01 314.742 37.02 314.742 37.03 314.742 37.04 314.742 37.05 314.742 37.06 314.742 37.07 314.742 37.08 314.742 37.09 314.742 37.1 314.742 37.11 314.742 37.12 314.742 37.13 314.742 37.14 314.742 37.15 314.742 37.16 314.742 37.17 314.742 37.18 314.742 37.19 314.742 37.2 314.742 37.21 314.742 37.22 37.23 37.24 37.25 37.26 37.27 37.28 37.29 37.3 37.31 37.32 37.33 37.34 37.35 37.36 37.37 37.38 37.39 37.4 37.41 37.42 37.43 37.44 37.45 37.46 37.47 37.48 37.49 37.5 37.51 37.52 37.53 37.54 37.55 37.56 37.57 37.58 37.59 37.6 37.61 37.62 37.63 37.64 37.65 37.66 37.67 37.68 37.69 37.7 37.71 37.72 415.305 37.73 415.305 37.74 415.305 37.75 415.305 37.76 415.305 37.77 415.305 37.78 420.13 37.79 420.13 37.8 207.652 420.13 37.81 207.652 420.13 37.82 207.652 420.13 37.83 207.652 420.13 37.84 207.652 420.13 37.85 207.652 420.13 37.86 207.652 420.13 37.87 207.652 420.13 37.88 207.652 420.13 37.89 207.652 420.13 37.9 207.652 420.13 37.91 207.652 420.13 37.92 207.652 420.13 37.93 207.652 420.13 37.94 207.652 420.13 37.95 207.652 420.13 37.96 207.652 420.13 37.97 207.652 420.13 37.98 420.13 37.99 420.13 38.0 420.13 38.01 420.13 38.02 420.13 38.03 420.13 38.04 420.13 38.05 420.13 38.06 420.13 38.07 420.13 38.08 420.13 38.09 420.13 38.1 420.13 38.11 420.13 38.12 420.13 38.13 420.13 38.14 420.13 38.15 420.13 38.16 420.13 38.17 420.13 38.18 420.13 38.19 420.13 38.2 420.13 38.21 420.13 38.22 420.13 38.23 420.13 38.24 420.13 38.25 420.13 38.26 420.13 38.27 420.13 38.28 311.127 420.13 38.29 311.127 420.13 38.3 311.127 420.13 38.31 311.127 420.13 38.32 311.127 420.13 38.33 311.127 420.13 38.34 314.742 420.13 38.35 314.742 420.13 38.36 314.742 420.13 38.37 314.742 420.13 38.38 314.742 420.13 38.39 314.742 420.13 38.4 314.742 420.13 38.41 314.742 420.13 38.42 314.742 420.13 38.43 314.742 420.13 38.44 314.742 420.13 38.45 314.742 420.13 38.46 314.742 420.13 38.47 314.742 420.13 38.48 314.742 420.13 38.49 314.742 420.13 38.5 314.742 420.13 38.51 314.742 420.13 38.52 314.742 420.13 38.53 314.742 420.13 38.54 314.742 420.13 38.55 314.742 420.13 38.56 314.742 420.13 38.57 314.742 420.13 38.58 314.742 420.13 38.59 314.742 420.13 38.6 314.742 420.13 38.61 314.742 420.13 38.62 314.742 420.13 38.63 314.742 420.13 38.64 314.742 420.13 38.65 314.742 420.13 38.66 314.742 420.13 38.67 314.742 420.13 38.68 314.742 420.13 38.69 314.742 420.13 38.7 314.742 420.13 38.71 314.742 420.13 38.72 314.742 420.13 38.73 314.742 420.13 38.74 314.742 420.13 38.75 314.742 420.13 38.76 420.13 38.77 420.13 38.78 369.994 420.13 38.79 369.994 420.13 38.8 369.994 420.13 38.81 369.994 420.13 38.82 369.994 420.13 38.83 369.994 420.13 38.84 374.294 420.13 38.85 374.294 420.13 38.86 374.294 420.13 38.87 374.294 420.13 38.88 374.294 420.13 38.89 374.294 420.13 38.9 374.294 420.13 38.91 374.294 420.13 38.92 420.13 38.93 420.13 38.94 420.13 38.95 420.13 38.96 38.97 38.98 420.13 38.99 420.13 39.0 420.13 39.01 420.13 39.02 420.13 39.03 420.13 39.04 420.13 39.05 420.13 39.06 420.13 39.07 420.13 39.08 420.13 39.09 420.13 39.1 420.13 39.11 420.13 39.12 420.13 39.13 420.13 39.14 420.13 39.15 420.13 39.16 420.13 39.17 420.13 39.18 420.13 39.19 420.13 39.2 420.13 39.21 420.13 39.22 420.13 39.23 420.13 39.24 420.13 39.25 420.13 39.26 420.13 39.27 420.13 39.28 420.13 39.29 420.13 39.3 420.13 39.31 420.13 39.32 420.13 39.33 420.13 39.34 420.13 39.35 420.13 39.36 420.13 39.37 420.13 39.38 420.13 39.39 420.13 39.4 420.13 39.41 420.13 39.42 420.13 39.43 420.13 39.44 420.13 39.45 420.13 39.46 39.47 39.48 420.13 39.49 420.13 39.5 70.1008 420.13 39.51 70.1008 420.13 39.52 70.1008 207.652 420.13 39.53 70.1008 207.652 420.13 39.54 70.1008 207.652 420.13 39.55 70.1008 207.652 420.13 39.56 70.1008 207.652 420.13 39.57 70.1008 207.652 420.13 39.58 70.1008 207.652 420.13 39.59 70.1008 207.652 420.13 39.6 70.1008 207.652 420.13 39.61 70.1008 207.652 420.13 39.62 70.1008 207.652 420.13 39.63 70.1008 207.652 420.13 39.64 210.065 70.1008 420.13 39.65 210.065 70.1008 420.13 39.66 210.065 70.1008 420.13 39.67 210.065 70.1008 420.13 39.68 210.065 70.1008 420.13 39.69 210.065 70.1008 420.13 39.7 210.065 70.1008 420.13 39.71 210.065 70.1008 420.13 39.72 210.065 70.1008 420.13 39.73 210.065 70.1008 420.13 39.74 210.065 70.1008 420.13 39.75 210.065 70.1008 420.13 39.76 210.065 70.1008 420.13 39.77 210.065 70.1008 420.13 39.78 210.065 70.1008 420.13 39.79 210.065 70.1008 420.13 39.8 210.065 70.1008 420.13 39.81 210.065 70.1008 420.13 39.82 70.1008 420.13 39.83 70.1008 420.13 39.84 70.1008 420.13 39.85 70.1008 420.13 39.86 70.1008 420.13 39.87 70.1008 420.13 39.88 70.1008 420.13 39.89 70.1008 420.13 39.9 70.1008 420.13 39.91 70.1008 420.13 39.92 70.1008 420.13 39.93 70.1008 420.13 39.94 70.1008 420.13 39.95 70.1008 420.13 39.96 70.1008 420.13 39.97 70.1008 420.13 39.98 70.1008 420.13 39.99 70.1008 420.13 40.0 70.1008 420.13 40.01 70.1008 420.13 40.02 70.1008 420.13 40.03 70.1008 420.13 40.04 70.1008 420.13 40.05 70.1008 420.13 40.06 70.1008 420.13 40.07 70.1008 420.13 40.08 70.1008 420.13 40.09 70.1008 420.13 40.1 70.1008 420.13 40.11 70.1008 420.13 40.12 70.1008 420.13 40.13 70.1008 420.13 40.14 70.1008 420.13 40.15 70.1008 420.13 40.16 70.1008 420.13 40.17 70.1008 420.13 40.18 70.1008 420.13 40.19 70.1008 420.13 40.2 70.1008 420.13 40.21 70.1008 420.13 40.22 280.403 70.1008 420.13 40.23 280.403 70.1008 420.13 40.24 280.403 70.1008 420.13 40.25 280.403 70.1008 420.13 40.26 280.403 70.1008 420.13 40.27 280.403 70.1008 420.13 40.28 280.403 420.13 40.29 280.403 420.13 40.3 280.403 420.13 40.31 280.403 420.13 40.32 280.403 420.13 40.33 280.403 420.13 40.34 420.13 40.35 420.13 40.36 420.13 40.37 420.13 40.38 420.13 40.39 420.13 40.4 420.13 40.41 420.13 40.42 420.13 40.43 420.13 40.44 420.13 40.45 420.13 40.46 420.13 40.47 420.13 40.48 420.13 40.49 420.13 40.5 420.13 40.51 420.13 40.52 420.13 40.53 420.13 40.54 420.13 40.55 420.13 40.56 40.57 40.58 40.59 40.6 40.61 40.62 40.63 40.64 40.65 40.66 40.67 40.68 40.69 40.7 40.71 40.72 40.73 40.74 40.75 40.76 40.77 40.78 40.79 40.8 40.81 40.82 40.83 40.84 40.85 40.86 40.87 40.88 40.89 40.9 40.91 40.92 40.93 40.94 40.95 40.96 40.97 40.98 40.99 41.0 41.01 41.02 41.03 41.04 41.05 41.06 207.652 41.07 207.652 41.08 207.652 41.09 207.652 41.1 207.652 41.11 207.652 41.12 207.652 41.13 207.652 41.14 207.652 41.15 207.652 41.16 207.652 41.17 207.652 41.18 207.652 41.19 207.652 41.2 207.652 41.21 207.652 41.22 207.652 41.23 207.652 41.24 207.652 41.25 207.652 41.26 207.652 41.27 207.652 41.28 41.29 41.3 41.31 41.32 41.33 41.34 41.35 41.36 41.37 41.38 41.39 41.4 41.41 41.42 41.43 41.44 41.45 41.46 41.47 41.48 41.49 41.5 41.51 41.52 41.53 41.54 41.55 41.56 41.57 41.58 41.59 41.6 41.61 41.62 41.63 41.64 280.403 41.65 280.403 41.66 280.403 41.67 280.403 41.68 280.403 41.69 280.403 41.7 280.403 41.71 280.403 41.72 280.403 41.73 280.403 41.74 280.403 41.75 280.403 41.76 280.403 41.77 280.403 41.78 41.79 41.8 41.81 41.82 41.83 41.84 41.85 41.86 41.87 41.88 41.89 41.9 41.91 41.92 41.93 41.94 41.95 41.96 41.97 41.98 41.99 42.0 42.01 42.02 42.03 42.04 42.05 42.06 42.07 42.08 42.09 42.1 42.11 42.12 42.13 42.14 42.15 42.16 42.17 42.18 42.19 42.2 42.21 42.22 42.23 42.24 42.25 42.26 42.27 42.28 42.29 42.3 42.31 42.32 42.33 42.34 42.35 42.36 42.37 42.38 42.39 42.4 42.41 42.42 42.43 42.44 42.45 42.46 42.47 42.48 42.49 42.5 42.51 42.52 42.53 42.54 445.113 42.55 445.113 42.56 445.113 42.57 445.113 42.58 445.113 42.59 445.113 42.6 445.113 42.61 445.113 42.62 445.113 42.63 445.113 42.64 222.556 445.113 42.65 222.556 445.113 42.66 222.556 445.113 42.67 222.556 445.113 42.68 222.556 445.113 42.69 222.556 445.113 42.7 222.556 445.113 42.71 222.556 445.113 42.72 222.556 92.4986 445.113 42.73 222.556 92.4986 445.113 42.74 222.556 92.4986 445.113 42.75 222.556 92.4986 445.113 42.76 222.556 92.4986 42.77 222.556 92.4986 42.78 222.556 92.4986 42.79 222.556 92.4986 42.8 222.556 92.4986 42.81 222.556 92.4986 42.82 222.556 92.4986 42.83 222.556 92.4986 42.84 222.556 92.4986 42.85 222.556 92.4986 42.86 222.556 92.4986 42.87 222.556 92.4986 42.88 222.556 92.4986 445.113 42.89 222.556 92.4986 445.113 42.9 222.556 92.4986 445.113 42.91 222.556 92.4986 445.113 42.92 222.556 92.4986 445.113 42.93 222.556 92.4986 445.113 42.94 222.556 92.4986 445.113 42.95 222.556 92.4986 445.113 42.96 222.556 92.4986 445.113 42.97 222.556 92.4986 445.113 42.98 222.556 92.4986 445.113 42.99 222.556 92.4986 445.113 43.0 222.556 92.4986 445.113 43.01 222.556 92.4986 445.113 43.02 222.556 92.4986 445.113 43.03 222.556 92.4986 445.113 43.04 222.556 92.4986 445.113 43.05 222.556 92.4986 445.113 43.06 222.556 92.4986 445.113 43.07 222.556 92.4986 445.113 43.08 222.556 92.4986 445.113 43.09 222.556 92.4986 445.113 43.1 222.556 92.4986 445.113 43.11 222.556 92.4986 445.113 43.12 222.556 92.4986 43.13 222.556 92.4986 43.14 222.556 92.4986 43.15 222.556 92.4986 43.16 222.556 92.4986 43.17 222.556 92.4986 43.18 222.556 92.4986 43.19 222.556 92.4986 43.2 222.556 92.4986 43.21 222.556 92.4986 43.22 222.556 92.4986 43.23 222.556 92.4986 43.24 222.556 92.4986 43.25 222.556 92.4986 43.26 222.556 92.4986 43.27 222.556 92.4986 43.28 222.556 92.4986 43.29 222.556 92.4986 43.3 222.556 92.4986 43.31 222.556 92.4986 43.32 222.556 92.4986 43.33 222.556 92.4986 43.34 222.556 92.4986 43.35 222.556 92.4986 43.36 222.556 92.4986 43.37 222.556 92.4986 43.38 92.4986 43.39 92.4986 43.4 92.4986 43.41 92.4986 43.42 92.4986 43.43 92.4986 43.44 92.4986 43.45 92.4986 43.46 92.4986 43.47 92.4986 43.48 92.4986 43.49 92.4986 43.5 92.4986 43.51 92.4986 43.52 92.4986 43.53 92.4986 43.54 92.4986 43.55 92.4986 43.56 92.4986 43.57 92.4986 43.58 92.4986 43.59 92.4986 43.6 92.4986 43.61 92.4986 43.62 92.4986 43.63 92.4986 43.64 92.4986 43.65 92.4986 43.66 92.4986 43.67 92.4986 43.68 92.4986 43.69 92.4986 43.7 92.4986 43.71 92.4986 43.72 92.4986 43.73 92.4986 43.74 92.4986 43.75 92.4986 43.76 92.4986 43.77 92.4986 43.78 92.4986 43.79 92.4986 43.8 92.4986 43.81 92.4986 43.82 92.4986 43.83 92.4986 43.84 92.4986 43.85 92.4986 43.86 92.4986 43.87 92.4986 43.88 92.4986 43.89 92.4986 43.9 92.4986 43.91 92.4986 43.92 92.4986 43.93 92.4986 43.94 92.4986 43.95 92.4986 43.96 92.4986 43.97 92.4986 43.98 92.4986 43.99 92.4986 44.0 92.4986 44.01 92.4986 44.02 92.4986 44.03 92.4986 44.04 92.4986 44.05 92.4986 44.06 93.5734 220 44.07 93.5734 220 44.08 93.5734 220 44.09 93.5734 220 44.1 93.5734 220 44.11 93.5734 220 44.12 222.556 92.4986 44.13 222.556 92.4986 44.14 222.556 92.4986 44.15 222.556 92.4986 44.16 222.556 92.4986 44.17 222.556 92.4986 44.18 222.556 92.4986 44.19 222.556 92.4986 44.2 222.556 93.5734 44.21 222.556 93.5734 44.22 222.556 93.5734 44.23 222.556 93.5734 44.24 222.556 93.5734 44.25 222.556 93.5734 44.26 222.556 93.5734 44.27 222.556 93.5734 44.28 222.556 93.5734 44.29 222.556 93.5734 44.3 222.556 93.5734 44.31 222.556 93.5734 44.32 222.556 93.5734 44.33 222.556 93.5734 44.34 222.556 93.5734 44.35 222.556 93.5734 44.36 222.556 93.5734 44.37 222.556 93.5734 44.38 222.556 93.5734 44.39 222.556 93.5734 44.4 222.556 93.5734 44.41 222.556 93.5734 44.42 222.556 93.5734 44.43 222.556 93.5734 44.44 93.5734 220 44.45 93.5734 220 44.46 93.5734 220 44.47 93.5734 220 44.48 93.5734 220 44.49 93.5734 220 44.5 93.5734 220 44.51 93.5734 220 44.52 93.5734 220 44.53 93.5734 220 44.54 93.5734 220 44.55 93.5734 220 44.56 93.5734 220 44.57 93.5734 220 44.58 220 44.59 220 44.6 220 44.61 220 44.62 93.5734 220 44.63 93.5734 220 44.64 93.5734 220 44.65 93.5734 220 44.66 93.5734 220 44.67 93.5734 220 44.68 280.403 222.556 93.5734 44.69 280.403 222.556 93.5734 44.7 280.403 222.556 93.5734 44.71 280.403 222.556 93.5734 44.72 280.403 222.556 93.5734 44.73 280.403 222.556 93.5734 44.74 280.403 93.5734 220 44.75 280.403 93.5734 220 44.76 280.403 93.5734 220 44.77 280.403 93.5734 220 44.78 280.403 92.4986 220 44.79 280.403 92.4986 220 44.8 280.403 92.4986 220 44.81 280.403 92.4986 220 44.82 280.403 92.4986 220 44.83 280.403 92.4986 220 44.84 222.556 92.4986 44.85 222.556 92.4986 44.86 222.556 92.4986 44.87 222.556 92.4986 44.88 222.556 92.4986 44.89 222.556 92.4986 44.9 222.556 92.4986 44.91 222.556 92.4986 44.92 222.556 92.4986 44.93 222.556 92.4986 44.94 222.556 92.4986 44.95 222.556 92.4986 44.96 222.556 92.4986 44.97 222.556 92.4986 44.98 222.556 92.4986 44.99 222.556 92.4986 45.0 92.4986 45.01 92.4986 45.02 92.4986 45.03 92.4986 45.04 92.4986 45.05 92.4986 45.06 92.4986 45.07 92.4986 45.08 92.4986 45.09 92.4986 45.1 92.4986 45.11 92.4986 45.12 92.4986 45.13 92.4986 45.14 92.4986 45.15 92.4986 45.16 92.4986 45.17 92.4986 45.18 92.4986 45.19 92.4986 45.2 92.4986 45.21 92.4986 45.22 92.4986 45.23 92.4986 45.24 93.5734 45.25 93.5734 45.26 93.5734 45.27 93.5734 45.28 93.5734 45.29 93.5734 45.3 93.5734 45.31 93.5734 45.32 93.5734 45.33 93.5734 45.34 93.5734 45.35 93.5734 45.36 93.5734 45.37 93.5734 45.38 93.5734 45.39 93.5734 45.4 92.4986 45.41 92.4986 45.42 92.4986 45.43 92.4986 45.44 92.4986 45.45 92.4986 45.46 92.4986 45.47 92.4986 45.48 92.4986 45.49 92.4986 45.5 92.4986 45.51 92.4986 45.52 92.4986 45.53 92.4986 45.54 92.4986 45.55 92.4986 45.56 92.4986 45.57 92.4986 45.58 92.4986 45.59 92.4986 45.6 92.4986 45.61 92.4986 45.62 92.4986 425.012 45.63 92.4986 425.012 45.64 92.4986 425.012 45.65 92.4986 425.012 45.66 425.012 45.67 425.012 45.68 210.065 420.13 45.69 210.065 420.13 45.7 210.065 420.13 45.71 210.065 420.13 45.72 210.065 420.13 45.73 210.065 420.13 45.74 124.905 207.652 420.13 45.75 124.905 207.652 420.13 45.76 124.905 207.652 420.13 45.77 124.905 207.652 420.13 45.78 124.905 207.652 420.13 45.79 124.905 207.652 420.13 45.8 124.905 207.652 420.13 45.81 124.905 207.652 420.13 45.82 124.905 207.652 420.13 45.83 124.905 207.652 420.13 45.84 210.065 124.905 420.13 45.85 210.065 124.905 420.13 45.86 124.905 420.13 45.87 124.905 420.13 45.88 124.905 420.13 45.89 124.905 420.13 45.9 124.905 420.13 45.91 124.905 420.13 45.92 124.905 420.13 45.93 124.905 420.13 45.94 124.905 420.13 45.95 124.905 420.13 45.96 210.065 124.905 420.13 45.97 210.065 124.905 420.13 45.98 210.065 124.905 420.13 45.99 210.065 124.905 420.13 46.0 210.065 124.905 420.13 46.01 210.065 124.905 420.13 46.02 124.905 207.652 420.13 46.03 124.905 207.652 420.13 46.04 124.905 207.652 420.13 46.05 124.905 207.652 420.13 46.06 124.905 207.652 420.13 46.07 124.905 207.652 420.13 46.08 124.905 420.13 46.09 124.905 420.13 46.1 124.905 420.13 46.11 124.905 420.13 46.12 124.905 420.13 46.13 124.905 420.13 46.14 124.905 420.13 46.15 124.905 420.13 46.16 124.905 420.13 46.17 124.905 420.13 46.18 124.905 420.13 46.19 124.905 420.13 46.2 124.905 420.13 46.21 124.905 420.13 46.22 124.905 420.13 46.23 124.905 420.13 46.24 124.905 420.13 46.25 124.905 420.13 46.26 124.905 420.13 46.27 124.905 420.13 46.28 124.905 420.13 46.29 124.905 420.13 46.3 124.905 420.13 46.31 124.905 420.13 46.32 420.13 46.33 420.13 46.34 420.13 46.35 420.13 46.36 420.13 46.37 420.13 46.38 420.13 46.39 420.13 46.4 420.13 46.41 420.13 46.42 420.13 46.43 420.13 46.44 420.13 46.45 420.13 46.46 420.13 46.47 420.13 46.48 420.13 46.49 420.13 46.5 420.13 46.51 420.13 46.52 420.13 46.53 420.13 46.54 420.13 46.55 420.13 46.56 420.13 46.57 420.13 46.58 420.13 46.59 420.13 46.6 420.13 46.61 420.13 46.62 420.13 46.63 420.13 46.64 420.13 46.65 420.13 46.66 420.13 46.67 420.13 46.68 420.13 46.69 420.13 46.7 420.13 46.71 420.13 46.72 420.13 46.73 420.13 46.74 46.75 46.76 46.77 46.78 46.79 46.8 46.81 46.82 46.83 46.84 46.85 46.86 46.87 46.88 46.89 46.9 46.91 46.92 46.93 46.94 46.95 46.96 46.97 46.98 46.99 47.0 47.01 47.02 47.03 47.04 47.05 47.06 47.07 47.08 47.09 47.1 47.11 47.12 210.065 47.13 210.065 47.14 210.065 47.15 210.065 47.16 210.065 47.17 210.065 47.18 207.652 47.19 207.652 47.2 207.652 47.21 207.652 47.22 207.652 47.23 207.652 47.24 207.652 47.25 207.652 47.26 207.652 47.27 207.652 47.28 207.652 47.29 207.652 47.3 207.652 47.31 207.652 47.32 207.652 47.33 207.652 47.34 207.652 47.35 207.652 47.36 207.652 47.37 207.652 47.38 207.652 47.39 207.652 47.4 207.652 47.41 207.652 47.42 207.652 47.43 207.652 47.44 207.652 47.45 207.652 47.46 207.652 47.47 207.652 47.48 207.652 47.49 207.652 47.5 207.652 47.51 207.652 47.52 207.652 47.53 207.652 47.54 207.652 47.55 207.652 47.56 47.57 47.58 47.59 47.6 47.61 47.62 47.63 47.64 47.65 47.66 47.67 47.68 47.69 47.7 47.71 47.72 47.73 47.74 47.75 47.76 47.77 47.78 47.79 47.8 47.81 47.82 47.83 47.84 47.85 47.86 47.87 47.88 47.89 47.9 47.91 47.92 47.93 47.94 47.95 47.96 47.97 47.98 47.99 48.0 48.01 48.02 48.03 48.04 48.05 48.06 48.07 48.08 48.09 48.1 48.11 48.12 48.13 48.14 48.15 48.16 48.17 48.18 48.19 48.2 333.458 48.21 333.458 48.22 333.458 48.23 333.458 48.24 333.458 48.25 333.458 48.26 333.458 48.27 333.458 48.28 333.458 48.29 333.458 48.3 333.458 48.31 333.458 48.32 333.458 48.33 333.458 48.34 333.458 48.35 333.458 48.36 48.37 48.38 48.39 48.4 333.458 48.41 333.458 48.42 333.458 48.43 333.458 48.44 333.458 48.45 333.458 48.46 333.458 48.47 333.458 48.48 333.458 48.49 333.458 48.5 333.458 48.51 333.458 48.52 333.458 48.53 333.458 48.54 333.458 48.55 333.458 48.56 48.57 48.58 369.994 48.59 369.994 48.6 369.994 48.61 369.994 48.62 369.994 48.63 369.994 48.64 369.994 48.65 369.994 48.66 369.994 48.67 369.994 48.68 369.994 48.69 369.994 48.7 374.294 48.71 374.294 48.72 374.294 48.73 374.294 48.74 374.294 220 124.905 48.75 374.294 220 124.905 48.76 374.294 220 124.905 48.77 374.294 220 124.905 48.78 374.294 220 124.905 48.79 374.294 220 124.905 48.8 374.294 220 124.905 48.81 374.294 220 124.905 48.82 374.294 220 124.905 48.83 374.294 220 124.905 48.84 374.294 220 124.905 48.85 374.294 220 124.905 48.86 374.294 220 124.905 48.87 374.294 220 124.905 48.88 374.294 220 124.905 48.89 374.294 220 124.905 48.9 374.294 220 124.905 48.91 374.294 220 124.905 48.92 374.294 124.905 48.93 374.294 124.905 48.94 369.994 124.905 48.95 369.994 124.905 48.96 369.994 124.905 48.97 369.994 124.905 48.98 369.994 124.905 48.99 369.994 124.905 49.0 374.294 124.905 49.01 374.294 124.905 49.02 374.294 124.905 49.03 374.294 124.905 49.04 374.294 124.905 49.05 374.294 124.905 49.06 374.294 124.905 49.07 374.294 124.905 49.08 369.994 124.905 49.09 369.994 124.905 49.1 369.994 124.905 49.11 369.994 124.905 49.12 369.994 49.13 369.994 49.14 374.294 49.15 374.294 49.16 374.294 49.17 374.294 49.18 374.294 49.19 374.294 49.2 374.294 49.21 374.294 49.22 374.294 49.23 374.294 49.24 374.294 49.25 374.294 49.26 374.294 49.27 374.294 49.28 374.294 49.29 374.294 49.3 374.294 49.31 374.294 49.32 374.294 49.33 374.294 49.34 374.294 49.35 374.294 49.36 374.294 49.37 374.294 49.38 374.294 49.39 374.294 49.4 374.294 49.41 374.294 49.42 374.294 49.43 374.294 49.44 374.294 49.45 374.294 49.46 374.294 49.47 374.294 49.48 374.294 49.49 374.294 49.5 374.294 49.51 374.294 49.52 374.294 49.53 374.294 49.54 374.294 49.55 374.294 49.56 374.294 49.57 374.294 49.58 374.294 49.59 374.294 49.6 311.127 374.294 49.61 311.127 374.294 49.62 311.127 374.294 49.63 311.127 374.294 49.64 311.127 49.65 311.127 49.66 314.742 49.67 314.742 49.68 314.742 49.69 314.742 49.7 314.742 49.71 314.742 49.72 314.742 49.73 314.742 49.74 314.742 49.75 314.742 49.76 314.742 49.77 314.742 49.78 314.742 49.79 314.742 49.8 314.742 49.81 314.742 49.82 314.742 49.83 314.742 49.84 314.742 49.85 314.742 49.86 314.742 49.87 314.742 49.88 314.742 49.89 314.742 49.9 314.742 49.91 314.742 49.92 314.742 49.93 314.742 49.94 314.742 49.95 314.742 49.96 314.742 49.97 314.742 49.98 314.742 49.99 314.742 50.0 314.742 50.01 314.742 50.02 314.742 50.03 314.742 50.04 314.742 50.05 314.742 50.06 314.742 50.07 314.742 50.08 314.742 50.09 314.742 50.1 314.742 50.11 314.742 50.12 314.742 50.13 314.742 50.14 314.742 493.883 50.15 314.742 493.883 50.16 314.742 493.883 50.17 314.742 493.883 50.18 314.742 493.883 50.19 314.742 493.883 50.2 311.127 493.883 50.21 311.127 493.883 50.22 311.127 493.883 50.23 311.127 493.883 50.24 222.556 311.127 493.883 50.25 222.556 311.127 493.883 50.26 222.556 311.127 493.883 50.27 222.556 311.127 493.883 50.28 222.556 493.883 249.811 50.29 222.556 493.883 249.811 50.3 220 493.883 249.811 50.31 220 493.883 249.811 50.32 220 493.883 249.811 50.33 220 493.883 249.811 50.34 220 493.883 249.811 50.35 220 493.883 249.811 50.36 220 493.883 249.811 50.37 220 493.883 249.811 50.38 220 493.883 249.811 50.39 220 493.883 249.811 50.4 220 493.883 249.811 50.41 220 493.883 249.811 50.42 220 493.883 249.811 50.43 220 493.883 249.811 50.44 220 493.883 249.811 50.45 220 493.883 249.811 50.46 220 493.883 249.811 50.47 220 493.883 249.811 50.48 220 493.883 249.811 50.49 220 493.883 249.811 50.5 220 493.883 249.811 50.51 220 493.883 249.811 50.52 220 493.883 249.811 50.53 220 493.883 249.811 50.54 220 493.883 249.811 50.55 220 493.883 249.811 50.56 220 493.883 249.811 50.57 220 493.883 249.811 50.58 220 493.883 249.811 50.59 220 493.883 249.811 50.6 220 249.811 50.61 220 249.811 50.62 220 249.811 50.63 220 249.811 50.64 220 249.811 50.65 220 249.811 50.66 249.811 50.67 249.811 50.68 249.811 50.69 249.811 50.7 249.811 50.71 249.811 50.72 249.811 50.73 249.811 50.74 249.811 50.75 249.811 50.76 249.811 50.77 249.811 50.78 249.811 50.79 249.811 50.8 249.811 50.81 249.811 50.82 249.811 50.83 249.811 50.84 249.811 50.85 249.811 50.86 249.811 50.87 249.811 50.88 249.811 50.89 249.811 50.9 249.811 50.91 249.811 50.92 249.811 50.93 249.811 50.94 249.811 50.95 249.811 50.96 249.811 50.97 249.811 50.98 249.811 50.99 249.811 51.0 249.811 51.01 249.811 51.02 249.811 51.03 249.811 51.04 249.811 51.05 249.811 51.06 249.811 51.07 249.811 51.08 249.811 51.09 249.811 51.1 249.811 51.11 249.811 51.12 249.811 51.13 249.811 51.14 249.811 51.15 249.811 51.16 249.811 51.17 249.811 51.18 249.811 51.19 249.811 51.2 311.127 249.811 51.21 311.127 249.811 51.22 311.127 249.811 51.23 311.127 249.811 51.24 311.127 51.25 311.127 51.26 314.742 51.27 314.742 51.28 314.742 51.29 314.742 51.3 314.742 51.31 314.742 51.32 314.742 51.33 314.742 51.34 314.742 51.35 314.742 51.36 314.742 51.37 314.742 51.38 314.742 51.39 314.742 51.4 314.742 51.41 314.742 51.42 314.742 51.43 314.742 51.44 314.742 51.45 314.742 51.46 314.742 51.47 314.742 51.48 314.742 51.49 314.742 51.5 314.742 51.51 314.742 51.52 314.742 51.53 314.742 51.54 314.742 51.55 314.742 51.56 314.742 51.57 314.742 51.58 314.742 51.59 314.742 51.6 314.742 51.61 314.742 51.62 314.742 51.63 314.742 51.64 314.742 51.65 314.742 51.66 314.742 51.67 314.742 51.68 314.742 51.69 314.742 51.7 314.742 51.71 314.742 51.72 314.742 51.73 314.742 51.74 51.75 51.76 51.77 51.78 51.79 51.8 51.81 51.82 51.83 51.84 51.85 51.86 51.87 51.88 51.89 51.9 51.91 51.92 51.93 51.94 83.3644 51.95 83.3644 51.96 83.3644 207.652 51.97 83.3644 207.652 51.98 83.3644 207.652 51.99 83.3644 207.652 52.0 83.3644 207.652 52.01 83.3644 207.652 52.02 83.3644 207.652 52.03 83.3644 207.652 52.04 83.3644 207.652 52.05 83.3644 207.652 52.06 83.3644 207.652 52.07 83.3644 207.652 52.08 83.3644 333.458 207.652 52.09 83.3644 333.458 207.652 52.1 83.3644 333.458 207.652 52.11 83.3644 333.458 207.652 52.12 83.3644 333.458 207.652 52.13 83.3644 333.458 207.652 52.14 83.3644 333.458 210.065 52.15 83.3644 333.458 210.065 52.16 82.4069 333.458 210.065 52.17 82.4069 333.458 210.065 52.18 82.4069 333.458 210.065 52.19 82.4069 333.458 210.065 52.2 82.4069 333.458 210.065 52.21 82.4069 333.458 210.065 52.22 83.3644 210.065 52.23 83.3644 210.065 52.24 83.3644 210.065 52.25 83.3644 210.065 52.26 83.3644 207.652 52.27 83.3644 207.652 52.28 83.3644 207.652 52.29 83.3644 207.652 52.3 83.3644 52.31 83.3644 52.32 83.3644 52.33 83.3644 52.34 83.3644 52.35 83.3644 52.36 83.3644 52.37 83.3644 52.38 83.3644 52.39 83.3644 52.4 83.3644 52.41 83.3644 52.42 83.3644 52.43 83.3644 52.44 83.3644 52.45 83.3644 52.46 83.3644 52.47 83.3644 52.48 83.3644 52.49 83.3644 52.5 83.3644 52.51 83.3644 52.52 83.3644 52.53 83.3644 52.54 83.3644 52.55 83.3644 52.56 83.3644 52.57 83.3644 52.58 83.3644 52.59 83.3644 52.6 83.3644 52.61 83.3644 52.62 83.3644 52.63 83.3644 52.64 83.3644 52.65 83.3644 52.66 83.3644 52.67 83.3644 52.68 83.3644 52.69 83.3644 52.7 83.3644 52.71 83.3644 52.72 83.3644 52.73 83.3644 52.74 83.3644 52.75 83.3644 52.76 83.3644 52.77 83.3644 52.78 83.3644 52.79 83.3644 52.8 83.3644 52.81 83.3644 52.82 83.3644 52.83 83.3644 52.84 83.3644 52.85 83.3644 52.86 83.3644 52.87 83.3644 52.88 83.3644 52.89 83.3644 52.9 83.3644 52.91 83.3644 52.92 83.3644 52.93 83.3644 52.94 83.3644 52.95 83.3644 52.96 83.3644 52.97 83.3644 52.98 83.3644 52.99 83.3644 53.0 83.3644 53.01 83.3644 53.02 83.3644 53.03 83.3644 53.04 83.3644 53.05 83.3644 53.06 83.3644 53.07 83.3644 53.08 83.3644 53.09 83.3644 53.1 83.3644 53.11 83.3644 53.12 83.3644 53.13 83.3644 53.14 83.3644 53.15 83.3644 53.16 83.3644 53.17 83.3644 53.18 83.3644 53.19 83.3644 53.2 83.3644 53.21 83.3644 53.22 83.3644 53.23 83.3644 53.24 83.3644 53.25 83.3644 53.26 83.3644 53.27 83.3644 53.28 83.3644 53.29 83.3644 53.3 83.3644 53.31 83.3644 53.32 83.3644 53.33 83.3644 53.34 83.3644 53.35 83.3644 53.36 83.3644 53.37 83.3644 53.38 83.3644 212.506 53.39 83.3644 212.506 53.4 83.3644 212.506 53.41 83.3644 212.506 53.42 83.3644 212.506 53.43 83.3644 212.506 53.44 83.3644 210.065 53.45 83.3644 210.065 53.46 83.3644 210.065 53.47 83.3644 210.065 53.48 210.065 53.49 210.065 53.5 212.506 53.51 212.506 53.52 212.506 53.53 212.506 53.54 212.506 53.55 212.506 53.56 mir_eval-0.8.2/tests/data/multipitch/est06.txt000066400000000000000000001175731475740344600213120ustar00rootroot000000000000000.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.30 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.40 0.41 0.42 0.43 0.44 0.45 0.46 0.47 0.48 0.49 0.50 0.51 0.52 0.53 0.54 0.55 0.56 587.33 0.57 493.88 587.33 0.58 493.88 587.33 0.59 493.88 587.33 0.60 493.88 587.33 0.61 493.88 587.33 0.62 185.00 493.88 587.33 0.63 185.00 493.88 587.33 0.64 185.00 493.88 587.33 0.65 185.00 493.88 587.33 0.66 185.00 493.88 587.33 0.67 185.00 493.88 587.33 0.68 185.00 493.88 587.33 0.69 185.00 493.88 587.33 0.70 185.00 493.88 587.33 0.71 185.00 493.88 587.33 0.72 185.00 493.88 587.33 0.73 185.00 493.88 587.33 0.74 185.00 493.88 587.33 0.75 185.00 493.88 587.33 0.76 185.00 493.88 587.33 0.77 185.00 493.88 587.33 0.78 185.00 493.88 587.33 0.79 185.00 493.88 587.33 0.80 185.00 493.88 587.33 0.81 185.00 493.88 587.33 0.82 185.00 493.88 587.33 0.83 185.00 493.88 587.33 0.84 185.00 493.88 587.33 0.85 185.00 493.88 587.33 622.25 0.86 185.00 493.88 622.25 0.87 185.00 493.88 622.25 0.88 185.00 493.88 622.25 0.89 185.00 493.88 622.25 0.90 185.00 493.88 622.25 0.91 185.00 493.88 622.25 0.92 185.00 493.88 622.25 0.93 185.00 493.88 622.25 0.94 185.00 493.88 622.25 0.95 185.00 493.88 622.25 0.96 185.00 493.88 622.25 0.97 185.00 493.88 622.25 0.98 185.00 493.88 622.25 0.99 185.00 493.88 622.25 1.00 185.00 493.88 622.25 1.01 185.00 493.88 622.25 1.02 185.00 493.88 622.25 1.03 185.00 493.88 622.25 1.04 185.00 493.88 622.25 1.05 185.00 493.88 622.25 1.06 185.00 493.88 622.25 1.07 185.00 493.88 622.25 1.08 185.00 493.88 622.25 1.09 185.00 493.88 622.25 1.10 185.00 493.88 622.25 1.11 185.00 493.88 622.25 932.33 1.12 185.00 493.88 622.25 932.33 1.13 185.00 493.88 622.25 932.33 1.14 185.00 493.88 622.25 932.33 1.15 185.00 493.88 622.25 932.33 1.16 185.00 493.88 622.25 932.33 1.17 185.00 493.88 622.25 932.33 1.18 185.00 493.88 622.25 932.33 1.19 185.00 493.88 932.33 1.20 185.00 493.88 932.33 1.21 185.00 493.88 932.33 1.22 185.00 493.88 932.33 1.23 185.00 493.88 932.33 1.24 185.00 493.88 932.33 1.25 185.00 246.94 493.88 932.33 1.26 185.00 246.94 493.88 932.33 1.27 185.00 246.94 493.88 932.33 1.28 185.00 246.94 493.88 932.33 1.29 185.00 246.94 493.88 932.33 1.30 185.00 246.94 493.88 932.33 1.31 185.00 246.94 493.88 932.33 1.32 185.00 246.94 493.88 932.33 1.33 185.00 246.94 493.88 932.33 1.34 185.00 246.94 493.88 932.33 1.35 185.00 246.94 493.88 932.33 1.36 185.00 246.94 493.88 932.33 1.37 185.00 246.94 493.88 932.33 1.38 185.00 246.94 493.88 830.61 932.33 1.39 185.00 246.94 493.88 830.61 932.33 1.40 185.00 246.94 493.88 830.61 932.33 1.41 185.00 246.94 493.88 830.61 932.33 1.42 185.00 246.94 493.88 830.61 1.43 185.00 246.94 493.88 830.61 1.44 185.00 246.94 493.88 830.61 1.45 185.00 493.88 830.61 1.46 185.00 493.88 830.61 1.47 185.00 493.88 830.61 1.48 185.00 493.88 830.61 1.49 185.00 493.88 830.61 1.50 185.00 246.94 493.88 830.61 1.51 185.00 246.94 493.88 830.61 1.52 185.00 246.94 493.88 830.61 1.53 185.00 246.94 493.88 830.61 1.54 185.00 246.94 493.88 830.61 1.55 185.00 246.94 493.88 830.61 1.56 185.00 246.94 493.88 830.61 1.57 185.00 246.94 493.88 830.61 1.58 185.00 246.94 493.88 830.61 1.59 185.00 246.94 493.88 830.61 1.60 185.00 246.94 493.88 830.61 1.61 185.00 493.88 659.26 830.61 1.62 185.00 493.88 659.26 830.61 1.63 185.00 493.88 659.26 830.61 1.64 185.00 493.88 659.26 830.61 1.65 185.00 493.88 659.26 830.61 1.66 185.00 493.88 659.26 830.61 1.67 185.00 493.88 659.26 830.61 1.68 185.00 493.88 659.26 830.61 1.69 185.00 493.88 659.26 830.61 1.70 185.00 493.88 659.26 1.71 185.00 493.88 659.26 1.72 185.00 493.88 659.26 1.73 185.00 493.88 659.26 1.74 185.00 493.88 659.26 1.75 185.00 493.88 659.26 1.76 185.00 493.88 659.26 1.77 185.00 493.88 659.26 1.78 185.00 493.88 659.26 1.79 185.00 493.88 659.26 1.80 185.00 493.88 659.26 1.81 185.00 493.88 659.26 1.82 185.00 493.88 659.26 1.83 185.00 493.88 659.26 1.84 185.00 493.88 659.26 1.85 185.00 493.88 659.26 1.86 185.00 493.88 622.25 659.26 1.87 185.00 493.88 622.25 659.26 1.88 185.00 493.88 622.25 659.26 1.89 185.00 493.88 622.25 659.26 1.90 185.00 493.88 622.25 659.26 1.91 185.00 493.88 622.25 659.26 1.92 185.00 493.88 622.25 659.26 1.93 185.00 493.88 622.25 659.26 1.94 185.00 493.88 622.25 659.26 1.95 185.00 493.88 622.25 659.26 1.96 185.00 493.88 622.25 659.26 1.97 185.00 493.88 622.25 1.98 185.00 493.88 622.25 1.99 185.00 493.88 622.25 2.00 185.00 493.88 622.25 2.01 185.00 493.88 622.25 2.02 185.00 493.88 622.25 2.03 185.00 493.88 622.25 2.04 185.00 493.88 622.25 2.05 185.00 246.94 493.88 622.25 2.06 185.00 246.94 493.88 622.25 2.07 185.00 246.94 493.88 622.25 2.08 185.00 246.94 493.88 2.09 185.00 246.94 493.88 2.10 185.00 246.94 493.88 587.33 2.11 185.00 246.94 493.88 587.33 2.12 185.00 246.94 493.88 587.33 2.13 185.00 246.94 493.88 587.33 2.14 185.00 246.94 493.88 587.33 2.15 185.00 246.94 493.88 587.33 2.16 185.00 246.94 493.88 587.33 2.17 185.00 246.94 493.88 587.33 2.18 185.00 246.94 493.88 587.33 2.19 185.00 246.94 493.88 587.33 2.20 185.00 246.94 493.88 587.33 2.21 185.00 246.94 493.88 587.33 2.22 185.00 246.94 493.88 587.33 2.23 185.00 246.94 493.88 587.33 2.24 185.00 246.94 493.88 587.33 2.25 185.00 246.94 493.88 587.33 2.26 185.00 246.94 493.88 587.33 2.27 185.00 246.94 493.88 587.33 2.28 185.00 246.94 493.88 587.33 2.29 185.00 246.94 493.88 587.33 2.30 493.88 587.33 2.31 493.88 587.33 2.32 493.88 587.33 2.33 493.88 587.33 2.34 493.88 587.33 2.35 493.88 587.33 2.36 185.00 493.88 587.33 2.37 185.00 493.88 587.33 2.38 185.00 493.88 587.33 2.39 185.00 493.88 587.33 2.40 185.00 493.88 587.33 2.41 185.00 246.94 493.88 587.33 2.42 185.00 246.94 493.88 587.33 2.43 185.00 246.94 493.88 587.33 622.25 2.44 185.00 246.94 493.88 587.33 622.25 2.45 185.00 246.94 493.88 587.33 622.25 2.46 185.00 246.94 493.88 587.33 622.25 2.47 185.00 246.94 493.88 587.33 622.25 2.48 185.00 246.94 493.88 622.25 2.49 185.00 246.94 493.88 622.25 2.50 185.00 246.94 493.88 622.25 2.51 185.00 246.94 493.88 622.25 2.52 185.00 246.94 493.88 622.25 2.53 185.00 246.94 493.88 622.25 2.54 185.00 246.94 493.88 622.25 2.55 185.00 246.94 493.88 622.25 2.56 185.00 246.94 493.88 622.25 2.57 185.00 246.94 493.88 622.25 2.58 185.00 246.94 493.88 622.25 2.59 185.00 246.94 493.88 622.25 2.60 185.00 246.94 493.88 622.25 2.61 185.00 246.94 493.88 622.25 2.62 185.00 246.94 493.88 622.25 2.63 185.00 246.94 493.88 622.25 2.64 185.00 246.94 493.88 622.25 2.65 185.00 493.88 622.25 2.66 185.00 493.88 622.25 2.67 185.00 493.88 622.25 2.68 185.00 493.88 622.25 2.69 185.00 493.88 622.25 2.70 185.00 493.88 622.25 2.71 185.00 493.88 622.25 2.72 185.00 493.88 622.25 2.73 493.88 622.25 2.74 493.88 622.25 2.75 493.88 622.25 2.76 493.88 622.25 2.77 493.88 622.25 2.78 493.88 622.25 2.79 493.88 2.80 493.88 2.81 493.88 2.82 415.30 493.88 2.83 415.30 493.88 2.84 415.30 493.88 2.85 185.00 415.30 493.88 2.86 185.00 415.30 493.88 2.87 185.00 415.30 493.88 2.88 185.00 415.30 493.88 2.89 185.00 415.30 493.88 2.90 185.00 415.30 493.88 2.91 185.00 415.30 493.88 2.92 185.00 415.30 493.88 2.93 185.00 415.30 493.88 2.94 185.00 415.30 493.88 2.95 415.30 493.88 2.96 415.30 493.88 2.97 415.30 493.88 2.98 415.30 493.88 2.99 415.30 493.88 3.00 415.30 493.88 3.01 185.00 415.30 493.88 3.02 185.00 415.30 493.88 3.03 185.00 415.30 493.88 3.04 185.00 415.30 3.05 185.00 415.30 3.06 185.00 415.30 3.07 185.00 415.30 3.08 185.00 369.99 415.30 3.09 185.00 369.99 415.30 3.10 185.00 369.99 415.30 3.11 185.00 369.99 415.30 3.12 185.00 369.99 415.30 3.13 185.00 369.99 415.30 3.14 185.00 369.99 415.30 3.15 185.00 246.94 369.99 415.30 3.16 185.00 246.94 369.99 415.30 3.17 185.00 246.94 369.99 415.30 3.18 185.00 246.94 369.99 415.30 3.19 185.00 246.94 369.99 415.30 3.20 185.00 246.94 369.99 415.30 3.21 185.00 246.94 369.99 415.30 3.22 185.00 246.94 369.99 3.23 185.00 246.94 369.99 3.24 185.00 246.94 369.99 3.25 185.00 246.94 369.99 3.26 185.00 246.94 369.99 3.27 185.00 246.94 369.99 3.28 185.00 246.94 369.99 3.29 185.00 246.94 369.99 3.30 185.00 369.99 587.33 3.31 185.00 369.99 587.33 3.32 185.00 369.99 587.33 3.33 185.00 369.99 587.33 3.34 185.00 369.99 587.33 3.35 185.00 369.99 587.33 3.36 185.00 369.99 587.33 3.37 185.00 369.99 587.33 3.38 185.00 369.99 587.33 3.39 185.00 369.99 587.33 3.40 185.00 369.99 587.33 3.41 185.00 369.99 587.33 3.42 185.00 369.99 587.33 3.43 185.00 369.99 587.33 3.44 185.00 369.99 587.33 3.45 185.00 369.99 587.33 3.46 185.00 369.99 587.33 3.47 185.00 369.99 587.33 3.48 185.00 369.99 587.33 3.49 185.00 369.99 587.33 3.50 185.00 369.99 587.33 3.51 185.00 369.99 587.33 3.52 185.00 369.99 587.33 3.53 185.00 369.99 587.33 3.54 185.00 369.99 587.33 3.55 185.00 369.99 587.33 3.56 185.00 369.99 587.33 3.57 185.00 369.99 587.33 3.58 185.00 369.99 587.33 3.59 185.00 369.99 587.33 3.60 185.00 369.99 587.33 3.61 185.00 369.99 587.33 3.62 185.00 369.99 587.33 3.63 185.00 369.99 587.33 3.64 185.00 369.99 587.33 3.65 185.00 369.99 587.33 3.66 185.00 369.99 587.33 622.25 3.67 185.00 369.99 587.33 622.25 3.68 185.00 369.99 587.33 622.25 3.69 185.00 369.99 587.33 622.25 3.70 185.00 587.33 622.25 3.71 185.00 587.33 622.25 3.72 185.00 587.33 622.25 3.73 185.00 622.25 3.74 185.00 622.25 3.75 185.00 622.25 3.76 185.00 622.25 3.77 185.00 622.25 3.78 185.00 622.25 3.79 185.00 622.25 3.80 185.00 622.25 3.81 185.00 622.25 3.82 185.00 622.25 3.83 185.00 246.94 622.25 3.84 185.00 246.94 493.88 622.25 987.77 3.85 185.00 246.94 493.88 622.25 987.77 3.86 185.00 246.94 493.88 622.25 987.77 3.87 185.00 246.94 493.88 622.25 987.77 3.88 185.00 246.94 493.88 622.25 987.77 3.89 185.00 246.94 493.88 622.25 987.77 3.90 185.00 246.94 493.88 622.25 987.77 3.91 185.00 246.94 493.88 622.25 987.77 3.92 185.00 246.94 493.88 622.25 987.77 3.93 185.00 246.94 493.88 622.25 987.77 3.94 185.00 246.94 493.88 622.25 987.77 3.95 185.00 246.94 493.88 622.25 987.77 3.96 185.00 246.94 493.88 622.25 987.77 3.97 185.00 246.94 493.88 622.25 987.77 3.98 185.00 246.94 493.88 622.25 987.77 3.99 185.00 246.94 493.88 622.25 987.77 4.00 185.00 246.94 493.88 622.25 987.77 4.01 185.00 246.94 493.88 622.25 987.77 4.02 185.00 246.94 493.88 622.25 987.77 4.03 185.00 246.94 493.88 622.25 987.77 4.04 185.00 246.94 493.88 622.25 987.77 4.05 185.00 246.94 493.88 622.25 987.77 4.06 185.00 246.94 493.88 622.25 932.33 987.77 4.07 185.00 622.25 932.33 987.77 4.08 185.00 622.25 932.33 987.77 4.09 185.00 622.25 932.33 987.77 4.10 185.00 622.25 932.33 987.77 4.11 185.00 932.33 987.77 4.12 185.00 932.33 987.77 4.13 185.00 932.33 987.77 4.14 185.00 932.33 987.77 4.15 185.00 932.33 987.77 4.16 185.00 932.33 987.77 4.17 185.00 932.33 987.77 4.18 185.00 246.94 932.33 987.77 4.19 185.00 246.94 932.33 987.77 4.20 185.00 246.94 932.33 987.77 4.21 185.00 246.94 932.33 987.77 4.22 185.00 246.94 932.33 987.77 4.23 185.00 246.94 932.33 987.77 4.24 185.00 246.94 932.33 987.77 4.25 185.00 246.94 932.33 987.77 4.26 185.00 932.33 4.27 185.00 932.33 4.28 185.00 932.33 4.29 185.00 415.30 830.61 932.33 4.30 185.00 415.30 830.61 932.33 4.31 185.00 415.30 830.61 932.33 4.32 185.00 415.30 830.61 932.33 4.33 185.00 415.30 830.61 932.33 4.34 185.00 415.30 830.61 932.33 4.35 185.00 415.30 830.61 932.33 4.36 185.00 415.30 830.61 932.33 4.37 185.00 415.30 830.61 932.33 4.38 185.00 415.30 830.61 932.33 4.39 185.00 415.30 830.61 932.33 4.40 185.00 415.30 830.61 932.33 4.41 185.00 415.30 830.61 932.33 4.42 185.00 415.30 830.61 932.33 4.43 185.00 415.30 830.61 932.33 4.44 185.00 415.30 830.61 932.33 4.45 185.00 415.30 830.61 932.33 4.46 185.00 415.30 830.61 932.33 4.47 185.00 246.94 415.30 830.61 932.33 4.48 185.00 246.94 415.30 830.61 932.33 4.49 185.00 246.94 415.30 493.88 830.61 932.33 4.50 185.00 246.94 415.30 493.88 830.61 932.33 4.51 185.00 246.94 493.88 830.61 932.33 4.52 185.00 246.94 493.88 830.61 932.33 4.53 185.00 246.94 493.88 830.61 932.33 4.54 185.00 246.94 493.88 830.61 932.33 4.55 185.00 246.94 493.88 830.61 932.33 4.56 185.00 246.94 493.88 622.25 830.61 932.33 4.57 185.00 246.94 493.88 622.25 830.61 4.58 185.00 246.94 493.88 622.25 830.61 4.59 185.00 246.94 493.88 622.25 830.61 4.60 185.00 246.94 493.88 622.25 830.61 4.61 185.00 246.94 493.88 622.25 830.61 4.62 185.00 246.94 493.88 622.25 830.61 4.63 185.00 246.94 493.88 622.25 830.61 4.64 185.00 246.94 493.88 622.25 830.61 4.65 185.00 246.94 622.25 830.61 4.66 185.00 622.25 830.61 4.67 185.00 622.25 830.61 4.68 185.00 622.25 830.61 4.69 185.00 622.25 4.70 185.00 622.25 4.71 185.00 622.25 4.72 185.00 587.33 622.25 4.73 185.00 587.33 622.25 4.74 185.00 587.33 622.25 4.75 185.00 587.33 622.25 4.76 185.00 587.33 622.25 4.77 185.00 587.33 622.25 4.78 185.00 587.33 622.25 4.79 185.00 587.33 622.25 4.80 185.00 587.33 622.25 4.81 185.00 587.33 622.25 4.82 185.00 587.33 622.25 4.83 185.00 587.33 622.25 4.84 185.00 587.33 622.25 4.85 185.00 587.33 622.25 4.86 185.00 587.33 4.87 185.00 587.33 4.88 185.00 587.33 4.89 185.00 587.33 4.90 185.00 587.33 4.91 185.00 587.33 4.92 185.00 587.33 4.93 185.00 587.33 4.94 185.00 587.33 4.95 587.33 4.96 587.33 4.97 587.33 4.98 587.33 4.99 587.33 5.00 587.33 5.01 587.33 5.02 587.33 5.03 587.33 5.04 587.33 5.05 587.33 5.06 587.33 5.07 587.33 5.08 587.33 5.09 587.33 5.10 587.33 5.11 587.33 622.25 5.12 587.33 622.25 5.13 587.33 622.25 5.14 246.94 587.33 622.25 5.15 246.94 587.33 622.25 5.16 246.94 587.33 622.25 5.17 246.94 587.33 622.25 5.18 246.94 587.33 622.25 5.19 246.94 587.33 622.25 5.20 246.94 587.33 622.25 5.21 246.94 587.33 622.25 5.22 246.94 622.25 5.23 185.00 246.94 622.25 5.24 185.00 246.94 622.25 5.25 185.00 246.94 622.25 5.26 185.00 246.94 622.25 5.27 185.00 246.94 622.25 5.28 185.00 246.94 622.25 5.29 185.00 622.25 5.30 185.00 622.25 5.31 185.00 622.25 5.32 185.00 622.25 5.33 185.00 622.25 5.34 185.00 622.25 5.35 185.00 622.25 5.36 185.00 622.25 5.37 622.25 5.38 622.25 5.39 622.25 5.40 5.41 415.30 5.42 415.30 5.43 415.30 5.44 185.00 415.30 5.45 185.00 415.30 5.46 185.00 415.30 5.47 185.00 415.30 5.48 185.00 415.30 5.49 185.00 415.30 5.50 185.00 415.30 5.51 185.00 415.30 5.52 185.00 415.30 5.53 185.00 415.30 5.54 185.00 415.30 5.55 185.00 415.30 5.56 185.00 415.30 5.57 185.00 415.30 5.58 185.00 415.30 5.59 185.00 415.30 5.60 415.30 5.61 415.30 5.62 207.65 415.30 5.63 207.65 415.30 5.64 207.65 415.30 5.65 207.65 415.30 5.66 207.65 415.30 5.67 207.65 415.30 5.68 207.65 415.30 5.69 207.65 369.99 415.30 5.70 185.00 207.65 369.99 415.30 5.71 185.00 207.65 369.99 415.30 5.72 185.00 369.99 415.30 5.73 185.00 369.99 415.30 5.74 185.00 369.99 415.30 5.75 185.00 369.99 415.30 5.76 185.00 369.99 415.30 5.77 185.00 369.99 415.30 5.78 185.00 369.99 415.30 5.79 185.00 369.99 415.30 5.80 185.00 369.99 415.30 5.81 185.00 369.99 415.30 5.82 185.00 369.99 415.30 5.83 185.00 369.99 415.30 5.84 185.00 369.99 5.85 185.00 369.99 5.86 185.00 369.99 5.87 185.00 369.99 5.88 185.00 369.99 5.89 185.00 369.99 5.90 185.00 369.99 5.91 185.00 369.99 622.25 5.92 185.00 369.99 622.25 5.93 185.00 369.99 622.25 5.94 185.00 369.99 622.25 5.95 185.00 369.99 622.25 5.96 185.00 369.99 622.25 5.97 185.00 369.99 622.25 5.98 185.00 369.99 622.25 5.99 369.99 622.25 6.00 369.99 622.25 6.01 369.99 622.25 6.02 369.99 622.25 6.03 369.99 622.25 6.04 369.99 622.25 6.05 369.99 622.25 659.26 6.06 369.99 622.25 659.26 6.07 369.99 622.25 659.26 6.08 369.99 622.25 659.26 6.09 369.99 659.26 6.10 369.99 659.26 6.11 659.26 6.12 659.26 6.13 207.65 659.26 6.14 207.65 659.26 6.15 207.65 659.26 6.16 207.65 659.26 6.17 207.65 659.26 6.18 207.65 659.26 6.19 207.65 392.00 659.26 6.20 207.65 392.00 659.26 6.21 207.65 392.00 659.26 6.22 207.65 392.00 659.26 6.23 207.65 392.00 659.26 6.24 207.65 392.00 659.26 6.25 392.00 659.26 6.26 392.00 659.26 6.27 392.00 659.26 6.28 392.00 659.26 6.29 392.00 659.26 6.30 392.00 659.26 6.31 392.00 659.26 6.32 392.00 659.26 6.33 392.00 659.26 6.34 392.00 659.26 6.35 392.00 659.26 6.36 659.26 6.37 659.26 6.38 659.26 6.39 659.26 6.40 415.30 659.26 6.41 415.30 659.26 6.42 415.30 659.26 6.43 415.30 659.26 6.44 415.30 659.26 6.45 415.30 659.26 6.46 415.30 659.26 6.47 415.30 659.26 6.48 415.30 659.26 6.49 415.30 659.26 6.50 415.30 659.26 6.51 415.30 659.26 6.52 415.30 659.26 6.53 415.30 659.26 6.54 415.30 622.25 659.26 6.55 415.30 622.25 659.26 6.56 622.25 659.26 6.57 622.25 659.26 6.58 622.25 659.26 6.59 622.25 659.26 6.60 622.25 6.61 622.25 6.62 622.25 6.63 622.25 6.64 622.25 6.65 622.25 6.66 622.25 6.67 622.25 6.68 622.25 6.69 622.25 6.70 622.25 6.71 622.25 6.72 622.25 6.73 622.25 6.74 622.25 739.99 6.75 207.65 622.25 739.99 6.76 207.65 622.25 739.99 6.77 207.65 622.25 739.99 6.78 207.65 622.25 739.99 6.79 207.65 622.25 739.99 6.80 103.83 207.65 311.13 622.25 739.99 6.81 103.83 207.65 311.13 622.25 739.99 6.82 103.83 207.65 311.13 554.37 622.25 739.99 6.83 103.83 207.65 311.13 554.37 622.25 739.99 6.84 103.83 207.65 311.13 554.37 622.25 739.99 6.85 103.83 207.65 311.13 554.37 622.25 739.99 6.86 103.83 207.65 311.13 554.37 622.25 739.99 6.87 103.83 207.65 311.13 554.37 622.25 739.99 6.88 103.83 207.65 311.13 554.37 622.25 739.99 6.89 103.83 207.65 311.13 554.37 622.25 739.99 6.90 207.65 311.13 554.37 622.25 739.99 6.91 207.65 554.37 622.25 739.99 6.92 207.65 554.37 622.25 739.99 6.93 207.65 554.37 622.25 739.99 6.94 207.65 554.37 622.25 739.99 6.95 207.65 554.37 622.25 739.99 6.96 207.65 554.37 622.25 739.99 6.97 207.65 554.37 622.25 739.99 6.98 207.65 554.37 622.25 739.99 6.99 207.65 554.37 622.25 739.99 7.00 110.00 554.37 622.25 739.99 7.01 110.00 554.37 622.25 7.02 110.00 493.88 554.37 622.25 7.03 110.00 493.88 554.37 622.25 7.04 110.00 493.88 554.37 622.25 7.05 110.00 493.88 554.37 622.25 7.06 110.00 493.88 554.37 622.25 739.99 7.07 110.00 493.88 554.37 622.25 739.99 7.08 110.00 493.88 554.37 622.25 739.99 7.09 110.00 493.88 554.37 622.25 739.99 7.10 110.00 493.88 554.37 622.25 739.99 7.11 493.88 554.37 622.25 739.99 7.12 493.88 554.37 622.25 739.99 7.13 493.88 622.25 739.99 7.14 493.88 622.25 739.99 7.15 493.88 622.25 739.99 7.16 493.88 622.25 739.99 7.17 493.88 622.25 739.99 7.18 207.65 466.16 493.88 622.25 739.99 7.19 207.65 466.16 493.88 622.25 739.99 7.20 207.65 466.16 493.88 622.25 739.99 7.21 207.65 466.16 622.25 739.99 7.22 207.65 466.16 622.25 739.99 7.23 207.65 466.16 622.25 739.99 7.24 207.65 466.16 622.25 739.99 7.25 207.65 466.16 622.25 739.99 7.26 207.65 466.16 622.25 739.99 7.27 207.65 466.16 622.25 739.99 7.28 207.65 466.16 622.25 739.99 7.29 207.65 466.16 622.25 739.99 7.30 207.65 466.16 622.25 739.99 7.31 207.65 466.16 622.25 739.99 7.32 207.65 466.16 622.25 739.99 7.33 207.65 466.16 622.25 739.99 7.34 207.65 466.16 622.25 739.99 7.35 207.65 466.16 622.25 739.99 7.36 207.65 466.16 622.25 739.99 7.37 207.65 466.16 622.25 739.99 7.38 207.65 466.16 622.25 739.99 7.39 207.65 466.16 622.25 739.99 7.40 207.65 466.16 554.37 622.25 7.41 207.65 440.00 466.16 554.37 659.26 880.00 7.42 103.83 440.00 466.16 554.37 659.26 880.00 7.43 103.83 440.00 466.16 554.37 659.26 880.00 7.44 103.83 440.00 554.37 659.26 880.00 7.45 103.83 440.00 554.37 659.26 880.00 7.46 103.83 440.00 554.37 659.26 880.00 7.47 103.83 440.00 554.37 659.26 880.00 7.48 103.83 440.00 554.37 659.26 880.00 7.49 103.83 440.00 554.37 659.26 880.00 7.50 103.83 440.00 554.37 659.26 880.00 7.51 103.83 440.00 554.37 659.26 880.00 7.52 103.83 440.00 554.37 659.26 880.00 7.53 103.83 440.00 554.37 659.26 880.00 7.54 103.83 440.00 554.37 659.26 880.00 7.55 103.83 440.00 554.37 659.26 880.00 7.56 103.83 440.00 554.37 659.26 880.00 7.57 103.83 440.00 554.37 659.26 880.00 7.58 103.83 440.00 554.37 659.26 880.00 7.59 103.83 440.00 554.37 659.26 880.00 7.60 440.00 554.37 659.26 880.00 7.61 440.00 554.37 659.26 880.00 7.62 440.00 554.37 659.26 880.00 7.63 440.00 554.37 659.26 880.00 7.64 440.00 554.37 659.26 880.00 7.65 440.00 554.37 659.26 880.00 7.66 440.00 554.37 659.26 880.00 7.67 220.00 440.00 554.37 659.26 880.00 1760.00 7.68 220.00 440.00 554.37 659.26 880.00 1760.00 7.69 220.00 440.00 554.37 659.26 880.00 1760.00 7.70 220.00 440.00 554.37 659.26 880.00 1760.00 7.71 220.00 440.00 554.37 659.26 880.00 1760.00 7.72 220.00 440.00 554.37 659.26 880.00 1760.00 7.73 220.00 440.00 554.37 659.26 880.00 1760.00 7.74 220.00 440.00 554.37 659.26 880.00 1760.00 7.75 220.00 440.00 466.16 554.37 659.26 880.00 1318.51 7.76 220.00 440.00 466.16 554.37 622.25 659.26 880.00 1318.51 7.77 220.00 440.00 466.16 622.25 659.26 880.00 1318.51 7.78 220.00 440.00 466.16 622.25 659.26 880.00 1318.51 7.79 466.16 622.25 659.26 880.00 1318.51 7.80 466.16 622.25 659.26 880.00 1318.51 7.81 466.16 622.25 659.26 1318.51 7.82 466.16 622.25 659.26 1318.51 7.83 466.16 622.25 659.26 1318.51 7.84 466.16 622.25 659.26 1318.51 7.85 466.16 622.25 1318.51 7.86 466.16 622.25 7.87 466.16 622.25 7.88 466.16 622.25 7.89 466.16 622.25 7.90 466.16 622.25 7.91 466.16 622.25 7.92 233.08 466.16 622.25 7.93 233.08 466.16 622.25 7.94 233.08 466.16 622.25 7.95 233.08 466.16 622.25 7.96 233.08 466.16 622.25 7.97 233.08 466.16 622.25 7.98 233.08 466.16 622.25 7.99 233.08 466.16 622.25 8.00 233.08 466.16 622.25 8.01 233.08 466.16 622.25 8.02 233.08 466.16 622.25 8.03 233.08 466.16 622.25 8.04 233.08 466.16 622.25 8.05 466.16 622.25 8.06 466.16 622.25 8.07 466.16 622.25 8.08 466.16 622.25 8.09 311.13 466.16 622.25 8.10 207.65 311.13 466.16 622.25 8.11 207.65 311.13 466.16 622.25 8.12 207.65 311.13 466.16 622.25 8.13 207.65 311.13 466.16 622.25 8.14 207.65 311.13 466.16 622.25 8.15 207.65 311.13 466.16 622.25 8.16 207.65 311.13 466.16 622.25 8.17 207.65 311.13 466.16 622.25 8.18 207.65 311.13 466.16 622.25 8.19 207.65 311.13 466.16 622.25 8.20 207.65 311.13 466.16 622.25 8.21 138.59 207.65 311.13 466.16 622.25 8.22 138.59 207.65 311.13 466.16 622.25 8.23 138.59 207.65 311.13 466.16 622.25 8.24 138.59 207.65 311.13 466.16 622.25 8.25 138.59 207.65 311.13 622.25 8.26 138.59 207.65 311.13 622.25 8.27 138.59 311.13 622.25 8.28 311.13 622.25 8.29 311.13 622.25 8.30 110.00 311.13 622.25 8.31 110.00 311.13 622.25 8.32 110.00 311.13 622.25 8.33 110.00 311.13 622.25 8.34 110.00 311.13 622.25 8.35 110.00 311.13 622.25 8.36 110.00 311.13 622.25 8.37 110.00 311.13 622.25 8.38 110.00 311.13 622.25 8.39 110.00 311.13 622.25 8.40 110.00 311.13 622.25 8.41 110.00 311.13 622.25 8.42 110.00 311.13 622.25 8.43 110.00 277.18 311.13 622.25 8.44 110.00 277.18 311.13 622.25 8.45 110.00 277.18 311.13 622.25 8.46 277.18 311.13 622.25 8.47 277.18 311.13 622.25 8.48 277.18 311.13 622.25 8.49 277.18 311.13 622.25 8.50 138.59 277.18 311.13 622.25 8.51 138.59 277.18 311.13 622.25 8.52 138.59 277.18 311.13 622.25 8.53 138.59 277.18 311.13 622.25 8.54 138.59 277.18 311.13 622.25 8.55 138.59 277.18 311.13 622.25 8.56 138.59 277.18 311.13 622.25 8.57 138.59 277.18 311.13 622.25 8.58 138.59 277.18 311.13 8.59 138.59 277.18 311.13 8.60 138.59 277.18 311.13 8.61 138.59 277.18 311.13 8.62 138.59 277.18 8.63 138.59 277.18 8.64 138.59 277.18 8.65 138.59 277.18 8.66 138.59 277.18 8.67 138.59 277.18 8.68 138.59 277.18 622.25 8.69 138.59 622.25 8.70 622.25 8.71 196.00 622.25 8.72 98.00 196.00 329.63 622.25 8.73 98.00 196.00 329.63 622.25 8.74 98.00 196.00 329.63 622.25 8.75 98.00 196.00 329.63 622.25 8.76 98.00 196.00 329.63 622.25 8.77 98.00 196.00 329.63 622.25 8.78 98.00 196.00 329.63 622.25 8.79 98.00 196.00 329.63 8.80 98.00 196.00 329.63 8.81 98.00 196.00 329.63 8.82 98.00 196.00 329.63 8.83 98.00 196.00 329.63 8.84 98.00 196.00 277.18 329.63 8.85 196.00 277.18 329.63 8.86 196.00 277.18 329.63 8.87 196.00 277.18 329.63 8.88 196.00 277.18 329.63 8.89 277.18 329.63 8.90 220.00 277.18 329.63 8.91 220.00 277.18 329.63 8.92 220.00 329.63 8.93 220.00 329.63 8.94 220.00 329.63 8.95 220.00 329.63 8.96 220.00 329.63 440.00 8.97 220.00 329.63 440.00 8.98 220.00 329.63 440.00 8.99 220.00 329.63 440.00 9.00 220.00 329.63 440.00 9.01 220.00 329.63 440.00 9.02 220.00 329.63 440.00 9.03 220.00 329.63 440.00 9.04 220.00 329.63 440.00 9.05 220.00 329.63 440.00 9.06 220.00 329.63 440.00 9.07 220.00 329.63 440.00 9.08 220.00 329.63 440.00 9.09 220.00 329.63 440.00 9.10 220.00 329.63 440.00 9.11 220.00 329.63 440.00 9.12 220.00 329.63 440.00 9.13 220.00 440.00 9.14 220.00 440.00 9.15 220.00 440.00 493.88 9.16 220.00 440.00 493.88 9.17 220.00 440.00 493.88 9.18 493.88 9.19 493.88 9.20 493.88 9.21 493.88 9.22 493.88 9.23 493.88 9.24 493.88 9.25 493.88 9.26 493.88 9.27 220.00 493.88 659.26 9.28 220.00 493.88 659.26 9.29 220.00 493.88 659.26 9.30 220.00 493.88 554.37 659.26 987.77 9.31 220.00 493.88 554.37 659.26 987.77 9.32 220.00 493.88 554.37 659.26 987.77 9.33 220.00 493.88 554.37 659.26 987.77 9.34 220.00 493.88 554.37 659.26 987.77 9.35 220.00 440.00 493.88 554.37 659.26 987.77 9.36 220.00 440.00 493.88 554.37 659.26 987.77 9.37 220.00 440.00 493.88 554.37 659.26 9.38 196.00 220.00 440.00 493.88 554.37 659.26 9.39 196.00 220.00 440.00 493.88 554.37 659.26 9.40 196.00 440.00 554.37 659.26 9.41 196.00 440.00 554.37 659.26 9.42 196.00 440.00 554.37 659.26 9.43 196.00 440.00 554.37 659.26 9.44 196.00 440.00 554.37 659.26 9.45 196.00 440.00 554.37 659.26 9.46 440.00 554.37 659.26 9.47 440.00 554.37 659.26 9.48 440.00 554.37 659.26 9.49 440.00 554.37 659.26 9.50 440.00 554.37 659.26 9.51 220.00 440.00 554.37 659.26 9.52 220.00 440.00 554.37 659.26 9.53 220.00 440.00 554.37 659.26 9.54 220.00 440.00 554.37 659.26 9.55 220.00 440.00 554.37 659.26 9.56 220.00 440.00 554.37 659.26 9.57 220.00 440.00 554.37 659.26 9.58 220.00 440.00 554.37 659.26 9.59 220.00 440.00 554.37 659.26 9.60 220.00 440.00 554.37 659.26 9.61 220.00 440.00 659.26 9.62 220.00 369.99 440.00 659.26 9.63 220.00 369.99 440.00 659.26 9.64 220.00 369.99 440.00 659.26 9.65 220.00 369.99 440.00 659.26 9.66 220.00 369.99 440.00 659.26 9.67 220.00 369.99 440.00 659.26 9.68 220.00 369.99 440.00 659.26 9.69 220.00 369.99 440.00 659.26 9.70 220.00 369.99 440.00 659.26 9.71 220.00 369.99 440.00 659.26 9.72 220.00 369.99 659.26 9.73 369.99 659.26 9.74 369.99 659.26 9.75 369.99 659.26 9.76 369.99 659.26 9.77 369.99 659.26 9.78 369.99 659.26 9.79 329.63 369.99 659.26 9.80 138.59 329.63 369.99 659.26 9.81 138.59 329.63 9.82 138.59 329.63 9.83 138.59 329.63 9.84 138.59 329.63 9.85 138.59 329.63 9.86 138.59 329.63 9.87 138.59 329.63 9.88 138.59 329.63 9.89 138.59 329.63 9.90 138.59 329.63 9.91 138.59 329.63 9.92 138.59 329.63 554.37 9.93 138.59 329.63 554.37 9.94 138.59 329.63 554.37 9.95 138.59 220.00 329.63 554.37 9.96 138.59 220.00 329.63 554.37 9.97 138.59 220.00 329.63 554.37 9.98 138.59 220.00 329.63 554.37 9.99 138.59 220.00 329.63 554.37 659.26 10.00 138.59 220.00 329.63 554.37 659.26 10.01 138.59 220.00 554.37 659.26 10.02 138.59 220.00 554.37 659.26 10.03 138.59 220.00 659.26 10.04 98.00 659.26 10.05 98.00 659.26 10.06 98.00 659.26 10.07 98.00 311.13 622.25 659.26 10.08 98.00 311.13 622.25 10.09 98.00 311.13 622.25 10.10 98.00 311.13 622.25 10.11 98.00 311.13 622.25 10.12 98.00 311.13 622.25 10.13 98.00 311.13 622.25 10.14 98.00 311.13 622.25 10.15 98.00 311.13 622.25 10.16 98.00 311.13 622.25 10.17 98.00 311.13 622.25 10.18 311.13 622.25 10.19 311.13 622.25 10.20 311.13 10.21 311.13 10.22 311.13 10.23 311.13 10.24 311.13 10.25 311.13 10.26 311.13 10.27 311.13 10.28 311.13 10.29 311.13 10.30 311.13 10.31 311.13 10.32 311.13 10.33 311.13 10.34 311.13 10.35 311.13 329.63 10.36 329.63 10.37 329.63 10.38 329.63 10.39 329.63 10.40 329.63 10.41 329.63 10.42 329.63 10.43 329.63 10.44 138.59 329.63 10.45 138.59 329.63 10.46 138.59 329.63 10.47 138.59 329.63 10.48 138.59 329.63 10.49 138.59 329.63 10.50 138.59 329.63 10.51 138.59 329.63 10.52 329.63 10.53 329.63 10.54 329.63 10.55 329.63 10.56 329.63 10.57 329.63 10.58 329.63 10.59 329.63 10.60 329.63 10.61 329.63 10.62 329.63 10.63 329.63 10.64 329.63 10.65 329.63 10.66 329.63 10.67 329.63 10.68 329.63 10.69 329.63 10.70 10.71 10.72 10.73 10.74 10.75 10.76 10.77 10.78 493.88 10.79 246.94 493.88 10.80 246.94 493.88 10.81 246.94 493.88 10.82 246.94 493.88 10.83 246.94 493.88 10.84 246.94 493.88 10.85 246.94 493.88 10.86 246.94 493.88 10.87 246.94 493.88 10.88 246.94 493.88 10.89 110.00 246.94 493.88 10.90 110.00 246.94 493.88 10.91 110.00 246.94 493.88 10.92 110.00 246.94 493.88 10.93 110.00 246.94 10.94 110.00 246.94 10.95 110.00 246.94 10.96 110.00 246.94 10.97 110.00 246.94 10.98 246.94 493.88 10.99 246.94 493.88 11.00 246.94 493.88 11.01 220.00 246.94 493.88 11.02 220.00 246.94 493.88 11.03 220.00 246.94 493.88 11.04 220.00 246.94 493.88 11.05 220.00 246.94 493.88 11.06 220.00 493.88 11.07 220.00 493.88 11.08 220.00 493.88 11.09 220.00 493.88 11.10 220.00 493.88 11.11 220.00 493.88 11.12 220.00 493.88 11.13 220.00 493.88 11.14 220.00 493.88 11.15 220.00 493.88 11.16 220.00 493.88 11.17 220.00 493.88 11.18 220.00 493.88 11.19 220.00 493.88 11.20 220.00 11.21 220.00 11.22 220.00 11.23 220.00 11.24 220.00 11.25 220.00 11.26 220.00 11.27 220.00 11.28 493.88 11.29 493.88 11.30 493.88 11.31 185.00 493.88 11.32 185.00 493.88 11.33 185.00 493.88 11.34 185.00 493.88 11.35 185.00 493.88 11.36 185.00 493.88 11.37 185.00 246.94 493.88 11.38 185.00 246.94 493.88 11.39 92.50 185.00 246.94 311.13 493.88 11.40 92.50 246.94 311.13 493.88 11.41 92.50 246.94 311.13 493.88 11.42 92.50 246.94 311.13 493.88 11.43 92.50 246.94 311.13 493.88 11.44 92.50 246.94 311.13 493.88 11.45 92.50 246.94 311.13 493.88 11.46 92.50 246.94 311.13 493.88 11.47 92.50 246.94 311.13 493.88 11.48 92.50 246.94 311.13 493.88 11.49 92.50 246.94 311.13 493.88 11.50 92.50 246.94 311.13 369.99 493.88 11.51 92.50 246.94 311.13 369.99 493.88 11.52 92.50 246.94 311.13 369.99 11.53 92.50 246.94 311.13 369.99 11.54 92.50 246.94 311.13 369.99 1108.73 11.55 246.94 311.13 369.99 1108.73 11.56 246.94 311.13 369.99 1108.73 11.57 246.94 311.13 1108.73 11.58 246.94 311.13 1108.73 11.59 246.94 311.13 1108.73 11.60 246.94 1108.73 11.61 246.94 1108.73 11.62 246.94 1108.73 11.63 246.94 1108.73 11.64 246.94 493.88 1108.73 11.65 246.94 369.99 493.88 1108.73 11.66 246.94 369.99 493.88 11.67 246.94 369.99 493.88 11.68 246.94 369.99 493.88 11.69 246.94 369.99 493.88 11.70 246.94 369.99 493.88 11.71 246.94 369.99 493.88 554.37 11.72 246.94 369.99 493.88 554.37 11.73 246.94 369.99 493.88 554.37 11.74 246.94 369.99 493.88 554.37 11.75 246.94 493.88 554.37 11.76 246.94 493.88 554.37 11.77 185.00 246.94 493.88 554.37 11.78 185.00 246.94 493.88 554.37 11.79 185.00 246.94 493.88 554.37 11.80 185.00 246.94 493.88 554.37 11.81 185.00 246.94 493.88 554.37 11.82 185.00 246.94 493.88 554.37 11.83 185.00 246.94 493.88 554.37 11.84 185.00 246.94 493.88 554.37 11.85 185.00 246.94 493.88 554.37 11.86 185.00 246.94 493.88 554.37 11.87 185.00 246.94 493.88 554.37 11.88 185.00 246.94 493.88 554.37 11.89 185.00 246.94 493.88 554.37 11.90 185.00 246.94 493.88 554.37 11.91 185.00 246.94 493.88 554.37 11.92 185.00 246.94 493.88 554.37 11.93 185.00 246.94 493.88 554.37 11.94 92.50 185.00 246.94 493.88 554.37 11.95 92.50 185.00 246.94 493.88 554.37 11.96 92.50 185.00 246.94 493.88 554.37 11.97 92.50 185.00 246.94 493.88 554.37 11.98 92.50 185.00 246.94 493.88 554.37 11.99 92.50 185.00 246.94 493.88 554.37 12.00 92.50 185.00 246.94 493.88 554.37 12.01 92.50 185.00 246.94 493.88 554.37 12.02 92.50 185.00 246.94 493.88 12.03 92.50 185.00 246.94 493.88 12.04 92.50 185.00 246.94 493.88 12.05 92.50 185.00 246.94 493.88 12.06 92.50 185.00 246.94 493.88 12.07 92.50 185.00 246.94 493.88 12.08 92.50 185.00 246.94 493.88 12.09 92.50 185.00 246.94 493.88 12.10 92.50 185.00 246.94 493.88 12.11 92.50 185.00 246.94 493.88 12.12 92.50 185.00 246.94 493.88 12.13 92.50 185.00 246.94 493.88 12.14 92.50 246.94 493.88 12.15 92.50 246.94 493.88 12.16 92.50 246.94 493.88 12.17 92.50 246.94 493.88 12.18 92.50 246.94 493.88 12.19 246.94 493.88 12.20 207.65 246.94 493.88 12.21 103.83 207.65 246.94 493.88 12.22 103.83 207.65 246.94 493.88 12.23 103.83 207.65 246.94 493.88 12.24 103.83 207.65 246.94 493.88 12.25 103.83 207.65 246.94 493.88 12.26 103.83 207.65 246.94 493.88 12.27 103.83 246.94 493.88 12.28 103.83 185.00 246.94 493.88 12.29 185.00 246.94 493.88 12.30 185.00 246.94 493.88 12.31 185.00 246.94 12.32 185.00 246.94 12.33 185.00 246.94 12.34 185.00 246.94 12.35 185.00 246.94 311.13 12.36 185.00 246.94 311.13 369.99 493.88 12.37 185.00 246.94 311.13 369.99 493.88 12.38 185.00 246.94 311.13 369.99 493.88 12.39 185.00 246.94 311.13 369.99 493.88 12.40 185.00 246.94 311.13 369.99 493.88 12.41 185.00 246.94 311.13 369.99 493.88 12.42 185.00 246.94 311.13 369.99 493.88 12.43 185.00 246.94 311.13 369.99 493.88 12.44 185.00 246.94 311.13 369.99 493.88 12.45 246.94 311.13 369.99 493.88 12.46 246.94 311.13 369.99 493.88 12.47 246.94 311.13 369.99 493.88 12.48 246.94 311.13 369.99 493.88 12.49 246.94 311.13 369.99 493.88 12.50 246.94 369.99 12.51 246.94 369.99 12.52 246.94 369.99 12.53 246.94 369.99 12.54 246.94 369.99 12.55 246.94 369.99 12.56 246.94 369.99 12.57 369.99 12.58 311.13 369.99 12.59 311.13 369.99 622.25 12.60 311.13 369.99 622.25 12.61 185.00 311.13 369.99 622.25 12.62 185.00 311.13 369.99 622.25 12.63 185.00 311.13 369.99 622.25 12.64 185.00 311.13 369.99 622.25 12.65 185.00 311.13 622.25 12.66 185.00 311.13 622.25 12.67 185.00 311.13 622.25 12.68 185.00 311.13 622.25 12.69 185.00 311.13 622.25 12.70 185.00 311.13 12.71 185.00 311.13 12.72 185.00 311.13 12.73 185.00 311.13 12.74 185.00 311.13 12.75 185.00 311.13 12.76 185.00 311.13 12.77 185.00 311.13 12.78 185.00 311.13 12.79 185.00 311.13 12.80 185.00 311.13 369.99 12.81 185.00 311.13 369.99 12.82 185.00 311.13 369.99 12.83 185.00 311.13 369.99 12.84 185.00 311.13 369.99 12.85 185.00 311.13 369.99 12.86 185.00 311.13 369.99 12.87 185.00 311.13 369.99 12.88 185.00 311.13 369.99 12.89 185.00 311.13 369.99 12.90 185.00 311.13 369.99 12.91 185.00 311.13 369.99 12.92 185.00 311.13 369.99 12.93 185.00 311.13 369.99 622.25 12.94 185.00 311.13 369.99 622.25 12.95 185.00 311.13 369.99 622.25 12.96 185.00 311.13 369.99 622.25 12.97 185.00 311.13 369.99 622.25 12.98 185.00 311.13 369.99 622.25 12.99 185.00 311.13 369.99 622.25 13.00 185.00 311.13 369.99 622.25 13.01 185.00 311.13 369.99 622.25 13.02 185.00 311.13 369.99 622.25 13.03 185.00 311.13 369.99 622.25 13.04 185.00 311.13 369.99 622.25 13.05 185.00 311.13 369.99 622.25 13.06 185.00 311.13 369.99 622.25 659.26 13.07 185.00 311.13 369.99 622.25 659.26 13.08 185.00 311.13 369.99 622.25 659.26 13.09 185.00 311.13 369.99 622.25 659.26 13.10 185.00 311.13 369.99 622.25 659.26 13.11 185.00 311.13 369.99 622.25 659.26 13.12 185.00 311.13 369.99 622.25 659.26 13.13 185.00 311.13 369.99 622.25 659.26 13.14 185.00 311.13 622.25 659.26 13.15 185.00 311.13 622.25 659.26 13.16 185.00 311.13 622.25 659.26 13.17 185.00 311.13 622.25 659.26 13.18 185.00 659.26 13.19 185.00 659.26 13.20 185.00 659.26 13.21 185.00 659.26 13.22 185.00 659.26 13.23 185.00 659.26 13.24 659.26 13.25 659.26 13.26 659.26 13.27 659.26 13.28 659.26 13.29 185.00 622.25 659.26 13.30 185.00 622.25 659.26 13.31 185.00 349.23 622.25 659.26 13.32 185.00 349.23 622.25 659.26 13.33 103.83 185.00 349.23 622.25 13.34 103.83 185.00 349.23 622.25 13.35 103.83 185.00 349.23 622.25 13.36 103.83 185.00 349.23 622.25 1046.50 13.37 103.83 349.23 622.25 1046.50 13.38 103.83 349.23 622.25 1046.50 13.39 103.83 349.23 622.25 1046.50 1864.66 13.40 103.83 349.23 622.25 1046.50 1864.66 13.41 103.83 349.23 622.25 1046.50 1864.66 13.42 103.83 349.23 622.25 1046.50 1864.66 13.43 103.83 349.23 622.25 1046.50 1864.66 13.44 103.83 349.23 622.25 1046.50 1864.66 13.45 103.83 349.23 622.25 1046.50 1864.66 13.46 103.83 349.23 622.25 1046.50 13.47 103.83 349.23 622.25 1046.50 13.48 103.83 207.65 349.23 622.25 1046.50 13.49 103.83 207.65 349.23 622.25 1046.50 13.50 103.83 207.65 349.23 622.25 1046.50 13.51 103.83 207.65 349.23 622.25 1046.50 13.52 103.83 207.65 349.23 622.25 1046.50 13.53 103.83 207.65 622.25 1046.50 13.54 103.83 207.65 622.25 1046.50 13.55 103.83 207.65 622.25 1046.50 13.56 103.83 207.65 622.25 1046.50 13.57 103.83 174.61 207.65 622.25 1046.50 13.58 103.83 174.61 207.65 466.16 622.25 1046.50 13.59 103.83 174.61 207.65 466.16 1046.50 13.60 103.83 174.61 207.65 466.16 13.61 103.83 174.61 207.65 466.16 13.62 103.83 174.61 207.65 466.16 13.63 103.83 174.61 207.65 466.16 13.64 103.83 174.61 207.65 349.23 466.16 13.65 103.83 174.61 207.65 349.23 466.16 13.66 103.83 207.65 349.23 466.16 13.67 103.83 207.65 349.23 466.16 13.68 103.83 207.65 349.23 466.16 13.69 103.83 207.65 349.23 466.16 13.70 103.83 207.65 349.23 466.16 13.71 103.83 207.65 349.23 466.16 13.72 103.83 207.65 349.23 466.16 13.73 103.83 207.65 349.23 466.16 13.74 103.83 207.65 349.23 466.16 13.75 103.83 207.65 233.08 349.23 466.16 13.76 103.83 207.65 233.08 349.23 466.16 932.33 13.77 103.83 207.65 233.08 349.23 466.16 932.33 13.78 103.83 207.65 233.08 349.23 415.30 466.16 932.33 13.79 103.83 207.65 233.08 349.23 415.30 466.16 932.33 13.80 103.83 207.65 233.08 349.23 415.30 466.16 932.33 13.81 103.83 207.65 233.08 349.23 415.30 466.16 932.33 13.82 103.83 207.65 233.08 349.23 415.30 466.16 932.33 13.83 103.83 207.65 233.08 349.23 415.30 466.16 932.33 13.84 103.83 207.65 233.08 349.23 415.30 466.16 932.33 13.85 103.83 207.65 233.08 349.23 415.30 466.16 932.33 13.86 103.83 207.65 349.23 415.30 932.33 13.87 103.83 207.65 349.23 415.30 932.33 13.88 103.83 207.65 349.23 415.30 932.33 13.89 103.83 207.65 349.23 415.30 932.33 13.90 103.83 207.65 415.30 13.91 103.83 207.65 415.30 13.92 103.83 207.65 415.30 13.93 103.83 207.65 415.30 13.94 103.83 207.65 415.30 13.95 103.83 207.65 415.30 13.96 103.83 207.65 415.30 13.97 103.83 207.65 415.30 13.98 103.83 207.65 415.30 13.99 103.83 277.18 415.30 14.00 103.83 277.18 415.30 14.01 103.83 277.18 415.30 14.02 103.83 277.18 14.03 103.83 277.18 14.04 103.83 277.18 349.23 14.05 103.83 277.18 349.23 14.06 103.83 277.18 349.23 14.07 103.83 277.18 349.23 14.08 103.83 277.18 349.23 14.09 103.83 277.18 349.23 14.10 277.18 349.23 14.11 277.18 349.23 14.12 277.18 349.23 14.13 277.18 349.23 14.14 277.18 349.23 14.15 277.18 349.23 14.16 277.18 349.23 14.17 277.18 349.23 14.18 277.18 349.23 14.19 277.18 349.23 14.20 277.18 349.23 14.21 277.18 349.23 14.22 277.18 14.23 277.18 14.24 277.18 14.25 277.18 14.26 277.18 14.27 277.18 14.28 277.18 14.29 277.18 14.30 277.18 14.31 277.18 14.32 277.18 14.33 277.18 14.34 277.18 14.35 277.18 14.36 110.00 277.18 14.37 110.00 277.18 14.38 110.00 277.18 14.39 110.00 277.18 14.40 110.00 277.18 369.99 14.41 277.18 369.99 14.42 277.18 369.99 14.43 277.18 369.99 14.44 277.18 369.99 14.45 233.08 277.18 369.99 14.46 233.08 277.18 369.99 14.47 233.08 277.18 369.99 14.48 233.08 277.18 369.99 14.49 233.08 277.18 369.99 14.50 233.08 277.18 369.99 14.51 233.08 277.18 369.99 14.52 233.08 277.18 369.99 14.53 233.08 277.18 369.99 14.54 233.08 277.18 369.99 14.55 233.08 277.18 369.99 14.56 233.08 277.18 369.99 14.57 233.08 277.18 369.99 14.58 233.08 277.18 369.99 14.59 233.08 277.18 369.99 14.60 233.08 277.18 369.99 14.61 233.08 277.18 369.99 14.62 233.08 277.18 369.99 14.63 233.08 277.18 369.99 14.64 233.08 277.18 369.99 14.65 233.08 277.18 369.99 14.66 233.08 277.18 369.99 14.67 277.18 369.99 14.68 277.18 369.99 14.69 277.18 369.99 14.70 277.18 369.99 14.71 277.18 369.99 14.72 277.18 369.99 14.73 116.54 277.18 369.99 14.74 116.54 277.18 369.99 14.75 116.54 277.18 369.99 14.76 116.54 277.18 369.99 554.37 14.77 116.54 277.18 554.37 14.78 116.54 277.18 311.13 554.37 14.79 116.54 311.13 554.37 14.80 116.54 311.13 554.37 1108.73 14.81 116.54 185.00 311.13 554.37 1108.73 14.82 116.54 185.00 311.13 554.37 1108.73 14.83 185.00 311.13 554.37 1108.73 14.84 185.00 311.13 1108.73 14.85 185.00 311.13 1108.73 14.86 185.00 311.13 1108.73 14.87 185.00 311.13 14.88 185.00 311.13 14.89 92.50 185.00 311.13 14.90 92.50 185.00 311.13 14.91 92.50 185.00 311.13 14.92 92.50 311.13 14.93 92.50 311.13 14.94 92.50 311.13 14.95 92.50 311.13 14.96 92.50 311.13 14.97 92.50 14.98 92.50 14.99 92.50 15.00 92.50 15.01 92.50 15.02 92.50 15.03 92.50 15.04 92.50 15.05 92.50 15.06 92.50 15.07 92.50 15.08 92.50 15.09 92.50 15.10 92.50 15.11 92.50 15.12 92.50 15.13 92.50 15.14 92.50 15.15 92.50 15.16 92.50 311.13 15.17 92.50 311.13 15.18 92.50 311.13 15.19 92.50 311.13 15.20 92.50 311.13 15.21 92.50 311.13 15.22 92.50 311.13 15.23 92.50 311.13 15.24 92.50 311.13 15.25 92.50 311.13 15.26 92.50 311.13 15.27 92.50 233.08 311.13 15.28 92.50 233.08 311.13 15.29 92.50 233.08 311.13 15.30 92.50 233.08 311.13 15.31 92.50 233.08 311.13 15.32 92.50 233.08 15.33 92.50 233.08 15.34 92.50 233.08 15.35 92.50 233.08 15.36 92.50 233.08 15.37 92.50 233.08 15.38 92.50 233.08 15.39 92.50 233.08 15.40 92.50 233.08 15.41 92.50 15.42 92.50 15.43 92.50 15.44 92.50 15.45 92.50 15.46 92.50 15.47 92.50 15.48 92.50 15.49 92.50 15.50 15.51 15.52 15.53 15.54 15.55 15.56 15.57 15.58 15.59 15.60 15.61 15.62 15.63 15.64 15.65 15.66 15.67 15.68 15.69 15.70 15.71 15.72 15.73 15.74 15.75 15.76 15.77 15.78 15.79 15.80 15.81 15.82 15.83 15.84 15.85 15.86 15.87 15.88 15.89 15.90 15.91 15.92 15.93 15.94 15.95 15.96 15.97 15.98 15.99 mir_eval-0.8.2/tests/data/multipitch/est07.txt000066400000000000000000002035451475740344600213060ustar00rootroot000000000000000.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.30 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.40 0.41 0.42 0.43 0.44 0.45 0.46 0.47 0.48 0.49 0.50 0.51 0.52 0.53 0.54 0.55 0.56 0.57 0.58 0.59 0.60 0.61 0.62 0.63 0.64 0.65 0.66 0.67 0.68 0.69 0.70 880.00 0.71 880.00 0.72 880.00 0.73 293.66 880.00 0.74 293.66 880.00 0.75 293.66 880.00 0.76 293.66 880.00 0.77 146.83 293.66 880.00 0.78 146.83 293.66 0.79 146.83 293.66 0.80 146.83 293.66 0.81 73.42 146.83 293.66 0.82 73.42 146.83 293.66 0.83 73.42 146.83 293.66 0.84 73.42 146.83 293.66 0.85 73.42 146.83 293.66 0.86 73.42 146.83 293.66 0.87 73.42 146.83 293.66 0.88 146.83 293.66 0.89 146.83 293.66 0.90 293.66 0.91 293.66 0.92 293.66 0.93 293.66 0.94 293.66 0.95 293.66 0.96 293.66 0.97 293.66 0.98 293.66 0.99 293.66 1.00 293.66 1.01 293.66 1.02 293.66 1.03 293.66 1.04 293.66 1.05 293.66 1.06 293.66 1.07 293.66 1.08 293.66 1.09 293.66 1.10 293.66 1.11 293.66 1.12 293.66 1.13 293.66 1.14 293.66 1.15 293.66 1.16 293.66 1.17 293.66 1.18 293.66 1.19 293.66 1.20 293.66 1.21 293.66 1.22 293.66 1.23 293.66 1.24 293.66 1.25 293.66 1.26 293.66 1.27 293.66 1.28 261.63 293.66 1.29 261.63 293.66 1.30 261.63 293.66 1.31 146.83 261.63 293.66 1.32 146.83 261.63 293.66 1.33 146.83 261.63 293.66 1.34 146.83 261.63 293.66 1.35 146.83 261.63 293.66 1.36 146.83 261.63 293.66 1.37 146.83 293.66 1.38 146.83 293.66 1.39 146.83 293.66 1.40 146.83 293.66 1.41 293.66 1.42 293.66 1.43 293.66 1.44 233.08 293.66 1.45 233.08 293.66 1.46 233.08 293.66 1.47 233.08 293.66 1.48 233.08 293.66 1.49 233.08 293.66 1.50 233.08 293.66 1.51 293.66 1.52 293.66 1.53 293.66 1.54 293.66 1.55 293.66 329.63 1.56 220.00 293.66 329.63 1.57 220.00 293.66 329.63 1.58 220.00 293.66 329.63 1.59 220.00 293.66 329.63 1.60 110.00 220.00 293.66 329.63 1.61 110.00 220.00 293.66 329.63 1.62 110.00 220.00 293.66 329.63 1.63 110.00 220.00 293.66 329.63 1.64 110.00 220.00 293.66 329.63 1.65 110.00 220.00 293.66 329.63 1.66 110.00 220.00 293.66 329.63 1.67 110.00 220.00 293.66 329.63 1.68 220.00 293.66 329.63 1.69 220.00 293.66 329.63 1.70 220.00 293.66 329.63 1.71 220.00 293.66 329.63 1.72 220.00 293.66 329.63 1.73 220.00 293.66 329.63 1.74 220.00 293.66 329.63 1.75 220.00 293.66 329.63 1.76 220.00 293.66 329.63 1.77 220.00 293.66 329.63 1.78 220.00 293.66 329.63 1.79 220.00 293.66 329.63 1.80 110.00 220.00 293.66 329.63 1.81 110.00 220.00 293.66 329.63 1.82 110.00 220.00 293.66 329.63 1.83 110.00 220.00 293.66 329.63 1.84 110.00 220.00 293.66 329.63 1.85 110.00 220.00 293.66 329.63 1.86 110.00 220.00 293.66 329.63 1.87 220.00 293.66 329.63 1.88 220.00 293.66 329.63 1.89 220.00 293.66 329.63 1.90 220.00 293.66 329.63 1.91 220.00 293.66 329.63 1.92 220.00 1.93 220.00 277.18 1.94 220.00 277.18 1.95 220.00 277.18 1.96 220.00 277.18 1.97 220.00 277.18 1.98 220.00 277.18 1.99 220.00 277.18 2.00 220.00 277.18 2.01 220.00 277.18 2.02 220.00 277.18 329.63 2.03 220.00 277.18 329.63 2.04 220.00 277.18 329.63 2.05 220.00 277.18 329.63 2.06 220.00 277.18 329.63 2.07 277.18 329.63 2.08 277.18 329.63 2.09 277.18 329.63 2.10 277.18 329.63 2.11 277.18 329.63 2.12 277.18 329.63 2.13 277.18 329.63 2.14 277.18 329.63 2.15 277.18 329.63 2.16 277.18 329.63 2.17 277.18 2.18 277.18 2.19 277.18 2.20 164.81 277.18 2.21 164.81 277.18 2.22 164.81 277.18 2.23 164.81 277.18 2.24 164.81 277.18 2.25 164.81 277.18 2.26 164.81 277.18 2.27 164.81 277.18 2.28 164.81 277.18 2.29 164.81 277.18 2.30 277.18 2.31 174.61 277.18 2.32 174.61 2.33 174.61 2.34 174.61 2.35 174.61 2.36 174.61 349.23 2.37 174.61 349.23 2.38 174.61 349.23 2.39 174.61 349.23 2.40 174.61 349.23 2.41 174.61 349.23 2.42 174.61 349.23 2.43 174.61 349.23 2.44 174.61 349.23 2.45 174.61 349.23 2.46 174.61 349.23 2.47 174.61 349.23 2.48 174.61 349.23 2.49 174.61 293.66 349.23 2.50 174.61 293.66 349.23 2.51 174.61 293.66 349.23 2.52 174.61 293.66 349.23 2.53 174.61 293.66 349.23 2.54 174.61 293.66 349.23 2.55 174.61 293.66 349.23 2.56 174.61 293.66 349.23 2.57 174.61 293.66 2.58 293.66 2.59 293.66 2.60 293.66 2.61 293.66 2.62 293.66 2.63 293.66 2.64 293.66 2.65 293.66 2.66 293.66 2.67 293.66 2.68 293.66 2.69 293.66 2.70 293.66 2.71 293.66 2.72 293.66 2.73 293.66 2.74 293.66 2.75 293.66 2.76 293.66 2.77 293.66 2.78 293.66 2.79 293.66 2.80 293.66 2.81 293.66 2.82 293.66 2.83 293.66 2.84 261.63 293.66 2.85 261.63 293.66 2.86 146.83 261.63 293.66 2.87 146.83 261.63 293.66 2.88 146.83 261.63 293.66 2.89 146.83 261.63 293.66 2.90 146.83 261.63 293.66 2.91 146.83 261.63 293.66 2.92 146.83 261.63 293.66 2.93 146.83 293.66 2.94 146.83 293.66 2.95 146.83 293.66 2.96 146.83 293.66 2.97 146.83 293.66 2.98 146.83 293.66 2.99 146.83 293.66 3.00 146.83 293.66 3.01 146.83 293.66 3.02 146.83 293.66 3.03 146.83 293.66 3.04 146.83 293.66 3.05 146.83 293.66 3.06 146.83 293.66 3.07 146.83 293.66 3.08 146.83 293.66 3.09 293.66 3.10 220.00 293.66 3.11 220.00 293.66 3.12 220.00 293.66 329.63 3.13 220.00 293.66 329.63 3.14 110.00 220.00 293.66 329.63 3.15 110.00 220.00 293.66 329.63 3.16 110.00 220.00 293.66 329.63 3.17 110.00 220.00 293.66 329.63 3.18 110.00 220.00 293.66 329.63 3.19 110.00 220.00 293.66 329.63 3.20 110.00 220.00 293.66 329.63 3.21 110.00 220.00 293.66 329.63 3.22 110.00 220.00 293.66 329.63 3.23 110.00 220.00 293.66 329.63 3.24 110.00 220.00 293.66 329.63 3.25 110.00 220.00 293.66 329.63 3.26 110.00 220.00 293.66 329.63 3.27 110.00 220.00 293.66 329.63 3.28 110.00 220.00 293.66 329.63 3.29 110.00 220.00 293.66 329.63 3.30 110.00 220.00 293.66 329.63 3.31 110.00 220.00 293.66 329.63 3.32 110.00 220.00 293.66 329.63 3.33 110.00 220.00 293.66 329.63 3.34 110.00 220.00 293.66 329.63 3.35 110.00 220.00 293.66 329.63 3.36 110.00 220.00 293.66 329.63 3.37 110.00 220.00 293.66 329.63 3.38 110.00 220.00 293.66 329.63 3.39 110.00 220.00 293.66 329.63 3.40 110.00 220.00 293.66 329.63 3.41 110.00 220.00 293.66 329.63 3.42 110.00 220.00 293.66 329.63 3.43 110.00 220.00 293.66 329.63 3.44 110.00 220.00 293.66 329.63 3.45 110.00 220.00 293.66 329.63 3.46 110.00 220.00 293.66 329.63 3.47 220.00 293.66 329.63 3.48 220.00 277.18 329.63 3.49 220.00 277.18 329.63 3.50 220.00 277.18 329.63 3.51 220.00 277.18 329.63 3.52 220.00 277.18 329.63 3.53 220.00 277.18 329.63 3.54 220.00 277.18 329.63 3.55 220.00 277.18 329.63 3.56 220.00 277.18 329.63 3.57 220.00 277.18 329.63 3.58 220.00 277.18 329.63 3.59 220.00 277.18 329.63 3.60 220.00 277.18 329.63 3.61 220.00 277.18 329.63 3.62 220.00 277.18 329.63 3.63 220.00 277.18 329.63 3.64 220.00 277.18 329.63 3.65 220.00 277.18 329.63 3.66 220.00 277.18 329.63 3.67 174.61 220.00 277.18 3.68 174.61 220.00 277.18 3.69 174.61 220.00 277.18 3.70 174.61 220.00 277.18 3.71 174.61 220.00 277.18 3.72 174.61 220.00 277.18 3.73 174.61 220.00 277.18 3.74 220.00 277.18 3.75 220.00 277.18 3.76 220.00 277.18 3.77 220.00 277.18 3.78 220.00 277.18 3.79 220.00 277.18 3.80 277.18 3.81 277.18 3.82 277.18 3.83 277.18 3.84 277.18 3.85 277.18 3.86 277.18 3.87 277.18 3.88 277.18 3.89 277.18 369.99 3.90 174.61 277.18 369.99 3.91 174.61 369.99 3.92 174.61 369.99 3.93 174.61 369.99 3.94 174.61 261.63 369.99 3.95 174.61 261.63 369.99 3.96 174.61 261.63 369.99 3.97 174.61 261.63 369.99 3.98 174.61 261.63 369.99 3.99 174.61 261.63 369.99 4.00 174.61 261.63 369.99 4.01 174.61 261.63 369.99 4.02 174.61 261.63 369.99 4.03 174.61 261.63 369.99 4.04 174.61 261.63 369.99 4.05 174.61 261.63 369.99 4.06 174.61 261.63 369.99 4.07 174.61 261.63 369.99 4.08 174.61 261.63 369.99 4.09 174.61 261.63 369.99 4.10 174.61 261.63 369.99 4.11 261.63 369.99 4.12 261.63 369.99 4.13 261.63 369.99 4.14 261.63 369.99 4.15 261.63 369.99 4.16 73.42 261.63 369.99 4.17 73.42 261.63 369.99 4.18 73.42 261.63 369.99 4.19 73.42 261.63 369.99 4.20 73.42 261.63 369.99 4.21 73.42 220.00 261.63 369.99 4.22 73.42 220.00 261.63 369.99 4.23 73.42 220.00 261.63 369.99 4.24 73.42 220.00 261.63 369.99 4.25 73.42 220.00 261.63 369.99 4.26 73.42 220.00 261.63 369.99 4.27 73.42 220.00 261.63 369.99 4.28 73.42 220.00 261.63 369.99 4.29 73.42 220.00 261.63 369.99 4.30 73.42 261.63 369.99 4.31 73.42 246.94 369.99 4.32 246.94 369.99 4.33 246.94 369.99 4.34 246.94 369.99 4.35 246.94 369.99 4.36 246.94 369.99 4.37 246.94 369.99 4.38 246.94 369.99 4.39 246.94 369.99 4.40 246.94 369.99 4.41 246.94 369.99 4.42 369.99 4.43 369.99 493.88 4.44 261.63 369.99 493.88 4.45 261.63 369.99 493.88 4.46 261.63 369.99 493.88 4.47 261.63 369.99 493.88 4.48 261.63 369.99 493.88 4.49 261.63 369.99 493.88 4.50 261.63 369.99 493.88 4.51 261.63 369.99 4.52 261.63 369.99 4.53 261.63 369.99 4.54 261.63 369.99 4.55 146.83 369.99 4.56 73.42 146.83 293.66 369.99 4.57 73.42 146.83 293.66 369.99 4.58 73.42 146.83 293.66 369.99 4.59 73.42 146.83 293.66 369.99 4.60 73.42 146.83 293.66 369.99 4.61 73.42 146.83 293.66 369.99 4.62 73.42 146.83 293.66 369.99 4.63 73.42 146.83 293.66 369.99 4.64 73.42 146.83 293.66 4.65 146.83 293.66 4.66 146.83 293.66 4.67 146.83 293.66 4.68 146.83 293.66 4.69 146.83 4.70 4.71 392.00 4.72 392.00 4.73 392.00 4.74 233.08 392.00 466.16 4.75 233.08 392.00 466.16 4.76 233.08 392.00 466.16 4.77 233.08 392.00 466.16 4.78 233.08 392.00 466.16 4.79 233.08 392.00 466.16 4.80 233.08 392.00 466.16 4.81 233.08 392.00 466.16 4.82 233.08 392.00 466.16 4.83 233.08 392.00 466.16 4.84 233.08 392.00 4.85 233.08 392.00 4.86 233.08 392.00 4.87 233.08 392.00 4.88 233.08 392.00 4.89 233.08 392.00 4.90 233.08 392.00 4.91 233.08 392.00 4.92 233.08 392.00 4.93 233.08 392.00 4.94 233.08 392.00 4.95 233.08 392.00 4.96 233.08 392.00 4.97 233.08 392.00 4.98 233.08 392.00 4.99 233.08 392.00 5.00 233.08 392.00 5.01 233.08 392.00 5.02 233.08 392.00 5.03 233.08 392.00 5.04 233.08 392.00 5.05 233.08 392.00 5.06 233.08 392.00 5.07 233.08 392.00 5.08 233.08 392.00 5.09 233.08 392.00 5.10 233.08 392.00 5.11 233.08 392.00 5.12 233.08 392.00 5.13 233.08 392.00 5.14 233.08 392.00 5.15 233.08 311.13 392.00 5.16 233.08 311.13 392.00 5.17 233.08 311.13 392.00 5.18 233.08 311.13 392.00 5.19 233.08 311.13 392.00 5.20 233.08 311.13 392.00 5.21 233.08 311.13 392.00 5.22 233.08 311.13 392.00 5.23 233.08 311.13 392.00 5.24 233.08 311.13 392.00 5.25 233.08 311.13 392.00 5.26 233.08 311.13 392.00 5.27 233.08 311.13 392.00 5.28 233.08 392.00 5.29 233.08 392.00 5.30 233.08 392.00 5.31 233.08 392.00 5.32 233.08 392.00 5.33 233.08 392.00 5.34 116.54 233.08 392.00 5.35 116.54 233.08 392.00 5.36 116.54 233.08 392.00 5.37 116.54 233.08 392.00 5.38 116.54 233.08 392.00 5.39 116.54 233.08 392.00 5.40 116.54 233.08 392.00 415.30 5.41 116.54 392.00 415.30 5.42 116.54 415.30 5.43 116.54 415.30 5.44 415.30 5.45 415.30 5.46 415.30 5.47 415.30 5.48 82.41 164.81 415.30 5.49 82.41 164.81 415.30 5.50 82.41 164.81 415.30 5.51 82.41 164.81 415.30 5.52 82.41 164.81 415.30 830.61 5.53 82.41 164.81 415.30 830.61 5.54 82.41 164.81 415.30 830.61 5.55 82.41 164.81 415.30 830.61 5.56 82.41 164.81 415.30 830.61 5.57 82.41 164.81 415.30 830.61 5.58 82.41 164.81 415.30 830.61 5.59 82.41 164.81 246.94 415.30 830.61 5.60 82.41 164.81 246.94 293.66 415.30 830.61 5.61 82.41 164.81 246.94 293.66 415.30 830.61 5.62 82.41 164.81 246.94 293.66 415.30 830.61 5.63 82.41 164.81 246.94 293.66 415.30 830.61 5.64 82.41 164.81 246.94 293.66 415.30 830.61 5.65 82.41 164.81 246.94 293.66 415.30 830.61 5.66 82.41 164.81 246.94 293.66 415.30 830.61 5.67 82.41 164.81 293.66 415.30 830.61 5.68 82.41 164.81 293.66 415.30 830.61 5.69 82.41 164.81 293.66 415.30 830.61 5.70 82.41 164.81 293.66 415.30 830.61 5.71 82.41 164.81 293.66 415.30 830.61 5.72 82.41 164.81 293.66 415.30 830.61 5.73 82.41 164.81 246.94 293.66 415.30 830.61 5.74 82.41 164.81 246.94 293.66 415.30 830.61 5.75 82.41 164.81 246.94 293.66 415.30 830.61 5.76 82.41 164.81 246.94 293.66 415.30 830.61 5.77 82.41 164.81 246.94 293.66 415.30 830.61 5.78 82.41 164.81 246.94 293.66 415.30 5.79 82.41 164.81 246.94 293.66 415.30 5.80 82.41 164.81 246.94 293.66 415.30 5.81 82.41 164.81 246.94 293.66 415.30 5.82 82.41 164.81 246.94 293.66 415.30 5.83 82.41 164.81 246.94 293.66 5.84 82.41 164.81 246.94 293.66 5.85 82.41 164.81 246.94 293.66 329.63 5.86 82.41 164.81 246.94 293.66 329.63 5.87 82.41 164.81 246.94 293.66 329.63 5.88 82.41 164.81 246.94 293.66 329.63 5.89 82.41 164.81 246.94 293.66 329.63 5.90 82.41 164.81 246.94 293.66 329.63 5.91 82.41 164.81 246.94 293.66 329.63 5.92 82.41 164.81 246.94 293.66 329.63 5.93 82.41 164.81 246.94 293.66 329.63 5.94 82.41 164.81 246.94 293.66 329.63 5.95 82.41 164.81 246.94 293.66 329.63 5.96 82.41 164.81 246.94 293.66 329.63 369.99 5.97 82.41 164.81 246.94 293.66 329.63 369.99 5.98 82.41 164.81 246.94 293.66 329.63 369.99 5.99 82.41 164.81 246.94 293.66 329.63 369.99 6.00 82.41 164.81 293.66 369.99 6.01 82.41 164.81 293.66 369.99 6.02 82.41 164.81 293.66 369.99 6.03 82.41 164.81 293.66 369.99 6.04 82.41 164.81 293.66 369.99 6.05 82.41 164.81 293.66 369.99 6.06 82.41 164.81 293.66 369.99 6.07 82.41 164.81 293.66 369.99 415.30 6.08 82.41 164.81 293.66 369.99 415.30 6.09 82.41 164.81 293.66 369.99 415.30 6.10 82.41 164.81 293.66 369.99 415.30 6.11 293.66 369.99 415.30 6.12 293.66 369.99 415.30 6.13 293.66 369.99 415.30 6.14 293.66 369.99 415.30 6.15 293.66 369.99 415.30 6.16 293.66 369.99 415.30 6.17 293.66 369.99 415.30 6.18 293.66 369.99 415.30 6.19 293.66 415.30 440.00 6.20 293.66 415.30 440.00 6.21 415.30 440.00 6.22 440.00 6.23 440.00 6.24 440.00 6.25 440.00 6.26 349.23 440.00 6.27 349.23 440.00 6.28 349.23 440.00 6.29 349.23 440.00 6.30 349.23 440.00 6.31 349.23 440.00 880.00 6.32 349.23 440.00 880.00 6.33 349.23 440.00 880.00 6.34 349.23 440.00 880.00 6.35 349.23 440.00 880.00 6.36 349.23 440.00 880.00 6.37 349.23 440.00 880.00 6.38 261.63 349.23 440.00 6.39 261.63 349.23 440.00 6.40 261.63 349.23 440.00 6.41 261.63 349.23 440.00 6.42 261.63 349.23 440.00 6.43 261.63 349.23 440.00 6.44 261.63 349.23 440.00 6.45 261.63 349.23 440.00 6.46 261.63 349.23 440.00 6.47 261.63 349.23 440.00 6.48 261.63 349.23 440.00 6.49 261.63 349.23 440.00 6.50 261.63 349.23 440.00 6.51 261.63 349.23 440.00 6.52 261.63 349.23 440.00 6.53 261.63 349.23 440.00 6.54 261.63 349.23 440.00 6.55 261.63 349.23 440.00 6.56 261.63 349.23 440.00 6.57 261.63 349.23 440.00 6.58 220.00 261.63 349.23 440.00 6.59 220.00 261.63 349.23 440.00 6.60 220.00 261.63 349.23 440.00 6.61 220.00 261.63 349.23 440.00 6.62 220.00 261.63 349.23 440.00 6.63 220.00 261.63 349.23 440.00 6.64 220.00 261.63 349.23 440.00 6.65 220.00 261.63 349.23 440.00 6.66 220.00 261.63 349.23 440.00 6.67 220.00 261.63 349.23 440.00 6.68 220.00 261.63 349.23 6.69 220.00 261.63 349.23 6.70 220.00 261.63 349.23 6.71 220.00 261.63 349.23 6.72 220.00 261.63 349.23 6.73 220.00 261.63 349.23 6.74 220.00 261.63 349.23 6.75 261.63 349.23 6.76 261.63 349.23 6.77 261.63 349.23 6.78 261.63 349.23 440.00 6.79 261.63 349.23 440.00 6.80 261.63 349.23 440.00 6.81 261.63 349.23 440.00 6.82 261.63 349.23 440.00 6.83 261.63 349.23 440.00 6.84 261.63 349.23 440.00 6.85 261.63 349.23 440.00 6.86 261.63 349.23 440.00 6.87 261.63 349.23 440.00 6.88 261.63 349.23 440.00 6.89 261.63 349.23 440.00 6.90 261.63 349.23 440.00 6.91 261.63 349.23 440.00 6.92 261.63 440.00 6.93 261.63 440.00 6.94 261.63 440.00 6.95 261.63 440.00 6.96 261.63 440.00 6.97 261.63 440.00 6.98 440.00 6.99 440.00 7.00 110.00 440.00 7.01 110.00 277.18 440.00 7.02 110.00 277.18 440.00 7.03 110.00 277.18 440.00 7.04 110.00 277.18 440.00 7.05 110.00 196.00 277.18 440.00 7.06 110.00 196.00 277.18 440.00 7.07 110.00 196.00 277.18 440.00 7.08 110.00 196.00 277.18 440.00 7.09 110.00 196.00 277.18 440.00 7.10 110.00 196.00 277.18 440.00 7.11 110.00 196.00 277.18 440.00 7.12 110.00 196.00 277.18 440.00 7.13 110.00 196.00 440.00 7.14 110.00 196.00 440.00 7.15 110.00 196.00 246.94 440.00 7.16 110.00 246.94 440.00 7.17 110.00 246.94 440.00 7.18 110.00 246.94 440.00 7.19 110.00 246.94 440.00 7.20 110.00 246.94 440.00 7.21 110.00 246.94 440.00 7.22 110.00 246.94 440.00 7.23 110.00 246.94 440.00 7.24 110.00 246.94 440.00 7.25 110.00 440.00 7.26 110.00 440.00 7.27 110.00 440.00 7.28 110.00 440.00 7.29 110.00 440.00 7.30 110.00 440.00 7.31 110.00 440.00 7.32 110.00 440.00 7.33 110.00 440.00 554.37 7.34 110.00 440.00 554.37 7.35 110.00 440.00 554.37 7.36 110.00 440.00 554.37 7.37 110.00 440.00 554.37 7.38 110.00 185.00 440.00 554.37 7.39 110.00 185.00 440.00 554.37 7.40 110.00 185.00 293.66 440.00 554.37 7.41 110.00 185.00 293.66 440.00 554.37 7.42 110.00 185.00 293.66 440.00 554.37 7.43 110.00 185.00 293.66 440.00 7.44 110.00 185.00 293.66 440.00 7.45 110.00 185.00 293.66 440.00 7.46 110.00 185.00 293.66 440.00 7.47 110.00 185.00 293.66 440.00 7.48 110.00 185.00 293.66 440.00 7.49 110.00 185.00 293.66 440.00 7.50 110.00 293.66 440.00 7.51 110.00 293.66 440.00 7.52 110.00 293.66 440.00 7.53 110.00 293.66 440.00 7.54 110.00 293.66 440.00 7.55 110.00 293.66 440.00 7.56 110.00 293.66 440.00 7.57 110.00 440.00 7.58 110.00 440.00 7.59 110.00 440.00 7.60 110.00 440.00 7.61 110.00 440.00 7.62 110.00 440.00 7.63 110.00 440.00 7.64 110.00 440.00 7.65 110.00 440.00 7.66 110.00 440.00 7.67 110.00 440.00 7.68 110.00 7.69 110.00 7.70 110.00 7.71 110.00 7.72 110.00 7.73 110.00 440.00 7.74 110.00 440.00 7.75 110.00 440.00 7.76 110.00 440.00 7.77 110.00 440.00 7.78 110.00 440.00 7.79 110.00 440.00 7.80 110.00 440.00 7.81 110.00 440.00 7.82 110.00 440.00 7.83 110.00 440.00 7.84 110.00 440.00 7.85 110.00 440.00 7.86 110.00 440.00 7.87 110.00 440.00 7.88 110.00 440.00 7.89 110.00 440.00 7.90 110.00 440.00 7.91 110.00 440.00 7.92 110.00 440.00 554.37 7.93 110.00 440.00 554.37 7.94 110.00 440.00 493.88 554.37 7.95 110.00 293.66 440.00 493.88 554.37 7.96 110.00 293.66 440.00 493.88 554.37 7.97 110.00 293.66 440.00 493.88 554.37 7.98 110.00 293.66 440.00 493.88 554.37 7.99 110.00 293.66 440.00 493.88 554.37 8.00 110.00 293.66 440.00 493.88 8.01 110.00 293.66 440.00 8.02 110.00 293.66 440.00 8.03 110.00 220.00 293.66 440.00 8.04 110.00 220.00 293.66 440.00 8.05 110.00 220.00 293.66 440.00 8.06 110.00 220.00 293.66 440.00 8.07 110.00 220.00 293.66 440.00 8.08 110.00 220.00 293.66 440.00 8.09 110.00 220.00 293.66 440.00 8.10 110.00 220.00 293.66 440.00 8.11 110.00 293.66 8.12 110.00 293.66 8.13 110.00 293.66 8.14 110.00 293.66 8.15 110.00 293.66 8.16 110.00 220.00 293.66 440.00 8.17 110.00 220.00 293.66 440.00 8.18 110.00 220.00 277.18 440.00 8.19 110.00 220.00 277.18 440.00 8.20 110.00 220.00 277.18 440.00 8.21 110.00 220.00 277.18 440.00 8.22 110.00 220.00 277.18 440.00 1864.66 8.23 110.00 220.00 277.18 440.00 1864.66 8.24 110.00 220.00 277.18 440.00 1864.66 8.25 110.00 220.00 277.18 440.00 1864.66 8.26 110.00 220.00 277.18 440.00 1864.66 8.27 110.00 220.00 277.18 440.00 1864.66 8.28 110.00 220.00 277.18 440.00 1864.66 8.29 110.00 220.00 277.18 440.00 1864.66 8.30 110.00 220.00 277.18 440.00 8.31 110.00 220.00 277.18 440.00 8.32 110.00 220.00 277.18 440.00 8.33 110.00 220.00 277.18 440.00 8.34 110.00 220.00 277.18 440.00 8.35 110.00 220.00 277.18 440.00 8.36 110.00 220.00 277.18 440.00 8.37 110.00 220.00 277.18 440.00 8.38 110.00 220.00 277.18 440.00 8.39 110.00 220.00 277.18 440.00 8.40 110.00 220.00 277.18 440.00 8.41 110.00 220.00 277.18 440.00 8.42 110.00 220.00 277.18 440.00 8.43 110.00 220.00 277.18 440.00 8.44 110.00 220.00 277.18 440.00 8.45 110.00 220.00 277.18 440.00 8.46 110.00 220.00 277.18 440.00 8.47 110.00 220.00 277.18 440.00 8.48 110.00 220.00 277.18 440.00 8.49 110.00 220.00 277.18 440.00 8.50 110.00 220.00 277.18 440.00 8.51 110.00 220.00 277.18 440.00 8.52 110.00 220.00 277.18 440.00 8.53 110.00 277.18 440.00 8.54 110.00 277.18 440.00 8.55 110.00 277.18 440.00 8.56 110.00 277.18 440.00 8.57 110.00 277.18 440.00 8.58 110.00 277.18 440.00 8.59 110.00 277.18 440.00 8.60 277.18 440.00 8.61 277.18 440.00 587.33 8.62 277.18 440.00 587.33 8.63 277.18 293.66 440.00 587.33 8.64 293.66 440.00 587.33 8.65 293.66 440.00 587.33 880.00 8.66 293.66 440.00 587.33 880.00 1046.50 8.67 293.66 440.00 587.33 880.00 1046.50 8.68 293.66 440.00 587.33 880.00 1046.50 8.69 293.66 440.00 587.33 880.00 1046.50 8.70 440.00 880.00 1046.50 8.71 146.83 440.00 880.00 1046.50 8.72 146.83 440.00 880.00 1046.50 8.73 146.83 440.00 880.00 1046.50 8.74 146.83 440.00 880.00 1046.50 8.75 146.83 440.00 880.00 1046.50 8.76 146.83 440.00 880.00 1046.50 8.77 146.83 440.00 880.00 1046.50 8.78 146.83 440.00 880.00 8.79 146.83 293.66 440.00 587.33 880.00 8.80 146.83 293.66 440.00 587.33 880.00 8.81 146.83 293.66 440.00 587.33 880.00 8.82 146.83 293.66 440.00 587.33 880.00 8.83 146.83 293.66 587.33 8.84 146.83 293.66 587.33 8.85 146.83 293.66 587.33 8.86 146.83 293.66 587.33 8.87 146.83 293.66 587.33 8.88 146.83 293.66 440.00 587.33 880.00 8.89 146.83 293.66 440.00 587.33 880.00 8.90 146.83 293.66 440.00 587.33 880.00 8.91 146.83 293.66 440.00 587.33 880.00 8.92 146.83 293.66 440.00 587.33 880.00 8.93 146.83 293.66 440.00 587.33 880.00 8.94 146.83 293.66 440.00 587.33 880.00 1760.00 8.95 146.83 293.66 440.00 587.33 880.00 1760.00 8.96 146.83 293.66 440.00 587.33 880.00 1760.00 8.97 146.83 293.66 440.00 587.33 880.00 1760.00 8.98 146.83 293.66 440.00 587.33 880.00 1760.00 8.99 146.83 293.66 440.00 587.33 880.00 1760.00 9.00 146.83 293.66 440.00 587.33 880.00 1760.00 9.01 146.83 293.66 440.00 587.33 880.00 1760.00 9.02 146.83 293.66 440.00 587.33 880.00 1760.00 9.03 146.83 293.66 587.33 9.04 146.83 293.66 587.33 9.05 146.83 293.66 587.33 9.06 146.83 293.66 587.33 9.07 146.83 293.66 587.33 9.08 146.83 293.66 587.33 9.09 146.83 293.66 587.33 9.10 146.83 293.66 587.33 9.11 146.83 293.66 587.33 9.12 146.83 293.66 523.25 587.33 9.13 146.83 293.66 523.25 587.33 9.14 146.83 293.66 523.25 587.33 9.15 146.83 293.66 523.25 587.33 9.16 146.83 293.66 523.25 587.33 9.17 146.83 293.66 523.25 587.33 9.18 146.83 293.66 523.25 587.33 9.19 146.83 293.66 523.25 587.33 9.20 146.83 293.66 523.25 587.33 9.21 146.83 293.66 523.25 587.33 9.22 146.83 293.66 523.25 587.33 9.23 146.83 293.66 523.25 587.33 9.24 146.83 293.66 587.33 9.25 146.83 293.66 587.33 9.26 146.83 293.66 587.33 9.27 146.83 293.66 587.33 9.28 146.83 293.66 587.33 9.29 146.83 293.66 587.33 9.30 146.83 293.66 587.33 9.31 146.83 293.66 587.33 9.32 146.83 293.66 587.33 9.33 146.83 293.66 587.33 9.34 146.83 293.66 587.33 9.35 146.83 293.66 587.33 9.36 146.83 293.66 440.00 587.33 9.37 146.83 293.66 440.00 9.38 146.83 293.66 440.00 1975.53 9.39 146.83 293.66 440.00 987.77 1975.53 9.40 293.66 440.00 659.26 987.77 1975.53 9.41 293.66 440.00 659.26 987.77 1975.53 9.42 220.00 293.66 440.00 659.26 987.77 1975.53 9.43 220.00 293.66 440.00 659.26 987.77 1975.53 9.44 220.00 293.66 440.00 659.26 987.77 1975.53 2093.00 9.45 220.00 293.66 440.00 659.26 987.77 1975.53 2093.00 9.46 220.00 293.66 440.00 659.26 987.77 1975.53 2093.00 9.47 220.00 293.66 440.00 659.26 987.77 1975.53 2093.00 9.48 220.00 293.66 440.00 659.26 987.77 1975.53 2093.00 9.49 220.00 293.66 440.00 659.26 987.77 1975.53 2093.00 9.50 220.00 293.66 440.00 659.26 987.77 1975.53 2093.00 9.51 220.00 293.66 440.00 659.26 987.77 1975.53 2093.00 9.52 220.00 293.66 440.00 659.26 987.77 1975.53 2093.00 9.53 220.00 293.66 440.00 659.26 987.77 1975.53 2093.00 9.54 220.00 293.66 440.00 659.26 987.77 1975.53 2093.00 9.55 220.00 293.66 440.00 659.26 987.77 1975.53 2093.00 9.56 220.00 293.66 440.00 659.26 987.77 1975.53 2093.00 9.57 220.00 293.66 440.00 659.26 987.77 1975.53 2093.00 9.58 220.00 293.66 440.00 659.26 987.77 1975.53 2093.00 9.59 220.00 293.66 440.00 659.26 987.77 1975.53 9.60 220.00 293.66 440.00 659.26 987.77 1975.53 9.61 220.00 293.66 440.00 659.26 987.77 1975.53 9.62 220.00 293.66 440.00 659.26 987.77 1975.53 9.63 220.00 293.66 440.00 659.26 9.64 220.00 293.66 440.00 659.26 9.65 220.00 293.66 440.00 659.26 9.66 220.00 293.66 440.00 659.26 9.67 220.00 293.66 440.00 659.26 9.68 220.00 293.66 440.00 659.26 9.69 220.00 293.66 440.00 659.26 9.70 220.00 293.66 440.00 659.26 9.71 220.00 293.66 440.00 659.26 9.72 220.00 293.66 440.00 659.26 9.73 220.00 293.66 440.00 659.26 9.74 220.00 293.66 440.00 659.26 9.75 220.00 293.66 440.00 659.26 9.76 220.00 293.66 440.00 587.33 659.26 9.77 220.00 293.66 440.00 587.33 659.26 9.78 220.00 293.66 440.00 587.33 659.26 9.79 293.66 440.00 587.33 659.26 9.80 293.66 440.00 554.37 587.33 659.26 9.81 293.66 440.00 554.37 587.33 659.26 9.82 293.66 440.00 554.37 587.33 659.26 9.83 293.66 440.00 554.37 659.26 9.84 293.66 440.00 554.37 659.26 9.85 293.66 440.00 554.37 659.26 880.00 9.86 293.66 440.00 554.37 659.26 880.00 1760.00 9.87 293.66 440.00 554.37 659.26 880.00 1760.00 9.88 293.66 440.00 554.37 659.26 880.00 1760.00 9.89 293.66 440.00 554.37 659.26 880.00 1760.00 9.90 293.66 440.00 554.37 659.26 880.00 1760.00 9.91 293.66 440.00 554.37 659.26 880.00 1760.00 9.92 440.00 554.37 659.26 880.00 1760.00 9.93 440.00 554.37 659.26 9.94 440.00 554.37 659.26 9.95 174.61 440.00 554.37 659.26 9.96 174.61 440.00 554.37 659.26 9.97 174.61 440.00 554.37 659.26 9.98 174.61 440.00 554.37 659.26 9.99 174.61 440.00 554.37 659.26 10.00 174.61 440.00 554.37 659.26 10.01 174.61 440.00 554.37 659.26 10.02 174.61 440.00 554.37 659.26 10.03 174.61 440.00 554.37 659.26 10.04 554.37 659.26 10.05 554.37 659.26 10.06 554.37 659.26 10.07 554.37 659.26 10.08 164.81 554.37 659.26 10.09 164.81 554.37 659.26 10.10 164.81 554.37 659.26 10.11 164.81 554.37 659.26 10.12 164.81 554.37 659.26 10.13 164.81 554.37 659.26 10.14 164.81 554.37 659.26 10.15 164.81 554.37 659.26 10.16 164.81 554.37 659.26 698.46 10.17 164.81 554.37 587.33 659.26 698.46 10.18 164.81 554.37 587.33 659.26 698.46 10.19 164.81 174.61 587.33 659.26 698.46 10.20 174.61 587.33 698.46 10.21 174.61 587.33 698.46 10.22 174.61 587.33 698.46 10.23 174.61 587.33 698.46 10.24 174.61 587.33 698.46 10.25 174.61 587.33 698.46 10.26 174.61 587.33 698.46 10.27 293.66 587.33 698.46 10.28 293.66 587.33 698.46 10.29 293.66 587.33 698.46 10.30 293.66 587.33 698.46 10.31 293.66 587.33 698.46 10.32 293.66 587.33 698.46 10.33 293.66 587.33 698.46 10.34 293.66 587.33 698.46 10.35 587.33 698.46 10.36 587.33 698.46 10.37 587.33 698.46 10.38 587.33 698.46 10.39 587.33 698.46 10.40 587.33 698.46 10.41 587.33 698.46 10.42 587.33 698.46 10.43 587.33 698.46 10.44 293.66 587.33 698.46 10.45 293.66 587.33 698.46 10.46 293.66 587.33 698.46 10.47 293.66 587.33 698.46 10.48 293.66 587.33 698.46 10.49 293.66 587.33 698.46 10.50 293.66 587.33 698.46 10.51 293.66 587.33 698.46 10.52 293.66 587.33 698.46 10.53 293.66 587.33 698.46 10.54 293.66 587.33 698.46 10.55 293.66 587.33 698.46 10.56 293.66 587.33 698.46 10.57 293.66 587.33 698.46 10.58 293.66 587.33 698.46 10.59 293.66 587.33 698.46 10.60 293.66 587.33 698.46 10.61 293.66 587.33 698.46 10.62 293.66 587.33 698.46 10.63 293.66 587.33 698.46 10.64 293.66 587.33 698.46 10.65 293.66 587.33 698.46 10.66 293.66 587.33 698.46 10.67 293.66 587.33 698.46 10.68 293.66 523.25 587.33 698.46 10.69 293.66 523.25 587.33 698.46 10.70 293.66 523.25 587.33 698.46 10.71 293.66 523.25 587.33 698.46 10.72 293.66 523.25 587.33 698.46 10.73 293.66 523.25 587.33 698.46 10.74 293.66 523.25 587.33 698.46 10.75 293.66 523.25 587.33 698.46 10.76 293.66 523.25 587.33 10.77 293.66 523.25 587.33 10.78 293.66 523.25 587.33 10.79 523.25 587.33 10.80 523.25 587.33 10.81 466.16 523.25 587.33 10.82 466.16 587.33 10.83 466.16 587.33 10.84 466.16 587.33 10.85 466.16 587.33 10.86 466.16 587.33 10.87 466.16 587.33 10.88 466.16 587.33 10.89 466.16 587.33 10.90 466.16 587.33 10.91 466.16 587.33 10.92 587.33 10.93 293.66 440.00 587.33 1046.50 10.94 293.66 440.00 587.33 1046.50 10.95 293.66 440.00 587.33 1046.50 10.96 220.00 293.66 440.00 587.33 659.26 1046.50 10.97 220.00 293.66 440.00 587.33 659.26 987.77 1046.50 1975.53 10.98 220.00 293.66 440.00 587.33 659.26 987.77 1046.50 1975.53 10.99 220.00 293.66 440.00 587.33 659.26 987.77 1046.50 1975.53 11.00 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 11.01 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 11.02 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 11.03 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 11.04 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 2093.00 11.05 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 2093.00 11.06 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 2093.00 11.07 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 2093.00 11.08 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 2093.00 11.09 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 2093.00 11.10 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 2093.00 11.11 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 2093.00 11.12 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 2093.00 11.13 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 2093.00 11.14 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 2093.00 11.15 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 2093.00 11.16 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 2093.00 11.17 196.00 220.00 293.66 440.00 587.33 659.26 987.77 1975.53 2093.00 11.18 196.00 220.00 440.00 587.33 659.26 987.77 1975.53 2093.00 11.19 196.00 220.00 440.00 587.33 659.26 987.77 1975.53 2093.00 11.20 196.00 220.00 440.00 587.33 659.26 987.77 1975.53 2093.00 11.21 196.00 220.00 440.00 587.33 659.26 987.77 1975.53 2093.00 11.22 196.00 220.00 440.00 587.33 659.26 987.77 1975.53 2093.00 11.23 196.00 220.00 440.00 587.33 659.26 987.77 1975.53 2093.00 11.24 196.00 220.00 440.00 587.33 659.26 987.77 1975.53 2093.00 11.25 196.00 220.00 440.00 587.33 659.26 987.77 1975.53 2093.00 11.26 196.00 220.00 440.00 587.33 659.26 987.77 1975.53 11.27 220.00 440.00 587.33 659.26 987.77 1975.53 11.28 220.00 440.00 587.33 659.26 987.77 1975.53 11.29 220.00 440.00 587.33 659.26 987.77 1975.53 11.30 220.00 440.00 554.37 587.33 659.26 987.77 1975.53 11.31 220.00 440.00 554.37 587.33 659.26 987.77 1975.53 11.32 440.00 554.37 659.26 987.77 1975.53 11.33 440.00 554.37 659.26 987.77 1975.53 11.34 440.00 554.37 659.26 987.77 1975.53 11.35 440.00 554.37 659.26 987.77 1975.53 11.36 440.00 554.37 659.26 1975.53 11.37 440.00 554.37 659.26 1975.53 11.38 440.00 554.37 659.26 1975.53 11.39 196.00 440.00 554.37 659.26 1975.53 11.40 196.00 440.00 554.37 659.26 11.41 196.00 440.00 554.37 659.26 11.42 196.00 440.00 554.37 659.26 11.43 196.00 440.00 554.37 659.26 11.44 196.00 440.00 554.37 659.26 11.45 196.00 440.00 554.37 659.26 11.46 196.00 440.00 554.37 659.26 11.47 440.00 554.37 659.26 11.48 440.00 554.37 659.26 11.49 440.00 554.37 659.26 11.50 554.37 659.26 11.51 554.37 659.26 1318.51 11.52 554.37 659.26 1318.51 11.53 554.37 659.26 1318.51 11.54 554.37 659.26 1318.51 11.55 554.37 659.26 1318.51 11.56 554.37 659.26 1318.51 11.57 554.37 659.26 1318.51 11.58 554.37 659.26 1318.51 11.59 554.37 659.26 11.60 554.37 659.26 11.61 554.37 659.26 11.62 554.37 659.26 11.63 164.81 554.37 659.26 11.64 164.81 554.37 659.26 11.65 164.81 329.63 554.37 659.26 11.66 164.81 329.63 554.37 659.26 11.67 164.81 329.63 554.37 659.26 11.68 164.81 329.63 554.37 659.26 11.69 164.81 329.63 554.37 659.26 11.70 164.81 329.63 554.37 659.26 11.71 164.81 329.63 554.37 659.26 739.99 11.72 164.81 329.63 554.37 659.26 739.99 11.73 164.81 554.37 659.26 739.99 11.74 164.81 440.00 554.37 739.99 11.75 164.81 440.00 554.37 739.99 11.76 164.81 440.00 523.25 739.99 11.77 440.00 523.25 739.99 11.78 440.00 523.25 739.99 11.79 440.00 523.25 739.99 11.80 174.61 440.00 523.25 739.99 11.81 174.61 440.00 523.25 739.99 11.82 174.61 440.00 523.25 739.99 11.83 174.61 440.00 523.25 739.99 11.84 174.61 440.00 523.25 739.99 880.00 1567.98 11.85 174.61 440.00 523.25 739.99 880.00 1567.98 11.86 174.61 440.00 523.25 739.99 880.00 1567.98 11.87 174.61 440.00 523.25 739.99 880.00 1567.98 11.88 174.61 440.00 523.25 739.99 880.00 1567.98 11.89 174.61 440.00 523.25 739.99 880.00 1567.98 11.90 174.61 440.00 523.25 739.99 880.00 1567.98 11.91 174.61 440.00 523.25 739.99 1479.98 1567.98 11.92 174.61 440.00 523.25 739.99 1479.98 1567.98 11.93 174.61 440.00 523.25 739.99 1479.98 11.94 174.61 440.00 523.25 739.99 1479.98 11.95 174.61 440.00 523.25 739.99 1479.98 11.96 440.00 523.25 739.99 1479.98 11.97 440.00 523.25 739.99 1479.98 11.98 440.00 523.25 739.99 1479.98 11.99 440.00 523.25 739.99 1479.98 12.00 440.00 523.25 739.99 1479.98 12.01 174.61 440.00 523.25 739.99 1479.98 12.02 174.61 440.00 523.25 739.99 1479.98 12.03 174.61 440.00 523.25 739.99 1479.98 12.04 174.61 440.00 523.25 739.99 1479.98 12.05 174.61 440.00 523.25 739.99 1479.98 12.06 174.61 523.25 739.99 12.07 174.61 523.25 739.99 12.08 523.25 739.99 12.09 523.25 739.99 12.10 523.25 739.99 12.11 523.25 739.99 12.12 164.81 523.25 739.99 12.13 164.81 523.25 739.99 12.14 164.81 739.99 12.15 164.81 493.88 739.99 12.16 164.81 493.88 739.99 12.17 164.81 493.88 739.99 12.18 164.81 493.88 739.99 12.19 164.81 493.88 739.99 12.20 164.81 493.88 739.99 12.21 164.81 493.88 739.99 12.22 164.81 493.88 739.99 12.23 164.81 493.88 739.99 12.24 164.81 493.88 523.25 739.99 1479.98 12.25 164.81 493.88 523.25 739.99 1479.98 12.26 164.81 493.88 523.25 739.99 1479.98 12.27 164.81 493.88 523.25 739.99 1479.98 12.28 164.81 493.88 523.25 739.99 1479.98 12.29 493.88 523.25 739.99 1479.98 12.30 493.88 523.25 739.99 1479.98 12.31 493.88 523.25 739.99 1479.98 12.32 493.88 523.25 739.99 1479.98 12.33 493.88 523.25 739.99 1479.98 12.34 493.88 523.25 739.99 1479.98 12.35 440.00 493.88 523.25 739.99 12.36 440.00 493.88 523.25 739.99 12.37 196.00 440.00 493.88 523.25 739.99 12.38 196.00 440.00 493.88 523.25 739.99 12.39 196.00 440.00 493.88 523.25 739.99 12.40 196.00 293.66 440.00 493.88 523.25 587.33 739.99 12.41 196.00 293.66 440.00 493.88 523.25 587.33 739.99 12.42 196.00 293.66 440.00 493.88 523.25 587.33 739.99 12.43 196.00 293.66 440.00 493.88 523.25 587.33 739.99 12.44 196.00 293.66 440.00 493.88 523.25 587.33 739.99 12.45 146.83 196.00 293.66 440.00 523.25 587.33 739.99 12.46 146.83 196.00 293.66 523.25 587.33 739.99 12.47 146.83 196.00 739.99 12.48 146.83 196.00 466.16 739.99 12.49 146.83 196.00 466.16 739.99 12.50 146.83 196.00 466.16 739.99 12.51 146.83 196.00 466.16 739.99 12.52 146.83 196.00 466.16 739.99 12.53 146.83 196.00 466.16 739.99 783.99 12.54 196.00 466.16 739.99 783.99 12.55 196.00 739.99 783.99 12.56 196.00 739.99 783.99 12.57 196.00 739.99 783.99 12.58 196.00 739.99 783.99 12.59 196.00 739.99 783.99 12.60 196.00 739.99 783.99 12.61 196.00 739.99 783.99 12.62 196.00 466.16 739.99 783.99 12.63 196.00 466.16 739.99 783.99 12.64 196.00 466.16 783.99 12.65 196.00 466.16 783.99 12.66 196.00 466.16 783.99 12.67 196.00 466.16 783.99 12.68 196.00 466.16 783.99 12.69 196.00 466.16 783.99 12.70 196.00 466.16 783.99 12.71 196.00 466.16 783.99 12.72 196.00 466.16 783.99 12.73 196.00 466.16 783.99 12.74 196.00 466.16 783.99 12.75 196.00 466.16 783.99 12.76 196.00 466.16 622.25 783.99 12.77 196.00 466.16 622.25 783.99 12.78 196.00 466.16 622.25 783.99 12.79 196.00 466.16 622.25 783.99 12.80 196.00 466.16 622.25 783.99 12.81 196.00 466.16 622.25 783.99 12.82 196.00 466.16 622.25 783.99 12.83 196.00 466.16 622.25 783.99 12.84 196.00 466.16 622.25 783.99 12.85 196.00 466.16 622.25 783.99 12.86 196.00 466.16 622.25 783.99 12.87 196.00 466.16 622.25 783.99 12.88 196.00 466.16 622.25 783.99 12.89 196.00 466.16 622.25 783.99 12.90 196.00 466.16 622.25 783.99 12.91 196.00 466.16 622.25 783.99 12.92 196.00 466.16 622.25 783.99 12.93 196.00 392.00 466.16 622.25 783.99 12.94 196.00 392.00 466.16 622.25 783.99 12.95 196.00 392.00 466.16 622.25 783.99 12.96 196.00 392.00 466.16 622.25 783.99 12.97 196.00 392.00 466.16 622.25 783.99 12.98 196.00 392.00 466.16 622.25 783.99 12.99 196.00 392.00 466.16 622.25 783.99 13.00 196.00 466.16 622.25 783.99 13.01 196.00 466.16 622.25 783.99 13.02 196.00 466.16 622.25 783.99 13.03 196.00 466.16 622.25 783.99 13.04 196.00 466.16 622.25 783.99 13.05 196.00 466.16 622.25 783.99 13.06 196.00 466.16 622.25 783.99 13.07 196.00 466.16 622.25 783.99 13.08 196.00 466.16 622.25 783.99 13.09 196.00 466.16 622.25 783.99 932.33 13.10 196.00 466.16 622.25 783.99 932.33 13.11 196.00 466.16 622.25 783.99 932.33 13.12 196.00 466.16 622.25 783.99 932.33 13.13 196.00 466.16 622.25 783.99 932.33 13.14 196.00 466.16 622.25 783.99 932.33 13.15 196.00 466.16 622.25 783.99 932.33 13.16 196.00 466.16 622.25 783.99 932.33 13.17 196.00 466.16 622.25 783.99 13.18 196.00 466.16 622.25 783.99 13.19 196.00 466.16 783.99 13.20 196.00 466.16 783.99 830.61 13.21 196.00 466.16 783.99 830.61 13.22 196.00 466.16 783.99 830.61 13.23 466.16 830.61 13.24 466.16 830.61 13.25 466.16 830.61 13.26 466.16 830.61 13.27 466.16 830.61 13.28 830.61 13.29 830.61 13.30 196.00 587.33 830.61 13.31 196.00 587.33 830.61 13.32 196.00 587.33 830.61 13.33 196.00 587.33 830.61 13.34 164.81 196.00 587.33 830.61 13.35 164.81 196.00 587.33 830.61 13.36 164.81 196.00 493.88 587.33 830.61 13.37 164.81 196.00 493.88 587.33 830.61 13.38 164.81 196.00 493.88 587.33 830.61 13.39 164.81 493.88 587.33 830.61 13.40 164.81 493.88 587.33 830.61 13.41 164.81 493.88 587.33 830.61 13.42 164.81 493.88 587.33 830.61 13.43 164.81 493.88 587.33 830.61 13.44 164.81 493.88 587.33 830.61 13.45 164.81 493.88 587.33 830.61 13.46 164.81 493.88 587.33 830.61 13.47 164.81 493.88 587.33 830.61 13.48 164.81 493.88 587.33 830.61 13.49 164.81 493.88 587.33 830.61 13.50 164.81 493.88 587.33 830.61 13.51 164.81 493.88 587.33 830.61 13.52 164.81 493.88 587.33 830.61 13.53 164.81 493.88 587.33 830.61 13.54 164.81 493.88 587.33 830.61 13.55 164.81 493.88 587.33 830.61 13.56 164.81 493.88 587.33 830.61 13.57 164.81 493.88 587.33 830.61 13.58 164.81 493.88 587.33 830.61 13.59 164.81 493.88 587.33 830.61 13.60 164.81 493.88 587.33 830.61 13.61 164.81 493.88 587.33 830.61 13.62 164.81 493.88 587.33 830.61 13.63 164.81 493.88 587.33 830.61 13.64 164.81 493.88 587.33 830.61 13.65 164.81 493.88 587.33 830.61 13.66 164.81 493.88 587.33 830.61 13.67 164.81 493.88 587.33 830.61 13.68 164.81 493.88 587.33 830.61 13.69 164.81 493.88 587.33 830.61 13.70 164.81 329.63 493.88 587.33 659.26 830.61 13.71 164.81 329.63 493.88 587.33 659.26 13.72 164.81 329.63 493.88 587.33 659.26 13.73 164.81 329.63 493.88 587.33 659.26 13.74 164.81 329.63 493.88 587.33 659.26 13.75 164.81 329.63 493.88 587.33 659.26 13.76 164.81 329.63 493.88 587.33 659.26 13.77 164.81 329.63 493.88 587.33 659.26 13.78 164.81 329.63 493.88 587.33 659.26 13.79 164.81 329.63 493.88 587.33 659.26 13.80 164.81 329.63 493.88 587.33 659.26 13.81 164.81 329.63 493.88 587.33 659.26 13.82 164.81 329.63 493.88 587.33 659.26 739.99 13.83 164.81 329.63 493.88 587.33 659.26 739.99 13.84 164.81 329.63 493.88 587.33 659.26 739.99 13.85 164.81 329.63 493.88 587.33 659.26 739.99 13.86 164.81 329.63 493.88 587.33 659.26 739.99 13.87 164.81 329.63 493.88 587.33 659.26 739.99 13.88 164.81 329.63 493.88 587.33 659.26 739.99 13.89 164.81 329.63 493.88 587.33 659.26 739.99 13.90 164.81 329.63 493.88 587.33 739.99 13.91 164.81 329.63 493.88 587.33 739.99 13.92 164.81 329.63 493.88 587.33 739.99 13.93 164.81 329.63 493.88 587.33 739.99 830.61 13.94 164.81 493.88 587.33 739.99 830.61 13.95 164.81 493.88 587.33 739.99 830.61 13.96 164.81 493.88 587.33 739.99 830.61 13.97 164.81 493.88 587.33 739.99 830.61 13.98 164.81 493.88 587.33 739.99 830.61 13.99 164.81 493.88 587.33 739.99 830.61 14.00 164.81 493.88 587.33 739.99 830.61 14.01 164.81 493.88 587.33 739.99 830.61 14.02 164.81 493.88 587.33 739.99 830.61 14.03 164.81 493.88 587.33 739.99 830.61 14.04 164.81 493.88 587.33 739.99 830.61 14.05 164.81 493.88 587.33 739.99 830.61 14.06 164.81 493.88 587.33 739.99 830.61 14.07 164.81 493.88 587.33 739.99 830.61 14.08 164.81 440.00 587.33 739.99 830.61 14.09 164.81 440.00 739.99 830.61 14.10 110.00 164.81 440.00 739.99 14.11 110.00 164.81 440.00 14.12 110.00 164.81 440.00 14.13 110.00 164.81 440.00 14.14 110.00 164.81 440.00 14.15 110.00 164.81 440.00 14.16 110.00 164.81 440.00 14.17 110.00 164.81 440.00 1396.91 14.18 110.00 164.81 440.00 698.46 880.00 1396.91 1661.22 14.19 110.00 164.81 440.00 698.46 880.00 1396.91 1661.22 14.20 110.00 164.81 440.00 698.46 880.00 1396.91 1661.22 14.21 110.00 164.81 440.00 698.46 880.00 1396.91 1661.22 14.22 110.00 164.81 440.00 698.46 880.00 1396.91 1661.22 14.23 110.00 164.81 440.00 698.46 880.00 1396.91 1661.22 14.24 110.00 164.81 440.00 698.46 880.00 1396.91 1661.22 14.25 110.00 164.81 440.00 698.46 880.00 1396.91 1661.22 14.26 110.00 164.81 440.00 698.46 880.00 1396.91 1661.22 14.27 110.00 164.81 440.00 698.46 880.00 1396.91 14.28 110.00 164.81 440.00 698.46 880.00 1396.91 14.29 110.00 164.81 440.00 698.46 880.00 1396.91 14.30 110.00 164.81 440.00 698.46 880.00 1396.91 14.31 110.00 164.81 440.00 523.25 698.46 880.00 1396.91 14.32 110.00 164.81 440.00 523.25 698.46 880.00 1396.91 14.33 110.00 164.81 440.00 523.25 698.46 880.00 1396.91 14.34 110.00 164.81 440.00 523.25 698.46 880.00 1396.91 14.35 110.00 164.81 440.00 523.25 698.46 880.00 1396.91 14.36 110.00 164.81 440.00 523.25 698.46 880.00 1396.91 14.37 110.00 164.81 440.00 523.25 698.46 880.00 1396.91 14.38 164.81 440.00 523.25 698.46 880.00 1396.91 14.39 164.81 440.00 523.25 698.46 880.00 1396.91 14.40 164.81 440.00 523.25 698.46 880.00 1396.91 14.41 164.81 440.00 523.25 698.46 880.00 1396.91 14.42 164.81 440.00 523.25 698.46 880.00 1396.91 14.43 164.81 440.00 523.25 698.46 880.00 1396.91 14.44 164.81 440.00 523.25 698.46 880.00 1396.91 14.45 164.81 440.00 523.25 698.46 880.00 1396.91 14.46 164.81 440.00 523.25 698.46 880.00 1396.91 14.47 440.00 523.25 698.46 880.00 1396.91 14.48 440.00 523.25 698.46 880.00 1396.91 14.49 440.00 523.25 698.46 880.00 14.50 440.00 523.25 698.46 880.00 14.51 440.00 523.25 698.46 880.00 14.52 220.00 440.00 523.25 698.46 880.00 14.53 220.00 440.00 523.25 698.46 880.00 14.54 220.00 440.00 523.25 698.46 880.00 14.55 220.00 440.00 523.25 698.46 880.00 14.56 220.00 440.00 523.25 698.46 880.00 14.57 220.00 440.00 523.25 698.46 880.00 14.58 220.00 440.00 523.25 698.46 880.00 14.59 220.00 440.00 523.25 698.46 880.00 14.60 220.00 440.00 523.25 698.46 880.00 14.61 220.00 440.00 523.25 698.46 880.00 14.62 220.00 440.00 523.25 698.46 880.00 14.63 220.00 440.00 523.25 698.46 880.00 14.64 220.00 440.00 523.25 698.46 880.00 14.65 440.00 523.25 698.46 880.00 14.66 440.00 523.25 698.46 880.00 14.67 440.00 523.25 698.46 880.00 14.68 440.00 523.25 698.46 880.00 14.69 440.00 523.25 698.46 880.00 14.70 440.00 523.25 698.46 880.00 14.71 440.00 523.25 880.00 14.72 440.00 523.25 880.00 14.73 440.00 523.25 880.00 14.74 440.00 523.25 880.00 14.75 440.00 523.25 880.00 14.76 440.00 523.25 880.00 14.77 440.00 523.25 880.00 14.78 440.00 523.25 880.00 14.79 440.00 523.25 659.26 880.00 14.80 440.00 523.25 659.26 880.00 14.81 440.00 523.25 659.26 880.00 14.82 523.25 659.26 880.00 14.83 523.25 659.26 880.00 14.84 659.26 880.00 1760.00 14.85 659.26 880.00 1760.00 14.86 659.26 880.00 1760.00 14.87 554.37 880.00 1760.00 14.88 554.37 880.00 1760.00 14.89 554.37 880.00 1760.00 14.90 554.37 880.00 1760.00 14.91 554.37 880.00 1760.00 14.92 554.37 880.00 1760.00 14.93 554.37 880.00 14.94 554.37 880.00 14.95 554.37 880.00 14.96 554.37 880.00 14.97 554.37 880.00 14.98 554.37 880.00 14.99 554.37 880.00 15.00 554.37 880.00 15.01 523.25 554.37 880.00 15.02 523.25 554.37 880.00 15.03 440.00 523.25 554.37 880.00 15.04 440.00 523.25 554.37 880.00 15.05 440.00 523.25 554.37 880.00 15.06 440.00 523.25 554.37 880.00 15.07 440.00 523.25 554.37 880.00 15.08 440.00 523.25 554.37 880.00 15.09 440.00 554.37 880.00 15.10 440.00 554.37 880.00 15.11 440.00 554.37 880.00 15.12 440.00 554.37 880.00 15.13 440.00 880.00 15.14 440.00 880.00 15.15 440.00 880.00 15.16 440.00 880.00 15.17 440.00 880.00 15.18 440.00 880.00 15.19 440.00 880.00 15.20 440.00 880.00 15.21 440.00 880.00 15.22 349.23 440.00 587.33 880.00 1046.50 15.23 349.23 440.00 587.33 880.00 1046.50 15.24 349.23 440.00 587.33 880.00 1046.50 15.25 349.23 440.00 587.33 880.00 1046.50 15.26 349.23 440.00 587.33 880.00 1046.50 15.27 349.23 440.00 587.33 880.00 1046.50 15.28 349.23 440.00 587.33 880.00 1046.50 15.29 349.23 440.00 587.33 880.00 1046.50 15.30 349.23 440.00 587.33 880.00 1046.50 15.31 349.23 440.00 587.33 880.00 15.32 349.23 440.00 587.33 880.00 15.33 440.00 587.33 880.00 15.34 440.00 587.33 880.00 15.35 440.00 587.33 880.00 15.36 220.00 329.63 440.00 587.33 880.00 15.37 220.00 329.63 440.00 587.33 880.00 15.38 220.00 329.63 440.00 587.33 880.00 15.39 220.00 329.63 440.00 587.33 880.00 15.40 220.00 329.63 440.00 587.33 880.00 15.41 220.00 329.63 440.00 587.33 880.00 15.42 220.00 329.63 440.00 587.33 880.00 15.43 220.00 329.63 440.00 587.33 880.00 15.44 220.00 329.63 440.00 587.33 880.00 15.45 440.00 587.33 880.00 15.46 440.00 587.33 880.00 15.47 440.00 587.33 880.00 15.48 293.66 440.00 587.33 880.00 15.49 293.66 440.00 587.33 880.00 15.50 293.66 440.00 587.33 880.00 15.51 293.66 587.33 880.00 15.52 293.66 587.33 880.00 15.53 220.00 293.66 587.33 880.00 15.54 220.00 293.66 587.33 880.00 15.55 220.00 293.66 587.33 880.00 15.56 220.00 293.66 440.00 587.33 880.00 15.57 220.00 293.66 440.00 587.33 880.00 15.58 220.00 293.66 440.00 587.33 880.00 15.59 220.00 293.66 440.00 587.33 880.00 15.60 220.00 293.66 440.00 587.33 880.00 15.61 220.00 293.66 440.00 587.33 880.00 15.62 220.00 293.66 329.63 440.00 587.33 880.00 15.63 220.00 329.63 440.00 587.33 880.00 15.64 220.00 329.63 440.00 587.33 880.00 15.65 220.00 329.63 440.00 587.33 880.00 15.66 220.00 329.63 440.00 587.33 880.00 15.67 220.00 329.63 440.00 587.33 880.00 15.68 220.00 329.63 440.00 587.33 880.00 15.69 220.00 329.63 440.00 587.33 880.00 15.70 220.00 329.63 440.00 587.33 880.00 15.71 220.00 329.63 440.00 587.33 880.00 15.72 220.00 329.63 440.00 587.33 880.00 15.73 220.00 329.63 440.00 587.33 880.00 15.74 220.00 329.63 440.00 587.33 880.00 15.75 220.00 329.63 440.00 587.33 880.00 15.76 220.00 329.63 440.00 587.33 880.00 15.77 220.00 329.63 440.00 587.33 880.00 15.78 220.00 329.63 440.00 587.33 880.00 15.79 220.00 329.63 440.00 587.33 880.00 15.80 220.00 329.63 440.00 587.33 880.00 15.81 220.00 329.63 440.00 587.33 880.00 15.82 220.00 329.63 440.00 587.33 880.00 15.83 220.00 329.63 440.00 587.33 880.00 15.84 220.00 329.63 440.00 587.33 880.00 15.85 220.00 329.63 440.00 587.33 880.00 15.86 220.00 329.63 440.00 587.33 880.00 15.87 220.00 329.63 440.00 587.33 880.00 15.88 220.00 329.63 440.00 587.33 880.00 15.89 220.00 329.63 440.00 587.33 880.00 15.90 220.00 329.63 440.00 587.33 880.00 15.91 220.00 329.63 440.00 587.33 880.00 15.92 220.00 329.63 440.00 587.33 880.00 15.93 220.00 329.63 440.00 587.33 880.00 15.94 220.00 329.63 440.00 587.33 880.00 15.95 220.00 329.63 440.00 587.33 880.00 15.96 220.00 329.63 440.00 587.33 880.00 15.97 220.00 329.63 440.00 587.33 880.00 15.98 220.00 329.63 440.00 587.33 880.00 15.99 220.00 329.63 440.00 587.33 880.00 16.00 220.00 329.63 440.00 587.33 880.00 16.01 220.00 329.63 440.00 587.33 880.00 16.02 220.00 329.63 440.00 587.33 880.00 16.03 220.00 329.63 440.00 587.33 880.00 16.04 220.00 329.63 440.00 587.33 880.00 16.05 220.00 329.63 440.00 587.33 880.00 16.06 220.00 329.63 440.00 587.33 880.00 16.07 220.00 329.63 440.00 554.37 587.33 880.00 16.08 220.00 329.63 440.00 554.37 587.33 880.00 16.09 220.00 329.63 440.00 554.37 587.33 880.00 16.10 220.00 329.63 440.00 554.37 587.33 880.00 16.11 220.00 329.63 440.00 554.37 587.33 880.00 16.12 220.00 329.63 440.00 554.37 587.33 880.00 16.13 220.00 329.63 440.00 554.37 587.33 880.00 16.14 220.00 329.63 440.00 554.37 587.33 880.00 16.15 220.00 329.63 440.00 554.37 587.33 880.00 16.16 220.00 329.63 440.00 554.37 880.00 16.17 220.00 329.63 440.00 554.37 880.00 16.18 220.00 329.63 440.00 554.37 880.00 16.19 220.00 329.63 440.00 554.37 880.00 16.20 220.00 329.63 440.00 554.37 880.00 16.21 220.00 329.63 440.00 554.37 880.00 16.22 220.00 329.63 440.00 554.37 880.00 16.23 220.00 329.63 440.00 554.37 880.00 16.24 220.00 329.63 440.00 554.37 880.00 16.25 220.00 329.63 440.00 554.37 880.00 16.26 220.00 329.63 440.00 554.37 880.00 16.27 220.00 329.63 440.00 554.37 880.00 16.28 220.00 329.63 440.00 554.37 880.00 16.29 220.00 329.63 440.00 554.37 880.00 16.30 220.00 329.63 440.00 554.37 880.00 16.31 220.00 329.63 440.00 554.37 880.00 16.32 220.00 329.63 440.00 554.37 880.00 16.33 220.00 329.63 440.00 554.37 880.00 16.34 220.00 329.63 440.00 554.37 880.00 16.35 220.00 329.63 440.00 554.37 880.00 16.36 220.00 329.63 440.00 554.37 880.00 16.37 220.00 329.63 440.00 554.37 880.00 16.38 220.00 329.63 440.00 554.37 880.00 16.39 220.00 329.63 440.00 554.37 880.00 16.40 220.00 329.63 440.00 554.37 880.00 16.41 220.00 329.63 440.00 554.37 880.00 16.42 220.00 329.63 440.00 554.37 880.00 16.43 220.00 329.63 440.00 554.37 880.00 16.44 220.00 329.63 440.00 554.37 880.00 16.45 220.00 329.63 440.00 554.37 880.00 16.46 220.00 329.63 440.00 554.37 880.00 16.47 220.00 329.63 440.00 554.37 880.00 16.48 220.00 329.63 440.00 554.37 880.00 16.49 220.00 329.63 440.00 554.37 880.00 16.50 220.00 329.63 440.00 554.37 880.00 16.51 220.00 329.63 440.00 554.37 880.00 16.52 220.00 329.63 440.00 554.37 880.00 16.53 220.00 329.63 440.00 554.37 880.00 16.54 220.00 329.63 440.00 554.37 587.33 880.00 16.55 220.00 329.63 440.00 554.37 587.33 880.00 16.56 220.00 329.63 440.00 554.37 587.33 880.00 16.57 220.00 329.63 440.00 554.37 587.33 880.00 16.58 220.00 293.66 329.63 440.00 554.37 587.33 880.00 16.59 220.00 293.66 329.63 440.00 554.37 587.33 880.00 16.60 220.00 293.66 329.63 440.00 554.37 587.33 880.00 16.61 220.00 293.66 329.63 440.00 554.37 587.33 16.62 220.00 293.66 329.63 440.00 554.37 587.33 16.63 220.00 293.66 329.63 440.00 554.37 587.33 16.64 220.00 293.66 329.63 440.00 554.37 587.33 16.65 220.00 293.66 329.63 440.00 554.37 587.33 16.66 220.00 293.66 329.63 554.37 587.33 16.67 220.00 293.66 329.63 587.33 16.68 220.00 293.66 329.63 587.33 16.69 220.00 293.66 329.63 587.33 16.70 220.00 293.66 329.63 587.33 16.71 220.00 293.66 329.63 587.33 16.72 220.00 293.66 329.63 587.33 16.73 220.00 293.66 329.63 587.33 16.74 220.00 293.66 329.63 587.33 16.75 220.00 293.66 329.63 587.33 16.76 293.66 329.63 587.33 16.77 293.66 329.63 587.33 16.78 293.66 329.63 587.33 16.79 293.66 587.33 16.80 293.66 587.33 16.81 293.66 587.33 16.82 293.66 587.33 16.83 293.66 587.33 16.84 293.66 587.33 16.85 293.66 587.33 16.86 293.66 587.33 16.87 293.66 587.33 16.88 293.66 587.33 16.89 293.66 440.00 587.33 16.90 293.66 440.00 587.33 16.91 293.66 440.00 587.33 16.92 293.66 440.00 587.33 16.93 293.66 440.00 587.33 16.94 293.66 440.00 587.33 16.95 220.00 293.66 440.00 587.33 16.96 220.00 293.66 440.00 587.33 16.97 220.00 293.66 440.00 587.33 16.98 220.00 293.66 440.00 587.33 16.99 220.00 293.66 587.33 17.00 220.00 293.66 587.33 17.01 220.00 293.66 587.33 17.02 220.00 293.66 587.33 17.03 220.00 293.66 587.33 17.04 220.00 293.66 587.33 17.05 220.00 293.66 587.33 17.06 293.66 587.33 17.07 293.66 587.33 17.08 293.66 587.33 17.09 293.66 587.33 17.10 293.66 587.33 17.11 293.66 587.33 17.12 293.66 587.33 17.13 293.66 587.33 17.14 293.66 587.33 17.15 293.66 587.33 17.16 293.66 587.33 17.17 293.66 587.33 17.18 293.66 523.25 587.33 17.19 293.66 523.25 587.33 17.20 293.66 523.25 587.33 17.21 293.66 523.25 587.33 17.22 293.66 523.25 587.33 17.23 293.66 523.25 587.33 17.24 293.66 523.25 587.33 17.25 293.66 523.25 587.33 17.26 293.66 523.25 587.33 17.27 293.66 523.25 587.33 17.28 293.66 523.25 17.29 293.66 523.25 17.30 293.66 523.25 17.31 293.66 523.25 17.32 523.25 17.33 466.16 523.25 17.34 466.16 523.25 17.35 466.16 523.25 17.36 466.16 523.25 17.37 466.16 523.25 17.38 466.16 523.25 17.39 466.16 523.25 17.40 466.16 523.25 17.41 466.16 523.25 17.42 466.16 523.25 17.43 466.16 523.25 17.44 466.16 523.25 17.45 440.00 466.16 523.25 17.46 440.00 466.16 17.47 440.00 466.16 17.48 440.00 17.49 440.00 17.50 440.00 17.51 440.00 17.52 440.00 17.53 440.00 17.54 440.00 17.55 440.00 17.56 440.00 17.57 440.00 17.58 440.00 17.59 440.00 17.60 440.00 17.61 440.00 17.62 440.00 17.63 440.00 17.64 440.00 17.65 440.00 17.66 440.00 17.67 440.00 17.68 440.00 17.69 440.00 17.70 440.00 17.71 440.00 17.72 440.00 17.73 440.00 17.74 440.00 17.75 440.00 17.76 440.00 17.77 440.00 17.78 440.00 17.79 440.00 17.80 440.00 17.81 440.00 17.82 440.00 17.83 138.59 440.00 17.84 138.59 440.00 17.85 138.59 440.00 17.86 138.59 440.00 17.87 138.59 440.00 17.88 138.59 440.00 17.89 138.59 440.00 17.90 138.59 440.00 17.91 138.59 440.00 17.92 138.59 440.00 17.93 138.59 440.00 17.94 138.59 440.00 17.95 138.59 440.00 17.96 138.59 440.00 17.97 440.00 17.98 440.00 17.99 440.00 18.00 440.00 18.01 440.00 18.02 440.00 18.03 440.00 18.04 440.00 18.05 440.00 18.06 440.00 18.07 110.00 440.00 18.08 110.00 440.00 18.09 110.00 138.59 440.00 18.10 110.00 138.59 440.00 18.11 110.00 138.59 440.00 18.12 110.00 138.59 440.00 18.13 110.00 138.59 440.00 18.14 110.00 138.59 440.00 18.15 110.00 138.59 440.00 18.16 110.00 138.59 440.00 18.17 110.00 138.59 440.00 18.18 110.00 138.59 440.00 18.19 110.00 138.59 440.00 18.20 110.00 138.59 440.00 18.21 110.00 138.59 440.00 18.22 110.00 440.00 18.23 110.00 698.46 18.24 110.00 698.46 18.25 698.46 18.26 698.46 18.27 698.46 18.28 698.46 18.29 698.46 18.30 698.46 18.31 698.46 18.32 698.46 18.33 698.46 18.34 698.46 18.35 698.46 18.36 698.46 18.37 146.83 698.46 18.38 146.83 698.46 18.39 146.83 698.46 18.40 146.83 698.46 18.41 146.83 698.46 18.42 146.83 698.46 18.43 146.83 698.46 18.44 698.46 18.45 698.46 18.46 698.46 18.47 698.46 18.48 698.46 18.49 98.00 698.46 18.50 98.00 698.46 18.51 98.00 698.46 18.52 98.00 698.46 18.53 98.00 698.46 18.54 98.00 698.46 18.55 98.00 698.46 18.56 98.00 698.46 18.57 98.00 698.46 18.58 698.46 18.59 698.46 18.60 698.46 18.61 698.46 18.62 698.46 18.63 293.66 698.46 18.64 293.66 698.46 18.65 293.66 698.46 18.66 293.66 698.46 18.67 293.66 698.46 18.68 293.66 698.46 18.69 293.66 698.46 18.70 293.66 698.46 18.71 293.66 698.46 18.72 293.66 698.46 18.73 293.66 349.23 698.46 18.74 293.66 349.23 698.46 18.75 293.66 349.23 698.46 18.76 293.66 349.23 698.46 18.77 349.23 698.46 18.78 349.23 698.46 18.79 349.23 698.46 18.80 349.23 698.46 18.81 698.46 18.82 698.46 18.83 523.25 698.46 18.84 523.25 698.46 18.85 523.25 698.46 18.86 523.25 698.46 18.87 293.66 523.25 698.46 18.88 293.66 523.25 698.46 18.89 293.66 523.25 698.46 18.90 293.66 523.25 698.46 18.91 293.66 523.25 698.46 18.92 293.66 523.25 698.46 18.93 293.66 523.25 698.46 18.94 293.66 523.25 18.95 293.66 523.25 18.96 146.83 293.66 523.25 18.97 146.83 466.16 523.25 18.98 146.83 466.16 523.25 18.99 146.83 466.16 523.25 19.00 146.83 466.16 523.25 19.01 146.83 466.16 523.25 19.02 146.83 466.16 523.25 19.03 146.83 466.16 523.25 19.04 466.16 523.25 19.05 293.66 466.16 19.06 293.66 466.16 19.07 293.66 466.16 19.08 293.66 440.00 19.09 293.66 440.00 19.10 293.66 440.00 19.11 293.66 440.00 19.12 440.00 19.13 440.00 19.14 440.00 19.15 440.00 19.16 440.00 19.17 440.00 19.18 440.00 19.19 440.00 19.20 440.00 19.21 440.00 19.22 440.00 19.23 440.00 19.24 440.00 19.25 440.00 19.26 440.00 19.27 440.00 19.28 440.00 19.29 440.00 19.30 440.00 19.31 220.00 329.63 440.00 19.32 220.00 329.63 440.00 19.33 220.00 329.63 440.00 19.34 220.00 329.63 440.00 19.35 220.00 329.63 440.00 19.36 220.00 329.63 440.00 19.37 220.00 329.63 440.00 19.38 220.00 329.63 440.00 19.39 220.00 329.63 440.00 19.40 220.00 329.63 440.00 19.41 220.00 329.63 440.00 19.42 220.00 329.63 440.00 19.43 329.63 440.00 19.44 440.00 19.45 440.00 19.46 440.00 19.47 440.00 19.48 440.00 19.49 440.00 19.50 440.00 19.51 440.00 19.52 440.00 19.53 440.00 19.54 440.00 19.55 329.63 440.00 19.56 329.63 440.00 880.00 19.57 329.63 440.00 880.00 19.58 329.63 440.00 880.00 19.59 329.63 440.00 880.00 19.60 329.63 440.00 880.00 19.61 329.63 440.00 880.00 19.62 329.63 440.00 880.00 19.63 329.63 440.00 880.00 19.64 329.63 440.00 880.00 19.65 329.63 440.00 880.00 19.66 329.63 440.00 880.00 19.67 329.63 440.00 880.00 19.68 110.00 329.63 440.00 880.00 19.69 110.00 220.00 329.63 440.00 880.00 19.70 110.00 220.00 329.63 440.00 880.00 19.71 110.00 220.00 440.00 19.72 110.00 220.00 440.00 19.73 110.00 220.00 440.00 19.74 110.00 220.00 440.00 19.75 110.00 220.00 440.00 19.76 110.00 220.00 440.00 19.77 110.00 220.00 329.63 440.00 19.78 110.00 220.00 329.63 440.00 19.79 110.00 220.00 329.63 440.00 19.80 110.00 220.00 329.63 440.00 19.81 110.00 220.00 329.63 440.00 19.82 110.00 220.00 329.63 440.00 698.46 19.83 110.00 220.00 329.63 440.00 698.46 19.84 220.00 329.63 440.00 698.46 19.85 220.00 329.63 440.00 698.46 19.86 220.00 329.63 698.46 19.87 220.00 329.63 698.46 19.88 220.00 329.63 698.46 19.89 220.00 293.66 329.63 698.46 19.90 220.00 293.66 698.46 19.91 220.00 293.66 698.46 19.92 220.00 293.66 698.46 19.93 220.00 293.66 698.46 19.94 293.66 698.46 19.95 293.66 698.46 19.96 293.66 698.46 19.97 293.66 698.46 19.98 293.66 698.46 19.99 293.66 698.46 20.00 293.66 698.46 20.01 293.66 698.46 20.02 293.66 698.46 20.03 293.66 698.46 20.04 293.66 698.46 1396.91 20.05 293.66 698.46 1396.91 20.06 293.66 698.46 1396.91 20.07 293.66 698.46 1396.91 20.08 293.66 698.46 1396.91 20.09 293.66 698.46 1396.91 20.10 293.66 698.46 1396.91 20.11 293.66 698.46 20.12 293.66 698.46 20.13 146.83 293.66 698.46 20.14 146.83 293.66 698.46 20.15 146.83 293.66 698.46 20.16 146.83 293.66 698.46 20.17 146.83 293.66 698.46 20.18 146.83 293.66 698.46 20.19 146.83 293.66 698.46 20.20 146.83 293.66 698.46 20.21 146.83 293.66 698.46 20.22 146.83 293.66 698.46 20.23 146.83 293.66 698.46 20.24 146.83 293.66 698.46 20.25 146.83 293.66 698.46 20.26 146.83 293.66 698.46 20.27 146.83 293.66 349.23 698.46 20.28 146.83 293.66 349.23 698.46 20.29 146.83 293.66 349.23 698.46 20.30 146.83 293.66 349.23 698.46 20.31 146.83 349.23 698.46 20.32 146.83 349.23 698.46 20.33 146.83 349.23 698.46 20.34 146.83 349.23 698.46 20.35 146.83 698.46 20.36 146.83 698.46 20.37 164.81 698.46 20.38 164.81 698.46 20.39 164.81 698.46 20.40 164.81 698.46 20.41 164.81 698.46 20.42 164.81 698.46 20.43 164.81 698.46 20.44 164.81 698.46 20.45 164.81 698.46 20.46 164.81 698.46 20.47 164.81 698.46 20.48 164.81 698.46 20.49 164.81 349.23 698.46 20.50 164.81 349.23 698.46 20.51 349.23 698.46 20.52 174.61 349.23 698.46 20.53 174.61 349.23 698.46 20.54 174.61 349.23 698.46 20.55 174.61 349.23 698.46 20.56 174.61 349.23 698.46 20.57 174.61 349.23 698.46 20.58 174.61 293.66 349.23 587.33 698.46 20.59 174.61 293.66 349.23 587.33 698.46 20.60 174.61 293.66 349.23 587.33 698.46 20.61 174.61 293.66 349.23 587.33 698.46 20.62 174.61 293.66 349.23 587.33 698.46 20.63 174.61 293.66 349.23 587.33 698.46 20.64 174.61 293.66 349.23 587.33 698.46 20.65 174.61 293.66 349.23 587.33 698.46 20.66 174.61 293.66 349.23 587.33 698.46 20.67 174.61 293.66 349.23 587.33 698.46 20.68 174.61 349.23 587.33 698.46 20.69 174.61 349.23 587.33 698.46 20.70 174.61 349.23 587.33 698.46 20.71 174.61 349.23 587.33 698.46 880.00 20.72 174.61 349.23 587.33 698.46 880.00 20.73 174.61 293.66 349.23 698.46 880.00 20.74 174.61 293.66 349.23 698.46 880.00 20.75 174.61 293.66 349.23 698.46 880.00 20.76 116.54 174.61 293.66 349.23 698.46 880.00 20.77 116.54 174.61 293.66 349.23 698.46 880.00 20.78 116.54 174.61 293.66 349.23 698.46 880.00 1396.91 20.79 116.54 174.61 293.66 349.23 698.46 880.00 1396.91 20.80 116.54 174.61 293.66 349.23 698.46 880.00 1396.91 20.81 116.54 174.61 293.66 349.23 698.46 880.00 1396.91 20.82 116.54 174.61 293.66 349.23 698.46 880.00 1396.91 20.83 116.54 174.61 293.66 349.23 698.46 880.00 932.33 1396.91 20.84 116.54 174.61 293.66 349.23 698.46 880.00 932.33 1396.91 20.85 116.54 174.61 293.66 349.23 880.00 932.33 20.86 116.54 174.61 293.66 349.23 880.00 932.33 20.87 116.54 174.61 293.66 349.23 880.00 932.33 20.88 116.54 174.61 293.66 349.23 880.00 932.33 20.89 116.54 174.61 293.66 349.23 880.00 932.33 20.90 116.54 174.61 293.66 349.23 880.00 932.33 20.91 116.54 174.61 293.66 349.23 880.00 932.33 20.92 116.54 174.61 293.66 349.23 880.00 932.33 20.93 116.54 174.61 293.66 349.23 880.00 932.33 20.94 116.54 174.61 293.66 349.23 880.00 932.33 20.95 116.54 174.61 293.66 349.23 880.00 932.33 20.96 116.54 174.61 293.66 349.23 880.00 932.33 20.97 116.54 174.61 293.66 349.23 880.00 932.33 20.98 116.54 174.61 293.66 349.23 880.00 932.33 20.99 116.54 174.61 293.66 349.23 880.00 932.33 21.00 116.54 174.61 293.66 880.00 932.33 21.01 116.54 174.61 293.66 880.00 932.33 21.02 116.54 174.61 293.66 880.00 932.33 21.03 116.54 174.61 293.66 880.00 932.33 21.04 116.54 293.66 880.00 932.33 21.05 116.54 293.66 349.23 880.00 932.33 21.06 116.54 293.66 349.23 880.00 932.33 21.07 116.54 293.66 349.23 880.00 932.33 21.08 116.54 293.66 349.23 880.00 932.33 21.09 116.54 233.08 293.66 349.23 466.16 880.00 932.33 21.10 116.54 233.08 293.66 349.23 466.16 880.00 932.33 21.11 116.54 233.08 293.66 349.23 466.16 880.00 932.33 21.12 116.54 233.08 293.66 349.23 466.16 880.00 932.33 21.13 116.54 233.08 293.66 466.16 880.00 932.33 21.14 116.54 233.08 293.66 466.16 880.00 932.33 21.15 116.54 233.08 293.66 466.16 880.00 932.33 21.16 116.54 293.66 783.99 880.00 932.33 21.17 116.54 174.61 293.66 783.99 880.00 932.33 21.18 116.54 174.61 293.66 783.99 880.00 932.33 21.19 116.54 174.61 293.66 783.99 880.00 932.33 21.20 116.54 174.61 293.66 783.99 880.00 932.33 21.21 116.54 174.61 293.66 392.00 783.99 880.00 932.33 21.22 116.54 174.61 293.66 392.00 783.99 880.00 932.33 21.23 116.54 174.61 293.66 392.00 783.99 880.00 932.33 21.24 116.54 174.61 293.66 392.00 783.99 880.00 932.33 21.25 116.54 174.61 293.66 392.00 783.99 880.00 932.33 21.26 116.54 174.61 293.66 392.00 466.16 783.99 880.00 932.33 21.27 116.54 174.61 293.66 392.00 466.16 783.99 880.00 932.33 21.28 116.54 174.61 293.66 466.16 783.99 880.00 932.33 21.29 116.54 174.61 293.66 466.16 783.99 880.00 932.33 21.30 116.54 174.61 293.66 466.16 783.99 932.33 21.31 116.54 174.61 293.66 466.16 783.99 932.33 21.32 116.54 293.66 466.16 783.99 932.33 21.33 116.54 293.66 698.46 783.99 932.33 21.34 116.54 293.66 698.46 783.99 932.33 21.35 116.54 698.46 783.99 932.33 21.36 116.54 698.46 783.99 932.33 21.37 116.54 698.46 932.33 21.38 116.54 440.00 698.46 932.33 21.39 116.54 440.00 698.46 932.33 21.40 116.54 440.00 698.46 932.33 21.41 116.54 440.00 698.46 932.33 21.42 116.54 440.00 698.46 932.33 21.43 116.54 440.00 698.46 21.44 116.54 440.00 698.46 21.45 116.54 440.00 698.46 21.46 116.54 440.00 698.46 1396.91 21.47 116.54 698.46 1396.91 21.48 698.46 880.00 1396.91 21.49 698.46 880.00 1396.91 21.50 698.46 880.00 1396.91 21.51 698.46 880.00 1396.91 21.52 110.00 698.46 880.00 1396.91 21.53 110.00 698.46 880.00 1396.91 21.54 110.00 698.46 880.00 1396.91 21.55 110.00 698.46 880.00 21.56 110.00 698.46 880.00 21.57 110.00 698.46 21.58 110.00 698.46 21.59 110.00 698.46 21.60 110.00 698.46 21.61 110.00 698.46 21.62 110.00 698.46 21.63 110.00 698.46 21.64 110.00 698.46 21.65 110.00 698.46 21.66 110.00 698.46 21.67 110.00 698.46 21.68 110.00 698.46 21.69 110.00 698.46 21.70 110.00 698.46 21.71 110.00 698.46 21.72 110.00 698.46 21.73 110.00 698.46 21.74 110.00 698.46 21.75 110.00 698.46 21.76 110.00 698.46 21.77 110.00 698.46 21.78 110.00 698.46 21.79 110.00 698.46 21.80 110.00 698.46 1396.91 21.81 110.00 698.46 1396.91 21.82 110.00 698.46 1396.91 21.83 110.00 698.46 1396.91 21.84 110.00 220.00 440.00 698.46 1396.91 21.85 110.00 220.00 440.00 659.26 698.46 1396.91 21.86 110.00 220.00 440.00 659.26 698.46 1396.91 21.87 110.00 220.00 440.00 659.26 698.46 1396.91 21.88 110.00 220.00 440.00 659.26 698.46 21.89 110.00 220.00 440.00 659.26 698.46 21.90 110.00 220.00 440.00 659.26 698.46 21.91 110.00 220.00 440.00 659.26 698.46 21.92 110.00 220.00 440.00 659.26 698.46 21.93 110.00 220.00 440.00 659.26 698.46 21.94 110.00 220.00 440.00 659.26 698.46 21.95 110.00 220.00 440.00 659.26 698.46 21.96 110.00 220.00 440.00 659.26 698.46 21.97 110.00 220.00 440.00 659.26 698.46 21.98 110.00 220.00 440.00 659.26 698.46 21.99 110.00 220.00 440.00 659.26 698.46 22.00 110.00 220.00 440.00 659.26 698.46 22.01 110.00 220.00 440.00 659.26 698.46 22.02 110.00 220.00 440.00 659.26 698.46 22.03 110.00 220.00 440.00 659.26 698.46 22.04 110.00 220.00 440.00 659.26 698.46 22.05 110.00 220.00 659.26 698.46 22.06 110.00 220.00 659.26 698.46 22.07 110.00 220.00 659.26 22.08 110.00 220.00 659.26 22.09 110.00 220.00 659.26 22.10 110.00 220.00 659.26 22.11 110.00 220.00 659.26 22.12 110.00 220.00 440.00 659.26 22.13 110.00 220.00 440.00 659.26 22.14 110.00 220.00 440.00 659.26 22.15 110.00 220.00 440.00 659.26 22.16 110.00 220.00 440.00 659.26 22.17 110.00 220.00 440.00 659.26 22.18 110.00 220.00 440.00 659.26 22.19 110.00 220.00 440.00 659.26 22.20 110.00 220.00 440.00 659.26 22.21 110.00 220.00 440.00 659.26 22.22 110.00 220.00 440.00 659.26 22.23 110.00 220.00 440.00 659.26 22.24 110.00 220.00 440.00 659.26 22.25 110.00 220.00 440.00 659.26 22.26 110.00 220.00 659.26 22.27 110.00 220.00 659.26 22.28 110.00 220.00 659.26 22.29 110.00 220.00 659.26 22.30 110.00 220.00 261.63 659.26 22.31 110.00 261.63 659.26 22.32 110.00 261.63 659.26 22.33 110.00 261.63 622.25 659.26 22.34 110.00 261.63 622.25 659.26 22.35 110.00 261.63 622.25 659.26 22.36 110.00 261.63 622.25 659.26 22.37 110.00 261.63 622.25 659.26 22.38 110.00 261.63 622.25 659.26 1046.50 22.39 110.00 261.63 622.25 659.26 1046.50 22.40 110.00 261.63 622.25 659.26 1046.50 22.41 110.00 261.63 622.25 659.26 1046.50 22.42 110.00 261.63 622.25 659.26 1046.50 22.43 110.00 261.63 622.25 659.26 1046.50 22.44 110.00 622.25 659.26 1046.50 22.45 110.00 622.25 659.26 1046.50 22.46 110.00 622.25 659.26 1046.50 22.47 110.00 622.25 659.26 22.48 110.00 622.25 659.26 22.49 110.00 369.99 622.25 659.26 22.50 110.00 369.99 622.25 659.26 22.51 110.00 369.99 622.25 659.26 22.52 110.00 369.99 622.25 659.26 22.53 110.00 369.99 622.25 659.26 22.54 110.00 369.99 622.25 659.26 22.55 110.00 369.99 622.25 659.26 22.56 110.00 369.99 622.25 659.26 22.57 110.00 369.99 622.25 659.26 22.58 110.00 369.99 622.25 22.59 110.00 261.63 369.99 622.25 22.60 110.00 261.63 369.99 622.25 22.61 110.00 261.63 369.99 622.25 22.62 110.00 261.63 369.99 622.25 22.63 110.00 261.63 369.99 622.25 22.64 110.00 261.63 369.99 622.25 22.65 110.00 261.63 369.99 622.25 22.66 110.00 261.63 369.99 622.25 22.67 110.00 261.63 369.99 622.25 22.68 110.00 261.63 622.25 1046.50 22.69 110.00 261.63 622.25 1046.50 22.70 261.63 622.25 1046.50 22.71 261.63 622.25 1046.50 22.72 261.63 622.25 1046.50 22.73 261.63 622.25 1046.50 22.74 261.63 622.25 1046.50 22.75 261.63 622.25 1046.50 22.76 261.63 622.25 1046.50 22.77 261.63 622.25 1046.50 22.78 261.63 622.25 1046.50 22.79 261.63 622.25 1046.50 22.80 261.63 622.25 1046.50 22.81 261.63 622.25 22.82 261.63 622.25 22.83 110.00 261.63 622.25 22.84 110.00 261.63 622.25 22.85 110.00 261.63 369.99 622.25 22.86 110.00 261.63 369.99 622.25 22.87 110.00 261.63 369.99 622.25 22.88 110.00 261.63 369.99 622.25 22.89 110.00 261.63 369.99 622.25 22.90 110.00 261.63 369.99 622.25 22.91 110.00 261.63 369.99 622.25 22.92 110.00 261.63 369.99 622.25 22.93 110.00 261.63 369.99 622.25 22.94 110.00 261.63 369.99 622.25 22.95 110.00 261.63 369.99 622.25 22.96 110.00 261.63 369.99 622.25 22.97 110.00 369.99 622.25 22.98 110.00 369.99 22.99 110.00 369.99 23.00 369.99 23.01 369.99 23.02 369.99 23.03 23.04 23.05 23.06 23.07 23.08 23.09 23.10 23.11 23.12 23.13 23.14 23.15 23.16 23.17 23.18 23.19 23.20 23.21 23.22 23.23 23.24 23.25 23.26 23.27 23.28 23.29 23.30 23.31 23.32 23.33 23.34 23.35 23.36 23.37 23.38 23.39 23.40 23.41 23.42 23.43 23.44 23.45 23.46 23.47 23.48 23.49 23.50 23.51 23.52 23.53 23.54 23.55 23.56 23.57 23.58 23.59 23.60 23.61 23.62 23.63 23.64 23.65 23.66 23.67 23.68 23.69 23.70 23.71 23.72 23.73 23.74 23.75 23.76 23.77 23.78 23.79 23.80 23.81 23.82 23.83 23.84 23.85 23.86 23.87 23.88 23.89 23.90 23.91 23.92 23.93 23.94 23.95 23.96 23.97 23.98 23.99 mir_eval-0.8.2/tests/data/multipitch/est08.txt000066400000000000000000001732331475740344600213070ustar00rootroot000000000000000.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.30 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.40 0.41 0.42 0.43 0.44 0.45 0.46 0.47 0.48 0.49 0.50 0.51 0.52 0.53 0.54 0.55 0.56 0.57 0.58 0.59 0.60 0.61 0.62 0.63 0.64 0.65 0.66 0.67 0.68 0.69 0.70 0.71 0.72 0.73 0.74 0.75 0.76 0.77 0.78 0.79 0.80 369.99 0.81 185.00 369.99 0.82 185.00 369.99 0.83 185.00 369.99 0.84 185.00 369.99 0.85 185.00 369.99 0.86 185.00 369.99 0.87 185.00 293.66 369.99 0.88 185.00 293.66 369.99 0.89 185.00 293.66 369.99 0.90 185.00 293.66 369.99 0.91 185.00 293.66 369.99 0.92 185.00 293.66 369.99 0.93 185.00 293.66 369.99 0.94 185.00 293.66 369.99 0.95 185.00 293.66 369.99 0.96 185.00 293.66 369.99 0.97 185.00 293.66 369.99 0.98 185.00 293.66 369.99 0.99 185.00 293.66 369.99 1.00 185.00 293.66 369.99 1.01 185.00 293.66 369.99 1.02 185.00 293.66 369.99 1.03 185.00 293.66 369.99 1.04 185.00 293.66 369.99 1.05 185.00 293.66 369.99 1.06 185.00 293.66 1.07 185.00 293.66 1.08 185.00 293.66 1.09 185.00 293.66 1.10 185.00 293.66 1.11 185.00 293.66 1.12 185.00 293.66 1.13 185.00 293.66 1.14 185.00 293.66 1.15 185.00 293.66 1.16 185.00 293.66 1.17 185.00 293.66 1.18 185.00 293.66 1.19 185.00 293.66 1.20 185.00 293.66 1.21 185.00 293.66 1.22 185.00 293.66 1.23 185.00 293.66 1.24 185.00 293.66 1.25 185.00 293.66 1.26 185.00 293.66 1.27 185.00 293.66 1.28 185.00 293.66 1.29 185.00 293.66 1.30 185.00 293.66 1.31 185.00 293.66 1.32 185.00 293.66 1.33 185.00 293.66 1.34 185.00 293.66 1.35 185.00 293.66 1.36 185.00 293.66 1.37 185.00 293.66 1.38 185.00 293.66 1.39 185.00 293.66 1.40 185.00 293.66 1.41 185.00 293.66 1.42 185.00 293.66 1.43 185.00 293.66 1.44 185.00 293.66 1.45 185.00 293.66 1.46 185.00 293.66 1.47 185.00 293.66 1.48 185.00 293.66 1.49 185.00 293.66 1.50 185.00 293.66 1.51 185.00 293.66 1.52 185.00 293.66 1.53 185.00 293.66 1.54 185.00 293.66 1.55 185.00 293.66 1.56 185.00 293.66 1.57 185.00 293.66 1.58 185.00 293.66 1.59 185.00 293.66 1.60 185.00 293.66 1.61 185.00 293.66 1.62 185.00 293.66 1.63 185.00 293.66 1.64 185.00 293.66 1.65 185.00 293.66 1.66 185.00 293.66 1.67 185.00 293.66 1.68 185.00 293.66 1.69 185.00 293.66 1.70 185.00 293.66 1.71 185.00 293.66 1.72 185.00 293.66 1.73 185.00 293.66 1.74 185.00 293.66 1.75 185.00 293.66 1.76 185.00 293.66 1.77 185.00 293.66 1.78 185.00 293.66 1.79 185.00 293.66 1.80 185.00 293.66 1.81 185.00 293.66 1.82 185.00 293.66 1.83 185.00 293.66 1.84 185.00 293.66 1.85 185.00 293.66 1.86 185.00 293.66 1.87 185.00 293.66 1.88 185.00 293.66 1.89 185.00 293.66 1.90 185.00 293.66 1.91 185.00 293.66 1.92 185.00 293.66 1.93 185.00 293.66 1.94 185.00 293.66 1.95 185.00 293.66 1.96 185.00 293.66 1.97 185.00 293.66 1.98 185.00 293.66 1.99 185.00 293.66 2.00 185.00 293.66 2.01 185.00 293.66 2.02 185.00 293.66 2.03 185.00 293.66 2.04 185.00 293.66 2.05 185.00 293.66 2.06 185.00 293.66 2.07 185.00 293.66 2.08 185.00 293.66 2.09 185.00 293.66 2.10 185.00 293.66 2.11 185.00 293.66 2.12 185.00 293.66 2.13 185.00 293.66 2.14 185.00 293.66 2.15 185.00 293.66 2.16 185.00 293.66 2.17 185.00 293.66 2.18 185.00 293.66 2.19 185.00 293.66 2.20 185.00 293.66 2.21 185.00 293.66 2.22 185.00 293.66 2.23 185.00 293.66 2.24 185.00 293.66 2.25 185.00 293.66 2.26 185.00 293.66 2.27 185.00 293.66 2.28 185.00 293.66 2.29 185.00 293.66 2.30 185.00 293.66 2.31 185.00 293.66 2.32 185.00 293.66 2.33 185.00 293.66 2.34 185.00 293.66 2.35 185.00 293.66 2.36 185.00 293.66 2.37 185.00 293.66 2.38 61.74 123.47 185.00 293.66 2.39 61.74 123.47 185.00 293.66 2.40 61.74 123.47 185.00 293.66 2.41 61.74 123.47 185.00 293.66 2.42 61.74 123.47 185.00 293.66 2.43 61.74 123.47 185.00 293.66 2.44 61.74 123.47 185.00 293.66 2.45 61.74 123.47 185.00 293.66 2.46 61.74 123.47 185.00 293.66 2.47 61.74 123.47 185.00 293.66 2.48 123.47 185.00 293.66 329.63 2.49 185.00 293.66 329.63 2.50 185.00 293.66 329.63 2.51 185.00 329.63 2.52 329.63 2.53 329.63 2.54 329.63 2.55 329.63 2.56 329.63 2.57 329.63 2.58 329.63 2.59 329.63 2.60 146.83 329.63 369.99 2.61 146.83 329.63 369.99 2.62 146.83 329.63 369.99 2.63 146.83 369.99 2.64 146.83 369.99 2.65 146.83 369.99 2.66 146.83 369.99 2.67 146.83 369.99 2.68 73.42 146.83 369.99 2.69 73.42 146.83 369.99 2.70 73.42 146.83 369.99 2.71 73.42 146.83 369.99 2.72 73.42 146.83 369.99 2.73 73.42 146.83 369.99 2.74 73.42 146.83 369.99 2.75 73.42 146.83 369.99 2.76 146.83 2.77 146.83 2.78 146.83 2.79 2.80 164.81 2.81 164.81 2.82 164.81 392.00 2.83 164.81 392.00 2.84 164.81 392.00 2.85 164.81 392.00 659.26 1318.51 2.86 164.81 392.00 659.26 1318.51 2.87 164.81 392.00 659.26 1318.51 2.88 164.81 392.00 659.26 1318.51 2.89 164.81 392.00 659.26 1318.51 2.90 164.81 392.00 659.26 1318.51 2.91 164.81 392.00 659.26 1318.51 2.92 82.41 164.81 392.00 659.26 1318.51 2.93 82.41 164.81 392.00 659.26 2.94 82.41 164.81 392.00 659.26 2.95 82.41 164.81 392.00 659.26 2.96 82.41 164.81 392.00 659.26 2.97 82.41 164.81 392.00 659.26 2.98 82.41 164.81 392.00 659.26 2.99 82.41 164.81 246.94 392.00 659.26 3.00 82.41 164.81 246.94 392.00 659.26 3.01 82.41 164.81 246.94 392.00 659.26 3.02 82.41 164.81 246.94 392.00 3.03 82.41 164.81 246.94 392.00 3.04 82.41 164.81 246.94 392.00 3.05 82.41 164.81 246.94 392.00 3.06 82.41 164.81 392.00 3.07 82.41 164.81 392.00 3.08 82.41 164.81 392.00 3.09 164.81 392.00 3.10 164.81 392.00 3.11 164.81 392.00 3.12 164.81 369.99 392.00 3.13 164.81 369.99 392.00 3.14 164.81 369.99 392.00 3.15 164.81 369.99 392.00 3.16 164.81 369.99 392.00 3.17 164.81 369.99 392.00 3.18 164.81 369.99 392.00 3.19 164.81 369.99 392.00 3.20 369.99 392.00 3.21 369.99 392.00 3.22 369.99 392.00 3.23 369.99 392.00 3.24 369.99 392.00 3.25 369.99 392.00 3.26 369.99 392.00 3.27 369.99 392.00 3.28 392.00 3.29 164.81 392.00 3.30 164.81 392.00 3.31 164.81 392.00 3.32 164.81 392.00 3.33 164.81 392.00 3.34 82.41 164.81 392.00 3.35 82.41 164.81 392.00 3.36 82.41 164.81 392.00 3.37 82.41 164.81 392.00 3.38 82.41 164.81 392.00 3.39 82.41 164.81 392.00 3.40 82.41 164.81 392.00 3.41 82.41 164.81 392.00 3.42 82.41 164.81 392.00 3.43 82.41 164.81 369.99 392.00 3.44 82.41 164.81 369.99 3.45 82.41 164.81 369.99 3.46 369.99 3.47 369.99 3.48 369.99 3.49 369.99 3.50 369.99 3.51 369.99 3.52 369.99 3.53 369.99 3.54 369.99 3.55 369.99 3.56 246.94 369.99 493.88 3.57 246.94 369.99 493.88 3.58 246.94 369.99 493.88 3.59 123.47 246.94 369.99 493.88 3.60 123.47 246.94 369.99 493.88 3.61 123.47 246.94 369.99 493.88 3.62 123.47 246.94 369.99 493.88 3.63 123.47 246.94 369.99 493.88 3.64 123.47 246.94 369.99 493.88 3.65 123.47 246.94 369.99 493.88 3.66 123.47 246.94 369.99 493.88 3.67 123.47 246.94 369.99 493.88 3.68 123.47 246.94 369.99 493.88 3.69 123.47 369.99 493.88 3.70 123.47 369.99 493.88 3.71 123.47 493.88 3.72 123.47 493.88 3.73 123.47 493.88 554.37 3.74 123.47 277.18 493.88 554.37 3.75 123.47 277.18 493.88 554.37 3.76 123.47 277.18 466.16 493.88 554.37 3.77 277.18 466.16 493.88 554.37 3.78 277.18 466.16 493.88 554.37 3.79 277.18 466.16 493.88 554.37 3.80 277.18 466.16 493.88 554.37 3.81 277.18 466.16 493.88 554.37 3.82 277.18 466.16 493.88 554.37 3.83 277.18 466.16 493.88 554.37 3.84 277.18 466.16 554.37 3.85 277.18 466.16 554.37 1318.51 3.86 277.18 466.16 554.37 1318.51 3.87 466.16 554.37 1318.51 3.88 466.16 554.37 1318.51 3.89 466.16 554.37 1318.51 3.90 466.16 554.37 1318.51 3.91 466.16 554.37 1318.51 3.92 466.16 554.37 1318.51 3.93 466.16 554.37 1318.51 3.94 466.16 554.37 1318.51 3.95 466.16 554.37 987.77 1318.51 3.96 138.59 466.16 554.37 987.77 3.97 138.59 466.16 554.37 987.77 3.98 138.59 466.16 554.37 987.77 3.99 138.59 277.18 466.16 554.37 987.77 4.00 92.50 138.59 185.00 277.18 466.16 554.37 987.77 4.01 92.50 138.59 185.00 277.18 466.16 554.37 987.77 4.02 92.50 138.59 185.00 277.18 466.16 554.37 4.03 92.50 138.59 185.00 277.18 466.16 554.37 4.04 92.50 138.59 185.00 277.18 466.16 554.37 4.05 92.50 138.59 185.00 277.18 466.16 554.37 4.06 92.50 138.59 185.00 277.18 466.16 554.37 4.07 92.50 138.59 185.00 277.18 466.16 554.37 4.08 92.50 138.59 185.00 466.16 554.37 4.09 92.50 185.00 466.16 554.37 4.10 92.50 185.00 466.16 554.37 4.11 92.50 185.00 466.16 554.37 4.12 92.50 185.00 466.16 554.37 4.13 92.50 185.00 277.18 466.16 554.37 4.14 92.50 185.00 277.18 466.16 554.37 4.15 92.50 185.00 277.18 466.16 554.37 4.16 92.50 185.00 277.18 554.37 4.17 92.50 185.00 277.18 554.37 4.18 92.50 185.00 277.18 554.37 4.19 92.50 185.00 277.18 554.37 4.20 92.50 185.00 277.18 554.37 4.21 92.50 185.00 277.18 554.37 4.22 92.50 185.00 277.18 369.99 554.37 739.99 4.23 92.50 185.00 277.18 369.99 554.37 739.99 4.24 92.50 185.00 277.18 369.99 554.37 739.99 4.25 185.00 369.99 554.37 739.99 4.26 185.00 369.99 554.37 739.99 4.27 185.00 369.99 554.37 739.99 1318.51 4.28 185.00 369.99 554.37 739.99 1318.51 4.29 185.00 369.99 554.37 739.99 1318.51 4.30 369.99 554.37 739.99 1318.51 4.31 369.99 554.37 739.99 783.99 1318.51 4.32 92.50 369.99 554.37 739.99 783.99 1318.51 4.33 92.50 369.99 554.37 739.99 783.99 1318.51 4.34 92.50 369.99 554.37 739.99 783.99 1318.51 4.35 92.50 369.99 554.37 739.99 783.99 1318.51 4.36 92.50 369.99 554.37 739.99 783.99 1318.51 4.37 92.50 369.99 554.37 739.99 783.99 1318.51 4.38 92.50 369.99 554.37 739.99 783.99 1318.51 4.39 92.50 369.99 554.37 739.99 783.99 1318.51 4.40 92.50 369.99 739.99 783.99 1318.51 4.41 92.50 369.99 739.99 783.99 1318.51 4.42 92.50 369.99 739.99 783.99 1318.51 4.43 92.50 369.99 739.99 783.99 1318.51 4.44 92.50 185.00 369.99 739.99 1318.51 4.45 92.50 185.00 369.99 739.99 1318.51 4.46 92.50 138.59 185.00 369.99 739.99 1318.51 4.47 92.50 138.59 185.00 369.99 739.99 1318.51 4.48 92.50 138.59 185.00 369.99 739.99 1318.51 4.49 92.50 138.59 185.00 369.99 739.99 1318.51 4.50 92.50 138.59 185.00 369.99 739.99 1318.51 4.51 92.50 138.59 185.00 369.99 739.99 1318.51 4.52 92.50 138.59 185.00 369.99 739.99 1318.51 4.53 92.50 138.59 185.00 369.99 739.99 1318.51 4.54 92.50 138.59 185.00 369.99 739.99 1318.51 4.55 92.50 138.59 185.00 369.99 739.99 1318.51 4.56 92.50 138.59 185.00 369.99 739.99 1318.51 4.57 92.50 138.59 185.00 369.99 739.99 1318.51 4.58 92.50 138.59 185.00 369.99 739.99 1318.51 4.59 92.50 138.59 185.00 369.99 739.99 4.60 92.50 138.59 185.00 369.99 739.99 4.61 92.50 138.59 185.00 369.99 739.99 4.62 92.50 138.59 185.00 369.99 739.99 4.63 92.50 138.59 185.00 369.99 739.99 4.64 92.50 138.59 185.00 369.99 739.99 4.65 92.50 138.59 185.00 369.99 739.99 4.66 92.50 138.59 185.00 369.99 739.99 4.67 92.50 138.59 185.00 369.99 739.99 4.68 92.50 138.59 185.00 369.99 739.99 4.69 92.50 138.59 185.00 369.99 739.99 4.70 92.50 138.59 185.00 369.99 739.99 4.71 92.50 138.59 185.00 369.99 739.99 4.72 92.50 138.59 185.00 369.99 739.99 4.73 92.50 185.00 369.99 587.33 739.99 4.74 92.50 185.00 369.99 587.33 739.99 4.75 92.50 185.00 369.99 587.33 739.99 1318.51 4.76 92.50 185.00 369.99 587.33 739.99 1318.51 4.77 92.50 185.00 369.99 587.33 739.99 1318.51 4.78 92.50 185.00 369.99 587.33 739.99 1318.51 4.79 92.50 185.00 369.99 587.33 739.99 1318.51 4.80 92.50 185.00 369.99 587.33 739.99 1318.51 4.81 92.50 123.47 185.00 369.99 587.33 739.99 1318.51 4.82 92.50 123.47 185.00 369.99 587.33 739.99 1318.51 4.83 92.50 123.47 185.00 369.99 587.33 739.99 1318.51 4.84 92.50 123.47 185.00 369.99 587.33 739.99 4.85 92.50 123.47 185.00 369.99 587.33 739.99 4.86 92.50 123.47 185.00 293.66 587.33 739.99 4.87 92.50 123.47 185.00 293.66 587.33 739.99 4.88 92.50 123.47 185.00 293.66 587.33 739.99 4.89 92.50 123.47 185.00 293.66 587.33 739.99 4.90 92.50 123.47 185.00 293.66 587.33 739.99 1174.66 4.91 92.50 123.47 185.00 293.66 587.33 739.99 1174.66 4.92 92.50 123.47 185.00 293.66 587.33 739.99 1174.66 4.93 92.50 123.47 185.00 293.66 587.33 1174.66 4.94 92.50 123.47 185.00 293.66 369.99 587.33 1174.66 4.95 92.50 123.47 293.66 369.99 587.33 1174.66 4.96 92.50 123.47 293.66 369.99 587.33 1174.66 4.97 92.50 123.47 293.66 369.99 587.33 4.98 92.50 123.47 293.66 369.99 587.33 4.99 92.50 123.47 293.66 369.99 587.33 5.00 92.50 123.47 293.66 369.99 587.33 5.01 92.50 123.47 293.66 369.99 587.33 5.02 92.50 123.47 293.66 369.99 587.33 5.03 123.47 293.66 369.99 587.33 5.04 123.47 293.66 369.99 587.33 5.05 123.47 293.66 369.99 587.33 5.06 123.47 293.66 369.99 587.33 5.07 123.47 293.66 369.99 587.33 5.08 123.47 293.66 369.99 587.33 5.09 123.47 293.66 369.99 587.33 5.10 123.47 293.66 369.99 587.33 5.11 123.47 293.66 369.99 587.33 5.12 123.47 293.66 369.99 587.33 5.13 123.47 293.66 369.99 587.33 5.14 123.47 293.66 369.99 587.33 5.15 123.47 293.66 369.99 587.33 5.16 123.47 293.66 369.99 587.33 5.17 123.47 293.66 369.99 587.33 5.18 123.47 293.66 369.99 587.33 5.19 123.47 293.66 369.99 587.33 5.20 123.47 293.66 369.99 587.33 5.21 123.47 293.66 369.99 587.33 5.22 123.47 293.66 369.99 587.33 5.23 123.47 293.66 369.99 587.33 5.24 123.47 293.66 369.99 587.33 5.25 123.47 293.66 369.99 493.88 587.33 5.26 123.47 493.88 587.33 5.27 123.47 493.88 587.33 5.28 123.47 493.88 587.33 5.29 123.47 493.88 587.33 5.30 123.47 493.88 587.33 5.31 493.88 587.33 5.32 493.88 587.33 5.33 493.88 587.33 5.34 415.30 493.88 587.33 5.35 415.30 493.88 587.33 5.36 415.30 493.88 587.33 5.37 415.30 493.88 587.33 5.38 415.30 493.88 587.33 5.39 415.30 493.88 5.40 415.30 493.88 5.41 415.30 493.88 5.42 415.30 493.88 5.43 415.30 493.88 5.44 415.30 493.88 5.45 415.30 493.88 5.46 493.88 5.47 493.88 5.48 246.94 493.88 5.49 246.94 493.88 5.50 246.94 493.88 5.51 246.94 493.88 5.52 246.94 415.30 493.88 5.53 246.94 415.30 493.88 5.54 246.94 415.30 493.88 5.55 146.83 246.94 415.30 493.88 5.56 146.83 246.94 415.30 493.88 5.57 146.83 246.94 415.30 493.88 5.58 146.83 246.94 415.30 493.88 5.59 146.83 246.94 415.30 493.88 5.60 146.83 246.94 415.30 493.88 5.61 146.83 246.94 349.23 415.30 493.88 5.62 146.83 246.94 349.23 415.30 493.88 5.63 146.83 349.23 415.30 493.88 5.64 146.83 349.23 415.30 493.88 5.65 146.83 349.23 415.30 493.88 5.66 146.83 349.23 415.30 493.88 5.67 146.83 349.23 415.30 493.88 987.77 5.68 146.83 349.23 415.30 493.88 987.77 5.69 146.83 349.23 415.30 493.88 987.77 5.70 146.83 349.23 415.30 493.88 987.77 5.71 146.83 349.23 415.30 987.77 5.72 146.83 246.94 349.23 415.30 987.77 5.73 146.83 246.94 349.23 415.30 987.77 5.74 146.83 246.94 415.30 987.77 5.75 146.83 246.94 415.30 987.77 5.76 146.83 246.94 415.30 987.77 5.77 246.94 415.30 987.77 5.78 246.94 369.99 415.30 5.79 246.94 369.99 5.80 369.99 5.81 369.99 5.82 369.99 5.83 185.00 369.99 554.37 5.84 185.00 277.18 369.99 554.37 5.85 185.00 277.18 369.99 554.37 5.86 185.00 277.18 369.99 554.37 5.87 92.50 185.00 277.18 369.99 554.37 5.88 92.50 185.00 277.18 369.99 554.37 5.89 92.50 185.00 277.18 369.99 554.37 5.90 92.50 185.00 277.18 369.99 554.37 5.91 92.50 185.00 277.18 369.99 554.37 5.92 92.50 185.00 277.18 369.99 554.37 5.93 92.50 185.00 369.99 554.37 5.94 92.50 185.00 369.99 554.37 5.95 92.50 185.00 369.99 554.37 5.96 92.50 185.00 369.99 554.37 5.97 92.50 185.00 369.99 554.37 5.98 92.50 185.00 369.99 554.37 5.99 92.50 185.00 369.99 554.37 1108.73 6.00 92.50 185.00 369.99 554.37 1108.73 6.01 92.50 369.99 554.37 1108.73 6.02 92.50 369.99 554.37 1108.73 6.03 92.50 369.99 554.37 1108.73 6.04 92.50 369.99 554.37 1108.73 6.05 146.83 369.99 554.37 1108.73 6.06 146.83 369.99 554.37 1108.73 6.07 146.83 369.99 554.37 1108.73 6.08 146.83 369.99 6.09 146.83 277.18 369.99 6.10 146.83 277.18 369.99 6.11 146.83 277.18 369.99 6.12 146.83 277.18 369.99 6.13 92.50 277.18 369.99 6.14 92.50 185.00 277.18 369.99 6.15 92.50 185.00 277.18 369.99 6.16 92.50 185.00 277.18 369.99 6.17 92.50 185.00 233.08 277.18 369.99 6.18 92.50 185.00 233.08 369.99 6.19 92.50 185.00 233.08 369.99 6.20 92.50 185.00 233.08 369.99 6.21 92.50 185.00 233.08 369.99 6.22 92.50 185.00 233.08 369.99 6.23 92.50 185.00 233.08 369.99 6.24 92.50 185.00 233.08 369.99 6.25 92.50 185.00 233.08 369.99 6.26 92.50 185.00 233.08 369.99 6.27 92.50 185.00 233.08 369.99 6.28 92.50 185.00 233.08 369.99 6.29 92.50 185.00 233.08 369.99 6.30 92.50 185.00 369.99 6.31 92.50 185.00 369.99 6.32 92.50 185.00 369.99 6.33 92.50 123.47 185.00 369.99 6.34 92.50 123.47 185.00 369.99 6.35 92.50 123.47 185.00 369.99 6.36 92.50 123.47 185.00 369.99 6.37 92.50 123.47 185.00 369.99 6.38 92.50 123.47 185.00 6.39 92.50 123.47 185.00 6.40 92.50 123.47 185.00 6.41 92.50 123.47 185.00 6.42 92.50 123.47 185.00 6.43 92.50 123.47 185.00 6.44 92.50 123.47 185.00 6.45 92.50 185.00 6.46 92.50 185.00 6.47 92.50 185.00 6.48 92.50 185.00 6.49 185.00 6.50 6.51 138.59 6.52 138.59 329.63 6.53 138.59 329.63 6.54 138.59 329.63 6.55 138.59 329.63 6.56 138.59 329.63 6.57 138.59 329.63 6.58 138.59 329.63 6.59 138.59 329.63 6.60 138.59 329.63 369.99 6.61 138.59 329.63 369.99 6.62 329.63 369.99 6.63 329.63 369.99 6.64 369.99 6.65 369.99 6.66 369.99 6.67 369.99 6.68 369.99 6.69 369.99 6.70 369.99 6.71 185.00 369.99 6.72 185.00 369.99 6.73 185.00 369.99 6.74 185.00 369.99 6.75 185.00 369.99 6.76 185.00 369.99 6.77 185.00 369.99 6.78 369.99 6.79 369.99 6.80 369.99 392.00 6.81 369.99 392.00 6.82 392.00 6.83 392.00 6.84 392.00 6.85 392.00 6.86 392.00 6.87 392.00 6.88 392.00 6.89 392.00 6.90 392.00 6.91 392.00 6.92 392.00 6.93 392.00 6.94 185.00 392.00 6.95 185.00 392.00 6.96 185.00 392.00 6.97 185.00 392.00 6.98 185.00 392.00 6.99 185.00 392.00 7.00 185.00 392.00 7.01 185.00 392.00 7.02 164.81 392.00 7.03 164.81 392.00 7.04 164.81 392.00 7.05 164.81 392.00 7.06 164.81 392.00 7.07 164.81 392.00 7.08 164.81 392.00 7.09 164.81 392.00 7.10 164.81 392.00 7.11 164.81 392.00 7.12 164.81 392.00 7.13 164.81 392.00 7.14 164.81 392.00 7.15 164.81 392.00 7.16 164.81 392.00 7.17 164.81 7.18 164.81 7.19 164.81 185.00 7.20 164.81 185.00 7.21 164.81 185.00 7.22 185.00 7.23 185.00 7.24 185.00 7.25 185.00 7.26 185.00 7.27 185.00 7.28 185.00 7.29 185.00 392.00 7.30 185.00 392.00 7.31 164.81 185.00 392.00 7.32 164.81 392.00 7.33 164.81 392.00 7.34 164.81 392.00 7.35 164.81 392.00 7.36 164.81 392.00 7.37 164.81 392.00 7.38 164.81 392.00 7.39 164.81 392.00 7.40 164.81 392.00 7.41 164.81 392.00 7.42 164.81 392.00 7.43 164.81 392.00 7.44 164.81 392.00 7.45 164.81 392.00 7.46 164.81 392.00 7.47 164.81 392.00 7.48 164.81 7.49 164.81 7.50 164.81 7.51 164.81 7.52 164.81 7.53 164.81 7.54 164.81 7.55 164.81 7.56 164.81 7.57 7.58 7.59 7.60 7.61 7.62 493.88 7.63 185.00 493.88 7.64 185.00 493.88 7.65 185.00 493.88 7.66 185.00 246.94 493.88 7.67 185.00 246.94 493.88 7.68 185.00 246.94 369.99 493.88 7.69 185.00 246.94 369.99 493.88 7.70 185.00 246.94 369.99 493.88 7.71 185.00 246.94 369.99 493.88 7.72 185.00 246.94 369.99 493.88 7.73 185.00 246.94 369.99 493.88 7.74 246.94 369.99 493.88 7.75 246.94 369.99 493.88 554.37 7.76 369.99 493.88 554.37 7.77 369.99 493.88 554.37 7.78 369.99 554.37 7.79 369.99 554.37 7.80 164.81 369.99 554.37 7.81 164.81 369.99 554.37 7.82 164.81 369.99 554.37 7.83 164.81 369.99 554.37 7.84 164.81 369.99 554.37 7.85 164.81 369.99 554.37 1479.98 7.86 164.81 369.99 554.37 1479.98 7.87 164.81 277.18 369.99 554.37 1479.98 7.88 164.81 277.18 369.99 554.37 1479.98 7.89 164.81 277.18 369.99 554.37 1479.98 7.90 164.81 277.18 369.99 554.37 1479.98 7.91 164.81 277.18 369.99 554.37 1479.98 7.92 164.81 277.18 369.99 554.37 1479.98 7.93 164.81 277.18 369.99 554.37 1479.98 7.94 164.81 277.18 369.99 554.37 1479.98 7.95 164.81 277.18 369.99 554.37 739.99 783.99 1479.98 7.96 164.81 277.18 369.99 554.37 739.99 783.99 7.97 164.81 277.18 369.99 554.37 739.99 783.99 7.98 164.81 277.18 369.99 554.37 739.99 783.99 7.99 164.81 277.18 369.99 554.37 739.99 783.99 8.00 164.81 277.18 369.99 554.37 739.99 783.99 8.01 164.81 277.18 369.99 554.37 739.99 783.99 8.02 164.81 277.18 369.99 554.37 739.99 783.99 8.03 164.81 277.18 369.99 554.37 739.99 8.04 164.81 277.18 369.99 554.37 739.99 8.05 164.81 277.18 369.99 554.37 8.06 164.81 277.18 369.99 554.37 8.07 164.81 277.18 369.99 554.37 8.08 164.81 277.18 369.99 554.37 8.09 164.81 277.18 369.99 554.37 8.10 164.81 277.18 369.99 554.37 8.11 164.81 277.18 369.99 554.37 8.12 164.81 369.99 8.13 164.81 369.99 8.14 164.81 369.99 8.15 164.81 369.99 8.16 164.81 329.63 369.99 8.17 164.81 329.63 369.99 8.18 164.81 329.63 369.99 8.19 164.81 329.63 369.99 8.20 164.81 329.63 369.99 8.21 164.81 277.18 329.63 369.99 554.37 8.22 164.81 277.18 329.63 369.99 554.37 8.23 164.81 277.18 329.63 369.99 554.37 8.24 164.81 277.18 329.63 369.99 554.37 739.99 8.25 164.81 277.18 369.99 554.37 739.99 8.26 164.81 277.18 369.99 554.37 739.99 8.27 164.81 277.18 369.99 554.37 739.99 8.28 164.81 277.18 369.99 554.37 739.99 8.29 164.81 369.99 554.37 739.99 8.30 164.81 369.99 554.37 739.99 8.31 164.81 369.99 554.37 739.99 8.32 164.81 369.99 554.37 739.99 8.33 164.81 369.99 739.99 8.34 164.81 369.99 739.99 8.35 164.81 369.99 739.99 8.36 164.81 369.99 739.99 8.37 164.81 369.99 739.99 8.38 164.81 369.99 739.99 8.39 164.81 369.99 554.37 739.99 8.40 164.81 369.99 554.37 739.99 8.41 164.81 369.99 554.37 739.99 8.42 369.99 554.37 739.99 8.43 369.99 554.37 739.99 8.44 369.99 554.37 739.99 8.45 369.99 554.37 739.99 8.46 369.99 739.99 8.47 369.99 739.99 8.48 369.99 739.99 8.49 369.99 739.99 8.50 369.99 739.99 8.51 369.99 739.99 8.52 369.99 739.99 8.53 369.99 739.99 8.54 369.99 739.99 8.55 369.99 739.99 8.56 369.99 739.99 8.57 369.99 739.99 8.58 369.99 739.99 8.59 369.99 739.99 8.60 185.00 369.99 739.99 8.61 185.00 369.99 739.99 8.62 185.00 369.99 739.99 8.63 185.00 369.99 739.99 8.64 185.00 369.99 739.99 8.65 185.00 369.99 440.00 739.99 8.66 185.00 369.99 440.00 739.99 8.67 185.00 369.99 440.00 739.99 8.68 185.00 369.99 440.00 739.99 8.69 185.00 369.99 440.00 739.99 8.70 185.00 369.99 440.00 739.99 8.71 185.00 369.99 440.00 739.99 8.72 185.00 369.99 440.00 739.99 8.73 185.00 369.99 440.00 739.99 8.74 185.00 369.99 440.00 739.99 8.75 185.00 369.99 440.00 739.99 8.76 185.00 369.99 440.00 587.33 739.99 8.77 185.00 369.99 440.00 587.33 739.99 8.78 185.00 369.99 440.00 587.33 739.99 8.79 185.00 369.99 440.00 587.33 739.99 8.80 185.00 369.99 440.00 587.33 739.99 8.81 185.00 293.66 369.99 440.00 587.33 739.99 8.82 185.00 293.66 369.99 440.00 587.33 739.99 8.83 185.00 293.66 369.99 440.00 587.33 739.99 8.84 185.00 293.66 369.99 440.00 587.33 739.99 8.85 185.00 293.66 369.99 587.33 8.86 185.00 246.94 293.66 369.99 587.33 8.87 185.00 246.94 293.66 369.99 587.33 8.88 185.00 246.94 369.99 587.33 8.89 123.47 185.00 246.94 369.99 587.33 8.90 123.47 185.00 246.94 369.99 587.33 8.91 123.47 185.00 246.94 369.99 587.33 8.92 123.47 185.00 246.94 369.99 587.33 8.93 123.47 185.00 246.94 369.99 587.33 8.94 123.47 185.00 246.94 369.99 587.33 8.95 123.47 185.00 369.99 587.33 8.96 123.47 185.00 369.99 587.33 8.97 123.47 185.00 369.99 587.33 8.98 123.47 185.00 369.99 587.33 8.99 123.47 185.00 293.66 369.99 587.33 9.00 123.47 185.00 293.66 369.99 587.33 9.01 123.47 185.00 293.66 369.99 587.33 9.02 123.47 185.00 293.66 369.99 587.33 9.03 123.47 185.00 293.66 369.99 587.33 9.04 123.47 185.00 293.66 369.99 587.33 9.05 123.47 185.00 293.66 369.99 587.33 9.06 123.47 185.00 293.66 369.99 587.33 9.07 123.47 185.00 293.66 369.99 587.33 9.08 123.47 185.00 293.66 369.99 587.33 9.09 123.47 185.00 293.66 369.99 587.33 9.10 123.47 185.00 293.66 369.99 587.33 9.11 123.47 185.00 293.66 369.99 587.33 9.12 123.47 185.00 293.66 369.99 587.33 9.13 123.47 185.00 293.66 369.99 587.33 9.14 123.47 185.00 293.66 369.99 587.33 9.15 123.47 185.00 293.66 369.99 587.33 9.16 123.47 185.00 293.66 369.99 587.33 9.17 123.47 185.00 293.66 369.99 587.33 9.18 123.47 185.00 293.66 369.99 587.33 9.19 123.47 185.00 293.66 369.99 587.33 9.20 123.47 185.00 293.66 369.99 587.33 9.21 123.47 185.00 293.66 369.99 587.33 9.22 123.47 185.00 293.66 369.99 587.33 9.23 123.47 185.00 293.66 369.99 587.33 9.24 123.47 185.00 293.66 369.99 587.33 9.25 123.47 185.00 293.66 369.99 587.33 9.26 123.47 185.00 293.66 369.99 587.33 9.27 123.47 185.00 293.66 369.99 587.33 9.28 123.47 185.00 293.66 369.99 587.33 9.29 123.47 185.00 293.66 369.99 587.33 9.30 123.47 185.00 293.66 369.99 587.33 9.31 123.47 185.00 293.66 369.99 587.33 9.32 123.47 185.00 293.66 369.99 9.33 293.66 369.99 9.34 293.66 369.99 9.35 246.94 293.66 349.23 369.99 9.36 246.94 293.66 349.23 369.99 9.37 207.65 246.94 293.66 349.23 369.99 9.38 207.65 246.94 293.66 349.23 9.39 207.65 246.94 293.66 349.23 9.40 207.65 246.94 293.66 349.23 415.30 9.41 207.65 246.94 293.66 349.23 415.30 9.42 207.65 246.94 293.66 349.23 415.30 9.43 207.65 246.94 293.66 349.23 415.30 9.44 207.65 246.94 293.66 349.23 415.30 9.45 246.94 349.23 415.30 9.46 246.94 349.23 415.30 9.47 246.94 349.23 415.30 9.48 246.94 349.23 415.30 9.49 246.94 349.23 415.30 9.50 246.94 349.23 415.30 9.51 207.65 349.23 415.30 9.52 207.65 349.23 415.30 9.53 207.65 349.23 415.30 9.54 207.65 349.23 415.30 9.55 207.65 349.23 415.30 9.56 207.65 349.23 9.57 207.65 349.23 9.58 207.65 349.23 9.59 207.65 349.23 9.60 207.65 349.23 9.61 207.65 349.23 9.62 207.65 246.94 349.23 9.63 207.65 246.94 349.23 9.64 207.65 246.94 9.65 207.65 246.94 9.66 207.65 246.94 9.67 207.65 246.94 9.68 207.65 246.94 9.69 207.65 246.94 9.70 207.65 246.94 9.71 69.30 207.65 246.94 9.72 69.30 207.65 246.94 349.23 9.73 69.30 207.65 246.94 349.23 9.74 69.30 207.65 246.94 349.23 9.75 69.30 207.65 246.94 349.23 9.76 69.30 207.65 246.94 349.23 9.77 69.30 207.65 246.94 349.23 9.78 69.30 207.65 246.94 349.23 9.79 69.30 207.65 349.23 9.80 69.30 207.65 9.81 207.65 9.82 207.65 9.83 1975.53 9.84 185.00 369.99 1318.51 1975.53 9.85 185.00 369.99 1318.51 1975.53 9.86 185.00 369.99 1318.51 1975.53 9.87 185.00 369.99 1318.51 1975.53 9.88 185.00 369.99 1318.51 1975.53 9.89 185.00 277.18 369.99 1318.51 1975.53 9.90 185.00 277.18 369.99 1318.51 9.91 185.00 277.18 369.99 1318.51 9.92 92.50 185.00 277.18 369.99 9.93 92.50 185.00 277.18 369.99 9.94 92.50 185.00 277.18 369.99 9.95 92.50 185.00 277.18 369.99 9.96 92.50 185.00 277.18 369.99 9.97 92.50 185.00 277.18 369.99 9.98 92.50 185.00 277.18 369.99 9.99 92.50 185.00 277.18 369.99 10.00 92.50 185.00 277.18 369.99 10.01 92.50 185.00 277.18 369.99 10.02 92.50 185.00 277.18 369.99 10.03 92.50 185.00 277.18 369.99 10.04 92.50 185.00 277.18 369.99 10.05 92.50 185.00 277.18 369.99 10.06 92.50 185.00 277.18 369.99 10.07 92.50 185.00 277.18 369.99 10.08 92.50 185.00 277.18 369.99 10.09 92.50 185.00 277.18 369.99 10.10 92.50 185.00 277.18 369.99 10.11 92.50 185.00 277.18 369.99 10.12 92.50 185.00 277.18 369.99 10.13 92.50 185.00 277.18 369.99 10.14 92.50 185.00 277.18 369.99 10.15 92.50 185.00 369.99 10.16 92.50 185.00 369.99 10.17 92.50 185.00 369.99 10.18 92.50 185.00 233.08 369.99 10.19 92.50 185.00 233.08 369.99 10.20 92.50 185.00 233.08 369.99 10.21 92.50 185.00 233.08 369.99 10.22 92.50 185.00 233.08 369.99 10.23 92.50 185.00 233.08 369.99 10.24 92.50 185.00 233.08 369.99 10.25 92.50 185.00 233.08 10.26 92.50 185.00 233.08 10.27 92.50 185.00 233.08 10.28 92.50 185.00 233.08 10.29 92.50 185.00 233.08 10.30 92.50 185.00 10.31 92.50 185.00 10.32 92.50 185.00 10.33 92.50 185.00 10.34 92.50 185.00 10.35 92.50 185.00 10.36 92.50 123.47 185.00 10.37 92.50 123.47 185.00 10.38 92.50 123.47 185.00 10.39 92.50 123.47 185.00 10.40 92.50 123.47 185.00 10.41 92.50 123.47 185.00 10.42 92.50 123.47 185.00 10.43 92.50 123.47 185.00 10.44 92.50 123.47 185.00 277.18 10.45 92.50 123.47 185.00 277.18 10.46 92.50 123.47 185.00 277.18 10.47 92.50 123.47 277.18 10.48 92.50 123.47 277.18 10.49 92.50 123.47 277.18 10.50 123.47 277.18 329.63 10.51 277.18 329.63 10.52 185.00 329.63 10.53 185.00 329.63 10.54 185.00 329.63 10.55 185.00 329.63 10.56 138.59 185.00 329.63 10.57 138.59 185.00 329.63 10.58 138.59 185.00 329.63 10.59 138.59 185.00 329.63 10.60 138.59 329.63 10.61 138.59 329.63 10.62 138.59 329.63 10.63 138.59 329.63 10.64 138.59 329.63 10.65 138.59 10.66 138.59 369.99 10.67 138.59 185.00 369.99 10.68 138.59 185.00 369.99 10.69 185.00 369.99 10.70 185.00 369.99 10.71 185.00 369.99 10.72 185.00 369.99 10.73 185.00 369.99 10.74 185.00 369.99 10.75 185.00 369.99 10.76 185.00 369.99 10.77 185.00 369.99 10.78 185.00 369.99 10.79 185.00 369.99 10.80 185.00 369.99 10.81 369.99 10.82 369.99 392.00 10.83 369.99 392.00 10.84 164.81 392.00 10.85 164.81 392.00 10.86 164.81 392.00 10.87 164.81 392.00 10.88 164.81 392.00 10.89 164.81 392.00 10.90 164.81 392.00 1318.51 10.91 164.81 392.00 1318.51 10.92 164.81 392.00 1318.51 10.93 164.81 392.00 1318.51 10.94 164.81 392.00 1318.51 10.95 82.41 164.81 392.00 1318.51 10.96 82.41 164.81 392.00 1318.51 10.97 82.41 164.81 392.00 1318.51 10.98 82.41 164.81 329.63 392.00 1318.51 10.99 82.41 164.81 329.63 392.00 1318.51 11.00 82.41 164.81 329.63 392.00 11.01 82.41 164.81 329.63 392.00 11.02 82.41 164.81 329.63 392.00 11.03 82.41 164.81 329.63 392.00 11.04 82.41 164.81 329.63 392.00 11.05 82.41 164.81 329.63 392.00 11.06 82.41 164.81 329.63 392.00 11.07 82.41 164.81 329.63 392.00 11.08 82.41 164.81 329.63 392.00 11.09 82.41 164.81 329.63 392.00 11.10 82.41 164.81 329.63 392.00 11.11 82.41 164.81 329.63 392.00 11.12 82.41 164.81 329.63 392.00 11.13 82.41 164.81 329.63 392.00 11.14 82.41 164.81 329.63 392.00 11.15 82.41 164.81 329.63 392.00 11.16 82.41 164.81 392.00 11.17 82.41 164.81 392.00 11.18 164.81 392.00 11.19 164.81 392.00 11.20 164.81 392.00 11.21 164.81 392.00 11.22 164.81 392.00 11.23 164.81 392.00 11.24 164.81 392.00 11.25 164.81 392.00 11.26 164.81 392.00 11.27 164.81 392.00 11.28 82.41 164.81 392.00 11.29 82.41 164.81 392.00 11.30 82.41 164.81 392.00 11.31 82.41 164.81 392.00 11.32 82.41 164.81 392.00 11.33 82.41 164.81 392.00 11.34 82.41 164.81 392.00 11.35 82.41 164.81 392.00 11.36 82.41 164.81 392.00 11.37 82.41 164.81 392.00 11.38 164.81 392.00 11.39 164.81 392.00 11.40 164.81 392.00 11.41 164.81 392.00 11.42 164.81 392.00 11.43 164.81 392.00 11.44 164.81 392.00 11.45 164.81 392.00 11.46 369.99 392.00 11.47 369.99 11.48 369.99 11.49 369.99 11.50 369.99 11.51 369.99 11.52 369.99 11.53 369.99 11.54 369.99 11.55 369.99 11.56 369.99 11.57 369.99 11.58 369.99 11.59 369.99 493.88 11.60 369.99 493.88 11.61 369.99 493.88 11.62 369.99 493.88 11.63 369.99 493.88 11.64 246.94 369.99 493.88 11.65 123.47 246.94 369.99 493.88 11.66 123.47 246.94 369.99 493.88 11.67 123.47 246.94 369.99 493.88 11.68 123.47 246.94 369.99 493.88 11.69 123.47 246.94 369.99 493.88 11.70 123.47 246.94 369.99 493.88 11.71 123.47 246.94 493.88 11.72 123.47 246.94 493.88 11.73 123.47 246.94 493.88 11.74 123.47 246.94 493.88 11.75 123.47 246.94 493.88 554.37 11.76 123.47 246.94 493.88 554.37 11.77 123.47 246.94 493.88 554.37 11.78 123.47 246.94 369.99 493.88 554.37 11.79 123.47 246.94 369.99 493.88 554.37 11.80 123.47 246.94 369.99 493.88 554.37 11.81 123.47 369.99 493.88 554.37 11.82 123.47 185.00 369.99 493.88 554.37 11.83 185.00 369.99 493.88 554.37 11.84 185.00 369.99 554.37 11.85 185.00 369.99 554.37 11.86 185.00 369.99 554.37 11.87 185.00 369.99 554.37 11.88 185.00 369.99 554.37 11.89 185.00 369.99 554.37 11.90 92.50 185.00 369.99 554.37 11.91 92.50 185.00 369.99 554.37 11.92 92.50 185.00 369.99 554.37 11.93 92.50 185.00 369.99 554.37 11.94 92.50 185.00 369.99 554.37 11.95 92.50 185.00 369.99 554.37 11.96 92.50 185.00 369.99 554.37 11.97 92.50 185.00 369.99 554.37 11.98 92.50 185.00 369.99 554.37 11.99 92.50 185.00 369.99 554.37 12.00 92.50 185.00 369.99 554.37 12.01 92.50 185.00 369.99 554.37 12.02 92.50 185.00 369.99 554.37 12.03 92.50 185.00 369.99 554.37 12.04 92.50 185.00 369.99 554.37 12.05 92.50 185.00 369.99 554.37 12.06 92.50 185.00 277.18 369.99 554.37 12.07 92.50 185.00 277.18 369.99 554.37 12.08 92.50 185.00 277.18 369.99 554.37 12.09 92.50 185.00 277.18 369.99 554.37 12.10 92.50 185.00 277.18 369.99 554.37 12.11 92.50 185.00 277.18 369.99 554.37 12.12 92.50 138.59 185.00 277.18 369.99 554.37 12.13 92.50 138.59 185.00 277.18 369.99 554.37 12.14 92.50 138.59 185.00 277.18 369.99 554.37 12.15 92.50 138.59 185.00 277.18 369.99 554.37 12.16 92.50 138.59 185.00 277.18 554.37 12.17 92.50 138.59 185.00 277.18 554.37 12.18 92.50 138.59 185.00 277.18 554.37 12.19 92.50 138.59 185.00 277.18 554.37 12.20 92.50 185.00 277.18 554.37 12.21 92.50 185.00 277.18 554.37 12.22 92.50 185.00 277.18 554.37 12.23 92.50 185.00 277.18 554.37 12.24 92.50 185.00 554.37 12.25 92.50 185.00 369.99 554.37 12.26 92.50 185.00 369.99 554.37 12.27 92.50 185.00 369.99 554.37 12.28 92.50 185.00 369.99 554.37 12.29 92.50 185.00 369.99 554.37 739.99 12.30 92.50 369.99 554.37 739.99 12.31 92.50 369.99 554.37 739.99 12.32 92.50 369.99 554.37 739.99 12.33 92.50 369.99 554.37 739.99 12.34 92.50 369.99 554.37 739.99 12.35 185.00 369.99 554.37 739.99 12.36 185.00 369.99 554.37 739.99 12.37 185.00 369.99 554.37 739.99 12.38 185.00 369.99 554.37 739.99 12.39 185.00 369.99 554.37 739.99 12.40 185.00 369.99 554.37 739.99 12.41 185.00 369.99 554.37 739.99 12.42 185.00 369.99 554.37 739.99 12.43 185.00 369.99 554.37 739.99 12.44 185.00 369.99 554.37 739.99 12.45 185.00 369.99 554.37 739.99 12.46 185.00 369.99 554.37 739.99 12.47 185.00 369.99 554.37 739.99 12.48 92.50 185.00 369.99 554.37 739.99 12.49 92.50 185.00 369.99 554.37 739.99 12.50 92.50 185.00 369.99 554.37 739.99 12.51 92.50 185.00 369.99 554.37 739.99 12.52 92.50 185.00 369.99 554.37 739.99 12.53 92.50 185.00 369.99 554.37 739.99 12.54 92.50 185.00 369.99 554.37 739.99 12.55 92.50 185.00 369.99 554.37 739.99 12.56 92.50 185.00 369.99 739.99 12.57 92.50 185.00 369.99 739.99 12.58 92.50 185.00 369.99 739.99 12.59 185.00 369.99 739.99 12.60 185.00 369.99 739.99 12.61 185.00 369.99 739.99 12.62 185.00 369.99 739.99 12.63 185.00 369.99 739.99 12.64 185.00 369.99 739.99 12.65 185.00 369.99 739.99 12.66 185.00 369.99 739.99 12.67 185.00 369.99 739.99 12.68 185.00 369.99 739.99 12.69 185.00 369.99 739.99 12.70 185.00 369.99 739.99 12.71 185.00 369.99 739.99 12.72 185.00 369.99 739.99 12.73 185.00 369.99 739.99 12.74 185.00 369.99 739.99 12.75 185.00 369.99 739.99 12.76 185.00 369.99 739.99 12.77 185.00 369.99 739.99 12.78 185.00 369.99 739.99 12.79 185.00 369.99 739.99 12.80 185.00 369.99 739.99 12.81 185.00 369.99 739.99 12.82 369.99 739.99 12.83 369.99 587.33 739.99 12.84 369.99 587.33 739.99 12.85 369.99 587.33 12.86 369.99 587.33 12.87 369.99 587.33 12.88 369.99 493.88 587.33 12.89 123.47 369.99 493.88 587.33 12.90 123.47 369.99 493.88 587.33 12.91 123.47 369.99 493.88 587.33 12.92 123.47 369.99 493.88 587.33 12.93 123.47 185.00 369.99 493.88 587.33 12.94 123.47 185.00 369.99 493.88 587.33 12.95 123.47 185.00 369.99 493.88 587.33 12.96 123.47 185.00 369.99 493.88 587.33 12.97 123.47 185.00 369.99 493.88 587.33 12.98 123.47 185.00 369.99 493.88 587.33 12.99 123.47 185.00 369.99 493.88 587.33 13.00 123.47 185.00 369.99 493.88 587.33 13.01 123.47 185.00 293.66 493.88 587.33 13.02 123.47 293.66 493.88 587.33 13.03 123.47 293.66 493.88 587.33 13.04 123.47 293.66 493.88 587.33 13.05 123.47 293.66 493.88 587.33 13.06 123.47 293.66 493.88 587.33 13.07 123.47 293.66 493.88 587.33 13.08 123.47 293.66 493.88 587.33 13.09 123.47 293.66 493.88 587.33 13.10 123.47 293.66 493.88 587.33 13.11 123.47 293.66 493.88 587.33 13.12 123.47 293.66 493.88 587.33 13.13 123.47 293.66 493.88 587.33 13.14 123.47 293.66 493.88 587.33 13.15 123.47 293.66 493.88 587.33 13.16 123.47 293.66 493.88 587.33 13.17 123.47 293.66 493.88 587.33 13.18 123.47 293.66 493.88 587.33 13.19 123.47 293.66 493.88 587.33 13.20 123.47 293.66 493.88 587.33 13.21 123.47 293.66 493.88 587.33 13.22 123.47 293.66 369.99 493.88 587.33 13.23 123.47 293.66 369.99 493.88 587.33 13.24 123.47 293.66 369.99 493.88 587.33 13.25 123.47 293.66 369.99 587.33 13.26 123.47 293.66 369.99 587.33 13.27 123.47 293.66 369.99 587.33 13.28 123.47 293.66 369.99 587.33 13.29 123.47 293.66 369.99 587.33 13.30 123.47 293.66 369.99 587.33 13.31 123.47 293.66 369.99 587.33 13.32 123.47 293.66 369.99 587.33 13.33 123.47 293.66 369.99 587.33 13.34 123.47 293.66 369.99 587.33 13.35 123.47 293.66 587.33 13.36 123.47 293.66 493.88 587.33 13.37 123.47 293.66 493.88 587.33 13.38 123.47 293.66 493.88 587.33 13.39 123.47 293.66 493.88 587.33 13.40 123.47 493.88 587.33 13.41 123.47 493.88 587.33 13.42 493.88 587.33 13.43 493.88 13.44 493.88 13.45 493.88 13.46 415.30 493.88 13.47 415.30 493.88 13.48 415.30 493.88 13.49 415.30 493.88 13.50 415.30 493.88 13.51 415.30 493.88 13.52 246.94 415.30 493.88 13.53 246.94 415.30 493.88 13.54 246.94 415.30 493.88 587.33 13.55 246.94 415.30 493.88 587.33 13.56 246.94 415.30 493.88 587.33 13.57 246.94 415.30 493.88 587.33 13.58 246.94 415.30 493.88 587.33 13.59 246.94 415.30 493.88 587.33 13.60 246.94 415.30 493.88 587.33 13.61 415.30 493.88 587.33 987.77 13.62 415.30 493.88 587.33 987.77 13.63 293.66 415.30 493.88 587.33 987.77 13.64 293.66 415.30 493.88 587.33 987.77 13.65 293.66 415.30 493.88 587.33 987.77 13.66 246.94 293.66 415.30 493.88 987.77 13.67 246.94 293.66 415.30 493.88 987.77 13.68 246.94 293.66 415.30 493.88 987.77 13.69 246.94 293.66 415.30 493.88 987.77 13.70 246.94 293.66 415.30 493.88 987.77 13.71 246.94 293.66 415.30 493.88 987.77 13.72 246.94 293.66 493.88 987.77 13.73 246.94 293.66 493.88 987.77 13.74 246.94 293.66 349.23 493.88 987.77 13.75 246.94 293.66 349.23 493.88 987.77 13.76 146.83 246.94 349.23 493.88 987.77 13.77 146.83 246.94 349.23 493.88 987.77 13.78 146.83 246.94 349.23 493.88 987.77 13.79 146.83 246.94 349.23 493.88 987.77 13.80 146.83 246.94 349.23 493.88 987.77 13.81 146.83 246.94 349.23 493.88 987.77 13.82 146.83 246.94 349.23 493.88 987.77 13.83 146.83 246.94 349.23 415.30 493.88 987.77 13.84 146.83 246.94 349.23 415.30 493.88 987.77 13.85 246.94 349.23 415.30 493.88 987.77 13.86 246.94 349.23 415.30 493.88 987.77 13.87 246.94 349.23 415.30 493.88 987.77 13.88 246.94 349.23 415.30 493.88 987.77 13.89 246.94 349.23 415.30 493.88 987.77 13.90 246.94 349.23 415.30 493.88 987.77 13.91 246.94 349.23 415.30 493.88 987.77 13.92 246.94 493.88 987.77 13.93 185.00 369.99 493.88 987.77 13.94 185.00 369.99 493.88 987.77 13.95 185.00 369.99 13.96 185.00 369.99 554.37 13.97 92.50 185.00 369.99 554.37 13.98 92.50 185.00 277.18 369.99 554.37 13.99 92.50 185.00 277.18 369.99 554.37 14.00 92.50 185.00 277.18 369.99 554.37 14.01 92.50 185.00 277.18 369.99 554.37 14.02 92.50 185.00 277.18 369.99 554.37 14.03 92.50 185.00 277.18 369.99 14.04 92.50 185.00 277.18 369.99 14.05 92.50 185.00 369.99 14.06 92.50 185.00 369.99 14.07 92.50 185.00 233.08 369.99 14.08 92.50 185.00 233.08 369.99 14.09 92.50 185.00 233.08 369.99 14.10 92.50 185.00 233.08 369.99 14.11 92.50 185.00 233.08 277.18 369.99 14.12 92.50 185.00 233.08 277.18 369.99 14.13 92.50 185.00 233.08 277.18 369.99 14.14 92.50 185.00 233.08 277.18 369.99 14.15 92.50 185.00 233.08 277.18 369.99 14.16 92.50 185.00 233.08 277.18 369.99 14.17 92.50 185.00 277.18 369.99 14.18 185.00 277.18 369.99 14.19 185.00 277.18 369.99 14.20 185.00 277.18 369.99 14.21 185.00 369.99 14.22 185.00 369.99 14.23 185.00 369.99 14.24 185.00 369.99 14.25 185.00 369.99 14.26 185.00 369.99 14.27 92.50 185.00 369.99 14.28 92.50 185.00 369.99 14.29 92.50 185.00 369.99 14.30 92.50 185.00 369.99 14.31 92.50 185.00 369.99 14.32 92.50 185.00 369.99 14.33 92.50 185.00 369.99 14.34 92.50 185.00 369.99 14.35 92.50 185.00 369.99 14.36 92.50 185.00 369.99 14.37 92.50 185.00 369.99 14.38 92.50 185.00 369.99 14.39 92.50 185.00 369.99 554.37 14.40 92.50 185.00 369.99 554.37 14.41 92.50 185.00 369.99 554.37 14.42 92.50 185.00 554.37 14.43 92.50 185.00 554.37 14.44 92.50 185.00 554.37 14.45 92.50 185.00 554.37 14.46 92.50 185.00 554.37 14.47 92.50 185.00 554.37 14.48 92.50 123.47 185.00 554.37 14.49 92.50 123.47 185.00 554.37 14.50 92.50 123.47 185.00 554.37 14.51 92.50 123.47 185.00 554.37 14.52 123.47 185.00 554.37 14.53 123.47 185.00 554.37 14.54 123.47 185.00 554.37 14.55 123.47 185.00 554.37 14.56 123.47 185.00 14.57 123.47 14.58 123.47 14.59 123.47 14.60 123.47 329.63 14.61 123.47 329.63 14.62 123.47 329.63 14.63 123.47 329.63 14.64 329.63 14.65 329.63 14.66 329.63 14.67 329.63 14.68 329.63 14.69 329.63 14.70 329.63 14.71 329.63 14.72 329.63 14.73 329.63 14.74 369.99 14.75 369.99 14.76 369.99 14.77 369.99 14.78 369.99 14.79 369.99 14.80 369.99 14.81 369.99 14.82 146.83 369.99 14.83 146.83 369.99 14.84 146.83 369.99 14.85 146.83 14.86 146.83 14.87 146.83 14.88 146.83 14.89 14.90 14.91 392.00 14.92 164.81 392.00 14.93 164.81 392.00 14.94 164.81 392.00 14.95 164.81 392.00 14.96 164.81 392.00 14.97 164.81 392.00 14.98 164.81 392.00 14.99 164.81 392.00 15.00 164.81 392.00 15.01 164.81 392.00 15.02 164.81 392.00 15.03 164.81 392.00 15.04 164.81 392.00 15.05 164.81 392.00 15.06 164.81 392.00 15.07 164.81 392.00 15.08 82.41 164.81 392.00 15.09 82.41 164.81 392.00 15.10 82.41 164.81 392.00 15.11 82.41 164.81 392.00 15.12 82.41 164.81 392.00 15.13 82.41 164.81 392.00 15.14 82.41 164.81 392.00 15.15 82.41 164.81 392.00 15.16 82.41 164.81 392.00 15.17 82.41 164.81 392.00 15.18 82.41 164.81 392.00 15.19 82.41 164.81 392.00 15.20 164.81 392.00 15.21 164.81 392.00 15.22 164.81 392.00 15.23 164.81 392.00 659.26 15.24 164.81 659.26 15.25 164.81 659.26 15.26 164.81 659.26 15.27 164.81 659.26 15.28 82.41 164.81 659.26 15.29 82.41 164.81 659.26 15.30 82.41 164.81 659.26 15.31 82.41 164.81 15.32 82.41 164.81 15.33 82.41 164.81 15.34 82.41 164.81 15.35 82.41 164.81 15.36 82.41 164.81 15.37 82.41 164.81 15.38 164.81 15.39 164.81 392.00 15.40 164.81 392.00 15.41 392.00 15.42 392.00 15.43 392.00 15.44 392.00 15.45 392.00 15.46 392.00 15.47 392.00 15.48 392.00 15.49 392.00 15.50 392.00 15.51 392.00 15.52 392.00 15.53 392.00 15.54 392.00 15.55 392.00 15.56 369.99 392.00 15.57 369.99 15.58 146.83 369.99 15.59 146.83 369.99 15.60 146.83 369.99 15.61 146.83 369.99 15.62 146.83 369.99 15.63 146.83 369.99 15.64 146.83 369.99 15.65 146.83 369.99 15.66 146.83 369.99 15.67 146.83 369.99 15.68 146.83 369.99 15.69 146.83 369.99 493.88 15.70 146.83 369.99 493.88 15.71 369.99 493.88 15.72 369.99 493.88 15.73 369.99 493.88 15.74 369.99 493.88 15.75 369.99 493.88 15.76 123.47 369.99 493.88 15.77 123.47 369.99 493.88 15.78 123.47 369.99 493.88 15.79 123.47 369.99 493.88 15.80 123.47 369.99 493.88 15.81 123.47 369.99 493.88 15.82 123.47 369.99 493.88 15.83 123.47 164.81 369.99 493.88 15.84 123.47 164.81 369.99 493.88 15.85 123.47 164.81 369.99 493.88 15.86 123.47 164.81 369.99 493.88 15.87 123.47 164.81 369.99 493.88 15.88 123.47 164.81 369.99 493.88 554.37 15.89 164.81 369.99 493.88 554.37 15.90 369.99 493.88 554.37 15.91 277.18 369.99 493.88 554.37 15.92 277.18 369.99 554.37 15.93 277.18 369.99 554.37 15.94 277.18 369.99 554.37 15.95 277.18 369.99 554.37 15.96 277.18 369.99 554.37 15.97 277.18 369.99 554.37 15.98 277.18 369.99 554.37 15.99 110.00 277.18 369.99 554.37 16.00 110.00 277.18 369.99 554.37 16.01 110.00 277.18 369.99 554.37 16.02 110.00 277.18 369.99 554.37 16.03 110.00 277.18 369.99 554.37 16.04 110.00 277.18 369.99 554.37 16.05 110.00 277.18 369.99 554.37 16.06 110.00 277.18 369.99 554.37 16.07 110.00 277.18 369.99 554.37 16.08 110.00 277.18 369.99 554.37 739.99 1479.98 16.09 110.00 277.18 369.99 554.37 739.99 1479.98 16.10 110.00 277.18 369.99 554.37 739.99 1479.98 16.11 110.00 277.18 369.99 554.37 739.99 1479.98 16.12 110.00 277.18 369.99 554.37 739.99 1479.98 16.13 110.00 277.18 369.99 554.37 739.99 1479.98 16.14 110.00 277.18 369.99 554.37 739.99 1479.98 16.15 110.00 277.18 369.99 554.37 739.99 1479.98 16.16 110.00 277.18 369.99 554.37 739.99 1479.98 16.17 110.00 277.18 369.99 554.37 739.99 1479.98 16.18 110.00 277.18 369.99 554.37 739.99 1479.98 16.19 110.00 277.18 369.99 554.37 739.99 1479.98 16.20 110.00 277.18 369.99 554.37 16.21 110.00 277.18 369.99 554.37 16.22 110.00 277.18 369.99 554.37 16.23 110.00 277.18 369.99 554.37 16.24 110.00 277.18 369.99 554.37 16.25 110.00 277.18 369.99 554.37 16.26 110.00 277.18 369.99 554.37 16.27 110.00 277.18 369.99 554.37 16.28 110.00 277.18 369.99 554.37 16.29 110.00 277.18 554.37 16.30 110.00 277.18 554.37 16.31 110.00 277.18 554.37 16.32 110.00 277.18 554.37 16.33 110.00 277.18 554.37 16.34 110.00 277.18 554.37 16.35 110.00 277.18 369.99 554.37 739.99 16.36 110.00 277.18 369.99 554.37 739.99 16.37 110.00 277.18 369.99 554.37 739.99 16.38 110.00 277.18 369.99 554.37 739.99 16.39 110.00 277.18 369.99 554.37 739.99 16.40 110.00 277.18 369.99 554.37 739.99 16.41 369.99 554.37 739.99 16.42 369.99 554.37 739.99 16.43 369.99 554.37 739.99 16.44 185.00 369.99 554.37 739.99 16.45 185.00 369.99 440.00 554.37 739.99 16.46 185.00 369.99 440.00 554.37 739.99 16.47 185.00 369.99 440.00 554.37 739.99 16.48 185.00 369.99 440.00 554.37 739.99 16.49 185.00 369.99 440.00 739.99 16.50 185.00 369.99 440.00 739.99 16.51 185.00 369.99 440.00 739.99 16.52 185.00 369.99 440.00 739.99 16.53 185.00 369.99 739.99 16.54 185.00 369.99 739.99 16.55 185.00 369.99 739.99 16.56 185.00 369.99 739.99 16.57 185.00 369.99 739.99 16.58 185.00 369.99 739.99 16.59 185.00 369.99 739.99 16.60 185.00 369.99 739.99 16.61 185.00 369.99 739.99 16.62 185.00 369.99 739.99 16.63 185.00 369.99 739.99 16.64 185.00 369.99 739.99 16.65 185.00 369.99 739.99 16.66 185.00 369.99 739.99 16.67 185.00 369.99 739.99 16.68 185.00 369.99 739.99 16.69 185.00 369.99 739.99 16.70 185.00 369.99 739.99 16.71 185.00 369.99 739.99 16.72 185.00 369.99 739.99 16.73 185.00 369.99 739.99 16.74 185.00 369.99 739.99 16.75 185.00 369.99 739.99 16.76 185.00 369.99 739.99 16.77 185.00 369.99 739.99 16.78 185.00 369.99 739.99 16.79 185.00 369.99 739.99 16.80 185.00 369.99 739.99 16.81 185.00 369.99 739.99 16.82 138.59 185.00 369.99 739.99 16.83 138.59 185.00 369.99 739.99 16.84 138.59 185.00 369.99 739.99 16.85 138.59 185.00 369.99 739.99 16.86 138.59 185.00 369.99 739.99 16.87 138.59 185.00 369.99 739.99 1318.51 16.88 138.59 185.00 369.99 587.33 739.99 1318.51 16.89 138.59 185.00 369.99 587.33 1318.51 16.90 138.59 185.00 369.99 587.33 1318.51 16.91 138.59 185.00 293.66 369.99 587.33 1318.51 16.92 185.00 293.66 369.99 587.33 1318.51 16.93 185.00 293.66 369.99 587.33 1318.51 16.94 185.00 293.66 369.99 587.33 1318.51 16.95 123.47 185.00 293.66 369.99 587.33 1318.51 16.96 123.47 185.00 293.66 369.99 587.33 16.97 123.47 185.00 293.66 369.99 587.33 16.98 123.47 185.00 293.66 369.99 587.33 739.99 1479.98 16.99 123.47 185.00 293.66 369.99 587.33 739.99 1244.51 1479.98 17.00 123.47 185.00 293.66 369.99 587.33 739.99 1244.51 1479.98 17.01 123.47 185.00 293.66 369.99 587.33 739.99 1244.51 1479.98 17.02 123.47 185.00 293.66 369.99 587.33 739.99 1244.51 1479.98 17.03 123.47 185.00 293.66 369.99 587.33 739.99 1244.51 1479.98 17.04 123.47 185.00 293.66 369.99 587.33 739.99 1244.51 1479.98 17.05 123.47 185.00 293.66 369.99 587.33 739.99 1244.51 17.06 123.47 185.00 293.66 369.99 587.33 1244.51 17.07 123.47 185.00 293.66 369.99 587.33 1244.51 17.08 123.47 185.00 293.66 369.99 587.33 1244.51 17.09 123.47 185.00 293.66 369.99 587.33 1244.51 17.10 123.47 185.00 293.66 369.99 587.33 1244.51 17.11 123.47 185.00 293.66 369.99 587.33 17.12 123.47 185.00 293.66 369.99 587.33 17.13 123.47 185.00 293.66 369.99 587.33 17.14 123.47 185.00 293.66 369.99 587.33 17.15 123.47 185.00 293.66 369.99 587.33 17.16 123.47 185.00 293.66 369.99 587.33 17.17 123.47 185.00 293.66 369.99 587.33 17.18 123.47 185.00 293.66 369.99 587.33 17.19 123.47 185.00 293.66 369.99 587.33 17.20 123.47 185.00 293.66 369.99 587.33 17.21 123.47 185.00 293.66 369.99 587.33 17.22 123.47 185.00 293.66 369.99 587.33 17.23 123.47 185.00 293.66 369.99 587.33 17.24 123.47 185.00 246.94 293.66 369.99 587.33 17.25 123.47 185.00 246.94 293.66 369.99 587.33 17.26 123.47 185.00 246.94 293.66 369.99 587.33 17.27 123.47 185.00 246.94 293.66 369.99 587.33 17.28 123.47 185.00 246.94 293.66 369.99 587.33 17.29 123.47 185.00 246.94 293.66 369.99 587.33 17.30 123.47 185.00 246.94 293.66 369.99 587.33 17.31 123.47 185.00 246.94 293.66 369.99 587.33 17.32 123.47 185.00 246.94 293.66 369.99 587.33 17.33 123.47 185.00 246.94 293.66 369.99 587.33 17.34 123.47 185.00 246.94 293.66 369.99 587.33 17.35 123.47 185.00 246.94 293.66 369.99 587.33 17.36 123.47 185.00 293.66 369.99 587.33 17.37 123.47 185.00 293.66 369.99 587.33 17.38 123.47 185.00 293.66 369.99 587.33 17.39 123.47 185.00 293.66 369.99 587.33 17.40 123.47 185.00 293.66 369.99 587.33 17.41 123.47 185.00 293.66 369.99 587.33 17.42 123.47 185.00 293.66 369.99 587.33 17.43 123.47 185.00 293.66 587.33 17.44 123.47 293.66 349.23 17.45 123.47 349.23 17.46 123.47 349.23 17.47 349.23 17.48 349.23 17.49 349.23 17.50 349.23 17.51 349.23 17.52 69.30 138.59 349.23 17.53 69.30 138.59 349.23 17.54 69.30 138.59 349.23 17.55 69.30 138.59 349.23 17.56 69.30 138.59 349.23 17.57 69.30 138.59 349.23 17.58 69.30 138.59 349.23 17.59 69.30 138.59 246.94 349.23 17.60 138.59 246.94 349.23 17.61 246.94 349.23 17.62 246.94 349.23 17.63 207.65 246.94 349.23 17.64 207.65 246.94 349.23 17.65 207.65 246.94 349.23 17.66 207.65 246.94 349.23 17.67 207.65 246.94 349.23 17.68 207.65 349.23 17.69 69.30 207.65 349.23 17.70 69.30 207.65 349.23 17.71 69.30 207.65 349.23 17.72 69.30 207.65 349.23 17.73 69.30 207.65 349.23 17.74 69.30 207.65 349.23 17.75 69.30 207.65 349.23 17.76 69.30 207.65 293.66 349.23 17.77 69.30 207.65 293.66 349.23 17.78 69.30 207.65 293.66 349.23 17.79 69.30 207.65 293.66 349.23 17.80 69.30 207.65 293.66 349.23 17.81 69.30 207.65 293.66 349.23 17.82 69.30 207.65 293.66 349.23 17.83 69.30 207.65 293.66 349.23 17.84 69.30 207.65 293.66 349.23 17.85 69.30 207.65 293.66 349.23 17.86 69.30 207.65 349.23 17.87 69.30 207.65 349.23 17.88 69.30 207.65 349.23 17.89 69.30 207.65 349.23 17.90 69.30 207.65 349.23 17.91 69.30 207.65 349.23 17.92 69.30 207.65 349.23 369.99 17.93 69.30 207.65 369.99 17.94 207.65 369.99 17.95 185.00 369.99 17.96 185.00 369.99 17.97 185.00 369.99 17.98 185.00 369.99 17.99 185.00 369.99 18.00 92.50 185.00 369.99 18.01 92.50 185.00 369.99 18.02 92.50 185.00 369.99 18.03 92.50 185.00 369.99 1318.51 18.04 92.50 185.00 369.99 1318.51 18.05 92.50 185.00 369.99 415.30 1318.51 18.06 92.50 185.00 369.99 415.30 1318.51 18.07 92.50 185.00 369.99 415.30 1318.51 18.08 92.50 185.00 369.99 415.30 1318.51 18.09 92.50 185.00 369.99 415.30 1318.51 18.10 92.50 185.00 369.99 415.30 1318.51 18.11 92.50 185.00 369.99 415.30 1318.51 18.12 92.50 185.00 369.99 415.30 1318.51 18.13 92.50 185.00 369.99 415.30 1318.51 18.14 92.50 185.00 369.99 415.30 18.15 92.50 185.00 369.99 415.30 18.16 92.50 185.00 369.99 415.30 18.17 92.50 185.00 369.99 415.30 18.18 92.50 185.00 369.99 415.30 18.19 92.50 185.00 369.99 415.30 18.20 92.50 185.00 369.99 415.30 18.21 92.50 185.00 369.99 415.30 18.22 92.50 185.00 369.99 415.30 18.23 92.50 185.00 369.99 18.24 92.50 185.00 369.99 18.25 92.50 185.00 369.99 18.26 92.50 185.00 369.99 18.27 92.50 185.00 369.99 18.28 92.50 185.00 369.99 18.29 92.50 185.00 369.99 18.30 92.50 185.00 369.99 18.31 92.50 185.00 369.99 18.32 92.50 185.00 369.99 18.33 92.50 185.00 369.99 18.34 92.50 185.00 369.99 18.35 92.50 185.00 369.99 18.36 92.50 185.00 369.99 18.37 92.50 185.00 369.99 18.38 92.50 185.00 369.99 18.39 92.50 185.00 369.99 18.40 92.50 185.00 369.99 18.41 92.50 185.00 369.99 18.42 92.50 185.00 369.99 18.43 92.50 185.00 369.99 18.44 92.50 185.00 369.99 587.33 18.45 92.50 185.00 369.99 587.33 18.46 92.50 185.00 369.99 587.33 18.47 92.50 185.00 369.99 587.33 18.48 92.50 185.00 369.99 587.33 18.49 92.50 185.00 369.99 587.33 18.50 92.50 185.00 369.99 587.33 18.51 92.50 185.00 369.99 587.33 18.52 92.50 185.00 369.99 587.33 18.53 92.50 185.00 369.99 587.33 18.54 92.50 185.00 369.99 587.33 18.55 92.50 185.00 369.99 587.33 18.56 92.50 185.00 369.99 587.33 18.57 92.50 185.00 369.99 587.33 18.58 92.50 185.00 369.99 587.33 659.26 18.59 92.50 185.00 554.37 587.33 659.26 18.60 92.50 185.00 554.37 587.33 659.26 18.61 92.50 185.00 554.37 587.33 659.26 18.62 185.00 554.37 587.33 659.26 18.63 185.00 554.37 659.26 18.64 185.00 554.37 659.26 18.65 554.37 659.26 18.66 277.18 554.37 659.26 18.67 277.18 554.37 659.26 18.68 277.18 554.37 587.33 659.26 18.69 92.50 277.18 587.33 659.26 18.70 92.50 277.18 587.33 659.26 18.71 92.50 277.18 587.33 659.26 18.72 92.50 277.18 587.33 659.26 18.73 92.50 277.18 369.99 587.33 659.26 739.99 18.74 92.50 369.99 587.33 659.26 739.99 18.75 92.50 369.99 659.26 739.99 18.76 92.50 369.99 659.26 739.99 18.77 92.50 185.00 369.99 659.26 739.99 18.78 92.50 185.00 369.99 659.26 739.99 18.79 92.50 185.00 369.99 659.26 739.99 18.80 92.50 185.00 293.66 369.99 659.26 739.99 18.81 92.50 185.00 293.66 369.99 659.26 739.99 18.82 92.50 185.00 293.66 369.99 659.26 739.99 18.83 92.50 185.00 293.66 369.99 659.26 739.99 18.84 92.50 185.00 293.66 369.99 659.26 739.99 18.85 92.50 185.00 293.66 369.99 659.26 739.99 18.86 92.50 185.00 293.66 369.99 659.26 739.99 18.87 92.50 185.00 293.66 369.99 659.26 739.99 18.88 92.50 185.00 293.66 369.99 659.26 739.99 18.89 92.50 185.00 293.66 369.99 659.26 739.99 783.99 18.90 92.50 185.00 369.99 659.26 739.99 783.99 18.91 92.50 185.00 369.99 659.26 739.99 783.99 18.92 92.50 185.00 369.99 659.26 739.99 783.99 18.93 92.50 185.00 369.99 659.26 739.99 783.99 18.94 185.00 369.99 659.26 739.99 783.99 18.95 185.00 369.99 659.26 739.99 783.99 18.96 185.00 369.99 659.26 739.99 783.99 18.97 185.00 369.99 659.26 783.99 18.98 185.00 369.99 659.26 783.99 18.99 185.00 369.99 783.99 19.00 185.00 369.99 783.99 19.01 185.00 369.99 783.99 19.02 185.00 783.99 19.03 185.00 783.99 19.04 185.00 783.99 19.05 185.00 783.99 19.06 185.00 783.99 19.07 185.00 783.99 19.08 185.00 329.63 783.99 19.09 92.50 185.00 329.63 783.99 19.10 92.50 185.00 329.63 783.99 19.11 92.50 185.00 329.63 783.99 19.12 92.50 185.00 329.63 783.99 19.13 92.50 185.00 329.63 783.99 19.14 92.50 185.00 329.63 783.99 19.15 92.50 185.00 329.63 783.99 19.16 92.50 185.00 329.63 783.99 19.17 92.50 185.00 329.63 783.99 19.18 185.00 329.63 783.99 19.19 185.00 329.63 783.99 19.20 185.00 329.63 783.99 19.21 185.00 329.63 783.99 19.22 185.00 329.63 783.99 19.23 185.00 329.63 739.99 783.99 19.24 185.00 329.63 739.99 783.99 19.25 185.00 329.63 739.99 783.99 19.26 185.00 329.63 369.99 739.99 783.99 19.27 185.00 329.63 369.99 739.99 783.99 19.28 185.00 369.99 739.99 783.99 19.29 185.00 369.99 739.99 783.99 19.30 185.00 369.99 739.99 783.99 19.31 185.00 369.99 739.99 783.99 19.32 185.00 369.99 739.99 783.99 19.33 185.00 369.99 739.99 783.99 19.34 185.00 369.99 739.99 783.99 19.35 185.00 369.99 739.99 783.99 19.36 185.00 369.99 739.99 783.99 19.37 185.00 369.99 739.99 783.99 19.38 185.00 369.99 739.99 783.99 19.39 185.00 369.99 739.99 783.99 19.40 185.00 369.99 739.99 783.99 19.41 185.00 369.99 739.99 783.99 19.42 185.00 329.63 369.99 739.99 783.99 19.43 185.00 329.63 369.99 739.99 783.99 19.44 185.00 329.63 783.99 19.45 185.00 329.63 783.99 19.46 185.00 329.63 783.99 19.47 185.00 329.63 783.99 19.48 185.00 329.63 783.99 19.49 185.00 329.63 783.99 19.50 185.00 329.63 783.99 19.51 185.00 329.63 783.99 19.52 185.00 329.63 783.99 19.53 185.00 329.63 739.99 783.99 19.54 185.00 329.63 739.99 783.99 19.55 185.00 329.63 739.99 783.99 19.56 185.00 369.99 739.99 783.99 19.57 185.00 369.99 739.99 783.99 19.58 185.00 369.99 739.99 783.99 19.59 185.00 369.99 739.99 783.99 19.60 185.00 369.99 739.99 783.99 19.61 185.00 329.63 369.99 739.99 783.99 19.62 185.00 329.63 369.99 739.99 783.99 19.63 185.00 329.63 369.99 739.99 783.99 19.64 185.00 329.63 369.99 739.99 783.99 19.65 185.00 329.63 369.99 587.33 739.99 783.99 19.66 185.00 329.63 369.99 587.33 739.99 783.99 19.67 185.00 329.63 369.99 587.33 739.99 783.99 19.68 185.00 329.63 369.99 587.33 739.99 783.99 19.69 185.00 329.63 369.99 587.33 739.99 783.99 19.70 185.00 329.63 369.99 587.33 739.99 783.99 19.71 185.00 329.63 369.99 587.33 739.99 783.99 19.72 185.00 369.99 587.33 739.99 783.99 19.73 185.00 369.99 587.33 739.99 783.99 19.74 185.00 246.94 369.99 587.33 19.75 185.00 246.94 369.99 587.33 19.76 185.00 246.94 369.99 587.33 19.77 185.00 246.94 369.99 587.33 19.78 185.00 246.94 369.99 587.33 19.79 185.00 246.94 369.99 587.33 19.80 185.00 246.94 369.99 587.33 19.81 185.00 246.94 369.99 587.33 19.82 185.00 246.94 369.99 587.33 19.83 185.00 246.94 369.99 587.33 19.84 185.00 246.94 369.99 587.33 19.85 185.00 369.99 587.33 19.86 185.00 369.99 587.33 19.87 185.00 587.33 19.88 185.00 554.37 587.33 19.89 554.37 587.33 19.90 554.37 587.33 19.91 554.37 19.92 554.37 19.93 554.37 19.94 554.37 19.95 554.37 19.96 185.00 554.37 19.97 185.00 369.99 554.37 19.98 185.00 233.08 369.99 554.37 19.99 185.00 233.08 369.99 554.37 20.00 185.00 233.08 369.99 554.37 20.01 185.00 233.08 369.99 554.37 20.02 185.00 233.08 369.99 554.37 20.03 185.00 233.08 369.99 554.37 20.04 185.00 233.08 369.99 554.37 20.05 185.00 233.08 369.99 554.37 20.06 185.00 233.08 369.99 554.37 20.07 185.00 233.08 369.99 554.37 20.08 185.00 233.08 369.99 554.37 20.09 185.00 233.08 369.99 554.37 20.10 185.00 554.37 20.11 185.00 554.37 20.12 185.00 554.37 20.13 185.00 554.37 20.14 185.00 554.37 20.15 185.00 554.37 20.16 185.00 554.37 20.17 185.00 554.37 20.18 185.00 554.37 20.19 185.00 369.99 554.37 20.20 185.00 369.99 554.37 20.21 185.00 369.99 554.37 20.22 185.00 369.99 554.37 20.23 185.00 369.99 554.37 20.24 185.00 369.99 554.37 20.25 185.00 369.99 554.37 20.26 185.00 369.99 554.37 20.27 185.00 369.99 554.37 20.28 185.00 369.99 554.37 20.29 185.00 369.99 554.37 20.30 185.00 369.99 554.37 20.31 185.00 369.99 554.37 20.32 185.00 369.99 554.37 20.33 185.00 369.99 554.37 20.34 185.00 369.99 466.16 554.37 20.35 185.00 369.99 466.16 554.37 20.36 185.00 466.16 554.37 20.37 185.00 466.16 554.37 20.38 185.00 466.16 554.37 20.39 185.00 466.16 554.37 20.40 185.00 466.16 554.37 20.41 185.00 466.16 554.37 20.42 185.00 466.16 554.37 20.43 185.00 466.16 554.37 20.44 185.00 466.16 554.37 20.45 185.00 466.16 554.37 20.46 185.00 466.16 554.37 20.47 185.00 466.16 554.37 20.48 185.00 466.16 554.37 20.49 466.16 493.88 554.37 20.50 466.16 493.88 20.51 466.16 493.88 20.52 466.16 493.88 20.53 466.16 493.88 20.54 493.88 20.55 185.00 369.99 493.88 20.56 185.00 369.99 493.88 20.57 185.00 369.99 493.88 20.58 185.00 369.99 493.88 20.59 185.00 369.99 493.88 20.60 185.00 369.99 493.88 20.61 185.00 369.99 493.88 20.62 185.00 369.99 493.88 20.63 493.88 554.37 20.64 493.88 554.37 20.65 493.88 554.37 20.66 493.88 554.37 20.67 493.88 554.37 20.68 493.88 554.37 20.69 493.88 554.37 20.70 493.88 554.37 20.71 493.88 554.37 20.72 493.88 554.37 20.73 493.88 554.37 20.74 493.88 554.37 20.75 369.99 493.88 554.37 20.76 369.99 493.88 554.37 20.77 369.99 493.88 554.37 20.78 369.99 493.88 554.37 20.79 369.99 493.88 554.37 20.80 369.99 493.88 554.37 659.26 20.81 369.99 493.88 554.37 659.26 20.82 369.99 493.88 554.37 659.26 20.83 369.99 493.88 554.37 659.26 20.84 369.99 554.37 659.26 20.85 369.99 554.37 659.26 20.86 277.18 369.99 554.37 659.26 20.87 92.50 185.00 277.18 369.99 554.37 659.26 20.88 92.50 185.00 277.18 369.99 554.37 659.26 20.89 92.50 185.00 277.18 369.99 554.37 659.26 20.90 92.50 185.00 277.18 369.99 554.37 659.26 20.91 92.50 185.00 277.18 369.99 554.37 659.26 20.92 92.50 185.00 277.18 369.99 554.37 659.26 20.93 92.50 185.00 277.18 369.99 554.37 659.26 20.94 92.50 185.00 277.18 369.99 554.37 659.26 20.95 92.50 185.00 277.18 369.99 554.37 659.26 20.96 92.50 185.00 277.18 369.99 554.37 659.26 20.97 92.50 185.00 277.18 369.99 554.37 659.26 20.98 92.50 185.00 277.18 369.99 554.37 659.26 20.99 92.50 185.00 277.18 369.99 554.37 659.26 21.00 92.50 185.00 277.18 369.99 554.37 659.26 21.01 92.50 185.00 277.18 369.99 554.37 659.26 21.02 92.50 185.00 277.18 369.99 554.37 659.26 21.03 92.50 185.00 277.18 369.99 554.37 659.26 21.04 92.50 185.00 277.18 369.99 554.37 659.26 21.05 92.50 185.00 277.18 369.99 659.26 21.06 92.50 185.00 277.18 369.99 659.26 21.07 92.50 185.00 277.18 369.99 659.26 21.08 92.50 185.00 277.18 369.99 659.26 21.09 92.50 185.00 277.18 369.99 659.26 21.10 92.50 185.00 277.18 369.99 659.26 21.11 92.50 185.00 277.18 369.99 659.26 21.12 92.50 185.00 277.18 369.99 659.26 21.13 92.50 185.00 277.18 369.99 659.26 21.14 92.50 185.00 277.18 369.99 659.26 21.15 92.50 185.00 277.18 369.99 659.26 21.16 92.50 185.00 277.18 369.99 587.33 659.26 21.17 92.50 185.00 277.18 369.99 587.33 659.26 21.18 185.00 369.99 587.33 659.26 21.19 185.00 369.99 587.33 659.26 21.20 185.00 369.99 587.33 659.26 21.21 185.00 246.94 369.99 587.33 659.26 21.22 185.00 246.94 369.99 587.33 659.26 21.23 185.00 246.94 369.99 587.33 659.26 21.24 185.00 246.94 369.99 587.33 659.26 21.25 185.00 246.94 369.99 587.33 659.26 21.26 185.00 246.94 369.99 587.33 659.26 21.27 185.00 246.94 369.99 587.33 659.26 21.28 185.00 246.94 369.99 587.33 659.26 21.29 185.00 246.94 369.99 587.33 659.26 21.30 185.00 246.94 369.99 587.33 659.26 21.31 185.00 369.99 587.33 659.26 21.32 185.00 369.99 587.33 659.26 21.33 185.00 369.99 587.33 659.26 21.34 185.00 369.99 587.33 659.26 21.35 185.00 369.99 587.33 659.26 21.36 185.00 369.99 587.33 659.26 21.37 185.00 369.99 587.33 659.26 21.38 185.00 369.99 587.33 659.26 21.39 185.00 369.99 587.33 659.26 21.40 185.00 369.99 587.33 659.26 21.41 185.00 369.99 587.33 659.26 21.42 185.00 369.99 587.33 659.26 21.43 185.00 369.99 587.33 659.26 21.44 185.00 369.99 587.33 659.26 21.45 185.00 369.99 587.33 659.26 21.46 185.00 369.99 587.33 659.26 21.47 185.00 246.94 369.99 587.33 659.26 21.48 185.00 246.94 369.99 587.33 659.26 21.49 185.00 246.94 369.99 587.33 659.26 21.50 185.00 246.94 369.99 587.33 659.26 21.51 185.00 246.94 369.99 587.33 21.52 185.00 246.94 369.99 587.33 21.53 185.00 246.94 369.99 587.33 21.54 185.00 246.94 369.99 587.33 21.55 185.00 246.94 369.99 587.33 21.56 185.00 246.94 369.99 587.33 21.57 185.00 246.94 369.99 493.88 587.33 21.58 246.94 369.99 493.88 587.33 21.59 246.94 369.99 493.88 587.33 21.60 196.00 246.94 493.88 587.33 21.61 196.00 246.94 493.88 587.33 21.62 196.00 246.94 493.88 21.63 196.00 246.94 493.88 21.64 196.00 493.88 21.65 196.00 493.88 21.66 196.00 493.88 21.67 196.00 493.88 21.68 196.00 493.88 21.69 196.00 493.88 21.70 196.00 493.88 21.71 196.00 493.88 21.72 196.00 493.88 21.73 196.00 493.88 21.74 369.99 466.16 493.88 21.75 369.99 466.16 493.88 21.76 369.99 466.16 493.88 21.77 369.99 466.16 493.88 21.78 185.00 369.99 466.16 493.88 21.79 185.00 369.99 466.16 21.80 185.00 369.99 466.16 21.81 185.00 369.99 466.16 21.82 185.00 369.99 466.16 21.83 185.00 369.99 466.16 21.84 185.00 369.99 466.16 21.85 185.00 369.99 466.16 21.86 185.00 369.99 466.16 21.87 185.00 369.99 466.16 21.88 92.50 185.00 369.99 466.16 659.26 21.89 92.50 185.00 369.99 466.16 659.26 21.90 92.50 185.00 369.99 466.16 659.26 21.91 92.50 185.00 369.99 466.16 493.88 659.26 21.92 92.50 185.00 369.99 466.16 493.88 659.26 21.93 92.50 185.00 369.99 466.16 493.88 659.26 21.94 92.50 185.00 369.99 466.16 493.88 659.26 21.95 92.50 185.00 466.16 493.88 659.26 21.96 92.50 185.00 466.16 493.88 659.26 21.97 185.00 466.16 493.88 21.98 185.00 466.16 21.99 185.00 466.16 22.00 185.00 466.16 22.01 185.00 466.16 22.02 185.00 466.16 22.03 185.00 466.16 22.04 185.00 466.16 22.05 22.06 22.07 22.08 22.09 22.10 22.11 22.12 22.13 22.14 22.15 22.16 22.17 22.18 22.19 22.20 22.21 22.22 22.23 22.24 22.25 22.26 22.27 22.28 22.29 22.30 22.31 22.32 22.33 22.34 22.35 22.36 22.37 22.38 22.39 22.40 22.41 22.42 22.43 22.44 22.45 22.46 22.47 22.48 22.49 22.50 22.51 22.52 22.53 22.54 22.55 22.56 22.57 22.58 22.59 22.60 22.61 22.62 22.63 22.64 22.65 22.66 22.67 22.68 22.69 22.70 22.71 22.72 22.73 22.74 22.75 22.76 22.77 22.78 22.79 22.80 22.81 22.82 22.83 22.84 22.85 22.86 22.87 22.88 22.89 22.90 22.91 22.92 22.93 22.94 22.95 22.96 22.97 22.98 22.99 mir_eval-0.8.2/tests/data/multipitch/est09.txt000066400000000000000000003243651475740344600213140ustar00rootroot000000000000000.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.30 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.40 0.41 0.42 0.43 0.44 0.45 0.46 0.47 0.48 0.49 0.50 0.51 0.52 0.53 246.94 0.54 246.94 0.55 246.94 0.56 246.94 0.57 246.94 0.58 246.94 0.59 246.94 0.60 246.94 0.61 246.94 0.62 246.94 0.63 246.94 0.64 246.94 0.65 246.94 0.66 246.94 0.67 246.94 0.68 246.94 0.69 246.94 0.70 246.94 0.71 246.94 0.72 246.94 0.73 246.94 0.74 246.94 0.75 246.94 0.76 246.94 0.77 246.94 0.78 246.94 0.79 246.94 0.80 246.94 0.81 246.94 0.82 246.94 0.83 246.94 0.84 246.94 0.85 246.94 0.86 246.94 0.87 246.94 0.88 246.94 0.89 246.94 0.90 246.94 0.91 246.94 0.92 246.94 0.93 246.94 0.94 0.95 277.18 0.96 277.18 0.97 277.18 0.98 277.18 0.99 277.18 1.00 277.18 1.01 277.18 1.02 277.18 1.03 110.00 277.18 1.04 110.00 277.18 1.05 110.00 277.18 1.06 110.00 277.18 1.07 110.00 277.18 1.08 110.00 277.18 1.09 110.00 277.18 1.10 110.00 277.18 1.11 110.00 277.18 1.12 110.00 277.18 1.13 110.00 277.18 1.14 110.00 277.18 1.15 110.00 277.18 1.16 110.00 277.18 1.17 110.00 277.18 1.18 110.00 277.18 1.19 110.00 277.18 1.20 110.00 277.18 1.21 110.00 277.18 1.22 110.00 277.18 1.23 110.00 277.18 1.24 110.00 277.18 1.25 110.00 277.18 1.26 110.00 277.18 1.27 110.00 277.18 1.28 110.00 277.18 1.29 110.00 277.18 1.30 110.00 277.18 1.31 110.00 220.00 277.18 440.00 1.32 110.00 220.00 277.18 440.00 1.33 110.00 220.00 277.18 440.00 1.34 110.00 220.00 277.18 440.00 1.35 110.00 220.00 277.18 440.00 1.36 110.00 220.00 277.18 440.00 1.37 110.00 220.00 277.18 440.00 1.38 110.00 220.00 277.18 440.00 1.39 110.00 220.00 277.18 440.00 1.40 110.00 220.00 277.18 440.00 1.41 110.00 220.00 277.18 440.00 1.42 110.00 220.00 277.18 440.00 1.43 110.00 220.00 277.18 440.00 1.44 110.00 220.00 277.18 440.00 1.45 220.00 277.18 440.00 1.46 220.00 277.18 440.00 1.47 220.00 277.18 440.00 1.48 220.00 277.18 440.00 1.49 220.00 277.18 440.00 1.50 220.00 277.18 440.00 1.51 220.00 277.18 440.00 1.52 220.00 277.18 440.00 1.53 220.00 277.18 440.00 1.54 220.00 277.18 440.00 1.55 220.00 277.18 440.00 1.56 220.00 277.18 440.00 1.57 220.00 277.18 440.00 1.58 220.00 277.18 440.00 1.59 220.00 277.18 440.00 1.60 220.00 277.18 440.00 1.61 220.00 277.18 440.00 1.62 220.00 277.18 440.00 1.63 220.00 277.18 440.00 1.64 220.00 277.18 440.00 1.65 220.00 277.18 440.00 1.66 220.00 277.18 440.00 1.67 277.18 415.30 440.00 1.68 415.30 440.00 1.69 415.30 440.00 1.70 415.30 440.00 1.71 110.00 415.30 440.00 1.72 110.00 415.30 440.00 1.73 110.00 415.30 440.00 1.74 110.00 415.30 440.00 1.75 110.00 415.30 440.00 1.76 110.00 415.30 440.00 1.77 110.00 440.00 1.78 110.00 1.79 110.00 1.80 110.00 1.81 1.82 1.83 1.84 1.85 1.86 1.87 1.88 1.89 1.90 1.91 1.92 1.93 207.65 1.94 207.65 1.95 207.65 1.96 207.65 1.97 207.65 1.98 207.65 1.99 207.65 2.00 207.65 2.01 207.65 2.02 2.03 369.99 2.04 369.99 2.05 185.00 369.99 2.06 185.00 369.99 2.07 185.00 369.99 2.08 185.00 369.99 2.09 185.00 369.99 2.10 185.00 369.99 2.11 185.00 369.99 2.12 185.00 369.99 2.13 185.00 369.99 2.14 185.00 369.99 2.15 185.00 369.99 2.16 185.00 369.99 2.17 185.00 369.99 987.77 2.18 185.00 369.99 987.77 2.19 185.00 369.99 987.77 2.20 185.00 369.99 987.77 2.21 185.00 369.99 987.77 2.22 185.00 369.99 987.77 2.23 185.00 369.99 987.77 2.24 185.00 369.99 987.77 2.25 185.00 369.99 987.77 2.26 185.00 369.99 987.77 2.27 185.00 369.99 987.77 2.28 185.00 369.99 987.77 2.29 185.00 369.99 987.77 2.30 185.00 369.99 987.77 2.31 185.00 369.99 987.77 2.32 185.00 369.99 987.77 2.33 185.00 369.99 987.77 2.34 185.00 369.99 987.77 2.35 185.00 369.99 987.77 2.36 185.00 369.99 987.77 2.37 185.00 369.99 987.77 2.38 185.00 369.99 987.77 2.39 185.00 369.99 987.77 2.40 185.00 369.99 987.77 2.41 185.00 369.99 987.77 2.42 185.00 369.99 987.77 2.43 185.00 369.99 987.77 2.44 185.00 369.99 987.77 2.45 185.00 369.99 987.77 2.46 185.00 369.99 987.77 2.47 185.00 369.99 987.77 2.48 110.00 185.00 220.00 329.63 369.99 987.77 2.49 55.00 110.00 164.81 185.00 220.00 329.63 369.99 987.77 2.50 55.00 110.00 164.81 220.00 329.63 369.99 987.77 2.51 55.00 110.00 164.81 220.00 329.63 369.99 554.37 987.77 1108.73 2.52 55.00 110.00 164.81 220.00 277.18 329.63 369.99 554.37 987.77 1108.73 2.53 55.00 110.00 164.81 220.00 277.18 329.63 369.99 554.37 987.77 1108.73 2.54 55.00 110.00 164.81 220.00 277.18 329.63 369.99 554.37 1108.73 2.55 55.00 110.00 164.81 220.00 277.18 329.63 369.99 554.37 1108.73 2.56 55.00 110.00 164.81 220.00 277.18 329.63 369.99 554.37 1108.73 2.57 55.00 110.00 164.81 220.00 277.18 329.63 369.99 554.37 1108.73 2.58 55.00 110.00 164.81 220.00 277.18 329.63 554.37 1108.73 2.59 55.00 110.00 164.81 220.00 277.18 329.63 554.37 1108.73 2.60 55.00 110.00 164.81 220.00 277.18 329.63 554.37 1108.73 2.61 55.00 110.00 164.81 220.00 277.18 329.63 554.37 1108.73 2.62 55.00 110.00 164.81 220.00 277.18 329.63 554.37 1108.73 2.63 55.00 110.00 164.81 220.00 277.18 329.63 554.37 1108.73 2.64 55.00 110.00 164.81 277.18 329.63 554.37 1108.73 2.65 55.00 110.00 164.81 277.18 329.63 554.37 1108.73 2.66 55.00 110.00 164.81 277.18 329.63 554.37 1108.73 2.67 55.00 110.00 164.81 277.18 329.63 554.37 1108.73 2.68 55.00 110.00 164.81 277.18 329.63 554.37 1108.73 2.69 55.00 110.00 164.81 277.18 329.63 554.37 1108.73 2.70 55.00 110.00 164.81 220.00 277.18 329.63 554.37 1108.73 2.71 55.00 110.00 164.81 220.00 277.18 329.63 554.37 1108.73 2.72 110.00 164.81 220.00 277.18 329.63 554.37 1108.73 2.73 110.00 164.81 220.00 277.18 329.63 554.37 1108.73 2.74 110.00 164.81 220.00 277.18 554.37 1108.73 2.75 110.00 164.81 220.00 277.18 554.37 1108.73 2.76 110.00 164.81 220.00 277.18 554.37 1108.73 2.77 110.00 164.81 220.00 277.18 554.37 1108.73 2.78 110.00 164.81 220.00 277.18 554.37 1108.73 2.79 110.00 164.81 277.18 329.63 554.37 1108.73 2.80 110.00 164.81 277.18 329.63 554.37 1108.73 2.81 110.00 164.81 277.18 329.63 554.37 1108.73 2.82 110.00 164.81 277.18 329.63 554.37 1108.73 2.83 110.00 164.81 277.18 329.63 554.37 1108.73 2.84 110.00 164.81 277.18 329.63 554.37 1108.73 2.85 110.00 164.81 277.18 329.63 554.37 1108.73 2.86 110.00 164.81 220.00 277.18 329.63 554.37 1108.73 2.87 110.00 164.81 220.00 277.18 329.63 440.00 554.37 880.00 1108.73 2.88 110.00 164.81 220.00 277.18 329.63 440.00 554.37 880.00 1108.73 2.89 110.00 164.81 220.00 277.18 329.63 440.00 554.37 880.00 1108.73 2.90 110.00 164.81 220.00 277.18 329.63 440.00 554.37 880.00 1108.73 2.91 110.00 164.81 220.00 277.18 329.63 440.00 554.37 880.00 1108.73 2.92 110.00 164.81 220.00 277.18 329.63 440.00 554.37 880.00 1108.73 2.93 110.00 164.81 220.00 277.18 440.00 554.37 880.00 2.94 110.00 164.81 220.00 277.18 440.00 554.37 880.00 2.95 110.00 164.81 220.00 277.18 440.00 554.37 880.00 2.96 110.00 164.81 220.00 277.18 440.00 554.37 880.00 2.97 110.00 164.81 220.00 277.18 440.00 554.37 880.00 2.98 110.00 164.81 220.00 277.18 440.00 554.37 880.00 2.99 110.00 164.81 220.00 277.18 440.00 880.00 3.00 110.00 164.81 220.00 277.18 440.00 880.00 3.01 110.00 164.81 220.00 277.18 440.00 880.00 3.02 110.00 164.81 220.00 277.18 440.00 880.00 3.03 110.00 164.81 220.00 277.18 440.00 880.00 3.04 110.00 164.81 220.00 277.18 440.00 880.00 3.05 110.00 164.81 220.00 277.18 440.00 880.00 3.06 110.00 164.81 220.00 440.00 880.00 3.07 110.00 164.81 220.00 440.00 880.00 3.08 110.00 164.81 220.00 440.00 880.00 3.09 110.00 164.81 220.00 440.00 880.00 3.10 110.00 164.81 220.00 440.00 880.00 3.11 110.00 164.81 220.00 440.00 880.00 3.12 110.00 164.81 220.00 440.00 880.00 3.13 110.00 164.81 220.00 440.00 880.00 3.14 110.00 164.81 220.00 440.00 880.00 3.15 110.00 164.81 220.00 440.00 880.00 3.16 110.00 164.81 220.00 329.63 440.00 554.37 880.00 3.17 110.00 164.81 220.00 277.18 329.63 440.00 554.37 880.00 3.18 110.00 164.81 220.00 277.18 329.63 440.00 554.37 880.00 3.19 110.00 164.81 220.00 277.18 329.63 440.00 554.37 880.00 3.20 110.00 164.81 220.00 277.18 329.63 440.00 554.37 880.00 3.21 110.00 164.81 220.00 277.18 329.63 440.00 554.37 880.00 3.22 110.00 164.81 220.00 277.18 329.63 440.00 554.37 880.00 3.23 110.00 164.81 220.00 277.18 329.63 440.00 554.37 830.61 880.00 3.24 110.00 164.81 220.00 277.18 440.00 830.61 880.00 3.25 110.00 164.81 220.00 277.18 440.00 830.61 880.00 3.26 110.00 164.81 220.00 277.18 440.00 830.61 880.00 3.27 110.00 164.81 220.00 277.18 440.00 830.61 880.00 3.28 110.00 164.81 220.00 277.18 440.00 830.61 880.00 3.29 110.00 164.81 277.18 440.00 830.61 880.00 3.30 110.00 164.81 277.18 440.00 830.61 880.00 3.31 110.00 164.81 277.18 440.00 830.61 880.00 3.32 110.00 164.81 277.18 440.00 830.61 880.00 3.33 110.00 164.81 277.18 440.00 830.61 880.00 3.34 110.00 164.81 277.18 440.00 830.61 880.00 3.35 110.00 164.81 277.18 440.00 830.61 880.00 3.36 110.00 164.81 277.18 440.00 830.61 880.00 3.37 110.00 164.81 277.18 440.00 830.61 880.00 3.38 110.00 164.81 277.18 440.00 830.61 880.00 3.39 110.00 164.81 277.18 440.00 830.61 880.00 3.40 110.00 164.81 277.18 440.00 830.61 880.00 3.41 110.00 164.81 277.18 440.00 830.61 880.00 3.42 110.00 164.81 277.18 440.00 830.61 880.00 3.43 110.00 164.81 277.18 440.00 830.61 880.00 3.44 110.00 164.81 277.18 440.00 830.61 880.00 3.45 110.00 164.81 277.18 440.00 830.61 880.00 3.46 110.00 164.81 277.18 440.00 830.61 880.00 3.47 110.00 164.81 277.18 440.00 830.61 880.00 3.48 110.00 164.81 277.18 440.00 830.61 880.00 3.49 110.00 164.81 277.18 440.00 830.61 880.00 3.50 110.00 164.81 277.18 440.00 830.61 880.00 3.51 110.00 164.81 277.18 440.00 830.61 880.00 3.52 110.00 164.81 277.18 440.00 830.61 880.00 3.53 110.00 164.81 277.18 440.00 830.61 880.00 3.54 110.00 164.81 277.18 830.61 3.55 110.00 164.81 277.18 830.61 3.56 110.00 164.81 277.18 830.61 3.57 110.00 164.81 277.18 3.58 110.00 164.81 277.18 3.59 110.00 164.81 277.18 3.60 110.00 164.81 277.18 3.61 110.00 164.81 277.18 3.62 110.00 164.81 277.18 3.63 110.00 164.81 277.18 739.99 3.64 110.00 164.81 277.18 739.99 3.65 110.00 164.81 277.18 739.99 3.66 110.00 164.81 277.18 739.99 3.67 110.00 164.81 277.18 739.99 3.68 110.00 164.81 277.18 739.99 3.69 110.00 164.81 277.18 739.99 3.70 110.00 164.81 277.18 739.99 3.71 110.00 164.81 277.18 739.99 3.72 110.00 164.81 277.18 739.99 3.73 110.00 277.18 739.99 3.74 110.00 277.18 739.99 3.75 146.83 277.18 739.99 3.76 146.83 277.18 739.99 3.77 146.83 277.18 293.66 739.99 3.78 146.83 277.18 293.66 739.99 3.79 146.83 277.18 293.66 739.99 3.80 146.83 277.18 293.66 739.99 3.81 146.83 277.18 293.66 739.99 3.82 146.83 277.18 293.66 739.99 3.83 110.00 146.83 277.18 293.66 739.99 3.84 110.00 146.83 293.66 739.99 3.85 110.00 146.83 293.66 739.99 3.86 110.00 146.83 293.66 739.99 3.87 110.00 146.83 293.66 739.99 3.88 110.00 146.83 293.66 329.63 739.99 3.89 110.00 146.83 293.66 329.63 3.90 110.00 146.83 293.66 329.63 3.91 110.00 146.83 220.00 293.66 329.63 3.92 110.00 220.00 293.66 329.63 3.93 110.00 220.00 293.66 329.63 3.94 110.00 164.81 220.00 293.66 329.63 3.95 110.00 164.81 220.00 293.66 329.63 3.96 110.00 164.81 220.00 293.66 329.63 3.97 110.00 164.81 220.00 293.66 329.63 3.98 110.00 164.81 220.00 293.66 329.63 3.99 110.00 164.81 220.00 293.66 329.63 4.00 110.00 164.81 220.00 293.66 329.63 659.26 4.01 110.00 164.81 220.00 293.66 329.63 659.26 4.02 110.00 164.81 220.00 293.66 329.63 659.26 4.03 110.00 164.81 220.00 293.66 329.63 659.26 4.04 110.00 164.81 220.00 293.66 329.63 659.26 4.05 110.00 164.81 220.00 293.66 329.63 659.26 4.06 110.00 164.81 220.00 293.66 329.63 659.26 4.07 110.00 164.81 220.00 293.66 329.63 659.26 4.08 110.00 164.81 220.00 293.66 329.63 659.26 4.09 110.00 164.81 220.00 277.18 293.66 329.63 659.26 4.10 110.00 164.81 220.00 277.18 293.66 329.63 659.26 4.11 110.00 164.81 220.00 277.18 293.66 329.63 659.26 4.12 110.00 164.81 220.00 277.18 329.63 659.26 4.13 110.00 164.81 220.00 277.18 329.63 659.26 4.14 110.00 164.81 220.00 277.18 329.63 659.26 4.15 110.00 164.81 220.00 277.18 329.63 659.26 4.16 110.00 164.81 220.00 277.18 329.63 659.26 4.17 110.00 164.81 220.00 277.18 329.63 659.26 4.18 110.00 164.81 220.00 277.18 329.63 659.26 4.19 110.00 164.81 220.00 329.63 659.26 4.20 110.00 164.81 220.00 329.63 659.26 4.21 110.00 164.81 220.00 329.63 659.26 4.22 110.00 164.81 220.00 329.63 659.26 4.23 110.00 164.81 329.63 659.26 4.24 110.00 164.81 329.63 659.26 4.25 110.00 164.81 329.63 659.26 4.26 110.00 164.81 329.63 659.26 4.27 110.00 164.81 329.63 659.26 4.28 110.00 164.81 329.63 659.26 4.29 110.00 164.81 329.63 659.26 4.30 110.00 185.00 329.63 659.26 4.31 110.00 185.00 329.63 659.26 4.32 110.00 185.00 329.63 659.26 4.33 185.00 659.26 4.34 185.00 659.26 4.35 185.00 659.26 4.36 185.00 659.26 4.37 415.30 659.26 4.38 415.30 659.26 4.39 415.30 659.26 4.40 415.30 659.26 4.41 207.65 415.30 659.26 4.42 207.65 415.30 659.26 4.43 207.65 415.30 659.26 4.44 207.65 415.30 659.26 4.45 207.65 415.30 659.26 4.46 110.00 207.65 415.30 659.26 4.47 110.00 207.65 415.30 659.26 4.48 110.00 207.65 415.30 659.26 4.49 110.00 207.65 369.99 415.30 4.50 110.00 207.65 369.99 415.30 4.51 110.00 207.65 369.99 415.30 4.52 110.00 207.65 369.99 415.30 4.53 110.00 207.65 369.99 415.30 4.54 110.00 207.65 369.99 415.30 4.55 110.00 207.65 369.99 415.30 4.56 110.00 207.65 369.99 415.30 4.57 110.00 207.65 369.99 415.30 4.58 110.00 207.65 369.99 415.30 4.59 110.00 207.65 369.99 415.30 4.60 110.00 207.65 369.99 415.30 4.61 110.00 207.65 369.99 415.30 4.62 207.65 415.30 4.63 207.65 277.18 415.30 4.64 277.18 440.00 4.65 277.18 440.00 1318.51 4.66 277.18 440.00 1318.51 4.67 277.18 440.00 1318.51 4.68 277.18 440.00 1318.51 4.69 277.18 440.00 1318.51 4.70 277.18 440.00 1318.51 4.71 277.18 440.00 1318.51 4.72 277.18 440.00 1318.51 4.73 277.18 440.00 4.74 92.50 277.18 440.00 4.75 92.50 277.18 440.00 4.76 92.50 185.00 277.18 440.00 4.77 92.50 185.00 277.18 415.30 440.00 4.78 92.50 185.00 277.18 415.30 440.00 4.79 92.50 185.00 220.00 277.18 415.30 659.26 4.80 92.50 185.00 220.00 277.18 415.30 659.26 1318.51 4.81 92.50 185.00 220.00 277.18 415.30 659.26 1318.51 4.82 92.50 185.00 220.00 277.18 415.30 659.26 1318.51 4.83 92.50 185.00 220.00 277.18 415.30 659.26 1318.51 4.84 92.50 185.00 220.00 277.18 415.30 659.26 1318.51 4.85 92.50 185.00 220.00 277.18 659.26 1318.51 4.86 92.50 185.00 220.00 277.18 659.26 1318.51 4.87 92.50 185.00 220.00 277.18 659.26 1318.51 4.88 92.50 185.00 220.00 277.18 659.26 1318.51 4.89 92.50 185.00 220.00 277.18 659.26 1318.51 4.90 92.50 185.00 220.00 277.18 659.26 1318.51 4.91 92.50 185.00 220.00 277.18 659.26 4.92 92.50 185.00 277.18 554.37 4.93 92.50 185.00 277.18 554.37 4.94 92.50 185.00 277.18 440.00 554.37 4.95 185.00 277.18 440.00 554.37 4.96 185.00 277.18 440.00 554.37 4.97 207.65 277.18 440.00 554.37 4.98 207.65 277.18 440.00 554.37 4.99 207.65 277.18 440.00 554.37 5.00 207.65 277.18 440.00 554.37 5.01 207.65 277.18 440.00 554.37 5.02 207.65 277.18 440.00 554.37 5.03 207.65 277.18 440.00 554.37 5.04 207.65 277.18 440.00 554.37 5.05 207.65 277.18 440.00 554.37 5.06 207.65 277.18 440.00 554.37 5.07 207.65 277.18 440.00 554.37 5.08 207.65 277.18 440.00 554.37 587.33 5.09 207.65 277.18 440.00 554.37 587.33 5.10 207.65 277.18 440.00 554.37 587.33 5.11 207.65 277.18 440.00 554.37 587.33 5.12 207.65 277.18 440.00 554.37 587.33 5.13 185.00 207.65 277.18 369.99 440.00 554.37 587.33 5.14 185.00 207.65 369.99 440.00 587.33 5.15 185.00 207.65 369.99 440.00 587.33 5.16 185.00 207.65 369.99 440.00 587.33 5.17 185.00 207.65 369.99 440.00 587.33 5.18 185.00 207.65 369.99 440.00 587.33 880.00 5.19 185.00 207.65 277.18 369.99 440.00 587.33 880.00 5.20 185.00 207.65 277.18 369.99 440.00 587.33 880.00 5.21 185.00 277.18 369.99 440.00 587.33 880.00 5.22 185.00 277.18 369.99 440.00 587.33 880.00 5.23 185.00 277.18 369.99 440.00 587.33 880.00 5.24 185.00 277.18 369.99 440.00 587.33 880.00 5.25 185.00 277.18 369.99 440.00 587.33 880.00 5.26 185.00 277.18 369.99 440.00 587.33 5.27 185.00 277.18 369.99 440.00 587.33 5.28 185.00 277.18 369.99 440.00 587.33 5.29 185.00 277.18 369.99 5.30 185.00 277.18 369.99 5.31 185.00 277.18 369.99 5.32 185.00 277.18 369.99 5.33 185.00 277.18 369.99 5.34 185.00 277.18 5.35 185.00 277.18 5.36 164.81 5.37 164.81 207.65 5.38 164.81 207.65 5.39 164.81 207.65 5.40 164.81 207.65 5.41 164.81 207.65 329.63 659.26 5.42 164.81 207.65 329.63 659.26 5.43 164.81 207.65 329.63 659.26 5.44 164.81 207.65 329.63 659.26 5.45 164.81 207.65 329.63 659.26 5.46 164.81 207.65 329.63 659.26 5.47 164.81 207.65 329.63 659.26 5.48 164.81 207.65 329.63 659.26 5.49 164.81 207.65 329.63 659.26 5.50 164.81 207.65 329.63 659.26 5.51 164.81 207.65 329.63 659.26 5.52 164.81 207.65 329.63 659.26 5.53 164.81 207.65 329.63 659.26 5.54 164.81 207.65 329.63 659.26 5.55 164.81 207.65 329.63 659.26 5.56 164.81 207.65 329.63 659.26 5.57 164.81 207.65 329.63 659.26 5.58 164.81 207.65 329.63 659.26 5.59 164.81 207.65 329.63 659.26 5.60 82.41 164.81 207.65 293.66 329.63 659.26 739.99 5.61 82.41 123.47 164.81 207.65 293.66 329.63 659.26 739.99 5.62 82.41 123.47 164.81 207.65 293.66 329.63 659.26 739.99 5.63 82.41 123.47 164.81 207.65 293.66 329.63 659.26 739.99 5.64 82.41 123.47 164.81 207.65 293.66 329.63 659.26 739.99 5.65 82.41 123.47 164.81 207.65 293.66 329.63 659.26 739.99 5.66 82.41 123.47 164.81 207.65 293.66 329.63 739.99 5.67 82.41 123.47 164.81 207.65 329.63 739.99 5.68 82.41 123.47 164.81 207.65 329.63 739.99 5.69 82.41 123.47 164.81 207.65 329.63 739.99 5.70 82.41 123.47 164.81 207.65 329.63 739.99 5.71 82.41 123.47 164.81 207.65 329.63 739.99 5.72 82.41 123.47 164.81 207.65 329.63 739.99 5.73 82.41 123.47 164.81 207.65 739.99 5.74 82.41 123.47 164.81 207.65 659.26 739.99 5.75 82.41 123.47 164.81 207.65 659.26 739.99 5.76 82.41 123.47 164.81 293.66 659.26 739.99 5.77 82.41 123.47 164.81 293.66 659.26 739.99 830.61 5.78 82.41 123.47 164.81 293.66 329.63 659.26 739.99 830.61 5.79 82.41 123.47 164.81 293.66 329.63 659.26 739.99 830.61 5.80 82.41 123.47 164.81 293.66 329.63 659.26 739.99 830.61 5.81 82.41 123.47 164.81 293.66 329.63 659.26 830.61 5.82 123.47 164.81 293.66 329.63 659.26 830.61 5.83 123.47 164.81 329.63 830.61 5.84 123.47 164.81 329.63 830.61 5.85 123.47 164.81 329.63 830.61 5.86 123.47 164.81 329.63 369.99 830.61 5.87 123.47 164.81 329.63 369.99 830.61 5.88 123.47 164.81 329.63 369.99 830.61 5.89 123.47 164.81 329.63 369.99 830.61 5.90 123.47 164.81 329.63 369.99 830.61 5.91 123.47 164.81 329.63 369.99 830.61 5.92 123.47 164.81 329.63 369.99 830.61 5.93 123.47 164.81 329.63 369.99 830.61 5.94 123.47 164.81 329.63 369.99 830.61 5.95 123.47 164.81 369.99 830.61 5.96 123.47 164.81 369.99 830.61 880.00 5.97 123.47 164.81 369.99 440.00 830.61 880.00 5.98 123.47 164.81 220.00 369.99 440.00 830.61 880.00 5.99 123.47 164.81 220.00 440.00 830.61 880.00 6.00 164.81 220.00 440.00 830.61 880.00 6.01 110.00 164.81 220.00 440.00 830.61 880.00 6.02 110.00 164.81 220.00 440.00 830.61 880.00 6.03 110.00 164.81 220.00 440.00 830.61 880.00 6.04 110.00 164.81 220.00 440.00 830.61 880.00 6.05 110.00 164.81 220.00 440.00 830.61 880.00 6.06 110.00 164.81 220.00 440.00 830.61 880.00 6.07 110.00 164.81 220.00 440.00 880.00 6.08 110.00 164.81 220.00 440.00 880.00 6.09 110.00 164.81 220.00 440.00 880.00 6.10 110.00 164.81 220.00 440.00 880.00 6.11 110.00 164.81 220.00 440.00 880.00 6.12 110.00 164.81 220.00 440.00 880.00 6.13 110.00 164.81 220.00 440.00 880.00 6.14 110.00 164.81 220.00 440.00 880.00 6.15 110.00 164.81 220.00 440.00 880.00 6.16 110.00 164.81 220.00 440.00 880.00 6.17 110.00 164.81 220.00 440.00 880.00 6.18 110.00 164.81 220.00 440.00 880.00 6.19 110.00 164.81 220.00 440.00 880.00 6.20 110.00 164.81 220.00 440.00 880.00 6.21 110.00 164.81 220.00 440.00 880.00 6.22 110.00 164.81 220.00 440.00 880.00 6.23 110.00 164.81 220.00 440.00 880.00 6.24 110.00 164.81 220.00 440.00 880.00 6.25 110.00 164.81 220.00 440.00 880.00 6.26 110.00 164.81 220.00 440.00 880.00 6.27 110.00 164.81 220.00 6.28 110.00 164.81 220.00 6.29 110.00 164.81 220.00 6.30 110.00 164.81 220.00 6.31 110.00 164.81 220.00 6.32 110.00 164.81 220.00 329.63 6.33 110.00 164.81 220.00 329.63 6.34 110.00 164.81 329.63 6.35 110.00 164.81 329.63 830.61 6.36 110.00 164.81 329.63 830.61 6.37 110.00 164.81 329.63 830.61 6.38 110.00 164.81 329.63 830.61 6.39 110.00 164.81 329.63 830.61 6.40 110.00 164.81 329.63 830.61 6.41 110.00 164.81 329.63 830.61 6.42 110.00 164.81 329.63 830.61 6.43 110.00 164.81 329.63 830.61 6.44 110.00 164.81 329.63 830.61 6.45 110.00 164.81 329.63 830.61 6.46 110.00 164.81 329.63 830.61 6.47 110.00 164.81 329.63 830.61 6.48 110.00 164.81 329.63 830.61 6.49 110.00 164.81 329.63 830.61 6.50 110.00 164.81 329.63 830.61 6.51 110.00 164.81 329.63 830.61 6.52 110.00 164.81 329.63 739.99 6.53 110.00 164.81 329.63 739.99 6.54 110.00 164.81 329.63 739.99 6.55 110.00 164.81 220.00 329.63 739.99 6.56 110.00 164.81 220.00 329.63 739.99 6.57 110.00 164.81 220.00 329.63 739.99 6.58 110.00 164.81 220.00 329.63 739.99 6.59 110.00 164.81 220.00 329.63 739.99 6.60 110.00 164.81 220.00 329.63 739.99 6.61 110.00 164.81 220.00 329.63 739.99 6.62 110.00 164.81 220.00 329.63 739.99 6.63 110.00 164.81 220.00 329.63 739.99 6.64 110.00 164.81 220.00 329.63 739.99 6.65 110.00 164.81 329.63 739.99 6.66 110.00 164.81 329.63 739.99 6.67 110.00 164.81 246.94 329.63 739.99 6.68 110.00 164.81 246.94 329.63 739.99 6.69 110.00 164.81 246.94 329.63 6.70 110.00 164.81 246.94 329.63 6.71 110.00 164.81 246.94 329.63 6.72 110.00 164.81 246.94 329.63 6.73 110.00 164.81 246.94 329.63 6.74 110.00 164.81 246.94 329.63 6.75 110.00 164.81 246.94 329.63 6.76 164.81 246.94 329.63 6.77 164.81 246.94 329.63 6.78 103.83 164.81 246.94 329.63 6.79 103.83 164.81 246.94 329.63 6.80 103.83 164.81 246.94 329.63 6.81 103.83 164.81 246.94 329.63 6.82 103.83 164.81 246.94 329.63 6.83 103.83 164.81 246.94 329.63 6.84 103.83 164.81 246.94 329.63 6.85 103.83 164.81 246.94 329.63 6.86 103.83 164.81 246.94 329.63 6.87 103.83 164.81 246.94 329.63 659.26 6.88 103.83 164.81 246.94 329.63 659.26 6.89 103.83 164.81 246.94 329.63 659.26 6.90 103.83 164.81 246.94 329.63 659.26 6.91 103.83 164.81 246.94 329.63 659.26 6.92 103.83 164.81 246.94 329.63 659.26 6.93 103.83 164.81 246.94 329.63 659.26 6.94 103.83 164.81 246.94 329.63 659.26 6.95 103.83 164.81 246.94 329.63 659.26 6.96 103.83 164.81 246.94 329.63 659.26 6.97 103.83 164.81 246.94 329.63 659.26 6.98 103.83 110.00 164.81 246.94 329.63 659.26 6.99 110.00 164.81 246.94 329.63 659.26 7.00 110.00 164.81 246.94 329.63 659.26 7.01 110.00 164.81 246.94 329.63 659.26 7.02 110.00 164.81 246.94 329.63 659.26 7.03 110.00 164.81 246.94 329.63 659.26 7.04 110.00 164.81 246.94 329.63 659.26 7.05 110.00 164.81 329.63 659.26 7.06 110.00 164.81 329.63 659.26 7.07 103.83 110.00 164.81 659.26 7.08 103.83 164.81 659.26 7.09 103.83 164.81 554.37 659.26 7.10 103.83 164.81 554.37 659.26 7.11 103.83 164.81 277.18 554.37 659.26 7.12 103.83 164.81 277.18 554.37 659.26 7.13 103.83 164.81 277.18 554.37 659.26 7.14 103.83 164.81 277.18 554.37 659.26 7.15 103.83 164.81 277.18 554.37 659.26 7.16 103.83 164.81 277.18 554.37 659.26 7.17 103.83 164.81 277.18 554.37 659.26 7.18 103.83 164.81 277.18 554.37 659.26 7.19 103.83 164.81 277.18 554.37 659.26 7.20 103.83 164.81 277.18 554.37 659.26 7.21 103.83 164.81 277.18 554.37 659.26 7.22 103.83 164.81 277.18 554.37 659.26 7.23 103.83 164.81 277.18 554.37 659.26 7.24 103.83 164.81 277.18 554.37 659.26 7.25 103.83 164.81 277.18 554.37 659.26 7.26 103.83 164.81 277.18 554.37 659.26 7.27 103.83 164.81 277.18 554.37 659.26 7.28 103.83 164.81 277.18 554.37 659.26 7.29 103.83 164.81 277.18 554.37 659.26 7.30 103.83 164.81 277.18 554.37 659.26 7.31 103.83 164.81 277.18 554.37 659.26 7.32 103.83 164.81 277.18 554.37 659.26 7.33 103.83 164.81 277.18 554.37 659.26 7.34 103.83 164.81 277.18 554.37 659.26 7.35 103.83 164.81 277.18 554.37 659.26 7.36 103.83 164.81 277.18 554.37 659.26 7.37 103.83 164.81 277.18 554.37 659.26 7.38 103.83 164.81 277.18 554.37 659.26 7.39 103.83 164.81 277.18 554.37 659.26 7.40 103.83 164.81 277.18 554.37 659.26 7.41 103.83 164.81 277.18 554.37 659.26 7.42 103.83 164.81 277.18 554.37 659.26 7.43 103.83 277.18 554.37 659.26 7.44 103.83 277.18 554.37 659.26 7.45 103.83 185.00 659.26 7.46 185.00 659.26 7.47 185.00 659.26 7.48 185.00 659.26 7.49 185.00 659.26 7.50 185.00 659.26 7.51 185.00 659.26 7.52 185.00 440.00 659.26 7.53 92.50 440.00 659.26 7.54 92.50 440.00 659.26 7.55 92.50 440.00 659.26 7.56 92.50 440.00 659.26 7.57 92.50 293.66 440.00 659.26 7.58 92.50 293.66 440.00 659.26 7.59 92.50 293.66 440.00 659.26 7.60 92.50 293.66 440.00 659.26 7.61 92.50 293.66 329.63 440.00 659.26 7.62 92.50 293.66 329.63 440.00 659.26 7.63 92.50 293.66 329.63 659.26 7.64 92.50 293.66 329.63 659.26 7.65 92.50 293.66 329.63 659.26 7.66 92.50 293.66 329.63 659.26 7.67 92.50 293.66 329.63 659.26 7.68 92.50 293.66 329.63 659.26 7.69 92.50 293.66 329.63 659.26 7.70 92.50 293.66 329.63 659.26 7.71 92.50 293.66 329.63 659.26 7.72 92.50 293.66 329.63 659.26 7.73 92.50 293.66 329.63 659.26 7.74 92.50 293.66 659.26 7.75 92.50 293.66 659.26 7.76 92.50 293.66 587.33 659.26 7.77 92.50 293.66 587.33 659.26 7.78 92.50 185.00 293.66 554.37 587.33 659.26 7.79 92.50 185.00 293.66 554.37 587.33 659.26 7.80 92.50 185.00 554.37 587.33 659.26 7.81 92.50 185.00 554.37 587.33 659.26 7.82 92.50 185.00 554.37 587.33 659.26 7.83 92.50 185.00 277.18 554.37 7.84 92.50 185.00 277.18 554.37 7.85 92.50 185.00 277.18 554.37 7.86 92.50 185.00 277.18 554.37 7.87 92.50 185.00 277.18 554.37 7.88 92.50 185.00 277.18 554.37 7.89 92.50 185.00 277.18 554.37 7.90 92.50 185.00 277.18 554.37 7.91 92.50 185.00 277.18 554.37 7.92 92.50 185.00 277.18 554.37 7.93 92.50 185.00 277.18 554.37 7.94 92.50 185.00 277.18 554.37 7.95 92.50 185.00 277.18 7.96 92.50 185.00 277.18 7.97 92.50 185.00 277.18 7.98 185.00 277.18 7.99 185.00 277.18 8.00 185.00 277.18 8.01 185.00 277.18 8.02 185.00 277.18 8.03 185.00 277.18 8.04 185.00 277.18 8.05 185.00 277.18 587.33 8.06 185.00 277.18 587.33 8.07 185.00 277.18 587.33 8.08 185.00 277.18 587.33 8.09 185.00 277.18 587.33 8.10 185.00 277.18 587.33 8.11 185.00 277.18 587.33 8.12 185.00 277.18 587.33 8.13 185.00 587.33 8.14 185.00 587.33 8.15 185.00 293.66 587.33 987.77 8.16 185.00 293.66 493.88 587.33 987.77 8.17 293.66 493.88 587.33 987.77 8.18 293.66 493.88 587.33 987.77 8.19 293.66 493.88 587.33 987.77 8.20 293.66 493.88 587.33 987.77 1318.51 8.21 293.66 493.88 587.33 987.77 1318.51 8.22 82.41 164.81 293.66 493.88 587.33 987.77 1318.51 8.23 82.41 164.81 293.66 493.88 587.33 987.77 1318.51 8.24 82.41 164.81 293.66 493.88 587.33 987.77 1318.51 8.25 82.41 164.81 293.66 493.88 587.33 987.77 1318.51 8.26 82.41 164.81 293.66 493.88 587.33 987.77 1318.51 8.27 82.41 164.81 293.66 493.88 587.33 987.77 1318.51 8.28 82.41 164.81 293.66 493.88 587.33 987.77 1318.51 8.29 82.41 164.81 293.66 493.88 587.33 987.77 1318.51 8.30 82.41 164.81 293.66 493.88 587.33 987.77 1318.51 8.31 82.41 164.81 493.88 587.33 987.77 1318.51 8.32 82.41 164.81 246.94 493.88 587.33 987.77 1318.51 8.33 82.41 164.81 246.94 493.88 587.33 987.77 1318.51 8.34 82.41 164.81 246.94 493.88 587.33 987.77 1318.51 8.35 82.41 164.81 246.94 493.88 587.33 987.77 1318.51 8.36 82.41 164.81 246.94 493.88 587.33 987.77 1318.51 8.37 82.41 164.81 246.94 493.88 587.33 987.77 1318.51 8.38 82.41 164.81 246.94 493.88 587.33 987.77 1318.51 8.39 82.41 164.81 246.94 493.88 587.33 987.77 1318.51 8.40 82.41 164.81 246.94 493.88 587.33 987.77 1318.51 8.41 82.41 164.81 246.94 493.88 587.33 987.77 1318.51 8.42 82.41 164.81 246.94 493.88 587.33 987.77 1318.51 8.43 82.41 164.81 246.94 493.88 587.33 987.77 1318.51 8.44 82.41 164.81 246.94 493.88 587.33 987.77 1318.51 8.45 82.41 164.81 246.94 493.88 987.77 8.46 82.41 164.81 246.94 493.88 987.77 8.47 82.41 164.81 246.94 493.88 987.77 8.48 82.41 164.81 246.94 493.88 987.77 1108.73 8.49 82.41 164.81 246.94 415.30 493.88 987.77 1108.73 8.50 82.41 164.81 246.94 415.30 493.88 987.77 1108.73 8.51 82.41 164.81 246.94 415.30 493.88 987.77 1108.73 8.52 82.41 164.81 246.94 415.30 493.88 987.77 1108.73 8.53 82.41 164.81 246.94 415.30 493.88 987.77 1108.73 8.54 82.41 164.81 246.94 415.30 493.88 1108.73 8.55 82.41 164.81 246.94 415.30 493.88 1108.73 8.56 82.41 164.81 246.94 415.30 493.88 1108.73 8.57 82.41 164.81 246.94 493.88 1108.73 8.58 82.41 164.81 246.94 493.88 1108.73 8.59 82.41 164.81 246.94 493.88 1108.73 8.60 82.41 164.81 246.94 493.88 1108.73 8.61 82.41 164.81 246.94 493.88 1108.73 8.62 82.41 164.81 246.94 493.88 1108.73 8.63 82.41 164.81 246.94 493.88 1108.73 8.64 82.41 164.81 246.94 493.88 1108.73 8.65 82.41 164.81 246.94 493.88 1108.73 8.66 82.41 164.81 246.94 493.88 1108.73 8.67 82.41 164.81 246.94 1108.73 8.68 82.41 164.81 246.94 1108.73 8.69 82.41 164.81 1108.73 8.70 82.41 164.81 1108.73 8.71 82.41 164.81 1108.73 8.72 82.41 164.81 1108.73 8.73 82.41 164.81 1108.73 8.74 82.41 164.81 246.94 1108.73 8.75 82.41 164.81 246.94 1108.73 8.76 82.41 164.81 246.94 1108.73 8.77 82.41 164.81 246.94 1108.73 8.78 82.41 164.81 246.94 329.63 659.26 1108.73 8.79 82.41 164.81 246.94 329.63 659.26 1108.73 8.80 82.41 164.81 246.94 329.63 587.33 659.26 1108.73 8.81 82.41 164.81 246.94 329.63 587.33 659.26 1108.73 8.82 82.41 164.81 246.94 329.63 587.33 659.26 1108.73 1174.66 8.83 82.41 164.81 246.94 329.63 587.33 659.26 1108.73 1174.66 8.84 82.41 164.81 246.94 329.63 587.33 659.26 1108.73 1174.66 8.85 82.41 164.81 246.94 329.63 587.33 659.26 1108.73 1174.66 8.86 82.41 164.81 246.94 587.33 1108.73 1174.66 8.87 82.41 164.81 246.94 587.33 1108.73 1174.66 8.88 82.41 164.81 246.94 587.33 1108.73 1174.66 8.89 82.41 164.81 246.94 587.33 1108.73 1174.66 8.90 82.41 164.81 246.94 587.33 1108.73 1174.66 8.91 82.41 164.81 246.94 587.33 1108.73 1174.66 8.92 82.41 164.81 246.94 587.33 1108.73 1174.66 8.93 82.41 164.81 246.94 587.33 1108.73 1174.66 8.94 82.41 164.81 246.94 587.33 1108.73 1174.66 8.95 82.41 164.81 246.94 587.33 1108.73 1174.66 8.96 82.41 164.81 246.94 587.33 1108.73 1174.66 8.97 82.41 164.81 246.94 587.33 1108.73 1174.66 8.98 82.41 164.81 246.94 587.33 1108.73 1174.66 8.99 82.41 164.81 246.94 587.33 1108.73 1174.66 9.00 82.41 164.81 246.94 587.33 1108.73 1174.66 9.01 82.41 164.81 246.94 587.33 1108.73 1174.66 9.02 82.41 164.81 246.94 587.33 1108.73 1174.66 9.03 82.41 164.81 246.94 587.33 1108.73 1174.66 9.04 82.41 164.81 246.94 587.33 1108.73 1174.66 9.05 82.41 164.81 246.94 587.33 1108.73 1174.66 9.06 82.41 164.81 246.94 587.33 1108.73 1174.66 9.07 82.41 164.81 246.94 587.33 1108.73 1174.66 9.08 82.41 164.81 246.94 587.33 1108.73 1174.66 9.09 82.41 164.81 246.94 587.33 1108.73 1174.66 9.10 82.41 164.81 246.94 587.33 1108.73 1174.66 9.11 82.41 164.81 246.94 587.33 1108.73 1174.66 9.12 82.41 164.81 246.94 587.33 1108.73 1174.66 9.13 82.41 164.81 246.94 587.33 1108.73 1174.66 9.14 82.41 164.81 246.94 587.33 1108.73 1174.66 9.15 82.41 164.81 246.94 587.33 1108.73 1174.66 9.16 82.41 164.81 246.94 587.33 1108.73 1174.66 9.17 82.41 164.81 246.94 587.33 1108.73 1174.66 9.18 82.41 164.81 246.94 587.33 1108.73 1174.66 9.19 82.41 164.81 246.94 587.33 1108.73 1174.66 9.20 82.41 164.81 246.94 1108.73 1174.66 9.21 82.41 164.81 246.94 1108.73 1174.66 9.22 82.41 164.81 246.94 1108.73 1174.66 9.23 82.41 164.81 246.94 1108.73 1174.66 9.24 82.41 164.81 246.94 1108.73 1174.66 9.25 82.41 164.81 246.94 587.33 1108.73 1174.66 9.26 82.41 164.81 246.94 587.33 1108.73 1174.66 9.27 82.41 164.81 246.94 587.33 1108.73 1174.66 9.28 82.41 164.81 246.94 587.33 1108.73 1174.66 9.29 82.41 164.81 246.94 587.33 1108.73 1174.66 9.30 82.41 164.81 246.94 587.33 1108.73 1174.66 9.31 82.41 164.81 246.94 587.33 1108.73 1174.66 9.32 82.41 164.81 246.94 587.33 1108.73 1174.66 9.33 82.41 164.81 246.94 587.33 1108.73 1174.66 9.34 82.41 164.81 246.94 587.33 1108.73 1174.66 9.35 82.41 164.81 246.94 587.33 1108.73 1174.66 9.36 82.41 164.81 246.94 587.33 1108.73 1174.66 9.37 82.41 164.81 246.94 587.33 1108.73 1174.66 9.38 82.41 164.81 246.94 587.33 1108.73 1174.66 9.39 82.41 164.81 246.94 587.33 1108.73 1174.66 9.40 82.41 164.81 246.94 587.33 1108.73 1174.66 9.41 82.41 164.81 246.94 587.33 1108.73 1174.66 9.42 82.41 164.81 246.94 587.33 1108.73 1174.66 9.43 82.41 164.81 246.94 587.33 1108.73 1174.66 9.44 82.41 164.81 246.94 587.33 1174.66 9.45 82.41 164.81 246.94 587.33 1174.66 9.46 82.41 164.81 246.94 587.33 1174.66 9.47 82.41 164.81 246.94 587.33 1174.66 9.48 82.41 164.81 246.94 587.33 1174.66 9.49 82.41 164.81 246.94 587.33 1174.66 9.50 82.41 164.81 246.94 587.33 1174.66 9.51 82.41 164.81 246.94 587.33 1174.66 9.52 246.94 493.88 587.33 9.53 246.94 493.88 587.33 9.54 246.94 493.88 587.33 987.77 9.55 185.00 246.94 493.88 587.33 987.77 9.56 185.00 246.94 493.88 587.33 987.77 9.57 185.00 246.94 293.66 493.88 587.33 987.77 9.58 185.00 246.94 293.66 493.88 587.33 987.77 9.59 185.00 246.94 293.66 493.88 587.33 987.77 9.60 185.00 246.94 293.66 493.88 587.33 987.77 9.61 185.00 246.94 293.66 493.88 587.33 987.77 9.62 185.00 246.94 293.66 493.88 587.33 987.77 9.63 185.00 293.66 493.88 587.33 987.77 9.64 185.00 293.66 493.88 587.33 987.77 9.65 185.00 293.66 493.88 587.33 987.77 9.66 185.00 293.66 493.88 587.33 987.77 9.67 185.00 293.66 493.88 587.33 987.77 9.68 185.00 293.66 493.88 587.33 987.77 9.69 185.00 293.66 493.88 587.33 987.77 9.70 185.00 293.66 493.88 587.33 987.77 9.71 185.00 246.94 293.66 493.88 587.33 987.77 9.72 185.00 246.94 293.66 493.88 587.33 987.77 9.73 185.00 246.94 293.66 493.88 587.33 987.77 9.74 123.47 185.00 246.94 293.66 493.88 587.33 987.77 9.75 123.47 185.00 246.94 293.66 493.88 587.33 987.77 9.76 123.47 185.00 246.94 293.66 493.88 587.33 987.77 9.77 123.47 185.00 246.94 293.66 493.88 587.33 987.77 9.78 123.47 185.00 246.94 293.66 493.88 587.33 987.77 9.79 123.47 185.00 246.94 293.66 493.88 587.33 987.77 9.80 123.47 185.00 246.94 293.66 493.88 587.33 987.77 9.81 123.47 185.00 246.94 293.66 493.88 587.33 987.77 9.82 123.47 185.00 246.94 293.66 493.88 587.33 987.77 9.83 123.47 185.00 246.94 293.66 493.88 587.33 987.77 9.84 123.47 185.00 246.94 293.66 493.88 587.33 987.77 9.85 123.47 185.00 246.94 293.66 493.88 587.33 987.77 9.86 123.47 185.00 246.94 293.66 493.88 587.33 987.77 9.87 123.47 185.00 246.94 293.66 493.88 587.33 987.77 9.88 123.47 185.00 246.94 293.66 493.88 587.33 987.77 9.89 123.47 185.00 246.94 369.99 493.88 587.33 987.77 9.90 123.47 185.00 246.94 369.99 493.88 987.77 9.91 123.47 185.00 246.94 369.99 493.88 987.77 9.92 123.47 185.00 246.94 369.99 493.88 987.77 9.93 123.47 185.00 246.94 369.99 493.88 987.77 9.94 123.47 185.00 246.94 369.99 493.88 987.77 9.95 123.47 185.00 246.94 369.99 493.88 987.77 9.96 123.47 185.00 246.94 369.99 493.88 987.77 9.97 123.47 185.00 246.94 369.99 493.88 987.77 9.98 123.47 185.00 246.94 369.99 493.88 987.77 9.99 123.47 185.00 246.94 369.99 493.88 987.77 10.00 123.47 185.00 246.94 369.99 493.88 987.77 10.01 123.47 185.00 246.94 493.88 987.77 10.02 123.47 185.00 246.94 493.88 587.33 987.77 10.03 123.47 185.00 246.94 493.88 587.33 987.77 10.04 123.47 185.00 246.94 493.88 587.33 987.77 10.05 123.47 185.00 246.94 493.88 587.33 987.77 10.06 123.47 185.00 246.94 493.88 587.33 987.77 10.07 123.47 185.00 246.94 493.88 587.33 987.77 10.08 123.47 185.00 246.94 493.88 587.33 987.77 10.09 123.47 185.00 246.94 493.88 587.33 987.77 10.10 123.47 185.00 246.94 493.88 587.33 987.77 10.11 123.47 185.00 246.94 493.88 587.33 987.77 10.12 123.47 185.00 246.94 493.88 587.33 987.77 10.13 123.47 185.00 246.94 493.88 587.33 987.77 10.14 123.47 185.00 246.94 493.88 587.33 987.77 10.15 123.47 185.00 246.94 493.88 587.33 987.77 10.16 123.47 185.00 246.94 493.88 587.33 987.77 10.17 123.47 185.00 246.94 493.88 587.33 987.77 10.18 123.47 185.00 246.94 493.88 587.33 987.77 10.19 123.47 185.00 246.94 493.88 587.33 987.77 10.20 123.47 185.00 246.94 493.88 587.33 987.77 10.21 123.47 185.00 246.94 493.88 587.33 987.77 10.22 123.47 185.00 246.94 493.88 587.33 987.77 10.23 123.47 185.00 246.94 493.88 587.33 987.77 10.24 123.47 185.00 246.94 493.88 587.33 987.77 10.25 123.47 185.00 246.94 493.88 587.33 987.77 10.26 123.47 185.00 246.94 493.88 587.33 987.77 10.27 123.47 185.00 246.94 493.88 587.33 987.77 10.28 123.47 185.00 246.94 493.88 587.33 987.77 10.29 123.47 185.00 246.94 493.88 587.33 987.77 10.30 98.00 123.47 196.00 493.88 587.33 987.77 10.31 82.41 98.00 123.47 196.00 329.63 392.00 493.88 587.33 987.77 10.32 82.41 98.00 123.47 196.00 329.63 392.00 493.88 587.33 987.77 10.33 82.41 98.00 123.47 196.00 329.63 392.00 493.88 587.33 987.77 10.34 82.41 98.00 123.47 196.00 329.63 392.00 493.88 587.33 987.77 10.35 82.41 98.00 123.47 196.00 329.63 392.00 493.88 587.33 987.77 10.36 82.41 98.00 123.47 196.00 329.63 392.00 493.88 587.33 987.77 10.37 82.41 98.00 123.47 196.00 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.38 82.41 98.00 123.47 196.00 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.39 82.41 98.00 123.47 196.00 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.40 82.41 123.47 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.41 82.41 123.47 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.42 82.41 123.47 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.43 82.41 123.47 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.44 82.41 123.47 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.45 82.41 123.47 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.46 82.41 123.47 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.47 82.41 123.47 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.48 82.41 123.47 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.49 82.41 123.47 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.50 82.41 123.47 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.51 82.41 123.47 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.52 82.41 123.47 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.53 82.41 123.47 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.54 82.41 123.47 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.55 82.41 123.47 246.94 329.63 392.00 493.88 587.33 783.99 987.77 10.56 82.41 123.47 246.94 329.63 392.00 493.88 783.99 987.77 10.57 82.41 123.47 246.94 329.63 392.00 493.88 783.99 987.77 10.58 82.41 123.47 246.94 329.63 392.00 493.88 783.99 987.77 10.59 82.41 123.47 246.94 329.63 392.00 493.88 987.77 10.60 82.41 123.47 246.94 329.63 392.00 493.88 987.77 10.61 82.41 123.47 246.94 329.63 392.00 493.88 987.77 10.62 82.41 123.47 246.94 329.63 392.00 493.88 987.77 10.63 82.41 123.47 246.94 329.63 493.88 987.77 10.64 82.41 123.47 246.94 329.63 493.88 987.77 10.65 82.41 196.00 246.94 329.63 493.88 987.77 10.66 82.41 196.00 246.94 329.63 493.88 987.77 10.67 82.41 196.00 246.94 329.63 493.88 987.77 10.68 196.00 246.94 329.63 493.88 987.77 10.69 196.00 246.94 329.63 493.88 987.77 10.70 196.00 246.94 329.63 493.88 987.77 10.71 98.00 196.00 246.94 329.63 493.88 659.26 987.77 10.72 98.00 196.00 246.94 293.66 329.63 493.88 659.26 987.77 10.73 98.00 196.00 246.94 293.66 329.63 493.88 659.26 987.77 10.74 98.00 196.00 246.94 293.66 329.63 493.88 659.26 987.77 10.75 98.00 196.00 246.94 293.66 329.63 493.88 659.26 987.77 10.76 98.00 196.00 246.94 293.66 329.63 493.88 659.26 987.77 10.77 98.00 196.00 246.94 293.66 329.63 493.88 659.26 987.77 10.78 98.00 196.00 246.94 293.66 329.63 493.88 987.77 10.79 98.00 196.00 293.66 329.63 493.88 987.77 10.80 98.00 196.00 293.66 329.63 493.88 987.77 10.81 98.00 196.00 293.66 329.63 493.88 987.77 10.82 98.00 196.00 293.66 329.63 493.88 587.33 987.77 10.83 98.00 196.00 293.66 329.63 493.88 587.33 987.77 10.84 196.00 293.66 493.88 554.37 587.33 987.77 10.85 196.00 554.37 587.33 987.77 10.86 196.00 554.37 587.33 987.77 10.87 196.00 554.37 587.33 987.77 10.88 196.00 554.37 587.33 987.77 10.89 196.00 554.37 587.33 987.77 10.90 196.00 554.37 587.33 987.77 10.91 196.00 554.37 987.77 10.92 196.00 987.77 10.93 196.00 493.88 987.77 10.94 196.00 493.88 987.77 10.95 196.00 493.88 987.77 10.96 196.00 493.88 987.77 10.97 196.00 493.88 987.77 10.98 196.00 493.88 987.77 10.99 196.00 493.88 987.77 1174.66 11.00 196.00 493.88 987.77 1174.66 11.01 196.00 493.88 987.77 1174.66 11.02 196.00 493.88 587.33 987.77 1174.66 11.03 196.00 493.88 587.33 987.77 1174.66 11.04 196.00 493.88 587.33 1174.66 11.05 196.00 493.88 587.33 1174.66 11.06 196.00 493.88 587.33 1174.66 11.07 196.00 493.88 587.33 1174.66 11.08 196.00 493.88 587.33 1174.66 11.09 196.00 493.88 587.33 1174.66 11.10 196.00 246.94 493.88 587.33 1174.66 11.11 246.94 493.88 1174.66 11.12 246.94 493.88 1174.66 11.13 246.94 493.88 1174.66 11.14 246.94 493.88 1174.66 11.15 246.94 493.88 1174.66 11.16 185.00 246.94 493.88 1174.66 11.17 185.00 246.94 493.88 1174.66 11.18 185.00 246.94 493.88 1174.66 11.19 185.00 246.94 493.88 1174.66 11.20 185.00 246.94 493.88 1174.66 11.21 185.00 246.94 493.88 1174.66 11.22 185.00 246.94 493.88 1174.66 11.23 185.00 246.94 493.88 1174.66 11.24 185.00 246.94 493.88 1174.66 11.25 185.00 246.94 493.88 1174.66 11.26 185.00 246.94 493.88 1174.66 11.27 185.00 246.94 493.88 1174.66 11.28 185.00 246.94 493.88 1174.66 11.29 185.00 246.94 493.88 1174.66 11.30 185.00 246.94 493.88 1174.66 11.31 185.00 246.94 493.88 1174.66 11.32 185.00 246.94 493.88 587.33 1174.66 11.33 185.00 246.94 493.88 587.33 1174.66 11.34 185.00 246.94 493.88 587.33 1174.66 11.35 185.00 246.94 493.88 587.33 987.77 1174.66 11.36 185.00 246.94 493.88 587.33 987.77 1174.66 11.37 185.00 246.94 493.88 587.33 987.77 1174.66 11.38 185.00 246.94 493.88 587.33 987.77 1174.66 11.39 185.00 246.94 493.88 587.33 987.77 1174.66 11.40 185.00 246.94 493.88 587.33 987.77 1174.66 11.41 185.00 246.94 493.88 587.33 987.77 1174.66 11.42 185.00 246.94 493.88 587.33 987.77 1174.66 11.43 123.47 185.00 246.94 493.88 587.33 987.77 1174.66 11.44 123.47 185.00 246.94 493.88 587.33 987.77 1174.66 11.45 123.47 185.00 246.94 493.88 587.33 987.77 1174.66 11.46 123.47 185.00 246.94 493.88 587.33 987.77 1174.66 11.47 123.47 185.00 246.94 493.88 587.33 987.77 1174.66 11.48 123.47 185.00 246.94 493.88 587.33 987.77 1174.66 11.49 123.47 185.00 246.94 493.88 587.33 987.77 1174.66 11.50 123.47 185.00 246.94 493.88 587.33 987.77 1174.66 11.51 123.47 185.00 246.94 493.88 587.33 987.77 1174.66 11.52 123.47 185.00 246.94 493.88 587.33 987.77 11.53 123.47 185.00 246.94 493.88 587.33 987.77 11.54 123.47 185.00 246.94 493.88 587.33 987.77 11.55 123.47 185.00 246.94 493.88 587.33 987.77 11.56 123.47 185.00 246.94 493.88 587.33 987.77 11.57 123.47 185.00 246.94 493.88 587.33 987.77 11.58 123.47 185.00 246.94 493.88 587.33 987.77 11.59 123.47 185.00 246.94 493.88 587.33 987.77 11.60 123.47 185.00 246.94 493.88 587.33 987.77 11.61 123.47 185.00 246.94 493.88 587.33 987.77 11.62 123.47 185.00 246.94 493.88 587.33 987.77 11.63 123.47 185.00 246.94 493.88 587.33 987.77 11.64 123.47 185.00 246.94 493.88 587.33 987.77 11.65 123.47 185.00 246.94 493.88 587.33 987.77 11.66 123.47 185.00 246.94 493.88 587.33 987.77 11.67 123.47 185.00 246.94 493.88 587.33 987.77 11.68 123.47 185.00 246.94 493.88 587.33 987.77 11.69 123.47 185.00 246.94 293.66 493.88 587.33 987.77 11.70 123.47 185.00 246.94 293.66 493.88 987.77 1975.53 11.71 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 1975.53 11.72 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 1975.53 11.73 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 1975.53 11.74 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 1975.53 11.75 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 1975.53 11.76 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 1975.53 11.77 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 1975.53 11.78 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 1975.53 11.79 123.47 185.00 246.94 493.88 987.77 1318.51 1975.53 11.80 123.47 185.00 246.94 493.88 987.77 1318.51 1975.53 11.81 123.47 185.00 246.94 493.88 987.77 1318.51 1975.53 11.82 123.47 185.00 246.94 493.88 987.77 1318.51 1975.53 11.83 123.47 185.00 246.94 493.88 987.77 1318.51 1975.53 11.84 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 1975.53 11.85 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 1975.53 11.86 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 1975.53 11.87 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 11.88 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 11.89 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 11.90 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 11.91 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 11.92 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 11.93 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 11.94 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 11.95 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 11.96 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 11.97 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 11.98 123.47 185.00 246.94 293.66 493.88 987.77 1318.51 11.99 123.47 185.00 246.94 293.66 1318.51 12.00 123.47 185.00 246.94 293.66 1318.51 12.01 123.47 185.00 246.94 293.66 1318.51 12.02 123.47 185.00 246.94 293.66 1318.51 12.03 123.47 185.00 246.94 293.66 1318.51 12.04 123.47 185.00 246.94 293.66 1318.51 12.05 123.47 185.00 246.94 293.66 1318.51 12.06 123.47 185.00 246.94 293.66 1318.51 12.07 123.47 185.00 246.94 293.66 1318.51 12.08 123.47 185.00 246.94 293.66 1318.51 12.09 185.00 293.66 587.33 1174.66 12.10 185.00 293.66 587.33 1174.66 12.11 185.00 293.66 587.33 1174.66 12.12 185.00 293.66 587.33 1174.66 12.13 185.00 293.66 587.33 1174.66 12.14 185.00 293.66 587.33 1174.66 12.15 185.00 246.94 293.66 587.33 1174.66 12.16 185.00 246.94 293.66 587.33 1174.66 12.17 185.00 246.94 293.66 369.99 587.33 1174.66 12.18 185.00 246.94 293.66 369.99 587.33 1174.66 12.19 185.00 246.94 293.66 369.99 440.00 587.33 1174.66 12.20 185.00 246.94 293.66 369.99 440.00 587.33 1174.66 12.21 185.00 246.94 293.66 369.99 440.00 587.33 1174.66 12.22 185.00 246.94 293.66 369.99 440.00 587.33 1174.66 12.23 185.00 246.94 293.66 369.99 440.00 587.33 1174.66 12.24 185.00 246.94 293.66 369.99 440.00 587.33 1174.66 12.25 61.74 123.47 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.26 61.74 123.47 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.27 61.74 123.47 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.28 61.74 123.47 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.29 61.74 123.47 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.30 61.74 123.47 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.31 61.74 123.47 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.32 61.74 123.47 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.33 61.74 123.47 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.34 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.35 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.36 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.37 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.38 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.39 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.40 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.41 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.42 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.43 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.44 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.45 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.46 185.00 246.94 293.66 369.99 440.00 587.33 1108.73 1174.66 12.47 185.00 246.94 293.66 369.99 440.00 587.33 12.48 185.00 246.94 293.66 369.99 440.00 587.33 12.49 185.00 293.66 369.99 440.00 587.33 12.50 185.00 293.66 440.00 587.33 12.51 185.00 293.66 587.33 12.52 293.66 587.33 12.53 293.66 587.33 12.54 82.41 164.81 293.66 415.30 587.33 12.55 82.41 164.81 293.66 415.30 587.33 12.56 82.41 164.81 293.66 415.30 587.33 12.57 82.41 164.81 293.66 415.30 587.33 12.58 82.41 164.81 246.94 293.66 415.30 587.33 12.59 82.41 164.81 246.94 293.66 415.30 587.33 12.60 82.41 164.81 246.94 293.66 415.30 587.33 12.61 82.41 164.81 246.94 293.66 415.30 493.88 587.33 987.77 12.62 82.41 164.81 246.94 293.66 415.30 493.88 587.33 987.77 12.63 82.41 164.81 246.94 293.66 415.30 493.88 587.33 987.77 12.64 82.41 164.81 246.94 293.66 415.30 493.88 587.33 987.77 12.65 82.41 164.81 246.94 415.30 493.88 587.33 987.77 12.66 82.41 164.81 246.94 415.30 493.88 587.33 987.77 12.67 82.41 164.81 246.94 415.30 493.88 587.33 987.77 12.68 82.41 164.81 246.94 415.30 493.88 587.33 987.77 12.69 82.41 164.81 246.94 415.30 493.88 587.33 987.77 12.70 82.41 164.81 246.94 415.30 493.88 587.33 987.77 12.71 82.41 164.81 246.94 415.30 493.88 587.33 987.77 12.72 82.41 164.81 246.94 415.30 493.88 587.33 987.77 12.73 82.41 164.81 246.94 415.30 493.88 587.33 987.77 12.74 82.41 164.81 246.94 415.30 493.88 587.33 987.77 12.75 82.41 164.81 246.94 415.30 493.88 587.33 987.77 12.76 82.41 164.81 415.30 493.88 587.33 987.77 12.77 82.41 164.81 415.30 493.88 587.33 987.77 12.78 82.41 164.81 415.30 493.88 587.33 987.77 12.79 82.41 164.81 415.30 493.88 587.33 987.77 12.80 82.41 164.81 415.30 493.88 587.33 987.77 12.81 82.41 164.81 415.30 493.88 587.33 987.77 12.82 82.41 164.81 415.30 493.88 587.33 987.77 12.83 82.41 164.81 415.30 493.88 587.33 987.77 12.84 82.41 164.81 415.30 493.88 587.33 987.77 12.85 82.41 164.81 415.30 493.88 587.33 987.77 12.86 82.41 164.81 415.30 493.88 587.33 987.77 12.87 82.41 164.81 246.94 369.99 493.88 587.33 987.77 12.88 82.41 164.81 246.94 369.99 493.88 987.77 12.89 82.41 164.81 246.94 369.99 493.88 987.77 12.90 82.41 164.81 246.94 369.99 493.88 987.77 12.91 82.41 164.81 246.94 369.99 493.88 987.77 12.92 82.41 164.81 246.94 369.99 493.88 987.77 12.93 82.41 164.81 246.94 369.99 493.88 987.77 12.94 82.41 164.81 246.94 369.99 493.88 987.77 12.95 82.41 164.81 246.94 369.99 493.88 987.77 12.96 82.41 164.81 246.94 369.99 493.88 987.77 12.97 164.81 246.94 369.99 493.88 987.77 12.98 164.81 246.94 369.99 493.88 739.99 987.77 12.99 164.81 246.94 369.99 493.88 739.99 987.77 13.00 164.81 246.94 369.99 493.88 739.99 987.77 13.01 164.81 246.94 369.99 493.88 739.99 987.77 13.02 164.81 246.94 369.99 493.88 739.99 987.77 13.03 164.81 246.94 369.99 493.88 739.99 987.77 13.04 164.81 369.99 493.88 739.99 987.77 13.05 164.81 369.99 493.88 739.99 987.77 13.06 164.81 369.99 493.88 739.99 987.77 13.07 164.81 369.99 493.88 987.77 13.08 164.81 369.99 493.88 987.77 13.09 164.81 369.99 493.88 987.77 13.10 164.81 369.99 493.88 987.77 13.11 164.81 369.99 493.88 987.77 13.12 164.81 369.99 493.88 739.99 987.77 13.13 164.81 369.99 493.88 739.99 987.77 13.14 164.81 369.99 493.88 739.99 987.77 13.15 164.81 369.99 493.88 739.99 987.77 13.16 164.81 369.99 415.30 493.88 739.99 987.77 13.17 164.81 369.99 415.30 493.88 739.99 987.77 13.18 164.81 369.99 415.30 493.88 739.99 987.77 13.19 164.81 369.99 415.30 493.88 739.99 987.77 13.20 164.81 369.99 415.30 493.88 739.99 987.77 13.21 164.81 369.99 415.30 493.88 739.99 987.77 13.22 164.81 369.99 415.30 493.88 739.99 987.77 13.23 164.81 369.99 415.30 493.88 739.99 987.77 13.24 164.81 369.99 415.30 493.88 739.99 987.77 13.25 164.81 369.99 493.88 739.99 987.77 13.26 164.81 369.99 493.88 739.99 987.77 13.27 164.81 369.99 493.88 739.99 987.77 13.28 164.81 329.63 369.99 493.88 739.99 987.77 13.29 164.81 329.63 369.99 493.88 739.99 987.77 13.30 164.81 329.63 369.99 493.88 739.99 987.77 13.31 164.81 329.63 369.99 493.88 739.99 987.77 13.32 164.81 329.63 369.99 493.88 739.99 987.77 13.33 164.81 329.63 369.99 493.88 739.99 987.77 13.34 164.81 329.63 369.99 493.88 739.99 987.77 13.35 164.81 329.63 369.99 493.88 739.99 987.77 13.36 164.81 329.63 369.99 493.88 739.99 987.77 1046.50 13.37 164.81 329.63 369.99 493.88 739.99 987.77 1046.50 13.38 164.81 329.63 369.99 493.88 987.77 1046.50 13.39 164.81 329.63 369.99 493.88 987.77 1046.50 13.40 164.81 329.63 369.99 493.88 987.77 1046.50 13.41 164.81 329.63 369.99 493.88 987.77 1046.50 13.42 164.81 329.63 369.99 493.88 987.77 1046.50 13.43 164.81 329.63 369.99 493.88 987.77 1046.50 13.44 164.81 329.63 369.99 493.88 987.77 1046.50 13.45 82.41 164.81 246.94 329.63 369.99 493.88 987.77 1046.50 13.46 82.41 164.81 246.94 329.63 369.99 493.88 987.77 1046.50 13.47 82.41 164.81 246.94 329.63 369.99 493.88 987.77 1046.50 13.48 82.41 164.81 246.94 329.63 369.99 493.88 987.77 1046.50 13.49 82.41 164.81 246.94 329.63 369.99 493.88 987.77 1046.50 13.50 82.41 164.81 246.94 329.63 369.99 493.88 659.26 987.77 1046.50 13.51 82.41 164.81 246.94 329.63 369.99 493.88 659.26 987.77 1046.50 13.52 82.41 164.81 246.94 329.63 369.99 493.88 659.26 987.77 1046.50 13.53 82.41 164.81 246.94 329.63 369.99 493.88 659.26 987.77 1046.50 13.54 82.41 164.81 246.94 329.63 493.88 659.26 987.77 1046.50 13.55 82.41 164.81 246.94 329.63 493.88 659.26 987.77 1046.50 13.56 82.41 164.81 246.94 329.63 493.88 659.26 987.77 1046.50 13.57 82.41 164.81 246.94 329.63 493.88 659.26 987.77 1046.50 13.58 82.41 164.81 246.94 329.63 493.88 659.26 987.77 1046.50 13.59 82.41 164.81 246.94 329.63 493.88 659.26 987.77 1046.50 13.60 82.41 164.81 246.94 329.63 493.88 659.26 987.77 1046.50 13.61 82.41 164.81 246.94 329.63 493.88 659.26 987.77 1046.50 13.62 164.81 329.63 659.26 987.77 1046.50 13.63 277.18 329.63 659.26 987.77 1046.50 13.64 277.18 329.63 659.26 987.77 1046.50 13.65 277.18 329.63 659.26 987.77 1046.50 13.66 277.18 329.63 659.26 987.77 1046.50 13.67 277.18 329.63 659.26 1046.50 13.68 277.18 329.63 1046.50 13.69 277.18 329.63 1046.50 13.70 277.18 329.63 1046.50 13.71 277.18 329.63 1046.50 13.72 277.18 329.63 369.99 1046.50 13.73 164.81 277.18 329.63 369.99 1046.50 13.74 164.81 277.18 329.63 369.99 1046.50 13.75 164.81 277.18 329.63 369.99 1046.50 13.76 164.81 277.18 329.63 369.99 1046.50 13.77 164.81 277.18 329.63 369.99 1046.50 13.78 164.81 277.18 329.63 369.99 1760.00 13.79 164.81 277.18 329.63 369.99 1760.00 13.80 164.81 277.18 329.63 1760.00 13.81 164.81 277.18 329.63 1760.00 13.82 164.81 277.18 329.63 1760.00 13.83 164.81 277.18 329.63 1760.00 13.84 164.81 277.18 329.63 1760.00 13.85 164.81 277.18 329.63 1760.00 13.86 164.81 277.18 329.63 1760.00 13.87 164.81 277.18 329.63 1760.00 13.88 164.81 277.18 329.63 1760.00 13.89 164.81 277.18 329.63 1760.00 13.90 164.81 277.18 329.63 1760.00 13.91 164.81 277.18 329.63 1760.00 13.92 164.81 277.18 329.63 1760.00 13.93 164.81 277.18 329.63 1760.00 13.94 164.81 277.18 329.63 1760.00 13.95 164.81 277.18 329.63 1760.00 13.96 164.81 277.18 329.63 1760.00 13.97 164.81 277.18 1760.00 13.98 164.81 277.18 1760.00 13.99 164.81 277.18 880.00 1760.00 14.00 164.81 277.18 880.00 1760.00 14.01 164.81 277.18 880.00 1760.00 14.02 164.81 277.18 830.61 880.00 1661.22 1760.00 14.03 164.81 277.18 830.61 880.00 1661.22 1760.00 14.04 164.81 277.18 830.61 880.00 1661.22 1760.00 14.05 164.81 277.18 830.61 880.00 1661.22 1760.00 14.06 164.81 277.18 830.61 880.00 1661.22 1760.00 14.07 164.81 277.18 830.61 880.00 1661.22 1760.00 14.08 164.81 277.18 830.61 880.00 1661.22 1760.00 14.09 164.81 277.18 830.61 880.00 1661.22 1760.00 14.10 164.81 277.18 830.61 880.00 1661.22 1760.00 14.11 164.81 277.18 830.61 880.00 1661.22 1760.00 14.12 164.81 277.18 830.61 880.00 1661.22 1760.00 14.13 164.81 277.18 830.61 880.00 1661.22 1760.00 14.14 164.81 277.18 830.61 880.00 1661.22 1760.00 14.15 164.81 277.18 830.61 880.00 1661.22 1760.00 14.16 164.81 277.18 830.61 880.00 1661.22 1760.00 14.17 164.81 277.18 830.61 880.00 1661.22 1760.00 14.18 164.81 277.18 329.63 830.61 880.00 1661.22 1760.00 14.19 164.81 329.63 830.61 880.00 1661.22 1760.00 14.20 164.81 293.66 329.63 830.61 880.00 1661.22 1760.00 14.21 164.81 293.66 329.63 830.61 880.00 1661.22 1760.00 14.22 164.81 293.66 329.63 830.61 880.00 1661.22 1760.00 14.23 164.81 293.66 329.63 830.61 880.00 1661.22 1760.00 14.24 164.81 293.66 329.63 830.61 880.00 1661.22 1760.00 14.25 164.81 293.66 329.63 830.61 880.00 1661.22 1760.00 14.26 164.81 293.66 329.63 830.61 880.00 1661.22 1760.00 14.27 164.81 293.66 329.63 830.61 880.00 1661.22 1760.00 14.28 164.81 293.66 329.63 830.61 880.00 1661.22 1760.00 14.29 164.81 293.66 329.63 830.61 880.00 1661.22 14.30 164.81 293.66 329.63 830.61 880.00 1661.22 14.31 164.81 293.66 329.63 830.61 880.00 1661.22 14.32 164.81 293.66 329.63 830.61 880.00 1661.22 14.33 164.81 293.66 329.63 830.61 880.00 1661.22 14.34 164.81 293.66 329.63 830.61 880.00 1661.22 14.35 164.81 293.66 329.63 830.61 880.00 1661.22 14.36 164.81 293.66 830.61 880.00 1661.22 14.37 164.81 293.66 830.61 880.00 1661.22 14.38 164.81 293.66 830.61 1661.22 14.39 164.81 293.66 587.33 14.40 164.81 293.66 493.88 587.33 1479.98 14.41 164.81 293.66 493.88 587.33 1479.98 14.42 164.81 293.66 493.88 587.33 1479.98 14.43 164.81 293.66 493.88 587.33 1479.98 14.44 164.81 293.66 493.88 587.33 1479.98 14.45 164.81 293.66 493.88 587.33 1479.98 14.46 164.81 293.66 493.88 587.33 1479.98 14.47 164.81 293.66 493.88 587.33 1479.98 14.48 164.81 293.66 493.88 587.33 1479.98 14.49 164.81 293.66 493.88 587.33 14.50 164.81 293.66 493.88 587.33 14.51 164.81 293.66 493.88 587.33 14.52 164.81 293.66 329.63 493.88 14.53 164.81 293.66 329.63 493.88 14.54 164.81 293.66 329.63 14.55 164.81 293.66 329.63 14.56 164.81 293.66 329.63 14.57 164.81 293.66 329.63 14.58 164.81 293.66 329.63 14.59 164.81 293.66 329.63 14.60 164.81 293.66 329.63 14.61 164.81 293.66 329.63 1479.98 14.62 164.81 293.66 329.63 1479.98 14.63 164.81 293.66 329.63 1479.98 14.64 164.81 293.66 329.63 1479.98 14.65 164.81 293.66 329.63 1479.98 14.66 164.81 293.66 1479.98 14.67 164.81 293.66 1479.98 14.68 164.81 293.66 1479.98 14.69 164.81 293.66 1479.98 14.70 164.81 293.66 1479.98 14.71 164.81 293.66 1479.98 14.72 164.81 293.66 1479.98 14.73 164.81 293.66 1479.98 14.74 164.81 293.66 1479.98 14.75 164.81 293.66 1479.98 14.76 164.81 293.66 1479.98 14.77 164.81 1479.98 14.78 164.81 1479.98 14.79 164.81 1479.98 14.80 164.81 14.81 164.81 14.82 14.83 146.83 185.00 14.84 146.83 185.00 14.85 146.83 185.00 14.86 146.83 185.00 14.87 146.83 185.00 14.88 146.83 185.00 277.18 14.89 146.83 185.00 277.18 14.90 146.83 277.18 14.91 146.83 277.18 14.92 146.83 277.18 14.93 146.83 277.18 14.94 146.83 277.18 14.95 146.83 277.18 14.96 277.18 554.37 14.97 277.18 554.37 14.98 277.18 554.37 14.99 277.18 554.37 15.00 277.18 554.37 15.01 277.18 554.37 15.02 277.18 554.37 15.03 185.00 277.18 554.37 15.04 185.00 277.18 554.37 15.05 185.00 277.18 15.06 185.00 277.18 15.07 185.00 277.18 15.08 185.00 277.18 15.09 185.00 277.18 15.10 185.00 277.18 15.11 185.00 277.18 15.12 185.00 277.18 15.13 185.00 277.18 15.14 185.00 277.18 15.15 277.18 15.16 277.18 15.17 207.65 277.18 15.18 207.65 277.18 15.19 207.65 15.20 207.65 15.21 207.65 15.22 207.65 587.33 15.23 82.41 207.65 587.33 15.24 82.41 207.65 587.33 15.25 82.41 207.65 587.33 15.26 82.41 146.83 207.65 587.33 15.27 82.41 146.83 207.65 587.33 15.28 82.41 146.83 207.65 587.33 15.29 82.41 146.83 207.65 587.33 15.30 82.41 146.83 207.65 554.37 587.33 15.31 82.41 146.83 207.65 554.37 15.32 82.41 146.83 207.65 554.37 15.33 82.41 146.83 207.65 554.37 15.34 82.41 146.83 207.65 277.18 554.37 15.35 82.41 146.83 207.65 277.18 554.37 15.36 82.41 146.83 207.65 277.18 554.37 15.37 82.41 146.83 277.18 554.37 15.38 82.41 146.83 277.18 554.37 15.39 82.41 277.18 554.37 15.40 82.41 277.18 554.37 15.41 82.41 277.18 554.37 15.42 277.18 554.37 1318.51 15.43 277.18 554.37 1318.51 15.44 277.18 554.37 1318.51 15.45 277.18 554.37 1318.51 15.46 277.18 554.37 1318.51 15.47 277.18 554.37 1318.51 15.48 277.18 554.37 1318.51 15.49 185.00 277.18 440.00 554.37 1318.51 15.50 185.00 277.18 440.00 554.37 1318.51 15.51 185.00 277.18 440.00 554.37 1318.51 15.52 92.50 185.00 220.00 277.18 440.00 554.37 659.26 1318.51 15.53 92.50 185.00 220.00 277.18 440.00 554.37 659.26 1318.51 15.54 92.50 185.00 220.00 277.18 440.00 554.37 659.26 1318.51 15.55 92.50 185.00 220.00 277.18 440.00 554.37 659.26 1318.51 15.56 92.50 185.00 220.00 277.18 440.00 554.37 659.26 1318.51 15.57 92.50 185.00 220.00 277.18 440.00 554.37 659.26 1318.51 15.58 92.50 185.00 220.00 277.18 440.00 554.37 659.26 1318.51 15.59 92.50 185.00 220.00 277.18 440.00 554.37 659.26 1318.51 15.60 92.50 185.00 220.00 277.18 440.00 554.37 659.26 1318.51 15.61 92.50 185.00 220.00 277.18 554.37 659.26 1318.51 15.62 92.50 185.00 220.00 277.18 554.37 659.26 1318.51 15.63 92.50 185.00 220.00 277.18 554.37 659.26 1318.51 15.64 92.50 185.00 220.00 277.18 554.37 659.26 1318.51 15.65 92.50 185.00 220.00 277.18 554.37 659.26 1318.51 15.66 92.50 185.00 220.00 277.18 554.37 659.26 1318.51 15.67 92.50 185.00 220.00 277.18 554.37 659.26 1318.51 15.68 92.50 185.00 220.00 277.18 554.37 659.26 1318.51 15.69 92.50 185.00 220.00 277.18 554.37 659.26 1318.51 15.70 92.50 185.00 277.18 554.37 659.26 1318.51 15.71 92.50 185.00 277.18 554.37 659.26 1318.51 15.72 92.50 185.00 277.18 554.37 659.26 1318.51 15.73 185.00 277.18 554.37 659.26 1318.51 15.74 185.00 277.18 554.37 659.26 1318.51 15.75 185.00 277.18 554.37 659.26 1318.51 15.76 185.00 277.18 554.37 659.26 1318.51 15.77 185.00 277.18 554.37 659.26 1318.51 15.78 185.00 277.18 659.26 1318.51 15.79 185.00 277.18 659.26 1318.51 15.80 185.00 277.18 659.26 1318.51 15.81 185.00 277.18 659.26 1318.51 15.82 185.00 277.18 659.26 1318.51 15.83 185.00 277.18 659.26 1318.51 15.84 185.00 277.18 659.26 1318.51 15.85 185.00 277.18 587.33 659.26 1318.51 15.86 185.00 277.18 587.33 1174.66 1318.51 15.87 185.00 277.18 587.33 1174.66 1318.51 15.88 185.00 277.18 587.33 1174.66 1318.51 15.89 185.00 277.18 587.33 1174.66 1318.51 15.90 185.00 277.18 587.33 1174.66 1318.51 15.91 185.00 277.18 587.33 1174.66 1318.51 15.92 185.00 277.18 587.33 1174.66 1318.51 15.93 185.00 277.18 587.33 1174.66 1318.51 15.94 185.00 277.18 587.33 1174.66 1318.51 15.95 185.00 277.18 587.33 1174.66 1318.51 15.96 185.00 277.18 587.33 1174.66 1318.51 15.97 185.00 277.18 587.33 1174.66 1318.51 15.98 185.00 277.18 587.33 1174.66 15.99 185.00 277.18 329.63 587.33 1174.66 16.00 185.00 277.18 329.63 587.33 1174.66 16.01 185.00 329.63 587.33 1174.66 16.02 185.00 329.63 587.33 1174.66 16.03 329.63 587.33 1174.66 16.04 329.63 587.33 1174.66 16.05 329.63 587.33 1174.66 16.06 329.63 587.33 1174.66 16.07 329.63 587.33 1174.66 16.08 329.63 587.33 1174.66 16.09 329.63 587.33 1174.66 16.10 329.63 587.33 1174.66 16.11 329.63 587.33 1174.66 16.12 329.63 587.33 1174.66 16.13 329.63 587.33 1174.66 16.14 329.63 587.33 1174.66 16.15 329.63 587.33 1174.66 16.16 329.63 587.33 1174.66 16.17 329.63 369.99 587.33 1174.66 16.18 369.99 587.33 1174.66 16.19 369.99 587.33 1174.66 16.20 220.00 293.66 369.99 587.33 1174.66 16.21 185.00 220.00 293.66 369.99 1174.66 16.22 185.00 220.00 293.66 369.99 1174.66 16.23 185.00 220.00 293.66 369.99 1174.66 16.24 185.00 220.00 293.66 369.99 1174.66 16.25 185.00 220.00 293.66 369.99 1108.73 1174.66 16.26 185.00 220.00 293.66 369.99 1108.73 1174.66 16.27 185.00 220.00 293.66 369.99 1108.73 1174.66 16.28 185.00 220.00 293.66 369.99 1108.73 1174.66 16.29 185.00 220.00 293.66 369.99 1108.73 1174.66 16.30 185.00 220.00 293.66 369.99 1108.73 1174.66 16.31 185.00 220.00 293.66 369.99 587.33 1108.73 1174.66 16.32 185.00 220.00 293.66 369.99 587.33 1108.73 1174.66 16.33 185.00 220.00 369.99 587.33 1108.73 1174.66 16.34 92.50 185.00 220.00 369.99 587.33 1108.73 1174.66 16.35 92.50 185.00 220.00 369.99 587.33 1108.73 1174.66 16.36 92.50 185.00 220.00 369.99 587.33 1108.73 1174.66 16.37 92.50 185.00 220.00 369.99 587.33 1108.73 1174.66 16.38 92.50 185.00 220.00 369.99 587.33 1108.73 1174.66 16.39 92.50 185.00 220.00 369.99 587.33 1108.73 1174.66 16.40 92.50 185.00 220.00 369.99 587.33 1108.73 1174.66 16.41 92.50 185.00 220.00 369.99 587.33 1108.73 1174.66 16.42 92.50 185.00 220.00 369.99 587.33 1108.73 1174.66 16.43 92.50 185.00 220.00 369.99 587.33 1108.73 1174.66 16.44 92.50 185.00 220.00 369.99 587.33 1108.73 1174.66 16.45 92.50 185.00 220.00 369.99 1108.73 1174.66 16.46 92.50 185.00 220.00 369.99 1108.73 1174.66 16.47 92.50 185.00 220.00 369.99 1108.73 1174.66 16.48 92.50 185.00 220.00 369.99 1108.73 1174.66 16.49 92.50 220.00 369.99 1108.73 1174.66 16.50 92.50 220.00 369.99 1108.73 1174.66 16.51 92.50 220.00 369.99 1108.73 1174.66 16.52 92.50 220.00 293.66 369.99 1108.73 1174.66 16.53 92.50 220.00 293.66 369.99 1108.73 1174.66 16.54 92.50 293.66 369.99 1108.73 1174.66 16.55 92.50 293.66 369.99 1108.73 1174.66 16.56 92.50 185.00 293.66 369.99 1108.73 1174.66 16.57 92.50 185.00 293.66 369.99 1108.73 1174.66 16.58 92.50 185.00 293.66 369.99 1108.73 1174.66 16.59 92.50 185.00 369.99 1108.73 1174.66 16.60 92.50 185.00 369.99 1108.73 1174.66 16.61 92.50 185.00 329.63 369.99 1108.73 1174.66 16.62 92.50 185.00 329.63 369.99 1108.73 1174.66 16.63 92.50 185.00 329.63 369.99 1108.73 1174.66 16.64 92.50 185.00 329.63 369.99 554.37 987.77 1108.73 1174.66 16.65 92.50 185.00 329.63 369.99 554.37 987.77 1108.73 1174.66 16.66 92.50 185.00 329.63 369.99 554.37 987.77 1108.73 1174.66 16.67 92.50 185.00 329.63 369.99 554.37 987.77 1108.73 1174.66 16.68 185.00 329.63 369.99 554.37 987.77 1108.73 1174.66 16.69 185.00 329.63 369.99 554.37 987.77 1108.73 1174.66 16.70 185.00 329.63 369.99 554.37 987.77 1108.73 1174.66 16.71 185.00 329.63 369.99 554.37 987.77 1108.73 1174.66 16.72 185.00 329.63 369.99 554.37 987.77 1108.73 1174.66 16.73 185.00 329.63 369.99 554.37 987.77 1108.73 1174.66 16.74 185.00 329.63 369.99 554.37 987.77 1108.73 1174.66 16.75 185.00 329.63 369.99 554.37 987.77 1108.73 1174.66 16.76 185.00 329.63 554.37 987.77 1108.73 1174.66 16.77 185.00 329.63 554.37 1108.73 1174.66 16.78 185.00 329.63 1108.73 1174.66 16.79 185.00 207.65 329.63 587.33 1108.73 1174.66 16.80 185.00 207.65 329.63 587.33 1108.73 1174.66 16.81 207.65 329.63 587.33 1108.73 1174.66 16.82 207.65 293.66 329.63 587.33 1108.73 1174.66 16.83 207.65 293.66 329.63 587.33 1108.73 1174.66 16.84 207.65 293.66 329.63 587.33 1174.66 16.85 207.65 293.66 329.63 587.33 1174.66 16.86 207.65 293.66 329.63 587.33 1174.66 16.87 207.65 293.66 587.33 1174.66 16.88 207.65 293.66 587.33 1174.66 16.89 207.65 587.33 1174.66 16.90 207.65 587.33 1174.66 16.91 587.33 1174.66 16.92 587.33 1174.66 16.93 554.37 587.33 1174.66 16.94 554.37 587.33 1174.66 16.95 554.37 587.33 1174.66 16.96 293.66 440.00 554.37 587.33 1174.66 16.97 293.66 440.00 554.37 16.98 293.66 440.00 554.37 880.00 16.99 293.66 440.00 554.37 880.00 17.00 293.66 440.00 554.37 880.00 17.01 293.66 440.00 554.37 880.00 17.02 293.66 440.00 554.37 880.00 17.03 293.66 440.00 554.37 587.33 880.00 17.04 293.66 440.00 554.37 587.33 880.00 17.05 293.66 440.00 587.33 880.00 17.06 293.66 440.00 587.33 880.00 17.07 293.66 440.00 587.33 880.00 17.08 293.66 440.00 587.33 880.00 17.09 293.66 440.00 587.33 880.00 17.10 293.66 440.00 587.33 880.00 17.11 293.66 440.00 587.33 880.00 17.12 440.00 880.00 17.13 440.00 880.00 17.14 17.15 17.16 554.37 17.17 554.37 17.18 554.37 17.19 220.00 440.00 554.37 880.00 1108.73 17.20 220.00 440.00 554.37 880.00 1108.73 17.21 220.00 440.00 554.37 880.00 1108.73 17.22 220.00 329.63 440.00 554.37 880.00 1108.73 17.23 220.00 329.63 440.00 554.37 880.00 1108.73 17.24 220.00 329.63 440.00 554.37 880.00 1108.73 17.25 220.00 329.63 440.00 554.37 880.00 1108.73 17.26 220.00 329.63 440.00 554.37 880.00 1108.73 17.27 220.00 329.63 440.00 554.37 880.00 1108.73 17.28 220.00 329.63 440.00 554.37 880.00 1108.73 17.29 220.00 329.63 440.00 554.37 880.00 1108.73 17.30 220.00 329.63 440.00 554.37 880.00 1108.73 17.31 220.00 329.63 440.00 554.37 880.00 1108.73 17.32 220.00 440.00 554.37 880.00 1108.73 1174.66 17.33 110.00 220.00 440.00 554.37 880.00 1108.73 1174.66 17.34 110.00 554.37 1108.73 1174.66 17.35 110.00 554.37 1108.73 1174.66 17.36 110.00 554.37 1108.73 1174.66 17.37 110.00 554.37 1108.73 1174.66 17.38 110.00 554.37 1108.73 1174.66 17.39 110.00 554.37 1108.73 1174.66 17.40 110.00 554.37 1108.73 1174.66 17.41 110.00 554.37 1108.73 1174.66 17.42 110.00 554.37 1108.73 1174.66 17.43 110.00 554.37 1108.73 1174.66 17.44 110.00 554.37 1108.73 1174.66 17.45 110.00 554.37 1108.73 1174.66 17.46 110.00 164.81 554.37 1108.73 1174.66 17.47 110.00 164.81 554.37 1108.73 1174.66 17.48 110.00 164.81 554.37 1108.73 1174.66 1318.51 17.49 110.00 164.81 554.37 1174.66 1318.51 17.50 110.00 164.81 554.37 1174.66 1318.51 17.51 110.00 164.81 554.37 1174.66 1318.51 17.52 110.00 164.81 554.37 1174.66 1318.51 17.53 110.00 164.81 554.37 1174.66 1318.51 17.54 110.00 164.81 1174.66 1318.51 17.55 110.00 164.81 1174.66 1318.51 17.56 110.00 164.81 1174.66 1318.51 17.57 110.00 164.81 1174.66 1318.51 17.58 110.00 164.81 1174.66 1318.51 17.59 110.00 164.81 1174.66 1318.51 17.60 110.00 164.81 1318.51 17.61 110.00 164.81 1318.51 17.62 110.00 164.81 1318.51 17.63 110.00 164.81 1318.51 17.64 110.00 164.81 1318.51 17.65 110.00 164.81 1318.51 17.66 110.00 164.81 1318.51 1479.98 17.67 110.00 164.81 1318.51 1479.98 17.68 110.00 164.81 1318.51 1479.98 17.69 110.00 164.81 1318.51 1479.98 17.70 110.00 185.00 1174.66 1318.51 1479.98 17.71 92.50 110.00 185.00 1174.66 1318.51 1479.98 17.72 92.50 185.00 1174.66 1318.51 1479.98 17.73 92.50 138.59 185.00 1174.66 1318.51 1479.98 17.74 92.50 138.59 185.00 1174.66 1318.51 1479.98 17.75 92.50 138.59 185.00 220.00 1174.66 1318.51 1479.98 17.76 92.50 138.59 185.00 220.00 1174.66 1479.98 17.77 92.50 138.59 185.00 220.00 1174.66 1479.98 17.78 92.50 138.59 185.00 220.00 1174.66 1479.98 17.79 92.50 138.59 185.00 220.00 1174.66 1479.98 17.80 92.50 138.59 185.00 220.00 1174.66 1479.98 17.81 92.50 138.59 185.00 220.00 1174.66 1479.98 17.82 92.50 138.59 185.00 220.00 1174.66 1479.98 17.83 92.50 138.59 185.00 220.00 1174.66 1479.98 17.84 92.50 138.59 185.00 220.00 1174.66 1479.98 1567.98 17.85 138.59 185.00 220.00 440.00 1479.98 1567.98 17.86 138.59 185.00 220.00 329.63 440.00 1479.98 1567.98 17.87 138.59 185.00 220.00 329.63 440.00 1479.98 1567.98 17.88 138.59 185.00 220.00 329.63 440.00 1479.98 1567.98 17.89 138.59 185.00 220.00 329.63 440.00 1479.98 1567.98 17.90 138.59 185.00 220.00 329.63 440.00 1479.98 1567.98 17.91 138.59 185.00 220.00 329.63 440.00 1479.98 1567.98 17.92 138.59 185.00 220.00 329.63 440.00 1479.98 1567.98 17.93 185.00 220.00 329.63 440.00 1479.98 1567.98 17.94 185.00 220.00 329.63 440.00 1479.98 1567.98 17.95 185.00 220.00 329.63 440.00 1479.98 1567.98 17.96 185.00 220.00 329.63 440.00 1479.98 1567.98 17.97 185.00 220.00 329.63 440.00 1479.98 1567.98 17.98 185.00 220.00 329.63 440.00 1479.98 1567.98 17.99 185.00 220.00 329.63 440.00 1479.98 1567.98 18.00 185.00 220.00 329.63 440.00 1479.98 1567.98 18.01 138.59 185.00 220.00 329.63 440.00 1479.98 1567.98 18.02 138.59 185.00 220.00 329.63 1479.98 1567.98 18.03 138.59 185.00 220.00 329.63 1479.98 1567.98 18.04 138.59 185.00 220.00 329.63 1479.98 1567.98 18.05 138.59 185.00 220.00 329.63 1479.98 1567.98 18.06 92.50 138.59 185.00 220.00 329.63 1479.98 1567.98 18.07 92.50 138.59 185.00 220.00 329.63 1479.98 1567.98 18.08 92.50 138.59 185.00 220.00 329.63 1479.98 18.09 92.50 138.59 220.00 1479.98 18.10 92.50 138.59 220.00 1479.98 18.11 92.50 138.59 220.00 369.99 739.99 1479.98 18.12 92.50 138.59 369.99 739.99 1479.98 18.13 138.59 369.99 739.99 1479.98 18.14 369.99 739.99 1479.98 18.15 110.00 369.99 739.99 1479.98 18.16 110.00 369.99 739.99 1479.98 18.17 110.00 369.99 739.99 18.18 110.00 369.99 739.99 1318.51 18.19 110.00 369.99 739.99 1318.51 18.20 110.00 369.99 739.99 1318.51 18.21 110.00 369.99 739.99 1318.51 18.22 110.00 369.99 739.99 1318.51 18.23 110.00 369.99 739.99 1318.51 18.24 110.00 369.99 739.99 1318.51 18.25 110.00 369.99 739.99 1318.51 18.26 110.00 369.99 739.99 1318.51 18.27 110.00 369.99 739.99 1318.51 18.28 369.99 739.99 1318.51 18.29 369.99 739.99 1318.51 18.30 369.99 739.99 1318.51 18.31 369.99 1318.51 18.32 369.99 1318.51 18.33 369.99 1318.51 18.34 369.99 18.35 369.99 18.36 369.99 18.37 369.99 1174.66 18.38 369.99 1174.66 18.39 110.00 369.99 1174.66 18.40 110.00 369.99 1174.66 18.41 110.00 369.99 1174.66 18.42 110.00 369.99 1174.66 18.43 110.00 369.99 1174.66 18.44 110.00 1174.66 18.45 110.00 1174.66 18.46 110.00 1174.66 18.47 110.00 1174.66 18.48 110.00 1174.66 18.49 110.00 739.99 1174.66 18.50 110.00 739.99 1174.66 18.51 110.00 739.99 1174.66 18.52 110.00 739.99 18.53 110.00 739.99 18.54 110.00 698.46 739.99 18.55 110.00 698.46 739.99 18.56 110.00 698.46 739.99 18.57 110.00 698.46 739.99 18.58 698.46 739.99 1108.73 18.59 698.46 739.99 1108.73 18.60 349.23 698.46 739.99 1108.73 18.61 349.23 698.46 1108.73 18.62 138.59 349.23 698.46 1108.73 18.63 138.59 349.23 698.46 1108.73 18.64 138.59 349.23 698.46 1108.73 18.65 138.59 349.23 698.46 1108.73 18.66 138.59 349.23 698.46 739.99 1108.73 18.67 69.30 138.59 349.23 698.46 739.99 1108.73 18.68 69.30 138.59 349.23 698.46 739.99 1108.73 18.69 69.30 138.59 349.23 739.99 1108.73 18.70 69.30 138.59 349.23 739.99 1108.73 18.71 69.30 138.59 349.23 739.99 1108.73 18.72 69.30 138.59 349.23 739.99 1108.73 18.73 69.30 138.59 349.23 739.99 1108.73 18.74 69.30 138.59 349.23 1108.73 18.75 69.30 138.59 349.23 1108.73 18.76 69.30 138.59 349.23 1108.73 18.77 69.30 138.59 349.23 1108.73 18.78 69.30 138.59 349.23 1108.73 18.79 69.30 138.59 349.23 1108.73 18.80 69.30 138.59 349.23 1108.73 18.81 69.30 138.59 349.23 1108.73 18.82 69.30 138.59 349.23 1108.73 18.83 69.30 138.59 349.23 1108.73 18.84 138.59 349.23 1108.73 18.85 138.59 349.23 1108.73 18.86 349.23 1108.73 18.87 349.23 1108.73 18.88 349.23 1108.73 18.89 349.23 1108.73 18.90 349.23 1108.73 18.91 349.23 1108.73 18.92 349.23 1108.73 18.93 349.23 1108.73 18.94 554.37 1108.73 18.95 277.18 554.37 1108.73 18.96 138.59 277.18 554.37 1108.73 18.97 138.59 277.18 554.37 1108.73 18.98 138.59 277.18 554.37 1108.73 18.99 138.59 277.18 554.37 1108.73 19.00 138.59 277.18 554.37 1108.73 19.01 138.59 277.18 554.37 1108.73 19.02 69.30 138.59 277.18 554.37 1108.73 19.03 69.30 138.59 277.18 554.37 1108.73 19.04 69.30 138.59 277.18 554.37 1108.73 19.05 69.30 138.59 277.18 554.37 1108.73 19.06 69.30 138.59 277.18 554.37 1108.73 19.07 69.30 138.59 277.18 554.37 1108.73 19.08 69.30 138.59 277.18 554.37 1108.73 19.09 69.30 138.59 277.18 554.37 1108.73 19.10 69.30 138.59 277.18 554.37 1108.73 19.11 69.30 138.59 277.18 554.37 1108.73 19.12 69.30 138.59 277.18 554.37 1108.73 19.13 69.30 138.59 277.18 554.37 1108.73 19.14 69.30 138.59 277.18 554.37 1108.73 19.15 69.30 138.59 277.18 554.37 1108.73 19.16 69.30 138.59 277.18 554.37 1108.73 19.17 69.30 138.59 277.18 554.37 1108.73 19.18 69.30 138.59 277.18 554.37 1108.73 19.19 69.30 138.59 277.18 554.37 1108.73 19.20 69.30 138.59 277.18 554.37 1108.73 19.21 138.59 277.18 554.37 1108.73 19.22 138.59 277.18 554.37 1108.73 19.23 138.59 277.18 554.37 1108.73 19.24 138.59 277.18 554.37 1108.73 19.25 138.59 277.18 554.37 1108.73 19.26 138.59 277.18 554.37 1108.73 19.27 138.59 277.18 554.37 1108.73 19.28 138.59 277.18 554.37 1108.73 19.29 138.59 277.18 554.37 1108.73 19.30 138.59 277.18 554.37 587.33 19.31 138.59 554.37 587.33 19.32 138.59 369.99 554.37 587.33 19.33 138.59 369.99 554.37 587.33 19.34 138.59 369.99 554.37 587.33 19.35 369.99 554.37 587.33 19.36 369.99 554.37 587.33 19.37 369.99 554.37 587.33 19.38 369.99 554.37 587.33 19.39 369.99 554.37 587.33 19.40 369.99 554.37 587.33 19.41 369.99 554.37 587.33 19.42 369.99 554.37 587.33 19.43 369.99 554.37 587.33 19.44 369.99 554.37 587.33 19.45 369.99 554.37 587.33 19.46 369.99 554.37 587.33 19.47 369.99 587.33 19.48 369.99 587.33 19.49 369.99 587.33 19.50 369.99 587.33 19.51 369.99 587.33 19.52 369.99 587.33 19.53 369.99 587.33 19.54 369.99 587.33 19.55 587.33 19.56 587.33 19.57 587.33 19.58 587.33 19.59 587.33 19.60 587.33 19.61 587.33 19.62 369.99 587.33 19.63 369.99 587.33 19.64 369.99 587.33 19.65 369.99 587.33 19.66 369.99 587.33 19.67 369.99 587.33 19.68 246.94 369.99 587.33 19.69 246.94 369.99 587.33 19.70 246.94 369.99 587.33 19.71 246.94 369.99 587.33 19.72 246.94 369.99 587.33 19.73 246.94 369.99 587.33 19.74 246.94 369.99 493.88 587.33 19.75 246.94 369.99 493.88 587.33 739.99 1479.98 19.76 246.94 369.99 493.88 587.33 739.99 1479.98 19.77 246.94 369.99 493.88 587.33 739.99 1479.98 19.78 246.94 369.99 493.88 587.33 739.99 1479.98 19.79 246.94 369.99 493.88 587.33 739.99 1479.98 19.80 246.94 369.99 493.88 587.33 739.99 1479.98 19.81 246.94 369.99 493.88 587.33 739.99 1479.98 19.82 246.94 369.99 493.88 587.33 739.99 1479.98 19.83 246.94 369.99 493.88 587.33 739.99 1479.98 19.84 246.94 369.99 493.88 587.33 739.99 1479.98 19.85 246.94 369.99 493.88 739.99 1479.98 19.86 246.94 369.99 493.88 739.99 1479.98 19.87 246.94 369.99 493.88 739.99 1479.98 19.88 246.94 369.99 493.88 739.99 1479.98 19.89 246.94 369.99 493.88 739.99 1479.98 19.90 246.94 369.99 493.88 739.99 1479.98 19.91 246.94 369.99 493.88 739.99 1479.98 19.92 246.94 369.99 493.88 739.99 1479.98 19.93 246.94 369.99 493.88 739.99 1479.98 19.94 246.94 369.99 493.88 739.99 1479.98 19.95 246.94 369.99 493.88 739.99 1479.98 19.96 246.94 369.99 493.88 739.99 1479.98 19.97 246.94 369.99 493.88 739.99 1479.98 19.98 246.94 369.99 493.88 739.99 1479.98 19.99 246.94 369.99 493.88 739.99 1479.98 20.00 246.94 369.99 493.88 739.99 1479.98 20.01 246.94 369.99 493.88 739.99 1479.98 20.02 246.94 369.99 493.88 739.99 1479.98 20.03 246.94 369.99 493.88 739.99 1479.98 20.04 246.94 369.99 493.88 739.99 1479.98 20.05 246.94 369.99 493.88 739.99 1479.98 20.06 246.94 369.99 493.88 739.99 1479.98 20.07 246.94 369.99 493.88 739.99 1479.98 20.08 246.94 369.99 493.88 739.99 1479.98 20.09 246.94 369.99 493.88 739.99 1479.98 20.10 493.88 1479.98 20.11 69.30 207.65 1479.98 20.12 69.30 207.65 349.23 698.46 1396.91 1479.98 20.13 69.30 207.65 349.23 698.46 1396.91 1479.98 20.14 69.30 207.65 349.23 698.46 1396.91 1479.98 20.15 69.30 207.65 349.23 698.46 1396.91 1479.98 20.16 69.30 207.65 349.23 698.46 1396.91 1479.98 20.17 69.30 207.65 349.23 698.46 1396.91 1479.98 20.18 69.30 207.65 349.23 698.46 1396.91 1479.98 20.19 69.30 207.65 349.23 493.88 698.46 1396.91 1479.98 20.20 69.30 207.65 349.23 493.88 698.46 1396.91 1479.98 20.21 69.30 207.65 349.23 493.88 698.46 1396.91 1479.98 20.22 69.30 207.65 349.23 493.88 698.46 1396.91 1479.98 20.23 69.30 207.65 349.23 493.88 698.46 1396.91 1479.98 20.24 69.30 207.65 349.23 493.88 698.46 1396.91 1479.98 20.25 69.30 207.65 349.23 493.88 698.46 1396.91 1479.98 20.26 69.30 207.65 349.23 493.88 698.46 1396.91 1479.98 20.27 207.65 349.23 493.88 698.46 1396.91 1479.98 20.28 207.65 349.23 493.88 698.46 1396.91 1479.98 20.29 207.65 349.23 493.88 698.46 1396.91 1479.98 20.30 207.65 349.23 698.46 1396.91 1479.98 20.31 207.65 349.23 698.46 1396.91 1479.98 20.32 207.65 349.23 698.46 1396.91 1479.98 20.33 207.65 349.23 698.46 1396.91 1479.98 20.34 207.65 349.23 698.46 1396.91 1479.98 20.35 207.65 1396.91 1479.98 20.36 207.65 1396.91 1479.98 20.37 207.65 1396.91 1479.98 20.38 207.65 1396.91 1479.98 20.39 207.65 1396.91 1479.98 20.40 207.65 1396.91 1479.98 20.41 207.65 1396.91 1479.98 20.42 207.65 1396.91 1479.98 20.43 69.30 138.59 207.65 1396.91 1479.98 20.44 69.30 138.59 207.65 1396.91 1479.98 20.45 69.30 138.59 207.65 1396.91 1479.98 20.46 69.30 138.59 207.65 1396.91 1479.98 20.47 69.30 138.59 207.65 698.46 1396.91 1479.98 20.48 69.30 138.59 207.65 698.46 1396.91 1479.98 20.49 69.30 138.59 207.65 698.46 1396.91 1479.98 20.50 138.59 207.65 698.46 1396.91 1479.98 20.51 138.59 207.65 698.46 1396.91 1479.98 20.52 138.59 207.65 698.46 1396.91 20.53 138.59 207.65 698.46 1108.73 1396.91 20.54 138.59 207.65 587.33 698.46 1108.73 1396.91 20.55 138.59 207.65 587.33 698.46 1108.73 1396.91 20.56 138.59 207.65 587.33 698.46 1108.73 1396.91 20.57 138.59 207.65 587.33 1108.73 1396.91 20.58 138.59 207.65 587.33 1108.73 1396.91 20.59 138.59 207.65 587.33 1108.73 1396.91 20.60 138.59 207.65 587.33 1108.73 1396.91 20.61 138.59 207.65 587.33 1108.73 1396.91 20.62 138.59 207.65 587.33 1108.73 1396.91 20.63 138.59 207.65 587.33 1108.73 1396.91 20.64 138.59 207.65 277.18 587.33 1108.73 1396.91 20.65 138.59 207.65 277.18 554.37 587.33 1108.73 1396.91 20.66 138.59 207.65 277.18 554.37 698.46 1108.73 1396.91 20.67 138.59 207.65 277.18 554.37 698.46 1108.73 1396.91 20.68 138.59 207.65 277.18 554.37 698.46 1108.73 1396.91 20.69 138.59 207.65 277.18 554.37 698.46 1108.73 1396.91 20.70 138.59 207.65 277.18 554.37 698.46 1108.73 1396.91 20.71 138.59 207.65 277.18 554.37 698.46 1108.73 1396.91 20.72 138.59 207.65 277.18 554.37 698.46 1108.73 1396.91 20.73 138.59 207.65 277.18 554.37 1108.73 1396.91 20.74 138.59 277.18 554.37 1108.73 20.75 138.59 277.18 554.37 1108.73 20.76 138.59 277.18 554.37 1108.73 20.77 138.59 277.18 554.37 1108.73 20.78 138.59 277.18 554.37 1108.73 20.79 138.59 277.18 554.37 1108.73 20.80 138.59 277.18 554.37 1108.73 20.81 138.59 277.18 554.37 1108.73 20.82 138.59 277.18 554.37 1108.73 20.83 138.59 277.18 554.37 1108.73 20.84 138.59 277.18 554.37 1108.73 20.85 138.59 277.18 554.37 1108.73 20.86 138.59 369.99 1108.73 20.87 138.59 369.99 1108.73 1174.66 20.88 369.99 1108.73 1174.66 20.89 369.99 1108.73 1174.66 20.90 369.99 1108.73 1174.66 20.91 369.99 1108.73 1174.66 20.92 369.99 1108.73 1174.66 20.93 369.99 1108.73 1174.66 20.94 369.99 1108.73 1174.66 20.95 369.99 1108.73 1174.66 20.96 369.99 1108.73 1174.66 20.97 369.99 1108.73 1174.66 20.98 369.99 1108.73 1174.66 20.99 369.99 1108.73 1174.66 21.00 369.99 1108.73 1174.66 21.01 369.99 1108.73 1174.66 21.02 369.99 1108.73 1174.66 21.03 123.47 369.99 1108.73 1174.66 21.04 123.47 369.99 1108.73 1174.66 21.05 123.47 369.99 1108.73 1174.66 21.06 123.47 369.99 1174.66 21.07 123.47 369.99 1174.66 21.08 123.47 369.99 1174.66 21.09 123.47 369.99 1174.66 21.10 123.47 369.99 1174.66 21.11 123.47 369.99 1174.66 21.12 123.47 369.99 1174.66 21.13 123.47 1174.66 21.14 123.47 1174.66 21.15 123.47 1174.66 21.16 123.47 1174.66 21.17 123.47 1174.66 21.18 123.47 1174.66 21.19 123.47 369.99 1174.66 21.20 123.47 369.99 739.99 1174.66 21.21 123.47 369.99 739.99 1174.66 21.22 123.47 369.99 739.99 1174.66 21.23 123.47 369.99 739.99 1174.66 21.24 123.47 369.99 739.99 1174.66 21.25 123.47 246.94 369.99 493.88 739.99 987.77 1174.66 21.26 123.47 246.94 369.99 493.88 739.99 987.77 21.27 123.47 246.94 369.99 493.88 739.99 987.77 21.28 123.47 246.94 369.99 493.88 739.99 987.77 21.29 123.47 246.94 369.99 493.88 739.99 987.77 21.30 123.47 246.94 369.99 493.88 739.99 987.77 21.31 123.47 246.94 369.99 493.88 739.99 987.77 21.32 123.47 246.94 369.99 493.88 739.99 987.77 21.33 123.47 246.94 369.99 493.88 739.99 987.77 21.34 123.47 246.94 369.99 493.88 739.99 987.77 21.35 123.47 246.94 369.99 493.88 739.99 987.77 1046.50 21.36 123.47 246.94 369.99 493.88 739.99 987.77 1046.50 21.37 123.47 246.94 369.99 493.88 739.99 987.77 1046.50 21.38 123.47 246.94 369.99 493.88 739.99 987.77 1046.50 21.39 123.47 246.94 369.99 493.88 739.99 987.77 1046.50 21.40 123.47 246.94 369.99 493.88 739.99 987.77 1046.50 21.41 123.47 246.94 369.99 493.88 739.99 987.77 1046.50 21.42 123.47 246.94 369.99 493.88 739.99 987.77 1046.50 21.43 123.47 246.94 369.99 493.88 739.99 987.77 1046.50 21.44 123.47 246.94 369.99 493.88 739.99 987.77 1046.50 21.45 123.47 369.99 1046.50 21.46 123.47 369.99 1046.50 21.47 123.47 369.99 1046.50 21.48 123.47 369.99 1046.50 21.49 123.47 369.99 1046.50 21.50 123.47 369.99 1046.50 21.51 123.47 369.99 1046.50 21.52 123.47 369.99 1046.50 21.53 123.47 369.99 1046.50 21.54 123.47 369.99 1046.50 21.55 123.47 369.99 1046.50 21.56 123.47 369.99 1046.50 21.57 123.47 369.99 1046.50 21.58 123.47 369.99 739.99 1046.50 21.59 123.47 369.99 698.46 739.99 1046.50 21.60 123.47 369.99 698.46 739.99 1046.50 21.61 369.99 698.46 739.99 1046.50 21.62 369.99 698.46 739.99 1046.50 21.63 207.65 369.99 698.46 739.99 21.64 207.65 369.99 698.46 739.99 21.65 207.65 349.23 369.99 698.46 21.66 207.65 349.23 369.99 698.46 21.67 207.65 349.23 369.99 698.46 21.68 207.65 349.23 369.99 698.46 21.69 207.65 349.23 698.46 21.70 207.65 349.23 698.46 21.71 207.65 349.23 698.46 21.72 207.65 349.23 698.46 830.61 21.73 207.65 349.23 698.46 830.61 21.74 207.65 349.23 698.46 830.61 21.75 207.65 349.23 698.46 830.61 21.76 207.65 349.23 698.46 830.61 21.77 207.65 349.23 698.46 830.61 21.78 207.65 349.23 698.46 830.61 21.79 207.65 349.23 698.46 830.61 21.80 207.65 349.23 830.61 21.81 207.65 349.23 830.61 21.82 207.65 349.23 830.61 21.83 207.65 349.23 830.61 21.84 207.65 349.23 830.61 21.85 207.65 349.23 830.61 21.86 207.65 349.23 830.61 21.87 207.65 349.23 415.30 830.61 21.88 207.65 349.23 415.30 830.61 21.89 207.65 349.23 415.30 830.61 21.90 207.65 349.23 415.30 830.61 21.91 207.65 349.23 415.30 830.61 21.92 207.65 349.23 415.30 830.61 21.93 207.65 349.23 415.30 830.61 21.94 138.59 207.65 349.23 415.30 830.61 21.95 138.59 207.65 349.23 415.30 830.61 21.96 138.59 207.65 349.23 415.30 830.61 21.97 138.59 207.65 277.18 349.23 554.37 830.61 21.98 138.59 277.18 349.23 554.37 830.61 21.99 138.59 277.18 349.23 554.37 830.61 1661.22 22.00 138.59 277.18 349.23 554.37 830.61 1661.22 22.01 138.59 277.18 349.23 554.37 830.61 1661.22 22.02 138.59 277.18 349.23 554.37 830.61 1661.22 22.03 138.59 277.18 349.23 554.37 830.61 1661.22 22.04 138.59 277.18 349.23 554.37 830.61 1661.22 22.05 138.59 207.65 277.18 349.23 554.37 830.61 1661.22 22.06 138.59 207.65 277.18 349.23 554.37 830.61 1661.22 22.07 138.59 207.65 277.18 349.23 554.37 830.61 1661.22 22.08 138.59 207.65 277.18 349.23 554.37 830.61 1661.22 22.09 138.59 207.65 277.18 349.23 415.30 554.37 830.61 1661.22 22.10 138.59 207.65 277.18 349.23 415.30 554.37 830.61 22.11 138.59 207.65 277.18 349.23 415.30 554.37 830.61 22.12 138.59 207.65 277.18 349.23 415.30 554.37 830.61 22.13 138.59 207.65 277.18 349.23 415.30 554.37 830.61 22.14 138.59 207.65 277.18 349.23 415.30 554.37 830.61 22.15 138.59 207.65 277.18 349.23 415.30 554.37 830.61 22.16 138.59 207.65 277.18 349.23 415.30 554.37 830.61 22.17 138.59 207.65 277.18 349.23 415.30 554.37 830.61 22.18 138.59 207.65 277.18 349.23 415.30 554.37 830.61 22.19 138.59 207.65 277.18 349.23 415.30 554.37 830.61 22.20 138.59 207.65 277.18 415.30 830.61 22.21 138.59 207.65 277.18 415.30 830.61 22.22 138.59 207.65 277.18 415.30 830.61 22.23 138.59 207.65 277.18 415.30 830.61 22.24 138.59 207.65 277.18 415.30 830.61 22.25 138.59 207.65 277.18 415.30 830.61 22.26 138.59 207.65 277.18 415.30 830.61 22.27 138.59 207.65 277.18 415.30 830.61 22.28 138.59 207.65 277.18 830.61 22.29 138.59 207.65 277.18 830.61 880.00 22.30 138.59 207.65 277.18 830.61 880.00 22.31 138.59 207.65 277.18 830.61 880.00 22.32 138.59 207.65 277.18 830.61 880.00 22.33 138.59 207.65 277.18 830.61 880.00 22.34 138.59 207.65 277.18 830.61 880.00 22.35 138.59 277.18 830.61 880.00 22.36 138.59 277.18 830.61 880.00 22.37 138.59 277.18 830.61 880.00 22.38 138.59 277.18 369.99 830.61 880.00 22.39 138.59 277.18 369.99 493.88 830.61 880.00 22.40 138.59 277.18 369.99 493.88 830.61 880.00 22.41 138.59 277.18 369.99 493.88 830.61 880.00 22.42 138.59 277.18 369.99 493.88 830.61 880.00 22.43 369.99 493.88 830.61 880.00 22.44 369.99 493.88 830.61 880.00 22.45 246.94 369.99 493.88 830.61 880.00 22.46 246.94 369.99 493.88 830.61 880.00 22.47 246.94 369.99 493.88 830.61 880.00 22.48 246.94 369.99 493.88 830.61 880.00 22.49 246.94 369.99 493.88 830.61 880.00 22.50 246.94 369.99 493.88 830.61 880.00 22.51 246.94 369.99 493.88 830.61 880.00 22.52 246.94 369.99 493.88 830.61 880.00 22.53 246.94 369.99 493.88 830.61 880.00 22.54 246.94 369.99 830.61 880.00 22.55 246.94 369.99 830.61 880.00 22.56 246.94 369.99 830.61 880.00 22.57 369.99 830.61 880.00 22.58 369.99 830.61 880.00 22.59 369.99 830.61 880.00 22.60 369.99 830.61 880.00 22.61 369.99 830.61 880.00 22.62 369.99 440.00 830.61 880.00 22.63 369.99 440.00 830.61 880.00 22.64 440.00 830.61 880.00 22.65 440.00 830.61 880.00 22.66 440.00 830.61 880.00 22.67 440.00 880.00 22.68 440.00 880.00 22.69 440.00 493.88 880.00 22.70 440.00 493.88 880.00 22.71 440.00 493.88 880.00 22.72 440.00 493.88 880.00 22.73 415.30 440.00 493.88 880.00 22.74 415.30 440.00 493.88 880.00 22.75 415.30 440.00 493.88 880.00 22.76 415.30 440.00 493.88 880.00 22.77 415.30 440.00 493.88 880.00 22.78 415.30 440.00 493.88 880.00 22.79 415.30 440.00 493.88 880.00 22.80 415.30 440.00 493.88 880.00 22.81 415.30 440.00 493.88 880.00 22.82 440.00 493.88 880.00 22.83 440.00 493.88 880.00 22.84 440.00 493.88 880.00 22.85 440.00 493.88 880.00 22.86 440.00 493.88 22.87 440.00 493.88 22.88 440.00 493.88 22.89 493.88 22.90 493.88 22.91 369.99 493.88 22.92 369.99 493.88 22.93 207.65 369.99 493.88 22.94 207.65 369.99 22.95 207.65 369.99 22.96 207.65 369.99 22.97 185.00 207.65 369.99 22.98 185.00 207.65 369.99 22.99 185.00 207.65 369.99 739.99 1479.98 23.00 185.00 207.65 369.99 739.99 1479.98 23.01 185.00 207.65 369.99 739.99 1479.98 23.02 185.00 207.65 369.99 739.99 1479.98 23.03 185.00 207.65 369.99 739.99 1479.98 23.04 138.59 185.00 207.65 369.99 739.99 1479.98 23.05 138.59 185.00 369.99 739.99 1479.98 23.06 138.59 185.00 369.99 739.99 1479.98 23.07 138.59 185.00 369.99 739.99 1396.91 1479.98 23.08 138.59 185.00 369.99 739.99 1396.91 1479.98 23.09 138.59 185.00 369.99 739.99 1396.91 1479.98 23.10 138.59 185.00 369.99 739.99 1396.91 1479.98 23.11 185.00 369.99 739.99 1396.91 1479.98 23.12 185.00 369.99 739.99 1396.91 23.13 185.00 369.99 415.30 739.99 1396.91 23.14 185.00 369.99 415.30 698.46 739.99 1396.91 23.15 369.99 415.30 698.46 739.99 1396.91 23.16 369.99 415.30 698.46 739.99 1396.91 23.17 369.99 415.30 698.46 739.99 1396.91 23.18 207.65 369.99 415.30 698.46 739.99 1396.91 1479.98 23.19 207.65 277.18 369.99 415.30 698.46 739.99 1396.91 1479.98 23.20 207.65 277.18 369.99 415.30 698.46 739.99 1396.91 1479.98 23.21 207.65 277.18 369.99 415.30 739.99 1396.91 1479.98 23.22 207.65 277.18 369.99 415.30 739.99 1396.91 1479.98 23.23 207.65 277.18 369.99 415.30 739.99 1396.91 1479.98 23.24 207.65 277.18 369.99 415.30 739.99 1396.91 1479.98 23.25 207.65 277.18 369.99 415.30 739.99 1396.91 1479.98 23.26 69.30 138.59 207.65 277.18 369.99 415.30 739.99 1396.91 1479.98 23.27 69.30 138.59 207.65 277.18 369.99 415.30 1396.91 1479.98 23.28 69.30 138.59 207.65 277.18 369.99 415.30 1396.91 1479.98 23.29 69.30 138.59 207.65 277.18 415.30 1396.91 1479.98 23.30 69.30 138.59 207.65 277.18 415.30 1396.91 1479.98 23.31 69.30 138.59 207.65 277.18 415.30 1396.91 1479.98 23.32 69.30 138.59 207.65 277.18 1396.91 1479.98 23.33 207.65 277.18 1396.91 1479.98 23.34 207.65 277.18 1396.91 1479.98 23.35 207.65 277.18 1396.91 1479.98 23.36 207.65 277.18 1396.91 1479.98 23.37 207.65 277.18 1396.91 1479.98 23.38 207.65 277.18 1396.91 1479.98 23.39 207.65 277.18 1396.91 1479.98 23.40 207.65 277.18 1396.91 1479.98 23.41 207.65 277.18 1396.91 1479.98 23.42 207.65 277.18 1396.91 1479.98 23.43 207.65 277.18 1396.91 1479.98 23.44 207.65 277.18 1396.91 1479.98 23.45 207.65 277.18 1396.91 1479.98 23.46 207.65 277.18 1396.91 1479.98 23.47 207.65 277.18 1396.91 1479.98 23.48 207.65 277.18 739.99 1396.91 1479.98 23.49 207.65 277.18 739.99 1396.91 1479.98 23.50 207.65 739.99 1396.91 1479.98 23.51 207.65 739.99 1174.66 1396.91 1479.98 23.52 138.59 207.65 739.99 1174.66 1396.91 1479.98 23.53 138.59 207.65 739.99 1174.66 1396.91 1479.98 23.54 138.59 207.65 739.99 1174.66 1396.91 1479.98 23.55 138.59 207.65 739.99 1174.66 1396.91 1479.98 23.56 138.59 207.65 277.18 554.37 739.99 1108.73 1174.66 1396.91 1479.98 23.57 138.59 207.65 277.18 554.37 739.99 1108.73 1174.66 1396.91 1479.98 23.58 138.59 207.65 277.18 554.37 739.99 1108.73 1174.66 1396.91 1479.98 23.59 138.59 207.65 277.18 554.37 739.99 1108.73 1174.66 1396.91 1479.98 23.60 138.59 207.65 277.18 554.37 1108.73 1174.66 1396.91 23.61 138.59 207.65 277.18 554.37 1108.73 1174.66 23.62 138.59 207.65 277.18 554.37 1108.73 1174.66 23.63 69.30 138.59 207.65 277.18 554.37 1108.73 1174.66 23.64 69.30 138.59 207.65 277.18 554.37 1108.73 1174.66 23.65 69.30 138.59 207.65 277.18 554.37 1108.73 1174.66 23.66 69.30 138.59 207.65 277.18 554.37 1108.73 1174.66 23.67 69.30 138.59 207.65 277.18 554.37 1108.73 1174.66 23.68 69.30 138.59 207.65 277.18 554.37 1108.73 1174.66 23.69 69.30 138.59 207.65 277.18 554.37 1108.73 1174.66 23.70 69.30 138.59 207.65 277.18 554.37 1108.73 1174.66 23.71 69.30 138.59 207.65 277.18 415.30 554.37 1108.73 1174.66 23.72 69.30 138.59 207.65 277.18 415.30 554.37 1108.73 1174.66 23.73 69.30 138.59 207.65 277.18 415.30 554.37 1108.73 1174.66 23.74 69.30 138.59 207.65 277.18 415.30 554.37 1108.73 1174.66 23.75 69.30 138.59 207.65 277.18 415.30 554.37 1108.73 1174.66 23.76 69.30 138.59 207.65 277.18 415.30 554.37 1108.73 1174.66 23.77 69.30 138.59 207.65 277.18 415.30 554.37 1108.73 1174.66 23.78 69.30 138.59 207.65 277.18 415.30 554.37 1108.73 1174.66 23.79 69.30 138.59 207.65 277.18 554.37 1108.73 1174.66 23.80 69.30 138.59 207.65 277.18 554.37 1108.73 1174.66 23.81 69.30 138.59 207.65 277.18 554.37 1108.73 1174.66 23.82 69.30 138.59 207.65 277.18 554.37 1108.73 1174.66 23.83 69.30 138.59 207.65 277.18 554.37 1108.73 1174.66 23.84 69.30 138.59 207.65 277.18 554.37 987.77 1108.73 1174.66 23.85 69.30 138.59 207.65 277.18 554.37 987.77 1108.73 1174.66 23.86 69.30 138.59 207.65 277.18 554.37 987.77 1108.73 1174.66 23.87 69.30 138.59 207.65 277.18 554.37 987.77 1108.73 1174.66 23.88 69.30 138.59 207.65 277.18 554.37 987.77 1108.73 1174.66 23.89 69.30 138.59 207.65 277.18 554.37 987.77 1108.73 1174.66 23.90 69.30 138.59 207.65 277.18 554.37 987.77 1108.73 1174.66 23.91 69.30 138.59 207.65 277.18 554.37 987.77 1108.73 1174.66 23.92 138.59 207.65 277.18 369.99 554.37 987.77 1108.73 1174.66 23.93 138.59 207.65 277.18 369.99 554.37 987.77 1108.73 1174.66 23.94 138.59 277.18 369.99 554.37 987.77 1108.73 1174.66 23.95 138.59 277.18 369.99 554.37 987.77 1108.73 1174.66 23.96 138.59 277.18 369.99 554.37 987.77 1108.73 1174.66 23.97 138.59 277.18 369.99 554.37 987.77 1108.73 1174.66 23.98 138.59 277.18 369.99 554.37 987.77 1108.73 1174.66 23.99 138.59 277.18 369.99 554.37 987.77 1108.73 1174.66 24.00 138.59 277.18 369.99 554.37 987.77 1108.73 24.01 138.59 277.18 369.99 554.37 987.77 1108.73 24.02 277.18 369.99 554.37 987.77 1108.73 24.03 277.18 369.99 554.37 987.77 1108.73 24.04 277.18 369.99 554.37 987.77 1108.73 24.05 369.99 554.37 987.77 1108.73 24.06 369.99 554.37 987.77 1108.73 24.07 369.99 554.37 987.77 1108.73 24.08 369.99 554.37 987.77 1108.73 24.09 369.99 554.37 987.77 1108.73 24.10 369.99 554.37 987.77 1108.73 24.11 369.99 554.37 987.77 1108.73 24.12 369.99 554.37 987.77 1108.73 24.13 369.99 987.77 24.14 369.99 987.77 24.15 369.99 24.16 369.99 24.17 369.99 880.00 24.18 369.99 880.00 24.19 369.99 880.00 24.20 369.99 880.00 24.21 369.99 880.00 24.22 369.99 880.00 24.23 369.99 880.00 24.24 369.99 880.00 24.25 369.99 880.00 24.26 369.99 880.00 24.27 369.99 880.00 24.28 369.99 880.00 24.29 369.99 880.00 24.30 138.59 369.99 880.00 24.31 138.59 369.99 880.00 24.32 138.59 880.00 24.33 138.59 880.00 24.34 138.59 880.00 24.35 138.59 880.00 24.36 138.59 880.00 24.37 138.59 277.18 880.00 24.38 138.59 277.18 880.00 24.39 277.18 880.00 24.40 277.18 880.00 24.41 277.18 415.30 880.00 24.42 277.18 415.30 880.00 24.43 277.18 415.30 880.00 24.44 277.18 415.30 830.61 880.00 24.45 277.18 415.30 830.61 880.00 24.46 277.18 415.30 830.61 880.00 24.47 277.18 415.30 830.61 880.00 24.48 277.18 415.30 830.61 880.00 24.49 277.18 415.30 830.61 880.00 24.50 138.59 277.18 415.30 830.61 880.00 24.51 138.59 277.18 415.30 830.61 880.00 24.52 138.59 277.18 369.99 415.30 880.00 24.53 138.59 277.18 369.99 415.30 24.54 138.59 277.18 369.99 415.30 24.55 138.59 277.18 369.99 415.30 739.99 24.56 138.59 277.18 369.99 415.30 739.99 24.57 138.59 277.18 369.99 739.99 24.58 138.59 277.18 369.99 739.99 24.59 138.59 277.18 369.99 739.99 24.60 138.59 277.18 369.99 739.99 24.61 138.59 277.18 369.99 739.99 24.62 138.59 277.18 369.99 739.99 24.63 138.59 277.18 369.99 739.99 24.64 277.18 369.99 739.99 24.65 277.18 369.99 739.99 24.66 277.18 369.99 739.99 24.67 277.18 369.99 739.99 24.68 277.18 369.99 739.99 24.69 277.18 369.99 739.99 24.70 277.18 369.99 24.71 277.18 369.99 24.72 277.18 24.73 277.18 24.74 277.18 24.75 277.18 24.76 277.18 24.77 277.18 830.61 24.78 277.18 830.61 24.79 277.18 830.61 24.80 277.18 830.61 24.81 277.18 830.61 24.82 277.18 830.61 24.83 277.18 329.63 830.61 24.84 277.18 329.63 830.61 24.85 277.18 329.63 830.61 24.86 277.18 329.63 830.61 24.87 277.18 329.63 830.61 24.88 277.18 329.63 830.61 24.89 277.18 329.63 830.61 24.90 277.18 329.63 830.61 24.91 277.18 329.63 830.61 24.92 277.18 329.63 830.61 24.93 277.18 329.63 830.61 24.94 277.18 830.61 24.95 277.18 830.61 24.96 277.18 830.61 24.97 277.18 830.61 24.98 277.18 830.61 24.99 277.18 830.61 25.00 277.18 830.61 25.01 277.18 830.61 25.02 277.18 830.61 25.03 277.18 830.61 25.04 277.18 830.61 25.05 277.18 830.61 25.06 277.18 830.61 25.07 277.18 830.61 25.08 277.18 830.61 25.09 277.18 830.61 25.10 277.18 830.61 25.11 277.18 830.61 25.12 277.18 830.61 25.13 277.18 830.61 25.14 277.18 415.30 830.61 25.15 277.18 415.30 830.61 25.16 277.18 415.30 830.61 25.17 415.30 830.61 25.18 415.30 830.61 25.19 207.65 415.30 830.61 25.20 207.65 415.30 830.61 25.21 207.65 415.30 830.61 25.22 207.65 415.30 830.61 25.23 207.65 415.30 830.61 25.24 207.65 415.30 830.61 25.25 207.65 415.30 830.61 25.26 207.65 415.30 830.61 25.27 207.65 415.30 830.61 25.28 207.65 415.30 830.61 25.29 207.65 415.30 830.61 25.30 207.65 415.30 830.61 25.31 207.65 415.30 830.61 25.32 207.65 415.30 830.61 25.33 207.65 415.30 830.61 25.34 138.59 207.65 415.30 830.61 25.35 138.59 207.65 415.30 830.61 25.36 138.59 207.65 415.30 830.61 25.37 138.59 207.65 415.30 830.61 25.38 138.59 207.65 415.30 830.61 25.39 138.59 207.65 415.30 830.61 25.40 138.59 207.65 415.30 830.61 25.41 138.59 207.65 415.30 830.61 25.42 138.59 207.65 415.30 830.61 25.43 138.59 207.65 415.30 830.61 25.44 138.59 207.65 415.30 830.61 25.45 138.59 207.65 415.30 830.61 25.46 207.65 415.30 830.61 25.47 207.65 415.30 830.61 25.48 207.65 415.30 830.61 25.49 207.65 415.30 830.61 25.50 207.65 415.30 830.61 25.51 207.65 415.30 830.61 25.52 207.65 415.30 830.61 25.53 103.83 207.65 415.30 830.61 25.54 103.83 207.65 415.30 830.61 25.55 103.83 207.65 415.30 830.61 25.56 103.83 207.65 415.30 830.61 25.57 103.83 207.65 415.30 830.61 25.58 103.83 207.65 415.30 830.61 25.59 103.83 207.65 415.30 830.61 25.60 207.65 415.30 830.61 25.61 207.65 415.30 830.61 25.62 138.59 207.65 415.30 830.61 25.63 138.59 207.65 415.30 830.61 25.64 138.59 207.65 415.30 830.61 25.65 138.59 207.65 415.30 830.61 25.66 138.59 207.65 415.30 830.61 25.67 138.59 207.65 415.30 830.61 25.68 138.59 207.65 415.30 830.61 25.69 138.59 207.65 415.30 830.61 25.70 138.59 207.65 415.30 830.61 25.71 138.59 207.65 415.30 830.61 25.72 138.59 207.65 415.30 830.61 25.73 138.59 207.65 415.30 830.61 25.74 138.59 207.65 415.30 830.61 25.75 138.59 207.65 415.30 830.61 25.76 138.59 207.65 415.30 830.61 25.77 138.59 207.65 415.30 830.61 25.78 138.59 207.65 415.30 830.61 25.79 138.59 207.65 415.30 830.61 25.80 138.59 207.65 415.30 25.81 138.59 207.65 415.30 25.82 138.59 207.65 415.30 25.83 207.65 415.30 25.84 207.65 415.30 25.85 207.65 415.30 25.86 207.65 415.30 25.87 207.65 415.30 25.88 415.30 25.89 220.00 415.30 440.00 25.90 220.00 415.30 440.00 25.91 220.00 415.30 440.00 25.92 220.00 415.30 440.00 25.93 220.00 415.30 440.00 25.94 220.00 415.30 440.00 25.95 220.00 415.30 440.00 25.96 220.00 329.63 415.30 25.97 220.00 329.63 25.98 220.00 329.63 25.99 220.00 329.63 26.00 220.00 329.63 26.01 220.00 329.63 26.02 220.00 329.63 26.03 220.00 329.63 26.04 220.00 277.18 329.63 26.05 220.00 277.18 329.63 26.06 220.00 277.18 26.07 220.00 277.18 26.08 220.00 277.18 26.09 220.00 277.18 26.10 220.00 277.18 26.11 220.00 277.18 26.12 220.00 277.18 554.37 1108.73 26.13 220.00 277.18 554.37 1108.73 26.14 220.00 277.18 554.37 1108.73 26.15 220.00 277.18 554.37 1108.73 26.16 220.00 277.18 554.37 1108.73 26.17 220.00 277.18 554.37 1108.73 26.18 220.00 277.18 554.37 1108.73 26.19 220.00 277.18 554.37 1108.73 26.20 220.00 277.18 554.37 1108.73 26.21 220.00 277.18 554.37 1108.73 26.22 220.00 277.18 554.37 1108.73 26.23 220.00 277.18 554.37 1108.73 26.24 220.00 554.37 1108.73 26.25 220.00 554.37 1108.73 26.26 220.00 554.37 1108.73 26.27 220.00 329.63 554.37 1108.73 26.28 220.00 329.63 554.37 1108.73 26.29 220.00 329.63 554.37 1108.73 26.30 220.00 277.18 329.63 554.37 1108.73 26.31 103.83 207.65 277.18 329.63 554.37 1108.73 26.32 103.83 207.65 277.18 329.63 554.37 1108.73 26.33 103.83 207.65 277.18 329.63 554.37 1108.73 26.34 103.83 207.65 277.18 329.63 554.37 1108.73 26.35 103.83 207.65 277.18 329.63 554.37 1108.73 26.36 103.83 207.65 277.18 329.63 554.37 1108.73 26.37 103.83 207.65 277.18 329.63 554.37 1108.73 26.38 207.65 277.18 329.63 554.37 1108.73 26.39 207.65 277.18 329.63 554.37 1108.73 26.40 207.65 277.18 329.63 554.37 1108.73 26.41 207.65 277.18 329.63 554.37 1108.73 26.42 207.65 277.18 329.63 554.37 1108.73 26.43 207.65 277.18 329.63 554.37 1108.73 26.44 207.65 277.18 329.63 554.37 1108.73 26.45 207.65 277.18 329.63 554.37 1108.73 26.46 207.65 277.18 329.63 554.37 1108.73 26.47 207.65 277.18 329.63 554.37 659.26 1108.73 26.48 207.65 329.63 554.37 659.26 1108.73 26.49 207.65 329.63 554.37 659.26 1108.73 26.50 207.65 329.63 554.37 659.26 1108.73 26.51 207.65 329.63 554.37 659.26 1108.73 26.52 207.65 329.63 554.37 659.26 1108.73 26.53 138.59 207.65 329.63 554.37 659.26 1108.73 26.54 138.59 207.65 329.63 554.37 659.26 1108.73 26.55 138.59 207.65 329.63 554.37 659.26 1108.73 26.56 138.59 207.65 329.63 554.37 659.26 1108.73 26.57 138.59 207.65 329.63 554.37 659.26 1108.73 26.58 138.59 329.63 554.37 659.26 1108.73 26.59 138.59 329.63 554.37 659.26 1108.73 26.60 138.59 329.63 554.37 659.26 1108.73 26.61 138.59 329.63 554.37 1108.73 26.62 277.18 329.63 830.61 1108.73 26.63 277.18 830.61 1108.73 26.64 277.18 830.61 1108.73 26.65 277.18 830.61 1108.73 26.66 277.18 830.61 1108.73 26.67 277.18 830.61 1108.73 26.68 277.18 329.63 830.61 1108.73 26.69 277.18 329.63 830.61 1108.73 26.70 207.65 277.18 329.63 830.61 1108.73 26.71 207.65 277.18 329.63 830.61 1108.73 26.72 207.65 277.18 329.63 830.61 26.73 207.65 277.18 329.63 830.61 26.74 207.65 277.18 329.63 830.61 26.75 207.65 277.18 329.63 830.61 26.76 207.65 277.18 329.63 830.61 26.77 207.65 277.18 329.63 830.61 26.78 207.65 277.18 329.63 830.61 26.79 207.65 277.18 329.63 830.61 26.80 207.65 277.18 329.63 830.61 26.81 207.65 277.18 329.63 830.61 26.82 138.59 207.65 277.18 329.63 830.61 26.83 138.59 207.65 277.18 329.63 830.61 26.84 138.59 207.65 277.18 329.63 830.61 26.85 138.59 207.65 277.18 329.63 830.61 26.86 138.59 207.65 277.18 329.63 830.61 26.87 138.59 207.65 277.18 830.61 26.88 138.59 207.65 277.18 830.61 26.89 138.59 207.65 277.18 830.61 26.90 138.59 207.65 277.18 830.61 26.91 138.59 207.65 277.18 830.61 26.92 138.59 207.65 277.18 830.61 26.93 138.59 207.65 277.18 830.61 26.94 138.59 207.65 277.18 830.61 26.95 138.59 207.65 277.18 830.61 26.96 138.59 207.65 277.18 830.61 26.97 138.59 207.65 830.61 26.98 138.59 830.61 26.99 138.59 830.61 27.00 138.59 415.30 830.61 27.01 138.59 415.30 830.61 27.02 138.59 415.30 830.61 27.03 138.59 415.30 830.61 27.04 138.59 415.30 830.61 27.05 138.59 246.94 415.30 830.61 27.06 138.59 246.94 415.30 830.61 27.07 138.59 246.94 415.30 830.61 27.08 138.59 246.94 415.30 830.61 27.09 138.59 246.94 415.30 830.61 27.10 138.59 246.94 415.30 830.61 27.11 138.59 246.94 415.30 830.61 27.12 138.59 246.94 415.30 830.61 27.13 138.59 246.94 415.30 830.61 27.14 138.59 246.94 415.30 830.61 27.15 138.59 246.94 415.30 830.61 27.16 138.59 246.94 415.30 830.61 27.17 138.59 246.94 415.30 830.61 27.18 138.59 246.94 415.30 830.61 27.19 138.59 246.94 415.30 830.61 27.20 138.59 246.94 415.30 830.61 27.21 138.59 246.94 415.30 830.61 27.22 138.59 246.94 415.30 830.61 27.23 138.59 246.94 415.30 830.61 27.24 138.59 246.94 415.30 830.61 27.25 138.59 246.94 415.30 830.61 27.26 138.59 415.30 830.61 27.27 138.59 415.30 830.61 27.28 415.30 830.61 27.29 415.30 830.61 27.30 415.30 830.61 27.31 415.30 830.61 27.32 830.61 27.33 830.61 880.00 27.34 92.50 185.00 277.18 830.61 880.00 27.35 92.50 185.00 277.18 830.61 880.00 27.36 92.50 185.00 277.18 830.61 880.00 27.37 92.50 185.00 277.18 830.61 880.00 27.38 92.50 185.00 277.18 830.61 880.00 27.39 92.50 185.00 277.18 830.61 880.00 27.40 92.50 185.00 277.18 830.61 880.00 27.41 92.50 185.00 277.18 830.61 880.00 27.42 92.50 185.00 277.18 830.61 880.00 27.43 92.50 185.00 277.18 830.61 880.00 27.44 92.50 185.00 277.18 830.61 880.00 27.45 92.50 185.00 220.00 277.18 440.00 830.61 880.00 27.46 92.50 185.00 220.00 277.18 440.00 830.61 880.00 27.47 92.50 185.00 220.00 277.18 440.00 830.61 880.00 27.48 92.50 185.00 220.00 277.18 440.00 830.61 880.00 27.49 92.50 185.00 220.00 277.18 440.00 830.61 880.00 27.50 92.50 185.00 220.00 277.18 440.00 554.37 830.61 880.00 27.51 92.50 185.00 220.00 277.18 440.00 554.37 830.61 880.00 27.52 92.50 185.00 220.00 277.18 440.00 554.37 830.61 880.00 1108.73 27.53 92.50 185.00 220.00 277.18 440.00 554.37 830.61 880.00 1108.73 27.54 92.50 185.00 220.00 277.18 440.00 554.37 830.61 880.00 1108.73 27.55 92.50 185.00 220.00 277.18 440.00 554.37 830.61 880.00 1108.73 27.56 92.50 185.00 220.00 277.18 440.00 554.37 830.61 880.00 1108.73 27.57 92.50 185.00 220.00 277.18 440.00 554.37 830.61 880.00 1108.73 27.58 92.50 220.00 277.18 440.00 554.37 830.61 880.00 1108.73 27.59 92.50 220.00 277.18 440.00 554.37 830.61 880.00 1108.73 27.60 92.50 220.00 277.18 440.00 554.37 830.61 880.00 1108.73 27.61 92.50 220.00 277.18 440.00 554.37 880.00 1108.73 27.62 92.50 220.00 277.18 440.00 554.37 880.00 1108.73 27.63 92.50 185.00 220.00 277.18 440.00 554.37 880.00 1108.73 27.64 92.50 185.00 220.00 277.18 440.00 554.37 880.00 1108.73 27.65 92.50 185.00 220.00 277.18 440.00 554.37 1108.73 27.66 185.00 220.00 277.18 440.00 554.37 1108.73 27.67 185.00 220.00 277.18 440.00 554.37 1108.73 27.68 185.00 27.69 185.00 27.70 1318.51 1396.91 27.71 698.46 1318.51 1396.91 27.72 207.65 698.46 1318.51 1396.91 27.73 207.65 698.46 1318.51 1396.91 27.74 207.65 698.46 1318.51 1396.91 27.75 207.65 698.46 1318.51 1396.91 27.76 207.65 329.63 659.26 698.46 1318.51 1396.91 27.77 207.65 329.63 659.26 698.46 1318.51 1396.91 27.78 207.65 329.63 659.26 698.46 1318.51 1396.91 27.79 207.65 329.63 659.26 698.46 1318.51 1396.91 27.80 207.65 329.63 659.26 698.46 1318.51 27.81 207.65 329.63 659.26 698.46 1318.51 27.82 207.65 329.63 659.26 698.46 1318.51 27.83 207.65 329.63 659.26 698.46 1318.51 27.84 207.65 329.63 659.26 1318.51 27.85 207.65 329.63 659.26 1318.51 27.86 329.63 659.26 1318.51 27.87 329.63 659.26 1318.51 27.88 1318.51 27.89 1318.51 27.90 1318.51 27.91 1318.51 27.92 207.65 1318.51 27.93 207.65 1318.51 27.94 207.65 1318.51 27.95 207.65 1318.51 27.96 207.65 1318.51 27.97 207.65 1318.51 27.98 207.65 1318.51 27.99 207.65 1318.51 28.00 207.65 1318.51 1396.91 28.01 207.65 1318.51 1396.91 28.02 207.65 220.00 659.26 1318.51 1396.91 28.03 220.00 659.26 1318.51 1396.91 28.04 92.50 220.00 659.26 1318.51 1396.91 28.05 92.50 220.00 659.26 1318.51 1396.91 28.06 92.50 185.00 220.00 659.26 1318.51 1396.91 28.07 92.50 185.00 220.00 659.26 1318.51 1396.91 28.08 92.50 185.00 220.00 659.26 1318.51 1396.91 28.09 92.50 185.00 220.00 659.26 1318.51 1396.91 28.10 92.50 185.00 220.00 659.26 1318.51 28.11 92.50 185.00 220.00 659.26 1318.51 28.12 92.50 185.00 220.00 659.26 1318.51 28.13 92.50 185.00 220.00 659.26 1318.51 28.14 92.50 185.00 220.00 659.26 1318.51 28.15 92.50 185.00 220.00 659.26 1318.51 28.16 92.50 185.00 220.00 659.26 1318.51 28.17 92.50 185.00 220.00 659.26 1318.51 28.18 92.50 185.00 220.00 440.00 659.26 1318.51 28.19 92.50 185.00 220.00 440.00 659.26 1318.51 28.20 92.50 185.00 220.00 277.18 440.00 659.26 1318.51 28.21 92.50 185.00 220.00 277.18 440.00 659.26 1318.51 28.22 92.50 185.00 220.00 277.18 440.00 659.26 1318.51 28.23 92.50 185.00 220.00 277.18 440.00 659.26 1318.51 28.24 92.50 185.00 220.00 277.18 440.00 659.26 1318.51 28.25 92.50 185.00 220.00 277.18 440.00 659.26 1318.51 28.26 92.50 185.00 220.00 277.18 440.00 659.26 1318.51 28.27 92.50 185.00 220.00 277.18 440.00 659.26 1318.51 28.28 92.50 185.00 220.00 277.18 440.00 659.26 1318.51 28.29 92.50 185.00 220.00 277.18 440.00 659.26 1318.51 28.30 92.50 185.00 220.00 277.18 440.00 659.26 1318.51 28.31 92.50 185.00 220.00 277.18 440.00 659.26 1318.51 28.32 92.50 185.00 220.00 277.18 440.00 659.26 1318.51 28.33 92.50 185.00 220.00 277.18 415.30 440.00 659.26 1318.51 28.34 92.50 185.00 220.00 277.18 415.30 440.00 659.26 1318.51 28.35 92.50 185.00 277.18 415.30 659.26 1318.51 28.36 92.50 185.00 277.18 415.30 659.26 1318.51 28.37 92.50 207.65 277.18 415.30 659.26 1318.51 28.38 92.50 207.65 415.30 659.26 1318.51 28.39 92.50 207.65 415.30 659.26 1318.51 28.40 92.50 207.65 415.30 659.26 1318.51 28.41 207.65 329.63 415.30 659.26 1318.51 28.42 207.65 329.63 415.30 659.26 1318.51 28.43 207.65 329.63 415.30 659.26 1318.51 28.44 207.65 329.63 415.30 659.26 1318.51 28.45 207.65 277.18 329.63 415.30 659.26 1318.51 28.46 207.65 277.18 329.63 415.30 659.26 1318.51 28.47 207.65 277.18 329.63 659.26 1318.51 28.48 207.65 277.18 329.63 659.26 1318.51 28.49 207.65 277.18 329.63 659.26 1318.51 28.50 207.65 277.18 329.63 659.26 1318.51 28.51 207.65 277.18 329.63 659.26 1318.51 28.52 207.65 277.18 329.63 659.26 1318.51 28.53 207.65 1318.51 28.54 207.65 1318.51 28.55 1318.51 28.56 28.57 28.58 28.59 28.60 28.61 28.62 28.63 28.64 28.65 28.66 28.67 28.68 28.69 28.70 28.71 28.72 28.73 28.74 28.75 28.76 28.77 28.78 28.79 28.80 28.81 28.82 28.83 28.84 28.85 28.86 28.87 28.88 28.89 28.90 28.91 28.92 28.93 28.94 28.95 28.96 28.97 28.98 28.99 mir_eval-0.8.2/tests/data/multipitch/output00.json000066400000000000000000000010601475740344600221620ustar00rootroot00000000000000{"Precision": 0.8246219899197312, "Recall": 0.3882492529442784, "Accuracy": 0.35863608686827686, "Chroma Precision": 0.8774500653350756, "Chroma Recall": 0.41312181402706977, "Chroma Accuracy": 0.39058540030744943, "Substitution Error": 0.081385129196695383, "Miss Error": 0.53036561785902614, "False Alarm Error": 0.0011865002636667252, "Total Error": 0.61293724731938826, "Chroma Substitution Error": 0.056512568113904024, "Chroma Miss Error": 0.53036561785902614, "Chroma False Alarm Error": 0.0011865002636667252, "Chroma Total Error": 0.58806468623659691}mir_eval-0.8.2/tests/data/multipitch/output01.json000066400000000000000000000010541475740344600221660ustar00rootroot00000000000000{"Precision": 0.7238741088506346, "Recall": 0.326561029181048, "Accuracy": 0.29038783482142855, "Chroma Precision": 0.8137715179968701, "Chroma Recall": 0.36711641041732035, "Chroma Accuracy": 0.33866415804327377, "Substitution Error": 0.11146846564166928, "Miss Error": 0.56197050517728275, "False Alarm Error": 0.013100094132412927, "Total Error": 0.68653906495136496, "Chroma Substitution Error": 0.070913084405396926, "Chroma Miss Error": 0.56197050517728275, "Chroma False Alarm Error": 0.013100094132412927, "Chroma Total Error": 0.64598368371509252}mir_eval-0.8.2/tests/data/multipitch/output02.json000066400000000000000000000010541475740344600221670ustar00rootroot00000000000000{"Precision": 0.7112561174551386, "Recall": 0.5278450363196125, "Accuracy": 0.43469591226321036, "Chroma Precision": 0.8166705507651674, "Chroma Recall": 0.6060763288366194, "Chroma Accuracy": 0.53349233735917989, "Substitution Error": 0.13807217802375188, "Miss Error": 0.33408278565663552, "False Alarm Error": 0.076213536261962408, "Total Error": 0.54836849994234982, "Chroma Substitution Error": 0.059840885506745073, "Chroma Miss Error": 0.33408278565663552, "Chroma False Alarm Error": 0.076213536261962408, "Chroma Total Error": 0.47013720742534304}mir_eval-0.8.2/tests/data/multipitch/output03.json000066400000000000000000000010161475740344600221660ustar00rootroot00000000000000{"Precision": 0.8890164561806353, "Recall": 0.20416593425909652, "Accuracy": 0.19909153239629757, "Chroma Precision": 0.9642173746651359, "Chroma Recall": 0.22143610476357883, "Chroma Accuracy": 0.21963126007932704, "Substitution Error": 0.025487783441729653, "Miss Error": 0.77034628229917379, "False Alarm Error": 0.0, "Total Error": 0.79583406574090354, "Chroma Substitution Error": 0.0082176129372473188, "Chroma Miss Error": 0.77034628229917379, "Chroma False Alarm Error": 0.0, "Chroma Total Error": 0.77856389523642111}mir_eval-0.8.2/tests/data/multipitch/output04.json000066400000000000000000000010531475740344600221700ustar00rootroot00000000000000{"Precision": 0.66839986581684, "Recall": 0.3125980545967995, "Accuracy": 0.27062818336162986, "Chroma Precision": 0.7759141227775914, "Chroma Recall": 0.36288045183558204, "Chroma Accuracy": 0.32845782448168132, "Substitution Error": 0.15147474113586445, "Miss Error": 0.53592720426733609, "False Alarm Error": 0.0036084091622215248, "Total Error": 0.69101035456542204, "Chroma Substitution Error": 0.1011923438970819, "Chroma Miss Error": 0.53592720426733609, "Chroma False Alarm Error": 0.0036084091622215248, "Chroma Total Error": 0.64072795732663945}mir_eval-0.8.2/tests/data/multipitch/output05.json000066400000000000000000000010561475740344600221740ustar00rootroot00000000000000{"Precision": 0.7472312703583062, "Recall": 0.3306237749337023, "Accuracy": 0.29736596494866741, "Chroma Precision": 0.8578501628664496, "Chroma Recall": 0.37956877666320765, "Chroma Accuracy": 0.35710798936920324, "Substitution Error": 0.089646027902686498, "Miss Error": 0.57973019716361118, "False Alarm Error": 0.022195318805488296, "Total Error": 0.69157154387178599, "Chroma Substitution Error": 0.040701026173181137, "Chroma Miss Error": 0.57973019716361118, "Chroma False Alarm Error": 0.022195318805488296, "Chroma Total Error": 0.64262654214228065}mir_eval-0.8.2/tests/data/multipitch/output06.json000066400000000000000000000010511475740344600221700ustar00rootroot00000000000000{"Precision": 0.6321412996075011, "Recall": 0.6311778793816678, "Accuracy": 0.46162420382165603, "Chroma Precision": 0.6838203227213258, "Chroma Recall": 0.6827781406488134, "Chroma Accuracy": 0.51894754261128584, "Substitution Error": 0.18833006749401263, "Miss Error": 0.18049205312431962, "False Alarm Error": 0.17896799477465708, "Total Error": 0.54779011539298939, "Chroma Substitution Error": 0.13672980622686698, "Chroma Miss Error": 0.18049205312431962, "Chroma False Alarm Error": 0.17896799477465708, "Chroma Total Error": 0.49618985412584365}mir_eval-0.8.2/tests/data/multipitch/output07.json000066400000000000000000000010511475740344600221710ustar00rootroot00000000000000{"Precision": 0.5150130548302873, "Recall": 0.6145817105468141, "Accuracy": 0.38928359976317345, "Chroma Precision": 0.5659268929503917, "Chroma Recall": 0.6753388378252064, "Chroma Accuracy": 0.44488916256157635, "Substitution Error": 0.21966038323726436, "Miss Error": 0.16575790621592149, "False Alarm Error": 0.35909020096588251, "Total Error": 0.74450849041906841, "Chroma Substitution Error": 0.15890325595887209, "Chroma Miss Error": 0.16575790621592149, "Chroma False Alarm Error": 0.35909020096588251, "Chroma Total Error": 0.68375136314067608}mir_eval-0.8.2/tests/data/multipitch/output08.json000066400000000000000000000010511475740344600221720ustar00rootroot00000000000000{"Precision": 0.39356984478935697, "Recall": 0.39615009066815454, "Accuracy": 0.24599393676916415, "Chroma Precision": 0.498059866962306, "Chroma Recall": 0.5013251499511787, "Chroma Accuracy": 0.33305532388101194, "Substitution Error": 0.29404379969312316, "Miss Error": 0.30980610963872229, "False Alarm Error": 0.31636211466034314, "Total Error": 0.9202120239921886, "Chroma Substitution Error": 0.18886874041009905, "Chroma Miss Error": 0.30980610963872229, "Chroma False Alarm Error": 0.31636211466034314, "Chroma Total Error": 0.81503696470916442}mir_eval-0.8.2/tests/data/multipitch/output09.json000066400000000000000000000010521475740344600221740ustar00rootroot00000000000000{"Precision": 0.6274555477909776, "Recall": 0.5184448578943992, "Accuracy": 0.3964189354917832, "Chroma Precision": 0.7192328596940756, "Chroma Recall": 0.5942772823506769, "Chroma Accuracy": 0.48237254595636098, "Substitution Error": 0.24161159940976454, "Miss Error": 0.23994354269583629, "False Alarm Error": 0.066209020337460706, "Total Error": 0.54776416244306148, "Chroma Substitution Error": 0.16577917495348687, "Chroma Miss Error": 0.23994354269583629, "Chroma False Alarm Error": 0.066209020337460706, "Chroma Total Error": 0.47193173798678384}mir_eval-0.8.2/tests/data/multipitch/ref00.txt000066400000000000000000005320271475740344600212600ustar00rootroot000000000000000.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 415.30 0.13 415.30 0.14 415.30 0.15 415.30 0.16 415.30 0.17 415.30 0.18 415.30 0.19 415.30 0.20 415.30 0.21 415.30 0.22 415.30 493.88 0.23 415.30 493.88 0.24 415.30 493.88 0.25 415.30 493.88 0.26 415.30 493.88 0.27 415.30 493.88 0.28 415.30 493.88 0.29 415.30 493.88 0.30 415.30 493.88 0.31 415.30 493.88 0.32 415.30 493.88 0.33 415.30 493.88 0.34 415.30 493.88 0.35 415.30 493.88 0.36 415.30 493.88 0.37 415.30 493.88 0.38 415.30 493.88 0.39 415.30 493.88 0.40 415.30 493.88 0.41 415.30 493.88 0.42 415.30 493.88 0.43 415.30 493.88 0.44 415.30 493.88 0.45 415.30 493.88 0.46 415.30 493.88 0.47 415.30 493.88 0.48 415.30 493.88 0.49 415.30 493.88 0.50 415.30 493.88 415.30 0.51 415.30 493.88 415.30 0.52 415.30 493.88 415.30 0.53 415.30 493.88 415.30 0.54 415.30 493.88 415.30 0.55 415.30 493.88 415.30 0.56 415.30 493.88 415.30 0.57 415.30 493.88 415.30 0.58 415.30 493.88 415.30 0.59 415.30 493.88 415.30 0.60 415.30 493.88 415.30 0.61 415.30 493.88 415.30 0.62 415.30 493.88 415.30 0.63 415.30 493.88 415.30 0.64 415.30 493.88 415.30 0.65 415.30 493.88 415.30 0.66 415.30 493.88 415.30 0.67 415.30 493.88 415.30 0.68 415.30 493.88 415.30 0.69 415.30 493.88 415.30 0.70 415.30 493.88 415.30 0.71 415.30 493.88 415.30 0.72 415.30 493.88 415.30 0.73 415.30 493.88 415.30 0.74 415.30 493.88 415.30 0.75 415.30 493.88 415.30 0.76 415.30 493.88 415.30 0.77 415.30 493.88 415.30 0.78 415.30 493.88 415.30 0.79 415.30 493.88 415.30 0.80 415.30 493.88 415.30 0.81 415.30 493.88 415.30 0.82 415.30 493.88 415.30 0.83 415.30 493.88 415.30 0.84 415.30 493.88 415.30 0.85 415.30 493.88 415.30 0.86 415.30 493.88 415.30 0.87 415.30 493.88 415.30 0.88 415.30 493.88 415.30 0.89 415.30 493.88 415.30 0.90 415.30 493.88 415.30 0.91 415.30 493.88 415.30 0.92 415.30 493.88 415.30 0.93 415.30 493.88 415.30 0.94 415.30 493.88 415.30 0.95 415.30 493.88 415.30 0.96 415.30 493.88 415.30 0.97 415.30 493.88 415.30 0.98 415.30 493.88 415.30 0.99 415.30 493.88 415.30 1.00 415.30 493.88 415.30 1.01 415.30 493.88 415.30 1.02 415.30 493.88 415.30 1.03 415.30 493.88 415.30 1.04 415.30 493.88 415.30 1.05 415.30 493.88 415.30 329.63 1.06 415.30 493.88 415.30 329.63 1.07 415.30 493.88 415.30 329.63 1.08 493.88 415.30 329.63 1.09 493.88 415.30 329.63 1.10 493.88 415.30 329.63 415.30 1.11 493.88 415.30 329.63 415.30 1.12 493.88 415.30 329.63 415.30 1.13 493.88 415.30 329.63 415.30 1.14 493.88 415.30 329.63 415.30 329.63 1.15 493.88 415.30 329.63 415.30 329.63 1.16 493.88 415.30 329.63 415.30 329.63 1.17 493.88 415.30 329.63 415.30 329.63 1.18 493.88 415.30 329.63 415.30 329.63 1.19 493.88 415.30 329.63 415.30 329.63 1.20 493.88 415.30 329.63 415.30 329.63 554.37 1.21 493.88 329.63 415.30 329.63 554.37 1.22 493.88 329.63 415.30 329.63 554.37 1.23 493.88 329.63 415.30 329.63 554.37 1.24 493.88 329.63 415.30 329.63 554.37 1.25 493.88 329.63 415.30 329.63 554.37 1.26 493.88 329.63 415.30 329.63 554.37 1.27 493.88 329.63 415.30 329.63 554.37 1.28 329.63 415.30 329.63 554.37 1.29 329.63 415.30 329.63 554.37 1.30 329.63 415.30 329.63 554.37 1.31 329.63 415.30 329.63 554.37 1.32 329.63 415.30 329.63 554.37 1.33 329.63 415.30 329.63 554.37 1.34 329.63 415.30 329.63 554.37 1.35 329.63 415.30 329.63 554.37 1.36 329.63 415.30 329.63 554.37 1.37 329.63 415.30 329.63 554.37 1.38 329.63 415.30 329.63 554.37 1.39 329.63 415.30 329.63 554.37 1.40 329.63 415.30 329.63 554.37 1.41 329.63 415.30 329.63 554.37 1.42 329.63 415.30 329.63 554.37 1.43 329.63 415.30 329.63 554.37 1.44 329.63 415.30 329.63 554.37 1.45 329.63 415.30 329.63 554.37 1.46 329.63 415.30 329.63 554.37 1.47 329.63 415.30 329.63 554.37 1.48 329.63 415.30 329.63 554.37 1.49 329.63 415.30 329.63 554.37 415.30 1.50 329.63 415.30 329.63 554.37 415.30 1.51 329.63 415.30 329.63 554.37 415.30 1.52 329.63 415.30 329.63 554.37 415.30 1.53 329.63 415.30 329.63 554.37 415.30 1.54 415.30 329.63 554.37 415.30 1.55 415.30 329.63 554.37 415.30 1.56 415.30 329.63 554.37 415.30 1.57 415.30 329.63 554.37 415.30 1.58 415.30 329.63 554.37 415.30 1.59 415.30 329.63 554.37 415.30 1.60 415.30 329.63 554.37 415.30 1.61 415.30 329.63 554.37 415.30 1.62 415.30 329.63 554.37 415.30 1.63 415.30 329.63 554.37 415.30 1.64 415.30 329.63 554.37 415.30 1.65 415.30 329.63 554.37 415.30 1.66 415.30 329.63 554.37 415.30 1.67 415.30 329.63 554.37 415.30 1.68 415.30 329.63 554.37 415.30 1.69 415.30 329.63 554.37 415.30 1.70 415.30 329.63 554.37 415.30 1.71 415.30 329.63 554.37 415.30 1.72 415.30 329.63 554.37 415.30 1.73 415.30 329.63 554.37 415.30 1.74 415.30 329.63 554.37 415.30 1.75 415.30 329.63 554.37 415.30 1.76 415.30 329.63 554.37 415.30 1.77 415.30 329.63 554.37 415.30 1.78 415.30 329.63 554.37 415.30 1.79 415.30 329.63 554.37 415.30 1.80 415.30 329.63 554.37 415.30 1.81 415.30 329.63 554.37 415.30 1.82 415.30 329.63 554.37 415.30 1.83 415.30 329.63 554.37 415.30 1.84 415.30 329.63 554.37 415.30 1.85 415.30 329.63 554.37 415.30 1.86 415.30 329.63 554.37 415.30 1.87 415.30 329.63 554.37 415.30 1.88 415.30 329.63 554.37 415.30 1.89 415.30 329.63 554.37 415.30 1.90 415.30 329.63 554.37 415.30 1.91 415.30 329.63 554.37 415.30 1.92 415.30 329.63 554.37 415.30 1.93 415.30 329.63 554.37 415.30 1.94 415.30 329.63 554.37 415.30 1.95 415.30 329.63 554.37 415.30 1.96 415.30 329.63 554.37 415.30 1.97 415.30 329.63 554.37 415.30 1.98 415.30 329.63 554.37 415.30 1.99 415.30 329.63 554.37 415.30 2.00 415.30 329.63 554.37 415.30 2.01 415.30 329.63 554.37 415.30 2.02 415.30 329.63 554.37 415.30 246.94 2.03 415.30 329.63 554.37 415.30 246.94 2.04 415.30 329.63 554.37 415.30 246.94 2.05 415.30 554.37 415.30 246.94 2.06 415.30 554.37 415.30 246.94 415.30 311.13 2.07 415.30 554.37 415.30 246.94 415.30 311.13 2.08 415.30 554.37 415.30 246.94 415.30 311.13 2.09 415.30 554.37 415.30 246.94 415.30 311.13 2.10 415.30 554.37 415.30 246.94 415.30 311.13 2.11 415.30 554.37 415.30 246.94 415.30 311.13 2.12 415.30 554.37 415.30 246.94 415.30 311.13 2.13 415.30 554.37 415.30 246.94 415.30 311.13 2.14 554.37 415.30 246.94 415.30 311.13 2.15 415.30 246.94 415.30 311.13 2.16 415.30 246.94 415.30 311.13 2.17 415.30 246.94 415.30 311.13 2.18 415.30 246.94 415.30 311.13 2.19 415.30 246.94 415.30 311.13 2.20 415.30 246.94 415.30 311.13 2.21 415.30 246.94 415.30 311.13 2.22 415.30 246.94 415.30 311.13 2.23 415.30 246.94 415.30 311.13 2.24 415.30 246.94 415.30 311.13 2.25 415.30 246.94 415.30 311.13 2.26 415.30 246.94 415.30 311.13 2.27 415.30 246.94 415.30 311.13 2.28 415.30 246.94 415.30 311.13 2.29 415.30 246.94 415.30 311.13 2.30 415.30 246.94 415.30 311.13 2.31 415.30 246.94 415.30 311.13 2.32 415.30 246.94 415.30 311.13 2.33 415.30 246.94 415.30 311.13 2.34 415.30 246.94 415.30 311.13 2.35 415.30 246.94 415.30 311.13 2.36 415.30 246.94 415.30 311.13 2.37 415.30 246.94 415.30 311.13 2.38 415.30 246.94 415.30 311.13 2.39 415.30 246.94 415.30 311.13 2.40 415.30 246.94 415.30 311.13 2.41 415.30 246.94 415.30 311.13 2.42 415.30 246.94 415.30 311.13 2.43 415.30 246.94 415.30 311.13 2.44 415.30 246.94 415.30 311.13 2.45 415.30 246.94 415.30 311.13 2.46 415.30 246.94 415.30 311.13 2.47 415.30 246.94 415.30 311.13 2.48 415.30 246.94 415.30 311.13 2.49 415.30 246.94 415.30 311.13 2.50 415.30 246.94 415.30 311.13 2.51 415.30 246.94 415.30 311.13 2.52 415.30 246.94 415.30 311.13 311.13 2.53 415.30 246.94 415.30 311.13 311.13 2.54 415.30 246.94 415.30 311.13 311.13 2.55 415.30 246.94 415.30 311.13 311.13 2.56 415.30 246.94 415.30 311.13 311.13 2.57 415.30 246.94 415.30 311.13 311.13 2.58 415.30 246.94 415.30 311.13 311.13 2.59 246.94 415.30 311.13 311.13 2.60 246.94 415.30 311.13 311.13 2.61 246.94 415.30 311.13 311.13 2.62 246.94 415.30 311.13 311.13 2.63 246.94 415.30 311.13 311.13 2.64 246.94 415.30 311.13 311.13 2.65 246.94 415.30 311.13 311.13 2.66 246.94 415.30 311.13 311.13 2.67 246.94 415.30 311.13 311.13 2.68 246.94 415.30 311.13 311.13 2.69 246.94 415.30 311.13 311.13 2.70 246.94 415.30 311.13 311.13 2.71 246.94 415.30 311.13 311.13 2.72 246.94 415.30 311.13 311.13 2.73 246.94 415.30 311.13 311.13 2.74 246.94 415.30 311.13 311.13 2.75 246.94 415.30 311.13 311.13 2.76 246.94 415.30 311.13 311.13 2.77 246.94 415.30 311.13 311.13 2.78 246.94 415.30 311.13 311.13 2.79 246.94 415.30 311.13 311.13 2.80 246.94 415.30 311.13 311.13 2.81 246.94 415.30 311.13 311.13 2.82 246.94 415.30 311.13 311.13 2.83 246.94 415.30 311.13 311.13 2.84 246.94 415.30 311.13 311.13 2.85 246.94 415.30 311.13 311.13 2.86 246.94 415.30 311.13 311.13 2.87 246.94 415.30 311.13 311.13 2.88 246.94 415.30 311.13 311.13 2.89 246.94 415.30 311.13 311.13 2.90 246.94 415.30 311.13 311.13 2.91 246.94 415.30 311.13 311.13 2.92 246.94 415.30 311.13 311.13 2.93 246.94 415.30 311.13 311.13 2.94 246.94 415.30 311.13 311.13 2.95 246.94 415.30 311.13 311.13 2.96 246.94 415.30 311.13 311.13 2.97 246.94 415.30 311.13 311.13 2.98 246.94 415.30 311.13 311.13 246.94 2.99 246.94 415.30 311.13 311.13 246.94 3.00 246.94 415.30 311.13 311.13 246.94 3.01 246.94 415.30 311.13 311.13 246.94 493.88 3.02 246.94 415.30 311.13 246.94 493.88 3.03 246.94 415.30 311.13 246.94 493.88 3.04 246.94 415.30 311.13 246.94 493.88 3.05 246.94 415.30 311.13 246.94 493.88 3.06 246.94 415.30 311.13 246.94 493.88 3.07 246.94 311.13 246.94 493.88 3.08 246.94 311.13 246.94 493.88 3.09 246.94 311.13 246.94 493.88 3.10 246.94 311.13 246.94 493.88 3.11 246.94 311.13 246.94 493.88 3.12 246.94 311.13 246.94 493.88 3.13 246.94 311.13 246.94 493.88 3.14 246.94 311.13 246.94 493.88 3.15 246.94 311.13 246.94 493.88 3.16 246.94 311.13 246.94 493.88 3.17 246.94 311.13 246.94 493.88 3.18 246.94 311.13 246.94 493.88 3.19 246.94 311.13 246.94 493.88 3.20 246.94 311.13 246.94 493.88 3.21 246.94 311.13 246.94 493.88 3.22 246.94 311.13 246.94 493.88 3.23 246.94 311.13 246.94 493.88 3.24 246.94 311.13 246.94 493.88 3.25 246.94 311.13 246.94 493.88 3.26 246.94 311.13 246.94 493.88 3.27 246.94 311.13 246.94 493.88 3.28 246.94 311.13 246.94 493.88 3.29 246.94 311.13 246.94 493.88 3.30 246.94 311.13 246.94 493.88 3.31 246.94 311.13 246.94 493.88 3.32 246.94 311.13 246.94 493.88 3.33 246.94 311.13 246.94 493.88 3.34 246.94 311.13 246.94 493.88 3.35 246.94 311.13 246.94 493.88 3.36 246.94 311.13 246.94 493.88 3.37 246.94 311.13 246.94 493.88 3.38 246.94 311.13 246.94 493.88 3.39 246.94 311.13 246.94 493.88 3.40 246.94 311.13 246.94 493.88 3.41 246.94 311.13 246.94 493.88 3.42 246.94 311.13 246.94 493.88 3.43 246.94 311.13 246.94 493.88 3.44 246.94 311.13 246.94 493.88 3.45 246.94 311.13 246.94 493.88 3.46 246.94 311.13 246.94 493.88 311.13 3.47 246.94 311.13 246.94 493.88 311.13 3.48 311.13 246.94 493.88 311.13 3.49 311.13 246.94 493.88 311.13 3.50 311.13 246.94 493.88 311.13 3.51 311.13 246.94 493.88 311.13 3.52 311.13 246.94 493.88 311.13 3.53 311.13 246.94 493.88 311.13 3.54 311.13 246.94 493.88 311.13 3.55 311.13 246.94 493.88 311.13 3.56 311.13 246.94 493.88 311.13 3.57 311.13 246.94 493.88 311.13 3.58 311.13 246.94 493.88 311.13 3.59 311.13 246.94 493.88 311.13 3.60 311.13 246.94 493.88 311.13 3.61 311.13 246.94 493.88 311.13 3.62 311.13 246.94 493.88 311.13 3.63 311.13 246.94 493.88 311.13 3.64 311.13 246.94 493.88 311.13 3.65 311.13 246.94 493.88 311.13 3.66 311.13 246.94 493.88 311.13 3.67 311.13 246.94 493.88 311.13 3.68 311.13 246.94 493.88 311.13 3.69 311.13 246.94 493.88 311.13 3.70 311.13 246.94 493.88 311.13 3.71 311.13 246.94 493.88 311.13 3.72 311.13 246.94 493.88 311.13 3.73 311.13 246.94 493.88 311.13 3.74 311.13 246.94 493.88 311.13 3.75 311.13 246.94 493.88 311.13 3.76 311.13 246.94 493.88 311.13 3.77 311.13 246.94 493.88 311.13 3.78 311.13 246.94 493.88 311.13 3.79 311.13 246.94 493.88 311.13 3.80 311.13 246.94 493.88 311.13 3.81 311.13 246.94 493.88 311.13 3.82 311.13 246.94 493.88 311.13 3.83 311.13 246.94 493.88 311.13 3.84 311.13 246.94 493.88 311.13 3.85 311.13 246.94 493.88 311.13 3.86 311.13 246.94 493.88 311.13 3.87 311.13 246.94 493.88 311.13 3.88 311.13 246.94 493.88 311.13 3.89 311.13 246.94 493.88 311.13 3.90 311.13 246.94 493.88 311.13 3.91 311.13 246.94 493.88 311.13 3.92 311.13 246.94 493.88 311.13 3.93 311.13 246.94 493.88 311.13 3.94 246.94 493.88 311.13 3.95 246.94 493.88 311.13 3.96 246.94 493.88 311.13 207.65 3.97 246.94 493.88 311.13 207.65 3.98 246.94 493.88 311.13 207.65 207.65 3.99 246.94 493.88 207.65 207.65 4.00 246.94 493.88 207.65 207.65 4.01 246.94 493.88 207.65 207.65 4.02 246.94 493.88 207.65 207.65 311.13 4.03 246.94 493.88 207.65 207.65 311.13 4.04 246.94 493.88 207.65 207.65 311.13 4.05 493.88 207.65 207.65 311.13 4.06 493.88 207.65 207.65 311.13 4.07 493.88 207.65 207.65 311.13 4.08 493.88 207.65 207.65 311.13 4.09 493.88 207.65 207.65 311.13 4.10 493.88 207.65 207.65 311.13 4.11 493.88 207.65 207.65 311.13 4.12 493.88 207.65 207.65 311.13 4.13 493.88 207.65 207.65 311.13 4.14 493.88 207.65 207.65 311.13 4.15 493.88 207.65 207.65 311.13 4.16 493.88 207.65 207.65 311.13 4.17 493.88 207.65 207.65 311.13 4.18 493.88 207.65 207.65 311.13 4.19 493.88 207.65 207.65 311.13 4.20 493.88 207.65 207.65 311.13 4.21 493.88 207.65 207.65 311.13 4.22 493.88 207.65 207.65 311.13 4.23 493.88 207.65 207.65 311.13 4.24 493.88 207.65 207.65 311.13 4.25 493.88 207.65 207.65 311.13 4.26 493.88 207.65 207.65 311.13 4.27 493.88 207.65 207.65 311.13 4.28 493.88 207.65 207.65 311.13 4.29 493.88 207.65 207.65 311.13 4.30 493.88 207.65 207.65 311.13 4.31 493.88 207.65 207.65 311.13 4.32 493.88 207.65 207.65 311.13 4.33 493.88 207.65 207.65 311.13 4.34 493.88 207.65 207.65 311.13 4.35 493.88 207.65 207.65 311.13 4.36 493.88 207.65 207.65 311.13 4.37 493.88 207.65 207.65 311.13 4.38 493.88 207.65 207.65 311.13 4.39 493.88 207.65 207.65 311.13 4.40 493.88 207.65 207.65 311.13 4.41 493.88 207.65 207.65 311.13 4.42 493.88 207.65 207.65 311.13 4.43 493.88 207.65 207.65 311.13 4.44 493.88 207.65 207.65 311.13 4.45 493.88 207.65 207.65 311.13 4.46 493.88 207.65 207.65 311.13 4.47 493.88 207.65 207.65 311.13 246.94 4.48 493.88 207.65 207.65 311.13 246.94 4.49 493.88 207.65 207.65 311.13 246.94 4.50 493.88 207.65 207.65 311.13 246.94 4.51 493.88 207.65 311.13 246.94 4.52 493.88 207.65 311.13 246.94 4.53 493.88 207.65 311.13 246.94 4.54 493.88 207.65 311.13 246.94 4.55 493.88 207.65 311.13 246.94 4.56 493.88 207.65 311.13 246.94 4.57 493.88 207.65 311.13 246.94 4.58 493.88 207.65 311.13 246.94 4.59 493.88 207.65 311.13 246.94 4.60 493.88 207.65 311.13 246.94 4.61 493.88 207.65 311.13 246.94 4.62 493.88 207.65 311.13 246.94 4.63 493.88 207.65 311.13 246.94 4.64 493.88 207.65 311.13 246.94 4.65 493.88 207.65 311.13 246.94 4.66 493.88 207.65 311.13 246.94 4.67 493.88 207.65 311.13 246.94 4.68 493.88 207.65 311.13 246.94 4.69 493.88 207.65 311.13 246.94 4.70 493.88 207.65 311.13 246.94 4.71 493.88 207.65 311.13 246.94 4.72 493.88 207.65 311.13 246.94 4.73 493.88 207.65 311.13 246.94 4.74 493.88 207.65 311.13 246.94 4.75 493.88 207.65 311.13 246.94 4.76 493.88 207.65 311.13 246.94 4.77 493.88 207.65 311.13 246.94 4.78 493.88 207.65 311.13 246.94 4.79 493.88 207.65 311.13 246.94 4.80 493.88 207.65 311.13 246.94 4.81 493.88 207.65 311.13 246.94 4.82 493.88 207.65 311.13 246.94 4.83 493.88 207.65 311.13 246.94 4.84 493.88 207.65 311.13 246.94 4.85 493.88 207.65 311.13 246.94 4.86 493.88 207.65 311.13 246.94 4.87 493.88 207.65 311.13 246.94 4.88 493.88 311.13 246.94 4.89 493.88 311.13 246.94 4.90 493.88 311.13 246.94 4.91 493.88 311.13 246.94 4.92 493.88 311.13 246.94 4.93 493.88 311.13 246.94 4.94 493.88 311.13 246.94 138.59 4.95 493.88 311.13 246.94 138.59 4.96 493.88 311.13 246.94 138.59 4.97 493.88 311.13 246.94 138.59 329.63 4.98 493.88 311.13 246.94 138.59 329.63 4.99 493.88 311.13 246.94 138.59 329.63 138.59 5.00 493.88 311.13 246.94 138.59 329.63 138.59 5.01 493.88 311.13 246.94 138.59 329.63 138.59 5.02 493.88 311.13 246.94 138.59 329.63 138.59 5.03 493.88 311.13 246.94 138.59 329.63 138.59 5.04 493.88 311.13 246.94 138.59 329.63 138.59 5.05 493.88 246.94 138.59 329.63 138.59 5.06 493.88 246.94 138.59 329.63 138.59 5.07 493.88 246.94 138.59 329.63 138.59 5.08 493.88 246.94 138.59 329.63 138.59 5.09 493.88 246.94 138.59 329.63 138.59 5.10 493.88 246.94 138.59 329.63 138.59 5.11 493.88 246.94 138.59 329.63 138.59 5.12 493.88 246.94 138.59 329.63 138.59 5.13 493.88 246.94 138.59 329.63 138.59 5.14 493.88 246.94 138.59 329.63 138.59 5.15 493.88 246.94 138.59 329.63 138.59 5.16 493.88 246.94 138.59 329.63 138.59 5.17 493.88 246.94 138.59 329.63 138.59 5.18 493.88 246.94 138.59 329.63 138.59 5.19 493.88 246.94 138.59 329.63 138.59 5.20 493.88 246.94 138.59 329.63 138.59 5.21 493.88 246.94 138.59 329.63 138.59 5.22 493.88 246.94 138.59 329.63 138.59 5.23 493.88 246.94 138.59 329.63 138.59 5.24 493.88 246.94 138.59 329.63 138.59 5.25 493.88 246.94 138.59 329.63 138.59 5.26 493.88 246.94 138.59 329.63 138.59 5.27 493.88 246.94 138.59 329.63 138.59 5.28 493.88 246.94 138.59 329.63 138.59 5.29 493.88 246.94 138.59 329.63 138.59 5.30 493.88 246.94 138.59 329.63 138.59 5.31 493.88 246.94 138.59 329.63 138.59 5.32 493.88 246.94 138.59 329.63 138.59 5.33 493.88 246.94 138.59 329.63 138.59 5.34 493.88 246.94 138.59 329.63 138.59 5.35 493.88 246.94 138.59 329.63 138.59 5.36 493.88 246.94 138.59 329.63 138.59 5.37 493.88 246.94 138.59 329.63 138.59 5.38 493.88 246.94 138.59 329.63 138.59 5.39 493.88 246.94 138.59 329.63 138.59 5.40 493.88 246.94 138.59 329.63 138.59 5.41 493.88 246.94 138.59 329.63 138.59 5.42 493.88 246.94 138.59 329.63 138.59 5.43 493.88 246.94 138.59 329.63 138.59 5.44 493.88 138.59 329.63 138.59 5.45 493.88 138.59 329.63 138.59 5.46 493.88 138.59 329.63 138.59 5.47 493.88 138.59 329.63 138.59 5.48 493.88 138.59 329.63 138.59 5.49 493.88 138.59 329.63 138.59 5.50 493.88 138.59 329.63 138.59 5.51 493.88 138.59 329.63 138.59 5.52 493.88 138.59 329.63 138.59 329.63 5.53 493.88 138.59 329.63 138.59 329.63 5.54 138.59 329.63 138.59 329.63 5.55 138.59 329.63 138.59 329.63 5.56 138.59 329.63 138.59 329.63 5.57 138.59 329.63 138.59 329.63 5.58 138.59 329.63 138.59 329.63 5.59 138.59 329.63 138.59 329.63 5.60 138.59 329.63 138.59 329.63 5.61 138.59 329.63 138.59 329.63 5.62 138.59 329.63 138.59 329.63 5.63 138.59 329.63 138.59 329.63 5.64 138.59 329.63 138.59 329.63 5.65 138.59 329.63 138.59 329.63 5.66 138.59 138.59 329.63 5.67 138.59 138.59 329.63 5.68 138.59 138.59 329.63 5.69 138.59 138.59 329.63 5.70 138.59 138.59 329.63 5.71 138.59 138.59 329.63 5.72 138.59 138.59 329.63 5.73 138.59 138.59 329.63 5.74 138.59 138.59 329.63 5.75 138.59 138.59 329.63 5.76 138.59 138.59 329.63 5.77 138.59 138.59 329.63 5.78 138.59 138.59 329.63 5.79 138.59 138.59 329.63 5.80 138.59 138.59 329.63 5.81 138.59 138.59 329.63 5.82 138.59 138.59 329.63 5.83 138.59 138.59 329.63 5.84 138.59 138.59 329.63 5.85 138.59 138.59 329.63 5.86 138.59 138.59 329.63 5.87 138.59 138.59 329.63 5.88 138.59 138.59 329.63 5.89 138.59 138.59 329.63 5.90 138.59 138.59 329.63 5.91 138.59 138.59 329.63 5.92 138.59 138.59 329.63 5.93 138.59 138.59 329.63 5.94 138.59 138.59 329.63 5.95 138.59 138.59 329.63 5.96 138.59 138.59 329.63 5.97 138.59 138.59 329.63 5.98 138.59 138.59 329.63 5.99 138.59 138.59 329.63 6.00 138.59 138.59 329.63 6.01 138.59 138.59 329.63 6.02 138.59 138.59 329.63 246.94 6.03 138.59 138.59 329.63 246.94 6.04 138.59 138.59 329.63 246.94 6.05 138.59 138.59 246.94 6.06 138.59 138.59 246.94 6.07 138.59 138.59 246.94 6.08 138.59 138.59 246.94 659.26 6.09 138.59 138.59 246.94 659.26 6.10 138.59 138.59 246.94 659.26 6.11 138.59 138.59 246.94 659.26 493.88 6.12 138.59 138.59 246.94 659.26 493.88 6.13 138.59 138.59 246.94 659.26 493.88 6.14 138.59 138.59 246.94 659.26 493.88 6.15 138.59 138.59 246.94 659.26 493.88 6.16 138.59 138.59 246.94 659.26 493.88 6.17 138.59 138.59 246.94 659.26 493.88 6.18 138.59 138.59 246.94 659.26 493.88 6.19 138.59 138.59 246.94 659.26 493.88 6.20 138.59 138.59 246.94 659.26 493.88 6.21 138.59 138.59 246.94 659.26 493.88 6.22 138.59 138.59 246.94 659.26 493.88 6.23 138.59 138.59 246.94 659.26 493.88 6.24 138.59 138.59 246.94 659.26 493.88 6.25 138.59 138.59 246.94 659.26 493.88 6.26 138.59 138.59 246.94 659.26 493.88 6.27 138.59 138.59 246.94 659.26 493.88 6.28 138.59 138.59 246.94 659.26 493.88 6.29 138.59 138.59 246.94 659.26 493.88 6.30 138.59 138.59 246.94 659.26 493.88 6.31 138.59 138.59 246.94 659.26 493.88 6.32 138.59 138.59 246.94 659.26 493.88 6.33 138.59 138.59 246.94 659.26 493.88 6.34 138.59 138.59 246.94 659.26 493.88 6.35 138.59 138.59 246.94 659.26 493.88 6.36 138.59 138.59 246.94 659.26 493.88 6.37 138.59 138.59 246.94 659.26 493.88 6.38 138.59 138.59 246.94 659.26 493.88 6.39 138.59 138.59 246.94 659.26 493.88 6.40 138.59 138.59 246.94 659.26 493.88 6.41 138.59 138.59 246.94 659.26 493.88 6.42 138.59 138.59 246.94 659.26 493.88 6.43 138.59 138.59 246.94 659.26 493.88 6.44 138.59 138.59 246.94 659.26 493.88 6.45 138.59 138.59 246.94 659.26 493.88 6.46 138.59 138.59 246.94 659.26 493.88 6.47 138.59 138.59 246.94 659.26 493.88 6.48 138.59 138.59 246.94 659.26 493.88 6.49 138.59 138.59 246.94 659.26 493.88 6.50 138.59 138.59 246.94 659.26 493.88 6.51 138.59 138.59 246.94 659.26 493.88 329.63 6.52 138.59 138.59 246.94 659.26 493.88 329.63 6.53 138.59 138.59 246.94 659.26 493.88 329.63 6.54 138.59 138.59 246.94 659.26 493.88 329.63 6.55 138.59 138.59 246.94 659.26 493.88 329.63 6.56 138.59 138.59 659.26 493.88 329.63 6.57 138.59 138.59 659.26 493.88 329.63 6.58 138.59 138.59 659.26 493.88 329.63 6.59 138.59 138.59 659.26 493.88 329.63 6.60 138.59 138.59 659.26 493.88 329.63 6.61 138.59 138.59 659.26 493.88 329.63 6.62 138.59 138.59 659.26 493.88 329.63 6.63 138.59 138.59 659.26 493.88 329.63 6.64 138.59 138.59 659.26 493.88 329.63 6.65 138.59 138.59 659.26 493.88 329.63 6.66 138.59 138.59 659.26 493.88 329.63 6.67 138.59 138.59 659.26 493.88 329.63 6.68 138.59 138.59 659.26 493.88 329.63 6.69 138.59 138.59 659.26 493.88 329.63 6.70 138.59 138.59 659.26 493.88 329.63 6.71 138.59 138.59 659.26 493.88 329.63 6.72 138.59 138.59 659.26 493.88 329.63 6.73 138.59 138.59 659.26 493.88 329.63 6.74 138.59 138.59 659.26 493.88 329.63 6.75 138.59 138.59 659.26 493.88 329.63 6.76 138.59 138.59 659.26 493.88 329.63 6.77 138.59 138.59 659.26 493.88 329.63 6.78 138.59 138.59 659.26 493.88 329.63 6.79 138.59 138.59 659.26 493.88 329.63 6.80 138.59 138.59 659.26 493.88 329.63 6.81 138.59 138.59 659.26 493.88 329.63 6.82 138.59 138.59 659.26 493.88 329.63 6.83 138.59 138.59 659.26 493.88 329.63 6.84 138.59 138.59 659.26 493.88 329.63 6.85 138.59 138.59 659.26 493.88 329.63 6.86 138.59 138.59 659.26 493.88 329.63 6.87 138.59 138.59 659.26 493.88 329.63 6.88 138.59 138.59 659.26 493.88 329.63 6.89 138.59 138.59 659.26 493.88 329.63 6.90 138.59 138.59 659.26 493.88 329.63 155.56 6.91 138.59 138.59 659.26 493.88 329.63 155.56 6.92 138.59 138.59 659.26 493.88 329.63 155.56 6.93 138.59 138.59 659.26 493.88 329.63 155.56 739.99 6.94 138.59 138.59 659.26 493.88 329.63 155.56 739.99 6.95 138.59 138.59 659.26 493.88 329.63 155.56 739.99 6.96 138.59 659.26 493.88 329.63 155.56 739.99 6.97 138.59 493.88 329.63 155.56 739.99 6.98 138.59 493.88 155.56 739.99 155.56 6.99 138.59 493.88 155.56 739.99 155.56 220.00 7.00 138.59 493.88 155.56 739.99 155.56 220.00 7.01 138.59 493.88 155.56 739.99 155.56 220.00 7.02 138.59 493.88 155.56 739.99 155.56 220.00 7.03 138.59 493.88 155.56 739.99 155.56 220.00 440.00 7.04 138.59 493.88 155.56 739.99 155.56 220.00 440.00 7.05 493.88 155.56 739.99 155.56 220.00 440.00 7.06 493.88 155.56 739.99 155.56 220.00 440.00 7.07 493.88 155.56 739.99 155.56 220.00 440.00 7.08 493.88 155.56 739.99 155.56 220.00 440.00 7.09 493.88 155.56 739.99 155.56 220.00 440.00 7.10 493.88 155.56 739.99 155.56 220.00 440.00 7.11 493.88 155.56 739.99 155.56 220.00 440.00 7.12 155.56 739.99 155.56 220.00 440.00 7.13 155.56 739.99 155.56 220.00 440.00 7.14 155.56 739.99 155.56 220.00 440.00 7.15 155.56 739.99 155.56 220.00 440.00 7.16 155.56 739.99 155.56 220.00 440.00 7.17 155.56 739.99 155.56 220.00 440.00 7.18 155.56 739.99 155.56 220.00 440.00 7.19 155.56 739.99 155.56 220.00 440.00 7.20 155.56 739.99 155.56 220.00 440.00 7.21 155.56 739.99 155.56 220.00 440.00 7.22 155.56 739.99 155.56 220.00 440.00 7.23 155.56 739.99 155.56 220.00 440.00 7.24 155.56 739.99 155.56 220.00 440.00 7.25 155.56 739.99 155.56 220.00 440.00 7.26 155.56 739.99 155.56 220.00 440.00 7.27 155.56 739.99 155.56 220.00 440.00 7.28 155.56 739.99 155.56 220.00 440.00 7.29 155.56 739.99 155.56 220.00 440.00 7.30 155.56 739.99 155.56 220.00 440.00 7.31 155.56 739.99 155.56 220.00 440.00 7.32 155.56 739.99 155.56 220.00 440.00 7.33 155.56 739.99 155.56 220.00 440.00 7.34 155.56 739.99 155.56 220.00 440.00 7.35 155.56 739.99 155.56 220.00 440.00 7.36 155.56 739.99 155.56 220.00 440.00 7.37 155.56 739.99 155.56 220.00 440.00 7.38 155.56 739.99 155.56 220.00 440.00 7.39 155.56 739.99 155.56 220.00 440.00 7.40 155.56 739.99 155.56 220.00 440.00 7.41 155.56 739.99 155.56 220.00 440.00 7.42 155.56 739.99 155.56 220.00 440.00 7.43 155.56 739.99 155.56 220.00 440.00 7.44 155.56 739.99 155.56 220.00 440.00 7.45 155.56 739.99 155.56 220.00 440.00 7.46 155.56 739.99 155.56 220.00 440.00 7.47 155.56 739.99 155.56 220.00 440.00 369.99 7.48 155.56 739.99 155.56 220.00 440.00 369.99 7.49 155.56 739.99 155.56 220.00 440.00 369.99 7.50 155.56 739.99 155.56 220.00 440.00 369.99 7.51 155.56 739.99 155.56 440.00 369.99 7.52 155.56 739.99 155.56 440.00 369.99 7.53 155.56 739.99 155.56 440.00 369.99 7.54 155.56 739.99 155.56 440.00 369.99 7.55 155.56 739.99 155.56 440.00 369.99 7.56 155.56 739.99 155.56 440.00 369.99 7.57 155.56 739.99 155.56 440.00 369.99 7.58 155.56 739.99 155.56 440.00 369.99 7.59 155.56 739.99 155.56 440.00 369.99 7.60 155.56 739.99 155.56 440.00 369.99 7.61 155.56 739.99 155.56 440.00 369.99 7.62 155.56 739.99 155.56 440.00 369.99 7.63 155.56 739.99 155.56 440.00 369.99 7.64 155.56 739.99 155.56 440.00 369.99 7.65 155.56 739.99 155.56 440.00 369.99 7.66 155.56 739.99 155.56 440.00 369.99 7.67 155.56 739.99 155.56 440.00 369.99 7.68 155.56 739.99 155.56 440.00 369.99 7.69 155.56 739.99 155.56 440.00 369.99 7.70 155.56 739.99 155.56 440.00 369.99 7.71 155.56 739.99 155.56 440.00 369.99 7.72 155.56 739.99 155.56 440.00 369.99 7.73 155.56 739.99 155.56 440.00 369.99 7.74 155.56 739.99 155.56 440.00 369.99 7.75 155.56 739.99 155.56 440.00 369.99 7.76 155.56 739.99 155.56 440.00 369.99 7.77 155.56 739.99 155.56 440.00 369.99 7.78 155.56 739.99 155.56 440.00 369.99 7.79 155.56 739.99 155.56 440.00 369.99 7.80 155.56 739.99 155.56 440.00 369.99 7.81 155.56 739.99 155.56 440.00 369.99 7.82 155.56 739.99 155.56 440.00 369.99 7.83 155.56 739.99 155.56 440.00 369.99 7.84 155.56 739.99 155.56 440.00 369.99 7.85 155.56 739.99 155.56 440.00 369.99 7.86 155.56 739.99 155.56 440.00 369.99 7.87 155.56 739.99 155.56 440.00 369.99 7.88 155.56 739.99 155.56 440.00 369.99 415.30 7.89 155.56 739.99 155.56 440.00 369.99 415.30 7.90 155.56 739.99 155.56 440.00 369.99 415.30 164.81 7.91 155.56 739.99 155.56 440.00 369.99 415.30 164.81 554.37 7.92 155.56 739.99 155.56 369.99 415.30 164.81 554.37 7.93 155.56 739.99 155.56 369.99 415.30 164.81 554.37 7.94 155.56 739.99 155.56 369.99 415.30 164.81 554.37 164.81 7.95 155.56 369.99 415.30 164.81 554.37 164.81 7.96 155.56 369.99 415.30 164.81 554.37 164.81 7.97 155.56 369.99 415.30 164.81 554.37 164.81 7.98 369.99 415.30 164.81 554.37 164.81 7.99 369.99 415.30 164.81 554.37 164.81 207.65 8.00 415.30 164.81 554.37 164.81 207.65 8.01 415.30 164.81 554.37 164.81 207.65 8.02 415.30 164.81 554.37 164.81 207.65 8.03 415.30 164.81 554.37 164.81 207.65 8.04 415.30 164.81 554.37 164.81 207.65 8.05 415.30 164.81 554.37 164.81 207.65 8.06 415.30 164.81 554.37 164.81 207.65 8.07 415.30 164.81 554.37 164.81 207.65 8.08 415.30 164.81 554.37 164.81 207.65 8.09 415.30 164.81 554.37 164.81 207.65 8.10 415.30 164.81 554.37 164.81 207.65 8.11 415.30 164.81 554.37 164.81 207.65 8.12 415.30 164.81 554.37 164.81 207.65 8.13 415.30 164.81 554.37 164.81 207.65 8.14 415.30 164.81 554.37 164.81 207.65 8.15 415.30 164.81 554.37 164.81 207.65 8.16 415.30 164.81 554.37 164.81 207.65 8.17 415.30 164.81 554.37 164.81 207.65 8.18 415.30 164.81 554.37 164.81 207.65 8.19 415.30 164.81 554.37 164.81 207.65 8.20 415.30 164.81 554.37 164.81 207.65 8.21 415.30 164.81 554.37 164.81 207.65 8.22 415.30 164.81 554.37 164.81 207.65 8.23 415.30 164.81 554.37 164.81 207.65 8.24 415.30 164.81 554.37 164.81 207.65 8.25 415.30 164.81 554.37 164.81 207.65 8.26 415.30 164.81 554.37 164.81 207.65 8.27 415.30 164.81 554.37 164.81 207.65 8.28 415.30 164.81 554.37 164.81 207.65 8.29 415.30 164.81 554.37 164.81 207.65 8.30 415.30 164.81 554.37 164.81 207.65 8.31 415.30 164.81 554.37 164.81 207.65 8.32 415.30 164.81 554.37 164.81 207.65 8.33 415.30 164.81 554.37 164.81 207.65 8.34 415.30 164.81 554.37 164.81 207.65 8.35 415.30 164.81 554.37 164.81 207.65 8.36 415.30 164.81 554.37 164.81 207.65 8.37 415.30 164.81 554.37 164.81 207.65 8.38 415.30 164.81 554.37 164.81 207.65 8.39 415.30 164.81 554.37 164.81 207.65 8.40 415.30 164.81 554.37 164.81 207.65 8.41 415.30 164.81 554.37 164.81 207.65 415.30 8.42 415.30 164.81 554.37 164.81 207.65 415.30 8.43 415.30 164.81 554.37 164.81 415.30 8.44 415.30 164.81 554.37 164.81 415.30 8.45 415.30 164.81 554.37 164.81 415.30 8.46 415.30 164.81 554.37 164.81 415.30 8.47 415.30 164.81 554.37 164.81 415.30 8.48 415.30 164.81 554.37 164.81 415.30 8.49 415.30 164.81 554.37 164.81 415.30 8.50 415.30 164.81 554.37 164.81 415.30 8.51 415.30 164.81 554.37 164.81 415.30 8.52 415.30 164.81 554.37 164.81 415.30 8.53 415.30 164.81 554.37 164.81 415.30 8.54 415.30 164.81 554.37 164.81 415.30 8.55 415.30 164.81 554.37 164.81 415.30 8.56 415.30 164.81 554.37 164.81 415.30 8.57 415.30 164.81 554.37 164.81 415.30 8.58 415.30 164.81 554.37 164.81 415.30 8.59 415.30 164.81 554.37 164.81 415.30 8.60 415.30 164.81 554.37 164.81 415.30 8.61 415.30 164.81 554.37 164.81 415.30 8.62 415.30 164.81 554.37 164.81 415.30 8.63 415.30 164.81 554.37 164.81 415.30 8.64 415.30 164.81 554.37 164.81 415.30 8.65 415.30 164.81 554.37 164.81 415.30 8.66 415.30 164.81 554.37 164.81 415.30 8.67 415.30 164.81 554.37 164.81 415.30 8.68 415.30 164.81 554.37 164.81 415.30 8.69 415.30 164.81 554.37 164.81 415.30 8.70 415.30 164.81 554.37 164.81 415.30 8.71 415.30 164.81 554.37 164.81 415.30 8.72 415.30 164.81 554.37 164.81 415.30 8.73 415.30 164.81 554.37 164.81 415.30 8.74 415.30 164.81 554.37 164.81 415.30 8.75 415.30 164.81 554.37 164.81 415.30 8.76 415.30 164.81 554.37 164.81 415.30 8.77 415.30 164.81 554.37 164.81 415.30 8.78 415.30 164.81 554.37 164.81 415.30 8.79 415.30 164.81 554.37 164.81 415.30 8.80 415.30 164.81 554.37 164.81 415.30 8.81 415.30 164.81 554.37 164.81 415.30 8.82 415.30 164.81 554.37 164.81 415.30 8.83 415.30 164.81 554.37 164.81 415.30 8.84 415.30 164.81 554.37 164.81 415.30 8.85 415.30 164.81 554.37 164.81 415.30 8.86 415.30 164.81 554.37 164.81 415.30 8.87 415.30 164.81 554.37 164.81 415.30 8.88 415.30 164.81 554.37 164.81 415.30 8.89 415.30 164.81 554.37 164.81 415.30 207.65 8.90 415.30 164.81 554.37 164.81 415.30 207.65 8.91 164.81 554.37 164.81 415.30 207.65 277.18 8.92 164.81 554.37 164.81 415.30 207.65 277.18 8.93 164.81 554.37 164.81 415.30 207.65 277.18 8.94 164.81 554.37 164.81 415.30 207.65 277.18 8.95 164.81 554.37 164.81 415.30 207.65 277.18 659.26 8.96 164.81 554.37 164.81 415.30 207.65 277.18 659.26 8.97 164.81 554.37 164.81 207.65 277.18 659.26 8.98 164.81 554.37 164.81 207.65 277.18 659.26 8.99 164.81 164.81 207.65 277.18 659.26 9.00 164.81 164.81 207.65 277.18 659.26 9.01 164.81 164.81 207.65 277.18 659.26 9.02 164.81 164.81 207.65 277.18 659.26 9.03 164.81 164.81 207.65 277.18 659.26 9.04 164.81 164.81 207.65 277.18 659.26 9.05 164.81 164.81 207.65 277.18 659.26 9.06 164.81 164.81 207.65 277.18 659.26 9.07 164.81 164.81 207.65 277.18 659.26 9.08 164.81 164.81 207.65 277.18 659.26 9.09 164.81 164.81 207.65 277.18 659.26 9.10 164.81 164.81 207.65 277.18 659.26 9.11 164.81 164.81 207.65 277.18 659.26 9.12 164.81 164.81 207.65 277.18 659.26 9.13 164.81 164.81 207.65 277.18 659.26 9.14 164.81 164.81 207.65 277.18 659.26 9.15 164.81 164.81 207.65 277.18 659.26 9.16 164.81 164.81 207.65 277.18 659.26 9.17 164.81 164.81 207.65 277.18 659.26 9.18 164.81 164.81 207.65 277.18 659.26 9.19 164.81 164.81 207.65 277.18 659.26 9.20 164.81 164.81 207.65 277.18 659.26 9.21 164.81 164.81 207.65 277.18 659.26 9.22 164.81 164.81 207.65 277.18 659.26 9.23 164.81 164.81 207.65 277.18 659.26 9.24 164.81 164.81 207.65 277.18 659.26 9.25 164.81 164.81 207.65 277.18 659.26 9.26 164.81 164.81 207.65 277.18 659.26 9.27 164.81 164.81 207.65 277.18 659.26 9.28 164.81 164.81 207.65 277.18 659.26 9.29 164.81 164.81 207.65 277.18 659.26 9.30 164.81 164.81 207.65 277.18 659.26 9.31 164.81 164.81 207.65 277.18 659.26 9.32 164.81 164.81 207.65 277.18 659.26 9.33 164.81 164.81 207.65 277.18 659.26 9.34 164.81 164.81 207.65 277.18 659.26 9.35 164.81 164.81 207.65 277.18 659.26 9.36 164.81 164.81 207.65 277.18 659.26 9.37 164.81 164.81 207.65 277.18 659.26 9.38 164.81 164.81 207.65 277.18 659.26 415.30 9.39 164.81 164.81 207.65 277.18 659.26 415.30 9.40 164.81 164.81 207.65 277.18 659.26 415.30 9.41 164.81 164.81 207.65 277.18 659.26 415.30 9.42 164.81 164.81 207.65 659.26 415.30 9.43 164.81 164.81 207.65 659.26 415.30 9.44 164.81 164.81 207.65 659.26 415.30 9.45 164.81 164.81 207.65 659.26 415.30 9.46 164.81 164.81 207.65 659.26 415.30 9.47 164.81 164.81 207.65 659.26 415.30 9.48 164.81 164.81 207.65 659.26 415.30 9.49 164.81 164.81 207.65 659.26 415.30 9.50 164.81 164.81 207.65 659.26 415.30 9.51 164.81 164.81 207.65 659.26 415.30 9.52 164.81 164.81 207.65 659.26 415.30 9.53 164.81 164.81 207.65 659.26 415.30 9.54 164.81 164.81 207.65 659.26 415.30 9.55 164.81 164.81 207.65 659.26 415.30 9.56 164.81 164.81 207.65 659.26 415.30 9.57 164.81 164.81 207.65 659.26 415.30 9.58 164.81 164.81 207.65 659.26 415.30 9.59 164.81 164.81 207.65 659.26 415.30 9.60 164.81 164.81 207.65 659.26 415.30 9.61 164.81 164.81 207.65 659.26 415.30 9.62 164.81 164.81 207.65 659.26 415.30 9.63 164.81 164.81 207.65 659.26 415.30 9.64 164.81 164.81 207.65 659.26 415.30 9.65 164.81 164.81 207.65 659.26 415.30 9.66 164.81 164.81 207.65 659.26 415.30 9.67 164.81 164.81 207.65 659.26 415.30 9.68 164.81 164.81 207.65 659.26 415.30 9.69 164.81 164.81 207.65 659.26 415.30 9.70 164.81 164.81 207.65 659.26 415.30 9.71 164.81 164.81 207.65 659.26 415.30 9.72 164.81 164.81 207.65 659.26 415.30 9.73 164.81 164.81 207.65 659.26 415.30 9.74 164.81 164.81 207.65 659.26 415.30 9.75 164.81 164.81 207.65 659.26 415.30 9.76 164.81 164.81 207.65 659.26 415.30 9.77 164.81 164.81 207.65 659.26 415.30 9.78 164.81 164.81 207.65 659.26 415.30 9.79 164.81 164.81 207.65 659.26 415.30 155.56 9.80 164.81 164.81 207.65 659.26 415.30 155.56 9.81 164.81 164.81 207.65 659.26 415.30 155.56 493.88 9.82 164.81 164.81 207.65 659.26 415.30 155.56 493.88 9.83 164.81 164.81 207.65 659.26 415.30 155.56 493.88 246.94 9.84 164.81 207.65 659.26 415.30 155.56 493.88 246.94 9.85 164.81 207.65 659.26 155.56 493.88 246.94 155.56 9.86 164.81 207.65 659.26 155.56 493.88 246.94 155.56 9.87 164.81 207.65 659.26 155.56 493.88 246.94 155.56 9.88 164.81 207.65 659.26 155.56 493.88 246.94 155.56 9.89 207.65 659.26 155.56 493.88 246.94 155.56 9.90 659.26 155.56 493.88 246.94 155.56 9.91 659.26 155.56 493.88 246.94 155.56 9.92 659.26 155.56 493.88 246.94 155.56 9.93 659.26 155.56 493.88 246.94 155.56 9.94 659.26 155.56 493.88 246.94 155.56 9.95 659.26 155.56 493.88 246.94 155.56 9.96 659.26 155.56 493.88 246.94 155.56 9.97 659.26 155.56 493.88 246.94 155.56 9.98 659.26 155.56 493.88 246.94 155.56 9.99 659.26 155.56 493.88 246.94 155.56 10.00 659.26 155.56 493.88 246.94 155.56 10.01 659.26 155.56 493.88 246.94 155.56 10.02 659.26 155.56 493.88 246.94 155.56 10.03 659.26 155.56 493.88 246.94 155.56 10.04 659.26 155.56 493.88 246.94 155.56 10.05 659.26 155.56 493.88 246.94 155.56 10.06 659.26 155.56 493.88 246.94 155.56 10.07 659.26 155.56 493.88 246.94 155.56 10.08 659.26 155.56 493.88 246.94 155.56 10.09 659.26 155.56 493.88 246.94 155.56 10.10 659.26 155.56 493.88 246.94 155.56 10.11 659.26 155.56 493.88 246.94 155.56 10.12 659.26 155.56 493.88 246.94 155.56 10.13 659.26 155.56 493.88 246.94 155.56 10.14 659.26 155.56 493.88 246.94 155.56 10.15 659.26 155.56 493.88 246.94 155.56 10.16 659.26 155.56 493.88 246.94 155.56 10.17 659.26 155.56 493.88 246.94 155.56 10.18 659.26 155.56 493.88 246.94 155.56 10.19 659.26 155.56 493.88 246.94 155.56 10.20 659.26 155.56 493.88 246.94 155.56 10.21 659.26 155.56 493.88 246.94 155.56 10.22 659.26 155.56 493.88 246.94 155.56 10.23 659.26 155.56 493.88 246.94 155.56 10.24 659.26 155.56 493.88 246.94 155.56 10.25 659.26 155.56 493.88 246.94 155.56 10.26 659.26 155.56 493.88 246.94 155.56 10.27 659.26 155.56 493.88 246.94 155.56 10.28 659.26 155.56 493.88 246.94 155.56 10.29 659.26 155.56 493.88 246.94 155.56 10.30 659.26 155.56 493.88 246.94 155.56 10.31 659.26 155.56 493.88 246.94 155.56 10.32 659.26 155.56 493.88 246.94 155.56 10.33 659.26 155.56 493.88 246.94 155.56 10.34 659.26 155.56 246.94 155.56 10.35 659.26 155.56 246.94 155.56 246.94 10.36 659.26 155.56 246.94 155.56 246.94 10.37 659.26 155.56 246.94 155.56 246.94 10.38 659.26 155.56 246.94 155.56 246.94 10.39 659.26 155.56 246.94 155.56 246.94 10.40 659.26 155.56 246.94 155.56 246.94 10.41 659.26 155.56 246.94 155.56 246.94 10.42 659.26 155.56 246.94 155.56 246.94 10.43 659.26 155.56 246.94 155.56 246.94 10.44 659.26 155.56 246.94 155.56 246.94 10.45 659.26 155.56 246.94 155.56 246.94 10.46 659.26 155.56 246.94 155.56 246.94 10.47 659.26 155.56 246.94 155.56 246.94 10.48 659.26 155.56 246.94 155.56 246.94 10.49 659.26 155.56 246.94 155.56 246.94 10.50 659.26 155.56 246.94 155.56 246.94 10.51 659.26 155.56 246.94 155.56 246.94 10.52 659.26 155.56 246.94 155.56 246.94 10.53 659.26 155.56 246.94 155.56 246.94 10.54 659.26 155.56 246.94 155.56 246.94 10.55 659.26 155.56 246.94 155.56 246.94 10.56 659.26 155.56 246.94 155.56 246.94 10.57 659.26 155.56 246.94 155.56 246.94 10.58 659.26 155.56 246.94 155.56 246.94 10.59 659.26 155.56 246.94 155.56 246.94 10.60 659.26 155.56 246.94 155.56 246.94 10.61 659.26 155.56 246.94 155.56 246.94 10.62 659.26 155.56 246.94 155.56 246.94 10.63 659.26 155.56 246.94 155.56 246.94 10.64 659.26 155.56 246.94 155.56 246.94 10.65 659.26 155.56 246.94 155.56 246.94 10.66 659.26 155.56 246.94 155.56 246.94 10.67 659.26 155.56 246.94 155.56 246.94 10.68 659.26 155.56 246.94 155.56 246.94 10.69 659.26 155.56 246.94 155.56 246.94 10.70 659.26 155.56 246.94 155.56 246.94 10.71 659.26 155.56 246.94 155.56 246.94 10.72 659.26 155.56 246.94 155.56 246.94 10.73 659.26 155.56 246.94 155.56 246.94 10.74 659.26 155.56 246.94 155.56 246.94 10.75 659.26 155.56 246.94 155.56 246.94 138.59 10.76 659.26 155.56 246.94 155.56 246.94 138.59 10.77 659.26 155.56 246.94 155.56 246.94 138.59 10.78 659.26 155.56 246.94 155.56 246.94 138.59 10.79 659.26 155.56 155.56 246.94 138.59 10.80 659.26 155.56 155.56 246.94 138.59 10.81 659.26 155.56 155.56 246.94 138.59 138.59 10.82 659.26 155.56 155.56 246.94 138.59 138.59 10.83 659.26 155.56 246.94 138.59 138.59 233.08 10.84 659.26 155.56 246.94 138.59 138.59 233.08 10.85 659.26 155.56 246.94 138.59 138.59 233.08 10.86 659.26 155.56 246.94 138.59 138.59 233.08 10.87 659.26 246.94 138.59 138.59 233.08 10.88 659.26 246.94 138.59 138.59 233.08 10.89 659.26 246.94 138.59 138.59 233.08 10.90 659.26 138.59 138.59 233.08 10.91 659.26 138.59 138.59 233.08 10.92 659.26 138.59 138.59 233.08 10.93 659.26 138.59 138.59 233.08 10.94 659.26 138.59 138.59 233.08 10.95 659.26 138.59 138.59 233.08 10.96 659.26 138.59 138.59 233.08 10.97 659.26 138.59 138.59 233.08 10.98 659.26 138.59 138.59 233.08 10.99 659.26 138.59 138.59 233.08 11.00 659.26 138.59 138.59 233.08 11.01 659.26 138.59 138.59 233.08 11.02 659.26 138.59 138.59 233.08 11.03 659.26 138.59 138.59 233.08 11.04 659.26 138.59 138.59 233.08 11.05 659.26 138.59 138.59 233.08 11.06 659.26 138.59 138.59 233.08 11.07 659.26 138.59 138.59 233.08 11.08 659.26 138.59 138.59 233.08 11.09 659.26 138.59 138.59 233.08 11.10 659.26 138.59 138.59 233.08 11.11 659.26 138.59 138.59 233.08 11.12 659.26 138.59 138.59 233.08 11.13 659.26 138.59 138.59 233.08 11.14 659.26 138.59 138.59 233.08 11.15 659.26 138.59 138.59 233.08 11.16 659.26 138.59 138.59 233.08 11.17 659.26 138.59 138.59 233.08 11.18 659.26 138.59 138.59 233.08 11.19 659.26 138.59 138.59 233.08 11.20 659.26 138.59 138.59 233.08 11.21 659.26 138.59 138.59 233.08 11.22 659.26 138.59 138.59 233.08 11.23 659.26 138.59 138.59 233.08 11.24 659.26 138.59 138.59 233.08 11.25 659.26 138.59 138.59 233.08 11.26 659.26 138.59 138.59 233.08 11.27 659.26 138.59 138.59 233.08 466.16 11.28 659.26 138.59 138.59 233.08 466.16 329.63 11.29 659.26 138.59 138.59 233.08 466.16 329.63 11.30 659.26 138.59 138.59 233.08 466.16 329.63 11.31 659.26 138.59 138.59 233.08 466.16 329.63 11.32 659.26 138.59 138.59 233.08 466.16 329.63 11.33 659.26 138.59 138.59 233.08 466.16 329.63 11.34 659.26 138.59 138.59 233.08 466.16 329.63 11.35 659.26 138.59 138.59 233.08 466.16 329.63 11.36 659.26 138.59 138.59 233.08 466.16 329.63 11.37 659.26 138.59 138.59 233.08 466.16 329.63 11.38 659.26 138.59 138.59 233.08 466.16 329.63 11.39 659.26 138.59 138.59 233.08 466.16 329.63 11.40 659.26 138.59 138.59 233.08 466.16 329.63 11.41 659.26 138.59 138.59 233.08 466.16 329.63 11.42 659.26 138.59 138.59 233.08 466.16 329.63 11.43 659.26 138.59 138.59 233.08 466.16 329.63 11.44 659.26 138.59 138.59 233.08 466.16 329.63 11.45 659.26 138.59 138.59 233.08 466.16 329.63 11.46 659.26 138.59 138.59 233.08 466.16 329.63 11.47 659.26 138.59 138.59 233.08 466.16 329.63 11.48 659.26 138.59 138.59 233.08 466.16 329.63 11.49 659.26 138.59 138.59 233.08 466.16 329.63 11.50 659.26 138.59 138.59 233.08 466.16 329.63 11.51 659.26 138.59 138.59 233.08 466.16 329.63 11.52 659.26 138.59 138.59 233.08 466.16 329.63 11.53 659.26 138.59 138.59 233.08 466.16 329.63 11.54 659.26 138.59 138.59 233.08 466.16 329.63 11.55 659.26 138.59 138.59 233.08 466.16 329.63 11.56 659.26 138.59 138.59 233.08 466.16 329.63 11.57 659.26 138.59 138.59 233.08 466.16 329.63 11.58 659.26 138.59 138.59 233.08 466.16 329.63 11.59 659.26 138.59 138.59 233.08 466.16 329.63 11.60 659.26 138.59 138.59 233.08 466.16 329.63 11.61 659.26 138.59 138.59 233.08 466.16 329.63 11.62 659.26 138.59 233.08 466.16 329.63 11.63 138.59 233.08 466.16 329.63 11.64 138.59 233.08 466.16 329.63 11.65 138.59 233.08 466.16 329.63 11.66 138.59 233.08 466.16 329.63 11.67 138.59 233.08 466.16 329.63 11.68 138.59 233.08 466.16 329.63 11.69 138.59 233.08 466.16 329.63 415.30 11.70 138.59 233.08 466.16 329.63 415.30 11.71 138.59 233.08 466.16 329.63 415.30 11.72 138.59 233.08 466.16 329.63 415.30 233.08 11.73 138.59 233.08 466.16 329.63 415.30 233.08 138.59 11.74 138.59 233.08 466.16 415.30 233.08 138.59 830.61 11.75 138.59 233.08 466.16 415.30 233.08 138.59 830.61 11.76 138.59 233.08 415.30 233.08 138.59 830.61 11.77 138.59 233.08 415.30 233.08 138.59 830.61 11.78 138.59 233.08 415.30 233.08 138.59 830.61 11.79 138.59 233.08 415.30 233.08 138.59 830.61 11.80 138.59 233.08 415.30 233.08 138.59 830.61 11.81 138.59 233.08 415.30 233.08 138.59 830.61 11.82 138.59 233.08 415.30 233.08 138.59 830.61 329.63 11.83 138.59 233.08 415.30 233.08 138.59 830.61 329.63 11.84 138.59 415.30 233.08 138.59 830.61 329.63 11.85 138.59 415.30 233.08 138.59 830.61 329.63 11.86 138.59 415.30 233.08 138.59 830.61 329.63 11.87 138.59 415.30 233.08 138.59 830.61 329.63 11.88 138.59 415.30 233.08 138.59 830.61 329.63 11.89 138.59 415.30 233.08 138.59 830.61 329.63 11.90 138.59 415.30 233.08 138.59 830.61 329.63 11.91 138.59 415.30 233.08 138.59 830.61 329.63 11.92 138.59 415.30 233.08 138.59 830.61 329.63 11.93 138.59 415.30 233.08 138.59 830.61 329.63 11.94 138.59 415.30 233.08 138.59 830.61 329.63 11.95 138.59 415.30 233.08 138.59 830.61 329.63 11.96 138.59 415.30 233.08 138.59 830.61 329.63 11.97 138.59 415.30 233.08 138.59 830.61 329.63 11.98 138.59 415.30 233.08 138.59 830.61 329.63 11.99 138.59 415.30 233.08 138.59 830.61 329.63 12.00 138.59 415.30 233.08 138.59 830.61 329.63 12.01 138.59 415.30 233.08 138.59 830.61 329.63 12.02 138.59 415.30 233.08 138.59 830.61 329.63 12.03 138.59 415.30 233.08 138.59 830.61 329.63 12.04 138.59 415.30 233.08 138.59 830.61 329.63 12.05 138.59 415.30 233.08 138.59 830.61 329.63 12.06 138.59 415.30 233.08 138.59 830.61 329.63 12.07 415.30 233.08 138.59 830.61 329.63 12.08 415.30 233.08 138.59 830.61 329.63 12.09 415.30 233.08 138.59 830.61 329.63 12.10 415.30 233.08 138.59 830.61 329.63 12.11 415.30 233.08 138.59 830.61 329.63 12.12 415.30 233.08 138.59 830.61 329.63 12.13 415.30 233.08 138.59 830.61 329.63 12.14 415.30 233.08 138.59 830.61 329.63 12.15 415.30 233.08 138.59 830.61 329.63 12.16 415.30 233.08 138.59 830.61 329.63 12.17 415.30 233.08 138.59 830.61 329.63 12.18 415.30 138.59 830.61 329.63 12.19 415.30 138.59 830.61 329.63 12.20 415.30 138.59 830.61 329.63 12.21 415.30 138.59 830.61 329.63 329.63 12.22 415.30 138.59 830.61 329.63 329.63 12.23 415.30 138.59 830.61 329.63 329.63 12.24 415.30 138.59 830.61 329.63 329.63 12.25 415.30 138.59 830.61 329.63 329.63 12.26 415.30 138.59 830.61 329.63 329.63 12.27 415.30 138.59 830.61 329.63 329.63 12.28 415.30 138.59 830.61 329.63 329.63 12.29 415.30 138.59 830.61 329.63 329.63 12.30 415.30 138.59 830.61 329.63 329.63 12.31 415.30 138.59 830.61 329.63 329.63 12.32 415.30 138.59 830.61 329.63 329.63 12.33 415.30 138.59 830.61 329.63 329.63 12.34 415.30 138.59 830.61 329.63 329.63 12.35 415.30 138.59 830.61 329.63 329.63 12.36 415.30 138.59 830.61 329.63 329.63 12.37 415.30 138.59 830.61 329.63 329.63 12.38 415.30 138.59 830.61 329.63 329.63 12.39 415.30 138.59 830.61 329.63 329.63 12.40 415.30 138.59 830.61 329.63 329.63 12.41 415.30 138.59 830.61 329.63 329.63 12.42 415.30 138.59 830.61 329.63 329.63 12.43 415.30 138.59 830.61 329.63 329.63 12.44 415.30 138.59 830.61 329.63 329.63 12.45 415.30 138.59 830.61 329.63 329.63 12.46 415.30 138.59 830.61 329.63 329.63 12.47 415.30 138.59 830.61 329.63 329.63 12.48 415.30 138.59 830.61 329.63 329.63 12.49 415.30 138.59 830.61 329.63 329.63 12.50 415.30 138.59 830.61 329.63 329.63 12.51 415.30 138.59 830.61 329.63 329.63 12.52 415.30 138.59 830.61 329.63 329.63 12.53 415.30 138.59 830.61 329.63 329.63 12.54 415.30 138.59 830.61 329.63 329.63 12.55 415.30 138.59 830.61 329.63 329.63 12.56 415.30 138.59 830.61 329.63 329.63 12.57 415.30 138.59 830.61 329.63 329.63 12.58 415.30 138.59 830.61 329.63 329.63 12.59 415.30 138.59 830.61 329.63 329.63 12.60 415.30 138.59 830.61 329.63 329.63 12.61 415.30 138.59 830.61 329.63 329.63 12.62 415.30 138.59 830.61 329.63 329.63 12.63 415.30 138.59 830.61 329.63 329.63 12.64 415.30 138.59 830.61 329.63 329.63 12.65 415.30 138.59 830.61 329.63 329.63 12.66 415.30 138.59 830.61 329.63 329.63 12.67 415.30 138.59 830.61 329.63 329.63 659.26 12.68 415.30 138.59 830.61 329.63 329.63 659.26 466.16 12.69 415.30 138.59 830.61 329.63 329.63 659.26 466.16 138.59 69.30 12.70 415.30 138.59 830.61 329.63 329.63 659.26 466.16 138.59 69.30 69.30 466.16 12.71 415.30 138.59 830.61 329.63 659.26 466.16 138.59 69.30 69.30 466.16 12.72 415.30 138.59 830.61 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 12.73 415.30 138.59 830.61 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 12.74 138.59 830.61 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 12.75 138.59 830.61 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 12.76 138.59 830.61 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 12.77 138.59 830.61 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 12.78 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.79 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.80 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.81 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.82 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.83 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.84 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.85 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.86 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.87 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.88 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.89 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.90 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.91 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.92 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.93 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.94 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.95 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.96 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.97 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.98 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.99 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.00 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.01 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.02 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.03 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.04 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.05 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.06 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.07 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.08 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.09 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.10 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.11 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.12 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.13 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.14 466.16 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.15 466.16 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.16 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.17 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.18 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.19 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.20 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.21 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.22 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.23 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.24 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.25 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.26 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.27 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.28 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.29 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.30 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.31 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.32 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.33 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.34 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.35 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.36 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.37 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.38 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.39 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.40 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.41 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.42 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.43 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.44 138.59 69.30 466.16 932.33 164.81 329.63 13.45 138.59 69.30 466.16 932.33 164.81 329.63 13.46 138.59 69.30 466.16 932.33 164.81 329.63 13.47 69.30 466.16 932.33 164.81 329.63 13.48 69.30 466.16 932.33 164.81 329.63 13.49 69.30 466.16 932.33 164.81 329.63 13.50 69.30 466.16 932.33 164.81 329.63 13.51 69.30 466.16 932.33 164.81 329.63 13.52 69.30 466.16 932.33 164.81 329.63 13.53 69.30 466.16 932.33 164.81 329.63 13.54 69.30 466.16 932.33 164.81 329.63 13.55 69.30 466.16 932.33 164.81 329.63 13.56 69.30 466.16 932.33 164.81 329.63 13.57 69.30 466.16 932.33 164.81 329.63 13.58 69.30 466.16 932.33 164.81 329.63 13.59 69.30 466.16 932.33 164.81 329.63 13.60 69.30 466.16 932.33 164.81 329.63 77.78 13.61 69.30 466.16 932.33 164.81 329.63 77.78 369.99 13.62 69.30 466.16 932.33 164.81 329.63 77.78 369.99 13.63 69.30 932.33 164.81 329.63 77.78 369.99 77.78 155.56 13.64 932.33 164.81 329.63 77.78 369.99 77.78 155.56 493.88 13.65 932.33 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 13.66 932.33 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 13.67 932.33 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 13.68 932.33 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 13.69 932.33 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 13.70 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 13.71 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 13.72 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 13.73 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.74 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.75 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.76 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.77 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.78 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.79 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.80 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.82 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.83 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.84 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.85 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.86 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.87 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.88 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.89 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.90 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.91 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.92 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.93 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.94 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.95 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.96 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.97 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.98 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.99 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.00 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.01 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.02 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.03 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.04 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.05 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.06 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.07 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.08 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.09 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.10 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.11 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.12 77.78 77.78 155.56 493.88 369.99 739.99 246.94 14.13 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.14 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.15 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.16 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.17 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.18 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.19 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.20 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.21 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.22 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.23 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.24 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.25 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.26 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.27 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.28 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.29 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.30 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.31 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.32 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.33 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.34 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.35 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.36 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.37 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.38 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.39 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.40 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.41 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.42 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.43 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.44 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.45 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.46 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.47 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.48 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.49 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.50 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.51 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.52 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.53 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 466.16 14.54 77.78 77.78 155.56 493.88 739.99 246.94 246.94 466.16 369.99 14.55 77.78 77.78 155.56 493.88 739.99 246.94 246.94 466.16 369.99 14.56 77.78 77.78 155.56 493.88 739.99 246.94 246.94 466.16 369.99 14.57 77.78 77.78 155.56 493.88 739.99 246.94 246.94 466.16 369.99 14.58 77.78 77.78 155.56 493.88 739.99 246.94 466.16 369.99 14.59 77.78 77.78 155.56 493.88 739.99 246.94 466.16 369.99 14.60 77.78 77.78 155.56 493.88 739.99 246.94 466.16 369.99 14.61 77.78 77.78 155.56 493.88 466.16 369.99 14.62 77.78 155.56 493.88 466.16 369.99 155.56 14.63 77.78 155.56 493.88 466.16 369.99 155.56 932.33 14.64 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.65 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.66 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.67 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.68 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.69 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.70 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.71 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.72 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.73 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.74 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.75 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.76 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.77 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.78 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.79 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.80 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.81 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.82 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.83 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.84 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.85 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.86 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.87 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.88 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.89 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.90 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.91 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.92 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.93 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.94 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.95 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.96 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.97 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.98 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.99 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 15.00 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 15.01 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 15.02 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 15.03 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 15.04 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 15.05 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 246.94 15.06 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 246.94 15.07 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 246.94 15.08 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.09 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.10 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.11 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.12 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.13 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.14 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.15 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.16 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.17 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.18 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.19 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.20 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.21 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.22 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.23 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.24 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.25 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.26 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.27 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.28 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.29 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.30 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.31 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.32 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.33 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.34 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.35 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.36 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.37 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.38 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.39 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.40 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.41 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.42 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.43 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.44 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.45 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.46 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.47 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.48 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.49 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.50 155.56 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 15.51 155.56 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 15.52 155.56 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 15.53 155.56 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 123.47 15.54 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 123.47 311.13 15.55 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 123.47 311.13 15.56 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 123.47 311.13 15.57 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 123.47 311.13 311.13 15.58 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 123.47 311.13 311.13 15.59 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 123.47 311.13 311.13 15.60 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 123.47 311.13 311.13 15.61 493.88 466.16 155.56 932.33 61.74 123.47 123.47 311.13 311.13 15.62 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.63 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.64 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.65 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.66 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.67 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.68 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.69 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.70 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.71 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.72 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.73 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.74 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.75 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.76 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.77 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.78 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.79 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.80 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.81 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.82 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.83 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.84 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.85 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.86 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.87 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.88 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.89 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.90 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.91 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.92 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.93 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.94 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.95 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.96 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.97 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.98 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 415.30 15.99 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 415.30 830.61 16.00 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 415.30 830.61 16.01 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 415.30 830.61 16.02 493.88 466.16 61.74 123.47 123.47 311.13 311.13 415.30 830.61 16.03 493.88 61.74 123.47 123.47 311.13 311.13 415.30 830.61 16.04 493.88 61.74 123.47 123.47 311.13 311.13 415.30 830.61 246.94 16.05 493.88 61.74 123.47 123.47 311.13 311.13 415.30 830.61 246.94 16.06 61.74 123.47 123.47 311.13 311.13 415.30 830.61 246.94 16.07 61.74 123.47 123.47 311.13 311.13 415.30 830.61 246.94 16.08 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.09 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.10 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.11 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.12 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.13 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.14 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.15 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.16 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.17 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.18 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.19 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.20 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.21 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.22 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.23 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.24 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.25 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.26 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.27 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.28 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.29 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.30 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.31 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.32 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.33 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.34 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.35 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.36 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.37 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.38 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.39 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.40 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.41 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.42 61.74 123.47 123.47 311.13 830.61 246.94 16.43 61.74 123.47 311.13 830.61 246.94 16.44 61.74 123.47 311.13 830.61 246.94 16.45 61.74 123.47 311.13 246.94 16.46 61.74 123.47 311.13 246.94 16.47 61.74 123.47 311.13 246.94 16.48 61.74 123.47 311.13 246.94 82.41 164.81 16.49 61.74 123.47 311.13 246.94 82.41 164.81 415.30 493.88 16.50 61.74 123.47 311.13 246.94 82.41 164.81 415.30 493.88 16.51 61.74 123.47 311.13 246.94 82.41 164.81 415.30 493.88 16.52 61.74 123.47 311.13 246.94 82.41 164.81 415.30 493.88 830.61 16.53 61.74 123.47 311.13 246.94 82.41 164.81 415.30 493.88 830.61 16.54 61.74 311.13 246.94 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.55 61.74 311.13 246.94 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.56 246.94 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.57 246.94 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.58 246.94 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.59 246.94 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.60 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.61 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.62 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.63 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.64 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.65 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.66 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.67 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.68 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.69 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.70 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.71 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.72 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.73 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.74 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.75 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.76 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.77 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.78 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.79 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.80 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.81 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.82 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.83 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.84 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.85 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.86 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.87 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.88 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.89 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.90 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.91 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.92 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.93 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.94 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.95 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.96 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.97 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.98 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.99 82.41 164.81 415.30 493.88 830.61 164.81 415.30 17.00 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.01 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.02 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.03 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.04 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.05 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.06 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.07 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.08 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.09 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.10 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.11 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.12 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.13 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.14 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.15 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.16 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.17 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.18 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.19 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.20 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.21 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.22 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.23 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.24 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.25 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.26 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.27 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.28 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.29 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.30 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.31 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.32 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.33 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.34 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.35 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.36 82.41 164.81 415.30 493.88 164.81 415.30 246.94 17.37 82.41 164.81 415.30 493.88 164.81 415.30 246.94 17.38 82.41 164.81 415.30 493.88 164.81 415.30 246.94 17.39 82.41 164.81 415.30 493.88 164.81 415.30 246.94 17.40 82.41 164.81 415.30 164.81 415.30 246.94 17.41 82.41 164.81 415.30 164.81 415.30 246.94 17.42 82.41 164.81 415.30 164.81 415.30 246.94 17.43 82.41 164.81 415.30 164.81 415.30 246.94 17.44 82.41 164.81 415.30 164.81 415.30 246.94 17.45 82.41 164.81 415.30 164.81 415.30 246.94 155.56 369.99 17.46 82.41 164.81 415.30 164.81 415.30 246.94 155.56 369.99 17.47 82.41 164.81 415.30 164.81 415.30 246.94 155.56 369.99 369.99 739.99 77.78 17.48 82.41 164.81 415.30 164.81 415.30 246.94 155.56 369.99 369.99 739.99 77.78 246.94 17.49 82.41 164.81 415.30 246.94 155.56 369.99 369.99 739.99 77.78 246.94 17.50 82.41 164.81 415.30 246.94 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.51 82.41 164.81 415.30 246.94 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.52 82.41 164.81 415.30 246.94 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.53 164.81 415.30 246.94 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.54 164.81 415.30 246.94 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.55 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.56 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.57 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.58 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.59 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.60 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.61 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.62 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.63 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.64 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.65 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.66 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.67 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.68 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.69 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.70 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.71 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.72 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.73 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.74 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.75 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.76 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.77 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.78 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.79 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.80 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.81 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.82 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.83 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.84 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.85 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.86 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.87 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.88 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.89 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.90 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.91 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.92 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.93 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.94 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.95 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.96 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.97 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 17.98 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 17.99 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.00 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.01 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.02 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.03 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.04 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.05 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.06 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.07 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.08 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.09 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.10 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.11 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.12 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.13 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.14 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.15 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.16 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.17 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.18 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.19 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.20 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.21 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.22 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.23 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.24 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.25 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.26 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.27 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.28 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.29 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.30 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.31 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.32 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.33 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.34 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.35 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.36 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.37 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.38 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 61.74 18.39 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 61.74 311.13 18.40 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 61.74 311.13 18.41 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 61.74 311.13 123.47 830.61 415.30 18.42 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 61.74 311.13 123.47 830.61 415.30 18.43 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 61.74 311.13 123.47 830.61 415.30 18.44 369.99 369.99 739.99 246.94 155.56 246.94 61.74 311.13 123.47 830.61 415.30 18.45 369.99 369.99 246.94 246.94 61.74 311.13 123.47 830.61 415.30 18.46 369.99 246.94 61.74 311.13 123.47 830.61 415.30 18.47 369.99 246.94 61.74 311.13 123.47 830.61 415.30 18.48 369.99 246.94 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.49 369.99 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.50 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.51 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.52 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.53 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.54 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.55 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.56 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.57 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.58 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.59 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.60 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.61 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.62 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.63 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.64 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.65 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.66 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.67 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.68 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.69 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.70 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.71 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.72 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.73 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.74 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.75 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.76 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.77 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.78 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.79 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.80 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.81 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.82 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.83 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.84 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.85 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.86 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.87 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.88 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.89 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.90 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.91 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.92 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.93 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.94 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.95 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.96 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.97 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.98 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.99 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.00 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.01 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.02 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.03 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.04 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.05 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.06 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.07 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.08 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.09 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.10 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.11 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.12 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.13 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.14 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.15 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.16 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.17 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.18 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.19 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.20 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.21 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.22 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.23 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.24 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.25 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.26 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.27 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.28 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.29 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.30 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.31 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.32 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.33 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.34 61.74 123.47 830.61 415.30 311.13 123.47 246.94 329.63 19.35 61.74 123.47 830.61 415.30 311.13 123.47 246.94 329.63 138.59 19.36 61.74 123.47 830.61 415.30 311.13 123.47 246.94 329.63 138.59 69.30 19.37 61.74 123.47 830.61 415.30 311.13 123.47 246.94 329.63 138.59 69.30 19.38 61.74 123.47 830.61 415.30 311.13 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.39 61.74 123.47 830.61 415.30 311.13 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.40 61.74 123.47 830.61 415.30 311.13 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.41 61.74 830.61 415.30 311.13 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.42 61.74 311.13 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.43 311.13 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.44 311.13 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.45 311.13 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.46 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.47 123.47 329.63 138.59 69.30 329.63 659.26 138.59 19.48 123.47 329.63 138.59 69.30 329.63 659.26 138.59 19.49 123.47 329.63 138.59 69.30 329.63 659.26 138.59 19.50 123.47 329.63 138.59 69.30 329.63 659.26 138.59 19.51 123.47 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.52 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.53 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.54 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.55 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.56 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.57 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.58 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.59 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.60 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.61 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.62 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.63 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.64 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.65 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.66 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.67 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.68 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.69 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.70 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.71 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.72 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.73 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.74 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.75 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.76 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.77 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.78 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.79 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.80 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.81 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.82 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.83 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.84 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.85 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.86 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.87 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.88 329.63 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.89 329.63 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.90 329.63 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.91 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.92 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.93 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.94 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.95 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.96 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.97 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.98 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.99 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.00 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.01 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.02 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.03 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.04 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.05 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.06 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.07 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.08 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.09 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.10 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.11 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.12 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.13 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.14 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.15 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.16 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.17 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.18 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.19 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.20 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.21 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.22 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.23 69.30 329.63 659.26 138.59 207.65 246.94 20.24 69.30 329.63 659.26 138.59 207.65 246.94 20.25 69.30 329.63 659.26 207.65 246.94 20.26 69.30 329.63 659.26 207.65 246.94 20.27 69.30 329.63 659.26 207.65 246.94 20.28 69.30 329.63 659.26 207.65 246.94 20.29 69.30 329.63 659.26 207.65 246.94 20.30 69.30 329.63 659.26 207.65 246.94 116.54 20.31 69.30 329.63 659.26 207.65 246.94 116.54 116.54 20.32 69.30 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 20.33 69.30 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 20.34 69.30 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 20.35 69.30 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 20.36 69.30 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 415.30 20.37 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 415.30 20.38 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.39 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.40 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.41 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.42 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.43 659.26 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.44 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.45 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.46 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.47 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.48 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.49 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.50 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.51 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.52 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.53 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.54 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.55 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.56 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.57 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.58 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.59 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.60 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.61 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.62 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.63 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.64 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.65 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.66 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.67 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.68 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.69 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.70 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.71 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.72 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.73 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.74 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.75 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.76 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.77 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.78 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.79 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.80 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.81 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.82 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.83 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.84 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.85 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.86 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.87 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.88 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.89 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.90 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.91 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.92 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.93 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.95 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.96 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.97 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.98 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.99 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.00 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.01 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.02 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.03 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.04 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.05 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.06 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.07 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.08 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.09 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.10 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.11 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.12 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.13 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.14 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.15 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.16 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.17 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.18 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.19 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.20 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.21 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.22 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.23 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.24 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.25 116.54 415.30 58.27 415.30 830.61 311.13 277.18 164.81 21.26 116.54 415.30 58.27 415.30 830.61 311.13 277.18 164.81 82.41 21.27 116.54 415.30 58.27 415.30 830.61 311.13 277.18 164.81 82.41 21.28 116.54 415.30 58.27 415.30 830.61 311.13 277.18 164.81 82.41 21.29 116.54 415.30 58.27 415.30 830.61 311.13 277.18 164.81 82.41 21.30 116.54 415.30 58.27 415.30 830.61 311.13 277.18 164.81 82.41 164.81 21.31 116.54 415.30 58.27 415.30 830.61 311.13 277.18 164.81 82.41 164.81 21.32 116.54 415.30 58.27 415.30 830.61 311.13 277.18 164.81 82.41 164.81 233.08 21.33 116.54 415.30 415.30 830.61 311.13 277.18 164.81 82.41 164.81 233.08 233.08 21.34 116.54 415.30 415.30 830.61 311.13 277.18 164.81 82.41 164.81 233.08 233.08 21.35 116.54 415.30 415.30 830.61 311.13 164.81 82.41 164.81 233.08 233.08 21.36 116.54 415.30 415.30 830.61 311.13 164.81 82.41 164.81 233.08 233.08 21.37 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.38 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.39 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.40 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.41 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.42 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.43 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.44 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.45 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.46 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.47 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.48 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.49 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.50 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.51 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.52 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.53 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.54 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.55 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.56 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.57 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.58 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.59 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.60 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.61 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.62 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.63 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.64 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.65 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.66 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.67 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.68 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.69 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.70 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.71 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.72 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.73 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.74 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.75 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.76 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.77 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 739.99 21.78 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 739.99 21.79 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 739.99 21.80 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 739.99 369.99 21.81 415.30 415.30 164.81 82.41 164.81 233.08 233.08 739.99 369.99 21.82 415.30 415.30 164.81 82.41 164.81 233.08 233.08 739.99 369.99 369.99 21.83 415.30 415.30 164.81 82.41 164.81 233.08 233.08 739.99 369.99 369.99 21.84 164.81 82.41 164.81 233.08 233.08 739.99 369.99 369.99 21.85 164.81 82.41 164.81 233.08 233.08 739.99 369.99 369.99 21.86 164.81 82.41 164.81 233.08 233.08 739.99 369.99 369.99 21.87 164.81 82.41 164.81 233.08 233.08 739.99 369.99 369.99 21.88 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.89 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.90 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.91 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.92 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.93 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.94 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.95 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.96 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.97 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.98 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.99 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.00 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.01 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.02 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.03 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.04 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.05 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.06 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.07 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.08 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.09 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.10 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.11 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.12 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.13 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.14 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.15 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.16 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.17 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.18 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.19 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.20 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.21 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.22 164.81 82.41 164.81 233.08 369.99 369.99 22.23 164.81 82.41 164.81 233.08 369.99 369.99 22.24 164.81 82.41 164.81 233.08 369.99 369.99 22.25 164.81 82.41 164.81 233.08 369.99 22.26 164.81 82.41 164.81 233.08 369.99 22.27 164.81 82.41 164.81 233.08 369.99 22.28 164.81 82.41 164.81 233.08 369.99 22.29 164.81 82.41 164.81 233.08 369.99 22.30 164.81 82.41 164.81 233.08 369.99 22.31 82.41 164.81 233.08 369.99 369.99 77.78 22.32 82.41 233.08 369.99 369.99 77.78 155.56 22.33 82.41 233.08 369.99 369.99 77.78 155.56 739.99 22.34 82.41 233.08 369.99 369.99 77.78 155.56 739.99 22.35 82.41 233.08 369.99 369.99 77.78 155.56 739.99 22.36 233.08 369.99 369.99 77.78 155.56 739.99 246.94 22.37 233.08 369.99 369.99 77.78 155.56 739.99 246.94 22.38 233.08 369.99 369.99 77.78 155.56 739.99 246.94 22.39 233.08 369.99 369.99 77.78 155.56 739.99 246.94 22.40 233.08 369.99 369.99 77.78 155.56 739.99 246.94 22.41 369.99 369.99 77.78 155.56 739.99 246.94 22.42 369.99 369.99 77.78 155.56 739.99 246.94 22.43 369.99 369.99 77.78 155.56 739.99 246.94 22.44 369.99 369.99 77.78 155.56 739.99 246.94 22.45 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.46 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.47 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.48 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.49 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.50 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.51 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.52 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.53 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.54 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.55 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.56 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.57 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.58 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.59 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.60 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.61 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.62 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.63 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.64 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.65 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.66 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.67 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.68 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.69 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.70 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.71 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.72 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.73 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.74 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.75 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.76 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.77 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.78 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.79 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.80 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.81 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.82 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.83 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.84 369.99 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.85 369.99 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.86 369.99 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.87 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.88 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.89 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.90 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.91 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.92 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.93 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.94 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.95 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.96 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.97 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.98 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.99 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.00 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.01 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.02 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.03 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.04 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.05 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.06 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.07 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.08 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.09 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.10 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.11 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.12 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.13 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.14 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.15 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.16 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.17 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.18 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.19 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.20 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.21 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.22 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.23 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.24 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.25 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.26 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.27 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.28 369.99 77.78 155.56 739.99 246.94 155.56 246.94 61.74 23.29 369.99 77.78 155.56 739.99 246.94 155.56 246.94 61.74 23.30 369.99 77.78 155.56 739.99 246.94 155.56 246.94 61.74 23.31 369.99 77.78 739.99 246.94 155.56 246.94 61.74 23.32 369.99 77.78 739.99 246.94 155.56 246.94 61.74 123.47 23.33 369.99 739.99 246.94 155.56 246.94 61.74 123.47 123.47 311.13 311.13 23.34 369.99 739.99 246.94 246.94 61.74 123.47 123.47 311.13 311.13 23.35 369.99 739.99 246.94 246.94 61.74 123.47 123.47 311.13 311.13 23.36 739.99 246.94 246.94 61.74 123.47 123.47 311.13 311.13 23.37 739.99 246.94 246.94 61.74 123.47 123.47 311.13 311.13 23.38 739.99 246.94 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.39 739.99 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.40 739.99 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.41 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.42 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.43 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.44 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.45 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.46 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.47 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.48 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.49 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.50 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.51 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.52 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.53 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.54 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.55 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.56 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.57 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.58 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.59 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.60 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.61 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.62 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.63 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.64 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.65 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.66 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.67 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.68 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.69 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.70 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.71 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.72 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.73 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.74 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.75 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.76 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.77 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.78 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.79 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.80 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.81 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.82 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.83 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.84 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.85 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.86 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.87 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.88 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.89 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.90 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.91 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.92 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.93 246.94 61.74 123.47 123.47 311.13 311.13 622.25 246.94 23.94 246.94 61.74 123.47 123.47 311.13 311.13 622.25 246.94 23.95 246.94 61.74 123.47 123.47 311.13 311.13 622.25 246.94 23.96 246.94 61.74 123.47 123.47 311.13 622.25 246.94 23.97 246.94 61.74 123.47 123.47 311.13 622.25 246.94 23.98 246.94 61.74 123.47 123.47 311.13 622.25 246.94 23.99 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.00 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.01 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.02 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.03 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.04 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.05 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.06 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.07 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.08 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.09 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.10 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.11 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.12 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.13 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.14 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.15 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.16 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.17 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.18 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.19 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.20 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.21 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.22 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.23 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.24 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.25 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.26 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.27 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.28 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.29 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.30 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.31 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.32 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.33 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.34 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.35 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.36 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.37 246.94 61.74 123.47 123.47 311.13 622.25 246.94 103.83 24.38 246.94 61.74 123.47 123.47 311.13 622.25 246.94 103.83 24.39 246.94 61.74 123.47 123.47 311.13 622.25 246.94 103.83 659.26 329.63 24.40 246.94 61.74 123.47 123.47 311.13 622.25 246.94 103.83 659.26 329.63 51.91 24.41 246.94 61.74 123.47 123.47 311.13 246.94 103.83 659.26 329.63 51.91 103.83 24.42 246.94 61.74 123.47 123.47 311.13 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.43 246.94 61.74 123.47 311.13 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.44 246.94 123.47 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.45 246.94 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.46 246.94 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.47 246.94 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.48 246.94 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.49 246.94 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.50 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.51 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.52 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.53 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.54 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.55 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.56 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.57 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.58 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.59 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.60 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.61 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.62 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.63 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.64 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.65 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.66 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.67 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.68 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.69 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.70 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.71 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.72 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.73 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.74 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.75 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.76 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.77 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.78 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.79 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.80 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.81 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.82 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.83 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.84 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.85 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.86 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.87 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.88 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.89 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.90 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.91 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.92 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.93 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.94 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.95 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.96 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.97 103.83 659.26 329.63 51.91 103.83 329.63 24.98 103.83 659.26 329.63 51.91 103.83 329.63 24.99 103.83 659.26 329.63 51.91 103.83 329.63 246.94 25.00 103.83 659.26 51.91 103.83 329.63 246.94 25.01 103.83 659.26 51.91 103.83 329.63 246.94 25.02 103.83 659.26 51.91 103.83 329.63 246.94 25.03 103.83 659.26 51.91 103.83 329.63 246.94 25.04 103.83 659.26 51.91 103.83 329.63 246.94 25.05 103.83 659.26 51.91 103.83 329.63 246.94 25.06 103.83 659.26 51.91 103.83 329.63 246.94 25.07 103.83 659.26 51.91 103.83 329.63 246.94 25.08 103.83 659.26 51.91 103.83 329.63 246.94 25.09 103.83 659.26 51.91 103.83 329.63 246.94 25.10 103.83 659.26 51.91 103.83 329.63 246.94 25.11 103.83 659.26 51.91 103.83 329.63 246.94 25.12 103.83 659.26 51.91 103.83 329.63 246.94 25.13 103.83 659.26 51.91 103.83 329.63 246.94 25.14 103.83 659.26 51.91 103.83 329.63 246.94 25.15 103.83 659.26 51.91 103.83 329.63 246.94 25.16 103.83 659.26 51.91 103.83 329.63 246.94 25.17 103.83 659.26 51.91 103.83 329.63 246.94 25.18 103.83 659.26 51.91 103.83 329.63 246.94 25.19 103.83 659.26 51.91 103.83 329.63 246.94 25.20 103.83 659.26 51.91 103.83 329.63 246.94 25.21 103.83 659.26 51.91 103.83 329.63 246.94 25.22 103.83 659.26 51.91 103.83 329.63 246.94 25.23 103.83 659.26 51.91 103.83 329.63 246.94 25.24 103.83 659.26 51.91 103.83 329.63 246.94 25.25 103.83 659.26 51.91 103.83 329.63 246.94 25.26 103.83 659.26 51.91 103.83 329.63 246.94 25.27 103.83 659.26 51.91 103.83 329.63 246.94 25.28 103.83 659.26 51.91 103.83 329.63 246.94 25.29 103.83 659.26 51.91 103.83 329.63 246.94 25.30 103.83 659.26 51.91 103.83 329.63 246.94 25.31 103.83 659.26 51.91 103.83 329.63 246.94 25.32 103.83 659.26 51.91 103.83 329.63 246.94 25.33 103.83 659.26 51.91 103.83 329.63 246.94 25.34 103.83 659.26 51.91 103.83 329.63 246.94 25.35 103.83 659.26 51.91 103.83 329.63 246.94 25.36 103.83 659.26 51.91 103.83 329.63 246.94 25.37 103.83 659.26 51.91 103.83 329.63 246.94 25.38 103.83 659.26 51.91 103.83 329.63 246.94 25.39 103.83 659.26 51.91 103.83 329.63 246.94 25.40 103.83 659.26 51.91 103.83 329.63 246.94 25.41 103.83 51.91 103.83 329.63 246.94 25.42 103.83 51.91 103.83 329.63 246.94 554.37 277.18 25.43 103.83 51.91 103.83 329.63 246.94 554.37 277.18 25.44 103.83 51.91 103.83 329.63 246.94 554.37 277.18 25.45 103.83 51.91 103.83 329.63 246.94 554.37 277.18 25.46 51.91 103.83 329.63 246.94 554.37 277.18 25.47 51.91 103.83 329.63 246.94 554.37 277.18 116.54 329.63 25.48 51.91 103.83 246.94 554.37 277.18 116.54 329.63 25.49 51.91 103.83 246.94 554.37 277.18 116.54 329.63 58.27 116.54 25.50 51.91 103.83 246.94 554.37 277.18 116.54 329.63 58.27 116.54 25.51 51.91 246.94 554.37 277.18 116.54 329.63 58.27 116.54 25.52 246.94 554.37 277.18 116.54 329.63 58.27 116.54 25.53 246.94 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.54 246.94 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.55 246.94 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.56 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.57 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.58 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.59 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.60 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.61 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.62 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.63 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.64 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.65 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.66 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.67 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.68 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.69 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.70 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.71 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.72 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.73 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.74 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.75 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.76 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.77 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.78 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.79 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.80 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.81 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.82 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.83 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.84 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.85 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.86 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.87 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.88 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.89 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.90 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.91 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.92 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.93 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.94 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.95 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.96 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.97 554.37 277.18 116.54 329.63 58.27 116.54 277.18 164.81 25.98 554.37 277.18 116.54 329.63 58.27 116.54 277.18 164.81 25.99 554.37 277.18 116.54 329.63 58.27 116.54 277.18 164.81 26.00 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.01 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.02 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.03 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.04 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.05 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.06 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.07 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.08 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.09 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.10 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.11 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.12 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.13 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.14 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.15 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.16 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.17 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.18 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.19 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.20 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.21 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.22 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.23 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.24 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.25 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.26 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.27 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.28 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.29 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.30 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.31 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.32 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.33 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.34 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.35 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.36 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.37 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.38 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.39 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.40 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.41 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.42 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.43 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.44 554.37 116.54 329.63 58.27 116.54 277.18 164.81 659.26 26.45 554.37 116.54 329.63 58.27 116.54 277.18 164.81 659.26 103.83 26.46 116.54 329.63 58.27 116.54 277.18 164.81 659.26 103.83 51.91 103.83 246.94 329.63 26.47 116.54 329.63 58.27 116.54 277.18 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.48 116.54 329.63 58.27 116.54 277.18 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.49 116.54 329.63 58.27 116.54 277.18 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.50 116.54 329.63 58.27 116.54 277.18 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.51 329.63 116.54 277.18 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.52 329.63 116.54 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.53 329.63 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.54 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.55 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.56 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.57 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.58 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.59 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.60 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.61 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.62 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.63 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.64 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.65 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.66 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.67 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.68 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.69 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.70 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.71 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.72 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.73 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.74 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.75 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.76 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.77 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.78 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.79 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.80 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.81 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.82 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.83 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.84 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.85 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.86 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.87 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.88 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.89 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.90 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.91 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.92 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.93 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.94 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.95 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.96 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.97 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.98 659.26 103.83 51.91 103.83 246.94 329.63 329.63 246.94 26.99 659.26 103.83 51.91 103.83 246.94 329.63 329.63 246.94 27.00 659.26 103.83 51.91 103.83 246.94 329.63 329.63 246.94 27.01 659.26 103.83 51.91 103.83 246.94 329.63 329.63 246.94 27.02 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.03 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.04 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.05 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.06 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.07 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.08 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.09 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.10 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.11 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.12 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.13 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.14 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.15 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.16 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.17 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.18 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.19 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.20 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.21 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.22 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.23 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.24 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.25 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.26 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.27 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.28 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.29 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.30 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.31 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.32 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.33 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.34 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.35 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.36 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.37 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.38 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.39 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.40 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.41 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.42 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.43 659.26 103.83 51.91 103.83 246.94 329.63 246.94 49.00 27.44 659.26 103.83 51.91 103.83 329.63 246.94 49.00 98.00 27.45 659.26 103.83 51.91 103.83 329.63 246.94 49.00 98.00 27.46 659.26 103.83 103.83 329.63 246.94 49.00 98.00 98.00 27.47 659.26 103.83 103.83 329.63 246.94 49.00 98.00 98.00 233.08 27.48 659.26 103.83 103.83 329.63 246.94 49.00 98.00 98.00 233.08 27.49 659.26 329.63 246.94 49.00 98.00 98.00 233.08 27.50 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.51 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.52 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.53 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.54 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.55 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.56 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.57 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.58 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.59 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.60 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.61 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.62 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.63 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.64 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.65 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.66 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.67 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.68 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.69 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.70 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.71 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.72 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.73 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.74 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.75 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.76 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.77 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.78 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.79 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.80 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.81 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.82 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.83 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.84 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.85 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.86 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.87 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.88 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.89 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.90 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.91 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.92 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.93 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.94 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.95 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.96 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.97 659.26 329.63 49.00 98.00 98.00 233.08 233.08 466.16 27.98 659.26 329.63 49.00 98.00 98.00 233.08 233.08 466.16 27.99 659.26 329.63 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.00 659.26 329.63 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.01 329.63 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.02 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.03 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.04 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.05 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.06 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.07 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.08 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.09 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.10 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.11 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.12 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.13 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.14 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.15 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.16 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.17 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.18 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.19 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.20 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.21 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.22 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.23 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.24 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.25 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.26 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.27 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.28 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.29 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.30 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.31 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.32 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.33 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.34 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.35 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.36 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.37 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.38 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.39 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.40 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.41 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.42 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.43 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.44 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.45 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.46 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.47 49.00 98.00 98.00 233.08 466.16 311.13 28.48 49.00 98.00 98.00 233.08 466.16 311.13 28.49 49.00 98.00 98.00 466.16 28.50 49.00 98.00 98.00 466.16 51.91 28.51 49.00 98.00 98.00 466.16 51.91 28.52 49.00 98.00 98.00 466.16 51.91 28.53 49.00 98.00 98.00 466.16 51.91 246.94 103.83 493.88 28.54 49.00 98.00 98.00 466.16 51.91 246.94 103.83 493.88 28.55 49.00 98.00 98.00 466.16 51.91 246.94 103.83 493.88 103.83 622.25 28.56 49.00 98.00 98.00 466.16 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.57 49.00 98.00 98.00 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.58 98.00 98.00 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.59 98.00 98.00 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.60 98.00 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.61 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.62 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.63 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.64 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.65 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.66 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.67 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.68 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.69 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.70 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.71 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.72 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.73 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.74 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.75 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.76 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.77 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.78 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.79 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.80 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.81 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.82 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.83 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.84 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.85 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.86 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.87 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.88 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.89 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.90 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.91 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.92 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.93 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.94 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.95 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.96 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.97 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.98 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.99 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.00 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.01 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.02 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.03 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.04 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.05 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.06 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.07 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.08 51.91 246.94 103.83 103.83 622.25 311.13 246.94 29.09 51.91 246.94 103.83 103.83 622.25 311.13 246.94 29.10 51.91 246.94 103.83 103.83 622.25 311.13 246.94 29.11 51.91 246.94 103.83 622.25 311.13 246.94 29.12 51.91 246.94 103.83 622.25 311.13 246.94 29.13 51.91 246.94 103.83 622.25 311.13 246.94 29.14 51.91 246.94 103.83 622.25 311.13 246.94 29.15 51.91 246.94 103.83 622.25 311.13 246.94 29.16 51.91 246.94 103.83 622.25 311.13 246.94 29.17 51.91 246.94 103.83 622.25 311.13 246.94 29.18 51.91 246.94 103.83 622.25 311.13 246.94 29.19 51.91 246.94 103.83 622.25 311.13 246.94 29.20 51.91 246.94 103.83 622.25 311.13 246.94 29.21 51.91 246.94 103.83 622.25 311.13 246.94 29.22 51.91 246.94 103.83 622.25 311.13 246.94 29.23 51.91 246.94 103.83 622.25 311.13 246.94 29.24 51.91 246.94 103.83 622.25 311.13 246.94 29.25 51.91 246.94 103.83 622.25 311.13 246.94 29.26 51.91 246.94 103.83 622.25 311.13 246.94 29.27 51.91 246.94 103.83 622.25 311.13 246.94 29.28 51.91 246.94 103.83 622.25 311.13 246.94 29.29 51.91 246.94 103.83 622.25 311.13 246.94 29.30 51.91 246.94 103.83 622.25 311.13 246.94 29.31 51.91 246.94 103.83 622.25 311.13 246.94 29.32 51.91 246.94 103.83 622.25 311.13 246.94 29.33 51.91 246.94 103.83 622.25 311.13 246.94 29.34 51.91 246.94 103.83 622.25 311.13 246.94 29.35 51.91 246.94 103.83 622.25 311.13 246.94 29.36 51.91 246.94 103.83 622.25 311.13 246.94 29.37 51.91 246.94 103.83 622.25 311.13 246.94 29.38 51.91 246.94 103.83 622.25 311.13 246.94 29.39 51.91 246.94 103.83 622.25 311.13 246.94 29.40 51.91 246.94 103.83 622.25 311.13 246.94 29.41 51.91 246.94 103.83 622.25 311.13 246.94 29.42 51.91 246.94 103.83 622.25 311.13 246.94 29.43 51.91 246.94 103.83 622.25 311.13 246.94 29.44 51.91 246.94 103.83 622.25 311.13 246.94 29.45 51.91 246.94 103.83 622.25 311.13 246.94 29.46 51.91 246.94 103.83 622.25 311.13 246.94 29.47 246.94 622.25 311.13 246.94 29.48 246.94 622.25 311.13 246.94 29.49 246.94 622.25 311.13 246.94 29.50 246.94 622.25 311.13 246.94 29.51 246.94 622.25 311.13 246.94 29.52 246.94 622.25 311.13 246.94 29.53 246.94 622.25 311.13 246.94 29.54 622.25 311.13 246.94 29.55 622.25 311.13 246.94 29.56 622.25 311.13 246.94 185.00 440.00 29.57 622.25 311.13 246.94 185.00 440.00 92.50 29.58 622.25 311.13 246.94 185.00 440.00 92.50 185.00 29.59 622.25 311.13 246.94 185.00 440.00 92.50 185.00 29.60 622.25 311.13 246.94 185.00 440.00 92.50 185.00 29.61 622.25 311.13 246.94 185.00 440.00 92.50 185.00 220.00 29.62 622.25 311.13 246.94 185.00 440.00 92.50 185.00 220.00 29.63 622.25 311.13 246.94 185.00 440.00 92.50 185.00 220.00 29.64 622.25 311.13 246.94 185.00 440.00 92.50 185.00 220.00 29.65 246.94 185.00 440.00 92.50 185.00 220.00 29.66 185.00 440.00 92.50 185.00 220.00 29.67 185.00 440.00 92.50 185.00 220.00 29.68 185.00 440.00 92.50 185.00 220.00 29.69 185.00 440.00 92.50 185.00 220.00 29.70 185.00 440.00 92.50 185.00 220.00 29.71 185.00 440.00 92.50 185.00 220.00 29.72 185.00 440.00 92.50 185.00 220.00 29.73 185.00 440.00 92.50 185.00 220.00 29.74 185.00 440.00 92.50 185.00 220.00 523.25 29.75 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.76 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.77 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.78 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.79 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.80 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.81 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.82 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.83 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.84 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.85 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.86 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.87 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.88 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.89 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.90 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.91 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.92 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.93 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.94 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.95 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.96 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.97 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.98 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.99 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.00 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.01 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.02 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.03 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.04 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.05 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.06 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.07 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.08 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.09 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.10 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.11 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.12 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.13 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.14 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.15 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.16 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.17 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.18 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.19 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.20 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.21 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.22 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.23 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.24 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.25 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.26 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.27 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.28 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.29 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.30 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.31 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.32 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.33 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.34 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.35 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.36 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.37 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.38 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.39 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.40 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.41 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.42 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.43 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.44 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.45 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.46 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.47 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.48 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.49 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.50 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.51 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.52 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.53 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.54 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.55 185.00 92.50 185.00 220.00 523.25 311.13 220.00 82.41 30.56 185.00 92.50 185.00 220.00 523.25 311.13 220.00 82.41 164.81 164.81 30.57 185.00 92.50 185.00 220.00 523.25 311.13 220.00 82.41 164.81 164.81 30.58 185.00 92.50 185.00 220.00 523.25 311.13 220.00 82.41 164.81 164.81 30.59 185.00 92.50 185.00 220.00 523.25 311.13 220.00 82.41 164.81 164.81 30.60 92.50 185.00 220.00 523.25 311.13 220.00 82.41 164.81 164.81 30.61 185.00 220.00 523.25 311.13 220.00 82.41 164.81 164.81 30.62 185.00 220.00 523.25 311.13 220.00 82.41 164.81 164.81 30.63 220.00 523.25 311.13 220.00 82.41 164.81 164.81 30.64 220.00 523.25 311.13 220.00 82.41 164.81 164.81 554.37 30.65 220.00 523.25 311.13 220.00 82.41 164.81 164.81 554.37 415.30 30.66 220.00 523.25 311.13 220.00 82.41 164.81 164.81 554.37 415.30 277.18 30.67 220.00 523.25 311.13 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.68 220.00 523.25 311.13 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.69 220.00 523.25 311.13 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.70 220.00 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.71 220.00 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.72 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.73 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.74 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.75 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.76 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.77 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.78 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.79 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.80 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.81 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.82 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.83 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.84 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.85 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.86 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.87 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.88 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.89 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.90 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.91 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.92 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.93 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.94 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.95 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.96 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.97 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.98 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.99 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.01 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.02 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.03 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.04 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.05 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.06 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.07 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.08 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.09 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.10 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.11 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.12 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.13 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.14 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.15 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.16 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.17 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.18 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.19 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.20 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.21 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.22 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.23 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.24 82.41 164.81 164.81 554.37 415.30 277.18 207.65 207.65 31.25 82.41 164.81 164.81 554.37 415.30 277.18 207.65 207.65 31.26 82.41 164.81 164.81 554.37 415.30 277.18 207.65 207.65 31.27 82.41 164.81 164.81 554.37 415.30 277.18 207.65 207.65 31.28 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.29 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.30 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.31 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.32 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.33 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.34 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.35 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.36 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.37 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.38 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.39 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.40 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.41 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.42 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.43 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.44 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.45 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.46 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.47 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.48 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.49 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.50 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.51 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.52 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.53 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.54 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.55 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.56 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.57 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.58 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.59 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.60 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.61 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.62 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.63 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.64 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.65 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.66 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.67 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.68 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.69 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.70 82.41 164.81 164.81 554.37 277.18 207.65 207.65 369.99 31.71 82.41 164.81 164.81 554.37 277.18 207.65 207.65 369.99 31.72 82.41 164.81 164.81 554.37 277.18 207.65 207.65 369.99 155.56 220.00 31.73 82.41 164.81 164.81 554.37 277.18 207.65 207.65 369.99 155.56 220.00 31.74 82.41 164.81 164.81 554.37 277.18 207.65 207.65 369.99 155.56 220.00 31.75 82.41 164.81 164.81 554.37 277.18 207.65 369.99 155.56 220.00 155.56 31.76 82.41 164.81 164.81 554.37 277.18 207.65 369.99 155.56 220.00 155.56 77.78 31.77 82.41 164.81 164.81 277.18 207.65 369.99 155.56 220.00 155.56 77.78 31.78 82.41 164.81 277.18 207.65 369.99 155.56 220.00 155.56 77.78 31.79 164.81 277.18 207.65 369.99 155.56 220.00 155.56 77.78 31.80 277.18 207.65 369.99 155.56 220.00 155.56 77.78 31.81 277.18 207.65 369.99 155.56 220.00 155.56 77.78 369.99 31.82 277.18 207.65 369.99 155.56 220.00 155.56 77.78 369.99 31.83 277.18 207.65 369.99 155.56 220.00 155.56 77.78 369.99 31.84 277.18 207.65 369.99 155.56 220.00 155.56 77.78 369.99 31.85 277.18 207.65 369.99 155.56 220.00 155.56 77.78 369.99 31.86 277.18 207.65 369.99 155.56 220.00 155.56 77.78 369.99 31.87 277.18 207.65 369.99 155.56 220.00 155.56 77.78 369.99 31.88 277.18 207.65 369.99 155.56 220.00 155.56 77.78 369.99 31.89 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.90 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.91 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.92 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.93 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.94 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.95 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.96 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.97 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.98 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.99 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.00 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.01 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.02 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.03 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.04 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.05 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.06 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.07 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.08 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.09 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.10 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.11 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.12 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.13 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.14 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.15 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.16 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.17 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.18 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.19 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.20 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.21 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.22 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.23 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.24 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.25 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.26 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.27 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.28 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.29 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.30 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.31 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.32 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.33 277.18 369.99 155.56 220.00 155.56 77.78 369.99 185.00 32.34 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.35 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.36 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.37 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.38 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.39 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.40 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.41 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.42 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.43 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.44 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.45 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.46 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.47 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.48 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.49 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.50 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.51 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.52 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.53 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.54 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.55 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.56 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.57 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.58 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.59 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.60 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.61 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.62 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.63 277.18 155.56 220.00 155.56 77.78 369.99 32.64 277.18 155.56 220.00 155.56 77.78 369.99 32.65 277.18 155.56 220.00 155.56 77.78 369.99 32.66 277.18 155.56 220.00 155.56 77.78 369.99 32.67 277.18 155.56 220.00 155.56 77.78 369.99 32.68 277.18 155.56 220.00 155.56 77.78 369.99 32.69 277.18 155.56 220.00 155.56 77.78 369.99 32.70 277.18 155.56 220.00 155.56 77.78 369.99 32.71 277.18 155.56 220.00 155.56 77.78 369.99 32.72 277.18 155.56 220.00 155.56 77.78 369.99 32.73 277.18 155.56 220.00 155.56 77.78 369.99 32.74 277.18 155.56 220.00 155.56 77.78 369.99 138.59 32.75 277.18 155.56 220.00 155.56 77.78 369.99 138.59 329.63 32.76 277.18 155.56 220.00 155.56 77.78 369.99 138.59 329.63 32.77 277.18 155.56 220.00 155.56 77.78 369.99 138.59 329.63 32.78 277.18 155.56 220.00 155.56 77.78 369.99 138.59 329.63 440.00 164.81 32.79 277.18 155.56 220.00 155.56 77.78 369.99 138.59 329.63 440.00 164.81 32.80 155.56 220.00 155.56 77.78 369.99 138.59 329.63 440.00 164.81 32.81 220.00 155.56 77.78 369.99 138.59 329.63 440.00 164.81 440.00 32.82 220.00 155.56 77.78 369.99 138.59 329.63 440.00 164.81 440.00 69.30 32.83 220.00 155.56 77.78 369.99 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.84 155.56 77.78 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.85 155.56 77.78 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.86 155.56 77.78 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.87 155.56 77.78 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.88 155.56 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.89 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.90 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.91 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.92 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.93 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.94 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.95 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.96 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.97 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.98 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.99 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.00 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.01 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.02 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.03 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.04 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.05 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.06 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.07 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.08 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.09 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.10 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.11 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.12 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.13 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.14 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.15 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.16 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.17 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.18 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.19 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.20 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.21 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.22 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.23 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.24 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.25 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.26 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.27 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.28 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.29 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.30 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.31 138.59 329.63 440.00 164.81 440.00 69.30 138.59 329.63 33.32 138.59 329.63 440.00 164.81 440.00 69.30 138.59 329.63 33.33 138.59 329.63 440.00 164.81 440.00 69.30 138.59 329.63 33.34 138.59 329.63 440.00 164.81 440.00 69.30 138.59 329.63 33.35 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.36 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.37 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.38 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.39 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.40 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.41 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.42 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.43 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.44 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.45 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.46 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.47 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.48 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.49 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.50 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.51 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.52 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.53 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.54 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.55 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.56 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.57 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.58 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.59 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.60 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.61 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.62 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.63 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.64 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.65 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.66 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.67 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.68 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.69 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.70 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.71 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.72 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.73 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.74 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.75 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.76 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.77 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.78 138.59 329.63 164.81 440.00 69.30 138.59 329.63 130.81 33.79 138.59 329.63 164.81 440.00 69.30 138.59 329.63 130.81 33.80 138.59 329.63 164.81 440.00 69.30 138.59 329.63 130.81 65.41 33.81 138.59 329.63 164.81 440.00 69.30 138.59 329.63 130.81 65.41 130.81 33.82 138.59 329.63 164.81 440.00 69.30 138.59 329.63 130.81 65.41 130.81 311.13 33.83 138.59 329.63 164.81 440.00 138.59 329.63 130.81 65.41 130.81 311.13 311.13 33.84 138.59 329.63 164.81 440.00 138.59 329.63 130.81 65.41 130.81 311.13 311.13 33.85 329.63 164.81 440.00 138.59 329.63 130.81 65.41 130.81 311.13 311.13 33.86 164.81 440.00 138.59 329.63 130.81 65.41 130.81 311.13 311.13 33.87 164.81 440.00 138.59 329.63 130.81 65.41 130.81 311.13 311.13 33.88 164.81 440.00 329.63 130.81 65.41 130.81 311.13 311.13 33.89 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.90 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.91 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.92 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.93 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.94 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.95 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.96 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.97 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.98 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.99 164.81 440.00 130.81 65.41 130.81 311.13 311.13 34.00 440.00 130.81 65.41 130.81 311.13 311.13 34.01 440.00 130.81 65.41 130.81 311.13 311.13 34.02 440.00 130.81 65.41 130.81 311.13 311.13 34.03 440.00 130.81 65.41 130.81 311.13 311.13 34.04 440.00 130.81 65.41 130.81 311.13 311.13 34.05 440.00 130.81 65.41 130.81 311.13 311.13 34.06 440.00 130.81 65.41 130.81 311.13 311.13 34.07 440.00 130.81 65.41 130.81 311.13 311.13 34.08 440.00 130.81 65.41 130.81 311.13 311.13 34.09 440.00 130.81 65.41 130.81 311.13 311.13 34.10 440.00 130.81 65.41 130.81 311.13 311.13 34.11 440.00 130.81 65.41 130.81 311.13 311.13 34.12 440.00 130.81 65.41 130.81 311.13 311.13 34.13 440.00 130.81 65.41 130.81 311.13 311.13 34.14 440.00 130.81 65.41 130.81 311.13 311.13 34.15 440.00 130.81 65.41 130.81 311.13 311.13 34.16 440.00 130.81 65.41 130.81 311.13 311.13 34.17 440.00 130.81 65.41 130.81 311.13 311.13 34.18 440.00 130.81 65.41 130.81 311.13 311.13 34.19 440.00 130.81 65.41 130.81 311.13 311.13 34.20 440.00 130.81 65.41 130.81 311.13 311.13 34.21 440.00 130.81 65.41 130.81 311.13 311.13 34.22 440.00 130.81 65.41 130.81 311.13 311.13 34.23 440.00 130.81 65.41 130.81 311.13 311.13 34.24 440.00 130.81 65.41 130.81 311.13 311.13 34.25 440.00 130.81 65.41 130.81 311.13 311.13 34.26 440.00 130.81 65.41 130.81 311.13 311.13 34.27 440.00 130.81 65.41 130.81 311.13 311.13 34.28 440.00 130.81 65.41 130.81 311.13 311.13 34.29 440.00 130.81 65.41 130.81 311.13 311.13 34.30 440.00 130.81 65.41 130.81 311.13 311.13 207.65 34.31 440.00 130.81 65.41 130.81 311.13 311.13 207.65 34.32 440.00 130.81 65.41 130.81 311.13 311.13 207.65 415.30 34.33 440.00 130.81 65.41 130.81 311.13 311.13 207.65 415.30 34.34 440.00 130.81 65.41 130.81 311.13 311.13 207.65 415.30 34.35 440.00 130.81 65.41 130.81 311.13 311.13 207.65 415.30 34.36 130.81 65.41 130.81 311.13 311.13 207.65 415.30 34.37 130.81 65.41 130.81 311.13 311.13 207.65 415.30 34.38 130.81 65.41 130.81 311.13 207.65 415.30 34.39 130.81 65.41 130.81 311.13 207.65 415.30 34.40 130.81 65.41 130.81 311.13 207.65 415.30 34.41 130.81 65.41 130.81 311.13 207.65 415.30 34.42 130.81 65.41 130.81 311.13 207.65 415.30 34.43 130.81 65.41 130.81 311.13 207.65 415.30 34.44 130.81 65.41 130.81 311.13 207.65 415.30 34.45 130.81 65.41 130.81 311.13 207.65 415.30 34.46 130.81 65.41 130.81 311.13 207.65 415.30 34.47 130.81 65.41 130.81 311.13 207.65 415.30 34.48 130.81 65.41 130.81 311.13 207.65 415.30 34.49 130.81 65.41 130.81 311.13 207.65 415.30 34.50 130.81 65.41 130.81 311.13 207.65 415.30 34.51 130.81 65.41 130.81 311.13 207.65 415.30 34.52 130.81 65.41 130.81 311.13 207.65 415.30 34.53 130.81 65.41 130.81 311.13 207.65 415.30 34.54 130.81 65.41 130.81 311.13 207.65 415.30 34.55 130.81 65.41 130.81 311.13 207.65 415.30 34.56 130.81 65.41 130.81 311.13 207.65 415.30 34.57 130.81 65.41 130.81 311.13 207.65 415.30 34.58 130.81 65.41 130.81 311.13 207.65 415.30 34.59 130.81 65.41 130.81 311.13 207.65 415.30 34.60 130.81 65.41 130.81 311.13 207.65 415.30 34.61 130.81 65.41 130.81 311.13 207.65 415.30 34.62 130.81 65.41 130.81 311.13 207.65 415.30 34.63 130.81 65.41 130.81 311.13 207.65 415.30 34.64 130.81 65.41 130.81 311.13 207.65 415.30 34.65 130.81 65.41 130.81 311.13 207.65 415.30 34.66 130.81 65.41 130.81 311.13 207.65 415.30 34.67 130.81 65.41 130.81 311.13 207.65 415.30 34.68 130.81 65.41 130.81 311.13 207.65 415.30 34.69 130.81 65.41 130.81 311.13 207.65 415.30 34.70 130.81 65.41 130.81 311.13 207.65 415.30 34.71 130.81 65.41 130.81 311.13 207.65 415.30 34.72 130.81 65.41 130.81 311.13 207.65 415.30 34.73 130.81 65.41 130.81 311.13 207.65 415.30 34.74 130.81 65.41 130.81 311.13 207.65 415.30 34.75 130.81 65.41 130.81 311.13 207.65 415.30 34.76 130.81 65.41 130.81 311.13 207.65 415.30 34.77 130.81 65.41 130.81 311.13 207.65 415.30 34.78 130.81 65.41 130.81 311.13 207.65 415.30 34.79 130.81 65.41 130.81 311.13 207.65 415.30 34.80 130.81 65.41 130.81 311.13 207.65 415.30 34.81 130.81 65.41 130.81 311.13 207.65 415.30 34.82 130.81 65.41 130.81 311.13 207.65 415.30 34.83 130.81 65.41 130.81 311.13 207.65 34.84 130.81 65.41 130.81 311.13 207.65 34.85 130.81 65.41 130.81 311.13 207.65 34.86 130.81 65.41 130.81 311.13 207.65 34.87 130.81 65.41 130.81 311.13 207.65 138.59 34.88 130.81 65.41 130.81 311.13 207.65 138.59 138.59 69.30 34.89 130.81 65.41 130.81 311.13 207.65 138.59 138.59 69.30 415.30 34.90 130.81 65.41 130.81 311.13 207.65 138.59 138.59 69.30 415.30 34.91 130.81 65.41 130.81 311.13 207.65 138.59 138.59 69.30 415.30 329.63 34.92 130.81 65.41 130.81 311.13 207.65 138.59 138.59 69.30 415.30 329.63 34.93 130.81 65.41 130.81 311.13 207.65 138.59 138.59 69.30 415.30 329.63 34.94 65.41 130.81 311.13 207.65 138.59 138.59 69.30 415.30 329.63 34.95 130.81 311.13 207.65 138.59 138.59 69.30 415.30 329.63 34.96 130.81 311.13 207.65 138.59 138.59 69.30 415.30 329.63 34.97 130.81 207.65 138.59 138.59 69.30 415.30 329.63 34.98 130.81 207.65 138.59 138.59 69.30 415.30 329.63 34.99 130.81 207.65 138.59 138.59 69.30 415.30 329.63 35.00 130.81 207.65 138.59 138.59 69.30 415.30 329.63 35.01 130.81 207.65 138.59 138.59 69.30 415.30 329.63 35.02 130.81 207.65 138.59 138.59 69.30 415.30 329.63 35.03 207.65 138.59 138.59 69.30 415.30 329.63 35.04 207.65 138.59 138.59 69.30 415.30 329.63 35.05 207.65 138.59 138.59 69.30 415.30 329.63 35.06 207.65 138.59 138.59 69.30 415.30 329.63 35.07 207.65 138.59 138.59 69.30 415.30 329.63 35.08 207.65 138.59 138.59 69.30 415.30 329.63 35.09 207.65 138.59 138.59 69.30 415.30 329.63 35.10 207.65 138.59 138.59 69.30 415.30 329.63 35.11 207.65 138.59 138.59 69.30 415.30 329.63 35.12 207.65 138.59 138.59 69.30 415.30 329.63 35.13 207.65 138.59 138.59 69.30 415.30 329.63 35.14 207.65 138.59 138.59 69.30 415.30 329.63 35.15 207.65 138.59 138.59 69.30 415.30 329.63 35.16 207.65 138.59 138.59 69.30 415.30 329.63 35.17 207.65 138.59 138.59 69.30 415.30 329.63 35.18 207.65 138.59 138.59 69.30 415.30 329.63 35.19 207.65 138.59 138.59 69.30 415.30 329.63 35.20 207.65 138.59 138.59 69.30 415.30 329.63 35.21 207.65 138.59 138.59 69.30 415.30 329.63 35.22 207.65 138.59 138.59 69.30 415.30 329.63 35.23 207.65 138.59 138.59 69.30 415.30 329.63 35.24 207.65 138.59 138.59 69.30 415.30 329.63 35.25 207.65 138.59 138.59 69.30 415.30 329.63 35.26 207.65 138.59 138.59 69.30 415.30 329.63 35.27 207.65 138.59 138.59 69.30 415.30 329.63 35.28 207.65 138.59 138.59 69.30 415.30 329.63 35.29 207.65 138.59 138.59 69.30 415.30 329.63 35.30 207.65 138.59 138.59 69.30 415.30 329.63 35.31 207.65 138.59 138.59 69.30 415.30 329.63 35.32 207.65 138.59 138.59 69.30 415.30 329.63 35.33 207.65 138.59 138.59 69.30 415.30 329.63 35.34 207.65 138.59 138.59 69.30 415.30 329.63 35.35 207.65 138.59 138.59 69.30 415.30 329.63 35.36 207.65 138.59 138.59 69.30 415.30 329.63 35.37 207.65 138.59 138.59 69.30 415.30 329.63 35.38 207.65 138.59 138.59 69.30 415.30 329.63 35.39 207.65 138.59 138.59 69.30 415.30 329.63 35.40 207.65 138.59 138.59 69.30 415.30 329.63 35.41 207.65 138.59 138.59 69.30 415.30 329.63 35.42 207.65 138.59 138.59 69.30 415.30 329.63 35.43 207.65 138.59 138.59 69.30 415.30 329.63 35.44 207.65 138.59 138.59 69.30 415.30 329.63 35.45 207.65 138.59 138.59 69.30 415.30 329.63 35.46 207.65 138.59 138.59 69.30 415.30 329.63 35.47 207.65 138.59 138.59 69.30 415.30 329.63 35.48 207.65 138.59 138.59 69.30 415.30 329.63 35.49 207.65 138.59 138.59 69.30 415.30 329.63 35.50 207.65 138.59 138.59 69.30 415.30 329.63 35.51 207.65 138.59 138.59 69.30 415.30 329.63 35.52 207.65 138.59 138.59 69.30 415.30 329.63 35.53 207.65 138.59 138.59 69.30 415.30 329.63 35.54 207.65 138.59 138.59 69.30 415.30 329.63 35.55 207.65 138.59 138.59 69.30 415.30 329.63 35.56 207.65 138.59 138.59 69.30 415.30 329.63 35.57 207.65 138.59 138.59 69.30 415.30 329.63 35.58 207.65 138.59 138.59 69.30 415.30 329.63 35.59 207.65 138.59 138.59 69.30 415.30 329.63 35.60 207.65 138.59 138.59 69.30 415.30 329.63 35.61 207.65 138.59 138.59 69.30 415.30 329.63 35.62 207.65 138.59 138.59 69.30 415.30 329.63 35.63 207.65 138.59 138.59 69.30 415.30 329.63 35.64 207.65 138.59 138.59 69.30 415.30 329.63 35.65 207.65 138.59 138.59 69.30 415.30 329.63 35.66 207.65 138.59 138.59 69.30 415.30 329.63 35.67 207.65 138.59 138.59 69.30 415.30 329.63 35.68 207.65 138.59 138.59 69.30 415.30 329.63 35.69 207.65 138.59 138.59 69.30 415.30 329.63 35.70 207.65 138.59 138.59 69.30 415.30 329.63 35.71 207.65 138.59 138.59 69.30 415.30 329.63 35.72 207.65 138.59 138.59 69.30 415.30 329.63 35.73 207.65 138.59 138.59 69.30 415.30 329.63 35.74 207.65 138.59 138.59 69.30 415.30 329.63 35.75 207.65 138.59 138.59 69.30 415.30 329.63 35.76 207.65 138.59 138.59 69.30 415.30 329.63 35.77 207.65 138.59 138.59 69.30 415.30 329.63 35.78 207.65 138.59 138.59 69.30 415.30 329.63 35.79 207.65 138.59 138.59 69.30 415.30 329.63 35.80 207.65 138.59 138.59 69.30 415.30 329.63 35.81 207.65 138.59 138.59 69.30 415.30 329.63 35.82 207.65 138.59 138.59 69.30 415.30 329.63 35.83 207.65 138.59 138.59 69.30 415.30 329.63 35.84 207.65 138.59 138.59 69.30 415.30 329.63 35.85 207.65 138.59 138.59 69.30 415.30 329.63 35.86 207.65 138.59 138.59 69.30 415.30 329.63 35.87 207.65 138.59 138.59 69.30 415.30 329.63 35.88 207.65 138.59 138.59 69.30 415.30 329.63 35.89 207.65 138.59 138.59 69.30 415.30 329.63 35.90 207.65 138.59 138.59 69.30 415.30 329.63 35.91 207.65 138.59 138.59 69.30 415.30 329.63 35.92 207.65 138.59 138.59 69.30 415.30 329.63 35.93 207.65 138.59 138.59 69.30 415.30 329.63 35.94 207.65 138.59 138.59 69.30 415.30 329.63 35.95 138.59 69.30 415.30 329.63 35.96 138.59 69.30 415.30 329.63 35.97 138.59 69.30 415.30 329.63 35.98 69.30 415.30 329.63 35.99 415.30 329.63 36.00 415.30 329.63 36.01 415.30 329.63 36.02 415.30 329.63 36.03 415.30 329.63 36.04 415.30 329.63 36.05 415.30 329.63 36.06 415.30 329.63 36.07 415.30 329.63 36.08 415.30 329.63 36.09 415.30 329.63 36.10 415.30 329.63 36.11 415.30 329.63 36.12 415.30 329.63 36.13 415.30 329.63 36.14 415.30 329.63 36.15 415.30 329.63 36.16 329.63mir_eval-0.8.2/tests/data/multipitch/ref01.txt000066400000000000000000003131761475740344600212630ustar00rootroot000000000000000.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 440.00 0.23 440.00 0.24 440.00 0.25 440.00 220.00 0.26 440.00 220.00 0.27 440.00 220.00 0.28 440.00 220.00 0.29 440.00 220.00 0.30 440.00 220.00 0.31 440.00 220.00 0.32 440.00 220.00 0.33 440.00 220.00 0.34 440.00 220.00 0.35 440.00 220.00 0.36 440.00 220.00 0.37 440.00 220.00 0.38 440.00 220.00 0.39 440.00 220.00 0.40 440.00 220.00 0.41 440.00 220.00 0.42 440.00 220.00 0.43 440.00 220.00 0.44 440.00 220.00 0.45 440.00 220.00 0.46 440.00 220.00 0.47 440.00 220.00 0.48 440.00 220.00 0.49 440.00 220.00 0.50 440.00 220.00 440.00 0.51 440.00 220.00 440.00 0.52 440.00 220.00 440.00 0.53 440.00 220.00 440.00 0.54 440.00 220.00 440.00 0.55 440.00 220.00 440.00 0.56 440.00 220.00 440.00 0.57 440.00 220.00 440.00 0.58 440.00 220.00 440.00 0.59 440.00 220.00 440.00 0.60 440.00 220.00 440.00 0.61 440.00 220.00 440.00 0.62 440.00 220.00 440.00 0.63 440.00 220.00 440.00 0.64 440.00 220.00 440.00 0.65 440.00 220.00 440.00 0.66 440.00 220.00 440.00 0.67 440.00 220.00 440.00 0.68 440.00 220.00 440.00 0.69 440.00 220.00 440.00 0.70 440.00 220.00 440.00 0.71 440.00 220.00 440.00 0.72 440.00 220.00 440.00 0.73 440.00 220.00 440.00 0.74 440.00 220.00 440.00 0.75 440.00 220.00 440.00 0.76 440.00 220.00 440.00 0.77 440.00 220.00 440.00 0.78 440.00 220.00 440.00 0.79 440.00 220.00 440.00 0.80 440.00 220.00 440.00 0.81 440.00 220.00 440.00 0.82 440.00 220.00 440.00 0.83 440.00 220.00 440.00 0.84 440.00 220.00 440.00 0.85 440.00 220.00 440.00 0.86 440.00 220.00 440.00 0.87 440.00 220.00 440.00 0.88 440.00 220.00 440.00 0.89 440.00 220.00 440.00 0.90 440.00 220.00 440.00 0.91 440.00 220.00 440.00 0.92 440.00 220.00 440.00 0.93 440.00 220.00 440.00 0.94 440.00 220.00 440.00 0.95 440.00 220.00 440.00 0.96 440.00 220.00 440.00 0.97 440.00 220.00 440.00 0.98 440.00 220.00 440.00 0.99 440.00 220.00 440.00 1.00 440.00 220.00 440.00 1.01 440.00 220.00 440.00 1.02 440.00 220.00 440.00 1.03 440.00 220.00 440.00 1.04 440.00 220.00 440.00 1.05 440.00 220.00 440.00 523.25 1.06 440.00 220.00 440.00 523.25 1.07 220.00 440.00 523.25 1.08 220.00 440.00 523.25 1.09 220.00 440.00 523.25 1.10 220.00 440.00 523.25 1.11 220.00 440.00 523.25 1.12 220.00 440.00 523.25 1.13 220.00 440.00 523.25 1.14 220.00 440.00 523.25 1.15 220.00 440.00 523.25 1.16 440.00 523.25 1.17 440.00 523.25 1.18 440.00 523.25 261.63 1.19 440.00 523.25 261.63 1.20 440.00 523.25 261.63 523.25 1.21 440.00 523.25 261.63 523.25 1.22 523.25 261.63 523.25 1.23 523.25 261.63 523.25 1.24 523.25 261.63 523.25 1.25 523.25 261.63 523.25 1.26 523.25 261.63 523.25 1.27 523.25 261.63 523.25 1.28 523.25 261.63 523.25 1.29 523.25 261.63 523.25 1.30 523.25 261.63 523.25 1.31 523.25 261.63 523.25 1.32 523.25 261.63 523.25 1.33 523.25 261.63 523.25 1.34 523.25 261.63 523.25 1.35 523.25 261.63 523.25 1.36 523.25 261.63 523.25 1.37 523.25 261.63 523.25 1.38 523.25 261.63 523.25 1.39 523.25 261.63 523.25 1.40 523.25 261.63 523.25 1.41 523.25 261.63 523.25 1.42 523.25 261.63 523.25 1.43 523.25 261.63 523.25 1.44 523.25 261.63 523.25 1.45 523.25 261.63 523.25 1.46 523.25 261.63 523.25 1.47 523.25 261.63 523.25 1.48 523.25 261.63 523.25 1.49 523.25 261.63 523.25 1.50 523.25 261.63 523.25 1.51 523.25 261.63 523.25 1.52 523.25 261.63 523.25 1.53 523.25 261.63 523.25 1.54 523.25 261.63 523.25 1.55 523.25 261.63 523.25 1.56 523.25 261.63 523.25 1.57 523.25 261.63 523.25 1.58 523.25 261.63 523.25 1.59 523.25 261.63 523.25 1.60 523.25 261.63 523.25 1.61 523.25 261.63 523.25 164.81 1.62 523.25 261.63 523.25 164.81 1.63 523.25 261.63 523.25 164.81 1.64 523.25 261.63 523.25 164.81 1.65 523.25 261.63 523.25 164.81 329.63 1.66 523.25 523.25 164.81 329.63 1.67 523.25 523.25 164.81 329.63 1.68 523.25 523.25 164.81 329.63 1.69 523.25 164.81 329.63 1.70 523.25 164.81 329.63 1.71 523.25 164.81 329.63 1.72 523.25 164.81 329.63 329.63 1.73 523.25 164.81 329.63 329.63 1.74 164.81 329.63 329.63 1.75 164.81 329.63 329.63 1.76 164.81 329.63 329.63 1.77 164.81 329.63 329.63 1.78 164.81 329.63 329.63 1.79 164.81 329.63 329.63 1.80 164.81 329.63 329.63 1.81 164.81 329.63 329.63 1.82 164.81 329.63 329.63 1.83 164.81 329.63 329.63 1.84 164.81 329.63 329.63 1.85 164.81 329.63 329.63 1.86 164.81 329.63 329.63 1.87 164.81 329.63 329.63 1.88 164.81 329.63 329.63 1.89 164.81 329.63 329.63 1.90 164.81 329.63 329.63 1.91 164.81 329.63 329.63 1.92 164.81 329.63 329.63 1.93 164.81 329.63 329.63 1.94 164.81 329.63 329.63 1.95 164.81 329.63 329.63 1.96 164.81 329.63 329.63 1.97 164.81 329.63 329.63 1.98 164.81 329.63 329.63 1.99 164.81 329.63 329.63 2.00 164.81 329.63 329.63 2.01 164.81 329.63 329.63 2.02 164.81 329.63 329.63 2.03 164.81 329.63 329.63 2.04 164.81 329.63 329.63 2.05 164.81 329.63 329.63 2.06 164.81 329.63 329.63 2.07 164.81 329.63 329.63 2.08 164.81 329.63 329.63 2.09 164.81 329.63 329.63 2.10 164.81 329.63 329.63 2.11 164.81 329.63 329.63 2.12 164.81 329.63 329.63 2.13 164.81 329.63 329.63 2.14 164.81 329.63 329.63 2.15 164.81 329.63 329.63 2.16 164.81 329.63 329.63 2.17 164.81 329.63 329.63 2.18 164.81 329.63 329.63 2.19 164.81 329.63 329.63 2.20 164.81 329.63 329.63 2.21 164.81 329.63 329.63 2.22 164.81 329.63 329.63 2.23 164.81 329.63 329.63 2.24 164.81 329.63 329.63 2.25 164.81 329.63 329.63 2.26 164.81 329.63 329.63 2.27 164.81 329.63 329.63 2.28 164.81 329.63 329.63 2.29 164.81 329.63 329.63 2.30 164.81 329.63 329.63 2.31 164.81 329.63 329.63 2.32 164.81 329.63 329.63 2.33 164.81 329.63 329.63 2.34 164.81 329.63 329.63 2.35 164.81 329.63 329.63 2.36 164.81 329.63 329.63 2.37 164.81 329.63 329.63 2.38 164.81 329.63 329.63 2.39 164.81 329.63 329.63 2.40 164.81 329.63 2.41 164.81 329.63 2.42 329.63 2.43 329.63 2.44 329.63 329.63 2.45 329.63 329.63 2.46 329.63 329.63 2.47 329.63 329.63 2.48 329.63 329.63 164.81 2.49 329.63 329.63 164.81 2.50 329.63 164.81 2.51 329.63 164.81 2.52 329.63 164.81 2.53 329.63 164.81 2.54 329.63 164.81 2.55 329.63 164.81 2.56 329.63 164.81 329.63 2.57 329.63 164.81 329.63 2.58 329.63 164.81 329.63 2.59 329.63 164.81 329.63 2.60 329.63 164.81 329.63 2.61 329.63 164.81 329.63 2.62 329.63 164.81 329.63 2.63 329.63 164.81 329.63 2.64 329.63 164.81 329.63 2.65 329.63 164.81 329.63 2.66 329.63 164.81 329.63 2.67 329.63 164.81 329.63 2.68 329.63 164.81 329.63 2.69 329.63 164.81 329.63 2.70 329.63 164.81 329.63 2.71 329.63 164.81 329.63 2.72 329.63 164.81 329.63 2.73 329.63 164.81 329.63 2.74 329.63 164.81 329.63 2.75 329.63 164.81 329.63 2.76 329.63 164.81 329.63 2.77 329.63 164.81 329.63 2.78 329.63 164.81 329.63 2.79 329.63 164.81 329.63 2.80 329.63 164.81 329.63 2.81 329.63 164.81 329.63 2.82 329.63 164.81 329.63 2.83 329.63 164.81 329.63 2.84 329.63 164.81 329.63 2.85 329.63 164.81 329.63 2.86 329.63 164.81 329.63 2.87 329.63 164.81 329.63 2.88 329.63 164.81 329.63 2.89 329.63 164.81 329.63 349.23 2.90 329.63 164.81 329.63 349.23 2.91 329.63 164.81 329.63 349.23 2.92 164.81 329.63 349.23 2.93 164.81 329.63 349.23 2.94 164.81 329.63 349.23 2.95 164.81 329.63 349.23 174.61 2.96 164.81 329.63 349.23 174.61 2.97 164.81 329.63 349.23 174.61 2.98 329.63 349.23 174.61 2.99 329.63 349.23 174.61 3.00 329.63 349.23 174.61 3.01 329.63 349.23 174.61 3.02 329.63 349.23 174.61 3.03 329.63 349.23 174.61 3.04 329.63 349.23 174.61 3.05 329.63 349.23 174.61 3.06 329.63 349.23 174.61 3.07 329.63 349.23 174.61 3.08 329.63 349.23 174.61 349.23 3.09 329.63 349.23 174.61 349.23 3.10 329.63 349.23 174.61 349.23 3.11 349.23 174.61 349.23 3.12 349.23 174.61 349.23 3.13 349.23 174.61 349.23 329.63 3.14 349.23 174.61 349.23 329.63 3.15 174.61 349.23 329.63 3.16 174.61 349.23 329.63 3.17 174.61 349.23 329.63 164.81 3.18 174.61 349.23 329.63 164.81 3.19 174.61 349.23 329.63 164.81 3.20 349.23 329.63 164.81 3.21 349.23 329.63 164.81 3.22 349.23 329.63 164.81 3.23 349.23 329.63 164.81 3.24 349.23 329.63 164.81 3.25 349.23 329.63 164.81 3.26 349.23 329.63 164.81 3.27 329.63 164.81 329.63 3.28 329.63 164.81 329.63 3.29 329.63 164.81 329.63 3.30 329.63 164.81 329.63 3.31 329.63 164.81 329.63 3.32 329.63 164.81 329.63 3.33 329.63 164.81 329.63 3.34 329.63 164.81 329.63 3.35 329.63 164.81 329.63 146.83 3.36 329.63 164.81 329.63 146.83 3.37 329.63 329.63 146.83 3.38 329.63 329.63 146.83 293.66 3.39 329.63 329.63 146.83 293.66 3.40 329.63 329.63 146.83 293.66 3.41 329.63 146.83 293.66 3.42 329.63 146.83 293.66 3.43 329.63 146.83 293.66 3.44 329.63 146.83 293.66 3.45 329.63 146.83 293.66 293.66 3.46 329.63 146.83 293.66 293.66 3.47 146.83 293.66 293.66 3.48 146.83 293.66 293.66 3.49 146.83 293.66 293.66 3.50 146.83 293.66 293.66 3.51 146.83 293.66 293.66 3.52 146.83 293.66 293.66 3.53 146.83 293.66 293.66 130.81 3.54 146.83 293.66 293.66 130.81 3.55 293.66 293.66 130.81 3.56 293.66 293.66 130.81 3.57 293.66 293.66 130.81 3.58 293.66 293.66 130.81 3.59 293.66 293.66 130.81 261.63 3.60 293.66 293.66 130.81 261.63 3.61 293.66 293.66 130.81 261.63 261.63 3.62 293.66 130.81 261.63 261.63 3.63 293.66 130.81 261.63 261.63 3.64 130.81 261.63 261.63 3.65 130.81 261.63 261.63 3.66 130.81 261.63 261.63 3.67 130.81 261.63 261.63 3.68 130.81 261.63 261.63 3.69 130.81 261.63 261.63 3.70 130.81 261.63 261.63 3.71 130.81 261.63 261.63 123.47 3.72 130.81 261.63 261.63 123.47 3.73 261.63 261.63 123.47 3.74 261.63 261.63 123.47 3.75 261.63 261.63 123.47 3.76 261.63 261.63 123.47 3.77 261.63 261.63 123.47 3.78 261.63 261.63 123.47 3.79 261.63 261.63 123.47 246.94 3.80 261.63 123.47 246.94 246.94 3.81 123.47 246.94 246.94 3.82 123.47 246.94 246.94 3.83 123.47 246.94 246.94 3.84 123.47 246.94 246.94 3.85 123.47 246.94 246.94 3.86 123.47 246.94 246.94 3.87 123.47 246.94 246.94 3.88 123.47 246.94 246.94 3.89 123.47 246.94 246.94 3.90 123.47 246.94 246.94 3.91 123.47 246.94 246.94 110.00 3.92 246.94 246.94 110.00 3.93 246.94 246.94 110.00 3.94 246.94 246.94 110.00 3.95 246.94 246.94 110.00 3.96 246.94 246.94 110.00 3.97 246.94 246.94 110.00 3.98 246.94 246.94 110.00 3.99 246.94 246.94 110.00 220.00 4.00 246.94 246.94 110.00 220.00 4.01 246.94 246.94 110.00 220.00 220.00 4.02 246.94 110.00 220.00 220.00 4.03 246.94 110.00 220.00 220.00 4.04 110.00 220.00 220.00 4.05 110.00 220.00 220.00 4.06 220.00 220.00 4.07 220.00 220.00 4.08 220.00 220.00 4.09 220.00 220.00 4.10 220.00 220.00 4.11 220.00 220.00 4.12 220.00 4.13 220.00 110.00 4.14 220.00 110.00 4.15 220.00 110.00 4.16 220.00 110.00 4.17 110.00 4.18 110.00 4.19 110.00 4.20 110.00 220.00 4.21 110.00 220.00 4.22 110.00 220.00 4.23 110.00 220.00 220.00 4.24 110.00 220.00 220.00 4.25 110.00 220.00 220.00 4.26 110.00 220.00 220.00 4.27 110.00 220.00 220.00 4.28 110.00 220.00 220.00 4.29 110.00 220.00 220.00 4.30 110.00 220.00 220.00 4.31 110.00 220.00 220.00 4.32 110.00 220.00 220.00 4.33 110.00 220.00 220.00 4.34 110.00 220.00 220.00 4.35 110.00 220.00 220.00 4.36 110.00 220.00 220.00 4.37 110.00 220.00 220.00 4.38 110.00 220.00 220.00 4.39 110.00 220.00 220.00 4.40 110.00 220.00 220.00 4.41 110.00 220.00 220.00 4.42 110.00 220.00 220.00 4.43 110.00 220.00 220.00 4.44 110.00 220.00 220.00 4.45 110.00 220.00 220.00 4.46 110.00 220.00 220.00 4.47 110.00 220.00 220.00 4.48 110.00 220.00 220.00 4.49 110.00 220.00 220.00 4.50 110.00 220.00 220.00 4.51 110.00 220.00 220.00 4.52 110.00 220.00 220.00 4.53 110.00 220.00 220.00 4.54 110.00 220.00 220.00 4.55 110.00 220.00 220.00 4.56 110.00 220.00 220.00 4.57 110.00 220.00 220.00 4.58 110.00 220.00 220.00 4.59 110.00 220.00 220.00 4.60 110.00 220.00 220.00 4.61 110.00 220.00 220.00 4.62 110.00 220.00 220.00 4.63 110.00 220.00 220.00 4.64 110.00 220.00 220.00 4.65 110.00 220.00 220.00 4.66 110.00 220.00 220.00 4.67 110.00 220.00 220.00 4.68 110.00 220.00 220.00 4.69 110.00 220.00 220.00 4.70 110.00 220.00 220.00 4.71 110.00 220.00 220.00 4.72 110.00 220.00 220.00 4.73 110.00 220.00 220.00 4.74 110.00 220.00 220.00 4.75 110.00 220.00 220.00 4.76 110.00 220.00 220.00 4.77 110.00 220.00 220.00 4.78 110.00 220.00 220.00 4.79 110.00 220.00 220.00 4.80 110.00 220.00 220.00 4.81 110.00 220.00 220.00 4.82 110.00 220.00 220.00 4.83 110.00 220.00 220.00 4.84 110.00 220.00 220.00 4.85 110.00 220.00 220.00 4.86 110.00 220.00 220.00 4.87 110.00 220.00 220.00 4.88 110.00 220.00 220.00 4.89 110.00 220.00 220.00 4.90 110.00 220.00 220.00 4.91 110.00 220.00 220.00 4.92 110.00 220.00 220.00 4.93 110.00 220.00 220.00 4.94 110.00 220.00 220.00 4.95 110.00 220.00 220.00 4.96 110.00 220.00 220.00 4.97 110.00 220.00 220.00 4.98 110.00 220.00 220.00 4.99 110.00 220.00 220.00 5.00 110.00 220.00 220.00 5.01 110.00 220.00 220.00 5.02 110.00 220.00 220.00 103.83 5.03 110.00 220.00 220.00 103.83 5.04 110.00 220.00 220.00 103.83 5.05 110.00 220.00 220.00 103.83 5.06 110.00 220.00 220.00 103.83 207.65 5.07 220.00 220.00 103.83 207.65 207.65 5.08 220.00 103.83 207.65 207.65 5.09 220.00 103.83 207.65 207.65 5.10 220.00 103.83 207.65 207.65 5.11 103.83 207.65 207.65 5.12 103.83 207.65 207.65 5.13 103.83 207.65 207.65 5.14 103.83 207.65 207.65 5.15 103.83 207.65 207.65 5.16 103.83 207.65 207.65 5.17 103.83 207.65 207.65 5.18 103.83 207.65 207.65 5.19 103.83 207.65 207.65 5.20 103.83 207.65 207.65 5.21 103.83 207.65 207.65 5.22 103.83 207.65 207.65 5.23 103.83 207.65 207.65 5.24 103.83 207.65 207.65 5.25 103.83 207.65 207.65 5.26 103.83 207.65 207.65 5.27 103.83 207.65 207.65 5.28 103.83 207.65 207.65 5.29 103.83 207.65 207.65 5.30 103.83 207.65 207.65 5.31 103.83 207.65 207.65 5.32 103.83 207.65 207.65 5.33 103.83 207.65 207.65 5.34 103.83 207.65 207.65 5.35 103.83 207.65 207.65 5.36 103.83 207.65 207.65 5.37 103.83 207.65 207.65 5.38 103.83 207.65 207.65 5.39 103.83 207.65 207.65 5.40 103.83 207.65 207.65 5.41 103.83 207.65 207.65 5.42 103.83 207.65 207.65 5.43 103.83 207.65 207.65 5.44 103.83 207.65 207.65 5.45 103.83 207.65 207.65 5.46 103.83 207.65 207.65 5.47 103.83 207.65 207.65 5.48 103.83 207.65 5.49 103.83 207.65 5.50 207.65 5.51 207.65 164.81 5.52 164.81 5.53 164.81 5.54 164.81 329.63 5.55 164.81 329.63 5.56 164.81 329.63 5.57 164.81 329.63 82.41 5.58 164.81 329.63 82.41 5.59 164.81 329.63 82.41 5.60 164.81 329.63 82.41 82.41 5.61 164.81 329.63 82.41 82.41 5.62 164.81 329.63 82.41 82.41 5.63 164.81 329.63 82.41 82.41 5.64 164.81 329.63 82.41 82.41 5.65 164.81 329.63 82.41 82.41 5.66 164.81 329.63 82.41 82.41 5.67 164.81 329.63 82.41 82.41 5.68 164.81 329.63 82.41 82.41 5.69 164.81 329.63 82.41 82.41 5.70 164.81 329.63 82.41 82.41 5.71 164.81 329.63 82.41 82.41 5.72 164.81 329.63 82.41 82.41 5.73 164.81 329.63 82.41 82.41 5.74 164.81 329.63 82.41 82.41 5.75 164.81 329.63 82.41 82.41 5.76 164.81 329.63 82.41 82.41 5.77 164.81 329.63 82.41 82.41 5.78 164.81 329.63 82.41 82.41 5.79 164.81 329.63 82.41 82.41 5.80 164.81 329.63 82.41 82.41 5.81 164.81 329.63 82.41 82.41 5.82 164.81 329.63 82.41 82.41 5.83 164.81 329.63 82.41 82.41 5.84 164.81 329.63 82.41 82.41 5.85 164.81 329.63 82.41 82.41 5.86 164.81 329.63 82.41 82.41 5.87 164.81 329.63 82.41 82.41 164.81 5.88 164.81 329.63 82.41 82.41 164.81 5.89 164.81 329.63 82.41 82.41 164.81 5.90 164.81 329.63 82.41 82.41 164.81 5.91 164.81 329.63 82.41 82.41 164.81 5.92 164.81 329.63 82.41 82.41 164.81 5.93 164.81 329.63 82.41 82.41 164.81 5.94 164.81 329.63 82.41 82.41 164.81 5.95 164.81 329.63 82.41 82.41 164.81 5.96 164.81 329.63 82.41 82.41 164.81 5.97 164.81 329.63 82.41 82.41 164.81 5.98 164.81 329.63 82.41 82.41 164.81 5.99 164.81 329.63 82.41 82.41 164.81 6.00 164.81 329.63 82.41 82.41 164.81 6.01 164.81 329.63 82.41 82.41 164.81 6.02 164.81 329.63 82.41 82.41 164.81 6.03 164.81 329.63 82.41 82.41 164.81 6.04 164.81 329.63 82.41 82.41 164.81 659.26 6.05 164.81 329.63 82.41 659.26 207.65 6.06 164.81 329.63 82.41 659.26 207.65 6.07 164.81 329.63 82.41 659.26 207.65 6.08 164.81 329.63 82.41 659.26 207.65 6.09 164.81 329.63 82.41 659.26 207.65 6.10 164.81 329.63 82.41 659.26 207.65 6.11 164.81 329.63 82.41 659.26 207.65 6.12 164.81 329.63 82.41 659.26 207.65 6.13 164.81 329.63 659.26 207.65 6.14 164.81 329.63 659.26 207.65 6.15 164.81 329.63 659.26 207.65 6.16 164.81 329.63 659.26 207.65 6.17 164.81 329.63 659.26 207.65 6.18 164.81 329.63 659.26 207.65 6.19 164.81 329.63 659.26 207.65 6.20 164.81 329.63 659.26 207.65 6.21 164.81 329.63 659.26 207.65 6.22 164.81 329.63 659.26 207.65 6.23 164.81 329.63 659.26 207.65 6.24 164.81 329.63 659.26 207.65 6.25 164.81 329.63 659.26 207.65 329.63 6.26 164.81 329.63 659.26 329.63 6.27 164.81 329.63 659.26 329.63 6.28 164.81 329.63 659.26 329.63 6.29 164.81 329.63 659.26 329.63 6.30 164.81 329.63 659.26 329.63 6.31 164.81 329.63 659.26 329.63 6.32 164.81 329.63 659.26 329.63 6.33 164.81 329.63 659.26 329.63 6.34 164.81 329.63 659.26 329.63 6.35 164.81 329.63 659.26 329.63 6.36 164.81 329.63 659.26 329.63 6.37 164.81 329.63 659.26 329.63 6.38 164.81 329.63 659.26 329.63 6.39 164.81 329.63 659.26 329.63 6.40 164.81 329.63 659.26 329.63 6.41 164.81 329.63 659.26 329.63 6.42 164.81 329.63 659.26 329.63 6.43 164.81 329.63 659.26 329.63 6.44 164.81 329.63 659.26 329.63 6.45 164.81 329.63 329.63 415.30 164.81 6.46 164.81 329.63 415.30 164.81 6.47 164.81 329.63 415.30 164.81 6.48 164.81 329.63 415.30 164.81 6.49 164.81 329.63 415.30 164.81 82.41 6.50 164.81 329.63 415.30 164.81 82.41 6.51 164.81 329.63 415.30 164.81 82.41 6.52 164.81 329.63 415.30 164.81 82.41 6.53 164.81 329.63 415.30 164.81 82.41 6.54 164.81 329.63 415.30 164.81 82.41 6.55 164.81 329.63 415.30 164.81 82.41 6.56 164.81 329.63 415.30 164.81 82.41 6.57 164.81 329.63 415.30 164.81 82.41 6.58 164.81 329.63 415.30 164.81 82.41 6.59 164.81 329.63 415.30 164.81 82.41 6.60 164.81 329.63 415.30 164.81 82.41 6.61 164.81 329.63 415.30 164.81 82.41 6.62 164.81 329.63 415.30 164.81 82.41 6.63 164.81 329.63 415.30 82.41 6.64 164.81 329.63 415.30 82.41 329.63 6.65 164.81 329.63 415.30 82.41 329.63 6.66 164.81 329.63 415.30 82.41 329.63 6.67 164.81 329.63 415.30 82.41 329.63 6.68 164.81 329.63 415.30 82.41 329.63 6.69 164.81 329.63 415.30 82.41 329.63 6.70 164.81 329.63 415.30 82.41 329.63 6.71 164.81 329.63 415.30 82.41 329.63 6.72 164.81 329.63 415.30 82.41 329.63 6.73 164.81 329.63 415.30 82.41 329.63 6.74 164.81 329.63 415.30 82.41 329.63 6.75 164.81 329.63 415.30 82.41 329.63 6.76 164.81 329.63 415.30 82.41 329.63 6.77 164.81 329.63 415.30 82.41 329.63 6.78 164.81 329.63 415.30 82.41 329.63 6.79 164.81 329.63 415.30 82.41 329.63 6.80 164.81 329.63 415.30 82.41 329.63 92.50 6.81 164.81 329.63 415.30 82.41 329.63 92.50 6.82 164.81 329.63 415.30 82.41 92.50 92.50 6.83 164.81 329.63 415.30 82.41 92.50 92.50 6.84 164.81 329.63 415.30 82.41 92.50 92.50 6.85 164.81 329.63 415.30 92.50 92.50 6.86 164.81 329.63 92.50 92.50 6.87 164.81 329.63 92.50 92.50 6.88 164.81 329.63 92.50 92.50 6.89 164.81 329.63 92.50 92.50 6.90 164.81 329.63 92.50 92.50 185.00 6.91 164.81 329.63 92.50 92.50 185.00 6.92 164.81 329.63 92.50 92.50 185.00 6.93 164.81 329.63 92.50 92.50 185.00 6.94 164.81 329.63 92.50 92.50 185.00 6.95 329.63 92.50 92.50 185.00 6.96 329.63 92.50 92.50 185.00 6.97 329.63 92.50 92.50 185.00 6.98 329.63 92.50 92.50 185.00 6.99 329.63 92.50 92.50 185.00 7.00 329.63 92.50 92.50 185.00 164.81 7.01 329.63 92.50 92.50 185.00 164.81 7.02 329.63 92.50 92.50 185.00 164.81 7.03 329.63 92.50 92.50 185.00 164.81 7.04 329.63 92.50 92.50 185.00 164.81 7.05 329.63 92.50 92.50 185.00 164.81 7.06 329.63 92.50 92.50 185.00 164.81 7.07 329.63 92.50 92.50 185.00 164.81 7.08 329.63 92.50 92.50 185.00 164.81 7.09 329.63 92.50 92.50 185.00 164.81 7.10 329.63 92.50 92.50 185.00 164.81 7.11 329.63 92.50 92.50 185.00 164.81 7.12 329.63 92.50 92.50 185.00 164.81 7.13 329.63 92.50 92.50 185.00 164.81 7.14 329.63 92.50 92.50 185.00 164.81 7.15 329.63 92.50 92.50 185.00 164.81 7.16 329.63 92.50 92.50 185.00 164.81 7.17 329.63 92.50 92.50 185.00 164.81 7.18 329.63 92.50 92.50 185.00 164.81 659.26 7.19 329.63 92.50 92.50 185.00 164.81 659.26 220.00 7.20 329.63 92.50 92.50 185.00 164.81 659.26 220.00 7.21 329.63 92.50 92.50 185.00 164.81 659.26 220.00 7.22 329.63 92.50 92.50 185.00 164.81 659.26 220.00 7.23 329.63 92.50 92.50 185.00 659.26 220.00 7.24 329.63 92.50 185.00 659.26 220.00 7.25 329.63 92.50 185.00 659.26 220.00 7.26 329.63 92.50 185.00 659.26 220.00 7.27 329.63 92.50 185.00 659.26 220.00 7.28 329.63 92.50 185.00 659.26 220.00 7.29 329.63 92.50 185.00 659.26 220.00 7.30 329.63 92.50 185.00 659.26 220.00 7.31 329.63 92.50 185.00 659.26 220.00 7.32 329.63 92.50 185.00 659.26 220.00 7.33 329.63 92.50 185.00 659.26 220.00 7.34 329.63 92.50 185.00 659.26 220.00 7.35 329.63 185.00 659.26 220.00 7.36 329.63 185.00 659.26 220.00 7.37 329.63 185.00 659.26 220.00 7.38 329.63 185.00 659.26 220.00 7.39 329.63 185.00 659.26 220.00 7.40 329.63 185.00 659.26 220.00 329.63 7.41 329.63 185.00 659.26 220.00 329.63 7.42 329.63 185.00 659.26 329.63 7.43 329.63 185.00 659.26 329.63 7.44 329.63 185.00 659.26 329.63 7.45 329.63 185.00 659.26 329.63 7.46 329.63 185.00 659.26 329.63 7.47 329.63 185.00 659.26 329.63 7.48 329.63 185.00 659.26 329.63 7.49 329.63 185.00 659.26 329.63 7.50 329.63 185.00 659.26 329.63 7.51 329.63 185.00 659.26 329.63 7.52 329.63 185.00 659.26 329.63 7.53 329.63 185.00 659.26 329.63 7.54 329.63 185.00 659.26 329.63 7.55 329.63 185.00 659.26 329.63 7.56 329.63 185.00 659.26 329.63 7.57 329.63 185.00 329.63 440.00 92.50 7.58 329.63 185.00 329.63 440.00 92.50 7.59 329.63 185.00 329.63 440.00 92.50 164.81 7.60 329.63 185.00 329.63 440.00 92.50 164.81 7.61 329.63 185.00 329.63 440.00 92.50 164.81 7.62 329.63 185.00 440.00 92.50 164.81 7.63 329.63 185.00 440.00 92.50 164.81 7.64 329.63 185.00 440.00 92.50 164.81 7.65 329.63 185.00 440.00 92.50 164.81 7.66 329.63 185.00 440.00 92.50 164.81 7.67 329.63 185.00 440.00 92.50 164.81 7.68 329.63 185.00 440.00 92.50 164.81 7.69 329.63 185.00 440.00 92.50 164.81 7.70 329.63 185.00 440.00 92.50 164.81 7.71 329.63 185.00 440.00 92.50 164.81 7.72 329.63 185.00 440.00 92.50 164.81 7.73 329.63 185.00 440.00 92.50 164.81 7.74 329.63 185.00 440.00 92.50 164.81 7.75 329.63 185.00 440.00 92.50 164.81 7.76 329.63 185.00 440.00 92.50 164.81 329.63 7.77 329.63 185.00 440.00 92.50 164.81 329.63 7.78 329.63 185.00 440.00 92.50 164.81 329.63 7.79 329.63 185.00 440.00 92.50 164.81 329.63 7.80 329.63 185.00 440.00 92.50 164.81 329.63 7.81 329.63 185.00 440.00 92.50 329.63 7.82 329.63 185.00 440.00 92.50 329.63 7.83 329.63 185.00 440.00 92.50 329.63 7.84 329.63 185.00 440.00 92.50 329.63 7.85 329.63 185.00 440.00 92.50 329.63 7.86 329.63 185.00 440.00 92.50 329.63 7.87 329.63 185.00 440.00 92.50 329.63 7.88 329.63 185.00 440.00 92.50 329.63 7.89 329.63 185.00 440.00 92.50 329.63 7.90 329.63 185.00 440.00 92.50 329.63 7.91 329.63 185.00 440.00 92.50 329.63 7.92 329.63 185.00 440.00 92.50 329.63 7.93 329.63 185.00 440.00 92.50 329.63 7.94 329.63 185.00 440.00 92.50 329.63 103.83 7.95 329.63 185.00 440.00 92.50 103.83 7.96 329.63 185.00 440.00 92.50 103.83 7.97 329.63 185.00 440.00 103.83 7.98 329.63 185.00 440.00 103.83 7.99 329.63 185.00 103.83 8.00 329.63 185.00 103.83 8.01 329.63 185.00 103.83 8.02 329.63 185.00 103.83 8.03 329.63 185.00 103.83 8.04 329.63 185.00 103.83 103.83 8.05 329.63 185.00 103.83 103.83 8.06 329.63 185.00 103.83 103.83 8.07 329.63 185.00 103.83 103.83 8.08 329.63 185.00 103.83 103.83 8.09 329.63 185.00 103.83 103.83 8.10 329.63 185.00 103.83 103.83 8.11 329.63 185.00 103.83 103.83 8.12 329.63 185.00 103.83 103.83 8.13 329.63 185.00 103.83 103.83 8.14 329.63 185.00 103.83 103.83 164.81 8.15 329.63 185.00 103.83 103.83 164.81 8.16 329.63 185.00 103.83 103.83 164.81 8.17 329.63 185.00 103.83 103.83 164.81 8.18 329.63 185.00 103.83 103.83 164.81 207.65 8.19 329.63 185.00 103.83 103.83 164.81 207.65 8.20 329.63 185.00 103.83 103.83 164.81 207.65 8.21 329.63 185.00 103.83 103.83 164.81 207.65 8.22 329.63 103.83 103.83 164.81 207.65 8.23 329.63 103.83 103.83 164.81 207.65 8.24 329.63 103.83 103.83 164.81 207.65 8.25 329.63 103.83 103.83 164.81 207.65 8.26 329.63 103.83 103.83 164.81 207.65 8.27 329.63 103.83 103.83 164.81 207.65 8.28 329.63 103.83 103.83 164.81 207.65 8.29 329.63 103.83 103.83 164.81 207.65 8.30 329.63 103.83 103.83 164.81 207.65 8.31 329.63 103.83 103.83 164.81 207.65 659.26 8.32 329.63 103.83 103.83 164.81 207.65 659.26 8.33 329.63 103.83 103.83 164.81 207.65 659.26 246.94 8.34 329.63 103.83 103.83 164.81 207.65 659.26 246.94 8.35 329.63 103.83 103.83 164.81 207.65 659.26 246.94 8.36 329.63 103.83 103.83 164.81 207.65 659.26 246.94 8.37 329.63 103.83 103.83 207.65 659.26 246.94 8.38 329.63 103.83 103.83 207.65 659.26 246.94 8.39 329.63 103.83 207.65 659.26 246.94 8.40 329.63 103.83 207.65 659.26 246.94 8.41 329.63 103.83 207.65 659.26 246.94 8.42 329.63 103.83 207.65 659.26 246.94 8.43 329.63 103.83 207.65 659.26 246.94 8.44 329.63 103.83 207.65 659.26 246.94 8.45 329.63 103.83 207.65 659.26 246.94 8.46 329.63 207.65 659.26 246.94 8.47 329.63 207.65 659.26 246.94 8.48 329.63 207.65 659.26 246.94 8.49 329.63 207.65 659.26 246.94 8.50 329.63 207.65 659.26 246.94 8.51 329.63 207.65 659.26 246.94 8.52 329.63 207.65 659.26 246.94 8.53 329.63 207.65 659.26 246.94 329.63 8.54 329.63 207.65 659.26 246.94 329.63 8.55 329.63 207.65 659.26 246.94 329.63 8.56 329.63 207.65 659.26 246.94 329.63 8.57 329.63 207.65 659.26 329.63 8.58 329.63 207.65 659.26 329.63 8.59 329.63 207.65 659.26 329.63 8.60 329.63 207.65 659.26 329.63 8.61 329.63 207.65 659.26 329.63 8.62 329.63 207.65 659.26 329.63 8.63 329.63 207.65 659.26 329.63 8.64 329.63 207.65 659.26 329.63 8.65 329.63 207.65 659.26 329.63 8.66 329.63 207.65 659.26 329.63 8.67 329.63 207.65 659.26 329.63 8.68 329.63 207.65 659.26 329.63 103.83 8.69 329.63 207.65 659.26 329.63 103.83 8.70 329.63 207.65 659.26 329.63 103.83 8.71 329.63 207.65 659.26 329.63 103.83 493.88 8.72 329.63 207.65 329.63 103.83 493.88 164.81 8.73 329.63 207.65 103.83 493.88 164.81 8.74 329.63 207.65 103.83 493.88 164.81 8.75 329.63 207.65 103.83 493.88 164.81 8.76 329.63 207.65 103.83 493.88 164.81 8.77 329.63 207.65 103.83 493.88 164.81 8.78 329.63 207.65 103.83 493.88 164.81 8.79 329.63 207.65 103.83 493.88 164.81 8.80 329.63 207.65 103.83 493.88 164.81 8.81 329.63 207.65 103.83 493.88 164.81 8.82 329.63 207.65 103.83 493.88 164.81 8.83 329.63 207.65 103.83 493.88 164.81 8.84 329.63 207.65 103.83 493.88 164.81 8.85 329.63 207.65 103.83 493.88 164.81 8.86 329.63 207.65 103.83 493.88 164.81 8.87 329.63 207.65 103.83 493.88 164.81 8.88 329.63 207.65 103.83 493.88 164.81 8.89 329.63 207.65 103.83 493.88 164.81 8.90 329.63 207.65 103.83 493.88 164.81 329.63 8.91 329.63 207.65 103.83 493.88 164.81 329.63 8.92 329.63 207.65 103.83 493.88 164.81 329.63 8.93 329.63 207.65 103.83 493.88 164.81 329.63 8.94 329.63 207.65 103.83 493.88 164.81 329.63 8.95 329.63 207.65 103.83 493.88 329.63 8.96 329.63 207.65 103.83 493.88 329.63 8.97 329.63 207.65 103.83 493.88 329.63 8.98 329.63 207.65 103.83 493.88 329.63 8.99 329.63 207.65 103.83 493.88 329.63 9.00 329.63 207.65 103.83 493.88 329.63 9.01 329.63 207.65 103.83 493.88 329.63 9.02 329.63 207.65 103.83 493.88 329.63 9.03 329.63 207.65 103.83 493.88 329.63 9.04 329.63 207.65 103.83 493.88 329.63 9.05 329.63 207.65 103.83 493.88 329.63 9.06 329.63 207.65 103.83 493.88 329.63 9.07 329.63 207.65 103.83 493.88 329.63 9.08 329.63 207.65 103.83 493.88 329.63 9.09 329.63 207.65 103.83 493.88 329.63 523.25 110.00 9.10 329.63 207.65 103.83 493.88 329.63 523.25 110.00 9.11 329.63 207.65 493.88 523.25 110.00 9.12 329.63 207.65 523.25 110.00 9.13 329.63 207.65 523.25 110.00 9.14 329.63 207.65 523.25 110.00 9.15 329.63 207.65 523.25 110.00 110.00 9.16 329.63 207.65 523.25 110.00 110.00 9.17 329.63 207.65 523.25 110.00 110.00 9.18 329.63 207.65 523.25 110.00 110.00 9.19 329.63 207.65 523.25 110.00 110.00 9.20 329.63 207.65 523.25 110.00 110.00 9.21 329.63 207.65 523.25 110.00 110.00 9.22 329.63 207.65 523.25 110.00 110.00 9.23 329.63 207.65 523.25 110.00 110.00 9.24 329.63 207.65 523.25 110.00 110.00 220.00 9.25 329.63 207.65 523.25 110.00 110.00 220.00 9.26 329.63 207.65 523.25 110.00 110.00 220.00 9.27 329.63 523.25 110.00 110.00 220.00 9.28 329.63 523.25 110.00 110.00 220.00 9.29 329.63 523.25 110.00 110.00 220.00 9.30 329.63 523.25 110.00 110.00 220.00 164.81 9.31 329.63 523.25 110.00 110.00 220.00 164.81 9.32 329.63 523.25 110.00 110.00 220.00 164.81 9.33 329.63 523.25 110.00 110.00 220.00 164.81 9.34 329.63 523.25 110.00 110.00 220.00 164.81 9.35 329.63 523.25 110.00 110.00 220.00 164.81 9.36 329.63 523.25 110.00 110.00 220.00 164.81 9.37 329.63 523.25 110.00 110.00 220.00 164.81 9.38 329.63 523.25 110.00 110.00 220.00 164.81 9.39 329.63 523.25 110.00 110.00 220.00 164.81 9.40 329.63 523.25 110.00 110.00 220.00 164.81 9.41 329.63 523.25 110.00 110.00 220.00 164.81 9.42 329.63 523.25 110.00 110.00 220.00 164.81 9.43 329.63 523.25 110.00 110.00 220.00 164.81 9.44 329.63 523.25 110.00 110.00 220.00 164.81 9.45 329.63 523.25 110.00 110.00 220.00 164.81 9.46 329.63 523.25 110.00 110.00 220.00 164.81 9.47 329.63 523.25 110.00 110.00 220.00 164.81 9.48 329.63 523.25 110.00 110.00 220.00 164.81 9.49 329.63 523.25 110.00 110.00 220.00 164.81 9.50 329.63 523.25 110.00 110.00 220.00 164.81 261.63 9.51 329.63 523.25 110.00 110.00 220.00 164.81 261.63 9.52 329.63 523.25 110.00 110.00 220.00 164.81 261.63 9.53 329.63 523.25 110.00 110.00 220.00 261.63 9.54 329.63 523.25 110.00 110.00 220.00 261.63 9.55 329.63 523.25 110.00 110.00 220.00 261.63 9.56 329.63 523.25 110.00 110.00 220.00 261.63 9.57 329.63 523.25 110.00 110.00 220.00 261.63 9.58 329.63 523.25 110.00 110.00 220.00 261.63 9.59 329.63 523.25 110.00 110.00 220.00 261.63 9.60 329.63 523.25 110.00 220.00 261.63 9.61 329.63 523.25 110.00 220.00 261.63 9.62 329.63 523.25 110.00 220.00 261.63 9.63 329.63 523.25 110.00 220.00 261.63 9.64 329.63 523.25 110.00 220.00 261.63 9.65 329.63 523.25 220.00 261.63 9.66 329.63 523.25 220.00 261.63 9.67 329.63 523.25 220.00 261.63 9.68 329.63 523.25 220.00 261.63 9.69 329.63 523.25 220.00 261.63 9.70 329.63 523.25 220.00 261.63 9.71 329.63 523.25 220.00 261.63 329.63 9.72 329.63 523.25 220.00 261.63 329.63 9.73 329.63 523.25 220.00 261.63 329.63 9.74 329.63 523.25 220.00 329.63 9.75 329.63 523.25 220.00 329.63 9.76 329.63 523.25 220.00 329.63 9.77 329.63 523.25 220.00 329.63 9.78 329.63 523.25 220.00 329.63 9.79 329.63 523.25 220.00 329.63 9.80 329.63 523.25 220.00 329.63 246.94 9.81 329.63 523.25 220.00 329.63 246.94 9.82 329.63 523.25 329.63 246.94 9.83 329.63 523.25 329.63 246.94 9.84 329.63 523.25 329.63 246.94 9.85 329.63 523.25 329.63 246.94 9.86 329.63 523.25 329.63 246.94 9.87 329.63 523.25 329.63 246.94 9.88 329.63 523.25 329.63 246.94 9.89 329.63 523.25 246.94 164.81 9.90 329.63 523.25 246.94 164.81 9.91 329.63 523.25 246.94 164.81 9.92 329.63 523.25 246.94 164.81 9.93 329.63 523.25 246.94 164.81 9.94 329.63 523.25 246.94 164.81 9.95 329.63 523.25 246.94 164.81 9.96 329.63 246.94 164.81 9.97 329.63 246.94 164.81 9.98 329.63 246.94 164.81 9.99 329.63 246.94 164.81 10.00 329.63 246.94 164.81 10.01 329.63 246.94 164.81 10.02 246.94 164.81 10.03 246.94 164.81 10.04 246.94 164.81 10.05 246.94 164.81 261.63 10.06 246.94 164.81 261.63 10.07 261.63 10.08 261.63 10.09 261.63 329.63 10.10 261.63 329.63 10.11 261.63 329.63 10.12 261.63 329.63 10.13 261.63 329.63 10.14 261.63 329.63 10.15 261.63 329.63 10.16 261.63 329.63 10.17 261.63 329.63 10.18 261.63 329.63 10.19 261.63 329.63 10.20 261.63 329.63 10.21 261.63 329.63 10.22 261.63 10.23 261.63 10.24 261.63 10.25 261.63 10.26 261.63 10.27 261.63 10.28 261.63 10.29 261.63 10.30 261.63 87.31 10.31 261.63 87.31 10.32 261.63 87.31 10.33 261.63 87.31 349.23 10.34 261.63 87.31 349.23 10.35 261.63 87.31 349.23 174.61 10.36 261.63 87.31 349.23 174.61 10.37 261.63 87.31 349.23 174.61 10.38 261.63 87.31 349.23 174.61 10.39 261.63 87.31 349.23 174.61 10.40 261.63 87.31 349.23 174.61 10.41 261.63 87.31 349.23 174.61 10.42 261.63 87.31 349.23 174.61 10.43 261.63 87.31 349.23 174.61 10.44 261.63 87.31 349.23 174.61 174.61 10.45 261.63 87.31 349.23 174.61 174.61 10.46 261.63 87.31 349.23 174.61 174.61 10.47 261.63 87.31 349.23 174.61 174.61 10.48 261.63 87.31 349.23 174.61 174.61 10.49 261.63 87.31 349.23 174.61 174.61 87.31 10.50 87.31 349.23 174.61 174.61 87.31 87.31 10.51 87.31 349.23 174.61 174.61 87.31 87.31 10.52 87.31 349.23 174.61 174.61 87.31 87.31 10.53 87.31 349.23 174.61 174.61 87.31 87.31 10.54 87.31 349.23 174.61 174.61 87.31 87.31 10.55 87.31 349.23 174.61 174.61 87.31 87.31 10.56 87.31 349.23 174.61 174.61 87.31 87.31 10.57 87.31 349.23 174.61 174.61 87.31 87.31 10.58 87.31 349.23 174.61 174.61 87.31 87.31 10.59 87.31 349.23 174.61 174.61 87.31 87.31 10.60 87.31 349.23 174.61 174.61 87.31 87.31 10.61 87.31 349.23 174.61 174.61 87.31 87.31 10.62 87.31 349.23 174.61 174.61 87.31 87.31 10.63 87.31 349.23 174.61 174.61 87.31 87.31 10.64 87.31 349.23 174.61 174.61 87.31 87.31 10.65 87.31 349.23 174.61 174.61 87.31 87.31 10.66 87.31 349.23 174.61 174.61 87.31 87.31 10.67 87.31 349.23 174.61 174.61 87.31 87.31 10.68 87.31 349.23 174.61 174.61 87.31 87.31 10.69 87.31 349.23 174.61 174.61 87.31 87.31 10.70 87.31 349.23 174.61 174.61 87.31 87.31 10.71 87.31 349.23 174.61 174.61 87.31 87.31 10.72 87.31 349.23 174.61 174.61 87.31 87.31 10.73 87.31 349.23 174.61 174.61 87.31 87.31 10.74 87.31 349.23 174.61 174.61 87.31 87.31 10.75 87.31 349.23 174.61 174.61 87.31 87.31 10.76 87.31 349.23 174.61 174.61 87.31 87.31 10.77 87.31 349.23 174.61 174.61 87.31 87.31 10.78 87.31 349.23 174.61 174.61 87.31 87.31 10.79 87.31 349.23 174.61 174.61 87.31 87.31 10.80 87.31 349.23 174.61 174.61 87.31 87.31 10.81 87.31 349.23 174.61 174.61 87.31 87.31 10.82 87.31 349.23 174.61 174.61 87.31 87.31 10.83 87.31 349.23 174.61 174.61 87.31 87.31 10.84 87.31 349.23 174.61 174.61 87.31 87.31 10.85 87.31 349.23 174.61 174.61 87.31 87.31 10.86 87.31 349.23 174.61 174.61 87.31 87.31 10.87 87.31 349.23 174.61 174.61 87.31 87.31 10.88 87.31 349.23 174.61 174.61 87.31 87.31 10.89 87.31 349.23 174.61 174.61 87.31 87.31 110.00 10.90 349.23 174.61 174.61 87.31 87.31 110.00 10.91 349.23 174.61 174.61 87.31 87.31 110.00 220.00 440.00 10.92 349.23 174.61 174.61 87.31 87.31 110.00 220.00 440.00 10.93 349.23 174.61 174.61 87.31 87.31 110.00 220.00 440.00 10.94 349.23 174.61 174.61 87.31 87.31 110.00 220.00 440.00 10.95 349.23 174.61 174.61 87.31 87.31 110.00 220.00 440.00 220.00 10.96 174.61 174.61 87.31 87.31 110.00 220.00 440.00 220.00 10.97 174.61 87.31 87.31 110.00 220.00 440.00 220.00 10.98 174.61 87.31 87.31 110.00 220.00 440.00 220.00 10.99 174.61 87.31 87.31 110.00 220.00 440.00 220.00 11.00 87.31 87.31 110.00 220.00 440.00 220.00 11.01 87.31 87.31 110.00 220.00 440.00 220.00 110.00 11.02 87.31 87.31 110.00 220.00 440.00 220.00 110.00 11.03 87.31 87.31 110.00 220.00 440.00 220.00 110.00 11.04 87.31 110.00 220.00 440.00 220.00 110.00 11.05 87.31 110.00 220.00 440.00 220.00 110.00 110.00 11.06 87.31 110.00 220.00 440.00 220.00 110.00 110.00 11.07 87.31 110.00 220.00 440.00 220.00 110.00 110.00 11.08 110.00 220.00 440.00 220.00 110.00 110.00 11.09 110.00 220.00 440.00 220.00 110.00 110.00 11.10 110.00 220.00 440.00 220.00 110.00 110.00 11.11 110.00 220.00 440.00 220.00 110.00 110.00 11.12 110.00 220.00 440.00 220.00 110.00 110.00 130.81 11.13 110.00 220.00 440.00 220.00 110.00 110.00 130.81 11.14 220.00 440.00 220.00 110.00 110.00 130.81 11.15 220.00 440.00 220.00 110.00 110.00 130.81 261.63 11.16 220.00 440.00 220.00 110.00 110.00 130.81 261.63 523.25 11.17 440.00 220.00 110.00 110.00 130.81 261.63 523.25 11.18 220.00 110.00 110.00 130.81 261.63 523.25 261.63 11.19 220.00 110.00 110.00 130.81 261.63 523.25 261.63 11.20 220.00 110.00 110.00 130.81 261.63 523.25 261.63 11.21 110.00 110.00 130.81 261.63 523.25 261.63 11.22 110.00 110.00 130.81 261.63 523.25 261.63 11.23 110.00 110.00 130.81 261.63 523.25 261.63 130.81 11.24 110.00 110.00 130.81 261.63 523.25 261.63 130.81 11.25 110.00 130.81 261.63 523.25 261.63 130.81 11.26 130.81 261.63 523.25 261.63 130.81 130.81 11.27 130.81 261.63 523.25 261.63 130.81 130.81 11.28 130.81 261.63 523.25 261.63 130.81 130.81 11.29 130.81 261.63 523.25 261.63 130.81 130.81 11.30 130.81 261.63 523.25 261.63 130.81 130.81 11.31 130.81 261.63 523.25 261.63 130.81 130.81 11.32 130.81 261.63 523.25 261.63 130.81 130.81 11.33 130.81 261.63 523.25 261.63 130.81 130.81 11.34 130.81 261.63 523.25 261.63 130.81 130.81 11.35 130.81 261.63 523.25 261.63 130.81 130.81 11.36 130.81 261.63 523.25 261.63 130.81 130.81 11.37 130.81 261.63 523.25 261.63 130.81 130.81 11.38 130.81 261.63 523.25 261.63 130.81 130.81 11.39 130.81 261.63 523.25 261.63 130.81 130.81 11.40 130.81 261.63 523.25 261.63 130.81 130.81 11.41 130.81 261.63 523.25 261.63 130.81 130.81 11.42 130.81 261.63 523.25 261.63 130.81 130.81 11.43 130.81 261.63 523.25 261.63 130.81 130.81 11.44 130.81 261.63 523.25 261.63 130.81 130.81 11.45 130.81 261.63 523.25 261.63 130.81 130.81 11.46 130.81 261.63 523.25 261.63 130.81 130.81 11.47 130.81 261.63 523.25 261.63 130.81 130.81 11.48 130.81 523.25 261.63 130.81 130.81 11.49 130.81 523.25 261.63 130.81 130.81 11.50 130.81 523.25 261.63 130.81 130.81 11.51 130.81 523.25 261.63 130.81 130.81 11.52 523.25 261.63 130.81 130.81 82.41 11.53 523.25 261.63 130.81 130.81 82.41 11.54 261.63 130.81 130.81 82.41 11.55 261.63 130.81 130.81 82.41 11.56 130.81 130.81 82.41 164.81 11.57 130.81 130.81 82.41 164.81 11.58 130.81 130.81 82.41 164.81 329.63 11.59 130.81 130.81 82.41 164.81 329.63 11.60 130.81 130.81 82.41 164.81 329.63 164.81 11.61 130.81 130.81 82.41 164.81 329.63 164.81 11.62 130.81 82.41 164.81 329.63 164.81 82.41 11.63 130.81 82.41 164.81 329.63 164.81 82.41 82.41 11.64 82.41 164.81 329.63 164.81 82.41 82.41 11.65 82.41 164.81 329.63 164.81 82.41 82.41 11.66 82.41 164.81 329.63 164.81 82.41 82.41 11.67 82.41 164.81 329.63 164.81 82.41 82.41 11.68 82.41 164.81 329.63 164.81 82.41 82.41 11.69 82.41 164.81 329.63 164.81 82.41 82.41 11.70 82.41 164.81 329.63 164.81 82.41 82.41 11.71 82.41 164.81 329.63 164.81 82.41 82.41 11.72 82.41 164.81 329.63 164.81 82.41 82.41 11.73 82.41 164.81 329.63 164.81 82.41 82.41 11.74 82.41 164.81 329.63 164.81 82.41 82.41 11.75 82.41 164.81 329.63 164.81 82.41 82.41 11.76 82.41 164.81 329.63 164.81 82.41 82.41 11.77 82.41 164.81 329.63 164.81 82.41 82.41 11.78 82.41 164.81 329.63 164.81 82.41 82.41 11.79 82.41 164.81 329.63 164.81 82.41 82.41 11.80 82.41 164.81 329.63 164.81 82.41 82.41 11.81 82.41 164.81 329.63 164.81 82.41 82.41 11.82 82.41 164.81 329.63 164.81 82.41 82.41 11.83 82.41 164.81 329.63 164.81 82.41 82.41 11.84 82.41 164.81 329.63 164.81 82.41 82.41 11.85 82.41 164.81 329.63 164.81 82.41 82.41 11.86 82.41 164.81 329.63 164.81 82.41 82.41 11.87 82.41 164.81 329.63 164.81 82.41 82.41 11.88 82.41 164.81 329.63 164.81 82.41 82.41 11.89 82.41 164.81 329.63 164.81 82.41 82.41 11.90 82.41 164.81 329.63 164.81 82.41 82.41 11.91 82.41 164.81 329.63 164.81 82.41 82.41 11.92 82.41 164.81 329.63 164.81 82.41 82.41 11.93 82.41 164.81 329.63 164.81 82.41 82.41 11.94 82.41 164.81 329.63 164.81 82.41 82.41 11.95 82.41 164.81 329.63 164.81 82.41 82.41 11.96 82.41 164.81 329.63 164.81 82.41 82.41 11.97 82.41 164.81 329.63 164.81 82.41 82.41 11.98 82.41 164.81 329.63 164.81 82.41 82.41 11.99 82.41 164.81 329.63 164.81 82.41 82.41 12.00 82.41 164.81 329.63 164.81 82.41 82.41 12.01 82.41 164.81 329.63 164.81 82.41 82.41 12.02 82.41 164.81 329.63 164.81 82.41 82.41 12.03 82.41 164.81 329.63 164.81 82.41 82.41 12.04 82.41 164.81 329.63 164.81 82.41 82.41 12.05 82.41 164.81 329.63 164.81 82.41 82.41 12.06 82.41 164.81 329.63 164.81 82.41 82.41 12.07 82.41 164.81 329.63 164.81 82.41 82.41 220.00 12.08 82.41 164.81 329.63 164.81 82.41 82.41 220.00 12.09 82.41 164.81 329.63 164.81 82.41 82.41 220.00 12.10 82.41 164.81 329.63 164.81 82.41 82.41 220.00 12.11 82.41 164.81 329.63 164.81 82.41 82.41 220.00 110.00 12.12 82.41 329.63 164.81 82.41 82.41 220.00 110.00 12.13 82.41 329.63 164.81 82.41 82.41 220.00 110.00 12.14 82.41 329.63 164.81 82.41 82.41 220.00 110.00 12.15 329.63 164.81 82.41 82.41 220.00 110.00 12.16 329.63 164.81 82.41 82.41 220.00 110.00 110.00 12.17 329.63 164.81 82.41 82.41 220.00 110.00 110.00 220.00 12.18 329.63 164.81 82.41 82.41 220.00 110.00 110.00 220.00 12.19 329.63 164.81 82.41 220.00 110.00 110.00 220.00 440.00 110.00 12.20 329.63 164.81 82.41 220.00 110.00 110.00 220.00 440.00 110.00 12.21 329.63 164.81 220.00 110.00 110.00 220.00 440.00 110.00 12.22 329.63 164.81 220.00 110.00 110.00 220.00 440.00 110.00 12.23 329.63 220.00 110.00 110.00 220.00 440.00 110.00 12.24 220.00 110.00 110.00 220.00 440.00 110.00 12.25 220.00 110.00 110.00 220.00 440.00 110.00 12.26 220.00 110.00 110.00 220.00 440.00 110.00 12.27 220.00 110.00 110.00 220.00 440.00 110.00 12.28 220.00 110.00 110.00 220.00 440.00 110.00 12.29 220.00 110.00 110.00 220.00 440.00 110.00 12.30 220.00 110.00 110.00 220.00 440.00 110.00 261.63 12.31 220.00 110.00 110.00 220.00 440.00 110.00 261.63 12.32 110.00 110.00 220.00 440.00 110.00 261.63 12.33 110.00 110.00 220.00 440.00 110.00 261.63 12.34 110.00 220.00 440.00 110.00 261.63 12.35 110.00 220.00 440.00 110.00 261.63 130.81 130.81 12.36 110.00 220.00 440.00 110.00 261.63 130.81 130.81 12.37 220.00 440.00 110.00 261.63 130.81 130.81 12.38 220.00 440.00 110.00 261.63 130.81 130.81 523.25 12.39 220.00 110.00 261.63 130.81 130.81 523.25 12.40 220.00 110.00 261.63 130.81 130.81 523.25 12.41 220.00 110.00 261.63 130.81 130.81 523.25 261.63 130.81 12.42 220.00 261.63 130.81 130.81 523.25 261.63 130.81 12.43 261.63 130.81 130.81 523.25 261.63 130.81 12.44 261.63 130.81 130.81 523.25 261.63 130.81 12.45 261.63 130.81 130.81 523.25 261.63 130.81 12.46 261.63 130.81 130.81 523.25 261.63 130.81 12.47 261.63 130.81 130.81 523.25 261.63 130.81 12.48 261.63 130.81 130.81 523.25 261.63 130.81 12.49 261.63 130.81 130.81 523.25 261.63 130.81 12.50 261.63 130.81 130.81 523.25 261.63 130.81 12.51 261.63 130.81 130.81 523.25 261.63 130.81 12.52 261.63 130.81 130.81 523.25 261.63 130.81 12.53 261.63 130.81 130.81 523.25 261.63 130.81 12.54 261.63 130.81 130.81 523.25 261.63 130.81 12.55 261.63 130.81 130.81 523.25 261.63 130.81 12.56 261.63 130.81 130.81 523.25 261.63 130.81 12.57 261.63 130.81 130.81 523.25 261.63 130.81 12.58 261.63 130.81 130.81 523.25 261.63 130.81 12.59 261.63 130.81 130.81 523.25 261.63 130.81 12.60 261.63 130.81 130.81 523.25 261.63 130.81 12.61 261.63 130.81 130.81 523.25 261.63 130.81 12.62 261.63 130.81 130.81 523.25 261.63 130.81 12.63 261.63 130.81 130.81 523.25 261.63 130.81 12.64 261.63 130.81 130.81 523.25 261.63 130.81 12.65 261.63 130.81 130.81 523.25 261.63 130.81 12.66 261.63 130.81 130.81 523.25 261.63 130.81 12.67 261.63 130.81 130.81 523.25 261.63 130.81 12.68 261.63 130.81 130.81 523.25 261.63 130.81 12.69 261.63 130.81 130.81 523.25 261.63 130.81 12.70 261.63 130.81 130.81 523.25 261.63 130.81 12.71 261.63 130.81 130.81 261.63 130.81 12.72 261.63 130.81 130.81 130.81 12.73 261.63 130.81 130.81 130.81 12.74 261.63 130.81 130.81 12.75 261.63 130.81 130.81 155.56 77.78 12.76 261.63 130.81 130.81 155.56 77.78 77.78 311.13 12.77 130.81 130.81 155.56 77.78 77.78 311.13 12.78 130.81 130.81 155.56 77.78 77.78 311.13 77.78 155.56 12.79 130.81 155.56 77.78 77.78 311.13 77.78 155.56 12.80 130.81 155.56 77.78 77.78 311.13 77.78 155.56 12.81 155.56 77.78 77.78 311.13 77.78 155.56 12.82 155.56 77.78 77.78 311.13 77.78 155.56 12.83 155.56 77.78 77.78 311.13 77.78 155.56 12.84 155.56 77.78 77.78 311.13 77.78 155.56 12.85 155.56 77.78 77.78 311.13 77.78 155.56 12.86 155.56 77.78 77.78 311.13 77.78 155.56 12.87 155.56 77.78 77.78 311.13 77.78 155.56 12.88 155.56 77.78 77.78 311.13 77.78 155.56 12.89 155.56 77.78 77.78 311.13 77.78 155.56 12.90 155.56 77.78 77.78 311.13 77.78 155.56 12.91 155.56 77.78 77.78 311.13 77.78 155.56 12.92 155.56 77.78 77.78 311.13 77.78 155.56 12.93 155.56 77.78 77.78 311.13 77.78 155.56 12.94 155.56 77.78 77.78 311.13 77.78 155.56 12.95 155.56 77.78 77.78 311.13 77.78 155.56 12.96 155.56 77.78 77.78 311.13 77.78 155.56 12.97 155.56 77.78 77.78 311.13 77.78 155.56 12.98 155.56 77.78 77.78 311.13 77.78 155.56 12.99 155.56 77.78 77.78 311.13 77.78 155.56 13.00 155.56 77.78 77.78 311.13 77.78 155.56 13.01 155.56 77.78 77.78 311.13 77.78 155.56 13.02 155.56 77.78 77.78 311.13 77.78 155.56 13.03 155.56 77.78 77.78 311.13 77.78 155.56 13.04 155.56 77.78 77.78 311.13 77.78 155.56 13.05 155.56 77.78 77.78 311.13 77.78 155.56 13.06 155.56 77.78 77.78 311.13 77.78 155.56 13.07 155.56 77.78 77.78 311.13 77.78 155.56 13.08 155.56 77.78 77.78 311.13 77.78 155.56 13.09 155.56 77.78 77.78 311.13 77.78 155.56 13.10 155.56 77.78 77.78 311.13 77.78 155.56 13.11 155.56 77.78 77.78 311.13 77.78 155.56 13.12 155.56 77.78 77.78 311.13 77.78 155.56 13.13 155.56 77.78 77.78 311.13 77.78 155.56 13.14 155.56 77.78 77.78 311.13 77.78 155.56 13.15 155.56 77.78 77.78 311.13 77.78 155.56 13.16 155.56 77.78 77.78 311.13 77.78 155.56 13.17 155.56 77.78 77.78 311.13 77.78 155.56 13.18 155.56 77.78 77.78 311.13 77.78 155.56 13.19 155.56 77.78 77.78 311.13 77.78 155.56 13.20 155.56 77.78 77.78 311.13 77.78 155.56 13.21 155.56 77.78 77.78 311.13 77.78 155.56 13.22 155.56 77.78 77.78 311.13 77.78 155.56 13.23 155.56 77.78 77.78 311.13 77.78 155.56 13.24 155.56 77.78 77.78 311.13 77.78 155.56 13.25 155.56 77.78 77.78 311.13 77.78 155.56 13.26 155.56 77.78 77.78 311.13 77.78 155.56 13.27 155.56 77.78 77.78 311.13 77.78 155.56 13.28 155.56 77.78 77.78 311.13 77.78 155.56 13.29 155.56 77.78 77.78 311.13 77.78 155.56 13.30 155.56 77.78 77.78 311.13 77.78 155.56 13.31 155.56 77.78 77.78 311.13 77.78 155.56 13.32 155.56 77.78 77.78 311.13 77.78 13.33 155.56 77.78 77.78 311.13 77.78 13.34 155.56 77.78 77.78 77.78 261.63 13.35 155.56 77.78 77.78 77.78 261.63 13.36 155.56 77.78 77.78 77.78 261.63 523.25 13.37 77.78 77.78 77.78 261.63 523.25 13.38 77.78 77.78 77.78 261.63 523.25 13.39 77.78 77.78 77.78 261.63 523.25 13.40 77.78 77.78 77.78 261.63 523.25 13.41 77.78 77.78 77.78 261.63 523.25 13.42 77.78 77.78 77.78 261.63 523.25 13.43 77.78 77.78 77.78 261.63 523.25 13.44 77.78 77.78 77.78 261.63 523.25 13.45 77.78 77.78 77.78 261.63 523.25 13.46 77.78 77.78 77.78 261.63 523.25 13.47 77.78 77.78 77.78 261.63 523.25 13.48 77.78 77.78 77.78 261.63 523.25 13.49 77.78 77.78 77.78 261.63 523.25 13.50 77.78 77.78 77.78 261.63 523.25 13.51 77.78 77.78 77.78 261.63 523.25 13.52 77.78 77.78 77.78 261.63 523.25 13.53 77.78 77.78 77.78 261.63 523.25 13.54 77.78 77.78 77.78 261.63 523.25 13.55 77.78 77.78 77.78 261.63 523.25 13.56 77.78 77.78 77.78 261.63 523.25 246.94 13.57 77.78 77.78 77.78 261.63 523.25 246.94 493.88 13.58 77.78 77.78 77.78 261.63 523.25 246.94 493.88 13.59 77.78 77.78 261.63 246.94 493.88 369.99 13.60 77.78 77.78 246.94 493.88 369.99 261.63 13.61 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.62 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.63 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.64 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.65 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.66 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.67 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.68 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.69 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.70 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.71 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.72 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.73 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.74 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.75 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.76 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.77 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.78 77.78 77.78 246.94 493.88 369.99 261.63 155.56 220.00 13.79 77.78 77.78 246.94 493.88 369.99 261.63 155.56 220.00 440.00 13.80 77.78 77.78 246.94 493.88 369.99 261.63 155.56 220.00 440.00 13.81 77.78 77.78 493.88 369.99 261.63 155.56 220.00 440.00 13.82 77.78 77.78 155.56 220.00 440.00 13.83 77.78 77.78 155.56 220.00 440.00 13.84 77.78 77.78 155.56 220.00 440.00 13.85 77.78 77.78 155.56 220.00 440.00 13.86 77.78 77.78 155.56 220.00 440.00 13.87 77.78 77.78 155.56 220.00 440.00 13.88 77.78 77.78 155.56 220.00 440.00 13.89 77.78 77.78 155.56 220.00 440.00 13.90 77.78 77.78 155.56 220.00 440.00 13.91 77.78 77.78 155.56 220.00 440.00 13.92 77.78 77.78 155.56 220.00 440.00 13.93 77.78 77.78 155.56 220.00 440.00 13.94 77.78 77.78 155.56 220.00 440.00 13.95 77.78 77.78 155.56 440.00 13.96 77.78 77.78 155.56 440.00 13.97 77.78 77.78 155.56 440.00 82.41 13.98 77.78 77.78 155.56 82.41 13.99 77.78 77.78 155.56 82.41 14.00 77.78 77.78 155.56 82.41 14.01 77.78 155.56 82.41 82.41 14.02 77.78 155.56 82.41 82.41 14.03 155.56 82.41 82.41 220.00 14.04 155.56 82.41 82.41 220.00 440.00 14.05 155.56 82.41 82.41 220.00 440.00 14.06 155.56 82.41 82.41 220.00 440.00 14.07 155.56 82.41 82.41 220.00 440.00 14.08 155.56 82.41 82.41 220.00 440.00 14.09 155.56 82.41 82.41 220.00 440.00 14.10 155.56 82.41 82.41 220.00 440.00 14.11 155.56 82.41 82.41 220.00 440.00 14.12 155.56 82.41 82.41 220.00 440.00 14.13 155.56 82.41 82.41 220.00 440.00 14.14 155.56 82.41 82.41 220.00 440.00 14.15 155.56 82.41 82.41 220.00 440.00 329.63 14.16 155.56 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.17 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.18 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.19 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.20 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.21 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.22 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.23 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.24 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.25 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.26 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.27 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.28 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.29 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.30 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.31 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.32 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.33 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.34 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.35 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.36 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.37 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.38 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.39 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.40 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.41 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.42 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.43 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.44 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.45 82.41 220.00 440.00 329.63 246.94 164.81 14.46 82.41 220.00 440.00 329.63 246.94 164.81 14.47 82.41 220.00 440.00 329.63 246.94 164.81 14.48 82.41 220.00 440.00 329.63 246.94 164.81 14.49 82.41 220.00 440.00 329.63 246.94 164.81 14.50 82.41 220.00 440.00 329.63 246.94 164.81 14.51 82.41 220.00 440.00 329.63 246.94 164.81 14.52 82.41 220.00 440.00 329.63 246.94 164.81 14.53 82.41 220.00 440.00 329.63 246.94 164.81 14.54 82.41 220.00 440.00 329.63 246.94 164.81 14.55 82.41 220.00 440.00 329.63 246.94 164.81 14.56 82.41 220.00 440.00 329.63 246.94 164.81 14.57 82.41 220.00 440.00 329.63 246.94 164.81 14.58 82.41 220.00 440.00 329.63 246.94 164.81 14.59 82.41 220.00 440.00 329.63 246.94 164.81 14.60 82.41 220.00 440.00 329.63 246.94 164.81 14.61 82.41 220.00 440.00 329.63 246.94 164.81 14.62 82.41 220.00 440.00 329.63 246.94 164.81 14.63 82.41 220.00 440.00 329.63 246.94 164.81 14.64 82.41 220.00 440.00 329.63 246.94 164.81 14.65 82.41 220.00 440.00 329.63 246.94 164.81 14.66 82.41 220.00 440.00 329.63 246.94 164.81 14.67 82.41 220.00 440.00 329.63 246.94 164.81 14.68 82.41 220.00 440.00 329.63 246.94 164.81 14.69 82.41 220.00 440.00 329.63 246.94 164.81 14.70 82.41 220.00 440.00 329.63 246.94 164.81 14.71 82.41 220.00 440.00 329.63 246.94 164.81 14.72 82.41 220.00 440.00 329.63 246.94 164.81 14.73 82.41 220.00 440.00 329.63 246.94 164.81 14.74 82.41 220.00 440.00 329.63 246.94 164.81 14.75 82.41 220.00 440.00 329.63 246.94 164.81 14.76 82.41 220.00 440.00 329.63 246.94 164.81 14.77 82.41 220.00 440.00 329.63 246.94 164.81 14.78 82.41 220.00 440.00 329.63 246.94 164.81 14.79 82.41 220.00 440.00 329.63 246.94 164.81 14.80 82.41 220.00 440.00 329.63 246.94 164.81 14.81 82.41 220.00 440.00 329.63 246.94 14.82 82.41 220.00 440.00 329.63 246.94 14.83 82.41 220.00 440.00 329.63 246.94 14.84 82.41 220.00 440.00 329.63 246.94 14.85 82.41 220.00 440.00 329.63 246.94 14.86 82.41 220.00 440.00 329.63 246.94 14.87 82.41 220.00 440.00 329.63 246.94 14.88 82.41 220.00 440.00 329.63 246.94 14.89 82.41 220.00 440.00 329.63 246.94 14.90 82.41 220.00 440.00 329.63 246.94 14.91 82.41 220.00 440.00 329.63 246.94 14.92 82.41 220.00 440.00 329.63 246.94 14.93 82.41 220.00 440.00 329.63 246.94 14.94 82.41 220.00 440.00 329.63 246.94 14.95 82.41 220.00 440.00 329.63 246.94 14.96 82.41 220.00 440.00 329.63 246.94 14.97 82.41 220.00 440.00 329.63 246.94 14.98 82.41 220.00 440.00 329.63 246.94 14.99 82.41 220.00 440.00 329.63 246.94 15.00 82.41 220.00 440.00 329.63 246.94 415.30 15.01 82.41 220.00 440.00 329.63 246.94 415.30 207.65 15.02 82.41 220.00 440.00 329.63 246.94 415.30 207.65 15.03 82.41 220.00 329.63 246.94 415.30 207.65 15.04 82.41 220.00 329.63 246.94 415.30 207.65 15.05 82.41 220.00 329.63 246.94 415.30 207.65 15.06 82.41 329.63 246.94 415.30 207.65 15.07 82.41 329.63 246.94 415.30 207.65 15.08 82.41 329.63 246.94 415.30 207.65 207.65 15.09 82.41 329.63 246.94 415.30 207.65 207.65 15.10 82.41 415.30 207.65 207.65 15.11 82.41 415.30 207.65 207.65 15.12 82.41 415.30 207.65 207.65 15.13 82.41 415.30 207.65 207.65 15.14 82.41 415.30 207.65 207.65 15.15 82.41 415.30 207.65 207.65 15.16 82.41 415.30 207.65 207.65 15.17 82.41 415.30 207.65 207.65 15.18 82.41 415.30 207.65 207.65 15.19 82.41 415.30 207.65 207.65 15.20 82.41 415.30 207.65 207.65 15.21 82.41 415.30 207.65 207.65 15.22 82.41 415.30 207.65 207.65 15.23 82.41 415.30 207.65 207.65 15.24 82.41 415.30 207.65 207.65 15.25 82.41 415.30 207.65 207.65 15.26 82.41 415.30 207.65 207.65 69.30 15.27 82.41 415.30 207.65 207.65 69.30 15.28 82.41 415.30 207.65 207.65 69.30 15.29 82.41 415.30 207.65 207.65 69.30 15.30 82.41 415.30 207.65 207.65 69.30 15.31 82.41 415.30 207.65 207.65 69.30 15.32 82.41 415.30 207.65 207.65 69.30 15.33 82.41 415.30 207.65 207.65 69.30 15.34 82.41 415.30 207.65 207.65 69.30 15.35 82.41 415.30 207.65 207.65 69.30 15.36 82.41 415.30 207.65 207.65 69.30 15.37 82.41 415.30 207.65 207.65 69.30 15.38 82.41 415.30 207.65 207.65 69.30 15.39 82.41 415.30 207.65 207.65 69.30 15.40 82.41 415.30 207.65 207.65 69.30 15.41 82.41 207.65 207.65 69.30 15.42 82.41 207.65 207.65 69.30 15.43 82.41 207.65 207.65 69.30 15.44 82.41 207.65 207.65 69.30 15.45 207.65 207.65 69.30 15.46 207.65 207.65 69.30 15.47 207.65 207.65 69.30 392.00 15.48 207.65 207.65 69.30 392.00 15.49 207.65 207.65 69.30 392.00 15.50 207.65 207.65 69.30 392.00 15.51 207.65 69.30 392.00 15.52 207.65 69.30 392.00 15.53 207.65 69.30 392.00 15.54 207.65 69.30 392.00 15.55 207.65 69.30 392.00 138.59 15.56 207.65 69.30 392.00 138.59 15.57 207.65 69.30 392.00 138.59 15.58 207.65 69.30 392.00 138.59 15.59 207.65 69.30 392.00 138.59 15.60 207.65 69.30 392.00 138.59 15.61 69.30 392.00 138.59 15.62 69.30 392.00 138.59 15.63 69.30 392.00 138.59 15.64 69.30 392.00 138.59 15.65 69.30 392.00 138.59 15.66 69.30 392.00 138.59 15.67 69.30 392.00 138.59 15.68 69.30 392.00 138.59 15.69 69.30 392.00 138.59 220.00 15.70 69.30 392.00 138.59 220.00 15.71 69.30 392.00 138.59 220.00 15.72 69.30 392.00 138.59 220.00 15.73 69.30 392.00 138.59 220.00 15.74 69.30 392.00 138.59 220.00 15.75 69.30 392.00 138.59 220.00 15.76 69.30 392.00 138.59 220.00 15.77 69.30 392.00 138.59 220.00 15.78 69.30 392.00 138.59 220.00 15.79 69.30 392.00 138.59 220.00 15.80 69.30 392.00 138.59 220.00 15.81 69.30 392.00 138.59 220.00 15.82 69.30 392.00 138.59 220.00 15.83 392.00 138.59 220.00 15.84 392.00 138.59 220.00 15.85 392.00 138.59 220.00 15.86 392.00 138.59 220.00 15.87 392.00 138.59 220.00 15.88 392.00 138.59 220.00 15.89 392.00 138.59 220.00 15.90 392.00 138.59 220.00 329.63 15.91 392.00 138.59 220.00 329.63 15.92 392.00 138.59 220.00 329.63 15.93 392.00 138.59 329.63 15.94 392.00 138.59 329.63 15.95 392.00 138.59 329.63 15.96 392.00 138.59 329.63 15.97 392.00 138.59 329.63 15.98 392.00 138.59 329.63 15.99 392.00 138.59 329.63 16.00 392.00 138.59 329.63 16.01 392.00 138.59 329.63 16.02 392.00 138.59 329.63 16.03 392.00 138.59 329.63 16.04 392.00 138.59 329.63 16.05 392.00 138.59 329.63 16.06 392.00 138.59 329.63 16.07 392.00 138.59 329.63 16.08 392.00 138.59 329.63 392.00 16.09 392.00 138.59 392.00 16.10 392.00 138.59 392.00 16.11 392.00 138.59 392.00 466.16 16.12 138.59 392.00 466.16 16.13 138.59 392.00 466.16 16.14 138.59 392.00 466.16 16.15 138.59 392.00 466.16 16.16 138.59 392.00 466.16 16.17 138.59 392.00 466.16 16.18 138.59 392.00 466.16 16.19 138.59 392.00 466.16 16.20 138.59 392.00 466.16 16.21 138.59 392.00 466.16 16.22 138.59 392.00 466.16 16.23 138.59 392.00 466.16 16.24 138.59 392.00 466.16 16.25 138.59 392.00 466.16 16.26 138.59 392.00 466.16 16.27 138.59 392.00 466.16 16.28 138.59 392.00 466.16 16.29 138.59 392.00 466.16 16.30 138.59 392.00 466.16 440.00 440.00 16.31 138.59 466.16 440.00 440.00 16.32 138.59 466.16 440.00 440.00 16.33 138.59 466.16 440.00 440.00 16.34 138.59 440.00 440.00 16.35 138.59 440.00 440.00 16.36 138.59 440.00 440.00 16.37 138.59 440.00 440.00 16.38 138.59 440.00 440.00 16.39 138.59 440.00 440.00 16.40 138.59 440.00 440.00 16.41 138.59 440.00 440.00 16.42 138.59 440.00 440.00 16.43 138.59 440.00 440.00 16.44 138.59 440.00 440.00 16.45 138.59 440.00 440.00 16.46 138.59 440.00 440.00 16.47 138.59 440.00 440.00 16.48 138.59 440.00 16.49 138.59 440.00 392.00 16.50 138.59 440.00 392.00 220.00 16.51 138.59 440.00 392.00 220.00 16.52 138.59 440.00 392.00 220.00 16.53 138.59 392.00 220.00 16.54 138.59 392.00 220.00 16.55 138.59 392.00 220.00 16.56 138.59 392.00 220.00 16.57 138.59 392.00 220.00 16.58 138.59 392.00 220.00 16.59 138.59 392.00 220.00 16.60 138.59 220.00 16.61 138.59 220.00 73.42 16.62 138.59 220.00 73.42 16.63 138.59 220.00 73.42 16.64 138.59 220.00 73.42 16.65 138.59 220.00 73.42 146.83 16.66 138.59 220.00 73.42 146.83 16.67 138.59 220.00 73.42 146.83 16.68 138.59 220.00 73.42 146.83 392.00 16.69 138.59 220.00 73.42 146.83 392.00 16.70 138.59 220.00 73.42 146.83 392.00 16.71 220.00 73.42 146.83 392.00 16.72 220.00 73.42 146.83 392.00 16.73 73.42 146.83 392.00 16.74 73.42 146.83 392.00 16.75 73.42 146.83 392.00 16.76 73.42 146.83 392.00 16.77 73.42 146.83 392.00 16.78 73.42 146.83 392.00 16.79 73.42 146.83 392.00 16.80 73.42 146.83 392.00 16.81 73.42 146.83 392.00 16.82 73.42 146.83 392.00 16.83 73.42 146.83 392.00 16.84 73.42 146.83 392.00 220.00 16.85 73.42 146.83 392.00 220.00 16.86 73.42 146.83 392.00 220.00 16.87 73.42 146.83 392.00 220.00 16.88 73.42 146.83 392.00 220.00 369.99 16.89 73.42 146.83 392.00 220.00 369.99 16.90 73.42 146.83 220.00 369.99 16.91 73.42 146.83 220.00 369.99 16.92 73.42 146.83 220.00 369.99 16.93 73.42 146.83 220.00 369.99 16.94 73.42 146.83 220.00 369.99 16.95 73.42 146.83 220.00 369.99 16.96 73.42 146.83 220.00 369.99 16.97 73.42 146.83 220.00 369.99 16.98 73.42 146.83 220.00 369.99 16.99 73.42 146.83 220.00 369.99 17.00 73.42 146.83 220.00 369.99 17.01 73.42 146.83 220.00 369.99 17.02 73.42 146.83 220.00 369.99 17.03 146.83 369.99 17.04 146.83 369.99 17.05 146.83 369.99 17.06 146.83 369.99 17.07 146.83 369.99 293.66 17.08 146.83 369.99 293.66 17.09 146.83 369.99 293.66 587.33 17.10 146.83 369.99 293.66 587.33 17.11 146.83 369.99 293.66 587.33 17.12 146.83 293.66 587.33 17.13 146.83 293.66 587.33 17.14 146.83 293.66 587.33 17.15 146.83 293.66 587.33 17.16 146.83 293.66 587.33 17.17 146.83 293.66 587.33 17.18 146.83 293.66 587.33 17.19 146.83 293.66 587.33 17.20 146.83 293.66 587.33 17.21 146.83 293.66 587.33 17.22 146.83 293.66 587.33 17.23 146.83 293.66 587.33 17.24 146.83 293.66 587.33 17.25 146.83 293.66 587.33 17.26 146.83 587.33 17.27 146.83 587.33 17.28 146.83 587.33 17.29 146.83 587.33 17.30 146.83 587.33 17.31 146.83 587.33 17.32 146.83 587.33 369.99 17.33 146.83 587.33 369.99 17.34 146.83 587.33 369.99 17.35 146.83 587.33 369.99 17.36 146.83 587.33 369.99 17.37 146.83 587.33 369.99 17.38 146.83 587.33 369.99 17.39 146.83 587.33 369.99 17.40 146.83 587.33 369.99 17.41 146.83 587.33 369.99 17.42 146.83 587.33 369.99 17.43 146.83 587.33 369.99 17.44 146.83 587.33 369.99 17.45 146.83 587.33 369.99 17.46 146.83 587.33 369.99 17.47 146.83 587.33 369.99 17.48 146.83 587.33 369.99 17.49 146.83 587.33 369.99 17.50 146.83 587.33 369.99 440.00 17.51 146.83 587.33 369.99 440.00 17.52 146.83 587.33 369.99 440.00 17.53 146.83 587.33 440.00 17.54 146.83 587.33 440.00 17.55 146.83 587.33 440.00 17.56 146.83 587.33 440.00 17.57 146.83 587.33 440.00 17.58 146.83 587.33 440.00 17.59 146.83 587.33 440.00 17.60 146.83 587.33 440.00 17.61 146.83 587.33 440.00 17.62 146.83 587.33 440.00 17.63 146.83 587.33 440.00 17.64 146.83 587.33 440.00 17.65 146.83 587.33 440.00 17.66 146.83 587.33 440.00 17.67 146.83 587.33 440.00 17.68 146.83 587.33 440.00 17.69 146.83 587.33 220.00 17.70 146.83 587.33 220.00 17.71 146.83 587.33 220.00 17.72 146.83 587.33 220.00 17.73 146.83 587.33 220.00 17.74 146.83 587.33 220.00 61.74 17.75 146.83 587.33 220.00 61.74 17.76 146.83 587.33 220.00 61.74 17.77 146.83 587.33 220.00 61.74 17.78 146.83 587.33 220.00 61.74 17.79 146.83 587.33 220.00 61.74 17.80 146.83 587.33 220.00 61.74 17.81 146.83 587.33 220.00 61.74 17.82 146.83 587.33 220.00 61.74 17.83 146.83 587.33 220.00 61.74 17.84 146.83 587.33 220.00 61.74 123.47 17.85 146.83 587.33 220.00 61.74 123.47 17.86 146.83 587.33 220.00 61.74 123.47 17.87 146.83 587.33 220.00 61.74 123.47 17.88 587.33 220.00 61.74 123.47 17.89 587.33 220.00 61.74 123.47 17.90 587.33 220.00 61.74 123.47 17.91 587.33 220.00 61.74 123.47 17.92 587.33 220.00 61.74 123.47 17.93 587.33 220.00 61.74 123.47 17.94 587.33 220.00 61.74 123.47 17.95 587.33 220.00 61.74 123.47 17.96 587.33 61.74 123.47 17.97 61.74 123.47 17.98 61.74 123.47 17.99 61.74 123.47 18.00 61.74 123.47 18.01 61.74 123.47 18.02 61.74 123.47 18.03 61.74 123.47 18.04 61.74 123.47 18.05 61.74 123.47 18.06 61.74 123.47 18.07 61.74 123.47 18.08 61.74 123.47 18.09 61.74 123.47 329.63 18.10 61.74 123.47 329.63 18.11 61.74 123.47 329.63 196.00 18.12 61.74 123.47 329.63 196.00 18.13 61.74 123.47 329.63 196.00 18.14 61.74 123.47 329.63 196.00 18.15 61.74 123.47 329.63 196.00 18.16 61.74 123.47 329.63 196.00 18.17 61.74 123.47 329.63 196.00 18.18 123.47 329.63 196.00 18.19 123.47 329.63 196.00 18.20 123.47 329.63 196.00 18.21 123.47 329.63 196.00 18.22 123.47 329.63 196.00 18.23 123.47 329.63 196.00 18.24 123.47 329.63 196.00 18.25 123.47 329.63 196.00 18.26 123.47 329.63 196.00 18.27 123.47 329.63 196.00 18.28 123.47 329.63 196.00 18.29 123.47 329.63 196.00 349.23 18.30 123.47 329.63 196.00 349.23 293.66 18.31 123.47 329.63 196.00 349.23 293.66 18.32 123.47 329.63 196.00 349.23 293.66 18.33 123.47 329.63 349.23 293.66 18.34 123.47 329.63 349.23 293.66 18.35 123.47 329.63 349.23 293.66 18.36 123.47 329.63 349.23 293.66 18.37 123.47 329.63 349.23 293.66 18.38 123.47 329.63 349.23 293.66 18.39 123.47 329.63 349.23 293.66 18.40 123.47 329.63 349.23 293.66 18.41 123.47 329.63 349.23 293.66 18.42 123.47 349.23 293.66 18.43 123.47 349.23 293.66 18.44 123.47 349.23 293.66 18.45 123.47 349.23 293.66 18.46 123.47 349.23 293.66 18.47 123.47 349.23 293.66 18.48 123.47 293.66 440.00 18.49 123.47 293.66 440.00 18.50 123.47 293.66 440.00 349.23 18.51 123.47 293.66 440.00 349.23 18.52 123.47 440.00 349.23 18.53 123.47 440.00 349.23 18.54 123.47 440.00 349.23 18.55 123.47 440.00 349.23 18.56 123.47 440.00 349.23 18.57 123.47 440.00 349.23 18.58 123.47 440.00 349.23 18.59 123.47 440.00 349.23 18.60 123.47 440.00 349.23 18.61 123.47 440.00 349.23 18.62 123.47 440.00 349.23 18.63 123.47 440.00 349.23 18.64 123.47 440.00 349.23 18.65 123.47 440.00 349.23 18.66 123.47 440.00 349.23 18.67 123.47 440.00 349.23 392.00 18.68 123.47 440.00 349.23 392.00 18.69 123.47 440.00 349.23 392.00 18.70 123.47 440.00 349.23 392.00 18.71 123.47 349.23 392.00 18.72 123.47 349.23 392.00 18.73 123.47 349.23 392.00 392.00 18.74 123.47 349.23 392.00 392.00 18.75 123.47 349.23 392.00 392.00 18.76 123.47 392.00 392.00 18.77 123.47 392.00 392.00 18.78 123.47 392.00 392.00 18.79 123.47 392.00 392.00 18.80 123.47 392.00 392.00 18.81 123.47 392.00 392.00 18.82 123.47 392.00 392.00 18.83 123.47 392.00 392.00 18.84 123.47 392.00 392.00 18.85 123.47 392.00 392.00 18.86 123.47 392.00 392.00 18.87 123.47 392.00 392.00 349.23 18.88 123.47 392.00 392.00 349.23 18.89 123.47 392.00 392.00 349.23 18.90 123.47 392.00 349.23 18.91 123.47 392.00 349.23 196.00 18.92 123.47 349.23 196.00 18.93 123.47 349.23 196.00 18.94 123.47 349.23 196.00 18.95 123.47 349.23 196.00 18.96 123.47 349.23 196.00 18.97 123.47 349.23 196.00 18.98 123.47 349.23 196.00 18.99 123.47 349.23 196.00 19.00 123.47 196.00 19.01 123.47 196.00 19.02 123.47 196.00 19.03 123.47 196.00 19.04 123.47 196.00 130.81 19.05 123.47 196.00 130.81 65.41 19.06 123.47 196.00 130.81 65.41 19.07 123.47 196.00 130.81 65.41 349.23 19.08 123.47 196.00 130.81 65.41 349.23 19.09 123.47 196.00 130.81 65.41 349.23 19.10 123.47 130.81 65.41 349.23 19.11 130.81 65.41 349.23 19.12 130.81 65.41 349.23 19.13 130.81 65.41 349.23 19.14 130.81 65.41 349.23 19.15 130.81 65.41 349.23 19.16 130.81 65.41 349.23 19.17 130.81 65.41 349.23 19.18 130.81 65.41 349.23 19.19 130.81 65.41 349.23 19.20 130.81 65.41 349.23 19.21 130.81 65.41 349.23 19.22 130.81 65.41 349.23 19.23 130.81 65.41 349.23 19.24 130.81 65.41 349.23 19.25 130.81 65.41 349.23 19.26 130.81 65.41 349.23 19.27 130.81 65.41 329.63 19.28 130.81 65.41 329.63 19.29 130.81 65.41 329.63 19.30 130.81 65.41 329.63 196.00 19.31 130.81 65.41 329.63 196.00 19.32 130.81 65.41 329.63 196.00 19.33 130.81 65.41 329.63 196.00 19.34 130.81 65.41 329.63 196.00 19.35 130.81 65.41 329.63 196.00 19.36 130.81 65.41 329.63 196.00 19.37 130.81 65.41 329.63 196.00 19.38 130.81 65.41 329.63 196.00 19.39 130.81 65.41 329.63 196.00 19.40 130.81 65.41 329.63 196.00 19.41 130.81 65.41 329.63 196.00 19.42 130.81 65.41 329.63 196.00 19.43 130.81 65.41 329.63 196.00 19.44 130.81 65.41 329.63 196.00 19.45 130.81 65.41 329.63 196.00 19.46 130.81 65.41 329.63 196.00 19.47 130.81 65.41 329.63 196.00 19.48 130.81 329.63 196.00 19.49 130.81 329.63 196.00 19.50 130.81 196.00 261.63 19.51 130.81 196.00 261.63 523.25 19.52 130.81 196.00 261.63 523.25 19.53 130.81 196.00 261.63 523.25 19.54 130.81 196.00 261.63 523.25 19.55 130.81 261.63 523.25 19.56 130.81 261.63 523.25 19.57 130.81 261.63 523.25 19.58 130.81 261.63 523.25 19.59 130.81 261.63 523.25 19.60 130.81 261.63 523.25 19.61 130.81 261.63 523.25 19.62 130.81 261.63 523.25 19.63 130.81 261.63 523.25 19.64 130.81 261.63 523.25 19.65 130.81 261.63 523.25 19.66 130.81 261.63 523.25 19.67 130.81 261.63 523.25 19.68 130.81 261.63 523.25 19.69 130.81 261.63 523.25 19.70 130.81 261.63 523.25 329.63 19.71 130.81 261.63 523.25 329.63 19.72 130.81 261.63 523.25 329.63 19.73 130.81 523.25 329.63 19.74 130.81 523.25 329.63 19.75 130.81 523.25 329.63 19.76 130.81 523.25 329.63 19.77 130.81 523.25 329.63 19.78 130.81 523.25 329.63 19.79 130.81 523.25 329.63 19.80 130.81 523.25 329.63 19.81 130.81 523.25 329.63 19.82 130.81 523.25 329.63 19.83 130.81 523.25 329.63 19.84 130.81 523.25 329.63 19.85 130.81 523.25 329.63 19.86 130.81 523.25 329.63 19.87 130.81 523.25 329.63 19.88 130.81 523.25 329.63 19.89 130.81 523.25 329.63 392.00 19.90 130.81 523.25 329.63 392.00 19.91 130.81 523.25 392.00 19.92 130.81 523.25 392.00 19.93 130.81 523.25 392.00 19.94 130.81 523.25 392.00 19.95 130.81 523.25 392.00 19.96 130.81 523.25 392.00 19.97 130.81 523.25 392.00 19.98 130.81 523.25 392.00 19.99 130.81 523.25 392.00 20.00 130.81 523.25 392.00 20.01 130.81 523.25 392.00 20.02 130.81 523.25 392.00 20.03 130.81 523.25 392.00 20.04 130.81 523.25 392.00 20.05 130.81 523.25 392.00 20.06 130.81 523.25 392.00 20.07 130.81 523.25 392.00 20.08 130.81 523.25 196.00 20.09 130.81 523.25 196.00 20.10 130.81 523.25 196.00 20.11 130.81 523.25 196.00 20.12 130.81 523.25 196.00 20.13 130.81 523.25 196.00 20.14 130.81 523.25 196.00 20.15 130.81 523.25 196.00 20.16 130.81 523.25 196.00 20.17 130.81 523.25 196.00 20.18 130.81 523.25 196.00 20.19 130.81 523.25 196.00 20.20 130.81 523.25 196.00 20.21 130.81 523.25 196.00 20.22 130.81 523.25 196.00 20.23 130.81 523.25 196.00 103.83 20.24 523.25 196.00 103.83 103.83 20.25 523.25 103.83 103.83 20.26 523.25 103.83 103.83 20.27 523.25 103.83 103.83 20.28 523.25 103.83 103.83 20.29 523.25 103.83 103.83 329.63 20.30 523.25 103.83 103.83 329.63 20.31 523.25 103.83 103.83 329.63 20.32 523.25 103.83 103.83 329.63 20.33 523.25 103.83 103.83 329.63 20.34 523.25 103.83 103.83 329.63 20.35 103.83 103.83 329.63 20.36 103.83 103.83 329.63 20.37 103.83 103.83 329.63 20.38 103.83 103.83 329.63 20.39 103.83 103.83 329.63 20.40 103.83 103.83 329.63 20.41 103.83 103.83 329.63 20.42 103.83 103.83 329.63 20.43 103.83 103.83 329.63 20.44 103.83 103.83 329.63 20.45 103.83 103.83 329.63 20.46 103.83 103.83 329.63 20.47 103.83 103.83 329.63 20.48 103.83 103.83 329.63 20.49 103.83 103.83 329.63 246.94 20.50 103.83 103.83 329.63 246.94 20.51 103.83 103.83 329.63 246.94 20.52 103.83 103.83 329.63 246.94 20.53 103.83 103.83 329.63 246.94 20.54 103.83 103.83 329.63 246.94 20.55 103.83 103.83 329.63 246.94 20.56 103.83 103.83 329.63 246.94 20.57 103.83 103.83 329.63 246.94 20.58 103.83 103.83 329.63 246.94 20.59 103.83 103.83 329.63 246.94 20.60 103.83 103.83 329.63 246.94 20.61 103.83 103.83 329.63 246.94 20.62 103.83 103.83 329.63 246.94 20.63 103.83 103.83 329.63 246.94 20.64 103.83 103.83 329.63 246.94 20.65 103.83 329.63 246.94 20.66 103.83 329.63 246.94 20.67 103.83 329.63 246.94 20.68 103.83 329.63 246.94 20.69 103.83 329.63 246.94 293.66 20.70 103.83 329.63 246.94 293.66 20.71 103.83 329.63 246.94 293.66 20.72 103.83 329.63 293.66 20.73 103.83 329.63 293.66 20.74 103.83 329.63 293.66 20.75 103.83 329.63 293.66 20.76 103.83 329.63 293.66 20.77 103.83 329.63 293.66 20.78 103.83 329.63 293.66 20.79 103.83 329.63 293.66 20.80 103.83 329.63 293.66 20.81 103.83 329.63 293.66 20.82 103.83 329.63 293.66 20.83 103.83 329.63 293.66 20.84 103.83 329.63 293.66 20.85 103.83 329.63 293.66 20.86 103.83 329.63 293.66 20.87 103.83 329.63 293.66 20.88 103.83 329.63 293.66 329.63 20.89 103.83 329.63 293.66 329.63 20.90 103.83 329.63 293.66 329.63 20.91 103.83 329.63 329.63 349.23 20.92 103.83 329.63 349.23 20.93 103.83 329.63 349.23 20.94 103.83 329.63 349.23 20.95 103.83 329.63 349.23 20.96 103.83 329.63 349.23 20.97 103.83 329.63 349.23 20.98 103.83 329.63 349.23 20.99 103.83 329.63 349.23 21.00 103.83 329.63 349.23 21.01 103.83 329.63 349.23 21.02 103.83 329.63 349.23 21.03 103.83 349.23 21.04 103.83 349.23 21.05 103.83 349.23 493.88 21.06 103.83 349.23 493.88 21.07 103.83 349.23 493.88 21.08 103.83 349.23 493.88 21.09 103.83 349.23 493.88 21.10 103.83 349.23 493.88 21.11 103.83 349.23 493.88 21.12 103.83 349.23 493.88 329.63 21.13 103.83 349.23 493.88 329.63 21.14 103.83 349.23 493.88 329.63 21.15 103.83 349.23 493.88 329.63 21.16 103.83 493.88 329.63 21.17 103.83 493.88 329.63 21.18 103.83 493.88 329.63 21.19 103.83 493.88 329.63 21.20 103.83 493.88 329.63 21.21 103.83 493.88 329.63 21.22 103.83 493.88 329.63 21.23 103.83 493.88 329.63 21.24 103.83 493.88 329.63 21.25 103.83 493.88 329.63 246.94 21.26 103.83 493.88 329.63 246.94 21.27 103.83 493.88 329.63 246.94 21.28 103.83 329.63 246.94 21.29 103.83 329.63 246.94 293.66 21.30 103.83 329.63 246.94 293.66 21.31 103.83 246.94 293.66 21.32 103.83 246.94 293.66 21.33 103.83 246.94 293.66 21.34 103.83 246.94 293.66 21.35 103.83 246.94 293.66 21.36 103.83 246.94 293.66 21.37 103.83 246.94 293.66 21.38 103.83 246.94 293.66 21.39 103.83 246.94 293.66 21.40 103.83 246.94 293.66 21.41 103.83 246.94 293.66 21.42 103.83 246.94 21.43 103.83 246.94 110.00 21.44 103.83 246.94 110.00 21.45 103.83 110.00 110.00 21.46 103.83 110.00 110.00 21.47 103.83 110.00 110.00 21.48 103.83 110.00 110.00 21.49 110.00 110.00 293.66 21.50 110.00 110.00 293.66 21.51 110.00 110.00 293.66 21.52 110.00 110.00 293.66 21.53 110.00 110.00 293.66 21.54 110.00 110.00 293.66 21.55 110.00 110.00 293.66 21.56 110.00 110.00 293.66 21.57 110.00 110.00 293.66 21.58 110.00 110.00 293.66 21.59 110.00 110.00 293.66 21.60 110.00 110.00 293.66 21.61 110.00 110.00 293.66 21.62 110.00 110.00 293.66 21.63 110.00 110.00 293.66 21.64 110.00 110.00 293.66 21.65 110.00 110.00 293.66 21.66 110.00 110.00 293.66 261.63 21.67 110.00 110.00 293.66 261.63 21.68 110.00 110.00 293.66 261.63 21.69 110.00 110.00 261.63 21.70 110.00 110.00 261.63 261.63 21.71 110.00 110.00 261.63 261.63 21.72 110.00 110.00 261.63 261.63 21.73 110.00 110.00 261.63 261.63 21.74 110.00 110.00 261.63 261.63 21.75 110.00 110.00 261.63 261.63 21.76 110.00 110.00 261.63 261.63 21.77 110.00 110.00 261.63 261.63 21.78 110.00 110.00 261.63 261.63 21.79 110.00 110.00 261.63 261.63 21.80 110.00 110.00 261.63 261.63 21.81 110.00 110.00 261.63 261.63 21.82 110.00 110.00 261.63 261.63 21.83 110.00 110.00 261.63 261.63 21.84 110.00 261.63 261.63 21.85 110.00 261.63 261.63 21.86 110.00 261.63 261.63 21.87 110.00 261.63 261.63 21.88 110.00 261.63 261.63 329.63 21.89 110.00 261.63 261.63 329.63 329.63 21.90 110.00 261.63 261.63 329.63 329.63 21.91 110.00 261.63 261.63 329.63 329.63 21.92 110.00 261.63 329.63 329.63 21.93 110.00 329.63 329.63 21.94 110.00 329.63 329.63 21.95 110.00 329.63 329.63 21.96 110.00 329.63 329.63 21.97 110.00 329.63 329.63 21.98 110.00 329.63 329.63 21.99 110.00 329.63 329.63 22.00 110.00 329.63 329.63 22.01 110.00 329.63 329.63 22.02 110.00 329.63 329.63 22.03 110.00 329.63 329.63 22.04 110.00 329.63 329.63 22.05 110.00 329.63 329.63 22.06 110.00 329.63 329.63 22.07 110.00 329.63 329.63 440.00 22.08 110.00 329.63 440.00 22.09 110.00 329.63 440.00 22.10 110.00 329.63 440.00 415.30 22.11 110.00 329.63 440.00 415.30 22.12 110.00 440.00 415.30 22.13 110.00 440.00 415.30 22.14 110.00 440.00 415.30 22.15 110.00 440.00 415.30 22.16 110.00 440.00 415.30 22.17 110.00 440.00 415.30 22.18 110.00 440.00 415.30 22.19 110.00 440.00 415.30 22.20 110.00 440.00 415.30 22.21 110.00 440.00 415.30 22.22 110.00 440.00 415.30 22.23 110.00 440.00 415.30 22.24 110.00 440.00 415.30 22.25 110.00 440.00 415.30 22.26 110.00 415.30 523.25 22.27 110.00 415.30 523.25 440.00 22.28 110.00 523.25 440.00 22.29 110.00 523.25 440.00 22.30 110.00 523.25 440.00 22.31 110.00 523.25 440.00 22.32 110.00 523.25 440.00 22.33 110.00 523.25 440.00 22.34 110.00 523.25 440.00 22.35 110.00 523.25 440.00 22.36 110.00 523.25 440.00 22.37 110.00 523.25 440.00 22.38 110.00 523.25 440.00 22.39 110.00 523.25 440.00 22.40 110.00 523.25 440.00 22.41 110.00 523.25 440.00 22.42 110.00 523.25 440.00 22.43 110.00 523.25 440.00 22.44 110.00 440.00 523.25 22.45 110.00 440.00 523.25 261.63 22.46 110.00 440.00 523.25 261.63 22.47 110.00 440.00 523.25 261.63 22.48 110.00 523.25 261.63 22.49 110.00 523.25 261.63 22.50 110.00 523.25 261.63 22.51 110.00 523.25 261.63 22.52 110.00 523.25 261.63 22.53 110.00 523.25 261.63 22.54 110.00 523.25 261.63 22.55 110.00 523.25 261.63 22.56 110.00 523.25 261.63 22.57 110.00 523.25 261.63 22.58 110.00 523.25 261.63 22.59 110.00 523.25 261.63 103.83 22.60 110.00 523.25 261.63 103.83 22.61 110.00 523.25 261.63 103.83 659.26 22.62 110.00 523.25 261.63 103.83 659.26 103.83 22.63 523.25 261.63 103.83 659.26 103.83 22.64 523.25 261.63 103.83 659.26 103.83 22.65 523.25 103.83 659.26 103.83 22.66 523.25 103.83 659.26 103.83 22.67 523.25 103.83 659.26 103.83 493.88 22.68 523.25 103.83 659.26 103.83 493.88 22.69 103.83 659.26 103.83 493.88 207.65 22.70 103.83 659.26 103.83 493.88 207.65 22.71 103.83 659.26 103.83 493.88 207.65 22.72 103.83 659.26 103.83 493.88 207.65 22.73 103.83 659.26 103.83 493.88 207.65 22.74 103.83 659.26 103.83 493.88 207.65 22.75 103.83 659.26 103.83 493.88 207.65 22.76 103.83 659.26 103.83 493.88 207.65 22.77 103.83 659.26 103.83 493.88 207.65 22.78 103.83 659.26 103.83 493.88 207.65 22.79 103.83 659.26 103.83 493.88 207.65 22.80 103.83 659.26 103.83 493.88 207.65 22.81 103.83 659.26 103.83 493.88 207.65 22.82 103.83 659.26 103.83 493.88 207.65 22.83 103.83 659.26 103.83 493.88 207.65 246.94 22.84 103.83 659.26 103.83 493.88 207.65 246.94 22.85 103.83 659.26 103.83 493.88 207.65 246.94 22.86 103.83 659.26 103.83 493.88 207.65 246.94 22.87 103.83 659.26 103.83 493.88 207.65 246.94 22.88 103.83 659.26 103.83 493.88 207.65 246.94 22.89 103.83 659.26 103.83 493.88 207.65 246.94 22.90 103.83 659.26 103.83 493.88 207.65 246.94 22.91 103.83 659.26 103.83 493.88 207.65 246.94 22.92 103.83 659.26 103.83 493.88 207.65 246.94 22.93 103.83 659.26 103.83 493.88 207.65 246.94 22.94 103.83 659.26 103.83 493.88 207.65 246.94 22.95 103.83 659.26 103.83 493.88 207.65 246.94 22.96 103.83 659.26 103.83 493.88 207.65 246.94 22.97 103.83 659.26 103.83 493.88 207.65 246.94 22.98 103.83 659.26 103.83 493.88 207.65 246.94 22.99 103.83 659.26 103.83 493.88 207.65 246.94 23.00 103.83 659.26 103.83 493.88 207.65 246.94 23.01 103.83 659.26 103.83 493.88 207.65 246.94 23.02 659.26 103.83 493.88 207.65 246.94 293.66 23.03 659.26 103.83 493.88 207.65 246.94 293.66 23.04 659.26 103.83 493.88 207.65 246.94 293.66 23.05 659.26 103.83 493.88 207.65 293.66 23.06 659.26 103.83 493.88 207.65 293.66 23.07 659.26 103.83 493.88 207.65 293.66 23.08 659.26 103.83 493.88 207.65 293.66 23.09 659.26 103.83 493.88 207.65 293.66 23.10 659.26 103.83 493.88 207.65 293.66 23.11 659.26 103.83 493.88 207.65 293.66 23.12 659.26 103.83 493.88 207.65 293.66 23.13 659.26 103.83 493.88 207.65 293.66 23.14 659.26 103.83 493.88 207.65 293.66 23.15 659.26 103.83 493.88 207.65 293.66 23.16 659.26 103.83 493.88 207.65 293.66 23.17 659.26 103.83 493.88 207.65 293.66 698.46 23.18 659.26 103.83 493.88 207.65 293.66 698.46 23.19 659.26 103.83 493.88 207.65 293.66 698.46 23.20 659.26 103.83 493.88 207.65 293.66 698.46 23.21 103.83 493.88 207.65 293.66 698.46 23.22 103.83 493.88 207.65 293.66 698.46 329.63 23.23 103.83 493.88 207.65 293.66 698.46 329.63 23.24 103.83 493.88 207.65 698.46 329.63 23.25 103.83 493.88 207.65 698.46 329.63 23.26 103.83 493.88 207.65 698.46 329.63 23.27 103.83 493.88 207.65 698.46 329.63 23.28 103.83 493.88 207.65 698.46 329.63 23.29 103.83 493.88 207.65 698.46 329.63 23.30 103.83 493.88 207.65 698.46 329.63 23.31 103.83 493.88 207.65 698.46 329.63 23.32 103.83 493.88 207.65 698.46 329.63 23.33 103.83 493.88 207.65 698.46 329.63 23.34 103.83 493.88 207.65 698.46 329.63 23.35 103.83 493.88 207.65 698.46 329.63 23.36 103.83 493.88 207.65 698.46 329.63 23.37 103.83 493.88 207.65 698.46 329.63 23.38 103.83 493.88 207.65 698.46 23.39 103.83 493.88 207.65 659.26 23.40 103.83 493.88 207.65 659.26 23.41 103.83 493.88 207.65 659.26 493.88 23.42 103.83 493.88 207.65 659.26 493.88 23.43 103.83 493.88 207.65 659.26 493.88 23.44 103.83 493.88 207.65 659.26 493.88 23.45 103.83 493.88 207.65 659.26 493.88 23.46 103.83 493.88 207.65 659.26 493.88 23.47 103.83 493.88 207.65 659.26 493.88 23.48 103.83 493.88 207.65 659.26 493.88 23.49 103.83 493.88 207.65 659.26 493.88 23.50 103.83 493.88 207.65 659.26 493.88 23.51 103.83 493.88 207.65 659.26 493.88 23.52 103.83 493.88 207.65 659.26 493.88 23.53 103.83 493.88 207.65 659.26 493.88 23.54 103.83 493.88 207.65 659.26 493.88 23.55 103.83 493.88 207.65 659.26 493.88 23.56 103.83 493.88 207.65 659.26 493.88 23.57 103.83 493.88 207.65 659.26 493.88 587.33 23.58 103.83 493.88 207.65 659.26 493.88 587.33 23.59 103.83 493.88 207.65 659.26 493.88 587.33 23.60 103.83 493.88 207.65 493.88 587.33 246.94 23.61 103.83 493.88 207.65 493.88 587.33 246.94 23.62 103.83 493.88 207.65 493.88 587.33 246.94 23.63 103.83 493.88 207.65 493.88 587.33 246.94 23.64 103.83 493.88 207.65 587.33 246.94 23.65 103.83 493.88 207.65 587.33 246.94 23.66 103.83 493.88 207.65 587.33 246.94 23.67 103.83 493.88 207.65 587.33 246.94 23.68 103.83 493.88 207.65 587.33 246.94 23.69 103.83 493.88 207.65 587.33 246.94 23.70 103.83 493.88 207.65 246.94 23.71 103.83 493.88 207.65 246.94 23.72 103.83 493.88 207.65 246.94 23.73 103.83 493.88 207.65 246.94 23.74 103.83 493.88 207.65 246.94 23.75 103.83 493.88 207.65 246.94 23.76 103.83 493.88 207.65 246.94 23.77 103.83 493.88 207.65 246.94 110.00 110.00 23.78 103.83 493.88 207.65 246.94 110.00 110.00 587.33 23.79 103.83 493.88 207.65 246.94 110.00 110.00 587.33 220.00 23.80 207.65 246.94 110.00 110.00 587.33 220.00 23.81 246.94 110.00 110.00 587.33 220.00 23.82 110.00 110.00 587.33 220.00 23.83 110.00 110.00 587.33 220.00 23.84 110.00 110.00 587.33 220.00 23.85 110.00 110.00 587.33 220.00 23.86 110.00 110.00 587.33 220.00 23.87 110.00 110.00 587.33 220.00 23.88 110.00 110.00 587.33 220.00 23.89 110.00 110.00 587.33 220.00 23.90 110.00 110.00 587.33 220.00 23.91 110.00 110.00 587.33 220.00 23.92 110.00 110.00 587.33 220.00 329.63 23.93 110.00 110.00 587.33 220.00 329.63 23.94 110.00 110.00 587.33 220.00 329.63 23.95 110.00 110.00 587.33 220.00 329.63 23.96 110.00 110.00 220.00 329.63 23.97 110.00 110.00 220.00 329.63 523.25 23.98 110.00 110.00 220.00 329.63 523.25 23.99 110.00 110.00 220.00 329.63 523.25 261.63 24.00 110.00 110.00 220.00 329.63 523.25 261.63 24.01 110.00 110.00 220.00 329.63 523.25 261.63 24.02 110.00 110.00 220.00 329.63 523.25 261.63 24.03 110.00 110.00 220.00 329.63 523.25 261.63 24.04 110.00 110.00 220.00 329.63 523.25 261.63 24.05 110.00 110.00 220.00 329.63 523.25 261.63 24.06 110.00 110.00 220.00 329.63 523.25 261.63 24.07 110.00 110.00 220.00 329.63 523.25 261.63 24.08 110.00 110.00 220.00 329.63 523.25 261.63 24.09 110.00 110.00 220.00 329.63 523.25 261.63 24.10 110.00 110.00 220.00 329.63 523.25 261.63 24.11 110.00 110.00 220.00 329.63 523.25 261.63 24.12 110.00 110.00 220.00 329.63 523.25 261.63 24.13 110.00 110.00 220.00 329.63 523.25 261.63 24.14 110.00 110.00 220.00 329.63 523.25 261.63 24.15 110.00 110.00 220.00 329.63 523.25 261.63 659.26 24.16 110.00 110.00 220.00 329.63 523.25 261.63 659.26 24.17 110.00 110.00 220.00 329.63 523.25 261.63 659.26 24.18 110.00 110.00 220.00 329.63 523.25 261.63 659.26 329.63 24.19 110.00 110.00 220.00 329.63 261.63 659.26 329.63 24.20 110.00 220.00 329.63 261.63 659.26 329.63 24.21 110.00 220.00 329.63 659.26 329.63 24.22 110.00 220.00 329.63 659.26 329.63 24.23 110.00 220.00 329.63 659.26 329.63 24.24 110.00 220.00 329.63 659.26 329.63 24.25 110.00 220.00 329.63 659.26 329.63 24.26 110.00 220.00 329.63 659.26 329.63 24.27 110.00 220.00 329.63 659.26 329.63 24.28 110.00 220.00 329.63 659.26 329.63 24.29 110.00 220.00 329.63 659.26 329.63 24.30 110.00 220.00 329.63 659.26 329.63 24.31 110.00 220.00 329.63 659.26 329.63 24.32 110.00 220.00 329.63 659.26 329.63 24.33 110.00 220.00 329.63 659.26 329.63 24.34 110.00 220.00 329.63 659.26 329.63 24.35 110.00 220.00 329.63 659.26 329.63 880.00 24.36 110.00 220.00 329.63 659.26 329.63 880.00 440.00 24.37 110.00 220.00 329.63 659.26 329.63 880.00 440.00 24.38 110.00 220.00 329.63 880.00 440.00 24.39 110.00 220.00 329.63 880.00 440.00 24.40 110.00 220.00 329.63 880.00 440.00 24.41 110.00 220.00 329.63 880.00 440.00 24.42 110.00 220.00 329.63 880.00 440.00 24.43 110.00 220.00 329.63 880.00 440.00 24.44 110.00 220.00 329.63 880.00 440.00 24.45 110.00 220.00 329.63 880.00 440.00 24.46 110.00 220.00 329.63 880.00 440.00 24.47 110.00 220.00 329.63 880.00 440.00 24.48 110.00 220.00 329.63 880.00 440.00 24.49 110.00 220.00 329.63 880.00 440.00 24.50 110.00 220.00 329.63 880.00 440.00 24.51 110.00 220.00 329.63 880.00 440.00 24.52 110.00 220.00 329.63 880.00 440.00 24.53 110.00 220.00 329.63 880.00 440.00 24.54 110.00 220.00 329.63 880.00 440.00 1046.50 24.55 110.00 220.00 329.63 880.00 1046.50 24.56 110.00 220.00 329.63 880.00 1046.50 523.25 24.57 110.00 220.00 329.63 1046.50 523.25 24.58 220.00 329.63 1046.50 523.25 24.59 220.00 329.63 1046.50 523.25 24.60 220.00 329.63 1046.50 523.25 24.61 220.00 329.63 1046.50 523.25 24.62 220.00 329.63 1046.50 523.25 24.63 220.00 329.63 1046.50 523.25 24.64 220.00 329.63 1046.50 523.25 24.65 220.00 329.63 523.25 24.66 220.00 329.63 523.25 24.67 220.00 329.63 523.25 24.68 220.00 329.63 523.25 24.69 220.00 329.63 523.25 24.70 220.00 329.63 523.25 24.71 220.00 329.63 523.25 24.72 220.00 329.63 523.25 261.63 1046.50 24.73 220.00 329.63 523.25 261.63 1046.50 24.74 220.00 329.63 523.25 261.63 1046.50 24.75 220.00 329.63 523.25 261.63 1046.50 24.76 220.00 329.63 523.25 261.63 1046.50 24.77 220.00 329.63 261.63 1046.50 24.78 220.00 329.63 261.63 1046.50 24.79 220.00 329.63 261.63 1046.50 24.80 220.00 329.63 261.63 1046.50 24.81 220.00 329.63 261.63 1046.50 24.82 220.00 329.63 261.63 1046.50 24.83 220.00 329.63 261.63 24.84 220.00 329.63 261.63 24.85 220.00 329.63 261.63 24.86 220.00 329.63 24.87 220.00 24.88 220.00 24.89 220.00 24.90 220.00 1046.50 349.23 24.91 220.00 1046.50 349.23 24.92 220.00 1046.50 349.23 73.42 73.42 24.93 220.00 1046.50 349.23 73.42 73.42 146.83 24.94 220.00 1046.50 349.23 73.42 73.42 146.83 24.95 1046.50 349.23 73.42 73.42 146.83 24.96 1046.50 349.23 73.42 73.42 146.83 24.97 1046.50 349.23 73.42 73.42 146.83 24.98 1046.50 349.23 73.42 73.42 146.83 24.99 1046.50 349.23 73.42 73.42 146.83 25.00 1046.50 349.23 73.42 73.42 146.83 25.01 1046.50 349.23 73.42 73.42 146.83 146.83 25.02 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.03 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.04 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.05 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.06 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.07 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.08 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.09 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.10 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.11 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.12 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.13 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.14 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.15 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.16 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.17 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.18 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.19 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.20 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.21 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.22 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.23 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.24 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.25 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.26 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.27 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.28 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.29 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.30 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.31 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 493.88 25.32 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 493.88 25.33 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 493.88 25.34 1046.50 349.23 73.42 146.83 146.83 220.00 349.23 493.88 25.35 1046.50 349.23 73.42 146.83 146.83 220.00 349.23 493.88 25.36 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.37 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.38 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.39 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.40 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.41 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.42 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.43 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.44 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.45 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.46 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.47 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.48 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.49 349.23 73.42 146.83 146.83 220.00 493.88 987.77 25.50 349.23 73.42 146.83 146.83 220.00 493.88 987.77 587.33 25.51 349.23 73.42 146.83 146.83 220.00 493.88 987.77 587.33 25.52 349.23 73.42 146.83 146.83 220.00 493.88 987.77 587.33 25.53 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.54 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.55 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.56 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.57 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.58 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.59 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.60 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.61 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.62 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.63 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.64 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.65 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.66 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.67 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.68 349.23 73.42 146.83 146.83 220.00 987.77 587.33 1174.66 25.69 349.23 73.42 146.83 146.83 220.00 987.77 1174.66 25.70 349.23 73.42 146.83 146.83 220.00 987.77 1174.66 698.46 25.71 349.23 73.42 146.83 146.83 220.00 1174.66 698.46 25.72 349.23 73.42 146.83 146.83 220.00 1174.66 698.46 25.73 349.23 73.42 146.83 146.83 220.00 1174.66 698.46 25.74 349.23 73.42 146.83 146.83 220.00 1174.66 698.46 25.75 349.23 73.42 146.83 146.83 220.00 1174.66 698.46 25.76 349.23 73.42 146.83 146.83 220.00 1174.66 698.46 25.77 349.23 146.83 146.83 220.00 1174.66 698.46 25.78 349.23 146.83 220.00 1174.66 698.46 25.79 349.23 146.83 220.00 1174.66 698.46 25.80 349.23 146.83 220.00 1174.66 698.46 25.81 349.23 146.83 220.00 1174.66 698.46 25.82 349.23 146.83 220.00 1174.66 698.46 25.83 349.23 146.83 220.00 1174.66 698.46 25.84 349.23 146.83 220.00 1174.66 698.46 25.85 349.23 146.83 220.00 1174.66 698.46 25.86 349.23 146.83 220.00 1174.66 698.46 1396.91 25.87 349.23 146.83 220.00 698.46 1396.91 349.23 25.88 349.23 146.83 220.00 698.46 1396.91 349.23 25.89 349.23 146.83 220.00 698.46 1396.91 349.23 25.90 349.23 146.83 220.00 1396.91 349.23 25.91 349.23 146.83 1396.91 349.23 25.92 349.23 146.83 1396.91 349.23 25.93 349.23 146.83 1396.91 349.23 25.94 349.23 146.83 1396.91 349.23 25.95 349.23 146.83 1396.91 349.23 25.96 349.23 146.83 1396.91 349.23 25.97 349.23 146.83 349.23 25.98 146.83 349.23 25.99 146.83 349.23 26.00 146.83 349.23 26.01 146.83 349.23 26.02 146.83 349.23 26.03 146.83 349.23 82.41 440.00 82.41 261.63 26.04 146.83 349.23 82.41 440.00 82.41 261.63 164.81 26.05 146.83 349.23 82.41 440.00 82.41 261.63 164.81 26.06 146.83 82.41 440.00 82.41 261.63 164.81 26.07 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 26.08 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 26.09 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 26.10 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 26.11 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 26.12 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 26.13 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 26.14 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 164.81 26.15 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 164.81 26.16 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 164.81 26.17 82.41 440.00 82.41 261.63 164.81 1396.91 164.81 26.18 82.41 440.00 82.41 261.63 164.81 1396.91 164.81 26.19 82.41 440.00 82.41 261.63 164.81 164.81 26.20 82.41 440.00 82.41 261.63 164.81 164.81 26.21 82.41 440.00 82.41 261.63 164.81 164.81 26.22 82.41 440.00 82.41 261.63 164.81 164.81 26.23 82.41 440.00 82.41 261.63 164.81 164.81 26.24 82.41 440.00 82.41 261.63 164.81 164.81 26.25 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.26 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.27 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.28 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.29 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.30 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.31 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.32 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.33 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.34 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.35 82.41 440.00 82.41 261.63 164.81 164.81 329.63 26.36 82.41 440.00 82.41 261.63 164.81 164.81 329.63 26.37 82.41 440.00 82.41 261.63 164.81 164.81 329.63 26.38 82.41 440.00 82.41 261.63 164.81 164.81 329.63 26.39 82.41 440.00 82.41 261.63 164.81 164.81 329.63 26.40 82.41 440.00 82.41 261.63 164.81 164.81 329.63 26.41 82.41 440.00 82.41 261.63 164.81 164.81 329.63 26.42 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1174.66 26.43 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1174.66 26.44 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1174.66 26.45 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1174.66 440.00 26.46 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1174.66 440.00 26.47 440.00 82.41 261.63 164.81 164.81 329.63 1174.66 440.00 26.48 440.00 82.41 261.63 164.81 164.81 1174.66 440.00 26.49 440.00 82.41 261.63 164.81 164.81 1174.66 440.00 26.50 440.00 82.41 261.63 164.81 164.81 1174.66 440.00 26.51 440.00 82.41 261.63 164.81 164.81 1174.66 440.00 26.52 440.00 82.41 261.63 164.81 164.81 440.00 26.53 440.00 82.41 261.63 164.81 164.81 440.00 26.54 440.00 82.41 261.63 164.81 164.81 440.00 26.55 440.00 82.41 261.63 164.81 164.81 440.00 26.56 440.00 82.41 261.63 164.81 164.81 440.00 26.57 440.00 82.41 261.63 164.81 164.81 440.00 26.58 440.00 82.41 261.63 164.81 164.81 440.00 26.59 440.00 82.41 261.63 164.81 164.81 440.00 26.60 440.00 82.41 261.63 164.81 164.81 440.00 1046.50 26.61 440.00 82.41 261.63 164.81 164.81 440.00 1046.50 26.62 440.00 82.41 261.63 164.81 164.81 440.00 1046.50 26.63 440.00 82.41 261.63 164.81 164.81 440.00 1046.50 26.64 440.00 82.41 261.63 164.81 164.81 440.00 1046.50 523.25 26.65 440.00 82.41 261.63 164.81 164.81 440.00 1046.50 523.25 26.66 440.00 82.41 261.63 164.81 164.81 1046.50 523.25 26.67 440.00 82.41 261.63 164.81 164.81 1046.50 523.25 26.68 440.00 82.41 261.63 164.81 164.81 1046.50 523.25 26.69 440.00 82.41 261.63 164.81 164.81 523.25 26.70 440.00 82.41 261.63 164.81 164.81 523.25 26.71 440.00 82.41 261.63 164.81 164.81 523.25 26.72 440.00 82.41 261.63 164.81 164.81 523.25 26.73 440.00 82.41 261.63 164.81 164.81 523.25 26.74 440.00 82.41 261.63 164.81 523.25 26.75 440.00 82.41 261.63 164.81 523.25 26.76 440.00 82.41 261.63 164.81 523.25 26.77 440.00 82.41 261.63 164.81 523.25 987.77 26.78 440.00 82.41 261.63 164.81 523.25 987.77 26.79 440.00 82.41 261.63 164.81 523.25 987.77 26.80 440.00 82.41 261.63 164.81 523.25 987.77 26.81 440.00 82.41 261.63 164.81 523.25 987.77 26.82 440.00 82.41 261.63 164.81 523.25 987.77 659.26 26.83 440.00 261.63 164.81 987.77 659.26 26.84 440.00 261.63 164.81 987.77 659.26 26.85 440.00 261.63 164.81 987.77 659.26 26.86 440.00 261.63 164.81 659.26 26.87 440.00 261.63 164.81 659.26 26.88 440.00 261.63 164.81 659.26 26.89 440.00 164.81 659.26 26.90 440.00 164.81 659.26 26.91 440.00 164.81 659.26 26.92 440.00 164.81 659.26 26.93 440.00 164.81 659.26 26.94 440.00 164.81 659.26 880.00 26.95 440.00 164.81 659.26 880.00 26.96 440.00 164.81 659.26 880.00 26.97 440.00 164.81 659.26 880.00 164.81 26.98 440.00 164.81 659.26 880.00 164.81 26.99 440.00 164.81 659.26 164.81 27.00 440.00 164.81 659.26 164.81 27.01 440.00 164.81 659.26 164.81 27.02 440.00 164.81 659.26 164.81 27.03 440.00 164.81 659.26 164.81 27.04 440.00 164.81 659.26 164.81 27.05 440.00 164.81 659.26 164.81 27.06 440.00 164.81 659.26 164.81 27.07 440.00 164.81 164.81 27.08 440.00 164.81 164.81 27.09 440.00 164.81 164.81 27.10 440.00 164.81 164.81 27.11 164.81 164.81 27.12 164.81 164.81 27.13 164.81 164.81 830.61 27.14 164.81 164.81 830.61 82.41 27.15 164.81 164.81 830.61 82.41 27.16 164.81 164.81 830.61 82.41 329.63 82.41 27.17 164.81 830.61 82.41 329.63 82.41 27.18 164.81 830.61 82.41 329.63 82.41 27.19 164.81 830.61 82.41 329.63 82.41 329.63 493.88 27.20 164.81 82.41 329.63 82.41 329.63 493.88 27.21 164.81 82.41 329.63 82.41 329.63 493.88 27.22 164.81 82.41 329.63 82.41 329.63 493.88 27.23 164.81 82.41 329.63 82.41 329.63 493.88 27.24 164.81 82.41 329.63 82.41 329.63 493.88 27.25 164.81 82.41 329.63 82.41 329.63 493.88 27.26 164.81 82.41 329.63 82.41 329.63 493.88 27.27 164.81 82.41 329.63 82.41 329.63 493.88 27.28 164.81 82.41 329.63 82.41 329.63 493.88 27.29 164.81 82.41 329.63 82.41 329.63 493.88 27.30 164.81 82.41 329.63 82.41 329.63 493.88 27.31 164.81 82.41 329.63 82.41 329.63 493.88 27.32 164.81 82.41 329.63 82.41 329.63 493.88 698.46 27.33 164.81 82.41 329.63 82.41 329.63 493.88 698.46 415.30 27.34 164.81 82.41 329.63 82.41 329.63 493.88 698.46 415.30 27.35 164.81 82.41 329.63 82.41 329.63 493.88 698.46 415.30 27.36 164.81 82.41 329.63 82.41 329.63 493.88 698.46 415.30 27.37 164.81 82.41 329.63 82.41 329.63 493.88 698.46 415.30 27.38 164.81 82.41 329.63 82.41 329.63 493.88 698.46 415.30 27.39 164.81 82.41 329.63 82.41 329.63 493.88 698.46 415.30 27.40 164.81 82.41 329.63 82.41 329.63 493.88 698.46 415.30 27.41 164.81 82.41 329.63 82.41 329.63 493.88 415.30 27.42 164.81 82.41 329.63 82.41 329.63 493.88 415.30 27.43 164.81 82.41 329.63 82.41 329.63 493.88 415.30 27.44 164.81 82.41 329.63 82.41 329.63 493.88 415.30 27.45 164.81 82.41 329.63 82.41 329.63 493.88 415.30 27.46 164.81 82.41 329.63 82.41 329.63 493.88 415.30 27.47 164.81 82.41 329.63 82.41 329.63 493.88 415.30 659.26 27.48 164.81 82.41 329.63 82.41 329.63 493.88 415.30 659.26 27.49 164.81 82.41 329.63 82.41 329.63 493.88 415.30 659.26 27.50 164.81 82.41 329.63 82.41 329.63 493.88 415.30 659.26 27.51 164.81 82.41 329.63 82.41 329.63 493.88 415.30 659.26 27.52 164.81 82.41 329.63 82.41 329.63 493.88 415.30 659.26 27.53 164.81 82.41 329.63 82.41 329.63 493.88 415.30 659.26 493.88 27.54 164.81 82.41 329.63 82.41 329.63 493.88 415.30 659.26 493.88 27.55 164.81 82.41 329.63 82.41 329.63 493.88 659.26 493.88 27.56 164.81 82.41 329.63 82.41 329.63 493.88 493.88 27.57 164.81 329.63 82.41 329.63 493.88 493.88 27.58 164.81 329.63 82.41 329.63 493.88 493.88 27.59 164.81 329.63 82.41 329.63 493.88 493.88 27.60 164.81 329.63 82.41 329.63 493.88 493.88 27.61 164.81 329.63 82.41 329.63 493.88 493.88 27.62 164.81 329.63 82.41 329.63 493.88 493.88 27.63 164.81 329.63 82.41 329.63 493.88 493.88 27.64 164.81 329.63 82.41 329.63 493.88 493.88 27.65 164.81 329.63 82.41 329.63 493.88 493.88 27.66 164.81 329.63 82.41 329.63 493.88 493.88 587.33 27.67 164.81 329.63 82.41 329.63 493.88 493.88 587.33 27.68 164.81 329.63 82.41 329.63 493.88 493.88 587.33 27.69 164.81 329.63 82.41 329.63 493.88 493.88 587.33 27.70 164.81 329.63 82.41 329.63 493.88 493.88 587.33 27.71 164.81 329.63 82.41 329.63 493.88 587.33 659.26 27.72 164.81 329.63 82.41 329.63 493.88 587.33 659.26 27.73 164.81 329.63 82.41 329.63 493.88 587.33 659.26 27.74 164.81 329.63 82.41 329.63 493.88 587.33 659.26 27.75 164.81 329.63 82.41 329.63 493.88 659.26 27.76 164.81 329.63 82.41 329.63 493.88 659.26 27.77 164.81 329.63 82.41 329.63 493.88 659.26 27.78 164.81 329.63 82.41 329.63 493.88 659.26 27.79 164.81 329.63 82.41 329.63 493.88 659.26 27.80 164.81 329.63 82.41 329.63 493.88 659.26 27.81 164.81 329.63 82.41 329.63 493.88 659.26 27.82 82.41 329.63 493.88 659.26 27.83 82.41 329.63 493.88 659.26 523.25 27.84 82.41 329.63 493.88 523.25 27.85 82.41 329.63 493.88 523.25 27.86 82.41 329.63 493.88 523.25 27.87 82.41 329.63 493.88 523.25 27.88 82.41 329.63 493.88 523.25 415.30 27.89 82.41 329.63 493.88 523.25 415.30 27.90 329.63 523.25 415.30 830.61 27.91 329.63 523.25 415.30 830.61 27.92 329.63 523.25 415.30 830.61 27.93 329.63 415.30 830.61 27.94 415.30 830.61 27.95 415.30 830.61 27.96 415.30 830.61 27.97 415.30 830.61 27.98 415.30 830.61 27.99 415.30 28.00 415.30 28.01 415.30 493.88 28.02 415.30 493.88 28.03 415.30 493.88 28.04 415.30 493.88 28.05 415.30 493.88 28.06 415.30 493.88 28.07 415.30 493.88 164.81 28.08 415.30 493.88 164.81 28.09 415.30 164.81 28.10 415.30 164.81 28.11 415.30 164.81 28.12 415.30 164.81 28.13 415.30 164.81 28.14 415.30 164.81 28.15 415.30 164.81 28.16 415.30 164.81 28.17 415.30 164.81 28.18 415.30 164.81 28.19 415.30 164.81 164.81 440.00 28.20 415.30 164.81 164.81 440.00 28.21 415.30 164.81 164.81 440.00 440.00 28.22 415.30 164.81 164.81 440.00 440.00 28.23 415.30 164.81 164.81 440.00 440.00 110.00 28.24 415.30 164.81 164.81 440.00 440.00 110.00 28.25 415.30 164.81 440.00 440.00 110.00 28.26 415.30 164.81 440.00 440.00 110.00 28.27 415.30 164.81 440.00 440.00 110.00 110.00 220.00 123.47 28.28 164.81 440.00 440.00 110.00 110.00 220.00 123.47 28.29 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.30 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.31 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.32 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.33 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.34 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.35 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.36 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.37 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.38 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.39 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.40 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.41 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.42 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.43 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.44 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.45 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.46 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.47 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.48 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.49 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.50 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.51 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.52 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.53 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.54 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.55 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.56 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.57 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.58 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.59 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.60 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.61 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.62 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.63 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.64 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.65 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.66 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.67 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.68 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.69 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.70 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.71 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.72 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.73 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.74 440.00 110.00 220.00 880.00 440.00 220.00 28.75 440.00 110.00 220.00 880.00 440.00 220.00 28.76 440.00 110.00 220.00 880.00 440.00 220.00 28.77 440.00 110.00 220.00 880.00 440.00 220.00 28.78 440.00 110.00 220.00 880.00 440.00 220.00 28.79 440.00 110.00 220.00 880.00 440.00 220.00 28.80 440.00 110.00 220.00 880.00 440.00 220.00 28.81 440.00 110.00 220.00 880.00 440.00 220.00 28.82 440.00 110.00 220.00 880.00 440.00 220.00 28.83 440.00 110.00 220.00 880.00 440.00 220.00 28.84 440.00 110.00 220.00 880.00 440.00 220.00 28.85 440.00 110.00 880.00 440.00 220.00 28.86 440.00 110.00 880.00 220.00 28.87 440.00 110.00 880.00 220.00 28.88 440.00 110.00 880.00 220.00 28.89 440.00 880.00 220.00 28.90 440.00 220.00 28.91 440.00 220.00 28.92 440.00 220.00 28.93 220.00mir_eval-0.8.2/tests/data/multipitch/ref02.txt000066400000000000000000004410451475740344600212610ustar00rootroot000000000000000.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.30 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.40 0.41 0.42 0.43 0.44 0.45 0.46 0.47 0.48 0.49 0.50 0.51 0.52 0.53 0.54 0.55 0.56 0.57 0.58 0.59 0.60 0.61 0.62 0.63 0.64 0.65 0.66 0.67 0.68 0.69 0.70 0.71 0.72 0.73 0.74 0.75 0.76 0.77 0.78 0.79 0.80 0.81 0.82 0.83 0.84 0.85 0.86 0.87 0.88 0.89 0.90 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1.00 1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.10 1.11 1.12 1.13 1.14 1.15 1.16 1.17 1.18 1.19 1.20 1.21 1.22 1.23 1.24 1.25 1.26 1.27 1.28 1.29 1.30 1.31 1.32 1.33 1.34 1.35 1.36 1.37 1.38 1.39 1.40 1.41 1.42 1.43 1.44 1.45 1.46 1.47 1.48 1.49 1.50 1.51 1.52 1.53 1.54 1.55 1.56 1.57 1.58 1.59 1.60 1.61 1.62 1.63 1.64 1.65 1.66 1.67 1.68 1.69 1.70 1.71 1.72 1.73 1.74 1.75 1.76 1.77 1.78 1.79 1.80 1.81 1.82 1.83 1.84 1.85 1.86 1.87 1.88 1.89 1.90 1.91 1.92 1.93 1.94 1.95 1.96 1.97 1.98 1.99 2.00 2.01 2.02 2.03 2.04 2.05 2.06 2.07 2.08 2.09 2.10 2.11 2.12 2.13 2.14 2.15 2.16 2.17 2.18 2.19 2.20 2.21 2.22 2.23 2.24 2.25 2.26 2.27 2.28 2.29 2.30 2.31 2.32 2.33 2.34 2.35 2.36 2.37 2.38 2.39 2.40 2.41 2.42 2.43 2.44 2.45 2.46 2.47 2.48 2.49 2.50 2.51 2.52 2.53 2.54 2.55 2.56 2.57 2.58 2.59 2.60 2.61 2.62 2.63 69.30 138.59 207.65 2.64 69.30 138.59 207.65 2.65 69.30 138.59 207.65 2.66 69.30 138.59 207.65 2.67 69.30 138.59 207.65 2.68 69.30 138.59 207.65 2.69 69.30 138.59 207.65 2.70 69.30 138.59 207.65 2.71 69.30 138.59 207.65 2.72 69.30 138.59 207.65 2.73 69.30 138.59 207.65 2.74 69.30 138.59 207.65 2.75 69.30 138.59 207.65 2.76 69.30 138.59 207.65 2.77 69.30 138.59 207.65 2.78 69.30 138.59 207.65 2.79 69.30 138.59 207.65 2.80 69.30 138.59 207.65 2.81 69.30 138.59 207.65 2.82 69.30 138.59 207.65 2.83 69.30 138.59 207.65 2.84 69.30 138.59 207.65 2.85 69.30 138.59 207.65 2.86 69.30 138.59 207.65 2.87 69.30 138.59 207.65 2.88 69.30 138.59 207.65 2.89 69.30 138.59 207.65 2.90 69.30 138.59 207.65 2.91 69.30 138.59 207.65 2.92 69.30 138.59 207.65 2.93 69.30 138.59 207.65 2.94 69.30 138.59 207.65 2.95 69.30 138.59 207.65 2.96 69.30 138.59 207.65 2.97 69.30 138.59 207.65 2.98 69.30 138.59 207.65 2.99 69.30 138.59 207.65 3.00 69.30 138.59 207.65 3.01 69.30 138.59 207.65 3.02 69.30 138.59 207.65 3.03 69.30 138.59 207.65 3.04 69.30 138.59 207.65 3.05 69.30 138.59 207.65 3.06 69.30 138.59 207.65 3.07 69.30 138.59 207.65 3.08 69.30 138.59 207.65 3.09 69.30 138.59 207.65 3.10 69.30 138.59 207.65 3.11 69.30 138.59 207.65 3.12 69.30 138.59 207.65 3.13 69.30 138.59 3.14 69.30 138.59 277.18 3.15 69.30 138.59 277.18 3.16 69.30 138.59 277.18 3.17 69.30 138.59 277.18 3.18 69.30 138.59 277.18 3.19 69.30 138.59 277.18 3.20 69.30 138.59 277.18 3.21 69.30 138.59 277.18 3.22 69.30 138.59 277.18 3.23 69.30 138.59 277.18 3.24 69.30 138.59 277.18 3.25 69.30 138.59 277.18 3.26 69.30 138.59 277.18 3.27 69.30 138.59 277.18 3.28 69.30 138.59 277.18 3.29 69.30 138.59 277.18 3.30 69.30 138.59 277.18 3.31 69.30 138.59 277.18 3.32 69.30 138.59 277.18 3.33 69.30 138.59 277.18 3.34 69.30 138.59 277.18 3.35 69.30 138.59 277.18 3.36 69.30 138.59 277.18 3.37 69.30 138.59 277.18 3.38 69.30 138.59 277.18 3.39 69.30 138.59 277.18 3.40 69.30 138.59 277.18 3.41 69.30 138.59 277.18 3.42 69.30 138.59 277.18 3.43 69.30 138.59 277.18 3.44 69.30 138.59 277.18 3.45 69.30 138.59 277.18 3.46 69.30 138.59 277.18 3.47 69.30 138.59 277.18 3.48 69.30 138.59 277.18 3.49 69.30 138.59 277.18 3.50 69.30 138.59 277.18 3.51 69.30 138.59 277.18 3.52 69.30 138.59 277.18 3.53 69.30 138.59 277.18 3.54 69.30 138.59 277.18 3.55 69.30 138.59 277.18 3.56 69.30 138.59 277.18 3.57 69.30 138.59 277.18 3.58 69.30 138.59 277.18 3.59 69.30 138.59 277.18 3.60 69.30 138.59 277.18 3.61 69.30 138.59 277.18 3.62 69.30 138.59 277.18 3.63 69.30 138.59 277.18 3.64 69.30 138.59 277.18 3.65 69.30 138.59 277.18 329.63 3.66 69.30 138.59 277.18 329.63 3.67 69.30 138.59 277.18 329.63 3.68 69.30 138.59 329.63 3.69 69.30 138.59 329.63 3.70 69.30 138.59 329.63 3.71 69.30 138.59 329.63 3.72 69.30 138.59 329.63 3.73 69.30 138.59 329.63 3.74 69.30 138.59 329.63 3.75 69.30 138.59 329.63 3.76 69.30 138.59 329.63 3.77 69.30 138.59 329.63 3.78 69.30 138.59 329.63 3.79 69.30 138.59 329.63 3.80 69.30 138.59 329.63 3.81 69.30 138.59 329.63 3.82 69.30 138.59 329.63 3.83 69.30 138.59 329.63 3.84 69.30 138.59 329.63 3.85 69.30 138.59 329.63 3.86 69.30 138.59 329.63 3.87 69.30 138.59 329.63 3.88 69.30 138.59 329.63 3.89 69.30 138.59 329.63 3.90 69.30 138.59 329.63 3.91 69.30 138.59 329.63 3.92 69.30 138.59 329.63 3.93 69.30 138.59 329.63 3.94 69.30 138.59 329.63 3.95 69.30 138.59 329.63 3.96 69.30 138.59 329.63 3.97 69.30 138.59 329.63 3.98 69.30 138.59 329.63 3.99 69.30 138.59 329.63 4.00 69.30 138.59 329.63 4.01 69.30 138.59 329.63 4.02 69.30 138.59 329.63 4.03 69.30 138.59 329.63 4.04 69.30 138.59 329.63 4.05 69.30 138.59 329.63 4.06 69.30 138.59 329.63 4.07 69.30 138.59 329.63 4.08 69.30 138.59 329.63 4.09 69.30 138.59 329.63 4.10 69.30 138.59 329.63 4.11 69.30 138.59 329.63 4.12 69.30 138.59 329.63 4.13 69.30 138.59 329.63 4.14 69.30 138.59 329.63 4.15 69.30 138.59 329.63 207.65 4.16 69.30 138.59 329.63 207.65 4.17 69.30 138.59 207.65 4.18 69.30 138.59 207.65 4.19 69.30 138.59 207.65 4.20 69.30 138.59 207.65 4.21 69.30 138.59 207.65 4.22 69.30 138.59 207.65 4.23 69.30 138.59 207.65 4.24 69.30 138.59 207.65 4.25 69.30 138.59 207.65 4.26 69.30 138.59 207.65 4.27 69.30 138.59 207.65 4.28 69.30 138.59 207.65 4.29 69.30 138.59 207.65 4.30 69.30 138.59 207.65 4.31 69.30 138.59 207.65 4.32 69.30 138.59 207.65 4.33 69.30 138.59 207.65 4.34 69.30 138.59 207.65 4.35 69.30 138.59 207.65 4.36 69.30 138.59 207.65 4.37 69.30 138.59 207.65 4.38 69.30 138.59 207.65 4.39 69.30 138.59 207.65 4.40 69.30 138.59 207.65 4.41 69.30 138.59 207.65 4.42 69.30 138.59 207.65 4.43 69.30 138.59 207.65 4.44 69.30 138.59 207.65 4.45 69.30 138.59 207.65 4.46 69.30 138.59 207.65 4.47 69.30 138.59 207.65 4.48 69.30 138.59 207.65 4.49 69.30 138.59 207.65 4.50 69.30 138.59 207.65 4.51 69.30 138.59 207.65 4.52 69.30 138.59 207.65 4.53 69.30 138.59 207.65 4.54 69.30 138.59 207.65 4.55 69.30 138.59 207.65 4.56 69.30 138.59 207.65 4.57 69.30 138.59 207.65 4.58 69.30 138.59 207.65 4.59 69.30 138.59 207.65 4.60 69.30 138.59 207.65 4.61 69.30 138.59 207.65 4.62 69.30 138.59 207.65 4.63 69.30 138.59 207.65 4.64 69.30 138.59 207.65 4.65 69.30 138.59 207.65 4.66 69.30 138.59 207.65 277.18 4.67 69.30 138.59 207.65 277.18 4.68 69.30 138.59 207.65 277.18 4.69 69.30 138.59 207.65 277.18 4.70 69.30 138.59 207.65 277.18 4.71 69.30 138.59 207.65 277.18 4.72 69.30 138.59 277.18 4.73 69.30 138.59 277.18 4.74 69.30 138.59 277.18 4.75 69.30 138.59 277.18 4.76 69.30 138.59 277.18 4.77 69.30 138.59 277.18 4.78 69.30 138.59 277.18 4.79 69.30 138.59 277.18 4.80 69.30 138.59 277.18 4.81 69.30 138.59 277.18 4.82 69.30 138.59 277.18 4.83 69.30 138.59 277.18 4.84 69.30 138.59 277.18 4.85 69.30 138.59 277.18 4.86 69.30 138.59 277.18 4.87 69.30 138.59 277.18 4.88 69.30 138.59 277.18 4.89 69.30 138.59 277.18 4.90 69.30 138.59 277.18 4.91 69.30 138.59 277.18 4.92 69.30 138.59 277.18 4.93 69.30 138.59 277.18 4.94 69.30 138.59 277.18 4.95 69.30 138.59 277.18 4.96 69.30 138.59 277.18 4.97 69.30 138.59 277.18 4.98 69.30 138.59 277.18 4.99 69.30 138.59 277.18 5.00 69.30 138.59 277.18 5.01 69.30 138.59 277.18 5.02 69.30 138.59 277.18 5.03 69.30 138.59 277.18 5.04 69.30 138.59 277.18 5.05 69.30 138.59 277.18 5.06 69.30 138.59 277.18 5.07 69.30 138.59 277.18 5.08 69.30 138.59 277.18 5.09 69.30 138.59 277.18 5.10 69.30 138.59 277.18 5.11 69.30 138.59 277.18 329.63 5.12 69.30 138.59 277.18 329.63 5.13 69.30 138.59 277.18 329.63 5.14 69.30 138.59 329.63 5.15 69.30 138.59 329.63 5.16 69.30 138.59 329.63 5.17 69.30 138.59 329.63 5.18 69.30 138.59 329.63 5.19 69.30 138.59 329.63 5.20 69.30 138.59 329.63 5.21 69.30 138.59 329.63 5.22 69.30 138.59 329.63 5.23 69.30 138.59 329.63 5.24 69.30 138.59 329.63 5.25 69.30 138.59 329.63 5.26 69.30 138.59 329.63 5.27 69.30 138.59 329.63 5.28 69.30 138.59 329.63 5.29 69.30 138.59 329.63 5.30 69.30 138.59 329.63 5.31 69.30 138.59 329.63 5.32 69.30 138.59 329.63 5.33 69.30 138.59 329.63 5.34 69.30 138.59 329.63 5.35 69.30 138.59 329.63 5.36 69.30 138.59 329.63 5.37 69.30 138.59 329.63 5.38 69.30 138.59 329.63 5.39 69.30 138.59 329.63 5.40 69.30 138.59 329.63 5.41 69.30 138.59 329.63 5.42 69.30 138.59 329.63 5.43 69.30 138.59 329.63 5.44 69.30 138.59 329.63 5.45 69.30 138.59 329.63 5.46 69.30 138.59 329.63 5.47 69.30 138.59 329.63 5.48 69.30 138.59 329.63 5.49 69.30 138.59 329.63 5.50 69.30 138.59 329.63 5.51 69.30 138.59 329.63 5.52 69.30 138.59 329.63 5.53 69.30 138.59 329.63 5.54 69.30 138.59 329.63 5.55 69.30 138.59 329.63 5.56 69.30 138.59 329.63 5.57 69.30 138.59 329.63 5.58 69.30 138.59 329.63 5.59 69.30 138.59 329.63 5.60 69.30 138.59 329.63 207.65 5.61 69.30 138.59 207.65 5.62 69.30 138.59 207.65 5.63 69.30 138.59 207.65 5.64 69.30 138.59 207.65 5.65 69.30 138.59 207.65 5.66 69.30 138.59 207.65 5.67 69.30 138.59 207.65 5.68 69.30 138.59 207.65 5.69 69.30 138.59 207.65 5.70 69.30 138.59 207.65 5.71 69.30 138.59 207.65 5.72 69.30 138.59 207.65 5.73 69.30 138.59 207.65 5.74 69.30 138.59 207.65 5.75 69.30 138.59 207.65 5.76 69.30 138.59 207.65 5.77 69.30 138.59 207.65 5.78 69.30 138.59 207.65 5.79 69.30 138.59 207.65 5.80 69.30 138.59 207.65 5.81 69.30 138.59 207.65 5.82 69.30 138.59 207.65 5.83 69.30 138.59 207.65 5.84 69.30 138.59 207.65 5.85 69.30 138.59 207.65 5.86 69.30 138.59 207.65 5.87 69.30 138.59 207.65 5.88 69.30 138.59 207.65 5.89 69.30 138.59 207.65 5.90 69.30 138.59 207.65 5.91 69.30 138.59 207.65 5.92 69.30 138.59 207.65 5.93 69.30 138.59 207.65 5.94 69.30 138.59 207.65 5.95 69.30 138.59 207.65 5.96 69.30 138.59 207.65 5.97 69.30 138.59 207.65 5.98 69.30 138.59 207.65 5.99 69.30 138.59 207.65 6.00 69.30 138.59 207.65 6.01 69.30 138.59 207.65 6.02 69.30 138.59 207.65 6.03 69.30 138.59 207.65 6.04 69.30 138.59 207.65 6.05 69.30 138.59 207.65 6.06 69.30 138.59 207.65 277.18 6.07 69.30 138.59 207.65 277.18 6.08 69.30 138.59 207.65 277.18 6.09 69.30 138.59 207.65 277.18 6.10 69.30 138.59 207.65 277.18 6.11 69.30 138.59 207.65 277.18 6.12 69.30 138.59 207.65 277.18 6.13 69.30 138.59 207.65 277.18 6.14 69.30 138.59 277.18 6.15 69.30 138.59 277.18 6.16 69.30 138.59 277.18 6.17 69.30 138.59 277.18 6.18 69.30 138.59 277.18 6.19 69.30 138.59 277.18 6.20 69.30 138.59 277.18 6.21 69.30 138.59 277.18 6.22 69.30 138.59 277.18 6.23 69.30 138.59 277.18 6.24 69.30 138.59 277.18 6.25 69.30 138.59 277.18 6.26 69.30 138.59 277.18 6.27 69.30 138.59 277.18 6.28 69.30 138.59 277.18 6.29 69.30 138.59 277.18 6.30 69.30 138.59 277.18 6.31 69.30 138.59 277.18 6.32 69.30 138.59 277.18 6.33 69.30 138.59 277.18 6.34 69.30 138.59 277.18 6.35 69.30 138.59 277.18 6.36 69.30 138.59 277.18 6.37 69.30 138.59 277.18 6.38 69.30 138.59 277.18 6.39 69.30 138.59 277.18 6.40 69.30 138.59 277.18 6.41 69.30 138.59 277.18 6.42 69.30 138.59 277.18 6.43 69.30 138.59 277.18 6.44 69.30 138.59 277.18 6.45 69.30 138.59 277.18 6.46 69.30 138.59 277.18 6.47 69.30 138.59 277.18 6.48 69.30 138.59 277.18 6.49 69.30 138.59 277.18 329.63 6.50 69.30 138.59 277.18 329.63 6.51 69.30 138.59 277.18 329.63 6.52 69.30 138.59 277.18 329.63 6.53 69.30 138.59 277.18 329.63 6.54 69.30 138.59 329.63 6.55 69.30 138.59 329.63 6.56 69.30 138.59 329.63 6.57 69.30 138.59 329.63 6.58 69.30 138.59 329.63 6.59 69.30 138.59 329.63 6.60 69.30 138.59 329.63 6.61 69.30 138.59 329.63 6.62 69.30 138.59 329.63 6.63 69.30 138.59 329.63 6.64 69.30 138.59 329.63 6.65 69.30 138.59 329.63 6.66 69.30 138.59 329.63 6.67 69.30 138.59 329.63 6.68 69.30 138.59 329.63 6.69 69.30 138.59 329.63 6.70 69.30 138.59 329.63 6.71 69.30 138.59 329.63 6.72 69.30 138.59 329.63 6.73 69.30 138.59 329.63 6.74 69.30 138.59 329.63 6.75 69.30 138.59 329.63 6.76 69.30 138.59 329.63 6.77 69.30 138.59 329.63 6.78 69.30 138.59 329.63 6.79 69.30 138.59 329.63 6.80 69.30 138.59 329.63 6.81 69.30 138.59 329.63 6.82 69.30 138.59 329.63 6.83 69.30 138.59 329.63 6.84 69.30 138.59 329.63 6.85 69.30 138.59 329.63 6.86 69.30 138.59 329.63 6.87 69.30 138.59 329.63 6.88 69.30 138.59 329.63 6.89 69.30 138.59 329.63 6.90 69.30 138.59 329.63 6.91 69.30 138.59 329.63 6.92 69.30 138.59 329.63 6.93 69.30 138.59 329.63 6.94 69.30 138.59 329.63 6.95 69.30 138.59 329.63 6.96 69.30 138.59 329.63 6.97 69.30 138.59 329.63 207.65 6.98 69.30 138.59 207.65 6.99 69.30 138.59 207.65 7.00 69.30 138.59 207.65 7.01 69.30 138.59 207.65 7.02 69.30 138.59 207.65 7.03 69.30 138.59 207.65 7.04 69.30 138.59 207.65 7.05 69.30 138.59 207.65 7.06 69.30 138.59 207.65 7.07 69.30 138.59 207.65 7.08 69.30 138.59 207.65 7.09 69.30 138.59 207.65 7.10 69.30 138.59 207.65 7.11 69.30 138.59 207.65 7.12 69.30 138.59 207.65 7.13 69.30 138.59 207.65 7.14 69.30 138.59 207.65 7.15 69.30 138.59 207.65 7.16 69.30 138.59 207.65 7.17 69.30 138.59 207.65 7.18 69.30 138.59 207.65 7.19 69.30 138.59 207.65 7.20 69.30 138.59 207.65 7.21 69.30 138.59 207.65 7.22 69.30 138.59 207.65 7.23 69.30 138.59 207.65 7.24 69.30 138.59 207.65 7.25 69.30 138.59 207.65 7.26 69.30 138.59 207.65 7.27 69.30 138.59 207.65 7.28 69.30 138.59 207.65 7.29 69.30 138.59 207.65 7.30 69.30 138.59 207.65 7.31 69.30 138.59 207.65 7.32 69.30 138.59 207.65 7.33 69.30 138.59 207.65 7.34 69.30 138.59 207.65 7.35 69.30 138.59 207.65 7.36 69.30 138.59 207.65 7.37 69.30 138.59 207.65 7.38 69.30 138.59 207.65 7.39 69.30 138.59 207.65 7.40 69.30 138.59 207.65 7.41 69.30 138.59 207.65 7.42 69.30 138.59 207.65 7.43 69.30 138.59 207.65 7.44 69.30 138.59 207.65 277.18 7.45 69.30 138.59 207.65 277.18 7.46 69.30 138.59 207.65 277.18 7.47 69.30 138.59 207.65 277.18 7.48 69.30 138.59 207.65 277.18 7.49 69.30 138.59 207.65 277.18 7.50 69.30 138.59 207.65 277.18 7.51 69.30 138.59 277.18 7.52 69.30 138.59 277.18 7.53 69.30 138.59 277.18 7.54 69.30 138.59 277.18 7.55 69.30 138.59 277.18 7.56 69.30 138.59 277.18 7.57 69.30 138.59 277.18 7.58 69.30 138.59 277.18 7.59 69.30 138.59 277.18 7.60 69.30 138.59 277.18 7.61 69.30 138.59 277.18 7.62 69.30 138.59 277.18 7.63 69.30 138.59 277.18 7.64 69.30 138.59 277.18 7.65 69.30 138.59 277.18 7.66 69.30 138.59 277.18 7.67 69.30 138.59 277.18 7.68 69.30 138.59 277.18 7.69 69.30 138.59 277.18 7.70 69.30 138.59 277.18 7.71 69.30 138.59 277.18 7.72 69.30 138.59 277.18 7.73 69.30 138.59 277.18 7.74 69.30 138.59 277.18 7.75 69.30 138.59 277.18 7.76 69.30 138.59 277.18 7.77 69.30 138.59 277.18 7.78 69.30 138.59 277.18 7.79 69.30 138.59 277.18 7.80 69.30 138.59 277.18 7.81 69.30 138.59 277.18 7.82 69.30 138.59 277.18 7.83 69.30 138.59 277.18 7.84 69.30 138.59 277.18 7.85 69.30 138.59 277.18 7.86 69.30 138.59 277.18 7.87 69.30 138.59 277.18 7.88 69.30 138.59 277.18 7.89 69.30 138.59 277.18 7.90 69.30 138.59 277.18 7.91 69.30 138.59 277.18 7.92 69.30 138.59 277.18 7.93 69.30 138.59 277.18 329.63 7.94 69.30 138.59 277.18 329.63 7.95 69.30 138.59 277.18 329.63 7.96 69.30 138.59 277.18 329.63 7.97 69.30 138.59 277.18 329.63 7.98 69.30 138.59 329.63 7.99 69.30 138.59 329.63 8.00 69.30 138.59 329.63 8.01 69.30 138.59 329.63 8.02 69.30 138.59 329.63 8.03 69.30 138.59 329.63 8.04 69.30 138.59 329.63 8.05 69.30 138.59 329.63 8.06 69.30 138.59 329.63 8.07 69.30 138.59 329.63 8.08 69.30 138.59 329.63 8.09 69.30 138.59 329.63 8.10 69.30 138.59 329.63 8.11 69.30 138.59 329.63 8.12 69.30 138.59 329.63 8.13 69.30 138.59 329.63 8.14 69.30 138.59 329.63 8.15 69.30 138.59 329.63 8.16 69.30 138.59 329.63 8.17 69.30 138.59 329.63 8.18 69.30 138.59 329.63 8.19 69.30 138.59 329.63 8.20 69.30 138.59 329.63 8.21 69.30 138.59 329.63 8.22 69.30 138.59 329.63 8.23 69.30 138.59 329.63 8.24 69.30 138.59 329.63 8.25 69.30 138.59 329.63 8.26 69.30 138.59 329.63 8.27 69.30 138.59 329.63 8.28 69.30 138.59 329.63 8.29 69.30 138.59 329.63 8.30 69.30 138.59 329.63 8.31 69.30 138.59 329.63 8.32 69.30 138.59 329.63 8.33 69.30 138.59 329.63 8.34 69.30 138.59 329.63 8.35 69.30 138.59 329.63 8.36 69.30 138.59 329.63 8.37 69.30 138.59 329.63 8.38 69.30 329.63 8.39 69.30 329.63 8.40 69.30 329.63 8.41 69.30 329.63 8.42 69.30 329.63 8.43 69.30 329.63 8.44 69.30 329.63 8.45 69.30 329.63 8.46 69.30 329.63 8.47 69.30 329.63 8.48 69.30 329.63 8.49 69.30 329.63 8.50 8.51 61.74 123.47 207.65 8.52 61.74 123.47 207.65 8.53 61.74 123.47 207.65 8.54 61.74 123.47 207.65 8.55 61.74 123.47 207.65 8.56 61.74 123.47 207.65 8.57 61.74 123.47 207.65 8.58 61.74 123.47 207.65 8.59 61.74 123.47 207.65 8.60 61.74 123.47 207.65 8.61 61.74 123.47 207.65 8.62 61.74 123.47 207.65 8.63 61.74 123.47 207.65 8.64 61.74 123.47 207.65 8.65 61.74 123.47 207.65 8.66 61.74 123.47 207.65 8.67 61.74 123.47 207.65 8.68 61.74 123.47 207.65 8.69 61.74 123.47 207.65 8.70 61.74 123.47 207.65 8.71 61.74 123.47 207.65 8.72 61.74 123.47 207.65 8.73 61.74 123.47 207.65 8.74 61.74 123.47 207.65 8.75 61.74 123.47 207.65 8.76 61.74 123.47 207.65 8.77 61.74 123.47 207.65 8.78 61.74 123.47 207.65 8.79 61.74 123.47 207.65 8.80 61.74 123.47 207.65 8.81 61.74 123.47 207.65 8.82 61.74 123.47 207.65 8.83 61.74 123.47 207.65 8.84 61.74 123.47 207.65 8.85 61.74 123.47 207.65 8.86 61.74 123.47 207.65 8.87 61.74 123.47 207.65 8.88 61.74 123.47 207.65 8.89 61.74 123.47 207.65 8.90 61.74 123.47 207.65 8.91 61.74 123.47 207.65 8.92 61.74 123.47 207.65 8.93 61.74 123.47 207.65 8.94 61.74 123.47 207.65 8.95 61.74 123.47 207.65 8.96 61.74 123.47 207.65 8.97 61.74 123.47 207.65 8.98 61.74 123.47 207.65 8.99 61.74 123.47 207.65 9.00 61.74 123.47 207.65 9.01 61.74 123.47 207.65 9.02 61.74 123.47 207.65 9.03 61.74 123.47 207.65 9.04 61.74 123.47 207.65 277.18 9.05 61.74 123.47 207.65 277.18 9.06 61.74 123.47 207.65 277.18 9.07 61.74 123.47 207.65 277.18 9.08 61.74 123.47 207.65 277.18 9.09 61.74 123.47 207.65 277.18 9.10 61.74 123.47 277.18 9.11 61.74 123.47 277.18 9.12 61.74 123.47 277.18 9.13 61.74 123.47 277.18 9.14 61.74 123.47 277.18 9.15 61.74 123.47 277.18 9.16 61.74 123.47 277.18 9.17 61.74 123.47 277.18 9.18 61.74 123.47 277.18 9.19 61.74 123.47 277.18 9.20 61.74 123.47 277.18 9.21 61.74 123.47 277.18 9.22 61.74 123.47 277.18 9.23 61.74 123.47 277.18 9.24 61.74 123.47 277.18 9.25 61.74 123.47 277.18 9.26 61.74 123.47 277.18 9.27 61.74 123.47 277.18 9.28 61.74 123.47 277.18 9.29 61.74 123.47 277.18 9.30 61.74 123.47 277.18 9.31 61.74 123.47 277.18 9.32 61.74 123.47 277.18 9.33 61.74 123.47 277.18 9.34 61.74 123.47 277.18 9.35 61.74 123.47 277.18 9.36 61.74 123.47 277.18 9.37 61.74 123.47 277.18 9.38 61.74 123.47 277.18 9.39 61.74 123.47 277.18 9.40 61.74 123.47 277.18 9.41 61.74 123.47 277.18 9.42 61.74 123.47 277.18 9.43 61.74 123.47 277.18 9.44 61.74 123.47 277.18 9.45 61.74 123.47 277.18 9.46 61.74 123.47 277.18 9.47 61.74 123.47 277.18 9.48 61.74 123.47 277.18 9.49 61.74 123.47 277.18 9.50 61.74 123.47 277.18 9.51 61.74 123.47 277.18 9.52 61.74 123.47 277.18 9.53 61.74 123.47 277.18 9.54 61.74 123.47 277.18 9.55 61.74 123.47 277.18 9.56 61.74 123.47 277.18 329.63 9.57 61.74 123.47 277.18 329.63 9.58 61.74 123.47 277.18 329.63 9.59 61.74 123.47 277.18 329.63 9.60 61.74 123.47 329.63 9.61 61.74 123.47 329.63 9.62 61.74 123.47 329.63 9.63 61.74 123.47 329.63 9.64 61.74 123.47 329.63 9.65 61.74 123.47 329.63 9.66 61.74 123.47 329.63 9.67 61.74 123.47 329.63 9.68 61.74 123.47 329.63 9.69 61.74 123.47 329.63 9.70 61.74 123.47 329.63 9.71 61.74 123.47 329.63 9.72 61.74 123.47 329.63 9.73 61.74 123.47 329.63 9.74 61.74 123.47 329.63 9.75 61.74 123.47 329.63 9.76 61.74 123.47 329.63 9.77 61.74 123.47 329.63 9.78 61.74 123.47 329.63 9.79 61.74 123.47 329.63 9.80 61.74 123.47 329.63 9.81 61.74 123.47 329.63 9.82 61.74 123.47 329.63 9.83 61.74 123.47 329.63 9.84 61.74 123.47 329.63 9.85 61.74 123.47 329.63 9.86 61.74 123.47 329.63 9.87 61.74 123.47 329.63 9.88 61.74 123.47 329.63 9.89 61.74 123.47 329.63 9.90 61.74 123.47 329.63 9.91 61.74 123.47 329.63 9.92 61.74 123.47 329.63 9.93 61.74 123.47 329.63 9.94 61.74 123.47 329.63 9.95 61.74 123.47 329.63 9.96 61.74 123.47 329.63 9.97 61.74 123.47 329.63 9.98 61.74 123.47 329.63 9.99 61.74 123.47 329.63 10.00 61.74 123.47 329.63 10.01 61.74 123.47 329.63 10.02 61.74 123.47 329.63 10.03 61.74 123.47 329.63 10.04 61.74 123.47 329.63 10.05 61.74 123.47 329.63 10.06 61.74 123.47 329.63 10.07 61.74 123.47 329.63 207.65 10.08 61.74 123.47 329.63 207.65 10.09 61.74 123.47 329.63 207.65 10.10 61.74 123.47 207.65 10.11 61.74 123.47 207.65 10.12 61.74 123.47 207.65 10.13 61.74 123.47 207.65 10.14 61.74 123.47 207.65 10.15 61.74 123.47 207.65 10.16 61.74 123.47 207.65 10.17 61.74 123.47 207.65 10.18 61.74 123.47 207.65 10.19 61.74 123.47 207.65 10.20 61.74 123.47 207.65 10.21 61.74 123.47 207.65 10.22 61.74 123.47 207.65 10.23 61.74 123.47 207.65 10.24 61.74 123.47 207.65 10.25 61.74 123.47 207.65 10.26 61.74 123.47 207.65 10.27 61.74 123.47 207.65 10.28 61.74 123.47 207.65 10.29 61.74 123.47 207.65 10.30 61.74 123.47 207.65 10.31 61.74 123.47 207.65 10.32 61.74 123.47 207.65 10.33 61.74 123.47 207.65 10.34 61.74 123.47 207.65 10.35 61.74 123.47 207.65 10.36 61.74 123.47 207.65 10.37 61.74 123.47 207.65 10.38 61.74 123.47 207.65 10.39 61.74 123.47 207.65 10.40 61.74 123.47 207.65 10.41 61.74 123.47 207.65 10.42 61.74 123.47 207.65 10.43 61.74 123.47 207.65 10.44 61.74 123.47 207.65 10.45 61.74 123.47 207.65 10.46 61.74 123.47 207.65 10.47 61.74 123.47 207.65 10.48 61.74 123.47 207.65 10.49 61.74 123.47 207.65 10.50 61.74 123.47 207.65 10.51 61.74 123.47 207.65 10.52 61.74 123.47 207.65 10.53 61.74 123.47 207.65 10.54 61.74 123.47 207.65 277.18 10.55 61.74 123.47 207.65 277.18 10.56 61.74 123.47 207.65 277.18 10.57 61.74 123.47 207.65 277.18 10.58 61.74 123.47 207.65 277.18 10.59 61.74 123.47 207.65 277.18 10.60 61.74 123.47 207.65 277.18 10.61 61.74 123.47 277.18 10.62 61.74 123.47 277.18 10.63 61.74 123.47 277.18 10.64 61.74 123.47 277.18 10.65 61.74 123.47 277.18 10.66 61.74 123.47 277.18 10.67 61.74 123.47 277.18 10.68 61.74 123.47 277.18 10.69 61.74 123.47 277.18 10.70 61.74 123.47 277.18 10.71 61.74 123.47 277.18 10.72 61.74 123.47 277.18 10.73 61.74 123.47 277.18 10.74 61.74 123.47 277.18 10.75 61.74 123.47 277.18 10.76 61.74 123.47 277.18 10.77 61.74 123.47 277.18 10.78 61.74 123.47 277.18 10.79 61.74 123.47 277.18 10.80 61.74 123.47 277.18 10.81 61.74 123.47 277.18 10.82 61.74 123.47 277.18 10.83 61.74 123.47 277.18 10.84 61.74 123.47 277.18 10.85 61.74 123.47 277.18 10.86 61.74 123.47 277.18 10.87 61.74 123.47 277.18 10.88 61.74 123.47 277.18 10.89 61.74 123.47 277.18 10.90 61.74 123.47 277.18 10.91 61.74 123.47 277.18 10.92 61.74 123.47 277.18 10.93 61.74 123.47 277.18 10.94 61.74 123.47 277.18 10.95 61.74 123.47 277.18 10.96 61.74 123.47 277.18 10.97 61.74 123.47 277.18 10.98 61.74 123.47 277.18 10.99 61.74 123.47 277.18 11.00 61.74 123.47 277.18 11.01 61.74 123.47 277.18 11.02 61.74 123.47 277.18 11.03 61.74 123.47 277.18 329.63 11.04 61.74 123.47 277.18 329.63 11.05 61.74 123.47 277.18 329.63 11.06 61.74 123.47 329.63 11.07 61.74 123.47 329.63 11.08 61.74 123.47 329.63 11.09 61.74 123.47 329.63 11.10 61.74 123.47 329.63 11.11 61.74 123.47 329.63 11.12 61.74 123.47 329.63 11.13 61.74 123.47 329.63 11.14 61.74 123.47 329.63 11.15 61.74 123.47 329.63 11.16 61.74 123.47 329.63 11.17 61.74 123.47 329.63 11.18 61.74 123.47 329.63 11.19 61.74 123.47 329.63 11.20 61.74 123.47 329.63 11.21 61.74 123.47 329.63 11.22 61.74 123.47 329.63 11.23 61.74 123.47 329.63 11.24 61.74 123.47 329.63 11.25 61.74 123.47 329.63 11.26 61.74 123.47 329.63 11.27 61.74 123.47 329.63 11.28 61.74 123.47 329.63 11.29 61.74 123.47 329.63 11.30 61.74 123.47 329.63 11.31 61.74 123.47 329.63 11.32 61.74 123.47 329.63 11.33 61.74 123.47 329.63 11.34 61.74 123.47 329.63 11.35 61.74 123.47 329.63 11.36 61.74 123.47 329.63 11.37 61.74 123.47 329.63 11.38 61.74 123.47 329.63 11.39 61.74 123.47 329.63 11.40 61.74 123.47 329.63 11.41 61.74 123.47 329.63 11.42 61.74 123.47 329.63 11.43 61.74 123.47 329.63 11.44 61.74 123.47 329.63 11.45 61.74 123.47 329.63 11.46 61.74 123.47 329.63 11.47 61.74 123.47 329.63 11.48 61.74 123.47 329.63 11.49 61.74 123.47 329.63 11.50 61.74 123.47 329.63 11.51 61.74 123.47 329.63 11.52 61.74 123.47 329.63 11.53 61.74 123.47 329.63 207.65 11.54 61.74 123.47 329.63 207.65 11.55 61.74 123.47 207.65 11.56 61.74 123.47 207.65 11.57 61.74 123.47 207.65 11.58 61.74 123.47 207.65 11.59 61.74 123.47 207.65 11.60 61.74 123.47 207.65 11.61 61.74 123.47 207.65 11.62 61.74 123.47 207.65 11.63 61.74 123.47 207.65 11.64 61.74 123.47 207.65 11.65 61.74 123.47 207.65 11.66 61.74 123.47 207.65 11.67 61.74 123.47 207.65 11.68 61.74 123.47 207.65 11.69 61.74 123.47 207.65 11.70 61.74 123.47 207.65 11.71 61.74 123.47 207.65 11.72 61.74 123.47 207.65 11.73 61.74 123.47 207.65 11.74 61.74 123.47 207.65 11.75 61.74 123.47 207.65 11.76 61.74 123.47 207.65 11.77 61.74 123.47 207.65 11.78 61.74 123.47 207.65 11.79 61.74 123.47 207.65 11.80 61.74 123.47 207.65 11.81 61.74 123.47 207.65 11.82 61.74 123.47 207.65 11.83 61.74 123.47 207.65 11.84 61.74 123.47 207.65 11.85 61.74 123.47 207.65 11.86 61.74 123.47 207.65 11.87 61.74 123.47 207.65 11.88 61.74 123.47 207.65 11.89 61.74 123.47 207.65 11.90 61.74 123.47 207.65 11.91 61.74 123.47 207.65 11.92 61.74 123.47 207.65 11.93 61.74 123.47 207.65 11.94 61.74 123.47 207.65 11.95 61.74 123.47 207.65 11.96 61.74 123.47 207.65 11.97 61.74 123.47 207.65 11.98 61.74 123.47 207.65 11.99 61.74 123.47 207.65 12.00 61.74 123.47 207.65 277.18 12.01 61.74 123.47 207.65 277.18 12.02 61.74 123.47 207.65 277.18 12.03 61.74 123.47 207.65 277.18 12.04 61.74 123.47 207.65 277.18 12.05 61.74 123.47 207.65 277.18 12.06 61.74 123.47 277.18 12.07 61.74 123.47 277.18 12.08 61.74 123.47 277.18 12.09 61.74 123.47 277.18 12.10 61.74 123.47 277.18 12.11 61.74 123.47 277.18 12.12 61.74 123.47 277.18 12.13 61.74 123.47 277.18 12.14 61.74 123.47 277.18 12.15 61.74 123.47 277.18 12.16 61.74 123.47 277.18 12.17 61.74 123.47 277.18 12.18 61.74 123.47 277.18 12.19 61.74 123.47 277.18 12.20 61.74 123.47 277.18 12.21 61.74 123.47 277.18 12.22 61.74 123.47 277.18 12.23 61.74 123.47 277.18 12.24 61.74 123.47 277.18 12.25 61.74 123.47 277.18 12.26 61.74 123.47 277.18 12.27 61.74 123.47 277.18 12.28 61.74 123.47 277.18 12.29 61.74 123.47 277.18 12.30 61.74 123.47 277.18 12.31 61.74 123.47 277.18 12.32 61.74 123.47 277.18 12.33 61.74 123.47 277.18 12.34 61.74 123.47 277.18 12.35 61.74 123.47 277.18 12.36 61.74 123.47 277.18 12.37 61.74 123.47 277.18 12.38 61.74 123.47 277.18 12.39 61.74 123.47 277.18 12.40 61.74 123.47 277.18 12.41 61.74 123.47 277.18 12.42 61.74 123.47 277.18 12.43 61.74 123.47 277.18 12.44 61.74 123.47 277.18 12.45 61.74 123.47 277.18 12.46 61.74 123.47 277.18 12.47 61.74 123.47 277.18 329.63 12.48 61.74 123.47 277.18 329.63 12.49 61.74 123.47 277.18 329.63 12.50 61.74 123.47 277.18 329.63 12.51 61.74 123.47 329.63 12.52 61.74 123.47 329.63 12.53 61.74 123.47 329.63 12.54 61.74 123.47 329.63 12.55 61.74 123.47 329.63 12.56 61.74 123.47 329.63 12.57 61.74 123.47 329.63 12.58 61.74 123.47 329.63 12.59 61.74 123.47 329.63 12.60 61.74 123.47 329.63 12.61 61.74 123.47 329.63 12.62 61.74 123.47 329.63 12.63 61.74 123.47 329.63 12.64 61.74 123.47 329.63 12.65 61.74 123.47 329.63 12.66 61.74 123.47 329.63 12.67 61.74 123.47 329.63 12.68 61.74 123.47 329.63 12.69 61.74 123.47 329.63 12.70 61.74 123.47 329.63 12.71 61.74 123.47 329.63 12.72 61.74 123.47 329.63 12.73 61.74 123.47 329.63 12.74 61.74 123.47 329.63 12.75 61.74 123.47 329.63 12.76 61.74 123.47 329.63 12.77 61.74 123.47 329.63 12.78 61.74 123.47 329.63 12.79 61.74 123.47 329.63 12.80 61.74 123.47 329.63 12.81 61.74 123.47 329.63 12.82 61.74 123.47 329.63 12.83 61.74 123.47 329.63 12.84 61.74 123.47 329.63 12.85 61.74 123.47 329.63 12.86 61.74 123.47 329.63 12.87 61.74 123.47 329.63 12.88 61.74 123.47 329.63 12.89 61.74 123.47 329.63 12.90 61.74 123.47 329.63 12.91 61.74 123.47 329.63 12.92 61.74 123.47 329.63 12.93 61.74 123.47 329.63 12.94 61.74 123.47 329.63 12.95 61.74 123.47 329.63 12.96 61.74 123.47 207.65 12.97 61.74 123.47 207.65 12.98 61.74 123.47 207.65 12.99 61.74 123.47 207.65 13.00 61.74 123.47 207.65 13.01 61.74 123.47 207.65 13.02 61.74 123.47 207.65 13.03 61.74 123.47 207.65 13.04 61.74 123.47 207.65 13.05 61.74 123.47 207.65 13.06 61.74 123.47 207.65 13.07 61.74 123.47 207.65 13.08 61.74 123.47 207.65 13.09 61.74 123.47 207.65 13.10 61.74 123.47 207.65 13.11 61.74 123.47 207.65 13.12 61.74 123.47 207.65 13.13 61.74 123.47 207.65 13.14 61.74 123.47 207.65 13.15 61.74 123.47 207.65 13.16 61.74 123.47 207.65 13.17 61.74 123.47 207.65 13.18 61.74 123.47 207.65 13.19 61.74 123.47 207.65 13.20 61.74 123.47 207.65 13.21 61.74 123.47 207.65 13.22 61.74 123.47 207.65 13.23 61.74 123.47 207.65 13.24 61.74 123.47 207.65 13.25 61.74 123.47 207.65 13.26 61.74 123.47 207.65 13.27 61.74 123.47 207.65 13.28 61.74 123.47 207.65 13.29 61.74 123.47 207.65 13.30 61.74 123.47 207.65 13.31 61.74 123.47 207.65 13.32 61.74 123.47 207.65 13.33 61.74 123.47 207.65 13.34 61.74 123.47 207.65 13.35 61.74 123.47 207.65 13.36 61.74 123.47 207.65 13.37 61.74 123.47 207.65 13.38 61.74 123.47 207.65 13.39 61.74 123.47 207.65 277.18 13.40 61.74 123.47 207.65 277.18 13.41 61.74 123.47 207.65 277.18 13.42 61.74 123.47 207.65 277.18 13.43 61.74 123.47 207.65 277.18 13.44 61.74 123.47 207.65 277.18 13.45 61.74 123.47 207.65 277.18 13.46 61.74 123.47 277.18 13.47 61.74 123.47 277.18 13.48 61.74 123.47 277.18 13.49 61.74 123.47 277.18 13.50 61.74 123.47 277.18 13.51 61.74 123.47 277.18 13.52 61.74 123.47 277.18 13.53 61.74 123.47 277.18 13.54 61.74 123.47 277.18 13.55 61.74 123.47 277.18 13.56 61.74 123.47 277.18 13.57 61.74 123.47 277.18 13.58 61.74 123.47 277.18 13.59 61.74 123.47 277.18 13.60 61.74 123.47 277.18 13.61 61.74 123.47 277.18 13.62 61.74 123.47 277.18 13.63 61.74 123.47 277.18 13.64 61.74 123.47 277.18 13.65 61.74 123.47 277.18 13.66 61.74 123.47 277.18 13.67 61.74 123.47 277.18 13.68 61.74 123.47 277.18 13.69 61.74 123.47 277.18 13.70 61.74 123.47 277.18 13.71 61.74 123.47 277.18 13.72 61.74 123.47 277.18 13.73 61.74 123.47 277.18 13.74 61.74 123.47 277.18 13.75 61.74 123.47 277.18 13.76 61.74 123.47 277.18 13.77 61.74 123.47 277.18 13.78 61.74 123.47 277.18 13.79 61.74 123.47 277.18 13.80 61.74 277.18 13.81 61.74 277.18 13.82 61.74 277.18 13.83 61.74 277.18 13.84 61.74 277.18 13.85 61.74 277.18 13.86 277.18 13.87 277.18 13.88 277.18 13.89 277.18 13.90 277.18 329.63 13.91 277.18 329.63 13.92 277.18 329.63 13.93 277.18 329.63 13.94 277.18 329.63 13.95 329.63 13.96 329.63 13.97 329.63 13.98 329.63 13.99 329.63 14.00 329.63 14.01 329.63 14.02 329.63 14.03 329.63 14.04 329.63 14.05 329.63 14.06 329.63 14.07 329.63 14.08 329.63 14.09 329.63 14.10 329.63 14.11 329.63 14.12 329.63 14.13 329.63 14.14 329.63 14.15 329.63 14.16 329.63 14.17 329.63 14.18 329.63 14.19 329.63 14.20 329.63 14.21 329.63 14.22 329.63 14.23 329.63 14.24 329.63 14.25 329.63 14.26 329.63 14.27 329.63 14.28 329.63 14.29 329.63 14.30 329.63 14.31 329.63 14.32 329.63 14.33 329.63 14.34 329.63 14.35 329.63 14.36 329.63 14.37 329.63 14.38 329.63 14.39 329.63 14.40 329.63 14.41 14.42 220.00 14.43 220.00 55.00 110.00 14.44 220.00 55.00 110.00 14.45 220.00 55.00 110.00 14.46 220.00 55.00 110.00 14.47 220.00 55.00 110.00 14.48 220.00 55.00 110.00 14.49 220.00 55.00 110.00 14.50 220.00 55.00 110.00 14.51 220.00 55.00 110.00 14.52 220.00 55.00 110.00 14.53 220.00 55.00 110.00 14.54 220.00 55.00 110.00 14.55 220.00 55.00 110.00 14.56 220.00 55.00 110.00 14.57 220.00 55.00 110.00 14.58 220.00 55.00 110.00 14.59 220.00 55.00 110.00 14.60 220.00 55.00 110.00 14.61 220.00 55.00 110.00 14.62 220.00 55.00 110.00 14.63 220.00 55.00 110.00 14.64 220.00 55.00 110.00 14.65 220.00 55.00 110.00 14.66 220.00 55.00 110.00 14.67 220.00 55.00 110.00 14.68 220.00 55.00 110.00 14.69 220.00 55.00 110.00 14.70 220.00 55.00 110.00 14.71 220.00 55.00 110.00 14.72 220.00 55.00 110.00 14.73 220.00 55.00 110.00 14.74 220.00 55.00 110.00 14.75 220.00 55.00 110.00 14.76 220.00 55.00 110.00 14.77 220.00 55.00 110.00 14.78 220.00 55.00 110.00 14.79 220.00 55.00 110.00 14.80 220.00 55.00 110.00 14.81 220.00 55.00 110.00 14.82 220.00 55.00 110.00 14.83 220.00 55.00 110.00 14.84 220.00 55.00 110.00 14.85 220.00 55.00 110.00 14.86 220.00 55.00 110.00 14.87 220.00 55.00 110.00 14.88 220.00 55.00 110.00 14.89 220.00 55.00 110.00 14.90 220.00 55.00 110.00 14.91 220.00 55.00 110.00 14.92 220.00 55.00 110.00 14.93 220.00 55.00 110.00 14.94 220.00 55.00 110.00 14.95 220.00 55.00 110.00 14.96 220.00 55.00 110.00 14.97 220.00 55.00 110.00 14.98 220.00 55.00 110.00 14.99 220.00 55.00 110.00 277.18 15.00 220.00 55.00 110.00 277.18 15.01 220.00 55.00 110.00 277.18 15.02 220.00 55.00 110.00 277.18 15.03 220.00 55.00 110.00 277.18 15.04 220.00 55.00 110.00 277.18 15.05 220.00 55.00 110.00 277.18 15.06 220.00 55.00 110.00 277.18 15.07 55.00 110.00 277.18 15.08 55.00 110.00 277.18 15.09 55.00 110.00 277.18 15.10 55.00 110.00 277.18 15.11 55.00 110.00 277.18 15.12 55.00 110.00 277.18 15.13 55.00 110.00 277.18 15.14 55.00 110.00 277.18 15.15 55.00 110.00 277.18 15.16 55.00 110.00 277.18 15.17 55.00 110.00 277.18 15.18 55.00 110.00 277.18 15.19 55.00 110.00 277.18 15.20 55.00 110.00 277.18 15.21 55.00 110.00 277.18 15.22 55.00 110.00 277.18 15.23 55.00 110.00 277.18 15.24 55.00 110.00 277.18 15.25 55.00 110.00 277.18 15.26 55.00 110.00 277.18 15.27 55.00 110.00 277.18 15.28 55.00 110.00 277.18 15.29 55.00 110.00 277.18 15.30 55.00 110.00 277.18 15.31 55.00 110.00 277.18 15.32 55.00 110.00 277.18 15.33 55.00 110.00 277.18 15.34 55.00 110.00 277.18 15.35 55.00 110.00 277.18 15.36 55.00 110.00 277.18 15.37 55.00 110.00 277.18 15.38 55.00 110.00 277.18 15.39 55.00 110.00 277.18 15.40 55.00 110.00 277.18 15.41 55.00 110.00 277.18 15.42 55.00 110.00 277.18 15.43 55.00 110.00 277.18 15.44 55.00 110.00 277.18 15.45 55.00 110.00 277.18 15.46 55.00 110.00 277.18 15.47 55.00 110.00 277.18 15.48 55.00 110.00 277.18 15.49 55.00 110.00 277.18 329.63 15.50 55.00 110.00 277.18 329.63 15.51 55.00 110.00 277.18 329.63 15.52 55.00 110.00 329.63 15.53 55.00 110.00 329.63 15.54 55.00 110.00 329.63 15.55 55.00 110.00 329.63 15.56 55.00 110.00 329.63 15.57 55.00 110.00 329.63 15.58 55.00 110.00 329.63 15.59 55.00 110.00 329.63 15.60 55.00 110.00 329.63 15.61 55.00 110.00 329.63 15.62 55.00 110.00 329.63 15.63 55.00 110.00 329.63 15.64 55.00 110.00 329.63 15.65 55.00 110.00 329.63 15.66 55.00 110.00 329.63 15.67 55.00 110.00 329.63 15.68 55.00 110.00 329.63 15.69 55.00 110.00 329.63 15.70 55.00 110.00 329.63 15.71 55.00 110.00 329.63 15.72 55.00 110.00 329.63 15.73 55.00 110.00 329.63 15.74 55.00 110.00 329.63 15.75 55.00 110.00 329.63 15.76 55.00 110.00 329.63 15.77 55.00 110.00 329.63 15.78 55.00 110.00 329.63 15.79 55.00 110.00 329.63 15.80 55.00 110.00 329.63 15.81 55.00 110.00 329.63 15.82 55.00 110.00 329.63 15.83 55.00 110.00 329.63 15.84 55.00 110.00 329.63 15.85 55.00 110.00 329.63 15.86 55.00 110.00 329.63 15.87 55.00 110.00 329.63 15.88 55.00 110.00 329.63 15.89 55.00 110.00 329.63 15.90 55.00 110.00 329.63 15.91 55.00 110.00 329.63 15.92 55.00 110.00 329.63 15.93 55.00 110.00 329.63 15.94 55.00 110.00 329.63 15.95 55.00 110.00 329.63 15.96 55.00 110.00 329.63 15.97 55.00 110.00 329.63 15.98 55.00 110.00 329.63 15.99 55.00 110.00 329.63 220.00 16.00 55.00 110.00 329.63 220.00 16.01 55.00 110.00 329.63 220.00 16.02 55.00 110.00 329.63 220.00 16.03 55.00 110.00 329.63 220.00 16.04 55.00 110.00 220.00 16.05 55.00 110.00 220.00 16.06 55.00 110.00 220.00 16.07 55.00 110.00 220.00 16.08 55.00 110.00 220.00 16.09 55.00 110.00 220.00 16.10 55.00 110.00 220.00 16.11 55.00 110.00 220.00 16.12 55.00 110.00 220.00 16.13 55.00 110.00 220.00 16.14 55.00 110.00 220.00 16.15 55.00 110.00 220.00 16.16 55.00 110.00 220.00 16.17 55.00 110.00 220.00 16.18 55.00 110.00 220.00 16.19 55.00 110.00 220.00 16.20 55.00 110.00 220.00 16.21 55.00 110.00 220.00 16.22 55.00 110.00 220.00 16.23 55.00 110.00 220.00 16.24 55.00 110.00 220.00 16.25 55.00 110.00 220.00 16.26 55.00 110.00 220.00 16.27 55.00 110.00 220.00 16.28 55.00 110.00 220.00 16.29 55.00 110.00 220.00 16.30 55.00 110.00 220.00 16.31 55.00 110.00 220.00 16.32 55.00 110.00 220.00 16.33 55.00 110.00 220.00 16.34 55.00 110.00 220.00 16.35 55.00 110.00 220.00 16.36 55.00 110.00 220.00 16.37 55.00 110.00 220.00 16.38 55.00 110.00 220.00 16.39 55.00 110.00 220.00 16.40 55.00 110.00 220.00 16.41 55.00 110.00 220.00 16.42 55.00 110.00 220.00 16.43 55.00 110.00 220.00 16.44 55.00 110.00 220.00 16.45 55.00 110.00 220.00 16.46 55.00 110.00 220.00 16.47 55.00 110.00 220.00 277.18 16.48 55.00 110.00 220.00 277.18 16.49 55.00 110.00 220.00 277.18 16.50 55.00 110.00 220.00 277.18 16.51 55.00 110.00 220.00 277.18 16.52 55.00 110.00 220.00 277.18 16.53 55.00 110.00 220.00 277.18 16.54 55.00 110.00 277.18 16.55 55.00 110.00 277.18 16.56 55.00 110.00 277.18 16.57 55.00 110.00 277.18 16.58 55.00 110.00 277.18 16.59 55.00 110.00 277.18 16.60 55.00 110.00 277.18 16.61 55.00 110.00 277.18 16.62 55.00 110.00 277.18 16.63 55.00 110.00 277.18 16.64 55.00 110.00 277.18 16.65 55.00 110.00 277.18 16.66 55.00 110.00 277.18 16.67 55.00 110.00 277.18 16.68 55.00 110.00 277.18 16.69 55.00 110.00 277.18 16.70 55.00 110.00 277.18 16.71 55.00 110.00 277.18 16.72 55.00 110.00 277.18 16.73 55.00 110.00 277.18 16.74 55.00 110.00 277.18 16.75 55.00 110.00 277.18 16.76 55.00 110.00 277.18 16.77 55.00 110.00 277.18 16.78 55.00 110.00 277.18 16.79 55.00 110.00 277.18 16.80 55.00 110.00 277.18 16.81 55.00 110.00 277.18 16.82 55.00 110.00 277.18 16.83 55.00 110.00 277.18 16.84 55.00 110.00 277.18 16.85 55.00 110.00 277.18 16.86 55.00 110.00 277.18 16.87 55.00 110.00 277.18 16.88 55.00 110.00 277.18 16.89 55.00 110.00 277.18 16.90 55.00 110.00 277.18 16.91 55.00 110.00 277.18 16.92 55.00 110.00 277.18 16.93 55.00 277.18 16.94 55.00 277.18 16.95 55.00 277.18 16.96 55.00 277.18 16.97 55.00 277.18 329.63 16.98 277.18 329.63 16.99 277.18 329.63 17.00 277.18 329.63 17.01 329.63 17.02 329.63 17.03 329.63 17.04 329.63 17.05 329.63 17.06 329.63 17.07 329.63 17.08 329.63 17.09 329.63 17.10 329.63 17.11 329.63 17.12 329.63 17.13 329.63 17.14 329.63 17.15 329.63 17.16 329.63 17.17 329.63 17.18 329.63 17.19 329.63 17.20 329.63 17.21 329.63 17.22 329.63 17.23 329.63 17.24 329.63 17.25 329.63 17.26 329.63 17.27 329.63 17.28 329.63 17.29 329.63 17.30 329.63 17.31 329.63 17.32 329.63 17.33 329.63 17.34 329.63 17.35 329.63 17.36 329.63 17.37 329.63 17.38 329.63 17.39 329.63 17.40 329.63 17.41 329.63 17.42 329.63 17.43 329.63 17.44 329.63 17.45 329.63 17.46 329.63 17.47 329.63 92.50 17.48 329.63 92.50 46.25 17.49 92.50 46.25 220.00 17.50 92.50 46.25 220.00 17.51 92.50 46.25 220.00 17.52 92.50 46.25 220.00 17.53 92.50 46.25 220.00 17.54 92.50 46.25 220.00 17.55 92.50 46.25 220.00 17.56 92.50 46.25 220.00 17.57 92.50 46.25 220.00 17.58 92.50 46.25 220.00 17.59 92.50 46.25 220.00 17.60 92.50 46.25 220.00 17.61 92.50 46.25 220.00 17.62 92.50 46.25 220.00 17.63 92.50 46.25 220.00 17.64 92.50 46.25 220.00 17.65 92.50 46.25 220.00 17.66 92.50 46.25 220.00 17.67 92.50 46.25 220.00 17.68 92.50 46.25 220.00 17.69 92.50 46.25 220.00 17.70 92.50 46.25 220.00 17.71 92.50 46.25 220.00 17.72 92.50 46.25 220.00 17.73 92.50 46.25 220.00 17.74 92.50 46.25 220.00 17.75 92.50 46.25 220.00 17.76 92.50 46.25 220.00 17.77 92.50 46.25 220.00 17.78 92.50 46.25 220.00 17.79 92.50 46.25 220.00 17.80 92.50 46.25 220.00 17.81 92.50 46.25 220.00 17.82 92.50 46.25 220.00 17.83 92.50 46.25 220.00 17.84 92.50 46.25 220.00 17.85 92.50 46.25 220.00 17.86 92.50 46.25 220.00 17.87 92.50 46.25 220.00 17.88 92.50 46.25 220.00 17.89 92.50 46.25 220.00 17.90 92.50 46.25 220.00 17.91 92.50 46.25 220.00 17.92 92.50 46.25 220.00 17.93 92.50 46.25 220.00 17.94 92.50 46.25 220.00 17.95 92.50 46.25 220.00 17.96 92.50 46.25 220.00 17.97 92.50 46.25 220.00 17.98 92.50 46.25 220.00 17.99 92.50 46.25 220.00 18.00 92.50 46.25 220.00 18.01 92.50 46.25 220.00 18.02 92.50 46.25 220.00 18.03 92.50 46.25 220.00 18.04 92.50 46.25 220.00 18.05 92.50 46.25 220.00 293.66 18.06 92.50 46.25 220.00 293.66 18.07 92.50 46.25 220.00 293.66 18.08 92.50 46.25 220.00 293.66 18.09 92.50 46.25 220.00 293.66 18.10 92.50 46.25 220.00 293.66 18.11 92.50 46.25 220.00 293.66 18.12 92.50 46.25 220.00 293.66 18.13 92.50 46.25 220.00 293.66 18.14 92.50 46.25 220.00 293.66 18.15 92.50 46.25 293.66 18.16 92.50 46.25 293.66 18.17 92.50 46.25 293.66 18.18 92.50 46.25 293.66 18.19 92.50 46.25 293.66 18.20 92.50 46.25 293.66 18.21 92.50 46.25 293.66 18.22 92.50 46.25 293.66 18.23 92.50 46.25 293.66 18.24 92.50 46.25 293.66 18.25 92.50 46.25 293.66 18.26 92.50 46.25 293.66 18.27 92.50 46.25 293.66 18.28 92.50 46.25 293.66 18.29 92.50 46.25 293.66 18.30 92.50 46.25 293.66 18.31 92.50 46.25 293.66 18.32 92.50 46.25 293.66 18.33 92.50 46.25 293.66 18.34 92.50 46.25 293.66 18.35 92.50 46.25 293.66 18.36 92.50 46.25 293.66 18.37 92.50 46.25 293.66 18.38 92.50 46.25 293.66 18.39 92.50 46.25 293.66 18.40 92.50 46.25 293.66 18.41 92.50 46.25 293.66 18.42 92.50 46.25 293.66 18.43 92.50 46.25 293.66 18.44 92.50 46.25 293.66 18.45 92.50 46.25 293.66 18.46 92.50 46.25 293.66 18.47 92.50 46.25 293.66 18.48 92.50 46.25 293.66 18.49 92.50 46.25 293.66 18.50 92.50 46.25 293.66 18.51 92.50 46.25 293.66 18.52 92.50 46.25 293.66 18.53 92.50 46.25 293.66 369.99 18.54 92.50 46.25 293.66 369.99 18.55 92.50 46.25 293.66 369.99 18.56 92.50 46.25 369.99 18.57 92.50 46.25 369.99 18.58 92.50 46.25 369.99 18.59 92.50 46.25 369.99 18.60 92.50 46.25 369.99 18.61 92.50 46.25 369.99 18.62 92.50 46.25 369.99 18.63 92.50 46.25 369.99 18.64 92.50 46.25 369.99 18.65 92.50 46.25 369.99 18.66 92.50 46.25 369.99 18.67 92.50 46.25 369.99 18.68 92.50 46.25 369.99 18.69 92.50 46.25 369.99 18.70 92.50 46.25 369.99 18.71 92.50 46.25 369.99 18.72 92.50 46.25 369.99 18.73 92.50 46.25 369.99 18.74 92.50 46.25 369.99 18.75 92.50 46.25 369.99 18.76 92.50 46.25 369.99 18.77 92.50 46.25 369.99 18.78 92.50 46.25 369.99 18.79 92.50 46.25 369.99 18.80 92.50 46.25 369.99 18.81 92.50 46.25 369.99 18.82 92.50 46.25 369.99 18.83 92.50 46.25 369.99 18.84 92.50 46.25 369.99 18.85 92.50 46.25 369.99 18.86 92.50 46.25 369.99 18.87 92.50 46.25 369.99 18.88 92.50 46.25 369.99 18.89 92.50 46.25 369.99 18.90 92.50 46.25 369.99 18.91 92.50 46.25 369.99 18.92 92.50 46.25 369.99 18.93 92.50 46.25 369.99 18.94 92.50 46.25 369.99 18.95 92.50 46.25 369.99 18.96 92.50 46.25 369.99 18.97 92.50 46.25 369.99 18.98 92.50 46.25 369.99 18.99 92.50 46.25 369.99 19.00 92.50 46.25 369.99 220.00 19.01 92.50 46.25 369.99 220.00 19.02 92.50 46.25 369.99 220.00 19.03 92.50 46.25 369.99 220.00 19.04 92.50 46.25 369.99 220.00 19.05 92.50 46.25 369.99 220.00 19.06 92.50 46.25 220.00 19.07 92.50 46.25 220.00 19.08 92.50 46.25 220.00 19.09 92.50 46.25 220.00 19.10 92.50 46.25 220.00 19.11 92.50 46.25 220.00 19.12 92.50 46.25 220.00 19.13 92.50 46.25 220.00 19.14 92.50 46.25 220.00 19.15 92.50 46.25 220.00 19.16 92.50 46.25 220.00 19.17 92.50 46.25 220.00 19.18 92.50 46.25 220.00 19.19 92.50 46.25 220.00 19.20 92.50 46.25 220.00 19.21 92.50 46.25 220.00 19.22 92.50 46.25 220.00 19.23 92.50 46.25 220.00 19.24 92.50 46.25 220.00 19.25 92.50 46.25 220.00 19.26 92.50 46.25 220.00 19.27 92.50 46.25 220.00 19.28 92.50 46.25 220.00 19.29 92.50 46.25 220.00 19.30 92.50 46.25 220.00 19.31 92.50 46.25 220.00 19.32 92.50 46.25 220.00 19.33 92.50 46.25 220.00 19.34 92.50 46.25 220.00 19.35 92.50 46.25 220.00 19.36 92.50 46.25 220.00 19.37 92.50 46.25 220.00 19.38 92.50 46.25 220.00 19.39 92.50 46.25 220.00 19.40 92.50 46.25 220.00 19.41 92.50 46.25 220.00 19.42 92.50 46.25 220.00 19.43 92.50 46.25 220.00 19.44 92.50 46.25 220.00 293.66 19.45 92.50 46.25 220.00 293.66 19.46 92.50 46.25 220.00 293.66 19.47 92.50 46.25 220.00 293.66 19.48 92.50 46.25 220.00 293.66 19.49 92.50 46.25 220.00 293.66 19.50 92.50 46.25 220.00 293.66 19.51 92.50 46.25 293.66 19.52 92.50 46.25 293.66 19.53 92.50 46.25 293.66 19.54 92.50 46.25 293.66 19.55 92.50 46.25 293.66 19.56 92.50 46.25 293.66 19.57 92.50 46.25 293.66 19.58 92.50 46.25 293.66 19.59 92.50 46.25 293.66 19.60 92.50 46.25 293.66 19.61 92.50 46.25 293.66 19.62 92.50 46.25 293.66 19.63 92.50 46.25 293.66 19.64 92.50 46.25 293.66 19.65 92.50 46.25 293.66 19.66 92.50 46.25 293.66 19.67 92.50 46.25 293.66 19.68 92.50 46.25 293.66 19.69 92.50 46.25 293.66 19.70 92.50 46.25 293.66 19.71 92.50 46.25 293.66 19.72 92.50 46.25 293.66 19.73 92.50 46.25 293.66 19.74 92.50 46.25 293.66 19.75 92.50 46.25 293.66 19.76 92.50 46.25 293.66 19.77 92.50 46.25 293.66 19.78 92.50 46.25 293.66 19.79 92.50 46.25 293.66 19.80 92.50 46.25 293.66 19.81 92.50 46.25 293.66 19.82 92.50 46.25 293.66 19.83 92.50 46.25 293.66 19.84 92.50 46.25 293.66 19.85 92.50 46.25 293.66 19.86 92.50 46.25 293.66 19.87 92.50 46.25 293.66 19.88 92.50 46.25 293.66 19.89 92.50 46.25 293.66 19.90 92.50 46.25 293.66 19.91 92.50 293.66 19.92 92.50 293.66 19.93 92.50 293.66 19.94 92.50 293.66 19.95 92.50 293.66 369.99 19.96 92.50 293.66 369.99 19.97 92.50 293.66 369.99 19.98 92.50 293.66 369.99 19.99 92.50 369.99 20.00 92.50 369.99 20.01 92.50 369.99 20.02 92.50 369.99 20.03 369.99 20.04 369.99 20.05 369.99 20.06 369.99 20.07 369.99 20.08 369.99 20.09 369.99 20.10 369.99 20.11 369.99 20.12 369.99 20.13 369.99 20.14 369.99 20.15 369.99 20.16 369.99 20.17 369.99 20.18 369.99 20.19 369.99 20.20 369.99 20.21 369.99 20.22 369.99 20.23 369.99 20.24 369.99 20.25 369.99 20.26 369.99 20.27 369.99 20.28 369.99 20.29 369.99 20.30 369.99 20.31 369.99 20.32 369.99 20.33 369.99 20.34 369.99 20.35 369.99 20.36 369.99 20.37 369.99 20.38 369.99 20.39 369.99 20.40 369.99 20.41 369.99 20.42 369.99 20.43 369.99 20.44 369.99 51.91 20.45 369.99 51.91 103.83 20.46 369.99 51.91 103.83 20.47 369.99 51.91 103.83 20.48 369.99 51.91 103.83 20.49 51.91 103.83 207.65 20.50 51.91 103.83 207.65 20.51 51.91 103.83 207.65 20.52 51.91 103.83 207.65 20.53 51.91 103.83 207.65 20.54 51.91 103.83 207.65 20.55 51.91 103.83 207.65 20.56 51.91 103.83 207.65 20.57 51.91 103.83 207.65 20.58 51.91 103.83 207.65 20.59 51.91 103.83 207.65 20.60 51.91 103.83 207.65 20.61 51.91 103.83 207.65 20.62 51.91 103.83 207.65 20.63 51.91 103.83 207.65 20.64 51.91 103.83 207.65 20.65 51.91 103.83 207.65 20.66 51.91 103.83 207.65 20.67 51.91 103.83 207.65 20.68 51.91 103.83 207.65 20.69 51.91 103.83 207.65 20.70 51.91 103.83 207.65 20.71 51.91 103.83 207.65 20.72 51.91 103.83 207.65 20.73 51.91 103.83 207.65 20.74 51.91 103.83 207.65 20.75 51.91 103.83 207.65 20.76 51.91 103.83 207.65 20.77 51.91 103.83 207.65 20.78 51.91 103.83 207.65 20.79 51.91 103.83 207.65 20.80 51.91 103.83 207.65 20.81 51.91 103.83 207.65 20.82 51.91 103.83 207.65 20.83 51.91 103.83 207.65 20.84 51.91 103.83 207.65 20.85 51.91 103.83 207.65 20.86 51.91 103.83 207.65 20.87 51.91 103.83 207.65 20.88 51.91 103.83 207.65 20.89 51.91 103.83 207.65 20.90 51.91 103.83 207.65 20.91 51.91 103.83 207.65 20.92 51.91 103.83 207.65 20.93 51.91 103.83 207.65 20.94 51.91 103.83 207.65 20.95 51.91 103.83 207.65 20.96 51.91 103.83 207.65 20.97 51.91 103.83 207.65 20.98 51.91 103.83 207.65 20.99 51.91 103.83 207.65 21.00 51.91 103.83 207.65 21.01 51.91 103.83 207.65 21.02 51.91 103.83 207.65 21.03 51.91 103.83 207.65 261.63 21.04 51.91 103.83 207.65 261.63 21.05 51.91 103.83 207.65 261.63 21.06 51.91 103.83 207.65 261.63 21.07 51.91 103.83 207.65 261.63 21.08 51.91 103.83 207.65 261.63 21.09 51.91 103.83 261.63 21.10 51.91 103.83 261.63 21.11 51.91 103.83 261.63 21.12 51.91 103.83 261.63 21.13 51.91 103.83 261.63 21.14 51.91 103.83 261.63 21.15 51.91 103.83 261.63 21.16 51.91 103.83 261.63 21.17 51.91 103.83 261.63 21.18 51.91 103.83 261.63 21.19 51.91 103.83 261.63 21.20 51.91 103.83 261.63 21.21 51.91 103.83 261.63 21.22 51.91 103.83 261.63 21.23 51.91 103.83 261.63 21.24 51.91 103.83 261.63 21.25 51.91 103.83 261.63 21.26 51.91 103.83 261.63 21.27 51.91 103.83 261.63 21.28 51.91 103.83 261.63 21.29 51.91 103.83 261.63 21.30 51.91 103.83 261.63 21.31 51.91 103.83 261.63 21.32 51.91 103.83 261.63 21.33 51.91 103.83 261.63 21.34 51.91 103.83 261.63 21.35 51.91 103.83 261.63 21.36 51.91 103.83 261.63 21.37 51.91 103.83 261.63 21.38 51.91 103.83 261.63 21.39 51.91 103.83 261.63 21.40 51.91 103.83 261.63 21.41 51.91 103.83 261.63 21.42 51.91 103.83 261.63 21.43 51.91 103.83 261.63 21.44 51.91 103.83 261.63 21.45 51.91 103.83 261.63 21.46 51.91 103.83 261.63 21.47 51.91 103.83 261.63 21.48 51.91 103.83 261.63 21.49 51.91 103.83 261.63 21.50 51.91 103.83 261.63 369.99 21.51 51.91 103.83 261.63 369.99 21.52 51.91 103.83 261.63 369.99 21.53 51.91 103.83 369.99 21.54 51.91 103.83 369.99 21.55 51.91 103.83 369.99 21.56 51.91 103.83 369.99 21.57 51.91 103.83 369.99 21.58 51.91 103.83 369.99 21.59 51.91 103.83 369.99 21.60 51.91 103.83 369.99 21.61 51.91 103.83 369.99 21.62 51.91 103.83 369.99 21.63 51.91 103.83 369.99 21.64 51.91 103.83 369.99 21.65 51.91 103.83 369.99 21.66 51.91 103.83 369.99 21.67 51.91 103.83 369.99 21.68 51.91 103.83 369.99 21.69 51.91 103.83 369.99 21.70 51.91 103.83 369.99 21.71 51.91 103.83 369.99 21.72 51.91 103.83 369.99 21.73 51.91 103.83 369.99 21.74 51.91 103.83 369.99 21.75 51.91 103.83 369.99 21.76 51.91 103.83 369.99 21.77 51.91 103.83 369.99 21.78 51.91 103.83 369.99 21.79 51.91 103.83 369.99 21.80 51.91 103.83 369.99 21.81 51.91 103.83 369.99 21.82 51.91 103.83 369.99 21.83 51.91 103.83 369.99 21.84 51.91 103.83 369.99 21.85 51.91 103.83 369.99 21.86 51.91 103.83 369.99 21.87 51.91 103.83 369.99 21.88 51.91 103.83 369.99 21.89 51.91 103.83 369.99 21.90 51.91 103.83 369.99 21.91 51.91 103.83 369.99 21.92 51.91 103.83 369.99 21.93 51.91 103.83 369.99 21.94 51.91 103.83 369.99 21.95 51.91 103.83 369.99 21.96 51.91 103.83 369.99 21.97 51.91 103.83 369.99 21.98 51.91 103.83 369.99 21.99 51.91 103.83 369.99 22.00 51.91 103.83 369.99 207.65 22.01 51.91 103.83 369.99 207.65 22.02 51.91 103.83 369.99 207.65 22.03 51.91 103.83 369.99 207.65 22.04 51.91 103.83 207.65 22.05 51.91 103.83 207.65 22.06 51.91 103.83 207.65 22.07 51.91 103.83 207.65 22.08 51.91 103.83 207.65 22.09 51.91 103.83 207.65 22.10 51.91 103.83 207.65 22.11 51.91 103.83 207.65 22.12 51.91 103.83 207.65 22.13 51.91 103.83 207.65 22.14 51.91 103.83 207.65 22.15 51.91 103.83 207.65 22.16 51.91 103.83 207.65 22.17 51.91 103.83 207.65 22.18 51.91 103.83 207.65 22.19 51.91 103.83 207.65 22.20 51.91 103.83 207.65 22.21 51.91 103.83 207.65 22.22 51.91 103.83 207.65 22.23 51.91 103.83 207.65 22.24 51.91 103.83 207.65 22.25 51.91 103.83 207.65 22.26 51.91 103.83 207.65 22.27 51.91 103.83 207.65 22.28 51.91 103.83 207.65 22.29 51.91 103.83 207.65 22.30 51.91 103.83 207.65 22.31 51.91 103.83 207.65 22.32 51.91 103.83 207.65 22.33 51.91 103.83 207.65 22.34 51.91 103.83 207.65 22.35 51.91 103.83 207.65 22.36 51.91 103.83 207.65 22.37 51.91 103.83 207.65 22.38 51.91 103.83 207.65 22.39 51.91 103.83 207.65 22.40 51.91 103.83 207.65 22.41 51.91 103.83 207.65 22.42 51.91 103.83 207.65 22.43 51.91 103.83 207.65 22.44 51.91 103.83 207.65 22.45 51.91 103.83 207.65 22.46 51.91 103.83 207.65 22.47 51.91 103.83 207.65 277.18 22.48 51.91 103.83 207.65 277.18 22.49 51.91 103.83 207.65 277.18 22.50 51.91 103.83 207.65 277.18 22.51 51.91 103.83 207.65 277.18 22.52 51.91 103.83 207.65 277.18 22.53 51.91 103.83 277.18 22.54 51.91 103.83 277.18 22.55 51.91 103.83 277.18 22.56 51.91 103.83 277.18 22.57 51.91 103.83 277.18 22.58 51.91 103.83 277.18 22.59 51.91 103.83 277.18 22.60 51.91 103.83 277.18 22.61 51.91 103.83 277.18 22.62 51.91 103.83 277.18 22.63 51.91 103.83 277.18 22.64 51.91 103.83 277.18 22.65 51.91 103.83 277.18 22.66 51.91 103.83 277.18 22.67 51.91 103.83 277.18 22.68 51.91 103.83 277.18 22.69 51.91 103.83 277.18 22.70 51.91 103.83 277.18 22.71 51.91 103.83 277.18 22.72 51.91 103.83 277.18 22.73 51.91 103.83 277.18 22.74 51.91 103.83 277.18 22.75 51.91 103.83 277.18 22.76 51.91 103.83 277.18 22.77 51.91 103.83 277.18 22.78 51.91 103.83 277.18 22.79 51.91 103.83 277.18 22.80 51.91 103.83 277.18 22.81 51.91 103.83 277.18 22.82 51.91 103.83 277.18 22.83 51.91 103.83 277.18 22.84 51.91 103.83 277.18 22.85 51.91 103.83 277.18 22.86 51.91 103.83 277.18 22.87 51.91 103.83 277.18 22.88 51.91 103.83 277.18 22.89 51.91 103.83 277.18 22.90 51.91 103.83 277.18 22.91 51.91 103.83 277.18 22.92 51.91 103.83 277.18 22.93 51.91 103.83 277.18 22.94 51.91 103.83 277.18 329.63 22.95 51.91 103.83 277.18 329.63 22.96 51.91 103.83 277.18 329.63 22.97 51.91 103.83 277.18 329.63 22.98 51.91 103.83 277.18 329.63 22.99 51.91 103.83 329.63 23.00 51.91 103.83 329.63 23.01 51.91 103.83 329.63 23.02 51.91 103.83 329.63 23.03 51.91 103.83 329.63 23.04 103.83 329.63 23.05 103.83 329.63 23.06 103.83 329.63 23.07 103.83 329.63 23.08 329.63 23.09 329.63 23.10 329.63 23.11 329.63 23.12 329.63 23.13 329.63 23.14 329.63 23.15 329.63 23.16 329.63 23.17 329.63 23.18 329.63 23.19 329.63 23.20 329.63 23.21 329.63 23.22 329.63 23.23 329.63 23.24 329.63 23.25 329.63 23.26 329.63 23.27 329.63 23.28 329.63 23.29 329.63 23.30 329.63 23.31 329.63 23.32 329.63 23.33 329.63 23.34 329.63 23.35 329.63 23.36 329.63 23.37 329.63 23.38 329.63 23.39 329.63 23.40 329.63 23.41 329.63 23.42 329.63 23.43 329.63 23.44 329.63 23.45 329.63 23.46 329.63 23.47 329.63 51.91 207.65 103.83 23.48 329.63 51.91 207.65 103.83 23.49 329.63 51.91 207.65 103.83 23.50 329.63 51.91 207.65 103.83 23.51 51.91 207.65 103.83 23.52 51.91 207.65 103.83 23.53 51.91 207.65 103.83 23.54 51.91 207.65 103.83 23.55 51.91 207.65 103.83 23.56 51.91 207.65 103.83 23.57 51.91 207.65 103.83 23.58 51.91 207.65 103.83 23.59 51.91 207.65 103.83 23.60 51.91 207.65 103.83 23.61 51.91 207.65 103.83 23.62 51.91 207.65 103.83 23.63 51.91 207.65 103.83 23.64 51.91 207.65 103.83 23.65 51.91 207.65 103.83 23.66 51.91 207.65 103.83 23.67 51.91 207.65 103.83 23.68 51.91 207.65 103.83 23.69 51.91 207.65 103.83 23.70 51.91 207.65 103.83 23.71 51.91 207.65 103.83 23.72 51.91 207.65 103.83 23.73 51.91 207.65 103.83 23.74 51.91 207.65 103.83 23.75 51.91 207.65 103.83 23.76 51.91 207.65 103.83 23.77 51.91 207.65 103.83 23.78 51.91 207.65 103.83 23.79 51.91 207.65 103.83 23.80 51.91 207.65 103.83 23.81 51.91 207.65 103.83 23.82 51.91 207.65 103.83 23.83 51.91 207.65 103.83 23.84 51.91 207.65 103.83 23.85 51.91 207.65 103.83 23.86 51.91 207.65 103.83 23.87 51.91 207.65 103.83 23.88 51.91 207.65 103.83 23.89 51.91 207.65 103.83 23.90 51.91 207.65 103.83 23.91 51.91 207.65 103.83 23.92 51.91 207.65 103.83 23.93 51.91 207.65 103.83 23.94 51.91 207.65 103.83 23.95 51.91 207.65 103.83 23.96 51.91 207.65 103.83 23.97 51.91 207.65 103.83 23.98 51.91 207.65 103.83 23.99 51.91 207.65 103.83 24.00 51.91 207.65 103.83 24.01 51.91 207.65 103.83 24.02 51.91 207.65 103.83 24.03 51.91 207.65 103.83 24.04 51.91 207.65 103.83 24.05 51.91 207.65 103.83 24.06 51.91 207.65 103.83 24.07 51.91 207.65 103.83 24.08 51.91 207.65 103.83 24.09 51.91 207.65 103.83 24.10 51.91 207.65 103.83 24.11 51.91 207.65 103.83 24.12 51.91 207.65 103.83 277.18 24.13 51.91 207.65 103.83 277.18 24.14 51.91 207.65 103.83 277.18 24.15 51.91 207.65 103.83 277.18 24.16 51.91 207.65 103.83 277.18 24.17 51.91 207.65 103.83 277.18 24.18 51.91 103.83 277.18 24.19 51.91 103.83 277.18 24.20 51.91 103.83 277.18 24.21 51.91 103.83 277.18 24.22 51.91 103.83 277.18 24.23 51.91 103.83 277.18 24.24 51.91 103.83 277.18 24.25 51.91 103.83 277.18 24.26 51.91 103.83 277.18 24.27 51.91 103.83 277.18 24.28 51.91 103.83 277.18 24.29 51.91 103.83 277.18 24.30 51.91 103.83 277.18 24.31 51.91 103.83 277.18 24.32 51.91 103.83 277.18 24.33 51.91 103.83 277.18 24.34 51.91 103.83 277.18 24.35 51.91 103.83 277.18 24.36 51.91 103.83 277.18 24.37 51.91 103.83 277.18 24.38 51.91 103.83 277.18 24.39 51.91 103.83 277.18 24.40 51.91 103.83 277.18 24.41 51.91 103.83 277.18 24.42 51.91 103.83 277.18 24.43 51.91 103.83 277.18 24.44 51.91 103.83 277.18 24.45 51.91 103.83 277.18 24.46 51.91 103.83 277.18 24.47 51.91 103.83 277.18 24.48 51.91 103.83 277.18 24.49 51.91 103.83 277.18 24.50 51.91 103.83 277.18 24.51 51.91 103.83 277.18 24.52 51.91 103.83 277.18 24.53 51.91 103.83 277.18 24.54 51.91 103.83 277.18 24.55 51.91 103.83 277.18 24.56 51.91 103.83 277.18 24.57 51.91 103.83 277.18 24.58 51.91 103.83 277.18 24.59 51.91 103.83 277.18 311.13 24.60 51.91 103.83 277.18 311.13 24.61 51.91 103.83 311.13 24.62 51.91 103.83 311.13 24.63 51.91 103.83 311.13 24.64 51.91 103.83 311.13 24.65 51.91 103.83 311.13 24.66 51.91 103.83 311.13 24.67 51.91 103.83 311.13 24.68 51.91 103.83 311.13 24.69 51.91 103.83 311.13 24.70 51.91 103.83 311.13 24.71 51.91 103.83 311.13 24.72 51.91 103.83 311.13 24.73 51.91 103.83 311.13 24.74 51.91 103.83 311.13 24.75 51.91 103.83 311.13 24.76 51.91 103.83 311.13 24.77 51.91 103.83 311.13 24.78 51.91 103.83 311.13 24.79 51.91 103.83 311.13 24.80 51.91 103.83 311.13 24.81 51.91 103.83 311.13 24.82 51.91 103.83 311.13 24.83 51.91 103.83 311.13 24.84 51.91 103.83 311.13 24.85 51.91 103.83 311.13 24.86 51.91 103.83 311.13 24.87 51.91 103.83 311.13 24.88 51.91 103.83 311.13 24.89 51.91 103.83 311.13 24.90 51.91 103.83 311.13 24.91 51.91 103.83 311.13 24.92 51.91 103.83 311.13 24.93 51.91 103.83 311.13 24.94 51.91 103.83 311.13 24.95 51.91 103.83 311.13 24.96 51.91 103.83 311.13 24.97 51.91 103.83 311.13 24.98 51.91 103.83 311.13 24.99 51.91 103.83 311.13 25.00 51.91 103.83 311.13 25.01 51.91 103.83 311.13 25.02 51.91 103.83 311.13 25.03 51.91 103.83 311.13 25.04 51.91 103.83 311.13 25.05 51.91 103.83 311.13 25.06 51.91 103.83 311.13 25.07 51.91 103.83 311.13 25.08 51.91 103.83 311.13 25.09 51.91 103.83 311.13 185.00 25.10 51.91 103.83 185.00 25.11 51.91 103.83 185.00 25.12 51.91 103.83 185.00 25.13 51.91 103.83 185.00 25.14 51.91 103.83 185.00 25.15 51.91 103.83 185.00 25.16 51.91 103.83 185.00 25.17 51.91 103.83 185.00 25.18 51.91 103.83 185.00 25.19 51.91 103.83 185.00 25.20 51.91 103.83 185.00 25.21 51.91 103.83 185.00 25.22 51.91 103.83 185.00 25.23 51.91 103.83 185.00 25.24 51.91 103.83 185.00 25.25 51.91 103.83 185.00 25.26 51.91 103.83 185.00 25.27 51.91 103.83 185.00 25.28 51.91 103.83 185.00 25.29 51.91 103.83 185.00 25.30 51.91 103.83 185.00 25.31 51.91 103.83 185.00 25.32 51.91 103.83 185.00 25.33 51.91 103.83 185.00 25.34 51.91 103.83 185.00 25.35 51.91 103.83 185.00 25.36 51.91 103.83 185.00 25.37 51.91 103.83 185.00 25.38 51.91 103.83 185.00 25.39 51.91 103.83 185.00 25.40 51.91 103.83 185.00 25.41 51.91 103.83 185.00 25.42 51.91 103.83 185.00 25.43 51.91 103.83 185.00 25.44 51.91 103.83 185.00 25.45 51.91 103.83 185.00 25.46 51.91 103.83 185.00 25.47 51.91 103.83 185.00 25.48 51.91 103.83 185.00 25.49 51.91 103.83 185.00 25.50 51.91 103.83 185.00 25.51 51.91 103.83 185.00 25.52 51.91 103.83 185.00 25.53 51.91 103.83 185.00 25.54 51.91 103.83 185.00 25.55 51.91 103.83 185.00 261.63 25.56 51.91 103.83 185.00 261.63 25.57 51.91 103.83 185.00 261.63 25.58 51.91 103.83 185.00 261.63 25.59 51.91 103.83 185.00 261.63 25.60 51.91 103.83 185.00 261.63 25.61 51.91 103.83 261.63 25.62 51.91 103.83 261.63 25.63 51.91 103.83 261.63 25.64 51.91 103.83 261.63 25.65 51.91 103.83 261.63 25.66 51.91 103.83 261.63 25.67 51.91 103.83 261.63 25.68 51.91 103.83 261.63 25.69 51.91 103.83 261.63 25.70 51.91 103.83 261.63 25.71 51.91 103.83 261.63 25.72 51.91 103.83 261.63 25.73 51.91 103.83 261.63 25.74 51.91 103.83 261.63 25.75 51.91 103.83 261.63 25.76 51.91 103.83 261.63 25.77 51.91 103.83 261.63 25.78 51.91 103.83 261.63 25.79 51.91 103.83 261.63 25.80 51.91 103.83 261.63 25.81 51.91 103.83 261.63 25.82 51.91 103.83 261.63 25.83 51.91 103.83 261.63 25.84 51.91 103.83 261.63 25.85 51.91 103.83 261.63 25.86 51.91 103.83 261.63 25.87 51.91 103.83 261.63 25.88 51.91 103.83 261.63 25.89 51.91 103.83 261.63 25.90 51.91 103.83 261.63 25.91 51.91 103.83 261.63 25.92 103.83 261.63 25.93 103.83 261.63 25.94 103.83 261.63 25.95 103.83 261.63 25.96 103.83 261.63 25.97 103.83 261.63 25.98 103.83 261.63 25.99 103.83 261.63 26.00 103.83 261.63 26.01 261.63 26.02 261.63 26.03 261.63 26.04 261.63 26.05 261.63 26.06 261.63 311.13 26.07 261.63 311.13 26.08 261.63 311.13 26.09 311.13 26.10 311.13 26.11 311.13 26.12 311.13 26.13 311.13 26.14 311.13 26.15 311.13 26.16 311.13 26.17 311.13 26.18 311.13 26.19 311.13 26.20 311.13 26.21 311.13 26.22 311.13 26.23 311.13 26.24 311.13 26.25 311.13 26.26 311.13 26.27 311.13 26.28 311.13 26.29 311.13 26.30 311.13 26.31 311.13 26.32 311.13 26.33 311.13 26.34 311.13 26.35 311.13 26.36 311.13 26.37 311.13 26.38 311.13 26.39 311.13 26.40 311.13 26.41 311.13 26.42 311.13 26.43 311.13 26.44 311.13 26.45 311.13 26.46 311.13 26.47 311.13 26.48 311.13 26.49 311.13 26.50 311.13 26.51 311.13 26.52 311.13 26.53 311.13 26.54 311.13 26.55 311.13 26.56 311.13 26.57 311.13 26.58 311.13 26.59 311.13 26.60 311.13 26.61 311.13 26.62 311.13 26.63 311.13 26.64 311.13 26.65 311.13 26.66 311.13 26.67 311.13 26.68 311.13 26.69 311.13 26.70 311.13 26.71 311.13 26.72 311.13 26.73 26.74 69.30 26.75 69.30 138.59 164.81 26.76 69.30 138.59 164.81 26.77 69.30 138.59 164.81 103.83 26.78 69.30 138.59 164.81 103.83 26.79 69.30 138.59 164.81 103.83 26.80 69.30 138.59 164.81 103.83 26.81 69.30 138.59 164.81 103.83 26.82 69.30 138.59 164.81 103.83 26.83 69.30 138.59 164.81 103.83 26.84 69.30 138.59 164.81 103.83 26.85 69.30 138.59 164.81 103.83 26.86 69.30 138.59 164.81 103.83 26.87 69.30 138.59 164.81 103.83 26.88 69.30 138.59 164.81 103.83 26.89 69.30 138.59 164.81 103.83 26.90 69.30 138.59 164.81 103.83 26.91 69.30 138.59 164.81 103.83 26.92 69.30 138.59 164.81 103.83 26.93 69.30 138.59 164.81 103.83 26.94 69.30 138.59 164.81 103.83 26.95 69.30 138.59 164.81 103.83 26.96 69.30 138.59 164.81 103.83 26.97 69.30 138.59 164.81 103.83 26.98 69.30 138.59 164.81 103.83 26.99 69.30 138.59 164.81 103.83 27.00 69.30 138.59 164.81 103.83 27.01 69.30 138.59 164.81 103.83 27.02 69.30 138.59 164.81 103.83 27.03 69.30 138.59 164.81 103.83 27.04 69.30 138.59 164.81 103.83 27.05 69.30 138.59 164.81 103.83 27.06 69.30 138.59 164.81 103.83 27.07 69.30 138.59 164.81 103.83 27.08 69.30 138.59 164.81 103.83 27.09 69.30 138.59 164.81 103.83 27.10 69.30 138.59 164.81 103.83 27.11 69.30 138.59 164.81 103.83 27.12 69.30 138.59 164.81 103.83 27.13 69.30 138.59 164.81 103.83 27.14 69.30 138.59 164.81 103.83 27.15 69.30 138.59 164.81 103.83 27.16 69.30 138.59 164.81 103.83 27.17 69.30 138.59 164.81 103.83 27.18 69.30 138.59 164.81 103.83 27.19 69.30 138.59 164.81 103.83 27.20 69.30 138.59 164.81 103.83 27.21 69.30 138.59 164.81 103.83 27.22 69.30 138.59 164.81 103.83 27.23 69.30 138.59 164.81 103.83 27.24 69.30 138.59 164.81 103.83 27.25 69.30 138.59 164.81 103.83 27.26 69.30 138.59 164.81 103.83 27.27 69.30 138.59 164.81 103.83 27.28 69.30 138.59 164.81 103.83 27.29 69.30 138.59 164.81 103.83 27.30 69.30 138.59 164.81 103.83 27.31 69.30 138.59 164.81 103.83 27.32 69.30 138.59 164.81 103.83 27.33 69.30 138.59 164.81 103.83 27.34 69.30 138.59 164.81 103.83 27.35 69.30 138.59 164.81 103.83 27.36 69.30 138.59 164.81 103.83 27.37 69.30 138.59 164.81 103.83 27.38 69.30 138.59 164.81 103.83 27.39 69.30 138.59 164.81 103.83 27.40 69.30 138.59 164.81 103.83 27.41 69.30 138.59 164.81 103.83 27.42 69.30 138.59 164.81 103.83 27.43 69.30 138.59 164.81 103.83 27.44 69.30 138.59 164.81 103.83 27.45 69.30 138.59 164.81 103.83 27.46 69.30 138.59 164.81 103.83 27.47 69.30 138.59 164.81 103.83 27.48 69.30 138.59 164.81 103.83 27.49 69.30 138.59 164.81 103.83 207.65 27.50 69.30 138.59 164.81 103.83 207.65 27.51 69.30 138.59 164.81 103.83 207.65 27.52 69.30 138.59 164.81 103.83 207.65 27.53 69.30 138.59 164.81 103.83 207.65 27.54 69.30 138.59 164.81 103.83 207.65 27.55 69.30 138.59 164.81 103.83 207.65 27.56 69.30 138.59 164.81 103.83 207.65 27.57 69.30 138.59 164.81 103.83 207.65 27.58 69.30 138.59 103.83 207.65 27.59 69.30 138.59 103.83 207.65 27.60 69.30 138.59 103.83 207.65 27.61 69.30 138.59 103.83 207.65 27.62 69.30 138.59 103.83 207.65 27.63 69.30 138.59 103.83 207.65 27.64 69.30 138.59 103.83 207.65 27.65 69.30 138.59 103.83 207.65 27.66 69.30 138.59 103.83 207.65 27.67 69.30 138.59 103.83 207.65 27.68 69.30 138.59 103.83 207.65 27.69 69.30 138.59 103.83 207.65 27.70 69.30 138.59 103.83 207.65 27.71 69.30 138.59 103.83 207.65 27.72 69.30 138.59 103.83 207.65 27.73 69.30 138.59 103.83 207.65 27.74 69.30 138.59 103.83 207.65 27.75 69.30 138.59 103.83 207.65 27.76 69.30 138.59 103.83 207.65 27.77 69.30 138.59 103.83 207.65 27.78 69.30 138.59 103.83 207.65 27.79 69.30 138.59 103.83 207.65 27.80 69.30 138.59 103.83 207.65 27.81 69.30 138.59 103.83 207.65 27.82 69.30 138.59 103.83 207.65 27.83 69.30 138.59 103.83 207.65 27.84 69.30 138.59 103.83 207.65 27.85 69.30 138.59 103.83 207.65 27.86 69.30 138.59 103.83 207.65 27.87 69.30 138.59 103.83 207.65 27.88 69.30 138.59 103.83 207.65 27.89 69.30 138.59 103.83 207.65 27.90 69.30 138.59 103.83 207.65 27.91 69.30 138.59 103.83 207.65 27.92 69.30 138.59 103.83 207.65 27.93 69.30 138.59 103.83 207.65 27.94 69.30 138.59 103.83 207.65 27.95 69.30 138.59 103.83 207.65 27.96 69.30 138.59 103.83 207.65 27.97 69.30 138.59 103.83 207.65 27.98 69.30 138.59 103.83 207.65 27.99 69.30 138.59 103.83 207.65 28.00 69.30 138.59 103.83 207.65 28.01 69.30 138.59 103.83 207.65 277.18 28.02 69.30 138.59 103.83 207.65 277.18 28.03 69.30 138.59 103.83 207.65 277.18 28.04 69.30 138.59 103.83 207.65 277.18 28.05 69.30 138.59 103.83 277.18 28.06 69.30 138.59 103.83 277.18 28.07 69.30 138.59 103.83 277.18 28.08 69.30 138.59 103.83 277.18 28.09 69.30 138.59 103.83 277.18 28.10 69.30 138.59 103.83 277.18 28.11 69.30 138.59 103.83 277.18 28.12 69.30 138.59 103.83 277.18 28.13 69.30 138.59 103.83 277.18 28.14 69.30 138.59 103.83 277.18 28.15 69.30 138.59 103.83 277.18 28.16 69.30 138.59 103.83 277.18 28.17 69.30 138.59 103.83 277.18 28.18 69.30 138.59 103.83 277.18 28.19 69.30 138.59 103.83 277.18 28.20 69.30 138.59 103.83 277.18 28.21 69.30 138.59 103.83 277.18 28.22 69.30 138.59 103.83 277.18 28.23 69.30 138.59 103.83 277.18 28.24 69.30 138.59 103.83 277.18 28.25 69.30 138.59 103.83 277.18 28.26 69.30 138.59 103.83 277.18 28.27 69.30 138.59 103.83 277.18 28.28 69.30 138.59 103.83 277.18 28.29 69.30 138.59 103.83 277.18 28.30 69.30 138.59 103.83 277.18 28.31 69.30 138.59 103.83 277.18 28.32 69.30 138.59 103.83 277.18 28.33 69.30 138.59 103.83 277.18 28.34 69.30 138.59 103.83 277.18 28.35 69.30 138.59 103.83 277.18 28.36 69.30 138.59 103.83 277.18 28.37 69.30 138.59 103.83 277.18 28.38 69.30 138.59 103.83 277.18 28.39 69.30 138.59 103.83 277.18 28.40 69.30 138.59 103.83 277.18 28.41 69.30 138.59 103.83 277.18 28.42 69.30 138.59 103.83 277.18 28.43 69.30 138.59 103.83 277.18 28.44 69.30 138.59 103.83 277.18 28.45 69.30 138.59 103.83 277.18 28.46 69.30 138.59 103.83 277.18 28.47 69.30 138.59 103.83 277.18 28.48 69.30 138.59 103.83 277.18 28.49 69.30 138.59 103.83 277.18 28.50 69.30 138.59 103.83 277.18 28.51 69.30 138.59 103.83 277.18 207.65 28.52 69.30 138.59 103.83 277.18 207.65 28.53 69.30 138.59 103.83 207.65 28.54 69.30 138.59 103.83 207.65 28.55 69.30 138.59 103.83 207.65 28.56 69.30 138.59 103.83 207.65 28.57 69.30 138.59 103.83 207.65 28.58 69.30 138.59 103.83 207.65 28.59 69.30 138.59 103.83 207.65 28.60 69.30 138.59 103.83 207.65 28.61 69.30 138.59 103.83 207.65 28.62 69.30 138.59 103.83 207.65 28.63 69.30 138.59 103.83 207.65 28.64 69.30 138.59 103.83 207.65 28.65 69.30 138.59 103.83 207.65 28.66 69.30 138.59 103.83 207.65 28.67 69.30 138.59 103.83 207.65 28.68 69.30 138.59 103.83 207.65 28.69 69.30 138.59 103.83 207.65 28.70 69.30 138.59 103.83 207.65 28.71 69.30 138.59 103.83 207.65 28.72 69.30 138.59 103.83 207.65 28.73 69.30 138.59 103.83 207.65 28.74 69.30 138.59 103.83 207.65 28.75 69.30 138.59 103.83 207.65 28.76 69.30 138.59 103.83 207.65 28.77 69.30 138.59 103.83 207.65 28.78 69.30 138.59 103.83 207.65 28.79 69.30 138.59 103.83 207.65 28.80 69.30 138.59 103.83 207.65 28.81 69.30 138.59 103.83 207.65 28.82 69.30 138.59 103.83 207.65 28.83 69.30 138.59 103.83 207.65 28.84 69.30 138.59 103.83 207.65 28.85 69.30 138.59 103.83 207.65 28.86 69.30 138.59 103.83 207.65 28.87 69.30 138.59 103.83 207.65 28.88 69.30 138.59 103.83 207.65 28.89 69.30 138.59 103.83 207.65 28.90 69.30 138.59 103.83 207.65 28.91 69.30 138.59 103.83 207.65 28.92 69.30 138.59 103.83 207.65 28.93 69.30 138.59 103.83 207.65 28.94 69.30 138.59 103.83 207.65 28.95 69.30 138.59 103.83 207.65 28.96 69.30 138.59 103.83 207.65 28.97 69.30 138.59 103.83 207.65 28.98 69.30 138.59 103.83 207.65 28.99 69.30 138.59 103.83 207.65 29.00 69.30 138.59 103.83 207.65 277.18 29.01 69.30 138.59 103.83 207.65 277.18 29.02 69.30 138.59 103.83 207.65 277.18 29.03 69.30 138.59 103.83 207.65 277.18 29.04 69.30 138.59 103.83 207.65 277.18 29.05 69.30 138.59 103.83 207.65 277.18 29.06 69.30 138.59 103.83 277.18 29.07 69.30 138.59 103.83 277.18 29.08 69.30 138.59 103.83 277.18 29.09 69.30 138.59 103.83 277.18 29.10 69.30 138.59 103.83 277.18 29.11 69.30 138.59 103.83 277.18 29.12 69.30 138.59 103.83 277.18 29.13 69.30 138.59 103.83 277.18 29.14 69.30 138.59 103.83 277.18 29.15 69.30 138.59 103.83 277.18 29.16 69.30 138.59 103.83 277.18 29.17 69.30 138.59 103.83 277.18 29.18 69.30 138.59 103.83 277.18 29.19 69.30 138.59 103.83 277.18 29.20 69.30 138.59 103.83 277.18 29.21 69.30 138.59 103.83 277.18 29.22 69.30 138.59 103.83 277.18 29.23 69.30 138.59 103.83 277.18 29.24 69.30 138.59 103.83 277.18 29.25 69.30 138.59 103.83 277.18 29.26 69.30 138.59 103.83 277.18 29.27 69.30 138.59 103.83 277.18 29.28 69.30 138.59 103.83 277.18 29.29 69.30 138.59 103.83 277.18 29.30 69.30 138.59 103.83 277.18 29.31 69.30 138.59 103.83 277.18 29.32 69.30 138.59 103.83 277.18 29.33 69.30 138.59 103.83 277.18 29.34 69.30 138.59 103.83 277.18 29.35 69.30 138.59 103.83 277.18 29.36 69.30 138.59 103.83 277.18 29.37 69.30 138.59 103.83 277.18 29.38 69.30 138.59 103.83 277.18 29.39 69.30 138.59 103.83 277.18 29.40 69.30 138.59 103.83 277.18 29.41 69.30 138.59 103.83 277.18 29.42 69.30 138.59 103.83 277.18 29.43 69.30 138.59 103.83 277.18 29.44 69.30 138.59 103.83 277.18 29.45 69.30 138.59 103.83 277.18 29.46 69.30 138.59 103.83 277.18 29.47 69.30 138.59 103.83 277.18 29.48 69.30 138.59 103.83 277.18 29.49 69.30 138.59 103.83 277.18 329.63 29.50 69.30 138.59 103.83 277.18 329.63 29.51 69.30 138.59 103.83 277.18 329.63 29.52 69.30 138.59 103.83 329.63 29.53 69.30 138.59 103.83 329.63 29.54 69.30 138.59 103.83 329.63 29.55 69.30 138.59 103.83 329.63 29.56 69.30 138.59 103.83 329.63 29.57 69.30 138.59 103.83 329.63 29.58 69.30 138.59 103.83 329.63 29.59 69.30 138.59 103.83 329.63 29.60 69.30 138.59 103.83 329.63 29.61 69.30 138.59 103.83 329.63 29.62 69.30 138.59 103.83 329.63 29.63 69.30 138.59 103.83 329.63 29.64 69.30 138.59 103.83 329.63 29.65 69.30 138.59 103.83 329.63 29.66 69.30 138.59 103.83 329.63 29.67 69.30 138.59 103.83 329.63 29.68 69.30 138.59 103.83 329.63 29.69 69.30 138.59 103.83 329.63 29.70 69.30 138.59 103.83 329.63 29.71 69.30 138.59 103.83 329.63 29.72 69.30 138.59 103.83 329.63 29.73 69.30 138.59 103.83 329.63 29.74 69.30 138.59 103.83 329.63 29.75 69.30 138.59 103.83 329.63 29.76 69.30 138.59 103.83 329.63 29.77 69.30 138.59 103.83 329.63 29.78 69.30 138.59 103.83 329.63 29.79 69.30 138.59 103.83 329.63 29.80 69.30 138.59 103.83 329.63 29.81 69.30 138.59 103.83 329.63 29.82 69.30 138.59 103.83 329.63 29.83 69.30 138.59 103.83 329.63 29.84 69.30 138.59 103.83 329.63 29.85 69.30 138.59 103.83 329.63 29.86 69.30 138.59 103.83 329.63 29.87 69.30 138.59 103.83 329.63 29.88 69.30 138.59 103.83 329.63 29.89 69.30 138.59 103.83 329.63 29.90 69.30 138.59 103.83 329.63 29.91 69.30 138.59 103.83 329.63 29.92 69.30 138.59 103.83 329.63 29.93 69.30 138.59 103.83 329.63 29.94 69.30 138.59 103.83 329.63 29.95 69.30 138.59 103.83 329.63 29.96 69.30 138.59 103.83 329.63 29.97 69.30 138.59 103.83 329.63 29.98 69.30 138.59 103.83 329.63 29.99 69.30 138.59 103.83 329.63 207.65 30.00 69.30 138.59 103.83 329.63 207.65 30.01 69.30 138.59 103.83 329.63 207.65 30.02 69.30 138.59 103.83 207.65 30.03 69.30 138.59 103.83 207.65 30.04 69.30 138.59 103.83 207.65 30.05 69.30 138.59 103.83 207.65 30.06 69.30 138.59 103.83 207.65 30.07 69.30 138.59 103.83 207.65 30.08 69.30 138.59 103.83 207.65 30.09 69.30 138.59 103.83 207.65 30.10 69.30 138.59 103.83 207.65 30.11 69.30 138.59 103.83 207.65 30.12 69.30 138.59 103.83 207.65 30.13 69.30 138.59 103.83 207.65 30.14 69.30 138.59 103.83 207.65 30.15 69.30 138.59 103.83 207.65 30.16 69.30 138.59 103.83 207.65 30.17 69.30 138.59 103.83 207.65 30.18 69.30 138.59 103.83 207.65 30.19 69.30 138.59 103.83 207.65 30.20 69.30 138.59 103.83 207.65 30.21 69.30 138.59 103.83 207.65 30.22 69.30 138.59 103.83 207.65 30.23 69.30 138.59 103.83 207.65 30.24 69.30 138.59 103.83 207.65 30.25 69.30 138.59 103.83 207.65 30.26 69.30 138.59 103.83 207.65 30.27 69.30 138.59 103.83 207.65 30.28 69.30 138.59 103.83 207.65 30.29 69.30 138.59 103.83 207.65 30.30 69.30 138.59 103.83 207.65 30.31 69.30 138.59 103.83 207.65 30.32 69.30 138.59 103.83 207.65 30.33 69.30 138.59 103.83 207.65 30.34 69.30 138.59 103.83 207.65 30.35 69.30 138.59 103.83 207.65 30.36 69.30 138.59 103.83 207.65 30.37 69.30 138.59 103.83 207.65 30.38 69.30 138.59 103.83 207.65 30.39 69.30 138.59 103.83 207.65 30.40 69.30 138.59 103.83 207.65 30.41 69.30 138.59 103.83 207.65 30.42 69.30 138.59 103.83 207.65 30.43 69.30 138.59 103.83 207.65 30.44 69.30 138.59 103.83 207.65 30.45 69.30 138.59 103.83 207.65 30.46 69.30 138.59 103.83 207.65 30.47 69.30 138.59 103.83 207.65 30.48 69.30 138.59 103.83 207.65 277.18 30.49 69.30 138.59 103.83 207.65 277.18 30.50 69.30 138.59 103.83 207.65 277.18 30.51 69.30 138.59 103.83 207.65 277.18 30.52 69.30 138.59 103.83 207.65 277.18 30.53 69.30 138.59 103.83 207.65 277.18 30.54 69.30 138.59 103.83 207.65 277.18 30.55 69.30 138.59 103.83 207.65 277.18 30.56 69.30 138.59 103.83 277.18 30.57 69.30 138.59 103.83 277.18 30.58 69.30 138.59 103.83 277.18 30.59 69.30 138.59 103.83 277.18 30.60 69.30 138.59 103.83 277.18 30.61 69.30 138.59 103.83 277.18 30.62 69.30 138.59 103.83 277.18 30.63 69.30 138.59 103.83 277.18 30.64 69.30 138.59 103.83 277.18 30.65 69.30 138.59 103.83 277.18 30.66 69.30 138.59 103.83 277.18 30.67 69.30 138.59 103.83 277.18 30.68 69.30 138.59 103.83 277.18 30.69 69.30 138.59 103.83 277.18 30.70 69.30 138.59 103.83 277.18 30.71 69.30 138.59 103.83 277.18 30.72 69.30 138.59 103.83 277.18 30.73 69.30 138.59 103.83 277.18 30.74 69.30 138.59 103.83 277.18 30.75 69.30 138.59 103.83 277.18 30.76 69.30 138.59 103.83 277.18 30.77 69.30 138.59 103.83 277.18 30.78 69.30 138.59 103.83 277.18 30.79 69.30 138.59 103.83 277.18 30.80 69.30 138.59 103.83 277.18 30.81 69.30 138.59 103.83 277.18 30.82 69.30 138.59 103.83 277.18 30.83 69.30 138.59 103.83 277.18 30.84 69.30 138.59 103.83 277.18 30.85 69.30 138.59 103.83 277.18 30.86 69.30 138.59 103.83 277.18 30.87 69.30 138.59 103.83 277.18 30.88 69.30 138.59 103.83 277.18 30.89 69.30 138.59 103.83 277.18 30.90 69.30 138.59 103.83 277.18 30.91 69.30 138.59 103.83 277.18 30.92 69.30 138.59 103.83 277.18 30.93 69.30 138.59 103.83 277.18 30.94 69.30 138.59 103.83 277.18 30.95 69.30 138.59 103.83 277.18 30.96 69.30 138.59 103.83 277.18 30.97 69.30 138.59 103.83 277.18 30.98 69.30 138.59 103.83 277.18 329.63 30.99 69.30 138.59 103.83 277.18 329.63 31.00 69.30 138.59 103.83 277.18 329.63 31.01 69.30 138.59 103.83 277.18 329.63 31.02 69.30 138.59 103.83 277.18 329.63 31.03 69.30 138.59 103.83 329.63 31.04 69.30 138.59 103.83 329.63 31.05 69.30 138.59 103.83 329.63 31.06 69.30 138.59 103.83 329.63 31.07 69.30 138.59 103.83 329.63 31.08 69.30 138.59 103.83 329.63 31.09 69.30 138.59 103.83 329.63 31.10 69.30 138.59 103.83 329.63 31.11 69.30 138.59 103.83 329.63 31.12 69.30 138.59 103.83 329.63 31.13 69.30 138.59 103.83 329.63 31.14 69.30 138.59 103.83 329.63 31.15 69.30 138.59 103.83 329.63 31.16 69.30 138.59 103.83 329.63 31.17 69.30 138.59 103.83 329.63 31.18 69.30 138.59 103.83 329.63 31.19 69.30 138.59 103.83 329.63 31.20 69.30 138.59 103.83 329.63 31.21 69.30 138.59 103.83 329.63 31.22 69.30 138.59 103.83 329.63 31.23 69.30 138.59 103.83 329.63 31.24 69.30 138.59 103.83 329.63 31.25 69.30 138.59 103.83 329.63 31.26 69.30 138.59 103.83 329.63 31.27 69.30 138.59 103.83 329.63 31.28 69.30 138.59 103.83 329.63 31.29 69.30 138.59 103.83 329.63 31.30 69.30 138.59 103.83 329.63 31.31 69.30 138.59 103.83 329.63 31.32 69.30 138.59 103.83 329.63 31.33 69.30 138.59 103.83 329.63 31.34 69.30 138.59 103.83 329.63 31.35 69.30 138.59 103.83 329.63 31.36 69.30 138.59 103.83 329.63 31.37 69.30 138.59 103.83 329.63 31.38 69.30 138.59 103.83 329.63 31.39 69.30 138.59 103.83 329.63 31.40 69.30 138.59 103.83 329.63 31.41 69.30 138.59 103.83 329.63 31.42 69.30 138.59 103.83 329.63 31.43 69.30 138.59 103.83 329.63 31.44 69.30 138.59 103.83 329.63 31.45 69.30 138.59 103.83 329.63 31.46 69.30 138.59 103.83 329.63 31.47 69.30 138.59 103.83 329.63 31.48 69.30 138.59 103.83 329.63 31.49 69.30 138.59 103.83 329.63 207.65 415.30 31.50 69.30 138.59 103.83 329.63 207.65 415.30 31.51 69.30 138.59 103.83 329.63 207.65 415.30 31.52 69.30 138.59 103.83 207.65 415.30 31.53 69.30 138.59 103.83 207.65 415.30 31.54 69.30 138.59 103.83 207.65 415.30 31.55 69.30 138.59 103.83 207.65 415.30 31.56 69.30 138.59 103.83 207.65 415.30 31.57 69.30 138.59 103.83 207.65 415.30 31.58 69.30 138.59 103.83 207.65 415.30 31.59 69.30 138.59 103.83 207.65 415.30 31.60 69.30 138.59 103.83 207.65 415.30 31.61 69.30 138.59 103.83 207.65 415.30 31.62 69.30 138.59 103.83 207.65 415.30 31.63 69.30 138.59 103.83 207.65 415.30 31.64 69.30 138.59 103.83 207.65 415.30 31.65 69.30 138.59 103.83 207.65 415.30 31.66 69.30 138.59 103.83 207.65 415.30 31.67 69.30 138.59 103.83 207.65 415.30 31.68 69.30 138.59 103.83 207.65 415.30 31.69 69.30 138.59 103.83 207.65 415.30 31.70 69.30 138.59 103.83 207.65 415.30 31.71 69.30 138.59 103.83 207.65 415.30 31.72 69.30 138.59 103.83 207.65 415.30 31.73 69.30 138.59 103.83 207.65 415.30 31.74 69.30 138.59 103.83 207.65 415.30 31.75 69.30 138.59 103.83 207.65 415.30 31.76 69.30 138.59 103.83 207.65 415.30 31.77 69.30 138.59 103.83 207.65 415.30 31.78 69.30 138.59 103.83 207.65 415.30 31.79 69.30 138.59 103.83 207.65 415.30 31.80 69.30 138.59 103.83 207.65 415.30 31.81 69.30 138.59 103.83 207.65 415.30 31.82 69.30 138.59 103.83 207.65 415.30 31.83 69.30 138.59 103.83 207.65 415.30 31.84 69.30 138.59 103.83 207.65 415.30 31.85 69.30 138.59 103.83 207.65 415.30 31.86 69.30 138.59 103.83 207.65 415.30 31.87 69.30 138.59 103.83 207.65 415.30 31.88 69.30 138.59 103.83 415.30 31.89 69.30 138.59 103.83 415.30 31.90 69.30 138.59 103.83 415.30 31.91 69.30 138.59 103.83 415.30 31.92 69.30 138.59 103.83 415.30 31.93 69.30 138.59 103.83 415.30 31.94 69.30 138.59 103.83 415.30 277.18 31.95 69.30 138.59 103.83 415.30 277.18 31.96 69.30 138.59 103.83 415.30 277.18 31.97 69.30 138.59 103.83 415.30 277.18 31.98 69.30 138.59 103.83 415.30 277.18 31.99 69.30 138.59 103.83 415.30 277.18 32.00 69.30 138.59 103.83 415.30 277.18 32.01 69.30 138.59 103.83 415.30 277.18 32.02 69.30 138.59 103.83 415.30 277.18 32.03 69.30 138.59 103.83 415.30 277.18 32.04 69.30 138.59 103.83 415.30 277.18 32.05 69.30 138.59 103.83 415.30 277.18 32.06 69.30 138.59 103.83 415.30 277.18 32.07 69.30 138.59 103.83 415.30 277.18 32.08 69.30 138.59 103.83 415.30 277.18 32.09 69.30 138.59 103.83 415.30 277.18 32.10 69.30 138.59 103.83 415.30 277.18 32.11 69.30 138.59 103.83 415.30 277.18 32.12 69.30 138.59 103.83 415.30 277.18 32.13 69.30 138.59 103.83 415.30 277.18 32.14 69.30 138.59 103.83 415.30 277.18 32.15 69.30 138.59 103.83 415.30 277.18 32.16 69.30 138.59 103.83 415.30 277.18 32.17 69.30 138.59 103.83 415.30 277.18 32.18 69.30 138.59 103.83 415.30 277.18 32.19 69.30 138.59 103.83 415.30 277.18 32.20 69.30 138.59 103.83 415.30 277.18 32.21 69.30 138.59 103.83 415.30 277.18 32.22 69.30 138.59 103.83 415.30 277.18 32.23 69.30 138.59 103.83 415.30 277.18 32.24 69.30 138.59 103.83 415.30 277.18 32.25 69.30 138.59 103.83 415.30 32.26 69.30 138.59 103.83 415.30 32.27 69.30 138.59 103.83 415.30 32.28 69.30 138.59 103.83 415.30 32.29 69.30 138.59 103.83 415.30 32.30 69.30 138.59 103.83 415.30 32.31 69.30 138.59 103.83 415.30 32.32 69.30 138.59 103.83 415.30 329.63 32.33 69.30 138.59 103.83 415.30 329.63 32.34 69.30 138.59 103.83 415.30 329.63 32.35 69.30 138.59 103.83 415.30 329.63 32.36 69.30 138.59 103.83 415.30 329.63 32.37 69.30 138.59 103.83 415.30 329.63 32.38 69.30 138.59 103.83 415.30 329.63 32.39 69.30 138.59 103.83 415.30 329.63 32.40 69.30 138.59 103.83 415.30 329.63 32.41 69.30 138.59 103.83 415.30 329.63 32.42 69.30 138.59 103.83 415.30 329.63 32.43 69.30 138.59 103.83 415.30 329.63 32.44 69.30 138.59 103.83 415.30 329.63 32.45 69.30 138.59 103.83 415.30 329.63 32.46 69.30 138.59 103.83 415.30 329.63 32.47 69.30 138.59 103.83 415.30 329.63 32.48 69.30 138.59 103.83 415.30 329.63 32.49 69.30 138.59 103.83 329.63 32.50 69.30 138.59 103.83 329.63 32.51 69.30 138.59 103.83 329.63 32.52 69.30 138.59 103.83 329.63 32.53 69.30 138.59 103.83 329.63 32.54 69.30 138.59 103.83 329.63 32.55 69.30 138.59 103.83 329.63 32.56 69.30 138.59 103.83 329.63 32.57 69.30 138.59 103.83 329.63 32.58 69.30 138.59 103.83 329.63 32.59 69.30 138.59 103.83 329.63 32.60 69.30 138.59 103.83 329.63 32.61 69.30 138.59 103.83 329.63 32.62 69.30 138.59 103.83 329.63 32.63 69.30 138.59 32.64 69.30 138.59 32.65 69.30 138.59 32.66 69.30 138.59 32.67 69.30 138.59 32.68 69.30 138.59 32.69 69.30 32.70 69.30 32.71 69.30 32.72 32.73 32.74 32.75 415.30 32.76 415.30 32.77 415.30 32.78 415.30 32.79 415.30 32.80 415.30 32.81 415.30 32.82 415.30 32.83 415.30 32.84 415.30 32.85 415.30 32.86 415.30 32.87 415.30 32.88 415.30 32.89 415.30 32.90 415.30 32.91 415.30 32.92 415.30 32.93 415.30 32.94 415.30 32.95 415.30 32.96 415.30 32.97 415.30 32.98 415.30 32.99 415.30 33.00 415.30 33.01 415.30 33.02 415.30 33.03 415.30 33.04 415.30 33.05 33.06 33.07 33.08 33.09 33.10 65.41 103.83 33.11 65.41 103.83 130.81 33.12 65.41 103.83 130.81 33.13 65.41 103.83 130.81 33.14 65.41 103.83 130.81 415.30 207.65 33.15 65.41 103.83 130.81 415.30 207.65 33.16 65.41 103.83 130.81 415.30 207.65 33.17 65.41 103.83 130.81 415.30 207.65 33.18 65.41 103.83 130.81 415.30 207.65 33.19 65.41 103.83 130.81 415.30 207.65 33.20 65.41 103.83 130.81 415.30 207.65 33.21 65.41 103.83 130.81 415.30 207.65 33.22 65.41 103.83 130.81 415.30 207.65 33.23 65.41 103.83 130.81 415.30 207.65 33.24 65.41 103.83 130.81 415.30 207.65 33.25 65.41 103.83 130.81 415.30 207.65 33.26 65.41 103.83 130.81 415.30 207.65 33.27 65.41 103.83 130.81 415.30 207.65 33.28 65.41 103.83 130.81 415.30 207.65 33.29 65.41 103.83 130.81 415.30 207.65 33.30 65.41 103.83 130.81 415.30 207.65 33.31 65.41 103.83 130.81 415.30 207.65 33.32 65.41 103.83 130.81 415.30 207.65 33.33 65.41 103.83 130.81 415.30 207.65 33.34 65.41 103.83 130.81 415.30 207.65 33.35 65.41 103.83 130.81 415.30 207.65 33.36 65.41 103.83 130.81 415.30 207.65 33.37 65.41 103.83 130.81 415.30 207.65 33.38 65.41 103.83 130.81 415.30 207.65 33.39 65.41 103.83 130.81 415.30 207.65 33.40 65.41 103.83 130.81 415.30 207.65 33.41 65.41 103.83 130.81 415.30 207.65 33.42 65.41 103.83 130.81 415.30 207.65 33.43 65.41 103.83 130.81 415.30 207.65 33.44 65.41 103.83 130.81 415.30 207.65 33.45 65.41 103.83 130.81 415.30 207.65 33.46 65.41 103.83 130.81 415.30 207.65 33.47 65.41 103.83 130.81 415.30 207.65 33.48 65.41 103.83 130.81 415.30 207.65 33.49 65.41 103.83 130.81 415.30 207.65 33.50 65.41 103.83 130.81 415.30 207.65 33.51 65.41 103.83 130.81 415.30 207.65 33.52 65.41 103.83 130.81 415.30 207.65 33.53 65.41 103.83 130.81 415.30 207.65 33.54 65.41 103.83 130.81 415.30 207.65 33.55 65.41 103.83 130.81 415.30 207.65 33.56 65.41 103.83 130.81 415.30 207.65 33.57 65.41 103.83 130.81 415.30 207.65 33.58 65.41 103.83 130.81 415.30 207.65 33.59 65.41 103.83 130.81 415.30 207.65 33.60 65.41 103.83 130.81 415.30 207.65 33.61 65.41 103.83 130.81 415.30 207.65 33.62 65.41 103.83 130.81 415.30 207.65 33.63 65.41 103.83 130.81 415.30 207.65 33.64 65.41 103.83 130.81 415.30 207.65 33.65 65.41 103.83 130.81 415.30 207.65 33.66 65.41 103.83 130.81 415.30 207.65 33.67 65.41 103.83 130.81 415.30 207.65 33.68 65.41 103.83 130.81 415.30 207.65 33.69 65.41 103.83 130.81 415.30 207.65 33.70 65.41 103.83 130.81 415.30 207.65 33.71 65.41 103.83 130.81 415.30 207.65 33.72 65.41 103.83 130.81 415.30 207.65 33.73 65.41 103.83 130.81 415.30 207.65 33.74 65.41 103.83 130.81 415.30 207.65 33.75 65.41 103.83 130.81 415.30 207.65 33.76 65.41 103.83 130.81 415.30 207.65 33.77 65.41 103.83 130.81 415.30 207.65 311.13 33.78 65.41 103.83 130.81 415.30 207.65 311.13 33.79 65.41 103.83 130.81 415.30 207.65 311.13 33.80 65.41 103.83 130.81 415.30 207.65 311.13 33.81 65.41 103.83 130.81 415.30 207.65 311.13 33.82 65.41 103.83 130.81 415.30 207.65 311.13 33.83 65.41 103.83 130.81 415.30 207.65 311.13 33.84 65.41 103.83 130.81 415.30 207.65 311.13 33.85 65.41 103.83 130.81 415.30 207.65 311.13 33.86 65.41 103.83 130.81 415.30 207.65 311.13 33.87 65.41 103.83 130.81 415.30 207.65 311.13 33.88 65.41 103.83 130.81 415.30 311.13 33.89 65.41 103.83 130.81 415.30 311.13 33.90 65.41 103.83 130.81 415.30 311.13 33.91 65.41 103.83 130.81 415.30 311.13 33.92 65.41 103.83 130.81 415.30 311.13 33.93 65.41 103.83 130.81 415.30 311.13 33.94 65.41 103.83 130.81 415.30 311.13 33.95 65.41 103.83 130.81 415.30 311.13 33.96 65.41 103.83 130.81 415.30 311.13 33.97 65.41 103.83 130.81 415.30 311.13 33.98 65.41 103.83 130.81 415.30 311.13 33.99 65.41 103.83 130.81 415.30 311.13 34.00 65.41 103.83 130.81 415.30 311.13 34.01 65.41 103.83 130.81 415.30 311.13 34.02 65.41 103.83 130.81 415.30 311.13 34.03 65.41 103.83 130.81 415.30 311.13 34.04 65.41 103.83 130.81 415.30 311.13 34.05 65.41 103.83 130.81 415.30 311.13 34.06 65.41 103.83 130.81 415.30 311.13 34.07 65.41 103.83 130.81 415.30 311.13 34.08 65.41 103.83 130.81 415.30 311.13 34.09 65.41 103.83 130.81 415.30 311.13 34.10 65.41 103.83 130.81 415.30 311.13 34.11 65.41 103.83 130.81 415.30 311.13 34.12 65.41 103.83 130.81 415.30 311.13 34.13 65.41 103.83 130.81 415.30 311.13 34.14 65.41 103.83 130.81 415.30 311.13 34.15 65.41 103.83 130.81 415.30 311.13 34.16 65.41 103.83 130.81 415.30 311.13 34.17 65.41 103.83 130.81 415.30 311.13 34.18 65.41 103.83 130.81 415.30 311.13 34.19 65.41 103.83 130.81 415.30 311.13 34.20 65.41 103.83 130.81 415.30 311.13 34.21 65.41 103.83 130.81 415.30 311.13 34.22 65.41 103.83 130.81 415.30 311.13 34.23 65.41 103.83 130.81 415.30 311.13 34.24 65.41 103.83 130.81 415.30 311.13 34.25 65.41 103.83 130.81 415.30 311.13 34.26 65.41 103.83 130.81 415.30 311.13 34.27 65.41 103.83 130.81 415.30 311.13 34.28 65.41 103.83 130.81 415.30 311.13 369.99 34.29 65.41 103.83 130.81 415.30 311.13 369.99 34.30 65.41 103.83 130.81 415.30 311.13 369.99 34.31 65.41 103.83 130.81 415.30 369.99 34.32 65.41 103.83 130.81 415.30 369.99 34.33 65.41 103.83 130.81 415.30 369.99 34.34 65.41 103.83 130.81 415.30 369.99 34.35 65.41 103.83 130.81 415.30 369.99 34.36 65.41 103.83 130.81 415.30 369.99 34.37 65.41 103.83 130.81 415.30 369.99 34.38 65.41 103.83 130.81 415.30 369.99 34.39 65.41 103.83 130.81 415.30 369.99 34.40 65.41 103.83 130.81 415.30 369.99 34.41 65.41 103.83 130.81 415.30 369.99 34.42 65.41 103.83 130.81 415.30 369.99 34.43 65.41 103.83 130.81 415.30 369.99 34.44 65.41 103.83 130.81 415.30 369.99 34.45 65.41 103.83 130.81 415.30 369.99 34.46 65.41 103.83 130.81 415.30 369.99 34.47 65.41 103.83 130.81 415.30 369.99 34.48 65.41 103.83 130.81 415.30 369.99 34.49 65.41 103.83 130.81 415.30 369.99 34.50 65.41 103.83 130.81 415.30 369.99 34.51 65.41 103.83 130.81 415.30 369.99 34.52 65.41 103.83 130.81 415.30 369.99 34.53 65.41 103.83 130.81 415.30 369.99 34.54 65.41 103.83 130.81 415.30 369.99 34.55 65.41 103.83 130.81 415.30 369.99 34.56 65.41 103.83 130.81 415.30 369.99 34.57 65.41 103.83 130.81 415.30 369.99 34.58 65.41 103.83 130.81 415.30 369.99 34.59 65.41 103.83 130.81 415.30 369.99 34.60 65.41 103.83 130.81 415.30 369.99 34.61 65.41 103.83 130.81 415.30 369.99 34.62 65.41 103.83 130.81 415.30 369.99 34.63 65.41 103.83 130.81 415.30 369.99 34.64 65.41 103.83 130.81 415.30 369.99 34.65 65.41 103.83 130.81 415.30 369.99 34.66 65.41 103.83 130.81 415.30 369.99 34.67 65.41 103.83 130.81 415.30 369.99 34.68 65.41 103.83 130.81 415.30 369.99 34.69 65.41 103.83 130.81 415.30 369.99 34.70 65.41 103.83 130.81 415.30 369.99 34.71 65.41 103.83 130.81 415.30 369.99 34.72 65.41 103.83 130.81 415.30 369.99 34.73 65.41 103.83 130.81 415.30 369.99 34.74 65.41 103.83 130.81 415.30 369.99 34.75 65.41 103.83 130.81 415.30 369.99 34.76 65.41 103.83 130.81 415.30 369.99 34.77 65.41 103.83 130.81 415.30 369.99 207.65 34.78 65.41 103.83 130.81 415.30 369.99 207.65 34.79 65.41 103.83 130.81 415.30 369.99 207.65 34.80 65.41 103.83 130.81 415.30 369.99 207.65 34.81 65.41 103.83 130.81 415.30 369.99 207.65 34.82 65.41 103.83 130.81 415.30 207.65 34.83 65.41 103.83 130.81 415.30 207.65 34.84 65.41 103.83 130.81 415.30 207.65 34.85 65.41 103.83 130.81 415.30 207.65 34.86 65.41 103.83 130.81 415.30 207.65 34.87 65.41 103.83 130.81 415.30 207.65 34.88 65.41 103.83 130.81 415.30 207.65 34.89 65.41 103.83 130.81 415.30 207.65 34.90 65.41 103.83 130.81 415.30 207.65 34.91 65.41 103.83 130.81 415.30 207.65 34.92 65.41 103.83 130.81 415.30 207.65 34.93 65.41 103.83 130.81 415.30 207.65 34.94 65.41 103.83 130.81 415.30 207.65 34.95 65.41 103.83 130.81 415.30 207.65 34.96 65.41 103.83 130.81 415.30 207.65 34.97 65.41 103.83 130.81 415.30 207.65 34.98 65.41 103.83 130.81 415.30 207.65 34.99 65.41 103.83 130.81 415.30 207.65 35.00 65.41 103.83 130.81 415.30 207.65 35.01 65.41 103.83 130.81 415.30 207.65 35.02 65.41 103.83 130.81 415.30 207.65 35.03 65.41 103.83 130.81 415.30 207.65 35.04 65.41 103.83 130.81 415.30 207.65 35.05 65.41 103.83 130.81 415.30 207.65 35.06 65.41 103.83 130.81 415.30 207.65 35.07 65.41 103.83 130.81 415.30 207.65 35.08 65.41 103.83 130.81 415.30 207.65 35.09 65.41 103.83 130.81 415.30 207.65 35.10 65.41 103.83 130.81 415.30 207.65 35.11 65.41 103.83 130.81 415.30 207.65 35.12 65.41 103.83 130.81 415.30 207.65 35.13 65.41 103.83 130.81 415.30 207.65 35.14 65.41 103.83 130.81 415.30 207.65 35.15 65.41 103.83 130.81 415.30 207.65 35.16 65.41 103.83 130.81 415.30 207.65 35.17 65.41 103.83 130.81 415.30 207.65 35.18 65.41 103.83 130.81 415.30 207.65 35.19 65.41 103.83 130.81 415.30 207.65 35.20 65.41 103.83 130.81 415.30 207.65 35.21 65.41 103.83 130.81 415.30 207.65 35.22 65.41 103.83 130.81 415.30 207.65 35.23 65.41 103.83 130.81 415.30 207.65 35.24 65.41 103.83 130.81 415.30 207.65 35.25 65.41 103.83 130.81 415.30 207.65 35.26 65.41 103.83 130.81 415.30 207.65 35.27 65.41 103.83 130.81 415.30 207.65 35.28 65.41 103.83 130.81 415.30 207.65 35.29 65.41 103.83 130.81 415.30 207.65 35.30 65.41 103.83 130.81 415.30 207.65 311.13 35.31 65.41 103.83 130.81 415.30 207.65 311.13 35.32 65.41 103.83 130.81 415.30 207.65 311.13 35.33 65.41 103.83 130.81 415.30 207.65 311.13 35.34 65.41 103.83 130.81 415.30 207.65 311.13 35.35 65.41 103.83 130.81 415.30 311.13 35.36 65.41 103.83 130.81 415.30 311.13 35.37 65.41 103.83 130.81 415.30 311.13 35.38 65.41 103.83 130.81 415.30 311.13 35.39 65.41 103.83 130.81 415.30 311.13 35.40 65.41 103.83 130.81 415.30 311.13 35.41 65.41 103.83 130.81 415.30 311.13 35.42 65.41 103.83 130.81 415.30 311.13 35.43 65.41 103.83 130.81 415.30 311.13 35.44 65.41 103.83 130.81 415.30 311.13 35.45 65.41 103.83 130.81 415.30 311.13 35.46 65.41 103.83 130.81 415.30 311.13 35.47 65.41 103.83 130.81 415.30 311.13 35.48 65.41 103.83 130.81 415.30 311.13 35.49 65.41 103.83 130.81 415.30 311.13 35.50 65.41 103.83 130.81 415.30 311.13 35.51 65.41 103.83 130.81 415.30 311.13 35.52 65.41 103.83 130.81 415.30 311.13 35.53 65.41 103.83 130.81 415.30 311.13 35.54 65.41 103.83 130.81 415.30 311.13 35.55 65.41 103.83 130.81 415.30 311.13 35.56 65.41 103.83 130.81 415.30 311.13 35.57 65.41 103.83 130.81 415.30 311.13 35.58 65.41 103.83 130.81 415.30 311.13 35.59 65.41 103.83 130.81 415.30 311.13 35.60 65.41 103.83 130.81 415.30 311.13 35.61 65.41 103.83 130.81 415.30 311.13 35.62 65.41 103.83 130.81 415.30 311.13 35.63 65.41 103.83 130.81 415.30 311.13 35.64 65.41 103.83 130.81 415.30 311.13 35.65 65.41 103.83 130.81 415.30 311.13 35.66 65.41 103.83 130.81 415.30 311.13 35.67 65.41 103.83 130.81 415.30 311.13 35.68 65.41 103.83 130.81 415.30 311.13 35.69 65.41 103.83 130.81 415.30 311.13 35.70 65.41 103.83 130.81 415.30 311.13 35.71 65.41 103.83 130.81 415.30 311.13 35.72 65.41 103.83 130.81 415.30 311.13 35.73 65.41 103.83 130.81 415.30 311.13 35.74 65.41 103.83 130.81 415.30 311.13 35.75 65.41 103.83 130.81 415.30 311.13 35.76 65.41 103.83 130.81 415.30 311.13 35.77 65.41 103.83 130.81 415.30 311.13 35.78 65.41 103.83 130.81 415.30 311.13 35.79 65.41 103.83 130.81 415.30 311.13 369.99 35.80 65.41 103.83 130.81 415.30 311.13 369.99 35.81 65.41 103.83 130.81 415.30 311.13 369.99 35.82 65.41 103.83 130.81 415.30 369.99 35.83 65.41 103.83 130.81 415.30 369.99 35.84 65.41 103.83 130.81 415.30 369.99 35.85 65.41 103.83 130.81 415.30 369.99 35.86 65.41 103.83 130.81 415.30 369.99 35.87 65.41 103.83 130.81 415.30 369.99 35.88 65.41 103.83 130.81 415.30 369.99 35.89 65.41 103.83 130.81 415.30 369.99 35.90 65.41 103.83 130.81 415.30 369.99 35.91 65.41 103.83 130.81 415.30 369.99 35.92 65.41 103.83 130.81 415.30 369.99 35.93 65.41 103.83 130.81 415.30 369.99 35.94 65.41 103.83 130.81 415.30 369.99 35.95 65.41 103.83 130.81 415.30 369.99 35.96 65.41 103.83 130.81 415.30 369.99 35.97 65.41 103.83 130.81 415.30 369.99 35.98 65.41 103.83 130.81 415.30 369.99 35.99 65.41 103.83 130.81 415.30 369.99 36.00 65.41 103.83 130.81 415.30 369.99 36.01 65.41 103.83 130.81 415.30 369.99 36.02 65.41 103.83 130.81 415.30 369.99 36.03 65.41 103.83 130.81 415.30 369.99 36.04 65.41 103.83 130.81 415.30 369.99 36.05 65.41 103.83 130.81 415.30 369.99 36.06 65.41 103.83 130.81 415.30 369.99 36.07 65.41 103.83 130.81 415.30 369.99 36.08 65.41 103.83 130.81 415.30 369.99 36.09 65.41 103.83 130.81 415.30 369.99 36.10 65.41 103.83 130.81 415.30 369.99 36.11 65.41 103.83 130.81 415.30 369.99 36.12 65.41 103.83 130.81 415.30 369.99 36.13 65.41 103.83 130.81 415.30 369.99 36.14 65.41 103.83 130.81 415.30 369.99 36.15 65.41 103.83 130.81 415.30 369.99 36.16 65.41 103.83 130.81 415.30 369.99 36.17 65.41 103.83 130.81 415.30 369.99 36.18 65.41 103.83 130.81 415.30 369.99 36.19 65.41 103.83 130.81 415.30 369.99 36.20 65.41 103.83 130.81 415.30 369.99 36.21 65.41 103.83 130.81 415.30 369.99 36.22 65.41 103.83 130.81 415.30 369.99 36.23 65.41 103.83 130.81 415.30 369.99 36.24 65.41 103.83 130.81 415.30 369.99 36.25 65.41 103.83 130.81 415.30 369.99 36.26 65.41 103.83 130.81 415.30 369.99 36.27 65.41 103.83 130.81 415.30 369.99 36.28 65.41 103.83 130.81 415.30 369.99 36.29 65.41 103.83 130.81 415.30 369.99 207.65 36.30 65.41 103.83 130.81 415.30 369.99 207.65 36.31 65.41 103.83 130.81 415.30 369.99 207.65 36.32 65.41 103.83 130.81 415.30 207.65 36.33 65.41 103.83 130.81 415.30 207.65 36.34 65.41 103.83 130.81 415.30 207.65 36.35 65.41 103.83 130.81 415.30 207.65 36.36 65.41 103.83 130.81 415.30 207.65 36.37 65.41 103.83 130.81 415.30 207.65 36.38 65.41 103.83 130.81 415.30 207.65 36.39 65.41 103.83 130.81 415.30 207.65 36.40 65.41 103.83 130.81 415.30 207.65 36.41 65.41 103.83 130.81 415.30 207.65 36.42 65.41 103.83 130.81 415.30 207.65 36.43 65.41 103.83 130.81 415.30 207.65 36.44 65.41 103.83 130.81 415.30 207.65 36.45 65.41 103.83 130.81 415.30 207.65 36.46 65.41 103.83 130.81 415.30 207.65 36.47 65.41 103.83 130.81 415.30 207.65 36.48 65.41 103.83 130.81 415.30 207.65 36.49 65.41 103.83 130.81 415.30 207.65 36.50 65.41 103.83 130.81 415.30 207.65 36.51 65.41 103.83 130.81 415.30 207.65 36.52 65.41 103.83 130.81 415.30 207.65 36.53 65.41 103.83 130.81 415.30 207.65 36.54 65.41 103.83 130.81 415.30 207.65 36.55 65.41 103.83 130.81 415.30 207.65 36.56 65.41 103.83 130.81 415.30 207.65 36.57 65.41 103.83 130.81 415.30 207.65 36.58 65.41 103.83 130.81 415.30 207.65 36.59 65.41 103.83 130.81 415.30 207.65 36.60 65.41 103.83 130.81 415.30 207.65 36.61 65.41 103.83 130.81 415.30 207.65 36.62 65.41 103.83 130.81 415.30 207.65 36.63 65.41 103.83 130.81 415.30 207.65 36.64 65.41 103.83 130.81 415.30 207.65 36.65 65.41 103.83 130.81 415.30 207.65 36.66 65.41 103.83 130.81 415.30 207.65 36.67 65.41 103.83 130.81 415.30 207.65 36.68 65.41 103.83 130.81 415.30 207.65 36.69 65.41 103.83 130.81 415.30 207.65 36.70 65.41 103.83 130.81 415.30 207.65 36.71 65.41 103.83 130.81 415.30 207.65 36.72 65.41 103.83 130.81 415.30 207.65 36.73 65.41 103.83 130.81 415.30 207.65 36.74 65.41 103.83 130.81 415.30 207.65 36.75 65.41 103.83 130.81 415.30 207.65 36.76 65.41 103.83 130.81 415.30 207.65 36.77 65.41 103.83 130.81 415.30 207.65 36.78 65.41 103.83 130.81 415.30 207.65 36.79 65.41 103.83 130.81 415.30 207.65 36.80 65.41 103.83 130.81 415.30 207.65 36.81 65.41 103.83 130.81 415.30 207.65 36.82 65.41 103.83 130.81 415.30 207.65 311.13 36.83 65.41 103.83 130.81 415.30 207.65 311.13 36.84 65.41 103.83 130.81 415.30 207.65 311.13 36.85 65.41 103.83 130.81 415.30 207.65 311.13 36.86 65.41 103.83 130.81 415.30 207.65 311.13 36.87 65.41 103.83 130.81 415.30 311.13 36.88 65.41 103.83 130.81 415.30 311.13 36.89 65.41 103.83 130.81 415.30 311.13 36.90 65.41 103.83 130.81 415.30 311.13 36.91 65.41 103.83 130.81 415.30 311.13 36.92 65.41 103.83 130.81 415.30 311.13 36.93 65.41 103.83 130.81 415.30 311.13 36.94 65.41 103.83 130.81 415.30 311.13 36.95 65.41 103.83 130.81 415.30 311.13 36.96 65.41 103.83 130.81 415.30 311.13 36.97 65.41 103.83 130.81 415.30 311.13 36.98 65.41 103.83 130.81 415.30 311.13 36.99 65.41 103.83 130.81 415.30 311.13 37.00 65.41 103.83 130.81 415.30 311.13 37.01 65.41 103.83 130.81 415.30 311.13 37.02 65.41 103.83 130.81 415.30 311.13 37.03 65.41 103.83 130.81 415.30 311.13 37.04 65.41 103.83 130.81 415.30 311.13 37.05 65.41 103.83 130.81 415.30 311.13 37.06 65.41 103.83 130.81 415.30 311.13 37.07 65.41 103.83 130.81 415.30 311.13 37.08 65.41 103.83 130.81 415.30 311.13 37.09 65.41 103.83 130.81 415.30 311.13 37.10 65.41 103.83 130.81 415.30 311.13 37.11 65.41 103.83 130.81 415.30 311.13 37.12 65.41 103.83 130.81 415.30 311.13 37.13 65.41 103.83 130.81 415.30 311.13 37.14 65.41 103.83 130.81 415.30 311.13 37.15 65.41 103.83 130.81 415.30 311.13 37.16 65.41 103.83 130.81 415.30 311.13 37.17 65.41 103.83 130.81 415.30 311.13 37.18 65.41 103.83 130.81 415.30 311.13 37.19 65.41 103.83 130.81 415.30 311.13 37.20 65.41 103.83 130.81 415.30 311.13 37.21 65.41 103.83 130.81 415.30 311.13 37.22 65.41 103.83 130.81 415.30 311.13 37.23 65.41 103.83 130.81 415.30 311.13 37.24 65.41 103.83 130.81 415.30 311.13 37.25 65.41 103.83 130.81 415.30 311.13 37.26 65.41 103.83 130.81 415.30 311.13 37.27 65.41 103.83 130.81 415.30 311.13 369.99 37.28 65.41 103.83 130.81 415.30 311.13 369.99 37.29 65.41 103.83 130.81 415.30 311.13 369.99 37.30 65.41 103.83 130.81 415.30 369.99 37.31 65.41 103.83 130.81 415.30 369.99 37.32 65.41 103.83 130.81 415.30 369.99 37.33 65.41 103.83 130.81 415.30 369.99 37.34 65.41 103.83 130.81 415.30 369.99 37.35 65.41 103.83 130.81 415.30 369.99 37.36 65.41 103.83 130.81 415.30 369.99 37.37 65.41 103.83 130.81 415.30 369.99 37.38 65.41 103.83 130.81 415.30 369.99 37.39 65.41 103.83 130.81 415.30 369.99 37.40 65.41 103.83 130.81 415.30 369.99 37.41 65.41 103.83 130.81 415.30 369.99 37.42 65.41 103.83 130.81 415.30 369.99 37.43 65.41 103.83 130.81 415.30 369.99 37.44 65.41 103.83 130.81 415.30 369.99 37.45 65.41 103.83 130.81 415.30 369.99 37.46 65.41 103.83 130.81 415.30 369.99 37.47 65.41 103.83 130.81 415.30 369.99 37.48 65.41 103.83 130.81 415.30 369.99 37.49 65.41 103.83 130.81 415.30 369.99 37.50 65.41 103.83 130.81 415.30 369.99 37.51 65.41 103.83 130.81 415.30 369.99 37.52 65.41 103.83 130.81 415.30 369.99 37.53 65.41 103.83 130.81 415.30 369.99 37.54 65.41 103.83 130.81 415.30 369.99 37.55 65.41 103.83 130.81 415.30 369.99 37.56 65.41 103.83 130.81 415.30 369.99 37.57 65.41 103.83 130.81 415.30 369.99 37.58 65.41 103.83 130.81 415.30 369.99 37.59 65.41 103.83 130.81 415.30 369.99 37.60 65.41 103.83 130.81 415.30 369.99 37.61 65.41 103.83 130.81 415.30 369.99 37.62 65.41 103.83 130.81 415.30 369.99 37.63 65.41 103.83 130.81 369.99 37.64 65.41 103.83 130.81 369.99 37.65 65.41 103.83 130.81 369.99 37.66 65.41 103.83 130.81 369.99 37.67 65.41 103.83 130.81 369.99 37.68 65.41 103.83 130.81 369.99 37.69 65.41 103.83 130.81 369.99 37.70 65.41 103.83 130.81 369.99 37.71 65.41 103.83 130.81 369.99 37.72 65.41 103.83 130.81 369.99 37.73 65.41 103.83 130.81 369.99 37.74 65.41 103.83 130.81 369.99 37.75 65.41 103.83 130.81 369.99 37.76 65.41 103.83 130.81 369.99 207.65 37.77 65.41 103.83 130.81 369.99 207.65 415.30 37.78 65.41 103.83 130.81 369.99 207.65 415.30 37.79 65.41 103.83 130.81 369.99 207.65 415.30 37.80 65.41 103.83 130.81 207.65 415.30 37.81 65.41 103.83 130.81 207.65 415.30 37.82 65.41 103.83 130.81 207.65 415.30 37.83 65.41 103.83 130.81 207.65 415.30 37.84 65.41 103.83 130.81 207.65 415.30 37.85 65.41 103.83 130.81 207.65 415.30 37.86 65.41 103.83 130.81 207.65 415.30 37.87 65.41 103.83 130.81 207.65 415.30 37.88 65.41 103.83 130.81 207.65 415.30 37.89 65.41 103.83 130.81 207.65 415.30 37.90 65.41 103.83 130.81 207.65 415.30 37.91 65.41 103.83 130.81 207.65 415.30 37.92 65.41 103.83 130.81 207.65 415.30 37.93 65.41 103.83 130.81 207.65 415.30 37.94 65.41 103.83 130.81 207.65 415.30 37.95 65.41 103.83 130.81 207.65 415.30 37.96 65.41 103.83 130.81 207.65 415.30 37.97 65.41 103.83 130.81 207.65 415.30 37.98 65.41 103.83 130.81 207.65 415.30 37.99 65.41 103.83 130.81 207.65 415.30 38.00 65.41 103.83 130.81 207.65 415.30 38.01 65.41 103.83 130.81 207.65 415.30 38.02 65.41 103.83 130.81 207.65 415.30 38.03 65.41 103.83 130.81 207.65 415.30 38.04 65.41 103.83 130.81 207.65 415.30 38.05 65.41 103.83 130.81 207.65 415.30 38.06 65.41 103.83 130.81 207.65 415.30 38.07 65.41 103.83 130.81 207.65 415.30 38.08 65.41 103.83 130.81 207.65 415.30 38.09 65.41 103.83 130.81 207.65 415.30 38.10 65.41 103.83 130.81 207.65 415.30 38.11 65.41 103.83 130.81 207.65 415.30 38.12 65.41 103.83 130.81 207.65 415.30 38.13 65.41 103.83 130.81 207.65 415.30 38.14 65.41 103.83 130.81 207.65 415.30 38.15 65.41 103.83 130.81 207.65 415.30 38.16 65.41 103.83 130.81 207.65 415.30 38.17 65.41 103.83 130.81 207.65 415.30 38.18 65.41 103.83 130.81 207.65 415.30 38.19 65.41 103.83 130.81 207.65 415.30 38.20 65.41 103.83 130.81 207.65 415.30 38.21 65.41 103.83 130.81 207.65 415.30 38.22 65.41 103.83 130.81 207.65 415.30 38.23 65.41 103.83 130.81 207.65 415.30 311.13 38.24 65.41 103.83 130.81 207.65 415.30 311.13 38.25 65.41 103.83 130.81 207.65 415.30 311.13 38.26 65.41 103.83 130.81 207.65 415.30 311.13 38.27 65.41 103.83 130.81 207.65 415.30 311.13 38.28 65.41 103.83 130.81 207.65 415.30 311.13 38.29 65.41 103.83 130.81 207.65 415.30 311.13 38.30 65.41 103.83 130.81 207.65 415.30 311.13 38.31 65.41 103.83 130.81 207.65 415.30 311.13 38.32 65.41 103.83 130.81 207.65 415.30 311.13 38.33 65.41 103.83 130.81 207.65 415.30 311.13 38.34 65.41 103.83 130.81 207.65 415.30 311.13 38.35 65.41 103.83 130.81 207.65 415.30 311.13 38.36 65.41 103.83 130.81 207.65 415.30 311.13 38.37 65.41 103.83 130.81 207.65 415.30 311.13 38.38 65.41 103.83 130.81 207.65 415.30 311.13 38.39 65.41 103.83 130.81 207.65 415.30 311.13 38.40 65.41 103.83 130.81 207.65 415.30 311.13 38.41 65.41 103.83 130.81 207.65 415.30 311.13 38.42 65.41 103.83 130.81 207.65 415.30 311.13 38.43 65.41 103.83 130.81 207.65 415.30 311.13 38.44 65.41 103.83 130.81 207.65 415.30 311.13 38.45 65.41 103.83 130.81 207.65 415.30 311.13 38.46 65.41 103.83 130.81 207.65 415.30 311.13 38.47 65.41 103.83 130.81 207.65 415.30 311.13 38.48 65.41 103.83 130.81 207.65 415.30 311.13 38.49 65.41 103.83 130.81 207.65 415.30 311.13 38.50 65.41 103.83 130.81 207.65 415.30 311.13 38.51 65.41 103.83 130.81 207.65 415.30 311.13 38.52 65.41 103.83 130.81 207.65 415.30 311.13 38.53 65.41 103.83 130.81 207.65 415.30 311.13 38.54 65.41 103.83 130.81 207.65 415.30 311.13 38.55 65.41 103.83 130.81 207.65 415.30 311.13 38.56 65.41 103.83 130.81 207.65 415.30 311.13 38.57 65.41 103.83 130.81 207.65 415.30 311.13 38.58 65.41 103.83 130.81 207.65 415.30 311.13 38.59 65.41 103.83 130.81 207.65 415.30 311.13 38.60 65.41 103.83 130.81 207.65 415.30 311.13 38.61 65.41 103.83 130.81 207.65 415.30 311.13 38.62 65.41 103.83 130.81 207.65 415.30 311.13 38.63 65.41 103.83 130.81 207.65 415.30 311.13 38.64 65.41 103.83 130.81 207.65 415.30 311.13 38.65 65.41 103.83 130.81 207.65 415.30 311.13 38.66 65.41 103.83 130.81 207.65 415.30 311.13 38.67 65.41 103.83 130.81 207.65 415.30 311.13 38.68 65.41 103.83 130.81 207.65 415.30 311.13 38.69 65.41 103.83 130.81 207.65 415.30 311.13 38.70 65.41 103.83 130.81 207.65 415.30 311.13 38.71 65.41 103.83 130.81 207.65 415.30 311.13 369.99 38.72 65.41 103.83 130.81 207.65 415.30 311.13 369.99 38.73 65.41 103.83 130.81 207.65 311.13 369.99 38.74 65.41 103.83 130.81 207.65 311.13 369.99 38.75 65.41 103.83 130.81 207.65 311.13 369.99 38.76 65.41 103.83 130.81 207.65 369.99 38.77 65.41 103.83 130.81 207.65 369.99 38.78 65.41 103.83 130.81 207.65 369.99 38.79 65.41 103.83 130.81 207.65 369.99 38.80 65.41 103.83 130.81 207.65 369.99 38.81 65.41 103.83 130.81 207.65 369.99 38.82 65.41 103.83 130.81 207.65 369.99 38.83 103.83 207.65 369.99 38.84 103.83 207.65 369.99 38.85 103.83 207.65 369.99 38.86 103.83 207.65 369.99 38.87 207.65 369.99 38.88 207.65 369.99 38.89 207.65 369.99 38.90 207.65 369.99 38.91 207.65 369.99 38.92 207.65 369.99 38.93 369.99 38.94 369.99 38.95 369.99 38.96 369.99 38.97 369.99 38.98 369.99 38.99 369.99 39.00 369.99 415.30 39.01 369.99 415.30 39.02 369.99 415.30 39.03 415.30 39.04 415.30 39.05 415.30 39.06 415.30 39.07 415.30 39.08 415.30 39.09 415.30 39.10 415.30 39.11 415.30 39.12 415.30 39.13 415.30 39.14 415.30 39.15 415.30 39.16 415.30 39.17 415.30 39.18 415.30 39.19 415.30 39.20 415.30 39.21 415.30 39.22 415.30 39.23 415.30 39.24 39.25 39.26 39.27 39.28 39.29 39.30 39.31 39.32 415.30 39.33 415.30 207.65 39.34 415.30 207.65 39.35 415.30 207.65 39.36 415.30 207.65 39.37 415.30 207.65 138.59 69.30 39.38 415.30 207.65 138.59 69.30 39.39 415.30 207.65 138.59 69.30 39.40 415.30 207.65 138.59 69.30 39.41 415.30 207.65 138.59 69.30 39.42 415.30 207.65 138.59 69.30 39.43 415.30 207.65 138.59 69.30 39.44 415.30 207.65 138.59 69.30 39.45 415.30 207.65 138.59 69.30 39.46 415.30 207.65 138.59 69.30 39.47 415.30 207.65 138.59 69.30 39.48 415.30 207.65 138.59 69.30 39.49 415.30 207.65 138.59 69.30 39.50 415.30 207.65 138.59 69.30 39.51 415.30 207.65 138.59 69.30 39.52 415.30 207.65 138.59 69.30 39.53 415.30 207.65 138.59 69.30 39.54 415.30 207.65 138.59 69.30 39.55 415.30 207.65 138.59 69.30 39.56 415.30 207.65 138.59 69.30 39.57 415.30 207.65 138.59 69.30 39.58 415.30 207.65 138.59 69.30 39.59 415.30 207.65 138.59 69.30 39.60 415.30 207.65 138.59 69.30 39.61 415.30 207.65 138.59 69.30 39.62 415.30 207.65 138.59 69.30 39.63 415.30 207.65 138.59 69.30 39.64 415.30 207.65 138.59 69.30 39.65 415.30 207.65 138.59 69.30 39.66 415.30 207.65 138.59 69.30 39.67 415.30 207.65 138.59 69.30 39.68 415.30 207.65 138.59 69.30 39.69 415.30 207.65 138.59 69.30 39.70 415.30 207.65 138.59 69.30 39.71 415.30 207.65 138.59 69.30 39.72 415.30 207.65 138.59 69.30 39.73 415.30 207.65 138.59 69.30 39.74 415.30 207.65 138.59 69.30 39.75 415.30 207.65 138.59 69.30 39.76 415.30 207.65 138.59 69.30 39.77 415.30 207.65 138.59 69.30 39.78 415.30 207.65 138.59 69.30 39.79 415.30 207.65 138.59 69.30 39.80 415.30 207.65 138.59 69.30 39.81 415.30 207.65 138.59 69.30 39.82 415.30 207.65 138.59 69.30 39.83 415.30 207.65 138.59 69.30 39.84 415.30 207.65 138.59 69.30 39.85 415.30 207.65 138.59 69.30 39.86 415.30 207.65 138.59 69.30 39.87 415.30 207.65 138.59 69.30 39.88 415.30 207.65 138.59 69.30 39.89 415.30 207.65 138.59 69.30 39.90 415.30 207.65 138.59 69.30 39.91 415.30 207.65 138.59 69.30 39.92 415.30 207.65 138.59 69.30 39.93 415.30 207.65 138.59 69.30 39.94 415.30 207.65 138.59 69.30 39.95 415.30 207.65 138.59 69.30 39.96 415.30 207.65 138.59 69.30 39.97 415.30 207.65 138.59 69.30 39.98 415.30 207.65 138.59 69.30 39.99 415.30 207.65 138.59 69.30 40.00 415.30 207.65 138.59 69.30 40.01 415.30 207.65 138.59 69.30 40.02 415.30 207.65 138.59 69.30 40.03 415.30 207.65 138.59 69.30 40.04 415.30 207.65 138.59 69.30 40.05 415.30 207.65 138.59 69.30 277.18 40.06 415.30 207.65 138.59 69.30 277.18 40.07 415.30 207.65 138.59 69.30 277.18 40.08 415.30 207.65 138.59 69.30 277.18 40.09 415.30 207.65 138.59 69.30 277.18 40.10 415.30 207.65 138.59 69.30 277.18 40.11 415.30 207.65 138.59 69.30 277.18 40.12 415.30 207.65 138.59 69.30 277.18 40.13 415.30 207.65 138.59 69.30 277.18 40.14 415.30 207.65 138.59 69.30 277.18 40.15 415.30 207.65 138.59 69.30 277.18 40.16 415.30 207.65 138.59 69.30 277.18 40.17 415.30 207.65 138.59 69.30 277.18 40.18 415.30 207.65 138.59 69.30 277.18 40.19 415.30 207.65 138.59 69.30 277.18 40.20 415.30 207.65 138.59 69.30 277.18 40.21 415.30 207.65 138.59 69.30 277.18 40.22 415.30 207.65 138.59 69.30 277.18 40.23 415.30 207.65 138.59 69.30 277.18 40.24 415.30 207.65 138.59 69.30 277.18 40.25 415.30 207.65 138.59 69.30 277.18 40.26 415.30 207.65 138.59 69.30 277.18 40.27 415.30 207.65 138.59 69.30 277.18 40.28 415.30 207.65 138.59 69.30 277.18 40.29 415.30 207.65 138.59 69.30 277.18 40.30 415.30 207.65 138.59 69.30 277.18 40.31 415.30 207.65 138.59 69.30 277.18 40.32 415.30 207.65 138.59 69.30 277.18 40.33 415.30 207.65 138.59 69.30 277.18 40.34 415.30 207.65 138.59 69.30 277.18 40.35 415.30 207.65 138.59 69.30 277.18 40.36 415.30 207.65 138.59 69.30 277.18 40.37 415.30 207.65 138.59 69.30 277.18 40.38 415.30 207.65 138.59 69.30 277.18 40.39 415.30 207.65 138.59 69.30 277.18 40.40 415.30 207.65 138.59 69.30 277.18 40.41 415.30 207.65 138.59 69.30 277.18 40.42 415.30 207.65 138.59 69.30 277.18 40.43 415.30 207.65 138.59 69.30 277.18 40.44 415.30 207.65 138.59 69.30 277.18 40.45 415.30 207.65 138.59 69.30 277.18 40.46 415.30 207.65 138.59 69.30 277.18 40.47 415.30 207.65 138.59 69.30 277.18 40.48 415.30 207.65 138.59 69.30 277.18 40.49 415.30 207.65 138.59 69.30 277.18 40.50 415.30 207.65 138.59 69.30 277.18 40.51 415.30 207.65 138.59 69.30 277.18 40.52 415.30 207.65 138.59 69.30 277.18 40.53 415.30 207.65 138.59 69.30 277.18 40.54 415.30 207.65 138.59 69.30 277.18 40.55 415.30 207.65 138.59 69.30 277.18 40.56 415.30 207.65 138.59 69.30 277.18 40.57 415.30 207.65 138.59 69.30 277.18 40.58 415.30 207.65 138.59 69.30 277.18 40.59 415.30 207.65 138.59 69.30 277.18 329.63 40.60 415.30 207.65 138.59 69.30 277.18 329.63 40.61 415.30 207.65 138.59 69.30 277.18 329.63 40.62 415.30 207.65 138.59 69.30 277.18 329.63 40.63 415.30 207.65 138.59 69.30 329.63 40.64 415.30 207.65 138.59 69.30 329.63 40.65 415.30 207.65 138.59 69.30 329.63 40.66 415.30 207.65 138.59 69.30 329.63 40.67 415.30 207.65 138.59 69.30 329.63 40.68 415.30 207.65 138.59 69.30 329.63 40.69 415.30 207.65 138.59 69.30 329.63 40.70 415.30 207.65 138.59 69.30 329.63 40.71 415.30 138.59 69.30 329.63 40.72 415.30 138.59 69.30 329.63 40.73 415.30 138.59 69.30 329.63 40.74 415.30 138.59 69.30 329.63 40.75 415.30 138.59 69.30 329.63 40.76 415.30 138.59 69.30 329.63 40.77 415.30 138.59 69.30 329.63 40.78 415.30 138.59 69.30 329.63 40.79 415.30 138.59 69.30 329.63 40.80 415.30 138.59 69.30 329.63 40.81 415.30 138.59 69.30 329.63 40.82 415.30 138.59 69.30 329.63 40.83 415.30 138.59 69.30 329.63 40.84 415.30 138.59 69.30 329.63 40.85 415.30 138.59 69.30 329.63 40.86 415.30 138.59 69.30 329.63 40.87 415.30 138.59 69.30 329.63 40.88 415.30 138.59 69.30 329.63 40.89 415.30 138.59 69.30 329.63 40.90 415.30 138.59 69.30 329.63 40.91 415.30 138.59 69.30 329.63 40.92 415.30 138.59 69.30 329.63 40.93 415.30 138.59 69.30 329.63 40.94 415.30 138.59 69.30 329.63 40.95 415.30 138.59 69.30 329.63 40.96 415.30 138.59 69.30 329.63 40.97 415.30 138.59 69.30 329.63 40.98 415.30 138.59 69.30 329.63 40.99 415.30 138.59 69.30 329.63 41.00 415.30 138.59 69.30 329.63 41.01 415.30 138.59 69.30 329.63 41.02 415.30 138.59 69.30 329.63 41.03 415.30 138.59 69.30 329.63 41.04 415.30 138.59 69.30 329.63 41.05 415.30 138.59 69.30 329.63 41.06 415.30 138.59 69.30 329.63 41.07 415.30 138.59 69.30 329.63 41.08 415.30 138.59 69.30 329.63 207.65 41.09 415.30 138.59 69.30 329.63 207.65 41.10 415.30 138.59 69.30 329.63 207.65 41.11 415.30 138.59 69.30 207.65 41.12 415.30 138.59 69.30 207.65 41.13 415.30 138.59 69.30 207.65 41.14 415.30 138.59 69.30 207.65 41.15 415.30 138.59 69.30 207.65 41.16 415.30 138.59 69.30 207.65 41.17 415.30 138.59 69.30 207.65 41.18 415.30 138.59 69.30 207.65 41.19 415.30 138.59 69.30 207.65 41.20 415.30 138.59 69.30 207.65 41.21 415.30 138.59 69.30 207.65 41.22 415.30 138.59 69.30 207.65 41.23 415.30 138.59 69.30 207.65 41.24 415.30 138.59 69.30 207.65 41.25 415.30 138.59 69.30 207.65 41.26 415.30 138.59 69.30 207.65 41.27 415.30 138.59 69.30 207.65 41.28 415.30 138.59 69.30 207.65 41.29 415.30 138.59 69.30 207.65 41.30 415.30 138.59 69.30 207.65 41.31 415.30 138.59 69.30 207.65 41.32 415.30 138.59 69.30 207.65 41.33 415.30 138.59 69.30 207.65 41.34 415.30 138.59 69.30 207.65 41.35 415.30 138.59 69.30 207.65 41.36 415.30 138.59 69.30 207.65 41.37 415.30 138.59 69.30 207.65 41.38 415.30 138.59 69.30 207.65 41.39 415.30 138.59 69.30 207.65 41.40 415.30 138.59 69.30 207.65 41.41 415.30 138.59 69.30 207.65 41.42 415.30 138.59 69.30 207.65 41.43 415.30 138.59 69.30 207.65 41.44 415.30 138.59 69.30 207.65 41.45 415.30 138.59 69.30 207.65 41.46 415.30 138.59 69.30 207.65 41.47 415.30 138.59 69.30 207.65 41.48 415.30 138.59 69.30 207.65 41.49 415.30 138.59 69.30 207.65 41.50 415.30 138.59 69.30 207.65 41.51 415.30 138.59 69.30 207.65 41.52 415.30 138.59 69.30 207.65 41.53 415.30 138.59 69.30 207.65 41.54 415.30 138.59 69.30 207.65 41.55 415.30 138.59 69.30 207.65 277.18 41.56 415.30 138.59 69.30 207.65 277.18 41.57 415.30 138.59 69.30 207.65 277.18 41.58 415.30 69.30 207.65 277.18 41.59 415.30 69.30 207.65 277.18 41.60 415.30 207.65 277.18 41.61 415.30 207.65 277.18 41.62 415.30 207.65 277.18 41.63 415.30 207.65 277.18 41.64 415.30 207.65 277.18 41.65 415.30 207.65 277.18 41.66 415.30 207.65 277.18 41.67 415.30 207.65 277.18 41.68 415.30 207.65 277.18 41.69 415.30 207.65 277.18 41.70 415.30 207.65 277.18 41.71 415.30 207.65 277.18 41.72 415.30 207.65 277.18 41.73 415.30 207.65 277.18 41.74 415.30 207.65 277.18 41.75 415.30 207.65 277.18 41.76 415.30 207.65 277.18 41.77 415.30 207.65 277.18 41.78 415.30 207.65 277.18 41.79 415.30 207.65 277.18 41.80 415.30 207.65 277.18 41.81 415.30 207.65 277.18 41.82 415.30 207.65 277.18 41.83 415.30 207.65 277.18 41.84 415.30 207.65 277.18 41.85 415.30 207.65 277.18 41.86 415.30 207.65 277.18 41.87 415.30 207.65 277.18 41.88 415.30 207.65 277.18 41.89 415.30 207.65 277.18 41.90 415.30 207.65 277.18 41.91 415.30 207.65 277.18 41.92 415.30 207.65 277.18 41.93 415.30 207.65 277.18 41.94 415.30 207.65 277.18 41.95 415.30 207.65 277.18 41.96 415.30 207.65 277.18 41.97 415.30 207.65 277.18 41.98 415.30 207.65 277.18 41.99 415.30 207.65 277.18 42.00 415.30 207.65 277.18 329.63 42.01 415.30 207.65 277.18 329.63 42.02 415.30 207.65 277.18 329.63 42.03 415.30 207.65 277.18 329.63 42.04 207.65 277.18 329.63 42.05 329.63 42.06 329.63 42.07 329.63 42.08 329.63 42.09 329.63 42.10 329.63 42.11 329.63 42.12 329.63 42.13 329.63 42.14 329.63 42.15 329.63 42.16 329.63 42.17 329.63 42.18 329.63 42.19 329.63 42.20 329.63 42.21 329.63 42.22 329.63 42.23 329.63 42.24 329.63 42.25 329.63 42.26 329.63 42.27 329.63 42.28 329.63 42.29 329.63 42.30 329.63 42.31 329.63 42.32 329.63 42.33 329.63 42.34 329.63 42.35 329.63 42.36 329.63 42.37 329.63 42.38 329.63 42.39 329.63 42.40 329.63 42.41 329.63 42.42 329.63 42.43 329.63 42.44 329.63 42.45 329.63 42.46 329.63 42.47 329.63 42.48 329.63 42.49 329.63 42.50 329.63 46.25 92.50 42.51 329.63 46.25 92.50 42.52 329.63 46.25 92.50 42.53 329.63 46.25 92.50 42.54 329.63 46.25 92.50 42.55 329.63 46.25 92.50 220.00 440.00 42.56 329.63 46.25 92.50 220.00 440.00 42.57 329.63 46.25 92.50 220.00 440.00 42.58 46.25 92.50 220.00 440.00 42.59 46.25 92.50 220.00 440.00 42.60 46.25 92.50 220.00 440.00 42.61 46.25 92.50 220.00 440.00 42.62 46.25 92.50 220.00 440.00 42.63 46.25 92.50 220.00 440.00 42.64 46.25 92.50 220.00 440.00 42.65 46.25 92.50 220.00 440.00 42.66 46.25 92.50 220.00 440.00 42.67 46.25 92.50 220.00 440.00 42.68 46.25 92.50 220.00 440.00 42.69 46.25 92.50 220.00 440.00 42.70 46.25 92.50 220.00 440.00 42.71 46.25 92.50 220.00 440.00 42.72 46.25 92.50 220.00 440.00 42.73 46.25 92.50 220.00 440.00 42.74 46.25 92.50 220.00 440.00 42.75 46.25 92.50 220.00 440.00 42.76 46.25 92.50 220.00 440.00 42.77 46.25 92.50 220.00 440.00 42.78 46.25 92.50 220.00 440.00 42.79 46.25 92.50 220.00 440.00 42.80 46.25 92.50 220.00 440.00 42.81 46.25 92.50 220.00 440.00 42.82 46.25 92.50 220.00 440.00 42.83 46.25 92.50 220.00 440.00 42.84 46.25 92.50 220.00 440.00 42.85 46.25 92.50 220.00 440.00 42.86 46.25 92.50 220.00 440.00 42.87 46.25 92.50 220.00 440.00 42.88 46.25 92.50 220.00 440.00 42.89 46.25 92.50 220.00 440.00 42.90 46.25 92.50 220.00 440.00 42.91 46.25 92.50 220.00 440.00 42.92 46.25 92.50 220.00 440.00 42.93 46.25 92.50 220.00 440.00 42.94 46.25 92.50 220.00 440.00 42.95 46.25 92.50 220.00 440.00 42.96 46.25 92.50 220.00 440.00 42.97 46.25 92.50 220.00 440.00 42.98 46.25 92.50 220.00 440.00 42.99 46.25 92.50 220.00 440.00 43.00 46.25 92.50 220.00 440.00 43.01 46.25 92.50 220.00 440.00 43.02 46.25 92.50 220.00 440.00 43.03 46.25 92.50 220.00 440.00 43.04 46.25 92.50 220.00 440.00 43.05 46.25 92.50 220.00 440.00 43.06 46.25 92.50 220.00 440.00 43.07 46.25 92.50 220.00 440.00 43.08 46.25 92.50 220.00 440.00 43.09 46.25 92.50 220.00 440.00 43.10 46.25 92.50 220.00 440.00 43.11 46.25 92.50 220.00 440.00 43.12 46.25 92.50 220.00 440.00 43.13 46.25 92.50 220.00 440.00 43.14 46.25 92.50 220.00 440.00 277.18 43.15 46.25 92.50 220.00 440.00 277.18 43.16 46.25 92.50 220.00 440.00 277.18 43.17 46.25 92.50 220.00 440.00 277.18 43.18 46.25 92.50 220.00 440.00 277.18 43.19 46.25 92.50 220.00 440.00 277.18 43.20 46.25 92.50 220.00 440.00 277.18 43.21 46.25 92.50 220.00 440.00 277.18 43.22 46.25 92.50 220.00 440.00 277.18 43.23 46.25 92.50 220.00 440.00 277.18 43.24 46.25 92.50 220.00 440.00 277.18 43.25 46.25 92.50 220.00 440.00 277.18 43.26 46.25 92.50 220.00 440.00 277.18 43.27 46.25 92.50 220.00 440.00 277.18 43.28 46.25 92.50 220.00 440.00 277.18 43.29 46.25 92.50 220.00 440.00 277.18 43.30 46.25 92.50 220.00 440.00 277.18 43.31 46.25 92.50 220.00 440.00 277.18 43.32 46.25 92.50 220.00 440.00 277.18 43.33 46.25 92.50 220.00 440.00 277.18 43.34 46.25 92.50 220.00 440.00 277.18 43.35 46.25 92.50 220.00 440.00 277.18 43.36 46.25 92.50 220.00 440.00 277.18 43.37 46.25 92.50 220.00 440.00 277.18 43.38 46.25 92.50 220.00 440.00 277.18 43.39 46.25 92.50 220.00 440.00 277.18 43.40 46.25 92.50 220.00 440.00 277.18 43.41 46.25 92.50 220.00 440.00 277.18 43.42 46.25 92.50 220.00 440.00 277.18 43.43 46.25 92.50 220.00 440.00 277.18 43.44 46.25 92.50 220.00 440.00 277.18 43.45 46.25 92.50 220.00 440.00 277.18 43.46 46.25 92.50 220.00 440.00 277.18 43.47 46.25 92.50 220.00 440.00 277.18 43.48 46.25 92.50 220.00 440.00 277.18 43.49 46.25 92.50 220.00 440.00 277.18 43.50 46.25 92.50 220.00 440.00 277.18 43.51 46.25 92.50 220.00 440.00 277.18 43.52 46.25 92.50 220.00 440.00 277.18 43.53 46.25 92.50 220.00 440.00 277.18 43.54 46.25 92.50 220.00 440.00 277.18 43.55 46.25 92.50 220.00 440.00 277.18 43.56 46.25 92.50 220.00 440.00 277.18 43.57 46.25 92.50 220.00 440.00 277.18 43.58 46.25 92.50 220.00 440.00 277.18 43.59 46.25 92.50 220.00 440.00 277.18 43.60 46.25 92.50 220.00 440.00 277.18 43.61 46.25 92.50 220.00 440.00 277.18 43.62 46.25 92.50 220.00 440.00 277.18 369.99 43.63 46.25 92.50 220.00 440.00 277.18 369.99 43.64 46.25 92.50 220.00 440.00 277.18 369.99 43.65 46.25 92.50 220.00 440.00 277.18 369.99 43.66 46.25 92.50 220.00 440.00 369.99 43.67 46.25 92.50 220.00 440.00 369.99 43.68 46.25 92.50 220.00 440.00 369.99 43.69 46.25 92.50 220.00 440.00 369.99 43.70 46.25 92.50 220.00 440.00 369.99 43.71 46.25 92.50 220.00 440.00 369.99 43.72 46.25 92.50 220.00 440.00 369.99 43.73 46.25 92.50 220.00 440.00 369.99 43.74 46.25 92.50 220.00 440.00 369.99 43.75 46.25 92.50 220.00 440.00 369.99 43.76 46.25 92.50 440.00 369.99 43.77 46.25 92.50 440.00 369.99 43.78 46.25 92.50 440.00 369.99 43.79 46.25 92.50 440.00 369.99 43.80 46.25 92.50 440.00 369.99 43.81 46.25 92.50 440.00 369.99 43.82 46.25 92.50 440.00 369.99 43.83 46.25 92.50 440.00 369.99 43.84 46.25 92.50 440.00 369.99 43.85 46.25 92.50 440.00 369.99 43.86 46.25 92.50 440.00 369.99 43.87 46.25 92.50 440.00 369.99 43.88 46.25 92.50 440.00 369.99 43.89 46.25 92.50 440.00 369.99 43.90 46.25 92.50 440.00 369.99 43.91 46.25 92.50 440.00 369.99 43.92 46.25 92.50 440.00 369.99 43.93 46.25 92.50 440.00 369.99 43.94 46.25 92.50 440.00 369.99 43.95 46.25 92.50 440.00 369.99 43.96 46.25 92.50 440.00 369.99 43.97 46.25 92.50 440.00 369.99 43.98 46.25 92.50 440.00 369.99 43.99 46.25 92.50 440.00 369.99 44.00 46.25 92.50 440.00 369.99 44.01 46.25 92.50 440.00 369.99 44.02 46.25 92.50 440.00 369.99 44.03 46.25 92.50 440.00 369.99 44.04 46.25 92.50 440.00 369.99 44.05 46.25 92.50 440.00 369.99 44.06 46.25 92.50 440.00 369.99 44.07 46.25 92.50 440.00 369.99 44.08 46.25 92.50 440.00 369.99 44.09 46.25 92.50 440.00 369.99 44.10 46.25 92.50 440.00 369.99 44.11 46.25 92.50 440.00 369.99 44.12 46.25 92.50 440.00 369.99 44.13 46.25 92.50 440.00 369.99 44.14 46.25 92.50 440.00 369.99 44.15 46.25 92.50 440.00 369.99 220.00 44.16 46.25 92.50 440.00 369.99 220.00 44.17 46.25 92.50 440.00 369.99 220.00 44.18 46.25 92.50 440.00 369.99 220.00 44.19 46.25 92.50 440.00 369.99 220.00 44.20 46.25 92.50 440.00 220.00 44.21 46.25 92.50 440.00 220.00 44.22 46.25 92.50 440.00 220.00 44.23 46.25 92.50 440.00 220.00 44.24 46.25 92.50 440.00 220.00 44.25 46.25 92.50 440.00 220.00 44.26 46.25 92.50 440.00 220.00 44.27 46.25 92.50 440.00 220.00 44.28 46.25 92.50 440.00 220.00 44.29 46.25 92.50 440.00 220.00 44.30 46.25 92.50 440.00 220.00 44.31 46.25 92.50 440.00 220.00 44.32 46.25 92.50 440.00 220.00 44.33 46.25 92.50 440.00 220.00 44.34 46.25 92.50 440.00 220.00 44.35 46.25 92.50 440.00 220.00 44.36 46.25 92.50 440.00 220.00 44.37 46.25 92.50 440.00 220.00 44.38 46.25 92.50 440.00 220.00 44.39 46.25 92.50 440.00 220.00 44.40 46.25 92.50 440.00 220.00 44.41 46.25 92.50 440.00 220.00 44.42 46.25 92.50 440.00 220.00 44.43 46.25 92.50 440.00 220.00 44.44 46.25 92.50 440.00 220.00 44.45 46.25 92.50 440.00 220.00 44.46 46.25 92.50 440.00 220.00 44.47 46.25 92.50 440.00 220.00 44.48 46.25 92.50 440.00 220.00 44.49 46.25 92.50 440.00 220.00 44.50 46.25 92.50 440.00 220.00 44.51 46.25 92.50 440.00 220.00 44.52 46.25 92.50 440.00 220.00 44.53 46.25 92.50 440.00 220.00 44.54 46.25 92.50 440.00 220.00 44.55 46.25 92.50 440.00 220.00 44.56 46.25 92.50 440.00 220.00 44.57 46.25 92.50 440.00 220.00 44.58 46.25 92.50 440.00 220.00 44.59 46.25 92.50 440.00 220.00 44.60 46.25 92.50 440.00 220.00 277.18 44.61 46.25 92.50 440.00 220.00 277.18 44.62 46.25 92.50 440.00 220.00 277.18 44.63 46.25 92.50 440.00 220.00 277.18 44.64 46.25 92.50 440.00 220.00 277.18 44.65 46.25 92.50 440.00 220.00 277.18 44.66 46.25 92.50 440.00 220.00 277.18 44.67 46.25 92.50 440.00 220.00 277.18 44.68 46.25 92.50 440.00 277.18 44.69 46.25 92.50 440.00 277.18 44.70 46.25 92.50 440.00 277.18 44.71 46.25 440.00 277.18 44.72 46.25 440.00 277.18 44.73 46.25 440.00 277.18 44.74 46.25 440.00 277.18 44.75 440.00 277.18 44.76 440.00 277.18 44.77 440.00 277.18 44.78 440.00 277.18 44.79 440.00 277.18 44.80 440.00 277.18 44.81 440.00 277.18 44.82 440.00 277.18 44.83 440.00 277.18 44.84 440.00 277.18 44.85 440.00 277.18 44.86 440.00 277.18 44.87 440.00 277.18 44.88 440.00 277.18 44.89 440.00 277.18 44.90 440.00 277.18 44.91 440.00 277.18 44.92 440.00 277.18 44.93 440.00 277.18 44.94 440.00 277.18 44.95 440.00 277.18 44.96 440.00 277.18 44.97 440.00 277.18 44.98 440.00 277.18 44.99 440.00 277.18 45.00 440.00 277.18 45.01 440.00 277.18 45.02 440.00 277.18 45.03 440.00 277.18 45.04 440.00 277.18 45.05 440.00 277.18 45.06 440.00 277.18 45.07 440.00 277.18 45.08 440.00 277.18 45.09 440.00 277.18 45.10 277.18 45.11 277.18 369.99 45.12 277.18 369.99 45.13 277.18 369.99 45.14 277.18 369.99 45.15 369.99 45.16 369.99 45.17 369.99 45.18 369.99 45.19 369.99 45.20 369.99 45.21 369.99 45.22 369.99 45.23 369.99 45.24 369.99 45.25 369.99 45.26 369.99 45.27 369.99 45.28 369.99 45.29 369.99 45.30 369.99 45.31 369.99 45.32 369.99 45.33 369.99 45.34 369.99 45.35 369.99 45.36 369.99 45.37 369.99 45.38 369.99 45.39 369.99 45.40 369.99 45.41 369.99 45.42 369.99 45.43 369.99 45.44 369.99 45.45 369.99 45.46 369.99 45.47 369.99 45.48 369.99 45.49 369.99 45.50 369.99 45.51 369.99 45.52 369.99 45.53 369.99 45.54 369.99 45.55 369.99 45.56 369.99 45.57 369.99 45.58 369.99 45.59 369.99 45.60 369.99 45.61 369.99 123.47 61.74 45.62 369.99 123.47 61.74 45.63 369.99 123.47 61.74 45.64 369.99 123.47 61.74 45.65 369.99 123.47 61.74 45.66 369.99 123.47 61.74 45.67 369.99 123.47 61.74 207.65 45.68 369.99 123.47 61.74 207.65 415.30 45.69 369.99 123.47 61.74 207.65 415.30 45.70 369.99 123.47 61.74 207.65 415.30 45.71 369.99 123.47 61.74 207.65 415.30 45.72 123.47 61.74 207.65 415.30 45.73 123.47 61.74 207.65 415.30 45.74 123.47 61.74 207.65 415.30 45.75 123.47 61.74 207.65 415.30 45.76 123.47 61.74 207.65 415.30 45.77 123.47 61.74 207.65 415.30 45.78 123.47 61.74 207.65 415.30 45.79 123.47 61.74 207.65 415.30 45.80 123.47 61.74 207.65 415.30 45.81 123.47 61.74 207.65 415.30 45.82 123.47 61.74 207.65 415.30 45.83 123.47 61.74 207.65 415.30 45.84 123.47 61.74 207.65 415.30 45.85 123.47 61.74 207.65 415.30 45.86 123.47 61.74 207.65 415.30 45.87 123.47 61.74 207.65 415.30 45.88 123.47 61.74 207.65 415.30 45.89 123.47 61.74 207.65 415.30 45.90 123.47 61.74 207.65 415.30 45.91 123.47 61.74 207.65 415.30 45.92 123.47 61.74 207.65 415.30 45.93 123.47 61.74 207.65 415.30 45.94 123.47 61.74 207.65 415.30 45.95 123.47 61.74 207.65 415.30 45.96 123.47 61.74 207.65 415.30 45.97 123.47 61.74 207.65 415.30 45.98 123.47 61.74 207.65 415.30 45.99 123.47 61.74 207.65 415.30 46.00 123.47 61.74 207.65 415.30 46.01 123.47 61.74 207.65 415.30 46.02 123.47 61.74 207.65 415.30 46.03 123.47 61.74 207.65 415.30 46.04 123.47 61.74 207.65 415.30 46.05 123.47 61.74 207.65 415.30 46.06 123.47 61.74 207.65 415.30 46.07 123.47 61.74 207.65 415.30 46.08 123.47 61.74 207.65 415.30 46.09 123.47 61.74 207.65 415.30 46.10 123.47 61.74 207.65 415.30 46.11 123.47 61.74 207.65 415.30 46.12 123.47 61.74 207.65 415.30 46.13 123.47 61.74 207.65 415.30 46.14 123.47 61.74 207.65 415.30 46.15 123.47 61.74 207.65 415.30 46.16 123.47 61.74 207.65 415.30 46.17 123.47 61.74 207.65 415.30 46.18 123.47 61.74 207.65 415.30 46.19 123.47 61.74 207.65 415.30 246.94 46.20 123.47 61.74 207.65 415.30 246.94 46.21 123.47 61.74 207.65 415.30 246.94 46.22 123.47 61.74 207.65 415.30 246.94 46.23 123.47 61.74 207.65 415.30 246.94 46.24 123.47 61.74 207.65 415.30 246.94 46.25 123.47 61.74 207.65 415.30 246.94 46.26 123.47 61.74 207.65 415.30 246.94 46.27 123.47 61.74 207.65 415.30 246.94 46.28 123.47 61.74 207.65 415.30 246.94 46.29 123.47 61.74 207.65 415.30 246.94 46.30 123.47 61.74 207.65 415.30 246.94 46.31 123.47 61.74 207.65 415.30 246.94 46.32 123.47 61.74 207.65 415.30 246.94 46.33 123.47 61.74 207.65 415.30 246.94 46.34 123.47 61.74 207.65 415.30 246.94 46.35 123.47 61.74 207.65 415.30 246.94 46.36 123.47 61.74 207.65 415.30 246.94 46.37 123.47 61.74 207.65 415.30 246.94 46.38 123.47 61.74 207.65 415.30 246.94 46.39 123.47 61.74 207.65 415.30 246.94 46.40 123.47 61.74 207.65 415.30 246.94 46.41 123.47 61.74 207.65 415.30 246.94 46.42 123.47 61.74 207.65 415.30 246.94 46.43 123.47 61.74 207.65 415.30 246.94 46.44 123.47 61.74 207.65 415.30 246.94 46.45 123.47 61.74 207.65 415.30 246.94 46.46 123.47 61.74 207.65 415.30 246.94 46.47 123.47 61.74 207.65 415.30 246.94 46.48 123.47 61.74 207.65 415.30 246.94 46.49 123.47 61.74 207.65 415.30 246.94 46.50 123.47 61.74 207.65 415.30 246.94 46.51 123.47 61.74 207.65 415.30 246.94 46.52 123.47 61.74 207.65 415.30 246.94 46.53 123.47 61.74 207.65 415.30 246.94 46.54 123.47 61.74 207.65 415.30 246.94 46.55 123.47 61.74 207.65 415.30 246.94 46.56 123.47 61.74 207.65 415.30 246.94 46.57 123.47 61.74 207.65 415.30 246.94 46.58 123.47 61.74 207.65 415.30 246.94 46.59 123.47 61.74 207.65 415.30 246.94 46.60 123.47 61.74 207.65 415.30 246.94 46.61 123.47 61.74 207.65 415.30 246.94 46.62 123.47 61.74 207.65 415.30 246.94 46.63 123.47 61.74 207.65 415.30 246.94 46.64 123.47 61.74 207.65 415.30 246.94 46.65 123.47 61.74 207.65 415.30 246.94 46.66 123.47 61.74 207.65 415.30 246.94 46.67 123.47 61.74 207.65 415.30 246.94 46.68 123.47 61.74 207.65 415.30 246.94 329.63 46.69 123.47 61.74 207.65 415.30 246.94 329.63 46.70 123.47 61.74 415.30 329.63 46.71 123.47 61.74 415.30 329.63 46.72 123.47 61.74 415.30 329.63 46.73 123.47 61.74 415.30 329.63 46.74 123.47 61.74 415.30 329.63 46.75 123.47 61.74 415.30 329.63 46.76 123.47 61.74 415.30 329.63 46.77 123.47 61.74 415.30 329.63 46.78 123.47 61.74 415.30 329.63 46.79 123.47 61.74 415.30 329.63 46.80 123.47 61.74 415.30 329.63 46.81 123.47 61.74 415.30 329.63 46.82 123.47 61.74 415.30 329.63 46.83 123.47 61.74 415.30 329.63 46.84 123.47 61.74 415.30 329.63 46.85 123.47 61.74 415.30 329.63 46.86 123.47 61.74 415.30 329.63 46.87 123.47 61.74 415.30 329.63 46.88 123.47 61.74 415.30 329.63 46.89 123.47 61.74 415.30 329.63 46.90 123.47 61.74 415.30 329.63 46.91 123.47 61.74 415.30 329.63 46.92 123.47 61.74 415.30 329.63 46.93 123.47 61.74 415.30 329.63 46.94 123.47 61.74 415.30 329.63 46.95 123.47 61.74 415.30 329.63 46.96 123.47 61.74 415.30 329.63 46.97 123.47 61.74 415.30 329.63 46.98 123.47 61.74 415.30 329.63 46.99 123.47 61.74 415.30 329.63 47.00 123.47 61.74 415.30 329.63 47.01 123.47 61.74 415.30 329.63 47.02 123.47 61.74 415.30 329.63 47.03 123.47 61.74 415.30 329.63 47.04 123.47 61.74 415.30 329.63 47.05 123.47 61.74 415.30 329.63 47.06 123.47 61.74 415.30 329.63 47.07 123.47 61.74 415.30 329.63 47.08 123.47 61.74 415.30 329.63 47.09 123.47 61.74 415.30 329.63 47.10 123.47 61.74 415.30 329.63 47.11 123.47 61.74 415.30 329.63 47.12 123.47 61.74 415.30 329.63 47.13 123.47 61.74 415.30 329.63 47.14 123.47 61.74 415.30 329.63 47.15 123.47 61.74 415.30 329.63 47.16 123.47 61.74 415.30 329.63 207.65 47.17 123.47 61.74 415.30 329.63 207.65 47.18 123.47 61.74 415.30 329.63 207.65 47.19 123.47 61.74 415.30 207.65 47.20 123.47 61.74 415.30 207.65 47.21 123.47 61.74 415.30 207.65 47.22 123.47 61.74 415.30 207.65 47.23 123.47 61.74 415.30 207.65 47.24 123.47 61.74 415.30 207.65 47.25 123.47 61.74 415.30 207.65 47.26 123.47 61.74 415.30 207.65 47.27 123.47 61.74 415.30 207.65 47.28 123.47 61.74 415.30 207.65 47.29 123.47 61.74 415.30 207.65 47.30 123.47 61.74 415.30 207.65 47.31 123.47 61.74 415.30 207.65 47.32 123.47 61.74 415.30 207.65 47.33 123.47 61.74 415.30 207.65 47.34 123.47 61.74 415.30 207.65 47.35 123.47 61.74 415.30 207.65 47.36 123.47 61.74 415.30 207.65 47.37 123.47 61.74 415.30 207.65 47.38 123.47 61.74 415.30 207.65 47.39 123.47 61.74 415.30 207.65 47.40 123.47 61.74 415.30 207.65 47.41 123.47 61.74 415.30 207.65 47.42 123.47 61.74 415.30 207.65 47.43 123.47 61.74 415.30 207.65 47.44 123.47 61.74 415.30 207.65 47.45 123.47 61.74 415.30 207.65 47.46 123.47 61.74 415.30 207.65 47.47 123.47 61.74 415.30 207.65 47.48 123.47 61.74 415.30 207.65 47.49 123.47 61.74 415.30 207.65 47.50 123.47 61.74 415.30 207.65 47.51 123.47 61.74 415.30 207.65 47.52 123.47 61.74 415.30 207.65 47.53 123.47 61.74 415.30 207.65 47.54 123.47 61.74 415.30 207.65 47.55 123.47 61.74 415.30 207.65 47.56 123.47 61.74 415.30 207.65 47.57 123.47 61.74 415.30 207.65 47.58 123.47 61.74 415.30 207.65 246.94 47.59 123.47 61.74 415.30 207.65 246.94 47.60 123.47 61.74 415.30 207.65 246.94 47.61 123.47 61.74 415.30 207.65 246.94 47.62 123.47 61.74 415.30 207.65 246.94 47.63 123.47 61.74 415.30 207.65 246.94 47.64 123.47 61.74 415.30 207.65 246.94 47.65 123.47 61.74 415.30 207.65 246.94 47.66 123.47 61.74 415.30 207.65 246.94 47.67 123.47 61.74 415.30 207.65 246.94 47.68 123.47 61.74 415.30 207.65 246.94 47.69 123.47 61.74 415.30 207.65 246.94 47.70 123.47 61.74 415.30 207.65 246.94 47.71 123.47 61.74 415.30 207.65 246.94 47.72 415.30 207.65 246.94 47.73 415.30 207.65 246.94 47.74 415.30 207.65 246.94 47.75 415.30 207.65 246.94 47.76 415.30 207.65 246.94 47.77 415.30 207.65 246.94 47.78 415.30 207.65 246.94 47.79 415.30 207.65 246.94 47.80 415.30 207.65 246.94 47.81 415.30 207.65 246.94 47.82 415.30 207.65 246.94 47.83 415.30 207.65 246.94 47.84 415.30 207.65 246.94 47.85 415.30 207.65 246.94 47.86 415.30 207.65 246.94 47.87 415.30 207.65 246.94 47.88 415.30 207.65 246.94 47.89 415.30 207.65 246.94 47.90 415.30 207.65 246.94 47.91 415.30 207.65 246.94 47.92 415.30 207.65 246.94 47.93 415.30 207.65 246.94 47.94 415.30 207.65 246.94 47.95 415.30 207.65 246.94 47.96 415.30 207.65 246.94 47.97 415.30 207.65 246.94 47.98 415.30 207.65 246.94 47.99 415.30 207.65 246.94 48.00 415.30 207.65 246.94 48.01 415.30 207.65 246.94 48.02 415.30 207.65 246.94 48.03 415.30 207.65 246.94 48.04 415.30 207.65 246.94 48.05 415.30 207.65 246.94 48.06 415.30 207.65 246.94 48.07 415.30 207.65 246.94 48.08 415.30 207.65 246.94 48.09 415.30 207.65 246.94 48.10 415.30 207.65 246.94 48.11 415.30 207.65 246.94 329.63 48.12 415.30 207.65 246.94 329.63 48.13 415.30 207.65 246.94 329.63 48.14 207.65 329.63 48.15 329.63 48.16 329.63 48.17 329.63 48.18 329.63 48.19 329.63 48.20 329.63 48.21 329.63 48.22 329.63 48.23 329.63 48.24 329.63 48.25 329.63 48.26 329.63 48.27 329.63 48.28 329.63 48.29 329.63 48.30 329.63 48.31 329.63 48.32 329.63 48.33 329.63 48.34 329.63 48.35 329.63 48.36 329.63 48.37 329.63 48.38 329.63 48.39 329.63 48.40 329.63 48.41 329.63 48.42 329.63 48.43 329.63 48.44 329.63 48.45 329.63 48.46 329.63 48.47 329.63 48.48 329.63 48.49 329.63 48.50 329.63 48.51 329.63 48.52 329.63 48.53 329.63 48.54 329.63 48.55 329.63 48.56 329.63 48.57 329.63 48.58 329.63 48.59 329.63 48.60 329.63 48.61 329.63 48.62 329.63 123.47 61.74 48.63 329.63 123.47 61.74 48.64 329.63 123.47 61.74 48.65 329.63 123.47 61.74 48.66 329.63 123.47 61.74 48.67 329.63 123.47 61.74 220.00 48.68 329.63 123.47 61.74 220.00 369.99 48.69 329.63 123.47 61.74 220.00 369.99 48.70 329.63 123.47 61.74 220.00 369.99 48.71 123.47 61.74 220.00 369.99 48.72 123.47 61.74 220.00 369.99 48.73 123.47 61.74 220.00 369.99 48.74 123.47 61.74 220.00 369.99 48.75 123.47 61.74 220.00 369.99 48.76 123.47 61.74 220.00 369.99 48.77 123.47 61.74 220.00 369.99 48.78 123.47 61.74 220.00 369.99 48.79 123.47 61.74 220.00 369.99 48.80 123.47 61.74 220.00 369.99 48.81 123.47 61.74 220.00 369.99 48.82 123.47 61.74 220.00 369.99 48.83 123.47 61.74 220.00 369.99 48.84 123.47 61.74 220.00 369.99 48.85 123.47 61.74 220.00 369.99 48.86 123.47 61.74 220.00 369.99 48.87 123.47 61.74 220.00 369.99 48.88 123.47 61.74 220.00 369.99 48.89 123.47 61.74 220.00 369.99 48.90 123.47 61.74 220.00 369.99 48.91 123.47 61.74 220.00 369.99 48.92 123.47 61.74 220.00 369.99 48.93 123.47 61.74 220.00 369.99 48.94 123.47 61.74 220.00 369.99 48.95 123.47 61.74 220.00 369.99 48.96 123.47 61.74 220.00 369.99 48.97 123.47 61.74 220.00 369.99 48.98 123.47 61.74 220.00 369.99 48.99 123.47 61.74 220.00 369.99 49.00 123.47 61.74 220.00 369.99 49.01 123.47 61.74 220.00 369.99 49.02 123.47 61.74 220.00 369.99 49.03 123.47 61.74 220.00 369.99 49.04 123.47 61.74 220.00 369.99 49.05 123.47 61.74 220.00 369.99 49.06 123.47 61.74 220.00 369.99 49.07 123.47 61.74 220.00 369.99 49.08 123.47 61.74 220.00 369.99 49.09 123.47 61.74 220.00 369.99 49.10 123.47 61.74 220.00 369.99 49.11 123.47 61.74 220.00 369.99 49.12 123.47 61.74 220.00 369.99 49.13 123.47 61.74 220.00 369.99 49.14 123.47 61.74 220.00 369.99 49.15 123.47 61.74 220.00 369.99 49.16 123.47 61.74 220.00 369.99 49.17 123.47 61.74 220.00 369.99 246.94 49.18 123.47 61.74 220.00 369.99 246.94 49.19 123.47 61.74 220.00 369.99 246.94 49.20 123.47 61.74 220.00 369.99 246.94 49.21 123.47 61.74 220.00 369.99 246.94 49.22 123.47 61.74 220.00 369.99 246.94 49.23 123.47 61.74 220.00 369.99 246.94 49.24 123.47 61.74 220.00 369.99 246.94 49.25 123.47 61.74 220.00 369.99 246.94 49.26 123.47 61.74 220.00 369.99 246.94 49.27 123.47 61.74 220.00 369.99 246.94 49.28 123.47 61.74 220.00 369.99 246.94 49.29 123.47 61.74 220.00 369.99 246.94 49.30 123.47 61.74 220.00 369.99 246.94 49.31 123.47 61.74 220.00 369.99 246.94 49.32 123.47 61.74 220.00 369.99 246.94 49.33 123.47 61.74 220.00 369.99 246.94 49.34 123.47 61.74 220.00 369.99 246.94 49.35 123.47 61.74 220.00 369.99 246.94 49.36 123.47 61.74 220.00 369.99 246.94 49.37 123.47 61.74 220.00 369.99 246.94 49.38 123.47 61.74 220.00 369.99 246.94 49.39 123.47 61.74 220.00 369.99 246.94 49.40 123.47 61.74 220.00 369.99 246.94 49.41 123.47 61.74 220.00 369.99 246.94 49.42 123.47 61.74 220.00 369.99 246.94 49.43 123.47 61.74 220.00 369.99 246.94 49.44 123.47 61.74 220.00 369.99 246.94 49.45 123.47 61.74 220.00 369.99 246.94 49.46 123.47 61.74 220.00 369.99 246.94 49.47 123.47 61.74 220.00 369.99 246.94 49.48 123.47 61.74 220.00 369.99 246.94 49.49 123.47 61.74 220.00 369.99 246.94 49.50 123.47 61.74 220.00 369.99 246.94 49.51 123.47 61.74 220.00 369.99 246.94 49.52 123.47 61.74 220.00 369.99 246.94 49.53 123.47 61.74 220.00 369.99 246.94 49.54 123.47 61.74 220.00 369.99 246.94 49.55 123.47 61.74 220.00 369.99 246.94 49.56 123.47 61.74 220.00 369.99 246.94 49.57 123.47 61.74 220.00 369.99 246.94 49.58 123.47 61.74 220.00 369.99 246.94 49.59 123.47 61.74 220.00 369.99 246.94 49.60 123.47 61.74 220.00 369.99 246.94 49.61 123.47 61.74 369.99 246.94 49.62 123.47 61.74 369.99 246.94 49.63 123.47 61.74 369.99 246.94 49.64 123.47 61.74 369.99 246.94 49.65 123.47 61.74 369.99 246.94 49.66 123.47 61.74 369.99 246.94 311.13 49.67 123.47 61.74 369.99 246.94 311.13 49.68 123.47 61.74 369.99 311.13 49.69 123.47 61.74 311.13 49.70 123.47 61.74 311.13 49.71 123.47 61.74 311.13 49.72 123.47 61.74 311.13 49.73 123.47 61.74 311.13 49.74 123.47 61.74 311.13 49.75 123.47 61.74 311.13 49.76 123.47 61.74 311.13 49.77 123.47 61.74 311.13 49.78 123.47 61.74 311.13 49.79 123.47 61.74 311.13 49.80 123.47 61.74 311.13 49.81 123.47 61.74 311.13 49.82 123.47 61.74 311.13 49.83 123.47 61.74 311.13 49.84 123.47 61.74 311.13 49.85 123.47 61.74 311.13 49.86 123.47 61.74 311.13 49.87 123.47 61.74 311.13 49.88 123.47 61.74 311.13 49.89 123.47 61.74 311.13 49.90 123.47 61.74 311.13 49.91 123.47 61.74 311.13 49.92 123.47 61.74 311.13 49.93 123.47 61.74 311.13 49.94 123.47 61.74 311.13 49.95 123.47 61.74 311.13 49.96 123.47 61.74 311.13 49.97 123.47 61.74 311.13 49.98 123.47 61.74 311.13 49.99 123.47 61.74 311.13 50.00 123.47 61.74 311.13 50.01 123.47 61.74 311.13 50.02 123.47 61.74 311.13 50.03 123.47 61.74 311.13 50.04 123.47 61.74 311.13 50.05 123.47 61.74 311.13 50.06 123.47 61.74 311.13 50.07 123.47 61.74 311.13 50.08 123.47 61.74 311.13 50.09 123.47 61.74 50.10 123.47 61.74 50.11 123.47 61.74 50.12 123.47 61.74 50.13 123.47 61.74 50.14 123.47 61.74 493.88 50.15 123.47 61.74 493.88 220.00 50.16 123.47 61.74 493.88 220.00 50.17 123.47 61.74 493.88 220.00 50.18 123.47 61.74 493.88 220.00 50.19 123.47 61.74 493.88 220.00 50.20 123.47 61.74 493.88 220.00 50.21 123.47 61.74 493.88 220.00 50.22 123.47 61.74 493.88 220.00 50.23 123.47 61.74 493.88 220.00 50.24 123.47 61.74 493.88 220.00 50.25 123.47 61.74 493.88 220.00 50.26 123.47 61.74 493.88 220.00 50.27 123.47 61.74 493.88 220.00 50.28 123.47 61.74 493.88 220.00 50.29 123.47 61.74 493.88 220.00 50.30 123.47 61.74 493.88 220.00 50.31 123.47 61.74 493.88 220.00 50.32 123.47 61.74 493.88 220.00 50.33 123.47 61.74 493.88 220.00 50.34 123.47 61.74 493.88 220.00 50.35 123.47 61.74 493.88 220.00 50.36 123.47 61.74 493.88 220.00 50.37 123.47 61.74 493.88 220.00 50.38 123.47 61.74 493.88 220.00 50.39 123.47 61.74 493.88 220.00 50.40 123.47 61.74 493.88 220.00 50.41 123.47 61.74 493.88 220.00 50.42 123.47 61.74 493.88 220.00 50.43 123.47 61.74 493.88 220.00 50.44 123.47 61.74 493.88 220.00 50.45 123.47 61.74 493.88 220.00 50.46 123.47 61.74 493.88 220.00 50.47 123.47 61.74 493.88 220.00 50.48 123.47 61.74 493.88 220.00 50.49 123.47 61.74 493.88 220.00 50.50 123.47 61.74 493.88 220.00 50.51 123.47 61.74 493.88 220.00 50.52 123.47 61.74 493.88 220.00 50.53 123.47 61.74 493.88 220.00 50.54 123.47 61.74 493.88 220.00 50.55 123.47 61.74 493.88 220.00 50.56 123.47 61.74 493.88 220.00 50.57 123.47 61.74 493.88 220.00 50.58 123.47 61.74 493.88 220.00 50.59 123.47 61.74 493.88 220.00 50.60 123.47 61.74 493.88 220.00 50.61 123.47 61.74 493.88 220.00 50.62 123.47 61.74 493.88 220.00 50.63 123.47 61.74 493.88 220.00 50.64 123.47 61.74 493.88 220.00 50.65 123.47 493.88 220.00 50.66 493.88 220.00 50.67 493.88 220.00 50.68 493.88 220.00 246.94 50.69 493.88 220.00 246.94 50.70 493.88 220.00 246.94 50.71 493.88 246.94 50.72 493.88 246.94 50.73 493.88 246.94 50.74 493.88 246.94 50.75 493.88 246.94 50.76 493.88 246.94 50.77 493.88 246.94 50.78 493.88 246.94 50.79 493.88 246.94 50.80 493.88 246.94 50.81 493.88 246.94 50.82 246.94 50.83 246.94 50.84 246.94 50.85 246.94 50.86 246.94 50.87 246.94 50.88 246.94 50.89 246.94 50.90 246.94 50.91 246.94 50.92 246.94 50.93 246.94 50.94 246.94 50.95 246.94 50.96 246.94 50.97 246.94 50.98 246.94 50.99 246.94 51.00 246.94 51.01 246.94 51.02 246.94 51.03 246.94 51.04 246.94 51.05 246.94 51.06 246.94 51.07 246.94 51.08 246.94 51.09 246.94 51.10 246.94 51.11 246.94 51.12 246.94 51.13 246.94 51.14 246.94 51.15 246.94 51.16 246.94 51.17 246.94 51.18 246.94 51.19 246.94 311.13 51.20 246.94 311.13 51.21 246.94 311.13 51.22 246.94 311.13 51.23 246.94 311.13 51.24 311.13 51.25 311.13 51.26 311.13 51.27 311.13 51.28 311.13 51.29 311.13 51.30 311.13 51.31 311.13 51.32 311.13 51.33 311.13 51.34 311.13 51.35 311.13 51.36 311.13 51.37 311.13 51.38 311.13 51.39 311.13 51.40 311.13 51.41 311.13 51.42 311.13 51.43 311.13 51.44 311.13 51.45 311.13 51.46 311.13 51.47 311.13 51.48 311.13 51.49 311.13 51.50 311.13 51.51 311.13 51.52 311.13 51.53 311.13 51.54 311.13 51.55 311.13 51.56 311.13 51.57 311.13 51.58 311.13 51.59 311.13 51.60 311.13 51.61 311.13 51.62 311.13 51.63 311.13 51.64 311.13 51.65 311.13 51.66 311.13 51.67 311.13 51.68 311.13 51.69 311.13 51.70 311.13 51.71 311.13 51.72 311.13 51.73 311.13 51.74 311.13 51.75 311.13 82.41 51.76 311.13 82.41 51.77 311.13 82.41 164.81 51.78 311.13 82.41 164.81 51.79 311.13 82.41 164.81 207.65 329.63 51.80 311.13 82.41 164.81 207.65 329.63 51.81 311.13 82.41 164.81 207.65 329.63 51.82 311.13 82.41 164.81 207.65 329.63 51.83 311.13 82.41 164.81 207.65 329.63 51.84 311.13 82.41 164.81 207.65 329.63 51.85 311.13 82.41 164.81 207.65 329.63 51.86 311.13 82.41 164.81 207.65 329.63 51.87 311.13 82.41 164.81 207.65 329.63 51.88 82.41 164.81 207.65 329.63 51.89 82.41 164.81 207.65 329.63 51.90 82.41 164.81 207.65 329.63 51.91 82.41 164.81 207.65 329.63 51.92 82.41 164.81 207.65 329.63 51.93 82.41 164.81 207.65 329.63 51.94 82.41 164.81 207.65 329.63 51.95 82.41 164.81 207.65 329.63 51.96 82.41 164.81 207.65 329.63 51.97 82.41 164.81 207.65 329.63 51.98 82.41 164.81 207.65 329.63 51.99 82.41 164.81 207.65 329.63 52.00 82.41 164.81 207.65 329.63 52.01 82.41 164.81 207.65 329.63 52.02 82.41 164.81 207.65 329.63 52.03 82.41 164.81 207.65 329.63 52.04 82.41 164.81 207.65 329.63 52.05 82.41 164.81 207.65 329.63 52.06 82.41 164.81 207.65 329.63 52.07 82.41 164.81 207.65 329.63 52.08 82.41 164.81 207.65 329.63 52.09 82.41 164.81 207.65 329.63 52.10 82.41 164.81 207.65 329.63 52.11 82.41 164.81 207.65 329.63 52.12 82.41 164.81 207.65 329.63 52.13 82.41 164.81 207.65 329.63 52.14 82.41 164.81 207.65 329.63 52.15 82.41 164.81 207.65 329.63 52.16 82.41 164.81 207.65 329.63 52.17 82.41 164.81 207.65 329.63 52.18 82.41 164.81 207.65 329.63 52.19 82.41 164.81 207.65 329.63 52.20 82.41 164.81 207.65 329.63 52.21 82.41 164.81 207.65 329.63 52.22 82.41 164.81 207.65 329.63 52.23 82.41 164.81 207.65 329.63 52.24 82.41 164.81 207.65 329.63 52.25 82.41 164.81 207.65 329.63 52.26 82.41 164.81 207.65 329.63 52.27 82.41 164.81 207.65 329.63 52.28 82.41 164.81 207.65 329.63 52.29 82.41 164.81 207.65 329.63 52.30 82.41 164.81 207.65 329.63 52.31 82.41 164.81 207.65 329.63 52.32 82.41 164.81 207.65 329.63 52.33 82.41 164.81 207.65 329.63 52.34 82.41 164.81 207.65 329.63 52.35 82.41 164.81 207.65 329.63 52.36 82.41 164.81 207.65 329.63 52.37 82.41 164.81 207.65 329.63 52.38 82.41 164.81 207.65 329.63 52.39 82.41 164.81 207.65 329.63 52.40 82.41 164.81 207.65 329.63 52.41 82.41 164.81 207.65 329.63 52.42 82.41 164.81 207.65 329.63 52.43 82.41 164.81 207.65 329.63 52.44 82.41 164.81 207.65 329.63 52.45 82.41 164.81 207.65 329.63 52.46 82.41 164.81 207.65 329.63 52.47 82.41 164.81 207.65 329.63 52.48 82.41 164.81 207.65 329.63 52.49 82.41 164.81 207.65 329.63 52.50 82.41 164.81 207.65 329.63 52.51 82.41 164.81 207.65 329.63 52.52 82.41 164.81 207.65 329.63 246.94 52.53 82.41 164.81 207.65 246.94 52.54 82.41 164.81 207.65 246.94 52.55 82.41 164.81 207.65 246.94 52.56 82.41 164.81 207.65 246.94 52.57 82.41 164.81 207.65 246.94 52.58 82.41 164.81 207.65 246.94 52.59 82.41 164.81 207.65 246.94 52.60 82.41 164.81 207.65 246.94 52.61 82.41 164.81 207.65 246.94 52.62 82.41 164.81 207.65 246.94 52.63 82.41 164.81 207.65 246.94 52.64 82.41 164.81 207.65 246.94 52.65 82.41 164.81 207.65 246.94 52.66 82.41 164.81 207.65 246.94 52.67 82.41 164.81 207.65 246.94 52.68 82.41 164.81 207.65 246.94 52.69 82.41 164.81 207.65 246.94 52.70 82.41 164.81 207.65 246.94 52.71 82.41 164.81 207.65 246.94 52.72 82.41 164.81 207.65 246.94 52.73 82.41 164.81 207.65 246.94 52.74 82.41 164.81 207.65 246.94 52.75 82.41 164.81 207.65 246.94 52.76 82.41 164.81 207.65 246.94 52.77 82.41 164.81 207.65 246.94 52.78 82.41 164.81 207.65 246.94 52.79 82.41 164.81 207.65 246.94 52.80 82.41 164.81 207.65 246.94 52.81 82.41 164.81 207.65 246.94 52.82 82.41 164.81 207.65 246.94 52.83 82.41 164.81 207.65 246.94 52.84 82.41 164.81 207.65 246.94 52.85 82.41 164.81 207.65 246.94 52.86 82.41 164.81 207.65 246.94 52.87 82.41 164.81 207.65 246.94 52.88 82.41 164.81 207.65 246.94 52.89 82.41 164.81 207.65 246.94 52.90 82.41 164.81 207.65 246.94 52.91 82.41 164.81 207.65 246.94 52.92 82.41 164.81 207.65 246.94 52.93 82.41 164.81 207.65 246.94 52.94 82.41 164.81 207.65 246.94 52.95 82.41 164.81 207.65 246.94 52.96 82.41 164.81 207.65 246.94 52.97 82.41 164.81 207.65 246.94 52.98 82.41 164.81 207.65 246.94 52.99 82.41 164.81 207.65 246.94 53.00 82.41 164.81 207.65 246.94 329.63 53.01 82.41 164.81 207.65 246.94 329.63 53.02 82.41 164.81 207.65 246.94 329.63 53.03 82.41 164.81 207.65 246.94 329.63 53.04 82.41 164.81 207.65 246.94 329.63 53.05 82.41 164.81 207.65 329.63 53.06 82.41 164.81 207.65 329.63 53.07 82.41 164.81 207.65 329.63 53.08 82.41 164.81 207.65 329.63 53.09 82.41 164.81 207.65 329.63 53.10 82.41 164.81 207.65 329.63 53.11 82.41 164.81 207.65 329.63 53.12 82.41 164.81 207.65 329.63 53.13 82.41 164.81 207.65 329.63 53.14 82.41 164.81 207.65 329.63 53.15 82.41 164.81 207.65 329.63 53.16 82.41 164.81 207.65 329.63 53.17 82.41 164.81 207.65 329.63 53.18 82.41 164.81 207.65 329.63 53.19 82.41 164.81 207.65 329.63 53.20 82.41 164.81 207.65 329.63 53.21 82.41 164.81 329.63 53.22 82.41 164.81 329.63 53.23 82.41 164.81 329.63 53.24 82.41 164.81 329.63 53.25 82.41 164.81 329.63 53.26 82.41 164.81 329.63 53.27 82.41 164.81 329.63 53.28 82.41 164.81 329.63 53.29 82.41 164.81 329.63 53.30 82.41 164.81 329.63 53.31 82.41 164.81 329.63 53.32 82.41 164.81 329.63 53.33 82.41 164.81 329.63 53.34 82.41 164.81 329.63 53.35 82.41 164.81 329.63 53.36 82.41 164.81 329.63 53.37 82.41 164.81 329.63 53.38 82.41 164.81 329.63 53.39 82.41 164.81 329.63 53.40 82.41 164.81 329.63 53.41 82.41 164.81 329.63 53.42 82.41 164.81 329.63 53.43 82.41 164.81 329.63 53.44 82.41 164.81 329.63 53.45 82.41 164.81 329.63 53.46 82.41 164.81 329.63 53.47 82.41 164.81 329.63 53.48 82.41 164.81 329.63 53.49 82.41 164.81 329.63 53.50 329.63 53.51 329.63 53.52 329.63mir_eval-0.8.2/tests/data/multipitch/ref03.txt000066400000000000000000005320271475740344600212630ustar00rootroot000000000000000.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 415.30 0.13 415.30 0.14 415.30 0.15 415.30 0.16 415.30 0.17 415.30 0.18 415.30 0.19 415.30 0.20 415.30 0.21 415.30 0.22 415.30 493.88 0.23 415.30 493.88 0.24 415.30 493.88 0.25 415.30 493.88 0.26 415.30 493.88 0.27 415.30 493.88 0.28 415.30 493.88 0.29 415.30 493.88 0.30 415.30 493.88 0.31 415.30 493.88 0.32 415.30 493.88 0.33 415.30 493.88 0.34 415.30 493.88 0.35 415.30 493.88 0.36 415.30 493.88 0.37 415.30 493.88 0.38 415.30 493.88 0.39 415.30 493.88 0.40 415.30 493.88 0.41 415.30 493.88 0.42 415.30 493.88 0.43 415.30 493.88 0.44 415.30 493.88 0.45 415.30 493.88 0.46 415.30 493.88 0.47 415.30 493.88 0.48 415.30 493.88 0.49 415.30 493.88 0.50 415.30 493.88 415.30 0.51 415.30 493.88 415.30 0.52 415.30 493.88 415.30 0.53 415.30 493.88 415.30 0.54 415.30 493.88 415.30 0.55 415.30 493.88 415.30 0.56 415.30 493.88 415.30 0.57 415.30 493.88 415.30 0.58 415.30 493.88 415.30 0.59 415.30 493.88 415.30 0.60 415.30 493.88 415.30 0.61 415.30 493.88 415.30 0.62 415.30 493.88 415.30 0.63 415.30 493.88 415.30 0.64 415.30 493.88 415.30 0.65 415.30 493.88 415.30 0.66 415.30 493.88 415.30 0.67 415.30 493.88 415.30 0.68 415.30 493.88 415.30 0.69 415.30 493.88 415.30 0.70 415.30 493.88 415.30 0.71 415.30 493.88 415.30 0.72 415.30 493.88 415.30 0.73 415.30 493.88 415.30 0.74 415.30 493.88 415.30 0.75 415.30 493.88 415.30 0.76 415.30 493.88 415.30 0.77 415.30 493.88 415.30 0.78 415.30 493.88 415.30 0.79 415.30 493.88 415.30 0.80 415.30 493.88 415.30 0.81 415.30 493.88 415.30 0.82 415.30 493.88 415.30 0.83 415.30 493.88 415.30 0.84 415.30 493.88 415.30 0.85 415.30 493.88 415.30 0.86 415.30 493.88 415.30 0.87 415.30 493.88 415.30 0.88 415.30 493.88 415.30 0.89 415.30 493.88 415.30 0.90 415.30 493.88 415.30 0.91 415.30 493.88 415.30 0.92 415.30 493.88 415.30 0.93 415.30 493.88 415.30 0.94 415.30 493.88 415.30 0.95 415.30 493.88 415.30 0.96 415.30 493.88 415.30 0.97 415.30 493.88 415.30 0.98 415.30 493.88 415.30 0.99 415.30 493.88 415.30 1.00 415.30 493.88 415.30 1.01 415.30 493.88 415.30 1.02 415.30 493.88 415.30 1.03 415.30 493.88 415.30 1.04 415.30 493.88 415.30 1.05 415.30 493.88 415.30 329.63 1.06 415.30 493.88 415.30 329.63 1.07 415.30 493.88 415.30 329.63 1.08 493.88 415.30 329.63 1.09 493.88 415.30 329.63 1.10 493.88 415.30 329.63 415.30 1.11 493.88 415.30 329.63 415.30 1.12 493.88 415.30 329.63 415.30 1.13 493.88 415.30 329.63 415.30 1.14 493.88 415.30 329.63 415.30 329.63 1.15 493.88 415.30 329.63 415.30 329.63 1.16 493.88 415.30 329.63 415.30 329.63 1.17 493.88 415.30 329.63 415.30 329.63 1.18 493.88 415.30 329.63 415.30 329.63 1.19 493.88 415.30 329.63 415.30 329.63 1.20 493.88 415.30 329.63 415.30 329.63 554.37 1.21 493.88 329.63 415.30 329.63 554.37 1.22 493.88 329.63 415.30 329.63 554.37 1.23 493.88 329.63 415.30 329.63 554.37 1.24 493.88 329.63 415.30 329.63 554.37 1.25 493.88 329.63 415.30 329.63 554.37 1.26 493.88 329.63 415.30 329.63 554.37 1.27 493.88 329.63 415.30 329.63 554.37 1.28 329.63 415.30 329.63 554.37 1.29 329.63 415.30 329.63 554.37 1.30 329.63 415.30 329.63 554.37 1.31 329.63 415.30 329.63 554.37 1.32 329.63 415.30 329.63 554.37 1.33 329.63 415.30 329.63 554.37 1.34 329.63 415.30 329.63 554.37 1.35 329.63 415.30 329.63 554.37 1.36 329.63 415.30 329.63 554.37 1.37 329.63 415.30 329.63 554.37 1.38 329.63 415.30 329.63 554.37 1.39 329.63 415.30 329.63 554.37 1.40 329.63 415.30 329.63 554.37 1.41 329.63 415.30 329.63 554.37 1.42 329.63 415.30 329.63 554.37 1.43 329.63 415.30 329.63 554.37 1.44 329.63 415.30 329.63 554.37 1.45 329.63 415.30 329.63 554.37 1.46 329.63 415.30 329.63 554.37 1.47 329.63 415.30 329.63 554.37 1.48 329.63 415.30 329.63 554.37 1.49 329.63 415.30 329.63 554.37 415.30 1.50 329.63 415.30 329.63 554.37 415.30 1.51 329.63 415.30 329.63 554.37 415.30 1.52 329.63 415.30 329.63 554.37 415.30 1.53 329.63 415.30 329.63 554.37 415.30 1.54 415.30 329.63 554.37 415.30 1.55 415.30 329.63 554.37 415.30 1.56 415.30 329.63 554.37 415.30 1.57 415.30 329.63 554.37 415.30 1.58 415.30 329.63 554.37 415.30 1.59 415.30 329.63 554.37 415.30 1.60 415.30 329.63 554.37 415.30 1.61 415.30 329.63 554.37 415.30 1.62 415.30 329.63 554.37 415.30 1.63 415.30 329.63 554.37 415.30 1.64 415.30 329.63 554.37 415.30 1.65 415.30 329.63 554.37 415.30 1.66 415.30 329.63 554.37 415.30 1.67 415.30 329.63 554.37 415.30 1.68 415.30 329.63 554.37 415.30 1.69 415.30 329.63 554.37 415.30 1.70 415.30 329.63 554.37 415.30 1.71 415.30 329.63 554.37 415.30 1.72 415.30 329.63 554.37 415.30 1.73 415.30 329.63 554.37 415.30 1.74 415.30 329.63 554.37 415.30 1.75 415.30 329.63 554.37 415.30 1.76 415.30 329.63 554.37 415.30 1.77 415.30 329.63 554.37 415.30 1.78 415.30 329.63 554.37 415.30 1.79 415.30 329.63 554.37 415.30 1.80 415.30 329.63 554.37 415.30 1.81 415.30 329.63 554.37 415.30 1.82 415.30 329.63 554.37 415.30 1.83 415.30 329.63 554.37 415.30 1.84 415.30 329.63 554.37 415.30 1.85 415.30 329.63 554.37 415.30 1.86 415.30 329.63 554.37 415.30 1.87 415.30 329.63 554.37 415.30 1.88 415.30 329.63 554.37 415.30 1.89 415.30 329.63 554.37 415.30 1.90 415.30 329.63 554.37 415.30 1.91 415.30 329.63 554.37 415.30 1.92 415.30 329.63 554.37 415.30 1.93 415.30 329.63 554.37 415.30 1.94 415.30 329.63 554.37 415.30 1.95 415.30 329.63 554.37 415.30 1.96 415.30 329.63 554.37 415.30 1.97 415.30 329.63 554.37 415.30 1.98 415.30 329.63 554.37 415.30 1.99 415.30 329.63 554.37 415.30 2.00 415.30 329.63 554.37 415.30 2.01 415.30 329.63 554.37 415.30 2.02 415.30 329.63 554.37 415.30 246.94 2.03 415.30 329.63 554.37 415.30 246.94 2.04 415.30 329.63 554.37 415.30 246.94 2.05 415.30 554.37 415.30 246.94 2.06 415.30 554.37 415.30 246.94 415.30 311.13 2.07 415.30 554.37 415.30 246.94 415.30 311.13 2.08 415.30 554.37 415.30 246.94 415.30 311.13 2.09 415.30 554.37 415.30 246.94 415.30 311.13 2.10 415.30 554.37 415.30 246.94 415.30 311.13 2.11 415.30 554.37 415.30 246.94 415.30 311.13 2.12 415.30 554.37 415.30 246.94 415.30 311.13 2.13 415.30 554.37 415.30 246.94 415.30 311.13 2.14 554.37 415.30 246.94 415.30 311.13 2.15 415.30 246.94 415.30 311.13 2.16 415.30 246.94 415.30 311.13 2.17 415.30 246.94 415.30 311.13 2.18 415.30 246.94 415.30 311.13 2.19 415.30 246.94 415.30 311.13 2.20 415.30 246.94 415.30 311.13 2.21 415.30 246.94 415.30 311.13 2.22 415.30 246.94 415.30 311.13 2.23 415.30 246.94 415.30 311.13 2.24 415.30 246.94 415.30 311.13 2.25 415.30 246.94 415.30 311.13 2.26 415.30 246.94 415.30 311.13 2.27 415.30 246.94 415.30 311.13 2.28 415.30 246.94 415.30 311.13 2.29 415.30 246.94 415.30 311.13 2.30 415.30 246.94 415.30 311.13 2.31 415.30 246.94 415.30 311.13 2.32 415.30 246.94 415.30 311.13 2.33 415.30 246.94 415.30 311.13 2.34 415.30 246.94 415.30 311.13 2.35 415.30 246.94 415.30 311.13 2.36 415.30 246.94 415.30 311.13 2.37 415.30 246.94 415.30 311.13 2.38 415.30 246.94 415.30 311.13 2.39 415.30 246.94 415.30 311.13 2.40 415.30 246.94 415.30 311.13 2.41 415.30 246.94 415.30 311.13 2.42 415.30 246.94 415.30 311.13 2.43 415.30 246.94 415.30 311.13 2.44 415.30 246.94 415.30 311.13 2.45 415.30 246.94 415.30 311.13 2.46 415.30 246.94 415.30 311.13 2.47 415.30 246.94 415.30 311.13 2.48 415.30 246.94 415.30 311.13 2.49 415.30 246.94 415.30 311.13 2.50 415.30 246.94 415.30 311.13 2.51 415.30 246.94 415.30 311.13 2.52 415.30 246.94 415.30 311.13 311.13 2.53 415.30 246.94 415.30 311.13 311.13 2.54 415.30 246.94 415.30 311.13 311.13 2.55 415.30 246.94 415.30 311.13 311.13 2.56 415.30 246.94 415.30 311.13 311.13 2.57 415.30 246.94 415.30 311.13 311.13 2.58 415.30 246.94 415.30 311.13 311.13 2.59 246.94 415.30 311.13 311.13 2.60 246.94 415.30 311.13 311.13 2.61 246.94 415.30 311.13 311.13 2.62 246.94 415.30 311.13 311.13 2.63 246.94 415.30 311.13 311.13 2.64 246.94 415.30 311.13 311.13 2.65 246.94 415.30 311.13 311.13 2.66 246.94 415.30 311.13 311.13 2.67 246.94 415.30 311.13 311.13 2.68 246.94 415.30 311.13 311.13 2.69 246.94 415.30 311.13 311.13 2.70 246.94 415.30 311.13 311.13 2.71 246.94 415.30 311.13 311.13 2.72 246.94 415.30 311.13 311.13 2.73 246.94 415.30 311.13 311.13 2.74 246.94 415.30 311.13 311.13 2.75 246.94 415.30 311.13 311.13 2.76 246.94 415.30 311.13 311.13 2.77 246.94 415.30 311.13 311.13 2.78 246.94 415.30 311.13 311.13 2.79 246.94 415.30 311.13 311.13 2.80 246.94 415.30 311.13 311.13 2.81 246.94 415.30 311.13 311.13 2.82 246.94 415.30 311.13 311.13 2.83 246.94 415.30 311.13 311.13 2.84 246.94 415.30 311.13 311.13 2.85 246.94 415.30 311.13 311.13 2.86 246.94 415.30 311.13 311.13 2.87 246.94 415.30 311.13 311.13 2.88 246.94 415.30 311.13 311.13 2.89 246.94 415.30 311.13 311.13 2.90 246.94 415.30 311.13 311.13 2.91 246.94 415.30 311.13 311.13 2.92 246.94 415.30 311.13 311.13 2.93 246.94 415.30 311.13 311.13 2.94 246.94 415.30 311.13 311.13 2.95 246.94 415.30 311.13 311.13 2.96 246.94 415.30 311.13 311.13 2.97 246.94 415.30 311.13 311.13 2.98 246.94 415.30 311.13 311.13 246.94 2.99 246.94 415.30 311.13 311.13 246.94 3.00 246.94 415.30 311.13 311.13 246.94 3.01 246.94 415.30 311.13 311.13 246.94 493.88 3.02 246.94 415.30 311.13 246.94 493.88 3.03 246.94 415.30 311.13 246.94 493.88 3.04 246.94 415.30 311.13 246.94 493.88 3.05 246.94 415.30 311.13 246.94 493.88 3.06 246.94 415.30 311.13 246.94 493.88 3.07 246.94 311.13 246.94 493.88 3.08 246.94 311.13 246.94 493.88 3.09 246.94 311.13 246.94 493.88 3.10 246.94 311.13 246.94 493.88 3.11 246.94 311.13 246.94 493.88 3.12 246.94 311.13 246.94 493.88 3.13 246.94 311.13 246.94 493.88 3.14 246.94 311.13 246.94 493.88 3.15 246.94 311.13 246.94 493.88 3.16 246.94 311.13 246.94 493.88 3.17 246.94 311.13 246.94 493.88 3.18 246.94 311.13 246.94 493.88 3.19 246.94 311.13 246.94 493.88 3.20 246.94 311.13 246.94 493.88 3.21 246.94 311.13 246.94 493.88 3.22 246.94 311.13 246.94 493.88 3.23 246.94 311.13 246.94 493.88 3.24 246.94 311.13 246.94 493.88 3.25 246.94 311.13 246.94 493.88 3.26 246.94 311.13 246.94 493.88 3.27 246.94 311.13 246.94 493.88 3.28 246.94 311.13 246.94 493.88 3.29 246.94 311.13 246.94 493.88 3.30 246.94 311.13 246.94 493.88 3.31 246.94 311.13 246.94 493.88 3.32 246.94 311.13 246.94 493.88 3.33 246.94 311.13 246.94 493.88 3.34 246.94 311.13 246.94 493.88 3.35 246.94 311.13 246.94 493.88 3.36 246.94 311.13 246.94 493.88 3.37 246.94 311.13 246.94 493.88 3.38 246.94 311.13 246.94 493.88 3.39 246.94 311.13 246.94 493.88 3.40 246.94 311.13 246.94 493.88 3.41 246.94 311.13 246.94 493.88 3.42 246.94 311.13 246.94 493.88 3.43 246.94 311.13 246.94 493.88 3.44 246.94 311.13 246.94 493.88 3.45 246.94 311.13 246.94 493.88 3.46 246.94 311.13 246.94 493.88 311.13 3.47 246.94 311.13 246.94 493.88 311.13 3.48 311.13 246.94 493.88 311.13 3.49 311.13 246.94 493.88 311.13 3.50 311.13 246.94 493.88 311.13 3.51 311.13 246.94 493.88 311.13 3.52 311.13 246.94 493.88 311.13 3.53 311.13 246.94 493.88 311.13 3.54 311.13 246.94 493.88 311.13 3.55 311.13 246.94 493.88 311.13 3.56 311.13 246.94 493.88 311.13 3.57 311.13 246.94 493.88 311.13 3.58 311.13 246.94 493.88 311.13 3.59 311.13 246.94 493.88 311.13 3.60 311.13 246.94 493.88 311.13 3.61 311.13 246.94 493.88 311.13 3.62 311.13 246.94 493.88 311.13 3.63 311.13 246.94 493.88 311.13 3.64 311.13 246.94 493.88 311.13 3.65 311.13 246.94 493.88 311.13 3.66 311.13 246.94 493.88 311.13 3.67 311.13 246.94 493.88 311.13 3.68 311.13 246.94 493.88 311.13 3.69 311.13 246.94 493.88 311.13 3.70 311.13 246.94 493.88 311.13 3.71 311.13 246.94 493.88 311.13 3.72 311.13 246.94 493.88 311.13 3.73 311.13 246.94 493.88 311.13 3.74 311.13 246.94 493.88 311.13 3.75 311.13 246.94 493.88 311.13 3.76 311.13 246.94 493.88 311.13 3.77 311.13 246.94 493.88 311.13 3.78 311.13 246.94 493.88 311.13 3.79 311.13 246.94 493.88 311.13 3.80 311.13 246.94 493.88 311.13 3.81 311.13 246.94 493.88 311.13 3.82 311.13 246.94 493.88 311.13 3.83 311.13 246.94 493.88 311.13 3.84 311.13 246.94 493.88 311.13 3.85 311.13 246.94 493.88 311.13 3.86 311.13 246.94 493.88 311.13 3.87 311.13 246.94 493.88 311.13 3.88 311.13 246.94 493.88 311.13 3.89 311.13 246.94 493.88 311.13 3.90 311.13 246.94 493.88 311.13 3.91 311.13 246.94 493.88 311.13 3.92 311.13 246.94 493.88 311.13 3.93 311.13 246.94 493.88 311.13 3.94 246.94 493.88 311.13 3.95 246.94 493.88 311.13 3.96 246.94 493.88 311.13 207.65 3.97 246.94 493.88 311.13 207.65 3.98 246.94 493.88 311.13 207.65 207.65 3.99 246.94 493.88 207.65 207.65 4.00 246.94 493.88 207.65 207.65 4.01 246.94 493.88 207.65 207.65 4.02 246.94 493.88 207.65 207.65 311.13 4.03 246.94 493.88 207.65 207.65 311.13 4.04 246.94 493.88 207.65 207.65 311.13 4.05 493.88 207.65 207.65 311.13 4.06 493.88 207.65 207.65 311.13 4.07 493.88 207.65 207.65 311.13 4.08 493.88 207.65 207.65 311.13 4.09 493.88 207.65 207.65 311.13 4.10 493.88 207.65 207.65 311.13 4.11 493.88 207.65 207.65 311.13 4.12 493.88 207.65 207.65 311.13 4.13 493.88 207.65 207.65 311.13 4.14 493.88 207.65 207.65 311.13 4.15 493.88 207.65 207.65 311.13 4.16 493.88 207.65 207.65 311.13 4.17 493.88 207.65 207.65 311.13 4.18 493.88 207.65 207.65 311.13 4.19 493.88 207.65 207.65 311.13 4.20 493.88 207.65 207.65 311.13 4.21 493.88 207.65 207.65 311.13 4.22 493.88 207.65 207.65 311.13 4.23 493.88 207.65 207.65 311.13 4.24 493.88 207.65 207.65 311.13 4.25 493.88 207.65 207.65 311.13 4.26 493.88 207.65 207.65 311.13 4.27 493.88 207.65 207.65 311.13 4.28 493.88 207.65 207.65 311.13 4.29 493.88 207.65 207.65 311.13 4.30 493.88 207.65 207.65 311.13 4.31 493.88 207.65 207.65 311.13 4.32 493.88 207.65 207.65 311.13 4.33 493.88 207.65 207.65 311.13 4.34 493.88 207.65 207.65 311.13 4.35 493.88 207.65 207.65 311.13 4.36 493.88 207.65 207.65 311.13 4.37 493.88 207.65 207.65 311.13 4.38 493.88 207.65 207.65 311.13 4.39 493.88 207.65 207.65 311.13 4.40 493.88 207.65 207.65 311.13 4.41 493.88 207.65 207.65 311.13 4.42 493.88 207.65 207.65 311.13 4.43 493.88 207.65 207.65 311.13 4.44 493.88 207.65 207.65 311.13 4.45 493.88 207.65 207.65 311.13 4.46 493.88 207.65 207.65 311.13 4.47 493.88 207.65 207.65 311.13 246.94 4.48 493.88 207.65 207.65 311.13 246.94 4.49 493.88 207.65 207.65 311.13 246.94 4.50 493.88 207.65 207.65 311.13 246.94 4.51 493.88 207.65 311.13 246.94 4.52 493.88 207.65 311.13 246.94 4.53 493.88 207.65 311.13 246.94 4.54 493.88 207.65 311.13 246.94 4.55 493.88 207.65 311.13 246.94 4.56 493.88 207.65 311.13 246.94 4.57 493.88 207.65 311.13 246.94 4.58 493.88 207.65 311.13 246.94 4.59 493.88 207.65 311.13 246.94 4.60 493.88 207.65 311.13 246.94 4.61 493.88 207.65 311.13 246.94 4.62 493.88 207.65 311.13 246.94 4.63 493.88 207.65 311.13 246.94 4.64 493.88 207.65 311.13 246.94 4.65 493.88 207.65 311.13 246.94 4.66 493.88 207.65 311.13 246.94 4.67 493.88 207.65 311.13 246.94 4.68 493.88 207.65 311.13 246.94 4.69 493.88 207.65 311.13 246.94 4.70 493.88 207.65 311.13 246.94 4.71 493.88 207.65 311.13 246.94 4.72 493.88 207.65 311.13 246.94 4.73 493.88 207.65 311.13 246.94 4.74 493.88 207.65 311.13 246.94 4.75 493.88 207.65 311.13 246.94 4.76 493.88 207.65 311.13 246.94 4.77 493.88 207.65 311.13 246.94 4.78 493.88 207.65 311.13 246.94 4.79 493.88 207.65 311.13 246.94 4.80 493.88 207.65 311.13 246.94 4.81 493.88 207.65 311.13 246.94 4.82 493.88 207.65 311.13 246.94 4.83 493.88 207.65 311.13 246.94 4.84 493.88 207.65 311.13 246.94 4.85 493.88 207.65 311.13 246.94 4.86 493.88 207.65 311.13 246.94 4.87 493.88 207.65 311.13 246.94 4.88 493.88 311.13 246.94 4.89 493.88 311.13 246.94 4.90 493.88 311.13 246.94 4.91 493.88 311.13 246.94 4.92 493.88 311.13 246.94 4.93 493.88 311.13 246.94 4.94 493.88 311.13 246.94 138.59 4.95 493.88 311.13 246.94 138.59 4.96 493.88 311.13 246.94 138.59 4.97 493.88 311.13 246.94 138.59 329.63 4.98 493.88 311.13 246.94 138.59 329.63 4.99 493.88 311.13 246.94 138.59 329.63 138.59 5.00 493.88 311.13 246.94 138.59 329.63 138.59 5.01 493.88 311.13 246.94 138.59 329.63 138.59 5.02 493.88 311.13 246.94 138.59 329.63 138.59 5.03 493.88 311.13 246.94 138.59 329.63 138.59 5.04 493.88 311.13 246.94 138.59 329.63 138.59 5.05 493.88 246.94 138.59 329.63 138.59 5.06 493.88 246.94 138.59 329.63 138.59 5.07 493.88 246.94 138.59 329.63 138.59 5.08 493.88 246.94 138.59 329.63 138.59 5.09 493.88 246.94 138.59 329.63 138.59 5.10 493.88 246.94 138.59 329.63 138.59 5.11 493.88 246.94 138.59 329.63 138.59 5.12 493.88 246.94 138.59 329.63 138.59 5.13 493.88 246.94 138.59 329.63 138.59 5.14 493.88 246.94 138.59 329.63 138.59 5.15 493.88 246.94 138.59 329.63 138.59 5.16 493.88 246.94 138.59 329.63 138.59 5.17 493.88 246.94 138.59 329.63 138.59 5.18 493.88 246.94 138.59 329.63 138.59 5.19 493.88 246.94 138.59 329.63 138.59 5.20 493.88 246.94 138.59 329.63 138.59 5.21 493.88 246.94 138.59 329.63 138.59 5.22 493.88 246.94 138.59 329.63 138.59 5.23 493.88 246.94 138.59 329.63 138.59 5.24 493.88 246.94 138.59 329.63 138.59 5.25 493.88 246.94 138.59 329.63 138.59 5.26 493.88 246.94 138.59 329.63 138.59 5.27 493.88 246.94 138.59 329.63 138.59 5.28 493.88 246.94 138.59 329.63 138.59 5.29 493.88 246.94 138.59 329.63 138.59 5.30 493.88 246.94 138.59 329.63 138.59 5.31 493.88 246.94 138.59 329.63 138.59 5.32 493.88 246.94 138.59 329.63 138.59 5.33 493.88 246.94 138.59 329.63 138.59 5.34 493.88 246.94 138.59 329.63 138.59 5.35 493.88 246.94 138.59 329.63 138.59 5.36 493.88 246.94 138.59 329.63 138.59 5.37 493.88 246.94 138.59 329.63 138.59 5.38 493.88 246.94 138.59 329.63 138.59 5.39 493.88 246.94 138.59 329.63 138.59 5.40 493.88 246.94 138.59 329.63 138.59 5.41 493.88 246.94 138.59 329.63 138.59 5.42 493.88 246.94 138.59 329.63 138.59 5.43 493.88 246.94 138.59 329.63 138.59 5.44 493.88 138.59 329.63 138.59 5.45 493.88 138.59 329.63 138.59 5.46 493.88 138.59 329.63 138.59 5.47 493.88 138.59 329.63 138.59 5.48 493.88 138.59 329.63 138.59 5.49 493.88 138.59 329.63 138.59 5.50 493.88 138.59 329.63 138.59 5.51 493.88 138.59 329.63 138.59 5.52 493.88 138.59 329.63 138.59 329.63 5.53 493.88 138.59 329.63 138.59 329.63 5.54 138.59 329.63 138.59 329.63 5.55 138.59 329.63 138.59 329.63 5.56 138.59 329.63 138.59 329.63 5.57 138.59 329.63 138.59 329.63 5.58 138.59 329.63 138.59 329.63 5.59 138.59 329.63 138.59 329.63 5.60 138.59 329.63 138.59 329.63 5.61 138.59 329.63 138.59 329.63 5.62 138.59 329.63 138.59 329.63 5.63 138.59 329.63 138.59 329.63 5.64 138.59 329.63 138.59 329.63 5.65 138.59 329.63 138.59 329.63 5.66 138.59 138.59 329.63 5.67 138.59 138.59 329.63 5.68 138.59 138.59 329.63 5.69 138.59 138.59 329.63 5.70 138.59 138.59 329.63 5.71 138.59 138.59 329.63 5.72 138.59 138.59 329.63 5.73 138.59 138.59 329.63 5.74 138.59 138.59 329.63 5.75 138.59 138.59 329.63 5.76 138.59 138.59 329.63 5.77 138.59 138.59 329.63 5.78 138.59 138.59 329.63 5.79 138.59 138.59 329.63 5.80 138.59 138.59 329.63 5.81 138.59 138.59 329.63 5.82 138.59 138.59 329.63 5.83 138.59 138.59 329.63 5.84 138.59 138.59 329.63 5.85 138.59 138.59 329.63 5.86 138.59 138.59 329.63 5.87 138.59 138.59 329.63 5.88 138.59 138.59 329.63 5.89 138.59 138.59 329.63 5.90 138.59 138.59 329.63 5.91 138.59 138.59 329.63 5.92 138.59 138.59 329.63 5.93 138.59 138.59 329.63 5.94 138.59 138.59 329.63 5.95 138.59 138.59 329.63 5.96 138.59 138.59 329.63 5.97 138.59 138.59 329.63 5.98 138.59 138.59 329.63 5.99 138.59 138.59 329.63 6.00 138.59 138.59 329.63 6.01 138.59 138.59 329.63 6.02 138.59 138.59 329.63 246.94 6.03 138.59 138.59 329.63 246.94 6.04 138.59 138.59 329.63 246.94 6.05 138.59 138.59 246.94 6.06 138.59 138.59 246.94 6.07 138.59 138.59 246.94 6.08 138.59 138.59 246.94 659.26 6.09 138.59 138.59 246.94 659.26 6.10 138.59 138.59 246.94 659.26 6.11 138.59 138.59 246.94 659.26 493.88 6.12 138.59 138.59 246.94 659.26 493.88 6.13 138.59 138.59 246.94 659.26 493.88 6.14 138.59 138.59 246.94 659.26 493.88 6.15 138.59 138.59 246.94 659.26 493.88 6.16 138.59 138.59 246.94 659.26 493.88 6.17 138.59 138.59 246.94 659.26 493.88 6.18 138.59 138.59 246.94 659.26 493.88 6.19 138.59 138.59 246.94 659.26 493.88 6.20 138.59 138.59 246.94 659.26 493.88 6.21 138.59 138.59 246.94 659.26 493.88 6.22 138.59 138.59 246.94 659.26 493.88 6.23 138.59 138.59 246.94 659.26 493.88 6.24 138.59 138.59 246.94 659.26 493.88 6.25 138.59 138.59 246.94 659.26 493.88 6.26 138.59 138.59 246.94 659.26 493.88 6.27 138.59 138.59 246.94 659.26 493.88 6.28 138.59 138.59 246.94 659.26 493.88 6.29 138.59 138.59 246.94 659.26 493.88 6.30 138.59 138.59 246.94 659.26 493.88 6.31 138.59 138.59 246.94 659.26 493.88 6.32 138.59 138.59 246.94 659.26 493.88 6.33 138.59 138.59 246.94 659.26 493.88 6.34 138.59 138.59 246.94 659.26 493.88 6.35 138.59 138.59 246.94 659.26 493.88 6.36 138.59 138.59 246.94 659.26 493.88 6.37 138.59 138.59 246.94 659.26 493.88 6.38 138.59 138.59 246.94 659.26 493.88 6.39 138.59 138.59 246.94 659.26 493.88 6.40 138.59 138.59 246.94 659.26 493.88 6.41 138.59 138.59 246.94 659.26 493.88 6.42 138.59 138.59 246.94 659.26 493.88 6.43 138.59 138.59 246.94 659.26 493.88 6.44 138.59 138.59 246.94 659.26 493.88 6.45 138.59 138.59 246.94 659.26 493.88 6.46 138.59 138.59 246.94 659.26 493.88 6.47 138.59 138.59 246.94 659.26 493.88 6.48 138.59 138.59 246.94 659.26 493.88 6.49 138.59 138.59 246.94 659.26 493.88 6.50 138.59 138.59 246.94 659.26 493.88 6.51 138.59 138.59 246.94 659.26 493.88 329.63 6.52 138.59 138.59 246.94 659.26 493.88 329.63 6.53 138.59 138.59 246.94 659.26 493.88 329.63 6.54 138.59 138.59 246.94 659.26 493.88 329.63 6.55 138.59 138.59 246.94 659.26 493.88 329.63 6.56 138.59 138.59 659.26 493.88 329.63 6.57 138.59 138.59 659.26 493.88 329.63 6.58 138.59 138.59 659.26 493.88 329.63 6.59 138.59 138.59 659.26 493.88 329.63 6.60 138.59 138.59 659.26 493.88 329.63 6.61 138.59 138.59 659.26 493.88 329.63 6.62 138.59 138.59 659.26 493.88 329.63 6.63 138.59 138.59 659.26 493.88 329.63 6.64 138.59 138.59 659.26 493.88 329.63 6.65 138.59 138.59 659.26 493.88 329.63 6.66 138.59 138.59 659.26 493.88 329.63 6.67 138.59 138.59 659.26 493.88 329.63 6.68 138.59 138.59 659.26 493.88 329.63 6.69 138.59 138.59 659.26 493.88 329.63 6.70 138.59 138.59 659.26 493.88 329.63 6.71 138.59 138.59 659.26 493.88 329.63 6.72 138.59 138.59 659.26 493.88 329.63 6.73 138.59 138.59 659.26 493.88 329.63 6.74 138.59 138.59 659.26 493.88 329.63 6.75 138.59 138.59 659.26 493.88 329.63 6.76 138.59 138.59 659.26 493.88 329.63 6.77 138.59 138.59 659.26 493.88 329.63 6.78 138.59 138.59 659.26 493.88 329.63 6.79 138.59 138.59 659.26 493.88 329.63 6.80 138.59 138.59 659.26 493.88 329.63 6.81 138.59 138.59 659.26 493.88 329.63 6.82 138.59 138.59 659.26 493.88 329.63 6.83 138.59 138.59 659.26 493.88 329.63 6.84 138.59 138.59 659.26 493.88 329.63 6.85 138.59 138.59 659.26 493.88 329.63 6.86 138.59 138.59 659.26 493.88 329.63 6.87 138.59 138.59 659.26 493.88 329.63 6.88 138.59 138.59 659.26 493.88 329.63 6.89 138.59 138.59 659.26 493.88 329.63 6.90 138.59 138.59 659.26 493.88 329.63 155.56 6.91 138.59 138.59 659.26 493.88 329.63 155.56 6.92 138.59 138.59 659.26 493.88 329.63 155.56 6.93 138.59 138.59 659.26 493.88 329.63 155.56 739.99 6.94 138.59 138.59 659.26 493.88 329.63 155.56 739.99 6.95 138.59 138.59 659.26 493.88 329.63 155.56 739.99 6.96 138.59 659.26 493.88 329.63 155.56 739.99 6.97 138.59 493.88 329.63 155.56 739.99 6.98 138.59 493.88 155.56 739.99 155.56 6.99 138.59 493.88 155.56 739.99 155.56 220.00 7.00 138.59 493.88 155.56 739.99 155.56 220.00 7.01 138.59 493.88 155.56 739.99 155.56 220.00 7.02 138.59 493.88 155.56 739.99 155.56 220.00 7.03 138.59 493.88 155.56 739.99 155.56 220.00 440.00 7.04 138.59 493.88 155.56 739.99 155.56 220.00 440.00 7.05 493.88 155.56 739.99 155.56 220.00 440.00 7.06 493.88 155.56 739.99 155.56 220.00 440.00 7.07 493.88 155.56 739.99 155.56 220.00 440.00 7.08 493.88 155.56 739.99 155.56 220.00 440.00 7.09 493.88 155.56 739.99 155.56 220.00 440.00 7.10 493.88 155.56 739.99 155.56 220.00 440.00 7.11 493.88 155.56 739.99 155.56 220.00 440.00 7.12 155.56 739.99 155.56 220.00 440.00 7.13 155.56 739.99 155.56 220.00 440.00 7.14 155.56 739.99 155.56 220.00 440.00 7.15 155.56 739.99 155.56 220.00 440.00 7.16 155.56 739.99 155.56 220.00 440.00 7.17 155.56 739.99 155.56 220.00 440.00 7.18 155.56 739.99 155.56 220.00 440.00 7.19 155.56 739.99 155.56 220.00 440.00 7.20 155.56 739.99 155.56 220.00 440.00 7.21 155.56 739.99 155.56 220.00 440.00 7.22 155.56 739.99 155.56 220.00 440.00 7.23 155.56 739.99 155.56 220.00 440.00 7.24 155.56 739.99 155.56 220.00 440.00 7.25 155.56 739.99 155.56 220.00 440.00 7.26 155.56 739.99 155.56 220.00 440.00 7.27 155.56 739.99 155.56 220.00 440.00 7.28 155.56 739.99 155.56 220.00 440.00 7.29 155.56 739.99 155.56 220.00 440.00 7.30 155.56 739.99 155.56 220.00 440.00 7.31 155.56 739.99 155.56 220.00 440.00 7.32 155.56 739.99 155.56 220.00 440.00 7.33 155.56 739.99 155.56 220.00 440.00 7.34 155.56 739.99 155.56 220.00 440.00 7.35 155.56 739.99 155.56 220.00 440.00 7.36 155.56 739.99 155.56 220.00 440.00 7.37 155.56 739.99 155.56 220.00 440.00 7.38 155.56 739.99 155.56 220.00 440.00 7.39 155.56 739.99 155.56 220.00 440.00 7.40 155.56 739.99 155.56 220.00 440.00 7.41 155.56 739.99 155.56 220.00 440.00 7.42 155.56 739.99 155.56 220.00 440.00 7.43 155.56 739.99 155.56 220.00 440.00 7.44 155.56 739.99 155.56 220.00 440.00 7.45 155.56 739.99 155.56 220.00 440.00 7.46 155.56 739.99 155.56 220.00 440.00 7.47 155.56 739.99 155.56 220.00 440.00 369.99 7.48 155.56 739.99 155.56 220.00 440.00 369.99 7.49 155.56 739.99 155.56 220.00 440.00 369.99 7.50 155.56 739.99 155.56 220.00 440.00 369.99 7.51 155.56 739.99 155.56 440.00 369.99 7.52 155.56 739.99 155.56 440.00 369.99 7.53 155.56 739.99 155.56 440.00 369.99 7.54 155.56 739.99 155.56 440.00 369.99 7.55 155.56 739.99 155.56 440.00 369.99 7.56 155.56 739.99 155.56 440.00 369.99 7.57 155.56 739.99 155.56 440.00 369.99 7.58 155.56 739.99 155.56 440.00 369.99 7.59 155.56 739.99 155.56 440.00 369.99 7.60 155.56 739.99 155.56 440.00 369.99 7.61 155.56 739.99 155.56 440.00 369.99 7.62 155.56 739.99 155.56 440.00 369.99 7.63 155.56 739.99 155.56 440.00 369.99 7.64 155.56 739.99 155.56 440.00 369.99 7.65 155.56 739.99 155.56 440.00 369.99 7.66 155.56 739.99 155.56 440.00 369.99 7.67 155.56 739.99 155.56 440.00 369.99 7.68 155.56 739.99 155.56 440.00 369.99 7.69 155.56 739.99 155.56 440.00 369.99 7.70 155.56 739.99 155.56 440.00 369.99 7.71 155.56 739.99 155.56 440.00 369.99 7.72 155.56 739.99 155.56 440.00 369.99 7.73 155.56 739.99 155.56 440.00 369.99 7.74 155.56 739.99 155.56 440.00 369.99 7.75 155.56 739.99 155.56 440.00 369.99 7.76 155.56 739.99 155.56 440.00 369.99 7.77 155.56 739.99 155.56 440.00 369.99 7.78 155.56 739.99 155.56 440.00 369.99 7.79 155.56 739.99 155.56 440.00 369.99 7.80 155.56 739.99 155.56 440.00 369.99 7.81 155.56 739.99 155.56 440.00 369.99 7.82 155.56 739.99 155.56 440.00 369.99 7.83 155.56 739.99 155.56 440.00 369.99 7.84 155.56 739.99 155.56 440.00 369.99 7.85 155.56 739.99 155.56 440.00 369.99 7.86 155.56 739.99 155.56 440.00 369.99 7.87 155.56 739.99 155.56 440.00 369.99 7.88 155.56 739.99 155.56 440.00 369.99 415.30 7.89 155.56 739.99 155.56 440.00 369.99 415.30 7.90 155.56 739.99 155.56 440.00 369.99 415.30 164.81 7.91 155.56 739.99 155.56 440.00 369.99 415.30 164.81 554.37 7.92 155.56 739.99 155.56 369.99 415.30 164.81 554.37 7.93 155.56 739.99 155.56 369.99 415.30 164.81 554.37 7.94 155.56 739.99 155.56 369.99 415.30 164.81 554.37 164.81 7.95 155.56 369.99 415.30 164.81 554.37 164.81 7.96 155.56 369.99 415.30 164.81 554.37 164.81 7.97 155.56 369.99 415.30 164.81 554.37 164.81 7.98 369.99 415.30 164.81 554.37 164.81 7.99 369.99 415.30 164.81 554.37 164.81 207.65 8.00 415.30 164.81 554.37 164.81 207.65 8.01 415.30 164.81 554.37 164.81 207.65 8.02 415.30 164.81 554.37 164.81 207.65 8.03 415.30 164.81 554.37 164.81 207.65 8.04 415.30 164.81 554.37 164.81 207.65 8.05 415.30 164.81 554.37 164.81 207.65 8.06 415.30 164.81 554.37 164.81 207.65 8.07 415.30 164.81 554.37 164.81 207.65 8.08 415.30 164.81 554.37 164.81 207.65 8.09 415.30 164.81 554.37 164.81 207.65 8.10 415.30 164.81 554.37 164.81 207.65 8.11 415.30 164.81 554.37 164.81 207.65 8.12 415.30 164.81 554.37 164.81 207.65 8.13 415.30 164.81 554.37 164.81 207.65 8.14 415.30 164.81 554.37 164.81 207.65 8.15 415.30 164.81 554.37 164.81 207.65 8.16 415.30 164.81 554.37 164.81 207.65 8.17 415.30 164.81 554.37 164.81 207.65 8.18 415.30 164.81 554.37 164.81 207.65 8.19 415.30 164.81 554.37 164.81 207.65 8.20 415.30 164.81 554.37 164.81 207.65 8.21 415.30 164.81 554.37 164.81 207.65 8.22 415.30 164.81 554.37 164.81 207.65 8.23 415.30 164.81 554.37 164.81 207.65 8.24 415.30 164.81 554.37 164.81 207.65 8.25 415.30 164.81 554.37 164.81 207.65 8.26 415.30 164.81 554.37 164.81 207.65 8.27 415.30 164.81 554.37 164.81 207.65 8.28 415.30 164.81 554.37 164.81 207.65 8.29 415.30 164.81 554.37 164.81 207.65 8.30 415.30 164.81 554.37 164.81 207.65 8.31 415.30 164.81 554.37 164.81 207.65 8.32 415.30 164.81 554.37 164.81 207.65 8.33 415.30 164.81 554.37 164.81 207.65 8.34 415.30 164.81 554.37 164.81 207.65 8.35 415.30 164.81 554.37 164.81 207.65 8.36 415.30 164.81 554.37 164.81 207.65 8.37 415.30 164.81 554.37 164.81 207.65 8.38 415.30 164.81 554.37 164.81 207.65 8.39 415.30 164.81 554.37 164.81 207.65 8.40 415.30 164.81 554.37 164.81 207.65 8.41 415.30 164.81 554.37 164.81 207.65 415.30 8.42 415.30 164.81 554.37 164.81 207.65 415.30 8.43 415.30 164.81 554.37 164.81 415.30 8.44 415.30 164.81 554.37 164.81 415.30 8.45 415.30 164.81 554.37 164.81 415.30 8.46 415.30 164.81 554.37 164.81 415.30 8.47 415.30 164.81 554.37 164.81 415.30 8.48 415.30 164.81 554.37 164.81 415.30 8.49 415.30 164.81 554.37 164.81 415.30 8.50 415.30 164.81 554.37 164.81 415.30 8.51 415.30 164.81 554.37 164.81 415.30 8.52 415.30 164.81 554.37 164.81 415.30 8.53 415.30 164.81 554.37 164.81 415.30 8.54 415.30 164.81 554.37 164.81 415.30 8.55 415.30 164.81 554.37 164.81 415.30 8.56 415.30 164.81 554.37 164.81 415.30 8.57 415.30 164.81 554.37 164.81 415.30 8.58 415.30 164.81 554.37 164.81 415.30 8.59 415.30 164.81 554.37 164.81 415.30 8.60 415.30 164.81 554.37 164.81 415.30 8.61 415.30 164.81 554.37 164.81 415.30 8.62 415.30 164.81 554.37 164.81 415.30 8.63 415.30 164.81 554.37 164.81 415.30 8.64 415.30 164.81 554.37 164.81 415.30 8.65 415.30 164.81 554.37 164.81 415.30 8.66 415.30 164.81 554.37 164.81 415.30 8.67 415.30 164.81 554.37 164.81 415.30 8.68 415.30 164.81 554.37 164.81 415.30 8.69 415.30 164.81 554.37 164.81 415.30 8.70 415.30 164.81 554.37 164.81 415.30 8.71 415.30 164.81 554.37 164.81 415.30 8.72 415.30 164.81 554.37 164.81 415.30 8.73 415.30 164.81 554.37 164.81 415.30 8.74 415.30 164.81 554.37 164.81 415.30 8.75 415.30 164.81 554.37 164.81 415.30 8.76 415.30 164.81 554.37 164.81 415.30 8.77 415.30 164.81 554.37 164.81 415.30 8.78 415.30 164.81 554.37 164.81 415.30 8.79 415.30 164.81 554.37 164.81 415.30 8.80 415.30 164.81 554.37 164.81 415.30 8.81 415.30 164.81 554.37 164.81 415.30 8.82 415.30 164.81 554.37 164.81 415.30 8.83 415.30 164.81 554.37 164.81 415.30 8.84 415.30 164.81 554.37 164.81 415.30 8.85 415.30 164.81 554.37 164.81 415.30 8.86 415.30 164.81 554.37 164.81 415.30 8.87 415.30 164.81 554.37 164.81 415.30 8.88 415.30 164.81 554.37 164.81 415.30 8.89 415.30 164.81 554.37 164.81 415.30 207.65 8.90 415.30 164.81 554.37 164.81 415.30 207.65 8.91 164.81 554.37 164.81 415.30 207.65 277.18 8.92 164.81 554.37 164.81 415.30 207.65 277.18 8.93 164.81 554.37 164.81 415.30 207.65 277.18 8.94 164.81 554.37 164.81 415.30 207.65 277.18 8.95 164.81 554.37 164.81 415.30 207.65 277.18 659.26 8.96 164.81 554.37 164.81 415.30 207.65 277.18 659.26 8.97 164.81 554.37 164.81 207.65 277.18 659.26 8.98 164.81 554.37 164.81 207.65 277.18 659.26 8.99 164.81 164.81 207.65 277.18 659.26 9.00 164.81 164.81 207.65 277.18 659.26 9.01 164.81 164.81 207.65 277.18 659.26 9.02 164.81 164.81 207.65 277.18 659.26 9.03 164.81 164.81 207.65 277.18 659.26 9.04 164.81 164.81 207.65 277.18 659.26 9.05 164.81 164.81 207.65 277.18 659.26 9.06 164.81 164.81 207.65 277.18 659.26 9.07 164.81 164.81 207.65 277.18 659.26 9.08 164.81 164.81 207.65 277.18 659.26 9.09 164.81 164.81 207.65 277.18 659.26 9.10 164.81 164.81 207.65 277.18 659.26 9.11 164.81 164.81 207.65 277.18 659.26 9.12 164.81 164.81 207.65 277.18 659.26 9.13 164.81 164.81 207.65 277.18 659.26 9.14 164.81 164.81 207.65 277.18 659.26 9.15 164.81 164.81 207.65 277.18 659.26 9.16 164.81 164.81 207.65 277.18 659.26 9.17 164.81 164.81 207.65 277.18 659.26 9.18 164.81 164.81 207.65 277.18 659.26 9.19 164.81 164.81 207.65 277.18 659.26 9.20 164.81 164.81 207.65 277.18 659.26 9.21 164.81 164.81 207.65 277.18 659.26 9.22 164.81 164.81 207.65 277.18 659.26 9.23 164.81 164.81 207.65 277.18 659.26 9.24 164.81 164.81 207.65 277.18 659.26 9.25 164.81 164.81 207.65 277.18 659.26 9.26 164.81 164.81 207.65 277.18 659.26 9.27 164.81 164.81 207.65 277.18 659.26 9.28 164.81 164.81 207.65 277.18 659.26 9.29 164.81 164.81 207.65 277.18 659.26 9.30 164.81 164.81 207.65 277.18 659.26 9.31 164.81 164.81 207.65 277.18 659.26 9.32 164.81 164.81 207.65 277.18 659.26 9.33 164.81 164.81 207.65 277.18 659.26 9.34 164.81 164.81 207.65 277.18 659.26 9.35 164.81 164.81 207.65 277.18 659.26 9.36 164.81 164.81 207.65 277.18 659.26 9.37 164.81 164.81 207.65 277.18 659.26 9.38 164.81 164.81 207.65 277.18 659.26 415.30 9.39 164.81 164.81 207.65 277.18 659.26 415.30 9.40 164.81 164.81 207.65 277.18 659.26 415.30 9.41 164.81 164.81 207.65 277.18 659.26 415.30 9.42 164.81 164.81 207.65 659.26 415.30 9.43 164.81 164.81 207.65 659.26 415.30 9.44 164.81 164.81 207.65 659.26 415.30 9.45 164.81 164.81 207.65 659.26 415.30 9.46 164.81 164.81 207.65 659.26 415.30 9.47 164.81 164.81 207.65 659.26 415.30 9.48 164.81 164.81 207.65 659.26 415.30 9.49 164.81 164.81 207.65 659.26 415.30 9.50 164.81 164.81 207.65 659.26 415.30 9.51 164.81 164.81 207.65 659.26 415.30 9.52 164.81 164.81 207.65 659.26 415.30 9.53 164.81 164.81 207.65 659.26 415.30 9.54 164.81 164.81 207.65 659.26 415.30 9.55 164.81 164.81 207.65 659.26 415.30 9.56 164.81 164.81 207.65 659.26 415.30 9.57 164.81 164.81 207.65 659.26 415.30 9.58 164.81 164.81 207.65 659.26 415.30 9.59 164.81 164.81 207.65 659.26 415.30 9.60 164.81 164.81 207.65 659.26 415.30 9.61 164.81 164.81 207.65 659.26 415.30 9.62 164.81 164.81 207.65 659.26 415.30 9.63 164.81 164.81 207.65 659.26 415.30 9.64 164.81 164.81 207.65 659.26 415.30 9.65 164.81 164.81 207.65 659.26 415.30 9.66 164.81 164.81 207.65 659.26 415.30 9.67 164.81 164.81 207.65 659.26 415.30 9.68 164.81 164.81 207.65 659.26 415.30 9.69 164.81 164.81 207.65 659.26 415.30 9.70 164.81 164.81 207.65 659.26 415.30 9.71 164.81 164.81 207.65 659.26 415.30 9.72 164.81 164.81 207.65 659.26 415.30 9.73 164.81 164.81 207.65 659.26 415.30 9.74 164.81 164.81 207.65 659.26 415.30 9.75 164.81 164.81 207.65 659.26 415.30 9.76 164.81 164.81 207.65 659.26 415.30 9.77 164.81 164.81 207.65 659.26 415.30 9.78 164.81 164.81 207.65 659.26 415.30 9.79 164.81 164.81 207.65 659.26 415.30 155.56 9.80 164.81 164.81 207.65 659.26 415.30 155.56 9.81 164.81 164.81 207.65 659.26 415.30 155.56 493.88 9.82 164.81 164.81 207.65 659.26 415.30 155.56 493.88 9.83 164.81 164.81 207.65 659.26 415.30 155.56 493.88 246.94 9.84 164.81 207.65 659.26 415.30 155.56 493.88 246.94 9.85 164.81 207.65 659.26 155.56 493.88 246.94 155.56 9.86 164.81 207.65 659.26 155.56 493.88 246.94 155.56 9.87 164.81 207.65 659.26 155.56 493.88 246.94 155.56 9.88 164.81 207.65 659.26 155.56 493.88 246.94 155.56 9.89 207.65 659.26 155.56 493.88 246.94 155.56 9.90 659.26 155.56 493.88 246.94 155.56 9.91 659.26 155.56 493.88 246.94 155.56 9.92 659.26 155.56 493.88 246.94 155.56 9.93 659.26 155.56 493.88 246.94 155.56 9.94 659.26 155.56 493.88 246.94 155.56 9.95 659.26 155.56 493.88 246.94 155.56 9.96 659.26 155.56 493.88 246.94 155.56 9.97 659.26 155.56 493.88 246.94 155.56 9.98 659.26 155.56 493.88 246.94 155.56 9.99 659.26 155.56 493.88 246.94 155.56 10.00 659.26 155.56 493.88 246.94 155.56 10.01 659.26 155.56 493.88 246.94 155.56 10.02 659.26 155.56 493.88 246.94 155.56 10.03 659.26 155.56 493.88 246.94 155.56 10.04 659.26 155.56 493.88 246.94 155.56 10.05 659.26 155.56 493.88 246.94 155.56 10.06 659.26 155.56 493.88 246.94 155.56 10.07 659.26 155.56 493.88 246.94 155.56 10.08 659.26 155.56 493.88 246.94 155.56 10.09 659.26 155.56 493.88 246.94 155.56 10.10 659.26 155.56 493.88 246.94 155.56 10.11 659.26 155.56 493.88 246.94 155.56 10.12 659.26 155.56 493.88 246.94 155.56 10.13 659.26 155.56 493.88 246.94 155.56 10.14 659.26 155.56 493.88 246.94 155.56 10.15 659.26 155.56 493.88 246.94 155.56 10.16 659.26 155.56 493.88 246.94 155.56 10.17 659.26 155.56 493.88 246.94 155.56 10.18 659.26 155.56 493.88 246.94 155.56 10.19 659.26 155.56 493.88 246.94 155.56 10.20 659.26 155.56 493.88 246.94 155.56 10.21 659.26 155.56 493.88 246.94 155.56 10.22 659.26 155.56 493.88 246.94 155.56 10.23 659.26 155.56 493.88 246.94 155.56 10.24 659.26 155.56 493.88 246.94 155.56 10.25 659.26 155.56 493.88 246.94 155.56 10.26 659.26 155.56 493.88 246.94 155.56 10.27 659.26 155.56 493.88 246.94 155.56 10.28 659.26 155.56 493.88 246.94 155.56 10.29 659.26 155.56 493.88 246.94 155.56 10.30 659.26 155.56 493.88 246.94 155.56 10.31 659.26 155.56 493.88 246.94 155.56 10.32 659.26 155.56 493.88 246.94 155.56 10.33 659.26 155.56 493.88 246.94 155.56 10.34 659.26 155.56 246.94 155.56 10.35 659.26 155.56 246.94 155.56 246.94 10.36 659.26 155.56 246.94 155.56 246.94 10.37 659.26 155.56 246.94 155.56 246.94 10.38 659.26 155.56 246.94 155.56 246.94 10.39 659.26 155.56 246.94 155.56 246.94 10.40 659.26 155.56 246.94 155.56 246.94 10.41 659.26 155.56 246.94 155.56 246.94 10.42 659.26 155.56 246.94 155.56 246.94 10.43 659.26 155.56 246.94 155.56 246.94 10.44 659.26 155.56 246.94 155.56 246.94 10.45 659.26 155.56 246.94 155.56 246.94 10.46 659.26 155.56 246.94 155.56 246.94 10.47 659.26 155.56 246.94 155.56 246.94 10.48 659.26 155.56 246.94 155.56 246.94 10.49 659.26 155.56 246.94 155.56 246.94 10.50 659.26 155.56 246.94 155.56 246.94 10.51 659.26 155.56 246.94 155.56 246.94 10.52 659.26 155.56 246.94 155.56 246.94 10.53 659.26 155.56 246.94 155.56 246.94 10.54 659.26 155.56 246.94 155.56 246.94 10.55 659.26 155.56 246.94 155.56 246.94 10.56 659.26 155.56 246.94 155.56 246.94 10.57 659.26 155.56 246.94 155.56 246.94 10.58 659.26 155.56 246.94 155.56 246.94 10.59 659.26 155.56 246.94 155.56 246.94 10.60 659.26 155.56 246.94 155.56 246.94 10.61 659.26 155.56 246.94 155.56 246.94 10.62 659.26 155.56 246.94 155.56 246.94 10.63 659.26 155.56 246.94 155.56 246.94 10.64 659.26 155.56 246.94 155.56 246.94 10.65 659.26 155.56 246.94 155.56 246.94 10.66 659.26 155.56 246.94 155.56 246.94 10.67 659.26 155.56 246.94 155.56 246.94 10.68 659.26 155.56 246.94 155.56 246.94 10.69 659.26 155.56 246.94 155.56 246.94 10.70 659.26 155.56 246.94 155.56 246.94 10.71 659.26 155.56 246.94 155.56 246.94 10.72 659.26 155.56 246.94 155.56 246.94 10.73 659.26 155.56 246.94 155.56 246.94 10.74 659.26 155.56 246.94 155.56 246.94 10.75 659.26 155.56 246.94 155.56 246.94 138.59 10.76 659.26 155.56 246.94 155.56 246.94 138.59 10.77 659.26 155.56 246.94 155.56 246.94 138.59 10.78 659.26 155.56 246.94 155.56 246.94 138.59 10.79 659.26 155.56 155.56 246.94 138.59 10.80 659.26 155.56 155.56 246.94 138.59 10.81 659.26 155.56 155.56 246.94 138.59 138.59 10.82 659.26 155.56 155.56 246.94 138.59 138.59 10.83 659.26 155.56 246.94 138.59 138.59 233.08 10.84 659.26 155.56 246.94 138.59 138.59 233.08 10.85 659.26 155.56 246.94 138.59 138.59 233.08 10.86 659.26 155.56 246.94 138.59 138.59 233.08 10.87 659.26 246.94 138.59 138.59 233.08 10.88 659.26 246.94 138.59 138.59 233.08 10.89 659.26 246.94 138.59 138.59 233.08 10.90 659.26 138.59 138.59 233.08 10.91 659.26 138.59 138.59 233.08 10.92 659.26 138.59 138.59 233.08 10.93 659.26 138.59 138.59 233.08 10.94 659.26 138.59 138.59 233.08 10.95 659.26 138.59 138.59 233.08 10.96 659.26 138.59 138.59 233.08 10.97 659.26 138.59 138.59 233.08 10.98 659.26 138.59 138.59 233.08 10.99 659.26 138.59 138.59 233.08 11.00 659.26 138.59 138.59 233.08 11.01 659.26 138.59 138.59 233.08 11.02 659.26 138.59 138.59 233.08 11.03 659.26 138.59 138.59 233.08 11.04 659.26 138.59 138.59 233.08 11.05 659.26 138.59 138.59 233.08 11.06 659.26 138.59 138.59 233.08 11.07 659.26 138.59 138.59 233.08 11.08 659.26 138.59 138.59 233.08 11.09 659.26 138.59 138.59 233.08 11.10 659.26 138.59 138.59 233.08 11.11 659.26 138.59 138.59 233.08 11.12 659.26 138.59 138.59 233.08 11.13 659.26 138.59 138.59 233.08 11.14 659.26 138.59 138.59 233.08 11.15 659.26 138.59 138.59 233.08 11.16 659.26 138.59 138.59 233.08 11.17 659.26 138.59 138.59 233.08 11.18 659.26 138.59 138.59 233.08 11.19 659.26 138.59 138.59 233.08 11.20 659.26 138.59 138.59 233.08 11.21 659.26 138.59 138.59 233.08 11.22 659.26 138.59 138.59 233.08 11.23 659.26 138.59 138.59 233.08 11.24 659.26 138.59 138.59 233.08 11.25 659.26 138.59 138.59 233.08 11.26 659.26 138.59 138.59 233.08 11.27 659.26 138.59 138.59 233.08 466.16 11.28 659.26 138.59 138.59 233.08 466.16 329.63 11.29 659.26 138.59 138.59 233.08 466.16 329.63 11.30 659.26 138.59 138.59 233.08 466.16 329.63 11.31 659.26 138.59 138.59 233.08 466.16 329.63 11.32 659.26 138.59 138.59 233.08 466.16 329.63 11.33 659.26 138.59 138.59 233.08 466.16 329.63 11.34 659.26 138.59 138.59 233.08 466.16 329.63 11.35 659.26 138.59 138.59 233.08 466.16 329.63 11.36 659.26 138.59 138.59 233.08 466.16 329.63 11.37 659.26 138.59 138.59 233.08 466.16 329.63 11.38 659.26 138.59 138.59 233.08 466.16 329.63 11.39 659.26 138.59 138.59 233.08 466.16 329.63 11.40 659.26 138.59 138.59 233.08 466.16 329.63 11.41 659.26 138.59 138.59 233.08 466.16 329.63 11.42 659.26 138.59 138.59 233.08 466.16 329.63 11.43 659.26 138.59 138.59 233.08 466.16 329.63 11.44 659.26 138.59 138.59 233.08 466.16 329.63 11.45 659.26 138.59 138.59 233.08 466.16 329.63 11.46 659.26 138.59 138.59 233.08 466.16 329.63 11.47 659.26 138.59 138.59 233.08 466.16 329.63 11.48 659.26 138.59 138.59 233.08 466.16 329.63 11.49 659.26 138.59 138.59 233.08 466.16 329.63 11.50 659.26 138.59 138.59 233.08 466.16 329.63 11.51 659.26 138.59 138.59 233.08 466.16 329.63 11.52 659.26 138.59 138.59 233.08 466.16 329.63 11.53 659.26 138.59 138.59 233.08 466.16 329.63 11.54 659.26 138.59 138.59 233.08 466.16 329.63 11.55 659.26 138.59 138.59 233.08 466.16 329.63 11.56 659.26 138.59 138.59 233.08 466.16 329.63 11.57 659.26 138.59 138.59 233.08 466.16 329.63 11.58 659.26 138.59 138.59 233.08 466.16 329.63 11.59 659.26 138.59 138.59 233.08 466.16 329.63 11.60 659.26 138.59 138.59 233.08 466.16 329.63 11.61 659.26 138.59 138.59 233.08 466.16 329.63 11.62 659.26 138.59 233.08 466.16 329.63 11.63 138.59 233.08 466.16 329.63 11.64 138.59 233.08 466.16 329.63 11.65 138.59 233.08 466.16 329.63 11.66 138.59 233.08 466.16 329.63 11.67 138.59 233.08 466.16 329.63 11.68 138.59 233.08 466.16 329.63 11.69 138.59 233.08 466.16 329.63 415.30 11.70 138.59 233.08 466.16 329.63 415.30 11.71 138.59 233.08 466.16 329.63 415.30 11.72 138.59 233.08 466.16 329.63 415.30 233.08 11.73 138.59 233.08 466.16 329.63 415.30 233.08 138.59 11.74 138.59 233.08 466.16 415.30 233.08 138.59 830.61 11.75 138.59 233.08 466.16 415.30 233.08 138.59 830.61 11.76 138.59 233.08 415.30 233.08 138.59 830.61 11.77 138.59 233.08 415.30 233.08 138.59 830.61 11.78 138.59 233.08 415.30 233.08 138.59 830.61 11.79 138.59 233.08 415.30 233.08 138.59 830.61 11.80 138.59 233.08 415.30 233.08 138.59 830.61 11.81 138.59 233.08 415.30 233.08 138.59 830.61 11.82 138.59 233.08 415.30 233.08 138.59 830.61 329.63 11.83 138.59 233.08 415.30 233.08 138.59 830.61 329.63 11.84 138.59 415.30 233.08 138.59 830.61 329.63 11.85 138.59 415.30 233.08 138.59 830.61 329.63 11.86 138.59 415.30 233.08 138.59 830.61 329.63 11.87 138.59 415.30 233.08 138.59 830.61 329.63 11.88 138.59 415.30 233.08 138.59 830.61 329.63 11.89 138.59 415.30 233.08 138.59 830.61 329.63 11.90 138.59 415.30 233.08 138.59 830.61 329.63 11.91 138.59 415.30 233.08 138.59 830.61 329.63 11.92 138.59 415.30 233.08 138.59 830.61 329.63 11.93 138.59 415.30 233.08 138.59 830.61 329.63 11.94 138.59 415.30 233.08 138.59 830.61 329.63 11.95 138.59 415.30 233.08 138.59 830.61 329.63 11.96 138.59 415.30 233.08 138.59 830.61 329.63 11.97 138.59 415.30 233.08 138.59 830.61 329.63 11.98 138.59 415.30 233.08 138.59 830.61 329.63 11.99 138.59 415.30 233.08 138.59 830.61 329.63 12.00 138.59 415.30 233.08 138.59 830.61 329.63 12.01 138.59 415.30 233.08 138.59 830.61 329.63 12.02 138.59 415.30 233.08 138.59 830.61 329.63 12.03 138.59 415.30 233.08 138.59 830.61 329.63 12.04 138.59 415.30 233.08 138.59 830.61 329.63 12.05 138.59 415.30 233.08 138.59 830.61 329.63 12.06 138.59 415.30 233.08 138.59 830.61 329.63 12.07 415.30 233.08 138.59 830.61 329.63 12.08 415.30 233.08 138.59 830.61 329.63 12.09 415.30 233.08 138.59 830.61 329.63 12.10 415.30 233.08 138.59 830.61 329.63 12.11 415.30 233.08 138.59 830.61 329.63 12.12 415.30 233.08 138.59 830.61 329.63 12.13 415.30 233.08 138.59 830.61 329.63 12.14 415.30 233.08 138.59 830.61 329.63 12.15 415.30 233.08 138.59 830.61 329.63 12.16 415.30 233.08 138.59 830.61 329.63 12.17 415.30 233.08 138.59 830.61 329.63 12.18 415.30 138.59 830.61 329.63 12.19 415.30 138.59 830.61 329.63 12.20 415.30 138.59 830.61 329.63 12.21 415.30 138.59 830.61 329.63 329.63 12.22 415.30 138.59 830.61 329.63 329.63 12.23 415.30 138.59 830.61 329.63 329.63 12.24 415.30 138.59 830.61 329.63 329.63 12.25 415.30 138.59 830.61 329.63 329.63 12.26 415.30 138.59 830.61 329.63 329.63 12.27 415.30 138.59 830.61 329.63 329.63 12.28 415.30 138.59 830.61 329.63 329.63 12.29 415.30 138.59 830.61 329.63 329.63 12.30 415.30 138.59 830.61 329.63 329.63 12.31 415.30 138.59 830.61 329.63 329.63 12.32 415.30 138.59 830.61 329.63 329.63 12.33 415.30 138.59 830.61 329.63 329.63 12.34 415.30 138.59 830.61 329.63 329.63 12.35 415.30 138.59 830.61 329.63 329.63 12.36 415.30 138.59 830.61 329.63 329.63 12.37 415.30 138.59 830.61 329.63 329.63 12.38 415.30 138.59 830.61 329.63 329.63 12.39 415.30 138.59 830.61 329.63 329.63 12.40 415.30 138.59 830.61 329.63 329.63 12.41 415.30 138.59 830.61 329.63 329.63 12.42 415.30 138.59 830.61 329.63 329.63 12.43 415.30 138.59 830.61 329.63 329.63 12.44 415.30 138.59 830.61 329.63 329.63 12.45 415.30 138.59 830.61 329.63 329.63 12.46 415.30 138.59 830.61 329.63 329.63 12.47 415.30 138.59 830.61 329.63 329.63 12.48 415.30 138.59 830.61 329.63 329.63 12.49 415.30 138.59 830.61 329.63 329.63 12.50 415.30 138.59 830.61 329.63 329.63 12.51 415.30 138.59 830.61 329.63 329.63 12.52 415.30 138.59 830.61 329.63 329.63 12.53 415.30 138.59 830.61 329.63 329.63 12.54 415.30 138.59 830.61 329.63 329.63 12.55 415.30 138.59 830.61 329.63 329.63 12.56 415.30 138.59 830.61 329.63 329.63 12.57 415.30 138.59 830.61 329.63 329.63 12.58 415.30 138.59 830.61 329.63 329.63 12.59 415.30 138.59 830.61 329.63 329.63 12.60 415.30 138.59 830.61 329.63 329.63 12.61 415.30 138.59 830.61 329.63 329.63 12.62 415.30 138.59 830.61 329.63 329.63 12.63 415.30 138.59 830.61 329.63 329.63 12.64 415.30 138.59 830.61 329.63 329.63 12.65 415.30 138.59 830.61 329.63 329.63 12.66 415.30 138.59 830.61 329.63 329.63 12.67 415.30 138.59 830.61 329.63 329.63 659.26 12.68 415.30 138.59 830.61 329.63 329.63 659.26 466.16 12.69 415.30 138.59 830.61 329.63 329.63 659.26 466.16 138.59 69.30 12.70 415.30 138.59 830.61 329.63 329.63 659.26 466.16 138.59 69.30 69.30 466.16 12.71 415.30 138.59 830.61 329.63 659.26 466.16 138.59 69.30 69.30 466.16 12.72 415.30 138.59 830.61 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 12.73 415.30 138.59 830.61 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 12.74 138.59 830.61 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 12.75 138.59 830.61 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 12.76 138.59 830.61 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 12.77 138.59 830.61 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 12.78 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.79 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.80 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.81 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.82 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.83 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.84 329.63 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.85 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.86 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.87 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.88 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.89 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.90 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.91 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.92 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.93 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.94 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.95 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.96 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.97 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.98 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 12.99 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.00 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.01 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.02 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.03 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.04 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.05 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.06 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.07 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.08 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.09 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.10 659.26 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.11 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.12 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.13 466.16 138.59 69.30 69.30 466.16 932.33 164.81 13.14 466.16 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.15 466.16 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.16 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.17 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.18 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.19 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.20 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.21 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.22 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.23 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.24 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.25 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.26 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.27 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.28 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.29 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.30 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.31 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.32 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.33 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.34 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.35 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.36 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.37 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.38 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.39 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.40 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.41 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.42 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.43 138.59 69.30 69.30 466.16 932.33 164.81 329.63 13.44 138.59 69.30 466.16 932.33 164.81 329.63 13.45 138.59 69.30 466.16 932.33 164.81 329.63 13.46 138.59 69.30 466.16 932.33 164.81 329.63 13.47 69.30 466.16 932.33 164.81 329.63 13.48 69.30 466.16 932.33 164.81 329.63 13.49 69.30 466.16 932.33 164.81 329.63 13.50 69.30 466.16 932.33 164.81 329.63 13.51 69.30 466.16 932.33 164.81 329.63 13.52 69.30 466.16 932.33 164.81 329.63 13.53 69.30 466.16 932.33 164.81 329.63 13.54 69.30 466.16 932.33 164.81 329.63 13.55 69.30 466.16 932.33 164.81 329.63 13.56 69.30 466.16 932.33 164.81 329.63 13.57 69.30 466.16 932.33 164.81 329.63 13.58 69.30 466.16 932.33 164.81 329.63 13.59 69.30 466.16 932.33 164.81 329.63 13.60 69.30 466.16 932.33 164.81 329.63 77.78 13.61 69.30 466.16 932.33 164.81 329.63 77.78 369.99 13.62 69.30 466.16 932.33 164.81 329.63 77.78 369.99 13.63 69.30 932.33 164.81 329.63 77.78 369.99 77.78 155.56 13.64 932.33 164.81 329.63 77.78 369.99 77.78 155.56 493.88 13.65 932.33 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 13.66 932.33 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 13.67 932.33 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 13.68 932.33 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 13.69 932.33 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 13.70 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 13.71 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 13.72 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 13.73 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.74 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.75 164.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.76 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.77 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.78 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.79 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.80 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.81 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.82 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.83 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.84 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.85 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.86 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.87 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.88 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.89 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.90 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.91 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.92 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.93 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.94 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.95 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.96 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.97 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.98 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 13.99 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.00 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.01 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.02 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.03 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.04 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.05 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.06 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.07 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.08 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.09 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.10 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.11 77.78 369.99 77.78 155.56 493.88 369.99 739.99 246.94 14.12 77.78 77.78 155.56 493.88 369.99 739.99 246.94 14.13 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.14 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.15 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.16 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.17 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.18 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.19 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.20 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.21 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.22 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.23 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.24 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.25 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.26 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.27 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.28 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.29 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.30 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.31 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.32 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.33 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.34 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.35 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.36 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.37 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.38 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.39 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.40 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.41 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.42 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.43 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.44 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.45 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.46 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.47 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.48 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.49 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.50 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.51 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.52 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 14.53 77.78 77.78 155.56 493.88 369.99 739.99 246.94 246.94 466.16 14.54 77.78 77.78 155.56 493.88 739.99 246.94 246.94 466.16 369.99 14.55 77.78 77.78 155.56 493.88 739.99 246.94 246.94 466.16 369.99 14.56 77.78 77.78 155.56 493.88 739.99 246.94 246.94 466.16 369.99 14.57 77.78 77.78 155.56 493.88 739.99 246.94 246.94 466.16 369.99 14.58 77.78 77.78 155.56 493.88 739.99 246.94 466.16 369.99 14.59 77.78 77.78 155.56 493.88 739.99 246.94 466.16 369.99 14.60 77.78 77.78 155.56 493.88 739.99 246.94 466.16 369.99 14.61 77.78 77.78 155.56 493.88 466.16 369.99 14.62 77.78 155.56 493.88 466.16 369.99 155.56 14.63 77.78 155.56 493.88 466.16 369.99 155.56 932.33 14.64 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.65 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.66 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.67 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.68 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.69 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.70 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.71 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.72 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.73 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.74 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.75 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.76 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.77 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.78 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.79 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.80 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.81 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.82 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.83 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.84 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.85 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.86 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.87 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.88 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.89 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.90 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.91 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.92 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.93 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.94 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.95 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.96 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.97 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.98 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 14.99 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 15.00 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 15.01 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 15.02 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 15.03 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 15.04 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 15.05 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 246.94 15.06 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 246.94 15.07 77.78 155.56 493.88 466.16 369.99 155.56 932.33 369.99 246.94 15.08 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.09 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.10 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.11 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.12 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.13 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.14 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.15 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.16 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.17 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.18 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.19 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.20 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.21 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.22 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.23 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.24 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.25 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.26 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.27 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.28 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.29 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.30 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.31 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.32 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.33 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.34 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.35 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.36 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.37 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.38 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.39 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.40 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.41 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.42 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.43 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.44 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.45 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.46 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.47 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.48 77.78 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.49 155.56 493.88 466.16 155.56 932.33 369.99 246.94 15.50 155.56 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 15.51 155.56 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 15.52 155.56 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 15.53 155.56 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 123.47 15.54 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 123.47 311.13 15.55 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 123.47 311.13 15.56 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 123.47 311.13 15.57 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 123.47 311.13 311.13 15.58 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 123.47 311.13 311.13 15.59 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 123.47 311.13 311.13 15.60 493.88 466.16 155.56 932.33 369.99 246.94 61.74 123.47 123.47 311.13 311.13 15.61 493.88 466.16 155.56 932.33 61.74 123.47 123.47 311.13 311.13 15.62 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.63 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.64 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.65 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.66 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.67 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.68 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.69 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.70 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.71 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.72 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.73 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.74 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.75 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.76 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.77 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.78 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.79 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.80 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.81 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.82 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.83 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.84 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.85 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.86 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.87 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.88 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.89 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.90 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.91 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.92 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.93 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.94 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.95 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.96 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.97 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 15.98 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 415.30 15.99 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 415.30 830.61 16.00 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 415.30 830.61 16.01 493.88 466.16 932.33 61.74 123.47 123.47 311.13 311.13 415.30 830.61 16.02 493.88 466.16 61.74 123.47 123.47 311.13 311.13 415.30 830.61 16.03 493.88 61.74 123.47 123.47 311.13 311.13 415.30 830.61 16.04 493.88 61.74 123.47 123.47 311.13 311.13 415.30 830.61 246.94 16.05 493.88 61.74 123.47 123.47 311.13 311.13 415.30 830.61 246.94 16.06 61.74 123.47 123.47 311.13 311.13 415.30 830.61 246.94 16.07 61.74 123.47 123.47 311.13 311.13 415.30 830.61 246.94 16.08 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.09 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.10 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.11 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.12 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.13 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.14 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.15 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.16 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.17 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.18 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.19 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.20 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.21 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.22 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.23 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.24 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.25 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.26 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.27 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.28 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.29 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.30 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.31 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.32 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.33 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.34 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.35 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.36 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.37 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.38 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.39 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.40 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.41 61.74 123.47 123.47 311.13 415.30 830.61 246.94 16.42 61.74 123.47 123.47 311.13 830.61 246.94 16.43 61.74 123.47 311.13 830.61 246.94 16.44 61.74 123.47 311.13 830.61 246.94 16.45 61.74 123.47 311.13 246.94 16.46 61.74 123.47 311.13 246.94 16.47 61.74 123.47 311.13 246.94 16.48 61.74 123.47 311.13 246.94 82.41 164.81 16.49 61.74 123.47 311.13 246.94 82.41 164.81 415.30 493.88 16.50 61.74 123.47 311.13 246.94 82.41 164.81 415.30 493.88 16.51 61.74 123.47 311.13 246.94 82.41 164.81 415.30 493.88 16.52 61.74 123.47 311.13 246.94 82.41 164.81 415.30 493.88 830.61 16.53 61.74 123.47 311.13 246.94 82.41 164.81 415.30 493.88 830.61 16.54 61.74 311.13 246.94 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.55 61.74 311.13 246.94 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.56 246.94 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.57 246.94 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.58 246.94 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.59 246.94 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.60 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.61 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.62 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.63 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.64 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.65 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.66 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.67 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.68 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.69 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.70 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.71 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.72 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.73 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.74 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.75 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.76 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.77 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.78 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.79 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.80 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.81 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.82 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.83 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.84 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.85 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.86 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.87 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.88 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.89 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.90 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.91 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.92 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.93 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.94 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.95 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.96 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.97 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.98 82.41 164.81 415.30 493.88 830.61 164.81 415.30 16.99 82.41 164.81 415.30 493.88 830.61 164.81 415.30 17.00 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.01 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.02 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.03 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.04 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.05 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.06 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.07 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.08 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.09 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.10 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.11 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.12 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.13 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.14 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.15 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.16 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.17 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.18 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.19 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.20 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.21 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.22 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.23 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.24 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.25 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.26 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.27 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.28 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.29 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.30 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.31 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.32 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.33 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.34 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.35 82.41 164.81 415.30 493.88 830.61 164.81 415.30 246.94 17.36 82.41 164.81 415.30 493.88 164.81 415.30 246.94 17.37 82.41 164.81 415.30 493.88 164.81 415.30 246.94 17.38 82.41 164.81 415.30 493.88 164.81 415.30 246.94 17.39 82.41 164.81 415.30 493.88 164.81 415.30 246.94 17.40 82.41 164.81 415.30 164.81 415.30 246.94 17.41 82.41 164.81 415.30 164.81 415.30 246.94 17.42 82.41 164.81 415.30 164.81 415.30 246.94 17.43 82.41 164.81 415.30 164.81 415.30 246.94 17.44 82.41 164.81 415.30 164.81 415.30 246.94 17.45 82.41 164.81 415.30 164.81 415.30 246.94 155.56 369.99 17.46 82.41 164.81 415.30 164.81 415.30 246.94 155.56 369.99 17.47 82.41 164.81 415.30 164.81 415.30 246.94 155.56 369.99 369.99 739.99 77.78 17.48 82.41 164.81 415.30 164.81 415.30 246.94 155.56 369.99 369.99 739.99 77.78 246.94 17.49 82.41 164.81 415.30 246.94 155.56 369.99 369.99 739.99 77.78 246.94 17.50 82.41 164.81 415.30 246.94 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.51 82.41 164.81 415.30 246.94 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.52 82.41 164.81 415.30 246.94 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.53 164.81 415.30 246.94 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.54 164.81 415.30 246.94 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.55 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.56 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.57 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.58 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.59 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.60 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.61 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.62 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.63 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.64 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.65 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.66 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.67 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.68 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.69 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.70 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.71 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.72 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.73 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.74 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.75 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.76 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.77 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.78 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.79 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.80 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.81 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.82 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.83 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.84 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.85 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.86 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.87 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.88 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.89 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.90 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.91 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.92 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.93 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.94 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.95 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.96 155.56 369.99 369.99 739.99 77.78 246.94 155.56 17.97 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 17.98 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 17.99 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.00 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.01 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.02 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.03 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.04 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.05 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.06 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.07 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.08 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.09 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.10 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.11 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.12 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.13 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.14 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.15 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.16 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.17 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.18 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.19 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.20 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.21 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.22 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.23 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.24 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.25 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.26 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.27 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.28 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.29 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.30 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.31 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.32 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.33 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.34 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.35 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.36 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.37 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 18.38 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 61.74 18.39 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 61.74 311.13 18.40 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 61.74 311.13 18.41 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 61.74 311.13 123.47 830.61 415.30 18.42 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 61.74 311.13 123.47 830.61 415.30 18.43 155.56 369.99 369.99 739.99 77.78 246.94 155.56 246.94 61.74 311.13 123.47 830.61 415.30 18.44 369.99 369.99 739.99 246.94 155.56 246.94 61.74 311.13 123.47 830.61 415.30 18.45 369.99 369.99 246.94 246.94 61.74 311.13 123.47 830.61 415.30 18.46 369.99 246.94 61.74 311.13 123.47 830.61 415.30 18.47 369.99 246.94 61.74 311.13 123.47 830.61 415.30 18.48 369.99 246.94 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.49 369.99 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.50 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.51 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.52 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.53 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.54 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.55 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.56 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.57 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.58 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.59 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.60 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.61 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.62 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.63 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.64 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.65 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.66 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.67 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.68 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.69 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.70 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.71 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.72 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.73 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.74 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.75 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.76 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.77 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.78 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.79 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.80 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.81 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.82 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.83 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.84 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.85 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.86 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.87 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.88 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.89 61.74 311.13 123.47 830.61 415.30 311.13 123.47 18.90 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.91 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.92 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.93 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.94 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.95 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.96 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.97 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.98 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 18.99 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.00 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.01 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.02 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.03 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.04 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.05 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.06 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.07 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.08 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.09 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.10 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.11 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.12 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.13 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.14 61.74 311.13 123.47 830.61 415.30 311.13 123.47 246.94 19.15 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.16 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.17 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.18 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.19 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.20 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.21 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.22 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.23 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.24 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.25 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.26 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.27 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.28 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.29 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.30 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.31 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.32 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.33 61.74 123.47 830.61 415.30 311.13 123.47 246.94 19.34 61.74 123.47 830.61 415.30 311.13 123.47 246.94 329.63 19.35 61.74 123.47 830.61 415.30 311.13 123.47 246.94 329.63 138.59 19.36 61.74 123.47 830.61 415.30 311.13 123.47 246.94 329.63 138.59 69.30 19.37 61.74 123.47 830.61 415.30 311.13 123.47 246.94 329.63 138.59 69.30 19.38 61.74 123.47 830.61 415.30 311.13 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.39 61.74 123.47 830.61 415.30 311.13 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.40 61.74 123.47 830.61 415.30 311.13 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.41 61.74 830.61 415.30 311.13 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.42 61.74 311.13 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.43 311.13 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.44 311.13 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.45 311.13 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.46 123.47 246.94 329.63 138.59 69.30 329.63 659.26 19.47 123.47 329.63 138.59 69.30 329.63 659.26 138.59 19.48 123.47 329.63 138.59 69.30 329.63 659.26 138.59 19.49 123.47 329.63 138.59 69.30 329.63 659.26 138.59 19.50 123.47 329.63 138.59 69.30 329.63 659.26 138.59 19.51 123.47 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.52 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.53 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.54 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.55 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.56 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.57 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.58 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.59 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.60 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.61 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.62 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.63 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.64 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.65 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.66 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.67 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.68 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.69 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.70 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.71 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.72 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.73 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.74 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.75 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.76 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.77 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.78 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.79 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.80 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.81 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.82 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.83 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.84 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.85 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.86 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.87 329.63 138.59 69.30 329.63 659.26 138.59 207.65 19.88 329.63 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.89 329.63 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.90 329.63 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.91 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.92 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.93 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.94 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.95 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.96 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.97 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.98 138.59 69.30 329.63 659.26 138.59 207.65 246.94 19.99 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.00 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.01 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.02 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.03 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.04 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.05 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.06 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.07 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.08 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.09 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.10 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.11 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.12 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.13 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.14 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.15 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.16 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.17 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.18 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.19 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.20 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.21 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.22 138.59 69.30 329.63 659.26 138.59 207.65 246.94 20.23 69.30 329.63 659.26 138.59 207.65 246.94 20.24 69.30 329.63 659.26 138.59 207.65 246.94 20.25 69.30 329.63 659.26 207.65 246.94 20.26 69.30 329.63 659.26 207.65 246.94 20.27 69.30 329.63 659.26 207.65 246.94 20.28 69.30 329.63 659.26 207.65 246.94 20.29 69.30 329.63 659.26 207.65 246.94 20.30 69.30 329.63 659.26 207.65 246.94 116.54 20.31 69.30 329.63 659.26 207.65 246.94 116.54 116.54 20.32 69.30 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 20.33 69.30 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 20.34 69.30 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 20.35 69.30 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 20.36 69.30 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 415.30 20.37 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 415.30 20.38 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.39 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.40 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.41 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.42 329.63 659.26 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.43 659.26 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.44 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.45 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.46 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.47 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.48 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.49 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.50 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.51 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.52 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.53 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.54 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.55 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.56 207.65 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.57 246.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.58 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.59 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.60 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.61 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.62 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.63 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.64 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.65 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.66 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.67 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.68 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.69 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.70 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.71 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.72 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.73 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.74 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.75 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.76 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.77 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.78 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.79 116.54 116.54 415.30 58.27 415.30 830.61 311.13 20.80 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.81 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.82 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.83 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.84 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.85 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.86 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.87 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.88 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.89 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.90 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.91 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.92 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.93 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.94 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.95 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.96 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.97 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.98 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 20.99 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.00 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.01 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.02 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.03 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.04 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.05 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.06 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.07 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.08 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.09 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.10 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.11 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.12 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.13 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.14 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.15 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.16 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.17 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.18 116.54 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.19 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.20 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.21 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.22 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.23 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.24 116.54 415.30 58.27 415.30 830.61 311.13 277.18 21.25 116.54 415.30 58.27 415.30 830.61 311.13 277.18 164.81 21.26 116.54 415.30 58.27 415.30 830.61 311.13 277.18 164.81 82.41 21.27 116.54 415.30 58.27 415.30 830.61 311.13 277.18 164.81 82.41 21.28 116.54 415.30 58.27 415.30 830.61 311.13 277.18 164.81 82.41 21.29 116.54 415.30 58.27 415.30 830.61 311.13 277.18 164.81 82.41 21.30 116.54 415.30 58.27 415.30 830.61 311.13 277.18 164.81 82.41 164.81 21.31 116.54 415.30 58.27 415.30 830.61 311.13 277.18 164.81 82.41 164.81 21.32 116.54 415.30 58.27 415.30 830.61 311.13 277.18 164.81 82.41 164.81 233.08 21.33 116.54 415.30 415.30 830.61 311.13 277.18 164.81 82.41 164.81 233.08 233.08 21.34 116.54 415.30 415.30 830.61 311.13 277.18 164.81 82.41 164.81 233.08 233.08 21.35 116.54 415.30 415.30 830.61 311.13 164.81 82.41 164.81 233.08 233.08 21.36 116.54 415.30 415.30 830.61 311.13 164.81 82.41 164.81 233.08 233.08 21.37 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.38 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.39 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.40 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.41 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.42 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.43 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.44 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.45 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.46 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.47 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.48 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.49 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.50 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.51 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.52 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.53 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.54 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.55 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.56 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.57 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.58 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.59 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.60 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.61 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.62 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.63 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.64 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.65 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.66 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.67 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.68 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.69 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.70 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.71 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.72 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.73 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.74 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.75 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.76 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 21.77 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 739.99 21.78 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 739.99 21.79 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 739.99 21.80 415.30 415.30 830.61 164.81 82.41 164.81 233.08 233.08 739.99 369.99 21.81 415.30 415.30 164.81 82.41 164.81 233.08 233.08 739.99 369.99 21.82 415.30 415.30 164.81 82.41 164.81 233.08 233.08 739.99 369.99 369.99 21.83 415.30 415.30 164.81 82.41 164.81 233.08 233.08 739.99 369.99 369.99 21.84 164.81 82.41 164.81 233.08 233.08 739.99 369.99 369.99 21.85 164.81 82.41 164.81 233.08 233.08 739.99 369.99 369.99 21.86 164.81 82.41 164.81 233.08 233.08 739.99 369.99 369.99 21.87 164.81 82.41 164.81 233.08 233.08 739.99 369.99 369.99 21.88 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.89 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.90 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.91 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.92 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.93 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.94 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.95 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.96 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.97 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.98 164.81 82.41 164.81 233.08 739.99 369.99 369.99 21.99 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.00 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.01 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.02 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.03 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.04 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.05 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.06 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.07 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.08 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.09 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.10 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.11 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.12 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.13 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.14 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.15 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.16 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.17 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.18 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.19 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.20 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.21 164.81 82.41 164.81 233.08 739.99 369.99 369.99 22.22 164.81 82.41 164.81 233.08 369.99 369.99 22.23 164.81 82.41 164.81 233.08 369.99 369.99 22.24 164.81 82.41 164.81 233.08 369.99 369.99 22.25 164.81 82.41 164.81 233.08 369.99 22.26 164.81 82.41 164.81 233.08 369.99 22.27 164.81 82.41 164.81 233.08 369.99 22.28 164.81 82.41 164.81 233.08 369.99 22.29 164.81 82.41 164.81 233.08 369.99 22.30 164.81 82.41 164.81 233.08 369.99 22.31 82.41 164.81 233.08 369.99 369.99 77.78 22.32 82.41 233.08 369.99 369.99 77.78 155.56 22.33 82.41 233.08 369.99 369.99 77.78 155.56 739.99 22.34 82.41 233.08 369.99 369.99 77.78 155.56 739.99 22.35 82.41 233.08 369.99 369.99 77.78 155.56 739.99 22.36 233.08 369.99 369.99 77.78 155.56 739.99 246.94 22.37 233.08 369.99 369.99 77.78 155.56 739.99 246.94 22.38 233.08 369.99 369.99 77.78 155.56 739.99 246.94 22.39 233.08 369.99 369.99 77.78 155.56 739.99 246.94 22.40 233.08 369.99 369.99 77.78 155.56 739.99 246.94 22.41 369.99 369.99 77.78 155.56 739.99 246.94 22.42 369.99 369.99 77.78 155.56 739.99 246.94 22.43 369.99 369.99 77.78 155.56 739.99 246.94 22.44 369.99 369.99 77.78 155.56 739.99 246.94 22.45 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.46 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.47 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.48 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.49 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.50 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.51 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.52 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.53 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.54 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.55 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.56 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.57 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.58 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.59 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.60 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.61 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.62 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.63 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.64 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.65 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.66 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.67 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.68 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.69 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.70 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.71 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.72 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.73 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.74 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.75 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.76 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.77 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.78 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.79 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.80 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.81 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.82 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.83 369.99 369.99 77.78 155.56 739.99 246.94 155.56 22.84 369.99 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.85 369.99 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.86 369.99 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.87 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.88 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.89 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.90 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.91 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.92 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.93 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.94 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.95 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.96 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.97 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.98 369.99 77.78 155.56 739.99 246.94 155.56 246.94 22.99 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.00 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.01 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.02 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.03 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.04 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.05 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.06 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.07 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.08 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.09 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.10 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.11 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.12 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.13 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.14 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.15 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.16 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.17 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.18 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.19 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.20 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.21 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.22 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.23 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.24 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.25 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.26 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.27 369.99 77.78 155.56 739.99 246.94 155.56 246.94 23.28 369.99 77.78 155.56 739.99 246.94 155.56 246.94 61.74 23.29 369.99 77.78 155.56 739.99 246.94 155.56 246.94 61.74 23.30 369.99 77.78 155.56 739.99 246.94 155.56 246.94 61.74 23.31 369.99 77.78 739.99 246.94 155.56 246.94 61.74 23.32 369.99 77.78 739.99 246.94 155.56 246.94 61.74 123.47 23.33 369.99 739.99 246.94 155.56 246.94 61.74 123.47 123.47 311.13 311.13 23.34 369.99 739.99 246.94 246.94 61.74 123.47 123.47 311.13 311.13 23.35 369.99 739.99 246.94 246.94 61.74 123.47 123.47 311.13 311.13 23.36 739.99 246.94 246.94 61.74 123.47 123.47 311.13 311.13 23.37 739.99 246.94 246.94 61.74 123.47 123.47 311.13 311.13 23.38 739.99 246.94 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.39 739.99 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.40 739.99 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.41 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.42 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.43 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.44 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.45 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.46 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.47 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.48 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.49 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.50 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.51 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.52 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.53 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.54 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.55 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.56 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.57 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.58 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.59 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.60 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.61 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.62 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.63 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.64 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.65 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.66 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.67 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.68 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.69 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.70 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.71 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.72 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.73 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.74 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.75 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.76 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.77 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.78 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.79 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.80 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.81 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.82 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.83 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.84 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.85 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.86 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.87 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.88 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.89 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.90 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.91 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.92 246.94 61.74 123.47 123.47 311.13 311.13 622.25 23.93 246.94 61.74 123.47 123.47 311.13 311.13 622.25 246.94 23.94 246.94 61.74 123.47 123.47 311.13 311.13 622.25 246.94 23.95 246.94 61.74 123.47 123.47 311.13 311.13 622.25 246.94 23.96 246.94 61.74 123.47 123.47 311.13 622.25 246.94 23.97 246.94 61.74 123.47 123.47 311.13 622.25 246.94 23.98 246.94 61.74 123.47 123.47 311.13 622.25 246.94 23.99 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.00 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.01 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.02 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.03 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.04 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.05 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.06 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.07 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.08 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.09 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.10 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.11 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.12 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.13 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.14 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.15 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.16 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.17 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.18 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.19 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.20 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.21 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.22 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.23 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.24 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.25 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.26 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.27 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.28 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.29 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.30 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.31 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.32 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.33 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.34 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.35 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.36 246.94 61.74 123.47 123.47 311.13 622.25 246.94 24.37 246.94 61.74 123.47 123.47 311.13 622.25 246.94 103.83 24.38 246.94 61.74 123.47 123.47 311.13 622.25 246.94 103.83 24.39 246.94 61.74 123.47 123.47 311.13 622.25 246.94 103.83 659.26 329.63 24.40 246.94 61.74 123.47 123.47 311.13 622.25 246.94 103.83 659.26 329.63 51.91 24.41 246.94 61.74 123.47 123.47 311.13 246.94 103.83 659.26 329.63 51.91 103.83 24.42 246.94 61.74 123.47 123.47 311.13 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.43 246.94 61.74 123.47 311.13 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.44 246.94 123.47 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.45 246.94 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.46 246.94 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.47 246.94 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.48 246.94 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.49 246.94 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.50 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.51 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.52 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.53 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.54 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.55 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.56 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.57 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.58 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.59 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.60 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.61 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.62 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.63 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.64 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.65 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.66 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.67 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.68 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.69 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.70 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.71 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.72 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.73 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.74 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.75 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.76 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.77 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.78 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.79 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.80 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.81 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.82 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.83 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.84 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.85 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.86 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.87 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.88 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.89 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.90 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.91 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.92 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.93 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.94 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.95 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.96 246.94 103.83 659.26 329.63 51.91 103.83 329.63 24.97 103.83 659.26 329.63 51.91 103.83 329.63 24.98 103.83 659.26 329.63 51.91 103.83 329.63 24.99 103.83 659.26 329.63 51.91 103.83 329.63 246.94 25.00 103.83 659.26 51.91 103.83 329.63 246.94 25.01 103.83 659.26 51.91 103.83 329.63 246.94 25.02 103.83 659.26 51.91 103.83 329.63 246.94 25.03 103.83 659.26 51.91 103.83 329.63 246.94 25.04 103.83 659.26 51.91 103.83 329.63 246.94 25.05 103.83 659.26 51.91 103.83 329.63 246.94 25.06 103.83 659.26 51.91 103.83 329.63 246.94 25.07 103.83 659.26 51.91 103.83 329.63 246.94 25.08 103.83 659.26 51.91 103.83 329.63 246.94 25.09 103.83 659.26 51.91 103.83 329.63 246.94 25.10 103.83 659.26 51.91 103.83 329.63 246.94 25.11 103.83 659.26 51.91 103.83 329.63 246.94 25.12 103.83 659.26 51.91 103.83 329.63 246.94 25.13 103.83 659.26 51.91 103.83 329.63 246.94 25.14 103.83 659.26 51.91 103.83 329.63 246.94 25.15 103.83 659.26 51.91 103.83 329.63 246.94 25.16 103.83 659.26 51.91 103.83 329.63 246.94 25.17 103.83 659.26 51.91 103.83 329.63 246.94 25.18 103.83 659.26 51.91 103.83 329.63 246.94 25.19 103.83 659.26 51.91 103.83 329.63 246.94 25.20 103.83 659.26 51.91 103.83 329.63 246.94 25.21 103.83 659.26 51.91 103.83 329.63 246.94 25.22 103.83 659.26 51.91 103.83 329.63 246.94 25.23 103.83 659.26 51.91 103.83 329.63 246.94 25.24 103.83 659.26 51.91 103.83 329.63 246.94 25.25 103.83 659.26 51.91 103.83 329.63 246.94 25.26 103.83 659.26 51.91 103.83 329.63 246.94 25.27 103.83 659.26 51.91 103.83 329.63 246.94 25.28 103.83 659.26 51.91 103.83 329.63 246.94 25.29 103.83 659.26 51.91 103.83 329.63 246.94 25.30 103.83 659.26 51.91 103.83 329.63 246.94 25.31 103.83 659.26 51.91 103.83 329.63 246.94 25.32 103.83 659.26 51.91 103.83 329.63 246.94 25.33 103.83 659.26 51.91 103.83 329.63 246.94 25.34 103.83 659.26 51.91 103.83 329.63 246.94 25.35 103.83 659.26 51.91 103.83 329.63 246.94 25.36 103.83 659.26 51.91 103.83 329.63 246.94 25.37 103.83 659.26 51.91 103.83 329.63 246.94 25.38 103.83 659.26 51.91 103.83 329.63 246.94 25.39 103.83 659.26 51.91 103.83 329.63 246.94 25.40 103.83 659.26 51.91 103.83 329.63 246.94 25.41 103.83 51.91 103.83 329.63 246.94 25.42 103.83 51.91 103.83 329.63 246.94 554.37 277.18 25.43 103.83 51.91 103.83 329.63 246.94 554.37 277.18 25.44 103.83 51.91 103.83 329.63 246.94 554.37 277.18 25.45 103.83 51.91 103.83 329.63 246.94 554.37 277.18 25.46 51.91 103.83 329.63 246.94 554.37 277.18 25.47 51.91 103.83 329.63 246.94 554.37 277.18 116.54 329.63 25.48 51.91 103.83 246.94 554.37 277.18 116.54 329.63 25.49 51.91 103.83 246.94 554.37 277.18 116.54 329.63 58.27 116.54 25.50 51.91 103.83 246.94 554.37 277.18 116.54 329.63 58.27 116.54 25.51 51.91 246.94 554.37 277.18 116.54 329.63 58.27 116.54 25.52 246.94 554.37 277.18 116.54 329.63 58.27 116.54 25.53 246.94 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.54 246.94 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.55 246.94 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.56 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.57 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.58 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.59 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.60 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.61 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.62 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.63 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.64 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.65 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.66 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.67 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.68 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.69 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.70 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.71 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.72 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.73 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.74 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.75 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.76 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.77 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.78 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.79 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.80 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.81 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.82 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.83 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.84 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.85 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.86 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.87 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.88 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.89 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.90 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.91 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.92 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.93 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.94 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.95 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.96 554.37 277.18 116.54 329.63 58.27 116.54 277.18 25.97 554.37 277.18 116.54 329.63 58.27 116.54 277.18 164.81 25.98 554.37 277.18 116.54 329.63 58.27 116.54 277.18 164.81 25.99 554.37 277.18 116.54 329.63 58.27 116.54 277.18 164.81 26.00 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.01 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.02 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.03 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.04 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.05 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.06 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.07 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.08 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.09 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.10 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.11 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.12 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.13 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.14 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.15 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.16 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.17 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.18 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.19 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.20 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.21 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.22 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.23 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.24 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.25 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.26 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.27 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.28 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.29 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.30 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.31 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.32 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.33 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.34 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.35 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.36 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.37 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.38 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.39 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.40 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.41 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.42 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.43 554.37 116.54 329.63 58.27 116.54 277.18 164.81 26.44 554.37 116.54 329.63 58.27 116.54 277.18 164.81 659.26 26.45 554.37 116.54 329.63 58.27 116.54 277.18 164.81 659.26 103.83 26.46 116.54 329.63 58.27 116.54 277.18 164.81 659.26 103.83 51.91 103.83 246.94 329.63 26.47 116.54 329.63 58.27 116.54 277.18 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.48 116.54 329.63 58.27 116.54 277.18 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.49 116.54 329.63 58.27 116.54 277.18 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.50 116.54 329.63 58.27 116.54 277.18 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.51 329.63 116.54 277.18 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.52 329.63 116.54 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.53 329.63 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.54 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.55 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.56 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.57 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.58 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.59 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.60 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.61 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.62 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.63 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.64 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.65 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.66 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.67 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.68 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.69 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.70 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.71 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.72 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.73 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.74 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.75 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.76 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.77 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.78 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.79 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.80 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.81 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.82 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.83 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.84 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.85 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.86 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.87 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.88 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.89 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.90 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.91 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.92 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.93 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.94 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.95 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.96 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.97 659.26 103.83 51.91 103.83 246.94 329.63 329.63 26.98 659.26 103.83 51.91 103.83 246.94 329.63 329.63 246.94 26.99 659.26 103.83 51.91 103.83 246.94 329.63 329.63 246.94 27.00 659.26 103.83 51.91 103.83 246.94 329.63 329.63 246.94 27.01 659.26 103.83 51.91 103.83 246.94 329.63 329.63 246.94 27.02 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.03 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.04 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.05 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.06 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.07 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.08 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.09 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.10 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.11 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.12 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.13 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.14 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.15 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.16 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.17 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.18 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.19 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.20 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.21 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.22 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.23 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.24 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.25 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.26 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.27 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.28 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.29 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.30 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.31 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.32 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.33 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.34 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.35 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.36 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.37 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.38 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.39 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.40 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.41 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.42 659.26 103.83 51.91 103.83 246.94 329.63 246.94 27.43 659.26 103.83 51.91 103.83 246.94 329.63 246.94 49.00 27.44 659.26 103.83 51.91 103.83 329.63 246.94 49.00 98.00 27.45 659.26 103.83 51.91 103.83 329.63 246.94 49.00 98.00 27.46 659.26 103.83 103.83 329.63 246.94 49.00 98.00 98.00 27.47 659.26 103.83 103.83 329.63 246.94 49.00 98.00 98.00 233.08 27.48 659.26 103.83 103.83 329.63 246.94 49.00 98.00 98.00 233.08 27.49 659.26 329.63 246.94 49.00 98.00 98.00 233.08 27.50 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.51 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.52 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.53 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.54 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.55 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.56 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.57 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.58 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.59 659.26 329.63 246.94 49.00 98.00 98.00 233.08 233.08 27.60 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.61 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.62 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.63 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.64 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.65 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.66 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.67 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.68 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.69 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.70 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.71 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.72 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.73 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.74 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.75 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.76 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.77 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.78 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.79 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.80 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.81 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.82 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.83 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.84 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.85 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.86 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.87 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.88 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.89 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.90 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.91 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.92 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.93 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.94 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.95 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.96 659.26 329.63 49.00 98.00 98.00 233.08 233.08 27.97 659.26 329.63 49.00 98.00 98.00 233.08 233.08 466.16 27.98 659.26 329.63 49.00 98.00 98.00 233.08 233.08 466.16 27.99 659.26 329.63 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.00 659.26 329.63 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.01 329.63 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.02 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.03 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.04 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.05 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.06 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.07 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.08 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.09 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.10 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.11 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.12 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.13 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.14 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.15 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.16 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.17 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.18 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.19 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.20 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.21 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.22 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.23 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.24 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.25 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.26 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.27 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.28 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.29 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.30 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.31 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.32 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.33 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.34 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.35 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.36 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.37 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.38 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.39 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.40 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.41 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.42 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.43 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.44 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.45 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.46 49.00 98.00 98.00 233.08 466.16 622.25 311.13 28.47 49.00 98.00 98.00 233.08 466.16 311.13 28.48 49.00 98.00 98.00 233.08 466.16 311.13 28.49 49.00 98.00 98.00 466.16 28.50 49.00 98.00 98.00 466.16 51.91 28.51 49.00 98.00 98.00 466.16 51.91 28.52 49.00 98.00 98.00 466.16 51.91 28.53 49.00 98.00 98.00 466.16 51.91 246.94 103.83 493.88 28.54 49.00 98.00 98.00 466.16 51.91 246.94 103.83 493.88 28.55 49.00 98.00 98.00 466.16 51.91 246.94 103.83 493.88 103.83 622.25 28.56 49.00 98.00 98.00 466.16 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.57 49.00 98.00 98.00 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.58 98.00 98.00 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.59 98.00 98.00 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.60 98.00 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.61 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.62 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.63 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.64 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.65 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.66 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.67 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.68 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.69 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.70 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.71 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.72 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.73 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.74 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.75 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.76 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.77 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.78 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.79 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.80 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.81 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.82 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.83 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.84 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.85 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.86 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.87 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.88 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.89 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.90 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.91 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.92 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.93 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.94 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.95 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.96 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.97 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.98 51.91 246.94 103.83 493.88 103.83 622.25 311.13 28.99 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.00 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.01 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.02 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.03 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.04 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.05 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.06 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.07 51.91 246.94 103.83 493.88 103.83 622.25 311.13 29.08 51.91 246.94 103.83 103.83 622.25 311.13 246.94 29.09 51.91 246.94 103.83 103.83 622.25 311.13 246.94 29.10 51.91 246.94 103.83 103.83 622.25 311.13 246.94 29.11 51.91 246.94 103.83 622.25 311.13 246.94 29.12 51.91 246.94 103.83 622.25 311.13 246.94 29.13 51.91 246.94 103.83 622.25 311.13 246.94 29.14 51.91 246.94 103.83 622.25 311.13 246.94 29.15 51.91 246.94 103.83 622.25 311.13 246.94 29.16 51.91 246.94 103.83 622.25 311.13 246.94 29.17 51.91 246.94 103.83 622.25 311.13 246.94 29.18 51.91 246.94 103.83 622.25 311.13 246.94 29.19 51.91 246.94 103.83 622.25 311.13 246.94 29.20 51.91 246.94 103.83 622.25 311.13 246.94 29.21 51.91 246.94 103.83 622.25 311.13 246.94 29.22 51.91 246.94 103.83 622.25 311.13 246.94 29.23 51.91 246.94 103.83 622.25 311.13 246.94 29.24 51.91 246.94 103.83 622.25 311.13 246.94 29.25 51.91 246.94 103.83 622.25 311.13 246.94 29.26 51.91 246.94 103.83 622.25 311.13 246.94 29.27 51.91 246.94 103.83 622.25 311.13 246.94 29.28 51.91 246.94 103.83 622.25 311.13 246.94 29.29 51.91 246.94 103.83 622.25 311.13 246.94 29.30 51.91 246.94 103.83 622.25 311.13 246.94 29.31 51.91 246.94 103.83 622.25 311.13 246.94 29.32 51.91 246.94 103.83 622.25 311.13 246.94 29.33 51.91 246.94 103.83 622.25 311.13 246.94 29.34 51.91 246.94 103.83 622.25 311.13 246.94 29.35 51.91 246.94 103.83 622.25 311.13 246.94 29.36 51.91 246.94 103.83 622.25 311.13 246.94 29.37 51.91 246.94 103.83 622.25 311.13 246.94 29.38 51.91 246.94 103.83 622.25 311.13 246.94 29.39 51.91 246.94 103.83 622.25 311.13 246.94 29.40 51.91 246.94 103.83 622.25 311.13 246.94 29.41 51.91 246.94 103.83 622.25 311.13 246.94 29.42 51.91 246.94 103.83 622.25 311.13 246.94 29.43 51.91 246.94 103.83 622.25 311.13 246.94 29.44 51.91 246.94 103.83 622.25 311.13 246.94 29.45 51.91 246.94 103.83 622.25 311.13 246.94 29.46 51.91 246.94 103.83 622.25 311.13 246.94 29.47 246.94 622.25 311.13 246.94 29.48 246.94 622.25 311.13 246.94 29.49 246.94 622.25 311.13 246.94 29.50 246.94 622.25 311.13 246.94 29.51 246.94 622.25 311.13 246.94 29.52 246.94 622.25 311.13 246.94 29.53 246.94 622.25 311.13 246.94 29.54 622.25 311.13 246.94 29.55 622.25 311.13 246.94 29.56 622.25 311.13 246.94 185.00 440.00 29.57 622.25 311.13 246.94 185.00 440.00 92.50 29.58 622.25 311.13 246.94 185.00 440.00 92.50 185.00 29.59 622.25 311.13 246.94 185.00 440.00 92.50 185.00 29.60 622.25 311.13 246.94 185.00 440.00 92.50 185.00 29.61 622.25 311.13 246.94 185.00 440.00 92.50 185.00 220.00 29.62 622.25 311.13 246.94 185.00 440.00 92.50 185.00 220.00 29.63 622.25 311.13 246.94 185.00 440.00 92.50 185.00 220.00 29.64 622.25 311.13 246.94 185.00 440.00 92.50 185.00 220.00 29.65 246.94 185.00 440.00 92.50 185.00 220.00 29.66 185.00 440.00 92.50 185.00 220.00 29.67 185.00 440.00 92.50 185.00 220.00 29.68 185.00 440.00 92.50 185.00 220.00 29.69 185.00 440.00 92.50 185.00 220.00 29.70 185.00 440.00 92.50 185.00 220.00 29.71 185.00 440.00 92.50 185.00 220.00 29.72 185.00 440.00 92.50 185.00 220.00 29.73 185.00 440.00 92.50 185.00 220.00 29.74 185.00 440.00 92.50 185.00 220.00 523.25 29.75 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.76 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.77 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.78 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.79 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.80 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.81 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.82 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.83 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.84 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.85 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.86 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.87 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.88 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.89 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.90 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.91 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.92 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.93 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.94 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.95 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.96 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.97 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.98 185.00 440.00 92.50 185.00 220.00 523.25 311.13 29.99 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.00 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.01 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.02 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.03 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.04 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.05 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.06 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.07 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.08 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.09 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.10 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.11 185.00 440.00 92.50 185.00 220.00 523.25 311.13 30.12 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.13 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.14 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.15 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.16 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.17 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.18 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.19 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.20 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.21 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.22 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.23 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.24 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.25 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.26 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.27 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.28 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.29 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.30 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.31 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.32 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.33 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.34 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.35 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.36 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.37 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.38 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.39 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.40 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.41 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.42 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.43 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.44 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.45 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.46 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.47 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.48 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.49 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.50 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.51 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.52 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.53 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.54 185.00 92.50 185.00 220.00 523.25 311.13 220.00 30.55 185.00 92.50 185.00 220.00 523.25 311.13 220.00 82.41 30.56 185.00 92.50 185.00 220.00 523.25 311.13 220.00 82.41 164.81 164.81 30.57 185.00 92.50 185.00 220.00 523.25 311.13 220.00 82.41 164.81 164.81 30.58 185.00 92.50 185.00 220.00 523.25 311.13 220.00 82.41 164.81 164.81 30.59 185.00 92.50 185.00 220.00 523.25 311.13 220.00 82.41 164.81 164.81 30.60 92.50 185.00 220.00 523.25 311.13 220.00 82.41 164.81 164.81 30.61 185.00 220.00 523.25 311.13 220.00 82.41 164.81 164.81 30.62 185.00 220.00 523.25 311.13 220.00 82.41 164.81 164.81 30.63 220.00 523.25 311.13 220.00 82.41 164.81 164.81 30.64 220.00 523.25 311.13 220.00 82.41 164.81 164.81 554.37 30.65 220.00 523.25 311.13 220.00 82.41 164.81 164.81 554.37 415.30 30.66 220.00 523.25 311.13 220.00 82.41 164.81 164.81 554.37 415.30 277.18 30.67 220.00 523.25 311.13 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.68 220.00 523.25 311.13 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.69 220.00 523.25 311.13 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.70 220.00 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.71 220.00 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.72 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.73 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.74 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.75 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.76 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.77 220.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.78 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.79 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.80 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.81 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.82 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.83 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.84 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.85 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.86 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.87 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.88 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.89 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.90 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.91 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.92 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.93 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.94 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.95 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.96 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.97 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.98 82.41 164.81 164.81 554.37 415.30 277.18 207.65 30.99 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.00 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.01 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.02 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.03 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.04 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.05 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.06 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.07 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.08 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.09 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.10 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.11 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.12 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.13 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.14 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.15 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.16 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.17 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.18 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.19 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.20 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.21 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.22 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.23 82.41 164.81 164.81 554.37 415.30 277.18 207.65 31.24 82.41 164.81 164.81 554.37 415.30 277.18 207.65 207.65 31.25 82.41 164.81 164.81 554.37 415.30 277.18 207.65 207.65 31.26 82.41 164.81 164.81 554.37 415.30 277.18 207.65 207.65 31.27 82.41 164.81 164.81 554.37 415.30 277.18 207.65 207.65 31.28 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.29 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.30 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.31 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.32 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.33 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.34 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.35 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.36 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.37 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.38 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.39 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.40 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.41 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.42 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.43 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.44 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.45 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.46 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.47 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.48 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.49 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.50 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.51 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.52 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.53 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.54 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.55 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.56 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.57 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.58 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.59 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.60 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.61 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.62 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.63 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.64 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.65 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.66 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.67 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.68 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.69 82.41 164.81 164.81 554.37 277.18 207.65 207.65 31.70 82.41 164.81 164.81 554.37 277.18 207.65 207.65 369.99 31.71 82.41 164.81 164.81 554.37 277.18 207.65 207.65 369.99 31.72 82.41 164.81 164.81 554.37 277.18 207.65 207.65 369.99 155.56 220.00 31.73 82.41 164.81 164.81 554.37 277.18 207.65 207.65 369.99 155.56 220.00 31.74 82.41 164.81 164.81 554.37 277.18 207.65 207.65 369.99 155.56 220.00 31.75 82.41 164.81 164.81 554.37 277.18 207.65 369.99 155.56 220.00 155.56 31.76 82.41 164.81 164.81 554.37 277.18 207.65 369.99 155.56 220.00 155.56 77.78 31.77 82.41 164.81 164.81 277.18 207.65 369.99 155.56 220.00 155.56 77.78 31.78 82.41 164.81 277.18 207.65 369.99 155.56 220.00 155.56 77.78 31.79 164.81 277.18 207.65 369.99 155.56 220.00 155.56 77.78 31.80 277.18 207.65 369.99 155.56 220.00 155.56 77.78 31.81 277.18 207.65 369.99 155.56 220.00 155.56 77.78 369.99 31.82 277.18 207.65 369.99 155.56 220.00 155.56 77.78 369.99 31.83 277.18 207.65 369.99 155.56 220.00 155.56 77.78 369.99 31.84 277.18 207.65 369.99 155.56 220.00 155.56 77.78 369.99 31.85 277.18 207.65 369.99 155.56 220.00 155.56 77.78 369.99 31.86 277.18 207.65 369.99 155.56 220.00 155.56 77.78 369.99 31.87 277.18 207.65 369.99 155.56 220.00 155.56 77.78 369.99 31.88 277.18 207.65 369.99 155.56 220.00 155.56 77.78 369.99 31.89 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.90 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.91 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.92 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.93 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.94 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.95 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.96 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.97 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.98 277.18 369.99 155.56 220.00 155.56 77.78 369.99 31.99 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.00 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.01 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.02 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.03 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.04 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.05 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.06 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.07 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.08 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.09 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.10 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.11 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.12 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.13 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.14 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.15 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.16 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.17 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.18 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.19 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.20 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.21 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.22 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.23 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.24 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.25 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.26 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.27 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.28 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.29 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.30 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.31 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.32 277.18 369.99 155.56 220.00 155.56 77.78 369.99 32.33 277.18 369.99 155.56 220.00 155.56 77.78 369.99 185.00 32.34 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.35 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.36 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.37 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.38 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.39 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.40 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.41 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.42 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.43 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.44 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.45 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.46 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.47 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.48 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.49 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.50 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.51 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.52 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.53 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.54 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.55 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.56 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.57 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.58 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.59 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.60 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.61 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.62 277.18 155.56 220.00 155.56 77.78 369.99 185.00 32.63 277.18 155.56 220.00 155.56 77.78 369.99 32.64 277.18 155.56 220.00 155.56 77.78 369.99 32.65 277.18 155.56 220.00 155.56 77.78 369.99 32.66 277.18 155.56 220.00 155.56 77.78 369.99 32.67 277.18 155.56 220.00 155.56 77.78 369.99 32.68 277.18 155.56 220.00 155.56 77.78 369.99 32.69 277.18 155.56 220.00 155.56 77.78 369.99 32.70 277.18 155.56 220.00 155.56 77.78 369.99 32.71 277.18 155.56 220.00 155.56 77.78 369.99 32.72 277.18 155.56 220.00 155.56 77.78 369.99 32.73 277.18 155.56 220.00 155.56 77.78 369.99 32.74 277.18 155.56 220.00 155.56 77.78 369.99 138.59 32.75 277.18 155.56 220.00 155.56 77.78 369.99 138.59 329.63 32.76 277.18 155.56 220.00 155.56 77.78 369.99 138.59 329.63 32.77 277.18 155.56 220.00 155.56 77.78 369.99 138.59 329.63 32.78 277.18 155.56 220.00 155.56 77.78 369.99 138.59 329.63 440.00 164.81 32.79 277.18 155.56 220.00 155.56 77.78 369.99 138.59 329.63 440.00 164.81 32.80 155.56 220.00 155.56 77.78 369.99 138.59 329.63 440.00 164.81 32.81 220.00 155.56 77.78 369.99 138.59 329.63 440.00 164.81 440.00 32.82 220.00 155.56 77.78 369.99 138.59 329.63 440.00 164.81 440.00 69.30 32.83 220.00 155.56 77.78 369.99 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.84 155.56 77.78 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.85 155.56 77.78 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.86 155.56 77.78 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.87 155.56 77.78 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.88 155.56 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.89 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.90 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.91 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.92 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.93 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.94 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.95 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.96 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.97 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.98 138.59 329.63 440.00 164.81 440.00 69.30 138.59 32.99 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.00 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.01 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.02 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.03 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.04 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.05 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.06 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.07 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.08 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.09 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.10 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.11 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.12 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.13 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.14 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.15 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.16 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.17 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.18 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.19 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.20 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.21 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.22 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.23 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.24 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.25 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.26 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.27 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.28 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.29 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.30 138.59 329.63 440.00 164.81 440.00 69.30 138.59 33.31 138.59 329.63 440.00 164.81 440.00 69.30 138.59 329.63 33.32 138.59 329.63 440.00 164.81 440.00 69.30 138.59 329.63 33.33 138.59 329.63 440.00 164.81 440.00 69.30 138.59 329.63 33.34 138.59 329.63 440.00 164.81 440.00 69.30 138.59 329.63 33.35 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.36 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.37 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.38 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.39 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.40 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.41 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.42 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.43 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.44 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.45 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.46 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.47 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.48 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.49 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.50 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.51 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.52 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.53 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.54 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.55 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.56 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.57 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.58 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.59 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.60 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.61 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.62 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.63 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.64 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.65 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.66 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.67 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.68 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.69 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.70 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.71 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.72 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.73 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.74 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.75 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.76 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.77 138.59 329.63 164.81 440.00 69.30 138.59 329.63 33.78 138.59 329.63 164.81 440.00 69.30 138.59 329.63 130.81 33.79 138.59 329.63 164.81 440.00 69.30 138.59 329.63 130.81 33.80 138.59 329.63 164.81 440.00 69.30 138.59 329.63 130.81 65.41 33.81 138.59 329.63 164.81 440.00 69.30 138.59 329.63 130.81 65.41 130.81 33.82 138.59 329.63 164.81 440.00 69.30 138.59 329.63 130.81 65.41 130.81 311.13 33.83 138.59 329.63 164.81 440.00 138.59 329.63 130.81 65.41 130.81 311.13 311.13 33.84 138.59 329.63 164.81 440.00 138.59 329.63 130.81 65.41 130.81 311.13 311.13 33.85 329.63 164.81 440.00 138.59 329.63 130.81 65.41 130.81 311.13 311.13 33.86 164.81 440.00 138.59 329.63 130.81 65.41 130.81 311.13 311.13 33.87 164.81 440.00 138.59 329.63 130.81 65.41 130.81 311.13 311.13 33.88 164.81 440.00 329.63 130.81 65.41 130.81 311.13 311.13 33.89 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.90 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.91 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.92 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.93 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.94 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.95 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.96 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.97 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.98 164.81 440.00 130.81 65.41 130.81 311.13 311.13 33.99 164.81 440.00 130.81 65.41 130.81 311.13 311.13 34.00 440.00 130.81 65.41 130.81 311.13 311.13 34.01 440.00 130.81 65.41 130.81 311.13 311.13 34.02 440.00 130.81 65.41 130.81 311.13 311.13 34.03 440.00 130.81 65.41 130.81 311.13 311.13 34.04 440.00 130.81 65.41 130.81 311.13 311.13 34.05 440.00 130.81 65.41 130.81 311.13 311.13 34.06 440.00 130.81 65.41 130.81 311.13 311.13 34.07 440.00 130.81 65.41 130.81 311.13 311.13 34.08 440.00 130.81 65.41 130.81 311.13 311.13 34.09 440.00 130.81 65.41 130.81 311.13 311.13 34.10 440.00 130.81 65.41 130.81 311.13 311.13 34.11 440.00 130.81 65.41 130.81 311.13 311.13 34.12 440.00 130.81 65.41 130.81 311.13 311.13 34.13 440.00 130.81 65.41 130.81 311.13 311.13 34.14 440.00 130.81 65.41 130.81 311.13 311.13 34.15 440.00 130.81 65.41 130.81 311.13 311.13 34.16 440.00 130.81 65.41 130.81 311.13 311.13 34.17 440.00 130.81 65.41 130.81 311.13 311.13 34.18 440.00 130.81 65.41 130.81 311.13 311.13 34.19 440.00 130.81 65.41 130.81 311.13 311.13 34.20 440.00 130.81 65.41 130.81 311.13 311.13 34.21 440.00 130.81 65.41 130.81 311.13 311.13 34.22 440.00 130.81 65.41 130.81 311.13 311.13 34.23 440.00 130.81 65.41 130.81 311.13 311.13 34.24 440.00 130.81 65.41 130.81 311.13 311.13 34.25 440.00 130.81 65.41 130.81 311.13 311.13 34.26 440.00 130.81 65.41 130.81 311.13 311.13 34.27 440.00 130.81 65.41 130.81 311.13 311.13 34.28 440.00 130.81 65.41 130.81 311.13 311.13 34.29 440.00 130.81 65.41 130.81 311.13 311.13 34.30 440.00 130.81 65.41 130.81 311.13 311.13 207.65 34.31 440.00 130.81 65.41 130.81 311.13 311.13 207.65 34.32 440.00 130.81 65.41 130.81 311.13 311.13 207.65 415.30 34.33 440.00 130.81 65.41 130.81 311.13 311.13 207.65 415.30 34.34 440.00 130.81 65.41 130.81 311.13 311.13 207.65 415.30 34.35 440.00 130.81 65.41 130.81 311.13 311.13 207.65 415.30 34.36 130.81 65.41 130.81 311.13 311.13 207.65 415.30 34.37 130.81 65.41 130.81 311.13 311.13 207.65 415.30 34.38 130.81 65.41 130.81 311.13 207.65 415.30 34.39 130.81 65.41 130.81 311.13 207.65 415.30 34.40 130.81 65.41 130.81 311.13 207.65 415.30 34.41 130.81 65.41 130.81 311.13 207.65 415.30 34.42 130.81 65.41 130.81 311.13 207.65 415.30 34.43 130.81 65.41 130.81 311.13 207.65 415.30 34.44 130.81 65.41 130.81 311.13 207.65 415.30 34.45 130.81 65.41 130.81 311.13 207.65 415.30 34.46 130.81 65.41 130.81 311.13 207.65 415.30 34.47 130.81 65.41 130.81 311.13 207.65 415.30 34.48 130.81 65.41 130.81 311.13 207.65 415.30 34.49 130.81 65.41 130.81 311.13 207.65 415.30 34.50 130.81 65.41 130.81 311.13 207.65 415.30 34.51 130.81 65.41 130.81 311.13 207.65 415.30 34.52 130.81 65.41 130.81 311.13 207.65 415.30 34.53 130.81 65.41 130.81 311.13 207.65 415.30 34.54 130.81 65.41 130.81 311.13 207.65 415.30 34.55 130.81 65.41 130.81 311.13 207.65 415.30 34.56 130.81 65.41 130.81 311.13 207.65 415.30 34.57 130.81 65.41 130.81 311.13 207.65 415.30 34.58 130.81 65.41 130.81 311.13 207.65 415.30 34.59 130.81 65.41 130.81 311.13 207.65 415.30 34.60 130.81 65.41 130.81 311.13 207.65 415.30 34.61 130.81 65.41 130.81 311.13 207.65 415.30 34.62 130.81 65.41 130.81 311.13 207.65 415.30 34.63 130.81 65.41 130.81 311.13 207.65 415.30 34.64 130.81 65.41 130.81 311.13 207.65 415.30 34.65 130.81 65.41 130.81 311.13 207.65 415.30 34.66 130.81 65.41 130.81 311.13 207.65 415.30 34.67 130.81 65.41 130.81 311.13 207.65 415.30 34.68 130.81 65.41 130.81 311.13 207.65 415.30 34.69 130.81 65.41 130.81 311.13 207.65 415.30 34.70 130.81 65.41 130.81 311.13 207.65 415.30 34.71 130.81 65.41 130.81 311.13 207.65 415.30 34.72 130.81 65.41 130.81 311.13 207.65 415.30 34.73 130.81 65.41 130.81 311.13 207.65 415.30 34.74 130.81 65.41 130.81 311.13 207.65 415.30 34.75 130.81 65.41 130.81 311.13 207.65 415.30 34.76 130.81 65.41 130.81 311.13 207.65 415.30 34.77 130.81 65.41 130.81 311.13 207.65 415.30 34.78 130.81 65.41 130.81 311.13 207.65 415.30 34.79 130.81 65.41 130.81 311.13 207.65 415.30 34.80 130.81 65.41 130.81 311.13 207.65 415.30 34.81 130.81 65.41 130.81 311.13 207.65 415.30 34.82 130.81 65.41 130.81 311.13 207.65 415.30 34.83 130.81 65.41 130.81 311.13 207.65 34.84 130.81 65.41 130.81 311.13 207.65 34.85 130.81 65.41 130.81 311.13 207.65 34.86 130.81 65.41 130.81 311.13 207.65 34.87 130.81 65.41 130.81 311.13 207.65 138.59 34.88 130.81 65.41 130.81 311.13 207.65 138.59 138.59 69.30 34.89 130.81 65.41 130.81 311.13 207.65 138.59 138.59 69.30 415.30 34.90 130.81 65.41 130.81 311.13 207.65 138.59 138.59 69.30 415.30 34.91 130.81 65.41 130.81 311.13 207.65 138.59 138.59 69.30 415.30 329.63 34.92 130.81 65.41 130.81 311.13 207.65 138.59 138.59 69.30 415.30 329.63 34.93 130.81 65.41 130.81 311.13 207.65 138.59 138.59 69.30 415.30 329.63 34.94 65.41 130.81 311.13 207.65 138.59 138.59 69.30 415.30 329.63 34.95 130.81 311.13 207.65 138.59 138.59 69.30 415.30 329.63 34.96 130.81 311.13 207.65 138.59 138.59 69.30 415.30 329.63 34.97 130.81 207.65 138.59 138.59 69.30 415.30 329.63 34.98 130.81 207.65 138.59 138.59 69.30 415.30 329.63 34.99 130.81 207.65 138.59 138.59 69.30 415.30 329.63 35.00 130.81 207.65 138.59 138.59 69.30 415.30 329.63 35.01 130.81 207.65 138.59 138.59 69.30 415.30 329.63 35.02 130.81 207.65 138.59 138.59 69.30 415.30 329.63 35.03 207.65 138.59 138.59 69.30 415.30 329.63 35.04 207.65 138.59 138.59 69.30 415.30 329.63 35.05 207.65 138.59 138.59 69.30 415.30 329.63 35.06 207.65 138.59 138.59 69.30 415.30 329.63 35.07 207.65 138.59 138.59 69.30 415.30 329.63 35.08 207.65 138.59 138.59 69.30 415.30 329.63 35.09 207.65 138.59 138.59 69.30 415.30 329.63 35.10 207.65 138.59 138.59 69.30 415.30 329.63 35.11 207.65 138.59 138.59 69.30 415.30 329.63 35.12 207.65 138.59 138.59 69.30 415.30 329.63 35.13 207.65 138.59 138.59 69.30 415.30 329.63 35.14 207.65 138.59 138.59 69.30 415.30 329.63 35.15 207.65 138.59 138.59 69.30 415.30 329.63 35.16 207.65 138.59 138.59 69.30 415.30 329.63 35.17 207.65 138.59 138.59 69.30 415.30 329.63 35.18 207.65 138.59 138.59 69.30 415.30 329.63 35.19 207.65 138.59 138.59 69.30 415.30 329.63 35.20 207.65 138.59 138.59 69.30 415.30 329.63 35.21 207.65 138.59 138.59 69.30 415.30 329.63 35.22 207.65 138.59 138.59 69.30 415.30 329.63 35.23 207.65 138.59 138.59 69.30 415.30 329.63 35.24 207.65 138.59 138.59 69.30 415.30 329.63 35.25 207.65 138.59 138.59 69.30 415.30 329.63 35.26 207.65 138.59 138.59 69.30 415.30 329.63 35.27 207.65 138.59 138.59 69.30 415.30 329.63 35.28 207.65 138.59 138.59 69.30 415.30 329.63 35.29 207.65 138.59 138.59 69.30 415.30 329.63 35.30 207.65 138.59 138.59 69.30 415.30 329.63 35.31 207.65 138.59 138.59 69.30 415.30 329.63 35.32 207.65 138.59 138.59 69.30 415.30 329.63 35.33 207.65 138.59 138.59 69.30 415.30 329.63 35.34 207.65 138.59 138.59 69.30 415.30 329.63 35.35 207.65 138.59 138.59 69.30 415.30 329.63 35.36 207.65 138.59 138.59 69.30 415.30 329.63 35.37 207.65 138.59 138.59 69.30 415.30 329.63 35.38 207.65 138.59 138.59 69.30 415.30 329.63 35.39 207.65 138.59 138.59 69.30 415.30 329.63 35.40 207.65 138.59 138.59 69.30 415.30 329.63 35.41 207.65 138.59 138.59 69.30 415.30 329.63 35.42 207.65 138.59 138.59 69.30 415.30 329.63 35.43 207.65 138.59 138.59 69.30 415.30 329.63 35.44 207.65 138.59 138.59 69.30 415.30 329.63 35.45 207.65 138.59 138.59 69.30 415.30 329.63 35.46 207.65 138.59 138.59 69.30 415.30 329.63 35.47 207.65 138.59 138.59 69.30 415.30 329.63 35.48 207.65 138.59 138.59 69.30 415.30 329.63 35.49 207.65 138.59 138.59 69.30 415.30 329.63 35.50 207.65 138.59 138.59 69.30 415.30 329.63 35.51 207.65 138.59 138.59 69.30 415.30 329.63 35.52 207.65 138.59 138.59 69.30 415.30 329.63 35.53 207.65 138.59 138.59 69.30 415.30 329.63 35.54 207.65 138.59 138.59 69.30 415.30 329.63 35.55 207.65 138.59 138.59 69.30 415.30 329.63 35.56 207.65 138.59 138.59 69.30 415.30 329.63 35.57 207.65 138.59 138.59 69.30 415.30 329.63 35.58 207.65 138.59 138.59 69.30 415.30 329.63 35.59 207.65 138.59 138.59 69.30 415.30 329.63 35.60 207.65 138.59 138.59 69.30 415.30 329.63 35.61 207.65 138.59 138.59 69.30 415.30 329.63 35.62 207.65 138.59 138.59 69.30 415.30 329.63 35.63 207.65 138.59 138.59 69.30 415.30 329.63 35.64 207.65 138.59 138.59 69.30 415.30 329.63 35.65 207.65 138.59 138.59 69.30 415.30 329.63 35.66 207.65 138.59 138.59 69.30 415.30 329.63 35.67 207.65 138.59 138.59 69.30 415.30 329.63 35.68 207.65 138.59 138.59 69.30 415.30 329.63 35.69 207.65 138.59 138.59 69.30 415.30 329.63 35.70 207.65 138.59 138.59 69.30 415.30 329.63 35.71 207.65 138.59 138.59 69.30 415.30 329.63 35.72 207.65 138.59 138.59 69.30 415.30 329.63 35.73 207.65 138.59 138.59 69.30 415.30 329.63 35.74 207.65 138.59 138.59 69.30 415.30 329.63 35.75 207.65 138.59 138.59 69.30 415.30 329.63 35.76 207.65 138.59 138.59 69.30 415.30 329.63 35.77 207.65 138.59 138.59 69.30 415.30 329.63 35.78 207.65 138.59 138.59 69.30 415.30 329.63 35.79 207.65 138.59 138.59 69.30 415.30 329.63 35.80 207.65 138.59 138.59 69.30 415.30 329.63 35.81 207.65 138.59 138.59 69.30 415.30 329.63 35.82 207.65 138.59 138.59 69.30 415.30 329.63 35.83 207.65 138.59 138.59 69.30 415.30 329.63 35.84 207.65 138.59 138.59 69.30 415.30 329.63 35.85 207.65 138.59 138.59 69.30 415.30 329.63 35.86 207.65 138.59 138.59 69.30 415.30 329.63 35.87 207.65 138.59 138.59 69.30 415.30 329.63 35.88 207.65 138.59 138.59 69.30 415.30 329.63 35.89 207.65 138.59 138.59 69.30 415.30 329.63 35.90 207.65 138.59 138.59 69.30 415.30 329.63 35.91 207.65 138.59 138.59 69.30 415.30 329.63 35.92 207.65 138.59 138.59 69.30 415.30 329.63 35.93 207.65 138.59 138.59 69.30 415.30 329.63 35.94 207.65 138.59 138.59 69.30 415.30 329.63 35.95 138.59 69.30 415.30 329.63 35.96 138.59 69.30 415.30 329.63 35.97 138.59 69.30 415.30 329.63 35.98 69.30 415.30 329.63 35.99 415.30 329.63 36.00 415.30 329.63 36.01 415.30 329.63 36.02 415.30 329.63 36.03 415.30 329.63 36.04 415.30 329.63 36.05 415.30 329.63 36.06 415.30 329.63 36.07 415.30 329.63 36.08 415.30 329.63 36.09 415.30 329.63 36.10 415.30 329.63 36.11 415.30 329.63 36.12 415.30 329.63 36.13 415.30 329.63 36.14 415.30 329.63 36.15 415.30 329.63 36.16 329.63mir_eval-0.8.2/tests/data/multipitch/ref04.txt000066400000000000000000003131761475740344600212660ustar00rootroot000000000000000.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 440.00 0.23 440.00 0.24 440.00 0.25 440.00 220.00 0.26 440.00 220.00 0.27 440.00 220.00 0.28 440.00 220.00 0.29 440.00 220.00 0.30 440.00 220.00 0.31 440.00 220.00 0.32 440.00 220.00 0.33 440.00 220.00 0.34 440.00 220.00 0.35 440.00 220.00 0.36 440.00 220.00 0.37 440.00 220.00 0.38 440.00 220.00 0.39 440.00 220.00 0.40 440.00 220.00 0.41 440.00 220.00 0.42 440.00 220.00 0.43 440.00 220.00 0.44 440.00 220.00 0.45 440.00 220.00 0.46 440.00 220.00 0.47 440.00 220.00 0.48 440.00 220.00 0.49 440.00 220.00 0.50 440.00 220.00 440.00 0.51 440.00 220.00 440.00 0.52 440.00 220.00 440.00 0.53 440.00 220.00 440.00 0.54 440.00 220.00 440.00 0.55 440.00 220.00 440.00 0.56 440.00 220.00 440.00 0.57 440.00 220.00 440.00 0.58 440.00 220.00 440.00 0.59 440.00 220.00 440.00 0.60 440.00 220.00 440.00 0.61 440.00 220.00 440.00 0.62 440.00 220.00 440.00 0.63 440.00 220.00 440.00 0.64 440.00 220.00 440.00 0.65 440.00 220.00 440.00 0.66 440.00 220.00 440.00 0.67 440.00 220.00 440.00 0.68 440.00 220.00 440.00 0.69 440.00 220.00 440.00 0.70 440.00 220.00 440.00 0.71 440.00 220.00 440.00 0.72 440.00 220.00 440.00 0.73 440.00 220.00 440.00 0.74 440.00 220.00 440.00 0.75 440.00 220.00 440.00 0.76 440.00 220.00 440.00 0.77 440.00 220.00 440.00 0.78 440.00 220.00 440.00 0.79 440.00 220.00 440.00 0.80 440.00 220.00 440.00 0.81 440.00 220.00 440.00 0.82 440.00 220.00 440.00 0.83 440.00 220.00 440.00 0.84 440.00 220.00 440.00 0.85 440.00 220.00 440.00 0.86 440.00 220.00 440.00 0.87 440.00 220.00 440.00 0.88 440.00 220.00 440.00 0.89 440.00 220.00 440.00 0.90 440.00 220.00 440.00 0.91 440.00 220.00 440.00 0.92 440.00 220.00 440.00 0.93 440.00 220.00 440.00 0.94 440.00 220.00 440.00 0.95 440.00 220.00 440.00 0.96 440.00 220.00 440.00 0.97 440.00 220.00 440.00 0.98 440.00 220.00 440.00 0.99 440.00 220.00 440.00 1.00 440.00 220.00 440.00 1.01 440.00 220.00 440.00 1.02 440.00 220.00 440.00 1.03 440.00 220.00 440.00 1.04 440.00 220.00 440.00 1.05 440.00 220.00 440.00 523.25 1.06 440.00 220.00 440.00 523.25 1.07 220.00 440.00 523.25 1.08 220.00 440.00 523.25 1.09 220.00 440.00 523.25 1.10 220.00 440.00 523.25 1.11 220.00 440.00 523.25 1.12 220.00 440.00 523.25 1.13 220.00 440.00 523.25 1.14 220.00 440.00 523.25 1.15 220.00 440.00 523.25 1.16 440.00 523.25 1.17 440.00 523.25 1.18 440.00 523.25 261.63 1.19 440.00 523.25 261.63 1.20 440.00 523.25 261.63 523.25 1.21 440.00 523.25 261.63 523.25 1.22 523.25 261.63 523.25 1.23 523.25 261.63 523.25 1.24 523.25 261.63 523.25 1.25 523.25 261.63 523.25 1.26 523.25 261.63 523.25 1.27 523.25 261.63 523.25 1.28 523.25 261.63 523.25 1.29 523.25 261.63 523.25 1.30 523.25 261.63 523.25 1.31 523.25 261.63 523.25 1.32 523.25 261.63 523.25 1.33 523.25 261.63 523.25 1.34 523.25 261.63 523.25 1.35 523.25 261.63 523.25 1.36 523.25 261.63 523.25 1.37 523.25 261.63 523.25 1.38 523.25 261.63 523.25 1.39 523.25 261.63 523.25 1.40 523.25 261.63 523.25 1.41 523.25 261.63 523.25 1.42 523.25 261.63 523.25 1.43 523.25 261.63 523.25 1.44 523.25 261.63 523.25 1.45 523.25 261.63 523.25 1.46 523.25 261.63 523.25 1.47 523.25 261.63 523.25 1.48 523.25 261.63 523.25 1.49 523.25 261.63 523.25 1.50 523.25 261.63 523.25 1.51 523.25 261.63 523.25 1.52 523.25 261.63 523.25 1.53 523.25 261.63 523.25 1.54 523.25 261.63 523.25 1.55 523.25 261.63 523.25 1.56 523.25 261.63 523.25 1.57 523.25 261.63 523.25 1.58 523.25 261.63 523.25 1.59 523.25 261.63 523.25 1.60 523.25 261.63 523.25 1.61 523.25 261.63 523.25 164.81 1.62 523.25 261.63 523.25 164.81 1.63 523.25 261.63 523.25 164.81 1.64 523.25 261.63 523.25 164.81 1.65 523.25 261.63 523.25 164.81 329.63 1.66 523.25 523.25 164.81 329.63 1.67 523.25 523.25 164.81 329.63 1.68 523.25 523.25 164.81 329.63 1.69 523.25 164.81 329.63 1.70 523.25 164.81 329.63 1.71 523.25 164.81 329.63 1.72 523.25 164.81 329.63 329.63 1.73 523.25 164.81 329.63 329.63 1.74 164.81 329.63 329.63 1.75 164.81 329.63 329.63 1.76 164.81 329.63 329.63 1.77 164.81 329.63 329.63 1.78 164.81 329.63 329.63 1.79 164.81 329.63 329.63 1.80 164.81 329.63 329.63 1.81 164.81 329.63 329.63 1.82 164.81 329.63 329.63 1.83 164.81 329.63 329.63 1.84 164.81 329.63 329.63 1.85 164.81 329.63 329.63 1.86 164.81 329.63 329.63 1.87 164.81 329.63 329.63 1.88 164.81 329.63 329.63 1.89 164.81 329.63 329.63 1.90 164.81 329.63 329.63 1.91 164.81 329.63 329.63 1.92 164.81 329.63 329.63 1.93 164.81 329.63 329.63 1.94 164.81 329.63 329.63 1.95 164.81 329.63 329.63 1.96 164.81 329.63 329.63 1.97 164.81 329.63 329.63 1.98 164.81 329.63 329.63 1.99 164.81 329.63 329.63 2.00 164.81 329.63 329.63 2.01 164.81 329.63 329.63 2.02 164.81 329.63 329.63 2.03 164.81 329.63 329.63 2.04 164.81 329.63 329.63 2.05 164.81 329.63 329.63 2.06 164.81 329.63 329.63 2.07 164.81 329.63 329.63 2.08 164.81 329.63 329.63 2.09 164.81 329.63 329.63 2.10 164.81 329.63 329.63 2.11 164.81 329.63 329.63 2.12 164.81 329.63 329.63 2.13 164.81 329.63 329.63 2.14 164.81 329.63 329.63 2.15 164.81 329.63 329.63 2.16 164.81 329.63 329.63 2.17 164.81 329.63 329.63 2.18 164.81 329.63 329.63 2.19 164.81 329.63 329.63 2.20 164.81 329.63 329.63 2.21 164.81 329.63 329.63 2.22 164.81 329.63 329.63 2.23 164.81 329.63 329.63 2.24 164.81 329.63 329.63 2.25 164.81 329.63 329.63 2.26 164.81 329.63 329.63 2.27 164.81 329.63 329.63 2.28 164.81 329.63 329.63 2.29 164.81 329.63 329.63 2.30 164.81 329.63 329.63 2.31 164.81 329.63 329.63 2.32 164.81 329.63 329.63 2.33 164.81 329.63 329.63 2.34 164.81 329.63 329.63 2.35 164.81 329.63 329.63 2.36 164.81 329.63 329.63 2.37 164.81 329.63 329.63 2.38 164.81 329.63 329.63 2.39 164.81 329.63 329.63 2.40 164.81 329.63 2.41 164.81 329.63 2.42 329.63 2.43 329.63 2.44 329.63 329.63 2.45 329.63 329.63 2.46 329.63 329.63 2.47 329.63 329.63 2.48 329.63 329.63 164.81 2.49 329.63 329.63 164.81 2.50 329.63 164.81 2.51 329.63 164.81 2.52 329.63 164.81 2.53 329.63 164.81 2.54 329.63 164.81 2.55 329.63 164.81 2.56 329.63 164.81 329.63 2.57 329.63 164.81 329.63 2.58 329.63 164.81 329.63 2.59 329.63 164.81 329.63 2.60 329.63 164.81 329.63 2.61 329.63 164.81 329.63 2.62 329.63 164.81 329.63 2.63 329.63 164.81 329.63 2.64 329.63 164.81 329.63 2.65 329.63 164.81 329.63 2.66 329.63 164.81 329.63 2.67 329.63 164.81 329.63 2.68 329.63 164.81 329.63 2.69 329.63 164.81 329.63 2.70 329.63 164.81 329.63 2.71 329.63 164.81 329.63 2.72 329.63 164.81 329.63 2.73 329.63 164.81 329.63 2.74 329.63 164.81 329.63 2.75 329.63 164.81 329.63 2.76 329.63 164.81 329.63 2.77 329.63 164.81 329.63 2.78 329.63 164.81 329.63 2.79 329.63 164.81 329.63 2.80 329.63 164.81 329.63 2.81 329.63 164.81 329.63 2.82 329.63 164.81 329.63 2.83 329.63 164.81 329.63 2.84 329.63 164.81 329.63 2.85 329.63 164.81 329.63 2.86 329.63 164.81 329.63 2.87 329.63 164.81 329.63 2.88 329.63 164.81 329.63 2.89 329.63 164.81 329.63 349.23 2.90 329.63 164.81 329.63 349.23 2.91 329.63 164.81 329.63 349.23 2.92 164.81 329.63 349.23 2.93 164.81 329.63 349.23 2.94 164.81 329.63 349.23 2.95 164.81 329.63 349.23 174.61 2.96 164.81 329.63 349.23 174.61 2.97 164.81 329.63 349.23 174.61 2.98 329.63 349.23 174.61 2.99 329.63 349.23 174.61 3.00 329.63 349.23 174.61 3.01 329.63 349.23 174.61 3.02 329.63 349.23 174.61 3.03 329.63 349.23 174.61 3.04 329.63 349.23 174.61 3.05 329.63 349.23 174.61 3.06 329.63 349.23 174.61 3.07 329.63 349.23 174.61 3.08 329.63 349.23 174.61 349.23 3.09 329.63 349.23 174.61 349.23 3.10 329.63 349.23 174.61 349.23 3.11 349.23 174.61 349.23 3.12 349.23 174.61 349.23 3.13 349.23 174.61 349.23 329.63 3.14 349.23 174.61 349.23 329.63 3.15 174.61 349.23 329.63 3.16 174.61 349.23 329.63 3.17 174.61 349.23 329.63 164.81 3.18 174.61 349.23 329.63 164.81 3.19 174.61 349.23 329.63 164.81 3.20 349.23 329.63 164.81 3.21 349.23 329.63 164.81 3.22 349.23 329.63 164.81 3.23 349.23 329.63 164.81 3.24 349.23 329.63 164.81 3.25 349.23 329.63 164.81 3.26 349.23 329.63 164.81 3.27 329.63 164.81 329.63 3.28 329.63 164.81 329.63 3.29 329.63 164.81 329.63 3.30 329.63 164.81 329.63 3.31 329.63 164.81 329.63 3.32 329.63 164.81 329.63 3.33 329.63 164.81 329.63 3.34 329.63 164.81 329.63 3.35 329.63 164.81 329.63 146.83 3.36 329.63 164.81 329.63 146.83 3.37 329.63 329.63 146.83 3.38 329.63 329.63 146.83 293.66 3.39 329.63 329.63 146.83 293.66 3.40 329.63 329.63 146.83 293.66 3.41 329.63 146.83 293.66 3.42 329.63 146.83 293.66 3.43 329.63 146.83 293.66 3.44 329.63 146.83 293.66 3.45 329.63 146.83 293.66 293.66 3.46 329.63 146.83 293.66 293.66 3.47 146.83 293.66 293.66 3.48 146.83 293.66 293.66 3.49 146.83 293.66 293.66 3.50 146.83 293.66 293.66 3.51 146.83 293.66 293.66 3.52 146.83 293.66 293.66 3.53 146.83 293.66 293.66 130.81 3.54 146.83 293.66 293.66 130.81 3.55 293.66 293.66 130.81 3.56 293.66 293.66 130.81 3.57 293.66 293.66 130.81 3.58 293.66 293.66 130.81 3.59 293.66 293.66 130.81 261.63 3.60 293.66 293.66 130.81 261.63 3.61 293.66 293.66 130.81 261.63 261.63 3.62 293.66 130.81 261.63 261.63 3.63 293.66 130.81 261.63 261.63 3.64 130.81 261.63 261.63 3.65 130.81 261.63 261.63 3.66 130.81 261.63 261.63 3.67 130.81 261.63 261.63 3.68 130.81 261.63 261.63 3.69 130.81 261.63 261.63 3.70 130.81 261.63 261.63 3.71 130.81 261.63 261.63 123.47 3.72 130.81 261.63 261.63 123.47 3.73 261.63 261.63 123.47 3.74 261.63 261.63 123.47 3.75 261.63 261.63 123.47 3.76 261.63 261.63 123.47 3.77 261.63 261.63 123.47 3.78 261.63 261.63 123.47 3.79 261.63 261.63 123.47 246.94 3.80 261.63 123.47 246.94 246.94 3.81 123.47 246.94 246.94 3.82 123.47 246.94 246.94 3.83 123.47 246.94 246.94 3.84 123.47 246.94 246.94 3.85 123.47 246.94 246.94 3.86 123.47 246.94 246.94 3.87 123.47 246.94 246.94 3.88 123.47 246.94 246.94 3.89 123.47 246.94 246.94 3.90 123.47 246.94 246.94 3.91 123.47 246.94 246.94 110.00 3.92 246.94 246.94 110.00 3.93 246.94 246.94 110.00 3.94 246.94 246.94 110.00 3.95 246.94 246.94 110.00 3.96 246.94 246.94 110.00 3.97 246.94 246.94 110.00 3.98 246.94 246.94 110.00 3.99 246.94 246.94 110.00 220.00 4.00 246.94 246.94 110.00 220.00 4.01 246.94 246.94 110.00 220.00 220.00 4.02 246.94 110.00 220.00 220.00 4.03 246.94 110.00 220.00 220.00 4.04 110.00 220.00 220.00 4.05 110.00 220.00 220.00 4.06 220.00 220.00 4.07 220.00 220.00 4.08 220.00 220.00 4.09 220.00 220.00 4.10 220.00 220.00 4.11 220.00 220.00 4.12 220.00 4.13 220.00 110.00 4.14 220.00 110.00 4.15 220.00 110.00 4.16 220.00 110.00 4.17 110.00 4.18 110.00 4.19 110.00 4.20 110.00 220.00 4.21 110.00 220.00 4.22 110.00 220.00 4.23 110.00 220.00 220.00 4.24 110.00 220.00 220.00 4.25 110.00 220.00 220.00 4.26 110.00 220.00 220.00 4.27 110.00 220.00 220.00 4.28 110.00 220.00 220.00 4.29 110.00 220.00 220.00 4.30 110.00 220.00 220.00 4.31 110.00 220.00 220.00 4.32 110.00 220.00 220.00 4.33 110.00 220.00 220.00 4.34 110.00 220.00 220.00 4.35 110.00 220.00 220.00 4.36 110.00 220.00 220.00 4.37 110.00 220.00 220.00 4.38 110.00 220.00 220.00 4.39 110.00 220.00 220.00 4.40 110.00 220.00 220.00 4.41 110.00 220.00 220.00 4.42 110.00 220.00 220.00 4.43 110.00 220.00 220.00 4.44 110.00 220.00 220.00 4.45 110.00 220.00 220.00 4.46 110.00 220.00 220.00 4.47 110.00 220.00 220.00 4.48 110.00 220.00 220.00 4.49 110.00 220.00 220.00 4.50 110.00 220.00 220.00 4.51 110.00 220.00 220.00 4.52 110.00 220.00 220.00 4.53 110.00 220.00 220.00 4.54 110.00 220.00 220.00 4.55 110.00 220.00 220.00 4.56 110.00 220.00 220.00 4.57 110.00 220.00 220.00 4.58 110.00 220.00 220.00 4.59 110.00 220.00 220.00 4.60 110.00 220.00 220.00 4.61 110.00 220.00 220.00 4.62 110.00 220.00 220.00 4.63 110.00 220.00 220.00 4.64 110.00 220.00 220.00 4.65 110.00 220.00 220.00 4.66 110.00 220.00 220.00 4.67 110.00 220.00 220.00 4.68 110.00 220.00 220.00 4.69 110.00 220.00 220.00 4.70 110.00 220.00 220.00 4.71 110.00 220.00 220.00 4.72 110.00 220.00 220.00 4.73 110.00 220.00 220.00 4.74 110.00 220.00 220.00 4.75 110.00 220.00 220.00 4.76 110.00 220.00 220.00 4.77 110.00 220.00 220.00 4.78 110.00 220.00 220.00 4.79 110.00 220.00 220.00 4.80 110.00 220.00 220.00 4.81 110.00 220.00 220.00 4.82 110.00 220.00 220.00 4.83 110.00 220.00 220.00 4.84 110.00 220.00 220.00 4.85 110.00 220.00 220.00 4.86 110.00 220.00 220.00 4.87 110.00 220.00 220.00 4.88 110.00 220.00 220.00 4.89 110.00 220.00 220.00 4.90 110.00 220.00 220.00 4.91 110.00 220.00 220.00 4.92 110.00 220.00 220.00 4.93 110.00 220.00 220.00 4.94 110.00 220.00 220.00 4.95 110.00 220.00 220.00 4.96 110.00 220.00 220.00 4.97 110.00 220.00 220.00 4.98 110.00 220.00 220.00 4.99 110.00 220.00 220.00 5.00 110.00 220.00 220.00 5.01 110.00 220.00 220.00 5.02 110.00 220.00 220.00 103.83 5.03 110.00 220.00 220.00 103.83 5.04 110.00 220.00 220.00 103.83 5.05 110.00 220.00 220.00 103.83 5.06 110.00 220.00 220.00 103.83 207.65 5.07 220.00 220.00 103.83 207.65 207.65 5.08 220.00 103.83 207.65 207.65 5.09 220.00 103.83 207.65 207.65 5.10 220.00 103.83 207.65 207.65 5.11 103.83 207.65 207.65 5.12 103.83 207.65 207.65 5.13 103.83 207.65 207.65 5.14 103.83 207.65 207.65 5.15 103.83 207.65 207.65 5.16 103.83 207.65 207.65 5.17 103.83 207.65 207.65 5.18 103.83 207.65 207.65 5.19 103.83 207.65 207.65 5.20 103.83 207.65 207.65 5.21 103.83 207.65 207.65 5.22 103.83 207.65 207.65 5.23 103.83 207.65 207.65 5.24 103.83 207.65 207.65 5.25 103.83 207.65 207.65 5.26 103.83 207.65 207.65 5.27 103.83 207.65 207.65 5.28 103.83 207.65 207.65 5.29 103.83 207.65 207.65 5.30 103.83 207.65 207.65 5.31 103.83 207.65 207.65 5.32 103.83 207.65 207.65 5.33 103.83 207.65 207.65 5.34 103.83 207.65 207.65 5.35 103.83 207.65 207.65 5.36 103.83 207.65 207.65 5.37 103.83 207.65 207.65 5.38 103.83 207.65 207.65 5.39 103.83 207.65 207.65 5.40 103.83 207.65 207.65 5.41 103.83 207.65 207.65 5.42 103.83 207.65 207.65 5.43 103.83 207.65 207.65 5.44 103.83 207.65 207.65 5.45 103.83 207.65 207.65 5.46 103.83 207.65 207.65 5.47 103.83 207.65 207.65 5.48 103.83 207.65 5.49 103.83 207.65 5.50 207.65 5.51 207.65 164.81 5.52 164.81 5.53 164.81 5.54 164.81 329.63 5.55 164.81 329.63 5.56 164.81 329.63 5.57 164.81 329.63 82.41 5.58 164.81 329.63 82.41 5.59 164.81 329.63 82.41 5.60 164.81 329.63 82.41 82.41 5.61 164.81 329.63 82.41 82.41 5.62 164.81 329.63 82.41 82.41 5.63 164.81 329.63 82.41 82.41 5.64 164.81 329.63 82.41 82.41 5.65 164.81 329.63 82.41 82.41 5.66 164.81 329.63 82.41 82.41 5.67 164.81 329.63 82.41 82.41 5.68 164.81 329.63 82.41 82.41 5.69 164.81 329.63 82.41 82.41 5.70 164.81 329.63 82.41 82.41 5.71 164.81 329.63 82.41 82.41 5.72 164.81 329.63 82.41 82.41 5.73 164.81 329.63 82.41 82.41 5.74 164.81 329.63 82.41 82.41 5.75 164.81 329.63 82.41 82.41 5.76 164.81 329.63 82.41 82.41 5.77 164.81 329.63 82.41 82.41 5.78 164.81 329.63 82.41 82.41 5.79 164.81 329.63 82.41 82.41 5.80 164.81 329.63 82.41 82.41 5.81 164.81 329.63 82.41 82.41 5.82 164.81 329.63 82.41 82.41 5.83 164.81 329.63 82.41 82.41 5.84 164.81 329.63 82.41 82.41 5.85 164.81 329.63 82.41 82.41 5.86 164.81 329.63 82.41 82.41 5.87 164.81 329.63 82.41 82.41 164.81 5.88 164.81 329.63 82.41 82.41 164.81 5.89 164.81 329.63 82.41 82.41 164.81 5.90 164.81 329.63 82.41 82.41 164.81 5.91 164.81 329.63 82.41 82.41 164.81 5.92 164.81 329.63 82.41 82.41 164.81 5.93 164.81 329.63 82.41 82.41 164.81 5.94 164.81 329.63 82.41 82.41 164.81 5.95 164.81 329.63 82.41 82.41 164.81 5.96 164.81 329.63 82.41 82.41 164.81 5.97 164.81 329.63 82.41 82.41 164.81 5.98 164.81 329.63 82.41 82.41 164.81 5.99 164.81 329.63 82.41 82.41 164.81 6.00 164.81 329.63 82.41 82.41 164.81 6.01 164.81 329.63 82.41 82.41 164.81 6.02 164.81 329.63 82.41 82.41 164.81 6.03 164.81 329.63 82.41 82.41 164.81 6.04 164.81 329.63 82.41 82.41 164.81 659.26 6.05 164.81 329.63 82.41 659.26 207.65 6.06 164.81 329.63 82.41 659.26 207.65 6.07 164.81 329.63 82.41 659.26 207.65 6.08 164.81 329.63 82.41 659.26 207.65 6.09 164.81 329.63 82.41 659.26 207.65 6.10 164.81 329.63 82.41 659.26 207.65 6.11 164.81 329.63 82.41 659.26 207.65 6.12 164.81 329.63 82.41 659.26 207.65 6.13 164.81 329.63 659.26 207.65 6.14 164.81 329.63 659.26 207.65 6.15 164.81 329.63 659.26 207.65 6.16 164.81 329.63 659.26 207.65 6.17 164.81 329.63 659.26 207.65 6.18 164.81 329.63 659.26 207.65 6.19 164.81 329.63 659.26 207.65 6.20 164.81 329.63 659.26 207.65 6.21 164.81 329.63 659.26 207.65 6.22 164.81 329.63 659.26 207.65 6.23 164.81 329.63 659.26 207.65 6.24 164.81 329.63 659.26 207.65 6.25 164.81 329.63 659.26 207.65 329.63 6.26 164.81 329.63 659.26 329.63 6.27 164.81 329.63 659.26 329.63 6.28 164.81 329.63 659.26 329.63 6.29 164.81 329.63 659.26 329.63 6.30 164.81 329.63 659.26 329.63 6.31 164.81 329.63 659.26 329.63 6.32 164.81 329.63 659.26 329.63 6.33 164.81 329.63 659.26 329.63 6.34 164.81 329.63 659.26 329.63 6.35 164.81 329.63 659.26 329.63 6.36 164.81 329.63 659.26 329.63 6.37 164.81 329.63 659.26 329.63 6.38 164.81 329.63 659.26 329.63 6.39 164.81 329.63 659.26 329.63 6.40 164.81 329.63 659.26 329.63 6.41 164.81 329.63 659.26 329.63 6.42 164.81 329.63 659.26 329.63 6.43 164.81 329.63 659.26 329.63 6.44 164.81 329.63 659.26 329.63 6.45 164.81 329.63 329.63 415.30 164.81 6.46 164.81 329.63 415.30 164.81 6.47 164.81 329.63 415.30 164.81 6.48 164.81 329.63 415.30 164.81 6.49 164.81 329.63 415.30 164.81 82.41 6.50 164.81 329.63 415.30 164.81 82.41 6.51 164.81 329.63 415.30 164.81 82.41 6.52 164.81 329.63 415.30 164.81 82.41 6.53 164.81 329.63 415.30 164.81 82.41 6.54 164.81 329.63 415.30 164.81 82.41 6.55 164.81 329.63 415.30 164.81 82.41 6.56 164.81 329.63 415.30 164.81 82.41 6.57 164.81 329.63 415.30 164.81 82.41 6.58 164.81 329.63 415.30 164.81 82.41 6.59 164.81 329.63 415.30 164.81 82.41 6.60 164.81 329.63 415.30 164.81 82.41 6.61 164.81 329.63 415.30 164.81 82.41 6.62 164.81 329.63 415.30 164.81 82.41 6.63 164.81 329.63 415.30 82.41 6.64 164.81 329.63 415.30 82.41 329.63 6.65 164.81 329.63 415.30 82.41 329.63 6.66 164.81 329.63 415.30 82.41 329.63 6.67 164.81 329.63 415.30 82.41 329.63 6.68 164.81 329.63 415.30 82.41 329.63 6.69 164.81 329.63 415.30 82.41 329.63 6.70 164.81 329.63 415.30 82.41 329.63 6.71 164.81 329.63 415.30 82.41 329.63 6.72 164.81 329.63 415.30 82.41 329.63 6.73 164.81 329.63 415.30 82.41 329.63 6.74 164.81 329.63 415.30 82.41 329.63 6.75 164.81 329.63 415.30 82.41 329.63 6.76 164.81 329.63 415.30 82.41 329.63 6.77 164.81 329.63 415.30 82.41 329.63 6.78 164.81 329.63 415.30 82.41 329.63 6.79 164.81 329.63 415.30 82.41 329.63 6.80 164.81 329.63 415.30 82.41 329.63 92.50 6.81 164.81 329.63 415.30 82.41 329.63 92.50 6.82 164.81 329.63 415.30 82.41 92.50 92.50 6.83 164.81 329.63 415.30 82.41 92.50 92.50 6.84 164.81 329.63 415.30 82.41 92.50 92.50 6.85 164.81 329.63 415.30 92.50 92.50 6.86 164.81 329.63 92.50 92.50 6.87 164.81 329.63 92.50 92.50 6.88 164.81 329.63 92.50 92.50 6.89 164.81 329.63 92.50 92.50 6.90 164.81 329.63 92.50 92.50 185.00 6.91 164.81 329.63 92.50 92.50 185.00 6.92 164.81 329.63 92.50 92.50 185.00 6.93 164.81 329.63 92.50 92.50 185.00 6.94 164.81 329.63 92.50 92.50 185.00 6.95 329.63 92.50 92.50 185.00 6.96 329.63 92.50 92.50 185.00 6.97 329.63 92.50 92.50 185.00 6.98 329.63 92.50 92.50 185.00 6.99 329.63 92.50 92.50 185.00 7.00 329.63 92.50 92.50 185.00 164.81 7.01 329.63 92.50 92.50 185.00 164.81 7.02 329.63 92.50 92.50 185.00 164.81 7.03 329.63 92.50 92.50 185.00 164.81 7.04 329.63 92.50 92.50 185.00 164.81 7.05 329.63 92.50 92.50 185.00 164.81 7.06 329.63 92.50 92.50 185.00 164.81 7.07 329.63 92.50 92.50 185.00 164.81 7.08 329.63 92.50 92.50 185.00 164.81 7.09 329.63 92.50 92.50 185.00 164.81 7.10 329.63 92.50 92.50 185.00 164.81 7.11 329.63 92.50 92.50 185.00 164.81 7.12 329.63 92.50 92.50 185.00 164.81 7.13 329.63 92.50 92.50 185.00 164.81 7.14 329.63 92.50 92.50 185.00 164.81 7.15 329.63 92.50 92.50 185.00 164.81 7.16 329.63 92.50 92.50 185.00 164.81 7.17 329.63 92.50 92.50 185.00 164.81 7.18 329.63 92.50 92.50 185.00 164.81 659.26 7.19 329.63 92.50 92.50 185.00 164.81 659.26 220.00 7.20 329.63 92.50 92.50 185.00 164.81 659.26 220.00 7.21 329.63 92.50 92.50 185.00 164.81 659.26 220.00 7.22 329.63 92.50 92.50 185.00 164.81 659.26 220.00 7.23 329.63 92.50 92.50 185.00 659.26 220.00 7.24 329.63 92.50 185.00 659.26 220.00 7.25 329.63 92.50 185.00 659.26 220.00 7.26 329.63 92.50 185.00 659.26 220.00 7.27 329.63 92.50 185.00 659.26 220.00 7.28 329.63 92.50 185.00 659.26 220.00 7.29 329.63 92.50 185.00 659.26 220.00 7.30 329.63 92.50 185.00 659.26 220.00 7.31 329.63 92.50 185.00 659.26 220.00 7.32 329.63 92.50 185.00 659.26 220.00 7.33 329.63 92.50 185.00 659.26 220.00 7.34 329.63 92.50 185.00 659.26 220.00 7.35 329.63 185.00 659.26 220.00 7.36 329.63 185.00 659.26 220.00 7.37 329.63 185.00 659.26 220.00 7.38 329.63 185.00 659.26 220.00 7.39 329.63 185.00 659.26 220.00 7.40 329.63 185.00 659.26 220.00 329.63 7.41 329.63 185.00 659.26 220.00 329.63 7.42 329.63 185.00 659.26 329.63 7.43 329.63 185.00 659.26 329.63 7.44 329.63 185.00 659.26 329.63 7.45 329.63 185.00 659.26 329.63 7.46 329.63 185.00 659.26 329.63 7.47 329.63 185.00 659.26 329.63 7.48 329.63 185.00 659.26 329.63 7.49 329.63 185.00 659.26 329.63 7.50 329.63 185.00 659.26 329.63 7.51 329.63 185.00 659.26 329.63 7.52 329.63 185.00 659.26 329.63 7.53 329.63 185.00 659.26 329.63 7.54 329.63 185.00 659.26 329.63 7.55 329.63 185.00 659.26 329.63 7.56 329.63 185.00 659.26 329.63 7.57 329.63 185.00 329.63 440.00 92.50 7.58 329.63 185.00 329.63 440.00 92.50 7.59 329.63 185.00 329.63 440.00 92.50 164.81 7.60 329.63 185.00 329.63 440.00 92.50 164.81 7.61 329.63 185.00 329.63 440.00 92.50 164.81 7.62 329.63 185.00 440.00 92.50 164.81 7.63 329.63 185.00 440.00 92.50 164.81 7.64 329.63 185.00 440.00 92.50 164.81 7.65 329.63 185.00 440.00 92.50 164.81 7.66 329.63 185.00 440.00 92.50 164.81 7.67 329.63 185.00 440.00 92.50 164.81 7.68 329.63 185.00 440.00 92.50 164.81 7.69 329.63 185.00 440.00 92.50 164.81 7.70 329.63 185.00 440.00 92.50 164.81 7.71 329.63 185.00 440.00 92.50 164.81 7.72 329.63 185.00 440.00 92.50 164.81 7.73 329.63 185.00 440.00 92.50 164.81 7.74 329.63 185.00 440.00 92.50 164.81 7.75 329.63 185.00 440.00 92.50 164.81 7.76 329.63 185.00 440.00 92.50 164.81 329.63 7.77 329.63 185.00 440.00 92.50 164.81 329.63 7.78 329.63 185.00 440.00 92.50 164.81 329.63 7.79 329.63 185.00 440.00 92.50 164.81 329.63 7.80 329.63 185.00 440.00 92.50 164.81 329.63 7.81 329.63 185.00 440.00 92.50 329.63 7.82 329.63 185.00 440.00 92.50 329.63 7.83 329.63 185.00 440.00 92.50 329.63 7.84 329.63 185.00 440.00 92.50 329.63 7.85 329.63 185.00 440.00 92.50 329.63 7.86 329.63 185.00 440.00 92.50 329.63 7.87 329.63 185.00 440.00 92.50 329.63 7.88 329.63 185.00 440.00 92.50 329.63 7.89 329.63 185.00 440.00 92.50 329.63 7.90 329.63 185.00 440.00 92.50 329.63 7.91 329.63 185.00 440.00 92.50 329.63 7.92 329.63 185.00 440.00 92.50 329.63 7.93 329.63 185.00 440.00 92.50 329.63 7.94 329.63 185.00 440.00 92.50 329.63 103.83 7.95 329.63 185.00 440.00 92.50 103.83 7.96 329.63 185.00 440.00 92.50 103.83 7.97 329.63 185.00 440.00 103.83 7.98 329.63 185.00 440.00 103.83 7.99 329.63 185.00 103.83 8.00 329.63 185.00 103.83 8.01 329.63 185.00 103.83 8.02 329.63 185.00 103.83 8.03 329.63 185.00 103.83 8.04 329.63 185.00 103.83 103.83 8.05 329.63 185.00 103.83 103.83 8.06 329.63 185.00 103.83 103.83 8.07 329.63 185.00 103.83 103.83 8.08 329.63 185.00 103.83 103.83 8.09 329.63 185.00 103.83 103.83 8.10 329.63 185.00 103.83 103.83 8.11 329.63 185.00 103.83 103.83 8.12 329.63 185.00 103.83 103.83 8.13 329.63 185.00 103.83 103.83 8.14 329.63 185.00 103.83 103.83 164.81 8.15 329.63 185.00 103.83 103.83 164.81 8.16 329.63 185.00 103.83 103.83 164.81 8.17 329.63 185.00 103.83 103.83 164.81 8.18 329.63 185.00 103.83 103.83 164.81 207.65 8.19 329.63 185.00 103.83 103.83 164.81 207.65 8.20 329.63 185.00 103.83 103.83 164.81 207.65 8.21 329.63 185.00 103.83 103.83 164.81 207.65 8.22 329.63 103.83 103.83 164.81 207.65 8.23 329.63 103.83 103.83 164.81 207.65 8.24 329.63 103.83 103.83 164.81 207.65 8.25 329.63 103.83 103.83 164.81 207.65 8.26 329.63 103.83 103.83 164.81 207.65 8.27 329.63 103.83 103.83 164.81 207.65 8.28 329.63 103.83 103.83 164.81 207.65 8.29 329.63 103.83 103.83 164.81 207.65 8.30 329.63 103.83 103.83 164.81 207.65 8.31 329.63 103.83 103.83 164.81 207.65 659.26 8.32 329.63 103.83 103.83 164.81 207.65 659.26 8.33 329.63 103.83 103.83 164.81 207.65 659.26 246.94 8.34 329.63 103.83 103.83 164.81 207.65 659.26 246.94 8.35 329.63 103.83 103.83 164.81 207.65 659.26 246.94 8.36 329.63 103.83 103.83 164.81 207.65 659.26 246.94 8.37 329.63 103.83 103.83 207.65 659.26 246.94 8.38 329.63 103.83 103.83 207.65 659.26 246.94 8.39 329.63 103.83 207.65 659.26 246.94 8.40 329.63 103.83 207.65 659.26 246.94 8.41 329.63 103.83 207.65 659.26 246.94 8.42 329.63 103.83 207.65 659.26 246.94 8.43 329.63 103.83 207.65 659.26 246.94 8.44 329.63 103.83 207.65 659.26 246.94 8.45 329.63 103.83 207.65 659.26 246.94 8.46 329.63 207.65 659.26 246.94 8.47 329.63 207.65 659.26 246.94 8.48 329.63 207.65 659.26 246.94 8.49 329.63 207.65 659.26 246.94 8.50 329.63 207.65 659.26 246.94 8.51 329.63 207.65 659.26 246.94 8.52 329.63 207.65 659.26 246.94 8.53 329.63 207.65 659.26 246.94 329.63 8.54 329.63 207.65 659.26 246.94 329.63 8.55 329.63 207.65 659.26 246.94 329.63 8.56 329.63 207.65 659.26 246.94 329.63 8.57 329.63 207.65 659.26 329.63 8.58 329.63 207.65 659.26 329.63 8.59 329.63 207.65 659.26 329.63 8.60 329.63 207.65 659.26 329.63 8.61 329.63 207.65 659.26 329.63 8.62 329.63 207.65 659.26 329.63 8.63 329.63 207.65 659.26 329.63 8.64 329.63 207.65 659.26 329.63 8.65 329.63 207.65 659.26 329.63 8.66 329.63 207.65 659.26 329.63 8.67 329.63 207.65 659.26 329.63 8.68 329.63 207.65 659.26 329.63 103.83 8.69 329.63 207.65 659.26 329.63 103.83 8.70 329.63 207.65 659.26 329.63 103.83 8.71 329.63 207.65 659.26 329.63 103.83 493.88 8.72 329.63 207.65 329.63 103.83 493.88 164.81 8.73 329.63 207.65 103.83 493.88 164.81 8.74 329.63 207.65 103.83 493.88 164.81 8.75 329.63 207.65 103.83 493.88 164.81 8.76 329.63 207.65 103.83 493.88 164.81 8.77 329.63 207.65 103.83 493.88 164.81 8.78 329.63 207.65 103.83 493.88 164.81 8.79 329.63 207.65 103.83 493.88 164.81 8.80 329.63 207.65 103.83 493.88 164.81 8.81 329.63 207.65 103.83 493.88 164.81 8.82 329.63 207.65 103.83 493.88 164.81 8.83 329.63 207.65 103.83 493.88 164.81 8.84 329.63 207.65 103.83 493.88 164.81 8.85 329.63 207.65 103.83 493.88 164.81 8.86 329.63 207.65 103.83 493.88 164.81 8.87 329.63 207.65 103.83 493.88 164.81 8.88 329.63 207.65 103.83 493.88 164.81 8.89 329.63 207.65 103.83 493.88 164.81 8.90 329.63 207.65 103.83 493.88 164.81 329.63 8.91 329.63 207.65 103.83 493.88 164.81 329.63 8.92 329.63 207.65 103.83 493.88 164.81 329.63 8.93 329.63 207.65 103.83 493.88 164.81 329.63 8.94 329.63 207.65 103.83 493.88 164.81 329.63 8.95 329.63 207.65 103.83 493.88 329.63 8.96 329.63 207.65 103.83 493.88 329.63 8.97 329.63 207.65 103.83 493.88 329.63 8.98 329.63 207.65 103.83 493.88 329.63 8.99 329.63 207.65 103.83 493.88 329.63 9.00 329.63 207.65 103.83 493.88 329.63 9.01 329.63 207.65 103.83 493.88 329.63 9.02 329.63 207.65 103.83 493.88 329.63 9.03 329.63 207.65 103.83 493.88 329.63 9.04 329.63 207.65 103.83 493.88 329.63 9.05 329.63 207.65 103.83 493.88 329.63 9.06 329.63 207.65 103.83 493.88 329.63 9.07 329.63 207.65 103.83 493.88 329.63 9.08 329.63 207.65 103.83 493.88 329.63 9.09 329.63 207.65 103.83 493.88 329.63 523.25 110.00 9.10 329.63 207.65 103.83 493.88 329.63 523.25 110.00 9.11 329.63 207.65 493.88 523.25 110.00 9.12 329.63 207.65 523.25 110.00 9.13 329.63 207.65 523.25 110.00 9.14 329.63 207.65 523.25 110.00 9.15 329.63 207.65 523.25 110.00 110.00 9.16 329.63 207.65 523.25 110.00 110.00 9.17 329.63 207.65 523.25 110.00 110.00 9.18 329.63 207.65 523.25 110.00 110.00 9.19 329.63 207.65 523.25 110.00 110.00 9.20 329.63 207.65 523.25 110.00 110.00 9.21 329.63 207.65 523.25 110.00 110.00 9.22 329.63 207.65 523.25 110.00 110.00 9.23 329.63 207.65 523.25 110.00 110.00 9.24 329.63 207.65 523.25 110.00 110.00 220.00 9.25 329.63 207.65 523.25 110.00 110.00 220.00 9.26 329.63 207.65 523.25 110.00 110.00 220.00 9.27 329.63 523.25 110.00 110.00 220.00 9.28 329.63 523.25 110.00 110.00 220.00 9.29 329.63 523.25 110.00 110.00 220.00 9.30 329.63 523.25 110.00 110.00 220.00 164.81 9.31 329.63 523.25 110.00 110.00 220.00 164.81 9.32 329.63 523.25 110.00 110.00 220.00 164.81 9.33 329.63 523.25 110.00 110.00 220.00 164.81 9.34 329.63 523.25 110.00 110.00 220.00 164.81 9.35 329.63 523.25 110.00 110.00 220.00 164.81 9.36 329.63 523.25 110.00 110.00 220.00 164.81 9.37 329.63 523.25 110.00 110.00 220.00 164.81 9.38 329.63 523.25 110.00 110.00 220.00 164.81 9.39 329.63 523.25 110.00 110.00 220.00 164.81 9.40 329.63 523.25 110.00 110.00 220.00 164.81 9.41 329.63 523.25 110.00 110.00 220.00 164.81 9.42 329.63 523.25 110.00 110.00 220.00 164.81 9.43 329.63 523.25 110.00 110.00 220.00 164.81 9.44 329.63 523.25 110.00 110.00 220.00 164.81 9.45 329.63 523.25 110.00 110.00 220.00 164.81 9.46 329.63 523.25 110.00 110.00 220.00 164.81 9.47 329.63 523.25 110.00 110.00 220.00 164.81 9.48 329.63 523.25 110.00 110.00 220.00 164.81 9.49 329.63 523.25 110.00 110.00 220.00 164.81 9.50 329.63 523.25 110.00 110.00 220.00 164.81 261.63 9.51 329.63 523.25 110.00 110.00 220.00 164.81 261.63 9.52 329.63 523.25 110.00 110.00 220.00 164.81 261.63 9.53 329.63 523.25 110.00 110.00 220.00 261.63 9.54 329.63 523.25 110.00 110.00 220.00 261.63 9.55 329.63 523.25 110.00 110.00 220.00 261.63 9.56 329.63 523.25 110.00 110.00 220.00 261.63 9.57 329.63 523.25 110.00 110.00 220.00 261.63 9.58 329.63 523.25 110.00 110.00 220.00 261.63 9.59 329.63 523.25 110.00 110.00 220.00 261.63 9.60 329.63 523.25 110.00 220.00 261.63 9.61 329.63 523.25 110.00 220.00 261.63 9.62 329.63 523.25 110.00 220.00 261.63 9.63 329.63 523.25 110.00 220.00 261.63 9.64 329.63 523.25 110.00 220.00 261.63 9.65 329.63 523.25 220.00 261.63 9.66 329.63 523.25 220.00 261.63 9.67 329.63 523.25 220.00 261.63 9.68 329.63 523.25 220.00 261.63 9.69 329.63 523.25 220.00 261.63 9.70 329.63 523.25 220.00 261.63 9.71 329.63 523.25 220.00 261.63 329.63 9.72 329.63 523.25 220.00 261.63 329.63 9.73 329.63 523.25 220.00 261.63 329.63 9.74 329.63 523.25 220.00 329.63 9.75 329.63 523.25 220.00 329.63 9.76 329.63 523.25 220.00 329.63 9.77 329.63 523.25 220.00 329.63 9.78 329.63 523.25 220.00 329.63 9.79 329.63 523.25 220.00 329.63 9.80 329.63 523.25 220.00 329.63 246.94 9.81 329.63 523.25 220.00 329.63 246.94 9.82 329.63 523.25 329.63 246.94 9.83 329.63 523.25 329.63 246.94 9.84 329.63 523.25 329.63 246.94 9.85 329.63 523.25 329.63 246.94 9.86 329.63 523.25 329.63 246.94 9.87 329.63 523.25 329.63 246.94 9.88 329.63 523.25 329.63 246.94 9.89 329.63 523.25 246.94 164.81 9.90 329.63 523.25 246.94 164.81 9.91 329.63 523.25 246.94 164.81 9.92 329.63 523.25 246.94 164.81 9.93 329.63 523.25 246.94 164.81 9.94 329.63 523.25 246.94 164.81 9.95 329.63 523.25 246.94 164.81 9.96 329.63 246.94 164.81 9.97 329.63 246.94 164.81 9.98 329.63 246.94 164.81 9.99 329.63 246.94 164.81 10.00 329.63 246.94 164.81 10.01 329.63 246.94 164.81 10.02 246.94 164.81 10.03 246.94 164.81 10.04 246.94 164.81 10.05 246.94 164.81 261.63 10.06 246.94 164.81 261.63 10.07 261.63 10.08 261.63 10.09 261.63 329.63 10.10 261.63 329.63 10.11 261.63 329.63 10.12 261.63 329.63 10.13 261.63 329.63 10.14 261.63 329.63 10.15 261.63 329.63 10.16 261.63 329.63 10.17 261.63 329.63 10.18 261.63 329.63 10.19 261.63 329.63 10.20 261.63 329.63 10.21 261.63 329.63 10.22 261.63 10.23 261.63 10.24 261.63 10.25 261.63 10.26 261.63 10.27 261.63 10.28 261.63 10.29 261.63 10.30 261.63 87.31 10.31 261.63 87.31 10.32 261.63 87.31 10.33 261.63 87.31 349.23 10.34 261.63 87.31 349.23 10.35 261.63 87.31 349.23 174.61 10.36 261.63 87.31 349.23 174.61 10.37 261.63 87.31 349.23 174.61 10.38 261.63 87.31 349.23 174.61 10.39 261.63 87.31 349.23 174.61 10.40 261.63 87.31 349.23 174.61 10.41 261.63 87.31 349.23 174.61 10.42 261.63 87.31 349.23 174.61 10.43 261.63 87.31 349.23 174.61 10.44 261.63 87.31 349.23 174.61 174.61 10.45 261.63 87.31 349.23 174.61 174.61 10.46 261.63 87.31 349.23 174.61 174.61 10.47 261.63 87.31 349.23 174.61 174.61 10.48 261.63 87.31 349.23 174.61 174.61 10.49 261.63 87.31 349.23 174.61 174.61 87.31 10.50 87.31 349.23 174.61 174.61 87.31 87.31 10.51 87.31 349.23 174.61 174.61 87.31 87.31 10.52 87.31 349.23 174.61 174.61 87.31 87.31 10.53 87.31 349.23 174.61 174.61 87.31 87.31 10.54 87.31 349.23 174.61 174.61 87.31 87.31 10.55 87.31 349.23 174.61 174.61 87.31 87.31 10.56 87.31 349.23 174.61 174.61 87.31 87.31 10.57 87.31 349.23 174.61 174.61 87.31 87.31 10.58 87.31 349.23 174.61 174.61 87.31 87.31 10.59 87.31 349.23 174.61 174.61 87.31 87.31 10.60 87.31 349.23 174.61 174.61 87.31 87.31 10.61 87.31 349.23 174.61 174.61 87.31 87.31 10.62 87.31 349.23 174.61 174.61 87.31 87.31 10.63 87.31 349.23 174.61 174.61 87.31 87.31 10.64 87.31 349.23 174.61 174.61 87.31 87.31 10.65 87.31 349.23 174.61 174.61 87.31 87.31 10.66 87.31 349.23 174.61 174.61 87.31 87.31 10.67 87.31 349.23 174.61 174.61 87.31 87.31 10.68 87.31 349.23 174.61 174.61 87.31 87.31 10.69 87.31 349.23 174.61 174.61 87.31 87.31 10.70 87.31 349.23 174.61 174.61 87.31 87.31 10.71 87.31 349.23 174.61 174.61 87.31 87.31 10.72 87.31 349.23 174.61 174.61 87.31 87.31 10.73 87.31 349.23 174.61 174.61 87.31 87.31 10.74 87.31 349.23 174.61 174.61 87.31 87.31 10.75 87.31 349.23 174.61 174.61 87.31 87.31 10.76 87.31 349.23 174.61 174.61 87.31 87.31 10.77 87.31 349.23 174.61 174.61 87.31 87.31 10.78 87.31 349.23 174.61 174.61 87.31 87.31 10.79 87.31 349.23 174.61 174.61 87.31 87.31 10.80 87.31 349.23 174.61 174.61 87.31 87.31 10.81 87.31 349.23 174.61 174.61 87.31 87.31 10.82 87.31 349.23 174.61 174.61 87.31 87.31 10.83 87.31 349.23 174.61 174.61 87.31 87.31 10.84 87.31 349.23 174.61 174.61 87.31 87.31 10.85 87.31 349.23 174.61 174.61 87.31 87.31 10.86 87.31 349.23 174.61 174.61 87.31 87.31 10.87 87.31 349.23 174.61 174.61 87.31 87.31 10.88 87.31 349.23 174.61 174.61 87.31 87.31 10.89 87.31 349.23 174.61 174.61 87.31 87.31 110.00 10.90 349.23 174.61 174.61 87.31 87.31 110.00 10.91 349.23 174.61 174.61 87.31 87.31 110.00 220.00 440.00 10.92 349.23 174.61 174.61 87.31 87.31 110.00 220.00 440.00 10.93 349.23 174.61 174.61 87.31 87.31 110.00 220.00 440.00 10.94 349.23 174.61 174.61 87.31 87.31 110.00 220.00 440.00 10.95 349.23 174.61 174.61 87.31 87.31 110.00 220.00 440.00 220.00 10.96 174.61 174.61 87.31 87.31 110.00 220.00 440.00 220.00 10.97 174.61 87.31 87.31 110.00 220.00 440.00 220.00 10.98 174.61 87.31 87.31 110.00 220.00 440.00 220.00 10.99 174.61 87.31 87.31 110.00 220.00 440.00 220.00 11.00 87.31 87.31 110.00 220.00 440.00 220.00 11.01 87.31 87.31 110.00 220.00 440.00 220.00 110.00 11.02 87.31 87.31 110.00 220.00 440.00 220.00 110.00 11.03 87.31 87.31 110.00 220.00 440.00 220.00 110.00 11.04 87.31 110.00 220.00 440.00 220.00 110.00 11.05 87.31 110.00 220.00 440.00 220.00 110.00 110.00 11.06 87.31 110.00 220.00 440.00 220.00 110.00 110.00 11.07 87.31 110.00 220.00 440.00 220.00 110.00 110.00 11.08 110.00 220.00 440.00 220.00 110.00 110.00 11.09 110.00 220.00 440.00 220.00 110.00 110.00 11.10 110.00 220.00 440.00 220.00 110.00 110.00 11.11 110.00 220.00 440.00 220.00 110.00 110.00 11.12 110.00 220.00 440.00 220.00 110.00 110.00 130.81 11.13 110.00 220.00 440.00 220.00 110.00 110.00 130.81 11.14 220.00 440.00 220.00 110.00 110.00 130.81 11.15 220.00 440.00 220.00 110.00 110.00 130.81 261.63 11.16 220.00 440.00 220.00 110.00 110.00 130.81 261.63 523.25 11.17 440.00 220.00 110.00 110.00 130.81 261.63 523.25 11.18 220.00 110.00 110.00 130.81 261.63 523.25 261.63 11.19 220.00 110.00 110.00 130.81 261.63 523.25 261.63 11.20 220.00 110.00 110.00 130.81 261.63 523.25 261.63 11.21 110.00 110.00 130.81 261.63 523.25 261.63 11.22 110.00 110.00 130.81 261.63 523.25 261.63 11.23 110.00 110.00 130.81 261.63 523.25 261.63 130.81 11.24 110.00 110.00 130.81 261.63 523.25 261.63 130.81 11.25 110.00 130.81 261.63 523.25 261.63 130.81 11.26 130.81 261.63 523.25 261.63 130.81 130.81 11.27 130.81 261.63 523.25 261.63 130.81 130.81 11.28 130.81 261.63 523.25 261.63 130.81 130.81 11.29 130.81 261.63 523.25 261.63 130.81 130.81 11.30 130.81 261.63 523.25 261.63 130.81 130.81 11.31 130.81 261.63 523.25 261.63 130.81 130.81 11.32 130.81 261.63 523.25 261.63 130.81 130.81 11.33 130.81 261.63 523.25 261.63 130.81 130.81 11.34 130.81 261.63 523.25 261.63 130.81 130.81 11.35 130.81 261.63 523.25 261.63 130.81 130.81 11.36 130.81 261.63 523.25 261.63 130.81 130.81 11.37 130.81 261.63 523.25 261.63 130.81 130.81 11.38 130.81 261.63 523.25 261.63 130.81 130.81 11.39 130.81 261.63 523.25 261.63 130.81 130.81 11.40 130.81 261.63 523.25 261.63 130.81 130.81 11.41 130.81 261.63 523.25 261.63 130.81 130.81 11.42 130.81 261.63 523.25 261.63 130.81 130.81 11.43 130.81 261.63 523.25 261.63 130.81 130.81 11.44 130.81 261.63 523.25 261.63 130.81 130.81 11.45 130.81 261.63 523.25 261.63 130.81 130.81 11.46 130.81 261.63 523.25 261.63 130.81 130.81 11.47 130.81 261.63 523.25 261.63 130.81 130.81 11.48 130.81 523.25 261.63 130.81 130.81 11.49 130.81 523.25 261.63 130.81 130.81 11.50 130.81 523.25 261.63 130.81 130.81 11.51 130.81 523.25 261.63 130.81 130.81 11.52 523.25 261.63 130.81 130.81 82.41 11.53 523.25 261.63 130.81 130.81 82.41 11.54 261.63 130.81 130.81 82.41 11.55 261.63 130.81 130.81 82.41 11.56 130.81 130.81 82.41 164.81 11.57 130.81 130.81 82.41 164.81 11.58 130.81 130.81 82.41 164.81 329.63 11.59 130.81 130.81 82.41 164.81 329.63 11.60 130.81 130.81 82.41 164.81 329.63 164.81 11.61 130.81 130.81 82.41 164.81 329.63 164.81 11.62 130.81 82.41 164.81 329.63 164.81 82.41 11.63 130.81 82.41 164.81 329.63 164.81 82.41 82.41 11.64 82.41 164.81 329.63 164.81 82.41 82.41 11.65 82.41 164.81 329.63 164.81 82.41 82.41 11.66 82.41 164.81 329.63 164.81 82.41 82.41 11.67 82.41 164.81 329.63 164.81 82.41 82.41 11.68 82.41 164.81 329.63 164.81 82.41 82.41 11.69 82.41 164.81 329.63 164.81 82.41 82.41 11.70 82.41 164.81 329.63 164.81 82.41 82.41 11.71 82.41 164.81 329.63 164.81 82.41 82.41 11.72 82.41 164.81 329.63 164.81 82.41 82.41 11.73 82.41 164.81 329.63 164.81 82.41 82.41 11.74 82.41 164.81 329.63 164.81 82.41 82.41 11.75 82.41 164.81 329.63 164.81 82.41 82.41 11.76 82.41 164.81 329.63 164.81 82.41 82.41 11.77 82.41 164.81 329.63 164.81 82.41 82.41 11.78 82.41 164.81 329.63 164.81 82.41 82.41 11.79 82.41 164.81 329.63 164.81 82.41 82.41 11.80 82.41 164.81 329.63 164.81 82.41 82.41 11.81 82.41 164.81 329.63 164.81 82.41 82.41 11.82 82.41 164.81 329.63 164.81 82.41 82.41 11.83 82.41 164.81 329.63 164.81 82.41 82.41 11.84 82.41 164.81 329.63 164.81 82.41 82.41 11.85 82.41 164.81 329.63 164.81 82.41 82.41 11.86 82.41 164.81 329.63 164.81 82.41 82.41 11.87 82.41 164.81 329.63 164.81 82.41 82.41 11.88 82.41 164.81 329.63 164.81 82.41 82.41 11.89 82.41 164.81 329.63 164.81 82.41 82.41 11.90 82.41 164.81 329.63 164.81 82.41 82.41 11.91 82.41 164.81 329.63 164.81 82.41 82.41 11.92 82.41 164.81 329.63 164.81 82.41 82.41 11.93 82.41 164.81 329.63 164.81 82.41 82.41 11.94 82.41 164.81 329.63 164.81 82.41 82.41 11.95 82.41 164.81 329.63 164.81 82.41 82.41 11.96 82.41 164.81 329.63 164.81 82.41 82.41 11.97 82.41 164.81 329.63 164.81 82.41 82.41 11.98 82.41 164.81 329.63 164.81 82.41 82.41 11.99 82.41 164.81 329.63 164.81 82.41 82.41 12.00 82.41 164.81 329.63 164.81 82.41 82.41 12.01 82.41 164.81 329.63 164.81 82.41 82.41 12.02 82.41 164.81 329.63 164.81 82.41 82.41 12.03 82.41 164.81 329.63 164.81 82.41 82.41 12.04 82.41 164.81 329.63 164.81 82.41 82.41 12.05 82.41 164.81 329.63 164.81 82.41 82.41 12.06 82.41 164.81 329.63 164.81 82.41 82.41 12.07 82.41 164.81 329.63 164.81 82.41 82.41 220.00 12.08 82.41 164.81 329.63 164.81 82.41 82.41 220.00 12.09 82.41 164.81 329.63 164.81 82.41 82.41 220.00 12.10 82.41 164.81 329.63 164.81 82.41 82.41 220.00 12.11 82.41 164.81 329.63 164.81 82.41 82.41 220.00 110.00 12.12 82.41 329.63 164.81 82.41 82.41 220.00 110.00 12.13 82.41 329.63 164.81 82.41 82.41 220.00 110.00 12.14 82.41 329.63 164.81 82.41 82.41 220.00 110.00 12.15 329.63 164.81 82.41 82.41 220.00 110.00 12.16 329.63 164.81 82.41 82.41 220.00 110.00 110.00 12.17 329.63 164.81 82.41 82.41 220.00 110.00 110.00 220.00 12.18 329.63 164.81 82.41 82.41 220.00 110.00 110.00 220.00 12.19 329.63 164.81 82.41 220.00 110.00 110.00 220.00 440.00 110.00 12.20 329.63 164.81 82.41 220.00 110.00 110.00 220.00 440.00 110.00 12.21 329.63 164.81 220.00 110.00 110.00 220.00 440.00 110.00 12.22 329.63 164.81 220.00 110.00 110.00 220.00 440.00 110.00 12.23 329.63 220.00 110.00 110.00 220.00 440.00 110.00 12.24 220.00 110.00 110.00 220.00 440.00 110.00 12.25 220.00 110.00 110.00 220.00 440.00 110.00 12.26 220.00 110.00 110.00 220.00 440.00 110.00 12.27 220.00 110.00 110.00 220.00 440.00 110.00 12.28 220.00 110.00 110.00 220.00 440.00 110.00 12.29 220.00 110.00 110.00 220.00 440.00 110.00 12.30 220.00 110.00 110.00 220.00 440.00 110.00 261.63 12.31 220.00 110.00 110.00 220.00 440.00 110.00 261.63 12.32 110.00 110.00 220.00 440.00 110.00 261.63 12.33 110.00 110.00 220.00 440.00 110.00 261.63 12.34 110.00 220.00 440.00 110.00 261.63 12.35 110.00 220.00 440.00 110.00 261.63 130.81 130.81 12.36 110.00 220.00 440.00 110.00 261.63 130.81 130.81 12.37 220.00 440.00 110.00 261.63 130.81 130.81 12.38 220.00 440.00 110.00 261.63 130.81 130.81 523.25 12.39 220.00 110.00 261.63 130.81 130.81 523.25 12.40 220.00 110.00 261.63 130.81 130.81 523.25 12.41 220.00 110.00 261.63 130.81 130.81 523.25 261.63 130.81 12.42 220.00 261.63 130.81 130.81 523.25 261.63 130.81 12.43 261.63 130.81 130.81 523.25 261.63 130.81 12.44 261.63 130.81 130.81 523.25 261.63 130.81 12.45 261.63 130.81 130.81 523.25 261.63 130.81 12.46 261.63 130.81 130.81 523.25 261.63 130.81 12.47 261.63 130.81 130.81 523.25 261.63 130.81 12.48 261.63 130.81 130.81 523.25 261.63 130.81 12.49 261.63 130.81 130.81 523.25 261.63 130.81 12.50 261.63 130.81 130.81 523.25 261.63 130.81 12.51 261.63 130.81 130.81 523.25 261.63 130.81 12.52 261.63 130.81 130.81 523.25 261.63 130.81 12.53 261.63 130.81 130.81 523.25 261.63 130.81 12.54 261.63 130.81 130.81 523.25 261.63 130.81 12.55 261.63 130.81 130.81 523.25 261.63 130.81 12.56 261.63 130.81 130.81 523.25 261.63 130.81 12.57 261.63 130.81 130.81 523.25 261.63 130.81 12.58 261.63 130.81 130.81 523.25 261.63 130.81 12.59 261.63 130.81 130.81 523.25 261.63 130.81 12.60 261.63 130.81 130.81 523.25 261.63 130.81 12.61 261.63 130.81 130.81 523.25 261.63 130.81 12.62 261.63 130.81 130.81 523.25 261.63 130.81 12.63 261.63 130.81 130.81 523.25 261.63 130.81 12.64 261.63 130.81 130.81 523.25 261.63 130.81 12.65 261.63 130.81 130.81 523.25 261.63 130.81 12.66 261.63 130.81 130.81 523.25 261.63 130.81 12.67 261.63 130.81 130.81 523.25 261.63 130.81 12.68 261.63 130.81 130.81 523.25 261.63 130.81 12.69 261.63 130.81 130.81 523.25 261.63 130.81 12.70 261.63 130.81 130.81 523.25 261.63 130.81 12.71 261.63 130.81 130.81 261.63 130.81 12.72 261.63 130.81 130.81 130.81 12.73 261.63 130.81 130.81 130.81 12.74 261.63 130.81 130.81 12.75 261.63 130.81 130.81 155.56 77.78 12.76 261.63 130.81 130.81 155.56 77.78 77.78 311.13 12.77 130.81 130.81 155.56 77.78 77.78 311.13 12.78 130.81 130.81 155.56 77.78 77.78 311.13 77.78 155.56 12.79 130.81 155.56 77.78 77.78 311.13 77.78 155.56 12.80 130.81 155.56 77.78 77.78 311.13 77.78 155.56 12.81 155.56 77.78 77.78 311.13 77.78 155.56 12.82 155.56 77.78 77.78 311.13 77.78 155.56 12.83 155.56 77.78 77.78 311.13 77.78 155.56 12.84 155.56 77.78 77.78 311.13 77.78 155.56 12.85 155.56 77.78 77.78 311.13 77.78 155.56 12.86 155.56 77.78 77.78 311.13 77.78 155.56 12.87 155.56 77.78 77.78 311.13 77.78 155.56 12.88 155.56 77.78 77.78 311.13 77.78 155.56 12.89 155.56 77.78 77.78 311.13 77.78 155.56 12.90 155.56 77.78 77.78 311.13 77.78 155.56 12.91 155.56 77.78 77.78 311.13 77.78 155.56 12.92 155.56 77.78 77.78 311.13 77.78 155.56 12.93 155.56 77.78 77.78 311.13 77.78 155.56 12.94 155.56 77.78 77.78 311.13 77.78 155.56 12.95 155.56 77.78 77.78 311.13 77.78 155.56 12.96 155.56 77.78 77.78 311.13 77.78 155.56 12.97 155.56 77.78 77.78 311.13 77.78 155.56 12.98 155.56 77.78 77.78 311.13 77.78 155.56 12.99 155.56 77.78 77.78 311.13 77.78 155.56 13.00 155.56 77.78 77.78 311.13 77.78 155.56 13.01 155.56 77.78 77.78 311.13 77.78 155.56 13.02 155.56 77.78 77.78 311.13 77.78 155.56 13.03 155.56 77.78 77.78 311.13 77.78 155.56 13.04 155.56 77.78 77.78 311.13 77.78 155.56 13.05 155.56 77.78 77.78 311.13 77.78 155.56 13.06 155.56 77.78 77.78 311.13 77.78 155.56 13.07 155.56 77.78 77.78 311.13 77.78 155.56 13.08 155.56 77.78 77.78 311.13 77.78 155.56 13.09 155.56 77.78 77.78 311.13 77.78 155.56 13.10 155.56 77.78 77.78 311.13 77.78 155.56 13.11 155.56 77.78 77.78 311.13 77.78 155.56 13.12 155.56 77.78 77.78 311.13 77.78 155.56 13.13 155.56 77.78 77.78 311.13 77.78 155.56 13.14 155.56 77.78 77.78 311.13 77.78 155.56 13.15 155.56 77.78 77.78 311.13 77.78 155.56 13.16 155.56 77.78 77.78 311.13 77.78 155.56 13.17 155.56 77.78 77.78 311.13 77.78 155.56 13.18 155.56 77.78 77.78 311.13 77.78 155.56 13.19 155.56 77.78 77.78 311.13 77.78 155.56 13.20 155.56 77.78 77.78 311.13 77.78 155.56 13.21 155.56 77.78 77.78 311.13 77.78 155.56 13.22 155.56 77.78 77.78 311.13 77.78 155.56 13.23 155.56 77.78 77.78 311.13 77.78 155.56 13.24 155.56 77.78 77.78 311.13 77.78 155.56 13.25 155.56 77.78 77.78 311.13 77.78 155.56 13.26 155.56 77.78 77.78 311.13 77.78 155.56 13.27 155.56 77.78 77.78 311.13 77.78 155.56 13.28 155.56 77.78 77.78 311.13 77.78 155.56 13.29 155.56 77.78 77.78 311.13 77.78 155.56 13.30 155.56 77.78 77.78 311.13 77.78 155.56 13.31 155.56 77.78 77.78 311.13 77.78 155.56 13.32 155.56 77.78 77.78 311.13 77.78 13.33 155.56 77.78 77.78 311.13 77.78 13.34 155.56 77.78 77.78 77.78 261.63 13.35 155.56 77.78 77.78 77.78 261.63 13.36 155.56 77.78 77.78 77.78 261.63 523.25 13.37 77.78 77.78 77.78 261.63 523.25 13.38 77.78 77.78 77.78 261.63 523.25 13.39 77.78 77.78 77.78 261.63 523.25 13.40 77.78 77.78 77.78 261.63 523.25 13.41 77.78 77.78 77.78 261.63 523.25 13.42 77.78 77.78 77.78 261.63 523.25 13.43 77.78 77.78 77.78 261.63 523.25 13.44 77.78 77.78 77.78 261.63 523.25 13.45 77.78 77.78 77.78 261.63 523.25 13.46 77.78 77.78 77.78 261.63 523.25 13.47 77.78 77.78 77.78 261.63 523.25 13.48 77.78 77.78 77.78 261.63 523.25 13.49 77.78 77.78 77.78 261.63 523.25 13.50 77.78 77.78 77.78 261.63 523.25 13.51 77.78 77.78 77.78 261.63 523.25 13.52 77.78 77.78 77.78 261.63 523.25 13.53 77.78 77.78 77.78 261.63 523.25 13.54 77.78 77.78 77.78 261.63 523.25 13.55 77.78 77.78 77.78 261.63 523.25 13.56 77.78 77.78 77.78 261.63 523.25 246.94 13.57 77.78 77.78 77.78 261.63 523.25 246.94 493.88 13.58 77.78 77.78 77.78 261.63 523.25 246.94 493.88 13.59 77.78 77.78 261.63 246.94 493.88 369.99 13.60 77.78 77.78 246.94 493.88 369.99 261.63 13.61 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.62 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.63 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.64 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.65 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.66 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.67 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.68 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.69 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.70 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.71 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.72 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.73 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.74 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.75 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.76 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.77 77.78 77.78 246.94 493.88 369.99 261.63 155.56 13.78 77.78 77.78 246.94 493.88 369.99 261.63 155.56 220.00 13.79 77.78 77.78 246.94 493.88 369.99 261.63 155.56 220.00 440.00 13.80 77.78 77.78 246.94 493.88 369.99 261.63 155.56 220.00 440.00 13.81 77.78 77.78 493.88 369.99 261.63 155.56 220.00 440.00 13.82 77.78 77.78 155.56 220.00 440.00 13.83 77.78 77.78 155.56 220.00 440.00 13.84 77.78 77.78 155.56 220.00 440.00 13.85 77.78 77.78 155.56 220.00 440.00 13.86 77.78 77.78 155.56 220.00 440.00 13.87 77.78 77.78 155.56 220.00 440.00 13.88 77.78 77.78 155.56 220.00 440.00 13.89 77.78 77.78 155.56 220.00 440.00 13.90 77.78 77.78 155.56 220.00 440.00 13.91 77.78 77.78 155.56 220.00 440.00 13.92 77.78 77.78 155.56 220.00 440.00 13.93 77.78 77.78 155.56 220.00 440.00 13.94 77.78 77.78 155.56 220.00 440.00 13.95 77.78 77.78 155.56 440.00 13.96 77.78 77.78 155.56 440.00 13.97 77.78 77.78 155.56 440.00 82.41 13.98 77.78 77.78 155.56 82.41 13.99 77.78 77.78 155.56 82.41 14.00 77.78 77.78 155.56 82.41 14.01 77.78 155.56 82.41 82.41 14.02 77.78 155.56 82.41 82.41 14.03 155.56 82.41 82.41 220.00 14.04 155.56 82.41 82.41 220.00 440.00 14.05 155.56 82.41 82.41 220.00 440.00 14.06 155.56 82.41 82.41 220.00 440.00 14.07 155.56 82.41 82.41 220.00 440.00 14.08 155.56 82.41 82.41 220.00 440.00 14.09 155.56 82.41 82.41 220.00 440.00 14.10 155.56 82.41 82.41 220.00 440.00 14.11 155.56 82.41 82.41 220.00 440.00 14.12 155.56 82.41 82.41 220.00 440.00 14.13 155.56 82.41 82.41 220.00 440.00 14.14 155.56 82.41 82.41 220.00 440.00 14.15 155.56 82.41 82.41 220.00 440.00 329.63 14.16 155.56 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.17 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.18 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.19 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.20 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.21 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.22 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.23 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.24 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.25 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.26 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.27 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.28 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.29 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.30 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.31 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.32 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.33 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.34 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.35 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.36 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.37 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.38 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.39 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.40 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.41 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.42 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.43 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.44 82.41 82.41 220.00 440.00 329.63 246.94 164.81 14.45 82.41 220.00 440.00 329.63 246.94 164.81 14.46 82.41 220.00 440.00 329.63 246.94 164.81 14.47 82.41 220.00 440.00 329.63 246.94 164.81 14.48 82.41 220.00 440.00 329.63 246.94 164.81 14.49 82.41 220.00 440.00 329.63 246.94 164.81 14.50 82.41 220.00 440.00 329.63 246.94 164.81 14.51 82.41 220.00 440.00 329.63 246.94 164.81 14.52 82.41 220.00 440.00 329.63 246.94 164.81 14.53 82.41 220.00 440.00 329.63 246.94 164.81 14.54 82.41 220.00 440.00 329.63 246.94 164.81 14.55 82.41 220.00 440.00 329.63 246.94 164.81 14.56 82.41 220.00 440.00 329.63 246.94 164.81 14.57 82.41 220.00 440.00 329.63 246.94 164.81 14.58 82.41 220.00 440.00 329.63 246.94 164.81 14.59 82.41 220.00 440.00 329.63 246.94 164.81 14.60 82.41 220.00 440.00 329.63 246.94 164.81 14.61 82.41 220.00 440.00 329.63 246.94 164.81 14.62 82.41 220.00 440.00 329.63 246.94 164.81 14.63 82.41 220.00 440.00 329.63 246.94 164.81 14.64 82.41 220.00 440.00 329.63 246.94 164.81 14.65 82.41 220.00 440.00 329.63 246.94 164.81 14.66 82.41 220.00 440.00 329.63 246.94 164.81 14.67 82.41 220.00 440.00 329.63 246.94 164.81 14.68 82.41 220.00 440.00 329.63 246.94 164.81 14.69 82.41 220.00 440.00 329.63 246.94 164.81 14.70 82.41 220.00 440.00 329.63 246.94 164.81 14.71 82.41 220.00 440.00 329.63 246.94 164.81 14.72 82.41 220.00 440.00 329.63 246.94 164.81 14.73 82.41 220.00 440.00 329.63 246.94 164.81 14.74 82.41 220.00 440.00 329.63 246.94 164.81 14.75 82.41 220.00 440.00 329.63 246.94 164.81 14.76 82.41 220.00 440.00 329.63 246.94 164.81 14.77 82.41 220.00 440.00 329.63 246.94 164.81 14.78 82.41 220.00 440.00 329.63 246.94 164.81 14.79 82.41 220.00 440.00 329.63 246.94 164.81 14.80 82.41 220.00 440.00 329.63 246.94 164.81 14.81 82.41 220.00 440.00 329.63 246.94 14.82 82.41 220.00 440.00 329.63 246.94 14.83 82.41 220.00 440.00 329.63 246.94 14.84 82.41 220.00 440.00 329.63 246.94 14.85 82.41 220.00 440.00 329.63 246.94 14.86 82.41 220.00 440.00 329.63 246.94 14.87 82.41 220.00 440.00 329.63 246.94 14.88 82.41 220.00 440.00 329.63 246.94 14.89 82.41 220.00 440.00 329.63 246.94 14.90 82.41 220.00 440.00 329.63 246.94 14.91 82.41 220.00 440.00 329.63 246.94 14.92 82.41 220.00 440.00 329.63 246.94 14.93 82.41 220.00 440.00 329.63 246.94 14.94 82.41 220.00 440.00 329.63 246.94 14.95 82.41 220.00 440.00 329.63 246.94 14.96 82.41 220.00 440.00 329.63 246.94 14.97 82.41 220.00 440.00 329.63 246.94 14.98 82.41 220.00 440.00 329.63 246.94 14.99 82.41 220.00 440.00 329.63 246.94 15.00 82.41 220.00 440.00 329.63 246.94 415.30 15.01 82.41 220.00 440.00 329.63 246.94 415.30 207.65 15.02 82.41 220.00 440.00 329.63 246.94 415.30 207.65 15.03 82.41 220.00 329.63 246.94 415.30 207.65 15.04 82.41 220.00 329.63 246.94 415.30 207.65 15.05 82.41 220.00 329.63 246.94 415.30 207.65 15.06 82.41 329.63 246.94 415.30 207.65 15.07 82.41 329.63 246.94 415.30 207.65 15.08 82.41 329.63 246.94 415.30 207.65 207.65 15.09 82.41 329.63 246.94 415.30 207.65 207.65 15.10 82.41 415.30 207.65 207.65 15.11 82.41 415.30 207.65 207.65 15.12 82.41 415.30 207.65 207.65 15.13 82.41 415.30 207.65 207.65 15.14 82.41 415.30 207.65 207.65 15.15 82.41 415.30 207.65 207.65 15.16 82.41 415.30 207.65 207.65 15.17 82.41 415.30 207.65 207.65 15.18 82.41 415.30 207.65 207.65 15.19 82.41 415.30 207.65 207.65 15.20 82.41 415.30 207.65 207.65 15.21 82.41 415.30 207.65 207.65 15.22 82.41 415.30 207.65 207.65 15.23 82.41 415.30 207.65 207.65 15.24 82.41 415.30 207.65 207.65 15.25 82.41 415.30 207.65 207.65 15.26 82.41 415.30 207.65 207.65 69.30 15.27 82.41 415.30 207.65 207.65 69.30 15.28 82.41 415.30 207.65 207.65 69.30 15.29 82.41 415.30 207.65 207.65 69.30 15.30 82.41 415.30 207.65 207.65 69.30 15.31 82.41 415.30 207.65 207.65 69.30 15.32 82.41 415.30 207.65 207.65 69.30 15.33 82.41 415.30 207.65 207.65 69.30 15.34 82.41 415.30 207.65 207.65 69.30 15.35 82.41 415.30 207.65 207.65 69.30 15.36 82.41 415.30 207.65 207.65 69.30 15.37 82.41 415.30 207.65 207.65 69.30 15.38 82.41 415.30 207.65 207.65 69.30 15.39 82.41 415.30 207.65 207.65 69.30 15.40 82.41 415.30 207.65 207.65 69.30 15.41 82.41 207.65 207.65 69.30 15.42 82.41 207.65 207.65 69.30 15.43 82.41 207.65 207.65 69.30 15.44 82.41 207.65 207.65 69.30 15.45 207.65 207.65 69.30 15.46 207.65 207.65 69.30 15.47 207.65 207.65 69.30 392.00 15.48 207.65 207.65 69.30 392.00 15.49 207.65 207.65 69.30 392.00 15.50 207.65 207.65 69.30 392.00 15.51 207.65 69.30 392.00 15.52 207.65 69.30 392.00 15.53 207.65 69.30 392.00 15.54 207.65 69.30 392.00 15.55 207.65 69.30 392.00 138.59 15.56 207.65 69.30 392.00 138.59 15.57 207.65 69.30 392.00 138.59 15.58 207.65 69.30 392.00 138.59 15.59 207.65 69.30 392.00 138.59 15.60 207.65 69.30 392.00 138.59 15.61 69.30 392.00 138.59 15.62 69.30 392.00 138.59 15.63 69.30 392.00 138.59 15.64 69.30 392.00 138.59 15.65 69.30 392.00 138.59 15.66 69.30 392.00 138.59 15.67 69.30 392.00 138.59 15.68 69.30 392.00 138.59 15.69 69.30 392.00 138.59 220.00 15.70 69.30 392.00 138.59 220.00 15.71 69.30 392.00 138.59 220.00 15.72 69.30 392.00 138.59 220.00 15.73 69.30 392.00 138.59 220.00 15.74 69.30 392.00 138.59 220.00 15.75 69.30 392.00 138.59 220.00 15.76 69.30 392.00 138.59 220.00 15.77 69.30 392.00 138.59 220.00 15.78 69.30 392.00 138.59 220.00 15.79 69.30 392.00 138.59 220.00 15.80 69.30 392.00 138.59 220.00 15.81 69.30 392.00 138.59 220.00 15.82 69.30 392.00 138.59 220.00 15.83 392.00 138.59 220.00 15.84 392.00 138.59 220.00 15.85 392.00 138.59 220.00 15.86 392.00 138.59 220.00 15.87 392.00 138.59 220.00 15.88 392.00 138.59 220.00 15.89 392.00 138.59 220.00 15.90 392.00 138.59 220.00 329.63 15.91 392.00 138.59 220.00 329.63 15.92 392.00 138.59 220.00 329.63 15.93 392.00 138.59 329.63 15.94 392.00 138.59 329.63 15.95 392.00 138.59 329.63 15.96 392.00 138.59 329.63 15.97 392.00 138.59 329.63 15.98 392.00 138.59 329.63 15.99 392.00 138.59 329.63 16.00 392.00 138.59 329.63 16.01 392.00 138.59 329.63 16.02 392.00 138.59 329.63 16.03 392.00 138.59 329.63 16.04 392.00 138.59 329.63 16.05 392.00 138.59 329.63 16.06 392.00 138.59 329.63 16.07 392.00 138.59 329.63 16.08 392.00 138.59 329.63 392.00 16.09 392.00 138.59 392.00 16.10 392.00 138.59 392.00 16.11 392.00 138.59 392.00 466.16 16.12 138.59 392.00 466.16 16.13 138.59 392.00 466.16 16.14 138.59 392.00 466.16 16.15 138.59 392.00 466.16 16.16 138.59 392.00 466.16 16.17 138.59 392.00 466.16 16.18 138.59 392.00 466.16 16.19 138.59 392.00 466.16 16.20 138.59 392.00 466.16 16.21 138.59 392.00 466.16 16.22 138.59 392.00 466.16 16.23 138.59 392.00 466.16 16.24 138.59 392.00 466.16 16.25 138.59 392.00 466.16 16.26 138.59 392.00 466.16 16.27 138.59 392.00 466.16 16.28 138.59 392.00 466.16 16.29 138.59 392.00 466.16 16.30 138.59 392.00 466.16 440.00 440.00 16.31 138.59 466.16 440.00 440.00 16.32 138.59 466.16 440.00 440.00 16.33 138.59 466.16 440.00 440.00 16.34 138.59 440.00 440.00 16.35 138.59 440.00 440.00 16.36 138.59 440.00 440.00 16.37 138.59 440.00 440.00 16.38 138.59 440.00 440.00 16.39 138.59 440.00 440.00 16.40 138.59 440.00 440.00 16.41 138.59 440.00 440.00 16.42 138.59 440.00 440.00 16.43 138.59 440.00 440.00 16.44 138.59 440.00 440.00 16.45 138.59 440.00 440.00 16.46 138.59 440.00 440.00 16.47 138.59 440.00 440.00 16.48 138.59 440.00 16.49 138.59 440.00 392.00 16.50 138.59 440.00 392.00 220.00 16.51 138.59 440.00 392.00 220.00 16.52 138.59 440.00 392.00 220.00 16.53 138.59 392.00 220.00 16.54 138.59 392.00 220.00 16.55 138.59 392.00 220.00 16.56 138.59 392.00 220.00 16.57 138.59 392.00 220.00 16.58 138.59 392.00 220.00 16.59 138.59 392.00 220.00 16.60 138.59 220.00 16.61 138.59 220.00 73.42 16.62 138.59 220.00 73.42 16.63 138.59 220.00 73.42 16.64 138.59 220.00 73.42 16.65 138.59 220.00 73.42 146.83 16.66 138.59 220.00 73.42 146.83 16.67 138.59 220.00 73.42 146.83 16.68 138.59 220.00 73.42 146.83 392.00 16.69 138.59 220.00 73.42 146.83 392.00 16.70 138.59 220.00 73.42 146.83 392.00 16.71 220.00 73.42 146.83 392.00 16.72 220.00 73.42 146.83 392.00 16.73 73.42 146.83 392.00 16.74 73.42 146.83 392.00 16.75 73.42 146.83 392.00 16.76 73.42 146.83 392.00 16.77 73.42 146.83 392.00 16.78 73.42 146.83 392.00 16.79 73.42 146.83 392.00 16.80 73.42 146.83 392.00 16.81 73.42 146.83 392.00 16.82 73.42 146.83 392.00 16.83 73.42 146.83 392.00 16.84 73.42 146.83 392.00 220.00 16.85 73.42 146.83 392.00 220.00 16.86 73.42 146.83 392.00 220.00 16.87 73.42 146.83 392.00 220.00 16.88 73.42 146.83 392.00 220.00 369.99 16.89 73.42 146.83 392.00 220.00 369.99 16.90 73.42 146.83 220.00 369.99 16.91 73.42 146.83 220.00 369.99 16.92 73.42 146.83 220.00 369.99 16.93 73.42 146.83 220.00 369.99 16.94 73.42 146.83 220.00 369.99 16.95 73.42 146.83 220.00 369.99 16.96 73.42 146.83 220.00 369.99 16.97 73.42 146.83 220.00 369.99 16.98 73.42 146.83 220.00 369.99 16.99 73.42 146.83 220.00 369.99 17.00 73.42 146.83 220.00 369.99 17.01 73.42 146.83 220.00 369.99 17.02 73.42 146.83 220.00 369.99 17.03 146.83 369.99 17.04 146.83 369.99 17.05 146.83 369.99 17.06 146.83 369.99 17.07 146.83 369.99 293.66 17.08 146.83 369.99 293.66 17.09 146.83 369.99 293.66 587.33 17.10 146.83 369.99 293.66 587.33 17.11 146.83 369.99 293.66 587.33 17.12 146.83 293.66 587.33 17.13 146.83 293.66 587.33 17.14 146.83 293.66 587.33 17.15 146.83 293.66 587.33 17.16 146.83 293.66 587.33 17.17 146.83 293.66 587.33 17.18 146.83 293.66 587.33 17.19 146.83 293.66 587.33 17.20 146.83 293.66 587.33 17.21 146.83 293.66 587.33 17.22 146.83 293.66 587.33 17.23 146.83 293.66 587.33 17.24 146.83 293.66 587.33 17.25 146.83 293.66 587.33 17.26 146.83 587.33 17.27 146.83 587.33 17.28 146.83 587.33 17.29 146.83 587.33 17.30 146.83 587.33 17.31 146.83 587.33 17.32 146.83 587.33 369.99 17.33 146.83 587.33 369.99 17.34 146.83 587.33 369.99 17.35 146.83 587.33 369.99 17.36 146.83 587.33 369.99 17.37 146.83 587.33 369.99 17.38 146.83 587.33 369.99 17.39 146.83 587.33 369.99 17.40 146.83 587.33 369.99 17.41 146.83 587.33 369.99 17.42 146.83 587.33 369.99 17.43 146.83 587.33 369.99 17.44 146.83 587.33 369.99 17.45 146.83 587.33 369.99 17.46 146.83 587.33 369.99 17.47 146.83 587.33 369.99 17.48 146.83 587.33 369.99 17.49 146.83 587.33 369.99 17.50 146.83 587.33 369.99 440.00 17.51 146.83 587.33 369.99 440.00 17.52 146.83 587.33 369.99 440.00 17.53 146.83 587.33 440.00 17.54 146.83 587.33 440.00 17.55 146.83 587.33 440.00 17.56 146.83 587.33 440.00 17.57 146.83 587.33 440.00 17.58 146.83 587.33 440.00 17.59 146.83 587.33 440.00 17.60 146.83 587.33 440.00 17.61 146.83 587.33 440.00 17.62 146.83 587.33 440.00 17.63 146.83 587.33 440.00 17.64 146.83 587.33 440.00 17.65 146.83 587.33 440.00 17.66 146.83 587.33 440.00 17.67 146.83 587.33 440.00 17.68 146.83 587.33 440.00 17.69 146.83 587.33 220.00 17.70 146.83 587.33 220.00 17.71 146.83 587.33 220.00 17.72 146.83 587.33 220.00 17.73 146.83 587.33 220.00 17.74 146.83 587.33 220.00 61.74 17.75 146.83 587.33 220.00 61.74 17.76 146.83 587.33 220.00 61.74 17.77 146.83 587.33 220.00 61.74 17.78 146.83 587.33 220.00 61.74 17.79 146.83 587.33 220.00 61.74 17.80 146.83 587.33 220.00 61.74 17.81 146.83 587.33 220.00 61.74 17.82 146.83 587.33 220.00 61.74 17.83 146.83 587.33 220.00 61.74 17.84 146.83 587.33 220.00 61.74 123.47 17.85 146.83 587.33 220.00 61.74 123.47 17.86 146.83 587.33 220.00 61.74 123.47 17.87 146.83 587.33 220.00 61.74 123.47 17.88 587.33 220.00 61.74 123.47 17.89 587.33 220.00 61.74 123.47 17.90 587.33 220.00 61.74 123.47 17.91 587.33 220.00 61.74 123.47 17.92 587.33 220.00 61.74 123.47 17.93 587.33 220.00 61.74 123.47 17.94 587.33 220.00 61.74 123.47 17.95 587.33 220.00 61.74 123.47 17.96 587.33 61.74 123.47 17.97 61.74 123.47 17.98 61.74 123.47 17.99 61.74 123.47 18.00 61.74 123.47 18.01 61.74 123.47 18.02 61.74 123.47 18.03 61.74 123.47 18.04 61.74 123.47 18.05 61.74 123.47 18.06 61.74 123.47 18.07 61.74 123.47 18.08 61.74 123.47 18.09 61.74 123.47 329.63 18.10 61.74 123.47 329.63 18.11 61.74 123.47 329.63 196.00 18.12 61.74 123.47 329.63 196.00 18.13 61.74 123.47 329.63 196.00 18.14 61.74 123.47 329.63 196.00 18.15 61.74 123.47 329.63 196.00 18.16 61.74 123.47 329.63 196.00 18.17 61.74 123.47 329.63 196.00 18.18 123.47 329.63 196.00 18.19 123.47 329.63 196.00 18.20 123.47 329.63 196.00 18.21 123.47 329.63 196.00 18.22 123.47 329.63 196.00 18.23 123.47 329.63 196.00 18.24 123.47 329.63 196.00 18.25 123.47 329.63 196.00 18.26 123.47 329.63 196.00 18.27 123.47 329.63 196.00 18.28 123.47 329.63 196.00 18.29 123.47 329.63 196.00 349.23 18.30 123.47 329.63 196.00 349.23 293.66 18.31 123.47 329.63 196.00 349.23 293.66 18.32 123.47 329.63 196.00 349.23 293.66 18.33 123.47 329.63 349.23 293.66 18.34 123.47 329.63 349.23 293.66 18.35 123.47 329.63 349.23 293.66 18.36 123.47 329.63 349.23 293.66 18.37 123.47 329.63 349.23 293.66 18.38 123.47 329.63 349.23 293.66 18.39 123.47 329.63 349.23 293.66 18.40 123.47 329.63 349.23 293.66 18.41 123.47 329.63 349.23 293.66 18.42 123.47 349.23 293.66 18.43 123.47 349.23 293.66 18.44 123.47 349.23 293.66 18.45 123.47 349.23 293.66 18.46 123.47 349.23 293.66 18.47 123.47 349.23 293.66 18.48 123.47 293.66 440.00 18.49 123.47 293.66 440.00 18.50 123.47 293.66 440.00 349.23 18.51 123.47 293.66 440.00 349.23 18.52 123.47 440.00 349.23 18.53 123.47 440.00 349.23 18.54 123.47 440.00 349.23 18.55 123.47 440.00 349.23 18.56 123.47 440.00 349.23 18.57 123.47 440.00 349.23 18.58 123.47 440.00 349.23 18.59 123.47 440.00 349.23 18.60 123.47 440.00 349.23 18.61 123.47 440.00 349.23 18.62 123.47 440.00 349.23 18.63 123.47 440.00 349.23 18.64 123.47 440.00 349.23 18.65 123.47 440.00 349.23 18.66 123.47 440.00 349.23 18.67 123.47 440.00 349.23 392.00 18.68 123.47 440.00 349.23 392.00 18.69 123.47 440.00 349.23 392.00 18.70 123.47 440.00 349.23 392.00 18.71 123.47 349.23 392.00 18.72 123.47 349.23 392.00 18.73 123.47 349.23 392.00 392.00 18.74 123.47 349.23 392.00 392.00 18.75 123.47 349.23 392.00 392.00 18.76 123.47 392.00 392.00 18.77 123.47 392.00 392.00 18.78 123.47 392.00 392.00 18.79 123.47 392.00 392.00 18.80 123.47 392.00 392.00 18.81 123.47 392.00 392.00 18.82 123.47 392.00 392.00 18.83 123.47 392.00 392.00 18.84 123.47 392.00 392.00 18.85 123.47 392.00 392.00 18.86 123.47 392.00 392.00 18.87 123.47 392.00 392.00 349.23 18.88 123.47 392.00 392.00 349.23 18.89 123.47 392.00 392.00 349.23 18.90 123.47 392.00 349.23 18.91 123.47 392.00 349.23 196.00 18.92 123.47 349.23 196.00 18.93 123.47 349.23 196.00 18.94 123.47 349.23 196.00 18.95 123.47 349.23 196.00 18.96 123.47 349.23 196.00 18.97 123.47 349.23 196.00 18.98 123.47 349.23 196.00 18.99 123.47 349.23 196.00 19.00 123.47 196.00 19.01 123.47 196.00 19.02 123.47 196.00 19.03 123.47 196.00 19.04 123.47 196.00 130.81 19.05 123.47 196.00 130.81 65.41 19.06 123.47 196.00 130.81 65.41 19.07 123.47 196.00 130.81 65.41 349.23 19.08 123.47 196.00 130.81 65.41 349.23 19.09 123.47 196.00 130.81 65.41 349.23 19.10 123.47 130.81 65.41 349.23 19.11 130.81 65.41 349.23 19.12 130.81 65.41 349.23 19.13 130.81 65.41 349.23 19.14 130.81 65.41 349.23 19.15 130.81 65.41 349.23 19.16 130.81 65.41 349.23 19.17 130.81 65.41 349.23 19.18 130.81 65.41 349.23 19.19 130.81 65.41 349.23 19.20 130.81 65.41 349.23 19.21 130.81 65.41 349.23 19.22 130.81 65.41 349.23 19.23 130.81 65.41 349.23 19.24 130.81 65.41 349.23 19.25 130.81 65.41 349.23 19.26 130.81 65.41 349.23 19.27 130.81 65.41 329.63 19.28 130.81 65.41 329.63 19.29 130.81 65.41 329.63 19.30 130.81 65.41 329.63 196.00 19.31 130.81 65.41 329.63 196.00 19.32 130.81 65.41 329.63 196.00 19.33 130.81 65.41 329.63 196.00 19.34 130.81 65.41 329.63 196.00 19.35 130.81 65.41 329.63 196.00 19.36 130.81 65.41 329.63 196.00 19.37 130.81 65.41 329.63 196.00 19.38 130.81 65.41 329.63 196.00 19.39 130.81 65.41 329.63 196.00 19.40 130.81 65.41 329.63 196.00 19.41 130.81 65.41 329.63 196.00 19.42 130.81 65.41 329.63 196.00 19.43 130.81 65.41 329.63 196.00 19.44 130.81 65.41 329.63 196.00 19.45 130.81 65.41 329.63 196.00 19.46 130.81 65.41 329.63 196.00 19.47 130.81 65.41 329.63 196.00 19.48 130.81 329.63 196.00 19.49 130.81 329.63 196.00 19.50 130.81 196.00 261.63 19.51 130.81 196.00 261.63 523.25 19.52 130.81 196.00 261.63 523.25 19.53 130.81 196.00 261.63 523.25 19.54 130.81 196.00 261.63 523.25 19.55 130.81 261.63 523.25 19.56 130.81 261.63 523.25 19.57 130.81 261.63 523.25 19.58 130.81 261.63 523.25 19.59 130.81 261.63 523.25 19.60 130.81 261.63 523.25 19.61 130.81 261.63 523.25 19.62 130.81 261.63 523.25 19.63 130.81 261.63 523.25 19.64 130.81 261.63 523.25 19.65 130.81 261.63 523.25 19.66 130.81 261.63 523.25 19.67 130.81 261.63 523.25 19.68 130.81 261.63 523.25 19.69 130.81 261.63 523.25 19.70 130.81 261.63 523.25 329.63 19.71 130.81 261.63 523.25 329.63 19.72 130.81 261.63 523.25 329.63 19.73 130.81 523.25 329.63 19.74 130.81 523.25 329.63 19.75 130.81 523.25 329.63 19.76 130.81 523.25 329.63 19.77 130.81 523.25 329.63 19.78 130.81 523.25 329.63 19.79 130.81 523.25 329.63 19.80 130.81 523.25 329.63 19.81 130.81 523.25 329.63 19.82 130.81 523.25 329.63 19.83 130.81 523.25 329.63 19.84 130.81 523.25 329.63 19.85 130.81 523.25 329.63 19.86 130.81 523.25 329.63 19.87 130.81 523.25 329.63 19.88 130.81 523.25 329.63 19.89 130.81 523.25 329.63 392.00 19.90 130.81 523.25 329.63 392.00 19.91 130.81 523.25 392.00 19.92 130.81 523.25 392.00 19.93 130.81 523.25 392.00 19.94 130.81 523.25 392.00 19.95 130.81 523.25 392.00 19.96 130.81 523.25 392.00 19.97 130.81 523.25 392.00 19.98 130.81 523.25 392.00 19.99 130.81 523.25 392.00 20.00 130.81 523.25 392.00 20.01 130.81 523.25 392.00 20.02 130.81 523.25 392.00 20.03 130.81 523.25 392.00 20.04 130.81 523.25 392.00 20.05 130.81 523.25 392.00 20.06 130.81 523.25 392.00 20.07 130.81 523.25 392.00 20.08 130.81 523.25 196.00 20.09 130.81 523.25 196.00 20.10 130.81 523.25 196.00 20.11 130.81 523.25 196.00 20.12 130.81 523.25 196.00 20.13 130.81 523.25 196.00 20.14 130.81 523.25 196.00 20.15 130.81 523.25 196.00 20.16 130.81 523.25 196.00 20.17 130.81 523.25 196.00 20.18 130.81 523.25 196.00 20.19 130.81 523.25 196.00 20.20 130.81 523.25 196.00 20.21 130.81 523.25 196.00 20.22 130.81 523.25 196.00 20.23 130.81 523.25 196.00 103.83 20.24 523.25 196.00 103.83 103.83 20.25 523.25 103.83 103.83 20.26 523.25 103.83 103.83 20.27 523.25 103.83 103.83 20.28 523.25 103.83 103.83 20.29 523.25 103.83 103.83 329.63 20.30 523.25 103.83 103.83 329.63 20.31 523.25 103.83 103.83 329.63 20.32 523.25 103.83 103.83 329.63 20.33 523.25 103.83 103.83 329.63 20.34 523.25 103.83 103.83 329.63 20.35 103.83 103.83 329.63 20.36 103.83 103.83 329.63 20.37 103.83 103.83 329.63 20.38 103.83 103.83 329.63 20.39 103.83 103.83 329.63 20.40 103.83 103.83 329.63 20.41 103.83 103.83 329.63 20.42 103.83 103.83 329.63 20.43 103.83 103.83 329.63 20.44 103.83 103.83 329.63 20.45 103.83 103.83 329.63 20.46 103.83 103.83 329.63 20.47 103.83 103.83 329.63 20.48 103.83 103.83 329.63 20.49 103.83 103.83 329.63 246.94 20.50 103.83 103.83 329.63 246.94 20.51 103.83 103.83 329.63 246.94 20.52 103.83 103.83 329.63 246.94 20.53 103.83 103.83 329.63 246.94 20.54 103.83 103.83 329.63 246.94 20.55 103.83 103.83 329.63 246.94 20.56 103.83 103.83 329.63 246.94 20.57 103.83 103.83 329.63 246.94 20.58 103.83 103.83 329.63 246.94 20.59 103.83 103.83 329.63 246.94 20.60 103.83 103.83 329.63 246.94 20.61 103.83 103.83 329.63 246.94 20.62 103.83 103.83 329.63 246.94 20.63 103.83 103.83 329.63 246.94 20.64 103.83 103.83 329.63 246.94 20.65 103.83 329.63 246.94 20.66 103.83 329.63 246.94 20.67 103.83 329.63 246.94 20.68 103.83 329.63 246.94 20.69 103.83 329.63 246.94 293.66 20.70 103.83 329.63 246.94 293.66 20.71 103.83 329.63 246.94 293.66 20.72 103.83 329.63 293.66 20.73 103.83 329.63 293.66 20.74 103.83 329.63 293.66 20.75 103.83 329.63 293.66 20.76 103.83 329.63 293.66 20.77 103.83 329.63 293.66 20.78 103.83 329.63 293.66 20.79 103.83 329.63 293.66 20.80 103.83 329.63 293.66 20.81 103.83 329.63 293.66 20.82 103.83 329.63 293.66 20.83 103.83 329.63 293.66 20.84 103.83 329.63 293.66 20.85 103.83 329.63 293.66 20.86 103.83 329.63 293.66 20.87 103.83 329.63 293.66 20.88 103.83 329.63 293.66 329.63 20.89 103.83 329.63 293.66 329.63 20.90 103.83 329.63 293.66 329.63 20.91 103.83 329.63 329.63 349.23 20.92 103.83 329.63 349.23 20.93 103.83 329.63 349.23 20.94 103.83 329.63 349.23 20.95 103.83 329.63 349.23 20.96 103.83 329.63 349.23 20.97 103.83 329.63 349.23 20.98 103.83 329.63 349.23 20.99 103.83 329.63 349.23 21.00 103.83 329.63 349.23 21.01 103.83 329.63 349.23 21.02 103.83 329.63 349.23 21.03 103.83 349.23 21.04 103.83 349.23 21.05 103.83 349.23 493.88 21.06 103.83 349.23 493.88 21.07 103.83 349.23 493.88 21.08 103.83 349.23 493.88 21.09 103.83 349.23 493.88 21.10 103.83 349.23 493.88 21.11 103.83 349.23 493.88 21.12 103.83 349.23 493.88 329.63 21.13 103.83 349.23 493.88 329.63 21.14 103.83 349.23 493.88 329.63 21.15 103.83 349.23 493.88 329.63 21.16 103.83 493.88 329.63 21.17 103.83 493.88 329.63 21.18 103.83 493.88 329.63 21.19 103.83 493.88 329.63 21.20 103.83 493.88 329.63 21.21 103.83 493.88 329.63 21.22 103.83 493.88 329.63 21.23 103.83 493.88 329.63 21.24 103.83 493.88 329.63 21.25 103.83 493.88 329.63 246.94 21.26 103.83 493.88 329.63 246.94 21.27 103.83 493.88 329.63 246.94 21.28 103.83 329.63 246.94 21.29 103.83 329.63 246.94 293.66 21.30 103.83 329.63 246.94 293.66 21.31 103.83 246.94 293.66 21.32 103.83 246.94 293.66 21.33 103.83 246.94 293.66 21.34 103.83 246.94 293.66 21.35 103.83 246.94 293.66 21.36 103.83 246.94 293.66 21.37 103.83 246.94 293.66 21.38 103.83 246.94 293.66 21.39 103.83 246.94 293.66 21.40 103.83 246.94 293.66 21.41 103.83 246.94 293.66 21.42 103.83 246.94 21.43 103.83 246.94 110.00 21.44 103.83 246.94 110.00 21.45 103.83 110.00 110.00 21.46 103.83 110.00 110.00 21.47 103.83 110.00 110.00 21.48 103.83 110.00 110.00 21.49 110.00 110.00 293.66 21.50 110.00 110.00 293.66 21.51 110.00 110.00 293.66 21.52 110.00 110.00 293.66 21.53 110.00 110.00 293.66 21.54 110.00 110.00 293.66 21.55 110.00 110.00 293.66 21.56 110.00 110.00 293.66 21.57 110.00 110.00 293.66 21.58 110.00 110.00 293.66 21.59 110.00 110.00 293.66 21.60 110.00 110.00 293.66 21.61 110.00 110.00 293.66 21.62 110.00 110.00 293.66 21.63 110.00 110.00 293.66 21.64 110.00 110.00 293.66 21.65 110.00 110.00 293.66 21.66 110.00 110.00 293.66 261.63 21.67 110.00 110.00 293.66 261.63 21.68 110.00 110.00 293.66 261.63 21.69 110.00 110.00 261.63 21.70 110.00 110.00 261.63 261.63 21.71 110.00 110.00 261.63 261.63 21.72 110.00 110.00 261.63 261.63 21.73 110.00 110.00 261.63 261.63 21.74 110.00 110.00 261.63 261.63 21.75 110.00 110.00 261.63 261.63 21.76 110.00 110.00 261.63 261.63 21.77 110.00 110.00 261.63 261.63 21.78 110.00 110.00 261.63 261.63 21.79 110.00 110.00 261.63 261.63 21.80 110.00 110.00 261.63 261.63 21.81 110.00 110.00 261.63 261.63 21.82 110.00 110.00 261.63 261.63 21.83 110.00 110.00 261.63 261.63 21.84 110.00 261.63 261.63 21.85 110.00 261.63 261.63 21.86 110.00 261.63 261.63 21.87 110.00 261.63 261.63 21.88 110.00 261.63 261.63 329.63 21.89 110.00 261.63 261.63 329.63 329.63 21.90 110.00 261.63 261.63 329.63 329.63 21.91 110.00 261.63 261.63 329.63 329.63 21.92 110.00 261.63 329.63 329.63 21.93 110.00 329.63 329.63 21.94 110.00 329.63 329.63 21.95 110.00 329.63 329.63 21.96 110.00 329.63 329.63 21.97 110.00 329.63 329.63 21.98 110.00 329.63 329.63 21.99 110.00 329.63 329.63 22.00 110.00 329.63 329.63 22.01 110.00 329.63 329.63 22.02 110.00 329.63 329.63 22.03 110.00 329.63 329.63 22.04 110.00 329.63 329.63 22.05 110.00 329.63 329.63 22.06 110.00 329.63 329.63 22.07 110.00 329.63 329.63 440.00 22.08 110.00 329.63 440.00 22.09 110.00 329.63 440.00 22.10 110.00 329.63 440.00 415.30 22.11 110.00 329.63 440.00 415.30 22.12 110.00 440.00 415.30 22.13 110.00 440.00 415.30 22.14 110.00 440.00 415.30 22.15 110.00 440.00 415.30 22.16 110.00 440.00 415.30 22.17 110.00 440.00 415.30 22.18 110.00 440.00 415.30 22.19 110.00 440.00 415.30 22.20 110.00 440.00 415.30 22.21 110.00 440.00 415.30 22.22 110.00 440.00 415.30 22.23 110.00 440.00 415.30 22.24 110.00 440.00 415.30 22.25 110.00 440.00 415.30 22.26 110.00 415.30 523.25 22.27 110.00 415.30 523.25 440.00 22.28 110.00 523.25 440.00 22.29 110.00 523.25 440.00 22.30 110.00 523.25 440.00 22.31 110.00 523.25 440.00 22.32 110.00 523.25 440.00 22.33 110.00 523.25 440.00 22.34 110.00 523.25 440.00 22.35 110.00 523.25 440.00 22.36 110.00 523.25 440.00 22.37 110.00 523.25 440.00 22.38 110.00 523.25 440.00 22.39 110.00 523.25 440.00 22.40 110.00 523.25 440.00 22.41 110.00 523.25 440.00 22.42 110.00 523.25 440.00 22.43 110.00 523.25 440.00 22.44 110.00 440.00 523.25 22.45 110.00 440.00 523.25 261.63 22.46 110.00 440.00 523.25 261.63 22.47 110.00 440.00 523.25 261.63 22.48 110.00 523.25 261.63 22.49 110.00 523.25 261.63 22.50 110.00 523.25 261.63 22.51 110.00 523.25 261.63 22.52 110.00 523.25 261.63 22.53 110.00 523.25 261.63 22.54 110.00 523.25 261.63 22.55 110.00 523.25 261.63 22.56 110.00 523.25 261.63 22.57 110.00 523.25 261.63 22.58 110.00 523.25 261.63 22.59 110.00 523.25 261.63 103.83 22.60 110.00 523.25 261.63 103.83 22.61 110.00 523.25 261.63 103.83 659.26 22.62 110.00 523.25 261.63 103.83 659.26 103.83 22.63 523.25 261.63 103.83 659.26 103.83 22.64 523.25 261.63 103.83 659.26 103.83 22.65 523.25 103.83 659.26 103.83 22.66 523.25 103.83 659.26 103.83 22.67 523.25 103.83 659.26 103.83 493.88 22.68 523.25 103.83 659.26 103.83 493.88 22.69 103.83 659.26 103.83 493.88 207.65 22.70 103.83 659.26 103.83 493.88 207.65 22.71 103.83 659.26 103.83 493.88 207.65 22.72 103.83 659.26 103.83 493.88 207.65 22.73 103.83 659.26 103.83 493.88 207.65 22.74 103.83 659.26 103.83 493.88 207.65 22.75 103.83 659.26 103.83 493.88 207.65 22.76 103.83 659.26 103.83 493.88 207.65 22.77 103.83 659.26 103.83 493.88 207.65 22.78 103.83 659.26 103.83 493.88 207.65 22.79 103.83 659.26 103.83 493.88 207.65 22.80 103.83 659.26 103.83 493.88 207.65 22.81 103.83 659.26 103.83 493.88 207.65 22.82 103.83 659.26 103.83 493.88 207.65 22.83 103.83 659.26 103.83 493.88 207.65 246.94 22.84 103.83 659.26 103.83 493.88 207.65 246.94 22.85 103.83 659.26 103.83 493.88 207.65 246.94 22.86 103.83 659.26 103.83 493.88 207.65 246.94 22.87 103.83 659.26 103.83 493.88 207.65 246.94 22.88 103.83 659.26 103.83 493.88 207.65 246.94 22.89 103.83 659.26 103.83 493.88 207.65 246.94 22.90 103.83 659.26 103.83 493.88 207.65 246.94 22.91 103.83 659.26 103.83 493.88 207.65 246.94 22.92 103.83 659.26 103.83 493.88 207.65 246.94 22.93 103.83 659.26 103.83 493.88 207.65 246.94 22.94 103.83 659.26 103.83 493.88 207.65 246.94 22.95 103.83 659.26 103.83 493.88 207.65 246.94 22.96 103.83 659.26 103.83 493.88 207.65 246.94 22.97 103.83 659.26 103.83 493.88 207.65 246.94 22.98 103.83 659.26 103.83 493.88 207.65 246.94 22.99 103.83 659.26 103.83 493.88 207.65 246.94 23.00 103.83 659.26 103.83 493.88 207.65 246.94 23.01 103.83 659.26 103.83 493.88 207.65 246.94 23.02 659.26 103.83 493.88 207.65 246.94 293.66 23.03 659.26 103.83 493.88 207.65 246.94 293.66 23.04 659.26 103.83 493.88 207.65 246.94 293.66 23.05 659.26 103.83 493.88 207.65 293.66 23.06 659.26 103.83 493.88 207.65 293.66 23.07 659.26 103.83 493.88 207.65 293.66 23.08 659.26 103.83 493.88 207.65 293.66 23.09 659.26 103.83 493.88 207.65 293.66 23.10 659.26 103.83 493.88 207.65 293.66 23.11 659.26 103.83 493.88 207.65 293.66 23.12 659.26 103.83 493.88 207.65 293.66 23.13 659.26 103.83 493.88 207.65 293.66 23.14 659.26 103.83 493.88 207.65 293.66 23.15 659.26 103.83 493.88 207.65 293.66 23.16 659.26 103.83 493.88 207.65 293.66 23.17 659.26 103.83 493.88 207.65 293.66 698.46 23.18 659.26 103.83 493.88 207.65 293.66 698.46 23.19 659.26 103.83 493.88 207.65 293.66 698.46 23.20 659.26 103.83 493.88 207.65 293.66 698.46 23.21 103.83 493.88 207.65 293.66 698.46 23.22 103.83 493.88 207.65 293.66 698.46 329.63 23.23 103.83 493.88 207.65 293.66 698.46 329.63 23.24 103.83 493.88 207.65 698.46 329.63 23.25 103.83 493.88 207.65 698.46 329.63 23.26 103.83 493.88 207.65 698.46 329.63 23.27 103.83 493.88 207.65 698.46 329.63 23.28 103.83 493.88 207.65 698.46 329.63 23.29 103.83 493.88 207.65 698.46 329.63 23.30 103.83 493.88 207.65 698.46 329.63 23.31 103.83 493.88 207.65 698.46 329.63 23.32 103.83 493.88 207.65 698.46 329.63 23.33 103.83 493.88 207.65 698.46 329.63 23.34 103.83 493.88 207.65 698.46 329.63 23.35 103.83 493.88 207.65 698.46 329.63 23.36 103.83 493.88 207.65 698.46 329.63 23.37 103.83 493.88 207.65 698.46 329.63 23.38 103.83 493.88 207.65 698.46 23.39 103.83 493.88 207.65 659.26 23.40 103.83 493.88 207.65 659.26 23.41 103.83 493.88 207.65 659.26 493.88 23.42 103.83 493.88 207.65 659.26 493.88 23.43 103.83 493.88 207.65 659.26 493.88 23.44 103.83 493.88 207.65 659.26 493.88 23.45 103.83 493.88 207.65 659.26 493.88 23.46 103.83 493.88 207.65 659.26 493.88 23.47 103.83 493.88 207.65 659.26 493.88 23.48 103.83 493.88 207.65 659.26 493.88 23.49 103.83 493.88 207.65 659.26 493.88 23.50 103.83 493.88 207.65 659.26 493.88 23.51 103.83 493.88 207.65 659.26 493.88 23.52 103.83 493.88 207.65 659.26 493.88 23.53 103.83 493.88 207.65 659.26 493.88 23.54 103.83 493.88 207.65 659.26 493.88 23.55 103.83 493.88 207.65 659.26 493.88 23.56 103.83 493.88 207.65 659.26 493.88 23.57 103.83 493.88 207.65 659.26 493.88 587.33 23.58 103.83 493.88 207.65 659.26 493.88 587.33 23.59 103.83 493.88 207.65 659.26 493.88 587.33 23.60 103.83 493.88 207.65 493.88 587.33 246.94 23.61 103.83 493.88 207.65 493.88 587.33 246.94 23.62 103.83 493.88 207.65 493.88 587.33 246.94 23.63 103.83 493.88 207.65 493.88 587.33 246.94 23.64 103.83 493.88 207.65 587.33 246.94 23.65 103.83 493.88 207.65 587.33 246.94 23.66 103.83 493.88 207.65 587.33 246.94 23.67 103.83 493.88 207.65 587.33 246.94 23.68 103.83 493.88 207.65 587.33 246.94 23.69 103.83 493.88 207.65 587.33 246.94 23.70 103.83 493.88 207.65 246.94 23.71 103.83 493.88 207.65 246.94 23.72 103.83 493.88 207.65 246.94 23.73 103.83 493.88 207.65 246.94 23.74 103.83 493.88 207.65 246.94 23.75 103.83 493.88 207.65 246.94 23.76 103.83 493.88 207.65 246.94 23.77 103.83 493.88 207.65 246.94 110.00 110.00 23.78 103.83 493.88 207.65 246.94 110.00 110.00 587.33 23.79 103.83 493.88 207.65 246.94 110.00 110.00 587.33 220.00 23.80 207.65 246.94 110.00 110.00 587.33 220.00 23.81 246.94 110.00 110.00 587.33 220.00 23.82 110.00 110.00 587.33 220.00 23.83 110.00 110.00 587.33 220.00 23.84 110.00 110.00 587.33 220.00 23.85 110.00 110.00 587.33 220.00 23.86 110.00 110.00 587.33 220.00 23.87 110.00 110.00 587.33 220.00 23.88 110.00 110.00 587.33 220.00 23.89 110.00 110.00 587.33 220.00 23.90 110.00 110.00 587.33 220.00 23.91 110.00 110.00 587.33 220.00 23.92 110.00 110.00 587.33 220.00 329.63 23.93 110.00 110.00 587.33 220.00 329.63 23.94 110.00 110.00 587.33 220.00 329.63 23.95 110.00 110.00 587.33 220.00 329.63 23.96 110.00 110.00 220.00 329.63 23.97 110.00 110.00 220.00 329.63 523.25 23.98 110.00 110.00 220.00 329.63 523.25 23.99 110.00 110.00 220.00 329.63 523.25 261.63 24.00 110.00 110.00 220.00 329.63 523.25 261.63 24.01 110.00 110.00 220.00 329.63 523.25 261.63 24.02 110.00 110.00 220.00 329.63 523.25 261.63 24.03 110.00 110.00 220.00 329.63 523.25 261.63 24.04 110.00 110.00 220.00 329.63 523.25 261.63 24.05 110.00 110.00 220.00 329.63 523.25 261.63 24.06 110.00 110.00 220.00 329.63 523.25 261.63 24.07 110.00 110.00 220.00 329.63 523.25 261.63 24.08 110.00 110.00 220.00 329.63 523.25 261.63 24.09 110.00 110.00 220.00 329.63 523.25 261.63 24.10 110.00 110.00 220.00 329.63 523.25 261.63 24.11 110.00 110.00 220.00 329.63 523.25 261.63 24.12 110.00 110.00 220.00 329.63 523.25 261.63 24.13 110.00 110.00 220.00 329.63 523.25 261.63 24.14 110.00 110.00 220.00 329.63 523.25 261.63 24.15 110.00 110.00 220.00 329.63 523.25 261.63 659.26 24.16 110.00 110.00 220.00 329.63 523.25 261.63 659.26 24.17 110.00 110.00 220.00 329.63 523.25 261.63 659.26 24.18 110.00 110.00 220.00 329.63 523.25 261.63 659.26 329.63 24.19 110.00 110.00 220.00 329.63 261.63 659.26 329.63 24.20 110.00 220.00 329.63 261.63 659.26 329.63 24.21 110.00 220.00 329.63 659.26 329.63 24.22 110.00 220.00 329.63 659.26 329.63 24.23 110.00 220.00 329.63 659.26 329.63 24.24 110.00 220.00 329.63 659.26 329.63 24.25 110.00 220.00 329.63 659.26 329.63 24.26 110.00 220.00 329.63 659.26 329.63 24.27 110.00 220.00 329.63 659.26 329.63 24.28 110.00 220.00 329.63 659.26 329.63 24.29 110.00 220.00 329.63 659.26 329.63 24.30 110.00 220.00 329.63 659.26 329.63 24.31 110.00 220.00 329.63 659.26 329.63 24.32 110.00 220.00 329.63 659.26 329.63 24.33 110.00 220.00 329.63 659.26 329.63 24.34 110.00 220.00 329.63 659.26 329.63 24.35 110.00 220.00 329.63 659.26 329.63 880.00 24.36 110.00 220.00 329.63 659.26 329.63 880.00 440.00 24.37 110.00 220.00 329.63 659.26 329.63 880.00 440.00 24.38 110.00 220.00 329.63 880.00 440.00 24.39 110.00 220.00 329.63 880.00 440.00 24.40 110.00 220.00 329.63 880.00 440.00 24.41 110.00 220.00 329.63 880.00 440.00 24.42 110.00 220.00 329.63 880.00 440.00 24.43 110.00 220.00 329.63 880.00 440.00 24.44 110.00 220.00 329.63 880.00 440.00 24.45 110.00 220.00 329.63 880.00 440.00 24.46 110.00 220.00 329.63 880.00 440.00 24.47 110.00 220.00 329.63 880.00 440.00 24.48 110.00 220.00 329.63 880.00 440.00 24.49 110.00 220.00 329.63 880.00 440.00 24.50 110.00 220.00 329.63 880.00 440.00 24.51 110.00 220.00 329.63 880.00 440.00 24.52 110.00 220.00 329.63 880.00 440.00 24.53 110.00 220.00 329.63 880.00 440.00 24.54 110.00 220.00 329.63 880.00 440.00 1046.50 24.55 110.00 220.00 329.63 880.00 1046.50 24.56 110.00 220.00 329.63 880.00 1046.50 523.25 24.57 110.00 220.00 329.63 1046.50 523.25 24.58 220.00 329.63 1046.50 523.25 24.59 220.00 329.63 1046.50 523.25 24.60 220.00 329.63 1046.50 523.25 24.61 220.00 329.63 1046.50 523.25 24.62 220.00 329.63 1046.50 523.25 24.63 220.00 329.63 1046.50 523.25 24.64 220.00 329.63 1046.50 523.25 24.65 220.00 329.63 523.25 24.66 220.00 329.63 523.25 24.67 220.00 329.63 523.25 24.68 220.00 329.63 523.25 24.69 220.00 329.63 523.25 24.70 220.00 329.63 523.25 24.71 220.00 329.63 523.25 24.72 220.00 329.63 523.25 261.63 1046.50 24.73 220.00 329.63 523.25 261.63 1046.50 24.74 220.00 329.63 523.25 261.63 1046.50 24.75 220.00 329.63 523.25 261.63 1046.50 24.76 220.00 329.63 523.25 261.63 1046.50 24.77 220.00 329.63 261.63 1046.50 24.78 220.00 329.63 261.63 1046.50 24.79 220.00 329.63 261.63 1046.50 24.80 220.00 329.63 261.63 1046.50 24.81 220.00 329.63 261.63 1046.50 24.82 220.00 329.63 261.63 1046.50 24.83 220.00 329.63 261.63 24.84 220.00 329.63 261.63 24.85 220.00 329.63 261.63 24.86 220.00 329.63 24.87 220.00 24.88 220.00 24.89 220.00 24.90 220.00 1046.50 349.23 24.91 220.00 1046.50 349.23 24.92 220.00 1046.50 349.23 73.42 73.42 24.93 220.00 1046.50 349.23 73.42 73.42 146.83 24.94 220.00 1046.50 349.23 73.42 73.42 146.83 24.95 1046.50 349.23 73.42 73.42 146.83 24.96 1046.50 349.23 73.42 73.42 146.83 24.97 1046.50 349.23 73.42 73.42 146.83 24.98 1046.50 349.23 73.42 73.42 146.83 24.99 1046.50 349.23 73.42 73.42 146.83 25.00 1046.50 349.23 73.42 73.42 146.83 25.01 1046.50 349.23 73.42 73.42 146.83 146.83 25.02 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.03 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.04 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.05 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.06 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.07 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.08 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.09 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.10 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.11 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 25.12 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.13 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.14 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.15 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.16 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.17 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.18 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.19 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.20 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.21 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.22 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.23 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.24 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.25 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.26 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.27 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.28 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.29 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.30 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 25.31 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 493.88 25.32 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 493.88 25.33 1046.50 349.23 73.42 73.42 146.83 146.83 220.00 349.23 493.88 25.34 1046.50 349.23 73.42 146.83 146.83 220.00 349.23 493.88 25.35 1046.50 349.23 73.42 146.83 146.83 220.00 349.23 493.88 25.36 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.37 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.38 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.39 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.40 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.41 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.42 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.43 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.44 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.45 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.46 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.47 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.48 1046.50 349.23 73.42 146.83 146.83 220.00 493.88 25.49 349.23 73.42 146.83 146.83 220.00 493.88 987.77 25.50 349.23 73.42 146.83 146.83 220.00 493.88 987.77 587.33 25.51 349.23 73.42 146.83 146.83 220.00 493.88 987.77 587.33 25.52 349.23 73.42 146.83 146.83 220.00 493.88 987.77 587.33 25.53 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.54 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.55 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.56 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.57 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.58 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.59 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.60 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.61 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.62 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.63 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.64 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.65 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.66 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.67 349.23 73.42 146.83 146.83 220.00 987.77 587.33 25.68 349.23 73.42 146.83 146.83 220.00 987.77 587.33 1174.66 25.69 349.23 73.42 146.83 146.83 220.00 987.77 1174.66 25.70 349.23 73.42 146.83 146.83 220.00 987.77 1174.66 698.46 25.71 349.23 73.42 146.83 146.83 220.00 1174.66 698.46 25.72 349.23 73.42 146.83 146.83 220.00 1174.66 698.46 25.73 349.23 73.42 146.83 146.83 220.00 1174.66 698.46 25.74 349.23 73.42 146.83 146.83 220.00 1174.66 698.46 25.75 349.23 73.42 146.83 146.83 220.00 1174.66 698.46 25.76 349.23 73.42 146.83 146.83 220.00 1174.66 698.46 25.77 349.23 146.83 146.83 220.00 1174.66 698.46 25.78 349.23 146.83 220.00 1174.66 698.46 25.79 349.23 146.83 220.00 1174.66 698.46 25.80 349.23 146.83 220.00 1174.66 698.46 25.81 349.23 146.83 220.00 1174.66 698.46 25.82 349.23 146.83 220.00 1174.66 698.46 25.83 349.23 146.83 220.00 1174.66 698.46 25.84 349.23 146.83 220.00 1174.66 698.46 25.85 349.23 146.83 220.00 1174.66 698.46 25.86 349.23 146.83 220.00 1174.66 698.46 1396.91 25.87 349.23 146.83 220.00 698.46 1396.91 349.23 25.88 349.23 146.83 220.00 698.46 1396.91 349.23 25.89 349.23 146.83 220.00 698.46 1396.91 349.23 25.90 349.23 146.83 220.00 1396.91 349.23 25.91 349.23 146.83 1396.91 349.23 25.92 349.23 146.83 1396.91 349.23 25.93 349.23 146.83 1396.91 349.23 25.94 349.23 146.83 1396.91 349.23 25.95 349.23 146.83 1396.91 349.23 25.96 349.23 146.83 1396.91 349.23 25.97 349.23 146.83 349.23 25.98 146.83 349.23 25.99 146.83 349.23 26.00 146.83 349.23 26.01 146.83 349.23 26.02 146.83 349.23 26.03 146.83 349.23 82.41 440.00 82.41 261.63 26.04 146.83 349.23 82.41 440.00 82.41 261.63 164.81 26.05 146.83 349.23 82.41 440.00 82.41 261.63 164.81 26.06 146.83 82.41 440.00 82.41 261.63 164.81 26.07 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 26.08 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 26.09 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 26.10 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 26.11 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 26.12 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 26.13 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 26.14 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 164.81 26.15 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 164.81 26.16 146.83 82.41 440.00 82.41 261.63 164.81 1396.91 164.81 26.17 82.41 440.00 82.41 261.63 164.81 1396.91 164.81 26.18 82.41 440.00 82.41 261.63 164.81 1396.91 164.81 26.19 82.41 440.00 82.41 261.63 164.81 164.81 26.20 82.41 440.00 82.41 261.63 164.81 164.81 26.21 82.41 440.00 82.41 261.63 164.81 164.81 26.22 82.41 440.00 82.41 261.63 164.81 164.81 26.23 82.41 440.00 82.41 261.63 164.81 164.81 26.24 82.41 440.00 82.41 261.63 164.81 164.81 26.25 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.26 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.27 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.28 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.29 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.30 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.31 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.32 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.33 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.34 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1318.51 26.35 82.41 440.00 82.41 261.63 164.81 164.81 329.63 26.36 82.41 440.00 82.41 261.63 164.81 164.81 329.63 26.37 82.41 440.00 82.41 261.63 164.81 164.81 329.63 26.38 82.41 440.00 82.41 261.63 164.81 164.81 329.63 26.39 82.41 440.00 82.41 261.63 164.81 164.81 329.63 26.40 82.41 440.00 82.41 261.63 164.81 164.81 329.63 26.41 82.41 440.00 82.41 261.63 164.81 164.81 329.63 26.42 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1174.66 26.43 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1174.66 26.44 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1174.66 26.45 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1174.66 440.00 26.46 82.41 440.00 82.41 261.63 164.81 164.81 329.63 1174.66 440.00 26.47 440.00 82.41 261.63 164.81 164.81 329.63 1174.66 440.00 26.48 440.00 82.41 261.63 164.81 164.81 1174.66 440.00 26.49 440.00 82.41 261.63 164.81 164.81 1174.66 440.00 26.50 440.00 82.41 261.63 164.81 164.81 1174.66 440.00 26.51 440.00 82.41 261.63 164.81 164.81 1174.66 440.00 26.52 440.00 82.41 261.63 164.81 164.81 440.00 26.53 440.00 82.41 261.63 164.81 164.81 440.00 26.54 440.00 82.41 261.63 164.81 164.81 440.00 26.55 440.00 82.41 261.63 164.81 164.81 440.00 26.56 440.00 82.41 261.63 164.81 164.81 440.00 26.57 440.00 82.41 261.63 164.81 164.81 440.00 26.58 440.00 82.41 261.63 164.81 164.81 440.00 26.59 440.00 82.41 261.63 164.81 164.81 440.00 26.60 440.00 82.41 261.63 164.81 164.81 440.00 1046.50 26.61 440.00 82.41 261.63 164.81 164.81 440.00 1046.50 26.62 440.00 82.41 261.63 164.81 164.81 440.00 1046.50 26.63 440.00 82.41 261.63 164.81 164.81 440.00 1046.50 26.64 440.00 82.41 261.63 164.81 164.81 440.00 1046.50 523.25 26.65 440.00 82.41 261.63 164.81 164.81 440.00 1046.50 523.25 26.66 440.00 82.41 261.63 164.81 164.81 1046.50 523.25 26.67 440.00 82.41 261.63 164.81 164.81 1046.50 523.25 26.68 440.00 82.41 261.63 164.81 164.81 1046.50 523.25 26.69 440.00 82.41 261.63 164.81 164.81 523.25 26.70 440.00 82.41 261.63 164.81 164.81 523.25 26.71 440.00 82.41 261.63 164.81 164.81 523.25 26.72 440.00 82.41 261.63 164.81 164.81 523.25 26.73 440.00 82.41 261.63 164.81 164.81 523.25 26.74 440.00 82.41 261.63 164.81 523.25 26.75 440.00 82.41 261.63 164.81 523.25 26.76 440.00 82.41 261.63 164.81 523.25 26.77 440.00 82.41 261.63 164.81 523.25 987.77 26.78 440.00 82.41 261.63 164.81 523.25 987.77 26.79 440.00 82.41 261.63 164.81 523.25 987.77 26.80 440.00 82.41 261.63 164.81 523.25 987.77 26.81 440.00 82.41 261.63 164.81 523.25 987.77 26.82 440.00 82.41 261.63 164.81 523.25 987.77 659.26 26.83 440.00 261.63 164.81 987.77 659.26 26.84 440.00 261.63 164.81 987.77 659.26 26.85 440.00 261.63 164.81 987.77 659.26 26.86 440.00 261.63 164.81 659.26 26.87 440.00 261.63 164.81 659.26 26.88 440.00 261.63 164.81 659.26 26.89 440.00 164.81 659.26 26.90 440.00 164.81 659.26 26.91 440.00 164.81 659.26 26.92 440.00 164.81 659.26 26.93 440.00 164.81 659.26 26.94 440.00 164.81 659.26 880.00 26.95 440.00 164.81 659.26 880.00 26.96 440.00 164.81 659.26 880.00 26.97 440.00 164.81 659.26 880.00 164.81 26.98 440.00 164.81 659.26 880.00 164.81 26.99 440.00 164.81 659.26 164.81 27.00 440.00 164.81 659.26 164.81 27.01 440.00 164.81 659.26 164.81 27.02 440.00 164.81 659.26 164.81 27.03 440.00 164.81 659.26 164.81 27.04 440.00 164.81 659.26 164.81 27.05 440.00 164.81 659.26 164.81 27.06 440.00 164.81 659.26 164.81 27.07 440.00 164.81 164.81 27.08 440.00 164.81 164.81 27.09 440.00 164.81 164.81 27.10 440.00 164.81 164.81 27.11 164.81 164.81 27.12 164.81 164.81 27.13 164.81 164.81 830.61 27.14 164.81 164.81 830.61 82.41 27.15 164.81 164.81 830.61 82.41 27.16 164.81 164.81 830.61 82.41 329.63 82.41 27.17 164.81 830.61 82.41 329.63 82.41 27.18 164.81 830.61 82.41 329.63 82.41 27.19 164.81 830.61 82.41 329.63 82.41 329.63 493.88 27.20 164.81 82.41 329.63 82.41 329.63 493.88 27.21 164.81 82.41 329.63 82.41 329.63 493.88 27.22 164.81 82.41 329.63 82.41 329.63 493.88 27.23 164.81 82.41 329.63 82.41 329.63 493.88 27.24 164.81 82.41 329.63 82.41 329.63 493.88 27.25 164.81 82.41 329.63 82.41 329.63 493.88 27.26 164.81 82.41 329.63 82.41 329.63 493.88 27.27 164.81 82.41 329.63 82.41 329.63 493.88 27.28 164.81 82.41 329.63 82.41 329.63 493.88 27.29 164.81 82.41 329.63 82.41 329.63 493.88 27.30 164.81 82.41 329.63 82.41 329.63 493.88 27.31 164.81 82.41 329.63 82.41 329.63 493.88 27.32 164.81 82.41 329.63 82.41 329.63 493.88 698.46 27.33 164.81 82.41 329.63 82.41 329.63 493.88 698.46 415.30 27.34 164.81 82.41 329.63 82.41 329.63 493.88 698.46 415.30 27.35 164.81 82.41 329.63 82.41 329.63 493.88 698.46 415.30 27.36 164.81 82.41 329.63 82.41 329.63 493.88 698.46 415.30 27.37 164.81 82.41 329.63 82.41 329.63 493.88 698.46 415.30 27.38 164.81 82.41 329.63 82.41 329.63 493.88 698.46 415.30 27.39 164.81 82.41 329.63 82.41 329.63 493.88 698.46 415.30 27.40 164.81 82.41 329.63 82.41 329.63 493.88 698.46 415.30 27.41 164.81 82.41 329.63 82.41 329.63 493.88 415.30 27.42 164.81 82.41 329.63 82.41 329.63 493.88 415.30 27.43 164.81 82.41 329.63 82.41 329.63 493.88 415.30 27.44 164.81 82.41 329.63 82.41 329.63 493.88 415.30 27.45 164.81 82.41 329.63 82.41 329.63 493.88 415.30 27.46 164.81 82.41 329.63 82.41 329.63 493.88 415.30 27.47 164.81 82.41 329.63 82.41 329.63 493.88 415.30 659.26 27.48 164.81 82.41 329.63 82.41 329.63 493.88 415.30 659.26 27.49 164.81 82.41 329.63 82.41 329.63 493.88 415.30 659.26 27.50 164.81 82.41 329.63 82.41 329.63 493.88 415.30 659.26 27.51 164.81 82.41 329.63 82.41 329.63 493.88 415.30 659.26 27.52 164.81 82.41 329.63 82.41 329.63 493.88 415.30 659.26 27.53 164.81 82.41 329.63 82.41 329.63 493.88 415.30 659.26 493.88 27.54 164.81 82.41 329.63 82.41 329.63 493.88 415.30 659.26 493.88 27.55 164.81 82.41 329.63 82.41 329.63 493.88 659.26 493.88 27.56 164.81 82.41 329.63 82.41 329.63 493.88 493.88 27.57 164.81 329.63 82.41 329.63 493.88 493.88 27.58 164.81 329.63 82.41 329.63 493.88 493.88 27.59 164.81 329.63 82.41 329.63 493.88 493.88 27.60 164.81 329.63 82.41 329.63 493.88 493.88 27.61 164.81 329.63 82.41 329.63 493.88 493.88 27.62 164.81 329.63 82.41 329.63 493.88 493.88 27.63 164.81 329.63 82.41 329.63 493.88 493.88 27.64 164.81 329.63 82.41 329.63 493.88 493.88 27.65 164.81 329.63 82.41 329.63 493.88 493.88 27.66 164.81 329.63 82.41 329.63 493.88 493.88 587.33 27.67 164.81 329.63 82.41 329.63 493.88 493.88 587.33 27.68 164.81 329.63 82.41 329.63 493.88 493.88 587.33 27.69 164.81 329.63 82.41 329.63 493.88 493.88 587.33 27.70 164.81 329.63 82.41 329.63 493.88 493.88 587.33 27.71 164.81 329.63 82.41 329.63 493.88 587.33 659.26 27.72 164.81 329.63 82.41 329.63 493.88 587.33 659.26 27.73 164.81 329.63 82.41 329.63 493.88 587.33 659.26 27.74 164.81 329.63 82.41 329.63 493.88 587.33 659.26 27.75 164.81 329.63 82.41 329.63 493.88 659.26 27.76 164.81 329.63 82.41 329.63 493.88 659.26 27.77 164.81 329.63 82.41 329.63 493.88 659.26 27.78 164.81 329.63 82.41 329.63 493.88 659.26 27.79 164.81 329.63 82.41 329.63 493.88 659.26 27.80 164.81 329.63 82.41 329.63 493.88 659.26 27.81 164.81 329.63 82.41 329.63 493.88 659.26 27.82 82.41 329.63 493.88 659.26 27.83 82.41 329.63 493.88 659.26 523.25 27.84 82.41 329.63 493.88 523.25 27.85 82.41 329.63 493.88 523.25 27.86 82.41 329.63 493.88 523.25 27.87 82.41 329.63 493.88 523.25 27.88 82.41 329.63 493.88 523.25 415.30 27.89 82.41 329.63 493.88 523.25 415.30 27.90 329.63 523.25 415.30 830.61 27.91 329.63 523.25 415.30 830.61 27.92 329.63 523.25 415.30 830.61 27.93 329.63 415.30 830.61 27.94 415.30 830.61 27.95 415.30 830.61 27.96 415.30 830.61 27.97 415.30 830.61 27.98 415.30 830.61 27.99 415.30 28.00 415.30 28.01 415.30 493.88 28.02 415.30 493.88 28.03 415.30 493.88 28.04 415.30 493.88 28.05 415.30 493.88 28.06 415.30 493.88 28.07 415.30 493.88 164.81 28.08 415.30 493.88 164.81 28.09 415.30 164.81 28.10 415.30 164.81 28.11 415.30 164.81 28.12 415.30 164.81 28.13 415.30 164.81 28.14 415.30 164.81 28.15 415.30 164.81 28.16 415.30 164.81 28.17 415.30 164.81 28.18 415.30 164.81 28.19 415.30 164.81 164.81 440.00 28.20 415.30 164.81 164.81 440.00 28.21 415.30 164.81 164.81 440.00 440.00 28.22 415.30 164.81 164.81 440.00 440.00 28.23 415.30 164.81 164.81 440.00 440.00 110.00 28.24 415.30 164.81 164.81 440.00 440.00 110.00 28.25 415.30 164.81 440.00 440.00 110.00 28.26 415.30 164.81 440.00 440.00 110.00 28.27 415.30 164.81 440.00 440.00 110.00 110.00 220.00 123.47 28.28 164.81 440.00 440.00 110.00 110.00 220.00 123.47 28.29 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.30 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.31 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.32 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.33 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.34 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.35 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.36 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.37 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.38 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 28.39 164.81 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.40 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.41 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.42 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.43 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.44 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.45 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.46 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.47 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.48 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.49 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.50 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.51 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.52 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.53 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.54 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.55 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.56 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.57 440.00 440.00 110.00 110.00 220.00 880.00 440.00 220.00 28.58 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.59 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.60 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.61 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.62 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.63 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.64 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.65 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.66 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.67 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.68 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.69 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.70 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.71 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.72 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.73 440.00 440.00 110.00 220.00 880.00 440.00 220.00 28.74 440.00 110.00 220.00 880.00 440.00 220.00 28.75 440.00 110.00 220.00 880.00 440.00 220.00 28.76 440.00 110.00 220.00 880.00 440.00 220.00 28.77 440.00 110.00 220.00 880.00 440.00 220.00 28.78 440.00 110.00 220.00 880.00 440.00 220.00 28.79 440.00 110.00 220.00 880.00 440.00 220.00 28.80 440.00 110.00 220.00 880.00 440.00 220.00 28.81 440.00 110.00 220.00 880.00 440.00 220.00 28.82 440.00 110.00 220.00 880.00 440.00 220.00 28.83 440.00 110.00 220.00 880.00 440.00 220.00 28.84 440.00 110.00 220.00 880.00 440.00 220.00 28.85 440.00 110.00 880.00 440.00 220.00 28.86 440.00 110.00 880.00 220.00 28.87 440.00 110.00 880.00 220.00 28.88 440.00 110.00 880.00 220.00 28.89 440.00 880.00 220.00 28.90 440.00 220.00 28.91 440.00 220.00 28.92 440.00 220.00 28.93 220.00mir_eval-0.8.2/tests/data/multipitch/ref05.txt000066400000000000000000004410451475740344600212640ustar00rootroot000000000000000.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.30 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.40 0.41 0.42 0.43 0.44 0.45 0.46 0.47 0.48 0.49 0.50 0.51 0.52 0.53 0.54 0.55 0.56 0.57 0.58 0.59 0.60 0.61 0.62 0.63 0.64 0.65 0.66 0.67 0.68 0.69 0.70 0.71 0.72 0.73 0.74 0.75 0.76 0.77 0.78 0.79 0.80 0.81 0.82 0.83 0.84 0.85 0.86 0.87 0.88 0.89 0.90 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1.00 1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.10 1.11 1.12 1.13 1.14 1.15 1.16 1.17 1.18 1.19 1.20 1.21 1.22 1.23 1.24 1.25 1.26 1.27 1.28 1.29 1.30 1.31 1.32 1.33 1.34 1.35 1.36 1.37 1.38 1.39 1.40 1.41 1.42 1.43 1.44 1.45 1.46 1.47 1.48 1.49 1.50 1.51 1.52 1.53 1.54 1.55 1.56 1.57 1.58 1.59 1.60 1.61 1.62 1.63 1.64 1.65 1.66 1.67 1.68 1.69 1.70 1.71 1.72 1.73 1.74 1.75 1.76 1.77 1.78 1.79 1.80 1.81 1.82 1.83 1.84 1.85 1.86 1.87 1.88 1.89 1.90 1.91 1.92 1.93 1.94 1.95 1.96 1.97 1.98 1.99 2.00 2.01 2.02 2.03 2.04 2.05 2.06 2.07 2.08 2.09 2.10 2.11 2.12 2.13 2.14 2.15 2.16 2.17 2.18 2.19 2.20 2.21 2.22 2.23 2.24 2.25 2.26 2.27 2.28 2.29 2.30 2.31 2.32 2.33 2.34 2.35 2.36 2.37 2.38 2.39 2.40 2.41 2.42 2.43 2.44 2.45 2.46 2.47 2.48 2.49 2.50 2.51 2.52 2.53 2.54 2.55 2.56 2.57 2.58 2.59 2.60 2.61 2.62 2.63 69.30 138.59 207.65 2.64 69.30 138.59 207.65 2.65 69.30 138.59 207.65 2.66 69.30 138.59 207.65 2.67 69.30 138.59 207.65 2.68 69.30 138.59 207.65 2.69 69.30 138.59 207.65 2.70 69.30 138.59 207.65 2.71 69.30 138.59 207.65 2.72 69.30 138.59 207.65 2.73 69.30 138.59 207.65 2.74 69.30 138.59 207.65 2.75 69.30 138.59 207.65 2.76 69.30 138.59 207.65 2.77 69.30 138.59 207.65 2.78 69.30 138.59 207.65 2.79 69.30 138.59 207.65 2.80 69.30 138.59 207.65 2.81 69.30 138.59 207.65 2.82 69.30 138.59 207.65 2.83 69.30 138.59 207.65 2.84 69.30 138.59 207.65 2.85 69.30 138.59 207.65 2.86 69.30 138.59 207.65 2.87 69.30 138.59 207.65 2.88 69.30 138.59 207.65 2.89 69.30 138.59 207.65 2.90 69.30 138.59 207.65 2.91 69.30 138.59 207.65 2.92 69.30 138.59 207.65 2.93 69.30 138.59 207.65 2.94 69.30 138.59 207.65 2.95 69.30 138.59 207.65 2.96 69.30 138.59 207.65 2.97 69.30 138.59 207.65 2.98 69.30 138.59 207.65 2.99 69.30 138.59 207.65 3.00 69.30 138.59 207.65 3.01 69.30 138.59 207.65 3.02 69.30 138.59 207.65 3.03 69.30 138.59 207.65 3.04 69.30 138.59 207.65 3.05 69.30 138.59 207.65 3.06 69.30 138.59 207.65 3.07 69.30 138.59 207.65 3.08 69.30 138.59 207.65 3.09 69.30 138.59 207.65 3.10 69.30 138.59 207.65 3.11 69.30 138.59 207.65 3.12 69.30 138.59 207.65 3.13 69.30 138.59 3.14 69.30 138.59 277.18 3.15 69.30 138.59 277.18 3.16 69.30 138.59 277.18 3.17 69.30 138.59 277.18 3.18 69.30 138.59 277.18 3.19 69.30 138.59 277.18 3.20 69.30 138.59 277.18 3.21 69.30 138.59 277.18 3.22 69.30 138.59 277.18 3.23 69.30 138.59 277.18 3.24 69.30 138.59 277.18 3.25 69.30 138.59 277.18 3.26 69.30 138.59 277.18 3.27 69.30 138.59 277.18 3.28 69.30 138.59 277.18 3.29 69.30 138.59 277.18 3.30 69.30 138.59 277.18 3.31 69.30 138.59 277.18 3.32 69.30 138.59 277.18 3.33 69.30 138.59 277.18 3.34 69.30 138.59 277.18 3.35 69.30 138.59 277.18 3.36 69.30 138.59 277.18 3.37 69.30 138.59 277.18 3.38 69.30 138.59 277.18 3.39 69.30 138.59 277.18 3.40 69.30 138.59 277.18 3.41 69.30 138.59 277.18 3.42 69.30 138.59 277.18 3.43 69.30 138.59 277.18 3.44 69.30 138.59 277.18 3.45 69.30 138.59 277.18 3.46 69.30 138.59 277.18 3.47 69.30 138.59 277.18 3.48 69.30 138.59 277.18 3.49 69.30 138.59 277.18 3.50 69.30 138.59 277.18 3.51 69.30 138.59 277.18 3.52 69.30 138.59 277.18 3.53 69.30 138.59 277.18 3.54 69.30 138.59 277.18 3.55 69.30 138.59 277.18 3.56 69.30 138.59 277.18 3.57 69.30 138.59 277.18 3.58 69.30 138.59 277.18 3.59 69.30 138.59 277.18 3.60 69.30 138.59 277.18 3.61 69.30 138.59 277.18 3.62 69.30 138.59 277.18 3.63 69.30 138.59 277.18 3.64 69.30 138.59 277.18 3.65 69.30 138.59 277.18 329.63 3.66 69.30 138.59 277.18 329.63 3.67 69.30 138.59 277.18 329.63 3.68 69.30 138.59 329.63 3.69 69.30 138.59 329.63 3.70 69.30 138.59 329.63 3.71 69.30 138.59 329.63 3.72 69.30 138.59 329.63 3.73 69.30 138.59 329.63 3.74 69.30 138.59 329.63 3.75 69.30 138.59 329.63 3.76 69.30 138.59 329.63 3.77 69.30 138.59 329.63 3.78 69.30 138.59 329.63 3.79 69.30 138.59 329.63 3.80 69.30 138.59 329.63 3.81 69.30 138.59 329.63 3.82 69.30 138.59 329.63 3.83 69.30 138.59 329.63 3.84 69.30 138.59 329.63 3.85 69.30 138.59 329.63 3.86 69.30 138.59 329.63 3.87 69.30 138.59 329.63 3.88 69.30 138.59 329.63 3.89 69.30 138.59 329.63 3.90 69.30 138.59 329.63 3.91 69.30 138.59 329.63 3.92 69.30 138.59 329.63 3.93 69.30 138.59 329.63 3.94 69.30 138.59 329.63 3.95 69.30 138.59 329.63 3.96 69.30 138.59 329.63 3.97 69.30 138.59 329.63 3.98 69.30 138.59 329.63 3.99 69.30 138.59 329.63 4.00 69.30 138.59 329.63 4.01 69.30 138.59 329.63 4.02 69.30 138.59 329.63 4.03 69.30 138.59 329.63 4.04 69.30 138.59 329.63 4.05 69.30 138.59 329.63 4.06 69.30 138.59 329.63 4.07 69.30 138.59 329.63 4.08 69.30 138.59 329.63 4.09 69.30 138.59 329.63 4.10 69.30 138.59 329.63 4.11 69.30 138.59 329.63 4.12 69.30 138.59 329.63 4.13 69.30 138.59 329.63 4.14 69.30 138.59 329.63 4.15 69.30 138.59 329.63 207.65 4.16 69.30 138.59 329.63 207.65 4.17 69.30 138.59 207.65 4.18 69.30 138.59 207.65 4.19 69.30 138.59 207.65 4.20 69.30 138.59 207.65 4.21 69.30 138.59 207.65 4.22 69.30 138.59 207.65 4.23 69.30 138.59 207.65 4.24 69.30 138.59 207.65 4.25 69.30 138.59 207.65 4.26 69.30 138.59 207.65 4.27 69.30 138.59 207.65 4.28 69.30 138.59 207.65 4.29 69.30 138.59 207.65 4.30 69.30 138.59 207.65 4.31 69.30 138.59 207.65 4.32 69.30 138.59 207.65 4.33 69.30 138.59 207.65 4.34 69.30 138.59 207.65 4.35 69.30 138.59 207.65 4.36 69.30 138.59 207.65 4.37 69.30 138.59 207.65 4.38 69.30 138.59 207.65 4.39 69.30 138.59 207.65 4.40 69.30 138.59 207.65 4.41 69.30 138.59 207.65 4.42 69.30 138.59 207.65 4.43 69.30 138.59 207.65 4.44 69.30 138.59 207.65 4.45 69.30 138.59 207.65 4.46 69.30 138.59 207.65 4.47 69.30 138.59 207.65 4.48 69.30 138.59 207.65 4.49 69.30 138.59 207.65 4.50 69.30 138.59 207.65 4.51 69.30 138.59 207.65 4.52 69.30 138.59 207.65 4.53 69.30 138.59 207.65 4.54 69.30 138.59 207.65 4.55 69.30 138.59 207.65 4.56 69.30 138.59 207.65 4.57 69.30 138.59 207.65 4.58 69.30 138.59 207.65 4.59 69.30 138.59 207.65 4.60 69.30 138.59 207.65 4.61 69.30 138.59 207.65 4.62 69.30 138.59 207.65 4.63 69.30 138.59 207.65 4.64 69.30 138.59 207.65 4.65 69.30 138.59 207.65 4.66 69.30 138.59 207.65 277.18 4.67 69.30 138.59 207.65 277.18 4.68 69.30 138.59 207.65 277.18 4.69 69.30 138.59 207.65 277.18 4.70 69.30 138.59 207.65 277.18 4.71 69.30 138.59 207.65 277.18 4.72 69.30 138.59 277.18 4.73 69.30 138.59 277.18 4.74 69.30 138.59 277.18 4.75 69.30 138.59 277.18 4.76 69.30 138.59 277.18 4.77 69.30 138.59 277.18 4.78 69.30 138.59 277.18 4.79 69.30 138.59 277.18 4.80 69.30 138.59 277.18 4.81 69.30 138.59 277.18 4.82 69.30 138.59 277.18 4.83 69.30 138.59 277.18 4.84 69.30 138.59 277.18 4.85 69.30 138.59 277.18 4.86 69.30 138.59 277.18 4.87 69.30 138.59 277.18 4.88 69.30 138.59 277.18 4.89 69.30 138.59 277.18 4.90 69.30 138.59 277.18 4.91 69.30 138.59 277.18 4.92 69.30 138.59 277.18 4.93 69.30 138.59 277.18 4.94 69.30 138.59 277.18 4.95 69.30 138.59 277.18 4.96 69.30 138.59 277.18 4.97 69.30 138.59 277.18 4.98 69.30 138.59 277.18 4.99 69.30 138.59 277.18 5.00 69.30 138.59 277.18 5.01 69.30 138.59 277.18 5.02 69.30 138.59 277.18 5.03 69.30 138.59 277.18 5.04 69.30 138.59 277.18 5.05 69.30 138.59 277.18 5.06 69.30 138.59 277.18 5.07 69.30 138.59 277.18 5.08 69.30 138.59 277.18 5.09 69.30 138.59 277.18 5.10 69.30 138.59 277.18 5.11 69.30 138.59 277.18 329.63 5.12 69.30 138.59 277.18 329.63 5.13 69.30 138.59 277.18 329.63 5.14 69.30 138.59 329.63 5.15 69.30 138.59 329.63 5.16 69.30 138.59 329.63 5.17 69.30 138.59 329.63 5.18 69.30 138.59 329.63 5.19 69.30 138.59 329.63 5.20 69.30 138.59 329.63 5.21 69.30 138.59 329.63 5.22 69.30 138.59 329.63 5.23 69.30 138.59 329.63 5.24 69.30 138.59 329.63 5.25 69.30 138.59 329.63 5.26 69.30 138.59 329.63 5.27 69.30 138.59 329.63 5.28 69.30 138.59 329.63 5.29 69.30 138.59 329.63 5.30 69.30 138.59 329.63 5.31 69.30 138.59 329.63 5.32 69.30 138.59 329.63 5.33 69.30 138.59 329.63 5.34 69.30 138.59 329.63 5.35 69.30 138.59 329.63 5.36 69.30 138.59 329.63 5.37 69.30 138.59 329.63 5.38 69.30 138.59 329.63 5.39 69.30 138.59 329.63 5.40 69.30 138.59 329.63 5.41 69.30 138.59 329.63 5.42 69.30 138.59 329.63 5.43 69.30 138.59 329.63 5.44 69.30 138.59 329.63 5.45 69.30 138.59 329.63 5.46 69.30 138.59 329.63 5.47 69.30 138.59 329.63 5.48 69.30 138.59 329.63 5.49 69.30 138.59 329.63 5.50 69.30 138.59 329.63 5.51 69.30 138.59 329.63 5.52 69.30 138.59 329.63 5.53 69.30 138.59 329.63 5.54 69.30 138.59 329.63 5.55 69.30 138.59 329.63 5.56 69.30 138.59 329.63 5.57 69.30 138.59 329.63 5.58 69.30 138.59 329.63 5.59 69.30 138.59 329.63 5.60 69.30 138.59 329.63 207.65 5.61 69.30 138.59 207.65 5.62 69.30 138.59 207.65 5.63 69.30 138.59 207.65 5.64 69.30 138.59 207.65 5.65 69.30 138.59 207.65 5.66 69.30 138.59 207.65 5.67 69.30 138.59 207.65 5.68 69.30 138.59 207.65 5.69 69.30 138.59 207.65 5.70 69.30 138.59 207.65 5.71 69.30 138.59 207.65 5.72 69.30 138.59 207.65 5.73 69.30 138.59 207.65 5.74 69.30 138.59 207.65 5.75 69.30 138.59 207.65 5.76 69.30 138.59 207.65 5.77 69.30 138.59 207.65 5.78 69.30 138.59 207.65 5.79 69.30 138.59 207.65 5.80 69.30 138.59 207.65 5.81 69.30 138.59 207.65 5.82 69.30 138.59 207.65 5.83 69.30 138.59 207.65 5.84 69.30 138.59 207.65 5.85 69.30 138.59 207.65 5.86 69.30 138.59 207.65 5.87 69.30 138.59 207.65 5.88 69.30 138.59 207.65 5.89 69.30 138.59 207.65 5.90 69.30 138.59 207.65 5.91 69.30 138.59 207.65 5.92 69.30 138.59 207.65 5.93 69.30 138.59 207.65 5.94 69.30 138.59 207.65 5.95 69.30 138.59 207.65 5.96 69.30 138.59 207.65 5.97 69.30 138.59 207.65 5.98 69.30 138.59 207.65 5.99 69.30 138.59 207.65 6.00 69.30 138.59 207.65 6.01 69.30 138.59 207.65 6.02 69.30 138.59 207.65 6.03 69.30 138.59 207.65 6.04 69.30 138.59 207.65 6.05 69.30 138.59 207.65 6.06 69.30 138.59 207.65 277.18 6.07 69.30 138.59 207.65 277.18 6.08 69.30 138.59 207.65 277.18 6.09 69.30 138.59 207.65 277.18 6.10 69.30 138.59 207.65 277.18 6.11 69.30 138.59 207.65 277.18 6.12 69.30 138.59 207.65 277.18 6.13 69.30 138.59 207.65 277.18 6.14 69.30 138.59 277.18 6.15 69.30 138.59 277.18 6.16 69.30 138.59 277.18 6.17 69.30 138.59 277.18 6.18 69.30 138.59 277.18 6.19 69.30 138.59 277.18 6.20 69.30 138.59 277.18 6.21 69.30 138.59 277.18 6.22 69.30 138.59 277.18 6.23 69.30 138.59 277.18 6.24 69.30 138.59 277.18 6.25 69.30 138.59 277.18 6.26 69.30 138.59 277.18 6.27 69.30 138.59 277.18 6.28 69.30 138.59 277.18 6.29 69.30 138.59 277.18 6.30 69.30 138.59 277.18 6.31 69.30 138.59 277.18 6.32 69.30 138.59 277.18 6.33 69.30 138.59 277.18 6.34 69.30 138.59 277.18 6.35 69.30 138.59 277.18 6.36 69.30 138.59 277.18 6.37 69.30 138.59 277.18 6.38 69.30 138.59 277.18 6.39 69.30 138.59 277.18 6.40 69.30 138.59 277.18 6.41 69.30 138.59 277.18 6.42 69.30 138.59 277.18 6.43 69.30 138.59 277.18 6.44 69.30 138.59 277.18 6.45 69.30 138.59 277.18 6.46 69.30 138.59 277.18 6.47 69.30 138.59 277.18 6.48 69.30 138.59 277.18 6.49 69.30 138.59 277.18 329.63 6.50 69.30 138.59 277.18 329.63 6.51 69.30 138.59 277.18 329.63 6.52 69.30 138.59 277.18 329.63 6.53 69.30 138.59 277.18 329.63 6.54 69.30 138.59 329.63 6.55 69.30 138.59 329.63 6.56 69.30 138.59 329.63 6.57 69.30 138.59 329.63 6.58 69.30 138.59 329.63 6.59 69.30 138.59 329.63 6.60 69.30 138.59 329.63 6.61 69.30 138.59 329.63 6.62 69.30 138.59 329.63 6.63 69.30 138.59 329.63 6.64 69.30 138.59 329.63 6.65 69.30 138.59 329.63 6.66 69.30 138.59 329.63 6.67 69.30 138.59 329.63 6.68 69.30 138.59 329.63 6.69 69.30 138.59 329.63 6.70 69.30 138.59 329.63 6.71 69.30 138.59 329.63 6.72 69.30 138.59 329.63 6.73 69.30 138.59 329.63 6.74 69.30 138.59 329.63 6.75 69.30 138.59 329.63 6.76 69.30 138.59 329.63 6.77 69.30 138.59 329.63 6.78 69.30 138.59 329.63 6.79 69.30 138.59 329.63 6.80 69.30 138.59 329.63 6.81 69.30 138.59 329.63 6.82 69.30 138.59 329.63 6.83 69.30 138.59 329.63 6.84 69.30 138.59 329.63 6.85 69.30 138.59 329.63 6.86 69.30 138.59 329.63 6.87 69.30 138.59 329.63 6.88 69.30 138.59 329.63 6.89 69.30 138.59 329.63 6.90 69.30 138.59 329.63 6.91 69.30 138.59 329.63 6.92 69.30 138.59 329.63 6.93 69.30 138.59 329.63 6.94 69.30 138.59 329.63 6.95 69.30 138.59 329.63 6.96 69.30 138.59 329.63 6.97 69.30 138.59 329.63 207.65 6.98 69.30 138.59 207.65 6.99 69.30 138.59 207.65 7.00 69.30 138.59 207.65 7.01 69.30 138.59 207.65 7.02 69.30 138.59 207.65 7.03 69.30 138.59 207.65 7.04 69.30 138.59 207.65 7.05 69.30 138.59 207.65 7.06 69.30 138.59 207.65 7.07 69.30 138.59 207.65 7.08 69.30 138.59 207.65 7.09 69.30 138.59 207.65 7.10 69.30 138.59 207.65 7.11 69.30 138.59 207.65 7.12 69.30 138.59 207.65 7.13 69.30 138.59 207.65 7.14 69.30 138.59 207.65 7.15 69.30 138.59 207.65 7.16 69.30 138.59 207.65 7.17 69.30 138.59 207.65 7.18 69.30 138.59 207.65 7.19 69.30 138.59 207.65 7.20 69.30 138.59 207.65 7.21 69.30 138.59 207.65 7.22 69.30 138.59 207.65 7.23 69.30 138.59 207.65 7.24 69.30 138.59 207.65 7.25 69.30 138.59 207.65 7.26 69.30 138.59 207.65 7.27 69.30 138.59 207.65 7.28 69.30 138.59 207.65 7.29 69.30 138.59 207.65 7.30 69.30 138.59 207.65 7.31 69.30 138.59 207.65 7.32 69.30 138.59 207.65 7.33 69.30 138.59 207.65 7.34 69.30 138.59 207.65 7.35 69.30 138.59 207.65 7.36 69.30 138.59 207.65 7.37 69.30 138.59 207.65 7.38 69.30 138.59 207.65 7.39 69.30 138.59 207.65 7.40 69.30 138.59 207.65 7.41 69.30 138.59 207.65 7.42 69.30 138.59 207.65 7.43 69.30 138.59 207.65 7.44 69.30 138.59 207.65 277.18 7.45 69.30 138.59 207.65 277.18 7.46 69.30 138.59 207.65 277.18 7.47 69.30 138.59 207.65 277.18 7.48 69.30 138.59 207.65 277.18 7.49 69.30 138.59 207.65 277.18 7.50 69.30 138.59 207.65 277.18 7.51 69.30 138.59 277.18 7.52 69.30 138.59 277.18 7.53 69.30 138.59 277.18 7.54 69.30 138.59 277.18 7.55 69.30 138.59 277.18 7.56 69.30 138.59 277.18 7.57 69.30 138.59 277.18 7.58 69.30 138.59 277.18 7.59 69.30 138.59 277.18 7.60 69.30 138.59 277.18 7.61 69.30 138.59 277.18 7.62 69.30 138.59 277.18 7.63 69.30 138.59 277.18 7.64 69.30 138.59 277.18 7.65 69.30 138.59 277.18 7.66 69.30 138.59 277.18 7.67 69.30 138.59 277.18 7.68 69.30 138.59 277.18 7.69 69.30 138.59 277.18 7.70 69.30 138.59 277.18 7.71 69.30 138.59 277.18 7.72 69.30 138.59 277.18 7.73 69.30 138.59 277.18 7.74 69.30 138.59 277.18 7.75 69.30 138.59 277.18 7.76 69.30 138.59 277.18 7.77 69.30 138.59 277.18 7.78 69.30 138.59 277.18 7.79 69.30 138.59 277.18 7.80 69.30 138.59 277.18 7.81 69.30 138.59 277.18 7.82 69.30 138.59 277.18 7.83 69.30 138.59 277.18 7.84 69.30 138.59 277.18 7.85 69.30 138.59 277.18 7.86 69.30 138.59 277.18 7.87 69.30 138.59 277.18 7.88 69.30 138.59 277.18 7.89 69.30 138.59 277.18 7.90 69.30 138.59 277.18 7.91 69.30 138.59 277.18 7.92 69.30 138.59 277.18 7.93 69.30 138.59 277.18 329.63 7.94 69.30 138.59 277.18 329.63 7.95 69.30 138.59 277.18 329.63 7.96 69.30 138.59 277.18 329.63 7.97 69.30 138.59 277.18 329.63 7.98 69.30 138.59 329.63 7.99 69.30 138.59 329.63 8.00 69.30 138.59 329.63 8.01 69.30 138.59 329.63 8.02 69.30 138.59 329.63 8.03 69.30 138.59 329.63 8.04 69.30 138.59 329.63 8.05 69.30 138.59 329.63 8.06 69.30 138.59 329.63 8.07 69.30 138.59 329.63 8.08 69.30 138.59 329.63 8.09 69.30 138.59 329.63 8.10 69.30 138.59 329.63 8.11 69.30 138.59 329.63 8.12 69.30 138.59 329.63 8.13 69.30 138.59 329.63 8.14 69.30 138.59 329.63 8.15 69.30 138.59 329.63 8.16 69.30 138.59 329.63 8.17 69.30 138.59 329.63 8.18 69.30 138.59 329.63 8.19 69.30 138.59 329.63 8.20 69.30 138.59 329.63 8.21 69.30 138.59 329.63 8.22 69.30 138.59 329.63 8.23 69.30 138.59 329.63 8.24 69.30 138.59 329.63 8.25 69.30 138.59 329.63 8.26 69.30 138.59 329.63 8.27 69.30 138.59 329.63 8.28 69.30 138.59 329.63 8.29 69.30 138.59 329.63 8.30 69.30 138.59 329.63 8.31 69.30 138.59 329.63 8.32 69.30 138.59 329.63 8.33 69.30 138.59 329.63 8.34 69.30 138.59 329.63 8.35 69.30 138.59 329.63 8.36 69.30 138.59 329.63 8.37 69.30 138.59 329.63 8.38 69.30 329.63 8.39 69.30 329.63 8.40 69.30 329.63 8.41 69.30 329.63 8.42 69.30 329.63 8.43 69.30 329.63 8.44 69.30 329.63 8.45 69.30 329.63 8.46 69.30 329.63 8.47 69.30 329.63 8.48 69.30 329.63 8.49 69.30 329.63 8.50 8.51 61.74 123.47 207.65 8.52 61.74 123.47 207.65 8.53 61.74 123.47 207.65 8.54 61.74 123.47 207.65 8.55 61.74 123.47 207.65 8.56 61.74 123.47 207.65 8.57 61.74 123.47 207.65 8.58 61.74 123.47 207.65 8.59 61.74 123.47 207.65 8.60 61.74 123.47 207.65 8.61 61.74 123.47 207.65 8.62 61.74 123.47 207.65 8.63 61.74 123.47 207.65 8.64 61.74 123.47 207.65 8.65 61.74 123.47 207.65 8.66 61.74 123.47 207.65 8.67 61.74 123.47 207.65 8.68 61.74 123.47 207.65 8.69 61.74 123.47 207.65 8.70 61.74 123.47 207.65 8.71 61.74 123.47 207.65 8.72 61.74 123.47 207.65 8.73 61.74 123.47 207.65 8.74 61.74 123.47 207.65 8.75 61.74 123.47 207.65 8.76 61.74 123.47 207.65 8.77 61.74 123.47 207.65 8.78 61.74 123.47 207.65 8.79 61.74 123.47 207.65 8.80 61.74 123.47 207.65 8.81 61.74 123.47 207.65 8.82 61.74 123.47 207.65 8.83 61.74 123.47 207.65 8.84 61.74 123.47 207.65 8.85 61.74 123.47 207.65 8.86 61.74 123.47 207.65 8.87 61.74 123.47 207.65 8.88 61.74 123.47 207.65 8.89 61.74 123.47 207.65 8.90 61.74 123.47 207.65 8.91 61.74 123.47 207.65 8.92 61.74 123.47 207.65 8.93 61.74 123.47 207.65 8.94 61.74 123.47 207.65 8.95 61.74 123.47 207.65 8.96 61.74 123.47 207.65 8.97 61.74 123.47 207.65 8.98 61.74 123.47 207.65 8.99 61.74 123.47 207.65 9.00 61.74 123.47 207.65 9.01 61.74 123.47 207.65 9.02 61.74 123.47 207.65 9.03 61.74 123.47 207.65 9.04 61.74 123.47 207.65 277.18 9.05 61.74 123.47 207.65 277.18 9.06 61.74 123.47 207.65 277.18 9.07 61.74 123.47 207.65 277.18 9.08 61.74 123.47 207.65 277.18 9.09 61.74 123.47 207.65 277.18 9.10 61.74 123.47 277.18 9.11 61.74 123.47 277.18 9.12 61.74 123.47 277.18 9.13 61.74 123.47 277.18 9.14 61.74 123.47 277.18 9.15 61.74 123.47 277.18 9.16 61.74 123.47 277.18 9.17 61.74 123.47 277.18 9.18 61.74 123.47 277.18 9.19 61.74 123.47 277.18 9.20 61.74 123.47 277.18 9.21 61.74 123.47 277.18 9.22 61.74 123.47 277.18 9.23 61.74 123.47 277.18 9.24 61.74 123.47 277.18 9.25 61.74 123.47 277.18 9.26 61.74 123.47 277.18 9.27 61.74 123.47 277.18 9.28 61.74 123.47 277.18 9.29 61.74 123.47 277.18 9.30 61.74 123.47 277.18 9.31 61.74 123.47 277.18 9.32 61.74 123.47 277.18 9.33 61.74 123.47 277.18 9.34 61.74 123.47 277.18 9.35 61.74 123.47 277.18 9.36 61.74 123.47 277.18 9.37 61.74 123.47 277.18 9.38 61.74 123.47 277.18 9.39 61.74 123.47 277.18 9.40 61.74 123.47 277.18 9.41 61.74 123.47 277.18 9.42 61.74 123.47 277.18 9.43 61.74 123.47 277.18 9.44 61.74 123.47 277.18 9.45 61.74 123.47 277.18 9.46 61.74 123.47 277.18 9.47 61.74 123.47 277.18 9.48 61.74 123.47 277.18 9.49 61.74 123.47 277.18 9.50 61.74 123.47 277.18 9.51 61.74 123.47 277.18 9.52 61.74 123.47 277.18 9.53 61.74 123.47 277.18 9.54 61.74 123.47 277.18 9.55 61.74 123.47 277.18 9.56 61.74 123.47 277.18 329.63 9.57 61.74 123.47 277.18 329.63 9.58 61.74 123.47 277.18 329.63 9.59 61.74 123.47 277.18 329.63 9.60 61.74 123.47 329.63 9.61 61.74 123.47 329.63 9.62 61.74 123.47 329.63 9.63 61.74 123.47 329.63 9.64 61.74 123.47 329.63 9.65 61.74 123.47 329.63 9.66 61.74 123.47 329.63 9.67 61.74 123.47 329.63 9.68 61.74 123.47 329.63 9.69 61.74 123.47 329.63 9.70 61.74 123.47 329.63 9.71 61.74 123.47 329.63 9.72 61.74 123.47 329.63 9.73 61.74 123.47 329.63 9.74 61.74 123.47 329.63 9.75 61.74 123.47 329.63 9.76 61.74 123.47 329.63 9.77 61.74 123.47 329.63 9.78 61.74 123.47 329.63 9.79 61.74 123.47 329.63 9.80 61.74 123.47 329.63 9.81 61.74 123.47 329.63 9.82 61.74 123.47 329.63 9.83 61.74 123.47 329.63 9.84 61.74 123.47 329.63 9.85 61.74 123.47 329.63 9.86 61.74 123.47 329.63 9.87 61.74 123.47 329.63 9.88 61.74 123.47 329.63 9.89 61.74 123.47 329.63 9.90 61.74 123.47 329.63 9.91 61.74 123.47 329.63 9.92 61.74 123.47 329.63 9.93 61.74 123.47 329.63 9.94 61.74 123.47 329.63 9.95 61.74 123.47 329.63 9.96 61.74 123.47 329.63 9.97 61.74 123.47 329.63 9.98 61.74 123.47 329.63 9.99 61.74 123.47 329.63 10.00 61.74 123.47 329.63 10.01 61.74 123.47 329.63 10.02 61.74 123.47 329.63 10.03 61.74 123.47 329.63 10.04 61.74 123.47 329.63 10.05 61.74 123.47 329.63 10.06 61.74 123.47 329.63 10.07 61.74 123.47 329.63 207.65 10.08 61.74 123.47 329.63 207.65 10.09 61.74 123.47 329.63 207.65 10.10 61.74 123.47 207.65 10.11 61.74 123.47 207.65 10.12 61.74 123.47 207.65 10.13 61.74 123.47 207.65 10.14 61.74 123.47 207.65 10.15 61.74 123.47 207.65 10.16 61.74 123.47 207.65 10.17 61.74 123.47 207.65 10.18 61.74 123.47 207.65 10.19 61.74 123.47 207.65 10.20 61.74 123.47 207.65 10.21 61.74 123.47 207.65 10.22 61.74 123.47 207.65 10.23 61.74 123.47 207.65 10.24 61.74 123.47 207.65 10.25 61.74 123.47 207.65 10.26 61.74 123.47 207.65 10.27 61.74 123.47 207.65 10.28 61.74 123.47 207.65 10.29 61.74 123.47 207.65 10.30 61.74 123.47 207.65 10.31 61.74 123.47 207.65 10.32 61.74 123.47 207.65 10.33 61.74 123.47 207.65 10.34 61.74 123.47 207.65 10.35 61.74 123.47 207.65 10.36 61.74 123.47 207.65 10.37 61.74 123.47 207.65 10.38 61.74 123.47 207.65 10.39 61.74 123.47 207.65 10.40 61.74 123.47 207.65 10.41 61.74 123.47 207.65 10.42 61.74 123.47 207.65 10.43 61.74 123.47 207.65 10.44 61.74 123.47 207.65 10.45 61.74 123.47 207.65 10.46 61.74 123.47 207.65 10.47 61.74 123.47 207.65 10.48 61.74 123.47 207.65 10.49 61.74 123.47 207.65 10.50 61.74 123.47 207.65 10.51 61.74 123.47 207.65 10.52 61.74 123.47 207.65 10.53 61.74 123.47 207.65 10.54 61.74 123.47 207.65 277.18 10.55 61.74 123.47 207.65 277.18 10.56 61.74 123.47 207.65 277.18 10.57 61.74 123.47 207.65 277.18 10.58 61.74 123.47 207.65 277.18 10.59 61.74 123.47 207.65 277.18 10.60 61.74 123.47 207.65 277.18 10.61 61.74 123.47 277.18 10.62 61.74 123.47 277.18 10.63 61.74 123.47 277.18 10.64 61.74 123.47 277.18 10.65 61.74 123.47 277.18 10.66 61.74 123.47 277.18 10.67 61.74 123.47 277.18 10.68 61.74 123.47 277.18 10.69 61.74 123.47 277.18 10.70 61.74 123.47 277.18 10.71 61.74 123.47 277.18 10.72 61.74 123.47 277.18 10.73 61.74 123.47 277.18 10.74 61.74 123.47 277.18 10.75 61.74 123.47 277.18 10.76 61.74 123.47 277.18 10.77 61.74 123.47 277.18 10.78 61.74 123.47 277.18 10.79 61.74 123.47 277.18 10.80 61.74 123.47 277.18 10.81 61.74 123.47 277.18 10.82 61.74 123.47 277.18 10.83 61.74 123.47 277.18 10.84 61.74 123.47 277.18 10.85 61.74 123.47 277.18 10.86 61.74 123.47 277.18 10.87 61.74 123.47 277.18 10.88 61.74 123.47 277.18 10.89 61.74 123.47 277.18 10.90 61.74 123.47 277.18 10.91 61.74 123.47 277.18 10.92 61.74 123.47 277.18 10.93 61.74 123.47 277.18 10.94 61.74 123.47 277.18 10.95 61.74 123.47 277.18 10.96 61.74 123.47 277.18 10.97 61.74 123.47 277.18 10.98 61.74 123.47 277.18 10.99 61.74 123.47 277.18 11.00 61.74 123.47 277.18 11.01 61.74 123.47 277.18 11.02 61.74 123.47 277.18 11.03 61.74 123.47 277.18 329.63 11.04 61.74 123.47 277.18 329.63 11.05 61.74 123.47 277.18 329.63 11.06 61.74 123.47 329.63 11.07 61.74 123.47 329.63 11.08 61.74 123.47 329.63 11.09 61.74 123.47 329.63 11.10 61.74 123.47 329.63 11.11 61.74 123.47 329.63 11.12 61.74 123.47 329.63 11.13 61.74 123.47 329.63 11.14 61.74 123.47 329.63 11.15 61.74 123.47 329.63 11.16 61.74 123.47 329.63 11.17 61.74 123.47 329.63 11.18 61.74 123.47 329.63 11.19 61.74 123.47 329.63 11.20 61.74 123.47 329.63 11.21 61.74 123.47 329.63 11.22 61.74 123.47 329.63 11.23 61.74 123.47 329.63 11.24 61.74 123.47 329.63 11.25 61.74 123.47 329.63 11.26 61.74 123.47 329.63 11.27 61.74 123.47 329.63 11.28 61.74 123.47 329.63 11.29 61.74 123.47 329.63 11.30 61.74 123.47 329.63 11.31 61.74 123.47 329.63 11.32 61.74 123.47 329.63 11.33 61.74 123.47 329.63 11.34 61.74 123.47 329.63 11.35 61.74 123.47 329.63 11.36 61.74 123.47 329.63 11.37 61.74 123.47 329.63 11.38 61.74 123.47 329.63 11.39 61.74 123.47 329.63 11.40 61.74 123.47 329.63 11.41 61.74 123.47 329.63 11.42 61.74 123.47 329.63 11.43 61.74 123.47 329.63 11.44 61.74 123.47 329.63 11.45 61.74 123.47 329.63 11.46 61.74 123.47 329.63 11.47 61.74 123.47 329.63 11.48 61.74 123.47 329.63 11.49 61.74 123.47 329.63 11.50 61.74 123.47 329.63 11.51 61.74 123.47 329.63 11.52 61.74 123.47 329.63 11.53 61.74 123.47 329.63 207.65 11.54 61.74 123.47 329.63 207.65 11.55 61.74 123.47 207.65 11.56 61.74 123.47 207.65 11.57 61.74 123.47 207.65 11.58 61.74 123.47 207.65 11.59 61.74 123.47 207.65 11.60 61.74 123.47 207.65 11.61 61.74 123.47 207.65 11.62 61.74 123.47 207.65 11.63 61.74 123.47 207.65 11.64 61.74 123.47 207.65 11.65 61.74 123.47 207.65 11.66 61.74 123.47 207.65 11.67 61.74 123.47 207.65 11.68 61.74 123.47 207.65 11.69 61.74 123.47 207.65 11.70 61.74 123.47 207.65 11.71 61.74 123.47 207.65 11.72 61.74 123.47 207.65 11.73 61.74 123.47 207.65 11.74 61.74 123.47 207.65 11.75 61.74 123.47 207.65 11.76 61.74 123.47 207.65 11.77 61.74 123.47 207.65 11.78 61.74 123.47 207.65 11.79 61.74 123.47 207.65 11.80 61.74 123.47 207.65 11.81 61.74 123.47 207.65 11.82 61.74 123.47 207.65 11.83 61.74 123.47 207.65 11.84 61.74 123.47 207.65 11.85 61.74 123.47 207.65 11.86 61.74 123.47 207.65 11.87 61.74 123.47 207.65 11.88 61.74 123.47 207.65 11.89 61.74 123.47 207.65 11.90 61.74 123.47 207.65 11.91 61.74 123.47 207.65 11.92 61.74 123.47 207.65 11.93 61.74 123.47 207.65 11.94 61.74 123.47 207.65 11.95 61.74 123.47 207.65 11.96 61.74 123.47 207.65 11.97 61.74 123.47 207.65 11.98 61.74 123.47 207.65 11.99 61.74 123.47 207.65 12.00 61.74 123.47 207.65 277.18 12.01 61.74 123.47 207.65 277.18 12.02 61.74 123.47 207.65 277.18 12.03 61.74 123.47 207.65 277.18 12.04 61.74 123.47 207.65 277.18 12.05 61.74 123.47 207.65 277.18 12.06 61.74 123.47 277.18 12.07 61.74 123.47 277.18 12.08 61.74 123.47 277.18 12.09 61.74 123.47 277.18 12.10 61.74 123.47 277.18 12.11 61.74 123.47 277.18 12.12 61.74 123.47 277.18 12.13 61.74 123.47 277.18 12.14 61.74 123.47 277.18 12.15 61.74 123.47 277.18 12.16 61.74 123.47 277.18 12.17 61.74 123.47 277.18 12.18 61.74 123.47 277.18 12.19 61.74 123.47 277.18 12.20 61.74 123.47 277.18 12.21 61.74 123.47 277.18 12.22 61.74 123.47 277.18 12.23 61.74 123.47 277.18 12.24 61.74 123.47 277.18 12.25 61.74 123.47 277.18 12.26 61.74 123.47 277.18 12.27 61.74 123.47 277.18 12.28 61.74 123.47 277.18 12.29 61.74 123.47 277.18 12.30 61.74 123.47 277.18 12.31 61.74 123.47 277.18 12.32 61.74 123.47 277.18 12.33 61.74 123.47 277.18 12.34 61.74 123.47 277.18 12.35 61.74 123.47 277.18 12.36 61.74 123.47 277.18 12.37 61.74 123.47 277.18 12.38 61.74 123.47 277.18 12.39 61.74 123.47 277.18 12.40 61.74 123.47 277.18 12.41 61.74 123.47 277.18 12.42 61.74 123.47 277.18 12.43 61.74 123.47 277.18 12.44 61.74 123.47 277.18 12.45 61.74 123.47 277.18 12.46 61.74 123.47 277.18 12.47 61.74 123.47 277.18 329.63 12.48 61.74 123.47 277.18 329.63 12.49 61.74 123.47 277.18 329.63 12.50 61.74 123.47 277.18 329.63 12.51 61.74 123.47 329.63 12.52 61.74 123.47 329.63 12.53 61.74 123.47 329.63 12.54 61.74 123.47 329.63 12.55 61.74 123.47 329.63 12.56 61.74 123.47 329.63 12.57 61.74 123.47 329.63 12.58 61.74 123.47 329.63 12.59 61.74 123.47 329.63 12.60 61.74 123.47 329.63 12.61 61.74 123.47 329.63 12.62 61.74 123.47 329.63 12.63 61.74 123.47 329.63 12.64 61.74 123.47 329.63 12.65 61.74 123.47 329.63 12.66 61.74 123.47 329.63 12.67 61.74 123.47 329.63 12.68 61.74 123.47 329.63 12.69 61.74 123.47 329.63 12.70 61.74 123.47 329.63 12.71 61.74 123.47 329.63 12.72 61.74 123.47 329.63 12.73 61.74 123.47 329.63 12.74 61.74 123.47 329.63 12.75 61.74 123.47 329.63 12.76 61.74 123.47 329.63 12.77 61.74 123.47 329.63 12.78 61.74 123.47 329.63 12.79 61.74 123.47 329.63 12.80 61.74 123.47 329.63 12.81 61.74 123.47 329.63 12.82 61.74 123.47 329.63 12.83 61.74 123.47 329.63 12.84 61.74 123.47 329.63 12.85 61.74 123.47 329.63 12.86 61.74 123.47 329.63 12.87 61.74 123.47 329.63 12.88 61.74 123.47 329.63 12.89 61.74 123.47 329.63 12.90 61.74 123.47 329.63 12.91 61.74 123.47 329.63 12.92 61.74 123.47 329.63 12.93 61.74 123.47 329.63 12.94 61.74 123.47 329.63 12.95 61.74 123.47 329.63 12.96 61.74 123.47 207.65 12.97 61.74 123.47 207.65 12.98 61.74 123.47 207.65 12.99 61.74 123.47 207.65 13.00 61.74 123.47 207.65 13.01 61.74 123.47 207.65 13.02 61.74 123.47 207.65 13.03 61.74 123.47 207.65 13.04 61.74 123.47 207.65 13.05 61.74 123.47 207.65 13.06 61.74 123.47 207.65 13.07 61.74 123.47 207.65 13.08 61.74 123.47 207.65 13.09 61.74 123.47 207.65 13.10 61.74 123.47 207.65 13.11 61.74 123.47 207.65 13.12 61.74 123.47 207.65 13.13 61.74 123.47 207.65 13.14 61.74 123.47 207.65 13.15 61.74 123.47 207.65 13.16 61.74 123.47 207.65 13.17 61.74 123.47 207.65 13.18 61.74 123.47 207.65 13.19 61.74 123.47 207.65 13.20 61.74 123.47 207.65 13.21 61.74 123.47 207.65 13.22 61.74 123.47 207.65 13.23 61.74 123.47 207.65 13.24 61.74 123.47 207.65 13.25 61.74 123.47 207.65 13.26 61.74 123.47 207.65 13.27 61.74 123.47 207.65 13.28 61.74 123.47 207.65 13.29 61.74 123.47 207.65 13.30 61.74 123.47 207.65 13.31 61.74 123.47 207.65 13.32 61.74 123.47 207.65 13.33 61.74 123.47 207.65 13.34 61.74 123.47 207.65 13.35 61.74 123.47 207.65 13.36 61.74 123.47 207.65 13.37 61.74 123.47 207.65 13.38 61.74 123.47 207.65 13.39 61.74 123.47 207.65 277.18 13.40 61.74 123.47 207.65 277.18 13.41 61.74 123.47 207.65 277.18 13.42 61.74 123.47 207.65 277.18 13.43 61.74 123.47 207.65 277.18 13.44 61.74 123.47 207.65 277.18 13.45 61.74 123.47 207.65 277.18 13.46 61.74 123.47 277.18 13.47 61.74 123.47 277.18 13.48 61.74 123.47 277.18 13.49 61.74 123.47 277.18 13.50 61.74 123.47 277.18 13.51 61.74 123.47 277.18 13.52 61.74 123.47 277.18 13.53 61.74 123.47 277.18 13.54 61.74 123.47 277.18 13.55 61.74 123.47 277.18 13.56 61.74 123.47 277.18 13.57 61.74 123.47 277.18 13.58 61.74 123.47 277.18 13.59 61.74 123.47 277.18 13.60 61.74 123.47 277.18 13.61 61.74 123.47 277.18 13.62 61.74 123.47 277.18 13.63 61.74 123.47 277.18 13.64 61.74 123.47 277.18 13.65 61.74 123.47 277.18 13.66 61.74 123.47 277.18 13.67 61.74 123.47 277.18 13.68 61.74 123.47 277.18 13.69 61.74 123.47 277.18 13.70 61.74 123.47 277.18 13.71 61.74 123.47 277.18 13.72 61.74 123.47 277.18 13.73 61.74 123.47 277.18 13.74 61.74 123.47 277.18 13.75 61.74 123.47 277.18 13.76 61.74 123.47 277.18 13.77 61.74 123.47 277.18 13.78 61.74 123.47 277.18 13.79 61.74 123.47 277.18 13.80 61.74 277.18 13.81 61.74 277.18 13.82 61.74 277.18 13.83 61.74 277.18 13.84 61.74 277.18 13.85 61.74 277.18 13.86 277.18 13.87 277.18 13.88 277.18 13.89 277.18 13.90 277.18 329.63 13.91 277.18 329.63 13.92 277.18 329.63 13.93 277.18 329.63 13.94 277.18 329.63 13.95 329.63 13.96 329.63 13.97 329.63 13.98 329.63 13.99 329.63 14.00 329.63 14.01 329.63 14.02 329.63 14.03 329.63 14.04 329.63 14.05 329.63 14.06 329.63 14.07 329.63 14.08 329.63 14.09 329.63 14.10 329.63 14.11 329.63 14.12 329.63 14.13 329.63 14.14 329.63 14.15 329.63 14.16 329.63 14.17 329.63 14.18 329.63 14.19 329.63 14.20 329.63 14.21 329.63 14.22 329.63 14.23 329.63 14.24 329.63 14.25 329.63 14.26 329.63 14.27 329.63 14.28 329.63 14.29 329.63 14.30 329.63 14.31 329.63 14.32 329.63 14.33 329.63 14.34 329.63 14.35 329.63 14.36 329.63 14.37 329.63 14.38 329.63 14.39 329.63 14.40 329.63 14.41 14.42 220.00 14.43 220.00 55.00 110.00 14.44 220.00 55.00 110.00 14.45 220.00 55.00 110.00 14.46 220.00 55.00 110.00 14.47 220.00 55.00 110.00 14.48 220.00 55.00 110.00 14.49 220.00 55.00 110.00 14.50 220.00 55.00 110.00 14.51 220.00 55.00 110.00 14.52 220.00 55.00 110.00 14.53 220.00 55.00 110.00 14.54 220.00 55.00 110.00 14.55 220.00 55.00 110.00 14.56 220.00 55.00 110.00 14.57 220.00 55.00 110.00 14.58 220.00 55.00 110.00 14.59 220.00 55.00 110.00 14.60 220.00 55.00 110.00 14.61 220.00 55.00 110.00 14.62 220.00 55.00 110.00 14.63 220.00 55.00 110.00 14.64 220.00 55.00 110.00 14.65 220.00 55.00 110.00 14.66 220.00 55.00 110.00 14.67 220.00 55.00 110.00 14.68 220.00 55.00 110.00 14.69 220.00 55.00 110.00 14.70 220.00 55.00 110.00 14.71 220.00 55.00 110.00 14.72 220.00 55.00 110.00 14.73 220.00 55.00 110.00 14.74 220.00 55.00 110.00 14.75 220.00 55.00 110.00 14.76 220.00 55.00 110.00 14.77 220.00 55.00 110.00 14.78 220.00 55.00 110.00 14.79 220.00 55.00 110.00 14.80 220.00 55.00 110.00 14.81 220.00 55.00 110.00 14.82 220.00 55.00 110.00 14.83 220.00 55.00 110.00 14.84 220.00 55.00 110.00 14.85 220.00 55.00 110.00 14.86 220.00 55.00 110.00 14.87 220.00 55.00 110.00 14.88 220.00 55.00 110.00 14.89 220.00 55.00 110.00 14.90 220.00 55.00 110.00 14.91 220.00 55.00 110.00 14.92 220.00 55.00 110.00 14.93 220.00 55.00 110.00 14.94 220.00 55.00 110.00 14.95 220.00 55.00 110.00 14.96 220.00 55.00 110.00 14.97 220.00 55.00 110.00 14.98 220.00 55.00 110.00 14.99 220.00 55.00 110.00 277.18 15.00 220.00 55.00 110.00 277.18 15.01 220.00 55.00 110.00 277.18 15.02 220.00 55.00 110.00 277.18 15.03 220.00 55.00 110.00 277.18 15.04 220.00 55.00 110.00 277.18 15.05 220.00 55.00 110.00 277.18 15.06 220.00 55.00 110.00 277.18 15.07 55.00 110.00 277.18 15.08 55.00 110.00 277.18 15.09 55.00 110.00 277.18 15.10 55.00 110.00 277.18 15.11 55.00 110.00 277.18 15.12 55.00 110.00 277.18 15.13 55.00 110.00 277.18 15.14 55.00 110.00 277.18 15.15 55.00 110.00 277.18 15.16 55.00 110.00 277.18 15.17 55.00 110.00 277.18 15.18 55.00 110.00 277.18 15.19 55.00 110.00 277.18 15.20 55.00 110.00 277.18 15.21 55.00 110.00 277.18 15.22 55.00 110.00 277.18 15.23 55.00 110.00 277.18 15.24 55.00 110.00 277.18 15.25 55.00 110.00 277.18 15.26 55.00 110.00 277.18 15.27 55.00 110.00 277.18 15.28 55.00 110.00 277.18 15.29 55.00 110.00 277.18 15.30 55.00 110.00 277.18 15.31 55.00 110.00 277.18 15.32 55.00 110.00 277.18 15.33 55.00 110.00 277.18 15.34 55.00 110.00 277.18 15.35 55.00 110.00 277.18 15.36 55.00 110.00 277.18 15.37 55.00 110.00 277.18 15.38 55.00 110.00 277.18 15.39 55.00 110.00 277.18 15.40 55.00 110.00 277.18 15.41 55.00 110.00 277.18 15.42 55.00 110.00 277.18 15.43 55.00 110.00 277.18 15.44 55.00 110.00 277.18 15.45 55.00 110.00 277.18 15.46 55.00 110.00 277.18 15.47 55.00 110.00 277.18 15.48 55.00 110.00 277.18 15.49 55.00 110.00 277.18 329.63 15.50 55.00 110.00 277.18 329.63 15.51 55.00 110.00 277.18 329.63 15.52 55.00 110.00 329.63 15.53 55.00 110.00 329.63 15.54 55.00 110.00 329.63 15.55 55.00 110.00 329.63 15.56 55.00 110.00 329.63 15.57 55.00 110.00 329.63 15.58 55.00 110.00 329.63 15.59 55.00 110.00 329.63 15.60 55.00 110.00 329.63 15.61 55.00 110.00 329.63 15.62 55.00 110.00 329.63 15.63 55.00 110.00 329.63 15.64 55.00 110.00 329.63 15.65 55.00 110.00 329.63 15.66 55.00 110.00 329.63 15.67 55.00 110.00 329.63 15.68 55.00 110.00 329.63 15.69 55.00 110.00 329.63 15.70 55.00 110.00 329.63 15.71 55.00 110.00 329.63 15.72 55.00 110.00 329.63 15.73 55.00 110.00 329.63 15.74 55.00 110.00 329.63 15.75 55.00 110.00 329.63 15.76 55.00 110.00 329.63 15.77 55.00 110.00 329.63 15.78 55.00 110.00 329.63 15.79 55.00 110.00 329.63 15.80 55.00 110.00 329.63 15.81 55.00 110.00 329.63 15.82 55.00 110.00 329.63 15.83 55.00 110.00 329.63 15.84 55.00 110.00 329.63 15.85 55.00 110.00 329.63 15.86 55.00 110.00 329.63 15.87 55.00 110.00 329.63 15.88 55.00 110.00 329.63 15.89 55.00 110.00 329.63 15.90 55.00 110.00 329.63 15.91 55.00 110.00 329.63 15.92 55.00 110.00 329.63 15.93 55.00 110.00 329.63 15.94 55.00 110.00 329.63 15.95 55.00 110.00 329.63 15.96 55.00 110.00 329.63 15.97 55.00 110.00 329.63 15.98 55.00 110.00 329.63 15.99 55.00 110.00 329.63 220.00 16.00 55.00 110.00 329.63 220.00 16.01 55.00 110.00 329.63 220.00 16.02 55.00 110.00 329.63 220.00 16.03 55.00 110.00 329.63 220.00 16.04 55.00 110.00 220.00 16.05 55.00 110.00 220.00 16.06 55.00 110.00 220.00 16.07 55.00 110.00 220.00 16.08 55.00 110.00 220.00 16.09 55.00 110.00 220.00 16.10 55.00 110.00 220.00 16.11 55.00 110.00 220.00 16.12 55.00 110.00 220.00 16.13 55.00 110.00 220.00 16.14 55.00 110.00 220.00 16.15 55.00 110.00 220.00 16.16 55.00 110.00 220.00 16.17 55.00 110.00 220.00 16.18 55.00 110.00 220.00 16.19 55.00 110.00 220.00 16.20 55.00 110.00 220.00 16.21 55.00 110.00 220.00 16.22 55.00 110.00 220.00 16.23 55.00 110.00 220.00 16.24 55.00 110.00 220.00 16.25 55.00 110.00 220.00 16.26 55.00 110.00 220.00 16.27 55.00 110.00 220.00 16.28 55.00 110.00 220.00 16.29 55.00 110.00 220.00 16.30 55.00 110.00 220.00 16.31 55.00 110.00 220.00 16.32 55.00 110.00 220.00 16.33 55.00 110.00 220.00 16.34 55.00 110.00 220.00 16.35 55.00 110.00 220.00 16.36 55.00 110.00 220.00 16.37 55.00 110.00 220.00 16.38 55.00 110.00 220.00 16.39 55.00 110.00 220.00 16.40 55.00 110.00 220.00 16.41 55.00 110.00 220.00 16.42 55.00 110.00 220.00 16.43 55.00 110.00 220.00 16.44 55.00 110.00 220.00 16.45 55.00 110.00 220.00 16.46 55.00 110.00 220.00 16.47 55.00 110.00 220.00 277.18 16.48 55.00 110.00 220.00 277.18 16.49 55.00 110.00 220.00 277.18 16.50 55.00 110.00 220.00 277.18 16.51 55.00 110.00 220.00 277.18 16.52 55.00 110.00 220.00 277.18 16.53 55.00 110.00 220.00 277.18 16.54 55.00 110.00 277.18 16.55 55.00 110.00 277.18 16.56 55.00 110.00 277.18 16.57 55.00 110.00 277.18 16.58 55.00 110.00 277.18 16.59 55.00 110.00 277.18 16.60 55.00 110.00 277.18 16.61 55.00 110.00 277.18 16.62 55.00 110.00 277.18 16.63 55.00 110.00 277.18 16.64 55.00 110.00 277.18 16.65 55.00 110.00 277.18 16.66 55.00 110.00 277.18 16.67 55.00 110.00 277.18 16.68 55.00 110.00 277.18 16.69 55.00 110.00 277.18 16.70 55.00 110.00 277.18 16.71 55.00 110.00 277.18 16.72 55.00 110.00 277.18 16.73 55.00 110.00 277.18 16.74 55.00 110.00 277.18 16.75 55.00 110.00 277.18 16.76 55.00 110.00 277.18 16.77 55.00 110.00 277.18 16.78 55.00 110.00 277.18 16.79 55.00 110.00 277.18 16.80 55.00 110.00 277.18 16.81 55.00 110.00 277.18 16.82 55.00 110.00 277.18 16.83 55.00 110.00 277.18 16.84 55.00 110.00 277.18 16.85 55.00 110.00 277.18 16.86 55.00 110.00 277.18 16.87 55.00 110.00 277.18 16.88 55.00 110.00 277.18 16.89 55.00 110.00 277.18 16.90 55.00 110.00 277.18 16.91 55.00 110.00 277.18 16.92 55.00 110.00 277.18 16.93 55.00 277.18 16.94 55.00 277.18 16.95 55.00 277.18 16.96 55.00 277.18 16.97 55.00 277.18 329.63 16.98 277.18 329.63 16.99 277.18 329.63 17.00 277.18 329.63 17.01 329.63 17.02 329.63 17.03 329.63 17.04 329.63 17.05 329.63 17.06 329.63 17.07 329.63 17.08 329.63 17.09 329.63 17.10 329.63 17.11 329.63 17.12 329.63 17.13 329.63 17.14 329.63 17.15 329.63 17.16 329.63 17.17 329.63 17.18 329.63 17.19 329.63 17.20 329.63 17.21 329.63 17.22 329.63 17.23 329.63 17.24 329.63 17.25 329.63 17.26 329.63 17.27 329.63 17.28 329.63 17.29 329.63 17.30 329.63 17.31 329.63 17.32 329.63 17.33 329.63 17.34 329.63 17.35 329.63 17.36 329.63 17.37 329.63 17.38 329.63 17.39 329.63 17.40 329.63 17.41 329.63 17.42 329.63 17.43 329.63 17.44 329.63 17.45 329.63 17.46 329.63 17.47 329.63 92.50 17.48 329.63 92.50 46.25 17.49 92.50 46.25 220.00 17.50 92.50 46.25 220.00 17.51 92.50 46.25 220.00 17.52 92.50 46.25 220.00 17.53 92.50 46.25 220.00 17.54 92.50 46.25 220.00 17.55 92.50 46.25 220.00 17.56 92.50 46.25 220.00 17.57 92.50 46.25 220.00 17.58 92.50 46.25 220.00 17.59 92.50 46.25 220.00 17.60 92.50 46.25 220.00 17.61 92.50 46.25 220.00 17.62 92.50 46.25 220.00 17.63 92.50 46.25 220.00 17.64 92.50 46.25 220.00 17.65 92.50 46.25 220.00 17.66 92.50 46.25 220.00 17.67 92.50 46.25 220.00 17.68 92.50 46.25 220.00 17.69 92.50 46.25 220.00 17.70 92.50 46.25 220.00 17.71 92.50 46.25 220.00 17.72 92.50 46.25 220.00 17.73 92.50 46.25 220.00 17.74 92.50 46.25 220.00 17.75 92.50 46.25 220.00 17.76 92.50 46.25 220.00 17.77 92.50 46.25 220.00 17.78 92.50 46.25 220.00 17.79 92.50 46.25 220.00 17.80 92.50 46.25 220.00 17.81 92.50 46.25 220.00 17.82 92.50 46.25 220.00 17.83 92.50 46.25 220.00 17.84 92.50 46.25 220.00 17.85 92.50 46.25 220.00 17.86 92.50 46.25 220.00 17.87 92.50 46.25 220.00 17.88 92.50 46.25 220.00 17.89 92.50 46.25 220.00 17.90 92.50 46.25 220.00 17.91 92.50 46.25 220.00 17.92 92.50 46.25 220.00 17.93 92.50 46.25 220.00 17.94 92.50 46.25 220.00 17.95 92.50 46.25 220.00 17.96 92.50 46.25 220.00 17.97 92.50 46.25 220.00 17.98 92.50 46.25 220.00 17.99 92.50 46.25 220.00 18.00 92.50 46.25 220.00 18.01 92.50 46.25 220.00 18.02 92.50 46.25 220.00 18.03 92.50 46.25 220.00 18.04 92.50 46.25 220.00 18.05 92.50 46.25 220.00 293.66 18.06 92.50 46.25 220.00 293.66 18.07 92.50 46.25 220.00 293.66 18.08 92.50 46.25 220.00 293.66 18.09 92.50 46.25 220.00 293.66 18.10 92.50 46.25 220.00 293.66 18.11 92.50 46.25 220.00 293.66 18.12 92.50 46.25 220.00 293.66 18.13 92.50 46.25 220.00 293.66 18.14 92.50 46.25 220.00 293.66 18.15 92.50 46.25 293.66 18.16 92.50 46.25 293.66 18.17 92.50 46.25 293.66 18.18 92.50 46.25 293.66 18.19 92.50 46.25 293.66 18.20 92.50 46.25 293.66 18.21 92.50 46.25 293.66 18.22 92.50 46.25 293.66 18.23 92.50 46.25 293.66 18.24 92.50 46.25 293.66 18.25 92.50 46.25 293.66 18.26 92.50 46.25 293.66 18.27 92.50 46.25 293.66 18.28 92.50 46.25 293.66 18.29 92.50 46.25 293.66 18.30 92.50 46.25 293.66 18.31 92.50 46.25 293.66 18.32 92.50 46.25 293.66 18.33 92.50 46.25 293.66 18.34 92.50 46.25 293.66 18.35 92.50 46.25 293.66 18.36 92.50 46.25 293.66 18.37 92.50 46.25 293.66 18.38 92.50 46.25 293.66 18.39 92.50 46.25 293.66 18.40 92.50 46.25 293.66 18.41 92.50 46.25 293.66 18.42 92.50 46.25 293.66 18.43 92.50 46.25 293.66 18.44 92.50 46.25 293.66 18.45 92.50 46.25 293.66 18.46 92.50 46.25 293.66 18.47 92.50 46.25 293.66 18.48 92.50 46.25 293.66 18.49 92.50 46.25 293.66 18.50 92.50 46.25 293.66 18.51 92.50 46.25 293.66 18.52 92.50 46.25 293.66 18.53 92.50 46.25 293.66 369.99 18.54 92.50 46.25 293.66 369.99 18.55 92.50 46.25 293.66 369.99 18.56 92.50 46.25 369.99 18.57 92.50 46.25 369.99 18.58 92.50 46.25 369.99 18.59 92.50 46.25 369.99 18.60 92.50 46.25 369.99 18.61 92.50 46.25 369.99 18.62 92.50 46.25 369.99 18.63 92.50 46.25 369.99 18.64 92.50 46.25 369.99 18.65 92.50 46.25 369.99 18.66 92.50 46.25 369.99 18.67 92.50 46.25 369.99 18.68 92.50 46.25 369.99 18.69 92.50 46.25 369.99 18.70 92.50 46.25 369.99 18.71 92.50 46.25 369.99 18.72 92.50 46.25 369.99 18.73 92.50 46.25 369.99 18.74 92.50 46.25 369.99 18.75 92.50 46.25 369.99 18.76 92.50 46.25 369.99 18.77 92.50 46.25 369.99 18.78 92.50 46.25 369.99 18.79 92.50 46.25 369.99 18.80 92.50 46.25 369.99 18.81 92.50 46.25 369.99 18.82 92.50 46.25 369.99 18.83 92.50 46.25 369.99 18.84 92.50 46.25 369.99 18.85 92.50 46.25 369.99 18.86 92.50 46.25 369.99 18.87 92.50 46.25 369.99 18.88 92.50 46.25 369.99 18.89 92.50 46.25 369.99 18.90 92.50 46.25 369.99 18.91 92.50 46.25 369.99 18.92 92.50 46.25 369.99 18.93 92.50 46.25 369.99 18.94 92.50 46.25 369.99 18.95 92.50 46.25 369.99 18.96 92.50 46.25 369.99 18.97 92.50 46.25 369.99 18.98 92.50 46.25 369.99 18.99 92.50 46.25 369.99 19.00 92.50 46.25 369.99 220.00 19.01 92.50 46.25 369.99 220.00 19.02 92.50 46.25 369.99 220.00 19.03 92.50 46.25 369.99 220.00 19.04 92.50 46.25 369.99 220.00 19.05 92.50 46.25 369.99 220.00 19.06 92.50 46.25 220.00 19.07 92.50 46.25 220.00 19.08 92.50 46.25 220.00 19.09 92.50 46.25 220.00 19.10 92.50 46.25 220.00 19.11 92.50 46.25 220.00 19.12 92.50 46.25 220.00 19.13 92.50 46.25 220.00 19.14 92.50 46.25 220.00 19.15 92.50 46.25 220.00 19.16 92.50 46.25 220.00 19.17 92.50 46.25 220.00 19.18 92.50 46.25 220.00 19.19 92.50 46.25 220.00 19.20 92.50 46.25 220.00 19.21 92.50 46.25 220.00 19.22 92.50 46.25 220.00 19.23 92.50 46.25 220.00 19.24 92.50 46.25 220.00 19.25 92.50 46.25 220.00 19.26 92.50 46.25 220.00 19.27 92.50 46.25 220.00 19.28 92.50 46.25 220.00 19.29 92.50 46.25 220.00 19.30 92.50 46.25 220.00 19.31 92.50 46.25 220.00 19.32 92.50 46.25 220.00 19.33 92.50 46.25 220.00 19.34 92.50 46.25 220.00 19.35 92.50 46.25 220.00 19.36 92.50 46.25 220.00 19.37 92.50 46.25 220.00 19.38 92.50 46.25 220.00 19.39 92.50 46.25 220.00 19.40 92.50 46.25 220.00 19.41 92.50 46.25 220.00 19.42 92.50 46.25 220.00 19.43 92.50 46.25 220.00 19.44 92.50 46.25 220.00 293.66 19.45 92.50 46.25 220.00 293.66 19.46 92.50 46.25 220.00 293.66 19.47 92.50 46.25 220.00 293.66 19.48 92.50 46.25 220.00 293.66 19.49 92.50 46.25 220.00 293.66 19.50 92.50 46.25 220.00 293.66 19.51 92.50 46.25 293.66 19.52 92.50 46.25 293.66 19.53 92.50 46.25 293.66 19.54 92.50 46.25 293.66 19.55 92.50 46.25 293.66 19.56 92.50 46.25 293.66 19.57 92.50 46.25 293.66 19.58 92.50 46.25 293.66 19.59 92.50 46.25 293.66 19.60 92.50 46.25 293.66 19.61 92.50 46.25 293.66 19.62 92.50 46.25 293.66 19.63 92.50 46.25 293.66 19.64 92.50 46.25 293.66 19.65 92.50 46.25 293.66 19.66 92.50 46.25 293.66 19.67 92.50 46.25 293.66 19.68 92.50 46.25 293.66 19.69 92.50 46.25 293.66 19.70 92.50 46.25 293.66 19.71 92.50 46.25 293.66 19.72 92.50 46.25 293.66 19.73 92.50 46.25 293.66 19.74 92.50 46.25 293.66 19.75 92.50 46.25 293.66 19.76 92.50 46.25 293.66 19.77 92.50 46.25 293.66 19.78 92.50 46.25 293.66 19.79 92.50 46.25 293.66 19.80 92.50 46.25 293.66 19.81 92.50 46.25 293.66 19.82 92.50 46.25 293.66 19.83 92.50 46.25 293.66 19.84 92.50 46.25 293.66 19.85 92.50 46.25 293.66 19.86 92.50 46.25 293.66 19.87 92.50 46.25 293.66 19.88 92.50 46.25 293.66 19.89 92.50 46.25 293.66 19.90 92.50 46.25 293.66 19.91 92.50 293.66 19.92 92.50 293.66 19.93 92.50 293.66 19.94 92.50 293.66 19.95 92.50 293.66 369.99 19.96 92.50 293.66 369.99 19.97 92.50 293.66 369.99 19.98 92.50 293.66 369.99 19.99 92.50 369.99 20.00 92.50 369.99 20.01 92.50 369.99 20.02 92.50 369.99 20.03 369.99 20.04 369.99 20.05 369.99 20.06 369.99 20.07 369.99 20.08 369.99 20.09 369.99 20.10 369.99 20.11 369.99 20.12 369.99 20.13 369.99 20.14 369.99 20.15 369.99 20.16 369.99 20.17 369.99 20.18 369.99 20.19 369.99 20.20 369.99 20.21 369.99 20.22 369.99 20.23 369.99 20.24 369.99 20.25 369.99 20.26 369.99 20.27 369.99 20.28 369.99 20.29 369.99 20.30 369.99 20.31 369.99 20.32 369.99 20.33 369.99 20.34 369.99 20.35 369.99 20.36 369.99 20.37 369.99 20.38 369.99 20.39 369.99 20.40 369.99 20.41 369.99 20.42 369.99 20.43 369.99 20.44 369.99 51.91 20.45 369.99 51.91 103.83 20.46 369.99 51.91 103.83 20.47 369.99 51.91 103.83 20.48 369.99 51.91 103.83 20.49 51.91 103.83 207.65 20.50 51.91 103.83 207.65 20.51 51.91 103.83 207.65 20.52 51.91 103.83 207.65 20.53 51.91 103.83 207.65 20.54 51.91 103.83 207.65 20.55 51.91 103.83 207.65 20.56 51.91 103.83 207.65 20.57 51.91 103.83 207.65 20.58 51.91 103.83 207.65 20.59 51.91 103.83 207.65 20.60 51.91 103.83 207.65 20.61 51.91 103.83 207.65 20.62 51.91 103.83 207.65 20.63 51.91 103.83 207.65 20.64 51.91 103.83 207.65 20.65 51.91 103.83 207.65 20.66 51.91 103.83 207.65 20.67 51.91 103.83 207.65 20.68 51.91 103.83 207.65 20.69 51.91 103.83 207.65 20.70 51.91 103.83 207.65 20.71 51.91 103.83 207.65 20.72 51.91 103.83 207.65 20.73 51.91 103.83 207.65 20.74 51.91 103.83 207.65 20.75 51.91 103.83 207.65 20.76 51.91 103.83 207.65 20.77 51.91 103.83 207.65 20.78 51.91 103.83 207.65 20.79 51.91 103.83 207.65 20.80 51.91 103.83 207.65 20.81 51.91 103.83 207.65 20.82 51.91 103.83 207.65 20.83 51.91 103.83 207.65 20.84 51.91 103.83 207.65 20.85 51.91 103.83 207.65 20.86 51.91 103.83 207.65 20.87 51.91 103.83 207.65 20.88 51.91 103.83 207.65 20.89 51.91 103.83 207.65 20.90 51.91 103.83 207.65 20.91 51.91 103.83 207.65 20.92 51.91 103.83 207.65 20.93 51.91 103.83 207.65 20.94 51.91 103.83 207.65 20.95 51.91 103.83 207.65 20.96 51.91 103.83 207.65 20.97 51.91 103.83 207.65 20.98 51.91 103.83 207.65 20.99 51.91 103.83 207.65 21.00 51.91 103.83 207.65 21.01 51.91 103.83 207.65 21.02 51.91 103.83 207.65 21.03 51.91 103.83 207.65 261.63 21.04 51.91 103.83 207.65 261.63 21.05 51.91 103.83 207.65 261.63 21.06 51.91 103.83 207.65 261.63 21.07 51.91 103.83 207.65 261.63 21.08 51.91 103.83 207.65 261.63 21.09 51.91 103.83 261.63 21.10 51.91 103.83 261.63 21.11 51.91 103.83 261.63 21.12 51.91 103.83 261.63 21.13 51.91 103.83 261.63 21.14 51.91 103.83 261.63 21.15 51.91 103.83 261.63 21.16 51.91 103.83 261.63 21.17 51.91 103.83 261.63 21.18 51.91 103.83 261.63 21.19 51.91 103.83 261.63 21.20 51.91 103.83 261.63 21.21 51.91 103.83 261.63 21.22 51.91 103.83 261.63 21.23 51.91 103.83 261.63 21.24 51.91 103.83 261.63 21.25 51.91 103.83 261.63 21.26 51.91 103.83 261.63 21.27 51.91 103.83 261.63 21.28 51.91 103.83 261.63 21.29 51.91 103.83 261.63 21.30 51.91 103.83 261.63 21.31 51.91 103.83 261.63 21.32 51.91 103.83 261.63 21.33 51.91 103.83 261.63 21.34 51.91 103.83 261.63 21.35 51.91 103.83 261.63 21.36 51.91 103.83 261.63 21.37 51.91 103.83 261.63 21.38 51.91 103.83 261.63 21.39 51.91 103.83 261.63 21.40 51.91 103.83 261.63 21.41 51.91 103.83 261.63 21.42 51.91 103.83 261.63 21.43 51.91 103.83 261.63 21.44 51.91 103.83 261.63 21.45 51.91 103.83 261.63 21.46 51.91 103.83 261.63 21.47 51.91 103.83 261.63 21.48 51.91 103.83 261.63 21.49 51.91 103.83 261.63 21.50 51.91 103.83 261.63 369.99 21.51 51.91 103.83 261.63 369.99 21.52 51.91 103.83 261.63 369.99 21.53 51.91 103.83 369.99 21.54 51.91 103.83 369.99 21.55 51.91 103.83 369.99 21.56 51.91 103.83 369.99 21.57 51.91 103.83 369.99 21.58 51.91 103.83 369.99 21.59 51.91 103.83 369.99 21.60 51.91 103.83 369.99 21.61 51.91 103.83 369.99 21.62 51.91 103.83 369.99 21.63 51.91 103.83 369.99 21.64 51.91 103.83 369.99 21.65 51.91 103.83 369.99 21.66 51.91 103.83 369.99 21.67 51.91 103.83 369.99 21.68 51.91 103.83 369.99 21.69 51.91 103.83 369.99 21.70 51.91 103.83 369.99 21.71 51.91 103.83 369.99 21.72 51.91 103.83 369.99 21.73 51.91 103.83 369.99 21.74 51.91 103.83 369.99 21.75 51.91 103.83 369.99 21.76 51.91 103.83 369.99 21.77 51.91 103.83 369.99 21.78 51.91 103.83 369.99 21.79 51.91 103.83 369.99 21.80 51.91 103.83 369.99 21.81 51.91 103.83 369.99 21.82 51.91 103.83 369.99 21.83 51.91 103.83 369.99 21.84 51.91 103.83 369.99 21.85 51.91 103.83 369.99 21.86 51.91 103.83 369.99 21.87 51.91 103.83 369.99 21.88 51.91 103.83 369.99 21.89 51.91 103.83 369.99 21.90 51.91 103.83 369.99 21.91 51.91 103.83 369.99 21.92 51.91 103.83 369.99 21.93 51.91 103.83 369.99 21.94 51.91 103.83 369.99 21.95 51.91 103.83 369.99 21.96 51.91 103.83 369.99 21.97 51.91 103.83 369.99 21.98 51.91 103.83 369.99 21.99 51.91 103.83 369.99 22.00 51.91 103.83 369.99 207.65 22.01 51.91 103.83 369.99 207.65 22.02 51.91 103.83 369.99 207.65 22.03 51.91 103.83 369.99 207.65 22.04 51.91 103.83 207.65 22.05 51.91 103.83 207.65 22.06 51.91 103.83 207.65 22.07 51.91 103.83 207.65 22.08 51.91 103.83 207.65 22.09 51.91 103.83 207.65 22.10 51.91 103.83 207.65 22.11 51.91 103.83 207.65 22.12 51.91 103.83 207.65 22.13 51.91 103.83 207.65 22.14 51.91 103.83 207.65 22.15 51.91 103.83 207.65 22.16 51.91 103.83 207.65 22.17 51.91 103.83 207.65 22.18 51.91 103.83 207.65 22.19 51.91 103.83 207.65 22.20 51.91 103.83 207.65 22.21 51.91 103.83 207.65 22.22 51.91 103.83 207.65 22.23 51.91 103.83 207.65 22.24 51.91 103.83 207.65 22.25 51.91 103.83 207.65 22.26 51.91 103.83 207.65 22.27 51.91 103.83 207.65 22.28 51.91 103.83 207.65 22.29 51.91 103.83 207.65 22.30 51.91 103.83 207.65 22.31 51.91 103.83 207.65 22.32 51.91 103.83 207.65 22.33 51.91 103.83 207.65 22.34 51.91 103.83 207.65 22.35 51.91 103.83 207.65 22.36 51.91 103.83 207.65 22.37 51.91 103.83 207.65 22.38 51.91 103.83 207.65 22.39 51.91 103.83 207.65 22.40 51.91 103.83 207.65 22.41 51.91 103.83 207.65 22.42 51.91 103.83 207.65 22.43 51.91 103.83 207.65 22.44 51.91 103.83 207.65 22.45 51.91 103.83 207.65 22.46 51.91 103.83 207.65 22.47 51.91 103.83 207.65 277.18 22.48 51.91 103.83 207.65 277.18 22.49 51.91 103.83 207.65 277.18 22.50 51.91 103.83 207.65 277.18 22.51 51.91 103.83 207.65 277.18 22.52 51.91 103.83 207.65 277.18 22.53 51.91 103.83 277.18 22.54 51.91 103.83 277.18 22.55 51.91 103.83 277.18 22.56 51.91 103.83 277.18 22.57 51.91 103.83 277.18 22.58 51.91 103.83 277.18 22.59 51.91 103.83 277.18 22.60 51.91 103.83 277.18 22.61 51.91 103.83 277.18 22.62 51.91 103.83 277.18 22.63 51.91 103.83 277.18 22.64 51.91 103.83 277.18 22.65 51.91 103.83 277.18 22.66 51.91 103.83 277.18 22.67 51.91 103.83 277.18 22.68 51.91 103.83 277.18 22.69 51.91 103.83 277.18 22.70 51.91 103.83 277.18 22.71 51.91 103.83 277.18 22.72 51.91 103.83 277.18 22.73 51.91 103.83 277.18 22.74 51.91 103.83 277.18 22.75 51.91 103.83 277.18 22.76 51.91 103.83 277.18 22.77 51.91 103.83 277.18 22.78 51.91 103.83 277.18 22.79 51.91 103.83 277.18 22.80 51.91 103.83 277.18 22.81 51.91 103.83 277.18 22.82 51.91 103.83 277.18 22.83 51.91 103.83 277.18 22.84 51.91 103.83 277.18 22.85 51.91 103.83 277.18 22.86 51.91 103.83 277.18 22.87 51.91 103.83 277.18 22.88 51.91 103.83 277.18 22.89 51.91 103.83 277.18 22.90 51.91 103.83 277.18 22.91 51.91 103.83 277.18 22.92 51.91 103.83 277.18 22.93 51.91 103.83 277.18 22.94 51.91 103.83 277.18 329.63 22.95 51.91 103.83 277.18 329.63 22.96 51.91 103.83 277.18 329.63 22.97 51.91 103.83 277.18 329.63 22.98 51.91 103.83 277.18 329.63 22.99 51.91 103.83 329.63 23.00 51.91 103.83 329.63 23.01 51.91 103.83 329.63 23.02 51.91 103.83 329.63 23.03 51.91 103.83 329.63 23.04 103.83 329.63 23.05 103.83 329.63 23.06 103.83 329.63 23.07 103.83 329.63 23.08 329.63 23.09 329.63 23.10 329.63 23.11 329.63 23.12 329.63 23.13 329.63 23.14 329.63 23.15 329.63 23.16 329.63 23.17 329.63 23.18 329.63 23.19 329.63 23.20 329.63 23.21 329.63 23.22 329.63 23.23 329.63 23.24 329.63 23.25 329.63 23.26 329.63 23.27 329.63 23.28 329.63 23.29 329.63 23.30 329.63 23.31 329.63 23.32 329.63 23.33 329.63 23.34 329.63 23.35 329.63 23.36 329.63 23.37 329.63 23.38 329.63 23.39 329.63 23.40 329.63 23.41 329.63 23.42 329.63 23.43 329.63 23.44 329.63 23.45 329.63 23.46 329.63 23.47 329.63 51.91 207.65 103.83 23.48 329.63 51.91 207.65 103.83 23.49 329.63 51.91 207.65 103.83 23.50 329.63 51.91 207.65 103.83 23.51 51.91 207.65 103.83 23.52 51.91 207.65 103.83 23.53 51.91 207.65 103.83 23.54 51.91 207.65 103.83 23.55 51.91 207.65 103.83 23.56 51.91 207.65 103.83 23.57 51.91 207.65 103.83 23.58 51.91 207.65 103.83 23.59 51.91 207.65 103.83 23.60 51.91 207.65 103.83 23.61 51.91 207.65 103.83 23.62 51.91 207.65 103.83 23.63 51.91 207.65 103.83 23.64 51.91 207.65 103.83 23.65 51.91 207.65 103.83 23.66 51.91 207.65 103.83 23.67 51.91 207.65 103.83 23.68 51.91 207.65 103.83 23.69 51.91 207.65 103.83 23.70 51.91 207.65 103.83 23.71 51.91 207.65 103.83 23.72 51.91 207.65 103.83 23.73 51.91 207.65 103.83 23.74 51.91 207.65 103.83 23.75 51.91 207.65 103.83 23.76 51.91 207.65 103.83 23.77 51.91 207.65 103.83 23.78 51.91 207.65 103.83 23.79 51.91 207.65 103.83 23.80 51.91 207.65 103.83 23.81 51.91 207.65 103.83 23.82 51.91 207.65 103.83 23.83 51.91 207.65 103.83 23.84 51.91 207.65 103.83 23.85 51.91 207.65 103.83 23.86 51.91 207.65 103.83 23.87 51.91 207.65 103.83 23.88 51.91 207.65 103.83 23.89 51.91 207.65 103.83 23.90 51.91 207.65 103.83 23.91 51.91 207.65 103.83 23.92 51.91 207.65 103.83 23.93 51.91 207.65 103.83 23.94 51.91 207.65 103.83 23.95 51.91 207.65 103.83 23.96 51.91 207.65 103.83 23.97 51.91 207.65 103.83 23.98 51.91 207.65 103.83 23.99 51.91 207.65 103.83 24.00 51.91 207.65 103.83 24.01 51.91 207.65 103.83 24.02 51.91 207.65 103.83 24.03 51.91 207.65 103.83 24.04 51.91 207.65 103.83 24.05 51.91 207.65 103.83 24.06 51.91 207.65 103.83 24.07 51.91 207.65 103.83 24.08 51.91 207.65 103.83 24.09 51.91 207.65 103.83 24.10 51.91 207.65 103.83 24.11 51.91 207.65 103.83 24.12 51.91 207.65 103.83 277.18 24.13 51.91 207.65 103.83 277.18 24.14 51.91 207.65 103.83 277.18 24.15 51.91 207.65 103.83 277.18 24.16 51.91 207.65 103.83 277.18 24.17 51.91 207.65 103.83 277.18 24.18 51.91 103.83 277.18 24.19 51.91 103.83 277.18 24.20 51.91 103.83 277.18 24.21 51.91 103.83 277.18 24.22 51.91 103.83 277.18 24.23 51.91 103.83 277.18 24.24 51.91 103.83 277.18 24.25 51.91 103.83 277.18 24.26 51.91 103.83 277.18 24.27 51.91 103.83 277.18 24.28 51.91 103.83 277.18 24.29 51.91 103.83 277.18 24.30 51.91 103.83 277.18 24.31 51.91 103.83 277.18 24.32 51.91 103.83 277.18 24.33 51.91 103.83 277.18 24.34 51.91 103.83 277.18 24.35 51.91 103.83 277.18 24.36 51.91 103.83 277.18 24.37 51.91 103.83 277.18 24.38 51.91 103.83 277.18 24.39 51.91 103.83 277.18 24.40 51.91 103.83 277.18 24.41 51.91 103.83 277.18 24.42 51.91 103.83 277.18 24.43 51.91 103.83 277.18 24.44 51.91 103.83 277.18 24.45 51.91 103.83 277.18 24.46 51.91 103.83 277.18 24.47 51.91 103.83 277.18 24.48 51.91 103.83 277.18 24.49 51.91 103.83 277.18 24.50 51.91 103.83 277.18 24.51 51.91 103.83 277.18 24.52 51.91 103.83 277.18 24.53 51.91 103.83 277.18 24.54 51.91 103.83 277.18 24.55 51.91 103.83 277.18 24.56 51.91 103.83 277.18 24.57 51.91 103.83 277.18 24.58 51.91 103.83 277.18 24.59 51.91 103.83 277.18 311.13 24.60 51.91 103.83 277.18 311.13 24.61 51.91 103.83 311.13 24.62 51.91 103.83 311.13 24.63 51.91 103.83 311.13 24.64 51.91 103.83 311.13 24.65 51.91 103.83 311.13 24.66 51.91 103.83 311.13 24.67 51.91 103.83 311.13 24.68 51.91 103.83 311.13 24.69 51.91 103.83 311.13 24.70 51.91 103.83 311.13 24.71 51.91 103.83 311.13 24.72 51.91 103.83 311.13 24.73 51.91 103.83 311.13 24.74 51.91 103.83 311.13 24.75 51.91 103.83 311.13 24.76 51.91 103.83 311.13 24.77 51.91 103.83 311.13 24.78 51.91 103.83 311.13 24.79 51.91 103.83 311.13 24.80 51.91 103.83 311.13 24.81 51.91 103.83 311.13 24.82 51.91 103.83 311.13 24.83 51.91 103.83 311.13 24.84 51.91 103.83 311.13 24.85 51.91 103.83 311.13 24.86 51.91 103.83 311.13 24.87 51.91 103.83 311.13 24.88 51.91 103.83 311.13 24.89 51.91 103.83 311.13 24.90 51.91 103.83 311.13 24.91 51.91 103.83 311.13 24.92 51.91 103.83 311.13 24.93 51.91 103.83 311.13 24.94 51.91 103.83 311.13 24.95 51.91 103.83 311.13 24.96 51.91 103.83 311.13 24.97 51.91 103.83 311.13 24.98 51.91 103.83 311.13 24.99 51.91 103.83 311.13 25.00 51.91 103.83 311.13 25.01 51.91 103.83 311.13 25.02 51.91 103.83 311.13 25.03 51.91 103.83 311.13 25.04 51.91 103.83 311.13 25.05 51.91 103.83 311.13 25.06 51.91 103.83 311.13 25.07 51.91 103.83 311.13 25.08 51.91 103.83 311.13 25.09 51.91 103.83 311.13 185.00 25.10 51.91 103.83 185.00 25.11 51.91 103.83 185.00 25.12 51.91 103.83 185.00 25.13 51.91 103.83 185.00 25.14 51.91 103.83 185.00 25.15 51.91 103.83 185.00 25.16 51.91 103.83 185.00 25.17 51.91 103.83 185.00 25.18 51.91 103.83 185.00 25.19 51.91 103.83 185.00 25.20 51.91 103.83 185.00 25.21 51.91 103.83 185.00 25.22 51.91 103.83 185.00 25.23 51.91 103.83 185.00 25.24 51.91 103.83 185.00 25.25 51.91 103.83 185.00 25.26 51.91 103.83 185.00 25.27 51.91 103.83 185.00 25.28 51.91 103.83 185.00 25.29 51.91 103.83 185.00 25.30 51.91 103.83 185.00 25.31 51.91 103.83 185.00 25.32 51.91 103.83 185.00 25.33 51.91 103.83 185.00 25.34 51.91 103.83 185.00 25.35 51.91 103.83 185.00 25.36 51.91 103.83 185.00 25.37 51.91 103.83 185.00 25.38 51.91 103.83 185.00 25.39 51.91 103.83 185.00 25.40 51.91 103.83 185.00 25.41 51.91 103.83 185.00 25.42 51.91 103.83 185.00 25.43 51.91 103.83 185.00 25.44 51.91 103.83 185.00 25.45 51.91 103.83 185.00 25.46 51.91 103.83 185.00 25.47 51.91 103.83 185.00 25.48 51.91 103.83 185.00 25.49 51.91 103.83 185.00 25.50 51.91 103.83 185.00 25.51 51.91 103.83 185.00 25.52 51.91 103.83 185.00 25.53 51.91 103.83 185.00 25.54 51.91 103.83 185.00 25.55 51.91 103.83 185.00 261.63 25.56 51.91 103.83 185.00 261.63 25.57 51.91 103.83 185.00 261.63 25.58 51.91 103.83 185.00 261.63 25.59 51.91 103.83 185.00 261.63 25.60 51.91 103.83 185.00 261.63 25.61 51.91 103.83 261.63 25.62 51.91 103.83 261.63 25.63 51.91 103.83 261.63 25.64 51.91 103.83 261.63 25.65 51.91 103.83 261.63 25.66 51.91 103.83 261.63 25.67 51.91 103.83 261.63 25.68 51.91 103.83 261.63 25.69 51.91 103.83 261.63 25.70 51.91 103.83 261.63 25.71 51.91 103.83 261.63 25.72 51.91 103.83 261.63 25.73 51.91 103.83 261.63 25.74 51.91 103.83 261.63 25.75 51.91 103.83 261.63 25.76 51.91 103.83 261.63 25.77 51.91 103.83 261.63 25.78 51.91 103.83 261.63 25.79 51.91 103.83 261.63 25.80 51.91 103.83 261.63 25.81 51.91 103.83 261.63 25.82 51.91 103.83 261.63 25.83 51.91 103.83 261.63 25.84 51.91 103.83 261.63 25.85 51.91 103.83 261.63 25.86 51.91 103.83 261.63 25.87 51.91 103.83 261.63 25.88 51.91 103.83 261.63 25.89 51.91 103.83 261.63 25.90 51.91 103.83 261.63 25.91 51.91 103.83 261.63 25.92 103.83 261.63 25.93 103.83 261.63 25.94 103.83 261.63 25.95 103.83 261.63 25.96 103.83 261.63 25.97 103.83 261.63 25.98 103.83 261.63 25.99 103.83 261.63 26.00 103.83 261.63 26.01 261.63 26.02 261.63 26.03 261.63 26.04 261.63 26.05 261.63 26.06 261.63 311.13 26.07 261.63 311.13 26.08 261.63 311.13 26.09 311.13 26.10 311.13 26.11 311.13 26.12 311.13 26.13 311.13 26.14 311.13 26.15 311.13 26.16 311.13 26.17 311.13 26.18 311.13 26.19 311.13 26.20 311.13 26.21 311.13 26.22 311.13 26.23 311.13 26.24 311.13 26.25 311.13 26.26 311.13 26.27 311.13 26.28 311.13 26.29 311.13 26.30 311.13 26.31 311.13 26.32 311.13 26.33 311.13 26.34 311.13 26.35 311.13 26.36 311.13 26.37 311.13 26.38 311.13 26.39 311.13 26.40 311.13 26.41 311.13 26.42 311.13 26.43 311.13 26.44 311.13 26.45 311.13 26.46 311.13 26.47 311.13 26.48 311.13 26.49 311.13 26.50 311.13 26.51 311.13 26.52 311.13 26.53 311.13 26.54 311.13 26.55 311.13 26.56 311.13 26.57 311.13 26.58 311.13 26.59 311.13 26.60 311.13 26.61 311.13 26.62 311.13 26.63 311.13 26.64 311.13 26.65 311.13 26.66 311.13 26.67 311.13 26.68 311.13 26.69 311.13 26.70 311.13 26.71 311.13 26.72 311.13 26.73 26.74 69.30 26.75 69.30 138.59 164.81 26.76 69.30 138.59 164.81 26.77 69.30 138.59 164.81 103.83 26.78 69.30 138.59 164.81 103.83 26.79 69.30 138.59 164.81 103.83 26.80 69.30 138.59 164.81 103.83 26.81 69.30 138.59 164.81 103.83 26.82 69.30 138.59 164.81 103.83 26.83 69.30 138.59 164.81 103.83 26.84 69.30 138.59 164.81 103.83 26.85 69.30 138.59 164.81 103.83 26.86 69.30 138.59 164.81 103.83 26.87 69.30 138.59 164.81 103.83 26.88 69.30 138.59 164.81 103.83 26.89 69.30 138.59 164.81 103.83 26.90 69.30 138.59 164.81 103.83 26.91 69.30 138.59 164.81 103.83 26.92 69.30 138.59 164.81 103.83 26.93 69.30 138.59 164.81 103.83 26.94 69.30 138.59 164.81 103.83 26.95 69.30 138.59 164.81 103.83 26.96 69.30 138.59 164.81 103.83 26.97 69.30 138.59 164.81 103.83 26.98 69.30 138.59 164.81 103.83 26.99 69.30 138.59 164.81 103.83 27.00 69.30 138.59 164.81 103.83 27.01 69.30 138.59 164.81 103.83 27.02 69.30 138.59 164.81 103.83 27.03 69.30 138.59 164.81 103.83 27.04 69.30 138.59 164.81 103.83 27.05 69.30 138.59 164.81 103.83 27.06 69.30 138.59 164.81 103.83 27.07 69.30 138.59 164.81 103.83 27.08 69.30 138.59 164.81 103.83 27.09 69.30 138.59 164.81 103.83 27.10 69.30 138.59 164.81 103.83 27.11 69.30 138.59 164.81 103.83 27.12 69.30 138.59 164.81 103.83 27.13 69.30 138.59 164.81 103.83 27.14 69.30 138.59 164.81 103.83 27.15 69.30 138.59 164.81 103.83 27.16 69.30 138.59 164.81 103.83 27.17 69.30 138.59 164.81 103.83 27.18 69.30 138.59 164.81 103.83 27.19 69.30 138.59 164.81 103.83 27.20 69.30 138.59 164.81 103.83 27.21 69.30 138.59 164.81 103.83 27.22 69.30 138.59 164.81 103.83 27.23 69.30 138.59 164.81 103.83 27.24 69.30 138.59 164.81 103.83 27.25 69.30 138.59 164.81 103.83 27.26 69.30 138.59 164.81 103.83 27.27 69.30 138.59 164.81 103.83 27.28 69.30 138.59 164.81 103.83 27.29 69.30 138.59 164.81 103.83 27.30 69.30 138.59 164.81 103.83 27.31 69.30 138.59 164.81 103.83 27.32 69.30 138.59 164.81 103.83 27.33 69.30 138.59 164.81 103.83 27.34 69.30 138.59 164.81 103.83 27.35 69.30 138.59 164.81 103.83 27.36 69.30 138.59 164.81 103.83 27.37 69.30 138.59 164.81 103.83 27.38 69.30 138.59 164.81 103.83 27.39 69.30 138.59 164.81 103.83 27.40 69.30 138.59 164.81 103.83 27.41 69.30 138.59 164.81 103.83 27.42 69.30 138.59 164.81 103.83 27.43 69.30 138.59 164.81 103.83 27.44 69.30 138.59 164.81 103.83 27.45 69.30 138.59 164.81 103.83 27.46 69.30 138.59 164.81 103.83 27.47 69.30 138.59 164.81 103.83 27.48 69.30 138.59 164.81 103.83 27.49 69.30 138.59 164.81 103.83 207.65 27.50 69.30 138.59 164.81 103.83 207.65 27.51 69.30 138.59 164.81 103.83 207.65 27.52 69.30 138.59 164.81 103.83 207.65 27.53 69.30 138.59 164.81 103.83 207.65 27.54 69.30 138.59 164.81 103.83 207.65 27.55 69.30 138.59 164.81 103.83 207.65 27.56 69.30 138.59 164.81 103.83 207.65 27.57 69.30 138.59 164.81 103.83 207.65 27.58 69.30 138.59 103.83 207.65 27.59 69.30 138.59 103.83 207.65 27.60 69.30 138.59 103.83 207.65 27.61 69.30 138.59 103.83 207.65 27.62 69.30 138.59 103.83 207.65 27.63 69.30 138.59 103.83 207.65 27.64 69.30 138.59 103.83 207.65 27.65 69.30 138.59 103.83 207.65 27.66 69.30 138.59 103.83 207.65 27.67 69.30 138.59 103.83 207.65 27.68 69.30 138.59 103.83 207.65 27.69 69.30 138.59 103.83 207.65 27.70 69.30 138.59 103.83 207.65 27.71 69.30 138.59 103.83 207.65 27.72 69.30 138.59 103.83 207.65 27.73 69.30 138.59 103.83 207.65 27.74 69.30 138.59 103.83 207.65 27.75 69.30 138.59 103.83 207.65 27.76 69.30 138.59 103.83 207.65 27.77 69.30 138.59 103.83 207.65 27.78 69.30 138.59 103.83 207.65 27.79 69.30 138.59 103.83 207.65 27.80 69.30 138.59 103.83 207.65 27.81 69.30 138.59 103.83 207.65 27.82 69.30 138.59 103.83 207.65 27.83 69.30 138.59 103.83 207.65 27.84 69.30 138.59 103.83 207.65 27.85 69.30 138.59 103.83 207.65 27.86 69.30 138.59 103.83 207.65 27.87 69.30 138.59 103.83 207.65 27.88 69.30 138.59 103.83 207.65 27.89 69.30 138.59 103.83 207.65 27.90 69.30 138.59 103.83 207.65 27.91 69.30 138.59 103.83 207.65 27.92 69.30 138.59 103.83 207.65 27.93 69.30 138.59 103.83 207.65 27.94 69.30 138.59 103.83 207.65 27.95 69.30 138.59 103.83 207.65 27.96 69.30 138.59 103.83 207.65 27.97 69.30 138.59 103.83 207.65 27.98 69.30 138.59 103.83 207.65 27.99 69.30 138.59 103.83 207.65 28.00 69.30 138.59 103.83 207.65 28.01 69.30 138.59 103.83 207.65 277.18 28.02 69.30 138.59 103.83 207.65 277.18 28.03 69.30 138.59 103.83 207.65 277.18 28.04 69.30 138.59 103.83 207.65 277.18 28.05 69.30 138.59 103.83 277.18 28.06 69.30 138.59 103.83 277.18 28.07 69.30 138.59 103.83 277.18 28.08 69.30 138.59 103.83 277.18 28.09 69.30 138.59 103.83 277.18 28.10 69.30 138.59 103.83 277.18 28.11 69.30 138.59 103.83 277.18 28.12 69.30 138.59 103.83 277.18 28.13 69.30 138.59 103.83 277.18 28.14 69.30 138.59 103.83 277.18 28.15 69.30 138.59 103.83 277.18 28.16 69.30 138.59 103.83 277.18 28.17 69.30 138.59 103.83 277.18 28.18 69.30 138.59 103.83 277.18 28.19 69.30 138.59 103.83 277.18 28.20 69.30 138.59 103.83 277.18 28.21 69.30 138.59 103.83 277.18 28.22 69.30 138.59 103.83 277.18 28.23 69.30 138.59 103.83 277.18 28.24 69.30 138.59 103.83 277.18 28.25 69.30 138.59 103.83 277.18 28.26 69.30 138.59 103.83 277.18 28.27 69.30 138.59 103.83 277.18 28.28 69.30 138.59 103.83 277.18 28.29 69.30 138.59 103.83 277.18 28.30 69.30 138.59 103.83 277.18 28.31 69.30 138.59 103.83 277.18 28.32 69.30 138.59 103.83 277.18 28.33 69.30 138.59 103.83 277.18 28.34 69.30 138.59 103.83 277.18 28.35 69.30 138.59 103.83 277.18 28.36 69.30 138.59 103.83 277.18 28.37 69.30 138.59 103.83 277.18 28.38 69.30 138.59 103.83 277.18 28.39 69.30 138.59 103.83 277.18 28.40 69.30 138.59 103.83 277.18 28.41 69.30 138.59 103.83 277.18 28.42 69.30 138.59 103.83 277.18 28.43 69.30 138.59 103.83 277.18 28.44 69.30 138.59 103.83 277.18 28.45 69.30 138.59 103.83 277.18 28.46 69.30 138.59 103.83 277.18 28.47 69.30 138.59 103.83 277.18 28.48 69.30 138.59 103.83 277.18 28.49 69.30 138.59 103.83 277.18 28.50 69.30 138.59 103.83 277.18 28.51 69.30 138.59 103.83 277.18 207.65 28.52 69.30 138.59 103.83 277.18 207.65 28.53 69.30 138.59 103.83 207.65 28.54 69.30 138.59 103.83 207.65 28.55 69.30 138.59 103.83 207.65 28.56 69.30 138.59 103.83 207.65 28.57 69.30 138.59 103.83 207.65 28.58 69.30 138.59 103.83 207.65 28.59 69.30 138.59 103.83 207.65 28.60 69.30 138.59 103.83 207.65 28.61 69.30 138.59 103.83 207.65 28.62 69.30 138.59 103.83 207.65 28.63 69.30 138.59 103.83 207.65 28.64 69.30 138.59 103.83 207.65 28.65 69.30 138.59 103.83 207.65 28.66 69.30 138.59 103.83 207.65 28.67 69.30 138.59 103.83 207.65 28.68 69.30 138.59 103.83 207.65 28.69 69.30 138.59 103.83 207.65 28.70 69.30 138.59 103.83 207.65 28.71 69.30 138.59 103.83 207.65 28.72 69.30 138.59 103.83 207.65 28.73 69.30 138.59 103.83 207.65 28.74 69.30 138.59 103.83 207.65 28.75 69.30 138.59 103.83 207.65 28.76 69.30 138.59 103.83 207.65 28.77 69.30 138.59 103.83 207.65 28.78 69.30 138.59 103.83 207.65 28.79 69.30 138.59 103.83 207.65 28.80 69.30 138.59 103.83 207.65 28.81 69.30 138.59 103.83 207.65 28.82 69.30 138.59 103.83 207.65 28.83 69.30 138.59 103.83 207.65 28.84 69.30 138.59 103.83 207.65 28.85 69.30 138.59 103.83 207.65 28.86 69.30 138.59 103.83 207.65 28.87 69.30 138.59 103.83 207.65 28.88 69.30 138.59 103.83 207.65 28.89 69.30 138.59 103.83 207.65 28.90 69.30 138.59 103.83 207.65 28.91 69.30 138.59 103.83 207.65 28.92 69.30 138.59 103.83 207.65 28.93 69.30 138.59 103.83 207.65 28.94 69.30 138.59 103.83 207.65 28.95 69.30 138.59 103.83 207.65 28.96 69.30 138.59 103.83 207.65 28.97 69.30 138.59 103.83 207.65 28.98 69.30 138.59 103.83 207.65 28.99 69.30 138.59 103.83 207.65 29.00 69.30 138.59 103.83 207.65 277.18 29.01 69.30 138.59 103.83 207.65 277.18 29.02 69.30 138.59 103.83 207.65 277.18 29.03 69.30 138.59 103.83 207.65 277.18 29.04 69.30 138.59 103.83 207.65 277.18 29.05 69.30 138.59 103.83 207.65 277.18 29.06 69.30 138.59 103.83 277.18 29.07 69.30 138.59 103.83 277.18 29.08 69.30 138.59 103.83 277.18 29.09 69.30 138.59 103.83 277.18 29.10 69.30 138.59 103.83 277.18 29.11 69.30 138.59 103.83 277.18 29.12 69.30 138.59 103.83 277.18 29.13 69.30 138.59 103.83 277.18 29.14 69.30 138.59 103.83 277.18 29.15 69.30 138.59 103.83 277.18 29.16 69.30 138.59 103.83 277.18 29.17 69.30 138.59 103.83 277.18 29.18 69.30 138.59 103.83 277.18 29.19 69.30 138.59 103.83 277.18 29.20 69.30 138.59 103.83 277.18 29.21 69.30 138.59 103.83 277.18 29.22 69.30 138.59 103.83 277.18 29.23 69.30 138.59 103.83 277.18 29.24 69.30 138.59 103.83 277.18 29.25 69.30 138.59 103.83 277.18 29.26 69.30 138.59 103.83 277.18 29.27 69.30 138.59 103.83 277.18 29.28 69.30 138.59 103.83 277.18 29.29 69.30 138.59 103.83 277.18 29.30 69.30 138.59 103.83 277.18 29.31 69.30 138.59 103.83 277.18 29.32 69.30 138.59 103.83 277.18 29.33 69.30 138.59 103.83 277.18 29.34 69.30 138.59 103.83 277.18 29.35 69.30 138.59 103.83 277.18 29.36 69.30 138.59 103.83 277.18 29.37 69.30 138.59 103.83 277.18 29.38 69.30 138.59 103.83 277.18 29.39 69.30 138.59 103.83 277.18 29.40 69.30 138.59 103.83 277.18 29.41 69.30 138.59 103.83 277.18 29.42 69.30 138.59 103.83 277.18 29.43 69.30 138.59 103.83 277.18 29.44 69.30 138.59 103.83 277.18 29.45 69.30 138.59 103.83 277.18 29.46 69.30 138.59 103.83 277.18 29.47 69.30 138.59 103.83 277.18 29.48 69.30 138.59 103.83 277.18 29.49 69.30 138.59 103.83 277.18 329.63 29.50 69.30 138.59 103.83 277.18 329.63 29.51 69.30 138.59 103.83 277.18 329.63 29.52 69.30 138.59 103.83 329.63 29.53 69.30 138.59 103.83 329.63 29.54 69.30 138.59 103.83 329.63 29.55 69.30 138.59 103.83 329.63 29.56 69.30 138.59 103.83 329.63 29.57 69.30 138.59 103.83 329.63 29.58 69.30 138.59 103.83 329.63 29.59 69.30 138.59 103.83 329.63 29.60 69.30 138.59 103.83 329.63 29.61 69.30 138.59 103.83 329.63 29.62 69.30 138.59 103.83 329.63 29.63 69.30 138.59 103.83 329.63 29.64 69.30 138.59 103.83 329.63 29.65 69.30 138.59 103.83 329.63 29.66 69.30 138.59 103.83 329.63 29.67 69.30 138.59 103.83 329.63 29.68 69.30 138.59 103.83 329.63 29.69 69.30 138.59 103.83 329.63 29.70 69.30 138.59 103.83 329.63 29.71 69.30 138.59 103.83 329.63 29.72 69.30 138.59 103.83 329.63 29.73 69.30 138.59 103.83 329.63 29.74 69.30 138.59 103.83 329.63 29.75 69.30 138.59 103.83 329.63 29.76 69.30 138.59 103.83 329.63 29.77 69.30 138.59 103.83 329.63 29.78 69.30 138.59 103.83 329.63 29.79 69.30 138.59 103.83 329.63 29.80 69.30 138.59 103.83 329.63 29.81 69.30 138.59 103.83 329.63 29.82 69.30 138.59 103.83 329.63 29.83 69.30 138.59 103.83 329.63 29.84 69.30 138.59 103.83 329.63 29.85 69.30 138.59 103.83 329.63 29.86 69.30 138.59 103.83 329.63 29.87 69.30 138.59 103.83 329.63 29.88 69.30 138.59 103.83 329.63 29.89 69.30 138.59 103.83 329.63 29.90 69.30 138.59 103.83 329.63 29.91 69.30 138.59 103.83 329.63 29.92 69.30 138.59 103.83 329.63 29.93 69.30 138.59 103.83 329.63 29.94 69.30 138.59 103.83 329.63 29.95 69.30 138.59 103.83 329.63 29.96 69.30 138.59 103.83 329.63 29.97 69.30 138.59 103.83 329.63 29.98 69.30 138.59 103.83 329.63 29.99 69.30 138.59 103.83 329.63 207.65 30.00 69.30 138.59 103.83 329.63 207.65 30.01 69.30 138.59 103.83 329.63 207.65 30.02 69.30 138.59 103.83 207.65 30.03 69.30 138.59 103.83 207.65 30.04 69.30 138.59 103.83 207.65 30.05 69.30 138.59 103.83 207.65 30.06 69.30 138.59 103.83 207.65 30.07 69.30 138.59 103.83 207.65 30.08 69.30 138.59 103.83 207.65 30.09 69.30 138.59 103.83 207.65 30.10 69.30 138.59 103.83 207.65 30.11 69.30 138.59 103.83 207.65 30.12 69.30 138.59 103.83 207.65 30.13 69.30 138.59 103.83 207.65 30.14 69.30 138.59 103.83 207.65 30.15 69.30 138.59 103.83 207.65 30.16 69.30 138.59 103.83 207.65 30.17 69.30 138.59 103.83 207.65 30.18 69.30 138.59 103.83 207.65 30.19 69.30 138.59 103.83 207.65 30.20 69.30 138.59 103.83 207.65 30.21 69.30 138.59 103.83 207.65 30.22 69.30 138.59 103.83 207.65 30.23 69.30 138.59 103.83 207.65 30.24 69.30 138.59 103.83 207.65 30.25 69.30 138.59 103.83 207.65 30.26 69.30 138.59 103.83 207.65 30.27 69.30 138.59 103.83 207.65 30.28 69.30 138.59 103.83 207.65 30.29 69.30 138.59 103.83 207.65 30.30 69.30 138.59 103.83 207.65 30.31 69.30 138.59 103.83 207.65 30.32 69.30 138.59 103.83 207.65 30.33 69.30 138.59 103.83 207.65 30.34 69.30 138.59 103.83 207.65 30.35 69.30 138.59 103.83 207.65 30.36 69.30 138.59 103.83 207.65 30.37 69.30 138.59 103.83 207.65 30.38 69.30 138.59 103.83 207.65 30.39 69.30 138.59 103.83 207.65 30.40 69.30 138.59 103.83 207.65 30.41 69.30 138.59 103.83 207.65 30.42 69.30 138.59 103.83 207.65 30.43 69.30 138.59 103.83 207.65 30.44 69.30 138.59 103.83 207.65 30.45 69.30 138.59 103.83 207.65 30.46 69.30 138.59 103.83 207.65 30.47 69.30 138.59 103.83 207.65 30.48 69.30 138.59 103.83 207.65 277.18 30.49 69.30 138.59 103.83 207.65 277.18 30.50 69.30 138.59 103.83 207.65 277.18 30.51 69.30 138.59 103.83 207.65 277.18 30.52 69.30 138.59 103.83 207.65 277.18 30.53 69.30 138.59 103.83 207.65 277.18 30.54 69.30 138.59 103.83 207.65 277.18 30.55 69.30 138.59 103.83 207.65 277.18 30.56 69.30 138.59 103.83 277.18 30.57 69.30 138.59 103.83 277.18 30.58 69.30 138.59 103.83 277.18 30.59 69.30 138.59 103.83 277.18 30.60 69.30 138.59 103.83 277.18 30.61 69.30 138.59 103.83 277.18 30.62 69.30 138.59 103.83 277.18 30.63 69.30 138.59 103.83 277.18 30.64 69.30 138.59 103.83 277.18 30.65 69.30 138.59 103.83 277.18 30.66 69.30 138.59 103.83 277.18 30.67 69.30 138.59 103.83 277.18 30.68 69.30 138.59 103.83 277.18 30.69 69.30 138.59 103.83 277.18 30.70 69.30 138.59 103.83 277.18 30.71 69.30 138.59 103.83 277.18 30.72 69.30 138.59 103.83 277.18 30.73 69.30 138.59 103.83 277.18 30.74 69.30 138.59 103.83 277.18 30.75 69.30 138.59 103.83 277.18 30.76 69.30 138.59 103.83 277.18 30.77 69.30 138.59 103.83 277.18 30.78 69.30 138.59 103.83 277.18 30.79 69.30 138.59 103.83 277.18 30.80 69.30 138.59 103.83 277.18 30.81 69.30 138.59 103.83 277.18 30.82 69.30 138.59 103.83 277.18 30.83 69.30 138.59 103.83 277.18 30.84 69.30 138.59 103.83 277.18 30.85 69.30 138.59 103.83 277.18 30.86 69.30 138.59 103.83 277.18 30.87 69.30 138.59 103.83 277.18 30.88 69.30 138.59 103.83 277.18 30.89 69.30 138.59 103.83 277.18 30.90 69.30 138.59 103.83 277.18 30.91 69.30 138.59 103.83 277.18 30.92 69.30 138.59 103.83 277.18 30.93 69.30 138.59 103.83 277.18 30.94 69.30 138.59 103.83 277.18 30.95 69.30 138.59 103.83 277.18 30.96 69.30 138.59 103.83 277.18 30.97 69.30 138.59 103.83 277.18 30.98 69.30 138.59 103.83 277.18 329.63 30.99 69.30 138.59 103.83 277.18 329.63 31.00 69.30 138.59 103.83 277.18 329.63 31.01 69.30 138.59 103.83 277.18 329.63 31.02 69.30 138.59 103.83 277.18 329.63 31.03 69.30 138.59 103.83 329.63 31.04 69.30 138.59 103.83 329.63 31.05 69.30 138.59 103.83 329.63 31.06 69.30 138.59 103.83 329.63 31.07 69.30 138.59 103.83 329.63 31.08 69.30 138.59 103.83 329.63 31.09 69.30 138.59 103.83 329.63 31.10 69.30 138.59 103.83 329.63 31.11 69.30 138.59 103.83 329.63 31.12 69.30 138.59 103.83 329.63 31.13 69.30 138.59 103.83 329.63 31.14 69.30 138.59 103.83 329.63 31.15 69.30 138.59 103.83 329.63 31.16 69.30 138.59 103.83 329.63 31.17 69.30 138.59 103.83 329.63 31.18 69.30 138.59 103.83 329.63 31.19 69.30 138.59 103.83 329.63 31.20 69.30 138.59 103.83 329.63 31.21 69.30 138.59 103.83 329.63 31.22 69.30 138.59 103.83 329.63 31.23 69.30 138.59 103.83 329.63 31.24 69.30 138.59 103.83 329.63 31.25 69.30 138.59 103.83 329.63 31.26 69.30 138.59 103.83 329.63 31.27 69.30 138.59 103.83 329.63 31.28 69.30 138.59 103.83 329.63 31.29 69.30 138.59 103.83 329.63 31.30 69.30 138.59 103.83 329.63 31.31 69.30 138.59 103.83 329.63 31.32 69.30 138.59 103.83 329.63 31.33 69.30 138.59 103.83 329.63 31.34 69.30 138.59 103.83 329.63 31.35 69.30 138.59 103.83 329.63 31.36 69.30 138.59 103.83 329.63 31.37 69.30 138.59 103.83 329.63 31.38 69.30 138.59 103.83 329.63 31.39 69.30 138.59 103.83 329.63 31.40 69.30 138.59 103.83 329.63 31.41 69.30 138.59 103.83 329.63 31.42 69.30 138.59 103.83 329.63 31.43 69.30 138.59 103.83 329.63 31.44 69.30 138.59 103.83 329.63 31.45 69.30 138.59 103.83 329.63 31.46 69.30 138.59 103.83 329.63 31.47 69.30 138.59 103.83 329.63 31.48 69.30 138.59 103.83 329.63 31.49 69.30 138.59 103.83 329.63 207.65 415.30 31.50 69.30 138.59 103.83 329.63 207.65 415.30 31.51 69.30 138.59 103.83 329.63 207.65 415.30 31.52 69.30 138.59 103.83 207.65 415.30 31.53 69.30 138.59 103.83 207.65 415.30 31.54 69.30 138.59 103.83 207.65 415.30 31.55 69.30 138.59 103.83 207.65 415.30 31.56 69.30 138.59 103.83 207.65 415.30 31.57 69.30 138.59 103.83 207.65 415.30 31.58 69.30 138.59 103.83 207.65 415.30 31.59 69.30 138.59 103.83 207.65 415.30 31.60 69.30 138.59 103.83 207.65 415.30 31.61 69.30 138.59 103.83 207.65 415.30 31.62 69.30 138.59 103.83 207.65 415.30 31.63 69.30 138.59 103.83 207.65 415.30 31.64 69.30 138.59 103.83 207.65 415.30 31.65 69.30 138.59 103.83 207.65 415.30 31.66 69.30 138.59 103.83 207.65 415.30 31.67 69.30 138.59 103.83 207.65 415.30 31.68 69.30 138.59 103.83 207.65 415.30 31.69 69.30 138.59 103.83 207.65 415.30 31.70 69.30 138.59 103.83 207.65 415.30 31.71 69.30 138.59 103.83 207.65 415.30 31.72 69.30 138.59 103.83 207.65 415.30 31.73 69.30 138.59 103.83 207.65 415.30 31.74 69.30 138.59 103.83 207.65 415.30 31.75 69.30 138.59 103.83 207.65 415.30 31.76 69.30 138.59 103.83 207.65 415.30 31.77 69.30 138.59 103.83 207.65 415.30 31.78 69.30 138.59 103.83 207.65 415.30 31.79 69.30 138.59 103.83 207.65 415.30 31.80 69.30 138.59 103.83 207.65 415.30 31.81 69.30 138.59 103.83 207.65 415.30 31.82 69.30 138.59 103.83 207.65 415.30 31.83 69.30 138.59 103.83 207.65 415.30 31.84 69.30 138.59 103.83 207.65 415.30 31.85 69.30 138.59 103.83 207.65 415.30 31.86 69.30 138.59 103.83 207.65 415.30 31.87 69.30 138.59 103.83 207.65 415.30 31.88 69.30 138.59 103.83 415.30 31.89 69.30 138.59 103.83 415.30 31.90 69.30 138.59 103.83 415.30 31.91 69.30 138.59 103.83 415.30 31.92 69.30 138.59 103.83 415.30 31.93 69.30 138.59 103.83 415.30 31.94 69.30 138.59 103.83 415.30 277.18 31.95 69.30 138.59 103.83 415.30 277.18 31.96 69.30 138.59 103.83 415.30 277.18 31.97 69.30 138.59 103.83 415.30 277.18 31.98 69.30 138.59 103.83 415.30 277.18 31.99 69.30 138.59 103.83 415.30 277.18 32.00 69.30 138.59 103.83 415.30 277.18 32.01 69.30 138.59 103.83 415.30 277.18 32.02 69.30 138.59 103.83 415.30 277.18 32.03 69.30 138.59 103.83 415.30 277.18 32.04 69.30 138.59 103.83 415.30 277.18 32.05 69.30 138.59 103.83 415.30 277.18 32.06 69.30 138.59 103.83 415.30 277.18 32.07 69.30 138.59 103.83 415.30 277.18 32.08 69.30 138.59 103.83 415.30 277.18 32.09 69.30 138.59 103.83 415.30 277.18 32.10 69.30 138.59 103.83 415.30 277.18 32.11 69.30 138.59 103.83 415.30 277.18 32.12 69.30 138.59 103.83 415.30 277.18 32.13 69.30 138.59 103.83 415.30 277.18 32.14 69.30 138.59 103.83 415.30 277.18 32.15 69.30 138.59 103.83 415.30 277.18 32.16 69.30 138.59 103.83 415.30 277.18 32.17 69.30 138.59 103.83 415.30 277.18 32.18 69.30 138.59 103.83 415.30 277.18 32.19 69.30 138.59 103.83 415.30 277.18 32.20 69.30 138.59 103.83 415.30 277.18 32.21 69.30 138.59 103.83 415.30 277.18 32.22 69.30 138.59 103.83 415.30 277.18 32.23 69.30 138.59 103.83 415.30 277.18 32.24 69.30 138.59 103.83 415.30 277.18 32.25 69.30 138.59 103.83 415.30 32.26 69.30 138.59 103.83 415.30 32.27 69.30 138.59 103.83 415.30 32.28 69.30 138.59 103.83 415.30 32.29 69.30 138.59 103.83 415.30 32.30 69.30 138.59 103.83 415.30 32.31 69.30 138.59 103.83 415.30 32.32 69.30 138.59 103.83 415.30 329.63 32.33 69.30 138.59 103.83 415.30 329.63 32.34 69.30 138.59 103.83 415.30 329.63 32.35 69.30 138.59 103.83 415.30 329.63 32.36 69.30 138.59 103.83 415.30 329.63 32.37 69.30 138.59 103.83 415.30 329.63 32.38 69.30 138.59 103.83 415.30 329.63 32.39 69.30 138.59 103.83 415.30 329.63 32.40 69.30 138.59 103.83 415.30 329.63 32.41 69.30 138.59 103.83 415.30 329.63 32.42 69.30 138.59 103.83 415.30 329.63 32.43 69.30 138.59 103.83 415.30 329.63 32.44 69.30 138.59 103.83 415.30 329.63 32.45 69.30 138.59 103.83 415.30 329.63 32.46 69.30 138.59 103.83 415.30 329.63 32.47 69.30 138.59 103.83 415.30 329.63 32.48 69.30 138.59 103.83 415.30 329.63 32.49 69.30 138.59 103.83 329.63 32.50 69.30 138.59 103.83 329.63 32.51 69.30 138.59 103.83 329.63 32.52 69.30 138.59 103.83 329.63 32.53 69.30 138.59 103.83 329.63 32.54 69.30 138.59 103.83 329.63 32.55 69.30 138.59 103.83 329.63 32.56 69.30 138.59 103.83 329.63 32.57 69.30 138.59 103.83 329.63 32.58 69.30 138.59 103.83 329.63 32.59 69.30 138.59 103.83 329.63 32.60 69.30 138.59 103.83 329.63 32.61 69.30 138.59 103.83 329.63 32.62 69.30 138.59 103.83 329.63 32.63 69.30 138.59 32.64 69.30 138.59 32.65 69.30 138.59 32.66 69.30 138.59 32.67 69.30 138.59 32.68 69.30 138.59 32.69 69.30 32.70 69.30 32.71 69.30 32.72 32.73 32.74 32.75 415.30 32.76 415.30 32.77 415.30 32.78 415.30 32.79 415.30 32.80 415.30 32.81 415.30 32.82 415.30 32.83 415.30 32.84 415.30 32.85 415.30 32.86 415.30 32.87 415.30 32.88 415.30 32.89 415.30 32.90 415.30 32.91 415.30 32.92 415.30 32.93 415.30 32.94 415.30 32.95 415.30 32.96 415.30 32.97 415.30 32.98 415.30 32.99 415.30 33.00 415.30 33.01 415.30 33.02 415.30 33.03 415.30 33.04 415.30 33.05 33.06 33.07 33.08 33.09 33.10 65.41 103.83 33.11 65.41 103.83 130.81 33.12 65.41 103.83 130.81 33.13 65.41 103.83 130.81 33.14 65.41 103.83 130.81 415.30 207.65 33.15 65.41 103.83 130.81 415.30 207.65 33.16 65.41 103.83 130.81 415.30 207.65 33.17 65.41 103.83 130.81 415.30 207.65 33.18 65.41 103.83 130.81 415.30 207.65 33.19 65.41 103.83 130.81 415.30 207.65 33.20 65.41 103.83 130.81 415.30 207.65 33.21 65.41 103.83 130.81 415.30 207.65 33.22 65.41 103.83 130.81 415.30 207.65 33.23 65.41 103.83 130.81 415.30 207.65 33.24 65.41 103.83 130.81 415.30 207.65 33.25 65.41 103.83 130.81 415.30 207.65 33.26 65.41 103.83 130.81 415.30 207.65 33.27 65.41 103.83 130.81 415.30 207.65 33.28 65.41 103.83 130.81 415.30 207.65 33.29 65.41 103.83 130.81 415.30 207.65 33.30 65.41 103.83 130.81 415.30 207.65 33.31 65.41 103.83 130.81 415.30 207.65 33.32 65.41 103.83 130.81 415.30 207.65 33.33 65.41 103.83 130.81 415.30 207.65 33.34 65.41 103.83 130.81 415.30 207.65 33.35 65.41 103.83 130.81 415.30 207.65 33.36 65.41 103.83 130.81 415.30 207.65 33.37 65.41 103.83 130.81 415.30 207.65 33.38 65.41 103.83 130.81 415.30 207.65 33.39 65.41 103.83 130.81 415.30 207.65 33.40 65.41 103.83 130.81 415.30 207.65 33.41 65.41 103.83 130.81 415.30 207.65 33.42 65.41 103.83 130.81 415.30 207.65 33.43 65.41 103.83 130.81 415.30 207.65 33.44 65.41 103.83 130.81 415.30 207.65 33.45 65.41 103.83 130.81 415.30 207.65 33.46 65.41 103.83 130.81 415.30 207.65 33.47 65.41 103.83 130.81 415.30 207.65 33.48 65.41 103.83 130.81 415.30 207.65 33.49 65.41 103.83 130.81 415.30 207.65 33.50 65.41 103.83 130.81 415.30 207.65 33.51 65.41 103.83 130.81 415.30 207.65 33.52 65.41 103.83 130.81 415.30 207.65 33.53 65.41 103.83 130.81 415.30 207.65 33.54 65.41 103.83 130.81 415.30 207.65 33.55 65.41 103.83 130.81 415.30 207.65 33.56 65.41 103.83 130.81 415.30 207.65 33.57 65.41 103.83 130.81 415.30 207.65 33.58 65.41 103.83 130.81 415.30 207.65 33.59 65.41 103.83 130.81 415.30 207.65 33.60 65.41 103.83 130.81 415.30 207.65 33.61 65.41 103.83 130.81 415.30 207.65 33.62 65.41 103.83 130.81 415.30 207.65 33.63 65.41 103.83 130.81 415.30 207.65 33.64 65.41 103.83 130.81 415.30 207.65 33.65 65.41 103.83 130.81 415.30 207.65 33.66 65.41 103.83 130.81 415.30 207.65 33.67 65.41 103.83 130.81 415.30 207.65 33.68 65.41 103.83 130.81 415.30 207.65 33.69 65.41 103.83 130.81 415.30 207.65 33.70 65.41 103.83 130.81 415.30 207.65 33.71 65.41 103.83 130.81 415.30 207.65 33.72 65.41 103.83 130.81 415.30 207.65 33.73 65.41 103.83 130.81 415.30 207.65 33.74 65.41 103.83 130.81 415.30 207.65 33.75 65.41 103.83 130.81 415.30 207.65 33.76 65.41 103.83 130.81 415.30 207.65 33.77 65.41 103.83 130.81 415.30 207.65 311.13 33.78 65.41 103.83 130.81 415.30 207.65 311.13 33.79 65.41 103.83 130.81 415.30 207.65 311.13 33.80 65.41 103.83 130.81 415.30 207.65 311.13 33.81 65.41 103.83 130.81 415.30 207.65 311.13 33.82 65.41 103.83 130.81 415.30 207.65 311.13 33.83 65.41 103.83 130.81 415.30 207.65 311.13 33.84 65.41 103.83 130.81 415.30 207.65 311.13 33.85 65.41 103.83 130.81 415.30 207.65 311.13 33.86 65.41 103.83 130.81 415.30 207.65 311.13 33.87 65.41 103.83 130.81 415.30 207.65 311.13 33.88 65.41 103.83 130.81 415.30 311.13 33.89 65.41 103.83 130.81 415.30 311.13 33.90 65.41 103.83 130.81 415.30 311.13 33.91 65.41 103.83 130.81 415.30 311.13 33.92 65.41 103.83 130.81 415.30 311.13 33.93 65.41 103.83 130.81 415.30 311.13 33.94 65.41 103.83 130.81 415.30 311.13 33.95 65.41 103.83 130.81 415.30 311.13 33.96 65.41 103.83 130.81 415.30 311.13 33.97 65.41 103.83 130.81 415.30 311.13 33.98 65.41 103.83 130.81 415.30 311.13 33.99 65.41 103.83 130.81 415.30 311.13 34.00 65.41 103.83 130.81 415.30 311.13 34.01 65.41 103.83 130.81 415.30 311.13 34.02 65.41 103.83 130.81 415.30 311.13 34.03 65.41 103.83 130.81 415.30 311.13 34.04 65.41 103.83 130.81 415.30 311.13 34.05 65.41 103.83 130.81 415.30 311.13 34.06 65.41 103.83 130.81 415.30 311.13 34.07 65.41 103.83 130.81 415.30 311.13 34.08 65.41 103.83 130.81 415.30 311.13 34.09 65.41 103.83 130.81 415.30 311.13 34.10 65.41 103.83 130.81 415.30 311.13 34.11 65.41 103.83 130.81 415.30 311.13 34.12 65.41 103.83 130.81 415.30 311.13 34.13 65.41 103.83 130.81 415.30 311.13 34.14 65.41 103.83 130.81 415.30 311.13 34.15 65.41 103.83 130.81 415.30 311.13 34.16 65.41 103.83 130.81 415.30 311.13 34.17 65.41 103.83 130.81 415.30 311.13 34.18 65.41 103.83 130.81 415.30 311.13 34.19 65.41 103.83 130.81 415.30 311.13 34.20 65.41 103.83 130.81 415.30 311.13 34.21 65.41 103.83 130.81 415.30 311.13 34.22 65.41 103.83 130.81 415.30 311.13 34.23 65.41 103.83 130.81 415.30 311.13 34.24 65.41 103.83 130.81 415.30 311.13 34.25 65.41 103.83 130.81 415.30 311.13 34.26 65.41 103.83 130.81 415.30 311.13 34.27 65.41 103.83 130.81 415.30 311.13 34.28 65.41 103.83 130.81 415.30 311.13 369.99 34.29 65.41 103.83 130.81 415.30 311.13 369.99 34.30 65.41 103.83 130.81 415.30 311.13 369.99 34.31 65.41 103.83 130.81 415.30 369.99 34.32 65.41 103.83 130.81 415.30 369.99 34.33 65.41 103.83 130.81 415.30 369.99 34.34 65.41 103.83 130.81 415.30 369.99 34.35 65.41 103.83 130.81 415.30 369.99 34.36 65.41 103.83 130.81 415.30 369.99 34.37 65.41 103.83 130.81 415.30 369.99 34.38 65.41 103.83 130.81 415.30 369.99 34.39 65.41 103.83 130.81 415.30 369.99 34.40 65.41 103.83 130.81 415.30 369.99 34.41 65.41 103.83 130.81 415.30 369.99 34.42 65.41 103.83 130.81 415.30 369.99 34.43 65.41 103.83 130.81 415.30 369.99 34.44 65.41 103.83 130.81 415.30 369.99 34.45 65.41 103.83 130.81 415.30 369.99 34.46 65.41 103.83 130.81 415.30 369.99 34.47 65.41 103.83 130.81 415.30 369.99 34.48 65.41 103.83 130.81 415.30 369.99 34.49 65.41 103.83 130.81 415.30 369.99 34.50 65.41 103.83 130.81 415.30 369.99 34.51 65.41 103.83 130.81 415.30 369.99 34.52 65.41 103.83 130.81 415.30 369.99 34.53 65.41 103.83 130.81 415.30 369.99 34.54 65.41 103.83 130.81 415.30 369.99 34.55 65.41 103.83 130.81 415.30 369.99 34.56 65.41 103.83 130.81 415.30 369.99 34.57 65.41 103.83 130.81 415.30 369.99 34.58 65.41 103.83 130.81 415.30 369.99 34.59 65.41 103.83 130.81 415.30 369.99 34.60 65.41 103.83 130.81 415.30 369.99 34.61 65.41 103.83 130.81 415.30 369.99 34.62 65.41 103.83 130.81 415.30 369.99 34.63 65.41 103.83 130.81 415.30 369.99 34.64 65.41 103.83 130.81 415.30 369.99 34.65 65.41 103.83 130.81 415.30 369.99 34.66 65.41 103.83 130.81 415.30 369.99 34.67 65.41 103.83 130.81 415.30 369.99 34.68 65.41 103.83 130.81 415.30 369.99 34.69 65.41 103.83 130.81 415.30 369.99 34.70 65.41 103.83 130.81 415.30 369.99 34.71 65.41 103.83 130.81 415.30 369.99 34.72 65.41 103.83 130.81 415.30 369.99 34.73 65.41 103.83 130.81 415.30 369.99 34.74 65.41 103.83 130.81 415.30 369.99 34.75 65.41 103.83 130.81 415.30 369.99 34.76 65.41 103.83 130.81 415.30 369.99 34.77 65.41 103.83 130.81 415.30 369.99 207.65 34.78 65.41 103.83 130.81 415.30 369.99 207.65 34.79 65.41 103.83 130.81 415.30 369.99 207.65 34.80 65.41 103.83 130.81 415.30 369.99 207.65 34.81 65.41 103.83 130.81 415.30 369.99 207.65 34.82 65.41 103.83 130.81 415.30 207.65 34.83 65.41 103.83 130.81 415.30 207.65 34.84 65.41 103.83 130.81 415.30 207.65 34.85 65.41 103.83 130.81 415.30 207.65 34.86 65.41 103.83 130.81 415.30 207.65 34.87 65.41 103.83 130.81 415.30 207.65 34.88 65.41 103.83 130.81 415.30 207.65 34.89 65.41 103.83 130.81 415.30 207.65 34.90 65.41 103.83 130.81 415.30 207.65 34.91 65.41 103.83 130.81 415.30 207.65 34.92 65.41 103.83 130.81 415.30 207.65 34.93 65.41 103.83 130.81 415.30 207.65 34.94 65.41 103.83 130.81 415.30 207.65 34.95 65.41 103.83 130.81 415.30 207.65 34.96 65.41 103.83 130.81 415.30 207.65 34.97 65.41 103.83 130.81 415.30 207.65 34.98 65.41 103.83 130.81 415.30 207.65 34.99 65.41 103.83 130.81 415.30 207.65 35.00 65.41 103.83 130.81 415.30 207.65 35.01 65.41 103.83 130.81 415.30 207.65 35.02 65.41 103.83 130.81 415.30 207.65 35.03 65.41 103.83 130.81 415.30 207.65 35.04 65.41 103.83 130.81 415.30 207.65 35.05 65.41 103.83 130.81 415.30 207.65 35.06 65.41 103.83 130.81 415.30 207.65 35.07 65.41 103.83 130.81 415.30 207.65 35.08 65.41 103.83 130.81 415.30 207.65 35.09 65.41 103.83 130.81 415.30 207.65 35.10 65.41 103.83 130.81 415.30 207.65 35.11 65.41 103.83 130.81 415.30 207.65 35.12 65.41 103.83 130.81 415.30 207.65 35.13 65.41 103.83 130.81 415.30 207.65 35.14 65.41 103.83 130.81 415.30 207.65 35.15 65.41 103.83 130.81 415.30 207.65 35.16 65.41 103.83 130.81 415.30 207.65 35.17 65.41 103.83 130.81 415.30 207.65 35.18 65.41 103.83 130.81 415.30 207.65 35.19 65.41 103.83 130.81 415.30 207.65 35.20 65.41 103.83 130.81 415.30 207.65 35.21 65.41 103.83 130.81 415.30 207.65 35.22 65.41 103.83 130.81 415.30 207.65 35.23 65.41 103.83 130.81 415.30 207.65 35.24 65.41 103.83 130.81 415.30 207.65 35.25 65.41 103.83 130.81 415.30 207.65 35.26 65.41 103.83 130.81 415.30 207.65 35.27 65.41 103.83 130.81 415.30 207.65 35.28 65.41 103.83 130.81 415.30 207.65 35.29 65.41 103.83 130.81 415.30 207.65 35.30 65.41 103.83 130.81 415.30 207.65 311.13 35.31 65.41 103.83 130.81 415.30 207.65 311.13 35.32 65.41 103.83 130.81 415.30 207.65 311.13 35.33 65.41 103.83 130.81 415.30 207.65 311.13 35.34 65.41 103.83 130.81 415.30 207.65 311.13 35.35 65.41 103.83 130.81 415.30 311.13 35.36 65.41 103.83 130.81 415.30 311.13 35.37 65.41 103.83 130.81 415.30 311.13 35.38 65.41 103.83 130.81 415.30 311.13 35.39 65.41 103.83 130.81 415.30 311.13 35.40 65.41 103.83 130.81 415.30 311.13 35.41 65.41 103.83 130.81 415.30 311.13 35.42 65.41 103.83 130.81 415.30 311.13 35.43 65.41 103.83 130.81 415.30 311.13 35.44 65.41 103.83 130.81 415.30 311.13 35.45 65.41 103.83 130.81 415.30 311.13 35.46 65.41 103.83 130.81 415.30 311.13 35.47 65.41 103.83 130.81 415.30 311.13 35.48 65.41 103.83 130.81 415.30 311.13 35.49 65.41 103.83 130.81 415.30 311.13 35.50 65.41 103.83 130.81 415.30 311.13 35.51 65.41 103.83 130.81 415.30 311.13 35.52 65.41 103.83 130.81 415.30 311.13 35.53 65.41 103.83 130.81 415.30 311.13 35.54 65.41 103.83 130.81 415.30 311.13 35.55 65.41 103.83 130.81 415.30 311.13 35.56 65.41 103.83 130.81 415.30 311.13 35.57 65.41 103.83 130.81 415.30 311.13 35.58 65.41 103.83 130.81 415.30 311.13 35.59 65.41 103.83 130.81 415.30 311.13 35.60 65.41 103.83 130.81 415.30 311.13 35.61 65.41 103.83 130.81 415.30 311.13 35.62 65.41 103.83 130.81 415.30 311.13 35.63 65.41 103.83 130.81 415.30 311.13 35.64 65.41 103.83 130.81 415.30 311.13 35.65 65.41 103.83 130.81 415.30 311.13 35.66 65.41 103.83 130.81 415.30 311.13 35.67 65.41 103.83 130.81 415.30 311.13 35.68 65.41 103.83 130.81 415.30 311.13 35.69 65.41 103.83 130.81 415.30 311.13 35.70 65.41 103.83 130.81 415.30 311.13 35.71 65.41 103.83 130.81 415.30 311.13 35.72 65.41 103.83 130.81 415.30 311.13 35.73 65.41 103.83 130.81 415.30 311.13 35.74 65.41 103.83 130.81 415.30 311.13 35.75 65.41 103.83 130.81 415.30 311.13 35.76 65.41 103.83 130.81 415.30 311.13 35.77 65.41 103.83 130.81 415.30 311.13 35.78 65.41 103.83 130.81 415.30 311.13 35.79 65.41 103.83 130.81 415.30 311.13 369.99 35.80 65.41 103.83 130.81 415.30 311.13 369.99 35.81 65.41 103.83 130.81 415.30 311.13 369.99 35.82 65.41 103.83 130.81 415.30 369.99 35.83 65.41 103.83 130.81 415.30 369.99 35.84 65.41 103.83 130.81 415.30 369.99 35.85 65.41 103.83 130.81 415.30 369.99 35.86 65.41 103.83 130.81 415.30 369.99 35.87 65.41 103.83 130.81 415.30 369.99 35.88 65.41 103.83 130.81 415.30 369.99 35.89 65.41 103.83 130.81 415.30 369.99 35.90 65.41 103.83 130.81 415.30 369.99 35.91 65.41 103.83 130.81 415.30 369.99 35.92 65.41 103.83 130.81 415.30 369.99 35.93 65.41 103.83 130.81 415.30 369.99 35.94 65.41 103.83 130.81 415.30 369.99 35.95 65.41 103.83 130.81 415.30 369.99 35.96 65.41 103.83 130.81 415.30 369.99 35.97 65.41 103.83 130.81 415.30 369.99 35.98 65.41 103.83 130.81 415.30 369.99 35.99 65.41 103.83 130.81 415.30 369.99 36.00 65.41 103.83 130.81 415.30 369.99 36.01 65.41 103.83 130.81 415.30 369.99 36.02 65.41 103.83 130.81 415.30 369.99 36.03 65.41 103.83 130.81 415.30 369.99 36.04 65.41 103.83 130.81 415.30 369.99 36.05 65.41 103.83 130.81 415.30 369.99 36.06 65.41 103.83 130.81 415.30 369.99 36.07 65.41 103.83 130.81 415.30 369.99 36.08 65.41 103.83 130.81 415.30 369.99 36.09 65.41 103.83 130.81 415.30 369.99 36.10 65.41 103.83 130.81 415.30 369.99 36.11 65.41 103.83 130.81 415.30 369.99 36.12 65.41 103.83 130.81 415.30 369.99 36.13 65.41 103.83 130.81 415.30 369.99 36.14 65.41 103.83 130.81 415.30 369.99 36.15 65.41 103.83 130.81 415.30 369.99 36.16 65.41 103.83 130.81 415.30 369.99 36.17 65.41 103.83 130.81 415.30 369.99 36.18 65.41 103.83 130.81 415.30 369.99 36.19 65.41 103.83 130.81 415.30 369.99 36.20 65.41 103.83 130.81 415.30 369.99 36.21 65.41 103.83 130.81 415.30 369.99 36.22 65.41 103.83 130.81 415.30 369.99 36.23 65.41 103.83 130.81 415.30 369.99 36.24 65.41 103.83 130.81 415.30 369.99 36.25 65.41 103.83 130.81 415.30 369.99 36.26 65.41 103.83 130.81 415.30 369.99 36.27 65.41 103.83 130.81 415.30 369.99 36.28 65.41 103.83 130.81 415.30 369.99 36.29 65.41 103.83 130.81 415.30 369.99 207.65 36.30 65.41 103.83 130.81 415.30 369.99 207.65 36.31 65.41 103.83 130.81 415.30 369.99 207.65 36.32 65.41 103.83 130.81 415.30 207.65 36.33 65.41 103.83 130.81 415.30 207.65 36.34 65.41 103.83 130.81 415.30 207.65 36.35 65.41 103.83 130.81 415.30 207.65 36.36 65.41 103.83 130.81 415.30 207.65 36.37 65.41 103.83 130.81 415.30 207.65 36.38 65.41 103.83 130.81 415.30 207.65 36.39 65.41 103.83 130.81 415.30 207.65 36.40 65.41 103.83 130.81 415.30 207.65 36.41 65.41 103.83 130.81 415.30 207.65 36.42 65.41 103.83 130.81 415.30 207.65 36.43 65.41 103.83 130.81 415.30 207.65 36.44 65.41 103.83 130.81 415.30 207.65 36.45 65.41 103.83 130.81 415.30 207.65 36.46 65.41 103.83 130.81 415.30 207.65 36.47 65.41 103.83 130.81 415.30 207.65 36.48 65.41 103.83 130.81 415.30 207.65 36.49 65.41 103.83 130.81 415.30 207.65 36.50 65.41 103.83 130.81 415.30 207.65 36.51 65.41 103.83 130.81 415.30 207.65 36.52 65.41 103.83 130.81 415.30 207.65 36.53 65.41 103.83 130.81 415.30 207.65 36.54 65.41 103.83 130.81 415.30 207.65 36.55 65.41 103.83 130.81 415.30 207.65 36.56 65.41 103.83 130.81 415.30 207.65 36.57 65.41 103.83 130.81 415.30 207.65 36.58 65.41 103.83 130.81 415.30 207.65 36.59 65.41 103.83 130.81 415.30 207.65 36.60 65.41 103.83 130.81 415.30 207.65 36.61 65.41 103.83 130.81 415.30 207.65 36.62 65.41 103.83 130.81 415.30 207.65 36.63 65.41 103.83 130.81 415.30 207.65 36.64 65.41 103.83 130.81 415.30 207.65 36.65 65.41 103.83 130.81 415.30 207.65 36.66 65.41 103.83 130.81 415.30 207.65 36.67 65.41 103.83 130.81 415.30 207.65 36.68 65.41 103.83 130.81 415.30 207.65 36.69 65.41 103.83 130.81 415.30 207.65 36.70 65.41 103.83 130.81 415.30 207.65 36.71 65.41 103.83 130.81 415.30 207.65 36.72 65.41 103.83 130.81 415.30 207.65 36.73 65.41 103.83 130.81 415.30 207.65 36.74 65.41 103.83 130.81 415.30 207.65 36.75 65.41 103.83 130.81 415.30 207.65 36.76 65.41 103.83 130.81 415.30 207.65 36.77 65.41 103.83 130.81 415.30 207.65 36.78 65.41 103.83 130.81 415.30 207.65 36.79 65.41 103.83 130.81 415.30 207.65 36.80 65.41 103.83 130.81 415.30 207.65 36.81 65.41 103.83 130.81 415.30 207.65 36.82 65.41 103.83 130.81 415.30 207.65 311.13 36.83 65.41 103.83 130.81 415.30 207.65 311.13 36.84 65.41 103.83 130.81 415.30 207.65 311.13 36.85 65.41 103.83 130.81 415.30 207.65 311.13 36.86 65.41 103.83 130.81 415.30 207.65 311.13 36.87 65.41 103.83 130.81 415.30 311.13 36.88 65.41 103.83 130.81 415.30 311.13 36.89 65.41 103.83 130.81 415.30 311.13 36.90 65.41 103.83 130.81 415.30 311.13 36.91 65.41 103.83 130.81 415.30 311.13 36.92 65.41 103.83 130.81 415.30 311.13 36.93 65.41 103.83 130.81 415.30 311.13 36.94 65.41 103.83 130.81 415.30 311.13 36.95 65.41 103.83 130.81 415.30 311.13 36.96 65.41 103.83 130.81 415.30 311.13 36.97 65.41 103.83 130.81 415.30 311.13 36.98 65.41 103.83 130.81 415.30 311.13 36.99 65.41 103.83 130.81 415.30 311.13 37.00 65.41 103.83 130.81 415.30 311.13 37.01 65.41 103.83 130.81 415.30 311.13 37.02 65.41 103.83 130.81 415.30 311.13 37.03 65.41 103.83 130.81 415.30 311.13 37.04 65.41 103.83 130.81 415.30 311.13 37.05 65.41 103.83 130.81 415.30 311.13 37.06 65.41 103.83 130.81 415.30 311.13 37.07 65.41 103.83 130.81 415.30 311.13 37.08 65.41 103.83 130.81 415.30 311.13 37.09 65.41 103.83 130.81 415.30 311.13 37.10 65.41 103.83 130.81 415.30 311.13 37.11 65.41 103.83 130.81 415.30 311.13 37.12 65.41 103.83 130.81 415.30 311.13 37.13 65.41 103.83 130.81 415.30 311.13 37.14 65.41 103.83 130.81 415.30 311.13 37.15 65.41 103.83 130.81 415.30 311.13 37.16 65.41 103.83 130.81 415.30 311.13 37.17 65.41 103.83 130.81 415.30 311.13 37.18 65.41 103.83 130.81 415.30 311.13 37.19 65.41 103.83 130.81 415.30 311.13 37.20 65.41 103.83 130.81 415.30 311.13 37.21 65.41 103.83 130.81 415.30 311.13 37.22 65.41 103.83 130.81 415.30 311.13 37.23 65.41 103.83 130.81 415.30 311.13 37.24 65.41 103.83 130.81 415.30 311.13 37.25 65.41 103.83 130.81 415.30 311.13 37.26 65.41 103.83 130.81 415.30 311.13 37.27 65.41 103.83 130.81 415.30 311.13 369.99 37.28 65.41 103.83 130.81 415.30 311.13 369.99 37.29 65.41 103.83 130.81 415.30 311.13 369.99 37.30 65.41 103.83 130.81 415.30 369.99 37.31 65.41 103.83 130.81 415.30 369.99 37.32 65.41 103.83 130.81 415.30 369.99 37.33 65.41 103.83 130.81 415.30 369.99 37.34 65.41 103.83 130.81 415.30 369.99 37.35 65.41 103.83 130.81 415.30 369.99 37.36 65.41 103.83 130.81 415.30 369.99 37.37 65.41 103.83 130.81 415.30 369.99 37.38 65.41 103.83 130.81 415.30 369.99 37.39 65.41 103.83 130.81 415.30 369.99 37.40 65.41 103.83 130.81 415.30 369.99 37.41 65.41 103.83 130.81 415.30 369.99 37.42 65.41 103.83 130.81 415.30 369.99 37.43 65.41 103.83 130.81 415.30 369.99 37.44 65.41 103.83 130.81 415.30 369.99 37.45 65.41 103.83 130.81 415.30 369.99 37.46 65.41 103.83 130.81 415.30 369.99 37.47 65.41 103.83 130.81 415.30 369.99 37.48 65.41 103.83 130.81 415.30 369.99 37.49 65.41 103.83 130.81 415.30 369.99 37.50 65.41 103.83 130.81 415.30 369.99 37.51 65.41 103.83 130.81 415.30 369.99 37.52 65.41 103.83 130.81 415.30 369.99 37.53 65.41 103.83 130.81 415.30 369.99 37.54 65.41 103.83 130.81 415.30 369.99 37.55 65.41 103.83 130.81 415.30 369.99 37.56 65.41 103.83 130.81 415.30 369.99 37.57 65.41 103.83 130.81 415.30 369.99 37.58 65.41 103.83 130.81 415.30 369.99 37.59 65.41 103.83 130.81 415.30 369.99 37.60 65.41 103.83 130.81 415.30 369.99 37.61 65.41 103.83 130.81 415.30 369.99 37.62 65.41 103.83 130.81 415.30 369.99 37.63 65.41 103.83 130.81 369.99 37.64 65.41 103.83 130.81 369.99 37.65 65.41 103.83 130.81 369.99 37.66 65.41 103.83 130.81 369.99 37.67 65.41 103.83 130.81 369.99 37.68 65.41 103.83 130.81 369.99 37.69 65.41 103.83 130.81 369.99 37.70 65.41 103.83 130.81 369.99 37.71 65.41 103.83 130.81 369.99 37.72 65.41 103.83 130.81 369.99 37.73 65.41 103.83 130.81 369.99 37.74 65.41 103.83 130.81 369.99 37.75 65.41 103.83 130.81 369.99 37.76 65.41 103.83 130.81 369.99 207.65 37.77 65.41 103.83 130.81 369.99 207.65 415.30 37.78 65.41 103.83 130.81 369.99 207.65 415.30 37.79 65.41 103.83 130.81 369.99 207.65 415.30 37.80 65.41 103.83 130.81 207.65 415.30 37.81 65.41 103.83 130.81 207.65 415.30 37.82 65.41 103.83 130.81 207.65 415.30 37.83 65.41 103.83 130.81 207.65 415.30 37.84 65.41 103.83 130.81 207.65 415.30 37.85 65.41 103.83 130.81 207.65 415.30 37.86 65.41 103.83 130.81 207.65 415.30 37.87 65.41 103.83 130.81 207.65 415.30 37.88 65.41 103.83 130.81 207.65 415.30 37.89 65.41 103.83 130.81 207.65 415.30 37.90 65.41 103.83 130.81 207.65 415.30 37.91 65.41 103.83 130.81 207.65 415.30 37.92 65.41 103.83 130.81 207.65 415.30 37.93 65.41 103.83 130.81 207.65 415.30 37.94 65.41 103.83 130.81 207.65 415.30 37.95 65.41 103.83 130.81 207.65 415.30 37.96 65.41 103.83 130.81 207.65 415.30 37.97 65.41 103.83 130.81 207.65 415.30 37.98 65.41 103.83 130.81 207.65 415.30 37.99 65.41 103.83 130.81 207.65 415.30 38.00 65.41 103.83 130.81 207.65 415.30 38.01 65.41 103.83 130.81 207.65 415.30 38.02 65.41 103.83 130.81 207.65 415.30 38.03 65.41 103.83 130.81 207.65 415.30 38.04 65.41 103.83 130.81 207.65 415.30 38.05 65.41 103.83 130.81 207.65 415.30 38.06 65.41 103.83 130.81 207.65 415.30 38.07 65.41 103.83 130.81 207.65 415.30 38.08 65.41 103.83 130.81 207.65 415.30 38.09 65.41 103.83 130.81 207.65 415.30 38.10 65.41 103.83 130.81 207.65 415.30 38.11 65.41 103.83 130.81 207.65 415.30 38.12 65.41 103.83 130.81 207.65 415.30 38.13 65.41 103.83 130.81 207.65 415.30 38.14 65.41 103.83 130.81 207.65 415.30 38.15 65.41 103.83 130.81 207.65 415.30 38.16 65.41 103.83 130.81 207.65 415.30 38.17 65.41 103.83 130.81 207.65 415.30 38.18 65.41 103.83 130.81 207.65 415.30 38.19 65.41 103.83 130.81 207.65 415.30 38.20 65.41 103.83 130.81 207.65 415.30 38.21 65.41 103.83 130.81 207.65 415.30 38.22 65.41 103.83 130.81 207.65 415.30 38.23 65.41 103.83 130.81 207.65 415.30 311.13 38.24 65.41 103.83 130.81 207.65 415.30 311.13 38.25 65.41 103.83 130.81 207.65 415.30 311.13 38.26 65.41 103.83 130.81 207.65 415.30 311.13 38.27 65.41 103.83 130.81 207.65 415.30 311.13 38.28 65.41 103.83 130.81 207.65 415.30 311.13 38.29 65.41 103.83 130.81 207.65 415.30 311.13 38.30 65.41 103.83 130.81 207.65 415.30 311.13 38.31 65.41 103.83 130.81 207.65 415.30 311.13 38.32 65.41 103.83 130.81 207.65 415.30 311.13 38.33 65.41 103.83 130.81 207.65 415.30 311.13 38.34 65.41 103.83 130.81 207.65 415.30 311.13 38.35 65.41 103.83 130.81 207.65 415.30 311.13 38.36 65.41 103.83 130.81 207.65 415.30 311.13 38.37 65.41 103.83 130.81 207.65 415.30 311.13 38.38 65.41 103.83 130.81 207.65 415.30 311.13 38.39 65.41 103.83 130.81 207.65 415.30 311.13 38.40 65.41 103.83 130.81 207.65 415.30 311.13 38.41 65.41 103.83 130.81 207.65 415.30 311.13 38.42 65.41 103.83 130.81 207.65 415.30 311.13 38.43 65.41 103.83 130.81 207.65 415.30 311.13 38.44 65.41 103.83 130.81 207.65 415.30 311.13 38.45 65.41 103.83 130.81 207.65 415.30 311.13 38.46 65.41 103.83 130.81 207.65 415.30 311.13 38.47 65.41 103.83 130.81 207.65 415.30 311.13 38.48 65.41 103.83 130.81 207.65 415.30 311.13 38.49 65.41 103.83 130.81 207.65 415.30 311.13 38.50 65.41 103.83 130.81 207.65 415.30 311.13 38.51 65.41 103.83 130.81 207.65 415.30 311.13 38.52 65.41 103.83 130.81 207.65 415.30 311.13 38.53 65.41 103.83 130.81 207.65 415.30 311.13 38.54 65.41 103.83 130.81 207.65 415.30 311.13 38.55 65.41 103.83 130.81 207.65 415.30 311.13 38.56 65.41 103.83 130.81 207.65 415.30 311.13 38.57 65.41 103.83 130.81 207.65 415.30 311.13 38.58 65.41 103.83 130.81 207.65 415.30 311.13 38.59 65.41 103.83 130.81 207.65 415.30 311.13 38.60 65.41 103.83 130.81 207.65 415.30 311.13 38.61 65.41 103.83 130.81 207.65 415.30 311.13 38.62 65.41 103.83 130.81 207.65 415.30 311.13 38.63 65.41 103.83 130.81 207.65 415.30 311.13 38.64 65.41 103.83 130.81 207.65 415.30 311.13 38.65 65.41 103.83 130.81 207.65 415.30 311.13 38.66 65.41 103.83 130.81 207.65 415.30 311.13 38.67 65.41 103.83 130.81 207.65 415.30 311.13 38.68 65.41 103.83 130.81 207.65 415.30 311.13 38.69 65.41 103.83 130.81 207.65 415.30 311.13 38.70 65.41 103.83 130.81 207.65 415.30 311.13 38.71 65.41 103.83 130.81 207.65 415.30 311.13 369.99 38.72 65.41 103.83 130.81 207.65 415.30 311.13 369.99 38.73 65.41 103.83 130.81 207.65 311.13 369.99 38.74 65.41 103.83 130.81 207.65 311.13 369.99 38.75 65.41 103.83 130.81 207.65 311.13 369.99 38.76 65.41 103.83 130.81 207.65 369.99 38.77 65.41 103.83 130.81 207.65 369.99 38.78 65.41 103.83 130.81 207.65 369.99 38.79 65.41 103.83 130.81 207.65 369.99 38.80 65.41 103.83 130.81 207.65 369.99 38.81 65.41 103.83 130.81 207.65 369.99 38.82 65.41 103.83 130.81 207.65 369.99 38.83 103.83 207.65 369.99 38.84 103.83 207.65 369.99 38.85 103.83 207.65 369.99 38.86 103.83 207.65 369.99 38.87 207.65 369.99 38.88 207.65 369.99 38.89 207.65 369.99 38.90 207.65 369.99 38.91 207.65 369.99 38.92 207.65 369.99 38.93 369.99 38.94 369.99 38.95 369.99 38.96 369.99 38.97 369.99 38.98 369.99 38.99 369.99 39.00 369.99 415.30 39.01 369.99 415.30 39.02 369.99 415.30 39.03 415.30 39.04 415.30 39.05 415.30 39.06 415.30 39.07 415.30 39.08 415.30 39.09 415.30 39.10 415.30 39.11 415.30 39.12 415.30 39.13 415.30 39.14 415.30 39.15 415.30 39.16 415.30 39.17 415.30 39.18 415.30 39.19 415.30 39.20 415.30 39.21 415.30 39.22 415.30 39.23 415.30 39.24 39.25 39.26 39.27 39.28 39.29 39.30 39.31 39.32 415.30 39.33 415.30 207.65 39.34 415.30 207.65 39.35 415.30 207.65 39.36 415.30 207.65 39.37 415.30 207.65 138.59 69.30 39.38 415.30 207.65 138.59 69.30 39.39 415.30 207.65 138.59 69.30 39.40 415.30 207.65 138.59 69.30 39.41 415.30 207.65 138.59 69.30 39.42 415.30 207.65 138.59 69.30 39.43 415.30 207.65 138.59 69.30 39.44 415.30 207.65 138.59 69.30 39.45 415.30 207.65 138.59 69.30 39.46 415.30 207.65 138.59 69.30 39.47 415.30 207.65 138.59 69.30 39.48 415.30 207.65 138.59 69.30 39.49 415.30 207.65 138.59 69.30 39.50 415.30 207.65 138.59 69.30 39.51 415.30 207.65 138.59 69.30 39.52 415.30 207.65 138.59 69.30 39.53 415.30 207.65 138.59 69.30 39.54 415.30 207.65 138.59 69.30 39.55 415.30 207.65 138.59 69.30 39.56 415.30 207.65 138.59 69.30 39.57 415.30 207.65 138.59 69.30 39.58 415.30 207.65 138.59 69.30 39.59 415.30 207.65 138.59 69.30 39.60 415.30 207.65 138.59 69.30 39.61 415.30 207.65 138.59 69.30 39.62 415.30 207.65 138.59 69.30 39.63 415.30 207.65 138.59 69.30 39.64 415.30 207.65 138.59 69.30 39.65 415.30 207.65 138.59 69.30 39.66 415.30 207.65 138.59 69.30 39.67 415.30 207.65 138.59 69.30 39.68 415.30 207.65 138.59 69.30 39.69 415.30 207.65 138.59 69.30 39.70 415.30 207.65 138.59 69.30 39.71 415.30 207.65 138.59 69.30 39.72 415.30 207.65 138.59 69.30 39.73 415.30 207.65 138.59 69.30 39.74 415.30 207.65 138.59 69.30 39.75 415.30 207.65 138.59 69.30 39.76 415.30 207.65 138.59 69.30 39.77 415.30 207.65 138.59 69.30 39.78 415.30 207.65 138.59 69.30 39.79 415.30 207.65 138.59 69.30 39.80 415.30 207.65 138.59 69.30 39.81 415.30 207.65 138.59 69.30 39.82 415.30 207.65 138.59 69.30 39.83 415.30 207.65 138.59 69.30 39.84 415.30 207.65 138.59 69.30 39.85 415.30 207.65 138.59 69.30 39.86 415.30 207.65 138.59 69.30 39.87 415.30 207.65 138.59 69.30 39.88 415.30 207.65 138.59 69.30 39.89 415.30 207.65 138.59 69.30 39.90 415.30 207.65 138.59 69.30 39.91 415.30 207.65 138.59 69.30 39.92 415.30 207.65 138.59 69.30 39.93 415.30 207.65 138.59 69.30 39.94 415.30 207.65 138.59 69.30 39.95 415.30 207.65 138.59 69.30 39.96 415.30 207.65 138.59 69.30 39.97 415.30 207.65 138.59 69.30 39.98 415.30 207.65 138.59 69.30 39.99 415.30 207.65 138.59 69.30 40.00 415.30 207.65 138.59 69.30 40.01 415.30 207.65 138.59 69.30 40.02 415.30 207.65 138.59 69.30 40.03 415.30 207.65 138.59 69.30 40.04 415.30 207.65 138.59 69.30 40.05 415.30 207.65 138.59 69.30 277.18 40.06 415.30 207.65 138.59 69.30 277.18 40.07 415.30 207.65 138.59 69.30 277.18 40.08 415.30 207.65 138.59 69.30 277.18 40.09 415.30 207.65 138.59 69.30 277.18 40.10 415.30 207.65 138.59 69.30 277.18 40.11 415.30 207.65 138.59 69.30 277.18 40.12 415.30 207.65 138.59 69.30 277.18 40.13 415.30 207.65 138.59 69.30 277.18 40.14 415.30 207.65 138.59 69.30 277.18 40.15 415.30 207.65 138.59 69.30 277.18 40.16 415.30 207.65 138.59 69.30 277.18 40.17 415.30 207.65 138.59 69.30 277.18 40.18 415.30 207.65 138.59 69.30 277.18 40.19 415.30 207.65 138.59 69.30 277.18 40.20 415.30 207.65 138.59 69.30 277.18 40.21 415.30 207.65 138.59 69.30 277.18 40.22 415.30 207.65 138.59 69.30 277.18 40.23 415.30 207.65 138.59 69.30 277.18 40.24 415.30 207.65 138.59 69.30 277.18 40.25 415.30 207.65 138.59 69.30 277.18 40.26 415.30 207.65 138.59 69.30 277.18 40.27 415.30 207.65 138.59 69.30 277.18 40.28 415.30 207.65 138.59 69.30 277.18 40.29 415.30 207.65 138.59 69.30 277.18 40.30 415.30 207.65 138.59 69.30 277.18 40.31 415.30 207.65 138.59 69.30 277.18 40.32 415.30 207.65 138.59 69.30 277.18 40.33 415.30 207.65 138.59 69.30 277.18 40.34 415.30 207.65 138.59 69.30 277.18 40.35 415.30 207.65 138.59 69.30 277.18 40.36 415.30 207.65 138.59 69.30 277.18 40.37 415.30 207.65 138.59 69.30 277.18 40.38 415.30 207.65 138.59 69.30 277.18 40.39 415.30 207.65 138.59 69.30 277.18 40.40 415.30 207.65 138.59 69.30 277.18 40.41 415.30 207.65 138.59 69.30 277.18 40.42 415.30 207.65 138.59 69.30 277.18 40.43 415.30 207.65 138.59 69.30 277.18 40.44 415.30 207.65 138.59 69.30 277.18 40.45 415.30 207.65 138.59 69.30 277.18 40.46 415.30 207.65 138.59 69.30 277.18 40.47 415.30 207.65 138.59 69.30 277.18 40.48 415.30 207.65 138.59 69.30 277.18 40.49 415.30 207.65 138.59 69.30 277.18 40.50 415.30 207.65 138.59 69.30 277.18 40.51 415.30 207.65 138.59 69.30 277.18 40.52 415.30 207.65 138.59 69.30 277.18 40.53 415.30 207.65 138.59 69.30 277.18 40.54 415.30 207.65 138.59 69.30 277.18 40.55 415.30 207.65 138.59 69.30 277.18 40.56 415.30 207.65 138.59 69.30 277.18 40.57 415.30 207.65 138.59 69.30 277.18 40.58 415.30 207.65 138.59 69.30 277.18 40.59 415.30 207.65 138.59 69.30 277.18 329.63 40.60 415.30 207.65 138.59 69.30 277.18 329.63 40.61 415.30 207.65 138.59 69.30 277.18 329.63 40.62 415.30 207.65 138.59 69.30 277.18 329.63 40.63 415.30 207.65 138.59 69.30 329.63 40.64 415.30 207.65 138.59 69.30 329.63 40.65 415.30 207.65 138.59 69.30 329.63 40.66 415.30 207.65 138.59 69.30 329.63 40.67 415.30 207.65 138.59 69.30 329.63 40.68 415.30 207.65 138.59 69.30 329.63 40.69 415.30 207.65 138.59 69.30 329.63 40.70 415.30 207.65 138.59 69.30 329.63 40.71 415.30 138.59 69.30 329.63 40.72 415.30 138.59 69.30 329.63 40.73 415.30 138.59 69.30 329.63 40.74 415.30 138.59 69.30 329.63 40.75 415.30 138.59 69.30 329.63 40.76 415.30 138.59 69.30 329.63 40.77 415.30 138.59 69.30 329.63 40.78 415.30 138.59 69.30 329.63 40.79 415.30 138.59 69.30 329.63 40.80 415.30 138.59 69.30 329.63 40.81 415.30 138.59 69.30 329.63 40.82 415.30 138.59 69.30 329.63 40.83 415.30 138.59 69.30 329.63 40.84 415.30 138.59 69.30 329.63 40.85 415.30 138.59 69.30 329.63 40.86 415.30 138.59 69.30 329.63 40.87 415.30 138.59 69.30 329.63 40.88 415.30 138.59 69.30 329.63 40.89 415.30 138.59 69.30 329.63 40.90 415.30 138.59 69.30 329.63 40.91 415.30 138.59 69.30 329.63 40.92 415.30 138.59 69.30 329.63 40.93 415.30 138.59 69.30 329.63 40.94 415.30 138.59 69.30 329.63 40.95 415.30 138.59 69.30 329.63 40.96 415.30 138.59 69.30 329.63 40.97 415.30 138.59 69.30 329.63 40.98 415.30 138.59 69.30 329.63 40.99 415.30 138.59 69.30 329.63 41.00 415.30 138.59 69.30 329.63 41.01 415.30 138.59 69.30 329.63 41.02 415.30 138.59 69.30 329.63 41.03 415.30 138.59 69.30 329.63 41.04 415.30 138.59 69.30 329.63 41.05 415.30 138.59 69.30 329.63 41.06 415.30 138.59 69.30 329.63 41.07 415.30 138.59 69.30 329.63 41.08 415.30 138.59 69.30 329.63 207.65 41.09 415.30 138.59 69.30 329.63 207.65 41.10 415.30 138.59 69.30 329.63 207.65 41.11 415.30 138.59 69.30 207.65 41.12 415.30 138.59 69.30 207.65 41.13 415.30 138.59 69.30 207.65 41.14 415.30 138.59 69.30 207.65 41.15 415.30 138.59 69.30 207.65 41.16 415.30 138.59 69.30 207.65 41.17 415.30 138.59 69.30 207.65 41.18 415.30 138.59 69.30 207.65 41.19 415.30 138.59 69.30 207.65 41.20 415.30 138.59 69.30 207.65 41.21 415.30 138.59 69.30 207.65 41.22 415.30 138.59 69.30 207.65 41.23 415.30 138.59 69.30 207.65 41.24 415.30 138.59 69.30 207.65 41.25 415.30 138.59 69.30 207.65 41.26 415.30 138.59 69.30 207.65 41.27 415.30 138.59 69.30 207.65 41.28 415.30 138.59 69.30 207.65 41.29 415.30 138.59 69.30 207.65 41.30 415.30 138.59 69.30 207.65 41.31 415.30 138.59 69.30 207.65 41.32 415.30 138.59 69.30 207.65 41.33 415.30 138.59 69.30 207.65 41.34 415.30 138.59 69.30 207.65 41.35 415.30 138.59 69.30 207.65 41.36 415.30 138.59 69.30 207.65 41.37 415.30 138.59 69.30 207.65 41.38 415.30 138.59 69.30 207.65 41.39 415.30 138.59 69.30 207.65 41.40 415.30 138.59 69.30 207.65 41.41 415.30 138.59 69.30 207.65 41.42 415.30 138.59 69.30 207.65 41.43 415.30 138.59 69.30 207.65 41.44 415.30 138.59 69.30 207.65 41.45 415.30 138.59 69.30 207.65 41.46 415.30 138.59 69.30 207.65 41.47 415.30 138.59 69.30 207.65 41.48 415.30 138.59 69.30 207.65 41.49 415.30 138.59 69.30 207.65 41.50 415.30 138.59 69.30 207.65 41.51 415.30 138.59 69.30 207.65 41.52 415.30 138.59 69.30 207.65 41.53 415.30 138.59 69.30 207.65 41.54 415.30 138.59 69.30 207.65 41.55 415.30 138.59 69.30 207.65 277.18 41.56 415.30 138.59 69.30 207.65 277.18 41.57 415.30 138.59 69.30 207.65 277.18 41.58 415.30 69.30 207.65 277.18 41.59 415.30 69.30 207.65 277.18 41.60 415.30 207.65 277.18 41.61 415.30 207.65 277.18 41.62 415.30 207.65 277.18 41.63 415.30 207.65 277.18 41.64 415.30 207.65 277.18 41.65 415.30 207.65 277.18 41.66 415.30 207.65 277.18 41.67 415.30 207.65 277.18 41.68 415.30 207.65 277.18 41.69 415.30 207.65 277.18 41.70 415.30 207.65 277.18 41.71 415.30 207.65 277.18 41.72 415.30 207.65 277.18 41.73 415.30 207.65 277.18 41.74 415.30 207.65 277.18 41.75 415.30 207.65 277.18 41.76 415.30 207.65 277.18 41.77 415.30 207.65 277.18 41.78 415.30 207.65 277.18 41.79 415.30 207.65 277.18 41.80 415.30 207.65 277.18 41.81 415.30 207.65 277.18 41.82 415.30 207.65 277.18 41.83 415.30 207.65 277.18 41.84 415.30 207.65 277.18 41.85 415.30 207.65 277.18 41.86 415.30 207.65 277.18 41.87 415.30 207.65 277.18 41.88 415.30 207.65 277.18 41.89 415.30 207.65 277.18 41.90 415.30 207.65 277.18 41.91 415.30 207.65 277.18 41.92 415.30 207.65 277.18 41.93 415.30 207.65 277.18 41.94 415.30 207.65 277.18 41.95 415.30 207.65 277.18 41.96 415.30 207.65 277.18 41.97 415.30 207.65 277.18 41.98 415.30 207.65 277.18 41.99 415.30 207.65 277.18 42.00 415.30 207.65 277.18 329.63 42.01 415.30 207.65 277.18 329.63 42.02 415.30 207.65 277.18 329.63 42.03 415.30 207.65 277.18 329.63 42.04 207.65 277.18 329.63 42.05 329.63 42.06 329.63 42.07 329.63 42.08 329.63 42.09 329.63 42.10 329.63 42.11 329.63 42.12 329.63 42.13 329.63 42.14 329.63 42.15 329.63 42.16 329.63 42.17 329.63 42.18 329.63 42.19 329.63 42.20 329.63 42.21 329.63 42.22 329.63 42.23 329.63 42.24 329.63 42.25 329.63 42.26 329.63 42.27 329.63 42.28 329.63 42.29 329.63 42.30 329.63 42.31 329.63 42.32 329.63 42.33 329.63 42.34 329.63 42.35 329.63 42.36 329.63 42.37 329.63 42.38 329.63 42.39 329.63 42.40 329.63 42.41 329.63 42.42 329.63 42.43 329.63 42.44 329.63 42.45 329.63 42.46 329.63 42.47 329.63 42.48 329.63 42.49 329.63 42.50 329.63 46.25 92.50 42.51 329.63 46.25 92.50 42.52 329.63 46.25 92.50 42.53 329.63 46.25 92.50 42.54 329.63 46.25 92.50 42.55 329.63 46.25 92.50 220.00 440.00 42.56 329.63 46.25 92.50 220.00 440.00 42.57 329.63 46.25 92.50 220.00 440.00 42.58 46.25 92.50 220.00 440.00 42.59 46.25 92.50 220.00 440.00 42.60 46.25 92.50 220.00 440.00 42.61 46.25 92.50 220.00 440.00 42.62 46.25 92.50 220.00 440.00 42.63 46.25 92.50 220.00 440.00 42.64 46.25 92.50 220.00 440.00 42.65 46.25 92.50 220.00 440.00 42.66 46.25 92.50 220.00 440.00 42.67 46.25 92.50 220.00 440.00 42.68 46.25 92.50 220.00 440.00 42.69 46.25 92.50 220.00 440.00 42.70 46.25 92.50 220.00 440.00 42.71 46.25 92.50 220.00 440.00 42.72 46.25 92.50 220.00 440.00 42.73 46.25 92.50 220.00 440.00 42.74 46.25 92.50 220.00 440.00 42.75 46.25 92.50 220.00 440.00 42.76 46.25 92.50 220.00 440.00 42.77 46.25 92.50 220.00 440.00 42.78 46.25 92.50 220.00 440.00 42.79 46.25 92.50 220.00 440.00 42.80 46.25 92.50 220.00 440.00 42.81 46.25 92.50 220.00 440.00 42.82 46.25 92.50 220.00 440.00 42.83 46.25 92.50 220.00 440.00 42.84 46.25 92.50 220.00 440.00 42.85 46.25 92.50 220.00 440.00 42.86 46.25 92.50 220.00 440.00 42.87 46.25 92.50 220.00 440.00 42.88 46.25 92.50 220.00 440.00 42.89 46.25 92.50 220.00 440.00 42.90 46.25 92.50 220.00 440.00 42.91 46.25 92.50 220.00 440.00 42.92 46.25 92.50 220.00 440.00 42.93 46.25 92.50 220.00 440.00 42.94 46.25 92.50 220.00 440.00 42.95 46.25 92.50 220.00 440.00 42.96 46.25 92.50 220.00 440.00 42.97 46.25 92.50 220.00 440.00 42.98 46.25 92.50 220.00 440.00 42.99 46.25 92.50 220.00 440.00 43.00 46.25 92.50 220.00 440.00 43.01 46.25 92.50 220.00 440.00 43.02 46.25 92.50 220.00 440.00 43.03 46.25 92.50 220.00 440.00 43.04 46.25 92.50 220.00 440.00 43.05 46.25 92.50 220.00 440.00 43.06 46.25 92.50 220.00 440.00 43.07 46.25 92.50 220.00 440.00 43.08 46.25 92.50 220.00 440.00 43.09 46.25 92.50 220.00 440.00 43.10 46.25 92.50 220.00 440.00 43.11 46.25 92.50 220.00 440.00 43.12 46.25 92.50 220.00 440.00 43.13 46.25 92.50 220.00 440.00 43.14 46.25 92.50 220.00 440.00 277.18 43.15 46.25 92.50 220.00 440.00 277.18 43.16 46.25 92.50 220.00 440.00 277.18 43.17 46.25 92.50 220.00 440.00 277.18 43.18 46.25 92.50 220.00 440.00 277.18 43.19 46.25 92.50 220.00 440.00 277.18 43.20 46.25 92.50 220.00 440.00 277.18 43.21 46.25 92.50 220.00 440.00 277.18 43.22 46.25 92.50 220.00 440.00 277.18 43.23 46.25 92.50 220.00 440.00 277.18 43.24 46.25 92.50 220.00 440.00 277.18 43.25 46.25 92.50 220.00 440.00 277.18 43.26 46.25 92.50 220.00 440.00 277.18 43.27 46.25 92.50 220.00 440.00 277.18 43.28 46.25 92.50 220.00 440.00 277.18 43.29 46.25 92.50 220.00 440.00 277.18 43.30 46.25 92.50 220.00 440.00 277.18 43.31 46.25 92.50 220.00 440.00 277.18 43.32 46.25 92.50 220.00 440.00 277.18 43.33 46.25 92.50 220.00 440.00 277.18 43.34 46.25 92.50 220.00 440.00 277.18 43.35 46.25 92.50 220.00 440.00 277.18 43.36 46.25 92.50 220.00 440.00 277.18 43.37 46.25 92.50 220.00 440.00 277.18 43.38 46.25 92.50 220.00 440.00 277.18 43.39 46.25 92.50 220.00 440.00 277.18 43.40 46.25 92.50 220.00 440.00 277.18 43.41 46.25 92.50 220.00 440.00 277.18 43.42 46.25 92.50 220.00 440.00 277.18 43.43 46.25 92.50 220.00 440.00 277.18 43.44 46.25 92.50 220.00 440.00 277.18 43.45 46.25 92.50 220.00 440.00 277.18 43.46 46.25 92.50 220.00 440.00 277.18 43.47 46.25 92.50 220.00 440.00 277.18 43.48 46.25 92.50 220.00 440.00 277.18 43.49 46.25 92.50 220.00 440.00 277.18 43.50 46.25 92.50 220.00 440.00 277.18 43.51 46.25 92.50 220.00 440.00 277.18 43.52 46.25 92.50 220.00 440.00 277.18 43.53 46.25 92.50 220.00 440.00 277.18 43.54 46.25 92.50 220.00 440.00 277.18 43.55 46.25 92.50 220.00 440.00 277.18 43.56 46.25 92.50 220.00 440.00 277.18 43.57 46.25 92.50 220.00 440.00 277.18 43.58 46.25 92.50 220.00 440.00 277.18 43.59 46.25 92.50 220.00 440.00 277.18 43.60 46.25 92.50 220.00 440.00 277.18 43.61 46.25 92.50 220.00 440.00 277.18 43.62 46.25 92.50 220.00 440.00 277.18 369.99 43.63 46.25 92.50 220.00 440.00 277.18 369.99 43.64 46.25 92.50 220.00 440.00 277.18 369.99 43.65 46.25 92.50 220.00 440.00 277.18 369.99 43.66 46.25 92.50 220.00 440.00 369.99 43.67 46.25 92.50 220.00 440.00 369.99 43.68 46.25 92.50 220.00 440.00 369.99 43.69 46.25 92.50 220.00 440.00 369.99 43.70 46.25 92.50 220.00 440.00 369.99 43.71 46.25 92.50 220.00 440.00 369.99 43.72 46.25 92.50 220.00 440.00 369.99 43.73 46.25 92.50 220.00 440.00 369.99 43.74 46.25 92.50 220.00 440.00 369.99 43.75 46.25 92.50 220.00 440.00 369.99 43.76 46.25 92.50 440.00 369.99 43.77 46.25 92.50 440.00 369.99 43.78 46.25 92.50 440.00 369.99 43.79 46.25 92.50 440.00 369.99 43.80 46.25 92.50 440.00 369.99 43.81 46.25 92.50 440.00 369.99 43.82 46.25 92.50 440.00 369.99 43.83 46.25 92.50 440.00 369.99 43.84 46.25 92.50 440.00 369.99 43.85 46.25 92.50 440.00 369.99 43.86 46.25 92.50 440.00 369.99 43.87 46.25 92.50 440.00 369.99 43.88 46.25 92.50 440.00 369.99 43.89 46.25 92.50 440.00 369.99 43.90 46.25 92.50 440.00 369.99 43.91 46.25 92.50 440.00 369.99 43.92 46.25 92.50 440.00 369.99 43.93 46.25 92.50 440.00 369.99 43.94 46.25 92.50 440.00 369.99 43.95 46.25 92.50 440.00 369.99 43.96 46.25 92.50 440.00 369.99 43.97 46.25 92.50 440.00 369.99 43.98 46.25 92.50 440.00 369.99 43.99 46.25 92.50 440.00 369.99 44.00 46.25 92.50 440.00 369.99 44.01 46.25 92.50 440.00 369.99 44.02 46.25 92.50 440.00 369.99 44.03 46.25 92.50 440.00 369.99 44.04 46.25 92.50 440.00 369.99 44.05 46.25 92.50 440.00 369.99 44.06 46.25 92.50 440.00 369.99 44.07 46.25 92.50 440.00 369.99 44.08 46.25 92.50 440.00 369.99 44.09 46.25 92.50 440.00 369.99 44.10 46.25 92.50 440.00 369.99 44.11 46.25 92.50 440.00 369.99 44.12 46.25 92.50 440.00 369.99 44.13 46.25 92.50 440.00 369.99 44.14 46.25 92.50 440.00 369.99 44.15 46.25 92.50 440.00 369.99 220.00 44.16 46.25 92.50 440.00 369.99 220.00 44.17 46.25 92.50 440.00 369.99 220.00 44.18 46.25 92.50 440.00 369.99 220.00 44.19 46.25 92.50 440.00 369.99 220.00 44.20 46.25 92.50 440.00 220.00 44.21 46.25 92.50 440.00 220.00 44.22 46.25 92.50 440.00 220.00 44.23 46.25 92.50 440.00 220.00 44.24 46.25 92.50 440.00 220.00 44.25 46.25 92.50 440.00 220.00 44.26 46.25 92.50 440.00 220.00 44.27 46.25 92.50 440.00 220.00 44.28 46.25 92.50 440.00 220.00 44.29 46.25 92.50 440.00 220.00 44.30 46.25 92.50 440.00 220.00 44.31 46.25 92.50 440.00 220.00 44.32 46.25 92.50 440.00 220.00 44.33 46.25 92.50 440.00 220.00 44.34 46.25 92.50 440.00 220.00 44.35 46.25 92.50 440.00 220.00 44.36 46.25 92.50 440.00 220.00 44.37 46.25 92.50 440.00 220.00 44.38 46.25 92.50 440.00 220.00 44.39 46.25 92.50 440.00 220.00 44.40 46.25 92.50 440.00 220.00 44.41 46.25 92.50 440.00 220.00 44.42 46.25 92.50 440.00 220.00 44.43 46.25 92.50 440.00 220.00 44.44 46.25 92.50 440.00 220.00 44.45 46.25 92.50 440.00 220.00 44.46 46.25 92.50 440.00 220.00 44.47 46.25 92.50 440.00 220.00 44.48 46.25 92.50 440.00 220.00 44.49 46.25 92.50 440.00 220.00 44.50 46.25 92.50 440.00 220.00 44.51 46.25 92.50 440.00 220.00 44.52 46.25 92.50 440.00 220.00 44.53 46.25 92.50 440.00 220.00 44.54 46.25 92.50 440.00 220.00 44.55 46.25 92.50 440.00 220.00 44.56 46.25 92.50 440.00 220.00 44.57 46.25 92.50 440.00 220.00 44.58 46.25 92.50 440.00 220.00 44.59 46.25 92.50 440.00 220.00 44.60 46.25 92.50 440.00 220.00 277.18 44.61 46.25 92.50 440.00 220.00 277.18 44.62 46.25 92.50 440.00 220.00 277.18 44.63 46.25 92.50 440.00 220.00 277.18 44.64 46.25 92.50 440.00 220.00 277.18 44.65 46.25 92.50 440.00 220.00 277.18 44.66 46.25 92.50 440.00 220.00 277.18 44.67 46.25 92.50 440.00 220.00 277.18 44.68 46.25 92.50 440.00 277.18 44.69 46.25 92.50 440.00 277.18 44.70 46.25 92.50 440.00 277.18 44.71 46.25 440.00 277.18 44.72 46.25 440.00 277.18 44.73 46.25 440.00 277.18 44.74 46.25 440.00 277.18 44.75 440.00 277.18 44.76 440.00 277.18 44.77 440.00 277.18 44.78 440.00 277.18 44.79 440.00 277.18 44.80 440.00 277.18 44.81 440.00 277.18 44.82 440.00 277.18 44.83 440.00 277.18 44.84 440.00 277.18 44.85 440.00 277.18 44.86 440.00 277.18 44.87 440.00 277.18 44.88 440.00 277.18 44.89 440.00 277.18 44.90 440.00 277.18 44.91 440.00 277.18 44.92 440.00 277.18 44.93 440.00 277.18 44.94 440.00 277.18 44.95 440.00 277.18 44.96 440.00 277.18 44.97 440.00 277.18 44.98 440.00 277.18 44.99 440.00 277.18 45.00 440.00 277.18 45.01 440.00 277.18 45.02 440.00 277.18 45.03 440.00 277.18 45.04 440.00 277.18 45.05 440.00 277.18 45.06 440.00 277.18 45.07 440.00 277.18 45.08 440.00 277.18 45.09 440.00 277.18 45.10 277.18 45.11 277.18 369.99 45.12 277.18 369.99 45.13 277.18 369.99 45.14 277.18 369.99 45.15 369.99 45.16 369.99 45.17 369.99 45.18 369.99 45.19 369.99 45.20 369.99 45.21 369.99 45.22 369.99 45.23 369.99 45.24 369.99 45.25 369.99 45.26 369.99 45.27 369.99 45.28 369.99 45.29 369.99 45.30 369.99 45.31 369.99 45.32 369.99 45.33 369.99 45.34 369.99 45.35 369.99 45.36 369.99 45.37 369.99 45.38 369.99 45.39 369.99 45.40 369.99 45.41 369.99 45.42 369.99 45.43 369.99 45.44 369.99 45.45 369.99 45.46 369.99 45.47 369.99 45.48 369.99 45.49 369.99 45.50 369.99 45.51 369.99 45.52 369.99 45.53 369.99 45.54 369.99 45.55 369.99 45.56 369.99 45.57 369.99 45.58 369.99 45.59 369.99 45.60 369.99 45.61 369.99 123.47 61.74 45.62 369.99 123.47 61.74 45.63 369.99 123.47 61.74 45.64 369.99 123.47 61.74 45.65 369.99 123.47 61.74 45.66 369.99 123.47 61.74 45.67 369.99 123.47 61.74 207.65 45.68 369.99 123.47 61.74 207.65 415.30 45.69 369.99 123.47 61.74 207.65 415.30 45.70 369.99 123.47 61.74 207.65 415.30 45.71 369.99 123.47 61.74 207.65 415.30 45.72 123.47 61.74 207.65 415.30 45.73 123.47 61.74 207.65 415.30 45.74 123.47 61.74 207.65 415.30 45.75 123.47 61.74 207.65 415.30 45.76 123.47 61.74 207.65 415.30 45.77 123.47 61.74 207.65 415.30 45.78 123.47 61.74 207.65 415.30 45.79 123.47 61.74 207.65 415.30 45.80 123.47 61.74 207.65 415.30 45.81 123.47 61.74 207.65 415.30 45.82 123.47 61.74 207.65 415.30 45.83 123.47 61.74 207.65 415.30 45.84 123.47 61.74 207.65 415.30 45.85 123.47 61.74 207.65 415.30 45.86 123.47 61.74 207.65 415.30 45.87 123.47 61.74 207.65 415.30 45.88 123.47 61.74 207.65 415.30 45.89 123.47 61.74 207.65 415.30 45.90 123.47 61.74 207.65 415.30 45.91 123.47 61.74 207.65 415.30 45.92 123.47 61.74 207.65 415.30 45.93 123.47 61.74 207.65 415.30 45.94 123.47 61.74 207.65 415.30 45.95 123.47 61.74 207.65 415.30 45.96 123.47 61.74 207.65 415.30 45.97 123.47 61.74 207.65 415.30 45.98 123.47 61.74 207.65 415.30 45.99 123.47 61.74 207.65 415.30 46.00 123.47 61.74 207.65 415.30 46.01 123.47 61.74 207.65 415.30 46.02 123.47 61.74 207.65 415.30 46.03 123.47 61.74 207.65 415.30 46.04 123.47 61.74 207.65 415.30 46.05 123.47 61.74 207.65 415.30 46.06 123.47 61.74 207.65 415.30 46.07 123.47 61.74 207.65 415.30 46.08 123.47 61.74 207.65 415.30 46.09 123.47 61.74 207.65 415.30 46.10 123.47 61.74 207.65 415.30 46.11 123.47 61.74 207.65 415.30 46.12 123.47 61.74 207.65 415.30 46.13 123.47 61.74 207.65 415.30 46.14 123.47 61.74 207.65 415.30 46.15 123.47 61.74 207.65 415.30 46.16 123.47 61.74 207.65 415.30 46.17 123.47 61.74 207.65 415.30 46.18 123.47 61.74 207.65 415.30 46.19 123.47 61.74 207.65 415.30 246.94 46.20 123.47 61.74 207.65 415.30 246.94 46.21 123.47 61.74 207.65 415.30 246.94 46.22 123.47 61.74 207.65 415.30 246.94 46.23 123.47 61.74 207.65 415.30 246.94 46.24 123.47 61.74 207.65 415.30 246.94 46.25 123.47 61.74 207.65 415.30 246.94 46.26 123.47 61.74 207.65 415.30 246.94 46.27 123.47 61.74 207.65 415.30 246.94 46.28 123.47 61.74 207.65 415.30 246.94 46.29 123.47 61.74 207.65 415.30 246.94 46.30 123.47 61.74 207.65 415.30 246.94 46.31 123.47 61.74 207.65 415.30 246.94 46.32 123.47 61.74 207.65 415.30 246.94 46.33 123.47 61.74 207.65 415.30 246.94 46.34 123.47 61.74 207.65 415.30 246.94 46.35 123.47 61.74 207.65 415.30 246.94 46.36 123.47 61.74 207.65 415.30 246.94 46.37 123.47 61.74 207.65 415.30 246.94 46.38 123.47 61.74 207.65 415.30 246.94 46.39 123.47 61.74 207.65 415.30 246.94 46.40 123.47 61.74 207.65 415.30 246.94 46.41 123.47 61.74 207.65 415.30 246.94 46.42 123.47 61.74 207.65 415.30 246.94 46.43 123.47 61.74 207.65 415.30 246.94 46.44 123.47 61.74 207.65 415.30 246.94 46.45 123.47 61.74 207.65 415.30 246.94 46.46 123.47 61.74 207.65 415.30 246.94 46.47 123.47 61.74 207.65 415.30 246.94 46.48 123.47 61.74 207.65 415.30 246.94 46.49 123.47 61.74 207.65 415.30 246.94 46.50 123.47 61.74 207.65 415.30 246.94 46.51 123.47 61.74 207.65 415.30 246.94 46.52 123.47 61.74 207.65 415.30 246.94 46.53 123.47 61.74 207.65 415.30 246.94 46.54 123.47 61.74 207.65 415.30 246.94 46.55 123.47 61.74 207.65 415.30 246.94 46.56 123.47 61.74 207.65 415.30 246.94 46.57 123.47 61.74 207.65 415.30 246.94 46.58 123.47 61.74 207.65 415.30 246.94 46.59 123.47 61.74 207.65 415.30 246.94 46.60 123.47 61.74 207.65 415.30 246.94 46.61 123.47 61.74 207.65 415.30 246.94 46.62 123.47 61.74 207.65 415.30 246.94 46.63 123.47 61.74 207.65 415.30 246.94 46.64 123.47 61.74 207.65 415.30 246.94 46.65 123.47 61.74 207.65 415.30 246.94 46.66 123.47 61.74 207.65 415.30 246.94 46.67 123.47 61.74 207.65 415.30 246.94 46.68 123.47 61.74 207.65 415.30 246.94 329.63 46.69 123.47 61.74 207.65 415.30 246.94 329.63 46.70 123.47 61.74 415.30 329.63 46.71 123.47 61.74 415.30 329.63 46.72 123.47 61.74 415.30 329.63 46.73 123.47 61.74 415.30 329.63 46.74 123.47 61.74 415.30 329.63 46.75 123.47 61.74 415.30 329.63 46.76 123.47 61.74 415.30 329.63 46.77 123.47 61.74 415.30 329.63 46.78 123.47 61.74 415.30 329.63 46.79 123.47 61.74 415.30 329.63 46.80 123.47 61.74 415.30 329.63 46.81 123.47 61.74 415.30 329.63 46.82 123.47 61.74 415.30 329.63 46.83 123.47 61.74 415.30 329.63 46.84 123.47 61.74 415.30 329.63 46.85 123.47 61.74 415.30 329.63 46.86 123.47 61.74 415.30 329.63 46.87 123.47 61.74 415.30 329.63 46.88 123.47 61.74 415.30 329.63 46.89 123.47 61.74 415.30 329.63 46.90 123.47 61.74 415.30 329.63 46.91 123.47 61.74 415.30 329.63 46.92 123.47 61.74 415.30 329.63 46.93 123.47 61.74 415.30 329.63 46.94 123.47 61.74 415.30 329.63 46.95 123.47 61.74 415.30 329.63 46.96 123.47 61.74 415.30 329.63 46.97 123.47 61.74 415.30 329.63 46.98 123.47 61.74 415.30 329.63 46.99 123.47 61.74 415.30 329.63 47.00 123.47 61.74 415.30 329.63 47.01 123.47 61.74 415.30 329.63 47.02 123.47 61.74 415.30 329.63 47.03 123.47 61.74 415.30 329.63 47.04 123.47 61.74 415.30 329.63 47.05 123.47 61.74 415.30 329.63 47.06 123.47 61.74 415.30 329.63 47.07 123.47 61.74 415.30 329.63 47.08 123.47 61.74 415.30 329.63 47.09 123.47 61.74 415.30 329.63 47.10 123.47 61.74 415.30 329.63 47.11 123.47 61.74 415.30 329.63 47.12 123.47 61.74 415.30 329.63 47.13 123.47 61.74 415.30 329.63 47.14 123.47 61.74 415.30 329.63 47.15 123.47 61.74 415.30 329.63 47.16 123.47 61.74 415.30 329.63 207.65 47.17 123.47 61.74 415.30 329.63 207.65 47.18 123.47 61.74 415.30 329.63 207.65 47.19 123.47 61.74 415.30 207.65 47.20 123.47 61.74 415.30 207.65 47.21 123.47 61.74 415.30 207.65 47.22 123.47 61.74 415.30 207.65 47.23 123.47 61.74 415.30 207.65 47.24 123.47 61.74 415.30 207.65 47.25 123.47 61.74 415.30 207.65 47.26 123.47 61.74 415.30 207.65 47.27 123.47 61.74 415.30 207.65 47.28 123.47 61.74 415.30 207.65 47.29 123.47 61.74 415.30 207.65 47.30 123.47 61.74 415.30 207.65 47.31 123.47 61.74 415.30 207.65 47.32 123.47 61.74 415.30 207.65 47.33 123.47 61.74 415.30 207.65 47.34 123.47 61.74 415.30 207.65 47.35 123.47 61.74 415.30 207.65 47.36 123.47 61.74 415.30 207.65 47.37 123.47 61.74 415.30 207.65 47.38 123.47 61.74 415.30 207.65 47.39 123.47 61.74 415.30 207.65 47.40 123.47 61.74 415.30 207.65 47.41 123.47 61.74 415.30 207.65 47.42 123.47 61.74 415.30 207.65 47.43 123.47 61.74 415.30 207.65 47.44 123.47 61.74 415.30 207.65 47.45 123.47 61.74 415.30 207.65 47.46 123.47 61.74 415.30 207.65 47.47 123.47 61.74 415.30 207.65 47.48 123.47 61.74 415.30 207.65 47.49 123.47 61.74 415.30 207.65 47.50 123.47 61.74 415.30 207.65 47.51 123.47 61.74 415.30 207.65 47.52 123.47 61.74 415.30 207.65 47.53 123.47 61.74 415.30 207.65 47.54 123.47 61.74 415.30 207.65 47.55 123.47 61.74 415.30 207.65 47.56 123.47 61.74 415.30 207.65 47.57 123.47 61.74 415.30 207.65 47.58 123.47 61.74 415.30 207.65 246.94 47.59 123.47 61.74 415.30 207.65 246.94 47.60 123.47 61.74 415.30 207.65 246.94 47.61 123.47 61.74 415.30 207.65 246.94 47.62 123.47 61.74 415.30 207.65 246.94 47.63 123.47 61.74 415.30 207.65 246.94 47.64 123.47 61.74 415.30 207.65 246.94 47.65 123.47 61.74 415.30 207.65 246.94 47.66 123.47 61.74 415.30 207.65 246.94 47.67 123.47 61.74 415.30 207.65 246.94 47.68 123.47 61.74 415.30 207.65 246.94 47.69 123.47 61.74 415.30 207.65 246.94 47.70 123.47 61.74 415.30 207.65 246.94 47.71 123.47 61.74 415.30 207.65 246.94 47.72 415.30 207.65 246.94 47.73 415.30 207.65 246.94 47.74 415.30 207.65 246.94 47.75 415.30 207.65 246.94 47.76 415.30 207.65 246.94 47.77 415.30 207.65 246.94 47.78 415.30 207.65 246.94 47.79 415.30 207.65 246.94 47.80 415.30 207.65 246.94 47.81 415.30 207.65 246.94 47.82 415.30 207.65 246.94 47.83 415.30 207.65 246.94 47.84 415.30 207.65 246.94 47.85 415.30 207.65 246.94 47.86 415.30 207.65 246.94 47.87 415.30 207.65 246.94 47.88 415.30 207.65 246.94 47.89 415.30 207.65 246.94 47.90 415.30 207.65 246.94 47.91 415.30 207.65 246.94 47.92 415.30 207.65 246.94 47.93 415.30 207.65 246.94 47.94 415.30 207.65 246.94 47.95 415.30 207.65 246.94 47.96 415.30 207.65 246.94 47.97 415.30 207.65 246.94 47.98 415.30 207.65 246.94 47.99 415.30 207.65 246.94 48.00 415.30 207.65 246.94 48.01 415.30 207.65 246.94 48.02 415.30 207.65 246.94 48.03 415.30 207.65 246.94 48.04 415.30 207.65 246.94 48.05 415.30 207.65 246.94 48.06 415.30 207.65 246.94 48.07 415.30 207.65 246.94 48.08 415.30 207.65 246.94 48.09 415.30 207.65 246.94 48.10 415.30 207.65 246.94 48.11 415.30 207.65 246.94 329.63 48.12 415.30 207.65 246.94 329.63 48.13 415.30 207.65 246.94 329.63 48.14 207.65 329.63 48.15 329.63 48.16 329.63 48.17 329.63 48.18 329.63 48.19 329.63 48.20 329.63 48.21 329.63 48.22 329.63 48.23 329.63 48.24 329.63 48.25 329.63 48.26 329.63 48.27 329.63 48.28 329.63 48.29 329.63 48.30 329.63 48.31 329.63 48.32 329.63 48.33 329.63 48.34 329.63 48.35 329.63 48.36 329.63 48.37 329.63 48.38 329.63 48.39 329.63 48.40 329.63 48.41 329.63 48.42 329.63 48.43 329.63 48.44 329.63 48.45 329.63 48.46 329.63 48.47 329.63 48.48 329.63 48.49 329.63 48.50 329.63 48.51 329.63 48.52 329.63 48.53 329.63 48.54 329.63 48.55 329.63 48.56 329.63 48.57 329.63 48.58 329.63 48.59 329.63 48.60 329.63 48.61 329.63 48.62 329.63 123.47 61.74 48.63 329.63 123.47 61.74 48.64 329.63 123.47 61.74 48.65 329.63 123.47 61.74 48.66 329.63 123.47 61.74 48.67 329.63 123.47 61.74 220.00 48.68 329.63 123.47 61.74 220.00 369.99 48.69 329.63 123.47 61.74 220.00 369.99 48.70 329.63 123.47 61.74 220.00 369.99 48.71 123.47 61.74 220.00 369.99 48.72 123.47 61.74 220.00 369.99 48.73 123.47 61.74 220.00 369.99 48.74 123.47 61.74 220.00 369.99 48.75 123.47 61.74 220.00 369.99 48.76 123.47 61.74 220.00 369.99 48.77 123.47 61.74 220.00 369.99 48.78 123.47 61.74 220.00 369.99 48.79 123.47 61.74 220.00 369.99 48.80 123.47 61.74 220.00 369.99 48.81 123.47 61.74 220.00 369.99 48.82 123.47 61.74 220.00 369.99 48.83 123.47 61.74 220.00 369.99 48.84 123.47 61.74 220.00 369.99 48.85 123.47 61.74 220.00 369.99 48.86 123.47 61.74 220.00 369.99 48.87 123.47 61.74 220.00 369.99 48.88 123.47 61.74 220.00 369.99 48.89 123.47 61.74 220.00 369.99 48.90 123.47 61.74 220.00 369.99 48.91 123.47 61.74 220.00 369.99 48.92 123.47 61.74 220.00 369.99 48.93 123.47 61.74 220.00 369.99 48.94 123.47 61.74 220.00 369.99 48.95 123.47 61.74 220.00 369.99 48.96 123.47 61.74 220.00 369.99 48.97 123.47 61.74 220.00 369.99 48.98 123.47 61.74 220.00 369.99 48.99 123.47 61.74 220.00 369.99 49.00 123.47 61.74 220.00 369.99 49.01 123.47 61.74 220.00 369.99 49.02 123.47 61.74 220.00 369.99 49.03 123.47 61.74 220.00 369.99 49.04 123.47 61.74 220.00 369.99 49.05 123.47 61.74 220.00 369.99 49.06 123.47 61.74 220.00 369.99 49.07 123.47 61.74 220.00 369.99 49.08 123.47 61.74 220.00 369.99 49.09 123.47 61.74 220.00 369.99 49.10 123.47 61.74 220.00 369.99 49.11 123.47 61.74 220.00 369.99 49.12 123.47 61.74 220.00 369.99 49.13 123.47 61.74 220.00 369.99 49.14 123.47 61.74 220.00 369.99 49.15 123.47 61.74 220.00 369.99 49.16 123.47 61.74 220.00 369.99 49.17 123.47 61.74 220.00 369.99 246.94 49.18 123.47 61.74 220.00 369.99 246.94 49.19 123.47 61.74 220.00 369.99 246.94 49.20 123.47 61.74 220.00 369.99 246.94 49.21 123.47 61.74 220.00 369.99 246.94 49.22 123.47 61.74 220.00 369.99 246.94 49.23 123.47 61.74 220.00 369.99 246.94 49.24 123.47 61.74 220.00 369.99 246.94 49.25 123.47 61.74 220.00 369.99 246.94 49.26 123.47 61.74 220.00 369.99 246.94 49.27 123.47 61.74 220.00 369.99 246.94 49.28 123.47 61.74 220.00 369.99 246.94 49.29 123.47 61.74 220.00 369.99 246.94 49.30 123.47 61.74 220.00 369.99 246.94 49.31 123.47 61.74 220.00 369.99 246.94 49.32 123.47 61.74 220.00 369.99 246.94 49.33 123.47 61.74 220.00 369.99 246.94 49.34 123.47 61.74 220.00 369.99 246.94 49.35 123.47 61.74 220.00 369.99 246.94 49.36 123.47 61.74 220.00 369.99 246.94 49.37 123.47 61.74 220.00 369.99 246.94 49.38 123.47 61.74 220.00 369.99 246.94 49.39 123.47 61.74 220.00 369.99 246.94 49.40 123.47 61.74 220.00 369.99 246.94 49.41 123.47 61.74 220.00 369.99 246.94 49.42 123.47 61.74 220.00 369.99 246.94 49.43 123.47 61.74 220.00 369.99 246.94 49.44 123.47 61.74 220.00 369.99 246.94 49.45 123.47 61.74 220.00 369.99 246.94 49.46 123.47 61.74 220.00 369.99 246.94 49.47 123.47 61.74 220.00 369.99 246.94 49.48 123.47 61.74 220.00 369.99 246.94 49.49 123.47 61.74 220.00 369.99 246.94 49.50 123.47 61.74 220.00 369.99 246.94 49.51 123.47 61.74 220.00 369.99 246.94 49.52 123.47 61.74 220.00 369.99 246.94 49.53 123.47 61.74 220.00 369.99 246.94 49.54 123.47 61.74 220.00 369.99 246.94 49.55 123.47 61.74 220.00 369.99 246.94 49.56 123.47 61.74 220.00 369.99 246.94 49.57 123.47 61.74 220.00 369.99 246.94 49.58 123.47 61.74 220.00 369.99 246.94 49.59 123.47 61.74 220.00 369.99 246.94 49.60 123.47 61.74 220.00 369.99 246.94 49.61 123.47 61.74 369.99 246.94 49.62 123.47 61.74 369.99 246.94 49.63 123.47 61.74 369.99 246.94 49.64 123.47 61.74 369.99 246.94 49.65 123.47 61.74 369.99 246.94 49.66 123.47 61.74 369.99 246.94 311.13 49.67 123.47 61.74 369.99 246.94 311.13 49.68 123.47 61.74 369.99 311.13 49.69 123.47 61.74 311.13 49.70 123.47 61.74 311.13 49.71 123.47 61.74 311.13 49.72 123.47 61.74 311.13 49.73 123.47 61.74 311.13 49.74 123.47 61.74 311.13 49.75 123.47 61.74 311.13 49.76 123.47 61.74 311.13 49.77 123.47 61.74 311.13 49.78 123.47 61.74 311.13 49.79 123.47 61.74 311.13 49.80 123.47 61.74 311.13 49.81 123.47 61.74 311.13 49.82 123.47 61.74 311.13 49.83 123.47 61.74 311.13 49.84 123.47 61.74 311.13 49.85 123.47 61.74 311.13 49.86 123.47 61.74 311.13 49.87 123.47 61.74 311.13 49.88 123.47 61.74 311.13 49.89 123.47 61.74 311.13 49.90 123.47 61.74 311.13 49.91 123.47 61.74 311.13 49.92 123.47 61.74 311.13 49.93 123.47 61.74 311.13 49.94 123.47 61.74 311.13 49.95 123.47 61.74 311.13 49.96 123.47 61.74 311.13 49.97 123.47 61.74 311.13 49.98 123.47 61.74 311.13 49.99 123.47 61.74 311.13 50.00 123.47 61.74 311.13 50.01 123.47 61.74 311.13 50.02 123.47 61.74 311.13 50.03 123.47 61.74 311.13 50.04 123.47 61.74 311.13 50.05 123.47 61.74 311.13 50.06 123.47 61.74 311.13 50.07 123.47 61.74 311.13 50.08 123.47 61.74 311.13 50.09 123.47 61.74 50.10 123.47 61.74 50.11 123.47 61.74 50.12 123.47 61.74 50.13 123.47 61.74 50.14 123.47 61.74 493.88 50.15 123.47 61.74 493.88 220.00 50.16 123.47 61.74 493.88 220.00 50.17 123.47 61.74 493.88 220.00 50.18 123.47 61.74 493.88 220.00 50.19 123.47 61.74 493.88 220.00 50.20 123.47 61.74 493.88 220.00 50.21 123.47 61.74 493.88 220.00 50.22 123.47 61.74 493.88 220.00 50.23 123.47 61.74 493.88 220.00 50.24 123.47 61.74 493.88 220.00 50.25 123.47 61.74 493.88 220.00 50.26 123.47 61.74 493.88 220.00 50.27 123.47 61.74 493.88 220.00 50.28 123.47 61.74 493.88 220.00 50.29 123.47 61.74 493.88 220.00 50.30 123.47 61.74 493.88 220.00 50.31 123.47 61.74 493.88 220.00 50.32 123.47 61.74 493.88 220.00 50.33 123.47 61.74 493.88 220.00 50.34 123.47 61.74 493.88 220.00 50.35 123.47 61.74 493.88 220.00 50.36 123.47 61.74 493.88 220.00 50.37 123.47 61.74 493.88 220.00 50.38 123.47 61.74 493.88 220.00 50.39 123.47 61.74 493.88 220.00 50.40 123.47 61.74 493.88 220.00 50.41 123.47 61.74 493.88 220.00 50.42 123.47 61.74 493.88 220.00 50.43 123.47 61.74 493.88 220.00 50.44 123.47 61.74 493.88 220.00 50.45 123.47 61.74 493.88 220.00 50.46 123.47 61.74 493.88 220.00 50.47 123.47 61.74 493.88 220.00 50.48 123.47 61.74 493.88 220.00 50.49 123.47 61.74 493.88 220.00 50.50 123.47 61.74 493.88 220.00 50.51 123.47 61.74 493.88 220.00 50.52 123.47 61.74 493.88 220.00 50.53 123.47 61.74 493.88 220.00 50.54 123.47 61.74 493.88 220.00 50.55 123.47 61.74 493.88 220.00 50.56 123.47 61.74 493.88 220.00 50.57 123.47 61.74 493.88 220.00 50.58 123.47 61.74 493.88 220.00 50.59 123.47 61.74 493.88 220.00 50.60 123.47 61.74 493.88 220.00 50.61 123.47 61.74 493.88 220.00 50.62 123.47 61.74 493.88 220.00 50.63 123.47 61.74 493.88 220.00 50.64 123.47 61.74 493.88 220.00 50.65 123.47 493.88 220.00 50.66 493.88 220.00 50.67 493.88 220.00 50.68 493.88 220.00 246.94 50.69 493.88 220.00 246.94 50.70 493.88 220.00 246.94 50.71 493.88 246.94 50.72 493.88 246.94 50.73 493.88 246.94 50.74 493.88 246.94 50.75 493.88 246.94 50.76 493.88 246.94 50.77 493.88 246.94 50.78 493.88 246.94 50.79 493.88 246.94 50.80 493.88 246.94 50.81 493.88 246.94 50.82 246.94 50.83 246.94 50.84 246.94 50.85 246.94 50.86 246.94 50.87 246.94 50.88 246.94 50.89 246.94 50.90 246.94 50.91 246.94 50.92 246.94 50.93 246.94 50.94 246.94 50.95 246.94 50.96 246.94 50.97 246.94 50.98 246.94 50.99 246.94 51.00 246.94 51.01 246.94 51.02 246.94 51.03 246.94 51.04 246.94 51.05 246.94 51.06 246.94 51.07 246.94 51.08 246.94 51.09 246.94 51.10 246.94 51.11 246.94 51.12 246.94 51.13 246.94 51.14 246.94 51.15 246.94 51.16 246.94 51.17 246.94 51.18 246.94 51.19 246.94 311.13 51.20 246.94 311.13 51.21 246.94 311.13 51.22 246.94 311.13 51.23 246.94 311.13 51.24 311.13 51.25 311.13 51.26 311.13 51.27 311.13 51.28 311.13 51.29 311.13 51.30 311.13 51.31 311.13 51.32 311.13 51.33 311.13 51.34 311.13 51.35 311.13 51.36 311.13 51.37 311.13 51.38 311.13 51.39 311.13 51.40 311.13 51.41 311.13 51.42 311.13 51.43 311.13 51.44 311.13 51.45 311.13 51.46 311.13 51.47 311.13 51.48 311.13 51.49 311.13 51.50 311.13 51.51 311.13 51.52 311.13 51.53 311.13 51.54 311.13 51.55 311.13 51.56 311.13 51.57 311.13 51.58 311.13 51.59 311.13 51.60 311.13 51.61 311.13 51.62 311.13 51.63 311.13 51.64 311.13 51.65 311.13 51.66 311.13 51.67 311.13 51.68 311.13 51.69 311.13 51.70 311.13 51.71 311.13 51.72 311.13 51.73 311.13 51.74 311.13 51.75 311.13 82.41 51.76 311.13 82.41 51.77 311.13 82.41 164.81 51.78 311.13 82.41 164.81 51.79 311.13 82.41 164.81 207.65 329.63 51.80 311.13 82.41 164.81 207.65 329.63 51.81 311.13 82.41 164.81 207.65 329.63 51.82 311.13 82.41 164.81 207.65 329.63 51.83 311.13 82.41 164.81 207.65 329.63 51.84 311.13 82.41 164.81 207.65 329.63 51.85 311.13 82.41 164.81 207.65 329.63 51.86 311.13 82.41 164.81 207.65 329.63 51.87 311.13 82.41 164.81 207.65 329.63 51.88 82.41 164.81 207.65 329.63 51.89 82.41 164.81 207.65 329.63 51.90 82.41 164.81 207.65 329.63 51.91 82.41 164.81 207.65 329.63 51.92 82.41 164.81 207.65 329.63 51.93 82.41 164.81 207.65 329.63 51.94 82.41 164.81 207.65 329.63 51.95 82.41 164.81 207.65 329.63 51.96 82.41 164.81 207.65 329.63 51.97 82.41 164.81 207.65 329.63 51.98 82.41 164.81 207.65 329.63 51.99 82.41 164.81 207.65 329.63 52.00 82.41 164.81 207.65 329.63 52.01 82.41 164.81 207.65 329.63 52.02 82.41 164.81 207.65 329.63 52.03 82.41 164.81 207.65 329.63 52.04 82.41 164.81 207.65 329.63 52.05 82.41 164.81 207.65 329.63 52.06 82.41 164.81 207.65 329.63 52.07 82.41 164.81 207.65 329.63 52.08 82.41 164.81 207.65 329.63 52.09 82.41 164.81 207.65 329.63 52.10 82.41 164.81 207.65 329.63 52.11 82.41 164.81 207.65 329.63 52.12 82.41 164.81 207.65 329.63 52.13 82.41 164.81 207.65 329.63 52.14 82.41 164.81 207.65 329.63 52.15 82.41 164.81 207.65 329.63 52.16 82.41 164.81 207.65 329.63 52.17 82.41 164.81 207.65 329.63 52.18 82.41 164.81 207.65 329.63 52.19 82.41 164.81 207.65 329.63 52.20 82.41 164.81 207.65 329.63 52.21 82.41 164.81 207.65 329.63 52.22 82.41 164.81 207.65 329.63 52.23 82.41 164.81 207.65 329.63 52.24 82.41 164.81 207.65 329.63 52.25 82.41 164.81 207.65 329.63 52.26 82.41 164.81 207.65 329.63 52.27 82.41 164.81 207.65 329.63 52.28 82.41 164.81 207.65 329.63 52.29 82.41 164.81 207.65 329.63 52.30 82.41 164.81 207.65 329.63 52.31 82.41 164.81 207.65 329.63 52.32 82.41 164.81 207.65 329.63 52.33 82.41 164.81 207.65 329.63 52.34 82.41 164.81 207.65 329.63 52.35 82.41 164.81 207.65 329.63 52.36 82.41 164.81 207.65 329.63 52.37 82.41 164.81 207.65 329.63 52.38 82.41 164.81 207.65 329.63 52.39 82.41 164.81 207.65 329.63 52.40 82.41 164.81 207.65 329.63 52.41 82.41 164.81 207.65 329.63 52.42 82.41 164.81 207.65 329.63 52.43 82.41 164.81 207.65 329.63 52.44 82.41 164.81 207.65 329.63 52.45 82.41 164.81 207.65 329.63 52.46 82.41 164.81 207.65 329.63 52.47 82.41 164.81 207.65 329.63 52.48 82.41 164.81 207.65 329.63 52.49 82.41 164.81 207.65 329.63 52.50 82.41 164.81 207.65 329.63 52.51 82.41 164.81 207.65 329.63 52.52 82.41 164.81 207.65 329.63 246.94 52.53 82.41 164.81 207.65 246.94 52.54 82.41 164.81 207.65 246.94 52.55 82.41 164.81 207.65 246.94 52.56 82.41 164.81 207.65 246.94 52.57 82.41 164.81 207.65 246.94 52.58 82.41 164.81 207.65 246.94 52.59 82.41 164.81 207.65 246.94 52.60 82.41 164.81 207.65 246.94 52.61 82.41 164.81 207.65 246.94 52.62 82.41 164.81 207.65 246.94 52.63 82.41 164.81 207.65 246.94 52.64 82.41 164.81 207.65 246.94 52.65 82.41 164.81 207.65 246.94 52.66 82.41 164.81 207.65 246.94 52.67 82.41 164.81 207.65 246.94 52.68 82.41 164.81 207.65 246.94 52.69 82.41 164.81 207.65 246.94 52.70 82.41 164.81 207.65 246.94 52.71 82.41 164.81 207.65 246.94 52.72 82.41 164.81 207.65 246.94 52.73 82.41 164.81 207.65 246.94 52.74 82.41 164.81 207.65 246.94 52.75 82.41 164.81 207.65 246.94 52.76 82.41 164.81 207.65 246.94 52.77 82.41 164.81 207.65 246.94 52.78 82.41 164.81 207.65 246.94 52.79 82.41 164.81 207.65 246.94 52.80 82.41 164.81 207.65 246.94 52.81 82.41 164.81 207.65 246.94 52.82 82.41 164.81 207.65 246.94 52.83 82.41 164.81 207.65 246.94 52.84 82.41 164.81 207.65 246.94 52.85 82.41 164.81 207.65 246.94 52.86 82.41 164.81 207.65 246.94 52.87 82.41 164.81 207.65 246.94 52.88 82.41 164.81 207.65 246.94 52.89 82.41 164.81 207.65 246.94 52.90 82.41 164.81 207.65 246.94 52.91 82.41 164.81 207.65 246.94 52.92 82.41 164.81 207.65 246.94 52.93 82.41 164.81 207.65 246.94 52.94 82.41 164.81 207.65 246.94 52.95 82.41 164.81 207.65 246.94 52.96 82.41 164.81 207.65 246.94 52.97 82.41 164.81 207.65 246.94 52.98 82.41 164.81 207.65 246.94 52.99 82.41 164.81 207.65 246.94 53.00 82.41 164.81 207.65 246.94 329.63 53.01 82.41 164.81 207.65 246.94 329.63 53.02 82.41 164.81 207.65 246.94 329.63 53.03 82.41 164.81 207.65 246.94 329.63 53.04 82.41 164.81 207.65 246.94 329.63 53.05 82.41 164.81 207.65 329.63 53.06 82.41 164.81 207.65 329.63 53.07 82.41 164.81 207.65 329.63 53.08 82.41 164.81 207.65 329.63 53.09 82.41 164.81 207.65 329.63 53.10 82.41 164.81 207.65 329.63 53.11 82.41 164.81 207.65 329.63 53.12 82.41 164.81 207.65 329.63 53.13 82.41 164.81 207.65 329.63 53.14 82.41 164.81 207.65 329.63 53.15 82.41 164.81 207.65 329.63 53.16 82.41 164.81 207.65 329.63 53.17 82.41 164.81 207.65 329.63 53.18 82.41 164.81 207.65 329.63 53.19 82.41 164.81 207.65 329.63 53.20 82.41 164.81 207.65 329.63 53.21 82.41 164.81 329.63 53.22 82.41 164.81 329.63 53.23 82.41 164.81 329.63 53.24 82.41 164.81 329.63 53.25 82.41 164.81 329.63 53.26 82.41 164.81 329.63 53.27 82.41 164.81 329.63 53.28 82.41 164.81 329.63 53.29 82.41 164.81 329.63 53.30 82.41 164.81 329.63 53.31 82.41 164.81 329.63 53.32 82.41 164.81 329.63 53.33 82.41 164.81 329.63 53.34 82.41 164.81 329.63 53.35 82.41 164.81 329.63 53.36 82.41 164.81 329.63 53.37 82.41 164.81 329.63 53.38 82.41 164.81 329.63 53.39 82.41 164.81 329.63 53.40 82.41 164.81 329.63 53.41 82.41 164.81 329.63 53.42 82.41 164.81 329.63 53.43 82.41 164.81 329.63 53.44 82.41 164.81 329.63 53.45 82.41 164.81 329.63 53.46 82.41 164.81 329.63 53.47 82.41 164.81 329.63 53.48 82.41 164.81 329.63 53.49 82.41 164.81 329.63 53.50 329.63 53.51 329.63 53.52 329.63mir_eval-0.8.2/tests/data/multipitch/ref06.txt000066400000000000000000001165631475740344600212710ustar00rootroot000000000000000.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.30 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.40 0.41 0.42 0.43 0.44 0.45 0.46 0.47 0.48 0.49 0.50 0.51 0.52 0.53 0.54 0.55 0.56 0.57 0.58 0.59 0.60 0.61 0.62 0.63 185.00 0.64 185.00 0.65 185.00 0.66 185.00 587.33 0.67 185.00 587.33 185.00 0.68 185.00 587.33 185.00 0.69 185.00 587.33 185.00 0.70 185.00 587.33 185.00 0.71 185.00 587.33 185.00 0.72 185.00 587.33 185.00 0.73 185.00 587.33 185.00 0.74 185.00 587.33 185.00 493.88 0.75 185.00 587.33 185.00 493.88 0.76 185.00 587.33 185.00 493.88 0.77 587.33 185.00 493.88 0.78 587.33 185.00 493.88 0.79 587.33 185.00 493.88 0.80 587.33 185.00 493.88 0.81 587.33 185.00 493.88 0.82 587.33 185.00 493.88 0.83 587.33 185.00 493.88 0.84 587.33 185.00 493.88 0.85 587.33 185.00 493.88 0.86 587.33 185.00 493.88 207.65 0.87 587.33 185.00 493.88 207.65 0.88 587.33 185.00 493.88 207.65 0.89 587.33 185.00 493.88 207.65 0.90 587.33 185.00 493.88 207.65 0.91 587.33 185.00 493.88 207.65 0.92 587.33 185.00 493.88 207.65 622.25 0.93 587.33 185.00 493.88 207.65 622.25 0.94 587.33 185.00 493.88 207.65 622.25 0.95 587.33 185.00 493.88 207.65 622.25 0.96 185.00 493.88 207.65 622.25 0.97 185.00 493.88 207.65 622.25 0.98 185.00 493.88 207.65 622.25 0.99 185.00 493.88 207.65 622.25 1.00 185.00 493.88 207.65 622.25 1.01 185.00 493.88 207.65 622.25 1.02 185.00 493.88 622.25 1.03 185.00 493.88 622.25 1.04 185.00 493.88 622.25 1.05 185.00 493.88 622.25 1.06 185.00 493.88 622.25 1.07 185.00 493.88 622.25 1.08 185.00 493.88 622.25 1.09 185.00 493.88 622.25 1.10 185.00 493.88 622.25 1.11 185.00 493.88 622.25 1.12 185.00 493.88 622.25 246.94 1.13 185.00 493.88 622.25 246.94 1.14 185.00 493.88 622.25 246.94 932.33 1.15 185.00 493.88 622.25 246.94 932.33 1.16 185.00 493.88 246.94 932.33 1.17 185.00 493.88 246.94 932.33 1.18 185.00 493.88 246.94 932.33 1.19 185.00 493.88 246.94 932.33 1.20 185.00 493.88 246.94 932.33 1.21 185.00 493.88 246.94 932.33 1.22 185.00 493.88 246.94 932.33 1.23 185.00 493.88 246.94 932.33 1.24 185.00 493.88 932.33 1.25 185.00 493.88 932.33 1.26 185.00 493.88 932.33 1.27 185.00 493.88 932.33 1.28 185.00 493.88 932.33 1.29 185.00 493.88 932.33 1.30 185.00 493.88 932.33 1.31 185.00 493.88 932.33 1.32 185.00 493.88 932.33 1.33 185.00 493.88 932.33 1.34 185.00 493.88 932.33 1.35 185.00 493.88 932.33 1.36 185.00 493.88 932.33 185.00 1.37 185.00 493.88 932.33 185.00 830.61 1.38 185.00 493.88 932.33 185.00 830.61 1.39 185.00 493.88 932.33 185.00 830.61 1.40 185.00 493.88 185.00 830.61 1.41 185.00 493.88 185.00 830.61 1.42 185.00 493.88 185.00 830.61 1.43 185.00 493.88 185.00 830.61 1.44 185.00 493.88 185.00 830.61 1.45 185.00 493.88 185.00 830.61 1.46 185.00 493.88 185.00 830.61 1.47 185.00 493.88 185.00 830.61 1.48 185.00 493.88 830.61 1.49 185.00 493.88 830.61 1.50 185.00 493.88 830.61 1.51 185.00 493.88 830.61 1.52 185.00 493.88 830.61 1.53 185.00 493.88 830.61 1.54 185.00 493.88 830.61 1.55 185.00 493.88 830.61 1.56 185.00 493.88 830.61 1.57 185.00 493.88 830.61 1.58 185.00 493.88 830.61 1.59 185.00 493.88 830.61 207.65 1.60 185.00 493.88 830.61 207.65 1.61 185.00 493.88 830.61 207.65 1.62 185.00 493.88 830.61 207.65 1.63 185.00 493.88 830.61 207.65 1.64 185.00 493.88 830.61 207.65 1.65 185.00 493.88 830.61 207.65 659.26 1.66 185.00 493.88 207.65 659.26 1.67 185.00 493.88 207.65 659.26 1.68 185.00 493.88 207.65 659.26 1.69 185.00 493.88 207.65 659.26 1.70 185.00 493.88 207.65 659.26 1.71 185.00 493.88 207.65 659.26 1.72 185.00 493.88 659.26 1.73 185.00 493.88 659.26 1.74 185.00 493.88 659.26 1.75 185.00 493.88 659.26 1.76 185.00 493.88 659.26 1.77 185.00 493.88 659.26 1.78 185.00 493.88 659.26 1.79 185.00 493.88 659.26 1.80 185.00 493.88 659.26 1.81 185.00 493.88 659.26 246.94 1.82 185.00 493.88 659.26 246.94 1.83 185.00 493.88 659.26 246.94 1.84 185.00 493.88 659.26 246.94 1.85 185.00 493.88 659.26 246.94 1.86 185.00 493.88 659.26 246.94 1.87 185.00 493.88 246.94 1.88 185.00 493.88 246.94 622.25 1.89 185.00 493.88 246.94 622.25 1.90 185.00 493.88 246.94 622.25 1.91 185.00 493.88 246.94 622.25 1.92 185.00 493.88 246.94 622.25 1.93 185.00 493.88 622.25 1.94 185.00 493.88 622.25 1.95 185.00 493.88 622.25 1.96 185.00 493.88 622.25 1.97 185.00 493.88 622.25 1.98 185.00 493.88 622.25 1.99 185.00 493.88 622.25 2.00 185.00 493.88 622.25 2.01 185.00 493.88 622.25 2.02 185.00 493.88 622.25 2.03 185.00 493.88 622.25 2.04 185.00 493.88 622.25 2.05 185.00 493.88 622.25 185.00 2.06 185.00 493.88 622.25 185.00 2.07 185.00 493.88 185.00 587.33 2.08 185.00 493.88 185.00 587.33 2.09 185.00 493.88 185.00 587.33 2.10 185.00 493.88 185.00 587.33 2.11 185.00 493.88 185.00 587.33 2.12 185.00 493.88 185.00 587.33 2.13 185.00 493.88 185.00 587.33 2.14 185.00 493.88 185.00 587.33 2.15 185.00 493.88 185.00 587.33 2.16 185.00 493.88 185.00 587.33 2.17 185.00 493.88 185.00 587.33 2.18 185.00 493.88 185.00 587.33 2.19 185.00 493.88 587.33 2.20 185.00 493.88 587.33 2.21 185.00 493.88 587.33 2.22 185.00 493.88 587.33 2.23 185.00 493.88 587.33 2.24 185.00 493.88 587.33 2.25 185.00 493.88 587.33 2.26 185.00 493.88 587.33 207.65 2.27 185.00 493.88 587.33 207.65 2.28 185.00 493.88 587.33 207.65 2.29 185.00 493.88 587.33 207.65 2.30 185.00 493.88 587.33 207.65 2.31 185.00 493.88 587.33 207.65 2.32 185.00 493.88 587.33 207.65 2.33 185.00 493.88 587.33 207.65 2.34 185.00 493.88 587.33 207.65 2.35 185.00 493.88 587.33 207.65 2.36 185.00 493.88 587.33 207.65 2.37 185.00 493.88 587.33 207.65 2.38 185.00 493.88 587.33 207.65 2.39 185.00 493.88 587.33 622.25 2.40 185.00 493.88 587.33 622.25 2.41 185.00 493.88 587.33 622.25 2.42 185.00 493.88 587.33 622.25 2.43 185.00 493.88 622.25 2.44 185.00 493.88 622.25 2.45 185.00 493.88 622.25 2.46 185.00 493.88 622.25 2.47 185.00 493.88 622.25 2.48 185.00 493.88 622.25 2.49 185.00 493.88 622.25 246.94 2.50 185.00 493.88 622.25 246.94 2.51 185.00 493.88 622.25 246.94 2.52 185.00 493.88 622.25 246.94 2.53 185.00 493.88 622.25 246.94 2.54 185.00 493.88 622.25 246.94 2.55 185.00 493.88 622.25 246.94 2.56 185.00 493.88 622.25 246.94 2.57 185.00 493.88 622.25 246.94 2.58 185.00 493.88 622.25 246.94 2.59 185.00 493.88 622.25 246.94 2.60 185.00 493.88 622.25 246.94 2.61 185.00 493.88 622.25 2.62 185.00 493.88 622.25 2.63 185.00 493.88 622.25 2.64 185.00 493.88 622.25 2.65 185.00 493.88 622.25 2.66 185.00 493.88 622.25 2.67 185.00 493.88 622.25 2.68 185.00 493.88 622.25 2.69 185.00 493.88 622.25 2.70 185.00 493.88 622.25 2.71 185.00 493.88 622.25 2.72 185.00 493.88 622.25 2.73 185.00 493.88 622.25 2.74 185.00 493.88 622.25 185.00 2.75 185.00 493.88 622.25 185.00 2.76 185.00 493.88 622.25 185.00 415.30 2.77 185.00 493.88 622.25 185.00 415.30 2.78 185.00 493.88 622.25 185.00 415.30 2.79 185.00 493.88 185.00 415.30 2.80 185.00 493.88 185.00 415.30 2.81 185.00 493.88 185.00 415.30 2.82 185.00 493.88 185.00 415.30 2.83 185.00 493.88 185.00 415.30 2.84 185.00 493.88 185.00 415.30 2.85 185.00 493.88 185.00 415.30 2.86 185.00 493.88 415.30 2.87 185.00 493.88 415.30 2.88 185.00 493.88 415.30 2.89 185.00 493.88 415.30 2.90 185.00 493.88 415.30 2.91 185.00 493.88 415.30 2.92 185.00 493.88 415.30 2.93 185.00 493.88 415.30 2.94 185.00 493.88 415.30 2.95 185.00 493.88 415.30 207.65 2.96 185.00 493.88 415.30 207.65 2.97 185.00 493.88 415.30 207.65 2.98 185.00 493.88 415.30 207.65 2.99 185.00 493.88 415.30 207.65 3.00 185.00 493.88 415.30 207.65 3.01 185.00 493.88 415.30 207.65 3.02 185.00 493.88 415.30 207.65 3.03 185.00 493.88 415.30 207.65 3.04 185.00 493.88 415.30 207.65 3.05 185.00 415.30 207.65 3.06 185.00 415.30 207.65 369.99 3.07 185.00 415.30 369.99 369.99 3.08 185.00 415.30 369.99 369.99 3.09 185.00 415.30 369.99 369.99 3.10 185.00 415.30 369.99 369.99 3.11 185.00 369.99 369.99 3.12 185.00 369.99 369.99 3.13 185.00 369.99 369.99 3.14 185.00 369.99 369.99 3.15 185.00 369.99 369.99 3.16 185.00 369.99 369.99 3.17 185.00 369.99 369.99 3.18 185.00 369.99 369.99 3.19 185.00 369.99 369.99 3.20 185.00 369.99 369.99 3.21 185.00 369.99 369.99 246.94 3.22 185.00 369.99 369.99 246.94 3.23 185.00 369.99 369.99 246.94 3.24 185.00 369.99 369.99 246.94 3.25 185.00 369.99 369.99 246.94 3.26 185.00 369.99 369.99 246.94 3.27 185.00 369.99 369.99 246.94 3.28 185.00 369.99 369.99 246.94 3.29 185.00 369.99 369.99 246.94 587.33 3.30 185.00 369.99 369.99 246.94 587.33 3.31 185.00 369.99 369.99 246.94 587.33 3.32 185.00 369.99 369.99 587.33 3.33 185.00 369.99 587.33 3.34 185.00 369.99 587.33 3.35 185.00 369.99 587.33 3.36 185.00 369.99 587.33 3.37 185.00 369.99 587.33 3.38 185.00 369.99 587.33 3.39 185.00 369.99 587.33 3.40 185.00 587.33 3.41 185.00 587.33 3.42 185.00 587.33 3.43 185.00 587.33 3.44 185.00 587.33 185.00 3.45 185.00 587.33 185.00 3.46 185.00 587.33 185.00 3.47 185.00 587.33 185.00 3.48 185.00 587.33 185.00 3.49 185.00 587.33 185.00 3.50 185.00 587.33 185.00 3.51 185.00 587.33 185.00 3.52 185.00 587.33 185.00 3.53 185.00 587.33 185.00 3.54 185.00 587.33 185.00 3.55 185.00 587.33 3.56 185.00 587.33 3.57 185.00 587.33 3.58 185.00 587.33 3.59 185.00 587.33 3.60 185.00 587.33 3.61 185.00 587.33 3.62 185.00 587.33 3.63 185.00 587.33 3.64 185.00 587.33 207.65 3.65 185.00 587.33 207.65 3.66 185.00 587.33 207.65 3.67 185.00 587.33 207.65 3.68 185.00 587.33 207.65 3.69 185.00 587.33 207.65 3.70 185.00 587.33 207.65 3.71 185.00 587.33 207.65 3.72 185.00 587.33 207.65 3.73 185.00 587.33 207.65 622.25 3.74 185.00 587.33 207.65 622.25 3.75 185.00 587.33 622.25 3.76 185.00 622.25 3.77 185.00 622.25 3.78 185.00 622.25 3.79 185.00 622.25 3.80 185.00 622.25 3.81 185.00 622.25 3.82 185.00 622.25 3.83 185.00 622.25 3.84 185.00 622.25 3.85 185.00 622.25 246.94 3.86 185.00 622.25 246.94 3.87 185.00 622.25 246.94 3.88 185.00 622.25 246.94 3.89 185.00 622.25 246.94 3.90 185.00 246.94 987.77 3.91 185.00 246.94 987.77 3.92 185.00 246.94 987.77 3.93 185.00 246.94 987.77 3.94 185.00 246.94 987.77 3.95 185.00 246.94 987.77 3.96 185.00 246.94 987.77 3.97 185.00 246.94 987.77 3.98 185.00 246.94 987.77 3.99 185.00 987.77 4.00 185.00 987.77 4.01 185.00 987.77 4.02 185.00 987.77 4.03 185.00 987.77 4.04 185.00 987.77 4.05 185.00 987.77 4.06 185.00 987.77 185.00 4.07 185.00 987.77 185.00 4.08 185.00 987.77 185.00 4.09 185.00 987.77 185.00 4.10 185.00 987.77 185.00 4.11 185.00 987.77 185.00 932.33 4.12 185.00 185.00 932.33 4.13 185.00 185.00 932.33 4.14 185.00 185.00 932.33 4.15 185.00 185.00 932.33 4.16 185.00 185.00 932.33 4.17 185.00 185.00 932.33 4.18 185.00 185.00 932.33 4.19 185.00 932.33 4.20 185.00 932.33 4.21 185.00 932.33 4.22 185.00 932.33 4.23 185.00 932.33 4.24 185.00 932.33 4.25 185.00 932.33 4.26 185.00 932.33 4.27 185.00 932.33 207.65 4.28 185.00 932.33 207.65 4.29 185.00 932.33 207.65 4.30 185.00 932.33 207.65 4.31 185.00 932.33 207.65 4.32 185.00 932.33 207.65 830.61 4.33 185.00 207.65 830.61 4.34 185.00 207.65 830.61 4.35 185.00 207.65 830.61 4.36 185.00 207.65 830.61 4.37 185.00 207.65 830.61 4.38 185.00 207.65 830.61 4.39 185.00 830.61 4.40 185.00 830.61 4.41 185.00 830.61 4.42 185.00 830.61 4.43 185.00 830.61 4.44 185.00 830.61 4.45 185.00 830.61 4.46 185.00 830.61 4.47 185.00 830.61 4.48 185.00 830.61 4.49 185.00 830.61 4.50 185.00 830.61 246.94 4.51 185.00 830.61 246.94 622.25 4.52 185.00 830.61 246.94 622.25 4.53 185.00 830.61 246.94 622.25 4.54 185.00 246.94 622.25 4.55 185.00 246.94 622.25 4.56 185.00 246.94 622.25 4.57 185.00 246.94 622.25 4.58 185.00 246.94 622.25 4.59 185.00 246.94 622.25 4.60 185.00 622.25 4.61 185.00 622.25 4.62 185.00 622.25 4.63 185.00 622.25 4.64 185.00 622.25 4.65 185.00 622.25 4.66 185.00 622.25 4.67 185.00 622.25 4.68 185.00 622.25 4.69 185.00 4.70 185.00 4.71 185.00 4.72 185.00 185.00 587.33 4.73 185.00 185.00 587.33 4.74 185.00 185.00 587.33 4.75 185.00 185.00 587.33 4.76 185.00 185.00 587.33 4.77 185.00 185.00 587.33 4.78 185.00 185.00 587.33 4.79 185.00 185.00 587.33 4.80 185.00 185.00 587.33 4.81 185.00 185.00 587.33 4.82 185.00 185.00 587.33 4.83 185.00 185.00 587.33 4.84 185.00 185.00 587.33 4.85 185.00 185.00 587.33 4.86 185.00 185.00 587.33 4.87 185.00 587.33 4.88 185.00 587.33 4.89 185.00 587.33 4.90 185.00 587.33 4.91 185.00 587.33 4.92 185.00 587.33 4.93 185.00 587.33 207.65 4.94 185.00 587.33 207.65 4.95 185.00 587.33 207.65 4.96 185.00 587.33 207.65 4.97 185.00 587.33 207.65 4.98 185.00 587.33 207.65 4.99 185.00 587.33 207.65 5.00 185.00 587.33 207.65 5.01 185.00 587.33 207.65 5.02 185.00 587.33 207.65 5.03 185.00 587.33 207.65 622.25 5.04 185.00 587.33 622.25 5.05 185.00 587.33 622.25 5.06 185.00 622.25 5.07 185.00 622.25 5.08 185.00 622.25 5.09 185.00 622.25 5.10 185.00 622.25 5.11 185.00 622.25 5.12 185.00 622.25 5.13 185.00 622.25 5.14 185.00 622.25 5.15 185.00 622.25 246.94 5.16 185.00 622.25 246.94 5.17 185.00 622.25 246.94 5.18 185.00 622.25 246.94 5.19 185.00 622.25 246.94 5.20 185.00 622.25 246.94 5.21 185.00 622.25 246.94 5.22 185.00 622.25 246.94 5.23 185.00 622.25 246.94 5.24 185.00 622.25 246.94 5.25 185.00 622.25 246.94 5.26 185.00 622.25 5.27 185.00 622.25 5.28 185.00 622.25 5.29 185.00 622.25 5.30 185.00 622.25 5.31 185.00 622.25 5.32 185.00 622.25 5.33 185.00 622.25 5.34 185.00 622.25 5.35 185.00 622.25 5.36 185.00 622.25 185.00 5.37 185.00 622.25 185.00 5.38 185.00 622.25 185.00 415.30 5.39 185.00 622.25 185.00 415.30 5.40 185.00 622.25 185.00 415.30 5.41 185.00 622.25 185.00 415.30 5.42 185.00 185.00 415.30 5.43 185.00 185.00 415.30 5.44 185.00 185.00 415.30 5.45 185.00 185.00 415.30 5.46 185.00 185.00 415.30 5.47 185.00 185.00 415.30 5.48 185.00 185.00 415.30 5.49 185.00 185.00 415.30 5.50 185.00 415.30 5.51 185.00 415.30 5.52 185.00 415.30 5.53 185.00 415.30 5.54 185.00 415.30 5.55 185.00 415.30 5.56 185.00 415.30 207.65 5.57 185.00 415.30 207.65 5.58 185.00 415.30 207.65 5.59 185.00 415.30 207.65 5.60 185.00 415.30 207.65 5.61 185.00 415.30 207.65 5.62 185.00 415.30 207.65 5.63 185.00 415.30 207.65 5.64 185.00 415.30 207.65 5.65 185.00 415.30 207.65 5.66 185.00 415.30 207.65 5.67 185.00 415.30 207.65 369.99 5.68 185.00 415.30 369.99 5.69 185.00 415.30 369.99 5.70 185.00 415.30 369.99 5.71 185.00 415.30 369.99 5.72 185.00 369.99 5.73 185.00 369.99 5.74 185.00 369.99 5.75 369.99 5.76 369.99 369.99 5.77 369.99 369.99 246.94 5.78 369.99 369.99 246.94 5.79 369.99 369.99 246.94 5.80 369.99 369.99 246.94 5.81 369.99 369.99 246.94 5.82 369.99 369.99 246.94 5.83 369.99 369.99 246.94 5.84 369.99 369.99 246.94 5.85 369.99 369.99 246.94 5.86 369.99 369.99 246.94 5.87 369.99 369.99 246.94 5.88 369.99 369.99 246.94 5.89 369.99 369.99 246.94 5.90 369.99 369.99 5.91 369.99 369.99 5.92 369.99 369.99 5.93 369.99 369.99 5.94 369.99 369.99 622.25 5.95 369.99 369.99 622.25 5.96 369.99 369.99 622.25 5.97 369.99 369.99 622.25 5.98 369.99 622.25 5.99 369.99 622.25 6.00 369.99 622.25 6.01 369.99 622.25 103.83 311.13 6.02 369.99 622.25 103.83 311.13 6.03 369.99 622.25 103.83 311.13 6.04 369.99 622.25 103.83 311.13 6.05 369.99 622.25 103.83 311.13 6.06 369.99 622.25 103.83 311.13 6.07 369.99 622.25 103.83 311.13 6.08 622.25 103.83 311.13 6.09 622.25 103.83 311.13 6.10 622.25 103.83 311.13 6.11 622.25 103.83 311.13 6.12 622.25 103.83 659.26 6.13 103.83 659.26 6.14 103.83 659.26 6.15 659.26 6.16 659.26 6.17 659.26 6.18 659.26 6.19 659.26 6.20 659.26 6.21 659.26 6.22 659.26 6.23 659.26 6.24 659.26 6.25 659.26 6.26 659.26 6.27 659.26 415.30 116.54 6.28 659.26 415.30 116.54 6.29 415.30 116.54 6.30 415.30 116.54 6.31 415.30 116.54 6.32 415.30 116.54 6.33 415.30 116.54 6.34 415.30 116.54 659.26 6.35 415.30 116.54 659.26 6.36 415.30 116.54 659.26 6.37 415.30 116.54 659.26 6.38 415.30 116.54 659.26 6.39 415.30 116.54 659.26 6.40 415.30 116.54 659.26 6.41 659.26 6.42 659.26 6.43 659.26 6.44 659.26 6.45 659.26 6.46 659.26 6.47 659.26 6.48 659.26 6.49 659.26 6.50 659.26 6.51 659.26 622.25 138.59 6.52 659.26 622.25 138.59 6.53 659.26 622.25 138.59 6.54 659.26 622.25 138.59 6.55 659.26 622.25 138.59 6.56 622.25 138.59 6.57 622.25 138.59 622.25 6.58 622.25 138.59 622.25 6.59 622.25 138.59 622.25 6.60 622.25 138.59 622.25 6.61 622.25 138.59 622.25 6.62 622.25 138.59 622.25 6.63 622.25 138.59 622.25 6.64 622.25 622.25 6.65 622.25 6.66 622.25 6.67 622.25 6.68 622.25 6.69 622.25 6.70 622.25 6.71 622.25 6.72 6.73 6.74 622.25 739.99 103.83 554.37 6.75 622.25 739.99 103.83 554.37 6.76 622.25 739.99 103.83 554.37 6.77 622.25 739.99 103.83 554.37 6.78 622.25 739.99 103.83 554.37 6.79 622.25 739.99 103.83 554.37 6.80 622.25 739.99 103.83 554.37 6.81 622.25 739.99 103.83 554.37 6.82 622.25 739.99 103.83 554.37 6.83 622.25 739.99 103.83 554.37 6.84 622.25 739.99 103.83 554.37 6.85 622.25 739.99 103.83 554.37 6.86 622.25 739.99 103.83 6.87 622.25 739.99 6.88 622.25 739.99 6.89 622.25 739.99 6.90 622.25 739.99 6.91 622.25 739.99 6.92 622.25 739.99 6.93 622.25 739.99 6.94 6.95 493.88 116.54 6.96 493.88 116.54 6.97 493.88 116.54 6.98 493.88 116.54 6.99 493.88 116.54 7.00 493.88 116.54 739.99 622.25 7.01 493.88 116.54 739.99 622.25 7.02 493.88 116.54 739.99 622.25 7.03 493.88 116.54 739.99 622.25 7.04 493.88 116.54 739.99 622.25 7.05 493.88 116.54 739.99 622.25 7.06 493.88 116.54 739.99 622.25 7.07 493.88 116.54 739.99 622.25 7.08 493.88 116.54 739.99 622.25 7.09 493.88 739.99 622.25 7.10 739.99 622.25 7.11 739.99 622.25 7.12 739.99 622.25 7.13 739.99 622.25 7.14 739.99 622.25 7.15 739.99 622.25 7.16 739.99 622.25 7.17 739.99 622.25 7.18 739.99 622.25 7.19 739.99 622.25 466.16 7.20 739.99 622.25 466.16 138.59 7.21 739.99 622.25 466.16 138.59 7.22 739.99 622.25 466.16 138.59 7.23 739.99 622.25 466.16 138.59 7.24 739.99 622.25 466.16 138.59 7.25 739.99 622.25 466.16 138.59 7.26 739.99 622.25 466.16 138.59 7.27 739.99 622.25 466.16 138.59 7.28 739.99 466.16 138.59 7.29 138.59 7.30 138.59 7.31 138.59 7.32 659.26 7.33 659.26 7.34 659.26 554.37 7.35 659.26 554.37 7.36 659.26 554.37 7.37 659.26 554.37 7.38 659.26 554.37 7.39 659.26 554.37 7.40 659.26 554.37 7.41 659.26 554.37 7.42 659.26 554.37 7.43 659.26 554.37 103.83 7.44 659.26 554.37 103.83 311.13 7.45 659.26 554.37 103.83 311.13 7.46 659.26 554.37 103.83 311.13 7.47 659.26 554.37 103.83 311.13 7.48 659.26 554.37 103.83 311.13 7.49 659.26 554.37 103.83 311.13 7.50 659.26 554.37 103.83 311.13 7.51 659.26 554.37 103.83 311.13 7.52 659.26 554.37 103.83 311.13 7.53 659.26 554.37 103.83 311.13 7.54 659.26 554.37 103.83 311.13 7.55 659.26 554.37 311.13 7.56 659.26 554.37 311.13 7.57 659.26 554.37 7.58 659.26 554.37 7.59 659.26 554.37 7.60 659.26 554.37 7.61 659.26 554.37 7.62 659.26 554.37 7.63 659.26 554.37 7.64 659.26 554.37 7.65 659.26 554.37 116.54 7.66 659.26 554.37 116.54 7.67 659.26 554.37 116.54 7.68 659.26 554.37 116.54 466.16 7.69 659.26 554.37 116.54 466.16 622.25 7.70 659.26 554.37 116.54 466.16 622.25 7.71 659.26 554.37 116.54 466.16 622.25 7.72 659.26 116.54 466.16 622.25 7.73 116.54 466.16 622.25 7.74 116.54 466.16 622.25 7.75 466.16 622.25 7.76 466.16 622.25 7.77 466.16 622.25 7.78 466.16 622.25 7.79 466.16 622.25 7.80 466.16 622.25 7.81 466.16 622.25 7.82 466.16 622.25 7.83 622.25 7.84 622.25 7.85 622.25 7.86 622.25 138.59 7.87 622.25 138.59 7.88 622.25 138.59 7.89 622.25 138.59 7.90 622.25 138.59 7.91 622.25 138.59 7.92 622.25 138.59 7.93 622.25 138.59 7.94 622.25 138.59 7.95 622.25 138.59 7.96 622.25 138.59 277.18 7.97 622.25 138.59 277.18 7.98 622.25 138.59 277.18 7.99 622.25 138.59 277.18 8.00 622.25 277.18 8.01 622.25 277.18 8.02 622.25 277.18 8.03 622.25 277.18 8.04 622.25 277.18 8.05 622.25 277.18 8.06 622.25 277.18 8.07 622.25 277.18 103.83 8.08 622.25 277.18 103.83 8.09 622.25 277.18 103.83 8.10 622.25 277.18 103.83 8.11 622.25 277.18 103.83 8.12 622.25 103.83 8.13 622.25 103.83 8.14 622.25 103.83 8.15 622.25 103.83 8.16 622.25 103.83 8.17 622.25 103.83 8.18 622.25 103.83 8.19 622.25 8.20 622.25 8.21 622.25 8.22 622.25 8.23 622.25 8.24 622.25 8.25 622.25 8.26 622.25 8.27 622.25 8.28 622.25 8.29 622.25 116.54 8.30 622.25 116.54 8.31 622.25 116.54 246.94 8.32 622.25 116.54 246.94 8.33 622.25 116.54 246.94 8.34 622.25 116.54 246.94 8.35 622.25 116.54 246.94 8.36 622.25 116.54 246.94 8.37 622.25 116.54 246.94 8.38 116.54 246.94 8.39 246.94 8.40 246.94 8.41 246.94 8.42 246.94 8.43 246.94 277.18 8.44 246.94 277.18 8.45 246.94 277.18 8.46 246.94 277.18 8.47 246.94 277.18 8.48 246.94 277.18 8.49 277.18 8.50 277.18 8.51 277.18 138.59 8.52 277.18 138.59 8.53 277.18 138.59 8.54 277.18 138.59 8.55 277.18 138.59 8.56 277.18 138.59 8.57 277.18 138.59 8.58 277.18 138.59 8.59 277.18 138.59 8.60 277.18 8.61 277.18 8.62 277.18 311.13 8.63 277.18 311.13 8.64 311.13 220.00 8.65 311.13 220.00 8.66 311.13 220.00 8.67 311.13 220.00 8.68 311.13 220.00 8.69 311.13 220.00 8.70 311.13 220.00 98.00 8.71 311.13 220.00 98.00 8.72 311.13 220.00 98.00 8.73 311.13 220.00 98.00 8.74 311.13 220.00 98.00 8.75 311.13 220.00 98.00 8.76 311.13 220.00 98.00 8.77 311.13 220.00 98.00 8.78 311.13 220.00 98.00 8.79 311.13 220.00 98.00 329.63 8.80 311.13 220.00 98.00 329.63 8.81 311.13 220.00 98.00 329.63 8.82 311.13 220.00 329.63 8.83 311.13 220.00 329.63 8.84 220.00 329.63 8.85 220.00 329.63 8.86 220.00 329.63 8.87 220.00 329.63 8.88 220.00 329.63 8.89 220.00 329.63 8.90 220.00 329.63 8.91 220.00 329.63 8.92 220.00 329.63 110.00 8.93 220.00 329.63 110.00 8.94 220.00 329.63 110.00 8.95 220.00 329.63 110.00 8.96 220.00 329.63 110.00 8.97 220.00 329.63 110.00 8.98 220.00 329.63 110.00 8.99 220.00 329.63 110.00 9.00 220.00 329.63 110.00 440.00 9.01 220.00 329.63 110.00 440.00 9.02 220.00 329.63 440.00 9.03 220.00 329.63 440.00 9.04 220.00 329.63 440.00 9.05 220.00 329.63 440.00 9.06 220.00 329.63 440.00 9.07 220.00 440.00 9.08 220.00 440.00 9.09 220.00 440.00 9.10 220.00 440.00 9.11 220.00 440.00 9.12 220.00 440.00 9.13 220.00 440.00 9.14 220.00 440.00 138.59 9.15 220.00 440.00 138.59 9.16 220.00 440.00 138.59 9.17 220.00 440.00 138.59 9.18 220.00 440.00 138.59 9.19 220.00 440.00 138.59 9.20 220.00 440.00 138.59 9.21 220.00 440.00 138.59 493.88 9.22 220.00 440.00 138.59 493.88 9.23 220.00 138.59 493.88 9.24 220.00 493.88 9.25 220.00 493.88 9.26 220.00 493.88 9.27 220.00 493.88 9.28 220.00 493.88 9.29 220.00 493.88 9.30 220.00 493.88 9.31 220.00 493.88 9.32 220.00 493.88 9.33 220.00 493.88 9.34 220.00 493.88 554.37 9.35 220.00 493.88 554.37 659.26 9.36 220.00 493.88 554.37 659.26 9.37 220.00 493.88 554.37 659.26 98.00 9.38 220.00 493.88 554.37 659.26 98.00 9.39 220.00 493.88 554.37 659.26 98.00 9.40 220.00 493.88 554.37 659.26 98.00 440.00 9.41 220.00 493.88 554.37 659.26 98.00 440.00 9.42 220.00 493.88 554.37 659.26 98.00 440.00 9.43 220.00 554.37 659.26 98.00 440.00 9.44 220.00 554.37 659.26 98.00 440.00 9.45 220.00 554.37 659.26 98.00 440.00 9.46 220.00 554.37 659.26 98.00 440.00 9.47 220.00 554.37 659.26 440.00 9.48 220.00 554.37 659.26 440.00 9.49 220.00 554.37 659.26 440.00 9.50 220.00 554.37 659.26 440.00 9.51 220.00 554.37 659.26 440.00 9.52 220.00 554.37 659.26 440.00 9.53 220.00 554.37 659.26 440.00 9.54 220.00 554.37 659.26 440.00 9.55 220.00 554.37 659.26 440.00 9.56 220.00 554.37 659.26 440.00 9.57 220.00 554.37 659.26 440.00 110.00 9.58 220.00 554.37 659.26 440.00 110.00 9.59 220.00 554.37 659.26 440.00 110.00 9.60 220.00 554.37 440.00 110.00 9.61 220.00 440.00 110.00 369.99 9.62 220.00 110.00 369.99 9.63 220.00 110.00 369.99 9.64 220.00 110.00 369.99 9.65 220.00 110.00 369.99 9.66 220.00 110.00 369.99 9.67 220.00 110.00 369.99 9.68 220.00 110.00 369.99 9.69 220.00 369.99 554.37 9.70 220.00 369.99 554.37 9.71 220.00 369.99 554.37 9.72 220.00 369.99 554.37 9.73 220.00 369.99 554.37 9.74 220.00 369.99 554.37 9.75 220.00 369.99 554.37 9.76 220.00 369.99 554.37 9.77 220.00 369.99 554.37 9.78 220.00 369.99 554.37 9.79 220.00 369.99 554.37 138.59 9.80 220.00 369.99 554.37 138.59 9.81 220.00 369.99 554.37 138.59 329.63 9.82 220.00 369.99 554.37 138.59 329.63 9.83 220.00 554.37 138.59 329.63 9.84 220.00 554.37 138.59 329.63 9.85 220.00 554.37 138.59 329.63 9.86 220.00 554.37 138.59 329.63 9.87 220.00 554.37 138.59 329.63 9.88 220.00 554.37 138.59 329.63 9.89 220.00 554.37 138.59 329.63 9.90 220.00 554.37 329.63 9.91 220.00 554.37 329.63 9.92 220.00 554.37 329.63 9.93 220.00 554.37 329.63 9.94 220.00 554.37 329.63 9.95 220.00 554.37 329.63 9.96 220.00 554.37 329.63 9.97 220.00 554.37 329.63 9.98 220.00 554.37 329.63 9.99 220.00 554.37 329.63 10.00 220.00 554.37 329.63 10.01 220.00 554.37 329.63 98.00 10.02 220.00 554.37 329.63 98.00 10.03 220.00 554.37 329.63 98.00 311.13 10.04 220.00 554.37 329.63 98.00 311.13 10.05 220.00 554.37 329.63 98.00 311.13 10.06 220.00 554.37 98.00 311.13 10.07 220.00 554.37 98.00 311.13 10.08 220.00 98.00 311.13 10.09 220.00 98.00 311.13 10.10 220.00 98.00 311.13 10.11 220.00 98.00 311.13 10.12 220.00 311.13 10.13 220.00 311.13 10.14 220.00 311.13 10.15 220.00 311.13 10.16 220.00 311.13 10.17 220.00 311.13 10.18 220.00 311.13 10.19 220.00 311.13 10.20 220.00 311.13 10.21 220.00 311.13 10.22 220.00 311.13 10.23 220.00 311.13 110.00 10.24 220.00 311.13 110.00 10.25 220.00 311.13 110.00 10.26 220.00 311.13 110.00 10.27 220.00 311.13 110.00 10.28 220.00 311.13 110.00 10.29 220.00 311.13 110.00 10.30 220.00 311.13 110.00 10.31 220.00 311.13 110.00 10.32 220.00 311.13 110.00 329.63 10.33 220.00 311.13 110.00 329.63 10.34 220.00 311.13 110.00 329.63 10.35 220.00 311.13 110.00 329.63 10.36 220.00 110.00 329.63 10.37 220.00 329.63 10.38 220.00 329.63 10.39 220.00 329.63 10.40 220.00 329.63 10.41 220.00 329.63 10.42 220.00 329.63 10.43 220.00 329.63 10.44 220.00 329.63 10.45 220.00 329.63 138.59 10.46 220.00 329.63 138.59 10.47 220.00 329.63 138.59 10.48 220.00 329.63 138.59 10.49 220.00 329.63 138.59 10.50 220.00 329.63 138.59 10.51 220.00 329.63 138.59 10.52 220.00 329.63 138.59 10.53 220.00 329.63 138.59 10.54 220.00 329.63 138.59 10.55 220.00 329.63 138.59 10.56 220.00 329.63 10.57 220.00 329.63 10.58 220.00 329.63 10.59 220.00 329.63 10.60 220.00 329.63 10.61 220.00 329.63 10.62 220.00 329.63 87.31 10.63 220.00 329.63 87.31 10.64 220.00 329.63 87.31 10.65 220.00 329.63 87.31 10.66 220.00 329.63 87.31 10.67 220.00 329.63 87.31 246.94 10.68 220.00 329.63 87.31 246.94 10.69 220.00 329.63 87.31 246.94 10.70 220.00 329.63 87.31 246.94 10.71 220.00 87.31 246.94 10.72 220.00 87.31 246.94 10.73 220.00 87.31 246.94 10.74 220.00 87.31 246.94 10.75 220.00 87.31 246.94 10.76 220.00 87.31 246.94 10.77 220.00 87.31 246.94 10.78 220.00 87.31 246.94 10.79 220.00 87.31 246.94 10.80 220.00 87.31 246.94 10.81 220.00 246.94 10.82 220.00 246.94 10.83 220.00 246.94 10.84 246.94 10.85 246.94 110.00 10.86 246.94 110.00 10.87 246.94 110.00 10.88 246.94 110.00 10.89 246.94 110.00 10.90 246.94 110.00 10.91 246.94 110.00 10.92 246.94 110.00 10.93 246.94 110.00 10.94 246.94 110.00 10.95 246.94 110.00 10.96 246.94 10.97 246.94 10.98 246.94 220.00 10.99 246.94 220.00 11.00 246.94 220.00 11.01 220.00 11.02 220.00 11.03 220.00 11.04 220.00 11.05 220.00 11.06 220.00 11.07 220.00 155.56 11.08 220.00 155.56 11.09 220.00 155.56 11.10 220.00 155.56 11.11 220.00 155.56 11.12 220.00 155.56 11.13 220.00 155.56 11.14 220.00 155.56 11.15 220.00 155.56 11.16 220.00 155.56 11.17 220.00 155.56 11.18 220.00 11.19 220.00 220.00 11.20 220.00 220.00 11.21 220.00 220.00 11.22 220.00 220.00 11.23 220.00 220.00 11.24 220.00 220.00 11.25 220.00 220.00 11.26 220.00 220.00 11.27 220.00 220.00 92.50 11.28 220.00 220.00 92.50 246.94 11.29 220.00 220.00 92.50 246.94 185.00 11.30 220.00 220.00 92.50 246.94 185.00 246.94 11.31 220.00 92.50 246.94 185.00 246.94 11.32 220.00 92.50 246.94 185.00 246.94 11.33 92.50 246.94 185.00 246.94 11.34 92.50 246.94 185.00 246.94 11.35 92.50 246.94 185.00 246.94 11.36 92.50 246.94 185.00 246.94 11.37 92.50 246.94 185.00 246.94 11.38 92.50 246.94 185.00 246.94 311.13 11.39 92.50 246.94 185.00 246.94 311.13 11.40 246.94 185.00 246.94 311.13 11.41 246.94 185.00 246.94 311.13 11.42 246.94 185.00 246.94 311.13 11.43 246.94 185.00 246.94 311.13 11.44 185.00 246.94 311.13 11.45 185.00 246.94 311.13 103.83 11.46 185.00 246.94 311.13 103.83 11.47 185.00 246.94 311.13 103.83 11.48 185.00 246.94 311.13 103.83 11.49 185.00 246.94 311.13 103.83 11.50 185.00 246.94 311.13 103.83 11.51 185.00 246.94 311.13 103.83 11.52 185.00 246.94 311.13 103.83 11.53 185.00 246.94 311.13 103.83 11.54 185.00 246.94 311.13 103.83 11.55 185.00 246.94 311.13 103.83 11.56 185.00 246.94 311.13 103.83 11.57 185.00 246.94 311.13 103.83 11.58 185.00 246.94 311.13 11.59 185.00 246.94 311.13 11.60 185.00 246.94 311.13 11.61 185.00 246.94 311.13 11.62 185.00 246.94 311.13 369.99 11.63 185.00 246.94 311.13 369.99 11.64 185.00 246.94 369.99 11.65 185.00 246.94 369.99 11.66 185.00 246.94 369.99 11.67 185.00 246.94 369.99 11.68 185.00 246.94 369.99 11.69 185.00 246.94 369.99 123.47 11.70 185.00 246.94 369.99 123.47 11.71 185.00 246.94 369.99 123.47 11.72 185.00 246.94 369.99 123.47 11.73 185.00 246.94 369.99 123.47 11.74 185.00 246.94 369.99 123.47 11.75 185.00 246.94 369.99 123.47 11.76 185.00 246.94 369.99 123.47 11.77 185.00 246.94 369.99 123.47 11.78 185.00 246.94 369.99 123.47 11.79 185.00 246.94 369.99 554.37 11.80 185.00 246.94 369.99 554.37 11.81 185.00 246.94 554.37 11.82 185.00 246.94 554.37 11.83 185.00 246.94 554.37 11.84 185.00 246.94 554.37 11.85 185.00 246.94 554.37 11.86 185.00 246.94 554.37 11.87 185.00 246.94 554.37 11.88 185.00 246.94 554.37 11.89 185.00 246.94 554.37 92.50 11.90 185.00 246.94 554.37 92.50 11.91 185.00 246.94 554.37 92.50 11.92 185.00 246.94 554.37 92.50 11.93 185.00 246.94 554.37 92.50 11.94 185.00 246.94 554.37 92.50 11.95 185.00 246.94 554.37 92.50 11.96 185.00 246.94 554.37 92.50 11.97 185.00 246.94 554.37 92.50 11.98 185.00 246.94 554.37 92.50 11.99 185.00 246.94 554.37 92.50 12.00 185.00 246.94 554.37 92.50 12.01 185.00 246.94 554.37 92.50 12.02 185.00 246.94 554.37 493.88 12.03 185.00 246.94 554.37 493.88 12.04 185.00 246.94 493.88 12.05 185.00 246.94 493.88 12.06 185.00 246.94 493.88 12.07 185.00 246.94 493.88 12.08 185.00 246.94 493.88 103.83 12.09 185.00 246.94 493.88 103.83 12.10 185.00 246.94 493.88 103.83 12.11 185.00 246.94 493.88 103.83 12.12 185.00 246.94 493.88 103.83 12.13 185.00 246.94 493.88 103.83 12.14 185.00 246.94 493.88 103.83 12.15 185.00 246.94 493.88 103.83 12.16 185.00 246.94 493.88 103.83 12.17 185.00 246.94 493.88 103.83 12.18 185.00 246.94 493.88 103.83 12.19 185.00 246.94 493.88 103.83 12.20 185.00 246.94 493.88 103.83 415.30 12.21 185.00 246.94 493.88 103.83 415.30 311.13 12.22 246.94 493.88 415.30 311.13 12.23 246.94 415.30 311.13 12.24 246.94 415.30 311.13 12.25 246.94 415.30 311.13 12.26 246.94 415.30 311.13 12.27 246.94 415.30 311.13 12.28 246.94 415.30 311.13 12.29 246.94 415.30 311.13 123.47 12.30 246.94 415.30 311.13 123.47 12.31 246.94 415.30 311.13 123.47 12.32 246.94 415.30 311.13 123.47 12.33 246.94 415.30 311.13 123.47 12.34 246.94 415.30 311.13 123.47 12.35 246.94 415.30 311.13 123.47 12.36 246.94 415.30 311.13 123.47 12.37 246.94 415.30 311.13 123.47 12.38 246.94 415.30 311.13 123.47 12.39 246.94 415.30 311.13 123.47 12.40 246.94 415.30 311.13 123.47 12.41 246.94 415.30 311.13 12.42 246.94 415.30 311.13 369.99 12.43 246.94 415.30 311.13 369.99 12.44 246.94 369.99 12.45 246.94 369.99 12.46 369.99 12.47 369.99 12.48 369.99 311.13 12.49 369.99 311.13 12.50 369.99 311.13 12.51 369.99 311.13 12.52 369.99 311.13 311.13 12.53 369.99 311.13 311.13 12.54 369.99 311.13 311.13 12.55 369.99 311.13 311.13 12.56 369.99 311.13 311.13 12.57 369.99 311.13 311.13 185.00 12.58 369.99 311.13 311.13 185.00 12.59 369.99 311.13 311.13 185.00 12.60 369.99 311.13 311.13 185.00 12.61 369.99 311.13 311.13 185.00 12.62 369.99 311.13 311.13 185.00 311.13 12.63 369.99 311.13 311.13 185.00 311.13 12.64 311.13 311.13 185.00 311.13 12.65 311.13 311.13 185.00 311.13 12.66 311.13 311.13 185.00 311.13 12.67 311.13 311.13 185.00 311.13 12.68 311.13 311.13 185.00 311.13 12.69 311.13 311.13 185.00 311.13 12.70 311.13 311.13 185.00 311.13 12.71 311.13 311.13 185.00 311.13 12.72 311.13 311.13 185.00 311.13 12.73 311.13 311.13 185.00 311.13 12.74 311.13 311.13 185.00 311.13 12.75 311.13 311.13 185.00 311.13 12.76 311.13 311.13 185.00 311.13 12.77 311.13 311.13 185.00 311.13 12.78 311.13 311.13 185.00 311.13 369.99 12.79 311.13 311.13 185.00 311.13 369.99 12.80 311.13 311.13 185.00 311.13 369.99 12.81 311.13 311.13 185.00 311.13 369.99 12.82 311.13 311.13 185.00 369.99 12.83 311.13 311.13 185.00 369.99 12.84 311.13 311.13 185.00 369.99 12.85 311.13 311.13 185.00 369.99 12.86 311.13 311.13 185.00 369.99 12.87 311.13 311.13 185.00 369.99 12.88 311.13 311.13 185.00 369.99 12.89 311.13 311.13 185.00 369.99 12.90 311.13 311.13 185.00 369.99 12.91 311.13 311.13 185.00 369.99 12.92 311.13 311.13 185.00 369.99 12.93 311.13 311.13 185.00 369.99 12.94 311.13 311.13 185.00 369.99 12.95 311.13 311.13 185.00 369.99 12.96 311.13 311.13 185.00 369.99 12.97 311.13 311.13 185.00 369.99 12.98 311.13 311.13 185.00 369.99 12.99 311.13 311.13 185.00 13.00 311.13 311.13 185.00 659.26 13.01 311.13 311.13 185.00 659.26 13.02 311.13 311.13 185.00 659.26 13.03 311.13 311.13 185.00 659.26 13.04 311.13 311.13 185.00 659.26 13.05 311.13 311.13 185.00 659.26 13.06 311.13 311.13 185.00 659.26 13.07 311.13 311.13 185.00 659.26 13.08 311.13 311.13 185.00 659.26 13.09 311.13 311.13 185.00 659.26 13.10 311.13 311.13 185.00 659.26 13.11 311.13 311.13 185.00 659.26 13.12 311.13 311.13 185.00 659.26 13.13 311.13 311.13 185.00 659.26 13.14 311.13 185.00 659.26 349.23 13.15 311.13 185.00 659.26 349.23 13.16 311.13 185.00 659.26 349.23 13.17 311.13 185.00 659.26 349.23 13.18 185.00 659.26 349.23 13.19 185.00 659.26 349.23 13.20 185.00 659.26 349.23 103.83 13.21 185.00 659.26 349.23 103.83 13.22 185.00 659.26 349.23 103.83 13.23 185.00 659.26 349.23 103.83 13.24 659.26 349.23 103.83 13.25 349.23 103.83 13.26 349.23 103.83 622.25 138.59 13.27 349.23 103.83 622.25 138.59 13.28 349.23 103.83 622.25 138.59 13.29 349.23 103.83 622.25 138.59 13.30 349.23 103.83 622.25 138.59 13.31 349.23 103.83 622.25 138.59 13.32 349.23 103.83 622.25 138.59 13.33 349.23 103.83 622.25 138.59 13.34 349.23 103.83 622.25 138.59 13.35 349.23 103.83 622.25 138.59 13.36 349.23 103.83 622.25 138.59 13.37 349.23 103.83 622.25 138.59 13.38 349.23 103.83 622.25 138.59 13.39 349.23 103.83 622.25 138.59 13.40 349.23 103.83 622.25 13.41 349.23 103.83 622.25 13.42 349.23 103.83 622.25 13.43 349.23 103.83 622.25 13.44 349.23 103.83 622.25 13.45 349.23 103.83 622.25 13.46 349.23 103.83 622.25 466.16 13.47 349.23 103.83 622.25 466.16 13.48 349.23 103.83 622.25 466.16 174.61 13.49 349.23 103.83 622.25 466.16 174.61 13.50 349.23 103.83 466.16 174.61 13.51 349.23 103.83 466.16 174.61 13.52 349.23 103.83 466.16 174.61 13.53 349.23 103.83 466.16 174.61 13.54 349.23 103.83 466.16 174.61 13.55 349.23 103.83 466.16 174.61 13.56 349.23 103.83 466.16 174.61 13.57 349.23 103.83 466.16 174.61 13.58 349.23 103.83 466.16 174.61 13.59 349.23 103.83 466.16 174.61 13.60 349.23 103.83 466.16 174.61 13.61 349.23 103.83 466.16 13.62 349.23 103.83 466.16 13.63 349.23 103.83 466.16 13.64 349.23 103.83 466.16 13.65 349.23 103.83 466.16 13.66 349.23 103.83 466.16 13.67 349.23 103.83 466.16 13.68 349.23 103.83 466.16 13.69 349.23 103.83 246.94 415.30 13.70 349.23 103.83 246.94 415.30 13.71 349.23 103.83 246.94 415.30 13.72 349.23 103.83 246.94 415.30 13.73 349.23 103.83 246.94 415.30 13.74 349.23 103.83 246.94 415.30 13.75 349.23 103.83 246.94 415.30 13.76 349.23 103.83 246.94 415.30 13.77 349.23 103.83 246.94 415.30 13.78 349.23 103.83 246.94 415.30 13.79 349.23 103.83 246.94 415.30 13.80 349.23 103.83 246.94 415.30 13.81 349.23 103.83 246.94 415.30 13.82 349.23 103.83 415.30 13.83 349.23 103.83 415.30 13.84 349.23 103.83 415.30 13.85 349.23 103.83 415.30 277.18 13.86 349.23 103.83 415.30 277.18 13.87 349.23 103.83 415.30 277.18 13.88 103.83 415.30 277.18 13.89 103.83 415.30 277.18 13.90 103.83 415.30 277.18 13.91 103.83 415.30 277.18 13.92 103.83 415.30 277.18 13.93 103.83 415.30 277.18 138.59 13.94 103.83 415.30 277.18 138.59 349.23 13.95 103.83 277.18 138.59 349.23 13.96 103.83 277.18 138.59 349.23 13.97 103.83 277.18 138.59 349.23 116.54 13.98 103.83 277.18 138.59 349.23 116.54 13.99 103.83 277.18 138.59 349.23 116.54 14.00 103.83 277.18 138.59 349.23 116.54 14.01 277.18 138.59 349.23 116.54 14.02 277.18 138.59 349.23 116.54 14.03 277.18 138.59 349.23 116.54 14.04 277.18 138.59 349.23 116.54 14.05 277.18 138.59 349.23 116.54 14.06 277.18 138.59 349.23 116.54 14.07 277.18 138.59 349.23 116.54 14.08 277.18 349.23 116.54 14.09 277.18 349.23 116.54 14.10 277.18 349.23 116.54 14.11 277.18 349.23 116.54 14.12 277.18 349.23 116.54 164.81 14.13 277.18 349.23 116.54 164.81 14.14 277.18 349.23 116.54 164.81 14.15 277.18 349.23 116.54 164.81 14.16 277.18 349.23 116.54 164.81 14.17 277.18 349.23 116.54 164.81 14.18 277.18 349.23 116.54 164.81 14.19 277.18 349.23 116.54 164.81 14.20 277.18 349.23 116.54 164.81 14.21 277.18 349.23 116.54 164.81 14.22 277.18 349.23 116.54 164.81 14.23 277.18 116.54 164.81 14.24 277.18 116.54 164.81 14.25 277.18 116.54 14.26 277.18 116.54 14.27 277.18 116.54 14.28 277.18 116.54 369.99 14.29 277.18 116.54 369.99 14.30 277.18 116.54 369.99 14.31 277.18 116.54 369.99 14.32 277.18 116.54 369.99 14.33 277.18 116.54 369.99 14.34 277.18 116.54 369.99 14.35 277.18 116.54 369.99 14.36 277.18 116.54 369.99 14.37 277.18 116.54 369.99 14.38 277.18 116.54 369.99 14.39 277.18 116.54 369.99 14.40 277.18 116.54 369.99 14.41 277.18 116.54 369.99 233.08 14.42 277.18 116.54 369.99 233.08 14.43 277.18 116.54 369.99 233.08 14.44 277.18 116.54 369.99 233.08 14.45 277.18 116.54 369.99 233.08 14.46 277.18 116.54 369.99 233.08 14.47 277.18 116.54 369.99 233.08 14.48 277.18 116.54 369.99 233.08 14.49 277.18 116.54 369.99 233.08 14.50 277.18 116.54 369.99 233.08 14.51 277.18 116.54 369.99 233.08 14.52 277.18 116.54 369.99 233.08 14.53 277.18 116.54 369.99 233.08 14.54 277.18 116.54 369.99 14.55 277.18 116.54 369.99 14.56 277.18 116.54 369.99 14.57 277.18 116.54 369.99 14.58 277.18 116.54 369.99 14.59 277.18 116.54 369.99 14.60 277.18 116.54 369.99 14.61 277.18 116.54 369.99 14.62 277.18 116.54 369.99 14.63 277.18 116.54 369.99 14.64 277.18 116.54 369.99 14.65 277.18 116.54 369.99 14.66 277.18 116.54 369.99 311.13 14.67 277.18 116.54 311.13 138.59 14.68 277.18 116.54 311.13 138.59 14.69 277.18 116.54 311.13 138.59 14.70 277.18 116.54 311.13 138.59 14.71 277.18 116.54 311.13 138.59 14.72 277.18 116.54 311.13 138.59 14.73 277.18 116.54 311.13 138.59 311.13 14.74 277.18 116.54 311.13 138.59 311.13 14.75 277.18 116.54 311.13 138.59 311.13 92.50 14.76 116.54 311.13 138.59 311.13 92.50 14.77 116.54 311.13 138.59 311.13 92.50 14.78 116.54 311.13 138.59 311.13 92.50 14.79 311.13 311.13 92.50 14.80 311.13 311.13 92.50 14.81 311.13 311.13 92.50 14.82 311.13 311.13 92.50 14.83 311.13 311.13 92.50 14.84 311.13 311.13 92.50 14.85 311.13 311.13 92.50 14.86 311.13 311.13 92.50 14.87 311.13 311.13 92.50 14.88 311.13 311.13 92.50 14.89 311.13 311.13 92.50 14.90 311.13 311.13 92.50 14.91 311.13 311.13 92.50 14.92 311.13 311.13 92.50 14.93 311.13 311.13 92.50 14.94 311.13 311.13 92.50 164.81 14.95 311.13 311.13 92.50 164.81 14.96 311.13 311.13 92.50 164.81 14.97 311.13 311.13 92.50 164.81 14.98 311.13 311.13 92.50 164.81 14.99 311.13 311.13 92.50 164.81 15.00 311.13 311.13 92.50 164.81 15.01 311.13 311.13 92.50 164.81 15.02 311.13 311.13 92.50 164.81 15.03 311.13 311.13 92.50 164.81 15.04 311.13 311.13 92.50 164.81 15.05 311.13 311.13 92.50 164.81 15.06 311.13 311.13 92.50 15.07 311.13 311.13 92.50 15.08 311.13 311.13 92.50 15.09 311.13 311.13 92.50 15.10 311.13 311.13 92.50 233.08 15.11 311.13 311.13 92.50 233.08 15.12 311.13 311.13 92.50 233.08 15.13 311.13 92.50 233.08 15.14 311.13 92.50 233.08 15.15 311.13 92.50 233.08 15.16 311.13 92.50 233.08 15.17 311.13 92.50 233.08 15.18 311.13 92.50 233.08 15.19 311.13 92.50 233.08 15.20 311.13 92.50 233.08 15.21 311.13 92.50 233.08 15.22 311.13 92.50 233.08 15.23 311.13 92.50 233.08 15.24 311.13 92.50 233.08 15.25 311.13 92.50 233.08 15.26 311.13 92.50 233.08 15.27 311.13 92.50 233.08 233.08 15.28 311.13 92.50 233.08 233.08 15.29 311.13 92.50 233.08 233.08 15.30 311.13 92.50 233.08 233.08 15.31 311.13 92.50 233.08 233.08 15.32 311.13 92.50 233.08 233.08 15.33 311.13 92.50 233.08 233.08 15.34 311.13 92.50 233.08 233.08 15.35 311.13 92.50 233.08 233.08 15.36 311.13 92.50 233.08 233.08 15.37 311.13 92.50 233.08 233.08 15.38 311.13 92.50 233.08 233.08 15.39 311.13 92.50 233.08 233.08mir_eval-0.8.2/tests/data/multipitch/ref07.txt000066400000000000000000001603601475740344600212640ustar00rootroot000000000000000.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.30 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.40 0.41 0.42 0.43 0.44 0.45 0.46 0.47 0.48 0.49 0.50 0.51 0.52 0.53 0.54 0.55 0.56 0.57 0.58 0.59 0.60 0.61 0.62 0.63 0.64 0.65 0.66 0.67 0.68 0.69 0.70 0.71 0.72 0.73 0.74 0.75 0.76 0.77 0.78 0.79 293.66 0.80 293.66 146.83 0.81 293.66 146.83 0.82 293.66 146.83 293.66 73.42 0.83 293.66 146.83 293.66 73.42 293.66 0.84 293.66 146.83 293.66 73.42 293.66 0.85 146.83 293.66 73.42 293.66 0.86 146.83 293.66 73.42 293.66 0.87 293.66 73.42 293.66 0.88 293.66 73.42 293.66 0.89 293.66 73.42 293.66 0.90 293.66 73.42 293.66 0.91 293.66 73.42 293.66 0.92 293.66 73.42 293.66 0.93 293.66 73.42 293.66 0.94 293.66 73.42 293.66 0.95 293.66 73.42 293.66 0.96 293.66 73.42 293.66 0.97 293.66 73.42 293.66 0.98 293.66 73.42 293.66 0.99 293.66 73.42 293.66 1.00 293.66 73.42 293.66 1.01 293.66 73.42 293.66 1.02 293.66 73.42 293.66 1.03 293.66 73.42 293.66 1.04 293.66 73.42 293.66 1.05 293.66 73.42 293.66 1.06 293.66 73.42 293.66 1.07 293.66 73.42 293.66 1.08 293.66 73.42 293.66 1.09 293.66 73.42 293.66 1.10 293.66 73.42 293.66 1.11 293.66 73.42 293.66 1.12 293.66 73.42 293.66 1.13 293.66 73.42 293.66 1.14 293.66 73.42 293.66 1.15 293.66 73.42 293.66 293.66 1.16 293.66 73.42 293.66 293.66 1.17 293.66 73.42 293.66 293.66 1.18 293.66 73.42 293.66 293.66 1.19 293.66 73.42 293.66 293.66 1.20 293.66 73.42 293.66 293.66 1.21 293.66 73.42 293.66 1.22 293.66 73.42 293.66 1.23 293.66 73.42 293.66 1.24 293.66 73.42 293.66 1.25 293.66 73.42 293.66 1.26 293.66 73.42 293.66 1.27 293.66 73.42 293.66 261.63 1.28 293.66 73.42 293.66 261.63 1.29 293.66 73.42 293.66 261.63 1.30 293.66 73.42 293.66 261.63 1.31 293.66 73.42 293.66 261.63 1.32 293.66 293.66 261.63 1.33 293.66 293.66 261.63 1.34 293.66 293.66 261.63 1.35 293.66 293.66 261.63 1.36 293.66 293.66 261.63 1.37 293.66 293.66 261.63 1.38 293.66 293.66 261.63 1.39 293.66 293.66 1.40 293.66 293.66 233.08 1.41 293.66 293.66 233.08 1.42 293.66 293.66 233.08 1.43 293.66 293.66 233.08 1.44 293.66 293.66 233.08 1.45 293.66 293.66 233.08 1.46 293.66 233.08 1.47 293.66 1.48 293.66 1.49 293.66 1.50 293.66 1.51 293.66 1.52 293.66 1.53 293.66 329.63 220.00 1.54 293.66 329.63 220.00 1.55 293.66 329.63 220.00 1.56 293.66 329.63 220.00 110.00 1.57 293.66 329.63 220.00 110.00 1.58 293.66 329.63 220.00 110.00 1.59 293.66 329.63 220.00 110.00 1.60 293.66 329.63 220.00 110.00 1.61 293.66 329.63 220.00 110.00 1.62 293.66 329.63 220.00 110.00 1.63 293.66 329.63 220.00 110.00 1.64 293.66 329.63 220.00 110.00 1.65 293.66 329.63 220.00 110.00 1.66 293.66 329.63 220.00 110.00 1.67 293.66 329.63 220.00 110.00 1.68 293.66 329.63 220.00 110.00 1.69 293.66 329.63 220.00 110.00 1.70 293.66 329.63 220.00 110.00 1.71 293.66 329.63 220.00 110.00 1.72 293.66 329.63 220.00 110.00 1.73 293.66 329.63 220.00 110.00 1.74 293.66 329.63 220.00 110.00 1.75 293.66 329.63 220.00 110.00 1.76 293.66 329.63 220.00 110.00 1.77 293.66 329.63 220.00 110.00 1.78 293.66 329.63 220.00 110.00 1.79 293.66 329.63 220.00 110.00 1.80 293.66 329.63 220.00 110.00 1.81 293.66 329.63 220.00 110.00 1.82 293.66 329.63 220.00 1.83 293.66 329.63 220.00 1.84 293.66 329.63 220.00 1.85 293.66 329.63 220.00 1.86 293.66 329.63 220.00 1.87 293.66 329.63 220.00 1.88 293.66 329.63 220.00 1.89 293.66 329.63 220.00 1.90 293.66 329.63 220.00 98.00 1.91 293.66 329.63 220.00 98.00 1.92 293.66 329.63 220.00 98.00 1.93 293.66 329.63 220.00 98.00 1.94 329.63 220.00 98.00 277.18 1.95 329.63 220.00 98.00 277.18 1.96 329.63 220.00 98.00 277.18 1.97 329.63 220.00 277.18 1.98 329.63 220.00 277.18 1.99 329.63 220.00 277.18 2.00 329.63 220.00 277.18 2.01 329.63 220.00 277.18 2.02 329.63 277.18 2.03 329.63 277.18 2.04 329.63 277.18 87.31 2.05 329.63 277.18 87.31 2.06 329.63 277.18 87.31 2.07 329.63 277.18 87.31 2.08 329.63 277.18 87.31 2.09 329.63 277.18 87.31 2.10 329.63 277.18 87.31 2.11 329.63 277.18 2.12 329.63 277.18 2.13 329.63 277.18 2.14 329.63 277.18 2.15 329.63 277.18 2.16 329.63 277.18 82.41 2.17 329.63 277.18 82.41 2.18 329.63 277.18 82.41 2.19 329.63 277.18 82.41 2.20 329.63 277.18 82.41 2.21 277.18 82.41 2.22 277.18 82.41 2.23 277.18 2.24 277.18 2.25 277.18 2.26 2.27 2.28 349.23 2.29 349.23 2.30 349.23 73.42 2.31 349.23 73.42 2.32 349.23 73.42 2.33 349.23 73.42 293.66 220.00 2.34 349.23 73.42 293.66 220.00 2.35 349.23 73.42 293.66 220.00 2.36 73.42 293.66 220.00 2.37 73.42 293.66 220.00 2.38 73.42 293.66 220.00 2.39 73.42 293.66 2.40 73.42 293.66 2.41 73.42 293.66 2.42 73.42 293.66 2.43 73.42 293.66 2.44 73.42 293.66 2.45 73.42 293.66 2.46 73.42 293.66 2.47 73.42 293.66 2.48 73.42 293.66 2.49 73.42 293.66 2.50 73.42 293.66 2.51 73.42 293.66 2.52 73.42 293.66 2.53 73.42 293.66 2.54 73.42 293.66 2.55 73.42 293.66 2.56 73.42 293.66 2.57 73.42 293.66 2.58 73.42 293.66 2.59 73.42 293.66 2.60 73.42 293.66 2.61 73.42 293.66 2.62 73.42 293.66 2.63 73.42 293.66 2.64 73.42 293.66 2.65 73.42 293.66 2.66 73.42 293.66 2.67 73.42 293.66 2.68 73.42 293.66 293.66 293.66 2.69 73.42 293.66 293.66 293.66 2.70 73.42 293.66 293.66 293.66 2.71 73.42 293.66 293.66 293.66 2.72 73.42 293.66 293.66 293.66 2.73 73.42 293.66 293.66 293.66 2.74 73.42 293.66 293.66 293.66 2.75 293.66 293.66 2.76 293.66 2.77 293.66 2.78 293.66 2.79 293.66 2.80 293.66 261.63 2.81 293.66 261.63 2.82 293.66 261.63 2.83 293.66 261.63 2.84 293.66 261.63 2.85 293.66 261.63 2.86 293.66 261.63 2.87 293.66 261.63 2.88 293.66 261.63 2.89 293.66 2.90 293.66 2.91 293.66 2.92 293.66 233.08 2.93 293.66 233.08 2.94 293.66 233.08 2.95 293.66 233.08 2.96 293.66 233.08 2.97 293.66 233.08 2.98 293.66 233.08 2.99 293.66 3.00 293.66 3.01 293.66 3.02 293.66 3.03 293.66 3.04 293.66 110.00 220.00 3.05 293.66 110.00 220.00 3.06 293.66 110.00 220.00 3.07 293.66 110.00 220.00 3.08 293.66 110.00 220.00 3.09 293.66 110.00 220.00 3.10 293.66 110.00 220.00 329.63 3.11 293.66 110.00 220.00 329.63 3.12 293.66 110.00 220.00 329.63 3.13 293.66 110.00 220.00 329.63 3.14 293.66 110.00 220.00 329.63 3.15 293.66 110.00 220.00 329.63 3.16 293.66 110.00 220.00 329.63 3.17 293.66 110.00 220.00 329.63 3.18 293.66 110.00 220.00 329.63 3.19 293.66 110.00 220.00 329.63 3.20 293.66 110.00 220.00 329.63 3.21 293.66 110.00 220.00 329.63 3.22 293.66 110.00 220.00 329.63 3.23 293.66 110.00 220.00 329.63 3.24 293.66 110.00 220.00 329.63 3.25 293.66 110.00 220.00 329.63 3.26 293.66 110.00 220.00 329.63 3.27 293.66 110.00 220.00 329.63 3.28 293.66 110.00 220.00 329.63 3.29 293.66 110.00 220.00 329.63 3.30 293.66 110.00 220.00 329.63 3.31 293.66 110.00 220.00 329.63 3.32 293.66 110.00 220.00 329.63 3.33 293.66 110.00 220.00 329.63 3.34 293.66 110.00 220.00 329.63 3.35 293.66 110.00 220.00 329.63 3.36 293.66 110.00 220.00 329.63 3.37 293.66 220.00 329.63 3.38 293.66 220.00 329.63 3.39 293.66 220.00 329.63 3.40 293.66 220.00 329.63 3.41 293.66 220.00 329.63 3.42 293.66 220.00 329.63 3.43 293.66 220.00 329.63 3.44 293.66 220.00 329.63 3.45 293.66 220.00 329.63 3.46 293.66 220.00 329.63 98.00 3.47 293.66 220.00 329.63 98.00 277.18 3.48 220.00 329.63 98.00 277.18 3.49 220.00 329.63 98.00 277.18 3.50 220.00 329.63 98.00 277.18 3.51 220.00 329.63 98.00 277.18 3.52 220.00 329.63 277.18 3.53 220.00 329.63 277.18 3.54 220.00 329.63 277.18 3.55 220.00 329.63 277.18 3.56 220.00 329.63 277.18 3.57 220.00 329.63 277.18 3.58 220.00 329.63 277.18 3.59 220.00 329.63 277.18 3.60 329.63 277.18 3.61 329.63 277.18 87.31 3.62 329.63 277.18 87.31 3.63 329.63 277.18 87.31 3.64 329.63 277.18 87.31 3.65 329.63 277.18 87.31 3.66 329.63 277.18 87.31 3.67 329.63 277.18 3.68 329.63 277.18 3.69 329.63 277.18 3.70 329.63 277.18 3.71 329.63 277.18 82.41 3.72 329.63 277.18 82.41 3.73 329.63 277.18 82.41 3.74 329.63 277.18 82.41 3.75 277.18 82.41 3.76 277.18 82.41 3.77 277.18 3.78 3.79 3.80 3.81 3.82 3.83 3.84 3.85 73.42 3.86 73.42 261.63 3.87 73.42 261.63 369.99 3.88 73.42 261.63 369.99 3.89 73.42 261.63 369.99 3.90 73.42 261.63 369.99 3.91 73.42 261.63 369.99 220.00 3.92 73.42 261.63 369.99 220.00 3.93 73.42 261.63 369.99 220.00 3.94 73.42 261.63 369.99 220.00 3.95 73.42 261.63 369.99 220.00 3.96 73.42 261.63 369.99 220.00 3.97 73.42 261.63 369.99 220.00 3.98 73.42 261.63 369.99 220.00 3.99 73.42 261.63 369.99 220.00 4.00 73.42 261.63 369.99 220.00 4.01 73.42 261.63 369.99 220.00 4.02 73.42 261.63 369.99 220.00 4.03 73.42 261.63 369.99 220.00 4.04 73.42 261.63 369.99 220.00 4.05 73.42 261.63 369.99 220.00 4.06 73.42 261.63 369.99 220.00 4.07 73.42 261.63 369.99 220.00 4.08 73.42 261.63 369.99 220.00 4.09 73.42 261.63 369.99 220.00 4.10 73.42 261.63 369.99 220.00 4.11 73.42 261.63 369.99 220.00 4.12 73.42 261.63 369.99 220.00 4.13 73.42 261.63 369.99 220.00 4.14 73.42 261.63 369.99 220.00 4.15 73.42 369.99 220.00 4.16 73.42 369.99 220.00 4.17 73.42 369.99 220.00 4.18 73.42 369.99 220.00 4.19 73.42 369.99 220.00 4.20 73.42 369.99 220.00 4.21 73.42 369.99 220.00 4.22 73.42 369.99 220.00 246.94 4.23 73.42 369.99 220.00 246.94 4.24 73.42 369.99 220.00 246.94 4.25 73.42 369.99 220.00 246.94 4.26 73.42 369.99 220.00 246.94 4.27 73.42 369.99 220.00 246.94 4.28 73.42 369.99 220.00 246.94 4.29 73.42 369.99 220.00 246.94 4.30 73.42 369.99 220.00 4.31 73.42 369.99 220.00 4.32 73.42 369.99 220.00 4.33 73.42 369.99 220.00 4.34 73.42 369.99 220.00 4.35 73.42 369.99 220.00 4.36 73.42 369.99 220.00 261.63 4.37 73.42 369.99 220.00 261.63 4.38 73.42 369.99 220.00 261.63 4.39 73.42 369.99 220.00 261.63 4.40 73.42 369.99 220.00 261.63 4.41 73.42 369.99 220.00 261.63 4.42 73.42 369.99 220.00 261.63 4.43 73.42 369.99 220.00 261.63 4.44 73.42 369.99 220.00 261.63 4.45 73.42 369.99 220.00 261.63 4.46 73.42 369.99 220.00 261.63 4.47 73.42 369.99 220.00 4.48 73.42 369.99 220.00 4.49 73.42 369.99 220.00 293.66 4.50 73.42 369.99 220.00 293.66 4.51 73.42 369.99 220.00 293.66 4.52 73.42 369.99 220.00 293.66 4.53 73.42 369.99 220.00 293.66 4.54 73.42 369.99 220.00 293.66 4.55 369.99 220.00 293.66 4.56 369.99 220.00 4.57 369.99 220.00 4.58 4.59 4.60 4.61 4.62 311.13 4.63 311.13 233.08 4.64 311.13 233.08 392.00 4.65 311.13 233.08 392.00 4.66 311.13 233.08 392.00 4.67 311.13 233.08 392.00 4.68 311.13 233.08 392.00 4.69 311.13 233.08 392.00 4.70 311.13 233.08 392.00 4.71 311.13 233.08 392.00 4.72 311.13 233.08 392.00 4.73 311.13 233.08 392.00 4.74 311.13 233.08 392.00 4.75 311.13 233.08 392.00 4.76 311.13 233.08 392.00 4.77 311.13 233.08 392.00 4.78 311.13 233.08 392.00 4.79 311.13 233.08 392.00 4.80 311.13 233.08 392.00 4.81 311.13 233.08 392.00 4.82 311.13 233.08 392.00 4.83 311.13 233.08 392.00 4.84 311.13 233.08 392.00 4.85 311.13 233.08 392.00 4.86 311.13 233.08 392.00 4.87 311.13 233.08 392.00 4.88 311.13 233.08 392.00 4.89 311.13 233.08 392.00 4.90 311.13 233.08 392.00 4.91 311.13 233.08 392.00 4.92 311.13 233.08 392.00 4.93 311.13 233.08 392.00 4.94 311.13 233.08 392.00 4.95 311.13 233.08 392.00 4.96 311.13 233.08 392.00 98.00 4.97 311.13 233.08 392.00 98.00 4.98 311.13 233.08 392.00 98.00 4.99 311.13 233.08 392.00 98.00 5.00 311.13 233.08 392.00 98.00 5.01 311.13 233.08 392.00 98.00 5.02 311.13 233.08 392.00 98.00 5.03 311.13 233.08 392.00 98.00 5.04 311.13 233.08 392.00 98.00 5.05 311.13 233.08 392.00 98.00 5.06 311.13 233.08 392.00 98.00 5.07 311.13 233.08 392.00 5.08 311.13 233.08 392.00 5.09 311.13 233.08 392.00 5.10 311.13 233.08 392.00 5.11 311.13 233.08 392.00 5.12 311.13 233.08 392.00 5.13 311.13 233.08 392.00 110.00 5.14 311.13 233.08 392.00 110.00 5.15 311.13 233.08 392.00 110.00 5.16 311.13 233.08 392.00 110.00 5.17 311.13 233.08 392.00 110.00 5.18 311.13 233.08 392.00 110.00 5.19 311.13 233.08 392.00 110.00 5.20 311.13 233.08 392.00 5.21 311.13 233.08 392.00 5.22 311.13 233.08 392.00 5.23 311.13 233.08 392.00 5.24 311.13 233.08 392.00 5.25 233.08 392.00 5.26 233.08 392.00 116.54 5.27 233.08 392.00 116.54 5.28 233.08 392.00 116.54 5.29 233.08 392.00 116.54 5.30 233.08 392.00 116.54 5.31 233.08 392.00 116.54 5.32 233.08 116.54 5.33 233.08 116.54 5.34 116.54 5.35 116.54 5.36 5.37 5.38 5.39 5.40 82.41 5.41 82.41 246.94 5.42 82.41 246.94 5.43 82.41 246.94 415.30 5.44 82.41 246.94 415.30 293.66 5.45 82.41 246.94 415.30 293.66 5.46 82.41 246.94 415.30 293.66 5.47 82.41 246.94 415.30 293.66 5.48 82.41 246.94 415.30 293.66 5.49 82.41 246.94 415.30 293.66 5.50 82.41 246.94 415.30 293.66 5.51 82.41 246.94 415.30 293.66 5.52 82.41 246.94 415.30 293.66 5.53 82.41 246.94 415.30 293.66 5.54 82.41 246.94 415.30 293.66 5.55 82.41 246.94 415.30 293.66 5.56 82.41 246.94 415.30 293.66 5.57 82.41 246.94 415.30 293.66 5.58 82.41 246.94 415.30 293.66 5.59 82.41 246.94 415.30 293.66 5.60 82.41 246.94 415.30 293.66 5.61 82.41 246.94 415.30 293.66 5.62 82.41 246.94 415.30 293.66 5.63 82.41 246.94 415.30 293.66 5.64 82.41 246.94 415.30 293.66 5.65 82.41 246.94 415.30 293.66 5.66 82.41 246.94 415.30 293.66 5.67 82.41 246.94 415.30 293.66 5.68 82.41 246.94 415.30 293.66 5.69 82.41 246.94 415.30 293.66 5.70 82.41 246.94 293.66 5.71 82.41 246.94 293.66 5.72 82.41 246.94 293.66 5.73 82.41 246.94 293.66 5.74 82.41 246.94 293.66 5.75 82.41 246.94 293.66 329.63 5.76 82.41 246.94 293.66 329.63 5.77 82.41 246.94 293.66 329.63 5.78 82.41 246.94 293.66 329.63 5.79 82.41 246.94 293.66 329.63 5.80 82.41 246.94 293.66 329.63 5.81 82.41 246.94 293.66 329.63 5.82 82.41 246.94 293.66 329.63 5.83 82.41 246.94 293.66 329.63 5.84 82.41 246.94 293.66 5.85 82.41 246.94 293.66 5.86 82.41 246.94 293.66 5.87 82.41 246.94 293.66 5.88 82.41 246.94 293.66 5.89 82.41 246.94 293.66 5.90 82.41 246.94 293.66 5.91 82.41 246.94 293.66 369.99 5.92 82.41 246.94 293.66 369.99 5.93 82.41 246.94 293.66 369.99 5.94 82.41 246.94 293.66 369.99 5.95 82.41 246.94 293.66 369.99 5.96 82.41 246.94 293.66 369.99 5.97 82.41 246.94 293.66 369.99 5.98 82.41 246.94 293.66 5.99 82.41 246.94 293.66 6.00 82.41 246.94 293.66 6.01 82.41 246.94 293.66 6.02 82.41 246.94 293.66 6.03 82.41 246.94 293.66 6.04 82.41 246.94 293.66 6.05 82.41 246.94 293.66 415.30 6.06 82.41 293.66 415.30 6.07 82.41 293.66 415.30 6.08 82.41 293.66 415.30 6.09 82.41 415.30 6.10 82.41 6.11 6.12 6.13 6.14 6.15 6.16 6.17 261.63 6.18 261.63 440.00 349.23 220.00 6.19 261.63 440.00 349.23 220.00 349.23 6.20 261.63 440.00 349.23 220.00 349.23 6.21 261.63 440.00 349.23 220.00 349.23 6.22 261.63 440.00 349.23 220.00 349.23 6.23 261.63 440.00 349.23 220.00 349.23 6.24 261.63 440.00 349.23 220.00 349.23 6.25 261.63 440.00 349.23 220.00 349.23 6.26 261.63 440.00 349.23 220.00 349.23 6.27 261.63 440.00 349.23 220.00 349.23 6.28 261.63 440.00 349.23 220.00 349.23 6.29 261.63 440.00 349.23 220.00 349.23 6.30 261.63 440.00 349.23 220.00 349.23 6.31 261.63 440.00 349.23 220.00 349.23 6.32 261.63 440.00 349.23 220.00 349.23 6.33 261.63 440.00 349.23 220.00 349.23 6.34 261.63 440.00 349.23 220.00 349.23 6.35 261.63 440.00 349.23 220.00 349.23 6.36 261.63 440.00 349.23 220.00 349.23 6.37 261.63 440.00 349.23 220.00 349.23 6.38 261.63 440.00 349.23 220.00 349.23 6.39 261.63 440.00 349.23 220.00 349.23 6.40 261.63 440.00 349.23 220.00 349.23 6.41 261.63 440.00 349.23 220.00 349.23 6.42 261.63 440.00 349.23 220.00 349.23 6.43 261.63 440.00 349.23 220.00 349.23 6.44 261.63 440.00 349.23 220.00 349.23 6.45 261.63 440.00 349.23 220.00 349.23 6.46 261.63 440.00 349.23 220.00 349.23 6.47 261.63 440.00 349.23 220.00 349.23 6.48 261.63 440.00 349.23 220.00 349.23 6.49 261.63 440.00 349.23 220.00 349.23 6.50 261.63 440.00 349.23 220.00 349.23 6.51 261.63 440.00 349.23 220.00 349.23 6.52 261.63 440.00 349.23 220.00 349.23 6.53 261.63 440.00 349.23 220.00 349.23 6.54 261.63 440.00 349.23 220.00 349.23 6.55 261.63 440.00 349.23 220.00 349.23 6.56 261.63 440.00 349.23 220.00 349.23 6.57 261.63 440.00 349.23 220.00 349.23 110.00 6.58 261.63 440.00 349.23 220.00 110.00 6.59 261.63 440.00 349.23 220.00 110.00 6.60 261.63 440.00 349.23 220.00 110.00 6.61 261.63 440.00 349.23 110.00 6.62 261.63 440.00 349.23 110.00 6.63 261.63 440.00 349.23 110.00 6.64 261.63 440.00 349.23 6.65 261.63 440.00 349.23 6.66 261.63 440.00 349.23 6.67 261.63 440.00 349.23 6.68 261.63 440.00 349.23 6.69 261.63 440.00 349.23 6.70 261.63 440.00 349.23 123.47 6.71 261.63 440.00 349.23 123.47 6.72 261.63 440.00 349.23 123.47 6.73 261.63 440.00 349.23 123.47 6.74 440.00 349.23 123.47 6.75 349.23 123.47 6.76 349.23 123.47 6.77 349.23 123.47 6.78 349.23 123.47 6.79 349.23 6.80 349.23 6.81 349.23 6.82 349.23 6.83 349.23 130.81 6.84 349.23 130.81 6.85 130.81 6.86 130.81 6.87 130.81 6.88 130.81 6.89 130.81 6.90 6.91 6.92 6.93 6.94 6.95 6.96 6.97 440.00 196.00 6.98 440.00 196.00 110.00 6.99 440.00 196.00 110.00 7.00 440.00 196.00 110.00 7.01 440.00 196.00 110.00 277.18 7.02 440.00 196.00 110.00 277.18 7.03 440.00 196.00 110.00 277.18 7.04 440.00 196.00 110.00 277.18 7.05 440.00 196.00 110.00 277.18 7.06 440.00 196.00 110.00 277.18 7.07 440.00 196.00 110.00 277.18 7.08 440.00 196.00 110.00 7.09 440.00 196.00 110.00 7.10 440.00 196.00 110.00 7.11 440.00 196.00 110.00 7.12 440.00 196.00 110.00 7.13 440.00 196.00 110.00 246.94 7.14 440.00 196.00 110.00 246.94 7.15 440.00 196.00 110.00 246.94 7.16 440.00 196.00 110.00 246.94 7.17 440.00 196.00 110.00 246.94 7.18 440.00 196.00 110.00 246.94 7.19 440.00 196.00 110.00 246.94 7.20 440.00 196.00 110.00 7.21 440.00 110.00 7.22 440.00 110.00 7.23 440.00 110.00 7.24 440.00 110.00 7.25 110.00 220.00 7.26 110.00 220.00 7.27 220.00 7.28 220.00 7.29 220.00 7.30 220.00 7.31 220.00 7.32 220.00 7.33 7.34 7.35 440.00 7.36 440.00 174.61 7.37 440.00 174.61 7.38 440.00 174.61 293.66 110.00 7.39 440.00 174.61 293.66 110.00 7.40 440.00 174.61 293.66 110.00 7.41 440.00 174.61 293.66 110.00 7.42 440.00 174.61 293.66 110.00 7.43 440.00 293.66 110.00 7.44 440.00 293.66 110.00 7.45 440.00 293.66 110.00 7.46 440.00 293.66 110.00 7.47 440.00 293.66 110.00 7.48 440.00 293.66 110.00 7.49 440.00 293.66 110.00 7.50 440.00 293.66 110.00 7.51 440.00 293.66 110.00 7.52 440.00 293.66 110.00 164.81 7.53 440.00 293.66 110.00 164.81 7.54 440.00 293.66 110.00 164.81 7.55 440.00 293.66 110.00 164.81 7.56 440.00 293.66 110.00 164.81 7.57 440.00 293.66 110.00 164.81 7.58 440.00 293.66 110.00 164.81 7.59 440.00 293.66 110.00 164.81 7.60 440.00 293.66 110.00 164.81 7.61 440.00 293.66 110.00 164.81 146.83 7.62 440.00 293.66 110.00 164.81 146.83 7.63 440.00 110.00 164.81 146.83 7.64 440.00 164.81 146.83 7.65 440.00 146.83 7.66 440.00 146.83 7.67 146.83 7.68 146.83 7.69 146.83 7.70 7.71 7.72 7.73 7.74 7.75 440.00 7.76 440.00 164.81 7.77 440.00 164.81 110.00 7.78 440.00 164.81 110.00 293.66 7.79 440.00 164.81 110.00 293.66 7.80 440.00 164.81 110.00 293.66 7.81 440.00 164.81 110.00 293.66 7.82 440.00 164.81 110.00 293.66 7.83 440.00 164.81 110.00 293.66 7.84 440.00 164.81 110.00 293.66 7.85 440.00 164.81 110.00 293.66 7.86 440.00 110.00 293.66 7.87 440.00 110.00 293.66 7.88 440.00 110.00 293.66 7.89 440.00 110.00 293.66 7.90 440.00 110.00 293.66 7.91 440.00 110.00 293.66 7.92 440.00 110.00 293.66 7.93 440.00 110.00 293.66 7.94 440.00 110.00 293.66 7.95 440.00 110.00 293.66 7.96 440.00 110.00 293.66 7.97 440.00 110.00 293.66 7.98 440.00 110.00 293.66 7.99 440.00 110.00 293.66 8.00 440.00 110.00 293.66 8.01 440.00 110.00 293.66 8.02 293.66 8.03 293.66 8.04 293.66 8.05 293.66 8.06 293.66 8.07 293.66 8.08 8.09 8.10 8.11 8.12 8.13 164.81 277.18 8.14 164.81 277.18 8.15 164.81 277.18 8.16 164.81 277.18 440.00 8.17 164.81 277.18 440.00 8.18 164.81 277.18 440.00 110.00 8.19 164.81 277.18 440.00 110.00 8.20 164.81 277.18 440.00 110.00 8.21 164.81 277.18 440.00 110.00 8.22 277.18 440.00 110.00 8.23 277.18 440.00 110.00 8.24 277.18 440.00 110.00 8.25 277.18 440.00 110.00 8.26 277.18 440.00 110.00 8.27 277.18 440.00 110.00 8.28 277.18 440.00 110.00 8.29 277.18 440.00 110.00 8.30 277.18 440.00 110.00 8.31 277.18 440.00 110.00 8.32 440.00 110.00 8.33 440.00 110.00 8.34 440.00 110.00 8.35 440.00 110.00 8.36 440.00 110.00 8.37 440.00 110.00 8.38 440.00 110.00 8.39 440.00 110.00 8.40 440.00 8.41 440.00 8.42 440.00 8.43 440.00 8.44 440.00 8.45 440.00 8.46 440.00 8.47 8.48 8.49 8.50 8.51 8.52 8.53 8.54 293.66 8.55 293.66 146.83 146.83 8.56 293.66 146.83 146.83 8.57 293.66 146.83 146.83 8.58 293.66 146.83 146.83 8.59 293.66 146.83 146.83 8.60 293.66 146.83 146.83 8.61 293.66 146.83 146.83 587.33 8.62 293.66 146.83 146.83 587.33 8.63 293.66 146.83 146.83 587.33 8.64 293.66 146.83 146.83 587.33 293.66 587.33 8.65 293.66 146.83 146.83 587.33 293.66 587.33 8.66 293.66 146.83 146.83 587.33 293.66 587.33 8.67 293.66 146.83 146.83 587.33 293.66 587.33 8.68 293.66 146.83 146.83 587.33 293.66 587.33 8.69 293.66 146.83 146.83 587.33 293.66 587.33 8.70 293.66 146.83 146.83 587.33 293.66 587.33 8.71 293.66 146.83 146.83 587.33 293.66 587.33 8.72 293.66 146.83 146.83 587.33 293.66 587.33 8.73 293.66 146.83 146.83 587.33 293.66 587.33 8.74 293.66 146.83 146.83 587.33 293.66 587.33 8.75 293.66 146.83 146.83 587.33 293.66 587.33 8.76 293.66 146.83 146.83 587.33 293.66 587.33 8.77 293.66 146.83 146.83 587.33 293.66 587.33 8.78 293.66 146.83 146.83 587.33 293.66 587.33 8.79 293.66 146.83 146.83 587.33 293.66 587.33 8.80 293.66 146.83 146.83 587.33 293.66 587.33 8.81 293.66 146.83 146.83 587.33 293.66 587.33 8.82 293.66 146.83 146.83 587.33 293.66 587.33 8.83 293.66 146.83 146.83 587.33 293.66 587.33 8.84 293.66 146.83 146.83 587.33 293.66 587.33 8.85 293.66 146.83 146.83 587.33 293.66 587.33 8.86 293.66 146.83 146.83 587.33 293.66 587.33 8.87 293.66 146.83 146.83 587.33 293.66 587.33 8.88 293.66 146.83 146.83 587.33 293.66 587.33 8.89 293.66 146.83 146.83 587.33 293.66 587.33 8.90 293.66 146.83 146.83 587.33 293.66 587.33 8.91 293.66 146.83 146.83 587.33 293.66 587.33 8.92 146.83 146.83 587.33 293.66 587.33 8.93 146.83 587.33 293.66 587.33 8.94 146.83 587.33 293.66 587.33 8.95 146.83 587.33 293.66 587.33 8.96 146.83 587.33 293.66 587.33 8.97 146.83 587.33 293.66 587.33 8.98 146.83 587.33 293.66 587.33 8.99 146.83 587.33 293.66 587.33 9.00 146.83 587.33 293.66 587.33 9.01 146.83 587.33 293.66 587.33 9.02 146.83 587.33 293.66 587.33 587.33 9.03 146.83 587.33 293.66 587.33 587.33 9.04 146.83 587.33 293.66 587.33 587.33 9.05 146.83 587.33 293.66 587.33 587.33 9.06 146.83 587.33 293.66 587.33 587.33 9.07 146.83 587.33 293.66 587.33 587.33 9.08 146.83 587.33 293.66 587.33 587.33 9.09 146.83 587.33 293.66 587.33 9.10 146.83 587.33 293.66 587.33 9.11 587.33 293.66 587.33 9.12 587.33 293.66 587.33 9.13 587.33 293.66 587.33 9.14 587.33 293.66 587.33 9.15 587.33 293.66 587.33 9.16 587.33 293.66 587.33 9.17 587.33 293.66 587.33 523.25 9.18 587.33 293.66 587.33 523.25 9.19 587.33 293.66 587.33 523.25 9.20 587.33 293.66 587.33 523.25 9.21 587.33 293.66 587.33 523.25 9.22 587.33 293.66 587.33 523.25 9.23 587.33 293.66 587.33 523.25 9.24 587.33 293.66 587.33 9.25 587.33 293.66 587.33 9.26 587.33 293.66 587.33 9.27 587.33 293.66 587.33 9.28 587.33 293.66 587.33 9.29 587.33 293.66 587.33 9.30 587.33 293.66 587.33 466.16 9.31 587.33 293.66 587.33 466.16 9.32 293.66 587.33 466.16 9.33 293.66 587.33 466.16 9.34 293.66 587.33 466.16 9.35 293.66 587.33 466.16 9.36 293.66 587.33 9.37 293.66 587.33 9.38 293.66 587.33 659.26 9.39 293.66 587.33 659.26 9.40 293.66 587.33 659.26 220.00 9.41 293.66 587.33 659.26 220.00 440.00 9.42 293.66 587.33 659.26 220.00 440.00 9.43 293.66 587.33 659.26 220.00 440.00 9.44 293.66 587.33 659.26 220.00 440.00 9.45 293.66 587.33 659.26 220.00 440.00 9.46 293.66 587.33 659.26 220.00 440.00 9.47 293.66 587.33 659.26 220.00 440.00 9.48 293.66 587.33 659.26 220.00 440.00 9.49 293.66 587.33 659.26 220.00 440.00 9.50 293.66 587.33 659.26 220.00 440.00 9.51 293.66 587.33 659.26 220.00 440.00 9.52 293.66 587.33 659.26 220.00 440.00 9.53 293.66 587.33 659.26 220.00 440.00 9.54 293.66 587.33 659.26 220.00 440.00 9.55 293.66 587.33 659.26 220.00 440.00 9.56 293.66 587.33 659.26 220.00 440.00 9.57 293.66 587.33 659.26 220.00 440.00 9.58 293.66 587.33 659.26 220.00 440.00 9.59 293.66 587.33 659.26 220.00 440.00 9.60 293.66 587.33 659.26 220.00 440.00 9.61 293.66 587.33 659.26 220.00 440.00 9.62 293.66 587.33 659.26 220.00 440.00 9.63 293.66 587.33 659.26 220.00 440.00 9.64 587.33 659.26 220.00 440.00 9.65 587.33 659.26 220.00 440.00 9.66 587.33 659.26 220.00 440.00 9.67 587.33 659.26 220.00 440.00 9.68 587.33 659.26 220.00 440.00 9.69 587.33 659.26 220.00 440.00 9.70 587.33 659.26 220.00 440.00 9.71 659.26 440.00 9.72 659.26 440.00 9.73 659.26 440.00 9.74 659.26 440.00 9.75 659.26 440.00 9.76 659.26 440.00 9.77 659.26 440.00 554.37 9.78 659.26 440.00 554.37 9.79 659.26 440.00 554.37 9.80 659.26 440.00 554.37 9.81 659.26 440.00 554.37 196.00 9.82 659.26 440.00 554.37 196.00 9.83 659.26 440.00 554.37 196.00 9.84 659.26 440.00 554.37 196.00 9.85 659.26 440.00 554.37 196.00 9.86 659.26 440.00 554.37 196.00 9.87 659.26 440.00 554.37 9.88 659.26 440.00 554.37 9.89 659.26 440.00 554.37 9.90 659.26 440.00 554.37 9.91 659.26 440.00 554.37 9.92 659.26 440.00 554.37 9.93 659.26 440.00 554.37 9.94 659.26 440.00 554.37 174.61 9.95 659.26 440.00 554.37 174.61 9.96 659.26 440.00 554.37 174.61 9.97 659.26 440.00 554.37 174.61 9.98 659.26 440.00 554.37 174.61 9.99 659.26 440.00 554.37 174.61 10.00 659.26 440.00 554.37 174.61 10.01 659.26 440.00 554.37 174.61 10.02 659.26 440.00 554.37 10.03 659.26 440.00 554.37 10.04 659.26 440.00 554.37 10.05 440.00 554.37 10.06 440.00 554.37 164.81 10.07 440.00 554.37 164.81 10.08 440.00 554.37 164.81 10.09 440.00 554.37 164.81 10.10 440.00 554.37 164.81 10.11 440.00 554.37 164.81 10.12 440.00 554.37 164.81 10.13 440.00 10.14 440.00 10.15 440.00 698.46 10.16 440.00 698.46 10.17 440.00 698.46 10.18 440.00 698.46 587.33 10.19 440.00 698.46 587.33 146.83 10.20 440.00 698.46 587.33 146.83 10.21 698.46 587.33 146.83 10.22 698.46 587.33 146.83 10.23 698.46 587.33 146.83 10.24 698.46 587.33 146.83 10.25 698.46 587.33 146.83 10.26 698.46 587.33 146.83 10.27 698.46 587.33 146.83 10.28 698.46 587.33 146.83 10.29 698.46 587.33 146.83 10.30 698.46 587.33 146.83 10.31 698.46 587.33 146.83 10.32 698.46 587.33 146.83 10.33 698.46 587.33 146.83 10.34 698.46 587.33 146.83 10.35 698.46 587.33 146.83 10.36 698.46 587.33 146.83 10.37 698.46 587.33 146.83 10.38 698.46 587.33 146.83 10.39 698.46 587.33 146.83 10.40 698.46 587.33 146.83 10.41 698.46 587.33 146.83 10.42 698.46 587.33 146.83 10.43 698.46 587.33 146.83 10.44 698.46 587.33 146.83 10.45 698.46 587.33 146.83 10.46 698.46 587.33 146.83 10.47 698.46 587.33 146.83 10.48 698.46 587.33 146.83 10.49 587.33 146.83 10.50 587.33 146.83 10.51 587.33 146.83 10.52 587.33 146.83 10.53 587.33 146.83 587.33 10.54 587.33 146.83 587.33 10.55 587.33 146.83 587.33 10.56 587.33 146.83 587.33 10.57 587.33 146.83 587.33 10.58 587.33 146.83 587.33 10.59 587.33 146.83 587.33 587.33 10.60 587.33 146.83 587.33 587.33 10.61 587.33 146.83 587.33 587.33 10.62 587.33 146.83 587.33 587.33 10.63 587.33 146.83 587.33 587.33 10.64 587.33 146.83 587.33 587.33 10.65 587.33 146.83 587.33 587.33 10.66 587.33 146.83 587.33 10.67 587.33 146.83 587.33 10.68 587.33 146.83 587.33 10.69 587.33 146.83 587.33 10.70 587.33 146.83 587.33 10.71 587.33 146.83 587.33 10.72 587.33 146.83 587.33 10.73 587.33 146.83 587.33 523.25 10.74 587.33 146.83 587.33 523.25 10.75 587.33 146.83 587.33 523.25 10.76 587.33 146.83 587.33 523.25 10.77 587.33 587.33 523.25 10.78 587.33 587.33 523.25 10.79 587.33 587.33 10.80 587.33 587.33 10.81 587.33 587.33 10.82 587.33 587.33 10.83 587.33 587.33 10.84 587.33 587.33 466.16 10.85 587.33 587.33 466.16 10.86 587.33 587.33 466.16 10.87 587.33 587.33 466.16 10.88 587.33 587.33 466.16 10.89 587.33 587.33 10.90 587.33 587.33 10.91 587.33 10.92 587.33 220.00 10.93 587.33 220.00 659.26 10.94 587.33 220.00 659.26 10.95 587.33 220.00 659.26 10.96 587.33 220.00 659.26 440.00 10.97 587.33 220.00 659.26 440.00 10.98 587.33 220.00 659.26 440.00 10.99 587.33 220.00 659.26 440.00 11.00 587.33 220.00 659.26 440.00 11.01 587.33 220.00 659.26 440.00 11.02 587.33 220.00 659.26 440.00 11.03 587.33 220.00 659.26 440.00 11.04 587.33 220.00 659.26 440.00 11.05 587.33 220.00 659.26 440.00 11.06 587.33 220.00 659.26 440.00 11.07 587.33 220.00 659.26 440.00 11.08 587.33 220.00 659.26 440.00 11.09 587.33 220.00 659.26 440.00 11.10 587.33 220.00 659.26 440.00 11.11 587.33 220.00 659.26 440.00 11.12 587.33 220.00 659.26 440.00 11.13 587.33 220.00 659.26 440.00 11.14 587.33 220.00 659.26 440.00 11.15 220.00 659.26 440.00 11.16 220.00 659.26 440.00 11.17 220.00 659.26 440.00 11.18 220.00 659.26 440.00 11.19 220.00 659.26 440.00 11.20 220.00 659.26 440.00 11.21 220.00 659.26 440.00 11.22 220.00 659.26 440.00 11.23 659.26 440.00 11.24 659.26 440.00 11.25 659.26 440.00 11.26 659.26 440.00 11.27 659.26 440.00 11.28 659.26 440.00 11.29 659.26 440.00 11.30 659.26 440.00 11.31 659.26 440.00 11.32 659.26 440.00 11.33 659.26 440.00 196.00 11.34 659.26 440.00 196.00 11.35 659.26 440.00 196.00 554.37 11.36 659.26 440.00 196.00 554.37 11.37 659.26 440.00 196.00 554.37 11.38 659.26 440.00 196.00 554.37 11.39 659.26 440.00 196.00 554.37 11.40 659.26 440.00 554.37 11.41 659.26 440.00 554.37 11.42 659.26 440.00 554.37 11.43 659.26 440.00 554.37 11.44 659.26 440.00 554.37 11.45 659.26 440.00 554.37 11.46 659.26 440.00 554.37 11.47 659.26 440.00 554.37 174.61 11.48 659.26 440.00 554.37 174.61 11.49 659.26 440.00 554.37 174.61 11.50 659.26 554.37 174.61 11.51 659.26 554.37 174.61 11.52 659.26 554.37 174.61 11.53 659.26 554.37 174.61 11.54 659.26 554.37 174.61 11.55 554.37 11.56 554.37 11.57 554.37 11.58 554.37 11.59 554.37 164.81 11.60 554.37 164.81 11.61 554.37 164.81 11.62 554.37 164.81 11.63 554.37 164.81 11.64 164.81 11.65 164.81 11.66 164.81 11.67 164.81 11.68 11.69 739.99 11.70 739.99 523.25 11.71 739.99 523.25 11.72 739.99 523.25 11.73 739.99 523.25 146.83 440.00 11.74 739.99 523.25 146.83 440.00 11.75 739.99 523.25 146.83 440.00 11.76 739.99 523.25 146.83 440.00 11.77 739.99 523.25 146.83 440.00 11.78 739.99 523.25 146.83 440.00 11.79 739.99 523.25 146.83 440.00 11.80 739.99 523.25 146.83 440.00 11.81 739.99 523.25 146.83 440.00 11.82 739.99 523.25 146.83 440.00 11.83 739.99 523.25 146.83 440.00 11.84 739.99 523.25 146.83 440.00 11.85 739.99 523.25 146.83 440.00 11.86 739.99 523.25 146.83 440.00 11.87 739.99 523.25 146.83 440.00 11.88 739.99 523.25 146.83 440.00 11.89 739.99 523.25 146.83 440.00 11.90 739.99 523.25 146.83 440.00 11.91 739.99 523.25 146.83 440.00 11.92 739.99 523.25 146.83 440.00 11.93 739.99 523.25 146.83 440.00 11.94 739.99 523.25 146.83 440.00 11.95 739.99 523.25 146.83 440.00 11.96 739.99 523.25 146.83 440.00 11.97 739.99 523.25 146.83 440.00 11.98 739.99 523.25 146.83 440.00 11.99 739.99 146.83 440.00 12.00 739.99 146.83 440.00 12.01 739.99 146.83 440.00 12.02 739.99 146.83 440.00 12.03 739.99 146.83 440.00 12.04 739.99 146.83 440.00 12.05 739.99 146.83 440.00 12.06 739.99 146.83 440.00 12.07 739.99 146.83 440.00 493.88 12.08 739.99 146.83 440.00 493.88 12.09 739.99 146.83 440.00 493.88 12.10 739.99 146.83 440.00 493.88 12.11 739.99 146.83 440.00 493.88 12.12 739.99 146.83 440.00 493.88 12.13 739.99 146.83 440.00 493.88 12.14 739.99 146.83 440.00 493.88 12.15 739.99 146.83 440.00 12.16 739.99 146.83 440.00 12.17 739.99 146.83 440.00 12.18 739.99 440.00 12.19 739.99 440.00 12.20 739.99 440.00 12.21 739.99 440.00 12.22 739.99 440.00 523.25 12.23 739.99 440.00 523.25 12.24 739.99 440.00 523.25 12.25 739.99 440.00 523.25 12.26 739.99 440.00 523.25 12.27 739.99 440.00 523.25 12.28 739.99 440.00 523.25 12.29 739.99 440.00 523.25 12.30 739.99 440.00 523.25 12.31 739.99 440.00 12.32 739.99 440.00 12.33 739.99 440.00 12.34 739.99 440.00 12.35 739.99 440.00 12.36 739.99 440.00 587.33 12.37 739.99 440.00 587.33 12.38 739.99 440.00 587.33 12.39 739.99 587.33 12.40 739.99 587.33 12.41 739.99 587.33 12.42 739.99 12.43 12.44 12.45 12.46 12.47 622.25 12.48 622.25 466.16 12.49 622.25 466.16 98.00 783.99 12.50 622.25 466.16 98.00 783.99 12.51 622.25 466.16 98.00 783.99 12.52 622.25 466.16 98.00 783.99 12.53 622.25 466.16 98.00 783.99 12.54 622.25 466.16 98.00 783.99 12.55 622.25 466.16 98.00 783.99 12.56 622.25 466.16 98.00 783.99 12.57 622.25 466.16 98.00 783.99 12.58 622.25 466.16 98.00 783.99 12.59 622.25 466.16 98.00 783.99 12.60 622.25 466.16 98.00 783.99 12.61 622.25 466.16 98.00 783.99 12.62 622.25 466.16 98.00 783.99 12.63 622.25 466.16 98.00 783.99 12.64 622.25 466.16 98.00 783.99 12.65 622.25 466.16 98.00 783.99 12.66 622.25 466.16 98.00 783.99 12.67 622.25 466.16 98.00 783.99 12.68 622.25 466.16 98.00 783.99 12.69 622.25 466.16 98.00 783.99 12.70 622.25 466.16 98.00 783.99 12.71 622.25 466.16 98.00 783.99 12.72 622.25 466.16 98.00 783.99 12.73 622.25 466.16 98.00 783.99 12.74 622.25 466.16 98.00 783.99 12.75 622.25 466.16 98.00 783.99 12.76 622.25 466.16 98.00 783.99 12.77 622.25 466.16 98.00 783.99 12.78 622.25 466.16 783.99 12.79 622.25 466.16 783.99 12.80 622.25 466.16 783.99 12.81 622.25 466.16 783.99 12.82 622.25 466.16 783.99 12.83 622.25 466.16 783.99 12.84 622.25 466.16 783.99 12.85 622.25 466.16 783.99 12.86 622.25 466.16 783.99 12.87 622.25 466.16 783.99 12.88 622.25 466.16 783.99 12.89 622.25 466.16 783.99 12.90 622.25 466.16 783.99 196.00 12.91 622.25 466.16 783.99 196.00 12.92 622.25 466.16 783.99 196.00 12.93 622.25 466.16 783.99 196.00 12.94 622.25 466.16 783.99 196.00 12.95 622.25 466.16 783.99 196.00 12.96 622.25 466.16 783.99 196.00 12.97 622.25 466.16 783.99 12.98 622.25 466.16 783.99 12.99 622.25 466.16 783.99 13.00 622.25 466.16 783.99 13.01 622.25 466.16 783.99 13.02 622.25 466.16 783.99 13.03 622.25 466.16 783.99 13.04 622.25 466.16 783.99 220.00 13.05 622.25 466.16 783.99 220.00 13.06 622.25 466.16 783.99 220.00 13.07 622.25 466.16 783.99 220.00 13.08 622.25 466.16 783.99 220.00 13.09 622.25 466.16 783.99 220.00 13.10 622.25 783.99 13.11 622.25 783.99 13.12 622.25 783.99 13.13 622.25 783.99 13.14 622.25 783.99 13.15 622.25 783.99 233.08 13.16 622.25 783.99 233.08 13.17 622.25 233.08 13.18 233.08 13.19 233.08 13.20 233.08 13.21 233.08 13.22 233.08 13.23 830.61 13.24 830.61 13.25 830.61 13.26 830.61 587.33 13.27 830.61 587.33 13.28 830.61 587.33 493.88 13.29 830.61 587.33 493.88 13.30 830.61 587.33 493.88 13.31 830.61 587.33 493.88 164.81 13.32 830.61 587.33 493.88 164.81 13.33 830.61 587.33 493.88 164.81 13.34 830.61 587.33 493.88 164.81 13.35 830.61 587.33 493.88 164.81 13.36 830.61 587.33 493.88 164.81 13.37 830.61 587.33 493.88 164.81 13.38 830.61 587.33 493.88 164.81 13.39 830.61 587.33 493.88 164.81 13.40 830.61 587.33 493.88 164.81 13.41 830.61 587.33 493.88 164.81 13.42 830.61 587.33 493.88 164.81 13.43 830.61 587.33 493.88 164.81 13.44 830.61 587.33 493.88 164.81 13.45 830.61 587.33 493.88 164.81 13.46 830.61 587.33 493.88 164.81 13.47 830.61 587.33 493.88 164.81 13.48 830.61 587.33 493.88 164.81 13.49 830.61 587.33 493.88 164.81 13.50 830.61 587.33 493.88 164.81 13.51 830.61 587.33 493.88 164.81 13.52 830.61 587.33 493.88 164.81 13.53 830.61 587.33 493.88 164.81 13.54 587.33 493.88 164.81 13.55 587.33 493.88 164.81 13.56 587.33 493.88 164.81 13.57 587.33 493.88 164.81 13.58 587.33 493.88 164.81 13.59 587.33 493.88 164.81 13.60 587.33 493.88 164.81 13.61 587.33 493.88 164.81 13.62 587.33 493.88 164.81 13.63 587.33 493.88 164.81 13.64 587.33 493.88 164.81 659.26 13.65 587.33 493.88 164.81 659.26 13.66 587.33 493.88 164.81 659.26 13.67 587.33 493.88 164.81 659.26 13.68 587.33 493.88 164.81 659.26 13.69 587.33 493.88 164.81 659.26 13.70 587.33 493.88 164.81 659.26 13.71 587.33 493.88 164.81 659.26 13.72 587.33 493.88 164.81 13.73 587.33 493.88 164.81 13.74 587.33 493.88 164.81 13.75 587.33 493.88 164.81 13.76 587.33 493.88 164.81 13.77 587.33 493.88 164.81 13.78 587.33 493.88 164.81 13.79 587.33 493.88 164.81 13.80 587.33 493.88 164.81 739.99 13.81 587.33 493.88 164.81 739.99 13.82 587.33 493.88 164.81 739.99 13.83 587.33 493.88 164.81 739.99 13.84 587.33 493.88 164.81 739.99 13.85 587.33 493.88 164.81 739.99 13.86 587.33 493.88 164.81 13.87 587.33 493.88 164.81 13.88 587.33 493.88 164.81 13.89 587.33 493.88 13.90 587.33 493.88 13.91 587.33 493.88 830.61 13.92 587.33 493.88 830.61 13.93 493.88 830.61 13.94 493.88 830.61 13.95 493.88 830.61 13.96 493.88 830.61 13.97 493.88 13.98 493.88 13.99 14.00 14.01 14.02 14.03 110.00 880.00 14.04 110.00 880.00 14.05 110.00 880.00 440.00 523.25 14.06 110.00 880.00 440.00 523.25 14.07 110.00 880.00 440.00 523.25 14.08 110.00 880.00 440.00 523.25 14.09 110.00 880.00 440.00 523.25 14.10 110.00 880.00 440.00 523.25 14.11 110.00 880.00 440.00 523.25 14.12 110.00 880.00 440.00 523.25 14.13 110.00 880.00 440.00 523.25 14.14 110.00 880.00 440.00 523.25 14.15 110.00 880.00 440.00 523.25 14.16 110.00 880.00 440.00 523.25 698.46 14.17 110.00 880.00 440.00 523.25 698.46 14.18 110.00 880.00 440.00 523.25 698.46 14.19 110.00 880.00 440.00 523.25 698.46 14.20 110.00 880.00 440.00 523.25 698.46 14.21 110.00 880.00 440.00 523.25 698.46 14.22 110.00 880.00 440.00 523.25 698.46 14.23 110.00 880.00 440.00 523.25 698.46 14.24 110.00 880.00 440.00 523.25 698.46 14.25 110.00 880.00 440.00 523.25 698.46 14.26 110.00 880.00 440.00 523.25 698.46 14.27 110.00 880.00 440.00 523.25 698.46 14.28 110.00 880.00 440.00 523.25 698.46 14.29 110.00 880.00 440.00 523.25 698.46 14.30 110.00 880.00 440.00 523.25 698.46 14.31 110.00 880.00 440.00 523.25 698.46 14.32 110.00 880.00 440.00 523.25 698.46 14.33 110.00 880.00 440.00 523.25 698.46 14.34 110.00 880.00 440.00 523.25 698.46 14.35 110.00 880.00 440.00 523.25 698.46 14.36 110.00 880.00 440.00 523.25 698.46 14.37 880.00 440.00 523.25 698.46 14.38 880.00 440.00 523.25 698.46 14.39 880.00 440.00 523.25 698.46 14.40 880.00 440.00 523.25 698.46 14.41 880.00 440.00 523.25 698.46 14.42 880.00 440.00 523.25 698.46 14.43 880.00 440.00 523.25 698.46 14.44 880.00 440.00 523.25 698.46 220.00 14.45 880.00 440.00 523.25 698.46 220.00 14.46 440.00 523.25 698.46 220.00 14.47 440.00 523.25 698.46 220.00 14.48 440.00 523.25 698.46 220.00 14.49 523.25 698.46 220.00 14.50 523.25 698.46 14.51 698.46 14.52 698.46 14.53 698.46 14.54 698.46 14.55 14.56 14.57 14.58 246.94 14.59 246.94 14.60 246.94 14.61 246.94 14.62 246.94 14.63 246.94 14.64 14.65 14.66 14.67 261.63 14.68 261.63 14.69 261.63 14.70 261.63 14.71 261.63 14.72 261.63 14.73 261.63 14.74 261.63 14.75 261.63 14.76 14.77 14.78 14.79 554.37 14.80 554.37 14.81 554.37 392.00 14.82 554.37 392.00 14.83 554.37 392.00 220.00 14.84 554.37 392.00 220.00 880.00 14.85 554.37 392.00 220.00 880.00 14.86 392.00 220.00 880.00 14.87 392.00 220.00 880.00 14.88 392.00 220.00 880.00 14.89 392.00 220.00 880.00 14.90 392.00 220.00 880.00 14.91 392.00 220.00 880.00 14.92 392.00 220.00 880.00 14.93 392.00 220.00 880.00 14.94 392.00 220.00 880.00 14.95 392.00 220.00 880.00 493.88 14.96 392.00 220.00 880.00 493.88 14.97 392.00 220.00 880.00 493.88 14.98 392.00 220.00 880.00 493.88 14.99 392.00 220.00 880.00 493.88 15.00 392.00 220.00 880.00 493.88 15.01 392.00 220.00 880.00 493.88 15.02 392.00 220.00 880.00 15.03 392.00 220.00 880.00 15.04 392.00 880.00 15.05 392.00 880.00 15.06 392.00 880.00 15.07 392.00 880.00 15.08 392.00 880.00 440.00 15.09 392.00 880.00 440.00 15.10 392.00 440.00 15.11 392.00 440.00 15.12 440.00 15.13 440.00 15.14 15.15 15.16 15.17 15.18 15.19 15.20 880.00 15.21 880.00 15.22 880.00 587.33 220.00 349.23 15.23 880.00 587.33 220.00 349.23 15.24 880.00 587.33 220.00 349.23 15.25 880.00 587.33 220.00 349.23 15.26 880.00 587.33 220.00 349.23 15.27 880.00 587.33 220.00 349.23 15.28 880.00 587.33 220.00 349.23 15.29 880.00 587.33 220.00 349.23 15.30 880.00 587.33 220.00 15.31 880.00 587.33 220.00 15.32 880.00 587.33 220.00 15.33 880.00 587.33 220.00 15.34 880.00 587.33 220.00 15.35 880.00 587.33 220.00 15.36 880.00 587.33 220.00 329.63 15.37 880.00 587.33 220.00 329.63 15.38 880.00 587.33 220.00 329.63 15.39 880.00 587.33 220.00 329.63 15.40 880.00 587.33 220.00 329.63 15.41 880.00 587.33 220.00 329.63 15.42 880.00 587.33 220.00 329.63 15.43 880.00 587.33 220.00 15.44 880.00 587.33 220.00 15.45 880.00 587.33 220.00 15.46 880.00 587.33 220.00 15.47 880.00 587.33 220.00 15.48 880.00 587.33 220.00 293.66 15.49 587.33 220.00 293.66 15.50 220.00 293.66 15.51 220.00 293.66 15.52 293.66 15.53 293.66 15.54 293.66 15.55 293.66 15.56 15.57 15.58 15.59 587.33 15.60 587.33 15.61 587.33 220.00 15.62 587.33 220.00 329.63 880.00 15.63 587.33 220.00 329.63 880.00 15.64 587.33 220.00 329.63 880.00 15.65 587.33 220.00 329.63 880.00 15.66 587.33 220.00 329.63 880.00 15.67 587.33 220.00 329.63 880.00 15.68 587.33 220.00 329.63 880.00 15.69 587.33 220.00 329.63 880.00 15.70 587.33 220.00 329.63 880.00 15.71 587.33 220.00 329.63 880.00 15.72 587.33 220.00 329.63 880.00 15.73 587.33 220.00 329.63 880.00 15.74 587.33 220.00 329.63 880.00 15.75 587.33 220.00 329.63 880.00 15.76 587.33 220.00 329.63 15.77 587.33 220.00 329.63 15.78 587.33 220.00 329.63 15.79 587.33 220.00 329.63 15.80 587.33 220.00 329.63 15.81 587.33 220.00 329.63 15.82 587.33 220.00 329.63 15.83 587.33 220.00 329.63 15.84 587.33 220.00 329.63 15.85 587.33 220.00 329.63 15.86 587.33 220.00 329.63 15.87 220.00 329.63 15.88 220.00 329.63 15.89 220.00 329.63 15.90 220.00 329.63 15.91 329.63 15.92 15.93 15.94 15.95 15.96 880.00 15.97 880.00 15.98 880.00 15.99 880.00 16.00 880.00 554.37 16.01 880.00 554.37 16.02 880.00 554.37 329.63 16.03 880.00 554.37 329.63 220.00 16.04 880.00 554.37 329.63 220.00 16.05 554.37 329.63 220.00 16.06 329.63 220.00 16.07 329.63 220.00 16.08 329.63 220.00 16.09 329.63 220.00 16.10 329.63 220.00 16.11 329.63 220.00 16.12 329.63 220.00 16.13 329.63 220.00 16.14 329.63 220.00 16.15 329.63 220.00 16.16 329.63 220.00 16.17 329.63 220.00 16.18 329.63 220.00 16.19 329.63 220.00 16.20 329.63 220.00 16.21 329.63 220.00 16.22 329.63 220.00 16.23 329.63 220.00 16.24 329.63 220.00 16.25 329.63 220.00 16.26 329.63 220.00 16.27 329.63 220.00 16.28 329.63 16.29 329.63 16.30 329.63 16.31 329.63 16.32 16.33 16.34 16.35 16.36 16.37 16.38 16.39 16.40 16.41 293.66 16.42 293.66 16.43 293.66 16.44 293.66 293.66 16.45 293.66 293.66 16.46 293.66 293.66 587.33 16.47 293.66 293.66 587.33 349.23 220.00 16.48 293.66 293.66 587.33 349.23 220.00 16.49 293.66 293.66 587.33 349.23 220.00 16.50 293.66 587.33 349.23 220.00 16.51 293.66 587.33 349.23 220.00 16.52 293.66 587.33 349.23 16.53 293.66 587.33 16.54 293.66 587.33 16.55 293.66 587.33 16.56 293.66 587.33 16.57 293.66 587.33 16.58 293.66 587.33 16.59 293.66 587.33 16.60 293.66 587.33 16.61 293.66 587.33 293.66 16.62 293.66 587.33 293.66 16.63 293.66 587.33 293.66 349.23 220.00 16.64 293.66 587.33 293.66 349.23 220.00 16.65 293.66 587.33 349.23 220.00 16.66 293.66 587.33 349.23 220.00 16.67 293.66 587.33 349.23 220.00 16.68 293.66 587.33 16.69 293.66 587.33 16.70 293.66 587.33 16.71 293.66 587.33 16.72 293.66 587.33 16.73 587.33 16.74 587.33 16.75 587.33 293.66 16.76 587.33 293.66 16.77 587.33 293.66 16.78 587.33 293.66 220.00 349.23 16.79 587.33 293.66 220.00 349.23 16.80 587.33 293.66 220.00 349.23 16.81 587.33 220.00 349.23 16.82 587.33 220.00 349.23 16.83 587.33 146.83 16.84 587.33 146.83 16.85 587.33 146.83 16.86 587.33 146.83 16.87 587.33 146.83 293.66 16.88 587.33 146.83 293.66 16.89 587.33 146.83 293.66 16.90 587.33 146.83 293.66 349.23 220.00 16.91 587.33 146.83 293.66 349.23 220.00 16.92 587.33 146.83 293.66 349.23 220.00 16.93 587.33 146.83 349.23 220.00 16.94 587.33 146.83 349.23 220.00 16.95 587.33 146.83 349.23 16.96 587.33 146.83 16.97 587.33 146.83 16.98 587.33 146.83 16.99 587.33 146.83 17.00 587.33 146.83 17.01 146.83 293.66 17.02 146.83 293.66 17.03 146.83 293.66 17.04 146.83 293.66 349.23 220.00 17.05 146.83 349.23 220.00 17.06 146.83 349.23 220.00 17.07 146.83 17.08 146.83 17.09 146.83 523.25 17.10 146.83 523.25 17.11 146.83 523.25 17.12 146.83 523.25 17.13 146.83 523.25 17.14 146.83 523.25 17.15 146.83 523.25 293.66 17.16 146.83 293.66 17.17 146.83 293.66 220.00 349.23 17.18 146.83 293.66 220.00 349.23 17.19 146.83 220.00 349.23 17.20 146.83 349.23 17.21 146.83 466.16 17.22 146.83 466.16 17.23 146.83 466.16 17.24 146.83 466.16 17.25 146.83 466.16 17.26 146.83 466.16 220.00 293.66 17.27 146.83 466.16 220.00 293.66 17.28 146.83 466.16 220.00 293.66 349.23 17.29 146.83 220.00 349.23 17.30 146.83 220.00 349.23 17.31 146.83 220.00 17.32 146.83 17.33 146.83 17.34 146.83 17.35 146.83 440.00 17.36 146.83 440.00 17.37 146.83 440.00 17.38 146.83 440.00 329.63 220.00 17.39 146.83 440.00 329.63 220.00 17.40 146.83 440.00 329.63 220.00 392.00 17.41 146.83 440.00 329.63 220.00 392.00 17.42 146.83 440.00 220.00 392.00 17.43 440.00 220.00 392.00 17.44 440.00 17.45 440.00 17.46 440.00 17.47 440.00 17.48 440.00 17.49 440.00 17.50 440.00 329.63 17.51 440.00 329.63 17.52 440.00 329.63 17.53 440.00 329.63 220.00 17.54 440.00 329.63 220.00 17.55 440.00 329.63 17.56 440.00 329.63 17.57 440.00 17.58 440.00 17.59 440.00 17.60 440.00 17.61 440.00 17.62 440.00 329.63 17.63 440.00 329.63 17.64 440.00 329.63 392.00 17.65 440.00 392.00 220.00 17.66 440.00 392.00 220.00 17.67 440.00 220.00 17.68 440.00 17.69 440.00 17.70 440.00 138.59 17.71 440.00 138.59 17.72 440.00 138.59 17.73 440.00 138.59 17.74 440.00 138.59 329.63 17.75 440.00 138.59 329.63 17.76 440.00 138.59 329.63 392.00 220.00 17.77 440.00 138.59 329.63 392.00 220.00 17.78 440.00 329.63 392.00 220.00 17.79 440.00 392.00 220.00 17.80 440.00 392.00 220.00 17.81 440.00 17.82 440.00 17.83 440.00 17.84 440.00 17.85 440.00 123.47 17.86 440.00 123.47 17.87 440.00 123.47 329.63 17.88 440.00 123.47 329.63 17.89 440.00 123.47 329.63 220.00 392.00 17.90 440.00 123.47 329.63 220.00 392.00 17.91 440.00 123.47 220.00 392.00 17.92 440.00 123.47 220.00 392.00 17.93 440.00 123.47 220.00 17.94 440.00 123.47 17.95 440.00 123.47 17.96 440.00 123.47 110.00 17.97 440.00 123.47 110.00 17.98 440.00 123.47 110.00 17.99 440.00 123.47 110.00 18.00 440.00 110.00 18.01 440.00 110.00 329.63 18.02 440.00 110.00 329.63 18.03 440.00 110.00 329.63 392.00 18.04 440.00 110.00 329.63 392.00 18.05 110.00 392.00 18.06 110.00 392.00 18.07 110.00 18.08 18.09 18.10 18.11 18.12 146.83 18.13 146.83 18.14 146.83 18.15 146.83 293.66 18.16 146.83 293.66 18.17 146.83 293.66 220.00 349.23 18.18 146.83 293.66 220.00 349.23 18.19 146.83 293.66 220.00 349.23 698.46 18.20 146.83 293.66 220.00 349.23 698.46 18.21 146.83 220.00 349.23 698.46 18.22 146.83 349.23 698.46 18.23 146.83 698.46 18.24 146.83 698.46 18.25 146.83 698.46 18.26 146.83 698.46 18.27 146.83 698.46 18.28 146.83 698.46 18.29 146.83 698.46 293.66 18.30 146.83 698.46 293.66 18.31 698.46 293.66 220.00 349.23 18.32 698.46 293.66 220.00 349.23 18.33 698.46 220.00 349.23 18.34 698.46 220.00 349.23 18.35 698.46 220.00 349.23 18.36 698.46 18.37 698.46 18.38 698.46 18.39 698.46 18.40 698.46 18.41 698.46 18.42 698.46 293.66 18.43 698.46 293.66 18.44 698.46 293.66 18.45 698.46 293.66 349.23 220.00 18.46 698.46 293.66 349.23 220.00 18.47 698.46 349.23 220.00 18.48 698.46 349.23 220.00 18.49 698.46 349.23 18.50 698.46 18.51 18.52 146.83 18.53 146.83 18.54 146.83 18.55 146.83 18.56 146.83 293.66 18.57 146.83 293.66 220.00 587.33 18.58 146.83 293.66 220.00 587.33 349.23 18.59 146.83 293.66 220.00 587.33 349.23 18.60 146.83 220.00 587.33 349.23 18.61 146.83 220.00 587.33 349.23 18.62 146.83 587.33 18.63 146.83 587.33 18.64 146.83 587.33 18.65 146.83 18.66 146.83 18.67 146.83 18.68 146.83 293.66 18.69 146.83 293.66 18.70 146.83 293.66 349.23 220.00 18.71 146.83 293.66 349.23 220.00 18.72 146.83 293.66 349.23 220.00 523.25 18.73 146.83 349.23 220.00 523.25 18.74 146.83 349.23 220.00 523.25 18.75 146.83 523.25 18.76 146.83 523.25 18.77 146.83 523.25 18.78 146.83 18.79 146.83 18.80 146.83 18.81 146.83 466.16 18.82 146.83 466.16 293.66 18.83 146.83 466.16 293.66 18.84 146.83 466.16 293.66 349.23 18.85 146.83 466.16 293.66 349.23 220.00 18.86 146.83 466.16 349.23 220.00 18.87 146.83 466.16 349.23 220.00 18.88 146.83 466.16 349.23 220.00 18.89 146.83 18.90 146.83 18.91 146.83 18.92 146.83 18.93 146.83 18.94 146.83 18.95 146.83 18.96 146.83 440.00 18.97 146.83 440.00 329.63 18.98 146.83 440.00 329.63 18.99 146.83 440.00 329.63 392.00 19.00 146.83 440.00 329.63 392.00 220.00 19.01 146.83 440.00 329.63 392.00 220.00 19.02 146.83 440.00 329.63 392.00 220.00 19.03 146.83 440.00 392.00 220.00 19.04 146.83 440.00 392.00 220.00 19.05 146.83 440.00 19.06 146.83 440.00 19.07 146.83 440.00 19.08 146.83 440.00 19.09 146.83 440.00 19.10 146.83 440.00 19.11 146.83 440.00 329.63 19.12 146.83 440.00 329.63 19.13 146.83 440.00 329.63 392.00 19.14 146.83 440.00 329.63 392.00 220.00 19.15 146.83 440.00 329.63 392.00 220.00 19.16 146.83 440.00 392.00 220.00 19.17 440.00 392.00 220.00 19.18 440.00 19.19 440.00 19.20 440.00 19.21 440.00 19.22 440.00 19.23 440.00 19.24 440.00 329.63 19.25 440.00 329.63 19.26 440.00 329.63 19.27 440.00 329.63 392.00 220.00 19.28 440.00 392.00 220.00 19.29 440.00 392.00 220.00 19.30 440.00 392.00 19.31 440.00 19.32 440.00 19.33 440.00 19.34 440.00 19.35 440.00 19.36 440.00 329.63 19.37 440.00 329.63 19.38 440.00 329.63 220.00 392.00 19.39 440.00 329.63 220.00 392.00 138.59 19.40 440.00 329.63 220.00 392.00 138.59 19.41 440.00 220.00 392.00 138.59 19.42 440.00 220.00 392.00 138.59 19.43 440.00 138.59 19.44 440.00 138.59 19.45 440.00 138.59 19.46 440.00 138.59 19.47 440.00 19.48 440.00 19.49 440.00 19.50 440.00 329.63 19.51 440.00 329.63 19.52 440.00 329.63 220.00 392.00 19.53 440.00 329.63 220.00 392.00 123.47 19.54 440.00 220.00 392.00 123.47 19.55 440.00 220.00 392.00 123.47 19.56 440.00 220.00 123.47 19.57 440.00 123.47 19.58 123.47 19.59 123.47 19.60 123.47 19.61 123.47 19.62 123.47 329.63 19.63 123.47 329.63 19.64 123.47 329.63 392.00 19.65 123.47 329.63 392.00 110.00 220.00 19.66 123.47 329.63 392.00 110.00 220.00 19.67 123.47 329.63 392.00 110.00 220.00 19.68 123.47 392.00 110.00 220.00 19.69 392.00 110.00 220.00 19.70 110.00 19.71 110.00 19.72 110.00 19.73 110.00 19.74 110.00 19.75 110.00 19.76 110.00 19.77 110.00 293.66 19.78 110.00 293.66 19.79 110.00 293.66 220.00 146.83 349.23 19.80 293.66 220.00 146.83 349.23 19.81 293.66 220.00 146.83 349.23 19.82 220.00 146.83 349.23 19.83 220.00 146.83 349.23 698.46 19.84 220.00 146.83 349.23 698.46 19.85 146.83 698.46 19.86 146.83 698.46 19.87 146.83 698.46 19.88 146.83 698.46 19.89 146.83 698.46 19.90 146.83 698.46 19.91 146.83 698.46 293.66 19.92 146.83 698.46 293.66 19.93 146.83 698.46 293.66 220.00 349.23 19.94 146.83 698.46 293.66 220.00 349.23 19.95 146.83 698.46 293.66 220.00 349.23 19.96 146.83 698.46 220.00 349.23 19.97 146.83 698.46 220.00 349.23 19.98 146.83 698.46 220.00 349.23 19.99 146.83 698.46 20.00 146.83 698.46 20.01 146.83 698.46 20.02 146.83 698.46 20.03 146.83 698.46 20.04 146.83 698.46 20.05 146.83 698.46 293.66 20.06 146.83 698.46 293.66 20.07 146.83 698.46 293.66 220.00 20.08 146.83 698.46 293.66 220.00 349.23 20.09 146.83 698.46 293.66 220.00 349.23 20.10 146.83 698.46 220.00 349.23 20.11 146.83 698.46 220.00 349.23 20.12 146.83 698.46 220.00 349.23 20.13 146.83 698.46 20.14 146.83 698.46 20.15 146.83 698.46 20.16 146.83 698.46 20.17 146.83 698.46 20.18 146.83 698.46 20.19 146.83 698.46 293.66 20.20 146.83 698.46 293.66 20.21 146.83 698.46 293.66 220.00 20.22 146.83 698.46 293.66 220.00 349.23 20.23 146.83 698.46 293.66 220.00 349.23 20.24 698.46 220.00 349.23 20.25 698.46 220.00 349.23 20.26 698.46 220.00 349.23 20.27 698.46 20.28 698.46 20.29 698.46 20.30 698.46 20.31 698.46 20.32 698.46 20.33 698.46 164.81 293.66 20.34 698.46 164.81 293.66 20.35 698.46 164.81 293.66 20.36 698.46 164.81 293.66 349.23 220.00 20.37 698.46 164.81 293.66 349.23 220.00 20.38 698.46 164.81 293.66 349.23 220.00 20.39 698.46 164.81 349.23 220.00 20.40 164.81 349.23 20.41 659.26 20.42 659.26 20.43 659.26 20.44 659.26 20.45 659.26 174.61 20.46 659.26 174.61 196.00 20.47 659.26 174.61 196.00 293.66 20.48 659.26 174.61 196.00 293.66 20.49 659.26 174.61 196.00 293.66 220.00 349.23 20.50 174.61 293.66 220.00 349.23 20.51 174.61 293.66 220.00 349.23 20.52 293.66 220.00 349.23 20.53 220.00 349.23 20.54 349.23 587.33 20.55 349.23 587.33 20.56 587.33 20.57 587.33 20.58 587.33 20.59 587.33 20.60 587.33 20.61 587.33 116.54 293.66 20.62 587.33 116.54 293.66 20.63 116.54 293.66 20.64 116.54 293.66 349.23 20.65 116.54 293.66 349.23 880.00 20.66 116.54 293.66 349.23 880.00 20.67 116.54 349.23 880.00 20.68 116.54 349.23 880.00 20.69 116.54 880.00 20.70 116.54 880.00 20.71 116.54 880.00 20.72 116.54 880.00 20.73 116.54 880.00 20.74 116.54 880.00 20.75 116.54 880.00 293.66 20.76 116.54 880.00 293.66 20.77 116.54 880.00 293.66 349.23 20.78 116.54 880.00 293.66 349.23 20.79 116.54 880.00 293.66 349.23 20.80 116.54 880.00 349.23 20.81 116.54 880.00 349.23 20.82 116.54 880.00 20.83 116.54 880.00 20.84 116.54 880.00 20.85 116.54 880.00 20.86 116.54 880.00 20.87 116.54 880.00 20.88 116.54 880.00 20.89 116.54 880.00 293.66 20.90 116.54 880.00 293.66 20.91 116.54 880.00 293.66 349.23 20.92 116.54 880.00 293.66 349.23 20.93 116.54 880.00 293.66 349.23 20.94 116.54 880.00 349.23 20.95 116.54 880.00 349.23 20.96 116.54 880.00 349.23 20.97 116.54 880.00 20.98 116.54 880.00 20.99 116.54 880.00 21.00 116.54 880.00 21.01 116.54 880.00 21.02 116.54 880.00 293.66 21.03 116.54 880.00 293.66 21.04 116.54 880.00 293.66 349.23 21.05 116.54 880.00 293.66 349.23 21.06 116.54 880.00 293.66 349.23 21.07 116.54 880.00 349.23 21.08 116.54 880.00 349.23 21.09 116.54 880.00 21.10 116.54 880.00 21.11 116.54 880.00 21.12 116.54 880.00 21.13 116.54 880.00 293.66 21.14 116.54 880.00 293.66 21.15 116.54 880.00 293.66 21.16 116.54 880.00 293.66 392.00 21.17 116.54 880.00 293.66 392.00 21.18 116.54 880.00 293.66 392.00 21.19 116.54 880.00 392.00 21.20 116.54 880.00 392.00 21.21 116.54 880.00 392.00 21.22 116.54 21.23 116.54 21.24 116.54 293.66 21.25 116.54 293.66 21.26 116.54 293.66 21.27 116.54 293.66 783.99 440.00 21.28 116.54 783.99 440.00 21.29 116.54 783.99 440.00 21.30 116.54 783.99 440.00 21.31 116.54 783.99 440.00 21.32 116.54 783.99 21.33 116.54 783.99 21.34 116.54 783.99 21.35 116.54 783.99 21.36 116.54 783.99 21.37 116.54 783.99 698.46 21.38 116.54 783.99 698.46 293.66 440.00 21.39 698.46 293.66 440.00 21.40 698.46 293.66 440.00 21.41 698.46 293.66 440.00 21.42 698.46 293.66 440.00 21.43 293.66 440.00 21.44 21.45 110.00 21.46 110.00 21.47 110.00 21.48 110.00 21.49 110.00 21.50 110.00 21.51 110.00 698.46 21.52 110.00 698.46 293.66 440.00 21.53 110.00 698.46 293.66 440.00 21.54 110.00 698.46 293.66 440.00 21.55 110.00 698.46 293.66 440.00 21.56 110.00 698.46 293.66 440.00 21.57 110.00 698.46 293.66 440.00 21.58 110.00 698.46 21.59 110.00 698.46 21.60 110.00 698.46 21.61 110.00 698.46 21.62 110.00 698.46 21.63 110.00 698.46 21.64 110.00 698.46 21.65 110.00 698.46 21.66 110.00 698.46 21.67 110.00 698.46 293.66 440.00 21.68 110.00 698.46 293.66 440.00 21.69 110.00 698.46 293.66 440.00 21.70 110.00 698.46 293.66 440.00 21.71 110.00 698.46 293.66 440.00 21.72 110.00 698.46 293.66 440.00 21.73 110.00 698.46 293.66 440.00 21.74 110.00 698.46 21.75 110.00 698.46 21.76 110.00 698.46 21.77 110.00 698.46 21.78 110.00 698.46 21.79 110.00 698.46 21.80 110.00 698.46 21.81 110.00 698.46 21.82 110.00 277.18 440.00 21.83 110.00 277.18 440.00 21.84 110.00 277.18 440.00 659.26 21.85 110.00 277.18 440.00 659.26 21.86 110.00 277.18 440.00 659.26 21.87 110.00 440.00 659.26 21.88 110.00 659.26 21.89 110.00 659.26 21.90 110.00 659.26 21.91 110.00 659.26 21.92 110.00 659.26 21.93 110.00 659.26 21.94 110.00 659.26 21.95 110.00 659.26 277.18 21.96 110.00 659.26 277.18 440.00 21.97 110.00 659.26 277.18 440.00 21.98 110.00 659.26 277.18 440.00 21.99 110.00 659.26 277.18 440.00 22.00 110.00 659.26 277.18 440.00 22.01 110.00 659.26 277.18 440.00 22.02 110.00 659.26 22.03 110.00 659.26 22.04 110.00 659.26 22.05 110.00 659.26 22.06 110.00 659.26 22.07 110.00 659.26 22.08 110.00 659.26 22.09 110.00 659.26 22.10 110.00 659.26 277.18 22.11 110.00 659.26 277.18 440.00 22.12 110.00 659.26 277.18 440.00 22.13 110.00 659.26 277.18 440.00 22.14 110.00 659.26 277.18 440.00 22.15 110.00 659.26 277.18 440.00 22.16 110.00 659.26 22.17 110.00 659.26 22.18 110.00 659.26 22.19 110.00 659.26 22.20 110.00 659.26 22.21 110.00 659.26 22.22 110.00 659.26 22.23 110.00 659.26 22.24 110.00 659.26 622.25 22.25 110.00 659.26 622.25 261.63 369.99 22.26 110.00 659.26 622.25 261.63 369.99 22.27 110.00 622.25 261.63 369.99 22.28 110.00 622.25 261.63 369.99 22.29 110.00 622.25 22.30 110.00 622.25 22.31 110.00 622.25 22.32 110.00 622.25 22.33 110.00 622.25 22.34 110.00 622.25 22.35 110.00 622.25 22.36 110.00 622.25 22.37 110.00 622.25 22.38 110.00 622.25 22.39 110.00 622.25 261.63 369.99 22.40 110.00 622.25 261.63 369.99 22.41 110.00 622.25 261.63 369.99 22.42 110.00 622.25 261.63 369.99 22.43 110.00 622.25 261.63 369.99 22.44 110.00 622.25 22.45 110.00 622.25 22.46 110.00 622.25 22.47 110.00 622.25 22.48 110.00 622.25 22.49 110.00 622.25 22.50 110.00 622.25 22.51 110.00 622.25 261.63 369.99 22.52 110.00 622.25 261.63 369.99 22.53 110.00 622.25 261.63 369.99 22.54 110.00 622.25 261.63 369.99 22.55 110.00 622.25 261.63 369.99 22.56 110.00 622.25 261.63 369.99 22.57 110.00 622.25 22.58 110.00 622.25 22.59 110.00 622.25 22.60 110.00 622.25 22.61 110.00 622.25 22.62 110.00 622.25 22.63 110.00 622.25 22.64 110.00 622.25 22.65 110.00 622.25 261.63 22.66 110.00 622.25 261.63 369.99 22.67 110.00 622.25 261.63 369.99 22.68 110.00 622.25 261.63 369.99 22.69 110.00 261.63 369.99 22.70 110.00 261.63 369.99 22.71 110.00 22.72 110.00 22.73 110.00 22.74 110.00 22.75 110.00 22.76 22.77 22.78 22.79 261.63 369.99 22.80 261.63 369.99 22.81 261.63 369.99 22.82 261.63 369.99 22.83 261.63 369.99 22.84 261.63 369.99 22.85 22.86 22.87 22.88 22.89 22.90 22.91 22.92 22.93 261.63 369.99 22.94 261.63 369.99 22.95 261.63 369.99 22.96 261.63 369.99 22.97 261.63 369.99mir_eval-0.8.2/tests/data/multipitch/ref08.txt000066400000000000000000001675041475740344600212740ustar00rootroot000000000000000.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.30 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.40 0.41 0.42 0.43 0.44 0.45 0.46 0.47 0.48 0.49 0.50 0.51 0.52 0.53 0.54 0.55 0.56 0.57 0.58 0.59 0.60 0.61 0.62 0.63 0.64 0.65 0.66 0.67 0.68 0.69 0.70 0.71 0.72 0.73 0.74 0.75 0.76 0.77 0.78 0.79 0.80 0.81 0.82 0.83 0.84 0.85 0.86 0.87 0.88 0.89 0.90 0.91 0.92 0.93 0.94 293.66 185.00 0.95 293.66 185.00 369.99 0.96 293.66 185.00 369.99 0.97 293.66 185.00 369.99 0.98 293.66 185.00 369.99 0.99 293.66 185.00 369.99 1.00 293.66 185.00 369.99 1.01 293.66 185.00 369.99 1.02 293.66 185.00 369.99 1.03 293.66 185.00 369.99 1.04 293.66 185.00 369.99 1.05 293.66 185.00 369.99 1.06 293.66 185.00 369.99 1.07 293.66 185.00 369.99 1.08 293.66 185.00 369.99 1.09 293.66 185.00 369.99 1.10 293.66 185.00 369.99 1.11 293.66 185.00 369.99 1.12 293.66 185.00 369.99 1.13 293.66 185.00 369.99 1.14 293.66 185.00 369.99 1.15 293.66 185.00 369.99 1.16 293.66 185.00 369.99 1.17 293.66 185.00 369.99 1.18 369.99 1.19 369.99 1.20 1.21 1.22 1.23 1.24 1.25 1.26 1.27 185.00 1.28 185.00 369.99 293.66 1.29 185.00 369.99 293.66 1.30 185.00 369.99 293.66 1.31 185.00 369.99 293.66 1.32 185.00 369.99 293.66 1.33 185.00 369.99 293.66 1.34 369.99 293.66 1.35 369.99 293.66 1.36 1.37 1.38 1.39 1.40 1.41 1.42 1.43 1.44 1.45 185.00 293.66 1.46 185.00 293.66 369.99 1.47 185.00 293.66 369.99 1.48 185.00 293.66 369.99 1.49 185.00 293.66 369.99 1.50 185.00 293.66 369.99 1.51 185.00 293.66 1.52 185.00 1.53 1.54 1.55 1.56 1.57 1.58 185.00 293.66 1.59 185.00 293.66 369.99 1.60 185.00 293.66 369.99 1.61 185.00 293.66 369.99 1.62 185.00 293.66 369.99 1.63 185.00 293.66 369.99 1.64 185.00 293.66 1.65 185.00 1.66 1.67 1.68 1.69 1.70 1.71 1.72 1.73 185.00 1.74 185.00 293.66 369.99 1.75 185.00 293.66 369.99 1.76 185.00 293.66 369.99 1.77 185.00 293.66 369.99 1.78 185.00 293.66 369.99 1.79 185.00 293.66 369.99 1.80 185.00 293.66 369.99 1.81 1.82 1.83 1.84 1.85 1.86 1.87 1.88 293.66 185.00 1.89 293.66 185.00 369.99 1.90 293.66 185.00 369.99 1.91 293.66 185.00 369.99 1.92 293.66 185.00 369.99 1.93 293.66 185.00 369.99 1.94 293.66 185.00 369.99 1.95 293.66 185.00 369.99 1.96 293.66 185.00 369.99 1.97 293.66 185.00 369.99 1.98 293.66 185.00 369.99 1.99 293.66 185.00 369.99 2.00 293.66 185.00 369.99 2.01 293.66 185.00 369.99 2.02 293.66 185.00 369.99 2.03 293.66 185.00 369.99 2.04 293.66 185.00 369.99 2.05 293.66 185.00 369.99 2.06 293.66 185.00 369.99 2.07 293.66 185.00 369.99 2.08 293.66 185.00 369.99 2.09 293.66 185.00 369.99 2.10 293.66 185.00 369.99 2.11 293.66 185.00 369.99 2.12 369.99 2.13 369.99 2.14 2.15 2.16 2.17 2.18 2.19 2.20 2.21 185.00 2.22 185.00 369.99 293.66 2.23 185.00 369.99 293.66 2.24 185.00 369.99 293.66 2.25 185.00 369.99 293.66 2.26 185.00 369.99 293.66 2.27 185.00 369.99 293.66 2.28 369.99 293.66 2.29 369.99 293.66 2.30 2.31 2.32 2.33 293.66 2.34 293.66 2.35 293.66 2.36 293.66 2.37 293.66 185.00 2.38 293.66 185.00 61.74 2.39 293.66 185.00 61.74 123.47 293.66 2.40 185.00 61.74 123.47 293.66 2.41 185.00 61.74 123.47 293.66 2.42 185.00 61.74 123.47 293.66 2.43 185.00 61.74 123.47 293.66 2.44 61.74 123.47 293.66 2.45 123.47 293.66 2.46 293.66 2.47 2.48 329.63 2.49 329.63 2.50 329.63 2.51 329.63 69.30 2.52 329.63 69.30 185.00 329.63 138.59 2.53 329.63 69.30 185.00 329.63 138.59 2.54 329.63 69.30 185.00 329.63 138.59 2.55 69.30 185.00 329.63 138.59 2.56 69.30 185.00 329.63 138.59 2.57 69.30 185.00 329.63 138.59 2.58 69.30 329.63 138.59 2.59 69.30 329.63 138.59 2.60 2.61 369.99 2.62 369.99 2.63 369.99 2.64 369.99 2.65 369.99 146.83 185.00 73.42 2.66 369.99 146.83 185.00 73.42 369.99 2.67 369.99 146.83 185.00 73.42 369.99 2.68 146.83 185.00 73.42 369.99 2.69 146.83 185.00 73.42 369.99 2.70 146.83 185.00 73.42 369.99 2.71 185.00 73.42 369.99 2.72 185.00 73.42 2.73 73.42 2.74 73.42 2.75 2.76 2.77 392.00 82.41 2.78 392.00 82.41 164.81 2.79 392.00 82.41 164.81 392.00 2.80 392.00 82.41 164.81 392.00 185.00 2.81 392.00 82.41 164.81 392.00 185.00 2.82 392.00 82.41 164.81 392.00 185.00 2.83 392.00 82.41 164.81 392.00 185.00 2.84 392.00 82.41 164.81 392.00 185.00 2.85 392.00 82.41 164.81 392.00 185.00 2.86 392.00 82.41 164.81 392.00 185.00 2.87 392.00 82.41 164.81 392.00 185.00 2.88 392.00 164.81 392.00 185.00 2.89 392.00 164.81 392.00 185.00 2.90 392.00 164.81 392.00 185.00 2.91 392.00 164.81 392.00 185.00 2.92 392.00 164.81 392.00 185.00 2.93 392.00 164.81 392.00 185.00 2.94 392.00 164.81 392.00 185.00 2.95 392.00 164.81 392.00 185.00 2.96 392.00 164.81 392.00 185.00 2.97 392.00 164.81 392.00 185.00 2.98 392.00 392.00 185.00 2.99 392.00 392.00 185.00 82.41 3.00 392.00 392.00 185.00 82.41 3.01 392.00 82.41 3.02 82.41 3.03 82.41 3.04 82.41 3.05 82.41 3.06 82.41 3.07 3.08 3.09 3.10 3.11 185.00 369.99 369.99 3.12 185.00 369.99 369.99 146.83 73.42 3.13 185.00 369.99 369.99 146.83 73.42 3.14 185.00 369.99 369.99 146.83 73.42 3.15 185.00 369.99 369.99 146.83 73.42 3.16 185.00 369.99 369.99 146.83 73.42 3.17 185.00 146.83 73.42 3.18 146.83 73.42 3.19 146.83 73.42 3.20 73.42 3.21 73.42 3.22 3.23 3.24 3.25 82.41 392.00 3.26 82.41 392.00 185.00 392.00 3.27 82.41 392.00 185.00 392.00 164.81 3.28 82.41 392.00 185.00 392.00 164.81 3.29 82.41 392.00 185.00 392.00 164.81 3.30 82.41 392.00 185.00 392.00 164.81 3.31 82.41 392.00 185.00 392.00 164.81 3.32 82.41 392.00 185.00 392.00 164.81 3.33 82.41 392.00 164.81 3.34 164.81 3.35 164.81 3.36 3.37 3.38 3.39 369.99 3.40 369.99 73.42 369.99 3.41 369.99 73.42 369.99 146.83 185.00 3.42 369.99 73.42 369.99 146.83 185.00 3.43 369.99 73.42 369.99 146.83 185.00 3.44 369.99 73.42 369.99 146.83 185.00 3.45 369.99 73.42 369.99 146.83 185.00 3.46 73.42 369.99 146.83 3.47 73.42 3.48 73.42 3.49 3.50 3.51 3.52 3.53 3.54 61.74 3.55 61.74 123.47 3.56 61.74 123.47 493.88 3.57 61.74 123.47 493.88 185.00 293.66 369.99 493.88 3.58 61.74 123.47 493.88 185.00 293.66 369.99 493.88 3.59 123.47 493.88 185.00 293.66 369.99 493.88 3.60 123.47 493.88 185.00 293.66 369.99 493.88 3.61 123.47 493.88 185.00 293.66 369.99 493.88 3.62 185.00 293.66 369.99 493.88 3.63 3.64 3.65 3.66 3.67 3.68 3.69 46.25 3.70 46.25 3.71 46.25 92.50 554.37 3.72 46.25 92.50 554.37 554.37 369.99 3.73 46.25 92.50 554.37 554.37 369.99 3.74 46.25 92.50 554.37 554.37 369.99 277.18 466.16 3.75 46.25 92.50 554.37 554.37 369.99 277.18 466.16 3.76 46.25 92.50 554.37 554.37 369.99 277.18 466.16 3.77 46.25 92.50 554.37 554.37 369.99 277.18 466.16 3.78 46.25 92.50 554.37 554.37 369.99 277.18 466.16 3.79 46.25 92.50 554.37 554.37 369.99 277.18 466.16 3.80 46.25 92.50 554.37 554.37 369.99 277.18 466.16 3.81 46.25 92.50 554.37 554.37 369.99 277.18 466.16 3.82 46.25 92.50 554.37 369.99 277.18 466.16 3.83 46.25 92.50 554.37 369.99 277.18 466.16 3.84 46.25 92.50 554.37 369.99 277.18 466.16 3.85 46.25 92.50 554.37 369.99 277.18 466.16 3.86 46.25 92.50 554.37 369.99 277.18 466.16 3.87 46.25 92.50 554.37 369.99 277.18 466.16 3.88 46.25 92.50 554.37 369.99 3.89 46.25 92.50 554.37 3.90 46.25 92.50 554.37 3.91 46.25 92.50 554.37 3.92 46.25 92.50 554.37 3.93 46.25 92.50 554.37 3.94 46.25 92.50 554.37 3.95 46.25 92.50 554.37 3.96 46.25 92.50 554.37 3.97 46.25 92.50 554.37 3.98 46.25 92.50 554.37 3.99 46.25 92.50 554.37 4.00 46.25 92.50 554.37 4.01 46.25 92.50 554.37 4.02 46.25 92.50 554.37 4.03 46.25 92.50 4.04 92.50 4.05 92.50 4.06 92.50 4.07 4.08 4.09 4.10 4.11 4.12 4.13 4.14 739.99 4.15 739.99 46.25 4.16 739.99 46.25 4.17 739.99 46.25 92.50 4.18 739.99 46.25 92.50 4.19 739.99 46.25 92.50 277.18 739.99 369.99 4.20 739.99 46.25 92.50 277.18 739.99 369.99 4.21 739.99 46.25 92.50 277.18 739.99 369.99 4.22 739.99 46.25 92.50 277.18 739.99 369.99 4.23 739.99 46.25 92.50 277.18 739.99 369.99 4.24 739.99 46.25 92.50 277.18 739.99 369.99 4.25 739.99 46.25 92.50 277.18 739.99 369.99 4.26 739.99 46.25 92.50 277.18 739.99 369.99 4.27 739.99 46.25 92.50 277.18 739.99 369.99 4.28 739.99 46.25 92.50 277.18 739.99 369.99 4.29 739.99 46.25 92.50 277.18 739.99 369.99 4.30 739.99 46.25 92.50 277.18 739.99 369.99 4.31 739.99 46.25 92.50 277.18 739.99 369.99 4.32 739.99 46.25 92.50 277.18 739.99 369.99 4.33 739.99 46.25 92.50 277.18 739.99 369.99 4.34 739.99 46.25 92.50 277.18 739.99 369.99 4.35 739.99 46.25 92.50 277.18 739.99 369.99 4.36 739.99 46.25 92.50 277.18 739.99 369.99 4.37 739.99 46.25 92.50 277.18 739.99 369.99 4.38 739.99 46.25 92.50 277.18 739.99 369.99 4.39 739.99 46.25 92.50 277.18 369.99 4.40 739.99 46.25 92.50 277.18 369.99 4.41 739.99 46.25 92.50 277.18 369.99 4.42 739.99 46.25 92.50 277.18 4.43 739.99 46.25 92.50 277.18 4.44 739.99 46.25 92.50 4.45 739.99 46.25 92.50 4.46 739.99 46.25 92.50 4.47 739.99 46.25 92.50 4.48 739.99 46.25 92.50 4.49 739.99 46.25 92.50 4.50 739.99 46.25 92.50 4.51 739.99 46.25 92.50 4.52 739.99 46.25 92.50 4.53 739.99 46.25 92.50 4.54 739.99 46.25 92.50 4.55 739.99 46.25 92.50 4.56 739.99 46.25 92.50 4.57 739.99 46.25 4.58 739.99 46.25 4.59 739.99 4.60 739.99 4.61 739.99 4.62 4.63 4.64 4.65 4.66 4.67 4.68 61.74 123.47 4.69 61.74 123.47 587.33 493.88 293.66 4.70 61.74 123.47 587.33 493.88 293.66 369.99 4.71 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.72 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.73 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.74 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.75 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.76 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.77 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.78 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.79 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.80 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.81 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.82 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.83 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.84 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.85 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.86 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.87 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.88 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.89 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.90 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.91 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.92 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.93 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.94 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.95 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.96 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.97 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.98 61.74 123.47 587.33 493.88 293.66 369.99 587.33 4.99 61.74 123.47 587.33 493.88 293.66 369.99 587.33 5.00 61.74 123.47 587.33 493.88 293.66 369.99 587.33 5.01 61.74 123.47 587.33 493.88 293.66 369.99 587.33 5.02 61.74 123.47 587.33 493.88 293.66 369.99 587.33 5.03 61.74 123.47 587.33 493.88 293.66 369.99 587.33 5.04 61.74 123.47 587.33 493.88 369.99 587.33 5.05 61.74 123.47 587.33 493.88 587.33 5.06 61.74 123.47 587.33 493.88 587.33 5.07 61.74 123.47 5.08 61.74 123.47 5.09 61.74 123.47 5.10 123.47 5.11 123.47 5.12 5.13 5.14 5.15 5.16 5.17 5.18 5.19 5.20 5.21 5.22 493.88 146.83 349.23 73.42 493.88 246.94 5.23 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.24 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.25 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.26 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.27 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.28 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.29 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.30 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.31 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.32 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.33 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.34 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.35 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.36 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.37 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.38 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.39 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.40 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.41 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.42 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.43 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.44 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.45 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.46 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.47 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.48 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.49 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.50 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.51 493.88 146.83 349.23 73.42 493.88 246.94 415.30 5.52 146.83 349.23 73.42 493.88 246.94 415.30 5.53 146.83 349.23 73.42 493.88 415.30 5.54 146.83 73.42 493.88 415.30 5.55 146.83 73.42 493.88 415.30 5.56 146.83 73.42 493.88 415.30 5.57 146.83 73.42 493.88 5.58 146.83 73.42 493.88 5.59 146.83 73.42 493.88 5.60 146.83 493.88 5.61 146.83 493.88 5.62 493.88 5.63 493.88 5.64 493.88 5.65 493.88 5.66 5.67 5.68 5.69 5.70 5.71 5.72 5.73 277.18 5.74 277.18 233.08 185.00 369.99 92.50 5.75 277.18 233.08 185.00 369.99 92.50 369.99 5.76 277.18 233.08 185.00 369.99 92.50 369.99 5.77 277.18 233.08 185.00 369.99 92.50 369.99 5.78 277.18 233.08 185.00 369.99 92.50 369.99 5.79 277.18 233.08 185.00 369.99 92.50 369.99 5.80 277.18 233.08 185.00 369.99 92.50 369.99 5.81 277.18 233.08 185.00 369.99 92.50 369.99 5.82 277.18 233.08 185.00 369.99 92.50 369.99 5.83 277.18 233.08 185.00 369.99 92.50 369.99 5.84 277.18 233.08 185.00 369.99 92.50 369.99 5.85 277.18 233.08 185.00 369.99 92.50 369.99 5.86 277.18 233.08 185.00 369.99 92.50 369.99 5.87 277.18 233.08 185.00 369.99 92.50 369.99 5.88 277.18 233.08 185.00 369.99 92.50 369.99 5.89 277.18 233.08 185.00 369.99 92.50 369.99 5.90 277.18 233.08 185.00 369.99 92.50 369.99 5.91 277.18 233.08 185.00 369.99 92.50 369.99 5.92 277.18 233.08 185.00 369.99 92.50 369.99 5.93 277.18 233.08 185.00 369.99 92.50 369.99 5.94 277.18 233.08 185.00 369.99 92.50 369.99 5.95 277.18 233.08 185.00 369.99 92.50 369.99 5.96 277.18 233.08 185.00 369.99 92.50 369.99 5.97 277.18 233.08 185.00 369.99 92.50 369.99 5.98 277.18 233.08 185.00 369.99 92.50 369.99 5.99 277.18 233.08 185.00 369.99 92.50 369.99 6.00 277.18 233.08 185.00 369.99 92.50 369.99 6.01 277.18 233.08 185.00 369.99 92.50 369.99 6.02 277.18 233.08 185.00 369.99 92.50 369.99 6.03 277.18 233.08 185.00 369.99 92.50 369.99 6.04 277.18 233.08 185.00 369.99 92.50 369.99 6.05 277.18 233.08 185.00 369.99 92.50 369.99 6.06 277.18 233.08 185.00 92.50 369.99 6.07 233.08 185.00 92.50 369.99 6.08 233.08 185.00 92.50 369.99 6.09 185.00 92.50 369.99 6.10 185.00 92.50 369.99 6.11 185.00 92.50 369.99 6.12 185.00 369.99 6.13 185.00 369.99 6.14 369.99 6.15 6.16 6.17 6.18 6.19 6.20 6.21 6.22 6.23 6.24 61.74 6.25 61.74 123.47 6.26 61.74 123.47 6.27 61.74 123.47 185.00 293.66 293.66 6.28 61.74 123.47 185.00 293.66 293.66 6.29 61.74 123.47 185.00 293.66 293.66 6.30 61.74 123.47 185.00 293.66 293.66 6.31 61.74 123.47 185.00 293.66 293.66 6.32 61.74 123.47 185.00 293.66 293.66 6.33 61.74 185.00 293.66 293.66 6.34 61.74 293.66 293.66 6.35 293.66 6.36 293.66 6.37 293.66 6.38 6.39 6.40 6.41 6.42 138.59 69.30 6.43 138.59 69.30 6.44 138.59 69.30 185.00 329.63 6.45 138.59 69.30 185.00 329.63 6.46 138.59 69.30 185.00 329.63 329.63 6.47 138.59 69.30 185.00 329.63 329.63 6.48 138.59 69.30 185.00 329.63 329.63 6.49 138.59 69.30 329.63 329.63 6.50 329.63 329.63 6.51 329.63 6.52 329.63 6.53 329.63 6.54 6.55 6.56 6.57 6.58 146.83 73.42 6.59 146.83 73.42 185.00 369.99 6.60 146.83 73.42 185.00 369.99 6.61 146.83 73.42 185.00 369.99 6.62 146.83 73.42 185.00 369.99 6.63 146.83 73.42 185.00 369.99 369.99 6.64 146.83 73.42 185.00 369.99 369.99 6.65 146.83 73.42 185.00 369.99 369.99 6.66 369.99 6.67 369.99 6.68 369.99 6.69 369.99 6.70 6.71 6.72 6.73 82.41 164.81 6.74 82.41 164.81 6.75 82.41 164.81 185.00 6.76 82.41 164.81 185.00 6.77 82.41 164.81 185.00 392.00 6.78 82.41 164.81 185.00 392.00 6.79 82.41 164.81 185.00 392.00 6.80 82.41 164.81 185.00 392.00 6.81 82.41 164.81 185.00 392.00 392.00 6.82 82.41 164.81 185.00 392.00 392.00 6.83 82.41 164.81 185.00 392.00 392.00 6.84 82.41 164.81 185.00 392.00 392.00 6.85 82.41 164.81 185.00 392.00 392.00 6.86 82.41 164.81 185.00 392.00 392.00 6.87 82.41 164.81 185.00 392.00 392.00 6.88 82.41 164.81 185.00 392.00 392.00 6.89 82.41 164.81 185.00 392.00 392.00 6.90 82.41 164.81 185.00 392.00 392.00 6.91 82.41 164.81 185.00 392.00 392.00 6.92 82.41 164.81 185.00 392.00 392.00 6.93 82.41 164.81 185.00 392.00 392.00 6.94 82.41 164.81 185.00 392.00 392.00 6.95 82.41 164.81 185.00 392.00 392.00 6.96 82.41 164.81 185.00 392.00 392.00 6.97 82.41 164.81 185.00 392.00 392.00 6.98 82.41 164.81 185.00 392.00 392.00 6.99 82.41 164.81 185.00 392.00 392.00 7.00 82.41 164.81 185.00 392.00 392.00 7.01 82.41 164.81 392.00 392.00 7.02 82.41 164.81 392.00 392.00 7.03 392.00 392.00 7.04 392.00 392.00 7.05 392.00 7.06 392.00 7.07 392.00 7.08 392.00 7.09 392.00 7.10 7.11 7.12 369.99 73.42 7.13 369.99 73.42 185.00 146.83 7.14 369.99 73.42 185.00 146.83 7.15 369.99 73.42 185.00 146.83 369.99 7.16 369.99 73.42 185.00 146.83 369.99 7.17 369.99 73.42 185.00 146.83 369.99 7.18 369.99 73.42 146.83 369.99 7.19 73.42 146.83 369.99 7.20 73.42 146.83 369.99 7.21 146.83 369.99 7.22 7.23 7.24 7.25 7.26 7.27 7.28 7.29 392.00 82.41 7.30 392.00 82.41 164.81 185.00 7.31 392.00 82.41 164.81 185.00 7.32 392.00 82.41 164.81 185.00 7.33 392.00 82.41 164.81 185.00 392.00 7.34 392.00 82.41 164.81 185.00 392.00 7.35 392.00 82.41 164.81 392.00 7.36 392.00 82.41 164.81 392.00 7.37 82.41 164.81 392.00 7.38 82.41 392.00 7.39 392.00 7.40 392.00 7.41 7.42 7.43 7.44 185.00 7.45 185.00 73.42 369.99 146.83 369.99 7.46 185.00 73.42 369.99 146.83 369.99 7.47 185.00 73.42 369.99 146.83 369.99 7.48 185.00 73.42 369.99 146.83 369.99 7.49 185.00 73.42 369.99 146.83 369.99 7.50 185.00 73.42 369.99 146.83 369.99 7.51 185.00 73.42 369.99 146.83 369.99 7.52 185.00 73.42 146.83 7.53 73.42 146.83 7.54 7.55 7.56 7.57 7.58 293.66 7.59 293.66 7.60 293.66 493.88 123.47 7.61 293.66 493.88 123.47 61.74 493.88 7.62 293.66 493.88 123.47 61.74 493.88 369.99 7.63 293.66 493.88 123.47 61.74 493.88 369.99 7.64 293.66 493.88 123.47 61.74 493.88 369.99 7.65 293.66 493.88 123.47 61.74 493.88 369.99 7.66 293.66 493.88 123.47 61.74 493.88 369.99 7.67 293.66 493.88 123.47 61.74 493.88 369.99 7.68 493.88 61.74 493.88 7.69 7.70 7.71 7.72 7.73 7.74 55.00 7.75 55.00 110.00 7.76 55.00 110.00 554.37 7.77 55.00 110.00 554.37 7.78 55.00 110.00 554.37 277.18 369.99 554.37 7.79 55.00 110.00 554.37 277.18 369.99 554.37 7.80 55.00 110.00 554.37 277.18 369.99 554.37 7.81 55.00 110.00 554.37 277.18 369.99 554.37 7.82 55.00 110.00 554.37 277.18 369.99 554.37 7.83 55.00 110.00 554.37 277.18 369.99 554.37 7.84 55.00 110.00 554.37 277.18 369.99 554.37 7.85 55.00 110.00 554.37 277.18 369.99 554.37 7.86 55.00 110.00 554.37 277.18 369.99 554.37 7.87 55.00 110.00 554.37 277.18 369.99 554.37 7.88 55.00 110.00 554.37 277.18 369.99 554.37 7.89 55.00 110.00 554.37 277.18 369.99 554.37 7.90 55.00 110.00 554.37 277.18 369.99 554.37 7.91 55.00 110.00 554.37 277.18 369.99 554.37 7.92 55.00 110.00 554.37 277.18 369.99 554.37 7.93 55.00 110.00 554.37 277.18 369.99 554.37 7.94 55.00 110.00 554.37 277.18 369.99 554.37 7.95 55.00 110.00 554.37 277.18 369.99 554.37 7.96 55.00 110.00 554.37 277.18 369.99 554.37 7.97 55.00 110.00 554.37 277.18 369.99 554.37 7.98 55.00 110.00 554.37 277.18 554.37 7.99 55.00 110.00 554.37 277.18 554.37 8.00 55.00 110.00 554.37 277.18 554.37 8.01 55.00 110.00 554.37 277.18 8.02 55.00 110.00 554.37 277.18 8.03 55.00 110.00 554.37 277.18 8.04 55.00 110.00 554.37 277.18 8.05 55.00 110.00 554.37 277.18 8.06 55.00 110.00 554.37 8.07 110.00 554.37 8.08 110.00 554.37 8.09 110.00 554.37 8.10 110.00 8.11 110.00 8.12 8.13 8.14 8.15 8.16 8.17 8.18 8.19 8.20 8.21 8.22 46.25 8.23 46.25 739.99 92.50 369.99 8.24 46.25 739.99 92.50 369.99 440.00 8.25 46.25 739.99 92.50 369.99 440.00 739.99 554.37 8.26 46.25 739.99 92.50 369.99 440.00 739.99 554.37 8.27 46.25 739.99 92.50 369.99 440.00 739.99 554.37 8.28 46.25 739.99 92.50 369.99 440.00 739.99 554.37 8.29 46.25 739.99 92.50 369.99 440.00 739.99 554.37 8.30 46.25 739.99 92.50 369.99 440.00 739.99 554.37 8.31 46.25 739.99 92.50 369.99 440.00 739.99 554.37 8.32 46.25 739.99 92.50 369.99 440.00 739.99 554.37 8.33 46.25 739.99 92.50 369.99 440.00 739.99 554.37 8.34 46.25 739.99 92.50 369.99 440.00 739.99 554.37 8.35 46.25 739.99 92.50 369.99 440.00 739.99 554.37 8.36 46.25 739.99 92.50 369.99 440.00 739.99 554.37 8.37 46.25 739.99 92.50 369.99 440.00 739.99 554.37 8.38 46.25 739.99 92.50 369.99 440.00 739.99 554.37 8.39 46.25 739.99 92.50 369.99 440.00 739.99 554.37 8.40 46.25 92.50 369.99 440.00 739.99 554.37 8.41 46.25 92.50 369.99 440.00 739.99 554.37 8.42 46.25 92.50 369.99 440.00 739.99 554.37 8.43 46.25 92.50 369.99 440.00 739.99 554.37 8.44 46.25 92.50 440.00 739.99 8.45 46.25 92.50 440.00 739.99 8.46 46.25 92.50 440.00 739.99 8.47 46.25 92.50 440.00 739.99 8.48 46.25 92.50 440.00 739.99 8.49 46.25 92.50 440.00 739.99 8.50 46.25 92.50 739.99 8.51 46.25 92.50 739.99 8.52 46.25 92.50 739.99 8.53 46.25 739.99 8.54 46.25 739.99 8.55 46.25 739.99 8.56 46.25 739.99 8.57 46.25 739.99 8.58 46.25 739.99 8.59 46.25 739.99 8.60 739.99 8.61 739.99 8.62 8.63 8.64 8.65 8.66 8.67 8.68 8.69 8.70 8.71 8.72 8.73 587.33 8.74 587.33 61.74 293.66 587.33 8.75 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.76 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.77 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.78 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.79 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.80 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.81 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.82 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.83 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.84 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.85 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.86 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.87 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.88 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.89 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.90 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.91 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.92 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.93 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.94 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.95 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.96 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.97 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.98 587.33 61.74 293.66 587.33 123.47 369.99 493.88 8.99 587.33 61.74 293.66 587.33 123.47 369.99 493.88 9.00 587.33 61.74 293.66 587.33 123.47 369.99 9.01 587.33 61.74 293.66 587.33 123.47 369.99 9.02 587.33 61.74 123.47 9.03 587.33 61.74 123.47 9.04 587.33 61.74 123.47 9.05 587.33 61.74 123.47 9.06 587.33 61.74 123.47 9.07 587.33 61.74 123.47 9.08 587.33 61.74 123.47 9.09 587.33 123.47 9.10 587.33 123.47 9.11 587.33 123.47 9.12 587.33 123.47 9.13 587.33 123.47 9.14 587.33 9.15 587.33 9.16 587.33 9.17 9.18 9.19 9.20 9.21 9.22 9.23 9.24 246.94 9.25 246.94 207.65 349.23 311.13 9.26 246.94 207.65 349.23 311.13 349.23 9.27 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.28 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.29 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.30 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.31 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.32 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.33 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.34 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.35 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.36 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.37 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.38 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.39 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.40 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.41 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.42 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.43 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.44 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.45 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.46 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.47 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.48 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.49 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.50 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.51 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.52 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.53 246.94 207.65 349.23 311.13 349.23 138.59 69.30 9.54 349.23 311.13 349.23 138.59 69.30 9.55 349.23 311.13 349.23 138.59 69.30 9.56 311.13 349.23 138.59 69.30 9.57 349.23 138.59 69.30 9.58 349.23 138.59 69.30 9.59 349.23 138.59 69.30 9.60 349.23 138.59 69.30 9.61 349.23 138.59 69.30 9.62 349.23 138.59 69.30 9.63 349.23 138.59 69.30 9.64 138.59 9.65 9.66 9.67 9.68 9.69 9.70 9.71 9.72 9.73 9.74 9.75 277.18 9.76 277.18 369.99 9.77 277.18 369.99 233.08 92.50 185.00 9.78 277.18 369.99 233.08 92.50 185.00 9.79 277.18 369.99 233.08 92.50 185.00 9.80 277.18 369.99 233.08 92.50 185.00 369.99 9.81 277.18 369.99 233.08 92.50 185.00 369.99 9.82 277.18 369.99 233.08 92.50 185.00 369.99 9.83 277.18 369.99 233.08 92.50 185.00 369.99 9.84 277.18 369.99 233.08 92.50 185.00 369.99 9.85 277.18 369.99 233.08 92.50 185.00 369.99 9.86 277.18 369.99 233.08 92.50 185.00 369.99 9.87 277.18 369.99 233.08 92.50 185.00 369.99 9.88 277.18 369.99 233.08 92.50 185.00 369.99 9.89 277.18 369.99 233.08 92.50 185.00 369.99 9.90 277.18 369.99 233.08 92.50 185.00 369.99 9.91 277.18 369.99 233.08 92.50 185.00 369.99 9.92 277.18 369.99 233.08 92.50 185.00 369.99 9.93 277.18 369.99 233.08 92.50 185.00 369.99 9.94 277.18 369.99 233.08 92.50 185.00 369.99 9.95 277.18 369.99 233.08 92.50 185.00 369.99 9.96 277.18 369.99 233.08 92.50 185.00 369.99 9.97 277.18 369.99 233.08 92.50 185.00 369.99 9.98 277.18 369.99 233.08 92.50 185.00 369.99 9.99 277.18 369.99 233.08 92.50 185.00 369.99 10.00 277.18 369.99 233.08 92.50 185.00 369.99 10.01 277.18 369.99 233.08 92.50 185.00 369.99 10.02 277.18 369.99 233.08 92.50 185.00 369.99 10.03 277.18 369.99 233.08 92.50 185.00 369.99 10.04 277.18 369.99 233.08 92.50 185.00 369.99 10.05 277.18 369.99 233.08 92.50 185.00 369.99 10.06 277.18 369.99 233.08 92.50 185.00 369.99 10.07 277.18 369.99 233.08 92.50 185.00 369.99 10.08 277.18 369.99 233.08 92.50 185.00 369.99 10.09 185.00 369.99 10.10 185.00 369.99 10.11 369.99 10.12 369.99 10.13 369.99 10.14 369.99 10.15 369.99 10.16 10.17 10.18 10.19 10.20 10.21 10.22 10.23 10.24 10.25 10.26 10.27 10.28 10.29 61.74 10.30 61.74 123.47 10.31 61.74 123.47 10.32 61.74 123.47 10.33 61.74 123.47 10.34 61.74 123.47 10.35 61.74 123.47 10.36 61.74 123.47 293.66 10.37 61.74 123.47 293.66 185.00 10.38 123.47 293.66 185.00 10.39 293.66 185.00 10.40 293.66 185.00 293.66 10.41 293.66 185.00 293.66 10.42 293.66 185.00 293.66 10.43 185.00 293.66 10.44 293.66 10.45 293.66 10.46 293.66 69.30 10.47 69.30 138.59 10.48 69.30 138.59 10.49 69.30 138.59 10.50 69.30 138.59 10.51 69.30 138.59 10.52 69.30 138.59 185.00 10.53 69.30 138.59 185.00 329.63 329.63 10.54 69.30 138.59 185.00 329.63 329.63 10.55 138.59 185.00 329.63 329.63 10.56 185.00 329.63 329.63 10.57 185.00 329.63 329.63 10.58 185.00 329.63 329.63 10.59 329.63 329.63 10.60 329.63 10.61 10.62 10.63 10.64 73.42 10.65 73.42 146.83 10.66 73.42 146.83 185.00 369.99 10.67 73.42 146.83 185.00 369.99 10.68 73.42 146.83 185.00 369.99 10.69 73.42 146.83 185.00 369.99 369.99 10.70 73.42 146.83 185.00 369.99 369.99 10.71 73.42 146.83 185.00 369.99 369.99 10.72 73.42 146.83 185.00 369.99 10.73 73.42 369.99 10.74 369.99 10.75 369.99 10.76 369.99 10.77 10.78 10.79 10.80 392.00 10.81 392.00 185.00 10.82 392.00 185.00 82.41 164.81 10.83 392.00 185.00 82.41 164.81 10.84 392.00 185.00 82.41 164.81 10.85 392.00 185.00 82.41 164.81 10.86 392.00 185.00 82.41 164.81 392.00 10.87 392.00 185.00 82.41 164.81 392.00 10.88 392.00 185.00 82.41 164.81 392.00 10.89 392.00 185.00 82.41 164.81 392.00 10.90 392.00 185.00 82.41 164.81 392.00 10.91 392.00 185.00 82.41 164.81 392.00 10.92 392.00 185.00 82.41 164.81 392.00 10.93 392.00 185.00 82.41 164.81 392.00 10.94 392.00 185.00 82.41 164.81 392.00 10.95 392.00 185.00 82.41 164.81 392.00 10.96 392.00 185.00 82.41 164.81 392.00 10.97 392.00 185.00 82.41 164.81 392.00 10.98 392.00 185.00 82.41 164.81 392.00 10.99 392.00 185.00 82.41 164.81 392.00 11.00 392.00 185.00 82.41 164.81 392.00 11.01 392.00 185.00 82.41 164.81 392.00 11.02 82.41 164.81 392.00 11.03 82.41 164.81 392.00 11.04 82.41 164.81 392.00 11.05 82.41 164.81 392.00 11.06 82.41 164.81 392.00 11.07 82.41 164.81 392.00 11.08 82.41 164.81 392.00 11.09 82.41 164.81 392.00 11.10 164.81 392.00 11.11 392.00 185.00 369.99 11.12 185.00 369.99 11.13 185.00 369.99 73.42 11.14 185.00 369.99 73.42 146.83 11.15 185.00 369.99 73.42 146.83 11.16 185.00 369.99 73.42 146.83 369.99 11.17 185.00 369.99 73.42 146.83 369.99 11.18 73.42 146.83 369.99 11.19 73.42 146.83 369.99 11.20 73.42 146.83 369.99 11.21 73.42 146.83 369.99 11.22 369.99 11.23 369.99 11.24 369.99 11.25 11.26 392.00 185.00 11.27 392.00 185.00 11.28 392.00 185.00 11.29 392.00 185.00 82.41 164.81 11.30 392.00 185.00 82.41 164.81 11.31 392.00 185.00 82.41 164.81 392.00 11.32 392.00 185.00 82.41 164.81 392.00 11.33 392.00 82.41 164.81 392.00 11.34 82.41 164.81 392.00 11.35 82.41 164.81 392.00 11.36 82.41 164.81 392.00 11.37 82.41 392.00 11.38 392.00 11.39 392.00 11.40 392.00 369.99 11.41 369.99 185.00 11.42 369.99 185.00 11.43 369.99 185.00 73.42 369.99 146.83 11.44 369.99 185.00 73.42 369.99 146.83 11.45 369.99 185.00 73.42 369.99 146.83 11.46 369.99 185.00 73.42 369.99 146.83 11.47 73.42 369.99 146.83 11.48 73.42 369.99 146.83 11.49 73.42 369.99 146.83 11.50 73.42 146.83 11.51 73.42 146.83 11.52 73.42 146.83 11.53 73.42 11.54 73.42 11.55 73.42 11.56 73.42 123.47 11.57 123.47 61.74 185.00 293.66 369.99 493.88 11.58 123.47 61.74 185.00 293.66 369.99 493.88 11.59 123.47 61.74 185.00 293.66 369.99 493.88 493.88 11.60 123.47 61.74 185.00 293.66 369.99 493.88 493.88 11.61 123.47 61.74 185.00 293.66 369.99 493.88 493.88 11.62 123.47 61.74 185.00 293.66 369.99 493.88 493.88 11.63 123.47 61.74 493.88 11.64 123.47 61.74 493.88 11.65 123.47 61.74 493.88 11.66 123.47 61.74 493.88 11.67 123.47 61.74 11.68 123.47 61.74 11.69 11.70 11.71 11.72 11.73 11.74 11.75 11.76 554.37 11.77 554.37 46.25 11.78 554.37 46.25 92.50 11.79 554.37 46.25 92.50 11.80 554.37 46.25 92.50 11.81 554.37 46.25 92.50 554.37 11.82 554.37 46.25 92.50 554.37 369.99 11.83 554.37 46.25 92.50 554.37 369.99 277.18 466.16 11.84 554.37 46.25 92.50 554.37 369.99 277.18 466.16 11.85 554.37 46.25 92.50 554.37 369.99 277.18 466.16 11.86 554.37 46.25 92.50 554.37 369.99 277.18 466.16 11.87 554.37 46.25 92.50 554.37 369.99 277.18 466.16 11.88 554.37 46.25 92.50 554.37 369.99 277.18 466.16 11.89 554.37 46.25 92.50 554.37 369.99 277.18 466.16 11.90 554.37 46.25 92.50 554.37 369.99 277.18 466.16 11.91 554.37 46.25 92.50 369.99 277.18 466.16 11.92 554.37 46.25 92.50 369.99 277.18 466.16 11.93 554.37 46.25 92.50 369.99 277.18 466.16 11.94 554.37 46.25 92.50 369.99 277.18 466.16 11.95 554.37 46.25 92.50 369.99 277.18 466.16 11.96 554.37 46.25 92.50 369.99 277.18 466.16 11.97 554.37 46.25 92.50 369.99 11.98 554.37 46.25 92.50 11.99 554.37 46.25 92.50 12.00 554.37 46.25 92.50 12.01 554.37 46.25 92.50 12.02 554.37 46.25 92.50 12.03 554.37 46.25 92.50 12.04 554.37 46.25 92.50 12.05 554.37 46.25 92.50 12.06 554.37 46.25 92.50 12.07 554.37 46.25 92.50 12.08 554.37 46.25 92.50 12.09 554.37 46.25 92.50 12.10 554.37 46.25 92.50 12.11 554.37 46.25 92.50 12.12 554.37 92.50 12.13 554.37 92.50 12.14 12.15 12.16 12.17 12.18 12.19 12.20 12.21 12.22 12.23 12.24 12.25 46.25 12.26 46.25 92.50 12.27 46.25 92.50 739.99 12.28 46.25 92.50 739.99 277.18 739.99 12.29 46.25 92.50 739.99 277.18 739.99 369.99 12.30 46.25 92.50 739.99 277.18 739.99 369.99 12.31 46.25 92.50 739.99 277.18 739.99 369.99 12.32 46.25 92.50 739.99 277.18 739.99 369.99 12.33 46.25 92.50 739.99 277.18 739.99 369.99 12.34 46.25 92.50 739.99 277.18 739.99 369.99 12.35 46.25 92.50 739.99 277.18 739.99 369.99 12.36 46.25 92.50 739.99 277.18 739.99 369.99 12.37 46.25 92.50 739.99 277.18 739.99 369.99 12.38 46.25 92.50 739.99 277.18 739.99 369.99 12.39 46.25 92.50 739.99 277.18 739.99 369.99 12.40 46.25 92.50 739.99 277.18 739.99 369.99 12.41 46.25 92.50 739.99 277.18 739.99 369.99 12.42 46.25 92.50 739.99 277.18 739.99 369.99 12.43 46.25 92.50 739.99 277.18 739.99 369.99 12.44 46.25 92.50 739.99 277.18 739.99 369.99 12.45 46.25 92.50 739.99 277.18 739.99 369.99 12.46 46.25 92.50 739.99 277.18 739.99 369.99 12.47 46.25 92.50 739.99 277.18 739.99 369.99 12.48 46.25 92.50 739.99 277.18 369.99 12.49 46.25 92.50 739.99 277.18 369.99 12.50 46.25 92.50 739.99 277.18 369.99 12.51 46.25 92.50 739.99 277.18 369.99 12.52 46.25 92.50 739.99 277.18 12.53 46.25 92.50 739.99 277.18 12.54 46.25 92.50 739.99 12.55 46.25 92.50 739.99 12.56 46.25 92.50 739.99 12.57 46.25 92.50 739.99 12.58 46.25 92.50 739.99 12.59 46.25 92.50 739.99 12.60 46.25 92.50 739.99 12.61 46.25 92.50 739.99 12.62 46.25 92.50 739.99 12.63 46.25 92.50 739.99 12.64 46.25 92.50 739.99 12.65 46.25 92.50 739.99 12.66 92.50 739.99 12.67 739.99 12.68 739.99 12.69 739.99 12.70 12.71 12.72 12.73 12.74 12.75 12.76 61.74 12.77 61.74 123.47 12.78 61.74 123.47 587.33 12.79 61.74 123.47 587.33 493.88 293.66 369.99 12.80 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.81 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.82 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.83 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.84 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.85 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.86 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.87 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.88 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.89 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.90 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.91 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.92 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.93 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.94 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.95 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.96 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.97 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.98 61.74 123.47 587.33 493.88 293.66 369.99 587.33 12.99 61.74 123.47 587.33 493.88 293.66 369.99 587.33 13.00 61.74 123.47 587.33 493.88 293.66 369.99 587.33 13.01 61.74 123.47 587.33 493.88 293.66 369.99 587.33 13.02 61.74 123.47 587.33 493.88 293.66 369.99 587.33 13.03 61.74 123.47 587.33 493.88 293.66 369.99 587.33 13.04 61.74 123.47 587.33 493.88 293.66 369.99 587.33 13.05 61.74 123.47 587.33 493.88 293.66 369.99 587.33 13.06 61.74 123.47 587.33 493.88 293.66 369.99 587.33 13.07 61.74 123.47 587.33 493.88 293.66 369.99 587.33 13.08 61.74 123.47 587.33 493.88 293.66 369.99 587.33 13.09 61.74 123.47 587.33 493.88 293.66 369.99 587.33 13.10 61.74 123.47 587.33 493.88 293.66 369.99 587.33 13.11 61.74 123.47 587.33 493.88 293.66 369.99 587.33 13.12 61.74 123.47 587.33 493.88 293.66 369.99 587.33 13.13 61.74 123.47 587.33 493.88 293.66 369.99 587.33 13.14 61.74 123.47 587.33 493.88 587.33 13.15 61.74 123.47 587.33 493.88 587.33 13.16 61.74 123.47 587.33 13.17 61.74 123.47 587.33 13.18 61.74 123.47 587.33 13.19 61.74 123.47 587.33 13.20 61.74 123.47 587.33 13.21 61.74 123.47 13.22 123.47 13.23 13.24 13.25 13.26 13.27 13.28 13.29 13.30 13.31 493.88 349.23 146.83 13.32 493.88 349.23 146.83 73.42 246.94 415.30 13.33 493.88 349.23 146.83 73.42 246.94 415.30 13.34 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.35 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.36 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.37 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.38 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.39 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.40 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.41 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.42 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.43 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.44 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.45 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.46 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.47 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.48 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.49 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.50 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.51 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.52 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.53 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.54 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.55 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.56 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.57 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.58 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.59 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.60 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.61 493.88 349.23 146.83 73.42 246.94 415.30 493.88 13.62 349.23 146.83 73.42 246.94 415.30 493.88 13.63 349.23 146.83 73.42 415.30 493.88 13.64 146.83 73.42 415.30 493.88 13.65 146.83 73.42 415.30 493.88 13.66 146.83 73.42 493.88 13.67 146.83 73.42 493.88 13.68 146.83 73.42 493.88 13.69 146.83 73.42 493.88 13.70 146.83 493.88 13.71 146.83 493.88 13.72 146.83 493.88 13.73 493.88 13.74 493.88 13.75 13.76 13.77 13.78 13.79 13.80 13.81 13.82 13.83 277.18 233.08 13.84 277.18 233.08 369.99 13.85 277.18 233.08 369.99 185.00 13.86 277.18 233.08 369.99 185.00 13.87 277.18 233.08 369.99 185.00 369.99 13.88 277.18 233.08 369.99 185.00 369.99 13.89 277.18 233.08 369.99 185.00 369.99 92.50 13.90 277.18 233.08 369.99 185.00 369.99 92.50 13.91 277.18 233.08 369.99 185.00 369.99 92.50 13.92 277.18 233.08 369.99 185.00 369.99 92.50 13.93 277.18 233.08 369.99 185.00 369.99 92.50 13.94 277.18 233.08 369.99 185.00 369.99 92.50 13.95 277.18 233.08 369.99 185.00 369.99 92.50 13.96 277.18 233.08 369.99 185.00 369.99 92.50 13.97 277.18 233.08 369.99 185.00 369.99 92.50 13.98 277.18 233.08 369.99 185.00 369.99 92.50 13.99 277.18 233.08 369.99 185.00 369.99 92.50 14.00 277.18 233.08 369.99 185.00 369.99 92.50 14.01 277.18 233.08 369.99 185.00 369.99 92.50 14.02 277.18 233.08 369.99 185.00 369.99 92.50 14.03 277.18 233.08 369.99 185.00 369.99 92.50 14.04 277.18 233.08 369.99 185.00 369.99 92.50 14.05 277.18 233.08 369.99 185.00 369.99 92.50 14.06 277.18 233.08 369.99 185.00 369.99 92.50 14.07 277.18 233.08 369.99 185.00 369.99 92.50 14.08 277.18 233.08 369.99 185.00 369.99 92.50 14.09 277.18 233.08 369.99 185.00 369.99 92.50 14.10 277.18 233.08 369.99 185.00 369.99 92.50 14.11 277.18 233.08 369.99 185.00 369.99 92.50 14.12 277.18 233.08 369.99 185.00 369.99 92.50 14.13 277.18 233.08 369.99 185.00 369.99 92.50 14.14 277.18 233.08 369.99 185.00 369.99 92.50 14.15 277.18 233.08 185.00 369.99 92.50 14.16 277.18 233.08 185.00 369.99 92.50 14.17 233.08 185.00 369.99 92.50 14.18 185.00 369.99 92.50 14.19 185.00 369.99 92.50 14.20 185.00 369.99 92.50 14.21 185.00 369.99 92.50 14.22 369.99 92.50 14.23 369.99 92.50 14.24 369.99 92.50 14.25 369.99 14.26 369.99 14.27 369.99 14.28 14.29 14.30 14.31 14.32 14.33 14.34 14.35 14.36 185.00 293.66 14.37 185.00 293.66 61.74 14.38 185.00 293.66 61.74 123.47 14.39 185.00 293.66 61.74 123.47 14.40 185.00 293.66 61.74 123.47 14.41 185.00 293.66 61.74 123.47 293.66 14.42 185.00 293.66 61.74 123.47 293.66 14.43 293.66 61.74 123.47 293.66 14.44 61.74 123.47 293.66 14.45 61.74 123.47 293.66 14.46 123.47 293.66 14.47 293.66 14.48 14.49 14.50 14.51 14.52 14.53 185.00 329.63 14.54 185.00 329.63 14.55 185.00 329.63 138.59 14.56 185.00 329.63 138.59 69.30 14.57 185.00 329.63 138.59 69.30 329.63 14.58 185.00 329.63 138.59 69.30 329.63 14.59 329.63 138.59 69.30 329.63 14.60 138.59 69.30 329.63 14.61 138.59 69.30 329.63 14.62 138.59 69.30 329.63 14.63 138.59 69.30 329.63 14.64 329.63 14.65 14.66 14.67 14.68 185.00 14.69 185.00 369.99 14.70 185.00 369.99 73.42 14.71 185.00 369.99 73.42 146.83 14.72 185.00 369.99 73.42 146.83 14.73 185.00 369.99 73.42 146.83 369.99 14.74 185.00 369.99 73.42 146.83 369.99 14.75 73.42 146.83 369.99 14.76 73.42 146.83 369.99 14.77 73.42 146.83 369.99 14.78 73.42 146.83 369.99 14.79 73.42 146.83 369.99 14.80 73.42 14.81 14.82 14.83 14.84 185.00 14.85 185.00 14.86 185.00 392.00 14.87 185.00 392.00 82.41 14.88 185.00 392.00 82.41 164.81 14.89 185.00 392.00 82.41 164.81 14.90 185.00 392.00 82.41 164.81 392.00 14.91 185.00 392.00 82.41 164.81 392.00 14.92 185.00 392.00 82.41 164.81 392.00 14.93 185.00 392.00 82.41 164.81 392.00 14.94 185.00 392.00 82.41 164.81 392.00 14.95 185.00 392.00 82.41 164.81 392.00 14.96 185.00 392.00 82.41 164.81 392.00 14.97 185.00 392.00 82.41 164.81 392.00 14.98 185.00 392.00 82.41 164.81 392.00 14.99 185.00 392.00 82.41 164.81 392.00 15.00 185.00 392.00 82.41 164.81 392.00 15.01 185.00 392.00 82.41 164.81 392.00 15.02 185.00 392.00 82.41 164.81 392.00 15.03 185.00 392.00 82.41 164.81 392.00 15.04 185.00 392.00 82.41 164.81 392.00 15.05 185.00 392.00 82.41 164.81 392.00 15.06 185.00 392.00 82.41 164.81 392.00 15.07 185.00 392.00 82.41 164.81 392.00 15.08 185.00 392.00 82.41 164.81 392.00 15.09 185.00 392.00 82.41 164.81 392.00 15.10 185.00 392.00 82.41 164.81 392.00 15.11 392.00 82.41 164.81 392.00 15.12 392.00 82.41 164.81 392.00 15.13 392.00 82.41 164.81 392.00 15.14 82.41 164.81 392.00 15.15 82.41 392.00 15.16 392.00 15.17 392.00 15.18 392.00 15.19 15.20 15.21 369.99 15.22 369.99 185.00 15.23 369.99 185.00 73.42 15.24 369.99 185.00 73.42 15.25 369.99 185.00 73.42 146.83 15.26 369.99 185.00 73.42 146.83 369.99 15.27 369.99 185.00 73.42 146.83 369.99 15.28 369.99 73.42 146.83 369.99 15.29 73.42 146.83 369.99 15.30 73.42 146.83 369.99 15.31 73.42 146.83 369.99 15.32 73.42 146.83 369.99 15.33 369.99 15.34 15.35 15.36 15.37 15.38 15.39 392.00 15.40 392.00 185.00 82.41 15.41 392.00 185.00 82.41 164.81 15.42 392.00 185.00 82.41 164.81 392.00 15.43 392.00 185.00 82.41 164.81 392.00 15.44 392.00 82.41 164.81 392.00 15.45 392.00 82.41 164.81 392.00 15.46 82.41 164.81 392.00 15.47 82.41 164.81 392.00 15.48 82.41 164.81 392.00 15.49 82.41 164.81 15.50 82.41 15.51 15.52 15.53 73.42 15.54 73.42 185.00 146.83 369.99 15.55 73.42 185.00 146.83 369.99 369.99 15.56 73.42 185.00 146.83 369.99 369.99 15.57 73.42 185.00 146.83 369.99 369.99 15.58 73.42 185.00 146.83 369.99 369.99 15.59 73.42 185.00 146.83 369.99 369.99 15.60 73.42 185.00 146.83 369.99 369.99 15.61 73.42 185.00 146.83 369.99 15.62 73.42 185.00 146.83 369.99 15.63 73.42 146.83 15.64 73.42 15.65 73.42 15.66 73.42 15.67 73.42 15.68 293.66 123.47 61.74 15.69 293.66 123.47 61.74 15.70 293.66 123.47 61.74 493.88 493.88 15.71 293.66 123.47 61.74 493.88 493.88 369.99 15.72 293.66 123.47 61.74 493.88 493.88 369.99 15.73 293.66 123.47 61.74 493.88 493.88 369.99 15.74 293.66 123.47 61.74 493.88 493.88 369.99 15.75 293.66 61.74 493.88 493.88 369.99 15.76 293.66 493.88 493.88 369.99 15.77 493.88 15.78 493.88 15.79 15.80 15.81 15.82 55.00 15.83 55.00 110.00 15.84 55.00 110.00 15.85 55.00 110.00 15.86 55.00 110.00 15.87 55.00 110.00 277.18 554.37 369.99 15.88 55.00 110.00 277.18 554.37 369.99 554.37 15.89 55.00 110.00 277.18 554.37 369.99 554.37 15.90 55.00 110.00 277.18 554.37 369.99 554.37 15.91 55.00 110.00 277.18 554.37 369.99 554.37 15.92 55.00 110.00 277.18 554.37 369.99 554.37 15.93 55.00 110.00 277.18 554.37 369.99 554.37 15.94 55.00 110.00 277.18 554.37 369.99 554.37 15.95 55.00 110.00 277.18 554.37 369.99 554.37 15.96 55.00 110.00 277.18 554.37 369.99 554.37 15.97 55.00 110.00 277.18 554.37 369.99 554.37 15.98 55.00 110.00 277.18 554.37 369.99 554.37 15.99 55.00 110.00 277.18 554.37 369.99 554.37 16.00 55.00 110.00 277.18 554.37 369.99 554.37 16.01 55.00 110.00 277.18 554.37 369.99 554.37 16.02 55.00 110.00 277.18 554.37 369.99 554.37 16.03 55.00 110.00 277.18 554.37 369.99 554.37 16.04 55.00 110.00 277.18 554.37 369.99 554.37 16.05 55.00 110.00 277.18 554.37 369.99 554.37 16.06 55.00 110.00 277.18 554.37 369.99 554.37 16.07 55.00 110.00 277.18 554.37 369.99 554.37 16.08 55.00 110.00 277.18 554.37 554.37 16.09 55.00 110.00 277.18 554.37 554.37 16.10 55.00 110.00 277.18 554.37 554.37 16.11 55.00 110.00 277.18 554.37 16.12 55.00 110.00 277.18 554.37 16.13 55.00 110.00 277.18 554.37 16.14 55.00 110.00 277.18 554.37 16.15 55.00 110.00 277.18 554.37 16.16 55.00 110.00 554.37 16.17 55.00 110.00 554.37 16.18 110.00 554.37 16.19 110.00 554.37 16.20 110.00 554.37 16.21 110.00 554.37 16.22 110.00 554.37 16.23 554.37 16.24 554.37 16.25 554.37 16.26 16.27 16.28 16.29 16.30 16.31 16.32 739.99 369.99 16.33 739.99 369.99 440.00 16.34 739.99 369.99 440.00 92.50 16.35 739.99 369.99 440.00 92.50 46.25 554.37 16.36 739.99 369.99 440.00 92.50 46.25 554.37 16.37 739.99 369.99 440.00 92.50 46.25 554.37 16.38 739.99 369.99 440.00 92.50 46.25 554.37 16.39 739.99 369.99 440.00 92.50 46.25 554.37 739.99 16.40 739.99 369.99 440.00 92.50 46.25 554.37 739.99 16.41 739.99 369.99 440.00 92.50 46.25 554.37 739.99 16.42 739.99 369.99 440.00 92.50 46.25 554.37 739.99 16.43 739.99 369.99 440.00 92.50 46.25 554.37 739.99 16.44 739.99 369.99 440.00 92.50 46.25 554.37 739.99 16.45 739.99 369.99 440.00 92.50 46.25 554.37 739.99 16.46 739.99 369.99 440.00 92.50 46.25 554.37 739.99 16.47 739.99 369.99 440.00 92.50 46.25 554.37 739.99 16.48 739.99 369.99 440.00 92.50 46.25 554.37 739.99 16.49 369.99 440.00 92.50 46.25 554.37 739.99 16.50 369.99 440.00 92.50 46.25 554.37 739.99 16.51 369.99 440.00 92.50 46.25 554.37 739.99 16.52 369.99 440.00 92.50 46.25 554.37 739.99 16.53 369.99 440.00 92.50 46.25 739.99 16.54 440.00 92.50 46.25 739.99 16.55 440.00 92.50 46.25 739.99 16.56 440.00 92.50 46.25 739.99 16.57 440.00 92.50 46.25 739.99 16.58 440.00 92.50 46.25 739.99 16.59 92.50 46.25 739.99 16.60 92.50 46.25 739.99 16.61 92.50 46.25 739.99 16.62 92.50 46.25 739.99 16.63 92.50 46.25 739.99 16.64 92.50 46.25 739.99 16.65 46.25 739.99 16.66 46.25 739.99 16.67 46.25 739.99 16.68 46.25 739.99 16.69 46.25 739.99 16.70 46.25 739.99 16.71 46.25 739.99 16.72 739.99 16.73 739.99 16.74 16.75 16.76 16.77 16.78 16.79 16.80 16.81 16.82 16.83 61.74 293.66 16.84 61.74 293.66 587.33 16.85 61.74 293.66 587.33 369.99 493.88 123.47 16.86 61.74 293.66 587.33 369.99 493.88 123.47 587.33 16.87 61.74 293.66 587.33 369.99 493.88 123.47 587.33 16.88 61.74 293.66 587.33 369.99 493.88 123.47 587.33 16.89 61.74 293.66 587.33 369.99 493.88 123.47 587.33 16.90 61.74 293.66 587.33 369.99 493.88 123.47 587.33 16.91 61.74 293.66 587.33 369.99 493.88 123.47 587.33 16.92 61.74 293.66 587.33 369.99 493.88 123.47 587.33 16.93 61.74 293.66 587.33 369.99 493.88 123.47 587.33 16.94 61.74 293.66 587.33 369.99 493.88 123.47 587.33 16.95 61.74 293.66 587.33 369.99 493.88 123.47 587.33 16.96 61.74 293.66 587.33 369.99 493.88 123.47 587.33 16.97 61.74 293.66 587.33 369.99 493.88 123.47 587.33 16.98 61.74 293.66 587.33 369.99 493.88 123.47 587.33 16.99 61.74 293.66 587.33 369.99 493.88 123.47 587.33 17.00 61.74 293.66 587.33 369.99 493.88 123.47 587.33 17.01 61.74 293.66 587.33 369.99 493.88 123.47 587.33 17.02 61.74 293.66 587.33 369.99 493.88 123.47 587.33 17.03 61.74 293.66 587.33 369.99 493.88 123.47 587.33 17.04 61.74 293.66 587.33 369.99 493.88 123.47 587.33 17.05 61.74 293.66 587.33 369.99 493.88 123.47 587.33 17.06 61.74 293.66 587.33 369.99 493.88 123.47 587.33 17.07 61.74 293.66 587.33 369.99 493.88 123.47 587.33 17.08 61.74 293.66 587.33 369.99 493.88 123.47 587.33 17.09 61.74 293.66 587.33 369.99 493.88 123.47 587.33 17.10 61.74 293.66 587.33 369.99 123.47 587.33 17.11 61.74 369.99 123.47 587.33 17.12 61.74 123.47 587.33 17.13 61.74 123.47 587.33 17.14 61.74 123.47 587.33 17.15 61.74 123.47 587.33 17.16 61.74 123.47 587.33 17.17 61.74 587.33 17.18 587.33 17.19 587.33 17.20 587.33 17.21 587.33 17.22 587.33 17.23 587.33 17.24 587.33 17.25 587.33 17.26 17.27 17.28 17.29 17.30 17.31 17.32 17.33 17.34 246.94 207.65 349.23 17.35 246.94 207.65 349.23 311.13 17.36 246.94 207.65 349.23 311.13 138.59 17.37 246.94 207.65 349.23 311.13 138.59 69.30 17.38 246.94 207.65 349.23 311.13 138.59 69.30 17.39 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.40 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.41 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.42 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.43 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.44 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.45 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.46 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.47 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.48 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.49 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.50 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.51 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.52 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.53 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.54 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.55 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.56 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.57 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.58 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.59 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.60 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.61 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.62 246.94 207.65 349.23 311.13 138.59 69.30 349.23 17.63 246.94 349.23 311.13 138.59 69.30 349.23 17.64 349.23 311.13 138.59 69.30 349.23 17.65 349.23 311.13 138.59 69.30 349.23 17.66 138.59 69.30 349.23 17.67 138.59 69.30 349.23 17.68 138.59 69.30 17.69 69.30 17.70 69.30 17.71 69.30 17.72 69.30 17.73 17.74 17.75 17.76 17.77 17.78 17.79 17.80 17.81 17.82 17.83 17.84 17.85 277.18 17.86 277.18 369.99 185.00 233.08 92.50 17.87 277.18 369.99 185.00 233.08 92.50 17.88 277.18 369.99 185.00 233.08 92.50 17.89 277.18 369.99 185.00 233.08 92.50 369.99 17.90 277.18 369.99 185.00 233.08 92.50 369.99 17.91 277.18 369.99 185.00 233.08 92.50 369.99 17.92 277.18 369.99 185.00 233.08 92.50 369.99 17.93 277.18 369.99 185.00 233.08 92.50 369.99 17.94 277.18 369.99 185.00 233.08 92.50 369.99 17.95 277.18 369.99 185.00 233.08 92.50 369.99 17.96 277.18 369.99 185.00 233.08 92.50 369.99 17.97 277.18 369.99 185.00 233.08 92.50 369.99 17.98 277.18 369.99 185.00 233.08 92.50 369.99 17.99 277.18 369.99 185.00 233.08 92.50 369.99 18.00 277.18 369.99 185.00 233.08 92.50 369.99 18.01 277.18 369.99 185.00 233.08 92.50 369.99 18.02 277.18 369.99 185.00 233.08 92.50 369.99 18.03 277.18 369.99 185.00 233.08 92.50 369.99 18.04 277.18 369.99 185.00 233.08 92.50 369.99 18.05 277.18 369.99 185.00 233.08 92.50 369.99 18.06 277.18 369.99 185.00 233.08 92.50 369.99 18.07 277.18 369.99 185.00 233.08 92.50 369.99 18.08 277.18 369.99 185.00 233.08 92.50 369.99 18.09 277.18 369.99 185.00 233.08 92.50 369.99 18.10 277.18 369.99 185.00 233.08 92.50 369.99 18.11 277.18 369.99 185.00 233.08 92.50 369.99 18.12 277.18 369.99 185.00 233.08 92.50 369.99 18.13 277.18 369.99 185.00 233.08 92.50 369.99 18.14 277.18 369.99 185.00 233.08 92.50 369.99 18.15 277.18 369.99 185.00 233.08 92.50 369.99 18.16 277.18 369.99 185.00 233.08 92.50 369.99 18.17 277.18 369.99 233.08 92.50 369.99 18.18 277.18 92.50 369.99 18.19 369.99 18.20 369.99 18.21 369.99 18.22 369.99 18.23 369.99 18.24 369.99 18.25 369.99 18.26 369.99 18.27 369.99 18.28 18.29 18.30 18.31 18.32 18.33 18.34 18.35 18.36 18.37 18.38 18.39 92.50 18.40 92.50 123.47 587.33 18.41 92.50 123.47 587.33 18.42 92.50 123.47 587.33 18.43 92.50 123.47 587.33 587.33 369.99 18.44 92.50 123.47 587.33 587.33 369.99 18.45 92.50 123.47 587.33 587.33 369.99 18.46 92.50 123.47 587.33 587.33 369.99 18.47 123.47 587.33 587.33 369.99 18.48 123.47 587.33 369.99 18.49 369.99 18.50 18.51 18.52 18.53 18.54 18.55 18.56 18.57 659.26 18.58 659.26 138.59 659.26 18.59 659.26 138.59 659.26 92.50 369.99 18.60 659.26 138.59 659.26 92.50 369.99 18.61 659.26 138.59 659.26 92.50 369.99 18.62 659.26 138.59 659.26 92.50 369.99 18.63 138.59 659.26 92.50 369.99 18.64 138.59 659.26 92.50 369.99 18.65 138.59 92.50 369.99 18.66 18.67 18.68 18.69 18.70 18.71 739.99 18.72 739.99 18.73 739.99 739.99 18.74 739.99 739.99 146.83 369.99 92.50 18.75 739.99 739.99 146.83 369.99 92.50 18.76 739.99 739.99 146.83 369.99 92.50 18.77 739.99 739.99 146.83 369.99 92.50 18.78 739.99 146.83 369.99 92.50 18.79 146.83 369.99 92.50 18.80 146.83 369.99 92.50 18.81 92.50 18.82 18.83 18.84 18.85 18.86 18.87 18.88 783.99 92.50 18.89 783.99 92.50 369.99 783.99 18.90 783.99 92.50 369.99 783.99 164.81 18.91 783.99 92.50 369.99 783.99 164.81 18.92 783.99 92.50 369.99 783.99 164.81 18.93 783.99 92.50 369.99 783.99 164.81 18.94 783.99 92.50 369.99 783.99 164.81 18.95 783.99 92.50 369.99 783.99 164.81 18.96 783.99 92.50 369.99 783.99 164.81 18.97 783.99 92.50 369.99 783.99 164.81 18.98 783.99 92.50 369.99 783.99 164.81 18.99 783.99 92.50 369.99 783.99 164.81 19.00 783.99 92.50 369.99 783.99 164.81 19.01 783.99 92.50 369.99 783.99 164.81 19.02 783.99 92.50 369.99 783.99 164.81 19.03 783.99 92.50 369.99 783.99 164.81 19.04 783.99 92.50 369.99 783.99 164.81 19.05 783.99 92.50 369.99 783.99 164.81 19.06 783.99 92.50 369.99 783.99 164.81 19.07 783.99 92.50 369.99 783.99 164.81 19.08 783.99 92.50 369.99 783.99 164.81 19.09 783.99 92.50 369.99 783.99 164.81 19.10 783.99 92.50 369.99 783.99 164.81 19.11 783.99 92.50 369.99 783.99 164.81 19.12 783.99 92.50 369.99 783.99 164.81 19.13 783.99 92.50 369.99 164.81 19.14 783.99 92.50 369.99 164.81 19.15 92.50 369.99 164.81 19.16 92.50 369.99 164.81 19.17 92.50 19.18 92.50 19.19 92.50 19.20 92.50 19.21 92.50 19.22 92.50 19.23 92.50 19.24 92.50 146.83 739.99 19.25 92.50 146.83 739.99 739.99 19.26 92.50 146.83 739.99 739.99 369.99 19.27 92.50 146.83 739.99 739.99 369.99 19.28 92.50 146.83 739.99 739.99 369.99 19.29 92.50 146.83 739.99 739.99 369.99 19.30 92.50 146.83 739.99 739.99 369.99 19.31 92.50 146.83 739.99 369.99 19.32 92.50 369.99 19.33 92.50 19.34 92.50 19.35 92.50 19.36 92.50 19.37 92.50 19.38 92.50 19.39 92.50 19.40 92.50 783.99 19.41 92.50 783.99 19.42 92.50 783.99 783.99 369.99 19.43 92.50 783.99 783.99 369.99 19.44 92.50 783.99 783.99 369.99 164.81 19.45 92.50 783.99 783.99 369.99 164.81 19.46 92.50 783.99 783.99 369.99 164.81 19.47 92.50 783.99 783.99 369.99 164.81 19.48 92.50 783.99 369.99 164.81 19.49 92.50 783.99 164.81 19.50 92.50 164.81 19.51 92.50 164.81 19.52 92.50 19.53 92.50 19.54 92.50 19.55 92.50 19.56 92.50 739.99 19.57 92.50 739.99 739.99 146.83 369.99 19.58 92.50 739.99 739.99 146.83 369.99 19.59 92.50 739.99 739.99 146.83 369.99 19.60 92.50 739.99 739.99 146.83 369.99 19.61 92.50 739.99 739.99 146.83 369.99 19.62 92.50 739.99 739.99 146.83 369.99 19.63 92.50 739.99 146.83 369.99 19.64 92.50 146.83 19.65 92.50 146.83 19.66 92.50 19.67 92.50 19.68 92.50 19.69 92.50 369.99 587.33 19.70 92.50 369.99 587.33 123.47 587.33 19.71 92.50 369.99 587.33 123.47 587.33 19.72 92.50 369.99 587.33 123.47 587.33 19.73 369.99 587.33 123.47 587.33 19.74 369.99 587.33 123.47 587.33 19.75 369.99 587.33 123.47 587.33 19.76 369.99 587.33 123.47 587.33 19.77 587.33 587.33 19.78 587.33 19.79 19.80 19.81 19.82 19.83 19.84 19.85 19.86 19.87 554.37 19.88 554.37 369.99 554.37 116.54 19.89 554.37 369.99 554.37 116.54 92.50 19.90 554.37 369.99 554.37 116.54 92.50 19.91 554.37 369.99 554.37 116.54 92.50 19.92 554.37 369.99 554.37 116.54 92.50 19.93 554.37 369.99 554.37 116.54 92.50 19.94 554.37 369.99 554.37 116.54 92.50 19.95 554.37 369.99 554.37 116.54 92.50 19.96 554.37 369.99 554.37 116.54 92.50 19.97 554.37 369.99 554.37 116.54 92.50 19.98 554.37 369.99 554.37 116.54 92.50 19.99 554.37 369.99 554.37 116.54 92.50 20.00 554.37 369.99 554.37 116.54 92.50 20.01 554.37 369.99 554.37 116.54 92.50 20.02 554.37 369.99 554.37 116.54 92.50 20.03 554.37 369.99 554.37 116.54 92.50 20.04 554.37 554.37 116.54 92.50 20.05 554.37 116.54 92.50 20.06 554.37 116.54 92.50 20.07 554.37 116.54 92.50 20.08 554.37 116.54 92.50 20.09 554.37 116.54 92.50 20.10 554.37 116.54 92.50 20.11 554.37 116.54 92.50 20.12 116.54 92.50 20.13 116.54 92.50 20.14 116.54 92.50 20.15 116.54 92.50 20.16 116.54 92.50 20.17 116.54 92.50 20.18 116.54 92.50 20.19 116.54 92.50 369.99 20.20 116.54 92.50 369.99 20.21 116.54 92.50 369.99 20.22 116.54 92.50 369.99 20.23 116.54 92.50 369.99 20.24 116.54 92.50 369.99 20.25 369.99 20.26 369.99 20.27 20.28 20.29 20.30 466.16 20.31 466.16 20.32 466.16 92.50 369.99 466.16 20.33 466.16 92.50 369.99 466.16 20.34 466.16 92.50 369.99 466.16 20.35 466.16 92.50 369.99 466.16 20.36 466.16 92.50 369.99 466.16 20.37 92.50 369.99 466.16 20.38 466.16 20.39 20.40 20.41 20.42 20.43 103.83 20.44 103.83 92.50 369.99 493.88 20.45 103.83 92.50 369.99 493.88 20.46 103.83 92.50 369.99 493.88 493.88 20.47 103.83 92.50 369.99 493.88 493.88 20.48 103.83 92.50 369.99 493.88 493.88 20.49 103.83 92.50 369.99 493.88 493.88 20.50 103.83 92.50 369.99 493.88 493.88 20.51 493.88 493.88 20.52 493.88 20.53 493.88 20.54 20.55 20.56 20.57 20.58 20.59 20.60 20.61 20.62 116.54 20.63 116.54 92.50 554.37 369.99 554.37 20.64 116.54 92.50 554.37 369.99 554.37 20.65 116.54 92.50 554.37 369.99 554.37 20.66 116.54 92.50 554.37 369.99 554.37 20.67 116.54 92.50 554.37 369.99 554.37 20.68 116.54 92.50 554.37 369.99 554.37 20.69 92.50 554.37 554.37 20.70 20.71 20.72 20.73 20.74 20.75 20.76 20.77 20.78 20.79 20.80 20.81 659.26 20.82 659.26 92.50 369.99 659.26 20.83 659.26 92.50 369.99 659.26 138.59 20.84 659.26 92.50 369.99 659.26 138.59 20.85 659.26 92.50 369.99 659.26 138.59 20.86 659.26 92.50 369.99 659.26 138.59 20.87 659.26 92.50 369.99 659.26 138.59 20.88 659.26 92.50 369.99 659.26 138.59 20.89 659.26 92.50 369.99 659.26 138.59 20.90 659.26 92.50 369.99 659.26 138.59 20.91 659.26 92.50 369.99 659.26 138.59 20.92 659.26 92.50 369.99 659.26 138.59 20.93 659.26 92.50 369.99 659.26 138.59 20.94 659.26 92.50 369.99 659.26 138.59 20.95 659.26 92.50 369.99 659.26 138.59 20.96 659.26 92.50 369.99 659.26 138.59 20.97 659.26 92.50 369.99 659.26 138.59 20.98 659.26 92.50 369.99 659.26 138.59 20.99 659.26 92.50 369.99 659.26 138.59 21.00 659.26 92.50 659.26 138.59 21.01 659.26 92.50 138.59 21.02 92.50 138.59 21.03 92.50 138.59 21.04 92.50 138.59 21.05 92.50 138.59 21.06 92.50 138.59 21.07 92.50 138.59 21.08 92.50 21.09 92.50 21.10 92.50 21.11 92.50 587.33 21.12 92.50 587.33 21.13 92.50 587.33 587.33 21.14 92.50 587.33 587.33 369.99 21.15 92.50 587.33 587.33 369.99 123.47 21.16 92.50 587.33 587.33 369.99 123.47 21.17 92.50 587.33 587.33 369.99 123.47 21.18 92.50 587.33 587.33 369.99 123.47 21.19 92.50 587.33 587.33 369.99 123.47 21.20 92.50 369.99 123.47 21.21 92.50 123.47 21.22 92.50 123.47 21.23 92.50 21.24 92.50 21.25 92.50 21.26 92.50 659.26 21.27 92.50 659.26 659.26 21.28 92.50 659.26 659.26 21.29 92.50 659.26 659.26 21.30 92.50 659.26 659.26 21.31 92.50 659.26 659.26 369.99 138.59 21.32 92.50 659.26 659.26 369.99 138.59 21.33 92.50 659.26 369.99 138.59 21.34 92.50 659.26 369.99 138.59 21.35 92.50 659.26 369.99 138.59 21.36 92.50 369.99 138.59 21.37 92.50 138.59 21.38 92.50 138.59 21.39 92.50 21.40 92.50 21.41 92.50 21.42 92.50 21.43 92.50 587.33 21.44 92.50 587.33 587.33 21.45 92.50 587.33 587.33 123.47 21.46 92.50 587.33 587.33 123.47 369.99 21.47 587.33 587.33 123.47 369.99 21.48 587.33 587.33 123.47 369.99 21.49 587.33 587.33 123.47 369.99 21.50 587.33 587.33 123.47 369.99 21.51 123.47 21.52 123.47 21.53 21.54 21.55 493.88 21.56 493.88 21.57 493.88 98.00 493.88 21.58 493.88 98.00 493.88 369.99 21.59 493.88 98.00 493.88 369.99 21.60 493.88 98.00 493.88 369.99 21.61 493.88 98.00 493.88 369.99 21.62 493.88 98.00 493.88 369.99 21.63 493.88 98.00 493.88 369.99 21.64 493.88 98.00 369.99 21.65 98.00 21.66 98.00 21.67 21.68 21.69 21.70 21.71 21.72 21.73 21.74 369.99 21.75 369.99 466.16 92.50 466.16 21.76 369.99 466.16 92.50 466.16 21.77 369.99 466.16 92.50 466.16 21.78 369.99 466.16 92.50 466.16 21.79 369.99 466.16 92.50 466.16 21.80 369.99 466.16 92.50 466.16 21.81 369.99 466.16 92.50 466.16 21.82 369.99 466.16 92.50 466.16 21.83 369.99 466.16 92.50 466.16 21.84 369.99 466.16 92.50 466.16 21.85 369.99 466.16 92.50 466.16 21.86 369.99 466.16 92.50 466.16 21.87 369.99 466.16 92.50 466.16 21.88 369.99 466.16 92.50 466.16 21.89 369.99 466.16 92.50 466.16 21.90 369.99 466.16 92.50 466.16 21.91 369.99 466.16 92.50 466.16 21.92 369.99 466.16 92.50 466.16 21.93 369.99 466.16 92.50 466.16 21.94 369.99 466.16 92.50 466.16 21.95 369.99 466.16 92.50 466.16 21.96 369.99 466.16 92.50 466.16 21.97 369.99 466.16 92.50 466.16 21.98 369.99 466.16 92.50 466.16 21.99 369.99 466.16 92.50 466.16mir_eval-0.8.2/tests/data/multipitch/ref09.txt000066400000000000000000003645671475740344600213050ustar00rootroot000000000000000.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.30 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.40 0.41 0.42 0.43 0.44 0.45 0.46 0.47 0.48 0.49 0.50 246.94 493.88 0.51 246.94 493.88 0.52 246.94 493.88 0.53 246.94 493.88 0.54 246.94 493.88 0.55 246.94 493.88 0.56 246.94 493.88 0.57 246.94 493.88 0.58 246.94 493.88 0.59 246.94 493.88 0.60 246.94 493.88 0.61 246.94 493.88 0.62 246.94 493.88 0.63 246.94 493.88 0.64 246.94 493.88 0.65 246.94 493.88 0.66 246.94 493.88 0.67 246.94 493.88 0.68 246.94 493.88 0.69 246.94 493.88 0.70 246.94 493.88 0.71 246.94 493.88 0.72 246.94 493.88 0.73 246.94 493.88 0.74 246.94 493.88 0.75 246.94 493.88 0.76 246.94 493.88 0.77 246.94 493.88 0.78 246.94 493.88 0.79 246.94 493.88 0.80 246.94 493.88 0.81 246.94 493.88 0.82 246.94 493.88 0.83 246.94 493.88 0.84 246.94 493.88 0.85 246.94 493.88 0.86 246.94 493.88 0.87 246.94 493.88 0.88 246.94 0.89 246.94 0.90 246.94 329.63 554.37 0.91 246.94 329.63 554.37 0.92 246.94 329.63 554.37 0.93 246.94 329.63 554.37 0.94 246.94 329.63 554.37 110.00 0.95 246.94 329.63 554.37 110.00 0.96 246.94 329.63 554.37 110.00 277.18 0.97 246.94 329.63 554.37 110.00 277.18 0.98 329.63 554.37 110.00 277.18 0.99 329.63 554.37 110.00 277.18 1.00 329.63 554.37 110.00 277.18 1.01 329.63 554.37 110.00 277.18 1.02 329.63 554.37 110.00 277.18 1.03 329.63 554.37 110.00 277.18 1.04 329.63 554.37 110.00 277.18 1.05 329.63 554.37 110.00 277.18 1.06 329.63 554.37 110.00 277.18 1.07 329.63 554.37 110.00 277.18 1.08 329.63 554.37 110.00 277.18 1.09 329.63 554.37 110.00 277.18 1.10 329.63 554.37 110.00 277.18 1.11 329.63 554.37 110.00 277.18 1.12 329.63 554.37 110.00 277.18 1.13 329.63 554.37 110.00 277.18 1.14 329.63 554.37 110.00 277.18 1.15 329.63 554.37 110.00 277.18 1.16 329.63 554.37 110.00 277.18 1.17 329.63 554.37 110.00 277.18 1.18 329.63 554.37 110.00 277.18 1.19 329.63 554.37 110.00 277.18 1.20 329.63 554.37 110.00 277.18 1.21 329.63 554.37 110.00 277.18 1.22 329.63 554.37 110.00 277.18 1.23 329.63 554.37 110.00 277.18 1.24 329.63 554.37 110.00 277.18 1.25 329.63 554.37 110.00 277.18 1.26 329.63 554.37 110.00 277.18 1.27 329.63 554.37 110.00 277.18 1.28 329.63 554.37 110.00 277.18 440.00 1.29 329.63 554.37 110.00 277.18 440.00 1.30 329.63 110.00 277.18 440.00 220.00 1.31 329.63 110.00 277.18 440.00 220.00 1.32 329.63 110.00 440.00 220.00 1.33 329.63 110.00 440.00 220.00 1.34 329.63 110.00 440.00 220.00 1.35 329.63 110.00 440.00 220.00 1.36 329.63 110.00 440.00 220.00 1.37 329.63 110.00 440.00 220.00 1.38 329.63 110.00 440.00 220.00 1.39 329.63 110.00 440.00 220.00 1.40 329.63 110.00 440.00 220.00 1.41 329.63 110.00 440.00 220.00 1.42 329.63 110.00 440.00 220.00 1.43 329.63 110.00 440.00 220.00 1.44 329.63 110.00 440.00 220.00 1.45 329.63 110.00 440.00 220.00 1.46 329.63 110.00 440.00 220.00 1.47 329.63 110.00 440.00 220.00 1.48 329.63 110.00 440.00 220.00 1.49 329.63 110.00 440.00 220.00 1.50 329.63 110.00 440.00 220.00 1.51 329.63 110.00 440.00 220.00 1.52 329.63 110.00 440.00 220.00 1.53 329.63 110.00 440.00 220.00 1.54 329.63 110.00 440.00 220.00 1.55 329.63 110.00 440.00 220.00 1.56 329.63 110.00 440.00 220.00 1.57 329.63 110.00 440.00 220.00 1.58 329.63 110.00 440.00 220.00 1.59 329.63 110.00 440.00 220.00 1.60 329.63 110.00 440.00 220.00 1.61 329.63 110.00 440.00 220.00 1.62 329.63 110.00 440.00 220.00 1.63 329.63 110.00 440.00 220.00 1.64 329.63 110.00 440.00 220.00 1.65 329.63 110.00 440.00 220.00 1.66 329.63 110.00 440.00 220.00 1.67 329.63 110.00 220.00 415.30 293.66 1.68 329.63 110.00 220.00 415.30 293.66 220.00 1.69 329.63 110.00 220.00 415.30 293.66 220.00 1.70 329.63 110.00 220.00 415.30 293.66 220.00 207.65 1.71 329.63 110.00 220.00 415.30 293.66 220.00 207.65 1.72 110.00 220.00 415.30 293.66 220.00 207.65 1.73 110.00 220.00 415.30 293.66 220.00 207.65 1.74 110.00 415.30 293.66 220.00 207.65 1.75 110.00 415.30 293.66 220.00 207.65 1.76 110.00 415.30 293.66 220.00 207.65 1.77 110.00 415.30 293.66 220.00 207.65 1.78 110.00 415.30 293.66 220.00 207.65 1.79 110.00 415.30 293.66 220.00 207.65 1.80 110.00 415.30 293.66 220.00 207.65 1.81 110.00 415.30 293.66 220.00 207.65 1.82 110.00 415.30 293.66 220.00 207.65 1.83 110.00 415.30 293.66 220.00 207.65 1.84 110.00 415.30 293.66 220.00 207.65 1.85 110.00 415.30 293.66 220.00 207.65 1.86 110.00 415.30 293.66 220.00 207.65 1.87 110.00 415.30 293.66 220.00 207.65 1.88 110.00 415.30 293.66 220.00 207.65 1.89 110.00 415.30 293.66 220.00 207.65 1.90 110.00 415.30 293.66 220.00 207.65 1.91 110.00 415.30 293.66 220.00 207.65 1.92 110.00 415.30 293.66 220.00 207.65 1.93 110.00 415.30 293.66 220.00 207.65 1.94 110.00 415.30 293.66 220.00 207.65 1.95 110.00 415.30 293.66 220.00 207.65 1.96 110.00 415.30 293.66 220.00 207.65 1.97 110.00 415.30 293.66 220.00 207.65 1.98 110.00 415.30 293.66 220.00 207.65 1.99 110.00 415.30 293.66 220.00 207.65 2.00 110.00 415.30 293.66 220.00 207.65 2.01 110.00 415.30 293.66 220.00 207.65 369.99 2.02 110.00 415.30 293.66 220.00 207.65 369.99 2.03 110.00 293.66 220.00 207.65 369.99 2.04 110.00 293.66 220.00 207.65 369.99 987.77 2.05 110.00 293.66 220.00 207.65 369.99 987.77 185.00 2.06 110.00 293.66 220.00 207.65 369.99 987.77 185.00 2.07 110.00 293.66 220.00 207.65 369.99 987.77 185.00 2.08 110.00 293.66 220.00 207.65 369.99 987.77 185.00 2.09 110.00 293.66 220.00 369.99 987.77 185.00 2.10 110.00 293.66 220.00 369.99 987.77 185.00 2.11 110.00 293.66 220.00 369.99 987.77 185.00 2.12 110.00 293.66 220.00 369.99 987.77 185.00 2.13 110.00 293.66 220.00 369.99 987.77 185.00 2.14 110.00 293.66 220.00 369.99 987.77 185.00 2.15 110.00 293.66 369.99 987.77 185.00 2.16 110.00 293.66 369.99 987.77 185.00 2.17 110.00 293.66 369.99 987.77 185.00 2.18 110.00 293.66 369.99 987.77 185.00 2.19 110.00 293.66 369.99 987.77 185.00 2.20 110.00 293.66 369.99 987.77 185.00 2.21 110.00 293.66 369.99 987.77 185.00 2.22 110.00 293.66 369.99 987.77 185.00 2.23 110.00 293.66 369.99 987.77 185.00 2.24 110.00 293.66 369.99 987.77 185.00 2.25 110.00 293.66 369.99 987.77 185.00 2.26 110.00 293.66 369.99 987.77 185.00 2.27 293.66 369.99 987.77 185.00 2.28 293.66 369.99 987.77 185.00 2.29 293.66 369.99 987.77 185.00 2.30 293.66 369.99 987.77 185.00 2.31 293.66 369.99 987.77 185.00 2.32 293.66 369.99 987.77 185.00 2.33 293.66 369.99 987.77 185.00 2.34 293.66 369.99 987.77 185.00 2.35 293.66 369.99 987.77 185.00 2.36 293.66 369.99 987.77 185.00 2.37 293.66 369.99 987.77 185.00 2.38 293.66 369.99 987.77 185.00 2.39 293.66 369.99 987.77 185.00 2.40 293.66 369.99 987.77 185.00 277.18 2.41 293.66 369.99 987.77 185.00 277.18 220.00 110.00 2.42 293.66 369.99 987.77 185.00 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.43 293.66 369.99 987.77 185.00 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.44 293.66 369.99 987.77 185.00 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.45 293.66 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.46 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.47 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.48 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.49 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.50 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.51 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.52 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.53 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.54 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.55 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.56 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.57 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.58 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.59 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.60 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.61 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.62 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.63 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.64 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.65 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.66 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.67 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.68 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.69 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.70 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.71 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.72 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.73 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.74 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.75 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.76 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.77 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.78 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.79 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.80 277.18 220.00 110.00 277.18 164.81 329.63 220.00 1108.73 2.81 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.82 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.83 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.84 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.85 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.86 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.87 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.88 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.89 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.90 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.91 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.92 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.93 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.94 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.95 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.96 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.97 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.98 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 2.99 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.00 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.01 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.02 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.03 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.04 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.05 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.06 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.07 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.08 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.09 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.10 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.11 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.12 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.13 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.14 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.15 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 3.16 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 830.61 3.17 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 830.61 3.18 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 830.61 3.19 277.18 220.00 110.00 277.18 164.81 329.63 220.00 880.00 830.61 3.20 220.00 110.00 277.18 164.81 329.63 220.00 830.61 3.21 220.00 110.00 277.18 164.81 329.63 220.00 830.61 3.22 220.00 110.00 277.18 164.81 329.63 220.00 830.61 3.23 220.00 110.00 277.18 164.81 329.63 220.00 830.61 3.24 220.00 110.00 277.18 164.81 329.63 220.00 830.61 3.25 220.00 110.00 277.18 164.81 329.63 220.00 830.61 3.26 220.00 110.00 277.18 164.81 329.63 220.00 830.61 3.27 220.00 110.00 277.18 164.81 329.63 220.00 830.61 3.28 110.00 277.18 164.81 329.63 220.00 830.61 3.29 110.00 277.18 164.81 329.63 220.00 830.61 3.30 110.00 164.81 329.63 220.00 830.61 3.31 110.00 164.81 329.63 220.00 830.61 3.32 110.00 164.81 220.00 830.61 3.33 110.00 164.81 220.00 830.61 3.34 110.00 164.81 220.00 830.61 3.35 110.00 164.81 220.00 830.61 3.36 110.00 164.81 220.00 830.61 3.37 110.00 164.81 220.00 830.61 3.38 110.00 164.81 220.00 830.61 3.39 110.00 164.81 220.00 830.61 3.40 110.00 164.81 220.00 830.61 3.41 110.00 164.81 220.00 830.61 3.42 110.00 164.81 220.00 830.61 3.43 110.00 164.81 220.00 830.61 3.44 110.00 164.81 220.00 830.61 3.45 110.00 164.81 220.00 830.61 3.46 110.00 164.81 220.00 830.61 3.47 110.00 164.81 220.00 830.61 3.48 110.00 164.81 220.00 830.61 3.49 110.00 164.81 220.00 830.61 138.59 3.50 110.00 164.81 220.00 830.61 138.59 3.51 110.00 220.00 830.61 138.59 3.52 110.00 220.00 830.61 138.59 277.18 3.53 110.00 220.00 830.61 138.59 277.18 739.99 3.54 110.00 220.00 830.61 138.59 277.18 739.99 3.55 110.00 220.00 830.61 138.59 277.18 739.99 3.56 110.00 220.00 138.59 277.18 739.99 3.57 110.00 138.59 277.18 739.99 3.58 110.00 138.59 277.18 739.99 3.59 138.59 277.18 739.99 3.60 138.59 277.18 739.99 3.61 138.59 277.18 739.99 3.62 138.59 277.18 739.99 3.63 138.59 277.18 739.99 3.64 138.59 277.18 739.99 3.65 138.59 277.18 739.99 3.66 138.59 277.18 739.99 3.67 138.59 277.18 739.99 3.68 138.59 277.18 739.99 146.83 3.69 277.18 739.99 146.83 3.70 277.18 739.99 146.83 3.71 277.18 739.99 146.83 3.72 277.18 739.99 146.83 293.66 3.73 277.18 739.99 146.83 293.66 3.74 277.18 739.99 146.83 293.66 3.75 739.99 146.83 293.66 3.76 739.99 146.83 293.66 3.77 739.99 146.83 293.66 3.78 739.99 146.83 293.66 3.79 739.99 146.83 293.66 3.80 739.99 146.83 293.66 3.81 739.99 146.83 293.66 3.82 739.99 146.83 293.66 3.83 739.99 146.83 293.66 3.84 739.99 146.83 293.66 3.85 739.99 146.83 293.66 3.86 739.99 146.83 293.66 110.00 277.18 220.00 3.87 739.99 146.83 293.66 110.00 277.18 220.00 164.81 3.88 739.99 146.83 293.66 110.00 277.18 220.00 164.81 3.89 739.99 146.83 293.66 110.00 277.18 220.00 164.81 3.90 739.99 146.83 293.66 110.00 277.18 220.00 164.81 329.63 3.91 739.99 146.83 293.66 110.00 277.18 220.00 164.81 329.63 3.92 739.99 293.66 110.00 277.18 220.00 164.81 329.63 659.26 3.93 739.99 110.00 277.18 220.00 164.81 329.63 659.26 3.94 739.99 110.00 277.18 220.00 164.81 329.63 659.26 3.95 110.00 277.18 220.00 164.81 329.63 659.26 3.96 110.00 277.18 220.00 164.81 329.63 659.26 3.97 110.00 277.18 220.00 164.81 329.63 659.26 3.98 110.00 277.18 220.00 164.81 329.63 659.26 3.99 110.00 277.18 220.00 164.81 329.63 659.26 4.00 110.00 277.18 220.00 164.81 329.63 659.26 4.01 110.00 277.18 220.00 164.81 329.63 659.26 4.02 110.00 277.18 220.00 164.81 329.63 659.26 4.03 110.00 277.18 220.00 164.81 329.63 659.26 4.04 110.00 277.18 220.00 164.81 329.63 659.26 4.05 110.00 277.18 220.00 164.81 329.63 659.26 4.06 110.00 277.18 220.00 164.81 329.63 659.26 4.07 110.00 277.18 220.00 164.81 329.63 659.26 4.08 110.00 277.18 220.00 164.81 329.63 659.26 4.09 110.00 277.18 220.00 164.81 329.63 659.26 4.10 110.00 277.18 220.00 164.81 329.63 659.26 4.11 110.00 277.18 220.00 164.81 329.63 659.26 4.12 110.00 277.18 220.00 164.81 329.63 659.26 4.13 110.00 277.18 220.00 164.81 329.63 659.26 4.14 110.00 277.18 220.00 164.81 329.63 659.26 4.15 110.00 277.18 220.00 164.81 329.63 659.26 4.16 110.00 277.18 220.00 164.81 329.63 659.26 4.17 110.00 277.18 220.00 164.81 329.63 659.26 4.18 110.00 277.18 220.00 164.81 329.63 659.26 4.19 110.00 277.18 220.00 164.81 329.63 659.26 4.20 110.00 277.18 220.00 164.81 329.63 659.26 4.21 110.00 277.18 220.00 164.81 329.63 659.26 369.99 4.22 110.00 277.18 220.00 164.81 329.63 659.26 369.99 4.23 110.00 277.18 220.00 164.81 329.63 659.26 369.99 4.24 110.00 277.18 220.00 164.81 329.63 659.26 369.99 4.25 110.00 277.18 220.00 164.81 329.63 659.26 369.99 4.26 110.00 277.18 220.00 164.81 329.63 659.26 369.99 185.00 4.27 110.00 277.18 220.00 164.81 329.63 659.26 369.99 185.00 4.28 110.00 277.18 220.00 164.81 329.63 659.26 369.99 185.00 4.29 110.00 277.18 220.00 329.63 659.26 369.99 185.00 4.30 110.00 277.18 220.00 329.63 659.26 369.99 185.00 4.31 110.00 277.18 220.00 659.26 369.99 185.00 4.32 110.00 277.18 220.00 659.26 369.99 185.00 4.33 110.00 277.18 220.00 659.26 369.99 185.00 4.34 110.00 277.18 220.00 659.26 369.99 185.00 4.35 110.00 277.18 220.00 659.26 369.99 185.00 4.36 110.00 277.18 220.00 659.26 369.99 185.00 4.37 110.00 277.18 220.00 659.26 369.99 185.00 4.38 110.00 277.18 220.00 659.26 369.99 185.00 4.39 110.00 277.18 220.00 659.26 369.99 185.00 4.40 110.00 277.18 220.00 659.26 369.99 185.00 415.30 4.41 110.00 277.18 220.00 659.26 369.99 185.00 415.30 207.65 4.42 110.00 277.18 220.00 659.26 369.99 185.00 415.30 207.65 4.43 110.00 277.18 220.00 659.26 185.00 415.30 207.65 4.44 110.00 277.18 659.26 185.00 415.30 207.65 4.45 110.00 277.18 659.26 415.30 207.65 4.46 110.00 659.26 415.30 207.65 4.47 110.00 659.26 415.30 207.65 4.48 110.00 659.26 415.30 207.65 4.49 110.00 659.26 415.30 207.65 4.50 110.00 659.26 415.30 207.65 4.51 110.00 659.26 415.30 207.65 4.52 110.00 659.26 415.30 207.65 4.53 110.00 659.26 415.30 207.65 4.54 110.00 659.26 415.30 207.65 4.55 110.00 659.26 415.30 207.65 4.56 110.00 659.26 415.30 207.65 4.57 110.00 659.26 415.30 207.65 277.18 220.00 92.50 4.58 110.00 659.26 415.30 207.65 277.18 220.00 92.50 4.59 110.00 659.26 207.65 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.60 110.00 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.61 110.00 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.62 110.00 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.63 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.64 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.65 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.66 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.67 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.68 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.69 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.70 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.71 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.72 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.73 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.74 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.75 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.76 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.77 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.78 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.79 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.80 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.81 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.82 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.83 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.84 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.85 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.86 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.87 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.88 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.89 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.90 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 4.91 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 554.37 4.92 659.26 277.18 220.00 92.50 277.18 220.00 440.00 220.00 554.37 415.30 4.93 277.18 220.00 92.50 277.18 220.00 440.00 220.00 554.37 415.30 4.94 277.18 92.50 277.18 220.00 220.00 554.37 415.30 4.95 277.18 92.50 277.18 220.00 220.00 554.37 415.30 207.65 4.96 277.18 92.50 277.18 220.00 220.00 554.37 415.30 207.65 4.97 277.18 92.50 277.18 220.00 220.00 554.37 415.30 207.65 4.98 277.18 92.50 277.18 220.00 220.00 554.37 415.30 207.65 4.99 277.18 92.50 277.18 220.00 220.00 554.37 415.30 207.65 5.00 277.18 92.50 277.18 220.00 220.00 554.37 415.30 207.65 5.01 277.18 92.50 277.18 220.00 220.00 554.37 415.30 207.65 5.02 277.18 92.50 277.18 220.00 220.00 554.37 415.30 207.65 5.03 277.18 92.50 277.18 220.00 220.00 554.37 415.30 207.65 5.04 277.18 92.50 277.18 220.00 220.00 554.37 415.30 207.65 5.05 277.18 92.50 277.18 220.00 220.00 554.37 415.30 207.65 5.06 277.18 92.50 277.18 220.00 220.00 554.37 415.30 207.65 5.07 277.18 92.50 277.18 220.00 554.37 415.30 207.65 5.08 277.18 92.50 277.18 220.00 554.37 415.30 207.65 369.99 5.09 277.18 92.50 277.18 220.00 554.37 415.30 207.65 369.99 5.10 277.18 92.50 277.18 220.00 554.37 415.30 207.65 369.99 587.33 5.11 277.18 92.50 277.18 220.00 554.37 207.65 369.99 587.33 185.00 5.12 277.18 92.50 277.18 220.00 207.65 369.99 587.33 185.00 5.13 277.18 92.50 277.18 220.00 207.65 369.99 587.33 185.00 5.14 277.18 92.50 277.18 220.00 369.99 587.33 185.00 5.15 277.18 92.50 277.18 220.00 369.99 587.33 185.00 5.16 277.18 92.50 277.18 220.00 369.99 587.33 185.00 5.17 277.18 92.50 277.18 220.00 369.99 587.33 185.00 5.18 277.18 92.50 277.18 220.00 369.99 587.33 185.00 5.19 277.18 92.50 277.18 220.00 369.99 587.33 185.00 5.20 277.18 92.50 277.18 220.00 369.99 587.33 185.00 5.21 277.18 92.50 277.18 220.00 369.99 587.33 185.00 5.22 277.18 92.50 277.18 220.00 369.99 587.33 185.00 5.23 277.18 92.50 277.18 220.00 369.99 587.33 185.00 5.24 277.18 92.50 277.18 220.00 369.99 587.33 185.00 5.25 277.18 92.50 277.18 220.00 369.99 587.33 185.00 5.26 277.18 92.50 277.18 220.00 369.99 587.33 185.00 5.27 277.18 92.50 277.18 220.00 369.99 587.33 185.00 329.63 5.28 277.18 92.50 277.18 369.99 587.33 185.00 329.63 293.66 659.26 123.47 5.29 277.18 92.50 277.18 587.33 185.00 329.63 293.66 659.26 123.47 5.30 277.18 92.50 277.18 587.33 185.00 329.63 293.66 659.26 123.47 5.31 92.50 277.18 587.33 329.63 293.66 659.26 123.47 164.81 5.32 92.50 277.18 329.63 293.66 659.26 123.47 164.81 5.33 92.50 329.63 293.66 659.26 123.47 164.81 5.34 92.50 329.63 293.66 659.26 123.47 164.81 5.35 92.50 329.63 293.66 659.26 123.47 164.81 5.36 329.63 293.66 659.26 123.47 164.81 5.37 329.63 293.66 659.26 123.47 164.81 5.38 329.63 293.66 659.26 123.47 164.81 5.39 329.63 293.66 659.26 123.47 164.81 5.40 329.63 293.66 659.26 123.47 164.81 5.41 329.63 293.66 659.26 123.47 164.81 5.42 329.63 293.66 659.26 123.47 164.81 5.43 329.63 293.66 659.26 123.47 164.81 5.44 329.63 293.66 659.26 123.47 164.81 5.45 329.63 293.66 659.26 123.47 164.81 5.46 329.63 293.66 659.26 123.47 164.81 5.47 329.63 293.66 659.26 123.47 164.81 5.48 329.63 293.66 659.26 123.47 164.81 5.49 329.63 293.66 659.26 123.47 164.81 5.50 329.63 293.66 659.26 123.47 164.81 5.51 329.63 293.66 659.26 123.47 164.81 5.52 329.63 293.66 659.26 123.47 164.81 5.53 329.63 293.66 659.26 123.47 164.81 5.54 329.63 293.66 659.26 123.47 164.81 5.55 329.63 293.66 659.26 123.47 164.81 5.56 329.63 293.66 659.26 123.47 164.81 5.57 329.63 293.66 659.26 123.47 164.81 5.58 329.63 293.66 659.26 123.47 164.81 5.59 329.63 293.66 659.26 123.47 164.81 5.60 329.63 293.66 659.26 123.47 164.81 5.61 329.63 293.66 659.26 123.47 164.81 5.62 329.63 293.66 659.26 123.47 164.81 5.63 329.63 293.66 659.26 123.47 164.81 5.64 329.63 293.66 659.26 123.47 164.81 5.65 329.63 293.66 659.26 123.47 164.81 739.99 5.66 329.63 293.66 659.26 123.47 164.81 739.99 5.67 329.63 293.66 123.47 164.81 739.99 5.68 329.63 293.66 123.47 164.81 739.99 5.69 329.63 293.66 123.47 164.81 739.99 5.70 329.63 293.66 123.47 164.81 739.99 5.71 329.63 293.66 123.47 164.81 739.99 5.72 329.63 293.66 123.47 164.81 739.99 5.73 329.63 293.66 123.47 164.81 739.99 5.74 329.63 293.66 123.47 164.81 739.99 5.75 329.63 293.66 123.47 164.81 739.99 5.76 329.63 293.66 123.47 164.81 739.99 5.77 329.63 293.66 123.47 164.81 739.99 5.78 329.63 293.66 123.47 164.81 739.99 5.79 329.63 293.66 123.47 164.81 739.99 5.80 329.63 293.66 123.47 164.81 739.99 5.81 329.63 293.66 123.47 164.81 739.99 5.82 329.63 293.66 123.47 164.81 739.99 830.61 5.83 329.63 293.66 123.47 164.81 739.99 830.61 5.84 329.63 293.66 123.47 164.81 830.61 5.85 329.63 293.66 123.47 164.81 830.61 5.86 329.63 293.66 123.47 164.81 830.61 5.87 329.63 293.66 123.47 164.81 830.61 5.88 329.63 293.66 123.47 164.81 830.61 5.89 329.63 293.66 123.47 164.81 830.61 5.90 329.63 293.66 123.47 164.81 830.61 5.91 329.63 293.66 123.47 164.81 830.61 5.92 329.63 293.66 123.47 164.81 830.61 5.93 329.63 293.66 123.47 164.81 830.61 5.94 329.63 293.66 123.47 164.81 830.61 5.95 329.63 293.66 123.47 164.81 830.61 5.96 329.63 293.66 123.47 164.81 830.61 110.00 5.97 329.63 293.66 123.47 164.81 830.61 110.00 5.98 329.63 293.66 123.47 164.81 830.61 110.00 880.00 5.99 329.63 293.66 123.47 164.81 830.61 110.00 880.00 6.00 329.63 293.66 164.81 830.61 110.00 880.00 220.00 6.01 329.63 293.66 110.00 880.00 220.00 6.02 329.63 293.66 110.00 880.00 220.00 6.03 329.63 293.66 110.00 880.00 220.00 6.04 329.63 293.66 110.00 880.00 220.00 6.05 293.66 110.00 880.00 220.00 6.06 293.66 110.00 880.00 220.00 6.07 293.66 110.00 880.00 220.00 6.08 293.66 110.00 880.00 220.00 6.09 293.66 110.00 880.00 220.00 6.10 293.66 110.00 880.00 220.00 6.11 293.66 110.00 880.00 220.00 6.12 293.66 110.00 880.00 220.00 6.13 293.66 110.00 880.00 220.00 6.14 293.66 110.00 880.00 220.00 6.15 293.66 110.00 880.00 220.00 6.16 293.66 110.00 880.00 220.00 6.17 293.66 110.00 880.00 220.00 6.18 293.66 110.00 880.00 220.00 6.19 293.66 110.00 880.00 220.00 6.20 293.66 110.00 880.00 220.00 6.21 293.66 110.00 880.00 220.00 6.22 293.66 110.00 880.00 220.00 6.23 293.66 110.00 880.00 220.00 6.24 293.66 110.00 880.00 220.00 6.25 293.66 110.00 880.00 220.00 6.26 293.66 110.00 880.00 220.00 6.27 293.66 110.00 880.00 220.00 6.28 293.66 110.00 880.00 220.00 6.29 293.66 110.00 880.00 220.00 6.30 293.66 110.00 880.00 220.00 164.81 6.31 293.66 110.00 880.00 220.00 164.81 329.63 6.32 293.66 110.00 880.00 220.00 164.81 329.63 6.33 293.66 110.00 880.00 220.00 164.81 329.63 6.34 293.66 110.00 880.00 220.00 164.81 329.63 830.61 6.35 293.66 110.00 220.00 164.81 329.63 830.61 6.36 293.66 110.00 220.00 164.81 329.63 830.61 6.37 293.66 110.00 164.81 329.63 830.61 6.38 293.66 110.00 164.81 329.63 830.61 6.39 293.66 110.00 164.81 329.63 830.61 6.40 293.66 110.00 164.81 329.63 830.61 6.41 293.66 110.00 164.81 329.63 830.61 6.42 293.66 110.00 164.81 329.63 830.61 6.43 293.66 110.00 164.81 329.63 830.61 6.44 293.66 110.00 164.81 329.63 830.61 6.45 293.66 110.00 164.81 329.63 830.61 6.46 293.66 110.00 164.81 329.63 830.61 6.47 293.66 110.00 164.81 329.63 830.61 6.48 293.66 110.00 164.81 329.63 830.61 6.49 293.66 110.00 164.81 329.63 830.61 6.50 293.66 110.00 164.81 329.63 830.61 6.51 293.66 110.00 164.81 329.63 830.61 739.99 6.52 293.66 110.00 164.81 329.63 830.61 739.99 6.53 293.66 110.00 164.81 329.63 830.61 739.99 6.54 293.66 110.00 164.81 329.63 830.61 739.99 6.55 293.66 110.00 164.81 329.63 830.61 739.99 6.56 293.66 110.00 164.81 329.63 830.61 739.99 6.57 293.66 110.00 164.81 329.63 739.99 6.58 293.66 110.00 164.81 329.63 739.99 6.59 293.66 110.00 164.81 329.63 739.99 6.60 293.66 110.00 164.81 329.63 739.99 6.61 293.66 110.00 164.81 329.63 739.99 6.62 293.66 110.00 329.63 739.99 6.63 293.66 110.00 329.63 739.99 6.64 293.66 110.00 329.63 739.99 6.65 293.66 110.00 329.63 739.99 6.66 293.66 110.00 329.63 739.99 6.67 293.66 110.00 739.99 246.94 493.88 6.68 293.66 110.00 739.99 246.94 493.88 6.69 293.66 110.00 739.99 246.94 493.88 103.83 164.81 6.70 293.66 110.00 739.99 246.94 493.88 103.83 164.81 659.26 6.71 293.66 110.00 739.99 246.94 493.88 103.83 164.81 659.26 329.63 6.72 293.66 110.00 739.99 246.94 493.88 103.83 164.81 659.26 329.63 6.73 293.66 739.99 246.94 493.88 103.83 164.81 659.26 329.63 6.74 293.66 246.94 493.88 103.83 164.81 659.26 329.63 6.75 293.66 246.94 493.88 103.83 164.81 659.26 329.63 6.76 246.94 493.88 103.83 164.81 659.26 329.63 6.77 246.94 493.88 103.83 164.81 659.26 329.63 6.78 246.94 493.88 103.83 164.81 659.26 329.63 6.79 246.94 493.88 103.83 164.81 659.26 329.63 6.80 246.94 493.88 103.83 164.81 659.26 329.63 6.81 246.94 493.88 103.83 164.81 659.26 329.63 6.82 246.94 493.88 103.83 164.81 659.26 329.63 6.83 246.94 493.88 103.83 164.81 659.26 329.63 6.84 246.94 493.88 103.83 164.81 659.26 329.63 6.85 246.94 493.88 103.83 164.81 659.26 329.63 6.86 246.94 493.88 103.83 164.81 659.26 329.63 6.87 246.94 493.88 103.83 164.81 659.26 329.63 6.88 246.94 493.88 103.83 164.81 659.26 329.63 6.89 246.94 493.88 103.83 164.81 659.26 329.63 6.90 246.94 493.88 103.83 164.81 659.26 329.63 6.91 246.94 493.88 103.83 164.81 659.26 329.63 6.92 246.94 493.88 103.83 164.81 659.26 329.63 6.93 246.94 493.88 103.83 164.81 659.26 329.63 6.94 246.94 493.88 103.83 164.81 659.26 329.63 6.95 246.94 493.88 103.83 164.81 659.26 329.63 6.96 246.94 493.88 103.83 164.81 659.26 329.63 6.97 246.94 493.88 103.83 164.81 659.26 329.63 6.98 246.94 493.88 103.83 164.81 659.26 329.63 6.99 246.94 493.88 103.83 164.81 659.26 329.63 7.00 246.94 493.88 103.83 164.81 659.26 329.63 7.01 246.94 493.88 103.83 164.81 659.26 329.63 7.02 246.94 493.88 103.83 164.81 659.26 329.63 7.03 246.94 493.88 103.83 164.81 659.26 329.63 277.18 554.37 7.04 246.94 493.88 103.83 164.81 659.26 329.63 277.18 554.37 7.05 493.88 103.83 164.81 659.26 329.63 277.18 554.37 7.06 493.88 103.83 164.81 659.26 329.63 277.18 554.37 7.07 493.88 103.83 164.81 659.26 329.63 277.18 554.37 7.08 103.83 164.81 659.26 329.63 277.18 554.37 7.09 103.83 164.81 659.26 329.63 277.18 554.37 7.10 103.83 164.81 659.26 329.63 277.18 554.37 7.11 103.83 164.81 659.26 329.63 277.18 554.37 7.12 103.83 164.81 659.26 329.63 277.18 554.37 7.13 103.83 164.81 659.26 329.63 277.18 554.37 7.14 103.83 164.81 659.26 329.63 277.18 554.37 7.15 103.83 164.81 659.26 329.63 277.18 554.37 7.16 103.83 164.81 659.26 329.63 277.18 554.37 7.17 103.83 164.81 659.26 329.63 277.18 554.37 7.18 103.83 164.81 659.26 329.63 277.18 554.37 7.19 103.83 164.81 659.26 329.63 277.18 554.37 7.20 103.83 164.81 659.26 329.63 277.18 554.37 7.21 103.83 164.81 659.26 329.63 277.18 554.37 7.22 103.83 164.81 659.26 329.63 277.18 554.37 7.23 103.83 164.81 659.26 329.63 277.18 554.37 7.24 103.83 164.81 659.26 329.63 277.18 554.37 7.25 103.83 164.81 659.26 329.63 277.18 554.37 7.26 103.83 164.81 659.26 329.63 277.18 554.37 7.27 103.83 164.81 659.26 329.63 277.18 554.37 7.28 103.83 164.81 659.26 329.63 277.18 554.37 7.29 103.83 164.81 659.26 329.63 277.18 554.37 7.30 103.83 164.81 659.26 329.63 277.18 554.37 7.31 103.83 164.81 659.26 329.63 277.18 554.37 7.32 103.83 164.81 659.26 329.63 277.18 554.37 7.33 103.83 164.81 659.26 329.63 277.18 554.37 7.34 103.83 164.81 659.26 329.63 277.18 554.37 7.35 103.83 164.81 659.26 329.63 277.18 554.37 7.36 103.83 164.81 659.26 329.63 277.18 554.37 7.37 103.83 164.81 659.26 329.63 277.18 554.37 7.38 103.83 164.81 659.26 329.63 277.18 554.37 7.39 103.83 164.81 659.26 329.63 277.18 554.37 7.40 103.83 164.81 659.26 329.63 277.18 554.37 440.00 7.41 103.83 164.81 659.26 329.63 277.18 554.37 440.00 587.33 293.66 7.42 103.83 164.81 659.26 329.63 277.18 440.00 587.33 293.66 7.43 103.83 164.81 659.26 329.63 440.00 587.33 293.66 92.50 7.44 103.83 164.81 659.26 440.00 587.33 293.66 92.50 7.45 103.83 164.81 659.26 440.00 587.33 293.66 92.50 7.46 103.83 164.81 659.26 440.00 587.33 293.66 92.50 7.47 103.83 164.81 659.26 440.00 587.33 293.66 92.50 7.48 103.83 164.81 659.26 440.00 587.33 293.66 92.50 7.49 164.81 659.26 440.00 587.33 293.66 92.50 7.50 164.81 440.00 587.33 293.66 92.50 7.51 164.81 440.00 587.33 293.66 92.50 7.52 164.81 440.00 587.33 293.66 92.50 7.53 164.81 440.00 587.33 293.66 92.50 7.54 164.81 440.00 587.33 293.66 92.50 7.55 164.81 440.00 587.33 293.66 92.50 7.56 164.81 440.00 587.33 293.66 92.50 7.57 164.81 440.00 587.33 293.66 92.50 7.58 164.81 440.00 587.33 293.66 92.50 7.59 164.81 440.00 587.33 293.66 92.50 7.60 164.81 440.00 587.33 293.66 92.50 7.61 164.81 440.00 587.33 293.66 92.50 7.62 164.81 440.00 587.33 293.66 92.50 7.63 164.81 440.00 587.33 293.66 92.50 7.64 164.81 440.00 587.33 293.66 92.50 7.65 164.81 440.00 587.33 293.66 92.50 7.66 164.81 440.00 587.33 293.66 92.50 7.67 164.81 440.00 587.33 293.66 92.50 7.68 164.81 440.00 587.33 293.66 92.50 7.69 164.81 440.00 587.33 293.66 92.50 7.70 164.81 440.00 587.33 293.66 92.50 7.71 164.81 440.00 587.33 293.66 92.50 659.26 7.72 164.81 440.00 587.33 293.66 92.50 659.26 7.73 164.81 440.00 587.33 293.66 92.50 659.26 7.74 164.81 440.00 587.33 293.66 92.50 659.26 7.75 164.81 440.00 587.33 293.66 92.50 659.26 7.76 164.81 440.00 587.33 293.66 92.50 659.26 7.77 164.81 440.00 293.66 92.50 659.26 7.78 164.81 440.00 293.66 92.50 659.26 554.37 7.79 164.81 440.00 293.66 92.50 659.26 554.37 277.18 7.80 164.81 440.00 293.66 92.50 659.26 554.37 277.18 7.81 164.81 440.00 293.66 92.50 659.26 554.37 277.18 7.82 164.81 440.00 92.50 659.26 554.37 277.18 7.83 164.81 440.00 92.50 659.26 554.37 277.18 7.84 164.81 440.00 92.50 659.26 554.37 277.18 7.85 164.81 440.00 92.50 659.26 554.37 277.18 7.86 164.81 440.00 92.50 659.26 554.37 277.18 7.87 164.81 440.00 92.50 659.26 554.37 277.18 7.88 164.81 440.00 92.50 659.26 554.37 277.18 7.89 164.81 440.00 92.50 659.26 554.37 277.18 7.90 164.81 440.00 92.50 659.26 277.18 7.91 164.81 440.00 92.50 659.26 277.18 7.92 164.81 440.00 92.50 659.26 277.18 587.33 7.93 164.81 440.00 92.50 659.26 277.18 587.33 7.94 164.81 440.00 92.50 659.26 277.18 587.33 7.95 164.81 440.00 92.50 659.26 277.18 587.33 7.96 164.81 440.00 92.50 659.26 277.18 587.33 293.66 7.97 164.81 440.00 92.50 659.26 277.18 587.33 293.66 7.98 164.81 440.00 92.50 659.26 277.18 587.33 293.66 7.99 164.81 440.00 92.50 659.26 277.18 587.33 293.66 8.00 164.81 440.00 92.50 659.26 587.33 293.66 8.01 164.81 440.00 92.50 659.26 587.33 293.66 8.02 164.81 440.00 92.50 659.26 587.33 293.66 8.03 164.81 440.00 92.50 659.26 587.33 293.66 8.04 440.00 92.50 659.26 587.33 293.66 8.05 440.00 92.50 659.26 587.33 293.66 8.06 440.00 92.50 659.26 587.33 293.66 8.07 440.00 92.50 659.26 587.33 293.66 8.08 440.00 92.50 659.26 587.33 293.66 8.09 440.00 92.50 659.26 293.66 8.10 440.00 92.50 659.26 293.66 987.77 8.11 440.00 92.50 659.26 293.66 987.77 82.41 8.12 440.00 92.50 659.26 293.66 987.77 82.41 8.13 440.00 92.50 659.26 293.66 987.77 82.41 493.88 246.94 8.14 440.00 92.50 293.66 987.77 82.41 493.88 246.94 164.81 415.30 8.15 440.00 92.50 293.66 987.77 82.41 493.88 246.94 164.81 415.30 8.16 440.00 987.77 82.41 493.88 246.94 164.81 415.30 8.17 440.00 987.77 82.41 493.88 246.94 164.81 415.30 8.18 440.00 987.77 82.41 493.88 246.94 164.81 415.30 8.19 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.20 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.21 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.22 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.23 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.24 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.25 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.26 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.27 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.28 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.29 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.30 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.31 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.32 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.33 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.34 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.35 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.36 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.37 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.38 440.00 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.39 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.40 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.41 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.42 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.43 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.44 987.77 82.41 493.88 246.94 164.81 415.30 415.30 8.45 987.77 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.46 987.77 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.47 987.77 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.48 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.49 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.50 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.51 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.52 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.53 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.54 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.55 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.56 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.57 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.58 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.59 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.60 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.61 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.62 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.63 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.64 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.65 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.66 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.67 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.68 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.69 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.70 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.71 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.72 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.73 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.74 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.75 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.76 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.77 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.78 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.79 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.80 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.81 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 8.82 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 1174.66 8.83 82.41 493.88 246.94 164.81 415.30 415.30 1108.73 1174.66 8.84 82.41 493.88 246.94 164.81 415.30 415.30 1174.66 8.85 82.41 493.88 246.94 164.81 415.30 415.30 1174.66 8.86 82.41 493.88 246.94 164.81 415.30 415.30 1174.66 8.87 82.41 493.88 246.94 164.81 415.30 1174.66 8.88 82.41 493.88 246.94 164.81 415.30 1174.66 8.89 82.41 493.88 246.94 164.81 415.30 1174.66 8.90 82.41 246.94 164.81 415.30 1174.66 8.91 82.41 246.94 164.81 415.30 1174.66 8.92 82.41 246.94 164.81 415.30 1174.66 8.93 82.41 164.81 415.30 1174.66 8.94 82.41 164.81 415.30 1174.66 8.95 82.41 164.81 415.30 1174.66 8.96 82.41 164.81 415.30 1174.66 8.97 82.41 164.81 415.30 1174.66 8.98 82.41 164.81 415.30 1174.66 8.99 82.41 164.81 415.30 1174.66 9.00 82.41 164.81 415.30 1174.66 9.01 82.41 164.81 415.30 1174.66 9.02 82.41 164.81 415.30 1174.66 9.03 82.41 164.81 415.30 1174.66 9.04 82.41 164.81 415.30 1174.66 9.05 82.41 164.81 415.30 1174.66 9.06 82.41 164.81 415.30 1174.66 9.07 82.41 164.81 415.30 1174.66 9.08 82.41 164.81 415.30 1174.66 9.09 82.41 164.81 415.30 1174.66 9.10 82.41 164.81 415.30 1174.66 9.11 82.41 164.81 415.30 1174.66 9.12 82.41 164.81 415.30 1174.66 9.13 82.41 164.81 415.30 1174.66 9.14 82.41 164.81 415.30 1174.66 9.15 82.41 164.81 415.30 1174.66 9.16 82.41 164.81 415.30 1174.66 9.17 82.41 164.81 415.30 1174.66 9.18 82.41 164.81 415.30 1174.66 246.94 493.88 9.19 82.41 164.81 415.30 1174.66 246.94 493.88 9.20 82.41 164.81 415.30 1174.66 246.94 493.88 9.21 82.41 164.81 415.30 1174.66 246.94 493.88 1108.73 9.22 82.41 164.81 415.30 1174.66 246.94 493.88 1108.73 9.23 82.41 164.81 415.30 246.94 493.88 1108.73 9.24 82.41 164.81 415.30 246.94 493.88 1108.73 9.25 82.41 164.81 415.30 246.94 493.88 1108.73 9.26 82.41 164.81 415.30 246.94 493.88 1108.73 9.27 82.41 164.81 415.30 246.94 493.88 1108.73 9.28 82.41 164.81 415.30 246.94 493.88 1108.73 9.29 82.41 164.81 415.30 246.94 493.88 1108.73 9.30 82.41 164.81 415.30 246.94 493.88 1108.73 9.31 82.41 164.81 415.30 246.94 493.88 1108.73 9.32 82.41 164.81 415.30 246.94 493.88 1108.73 9.33 82.41 164.81 415.30 246.94 493.88 1108.73 9.34 82.41 164.81 415.30 246.94 493.88 1108.73 9.35 82.41 164.81 415.30 246.94 493.88 9.36 82.41 164.81 415.30 246.94 493.88 1174.66 9.37 82.41 164.81 415.30 246.94 493.88 1174.66 9.38 82.41 164.81 415.30 246.94 493.88 1174.66 9.39 82.41 164.81 415.30 246.94 493.88 1174.66 9.40 82.41 164.81 246.94 493.88 1174.66 9.41 82.41 164.81 246.94 493.88 1174.66 9.42 82.41 164.81 246.94 493.88 1174.66 9.43 82.41 164.81 246.94 493.88 1174.66 9.44 82.41 164.81 246.94 493.88 1174.66 9.45 82.41 164.81 246.94 493.88 1174.66 9.46 82.41 164.81 246.94 493.88 1174.66 9.47 82.41 164.81 246.94 493.88 1174.66 9.48 82.41 164.81 246.94 493.88 1174.66 9.49 82.41 164.81 246.94 493.88 1174.66 9.50 82.41 164.81 246.94 493.88 1174.66 9.51 82.41 164.81 246.94 493.88 1174.66 587.33 9.52 82.41 164.81 246.94 493.88 1174.66 587.33 293.66 9.53 82.41 164.81 246.94 493.88 1174.66 587.33 293.66 369.99 123.47 369.99 9.54 82.41 164.81 246.94 1174.66 587.33 293.66 369.99 123.47 369.99 185.00 9.55 164.81 246.94 587.33 293.66 369.99 123.47 369.99 185.00 9.56 164.81 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.57 164.81 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.58 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.59 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.60 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.61 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.62 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.63 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.64 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.65 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.66 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.67 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.68 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.69 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.70 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.71 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.72 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.73 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.74 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.75 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.76 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.77 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.78 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.79 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.80 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.81 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.82 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.83 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.84 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.85 587.33 293.66 369.99 123.47 369.99 185.00 987.77 9.86 587.33 293.66 369.99 123.47 369.99 185.00 987.77 246.94 9.87 587.33 293.66 369.99 123.47 369.99 185.00 987.77 246.94 9.88 587.33 293.66 369.99 123.47 369.99 185.00 987.77 246.94 493.88 9.89 587.33 293.66 369.99 123.47 369.99 185.00 987.77 246.94 493.88 9.90 369.99 123.47 369.99 185.00 987.77 246.94 493.88 9.91 369.99 123.47 369.99 185.00 987.77 246.94 493.88 9.92 123.47 369.99 185.00 987.77 246.94 493.88 9.93 123.47 369.99 185.00 987.77 246.94 493.88 9.94 123.47 369.99 185.00 987.77 246.94 493.88 9.95 123.47 369.99 185.00 987.77 246.94 493.88 9.96 123.47 369.99 185.00 987.77 246.94 493.88 9.97 123.47 369.99 185.00 987.77 246.94 493.88 9.98 123.47 369.99 185.00 987.77 246.94 493.88 9.99 123.47 369.99 185.00 987.77 246.94 493.88 10.00 123.47 369.99 185.00 987.77 246.94 493.88 10.01 123.47 369.99 185.00 987.77 246.94 493.88 10.02 123.47 369.99 185.00 987.77 246.94 493.88 10.03 123.47 369.99 185.00 987.77 246.94 493.88 10.04 123.47 369.99 185.00 987.77 246.94 493.88 10.05 123.47 369.99 185.00 987.77 246.94 493.88 10.06 123.47 369.99 185.00 987.77 246.94 493.88 10.07 123.47 369.99 185.00 987.77 246.94 493.88 10.08 123.47 369.99 185.00 987.77 246.94 493.88 10.09 123.47 369.99 185.00 987.77 246.94 493.88 10.10 123.47 369.99 185.00 987.77 246.94 493.88 10.11 123.47 369.99 185.00 987.77 246.94 493.88 10.12 123.47 369.99 185.00 987.77 246.94 493.88 10.13 369.99 185.00 987.77 246.94 493.88 10.14 369.99 185.00 987.77 246.94 493.88 10.15 369.99 185.00 987.77 246.94 493.88 10.16 369.99 185.00 987.77 246.94 493.88 10.17 369.99 185.00 987.77 246.94 493.88 10.18 369.99 185.00 987.77 246.94 493.88 10.19 369.99 185.00 987.77 246.94 493.88 392.00 82.41 10.20 369.99 987.77 246.94 493.88 392.00 82.41 196.00 10.21 369.99 987.77 246.94 493.88 392.00 82.41 196.00 123.47 10.22 369.99 987.77 246.94 493.88 392.00 82.41 196.00 123.47 10.23 987.77 246.94 493.88 392.00 82.41 196.00 123.47 329.63 10.24 987.77 246.94 493.88 392.00 82.41 196.00 123.47 329.63 659.26 10.25 987.77 246.94 493.88 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.26 987.77 246.94 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.27 987.77 246.94 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.28 987.77 246.94 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.29 987.77 246.94 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.30 987.77 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.31 987.77 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.32 987.77 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.33 987.77 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.34 987.77 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.35 987.77 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.36 987.77 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.37 987.77 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.38 987.77 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.39 987.77 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.40 987.77 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.41 987.77 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.42 987.77 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.43 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.44 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.45 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.46 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.47 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.48 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.49 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.50 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.51 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.52 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.53 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.54 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.55 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.56 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.57 392.00 82.41 196.00 123.47 329.63 659.26 392.00 10.58 392.00 82.41 196.00 123.47 329.63 659.26 392.00 987.77 293.66 587.33 10.59 392.00 82.41 196.00 123.47 329.63 659.26 392.00 987.77 293.66 587.33 10.60 392.00 82.41 196.00 123.47 329.63 392.00 987.77 293.66 587.33 98.00 10.61 392.00 82.41 196.00 123.47 329.63 392.00 987.77 293.66 587.33 98.00 10.62 392.00 82.41 196.00 329.63 392.00 987.77 293.66 587.33 98.00 10.63 392.00 82.41 196.00 329.63 392.00 987.77 293.66 587.33 98.00 10.64 392.00 82.41 196.00 329.63 392.00 987.77 293.66 587.33 98.00 10.65 392.00 82.41 196.00 392.00 987.77 293.66 587.33 98.00 10.66 392.00 82.41 196.00 392.00 987.77 293.66 587.33 98.00 10.67 392.00 82.41 196.00 392.00 987.77 293.66 587.33 98.00 10.68 392.00 82.41 196.00 392.00 987.77 293.66 587.33 98.00 10.69 392.00 82.41 196.00 392.00 987.77 293.66 587.33 98.00 10.70 392.00 82.41 196.00 392.00 987.77 293.66 587.33 98.00 10.71 392.00 82.41 196.00 392.00 987.77 293.66 587.33 98.00 10.72 392.00 82.41 196.00 392.00 987.77 293.66 587.33 98.00 10.73 392.00 82.41 196.00 392.00 987.77 293.66 587.33 98.00 10.74 392.00 82.41 196.00 392.00 987.77 293.66 587.33 98.00 554.37 10.75 392.00 82.41 196.00 392.00 987.77 293.66 587.33 98.00 554.37 10.76 392.00 82.41 196.00 392.00 987.77 293.66 587.33 98.00 554.37 10.77 392.00 82.41 196.00 392.00 987.77 293.66 587.33 98.00 554.37 277.18 10.78 392.00 82.41 196.00 392.00 987.77 293.66 98.00 554.37 277.18 10.79 82.41 196.00 392.00 987.77 293.66 98.00 554.37 277.18 10.80 196.00 392.00 987.77 293.66 98.00 554.37 277.18 10.81 196.00 392.00 987.77 293.66 98.00 554.37 277.18 10.82 196.00 392.00 987.77 293.66 98.00 554.37 277.18 10.83 196.00 392.00 987.77 98.00 554.37 277.18 10.84 196.00 392.00 987.77 98.00 554.37 277.18 10.85 196.00 392.00 987.77 98.00 554.37 277.18 10.86 196.00 392.00 987.77 98.00 554.37 277.18 10.87 196.00 392.00 987.77 98.00 554.37 277.18 10.88 196.00 392.00 987.77 98.00 554.37 277.18 10.89 196.00 392.00 987.77 98.00 554.37 277.18 10.90 196.00 392.00 987.77 98.00 554.37 277.18 10.91 196.00 392.00 987.77 98.00 554.37 277.18 10.92 196.00 392.00 987.77 98.00 554.37 277.18 10.93 196.00 392.00 987.77 98.00 554.37 277.18 10.94 196.00 392.00 987.77 98.00 554.37 277.18 10.95 196.00 392.00 987.77 98.00 554.37 277.18 10.96 196.00 392.00 987.77 98.00 554.37 277.18 246.94 10.97 196.00 392.00 987.77 98.00 554.37 277.18 246.94 293.66 493.88 1174.66 10.98 196.00 392.00 987.77 98.00 554.37 277.18 246.94 293.66 493.88 1174.66 10.99 392.00 987.77 98.00 277.18 246.94 293.66 493.88 1174.66 185.00 11.00 987.77 98.00 277.18 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.01 987.77 98.00 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.02 98.00 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.03 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.04 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.05 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.06 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.07 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.08 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.09 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.10 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.11 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.12 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.13 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.14 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.15 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.16 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.17 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.18 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.19 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.20 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.21 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.22 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.23 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.24 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.25 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.26 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.27 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.28 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.29 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.30 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.31 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.32 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.33 246.94 293.66 493.88 1174.66 185.00 246.94 123.47 293.66 11.34 246.94 293.66 493.88 185.00 246.94 123.47 293.66 987.77 246.94 11.35 246.94 293.66 493.88 185.00 246.94 123.47 293.66 987.77 246.94 11.36 246.94 293.66 493.88 185.00 246.94 123.47 293.66 987.77 246.94 11.37 246.94 293.66 493.88 185.00 246.94 123.47 293.66 987.77 246.94 11.38 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.39 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.40 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.41 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.42 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.43 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.44 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.45 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.46 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.47 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.48 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.49 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.50 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.51 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.52 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.53 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.54 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.55 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.56 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.57 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.58 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.59 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.60 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.61 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.62 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 11.63 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 293.66 11.64 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 293.66 11.65 246.94 293.66 493.88 246.94 123.47 293.66 987.77 246.94 293.66 11.66 293.66 493.88 246.94 123.47 293.66 987.77 246.94 293.66 11.67 293.66 493.88 246.94 123.47 293.66 987.77 246.94 293.66 11.68 293.66 246.94 123.47 293.66 987.77 246.94 293.66 11.69 293.66 246.94 123.47 293.66 987.77 246.94 293.66 11.70 293.66 246.94 123.47 293.66 987.77 246.94 293.66 1318.51 11.71 293.66 246.94 123.47 293.66 987.77 246.94 293.66 1318.51 11.72 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.73 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.74 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.75 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.76 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.77 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.78 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.79 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.80 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.81 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.82 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.83 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.84 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.85 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.86 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.87 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.88 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.89 293.66 246.94 123.47 293.66 246.94 293.66 1318.51 11.90 293.66 123.47 293.66 246.94 293.66 1318.51 11.91 293.66 123.47 293.66 246.94 293.66 1318.51 11.92 293.66 123.47 293.66 246.94 293.66 1318.51 11.93 293.66 123.47 293.66 246.94 293.66 1318.51 11.94 293.66 123.47 293.66 246.94 293.66 1318.51 11.95 293.66 123.47 293.66 246.94 293.66 1318.51 11.96 293.66 123.47 293.66 246.94 293.66 1318.51 11.97 293.66 123.47 293.66 246.94 293.66 1318.51 11.98 293.66 123.47 293.66 246.94 293.66 1318.51 11.99 293.66 123.47 293.66 246.94 293.66 1318.51 12.00 293.66 123.47 293.66 246.94 293.66 1318.51 12.01 293.66 123.47 293.66 246.94 293.66 1318.51 12.02 123.47 293.66 246.94 293.66 1318.51 12.03 123.47 246.94 293.66 1318.51 369.99 12.04 123.47 246.94 293.66 1318.51 369.99 880.00 12.05 123.47 246.94 1318.51 369.99 880.00 440.00 12.06 123.47 246.94 1318.51 369.99 880.00 440.00 440.00 1174.66 12.07 123.47 246.94 1318.51 369.99 880.00 440.00 440.00 1174.66 12.08 123.47 246.94 1318.51 369.99 880.00 440.00 440.00 1174.66 12.09 123.47 246.94 369.99 880.00 440.00 440.00 1174.66 12.10 123.47 369.99 880.00 440.00 440.00 1174.66 12.11 123.47 369.99 880.00 440.00 440.00 1174.66 12.12 123.47 369.99 880.00 440.00 440.00 1174.66 12.13 123.47 369.99 880.00 440.00 440.00 1174.66 12.14 123.47 369.99 880.00 440.00 440.00 1174.66 12.15 123.47 369.99 880.00 440.00 440.00 1174.66 12.16 123.47 369.99 880.00 440.00 440.00 1174.66 12.17 123.47 369.99 880.00 440.00 440.00 1174.66 12.18 123.47 369.99 880.00 440.00 440.00 1174.66 12.19 123.47 369.99 880.00 440.00 440.00 1174.66 12.20 123.47 369.99 880.00 440.00 440.00 1174.66 12.21 123.47 369.99 880.00 440.00 440.00 1174.66 12.22 123.47 369.99 880.00 440.00 440.00 1174.66 12.23 123.47 369.99 880.00 440.00 440.00 1174.66 12.24 123.47 369.99 880.00 440.00 440.00 1174.66 1108.73 12.25 123.47 369.99 880.00 440.00 440.00 1174.66 1108.73 12.26 123.47 369.99 880.00 440.00 440.00 1174.66 1108.73 12.27 123.47 369.99 880.00 440.00 440.00 1108.73 12.28 123.47 369.99 880.00 440.00 440.00 1108.73 12.29 123.47 369.99 880.00 440.00 440.00 1108.73 12.30 123.47 369.99 880.00 440.00 440.00 1108.73 12.31 123.47 369.99 880.00 440.00 440.00 1108.73 12.32 123.47 369.99 880.00 440.00 440.00 1108.73 12.33 123.47 369.99 880.00 440.00 440.00 1108.73 12.34 123.47 369.99 880.00 440.00 440.00 1108.73 12.35 123.47 369.99 880.00 440.00 440.00 1108.73 12.36 123.47 369.99 880.00 440.00 440.00 1108.73 12.37 123.47 369.99 880.00 440.00 440.00 1108.73 12.38 123.47 369.99 880.00 440.00 440.00 1108.73 12.39 123.47 369.99 880.00 440.00 440.00 1108.73 12.40 123.47 369.99 880.00 440.00 440.00 1108.73 12.41 123.47 369.99 880.00 440.00 440.00 1108.73 12.42 123.47 369.99 880.00 440.00 440.00 1108.73 164.81 587.33 12.43 123.47 369.99 880.00 440.00 440.00 1108.73 164.81 587.33 415.30 12.44 123.47 369.99 880.00 440.00 440.00 164.81 587.33 415.30 246.94 987.77 830.61 12.45 123.47 369.99 880.00 440.00 164.81 587.33 415.30 246.94 987.77 830.61 12.46 123.47 369.99 164.81 587.33 415.30 246.94 987.77 830.61 12.47 123.47 369.99 164.81 587.33 415.30 246.94 987.77 830.61 12.48 123.47 369.99 164.81 587.33 415.30 246.94 987.77 830.61 12.49 369.99 164.81 587.33 415.30 246.94 987.77 830.61 12.50 164.81 587.33 415.30 246.94 987.77 830.61 12.51 164.81 587.33 415.30 246.94 987.77 830.61 12.52 164.81 587.33 415.30 246.94 987.77 830.61 12.53 164.81 587.33 415.30 246.94 987.77 830.61 12.54 164.81 587.33 415.30 246.94 987.77 830.61 12.55 164.81 587.33 415.30 246.94 987.77 830.61 12.56 164.81 587.33 415.30 246.94 987.77 830.61 12.57 164.81 587.33 415.30 246.94 987.77 830.61 12.58 164.81 587.33 415.30 246.94 987.77 830.61 12.59 164.81 587.33 415.30 246.94 987.77 830.61 12.60 164.81 587.33 415.30 246.94 987.77 830.61 12.61 164.81 587.33 415.30 246.94 987.77 830.61 12.62 164.81 587.33 415.30 246.94 987.77 830.61 12.63 164.81 587.33 415.30 246.94 987.77 830.61 12.64 164.81 587.33 415.30 246.94 987.77 830.61 12.65 164.81 587.33 415.30 246.94 987.77 830.61 12.66 164.81 587.33 415.30 246.94 987.77 830.61 12.67 164.81 587.33 415.30 246.94 987.77 830.61 12.68 164.81 587.33 415.30 246.94 987.77 830.61 12.69 164.81 587.33 415.30 246.94 987.77 830.61 12.70 164.81 587.33 415.30 246.94 987.77 830.61 12.71 164.81 587.33 415.30 246.94 987.77 830.61 12.72 164.81 587.33 415.30 246.94 987.77 830.61 12.73 164.81 587.33 415.30 246.94 987.77 830.61 12.74 164.81 587.33 415.30 246.94 987.77 830.61 12.75 164.81 587.33 415.30 246.94 987.77 830.61 12.76 164.81 587.33 415.30 246.94 987.77 830.61 12.77 164.81 587.33 415.30 246.94 987.77 830.61 12.78 164.81 587.33 415.30 246.94 987.77 830.61 12.79 164.81 587.33 415.30 246.94 987.77 830.61 12.80 164.81 587.33 415.30 246.94 987.77 830.61 12.81 164.81 587.33 415.30 246.94 987.77 830.61 369.99 12.82 164.81 587.33 415.30 246.94 987.77 830.61 369.99 739.99 12.83 164.81 587.33 415.30 246.94 987.77 830.61 369.99 739.99 12.84 164.81 587.33 415.30 246.94 987.77 830.61 369.99 739.99 12.85 164.81 587.33 246.94 987.77 830.61 369.99 739.99 12.86 164.81 587.33 246.94 987.77 830.61 369.99 739.99 12.87 164.81 587.33 246.94 987.77 369.99 739.99 12.88 164.81 587.33 246.94 987.77 369.99 739.99 12.89 164.81 587.33 246.94 987.77 369.99 739.99 12.90 164.81 587.33 246.94 987.77 369.99 739.99 12.91 164.81 587.33 246.94 987.77 369.99 739.99 12.92 164.81 587.33 246.94 987.77 369.99 739.99 12.93 164.81 587.33 246.94 987.77 369.99 739.99 12.94 164.81 587.33 246.94 987.77 369.99 739.99 12.95 164.81 587.33 246.94 987.77 369.99 739.99 12.96 164.81 587.33 246.94 987.77 369.99 739.99 12.97 164.81 587.33 246.94 987.77 369.99 739.99 12.98 164.81 587.33 246.94 987.77 369.99 739.99 12.99 164.81 587.33 246.94 987.77 369.99 739.99 13.00 164.81 587.33 246.94 987.77 369.99 739.99 13.01 164.81 587.33 246.94 987.77 369.99 739.99 13.02 164.81 587.33 246.94 987.77 369.99 739.99 13.03 164.81 587.33 246.94 987.77 369.99 739.99 13.04 164.81 587.33 246.94 987.77 369.99 739.99 13.05 164.81 587.33 246.94 987.77 369.99 739.99 13.06 164.81 587.33 246.94 987.77 369.99 739.99 13.07 164.81 587.33 246.94 987.77 369.99 739.99 13.08 164.81 587.33 246.94 987.77 369.99 739.99 13.09 164.81 587.33 246.94 987.77 369.99 739.99 13.10 164.81 587.33 246.94 987.77 369.99 739.99 13.11 164.81 587.33 246.94 987.77 369.99 739.99 13.12 164.81 587.33 246.94 987.77 369.99 739.99 13.13 164.81 587.33 246.94 987.77 369.99 739.99 13.14 164.81 587.33 246.94 987.77 369.99 739.99 13.15 164.81 587.33 246.94 987.77 369.99 739.99 13.16 164.81 587.33 246.94 987.77 369.99 739.99 13.17 164.81 587.33 246.94 987.77 369.99 739.99 13.18 164.81 587.33 246.94 987.77 369.99 739.99 13.19 164.81 587.33 246.94 987.77 369.99 739.99 659.26 13.20 164.81 587.33 246.94 987.77 369.99 739.99 659.26 329.63 13.21 164.81 587.33 246.94 987.77 369.99 659.26 329.63 13.22 164.81 587.33 246.94 987.77 369.99 659.26 329.63 13.23 164.81 587.33 246.94 987.77 369.99 659.26 329.63 13.24 164.81 587.33 246.94 987.77 659.26 329.63 13.25 164.81 587.33 246.94 987.77 659.26 329.63 13.26 164.81 587.33 246.94 987.77 659.26 329.63 13.27 164.81 587.33 246.94 987.77 659.26 329.63 13.28 164.81 587.33 246.94 987.77 659.26 329.63 13.29 164.81 587.33 246.94 987.77 659.26 329.63 13.30 164.81 587.33 246.94 987.77 659.26 329.63 13.31 164.81 587.33 246.94 987.77 659.26 329.63 13.32 164.81 587.33 246.94 987.77 659.26 329.63 13.33 164.81 587.33 246.94 987.77 659.26 329.63 13.34 164.81 587.33 246.94 987.77 659.26 329.63 13.35 164.81 587.33 246.94 987.77 659.26 329.63 13.36 164.81 587.33 246.94 987.77 659.26 329.63 13.37 164.81 587.33 246.94 987.77 659.26 329.63 13.38 164.81 587.33 246.94 987.77 659.26 329.63 13.39 164.81 587.33 246.94 987.77 659.26 329.63 13.40 164.81 587.33 246.94 987.77 659.26 329.63 13.41 164.81 587.33 246.94 987.77 659.26 329.63 13.42 164.81 587.33 246.94 987.77 659.26 329.63 13.43 164.81 587.33 246.94 987.77 659.26 329.63 13.44 164.81 587.33 246.94 987.77 659.26 329.63 13.45 164.81 587.33 246.94 987.77 659.26 329.63 13.46 164.81 587.33 246.94 987.77 659.26 329.63 13.47 164.81 587.33 246.94 987.77 659.26 329.63 13.48 164.81 587.33 246.94 987.77 659.26 329.63 13.49 164.81 587.33 246.94 987.77 659.26 329.63 13.50 164.81 587.33 246.94 987.77 659.26 329.63 13.51 164.81 587.33 246.94 987.77 659.26 329.63 13.52 164.81 587.33 246.94 987.77 659.26 329.63 13.53 164.81 587.33 246.94 987.77 659.26 329.63 13.54 164.81 587.33 246.94 987.77 659.26 329.63 554.37 554.37 13.55 164.81 587.33 246.94 987.77 659.26 329.63 554.37 554.37 13.56 164.81 587.33 246.94 987.77 659.26 329.63 554.37 554.37 13.57 164.81 246.94 659.26 329.63 554.37 554.37 1760.00 13.58 164.81 246.94 659.26 329.63 554.37 554.37 1760.00 13.59 164.81 246.94 659.26 329.63 554.37 554.37 1760.00 277.18 13.60 164.81 246.94 659.26 329.63 554.37 554.37 1760.00 277.18 13.61 164.81 246.94 659.26 329.63 554.37 554.37 1760.00 277.18 13.62 164.81 246.94 659.26 329.63 554.37 554.37 1760.00 277.18 13.63 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.64 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.65 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.66 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.67 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.68 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.69 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.70 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.71 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.72 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.73 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.74 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.75 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.76 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.77 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.78 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.79 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.80 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.81 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.82 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.83 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.84 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.85 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.86 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.87 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.88 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.89 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.90 164.81 659.26 329.63 554.37 554.37 1760.00 277.18 13.91 659.26 329.63 554.37 554.37 1760.00 277.18 13.92 659.26 329.63 554.37 554.37 1760.00 277.18 13.93 659.26 329.63 554.37 554.37 1760.00 277.18 13.94 659.26 329.63 554.37 554.37 1760.00 277.18 13.95 659.26 329.63 554.37 554.37 277.18 13.96 659.26 329.63 554.37 554.37 277.18 1661.22 13.97 659.26 329.63 554.37 554.37 277.18 1661.22 493.88 13.98 659.26 329.63 554.37 554.37 277.18 1661.22 493.88 293.66 13.99 659.26 329.63 554.37 277.18 1661.22 493.88 293.66 493.88 14.00 659.26 329.63 554.37 1661.22 493.88 293.66 493.88 14.01 329.63 554.37 1661.22 493.88 293.66 493.88 14.02 329.63 554.37 1661.22 493.88 293.66 493.88 14.03 329.63 1661.22 493.88 293.66 493.88 14.04 329.63 1661.22 493.88 293.66 493.88 14.05 329.63 1661.22 493.88 293.66 493.88 14.06 329.63 1661.22 493.88 293.66 493.88 14.07 329.63 1661.22 493.88 293.66 493.88 14.08 329.63 1661.22 493.88 293.66 493.88 14.09 329.63 1661.22 493.88 293.66 493.88 14.10 329.63 1661.22 493.88 293.66 493.88 14.11 329.63 1661.22 493.88 293.66 493.88 14.12 329.63 1661.22 493.88 293.66 493.88 14.13 329.63 1661.22 493.88 293.66 493.88 14.14 329.63 1661.22 493.88 293.66 493.88 14.15 329.63 1661.22 493.88 293.66 493.88 14.16 329.63 1661.22 493.88 293.66 493.88 14.17 329.63 1661.22 493.88 293.66 493.88 14.18 329.63 1661.22 493.88 293.66 493.88 14.19 329.63 1661.22 493.88 293.66 493.88 14.20 329.63 1661.22 493.88 293.66 493.88 14.21 329.63 1661.22 493.88 293.66 493.88 14.22 329.63 1661.22 493.88 293.66 493.88 14.23 329.63 1661.22 493.88 293.66 493.88 14.24 329.63 1661.22 493.88 293.66 493.88 14.25 329.63 1661.22 493.88 293.66 493.88 14.26 329.63 1661.22 493.88 293.66 493.88 14.27 329.63 1661.22 493.88 293.66 493.88 14.28 329.63 1661.22 493.88 293.66 493.88 14.29 329.63 1661.22 493.88 293.66 493.88 14.30 329.63 1661.22 493.88 293.66 493.88 14.31 329.63 1661.22 493.88 293.66 493.88 14.32 329.63 1661.22 493.88 293.66 493.88 293.66 14.33 329.63 1661.22 493.88 493.88 293.66 14.34 329.63 1661.22 493.88 493.88 293.66 587.33 69.30 14.35 329.63 1661.22 493.88 493.88 293.66 587.33 69.30 164.81 14.36 1661.22 493.88 493.88 293.66 587.33 69.30 164.81 1479.98 14.37 1661.22 493.88 493.88 293.66 587.33 69.30 164.81 1479.98 14.38 1661.22 493.88 493.88 293.66 587.33 69.30 164.81 1479.98 14.39 1661.22 493.88 493.88 293.66 587.33 69.30 164.81 1479.98 14.40 493.88 293.66 587.33 69.30 164.81 1479.98 14.41 493.88 293.66 587.33 69.30 164.81 1479.98 14.42 493.88 293.66 587.33 69.30 164.81 1479.98 14.43 493.88 293.66 587.33 69.30 164.81 1479.98 14.44 493.88 293.66 587.33 69.30 164.81 1479.98 14.45 493.88 293.66 587.33 69.30 164.81 1479.98 14.46 493.88 293.66 587.33 69.30 164.81 1479.98 14.47 493.88 293.66 587.33 69.30 164.81 1479.98 14.48 493.88 293.66 587.33 69.30 164.81 1479.98 14.49 493.88 293.66 587.33 69.30 164.81 1479.98 14.50 493.88 293.66 587.33 69.30 164.81 1479.98 14.51 493.88 293.66 587.33 69.30 164.81 1479.98 14.52 493.88 293.66 587.33 69.30 164.81 1479.98 14.53 493.88 293.66 587.33 69.30 164.81 1479.98 14.54 493.88 293.66 587.33 69.30 164.81 1479.98 14.55 493.88 293.66 587.33 69.30 164.81 1479.98 14.56 493.88 293.66 587.33 69.30 164.81 1479.98 14.57 493.88 293.66 587.33 69.30 164.81 1479.98 14.58 493.88 293.66 587.33 69.30 164.81 1479.98 14.59 493.88 293.66 587.33 69.30 164.81 1479.98 14.60 493.88 293.66 587.33 69.30 164.81 1479.98 14.61 493.88 293.66 587.33 69.30 164.81 1479.98 14.62 493.88 293.66 587.33 69.30 164.81 1479.98 14.63 493.88 293.66 587.33 69.30 164.81 1479.98 14.64 493.88 293.66 587.33 69.30 164.81 1479.98 14.65 493.88 293.66 587.33 69.30 164.81 1479.98 14.66 493.88 293.66 587.33 69.30 164.81 1479.98 14.67 493.88 293.66 587.33 69.30 164.81 1479.98 14.68 493.88 293.66 587.33 69.30 164.81 1479.98 14.69 493.88 293.66 587.33 69.30 164.81 1479.98 14.70 493.88 293.66 587.33 69.30 164.81 1479.98 14.71 493.88 293.66 587.33 69.30 164.81 1479.98 14.72 493.88 293.66 587.33 69.30 164.81 1479.98 14.73 493.88 293.66 587.33 69.30 164.81 1479.98 73.42 1318.51 185.00 14.74 493.88 293.66 587.33 69.30 164.81 73.42 1318.51 185.00 277.18 14.75 293.66 587.33 69.30 164.81 73.42 1318.51 185.00 277.18 554.37 14.76 587.33 164.81 73.42 1318.51 185.00 277.18 554.37 14.77 587.33 164.81 73.42 1318.51 185.00 277.18 554.37 14.78 587.33 73.42 1318.51 185.00 277.18 554.37 14.79 587.33 73.42 1318.51 185.00 277.18 554.37 14.80 73.42 1318.51 185.00 277.18 554.37 14.81 73.42 1318.51 185.00 277.18 554.37 14.82 73.42 1318.51 185.00 277.18 554.37 14.83 73.42 1318.51 185.00 277.18 554.37 14.84 73.42 1318.51 185.00 277.18 554.37 14.85 73.42 1318.51 185.00 277.18 554.37 14.86 73.42 1318.51 185.00 277.18 554.37 14.87 73.42 1318.51 185.00 277.18 554.37 14.88 73.42 1318.51 185.00 277.18 554.37 14.89 73.42 1318.51 185.00 277.18 554.37 14.90 73.42 1318.51 185.00 277.18 554.37 14.91 73.42 1318.51 185.00 277.18 554.37 14.92 73.42 1318.51 185.00 277.18 554.37 14.93 73.42 1318.51 185.00 277.18 554.37 14.94 73.42 1318.51 185.00 277.18 554.37 14.95 73.42 1318.51 185.00 277.18 554.37 14.96 73.42 1318.51 185.00 277.18 554.37 14.97 73.42 1318.51 185.00 277.18 554.37 14.98 73.42 1318.51 185.00 277.18 554.37 14.99 73.42 1318.51 185.00 277.18 554.37 15.00 73.42 1318.51 185.00 277.18 554.37 15.01 73.42 1318.51 185.00 277.18 554.37 15.02 73.42 1318.51 185.00 277.18 554.37 15.03 73.42 1318.51 185.00 277.18 554.37 15.04 73.42 1318.51 185.00 277.18 554.37 15.05 73.42 1318.51 185.00 277.18 554.37 15.06 73.42 1318.51 185.00 277.18 554.37 15.07 73.42 1318.51 185.00 277.18 554.37 15.08 73.42 1318.51 185.00 277.18 554.37 82.41 246.94 15.09 73.42 1318.51 185.00 277.18 554.37 82.41 246.94 15.10 73.42 1318.51 185.00 277.18 554.37 82.41 246.94 207.65 15.11 73.42 1318.51 185.00 277.18 554.37 82.41 246.94 207.65 493.88 15.12 73.42 1318.51 185.00 554.37 82.41 246.94 207.65 493.88 15.13 73.42 1318.51 185.00 554.37 82.41 246.94 207.65 493.88 15.14 73.42 1318.51 554.37 82.41 246.94 207.65 493.88 15.15 1318.51 82.41 246.94 207.65 493.88 15.16 1318.51 82.41 246.94 207.65 493.88 15.17 1318.51 82.41 246.94 207.65 493.88 15.18 1318.51 82.41 246.94 207.65 493.88 15.19 1318.51 82.41 246.94 207.65 493.88 15.20 1318.51 82.41 246.94 207.65 493.88 15.21 1318.51 82.41 246.94 207.65 493.88 15.22 1318.51 82.41 246.94 207.65 493.88 15.23 1318.51 82.41 246.94 207.65 493.88 15.24 1318.51 82.41 246.94 207.65 493.88 15.25 1318.51 82.41 246.94 207.65 493.88 15.26 1318.51 82.41 246.94 207.65 493.88 15.27 1318.51 82.41 246.94 207.65 493.88 554.37 15.28 1318.51 82.41 246.94 207.65 493.88 554.37 15.29 1318.51 82.41 246.94 207.65 554.37 277.18 15.30 1318.51 82.41 246.94 207.65 554.37 277.18 15.31 1318.51 82.41 207.65 554.37 277.18 15.32 1318.51 82.41 207.65 554.37 277.18 15.33 1318.51 82.41 207.65 554.37 277.18 15.34 1318.51 82.41 207.65 554.37 277.18 15.35 1318.51 82.41 207.65 554.37 277.18 15.36 1318.51 82.41 207.65 554.37 277.18 15.37 1318.51 82.41 207.65 554.37 277.18 15.38 1318.51 82.41 207.65 554.37 277.18 15.39 1318.51 82.41 207.65 554.37 277.18 15.40 1318.51 82.41 207.65 554.37 277.18 15.41 1318.51 82.41 207.65 554.37 277.18 15.42 1318.51 82.41 207.65 554.37 277.18 15.43 1318.51 82.41 207.65 554.37 277.18 15.44 1318.51 82.41 207.65 554.37 277.18 15.45 1318.51 82.41 554.37 277.18 220.00 15.46 1318.51 82.41 554.37 277.18 220.00 15.47 1318.51 82.41 554.37 277.18 220.00 15.48 1318.51 82.41 277.18 220.00 15.49 1318.51 82.41 277.18 220.00 440.00 92.50 220.00 15.50 1318.51 277.18 220.00 440.00 92.50 220.00 15.51 1318.51 277.18 220.00 440.00 92.50 220.00 15.52 1318.51 220.00 440.00 92.50 220.00 15.53 1318.51 220.00 440.00 92.50 220.00 15.54 1318.51 220.00 440.00 92.50 220.00 15.55 1318.51 220.00 440.00 92.50 220.00 15.56 1318.51 220.00 440.00 92.50 220.00 15.57 1318.51 220.00 440.00 92.50 220.00 15.58 1318.51 220.00 440.00 92.50 220.00 15.59 1318.51 220.00 440.00 92.50 220.00 15.60 1318.51 220.00 440.00 92.50 220.00 15.61 1318.51 220.00 440.00 92.50 220.00 15.62 1318.51 220.00 440.00 92.50 220.00 15.63 1318.51 220.00 440.00 92.50 220.00 15.64 1318.51 220.00 440.00 92.50 220.00 15.65 1318.51 220.00 440.00 92.50 220.00 15.66 1318.51 220.00 440.00 92.50 220.00 277.18 554.37 15.67 1318.51 220.00 440.00 92.50 220.00 277.18 554.37 15.68 1318.51 440.00 92.50 220.00 277.18 554.37 15.69 1318.51 92.50 220.00 277.18 554.37 15.70 1318.51 92.50 220.00 277.18 554.37 15.71 1318.51 92.50 220.00 277.18 554.37 15.72 1318.51 92.50 220.00 277.18 554.37 15.73 1318.51 92.50 220.00 277.18 554.37 15.74 1318.51 92.50 220.00 277.18 554.37 15.75 1318.51 92.50 220.00 277.18 554.37 15.76 1318.51 92.50 220.00 277.18 554.37 15.77 1318.51 92.50 220.00 277.18 554.37 15.78 1318.51 92.50 220.00 277.18 554.37 15.79 1318.51 92.50 220.00 277.18 554.37 15.80 1318.51 92.50 220.00 277.18 554.37 15.81 1318.51 92.50 220.00 277.18 554.37 293.66 15.82 1318.51 92.50 277.18 554.37 293.66 1174.66 185.00 15.83 1318.51 92.50 554.37 293.66 1174.66 185.00 587.33 15.84 1318.51 92.50 554.37 293.66 1174.66 185.00 587.33 15.85 92.50 293.66 1174.66 185.00 587.33 15.86 92.50 293.66 1174.66 185.00 587.33 15.87 92.50 293.66 1174.66 185.00 587.33 15.88 92.50 293.66 1174.66 185.00 587.33 15.89 92.50 293.66 1174.66 185.00 587.33 15.90 92.50 293.66 1174.66 185.00 587.33 15.91 92.50 293.66 1174.66 185.00 587.33 15.92 92.50 293.66 1174.66 185.00 587.33 15.93 92.50 293.66 1174.66 185.00 587.33 15.94 92.50 293.66 1174.66 185.00 587.33 15.95 92.50 293.66 1174.66 185.00 587.33 15.96 92.50 1174.66 185.00 587.33 207.65 15.97 92.50 1174.66 185.00 587.33 207.65 329.63 15.98 92.50 1174.66 185.00 207.65 329.63 659.26 15.99 92.50 1174.66 185.00 207.65 329.63 659.26 16.00 92.50 1174.66 207.65 329.63 659.26 16.01 92.50 1174.66 207.65 329.63 659.26 16.02 92.50 1174.66 207.65 329.63 659.26 16.03 92.50 1174.66 207.65 329.63 659.26 16.04 92.50 1174.66 207.65 329.63 659.26 16.05 92.50 1174.66 207.65 329.63 659.26 16.06 92.50 1174.66 207.65 329.63 659.26 16.07 92.50 1174.66 207.65 329.63 659.26 16.08 92.50 1174.66 207.65 329.63 659.26 16.09 92.50 1174.66 207.65 329.63 659.26 16.10 92.50 1174.66 207.65 329.63 659.26 16.11 92.50 1174.66 207.65 329.63 659.26 16.12 92.50 1174.66 207.65 329.63 659.26 16.13 92.50 1174.66 207.65 329.63 659.26 16.14 92.50 1174.66 207.65 329.63 659.26 16.15 92.50 1174.66 207.65 329.63 659.26 220.00 16.16 92.50 1174.66 207.65 329.63 220.00 739.99 1108.73 16.17 92.50 1174.66 207.65 329.63 220.00 739.99 1108.73 369.99 16.18 92.50 329.63 220.00 739.99 1108.73 369.99 16.19 92.50 220.00 739.99 1108.73 369.99 16.20 92.50 220.00 739.99 1108.73 369.99 16.21 92.50 220.00 739.99 1108.73 369.99 16.22 92.50 220.00 739.99 1108.73 369.99 16.23 92.50 220.00 739.99 1108.73 369.99 16.24 92.50 220.00 739.99 1108.73 369.99 16.25 92.50 220.00 739.99 1108.73 369.99 16.26 92.50 220.00 739.99 1108.73 369.99 16.27 92.50 220.00 739.99 1108.73 369.99 16.28 92.50 220.00 739.99 1108.73 369.99 16.29 92.50 220.00 739.99 1108.73 369.99 16.30 92.50 220.00 739.99 1108.73 369.99 16.31 92.50 220.00 739.99 1108.73 369.99 16.32 92.50 220.00 739.99 1108.73 369.99 16.33 92.50 220.00 739.99 1108.73 369.99 16.34 92.50 220.00 739.99 1108.73 369.99 16.35 92.50 220.00 739.99 1108.73 369.99 16.36 92.50 220.00 739.99 1108.73 369.99 16.37 92.50 220.00 739.99 1108.73 369.99 16.38 92.50 220.00 739.99 1108.73 369.99 16.39 92.50 220.00 739.99 1108.73 369.99 16.40 92.50 220.00 739.99 1108.73 369.99 16.41 92.50 220.00 739.99 1108.73 369.99 16.42 92.50 220.00 739.99 1108.73 369.99 16.43 92.50 220.00 739.99 1108.73 369.99 16.44 92.50 220.00 739.99 1108.73 369.99 16.45 92.50 220.00 739.99 1108.73 369.99 16.46 92.50 220.00 739.99 1108.73 369.99 16.47 92.50 220.00 739.99 1108.73 369.99 16.48 92.50 220.00 739.99 1108.73 369.99 16.49 92.50 220.00 739.99 1108.73 369.99 185.00 16.50 92.50 220.00 1108.73 369.99 185.00 16.51 92.50 185.00 987.77 16.52 92.50 185.00 987.77 329.63 659.26 16.53 92.50 185.00 987.77 329.63 659.26 16.54 92.50 185.00 987.77 329.63 659.26 16.55 92.50 185.00 987.77 329.63 659.26 16.56 92.50 185.00 987.77 329.63 659.26 16.57 92.50 185.00 987.77 329.63 659.26 16.58 92.50 185.00 987.77 329.63 659.26 16.59 92.50 185.00 987.77 329.63 659.26 16.60 92.50 185.00 987.77 329.63 659.26 16.61 92.50 185.00 987.77 329.63 659.26 16.62 92.50 185.00 987.77 329.63 659.26 16.63 92.50 185.00 987.77 329.63 659.26 16.64 92.50 185.00 987.77 329.63 659.26 16.65 92.50 185.00 987.77 329.63 659.26 16.66 92.50 185.00 987.77 329.63 659.26 207.65 16.67 92.50 185.00 987.77 329.63 659.26 207.65 16.68 92.50 185.00 987.77 329.63 659.26 207.65 16.69 92.50 185.00 987.77 329.63 659.26 207.65 1108.73 587.33 16.70 92.50 987.77 329.63 659.26 207.65 1108.73 587.33 293.66 16.71 92.50 329.63 659.26 207.65 1108.73 587.33 293.66 16.72 92.50 329.63 207.65 1108.73 587.33 293.66 16.73 92.50 329.63 207.65 1108.73 587.33 293.66 16.74 92.50 207.65 1108.73 587.33 293.66 16.75 92.50 207.65 1108.73 587.33 293.66 16.76 92.50 207.65 1108.73 587.33 293.66 16.77 92.50 207.65 1108.73 587.33 293.66 16.78 92.50 207.65 1108.73 587.33 293.66 16.79 92.50 207.65 1108.73 587.33 293.66 16.80 92.50 207.65 1108.73 587.33 293.66 16.81 92.50 207.65 1108.73 587.33 293.66 16.82 92.50 207.65 1108.73 587.33 293.66 16.83 92.50 207.65 1108.73 587.33 293.66 16.84 92.50 207.65 1108.73 587.33 293.66 16.85 92.50 207.65 1108.73 587.33 293.66 16.86 92.50 207.65 1108.73 587.33 293.66 220.00 16.87 92.50 1108.73 587.33 293.66 220.00 16.88 92.50 1108.73 587.33 293.66 220.00 277.18 880.00 16.89 92.50 1108.73 587.33 293.66 220.00 277.18 880.00 554.37 16.90 92.50 587.33 293.66 220.00 277.18 880.00 554.37 16.91 92.50 587.33 220.00 277.18 880.00 554.37 16.92 92.50 220.00 277.18 880.00 554.37 16.93 92.50 220.00 277.18 880.00 554.37 16.94 92.50 220.00 277.18 880.00 554.37 16.95 92.50 220.00 277.18 880.00 554.37 16.96 92.50 220.00 277.18 880.00 554.37 16.97 92.50 220.00 277.18 880.00 554.37 16.98 92.50 220.00 277.18 880.00 554.37 16.99 92.50 220.00 277.18 880.00 554.37 17.00 92.50 220.00 277.18 880.00 554.37 17.01 92.50 220.00 277.18 880.00 554.37 17.02 92.50 220.00 277.18 880.00 554.37 17.03 92.50 220.00 277.18 880.00 554.37 17.04 92.50 220.00 277.18 880.00 554.37 17.05 92.50 220.00 277.18 880.00 554.37 17.06 92.50 220.00 277.18 880.00 554.37 17.07 92.50 220.00 277.18 880.00 554.37 17.08 92.50 220.00 277.18 880.00 554.37 1108.73 17.09 92.50 220.00 277.18 880.00 554.37 1108.73 17.10 220.00 277.18 880.00 554.37 1108.73 17.11 220.00 277.18 880.00 554.37 1108.73 17.12 220.00 277.18 554.37 1108.73 17.13 220.00 277.18 554.37 1108.73 17.14 220.00 277.18 554.37 1108.73 17.15 220.00 277.18 554.37 1108.73 17.16 220.00 277.18 554.37 1108.73 17.17 220.00 277.18 554.37 1108.73 17.18 220.00 277.18 554.37 1108.73 17.19 277.18 554.37 1108.73 17.20 277.18 554.37 1108.73 17.21 277.18 554.37 1108.73 17.22 277.18 554.37 1108.73 17.23 277.18 554.37 1108.73 17.24 277.18 554.37 1108.73 17.25 277.18 554.37 1108.73 17.26 277.18 554.37 1108.73 1174.66 17.27 277.18 554.37 1108.73 1174.66 17.28 277.18 554.37 1108.73 1174.66 17.29 277.18 554.37 1174.66 17.30 277.18 554.37 1174.66 17.31 277.18 554.37 1174.66 17.32 277.18 554.37 1174.66 55.00 110.00 17.33 277.18 554.37 1174.66 55.00 110.00 17.34 277.18 554.37 1174.66 55.00 110.00 17.35 277.18 554.37 1174.66 55.00 110.00 17.36 277.18 554.37 1174.66 55.00 110.00 17.37 277.18 554.37 1174.66 55.00 110.00 17.38 277.18 554.37 1174.66 55.00 110.00 17.39 277.18 554.37 1174.66 55.00 110.00 17.40 277.18 554.37 1174.66 55.00 110.00 17.41 277.18 554.37 1174.66 55.00 110.00 17.42 277.18 554.37 1174.66 55.00 110.00 17.43 277.18 554.37 1174.66 55.00 110.00 17.44 277.18 554.37 1174.66 55.00 110.00 1318.51 17.45 277.18 554.37 55.00 110.00 1318.51 17.46 277.18 554.37 55.00 110.00 1318.51 17.47 277.18 554.37 55.00 110.00 1318.51 17.48 277.18 554.37 55.00 110.00 1318.51 17.49 277.18 554.37 55.00 110.00 1318.51 17.50 277.18 554.37 55.00 110.00 1318.51 17.51 277.18 554.37 55.00 110.00 1318.51 17.52 277.18 554.37 55.00 110.00 1318.51 17.53 277.18 554.37 55.00 110.00 1318.51 17.54 277.18 554.37 55.00 110.00 1318.51 17.55 277.18 554.37 55.00 110.00 1318.51 17.56 277.18 554.37 55.00 110.00 1318.51 17.57 277.18 554.37 1318.51 17.58 277.18 554.37 1318.51 17.59 277.18 554.37 1318.51 17.60 277.18 554.37 1318.51 17.61 277.18 554.37 1318.51 17.62 277.18 554.37 1318.51 17.63 277.18 554.37 1318.51 1479.98 17.64 277.18 554.37 1318.51 1479.98 92.50 17.65 277.18 554.37 1479.98 92.50 46.25 17.66 277.18 554.37 1479.98 92.50 46.25 17.67 277.18 554.37 1479.98 92.50 46.25 17.68 277.18 554.37 1479.98 92.50 46.25 440.00 17.69 277.18 554.37 1479.98 92.50 46.25 440.00 17.70 277.18 1479.98 92.50 46.25 440.00 17.71 277.18 1479.98 92.50 46.25 440.00 17.72 277.18 1479.98 92.50 46.25 440.00 17.73 277.18 1479.98 92.50 46.25 440.00 17.74 277.18 1479.98 92.50 46.25 440.00 17.75 277.18 1479.98 92.50 46.25 440.00 17.76 277.18 1479.98 92.50 46.25 440.00 17.77 277.18 1479.98 92.50 46.25 440.00 17.78 277.18 1479.98 92.50 46.25 440.00 17.79 277.18 1479.98 92.50 46.25 440.00 17.80 277.18 1479.98 92.50 46.25 440.00 17.81 277.18 1479.98 92.50 46.25 440.00 17.82 277.18 1479.98 92.50 46.25 440.00 17.83 277.18 1479.98 92.50 46.25 440.00 17.84 277.18 1479.98 92.50 46.25 440.00 17.85 277.18 1479.98 92.50 46.25 440.00 17.86 277.18 1479.98 92.50 46.25 440.00 17.87 277.18 1479.98 92.50 46.25 440.00 17.88 277.18 1479.98 92.50 46.25 440.00 17.89 277.18 1479.98 92.50 46.25 440.00 17.90 277.18 1479.98 92.50 46.25 440.00 17.91 277.18 1479.98 92.50 46.25 440.00 17.92 277.18 1479.98 92.50 46.25 440.00 17.93 277.18 1479.98 92.50 46.25 440.00 17.94 277.18 1479.98 92.50 46.25 440.00 17.95 277.18 1479.98 92.50 46.25 440.00 17.96 277.18 1479.98 92.50 46.25 440.00 17.97 277.18 1479.98 92.50 46.25 440.00 17.98 277.18 1479.98 92.50 46.25 440.00 1318.51 17.99 277.18 1479.98 92.50 46.25 440.00 1318.51 18.00 277.18 92.50 440.00 1318.51 18.01 277.18 92.50 440.00 1318.51 18.02 277.18 92.50 440.00 1318.51 18.03 277.18 92.50 440.00 1318.51 110.00 18.04 277.18 92.50 440.00 1318.51 110.00 55.00 18.05 277.18 92.50 1318.51 110.00 55.00 739.99 18.06 277.18 92.50 1318.51 110.00 55.00 739.99 369.99 18.07 277.18 1318.51 110.00 55.00 739.99 369.99 18.08 1318.51 110.00 55.00 739.99 369.99 18.09 1318.51 110.00 55.00 739.99 369.99 18.10 1318.51 110.00 55.00 739.99 369.99 18.11 1318.51 110.00 55.00 739.99 369.99 18.12 1318.51 110.00 55.00 739.99 369.99 18.13 1318.51 110.00 55.00 739.99 369.99 18.14 1318.51 110.00 55.00 739.99 369.99 18.15 1318.51 110.00 55.00 739.99 369.99 18.16 1318.51 110.00 55.00 739.99 369.99 1174.66 18.17 1318.51 110.00 55.00 739.99 369.99 1174.66 18.18 1318.51 110.00 55.00 739.99 369.99 1174.66 18.19 110.00 55.00 739.99 369.99 1174.66 18.20 110.00 55.00 739.99 369.99 1174.66 18.21 110.00 55.00 739.99 369.99 1174.66 18.22 110.00 55.00 739.99 369.99 1174.66 18.23 110.00 55.00 739.99 369.99 1174.66 18.24 110.00 55.00 739.99 369.99 1174.66 18.25 110.00 55.00 739.99 369.99 1174.66 18.26 110.00 55.00 739.99 369.99 1174.66 18.27 110.00 55.00 739.99 369.99 1174.66 18.28 110.00 55.00 739.99 369.99 1174.66 18.29 110.00 55.00 739.99 369.99 1174.66 18.30 110.00 55.00 739.99 369.99 1174.66 18.31 110.00 55.00 739.99 369.99 1174.66 18.32 110.00 739.99 369.99 1174.66 18.33 110.00 739.99 369.99 1174.66 18.34 110.00 739.99 369.99 1174.66 18.35 110.00 739.99 369.99 1174.66 18.36 110.00 739.99 369.99 1174.66 1108.73 18.37 110.00 739.99 369.99 1174.66 1108.73 18.38 739.99 369.99 1174.66 1108.73 18.39 739.99 369.99 1108.73 18.40 739.99 369.99 1108.73 18.41 739.99 369.99 1108.73 18.42 739.99 369.99 1108.73 18.43 739.99 369.99 1108.73 18.44 739.99 369.99 1108.73 138.59 69.30 18.45 739.99 369.99 1108.73 138.59 69.30 349.23 18.46 739.99 369.99 1108.73 138.59 69.30 349.23 18.47 739.99 369.99 1108.73 138.59 69.30 349.23 698.46 18.48 739.99 369.99 1108.73 138.59 69.30 349.23 698.46 18.49 369.99 1108.73 138.59 69.30 349.23 698.46 18.50 369.99 1108.73 138.59 69.30 349.23 698.46 18.51 1108.73 138.59 69.30 349.23 698.46 18.52 1108.73 138.59 69.30 349.23 698.46 18.53 1108.73 138.59 69.30 349.23 698.46 18.54 1108.73 138.59 69.30 349.23 698.46 18.55 1108.73 138.59 69.30 349.23 698.46 18.56 1108.73 138.59 69.30 349.23 698.46 18.57 1108.73 138.59 69.30 349.23 698.46 18.58 1108.73 138.59 69.30 349.23 698.46 18.59 1108.73 138.59 69.30 349.23 698.46 18.60 1108.73 138.59 69.30 349.23 698.46 18.61 1108.73 138.59 69.30 349.23 698.46 18.62 1108.73 138.59 69.30 349.23 698.46 18.63 1108.73 138.59 69.30 349.23 698.46 18.64 1108.73 138.59 69.30 349.23 698.46 18.65 1108.73 138.59 69.30 349.23 698.46 18.66 1108.73 138.59 69.30 349.23 698.46 18.67 1108.73 138.59 69.30 349.23 698.46 18.68 1108.73 138.59 69.30 349.23 698.46 18.69 1108.73 138.59 69.30 349.23 698.46 18.70 1108.73 138.59 69.30 349.23 698.46 18.71 1108.73 138.59 69.30 349.23 698.46 18.72 1108.73 138.59 69.30 349.23 698.46 18.73 1108.73 138.59 69.30 349.23 698.46 18.74 1108.73 138.59 69.30 349.23 698.46 18.75 1108.73 138.59 69.30 349.23 698.46 18.76 1108.73 138.59 69.30 349.23 698.46 18.77 1108.73 138.59 69.30 349.23 698.46 18.78 1108.73 138.59 69.30 349.23 698.46 18.79 1108.73 138.59 69.30 349.23 698.46 18.80 1108.73 138.59 69.30 349.23 698.46 18.81 1108.73 138.59 69.30 349.23 698.46 18.82 1108.73 138.59 69.30 349.23 698.46 18.83 1108.73 138.59 69.30 349.23 698.46 18.84 1108.73 138.59 69.30 349.23 698.46 277.18 18.85 1108.73 138.59 69.30 349.23 698.46 277.18 554.37 18.86 1108.73 138.59 69.30 349.23 698.46 277.18 554.37 18.87 1108.73 138.59 69.30 349.23 698.46 277.18 554.37 18.88 1108.73 138.59 69.30 349.23 277.18 554.37 18.89 1108.73 138.59 69.30 349.23 277.18 554.37 18.90 1108.73 138.59 69.30 349.23 277.18 554.37 18.91 1108.73 138.59 69.30 349.23 277.18 554.37 18.92 1108.73 138.59 69.30 349.23 277.18 554.37 18.93 1108.73 138.59 69.30 349.23 277.18 554.37 18.94 1108.73 138.59 69.30 349.23 277.18 554.37 18.95 1108.73 138.59 69.30 349.23 277.18 554.37 18.96 1108.73 138.59 69.30 349.23 277.18 554.37 18.97 1108.73 138.59 69.30 349.23 277.18 554.37 18.98 1108.73 138.59 69.30 349.23 277.18 554.37 18.99 1108.73 138.59 69.30 349.23 277.18 554.37 19.00 1108.73 138.59 69.30 349.23 277.18 554.37 19.01 1108.73 138.59 69.30 349.23 277.18 554.37 19.02 1108.73 138.59 69.30 349.23 277.18 554.37 19.03 1108.73 138.59 69.30 349.23 277.18 554.37 19.04 1108.73 138.59 69.30 349.23 277.18 554.37 19.05 1108.73 138.59 69.30 349.23 277.18 554.37 19.06 1108.73 138.59 69.30 349.23 277.18 554.37 19.07 1108.73 138.59 69.30 349.23 277.18 554.37 19.08 1108.73 138.59 69.30 349.23 277.18 554.37 19.09 1108.73 138.59 69.30 349.23 277.18 554.37 19.10 1108.73 138.59 69.30 349.23 277.18 554.37 19.11 1108.73 138.59 69.30 349.23 277.18 554.37 19.12 1108.73 138.59 69.30 349.23 277.18 554.37 19.13 1108.73 138.59 69.30 349.23 277.18 554.37 19.14 1108.73 138.59 69.30 349.23 277.18 554.37 19.15 1108.73 138.59 69.30 349.23 277.18 554.37 19.16 1108.73 138.59 69.30 349.23 277.18 554.37 19.17 1108.73 138.59 69.30 349.23 277.18 554.37 19.18 1108.73 138.59 69.30 349.23 277.18 554.37 19.19 1108.73 138.59 69.30 349.23 277.18 554.37 19.20 1108.73 138.59 69.30 349.23 277.18 554.37 293.66 19.21 1108.73 138.59 69.30 349.23 554.37 293.66 19.22 1108.73 138.59 69.30 349.23 554.37 293.66 369.99 19.23 1108.73 138.59 69.30 349.23 554.37 293.66 369.99 587.33 19.24 1108.73 138.59 69.30 349.23 554.37 293.66 369.99 587.33 19.25 1108.73 138.59 69.30 554.37 293.66 369.99 587.33 19.26 1108.73 138.59 69.30 293.66 369.99 587.33 19.27 138.59 69.30 293.66 369.99 587.33 19.28 138.59 69.30 293.66 369.99 587.33 19.29 138.59 69.30 293.66 369.99 587.33 19.30 69.30 293.66 369.99 587.33 19.31 69.30 293.66 369.99 587.33 19.32 69.30 293.66 369.99 587.33 19.33 69.30 293.66 369.99 587.33 19.34 69.30 293.66 369.99 587.33 19.35 69.30 293.66 369.99 587.33 19.36 69.30 293.66 369.99 587.33 19.37 69.30 293.66 369.99 587.33 19.38 69.30 293.66 369.99 587.33 19.39 69.30 293.66 369.99 587.33 19.40 69.30 293.66 369.99 587.33 19.41 69.30 293.66 369.99 587.33 19.42 69.30 293.66 369.99 587.33 19.43 69.30 293.66 369.99 587.33 19.44 69.30 293.66 369.99 587.33 19.45 69.30 293.66 369.99 587.33 19.46 69.30 293.66 369.99 587.33 19.47 69.30 293.66 369.99 587.33 19.48 69.30 293.66 369.99 587.33 19.49 69.30 293.66 369.99 587.33 19.50 69.30 293.66 369.99 587.33 19.51 69.30 293.66 369.99 587.33 19.52 69.30 293.66 369.99 587.33 19.53 69.30 293.66 369.99 587.33 19.54 69.30 293.66 369.99 587.33 19.55 69.30 293.66 369.99 587.33 19.56 69.30 293.66 369.99 587.33 19.57 69.30 293.66 369.99 587.33 19.58 69.30 293.66 369.99 587.33 19.59 69.30 293.66 369.99 587.33 493.88 19.60 69.30 293.66 369.99 493.88 246.94 19.61 69.30 293.66 369.99 493.88 246.94 1479.98 19.62 69.30 293.66 369.99 493.88 246.94 1479.98 19.63 69.30 369.99 493.88 246.94 1479.98 19.64 69.30 369.99 493.88 246.94 1479.98 19.65 69.30 369.99 493.88 246.94 1479.98 19.66 69.30 369.99 493.88 246.94 1479.98 19.67 69.30 369.99 493.88 246.94 1479.98 19.68 69.30 369.99 493.88 246.94 1479.98 19.69 69.30 369.99 493.88 246.94 1479.98 19.70 69.30 369.99 493.88 246.94 1479.98 19.71 69.30 369.99 493.88 246.94 1479.98 19.72 69.30 369.99 493.88 246.94 1479.98 19.73 69.30 369.99 493.88 246.94 1479.98 19.74 69.30 369.99 493.88 246.94 1479.98 19.75 69.30 369.99 493.88 246.94 1479.98 19.76 69.30 369.99 493.88 246.94 1479.98 19.77 69.30 369.99 493.88 246.94 1479.98 19.78 69.30 369.99 493.88 246.94 1479.98 19.79 69.30 369.99 493.88 246.94 1479.98 19.80 69.30 369.99 493.88 246.94 1479.98 19.81 69.30 369.99 493.88 246.94 1479.98 19.82 69.30 369.99 493.88 246.94 1479.98 19.83 69.30 369.99 493.88 246.94 1479.98 19.84 69.30 369.99 493.88 246.94 1479.98 19.85 69.30 369.99 493.88 246.94 1479.98 19.86 69.30 369.99 493.88 246.94 1479.98 19.87 69.30 369.99 493.88 246.94 1479.98 19.88 69.30 369.99 493.88 246.94 1479.98 19.89 69.30 369.99 493.88 246.94 1479.98 19.90 69.30 369.99 493.88 246.94 1479.98 19.91 69.30 369.99 493.88 246.94 1479.98 19.92 69.30 369.99 493.88 246.94 1479.98 19.93 69.30 369.99 493.88 246.94 1479.98 19.94 69.30 369.99 493.88 246.94 1479.98 19.95 69.30 493.88 246.94 1479.98 19.96 69.30 493.88 246.94 1479.98 19.97 69.30 493.88 246.94 1479.98 349.23 19.98 69.30 493.88 246.94 1479.98 349.23 19.99 69.30 493.88 246.94 1479.98 349.23 415.30 20.00 69.30 493.88 246.94 1479.98 349.23 415.30 1396.91 20.01 69.30 493.88 246.94 1479.98 349.23 415.30 1396.91 20.02 69.30 493.88 246.94 1479.98 349.23 415.30 1396.91 20.03 69.30 493.88 246.94 1479.98 349.23 415.30 1396.91 20.04 69.30 493.88 246.94 1479.98 349.23 415.30 1396.91 138.59 20.05 69.30 246.94 349.23 415.30 1396.91 138.59 207.65 20.06 69.30 246.94 349.23 415.30 1396.91 138.59 207.65 20.07 69.30 246.94 349.23 415.30 1396.91 138.59 207.65 20.08 69.30 246.94 349.23 415.30 1396.91 138.59 207.65 20.09 69.30 246.94 349.23 415.30 1396.91 138.59 207.65 20.10 69.30 246.94 349.23 415.30 1396.91 138.59 207.65 20.11 69.30 349.23 415.30 1396.91 138.59 207.65 20.12 69.30 349.23 415.30 1396.91 138.59 207.65 20.13 69.30 349.23 415.30 1396.91 138.59 207.65 20.14 349.23 415.30 1396.91 138.59 207.65 20.15 349.23 415.30 1396.91 138.59 207.65 20.16 349.23 415.30 1396.91 138.59 207.65 20.17 349.23 415.30 1396.91 138.59 207.65 20.18 349.23 415.30 1396.91 138.59 207.65 20.19 349.23 415.30 1396.91 138.59 207.65 20.20 349.23 415.30 1396.91 138.59 207.65 20.21 349.23 415.30 1396.91 138.59 207.65 20.22 349.23 415.30 1396.91 138.59 207.65 20.23 349.23 415.30 1396.91 138.59 207.65 20.24 349.23 415.30 1396.91 138.59 207.65 20.25 349.23 415.30 1396.91 138.59 207.65 20.26 349.23 415.30 1396.91 138.59 207.65 20.27 349.23 415.30 1396.91 138.59 207.65 20.28 349.23 415.30 1396.91 138.59 207.65 20.29 349.23 415.30 1396.91 138.59 207.65 20.30 349.23 415.30 1396.91 138.59 207.65 20.31 349.23 415.30 1396.91 138.59 207.65 20.32 349.23 415.30 138.59 207.65 20.33 349.23 415.30 138.59 207.65 20.34 349.23 415.30 138.59 207.65 20.35 349.23 415.30 138.59 207.65 20.36 349.23 415.30 138.59 207.65 20.37 349.23 415.30 138.59 207.65 20.38 349.23 415.30 138.59 207.65 20.39 349.23 415.30 138.59 207.65 20.40 349.23 415.30 138.59 207.65 20.41 349.23 415.30 138.59 207.65 20.42 349.23 415.30 138.59 207.65 1108.73 20.43 349.23 415.30 138.59 207.65 1108.73 20.44 349.23 415.30 138.59 207.65 1108.73 20.45 349.23 415.30 138.59 207.65 1108.73 20.46 349.23 415.30 138.59 207.65 1108.73 20.47 349.23 415.30 138.59 207.65 1108.73 20.48 349.23 415.30 138.59 207.65 1108.73 20.49 349.23 415.30 138.59 207.65 1108.73 20.50 349.23 415.30 138.59 207.65 1108.73 20.51 349.23 415.30 138.59 207.65 1108.73 20.52 349.23 415.30 138.59 207.65 1108.73 20.53 349.23 415.30 138.59 207.65 1108.73 20.54 349.23 415.30 138.59 207.65 1108.73 20.55 349.23 415.30 138.59 207.65 1108.73 20.56 349.23 415.30 138.59 207.65 1108.73 20.57 349.23 415.30 138.59 207.65 1108.73 20.58 349.23 415.30 138.59 207.65 1108.73 20.59 349.23 415.30 138.59 207.65 1108.73 20.60 349.23 415.30 138.59 207.65 1108.73 20.61 349.23 415.30 138.59 207.65 1108.73 20.62 349.23 415.30 138.59 207.65 1108.73 20.63 349.23 415.30 138.59 207.65 1108.73 20.64 349.23 415.30 138.59 207.65 1108.73 20.65 349.23 415.30 138.59 207.65 1108.73 20.66 349.23 415.30 138.59 207.65 1108.73 20.67 349.23 415.30 138.59 207.65 1108.73 20.68 349.23 415.30 138.59 207.65 1108.73 20.69 349.23 415.30 138.59 207.65 1108.73 20.70 349.23 415.30 138.59 207.65 1108.73 20.71 349.23 415.30 138.59 207.65 1108.73 20.72 349.23 415.30 138.59 207.65 1108.73 20.73 349.23 415.30 138.59 207.65 1108.73 20.74 349.23 415.30 138.59 207.65 1108.73 20.75 349.23 415.30 138.59 207.65 1108.73 20.76 349.23 415.30 138.59 207.65 1108.73 20.77 349.23 415.30 138.59 207.65 1108.73 20.78 349.23 415.30 138.59 207.65 1108.73 20.79 349.23 415.30 138.59 207.65 1108.73 20.80 349.23 415.30 138.59 207.65 1108.73 20.81 349.23 415.30 138.59 1108.73 1174.66 20.82 349.23 415.30 138.59 1108.73 1174.66 20.83 349.23 415.30 138.59 1174.66 123.47 20.84 349.23 138.59 1174.66 123.47 369.99 20.85 349.23 1174.66 123.47 369.99 20.86 349.23 1174.66 123.47 369.99 20.87 349.23 1174.66 123.47 369.99 20.88 1174.66 123.47 369.99 20.89 1174.66 123.47 369.99 20.90 1174.66 123.47 369.99 20.91 1174.66 123.47 369.99 20.92 1174.66 123.47 369.99 20.93 1174.66 123.47 369.99 20.94 1174.66 123.47 369.99 20.95 1174.66 123.47 369.99 20.96 1174.66 123.47 369.99 20.97 1174.66 123.47 369.99 20.98 1174.66 123.47 369.99 20.99 1174.66 123.47 369.99 21.00 1174.66 123.47 369.99 21.01 1174.66 123.47 369.99 21.02 1174.66 123.47 369.99 21.03 1174.66 123.47 369.99 21.04 1174.66 123.47 369.99 21.05 1174.66 123.47 369.99 21.06 1174.66 123.47 369.99 21.07 1174.66 123.47 369.99 21.08 1174.66 123.47 369.99 21.09 1174.66 123.47 369.99 21.10 1174.66 123.47 369.99 21.11 1174.66 123.47 369.99 21.12 1174.66 123.47 369.99 21.13 1174.66 123.47 369.99 21.14 1174.66 123.47 369.99 21.15 1174.66 123.47 369.99 21.16 1174.66 123.47 369.99 21.17 1174.66 123.47 369.99 987.77 21.18 123.47 369.99 987.77 21.19 123.47 369.99 987.77 21.20 123.47 369.99 987.77 21.21 123.47 369.99 987.77 739.99 21.22 123.47 369.99 987.77 739.99 369.99 21.23 123.47 369.99 987.77 739.99 369.99 21.24 123.47 369.99 987.77 739.99 369.99 21.25 123.47 369.99 987.77 739.99 369.99 21.26 123.47 369.99 987.77 739.99 369.99 21.27 123.47 369.99 987.77 739.99 369.99 21.28 123.47 369.99 987.77 739.99 369.99 21.29 123.47 369.99 987.77 739.99 369.99 21.30 123.47 369.99 987.77 739.99 369.99 21.31 123.47 369.99 987.77 739.99 369.99 21.32 123.47 369.99 987.77 739.99 369.99 21.33 123.47 369.99 987.77 739.99 369.99 21.34 123.47 369.99 987.77 739.99 369.99 21.35 369.99 987.77 739.99 369.99 21.36 369.99 987.77 739.99 369.99 21.37 369.99 987.77 739.99 369.99 21.38 369.99 987.77 739.99 369.99 21.39 369.99 987.77 739.99 369.99 21.40 369.99 987.77 739.99 369.99 21.41 369.99 987.77 739.99 369.99 21.42 369.99 987.77 739.99 369.99 21.43 369.99 987.77 739.99 369.99 21.44 369.99 987.77 739.99 369.99 21.45 369.99 987.77 739.99 369.99 21.46 369.99 987.77 739.99 369.99 21.47 369.99 987.77 739.99 369.99 21.48 369.99 987.77 739.99 369.99 21.49 369.99 987.77 739.99 369.99 21.50 369.99 987.77 739.99 369.99 21.51 369.99 987.77 739.99 369.99 21.52 369.99 987.77 739.99 369.99 21.53 369.99 987.77 739.99 369.99 21.54 369.99 987.77 739.99 369.99 21.55 369.99 987.77 739.99 369.99 21.56 369.99 987.77 739.99 369.99 21.57 369.99 987.77 739.99 369.99 830.61 21.58 369.99 987.77 739.99 369.99 830.61 349.23 21.59 369.99 987.77 739.99 369.99 830.61 349.23 207.65 21.60 369.99 987.77 739.99 369.99 830.61 349.23 207.65 21.61 987.77 369.99 830.61 349.23 207.65 138.59 21.62 369.99 830.61 349.23 207.65 138.59 21.63 369.99 830.61 349.23 207.65 138.59 21.64 830.61 349.23 207.65 138.59 21.65 830.61 349.23 207.65 138.59 349.23 698.46 21.66 830.61 349.23 207.65 138.59 349.23 698.46 21.67 830.61 349.23 207.65 138.59 349.23 698.46 21.68 830.61 349.23 207.65 138.59 349.23 698.46 21.69 830.61 349.23 207.65 138.59 349.23 698.46 21.70 830.61 349.23 207.65 138.59 349.23 698.46 21.71 830.61 349.23 207.65 138.59 349.23 698.46 21.72 830.61 349.23 207.65 138.59 349.23 698.46 21.73 830.61 349.23 207.65 138.59 349.23 698.46 21.74 830.61 349.23 207.65 138.59 349.23 698.46 21.75 830.61 349.23 207.65 138.59 349.23 698.46 21.76 830.61 349.23 207.65 138.59 349.23 698.46 21.77 830.61 349.23 207.65 138.59 349.23 698.46 21.78 830.61 349.23 207.65 138.59 349.23 698.46 21.79 830.61 349.23 207.65 138.59 349.23 698.46 21.80 830.61 349.23 207.65 138.59 349.23 698.46 21.81 830.61 349.23 207.65 138.59 349.23 698.46 21.82 830.61 349.23 207.65 138.59 349.23 698.46 21.83 830.61 349.23 207.65 138.59 349.23 698.46 21.84 830.61 349.23 207.65 138.59 349.23 698.46 21.85 830.61 349.23 207.65 138.59 349.23 698.46 21.86 830.61 349.23 207.65 138.59 349.23 698.46 21.87 830.61 349.23 207.65 138.59 349.23 698.46 21.88 830.61 349.23 207.65 138.59 349.23 698.46 21.89 830.61 349.23 207.65 138.59 349.23 698.46 21.90 830.61 349.23 207.65 138.59 349.23 698.46 21.91 830.61 349.23 207.65 138.59 349.23 698.46 21.92 830.61 349.23 207.65 138.59 349.23 698.46 554.37 21.93 830.61 349.23 207.65 138.59 349.23 698.46 554.37 21.94 830.61 349.23 207.65 138.59 349.23 554.37 21.95 830.61 349.23 207.65 138.59 349.23 554.37 21.96 830.61 349.23 207.65 138.59 349.23 554.37 21.97 830.61 349.23 207.65 138.59 349.23 554.37 277.18 21.98 830.61 349.23 207.65 138.59 349.23 554.37 277.18 21.99 830.61 207.65 138.59 349.23 554.37 277.18 22.00 830.61 207.65 138.59 349.23 554.37 277.18 22.01 830.61 207.65 138.59 349.23 554.37 277.18 22.02 830.61 207.65 138.59 349.23 554.37 277.18 22.03 830.61 207.65 138.59 349.23 554.37 277.18 22.04 830.61 207.65 138.59 349.23 554.37 277.18 22.05 830.61 207.65 138.59 349.23 554.37 277.18 22.06 830.61 207.65 138.59 349.23 554.37 277.18 22.07 830.61 207.65 138.59 349.23 554.37 277.18 22.08 830.61 207.65 138.59 349.23 554.37 277.18 22.09 830.61 207.65 138.59 349.23 554.37 277.18 22.10 830.61 207.65 138.59 349.23 554.37 277.18 22.11 830.61 207.65 138.59 349.23 554.37 277.18 22.12 830.61 207.65 138.59 349.23 554.37 277.18 22.13 830.61 207.65 138.59 349.23 554.37 277.18 22.14 830.61 207.65 138.59 349.23 554.37 277.18 22.15 830.61 207.65 138.59 349.23 554.37 277.18 22.16 830.61 207.65 138.59 349.23 554.37 277.18 22.17 830.61 207.65 138.59 349.23 554.37 277.18 22.18 830.61 207.65 138.59 349.23 554.37 277.18 22.19 830.61 207.65 138.59 349.23 554.37 277.18 22.20 830.61 207.65 138.59 349.23 554.37 277.18 22.21 830.61 207.65 138.59 349.23 554.37 277.18 22.22 830.61 207.65 138.59 349.23 554.37 277.18 22.23 830.61 138.59 349.23 554.37 277.18 22.24 830.61 138.59 349.23 554.37 277.18 22.25 830.61 138.59 349.23 554.37 277.18 22.26 830.61 138.59 349.23 554.37 277.18 22.27 830.61 138.59 349.23 554.37 277.18 22.28 830.61 138.59 349.23 554.37 277.18 22.29 830.61 138.59 349.23 554.37 277.18 22.30 830.61 138.59 349.23 554.37 277.18 246.94 22.31 830.61 138.59 554.37 246.94 293.66 369.99 22.32 830.61 138.59 554.37 246.94 293.66 369.99 493.88 22.33 830.61 138.59 246.94 293.66 369.99 493.88 22.34 830.61 138.59 246.94 293.66 369.99 493.88 22.35 830.61 138.59 246.94 293.66 369.99 493.88 22.36 830.61 138.59 246.94 293.66 369.99 493.88 22.37 830.61 138.59 246.94 293.66 369.99 493.88 22.38 830.61 138.59 246.94 293.66 369.99 493.88 22.39 830.61 138.59 246.94 293.66 369.99 493.88 22.40 830.61 138.59 246.94 293.66 369.99 493.88 22.41 830.61 138.59 246.94 293.66 369.99 493.88 22.42 830.61 138.59 246.94 293.66 369.99 493.88 22.43 830.61 138.59 246.94 293.66 369.99 493.88 22.44 830.61 138.59 246.94 293.66 369.99 493.88 22.45 830.61 138.59 246.94 293.66 369.99 493.88 22.46 830.61 138.59 246.94 293.66 369.99 493.88 22.47 830.61 138.59 246.94 293.66 369.99 493.88 22.48 830.61 138.59 246.94 293.66 369.99 493.88 22.49 830.61 138.59 246.94 293.66 369.99 493.88 220.00 22.50 830.61 138.59 246.94 293.66 369.99 493.88 220.00 22.51 830.61 138.59 246.94 293.66 369.99 493.88 220.00 22.52 830.61 138.59 293.66 369.99 493.88 220.00 440.00 22.53 830.61 138.59 293.66 369.99 493.88 220.00 440.00 22.54 830.61 138.59 293.66 369.99 493.88 220.00 440.00 22.55 830.61 138.59 293.66 369.99 220.00 440.00 22.56 830.61 138.59 293.66 369.99 220.00 440.00 22.57 830.61 138.59 293.66 369.99 220.00 440.00 22.58 830.61 138.59 293.66 369.99 220.00 440.00 22.59 830.61 138.59 293.66 369.99 220.00 440.00 22.60 830.61 138.59 293.66 369.99 220.00 440.00 22.61 830.61 138.59 293.66 369.99 220.00 440.00 22.62 830.61 138.59 293.66 369.99 220.00 440.00 22.63 830.61 138.59 293.66 369.99 220.00 440.00 22.64 830.61 138.59 293.66 369.99 220.00 440.00 22.65 830.61 138.59 293.66 369.99 220.00 440.00 22.66 830.61 138.59 293.66 220.00 440.00 22.67 830.61 138.59 293.66 220.00 440.00 22.68 830.61 138.59 293.66 220.00 440.00 22.69 138.59 293.66 220.00 440.00 1479.98 22.70 138.59 293.66 220.00 440.00 1479.98 207.65 22.71 138.59 293.66 220.00 440.00 1479.98 207.65 415.30 22.72 138.59 293.66 440.00 1479.98 207.65 415.30 22.73 138.59 293.66 440.00 1479.98 207.65 415.30 22.74 138.59 293.66 1479.98 207.65 415.30 22.75 138.59 293.66 1479.98 207.65 415.30 22.76 138.59 293.66 1479.98 207.65 415.30 22.77 138.59 293.66 1479.98 207.65 415.30 22.78 138.59 293.66 1479.98 207.65 415.30 22.79 138.59 293.66 1479.98 207.65 415.30 22.80 138.59 293.66 1479.98 207.65 415.30 22.81 138.59 293.66 1479.98 207.65 415.30 22.82 138.59 293.66 1479.98 207.65 415.30 22.83 293.66 1479.98 207.65 415.30 22.84 293.66 1479.98 207.65 415.30 22.85 293.66 1479.98 207.65 415.30 22.86 293.66 1479.98 207.65 415.30 22.87 293.66 1479.98 207.65 415.30 22.88 293.66 1479.98 207.65 415.30 369.99 22.89 293.66 1479.98 207.65 415.30 369.99 185.00 22.90 293.66 1479.98 207.65 415.30 369.99 185.00 22.91 293.66 1479.98 207.65 415.30 369.99 185.00 22.92 293.66 1479.98 207.65 369.99 185.00 22.93 293.66 1479.98 369.99 185.00 22.94 293.66 1479.98 369.99 185.00 22.95 293.66 1479.98 369.99 185.00 22.96 293.66 1479.98 369.99 185.00 22.97 293.66 1479.98 369.99 185.00 22.98 293.66 1479.98 369.99 185.00 22.99 293.66 1479.98 369.99 185.00 23.00 293.66 1479.98 369.99 185.00 23.01 293.66 1479.98 369.99 185.00 23.02 293.66 1479.98 369.99 185.00 23.03 293.66 1479.98 369.99 185.00 23.04 293.66 1479.98 369.99 185.00 23.05 293.66 1479.98 369.99 185.00 23.06 293.66 1479.98 369.99 185.00 23.07 293.66 1479.98 369.99 185.00 23.08 293.66 1479.98 369.99 185.00 23.09 293.66 1479.98 369.99 185.00 23.10 293.66 1479.98 369.99 185.00 23.11 293.66 369.99 185.00 1396.91 138.59 23.12 293.66 369.99 185.00 1396.91 138.59 415.30 349.23 23.13 293.66 369.99 185.00 1396.91 138.59 415.30 349.23 207.65 23.14 293.66 369.99 185.00 1396.91 138.59 415.30 349.23 207.65 23.15 293.66 185.00 1396.91 138.59 415.30 349.23 207.65 23.16 293.66 185.00 1396.91 138.59 415.30 349.23 207.65 23.17 293.66 1396.91 138.59 415.30 349.23 207.65 23.18 293.66 1396.91 138.59 415.30 349.23 207.65 23.19 293.66 1396.91 138.59 415.30 349.23 207.65 23.20 1396.91 138.59 415.30 349.23 207.65 23.21 1396.91 138.59 415.30 349.23 207.65 23.22 1396.91 138.59 415.30 349.23 207.65 23.23 1396.91 138.59 415.30 349.23 207.65 23.24 1396.91 138.59 415.30 349.23 207.65 23.25 1396.91 138.59 415.30 349.23 207.65 23.26 1396.91 138.59 415.30 349.23 207.65 23.27 1396.91 138.59 415.30 349.23 207.65 23.28 1396.91 138.59 415.30 349.23 207.65 23.29 1396.91 138.59 415.30 349.23 207.65 23.30 1396.91 138.59 415.30 349.23 207.65 23.31 1396.91 138.59 415.30 349.23 207.65 23.32 1396.91 138.59 415.30 349.23 207.65 23.33 1396.91 138.59 415.30 349.23 207.65 23.34 1396.91 138.59 415.30 349.23 207.65 23.35 1396.91 138.59 415.30 349.23 207.65 23.36 1396.91 138.59 415.30 349.23 207.65 23.37 1396.91 138.59 415.30 349.23 207.65 23.38 1396.91 138.59 415.30 349.23 207.65 23.39 1396.91 138.59 415.30 349.23 207.65 23.40 1396.91 138.59 415.30 349.23 207.65 23.41 1396.91 138.59 415.30 349.23 207.65 23.42 1396.91 138.59 415.30 349.23 207.65 1108.73 23.43 1396.91 138.59 415.30 349.23 207.65 1108.73 23.44 1396.91 138.59 415.30 349.23 207.65 1108.73 23.45 138.59 415.30 349.23 207.65 1108.73 23.46 138.59 415.30 349.23 207.65 1108.73 23.47 138.59 415.30 349.23 207.65 1108.73 23.48 138.59 415.30 349.23 207.65 1108.73 23.49 138.59 415.30 349.23 207.65 1108.73 23.50 138.59 415.30 349.23 207.65 1108.73 23.51 138.59 415.30 349.23 207.65 1108.73 23.52 138.59 415.30 349.23 207.65 1108.73 23.53 138.59 415.30 349.23 207.65 1108.73 23.54 138.59 415.30 349.23 207.65 1108.73 23.55 138.59 415.30 349.23 207.65 1108.73 23.56 138.59 415.30 349.23 207.65 1108.73 23.57 138.59 415.30 349.23 207.65 1108.73 23.58 138.59 415.30 349.23 207.65 1108.73 23.59 138.59 415.30 349.23 207.65 1108.73 23.60 138.59 415.30 349.23 207.65 1108.73 23.61 138.59 415.30 349.23 207.65 1108.73 23.62 138.59 415.30 349.23 207.65 1108.73 23.63 138.59 415.30 349.23 207.65 1108.73 23.64 138.59 415.30 349.23 207.65 1108.73 23.65 138.59 415.30 349.23 207.65 1108.73 23.66 138.59 415.30 349.23 207.65 1108.73 23.67 138.59 415.30 349.23 207.65 1108.73 23.68 138.59 415.30 349.23 207.65 1108.73 23.69 138.59 415.30 349.23 207.65 1108.73 23.70 138.59 415.30 349.23 207.65 1108.73 23.71 138.59 415.30 349.23 207.65 1108.73 23.72 138.59 415.30 349.23 207.65 1108.73 23.73 138.59 415.30 349.23 207.65 1108.73 23.74 138.59 415.30 349.23 207.65 1108.73 23.75 138.59 415.30 349.23 207.65 1108.73 23.76 138.59 415.30 349.23 207.65 1108.73 23.77 138.59 415.30 349.23 207.65 1108.73 23.78 138.59 415.30 349.23 207.65 1108.73 23.79 138.59 415.30 349.23 207.65 1108.73 23.80 138.59 415.30 349.23 207.65 1108.73 23.81 138.59 415.30 349.23 207.65 1108.73 987.77 23.82 138.59 415.30 349.23 207.65 987.77 23.83 138.59 415.30 349.23 207.65 987.77 220.00 23.84 138.59 415.30 349.23 207.65 987.77 220.00 23.85 138.59 415.30 349.23 987.77 220.00 23.86 138.59 415.30 349.23 987.77 220.00 369.99 23.87 138.59 415.30 349.23 987.77 220.00 369.99 23.88 138.59 349.23 987.77 220.00 369.99 23.89 138.59 349.23 987.77 220.00 369.99 23.90 138.59 349.23 987.77 220.00 369.99 23.91 138.59 987.77 220.00 369.99 23.92 138.59 987.77 220.00 369.99 23.93 138.59 987.77 220.00 369.99 23.94 138.59 987.77 220.00 369.99 23.95 138.59 987.77 220.00 369.99 23.96 138.59 987.77 220.00 369.99 23.97 138.59 987.77 220.00 369.99 23.98 138.59 987.77 220.00 369.99 23.99 138.59 987.77 220.00 369.99 24.00 138.59 987.77 220.00 369.99 880.00 24.01 138.59 987.77 220.00 369.99 880.00 24.02 138.59 220.00 369.99 880.00 24.03 138.59 220.00 369.99 880.00 24.04 138.59 220.00 369.99 880.00 24.05 138.59 220.00 369.99 880.00 24.06 138.59 220.00 369.99 880.00 24.07 138.59 220.00 369.99 880.00 24.08 138.59 220.00 369.99 880.00 24.09 138.59 220.00 369.99 880.00 24.10 138.59 220.00 369.99 880.00 24.11 138.59 220.00 369.99 880.00 24.12 138.59 220.00 369.99 880.00 24.13 138.59 220.00 369.99 880.00 24.14 138.59 220.00 369.99 880.00 24.15 138.59 220.00 369.99 880.00 24.16 138.59 220.00 369.99 880.00 24.17 138.59 220.00 369.99 880.00 24.18 138.59 220.00 369.99 880.00 830.61 24.19 138.59 220.00 369.99 880.00 830.61 24.20 138.59 220.00 369.99 830.61 24.21 138.59 220.00 369.99 830.61 277.18 24.22 138.59 220.00 369.99 830.61 277.18 24.23 369.99 830.61 277.18 554.37 24.24 369.99 830.61 277.18 554.37 24.25 369.99 830.61 277.18 554.37 24.26 369.99 830.61 277.18 554.37 24.27 369.99 830.61 277.18 554.37 24.28 369.99 830.61 277.18 554.37 24.29 369.99 830.61 277.18 554.37 24.30 369.99 830.61 277.18 554.37 24.31 369.99 830.61 277.18 554.37 24.32 369.99 830.61 277.18 554.37 24.33 369.99 830.61 277.18 554.37 24.34 369.99 830.61 277.18 554.37 24.35 369.99 830.61 277.18 554.37 24.36 369.99 830.61 277.18 554.37 24.37 369.99 830.61 277.18 554.37 739.99 24.38 369.99 277.18 554.37 739.99 24.39 369.99 277.18 554.37 739.99 24.40 369.99 277.18 554.37 739.99 24.41 369.99 277.18 554.37 739.99 24.42 369.99 277.18 554.37 739.99 24.43 369.99 277.18 554.37 739.99 24.44 369.99 277.18 554.37 739.99 24.45 369.99 277.18 554.37 739.99 24.46 369.99 277.18 554.37 739.99 24.47 369.99 277.18 554.37 739.99 24.48 369.99 277.18 554.37 739.99 24.49 369.99 277.18 554.37 739.99 24.50 369.99 277.18 554.37 739.99 24.51 369.99 277.18 554.37 739.99 24.52 369.99 277.18 554.37 739.99 24.53 369.99 554.37 739.99 24.54 369.99 739.99 24.55 369.99 739.99 24.56 369.99 739.99 24.57 369.99 739.99 24.58 369.99 739.99 24.59 369.99 739.99 830.61 24.60 369.99 739.99 830.61 24.61 369.99 739.99 830.61 138.59 24.62 369.99 739.99 830.61 138.59 329.63 277.18 24.63 369.99 739.99 830.61 138.59 329.63 277.18 554.37 24.64 369.99 739.99 830.61 138.59 329.63 277.18 554.37 24.65 369.99 830.61 138.59 329.63 277.18 554.37 24.66 369.99 830.61 138.59 329.63 277.18 554.37 24.67 369.99 830.61 138.59 329.63 277.18 554.37 24.68 369.99 830.61 138.59 329.63 277.18 554.37 24.69 830.61 138.59 329.63 277.18 554.37 24.70 830.61 138.59 329.63 277.18 554.37 24.71 830.61 138.59 329.63 277.18 554.37 24.72 830.61 138.59 329.63 277.18 554.37 24.73 830.61 138.59 329.63 277.18 554.37 24.74 830.61 138.59 329.63 277.18 554.37 24.75 830.61 138.59 329.63 277.18 554.37 24.76 830.61 138.59 329.63 277.18 554.37 24.77 830.61 138.59 329.63 277.18 554.37 24.78 830.61 138.59 329.63 277.18 554.37 24.79 830.61 138.59 329.63 277.18 554.37 24.80 830.61 138.59 329.63 277.18 554.37 24.81 830.61 138.59 329.63 277.18 554.37 24.82 830.61 138.59 329.63 277.18 554.37 24.83 830.61 138.59 329.63 277.18 554.37 24.84 830.61 138.59 329.63 277.18 554.37 24.85 830.61 138.59 329.63 277.18 554.37 24.86 830.61 138.59 329.63 277.18 554.37 24.87 830.61 138.59 329.63 277.18 554.37 24.88 830.61 138.59 329.63 277.18 554.37 24.89 830.61 138.59 329.63 277.18 554.37 24.90 830.61 138.59 329.63 277.18 554.37 24.91 830.61 138.59 329.63 277.18 554.37 24.92 830.61 138.59 329.63 277.18 554.37 24.93 830.61 138.59 329.63 277.18 554.37 24.94 830.61 138.59 329.63 277.18 554.37 24.95 830.61 138.59 329.63 277.18 554.37 24.96 830.61 138.59 329.63 277.18 554.37 24.97 830.61 138.59 329.63 277.18 554.37 24.98 830.61 138.59 329.63 277.18 554.37 24.99 830.61 138.59 329.63 277.18 554.37 25.00 830.61 138.59 329.63 277.18 554.37 25.01 830.61 138.59 329.63 277.18 554.37 25.02 830.61 138.59 329.63 277.18 554.37 25.03 830.61 138.59 329.63 277.18 554.37 207.65 415.30 25.04 830.61 138.59 329.63 277.18 207.65 415.30 25.05 830.61 138.59 329.63 277.18 207.65 415.30 25.06 830.61 138.59 329.63 277.18 207.65 415.30 25.07 830.61 138.59 329.63 207.65 415.30 25.08 830.61 138.59 329.63 207.65 415.30 25.09 830.61 138.59 329.63 207.65 415.30 25.10 830.61 138.59 329.63 207.65 415.30 25.11 830.61 138.59 329.63 207.65 415.30 25.12 830.61 138.59 329.63 207.65 415.30 25.13 830.61 138.59 329.63 207.65 415.30 25.14 830.61 138.59 329.63 207.65 415.30 25.15 830.61 138.59 329.63 207.65 415.30 25.16 830.61 138.59 329.63 207.65 415.30 25.17 830.61 138.59 329.63 207.65 415.30 25.18 830.61 138.59 329.63 207.65 415.30 25.19 830.61 138.59 329.63 207.65 415.30 25.20 830.61 138.59 329.63 207.65 415.30 25.21 830.61 138.59 329.63 207.65 415.30 25.22 830.61 138.59 329.63 207.65 415.30 25.23 830.61 138.59 329.63 207.65 415.30 25.24 830.61 138.59 329.63 207.65 415.30 25.25 830.61 138.59 329.63 207.65 415.30 25.26 830.61 138.59 329.63 207.65 415.30 25.27 830.61 138.59 329.63 207.65 415.30 25.28 830.61 138.59 329.63 207.65 415.30 25.29 830.61 138.59 329.63 207.65 415.30 25.30 830.61 138.59 329.63 207.65 415.30 25.31 830.61 138.59 329.63 207.65 415.30 25.32 830.61 138.59 329.63 207.65 25.33 830.61 138.59 329.63 207.65 25.34 830.61 138.59 329.63 207.65 25.35 830.61 138.59 329.63 25.36 830.61 138.59 329.63 25.37 830.61 138.59 329.63 25.38 830.61 138.59 329.63 25.39 830.61 138.59 329.63 25.40 830.61 138.59 329.63 25.41 830.61 138.59 329.63 25.42 830.61 138.59 329.63 415.30 25.43 830.61 138.59 329.63 415.30 25.44 830.61 138.59 329.63 415.30 25.45 830.61 138.59 329.63 415.30 25.46 830.61 138.59 329.63 415.30 207.65 25.47 830.61 138.59 329.63 415.30 207.65 25.48 830.61 138.59 415.30 207.65 25.49 830.61 138.59 415.30 207.65 25.50 830.61 138.59 415.30 207.65 25.51 830.61 138.59 415.30 207.65 25.52 830.61 138.59 415.30 207.65 25.53 830.61 138.59 415.30 207.65 25.54 830.61 138.59 415.30 207.65 25.55 830.61 138.59 415.30 207.65 25.56 830.61 138.59 415.30 207.65 25.57 830.61 138.59 415.30 207.65 25.58 830.61 138.59 415.30 207.65 25.59 830.61 138.59 415.30 207.65 25.60 830.61 138.59 415.30 207.65 25.61 830.61 138.59 415.30 207.65 25.62 830.61 138.59 415.30 207.65 25.63 830.61 138.59 415.30 207.65 25.64 830.61 138.59 415.30 207.65 25.65 830.61 138.59 415.30 207.65 25.66 830.61 138.59 415.30 207.65 25.67 830.61 138.59 415.30 207.65 25.68 830.61 138.59 415.30 207.65 25.69 830.61 138.59 415.30 207.65 25.70 830.61 138.59 415.30 207.65 25.71 830.61 138.59 415.30 207.65 25.72 830.61 138.59 415.30 207.65 25.73 830.61 138.59 415.30 207.65 25.74 830.61 138.59 415.30 207.65 25.75 830.61 138.59 415.30 207.65 25.76 830.61 138.59 415.30 207.65 25.77 830.61 138.59 415.30 207.65 25.78 830.61 138.59 415.30 207.65 25.79 830.61 138.59 415.30 207.65 25.80 830.61 138.59 415.30 207.65 25.81 830.61 138.59 415.30 207.65 25.82 830.61 138.59 415.30 207.65 440.00 25.83 830.61 138.59 415.30 207.65 440.00 329.63 25.84 830.61 138.59 415.30 207.65 440.00 329.63 220.00 25.85 830.61 138.59 207.65 440.00 329.63 220.00 92.50 25.86 830.61 138.59 440.00 329.63 220.00 92.50 25.87 830.61 440.00 329.63 220.00 92.50 1108.73 25.88 830.61 440.00 329.63 220.00 92.50 1108.73 25.89 830.61 440.00 329.63 220.00 92.50 1108.73 25.90 830.61 440.00 329.63 220.00 92.50 1108.73 25.91 440.00 329.63 220.00 92.50 1108.73 25.92 440.00 329.63 220.00 92.50 1108.73 25.93 440.00 329.63 220.00 92.50 1108.73 25.94 440.00 329.63 220.00 92.50 1108.73 25.95 440.00 329.63 220.00 92.50 1108.73 25.96 440.00 329.63 220.00 92.50 1108.73 25.97 440.00 329.63 220.00 92.50 1108.73 25.98 440.00 329.63 220.00 92.50 1108.73 25.99 440.00 329.63 220.00 92.50 1108.73 26.00 440.00 329.63 220.00 92.50 1108.73 26.01 440.00 329.63 220.00 92.50 1108.73 26.02 440.00 329.63 220.00 92.50 1108.73 554.37 277.18 26.03 440.00 329.63 92.50 1108.73 554.37 277.18 26.04 440.00 329.63 92.50 1108.73 554.37 277.18 26.05 329.63 92.50 1108.73 554.37 277.18 26.06 329.63 92.50 1108.73 554.37 277.18 26.07 329.63 92.50 1108.73 554.37 277.18 26.08 329.63 92.50 1108.73 554.37 277.18 26.09 329.63 92.50 1108.73 554.37 277.18 26.10 329.63 92.50 1108.73 554.37 277.18 26.11 329.63 92.50 1108.73 554.37 277.18 26.12 92.50 1108.73 554.37 277.18 26.13 92.50 1108.73 554.37 277.18 26.14 92.50 1108.73 554.37 277.18 26.15 92.50 1108.73 554.37 277.18 26.16 92.50 1108.73 554.37 277.18 26.17 92.50 1108.73 554.37 277.18 26.18 92.50 1108.73 554.37 277.18 26.19 92.50 554.37 277.18 26.20 92.50 554.37 277.18 26.21 92.50 554.37 277.18 659.26 26.22 92.50 554.37 277.18 659.26 26.23 92.50 277.18 659.26 26.24 92.50 277.18 659.26 26.25 92.50 277.18 659.26 26.26 92.50 277.18 659.26 329.63 26.27 92.50 659.26 329.63 1108.73 138.59 26.28 659.26 329.63 1108.73 138.59 26.29 659.26 329.63 1108.73 138.59 207.65 26.30 659.26 329.63 1108.73 138.59 207.65 26.31 659.26 329.63 1108.73 138.59 207.65 26.32 659.26 329.63 1108.73 138.59 207.65 26.33 659.26 329.63 1108.73 138.59 207.65 26.34 659.26 329.63 1108.73 138.59 207.65 26.35 659.26 329.63 1108.73 138.59 207.65 26.36 659.26 329.63 1108.73 138.59 207.65 26.37 659.26 329.63 1108.73 138.59 207.65 26.38 659.26 329.63 1108.73 138.59 207.65 26.39 659.26 329.63 1108.73 138.59 207.65 26.40 659.26 329.63 1108.73 138.59 207.65 26.41 659.26 329.63 1108.73 138.59 207.65 26.42 659.26 329.63 1108.73 138.59 207.65 26.43 659.26 329.63 1108.73 138.59 207.65 26.44 659.26 329.63 1108.73 138.59 207.65 26.45 659.26 329.63 1108.73 138.59 207.65 26.46 659.26 329.63 1108.73 138.59 207.65 26.47 659.26 329.63 1108.73 138.59 207.65 26.48 659.26 329.63 1108.73 138.59 207.65 26.49 659.26 329.63 1108.73 138.59 207.65 26.50 659.26 329.63 1108.73 138.59 207.65 26.51 659.26 1108.73 138.59 207.65 26.52 659.26 1108.73 138.59 207.65 26.53 659.26 1108.73 138.59 207.65 26.54 659.26 1108.73 138.59 207.65 26.55 659.26 1108.73 138.59 207.65 26.56 659.26 1108.73 138.59 207.65 26.57 659.26 1108.73 138.59 207.65 26.58 659.26 1108.73 138.59 207.65 26.59 659.26 1108.73 138.59 207.65 26.60 659.26 1108.73 138.59 207.65 26.61 659.26 1108.73 138.59 207.65 830.61 26.62 659.26 1108.73 138.59 207.65 830.61 26.63 659.26 138.59 207.65 830.61 329.63 277.18 26.64 659.26 138.59 207.65 830.61 329.63 277.18 26.65 659.26 138.59 830.61 329.63 277.18 26.66 659.26 138.59 830.61 329.63 277.18 26.67 659.26 138.59 830.61 329.63 277.18 26.68 659.26 138.59 830.61 329.63 277.18 26.69 659.26 138.59 830.61 329.63 277.18 26.70 659.26 138.59 830.61 329.63 277.18 26.71 659.26 138.59 830.61 329.63 277.18 26.72 659.26 138.59 830.61 329.63 277.18 26.73 659.26 138.59 830.61 329.63 277.18 26.74 659.26 138.59 830.61 329.63 277.18 26.75 659.26 138.59 830.61 329.63 277.18 26.76 659.26 138.59 830.61 329.63 277.18 26.77 659.26 138.59 830.61 329.63 277.18 26.78 659.26 138.59 830.61 329.63 277.18 26.79 659.26 138.59 830.61 329.63 277.18 26.80 659.26 138.59 830.61 329.63 277.18 26.81 659.26 138.59 830.61 329.63 277.18 26.82 659.26 138.59 830.61 329.63 277.18 26.83 659.26 138.59 830.61 329.63 277.18 26.84 659.26 138.59 830.61 329.63 277.18 26.85 659.26 138.59 830.61 329.63 277.18 26.86 659.26 138.59 830.61 329.63 277.18 26.87 659.26 138.59 830.61 329.63 277.18 26.88 659.26 138.59 329.63 277.18 26.89 659.26 138.59 329.63 277.18 26.90 659.26 138.59 329.63 277.18 26.91 659.26 138.59 329.63 277.18 26.92 659.26 138.59 329.63 277.18 26.93 659.26 138.59 329.63 277.18 26.94 659.26 138.59 329.63 277.18 26.95 659.26 138.59 277.18 830.61 26.96 659.26 138.59 277.18 830.61 26.97 659.26 138.59 277.18 830.61 246.94 26.98 659.26 138.59 277.18 830.61 246.94 26.99 659.26 138.59 277.18 830.61 246.94 27.00 659.26 138.59 277.18 830.61 246.94 27.01 659.26 138.59 277.18 830.61 246.94 27.02 659.26 138.59 830.61 246.94 27.03 659.26 138.59 830.61 246.94 27.04 659.26 138.59 830.61 246.94 415.30 27.05 659.26 138.59 830.61 246.94 415.30 27.06 659.26 138.59 830.61 246.94 415.30 27.07 659.26 138.59 830.61 246.94 415.30 27.08 659.26 138.59 830.61 246.94 415.30 27.09 659.26 138.59 830.61 246.94 415.30 27.10 659.26 138.59 830.61 246.94 415.30 27.11 659.26 138.59 830.61 246.94 415.30 27.12 659.26 138.59 830.61 246.94 415.30 27.13 659.26 138.59 830.61 246.94 415.30 27.14 659.26 138.59 830.61 246.94 415.30 27.15 659.26 138.59 830.61 246.94 415.30 27.16 659.26 138.59 830.61 246.94 415.30 27.17 659.26 138.59 830.61 246.94 415.30 27.18 659.26 138.59 830.61 246.94 415.30 27.19 659.26 138.59 830.61 246.94 415.30 27.20 659.26 138.59 830.61 246.94 415.30 27.21 659.26 138.59 830.61 246.94 415.30 27.22 659.26 138.59 830.61 246.94 415.30 27.23 659.26 138.59 830.61 246.94 415.30 27.24 659.26 138.59 830.61 246.94 415.30 27.25 659.26 138.59 830.61 246.94 415.30 27.26 659.26 138.59 830.61 246.94 415.30 27.27 659.26 138.59 830.61 246.94 415.30 27.28 659.26 138.59 830.61 246.94 415.30 27.29 659.26 138.59 830.61 246.94 415.30 880.00 27.30 659.26 138.59 830.61 246.94 415.30 880.00 27.31 659.26 138.59 830.61 246.94 415.30 880.00 27.32 659.26 138.59 246.94 415.30 880.00 27.33 659.26 138.59 246.94 415.30 880.00 220.00 27.34 659.26 138.59 246.94 415.30 880.00 220.00 92.50 27.35 659.26 246.94 415.30 880.00 220.00 92.50 27.36 659.26 246.94 415.30 880.00 220.00 92.50 27.37 659.26 415.30 880.00 220.00 92.50 369.99 27.38 659.26 415.30 880.00 220.00 92.50 369.99 27.39 659.26 415.30 880.00 220.00 92.50 369.99 277.18 27.40 659.26 880.00 220.00 92.50 369.99 277.18 554.37 27.41 659.26 880.00 220.00 92.50 369.99 277.18 554.37 27.42 659.26 880.00 220.00 92.50 369.99 277.18 554.37 27.43 880.00 220.00 92.50 369.99 277.18 554.37 27.44 880.00 220.00 92.50 369.99 277.18 554.37 27.45 880.00 220.00 92.50 369.99 277.18 554.37 27.46 880.00 220.00 92.50 369.99 277.18 554.37 27.47 880.00 220.00 92.50 369.99 277.18 554.37 27.48 880.00 220.00 92.50 369.99 277.18 554.37 27.49 880.00 220.00 92.50 369.99 277.18 554.37 1108.73 27.50 880.00 220.00 92.50 369.99 277.18 554.37 1108.73 27.51 880.00 220.00 92.50 369.99 277.18 554.37 1108.73 27.52 220.00 92.50 369.99 277.18 554.37 1108.73 27.53 220.00 92.50 369.99 277.18 554.37 1108.73 27.54 220.00 92.50 369.99 277.18 554.37 1108.73 27.55 220.00 92.50 369.99 277.18 554.37 1108.73 27.56 220.00 92.50 369.99 277.18 554.37 1108.73 27.57 220.00 92.50 369.99 277.18 554.37 1108.73 27.58 220.00 92.50 369.99 277.18 554.37 1108.73 27.59 220.00 92.50 369.99 277.18 554.37 1108.73 27.60 220.00 92.50 369.99 277.18 554.37 1108.73 27.61 220.00 92.50 369.99 277.18 554.37 1108.73 27.62 220.00 92.50 369.99 277.18 554.37 1108.73 27.63 220.00 92.50 369.99 277.18 554.37 1108.73 27.64 220.00 92.50 369.99 277.18 554.37 1108.73 27.65 220.00 92.50 369.99 277.18 554.37 1108.73 27.66 220.00 92.50 369.99 277.18 554.37 1108.73 27.67 220.00 92.50 369.99 277.18 554.37 1108.73 27.68 220.00 92.50 369.99 277.18 554.37 1108.73 27.69 220.00 92.50 369.99 277.18 554.37 1108.73 138.59 1318.51 27.70 220.00 92.50 277.18 554.37 1108.73 138.59 1318.51 207.65 27.71 220.00 92.50 277.18 554.37 1108.73 138.59 1318.51 207.65 27.72 220.00 92.50 277.18 554.37 138.59 1318.51 207.65 27.73 220.00 277.18 554.37 138.59 1318.51 207.65 329.63 27.74 220.00 277.18 554.37 138.59 1318.51 207.65 329.63 27.75 277.18 554.37 138.59 1318.51 207.65 329.63 27.76 277.18 554.37 138.59 1318.51 207.65 329.63 27.77 277.18 554.37 138.59 1318.51 207.65 329.63 27.78 277.18 554.37 138.59 1318.51 207.65 329.63 27.79 277.18 554.37 138.59 1318.51 207.65 329.63 27.80 277.18 554.37 138.59 1318.51 207.65 329.63 27.81 277.18 554.37 138.59 1318.51 207.65 329.63 27.82 277.18 554.37 138.59 1318.51 207.65 329.63 27.83 277.18 554.37 138.59 1318.51 207.65 329.63 27.84 277.18 554.37 138.59 1318.51 207.65 329.63 27.85 277.18 554.37 138.59 1318.51 207.65 329.63 27.86 277.18 554.37 138.59 1318.51 207.65 329.63 27.87 277.18 554.37 138.59 1318.51 207.65 329.63 27.88 277.18 554.37 138.59 1318.51 207.65 329.63 27.89 277.18 554.37 138.59 1318.51 207.65 329.63 27.90 277.18 554.37 138.59 1318.51 207.65 329.63 27.91 277.18 554.37 138.59 1318.51 207.65 329.63 27.92 277.18 554.37 138.59 1318.51 207.65 329.63 27.93 277.18 554.37 138.59 1318.51 207.65 329.63 27.94 277.18 554.37 138.59 1318.51 207.65 329.63 27.95 277.18 554.37 138.59 1318.51 207.65 329.63 27.96 277.18 554.37 138.59 1318.51 207.65 329.63 27.97 277.18 554.37 138.59 1318.51 207.65 329.63 27.98 277.18 554.37 138.59 1318.51 207.65 329.63 27.99 277.18 554.37 138.59 1318.51 207.65 329.63 28.00 277.18 554.37 138.59 1318.51 207.65 329.63 28.01 277.18 554.37 138.59 1318.51 207.65 329.63 28.02 277.18 554.37 138.59 1318.51 207.65 329.63 28.03 277.18 554.37 138.59 1318.51 207.65 329.63 28.04 277.18 554.37 138.59 1318.51 207.65 329.63 28.05 277.18 554.37 138.59 1318.51 207.65 329.63 28.06 277.18 554.37 138.59 1318.51 207.65 329.63 28.07 277.18 554.37 138.59 1318.51 207.65 329.63 28.08 277.18 554.37 138.59 1318.51 207.65 329.63 28.09 277.18 554.37 138.59 1318.51 207.65 329.63 28.10 277.18 554.37 138.59 1318.51 207.65 329.63 28.11 277.18 554.37 138.59 1318.51 207.65 329.63 28.12 277.18 554.37 138.59 1318.51 207.65 329.63 28.13 277.18 554.37 138.59 1318.51 207.65 329.63 28.14 277.18 554.37 138.59 1318.51 207.65 329.63 28.15 277.18 554.37 138.59 1318.51 207.65 329.63 28.16 277.18 554.37 138.59 1318.51 207.65 329.63 28.17 277.18 554.37 138.59 1318.51 207.65 329.63 28.18 277.18 554.37 138.59 1318.51 207.65 329.63 28.19 277.18 554.37 138.59 1318.51 207.65 329.63 28.20 277.18 138.59 1318.51 207.65 329.63 28.21 277.18 138.59 1318.51 207.65 329.63 28.22 277.18 138.59 1318.51 207.65 329.63 28.23 277.18 138.59 1318.51 207.65 329.63 28.24 277.18 138.59 1318.51 207.65 329.63 28.25 277.18 138.59 1318.51 207.65 329.63 28.26 277.18 138.59 1318.51 207.65 329.63 28.27 277.18 138.59 1318.51 207.65 329.63 28.28 277.18 138.59 1318.51 329.63mir_eval-0.8.2/tests/data/onset/000077500000000000000000000000001475740344600165405ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/onset/est00.txt000066400000000000000000000012571475740344600202410ustar00rootroot00000000000000# A comment 1.741496598639455662e-01 4.150566893424036397e-01 8.504308390022675690e-01 9.926530612244898188e-01 1.904036281179138257e+00 2.023038548752834398e+00 2.214603174603174462e+00 2.438095238095238315e+00 2.609342403628117868e+00 3.482993197278911435e+00 4.684625850340135678e+00 4.728163265306122298e+00 5.700498866213151494e+00 5.868843537414965894e+00 6.217142857142857082e+00 6.266485260770974897e+00 6.385487528344671482e+00 6.713469387755101714e+00 7.439092970521541837e+00 7.471020408163265181e+00 8.182131519274376430e+00 8.405623582766439839e+00 8.852607709750566656e+00 9.232834467120181188e+00 9.505668934240363299e+00 9.665306122448980020e+00 9.830748299319727934e+00 mir_eval-0.8.2/tests/data/onset/est01.txt000066400000000000000000000001131475740344600202300ustar00rootroot000000000000001.015873015873015872e-01 1.416707482993197331e+01 1.468081632653061241e+01 mir_eval-0.8.2/tests/data/onset/est02.txt000066400000000000000000000016041475740344600202370ustar00rootroot000000000000002.031746031746031744e-01 4.353741496598639293e-01 6.559637188208616854e-01 8.620408163265306234e-01 1.062312925170068034e+00 1.288707482993197262e+00 1.497687074829932019e+00 1.732789115646258482e+00 1.906938775510204076e+00 2.113015873015873236e+00 2.533877551020408347e+00 2.742857142857142883e+00 2.960544217687074653e+00 3.163718820861677994e+00 3.343673469387755226e+00 3.398820861678004679e+00 3.625215419501133685e+00 3.822585034013605387e+00 4.257959183673469816e+00 4.484353741496598822e+00 4.678820861678004484e+00 4.913922902494331169e+00 5.111292517006802427e+00 5.305759637188208977e+00 5.523446712018140303e+00 5.700498866213151494e+00 5.947210884353741456e+00 6.135873015873015923e+00 6.507392290249432776e+00 6.725079365079364990e+00 6.934058956916099525e+00 7.151746031746031740e+00 7.540680272108843951e+00 7.938321995464852954e+00 8.251791383219954312e+00 8.353378684807255539e+00 mir_eval-0.8.2/tests/data/onset/est03.txt000066400000000000000000000011611475740344600202360ustar00rootroot000000000000009.578231292517007389e-02 2.380045351473922821e-01 3.773242630385487684e-01 4.469841269841269837e-01 5.659863945578231803e-01 7.517460317460317176e-01 8.968707482993196756e-01 1.007165532879818581e+00 1.155192743764172247e+00 1.282902494331065846e+00 1.369977324263038643e+00 1.497687074829932019e+00 1.538321995464852598e+00 1.683446712018140667e+00 1.808253968253968225e+00 1.869206349206349316e+00 1.976598639455782402e+00 2.113015873015873236e+00 2.153650793650793815e+00 2.275555555555555554e+00 2.618049886621315103e+00 2.946031746031746223e+00 3.038911564625850215e+00 3.085351473922902432e+00 3.140498866213151885e+00 mir_eval-0.8.2/tests/data/onset/est04.txt000066400000000000000000000021451475740344600202420ustar00rootroot000000000000009.868480725623582361e-02 1.509297052154195129e-01 2.060770975056689380e-01 2.670294784580498626e-01 3.308843537414966063e-01 3.918367346938775309e-01 4.527891156462585109e-01 5.253514739229024899e-01 5.979138321995465244e-01 6.588662131519273935e-01 7.256235827664399007e-01 8.039909297052154624e-01 8.649433106575963315e-01 9.317006802721088388e-01 9.984580498866213460e-01 1.065215419501133853e+00 1.149387755102040831e+00 1.204535147392290284e+00 1.294512471655328900e+00 1.338049886621315299e+00 1.445442176870748385e+00 1.483174603174603146e+00 1.622494331065759576e+00 1.738594104308390120e+00 1.785034013605442116e+00 1.863401360544217678e+00 1.918548752834467130e+00 1.962086167800453529e+00 2.319092970521541730e+00 2.464217687074830021e+00 2.571609977324262886e+00 2.702222222222222303e+00 2.800907029478457932e+00 2.980861678004535165e+00 3.244988662131519153e+00 3.305941043083900244e+00 3.422040816326530788e+00 3.480090702947845838e+00 3.662947845804988667e+00 3.741315192743764229e+00 3.898049886621315352e+00 4.002539682539682175e+00 4.234739229024943263e+00 4.533696145124716637e+00 4.687528344671202163e+00 mir_eval-0.8.2/tests/data/onset/est05.txt000066400000000000000000000001751475740344600202440ustar00rootroot000000000000002.438095238095238093e-01 1.190022675736961411e+00 2.086893424036281086e+00 4.130249433106575552e+00 4.612063492063492198e+00 mir_eval-0.8.2/tests/data/onset/est06.txt000066400000000000000000000003721475740344600202440ustar00rootroot000000000000003.047619047619047894e-01 4.295691609977324021e-01 5.601814058956916531e-01 7.111111111111111382e-01 8.272108843537414602e-01 9.520181405895691285e-01 1.076825396825396908e+00 1.239365079365079447e+00 1.520907029478458128e+00 1.657324263038548740e+00 mir_eval-0.8.2/tests/data/onset/est07.txt000066400000000000000000000003721475740344600202450ustar00rootroot000000000000003.121541950113378983e-01 4.543764172335601481e-01 6.053061224489796333e-01 9.478004535147391829e-01 1.072607709750566851e+00 1.252562358276643861e+00 1.568934240362811705e+00 1.888208616780045368e+00 2.065260770975056559e+00 2.248117913832199388e+00 mir_eval-0.8.2/tests/data/onset/est08.txt000066400000000000000000000004231475740344600202430ustar00rootroot000000000000001.770521541950113298e-01 2.089795918367347016e-01 4.847165532879818550e-01 6.907936507936508486e-01 8.126984126984126977e-01 1.198730158730158646e+00 1.253877551020408099e+00 1.367074829931972824e+00 1.689251700680272084e+00 2.162358276643991051e+00 3.059229024943310726e+00 mir_eval-0.8.2/tests/data/onset/est09.txt000066400000000000000000000026521475740344600202520ustar00rootroot000000000000003.366893424036281335e-01 4.673015873015873289e-01 6.327437641723355766e-01 7.401360544217686632e-01 8.794557823129252050e-01 1.007165532879818581e+00 1.152290249433106650e+00 1.410612244897959222e+00 1.549931972789115653e+00 1.692154195011337903e+00 1.819863945578231279e+00 1.964988662131519348e+00 2.089795918367347127e+00 2.226213151927437739e+00 2.496145124716553365e+00 2.629659863945578380e+00 2.783492063492063462e+00 2.896689342403627965e+00 3.050521541950113491e+00 3.175328798185940826e+00 3.308843537414965841e+00 3.439455782312925258e+00 3.517823129251700820e+00 3.575873015873015870e+00 3.706485260770974843e+00 3.837097505668934261e+00 3.973514739229024872e+00 4.240544217687074458e+00 4.391473922902494387e+00 4.533696145124716637e+00 4.655600907029478819e+00 4.794920634920634583e+00 4.934240362811791236e+00 5.059047619047619015e+00 5.198367346938775668e+00 5.326077097505669045e+00 5.462494331065759212e+00 5.601814058956915865e+00 5.735328798185941324e+00 5.868843537414965894e+00 6.011065759637188144e+00 6.130068027210884729e+00 6.405804988662131549e+00 6.536417233560090523e+00 6.687346938775510452e+00 6.817959183673469425e+00 6.957278911564626078e+00 7.102403628117913925e+00 7.221405895691609622e+00 7.491337868480725248e+00 7.627755102040816304e+00 7.775782312925169748e+00 7.903492063492063124e+00 8.042811791383220665e+00 8.190839002267573221e+00 8.306938775510204209e+00 8.585578231292517515e+00 8.724897959183673279e+00 mir_eval-0.8.2/tests/data/onset/output00.json000066400000000000000000000001411475740344600211270ustar00rootroot00000000000000{"F-measure": 0.5306122448979591, "Precision": 0.48148148148148145, "Recall": 0.5909090909090909}mir_eval-0.8.2/tests/data/onset/output01.json000066400000000000000000000001431475740344600211320ustar00rootroot00000000000000{"F-measure": 0.03278688524590164, "Precision": 0.3333333333333333, "Recall": 0.017241379310344827}mir_eval-0.8.2/tests/data/onset/output02.json000066400000000000000000000001421475740344600211320ustar00rootroot00000000000000{"F-measure": 0.17582417582417584, "Precision": 0.2222222222222222, "Recall": 0.14545454545454545}mir_eval-0.8.2/tests/data/onset/output03.json000066400000000000000000000001021475740344600211270ustar00rootroot00000000000000{"F-measure": 0.5, "Precision": 0.4, "Recall": 0.6666666666666666}mir_eval-0.8.2/tests/data/onset/output04.json000066400000000000000000000000631475740344600211360ustar00rootroot00000000000000{"F-measure": 0.0, "Precision": 0.0, "Recall": 0.0}mir_eval-0.8.2/tests/data/onset/output05.json000066400000000000000000000001041475740344600211330ustar00rootroot00000000000000{"F-measure": 0.22222222222222224, "Precision": 0.2, "Recall": 0.25}mir_eval-0.8.2/tests/data/onset/output06.json000066400000000000000000000001221475740344600211340ustar00rootroot00000000000000{"F-measure": 0.0909090909090909, "Precision": 0.1, "Recall": 0.08333333333333333}mir_eval-0.8.2/tests/data/onset/output07.json000066400000000000000000000001211475740344600211340ustar00rootroot00000000000000{"F-measure": 0.9523809523809523, "Precision": 1.0, "Recall": 0.9090909090909091}mir_eval-0.8.2/tests/data/onset/output08.json000066400000000000000000000001221475740344600211360ustar00rootroot00000000000000{"F-measure": 0.4210526315789474, "Precision": 0.36363636363636365, "Recall": 0.5}mir_eval-0.8.2/tests/data/onset/output09.json000066400000000000000000000001441475740344600211430ustar00rootroot00000000000000{"F-measure": 0.04838709677419355, "Precision": 0.05172413793103448, "Recall": 0.045454545454545456}mir_eval-0.8.2/tests/data/onset/ref00.txt000077500000000000000000000004101475740344600202130ustar00rootroot000000000000000.355011337 0.807006802 0.943990929 1.968367346 2.171428571 2.380612244 2.563265306 3.439455782 4.643990929 6.185215419 6.339047619 6.526258503 6.678639455 7.397006802 8.354829931 8.798911564 8.877278911 8.948390022 9.184943310 9.430204081 9.601451247 9.811882086 mir_eval-0.8.2/tests/data/onset/ref01.txt000077500000000000000000000013131475740344600202170ustar00rootroot000000000000000.052607709 0.322176870 0.584126984 0.833990929 1.092789115 1.361995464 1.620317460 1.867006802 2.128979591 2.380045351 2.647074829 2.911201814 3.183310657 3.424943310 3.678185941 3.939410430 4.207891156 4.470997732 4.738321995 4.983582766 5.253514739 5.512562358 5.780317460 6.030657596 6.293333333 6.576326530 6.833922902 7.084263038 7.348390022 7.613242630 7.857777777 8.130612244 8.386757369 8.632018140 8.898321995 9.162448979 9.421496598 9.699410430 9.935238095 10.200090702 10.454784580 10.726167800 10.981587301 11.233378684 11.494603174 11.758730158 12.018503401 12.270294784 12.531519274 12.805804988 13.062675736 13.327528344 13.581496598 13.848526077 14.094512471 14.360816326 14.612607709 14.898503401 mir_eval-0.8.2/tests/data/onset/ref02.txt000077500000000000000000000012241475740344600202210ustar00rootroot000000000000000.157142857 0.378571428 0.587755102 0.798979591 0.996938775 1.220408163 1.441836734 1.561224489 1.667346938 1.750000000 1.833673469 2.057142857 2.295918367 2.378004535 2.471428571 2.681995464 2.902040816 3.127551020 3.279591836 3.327551020 3.461995464 3.553990929 3.761224489 3.992993197 4.200000000 4.414693877 4.535147392 4.616326530 4.744897959 4.846938775 4.993877551 5.045918367 5.228571428 5.366326530 5.451020408 5.639795918 5.734693877 5.880612244 5.957142857 6.063265306 6.257142857 6.359183673 6.440816326 6.664285714 6.872993197 7.089795918 7.284693877 7.470408163 7.559183673 7.675011337 7.763990929 7.873469387 8.101020408 8.181632653 8.277551020 mir_eval-0.8.2/tests/data/onset/ref03.txt000077500000000000000000000002641475740344600202250ustar00rootroot000000000000000.026848072 0.211882086 0.379501133 0.514897959 0.703469387 0.844625850 0.958163265 1.096417233 1.231383219 1.487528344 1.636530612 1.779795918 1.938140589 2.075283446 2.231292517 mir_eval-0.8.2/tests/data/onset/ref04.txt000077500000000000000000000000211475740344600202150ustar00rootroot000000000000000.00394557823129 mir_eval-0.8.2/tests/data/onset/ref05.txt000077500000000000000000000000601475740344600202210ustar00rootroot000000000000000.194467120 1.128639455 2.023877551 4.079727891 mir_eval-0.8.2/tests/data/onset/ref06.txt000066400000000000000000000004541475740344600202260ustar00rootroot000000000000000.000000000000000000e+00 2.479999999999999982e-01 3.679999999999999938e-01 5.020000000000000018e-01 6.410000000000000142e-01 7.690000000000000169e-01 8.930000000000000160e-01 1.020000000000000018e+00 1.183000000000000052e+00 1.461000000000000076e+00 1.600999999999999979e+00 1.655999999999999917e+00 mir_eval-0.8.2/tests/data/onset/ref07.txt000066400000000000000000000004231475740344600202230ustar00rootroot000000000000000.000000000000000000e+00 3.300000000000000155e-01 4.959999999999999964e-01 6.500000000000000222e-01 9.599999999999999645e-01 1.116000000000000103e+00 1.278000000000000025e+00 1.612999999999999989e+00 1.933000000000000052e+00 2.108999999999999986e+00 2.250000000000000000e+00 mir_eval-0.8.2/tests/data/onset/ref08.txt000066400000000000000000000003101475740344600202170ustar00rootroot000000000000001.499999999999999944e-01 6.280000000000000027e-01 6.939999999999999503e-01 1.141000000000000014e+00 1.179000000000000048e+00 1.298999999999999932e+00 1.631999999999999895e+00 2.104999999999999982e+00 mir_eval-0.8.2/tests/data/onset/ref09.txt000066400000000000000000000031611475740344600202270ustar00rootroot000000000000000.000000000000000000e+00 2.770000000000000240e-01 4.129999999999999782e-01 5.699999999999999512e-01 6.830000000000000515e-01 8.139999999999999458e-01 9.489999999999999547e-01 1.098000000000000087e+00 1.350999999999999979e+00 1.493999999999999995e+00 1.631999999999999895e+00 1.762999999999999901e+00 1.897999999999999909e+00 2.032999999999999918e+00 2.172000000000000153e+00 2.438000000000000167e+00 2.575000000000000178e+00 2.717999999999999972e+00 2.841000000000000192e+00 2.987999999999999989e+00 3.117999999999999883e+00 3.254000000000000004e+00 3.367999999999999883e+00 3.443000000000000060e+00 3.503000000000000114e+00 3.572000000000000064e+00 3.649000000000000021e+00 3.774000000000000021e+00 3.919000000000000039e+00 4.049999999999999822e+00 4.179999999999999716e+00 4.338000000000000078e+00 4.463000000000000078e+00 4.597000000000000419e+00 4.732000000000000206e+00 4.743000000000000327e+00 4.865000000000000213e+00 5.003999999999999559e+00 5.136000000000000121e+00 5.269999999999999574e+00 5.410000000000000142e+00 5.528999999999999915e+00 5.676000000000000156e+00 5.807999999999999829e+00 5.817000000000000171e+00 5.945999999999999730e+00 6.076999999999999957e+00 6.219999999999999751e+00 6.349999999999999645e+00 6.482999999999999652e+00 6.621999999999999886e+00 6.759999999999999787e+00 6.903999999999999915e+00 7.038000000000000256e+00 7.169999999999999929e+00 7.306000000000000050e+00 7.434999999999999609e+00 7.573999999999999844e+00 7.711000000000000298e+00 7.847000000000000419e+00 7.990000000000000213e+00 8.130000000000000782e+00 8.253999999999999559e+00 8.391999999999999460e+00 8.528000000000000469e+00 8.670999999999999375e+00mir_eval-0.8.2/tests/data/pattern/000077500000000000000000000000001475740344600170655ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/pattern/est00.txt000066400000000000000000000033241475740344600205630ustar00rootroot00000000000000pattern1 occurrence1 77.000000, 67.000000 77.500000, 77.000000 78.000000, 76.000000 81.000000, 81.000000 82.000000, 77.000000 83.000000, 82.000000 84.000000, 73.000000 86.500000, 79.000000 87.000000, 76.000000 87.500000, 81.000000 88.000000, 77.000000 88.500000, 74.000000 90.500000, 77.000000 91.000000, 74.000000 91.500000, 79.000000 occurrence2 220.000000, 62.000000 220.500000, 65.000000 221.000000, 56.000000 221.500000, 59.000000 222.000000, 64.000000 225.000000, 64.000000 226.000000, 60.000000 227.000000, 65.000000 228.000000, 56.000000 230.500000, 62.000000 231.000000, 59.000000 231.500000, 64.000000 232.000000, 60.000000 232.500000, 57.000000 233.000000, 54.000000 233.500000, 63.000000 234.000000, 52.000000 234.500000, 64.000000 234.750000, 60.000000 235.000000, 57.000000 235.500000, 60.000000 235.750000, 57.000000 pattern2 occurrence1 90.500000, 77.000000 91.000000, 74.000000 91.500000, 79.000000 92.000000, 76.000000 92.500000, 72.000000 93.000000, 69.000000 93.500000, 77.000000 94.000000, 74.000000 94.500000, 71.000000 95.000000, 68.000000 95.500000, 76.000000 96.000000, 72.000000 98.250000, 72.000000 98.500000, 76.000000 98.750000, 80.000000 99.000000, 83.000000 99.250000, 80.000000 99.500000, 76.000000 99.750000, 72.000000 occurrence2 313.000000, 47.000000 313.250000, 50.000000 313.750000, 47.000000 314.000000, 43.000000 314.750000, 45.000000 315.000000, 47.000000 315.750000, 45.000000 316.000000, 48.000000 316.750000, 62.000000 317.000000, 65.000000 317.750000, 62.000000 318.000000, 59.000000 318.750000, 48.000000 319.000000, 52.000000 319.750000, 48.000000 320.000000, 45.000000 320.250000, 47.000000 320.500000, 50.000000 320.750000, 54.000000 321.000000, 57.000000 322.500000, 56.000000 322.750000, 54.000000 mir_eval-0.8.2/tests/data/pattern/est01.txt000066400000000000000000000151451475740344600205700ustar00rootroot00000000000000pattern1 occurrence1 1.0000000000, 65.0000000000 2.0000000000, 61.0000000000 3.0000000000, 66.0000000000 4.0000000000, 57.0000000000 6.5000000000, 63.0000000000 7.0000000000, 60.0000000000 7.5000000000, 65.0000000000 8.0000000000, 61.0000000000 occurrence2 4.000000, 56.000000 6.500000, 62.000000 7.000000, 59.000000 7.500000, 64.000000 8.000000, 60.000000 8.500000, 57.000000 9.000000, 54.000000 9.000000, 69.000000 9.500000, 63.000000 10.000000, 52.000000 10.000000, 67.000000 10.500000, 64.000000 10.750000, 60.000000 11.000000, 57.000000 11.000000, 72.000000 11.500000, 60.000000 11.750000, 57.000000 12.000000, 54.000000 12.000000, 63.000000 12.250000, 57.000000 12.750000, 54.000000 13.000000, 51.000000 13.250000, 54.000000 13.750000, 51.000000 14.000000, 47.000000 14.500000, 69.000000 14.750000, 49.000000 15.000000, 51.000000 15.000000, 66.000000 15.500000, 71.000000 15.750000, 49.000000 16.000000, 52.000000 16.000000, 67.000000 16.500000, 64.000000 16.750000, 53.000000 17.000000, 57.000000 17.000000, 61.000000 17.500000, 69.000000 17.750000, 53.000000 pattern2 occurrence1 23.000000, 62.000000 23.000000, 77.000000 23.500000, 65.000000 23.750000, 62.000000 24.000000, 59.000000 24.000000, 68.000000 24.250000, 62.000000 24.500000, 53.000000 24.750000, 59.000000 25.000000, 47.000000 25.000000, 56.000000 25.250000, 59.000000 25.500000, 50.000000 25.750000, 56.000000 26.000000, 44.000000 26.000000, 52.000000 26.500000, 47.000000 26.500000, 74.000000 26.750000, 54.000000 27.000000, 52.000000 27.000000, 56.000000 27.000000, 71.000000 27.500000, 76.000000 27.750000, 54.000000 28.000000, 45.000000 28.000000, 57.000000 28.000000, 72.000000 28.500000, 69.000000 28.750000, 59.000000 29.000000, 62.000000 29.000000, 66.000000 29.500000, 54.000000 29.500000, 74.000000 29.750000, 59.000000 30.000000, 55.000000 30.000000, 55.000000 30.000000, 71.000000 30.500000, 67.000000 30.750000, 57.000000 31.000000, 60.000000 31.000000, 64.000000 31.500000, 52.000000 31.500000, 72.000000 31.750000, 57.000000 32.000000, 53.000000 32.000000, 53.000000 32.000000, 69.000000 32.250000, 65.000000 32.500000, 55.000000 32.500000, 71.000000 32.750000, 65.000000 33.000000, 57.000000 33.000000, 72.000000 33.250000, 65.000000 33.500000, 55.000000 33.500000, 69.000000 33.750000, 65.000000 occurrence2 106.000000, 48.000000 106.000000, 69.000000 106.500000, 45.000000 106.750000, 60.000000 107.000000, 40.000000 107.000000, 61.000000 107.500000, 43.000000 107.750000, 59.000000 108.000000, 41.000000 108.000000, 62.000000 108.250000, 38.000000 108.500000, 65.000000 108.500000, 71.000000 108.750000, 40.000000 109.000000, 40.000000 109.000000, 56.000000 109.000000, 64.000000 109.500000, 59.000000 109.500000, 68.000000 109.750000, 38.000000 110.000000, 33.000000 110.000000, 45.000000 110.000000, 60.000000 110.000000, 64.000000 110.000000, 69.000000 pattern3 occurrence1 42.000000, 52.000000 42.000000, 67.000000 42.000000, 72.000000 42.500000, 60.000000 42.750000, 52.000000 43.000000, 54.000000 43.000000, 57.000000 43.500000, 62.000000 43.750000, 52.000000 44.000000, 55.000000 44.000000, 59.000000 44.500000, 52.000000 44.500000, 67.000000 44.750000, 59.000000 45.000000, 57.000000 45.000000, 61.000000 45.000000, 64.000000 45.500000, 69.000000 45.750000, 59.000000 46.000000, 62.000000 46.000000, 66.000000 46.500000, 50.000000 46.750000, 66.000000 47.000000, 47.000000 47.000000, 68.000000 47.500000, 52.000000 47.750000, 66.000000 48.000000, 48.000000 48.000000, 69.000000 48.250000, 71.000000 48.500000, 45.000000 48.500000, 74.000000 48.750000, 78.000000 49.000000, 42.000000 49.000000, 81.000000 49.250000, 72.000000 49.500000, 51.000000 49.500000, 71.000000 49.750000, 78.000000 50.000000, 40.000000 50.000000, 79.000000 50.250000, 71.000000 50.500000, 76.000000 50.750000, 72.000000 51.000000, 69.000000 51.000000, 84.000000 51.500000, 72.000000 51.750000, 69.000000 occurrence2 83.000000, 55.000000 83.000000, 82.000000 83.250000, 55.000000 83.500000, 58.000000 83.750000, 55.000000 84.000000, 52.000000 84.000000, 73.000000 84.250000, 55.000000 84.500000, 70.000000 84.750000, 52.000000 85.000000, 49.000000 85.000000, 64.000000 85.250000, 52.000000 85.500000, 67.000000 85.750000, 49.000000 86.000000, 45.000000 86.000000, 61.000000 86.500000, 76.000000 86.500000, 79.000000 86.750000, 47.000000 87.000000, 49.000000 87.000000, 69.000000 87.000000, 76.000000 87.500000, 81.000000 87.750000, 47.000000 88.000000, 50.000000 88.000000, 77.000000 88.250000, 53.000000 88.500000, 69.000000 88.500000, 74.000000 88.750000, 50.000000 89.000000, 47.000000 89.000000, 62.000000 89.250000, 50.000000 89.500000, 65.000000 89.750000, 47.000000 90.000000, 43.000000 90.000000, 59.000000 90.500000, 74.000000 90.500000, 77.000000 90.750000, 45.000000 91.000000, 47.000000 91.000000, 67.000000 91.000000, 74.000000 91.500000, 79.000000 91.750000, 45.000000 92.000000, 48.000000 92.000000, 76.000000 92.500000, 72.000000 92.750000, 62.000000 93.000000, 65.000000 93.000000, 69.000000 93.500000, 77.000000 93.750000, 62.000000 pattern4 occurrence1 102.000000, 44.000000 102.000000, 65.000000 102.250000, 62.000000 102.500000, 59.000000 102.750000, 56.000000 103.000000, 62.000000 103.250000, 59.000000 103.500000, 56.000000 103.750000, 52.000000 104.000000, 52.000000 104.500000, 50.000000 104.750000, 66.000000 105.000000, 47.000000 105.000000, 68.000000 105.500000, 52.000000 105.750000, 66.000000 106.000000, 48.000000 106.000000, 69.000000 106.500000, 45.000000 106.750000, 60.000000 107.000000, 40.000000 107.000000, 61.000000 107.500000, 43.000000 107.750000, 59.000000 108.000000, 41.000000 108.000000, 62.000000 108.250000, 38.000000 108.500000, 65.000000 108.500000, 71.000000 108.750000, 40.000000 109.000000, 40.000000 109.000000, 56.000000 109.000000, 64.000000 109.500000, 59.000000 109.500000, 68.000000 109.750000, 38.000000 110.000000, 33.000000 110.000000, 45.000000 110.000000, 60.000000 110.000000, 64.000000 110.000000, 69.000000 occurrence2 103.000000, 62.000000 103.250000, 59.000000 103.500000, 56.000000 103.750000, 52.000000 104.000000, 52.000000 104.500000, 50.000000 104.750000, 66.000000 105.000000, 47.000000 105.000000, 68.000000 105.500000, 52.000000 105.750000, 66.000000 106.000000, 48.000000 106.000000, 69.000000 106.500000, 45.000000 106.750000, 60.000000 107.000000, 40.000000 107.000000, 61.000000 107.500000, 43.000000 107.750000, 59.000000 108.000000, 41.000000 108.000000, 62.000000 108.250000, 38.000000 108.500000, 65.000000 108.500000, 71.000000 108.750000, 40.000000 109.000000, 40.000000 109.000000, 56.000000 109.000000, 64.000000 109.500000, 59.000000 109.500000, 68.000000 109.750000, 38.000000 110.000000, 33.000000 110.000000, 45.000000 110.000000, 60.000000 110.000000, 64.000000 110.000000, 69.000000 mir_eval-0.8.2/tests/data/pattern/est02.txt000066400000000000000000001725001475740344600205700ustar00rootroot00000000000000pattern1 occurrence1 3.000000, 60.000000 3.000000, 68.000000 4.000000, 56.000000 4.000000, 65.000000 5.000000, 53.000000 5.000000, 56.000000 5.000000, 60.000000 5.000000, 65.000000 6.000000, 55.000000 6.000000, 58.000000 6.000000, 60.000000 6.000000, 64.000000 7.000000, 53.000000 7.000000, 56.000000 7.000000, 60.000000 7.000000, 65.000000 8.000000, 52.000000 8.000000, 55.000000 8.000000, 60.000000 8.000000, 67.000000 9.000000, 53.000000 9.000000, 56.000000 9.000000, 60.000000 9.000000, 70.000000 10.000000, 68.000000 11.000000, 63.000000 11.000000, 72.000000 12.000000, 65.000000 12.000000, 73.000000 13.000000, 61.000000 13.000000, 70.000000 14.000000, 44.000000 14.000000, 56.000000 15.000000, 63.000000 15.000000, 72.000000 16.000000, 60.000000 16.000000, 68.000000 17.000000, 56.000000 17.000000, 60.000000 17.000000, 63.000000 17.000000, 68.000000 18.000000, 58.000000 18.000000, 61.000000 18.000000, 63.000000 18.000000, 67.000000 19.000000, 56.000000 19.000000, 60.000000 19.000000, 63.000000 19.000000, 68.000000 20.000000, 55.000000 20.000000, 58.000000 20.000000, 63.000000 20.000000, 70.000000 21.000000, 56.000000 21.000000, 60.000000 21.000000, 63.000000 21.000000, 73.000000 22.000000, 72.000000 23.000000, 60.000000 23.000000, 63.000000 23.000000, 68.000000 23.000000, 75.000000 24.000000, 58.000000 24.000000, 61.000000 24.000000, 67.000000 24.000000, 75.000000 25.000000, 56.000000 25.000000, 60.000000 25.000000, 68.000000 25.000000, 75.000000 26.000000, 55.000000 26.000000, 58.000000 26.000000, 70.000000 26.000000, 75.000000 27.000000, 56.000000 27.000000, 73.000000 27.000000, 75.000000 28.000000, 72.000000 29.000000, 49.000000 29.000000, 58.000000 29.000000, 77.000000 30.000000, 51.000000 30.000000, 60.000000 30.000000, 68.000000 32.000000, 51.000000 32.000000, 61.000000 32.000000, 67.000000 32.000000, 70.000000 33.000000, 56.000000 33.000000, 60.000000 33.000000, 68.000000 35.000000, 79.000000 35.500000, 77.000000 occurrence2 29.000000, 49.000000 29.000000, 58.000000 29.000000, 77.000000 30.000000, 51.000000 30.000000, 60.000000 30.000000, 68.000000 32.000000, 51.000000 32.000000, 61.000000 32.000000, 67.000000 32.000000, 70.000000 33.000000, 56.000000 33.000000, 60.000000 33.000000, 68.000000 35.000000, 79.000000 35.500000, 77.000000 36.000000, 51.000000 36.000000, 60.000000 36.000000, 68.000000 38.000000, 51.000000 38.000000, 61.000000 38.000000, 67.000000 38.000000, 70.000000 39.000000, 56.000000 39.000000, 60.000000 39.000000, 68.000000 41.000000, 60.000000 41.000000, 68.000000 42.000000, 61.000000 42.000000, 70.000000 43.000000, 58.000000 43.000000, 67.000000 44.000000, 53.000000 45.000000, 60.000000 45.000000, 68.000000 46.000000, 56.000000 46.000000, 65.000000 47.000000, 53.000000 47.000000, 56.000000 47.000000, 60.000000 47.000000, 65.000000 48.000000, 55.000000 48.000000, 58.000000 48.000000, 60.000000 48.000000, 64.000000 49.000000, 53.000000 49.000000, 56.000000 49.000000, 60.000000 49.000000, 65.000000 50.000000, 52.000000 50.000000, 55.000000 50.000000, 60.000000 50.000000, 67.000000 51.000000, 53.000000 51.000000, 56.000000 51.000000, 60.000000 51.000000, 70.000000 52.000000, 68.000000 53.000000, 63.000000 53.000000, 72.000000 54.000000, 65.000000 54.000000, 73.000000 55.000000, 61.000000 55.000000, 70.000000 56.000000, 44.000000 56.000000, 56.000000 57.000000, 63.000000 57.000000, 72.000000 58.000000, 60.000000 58.000000, 68.000000 59.000000, 56.000000 59.000000, 60.000000 59.000000, 63.000000 59.000000, 68.000000 60.000000, 58.000000 60.000000, 61.000000 60.000000, 63.000000 60.000000, 67.000000 61.000000, 56.000000 61.000000, 60.000000 61.000000, 63.000000 61.000000, 68.000000 pattern2 occurrence1 3.000000, 60.000000 3.000000, 68.000000 4.000000, 56.000000 4.000000, 65.000000 5.000000, 53.000000 5.000000, 56.000000 5.000000, 60.000000 5.000000, 65.000000 6.000000, 55.000000 6.000000, 58.000000 6.000000, 60.000000 6.000000, 64.000000 7.000000, 53.000000 7.000000, 56.000000 7.000000, 60.000000 7.000000, 65.000000 8.000000, 52.000000 8.000000, 55.000000 8.000000, 60.000000 8.000000, 67.000000 9.000000, 53.000000 9.000000, 56.000000 9.000000, 60.000000 9.000000, 70.000000 10.000000, 68.000000 11.000000, 63.000000 11.000000, 72.000000 12.000000, 65.000000 12.000000, 73.000000 13.000000, 61.000000 13.000000, 70.000000 14.000000, 44.000000 14.000000, 56.000000 15.000000, 63.000000 15.000000, 72.000000 16.000000, 60.000000 16.000000, 68.000000 17.000000, 56.000000 17.000000, 60.000000 17.000000, 63.000000 17.000000, 68.000000 18.000000, 58.000000 18.000000, 61.000000 18.000000, 63.000000 18.000000, 67.000000 19.000000, 56.000000 19.000000, 60.000000 19.000000, 63.000000 19.000000, 68.000000 20.000000, 55.000000 20.000000, 58.000000 20.000000, 63.000000 20.000000, 70.000000 21.000000, 56.000000 21.000000, 60.000000 21.000000, 63.000000 21.000000, 73.000000 22.000000, 72.000000 23.000000, 60.000000 23.000000, 63.000000 23.000000, 68.000000 23.000000, 75.000000 24.000000, 58.000000 24.000000, 61.000000 24.000000, 67.000000 24.000000, 75.000000 25.000000, 56.000000 25.000000, 60.000000 25.000000, 68.000000 25.000000, 75.000000 26.000000, 55.000000 26.000000, 58.000000 26.000000, 70.000000 26.000000, 75.000000 27.000000, 56.000000 27.000000, 73.000000 27.000000, 75.000000 28.000000, 72.000000 29.000000, 49.000000 29.000000, 58.000000 29.000000, 77.000000 30.000000, 51.000000 30.000000, 60.000000 30.000000, 68.000000 32.000000, 51.000000 32.000000, 61.000000 32.000000, 67.000000 32.000000, 70.000000 33.000000, 56.000000 33.000000, 60.000000 33.000000, 68.000000 35.000000, 79.000000 35.500000, 77.000000 36.000000, 51.000000 36.000000, 60.000000 36.000000, 68.000000 38.000000, 51.000000 38.000000, 61.000000 38.000000, 67.000000 38.000000, 70.000000 39.000000, 56.000000 39.000000, 60.000000 39.000000, 68.000000 41.000000, 60.000000 41.000000, 68.000000 42.000000, 61.000000 42.000000, 70.000000 occurrence2 276.000000, 52.000000 276.000000, 72.000000 276.500000, 71.000000 277.000000, 55.000000 277.000000, 72.000000 277.500000, 74.000000 278.000000, 60.000000 278.000000, 72.000000 278.500000, 70.000000 279.000000, 53.000000 279.000000, 69.000000 279.500000, 67.000000 280.000000, 57.000000 280.000000, 69.000000 280.500000, 70.000000 281.000000, 60.000000 281.000000, 69.000000 281.500000, 65.000000 282.000000, 45.000000 282.000000, 69.000000 282.000000, 69.000000 282.500000, 44.000000 283.000000, 45.000000 283.000000, 72.000000 283.500000, 41.000000 284.000000, 43.000000 284.000000, 77.000000 284.500000, 45.000000 285.000000, 46.000000 285.000000, 67.000000 285.000000, 67.000000 285.500000, 45.000000 286.000000, 46.000000 286.000000, 74.000000 286.500000, 43.000000 287.000000, 45.000000 287.000000, 77.000000 287.500000, 47.000000 288.000000, 48.000000 288.000000, 67.000000 288.500000, 47.000000 289.000000, 48.000000 289.000000, 77.000000 289.500000, 45.000000 290.000000, 47.000000 290.000000, 76.000000 290.500000, 49.000000 291.000000, 50.000000 291.000000, 65.000000 291.500000, 45.000000 292.000000, 47.000000 292.000000, 74.000000 292.500000, 43.000000 293.000000, 48.000000 293.000000, 64.000000 293.000000, 72.000000 293.500000, 42.000000 294.000000, 43.000000 294.500000, 67.000000 295.000000, 64.000000 295.500000, 60.000000 296.000000, 31.000000 296.000000, 59.000000 296.000000, 65.000000 296.500000, 62.000000 297.000000, 36.000000 297.000000, 60.000000 298.000000, 48.000000 299.000000, 60.000000 300.000000, 48.000000 300.000000, 60.000000 300.000000, 64.000000 300.500000, 62.000000 301.000000, 64.000000 301.500000, 60.000000 302.000000, 62.000000 302.500000, 64.000000 303.000000, 59.000000 303.000000, 65.000000 303.500000, 64.000000 304.000000, 65.000000 304.500000, 62.000000 305.000000, 64.000000 305.500000, 65.000000 306.000000, 58.000000 306.000000, 67.000000 306.500000, 66.000000 307.000000, 67.000000 307.500000, 64.000000 308.000000, 65.000000 308.500000, 67.000000 309.000000, 57.000000 309.000000, 69.000000 309.500000, 65.000000 310.000000, 69.000000 310.500000, 72.000000 311.000000, 77.000000 311.500000, 81.000000 312.000000, 64.000000 312.000000, 72.000000 312.000000, 84.000000 312.500000, 62.000000 313.000000, 64.000000 313.500000, 60.000000 314.000000, 62.000000 314.500000, 64.000000 315.000000, 65.000000 315.000000, 71.000000 315.000000, 83.000000 315.500000, 64.000000 pattern3 occurrence1 3.000000, 60.000000 3.000000, 68.000000 4.000000, 56.000000 4.000000, 65.000000 5.000000, 53.000000 5.000000, 56.000000 5.000000, 60.000000 5.000000, 65.000000 6.000000, 55.000000 6.000000, 58.000000 6.000000, 60.000000 6.000000, 64.000000 7.000000, 53.000000 7.000000, 56.000000 7.000000, 60.000000 7.000000, 65.000000 8.000000, 52.000000 8.000000, 55.000000 8.000000, 60.000000 8.000000, 67.000000 9.000000, 53.000000 9.000000, 56.000000 9.000000, 60.000000 9.000000, 70.000000 10.000000, 68.000000 11.000000, 63.000000 11.000000, 72.000000 12.000000, 65.000000 12.000000, 73.000000 13.000000, 61.000000 13.000000, 70.000000 14.000000, 44.000000 14.000000, 56.000000 15.000000, 63.000000 15.000000, 72.000000 16.000000, 60.000000 16.000000, 68.000000 17.000000, 56.000000 17.000000, 60.000000 17.000000, 63.000000 17.000000, 68.000000 18.000000, 58.000000 18.000000, 61.000000 18.000000, 63.000000 18.000000, 67.000000 19.000000, 56.000000 19.000000, 60.000000 19.000000, 63.000000 19.000000, 68.000000 20.000000, 55.000000 20.000000, 58.000000 20.000000, 63.000000 20.000000, 70.000000 21.000000, 56.000000 21.000000, 60.000000 21.000000, 63.000000 21.000000, 73.000000 22.000000, 72.000000 23.000000, 60.000000 23.000000, 63.000000 23.000000, 68.000000 23.000000, 75.000000 24.000000, 58.000000 24.000000, 61.000000 24.000000, 67.000000 24.000000, 75.000000 25.000000, 56.000000 25.000000, 60.000000 25.000000, 68.000000 25.000000, 75.000000 26.000000, 55.000000 26.000000, 58.000000 26.000000, 70.000000 26.000000, 75.000000 27.000000, 56.000000 27.000000, 73.000000 27.000000, 75.000000 28.000000, 72.000000 29.000000, 49.000000 29.000000, 58.000000 29.000000, 77.000000 30.000000, 51.000000 30.000000, 60.000000 30.000000, 68.000000 32.000000, 51.000000 32.000000, 61.000000 32.000000, 67.000000 32.000000, 70.000000 occurrence2 3.000000, 60.000000 3.000000, 68.000000 4.000000, 56.000000 4.000000, 65.000000 5.000000, 53.000000 5.000000, 56.000000 5.000000, 60.000000 5.000000, 65.000000 6.000000, 55.000000 6.000000, 58.000000 6.000000, 60.000000 6.000000, 64.000000 7.000000, 53.000000 7.000000, 56.000000 7.000000, 60.000000 7.000000, 65.000000 8.000000, 52.000000 8.000000, 55.000000 8.000000, 60.000000 8.000000, 67.000000 9.000000, 53.000000 9.000000, 56.000000 9.000000, 60.000000 9.000000, 70.000000 10.000000, 68.000000 11.000000, 63.000000 11.000000, 72.000000 12.000000, 65.000000 12.000000, 73.000000 13.000000, 61.000000 13.000000, 70.000000 14.000000, 44.000000 14.000000, 56.000000 15.000000, 63.000000 15.000000, 72.000000 16.000000, 60.000000 16.000000, 68.000000 17.000000, 56.000000 17.000000, 60.000000 17.000000, 63.000000 17.000000, 68.000000 18.000000, 58.000000 18.000000, 61.000000 18.000000, 63.000000 18.000000, 67.000000 19.000000, 56.000000 19.000000, 60.000000 19.000000, 63.000000 19.000000, 68.000000 20.000000, 55.000000 20.000000, 58.000000 20.000000, 63.000000 20.000000, 70.000000 21.000000, 56.000000 21.000000, 60.000000 21.000000, 63.000000 21.000000, 73.000000 22.000000, 72.000000 23.000000, 60.000000 23.000000, 63.000000 23.000000, 68.000000 23.000000, 75.000000 24.000000, 58.000000 24.000000, 61.000000 24.000000, 67.000000 24.000000, 75.000000 25.000000, 56.000000 25.000000, 60.000000 25.000000, 68.000000 25.000000, 75.000000 26.000000, 55.000000 26.000000, 58.000000 26.000000, 70.000000 26.000000, 75.000000 27.000000, 56.000000 27.000000, 73.000000 27.000000, 75.000000 28.000000, 72.000000 29.000000, 49.000000 29.000000, 58.000000 29.000000, 77.000000 30.000000, 51.000000 30.000000, 60.000000 30.000000, 68.000000 32.000000, 51.000000 32.000000, 61.000000 32.000000, 67.000000 32.000000, 70.000000 pattern4 occurrence1 41.000000, 60.000000 41.000000, 68.000000 42.000000, 61.000000 42.000000, 70.000000 43.000000, 58.000000 43.000000, 67.000000 44.000000, 53.000000 45.000000, 60.000000 45.000000, 68.000000 46.000000, 56.000000 46.000000, 65.000000 47.000000, 53.000000 47.000000, 56.000000 47.000000, 60.000000 47.000000, 65.000000 48.000000, 55.000000 48.000000, 58.000000 48.000000, 60.000000 48.000000, 64.000000 49.000000, 53.000000 49.000000, 56.000000 49.000000, 60.000000 49.000000, 65.000000 50.000000, 52.000000 50.000000, 55.000000 50.000000, 60.000000 50.000000, 67.000000 51.000000, 53.000000 51.000000, 56.000000 51.000000, 60.000000 51.000000, 70.000000 52.000000, 68.000000 53.000000, 63.000000 53.000000, 72.000000 54.000000, 65.000000 54.000000, 73.000000 55.000000, 61.000000 55.000000, 70.000000 56.000000, 44.000000 56.000000, 56.000000 57.000000, 63.000000 57.000000, 72.000000 58.000000, 60.000000 58.000000, 68.000000 59.000000, 56.000000 59.000000, 60.000000 59.000000, 63.000000 59.000000, 68.000000 60.000000, 58.000000 60.000000, 61.000000 60.000000, 63.000000 60.000000, 67.000000 61.000000, 56.000000 61.000000, 60.000000 61.000000, 63.000000 61.000000, 68.000000 62.000000, 55.000000 62.000000, 58.000000 62.000000, 63.000000 62.000000, 70.000000 63.000000, 56.000000 63.000000, 60.000000 63.000000, 63.000000 63.000000, 73.000000 64.000000, 72.000000 65.000000, 60.000000 65.000000, 63.000000 65.000000, 68.000000 65.000000, 75.000000 66.000000, 58.000000 66.000000, 61.000000 66.000000, 67.000000 66.000000, 75.000000 67.000000, 56.000000 67.000000, 60.000000 67.000000, 68.000000 67.000000, 75.000000 68.000000, 55.000000 68.000000, 58.000000 68.000000, 70.000000 68.000000, 75.000000 69.000000, 56.000000 69.000000, 73.000000 69.000000, 75.000000 70.000000, 72.000000 71.000000, 49.000000 71.000000, 58.000000 71.000000, 77.000000 72.000000, 51.000000 72.000000, 60.000000 72.000000, 68.000000 74.000000, 51.000000 74.000000, 61.000000 74.000000, 67.000000 74.000000, 70.000000 75.000000, 56.000000 75.000000, 60.000000 75.000000, 68.000000 77.000000, 79.000000 77.500000, 77.000000 78.000000, 51.000000 78.000000, 60.000000 78.000000, 68.000000 80.000000, 51.000000 80.000000, 61.000000 80.000000, 67.000000 80.000000, 70.000000 81.000000, 56.000000 81.000000, 60.000000 81.000000, 68.000000 83.000000, 72.000000 83.000000, 75.000000 84.000000, 73.000000 84.000000, 76.000000 85.000000, 55.000000 85.000000, 58.000000 85.000000, 70.000000 85.000000, 73.000000 86.000000, 58.000000 86.000000, 61.000000 87.000000, 72.000000 87.000000, 75.000000 88.000000, 56.000000 88.000000, 60.000000 88.000000, 68.000000 88.000000, 72.000000 89.000000, 60.000000 89.000000, 63.000000 90.000000, 75.000000 90.000000, 78.000000 91.000000, 57.000000 91.000000, 60.000000 91.000000, 72.000000 91.000000, 75.000000 92.000000, 60.000000 92.000000, 63.000000 93.000000, 73.000000 93.000000, 77.000000 94.000000, 58.000000 94.000000, 61.000000 94.000000, 70.000000 94.000000, 73.000000 95.000000, 61.000000 95.000000, 65.000000 96.000000, 53.000000 96.000000, 61.000000 96.000000, 65.000000 96.000000, 70.000000 98.000000, 53.000000 98.000000, 63.000000 98.000000, 69.000000 98.000000, 72.000000 99.000000, 58.000000 99.000000, 61.000000 99.000000, 70.000000 101.000000, 78.000000 101.500000, 77.000000 102.000000, 53.000000 102.000000, 61.000000 102.000000, 70.000000 104.000000, 53.000000 104.000000, 63.000000 104.000000, 69.000000 104.000000, 72.000000 105.000000, 58.000000 105.000000, 61.000000 105.000000, 70.000000 107.000000, 53.000000 107.000000, 63.000000 107.000000, 69.000000 107.000000, 73.000000 107.500000, 72.000000 occurrence2 287.000000, 45.000000 287.000000, 77.000000 287.500000, 47.000000 288.000000, 48.000000 288.000000, 67.000000 288.500000, 47.000000 289.000000, 48.000000 289.000000, 77.000000 289.500000, 45.000000 290.000000, 47.000000 290.000000, 76.000000 290.500000, 49.000000 291.000000, 50.000000 291.000000, 65.000000 291.500000, 45.000000 292.000000, 47.000000 292.000000, 74.000000 292.500000, 43.000000 293.000000, 48.000000 293.000000, 64.000000 293.000000, 72.000000 293.500000, 42.000000 294.000000, 43.000000 294.500000, 67.000000 295.000000, 64.000000 295.500000, 60.000000 296.000000, 31.000000 296.000000, 59.000000 296.000000, 65.000000 296.500000, 62.000000 297.000000, 36.000000 297.000000, 60.000000 298.000000, 48.000000 299.000000, 60.000000 300.000000, 48.000000 300.000000, 60.000000 300.000000, 64.000000 300.500000, 62.000000 301.000000, 64.000000 301.500000, 60.000000 302.000000, 62.000000 302.500000, 64.000000 303.000000, 59.000000 303.000000, 65.000000 303.500000, 64.000000 304.000000, 65.000000 304.500000, 62.000000 305.000000, 64.000000 305.500000, 65.000000 306.000000, 58.000000 306.000000, 67.000000 306.500000, 66.000000 307.000000, 67.000000 307.500000, 64.000000 308.000000, 65.000000 308.500000, 67.000000 309.000000, 57.000000 309.000000, 69.000000 309.500000, 65.000000 310.000000, 69.000000 310.500000, 72.000000 311.000000, 77.000000 311.500000, 81.000000 312.000000, 64.000000 312.000000, 72.000000 312.000000, 84.000000 312.500000, 62.000000 313.000000, 64.000000 313.500000, 60.000000 314.000000, 62.000000 314.500000, 64.000000 315.000000, 65.000000 315.000000, 71.000000 315.000000, 83.000000 315.500000, 64.000000 316.000000, 65.000000 316.500000, 62.000000 317.000000, 64.000000 317.500000, 65.000000 318.000000, 67.000000 318.000000, 70.000000 318.000000, 82.000000 318.500000, 65.000000 319.000000, 67.000000 319.500000, 64.000000 319.500000, 67.000000 320.000000, 65.000000 320.000000, 69.000000 320.500000, 67.000000 320.500000, 70.000000 321.000000, 69.000000 321.000000, 72.000000 321.500000, 67.000000 321.500000, 70.000000 322.000000, 69.000000 322.000000, 72.000000 322.500000, 65.000000 322.500000, 69.000000 323.000000, 67.000000 323.000000, 70.000000 323.500000, 69.000000 323.500000, 72.000000 324.000000, 70.000000 324.000000, 74.000000 324.500000, 69.000000 324.500000, 72.000000 325.000000, 70.000000 325.000000, 74.000000 325.500000, 67.000000 325.500000, 70.000000 325.500000, 76.000000 326.000000, 69.000000 326.000000, 72.000000 326.000000, 77.000000 326.500000, 70.000000 326.500000, 74.000000 326.500000, 79.000000 327.000000, 72.000000 327.000000, 76.000000 327.000000, 81.000000 327.500000, 70.000000 327.500000, 74.000000 327.500000, 79.000000 328.000000, 72.000000 328.000000, 76.000000 328.000000, 81.000000 328.500000, 69.000000 328.500000, 72.000000 328.500000, 77.000000 329.000000, 70.000000 329.000000, 74.000000 329.000000, 79.000000 329.500000, 72.000000 329.500000, 76.000000 329.500000, 81.000000 330.000000, 74.000000 330.000000, 77.000000 330.000000, 82.000000 330.500000, 72.000000 330.500000, 76.000000 330.500000, 81.000000 331.000000, 70.000000 331.000000, 74.000000 331.000000, 79.000000 331.500000, 72.000000 331.500000, 76.000000 331.500000, 81.000000 332.000000, 70.000000 332.000000, 74.000000 332.000000, 79.000000 332.500000, 69.000000 332.500000, 72.000000 332.500000, 77.000000 333.000000, 67.000000 333.000000, 70.000000 333.000000, 76.000000 333.500000, 69.000000 333.500000, 72.000000 333.500000, 77.000000 334.000000, 67.000000 334.000000, 70.000000 334.000000, 76.000000 334.500000, 65.000000 334.500000, 69.000000 334.500000, 74.000000 335.000000, 64.000000 335.000000, 67.000000 335.000000, 72.000000 335.500000, 65.000000 335.500000, 69.000000 335.500000, 74.000000 336.000000, 64.000000 336.000000, 67.000000 336.000000, 72.000000 339.000000, 62.000000 339.000000, 65.000000 339.000000, 71.000000 342.000000, 60.000000 342.000000, 64.000000 342.000000, 70.000000 345.000000, 53.000000 345.000000, 69.000000 345.500000, 67.000000 346.000000, 57.000000 346.000000, 69.000000 346.500000, 65.000000 347.000000, 60.000000 347.000000, 67.000000 347.500000, 69.000000 348.000000, 62.000000 348.000000, 70.000000 348.500000, 69.000000 349.000000, 55.000000 349.000000, 70.000000 349.500000, 67.000000 350.000000, 53.000000 350.000000, 69.000000 350.500000, 71.000000 351.000000, 52.000000 351.000000, 72.000000 351.500000, 71.000000 352.000000, 55.000000 352.000000, 72.000000 352.500000, 74.000000 353.000000, 60.000000 353.000000, 72.000000 353.500000, 70.000000 354.000000, 53.000000 354.000000, 69.000000 354.500000, 67.000000 355.000000, 57.000000 355.000000, 69.000000 355.500000, 70.000000 pattern5 occurrence1 54.000000, 65.000000 54.000000, 73.000000 55.000000, 61.000000 55.000000, 70.000000 56.000000, 44.000000 56.000000, 56.000000 57.000000, 63.000000 57.000000, 72.000000 58.000000, 60.000000 58.000000, 68.000000 59.000000, 56.000000 59.000000, 60.000000 59.000000, 63.000000 59.000000, 68.000000 60.000000, 58.000000 60.000000, 61.000000 60.000000, 63.000000 60.000000, 67.000000 61.000000, 56.000000 61.000000, 60.000000 61.000000, 63.000000 61.000000, 68.000000 62.000000, 55.000000 62.000000, 58.000000 62.000000, 63.000000 62.000000, 70.000000 63.000000, 56.000000 63.000000, 60.000000 63.000000, 63.000000 63.000000, 73.000000 64.000000, 72.000000 65.000000, 60.000000 65.000000, 63.000000 65.000000, 68.000000 65.000000, 75.000000 66.000000, 58.000000 66.000000, 61.000000 66.000000, 67.000000 66.000000, 75.000000 67.000000, 56.000000 67.000000, 60.000000 67.000000, 68.000000 67.000000, 75.000000 68.000000, 55.000000 68.000000, 58.000000 68.000000, 70.000000 68.000000, 75.000000 69.000000, 56.000000 69.000000, 73.000000 69.000000, 75.000000 70.000000, 72.000000 71.000000, 49.000000 71.000000, 58.000000 71.000000, 77.000000 72.000000, 51.000000 72.000000, 60.000000 72.000000, 68.000000 74.000000, 51.000000 74.000000, 61.000000 74.000000, 67.000000 74.000000, 70.000000 75.000000, 56.000000 75.000000, 60.000000 75.000000, 68.000000 77.000000, 79.000000 77.500000, 77.000000 78.000000, 51.000000 78.000000, 60.000000 78.000000, 68.000000 80.000000, 51.000000 80.000000, 61.000000 80.000000, 67.000000 80.000000, 70.000000 81.000000, 56.000000 81.000000, 60.000000 81.000000, 68.000000 83.000000, 72.000000 83.000000, 75.000000 84.000000, 73.000000 84.000000, 76.000000 85.000000, 55.000000 85.000000, 58.000000 85.000000, 70.000000 85.000000, 73.000000 86.000000, 58.000000 86.000000, 61.000000 87.000000, 72.000000 87.000000, 75.000000 88.000000, 56.000000 88.000000, 60.000000 88.000000, 68.000000 88.000000, 72.000000 89.000000, 60.000000 89.000000, 63.000000 90.000000, 75.000000 90.000000, 78.000000 91.000000, 57.000000 91.000000, 60.000000 91.000000, 72.000000 91.000000, 75.000000 92.000000, 60.000000 92.000000, 63.000000 93.000000, 73.000000 93.000000, 77.000000 94.000000, 58.000000 94.000000, 61.000000 94.000000, 70.000000 94.000000, 73.000000 95.000000, 61.000000 95.000000, 65.000000 96.000000, 53.000000 96.000000, 61.000000 96.000000, 65.000000 96.000000, 70.000000 98.000000, 53.000000 98.000000, 63.000000 98.000000, 69.000000 98.000000, 72.000000 99.000000, 58.000000 99.000000, 61.000000 99.000000, 70.000000 101.000000, 78.000000 101.500000, 77.000000 102.000000, 53.000000 102.000000, 61.000000 102.000000, 70.000000 104.000000, 53.000000 104.000000, 63.000000 104.000000, 69.000000 104.000000, 72.000000 105.000000, 58.000000 105.000000, 61.000000 105.000000, 70.000000 107.000000, 53.000000 107.000000, 63.000000 107.000000, 69.000000 107.000000, 73.000000 107.500000, 72.000000 108.000000, 58.000000 108.000000, 61.000000 108.000000, 70.000000 110.000000, 53.000000 110.000000, 63.000000 110.000000, 69.000000 110.000000, 73.000000 110.500000, 72.000000 111.000000, 58.000000 111.000000, 61.000000 111.000000, 70.000000 113.000000, 61.000000 113.000000, 73.000000 113.500000, 60.000000 113.500000, 72.000000 114.000000, 58.000000 114.000000, 70.000000 114.500000, 60.000000 114.500000, 72.000000 115.000000, 61.000000 115.000000, 73.000000 115.500000, 60.000000 115.500000, 72.000000 116.000000, 58.000000 116.000000, 70.000000 116.500000, 60.000000 116.500000, 72.000000 117.000000, 58.000000 117.000000, 70.000000 117.500000, 56.000000 117.500000, 68.000000 118.000000, 55.000000 118.000000, 67.000000 118.500000, 56.000000 118.500000, 68.000000 119.000000, 55.000000 119.000000, 67.000000 119.500000, 53.000000 119.500000, 65.000000 occurrence2 104.000000, 53.000000 104.000000, 63.000000 104.000000, 69.000000 104.000000, 72.000000 105.000000, 58.000000 105.000000, 61.000000 105.000000, 70.000000 107.000000, 53.000000 107.000000, 63.000000 107.000000, 69.000000 107.000000, 73.000000 107.500000, 72.000000 108.000000, 58.000000 108.000000, 61.000000 108.000000, 70.000000 110.000000, 53.000000 110.000000, 63.000000 110.000000, 69.000000 110.000000, 73.000000 110.500000, 72.000000 111.000000, 58.000000 111.000000, 61.000000 111.000000, 70.000000 113.000000, 61.000000 113.000000, 73.000000 113.500000, 60.000000 113.500000, 72.000000 114.000000, 58.000000 114.000000, 70.000000 114.500000, 60.000000 114.500000, 72.000000 115.000000, 61.000000 115.000000, 73.000000 115.500000, 60.000000 115.500000, 72.000000 116.000000, 58.000000 116.000000, 70.000000 116.500000, 60.000000 116.500000, 72.000000 117.000000, 58.000000 117.000000, 70.000000 117.500000, 56.000000 117.500000, 68.000000 118.000000, 55.000000 118.000000, 67.000000 118.500000, 56.000000 118.500000, 68.000000 119.000000, 55.000000 119.000000, 67.000000 119.500000, 53.000000 119.500000, 65.000000 120.000000, 52.000000 120.000000, 64.000000 120.500000, 53.000000 120.500000, 65.000000 121.000000, 55.000000 121.000000, 67.000000 121.500000, 53.000000 121.500000, 65.000000 122.000000, 56.000000 122.000000, 68.000000 122.500000, 47.000000 122.500000, 59.000000 123.000000, 48.000000 123.000000, 60.000000 124.000000, 60.000000 125.000000, 60.000000 125.000000, 68.000000 126.000000, 61.000000 126.000000, 70.000000 127.000000, 58.000000 127.000000, 67.000000 128.000000, 58.000000 128.000000, 67.000000 128.000000, 76.000000 129.000000, 60.000000 129.000000, 68.000000 129.000000, 77.000000 130.000000, 56.000000 130.000000, 65.000000 130.000000, 80.000000 131.000000, 53.000000 131.000000, 56.000000 131.000000, 84.000000 132.000000, 52.000000 132.000000, 55.000000 132.000000, 85.000000 133.000000, 55.000000 133.000000, 58.000000 133.000000, 82.000000 134.000000, 55.000000 134.000000, 58.000000 134.000000, 82.000000 135.000000, 53.000000 135.000000, 56.000000 135.000000, 84.000000 136.000000, 56.000000 136.000000, 60.000000 136.000000, 80.000000 137.000000, 56.000000 137.000000, 60.000000 137.000000, 65.000000 137.000000, 80.000000 138.000000, 55.000000 138.000000, 58.000000 138.000000, 64.000000 138.000000, 82.000000 139.000000, 58.000000 139.000000, 61.000000 139.000000, 64.000000 139.000000, 79.000000 140.000000, 58.000000 140.000000, 61.000000 140.000000, 64.000000 140.000000, 79.000000 141.000000, 59.000000 141.000000, 62.000000 141.000000, 65.000000 141.000000, 80.000000 142.000000, 68.000000 142.000000, 77.000000 143.000000, 59.000000 143.000000, 62.000000 143.000000, 68.000000 143.000000, 77.000000 144.000000, 60.000000 144.000000, 68.000000 144.000000, 77.000000 146.000000, 60.000000 146.000000, 70.000000 146.000000, 76.000000 146.000000, 79.000000 147.000000, 65.000000 147.000000, 68.000000 147.000000, 77.000000 149.000000, 75.000000 149.500000, 73.000000 150.000000, 48.000000 150.000000, 56.000000 150.000000, 65.000000 152.000000, 48.000000 152.000000, 58.000000 152.000000, 64.000000 152.000000, 67.000000 153.000000, 53.000000 153.000000, 56.000000 153.000000, 65.000000 156.000000, 36.000000 156.000000, 48.000000 156.000000, 52.000000 156.000000, 55.000000 156.000000, 60.000000 159.000000, 41.000000 159.000000, 53.000000 161.000000, 72.000000 161.000000, 75.000000 162.000000, 73.000000 162.000000, 76.000000 163.000000, 55.000000 163.000000, 58.000000 163.000000, 70.000000 163.000000, 73.000000 164.000000, 58.000000 164.000000, 61.000000 165.000000, 72.000000 165.000000, 75.000000 166.000000, 56.000000 166.000000, 60.000000 166.000000, 68.000000 166.000000, 72.000000 167.000000, 60.000000 167.000000, 63.000000 pattern6 occurrence1 55.000000, 61.000000 55.000000, 70.000000 56.000000, 44.000000 56.000000, 56.000000 57.000000, 63.000000 57.000000, 72.000000 58.000000, 60.000000 58.000000, 68.000000 59.000000, 56.000000 59.000000, 60.000000 59.000000, 63.000000 59.000000, 68.000000 60.000000, 58.000000 60.000000, 61.000000 60.000000, 63.000000 60.000000, 67.000000 61.000000, 56.000000 61.000000, 60.000000 61.000000, 63.000000 61.000000, 68.000000 62.000000, 55.000000 62.000000, 58.000000 62.000000, 63.000000 62.000000, 70.000000 63.000000, 56.000000 63.000000, 60.000000 63.000000, 63.000000 63.000000, 73.000000 64.000000, 72.000000 65.000000, 60.000000 65.000000, 63.000000 65.000000, 68.000000 65.000000, 75.000000 66.000000, 58.000000 66.000000, 61.000000 66.000000, 67.000000 66.000000, 75.000000 67.000000, 56.000000 67.000000, 60.000000 67.000000, 68.000000 67.000000, 75.000000 68.000000, 55.000000 68.000000, 58.000000 68.000000, 70.000000 68.000000, 75.000000 69.000000, 56.000000 69.000000, 73.000000 69.000000, 75.000000 70.000000, 72.000000 71.000000, 49.000000 71.000000, 58.000000 71.000000, 77.000000 72.000000, 51.000000 72.000000, 60.000000 72.000000, 68.000000 74.000000, 51.000000 74.000000, 61.000000 74.000000, 67.000000 74.000000, 70.000000 75.000000, 56.000000 75.000000, 60.000000 75.000000, 68.000000 77.000000, 79.000000 77.500000, 77.000000 78.000000, 51.000000 78.000000, 60.000000 78.000000, 68.000000 80.000000, 51.000000 80.000000, 61.000000 80.000000, 67.000000 80.000000, 70.000000 81.000000, 56.000000 81.000000, 60.000000 81.000000, 68.000000 83.000000, 72.000000 83.000000, 75.000000 84.000000, 73.000000 84.000000, 76.000000 85.000000, 55.000000 85.000000, 58.000000 85.000000, 70.000000 85.000000, 73.000000 86.000000, 58.000000 86.000000, 61.000000 87.000000, 72.000000 87.000000, 75.000000 88.000000, 56.000000 88.000000, 60.000000 88.000000, 68.000000 88.000000, 72.000000 89.000000, 60.000000 89.000000, 63.000000 90.000000, 75.000000 90.000000, 78.000000 91.000000, 57.000000 91.000000, 60.000000 91.000000, 72.000000 91.000000, 75.000000 92.000000, 60.000000 92.000000, 63.000000 93.000000, 73.000000 93.000000, 77.000000 94.000000, 58.000000 94.000000, 61.000000 94.000000, 70.000000 94.000000, 73.000000 95.000000, 61.000000 95.000000, 65.000000 96.000000, 53.000000 96.000000, 61.000000 96.000000, 65.000000 96.000000, 70.000000 98.000000, 53.000000 98.000000, 63.000000 98.000000, 69.000000 98.000000, 72.000000 99.000000, 58.000000 99.000000, 61.000000 99.000000, 70.000000 101.000000, 78.000000 101.500000, 77.000000 102.000000, 53.000000 102.000000, 61.000000 102.000000, 70.000000 104.000000, 53.000000 104.000000, 63.000000 104.000000, 69.000000 104.000000, 72.000000 105.000000, 58.000000 105.000000, 61.000000 105.000000, 70.000000 107.000000, 53.000000 107.000000, 63.000000 107.000000, 69.000000 107.000000, 73.000000 107.500000, 72.000000 occurrence2 55.000000, 61.000000 55.000000, 70.000000 56.000000, 44.000000 56.000000, 56.000000 57.000000, 63.000000 57.000000, 72.000000 58.000000, 60.000000 58.000000, 68.000000 59.000000, 56.000000 59.000000, 60.000000 59.000000, 63.000000 59.000000, 68.000000 60.000000, 58.000000 60.000000, 61.000000 60.000000, 63.000000 60.000000, 67.000000 61.000000, 56.000000 61.000000, 60.000000 61.000000, 63.000000 61.000000, 68.000000 62.000000, 55.000000 62.000000, 58.000000 62.000000, 63.000000 62.000000, 70.000000 63.000000, 56.000000 63.000000, 60.000000 63.000000, 63.000000 63.000000, 73.000000 64.000000, 72.000000 65.000000, 60.000000 65.000000, 63.000000 65.000000, 68.000000 65.000000, 75.000000 66.000000, 58.000000 66.000000, 61.000000 66.000000, 67.000000 66.000000, 75.000000 67.000000, 56.000000 67.000000, 60.000000 67.000000, 68.000000 67.000000, 75.000000 68.000000, 55.000000 68.000000, 58.000000 68.000000, 70.000000 68.000000, 75.000000 69.000000, 56.000000 69.000000, 73.000000 69.000000, 75.000000 70.000000, 72.000000 71.000000, 49.000000 71.000000, 58.000000 71.000000, 77.000000 72.000000, 51.000000 72.000000, 60.000000 72.000000, 68.000000 74.000000, 51.000000 74.000000, 61.000000 74.000000, 67.000000 74.000000, 70.000000 75.000000, 56.000000 75.000000, 60.000000 75.000000, 68.000000 77.000000, 79.000000 77.500000, 77.000000 78.000000, 51.000000 78.000000, 60.000000 78.000000, 68.000000 80.000000, 51.000000 80.000000, 61.000000 80.000000, 67.000000 80.000000, 70.000000 81.000000, 56.000000 81.000000, 60.000000 81.000000, 68.000000 83.000000, 72.000000 83.000000, 75.000000 84.000000, 73.000000 84.000000, 76.000000 85.000000, 55.000000 85.000000, 58.000000 85.000000, 70.000000 85.000000, 73.000000 86.000000, 58.000000 86.000000, 61.000000 87.000000, 72.000000 87.000000, 75.000000 88.000000, 56.000000 88.000000, 60.000000 88.000000, 68.000000 88.000000, 72.000000 89.000000, 60.000000 89.000000, 63.000000 90.000000, 75.000000 90.000000, 78.000000 91.000000, 57.000000 91.000000, 60.000000 91.000000, 72.000000 91.000000, 75.000000 92.000000, 60.000000 92.000000, 63.000000 93.000000, 73.000000 93.000000, 77.000000 94.000000, 58.000000 94.000000, 61.000000 94.000000, 70.000000 94.000000, 73.000000 95.000000, 61.000000 95.000000, 65.000000 96.000000, 53.000000 96.000000, 61.000000 96.000000, 65.000000 96.000000, 70.000000 98.000000, 53.000000 98.000000, 63.000000 98.000000, 69.000000 98.000000, 72.000000 99.000000, 58.000000 99.000000, 61.000000 99.000000, 70.000000 101.000000, 78.000000 101.500000, 77.000000 102.000000, 53.000000 102.000000, 61.000000 102.000000, 70.000000 104.000000, 53.000000 104.000000, 63.000000 104.000000, 69.000000 104.000000, 72.000000 105.000000, 58.000000 105.000000, 61.000000 105.000000, 70.000000 107.000000, 53.000000 107.000000, 63.000000 107.000000, 69.000000 107.000000, 73.000000 107.500000, 72.000000 pattern7 occurrence1 107.000000, 53.000000 107.000000, 63.000000 107.000000, 69.000000 107.000000, 73.000000 107.500000, 72.000000 108.000000, 58.000000 108.000000, 61.000000 108.000000, 70.000000 110.000000, 53.000000 110.000000, 63.000000 110.000000, 69.000000 110.000000, 73.000000 110.500000, 72.000000 111.000000, 58.000000 111.000000, 61.000000 111.000000, 70.000000 113.000000, 61.000000 113.000000, 73.000000 113.500000, 60.000000 113.500000, 72.000000 114.000000, 58.000000 114.000000, 70.000000 114.500000, 60.000000 114.500000, 72.000000 115.000000, 61.000000 115.000000, 73.000000 115.500000, 60.000000 115.500000, 72.000000 116.000000, 58.000000 116.000000, 70.000000 116.500000, 60.000000 116.500000, 72.000000 117.000000, 58.000000 117.000000, 70.000000 117.500000, 56.000000 117.500000, 68.000000 118.000000, 55.000000 118.000000, 67.000000 118.500000, 56.000000 118.500000, 68.000000 119.000000, 55.000000 119.000000, 67.000000 119.500000, 53.000000 119.500000, 65.000000 120.000000, 52.000000 120.000000, 64.000000 120.500000, 53.000000 120.500000, 65.000000 121.000000, 55.000000 121.000000, 67.000000 121.500000, 53.000000 121.500000, 65.000000 122.000000, 56.000000 122.000000, 68.000000 122.500000, 47.000000 122.500000, 59.000000 123.000000, 48.000000 123.000000, 60.000000 124.000000, 60.000000 125.000000, 60.000000 125.000000, 68.000000 126.000000, 61.000000 126.000000, 70.000000 127.000000, 58.000000 127.000000, 67.000000 128.000000, 58.000000 128.000000, 67.000000 128.000000, 76.000000 129.000000, 60.000000 129.000000, 68.000000 129.000000, 77.000000 130.000000, 56.000000 130.000000, 65.000000 130.000000, 80.000000 131.000000, 53.000000 131.000000, 56.000000 131.000000, 84.000000 132.000000, 52.000000 132.000000, 55.000000 132.000000, 85.000000 133.000000, 55.000000 133.000000, 58.000000 133.000000, 82.000000 134.000000, 55.000000 134.000000, 58.000000 134.000000, 82.000000 135.000000, 53.000000 135.000000, 56.000000 135.000000, 84.000000 136.000000, 56.000000 136.000000, 60.000000 136.000000, 80.000000 137.000000, 56.000000 137.000000, 60.000000 137.000000, 65.000000 137.000000, 80.000000 138.000000, 55.000000 138.000000, 58.000000 138.000000, 64.000000 138.000000, 82.000000 139.000000, 58.000000 139.000000, 61.000000 139.000000, 64.000000 139.000000, 79.000000 140.000000, 58.000000 140.000000, 61.000000 140.000000, 64.000000 140.000000, 79.000000 141.000000, 59.000000 141.000000, 62.000000 141.000000, 65.000000 141.000000, 80.000000 142.000000, 68.000000 142.000000, 77.000000 143.000000, 59.000000 143.000000, 62.000000 143.000000, 68.000000 143.000000, 77.000000 144.000000, 60.000000 144.000000, 68.000000 144.000000, 77.000000 146.000000, 60.000000 146.000000, 70.000000 146.000000, 76.000000 146.000000, 79.000000 147.000000, 65.000000 147.000000, 68.000000 147.000000, 77.000000 149.000000, 75.000000 149.500000, 73.000000 150.000000, 48.000000 150.000000, 56.000000 150.000000, 65.000000 152.000000, 48.000000 152.000000, 58.000000 152.000000, 64.000000 152.000000, 67.000000 153.000000, 53.000000 153.000000, 56.000000 153.000000, 65.000000 156.000000, 36.000000 156.000000, 48.000000 156.000000, 52.000000 156.000000, 55.000000 156.000000, 60.000000 occurrence2 304.000000, 65.000000 304.500000, 62.000000 305.000000, 64.000000 305.500000, 65.000000 306.000000, 58.000000 306.000000, 67.000000 306.500000, 66.000000 307.000000, 67.000000 307.500000, 64.000000 308.000000, 65.000000 308.500000, 67.000000 309.000000, 57.000000 309.000000, 69.000000 309.500000, 65.000000 310.000000, 69.000000 310.500000, 72.000000 311.000000, 77.000000 311.500000, 81.000000 312.000000, 64.000000 312.000000, 72.000000 312.000000, 84.000000 312.500000, 62.000000 313.000000, 64.000000 313.500000, 60.000000 314.000000, 62.000000 314.500000, 64.000000 315.000000, 65.000000 315.000000, 71.000000 315.000000, 83.000000 315.500000, 64.000000 316.000000, 65.000000 316.500000, 62.000000 317.000000, 64.000000 317.500000, 65.000000 318.000000, 67.000000 318.000000, 70.000000 318.000000, 82.000000 318.500000, 65.000000 319.000000, 67.000000 319.500000, 64.000000 319.500000, 67.000000 320.000000, 65.000000 320.000000, 69.000000 320.500000, 67.000000 320.500000, 70.000000 321.000000, 69.000000 321.000000, 72.000000 321.500000, 67.000000 321.500000, 70.000000 322.000000, 69.000000 322.000000, 72.000000 322.500000, 65.000000 322.500000, 69.000000 323.000000, 67.000000 323.000000, 70.000000 323.500000, 69.000000 323.500000, 72.000000 324.000000, 70.000000 324.000000, 74.000000 324.500000, 69.000000 324.500000, 72.000000 325.000000, 70.000000 325.000000, 74.000000 325.500000, 67.000000 325.500000, 70.000000 325.500000, 76.000000 326.000000, 69.000000 326.000000, 72.000000 326.000000, 77.000000 326.500000, 70.000000 326.500000, 74.000000 326.500000, 79.000000 327.000000, 72.000000 327.000000, 76.000000 327.000000, 81.000000 327.500000, 70.000000 327.500000, 74.000000 327.500000, 79.000000 328.000000, 72.000000 328.000000, 76.000000 328.000000, 81.000000 328.500000, 69.000000 328.500000, 72.000000 328.500000, 77.000000 329.000000, 70.000000 329.000000, 74.000000 329.000000, 79.000000 329.500000, 72.000000 329.500000, 76.000000 329.500000, 81.000000 330.000000, 74.000000 330.000000, 77.000000 330.000000, 82.000000 330.500000, 72.000000 330.500000, 76.000000 330.500000, 81.000000 331.000000, 70.000000 331.000000, 74.000000 331.000000, 79.000000 331.500000, 72.000000 331.500000, 76.000000 331.500000, 81.000000 332.000000, 70.000000 332.000000, 74.000000 332.000000, 79.000000 332.500000, 69.000000 332.500000, 72.000000 332.500000, 77.000000 333.000000, 67.000000 333.000000, 70.000000 333.000000, 76.000000 333.500000, 69.000000 333.500000, 72.000000 333.500000, 77.000000 334.000000, 67.000000 334.000000, 70.000000 334.000000, 76.000000 334.500000, 65.000000 334.500000, 69.000000 334.500000, 74.000000 335.000000, 64.000000 335.000000, 67.000000 335.000000, 72.000000 335.500000, 65.000000 335.500000, 69.000000 335.500000, 74.000000 336.000000, 64.000000 336.000000, 67.000000 336.000000, 72.000000 339.000000, 62.000000 339.000000, 65.000000 339.000000, 71.000000 342.000000, 60.000000 342.000000, 64.000000 342.000000, 70.000000 345.000000, 53.000000 345.000000, 69.000000 345.500000, 67.000000 346.000000, 57.000000 346.000000, 69.000000 346.500000, 65.000000 347.000000, 60.000000 347.000000, 67.000000 347.500000, 69.000000 348.000000, 62.000000 348.000000, 70.000000 348.500000, 69.000000 349.000000, 55.000000 349.000000, 70.000000 349.500000, 67.000000 350.000000, 53.000000 350.000000, 69.000000 350.500000, 71.000000 351.000000, 52.000000 351.000000, 72.000000 351.500000, 71.000000 352.000000, 55.000000 352.000000, 72.000000 352.500000, 74.000000 353.000000, 60.000000 353.000000, 72.000000 353.500000, 70.000000 354.000000, 53.000000 354.000000, 69.000000 354.500000, 67.000000 355.000000, 57.000000 355.000000, 69.000000 355.500000, 70.000000 pattern8 occurrence1 152.000000, 48.000000 152.000000, 58.000000 152.000000, 64.000000 152.000000, 67.000000 153.000000, 53.000000 153.000000, 56.000000 153.000000, 65.000000 156.000000, 36.000000 156.000000, 48.000000 156.000000, 52.000000 156.000000, 55.000000 156.000000, 60.000000 159.000000, 41.000000 159.000000, 53.000000 161.000000, 72.000000 161.000000, 75.000000 162.000000, 73.000000 162.000000, 76.000000 163.000000, 55.000000 163.000000, 58.000000 163.000000, 70.000000 163.000000, 73.000000 164.000000, 58.000000 164.000000, 61.000000 165.000000, 72.000000 165.000000, 75.000000 166.000000, 56.000000 166.000000, 60.000000 166.000000, 68.000000 166.000000, 72.000000 167.000000, 60.000000 167.000000, 63.000000 168.000000, 75.000000 168.000000, 78.000000 169.000000, 57.000000 169.000000, 60.000000 169.000000, 72.000000 169.000000, 75.000000 occurrence2 217.000000, 58.000000 217.000000, 61.000000 217.000000, 64.000000 217.000000, 79.000000 218.000000, 58.000000 218.000000, 61.000000 218.000000, 64.000000 218.000000, 79.000000 219.000000, 59.000000 219.000000, 62.000000 219.000000, 65.000000 219.000000, 80.000000 220.000000, 68.000000 220.000000, 77.000000 221.000000, 59.000000 221.000000, 62.000000 221.000000, 68.000000 221.000000, 77.000000 222.000000, 60.000000 222.000000, 68.000000 222.000000, 77.000000 224.000000, 60.000000 224.000000, 70.000000 224.000000, 76.000000 224.000000, 79.000000 225.000000, 65.000000 225.000000, 68.000000 225.000000, 77.000000 227.000000, 75.000000 227.500000, 73.000000 228.000000, 48.000000 228.000000, 56.000000 228.000000, 65.000000 230.000000, 48.000000 230.000000, 58.000000 230.000000, 64.000000 230.000000, 67.000000 231.000000, 53.000000 231.000000, 56.000000 231.000000, 65.000000 234.000000, 36.000000 234.000000, 48.000000 234.000000, 52.000000 234.000000, 55.000000 234.000000, 60.000000 pattern9 occurrence1 152.000000, 48.000000 152.000000, 58.000000 152.000000, 64.000000 152.000000, 67.000000 153.000000, 53.000000 153.000000, 56.000000 153.000000, 65.000000 156.000000, 36.000000 156.000000, 48.000000 156.000000, 52.000000 156.000000, 55.000000 156.000000, 60.000000 159.000000, 41.000000 159.000000, 53.000000 161.000000, 72.000000 161.000000, 75.000000 162.000000, 73.000000 162.000000, 76.000000 163.000000, 55.000000 163.000000, 58.000000 163.000000, 70.000000 163.000000, 73.000000 164.000000, 58.000000 164.000000, 61.000000 165.000000, 72.000000 165.000000, 75.000000 166.000000, 56.000000 166.000000, 60.000000 166.000000, 68.000000 166.000000, 72.000000 167.000000, 60.000000 167.000000, 63.000000 168.000000, 75.000000 168.000000, 78.000000 169.000000, 57.000000 169.000000, 60.000000 169.000000, 72.000000 169.000000, 75.000000 170.000000, 60.000000 170.000000, 63.000000 171.000000, 73.000000 171.000000, 77.000000 172.000000, 58.000000 172.000000, 61.000000 172.000000, 70.000000 172.000000, 73.000000 173.000000, 61.000000 173.000000, 65.000000 174.000000, 53.000000 174.000000, 61.000000 174.000000, 65.000000 174.000000, 70.000000 176.000000, 53.000000 176.000000, 63.000000 176.000000, 69.000000 176.000000, 72.000000 177.000000, 58.000000 177.000000, 61.000000 177.000000, 70.000000 occurrence2 170.000000, 60.000000 170.000000, 63.000000 171.000000, 73.000000 171.000000, 77.000000 172.000000, 58.000000 172.000000, 61.000000 172.000000, 70.000000 172.000000, 73.000000 173.000000, 61.000000 173.000000, 65.000000 174.000000, 53.000000 174.000000, 61.000000 174.000000, 65.000000 174.000000, 70.000000 176.000000, 53.000000 176.000000, 63.000000 176.000000, 69.000000 176.000000, 72.000000 177.000000, 58.000000 177.000000, 61.000000 177.000000, 70.000000 179.000000, 78.000000 179.500000, 77.000000 180.000000, 53.000000 180.000000, 61.000000 180.000000, 70.000000 182.000000, 53.000000 182.000000, 63.000000 182.000000, 69.000000 182.000000, 72.000000 183.000000, 58.000000 183.000000, 61.000000 183.000000, 70.000000 185.000000, 53.000000 185.000000, 63.000000 185.000000, 69.000000 185.000000, 73.000000 185.500000, 72.000000 186.000000, 58.000000 186.000000, 61.000000 186.000000, 70.000000 188.000000, 53.000000 188.000000, 63.000000 188.000000, 69.000000 188.000000, 73.000000 188.500000, 72.000000 189.000000, 58.000000 189.000000, 61.000000 189.000000, 70.000000 191.000000, 61.000000 191.000000, 73.000000 191.500000, 60.000000 191.500000, 72.000000 192.000000, 58.000000 192.000000, 70.000000 192.500000, 60.000000 192.500000, 72.000000 193.000000, 61.000000 193.000000, 73.000000 193.500000, 60.000000 193.500000, 72.000000 194.000000, 58.000000 194.000000, 70.000000 194.500000, 60.000000 194.500000, 72.000000 195.000000, 58.000000 195.000000, 70.000000 195.500000, 56.000000 195.500000, 68.000000 196.000000, 55.000000 196.000000, 67.000000 196.500000, 56.000000 196.500000, 68.000000 pattern10 occurrence1 152.000000, 48.000000 152.000000, 58.000000 152.000000, 64.000000 152.000000, 67.000000 153.000000, 53.000000 153.000000, 56.000000 153.000000, 65.000000 156.000000, 36.000000 156.000000, 48.000000 156.000000, 52.000000 156.000000, 55.000000 156.000000, 60.000000 159.000000, 41.000000 159.000000, 53.000000 161.000000, 72.000000 161.000000, 75.000000 162.000000, 73.000000 162.000000, 76.000000 163.000000, 55.000000 163.000000, 58.000000 163.000000, 70.000000 163.000000, 73.000000 164.000000, 58.000000 164.000000, 61.000000 165.000000, 72.000000 165.000000, 75.000000 occurrence2 260.000000, 47.000000 260.000000, 76.000000 260.500000, 49.000000 261.000000, 50.000000 261.000000, 65.000000 261.500000, 45.000000 262.000000, 47.000000 262.000000, 74.000000 262.500000, 43.000000 263.000000, 48.000000 263.000000, 64.000000 263.000000, 72.000000 263.500000, 42.000000 264.000000, 43.000000 264.500000, 67.000000 265.000000, 64.000000 265.500000, 60.000000 266.000000, 31.000000 266.000000, 59.000000 266.000000, 65.000000 266.500000, 62.000000 267.000000, 36.000000 267.000000, 60.000000 268.000000, 48.000000 269.000000, 60.000000 270.000000, 53.000000 270.000000, 69.000000 270.500000, 67.000000 271.000000, 57.000000 271.000000, 69.000000 271.500000, 65.000000 272.000000, 60.000000 272.000000, 67.000000 272.500000, 69.000000 273.000000, 62.000000 273.000000, 70.000000 273.500000, 69.000000 pattern11 occurrence1 152.000000, 48.000000 152.000000, 58.000000 152.000000, 64.000000 152.000000, 67.000000 153.000000, 53.000000 153.000000, 56.000000 153.000000, 65.000000 156.000000, 36.000000 156.000000, 48.000000 156.000000, 52.000000 156.000000, 55.000000 156.000000, 60.000000 159.000000, 41.000000 159.000000, 53.000000 161.000000, 72.000000 161.000000, 75.000000 162.000000, 73.000000 162.000000, 76.000000 163.000000, 55.000000 163.000000, 58.000000 163.000000, 70.000000 163.000000, 73.000000 164.000000, 58.000000 164.000000, 61.000000 165.000000, 72.000000 165.000000, 75.000000 166.000000, 56.000000 166.000000, 60.000000 166.000000, 68.000000 166.000000, 72.000000 167.000000, 60.000000 167.000000, 63.000000 168.000000, 75.000000 168.000000, 78.000000 169.000000, 57.000000 169.000000, 60.000000 169.000000, 72.000000 169.000000, 75.000000 170.000000, 60.000000 170.000000, 63.000000 171.000000, 73.000000 171.000000, 77.000000 172.000000, 58.000000 172.000000, 61.000000 172.000000, 70.000000 172.000000, 73.000000 occurrence2 152.000000, 48.000000 152.000000, 58.000000 152.000000, 64.000000 152.000000, 67.000000 153.000000, 53.000000 153.000000, 56.000000 153.000000, 65.000000 156.000000, 36.000000 156.000000, 48.000000 156.000000, 52.000000 156.000000, 55.000000 156.000000, 60.000000 159.000000, 41.000000 159.000000, 53.000000 161.000000, 72.000000 161.000000, 75.000000 162.000000, 73.000000 162.000000, 76.000000 163.000000, 55.000000 163.000000, 58.000000 163.000000, 70.000000 163.000000, 73.000000 164.000000, 58.000000 164.000000, 61.000000 165.000000, 72.000000 165.000000, 75.000000 166.000000, 56.000000 166.000000, 60.000000 166.000000, 68.000000 166.000000, 72.000000 167.000000, 60.000000 167.000000, 63.000000 168.000000, 75.000000 168.000000, 78.000000 169.000000, 57.000000 169.000000, 60.000000 169.000000, 72.000000 169.000000, 75.000000 170.000000, 60.000000 170.000000, 63.000000 171.000000, 73.000000 171.000000, 77.000000 172.000000, 58.000000 172.000000, 61.000000 172.000000, 70.000000 172.000000, 73.000000 173.000000, 61.000000 173.000000, 65.000000 pattern12 occurrence1 169.000000, 57.000000 169.000000, 60.000000 169.000000, 72.000000 169.000000, 75.000000 170.000000, 60.000000 170.000000, 63.000000 171.000000, 73.000000 171.000000, 77.000000 172.000000, 58.000000 172.000000, 61.000000 172.000000, 70.000000 172.000000, 73.000000 173.000000, 61.000000 173.000000, 65.000000 174.000000, 53.000000 174.000000, 61.000000 174.000000, 65.000000 174.000000, 70.000000 176.000000, 53.000000 176.000000, 63.000000 176.000000, 69.000000 176.000000, 72.000000 177.000000, 58.000000 177.000000, 61.000000 177.000000, 70.000000 179.000000, 78.000000 179.500000, 77.000000 180.000000, 53.000000 180.000000, 61.000000 180.000000, 70.000000 182.000000, 53.000000 182.000000, 63.000000 182.000000, 69.000000 182.000000, 72.000000 183.000000, 58.000000 183.000000, 61.000000 183.000000, 70.000000 185.000000, 53.000000 185.000000, 63.000000 185.000000, 69.000000 185.000000, 73.000000 185.500000, 72.000000 186.000000, 58.000000 186.000000, 61.000000 186.000000, 70.000000 occurrence2 259.000000, 48.000000 259.000000, 77.000000 259.500000, 45.000000 260.000000, 47.000000 260.000000, 76.000000 260.500000, 49.000000 261.000000, 50.000000 261.000000, 65.000000 261.500000, 45.000000 262.000000, 47.000000 262.000000, 74.000000 262.500000, 43.000000 263.000000, 48.000000 263.000000, 64.000000 263.000000, 72.000000 263.500000, 42.000000 264.000000, 43.000000 264.500000, 67.000000 265.000000, 64.000000 265.500000, 60.000000 266.000000, 31.000000 266.000000, 59.000000 266.000000, 65.000000 266.500000, 62.000000 267.000000, 36.000000 267.000000, 60.000000 268.000000, 48.000000 269.000000, 60.000000 270.000000, 53.000000 270.000000, 69.000000 270.500000, 67.000000 271.000000, 57.000000 271.000000, 69.000000 271.500000, 65.000000 272.000000, 60.000000 272.000000, 67.000000 272.500000, 69.000000 273.000000, 62.000000 273.000000, 70.000000 273.500000, 69.000000 274.000000, 55.000000 274.000000, 70.000000 274.500000, 67.000000 275.000000, 53.000000 275.000000, 69.000000 275.500000, 71.000000 276.000000, 52.000000 276.000000, 72.000000 276.500000, 71.000000 pattern13 occurrence1 171.000000, 73.000000 171.000000, 77.000000 172.000000, 58.000000 172.000000, 61.000000 172.000000, 70.000000 172.000000, 73.000000 173.000000, 61.000000 173.000000, 65.000000 174.000000, 53.000000 174.000000, 61.000000 174.000000, 65.000000 174.000000, 70.000000 176.000000, 53.000000 176.000000, 63.000000 176.000000, 69.000000 176.000000, 72.000000 177.000000, 58.000000 177.000000, 61.000000 177.000000, 70.000000 179.000000, 78.000000 179.500000, 77.000000 180.000000, 53.000000 180.000000, 61.000000 180.000000, 70.000000 182.000000, 53.000000 182.000000, 63.000000 182.000000, 69.000000 182.000000, 72.000000 183.000000, 58.000000 183.000000, 61.000000 183.000000, 70.000000 occurrence2 218.000000, 58.000000 218.000000, 61.000000 218.000000, 64.000000 218.000000, 79.000000 219.000000, 59.000000 219.000000, 62.000000 219.000000, 65.000000 219.000000, 80.000000 220.000000, 68.000000 220.000000, 77.000000 221.000000, 59.000000 221.000000, 62.000000 221.000000, 68.000000 221.000000, 77.000000 222.000000, 60.000000 222.000000, 68.000000 222.000000, 77.000000 224.000000, 60.000000 224.000000, 70.000000 224.000000, 76.000000 224.000000, 79.000000 225.000000, 65.000000 225.000000, 68.000000 225.000000, 77.000000 227.000000, 75.000000 227.500000, 73.000000 228.000000, 48.000000 228.000000, 56.000000 228.000000, 65.000000 230.000000, 48.000000 230.000000, 58.000000 230.000000, 64.000000 230.000000, 67.000000 231.000000, 53.000000 231.000000, 56.000000 231.000000, 65.000000 pattern14 occurrence1 191.000000, 61.000000 191.000000, 73.000000 191.500000, 60.000000 191.500000, 72.000000 192.000000, 58.000000 192.000000, 70.000000 192.500000, 60.000000 192.500000, 72.000000 193.000000, 61.000000 193.000000, 73.000000 193.500000, 60.000000 193.500000, 72.000000 194.000000, 58.000000 194.000000, 70.000000 194.500000, 60.000000 194.500000, 72.000000 195.000000, 58.000000 195.000000, 70.000000 195.500000, 56.000000 195.500000, 68.000000 196.000000, 55.000000 196.000000, 67.000000 196.500000, 56.000000 196.500000, 68.000000 197.000000, 55.000000 197.000000, 67.000000 197.500000, 53.000000 197.500000, 65.000000 198.000000, 52.000000 198.000000, 64.000000 198.500000, 53.000000 198.500000, 65.000000 199.000000, 55.000000 199.000000, 67.000000 199.500000, 53.000000 199.500000, 65.000000 200.000000, 56.000000 200.000000, 68.000000 200.500000, 47.000000 200.500000, 59.000000 201.000000, 48.000000 201.000000, 60.000000 202.000000, 60.000000 203.000000, 60.000000 203.000000, 68.000000 204.000000, 61.000000 204.000000, 70.000000 205.000000, 58.000000 205.000000, 67.000000 206.000000, 58.000000 206.000000, 67.000000 206.000000, 76.000000 207.000000, 60.000000 207.000000, 68.000000 207.000000, 77.000000 208.000000, 56.000000 208.000000, 65.000000 208.000000, 80.000000 209.000000, 53.000000 209.000000, 56.000000 209.000000, 84.000000 210.000000, 52.000000 210.000000, 55.000000 210.000000, 85.000000 211.000000, 55.000000 211.000000, 58.000000 211.000000, 82.000000 212.000000, 55.000000 212.000000, 58.000000 212.000000, 82.000000 213.000000, 53.000000 213.000000, 56.000000 213.000000, 84.000000 214.000000, 56.000000 214.000000, 60.000000 214.000000, 80.000000 215.000000, 56.000000 215.000000, 60.000000 215.000000, 65.000000 215.000000, 80.000000 216.000000, 55.000000 216.000000, 58.000000 216.000000, 64.000000 216.000000, 82.000000 217.000000, 58.000000 217.000000, 61.000000 217.000000, 64.000000 217.000000, 79.000000 218.000000, 58.000000 218.000000, 61.000000 218.000000, 64.000000 218.000000, 79.000000 219.000000, 59.000000 219.000000, 62.000000 219.000000, 65.000000 219.000000, 80.000000 220.000000, 68.000000 220.000000, 77.000000 221.000000, 59.000000 221.000000, 62.000000 221.000000, 68.000000 221.000000, 77.000000 222.000000, 60.000000 222.000000, 68.000000 222.000000, 77.000000 224.000000, 60.000000 224.000000, 70.000000 224.000000, 76.000000 224.000000, 79.000000 225.000000, 65.000000 225.000000, 68.000000 225.000000, 77.000000 227.000000, 75.000000 227.500000, 73.000000 228.000000, 48.000000 228.000000, 56.000000 228.000000, 65.000000 230.000000, 48.000000 230.000000, 58.000000 230.000000, 64.000000 230.000000, 67.000000 231.000000, 53.000000 231.000000, 56.000000 231.000000, 65.000000 234.000000, 36.000000 234.000000, 48.000000 234.000000, 52.000000 234.000000, 55.000000 234.000000, 60.000000 237.000000, 41.000000 237.000000, 53.000000 occurrence2 234.000000, 36.000000 234.000000, 48.000000 234.000000, 52.000000 234.000000, 55.000000 234.000000, 60.000000 237.000000, 41.000000 237.000000, 53.000000 239.000000, 60.000000 240.000000, 53.000000 240.000000, 69.000000 240.500000, 67.000000 241.000000, 57.000000 241.000000, 69.000000 241.500000, 65.000000 242.000000, 60.000000 242.000000, 67.000000 242.500000, 69.000000 243.000000, 62.000000 243.000000, 70.000000 243.500000, 69.000000 244.000000, 55.000000 244.000000, 70.000000 244.500000, 67.000000 245.000000, 53.000000 245.000000, 69.000000 245.500000, 71.000000 246.000000, 52.000000 246.000000, 72.000000 246.500000, 71.000000 247.000000, 55.000000 247.000000, 72.000000 247.500000, 74.000000 248.000000, 60.000000 248.000000, 72.000000 248.500000, 70.000000 249.000000, 53.000000 249.000000, 69.000000 249.500000, 67.000000 250.000000, 57.000000 250.000000, 69.000000 250.500000, 70.000000 251.000000, 60.000000 251.000000, 69.000000 251.500000, 65.000000 252.000000, 45.000000 252.000000, 69.000000 252.000000, 69.000000 252.500000, 44.000000 253.000000, 45.000000 253.000000, 72.000000 253.500000, 41.000000 254.000000, 43.000000 254.000000, 77.000000 254.500000, 45.000000 255.000000, 46.000000 255.000000, 67.000000 255.000000, 67.000000 255.500000, 45.000000 256.000000, 46.000000 256.000000, 74.000000 256.500000, 43.000000 257.000000, 45.000000 257.000000, 77.000000 257.500000, 47.000000 258.000000, 48.000000 258.000000, 67.000000 258.500000, 47.000000 259.000000, 48.000000 259.000000, 77.000000 259.500000, 45.000000 260.000000, 47.000000 260.000000, 76.000000 260.500000, 49.000000 261.000000, 50.000000 261.000000, 65.000000 261.500000, 45.000000 262.000000, 47.000000 262.000000, 74.000000 262.500000, 43.000000 263.000000, 48.000000 263.000000, 64.000000 263.000000, 72.000000 263.500000, 42.000000 264.000000, 43.000000 264.500000, 67.000000 265.000000, 64.000000 265.500000, 60.000000 266.000000, 31.000000 266.000000, 59.000000 266.000000, 65.000000 266.500000, 62.000000 267.000000, 36.000000 267.000000, 60.000000 268.000000, 48.000000 269.000000, 60.000000 270.000000, 53.000000 270.000000, 69.000000 270.500000, 67.000000 271.000000, 57.000000 271.000000, 69.000000 271.500000, 65.000000 272.000000, 60.000000 272.000000, 67.000000 272.500000, 69.000000 273.000000, 62.000000 273.000000, 70.000000 273.500000, 69.000000 274.000000, 55.000000 274.000000, 70.000000 274.500000, 67.000000 275.000000, 53.000000 275.000000, 69.000000 275.500000, 71.000000 276.000000, 52.000000 276.000000, 72.000000 276.500000, 71.000000 277.000000, 55.000000 277.000000, 72.000000 277.500000, 74.000000 278.000000, 60.000000 278.000000, 72.000000 278.500000, 70.000000 279.000000, 53.000000 279.000000, 69.000000 279.500000, 67.000000 280.000000, 57.000000 280.000000, 69.000000 280.500000, 70.000000 281.000000, 60.000000 281.000000, 69.000000 281.500000, 65.000000 occurrence3 191.000000, 61.000000 191.000000, 73.000000 191.500000, 60.000000 191.500000, 72.000000 192.000000, 58.000000 192.000000, 70.000000 192.500000, 60.000000 192.500000, 72.000000 193.000000, 61.000000 193.000000, 73.000000 193.500000, 60.000000 193.500000, 72.000000 194.000000, 58.000000 194.000000, 70.000000 194.500000, 60.000000 194.500000, 72.000000 195.000000, 58.000000 195.000000, 70.000000 195.500000, 56.000000 195.500000, 68.000000 196.000000, 55.000000 196.000000, 67.000000 196.500000, 56.000000 196.500000, 68.000000 197.000000, 55.000000 197.000000, 67.000000 197.500000, 53.000000 197.500000, 65.000000 198.000000, 52.000000 198.000000, 64.000000 198.500000, 53.000000 198.500000, 65.000000 199.000000, 55.000000 199.000000, 67.000000 199.500000, 53.000000 199.500000, 65.000000 200.000000, 56.000000 200.000000, 68.000000 200.500000, 47.000000 200.500000, 59.000000 201.000000, 48.000000 201.000000, 60.000000 202.000000, 60.000000 203.000000, 60.000000 203.000000, 68.000000 204.000000, 61.000000 204.000000, 70.000000 205.000000, 58.000000 205.000000, 67.000000 206.000000, 58.000000 206.000000, 67.000000 206.000000, 76.000000 207.000000, 60.000000 207.000000, 68.000000 207.000000, 77.000000 208.000000, 56.000000 208.000000, 65.000000 208.000000, 80.000000 209.000000, 53.000000 209.000000, 56.000000 209.000000, 84.000000 210.000000, 52.000000 210.000000, 55.000000 210.000000, 85.000000 211.000000, 55.000000 211.000000, 58.000000 211.000000, 82.000000 212.000000, 55.000000 212.000000, 58.000000 212.000000, 82.000000 213.000000, 53.000000 213.000000, 56.000000 213.000000, 84.000000 214.000000, 56.000000 214.000000, 60.000000 214.000000, 80.000000 215.000000, 56.000000 215.000000, 60.000000 215.000000, 65.000000 215.000000, 80.000000 216.000000, 55.000000 216.000000, 58.000000 216.000000, 64.000000 216.000000, 82.000000 217.000000, 58.000000 217.000000, 61.000000 217.000000, 64.000000 217.000000, 79.000000 218.000000, 58.000000 218.000000, 61.000000 218.000000, 64.000000 218.000000, 79.000000 219.000000, 59.000000 219.000000, 62.000000 219.000000, 65.000000 219.000000, 80.000000 220.000000, 68.000000 220.000000, 77.000000 221.000000, 59.000000 221.000000, 62.000000 221.000000, 68.000000 221.000000, 77.000000 222.000000, 60.000000 222.000000, 68.000000 222.000000, 77.000000 224.000000, 60.000000 224.000000, 70.000000 224.000000, 76.000000 224.000000, 79.000000 225.000000, 65.000000 225.000000, 68.000000 225.000000, 77.000000 227.000000, 75.000000 227.500000, 73.000000 228.000000, 48.000000 228.000000, 56.000000 228.000000, 65.000000 230.000000, 48.000000 230.000000, 58.000000 230.000000, 64.000000 230.000000, 67.000000 231.000000, 53.000000 231.000000, 56.000000 231.000000, 65.000000 234.000000, 36.000000 234.000000, 48.000000 234.000000, 52.000000 234.000000, 55.000000 234.000000, 60.000000 237.000000, 41.000000 237.000000, 53.000000 pattern15 occurrence1 312.000000, 64.000000 312.000000, 72.000000 312.000000, 84.000000 312.500000, 62.000000 313.000000, 64.000000 313.500000, 60.000000 314.000000, 62.000000 314.500000, 64.000000 315.000000, 65.000000 315.000000, 71.000000 315.000000, 83.000000 315.500000, 64.000000 316.000000, 65.000000 316.500000, 62.000000 317.000000, 64.000000 317.500000, 65.000000 318.000000, 67.000000 318.000000, 70.000000 318.000000, 82.000000 318.500000, 65.000000 319.000000, 67.000000 319.500000, 64.000000 319.500000, 67.000000 320.000000, 65.000000 320.000000, 69.000000 320.500000, 67.000000 320.500000, 70.000000 321.000000, 69.000000 321.000000, 72.000000 321.500000, 67.000000 321.500000, 70.000000 occurrence2 316.000000, 65.000000 316.500000, 62.000000 317.000000, 64.000000 317.500000, 65.000000 318.000000, 67.000000 318.000000, 70.000000 318.000000, 82.000000 318.500000, 65.000000 319.000000, 67.000000 319.500000, 64.000000 319.500000, 67.000000 320.000000, 65.000000 320.000000, 69.000000 320.500000, 67.000000 320.500000, 70.000000 321.000000, 69.000000 321.000000, 72.000000 321.500000, 67.000000 321.500000, 70.000000 322.000000, 69.000000 322.000000, 72.000000 322.500000, 65.000000 322.500000, 69.000000 323.000000, 67.000000 323.000000, 70.000000 323.500000, 69.000000 323.500000, 72.000000 324.000000, 70.000000 324.000000, 74.000000 324.500000, 69.000000 324.500000, 72.000000 325.000000, 70.000000 325.000000, 74.000000 325.500000, 67.000000 325.500000, 70.000000 325.500000, 76.000000 mir_eval-0.8.2/tests/data/pattern/output00.json000066400000000000000000000005441475740344600214630ustar00rootroot00000000000000{"F": 0.0, "P": 0.0, "R": 0.0, "F_est": 0.35878787878787882, "P_est": 0.44848484848484849, "R_est": 0.29898989898989897, "F_occ.5": 0.0, "P_occ.5": 0, "R_occ.5": 0, "F_occ.75": 0.0, "P_occ.75": 0, "R_occ.75": 0, "F_3": 0.16165324386492833, "P_3": 0.20206655483116043, "R_3": 0.13471103655410696, "FFP": 0.20206655483116043, "FFTP_est": 0.29898989898989897}mir_eval-0.8.2/tests/data/pattern/output01.json000066400000000000000000000006021475740344600214570ustar00rootroot00000000000000{"F": 0.28571428571428575, "P": 0.25, "R": 0.3333333333333333, "F_est": 0.25249448754612192, "P_est": 0.25927023102889601, "R_est": 0.246063877642825, "F_occ.5": 0.0, "P_occ.5": 0, "R_occ.5": 0, "F_occ.75": 0.0, "P_occ.75": 0, "R_occ.75": 0, "F_3": 0.10211154049937549, "P_3": 0.094650816870979773, "R_3": 0.11084906966815376, "FFP": 0.094650816870979773, "FFTP_est": 0.246063877642825}mir_eval-0.8.2/tests/data/pattern/output02.json000066400000000000000000000007141475740344600214640ustar00rootroot00000000000000{"F": 0.0, "P": 0.0, "R": 0.0, "F_est": 0.59059477273784466, "P_est": 0.53696061490272651, "R_est": 0.65613236703756328, "F_occ.5": 0.47732667346571606, "P_occ.5": 0.56455932565087485, "R_occ.5": 0.41344360478577541, "F_occ.75": 0.47732667346571606, "P_occ.75": 0.56455932565087485, "R_occ.75": 0.41344360478577541, "F_3": 0.36829084595436512, "P_3": 0.33484219438175999, "R_3": 0.40916375938472338, "FFP": 0.46540500984993144, "FFTP_est": 0.60838976846150139}mir_eval-0.8.2/tests/data/pattern/ref00.txt000066400000000000000000000216371475740344600205530ustar00rootroot00000000000000pattern1 occurrence1 21.0000000000, 76.0000000000 22.0000000000, 72.0000000000 23.0000000000, 77.0000000000 24.0000000000, 68.0000000000 26.5000000000, 74.0000000000 27.0000000000, 71.0000000000 27.5000000000, 76.0000000000 28.0000000000, 72.0000000000 occurrence2 81.0000000000, 81.0000000000 82.0000000000, 77.0000000000 83.0000000000, 82.0000000000 84.0000000000, 73.0000000000 86.5000000000, 79.0000000000 87.0000000000, 76.0000000000 87.5000000000, 81.0000000000 88.0000000000, 77.0000000000 occurrence3 225.0000000000, 64.0000000000 226.0000000000, 60.0000000000 227.0000000000, 65.0000000000 228.0000000000, 56.0000000000 230.5000000000, 62.0000000000 231.0000000000, 59.0000000000 231.5000000000, 64.0000000000 232.0000000000, 60.0000000000 occurrence4 259.0000000000, 55.0000000000 260.0000000000, 52.0000000000 261.0000000000, 57.0000000000 262.0000000000, 47.0000000000 264.5000000000, 53.0000000000 265.0000000000, 50.0000000000 265.5000000000, 55.0000000000 266.0000000000, 52.0000000000 occurrence5 323.0000000000, 52.0000000000 324.0000000000, 48.0000000000 325.0000000000, 53.0000000000 326.0000000000, 44.0000000000 328.5000000000, 50.0000000000 329.0000000000, 47.0000000000 329.5000000000, 52.0000000000 330.0000000000, 48.0000000000 occurrence6 49.0000000000, 81.0000000000 50.0000000000, 79.0000000000 51.0000000000, 84.0000000000 52.0000000000, 75.0000000000 54.5000000000, 81.0000000000 55.0000000000, 78.0000000000 55.5000000000, 83.0000000000 56.0000000000, 79.0000000000 occurrence7 121.0000000000, 69.0000000000 122.0000000000, 67.0000000000 123.0000000000, 72.0000000000 124.0000000000, 63.0000000000 126.5000000000, 69.0000000000 127.0000000000, 66.0000000000 127.5000000000, 71.0000000000 128.0000000000, 67.0000000000 occurrence8 226.0000000000, 60.0000000000 227.0000000000, 65.0000000000 228.0000000000, 56.0000000000 230.5000000000, 62.0000000000 231.0000000000, 59.0000000000 231.5000000000, 64.0000000000 232.0000000000, 60.0000000000 pattern2 occurrence1 36.5000000000, 84.0000000000 36.6250000000, 83.0000000000 36.7500000000, 81.0000000000 36.8750000000, 79.0000000000 37.0000000000, 77.0000000000 37.5000000000, 81.0000000000 37.6250000000, 79.0000000000 37.7500000000, 77.0000000000 37.8750000000, 76.0000000000 38.0000000000, 74.0000000000 38.1250000000, 76.0000000000 38.2500000000, 77.0000000000 38.6250000000, 76.0000000000 38.7500000000, 74.0000000000 38.8750000000, 72.0000000000 39.0000000000, 71.0000000000 39.1250000000, 72.0000000000 39.2500000000, 74.0000000000 39.6250000000, 72.0000000000 39.7500000000, 71.0000000000 39.8750000000, 69.0000000000 40.0000000000, 67.0000000000 40.7500000000, 69.0000000000 40.8750000000, 71.0000000000 41.0000000000, 71.0000000000 41.7500000000, 69.0000000000 41.8750000000, 71.0000000000 42.0000000000, 72.0000000000 occurrence2 134.5000000000, 69.0000000000 134.6250000000, 67.0000000000 134.7500000000, 65.0000000000 134.8750000000, 64.0000000000 135.0000000000, 62.0000000000 135.5000000000, 65.0000000000 135.6250000000, 64.0000000000 135.7500000000, 62.0000000000 135.8750000000, 60.0000000000 136.0000000000, 59.0000000000 136.1250000000, 60.0000000000 136.2500000000, 62.0000000000 136.6250000000, 60.0000000000 136.7500000000, 59.0000000000 136.8750000000, 57.0000000000 137.0000000000, 56.0000000000 137.1250000000, 57.0000000000 137.2500000000, 59.0000000000 137.6250000000, 57.0000000000 137.7500000000, 56.0000000000 137.8750000000, 54.0000000000 138.0000000000, 52.0000000000 138.7500000000, 54.0000000000 138.8750000000, 56.0000000000 139.0000000000, 56.0000000000 139.7500000000, 54.0000000000 139.8750000000, 56.0000000000 140.0000000000, 57.0000000000 occurrence3 162.5000000000, 76.0000000000 162.6250000000, 74.0000000000 162.7500000000, 72.0000000000 162.8750000000, 71.0000000000 163.0000000000, 69.0000000000 163.5000000000, 72.0000000000 163.6250000000, 71.0000000000 163.7500000000, 69.0000000000 163.8750000000, 67.0000000000 164.0000000000, 66.0000000000 164.1250000000, 67.0000000000 164.2500000000, 69.0000000000 164.6250000000, 67.0000000000 164.7500000000, 66.0000000000 164.8750000000, 64.0000000000 165.0000000000, 63.0000000000 165.1250000000, 64.0000000000 165.2500000000, 66.0000000000 165.6250000000, 64.0000000000 165.7500000000, 63.0000000000 165.8750000000, 61.0000000000 166.0000000000, 59.0000000000 166.7500000000, 61.0000000000 166.8750000000, 63.0000000000 167.0000000000, 63.0000000000 167.7500000000, 61.0000000000 167.8750000000, 63.0000000000 168.0000000000, 64.0000000000 occurrence4 234.5000000000, 64.0000000000 234.6250000000, 62.0000000000 234.7500000000, 60.0000000000 234.8750000000, 59.0000000000 235.0000000000, 57.0000000000 235.5000000000, 60.0000000000 235.6250000000, 59.0000000000 235.7500000000, 57.0000000000 235.8750000000, 55.0000000000 236.0000000000, 54.0000000000 236.1250000000, 55.0000000000 236.2500000000, 57.0000000000 236.6250000000, 55.0000000000 236.7500000000, 54.0000000000 236.8750000000, 52.0000000000 237.0000000000, 51.0000000000 237.1250000000, 52.0000000000 237.2500000000, 54.0000000000 237.6250000000, 52.0000000000 237.7500000000, 51.0000000000 237.8750000000, 49.0000000000 238.0000000000, 47.0000000000 238.7500000000, 49.0000000000 238.8750000000, 51.0000000000 239.0000000000, 51.0000000000 239.7500000000, 49.0000000000 239.8750000000, 51.0000000000 240.0000000000, 52.0000000000 occurrence5 290.5000000000, 57.0000000000 290.6250000000, 55.0000000000 290.7500000000, 53.0000000000 290.8750000000, 52.0000000000 291.0000000000, 50.0000000000 291.5000000000, 53.0000000000 291.6250000000, 52.0000000000 291.7500000000, 50.0000000000 291.8750000000, 48.0000000000 292.0000000000, 47.0000000000 292.1250000000, 48.0000000000 292.2500000000, 50.0000000000 292.6250000000, 48.0000000000 292.7500000000, 47.0000000000 292.8750000000, 45.0000000000 293.0000000000, 44.0000000000 293.1250000000, 45.0000000000 293.2500000000, 47.0000000000 293.6250000000, 45.0000000000 293.7500000000, 44.0000000000 293.8750000000, 42.0000000000 294.0000000000, 40.0000000000 294.7500000000, 42.0000000000 294.8750000000, 44.0000000000 295.0000000000, 44.0000000000 295.7500000000, 42.0000000000 295.8750000000, 44.0000000000 296.0000000000, 45.0000000000 occurrence6 306.5000000000, 62.0000000000 306.6250000000, 60.0000000000 306.7500000000, 58.0000000000 306.8750000000, 57.0000000000 307.0000000000, 55.0000000000 307.5000000000, 58.0000000000 307.6250000000, 57.0000000000 307.7500000000, 55.0000000000 307.8750000000, 53.0000000000 308.0000000000, 52.0000000000 308.1250000000, 53.0000000000 308.2500000000, 55.0000000000 308.6250000000, 53.0000000000 308.7500000000, 52.0000000000 308.8750000000, 50.0000000000 309.0000000000, 49.0000000000 309.1250000000, 50.0000000000 309.2500000000, 52.0000000000 309.6250000000, 50.0000000000 309.7500000000, 49.0000000000 309.8750000000, 47.0000000000 310.0000000000, 45.0000000000 310.7500000000, 47.0000000000 310.8750000000, 49.0000000000 311.0000000000, 49.0000000000 311.7500000000, 47.0000000000 311.8750000000, 49.0000000000 312.0000000000, 50.0000000000 occurrence7 312.0000000000, 50.0000000000 312.1250000000, 52.0000000000 312.2500000000, 53.0000000000 312.6250000000, 52.0000000000 312.7500000000, 50.0000000000 312.8750000000, 48.0000000000 313.0000000000, 47.0000000000 313.1250000000, 48.0000000000 313.2500000000, 50.0000000000 313.6250000000, 48.0000000000 313.7500000000, 47.0000000000 313.8750000000, 45.0000000000 314.0000000000, 43.0000000000 314.7500000000, 45.0000000000 314.8750000000, 47.0000000000 315.0000000000, 47.0000000000 315.7500000000, 45.0000000000 315.8750000000, 47.0000000000 316.0000000000, 48.0000000000 pattern3 occurrence1 248.5000000000, 53.0000000000 249.0000000000, 47.0000000000 249.5000000000, 50.0000000000 250.0000000000, 44.0000000000 250.5000000000, 47.0000000000 251.0000000000, 52.0000000000 252.0000000000, 45.0000000000 occurrence2 276.5000000000, 60.0000000000 277.0000000000, 54.0000000000 277.5000000000, 57.0000000000 278.0000000000, 51.0000000000 278.5000000000, 54.0000000000 279.0000000000, 59.0000000000 280.0000000000, 52.0000000000 occurrence3 150.5000000000, 69.0000000000 151.0000000000, 62.0000000000 151.5000000000, 65.0000000000 152.0000000000, 59.0000000000 152.5000000000, 62.0000000000 153.0000000000, 65.0000000000 occurrence4 68.5000000000, 77.0000000000 69.0000000000, 71.0000000000 69.5000000000, 74.0000000000 70.0000000000, 68.0000000000 71.0000000000, 71.0000000000 occurrence5 196.5000000000, 70.0000000000 197.0000000000, 64.0000000000 197.5000000000, 67.0000000000 198.0000000000, 61.0000000000 198.5000000000, 76.0000000000 199.0000000000, 69.0000000000 occurrence6 200.5000000000, 69.0000000000 201.0000000000, 62.0000000000 201.5000000000, 65.0000000000 202.0000000000, 59.0000000000 202.5000000000, 74.0000000000 203.0000000000, 67.0000000000 mir_eval-0.8.2/tests/data/pattern/ref01.txt000066400000000000000000000212671475740344600205530ustar00rootroot00000000000000pattern1 occurrence1 1.0000000000, 64.0000000000 2.0000000000, 60.0000000000 3.0000000000, 65.0000000000 4.0000000000, 56.0000000000 6.5000000000, 62.0000000000 7.0000000000, 59.0000000000 7.5000000000, 64.0000000000 8.0000000000, 60.0000000000 occurrence2 21.0000000000, 76.0000000000 22.0000000000, 72.0000000000 23.0000000000, 77.0000000000 24.0000000000, 68.0000000000 26.5000000000, 74.0000000000 27.0000000000, 71.0000000000 27.5000000000, 76.0000000000 28.0000000000, 72.0000000000 occurrence3 35.0000000000, 55.0000000000 36.0000000000, 52.0000000000 37.0000000000, 57.0000000000 38.0000000000, 47.0000000000 40.5000000000, 53.0000000000 41.0000000000, 50.0000000000 41.5000000000, 55.0000000000 42.0000000000, 52.0000000000 occurrence4 81.0000000000, 81.0000000000 82.0000000000, 77.0000000000 83.0000000000, 82.0000000000 84.0000000000, 73.0000000000 86.5000000000, 79.0000000000 87.0000000000, 76.0000000000 87.5000000000, 81.0000000000 88.0000000000, 77.0000000000 occurrence5 99.0000000000, 52.0000000000 100.0000000000, 48.0000000000 101.0000000000, 53.0000000000 102.0000000000, 44.0000000000 104.5000000000, 50.0000000000 105.0000000000, 47.0000000000 105.5000000000, 52.0000000000 106.0000000000, 48.0000000000 occurrence6 9.0000000000, 69.0000000000 10.0000000000, 67.0000000000 11.0000000000, 72.0000000000 12.0000000000, 63.0000000000 14.5000000000, 69.0000000000 15.0000000000, 66.0000000000 15.5000000000, 71.0000000000 16.0000000000, 67.0000000000 occurrence7 49.0000000000, 81.0000000000 50.0000000000, 79.0000000000 51.0000000000, 84.0000000000 52.0000000000, 75.0000000000 54.5000000000, 81.0000000000 55.0000000000, 78.0000000000 55.5000000000, 83.0000000000 56.0000000000, 79.0000000000 occurrence8 66.0000000000, 60.0000000000 67.0000000000, 65.0000000000 68.0000000000, 56.0000000000 70.5000000000, 62.0000000000 71.0000000000, 59.0000000000 71.5000000000, 64.0000000000 72.0000000000, 60.0000000000 pattern2 occurrence1 10.5000000000, 64.0000000000 10.6250000000, 62.0000000000 10.7500000000, 60.0000000000 10.8750000000, 59.0000000000 11.0000000000, 57.0000000000 11.5000000000, 60.0000000000 11.6250000000, 59.0000000000 11.7500000000, 57.0000000000 11.8750000000, 55.0000000000 12.0000000000, 54.0000000000 12.1250000000, 55.0000000000 12.2500000000, 57.0000000000 12.6250000000, 55.0000000000 12.7500000000, 54.0000000000 12.8750000000, 52.0000000000 13.0000000000, 51.0000000000 13.1250000000, 52.0000000000 13.2500000000, 54.0000000000 13.6250000000, 52.0000000000 13.7500000000, 51.0000000000 13.8750000000, 49.0000000000 14.0000000000, 47.0000000000 14.7500000000, 49.0000000000 14.8750000000, 51.0000000000 15.0000000000, 51.0000000000 15.7500000000, 49.0000000000 15.8750000000, 51.0000000000 16.0000000000, 52.0000000000 occurrence2 22.5000000000, 69.0000000000 22.6250000000, 67.0000000000 22.7500000000, 65.0000000000 22.8750000000, 64.0000000000 23.0000000000, 62.0000000000 23.5000000000, 65.0000000000 23.6250000000, 64.0000000000 23.7500000000, 62.0000000000 23.8750000000, 60.0000000000 24.0000000000, 59.0000000000 24.1250000000, 60.0000000000 24.2500000000, 62.0000000000 24.6250000000, 60.0000000000 24.7500000000, 59.0000000000 24.8750000000, 57.0000000000 25.0000000000, 56.0000000000 25.1250000000, 57.0000000000 25.2500000000, 59.0000000000 25.6250000000, 57.0000000000 25.7500000000, 56.0000000000 25.8750000000, 54.0000000000 26.0000000000, 52.0000000000 26.7500000000, 54.0000000000 26.8750000000, 56.0000000000 27.0000000000, 56.0000000000 27.7500000000, 54.0000000000 27.8750000000, 56.0000000000 28.0000000000, 57.0000000000 occurrence3 36.5000000000, 84.0000000000 36.6250000000, 83.0000000000 36.7500000000, 81.0000000000 36.8750000000, 79.0000000000 37.0000000000, 77.0000000000 37.5000000000, 81.0000000000 37.6250000000, 79.0000000000 37.7500000000, 77.0000000000 37.8750000000, 76.0000000000 38.0000000000, 74.0000000000 38.1250000000, 76.0000000000 38.2500000000, 77.0000000000 38.6250000000, 76.0000000000 38.7500000000, 74.0000000000 38.8750000000, 72.0000000000 39.0000000000, 71.0000000000 39.1250000000, 72.0000000000 39.2500000000, 74.0000000000 39.6250000000, 72.0000000000 39.7500000000, 71.0000000000 39.8750000000, 69.0000000000 40.0000000000, 67.0000000000 40.7500000000, 69.0000000000 40.8750000000, 71.0000000000 41.0000000000, 71.0000000000 41.7500000000, 69.0000000000 41.8750000000, 71.0000000000 42.0000000000, 72.0000000000 occurrence4 50.5000000000, 76.0000000000 50.6250000000, 74.0000000000 50.7500000000, 72.0000000000 50.8750000000, 71.0000000000 51.0000000000, 69.0000000000 51.5000000000, 72.0000000000 51.6250000000, 71.0000000000 51.7500000000, 69.0000000000 51.8750000000, 67.0000000000 52.0000000000, 66.0000000000 52.1250000000, 67.0000000000 52.2500000000, 69.0000000000 52.6250000000, 67.0000000000 52.7500000000, 66.0000000000 52.8750000000, 64.0000000000 53.0000000000, 63.0000000000 53.1250000000, 64.0000000000 53.2500000000, 66.0000000000 53.6250000000, 64.0000000000 53.7500000000, 63.0000000000 53.8750000000, 61.0000000000 54.0000000000, 59.0000000000 54.7500000000, 61.0000000000 54.8750000000, 63.0000000000 55.0000000000, 63.0000000000 55.7500000000, 61.0000000000 55.8750000000, 63.0000000000 56.0000000000, 64.0000000000 occurrence5 66.5000000000, 57.0000000000 66.6250000000, 55.0000000000 66.7500000000, 53.0000000000 66.8750000000, 52.0000000000 67.0000000000, 50.0000000000 67.5000000000, 53.0000000000 67.6250000000, 52.0000000000 67.7500000000, 50.0000000000 67.8750000000, 48.0000000000 68.0000000000, 47.0000000000 68.1250000000, 48.0000000000 68.2500000000, 50.0000000000 68.6250000000, 48.0000000000 68.7500000000, 47.0000000000 68.8750000000, 45.0000000000 69.0000000000, 44.0000000000 69.1250000000, 45.0000000000 69.2500000000, 47.0000000000 69.6250000000, 45.0000000000 69.7500000000, 44.0000000000 69.8750000000, 42.0000000000 70.0000000000, 40.0000000000 70.7500000000, 42.0000000000 70.8750000000, 44.0000000000 71.0000000000, 44.0000000000 71.7500000000, 42.0000000000 71.8750000000, 44.0000000000 72.0000000000, 45.0000000000 occurrence6 82.5000000000, 62.0000000000 82.6250000000, 60.0000000000 82.7500000000, 58.0000000000 82.8750000000, 57.0000000000 83.0000000000, 55.0000000000 83.5000000000, 58.0000000000 83.6250000000, 57.0000000000 83.7500000000, 55.0000000000 83.8750000000, 53.0000000000 84.0000000000, 52.0000000000 84.1250000000, 53.0000000000 84.2500000000, 55.0000000000 84.6250000000, 53.0000000000 84.7500000000, 52.0000000000 84.8750000000, 50.0000000000 85.0000000000, 49.0000000000 85.1250000000, 50.0000000000 85.2500000000, 52.0000000000 85.6250000000, 50.0000000000 85.7500000000, 49.0000000000 85.8750000000, 47.0000000000 86.0000000000, 45.0000000000 86.7500000000, 47.0000000000 86.8750000000, 49.0000000000 87.0000000000, 49.0000000000 87.7500000000, 47.0000000000 87.8750000000, 49.0000000000 88.0000000000, 50.0000000000 occurrence7 88.0000000000, 50.0000000000 88.1250000000, 52.0000000000 88.2500000000, 53.0000000000 88.6250000000, 52.0000000000 88.7500000000, 50.0000000000 88.8750000000, 48.0000000000 89.0000000000, 47.0000000000 89.1250000000, 48.0000000000 89.2500000000, 50.0000000000 89.6250000000, 48.0000000000 89.7500000000, 47.0000000000 89.8750000000, 45.0000000000 90.0000000000, 43.0000000000 90.7500000000, 45.0000000000 90.8750000000, 47.0000000000 91.0000000000, 47.0000000000 91.7500000000, 45.0000000000 91.8750000000, 47.0000000000 92.0000000000, 48.0000000000 pattern3 occurrence1 24.5000000000, 53.0000000000 25.0000000000, 47.0000000000 25.5000000000, 50.0000000000 26.0000000000, 44.0000000000 26.5000000000, 47.0000000000 27.0000000000, 52.0000000000 28.0000000000, 45.0000000000 occurrence2 52.5000000000, 60.0000000000 53.0000000000, 54.0000000000 53.5000000000, 57.0000000000 54.0000000000, 51.0000000000 54.5000000000, 54.0000000000 55.0000000000, 59.0000000000 56.0000000000, 52.0000000000 occurrence3 38.5000000000, 69.0000000000 39.0000000000, 62.0000000000 39.5000000000, 65.0000000000 40.0000000000, 59.0000000000 40.5000000000, 62.0000000000 41.0000000000, 65.0000000000 occurrence4 68.5000000000, 77.0000000000 69.0000000000, 71.0000000000 69.5000000000, 74.0000000000 70.0000000000, 68.0000000000 71.0000000000, 71.0000000000 occurrence5 84.5000000000, 70.0000000000 85.0000000000, 64.0000000000 85.5000000000, 67.0000000000 86.0000000000, 61.0000000000 86.5000000000, 76.0000000000 87.0000000000, 69.0000000000 occurrence6 88.5000000000, 69.0000000000 89.0000000000, 62.0000000000 89.5000000000, 65.0000000000 90.0000000000, 59.0000000000 90.5000000000, 74.0000000000 91.0000000000, 67.0000000000 mir_eval-0.8.2/tests/data/pattern/ref02.txt000066400000000000000000002270411475740344600205520ustar00rootroot00000000000000pattern1 occurrence1 -1.0000000000, 60.0000000000 -1.0000000000, 68.0000000000 0.0000000000, 61.0000000000 0.0000000000, 70.0000000000 1.0000000000, 58.0000000000 1.0000000000, 67.0000000000 2.0000000000, 53.0000000000 3.0000000000, 60.0000000000 3.0000000000, 68.0000000000 4.0000000000, 56.0000000000 4.0000000000, 65.0000000000 5.0000000000, 53.0000000000 5.0000000000, 56.0000000000 5.0000000000, 60.0000000000 5.0000000000, 65.0000000000 6.0000000000, 55.0000000000 6.0000000000, 58.0000000000 6.0000000000, 60.0000000000 6.0000000000, 64.0000000000 7.0000000000, 53.0000000000 7.0000000000, 56.0000000000 7.0000000000, 60.0000000000 7.0000000000, 65.0000000000 8.0000000000, 52.0000000000 8.0000000000, 55.0000000000 8.0000000000, 60.0000000000 8.0000000000, 67.0000000000 9.0000000000, 53.0000000000 9.0000000000, 56.0000000000 9.0000000000, 60.0000000000 9.0000000000, 70.0000000000 10.0000000000, 68.0000000000 occurrence2 11.0000000000, 63.0000000000 11.0000000000, 72.0000000000 12.0000000000, 65.0000000000 12.0000000000, 73.0000000000 13.0000000000, 61.0000000000 13.0000000000, 70.0000000000 14.0000000000, 56.0000000000 15.0000000000, 63.0000000000 15.0000000000, 72.0000000000 16.0000000000, 60.0000000000 16.0000000000, 68.0000000000 17.0000000000, 56.0000000000 17.0000000000, 60.0000000000 17.0000000000, 63.0000000000 17.0000000000, 68.0000000000 18.0000000000, 58.0000000000 18.0000000000, 61.0000000000 18.0000000000, 63.0000000000 18.0000000000, 67.0000000000 19.0000000000, 56.0000000000 19.0000000000, 60.0000000000 19.0000000000, 63.0000000000 19.0000000000, 68.0000000000 20.0000000000, 55.0000000000 20.0000000000, 58.0000000000 20.0000000000, 63.0000000000 20.0000000000, 70.0000000000 21.0000000000, 56.0000000000 21.0000000000, 60.0000000000 21.0000000000, 63.0000000000 21.0000000000, 73.0000000000 22.0000000000, 72.0000000000 occurrence3 41.0000000000, 60.0000000000 41.0000000000, 68.0000000000 42.0000000000, 61.0000000000 42.0000000000, 70.0000000000 43.0000000000, 58.0000000000 43.0000000000, 67.0000000000 44.0000000000, 53.0000000000 45.0000000000, 60.0000000000 45.0000000000, 68.0000000000 46.0000000000, 56.0000000000 46.0000000000, 65.0000000000 47.0000000000, 53.0000000000 47.0000000000, 56.0000000000 47.0000000000, 60.0000000000 47.0000000000, 65.0000000000 48.0000000000, 55.0000000000 48.0000000000, 58.0000000000 48.0000000000, 60.0000000000 48.0000000000, 64.0000000000 49.0000000000, 53.0000000000 49.0000000000, 56.0000000000 49.0000000000, 60.0000000000 49.0000000000, 65.0000000000 50.0000000000, 52.0000000000 50.0000000000, 55.0000000000 50.0000000000, 60.0000000000 50.0000000000, 67.0000000000 51.0000000000, 53.0000000000 51.0000000000, 56.0000000000 51.0000000000, 60.0000000000 51.0000000000, 70.0000000000 52.0000000000, 68.0000000000 occurrence4 53.0000000000, 63.0000000000 53.0000000000, 72.0000000000 54.0000000000, 65.0000000000 54.0000000000, 73.0000000000 55.0000000000, 61.0000000000 55.0000000000, 70.0000000000 56.0000000000, 56.0000000000 57.0000000000, 63.0000000000 57.0000000000, 72.0000000000 58.0000000000, 60.0000000000 58.0000000000, 68.0000000000 59.0000000000, 56.0000000000 59.0000000000, 60.0000000000 59.0000000000, 63.0000000000 59.0000000000, 68.0000000000 60.0000000000, 58.0000000000 60.0000000000, 61.0000000000 60.0000000000, 63.0000000000 60.0000000000, 67.0000000000 61.0000000000, 56.0000000000 61.0000000000, 60.0000000000 61.0000000000, 63.0000000000 61.0000000000, 68.0000000000 62.0000000000, 55.0000000000 62.0000000000, 58.0000000000 62.0000000000, 63.0000000000 62.0000000000, 70.0000000000 63.0000000000, 56.0000000000 63.0000000000, 60.0000000000 63.0000000000, 63.0000000000 63.0000000000, 73.0000000000 64.0000000000, 72.0000000000 occurrence5 437.0000000000, 60.0000000000 437.0000000000, 68.0000000000 438.0000000000, 61.0000000000 438.0000000000, 70.0000000000 439.0000000000, 58.0000000000 439.0000000000, 67.0000000000 440.0000000000, 53.0000000000 441.0000000000, 60.0000000000 441.0000000000, 68.0000000000 442.0000000000, 56.0000000000 442.0000000000, 65.0000000000 443.0000000000, 53.0000000000 443.0000000000, 56.0000000000 443.0000000000, 60.0000000000 443.0000000000, 65.0000000000 444.0000000000, 55.0000000000 444.0000000000, 58.0000000000 444.0000000000, 60.0000000000 444.0000000000, 64.0000000000 445.0000000000, 53.0000000000 445.0000000000, 56.0000000000 445.0000000000, 60.0000000000 445.0000000000, 65.0000000000 446.0000000000, 52.0000000000 446.0000000000, 55.0000000000 446.0000000000, 60.0000000000 446.0000000000, 67.0000000000 447.0000000000, 53.0000000000 447.0000000000, 56.0000000000 447.0000000000, 60.0000000000 447.0000000000, 70.0000000000 448.0000000000, 68.0000000000 occurrence6 449.0000000000, 63.0000000000 449.0000000000, 72.0000000000 450.0000000000, 65.0000000000 450.0000000000, 73.0000000000 451.0000000000, 61.0000000000 451.0000000000, 70.0000000000 452.0000000000, 56.0000000000 453.0000000000, 63.0000000000 453.0000000000, 72.0000000000 454.0000000000, 60.0000000000 454.0000000000, 68.0000000000 455.0000000000, 56.0000000000 455.0000000000, 60.0000000000 455.0000000000, 63.0000000000 455.0000000000, 68.0000000000 456.0000000000, 58.0000000000 456.0000000000, 61.0000000000 456.0000000000, 63.0000000000 456.0000000000, 67.0000000000 457.0000000000, 56.0000000000 457.0000000000, 60.0000000000 457.0000000000, 63.0000000000 457.0000000000, 68.0000000000 458.0000000000, 55.0000000000 458.0000000000, 58.0000000000 458.0000000000, 63.0000000000 458.0000000000, 70.0000000000 459.0000000000, 56.0000000000 459.0000000000, 60.0000000000 459.0000000000, 63.0000000000 459.0000000000, 73.0000000000 460.0000000000, 72.0000000000 pattern2 occurrence1 239.0000000000, 60.0000000000 240.0000000000, 53.0000000000 240.0000000000, 69.0000000000 240.5000000000, 67.0000000000 241.0000000000, 57.0000000000 241.0000000000, 69.0000000000 241.5000000000, 65.0000000000 242.0000000000, 60.0000000000 242.0000000000, 67.0000000000 242.5000000000, 69.0000000000 243.0000000000, 62.0000000000 243.0000000000, 70.0000000000 243.5000000000, 69.0000000000 244.0000000000, 55.0000000000 244.0000000000, 70.0000000000 244.5000000000, 67.0000000000 245.0000000000, 53.0000000000 245.0000000000, 69.0000000000 245.5000000000, 71.0000000000 246.0000000000, 52.0000000000 246.0000000000, 72.0000000000 246.5000000000, 71.0000000000 247.0000000000, 55.0000000000 247.0000000000, 72.0000000000 247.5000000000, 74.0000000000 248.0000000000, 60.0000000000 248.0000000000, 72.0000000000 248.5000000000, 70.0000000000 249.0000000000, 53.0000000000 249.0000000000, 69.0000000000 249.5000000000, 67.0000000000 250.0000000000, 57.0000000000 250.0000000000, 69.0000000000 250.5000000000, 70.0000000000 251.0000000000, 60.0000000000 251.0000000000, 69.0000000000 251.5000000000, 65.0000000000 occurrence2 269.0000000000, 60.0000000000 270.0000000000, 53.0000000000 270.0000000000, 69.0000000000 270.5000000000, 67.0000000000 271.0000000000, 57.0000000000 271.0000000000, 69.0000000000 271.5000000000, 65.0000000000 272.0000000000, 60.0000000000 272.0000000000, 67.0000000000 272.5000000000, 69.0000000000 273.0000000000, 62.0000000000 273.0000000000, 70.0000000000 273.5000000000, 69.0000000000 274.0000000000, 55.0000000000 274.0000000000, 70.0000000000 274.5000000000, 67.0000000000 275.0000000000, 53.0000000000 275.0000000000, 69.0000000000 275.5000000000, 71.0000000000 276.0000000000, 52.0000000000 276.0000000000, 72.0000000000 276.5000000000, 71.0000000000 277.0000000000, 55.0000000000 277.0000000000, 72.0000000000 277.5000000000, 74.0000000000 278.0000000000, 60.0000000000 278.0000000000, 72.0000000000 278.5000000000, 70.0000000000 279.0000000000, 53.0000000000 279.0000000000, 69.0000000000 279.5000000000, 67.0000000000 280.0000000000, 57.0000000000 280.0000000000, 69.0000000000 280.5000000000, 70.0000000000 281.0000000000, 60.0000000000 281.0000000000, 69.0000000000 281.5000000000, 65.0000000000 occurrence3 345.0000000000, 53.0000000000 345.0000000000, 69.0000000000 345.5000000000, 67.0000000000 346.0000000000, 57.0000000000 346.0000000000, 69.0000000000 346.5000000000, 65.0000000000 347.0000000000, 60.0000000000 347.0000000000, 67.0000000000 347.5000000000, 69.0000000000 348.0000000000, 62.0000000000 348.0000000000, 70.0000000000 348.5000000000, 69.0000000000 349.0000000000, 55.0000000000 349.0000000000, 70.0000000000 349.5000000000, 67.0000000000 350.0000000000, 53.0000000000 350.0000000000, 69.0000000000 350.5000000000, 71.0000000000 351.0000000000, 52.0000000000 351.0000000000, 72.0000000000 351.5000000000, 71.0000000000 352.0000000000, 55.0000000000 352.0000000000, 72.0000000000 352.5000000000, 74.0000000000 353.0000000000, 60.0000000000 353.0000000000, 72.0000000000 353.5000000000, 70.0000000000 354.0000000000, 53.0000000000 354.0000000000, 69.0000000000 354.5000000000, 67.0000000000 355.0000000000, 57.0000000000 355.0000000000, 69.0000000000 355.5000000000, 70.0000000000 356.0000000000, 60.0000000000 356.0000000000, 69.0000000000 356.5000000000, 65.0000000000 occurrence4 414.0000000000, 53.0000000000 414.0000000000, 69.0000000000 414.5000000000, 67.0000000000 415.0000000000, 57.0000000000 415.0000000000, 69.0000000000 415.5000000000, 65.0000000000 416.0000000000, 60.0000000000 416.0000000000, 67.0000000000 416.5000000000, 69.0000000000 417.0000000000, 62.0000000000 417.0000000000, 70.0000000000 417.5000000000, 69.0000000000 418.0000000000, 55.0000000000 418.0000000000, 70.0000000000 418.5000000000, 67.0000000000 419.0000000000, 53.0000000000 419.0000000000, 69.0000000000 419.5000000000, 71.0000000000 420.0000000000, 52.0000000000 420.0000000000, 72.0000000000 420.5000000000, 71.0000000000 421.0000000000, 55.0000000000 421.0000000000, 72.0000000000 421.5000000000, 74.0000000000 422.0000000000, 60.0000000000 422.0000000000, 72.0000000000 422.5000000000, 70.0000000000 423.0000000000, 53.0000000000 423.0000000000, 69.0000000000 423.5000000000, 67.0000000000 424.0000000000, 57.0000000000 424.0000000000, 69.0000000000 424.5000000000, 70.0000000000 425.0000000000, 60.0000000000 425.0000000000, 69.0000000000 425.5000000000, 65.0000000000 pattern3 occurrence1 -1.0000000000, 60.0000000000 -1.0000000000, 68.0000000000 0.0000000000, 61.0000000000 0.0000000000, 70.0000000000 1.0000000000, 58.0000000000 1.0000000000, 67.0000000000 2.0000000000, 53.0000000000 3.0000000000, 60.0000000000 3.0000000000, 68.0000000000 4.0000000000, 56.0000000000 4.0000000000, 65.0000000000 5.0000000000, 53.0000000000 5.0000000000, 56.0000000000 5.0000000000, 60.0000000000 5.0000000000, 65.0000000000 6.0000000000, 55.0000000000 6.0000000000, 58.0000000000 6.0000000000, 60.0000000000 6.0000000000, 64.0000000000 7.0000000000, 53.0000000000 7.0000000000, 56.0000000000 7.0000000000, 60.0000000000 7.0000000000, 65.0000000000 8.0000000000, 52.0000000000 8.0000000000, 55.0000000000 8.0000000000, 60.0000000000 8.0000000000, 67.0000000000 9.0000000000, 53.0000000000 9.0000000000, 56.0000000000 9.0000000000, 60.0000000000 9.0000000000, 70.0000000000 10.0000000000, 68.0000000000 11.0000000000, 63.0000000000 11.0000000000, 72.0000000000 12.0000000000, 65.0000000000 12.0000000000, 73.0000000000 13.0000000000, 61.0000000000 13.0000000000, 70.0000000000 14.0000000000, 44.0000000000 14.0000000000, 56.0000000000 15.0000000000, 63.0000000000 15.0000000000, 72.0000000000 16.0000000000, 60.0000000000 16.0000000000, 68.0000000000 17.0000000000, 56.0000000000 17.0000000000, 60.0000000000 17.0000000000, 63.0000000000 17.0000000000, 68.0000000000 18.0000000000, 58.0000000000 18.0000000000, 61.0000000000 18.0000000000, 63.0000000000 18.0000000000, 67.0000000000 19.0000000000, 56.0000000000 19.0000000000, 60.0000000000 19.0000000000, 63.0000000000 19.0000000000, 68.0000000000 20.0000000000, 55.0000000000 20.0000000000, 58.0000000000 20.0000000000, 63.0000000000 20.0000000000, 70.0000000000 21.0000000000, 56.0000000000 21.0000000000, 60.0000000000 21.0000000000, 63.0000000000 21.0000000000, 73.0000000000 22.0000000000, 72.0000000000 23.0000000000, 60.0000000000 23.0000000000, 63.0000000000 23.0000000000, 68.0000000000 23.0000000000, 75.0000000000 24.0000000000, 58.0000000000 24.0000000000, 61.0000000000 24.0000000000, 67.0000000000 24.0000000000, 75.0000000000 25.0000000000, 56.0000000000 25.0000000000, 60.0000000000 25.0000000000, 68.0000000000 25.0000000000, 75.0000000000 26.0000000000, 55.0000000000 26.0000000000, 58.0000000000 26.0000000000, 70.0000000000 26.0000000000, 75.0000000000 27.0000000000, 56.0000000000 27.0000000000, 73.0000000000 27.0000000000, 75.0000000000 28.0000000000, 72.0000000000 29.0000000000, 49.0000000000 29.0000000000, 58.0000000000 29.0000000000, 77.0000000000 30.0000000000, 51.0000000000 30.0000000000, 60.0000000000 30.0000000000, 68.0000000000 32.0000000000, 51.0000000000 32.0000000000, 61.0000000000 32.0000000000, 67.0000000000 32.0000000000, 70.0000000000 33.0000000000, 56.0000000000 33.0000000000, 60.0000000000 33.0000000000, 68.0000000000 35.0000000000, 79.0000000000 35.5000000000, 77.0000000000 36.0000000000, 51.0000000000 36.0000000000, 60.0000000000 36.0000000000, 68.0000000000 38.0000000000, 51.0000000000 38.0000000000, 61.0000000000 38.0000000000, 67.0000000000 38.0000000000, 70.0000000000 39.0000000000, 56.0000000000 39.0000000000, 60.0000000000 39.0000000000, 68.0000000000 occurrence2 41.0000000000, 60.0000000000 41.0000000000, 68.0000000000 42.0000000000, 61.0000000000 42.0000000000, 70.0000000000 43.0000000000, 58.0000000000 43.0000000000, 67.0000000000 44.0000000000, 53.0000000000 45.0000000000, 60.0000000000 45.0000000000, 68.0000000000 46.0000000000, 56.0000000000 46.0000000000, 65.0000000000 47.0000000000, 53.0000000000 47.0000000000, 56.0000000000 47.0000000000, 60.0000000000 47.0000000000, 65.0000000000 48.0000000000, 55.0000000000 48.0000000000, 58.0000000000 48.0000000000, 60.0000000000 48.0000000000, 64.0000000000 49.0000000000, 53.0000000000 49.0000000000, 56.0000000000 49.0000000000, 60.0000000000 49.0000000000, 65.0000000000 50.0000000000, 52.0000000000 50.0000000000, 55.0000000000 50.0000000000, 60.0000000000 50.0000000000, 67.0000000000 51.0000000000, 53.0000000000 51.0000000000, 56.0000000000 51.0000000000, 60.0000000000 51.0000000000, 70.0000000000 52.0000000000, 68.0000000000 53.0000000000, 63.0000000000 53.0000000000, 72.0000000000 54.0000000000, 65.0000000000 54.0000000000, 73.0000000000 55.0000000000, 61.0000000000 55.0000000000, 70.0000000000 56.0000000000, 44.0000000000 56.0000000000, 56.0000000000 57.0000000000, 63.0000000000 57.0000000000, 72.0000000000 58.0000000000, 60.0000000000 58.0000000000, 68.0000000000 59.0000000000, 56.0000000000 59.0000000000, 60.0000000000 59.0000000000, 63.0000000000 59.0000000000, 68.0000000000 60.0000000000, 58.0000000000 60.0000000000, 61.0000000000 60.0000000000, 63.0000000000 60.0000000000, 67.0000000000 61.0000000000, 56.0000000000 61.0000000000, 60.0000000000 61.0000000000, 63.0000000000 61.0000000000, 68.0000000000 62.0000000000, 55.0000000000 62.0000000000, 58.0000000000 62.0000000000, 63.0000000000 62.0000000000, 70.0000000000 63.0000000000, 56.0000000000 63.0000000000, 60.0000000000 63.0000000000, 63.0000000000 63.0000000000, 73.0000000000 64.0000000000, 72.0000000000 65.0000000000, 60.0000000000 65.0000000000, 63.0000000000 65.0000000000, 68.0000000000 65.0000000000, 75.0000000000 66.0000000000, 58.0000000000 66.0000000000, 61.0000000000 66.0000000000, 67.0000000000 66.0000000000, 75.0000000000 67.0000000000, 56.0000000000 67.0000000000, 60.0000000000 67.0000000000, 68.0000000000 67.0000000000, 75.0000000000 68.0000000000, 55.0000000000 68.0000000000, 58.0000000000 68.0000000000, 70.0000000000 68.0000000000, 75.0000000000 69.0000000000, 56.0000000000 69.0000000000, 73.0000000000 69.0000000000, 75.0000000000 70.0000000000, 72.0000000000 71.0000000000, 49.0000000000 71.0000000000, 58.0000000000 71.0000000000, 77.0000000000 72.0000000000, 51.0000000000 72.0000000000, 60.0000000000 72.0000000000, 68.0000000000 74.0000000000, 51.0000000000 74.0000000000, 61.0000000000 74.0000000000, 67.0000000000 74.0000000000, 70.0000000000 75.0000000000, 56.0000000000 75.0000000000, 60.0000000000 75.0000000000, 68.0000000000 77.0000000000, 79.0000000000 77.5000000000, 77.0000000000 78.0000000000, 51.0000000000 78.0000000000, 60.0000000000 78.0000000000, 68.0000000000 80.0000000000, 51.0000000000 80.0000000000, 61.0000000000 80.0000000000, 67.0000000000 80.0000000000, 70.0000000000 81.0000000000, 56.0000000000 81.0000000000, 60.0000000000 81.0000000000, 68.0000000000 occurrence3 437.0000000000, 60.0000000000 437.0000000000, 68.0000000000 438.0000000000, 61.0000000000 438.0000000000, 70.0000000000 439.0000000000, 58.0000000000 439.0000000000, 67.0000000000 440.0000000000, 53.0000000000 441.0000000000, 60.0000000000 441.0000000000, 68.0000000000 442.0000000000, 56.0000000000 442.0000000000, 65.0000000000 443.0000000000, 53.0000000000 443.0000000000, 56.0000000000 443.0000000000, 60.0000000000 443.0000000000, 65.0000000000 444.0000000000, 55.0000000000 444.0000000000, 58.0000000000 444.0000000000, 60.0000000000 444.0000000000, 64.0000000000 445.0000000000, 53.0000000000 445.0000000000, 56.0000000000 445.0000000000, 60.0000000000 445.0000000000, 65.0000000000 446.0000000000, 52.0000000000 446.0000000000, 55.0000000000 446.0000000000, 60.0000000000 446.0000000000, 67.0000000000 447.0000000000, 53.0000000000 447.0000000000, 56.0000000000 447.0000000000, 60.0000000000 447.0000000000, 70.0000000000 448.0000000000, 68.0000000000 449.0000000000, 63.0000000000 449.0000000000, 72.0000000000 450.0000000000, 65.0000000000 450.0000000000, 73.0000000000 451.0000000000, 61.0000000000 451.0000000000, 70.0000000000 452.0000000000, 44.0000000000 452.0000000000, 56.0000000000 453.0000000000, 63.0000000000 453.0000000000, 72.0000000000 454.0000000000, 60.0000000000 454.0000000000, 68.0000000000 455.0000000000, 56.0000000000 455.0000000000, 60.0000000000 455.0000000000, 63.0000000000 455.0000000000, 68.0000000000 456.0000000000, 58.0000000000 456.0000000000, 61.0000000000 456.0000000000, 63.0000000000 456.0000000000, 67.0000000000 457.0000000000, 56.0000000000 457.0000000000, 60.0000000000 457.0000000000, 63.0000000000 457.0000000000, 68.0000000000 458.0000000000, 55.0000000000 458.0000000000, 58.0000000000 458.0000000000, 63.0000000000 458.0000000000, 70.0000000000 459.0000000000, 56.0000000000 459.0000000000, 60.0000000000 459.0000000000, 63.0000000000 459.0000000000, 73.0000000000 460.0000000000, 72.0000000000 461.0000000000, 60.0000000000 461.0000000000, 63.0000000000 461.0000000000, 68.0000000000 461.0000000000, 75.0000000000 462.0000000000, 58.0000000000 462.0000000000, 61.0000000000 462.0000000000, 67.0000000000 462.0000000000, 75.0000000000 463.0000000000, 56.0000000000 463.0000000000, 60.0000000000 463.0000000000, 68.0000000000 463.0000000000, 75.0000000000 464.0000000000, 55.0000000000 464.0000000000, 58.0000000000 464.0000000000, 70.0000000000 464.0000000000, 75.0000000000 465.0000000000, 56.0000000000 465.0000000000, 73.0000000000 465.0000000000, 75.0000000000 466.0000000000, 72.0000000000 467.0000000000, 49.0000000000 467.0000000000, 58.0000000000 467.0000000000, 77.0000000000 468.0000000000, 51.0000000000 468.0000000000, 60.0000000000 468.0000000000, 68.0000000000 470.0000000000, 51.0000000000 470.0000000000, 61.0000000000 470.0000000000, 67.0000000000 470.0000000000, 70.0000000000 471.0000000000, 56.0000000000 471.0000000000, 60.0000000000 471.0000000000, 68.0000000000 473.0000000000, 79.0000000000 473.5000000000, 77.0000000000 474.0000000000, 51.0000000000 474.0000000000, 60.0000000000 474.0000000000, 68.0000000000 476.0000000000, 51.0000000000 476.0000000000, 61.0000000000 476.0000000000, 67.0000000000 476.0000000000, 70.0000000000 477.0000000000, 56.0000000000 477.0000000000, 60.0000000000 477.0000000000, 68.0000000000 pattern4 occurrence1 83.0000000000, 72.0000000000 83.0000000000, 75.0000000000 84.0000000000, 73.0000000000 84.0000000000, 76.0000000000 85.0000000000, 55.0000000000 85.0000000000, 58.0000000000 85.0000000000, 70.0000000000 85.0000000000, 73.0000000000 86.0000000000, 58.0000000000 86.0000000000, 61.0000000000 87.0000000000, 72.0000000000 87.0000000000, 75.0000000000 88.0000000000, 56.0000000000 88.0000000000, 60.0000000000 88.0000000000, 68.0000000000 88.0000000000, 72.0000000000 89.0000000000, 60.0000000000 89.0000000000, 63.0000000000 90.0000000000, 75.0000000000 90.0000000000, 78.0000000000 91.0000000000, 57.0000000000 91.0000000000, 60.0000000000 91.0000000000, 72.0000000000 91.0000000000, 75.0000000000 92.0000000000, 60.0000000000 92.0000000000, 63.0000000000 93.0000000000, 73.0000000000 93.0000000000, 77.0000000000 94.0000000000, 58.0000000000 94.0000000000, 61.0000000000 94.0000000000, 70.0000000000 94.0000000000, 73.0000000000 95.0000000000, 61.0000000000 95.0000000000, 65.0000000000 96.0000000000, 53.0000000000 96.0000000000, 61.0000000000 96.0000000000, 65.0000000000 96.0000000000, 70.0000000000 98.0000000000, 53.0000000000 98.0000000000, 63.0000000000 98.0000000000, 69.0000000000 98.0000000000, 72.0000000000 99.0000000000, 58.0000000000 99.0000000000, 61.0000000000 99.0000000000, 70.0000000000 101.0000000000, 78.0000000000 101.5000000000, 77.0000000000 102.0000000000, 53.0000000000 102.0000000000, 61.0000000000 102.0000000000, 70.0000000000 104.0000000000, 53.0000000000 104.0000000000, 63.0000000000 104.0000000000, 69.0000000000 104.0000000000, 72.0000000000 105.0000000000, 58.0000000000 105.0000000000, 61.0000000000 105.0000000000, 70.0000000000 107.0000000000, 53.0000000000 107.0000000000, 63.0000000000 107.0000000000, 69.0000000000 107.0000000000, 73.0000000000 107.5000000000, 72.0000000000 108.0000000000, 58.0000000000 108.0000000000, 61.0000000000 108.0000000000, 70.0000000000 110.0000000000, 53.0000000000 110.0000000000, 63.0000000000 110.0000000000, 69.0000000000 110.0000000000, 73.0000000000 110.5000000000, 72.0000000000 111.0000000000, 58.0000000000 111.0000000000, 61.0000000000 111.0000000000, 70.0000000000 113.0000000000, 61.0000000000 113.0000000000, 73.0000000000 113.5000000000, 60.0000000000 113.5000000000, 72.0000000000 114.0000000000, 58.0000000000 114.0000000000, 70.0000000000 114.5000000000, 60.0000000000 114.5000000000, 72.0000000000 115.0000000000, 61.0000000000 115.0000000000, 73.0000000000 115.5000000000, 60.0000000000 115.5000000000, 72.0000000000 116.0000000000, 58.0000000000 116.0000000000, 70.0000000000 116.5000000000, 60.0000000000 116.5000000000, 72.0000000000 117.0000000000, 58.0000000000 117.0000000000, 70.0000000000 117.5000000000, 56.0000000000 117.5000000000, 68.0000000000 118.0000000000, 55.0000000000 118.0000000000, 67.0000000000 118.5000000000, 56.0000000000 118.5000000000, 68.0000000000 119.0000000000, 55.0000000000 119.0000000000, 67.0000000000 119.5000000000, 53.0000000000 119.5000000000, 65.0000000000 120.0000000000, 52.0000000000 120.0000000000, 64.0000000000 120.5000000000, 53.0000000000 120.5000000000, 65.0000000000 121.0000000000, 55.0000000000 121.0000000000, 67.0000000000 121.5000000000, 53.0000000000 121.5000000000, 65.0000000000 122.0000000000, 56.0000000000 122.0000000000, 68.0000000000 122.5000000000, 47.0000000000 122.5000000000, 59.0000000000 123.0000000000, 48.0000000000 123.0000000000, 60.0000000000 124.0000000000, 60.0000000000 125.0000000000, 60.0000000000 125.0000000000, 68.0000000000 126.0000000000, 61.0000000000 126.0000000000, 70.0000000000 127.0000000000, 58.0000000000 127.0000000000, 67.0000000000 128.0000000000, 58.0000000000 128.0000000000, 67.0000000000 128.0000000000, 76.0000000000 129.0000000000, 60.0000000000 129.0000000000, 68.0000000000 129.0000000000, 77.0000000000 130.0000000000, 56.0000000000 130.0000000000, 65.0000000000 130.0000000000, 80.0000000000 131.0000000000, 53.0000000000 131.0000000000, 56.0000000000 131.0000000000, 84.0000000000 132.0000000000, 52.0000000000 132.0000000000, 55.0000000000 132.0000000000, 85.0000000000 133.0000000000, 55.0000000000 133.0000000000, 58.0000000000 133.0000000000, 82.0000000000 134.0000000000, 55.0000000000 134.0000000000, 58.0000000000 134.0000000000, 82.0000000000 135.0000000000, 53.0000000000 135.0000000000, 56.0000000000 135.0000000000, 84.0000000000 136.0000000000, 56.0000000000 136.0000000000, 60.0000000000 136.0000000000, 80.0000000000 137.0000000000, 56.0000000000 137.0000000000, 60.0000000000 137.0000000000, 65.0000000000 137.0000000000, 80.0000000000 138.0000000000, 55.0000000000 138.0000000000, 58.0000000000 138.0000000000, 64.0000000000 138.0000000000, 82.0000000000 139.0000000000, 58.0000000000 139.0000000000, 61.0000000000 139.0000000000, 64.0000000000 139.0000000000, 79.0000000000 140.0000000000, 58.0000000000 140.0000000000, 61.0000000000 140.0000000000, 64.0000000000 140.0000000000, 79.0000000000 141.0000000000, 59.0000000000 141.0000000000, 62.0000000000 141.0000000000, 65.0000000000 141.0000000000, 80.0000000000 142.0000000000, 68.0000000000 142.0000000000, 77.0000000000 143.0000000000, 59.0000000000 143.0000000000, 62.0000000000 143.0000000000, 68.0000000000 143.0000000000, 77.0000000000 144.0000000000, 60.0000000000 144.0000000000, 68.0000000000 144.0000000000, 77.0000000000 146.0000000000, 60.0000000000 146.0000000000, 70.0000000000 146.0000000000, 76.0000000000 146.0000000000, 79.0000000000 147.0000000000, 65.0000000000 147.0000000000, 68.0000000000 147.0000000000, 77.0000000000 149.0000000000, 75.0000000000 149.5000000000, 73.0000000000 150.0000000000, 48.0000000000 150.0000000000, 56.0000000000 150.0000000000, 65.0000000000 152.0000000000, 48.0000000000 152.0000000000, 58.0000000000 152.0000000000, 64.0000000000 152.0000000000, 67.0000000000 153.0000000000, 53.0000000000 153.0000000000, 56.0000000000 153.0000000000, 65.0000000000 156.0000000000, 36.0000000000 156.0000000000, 48.0000000000 156.0000000000, 52.0000000000 156.0000000000, 55.0000000000 156.0000000000, 60.0000000000 159.0000000000, 41.0000000000 159.0000000000, 53.0000000000 occurrence2 161.0000000000, 72.0000000000 161.0000000000, 75.0000000000 162.0000000000, 73.0000000000 162.0000000000, 76.0000000000 163.0000000000, 55.0000000000 163.0000000000, 58.0000000000 163.0000000000, 70.0000000000 163.0000000000, 73.0000000000 164.0000000000, 58.0000000000 164.0000000000, 61.0000000000 165.0000000000, 72.0000000000 165.0000000000, 75.0000000000 166.0000000000, 56.0000000000 166.0000000000, 60.0000000000 166.0000000000, 68.0000000000 166.0000000000, 72.0000000000 167.0000000000, 60.0000000000 167.0000000000, 63.0000000000 168.0000000000, 75.0000000000 168.0000000000, 78.0000000000 169.0000000000, 57.0000000000 169.0000000000, 60.0000000000 169.0000000000, 72.0000000000 169.0000000000, 75.0000000000 170.0000000000, 60.0000000000 170.0000000000, 63.0000000000 171.0000000000, 73.0000000000 171.0000000000, 77.0000000000 172.0000000000, 58.0000000000 172.0000000000, 61.0000000000 172.0000000000, 70.0000000000 172.0000000000, 73.0000000000 173.0000000000, 61.0000000000 173.0000000000, 65.0000000000 174.0000000000, 53.0000000000 174.0000000000, 61.0000000000 174.0000000000, 65.0000000000 174.0000000000, 70.0000000000 176.0000000000, 53.0000000000 176.0000000000, 63.0000000000 176.0000000000, 69.0000000000 176.0000000000, 72.0000000000 177.0000000000, 58.0000000000 177.0000000000, 61.0000000000 177.0000000000, 70.0000000000 179.0000000000, 78.0000000000 179.5000000000, 77.0000000000 180.0000000000, 53.0000000000 180.0000000000, 61.0000000000 180.0000000000, 70.0000000000 182.0000000000, 53.0000000000 182.0000000000, 63.0000000000 182.0000000000, 69.0000000000 182.0000000000, 72.0000000000 183.0000000000, 58.0000000000 183.0000000000, 61.0000000000 183.0000000000, 70.0000000000 185.0000000000, 53.0000000000 185.0000000000, 63.0000000000 185.0000000000, 69.0000000000 185.0000000000, 73.0000000000 185.5000000000, 72.0000000000 186.0000000000, 58.0000000000 186.0000000000, 61.0000000000 186.0000000000, 70.0000000000 188.0000000000, 53.0000000000 188.0000000000, 63.0000000000 188.0000000000, 69.0000000000 188.0000000000, 73.0000000000 188.5000000000, 72.0000000000 189.0000000000, 58.0000000000 189.0000000000, 61.0000000000 189.0000000000, 70.0000000000 191.0000000000, 61.0000000000 191.0000000000, 73.0000000000 191.5000000000, 60.0000000000 191.5000000000, 72.0000000000 192.0000000000, 58.0000000000 192.0000000000, 70.0000000000 192.5000000000, 60.0000000000 192.5000000000, 72.0000000000 193.0000000000, 61.0000000000 193.0000000000, 73.0000000000 193.5000000000, 60.0000000000 193.5000000000, 72.0000000000 194.0000000000, 58.0000000000 194.0000000000, 70.0000000000 194.5000000000, 60.0000000000 194.5000000000, 72.0000000000 195.0000000000, 58.0000000000 195.0000000000, 70.0000000000 195.5000000000, 56.0000000000 195.5000000000, 68.0000000000 196.0000000000, 55.0000000000 196.0000000000, 67.0000000000 196.5000000000, 56.0000000000 196.5000000000, 68.0000000000 197.0000000000, 55.0000000000 197.0000000000, 67.0000000000 197.5000000000, 53.0000000000 197.5000000000, 65.0000000000 198.0000000000, 52.0000000000 198.0000000000, 64.0000000000 198.5000000000, 53.0000000000 198.5000000000, 65.0000000000 199.0000000000, 55.0000000000 199.0000000000, 67.0000000000 199.5000000000, 53.0000000000 199.5000000000, 65.0000000000 200.0000000000, 56.0000000000 200.0000000000, 68.0000000000 200.5000000000, 47.0000000000 200.5000000000, 59.0000000000 201.0000000000, 48.0000000000 201.0000000000, 60.0000000000 202.0000000000, 60.0000000000 203.0000000000, 60.0000000000 203.0000000000, 68.0000000000 204.0000000000, 61.0000000000 204.0000000000, 70.0000000000 205.0000000000, 58.0000000000 205.0000000000, 67.0000000000 206.0000000000, 58.0000000000 206.0000000000, 67.0000000000 206.0000000000, 76.0000000000 207.0000000000, 60.0000000000 207.0000000000, 68.0000000000 207.0000000000, 77.0000000000 208.0000000000, 56.0000000000 208.0000000000, 65.0000000000 208.0000000000, 80.0000000000 209.0000000000, 53.0000000000 209.0000000000, 56.0000000000 209.0000000000, 84.0000000000 210.0000000000, 52.0000000000 210.0000000000, 55.0000000000 210.0000000000, 85.0000000000 211.0000000000, 55.0000000000 211.0000000000, 58.0000000000 211.0000000000, 82.0000000000 212.0000000000, 55.0000000000 212.0000000000, 58.0000000000 212.0000000000, 82.0000000000 213.0000000000, 53.0000000000 213.0000000000, 56.0000000000 213.0000000000, 84.0000000000 214.0000000000, 56.0000000000 214.0000000000, 60.0000000000 214.0000000000, 80.0000000000 215.0000000000, 56.0000000000 215.0000000000, 60.0000000000 215.0000000000, 65.0000000000 215.0000000000, 80.0000000000 216.0000000000, 55.0000000000 216.0000000000, 58.0000000000 216.0000000000, 64.0000000000 216.0000000000, 82.0000000000 217.0000000000, 58.0000000000 217.0000000000, 61.0000000000 217.0000000000, 64.0000000000 217.0000000000, 79.0000000000 218.0000000000, 58.0000000000 218.0000000000, 61.0000000000 218.0000000000, 64.0000000000 218.0000000000, 79.0000000000 219.0000000000, 59.0000000000 219.0000000000, 62.0000000000 219.0000000000, 65.0000000000 219.0000000000, 80.0000000000 220.0000000000, 68.0000000000 220.0000000000, 77.0000000000 221.0000000000, 59.0000000000 221.0000000000, 62.0000000000 221.0000000000, 68.0000000000 221.0000000000, 77.0000000000 222.0000000000, 60.0000000000 222.0000000000, 68.0000000000 222.0000000000, 77.0000000000 224.0000000000, 60.0000000000 224.0000000000, 70.0000000000 224.0000000000, 76.0000000000 224.0000000000, 79.0000000000 225.0000000000, 65.0000000000 225.0000000000, 68.0000000000 225.0000000000, 77.0000000000 227.0000000000, 75.0000000000 227.5000000000, 73.0000000000 228.0000000000, 48.0000000000 228.0000000000, 56.0000000000 228.0000000000, 65.0000000000 230.0000000000, 48.0000000000 230.0000000000, 58.0000000000 230.0000000000, 64.0000000000 230.0000000000, 67.0000000000 231.0000000000, 53.0000000000 231.0000000000, 56.0000000000 231.0000000000, 65.0000000000 234.0000000000, 36.0000000000 234.0000000000, 48.0000000000 234.0000000000, 52.0000000000 234.0000000000, 55.0000000000 234.0000000000, 60.0000000000 237.0000000000, 41.0000000000 237.0000000000, 53.0000000000 occurrence3 479.0000000000, 72.0000000000 479.0000000000, 75.0000000000 480.0000000000, 73.0000000000 480.0000000000, 76.0000000000 481.0000000000, 55.0000000000 481.0000000000, 58.0000000000 481.0000000000, 70.0000000000 481.0000000000, 73.0000000000 482.0000000000, 58.0000000000 482.0000000000, 61.0000000000 483.0000000000, 72.0000000000 483.0000000000, 75.0000000000 484.0000000000, 56.0000000000 484.0000000000, 60.0000000000 484.0000000000, 68.0000000000 484.0000000000, 72.0000000000 485.0000000000, 60.0000000000 485.0000000000, 63.0000000000 486.0000000000, 75.0000000000 486.0000000000, 78.0000000000 487.0000000000, 57.0000000000 487.0000000000, 60.0000000000 487.0000000000, 72.0000000000 487.0000000000, 75.0000000000 488.0000000000, 60.0000000000 488.0000000000, 63.0000000000 489.0000000000, 73.0000000000 489.0000000000, 77.0000000000 490.0000000000, 58.0000000000 490.0000000000, 61.0000000000 490.0000000000, 70.0000000000 490.0000000000, 73.0000000000 491.0000000000, 61.0000000000 491.0000000000, 65.0000000000 492.0000000000, 53.0000000000 492.0000000000, 61.0000000000 492.0000000000, 65.0000000000 492.0000000000, 70.0000000000 494.0000000000, 53.0000000000 494.0000000000, 63.0000000000 494.0000000000, 69.0000000000 494.0000000000, 72.0000000000 495.0000000000, 58.0000000000 495.0000000000, 61.0000000000 495.0000000000, 70.0000000000 497.0000000000, 78.0000000000 497.5000000000, 77.0000000000 498.0000000000, 53.0000000000 498.0000000000, 61.0000000000 498.0000000000, 70.0000000000 500.0000000000, 53.0000000000 500.0000000000, 63.0000000000 500.0000000000, 69.0000000000 500.0000000000, 72.0000000000 501.0000000000, 58.0000000000 501.0000000000, 61.0000000000 501.0000000000, 70.0000000000 503.0000000000, 53.0000000000 503.0000000000, 63.0000000000 503.0000000000, 69.0000000000 503.0000000000, 73.0000000000 503.5000000000, 72.0000000000 504.0000000000, 58.0000000000 504.0000000000, 61.0000000000 504.0000000000, 70.0000000000 506.0000000000, 53.0000000000 506.0000000000, 63.0000000000 506.0000000000, 69.0000000000 506.0000000000, 73.0000000000 506.5000000000, 72.0000000000 507.0000000000, 58.0000000000 507.0000000000, 61.0000000000 507.0000000000, 70.0000000000 509.0000000000, 61.0000000000 509.0000000000, 73.0000000000 509.5000000000, 60.0000000000 509.5000000000, 72.0000000000 510.0000000000, 58.0000000000 510.0000000000, 70.0000000000 510.5000000000, 60.0000000000 510.5000000000, 72.0000000000 511.0000000000, 61.0000000000 511.0000000000, 73.0000000000 511.5000000000, 60.0000000000 511.5000000000, 72.0000000000 512.0000000000, 58.0000000000 512.0000000000, 70.0000000000 512.5000000000, 60.0000000000 512.5000000000, 72.0000000000 513.0000000000, 58.0000000000 513.0000000000, 70.0000000000 513.5000000000, 56.0000000000 513.5000000000, 68.0000000000 514.0000000000, 55.0000000000 514.0000000000, 67.0000000000 514.5000000000, 56.0000000000 514.5000000000, 68.0000000000 515.0000000000, 55.0000000000 515.0000000000, 67.0000000000 515.5000000000, 53.0000000000 515.5000000000, 65.0000000000 516.0000000000, 52.0000000000 516.0000000000, 64.0000000000 516.5000000000, 53.0000000000 516.5000000000, 65.0000000000 517.0000000000, 55.0000000000 517.0000000000, 67.0000000000 517.5000000000, 53.0000000000 517.5000000000, 65.0000000000 518.0000000000, 56.0000000000 518.0000000000, 68.0000000000 518.5000000000, 47.0000000000 518.5000000000, 59.0000000000 519.0000000000, 48.0000000000 519.0000000000, 60.0000000000 520.0000000000, 60.0000000000 521.0000000000, 60.0000000000 521.0000000000, 68.0000000000 522.0000000000, 61.0000000000 522.0000000000, 70.0000000000 523.0000000000, 58.0000000000 523.0000000000, 67.0000000000 524.0000000000, 58.0000000000 524.0000000000, 67.0000000000 524.0000000000, 76.0000000000 525.0000000000, 60.0000000000 525.0000000000, 68.0000000000 525.0000000000, 77.0000000000 526.0000000000, 56.0000000000 526.0000000000, 65.0000000000 526.0000000000, 80.0000000000 527.0000000000, 53.0000000000 527.0000000000, 56.0000000000 527.0000000000, 84.0000000000 528.0000000000, 52.0000000000 528.0000000000, 55.0000000000 528.0000000000, 85.0000000000 529.0000000000, 55.0000000000 529.0000000000, 58.0000000000 529.0000000000, 82.0000000000 530.0000000000, 55.0000000000 530.0000000000, 58.0000000000 530.0000000000, 82.0000000000 531.0000000000, 53.0000000000 531.0000000000, 56.0000000000 531.0000000000, 84.0000000000 532.0000000000, 56.0000000000 532.0000000000, 60.0000000000 532.0000000000, 80.0000000000 533.0000000000, 56.0000000000 533.0000000000, 60.0000000000 533.0000000000, 65.0000000000 533.0000000000, 80.0000000000 534.0000000000, 55.0000000000 534.0000000000, 58.0000000000 534.0000000000, 64.0000000000 534.0000000000, 82.0000000000 535.0000000000, 58.0000000000 535.0000000000, 61.0000000000 535.0000000000, 64.0000000000 535.0000000000, 79.0000000000 536.0000000000, 58.0000000000 536.0000000000, 61.0000000000 536.0000000000, 64.0000000000 536.0000000000, 79.0000000000 537.0000000000, 59.0000000000 537.0000000000, 62.0000000000 537.0000000000, 65.0000000000 537.0000000000, 80.0000000000 538.0000000000, 68.0000000000 538.0000000000, 77.0000000000 539.0000000000, 59.0000000000 539.0000000000, 62.0000000000 539.0000000000, 68.0000000000 539.0000000000, 77.0000000000 540.0000000000, 60.0000000000 540.0000000000, 68.0000000000 540.0000000000, 77.0000000000 542.0000000000, 60.0000000000 542.0000000000, 70.0000000000 542.0000000000, 76.0000000000 542.0000000000, 79.0000000000 543.0000000000, 65.0000000000 543.0000000000, 68.0000000000 543.0000000000, 77.0000000000 545.0000000000, 75.0000000000 545.5000000000, 73.0000000000 546.0000000000, 48.0000000000 546.0000000000, 56.0000000000 546.0000000000, 65.0000000000 548.0000000000, 48.0000000000 548.0000000000, 58.0000000000 548.0000000000, 64.0000000000 548.0000000000, 67.0000000000 549.0000000000, 53.0000000000 549.0000000000, 56.0000000000 549.0000000000, 65.0000000000 552.0000000000, 36.0000000000 552.0000000000, 48.0000000000 552.0000000000, 52.0000000000 552.0000000000, 55.0000000000 552.0000000000, 60.0000000000 555.0000000000, 41.0000000000 555.0000000000, 53.0000000000 pattern5 occurrence1 239.0000000000, 60.0000000000 240.0000000000, 53.0000000000 240.0000000000, 69.0000000000 240.5000000000, 67.0000000000 241.0000000000, 57.0000000000 241.0000000000, 69.0000000000 241.5000000000, 65.0000000000 242.0000000000, 60.0000000000 242.0000000000, 67.0000000000 242.5000000000, 69.0000000000 243.0000000000, 62.0000000000 243.0000000000, 70.0000000000 243.5000000000, 69.0000000000 244.0000000000, 55.0000000000 244.0000000000, 70.0000000000 244.5000000000, 67.0000000000 245.0000000000, 53.0000000000 245.0000000000, 69.0000000000 245.5000000000, 71.0000000000 246.0000000000, 52.0000000000 246.0000000000, 72.0000000000 246.5000000000, 71.0000000000 247.0000000000, 55.0000000000 247.0000000000, 72.0000000000 247.5000000000, 74.0000000000 248.0000000000, 60.0000000000 248.0000000000, 72.0000000000 248.5000000000, 70.0000000000 249.0000000000, 53.0000000000 249.0000000000, 69.0000000000 249.5000000000, 67.0000000000 250.0000000000, 57.0000000000 250.0000000000, 69.0000000000 250.5000000000, 70.0000000000 251.0000000000, 60.0000000000 251.0000000000, 69.0000000000 251.5000000000, 65.0000000000 252.0000000000, 45.0000000000 252.0000000000, 69.0000000000 252.5000000000, 44.0000000000 253.0000000000, 45.0000000000 253.0000000000, 72.0000000000 253.5000000000, 41.0000000000 254.0000000000, 43.0000000000 254.0000000000, 77.0000000000 254.5000000000, 45.0000000000 255.0000000000, 46.0000000000 255.0000000000, 67.0000000000 255.5000000000, 45.0000000000 256.0000000000, 46.0000000000 256.0000000000, 74.0000000000 256.5000000000, 43.0000000000 257.0000000000, 45.0000000000 257.0000000000, 77.0000000000 257.5000000000, 47.0000000000 258.0000000000, 48.0000000000 258.0000000000, 67.0000000000 258.5000000000, 47.0000000000 259.0000000000, 48.0000000000 259.0000000000, 77.0000000000 259.5000000000, 45.0000000000 260.0000000000, 47.0000000000 260.0000000000, 76.0000000000 260.5000000000, 49.0000000000 261.0000000000, 50.0000000000 261.0000000000, 65.0000000000 261.5000000000, 45.0000000000 262.0000000000, 47.0000000000 262.0000000000, 74.0000000000 262.5000000000, 43.0000000000 263.0000000000, 48.0000000000 263.0000000000, 64.0000000000 263.0000000000, 72.0000000000 263.5000000000, 42.0000000000 264.0000000000, 43.0000000000 264.5000000000, 67.0000000000 265.0000000000, 64.0000000000 265.5000000000, 60.0000000000 266.0000000000, 31.0000000000 266.0000000000, 59.0000000000 266.0000000000, 65.0000000000 266.5000000000, 62.0000000000 267.0000000000, 36.0000000000 267.0000000000, 60.0000000000 268.0000000000, 48.0000000000 occurrence2 269.0000000000, 60.0000000000 270.0000000000, 53.0000000000 270.0000000000, 69.0000000000 270.5000000000, 67.0000000000 271.0000000000, 57.0000000000 271.0000000000, 69.0000000000 271.5000000000, 65.0000000000 272.0000000000, 60.0000000000 272.0000000000, 67.0000000000 272.5000000000, 69.0000000000 273.0000000000, 62.0000000000 273.0000000000, 70.0000000000 273.5000000000, 69.0000000000 274.0000000000, 55.0000000000 274.0000000000, 70.0000000000 274.5000000000, 67.0000000000 275.0000000000, 53.0000000000 275.0000000000, 69.0000000000 275.5000000000, 71.0000000000 276.0000000000, 52.0000000000 276.0000000000, 72.0000000000 276.5000000000, 71.0000000000 277.0000000000, 55.0000000000 277.0000000000, 72.0000000000 277.5000000000, 74.0000000000 278.0000000000, 60.0000000000 278.0000000000, 72.0000000000 278.5000000000, 70.0000000000 279.0000000000, 53.0000000000 279.0000000000, 69.0000000000 279.5000000000, 67.0000000000 280.0000000000, 57.0000000000 280.0000000000, 69.0000000000 280.5000000000, 70.0000000000 281.0000000000, 60.0000000000 281.0000000000, 69.0000000000 281.5000000000, 65.0000000000 282.0000000000, 45.0000000000 282.0000000000, 69.0000000000 282.5000000000, 44.0000000000 283.0000000000, 45.0000000000 283.0000000000, 72.0000000000 283.5000000000, 41.0000000000 284.0000000000, 43.0000000000 284.0000000000, 77.0000000000 284.5000000000, 45.0000000000 285.0000000000, 46.0000000000 285.0000000000, 67.0000000000 285.5000000000, 45.0000000000 286.0000000000, 46.0000000000 286.0000000000, 74.0000000000 286.5000000000, 43.0000000000 287.0000000000, 45.0000000000 287.0000000000, 77.0000000000 287.5000000000, 47.0000000000 288.0000000000, 48.0000000000 288.0000000000, 67.0000000000 288.5000000000, 47.0000000000 289.0000000000, 48.0000000000 289.0000000000, 77.0000000000 289.5000000000, 45.0000000000 290.0000000000, 47.0000000000 290.0000000000, 76.0000000000 290.5000000000, 49.0000000000 291.0000000000, 50.0000000000 291.0000000000, 65.0000000000 291.5000000000, 45.0000000000 292.0000000000, 47.0000000000 292.0000000000, 74.0000000000 292.5000000000, 43.0000000000 293.0000000000, 48.0000000000 293.0000000000, 64.0000000000 293.0000000000, 72.0000000000 293.5000000000, 42.0000000000 294.0000000000, 43.0000000000 294.5000000000, 67.0000000000 295.0000000000, 64.0000000000 295.5000000000, 60.0000000000 296.0000000000, 31.0000000000 296.0000000000, 59.0000000000 296.0000000000, 65.0000000000 296.5000000000, 62.0000000000 297.0000000000, 36.0000000000 297.0000000000, 60.0000000000 298.0000000000, 48.0000000000 pattern6 occurrence1 299.0000000000, 60.0000000000 300.0000000000, 48.0000000000 300.0000000000, 60.0000000000 300.0000000000, 64.0000000000 300.5000000000, 62.0000000000 301.0000000000, 64.0000000000 301.5000000000, 60.0000000000 302.0000000000, 62.0000000000 302.5000000000, 64.0000000000 303.0000000000, 59.0000000000 303.0000000000, 65.0000000000 303.5000000000, 64.0000000000 304.0000000000, 65.0000000000 304.5000000000, 62.0000000000 305.0000000000, 64.0000000000 305.5000000000, 65.0000000000 306.0000000000, 58.0000000000 306.0000000000, 67.0000000000 306.5000000000, 66.0000000000 307.0000000000, 67.0000000000 307.5000000000, 64.0000000000 308.0000000000, 65.0000000000 308.5000000000, 67.0000000000 309.0000000000, 57.0000000000 309.0000000000, 69.0000000000 309.5000000000, 65.0000000000 310.0000000000, 69.0000000000 310.5000000000, 72.0000000000 311.0000000000, 77.0000000000 311.5000000000, 81.0000000000 312.0000000000, 64.0000000000 312.0000000000, 72.0000000000 312.0000000000, 84.0000000000 312.5000000000, 62.0000000000 313.0000000000, 64.0000000000 313.5000000000, 60.0000000000 314.0000000000, 62.0000000000 314.5000000000, 64.0000000000 315.0000000000, 65.0000000000 315.0000000000, 71.0000000000 315.0000000000, 83.0000000000 315.5000000000, 64.0000000000 316.0000000000, 65.0000000000 316.5000000000, 62.0000000000 317.0000000000, 64.0000000000 317.5000000000, 65.0000000000 318.0000000000, 67.0000000000 318.0000000000, 70.0000000000 318.0000000000, 82.0000000000 318.5000000000, 65.0000000000 319.0000000000, 67.0000000000 319.5000000000, 64.0000000000 319.5000000000, 67.0000000000 320.0000000000, 65.0000000000 320.0000000000, 69.0000000000 320.5000000000, 67.0000000000 320.5000000000, 70.0000000000 321.0000000000, 69.0000000000 321.0000000000, 72.0000000000 321.5000000000, 67.0000000000 321.5000000000, 70.0000000000 322.0000000000, 69.0000000000 322.0000000000, 72.0000000000 322.5000000000, 65.0000000000 322.5000000000, 69.0000000000 323.0000000000, 67.0000000000 323.0000000000, 70.0000000000 323.5000000000, 69.0000000000 323.5000000000, 72.0000000000 324.0000000000, 70.0000000000 324.0000000000, 74.0000000000 324.5000000000, 69.0000000000 324.5000000000, 72.0000000000 325.0000000000, 70.0000000000 325.0000000000, 74.0000000000 325.5000000000, 67.0000000000 325.5000000000, 70.0000000000 325.5000000000, 76.0000000000 326.0000000000, 69.0000000000 326.0000000000, 72.0000000000 326.0000000000, 77.0000000000 326.5000000000, 70.0000000000 326.5000000000, 74.0000000000 326.5000000000, 79.0000000000 327.0000000000, 72.0000000000 327.0000000000, 76.0000000000 327.0000000000, 81.0000000000 327.5000000000, 70.0000000000 327.5000000000, 74.0000000000 327.5000000000, 79.0000000000 328.0000000000, 72.0000000000 328.0000000000, 76.0000000000 328.0000000000, 81.0000000000 328.5000000000, 69.0000000000 328.5000000000, 72.0000000000 328.5000000000, 77.0000000000 329.0000000000, 70.0000000000 329.0000000000, 74.0000000000 329.0000000000, 79.0000000000 329.5000000000, 72.0000000000 329.5000000000, 76.0000000000 329.5000000000, 81.0000000000 330.0000000000, 74.0000000000 330.0000000000, 77.0000000000 330.0000000000, 82.0000000000 330.5000000000, 72.0000000000 330.5000000000, 76.0000000000 330.5000000000, 81.0000000000 331.0000000000, 70.0000000000 331.0000000000, 74.0000000000 331.0000000000, 79.0000000000 331.5000000000, 72.0000000000 331.5000000000, 76.0000000000 331.5000000000, 81.0000000000 332.0000000000, 70.0000000000 332.0000000000, 74.0000000000 332.0000000000, 79.0000000000 332.5000000000, 69.0000000000 332.5000000000, 72.0000000000 332.5000000000, 77.0000000000 333.0000000000, 67.0000000000 333.0000000000, 70.0000000000 333.0000000000, 76.0000000000 333.5000000000, 69.0000000000 333.5000000000, 72.0000000000 333.5000000000, 77.0000000000 334.0000000000, 67.0000000000 334.0000000000, 70.0000000000 334.0000000000, 76.0000000000 334.5000000000, 65.0000000000 334.5000000000, 69.0000000000 334.5000000000, 74.0000000000 335.0000000000, 64.0000000000 335.0000000000, 67.0000000000 335.0000000000, 72.0000000000 335.5000000000, 65.0000000000 335.5000000000, 69.0000000000 335.5000000000, 74.0000000000 336.0000000000, 64.0000000000 336.0000000000, 67.0000000000 336.0000000000, 72.0000000000 339.0000000000, 62.0000000000 339.0000000000, 65.0000000000 339.0000000000, 71.0000000000 342.0000000000, 60.0000000000 342.0000000000, 64.0000000000 342.0000000000, 70.0000000000 345.0000000000, 53.0000000000 345.0000000000, 69.0000000000 345.5000000000, 67.0000000000 346.0000000000, 57.0000000000 346.0000000000, 69.0000000000 346.5000000000, 65.0000000000 347.0000000000, 60.0000000000 347.0000000000, 67.0000000000 347.5000000000, 69.0000000000 348.0000000000, 62.0000000000 348.0000000000, 70.0000000000 348.5000000000, 69.0000000000 349.0000000000, 55.0000000000 349.0000000000, 70.0000000000 349.5000000000, 67.0000000000 350.0000000000, 53.0000000000 350.0000000000, 69.0000000000 350.5000000000, 71.0000000000 351.0000000000, 52.0000000000 351.0000000000, 72.0000000000 351.5000000000, 71.0000000000 352.0000000000, 55.0000000000 352.0000000000, 72.0000000000 352.5000000000, 74.0000000000 353.0000000000, 60.0000000000 353.0000000000, 72.0000000000 353.5000000000, 70.0000000000 354.0000000000, 53.0000000000 354.0000000000, 69.0000000000 354.5000000000, 67.0000000000 355.0000000000, 57.0000000000 355.0000000000, 69.0000000000 355.5000000000, 70.0000000000 356.0000000000, 60.0000000000 356.0000000000, 69.0000000000 356.5000000000, 65.0000000000 357.0000000000, 45.0000000000 357.0000000000, 69.0000000000 357.5000000000, 44.0000000000 358.0000000000, 45.0000000000 358.0000000000, 72.0000000000 358.5000000000, 41.0000000000 359.0000000000, 43.0000000000 359.0000000000, 77.0000000000 359.5000000000, 45.0000000000 360.0000000000, 46.0000000000 360.0000000000, 74.0000000000 360.5000000000, 45.0000000000 361.0000000000, 46.0000000000 361.0000000000, 67.0000000000 361.5000000000, 43.0000000000 362.0000000000, 45.0000000000 362.0000000000, 65.0000000000 362.5000000000, 47.0000000000 363.0000000000, 48.0000000000 363.0000000000, 64.0000000000 363.5000000000, 47.0000000000 364.0000000000, 48.0000000000 364.0000000000, 67.0000000000 364.5000000000, 46.0000000000 365.0000000000, 45.0000000000 365.0000000000, 72.0000000000 365.5000000000, 43.0000000000 366.0000000000, 41.0000000000 366.0000000000, 65.0000000000 367.0000000000, 53.0000000000 occurrence2 368.0000000000, 60.0000000000 369.0000000000, 48.0000000000 369.0000000000, 60.0000000000 369.0000000000, 64.0000000000 369.5000000000, 62.0000000000 370.0000000000, 64.0000000000 370.5000000000, 60.0000000000 371.0000000000, 62.0000000000 371.5000000000, 64.0000000000 372.0000000000, 59.0000000000 372.0000000000, 65.0000000000 372.5000000000, 64.0000000000 373.0000000000, 65.0000000000 373.5000000000, 62.0000000000 374.0000000000, 64.0000000000 374.5000000000, 65.0000000000 375.0000000000, 58.0000000000 375.0000000000, 67.0000000000 375.5000000000, 66.0000000000 376.0000000000, 67.0000000000 376.5000000000, 64.0000000000 377.0000000000, 65.0000000000 377.5000000000, 67.0000000000 378.0000000000, 57.0000000000 378.0000000000, 69.0000000000 378.5000000000, 65.0000000000 379.0000000000, 69.0000000000 379.5000000000, 72.0000000000 380.0000000000, 77.0000000000 380.5000000000, 81.0000000000 381.0000000000, 64.0000000000 381.0000000000, 72.0000000000 381.0000000000, 84.0000000000 381.5000000000, 62.0000000000 382.0000000000, 64.0000000000 382.5000000000, 60.0000000000 383.0000000000, 62.0000000000 383.5000000000, 64.0000000000 384.0000000000, 65.0000000000 384.0000000000, 71.0000000000 384.0000000000, 83.0000000000 384.5000000000, 64.0000000000 385.0000000000, 65.0000000000 385.5000000000, 62.0000000000 386.0000000000, 64.0000000000 386.5000000000, 65.0000000000 387.0000000000, 67.0000000000 387.0000000000, 70.0000000000 387.0000000000, 82.0000000000 387.5000000000, 65.0000000000 388.0000000000, 67.0000000000 388.5000000000, 64.0000000000 388.5000000000, 67.0000000000 389.0000000000, 65.0000000000 389.0000000000, 69.0000000000 389.5000000000, 67.0000000000 389.5000000000, 70.0000000000 390.0000000000, 69.0000000000 390.0000000000, 72.0000000000 390.5000000000, 67.0000000000 390.5000000000, 70.0000000000 391.0000000000, 69.0000000000 391.0000000000, 72.0000000000 391.5000000000, 65.0000000000 391.5000000000, 69.0000000000 392.0000000000, 67.0000000000 392.0000000000, 70.0000000000 392.5000000000, 69.0000000000 392.5000000000, 72.0000000000 393.0000000000, 70.0000000000 393.0000000000, 74.0000000000 393.5000000000, 69.0000000000 393.5000000000, 72.0000000000 394.0000000000, 70.0000000000 394.0000000000, 74.0000000000 394.5000000000, 67.0000000000 394.5000000000, 70.0000000000 394.5000000000, 76.0000000000 395.0000000000, 69.0000000000 395.0000000000, 72.0000000000 395.0000000000, 77.0000000000 395.5000000000, 70.0000000000 395.5000000000, 74.0000000000 395.5000000000, 79.0000000000 396.0000000000, 72.0000000000 396.0000000000, 76.0000000000 396.0000000000, 81.0000000000 396.5000000000, 70.0000000000 396.5000000000, 74.0000000000 396.5000000000, 79.0000000000 397.0000000000, 72.0000000000 397.0000000000, 76.0000000000 397.0000000000, 81.0000000000 397.5000000000, 69.0000000000 397.5000000000, 72.0000000000 397.5000000000, 77.0000000000 398.0000000000, 70.0000000000 398.0000000000, 74.0000000000 398.0000000000, 79.0000000000 398.5000000000, 72.0000000000 398.5000000000, 76.0000000000 398.5000000000, 81.0000000000 399.0000000000, 74.0000000000 399.0000000000, 77.0000000000 399.0000000000, 82.0000000000 399.5000000000, 72.0000000000 399.5000000000, 76.0000000000 399.5000000000, 81.0000000000 400.0000000000, 70.0000000000 400.0000000000, 74.0000000000 400.0000000000, 79.0000000000 400.5000000000, 72.0000000000 400.5000000000, 76.0000000000 400.5000000000, 81.0000000000 401.0000000000, 70.0000000000 401.0000000000, 74.0000000000 401.0000000000, 79.0000000000 401.5000000000, 69.0000000000 401.5000000000, 72.0000000000 401.5000000000, 77.0000000000 402.0000000000, 67.0000000000 402.0000000000, 70.0000000000 402.0000000000, 76.0000000000 402.5000000000, 69.0000000000 402.5000000000, 72.0000000000 402.5000000000, 77.0000000000 403.0000000000, 67.0000000000 403.0000000000, 70.0000000000 403.0000000000, 76.0000000000 403.5000000000, 65.0000000000 403.5000000000, 69.0000000000 403.5000000000, 74.0000000000 404.0000000000, 64.0000000000 404.0000000000, 67.0000000000 404.0000000000, 72.0000000000 404.5000000000, 65.0000000000 404.5000000000, 69.0000000000 404.5000000000, 74.0000000000 405.0000000000, 64.0000000000 405.0000000000, 67.0000000000 405.0000000000, 72.0000000000 408.0000000000, 62.0000000000 408.0000000000, 65.0000000000 408.0000000000, 71.0000000000 411.0000000000, 60.0000000000 411.0000000000, 64.0000000000 411.0000000000, 70.0000000000 414.0000000000, 53.0000000000 414.0000000000, 69.0000000000 414.5000000000, 67.0000000000 415.0000000000, 57.0000000000 415.0000000000, 69.0000000000 415.5000000000, 65.0000000000 416.0000000000, 60.0000000000 416.0000000000, 67.0000000000 416.5000000000, 69.0000000000 417.0000000000, 62.0000000000 417.0000000000, 70.0000000000 417.5000000000, 69.0000000000 418.0000000000, 55.0000000000 418.0000000000, 70.0000000000 418.5000000000, 67.0000000000 419.0000000000, 53.0000000000 419.0000000000, 69.0000000000 419.5000000000, 71.0000000000 420.0000000000, 52.0000000000 420.0000000000, 72.0000000000 420.5000000000, 71.0000000000 421.0000000000, 55.0000000000 421.0000000000, 72.0000000000 421.5000000000, 74.0000000000 422.0000000000, 60.0000000000 422.0000000000, 72.0000000000 422.5000000000, 70.0000000000 423.0000000000, 53.0000000000 423.0000000000, 69.0000000000 423.5000000000, 67.0000000000 424.0000000000, 57.0000000000 424.0000000000, 69.0000000000 424.5000000000, 70.0000000000 425.0000000000, 60.0000000000 425.0000000000, 69.0000000000 425.5000000000, 65.0000000000 426.0000000000, 45.0000000000 426.0000000000, 69.0000000000 426.5000000000, 44.0000000000 427.0000000000, 45.0000000000 427.0000000000, 72.0000000000 427.5000000000, 41.0000000000 428.0000000000, 43.0000000000 428.0000000000, 77.0000000000 428.5000000000, 45.0000000000 429.0000000000, 46.0000000000 429.0000000000, 74.0000000000 429.5000000000, 45.0000000000 430.0000000000, 46.0000000000 430.0000000000, 67.0000000000 430.5000000000, 43.0000000000 431.0000000000, 45.0000000000 431.0000000000, 65.0000000000 431.5000000000, 47.0000000000 432.0000000000, 48.0000000000 432.0000000000, 64.0000000000 432.5000000000, 47.0000000000 433.0000000000, 48.0000000000 433.0000000000, 67.0000000000 433.5000000000, 46.0000000000 434.0000000000, 45.0000000000 434.0000000000, 72.0000000000 434.5000000000, 43.0000000000 435.0000000000, 41.0000000000 435.0000000000, 65.0000000000 436.0000000000, 53.0000000000 pattern7 occurrence1 41.0000000000, 60.0000000000 41.0000000000, 68.0000000000 42.0000000000, 61.0000000000 42.0000000000, 70.0000000000 43.0000000000, 58.0000000000 43.0000000000, 67.0000000000 44.0000000000, 53.0000000000 45.0000000000, 60.0000000000 45.0000000000, 68.0000000000 46.0000000000, 56.0000000000 46.0000000000, 65.0000000000 47.0000000000, 53.0000000000 47.0000000000, 56.0000000000 47.0000000000, 60.0000000000 47.0000000000, 65.0000000000 48.0000000000, 55.0000000000 48.0000000000, 58.0000000000 48.0000000000, 60.0000000000 48.0000000000, 64.0000000000 49.0000000000, 53.0000000000 49.0000000000, 56.0000000000 49.0000000000, 60.0000000000 49.0000000000, 65.0000000000 50.0000000000, 52.0000000000 50.0000000000, 55.0000000000 50.0000000000, 60.0000000000 50.0000000000, 67.0000000000 51.0000000000, 53.0000000000 51.0000000000, 56.0000000000 51.0000000000, 60.0000000000 51.0000000000, 70.0000000000 52.0000000000, 68.0000000000 53.0000000000, 63.0000000000 53.0000000000, 72.0000000000 54.0000000000, 65.0000000000 54.0000000000, 73.0000000000 55.0000000000, 61.0000000000 55.0000000000, 70.0000000000 56.0000000000, 44.0000000000 56.0000000000, 56.0000000000 57.0000000000, 63.0000000000 57.0000000000, 72.0000000000 58.0000000000, 60.0000000000 58.0000000000, 68.0000000000 59.0000000000, 56.0000000000 59.0000000000, 60.0000000000 59.0000000000, 63.0000000000 59.0000000000, 68.0000000000 60.0000000000, 58.0000000000 60.0000000000, 61.0000000000 60.0000000000, 63.0000000000 60.0000000000, 67.0000000000 61.0000000000, 56.0000000000 61.0000000000, 60.0000000000 61.0000000000, 63.0000000000 61.0000000000, 68.0000000000 62.0000000000, 55.0000000000 62.0000000000, 58.0000000000 62.0000000000, 63.0000000000 62.0000000000, 70.0000000000 63.0000000000, 56.0000000000 63.0000000000, 60.0000000000 63.0000000000, 63.0000000000 63.0000000000, 73.0000000000 64.0000000000, 72.0000000000 65.0000000000, 60.0000000000 65.0000000000, 63.0000000000 65.0000000000, 68.0000000000 65.0000000000, 75.0000000000 66.0000000000, 58.0000000000 66.0000000000, 61.0000000000 66.0000000000, 67.0000000000 66.0000000000, 75.0000000000 67.0000000000, 56.0000000000 67.0000000000, 60.0000000000 67.0000000000, 68.0000000000 67.0000000000, 75.0000000000 68.0000000000, 55.0000000000 68.0000000000, 58.0000000000 68.0000000000, 70.0000000000 68.0000000000, 75.0000000000 69.0000000000, 56.0000000000 69.0000000000, 73.0000000000 69.0000000000, 75.0000000000 70.0000000000, 72.0000000000 71.0000000000, 49.0000000000 71.0000000000, 58.0000000000 71.0000000000, 77.0000000000 72.0000000000, 51.0000000000 72.0000000000, 60.0000000000 72.0000000000, 68.0000000000 74.0000000000, 51.0000000000 74.0000000000, 61.0000000000 74.0000000000, 67.0000000000 74.0000000000, 70.0000000000 75.0000000000, 56.0000000000 75.0000000000, 60.0000000000 75.0000000000, 68.0000000000 77.0000000000, 79.0000000000 77.5000000000, 77.0000000000 78.0000000000, 51.0000000000 78.0000000000, 60.0000000000 78.0000000000, 68.0000000000 80.0000000000, 51.0000000000 80.0000000000, 61.0000000000 80.0000000000, 67.0000000000 80.0000000000, 70.0000000000 81.0000000000, 56.0000000000 81.0000000000, 60.0000000000 81.0000000000, 68.0000000000 83.0000000000, 72.0000000000 83.0000000000, 75.0000000000 84.0000000000, 73.0000000000 84.0000000000, 76.0000000000 85.0000000000, 55.0000000000 85.0000000000, 58.0000000000 85.0000000000, 70.0000000000 85.0000000000, 73.0000000000 86.0000000000, 58.0000000000 86.0000000000, 61.0000000000 87.0000000000, 72.0000000000 87.0000000000, 75.0000000000 88.0000000000, 56.0000000000 88.0000000000, 60.0000000000 88.0000000000, 68.0000000000 88.0000000000, 72.0000000000 89.0000000000, 60.0000000000 89.0000000000, 63.0000000000 90.0000000000, 75.0000000000 90.0000000000, 78.0000000000 91.0000000000, 57.0000000000 91.0000000000, 60.0000000000 91.0000000000, 72.0000000000 91.0000000000, 75.0000000000 92.0000000000, 60.0000000000 92.0000000000, 63.0000000000 93.0000000000, 73.0000000000 93.0000000000, 77.0000000000 94.0000000000, 58.0000000000 94.0000000000, 61.0000000000 94.0000000000, 70.0000000000 94.0000000000, 73.0000000000 95.0000000000, 61.0000000000 95.0000000000, 65.0000000000 96.0000000000, 53.0000000000 96.0000000000, 61.0000000000 96.0000000000, 65.0000000000 96.0000000000, 70.0000000000 98.0000000000, 53.0000000000 98.0000000000, 63.0000000000 98.0000000000, 69.0000000000 98.0000000000, 72.0000000000 99.0000000000, 58.0000000000 99.0000000000, 61.0000000000 99.0000000000, 70.0000000000 101.0000000000, 78.0000000000 101.5000000000, 77.0000000000 102.0000000000, 53.0000000000 102.0000000000, 61.0000000000 102.0000000000, 70.0000000000 104.0000000000, 53.0000000000 104.0000000000, 63.0000000000 104.0000000000, 69.0000000000 104.0000000000, 72.0000000000 105.0000000000, 58.0000000000 105.0000000000, 61.0000000000 105.0000000000, 70.0000000000 107.0000000000, 53.0000000000 107.0000000000, 63.0000000000 107.0000000000, 69.0000000000 107.0000000000, 73.0000000000 107.5000000000, 72.0000000000 108.0000000000, 58.0000000000 108.0000000000, 61.0000000000 108.0000000000, 70.0000000000 110.0000000000, 53.0000000000 110.0000000000, 63.0000000000 110.0000000000, 69.0000000000 110.0000000000, 73.0000000000 110.5000000000, 72.0000000000 111.0000000000, 58.0000000000 111.0000000000, 61.0000000000 111.0000000000, 70.0000000000 113.0000000000, 61.0000000000 113.0000000000, 73.0000000000 113.5000000000, 60.0000000000 113.5000000000, 72.0000000000 114.0000000000, 58.0000000000 114.0000000000, 70.0000000000 114.5000000000, 60.0000000000 114.5000000000, 72.0000000000 115.0000000000, 61.0000000000 115.0000000000, 73.0000000000 115.5000000000, 60.0000000000 115.5000000000, 72.0000000000 116.0000000000, 58.0000000000 116.0000000000, 70.0000000000 116.5000000000, 60.0000000000 116.5000000000, 72.0000000000 117.0000000000, 58.0000000000 117.0000000000, 70.0000000000 117.5000000000, 56.0000000000 117.5000000000, 68.0000000000 118.0000000000, 55.0000000000 118.0000000000, 67.0000000000 118.5000000000, 56.0000000000 118.5000000000, 68.0000000000 119.0000000000, 55.0000000000 119.0000000000, 67.0000000000 119.5000000000, 53.0000000000 119.5000000000, 65.0000000000 120.0000000000, 52.0000000000 120.0000000000, 64.0000000000 120.5000000000, 53.0000000000 120.5000000000, 65.0000000000 121.0000000000, 55.0000000000 121.0000000000, 67.0000000000 121.5000000000, 53.0000000000 121.5000000000, 65.0000000000 122.0000000000, 56.0000000000 122.0000000000, 68.0000000000 122.5000000000, 47.0000000000 122.5000000000, 59.0000000000 123.0000000000, 48.0000000000 123.0000000000, 60.0000000000 124.0000000000, 60.0000000000 125.0000000000, 60.0000000000 125.0000000000, 68.0000000000 126.0000000000, 61.0000000000 126.0000000000, 70.0000000000 127.0000000000, 58.0000000000 127.0000000000, 67.0000000000 128.0000000000, 58.0000000000 128.0000000000, 67.0000000000 128.0000000000, 76.0000000000 129.0000000000, 60.0000000000 129.0000000000, 68.0000000000 129.0000000000, 77.0000000000 130.0000000000, 56.0000000000 130.0000000000, 65.0000000000 130.0000000000, 80.0000000000 131.0000000000, 53.0000000000 131.0000000000, 56.0000000000 131.0000000000, 84.0000000000 132.0000000000, 52.0000000000 132.0000000000, 55.0000000000 132.0000000000, 85.0000000000 133.0000000000, 55.0000000000 133.0000000000, 58.0000000000 133.0000000000, 82.0000000000 134.0000000000, 55.0000000000 134.0000000000, 58.0000000000 134.0000000000, 82.0000000000 135.0000000000, 53.0000000000 135.0000000000, 56.0000000000 135.0000000000, 84.0000000000 136.0000000000, 56.0000000000 136.0000000000, 60.0000000000 136.0000000000, 80.0000000000 137.0000000000, 56.0000000000 137.0000000000, 60.0000000000 137.0000000000, 65.0000000000 137.0000000000, 80.0000000000 138.0000000000, 55.0000000000 138.0000000000, 58.0000000000 138.0000000000, 64.0000000000 138.0000000000, 82.0000000000 139.0000000000, 58.0000000000 139.0000000000, 61.0000000000 139.0000000000, 64.0000000000 139.0000000000, 79.0000000000 140.0000000000, 58.0000000000 140.0000000000, 61.0000000000 140.0000000000, 64.0000000000 140.0000000000, 79.0000000000 141.0000000000, 59.0000000000 141.0000000000, 62.0000000000 141.0000000000, 65.0000000000 141.0000000000, 80.0000000000 142.0000000000, 68.0000000000 142.0000000000, 77.0000000000 143.0000000000, 59.0000000000 143.0000000000, 62.0000000000 143.0000000000, 68.0000000000 143.0000000000, 77.0000000000 144.0000000000, 60.0000000000 144.0000000000, 68.0000000000 144.0000000000, 77.0000000000 146.0000000000, 60.0000000000 146.0000000000, 70.0000000000 146.0000000000, 76.0000000000 146.0000000000, 79.0000000000 147.0000000000, 65.0000000000 147.0000000000, 68.0000000000 147.0000000000, 77.0000000000 149.0000000000, 75.0000000000 149.5000000000, 73.0000000000 150.0000000000, 48.0000000000 150.0000000000, 56.0000000000 150.0000000000, 65.0000000000 152.0000000000, 48.0000000000 152.0000000000, 58.0000000000 152.0000000000, 64.0000000000 152.0000000000, 67.0000000000 153.0000000000, 53.0000000000 153.0000000000, 56.0000000000 153.0000000000, 65.0000000000 156.0000000000, 36.0000000000 156.0000000000, 48.0000000000 156.0000000000, 52.0000000000 156.0000000000, 55.0000000000 156.0000000000, 60.0000000000 159.0000000000, 41.0000000000 159.0000000000, 53.0000000000 occurrence2 437.0000000000, 60.0000000000 437.0000000000, 68.0000000000 438.0000000000, 61.0000000000 438.0000000000, 70.0000000000 439.0000000000, 58.0000000000 439.0000000000, 67.0000000000 440.0000000000, 53.0000000000 441.0000000000, 60.0000000000 441.0000000000, 68.0000000000 442.0000000000, 56.0000000000 442.0000000000, 65.0000000000 443.0000000000, 53.0000000000 443.0000000000, 56.0000000000 443.0000000000, 60.0000000000 443.0000000000, 65.0000000000 444.0000000000, 55.0000000000 444.0000000000, 58.0000000000 444.0000000000, 60.0000000000 444.0000000000, 64.0000000000 445.0000000000, 53.0000000000 445.0000000000, 56.0000000000 445.0000000000, 60.0000000000 445.0000000000, 65.0000000000 446.0000000000, 52.0000000000 446.0000000000, 55.0000000000 446.0000000000, 60.0000000000 446.0000000000, 67.0000000000 447.0000000000, 53.0000000000 447.0000000000, 56.0000000000 447.0000000000, 60.0000000000 447.0000000000, 70.0000000000 448.0000000000, 68.0000000000 449.0000000000, 63.0000000000 449.0000000000, 72.0000000000 450.0000000000, 65.0000000000 450.0000000000, 73.0000000000 451.0000000000, 61.0000000000 451.0000000000, 70.0000000000 452.0000000000, 44.0000000000 452.0000000000, 56.0000000000 453.0000000000, 63.0000000000 453.0000000000, 72.0000000000 454.0000000000, 60.0000000000 454.0000000000, 68.0000000000 455.0000000000, 56.0000000000 455.0000000000, 60.0000000000 455.0000000000, 63.0000000000 455.0000000000, 68.0000000000 456.0000000000, 58.0000000000 456.0000000000, 61.0000000000 456.0000000000, 63.0000000000 456.0000000000, 67.0000000000 457.0000000000, 56.0000000000 457.0000000000, 60.0000000000 457.0000000000, 63.0000000000 457.0000000000, 68.0000000000 458.0000000000, 55.0000000000 458.0000000000, 58.0000000000 458.0000000000, 63.0000000000 458.0000000000, 70.0000000000 459.0000000000, 56.0000000000 459.0000000000, 60.0000000000 459.0000000000, 63.0000000000 459.0000000000, 73.0000000000 460.0000000000, 72.0000000000 461.0000000000, 60.0000000000 461.0000000000, 63.0000000000 461.0000000000, 68.0000000000 461.0000000000, 75.0000000000 462.0000000000, 58.0000000000 462.0000000000, 61.0000000000 462.0000000000, 67.0000000000 462.0000000000, 75.0000000000 463.0000000000, 56.0000000000 463.0000000000, 60.0000000000 463.0000000000, 68.0000000000 463.0000000000, 75.0000000000 464.0000000000, 55.0000000000 464.0000000000, 58.0000000000 464.0000000000, 70.0000000000 464.0000000000, 75.0000000000 465.0000000000, 56.0000000000 465.0000000000, 73.0000000000 465.0000000000, 75.0000000000 466.0000000000, 72.0000000000 467.0000000000, 49.0000000000 467.0000000000, 58.0000000000 467.0000000000, 77.0000000000 468.0000000000, 51.0000000000 468.0000000000, 60.0000000000 468.0000000000, 68.0000000000 470.0000000000, 51.0000000000 470.0000000000, 61.0000000000 470.0000000000, 67.0000000000 470.0000000000, 70.0000000000 471.0000000000, 56.0000000000 471.0000000000, 60.0000000000 471.0000000000, 68.0000000000 473.0000000000, 79.0000000000 473.5000000000, 77.0000000000 474.0000000000, 51.0000000000 474.0000000000, 60.0000000000 474.0000000000, 68.0000000000 476.0000000000, 51.0000000000 476.0000000000, 61.0000000000 476.0000000000, 67.0000000000 476.0000000000, 70.0000000000 477.0000000000, 56.0000000000 477.0000000000, 60.0000000000 477.0000000000, 68.0000000000 479.0000000000, 72.0000000000 479.0000000000, 75.0000000000 480.0000000000, 73.0000000000 480.0000000000, 76.0000000000 481.0000000000, 55.0000000000 481.0000000000, 58.0000000000 481.0000000000, 70.0000000000 481.0000000000, 73.0000000000 482.0000000000, 58.0000000000 482.0000000000, 61.0000000000 483.0000000000, 72.0000000000 483.0000000000, 75.0000000000 484.0000000000, 56.0000000000 484.0000000000, 60.0000000000 484.0000000000, 68.0000000000 484.0000000000, 72.0000000000 485.0000000000, 60.0000000000 485.0000000000, 63.0000000000 486.0000000000, 75.0000000000 486.0000000000, 78.0000000000 487.0000000000, 57.0000000000 487.0000000000, 60.0000000000 487.0000000000, 72.0000000000 487.0000000000, 75.0000000000 488.0000000000, 60.0000000000 488.0000000000, 63.0000000000 489.0000000000, 73.0000000000 489.0000000000, 77.0000000000 490.0000000000, 58.0000000000 490.0000000000, 61.0000000000 490.0000000000, 70.0000000000 490.0000000000, 73.0000000000 491.0000000000, 61.0000000000 491.0000000000, 65.0000000000 492.0000000000, 53.0000000000 492.0000000000, 61.0000000000 492.0000000000, 65.0000000000 492.0000000000, 70.0000000000 494.0000000000, 53.0000000000 494.0000000000, 63.0000000000 494.0000000000, 69.0000000000 494.0000000000, 72.0000000000 495.0000000000, 58.0000000000 495.0000000000, 61.0000000000 495.0000000000, 70.0000000000 497.0000000000, 78.0000000000 497.5000000000, 77.0000000000 498.0000000000, 53.0000000000 498.0000000000, 61.0000000000 498.0000000000, 70.0000000000 500.0000000000, 53.0000000000 500.0000000000, 63.0000000000 500.0000000000, 69.0000000000 500.0000000000, 72.0000000000 501.0000000000, 58.0000000000 501.0000000000, 61.0000000000 501.0000000000, 70.0000000000 503.0000000000, 53.0000000000 503.0000000000, 63.0000000000 503.0000000000, 69.0000000000 503.0000000000, 73.0000000000 503.5000000000, 72.0000000000 504.0000000000, 58.0000000000 504.0000000000, 61.0000000000 504.0000000000, 70.0000000000 506.0000000000, 53.0000000000 506.0000000000, 63.0000000000 506.0000000000, 69.0000000000 506.0000000000, 73.0000000000 506.5000000000, 72.0000000000 507.0000000000, 58.0000000000 507.0000000000, 61.0000000000 507.0000000000, 70.0000000000 509.0000000000, 61.0000000000 509.0000000000, 73.0000000000 509.5000000000, 60.0000000000 509.5000000000, 72.0000000000 510.0000000000, 58.0000000000 510.0000000000, 70.0000000000 510.5000000000, 60.0000000000 510.5000000000, 72.0000000000 511.0000000000, 61.0000000000 511.0000000000, 73.0000000000 511.5000000000, 60.0000000000 511.5000000000, 72.0000000000 512.0000000000, 58.0000000000 512.0000000000, 70.0000000000 512.5000000000, 60.0000000000 512.5000000000, 72.0000000000 513.0000000000, 58.0000000000 513.0000000000, 70.0000000000 513.5000000000, 56.0000000000 513.5000000000, 68.0000000000 514.0000000000, 55.0000000000 514.0000000000, 67.0000000000 514.5000000000, 56.0000000000 514.5000000000, 68.0000000000 515.0000000000, 55.0000000000 515.0000000000, 67.0000000000 515.5000000000, 53.0000000000 515.5000000000, 65.0000000000 516.0000000000, 52.0000000000 516.0000000000, 64.0000000000 516.5000000000, 53.0000000000 516.5000000000, 65.0000000000 517.0000000000, 55.0000000000 517.0000000000, 67.0000000000 517.5000000000, 53.0000000000 517.5000000000, 65.0000000000 518.0000000000, 56.0000000000 518.0000000000, 68.0000000000 518.5000000000, 47.0000000000 518.5000000000, 59.0000000000 519.0000000000, 48.0000000000 519.0000000000, 60.0000000000 520.0000000000, 60.0000000000 521.0000000000, 60.0000000000 521.0000000000, 68.0000000000 522.0000000000, 61.0000000000 522.0000000000, 70.0000000000 523.0000000000, 58.0000000000 523.0000000000, 67.0000000000 524.0000000000, 58.0000000000 524.0000000000, 67.0000000000 524.0000000000, 76.0000000000 525.0000000000, 60.0000000000 525.0000000000, 68.0000000000 525.0000000000, 77.0000000000 526.0000000000, 56.0000000000 526.0000000000, 65.0000000000 526.0000000000, 80.0000000000 527.0000000000, 53.0000000000 527.0000000000, 56.0000000000 527.0000000000, 84.0000000000 528.0000000000, 52.0000000000 528.0000000000, 55.0000000000 528.0000000000, 85.0000000000 529.0000000000, 55.0000000000 529.0000000000, 58.0000000000 529.0000000000, 82.0000000000 530.0000000000, 55.0000000000 530.0000000000, 58.0000000000 530.0000000000, 82.0000000000 531.0000000000, 53.0000000000 531.0000000000, 56.0000000000 531.0000000000, 84.0000000000 532.0000000000, 56.0000000000 532.0000000000, 60.0000000000 532.0000000000, 80.0000000000 533.0000000000, 56.0000000000 533.0000000000, 60.0000000000 533.0000000000, 65.0000000000 533.0000000000, 80.0000000000 534.0000000000, 55.0000000000 534.0000000000, 58.0000000000 534.0000000000, 64.0000000000 534.0000000000, 82.0000000000 535.0000000000, 58.0000000000 535.0000000000, 61.0000000000 535.0000000000, 64.0000000000 535.0000000000, 79.0000000000 536.0000000000, 58.0000000000 536.0000000000, 61.0000000000 536.0000000000, 64.0000000000 536.0000000000, 79.0000000000 537.0000000000, 59.0000000000 537.0000000000, 62.0000000000 537.0000000000, 65.0000000000 537.0000000000, 80.0000000000 538.0000000000, 68.0000000000 538.0000000000, 77.0000000000 539.0000000000, 59.0000000000 539.0000000000, 62.0000000000 539.0000000000, 68.0000000000 539.0000000000, 77.0000000000 540.0000000000, 60.0000000000 540.0000000000, 68.0000000000 540.0000000000, 77.0000000000 542.0000000000, 60.0000000000 542.0000000000, 70.0000000000 542.0000000000, 76.0000000000 542.0000000000, 79.0000000000 543.0000000000, 65.0000000000 543.0000000000, 68.0000000000 543.0000000000, 77.0000000000 545.0000000000, 75.0000000000 545.5000000000, 73.0000000000 546.0000000000, 48.0000000000 546.0000000000, 56.0000000000 546.0000000000, 65.0000000000 548.0000000000, 48.0000000000 548.0000000000, 58.0000000000 548.0000000000, 64.0000000000 548.0000000000, 67.0000000000 549.0000000000, 53.0000000000 549.0000000000, 56.0000000000 549.0000000000, 65.0000000000 552.0000000000, 36.0000000000 552.0000000000, 48.0000000000 552.0000000000, 52.0000000000 552.0000000000, 55.0000000000 552.0000000000, 60.0000000000 555.0000000000, 41.0000000000 555.0000000000, 53.0000000000 mir_eval-0.8.2/tests/data/segment/000077500000000000000000000000001475740344600170525ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/segment/est00.lab000066400000000000000000000004661475740344600204730ustar00rootroot00000000000000# comment 0.000 6.000 A 6.000 14.800 B 14.800 26.400 C 26.400 34.800 B 34.800 46.600 C 46.600 52.600 D 52.600 58.000 E 58.000 67.200 F 67.200 85.800 G 85.800 95.000 B 95.000 107.200 C 107.200 114.000 D 114.000 119.000 E 119.000 127.800 F 127.800 133.800 D 133.800 138.400 E 138.400 147.400 H mir_eval-0.8.2/tests/data/segment/est01.lab000066400000000000000000000002431475740344600204650ustar00rootroot000000000000000.000 5.550 N1 5.550 17.264 B 17.264 23.116 N2 23.116 36.467 B 36.467 110.980 N3 110.980 154.076 A 154.076 197.265 A 197.265 241.232 A 241.232 291.979 N5 mir_eval-0.8.2/tests/data/segment/est02.lab000066400000000000000000000006261475740344600204730ustar00rootroot000000000000000.000 3.750 N1 3.750 17.415 A 17.415 33.158 A 33.158 48.913 A 48.913 64.656 A 64.656 80.399 A 80.399 96.142 A 96.142 111.897 A 111.897 127.628 A 127.628 141.398 A 141.398 164.525 N9 164.525 180.280 B 180.280 196.023 B 196.023 207.331 N10 207.331 224.061 A 224.061 239.804 A 239.804 253.574 A 253.574 261.457 N13 261.457 277.200 A 277.200 292.943 A 292.943 308.686 A 308.686 321.991 A mir_eval-0.8.2/tests/data/segment/est03.lab000066400000000000000000000003331475740344600204670ustar00rootroot000000000000000.000 32.009 Seg#001 32.009 61.652 Seg#002 61.652 100.252 Seg#003 100.252 123.652 Seg#004 123.652 159.359 Seg#005 159.359 191.094 Seg#006 191.094 217.223 Seg#007 217.223 262.742 Seg#008 262.742 288.000 Seg#009 mir_eval-0.8.2/tests/data/segment/est04.lab000066400000000000000000000003231475740344600204670ustar00rootroot000000000000000.000 19.522 Seg#001 19.522 31.083 Seg#002 31.083 52.390 Seg#003 52.390 69.346 Seg#004 69.346 89.580 Seg#005 89.580 96.447 Seg#006 96.447 106.017 Seg#007 106.017 121.020 Seg#008 121.020 139.833 Seg#009 mir_eval-0.8.2/tests/data/segment/est05.lab000066400000000000000000000007541475740344600205000ustar00rootroot000000000000000.000 27.408 Seg#001 27.408 68.069 Seg#002 68.069 94.822 Seg#003 94.822 128.659 Seg#004 128.659 147.444 Seg#005 147.444 160.784 Seg#006 160.784 193.152 Seg#007 193.152 232.371 Seg#008 232.371 251.103 Seg#009 251.103 255.417 Seg#010 255.417 266.069 Seg#011 266.069 276.230 Seg#012 276.230 279.931 Seg#013 279.931 302.550 Seg#014 302.550 315.533 Seg#015 315.533 339.258 Seg#016 339.258 341.066 Seg#017 341.066 366.039 Seg#018 366.039 402.347 Seg#019 402.347 431.962 Seg#020 mir_eval-0.8.2/tests/data/segment/est06.lab000066400000000000000000000003171475740344600204740ustar00rootroot000000000000000.000 0.499 Seg#001 0.499 3.823 Seg#002 3.823 28.706 Seg#003 28.706 42.635 Seg#004 42.635 66.801 Seg#005 66.801 79.868 Seg#006 79.868 108.669 Seg#007 108.669 117.563 Seg#008 117.563 124.552 Seg#009 mir_eval-0.8.2/tests/data/segment/est07.lab000066400000000000000000000002661475740344600205000ustar00rootroot000000000000000.000 58.249 C 58.249 74.409 C 74.409 86.529 B 86.529 112.788 B 112.788 120.868 D 120.868 159.247 B 159.247 175.406 C 175.406 183.486 D 183.486 211.765 B 211.765 227.733 C mir_eval-0.8.2/tests/data/segment/est08.lab000066400000000000000000000002371475740344600204770ustar00rootroot000000000000000.000 15.920 C 15.920 36.543 D 36.543 50.721 B 50.721 85.522 D 85.522 97.122 B 97.122 134.501 D 134.501 169.302 D 169.302 180.903 C 180.903 185.400 C mir_eval-0.8.2/tests/data/segment/est09.lab000066400000000000000000000002621475740344600204760ustar00rootroot000000000000000.000 10.902 B 10.902 43.431 D 43.431 51.563 B 51.563 59.695 B 59.695 94.257 D 94.257 102.389 B 102.389 120.686 D 120.686 128.818 D 128.818 155.248 D 155.248 182.000 B mir_eval-0.8.2/tests/data/segment/output00.json000066400000000000000000000014451475740344600214510ustar00rootroot00000000000000{"Precision@0.5": 0.3333333333333333, "Recall@0.5": 0.6, "F-measure@0.5": 0.42857142857142855, "Precision@3.0": 0.5, "Recall@3.0": 0.9, "F-measure@3.0": 0.6428571428571429, "Ref-to-est deviation": 0.3989999999999996, "Est-to-ref deviation": 2.8474999999999997, "Pairwise Precision": 0.8744274410225826, "Pairwise Recall": 0.4806828513199742, "Pairwise F-measure": 0.6203513883678935, "Rand Index": 0.8289077311831233, "Adjusted Rand Index": 0.5216688396951437, "Mutual Information": 1.1375211793868052, "Adjusted Mutual Information": 0.587379258678572, "Normalized Mutual Information": 0.6939260940391484, "NCE Over": 0.6199174381303865, "NCE Under": 0.8569466776016775, "NCE F-measure": 0.719411059330737, "V Precision": 0.590037137766286, "V Recall": 0.8161069755903478, "V-measure": 0.6848991073026666}mir_eval-0.8.2/tests/data/segment/output01.json000066400000000000000000000014601475740344600214470ustar00rootroot00000000000000{"Precision@0.5": 0.5454545454545454, "Recall@0.5": 0.4, "F-measure@0.5": 0.4615384615384615, "Precision@3.0": 0.5454545454545454, "Recall@3.0": 0.4, "F-measure@3.0": 0.4615384615384615, "Ref-to-est deviation": 13.036000000000001, "Est-to-ref deviation": 0.3359999999999985, "Pairwise Precision": 0.4993901657926098, "Pairwise Recall": 0.6122131984623336, "Pairwise F-measure": 0.5500761521812191, "Rand Index": 0.7541046088414509, "Adjusted Rand Index": 0.383287188265407, "Mutual Information": 0.8298500378099933, "Adjusted Mutual Information": 0.5476970266015448, "Normalized Mutual Information": 0.572695060137702, "NCE Over": 0.7123495615691824, "NCE Under": 0.6198417839591657, "NCE F-measure": 0.662883788470274, "V Precision": 0.59718972940023, "V Recall": 0.5492050779833786, "V-measure": 0.572193156831662}mir_eval-0.8.2/tests/data/segment/output02.json000066400000000000000000000015331475740344600214510ustar00rootroot00000000000000{"Precision@0.5": 0.08333333333333333, "Recall@0.5": 0.18181818181818182, "F-measure@0.5": 0.1142857142857143, "Precision@3.0": 0.20833333333333334, "Recall@3.0": 0.45454545454545453, "F-measure@3.0": 0.28571428571428575, "Ref-to-est deviation": 2.4509999999999934, "Est-to-ref deviation": 7.9399999999999995, "Pairwise Precision": 0.2672317510709366, "Pairwise Recall": 0.8168035627504561, "Pairwise F-measure": 0.4027098445443217, "Rand Index": 0.5319929982495624, "Adjusted Rand Index": 0.15746191367518272, "Mutual Information": 0.5875580090173058, "Adjusted Mutual Information": 0.31916695064697315, "Normalized Mutual Information": 0.4589766773608936, "NCE Over": 0.840693801923244, "NCE Under": 0.4364389820106126, "NCE F-measure": 0.5745863730219845, "V Precision": 0.6546216709365502, "V Recall": 0.32180356947221267, "V-measure": 0.4314914888375012}mir_eval-0.8.2/tests/data/segment/output03.json000066400000000000000000000015341475740344600214530ustar00rootroot00000000000000{"Precision@0.5": 0.18181818181818182, "Recall@0.5": 0.15384615384615385, "F-measure@0.5": 0.16666666666666669, "Precision@3.0": 0.5454545454545454, "Recall@3.0": 0.46153846153846156, "F-measure@3.0": 0.4999999999999999, "Ref-to-est deviation": 2.832000000000008, "Est-to-ref deviation": 1.6999999999999957, "Pairwise Precision": 0.7954247684219311, "Pairwise Recall": 0.20372577015066376, "Pairwise F-measure": 0.3243725890898819, "Rand Index": 0.6171646611901732, "Adjusted Rand Index": 0.17206814668546003, "Mutual Information": 0.7069980597186302, "Adjusted Mutual Information": 0.3228843702423049, "Normalized Mutual Information": 0.4718348883991217, "NCE Over": 0.36093183448445665, "NCE Under": 0.7989240945963056, "NCE F-measure": 0.4972292365742599, "V Precision": 0.32453331344779024, "V Recall": 0.6859947890878926, "V-measure": 0.44061745804392516}mir_eval-0.8.2/tests/data/segment/output04.json000066400000000000000000000014341475740344600214530ustar00rootroot00000000000000{"Precision@0.5": 0.2, "Recall@0.5": 0.5, "F-measure@0.5": 0.28571428571428575, "Precision@3.0": 0.3, "Recall@3.0": 0.75, "F-measure@3.0": 0.4285714285714285, "Ref-to-est deviation": 0.28300000000000125, "Est-to-ref deviation": 5.5510000000000055, "Pairwise Precision": 0.9259504360795314, "Pairwise Recall": 0.35218495476813033, "Pairwise F-measure": 0.5102836753967455, "Rand Index": 0.7634802520108155, "Adjusted Rand Index": 0.3932978729758545, "Mutual Information": 0.9753774660402063, "Adjusted Mutual Information": 0.46809981616245017, "Normalized Mutual Information": 0.6531566123520159, "NCE Over": 0.4989682378320722, "NCE Under": 0.9101726390597747, "NCE F-measure": 0.6445732222832662, "V Precision": 0.4697768990421939, "V Recall": 0.9081194948686581, "V-measure": 0.619224438273351}mir_eval-0.8.2/tests/data/segment/output05.json000066400000000000000000000015371475740344600214600ustar00rootroot00000000000000{"Precision@0.5": 0.38095238095238093, "Recall@0.5": 0.4444444444444444, "F-measure@0.5": 0.41025641025641024, "Precision@3.0": 0.47619047619047616, "Recall@3.0": 0.5555555555555556, "F-measure@3.0": 0.5128205128205129, "Ref-to-est deviation": 0.8845000000000027, "Est-to-ref deviation": 2.0920000000000414, "Pairwise Precision": 0.8936198585154119, "Pairwise Recall": 0.12923035832531626, "Pairwise F-measure": 0.22580591492517105, "Rand Index": 0.6057626818003455, "Adjusted Rand Index": 0.12775042299090225, "Mutual Information": 0.8118894611245795, "Adjusted Mutual Information": 0.2857955541041399, "Normalized Mutual Information": 0.49582597324973304, "NCE Over": 0.32765438933312685, "NCE Under": 0.9012719390410426, "NCE F-measure": 0.48059139102383136, "V Precision": 0.28728701796701817, "V Recall": 0.8557414027572561, "V-measure": 0.43016147506335445}mir_eval-0.8.2/tests/data/segment/output06.json000066400000000000000000000014311475740344600214520ustar00rootroot00000000000000{"Precision@0.5": 0.6, "Recall@0.5": 0.5, "F-measure@0.5": 0.5454545454545454, "Precision@3.0": 0.9, "Recall@3.0": 0.75, "F-measure@3.0": 0.8181818181818182, "Ref-to-est deviation": 0.37199999999999966, "Est-to-ref deviation": 0.1349999999999978, "Pairwise Precision": 0.7930906509181269, "Pairwise Recall": 0.42685807583415836, "Pairwise F-measure": 0.5550022583559169, "Rand Index": 0.7779261688615399, "Adjusted Rand Index": 0.4242977075000336, "Mutual Information": 1.035858923763909, "Adjusted Mutual Information": 0.5522348156967383, "Normalized Mutual Information": 0.6674317823737799, "NCE Over": 0.6238817066529372, "NCE Under": 0.856245768212157, "NCE F-measure": 0.7218244107457634, "V Precision": 0.5562329768516343, "V Recall": 0.8008607951366766, "V-measure": 0.6564987524332658}mir_eval-0.8.2/tests/data/segment/output07.json000066400000000000000000000015331475740344600214560ustar00rootroot00000000000000{"Precision@0.5": 0.4166666666666667, "Recall@0.5": 0.4166666666666667, "F-measure@0.5": 0.4166666666666667, "Precision@3.0": 0.4166666666666667, "Recall@3.0": 0.4166666666666667, "F-measure@3.0": 0.4166666666666667, "Ref-to-est deviation": 2.3029999999999973, "Est-to-ref deviation": 2.0904999999999916, "Pairwise Precision": 0.4223814364640884, "Pairwise Recall": 0.5491989347481521, "Pairwise F-measure": 0.47751363003359354, "Rand Index": 0.5964686214170435, "Adjusted Rand Index": 0.15784334203696132, "Mutual Information": 0.29666187029734625, "Adjusted Mutual Information": 0.2439028213895503, "Normalized Mutual Information": 0.2842593987759491, "NCE Over": 0.45120545761579733, "NCE Under": 0.4320411658955198, "NCE F-measure": 0.44141540262395995, "V Precision": 0.32978028695038797, "V Recall": 0.24502194033392954, "V-measure": 0.2811520274520297}mir_eval-0.8.2/tests/data/segment/output08.json000066400000000000000000000014561475740344600214630ustar00rootroot00000000000000{"Precision@0.5": 0.36363636363636365, "Recall@0.5": 0.2, "F-measure@0.5": 0.25806451612903225, "Precision@3.0": 0.7272727272727273, "Recall@3.0": 0.4, "F-measure@3.0": 0.5161290322580645, "Ref-to-est deviation": 5.225, "Est-to-ref deviation": 0.9710000000000036, "Pairwise Precision": 0.44839875095110193, "Pairwise Recall": 0.7850756399553728, "Pairwise F-measure": 0.5707892096558619, "Rand Index": 0.6475984889368591, "Adjusted Rand Index": 0.30779373726984793, "Mutual Information": 0.4046609393909751, "Adjusted Mutual Information": 0.29558782096748565, "Normalized Mutual Information": 0.3794279546668087, "NCE Over": 0.6084725966142581, "NCE Under": 0.4654090955931627, "NCE F-measure": 0.5274113208902106, "V Precision": 0.4847412878552114, "V Recall": 0.2969946575411979, "V-measure": 0.3683227658404129}mir_eval-0.8.2/tests/data/segment/output09.json000066400000000000000000000015231475740344600214570ustar00rootroot00000000000000{"Precision@0.5": 0.18181818181818182, "Recall@0.5": 0.18181818181818182, "F-measure@0.5": 0.18181818181818182, "Precision@3.0": 0.45454545454545453, "Recall@3.0": 0.45454545454545453, "F-measure@3.0": 0.45454545454545453, "Ref-to-est deviation": 2.003, "Est-to-ref deviation": 6.128999999999991, "Pairwise Precision": 0.30179861778785755, "Pairwise Recall": 0.6240045992191486, "Pairwise F-measure": 0.4068331629834462, "Rand Index": 0.509983392618762, "Adjusted Rand Index": 0.06878135700536266, "Mutual Information": 0.18722544508364072, "Adjusted Mutual Information": 0.12414774373232058, "Normalized Mutual Information": 0.1921195689816766, "NCE Over": 0.3540591969283001, "NCE Under": 0.32758171294161753, "NCE F-measure": 0.3403062126498245, "V Precision": 0.29486295945439467, "V Recall": 0.12517655270774686, "V-measure": 0.17574503215524864}mir_eval-0.8.2/tests/data/segment/raw_data/000077500000000000000000000000001475740344600206345ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/segment/raw_data/LEGEND000066400000000000000000000001461475740344600215160ustar00rootroot00000000000000Fold Track S_Over S_Under F_Pair P_Pair R_Pair RAND F@0.5 P@0.5 R@0.5 F@3.0 P@3.0 R@3.0 T_to_P P_to_T mir_eval-0.8.2/tests/data/segment/raw_data/cf5segmentsstructmrx09000016.js000066400000000000000000000020421475740344600262270ustar00rootroot00000000000000var cf5segmentsstructmrx09000016_data = [ [{o: 0.383, f: 7.332, l: "Intro", a: 0}, {o: 7.332, f: 27.109, l: "Verse", a: 1}, {o: 27.109, f: 47.015, l: "Verse", a: 0}, {o: 47.015, f: 67.123, l: "Bridge", a: 1}, {o: 67.123, f: 87.103, l: "Verse (Guitar Solo)", a: 0}, {o: 87.103, f: 107.649, l: "Verse", a: 1}, {o: 107.649, f: 128.114, l: "Bridge", a: 0}, {o: 128.114, f: 142.763, l: "Outro (fade-out)", a: 1}], [{o: 0, f: 6, l: "A", a: 0}, {o: 6, f: 14.8, l: "B", a: 1}, {o: 14.8, f: 26.4, l: "C", a: 0}, {o: 26.4, f: 34.8, l: "B", a: 1}, {o: 34.8, f: 46.6, l: "C", a: 0}, {o: 46.6, f: 52.6, l: "D", a: 1}, {o: 52.6, f: 58, l: "E", a: 0}, {o: 58, f: 67.2, l: "F", a: 1}, {o: 67.2, f: 85.8, l: "G", a: 0}, {o: 85.8, f: 95, l: "B", a: 1}, {o: 95, f: 107.2, l: "C", a: 0}, {o: 107.2, f: 114, l: "D", a: 1}, {o: 114, f: 119, l: "E", a: 0}, {o: 119, f: 127.8, l: "F", a: 1}, {o: 127.8, f: 133.8, l: "D", a: 0}, {o: 133.8, f: 138.4, l: "E", a: 1}, {o: 138.4, f: 147.4, l: "H", a: 0}] ]; var cf5segmentsstructmrx09000016_seriesNames = ["Ground-truth","Prediction"]; mir_eval-0.8.2/tests/data/segment/raw_data/cf5segmentsstructmrx09000016_results.txt000066400000000000000000000001711475740344600302140ustar00rootroot000000000000000 struct_mrx_09_000016 0.6220 0.8514 0.6192 0.8644 0.4823 0.8386 0.3704 0.2778 0.5556 0.5926 0.4444 0.8889 0.4490 4.5000 mir_eval-0.8.2/tests/data/segment/raw_data/cf6segmentssalami000970.js000066400000000000000000000017221475740344600252670ustar00rootroot00000000000000var cf6segmentssalami000970_data = [ [{o: 0.436, f: 111.316, l: "N", a: 0}, {o: 111.316, f: 124.345, l: "A", a: 1}, {o: 124.345, f: 137.409, l: "B", a: 0}, {o: 137.409, f: 154.178, l: "C", a: 1}, {o: 154.178, f: 167.193, l: "A", a: 0}, {o: 167.193, f: 180.41, l: "B", a: 1}, {o: 180.41, f: 197.305, l: "C", a: 0}, {o: 197.305, f: 210.605, l: "A", a: 1}, {o: 210.605, f: 224.052, l: "B", a: 0}, {o: 224.052, f: 241.258, l: "C", a: 1}, {o: 241.258, f: 254.268, l: "A", a: 0}, {o: 254.268, f: 267.205, l: "B", a: 1}, {o: 267.205, f: 292.617, l: "C'", a: 0}], [{o: 0, f: 5.55, l: "N1", a: 0}, {o: 5.55, f: 17.264, l: "B", a: 1}, {o: 17.264, f: 23.116, l: "N2", a: 0}, {o: 23.116, f: 36.467, l: "B", a: 1}, {o: 36.467, f: 110.98, l: "N3", a: 0}, {o: 110.98, f: 154.076, l: "A", a: 1}, {o: 154.076, f: 197.265, l: "A", a: 0}, {o: 197.265, f: 241.232, l: "A", a: 1}, {o: 241.232, f: 291.979, l: "N5", a: 0}] ]; var cf6segmentssalami000970_seriesNames = ["Ground-truth","Prediction"]; mir_eval-0.8.2/tests/data/segment/raw_data/cf6segmentssalami000970_results.txt000066400000000000000000000001621475740344600272500ustar00rootroot000000000000000 salami000970 0.6933 0.5805 0.5464 0.4956 0.6088 0.7543 0.4167 0.5000 0.3571 0.5000 0.6000 0.4286 13.0770 0.5370 mir_eval-0.8.2/tests/data/segment/raw_data/cf6segmentsstructmrx09000117.js000066400000000000000000000025521475740344600262400ustar00rootroot00000000000000var cf6segmentsstructmrx09000117_data = [ [{o: 0.2, f: 76.986, l: "Intro", a: 0}, {o: 76.986, f: 92.729, l: "Verse", a: 1}, {o: 92.729, f: 108.453, l: "Verse", a: 0}, {o: 108.453, f: 124.201, l: "Bridge", a: 1}, {o: 124.201, f: 139.933, l: "Refrain", a: 0}, {o: 139.933, f: 195.049, l: "Instrumental solo", a: 1}, {o: 195.049, f: 210.808, l: "Break", a: 0}, {o: 210.808, f: 226.512, l: "Ad Lib", a: 1}, {o: 226.512, f: 322.56, l: "Outro", a: 0}], [{o: 0, f: 3.75, l: "N1", a: 0}, {o: 3.75, f: 17.415, l: "A", a: 1}, {o: 17.415, f: 33.158, l: "A", a: 0}, {o: 33.158, f: 48.913, l: "A", a: 1}, {o: 48.913, f: 64.656, l: "A", a: 0}, {o: 64.656, f: 80.399, l: "A", a: 1}, {o: 80.399, f: 96.142, l: "A", a: 0}, {o: 96.142, f: 111.897, l: "A", a: 1}, {o: 111.897, f: 127.628, l: "A", a: 0}, {o: 127.628, f: 141.398, l: "A", a: 1}, {o: 141.398, f: 164.525, l: "N9", a: 0}, {o: 164.525, f: 180.28, l: "B", a: 1}, {o: 180.28, f: 196.023, l: "B", a: 0}, {o: 196.023, f: 207.331, l: "N10", a: 1}, {o: 207.331, f: 224.061, l: "A", a: 0}, {o: 224.061, f: 239.804, l: "A", a: 1}, {o: 239.804, f: 253.574, l: "A", a: 0}, {o: 253.574, f: 261.457, l: "N13", a: 1}, {o: 261.457, f: 277.2, l: "A", a: 0}, {o: 277.2, f: 292.943, l: "A", a: 1}, {o: 292.943, f: 308.686, l: "A", a: 0}, {o: 308.686, f: 321.991, l: "A", a: 1}] ]; var cf6segmentsstructmrx09000117_seriesNames = ["Ground-truth","Prediction"]; mir_eval-0.8.2/tests/data/segment/raw_data/cf6segmentsstructmrx09000117_results.txt000066400000000000000000000001721475740344600302200ustar00rootroot000000000000000 struct_mrx_09_000117 0.8303 0.4029 0.4005 0.2658 0.8119 0.5314 0.0606 0.0435 0.1000 0.3030 0.2174 0.5000 2.9320 12.3300 mir_eval-0.8.2/tests/data/segment/raw_data/mp1segmentssalami000119.js000066400000000000000000000016501475740344600253010ustar00rootroot00000000000000var mp1segmentssalami000119_data = [ [{o: 0.041, f: 5.478, l: "Z", a: 0}, {o: 5.478, f: 24.498, l: "A", a: 1}, {o: 24.498, f: 44.068, l: "B", a: 0}, {o: 44.068, f: 63.352, l: "C", a: 1}, {o: 63.352, f: 82.6, l: "B", a: 0}, {o: 82.6, f: 101.552, l: "C", a: 1}, {o: 101.552, f: 120.82, l: "B", a: 0}, {o: 120.82, f: 149.498, l: "C", a: 1}, {o: 149.498, f: 187.963, l: "C", a: 0}, {o: 187.963, f: 263.877, l: "C", a: 1}, {o: 263.877, f: 288.16, l: "Z", a: 0}], [{o: 0, f: 32.009, l: "Seg#001", a: 0}, {o: 32.009, f: 61.652, l: "Seg#002", a: 1}, {o: 61.652, f: 100.252, l: "Seg#003", a: 0}, {o: 100.252, f: 123.652, l: "Seg#004", a: 1}, {o: 123.652, f: 159.359, l: "Seg#005", a: 0}, {o: 159.359, f: 191.094, l: "Seg#006", a: 1}, {o: 191.094, f: 217.223, l: "Seg#007", a: 0}, {o: 217.223, f: 262.742, l: "Seg#008", a: 1}, {o: 262.742, f: 288, l: "Seg#009", a: 0}] ]; var mp1segmentssalami000119_seriesNames = ["Ground-truth","Prediction"]; mir_eval-0.8.2/tests/data/segment/raw_data/mp1segmentssalami000119_results.txt000066400000000000000000000001611475740344600272610ustar00rootroot000000000000000 salami000119 0.3301 0.7676 0.3200 0.7935 0.2004 0.6162 0.1818 0.2000 0.1667 0.5454 0.6000 0.5000 2.9813 2.2660 mir_eval-0.8.2/tests/data/segment/raw_data/mp1segmentsstructmrx09000084.js000066400000000000000000000012311475740344600262530ustar00rootroot00000000000000var mp1segmentsstructmrx09000084_data = [ [{o: 0, f: 34.752, l: "Part 1", a: 0}, {o: 34.752, f: 89.014, l: "Part 2", a: 1}, {o: 89.014, f: 123.498, l: "Part 3 (with complete ending)", a: 0}], [{o: 0, f: 19.522, l: "Seg#001", a: 0}, {o: 19.522, f: 31.083, l: "Seg#002", a: 1}, {o: 31.083, f: 52.39, l: "Seg#003", a: 0}, {o: 52.39, f: 69.346, l: "Seg#004", a: 1}, {o: 69.346, f: 89.58, l: "Seg#005", a: 0}, {o: 89.58, f: 96.447, l: "Seg#006", a: 1}, {o: 96.447, f: 106.017, l: "Seg#007", a: 0}, {o: 106.017, f: 121.02, l: "Seg#008", a: 1}, {o: 121.02, f: 139.833, l: "Seg#009", a: 0}] ]; var mp1segmentsstructmrx09000084_seriesNames = ["Ground-truth","Prediction"]; mir_eval-0.8.2/tests/data/segment/raw_data/mp1segmentsstructmrx09000084_results.txt000066400000000000000000000001721475740344600302420ustar00rootroot000000000000000 struct_mrx_09_000084 0.4981 0.9093 0.5342 0.9009 0.3797 0.8115 0.1429 0.1000 0.2500 0.4286 0.3000 0.7500 1.5221 11.3320 mir_eval-0.8.2/tests/data/segment/raw_data/mp2segmentssalami000666.js000066400000000000000000000031571475740344600253150ustar00rootroot00000000000000var mp2segmentssalami000666_data = [ [{o: 0.372, f: 23.49, l: "A", a: 0}, {o: 23.49, f: 147.424, l: "A", a: 1}, {o: 147.424, f: 171.866, l: "A", a: 0}, {o: 171.866, f: 183.994, l: "C", a: 1}, {o: 183.994, f: 196.361, l: "C", a: 0}, {o: 196.361, f: 208.201, l: "D", a: 1}, {o: 208.201, f: 220.353, l: "C", a: 0}, {o: 220.353, f: 232.328, l: "D", a: 1}, {o: 232.328, f: 254.136, l: "C", a: 0}, {o: 254.136, f: 266.072, l: "D", a: 1}, {o: 266.072, f: 278.6, l: "C", a: 0}, {o: 278.6, f: 302.37, l: "D", a: 1}, {o: 302.37, f: 315.045, l: "C", a: 0}, {o: 315.045, f: 327.589, l: "D", a: 1}, {o: 327.589, f: 341.35, l: "D", a: 0}, {o: 341.35, f: 431.961, l: "A", a: 1}], [{o: 0, f: 27.408, l: "Seg#001", a: 0}, {o: 27.408, f: 68.069, l: "Seg#002", a: 1}, {o: 68.069, f: 94.822, l: "Seg#003", a: 0}, {o: 94.822, f: 128.659, l: "Seg#004", a: 1}, {o: 128.659, f: 147.444, l: "Seg#005", a: 0}, {o: 147.444, f: 160.784, l: "Seg#006", a: 1}, {o: 160.784, f: 193.152, l: "Seg#007", a: 0}, {o: 193.152, f: 232.371, l: "Seg#008", a: 1}, {o: 232.371, f: 251.103, l: "Seg#009", a: 0}, {o: 251.103, f: 255.417, l: "Seg#010", a: 1}, {o: 255.417, f: 266.069, l: "Seg#011", a: 0}, {o: 266.069, f: 276.23, l: "Seg#012", a: 1}, {o: 276.23, f: 279.931, l: "Seg#013", a: 0}, {o: 279.931, f: 302.55, l: "Seg#014", a: 1}, {o: 302.55, f: 315.533, l: "Seg#015", a: 0}, {o: 315.533, f: 339.258, l: "Seg#016", a: 1}, {o: 339.258, f: 341.066, l: "Seg#017", a: 0}, {o: 341.066, f: 366.039, l: "Seg#018", a: 1}, {o: 366.039, f: 402.347, l: "Seg#019", a: 0}, {o: 402.347, f: 431.962, l: "Seg#020", a: 1}] ]; var mp2segmentssalami000666_seriesNames = ["Ground-truth","Prediction"]; mir_eval-0.8.2/tests/data/segment/raw_data/mp2segmentssalami000666_results.txt000066400000000000000000000001611475740344600272710ustar00rootroot000000000000000 salami000666 0.3285 0.8827 0.2194 0.8914 0.1251 0.6058 0.4210 0.3810 0.4706 0.5263 0.4762 0.5882 1.2814 2.0915 mir_eval-0.8.2/tests/data/segment/raw_data/mp2segmentsstructmrx09000132.js000066400000000000000000000017061475740344600262550ustar00rootroot00000000000000var mp2segmentsstructmrx09000132_data = [ [{o: 0.384, f: 3.686, l: "Intro", a: 0}, {o: 3.686, f: 15.372, l: "Verse", a: 1}, {o: 15.372, f: 27.121, l: "Verse", a: 0}, {o: 27.121, f: 42.51, l: "Refrain", a: 1}, {o: 42.51, f: 54.285, l: "Verse", a: 0}, {o: 54.285, f: 66.194, l: "Verse", a: 1}, {o: 66.194, f: 81.67, l: "Refrain", a: 0}, {o: 81.67, f: 93.143, l: "Verse (Guitar Solo)", a: 1}, {o: 93.143, f: 108.536, l: "Refrain", a: 0}, {o: 108.536, f: 119.267, l: "Outro (fade out)", a: 1}], [{o: 0, f: 0.499, l: "Seg#001", a: 0}, {o: 0.499, f: 3.823, l: "Seg#002", a: 1}, {o: 3.823, f: 28.706, l: "Seg#003", a: 0}, {o: 28.706, f: 42.635, l: "Seg#004", a: 1}, {o: 42.635, f: 66.801, l: "Seg#005", a: 0}, {o: 66.801, f: 79.868, l: "Seg#006", a: 1}, {o: 79.868, f: 108.669, l: "Seg#007", a: 0}, {o: 108.669, f: 117.563, l: "Seg#008", a: 1}, {o: 117.563, f: 124.552, l: "Seg#009", a: 0}] ]; var mp2segmentsstructmrx09000132_seriesNames = ["Ground-truth","Prediction"]; mir_eval-0.8.2/tests/data/segment/raw_data/mp2segmentsstructmrx09000132_results.txt000066400000000000000000000001711475740344600302340ustar00rootroot000000000000000 struct_mrx_09_000132 0.6241 0.8438 0.5560 0.7901 0.4289 0.7960 0.3810 0.4000 0.3636 0.7619 0.8000 0.7273 1.5851 0.4952 mir_eval-0.8.2/tests/data/segment/raw_data/rbh3segmentssalami000025.js000066400000000000000000000016031475740344600254340ustar00rootroot00000000000000var rbh3segmentssalami000025_data = [ [{o: 0.488, f: 34.145, l: "A", a: 0}, {o: 34.145, f: 62.367, l: "B", a: 1}, {o: 62.367, f: 86.586, l: "B", a: 0}, {o: 86.586, f: 102.772, l: "C", a: 1}, {o: 102.772, f: 126.972, l: "B", a: 0}, {o: 126.972, f: 143.189, l: "C", a: 1}, {o: 143.189, f: 159.275, l: "D", a: 0}, {o: 159.275, f: 183.465, l: "B", a: 1}, {o: 183.465, f: 193.567, l: "C", a: 0}, {o: 193.567, f: 227.796, l: "C", a: 1}], [{o: 0, f: 58.249, l: "C", a: 0}, {o: 58.249, f: 74.409, l: "C", a: 1}, {o: 74.409, f: 86.529, l: "B", a: 0}, {o: 86.529, f: 112.788, l: "B", a: 1}, {o: 112.788, f: 120.868, l: "D", a: 0}, {o: 120.868, f: 159.247, l: "B", a: 1}, {o: 159.247, f: 175.406, l: "C", a: 0}, {o: 175.406, f: 183.486, l: "D", a: 1}, {o: 183.486, f: 211.765, l: "B", a: 0}, {o: 211.765, f: 227.733, l: "C", a: 1}] ]; var rbh3segmentssalami000025_seriesNames = ["Ground-truth","Prediction"]; mir_eval-0.8.2/tests/data/segment/raw_data/rbh3segmentssalami000025_results.txt000066400000000000000000000001611475740344600274160ustar00rootroot000000000000000 salami000025 0.4482 0.3491 0.4746 0.4203 0.5451 0.5955 0.4546 0.4546 0.4546 0.4546 0.4546 0.4546 4.1181 4.1181 mir_eval-0.8.2/tests/data/segment/raw_data/rbh3segmentssalami000068.js000066400000000000000000000022011475740344600254360ustar00rootroot00000000000000var rbh3segmentssalami000068_data = [ [{o: 0.139, f: 5.41, l: "A", a: 0}, {o: 5.41, f: 15.581, l: "B", a: 1}, {o: 15.581, f: 25.983, l: "C", a: 0}, {o: 25.983, f: 31.045, l: "D", a: 1}, {o: 31.045, f: 41.583, l: "C", a: 0}, {o: 41.583, f: 51.733, l: "D", a: 1}, {o: 51.733, f: 62.009, l: "C", a: 0}, {o: 62.009, f: 67.272, l: "D", a: 1}, {o: 67.272, f: 88.013, l: "E", a: 0}, {o: 88.013, f: 98.093, l: "B", a: 1}, {o: 98.093, f: 108.558, l: "C", a: 0}, {o: 108.558, f: 113.773, l: "D", a: 1}, {o: 113.773, f: 124.018, l: "C", a: 0}, {o: 124.018, f: 134.292, l: "D", a: 1}, {o: 134.292, f: 144.632, l: "C", a: 0}, {o: 144.632, f: 149.704, l: "D", a: 1}, {o: 149.704, f: 170.478, l: "C", a: 0}, {o: 170.478, f: 185.469, l: "B", a: 1}], [{o: 0, f: 15.92, l: "C", a: 0}, {o: 15.92, f: 36.543, l: "D", a: 1}, {o: 36.543, f: 50.721, l: "B", a: 0}, {o: 50.721, f: 85.522, l: "D", a: 1}, {o: 85.522, f: 97.122, l: "B", a: 0}, {o: 97.122, f: 134.501, l: "D", a: 1}, {o: 134.501, f: 169.302, l: "D", a: 0}, {o: 169.302, f: 180.903, l: "C", a: 1}, {o: 180.903, f: 185.4, l: "C", a: 0}] ]; var rbh3segmentssalami000068_seriesNames = ["Ground-truth","Prediction"]; mir_eval-0.8.2/tests/data/segment/raw_data/rbh3segmentssalami000068_results.txt000066400000000000000000000001611475740344600274250ustar00rootroot000000000000000 salami000068 0.6091 0.4092 0.5674 0.4452 0.7823 0.6475 0.2759 0.4000 0.2105 0.5517 0.8000 0.4210 5.4102 0.9919 mir_eval-0.8.2/tests/data/segment/raw_data/rbh4segmentsstructmrx09000020.js000066400000000000000000000016231475740344600264100ustar00rootroot00000000000000var rbh4segmentsstructmrx09000020_data = [ [{o: 0.245, f: 3.424, l: "Intro", a: 0}, {o: 3.424, f: 27.753, l: "Verse", a: 1}, {o: 27.753, f: 52.156, l: "Refrain", a: 0}, {o: 52.156, f: 75.851, l: "Verse", a: 1}, {o: 75.851, f: 100.386, l: "Refrain", a: 0}, {o: 100.386, f: 122.004, l: "Verse (instrumental)", a: 1}, {o: 122.004, f: 137.268, l: "Bridge", a: 0}, {o: 137.268, f: 161.414, l: "Refrain", a: 1}, {o: 161.414, f: 179.425, l: "Outro", a: 0}], [{o: 0, f: 10.902, l: "B", a: 0}, {o: 10.902, f: 43.431, l: "D", a: 1}, {o: 43.431, f: 51.563, l: "B", a: 0}, {o: 51.563, f: 59.695, l: "B", a: 1}, {o: 59.695, f: 94.257, l: "D", a: 0}, {o: 94.257, f: 102.389, l: "B", a: 1}, {o: 102.389, f: 120.686, l: "D", a: 0}, {o: 120.686, f: 128.818, l: "D", a: 1}, {o: 128.818, f: 155.248, l: "D", a: 0}, {o: 155.248, f: 182, l: "B", a: 1}] ]; var rbh4segmentsstructmrx09000020_seriesNames = ["Ground-truth","Prediction"]; mir_eval-0.8.2/tests/data/segment/raw_data/rbh4segmentsstructmrx09000020_results.txt000066400000000000000000000001711475740344600303710ustar00rootroot000000000000000 struct_mrx_09_000020 0.3517 0.2743 0.4005 0.2959 0.6193 0.5149 0.0952 0.0909 0.1000 0.4762 0.4546 0.5000 2.9997 6.1291 mir_eval-0.8.2/tests/data/segment/ref00.lab000066400000000000000000000003051475740344600204440ustar00rootroot000000000000000.383 7.332 Intro 7.332 27.109 Verse 27.109 47.015 Verse 47.015 67.123 Bridge 67.123 87.103 Verse (Guitar Solo) 87.103 107.649 Verse 107.649 128.114 Bridge 128.114 142.763 Outro (fade-out) mir_eval-0.8.2/tests/data/segment/ref01.lab000066400000000000000000000003661475740344600204540ustar00rootroot000000000000000.436 111.316 N 111.316 124.345 A 124.345 137.409 B 137.409 154.178 C 154.178 167.193 A 167.193 180.410 B 180.410 197.305 C 197.305 210.605 A 210.605 224.052 B 224.052 241.258 C 241.258 254.268 A 254.268 267.205 B 267.205 292.617 C' mir_eval-0.8.2/tests/data/segment/ref02.lab000066400000000000000000000003311475740344600204450ustar00rootroot000000000000000.200 76.986 Intro 76.986 92.729 Verse 92.729 108.453 Verse 108.453 124.201 Bridge 124.201 139.933 Refrain 139.933 195.049 Instrumental solo 195.049 210.808 Break 210.808 226.512 Ad Lib 226.512 322.560 Outro mir_eval-0.8.2/tests/data/segment/ref03.lab000066400000000000000000000003031475740344600204450ustar00rootroot000000000000000.041 5.478 Z 5.478 24.498 A 24.498 44.068 B 44.068 63.352 C 63.352 82.600 B 82.600 101.552 C 101.552 120.820 B 120.820 149.498 C 149.498 187.963 C 187.963 263.877 C 263.877 288.160 Z mir_eval-0.8.2/tests/data/segment/ref04.lab000066400000000000000000000001311475740344600204450ustar00rootroot000000000000000.000 34.752 Part 1 34.752 89.014 Part 2 89.014 123.498 Part 3 (with complete ending) mir_eval-0.8.2/tests/data/segment/ref05.lab000066400000000000000000000004541475740344600204560ustar00rootroot000000000000000.372 23.490 A 23.490 147.424 A 147.424 171.866 A 171.866 183.994 C 183.994 196.361 C 196.361 208.201 D 208.201 220.353 C 220.353 232.328 D 232.328 254.136 C 254.136 266.072 D 266.072 278.600 C 278.600 302.370 D 302.370 315.045 C 315.045 327.589 D 327.589 341.350 D 341.350 431.961 A mir_eval-0.8.2/tests/data/segment/ref06.lab000066400000000000000000000003611475740344600204540ustar00rootroot000000000000000.384 3.686 Intro 3.686 15.372 Verse 15.372 27.121 Verse 27.121 42.510 Refrain 42.510 54.285 Verse 54.285 66.194 Verse 66.194 81.670 Refrain 81.670 93.143 Verse (Guitar Solo) 93.143 108.536 Refrain 108.536 119.267 Outro (fade out) mir_eval-0.8.2/tests/data/segment/ref07.lab000066400000000000000000000002661475740344600204610ustar00rootroot000000000000000.488 34.145 A 34.145 62.367 B 62.367 86.586 B 86.586 102.772 C 102.772 126.972 B 126.972 143.189 C 143.189 159.275 D 159.275 183.465 B 183.465 193.567 C 193.567 227.796 C mir_eval-0.8.2/tests/data/segment/ref08.lab000066400000000000000000000004761475740344600204650ustar00rootroot000000000000000.139 5.410 A 5.410 15.581 B 15.581 25.983 C 25.983 31.045 D 31.045 41.583 C 41.583 51.733 D 51.733 62.009 C 62.009 67.272 D 67.272 88.013 E 88.013 98.093 B 98.093 108.558 C 108.558 113.773 D 113.773 124.018 C 124.018 134.292 D 134.292 144.632 C 144.632 149.704 D 149.704 170.478 C 170.478 185.469 B mir_eval-0.8.2/tests/data/segment/ref09.lab000066400000000000000000000003311475740344600204540ustar00rootroot000000000000000.245 3.424 Intro 3.424 27.753 Verse 27.753 52.156 Refrain 52.156 75.851 Verse 75.851 100.386 Refrain 100.386 122.004 Verse (instrumental) 122.004 137.268 Bridge 137.268 161.414 Refrain 161.414 179.425 Outro mir_eval-0.8.2/tests/data/separation/000077500000000000000000000000001475740344600175555ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/separation/est01/000077500000000000000000000000001475740344600205115ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/separation/est01/0.wav000066400000000000000000000372541475740344600214020ustar00rootroot00000000000000RIFF>WAVEfmt @>data>RUsf 9Yp| l>V7`- X {S-"&/PWPZz  ( O2 a1hEO $p9k O  f W [k "$W8 <c #'( @ U-kuTDAV)a4OE "  {Bs#ck^;d` Dx `%z!fm-Jw^#ܟgcHF toDvJZW/Q8 # FpGher :l lnA>Z-6(}GWM[ KA dOVHx`%RD @j^ W E!!u~!MumLjpه. |8}4%{G"SU+3 Y! )`w|uBs O *>X &()R+.'h #x=ޣ G.]:lָ x s&A/m,2)#"^"b  ?w 1xG&sN`j$^$ w (K*j 7 !#""N ϑaR!h7!yQB9480&&i" k_"aa%i>5z ? L P(- #xcd3 ye {2cg r e&  Egv {$"T6M L ӮڎX: N gnB^Fb"{/K=>,Bwhֳ=**- 1  T k @qa g ^OrC}<y&:(? YeHI7 :`>q_q7ZdBh @ MCo o _ ?;Cwh d,Hl,#-B d'#9 +P7 q޻ jjH^ s L"3: #aO m_rۋݮLNa* - ;  8 o ;cm&88c=b!%%I!c>JDZ{PKx(G-/btb &./~yT TbbJav"B p(,*!, @ah?C%#Ccd 4xBS &@]lV@XO)C *I=%SDo Wh qEEףנkSY!E p%(w)$j MiE ? I ((w a[Q A D PV `S@ cy~++"S r0 !6wc| ;? pY_> ,Kv bf%xk6@)2 gC *"7,U U "~ )}]w)?&x?e5^B j \ TXF | sgT"<(ws3 p v4(5Qu8'5z9Cw N'rm  > x % C!1FJmZ N by}#S { 4.4vm$&143b+1 86CO 9 N|e1<rn+k'}C<6K- , lG l ^i=1 L'z#jgT sc6,o/&bJYJ]4|Md v( JZl ,9B |cT 3 M erb  C P?1ۛ|e VQEw{ 8&A+N%|9/ YIMWN) p V#| nxWz0)N>/:k@K!q**@& 9 :L >,o*=Jd2)\ b w LTArq &# kl(Fhzz|P(\$c$f[3` "p T hY6[ rrLC&+&<h/X <i["  W HSXP!C x4~m>8maYUY<cMI me[g !(K%H  ,[ߦV#\p  ,) 3 g,2/'N d c_k  McL  sWSE=0rX2 8)$u|. +n{. X%p|'R #]U5 x 0vWeYT6r FB}Xm(c*! ZU54n (^}v6\"t   E 3| eDKst`o  Q }n c UN%k]%mzH &ca0:J 'X%Mx  wCu}\ae'eVJ]E)g2N1k)z=,k @ޞO b8Cp;XdZa `(Y( <8u~[ ! =G s X5Zy ~u9@C. ;  9qݷQl G2#SVJe?)0(iY :HC NOx"b$ L~'mZfrf  f}du :" K)T\YE %)J#l *) ?`hM2nSMDt5 JtOA17j b?(ߞ  C#K'"56-Z!aF3fQ-FQH mS2O6.!c & i %`2]@  8J`)k2RB(~ hB%:X` L)=> >#1HUZ$$`# ?)\h{E}r!9%zG]w 7Ee3 Lr  q v%L%, ](O>u `g q  ?&*(z x  ) B hy;Eg`MGb1+L   5i9y;H _DK/*T>J^  GfI`-?`.mw, f PJ ^`P4l{c;/0V{@Z- Z  ( s P 5"|5P$& W 5s^G  k^AIp;O?b- s  'v[, n U)p{;Sl\w1()Mj"  IE.=# 1L 7 ,`;gPb1 /   {Z8XS$ #2MvIJ; rpl37 sUJ B Hz;vr &*%k Ml.ZY zY {THJO#!dP4< .")[[ ) ,e?? Ws)spo&%x L\3 !K RU2 =~(h D,9LsP A ht&! & )]B 5 %jp3;x!,( *+3$"2  zxOf6g[A@#)%E AHtSA۸T*K $&L&D ! A A"A Hy3P!P.Dި:Pl ; p:@ _ 9:*f -}+A 'D+&Fp8 |({wuS FdJd}#"++ #r$6A @glBzP[}<G}7DU l'x153P+X elGؖ*L.qP K 7M%*&uf &|:c}p e 3  0 tl 5w -@  1O z}M D I Xe g:rS4LDf'%,()gTE(tXS;4  0;D0~[e "U[aO|}>2y;kT UM )<-T&[ Gdܼبyk n t[bb V w N -2  h\|S\/m^g63U )w0> 1  7xel&g&ue -'( xUAr g} 1c'j\d_kqXX 8XuYiR{@$hy*>]183+Rak 0 N u\KH 35)-\9#(&3Bc/ eGCLAh}pBXZez< %&#wh JL~7T=-wZn^$"J"~ K ;L{;|#! @\~_ ݋z+7 ti .j 1 Xj.F 7 ?9_Ox?pp   J x jo:^ nC^ii$,V=H&!#   ' w. vp\cjl_;#O& TZ iK$VmAw w9Zf[Jh$*M bm.$ o1s D :\Hm*XRi \Ym@ A  3 e$|}K$ " :^+{XR#6L"S&!X6 5=6UjRnr~` ]  51as& 5Q1*zu T @|-;qm 6 7w{76h|U'jU !i p{ G DjV,VwD. s}m ,0-"2& R#Hvm| #a [ P iR |)9uV*N  2-Y @ U \ + @-l %XEo]"P{+d 3#[CU kq, |1 VP{N۷ۮyz&&Z*(>#S$*,.k*1!y v38'S c 5 4]YЉh+C w -dP-r-=WAP:d-m T]L%߼G,` }hz  H  v FS RX:lUw'ؘݣ = ym= )\3^1"*(o!F2i,cT)@B  p "3 kIf!QN&S[y`7e'%&:   fF I W @ iw_}n1  ;^Gajbc z I/ ? l = r#L޶t \Sd| E|4K*w,1+ L UP C[6 QwE! ~d 8Tlngg  } b=:jLU b~ )_M CqE $R%-h#F+gF{b  ek+z?  r :E3vVKT  z ;;`* "Xp1- oG7 % W C i RSX3R  _b?=sQT#p 7M "+ Ud= #2z|^4o"d  (Mp6ެ !!u  I '`Y1z ++-hTJ]DV$*& k jlt)Tu k f Un@ue-frwz @eF)'(t = Do`h~8 '0%N:}*Ot\ - ` n Jd  Z1w8pZZ |x(,lW rDe- s?"n%=, '{, (~$#yo `j}55%at0LpSr@rk v S7l` "} (LV^IH-d / OlHTcsOW1 0   h v!n ,7u@Yc^?bnqV=B G h Uc$mD| P7;  (c  yz7?pW 7d`"xcvQ *o4_"n~ TQpZ>N ir?T Zh 2|T  lJw&N6AXV= Bf99dZ~[4>o $>}2^n83NGt"]N* Z Ue317\A I [ Q)0 c"f'-1(F "80 Y# zKc 3`*E x,+46rs3 @W>%Pi`r(at  nqN *Y/ D5+Bc)fG;_G@mir_eval-0.8.2/tests/data/separation/est01/1.wav000066400000000000000000000372541475740344600214030ustar00rootroot00000000000000RIFF>WAVEfmt @>data>0D&*9ם DK)r1 *'J3 B&o82)84 e8C` ư&)2 Zy`M6#+p MAwF,>H";U~D ۳TqP2X^K.-R? FNatVIVm=b^U]ߦʛ|X|baM22qȨNΧ >?O<=[FUb@ ,y6Nj9.2= &B,܀̶ŦO 6Kek Htߗ$p\: WH ȏ7x 1_c? G2#ω KZ[R]œs2>1 JrZ{\~ 'bug I"mk׽Di2aLKxky޿ ; 8rJ ibm1 Ċ py`<qՖK*މSݍs#1RXM$ 8 o1@KhQ_ :(Uod3Rw\O^h$×!A1Mgh[`bl' zi8kEɐ;W 7QfP% ӺgXt DnjdPv=42L c9ձd`Œc=fECS/iPF_X07}cpuvŵ#*_5Iɇ< !E /;[vI $@*@gFY3\ϝ[%`߰uFq&{&$pUBL`JE= \"߆ݠC=$PXgp{uoړAGPۮSM{;Abډ!c9ZY Yvp,a{hž j`BMEC` ; .  v}ayߜHF "s߈`g|NC#O 5'X6UDy! +3ލ}5/ξ~)pQݭ G]ܛv]s0n۱c|p?CUU4XO_&U[4jMW%ߎCբ>xr"#K܌Z^̯e;p \&ۤ[r^^ó)& m\ m,ķņDq & (D ز祲E &(!h 'XձŅݟ;ƈ] ").)i#Am$oxM p"^)0-߷mS !&/-Dڮ!ŢԀg [#**bIR ͫ@x)%4%?T~ YȟޞjΫx_R EK}4̠'  =OF4(1!`!*471 9ݙoޗ/gOϟ!"U J)t}ۘl˹]ZΒ!W#+ f^ڲu"ۨ# |0gݢib|4ņMʬ!Htܹ` ʊ:w+za߆'ʁ/_߲T&1epo_ސ^Vmu V`9tNj +~$ߣݞּ, %#/T=50DP* 4 ݖqԸű/ 5DKM_0©έ q#TA7+sr{ay/~i%ÕV5LtbB"c wtKJƐ^[D&*hdӭuʸ+tRqJ \2a$!yƳ,7ٽ3'G6ŁկD oU .S܄˸äö* yQOC tֻ,ηgmpвcR,KoȞ,+^Y6֢ʃ\X:E ̪i՟ Vaλ0 u Rvsޭߜ!Н3<0!j6K})(j"~ߊ F۳Ұ^v^"@ztܖyumKI!,pF/s_5: $QA7IٚZ¾! ]:mWͽ(X;!ݠޥ3UӻǺu++!*'ܬ¶"j5"$(7ޠah".{߾U1vQOֳvŎ" J%# 0~L'Ԫ!&  %گ] X!/ m C.ߺOߵOD<ڦUz !|!߽݋KIkώ \!#ML9{a /۹r !$K:4aسی't*t* %5mj"w.a ڋj:Ɋk&~3ړ)J^4St{&u<۱+ {3IcpŬ+%A܈%Tݱȁni$inv,֛ʁ38$v(QPi,̍`R#> ;[G7WQÌ`#9! 9f=ܦ$y߅SmһǷ3 u.y# ߹==@9/'! tv|J K !r|0k{>"}ހٍт %?6"߅w#4 Ө´J!(g)CI=ԥZ~ S{ܬ͊śsB J,&eb pr"gڹ/ĩӥ x.4/l3ތϴ,u @u_oԩ'_G`3 vX zݳO @Bv9HB+B!I^Qܼ'ݺHW3  yݕ MږʗFA+; SS C,jJiD#kjHx ؼ.KHԶɈ.2 / \;s|ؓڛṂ[ gX:Y f,7٣ςǚ޶s{5;ZٓJ)үw#Q^PڪG?Ii t`<ڙ[ש̌šf"nhBi/.$=ƫ #d[:dn,A;rܛvȁ X NU615Ņ2NTW*}8972g'ۥކfɞ~#s(ޠݜsX|| D܊ޭ/ F vxب۲͏ Yژoϭn0ozHq%߀zz}(ي@Dg T/?ޙ55DN gR)"ۿ١u˧Y8 ^u$7{(fD&ZB-aQڂߌn8$B-"LٴޭޏəƔӊ' #`1%ًNL+KB5 bݕ[ۂޯ0+ɟRU qi[!,ݩܰҕZ{O 5b3 ޤ֍o N&4pܗqMŦ۞Q!#&\ۓ;P`V ^ u(O+Ybޟz˂7ۭ\y/(M%t:ܳ-2\  >#iߎLGIg1O^܍٦| tn(C"ګOuzSgCPۥl1MNJӬ.  0O1@ VmWۭڈڪ#4 "nhMUvfFtvI`?оǪah !K8A[ڲz?-# qMnKK̟RsgV35 1K׊ƶq-noڣ"@۞ՖʄoAWA~&qjţƓYW}lxvJZԻsú΢z:? 5e l&ݨ/a؃M,vJoՃڣб Zg 7]/u ۰Sר?@-߰s-^/8ղڋǫ@6(< Fӌ/ۂqx*!,v#\`%DȎ>!7d$s Z۷c ! Բjɻ'# }"$AKXٍIJʿ"O M, `׼܎)p"-,8IEۮӝʑrې$8-/yh ؘױۤݠ͖ǽѬ !"3ۘ1ۄLЏNj,$zn7A{Uƾ0r"% B oڦNH'ΫƢKW!je`op[-ܖ!!i(Kst{ܩ}Ǐ.}9 }J=ۡۗ׶q[͞q9!D ae*B(%-5E3v}"*[x_8\(2Ҹ}2U Q!!HCS,RzE? $[տ̓üƑو$i +TR߯ٮ֭Bg i!r#g޺UoPڜ=Zq5]H$  hX0uŴ؎h"T `A`ޕtjԚΔMê oe"jmI֓Ԑ.$+$:nOOI*$;=#4, }ևӵ? ##_.l=* %T}+|)H@MZU;Ԝغ $+HrO#{Z*)x" K}\e؋DW?$ %eQ 6ڛٮѣųoߕ($@iL_ۓڊ:oš\  "x~nj6CŪ5` H6&EyӔ<+nM,\٪xX؅6*ZCno{ِϗ&‡~ #'&xI=ޞ~ٰһqQ]e:  ڛ+*ĿC ';tk$}ͭн f >qpF8=ۈۇگu7+ 8f' ۼیԩȃtŊ,NnD$oD)80l|Ӡ $RH4L2 ht+MbF{ Fus%ԣȐ $A}oEYd؀˭Z N\i"j9ϤObb S"E0UΫK\)M9wG\b=;@VçV89̡Na=kgl)̶̂tN+B~(>ܯ0Ĥ˭~AMK-kR̛))D js7Yu>o *$vs]'o3k`mܒeR(799/Bze BMM,#M%ӻ.#caIH^)!cεʔj- i5{{7Ε U e e LY*͢гGPgs-/ ͪ$Agt֗\:xh[ ,j@bO VՅI.E $߭ ɟmQ.} ߿7SRDh ^:& ?,G<͋RߡJ nnMyªe 9;\a@r_;߳}7 ^nC߬vIP 1 e?e߶܅ޙ3ŧ~M.20~;V [ܩٷnDZT;8JZsȹ/i kK>8ًךԝͻ#T΋d% 3(\0ߣr׳[U([)R>'F؝֛šu)q2 -)b"vpؔvKʥA$#1+*i3R#}@d橶$3F-#xes&b˯7L63 ! 27OfwܒAS5k=,s,y_ ރ+k)9\+ C=# IܴS t̸:G8uc5 ٮ}բ>*3u@PG4('΀ł\^?E3<HQ=22}_@8J9Bk4wr}ڮӡД̣Sױ.ٚ/?7e & Ge\oՙ{/'A";:',_^,бέLGw[4\=!0 1iԽϟ#Ī^)!=7g$-lH߃ֆѓ; ŪB7;f-L<ٹҬЫJYi,׌e,;|4! @Nj]ԥ@@Ͼjlj 57)6LV@j$LZ-j *'6(.'6mZbКI/g. *t N?L;%e* K^ֆұ˜ş,ǔg#] ~r] x׳Q ĸmȢ`u ]$W0ڻ#&y=V M 5Hݾjar  nEj, ga3d7D F5P+(f@}p+ c~ڗցΑח]|s K?Z96tl_4ۄ\GDviٛu̿zƑi dA87Td.p ƞ $^pʎ DX 7nUtߊ2ڻ$)u#q 2Hܫ?rX;Z3( "9InB۷Ѿ1uV!,m! $9O1ZԽ/G3,.@rpmir_eval-0.8.2/tests/data/separation/est02/000077500000000000000000000000001475740344600205125ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/separation/est02/0.wav000066400000000000000000000372541475740344600214030ustar00rootroot00000000000000RIFF>WAVEfmt @>data>2T:,A=SvPfg d3 9MAB/L & 'c|m!RhB& QS>$`"eUo#[$F|AWH8Re:i,N-dnR,D0k>b rsq*Hx [&xd)%JaR9 } M .   S g'.G)v-QnR{& T -VW2 %_L֗+š5֡<ː_BчwKKKyE³3ȷȆ[iܓoz0%+4O5;BDNR V^5`bddeeeb^[JYXZ1Z1ZXlTqSQMJFEEAD@ =}962S/:+)$!f=^u 0&ӇHȦ𽗸\5 jADZNI/È=: R }zho ǩܴ͠/DFl"($1m72=HRZychmVsuvv%qnZmtjj$kh hAe'a\WGTMXKKEuC:A2<81*$  YUt Kņo{i%eB@7^/vrѭepFҸj¶ŗFһ 95l_& "%+d1/6D;C==g??UABJEHWJKLKJzHC:BA@!=u;l;9[74/A-n(!Y %b}L \ |fӞJϦB˔-˨YiKȗȈƕhCTƈGƌyDZ]ȑt̀O|%Ռכg /_ : V VO>r"H% ''n(W((l)X*,,.x0122w220..,{,,**)r('H$!a;mND  G-V~ dܙڣر-ͨ5\”0ԼIrG3?%'Xȕvͭj۱? Y^ jR8*kY" "V#%$%&&&%&E''(W)L*++))($"!!rz M > 8Bi1݉,?./͠yɜv~f÷"ĻyvĐK˴Άbi]إGVܦݐ O*X rx6!#$}%'m)1**?)'"! $"f#"""; +AMNX/ X(x# E/>Վi9ͻːɛȪǙǞʔ̝zSq N1رR~ڠڀF?K_9+pe9yc\(y u eS)]*)ePiWb;M  3}s_0Lu&b#܌Wd`8֝׳ڻa֞ؤcջv F<۶R|U)}ihi #  -;nlq? 1hV3 e Q&v,dP.z38u(m؏U5@:'kUޣnYiKm}E<]32   c =8mBBCqCu w 1 'Ih#sN=/T),o1.kq"mBy8C`ߪ!G!ߤ+IhVO.tCA~I21KJ - f Zz   _ :y8IS9y2ZCZ9:l0}5ojmVMJEx7NO"g^9 S/Cx. /  A!  KK%BWLR|o %fKdb^jC_[9)l%VQ1Jp~Qkf`*]eq F6V DLe zK!=^s?mQo?[a\#P Z#V~<#CN.s+o:|fcESGv_<4dXfP 4hj3)'.3ReOYw' W2`l8S!=  D4NzMQ >|gAeWX1,W9#hK;m("7? *N0}) #jk73+Hxw#Ax_`IMWyWFvL}!yDD$1J9X?M?f{mggp4T",O_6b&p-SfYbpL:G#B+sp)W-pm_h0pv$J]Iu$@a(gaU"IR J*U kT"1=>Wwexi[41Q-<]>>|r$kv ,|7agfnvsPas)_je .VxZ!+5_-E&$#* R81[b ?v;0^-+x5yFw{f; Akt]jiX m(,`(B}|e!EoT,s}rJI#\mS:2[}j~{WS-&|Yz N=< \NOgyIT&ZwG F{d)PoRf\znj"bNqkR 1Q_$N$/&wu&}g66oU+%dzVA s RJ)!%/x!1%w+e7%^4 />ors-2KX Z9&: g]mWSQ5X }WqpAm@-A6V7S-h aL$@Y`>k= + ?%bN 'S#WPN7E*QL@!TZx ;AHq .D ;o $J;NZwe5Z#q)2*07 @qub7w:m5,MpiivGd"cD#,az$J48s1j ,rW?!6fiu}f+bA+P|x+j?J+T5h...5( 6P41Bd#a3]~+4UVal r _sh`Ir2CT^7/NeT+(p)9ahL{T]F\Z` t)m(Njc<Ei`L"#K\u9 Qc\OA YXKB@ -vcC?hG&RS!-Lj[!|?,T}D0BkBE;agYKOng+v<%U\),p[AA8!0VgM!'s`?W0gPw`6:m0.*LJR.E<9A)0`{oqR R8tZ;TC| +}id@EhAnqf^Z1zaK fO- $? 8B;,!/D0jw,5gd8,@bx?Q)MN%[In=veD/6"uBse=J5<^_UBCPg"j;qv+ q9 lpG40" Aid#@$BMbrzKK{UKkY;VWa Y ]++ISAQ 9ZXL*sF2Cx@ (xH VNKDTtlE 1RJz~bEY G aX30(PQLbCCz]c!&/KLCR_usmVWQYAJQya*# u[@zG+28l`+Zn+ %SGWXkCbY`|}@;*LL=Bo#  8m .1=e:67!c#4* _C&\7o,i@m;IyjNK0BM^(D@f'e2CA46Hd [ &M/ W,hhJ@9 Ype$$*&D^kwsysvhF@ P/8N2'&:JO`gJA$"W=9Beu&Si{|gWSYhT% zfeQA2wOW4KE2,|V5 0=f{V& (7isga\SJ,:Urz? +x POo?HSh{8S60 W|Sw^j"uc7psick9>NGya(JINBMg8HF?zgd8J:7`7G W].Yr7E 5D'sYIT(R?br,|``_?TOe_Ivcrf;7=t:vU/ z B{E;cU $<S*q)Nm xjH7 ;c`)T]E~t3 0di#KG Ni r8;GE,MQ_.i=A4?88 ?[Cw*^{!2_sZQ"eB4LVcKOw7KAB3_&'QIQQR\'k6[f>ZQ]9.o2Q}] }<6k ) ,C`i^I+4Ma`N8!|w|{tomjlsuy~i`J30>lj[IesYWayP|e0?\9Lo6%j$}X!sgJZ3uDA,k}%(;<25N d~2VMe` hvFK9,2Xe1 1lh.z1 8NlAu:gv2(4':uyP))S4H>a;:uG,e.x}sqxMB khTQ~Y |]uQ/#7s\D9aT:Z1xN[A,uW;aGvr-4s$jhrK+f8%1G-NM\-q*$\-IHcSev~V<2.j'p MF:_b^q6gRDdH<6IY_tS6%,Wd Vx}]2AyCzL=We6jVeo"mJ?iB:)THCGS%&wCC~vL3TC/QSbt9 Z;]AKX ??6 7xq3g  GX9a0Pg"5 l ;]ߪۑ (@KmQ«LUɖz(Cęɛ䟯UN꾧J)ɾJӟR@814"#%)4+V059>_B?FJ9MOTU=STURPYQTUaWAYW!SO_OPRuSfSPKD< 6/=+'#l!41U oXnס|>#ųt+ڨ#ӥi;sNezNIۤ\ j5Wˋؓ4PWmO &:-0s2s347n;?JDGJMNLPR?SbS/ROwNLG^FGDdB"A(=95|01,(j&$)!qX8M]OۨײԄҊżeӸsg쭖˨_Y-姩ϡգ@ {qLsekɟ˚θtsKa7q- K '\!$(-/G3a7D9V< >>E@??@@@@BBCBAD@>%>R=--1//..-z,E+)Y('&5&(&%$a"u n ]1G=޹;ׁQ&χ5ͻS,H5Ȯ)keDɠʩ&t~Gڏ8ܠެ6Q{|<FiK - 5 A!"j#.$$ %$%y%d%%h&a&&%$$#"#"!|}X2/p ,  i=;f%K&^܍ڀ؛ӽ%йF̈qLɎLȊapqK)ϜaiӽԿ JKM^UFJIR f +t"i7< i ce.W! J s d,;AExMܠp,\ԫTE\mҋҕiLOIiٽaݝ޷Yfh0cuo < /Wb<+N+g}s#v).l!^ *y4 A` Vݢۻ2 {MVIIԒ:հ֏z׿ Pۊs߂Q.t.Z"v"v^+j  p{a 8_H+Acp 4 ]  RY6`,"Hj8 ߘSyRۙ?ڪ&ڃ> ޫ(yH3 3Vu!)a%jPXXhz!C W _ n u gXq ` y R ]cV~) r"~AVrv: u&Oߨh0p?Q9!# 'l@h% *O"zgC T t 5 N   l / u>aF@#0E"95_ySgZ5&K>Hx2 #\JOr'UQ^v+)GXX,/OYQ}(=qJeS<{>1zS'2tF 0Ed;1n|O99~WMBC>e)9QPVTxL~ PmoA)^s) ?\(`*Iwm}}: <^R]%i+~;lVJ6+'UIY6t SP. % .8:kNy8|db,}bGfV^#pG0<'a sM7RA6,(AN` jZ Mk^1 OMs}{exXRui=r+Kpwt)2aljXF$d"{1uY3-4+C.8WEx1 JWGqfk GUsu >s`% sOj~XZv2NG1?dEZm46:j 'r iAMxMrn s   z:cz9}#..;[gCrkι4O  yvY-Bϕ’ѓy'y/gQ U΅;/LE(bzM{:$*#2*5$#P mir_eval-0.8.2/tests/data/separation/est02/1.wav000066400000000000000000000372541475740344600214040ustar00rootroot00000000000000RIFF>WAVEfmt @>data>\M+ZgvM}+y]4dE U`ElrL,hfjALFKR4\E%WDJ$`s߸Rۘhln /Ըeׁ֝ٔVۃڹױ֨לߔ1${\ rHE7E'*ܕN|U [őĩPĜvŅȗl [WslrkCiB&u+v,P݉Ҋ3Ɉ= &V5<[нRLJ'Ԣ(k { 7 07A.#ahs߀ ^ ͎)ĝ±#Y^v<̡ʱyv,ׯF_ږܰؖԺRѵ= ?Ԓ ޴Ld6N)  m % &L<.`>`)wJ2M)aZr{ ۗڷf>NJIoz!30,VIbsxSXNi3:anR }L3ߧxި6s@Oւ 0R(dܣF*EIkn+aun?B;N3ppozٹ؆܅*WRaـژ!]\z5f}JY K#Y:`K:2F@2EYHs}v*:F߂]Y_-=eLtS|Zo[6 v6 2< ?8;) Pdvݷsv٥Pםx oD!2I%}=@{ ?-j! `K3H3ajV~Tӗѹ }AGu;EBzt6M  *o8jcWE&(U\M ޼TZ44cylcBE`PKk2/aTVa]6!?q_VZeWڤ֜{VG?Ԍրח؛9dUX?j{v 2Pfj- - ;ii2׆ ֱ OҁaкѨѠݏw|]VN_"(>~` F|+C[y$. aOSF Wyul. Nc%1GCp.vIFh3iEAey E oz[@݈sءe xZTeSKk xXWw&&WX4M;xeٮڮӵԾϐбlN֞wEb(C82kh. 1X13j+.YM9J26Aor XJb>WT We\NT;%*dPjD+i} ܊ؑ4UΨIԳױjE݀[5b+~  S - =NVޠܶ=ӌԐ_NսgSb&S0X#/rdj K7ok``D 1-5F[u'_ORp A%asa ^J00j*;]nKtmkQ#(!ZX6eܞM~ԙҚ҃el}a+0$1_d-zl ( j ]W` Dsb`$S3ْCݦֈր֠NՄazy$?zQ6`qE~hPr7 )`pA~@LyHsP.HY2t<7@I%>Kbe)'"*>C\! D'd )`I/0إ8tס֬Oйd՟s-ݸ>dl / M 3Y!ZSBK1%ڲFmzԫtx=`{FI%H:R'*zO>V0Rg.QNWn`~hl\b@%"{0hTR@zS#e  ^  ` o`d"@jBuߴd;R9ڽ؈(t[Ս//ߒh gFMn|Fx h8e#SV;tJD^+HJ1PX'7V5ON:?2>&nR-5ZhO&rN> @eTrLܬٿ_ӬЦφЃґӌ~ד؁S_j {x^ ` L j  h?0nm.VڧԞ՗:״ضB܈J3(E>dup[[ d]u9*},[uXv TAw|)+*f72KM,vdfJSDMgDt~{*o/ޠS n,zCʪ˶Uz oH+ w8PD0sN\p7 f $fRO&eJٓt)ԟҷ-פF؆dx3a4[a }   ~6"E|'T\eN a]dbIhީE  NBߩQަ2&+ؗw0  mٮDi ~BDILԣ#֨1|#HS?rS^SmӽݰY DB"` {Cg"x\2 Jl_Չ׾5 .zؾZQЅ68C0[uZsun@9LBi _a3W6C3~k4HiI޴r۫߬- OScP}/ߓ~X6o/J96#Z ~73ofHYMkq9Si@a ۊa؝[fq{|PCpI) f Umvb +nkOb VׁD+igaD<:-b bfY?n20r?^{V~h\4 +fR /|'*O~60Kl-ݸߗ_ OJݹ; 8IPCOT,wW}L%w b.u?6GڅYhٴۯM/oޡePۭ %^  n tM:dJ&- 6._' vR?=,2&F$/j=/ 1"c2vאtסو߃P>!` aS - f  cj0=MZFwxO Cˍ7`6*pzlɤJ:ӜրKL~d Yd<M !#&*)$ jG3 C2*S!wڟ.EEDzŸӳkv/ 2ŷ3߻vš3ĞŒ(Okٵ l_1f*ehz_(MQU&lիˑ Ȳմp>$ ҜԛgƯ0T ֟ׄ[BicA1k'd>^v*P: gYT(S)2 'du+_M DZ gF@}$rrΤפp s8ZGO   *ݢ۶5fܗnvwv ĶF;7 Zyϐ߮eԪDЋ̍VG^wk.'K۫aОpOoroR }2{8էkX:x (~ aF[ ~ ֣Ҏ:T<1b2 }AI R^ OVpFe{ؾІМ3 |ߊ&{t KێݸWgx7-7qP(3  kq /g~˽,ǁn#Cn\F?ljHj M}!Rܩi N ^4 Z P'<$ۣNͿ̡͞E{ s] c֌m̞҇0|ALԤԂn6VIZU" - 6LWv%G3E $ \ IO߼X&ΟMظv^tt4Mڭف(f0F" J/rV߅܏r~>J#utF#7ԇGdvԎv3XOAmUo e <+I߽ޟި! xUHbG7`d~e)p6I5*":%s.{{}Y&I 4S8ky ,ޢz jیۧݷSDP,6x'O.xdAz"g*]hxރv6!=JTFUWYd[g|JV#)qHnܺBފoKa,p_C&UO1HB H IHhZj^ltТ^ݸc~ lr2_YV+`0Nf6g#Xcoz%\-&`ݔA{ S O=̊ʹ կX!;E2YM Wf fB4߷yԙ Nؚ֩٬_ޟIP8.RxnPl?"ٽٟ(3> {"!9~ BR6יУ Ϲ@+܈g6~G ci\rڼ<և֊ܬ]A;0nckoUhb)ܘ&6!9tb<ҨhϧA5/ .  Ww3y֫$Ѥи*`o9&)Yw+^a3G<[<#ז:Ьp8ϦDD:b]Zv7EI'. !6 "Kg3ݶU#ڳ܄+FnZcFFvcm?4߿ܕ۝ߡy  {  Z2+{ݟ=lє'պ٤ިOMw 6`U4O.BZ!b%eGDߑ5r^\yD| d5'Bme) Q_,0ff !q# Vsdn>l$U v ~dQI[Qa 25GTV^@ݪpU4e` X:ޱۼםևjՊG(`mir_eval-0.8.2/tests/data/separation/est02/2.wav000066400000000000000000000372541475740344600214050ustar00rootroot00000000000000RIFF>WAVEfmt @>data>;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;<;<;;<;<Im Bclm ^)dR~7 T0|#!36VjNq @J"Wp2Romi)G#6Ds3k/1lQd/ghWi_"5mkޱ]U]6H:.ZO~0lZ5XlKdN<1uoa=UNpEr_k=o&hE(zgw$wT)4}DU Iw'f!9y%K/ "XK4!o: :ۦ GB~o7-<|_L@>Q| AB|E#Lbiwބ{'c ?? @9 A7Y iߪ:v<%U#`c UE~"!v_ޥ}S/lg)Jr8Un*[9]]8BV*D8$57|IN",`$!znBUDFOu/,z\-$|H$1yvC:wZGk |# =SF%_O)!L;em%-m5'`MyC^>L`~;KMCv\3 GVGf7:~D%y:&]o3-+^6+9_ww{*G]tdeQk'VtO"Ek+8z4(E=# meOE]xI{p&;,~IYd+Wq=<D@6!Y' yT^|#?}CCc]xj3%aksB 8XU:fhHaOQx=z1 ;iD+-vg&Y3 U =~xy8^mi)+YL'"tz%)J0VP# *.pbpC2Q `CP!e+Lu2&L^eD\lz[)wSM&#+xwC5X-&vYjgNK|\?%]oA+` EB;G 8b-zu1زnߴ߬ٶ ךӤcNۻ݄۹ؒ5۬Q2jaBiwjEY@ܑ۹;`ڬכԘ.@5ۙרS %&1= pP2֩_vsԁp TrxA *:nރ#ڇoDΰJAӾӢSԄԡ ,= 3d|Fe(}Μͳxb6m׼@s^@W+@^Mkl8Dޑ>4hԣMպW"W3'TKHI}ސӔѯľ[Be zf_0i ] *#gN݆^ֽ_ h֬Exy܅$w ѸvoZ9܇W+ʬû˷ckMXXQGv G¿ɺr$ԨҔE9rRxHlMq3؇Ɠ x=()ekȭ\ؐIi)8 y;Q}Qa|ܫA5 2av6֭ xȩQ" s]=T>Bmsh2kl]ZW^|cւ(` %,б߷ÕG/] u {%|ԝ&{bw ޛσуn4Q趥DP#d*R;qQ dxۇܖ]R=$ϩtǾ>\xrƀlloڿ֌SEj 0й{r049'.lֲ<,_>DZҲͻΓɄk0e&$92 ^'{osvkKj$2ڬta4yմeɊ|RɁ??{P;caNJ[; k+j{d5Bx)n#6 uBѦ+O+d4_"&wֻbrʾ)+i'ƹ :iFƌQ '0&.,&שгCJ9ٝזӁ65>߲܏ѣЫZ'93%S~s~t N  E?Aγϡ 6ذWLw)3/( B lZw8gU L#EyT!O(f#[`/N;ɇ 7 Z0< #l]M6jȧFƜ #-*"9? h6޼u>6 34d.Ɓֹ=پ~ԈՕ5ƋF /)6i%%ZZ/KV}pfuxuDɉȽU dw'?n[F<ρ/Piͱ" a$~UQ ۡw3DupM_vU,Һ  OH g0=n}ܕl͊aª鯤SXB;$E=(V"F*EԾ&δ٩d.Qǀ5HfK zJZd i @ hɽB״$0ҷȰ G  n) C"iؘ˃l ĐC2í͚BhQe!/ t y B{#/{ҡ˩KȤYʤĜ]>fsl"@  4 ! 7\]߽֔û7ӷڍH{-yh!v5v%!!Ѕ"_SĄJĴVCCz^Z2=.'(,q%΃ĝ0êċں^jA"Lh& ; | & ~M:ƪKDZăT‡갑{νݥ/ 5g vb ]+8ٹQNʺ]PzSЀ]΢D  P9$fRQſܸl}ܗ@ɳ`]&)$ b 3^*.qHMn[K<ēѪь٘ŻO֞lՖ1# f  Un0n6-9ы;2d(ƾ]1țzvjfa ?N o#gFRKJ׮73u+/?g'4V }ߦ߾Nۑۗk,ѳfa D Kj1bugJ! _TоH3 B]X0j&y|C| H chNԗB̄Ν5m҄hPȳi.ߐweK`c :yt=زTX1H؈3uW,gf h 7?*I5LAU9Љ`&<|wqk5; Xg` # ?8'R`In`Ě#דւX,ޢF KݔlҖjf ǙΘIC:5 ~r^1Z[0tg~f |Ѽɸ?TaTۋ'֥~=s#Kf D ۯf؜d]齍2 X\:w~`9K" )ޝk o!(R/R\J[UԑA%[NOL3 Voն91mĴl0yLJz47> q]Va ' HO_ԗ IcLg;"A$EtEKr;ͯ٠ً/Ɋͳ]r X=RQqe{ 3ѳǓC sQǕ}mRMI~kota]kZ JLܽqܥE2Mݼ٫ga {*z.߻6xdQ r,dPJ;A^dG.ݩ؁yT L { ?s} h 1ؤ!}[bLij޲1mߎR^8lexM1P E=SUt󸬺," \RPWfND#$_,НT[ݻaMlCPizՓu 9 \2.%Vw QO8[/ @T!vw-8=?|u'# =,RL2kUbT)Ǝg;%j]ՠ  \ |m  ޸(:5f8:g`&J5w 4R|0kcU$2-B3M zt:0btϼǧ46kE`c.%#>m E3,?,~QxyU{)Sg 2)7YD~ZBM­ܪg Sk0/` k#S25ic}0خ'ޖ=ʲ Y!3;2dfW? K_!1WGί1.0!eV b >^U (t4,ءӟ.* J4"MPjGR!p4By%u˩nW"5*eq ~ ޫ ݔhǴqar%!$ GK7:m*aӄ}i˭|4GB/0 gYaA@xUyw$Í72#1i:H c <Y dRv'X?#JI- *]<Ņh0_᭎?/'d8I  P %%; m.N˸lw*\#]G<  @ vնs-R^:=80cn q1aGB) TU$ʦτ83@N'"Ѱ9xa28Og|ŬĤG15BHE ;" (Z*#VOƾS<MX2@r/8cL8Rq+¬lo +,c>r1 ~ȕQ2 $)*s{?J#ըF2@"( -aެ|oa_ȶ+ݯ ?#@*b,y >k) 0QSȼ<ػ\| *3.}>V(+7RƟAZ 1Ee=1ʮ0 {#u+$|\ ݐcݡU~#p0'!pԆ\: \?,cwܼ'Ըո}zdz&ţyܩfZ ɾ` K o*_4ʟEW $)V ցmN 6E44%6z. |$^T0ΘER @`:5XPJۥ"Ri۰^k_E7*Ɏ`5+ 3{\qIS P6IEǀf?l*'20( [ٽxҹk!m E'Ӱ85eH: fAٺ Х2Zdc ,Jy "O5 lF7Ÿn+  ݤ͢I̐'U`vt5-EѾƕ,<ΰɝ$wA@aNƝ.|] w=ؐ Xcܻ'NޯX )C*S)ؽ󶉭W_ (ûW&Ra &/-&*\ F4Q@ۍqa'K,~ҵ%j]iǮkIX6V8I>G`8k-"w3+  1 x?طюw/ ~قmir_eval-0.8.2/tests/data/separation/est03/000077500000000000000000000000001475740344600205135ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/separation/est03/0.wav000066400000000000000000000372541475740344600214040ustar00rootroot00000000000000RIFF>WAVEfmt @>data>sUXo  $%$&"wj^RI@7.'# %+4?GS`lxrcR]vjQD3% )2=KZhwyncXPE=5,'%#!#%',28@GKS]chs| ivW:rN.4St)BTbmuvph\I5xV4ue\XUX_hw $`/I_tq[=Dr(JV+ 0^f'd0=,MenmdJ%5$Pn{&J5rI-!"3V& .OsR*q!   . ]Ks/,-[R>LuZ ; 4 )fMp_2 /xIf JQS[ #kq02qUc ny)u&"܎[tӐҝж*FUީ9[ Y \ I %#"';f~] w>%_ +!& ,u16E70( (0! +' 5ĺ屛ħi+E=!ܑԒɕͤV"uƄ-הG{@f[ 'N)"$&(p*+,T----,7,0+)e(&$"@ GWH rwB$e3?ձ7~I//XMb𩿨ħ>3o禞ϩG'B%AƫʺH` x 3%)O.26:>~BEII^L7OQ7T[V>XYE[e\G]]D^`^>^]D]o\`[ZXVUSPN'LIFDAAP>Y;P8E582 /!,h(P$8!yfZ? D p 0y(d?Ag!lC7L3 F {U;.'&(.5 6"2$&&()+|-&/0:2346778399999}98I8g7P65~31/-f+(#&;#$ m3+  zT% ، ʏmk׶M[۟CӚm*#Uc:GL9J{ʨ9[ Ƶf?ƵɉS_j Xwi7_A^Fdm^:V%y6e0Rz[j[5Z+Bh=",Hn#r~HQq ` 0NajgY@eKW?\9t % E \ q !!!0!B!T!j!!!!!!! "#"="O"e"~""""""""""""""""""u"P"&"!!!@! L i  h, > y&*#p^T\wUM$ 8iتXAhәs[UYoӕTԯՉ֑%gيPܾݖtL2yGUPun>&Wb2d ?RK,Ujt(L! 2r"ޡlC)%Ckޟ-߇YY;H/Hc5J\o s`J2~\7 !i"?#$$%&\'+(()*p+<, --.q/80012O3 445>667K889*::;Z<<{==t>>G???1@f@@@@@@z@H@@?R?>_>=$=j<;:9876v5142z10y.,;+)'% $"  Y 3 "cB9]$ޔܖک4ӁKXɪoE2 *f?{ý?XͿMn ±běe6 Ⱦɝ~_E.ѪҋmP. ׺؎_-܇I}2D@0uV>(}+>G|Q*|j\NB<60--, . / - 0 2330/*# vLq, !1""g##}$$v%%M&&'U'''(@(g(((((((((d(@((''o'.'&&G&%%9%$t$ $#8#""\""!!3! K TZVP;X!Kg{kL< 6 L +Y<^z&Ec'YKq! |,~7/w#}/}3|J nX?*k? B*B,*es==K w*Iem{h#GD,ux,j6 4tԿӀсѿxB,YИKѾAw(Ժ՛ֈׄ؏٦5z(sx4vy)B[? &UtrK !_"#$0&e'()*+,-./01g2/334F55y6777]889W9999:::::999?988187C76)654*4h3210/.-,+*)K('%w$ #!Z ww5]l ( B|eh'~:5KQT"WN7KD]6}iS<#Jk .0`RK?nxL%NS8 l(;ۘ^8ӭ+дBˆ:ƥœĎܼ7ǽbRZw[־h ù/LjzxOԓ֎ 9zh1tj[G 6 A h"$&(*|,X.$013256@89 ;X<=>?@ABxC7DDvEEqFF%GcGGGGGGoG7GFF-FE2EDCGCBA@@ ?>=;:9x8;754N320/).,O+)[(&N%#&" E?d , k .oC.9vgsHq;=u׼ mZ|#ҜnM;9B\҅ҷHӣ ԋ#n#ج1ڭcC.Y*m cq86XoywkT05{ {BH,vJ)xzA!%JJ,T7(-6T{GM_D55=Stbz\Xr8z leW7d!"}$&'(p*+=-./71w234 6&788B9B:4;<<=>T?@@CAAPBB0CCCCZCCC0DaDDDDDD}DXD(DCCQCBBBA@a@??I>~=<;:9876y5F431h0/-',*!)'%N$" )a&18; ; 90%Fv8ۍWUц P)#aóƒJӿۿV ˜9Ûa0 :[сҩ%T|٣ %9JRXVI7\aXEBCo"~+uh \ i d2 ;xtLQ$T!@pN] 6  TUCi x!!"#$%&b'=( ))*a+,,v-..O//f00c11?223X333,4d4444455!5555444h4/433R322+21>10,0/.P.-,-,c+*)('&%$#"!q >q_   Z "~5y2n\!l c$ޖ1وC ӳүѽ<΂A̹A{1ɶɪɰZʨlě0ΕX Ҥӈp\K>3)  uLbg]Wq=G9G h(T0ߠ'޶NܛNۯۏ|zۃۖۻ+|DGވ@6{&}. p.Pg / QXu!"`$%')* ,|-.?012"4[56789:;<=c>-??@?AAiBBaCC,D}DDE2EVEnEzE}EsE\E >9=^[X4&]{GIJBr[%'7m@t"3@KXgw%[/`iObgn߆ߴ=W*ie;.8WS ' Z$# u8 !"'$e%&'(*&+3,8-2.%/0012`3 445'66Z77j88Y99,:::(;};;::Q;;;<@&2_qǚI ҲՑxaI0r"A4J@M A D $ $  _EqK( 7zCr6,hDΧ΋ΑζfϚ[G"ԇو]JCKb\'iMw i2@_M!"$R%&'(*$+.,.-".//01o23334L55677+88999=:::;A;h;;;;;;v;O;;::F:9}9988Y76654]433Z2100U/.-, ,O+*)(*(i'&%L%$$p#"Y"!g! < Vo= k-@kV!63q <"c{M:(ވ;Ӎ:Ȟ ¶|VSt7ߢўfm>)(Dtp)ԪV޴qm_(ڎD3 x_f}>: I[S2z/rQCMz0ыσͭ ʟlrư*LťƟ"ʣN OAl,]b <  T!mE:Lz"$')C,.41|3>69;g>ACEEHxJLnN+PQSQTOUVVW(WWV?V|UT\SQkPNLJ^HExC@>M;o852/,)!u% ,  j7q > , 2 N  [ME$IM 0m|R [ o1FB(x+ҐMݽXˮh2/aɟkJl̗nV󓪓r>N*CfAI}հRuSFFKVahkcN*7 H^R :5zP|sE\))5<K C - 5y9]$}5ܲڦخ=ћ΢Q 4z/+sŁB):s` TVZtn3 d=#&*Q.15 9u>?&@@rABB_CDDOEEF=GGH$II_JJKtLM*NN-OOPyPP%QgQQQQQQQQ^Q QP,PON:NeMvLtKVJIGeFDDCA?=;97>52]0-&+m(%"U x Tz .di+NŨQ!g˯Uӫͪ(r*5^ER֭N氞uizF<|2κь`8߷>$Sn!WnZ H P . Pkp>5ݦڀY0.?9%_ʧd4:qࢇe|̢S5*o|x?ƾUԛ؄xsy P["a&)-H0h3r6d9=<>A [RlSq , b|%]h9 ~-SۡHn͋ʦǿGʳ&!ũkt?)G&$VJz螕ee?9rͿ!֒ ߉_!. }3C  1#c%X')*+,f--..-1-l,q+7*(B'r%f#,!F VC~#܉ ױoMPp̲ɘA *s`ĿI%G¨qE% 6ẎͼGјYATܐ@qXPUVS. "3 v ]F2 !s#%+(x*,.163A5>7'9:@ABIDEFGHIMJJK LrLLL M0M+MMLLvL$LKXKJdJISIH)HGF_FE.EDDvCBkBAtAA@5@??5?>>p>6>>==w=I=!=<+b)i'S%&# zh"6: ,q*=YݻڡחԠѼ@ɦ*v~kʳȱe񯥯lӵ)ؾrKN=9."ԙWڤ)ݛ6aqd; pAN69)ތ=}؝$թ0ҷAg˯e'"lͿGܾT9;Zf{ksÙ9dzG˽͝ϙѣ:ۦ4kh:d= cYj!6$&(*-/024-67;9:;#=@>E?6@ AAyB CCCHDDDDDDDDZDDCwCCB;BAFA@I@?D?>D>=X=>&??|@9AABCND EEFGfH4IIJ|K,LLmMMsNN7O{OOOOOkOONNeMLKJFIG`FDB@><4:74*26/,(%";F= #:AVϳ˰H6㱱uٞМ6EG?r񒟓{!ʞΠ$wݩUvȶ{6`ǿa]ֱ'dZ]m+5"\j-w (;IT]cgr)w5ڲ>ؓ[8+3P؂&ٛ%o/J,2x&I@z6 R Hw` d!"#%>&['n(u)s*i+P,--../500w1223m33&4443;3333)4F4g4z44444444s4b4N474!4 4333333|3o3e3`3_3_3e3n3~33333 424\4444$5X5555"6Q6x66666666x6@655+544^3210/q.#-+5*(&$" EE  oq2CW~ЍaGF``Y񫹪ߨ=ͧqhr&;N )OҀն"WTHqvV 9 I)g  4ax~u`>_9@{:۾]2ӇѕN%m0a>a ~Y/ q" $%Z'(p*+U-.0O12345678v96::; <<()*+-,.//$0 112Z344 555Q666677666y6-65p544f3u1l0/H/.-?-,+ +D*~)('.'n&%$;$#";"! !  ->5sl8 !!"" ###h$$2%%% &4&O&T&F&#&%%&%$#4#S"R!3 mh  Obl:ݦbVXhˑ*Ý1軽ݵ&> /ɬ̬=I-ڵKCǔSնؚ|X,_Axif{Jkvhcg}?e?ް,zmir_eval-0.8.2/tests/data/separation/est03/1.wav000066400000000000000000000372541475740344600214050ustar00rootroot00000000000000RIFF>WAVEfmt @>data> %2.$ +31454*(68>NV^gaXPB7BPWeqw$~~gw{JQG2 P]V?kw:T EtM@ -D'~^ ^h"?l|163;jB".Z @xfsE2L"j'Q`uk vK @1zX / lz@!mP9wAuBQ P u3ESg ecP;_[ b=("Y[hw k >>  +!' N #1T'3(3<1G14#1:R &W/55&&;A4>1$'R"( %M(D>) 5$) l'$_70.#'N$G"S'% ^%"Q"Z/"z+(3'2"P(&=_ 8,r#:` [$F@Mnnpé3V]թϴܩADؤʙ+չMp ϷfV9~e"2ۼ*ܒI!Q#d SFy C?NwK7+F#o @ ['>C·þܗԩ]X|E۸Ez[#ԭߨםЭ򤂕*Ⱦ,yh3n nXT6oT %Q: G$^0,):7K*n)86!UM]/ !#/8EFp#7%HC(:,NCUi-9};Eg:J#5h@9.( 5Y f1)! ';<& E S)/9/) 7(V)[#v!%2`9,+C.>=88KA/T35=2771>;4D >L&9A/:Bw06*>D7wG=B/-C+50S*8 534-F$=1- 0i&0b(ޜ@ʿ“Z`@u` EBУ ̦~14)0,\xukx&LOO0I3f"6${b#hE   E   G  M \  $ ? { / +  |d O N g  _ xO ]   N AC.e"-88I t0,s yXaP:'!X y6B;;\N~-G* iI!,\)J0ax]-Y_Z+WgkNR=\P\'4oUZwk{L9&h5 ,c WRMy1czj0h[x\$'8 QM]=Q6G?Jj! ZPX;j2==D4C ;Wm+(S z'D I@.)*(*vD(fb}=6 dTKi<p .)]C^p}(=RF2ymuubulssbX]^SWMIG&->, "&#.-#%20!)'.1mir_eval-0.8.2/tests/data/separation/est03/2.wav000066400000000000000000000372541475740344600214060ustar00rootroot00000000000000RIFF>WAVEfmt @>data>#8-(" dzP?_%VM`4'faVd:|F?q?+^?"&RA)1\$2LY`n?V;,jfc2P<= W?@<^d1 %;@Y1oU05?H) >=&CkiLi6mWe(\c@1E>!!y+nj! \{2;Bo%I)C #_;H-\1e%oarf4o1Nn5xK&&UC=D3&Hc9D%V+!bH#jC W&oiP]maEB5,,CiFaqzj tW?x?q'XLLMC!{F b}Ym z p 9 ^ `' ! =" IO f|/-"  h[Iơ*N4ԷI˶,\J8(`AbubytweUnzmbKu@ 05'6>,/8"E)R['9Ӓ 63Ҕ{ -pyQz 0 $1D=FOEWZE]\YUCQ.M~D>6(B!3ТjØa*Ʋ> ǥYv§.ld 5< ]  V&>-u,406a1/ **#'UBvg ޞ(J-+,ix}M A  <! /k?7>GMLUY5REe] Qx\8[S*OP:YP:FL :?Y<789421C2J-,,$"#"$ Er   boAk=.#Ipd20G%qYGs   pI~! $&R%*++g1.030C1/\45E020;/.?)B(]"L "4 \:lߴܾB&ԠE*ŵư 4ɷ#BUrҾvCiąx |i5^9JN,I+T _J #s B n 2 m R<$'>{ F&zBt:raM)7?]75mpNXcnlpA h2FbGP : A Y < S  D 1 n < _  Z 7 z ] I ~ o u \ $C2Ai{-}*qi74 l G f 7  k }%)f8r<0{6$'=3y&CO( *p }cw}}cG ^zxB?l Wq- y{sQX2;PYkg(<+a6K# ( 5 DF1 B M SK ! I(! 0><.'L9A"pO/1.  G29&$.* Z 5(X1& HFB EN % ; ! ,<  %8D   !%.&                     %71<K;)71$--=TUI8.:+&AI;OO?RQECY_bjQ]T*xi2u~[]e[F?E.BY_njV"|K-#+ 5:3d?S8XuwvjunxwwdSsB$-&hPRs m +c;7!DlW*d9Y^)7VV x00N [b#,mGBSx&kQ;lW3QJZs5d\P})&I?5b1>K*+*hG-PO U~b&Q\vi1Y)87PvpOZNV i:.$X?sbVgq iz ^&A+GYQoi~'%Cz, G} Yime.r]mqe\B&e,>8R&#09kf)~}+1@`dX[G'*-  &2  C^MWN@UZ?,  2E:#7.; |Oj,,%M_O>$'32&,- 3P Rj~KQ 5s r{HDOc!Mss>`"wcm 41Awl1JVZT]6,*fN)K(6@VoD!=#{J]GE%gm2%. ~Zw#7t&;;3Gpjj2 e:B{Lh/M U93 ,d Y1B 5-("oWR:L=Wj:8&djb>0J*:^=& Ly*5s Ul#l$fcw)3/JF}}}wq>NjE?  G>nOgp(y%D7 ;z=QENO3m G_1B(KߝM݆1iӶс$cAby4tOjȰaEݷܙڲ'QҪޚ׀$0|QQvfX p< + U##"#Q$ G ="!3EG 2 jJ\gTr^VDNۂbתEZ;O'ٸֲ,Pn_=7?,_WcY %H j)%(.P)0<93f67O58-0659316k:45:/1\2u,/j1-'))-`(\#()$C"t$) >V { [ ''   Z h  z 5{-19,*bo geFjj>L(8'!?ܬ؆ؓۆ؀F{tY++X#6>wBzj&U$##,F-^-/$.,,,*R)'((:%BqkM -[n8:pnܖ ݚ4ރ|ݬҞn1YElR1Sv3t/O Umdpt  e&u| s!-Iab ZCC ^ ju J9zhL?Ng)2 :f 9A '> ffj!%QG m d'LxzGc'TC vefBާ۴ڞ^`0B8'؈ڈ\ۏ۵Ql[8=R+)?bn@ yf6$, LML;#G { K ( D H=  67SM߆܄*֛ՐlAԻiӬ-!vտNׇמع_D97_8.;!. "43.   "+;"4* $  ()$3?;<$ (*(/+-0&&($           $"",/$#"   '"!!    !                                         mir_eval-0.8.2/tests/data/separation/est03/3.wav000066400000000000000000000372541475740344600214070ustar00rootroot00000000000000RIFF>WAVEfmt @>data>؅]mj]g_!o>.g|Z"4=3=߫KQG)hnb"2UYm֯ոdךٷ@F%h3!`Ld+ ] UF!i#SށܙَpVC$~n+jpTK]x?P@5/߉}݄<)wBTHP Ѝ I޶~ vYP;NפP,/ժ(+JJgkO$c{JsՐRyjӣا"IhFuLBz X` KK6&Z^Bϫ:Xb]`Dl"xo3G* q:I>ݖ۵ْՒںpS ]P/=]~&d߳ ]'&\py~uCޡBMN|ߢm֌݆۝݌ڀת{5YHru EO؀0"Q2{ZӃ։ۈrބֵٰMXxN h$G^>JU ӦѨʪςՊ[l׵7zPtQ!M xUpޑ֌Dֿ̔ʬp[sǨrzީZ#Ay4^d  '%E?Aۦv؟ҫQ ʼnۍ`iبt|n&#ȑdUҎ޼^_ҿ&[Xڻ 02͂h,'h&(b.P)I' ՙ|͑ԇy>4--*"R p߭'gR.QQºϋ"է^.jK7 r}hl֊,ռ([\UrtਘLĭlF=]>95ĭ̝E54 ;6 A4nI8 6 򿶼`Hv/ 0RN X0YʒωlA Ќ͢:+=S^Wx.3'[{=׸GQq Ȇ bG)BD.78)$ֿզ`rDNaNfjoE|F#" ċΫ ~ _i]ûƵ붭fǗ߁  $P(4&˺ v zP&h%PĶ ϰC"(w!`%WEۣn"%yژsOت¯ 5/%^}ӂ7qθ u-1ٵnY5͠w P`ѝgfNˆHQ 3c-W}ou<? d ϴWΰ?=y( 1Nv9+X@kť3bڭjR@w6˦abғ  #ށ+UTkC|nb hYǻ?-+thLˊ܁µ/aC ۗ|*ŀU&tS'~<'tϖI1  mFÁAZ):T@ U&( ŜDJ ! mwy<3a m {lCUX_U5 DvNжVyKށa<7^^˨!Pnϊ\SU#ۉǚڄ߽D"?Ykկ4Qkb:^޶ΣQθ0 e0Co7^Fbܵm6 ԃؙ݈0]2M@)%7 ؟UծF. ,.Z#OQs=%,ۦ؛g@5r%oa-4{ccCo^ىۚ'Yc^4C%ߍةX~FߗTP}I w]R׫֔׺jgx&8M\ rc4HEזҵլ٩g3]R> O$ݯ)p:3J$}҇g$U x(7&ס8ς@L!)yL>ٳM՟{5]&`R$a ٮ9e$%ڼՅC$m_iH ((RmGڢXفڮK޲>p4э2sف,H Rh4 C-:/]IwјԡJFAܑ3IUDDRKEK݈] ҤՓFI`<  x?-ibq)AZ۝۶Ӧi=P3.mtmD9_ڐԖ.B; R`d,0m#x ׉t|Q><߷L@V T{ԝй֛ܳUNpy>ܛ  uo;C^̓Rsu=֣ԣX,"  uz<Wή>L(/kpԠӗѤ۝'$r4" _ 6 $ (Wбfk޷\W߶ոҒ֡el 9 yHث?/RYqԄ%ܸٻF GS $Jݗٝպ_ԉIֺ׫ڰ؇!ًfI|w f /@Y{ӤԬҪդPԢ3Yٕթ׻dMc{ ? YQBܬ/cڌxܰCЩs'"* (n8 -ۢӒρ$ϟ+Z־J-QUZ~cx @ߑ]Vӛ6ф[l֌ې.XHR.:SY. RaynSOxxV-cҴ CعY# bho32)#+8 ,N8WK݋ns݋ިJaB}Ar~b3xy )l Yڻ-K۸Uk޴y,$rxyL @ߎޱܷ݅۷^ۑ۲۳B*Jc[aQb%gCj@@9}!fdg[v`PjQCGB)B/HwT1c=~%$vKs,4LY((2nivWK=T+9=W H?&I#u884BWk [uq6-DW.,bcN$ao JP[g(sU_8%<X/s,y|OU-/D-fWpQ-jDyDw$nuFg sI&h.cj DgOm(&0zDL=pO?AV4_X',<^gL%\39/;&tx{8`Wh<4[w m i3eP_Xa'.vI6c HY %k)ynG7Z1#uyHK޸݈QTlE_Nb:VO=-VxhwY^?R3A/}FC?S{U:#C( |r|X\jqLU3x2ZV16eZcdATa=p߹+#u1Rn}{ A/%_wC%u܆I33qۀyn+2QOwYdbۘߦkzYTAN{]"8=\L[aӀ$ԑP t;e #˿O̒ ?q5vĘ2Y ` !뾮҆);|.e"TƉܩWyd mkx?pi|'Vs M)vz{A  Y}%uDX?sP_3m P] p'"6¯~ 4  _GhMұ+(82 [ 4 1پeȰդ|: =Ƶq.I\ l\j(d g_XԸ5ΏݕsldK l LI`j,Ljǔ֠.` A 5fƺ* !A6G΋¾JɮΫEgI O۳⿡üýC#sK'ȺlƯw{YB-1݂͹!ֲ+r g ԍܾ`aۑQ.- vfο}jUGV mU5-Ƽ!!ca ڍ[/:b%ڦ*D < 0;޼SOĹA mw}> `,r̄wimuP܈ס ՂGQB> %+u.UF27%(1د Ya&i9 دE޻PJ=>n}!d[O*Rv7WvV{Rypd +$!0NfOUzC3Uj$iP"** J1C-w{E:L8s.hRM Y0yt5ߢA{x*9":0A=?vM` 1[ݸpaۓލ ;Ak.@6;& cA޳޸߿h.|ME.E!l[Vh'iXy;:q ]g94߇M9LaTw;TmgqER=l"" m$ ?!3d5H3' 6m\H=kWS"=E$r\/''5$ M,S@`h%S-[lV&~Kvu47tJl+r QX !"A~).C|A>kgV5uHh#Ce ]%<,3avjJsdz +2xT+:'#$.,])U }ִVRڦh v,b- :T޳}Z(F3&Mu<gl?jQ-mS@&snNDyu=@K$kS8@ttK;|6܊ڽPڡGZxKC&{Sn&v j>dXymSnϗ bwdBtAJN54u֫ק8#E F (ّ͞&M;jG۷٤|} oR 83u-kHbz2Ք!)(~KIh9ڙdA-n G %G뻟0l 26KYX֘ٽF{f^&Yʅѕ #b3mК s.cМ;jѱل 'V$Q6)iܽiC^4ץ5 Z7B^Wͮi^5؃IihސO[3$$9=[VڝCx܇},۠E2ՋٗYG |/,$m#; $mir_eval-0.8.2/tests/data/separation/est05/000077500000000000000000000000001475740344600205155ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/separation/est05/0.wav000066400000000000000000000372541475740344600214060ustar00rootroot00000000000000RIFF>WAVEfmt @>data>6 8 ]/oMyIUv UOU O4% wRJrqgCIhb= @jx_ km9RkDrJHX 4[" nBl_xoWZ ) 1 iYxf-@'Tw7X ,:176?/^sY%C<;Fg T[f?Trf?P\cp] DxK9 ~ I78XU$~p^\Pja2 p wERerw"n+7L# pN9I:=@XFPZ   XUwziRSiIJ1~`w w]O IVBms |@ { W-;9ոKj$$U$B#xz"^G ߒ rz<2so$.0h2F3( Ub+$| d &B.͋sJ%,C1583(4 n"O<~p! @ Jћb(018:3X% JP![\̍/*@$-21(-]T` l׶40 g<R!).+" X2k8kjj~ ["&#RA 9;JN-+Q=n-:2 k, H2MC$R>zY~MJ# x V [_b/1+A2mTE bc451Xya(>~( qY0\8 y}  ;z,)n<.wE- qFS*$]C9X|:2=M1_2yx1Cmx;u7`i Om;\DJS}egBgd|3+x&'I )gG e+uCt`;Yczj\4{]]cE2kfNJqPou^YW&WBt6U5u>o[++3+, Vxo`)jr;BT" MVL.r~H~r@>6NX 5pKnZ:p0Su]g~N,vxGbtL ?{P xzz2$[Fn h[%f#eڧtF%",0' o&1MS'  @{w<ѻ!-m*5|<%4! `߽k 'Ɋȱ u2(4>W<8.V܆GUz 9~N֋PЦ.$80;B;(`9հ5Ӈ]N "1+.&&dm+7+ADD8 . SڒZ"Y$& $ LNì#0q<F.C 2cҤ71 lQ)(x BAZнAW=}$^&A5 BNID1&#qc$ω9 !B'$~gP;/mz3&14BH?q-xJДڛm %w#H8zxЏH̍Z%3 A G>L,h|ҚZR a}AW\zwJ$/2@eC8:',]A0ߎ ifw4,ƀӥ -NZTT.T:l=~5&; &Ke # ݉רL[ '6;3'oLi"-C  d[ެ/$eՂܝ "%`15u0&.5WAހ<  ] q:BX} ,3=0&rTod3@Sn33i` ߠ1%w  +.(Z T ]U_pCHR@sAS] !~` {_]Enm/@" RR H {aoLe"gt{0-,  e.z0L1!XN,p y d yJuD= x;7nB4; ujo . 9/wY>lAY&Q+/ &  V k _2n 4uouFgr  p oPQDpM0ir6~4-s2=VsB-PbnHgW7t_` E28Vw^maj73~sQAp3O\iH6;Zs::AQDX~F,=-/xp&jyRYV1+SD!6Ve*#.R%Z"!4 }.f`r Ss#5#&u3l2zQuA-;|/wD@H&V;p3Bg's|m{D$ Mi_' QicS/`r~w0QOHz:j{JBD9tY6)gUT7ZHa [@k.APov *4Igc.o|.&Bh"% EY&($('%(&$89Nmcegchchf:*&hj\#.(/CZlgl%/ zejilVW@$-&2 0&-',H(8mhhjhjglc{oOcnfjr_>u@7VUUV3j< z%"yGw;9-Kd2`04Of$>j@K S:Wp;dM[owDprODcn;|DnZ"=@=k@gTLj,q5ZXcJ(eb;Sa-9'e3kj`|n@g.a76+qW;ca($Ul~#e..s@F# & {=+q58^muoyBU1SH.~^--'$@CZ!!e KjmDu<&R%.[ Z ->?4%8^&r I(`iu ejXrM]n ڊ0Q?9q*&=`NB?'vL6lV(ND9A.na@ |1\Qh(3[(φ*&;3#p PGM j\?WYd#aڅ L1O<0d!@sy ;vL@~|u2Se L Nэ-=2#y_$S  7dnr2}EX!'*~'$ M3#}AFap_ f,L "/()+%= E)893%m :y]]7x]$`'Q%a&C$ Ou {;S"%&! 8Y Ft +2scq\vU4vM >o%({",G q@jnge%K~$]'f'?#1  o-gs=t.PRr5LS#'@&$"S uBZ74IV=o ~pq!'(,'%"#>Mp>cciuV\jQ@5W*X()Y,%F oVa PKV~zݎd) '})*-4(DPogg#f 6/I8D= -P$':.A/+&N jR*k3Qthܕ-= sb!&C-_0.>*e$nZOY/%V}zIM0n"+O/,+;' 1pi(6BPZIH&6#k(4,.-q)":1Wܞހ=s ;h;o!V(+++_%3 eE1/޽[e%Taum!P'*+(F$;| 7<+wCajq2n 4_p!%(=*e'}#\T vm,ݍ,8I7Tu"/6jC"&(&! sZ_3vPf,?Y* }H-= w5#%%!.%Mh\`R*-[E557!#e!# &}oy7Q_ &^""ohyOy 6xc x-wK:u,&]>DnJ \Hc #CpS}c&ejt} WF2 RIo6[~{`H3O- 5fl2_ )^sjdxUa|PZA Xn|\+| =|ghSIsVcqFs< zTG +  ~Kix*tQMm&DB9#LD$}5#R^{( =p"P! > 43x%*SX(7~g ]s^#r*+i)#~R ^#cS}mY%v1ݗu#CB 3!%(("(!Z If S^RQ ݏdH x94$M%$$*oI .9&D}d1[19\ؖi"''$!9 ;]]bxe+73'V(A'# +SM)Uec8'L6Lmh t+i-)8%Bu0 :x &\ʲ 04L%%\ IWPa2C ȪM ],W4$V t w FSLYb9dlO!FEĉ !_2+Bg 3  F.Md3>kALV,?+K~8M 3z Jz YIgwDWm 90&.*XRKP#)aCe=?oCqZvE # SL<.]Tz9Z[] 6.KI9SM_]S ;46&@oH>E>`|GH}}ָ\S -B{yX^P7,M$TKm^d> Ko!c2 5 J9q%F}j/,ʞČ T  W$C&Ew[zYLUY$ʀ՚K4 +{ W ('+ 7LUiX~zao=/ R  3!(f#>,J,g{}fvB<  D %*"$X'DCh<d>jb0TK )u"*&{ V['9;c~hh{)Q; &='2 GwDZAf٨Χ`$&x6<\ hM.<4y+)8zӠ= P $&` H>e?0kDn!5}rDeڊҿwm:bd!" @,Pa d?9xj4ؤ 3<<H 9fCQtEN7vֻZd0 bKKP 9 3;rw`&1ܡ؋1;^SZ tQ1%n^?5٧ Wh0IB A9|[{mBuXi e:C=H^o1F/  .!E q ?txVKMUY@jL?'*:h  7F [`5G$+xoE+: F^; ewubA+c1 D )  *Mrb^vxV7[j/, x^ xGr C NPG|#2SiVLmOl5=| { ReNqr'pAZWmhKLQ5$5bN R0 A&C1sREgCO\!Qp[0 2X[8T7Ya#o!Sw{40S&* S+eF Px:1=iJ,N'y [ xk8]{M{X]:#<%hQ - 11k(!f{[;}%\S"J~H J 6 (O 7O^C_kz:GOk7BdIG[\Zv]3c#wy0Bn]))luZ zh 4 0&lw Ypvf5I^ YOWgE} - ? 3\ CKmir_eval-0.8.2/tests/data/separation/est05/1.wav000066400000000000000000000372541475740344600214070ustar00rootroot00000000000000RIFF>WAVEfmt @>data>%Gg* x|=hRD3c  _  {K%^=H,@7CZD"3=U'  a c;kP8<6-z0n| Sq   8/ I > 1sY iGh6S Kn$ he]Kz'iR U 1tw]d3G`Bw\fw } P$ M5C$gjf$zG/0[m0;DO`7/q7  n [ S,M 78 2_P,mY(`U:jkea ;g4q_N/ f NZ2K>8TCqa |1R]P T { m?jJ#O0CPoa6n'T B 6 u   U  0ysz7*C6!feG  H@6 b %+2-irl[c3tUeB'c ]  >zܸTG [x ~KH2&<. A+:k$J2 e>g R f dTn&[w |zTV ] 7 + P*| Y> YG5thETn iB(g4(ju #2F{?DjZ 1ii (s Niwt663H ,!&!@ u;=  >$m "- 7 ] $j] [yZvߝZ S4Bj= K_ sܷ:6Z %cO=YC5ld"^mU'{ *  M dGz]\ nS/2\i%v@*7VuvHY_ )C5^X5Xaz $q =m( *9 \@pt^?xbu,{h0{h|   wfUa$][>k2   AIG( = ^ " 8&", QC V  }GL9g p4Lw# c i<.K\Z }J7dAr   %  >9JUkw.fNXA?^_ } P w AT>%i])#unDzRXG w HoNd)&W7XSf @ qf  6E \yu S6Qm8n_^6oVR<5Qr#Pl P Mj Y. QW!]ojK>m! ] ^ F e% R=L'KWA"Mn D[ ]R` ?Ly9X}.Q3A$mOPM8Z(P WIx| Z:GvI5!27p, "CL Z E#2S\moa%aytF _ {^p ,! NqS,vW6ZN1)8X   <JZ.l"qOo6_G H g h^ a Ew C7(_w&(]o  i Dh>DEm,?6kv"!  -I G !}]e K 9J r+<OT   M M: UW Q3 2vPdv e 1 On42TE) / +T k{&-=@P | [ D 3xAX$:_2MQ2;'B\bJ. 4  wyB;GO/SQk-*7am9F_ ZSV' j } <  ^%zv%Yb<P ;*HR.EV 9 M }   M&fDO> ay;_qT=+D'P n "7 m wB{hhV>VY KDi a 0tLvwWiT$}  OZ<:eh7e1` gyx 5RP[{3Z+s{J>1!=ybL+_C~le~4@p&R 3E*|BAj7MJ<"7xJ" ~@4}u6 4 k0mr#dnbI&6k!4/ _{l{)BD"=jO<M (7"8|KriO? WLX e'4.t8(]1:+1n 0   &.*1"51,@<M*?h^(>CI2 = )":<Ab21 ;mIQ+Yjf) xR .tqD]_s TK)/Y.C TTr>b:qKkpZDn Um"CoDKMmm<{`q">v6H~zs0k(IH!<u} r j)HM;:nyM W{l=|(w aG oARh%V@qRa,7NtGw foVv{1 92@# *x!,: Z}8q'b=g9fC'F=xXHZJ)TAV(@Hk(d!sF6Mj_nIi7L%X'!6}ol8 _Na#yhS%)0v ;b5Yb^1WH)]Q<TQw 0?1>7N|jPDjD Es7y6C&XaH4 m(Sji:OcF ;?| ?~ SM: l%$r(0PQZc>vED4s C<lIsU&%.CziL3w7)AL7~Uzpa>SyD.{kU/mXi#c;[`"DNoK(1ZW {.;~V&i)|KY!S`Jkc}Gc{; `OY?-+yYBbH*DfC5azyGct U1XE$:)ufT}="LL5 ]B!8$<3l~iNhiz"0K0ul#c+v<ARa \>A  (k#GmYD o^gq 5@)l 7;{GdMVsEpY~u . L  Ll4|>)TSTi{^Ut }D  )qT(T P_xH {]*O q(^Jp +c1.#v d ,jm%Ehx=XhK  q N>6 uj_CZiV@7}a| :`QRqUhT   #:O3 $  r}0Fitr~=% 1qd/G a1RU4y .)E)']Kg5)'$zV6?oe%9P0B.5b19c1: <iHV&({Mp&Kele(Ec".Ec55dojD@u!|&9  L^~%Ix nB1/l? g)U7wIH{_=s %KPO4lD.;/bkMEU7oA{D'rzsz i[ 8q^9!Z.o"vzyyABq(ylIf u*Uf }VAPkY_GCPxZR_~zVHW>0D;\}"FAz2|:IdW`mF4} X BN+$cqcO-ZgH_p3=.;?]z(*$-Zg4vKp,Fg5mxc6hd1".-A>>xr1 Jx;jHnGuhXbSY5R<}!y^{A ~<'_7d[eFZCYsX +t u pOw3mbzxJ=.^/7S  X7`'~`D.SxiAp)dl 7jAUXQE)g$ |YMI@MoDxp0 "yCZ1[c@4,W 3/d1gM;G.PXw@MM; q&GKxXU};r-h5YeU)B CpUh!MHa~g d+3EvhK}_jTmBjHTR cr3K,S7d'.v`cQ >yOw5=j[=B5kT6{E?;" Gz:G7PcPN8AacPp; TzJQ {rbD^ f#_){``G #s[>,`Jd>-o/)#"2JY'_=gK$%c|hqwN-0w4b GQ!=gC[ ;Xvk/-I"^C\E`++p N0FcTP('>.x;GC4`}N _^aZn,4B~1$k !u]aT^o-?t8Xc@&RxZOLz N,[Cce?1=:P;C{0"Kn;Gz yS_>mF'MkA8jB3VVw/W`j"2%=9P\<'>pW#R>9c:0 y KrPE_~:w9e>8{~kE:0#9n*ciZ wk][~5Ky;\nq&IpaZt#&Mzs|w5Elwfaki~9%.Zs_VH Z~e T) &G 7m6diZ^,{XUH=VLgXIRgw @[8 FI>6$t#zKCu<0U9ub_NqB\3ZZH2(v=VNTjW+Q ]671F}hj' x r`$c)\  s wht:b@hGgHF!P[ 4UkU u3d^W (.[gdo_$R BCj7D*|%*;B@(_ Wp B `4>u_RZbfS w r JY9W<e!~OJ-! o}  Yv14C RJKT$?E L: T|*^ G[P +iVO/zX&:y M -DY*9S y}]L A Lr4 C ]BvcAfLq<=H+ B:P  FA@3[){Sz+  W * G;]+kS6(F~rX  d  B ,0[>M+$ I$NG \ T_{~?p&u>BjMH% 0<  X ju}451VG]:a7_:  0 o WF~;#"\ ,' =  Q .z; ~qaCs>k#  t &WM$ -H(T]z?8  k  Q1%[6[kdi} x iHS7b~_yvT ~ k 8R F W,ZXTmE_R{'  Kz5 v rg 8a^^Ln3 Y1`L\ P k 4 2kH_@b"!MfhBZ! M (mir_eval-0.8.2/tests/data/separation/est05/2.wav000066400000000000000000000372541475740344600214100ustar00rootroot00000000000000RIFF>WAVEfmt @>data> .%aDgMgLn'z"w )n} #u Np<} Auo4 9,8n2JF43 6 wz L`?cNpaL h q Q!h_f){[w<-* { +  C Huz`SMCwD" WK  ^>PqXB 7]P d \au Y ' NhaS '*Mz#%#&!P)J3sLd w i&:u.- SN$J=  *  >TV~ׇ2׊ n;"n  ' b m҂No ICrn]2og* `a  ;Εz$я۪W~ Z!'#1+8YCz LޏA &..#/.%Bg\ y %н'Ğ?ˌ_"'*l,,'X h3K ):ݔ٣džưcAu5e $)/.o&.aty F 4 CXnzZL&IB"(7**(  dgkZEa8w_f-KN FF  ^ %  $K1T'9۪H! JH8 j`  9W$:͊`&ѵqeg ##%&"   " !<f@ڗ>wʀ,uש,@6I99G719+"=@ K2A];49;x.9~@ EIEb?5+Z#/; [ o l 0 gҽ7&!'.?5C740T)$$b   @TCGߐ٬Ш̽ |܏ $J,3R:94=1+{$  4 B (zԍɇn.˾m˧|@"n-2j584("b l ?9%#Tm ] yJū6 ). 4B87909n0a)%Clk Y( ЮZC巣^3߭ '4DMHD@8w0&Hr 4J![P®1y ;Q/4;@AIMoID#=4/'n4 .Hʰq-T55m at1h:0?f#R,v'i!%V!V \<- ffӬj˔$w/Ebsc#'J#h~tu  |"ל3'_ )9!~!!#J&%l"%!~ bށҗnDα֑Z&'(*o'(&lhS#ΰȶVعơЙ;l!!L !,-,,,,)!Z(k g׿ۼ }tتY:f:K [+6;@?;0Z%f[ rCؘ1 LJ W!~#&!"%$M"#(##q %V ϔԶL(X3 g a:L!'?-r0,(%M!VD 6BoAzmϾș ̈&D(+)Y,22-'3" + | 9zNb֖Jȃ>˗ݴv "%@&R#"B   !<iJl#ڰԤR? D@)[  HY`K:^X 01 c>[y7IUv~*~Xf%qtݼ[_tbNX7KC&SkY:߀)i@b f7/W 7 HJVm7<-N ' >cX*|a 'u!#| C YY u# AOPH((RL$*hB} # [;v2'@mo*y}p ht?9kpb,MGGE th@HhGVx>e~ 0 x4[=D9i^.Pt C3 DDZg[Jxo_A=qpH~>DS Y `[ jf)[ =  ?t4 T wuE  C y#ocn2h  4:x\R^/a7Q}O*\8SF@DV7r\a4bAK4i $4L79?A` xPMvC6q Xv_?&92' ,q^G3yN2|J@)A Swf x&brE^cCt{?%gQ'=w,3fz\)9$=g'Cl+~%"], # #2II@LqnfgALh><A_`a^a9zAPVt6#)( CEf`;AD"?7pa0iBCo"dBYtL,U}$;3jOuNV6Zu|& :wB5XV'.F&DC\|ECIEEN341~/",HY\J GQ*0B644Q %-hwItp>HD!H>/F$#? +" K3; I;&@, 9JC;53@ .E E6^L;ts<c41"C  :j %njV>]g(:R^,/M86 g|/[, !@r|/J.@ 2 $) 1\VaZ-DAc  L TjX8WjVnc}g)+29/ B 1W`  / uf-|P,s:({lCl #(M2 \ Qc.u2{ta+0(+4Uw Q1 JK#f~d$Z0i^ 4ns$ 1`WYlYT\ [/Nc7b+sD_ >PlEZj@U{$  k+}W d 9 J  #(u~|mvV=5 ]  r V %tG3u*D#ARWx ,  y .%m; % w;%O+Je $#"|  ? %w% Fp~qd+o?|T[!u3> A  : @1HYJn2&jRT_anMo q "NGpx&rA-a4^ 7_ m V`yA2+ 5MY\' H0@"N cp "T%m P r }XO*ssDV<M'g}4N9q MZ\L  NZ-! LNdm   ]j_A0{U O[b}/  p |71R` BD`- H  |oiW v ;rTn(|@  W7:GV~RD7\1k}`s VV= WTussVT0Iy="JFxC1+n<da%8_h@5(V7$GZ TCPk(C%D ;%o3W6[:3J CE;/ ] $ u#]B|pOip-zX]d:vV\ Mc:Z,#\SfZ+n^+*Y #w   RvLcP(Ya?p  #  G D+8 m/[$)}KEA3aKDL>H1Jyc 4b+7|\yYq[ 2A$ t %22 02>2/OLK MA)5,b~6V{wL: <]#s>4y@]vh'<RvDt@{ jG(!<9>G|M:BO rx'Fli^'A_PXY?j0RSbL@}-,0u pc!ZsrT>=KSWGO`wr!.-_T(^poR<48pE!Xcfrx6 J^|/)Hb=Hs{nkw3g GVUUI3qxH!uMY}0veCsE7W c][E(eYRd&F2aPma)vF:DYY[+`Vhre Ij`8(=Kc GSy QEPng`w]6n@Inf>DU:Lz3qs-PTTi$g#.T;_A[[,$(t7"e\^ V+$ (i>NP61FL>TU6~S}H FRQ#oB8hVvU+_w&Xfd19,&ehA{{h  1gNq,VB$81#H2kA5bhX+ 9U%N b fg4$iOKb.]AoNJ,nhdwtCn[Ze}~# Fz qWSY+[dd:\|A147Gw[obiA3@g~s,Z 5t6ZOTutL>B lmd  56h_l%NZpM_ > G9 7 x-YkJC_1">k5Y V25K: E + ((TZ%?`# 3 b2y01u#O"%&%arhzp?1rNVWiiW} #'('k4E6I_IY@?BM#&)}(!z Ns\wIL)&}2z7 5"&%[ \kGtJ3.6Q1a; a&1i;:C5, W mݾ&*7=: 5."L &R\Tdڠٟۨ*ރ1C},-8:b670#YJA\5VXl!"{1642'n a%nCR`sNܪ\$2x8v73) ;wDTfK=l޴E+m-X565.. '3kg4em *f5: ;6G+,4M M]D 59+"/3q5 3C)&7mc*CX+ݴd*f+3K55d/!F kF%et2P q$.2 521' :] ,y/ض[O={ p&q-32-'O; _AxG(3e-bmmGI(e02&1+$c&% 2|nJLp.#]LJUz %+.W+'!mJ ~gOvjYڈܬ$ !H*--u+%~:g FUfM4st  '+;+&)#%W D: @* M8߮S- &|+.-(!z5OaIke#r޲v C!)-|-&,&'  f^&H^HVX c'++)$>nu:Fd]/5ްKo  L'4**g'-! oX2Rt`Bol %!""d" ! F|b@22ڏtS!O)(.--'R2iMzj ~$=+/|/*-' Pb 0Bb5=K@"x h2^,78 r {cow5:--yF)F@`,J&rl=I&\n$uAB Q u O=;] tN1 E i?J!R, Yxv?nB \4>> I~o..;=G;>N~X^ 4  +SC&"]3< t`iCI /q o-g:$=ck^? :4r 9Te*%>P@Q.t50Zb<#T!'m~>XaOER+WAnlM2Q![jcH9!hSf]~g+lcS$];*60}_mnFc8Dd#i"Ok>/y3b5jPi OOwA I w_#2KpG)=(digR6%h#Nxi%# (:/|_7hfay>{G <fBjAg;5j6C|z{-.6n Nt O9e+38 4re6Nu,\I gZ.7A!tVu5zMm$~kW  E(4cJtapx)5/?af7H;YD#v:b IU?5Xuwg!P#o)@zmNu^[#=U 5PzKy&t:[~g?Lg?)eH .cmir_eval-0.8.2/tests/data/separation/est06/000077500000000000000000000000001475740344600205165ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/separation/est06/0.wav000066400000000000000000001750541475740344600214100ustar00rootroot00000000000000RIFF$WAVEfmt >dataujt, {`94lV%XJ0^ge,H"6 PTnS[Km */?V&ozkHr:h%QVw037dsNCV_4MJG3kE - -3p#+;j2FVZw ,wo4|B-O^dc.h9n&p-uux8 L.i)b:6w4Za783_Yl(g~> X]2'A! )LfNZ\1 &*(26@rizwP>IH b=2`(>X^.ZNRAT '"*6JI" Z>#$Ms3|\7x$w8d9.7s2jH3u)4WxW]~e`_h{\ +Qj\ &yO{3 'U|awb;P(KH(AQ'B<2;L]Gsa=&Op%EBTUNxO5d +:nY~8] "IB$1FfeviQN1^; :po:'^;6f8Kv,Uf PY3^6ylGn '?~LQlIjqk0l2N}xm|iVj`/tacT <$2%HSy]' 9\!2%78hwAQ@C4- Tx2> -mJbQrm7e}Y'!.q>[]TryfYWyVMyvpN&$p@tOp@*uLm1/tp,UX2vx"]*[]+tr:A=h? J{vkqT(R'.&+,gHegR*m3!sOsGi1J#FC$3=""3){4Q/$rQU$%!A +;%2/+Y%i2ihU{R{(wdy4~ 2O+lLLIdz@sw@_h^%X/G:*#@ n;{-c$Yh@ZnLt 0@  :=8 m Eo?R_CEB=8  A*d6F48bw @ V /{=pd92V=\Iy<L+]e#- |E\{_jCtuEop le_YKFlgLzZr497; Z# bC5d{I0msQ(HDvy }?ZL-zcG(ug1oJxM U'F`T3B vt@VI>b"%/FS-B,~+:h-mUPb*n]1&jk& qN>]R8C"@:;#dD N-;QzI7K8NH\:`\+{F; ~Y]SUtqU6xF, BIT 6S#W9<bwHl{t$WWHD <| _]1AsjU%Sl{=4}$f*Wo1`-52*/T<o{29i12zwDaC&`v _&h]:&>e 6xnPTg*XErqZQUVyN)RxOX[tIJWXjqA>rJha;N()=!(rcKP*5J KloLwel8)"3+?lGl+ZfQJ'f\%)+h-" j0j{h7~^*>*s {41]tbN ZiQI}H+?%`8t9>Bm[Rm-0,2" vFv$ NnZ71Zbi%{I Ll 6)i/t:N}6T+BD+Z3JP=B*,0b@ {0%$<%dFLBt[[)\m5{I@R}uMXV?z8['CH4|Am6\;V%$wmO:HT?KG`SbWESw Bx[y];EW"( O.*0x+a/NW9sKx-:eo7!]Cr?2`omWvjIz\F ;@? E-o5CM s`g%;)Y 6E|Gz^ojRS;?Q;vkqs Y8HNORa'Z&np~:*.ndXST}~~'wl[@DapTE tI$2e"B.LDuhBk&9| 4(ky''}~1 ww*F)}?D%F<&*  81hRG~,jHA7rf`L1 Hk } NV2u.?b=;{Uf>uQb.NGpf}|w iW-zop:2gTOAIiy3S~YwU=]&Z9~ZIi/F6;}:khF&d!?Y/x,&A?x g%j"#ij"R9-FO:7RU&L78*IM>1q C$V[|`| a.v (/q9StIag{*0uF U [((ZvglvJFQPQmiP"FDm zI(v [6B,9h*nv-:X(q= &4o-'& cGasd2sgS(KFdXTS '4XOw?h!j6h6!idz=+CZ=1dmh4^oCa+ v9^1:s\sV%1=;@0u1}m@8a&VUqlL$0+]0V~{4~N~zLB>zYEctv%sI@O"rQ"$"/FxeC/N!agLizK*`!DyxPoGi{8+;h, -]p=/YAZ8$Gh%'cW7*Y H3iIHWrf:1.+?JgU=q_TPHZ766 vOE$l*Y-`zoX; ( byk~J^` Kt |=K"$tYIoJfO.G[,~H;xpIo4pRiH{}0p;:M:Y.E8l($SZTDt!2AJ3Dj:mdQ}< 1f0WZPY\3T6/n u/E(Me-kK2yCd|wrl'I5]eAB{n}zXL!vm[?+VGW?uo($I We4?cjw?Cs"",1yI`!np&-) KfMB-g\2]Zhy9&5Y(+S4>u^^uAN@Y7TaPKr; 1WY0d|[6 Hit@QK:SLRTb zqRVp6cIc9yL2RDp}2wC* x$!nf$cTyqsnYi616tB"A\0Gx y<-Ds 9bv3`)6]|_%eVhD&TF.! Y@u{;6[+MdCwNX85!]7jFEUQ5a>%[bVnubrm #+|j/`*O &-H&7FtsUIA^js_!5J>s(0$Z f3kDdj^=>Y79nw;o'%<*$/c+--uW7  ~!O*> )u+JF*_|h!kiYI;LS}$  n;n)]kx4>PZ[%eV\@a_H@YL IbMs6lu DD)63F6GI}S#F (yev4P<&+;WO|pN;G|97paRs}91v8A} tfejR%0Zz^D^nnTmGj1j;$N@qj8W>z]ehQIRR{rdO-W}s CE*l_c5C,tR;05+|+D@>TKZ P-dCP1Z& w[TL? __yf#-A*3Y^@-A5w/ {:. HJRD5$Q~iX*`v@xv\n'7QGaKHL[,.JZR B#fB/3uTL S>9Xkc-h:Ib[xHN"\{T=BRn$O/6{&qB}Ig$xA]O/B8- C{+@{._1V2gMg_^5 tyvqawFU+a8X-P@gZQel O7A'w }t?U*]oG<y@bm7=X"&_EY]WF> 8S.L%4<P ;~mE|9?%b(ISt8T*Wod%f4]wT\_lQ5m~pc^bIbHqlQ?Pq4i\D]}jUa?1 #7Gm`1Uvb3o?] NYyJ=hNuH o1|f$zL8l9aE><0=tOL/?56_lJGU Tn@&35CfElxx nD /jd7)\x02.92b-"" 87D"Z1CG/EfhpGBR%H} jam\% icrS%[;Zw;tDV0o\ngMCfNBquM[=*Uh +TCd}_",Geosx(kGiuO*lg<B3M0:C:IK.QIj aN8Bm wM  kt4*=,K<dR` :95.qCYk~N$[F|8%L6-_}{|WG U^")c{JWI#8 =yZy8L]xV4O"W3u cnv5HWY4rEdWubZ'R8&#u~lU6z ?} XkNl^u;) }:fL:{ JbE,$$;3,N U[/(@L x0-5_F  #'`x6_. |CcU|5G'hC H%57pLm 1'yMqzOH%]^Q8`@)dLx$PE1pU>9EH,xr{&x~njCWLIon)"R?c&eue[;O0|u$Y{6=fLOt\@ZQuo^noC/b6;+Sog1x6m'?edG*|yOduIo|C}9@xJ@P\49.qhR449]B -B~_j)0_vNN"F|4/-*nrc_IP}e;|s'S*;hHV] gf  lj&#eaw|_,\rA >M?JS_L1A&+_:q^"> We*8A%f<!YcgE#qSS&BzjB/I<+? VI.7_hlN-}Czb0H vQ5e IcjGI6/&o%@c .q z%|rjQOq29}. 1ViiVb6C5,tP< !98"b^+uoI` mmtQko5LOE=Bk6jZO=I gz{7;S(BDX4$~Z8a%29cN{ByFkP i<d`5H\5Irst4H(p[o+@wni_@L@@sp5g d*n4jYl<o/#)[y ||ZQB2^i%^;fEXnZ  bml Z-C;0){Tg7]gYS&L808%I@y_pMZn73\=z[)w`7! 6y 4L '?RKF l,Q28fw,WE% K*;nVe~8O CH5:Uk"VWjmWi-333"\rUI?2|w&f !KsWV\T! bxrKyFWYV$|gGuIE !?] BM@Pq)+jNanB@(,wA)/;XCQ%zr&M 0|t%("2 ,/d0R ~0(8*]g6em'ykq%5O{poA>>HiC06W:a8Z{3 o@=T)_TP(%-WDQj ebEjZW= Gh=pj&G+&|0#d )(F7Vc*KN6HK1S2-l-eS=3J@A$  Iy%7 6-Cy']~nKgr+3$'B5]4de@<^86m# kOl/Q_iXK5`|0PXC)/lwNPJ;JCIjA*@[-nSIh YbcTq-erX||ywQO.T?{#7E "%ck]ee K_`2U[t;J\[}y1jG Iy\j>`Q9%o#r)|g;)Q! (LJGH5 M0`'F2}:c=D5.ZY9o/8vSES v{:ozhwi}q3+Z;?VF"=V!(:%PUU+X5Jf ^B+TYDAl4m16kpaaMY5^G"zLzf7EquVI,1)kZJz?-g7n)#@d7kC`h@7xkrN=K ,_%D3wP) O( N=Y|ZB- oJXsS7?W9VZMY\Rv![]hy#|+Ng 2/V'rK?*z?^X 7E ~*Ifyfzr8_L' &Nk*1AoFWOe \DY&(mx:m;$-*x 14]d-t9+*2 z#M P 8 "Zv6*,[Stz<,   _>xMw`lH'%3!:8 q/&V}]mXJ[W*e"W]42'W1MJw\~&[1V HOe`G4j(XPQt;hWnwAw#aSm (5[b=$e\bZ`. fxQ1K:rgKI gt9]v-B C(M:. hEhr s^wyn- ;Ttwwl{?_]aCA  bL',nS4TB:Im:E5E^qM+=eD|nNZ?My#NUHTC?\zr|rK4L Q"w]g<6zMvnV6 fo"b VFNLE|TAWQmzV6Y j'S}!,,"9o}1iN*^)r&^Y4L vB}(Jfrb5C*hjI@2U\ %Qe.` BJ'*hRT`:|43$P]g=j]ZH;\0deZD onn$$M-1f``<w|w,`HPF9;m}`9N1x<hCynWKfd~zID 2AeMM24:lhI\}!(y+ud`+k }wVOua[3*t,*C9Y:5aX6:#dVH0?^3Z'Ajg}U id(#lful KB7pAj\Of u.uYm_61ip b_qzr}U Q) W$CQ/1m y<~+J!uFKF/#q dF^i1m/XRt~ "AGw)~LK8*;:#Rd wEY4PyO[q830/;Su-}tMQuc;5i.T*Kb,JJ&R "p'%1diM;dvvqLx6{""P '^/&6Fz3T[~d [@{g*p$- N9[4kKNqk=P8'-=^rG&$Au< OCqfKK'1c`ci a|2/ %ZN?=u"?vB jACb(oi1/03j;VA[*3^@ ~x4M]1KQsuBC`]\d  sM[d,F~<OF?/FcGj{ s5@Gs]`p8r^-P3~t]yNr~w3{ '$ek,Fn|l]\)ragl2sb 5K$WxJLjNyKQ6(D@3y rIhJYdR9l gy`Ml ' F [w 6jqu[>3< {5w,HtDm~17cOt5yRd1cE}WKK^RW< xzR z`F+''/NF%\'NC\1 _UXY>.Y5I3Lc}[6 AT,CSR^$47%<&> ;oJi`t$Xp2p 6tng7|X3m%#gKV[74Kyej[2W'!_\,NiZFW/K<=ZrN}U+Ee%xt}rSUmUmBD-MsYl|hP{".t3*oxC[qTH%)lb]&>Qc1Z}%HZ`)*S,nBxVB)2g7q&0d LQGXPm8,_c!a[5:j3Ki9h b?epHB/<5q<8f2;P<Dnic( J[ZY1P;rvWD2GJ}r8whE$%hV_G5[rr~C}Opacc6h[bG.3*}1UWb60*76 ?v;s83>u7KzL|MZCWEZA`G6+o3i4}|M1',` #zwtYQY7nF6pZB-Y`oAH"f%w0F\6U'Vw/DPPoD.]c\Z@udW fk7*JHBWC:rZ4LPvg(]*tc_Zh&whZ$c=]0n~FxK99K|fmQiCO/]>OSz{&M5%^RTIdd ,Fn[#x 08"{Wx\;'>#:X1VtdLC 9vR%|'o|v#HzDjNd%=_f\<C)& gt4J8vB;]x@V&7(]I(cZ T s ]m&n[9<HO >1t^DV"a<Kcv, mbA{ms M$D7K])o,  <:C~wY?B)(+D,=aSI%^=?!Rd !AoE5d0$,}iqWFapw|J MkGLnEP1sb<-=hVh;w&CvCj0/IIQXHIe";;@"f<Yo$t{|^[]lAvrpeT;s qhI$n y[,E~==3xU<!^y-M`.aqFnmM}#p9>QiAr[Qw#f eV4B ~g:;"6Pj^X\ irSHQU>QX0a^8?oh$_BgJ94%qGfMDmi2|T7MX/s;iLi+8aF_,.^Kx,xj\9\FSx>u7ghP.!>tPD'vI!Ge;__;[H1%z T y>DQ M:NU4WT>4Pm!>a&5@7m1j2pY3)dU:gE /&6(Ea@3/+yCHA@GMcBo1 2J",rqeOU*?[^?oM/^an( L4VWP=o Bg~.!;BBX bdD3Z7E"GOX5^>'(JSd+J+W0L{7v3wW:0i=h#3@/_>C(:&:#V,C OsgU>ym%pHhV63y|jeLo(X~t]kGL$P sQ K=6 ST!" "{~K=W4,+'Fw(8r}B d6lcy<@#Frnb^6pv*(QVmzoS>5#ED9^%;zt_Osymq6|RtABc@@ztQbMj]j|u"FC- #7^aOK -3oCk60>9^OzS'PzcS=,(h2_-A!y|k2eDa#XR|\? -%"0 #.khS]H1GO _a&p2-MJ7o2\@v1/,\9E0TpD,j<(oa , V$cd2e$ sdlV^p0N-=<cU Se< &@LgP  $  X p  f md    ao  e  2  *t6,/Or6d X '3t^ 'QBM j4BA2&G  [ >wrM 3  t # / eLyh8vTx _ y  ~ X  u j ^ = w : 3 S- Z   ; 0 Y^34]   M ~   + L } &r   k 6    ZpqzjKz06" `NjM2/<uTTKnHX$Wd #I48:!wf0rRjKyPR0.H7kJE5?1S 4gxT?B^Mj;R tWscV+-2ASHl_CTxxU} a6B@3*!6L}p8+5EzqN~=t_1[se3cAg*>J G(=:"%r=U%OlP2 ]j-pHPh*FPj$]`+N':9 7($(c'Z^6""KcC#Oe.V|}[SgSBTAtsjB xjJ-(G7_f$7I)ARCR#8%rSRs3h3g*/t Pgl; b0S @,N kRwPh6_Fv[]?DR=-p %uih6 M\0|<CsDC(:(6  /k hKkh.ECs4U.*_Z]vR?:8myv~ xwH+d%1Jq }9;Va| VWc^iSKLDX,\eeTiRLR9~\Yd"6 TJR@g,Knlvs6.>Y1 ]:x<;DzK[@94dw~;:D<,/ { _'s)fe_0i0O("M; wh'_ 3TT*pyF ! 1bRA$y8,0 2tJ-jv/-9i+&bv@ib ZelT7N2: q8SPUJh%.;+=  + \`{)K] ia~UsB;^\R'h*rH}#{A-}B1=X|r1?ZEn%%=(TO5YjCyWH z2HG 8SX N{+$CO`osRi( {ZG7Pv%\\5] ,#E)MIy%Q9"W5d6A7p![~/%1HoX~STy gU}B\w5J='5|R,u V2T[vefgU9arytc8; K:c]Rw:mb^4'B01 n4_|G[g J+5UL#p4W `yf&"*I H/ 2&J=[|>UW! S)=`pK# 6*zt:l] f:D\r \S:+'p@+^jCE![y[d'{m+V&Y6cWo#I_?C]O h$(jT Cz&^DjLT.@c3mF?7M{?0O$] F[MH_}w%~8JoUZzuAfH "|wMAS s:ime39i4$QXX(fj"D'v-#F?_"T%`E|:]RC;cp!XlqJ4j%4R(!"eLj2je4gp!~c2$ peI8_}h AHQi5"?~^'Z @0#rJo;~q lsPp |>2RB:atW7.}n?(g_p~tLS'N>C+7-PSvRW5xq|x.P!y ~d.Oy<1rT~ 92;[{ubZEyd'GL qhb =ltpx=$U2v8$v}1_oU_lMpflr25TXZ#Ncw* KZvut#>=0tmk$15 BrJfS4B P/Zkod7I=$}@3}'g,Ddh cxyV,A)e (rgqAuWxSH% g)%0n0y2'd^n~3D+ /@f {=X;k WVQ7!LwyD;p5{vv.C DI#E o]]`;qH2PHlVcIxS P2=:bC6w;~,gt`!/bo{c[}X=\G>NAy*]-(e'mF0UbNu<>b;]e+9=bA<$,w*. R7DA(nC!rl&=3(f~ 7ebm;n +rx!V  W}n5A|ml.@}o}Cu${D`[?dg?G>cL"EY-*X%B_.gglXCsNP.g!?)LRC+l?~1 Q468}xP< -IdU*nEuog;wI>1z!|)/z)-7W^Q>P^<9(oyd~b5gwZ'6fef:\/ s`EeHBm2faA ;5dj$t.3vt<O|~dJRF7,xXGk&9O<nCo/MYXO S9,+3;tok v \k.Z(h=G[X|$}fy&#[  |!q~WZlsIf%-E#.L}Q-p4I5IGQSi Y(F)ITfi>P`Xh-rT_9t G[['WD8I m)UAxF(. lFVX$y&,nAKTD5M] |h\/mt#*s-8]VN. 11F2 9Tjs*S}n y$5E AhopYIPAi,cHxdq/+f$Ur5ycSP#o2~^L sbp~9mcSKO(,;*B5^7X </&Fw,z,.@dcviS*?z|yOr|P7%85_KapX*LGR5g!]B/.\^0XBINd&{6O2uZ]-Jr>[~Z^\\1+ MW^HUv{<m$dv}F%sR'_MuB>G"-4Xxzzy@-'Cd"e-6\,$A*HC;{S\s G*Miw98RQ?ny) m4?Gu8}BaCA7x3x%(LBuAyEL9gUN@zv&on_$*&]kq|AP$nr@U<_DQ sNU?Z:ypmW 9g:@ oZSjDzpW'n0"W%lCE= !s$}1QLfRc~3]@FqX$HZ#tu"^){^TxM$4Hs W?g6jB^bO`4:K46|+Zh9|QLJ}|mKIII/% *>3l$]W%O/j%,#Qm`-yeHM,r_$d;l* O8cx72R4w2.rwr XYh6S|1L9aqm:4A)M;6XMXsbz&+D8S:]{Mu*M/"EG \dw]4xoEAaaQXnDv !FY 80hqJ%3PuiB?NO7,g)+l,tx8J;THJ*7eZ0Js`$D8:=iqh\ZaV;m~~ 5opz/IuS[OhGHdnXchhVV~5>00`h}jhg? ;f[4I7IrM<O(Ga @M6"z0OqJA+ ?7O.CV?HVueDkNz$=jtP2b9hZTmg[K'' $1^(bc4Qj:<u$ub-WE=alp'3w \5crC(2a6vDh:jHe}yGZZe P~^N:Y34 kT36\db~@DeXVGxLf& |KjM/B FHlg$dm{=uWNZ%zyi CsO^~j[&u=05bMb?mw0XGLF=9vbJpPj4O5g\(7iG)JHmN*.88H!/1OK26~j:uj_|(?n/lS y@@Hj$F]ILn-bZC+*NYvL\< WZGv`  "*H`mRm]H2@b6w0Hmc0[Le C9)y<+j2}^rpwyyxTF9p7;@.}$4XJGYTL#-ZlJ~ jxXW]p DepP`<@GO`gXXfJ'zm^%h [p>h28 16V1> Qb)q*K}FY&B&]mnQ.prr?DCACPftgX'd(]V)#?!MpFe.iYLRuKk>BdYmyCQ n,~6F2".1m}Piwd*6Z '3#\]#bh9N4Re^g%di6*6d be*7d15iM5#}Tg"_V4O_ ~) p q5<'&VuC{bB fbOW.`bD3tD}a;55Ah4kKc(GDYylCo#-b_B c~frePJB}m.i>{q>O;<Ez>DW233@mG_lD%6R)vosd}lBgbDav[_xU~CKAQUH1C ]l?~8B|O3jz}/e2ddjd$ 7#>Fbv~Si-9G0{@l%(aB ue@ WCBk a|0R?<1B>=+i{80(S)L1L|/!^_)tc.Exv##xp]a2~\/GcWJp;V rl xrMZ46eN0SIA`ksW7j5g=1(KxBtYe;cP<cimo0/H#]/p 2V eGk*{1(O!'U X&_MFuv!n~1%"h[o-zCE{e~tmrTn5Fe3GaO3iKT-JWNY+z DNOQ7yz_*i~+M.HW' m.% B362 4x\I2UAf6oF};P  WKU  BVo,-uO %'zEs"E 6#+xZPop \^MXj qwUfx[eR0)/?V{J.K:oj|g8q1Ckw,c#|ND Q)oxpH!tYSFA B`?!.vF]'Ykqt:yv +o~`gX|ggt`[R"'%(F?LN$%opp^ {-}'E _d%W{]|*&nH+S4&h?FG"n{tF)HqltyogfY[ m&_o/q-^c"t4P9oT)sPSWL32WbTuowQ8 /gyvIlG28)lt#F*>9cX`Ap57.l- #6*BR .1dRF&!L}]T'~{OHzJ [Fdm8FXS7wT^Yoae<4UaJ,\:(aTM7W5zba3J-^GJ) BW7X!!(TOMSA _;}c|"6WT22fKZZb@NFFE+O^`K+ ~Gm$Y-t(c- @~Bf;XD%6u?DRN n8CDSx< \(O/O].z/to, =ZArQ:4l[w/"l#%FCpRo" i{j G6@gNg9kACt)S&:*_h;w5nB@z!$1or"h` D3/&j+.P[Ul}SsT43WWl9E hylmEUus l,Q?v[.=+]E`@ht_ qzZZaR;y>7LJ#!bE%5(o>s;4:9O^jyGo# q/6*6!}zJ9 L kc +X 0mX"V/**s$M;amxFz*I+* &Ar8,D*Q(r7R9^y(,r,vboZ~9TBVqR]9h[NN2*/t8:ZYg\9q} "F~A!]~L]0"o\K':9 (sRIN/4]5<V{~R #-i=EUsT<'J9\ \\UA`I^b?:sBU Aot!Hzau}XSMl '2 ,aN;)^~)px .Q40QW9drSv% "A<,@]%n]=Ze'n@ 5 >9A.;H&ei*\ ]Q / F&il":@WF*LF8|+kkG)*I)L)"QmPF~ 5/;Xf8ZkE`b))S@]SO* .72ryB8&m5!OTFJL(w SLUL@$n4 PRn7C:L@V5P\oTdL_1'j.2`+he- xW(pW]*4T6[..&h:ktR R;~f,$:7g.=4 hezu+]|]` vi$)*A"+fyomvMt"gHp@AP<blx;R2>4<A:2l+" F Y41c"@ G>P'@7l#?MY?p-PE@:wX Ek`Q'm!'e'CU E1sdv,H)hbc4'/4Um5NN0YJr I!0 ! -:{U.uWU"n*&EgJ(Sb!a|>yL2tTnS0SM^`^W4%$'5LvMV R6_$EP-R<8*LVX;4n]mU2R y) nv,v+ZLHR#N?Z1'FKNN}KQzc`ACI{WIi25S-A7F`Wf&hj"2] WuZ<+e\iBvuF\EM;<pm > 57gV `A /V&)2@(?>/?0![8$LNbKY] zx s[`+UH~ueeG>;A#nTU9m6T;X}o ()^ +4zv=MW]b^U)sM2)5<-DWjx>uA_?gz:,22,S#9 fAdh:m#ex*Q/Os"p<|%|2X\K[QEMe0\ p3( U #`s#sp1gl^ mlxE\DV)7F!2P{h3wD.$ =k|v2:9!dl\,~|CTJB].)#),?ear7:,9 / )+ W!9 C^n]9{c%WU'i 1ltwO9+8u&0njoR5S+<_o,d0vtUm0h%<C{p]qCN{4W 'sZ~Q]*72H^#IscaH}e =,Eb5WP+ N_<e[@Q++Aud(.E+rZ|pYsQ]CR]M04xUL0|^qh8`Phld1L8?!UbbvPu[m^ue{rwx/i-3p~loif5^|i|VO.sZ?|Vy`K{ F W5#JqhN2t"VR#,}ESxaI%3=b[)//;R/Fzn;e46u@?NDi\lEUOB; m :7S<X8~rp||hU$:nlo$Fy I2tx2gU6= :*PY_{FPgMfT`p#$W# *D$TgwPWy42;'bQMm4uTp;=)hH{ RhKO=rKZGe YG!zF[~a6&8!I)Z2psD$Fu9{P4kS& d ' g#DJXZ=rN 3V2, aDT>;CHb@ZZbh !alX(,/37f`b#)k! i>W5*j4\.P nrxCmir_eval-0.8.2/tests/data/separation/est06/1.wav000066400000000000000000001750541475740344600214110ustar00rootroot00000000000000RIFF$WAVEfmt >data~'0On-GB 762S!}RYV] $)=co`K?<F94?=7  rfJ#.g&@H7 = CIM3 -<J8 1%4ai?3~bsvJ]NatqcHR i4A5 x*y1B=p~i*  |wt0MiU"AWT* at--"  (82g$a& $ tuuk-HEIkq m Q@IA"'$w v`yq} ;qq.<H@&b}ss<?`t{iE;"&H`aK;.#immx |w`^rsq o%  +=2:4wlYT`x R7 >MyS?GJ1$ (IQQjh4 $=<,xXBjZNkEiRXp#lY`p()-419-'/;/LFMJTM\mu`K5' ky0n&.dRM2!5KM I*Q&r j||tqvKqAgUzsk*l]S0HkBb'L]dynKY b #y1x>$)h09I,GB#$ JYT-' $4\dP90K;.]L,! <JJ rlj6D5)f"zXTZKM_:$j,rQ*Y!>U7GN 'kIza]KSWn~AKJq,5R7mu0yIj-(KN]D]u17 8KSJ*._dG+y  RJW{)N#dcMNx&$7_ EJu5IPulpBK4Ge(c$d>5t&@<Y#if<aNk{% LwL.^o7D+o|^^9X<t0R?D%S b(}!d{uqOh7$d#-BfAt;gB.Rs1f\;%5V_goK+\+  qX G[0^D*dy(fRZ%XL4nNm7`<:9oOp mg {a$mLz};n(:4p&E>.D}x[CDcKJ^H:f r"~ts;M~/=EfWz0<+c"z@ ys+o1i[&CecbifZX{&fXfzu+k.a i(6p8cdI^a%\C'Gox$ \p=:~=P^gYfJGtc](a:!*8 ;nwz=7ZgAY i%+/.}836 P>I_<e+$q0u4*`ofRH`w 9od>&;R WMii ) l2a$K>Q*]a`)NRv }=A6# [# 7,Zy U1 &/pDkJ.p~aL,{)+ Iv#}"-QjbIUKA) n?OX.9ACAw~[j5z+ FCpy[[WZ~d"gxJOyAet?cz4 l0b- t ~YqtQ&hX5')3aW ^H;@ 3.CxuwGM ]?mE2$c1:6nv)U&UbX ?f62_vXa gD}O;(Pj.MiNIeJuV=%n` peVk[ *K& ;$4lhCY$l>/sL7)}f~r+#=F<y;"[n ?W'(J]]48%Fo 4MLjR\-.MwlU+mjIF[_j$j/L(*/^vGzdE`&r Q>4 [^qrv|YE9g*1D3:-(c|r}WptohX/"JH f6 O8 Ma (r*2R/$qb(y S] <*(;a*pJHrOfgTD.IqT1i)UZR\t/E9;\~O]&J(0QhK0~~Oi<N%Y=V` a"gqmb fzCGCg'}=2xb;((-$## f@^+>lgPUB0u&QT_ us#S2?I"$"2}f.3!--^4T)1_g1n&-.` e{ EYOCc ^yT2=u@lOyk_/kP s"zc{=5OtH65[l!Ov|c kj)Sv:X+]%IIv (6kAa,D0 6 OSVkA L!bA:I %/;j Ae3+e'lv\qCO AOhSp{4"S.Vx C %tk\A57Q;`$Sv<6Q:WT +.p5va$mt^rx$P! < jHt\{`rf'Gv (*pO?8zbEmrGhK4 /Ga9+5+L[S=Hh|qXJ/Fdw2UcfG )H qv h'K#Yo]+E GS9.-uex C&^PFZ jbjYJ4ko6 7dZV:&*50  NAu}3Lk%wN1<@ g-$_D%.bk3M O"Jl J};({2FqSO/4UNi;Pu9s<)rZMpMD!%`w|no<% G,3.fL q* >o^ Kw#:I`%liPdD{$ r?6iXpzZ<$mZl2ZTOqi?+*3C%3k~b w 206iSc;  i a%S ]rq sfN:CQ9{<TwYtLBF@mb oC6&)mz<#F PHzpo^oXtN.TuzhHqR7=Yz^=Rt 9z{4+=n>o-Th #V,_l{~P[kw!Y N%qbnrQEFZd<wtOLXFcu/S2`J<&P~f;H^O[Rb4 5+QxJ8mcC$ "CJ)!8H"5~r]o\#w7\H8t%V'a*` axo1q.QZyQ`7{D:eJjN!)%B;FF' LQ\Uf{C6Ur$FP9I0K1$6b<0#'8&s>eP<L&|-.6'G9~)XuORyph]o) tMsp0^aA$477\( 7 lf`  zqcJTUoSNKL^ J@ol^u,[ie)AKYb'" 'wpcT}hWL81 -AB%/L2;S:U" 4 efwChv|AWP&fSh}zzq>YYhtEc@|ej^u_uqI1Quf 1 "0R1_F>$l?xXa|P^]QYaCD&$)  1.,  &)$% gmtLkgEGi,F~cutqKWCUh zund Grr2ZO(3N%n~<r!LPwD,)rx 4hx8x>Q'szF.cO#W\ (KT4C2;Hyv " 6 C:!f"Tjdais9,=sszMtZ]K _ZxuYfgz|azbqX !#K'+9B#M/RYU+19CF@gB,IDN1LF6dA8KB )0C%</17/*:?SS\PGM?'"1MQQ;F:KEy*K E52 2G$$u|( )5= @]@)%#2 /<3<> #) " 03 0"0KISO:0C D1&   CM F.*;&e1K?27)&0B/WShS 63?   3=:RN2M5M?Q^Hj9tsgZ[U6DD8;L-F=   ' 4""48,'8N@7"  %5;T`*1<>] TQ+0]F-,(<56JHL 3(.>Q9/+)A#$G".( ' 9 (15LG-$# )  P1)8E2 . '*$6,'%"%E7Gb$t9lCW=G(-AG M\w^  BVlE[[^jVA 4GA@=M!RI t#~te>QYeWJSH/#()HOJ:e9h/iy9]<d9_*l Z+ ,( + 8Sb<-Hnzc6j?q>l WD4 6I4 -@@>$ "Janr)sHiOZUcO`NfZkcd5vEt..}GQ2! E%Z ghs w@-<.e2t&9{==>9=pcu\z_yf<uB # 15?! ,1!8;Q+A"QA3%;Q^ e'sV; -P`}f< @'D@,2&8[.x,x#e\a]lR66536#!;QZ(  &' !8Z^H1.!  $21'0'(@1MP8+40V4a^]1. Z bog_RbN4+(0?4`=mybKI5D@ AQ> %4CC)6Q0[i)JE>05N7DLfM:18% ei^naO=);  '?XPPB:;157!@ ?8  1FUE,+ %)*41($'  "'80:_[o-FG?80=DMPKI<j;IE@UB#U-pgY_B<)*;%.*%+ "! 45LK@_+ l:! ' :.;4<L^bO-'%(, &#?B+//3XcbT5>FWbuj 1Rp~^v7Ej_bv}(=H?5KRkiu#3/xU4#9RS}'HTB/1AEDB$E<3@{:P jg C50 m di[R2{f.]lvP.(ViylG) +Hbhq_1 5-FTV, 9C>(DA03#(:D8 nVf3 (BL.5>B3>:*UYZl Q _F E _ ! 3oe;uf]A$R!@s/|ed1)Wuh"5Dyj}w[p{"#BnN.gV H| Cz83 xC)7.Y:Y,WR8Pv,4mN$zdMPV@4L6w\ruQc>1-2b:Yt}ovvOsC{2*,Dd b OF-[DJC<"4/SDq2ghGp`p]6W~eK &\a1mi G^W;@OzwpYOI67wNjTyVic:(36#T6 @O 2'BJD204;V#nSdltknO%G|>P]]wFS98BX$X$n18RNGUj],(}3NAE?prvqy JY_p(tXDm'i#8uAt_.W=gI%w s,Z/^/pg}tqmyn\$$x5~'zr r . "=1Y8O6R7TBq^n|ixfS_I&mXh00 QuN)9^| X)0HgwY)rOJC0>bCF5WpO?*&,=pty"=ME4:$oEu;f7w@GuFHEKQX9vE?,k\A# 0 LdEV&&r7t_9zJ&Y01 "?.J_rM)#:KOX2o,OG={F0:x`muF;A`c*)TVdqtP@\:"}g#Qt\.|_~mRh8K# yh||tN?Kv9R"i&h9WOG^!WB=!B<V0^/B=!VBt'-TGCi{?#&l0d-F'2,EU$Q.kKNVs~~2DLJ$v lU M|! P:Wj^a=e@?4 Gf00#q^Ya-?*m%)T"&xSRd{iSA5%Ei!d9Fl\Cf|"Ks{)EaR%'($(DI,o_KL[ot Z$Y01<Su<zM|!c: z <) $ 9U7JDGXdsE|sY:&*iAwB! %3;iRP["y=D0,DijC ,N_tsa70Rcd` fj_L3;MC%%9MH=;47Jl)3  52&5*)CNS+k:v#qo!w7}2d0W4brncYOfpC(3B?4 u$'%'GUJ~b]f|rwb3hbdw I|z~t^Ecuq9 EE.=d\dii{,?8$ ! obtX:=[t  K\K3!ni~|qfY;9g." &#(CN}CE?-COB>A[lrfbQ3xjy|qpufQJ Vap~~VIZN)"=>4*n]bBVdsnzzhOZ!n{00%'/4. {[U [o7@-.@@HG;.'+**$%%!{h  !(  uJJOFC(+>^z}9PNFOGG  /3%:C20$%    }})( ,-{wo^s !.B(C=0(*9<+(0<*<%FF 92, * 3":E<C=I9Z/X)\ES3 8&} '#173  2"0=3*;-`9VTJI"zurgWa\T:5Q~zo-J t`X&D;QHTDh,e'O!+7<.(: +-.'(&3:S-B4;?C/7"      '<KGD6R>E*PC ]6oKd/9%!yty}rto 2Q<Z!O(V2P*QZUOHRFM@"2$ #<$ wM:t>}Znlkpx]agv\vxm 0=>:X/T=S7G/@4V9`9x-]TPJIVQ\h tc6gDdbUVW5^,U1Y9]G`[bZ_HmEJ8,a]m|zsy42#&,.<SUUr<Ymxq{Un?WUY?+* !qL^tsvtsg`^Nm'853G@'A7cLeMDBAeq|rttvibXjQ9_/9 %,!!9ANWID%- ""  w"&4E::0! $8*!,1%,5FCKbdgmc\>!fB8 y||!5A^6U@OCC(PsqOMGO<p}yq<u.Zl#%&7A@8P[\/3 ?7Opq(O:GVNL9(  &  SiRYP `"TZG%):NZn { X#;-;&.GC/* '.'  "!!)#  GU{i[S}v A5tn_zrLj.|~mQE42s6*,+$@$XizQ" zIt#s.Vwwf<2FCT ";Rs`|l7]9+_wddo}F\Z?8+ GgjU TNMW?N<A(4 lc]`Ztsmbn]i(4Rrld-yQu}\F@|s}h,Z@-Gx 0'7G:fF\rjgcQbCWWIjEq[~R<<yOe[a9fop#f=^?H8JMG1p]*Z<]?r_K GHHS`SH36*/=/T9N4:F4rNbhr^ubliKlZp*VOA=8CV4-/3`-2'I:Ya`p\d]?H$-/!}9Y4b.w v{ ->MC\~u|hS7hWP:(qzU*T.eOS S #K]iW?YxiDUM{':HrW6KfF}@WR8 |ah}t[46Us%H8<9xZn^p9W#| *73OnbyYfbG[Y@|~6n=' Fe<N/EMKGq!8~/^ O'6Os P@i} /*kJ8$dlW{-)N~ypn *zrNc)bKeXp$pP'^R}@(@J7{C FPQ+/gz(xO;%wDlIxo<Ol~Vk!@+l^7 ,PP>T/`I5+U|!MzFNtU o}X\3 +[WalN< k>:$ X+= Pm7peGKD 8xp^EvVzlra - g%$$ Ix6[d^)}[6/{3XK(|I%Lk)9wlD}}3>w?[U).4.KG-_)LXXJFPm!h0J8m/<.I>n1 7]cF$0xk>Fra- @Y!Qr)|W2"kw .Fsx+jt8+frC )YcSnTd`gh2UT(It&rqrqt^22bSc#4%B\!tODZo`,q?+v>Wy fd4%Fx~uB aDKGtPuWU tL#9jH,,p([iH%YV~(k_&o"gx<d1H'&)TF <Vp-UE_dT2Q%OEc a?}h,0Qhz` #T\s [A6nZ.eG{R;]%1E^p>U7j&U)cD@!QFsJY48Q7|ZGs WUu;W@<6mC#%`Yu4+:ajr*ysxr?L?Y`M};-Jj\F`GvI'&7*W<(NZ_&N{? L<{H);e"<-r*XIqW Jw\-] EvbGn!-ab)o  .91"aM4UpOunrDe &|E%]GE##UjY`k1LZrpjDvIi6r7nf5 ilK;k 8yE c( Cu+cbR.~}jP7%qiL1#G2Y SB{Zk6#i:S]tedKpB7[TyZY%13a4IEX,xv=}%*nmM2FSVT5H=C=6e|@b*=b_n1: L$Qg_lg<'"U}or^zkoP?81i\~Oy]Wt< -i  MNy[}M_.Fti!Bp]ktft*!i2*C^*W_M  EzavFpwD;/ ' Aw2-.Cl&8@RDq!+KfrL : iii7szI,_eX8;S88mH 8W"a7Nw(oZRF,R*9,gRK2RG90?{):0#/Q*jBr\wYp Q\kWxC2^{d~KlaBx $@_=_EgLmwwf qQ7<7%N+y.`]2MgP,#}Nn$2XC1-w'y0 J'?Dk1>F!.j.s->~31 ~ct ?7lYe7KTaK#(s !`J:XC`fyW!a 7+;XUx{lrn-SJEZ-Y8 ?*E>ca"Hd4h%PtCoFP J`[d_eLHZNPQd> I,G$I-_<b;Q=%0 (yJb6.*/G]txeC&) ::1  ! !txaQ$.[wpfcqzYh=l}-fohy|[,Bi0/ d}/-IcVfhPKYU83?XzF61t?tKBU=K6VM`[I#} u?Rvgu6|k"M2D@C$&,%#*'4*569\u|# 5VB8#*<T'l k(?0=2 !%@EYk\@ /=.84 D:BkMjQcaqi^\PK; 2;F3 0CXk']P>u)~0o_N4&})XBVRAU1-"JZ>6CWLD 6vs8n=uB &.7)#WDtjxP;dON]yJD;(I0f8W%Y&\EvQizq{uj_(TbG@I]]X%G,u=G*p=  zw^[gMyw`  & 8y[;#.# A ;< ERSd?q?<j!^W]U >  :>De#L-d$n?r:lHSJMMB >< & z~ v8,B6SOiX~a2b#?)"H K"^H-$-9@BM0N/ &+8=68GM5kCDF;?W;K)A./ #913_g[-"$$"72<#&+ aO^kp q<R eL@eNa\brr}]ffXJNp<@^?S.Q6b4BI0q!Y)MT33l)]SCkh]oXvxhmfN9$" 1_q@gtzM8}ZWrqqBOt 4 (-<gfjm`_lwL{;P( ?ox, 5=2!. :\ x)e8w/}qU' *5? /B)WU'$& t4'<42fI_8<,-#*4R9L.Q5OFW;(E?G70O-i ; > %1 SWixnuT19 z&Zk+]bR\,n:hEWA=j%!9^qukg&t YeZBYeYZhz{|a;J\VblQ?-(/yo<xa5 6^W}}`w| Z k"?CV<nF8Kjs39v,$%.J(r2Es/ xodVsm) * n^QR&69,m,/|CQ:8N*Z?F YtnK5,8I#bxlpTF#58x@$&4 ~TFLC^UmNCA.mLC.E-jN[[KC %9EalHS7WE/#&}0Rlm{4W;H!Db-!$BKbR~Gr5N3$# /JD|lilVM?pmyy3cU9@Y[GX&P[j< }{T VsYbvSE! $0#LP&+8MFqdOSZ@<:RJm1Iq/ZbU$WI.wkZ4/&945Im}oXT|o;'6]Pk*[IS'!D9)$EFizl0"au 1$)+ZB67T a l0l?[AaH9Q>ZV;,<s^srcF=AJj6]>bKQQ=w a$E?%Dxe\a,Z< q 2~%Bx _3[^]&.<}5IZPIP0\<1(:[hN8-d"ME8=,k1!?J+id0V%bgqFU/[Y"Vlo ?%'|8.]0j]g'0:Dv|{fI)C1M~;u}xrZ%YAi}nkhOE^_y&{b**e>;H[4C1'W j.T!$e!6S`UM+ wH)31FTF;:N>6<YUTb^bS8+9cHN::412C6F[ClgwWVP]9-# 4&) 3mNt%:g*: Pfq8 #3/@[<ejjo p8"+%R KSxmiIy9},87~ jGH z&zWqKMK0 }-v5@cZgX.pde+^P{UN$ LfWND`iZ\8|! .Zviowq{L54%>XEthcVXW;-` PFNUTWNJ G hxu[[)r ,w3w?`(m~(*:w nZq^PV_%{"! mV c0z~hkiJB;[ZN[_wn jnM>5CTOcYdeNNPP=8@IUoqgdowm p.o1~m)7DEM#`3pPQJ|f_Z{<{iv^bXQ`pdbUOCDJU1/(=D/NU39.:C'!$"&6  '"@k-t($u'l9v\|uh9!``[SG- :0!% !/ A9>B#' "  )=9#!1 % &.)!,|jx{%JHEn@Ogzutsia^WD8J].DH7"+Sc W SD(OI/",)/ ',8EP_olDZQ67 smts~/(7F=h6d-c'C.EKSDj"2OK]sXeV>SkjgM:%#8"7">'-#% >RG# 1*GG=/I_.hS8Ywool3v ! OdH&(#&#/FRO.F7F)moQoO(R.& O,kP3>Q<*070*6#;RY> ,BF4 O-lLdLE|cdFcK|7gMeE`007769C/2L.r@6]"M05()5O<C K;t"gRfQwI#y'=*.;]Vm+Q2P``hzO61GO'c5  Lh)ynWA 5%'*? 1 elP?-:,&[|Gq0a^Qfl]Ks=]`\Q44PV A+ AV\U {\m R!E4?5oe*to' *y d[zl6MX&@fwCXMdw4<Hl t5<BOQaIk$ y /9j[S(4-{CJ=b|v/UJ[LAj 9)o3Ld \|a)]m^Q UrC`dy:mZ9w\3r2/{m:7, w<[)L'eD t z2b3G> )x)YW=M <xPV1>$_sX]C3HjU\<92g M.<6f v Q hwI?l3_-<y(BxraycS|@za3zs_rjI /<U09^4/Q@)/+Xn~`B~kZ!doZdy0jjF}fpdS 7U[ + ,po  s6duFaw"^%cAyMcgh=XssK>+8///%Y^D5V;- G5Kg DVv4&Gi\r*!{Afh>ld"db>&DV.E*g  /<& )/#?X[iTOk<+G 8)FUK:GTUnuoxg 2OD$BdqU E6,@Mje't~~qb}csShS{fk}rvrw}yqgtkP[~oqU;3NJymmh{myB: 6')' >:7; 3-!)&"4U }2s<W5`"xx\Z 2 yQ?GEGwZsZUJpm--7+) #uukolY=c9P/9BC_`bbnk #(!"0 Gma]Y?RR0% wsmiiZerw&=PR`X)  usprdm`l\f 8-& z~~" 0bf]Q( VLtm OUxxjfx  x 7b3! ?25&0< /8fiw ;AD"rakA:62>TmTsGQC4*+ !B>D>,(!(0GST P`Y_UA75Qksuv "0:<FyJxB7l([GMylLis}yaa=F:4PC6<> m L24@Sot`ceND40~:06f\_r "8Zz <<1# `H}YGMX '-'F3E?gMq9f^]?"-A(KGSw |3B.!k]P"" u`ibZen+#C<)"/8OZEN:CJ5|({]wq&]DL1=OUZks,dHplB.%*0QnUGB@fe\9* /Nx&Unounq<QaY83J";eyuSC7 )4e,Z8$28m!%B4d!iU-o~$5ZcF[ ral|rN [)]!V TJ.07!H1&&ASy #|h.|Cr9 j[ GU\rX>@7>`]YU Tq ;,yLcTn={Fs)u/44) okdbl s5i3]4^`Wtfmgxo_aTHOLOR D==UgVd rv+r#=OK)}\1 'N\UfHAHk~moKcbAI1>C,F=!,3.JYvf_tx~}qm]L  *H,;HEUw2IyHUT8&14+RE }*zH~\eAp*]Qfooi$[ mOKCCV f `PaaMdcXG;C+V0mtem|r}dgo p-b%0 3>\H-2E$a*V6X#fEAK}n-y>*fS8F_gg Q?BPB8DYyn_Zfox_.49CH*HA942 E`ffrd!_)eAz,vc]h^@;;9+KY`^Shkj1]rZJ ! 4VxihXyPu'joxW3TQYARUCJ L( LHjfsrj,>dIc.ZsqQWh){0W4`0ka|phBWX@#6+." AG5-82D)Q[zxNCJe\l]0h6Qj~2sQNMQI9 +#`"I<77 {@]#gT<>3@"M)g<d7nw-3c$n\L][4q3KL:z7K;]c]:0fx0CbV1'!/84 5<r! i N|% (ILWV)E<C+?@5%'= Q,?7)IA12( #wS3/5ww':)ANJaizd1>*+<!*'  $$'D^B();:AA,#Pr-&enoO 3/3*BNI8]97)/C^G[est  ({TRS8m[`*%G#K}4Yjg}q~wKg1HC0a,^P-7 "A3KHCFa]V\; 6f+| E81>IA~)1rtL<<\0Asc}Dnv4 $fNV<.F>xcj^k!e\X}ps#'G,76Hz?NBejq`9u(hA+vnR<+jVX!;;fhRddY^gdTVL(K#1 @&Xse"T: g-<,\rT*JZ %h?#P4Z]>TM`$:aB;(/HVs!Y^qtgN !lN|8Q;"ub++j0e 7@LJTK!'FzSq\tM~zo IK.T@+<N?& 7I@1??5#OGgq!vneHXT0*]N\.K(vdCCRky=loLxM{.yn6tghI/fN# CeM^L]Tv:Y!ZY9q|kHZUU H\Z*3Ls|!?Y<x[/+y>T3YV{EIxH;}t:c1YTEUK)W 3f_6~i%^\e=Sc*W\2y"pNBINJo\&) +Kw+ @_D'yR z;2C"#BZ8PMXlce 4Mr|r\X>L@M&C d,I$!wJ m_[V+@B( ;s]Jt<4m yu=a{+1_x4_%;Rot0A?UG~o6{J51-+rI]XQ\iJX?d(7iY{]vXw \|&WNN*#%"]yHk-gdk`!9N9 }9=V\J+6AAHjA,6DyDxJ]D .T=55s~Dy$ ?@'{mhDhzfWn!]bXxwxK4t[IJI;`>U[kIQ>`yx8^KZDW_9jK<]!O$Y{ <?2'+SUK5<r! ]"xHy *Rpn 9eOBeK 7~1^%% gm*SVF 5RtQ ."!"47vmd}"ndO!,y[rTdA\_?p-8fUU<WwVy<V3Ru[=1xOwZ#k_ V| ~;mjkbUHa?shl-+iT ?V 0U Rm,BQ"q?P (<5wB">'uHT]K9|f+D'WQnPSh+n::QY^3 ?R9eZD}Th*pP$62G_jP,+ \m||vO(/$f F CX\9iPT@2 OGRo"lBB4&@!<~GB(>:h$+U.Md-}/OdlMdfk3BE 8TvJ@h-? F+ "Ij.j 39>r5v xd9 $Wj]*-, '+fl'6$>?S}T*T)nkEpZxojjKG):EqwpD:q$y^]Q [sE`>-,16-+ `]=  9VQ#Xw=jSl!(:;G1k,)Z'r/+vGTYCsR1I;nC'@z2<  .p}#  ew9J"_h^4cMFO+eSN ]Sp7EaRi?]VJjB|c6vVKAX~vsX3+# pm{t"2N@PK{'uU5RJ=ES2{cA%&' mJ= Q4F+.C6L"u{t*A\p!{ r ?U:\wq)sIn}|sE#/A*kSv08?AV`c"Qt/CCtovua~RnV_t+}YQ";#HBFjC XF$^9D3CR4YAjW+uyR|ym|}X9&?}<^ \]1? ?(xB zA=GX88^~_X^S\2.v% .$11LjkG1[PD?b wG|gL^7G8b(L#$ a@O*LK_o]rks!U8B  6 ecPwX$UfslM>,0%8Y5O  *Ah?[jzBJ 7Kz.uR;+Sl:p;N.LG>2R+d"DL.hkXUN^eNFn2odS7,B0scz14$PKh__k8sAU1MHvOL "^saeIuEAZf[`,D !(E[s|_YSEhImir_eval-0.8.2/tests/data/separation/est07/000077500000000000000000000000001475740344600205175ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/separation/est07/0.wav000066400000000000000000000372541475740344600214100ustar00rootroot00000000000000RIFF>WAVEfmt @>data> j!3 4w,s ]ۧՄ;+:ʯȡ_xВcJޣ6>#X6H . ( bONQl?YąkBϓ̋ kTbML.SNP]O*PY <}@ܦزLvQyÔC+=KƗ˫PpW]tyMJ_e2r K@ 3q3yǧť=р֠כGlv\&ҷՍ٦ޭ 4 đ<;+O+s% L|et&4 5k#((kU%mҼڵ$ Ã̼ƀLWto/?c1)S0O 4 $q6S}lټ(%ɩco5ԝˡˆ1Ul$ ?թ4t&u)>?[yx w %&M| [`ĆȲпg̏dʳ_ԉlLn15 j ) pUwZνkƚ?ն?͗aΞdϥI7%2RAXy c9ݏ \8N n˧Leѽ`ƶʳ.إ/)IC')M ` >ո3œ ̀Нv͑̿цӒS˔KI՝? 9S[eS?:.JٌmÄ9ŹǠʐEͨҏԋelC}/ _d^6aٱH̤Ȏ5ɭI͵̃Ԑs 3#pY:>P!C]U,YpTܧIܵ 0FոՏ2LGw?u5C D^t&SHF F<\7d؛9d~فڱڄۈt'8i@/0{zh[HQw+\VS޷ޫ޶ތrދނޮ.ߪ<h1L H?eGo=9T^xeB,r;L[V&'/$'+[` Txk3RRR+]$zi'>!w/d1|M-T +0tW5,b;@#vfx__1AdNApn-}|:Z_6A i ^ˬͱPlҩpʳxްYyZ2\ p+05=&û$lֆ-+65@#ŻĮ>a܀zRB47F>i%=7ƳąP߲xSãȎɴcKlіμ7Γҳ?-ۿoNvU$KZFJ#:K؜T`WZ$6?r],X #چ"y޲ k}NweJv#礤s{הǍXˈzڬvԬ̯ѐޞScο/ !T,cP>ܭ H˄2€sfM̆Gեݺ͈ /pluji -5 f}PZ!g)nvLߐuD,ȬR {G̸DDGK6y qO˼"*5.^QV*I>ȿ]řͼ=uq2'm.ˈTT(9ڿu -9|^z1(}( 3įkΉ]݃w+r>QAPܼ֞qǓFs"d5PT!P̤ݠHs!$VׂF|mֹ֗yەޫ1҂C/.3^ҷp1 6O_Mnjv e%Gj`R\{vә׬N ݓك֦ZgU v)Qiњ}~V2G[p̫=|Ӳ E%ۉpq]yQ*݇CHm溞:Ze]|ڄ%$֜jK`d>F@n O9D< Г$ "5MإAo  Q؅׬רEcoxo|XBݖkSK+ 溢l`e7 ~˹ܗփ@*FԒԎ՛<Sъ*$ Ѳt 1GX ̊TJD} f^uʼ6ǀڀς١70"Dgٱ)UGe K̄P |$^ ? J:'SڴaY#8@ؽ8jxA"ގ[ۭWn*ui 'z@*Pshʴ .%U1k"Jނȣҵ?X/Ċ}ҀѸEHIڞ;޺9 i .?<桫m"!De:҇JɽS^pH{CJ\׭>9ږ `7;%ዮʠBEi ]žchAɘPՇL5)&=[*ԴxBAi _@-?/h2FL6  ˸ԩS<օ\e؟Bh,ȘӶ8JE'3;C& )*B92< φN źƆnu4k &xw/PfMMW&&K .&7S&֜ΟH8 }z幝^Xľן`@q@*sj08&&&32JLV6֙Mt˄wI^ǜ~0f@ܹkH(g{x s ##(-Q|^QHJ Bۃq$аѲKw՟KE[RhRn~#~Kcz F-\*  "!-"haVDЩbU,8Yߙe/{zf?|-HI#m|* Or)' {WW#.؜" %ƲҚ8g0o\TJr|n ' n!ɲɭy u - :Z~<HH i{f\xXNa"K*e]@ϺIYvN/x˅ؖ}V@ƀz|,K{ sIY_: c-} 0 %g)zLӰ'˭ΨŢfq,V-|)6ޗF6Q&v!"S}(,%  yȯF ,3р+Bv"jT>d~usW#vbu۠8ԉM&L  b ~~MJccɐ51a~ޯXϋϨ~IoJp-\u?xσ5[/ l ; iCF${aPܰm-ǹCu /a tg,ܦ4" ֵ޵#M f߾Nl ( X@Ȭ\Ġb)kF4 ]$XПtܺ%ƝN^Aف؂ޫR,- w <ryfYz2Mj3יM;/<3r!w&DGcGal7) %iEj3Jv4Eo ϻ=ȿ\ϛҥ q_Փ>[܉`h:tۂ~YBC4`@2s9`ԬAї ҟ'؛Gߪ*Co֙.x٪E RH׿׏Rߙ@i"c`L^;P0 5<]C9َ!ٹڣ Wq2ҨuiKgMKoׂ JއSwS_0/;zk,0Bpܶܜ&ـ/G`CܼGB RE Dғֱq߬ڒ{A׍ުrHn@mq7*2F:gSTN-{ܱژ84߮?uz  zz=[aߋޔߺ&3#ٷӱӍM'0v3KAIb:<$@4e/1cyo n A͢օYIV@#6uײ\|oHE VyO\6b2ܻ`p$ޙ|@c`6߻/) wt {?̝%52Җwc3ް[O#^[Ipp+A5ڿݧIٞ:%Qjgg|QN-))>T \]P^eE#џI)!2 :IR$0oܯywqbvߘQ|#7vg_ m-*)9A_mյ܌nk;e{mcFVܞ QMq܆כN5tޜl Ii%s] ΅Q`4݅yxP OdeTCbWI^-މ=_Cيؚ5ܺ߅c{YRQ+QI9N" ;O̠"6`ޟގZ֦ڪI.@.I3N@!-/ب.I dC_ b^< 6Wϱy=}!ޡBמ۔l 6gv,lZS^d]<ݤߒS%SOtV@ܳSM6%dڥ2ԡ,1aYgxgzAvS, Kݬu'kBn}3ߧgB|R:aa.l%i۾xRݸ6 4B/to@ei} Hhۂ+}ߞmޔߐ<\rsD~EI]ٌڸCz,m:VipiT\Aٷ: IV|?qBC9ж)=M1-4ߙ urܮr!z9M'hj*#X%I^۱ K)mXZisyCr"pn19ݮۥٿۈ[(7f Oh4+#5p\P߸+:O&-s*e_24 #XڔNF[g؄هܾ2OWNzr'awG-vm'߫oWJ:>9 \4ۊV_v\_߱d6Q^o9:*Cy2|!V)N lzAF#x*%3&n_rzQ2ik5QzBM;eAL.[^{m^X4$O?@>JE( PZ jVw\IUcUE4ex%TeNqO(;nolOC,f O"luMyM7{d:]+4?"_ #[f&vyD )LNT[#vOBu^/M]T %imN[yaM'rw!U.yq # q+/3(@c1tAo 4TdecncYPalSMTZK??bXTF:65;8@aFV#Dq}`A!$ ,:LBC1=2 =CXV9:858;/43 !,0*C@aql?B#   U_kgSe=)&Hlu^*qN;p@6",*~v"E=Kcjfms[wCK`O>/]GOce  #3zz@Z^M9-ޗ%ݖ;i0*߶B<1Lh@WkaOl9oӖ>ʫĹ-̹қٓYSm#K3C 2FjiY q?_)WH$b97հU5[O\o#3\ \lpp ޒۅn ?{L\,ݱK1sȂY(!:[ӌH@| O%/;Hl&ڌXwwtMݿ!΁Զ01+8- F / a7SS[C|%*:KMRRГ 1HՒ{^F:֪<֞^ۋyWP wG$d?A A54L=s)ٛC)&o_畵4L# uٖ׼PcOGÒhAbOz)8Z>ʿ]]# )'S1D͠) !A.}!nJv#d#iP /a NS:aUBRJ*t#ݍ$̎r4l |y"/N(uBh-RRfxhҏ_ݒ% Dޫ9bL fWAVEfmt @>data>):ӂ/ԕWՋխ,J4- ֔9؊˷މ5,8O]η3ÿuFǼ]bɒQ.ʅuʲRw*F׸HԻGdјdXyʰiǴ$ʢἒ˺?=\aÕèB[OZϐ͔˸ИrҺsnԵҮlڛC-%fϜ8yóîwشϩپ[rrh%7)Ai̘e;ђ z}1ֵҘ δ=ЀRhٿbO=}P/4ҜΎҲϪ%PŰNɬΑVԢן/_%evΌկyسkWF0 c@``(ZFԸUA#ŞҜwG,'G ׆$¹H~cԎىc[՚C<ĻŇ<Иϑg+S4PC˾z,(M$7ZlŚEm2޳Vt=LaۢTMѾϼPҤ-+֓}͓ȱP{fķĥFɄѪ:Bؽ^ec5tkǷۯ,п[_ՌEmZƲr̒ц٨"ήZ֮҇>QQ: ZȀͭ[*̰壀/̨hB (L{ڦڽו[ђcohǑ ֡kб1ˀf'<ȋ &UuÿMqŭԅ;k'[N`ڤbü6{eǺDuɡ͕З$ɟνѣƍŦ QԮԈ4˓3MYʤD̦{'M'Htʗx<ƻiǖd At-]Cґӳ̲61 z[ׇ϶ ŃĵB8XFʵR ɹFnT RΨ0K5ǚbDЧ“A-E9ǏΙsԵ@B=ȏ !,|wM?дojM)l]ƗǿeDz/iWO-Ҏ~ ) rȫ@^Sx5Cק͕TFʽ<`Վ]K c ʥ̮l "Aǽ^ŽŜõR^ƥȱ]\#gCc63{*Ƣ" 5jȁľ4sȭQ֟ΗkXɍ̑ʬ{*LdSdXϑќXSƖx:]̰mɐdzʶ.q.YUݼeΠPHb*M(ldοΝπ̓˭WFѓ\eѸψ{6ͧєϖ̑JcxÎƞɮ:F|*ƂnjW{Y}}!˶ ʹE<͇}Ӻ1{F! ӃukΩҪ΄i˓:xy M ;ȣɭ2mU/BܠQk.=SoKֻʖ`ҿ~ʫ[7ӝ{ԫr'xlȵ7EƢʓυcK2ƵÙ4ɐˊtv h''(̓$JD͎wuFAúhcyAɯȌ¥+^!y֓ֈJwuǣDž]o`/̳hB7!*į,ȩʼcĆp: {6˞ ɡĆBÑã r=Ǵ#'/ω9.>βB5xWC˵,dcqŻk=ăbp8EWjxIJ8ʵʣ=&\̬ ΁%2ͩjj ɑɷpcɽmZ5}8ȡȂ {ry0T ˹1͉MǖD/ȇ~OP˧ʟʖ̧AGmŬàhd\5S]2ɒs˘̉D ̀<̥ͽ̃!ʱɽm8r;OȟȠrǧLjnjǪ|ǐ$J7,W˚ Bt͙lM7>"ͤIfKˈˠDWʄ yȡƤƴ I Yǩ ǗUUǢ0-rv!˪̎C͖ͳͫP{̙t-kʆb Y6pYzȬb2ǝǓ6J.ʋʘʅʔpNɍɆ:eȤə1˚ˎP˶ʚʩʽ#˿ʚʔʱʥI %Wʩʗ1Ʌ7mɡyY*ɠPȈ{ǓgS3˙˚/ˋʊTɫ,xʭH1;HʗEnd;=ɾf.ɛɿɾɜɩɳɸɴxYeMʤʍ(0sʕʣʋʵ,ɼQ ʖp3pɤcT^ˡaPʬɋCRɉȏ&hpROȿiɺ0ʹɜw˔ʪjɽ[ J9wɂ7hej~˪ʣʨem/Vȏmxwgɜ/$I#ʫɑ)ɤr[ʼqșM,ʡyEX]5ʝ˨-&lɷ2QdɭHj_tIQuLɃ8rUpȤ\ɸ"ʈ +ɦ9ʴw<\ʎɐɦ FʸC˷2Dȩʡjʌ{.p,ʰ!h !yyWɣʩ1C$mEk˴04ckɩʜʻʿx]=*-D.*ɅɁɱɜZJȽf@OȈɃʑʤmȱȖ>ʑ˥hAq|<ʣd̎˺ʝ|ʧpʪn}Sb#ɹȰȥɊ˟pNɘ ʲʆ[4ɸɝ|ˇʱʷʶʽʨʶʹT}! !Ȕȅ,ls0ȈȰȫɜʩBz 6ɉ%ʲʡʯ_o@ʾʛʦʚʂʠWɂ ȵFxɿʶɒkʧ˧#fʙj]cʏEm˃}8 ʡ}-ɷɡJȆuȤ 8 ȏbʽ}kIɚ8ʖʰʛʗʸʿʷ3PKʱ!(cʍʳʐDʅosȝȜȗȏjTqȆ: ʋT.Sɺ 66b~ʵ/YM' *O˔Gɫɍ[ɰȯȲȧ)zɄɚɽɺ$Wʨʒʪ Lˊ˥ˢˤs˞IZoy;Pȯȯzɮ^ .ZSTyɰ$ʈʅCG:1 7g˚+ ̙%ʕʌw5ɧɞɊɅF Ȳk ǮǷZɽJʖzʇʂʌʈʔ=ˏ* ̬dEzˍLˆ8uoɉB0ɂɳɸɊav9Qpl˥Dʒ7jɄHˁc̩~Ʌ j@Hɓɨ'dȽǖ,\Ȫ_Eʠʷnj.0EeɆɧVʱʤyTY]tʻ0ˠ>T ̜ ˿ʭKe˶">F^̛̅>$Am̛̒c̽_˻r+ɠ<ɻIǵNjsJ6-,PyDZ1]ȇȸGɑɾ`ʱDrˠ>fy̷̲̒̄G˸ˠpʘʺF=ɾy tɀɬɑ_ȎnvȎȉaDV\G?!3=Oj"XɅ)Mcʓ:9),(.:-H˃˪˯ˎhJ=40*qə~[4,)Ƚȼ]ɠɺɴɬɖ|r|ɁsfK(.S|ɮ+C`ʎ0Xe_4ʿʴʭʛʃwpvtQ4-+1.1/ɡɄɅɒɵɽɳɸɪɜɍoT4%Dhɗ  +7AH>8-/P~ʩ ʢ_ɨɏɏɏuZ:$/Kmɏɔ|eS]ɁɢɻɵɟɟɞɦCxʊʌʔʨʾʳʔzuvobJ/ "'" 6cplV*ɽɂO. 2M\gcS?1 8cɜ&cʏʓʃwsʖʵʨʀdaprk[5ɮɅ:ȕa@ *OȆ-Ɇ#UaH(.\ʎʻ ʦxE"0Zʌ6Wx˂]-ʠ}b= ɢɋqD ȥȇ`AEWzɡ&) ɽɻɾ9Tmj\I90$)8:>Yxʗʷʾʶʡ|X&ɘɂpintɌɜɺ&:Oh}ʅʎʅ~{aN5 ɸɛɊp`ZX[bpɁɖɯɵɮɰɺ8O^gbfqqg[K6 ɿɧɘɝɺIʀʹʺʪTK2ɧnC .O{ɜɱ-Tsuʏʧʥʬʵʼʹʻʷʕ~g=&ɾ-4*)+0:GQa}ʎʜʜʊ}ke]J2 ɦ|S,-:P^lɏɲ+fʚ ʻʦʁa@ɾɯɞɈɄɃɆɢɻ'DgʂʔʜʍyiH5ɯɒtO/)C^tɑɯ1[~ʞʹʠʂcJ- ɦɐɎɋɋɎɟɿ  ɻɸɷɬɱɭɧɽɰɳɫəɤɽ+:KQiʏʗʟʰʦʙʜʓʁzypVG6ɺɼɰɵɾɗɂl`njzɠɡɬ-Yfʀʘʊʑʚʑʘʖʋʄs]K6+50(6/ /ɬɞɓɌɉxdpɆɠDVRN;Lfdʆʕ}ʒʕ~ʒʇaWN@84)+*/0),* ɸɷɲɓɑɎɋɠɲɹɼɥ{_WJOY`uɂɕɭɱ (BEmʙʥ # ʤʑʋJ ɮɶɧɫɌX;ȼȉjW' KMrȿ+|ɱwʯw:̖3cp͗́Cͽ̀U˧hʫHB!GɅ]v]ǭdžƍłĥĵĖuţŞƱǙ?3b˯piΙΡA.u5m=YCǣȐ [aȧ2cJˡBD^˃ʖ"j^ȶƫŝŞgũŅ_50;L̺̼?ΨJ̰ȾȂȋȯ ȏn`]NǓǛO~А>J)iôíA ƔBʞHʟ.}Hςλ̟́[˜ɪ!9y9>Moɇ \ǽƙƽƳ]ǕRFȇʓԭ!ӛ΢3ъ7_ ˖˿]%n6~ȸtŭǎ}*5:ǁM)7˟d&ARɸnʉҸк[Aε_U-yrȆ!́@5̺@śN zêļŷyrCϗhd^42]1Ŷō¦̊= MMˊAN ͽPϺήͽ̡̼\ˍ͔3ЅG/Ū3:ȥĉO^h ɪ,:ΓsxħͥQ;èÃ˞$Ā`mΨ9`wΫ.͸̘̊ͬκͶ͡Η)Ω{.5~E|śȅ[d¾x8؉"y}B¢8t6.ʌ~C;7?i-ըe+бԍտ4ʟmI%a{$z]ű 'ǠVثHN3qvռnrbGV mqP˄z6dʻfՏӽ,"!ل Sėï-Ņ1&ئY܏E.!4Nr\̕K@ɡ"͖ͨ/הvC͙͖Єo87̈́ȜìKtxq̭@эzɇƿӽͽ< Ƿ;o1Ǹ|Ϡ6xXcфԢ{ҢҸsѸѨG0ЮcˎǀAš˪Tm^-N&{NǺ麅J 6)UKʈ͗Э(E+K8 ֐կ(>ԐҮ]Ӎ'ҝk1˯ȑUiϘFȈe|jï-ȷڹ¹޹lr¯ǚʉɯ̢M+tkcfشظ  oM˳ʹ̘ȩˡ0ʺҶ̴>XŹl7uN_՘OڙڰVٹvԘ@yЁϜш'dwpDžD׽33U]yygȺ)Rhئdvڌڔڷ/aٯ_՚ҘM- rhxλ iK ƥMοg*PZJ߳/⽻Z4KЋӏp؄oۋܵJܗۂM{ؿ0_Ρzݹ۱M ̙ŁƀоlFpwذ zy?[<ʿn960-kuJ۽:݋Sֵlt֦Ҩн̧  R5qOL[軪Å>Z mWڎݎ4ۙ$֕ӺN$x?۰ܧ,٠ߕ۫X Tɬ}ŰN ɵ['v̊zKRuPjNR\lD cHƮuՐn鞙Rƴ~(okNWѶ$'~ѝ8,0 6^z;z_mŭtSEɁF r߸>{=9G9kF ìE!ߪadw츟P=ιR ݼODnXݰGxB G>F+ۗ@Iմׄ2$."ŭ5ȹ|j㬈Iɜ ˌȧzǚ$LjO.9̡@(%YՓؙ}U)߶O)Wy -Qɧ]ɍɽ/f/GH*&Z})}2ԧ)#c ΧZŢȹ˛̧Ĭ}TֈO˝s׉7 {&mir_eval-0.8.2/tests/data/separation/est08/000077500000000000000000000000001475740344600205205ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/separation/est08/0.wav000066400000000000000000000372541475740344600214110ustar00rootroot00000000000000RIFF>WAVEfmt @>data>tl_ !T(WXR Bp}=Cn[>Xk ^}_DkvDl-;_1e1SAjeߓY-DH'3H}N"|r eVHJ< be ml-  S()YywwerlD@r${dg)v.Kja{h9(&Jc///DJZ*qYb'Y ?13U_%,mbmY P5Z_9j~h.p{ BxffM+03So0_9+nHRY Y|-xy]:g;tr2 .l  KT 4:0E !g\y,8uBj Y^)2 zE۷,-=z*YvWXX ru+v>+_ |;F޾Q٦+&t)ejM߻t D%tn[4|r!6!S-^zأ֞6]I9OrW@ N&[`Ukmf "@f!3.(S9F@=YBxW'n IwmRm,߰  > G?/&UNBQdf\ Lp ;3YF(׆}ۀ)  h w]mv}iAv{ ed A9nT[ӬSPFv44ֵk!) $ J];dhKs_ jܯIRMFfgۘڣir I_fo-y ! b9~g&vݔ+pvIZs 3 HS**|Z@kekP+ p5U9|hpݝdg 77:+ /hjCy9SQ;l3k:`&U%O&U}T)"v0R,  Fq8cl155\"SL~g#dhy=M$/ f_i a?Fn x KcF9)~'IEhOJP m9rE %gR&?W|t,01p{$nl,| /zkv[ < xF^|uPx=J+Vgc:B+LvIqvo-S$qH`d `F?CL <p.i;MQE_3~oXe e79~O#0nTtmW* fhU{j5_4a" w3. $yQlLDIx ?~'0Lc@;3C+me.[lQw(vBvIJG6u[OZ&"|pFu,n{VssPItVaZz?vUY\qKCMtOf=4(Tɮ'omݳO >6u|TTR*:MeK$/ݷMl*gD/Bܧܾހޡ<-220r}?`AO_S3iؘ1Z.QfCI Sq`ݴx98UP3 X2ܣ%g_T$m]r ,:HUoۻ4=wV cTB1ݳu lRo Pه(BVp4;zTiB Iw ; IesϹs "&|Ȅ«q& [ʧ؁btG'sA@pN,\1F \i֏ܠGj ڙ֙///+M]Kը BE 3ҟ͚BT.zlf/ʌ/%;I[ORܕF י0Z+JxKiS;-+-ۂ3 _.blVS`Ҏ'=p$ߩOCH7M^ rO :.Ǘ_8C&OAi>z !d_  P7ü4?Ge!ʠ`֔q*kS$`7(ܣXˍa b0 IA7~fnb0?h Wۖ`'?x/B&~%ԯ9> }*?$)z)?V pE_R<ȡ޲!N2j&n.6?&Rz:P. ٩ҤѴڇFWWa4̷V2= ojĵW s(γe'B ذS$(>*Pk.HN!ϰwg )0**  vE JEE5(*ҙCNZ z)fg4~oN}T w靭Z>/ԗl]"ap[T%V;V'n Դ:ҚC=_Q+C{ƫ J. 46F - _f"򽶷",u(K峸ܕ6E -!$%$ܟg#j2N|N"91;̩. G2bPP/ϕ_`׬LKEc ޺޽?o~Lrރ 8<{+{WݭqΡ#*VXNB.ִg[[E w  ‰ǥcpͅ ç)4+1V!Elr9J<38i8Yݡa6 D7)ߙakn$C8Q ES!a- 0,xsԝɳ5"EI0%,/Rޑ -u:D05õݻ̟$[#_LR%V&5p J"f-2&)1Ќll1oG4?p*%ì(Sterf ]M V/`h7'%\| չS 58Y3T^(  Pv#Q F˖E+5J&0*wi%rGR." ]ۢl BOI {E XےRɉEKuY A {$5?WD ĭr;9! rȻAփFey (N B (˙܆%x>6.IB7> `Ž)~klPZY@&k sG޹Ssc9 +<480&D HǦ! #%6\^`G  ~ v_ֽ= lf  $b(CT|֫Xp44^N܏p"' yj$fiqC kX^V_jؑNjkGlyB]ڔ4h G"x >zS8l|Z^Y-7"n yd֟ҳ(;V19 64\Y /4(#toY%Ԓq \ \ hvx*> ً5 7,4#یQqCQ ߬N@I1#Az9FN)B]B&wF= h ]AP$-QJg 7SY/7+C xز`ʞ>@F %gZe ngRCj}q05D JhݻEs8p9)L6): vɺJJ?Z} Y uĴ׃X6Bq,}La*Kj$G ;q (&=0 ;H"h >Tۖט;] {(_~_=FnOq d*4log'݌,7!>rPDb_X^ v v:`u:/4Yr<ִͳg!K :޹4U.Q?]>'na75&(!lCb'j6Blv. }/1!4US[:-a 8$N0Sm|+\Qz  1q+KDAzQ"emoa`>gy_xD8.!{BhT.yrוP1E.0acNlL (MoFyin3&N0H [tgl5Dy xt2Bw%_L%~gqeGz(J}fyH[E"U#'Tyw t-+~տ'D+fx(8Fۡ:Kr zupg zl wU4*:b tl`!{,5` W1pWn+ܴwA MZw.p: ]G"#oY w{O {J @ٿݛuaS{3D{K;=kK("#WJkZ=Bf~4KJ::->>< IpjخD2F ) =ZJ  lX[~r^$Sa ~ay l|3@ h .ۀUB<!cT4|tN0e>g}+eBJ)#cw'  `jA;W" /<_=G?_: i^?wSvJ3dB7K$TT79@uJK5r$BAir$LbE1eRM -/nsbo0b)@qD}CT $RDp`!>fHxkF5E2k<%[d 1 w2HaY7{Av9cvLh+ #n?(^#@81NhK,wb<,2C_n_]YB,wVc$kJ*kzqB%YHLFo>6jH gp OR7@~1  lJ5<.6VM\TZ_l0{t?Ht A'|Cl {'l|*0'poxOKTAMj2i,nMi@Z(gk([W:AM5 y]2n.T]t ~ -9KNS>Vyyv+? wW&ZHgGPoO` G0SI:r2{o_`m~J.$k !z;P2@0k34gCw|Dk:4VSB: IkW=No*I(,B4/8b!FIv[i67M k>j<c$AQ=MKk##.HI@nX~ "0M]viD?L*Bq q=~!WYlAfM5WurF*w1vec`>BN6o\USoSi>jitNC =Mflc/E$:tW^~& [0P"3,Uo3MEm'6KfZV cKD8z)D9a31_ f=+f]M .XCjuR0/UWb|U3>|>O~KJKI PVdlG(%-*ha6KoR`h &3f5b}7tov>&#XV9G}J"j KOh0~e+4i#vTMsW;U?-xepblHbD ,tF|>rR#Gh3x%:* tP$iW$aO5Q~Aco/;^Hk5M>{Fd!2*@2(dfp{/XliX mG%"$W*:n>Ho '/+82(\kLx#zd"M4& _Ae/ uP^IlQ!K _:>*bj!m5_Jjc|q?bq1AE }ixp-Wn6aHaA(p+Fy*-q*>N< voEz^)&f?(x%.0|?5NI{2L9|$`Pn}4gl/Zv(VYc^jG&x,inB(?^bI& nԙ֓O$l4R@* VY8b_˴ߵV 3ɨ?ЩB\  b W,Q M | ]vLd/'ccض߻ZjߎO( C \5|ْ#*#yYձ>oUSvDiv;0^1M- "~#K×^5*۵הP܈..1(j:0`% w9Cp( ڂ5} 2R9fH>35ٸ mz߯VCK$*& < vЋkN[-qn^j۫G,i,C8_/ u{ֺ֤Mί! 3n'A)!Q؟?Z2/Gmir_eval-0.8.2/tests/data/separation/est08/1.wav000066400000000000000000000372541475740344600214120ustar00rootroot00000000000000RIFF>WAVEfmt @>data>{UV(S{HZA߾ԑƝ:Hcٲ@$ ؼ#2 @Oޛܟٟԗ?ՙZ+ . N $.HzʆɧCԝȌϢ}hիؐܙ؏جݪj?]ݱց _H>ݳo9(tuM̍OΞ(˃QޡKxJώ}Hx{=mtްmR"= {$TjJQ4%tb|5Ɓ҈ .V"pܪ<ͣȕ!oz?pq5ùeZnRmٞGƦ'4mۻЕΔq۶(#,ETϗ˓hێ$ P9"u^'ʀ̻F69i@݋Ϻ2ajS 5$xoۓͲ)Vƕ̙ 2ڟeNˊ҃? dAؘ̪eG'2%1hDWѫ|IbmB$zݢؽشߣˉFeHJ sh|م| @)ER~xթy<$ي>~Y;9ѵ=ަ(c9Q@/ݪt)"e-$MS ҍ&-dťKb"^*BL$0߷؝َFثP$:,n&SjdMДȜҘ8Ճe ٣lyg`%oWߴl*A0 |HjkY7\΂sOؒ:7)!d2պޮJN7 v ^yPEa)y4֪s{ *yd+S֙JDʐZ]>aӆ]rw\-GH?biX/ڪ0*#PAUǺ_rڔS/(& π̭Gϡޘi 3*۝*ETuTG }Bx٢ՒSTX ~c>ՎRC ΐ ­Ǎ;TVNf;ޜݟd(AfXq;YVMpbg@/ t#ަ7ގdЗƌLfW.$ AE ٶףji1SV(Lh*1M%nKۢߴ[جx=mܠͺksٽBMSxI7@F-wDqR{r-lڿׂb`GMZ|ު-2l(7;ۿ_:oF'٥s"J+]0h<ݳZb"z߫bI٪p`Dն$ 9?_ڀ҇L8" ftIS}3$Am@ݨcFy( ۊ؝ޞg1vߗA_ޒCUSՓvӾ˜ gݟ6Lݨ6}4=}X W #Ctҷ1# ۅTw6n}=(ښ[3د߶oӒճڀ9&-nr~YB+ MpԸjݹ?/]8S a`?J<(K{-8}L&HUޗ[յ;oUoIF:]}ܓ߭{޽phSHiܕܯxl h+x, >5D"޶ݱޠg ߫ݲ[r8n{tP A..S:1ߙ"ߘt,GRۣڕܽa' } yc> ܣmںHo%;mO5߄ߒ''cj3CB<-t܀u DQZZfz^|bzc4ްZ\|Y܊gޞm޶o ݼ0[Re9n:vw9&1l.Y1}HW )5ݡݕwߏ>c?:e3*߻ AO/O=ކv܆i߈އb\v\ޭ]*Y)[& !<@ۣ݈Ax޼D.%(ޥߨ݁0ޝ )[ޟݫ߽- hxr2= > SޘigޏI:ދtx$*W@`ݨ%?uS)XP^}@Z(G-"4ܞ܊ݦ-sR]"Sx$~,P2W޾ݘޑ޻X6'ݯ=kwkL:/ IM<":[pR>q,2YH#6N~xމA+1aX`=j'S}16ޔzr*\=FK!/`Aݶ?W~p? laSk7rgaNl2L@Kx߄޸,߲eV<7D-sv%LGx߭ߵGߗ!$AI%ߠޱkݏYYu^0{48upfݰݩ݁8BP--s1C;ݎ}H-=v7b|ްީ~ތ qߐ,߾ݷފ_ yt"N޸QE < i%*i~J(HޯTHxr _Wv*8n n k31g{UQڌRPK(=9r9TB#@fh߲fY>Ad Scg+P:ߞnuص٦.2߾9Vd /</uwޑ Tfw+߮ܭܤ ?ڑS.. 7,{9Gq%)߹ ߍ^ _iܤ%ۏ'`U<޲tNS28SB_lqެ*ݡR=aBkw߁ލZLC':cA'<]5(r rS^mIxܕF߻Ho;)߅3H*gߢ߹ߎߤ f9 &2ޥݎRwߝݹHR>\Xgv/NAvpQKޢߦ+n $"7>`޾ߩߠIw>&Ei%A@=C,7pJF00z}V1Ndގ-[IjKF I1'@ߗ54E-c ~y>Hއ߃߫K$n$lW4K.66|i1!#\0G.]u޹ߙ߁H)\37ZHnS|C?9OެaߧV"Amg+)%YhR!+xeb3ߘI0q&0Ir*OKRr!ߝjH7zUF,1~}{sK4e!t+0aVX..c߂n Q9+S@{ 7,#R7LY'L72tNcl* X'S'vz ?5i6s߯)ܫܭ.ޣ'p`}k DO6Z(ty߰g*h~w89LE-4!C#e'Xf~d #V_ XNZX.5-tEߟ Y}cuKNDpSޕG+r31_.,m߮_fhbJ8QmFx7i Ou$pݠ+ mqu߾]ކoSsWcxr#l:N[mW :*CbfkAm/}J 3\u9I04y99ݽ1ߕgS8߀p2{0t7T>60vv Ex߁nߋބD5rYߚIRf^./Wv8em@] 1N'2߽kc߮x~Hs{cv&'6e^B ?(&S$4PIGMc6Md\ZH ?s!ߑyۙ8rdQo (;xk %Jk9wg71\Vޢhާ;Z"xbݻ\b`F88PGG"=0ހ jp0fDߨCvEPGbu;2L0i>ݑݎߝ3,F}hhV3YFr\o` Xj; nu߼K\##S>߼|&F_u -^zW(9޾߄tޫߎtߦ.Rs;*QZ-SxYcCqq5߁4B1kݍoyyB-4hVG +pAX%C`߳X7qM{Vq6&B:QkyC_&gkr~%zhM[X(p JJ?Ie `f/k_QviN*cmxarTzD:Uj|E&U!#ߧpA/e[hw9fJ;lk .|9Nws?e "7YI@'muGUWN+3 'wAN$ߍ9ޢ2J߆ߛ (jt24820{Z)&sdM$q,5v)IpS49G/; `X|OqwN] `OJhߏHC*'%CDx0aRCHy=*Uh<#gqN3gJf}d5P^A?7OߧCߺߜSq^EPQXTFSUc߂ߑߺSh08T}}~Ha}l961i@b:Jv߱ gD3+ IZ\&J$\T|j|߳7ݜ$ޛ4"Z@Yd#@4$/|S߳Iz V3V[kOp!"nC2OߛߍߋU $3QOJ_CGt8Fu[ޚ9 >LVGDEXq0zgް݆ވ2!ߎR޾ޫJ\<< s~&:jߏjߩ߾RhD`R8?;<LMG vޤv$n0l$^z{ Sy8w9ny~߿Nkh\  mxSi,5KU5mq;"ߪlޣS@G G߰|3^pX 6aIzSg+Le]ODV"b w3tmuW ޤܺܫm-ܧeL\}3Pw!`Nܵۅڠ܊{w߷84BVkY|Y ߠ`J?%,ތޫލ߲G=t @ީY$u?u2JMtqGm\D< \ۇޯ,Oq={9;Bܪwܟuݵk U3<%[MC ^މ*ۓm|9nުޣ 1ߗ3"bm=I3j%Q|VoCnݟ@;ܝjޓޱf߫|bfPS/>=!do"i~fWU~ ܚیًw׉֏5@d' J1Ct8_^aa$AO|/&u:gYQڳw׽ג#֯|5EpߑP8?]Z I2`$q~?~7W>Nnm=FE@Py=A~7ݰy&ާޜha9 p۫ߢ~Z 8M6xY[.wSۥ0pTܘٹw׸dGXU@Q^߁޴e1ߦk/i.ڪ 1xfg@i2Qږ_4l]ۜ:sB3YZPjScsR)Y ߂{+|߭t޵uJKS2)|QjF-uϡ,mܫ)ڢ4cXٯ#H2ݯ@ S.6$6ܿڳ9IL[R%7ۉ9vݮ>$ߋ1VbX۔oIIҢ֘6<50Cvxw7 bKb=`޻"ƈ2d!a-+45ܸ߼Z'Vݽn UN#}WAVEfmt @>data>2;{>ߌߛo>m*Gݡv(޹*Tlbޙ7ڗ2`݉'u$ :V6E4JՖXՈ ٞZD,b)<n]VWڱK۶Jܭ߅=U"kLM[mFOܰݡbަ"{q[ܶރߦ-ߑ\duMqBݱP//Eہܻ}ݡic1 8ٴرhܗHPg4Q ܱjmءץ9_A߇ )c~ ߧ }t7܍zpـۯ(Uާ-;o;Yo>ޠܝ.@Lڋ۾ܓ\n8M ;9(݄JQ O߯~ߍޭzݢܗ Ay)(S YޤުޜR@Kx^(ݴ/ޗC2HP.ڼڅ{+,ߺ߂D4Q&*ߔ&߀߬\ޢݦۄۯhܪܗ܈;ވ'ߺ8l߫UpuۚNܝ4޳ޕfC ߎ@=ܖ޹ߦ./{05Ovݮܤ۱٦y+ I ;ߨp!Hzqp(ݍݍMބ'ߙfF;'ݕ\ގv:7v܉*ܐݭwOy8_޷;%߹kKھ9޿x*f ^T8@٤uCW܁ܒۓXf޴߈j.v^'Mܪ܂lr݆,܄߀~N;H z߱ޱ\+N܌܋އ)/flݷNt ۉ^jءفک[\Y76aY"Zߚqڜ1_<ژ|4 >yZ2iKtރ?؃רعٕ#մ6܄\ mM޷ۗو،iCALC0 g;/y<8ހpۿ܄:ۊږږt޳ݨSC݉ے-!qMp-$܍/Mܝ s}ܑ ߉߷`p݇ߨ-fݝܳۥJN.o9Q[lqqpga(`۹6w֛N-ֳ^׈ڲ܋9+*9fcڕ=nڊ۫ܖ%A@"Er=߲cߥޯޣoޛi1rه"%tݍݺA/W$5߃,G[A 2۠orڏڳcGC؋׃ٳ*RBޢݓf܁ܮZyif`:$aܨ܎-MY}|޲ DJ UWfܣ9Oיp ڎ4d{b}5^V2.b߾F%C۰eڝڴٳכbh:S|lM= {ݟۀնoYIybهڳqj[ ?)s߰-&،֖MGR%ߤb3I,qRb߈ޕ܈ۘ޸߈ ߹Jxߕߙޯg_ޓ1Wl]ݖRcڙs1Iߪ޸x,s߼ޭ;ܢ])4ۅGKr|lߡgUjHؿtڇےHiٶפUL,9c @3ܼ9؟e}۶Aݍނߢw;uf5GrHۭ^ٽ@۠eq? ށ! ߭߭ߝߑV߮j߯ߜG#ݖW߄aܼHx߰ ݫLڟ9%ܞ FzCOވ׌^ݍQ!܅`HV2?ބY.[KP Z۳۟ی؅ގ:P_Mhقًؖܵܛ`OdڔVގ:F* VRٮٱu޶,ޤ([ܯ]!j^3oޖ{xH\*ڑMll'ޢ#y[;26@!U-3uߎ݌>3ۡ5ߪ~Uޖ"ޝݨݠ.\ޞܮ^׻׫(ܲA޹rBu[߅Uۅۡ޸95L2'Ot`T*`ڏ,.Jݛ1ޑd7 =?VV#܂"pnݡ߉nڶ;ڂwؼ 2ܾ'?H'@܊>vׇ jnۡf߂%L ZLۊcߚ߄Vhaݶhޣܷޝ};A0^.IU7yϥ"хV߳8,n*.ݐc8(EփٌXLy٘:@p@Tُfq1[cV־EF[jX.m{6a ٢%J<-ڍX؃tE|V&KS*"-xyЗѵM8ANr0bg?؄Vڼ=0w&1JۣԜЏDhԚ5a5MTͮΟ)q ܩܸ6ro ~ֵSB- ̐ϤH:6P3-IwZ1FҊaPu6&fWj;g۬؊4`nvگ+Ӭt_5ҪbۃP s%eoXmԢ+wչܛ9ܼ-Dhl͗!3޲ܩ@#xEazݸ o݁}Cמ]n^ېqҥѸ:HN7 ܻ՚r^.B!Zք76!.fۑT-oZJAbL~`59mٮXفׅ֮% `9=!_|Kk`!@9##dբѧrRKv8 4v XC BՄC͸ϺPIթ9Y̗G,*Y/Eەd;bұygv؂ٗ3wajtfy42= pY׃vUAϜ|PJ gthG:ݐЗ,,bԐ8{7@IM) {MVUϧdՔ)BԆb޶ +}A"q KhxԈ̎7Z%Co*xؓڊ(p +}>͎ǖϜև(~ژC? nE&F[;F o˭ʶ̌ͻ`߸R[J+cbԣFq,ӐU՚ԪYa@_װ VAѹa"wْوOY@B#miٙАzX~׽B̒>c؍\3z<\@f љќP֧ة]ۊ k>ۼ غۘy!/ɥd&M:/^.5SoҢўЯC\׈> *loJ{Kܸ֔tۥ_M˞(Kk=c(p0ֺxϒq+?'R{U/-_׹T/@a4Vbaܭ]}pk4̀xznՔF$`̧L~(`Qӝ0ӀMܳܚMK֥ЬΫ ٖmP߮hh-~4aYЀ1 iٍP]އ դօID.;b֕-lqyX;̔,};ӯүp{_xշY"Y!#L >۪Zu>Or^Y;Y|ԦՏI׭ 8ٗJOHڅw\qۡڵ٤|=^^8cbV7b5٧ڏE~Xwn֠sߏ@"eە&"yݽ/*d1ߞY7lf٪؆Uظ~߭ E~ ޢi?yp$ݗ%qܦo7Di!9֡8@ۖܭfտmdzctܑ- ڦئjߊUEڷާK>\t20O܋ެz(3ۣߪZلދmGߚަذ )F=D߭6RQתֽGBeT-&>ڤrۀ8'؈رz. ic,JIdTKl| ܪQܶܿް )&0.'X֨kܥGs]{L؞ZDٱڴݎ3(b=gYZܺKۊ*׺MԴ΋UU]]S,|Gh:܄7߾ٮ9 ؞u!ߊxK2 G6;sД)ʌiن۫PؔݱG݋;@Jyڈ0E׃-p!.G/DHL4IӳM DRLLq [[l7.I-;lקDؔ՘ׁJwޙ@!g &* OAԋT(=3:߭Tر0ٷӦ֏էZp >QP[{ھۯަZ++K;I;jrؙAםxۖ|ؙܭ}l@*Hp1<؃ еЩҥ ޽J,beE߭+/ۍS֪ӨG!]׻K -3D.FԭvΪӝϘӓ Ե+/Ye*ޒդՇ`M׋Գ٤0IBP&1ڛػըѠv$(?؂w"h]u:3/ߴQٝF^Fۗކ%I4tۏ|փԛ`Wӭ!Үa ٦qRL!I"\4J ܦׅaчО]Ͽц؊ߦ -l>b ԷOpѯϏd"zޤJ>15G_RV۱ےG].3pi Zݩ],U$2~҆q0i,y&S"ކާeYuJnׂn&.[\HTPٔ'7sЄ Iќ׶dk;Fߤ!G؟QN-ݮ޾*4d:ԓڜ؅a1d̙́<يvٞ_^p)LאзeʯNǽП82^lkrSMhrv]ѩ̡b4ι`֮Z70o.٘XۦۖY!R,d֊Ӛda' :Ȏ_ ѓ׍LYhP@֜hJ;ɹ|H_0E{q@%nNߣ~B!OЎ\2!JI/j݀(מ%ҽJ֋/IyQ%!;HL3l&lfŢ}áRβ F3[ڲԒ̀z ӕؿ)?:bDhڵ֌Su?b֍B٬բRk[DЁb ׵ 5j.OhKϩXnČȭһLidgѨj{T߇s;P+TjS ִ׏jiF, T&gݿׂ0̱)+åMD&ګ6uRw+dKICԉvѩ_ƿ&=4Ţ@Сcבs:dUOA IkLF,l9n4XE P>yG]nc9ƘUGEƈ4L_GlOWPe^LʳLY|?E iNmEߤܣ[gJR.t;=G/rҖUS=JJԭۍmVd]T. Ukׇ]=ƽJ3ƜƄȻӽ`EW7#8 1..K~|ѽzҼԑyAb3[נ(i֐,7'ٿvN3H=?W-o۝vy7I:~[ގN7hSW40lAwե$7D-ґ'ܦNf?U7PTߥޮ۝\8=ۻڥۍټgsѧ{+JyavP!{ /(=(fT7FP}&ޕޛه 3֒d`*-jߧޤV* ݧߍtdw #ߴߎu<>݆JعFю/&ѳ9ҤԤ֤6ݦߘ\u!|Mxstp&wAcׅi߱i{Mt~ވݬܭ6-IݮZڹٝپYMT6ܭܸݻ9@9dcTЃ1Ԯ,x^F ZGZb%gcݲܸIذV׵Քbgb%'T(YSY1eBHߵڐ5oG֛ `gy[Mݛߍ rkGC<ߵ{ܤ}טd:Ӛ5PLݿ:UWL$g'-/rpwO݇ ێ؋եD(>wځݓz._\u:۩ّ0TI;uX5֠0ڗ1#W1# a1z`<`يי$րN`>,8Isv.6)s; ݟޔNAܲd=۶C%ٖلڿ۫۵߃ , ih=).ڧٕsy>֢\ڟUM߼mgk/h% m1Tl/֭չr՞Okw؈oޭj;*v'U *Nޯ'ޝNݢ۹۔3UIۨۘ7ޝe )yAr)8ߒޢ8"672ޕ:.ܽ%ؚQO}Bه~ݠt|yS][bSY68ޟޠޙZݔ5`ޔޮnނhyT ݋ޚ߿\JFߞ}jݭ- QYܔJܛ܉bެwzz/U٨JOֳ6D+,ޓp*+h&C<E fڭ8Dgېgٱ*Dr_[qMgl܁cLBqhjؚ0Ї&Ժوprޤaqvvlpe˭}ǵZɶAW ޢ=2ccށys л ח +oF$[*˪ʉCFʳ=ҡ׻Vo=RmMNӍйb֔ސE\@$wڿղ͓.Ӑd۞S^:|޶׬֯7i ![v`LH>ڵڂ(c΀ ]ٍش#0b"IUbTJ٪ܑ݈w؜3yO0יؚcjަ(xCߗdّ۳pՉ#܇QxWq@pm (OCwؒڰB5igy߈U?c=܏{Pװ׭C, :~0cj{Ko1כ>ԥACрR܌ o4AIbeiܞYܯq̺ȓɀΩ}ڭ*NRvݙIS\D\_~zր'tӫT*9uܼa=`CRݵ]h՛Ӱ݇c9kQr+%8ފ ی! 9j:ދ0Bhܩ۝\Ճ .0ܯ۰)W1Z(!0WAVEfmt @>data>vvvwvvvvvvvvvvwvvvvvvvvvvvvvvvvvvvvvvvvvvvvvwvvvvvvvwvvvvvvvvvvvvwvvvvvvvvvwvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvwvvvvvvvvvvvwuxtxzjUuv;TJ{X?oh 2*L*w~yf {h4n\(Fp_S-PJ5fcXxdG!( mX|kWH+rygJ.pY:GWPFt Kn4T":[64ZGl!v) j9H&'T@hLpy]| 9 i 3X.WoRjT*wy*K?;@P }# R~lwsM|V41hEBM0=u# $O6a|Bc+V!?G5P/6w>]fAKL"Oh)R34H`LDY!!Ai|K7)xwB!q(R{7ifaD`4Lpdi&YN()xM#=F*DP]Ebqr&*Rl1sKF,\@zyxY2/m WFi5?;0.`VU)`;F0l+zEUdBa2i47O?E4-6 s2a0#V Noq{*0noZ;uH]jjl&LEtC%q"Idw  % q1z e(E o~3-%tV"Y#K?Zb0Z}*o !HNb ;h:JKGI8f;5a +;vs=m_zUKޜvxSr$;2t/_me |q DD&w%~ga~~c]x"iEQEOaC\rm/!=3Cp,pG $Zq=P5fA_:^I+)` Q 2Gk#}{RdWO"9~Pqnuy!L A/ n ]  -(i(V87LexD)yGF 0?&~~~+4y):Tv8d}Cg: 2m%L?5]~"q](XJt Og@Nvo gh[qW}!(TYiQ#ZB$:f%LO{L`6bDcc7W:+@ Ln; [ <<`3.rOPl K,qs/eKBCFT'.!xp.B \ *Q m0<6m$W\NX)L 0z<-G:sy[~l<CyxNp1tEKb1CR17}`_n7,ud)32+1FGs]r+*H.P:wT&\ @/O}EuEA$gS<\_)KB6_22:y.Rkm)7d'l>Z\KFx% {n+^{_ c: I{s VEMGh7 NrSj 9YrwCdN ^K~mL}Yh;e^& qML %P }s@p[6Y${d E""/ C+V"%g}L.9)a?\ܒm~d3QXHh9fV)Ko$)' FF/h "qQBa<5@l t!rԁ"ޛc&=bW8w5*v !(K}^ eߤ\U=yYpI!ۈ+h1LKU- 7 )s٦mMY//6RGpcɒl ߆4zڭMjg./[aful ֍(29BPfS,Jde F ݡs R`,Cˀ$Uu- y׋754a_ 5U~4kL-8UЦڶ e`O#,͸] rWn!N NJ֩% Y[R%ߝdH 8i絼ʿ<[cX 9`It>8d(:\,s[T \ |͘Ys@y:ӂVfsEJZMFZK gϯ*L(JTͽuS<)kAkUaq aKݮߜ:f+7fNN Uo<7 F 9 }wީ OaAdw?SLp7UߛJ5m\\4QY`fn je޼?;*y QYn Jl\+ke3u/~8*C U(HKk- r.aR\8("Qܱ'E/eM}bE}dL? ~ NRt1ؔ1 /![A2da [82W !- ;B ISU404d5_!V7|@c޵9Hv5 #.=E+ߡuB(MltTڤj׫%&cИ?I j%] ՇZeރ >]6؇) E_E6n`{xKXL-D3at˽JLK qf1; fnr %\yY81QDo$˾} <Q8:*`Q'?M)y2@"ze(b'#A~KB5!z`XD :)'"50 40 mz&C i߱X1p*,dt3cy ܘڑr6} <3GfJpMjXy([ /aOyV[W{ p <Cn^=XF'GjyLo80e$W -_=Cq\3jM.3~xj+6B=,vik54L>kCOU{#'t9ey{ p 1(` ,-9>_JI?piZy#z|BHUsiA8V;ph%%i9S,*-Mx"clK;Ef?e3G'*. QB44]El+{D6{$~{lS5k132T&I=h*I674tl0>`lTA\@;6Al)OEB@ A'9q\Tq\> wq+U`'Wi<;s|4O,^%U)3lBf|7Z q$2DOE!PDc5fK EpSYOJTl0Uha tYA!]]68={IOla)sW18rJgIGlqBp-EROh4f$,9,js?8[Cn7?3bQr5tz`+qaY Y>GKG1ygk`Jzy\T{&oQfF*c -_Y>0zXqL#Tvc&QY0-'s' tk-"U'|J!M$5wbZ\8*CoF~QK 4( a2w" ] B>օ5 ٝA 2Y/?<) ʮ=v̕]GJ'I)ZXOH'ew]I}̳ͫəΖ&7 @F;)Qm~"I˼Io<U!6DLK8;T3zҶl=r_"(ɹϝ ,X= LiDt00\H?Ėʃa8:OOF8 EsYγX෗‰/SgfWW5q~]Q"$έԬ =9Y*`N/ QɄ&͓ װ*NG^E_=B#`´΢#NQܰ2PkXF)*}R;d">ܐh&;rIW@Qc(7Q OpN%o121(`vg(E6x# zn.0X1-AщڧMQH A-BG,?$'3yZDٜیߴP')l2 M5tB׵D VUJȺE!$,r4#0@mFT5@sHnՌ?n+C..N% ̆/HODٲ2["QٌoJ"J.G) O*;ر>Cͱ;Wt&N'-__z'.lZaΤʥ!=e!-+2QX~-d5_ufdU-O4,: N|cw1T`p; .2-c,Y? S|ܹ% o702#6Kv4$6K)w,-].#cZ}wGݕ=Ȧ&0o-:0g S x{y-ˡ v5:2G"4d :Ĕ׍1݌ԃrdҼT4Q6;j+޵^W 3=>;)\3ķVڈ)۟G`i  ?A::6i1n_(ɾԲNݗ+.ѬAمn a04?G9>'Aٜݧߍϊk.,U*sEnG(=:,9 Nռ|ΖUՈکևU'CG9gIQ6/L2c̉'b2vܘ#s?.@94n0 ƻ$ι֠k۞ـG )-A222(k׊̶$~eԫ77cW'+8&/q{u>ÄԤާn4 @-$.%\%TDyѹِ߹uy = ~:!D7̥iuˣ9O ZV)0'O.6$¼lEP| LLڦm(<(M##Zic٩f T!̎}Նc,Q%3ȩӄT2] zF%֦:"tjծĂ`(Sc JZ\ ")" سɾAaE"IV5Ԗԇ %']NrN6ޘq ʠ*QnaF 5 J Ȳv]y aCz΄:wpV g\< h95}r72 %L b W1Iܤlq\s5.hLqdY D{ٔpae~ W<&\L&_2-K7ȣV,g  ~J܂>֦vO2 .`΅HltE!f e҉3+EԢy <$"~!9 #q͌ʁB)ܽf*G<<5"i7W@0|^{t̪? yvhS0"$]#\]_J }'9dq ݼg  !6-0ڨ%6lИUNp )d  J t(S4V>װanԋkJ- E X'.ޥ'=* QDBSD  Dկ,F; J B1@-W= {c@%}P+ ,#;\%SIzu4z0VF hLuk&2 l xU'<*LrD(v_x^ ieyA)J2!  ,hb}u7c9(9lXT"!DvUo4JVJ2N^]nv%#'mM@@!=I?FP`ZB|I51BK5IcQNVFSd| _ Ol5/A =+=I3G3f\=(x>R(Fe uF~:uun_ -:{0MOn)ja +m;j;d`Rb4t9f3 y ݌1M0~DEY]YUu,u;{$7 bJ%`Td.@s3Q'R?o1?fL^ fK4U.:w)1p'p!Gxl{Dq/2A_/) w10TQO; U{tP&HJ,tI{L@(Vdpt$4F'%RCvwte277^C=gl;h1VjkFY. wX!`n~q! j$F}v<\EeAura[t=mCa_g?;dFM0Ck,>!rE3 0^lBM>MM @2 ;~/O+Z1_Q V&zO`QC$GO4#[1_''7/: ,Qyz#v!f(" 3p#l%@)~'"Zoaav;vs%mir_eval-0.8.2/tests/data/separation/output01.json000066400000000000000000000077141475740344600221620ustar00rootroot00000000000000{"Sources":{"Source to Distortion": [1.6357250261616694, 8.35730768374355], "Source to Interference": [2.869614536623785, 19.596668518613885], "Source to Artifact": [9.511469033244348, 8.744100747692844], "Source permutation": [0, 1]}, "Framewise": { "Source to Distortion": [ [ 5.149669474914772, 3.1488100796540404, 1.6539826780575286, 2.8748397843157396, 2.6745263013094145, 2.5542948621892525, 0.41438689453916433 ], [ 8.140962974194387, 9.168101838553662, 9.20529893957309, 8.556308362721357, 18.666441030639284, 16.815137099504994, 10.585218780016422 ] ], "Source to Interference": [ [ 7.904800707297028, 4.0570038445068395, 2.22137218148402, 3.61373944766269, 3.149070649891711, 3.1501808657513037, 1.8032413005929873 ], [ 15.402937023765805, 13.875470944863594, 16.175846921346125, 14.675806974690932, 22.988234803441774, 20.54239992419536, 15.217408852352577 ] ], "Source to Artifact": [ [ 9.08313970096718, 11.83030341933345, 12.813737665972784, 12.499974926704931, 14.239859841858657, 13.189827403144259, 8.243205007241274 ], [ 9.167978020038662, 11.135668579824056, 10.282717737529854, 9.918738648986986, 20.69256955203501, 19.24839646750305, 12.546051958209466 ] ], "Source permutation": [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ], "win": 2000, "hop": 1000 }, "Images": { "Source to Distortion": [ -3.728734240907568, -0.4318201250413093 ], "Image to Spatial": [ -3.101322996790156, -0.28353454509577714 ], "Source to Interference": [ 2.8696145365946797, 19.596668515448087 ], "Source to Artifact": [ 9.511469033350544, 8.744100747708758 ], "Source permutation": [ 0, 1 ], "nchan": 2, "gain": 0.0, "reverse": false }, "Images Framewise": { "Source to Distortion": [ [ -3.610134649333453, -3.8689468446156905 ], [ -1.025984860608304, -0.3227907605130132 ] ], "Image to Spatial": [ [ -3.122461076386494, -3.20865288224359 ], [ -0.9437277119526215, -0.23800696552017314 ] ], "Source to Interference": [ [ 3.9650508040494343, 2.5015023988684137 ], [ 19.22571259353907, 20.412950345526504 ] ], "Source to Artifact": [ [ 10.543876939080949, 12.175832774712031 ], [ 11.046588452497266, 11.060465308797735 ] ], "Source permutation": [ [ 0.0, 0.0 ], [ 1.0, 1.0 ] ], "win": 3500, "hop": 3000, "nchan": 2, "gain": 0.0, "reverse": false } } mir_eval-0.8.2/tests/data/separation/output02.json000066400000000000000000000225671475740344600221660ustar00rootroot00000000000000{"Sources":{"Source to Distortion": [10.402442396290404, 11.615179897174547, 8.213820164496585], "Source to Interference": [13.688266627376017, 15.194137115835119, 10.084397177627933], "Source to Artifact": [13.335559184910213, 14.252119758894345, 13.179999062945116], "Source permutation": [2, 0, 1]}, "Framewise": { "Source to Distortion": [ [ -3.3683586251724176, -0.4258131004730029, 5.737954384287263, 13.496549686251882, 11.133937944745513, 11.744969792989144, 8.783665593807779, 0.10586742903207497, -3.392353303563334 ], [ 4.114269729136045, 3.6731744276418876, 4.706638787684438, 4.608061014987869, 2.501270404894758, 3.7095657831177444, 1.3676712483128473, 2.956226287243273, 5.2440986381143295 ], [ 16.978354236989194, 17.741897091793426, 14.577608333324958, 12.739000711173317, 2.2621375012667193, 1.6333311475483014, 1.2550203261532684, 1.6631735614600018, -1.1497584991656096 ] ], "Source to Interference": [ [ -3.361311383159377, -0.41805884675415195, 5.750722251019655, 13.873877733477302, 11.422785774638367, 11.873782070113656, 9.384159481188938, 0.14357942689956213, -3.3915520815178564 ], [ 4.161081265635496, 3.6783663733941028, 4.713902939683422, 4.6264150711234775, 2.5491113448998397, 3.8484107075454532, 1.4468443722471211, 2.981135208402449, 5.28057243985441 ], [ 17.03250354285748, 17.84514324717382, 14.647512686549733, 12.895973966261625, 2.298647095986888, 1.689623136425914, 1.3021291134452864, 1.7020151192991826, -1.1403297080800905 ] ], "Source to Artifact": [ [ 29.54115930781021, 30.284864375869876, 32.085430463346434, 24.4689397612799, 23.350922624102438, 27.360805465204532, 18.14687428019694, 23.676861051371574, 38.977423833872535 ], [ 25.22211095634335, 34.44975192272571, 33.740050065681054, 29.643799086772052, 24.025161181124336, 20.230457095212245, 21.146116053327013, 27.153624667590456, 27.147893385072148 ], [ 36.1324813954066, 34.10327241414194, 32.691764718319675, 27.454243214145258, 25.045465569457566, 22.781967782806024, 23.333232859196787, 24.409599008507577, 29.106022947569375 ] ], "Source permutation": [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ], [ 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0 ] ], "win": 1200, "hop": 800 }, "Images": { "Source to Distortion": [ -1.8775463755729618, -3.3887395937444476, 0.9747284594596128 ], "Image to Spatial": [ -0.8589065941545819, -2.7043695498276343, 2.8930111354532895 ], "Source to Interference": [ 13.688266928269748, 15.194137341965568, 10.084397086748702 ], "Source to Artifact": [ 13.335559171890424, 14.252119748135586, 13.179999070154329 ], "Source permutation": [ 2, 0, 1 ], "nchan": 2, "gain": 3.0, "reverse": true }, "Images Framewise": { "Source to Distortion": [ [ -11.614228844618804, -5.008678822252923, 3.2383992767890897, 5.453958144668951, 2.1004345511608293, 1.578438283107806, 1.7170021719232518, -6.724556591393716, -2.7989921444160815 ], [ -2.6772513397327313, -7.70614904807331, -12.643073365588425, -13.857563303999301, -14.794561242422972, -14.419593058031563, -14.243452366815628, -3.4840667763821425, -6.687913508461344 ], [ 2.053185842579845, 1.9854522015713219, 1.9249036337181638, 1.686324789474099, -4.208020949310968, -6.239651644568832, -5.800603582950306, -4.155670065507797, -6.998789124033747 ] ], "Image to Spatial": [ [ -6.342642426729091, -1.3779534168628726, 5.0702131939383275, 5.831309013846431, 2.245863798407403, 1.6601523401957372, 1.9142589759698259, -3.9870380440341373, 0.037586973762036194 ], [ -1.349377784842438, -5.953438120047759, -10.972563351438128, -12.102748321014795, -12.227860344070313, -12.372687676758218, -11.091952373738739, -1.5355525512440464, -5.441900648087925 ], [ 2.302722293773217, 2.200164843986763, 2.3854236136064895, 2.3883773862073503, -0.5838165671281382, -2.782932641429039, -2.0511812620158207, -0.4175484764395975, -1.2608875491737064 ] ], "Source to Interference": [ [ -3.3613113999856163, -0.41805884815136635, 5.750722250758927, 13.873877719484689, 11.42278577755504, 11.873782067658286, 9.384158517962705, 0.1435793526388831, -3.391552081359699 ], [ 4.161081261514829, 3.6783663705120957, 4.713902939692706, 4.626415069648544, 2.549111345491055, 3.8484107053594805, 1.4468443970717002, 2.9811351444485936, 5.280572440663402 ], [ 17.032502610132568, 17.84514318855103, 14.647512685778041, 12.89597395611403, 2.2986470964724908, 1.689623135153164, 1.3021290607635574, 1.7020151053995032, -1.1403297080475863 ] ], "Source to Artifact": [ [ 29.541159284469806, 30.284864376603664, 32.08543046340018, 24.46893976177227, 23.35092262389296, 27.360805465361423, 18.146874195853638, 23.676860735173122, 38.97742383230484 ], [ 25.22211095028493, 34.44975192338721, 33.74005006567967, 29.643799086977968, 24.02516118091551, 20.230457095840976, 21.146115340325892, 27.153624219688183, 27.147893384824293 ], [ 36.132481064536144, 34.103272414992134, 32.69176471834025, 27.454243214386686, 25.04546556931182, 22.78196778318227, 23.33323120636724, 24.409598992734267, 29.106022947464627 ] ], "Source permutation": [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ], [ 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0 ] ], "win": 1200, "hop": 800, "nchan": 2, "gain": 3.0, "reverse": true } } mir_eval-0.8.2/tests/data/separation/output03.json000066400000000000000000000240041475740344600221530ustar00rootroot00000000000000{"Sources":{"Source to Distortion": [7.227899883748847, -4.463066010999018, 1.2821108384488062, 12.080451610955636], "Source to Interference": [9.099154153186786, -0.6395992455508694, 4.933804919293891, 18.322102002191336], "Source to Artifact": [12.29049343816683, 1.2044404039163803, 4.942972769893187, 13.322032058619765], "Source permutation": [0, 1, 2, 3]}, "Framewise": { "Source to Distortion": [ [ 6.334331918339612, 5.669633027022265, 9.514464186545139, 10.71164392578315, 9.297428445800008, 8.771713568590616, 10.403935522673704 ], [ -8.513135611073594, -8.064798819888791, -8.251509304933107, -7.850194258047162, -12.458178865642155, -4.6179776078665995, -2.644615618710851 ], [ 3.9540843403165615, -3.0720269164432774, -12.10520682558961, 11.990534899929347, 4.810319300991273, -0.47816637025080955, -5.219895828058016 ], [ 12.060237250059458, 13.935491387386808, 12.426917555156134, 13.636511936766013, 15.425723921844167, 14.704418986550998, 14.483143404404505 ] ], "Source to Interference": [ [ 6.517511430418773, 5.811584235204686, 9.584118567039901, 12.0535044371654, 9.757649467411412, 8.950021021537328, 10.46565243486915 ], [ -7.063426513233857, -6.919588115314706, -7.0510675813016475, -6.414204157657953, -11.905715000061399, -4.197909156233509, -2.4813855006475842 ], [ 4.141014910687602, -3.0662821416570836, -10.876089318848761, 13.1396178007717, 5.717548749645411, 0.2376957317518501, -4.954793379034611 ], [ 12.922416671673943, 14.906538658441146, 13.278126105039757, 14.832517357389065, 15.848218198376067, 15.42135925531434, 15.706812594153735 ] ], "Source to Artifact": [ [ 21.048836346016834, 21.608583262197634, 27.951027125793622, 16.72864879954062, 19.710211838041786, 23.24729692355166, 29.2821572605892 ], [ 4.79964549937246, 6.007384762964339, 5.752039211870982, 4.961749710617883, 8.947021685277118, 11.332878323275246, 16.112437890835338 ], [ 19.123969289544746, 30.52457226127728, 5.194061850315177, 18.53256678532119, 13.088137800677963, 10.597476679719989, 13.214694804585587 ], [ 19.72218257905594, 21.055515792722215, 20.12256294009786, 19.96175152988701, 25.866418972581066, 23.003854645101143, 20.69699250545369 ] ], "Source permutation": [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ], [ 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0 ], [ 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0 ] ], "win": 2000, "hop": 1000 }, "Images": { "Source to Distortion": [ 5.712753094141592, -0.5289757449175277, 2.549532481747531, 7.304802908427809 ], "Image to Spatial": [ 8.318816498816233, 0.29976988809635446, 4.804595475041144, 9.81187117187988 ], "Source to Interference": [ 9.099154152762832, -0.639599245138507, 4.933804919281571, 18.322102007674253 ], "Source to Artifact": [ 12.290493438213053, 1.2044404037004555, 4.942972769894986, 13.322032058536436 ], "Source permutation": [ 0, 1, 2, 3 ], "nchan": 1, "gain": 0.5, "reverse": false }, "Images Framewise": { "Source to Distortion": [ [ 4.19954929801372, 3.96782825444149, 4.361892868515408, 6.5073212368026825, 6.955560133790401, 5.984627571776252, 7.929196739408663 ], [ -1.4095944954010409e-05, -2.8326066278908866e-06, 1.1949171397866073e-05, 9.838309428075156e-06, -0.043281902154532, -1.409758632530891, -1.4422546911181748 ], [ 3.117618233726835, -0.28622284622982813, -0.015140774063767213, 5.574189592449486, 3.7010547007907855, 1.167937056847659, 0.4592080989842254 ], [ 7.354561939979786, 8.361046167970864, 6.775511410749754, 6.889497911805611, 6.804044580985504, 6.417840147181597, 8.290624270950048 ] ], "Image to Spatial": [ [ 6.112430375659283, 5.316079069648002, 5.027546972941165, 7.561106359147739, 9.767718417885034, 9.05195120319567, 10.595479265345196 ], [ -1.4080045367696296e-05, -2.817805683465462e-06, 1.1963908148885579e-05, 9.85242188014322e-06, -0.0413096055991435, 1.04551585205587, 0.6549993870997048 ], [ 5.452577519367842, 0.5197310016117918, 0.0038051781058960924, 5.86891871912888, 5.528354657099386, 3.496684925008192, 0.6693780756670293 ], [ 9.918609420131812, 10.363424299608557, 8.899797095616515, 8.279821888574899, 7.633159453549365, 7.435927366549889, 10.021556206256408 ] ], "Source to Interference": [ [ 6.517511430418773, 5.811584235204686, 9.584118567039901, 12.0535044371654, 9.757649467411412, 8.950021021537328, 10.46565243486915 ], [ -7.063426513233857, -6.919588115314706, -7.0510675813016475, -6.414204157657953, -11.905715000061399, -4.197909156233509, -2.4813855006475842 ], [ 4.141014910687602, -3.0662821416570836, -10.876089318848761, 13.1396178007717, 5.717548749645411, 0.2376957317518501, -4.954793379034611 ], [ 12.922416671673943, 14.906538658441146, 13.278126105039757, 14.832517357389065, 15.848218198376067, 15.42135925531434, 15.706812594153735 ] ], "Source to Artifact": [ [ 21.048836346016834, 21.608583262197634, 27.951027125793622, 16.72864879954062, 19.710211838041786, 23.24729692355166, 29.2821572605892 ], [ 4.79964549937246, 6.007384762964339, 5.752039211870982, 4.961749710617883, 8.947021685277118, 11.332878323275246, 16.112437890835338 ], [ 19.123969289544746, 30.52457226127728, 5.194061850315177, 18.53256678532119, 13.088137800677963, 10.597476679719989, 13.214694804585587 ], [ 19.72218257905594, 21.055515792722215, 20.12256294009786, 19.96175152988701, 25.866418972581066, 23.003854645101143, 20.69699250545369 ] ], "Source permutation": [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ], [ 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0 ], [ 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0 ] ], "win": 2000, "hop": 1000, "nchan": 1, "gain": 0.5, "reverse": false } } mir_eval-0.8.2/tests/data/separation/output05.json000066400000000000000000000164031475740344600221610ustar00rootroot00000000000000{"Sources":{"Source to Distortion": [15.989628144732425, 2.92585277037319, 10.390551440343547], "Source to Interference": [19.310156466664875, 5.042019427791443, 13.118530603652601], "Source to Artifact": [18.76100033748606, 8.24665350507413, 13.909608717243112], "Source permutation": [0, 1, 2]}, "Framewise": { "Source to Distortion": [ [ 11.440536675067579, 17.328375913229216, 19.246247909082772, 19.15107868850007, 23.354771324431663, 23.2109174572615, 18.48919767884879 ], [ 3.200499507597892, 2.4697810981951642, -3.834624099549914, 7.9313336264114165, 11.17292272933065, -2.3006149433583194, 3.30279924326439 ], [ 13.12435813742717, 12.993318101201163, 5.859129776687109, 3.147786090782722, -8.938596094423708, 14.239433380167759, 13.548815748136056 ] ], "Source to Interference": [ [ 12.765247980489129, 17.486351217195573, 20.940410354949456, 20.026300194268384, 23.96794059785485, 25.230972473267187, 19.4020464311528 ], [ 3.75929678707931, 2.5558209152386198, -3.2068474186796414, 8.55800311839287, 11.583077988395162, -0.8357643907276845, 4.022718590112774 ], [ 13.999773465737002, 13.100223365279911, 6.902335250633238, 3.6665574675697377, -8.731410599686226, 16.160022781780587, 14.258939589164363 ] ], "Source to Artifact": [ [ 17.466580806940193, 31.875865139417332, 24.188953472076662, 26.580960148056274, 32.17717152062089, 27.519079324974953, 25.761041518334498 ], [ 13.907516503437991, 21.46132816292758, 9.778502652957963, 17.2150438419717, 21.916364560727757, 6.579408542410596, 12.911739918453357 ], [ 20.679969040167208, 29.342166172612735, 13.370936872608572, 14.185660075488357, 13.656085168710208, 18.811784798091374, 21.9234509312971 ] ], "Source permutation": [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ], [ 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0 ] ], "win": 1600, "hop": 1000 }, "Images": { "Source to Distortion": [ 2.163258282027192, 0.897843090973953, 1.2282412977280202 ], "Image to Spatial": [ 2.675154373977956, 8.372130218893792, 2.8493541624550485 ], "Source to Interference": [ 19.310016796340754, 5.042011979810868, 13.118530796703595 ], "Source to Artifact": [ 18.761000317979864, 8.246653519942392, 13.90960877164283 ], "Source permutation": [ 0, 1, 2 ], "nchan": 3, "gain": 2.0, "reverse": false }, "Images Framewise": { "Source to Distortion": [ [ 1.4640689573054708, 2.7226855497949582, 2.01993537403283, 2.0707454220204204, 1.7654217138662174, 2.2757164947868103 ], [ 0.5862203071772628, -2.555224133136584, 0.8281683915332907, 3.9038945737714243, -8.166310458073198, 0.8747108716969225 ], [ 1.863929146719244, 0.4142955685304883, -0.16934518084163938, -11.026720818380532, 2.337017329764834, 1.2285975158734879 ] ], "Image to Spatial": [ [ 2.6743459740517226, 3.042138197061535, 2.171851184655353, 2.21990367646539, 1.846909125722322, 2.5667921667091735 ], [ 6.986314555664403, 1.1937990357095065, 5.924077706272566, 6.798483342879064, -3.204161142391748, 5.557574882687534 ], [ 2.786320464519493, 1.269399072157903, 2.104572025397564, -8.40225081501467, 3.7447725133852394, 2.015366273884354 ] ], "Source to Interference": [ [ 12.765247987217723, 18.548198326401238, 21.56942205365922, 21.727536058601494, 25.074504242651123, 19.402046376019406 ], [ 3.7592969952118938, 2.9643294210871796, 3.4521164707672103, 8.89989960878802, -0.013368601758496676, 4.022718272413978 ], [ 13.999773826767068, 12.840068959398272, 7.855283150243267, 2.0128880192086265, 13.254450179478315, 14.258939821646521 ] ], "Source to Artifact": [ [ 17.466581324467473, 30.64449260447506, 31.818219899436677, 31.403889961649718, 29.742506431757878, 25.76104133124133 ], [ 13.90751663604565, 19.286311163564886, 18.04982577022389, 21.32488824647362, 8.415006032654246, 12.91174006255146 ], [ 20.67996907702124, 26.253639802519878, 20.39833802217094, 14.985002236348938, 16.75512467904216, 21.9234510210249 ] ], "Source permutation": [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ], [ 2.0, 2.0, 2.0, 2.0, 2.0, 2.0 ] ], "win": 1600, "hop": 1200, "nchan": 3, "gain": 2.0, "reverse": false } } mir_eval-0.8.2/tests/data/separation/output06.json000066400000000000000000000316551475740344600221700ustar00rootroot00000000000000{"Sources":{"Source to Distortion": [13.78338204929278, 7.250163706520247], "Source to Interference": [16.204235407537556, 11.658569116183275], "Source to Artifact": [17.578736233831776, 9.491272183553724], "Source permutation": [0, 1]}, "Framewise": { "Source to Distortion": [ [ 15.770861118084023, 10.266491728120815, 10.616425286260341, 10.402612463899505, 11.341693557777493, 17.977919644661608, 20.899809133103066, 20.684958728768006, 19.81641283106371, 15.157352480870586, 10.918400740940763, 12.794284048570162, 16.35341492981471, 19.142915379163863, 20.356182145650912, 19.68432366646042, 21.236160511571388, 21.498314308873177, 21.411517037797086, 15.689348142010811, 14.973688010752495 ], [ 10.234148337188175, 13.494352305226032, 13.261602906653147, 10.270234658668533, 8.926526735416843, 0.7285082470816284, -1.445026004087403, -0.3491037224516751, -3.5361158771361154, -4.871801382705655, 7.024768329666901, 9.435832460228072, 10.397105843295142, 1.8924601837813337, -5.498679269679663, -5.707465929170647, -3.016408381580664, 0.9723598073007549, -8.41491576524177, 9.75331347871246, 11.817349843774206 ] ], "Source to Interference": [ [ 16.983165650601777, 11.066620858416801, 11.119816633976619, 11.248434408988468, 12.128696219803377, 19.13596762600305, 22.814960093766867, 22.86219678218422, 24.300128659029884, 23.182897730381974, 13.635867354293921, 13.74969822569331, 17.406888721891345, 20.68435836131071, 23.949389057429066, 23.57485883876062, 25.266629368983104, 22.704300333535944, 28.52307118467533, 17.130537763017905, 16.54037884417558 ], [ 12.761302701100185, 16.725423398871758, 15.505315585789596, 12.82284038108909, 11.569695660595814, 3.5198548561320138, 0.3365083764479299, 1.1806141185060266, -0.9230897029461725, -2.5762143138651847, 9.106024425218664, 11.226290236310998, 12.707662470216736, 3.5750031043137893, -4.155211115828419, -3.156892835441405, 0.8942659663030604, 2.39831853815833, -5.992697570650662, 12.918316411158452, 15.40943603382166 ] ], "Source to Artifact": [ [ 21.99077800512083, 18.333746530033405, 20.547726687968467, 18.23786659984539, 19.405526331340425, 24.337330971503963, 25.400719693560223, 24.749387110512938, 21.74464595790909, 15.92278043653074, 14.426776962742522, 20.018559739001624, 23.099310341295208, 24.426373457428518, 22.870091804407828, 21.982106951716652, 23.433829394223462, 27.675020583617965, 22.35677824908201, 21.2639494831869, 20.25679399600904 ], [ 14.012229445929318, 16.385904318487157, 17.32399989862944, 14.013214533201253, 12.630371248910073, 5.567003858183554, 6.130538618398581, 7.385045791985439, 3.4078156073272456, 3.4811516488943166, 11.721747364516004, 14.464250937066641, 14.468754307872985, 8.405501929920156, 5.818303254181928, 2.6865395454609016, 1.8346519846706522, 8.477254710078228, 2.2431515909826487, 12.83054983253958, 14.437888709785698 ] ], "Source permutation": [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ], "win": 1400, "hop": 700 }, "Images": { "Source to Distortion": [ 4.064384201051032, 3.038140191822751 ], "Image to Spatial": [ 4.2879761035049695, 3.5250443403090737 ], "Source to Interference": [ 16.204235407534707, 11.658569116182962 ], "Source to Artifact": [ 17.57873623383274, 9.491272183553775 ], "Source permutation": [ 0, 1 ], "nchan": 2, "gain": 0.15, "reverse": true }, "Images Framewise": { "Source to Distortion": [ [ 4.117419268849969, 3.404760584148478, 3.580617666901382, 3.5797608104702894, 3.659998659710374, 4.207105486629724, 4.270863765260916, 4.220394181272049, 4.216632880349893, 3.9285482622458283, 3.5546202403109177, 3.9486055105584943, 4.111378352283996, 4.235035943571582, 4.221309951381499, 4.257700615094955, 4.3013969596916715, 4.285296208666528, 4.307183770801567, 4.139987661546405, 4.115106885313501 ], [ 3.1905908448064144, 3.247026431796786, 3.194355189052204, 3.0654520919430723, 2.61420098085057, 0.2087777138236804, -2.3484300223219923, -2.9419470404441945, -6.020107795326631, -6.03024714724787, 3.115826293743474, 3.2023857090762124, 2.9876542216812414, -1.8264261719831683, -2.926105777573023, -1.63949835880122, -3.7989003862454163, -11.768189421606994, -18.02829560081907, 3.1414599127022482, 3.518099641928803 ] ], "Image to Spatial": [ [ 4.265946270456123, 3.862008474995351, 4.006347275011335, 4.012938245485315, 4.001145757814493, 4.2954232993153205, 4.315513654297631, 4.266107502288021, 4.272049981361309, 4.056150986107566, 3.8994045526807386, 4.231496668590401, 4.239916766404593, 4.302680762837564, 4.27309780314319, 4.318665094317284, 4.343992335550145, 4.324702081070074, 4.34969534547889, 4.293376619628399, 4.288744140001434 ], [ 3.4332164140630663, 3.3665447951896637, 3.3129303686199356, 3.2638752736746355, 2.8421960702384803, 0.894774218732992, -0.013513052652211146, -0.7698875505954419, -2.232912338699759, 2.378386225593676, 3.7150052170924344, 3.524371675011229, 3.23366107884534, 0.12244334429659523, 0.7237286409011028, 1.1697520139872948, -0.917728106038417, -9.371059914549628, -9.114054598374521, 3.4224066196840885, 3.730955345937695 ] ], "Source to Interference": [ [ 16.983165650601663, 11.066620858417622, 11.119816633976146, 11.248434408986954, 12.128696219802212, 19.135967626002905, 22.814960093762927, 22.86219678220032, 24.300128659031138, 23.182897730381807, 13.63586735429285, 13.749698225717568, 17.4068887219101, 20.684358361309823, 23.949389057406552, 23.5748588387573, 25.266629369058286, 22.70430033353293, 28.523071184674997, 17.13053776301665, 16.540378844175308 ], [ 12.761302701095055, 16.72542339885745, 15.505315585790246, 12.822840381088369, 11.569695660590076, 3.5198548561316216, 0.3365083764475069, 1.1806141185066974, -0.9230897029461338, -2.5762143138653473, 9.106024425218695, 11.226290236193112, 12.707662470218244, 3.575003104313886, -4.155211115829531, -3.156892835440776, 0.8942659662898784, 2.3983185381577683, -5.992697570650948, 12.91831641115734, 15.40943603382102 ] ], "Source to Artifact": [ [ 21.990778005120966, 18.33374653003158, 20.54772668796959, 18.23786659984509, 19.405526331340955, 24.337330971503857, 25.400719693560475, 24.749387110513187, 21.744645957909057, 15.922780436530795, 14.426776962742519, 20.018559739003905, 23.099310341297887, 24.426373457428475, 22.870091804408545, 21.982106951716602, 23.43382939422338, 27.67502058361842, 22.35677824908202, 21.26394948318737, 20.25679399600897 ], [ 14.012229445929735, 16.385904318490848, 17.323999898629516, 14.013214533201236, 12.63037124891111, 5.567003858183495, 6.13053861839874, 7.385045791985267, 3.407815607327187, 3.4811516488944223, 11.721747364516418, 14.464250937057635, 14.46875430787298, 8.405501929920085, 5.818303254182101, 2.686539545460951, 1.8346519846706086, 8.477254710078375, 2.2431515909828548, 12.830549832539608, 14.43788870978543 ] ], "Source permutation": [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ], "win": 1400, "hop": 700, "nchan": 2, "gain": 0.15, "reverse": true } } mir_eval-0.8.2/tests/data/separation/output07.json000066400000000000000000000160311475740344600221600ustar00rootroot00000000000000{"Sources":{"Source to Distortion": [31.65426748072045, 30.509880888730656], "Source to Interference": [41.534168992046155, 37.73978731132595], "Source to Artifact": [32.12569904260708, 31.421680139098243], "Source permutation": [0, 1]}, "Framewise": { "Source to Distortion": [ [ 34.80070239467067, 26.233964206351303, 35.52152001095222, 37.491913036007325, 34.44692576864385, 30.644871381679888, 29.53300714715028, 34.512840543932896, 33.31009727280657, 34.36391651078961 ], [ 26.130863585770637, 30.05752044658083, 36.18594879129595, 34.537511946262526, 35.130012109898374, 34.565317116657496, 34.63959606031987, 39.223908390181435, 31.063860723680932, 29.51190339241336 ] ], "Source to Interference": [ [ 37.056235077666095, 29.04314269432124, 38.35924656300556, 39.94487087965189, 39.60727483981047, 36.322356323417075, 32.809992822610944, 37.373695325278916, 34.47844491232085, 37.066900409631224 ], [ 27.845610482037387, 34.54337418412345, 38.54337124412963, 35.20532609957952, 37.13331392820961, 38.31297112963255, 37.57026768557177, 41.02765296670008, 32.00348725573812, 33.393514333858064 ] ], "Source to Artifact": [ [ 38.725975834383235, 29.46056377159172, 38.71216923960858, 41.142198992353336, 36.026084877124205, 32.015943551221454, 32.29432790970611, 37.678707082629735, 39.584853266235726, 37.70579937932512 ], [ 31.003032704566586, 31.969991606105687, 39.96554793807786, 42.99973779383219, 39.454447341682354, 36.946110823960595, 37.73177148964179, 43.91104655903011, 38.176234225694444, 31.798816376280424 ] ], "Source permutation": [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ], "win": 1000, "hop": 750 }, "Images": { "Source to Distortion": [ 1.7583517906290023, 1.700757929346703 ], "Image to Spatial": [ 1.759796121885355, 1.703287840079689 ], "Source to Interference": [ 41.534168989923394, 37.73978780133325 ], "Source to Artifact": [ 32.125699044478075, 31.421680111910717 ], "Source permutation": [ 0, 1 ], "nchan": 3, "gain": 0.0, "reverse": false }, "Images Framewise": { "Source to Distortion": [ [ 1.7557212625185228, 1.7547138785946859, 1.7596843790872958, 1.759055848870768, 1.75875122726139, 1.7574519775193291, 1.7568176293537074, 1.7586480165943554, 1.7592363101234085, 1.7592638145539201 ], [ 1.6924649211005733, 1.7016692668632922, 1.7043722099280738, 1.7036499830252747, 1.7041040471838227, 1.7039242185501602, 1.7041741414448572, 1.7043970483380702, 1.702430129381245, 1.701751212753497 ] ], "Image to Spatial": [ [ 1.7564115904843982, 1.7597473682073619, 1.7602869182174874, 1.7594335093388682, 1.7595170180900648, 1.7592760076460983, 1.759173760912185, 1.7593912607029725, 1.7602184244029835, 1.7600362671204637 ], [ 1.699285156121919, 1.7045012461538642, 1.7050670369289587, 1.704666147436396, 1.7049902335583038, 1.704933563419315, 1.7051655313634067, 1.7047425405294456, 1.7046661546430155, 1.7048499625703208 ] ], "Source to Interference": [ [ 37.056235077774694, 29.043142694487507, 38.359246563037466, 39.94487087969612, 39.60727483971729, 36.32235632350306, 32.80999282286602, 37.37369532659421, 34.47844490855107, 37.066900409446795 ], [ 27.845610482247693, 34.54337418051188, 38.54337124491327, 35.20532609961636, 37.13331395958441, 38.312971130155766, 37.57026768559318, 41.02765296778991, 32.00348725880361, 33.39351433530094 ] ], "Source to Artifact": [ [ 38.72597583438812, 29.46056377170782, 38.71216923958582, 41.14219899235472, 36.02608487624218, 32.01594355122171, 32.29432790970482, 37.67870708376333, 39.58485326321377, 37.705799379313504 ], [ 31.003032704528973, 31.969991606882164, 39.965547938040004, 42.99973779384051, 39.45444733874109, 36.94611082395758, 37.73177148963505, 43.91104655926426, 38.17623422559254, 31.798816376335633 ] ], "Source permutation": [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ], "win": 1000, "hop": 750, "nchan": 3, "gain": 0.0, "reverse": false } } mir_eval-0.8.2/tests/data/separation/output08.json000066400000000000000000000224611475740344600221650ustar00rootroot00000000000000{"Sources":{"Source to Distortion": [12.658621714161605, 19.353779851187323, 16.490559932201563], "Source to Interference": [16.647925846010466, 24.298418678982788, 19.534653901953313], "Source to Artifact": [14.963487364475371, 21.04662056008085, 19.51540110868908], "Source permutation": [0, 1, 2]}, "Framewise": { "Source to Distortion": [ [ 16.192865169727398, 13.028356898467596, 14.893095079349159, 13.206184448743779, 11.278322194600843, 11.149686478954122, 13.481957165397043, 10.418114868053863, 13.680843762014243 ], [ 19.16928643751411, 22.33260979627913, 20.88501614523839, 23.17546022589123, 23.569714393137026, 25.417457455374443, 22.707319453703875, 19.755994742864043, 16.47491192002275 ], [ 20.149927282268454, 20.267695322224103, 18.496572664869277, 16.18703221162405, 19.024302145824258, 14.190596411379516, 16.88279138847638, 19.921302938784912, 21.2584705532771 ] ], "Source to Interference": [ [ 16.288295958752727, 13.118430955873595, 14.930286338199622, 13.264972384336719, 11.365058006587974, 11.200327720655764, 13.56547042390435, 10.467023286202862, 13.865385487811974 ], [ 19.51303533008609, 22.42708511693099, 21.00741091217366, 23.30046863949658, 23.734218387200183, 25.514157962740356, 22.775316455057478, 19.874311587607504, 16.583023468025996 ], [ 20.31754190446126, 20.345014205362993, 18.562319621923248, 16.269550631841422, 19.241210680291484, 14.207980885183762, 16.920950511451522, 19.97320737927088, 21.36217552372802 ] ], "Source to Artifact": [ [ 32.92235489483052, 30.111966640647857, 35.72247463881086, 32.12060555291033, 28.623592109542486, 30.825308450625837, 30.870941019057348, 30.30003790763802, 27.664459179077237 ], [ 30.403770694506083, 39.02918697290886, 36.480585812213675, 38.66653008995361, 37.88613537966818, 42.00145811413804, 40.81708087956089, 35.50687209189353, 32.66233068093355 ], [ 34.40837037041166, 37.84121399852104, 36.788544740106815, 33.54189410422633, 32.19879673409346, 38.33727533707226, 37.55107654103121, 39.216506650434496, 37.56168867998662 ] ], "Source permutation": [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ], [ 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0 ] ], "win": 1100, "hop": 850 }, "Images": { "Source to Distortion": [ 5.564462357516159, 13.543786828358558, 14.790182930065344 ], "Image to Spatial": [ 5.944542395012337, 15.364637810803266, 19.388466227656373 ], "Source to Interference": [ 16.647925479510807, 24.298418874234812, 19.53465377105395 ], "Source to Artifact": [ 14.963487374060156, 21.046620558943488, 19.515401109517914 ], "Source permutation": [ 0, 1, 2 ], "nchan": 4, "gain": 1.0, "reverse": false }, "Images Framewise": { "Source to Distortion": [ [ 5.294990460101518, 4.687705558241064, 7.15239687398372, 7.056277354255535, 4.836621026089924, 4.606203323283599, 4.476283581464221, 4.4513527353179505, 5.505522083738992 ], [ 13.375814667564757, 13.234386523239749, 13.962318060375573, 14.47242477721307, 14.680861756879459, 14.944545542008466, 14.546485099539886, 12.898782981988798, 11.774378159344677 ], [ 19.453436963657346, 18.773763229989346, 15.7382856333261, 11.788681629922612, 11.315202779808523, 13.41549683555196, 15.396491568239512, 18.668470174410317, 17.65413081367002 ] ], "Image to Spatial": [ [ 5.399685549299138, 4.816675552115289, 7.641548903848636, 7.855560444625053, 5.314916078156076, 4.863921460742268, 4.585930784612097, 4.6535108992860845, 5.78072840942011 ], [ 15.028813235733114, 13.968520558761492, 15.350564189566917, 15.346538452591087, 15.514240646162706, 15.507050971670694, 15.553893947514421, 14.286480610504693, 14.269466348586892 ], [ 27.897930807565523, 24.26770806636389, 18.894550278738468, 13.600079956657346, 12.013564755866623, 21.007029393784368, 20.871187088270126, 24.378951406104598, 20.072858575521476 ] ], "Source to Interference": [ [ 16.288298722144038, 13.11843104098601, 14.93028616587486, 13.2649721932521, 11.365054983910273, 11.200328214591442, 13.565470544044487, 10.467023396120922, 13.865383757870347 ], [ 19.513039699388695, 22.42707966527728, 21.007411139412852, 23.300468118797344, 23.734193134223283, 25.514168159637173, 22.77531645692427, 19.87431171391975, 16.583023375565034 ], [ 20.317548379871347, 20.345012200602774, 18.56231909329937, 16.2695504711067, 19.241209935568143, 14.207980823648864, 16.920950527564614, 19.973207276296236, 21.362175129090893 ] ], "Source to Artifact": [ [ 32.922354537610794, 30.11196661488308, 35.72247463305713, 32.12060552923858, 28.623592081799295, 30.825308079137642, 30.870941012978133, 30.30003772490787, 27.664459350203707 ], [ 30.40377049649575, 39.02918663674912, 36.48058577529872, 38.66653003496973, 37.886134635059214, 42.00145670488575, 40.81708087807754, 35.50687207789059, 32.66233065310512 ], [ 34.408370059844664, 37.84121390962211, 36.78854469136054, 33.541894094549335, 32.19879667507221, 38.33727532234484, 37.551076539971504, 39.21650683048246, 37.56168803523778 ] ], "Source permutation": [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ], [ 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0 ] ], "win": 1100, "hop": 850, "nchan": 4, "gain": 1.0, "reverse": false } } mir_eval-0.8.2/tests/data/separation/output09.json000066400000000000000000000075431475740344600221720ustar00rootroot00000000000000{"Sources":{"Source to Distortion": [6.533836035573265], "Source to Interference": [Infinity], "Source to Artifact": [6.533836035573265], "Source permutation": [0]}, "Framewise": { "Source to Distortion": [ [ 12.119934389970112, 9.839136413593899, 10.104607545126424, 14.83174440067323, 10.402492739711457, 9.962792788321892, 7.591397020480595, 6.953836345225294, 19.31013868039556, 14.789903496557441, 11.069772397512526, 10.153206550236124, 9.717806202451953, 7.908023275472441, 8.189812854799017, 18.577301858851083 ] ], "Source to Interference": [ [ Infinity, Infinity, Infinity, Infinity, Infinity, Infinity, Infinity, Infinity, Infinity, Infinity, Infinity, Infinity, Infinity, Infinity, Infinity, Infinity ] ], "Source to Artifact": [ [ 12.119934389970112, 9.839136413593899, 10.104607545126424, 14.83174440067323, 10.402492739711457, 9.962792788321892, 7.591397020480595, 6.953836345225294, 19.31013868039556, 14.789903496557441, 11.069772397512526, 10.153206550236124, 9.717806202451953, 7.908023275472441, 8.189812854799017, 18.577301858851083 ] ], "Source permutation": [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ], "win": 500, "hop": 500 }, "Images": { "Source to Distortion": [ -5.124915966181872 ], "Image to Spatial": [ -4.220713809183423 ], "Source to Interference": [ Infinity ], "Source to Artifact": [ 6.533836035573084 ], "Source permutation": [ 0 ], "nchan": 2, "gain": 2.2, "reverse": false }, "Images Framewise": { "Source to Distortion": [ [ -2.051176730267349, -5.146884744328681, -6.734284215137559, -3.6310338903056136, -4.122510730027927, -4.167078355532121 ] ], "Image to Spatial": [ [ -0.27238760025916553, -4.020905870109551, -6.301402520259074, -2.852803081793685, -3.718817899898826, -3.225307329367855 ] ], "Source to Interference": [ [ Infinity, Infinity, Infinity, Infinity, Infinity, Infinity ] ], "Source to Artifact": [ [ 8.08886938787347, 5.948179995182407, 8.011113169865057, 8.942785959170472, 11.216100461431367, 7.379612746411304 ] ], "Source permutation": [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ], "win": 1500, "hop": 1200, "nchan": 2, "gain": 2.2, "reverse": false } } mir_eval-0.8.2/tests/data/separation/ref01/000077500000000000000000000000001475740344600204725ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/separation/ref01/0.wav000077500000000000000000000372541475740344600213660ustar00rootroot00000000000000RIFF>WAVEfmt @>data> O h|f+Pr -&cYn_(0j   dCBg@9fp{W k8S&@U)\  t $Z! f9KQ%)%acC ol=E  A  Ir:,, r;", /MvDN Z<=W`B40O`| 2<j $ `m.e$+{ Xy}@8dl]  tk k}_Q-=?4UrF^@,8o}KPA[t 9 G?gLgprG 3 =f4M]jCr%Z~T99-B:_xܝpvUd="-MXM:%& 4yؓ+ӛo*ե|BI+1m9BQF?@2+ Kn~TڌؠV}e:2T  c 1H a!EzP[LzQl4Pr&A02/,&fx \ $! t X *Ƚ׼\ɗЁ>'iV c5Dx"^%')3,)g_lcywu$*(#!p DD*XTSf,۽vP#a e >#@$c#"`NdV}di۞S>od= !]""O'&&~sjv,TdJGHl٘~F!1$V"^0:d}8c(x  l^&o@ W B \o2$  z t ;d&Zs t\[ :o։/P[>^1  I2%)[031c+%LJgqd}ޢGۃ55 "CSKmbrN= J  f 0y .pc hA|}y(#_0Kp ^Ll( GU +9[*~Gc J  R {rk]Z  |j G\-q?y[Ks^z k m#Bjy\')e+&ArhoOMAoF' W#~\%y 5 ~ 8Oakڂ!j;|z{_f Y]7 N ^ RD t0,އ`p?? z 31 {b N%SKz]( cX '#&*)<&! Rf.G5|  qx y,"IkN8{ , v;-X $a  \[-Xw@ X#(5+?(*!Tt<  x"a]l:9V/|Ls f  BEesw޸;!YZ/"v!_ K p; 2 _WfG4**Tx} G-f vB\CU !fFy:a 1 Z_ E !kGH`/$-K<pO.>D 3 Q gAB D  buq|fWw80_fAg" ^b !N A b j[ 7R9> (?Ey3MgR Ao.3f zE*..(_Fq t @h)DRpWu}Ch | "d#? r 13@-F_& f N m;PG I6g/_ nKYiSf*7:C li |R ]UdM,`  ]D?b- 3 z*SMWdF&AtxvNTQJ ( dbiOc.s>3.Y ]q P K= ?  >H@DCC4/Sp sr |!9[^D  A5Y6GGRJ7  V Yj  s  Z'7HK>Z4UsmEtMp[ iYWHieN /K5$IiWy%cH MN8Q. z _L8S$ t}&* =F~ #2r9UZCt6 a 99L r 6|d 3&> O ??+ZdA] i# O /#O  2`"ad}bQ"J9 >]cHL C >r:==g ' 2 s u9I` A/_o_ ]zdfz0izZ @* YP|Q[3z_ TgAvt5j  a"a`^[f Qq  L___in;%|06 S U q__aN # 7  j zN@Y6n`quD]!  C +WP  '4PJ )_;:iG$uB-FB!_ D x J J:XI vz=JdA H 8 ~W&Wxn89b4^>Co*dxopFh17; T tm 4IVC/Igq3!]; aKa:u?YH+5C=W[0=rGm- 0 xddb44;9HFI*}:V4kl ^:U{A h}}g0a5GI_INX#2w7F^C  ]Y@Dto+ h  aj|\YY6i}q K z B O l w g-Sa +w17w e w x #/hFv*xLBTtFYrPy m g L oa*Hh+,:tJ+^j  *.  X wy@Ib".8 aU1Ym / U 9.f xc?=6E ]i' /5*T6bKMvW2-tlQz W = L d ZOb?-BWJ TZ [ T ` M % \P'4Ix}S# { #!D+g>3d(- > : d  -  ]?}J~O/E o g L 6 y:\0z) <<;ZA#1 Zs} r( TDH(K_Ui/ S KCh _c1i*G;YfXC   B OoL qz>W4DZ]97d *+ i VnQ J"a t#pV) &/ 7 UBRUpsRD4 L(#  _ 3X4|-&~lc/, 5 Y@ p 0s6ss8 ]^  0SL+4"#emM %M{ ^6L(vl+c nQ'k [6R2j97 YGsp  svTWcWys1(! dx \ i !{iUd@[`- Y 6(1i q NG-$Vz(Z7K 5 ' >-|^SDG(3nq n.W;r v5 =i cV~GOA:lD'>U L* /  SFs /2Qu\y C |v)Q e!Q /b Gbb)z} \X6 +U=pBMsC k5d6  ^!"E/OU'T > , O g H<c 2dvh'U A ] j?_!d+ p,  D  ^*j  2.h  C MaJMF/TI}\cBX] |  g 2P^3S_{o, yA E  B : _SZS7lWI_a Z P  u)mrV/e6~D O  ^  l H  j C H%LMCL [I6 RD F6  h>2q7A! 6elR 8 , # Hj {{SgCK &VR?[>x`C{ 6@|Iu?q"ko9 C63P5 3 P RI.~ 94 8 iQT +;eZ  8e}-?2.~ 1&s@\ѩb9%q >h{d%--.+'\ 7x2EJ1Z5ٓ8A{BdiY b$'$ *g S  GnH#E  19&.= b[s  ,G.PN<;w B| yGOAN (V7{Ue j Q( :; :VF.\h3M'hmXyO R! nic{ Ju/4eKt`  bK_q { ;V u+b?O:{CH QoD GRjaHZh2 / =r41  d  Hw{O-u[Cc7fk\ A -  6x(+% k*-R   uq2Z 3k?HP2KUgj  j[@@5 )dT& {e3K0n\  X"[K%#F[2t!Xn!Thg!]TCG  3 J 6UmWqqFLDwa5u;   b  )0T(p:joQ?j-ZH M +V y)v(wwq*"O0-(~~Gd``/YC}_{ ._ /X#8-< ^dvPk 0_"FNyQ 5  o2@6L<1k@O|wA-Ku}"~9GP7R[ut x@r%_ZKM:)Ze0 Y i6"jwB~ wP+LK.X+[WYu-)1Tf04zd-Gxl86rM:;oqtOJ7z o  O6w;:Sm">&Z($4kJ26 QizP|qO89KqV}rPy /  "_p~8CwEm6&2D4+ljwU@Wv<&f|.xUeWa0j}E"ZW~7D0[t M#[f5_*-F7x =lZ h6P%3.lY_a4b=`$]0vNbg863}(k@AUmU@#&Uny="0M#-gfu 'X$) rtX>Ng >nDTTZ1N82-OA if$E&B4[F~bo#3yn\|3Ko[|RlKu0Nl4N?6CJvg^kiH`F hu;RH_Lx8')\B95 _WCmK+?4Lvqq^0:DJ CPqUW[|__Z>?=Le_ %mir_eval-0.8.2/tests/data/separation/ref01/1.wav000077500000000000000000000372541475740344600213670ustar00rootroot00000000000000RIFF>WAVEfmt @>data>$BwMzD#Z ^ eFU4# KH%v T& ׈(IQTk8Ŏa .(}61%pv{,,J2^"I-;k ]p2Eخq,c_ ,7MY* "  "D,DUޤ%5'{"1qV-;۱T>+_ˬ2‰(2BLP ,HL^1a-8ia\Z(@EX`!͢ƾG*ة( P0\mӔ 1=M?Y3[eXr4|J5LuGl4Z,t1 yIT5E Сv~'B;nS5:Ih?OG٢3:"x |LCgӽ/E(ynGa/®u.=kP_ϴ.bk&t=(L%[ +`Lt6,ٰ)u Ȯ.5'Նa0gLְWb^)(C?N[I4^Oπ@#i6@'g HA}09gow]=9U2Y73ex%t0f^37Mxل*9J)W-@W(/9xA <:>%vYᕷ-ED&<ՙTs+ಹA!,|Iv#K (CæԱ(B&ev{!D)DP5>=%E1 5A{Ξ 9*4ݛ3dϕp:-?e; kF!vˎ 9r2ڣgURZ-w>1; +&Y}$=d1\6d/׷'pfs:8CL  .v.4nA gbن5 uwA7z\#+[\ Ř\L+- g? C 俇ǢA17 +HS([ɬ԰&8m!m>߳!SG(diG;!fj}+ Ǫ! 3&?!jBOqDD%M޻Rf 2T֘Yuy \vd}4PەJ/yHc=NZ~6).1/PmӔJ=XQyF-غsSw`0H 7K]ؼԘ֔_d3By+ݳ83ݶR)[FOy, \:l}ܲb\<X~|ƭLC)$C8& 78Fdߡߥ ' %h?61zrvܣ ʗdQ%>43b،{ٞ;&9$N?5Xxڤ?L*Û̮0!#B:*D$QE _bO}t?;{ZgSԇԴɈն}?:)$7E]c~QBA"%d ԠǛfIJj2?B!&bU"3$^۴Fi"eHj"&EC& z@P"䩨o1x@C+*  ,q/|.b;D/ Z P X_F乶 :6D%2P4@+⣩1 *8H:]y5.1p+RD_@Q%qj2k)©1LXDr"yYݓǬإyj$IK,rتYEٸпw8TF7O$6 ؇sڐ/ ہ@N<8?I-tⱐd< 7K^>9&ղR&!G4LvC!kݶC/qڏ״R2í0LG*&elO#k-$jI"M/1\ۖ.Ϙ֩A.eCfK3 7םAgl-ŰB{@M:Skfa8HG 9M^@+#ՍGtY\̽4IMEt#ԍۃWr өk2M2H''݌62}E,JH+k֨?an9ϣ{'JMP1)հ}uiUlnM ƹM!GN4 մ M?lΪ2 EN6 wխDeܥA9O;Ogjéc@PY>%sL_ճ>QAJWl4՞K4eҹ cK$73 #LeR6 :3ҶJÕ0JVe< rά%obB;lز]ES=I:L7\Ѧ;~>זuEWCA5nMѭӟW e>UGΠ0ɛ=Ԩ#:RdF$G=тRkg#'4Ⱦf9bUK"rϛxk]Rǣ-5UP)*:rً yISE]/RQ.>Az/[>j+,^QSE3Uܫעɂ]u8&M-T7 yЌչ!6[JM0"KT:Ґ~ܵ֩yWGR;%lutmNgEPU1A!֓TNҚŲaф ?UpF^]֕[Ʒݣ5$QI&$Gӝ'@1}PUL2*eH=ݷM%JN2&ֲݥDɩSeE4O8/g_͖ѫ?(>P@+ە+svbݪL!*;6dNDn!"3޶b(Sg%4_Q,JGw(dډXI/OE~M4> `Q e4EP 9K;yF K].,ϵQ'_/KE#.b6ſ6{Z[oCK3B t-qCé`" 9*NA%ި[k«K\*RLM1Y؀۴ߤհSzs@SD8dFЪ/-K#HbM4 ܟy?-XÀï҇95KAB!$)9 1!Ƹ4BN"9vL:xֆ x &yI0MR2 $ML%ɝq@i/LH)~".9CM Ю%ڪp4IL)C /V,-J[ΣM 5 ,7J=/ٽl٨W֒ 9DLb=QOU3zK~ƞPѭ 2NHz>r[ܖ7I7#?l?R&ߥuIԆ|ɴ6;7A/KT6wޔ2jJV%H=9#{;Hvyèt:B.} I-!w+ʒؠһc$B@&VQ%!TК͢ə6BL@yGQشߠanFRQ:q0˚~cE+NpM1e 8w7ݐcŢF}10MH+ z~.A8nAˍ_0JE<)am1+cϺnح.mJEj(pc D2~Մҗ£Sп%FF* :؀ҘuÙC&:D3H+.qHmz 79bC/A׽Ͻ0޷<O*E$A%79Z*Ήoϖ~!))OOI2 L7d0 ӑɦ@1LZ@>bn5&5հıgBCD&=@$ FȣS5I::Gޭ[ɉ ;1*LJ*]*pbw#ŶڤfIC M 5yB|^%r孊0_JA KrpC Πt8 ȫا7%EI0.>T]UmӋҸKY䥾Q 8QIy7-9x]l#A> xԷɒcFE/ 8HC60؉ ` 0PJ)-l4|ȚTǦZWC%CNR57 ):IĿ4]Ӵ@B.Q<(`ZŒ)β/KE$(8lׄzG]#IK.r:p>egd3t>KIq3@ jQѢ9 U-D9X:RfˉK`@OB"(I;G-4͖̇Η$s!;Jj8 :;%۾ɚpإF 8jR?Gx#VPg>bĶ|OB4QI &h%۹nɝпǮ32s%nH J.P sMͻ ~̂Jvݒ>N;vq3d<Κщ7ʫ*5K5NtA<x+*>x׺Ӟ&k(+FA "#޵ ?osŒM1w>E/ 8 pƀDN|3HI;W.ٛӏ`C3-IqB ޠkP+YիirB:"EF&l 3˄ޯ 7WC- K4b)0DX/Шy8*D= G zޠK^՘nAͲ"JN,27 " ¨Yl#GP8 s.ȆL9z1[H>OiB Z̍V՗Ѽz޼K?FT.0Dd!/(҇o1pw}w H1N24"Iη`Ot~uY>L9u4uȟ%#u1&~B@ %}^|9$:̹z| p8GH6( ߌիѶ@W)D%?( A`t~3G?=+C*IFʂɶw,J*?6SBfB-Tb̉¯ӻ=VE0{7'8xCv̎Șα] 7JY=H)'Baΰ)D{k$A>#_gI_ hͻ^܋ 1@@3^XUOͼ "B@$^|ַ3ɠƲBڴ7C0s 8vP;!ɋ#ٮaȗ%>29iy(e+Jr Aq5?z- H0asΡ˦ͩé9'@DAT'/rpn̴NFN6 oI0c՞ŀ"ĥƨ%T :{M>pQ+>[#ִbSK%DE&*3=kn̾8qϨб\ѷd 9>K:sn_N>!ˮd (GC#%4ZיиӲ'm=Hf2! g/^߹$̦ƛi߈BK5  ,ӪsjΝE8ak-7PDTtZyܑƍQ\&2MMO/zН$˸ @DP<}K7C;̥΀ju5-IOC#;h=R&-̪JߥH;eG3C!#֫`Α<ڷˍ,G@S?aŷכнݮU\AG .77~Kε؏G45Ж5OJj;h3L2Gͪ~״+(!HD($w(3qR JHi۳ҽS[y.H}?c7 uR~șY?LD.+ cZb"j޴ф.^4G9l.q+8=ޥ5Lʩn'FC`$0>mpނ믇3 ?G/B HF7}r~y|5̬{3XG9mTjܰī#}CBp%e WۚBʲ }7U܎ٕ޵BD(fb|bڢDڈ=u;E0 5XnMXܛҠ?1"E87aCۜޔٚbFH&ZB<=fH޼i۲2(vt2YO1;-֎}7@ 4='~=.%~1-}ѲH6>'Af}*FښI̻7;"j% J6]rҰ@k8]9>F\Lڌ߬߁q9b 96h g6x cP̱Ȇ$H;2 WME3fӷ +9u+ ?hTQޔ.<$d[1Y8# wqZ~1&05a5:uz&dݎ̒/æU83&ܑ֖SǕ-9Ⱥ)>2Ujk۸ܦ<Ð ̮/@j0u 2wND#-ڲG/E*Nd4Br/ xuע\;5d z6B.V '&I+׹ҪvwȾџ 56C0 \axΠ|5rEa3Kqo8֔ Ƀ\2E}6ph}HܡֈܰD'U.D#9_\stqQ*Ba!@?#.8g5#I\,P_iGU G^3:,tt1fY6BH09,nmMVs̳4 M(òݺ>2y0Z!+w Gԁv3ӳ 86 +46/ %/m0[35X|!9S9'|eurٵ _pqlİWX4n7'*^bfԘ;lxb!p/1*mӑBT꽦7S ( 0P&XefЖ`J#*2$, ]٭ө'f:ôT!3T0B hPCWq*1!֭6@<0c2~%MhE)RĄ335R# .dk)L=KF, 1-H2NN'R(' X9 ՘Ҟzg,.z"^ gfd2E%82` 7ڦӵ48:5'" qb׉|J R3=.j V*ٓKksH'91\as դU I5x1Q@a0O8Ox)Ə..{jGo׳Wʿ,*"T ?BƘ㱙,-'wjbr_2Ǻtu#].:$eiP&x$vG., m!/Suܿu/vڽn߻ F*D2$U =\2ܣZ¾ıඒk$j3)Jr(bzr۽,ѲlFʸ0I3 /O1co B} ڶҮı ƛH121S"Ey?ƧÕ .|1mir_eval-0.8.2/tests/data/separation/ref02/000077500000000000000000000000001475740344600204735ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/separation/ref02/0.wav000077500000000000000000000372541475740344600213670ustar00rootroot00000000000000RIFF>WAVEfmt @>data>KT8)%+!-OUDWdcuhxu@[y]ku{mlxQ2/(?jpnc\`jkS{sHfusPfaaFDCfJLQ15AIPIkaTTB[Pe~O^rbqfgMO`PiJ&X_\rot\@DJVsH=nCRUs`HK%D53 k4 R" XQ#n)ӊW(ܾKSR߀X>]RTx%zJ6M^ :Br qL *9B:8d;n3Nx+\.Ahk?yOWfX+oMSPF ;Tn^hQnW+zQ`MV[{#o"[2WTAb"@\{bmlKcuJKHH[*cF,A~]jAuT>A7 ]IP|d14Ko8 `Yw"V8w<~iJJaGm"rexa({ifd!4 N05L'KyM#jMQWji`\SsIb5MHie\^ߍX] iK;+! /(&iJ}s4s!gcJgpxe2 d'/!GHB%cCDW;V uLFCF ]\E0X%c+r^\D a]c;gFD%nk"@VZ"d?;X oO Ez[|/GX=[ZYQ4x"9kf3-jG~dJ =[)/_(s4Zz6O+;uH]s(lwX~b(ߜQ1uFitL(pUw' @1@%$QS"BMQ"w7,pupwoQU`zecJ&KQ! nJX|mF0 b-$^BW8psp0Px\;GO{H:s&T*7?T:C] V gC'0oda 'dmݴ0i|R8ew &+ )7[;ݏBt ; u-]|Ez)pM#c:7eZg1oޣE Rxm(se_ fOqR@V+1 u?ߙߑG#Xۙ{ePQ_52Is'&^ ?A/{&)f&] `!޲X%pڟI7n/ >۶-IgfA:!m=^w?keoP"wgE޸?-<էae^֡w vz52 y|V5ED!CJH7;Q|_߃vޝEۂسմ3.%"mܥߌj-k9S`WmaMD7dWev~azh1A$r۱Ilڵ.hI܂Y&OB!o4uwr= l L0Ks}A;> N,Lt eH+Nl&KJQ܂ށ9l;qP|3\.Z{O;J!B=.P2qiW_dDn 7}$߻z ߷A|2ZOIzߖy 78M\4E*DH!)jw gv 6$p79MU**tM.WqYI-GL=lHL^Ks>bW:zCt^h\\jFߺQ ߫#R.ߛuM6G;;{6H}n2A'ވ\5ܚ "ܝ۷R0۝]MCڿҶȂwñŸ u r3؏j' f$*h)*V#; Kռ%Dļ|Ўn:Ov38\M1)تΤpDT mƑP'I$/*08%|X P:)؁WM^ P}2=υ˩ʟǦL.ž4Le^K߶  0!v!9&5!6 M epًQ/ϱwz*ճOh>]k WŕͲmx^ЕVs#)U+.N 15-{4xڨƁ92, E{|8Jļ߾ɑ<&פ՜oUĤq0`Й:ٮZ3ǥȻuyAXRUEM q&! )M)$S.tȷoݢ6i1uҴ P*X>잆O&# 9<9U0г 90#hTY) )c"2՟H}"^Ȫ[ʰpq rES?`3MBH&y3t-l.ŬZaY -ɿ\O0`] ש+xTE#>Kq:ƪe}ֽl%v=w}!Į[צXڼ޼>_¯&?C7v(ʻQ!T:¦'ْ@fiݔ45tȝ>-ij-sƁ!<26Pųkf (')3"ˀم0L ߂u_ܾ^O,z&t 62(Ȥq7ٺ)O ׼!Ͽ3՞M Yg* |ɐ`ӚC}'X+5;ܘڴQMb# 8 J9҄9z 1Q{ĐɱԡEۿr:U,s`>حؐ`x FfZتьT.sSUDG9Љ͇ϴrȓrσ|0(@qfpظ!|cpMmMڏ[ G0FJ+!(,$6%)xMٜoG&"ݿ/0 sJnC:ض"ý5װ'I#+bфʛэMθ]δ@'H#; W ܪ̵ԕ mre'ʻG0Eő0<(16& 'Ӆ̜=q7˔Y2nj؆ãwAժJ,0?56} oҹ۶ ݖϖS ,)M׽'b݀* /#K|$ҭV A6@bcWͼG 󫄥U4 3v7i,h| ]J1AdA9EAN% uZxO #C0bkېǢI []1؟ڶӽǍ߬άq 4kx *|gyntA̳fe̽9«o>SQ !_ɞ _  D4Os%޿_߸IŸخ4> {s (Ȕ֋1:8U Na)&&ٰ1}^8տ޻f 7 }"ѤBR~+IRװsmBނȿE#@/XCѢgNa' @$.-hځŽ|դ̚ZZƸ䤞{#6 GQeE҆V+]Ph4G g}; !&hxɹak޾ M !3gY yߎ ʌWVݻ͎mĝIJx9|˓~gߒ  R/1ԯ™&>x ʶhNxǍa+*L   ui o*iʺՖSǾY2"=FB5 6AZ$Fףʓyˣ%-\ZʝٰuWkM   ʆ͇fМ։F䱾)|wu hoz   3  (zitĦTRDS 7"Oܓi'Mzoߧ (Ƚ@PĞIȣ, ӑџ !޷l#-MD(T4h  D|Z؎Z,y'G"&:ÕՍdV2$֕סtOGw@ٻ8v\?U@EÁZ'o*( 9/; 4tFl? )rè.ԯJU (l"8 v?l)ui:5_A/)h WC Qy)L!`DFÁſֽ A +ZTG [m mN?:b>^K̺ç6>xzK !P ,$|MXLWrL<`νJz, E95tsn3C  ]ԃ9jǤ:&Д|߶ l:g*m}]2T~ּDŲδܡی;8zoR$0J tL  ibw1糱Ƙ؈}\v\1K8yIP@x9ѻ]mRftVlGz="Bdyy}$7gFߗ(>Y볈.}AUSd LR{Ur޾ѼUHaH(c2uЙuq˺,Śi-؟s 'X   5 ^9QäƵO 1'S8'r)bL@H* P8& ߇t΄بQظh4bY r? _ A o ݺ|VѕmծF'7 --f>1 J ȁE(< C  LG jҭ1vT00 .m\ Wn,vr#T'D;n- N)h%W H n3Zt+{b5. n A/c 'n ],hv Û ɡ] &#6J0d{ cIU͢|ޒu=S!V! AX rQѣʎ1,7 :"} uGrջ>p֧#O QcaGw x(*GwP_Ǹ~ܳ&h0G% +4g^ t|MՎ›ڗ' jS(! xFIj (F5KŭQ'*#HeL 'AѪ$XGH +H[GA%봰 r %2*>TJ|bn p*YPŇQ1& #\- N2r|-ƙ%ϝ|&U1 ۚ0-QeNXYhrc"/)tԸ<>lnGt(; #oT.( _EӺQ D|֝ȝp>u+O".5?oxAg$Ǿb\Fʵ. +( W23ۈd`ɤ3)bҫם!t?n]kג @R_25a٩d$3Ou$®hٚ2 *5W#J \r 5y7ğk`󝓽;4-l%ۏ-La"BCɌ4+!)sy"Z4ӣL ^lӛլ? o"q !;ӥԽ,&sm),?o`pηqL4xDq'"FAu ˤjޅ W(z.L^ɺL n #4mѣ0sK%+Z!qڳϝ;}lg#!0w>4g!1K*iۘRz$i <բ˲JL v-*Ju5 8F ~a8$zX{!ߘ/ YuEQTQJIu*Qf%ׯ(cF1cB$Y$- w 'I/]s+_ t 3YC%\*$L DarR2 l $Wm9pç*)PܞۊP6 $ pYwאo9?.Yo 3V_ݒf VߠߨGn |m-~ |i|^?Tˣk:1 09aB2֟8܊U q iXߩۙ;-| 6֮ձXu=r]Ҏ巌8ŧ=l@<5 h3ס1i" b"bԮTP0 K eGj }(fXmq4!øDԫTJ Qtۊ. >t.•}Šc% ݲvٓ܎I 9{(sy.ZG1 FS[qt=@{tݱW~=' mir_eval-0.8.2/tests/data/separation/ref02/1.wav000077500000000000000000000372541475740344600213700ustar00rootroot00000000000000RIFF>WAVEfmt @>data>eckhX^heuzujqsxeVJSt}dVVgxsc\UU[ntqpx~[LCHShf]^n~oc^ix{~x}{~trltn\.%z$ 9v!B#!Mw<~ 8$Zۖq4̚ŕ1Z9·Т}C*# #0)n.a36886429.w,*%M"x mi۸ȭW;Tc:x ; H#eB* 墮)R=jՌgPjH j'w/b26$=?C_GGJLJ"LLsJ>>=b=Q=;;9876I6o21c/*(## (rImGۨԽ'/N5Ñ.{KF X-׊X܋IuAÿ6z* cS!*4">%EMbTAZ`Ig>k ostuvtspZlgc_ZVUPKFwC_>: 81-()"/Z &"ҟTJm-V[ܹ𻳽f*ÜnŐR0DS0Ţ^˅͆W؟ތ["-< z&rSk #G&(*/-/>012W3,444`4332:2t10/.-+)C(V%#!; =L3  uji wϣ ǑſL,KAD v"EHEƅȺHϽҺ3"ߧHCg Dy n#hdi p"%$%s'(.**+,,-?- -,,+%+*e)_(]'%$"(!q# B(\sv%^ߏGۙլҖe̼+AUdzǔ.T' 0Hќ>ԁ\+9R|KzNkv, ( X#& !j" ###T$M$b$*$#i#"!(! 0#o dHVKn MC1rtͿ;ʪ6ȸ bt;+&Sί Ѹ|E,*Oރ0jiNT?6M Z U3j] &5;4 s $ \_ g - \ {~{ ALiڰ؁tx՗@Ӳ6іmhrњKҺEԯէָ [۶ގ-hjJ< s>rO > =rXHS~p0j8yyL B Cg 4i%u< 0o_Yo۟9٤(q2+[נt٦a3*IvY*,MwO8D'-n t-gfT}d,wx-m t>Y 1:Jm9y-`NP[z%zfݒG =ݐh~!Y0-P)i5}[TQ C O  f y 2   t [  lK, FnJ\a,&W4 k"nTA724=O_r)>HOOA3^dd  ; d i < [ p,z(Lp:c_Vh\^fy WVk0pXH;*! oGl$h|af%&cShPj=s+DXl$?dc[.%JR!huWiMF|\>!}W/e(1fq[!s(MeuulY6 G*B8hTHGs3h"j c,&Yc'B|p@9S/Bt2}?Hy&}Me`;?8GORF3>:_jT*C;`:'{3lV_ t)~Y>+##*6PuSV" GwWE/k,?B8t%u3ctC >*UovlZ<_= =u{4dE)  3Ps P5O( 0BZlrqeHy-}N 'ARZa\O=#x;^ T1=DA<513A\]i$wJ$ *Nw[8?c2}]:\.N_G Ez,?KSTNE8"k6?] ]G Y*bB7>f&Q*@j>|K1(|&|(({hHMHo"&+./(oH[$n0k'UT%k; d>uY>&)?Vn?_ +Km6Ro*9HU^gqv|}wpkbWNB3%q^G6" rdRB4$  !)5@HQ]fo{yqxa|eeU=?.*m< epnNTFc?|E`]L *nE>n"Maxv5dbb?Wa&km1&JaT5.`u}%UDy%j_u-Y)izgCCUDwl*Lmyl\: 4*][ _xigqp^\IVJkaEL."D&>drnQS۸ՠŜj%rI`LƆ϶֌" %#)/3N7098 74 2.,)&$"su c_Oя޽bvɏ?CՀ-x/~啐jZb(θ¾'cX}( jd!'-26:>AtDrFHII+J$JIIGsFD3DCB;BCAq@@?v??>8>===<;c: 9{75i30-*&z"/Y gt{ǢorV5-F*͐֏f)ߋ ]_3ʑɕ9DO.Y( (2 :72-(" .c$Y#QҞ˜ctd tĽNƇ`1mξo=¸eBCi˩Ў-_ڃ.f8sx BG "'%q')+-a/012B33333u322210//.,+>)?'%"h W<~  ?hgBݴڬ׶ eɳǖŨSK8źlٺj1"Fˆ{ƗCϿ:ܕY98EB=La a O%t9o x"G$%c'()*j++g,,,,b,+o+*)('&%$" !c] * JM~]Acߤݭ=ضPӳ{YM[p͍~ʨiIHiɫʢH IѡԛP",IWezY-H:D 2  H* CPK 6!""A##$<$?$$#G#"!!. <.,.?A 4 2PCEdE/ܫڊ؂֔ z̸Il7$1`Ȳ*yMAU͏bҮwUGO`zLd:L- 8 + %kt N t y \  > q.p ;vݟOTԩә1ѵћќѱ-ґӯl<&&5[ّ/ݔ ,EhQ:J ^ f :Xd_>V@uqC  c^(bL'{H=l߱ޕݍܛۺB٨$ط` Hוv٪h8/V'jiM9I7U + ? > / Lg4<yc8^ s x m Z 7>*Y~ 'R+IYߊ޴c" A݊KWߥc1 @kbH6P '9><.d 4  s 8 @ 6  n  6  z JxfD!dM@659D\xW zs9 4n~tIW4 /CQ^mw~|ufP6q)v  ~7 ~   > $N#W  .Ff4~3Z lPACQjO |W|CziYJ>4( tJZ Up`#p.=;,z-rp6P6Nbs5Z3z&rt4RI$(PMOpK'tJ{;\=WC e+RtkHEQNI D_Nz }SL2HME=&g"zAL=z57&v`Rc*~|/w%i:>l(v1xwM0{(y)x c3PZGzd.GZfc[L0y6C/3([+f7ofo Xh"\<%#9X|T;R) 0H]fh[Ay0~O ':FPSN@)\ >-a"%)+'*8Lk9~(Eb>)@]~RR"qgCsLH,Q74Uo=azs( PUbDD:<%;HE_2؍N-? 6./>LNkVUYDu2[gCMsWAVEfmt @>data>JJGtnѢϒϺj۝Rzٰ؏٦ڇQײӛӇ6Ϡ͹%;_9ۇRhh=Q>@TbsN1X1xi޿sقա,[zŠŦ%Ʋơ6[ǛƸ3ս oʫϔgOB!k xqzY/2َԗd!b'm߭!-vn D(QϿӍժjعݴ[^.,+9=t*mNvsߢZ8ա(ԟ$=kX߷ՠӫRϊ<ֻDKA?(|zߌt*7Ծ بG֤ǘǘƯɂ<Ҫݥq,cE ŷ ˳gš7+ Gse2/nHKp\إcBSٳݞM.9i4ЍC϶Я҂=>س- d^SԆԈٝ٘9ׁo%boڜ<cONm/wI`a7w7QX>TױҤ @*Úƴ@׳^'<$YMMD!t>I wՔp KB̮p΁MȚżç¹V.Ϧ՝aߤߎ VoJ=)sm%w,5}ݙjܯ֎)ӞԹԣl2n֫AסMA5H;Ms^PԹԄٔݣ(ڼՈQk{՟?״VސIVݩ߲*;z~bNpEc8G1I"!dݽaZ׾@e;^1ʣKмvs]ڞs& %,Fa'z9Lt3ʞ̅̌qxfxׂתi5ڑ[ۼޤ(?`sBI qV]BF ݔ`ڪځةWجz\ھٹe4 gF'CUԪrz Eؿ8Bx^HCcd@D8O~!/f]A#| | Ƅļ1ƣXTan<ֆҠZϊyԟۇ~RI17RG5Qߏe߇h۵XUـ|׆ל06۔~՟i֡Vܬx۞{$ܻڨ7(C ؄ vwo]ӘџN#6ޗZ]fJV+It=GBOߞx[}QSsר!gIȭB9m.ȤM˩ː͘Oѹ*ҴܼH.j4,*{ ) I4 +ހK݄6S̫ȹPzYgſIҞWE׃ךфm.X`>ElZٚR؇^+>U<װ֗WيٗTMפ MHӀ{חuԻpѭϜ̴$шא٢ ,Jݪ bla%C)yh'#45cWZ~i٠=2{fǜ[-Ͷ͡JfQsСi}$qgl~^F!Q#/i|@yۻӖaiW=Șwǧ^[ͣΩXVӫғi8״N+F"xR=@JG D-h^ӣ&>܍ޜ '0#N:ծ9٥?H^ݘfݬ'nڲֈؓ~J(Ӆ1ѓb̄ђ)TپE3 Oe ~<]fH@<ڽlODK͙˖lĎ«cƿ7 „~ũ=4߇{7r0oޟIٌB93ɧ˻̟ʎΞ"ՀH p؛SڊݒAm%.sAUFk*(3߈ 'x|ԟ@LMB cHlՃڿ=݌܄jYڮ |LuοͰK(Ғd2a}^o0>/@I4aX K2 s^Dnց;ҥa͇[jT[űĝ~]i*7)=7Khm.`zNDB[M,%ܤ+Xe8̰3D4)Ǚ>ˉ"q||lIOXv2gَ۾ڴ֔xU|pҖ ݡhZIr&7YhM[HߚܣPOVր|˫ɠ1̳u K:ۉݲݟ&&?05m*@YX}220wە׈TҽϹͯsDģ*ݼ۾ .`a/MưǛΉՐi3<QF57 oѲ`~ɚBο!uβwm̾YvNȲ|ΠMӝ1UԠԡIpXT݃nuaqQp+>j99y ]qXK݃,ݚ?2LPgٝzGWsshݬslՎ]Јz DžO)%BP`Y>@ p.k,N<, WnXu Ұ ̘ɥp{`$u4EȾ O|GlE|,b0 AM.l ۹h֌a4ɿ6v{ ~ɼT,(7קYكL"b=n[0*qL\|)0ݿv{dۊܝ8ݼܾQ%ߵݑW,"b.ٺ^s(>̛!W˓"HYİiǥ̆Cӳ&ޚ,C@o8_SQJ|)߉O}ث$ѵϓnw} V'%ɴ|S_tdֵߝ|KR/e\i~)`SLDdճsՑчѫнΧ̀͘<>ؕ׽nڢG^RvGBl{dfBO.Hߘ^f}Al =ޏp]p5'q? ;#uF 'Ѕ2N]=̺fOަWQ8!S4HD4ޝ!c/cfj$Õȓ8)Κy\ع۲ۮ4rnL)13FlK ݅;جٰm֯ՠR8L2?/B٧h`ڋپn PڛKGޠޮޑߕe9? |(~6H=ii!( M3p5 ݽA^ӌ9 gɘrU0)~̑ͭ?eĖƓȻɲ6ʾʇˉҟLVa$/h*2q A$ܴ]ܧnQ-ԛ MϠҗuްڐazogŽ-ƌҍ}ֽdJINPDzx7vVr pĭ5ӧy1b*DۨBB΃h$ǖhƵŀǻ%͏30%XtKmLgFwZ=$M:&$xTߌvBΪ?#?Q lЅѷ_vѨ:!ؠh֐ӑͶ 1>ɉ՛lކuLf RO v V1D'+ :qQՇAKϊ ւجl+~@V ̲αLBwږ߭9mu:)?Yi~{kޖkiEϢ̥yY{Ȣʁx\ѻ5ܟS$AܥѤς{Ҁӱ׳Rj/Lq fyxNs@~8[ȝȝȨȒ˒xĽ Ƙ 9d|9=ov[Ey}z8R /@пɏйX Ox˚8#Z,ϻҷ@؋v>!sB .XzRމڕۈs3گrϏTз~'qhM;I8o<[ګ@_·̌:ɁɰW1SsZ=?vZW/5<rD$Pش6ճӄ^ғkd^;Ǎĝa\ɯ XD=M_Lڱ+@_6YcmIe֭͠) ͗Ϙ>/aɐɰɑˆ/υйҰ_ۜ.n]$F Y(CV~ݠ~9|[yjѳ=yeEۻjt>qLZ=x{qRǺƥɎȈ˦LІ R /NIzޣۦԍnӚϡό2ѿЇЕ9+#X6ב]̲ʢʮ̨͒ϔ9֗ٚݶ.߁& j9۠ڻXՊ҃GګS* ^Rްܫىwpd,6O Wq}ܔ޸f!=sٱΠGpJ=xE8\Ҥ֢g@Y8_oBE_Z~*54 mnuSa+pԽ/{Ň[<&ՇԻҀ8ҋVGM>~&fCQ  /{٭ԆAtѺ|΢̕͵ΜΦӘѩΈ˴ʌ0^ʮ4>ЭҎ2g׉npfW~[ݸ ۈ8ؘDԾԡwOai`HF٠{I٤ڬ1|۠s?8P_ߞ=[vjXƆȯ4aѼ1J-%hWD L#t#fV, N5%̽ɧ_V7{ȣ5Sk~ޔݣܙ _ke B$(ݤ^J[D~C_ŚƩȇ&8ӳ %ҴjӺ>y$ڄw۾ޥEi4Nr/ݠڴyلۅ`u}82V&,ߥkݪH܉ޠZ842'ղK{?ʧYǰ#ɵɵYʎ˚L΢e܅AX;LLb+o`>4oCCä±j `şqќ2؜5Ӛ`״ڜ߯-(zWJZp:?"}aܺ,lԎsLkˊ˲KA H-ջ`/҇W-'EQ!hoݜ=oߺMcE+پܕ(rvH>ޔ߫߳ߖx݃K܅VޓG.&B_ہ՚2hԧrֲהhuO}&dCg~ayGf#>o~&N߯C:ξ1ȑƿ7öƸo涮YĴe׮fSNӿgӊ҅vث٭HԔU=ŋ7يd)8$~)/336 :5Z/*#K1hչq7]̀tpTM;| []{ ߕЅ\Ǔdؐ}c{ˁǣGDخǩ̝81ԅUӏ̾*Vߧʧw۹l ^W#.z Niԭš׶dzi@3fd|yޒ޻kץkdhΞX֩hK/- v"rudoto_BF6LHjʡ/ɂmcNk;ۧsȘǶka!etw :JJ8ѶυsјhΧ*Ir~Z!ۢp߆ z-eݧޱs;; n޼+O3LQഔH'Nlan\+cŮƞɟXnw8 j  V+҂ɮģ΀İʉD?bڋܪjxpӟێR[MmzS'{Q$|"&3fέF BNQa*eѻ׿ 'r P "ڦюe#ʶfɢˢRSں؊}ӥo0<ڞkآ޳4#}Aߠ^ԧS؋Fi mزAOľ^̰ϸW48J=ʲBӋ LQB 4`H}1v2Hɤ&f}7Xѡɗ 6}ǩ"9ؑ_CߟRk_Obr٘|Vu5"w݆ܢۋ2U8/Jȟ~J=՘߂&'m ԊΟfzŵfhGQ]O":QݎS$ʅʫ a;R0\Bh _ܨ9֤]سщ51ZbjRȰtεc"ݱ sݵʲwПtJ n BC Nݶ׸(aûqT+hTSRqqќVx C$(y\?9AO߶ܧ\0N+۝[SѷɐȲҠ֑2kږK"݈DۿLmƽױX#fnٳNt:kܱuG%$M},v eFZz2VpQo8ۦׯӐEPN`KNwpE@rҟ7)*(pi!ކ)NY+Q ~ za 1;x[#轈5Gilh|qC fǚ3[,fue #Ap RivO ;5Ӯ,٣)2][vTAf[,frŠҳJ߯N-NT\Ƶs`ŗw;liܗg&7"$#*vY5.^ṋKk(ȷD]b5͹/в\Ԗ AG4|TUu9 T e5uOιȑyqb6ϕcFֳًT۔`!$*a ҰӔ!ՅH׻d!YbJߢlQ>M_m-څИ˃w'߷rpuݰӤ3Ȼҷ5 :߾A$1Ġȝpe̵ϫރk,/`.n#hbemmcJ\/KƾشJ, ϔ|L߭_T>˳κx֗@D@  Y u mw$ٲq֑Eپs1<݀հ(۴tk6N-nӪӧՔ߼[WX&K ]mir_eval-0.8.2/tests/data/separation/ref03/000077500000000000000000000000001475740344600204745ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/separation/ref03/0.wav000077500000000000000000000372541475740344600213700ustar00rootroot00000000000000RIFF>WAVEfmt @>data> !$#" &4(194\%f.w(h$E h_j5Wۑc\ϨмҘ2~z3- i!)06<BF[J8MOOO)NKHhC=7/'  ۱1ϑLeiHiƐSͣj֍uT- 2"%%(*+,0-Q--M,8+)'%v# NJ x@4bcw):ٔ- P|\iҠ҃/ CٔgE{oa\_fifinq q t}~z~ "$&(*,.k0b2V4@6*8 :;=?9ABD&FG IbJKLMNIOOLPPP{P(PONML[KIGE CA@)=9/692-y)$HgU襋PsI%ՙɞPD94|2ъ n-f !#$$$ %$m$#"!8 mn % ;?EE5*  '\՝ӒѲTʋ_`?Ę}āızƥǠȹB̪0{B3_-ZKPbwz e 7;}!#%'(*m,./$12325\6x7~8p9P:;;}<===^>>>?4?G?I?9?!?>>>:>==!=<;<;<;::98K877Z654O432;210-0/.7.-,c,+?+*5*)S)((=(''v':''&&&&&&&&&&&'D'l''''(E(p((((((((o(,('l'&<&{%$#f"!3Ah   \c`ߗڼл˨Ə{lkǨ9֟ٗO BNj؆ DžTLŌdeÕw|I4|ڿUZa/sr! ga} v"$F%?&&T'z'Q'&B&W%6$"L!x3; #|x&#}̟k[mȭǢT..UƜ ǚI!Ơ|ӂZA>Jfߕ cpr  r <>|!$&')+G-.02d34607M8Q9B:!;;>-?x????@ @????C?>>J>=v=>>?6?H?H?>?'??>>R>==9=#:  h /"#$^%%&&%%J$5#!g >h xfT@/ -Hx)ܪK \^-ƆŦqasĬœ2?˚ Ζ=ԣؚ֚ڮ7|-dJTSJ> k]! #%&(*0,-U/0/2|3456789{:&;;P<<1===>+>?>K>G>1>>==f==<_<;y;;:9m98<876P654K43232100m/..j-,,+*R*)A)(D('c''&W& &%%]%5%%$$$$$$$ % %A%c%%%%%"&F&j&&&&&&{&U&&%b%$R$#"! 1n XoC,tۦַѿǭ•OJ*d+؃Մ~苭ӑS!gN | ]1>9- 1|͔S7uYg/8񊤍&R⤬߳-Ė'ϵ5ڪ Llf7Bpd 9Y !"#n$$$$ $R#T"!57; & BSTPH6$o "$|&N( *+O-.G012&4H5Z6V75899v: ;;$L$Y$m$$$$$ %4%Y%|%%%%%%%%%%`%%$-$#"""! j,RR&E l};_ڌՠЧˡƓpnqw˓stڊdžch܃̃!*͇X2qۙ }."\-@bU: ,] !"$$@%t%_% %v$#">!h:x jcdkrؔX37`ΪˬgNXƉ[qĖ]@Ggɧxϧe8.Rވ __QLR>  ~2 :aw "v$`&7()+K-.R013F4m567o8D9 ::_;;j<<*=q=========[==->5>1>#>>==l==n vċzϜ#qĀУ/۬[Ym Pw!#D$#%%&&%\%$#i" WP4i n[L:)%>l݁ؽՖӋў=qGōhZuɬjΊ>1jTkcukM "43 G"E$/& ()+5-.I013M4{5678r9?::;2<<=}== >4>X>b>a>V>8>>==W==<=<;U;:P:99988`766g54 4Y321C10/3/.-8-,+Y+*.*)+)(/('X'&&M&&%%W%.%%$$$$$$$%#%C%c%%%%%&@&\&q&~&}&&r&Q&$&%%%$#6#_"b!@ 4OA> K -l5/Sd^L?.$-FyߏyІDŽl|d2l fb褲γÆϪ5ڱt6 E{'x!"7$%%%#&=&&%$#"p!'# F PUTG6&U!ۯ^'%Yγ0ɠȑǪYđooĕHň^Qaɒ?ͿYөՏ׋ٞۺ"ff:" l 4.q!#%')W+-.012+4]5y67z8_90::;.<<#===>F>i>u>{>r>V>4>==}=#=/9\ʤ~~S<5@\݃߶EZ8$!' f $y At!#%'Q)+,T./N12315R6c7[8>9::;<<===>F>j>>>}>h>F>>==D=<<<;.;: :98a877x65 5r433]210I0/.=.-,R,++*)y)(y(('7'&&<&%%%S%1%%$$$$$$%-%C%c%%%%% &C&a&y&&&&&n&D& &%Q%$F$#"! 0 "d zBF^!Pbg`P@.-DtȤX#)~#(FzmɄІuڏ}˧űbZ̃ؕat_z Z Wi: {"#$%!&R&F&%N%{$e#" CZ} oZE4"$1J}0ܱK ^d ;Ɠŵ|kćţG ]˻,ιb$J-Q9)+! UX-B!L#A%$'(*n,./ 1m234617,899:`;;<=j==>=>g>|>>>j>M>&>==Y=<<0<;I;:::99|878765=543.3|211f0//X.- -g,+2+**)((('?'&&=&%%%T%(% %$$$$$$%%:%P%o%%%% &0&O&k&}&&&|&g&?&&%Y%$S$#"! fFyZ   Dh`1eAW`^M8+%4d.-‘ÇI;i` q8]ܕȝ(ϦA:YsNvv 86uq '"#$y%&@&?&%j%$#Y" *O>/  (% BߤڹwQHdϬ̜S10VƤŹ|fuħŁƻǻmf ѿҐo_gܠVe<2(!  o 8"_ "$&([* ,-=/02k3456789:1;;d<R>n>z>r>b>F>>==V==<6<;K;:I:9$987N766R543H321-1~0//n.--|,+F+**))(('I'&&>&%%}%T%(%%$$$$$$$%#%B%c%%%%%&6&Q&d&j&l&g&W&4&&%Y%$^$#""!$q^ r ! 4&@NP=)?ؕ\6u{QW )ۋ՘:Υϴ Ś,H(tw" w! !A#f$M%%4&=&&%$#")!z%] ~iVB>BUݔ(թӟѹPʇVRrƻ+ſzYfĕTŧƁ{Ȓ̆ ϥZ"'S$C" q HW7Q c"`$F&#()+K-.V013`45678|9M:;;:<<*===>?>_>i>h>^>A>>==]==A=+ =ڎ;5Ύ˸oNJ2ŽvVQr,ſuA3Jz)ͩ@ѶӒ{}ٌۦTX( t[ $[!#%')I+,.0s124F5d6r7d8H9::};<< =l===->O>^>d>W><>>==a==&*& &%%K%$a$# #:"F!) C^W&4| ?9yp5J! CF+MeԊ򆝅KE膨͊YH-"Yף߷JEkuE|w6 ~1!"#$%&$&&%$$"! HV=L }iTNSXylؚbJQЁGɫȐǢ=p@=\ĝŐ? +rUϐS% 3]ߐ"u9 |yh < PHly!u#p%Q')*,%./1234"6.7%899:N;;q<<>K>J>H>3> >==`=='>=>K>C>0>>==k==<_<;;;::m98D876^655X432@210-0{/..z-,.,+*b*)I)(M('i''&N&%%v%?%%$$$$$$$$$$$$!%?%e%%%%%&&!&"&&%%%N%$q$#2#i"}!r Dln c hVܽиϳۮZݠݔug^xN!a<ɇʼn+h行mwvŇѰ;ܴVzuGGsa pmC@ !V#w$I%% &&%5%k$`#" qN zjbm]o'\T ]s7#3h:Ŝy|Ȟ0̟*ЅR5+3Djޠ"v.xcij^ 5 S$\ "$&Y(!*+u-/{01:3y456789L:;;2<<=r===>9>H>E>0>>==u=(=2>?>?>/>>=={=/=<<<;2;:+:9 9s87;765B543,3|211c0//W.--c,+%+*)q)(t('''&^&&%~%D%%$$$$$$$$$$$$$%>%b%%%%%%& &%%%%Q%$$$d#"! [Zd^ J6ipR!{ݭϿ$6B6"wWAVEfmt @>data>,Pt|M,Eu~YfJCe+IҀ9<J|֢ⲲOm4imɼF? `Q RUtܑ 2q%x[ê6Ԡ}ǭGVaM"K֑8Ѭǻf'Dnٮ޲g q3.rض:Fݝi0۹E KGe ?ޔ-#OPgV4@ފ7ȃ/</hn"=:F$%©\蜬C e ګQCJ!m1]ꍉɚ@<ψ 1 >)jP)@)S<;knɤ w m ;+9S: η4ߔ q |*ї>QħKO][ I~ (mߑb*g 2$gӁ^즼\8 t1 ~&=l TDA $w X08gϢ=<kzیǿ#J;@wLml͵@tADړhw79JѝtJ<*0#F8.Kͅپ{4|۷rL42ފ-ٽC 6H]S[;:B<6gK '= 3PS/>~ :e5R%7!m)(yaAg4޶8a| ( *%\h>!a&Ph44ksJr)VJiq3>BF0DyF=T"v0(ݽFۘNlvۭ*;,o+Yh=};h Zc &7hk |)Gb4 YWw(,?d;32:%S\ng+6Ci./ZLx69-wp  c6-&L9u06olC&`&`e:3rmOzv/y&t!e>L >O' !mir_eval-0.8.2/tests/data/separation/ref03/2.wav000077500000000000000000000372541475740344600213720ustar00rootroot00000000000000RIFF>WAVEfmt @>data>999999999999999999999999999999999999999999999999999999999999999999999999989878989999999999998987:9898998999999999999999999989989989999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999998989:989899999998989:98999999999999999999999999999999999999999999999989:8999999899899999999999999999999999999999999999999999999999999999999999999999899898:;98989999989988989999989878989899999999999989999889999999999999999999999999999999998989989769898996>0C/9KIf_v1eJ1iL6@D|&+h 2v1i#ZףrWͬ+ޝy c #>-sQ\UDG.%O""RŅr9uͮЦq?!̒m'&XnmiVdzAYR47&" 36"f,=g&+އ!:Ս˖#, Jnf#2VBO-^jp)uu/qoj]bWNHAT6#;(ҘRvjMHLx =+,!)0%".A :4-" -CAf?POZ]j~o`he `6TJ?,0}ٚ10õۯ@z1ۮaąNk_[T0Z)BAKHO.OҒl̝iʴ¾Ƶ8ĐܼŵHޟ$(O MCLOx ' 4`:$q(.)&2463 <>:<=< 48]E7$?t$ P;*P8ߑzsv ^UHWр9)\>X״)rV_ \ ' h - u .]s nj    A ]C+$ kkw? IK " !B L<F npuy_4!\V BPvR1%IR (qBf"Wi:JxB -  |Gz47p w `wXSsw  zD"^/+ݘP/*ҌxmZeB>&'bKlA$ y >  ( P [Fdk*!fX$! J:*+{   m<t~`;>Zl}rLUUlYU1F_kߐHfLۀJڤً8kK{ձՋFղ 4>ڙܞ$+<##`Y4^ d^UP | dc9=' zQj`#z V 9 ` " 6  % ^Lz  \ g $  ';usS"H;ZYSxcGP.&(E) p I*|!l2M10x$q /PD&ܘSe!NߴG[k# 7*C'mtYCL݅Y٪أ{׳<ٖ |F=C/4Su|:   [ w  M V(td8K7\f*XPbp_Q*fw}cs>'KkYGQ  p45W!W"I#x&+&"%v)('&&&'()('&$$R#! Izx<oi z  ^HcP5 zB~"6 {Ikq2y]Eے֡ӛЬa˳P;ͻA#ͷѹҥI[ן? ';jq&"t F 7m#@<% - m t9;$W '/![(YOo4Nzov+$J=Qk V1jEa2w+}(|wbNy} g `  P no3_# !zdXSd{ap{u>-zci#u%v '6fm W}&$LKQQh?0ND32@5( l,:AFSg&2Ix&38wbQwh' hW4;! =%WDhda~j FJ-In7dvoO=65%popxBLdGKFnh /p]xQLZHBPRNP% ooV jp}G]L$ga92#9o.,e Wz3IswVUl.J@c*aN&EO!<kW-,@ZF )S.N8SFTRS1v]_|mt;cpsRa+4 km{Q)am?QGF9B%4w2_4CSOPaRqYgkVp#K8nAV{wO8TcyPjed \HFMn" 2TTw6>OBf#bGF)cJ9 0~#VyTiwghuIsE 5#Jkdck]+X>HF#TN$d:^P43hG|krv?rb3tx%XvAza\@t4prZZ^un@yHYm Oc3=YD#YZKeNgF#o%|mX ^<g5i|f (-)rtEgo=O2gI&yHy v}q33,o@.u+$!V+K=~`p cU)[:575vk@HMVs`7Jy\XX`iy>`k"/p=ha|HI-D ";)%qv5v3^C<&]4 Z3)F=slqoX9&8aCli_8d$l6Zjh ]ch.nn?P$FxVI p h#$ _qI1p|:y)D5~CT$O, h{v>'U6\jE@&Q`':+6\T~uKj :t&g{;yCW{ ffT@|%sWa~y==yaZ=dE\Hzva ovb_k#R=U="e0_l;DTISh*|G:E)M3H`'fzx;;4(F=FA<"'|$^d@zOP7q ** qbmZ9oRAR@O 0"J=czZ]eZ{~m6^ ?2K2L\Fhpl1<#G"::<2<;960- .'S%~&_#<aJo Ll!7z3+:֕ӵQ=|{ݵѾ,}ɛW^ӪrۼأCzg $iX}P ^UcnL 5wkkv?pޗ9E ӻ ]B٦_!Ici b#a$A3ܟ۵ڑڼ/א \j՘CxS0,@(@O=qoxNI,9^ G H |?Rt  U.dU  >DkT _ ! ] 0 G k k`#>FGo Y [ # -s;@#v% fCG=?}QT^ ;pH"xdoYn),.ڦۅ@(ۇXݢߺs},P{__lP0AAaLT#9Xۏ\:F<x~H)3!>')oO?If'z>obh&vQ=dZ;Za+Y5y"N~2*Oy"" ||e*4> mhcly0}Tsyk\qrT(X@rz;|Kxtz 5JFE#@@lE3=@~"*SDUES lk@`gW!x._S esF3w)rKu`,R_|(Vc FV~KG6ER}.J[c5>x-z%k & ,7eTj* l  s(~Ce_,!^Ae=-n 9hp4ec`vjsLkwTSr^\IH[(Xj L"ueg%O>,ZsQsU@I)ysWFKcrA -6CghHj+l3P/i\@@/}12 81?ge*'x'+&: z@du<#Smir_eval-0.8.2/tests/data/separation/ref03/3.wav000077500000000000000000000372541475740344600213730ustar00rootroot00000000000000RIFF>WAVEfmt @>data>B6-!i2/o] s)HkM.YPK"5sdc7dCU()!Xj&e?lvj9 [y;rM~G y6dw5;IDXkbi1w!tq@glA[v`1Fp/e1w2g%$h=I2fE;}J.o}Y97+\6]HF/#vqHOy)w$c{c =P/'Upn4RBb'>tbvZ&MDH{Eb.0Q\{\B f7r[rPRnf':P2Y1$'# Z^]G= ]$)1k66m95,[=~+-=zrZNB7En1$*s{D_vfn-c9^$,]~/;vc5m b_,V6#N/l<"ځޢ߻47 U0ܰvC*~rx8~m#qI2VXߩݧݫGԌx4`ֳ֨e$*MS8GX3VLgI~?P6n6 lK֯ ϞϾϳ%ۡQ9LK7,s*%$IRb]hBV߁^ܔܑ܈ܶ}kް M=A}le5E~ _Djܚڪ۵Hݽ6$}\L8# Pf{-^%ޥ݄JܚHۛVޯG\k:AY ; L&rR1`Fܻ@D*{ڼڕ۟f 2j>$ N25? &D4Y<۬Eܞ݂)߁;D)/"<AQJBx gq"trS-Xرتhݠޣ{pD 5a JlpW0}rދےئV֐rl׵يhzړۃܸ޴f~NoL[F"$ ֞0ڨڛlZC=}}.E b 3A F45n_?+vءa}zV!N&t{M =N#p%}{4'-3hsٗٓGe5 Bwj w!v$("] #ٟ؞lG-& W#ל֤ (Q۲ڭT.%Yr +*R.,  yyLgѪ Ԙыb!ӳ{X8&$.-j-#aTįHq5pDpդ!EݢنՅx $,10]$O`ӲlØ~)ON'\m w'],a-!4&ռf޻;pdw7tؠӊ˲BЄ +6r'()"ۣbǗ֦-HK޽Z!ˉk>}7-).*"zxzZ׮{JiXLяb Y-b4*}^ Ӎ̐2%Ҭڵ"E;'!Տ*c,&"*."`;ض !-Ջ D- >'sΓzj^t")."GWVҬ!и՚ߐo" |2˥S  q *[-[ I5UB"p QN¨@)ٲAӝ7'<1=)56 ܄ҿb߮-ܤovb $w5 =(v0$p2Z%/# Q  ͸c(74R-2c/ݧmCȌvo bM@.W B&l4օcWKS* P  A~K>&Ij  V A ݿqў `pڎz0]j3^n$r ^#YUح^ n )TkʩE\O#*vߴL uod\؊ٿ3[LpxA`2ݭfn )nt BPqݲ "3zݧ}7ߡj挸E)h d2fߙ=f{bHt9O46Wu_);n->[߻]3&1($xyݵߘ\MN!@p\_ j]K^b21x|J7q8޵-LpO`&RUX߰X%j2 ߱hO[*] (  z x 6-FhImnҕ#pƤn]%t) &G3ӇZ/.T߀T%] C%-@|њ{g0$ͪ`3 NE@IO%ӆְxD9DoZ?ޙFU\a8Y |:eIPۑtG]=Xݳy +/ `,g۷GaTeڅ"ݢw-"o#T @]3,{cG!u!sJQӎ~W \^k?  _P~hr:bߕ:QofV8 *!gC5c"6X'CQ".ӘֱObe@CY&FC8Q7bcqpZToWAZ!cQEc{D[yo"6](l9F8r;ߪ(ߝ4U<,uihu "51c!6[}ߡݓݽ`7jy 4FK_6FBK) ߤ&/Dl16~eg G?Nq(dkF߆[MS,#TSr4i\Q5" tUyT49yz"9) N<&>t}&/@>Av%!=r ohH jF?e\%SMVLTOQQPQQPQRNTMTPO15Nnlo Nc(EY7zv#'?g'!p 2xBjvVNOeB 6E60ja i0&ETh`#Syi@3&?<fLkO'?ps >Vf*_%]qh~z8W`Y֔ތXC2޻9aN l! V65n/ֽVEb<&#kPa+ܮ"l9߂?MxXj P MOg>Gd W(DA.Ca;WtsK LDP0F p{RSp$La{B#UFK_a;t`_, hcͫڰ֓iɴQݶC}$ U r \ Zgpߺ̃|۔{(݄tO|5Q  AVt֜8ÅƾœȔCvfxѮi $W ;c`JЯ?vќe.ߤ_Ev7^)7L<3"q ^>ݼޔݥ7ڔhڽ˄ "):90"k h5tG̰߃k_݉fJ~ഩ'V /18){.)RR''B0:i}ŸX"% N[( $ԒxÀdlӳ$1d5b c;"NȹŲ\ҥѢC0 [dR~ 26#@C'd̚T?-k  b sܦݩT fTL- T$'ZSҿ ڂߧ$XU`O. LC{.jBKao+8R=q! &&o&9so4V/+7h4>3$b^.Uh? [1 ( m&[G6;P]r!rCW:P}6]Hw0"2sSZGw3SEAYOq}89MMC;3.*KKvvX 45zdq0 @n=V 7 5YINJ ?@= %XXnm34ui}\7-!-@%/ ,%[ xW;2t1o?ZSTZG[`Jsc:QXF1#eQ23 ReF"cA$JV+@2&R.h .vw~jxm|=JJuS cK9"Cm c$Ӄ5[ ?mtvS$;61݉+љdٓb c7 D748܆%z Nr(H :ח_tV2 +vG)ṣْO|viyi ~K ]JuO3J;'tgam|эtC] Lfϒ,Dʇ޶;۵4ŗcߏT} ճɹ {LgvQ > |vɱڞwߦSuKRr y oo..fK8\K U9r.0aڕ2wY;9j z!ES O9۝5N)x ^By??LD-Y* ( G> .2'wX{vTB<n Z H _lc{hvg%kOqb J='vlH_WioJDo6VW[z<9Ipo pe* -+6+47Fv|)Y$x\lD"4 -jwAM(T1k$]l6Lz+Y @|:(W.u-%ZCEd!hX7S\1 EEoDp=8}9yr=<) ~ rg E*d=YIRtKK;cJ3'yCB1>p4g2jx[c*/xRYw#\S:GX;+:f^be-V{ ~ ej=c>y'cEAi8 wc%ߴ׶:F۾!FVO&$I hFD+һ^0\<bJ#&t(,{սu'cl΃O0LH1x : ([ hW%M¯. =Jf4vhĵeߴP#, -B-y Cn{֕ ж, 0.Ų%ɍ|" CF(-9 @=KƠ͍Ƌ'y $((%Ѐɑ38 ߦݚknٟYsu 6Χ#ntJẅ&۴p&s9Z(=UY4 S~"Pɣ;eV X1 %߯.I Hs% \~d˪+ ~K  נfCָ߉r dt V}Y7cܸՏNU7 p U .?fv*#L @CM$h; kq& 5!8FDgT-}V&R4$GdǮݔ,Fټ^ )dبdžD:4EI%TJ*M~_0 @6Zq݄|2.aMqO!V>5lri%(UoaܦHT6b;z؄lj3 'd¡ކ ߗ4(+$X,_C]ۛ{  7Y^}O8nOވ-[\@W̓ sh bVҌ&KOEߐuݐ֧g* xړ!v%)-sI`B$nMZhLިSNO j_asv{qq yڽ_[vM8[D;ӗ"!C$Rګ+jg9E[: }>;!*Zx-Cwث71', '\ګ;O;i3+wHRct.<%xJdqpڨ Mڄ@fU.j) $F^B<n[ܮc5bk,Ysn") 0ޓ?5֝қj &#lt$og._ iZ5rP}w0#ʔP`2X77!'L^9ӱmir_eval-0.8.2/tests/data/separation/ref05/000077500000000000000000000000001475740344600204765ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/separation/ref05/0.wav000066400000000000000000000372541475740344600213670ustar00rootroot00000000000000RIFF>WAVEfmt @>data> Gp /~] `=*NbLn0E OJ hRWvpy;%V[-_ 0mEfJ ^ ~$Yb!j_,K,s: < , ( i# $TPOlo@aG # = t Bu^ScB}pQe'l|-(6b  n U dz/T)10o?(\ ;   M;@:[5 q0kL3  uj9}MV 'd] F (/a ^o'~ 2a IT("~%2j B k'_  L'ݼ@ Y "o#t ^OqO  hCȍ֐߇ *$A*++(jgIW  |Í HvE!+/22 + hk\* [ mE>¥ʋ2(/5a9%5'Ck?>ߥ _.C| hqDž4(w!}*199/Itv  /-(؝, )175*h 9Cz EL׼ՓQ]$,3/$bCyFU.wsߓܙܟR ,#*'!|1~g`Bm[PBJhh c7_Yn<bd=~:K`4.>sMB g J34tb489ds %| JbX }N,UeO[ ?0;%~$xj+KHJ 0SVHB)+!S -=t{|Ua0MW`Uq>!I(70xmjgD" {vhM0KP@(=#_< vZgPw$ ue]VE)1\-W4 9cKjHYRQ/HUX\~`hHDEwt$1,O==[ U(3[R`;&~fG&'v)^UUY'j 9[pgQ!qPn*] PFcHD258nT0lkJP+;=6X=|?3K]u1:J;1$ d,YB8n64@9<BI&0\RJn__n%4"W{5+Lh lBW"zX2KnLR-Gy DzN_5@zGmc)" o -VBe!qmpJ^GVh?S up#2[4iT;ubZA N< ._XK%4'c Zzu"c1^rBhi\03 pHPTZ/ R r w7!h[Mv1U޷ܩY^&0}5,*p< QW}[> n-ˡ mΤׂs"%1=B9<' EsUUJ:^3du6, .W QG4_jUU"; ܗǖݽß -!0d>JOM@*ڔ3< R!5^ FȻU!ƅY&6qCNM;'&z&͔ճB ! 10ύ¿=T+8JFNqI6F J5̗W:)̼Ѿq͐&T+9SGRNFG3 ҋcϋ8mh׾ϒ ,:GN&Dy1} Mٰ̈́j?FS ߙ5ÊiVN "_*:!HKA/  ϔ@v ݧM:ȶV)o7EH#>a. QyֺGܯdWHފ+ٰ,&56CFe<-W3 hVՓaݜ3- Z xH iu͋ؕ 0?C: . x9hpf T *k.qP[ѳe}%@+%9X>8,7 _ܢ@y pLlץ2&T#x085-" y'h$E MۈoA@ $/J2j-%kgN[UbM%߇` (+'!*j=a*JcS k!%s# 1E hY2U/%D>:-J  Qv'v 4LX [C\ L K ^ mjrxHz7j)Cx=c}{Y  ;M+>X|YabQ1 @ # )NGm2+9[z [d *   ?nq4 LHAi}KtQn6Ak`TO,_*,Y'OCoG<a2'nWC2n03@kba&TRrC:+r-h(v|W;d]\_^Iz3Yh1{w`JM{tDVM+%7:FbU\4f`V JK(l\~l2n|lDNW2 |;KUEms!F?H<#&8bw}<,QS`Was <=HNA'[a#4_(9ABQJB9$! !3Ke)J\ev|x|}mcY=61oaYHEE:2)! #"#"#.5?GQdt#)2;CEHX][\[\\[^VKID=8:8.%w{lheUXRED>744434+'-*,+*dbnL.#<կTLn"),m*$?wO{)>[e:MX0JsvihfyXN(,j,)v\ &MTVWG7X:)7hsyWߪuS ,5"&+(*% =R+"5z/;Dhpy  %((%# lC9<5K>cK!Ed=F^ :vE%"%&"3 bX(ry2WBcQG /}[ %("Dn}s1'J?Y?$<'&'"z /2j Em6HaIu2 >;@#@(&$"@* nXxA'Q,Qm9 odۿ tD ')'&>#A\o_TRI>.]*<(),%2 I:w\#BO&,p|ib~frOe'r)*-( Rc 0XYN]ZJ)ܰ $'.6/ ,&  J? [kpBeMX e,!&-;01.V*[$gJTbk=eM-u@z ߬޸H"b("+r/9-b,' gu 8DH`EPdJ?W(,.,)"KycV>08r9@(!_(+,N+%p ?zq'0+Eiv7#x "C'*+(8$ }r  { @ށy\8Km&S@ajg Fq!%(Z*'#ut W,(ިޔn?z\psdCnH=#A&|(%! PVQ~o2v3Nx: S+ h#%$!4z߆]L<,zP v1V!Y" \ 6Th $^6"9YJM  U(# J!& O4\a vNKF tbI: .3&-off( ? t9=u *)Vhix%riv`vY6RLq f S 6gSjKRP9B %  hJ&0UD^ e\%[0(HH sZAt #\V}csjGC[ [O#P8// f"+{oc`$OBf'IW8  b7f+0 UWHW8:iZg?" `J^ #vZuJ=g1[{t,!!!h / J{^>W^NK4$ڌ$ \ E$''o'!s xR9'23;A.a|۰ #$$% 8! !+pQ? Kئ&si$((;%!MSJ6F2A((yi .d=x+ڂt'(($ ^]<4k;S"ӳHa 4+-)r%^tcBDkR:2U άv3 04$ 7 h `{Wk7Xr[s(BO+{ +!,4%A c S&[/T6:ގ<1mV!t2,'DP +  )^v{wRt}Ye6MŹƱe\-4+&9   4 M>'n6g& &')?`VvFy}Z!c9< @ӡa8( Zs,(>"n5#RҺlO q@A .(7*F}ƺ  !xO }m6L%+]pn༨d ! %l- hD6h fz+s/1);  T''c TfWohBxʯ^ g K ey+) Hr @-Rm yܥʈ̭  z")$d b@RRkMltq+Տc@QX 8 Hc&+D#34YZ;2s'4r΀\ S!/*[&Dp [{;\X:A{+8$R{t͑1M e'(ryCaHqiMWz*! xcE{$&L} E1{=l |]^ :Л0wW#>& \ t &T~PڢѪ՝p" #0 } :f|LQPdյYR ] e ;"M WPA,F1IL{=YRB) 6, 7[Gex;v.37 2{J C#&w$5mQjޚS"_0%wr >&(v3_$} ۮ8]+ F+H |A1;go:62qC ] aZ\dT6?Ub ^u|pAVOc 3dP E]Zu6Bik !0pi >9NwJO>Xz_Lm vcCD 8%M[anHDbU1G*)lYS9z"{%v,x-T6N\Q[E8Lwv{_R4}9 (a] 9  Oy~D<$WAVEfmt @>data>y{klMe 7#obDJnU@ESJ` {d'D zTBWE-1Pb1aY#nU!3fIUB8t8:k? i+^]_c @LA&v8R G|BjOyK1QS; AqOrn<X)|`"f7m8eY~U?QX 8{~y27PQTKqpoOE$E7db!cbI6JR$Ae0*DH:3E% 9b]fQ2 :gFC>{b |/. ?LfVt*P%B-DF;'u4`$v G X dIq me|  t rHhq|oש" "> u6 n _ VW4xxXt5$}A @} S"y; i=o(iP E#د,1 H6 $f}gҨ!z"] ,h N,\@| ="r t$ W A $&2Z83P!,| @H6 x  q} l߶Zӵ߼ %&?9 }+< #Α؃^]O"%  ?q+ 0 m5h6$,#8EFo  ( FQA\܂8$#~ J (4$ ZX1pIq %'B 2d  ` l1'#t %n 4S:IODκIP $hNu10%'D@$L]n#(!e)zy@~+t RGՉc:dM{- x%GE:߿tN 3/ *KX)XB{np  Bi=c>9eq*=&{|ݐXAh% %Aui;jR. TQ"!wlM 4@$c t QS/& # /Gfq1+ 1Y/A[HC5XV 1Mc v(-dO0U?tve^1mqd*X B QguVj\MIJg|w R @ <MZAz~ 0Y,b/)oLRT^x[#G !h/n" %]y6^`a| <H )Hd+TU3tT"?Eji@ zKRP/ G ZBmh ++ha }N4^I *$. ;n#)E<8: kN{]P% }T82 \Od%_^E .VI0d/ W:FV $-/9GWJJoflT@Rp;XG3d\{]  KY2md%P3{QRA 2+*8sOrla~7/f xihx:0B+R)]]9W-$9<(pbfTCD7+,,+/1:KUdx!07?DJOU[XZ``cdgpw{z}ytni`YRID?5) !*-,49>DJOMNVZYYYYYYYXZVNNNNNNNFB<594,-$!   "!! $-,,-+14-+07878777878643-+-,$ " "  !" " $,,,,,,,,,,,,,,,,-) !"        "5|* f"vUOwIt$ Pk a|F 8(*b'>W) B^`gH+:6tyI U|0i' yIbj|(qo1<=Ma69n]J7!F+J3p*y,4AlrB@ 3Cs`B/{|$BNx6 OYGW|6f0'3*G:ey~d8!E r! q; #q=+D)wp|o}Ut5{PI0AhHbe$o:B7$O #da.QB ^\s$DvhP-V]qA?P7""T&E4][/(=51'e&Hd*}B-*C)Yg{:Wjhe[O#D+Lm57N-My3ux7y.xS,3pv`B<{(] ?0e1  @h?YOei" {X E"7Kaq<9~] B{xb j}MIX>!J2qglfCe>b!K>V BTD?Sg>GMNCxGJ3 F[bi@fAR7% 1O>51/* /&3B d}[V_< .0 LO>5.5!  # gg/Z SM~|)hp"\dNA~[LIaK @7XX 1IQ*)B.#}h{``X L8I(NAM %ju5(^jt]XtGr> 6nbW8OQY6qH=!^tMPqgsLf^}P^zkg,&>c Is) f . L`c[><0Gw*/< w . ]^ oAgXeK 9*u D< 'ju>t*b8B#G\T\Q<TQ JIGLj..F~ޕhFH:I /hVsߋ3L ?/F(8WD&`W+. kaB28' \F}^K!"M~d 0TSoAg:z"#e  *E=_6Dev$-6B:t5&$$!-1A XCw (A{=ߊ %$Ml &Ay[u"z|.%%B }k  T}eD*eE(""'$<  TT fI/^#(՞A>+%M%` ,&it=%_~r֯՚ !$> X o=*}aaF6γ#%IFJ *Y `rHAeM92 [mϏ=(5& a >@~Y Z u3{yuRaA/|0 *R)do_J- D n@p%ioHnTbNy_EnCݧj<SCC)I,x  }{P9~R`P 0 7'urh} o 2:g<9 :J"X,7@I&8ZqEl2W43220z4h(\oH=5d_!/+ 0JFY F{| #Kh|y\A..CVdpw{}}k_]cp{~~zsnqle[?(   !)-//47;BFMNMNMNNNNNNMOKBC?77870+-,,-) "    "(.+-,,,$&'!!!"%,,/0+--$ $.<B<;9688-  (177?DAD?84,%     44 #56!'57*   !!!'0),!CR*^q2z@uQ+:>(Fo#+]IYg) (EB e &[?K["E&j7dfDG t ^-B's~)fCa@p$79%M+M`[b]G|z?n0WcX]cGr8%ZY$#)Cy3&<}Q::(T.x> '@,^H<#!`o5^.F,PYe}[}(Oe"_bA,=+e\D;+`&!X% ( 3  ~};3US?#..  # 04*Z/vgpn:9%epp |~VQjF 4 ~@gn0w<7X&i.:6bo4Bp-ijPh{GjFC"W".Tf>K--}=V[8=Xtn6/H$h j!#)' D~l? 6G=pb%q\;:6g'*TY 9^{W7lyr uXMm PkZUH#4 mOfHKi]tnr;`4=YAXD+=!SCpp*,`#  5406.7!/2.ET0#2$1.%)'7   $+,! 2H<?$ 9>wsFK,LJ .B++$8/  %# '*CN6JJWZ5MB7IUXF@HI3=D1-/0(*#  !&%)$'+5 $#"'$                 !  &$     +'6 $( 94    5"   6: Be"I?h2 L "&04! 006 $! B]3BWY,A:V?P Kg" ?SC Y8   0X@i Z}q 0Yg\% ;rT[KKPE;cnh2}9 d >&SkJ O~46h2x !T_FMym >UrXS01i G ?0w8J9`yWVGi LA `~$8c\< n2cO>(U5 .\y e.[ s.h&gIVo aR$9d-o/ 4x-   N f> `uU|B:'O2 G ~# 5 {qb.%7n#e{Yx' u VJ + <gkuHN wxw(;vPQd|D 7g   rn M%#5 r#[,!g) QqN#Fd mA) y hf T4KZ z HA+YkR:~=]sC (  mir_eval-0.8.2/tests/data/separation/ref05/2.wav000066400000000000000000000372541475740344600213710ustar00rootroot00000000000000RIFF>WAVEfmt @>data>}r~||XK[zP xFQ;fZ=  6>GVq QR~ZD2ll1EH5rX/2n1++IQe1$FS\)H~G.zjM|z1tNq\ Rw@cn=J4Mqy@f]|V~}K[PRN>[g4iS; Te[He*LlZ /^8 ,  BG PQe F ##"!xg ~wG"ϐƆ!  )(/155.#!\ = }  zݮ&˭vQ֯Im(:h52>y1p% h؆)fOY76.!+6.,! J RjBvώ&g*Iڰ (43//C4*!lr  i \RELڹ)S΢n!,31N/-&'he ^  j  7$̦5 `"k+/10.)!a* Dc4 LЕˊ&ʩKw>$%u*.,(% a   )=5 ?c!4"p!D );&p0Xܞg1]; PAC2  m-YWR2sC҉T"9O ^#%U%#0!BiuZ+;  &:x4.'!md}8 a5q ׷ܱ 14]} <] h|)5>FHEtA:T4F. '!sZ (d(TmCyȵ¼7ƺp )4~=]C.Dn@;6V1+6$J tFz,ZqLC R(05>EEA`<[6J0*#q yl,bQ^Ӏe &)5]=CEC(?k93g-&&vc5 y5Hcd$j62ĩ[N'$471+$t* 7ެ`g{f|ZхZ<&3 v{Ͷ-7&=AZA`=891*&X< TQ :qqSzpx}zd-85:8::6F,"L S>: e#LIPm ~)%)(M&-431-$ &Q Fe;SyŐ͸<څz r%#P%/?5/1%tp_  \ 3 \`D3࿤ f>R `#+L.)H&",c# v/x9Ti 9ĴԳ~W  z,52m*" ^ }. 9UQÄЄj¼ԬwI0h D)T1O1?/&0u b>sČCavq &*i,-1,?+ SZ EQ(ɁQ #8Tb ^#" &,-(!&) g+(܎=ϫҀoӜ:YYo '*('*&j b5I=ΥLʏX(FlI0D5 j&((0 /@%? ek 49%,ϓHf:ٞ+ \"# '-+(%"+r  uFԝ LS T_g (-,K)&P&jU '6 P?Wґ;X`> r0tj%+I-)('*$K F?;  iدӵԫҊ%y )h%+*)(3'yQ evHK؅EH:-F?|Aq^q"&%#n%(Z <B JNל SʥƱ CiZM i&d)%P$#U <_X Va}QQ ȸ+ `!k'**w):(Y'@%!. eO_1K_q 7f˃؉ } ),++)w"?;d P:xQמӁ\ʉ/t |. $&z*&,Z'l!;J r {ܒ֤4҄Wh= !:%&%ia3u 5sݬ$ x ^ o( J>h*H 2]F; 5A-f.  ?}_Ay2J#iy ; 0vlD@_Jz#2(Nz&NQ&">p:p13m1\#yF!i&Is G5WL2IsObMU"O(Y|a:x E   4W8fxS bA#I3S :( C @ V T`>zE!!P|b0 e <Y&`\26Y".cH p\9/{ v[o/%t@9-M~E'<[| $g53.$&pcT Y;\v+c7rO*8.>!ipzdU@L:|@4o&/_OO{DCD-SQd"7^Wu `Dzb;u6Y'`\t e:vWSz7qkNwhvovQ5VK8PaZ{PyhR%*'m{kC>@W\k^)2*LPQg2t&Gbdo'4n: J+2esgCfU}iW_@( 1       !0-4?9>CBGA;<;ISMVecddVNPQK;-&(((((''(' '(5?:>6'')""*%.<<;<;<<<<<;<;<<-'(  ()%/66<=,(0*&)(*!(775<KL;:?47=-'#!"(('7<=CMK:=DLQA;745,'  #ggU&P/" Y?%)9;mD/o0:%B@:7lVcK]? Vs m 'hhZ.PIV\D(D g ?zixZ^'*{|SLrzzBoM Y<8p ~H < 9}qfrW^9dp8)@u f'1 ,$ %zb4 CO!(:*) knk "D== [J & w@RrP !NoY|",G2^fdI n8Ru{P]@TfeS%02)^-65#t_`2G``D=D :B"r9'.7] Y.l!)EqMr 5 V .#_AD_CX so0' x! TI$A3m? aR}.,XFKz<!Y7 )( b lH Kl^V>j  ,8rlX * t 9 U `4PvL Xxe. OY X 7 W 9 pR m" xJ-yf@F_;Io2t[g1fw}|9tlzCkY *M3f;#xi3H)r\f./-| 4  S Ga[&| [gJ j}7C|O>JY 5# Z i%.H'Wd[dd"a<;ey @cCbkq-9Aq'LN'aL0DJrxb-aZ_ZujR#mu9F$[GI:[@Z ldoGAC)v$N97R,L uf}pW7/; !; ~R4e8Xu!*yP)| "S_VO\z}l|nkhitW962>>)%*42"(..&6AHJ;<;AQPPX`bkrdbf^YY_edVMWVNPPPOPOD3)' "-<JBIQHK[[R[]d^UdedbkwpuzxjbeUPJ=4+    #*&')&*% %)51,9;AQPO_dhyxuzxxwzqXUSO>.) } *6.,776<=9BPPPPPPA:<2../,(%.<;>5,=;<<-42  ")'('('(("" &%%"$(   "$1('(('%/66.4>;;LL9ARNQP@JM:;>5(&*!!"';RPNWbku|}vyibedVMSGCI?205)&)&*! #(,<GD>BMOP^fccfbi}}~xzvzwkRPQ@=(#'.83DJ;;<=6)  /<:KRJ`!.=<;>+6LFVQGS??ROOQOPQJJQPOPPA;;3;/#,"  #'.;>C>:=;=;<<-4?9=HKH=:>:<JC9=;<<<<<<.%6BB7 ! %/66==9D?AQNTGFE5N1G>4;?A2&#$ '7;Ogcdq|~zvzrcddddddddcf]PNQPA;7(""*&(5>;<=:AQPO^fcdrywxxxwzrddVNQORI=5*!  )D"2>iu^R~e\S&<e<HQe|Oo_D#&4K\' $bryZ/"yG~+ (^w.>l\V+}eGl=#Ykhm5Z}SF 4b% %ix~p"?Hvk95}^9Pa"jznwf`+\"X-DJx-^]\NG/%S7`2'-9QYy.vR\=zuo||3*-)lKFtRASPMJ3J*F+C]hu\E HHv,=@xw} 4g~^;>YjKo) 8`I;8 [@2s~`4O*kc_%/C5Q} %!| jocQ,9L<)>B:RN'g>]f.'?-a  {7 X  IUWm(Zll CZ& e{8U]> `HcXMp"'zKo j $!A;~h}/ D }%l %@'g#O _0y3L W'B)#*$p =,Z1D{gn bH7#X*Q.-f'$ qI[V) Qg%/Q22+ \{X7PYj[?}{$-v56.#Hj n? T_YJ۸kC#,}78\/"&{ )h" d)ea!,9:2i*y z/H(`Hޯ [#+9:b4J.&"NIX-܁i g(7: 73&i @| 7 %e@];R#39!84+>:aecc6u0_78r7f.6vIK iۏ  %*`4I8~823&-| \JUDrݒc/4#068,6-T*R$ ޹\ܪ.'4Y+U56H61$0}snP-qLf/vL#.v3Z683)C^Q@AYfw$1xܛ f/ J(H06X4/&`,Q WQߥ'MS|+23+2',"-+d')WLF܉D"V+13/{)&! u$Gu12y94{P jC$9-13.0(  bEZjtݎ[9 `$A-2/p,>&^  KD;TT,5ܨ5 9U 2#++i/-*$5 q9]SGNoۙ܉T, !F*g.O-+$}&k %= %I1ߋܫ W J < (/.,^+%g&sl]VA$P+*;)&> z K]q^26:c q&T)'='  MhDREXdYT!'&'?$F M(]ABio_i"#C# ^{I3: Ee2  0Y) o=~&g*_Sgs YhH MBy"AwWVx/ hR:]L Z p^[OFA3c$PZ` ^ s B R ust;=6'WSC E #7,#sgekD E<9[B}ZUv>a720q.>J?I`0U+7?qg<~&_t@$hV:%:4~IfYVJR_q>^xx]A,!7>CKQOQPA;* rhXLMJS_ez&.;JV[cr{~wxxysccf_XQA;9  *5>;<<;3,')1')/.<;=;.403>;;<JQP\`YXah\O__UVOPL:.'"*'((((((')&.<;=6'&*!   ')&(5>;;<;<=,'(  ;J!9W_w\@uXMF0k&Sin % ))15F6;+rmRY<_LD^0&r@?:St^7_/{AsegVkdi( J*&f4^0e/h4@:~mir_eval-0.8.2/tests/data/separation/ref06/000077500000000000000000000000001475740344600204775ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/separation/ref06/0.wav000066400000000000000000001750541475740344600213710ustar00rootroot00000000000000RIFF$WAVEfmt >datajJ0 UNo<+;-Q PVBtKF%*>.2@ DC{&AT\jPRj:x&QibpwghXPVx&hj~Vb!G5Vpb^-]1 n.UTtE_J$&nj+ ,Z@v1:a{>^>5[Jv3{eM1mcOBr4NCM)~\z2BI[r6<bjp.RkLflzP$ng n';RZVf6 8 fjKX-N*>"x )4H&tbMN(QNeB9e'e.+ j'QK2y+ w~D@"HpvOv?$I*jFXjN+ij$V R+ZmC*Qb@@2vryl/zwUT'V^N^?ZWUHm^Tm1P..J<f~ D"Zi~;: &:g'/sfU-$z.!2d R~7 FXlA>I=@Y{>f ;.6>dn6vj6WnMAZHyE*F=b:m-`f  m,m@z{.2'.b, N;?2>8">@bs m: ~YMrKD<{ 7186t9Nd.3sEig>)VBR>Ft*O^Y_NjR mO(*>^ti9}2xrtxO%m3fWaVt+rvR6 5h*]&B}f&~3z?()8^ |2VE#:u(^I:]Jf2)sKm\+- ;V%S)Ul>CE :Q2)kiw$,O)\\JxHyv_EvnrX~8"[-W`(J!0H2n  "fX9q zzJ q9VI N~rVM~z;ay';B:t16tP=z,(^^jSO}t>EO rBDr!TyhFVm^J6#jBBxca:^  nU&B<~Rj`,Bw%>8+i :^j~G RHa(}m2(q~A@d)b>rFVJKZvNOq"=cnDG.in*[x~ T581A>d}7(8{F#<6Et(9V=hN&VW#N'.>wFas7)Vo~K ]1Y}nS%WBy4^Dg\-jrD bS lGBknxvHaU?3R ['PR.,: [EOhJ*XDLBJ #wmGonj|0su9>Us?psS2Z.n A<R<,R".,OfR[`~$..sFQ?.w<&FT,=ZmB [x-.(*nz[ xr"4v"q)mb:8`r"Rz<#os~JU (&S.Kxrr=LR^J\uPo" |:Bh<AeE!1(;O?@ ZJ?NNh'`v$tpIG7Vh{V879l"h"{\n>Be2A. \699CxZ>.L c1q:h^B} =)DuM N1`[(Su8WN7>vv1-ft|pxzAuw?fh_I[XvwkZG/u$5^*BNv7@7N gh^7B"R-Cee^j_H#V49CL Rh MfG&Bf^,&!4~RRzp,04xV&l?iK5N&E'EJ}HGzK^L~Z"RGn3XQKBT]PBy{Yi:s36BN4H^% LyJMeUmXjWvF2I:Zn4zRB<q.rmfdo4MorlR})5n>&w^#a->GoI~fYAvY x_I 6odLBAl^6Tvc)PFxSlBge@lj"&sOBR 6ufcLP:f:R<qR&Nc&.fLqW6JIB>!S:}JYg`b:B2"1G,b*w1!>njd9vd~ JeuUX"/lFpIH?D4 jAbDt@vz/&S\*PC|>swYzS$ZJC P.~&w:CF kfHc#}Zvo-_pGc 'XgzrIRJ~Qqy[0 bQ*i^C/6ip}P+t/Gv%["ccl9W=o9" rZiyJNI12wz ;Z<I^ 1$Kz ?2pkDc7AfZ/Qbz2`=Jz9+"q~~?gb!roB{ln~k\B2:b IPJZd*XXUgvTzWg*2H6h=cf`v82D: f}m>+#wti edg~Fheb YV'!'zW_.rw:>J4B.pS$A'2ud6>YNij,j:Q/ GJDz0C4SN [q27@#,rrf9+q,GtV1r=N; vB-~mqHZf."zJa-*Q7VHaWp}?wDKSRL|>|_tv]Z{<4 =g;cnct^R*&NOAo>&wY^d):\J]gK6WQTwt@bE1342,m~r5P^mz_EN6{zXP+iVzH-z61Ff2:E)Yi5xZeurju;2tC@ w*s@]!4Ow$8!p P]8wqfyl Q%`|6J4 >Pvv#NrJB,)lbU JY,vooq|dc3-`8om?b,lU ]n=-co!(IfMm >f;d{*h*wwJ{jIeV>Z<neAQ~:@0yi(BZG%_O6#z ac,==Z"ezJ0RSKAW4>0:0lT e*>A(f*JXx}^,OG&Iv 3N 4'B?-8w j`qN0`$A*F#d1BF*-ZWr1ftGe&!,o#v`1TxDw-gd^?N:[Jq)K (KR2I)X#RZno,-"W.B6tJB3jRO" \WZfF(1P&mr ,zL_9 G@\?k_tR^[;^mb&i@:/aA/a\h oh@aT=TL.4ff- vjtyZ&*$' oLjlt6.M^(?r;g3>urKZ&IV. h+G0% }*0nE6M!LLsOa]NbF.z3K$68$.A 5ww~i~&`6GWz@eyq&MEu%UOK*Db]lKjnfZvx5zjgvSo6pfkhZ6f5DU d c+)U|Vsc~/fyoA]E%B]{f.?+VE\tJvBCR6 Bq> a^:AZ$K[|=Z(8K)43NTu*.OD|x6'&BC) Mm[2Xt8xbJtdVk jcw-Xr"YT  J 2`~Rf&:n2DOS0 nb3HnlY&2Z&2v*cn2?M}%d jt]}/iK$^^/N1> j,g&>iU9E_?|~iG,J,)cipd":AWL1~ P"spo3Tk6M}(V q\6uuwv`F)p9|ul"VC86E2JB)xxFm ^rW5X~u )#mh[zNR3RF$s-^Dm'rvg5qQ1ur1bZ?d44HJqg>xb:O9_nU90''&?N;OVfw6"C} [lY6Qf'v-q^  7'Jg*4d>dN! -FM_.sZp3kb8G6a^hCS2O typ_gF,rtXrAPNW~>RH<~FUrFfe2g")6C?*-nVRv RV* M <k?Z :m<>@?4\Ma'P[vD;?W^{+p6M.Lz/:6(lJ@*KN*TLj Iw p[p'*GXhr;h  n:b F)RB ZEr; ik j/*fBnjdcr2LRV@D2~iJw6m-Oxf)=j=*sbCF^G*OXyD*?^~>Tq9f(V "WqcL^^7~}xC(pRv.Zdl\(O~"\ 2Bx!_\r&~grq iV<TDN$VuVjfRe^Bh@R>VBE<Fx'6(f$^Pyd~Ob)Bz 4l[$>:-Nr&!`*:BV-= OC<G]-0iB f[!GU 6co1Mncz6]J n* :"W _Jw`fZWTLjV({PJaYIUT2>.1.JlRY>*A]KXhn>~ vdPsPT&HbMz4l&&.Tpuc#A ,,I?*2o5A5^"^ w^uTVc11n . &&)@.n3nr+b f=XL sN [" 6ddpW.AY<WVFCs'LUEUkEW$Br" .6bD=!)hU);+J&D+:tJnZ.JmLZC>Z\wC;b(\yr VhB>Z'Bp:t:|Uu|vbl& _("K7E=6;YW+ZB FCtby S?m}&xC "CgNR,r"FD*A0Y~o\j:X>%"N.\&4fiIUC!j[Vz4 *R&JVv0}:REfJd e){N P& 6{5^v*Fkr;H+~SMQ0XjLj!P;F gbNl(('' VNxHjd|m.zdf8:fMaVaL#Oq!}:KI-dFRykb92cts)j=S y< j^`vXCusjp!_!}t6Rx{xG9o~GsQ|r")MNbsAgj9D kB !*&~/+WBN~L@>s:nfee%.BnnA0?]^=3 Rw:qV"BLNy 'VRoO"lto6M%o^cdY0 D`N*a;3&iG|eJR9f@7Y2Mt6#b<*(K"5k #?  n2E! 2"AFmp\nC {ZH^?,."@EHR,u)nTEz"5mVer+]r6&Iv8 ;|N.dVJP ~ v)YrGqZc^<3C'Zj_}c6Xxf@Fp<;h z TX"79tD\x7i+R*1#8IKC2i1N9Qhx2^bf YdRgMnY_H1uZr2,-F[HT>rzy[VtEi.>D]]QS2"e] SzvDa iOZX}QRrV&V&!w>*OljJv ..G !G^[kH#Bxi;V{-<d3 .@ r*4VrrIDFCh%2x*@{zu`2"<#B4/\ i4n9\H6YP^P^^)P[O7mwv Z3VK/&[*~$.Rq(\ D:DJkY?ZU&q{6-P_g1c5j/,>"v)s/F]8R>@R"H@C=cpa/Fq"Krr(D%7TDjw#f5fd7i:Z:V7*of[t@r9+X*nrg4{HS,&,P)fqM-R8 )0jNf]u4JD{oVA_=9&NX$d::s#onH A "ZM.sxTu(OpVci&ONBx}sZ6)N@2V_a@J}\ZH *Zl2YB-zv^ Z* R,9n5bK8Ebn~jpZffV|zp~NzVNK[f.x&m@;`Fv#:"af,:5"u>N%2J $[ba}B(=$&C>miZ2m[r~P3@\tz*^TGs_za{_)"CoTSR4(6\6Xo&ei&R1L1D>kNJV F|@fl4uxD ~Qdhm.|B6bsR&cMGQert>[ M|:Spnnw%"H|=ZvfZFZ;Cr2CnrWm."z@aA59 ~Ao0Gf)8FRjR_0KNnjOG)8Jv2#eu^jFsnbozMaKKlwsF+Tj';lSv2KVCpyB+r_'A:zDL[YzAZ6*Nz&bBf7wJkpvJ K?z 4aP.=13^Z awgJurb 8:-Z |wq]cBF<5 A)([^SV2,"!uRf}<' O}f qcv:6yfvfN:$?qcEdn*[Zi)W6jBQNn~aX;f&q.U&!cGY7(J"!M N5nzHE Dq,9\4 "rVc}}b>Ev K^P%>z#,>@.Y4BXvyZ"Q !R!&sqJlnA @M&LJ!~$x6^  KlZrG~[d.J/ZL )3:~UKvbn-)=s6^w 596 ]-Z2P:O>:STq&zt~bORLx/eEjUS;>#q8' rVon :QnVAGZ xsF&[ h|\`rh t3jnh|k#>-Ya7=*ve'^"ZOPBrf^H K:Z B:R* jkaf$BC@E6vO F5q5`KihV"5Cln|n`n*V8_`.N[rV ?.6Y?zRK:IZc>l@oHB5yZ.jX"}wZ2rZ$7WgEx>sxR^Pp&uVUqB=v)/) lNXZGn0j g[F.*!S#' [Bc^d7b.m+tF:'1,V:BhZ)SWLAVVW^~cWvVd2%%7f?]fE(< (kr ^yBK2XMB-@j.2'_rtnX:5Vsf:K3?Ff*?7u.7>:Kw/tOjS0D S&5x~w*NV>zF2&pnmN"dO`H=3 icVP~2&2y 0 is;aQb{Y:}y"*>&IN}Z1.YBkw h z`  V\)b8oVYxuDgc <+^{9;X DRKz 5jkf,/vW"KU!H_b4.DOWqF/VRrzbZO /6J@:!+*V"l,oL^O"1!yZz[ ]:i%r6 [&[b"6Kx8Th0( > |).z*}Gv?~> -ef`i%e xc=~6zmz^Fn(0fP--VgR\CZQ2*2\TZfr+~^fJpo'T&6>6Noz/fFFZV,NU&tFqgV*,b)S:ZfJ*TG rNa fE !? SIC,2 ~-ad*nz>zj~R00Vc> vK"Fa0nSVC5Z^~r ;EbdrfPqH*9|:>?VDM^-r xL^ )L@JRv:[k6xDZb ZFS.$ :ER)\Qf.Y:r\bsP: qd:JsRQ^q  euH yb/f &2d#FB8ox:WNA22 *<N~CM{ME-` 2of*f0K[;6@#2J V]7;=zGN.3b?6Ckp3%'}p*5ph0rE 5@BdYLtY u~CrwnF<6n n>%fF:J=l.$)M9r<VnjZ6'B=sh\bdg^:SJGz17-[^jda~fBH+YXBf-~x [ Mb$ !h3j2hK1F/6T; ~<  %pF7doz.t.F&8 T V2*I:6<W1"j~Ja(X>PS2>]"IzRr4zOl$_ zHA}9JbY*ai+SdUR"z< pdg{ i$SbJ6&g b;|<\[S b{__Vd*SED" Z?vnn(skn&2K2'nER.H~qX.Jvd 7W`f"8d\y.'~B&! cR2S*HxdhA((^^uo~iZi T&E4m6j3h?:~3G@8@@ ]+b#gVF,F!i8,u&X MOM\i`LN1OjrZf2Vx~aZR&QjctC(C/.Fr:$g!h4~aOUn'wJOl n4xF^),]~L 1Aw KN);XX8V2t*.Euu5 m7]FvLtBbr zwz6a^)bGvh 44e:[iJ[H+)Z=%&(pzUYkoF;jN 8)hH9&Q b"Mt~PZ:/A=q{* @N]jmjW8>*DOwu?knNI*F1wgNeVN@,Ac42 cB/#rf?c_(&<&p&l;RVy Z`f8&|#b&bg 0Cb9Q{rf1'|~PF6`fG>FN1vB=dgBJw\uk]+)nz+f2}$5)KEu=P]r?jTighG6bRnM+|,Y_\bNE<zv`:&}``Lr: %fD68V{X&>i AfAJ *boqZW<J26njC^</N$lSBSx,&azl6v+:"&vh:J VI\qfo*^'NUj@D-5IBBJR/9U>7N7ao@E")f.:KhRQPYL"t+v~j~N(ol0P6ui-0FfA^ %GSJH $nOE%"/C^% +L%SUQ9)0@I^fMGE=g^:L>R>+6*)$+B|D 3; f R:jE a 6 pr#w,+f83"b |@Gb"j6>."_ ? y.$$&dEZ">x (E7n>\:  F"~{Wl@`=X@Q3528n)z7+Ena*FNan"36=^\"bXNs:|O6IPSn}r "vd?2+^WH2Fz;Z"4$_^ZA5BkheyWJu X 0&?rJo`f]'Owar>NV&g ,Jm]xG^py8(KzmA{es$sbf MjrqiBf m bnOF^o0H\"HG"SN"rB:&NGn#F{*6]2I62,.v-H`YEF >G2>V{Sn0*k^S"xn~,EXR^czo$Y?Tf[\Y :i.B3vO~:M 2T & g> mLR  L X nYGr-to}" v  -  & ^ 1 * & q i :Yj,!^j~.yzA6~ $_n<n9p3G5 CNiL+>)uB^vv):-B/^D t&>&|#zO\2g&:0ZW6tr^yaJ~: L\ LnNF;+~f1viFZi5p n lxWNMVqBI0'7B' FV"X|v?&o^[/`Us z,X1%R #Jzs nO3^vFz^#d4=~7xd!Ub"S7"V3BO7^D_|PtE[tN6BjT"5YiBF bw2HP4/~v_1_Q=v5R>f ubjdteyRk:Sf~bf>:2 z:mNu}>&-c.<~~Fr~a5vFY~jnYn)/ini@P,c-f2ug|?^!.|AC\i"_$!rK&Y9e *zrV })&ufERuB_T6R~H*nOZZ{Wj;/~W2v@/:EadpJ:K1 FriufBr2T<6h?HB-]mJ8yjy&}s C4)fJy/vFm\61=@G,XZqpG2N.VVQF,G K k^Z6mY?3Ff[6FJR4!T6yQ :Nov!:N$6R $4d4,N/s!6zVtH<c>4fT '.~d{ T 8h.'I%co'P:4acs6>); 'BMDlIpQW *~~&B^ B@s=`[p .hQf &&#!`X"RsnUV\ry@GA &&[#f(V?Mn,UR6[Z0fC~]JB&BF:&Su6Irm^u  6U]L%;;~t 0/i;mX6$F*%* ?:M}{iIECMJ:fNb*2f'3jBx:Gdd.~,WIj'{!}pn *~F?j` z_I19 L}~)<+`~4.(.Yo(2>% x;r~K/j_zo~Q&izga<Wz9L2mr. w2dJPQ~viw*Ehr9{Q]3V7Db|>jSnz_ge(K+LYg#k"+G$(zi3.Z wG})C+\*9=/3^xt@FB!n/]b!F6wB2LPgWaqx:y;>J*ZoW4n^X 0*J v"$z~RV:=y^n>EhwdC!~vq/w!\@ir'w*iS:n^>B X@6 rBn2mW<#] >f]kPo"RJ\FaMA^QvftY5vU-=$iVKiSh]E24\"pnT,` ./#J9x>@{]X.N. ~i*MRdK/@6CA*^DM|x21l>-/ v^LF.">>7 /bPa:mFLqr(+( fdRAsfzdLh f 5?j3I;Nh)I2m8w:^J~/K W;nAh{"2phq:vx W: 6+S:Wv`c4$L9~e WXgLzVlC* O"VNroJ;^P2rAzM;3&j5QPb>_1 >~*NV1$w*^ v5qzP7UvTLNiGY 4NrX(XSQ 2:Zmb6#g;bUt -0~@Rym-r gx:3!Oifun.R/5r$"vnZQLB;v[NOSFM>^+2.jEz..JID5C^0x  Z$fFT&&bV^oZoF)O/KF3{KS:Z0 7k._Mn 'Zb R<*5J DZa`:UGKV#>RrFoFd#Na&;Bm Aiz*GMF.[ 2JQQJ  9t}va,0VbN6$ 7BBE=d!%m^&H(a_6>J2I`1 = d_|f ~~+>*06CD Cnt-<~*V _<9_>B&yJMDY/."*l^2O&73dRs#WW 'n-oNA*|A/^ uZDB>RjOTz4eB<3=`a^sJf^`i,vcElVbqu Oz7<OIf| I2.Rif'RSfRXy-|r9f|oFQCR6>`, 3XFN^AyaQj\nbUk~pn;o0P<s% Y>#<U}#T4Vrkkfq/JX~$l o;i] vf0 rY~cvtW}E]_'o0~GVZse+h (x7V3m7 G>0f2aJ r;|E=z u@+6:z`6UR^ a xfWDN_9;M@ATS#}>Kb'JE7>.PIpN2 m %\@wNL:*m V,br'w'9\yXZ"I:R|[g}(G}DBU% !V Lx^)&6JMwy:`5"U"lFnRCi4zC6+1}f 9YVvMH'@H`\&`}S*$ 09m^ > 6H:q2~**f4jLpSd6m%V4YhGBi O~dLrwuFJNJ8:Z.d>(!S_\elV(9T\1Jd='*6jZN\frfA}m //jW1R2  J( T^Ya{zn frEL xUc tBZBRJa#&Da*:.kX a2zNmrBVF\96"4r"mR6h8Q`=`LR4V)?+*)nQaR,L~|}FQ&Z{<3/a#:0@>kWvVu Dc6P>sz^e;,x0.g?Z'.>K+Uj(Y. ~&OJdW ^aFtD?;&fpdf"Yv*TcTCh`o;](#IUw[~YEmZZYO2 }({<VRav~ y] ,JVZZbn&w W0G$noV*9]N:W~B bAN&HPdv4P&Y3[8RM5rzX2W?J<{:R!)``H@KT:*(+>iRkK?:5IcUp~=z<V#x~`[I^N+mxX}Jb{) B$_glp>E6,B :?+8y"i{| =cuD,>~*8*~D2[Ij@_v|ohZb7+q91fK,6^=NmqE;g"'~([I9_-zcmc 6 b?2& N$QF^$r0:&nf|5R"T-RK 3`/[ldwc.fN 9W>&D`j5ZttMjtU~N6C&+AVZY`;< t/8efZ?[$Fy+Nt^'&1v^V}|D84+( @YWn,!,gLM02SbUu66 rqluA%_~:B)#nRXLuqVjyO3-nm(6J-=Ff+PE2jj>aH&e _vS`mI86({^mQ-VN\A; cFjv4rw UG:Vr8V*&%t\J.: j?^' "c*N*9x,RB &)_n^N6>Jb6X.ZnK1 #~57"?CzH'+2HF,^VUJ:>R? ";52*?{:92Z| Fe[;`4{ r.%(2i;r]vbvV~v6VB^O<Cs:Zp@^sH&N]\s>G=(tF2:/>P*X\-m?Vh8 FRt+KfZ. aJuJ;6nl] &dPXh<vc:ZMA{B_C`R[Xxxo^X>CoS*UnH,fJ&fD]t,4gllY!QK5 B~tz6DFt=d~'Xhf*O8q,vP*2B#|BbcBavn0^ H6, t8P@qePgBxnH \Bj0B3NgU'>"O#en WQ)UtP~~Y jk rX^bFE+l[E-6 ^>wjdpGQgaQH={W:HAx6Ihn:cD6s+M}*N8C0bCukrmFs]=X'o.zZi 9036_FqF2o>/N\}4lIIv/ -29p3bS|bhI4H4a3 8B>fnB&y#a4qd/16|rL._}snA>Idj (ch5TdZ R%tAN+22r>*P?ve>_-r3tFzJp2vbV"oVV-[aj0;B}56^46TB:p~2A:l%oBV6|0Y>v &Y02LB2q;n9tR|~Id&,)GoZ] dr0O%'!Vs{*&:r,0#:Jn2#KB^/5}~(Zj3|^% Zbg~| W4{ZH{fer>YN&^J*zw~Id:t f";F;Jb|7H]o~Dmr r &6_Xk]lIbAF2NM;1J"Bjb=> ^FGi=F@sP6p2.VbO=90(f~S2T4BO'> @b:@bbvD*."5fnqk&7bRv8?f?.i#k3IF^S,ffgN*aS7RCa~V&+62j{h3#BRy>35 Jli|.u XJ*fif< r}Dwj]SfI&+fsX,B6rqp}>5~E)@>0X'F%:{]N B"k:bWJykgr)&^@bwnCs>wol:`h&(0Jp'L\lf~52dKzt3+)pKvJl\3S[^GlE~t Cs| (G4ltzB`^|\pX3%/fh9Pj< =_ZRtR~^neijj8e[r_@2OJ22jIC[ja~lJ}V%Y!"^66!lz?VZVNDnJ~dKk\A_)O;d%xNca9FWYu{]. p@2jhN`%wTrKJn #8J;*&&NW7IjC[LFF ~jzv~:CO>):Z&lX>u08j)F mHJv]*6z mJF'96]Br D~6X{x3?8K&%5^;\2"tSQ7wJoB,? fP%hr=1q^`( *O+&w'`cNNvvoNJ"~gH62.|Yuz6_RlE !v/x *Zxre[zn~8tqbJp"f ZH\RPN7zIj7,oY~VB=]|Dc[8Iw3I6.b^b27f*M Ffjv>\J8%mg";1mA}D#G'S +%J)1zc N{u1d>P;Z<8'SG.UVhb\Gu7D**=^E |l4Ys6|x(BHaJub!-_~w :0t@jB&lfNBJ>~cU#t>x5*J=NRFKIH-Z[|^`+2~O~=`j+!bVx!&Tlj&4J: :f2vu,!*w?b.I~ObDn.^3]noj:pBZt]~$Z~  .; Ln%oFWffP:AL<dBq z6Cnn/2FpnI[2dU"h~6 - TBr[H8X2H)l5nB(VX`XX?.Qv3zW>\f*)N5fN3Xo*aoNde!Kd'n t=Ec,rD _b74<~H <8VCIG61XO7:qcZb Sj SKPrt>[-b8"s$*>*p0B^FrF&l#l~ u1F24lxJ|9\W.(Rvf ?_PVM^Sg4-N@t/CuB^aY/]d5\AfNm@QF @ ]Be=:;-]R57@TG 7&C_(j%6E{N._?,nJXBQ-ovX;zM\lRH&6&`m0#2J+>:x}mjVO]oaCp+h7L.`wZR~A$NW NF3A~wR.i~/K{(> ,bG0rHz%hmr1^PR^ :UcZ.z ve&B^f0XJvuqjr I"<2>SgI~.qFNW.0?F^32f[V@&iZ.F*)@s-& G7d9E~R.+?-z=1!INpT kRi vK>lC6.L2 PnpQ^r0F|.xv/CL2r)6 b+VXZfrs]+?<_BXCe&*DUC(H?&2(rngDwaOw6&S?fFvi~1Kr wEOiI@!%Bc^^kv*Pj%qrvr 'G_'I . ;(M G@yr[B`4zV0G}VFDj6n[MAv|3riN0b?;ZV juj. Q dv;4lMczdf"EY,%VchqFczb]tt{LZXGhtWp(%0y`y+$,*gKCq9>2hZwqJVh2y+RWoNxB2*:~'G9mr -5"]P@ vJJF .+801=okRJZ.r:&bE>6=$rB*A0B2w_6 r9 vEhz6%[^UTr5Z&&++wArVLS >.5v8]=/<vzfeMbkAc C f[`&R %nRH0yRV+~^>CKBTb? ~U.yIjrXFnjZZFUmkvj(mj&OdE6U61%E \Bfj~Z{Ef"z[  22SpH=7&i Av4A YnyZ.ibC76$68Bq\5Pz6w]OEWO%(h7g~ rWnF#Yb *{:>v"M:%MRcoik8b\Fyct6N"#::y>vA^) v% 9>de.(O\iyWhd8d !~BBAv&N7nn^XTZ%^+jYhkNn&f6^1Ih*8[qezl8Hpc:b@./]HF2A!I*,.AE3W6 2y~^~ibQr4G>ys6M;YV_>Bbo/A /!FZ gI,+;XFx~O*t ~b{Zz~=f`yJ  :8=vZU.:$'?8*inA*DT|ipF2!:sFj8nD^Xtpe"^ v"NB6]+^y(UL Sd"5~%4C 2n)B'vL*QW=%rI@w.q&qvN4BZN1@ B* fi1kz[ vD}9ru?`mVZf?|'n.T-vO^t1 /Q`FJ8H,^IZ"O"Zc'F{O*g>B4e< Rm{rw>'^0sB1%J{:E;gGf}9h2B~O~zy1"dB`q^k&hn |oG-b `v&t b5^~ZnnF\ z%RZoxr@v`:K5[xR< }`$ !IETt6 ^j >%S!S5`7&L.3]%u?C]sg.bogou }4ZW@XIz2f/gEpgzyre S*B"25BZKZa %&>a"t/*=>%)\<["z$^zbIIsZB`JzPwZ$6CV~pFV66IFifO @#Mzr+c-5QekF^2?zG"_i 4%TuN~U`.an@*bUUR^rB8D& lB"0t :z.aRRmir_eval-0.8.2/tests/data/separation/ref06/1.wav000066400000000000000000001750541475740344600213720ustar00rootroot00000000000000RIFF$WAVEfmt >dataAf1Xxbi*'+&*/) ++9(9&42061/N^Z>VX>U!SA$3S\$mJcS0bc:m8-uU\!ndY}`qgf7q&\b?.e@.! A]}5Pm]._8`%w.AU4WMj d=\_[`ZWQUKU0NG7u}RuqAKhnP$l?0;T_?Ca HaZ8BX$WD) UAqOW  JmT74cW6 .6Y)v/fIEk%fH+^Iy|M'~Q-Z^|ld~5Ma+VB,WW13?@(79<73XW$fNRoYDsoJwx" 6<"-:(?}+g<JkVV}rd_s+bPtv[z%o]1)+#*#;BK2W=CB%P#F ' 8 ]g+UP'`U2(9J!X2[A[PYUOTCT;M6A08#3/$9IY1\@IO%WJ+(9 5 73A3(1<. . .'- 0;2&!71# Cij2j\qdSaiY!   184)%42' ,Ma"bAbXV[;[T=!6]b*BO0_D/-Mc pBlXcg`fT^9ZR<=_r1uQ{humNqqT 8Xi*dLV`H`SG&@[ w4OsiZz:pZ? "97)26)     #)9 3$23 .JD$:AAC>6$; =(6Tj-nHd_Lg%`N+*;.!074.* 2    *.;&@)944<#7 2&,E`$m:pTsdegNl8c+O 9* !& ** ='L&O4MDKIIHCF/EA1 &((#%&,B @#6:0>4/# !    $ & $%,' (' 3n%Xm@lHUo2+i+f-IW!f?kMw\cj=X\>o'L.d?fD 9 (h87IgPFLVx9cr>j2_M /6p):<t4"pwbKeeGTuk}ZnDg,X#E9.k -XpYOmpXI]u}-yIS*boE^_n@T(8fI&<0n  }.8 ,hSr1yTOddD vaiu]^Evx){72, ehDY4GE.knm<4J`: xz(t}~l(G, Yb( T;3&Lfq"FA"=!s;idGojB|BG^ *nh"-d'mW{Il?6C -g".N@ v-LXnU| ;Ufn&PYPe!FTE0 jAb"ZVBWUPpQ0&i4Do5<fwl>nl-DlJ!'U3@DKFCS2=ai~Rtz/XG5h LdgW%VC#_.OZwUY^db;c)Z351uN}&az./6g6;lE{l}\Mu_C#nKi)@@DpCc\|KhBf|,.0o1 }oyF*Tx%c9>zGSCs~Ua[ER~9ZU-0Gxmv=`BC 8pS'r ~6 0I8b%o"R$AL.!a *ahVy|w/|~1OM7 RQgV`75=8@0r]|{)P)\>v^3bE"ZB(, 75.6=~P_FJ]]!=.)D)a@d}NJb% H 2'!P{}D Cz%H^A|8<,FhS~\#R3r&N'5l\ vw\~Uu5Sc G h_ HT riuK@H^Ard|nR?* )4{x-|vx-gO/] :jfre~%+@>G;( p q5%i[&YSHjbL6}D?rwScdm_BY{O]'gUwTg#)T!e%t=&Oz5D<gOU9nffw)u4dD$2Z;ALMcl.;`=OCj# t!h$09"G( B/zq}bDNK`=yAqyr|>J].= >;?Z~2$Ez8aq4c|,f3Kc O C$6a5G;~d5Lq6!;|dVZXD-ZC0k.8+H(y7qVKnCn[qK9c(`/Nk~mb=@4d3qa981:IB@suX  $k>}g$hKOvXK|G-x'I%@%?O,zlXVw>$Cd &6D cIY|&:?d" h#b#aLGUJ)-=7!CWb/y*G&'27= qh nVZ!k:$?0>Jg0.!=*/9HE]Uy"_*/bm/OZ2\79qhCzZR7cO-*|f>bJ@"pi$y"WES<_KL Z0I:&@+>J4 A; k`eC a2)Q2S $cTZu%ySK[k?ez=E p*[mL.r. m2VP=sHj 6CDdsYJ( #C^a^KStjfaFb h|;6Hj2-P^7dOP]`~{0:eY ; z(ef7*i/;%' +'b m{kl0U6u|2r ^nDh1FWEo#!/{H,ud [j.Z)l.,\+?:N1;~4B3'#>34%UV':JS'>HYK<7RAKW6_8ZMTXKV,OBJY/1/Y%N2h<+hSHd*7Ip-kbBC\=&NzC1b&# xiIbhR*qM <#2` zElt_{"'#J)3I4b0Y>KpY6,f\3I^G9&WI+*Vv!bF2j7dm7,kY7EpE;8J i]K9F )rV\Jahkj*fPxA ju#desQ$50 HL`T(^RY5"y 8&i:f[sZ tG8zdXq1t-}ry 4:7-+515M*W)LBBQ;J5?@9J1=8.D2=@-H,K8QBJECJRH`>THNXdSsGpWqjKijUL ]/|hC~"v9M[<X+E#nGxvER]2/. wINmD 1 J ,EUP*9N_%krvn3S $ 7SX;^Zodgt  & 24 4,50:1=1C5J8G<@DIDV<YAQNOSVNfIjNa\ScQ]aPkJdWYcS`PTZObKTQB[ESL@M>MEGG;H?DR9U7LHHPMIVCgGrNq\vhjk|zcMw>b,L=-sdWIq:f2Y,J%A<6.()++#+1,90;==?9E9I:C>=D=AE:K8Q>LEFJJIVB\C[N[V[UaUjTpXoajgmirdudyivlopiokilbfbZeRaIW@N=F2= :2"{ukdaxbpdl^kep9jnY`4$6~)Pk ^[)bG~*B +>sGp.h LJXo7<T@ 1e/izmF1ox~.Cu` ZY'[kBBxCawEowSj) (>Y`2PNBZROv?F{fi|hvze_m|pzhs~qhyol}bpeTrFmJTSBRCDL*MD*-5,#0,   '*&"%'($0"5$4+11/11.7,:-5126133/6.4//2*1,--(-(**$*!(###! !                                                                                   p|HmjQ5X`OCk`i#Ck1G}ZUo@q%h?Jya".| 7@wUH8`d6YEb:8<PT7y~Ukw~5C6&bM#^xnt{{ 4sgs ,_V+)) tN]_;FCZ7\W%4QUz;8:VND[,~)-t90_Q;\9eh'NX/cP22W'Hun: wDcD^xU^sW>L/H;!A<rC=KWxJRs1%,' +KYQ@<R2O7<@0H1U9^ARL2WQ6 # !05**1, ' '*$#$'% 0*# 7Zp,WLg[" "9>1<'@<%7; ' ! ' "! -#*; @2># 1J1$C7,/ $- 7G,*C#2#%42 *,-1'*@[M.BS,L?1)8 7e\zd/QN9HK;(` K?N/qg3` i;}Glf4U`&bT2 >u-aKT!EPA90KA0-RW UFbR-MZ>1FL#U@*DP5~A SppwqZrs+gnt?'R_JCRZYI*HV5frxtvoZwuN[|^IHV4\Z)#MZ/r~BU*4P5OAsDV@vtw|Zoo_j&{w ,^WM[JZ:8V?  $;EZ4K=PO* *.8 8!eL'WR)*@UP8/K P2! .]U(OV0~F'zX_&K E* A-54 \{I;tzG 'EB *1!0#m \X!xb*(NS DO0,GC8?AAN5/8I6 /UI"%JJ+C@8A3/'1 &2% ,+ 5 . &&  8;)<2" *'#6!1($KaxABSoR0d Y9JkF9aO&#  + )SqTDe\@:2>BF12 E2" 1,8:)= -*&+ 5:3/ 54 '& "%@ME2 HC+-$ )).$#-&:7,45-   IM+:!L/  0em GU)hM*5A 7+<6#*$"&>$>2@>`Y1:T/X<-""4IL,@I) 1-  =QD/IE?a:*ZC "() .FK$0= G5243+>1F/37A7 )- # +!     #.% *&$* *0'('+* -" *###!! ,)')   !$+>#6%#7 6%"+,.&;)=)$4:) /> D&<7(?;*#+ )!          %!! %*'!& '  +%%&'*&#&& )38#3.'32'   ",./(/*%,,&  ## !  ! !                                                                                                                "'&#%    "%#"!          #($%#               &.1 -)&-#+%!        "#%* 3"4&/.+1&-))0$5$:+=0E5O8X>bHeP_ZO^8[)N#9').!1#5)6-602321  j5 O#>iAk%gQ>O]"r5ASr#@UZO(51*,~]-ob2zJ& ~mgoaXYD]tcb%!~> uCVn,eEXe6Y,g"`&Nf Gy/d{UDe,W8"3)94A>HSQs[jXPhO|>H ZJHmFX5UTI9"Jt G7.3@O&tIt,Hc02r+ 1OR=LN*D^&,VCB ~\DhvXiVAxMe%y,TtAaxK\~lZec-Io!JpLrQ:  7{I&GrD n:^(h8?oK/57!4[?qw]:LEVX7 -{(%!D? >]jAjcnsytvYD4YJy0 Jq|"\ [mY0jlOm 7pqAM*BOn/`A_EDvQTnPYq -e QKVOp U|H5sJ*30UUD`JV-6( dD& UrH}DNRq3bI!-fS|4Ae(~DB xu X KG\qZawc'S(lHP Tp4CY4HF.%fRP Y#Nx?gV]%Eb)Hq*PY0/]O]-n!Y:9 "i: wMvO:YWh f Nn7t@9f-T_j!-Sr\F BW:]*RpS?3uCt`6/f]t_EQfh D#%=(= I1zbZa) n<up|)]4;hSY-F^&4p'uqNP{jp\r@ICIp/rC Rc7@Z@@3m!x.>$m#r4kUj'I8[g5!DrNs:' M`,Ha_RIODR!/%)FlLz"s}L\oV&SI7E+}c}IO;%nMCD>%z$XW{}~u~E9|[WO;zu4hF]}WE\"$d@RchJHQ&_L{tR#yW+&!N[a"\Q"hRPiEakPA0eEc)k]+y*UyiB#AY6AuXHd`('GN"uqrgzwZw\Z-_{7PD:0ZTDY6pVgSx_D#S@=2 on/QSwT+x93#@M}1CwgP- HU$4Lj}6t$QZPC-VALS<1$qvIv0 Xt7$[YXv<aMX$9, m !~K^[ks<zNlY|Soho^t.74Vp[n0'5:^VA|c4D=0F!e)P\< $ D-h@u<I1Q]%=l@@_3Z4loi6aP U!f0N 3$Er< :CQ+WT6,%p:=.)-+a5Jxm81zJ~zX!.aC%FCAf[rM>^l. /'\:kC6j-uP2#eE6L~2; HjBM}bE's X<#VPL5)<2 %! L S&,StEetMsQ'"_HuF'Q/GES@\@Af"`|OL>E]g L,B!cezXgO!6{rTIc<l4l|$bL ?5;w{H!G 5?>Sn]\tkfucN5t_I=1(?h}ME"krn' z=SEReSX~+GOM>CI%HB+ :v*`o&y4C,0[I=v;Nu& $  9]x,}OlkOv$jQ-_. vG!>l%Bj*5.! 0-!  1> @(77)<6)# # ! 0>H)I7DB;E/@$9.$%0:!?*=46:.:"4-# - 7>'C1B89=-> 8,   $*,)&$)'#                                                                            &!$X%5IC *#!$&#      P#E;O ! #"       c3=skWk=_ h8]|Vx ~^:6m0 IqsN<9<+k =+8 se$C\~R]'cxeQ;peBBgu3zZTlry_lyumeD&w|~2w :f \6F $EXcje.Q;H@F_ _7IU)[J/Fa c7ZWN]3VL8 +QdQD4\R6 \SrZ1hztWkqKngP!&5 /.D&?- /2 4:pf%@a+f!D*#  !(AV"F66N>FR4H7HJ4! 05!$.Y%NHTJC=F!QZID-UI0 z  +Q!H2z\N%YRh8CugPJ[3Uh#V8/$Sx#mjs5 { zztG g-siGCXe)eI?WgN{7KVt"U!70'    $., , =3#(7(3&&!%%%"442-+1!/* *<1"63%"$( &       " (&"'!$ )/+$"+!*%"%'"*",#*'0).'&++-+%+&3)+&'.,*1$+(%-)*7#3$"0"30#2&*#0)%* *%('"' &'!)"'*&!            " #! "("!%#"#% % %"*#$""&,$."',%#22 ",0/#,(!,.."),)#-##(+$!$"$*'' %! &4 +,/?,/79/#            " ##!  ! !!!u !o7/]~Dz0c x<9o];WEdm9=HY-dXV$9TEY68=<GI=)";I>)Q>-   )' +,,!4_['  03ILU_"p 9" ,dJ75Bu(} %F'q;'/n:+$>% ^D"]\L>p"geF%K^P;@nUZ<y wVj9l+0 }}v}m xk%C_;x$%*#cW1a<O^~swPXudlY`5PS=-4A<2$;x` h`32.9-jqZt}h_MgR[]P9U(Y! 9-5#Tb^e V)MlBv1A>QI!R X,?H(PBV\t%-3, *" f^;MQxX ) ' ! DG  %%. (52 "  ()  #-%-#(.+%(3($2& # #                                                                                                                                                                                   $ #   #!  ,4 (#(2'&..;)8**3.8))))    !8W \*8LWA  Nb&,"H%|;. c |Z@usfuS:Z=s4Mg=Oae6ZF<$f^L+PW8@VBLYuSy58< 06}h@H-r yeWKl)`d nCa[ZMt0G&IX \;Skx~vHyu8'7r%ae+xbuE,(n z_ {8`G T$^(pEYk%Dq%Pd6U?@mgV3s9MQ.c^m]LR~gmllee:{/\Tm^z  A F_2@;mXrWF }eYeIXzD4r^ TcCbcaN5jI*=O_48xHWBT@d\c{]qm__l1Lh@oO_^ub+Jc aO!`Z7s"/'tF{cg*k/@ WG ~L+mP!r9m?og MzDC\wersVYsxsUL5>)<tD,3ZS=>wV&H qh WdB>W:qlV=6,OH`v.IZY>y?B wk>^bn%[x']{)@<V+[t;UMte|POz}|m4?kt.Cm2eK^{-t0"U%jlIfS|X=rur9Cg8RD }Fw%!xT0)hNFe4=Qn[)#C(DlhK,HNz7~_p0@if_: o (]-p/eoMsn#~9:%ZFE[  nQ%RFEJzwub~2sN k_x{qV#u``]sCGaL2=nc7z!VD{nvp_rYu[<YTbCBs?v%:-40 ?Z/# $&06cPtmRe R5cP%@o9V1d#Z*q"p|nO`f\*0B;#X1)XJ}DdW{ucwKE ?G Fi/7N7.@~vOX,f'?[/kPUn([y F?A  9;Up;9+Zv\{*2{0u 4HK(;AF=rT#h?u%]D1f16IE;ef8_|:OP)[xV19v,`i^]O(Q@xC'.\Z89W%AI*6E0 ^9rP#I6~b@gSttn7 O0Vg`P\Qm?L'T>(p*gj&1v 7) .*$&*(%%UyEgj0|j:Db )WUTj79 *ugASU&cTx*,,uZssNv1R,mTIYfC1CudEsQ8!&:nR.|(f6C46AF+,o-\jz -axX1}HYK,c~m_C#LGx+2 Y+O6d >52 f_|YSBGD|4s rz^0sI,%&!79us@3?pcGVjj`6x!d>$pu si|eIy7N~)Kp  Ewpyd"S~U9313`r@+8Yg;@e2S;4jo%72 F-{EHnw:}w^w*BPzJ;~:{smJ8J )Cg6nCG+*M'*(($&l) DB@=\ ,D'_7PJfd9P*$z3QC RD/;-V'dZYP#pWXgUNT2c,q*c4.E?WY\lgagvlkuprud}8}tS!gd(,R` Fq0T-YEG\fmir_eval-0.8.2/tests/data/separation/ref07/000077500000000000000000000000001475740344600205005ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/separation/ref07/0.wav000066400000000000000000000372541475740344600213710ustar00rootroot00000000000000RIFF>WAVEfmt @>data>mFJm+/#(^ԝ34ׇ̎9Σ=HֽڳOY m!%9aՊΟ:ǠHК[- Ĝ Җ ~z`J"e*7 gl~ -&׆0ϲM'HIñ|zˠ{ˬUԟۅ%MESM}QRInV N  RmaԿǒ罰ıbԈL]+ƯE̦_Eב=M e XXe?a~ĽPHν*uʾͳV0Ƕ^پ<8J~$}d7S vi |Uܹz/M=~ʍ8D }&i>jW9;)(H[AifY2/tǕɰ̜~XղԖ5ٙރg%gQg?C)X9 a5~5< ֒ ,{ȐƸA\;̏*WaٓީZ}fBNkf\0v+VEַ֫SMס eFߌb"12 VN6h!5s$cޏTJۯ('v*\ۃquB)@b8 F<;JbM yeh27 dYfS>$3mjP0|s(~3%O|UZ\ &4)6t5HB' O'?iWPU\y[F!?Zij"=Ki'!! +Kq{ti:T(!9[1IUZK: xfWQE:23401+*7Ro~|j]LCFcrM%߳(|VuQ[ln1dDr yZo3x4 H~ S%Sl+ Dva@jOEpc}4v ]r"6f7Vd /]!x#Zv-s5='E|]Fl+>@v#K-xHD+}k" T8vI1I2L :X P EG3P"vh|@wxyd_C&F|/o a{5_` W>/Mߒ\Wq[-*.d2Fh/j^B*H/LC8 .`k9_ߥamo9 a#$v jZOYFM,9gу!؂#څ*NgS?[" /4&0DÒ~Sbő7rĸĿۜP {iGJ9a4cFu>$.ҏJ-}A/IMƓђS^>y? ۆ. S.0JIZEk"ؤ˔B;&<ѽm,xϯԿY 9zԟE:WY{~Nqe(J"?ɸ?{OZ/˛Ñ}i کbZҹٚ:יѿ[8Es: !T0c>?$2u Ե(¹DžNߎڊV̓y?<ӽ͸=#בb Y95eP aCd߼N8eUƆ\FͳRrEI ̌h d-]Uòaarq5 ˺5O }UdTeͱ8J1?ټ^ _7\0Q |$Ci (ӵ6ASٹf{,Ԑ\߿{ԺЛ /8hr"n3S!N8aӡkGya@ڔ @s4Fہiݣ>ԍщDp; |4$Ofɜs!V s:Z҈ad\,SsoiowiӂܟIOcέYu(P[Sl IBqV!sҴ򲾺KuܰӴj6g,ܫ}/!/ӺQ)ޣ/Ό=δ԰(nnܵ>'ћ,^ێىQ|jD x.Н;] |9D >z 0uV٫+/.Ěش2ۭݎq,־ Fܮn%!޴)ЬܖiJX*X <[{ '" [ۭC !Ӧ 8UГiw$2Gl *”a"C+ʬĻ0 fer@arImJ|: Xtמ[Є =% / J='dc$.Ӳk+~߅s̓v/<ҸɩI[$<ҋ: oA~g}JI !I G(@D{5 ?%ܝRߓB]G-zYE2ޮҍѝy$u"!w n.6 0= !d߱oݺn!*fi*ޟ,¢xPʶ™?I)giC!:(=&" 'h\ՙd .4x0YSǎҟBr߷*F]+a}r $% .(A02HwA L}յt޲ԈP օGߵR5|O?   ,:3 = ,ŰypN >!Ƽ/3daK +.{rfhUZ. H/'!8%yԼ:s$PyCk/,([f $`J gT"''(64dc ׬ D5ҧY͏_ZZ5hխNv0U$jn E#W$)5.uhqbպ΃tգ̥n@^ 1ZY 9!-K"]5ҿ䳎<ljϔI ΛE:b8ԗƀ#&d˭+ hlT%[i\Of'%r f5ൌ‰rũ&ؔ"'c^5 0ߛ@SY +u$ &QZν䲒@rP lxug.r 2ɘs"iǗս,U8 kRO{_>\$ ;a$(Tݶ~{(R#۞(Ѷ%ĕ]ޭ:q}j&-qB zg$@ L(+2% Qγe S]_zsӮHz;܇tml27zouKY@ &:SDT.e $bޯo[9і۱׵`92/)uyj=;JW¸1ɢf8aӫH%{r&FbS+n`)9H  Y"j.Ie˫យ û ,ݘ]I؞ӽkGm"B  ,/3EnCCx{ȸʕ.b.,޷̩#ٲѣAۮ[՘SWFx88W7R o O.dY*sуơűg q0F΅љΐ+eBjA/ 0SC[S^ @&Z_Sߔ >w,+x ;ժJu=ϒju@c\tXڕGV F*I98Ra'=@sgeɼ,p?(ѵnƸԺ~@4},7r;ٹ Dm*mG3P+BC_njwZݓ$Ⱥə ٗjc4 aw̘ פ߉gMvB+:OOl &aT>@:mմc}ѦCћүEZܧh86z!՛EդB߃&eܽ#]E1n|Q_Ii9se!ٱՇ֮ب׽ׇN רג٠6L Z2wҢҏ|.bGߟxԪך݃v0x){|(*jzj%ݩ݂_kؖzٹڰO3  ߲QD ,pE4g&bԦ|e F aa1*fQa+:ܻ[#ݯN-ڝN~BެO[ ecqUކߊS$,?т}[I$[X߄gVW@{}۾nX߅߲ޡߥ]\p< Ocnuf]NBmJ$d8zp3rd:#dfEګݢߺJvQW}j ߒjevRfT)׉ 5(}q] |^ JUٹ܏RVسכߵ)'ZD9+Y x_J' AձC<;6> -܁FT53$ׄqkgP"p;O"\3 1ͱȄu,r92 ߹LٿR|v]jyk+%BYuޓ!p*ROg؁ۈ Uu?/ݕY3.IH ̮|)ݔpXժ1 cS 55CٷׅەޜBqrߛߐZߘߞpp F!Kҷ\RjYޱޖ %M7_k:I4xK,߀>Ejؖe{xޅެ߁-k}06z,R0޻a  -En I(nYG8a7)7JF %88t >d9WTs!͔?MH?@_Nن֧$B CbaV)H4SP"ܿ٬X~E>KAmIBbd/##+y )ZGZ5/Se$"aF3jyH݀ r~߶k @$ק`F2{߄޻|לUX!a-^kf}ګުSuA.ߧbBBA%ؠ9 tgS&X5ׂ^ہ)i$~,40,=yiq#۵nI\oj H9 mC;U]@Q5mV3.[Z.I?S>eG$i#t-A =1(H5֔&ڽ4-Tފٳ0""ULlw-@nM~;|UݫށX"3IvPyg*ۑܵ7*-4.H6f&Y4fy7{oC1HB~9YiߢC=n=mJFb+!ڥQZ=ܰ ޼3z34 v(Lk^$jHr!9AITt5+ U]%܊(ފXDx2u\ja<2c1}ߔxCm }&U5@q]dJݻm/4"rkSj}a `: VuCoޛ.E(yJS7sQILv|޹!p~Xy^J(NH/NeWvOd޿Yl_hIJV0=y3+JwB>y@Uw}I>X|xdu`SasXYzfP G|_B~@'k8+'>TDN-9K45 3U_&lQ7 =zE\.`dD!LDLltS?zJGRFu7!j|56ziXCA1e=aHv 12,?N.;G*OYE& yM3A+;>:=Q2Pݞ4L#*]Χ5H $ y<M"6b/p ֓J7M" ֧r<ܷܒ֙kL{ўѐ|\ ap4%v 9؆Ρ_̩ͣփs"! pن$݌%;-`1T؉ҳ> {(s߄$fQ^(4 Ifj$i/ f!fr! Zڸ.5֍K,֧ѭ FE"0P'dPeRENӐq̹av:"y5Aݯ|̦Vdՠw3'lܤ |OײTeu*gc-`V/p6xUVm(_.ljkǺu ;0~4;\ g Jrar t[vSψ֦& mir_eval-0.8.2/tests/data/separation/ref07/1.wav000066400000000000000000000372541475740344600213720ustar00rootroot00000000000000RIFF>WAVEfmt @>data>ˍ͛ڲܾ-}ߺ,'ހekL'ִոi4鷟ѸYj®>빺4͌nmnӅЩV\ԥޘz ߁\ښܼؑ2a+#Кίʋ еY-Ѹ´ԥḞΝ-GҊۙ23ؿ,+K ޳ݝݡU)lޯީRن΅ɻ:^ƽݶˍ׺𱚣(,cfԍ 54ЋيؠڪߚINM.ڵVsÒVO׈(GܵY̩ճIWقͣNˣa˕ c@ܻرTbӥԚZl"h Uz"hvT ac-L/Կ?HZ۵ޥFh2hΖόҮ׽ٜc(X]cnòƪDn  F yO~tӫ0(ų('ցrTӡ;ĹkۆKڙ ɎS͘FO0iљZ|jDLYV='?_L߾NȵGg}br ˹ 9K33R7ۓkՉ́8Ƈ6mӷ1ĝ,X<–жFtm-Ï&gpىxϝʹ%ҍߪ"֗v8Yiܜ{mO˽ˎ,hͅ yw fra-c2IkΑwݴ|Όq7^Kͼ^ ܫxʔFk5իsש*ӎ m{_֫z ʀȥͨ)dzbv&ׯЎgU?‹N @tj:}C;ڛa֢؜TcwѰ,Tl@ѹ͂wȘxǃNJ=2J[̹̩ͤܿX Ύ˦ԋ?Ȕ­ʩP ըY&y i˄ޖfպ~>λ(܄Jwm1Ǻ̠{.iǐ|7gBwL.JѢZ"w,"yԘیڒʥz4ާ׿93Ӏж\3?ͰƯŖ.'ʶ)˘ͮPI̬k]U.ۢ'CjfƮ޵ԆqLȭ0˥2 I iTԉԅU6˃Fg9`:ІJCѴXܫ 0ʡxƿ kD@m|: WNѝۙ؄RՅ(׽#۴փEД~Ѵȡ?_ȍȒ7ɔ_х %ϼТ@6Zs֊zɪuOƜȤeՌӑR սẏ ֹڼ B٨qӷіM^CeٲsIŊ.)K1х^fFE5W#$̛ύIX$- ʮMخ݂Ցҧ҃Ρʹ:ک нeŗ<̄שדӕ`J ods̅mDjm8ҷB}ͪʨо\A?ޅޏٞգͭ#Tςe\8^ɴL˲ 4c?"RԓQdҬSk}Ӊu#mʲz,%pΪώҔӓտ)A֧ոԓtյ$^ԡ&эoБjϬ͗ γ{̱˱͐ͥϝжМѲ SS.(ӵәӥDԂP2~ Х϶+`U΃ξ΅>AfNχҥӜ_;Tӯ$ԐMbfqՎЩ8ϢmϔѼ&FκRqҞз(d0eӽAґβIB̸̘ ͎Pб a7/b Էwҁҕ|eҠӰqCь/ψ@^И1CҼ҇.ӼؘsԕԅaG̯myr ԇӈnԓy҄Ӊ_:ջ 33` ծchϔ6N= SvQцҒ^'ԃt<ל>rgxb~̺ʍ-Eʤ̋ͩtT .vԵԓJ3bgӫӈt֜ՄRaqӴ???}ͻ́VWzZϝЁД_Ұҧҧ{yԗpב՞ԛUϬͭ|Uʭi̞)дӘIcՑHӯU4sm/ӴEԸԐ(ԀӳZ͂=5qΘ@aсұқ҃tmMѤlWѱVTҋN+fЂz˜ʽʆ̥͎ξѼҲ>ԣ,2ӀJ6ѹЉgјҋ)ӋӴӈrjsdx϶В>ъѸ"ѵў]=п 7Lяѿ=$Ѱq iϽϯК,ѝsLwroq\ҕҗl==-b=.bϼϨϋfkVg_ЁЪ ЪиЧЌЉБ;чk/MUmv_0ҪҁtQѤѢѢѫѦ{bQ:лЛuU7,KoИj?E^dY'uм\* %gФAѢG҄ҪҿһҝҀX4#NPE3 ѳ|5зy> #Jк-\сѦѻ (+)'" ѻѫљщpZSG8.'!!"%'('!//;VrшѕѡѵѾѵѷѲѪѦѢѤѭѵѲѫѬѧѠџіхv^I7# )=J]kxрчышх~qc\YUU`ilvхёљѧѶѹѿѳѫѥѝэ|vtnifcehga[ZWWYY\[YY\ejlnos{уфруъьыцсрxx}|xwz}хёњѦѨѦѪѩѥџљіѓырunlfaa__gklwxommmjhd_ht|сщёїњњћѝѡѤўѐщсod^YXWY\anyz{}съяѓѓяъшьъччтwqrotwv|уыюёѐяѐърwz}zтцчу|uwvvuqw||}}}сwmlggiinppqpqvvx{z{|сртхчэєѕііѓѐяюьцушяѕђчхс~zsuwuwz~цчф~wuplfcc_YSRV[[XXZaixшѕўѠѠџўѝјњњёышчюђюђієєѕїѓюыщхфсoa`]VXYX_cbcipps|ytwz|}|yutty~счьыюђѐѓїєїѝіѐѕєяьх{uphjppvwtсфхь~ptsmuupwytqvmceiejvqpqrwwрчтуяьшєіѐєџњљѢѣѡѡѥјѐэvmth`vthtm^fh^a\\fitштyсunyrjoqmzчцюіѓэёющяѐысуыыхчш{цэ{}чрzфсyцыхыфvyqvmb]Y]gfkqqр~xтчр|xtтсzшѐштц{xvorvs}яѕђящ}ywv}чыхщѓѐьёцxцѐщъящфу~tidb[SW[]kb_xuq~уцъфv}р|ыхz~y}~|zyр|фчѐѕыёёщѕќѐѐъухvt}{тчьёѐяътuplbmus}xlhVW[MYOJl^RgbiєщyёыєѤћѓѕїќџѝѤѡѥѥџѝњѕучяу|wysglljma_imjjmpw|yzywqkljgiorxxyуфщэчф}тѕячїєшыцутф|tyчууєяьъцт~цуtktoo|txr_gkiroxушщѐѐутtfmrllsyv}тy~фчюьяђѓѝўіѐцzх{nтhYfknfтхp}~vуфцѐ|~yhzs`qx}ч|єю}єшy{ёѐтщрuфxgt~dhцooъхjqуznxыo~сwъt|}wъфќђцъvu{}шѕфцэ|сmqtoymr~єщтшv|oh{oorb]cgqz{р|рчшьюыэцyсрхф}сryяѐєљјѓћїюњё~~znbgwhd_ZiXfzmpjluuс}{щфушхрylgqwтѓєюђюіѪѫџэцwlxwфэрtnmbwы~}vkkryyyхkqtc|rqxu|цфpхфръw}}szчщышюѝф|у|ыяvё}yущцтш{ompic{u`t|wхwhwqhuстфх{yюќѓїљьтщы}цяяor_i{jcb_ftyupzxw{{фs}ятёїюѕѓqupю}сyoр}фљѓљѤш~ътфусрwovvdsmjiNZ_k|sw|uфєсьфnlrш~vsххcYf{хюътэѝѝѦѶѦѥѩѢѣїљђshnd\]ZTGRa`nyztYYnoут|уtv}тяёуцъхѝѢѣѥњјчыщ{тunrhnnklsюwr|}zцьтu}тao}gnj`lmnrръg_ыџѡѠѕљют~x~чѓvыьхюэ}v|yfрыxшwmpcidyьxkkjklyт}zxщшцщыюѕёvчѢъ{чы{uzjt|{фotsiwosvmsst{рцљєэч~х|ртtpnkkzуxzфxpyчюђјѐууьцюіyntovъщyzvhifo}{uqфухѐш}oxup{vsej}fqъсх|zхшіџъxzxсьэѓљјьръцрч{utktuqчяxggbhqgjkrtwшрvrqrw}r}ъu}яъэёѓэѐњѕѕћђѐя{w{{wz{kgtfagcguс~|уynx~{|~{sr}шѕщ~}xowцђїђѐ~rтxr~wqeqъшыэф|цы~цёу~с|rqрxffhnqtifqrxyzсуячцљѐѓёxrsspxъсvюэxцѐєѕщєћяєяtkig\_eQPaboutwzvьтzvoр}wчфыјюљірѐю~}ѐќэѓћщфђъту~umnglwiuqVYe[S`f]acaqцчцюђїїѕџѨѣњјћётыщхmy}u~yow{рzqyp~щ~т|tklvqqsbZhnmmчє|уѐэыяїэyvvltuhmw{ряѝљѣѡѝњћѨєѐхmwsdXahXWcmotuvldov}{~тq{ыычx~ыщцфу|фьыѐюњїщю|pvw~|t}фxёѐчтpqr]^`ceOVbdtzыыфшїџџѫѥюєіффцzvwtotс|}сxyсчц~zvx~rojVST^fmxnyzуџџљћѓюччъщщрmmсыёрsряфуэхфьxirtxрl\_aetсyz|zьѕѓъ~xfjzjj|ngрфѐёыєѓььяыцьытсьшz{l\ftsr~{rr{эьуррxnlstjtuvvmruxтvwрсяёіљьюџѠюф~twuyтсщ}uysskcmrkommst}xvрщцчщрфхчуььчыъzjmrsm{шъѐшцс{~~owх|xz~vuxns{upx~~рххц|wычzxt{|тт}s{шъцrqsouwсщчшцурьчтхttrtухчьуvqintmsldzznсрујюсььъю~yу~xzz{yqkpт}wтъшщяштэуlцьуђ|fok]emlwodxuv|tррстzшѓц|тррчэѓѝјъшьэщьхw{у|хюс|tb`b\go`_bchrwnvlg~rsтсфюѢѝѡњщѐљѣџѝѡєјѕ}ыщ~ш~tohebcbVTcgnouzqoa_kfktgnх}}ѐячяіёјѢѠѥѧѠћѠћъшф{ррsxqmkdcdkebiioqfhlmtvuw{vzтчђђъђћяћќшієрyuihvuwрфсхэыщээъш}{|ojhijec`__drvzчрсърсттщщюяяяѐёьэъссz{тzyс|~ф~{uw||{olkiihnuzсчсру}ууutyсущсэїчс}psroу{хсu{~ч~xzтц}чщ}хttхсру~sszqq~}|р|~zoqqqy{чу|ц~х{puwkmрхсѐярюђьёёьчус|vvqkpogqwu{{y~~тvру|{u{|zzuvwv|}фььср|шът{z{wфуэёусс}учычуттvkujfvmiumhmjillosxz~чщ{чсчщщяъюњјљѤѠјђъъц}ух{{tgihgedccb]ceeggutn}ууюъуцсхчфюєѐѕќіјљѐщшфчяьц||{rph__eghlmtz{vsrnvvpxzvрщфут}тэььєщцъхъэьъфхvyvorneiouусщь~эvѐxwѤѿЛRѠѹхщѨublu[>Dtub@4MTVOX}хjsјѴѹѳѯѤѤѐbJHVvj_pwvnmuт{baiwђътѝњ}rxzсx}хуy{щт~хр|фы}~rmmlkjlgk}рфьэыv}ъяюцхъутц~zxnrvyzolx{w|yyppцчфщщюэуыѓїљь|{|vruvtj_fuvvyuvwpnnxтртуъэфшрт|v}тсчу~ухьь~ур}{wzрzvtpuwnjsvpouтx{zтысy~{x}сыёяёђэьыфчшцуxtttrkbab^fkq|zyхѐђѐъчшчф}~zy}}zyw{хф~~{ууструу|xzwrstvvxрхыяьцтxuyuqnjnrqosx|}vwуцчыящчцшююшуустурр{ywvxyz|wspoqsrqmjkotx{руухцъэьыхр}x{цьэёёыыььышф|xxtqtskd`bfehmptvxтышчцтфцууфсрстуухчъшцфуутфт{yytsqlpnorrtu|хыёѓяшфс~}zwusssuvwywvvw|рфффу~|yw}|vvw|тфчщцшээщцчшфцчфywtrqoonkjkkotuz~}}~~~р~{xwyрщьэёѓёяюыъъщццт}р|vuoljijiorrvyzzztruvyyy}ртццхфтцыэыъшчшшшыцт}wvutuuvuux{рцщшу~xvsnknqoquttxywyx{сфщьыщшщчхфс||}~с~утфццфср}ру{xuppnmpnkklmptyрссуфцыычфрzz|схщщшъшщщшцсср}{y|{smkhimnpsvx|ухцфрр~р}|рсс~}}}тцтссссуцтр~yx{yxxxwttw|тшьыцус|yvoquvxvuvuw|{y{рцшчъцццср~|{zyz~~рсуцхс~~~}рф}{uuvvzytrpqttx~~~|~ссzvsrw|ръѐѐѐяююэьщчцт~}~{wtoljmqpptvxсчфт~zyvvxwuvwusuy|суфцффхушьъыящцфywyx~р{|~ръѓячх~rrpjmnmnoqtz~xttu{ффучсрфрууzxwxтуцурхчччсср|}~{wtrpompsonrs|ххшщчыъчыьыц~{|ущьэщсццрс}troomjnkd`^Zdoltyyфюѕіїїѓяыыцущтррy}~z{|yzysuwuz{v{}}тфстъшхщццьццьсyukfedcfffmry|x{уццъюђљћїѕѐэщ~wpigigmpkqywсшсцьчюјѓёђхфу}{zsnledolgsrjlrutsndemntучщљѝѓўѧџѧѬѤѩѪўќїщхwjg\clfiomqvni]XZKPSM^b[mz}ђєяѤѦѡѫѝђњѓѓїёюэфхрksublp_m{pрёчыюшјѧћѝѧѠѕэф{zypkicZVX]]Y[\Z\ZY`bYYfjq}x~эр}zєѕѓѫѦѬѮѰѱѮѰѨѣѢѢљѐђъ~~рссхттуve]`\^bQVgVU^NLVLGVPBNPEEF:=GCDS^Y^jlwщшяѧѬѳ 4MFRgiot^D>!љѓ_жигмЧЖ|^U: >Zn4љ,ҌubԚպoԴjӀ/Ҡ.Ћ\onЮВ-DzDb˕ˍu ͨϿЩ V}TהתׂWր}XXif>νyQΔΏSϳҟMӣ`bzk~ϐ'4 ΙψИҶ$Ԥ)bf֝֎N֘pֶR$ԄtoВ;cQϡpV^P<ε-MCԅX)qjVɩʦ)̨ϕsѺХ9 Ѯ^ nrGԩ]=Ooв8ζ>KjBϊd&"]ɖa%ɑ>h T̙YϼCJؽշGר7$)1ԸӺҨ ʹϋό˓̀dw`-˻UԪ}DޭсXR A  FԕYND9\ظݮېl։;ڕѮπѱԪ=б[_/Dϭ_[έ*̦ͷ&2ZXR̵͇#RɥƗəОE˞)SҭڠKm]{ҦU؄k[IeFЭЄ[ӠRш~1ИhʫUʜδvAԉ{Uш̻g͕ͧǨfΘ՞?̺ґd.aU֒ הi?ՙ$NyFKV fғdAkGC8z˼\Jԃ+<ʐiNDž9gҼӀ>θ˫*eڃM֍Lלի|֕!%!Zv־mj5u@U~ŭE5cժE{FTɵɤG.`ҕKHՖ/Ҭ՗/܇91 RL!ц~ҧ!߷K >)͟ZVɦMɃ [۲tGm~iʊ> ͮ˺'ȡљE[ذmغ׶_7a;pԇod͒4OhM1Thǐ:,tߘ#cٲ^ЛӴ̺L¬B5;ܮ%чP߁wү߻FIآ݄{/PcsΉrƅ`BΰĘM!ز4_M SLBjcJZ%@iԟ߯תoC"kȜMXsr뮢4޽D`T˔ʟӺ:U! YWب!"ןۉ= ܥN׸m(juʹɼ0WJeØ7+ɾ[b?6>ؾޥߋYߌO]ۨډ٘3ՐӉFyhЎcȇ,Q|w#结.bŋUҕRzT;"ޯݯ^T\>VՎ'Ɂ@UÇ'x󺂼Lּ\M¤ɮWUѣf׻LbjFG\h%fMߑސ!K<89:֭\wVvMwuq۶TԽoD7պظS '9Ufݩ8ײ\ATZ/!F/ƼwEXS[Nd"NϢ7;VkA ޱ,lߑ*SշӖcnH㯼l񶘶N ٸ#ʷz`c[d|9#VhۣAQDA!jf׷q"Ty0 Y3Ҳh??rcցװwUkG$KVLKЖӯ/dž`%^؛٭ B~Tڞh?jܛ u?=Ҡ֮ՉMѧ򠾪ȷ‹m VǿЅss_ٮTIa>ۣm'˜Ĩ4 շ˸.q7Jv&PgzcjMZ  FS-RB'cħ7zkq^Sy+Kۖ֗LْS # 7oLkũVQ#iҼͿUї۴ׯ8݅_+ATm fi@jtR+7eݩ) ͵c 9ִ[6ֱgحB_zk$$N\,YpdNV޴y-'AǬ?Ų<4wѫӥYq ۝;9H[PU' "|#ћemJ9ǰPȔ#T˲ΫDvӹK+)^ܹ-шۅ-N:⼲=mir_eval-0.8.2/tests/data/separation/ref08/000077500000000000000000000000001475740344600205015ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/separation/ref08/0.wav000066400000000000000000000372541475740344600213720ustar00rootroot00000000000000RIFF>WAVEfmt @>data>4(Ҽ]ٛMfݱCn58n_L*Nݖ١H8ٵ՝!|۸bd$-1GoU42:S 3&گx\bS8>dFa:?Դ*ِAXY!/'qL FEp&;5\TG{գ 3~l`f 8 R&~9%޹ Yxd (NkX؆HќN֬7N A_:s$f3uo۶_cJ|DۘOԈԔNwl z4C#*Jgg߱k?=r|V+ܨֈ^Ճ[^؇کڨGm|߂yFn+In/ ߵߠ/.O۰տ6؟ ܙڇKړܽڬkn`UY8 /;%޻Rݶ %Ut^"C*IҡE>ܰ3^ށ5֧ض_/UD,e~a\Nu`V"ѹin̦Փߓm9&~SԫԤ{aWA"\6,Xk֊5S !euZspȰ0Im.wѕn]^ޣ#hܓ8\a,qAB 9NM~oԁuƩ ʇܙ'.˙ΑF0tؐ|1'P{Jԭ jJqъ<ŪMPmk@8ؑ7Ӹ^ۅk&`@b6R_VbΓE Wg)]JԵnZףٖ9dѦV˕Ճߛؕu( ^]` (лQ Uu@Ԍ[S_݃#RޓڑܐRաΞE_;NۙMe8htQȊ`TJ Q TJL~ǔ-KղeކgM"~ӬfRJ@+Ctkԩeψg"w#' >b:Ş?X<ߥ]o;uņ+]bDܛmԼxۑ1xUJt܁b6||&?ݻ\i ؠNcF̞ ȍɺжܾ^rxߍ/!M`Q uحM|~j)K!A!w %x #ݫ.CQb҂>e&JW+!޴?tDg)(}&ch^TZde3o؅$^ԖG'Dd)(H_ݑTins*3Hڞ۶ۤ-#].ޝciP"oFU_F)Gޫ*G\V0ްߕ߅jږV[[ -zދܵ6sLH>!!w2CU:ݺqm r(Tݣt߇Z߁@J oqZ=yu[Aa;H<^ڪSܕMA6۔߸BG+l߬Hdm]w b#|PbbM"U,F! . MU4&Z(߈_ޛ{߮X],C"#XX)ܽ} ߺN_!!ߒޕޙ][Lsbmߓa|auupݢݝa&BVCm:ߘ{ u~E ;d}<(_qyyF/Sv_Q&SRp_198vt@{Euk9S;lߣߠ[t_~F7A>7%9߱N'O:ucߣg^ (gf߼gt`.54?U nSޏpݑ01߹޷!]߆9|ݢ ߷i9}߭]=5<ށ#N=M 'l"{ Z"iQ߫"ߥzX)wXR ޣ]G.Tpߋߐul߯]~ߘ߭U߬x{} PB w ErmC]+D6jޜߎߕߦpC@Iߧ0U|SLIv%+h ~)l@z.YN=o vߜߗqTߠc9$ݒQ&ݵ qgXR^:-7X({~XSٵֵbۏYٝ׫,}ͻ͈?EA:'gHb&/.=,}y6 rd"͉q̹Tҹݬnȸҿ0*(K~ mL@I~ptN &'egحʶqaЃu9>:%ɩ9ҔhO1>+ű ּ֠)I׉G+?t.o΋kJ?+99)~ԃf@dz^=oDރC ʟDC8F5ɹCj>W#%Q죷풏Qo;]Va"<4iǪ"XD,GnʼF}ɤP{5]a1붺XD41BBƧTϻwYϪIt࠽yˡK VtLJKA]%j+e ҉o}>Ԗ(Tݕ)4T,B!}ѹϼ 뿃Sn,J6r}ʼ' 9`X]ٝv́="N QO"">8ڲ:4:GD*Nō֋)6ˮ][^Up Ǒe"uCjѴҡ%ԡ(ߺ.Z'Ե$p(Y6<`n~{'΀óPs"*`ԁ/Fo{Qڥs^,Pŕ?l uۯ AV!96OVhu}dAJ32u'YquʔDV܁ ռ5;Ԑg*fӜ}7 杒nwj$>! &t9ЗۃҸ/5Y Q$u3fRu̾ߨL!^mδ% Yߩې;S J &VqZCG-C,F9PmgV}6ּH*sY 5|. $e֎BϖxÉ7 惹7"kX`NO Μ<bZ/\"0YV}.۠ 1θ^ܘ_WDeudۗ$(, NbP¿_nZxS;$ Xaj8M 8adfį gVDʔ¤<ݻ )& .ڣҵɗńNJtگ+P>H-5gI2aـکܞӻxۂpe{BˁAy%GאǝOk2Qd7q*&H`ϭ!'Dْ רȯ;Fo8߮ɓӼ('(5J;`5hѴ N}w%6axzYcԉH`GS \ c4ؽSBW+8:"miǏҝCFjiD% 5~Z<%2pZlQV]Œ,bV*$]'tcӵF #e ٮF&͡E {"ژÿK2#$3;Ջݔ>0ˬ-S·Šзx|:|%/\P~~R:2o/xھƨfh>h־i߳c"tda. kX%CIr>(6H>"ñ#Iz`]LӀ/p*pVGMѵ Z s[Ssdȹsl i.+w+**u]ﷇכe@wkԟι/ljkk~Dڤ7;lĪc23*E,y!)ξY½|Z9Ռk1YV#nwd39vAa?8Y k qLc>=Je|C#fNʃJԱK SboXAϣҼ޼XS8ީq;ٮ3zg[غ<ȾȮǜ G 2 u+Q 4+ٙY@^NԹۂ*WT*'*{+KR =S(0+NЌ@cء>yhԄyߡZO$L '%Oٹˢ*J?KҸT4ތՀ/Z !-׽77lQ7ߺL~rNDZ0)L'Lԯy2:֞?bJ݄іг2\-& R|',-JPzYMHi1IS<uii\Y۩ثڋЀcBg B,s񫆵ǠhPF/.- opdYʗϳTڮ'2̉ƘK׮DsAf_K+r>Q P mi:#qvΙ݇aIb?a&WӔԏr:xҢΎrF _e\K 'FҬEϲLO'KևI֟%>j$i}2(1zWUҖա֚s'|x`\t9x<ϩʺƏ'4x 5q0US)r] y՞h[-k.ܸݺVjE՜ޙs HKkѸ خD!gޯ ۈj}G @DC]q$[Ě.x9א/#}b!Z 0G ZS.'OLwۇJ09NtkRdV<+վå̄nF/+ |ҧ~!kAAKpvl֭vWX 4W!V,^׳V31qkĩ#k~Fu~|۷N@2Rѯ!&}ֈ>[^Q)e|Cۑ޻+ ӌ}qFޑo_@ؠLc.; ]۷QڵK ϪӦ_}$UtE~S 'c1YJܧ9Ӱڋk( ذ  -Ժ٪>N\جܲvWc؆ +g&{s١m]`c@ΖϩԴ5k߾$eaS x-7֚"om= wp&ܣ4(ܷjZA'a)>0ߕ0x"ؙЃ͏Ψ ԃi8ݜH!x5] b1. L2PHG<РZ̑ ({PdK߲o4K=׭Eӑ]ؙ:ۂRזٛ߆n߽|)X ] SQںڣl>$݈ףyh[z]pU۩a3VsI:vZ&$q܀ճѲҌ~@ATzq@'7) . P( 0vd@$*@̑,đA[Y" ;nh!0a ]}ދ@}$Q m͓ ѐԛi^"Ec_DzSڀ+tr]۠ C [#;xqL$fR<j0pN4hٓFj՜fצ״ToV(MsT2\47ϴؿߘ -sN1HՀ!l]zIJ65c&tݯrْݡ!L3ױ%ף׵no*?D{uܿګյ̖Ǻ8Ӿ+BL"͐ ݚ[,{${\/{(ڷݪ.j6?וک W݀qL9`^ߢ%]I`\ͨJj2xaAӱJyކlz S64D*^wNAIK;5ߑ !׬֩NCiLyf +s!_Ek^-V G׮ձ,YۙX6.cHhs7" \e(נ?1=ۈޙa&THv:t.s&ڠeT3j܁}Jw @ '(OQ$O@lߙk!۝\Rl-wgrNlaީ:rؒcBu؏r[`_f`OV) !Aߏߪ0(ssݲ)V ZM ߂:$:2LT~!ܻ]۔=.}3>"Z*(Z8HkQߡ*nߜߟߊߟ$`{#NMNrf{7ߺ7kߝޟۖ`F.dni7g_}Ky'f]|&N?m`Dv'pYZBv&O|Rk-ڏۛBSQ9ޘވެݎ߿߭߁ޤޯO)=o.FV)JWߓ`Fr ކ)yIߢN:W_0w7Y:[Y?Qm{ sjeg( XޕsYg+#_2 euBY;g߉ߤ߶ߙjaߟߵ)< I<7jRߔ Csq?!( o!3 iC@d*^;`||OK2{MPe ߕߙu[~-:-AQdw%zr_j8Cnz|yX6!Grm=&CJu"@cwhgz9aqi3#F '\<D;MD6JNwR.VM-lW ,E)2ncZwhYR&HB8$;W-.WK0nmbkvMSAM- "ZVgX5hifBooTsowyL[=8&<5c[XWS[H-Te\c*  " 4{]|+wu|cBhP)P8!NY: 4k<oW:FxkCUL)'`: q<3odfZ[)&?Od2ho7ZZV߆G}ܑ݁GP6lN?Hl>y#t6fD/ަ@{\tܹ؞aWπlR6/Hh%qFY1߶pJd)ilu~xYlH^ߝGʄ6ʣ qݔޜ\*I*nQשظ۽4*aVh#1(Ц&ĢŠȦ~3{fz=sTܚD"vt֝ڦs.Wݝ!, @ s#˭ʹGǾ5A@d4u'ߟrFvz3Oh7F %Sb  \ yɲzHƄ*ج;m+ vׇM$XلX=gw[NٚInim Sj;SҶü ޻KT MɑS \S!SߡpP`hא&A%& ¯fw " 6ƼeBrД1ջ"ݺ ?e-W̎Hdqp- ΒĔ4Te CfΎ@/Qڊ]h4lKG=Ƞ(\ =r_èϬ! 1(u%2g_;:̊3qǠ̮C Њ~L4l/AШʹهsK(u \?+N̰?,ʤ,ډB\͕C\`lKOX:țǭ(9PSg1$BYh_05ٳ7h|ԛ~ͻ?U 3_Rd6ݮ { mir_eval-0.8.2/tests/data/separation/ref08/1.wav000066400000000000000000000372541475740344600213730ustar00rootroot00000000000000RIFF>WAVEfmt @>data><5*_b,fD#| feΝPѠ3ĀjvLڨ0SQ<9a\%#g(n'J'kCzvscߞ/2R|!}ޥת kL8/؁(5  mOj_ZVw&LOՓ>|/כ;:v#!OI6 B7E['n / –CEGM) 1J׫BبV~W{tK^hxXzjUM"pG'6ȕ`д6Z aI5ȊΠսcws='{vՒиiril*} jͿVɾ]VO4^Uʓ܈g8YJQ&-x F4џ!R4 2څޢUֿ1(BX~3DuOВSv7*}[e/-JvwOZXڽΙWO-tR> Cڦw[ .,~oւaޕ:߀W~ hӡJ _ATvx5{rW&I0p&a/;J. &vgmU~(k,:yuۦ}8+hGN4LTVڏU)h\ 0Ӵq_Ҙ }؛a̛8OKTjL0ڱמ$jl^Cxkݫm 0 Om$0$r!hl/@ϛY~[W_ЋԺz mY|$6lu$D bx NY&4vޣoՙԓѻҞ۽60۟qޢ'H߉UFs *S ѽ 7΃ x 7Ъ؅aPij l7N_i+APjHP 1W%Mќ۪n>Z3,9 %4Jܹ_5-Rwa. V}_%͍Yھ'Nö6>~/f|ޠ) SvHeP{U.6^Z$>Y<{ޫ!ոt9׋߬6I##i-b>8NދF* GRr'V,UGܽȄWӢR֡JV#S8cݥܒANq1HhJ=߈֙ګY1D;_Jۦ |=ϥ$ʪC}E݆ OlK/V$0 7/S$"qF2@M73\\/Ge2'z3;ޢ޳ސ^s|wnRS#]P`BGsTI,?l- 3 O%v(ߡ:ܧU!L/?6xCݤv4WeOړކO8)ءE ߂Yn7gLipmEaۅҍg>n2& _ N Z`wR؂>Lj-xSzD&nF$~0{Pۄ{q>y-A^Ce zy.9߹GۭPpM*!!9S߭۰/Cep8%}!O yO1Eߠ޻<,?ށTnJ&B{t|%]o/$Y: ivI2}`Rol`ޑ~/5fo_6.5j0YK".=SqZHGd &%$ t.6}[OߔU/@+)A~.A<? LDc%|q{fA|2݄߭ݝ9ffr==p7[-s txwUEHi:P2* U|SCkFk|P!yipre;t(|7Fg.Y<}t%@~dwQFE'2S6 QHg?j`t(=)!, ~p"Wb%#8^}?`t}9&bM;rha {EI%# .b1w{DIvp@ }Y-v&G]glT`GF%q 1;;2*ooukOMF+ #\numd~b?H* 5BL_\p~+O4%$+,83ETfhm}mjfYb}c#=V[y}{wnP1  5Smuv}w_INF++8@^z}~e_c@Ec_W^fZM2  VGQlMPaR\b>:XhzxaPaVHM>=C*' *CM]em~|vqo]FILDVmfqsgcd_JQeZVaenvpcn}vnxrmmpox~v`[cK50/1#)A;@JDVab]jowlskcgsueij\KA?FI7HO4BKF9@\E=ZZc}ynhlPPXUaKOeBFTFHHOa`ivr}|u{skg=[?2/2%5$'@2=91OOR{tay}uf\U]jXOjnl~|xmojAZhN^e]Ud~{nwzvnl`VCKYRQD?>IQ34E' <;57M[GU^]`Xhkahfk{~vn{w\eq_WVORY\ekiozruqVbcKJUK-180*7,/'/;@[OOahSWsimb[h[\koaVah^JL\ZhdXwqYk~yye`jTDSXCMS<8PR5BV>D^JAYiaJVTG`gKL\RYomRRgYPU\PFfhWihZngJQ\Xekjxp{zw|zihm\T8-5:MA4>=HbVWrZEOf`KY`^J-&:D8;<5D[\Tn|gt}fmglqdlvt{Yw}xisvgjaYj_LagaVXhSPTHH39C/DMAPASlPnx^cgtywzl_k_JVNCB%,I@DSgdGnrlmVYSJBSG1LF;C8GE;LO`yrfghjopn`JB?BG@;BNNG=DcdRWhf\uvj}mXbdhchjIWYOfWLNIODEM>HSGKV^^ZccTaeTc[DKSYZ\SRcUX`MT^]ct{~w{ornwsbuuhb^glp{s^fZTi]T^jaNak]fcVXSJKFOa\H;DGPT^[Yphgshfhtylxjp}xai\EQKB7(30,HNKVV]o{rrdgd\TETZPMM]ddhglnm}whri\\ckajqSPgY\oSKVVUKWc_fZH`meoucYvedvqzi^cb\SJHF?FX\Zgmr|{ofZcgKT\>TqOKeb]jrgZhkj~m[ktnklUHkuU]ricakj`kiceWSmqYXge^RBITYP=M_corrrjsrij_[^Xahko^ivdcdVU`^YZU_hje]dfu{jka\`[\TT_Y`neT`eVS`h]jsbfqtmrup~zjlsi[[FCTJ>FV[a`_kmjfothptnlplW`TE`eeVIXTJQfeU]jqltu^osfokjquqsucPP]SNfYOgZMZ\eh^[ftsxvjpobade^OMQZWITdcclh`kyaczw~ihpaT_]ORKMRJYPHYVXZYejempfiuvy~njtposmcdpdSa]R[ZMRZP]bR]jnjpqklXckV_WWaS`]PWFE]ddaisxifstxtqrlcj_GW`TW_d`^UERZP[UAYaR]`X]ed[euxvrsrzjWmeYmbWqmYip]^kkeflknk]ae`VUSWZLT_`]S^rh]dW[m]RZXWZXW]hc`hsz{|{yyjd[ZTHGBAHNSWbe[kn`dhc\mxlljiqmhaTNPOOMW`\\cjdcnqukamnqtkmutpqprkadTMSKJFIDB[XPZY`jcfy{wypurqi\]^[`_aeZXaXDWeX_g_^jskrypupjpd[^\TM\^K\h\giXTa[FShXXpe`wwq|unrth_XOORMGMW_ffmndkkdoqmneadbd_RS]YT^ebYU`W`qb_chhgumi|sgqlcfmja_eaP^gN[mSRZKMZZQR]_akqnxqdsm]\\^OFY][jrjotopnequhpqglnicejg]ajZQUVXKLWHN`X[_VUW^c^\knknnjlomz~tsqpgehWSb[PacYfkcbb[YfhXV`[]kaV[QL_f`eeciehh`jjgoc^ia]lg]cchhizhlrk~HAi,{zwr]8MogD6ZaA=.D:=omY~sZJLK',6:EQ*040$1MM4+?YWlvwqphhP;G?BPKRL7BTB<[hhheglwomep|yxkqnd\8Np^]PDVS1+[aHIS~huh`hvxlj^u~hg^chF?TSWFEc^UT^k`p___R^lkcmlt{mxremcLPa]Q6IIFRfms|y{s{vgg^NOG;7-(%+>FIYbiz|qpnn`RZMGZG8JB=ODE[X]h_hxx|rvgztfzxjrml{iw{f[ZOCFD79B;17?<8;<:===FKB?R[Udmg}mqrw}ltsu~{}gOLC0, "+,7FLMPTPQQFLa[Rdgcun]u|p'U2:! ~zO7E"4+ALoRu"^-pM  EF:YMQhv:$yTwvj")kF+[epW[ b@>14!YpޘYߜgS U 8^\=Wz?a~UH;={؆KޡRm-@dt>OmIF(ZY">2PH=&j:wڰp"D,fQg9v7Ou>"p>x,{\8BOٽ>Kݮc-]݅!c#}_+dvSM}Ny> \I ,Iw&mZD*ߍ~5m):fٕߵ1YuzRKXS-'?8o%BdP7tCFז,&Eؚ9)HnE-D{dqowbpqf[PNxkl*;֗ͨOK#Y-ߒ!C)EY/} nnWL~^=޵`xGO|&AA /z6,Waquxlsq `5lW [S~Ыe,wXכܑ)تy:@/~=0^:D[SKkja qh#  QBnԧeh޶٩5ε$rOwBCYxWG("+>I< Ͷy"`8'&C5/`F2^Y3n= V7 ZI ӂȽ.ӹ)Ӱb aVS/Vj: A)SP-|}ɀM! ~j@ F{ M8 :b%5n$wZܔ/kWg7 xuM=" 0ܟڅۜ A߄ >߇mfy46; #W\E ,q WAVEfmt @>data>e3߼nzLޝAߖVޕ{{ބOi޾ުދIHk4Fބ l<߸`5߹`޽ܜp@952܉yݗݭ"jgo!߷ߺL߄B1ݒݧ݅1ݜ'ަ4gOHߎ&8ޮމyG9޴(,MSP*ސސyT'-sް.i0=dk4ݴޭtߤ߇8ުާގTݖ݅ݗݠݓ{kݕހ޿޸ޯxߨ~ޣQ&s޵$ ޷ޮR$DdhP޹%sގwcbmގުޚހރތ޳ޛކޖުުތeP=:]wނތ}ޟ޶޸޼ިކނބpd~ޕޗެ޶އpO@OML`aqޖޝ޴"5(ޣރ[7%"*72*4H]oށސޞ޺ޯޜވ|{sov}zyއމހse_JDYQGZWTlrޠ޲޼ްޝޣޜޛޢޜތ}ކޅsupkކޜގނތޚ޼޷޺޼޻ީ{YOLOO75RE8Ksޒޚޞޞޡ޳޹ުޙ|byާ޿ުދ{ކޖޤ޶ޫޒލޓޚޛޛޥ޴޼޸ޱޮ޳޿ްޱ޳ޕ|hS?4 #0CUPMTiޖ޷޿޸ޭޱ޸ާޓއކޟ޲ައbB>OSN9.Gert}ގޥ޹޸޷޸޵޵ަޙޖލފޔޤޢޛޟޛޔޝޘxnxv~ދބoa\ey}qkuއޑޑޓޔޕޡޫްޮުޱ޹޵ުޢޝޚދvcRRY^c_OCJRTY_hwވޓޔޓޕޙޓފnjmg_[Y_p}ޅމހށސޖލ~}ވޓޛޠަިޫ޳޾޻ޮޫޥޣޮ޺޶ަޖފޅށygUTX\e_MJNPUZcjorkijpywsxxzރމޒޘޕސމނ}{yy~ހ}}ފޟުޮޮ޲޽޵ެިޠޝޘޒބvtmhikr|wvy{ށxmomku}ހހހހxnpzujffiqދޓޕޒޗޘޏޓޜޝޚގނނފސޚޤޥު޴޺޵ަޝޢޥޭޣ޻!ޭb6Lސ޹ޝ^6Bރ޸ޅbvޭ޳މou~ރ{W-#Jރޝޗގމގޛިޢވw~މޑޏވ~xށށvfQD?S|ޕޓޗޣޤީޮާޖޕޮ޸ގޑެ޵޼޺޳ޣދ~u{އވއkZqރމރuޤ޻޸޸޵ުޯް{)/cސޅ[FVލ޿ޢށތޥެޥޅM,2C[qirާޫޏވޖޟޤޛޏފޟޤޤ޴޳޳ޫިޯޭކ^>6GUސީo8Unށޯޯޖoޢޤޚރ[fTZpb^gt~ކޖޤޤޫޥޗzއzSrfR@QoQjst޲ޗ޼޳޻ުސޥ}ދޫy_onXWiT;Uޢޢl{b|ޜ޿m_ޑސޜލxމު޿ެޥހ\Zހޞsއބބޏ>EM>4-Hiޔmލޑ޶w ޗ߃޶4ކoTުnގ޲ގޱޜާނށޓXހޭdޓޫf|feޫގe;Qi2pހTqލާޘrod^ޑ2hދvs]yޛUc޵eޅްކޕޙޡޙލދމޟޠޚތ޵ީ޼ޅoUSާV޺XtW[޶M޴qUeުލލކ޶mޔeYގzHVޢbކ_hޝޣޫ{ޏޝތ!<ޠxvޕހe޷Yށލ޻ދޢރއXmkޔjpީ=ލޚd޹ނLމސ޻ްޜޒްޠ޼Oއ5F޳aiwނސ+ޏޘAޠވZ(ޢiD=ފh?ށޛހޚx\ީޚmPްޡ޵]tޒޅތވ^޿ޢ7yWކޣޖޠkހިޚޒBmU޶އm޻ޭ޴ި ޢމ޳ߝ޸ިށSޗ=ޗ?pުނUޔvޢިލ޴ުޫ:}vޤutތޖ%ޢg{)ިdޞJރc7ޟތ ߩXޗހ_ޛޫޘ޵މސު*ޟ.ހwGީ6ޒ޿ނާJޱ[އޒޯޅOn=4ނ}Q4V@-3gyyުޝޛކޤ[ނhLޘ|ޓވ~"ވޘޖMThߖ=޷3*<޵޼pޯ`߯n ޚ|EރKgޟޫt_ޫޠiaw ^ޟI2 30ދ;޴^ ߛEޡ1fKcފX߫ޙ޻8-ވRN޾ނ0ޡޜ޳16fJmޥ6) ߙ&޾ލ޻*P<*)߽ބlލQ ޘfa 5+ސߴ4I޵%QݮK}ޮUߣ߄YSZYgj޸+ޣ0߭2~޵|ްݽm@vVݬpZߕݒVa{1dcޅ޻)"ߍݿlyBޔ BUߟ\;`Iތ;{FZSޱ*a޶޻Cސ޹ޅހ"މޢއbn }rH^rWߑGg ݬݦ(ݙܝhݎݠݣXޤ89ޅ' ޠ޴`ޘ)D߻ kq' ^OԮ՘Rkw%߉6Xޱ݅gQ&,iݍ xfuY޺Z;ub6=%g٢VӸ ޼a%}Qt>k"@֢)4زPmVc&0=CR*I"@$WPԽԫs ބ, \Y2U R4\ٛ[|ݍg9!pW**+ JB"ܫ' M@5MGwgN:ډԺ#ϻԒڷً،ل݆miޢްNT3E׾jFn0rt4?10L/b+ܮՇRʨ\Ԩ8iٖSh G׹AkQiosCʴRB~هz,pT,t0vtX۔(0[>rպ~ޓ P}Zr؃t _%'{R(+Fe\ۈpOۙܳ)no-r\ϳӌ*7Ͻ7*maR xviȓ[ʸϨ ܳfcّ2W+z.3?=K#Tאx|OK=ր%$2@ZL;*4̕ȸ*ˢԴٵۗ؜Q;w֜uˣӐߪGT@VӶաҎϨɐOиa ]ޡEXZAsz}ILa<ӹR q٪Џej#Η6(JE7ٿҁaOٗڣؚױ_ݸ@Sۑ!հdQd_xeb̀lFӒc*+׶ېo0w S}ڲ+(Z܎|֯*ٯ%Kӟ7خфEz@DӶؿy\-޸*'rǴ/ ۏu ]EISҠӈ[ '[2cΗͷ8[ҫpm+TOE H:2Ϗ©êǷ<9 {ڋZvޑ/׳ϸ"vϿgվ׋FR&bIڒȉĈӶ߸zݝjFUlp>6$YQ ׎+y2ڹ1 \B nqދ*ߔ\Dߚ}R; Feҧ/=rFY\_ \;cxz xN$ܼaL*(+Պԁ\ւcڦۯۿN'ڙ!,G=؊֟nوU ׁ.,bK֮ 0ٙA.ڮ Qs,aݴϠczX֜,Jָ3ZZݚB*ޗۄܼr^ίCMf؈X49JlDz{֤҄lJ҉՚ڇd t߀ ۜDTC4΄TѶָݠ9׈7?Γʸ\ցޔߛtސA\׾A]C;ߢJ&6%hB4XG[:+>͠PX,%6_:|21lւЪ Pfչڿmޫ6pd)|@/i ~6ֱ܇ۇf!Mtxqޔ?LۮYӄ9l/ґqݵJ/H>G;Eϕʞ$XL0[*0ܿ ޶ڽJӄ{Ӥ=Dp$Z9J%׼ʏȦoop Hp)q޲ߓnr{>!{sU+*OӾֺޭkݣr >^ͳ^Ƶm мӣ 9+ 7?b4zدխ&11{ *ժ֟OuPL-4U[ 5ǍD8ѩ$-(J2`ӆ?٬Ԕb`'xa  Wcߠ^ү̋>O8{ |uex{[{.Q.y8BEMOK2lНV0ؤطܳk'`#R+[3^ ʁQ XgQh.htn+ڧՌϐяУ=ѦoۄUskzav@Yڅ"oƒɨF_bUP0%GNkӛ/Sf:*6:A/*0ZǻSZ6Uoއ?x*Lu#'1OK|բΔ4J˪a4%eaIuxY8ξ&6:Nʧlݬ NZhQT!KԨ̓lj1Ƚ?'Tކ3O"0;bUHLlΙ2ưWώ`[C/ aiz ,}ΙסִoR*{x$kPЎʬƝXwl͏\|F$K&]D U)ˬa ֟i}g֫ҝ͡ƈ")2މ`%%9_[ۮ~J̓˸ˤͳ. ݈^? /&qc`Ҫ#x) 2IḋQ\cjyvGߎdv͸S̗Ͳ̉@ \?R 7ݰ5͒IWŰr^̚Qv߾3`*QQ%یwцу,6̛) ֍q2"o.jmנψ_"AFpmىΔɠ @Ћ2ކZA6d^uB'r̵Ҙo~J"*Di޵εͧ׊Ҁ` !%Pp@mqVxU^jЩ-7(ϟ]̱ύ՝\48K ߽֧՛ͪ7DT\ܶ^Y]~RZћ6wv:ޫ W7 "qܸd׆Ѭ~;e;ӵݨ\jl$57H8w\Sφ̔'Ӧځl;/^^Ty$գt|nXҒ<@ٯܟrߛ6;sfDٹiΜ̴̎ n=bQ+:d!ԪշX:jڮ^}nyzk!aз͊ ЉծݴHd=a?B6ֺԡEڲvJ%)Xzq+B]ϣlц ~aW~K.B0"ӭաP׉ٱڦXe mMDq.3xIT}?"׿PjA3mNw.V+w/c߽^rһA*/޷V|l&R݆܋#"ש1;}ׯ}ݣނ{2T/ܥUֹτҺԩ2-TUL6߽E۟D;ٶB=Gظz:9Cdqڹطi|3}{LB3%oJPPޥyrQcLۜgwKfݜ00G0ktg׫׷_2Cށ!rhFb8v/ݏިa(ߩXގIae޿ߒޚq޿ްީd^~:^<s#߃Y_߃`ݖhݏ݂݆mގެC0ޤ݌޼OMLށm5߾ޫ/*N[ݖ>ܝݵ ܞPDvVIfn޹5. t@ߏޟߋ$  US߆<ܟb8۟#t=ܫwޕT߂=KV+@JLݥWެ, /ޑN#-qބފ?ܼܢiA:t^޽ 6J>Z?ߜޕASݖݒݓxݍލ߹GސO)|@Sܷ{ݮ܄sޢNA\޽ߘߗ_Kj[c߀ߏߘ]ނd߈߿C ޮ]ݡޢބ^ްH(ޔ?޽73jK޾Zm݀ݱݍBߍߺ޼{RF8ޑ sޕݠݍ.O*6+C,:Kޑޯ&6t<)X޲޿jYޒޛޑފޝގ<ݶݤ8*ީޔwjdޔu y2ފaޑ޽ޞCފދ{޽ލ]R޺ݙR<1 QR޵ބށ}N@ޞQU-މHގޫ޶޶6ߘޞ7/hyM:Bނ`ޞ9܆doݞݸ[:B߷ވި!޻2޷G,߸^uތjہR$uږړܯ5MB3m;pzP- #Hn~E܅wpi֝:٢ڴj .'M_ܥژ&ړE#'su?X@פՋn-ڬGn*\js? חP[2)@b] "Wނ״إFORxJ)`@BCB'C?j"_ڂmEs\0Gg5ֶllϷφϲ,۱tE@=n$|6ڦ)]\Mڮ-܊PuٞĻɷȱc˓0~`]1&I!) `OۡӡZ<1ЍsΗ%EFopp)?mܛ֎ʦȀBȥafڼss#N syW޻;I:OލޝޖۙW"wм˛@Fܡ" MLPGiң=3ƿkͬI)TT$QݯܙSٯ}j+/ѿM< =qCWvwmZԀ{JȧȲȴj$cvA4޷|ղ1{ @L#QBлԡ؋ٸ'TJߕۻէZv/EgbB46JXpk7X׮_?ݏ<5.03ݫBԠ3~݀yAֈ0Zr5;ܡ>4!;QHJуNԴT~yދJ-۳jz3!FٽԧθRn_Mc`Iێ&[ӑг<иM>Ih@T6M-HQ^/xұ˿t2Ί8۪a%{6u:ӬҀRCIмVӃ޳#1j6C2b!ܓOڦPҔ\͛D0ږ۴1_2OAI&Pո y` "$}JF/NPsWچڿٱ#4aܶ-O۳۸q 1~Jy +Xcڊٴܺe\'o Pb:ڐو, ޓ1<P.޿۹=3ِ lڻܧIk4 GBygٖض٣ڲ=ݐlvA/߮{(L|&}3ߟ^9QׂvW,_\!w8e&ޔ܆ܐޥcރk Bh jݰݧ{6ݝ߈޸<<, y޾ݢ"ِCN:۪۟.1>%߭H 0޼+fXZP?ښ ws1PiߥRIh t}ާM܋ڮ Z՛ոՏ3ؼڔِܲ[;UP2޻ٕ![٤8۸v `!@Lcގ|n!ߜިޠހrݏ~ X0ޚl6֔]#ԣ&AGQ8ߦrpa $߀ݲ$5!ކmݕ aܦ%ݹ&kzގlݒߴmir_eval-0.8.2/tests/data/separation/ref09/000077500000000000000000000000001475740344600205025ustar00rootroot00000000000000mir_eval-0.8.2/tests/data/separation/ref09/0.wav000066400000000000000000000372541475740344600213730ustar00rootroot00000000000000RIFF>WAVEfmt @>data>llllmlllllllllllllmlllllllmllllllllllmmllllllllllllllmllllmlllllllllmlllmlllllllllmllllmlllmmllllmlllllllllllllllllllllllllllllllllllllllllllllmllmlllllllllllllmlmmlllllmllllllllllllllllkllllllmmlllllllllllllllllllmllllmllmlllllllllllllllllllllllllllllllllllmmlllllllllllllllllllllllmlllllllllllmmllllmlllllllllllllllllmmllllllllmlllllllllllmlllmlmllllllllllllllllllllllllllllllllllllllllllklllllllllllllllmlklmllllllllllllmlllllllmlllllllmllllklmlllllmllllllllllmlllllllllllmlllmllllllllllllllllllllmlllllmlllllllllllllllkllllllmmllmllllllllllllmmlllmlllmllllmllllmllllllmlllllllllllmmlllllllllllmllllllllllmmllllllllllllllllllllllmllmlllllmlllllllllllmlllllmllllllllmmllllmmllllmllllmlllllllmllllllllllllllllmllllllllllllllllllllmllllllllllmlllllllllmmllllllmllmlllmmmlllllllllllllllllllmlllllllllllllllllllllllllllllllllllllllllllllllmlllllllllllllllllllllllllllmlkllllllllmllllllllmmllmllllllllllllllllmmlllllllllmllllllllllmmlllmllmlllllllllllkllmllllllllllmlllllllllmllllmlllllllllllllllmllllllllllllllllllllllllllllllllllmlllllmlllllllllllllllllmllmknjmmhy..P7Buv) SP"\'{3XLgLj&v"=L54WQKELG9AI-MuZeLjqC]!.hD2v3.d5#5R$w&M.Ok'g5b'2X=;S\H6"V-pN?>iv9p{b}dfeEu>v>{<-3fM]><Ajo ;}>BfR:nN2|e<6HE}29#U K+@z;'r3 p7 |-z l}Ch2\$a;qU sXacW{rVQOy8f5lGYY tQj&xIebS-Rh;n*/ II40;e>@^y{')2OSj= 4*\}*MgOV#K?E>du-9"0fL'R #-8ul8TQoPQ5E L,_+$b s-4z2{Z~b%u ZM!ZY0Rs{^ ?`~4j)t6^)fLNv): UT%D\} 13xa2_t@Zo% 8vt_CIb_CLE5gMn@F$qln_Ej;JkaiT'$bHxr!m;1{ ^{P9%&[24K1)sHOwP/,e9L}'eٞEtZ { 'tpȸ# $L ̝^2!" %ΰW-(J)'H)67x&}eDr,:67. a*39P%MN|8z֑A{*{GOEH>3$Z>* G4ODM3(/ȱ٘1gksQC ڳ, $30D`0>8J˲_0`\3 9)N&.a.)MKr6lKFlh?U j Rϸ1HJIpYKC:oΧ2+" #Bo.UZ7:wZ_A R'ԪvRs䞹9NY< eXJbh崼' K HDЪAV-W<+@S < ي( VNމߔ|A]1ʯ=NZV *֫'#G5GӖB` 3$GeD ۢ̊ ׍5zD1c#3p}zR  qs<^jnɤfޅJa0̓63[ [#Y qڢ1U[)uo Z( mg7yUV%?B²,O g4ruIϋüveUgU# '8 |٦_ԨۄĿXĕ QY3"Y8xɆ)" Pw? kؙC(\ƚFZk"^;߂۫4 !u 2B]ǻY-[$ay/2>$?a Cp\yI0Hݪ$O<~[$ t۲CG4P 'U[nuw%_ *tJCJ )<40BA{qhQg}?_E~eo \BPupRu2t$L.* ]n.5Q}k^0VXm UCAI %&WIVl}im_>T(F/]i_ jdo$FU0P|/D;o8v?fas# ul d#0y; > Gq}2~?EwS^05<V^0ߠH t{)؎M,`ٸϬsތ _M5&yo`<ٸi wb)z 3!655р3q0?} pۧ5&xWQx-t3 k:QE-F" M55NRYs+bď-/3 -;!k7sU;q e8JOyA!uz2{CXUl^up9gE ؋}CXo " uP%ClU}??Pk(#H^R !"х1He R:X-Kcgk88l.-ZQGk ݻ> :W!X d P#%lf,e9l!t$h%v~=:7C7Zs BeR %~g[wCRW7*IV~x`ap;XXKy:;SG (1G]7e#vg=7U!<2lUJ 9sGGiudpj\xYdXb3]$3k~(& LDfjri~X "$9=IR7LOHjtE"4?#'%IORYzwp"GOcgNlT3K(.HmbN1(:mQwsPWnyhsqfd5 #00*L(4]ehSOJ10$&4 b1*?f><7rE6SVR!Um|QniZo**`XGk[?%TDKTo58@M('6Q_20 SR(sat&eJq;>o]j{j[U\k eUFds.MtpHWTm'<#98N>GNf |m  3Z$ByKf۾',g+9<,-. 56Щϵˈ}A!AYUVI{* fvQ#+D"4<tPC")J0-PƧ,@"Œ9d*10i+Ljd~աe&۬w?a' ACY@K(6]zO ޖRO *T6I$ˆs9|?bׯۍE ;]FN'ujUi.0U)~.#aѣ]8i'.V,!pl߁Y#b)S<ݳv ";97q2}u{ܔ؉Кf16%&A"X2V=|~iK Q #(()##rg@[_n>U; օΛW.0-3,({jv3@52ߴ3|W .-, C.0MSݹ[ئu[(R/-G*L?tݯU؅F&E-0 2)I]۾/׹u<|* ,.$jI#ٖظ*dl(,/6+-`Y0[(%Uiֶ5@8-=5 <ڹ^l<'ڙҤ ܣ/796c>MLx%sݕ٭.?׃hP,==>']/Uۻ2V"N߂mجڍ2Bhb#==m?m/hۄޗ܋6ڂޏ 2@<8! jةӳ*ٖdjإDغo`$@ B<0lyՊdq!un.B72 .x̽èӄ#c3p ?9@-20mzG$&CݜJk}e">5-%?*۟˒^I֞|@P8)!( 8jRΆ۾Pԃӆ܂MhFLE O1 դ(Di7u!35 $9%c]B ʺЦ kif;Z)(0%0 W.FN{ZJְx +x֑Z$X%)#U#$ פЀ޴LO,&VS 8P4a7֩ĄKm_ %_!;hѫ 6 1Ϧ&գ5 Vk TӽS] ڬ̅PW'X wͩ'ޚ^}6~`_,`2*  EЮ}!%5jb/se qa4׸KFRK!UU'0b,/l'<oޔF&N^ޡi3q+"]GFKS%ڍ {8݋fhʒT / S1{R% ۗـv<#  ڻ<8wz  !]&h ڢ3[)tR% :?ѕڒ,p)9.q"}`-Bi]܁r3Wُ3|Y: !&"t2 ,W؉{*moHl] le`"/tءRqG]8Tr)>&?f B+ V Wq]'lgSں/5!  D o ؝&֟"dKb p re5|} ;OIsmLc}% T ?3OEFBJK.p|XG*\#;_ubEOYvqfqL ?ߡތ e O gsP)!>Ly%7Yh,#dN  hIw!U""f W\r}jFPR LDDr_ T&V)/19)_5bd8LI,-Z %v2 gw|WW)5-P\_yO` ,P&>O{N{i,WtoWt:%9sVP Q!F>M4Jd~ 4d*VN'?3`Z;.K M[WM?I&@*VYM-e_1]'ueFD"/a:*Ly8N:ILo^hw=!EYo AsRd2 8@D=C.{UFRfim!8#NUQ}/~s\.,PNj0#Q @QI ?W"b9l GVrKpk5gN|pTK=:=]~$)>#(aE p(Y|a ?z{+c {qf[["'` 0 file_sets = list(zip(ref_files, est_files, sco_files)) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize( "metric", [ mir_eval.alignment.absolute_error, mir_eval.alignment.percentage_correct, mir_eval.alignment.percentage_correct_segments, ( lambda ref_ts, est_ts: mir_eval.alignment.percentage_correct_segments( ref_ts, est_ts, duration=max(np.max(ref_ts), np.max(est_ts)) ) ), mir_eval.alignment.karaoke_perceptual_metric, ], ) @pytest.mark.parametrize( "est_alignment, pred_alignment", [ ( np.array([[1.0, 2.0]]), np.array([[1.0, 2.0]]), ), # alignments must be 1d ndarray ( np.array([[-1.0, 2.0]]), np.array([[1.0, 2.0]]), ), # alignments must be non-negative (np.array([[2.0, 1.0]]), np.array([[1.0, 2.0]])), # alignments must be sorted ( np.array([[1.0, 2.0]]), np.array([[1.0]]), ), # alignments must have the same length ], ) def test_alignment_functions_fail(metric, est_alignment, pred_alignment): metric(est_alignment, pred_alignment) @pytest.fixture def alignment_data(request): ref_f, est_f, sco_f = request.param with open(sco_f) as f: expected_scores = json.load(f) reference_alignments = mir_eval.io.load_events(ref_f) estimated_alignments = mir_eval.io.load_events(est_f) return reference_alignments, estimated_alignments, expected_scores @pytest.mark.parametrize("alignment_data", file_sets, indirect=True) def test_alignment_functions(alignment_data): reference_alignments, estimated_alignments, expected_scores = alignment_data scores = mir_eval.alignment.evaluate(reference_alignments, estimated_alignments) assert scores.keys() == expected_scores.keys() for metric in scores: assert np.allclose(scores[metric], expected_scores[metric], atol=A_TOL) mir_eval-0.8.2/tests/test_beat.py000066400000000000000000000103301475740344600170200ustar00rootroot00000000000000""" Unit tests for mir_eval.beat """ import numpy as np import json import mir_eval import glob import pytest A_TOL = 1e-12 # Path to the fixture files REF_GLOB = "data/beat/ref*.txt" EST_GLOB = "data/beat/est*.txt" SCORES_GLOB = "data/beat/output*.json" ref_files = sorted(glob.glob(REF_GLOB)) est_files = sorted(glob.glob(EST_GLOB)) sco_files = sorted(glob.glob(SCORES_GLOB)) assert len(ref_files) == len(est_files) == len(sco_files) > 0 file_sets = list(zip(ref_files, est_files, sco_files)) @pytest.fixture def beat_data(request): ref_f, est_f, sco_f = request.param with open(sco_f) as f: expected_scores = json.load(f) reference_beats = mir_eval.io.load_events(ref_f) estimated_beats = mir_eval.io.load_events(est_f) return reference_beats, estimated_beats, expected_scores def test_trim_beats(): # Construct dummy beat times [0., 1., ...] dummy_beats = np.arange(10, dtype=np.float64) # We expect trim_beats to remove all beats < 5s expected_beats = np.arange(5, 10, dtype=np.float64) assert np.allclose(mir_eval.beat.trim_beats(dummy_beats), expected_beats) @pytest.mark.parametrize( "metric", [ mir_eval.beat.f_measure, mir_eval.beat.cemgil, mir_eval.beat.goto, mir_eval.beat.p_score, mir_eval.beat.continuity, mir_eval.beat.information_gain, ], ) def test_beat_empty_warnings(metric): with pytest.warns(UserWarning, match="Reference beats are empty."): metric(np.array([]), np.arange(10)) with pytest.warns(UserWarning, match="Estimated beats are empty."): metric(np.arange(10), np.array([])) with pytest.warns(UserWarning, match="beats are empty."): assert np.allclose(metric(np.array([]), np.array([])), 0) @pytest.mark.parametrize( "metric", [ mir_eval.beat.f_measure, mir_eval.beat.cemgil, mir_eval.beat.goto, mir_eval.beat.p_score, mir_eval.beat.continuity, mir_eval.beat.information_gain, ], ) @pytest.mark.parametrize( "beats", [ np.array([[1.0, 2.0]]), # beats must be a 1d array np.array([1e10, 1e11]), # beats must be not huge np.array([2.0, 1.0]), # must be sorted ], ) @pytest.mark.xfail(raises=ValueError) def test_beat_fail(metric, beats): metric(beats, beats) @pytest.mark.parametrize( "metric", [ mir_eval.beat.f_measure, mir_eval.beat.cemgil, mir_eval.beat.goto, mir_eval.beat.p_score, mir_eval.beat.continuity, mir_eval.beat.information_gain, ], ) def test_beat_perfect(metric): beats = np.arange(10, dtype=np.float64) assert np.allclose(metric(beats, beats), 1) @pytest.mark.parametrize("beat_data", file_sets, indirect=True) def test_beat_functions(beat_data): reference_beats, estimated_beats, expected_scores = beat_data # Compute scores scores = mir_eval.beat.evaluate(reference_beats, estimated_beats) # Compare them assert scores.keys() == expected_scores.keys() for metric in scores: assert np.allclose(scores[metric], expected_scores[metric], atol=A_TOL) # Unit tests for specific behavior not covered by the above def test_goto_proportion_correct(): # This covers the case when over 75% of the beat tracking is correct, and # more than 3 beats are incorrect assert mir_eval.beat.goto( np.arange(100), np.append(np.arange(80), np.arange(80, 100) + 0.2) ) @pytest.mark.parametrize( "metric", [mir_eval.beat.p_score, mir_eval.beat.continuity, mir_eval.beat.information_gain], ) def test_warning_on_one_beat(metric): # This tests the metrics where passing only a single beat raises a warning # and returns 0 with pytest.warns(UserWarning, match="Only one reference beat"): metric(np.array([10]), np.arange(10)) with pytest.warns(UserWarning, match="Only one estimated beat"): metric(np.arange(10), np.array([10])) def test_continuity_edge_cases(): # There is some special-case logic for when there are few beats assert np.allclose( mir_eval.beat.continuity(np.array([6.0, 6.0]), np.array([6.0, 7.0])), 0.0 ) assert np.allclose( mir_eval.beat.continuity(np.array([6.0, 6.0]), np.array([6.5, 7.0])), 0.0 ) mir_eval-0.8.2/tests/test_chord.py000066400000000000000000000507571475740344600172250ustar00rootroot00000000000000""" Unit tests for mir_eval.chord """ import mir_eval import numpy as np import pytest import glob import json A_TOL = 1e-12 # Path to the fixture files REF_GLOB = "data/chord/ref*.lab" EST_GLOB = "data/chord/est*.lab" SCORES_GLOB = "data/chord/output*.json" ref_files = sorted(glob.glob(REF_GLOB)) est_files = sorted(glob.glob(EST_GLOB)) sco_files = sorted(glob.glob(SCORES_GLOB)) assert len(ref_files) == len(est_files) == len(sco_files) > 0 file_sets = list(zip(ref_files, est_files, sco_files)) @pytest.fixture def chord_data(request): ref_f, est_f, sco_f = request.param with open(sco_f) as f: expected_scores = json.load(f) # Load in reference melody ref_intervals, ref_labels = mir_eval.io.load_labeled_intervals(ref_f) # Load in estimated melody est_intervals, est_labels = mir_eval.io.load_labeled_intervals(est_f) return ref_intervals, ref_labels, est_intervals, est_labels, expected_scores @pytest.mark.parametrize( "pitch, semitone", [("Gbb", 5), ("G", 7), ("G#", 8), ("Cb", 11), ("B#", 0)] ) def test_pitch_class_to_semitone_valid(pitch, semitone): assert mir_eval.chord.pitch_class_to_semitone(pitch) == semitone @pytest.mark.parametrize("pitch", ["Cab", "#C", "bG"]) @pytest.mark.xfail(raises=mir_eval.chord.InvalidChordException) def test_pitch_class_to_semitone_fail(pitch): mir_eval.chord.pitch_class_to_semitone(pitch) @pytest.mark.parametrize( "degree, semitone", [ ("b7", 10), ("#3", 5), ("1", 0), ("b1", -1), ("#7", 12), ("bb5", 5), ("11", 17), ("#13", 22), ], ) def test_scale_degree_to_semitone(degree, semitone): assert mir_eval.chord.scale_degree_to_semitone(degree) == semitone @pytest.mark.parametrize("degree", ["7b", "4#", "77", "15"]) @pytest.mark.xfail(raises=mir_eval.chord.InvalidChordException) def test_scale_degree_to_semitone(degree): mir_eval.chord.scale_degree_to_semitone(degree) @pytest.mark.parametrize( "degree, bitmap, modulo, length", [ ("3", [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0], True, 12), ("*3", [0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0], True, 12), ("b1", [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], True, 12), ("9", [0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], True, 12), ("9", [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], False, 12), ("9", [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], False, 15), ], ) def test_scale_degree_to_bitmap(degree, bitmap, modulo, length): assert np.allclose( mir_eval.chord.scale_degree_to_bitmap(degree, modulo=modulo, length=length), bitmap, ) @pytest.mark.parametrize( "label", ["C", "Eb:min/5", "A#:dim7", "B:maj(*1,*5)/3", "A#:sus4", "A:(9,11)"] ) def test_validate_chord_label(label): # For valid labels, calling the function without an error = pass mir_eval.chord.validate_chord_label(label) @pytest.mark.parametrize( "label", ["C::maj", "C//5", "C((4)", "C5))", "C:maj(*3/3", "Cmaj*3/3)", "asdf"] ) @pytest.mark.xfail(raises=mir_eval.chord.InvalidChordException) def test_validate_bad_chord_label(label): mir_eval.chord.validate_chord_label(label) @pytest.mark.parametrize( "label, split", [ ("C", ["C", "maj", set(), "1"]), ("B:maj(*1,*3)/5", ["B", "maj", {"*1", "*3"}, "5"]), ("Ab:min/b3", ["Ab", "min", set(), "b3"]), ("N", ["N", "", set(), ""]), ("G:(3)", ["G", "", {"3"}, "1"]), ], ) def test_split(label, split): assert mir_eval.chord.split(label) == split @pytest.mark.parametrize( "label, split", [("C", ["C", "maj", set(), "1"]), ("C:minmaj7", ["C", "min", {"7"}, "1"])], ) def test_split_extended(label, split): # Test with reducing extended chords mir_eval.chord.split(label, reduce_extended_chords=True) == split @pytest.mark.xfail(raises=mir_eval.chord.InvalidChordException) def test_split_fail(): # Test that an exception is raised when a chord with an omission but no # quality is supplied mir_eval.chord.split("C(*5)") # Arguments are root, quality, extensions, bass @pytest.mark.parametrize( "label, split", [ ("F#", ("F#", "", None, "")), ("F#:hdim7", ("F#", "hdim7", None, "")), ("F#:(*b3,4)", ("F#", "", ["*b3", "4"], "")), ("F#/b7", ("F#", "", None, "b7")), ("F#:(*b3,4)/b7", ("F#", "", ["*b3", "4"], "b7")), ("F#:hdim7/b7", ("F#", "hdim7", None, "b7")), ("F#:hdim7(*b3,4)/b7", ("F#", "hdim7", ["*b3", "4"], "b7")), ], ) def test_join(label, split): # Test is relying on implicit parameter ordering here: root, quality, extensions, bass assert mir_eval.chord.join(*split) == label @pytest.mark.parametrize( "bitmap, root, expected_bitmap", [ ([1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0], 0, [1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0]), ([1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0], 5, [1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0]), ( [1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0], 11, [0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1], ), ], ) def test_rotate_bitmaps_to_roots(bitmap, root, expected_bitmap): ans = mir_eval.chord.rotate_bitmaps_to_roots([bitmap], [root]) assert np.all(ans == [expected_bitmap]) @pytest.mark.parametrize( "label, e_root, e_interval, e_bass, reduce, strict", [ ("B:maj(*1,*3)/5", 11, [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0], 7, False, False), ("G:dim", 7, [1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0], 0, False, False), ("C:(3)/3", 0, [1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0], 4, False, False), ("A:9/b3", 9, [1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0], 3, False, False), ("G:dim(4)/6", 7, [1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0], 9, False, False), ("A:9", 9, [1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0], 0, True, False), ], ) def test_chord_encode(label, e_root, e_interval, e_bass, reduce, strict): root, intervals, bass = mir_eval.chord.encode( label, reduce_extended_chords=reduce, strict_bass_intervals=strict ) assert root == e_root, (root, e_root) assert np.all(intervals == e_interval), (intervals, e_interval) assert bass == e_bass, (bass, e_bass) @pytest.mark.xfail(raises=mir_eval.chord.InvalidChordException) def test_chord_encode_fail(): # Non-chord bass notes *must* be explicitly named as extensions when # strict_bass_intervals == True mir_eval.chord.encode( "G:dim(4)/6", reduce_extended_chords=False, strict_bass_intervals=True ) def test_encode_many(): """Does all of the logic for checking encode_many""" labels = ["B:maj(*1,*3)/5", "B:maj(*1,*3)/5", "N", "C:min", "C:min"] expected_roots = [11, 11, -1, 0, 0] expected_intervals = [ [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0], [1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0], ] expected_basses = [7, 7, -1, 0, 0] roots, intervals, basses = mir_eval.chord.encode_many(labels) assert np.all(roots == expected_roots) assert np.all(intervals == expected_intervals) assert np.all(basses == expected_basses) def __check_one_metric(metric, ref_label, est_label, score): """Checks that a metric function produces score given ref_label and est_label""" # We provide a dummy interval. We're just checking one pair # of labels at a time. assert metric([ref_label], [est_label]) == score def __check_not_comparable(metric, ref_label, est_label): """Checks that ref_label is not comparable to est_label by metric""" # Try to produce the warning with pytest.warns( UserWarning, match="No reference chords were comparable to estimated chords, returning 0.", ): score = mir_eval.chord.weighted_accuracy( metric([ref_label], [est_label]), np.array([1]) ) # And confirm that the metric is 0 assert np.allclose(score, 0) # TODO(ejhumphrey): Comparison functions lacking unit tests. # test_root() @pytest.mark.parametrize( "ref_label, est_label, score", [ ("N", "N", 1.0), ("C:maj", "N", 0.0), ("C:maj", "C:aug", 0.0), ("C:maj", "C:dim", 0.0), ("C:min", "C:dim", 0.0), ("C:maj", "C:5", 0.0), ("C:maj", "C:sus4", 0.0), ("G:min", "G:sus2", 0.0), ("C:maj", "G:maj", 0.0), ("C:min", "C:hdim7", 0.0), ("C:min", "C:min7", 1.0), ("C:maj", "C:maj6", 1.0), ("F:maj", "F:min6", 0.0), ("C:maj7", "C:minmaj7", 1.0), ("A:maj", "A:7", 1.0), ("A:maj", "A:9", 1.0), ], ) def test_mirex(ref_label, est_label, score): __check_one_metric(mir_eval.chord.mirex, ref_label, est_label, score) @pytest.mark.parametrize("ref, est", [("C:5", "C:maj"), ("X", "N")]) def test_mirex_nocomp(ref, est): __check_not_comparable(mir_eval.chord.mirex, ref, est) @pytest.mark.parametrize( "ref_label, est_label, score", [ ("N", "N", 1.0), ("C:maj", "N", 0.0), ("C:maj", "C:aug", 1.0), ("C:maj", "C:dim", 0.0), ("C:min", "C:dim", 1.0), ("C:maj", "C:sus4", 1.0), ("G:min", "G:sus2", 0.0), ("C:maj", "G:maj", 0.0), ("C:min", "C:hdim7", 1.0), ("C:min", "C:min7", 1.0), ("C:maj", "C:maj6", 1.0), ("F:maj", "F:min6", 0.0), ("C:maj", "C:minmaj7", 0.0), ("A:maj", "A:7", 1.0), ("A:maj", "A:9", 1.0), ], ) def test_thirds(ref_label, est_label, score): __check_one_metric(mir_eval.chord.thirds, ref_label, est_label, score) def test_thirds_nocomp(): __check_not_comparable(mir_eval.chord.thirds, "X", "N") @pytest.mark.parametrize( "ref_label, est_label, score", [ ("C:maj/5", "C:sus4/5", 1.0), ("G:min", "G:min/b3", 0.0), ("C:maj", "C:maj/5", 0.0), ("C:min/b3", "C:hdim7/b3", 1.0), ("C:min", "C:dim", 1.0), ], ) def test_thirds_inv(ref_label, est_label, score): __check_one_metric(mir_eval.chord.thirds_inv, ref_label, est_label, score) def test_thirds_inv_nocomp(): __check_not_comparable(mir_eval.chord.thirds_inv, "X", "N") @pytest.mark.parametrize( "ref_label, est_label, score", [ ("C:min", "C:min7", 1.0), ("C:maj", "C:7", 1.0), ("C:maj", "C:aug", 0.0), ("C:min", "C:dim", 0.0), ("C:maj", "C:sus2", 0.0), ("C:maj", "C:sus4", 0.0), ("G:min", "G:minmaj7", 1.0), ("C:maj", "G:maj", 0.0), ("C:min", "C:hdim7", 0.0), ("C:min", "C:min6", 1.0), ], ) def test_triads(ref_label, est_label, score): __check_one_metric(mir_eval.chord.triads, ref_label, est_label, score) def test_triads_nocomp(): __check_not_comparable(mir_eval.chord.triads, "X", "N") @pytest.mark.parametrize( "ref_label, est_label, score", [ ("C:maj/5", "C:maj7/5", 1.0), ("G:min", "G:min7/5", 0.0), ("C:maj", "C:7/5", 0.0), ("C:min/b3", "C:min6/b3", 1.0), ("C:min/b3", "C:dim/b3", 0.0), ], ) def test_triads_inv(ref_label, est_label, score): __check_one_metric(mir_eval.chord.triads_inv, ref_label, est_label, score) def test_triads_inv_nocomp(): __check_not_comparable(mir_eval.chord.triads_inv, "X", "N") @pytest.mark.parametrize( "ref_label, est_label, score", [ ("C:min", "C:min7", 0.0), ("C:maj", "C:maj6", 0.0), ("C:7", "C:9", 1.0), ("C:maj7", "C:maj7/5", 1.0), ("C:sus2", "C:sus2/2", 1.0), ("C:7/3", "C:11/b7", 1.0), ("G:min", "G:sus2", 0.0), ("C:maj", "G:maj", 0.0), ("C:min", "C:hdim7", 0.0), ("C:min", "C:minmaj7", 0.0), ], ) def test_tetrads(ref_label, est_label, score): __check_one_metric(mir_eval.chord.tetrads, ref_label, est_label, score) def test_tetrads_nocomp(): __check_not_comparable(mir_eval.chord.tetrads, "X", "N") @pytest.mark.parametrize( "ref_label, est_label, score", [ ("C:maj7/5", "C:maj7/3", 0.0), ("G:min", "G:min/b3", 0.0), ("C:7/5", "C:13/5", 1.0), ("C:min/b3", "C:hdim7/b3", 0.0), ("C:min9", "C:min7", 1.0), ], ) def test_tetrads_inv(ref_label, est_label, score): __check_one_metric(mir_eval.chord.tetrads_inv, ref_label, est_label, score) def test_tetrads_inv_nocomp(): __check_not_comparable(mir_eval.chord.tetrads_inv, "X", "N") @pytest.mark.parametrize( "ref_label, est_label, score", [ ("N", "N", 1.0), ("C:maj", "N", 0.0), ("C:maj", "C:aug", 0.0), ("C:min", "C:dim", 0.0), ("G:maj7", "G", 1.0), ], ) def test_majmin(ref_label, est_label, score): __check_one_metric(mir_eval.chord.majmin, ref_label, est_label, score) @pytest.mark.parametrize("ref_label, est_label", [("C:aug", "C:maj"), ("X", "N")]) def test_majmin_nocomp(ref_label, est_label): __check_not_comparable(mir_eval.chord.majmin, ref_label, est_label) @pytest.mark.parametrize( "ref_label, est_label, score", [ ("C:maj/5", "C:sus4/5", 0.0), ("G:min", "G:min/b3", 0.0), ("C:maj/5", "C:maj/5", 1.0), ("C:min7", "C:min", 1.0), ("G:min/b3", "G:min/b3", 1.0), ("C:maj7/5", "C:maj/5", 1.0), ("C:7", "C:maj", 1.0), ], ) def test_majmin_inv(ref_label, est_label, score): __check_one_metric(mir_eval.chord.majmin_inv, ref_label, est_label, score) @pytest.mark.parametrize( "ref_label, est_label", [ ("C:hdim7/b3", "C:min/b3"), ("C:maj/4", "C:maj/4"), ("C:maj/2", "C:sus2/2"), ("X", "N"), ], ) def test_majmin_inv_nocomp(ref_label, est_label): __check_not_comparable(mir_eval.chord.majmin_inv, ref_label, est_label) @pytest.mark.parametrize( "ref_label, est_label, score", [ ("C:min", "C:min7", 0.0), ("C:maj", "C:maj6", 0.0), ("C:7", "C:9", 1.0), ("C:maj7", "C:maj7/5", 1.0), ("C:7/3", "C:11/b7", 1.0), ("G:min", "G:sus2", 0.0), ("C:maj", "G:maj", 0.0), ("C:7", "C:maj7", 0.0), ], ) def test_sevenths(ref_label, est_label, score): __check_one_metric(mir_eval.chord.sevenths, ref_label, est_label, score) @pytest.mark.parametrize( "ref_label, est_label", [("C:sus2", "C:sus2/2"), ("C:hdim7", "C:hdim7"), ("X", "N")] ) def test_sevenths_nocomp(ref_label, est_label): __check_not_comparable(mir_eval.chord.sevenths, ref_label, est_label) @pytest.mark.parametrize( "ref_label, est_label, score", [ ("C:maj7/5", "C:maj7/3", 0.0), ("G:min", "G:min/b3", 0.0), ("C:7/5", "C:13/5", 1.0), ("C:min7/b7", "C:min7/b7", 1.0), ], ) def test_sevenths_inv(ref_label, est_label, score): __check_one_metric(mir_eval.chord.sevenths_inv, ref_label, est_label, score) @pytest.mark.parametrize( "ref_label, est_label", [("C:dim7/b3", "C:dim7/b3"), ("X", "N")] ) def test_sevenths_inv_nocomp(ref_label, est_label): __check_not_comparable(mir_eval.chord.sevenths_inv, ref_label, est_label) def test_directional_hamming_distance(): ref_ivs = np.array([[0.0, 1.0], [1.0, 2.0], [2.0, 3.0]]) est_ivs = np.array([[0.0, 0.9], [0.9, 1.8], [1.8, 2.5]]) dhd_ref_to_est = (0.1 + 0.2 + 0.5) / 3.0 dhd_est_to_ref = (0.0 + 0.1 + 0.2) / 2.5 dhd = mir_eval.chord.directional_hamming_distance assert np.allclose(dhd_ref_to_est, dhd(ref_ivs, est_ivs)) assert np.allclose(dhd_est_to_ref, dhd(est_ivs, ref_ivs)) assert np.allclose(0, dhd(ref_ivs, ref_ivs)) assert np.allclose(0, dhd(est_ivs, est_ivs)) ivs_overlap_all = np.array([[0.0, 1.0], [0.9, 2.0]]) ivs_overlap_one = np.array([[0.0, 1.0], [0.9, 2.0], [2.0, 3.0]]) with pytest.raises(ValueError): dhd(ivs_overlap_all, est_ivs) with pytest.raises(ValueError): dhd(ivs_overlap_one, est_ivs) def test_segmentation_functions(): ref_ivs = np.array([[0.0, 2.0], [2.0, 2.5], [2.5, 3.2]]) est_ivs = np.array([[0.0, 3.0], [3.0, 3.5]]) true_oseg = 1.0 - 0.2 / 3.2 true_useg = 1.0 - (1.0 + 0.2) / 3.5 true_seg = min(true_oseg, true_useg) assert np.allclose(true_oseg, mir_eval.chord.overseg(ref_ivs, est_ivs)) assert np.allclose(true_useg, mir_eval.chord.underseg(ref_ivs, est_ivs)) assert np.allclose(true_seg, mir_eval.chord.seg(ref_ivs, est_ivs)) ref_ivs = np.array([[0.0, 2.0], [2.0, 2.5], [2.5, 3.2]]) est_ivs = np.array([[0.0, 2.0], [2.0, 2.5], [2.5, 3.2]]) true_oseg = 1.0 true_useg = 1.0 true_seg = 1.0 assert np.allclose(true_oseg, mir_eval.chord.overseg(ref_ivs, est_ivs)) assert np.allclose(true_useg, mir_eval.chord.underseg(ref_ivs, est_ivs)) assert np.allclose(true_seg, mir_eval.chord.seg(ref_ivs, est_ivs)) ref_ivs = np.array([[0.0, 2.0], [2.0, 2.5], [2.5, 3.2]]) est_ivs = np.array([[0.0, 3.2]]) true_oseg = 1.0 true_useg = 1 - 1.2 / 3.2 true_seg = min(true_oseg, true_useg) assert np.allclose(true_oseg, mir_eval.chord.overseg(ref_ivs, est_ivs)) assert np.allclose(true_useg, mir_eval.chord.underseg(ref_ivs, est_ivs)) assert np.allclose(true_seg, mir_eval.chord.seg(ref_ivs, est_ivs)) ref_ivs = np.array([[0.0, 2.0], [2.0, 2.5], [2.5, 3.2]]) est_ivs = np.array([[3.2, 3.5]]) true_oseg = 1.0 true_useg = 1.0 true_seg = 1.0 assert np.allclose(true_oseg, mir_eval.chord.overseg(ref_ivs, est_ivs)) assert np.allclose(true_useg, mir_eval.chord.underseg(ref_ivs, est_ivs)) assert np.allclose(true_seg, mir_eval.chord.seg(ref_ivs, est_ivs)) def test_merge_chord_intervals(): intervals = np.array([[0.0, 1.0], [1.0, 2.0], [2.0, 3], [3.0, 4.0], [4.0, 5.0]]) labels = ["C:maj", "C:(1,3,5)", "A:maj", "A:maj7", "A:maj7/3"] assert np.allclose( np.array([[0.0, 2.0], [2.0, 3], [3.0, 4.0], [4.0, 5.0]]), mir_eval.chord.merge_chord_intervals(intervals, labels), ) def test_weighted_accuracy(): # First, test for a warning on empty beats with pytest.warns(UserWarning, match="No nonzero weights, returning 0"): score = mir_eval.chord.weighted_accuracy( np.array([1, 0, 1]), np.array([0, 0, 0]) ) # And that the metric is 0 assert np.allclose(score, 0) # len(comparisons) must equal len(weights) comparisons = np.array([1, 0, 1]) weights = np.array([1, 1]) with pytest.raises(ValueError): mir_eval.chord.weighted_accuracy(comparisons, weights) # Weights must all be positive comparisons = np.array([1, 1]) weights = np.array([-1, -1]) with pytest.raises(ValueError): mir_eval.chord.weighted_accuracy(comparisons, weights) # Make sure accuracy = 1 and 0 when all comparisons are True and False resp comparisons = np.array([1, 1, 1]) weights = np.array([1, 1, 1]) score = mir_eval.chord.weighted_accuracy(comparisons, weights) assert np.allclose(score, 1) comparisons = np.array([0, 0, 0]) score = mir_eval.chord.weighted_accuracy(comparisons, weights) assert np.allclose(score, 0) @pytest.mark.parametrize("chord_data", file_sets, indirect=True) def test_chord_functions(chord_data): ref_intervals, ref_labels, est_intervals, est_labels, expected_scores = chord_data # Compute scores scores = mir_eval.chord.evaluate( ref_intervals, ref_labels, est_intervals, est_labels ) # Compare them assert scores.keys() == expected_scores.keys() for metric in scores: assert np.allclose(scores[metric], expected_scores[metric], atol=A_TOL) def test_quality_to_bitmap(): # Test simple case assert np.all( mir_eval.chord.quality_to_bitmap("maj") == np.array([1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0]) ) @pytest.mark.xfail(raises=mir_eval.chord.InvalidChordException) @pytest.mark.parametrize("quality", ["maj5", "2", "#7"]) def test_quality_to_bitmap_fail(quality): # Check exceptions for qualities not in the QUALITIES list mir_eval.chord.quality_to_bitmap(quality) def test_validate(): # Test that the validate function raises the appropriate errors and # warnings with pytest.warns() as w: # First, test for warnings on empty labels mir_eval.chord.validate([], []) assert len(w) == 2 assert issubclass(w[-1].category, UserWarning) assert str(w[-1].message) == "Estimated labels are empty" assert issubclass(w[-2].category, UserWarning) assert str(w[-2].message) == "Reference labels are empty" # Test that error is thrown on different-length labels with pytest.raises(ValueError): mir_eval.chord.validate([], ["C"]) @pytest.mark.parametrize("quality", list(mir_eval.chord.QUALITIES.keys())) def test_chord_qualities(quality): if len(quality) > 0: mir_eval.chord.encode(f"C:{quality}", reduce_extended_chords=True) else: mir_eval.chord.encode("C", reduce_extended_chords=True) mir_eval-0.8.2/tests/test_display.py000066400000000000000000000313431475740344600175610ustar00rootroot00000000000000#!/usr/bin/env python """Unit tests for the display module""" # For testing purposes, clobber the rcfile import matplotlib import matplotlib.pyplot as plt import numpy as np import pytest import mir_eval import mir_eval.display from mir_eval.io import load_labeled_intervals from mir_eval.io import load_valued_intervals from mir_eval.io import load_labeled_events from mir_eval.io import load_ragged_time_series from mir_eval.io import load_wav from packaging import version # Workaround to enable test skipping on older matplotlibs where we know it to be problematic MPL_VERSION = version.parse(matplotlib.__version__) OLD_MPL = not (MPL_VERSION >= version.parse("3.8.0")) # Workaround for old freetype builds with our image fixtures FT_VERSION = version.parse(matplotlib.ft2font.__freetype_version__) OLD_FT = not (FT_VERSION >= version.parse("2.10")) STYLE = "default" @pytest.mark.mpl_image_compare( baseline_images=["test_display_segment"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_segment(): plt.figure() # Load some segment data intervals, labels = load_labeled_intervals("data/segment/ref00.lab") # Plot the segments with no labels mir_eval.display.segments(intervals, labels, text=False) # Draw a legend plt.legend(loc="upper right") return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_segment_text"], extensions=["png"], style=STYLE, tolerance=6, ) @pytest.mark.xfail(OLD_MPL, reason=f"matplotlib version < {MPL_VERSION}", strict=False) def test_display_segment_text(): plt.figure() # Load some segment data intervals, labels = load_labeled_intervals("data/segment/ref00.lab") # Plot the segments with no labels mir_eval.display.segments(intervals, labels, text=True) return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_labeled_intervals"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_labeled_intervals(): plt.figure() # Load some chord data intervals, labels = load_labeled_intervals("data/chord/ref01.lab") # Plot the chords with nothing fancy mir_eval.display.labeled_intervals(intervals, labels) return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_labeled_intervals_noextend"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_labeled_intervals_noextend(): plt.figure() # Load some chord data intervals, labels = load_labeled_intervals("data/chord/ref01.lab") # Plot the chords with nothing fancy ax = plt.axes() ax.set_yticklabels([]) mir_eval.display.labeled_intervals( intervals, labels, label_set=[], extend_labels=False, ax=ax ) return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_labeled_intervals_compare"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_labeled_intervals_compare(): plt.figure() # Load some chord data ref_int, ref_labels = load_labeled_intervals("data/chord/ref01.lab") est_int, est_labels = load_labeled_intervals("data/chord/est01.lab") # Plot reference and estimates using label set extension mir_eval.display.labeled_intervals( ref_int, ref_labels, alpha=0.5, label="Reference" ) mir_eval.display.labeled_intervals(est_int, est_labels, alpha=0.5, label="Estimate") plt.legend(loc="upper right") return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_labeled_intervals_compare_noextend"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_labeled_intervals_compare_noextend(): plt.figure() # Load some chord data ref_int, ref_labels = load_labeled_intervals("data/chord/ref01.lab") est_int, est_labels = load_labeled_intervals("data/chord/est01.lab") # Plot reference and estimate, but only use the reference labels mir_eval.display.labeled_intervals( ref_int, ref_labels, alpha=0.5, label="Reference" ) mir_eval.display.labeled_intervals( est_int, est_labels, extend_labels=False, alpha=0.5, label="Estimate" ) plt.legend(loc="upper right") return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_labeled_intervals_compare_common"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_labeled_intervals_compare_common(): plt.figure() # Load some chord data ref_int, ref_labels = load_labeled_intervals("data/chord/ref01.lab") est_int, est_labels = load_labeled_intervals("data/chord/est01.lab") label_set = list(sorted(set(ref_labels) | set(est_labels))) # Plot reference and estimate with a common label set mir_eval.display.labeled_intervals( ref_int, ref_labels, label_set=label_set, alpha=0.5, label="Reference" ) mir_eval.display.labeled_intervals( est_int, est_labels, label_set=label_set, alpha=0.5, label="Estimate" ) plt.legend(loc="upper right") return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_hierarchy_nolabel"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_hierarchy_nolabel(): plt.figure() # Load some chord data int0, lab0 = load_labeled_intervals("data/hierarchy/ref00.lab") int1, lab1 = load_labeled_intervals("data/hierarchy/ref01.lab") # Plot reference and estimate with a common label set mir_eval.display.hierarchy([int0, int1], [lab0, lab1]) plt.legend(loc="upper right") return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_hierarchy_label"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_hierarchy_label(): plt.figure() # Load some chord data int0, lab0 = load_labeled_intervals("data/hierarchy/ref00.lab") int1, lab1 = load_labeled_intervals("data/hierarchy/ref01.lab") # Plot reference and estimate with a common label set mir_eval.display.hierarchy([int0, int1], [lab0, lab1], levels=["Large", "Small"]) plt.legend(loc="upper right") return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_pitch_hz"], extensions=["png"], style=STYLE, tolerance=6, ) @pytest.mark.xfail(OLD_FT, reason=f"freetype version < {FT_VERSION}", strict=False) def test_display_pitch_hz(): plt.figure() ref_times, ref_freqs = load_labeled_events("data/melody/ref00.txt") est_times, est_freqs = load_labeled_events("data/melody/est00.txt") # Plot pitches on a Hz scale mir_eval.display.pitch(ref_times, ref_freqs, unvoiced=True, label="Reference") mir_eval.display.pitch(est_times, est_freqs, unvoiced=True, label="Estimate") plt.legend(loc="upper left") return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_pitch_midi"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_pitch_midi(): plt.figure() times, freqs = load_labeled_events("data/melody/ref00.txt") # Plot pitches on a midi scale with note tickers mir_eval.display.pitch(times, freqs, midi=True) mir_eval.display.ticker_notes() return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_pitch_midi_hz"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_pitch_midi_hz(): plt.figure() times, freqs = load_labeled_events("data/melody/ref00.txt") # Plot pitches on a midi scale with note tickers mir_eval.display.pitch(times, freqs, midi=True) mir_eval.display.ticker_pitch() return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_multipitch_hz_unvoiced"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_multipitch_hz_unvoiced(): plt.figure() times, pitches = load_ragged_time_series("data/multipitch/est01.txt") # Plot pitches on a midi scale with note tickers mir_eval.display.multipitch(times, pitches, midi=False, unvoiced=True) return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_multipitch_hz_voiced"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_multipitch_hz_voiced(): plt.figure() times, pitches = load_ragged_time_series("data/multipitch/est01.txt") mir_eval.display.multipitch(times, pitches, midi=False, unvoiced=False) return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_multipitch_midi"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_multipitch_midi(): plt.figure() ref_t, ref_p = load_ragged_time_series("data/multipitch/ref01.txt") est_t, est_p = load_ragged_time_series("data/multipitch/est01.txt") # Plot pitches on a midi scale with note tickers mir_eval.display.multipitch(ref_t, ref_p, midi=True, alpha=0.5, label="Reference") mir_eval.display.multipitch(est_t, est_p, midi=True, alpha=0.5, label="Estimate") plt.legend(loc="upper left") return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_piano_roll"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_piano_roll(): plt.figure() ref_t, ref_p = load_valued_intervals("data/transcription/ref04.txt") est_t, est_p = load_valued_intervals("data/transcription/est04.txt") mir_eval.display.piano_roll(ref_t, ref_p, label="Reference", alpha=0.5) mir_eval.display.piano_roll( est_t, est_p, label="Estimate", alpha=0.5, facecolor="r" ) plt.legend(loc="upper right") return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_piano_roll_midi"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_piano_roll_midi(): plt.figure() ref_t, ref_p = load_valued_intervals("data/transcription/ref04.txt") est_t, est_p = load_valued_intervals("data/transcription/est04.txt") ref_midi = mir_eval.util.hz_to_midi(ref_p) est_midi = mir_eval.util.hz_to_midi(est_p) mir_eval.display.piano_roll(ref_t, midi=ref_midi, label="Reference", alpha=0.5) mir_eval.display.piano_roll( est_t, midi=est_midi, label="Estimate", alpha=0.5, facecolor="r" ) plt.legend(loc="upper right") return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_ticker_midi_zoom"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_ticker_midi_zoom(): plt.figure() plt.plot(np.arange(3)) mir_eval.display.ticker_notes() return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_separation"], extensions=["png"], style=STYLE, tolerance=6, ) @pytest.mark.xfail(OLD_FT, reason=f"freetype version < {FT_VERSION}", strict=False) @pytest.mark.skip() def test_display_separation(): plt.figure() x0, fs = load_wav("data/separation/ref05/0.wav") x1, fs = load_wav("data/separation/ref05/1.wav") x2, fs = load_wav("data/separation/ref05/2.wav") mir_eval.display.separation([x0, x1, x2], fs=fs) return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_separation_label"], extensions=["png"], style=STYLE, tolerance=6, ) @pytest.mark.xfail(OLD_FT, reason=f"freetype version < {FT_VERSION}", strict=False) @pytest.mark.skip() def test_display_separation_label(): plt.figure() x0, fs = load_wav("data/separation/ref05/0.wav") x1, fs = load_wav("data/separation/ref05/1.wav") x2, fs = load_wav("data/separation/ref05/2.wav") mir_eval.display.separation([x0, x1, x2], fs=fs, labels=["Alice", "Bob", "Carol"]) plt.legend(loc="upper right") return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_events"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_events(): plt.figure() # Load some event data beats_ref = mir_eval.io.load_events("data/beat/ref00.txt")[:30] beats_est = mir_eval.io.load_events("data/beat/est00.txt")[:30] # Plot both with labels mir_eval.display.events(beats_ref, label="reference") mir_eval.display.events(beats_est, label="estimate") plt.legend(loc="upper right") return plt.gcf() @pytest.mark.mpl_image_compare( baseline_images=["test_display_labeled_events"], extensions=["png"], style=STYLE, tolerance=6, ) def test_display_labeled_events(): plt.figure() # Load some event data beats_ref = mir_eval.io.load_events("data/beat/ref00.txt")[:10] labels = list("abcdefghijklmnop") # Plot both with labels mir_eval.display.events(beats_ref, labels) return plt.gcf() @pytest.mark.xfail(raises=ValueError) def test_display_pianoroll_nopitch_nomidi(): # Issue 214 mir_eval.display.piano_roll([[0, 1]]) mir_eval-0.8.2/tests/test_hierarchy.py000066400000000000000000000220131475740344600200640ustar00rootroot00000000000000""" Unit tests for mir_eval.hierarchy """ import glob import re import json import numpy as np import scipy.sparse import mir_eval import pytest A_TOL = 1e-12 @pytest.mark.parametrize("window", [5, 10, 15, 30, 90, None]) @pytest.mark.parametrize("frame_size", [0.1, 0.5, 1.0]) def test_tmeasure_pass(window, frame_size): # The estimate here gets none of the structure correct. ref = [[[0, 30]], [[0, 15], [15, 30]]] # convert to arrays ref = [np.asarray(_) for _ in ref] est = ref[:1] # The estimate should get 0 score here scores = mir_eval.hierarchy.tmeasure(ref, est, window=window, frame_size=frame_size) for k in scores: assert k == 0.0 # The reference should get a perfect score here scores = mir_eval.hierarchy.tmeasure(ref, ref, window=window, frame_size=frame_size) for k in scores: assert k == 1.0 def test_tmeasure_warning(): # Warn if there are missing boundaries from one layer to the next ref = [[[0, 5], [5, 10]], [[0, 10]]] ref = [np.asarray(_) for _ in ref] with pytest.warns( UserWarning, match="Segment hierarchy is inconsistent at level 1" ): mir_eval.hierarchy.tmeasure(ref, ref) def test_tmeasure_fail_span(): # Does not start at 0 ref = [[[1, 10]], [[1, 5], [5, 10]]] ref = [np.asarray(_) for _ in ref] with pytest.raises(ValueError): mir_eval.hierarchy.tmeasure(ref, ref) # Does not end at the right time ref = [[[0, 5]], [[0, 5], [5, 6]]] ref = [np.asarray(_) for _ in ref] with pytest.raises(ValueError): mir_eval.hierarchy.tmeasure(ref, ref) # Two annotaions of different shape ref = [[[0, 10]], [[0, 5], [5, 10]]] ref = [np.asarray(_) for _ in ref] est = [[[0, 15]], [[0, 5], [5, 15]]] est = [np.asarray(_) for _ in est] with pytest.raises(ValueError): mir_eval.hierarchy.tmeasure(ref, est) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize( "window, frame_size", [(None, -1), (None, 0), (15, -1), (15, 0), (15, 30), (30, -1), (30, 0), (30, 60)], ) def test_tmeasure_fail_frame_size(window, frame_size): ref = [[[0, 60]], [[0, 30], [30, 60]]] ref = [np.asarray(_) for _ in ref] mir_eval.hierarchy.tmeasure(ref, ref, window=window, frame_size=frame_size) @pytest.mark.parametrize("frame_size", [0.1, 0.5, 1.0]) def test_lmeasure_pass(frame_size): # The estimate here gets none of the structure correct. ref = [[[0, 30]], [[0, 15], [15, 30]]] ref_lab = [["A"], ["a", "b"]] # convert to arrays ref = [np.asarray(_) for _ in ref] est = ref[:1] est_lab = ref_lab[:1] # The estimate should get 0 score here scores = mir_eval.hierarchy.lmeasure( ref, ref_lab, est, est_lab, frame_size=frame_size ) for k in scores: assert k == 0.0 # The reference should get a perfect score here scores = mir_eval.hierarchy.lmeasure( ref, ref_lab, ref, ref_lab, frame_size=frame_size ) for k in scores: assert k == 1.0 def test_lmeasure_warning(): # Warn if there are missing boundaries from one layer to the next ref = [[[0, 5], [5, 10]], [[0, 10]]] ref = [np.asarray(_) for _ in ref] ref_lab = [["a", "b"], ["A"]] with pytest.warns( UserWarning, match="Segment hierarchy is inconsistent at level 1" ): mir_eval.hierarchy.lmeasure(ref, ref_lab, ref, ref_lab) def test_lmeasure_fail_span(): # Does not start at 0 ref = [[[1, 10]], [[1, 5], [5, 10]]] ref_lab = [["A"], ["a", "b"]] ref = [np.asarray(_) for _ in ref] with pytest.raises(ValueError): mir_eval.hierarchy.lmeasure(ref, ref_lab, ref, ref_lab) # Does not end at the right time ref = [[[0, 5]], [[0, 5], [5, 6]]] ref = [np.asarray(_) for _ in ref] with pytest.raises(ValueError): mir_eval.hierarchy.lmeasure(ref, ref_lab, ref, ref_lab) # Two annotations of different shape ref = [[[0, 10]], [[0, 5], [5, 10]]] ref = [np.asarray(_) for _ in ref] est = [[[0, 15]], [[0, 5], [5, 15]]] est = [np.asarray(_) for _ in est] with pytest.raises(ValueError): mir_eval.hierarchy.lmeasure(ref, ref_lab, est, ref_lab) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize("frame_size", [-1, 0]) def test_lmeasure_fail_frame_size(frame_size): ref = [[[0, 60]], [[0, 30], [30, 60]]] ref = [np.asarray(_) for _ in ref] ref_lab = [["A"], ["a", "b"]] mir_eval.hierarchy.lmeasure(ref, ref_lab, ref, ref_lab, frame_size=frame_size) SCORES_GLOB = "data/hierarchy/output*.json" sco_files = sorted(glob.glob(SCORES_GLOB)) @pytest.fixture def hierarchy_outcomes(request): sco_f = request.param with open(sco_f) as fdesc: expected_scores = json.load(fdesc) window = float(re.match(r".*output_w=(\d+).json$", sco_f).groups()[0]) return expected_scores, window @pytest.mark.parametrize("hierarchy_outcomes", sco_files, indirect=True) def test_hierarchy_regression(hierarchy_outcomes): expected_scores, window = hierarchy_outcomes # Hierarchy data is split across multiple lab files for these tests ref_files = sorted(glob.glob("data/hierarchy/ref*.lab")) est_files = sorted(glob.glob("data/hierarchy/est*.lab")) ref_hier = [mir_eval.io.load_labeled_intervals(_) for _ in ref_files] est_hier = [mir_eval.io.load_labeled_intervals(_) for _ in est_files] ref_ints = [seg[0] for seg in ref_hier] ref_labs = [seg[1] for seg in ref_hier] est_ints = [seg[0] for seg in est_hier] est_labs = [seg[1] for seg in est_hier] outputs = mir_eval.hierarchy.evaluate( ref_ints, ref_labs, est_ints, est_labs, window=window ) assert outputs.keys() == expected_scores.keys() for key in expected_scores: assert np.allclose(expected_scores[key], outputs[key], atol=A_TOL) def test_count_inversions(): # inversion count = |{(i, j) : a[i] >= b[j]}| a = [2, 4, 6] b = [1, 2, 3, 4] # All inversions (a, b) are: # (2, 1), (2, 2) # (4, 1), (4, 2), (4, 3), (4, 4) # (6, 1), (6, 2), (6, 3), (6, 4) assert mir_eval.hierarchy._count_inversions(a, b) == 10 # All inversions (b, a) are: # (2, 2) # (3, 2) # (4, 2), (4, 4) assert mir_eval.hierarchy._count_inversions(b, a) == 4 # And test with repetitions a = [2, 2, 4] b = [1, 2, 4, 4] # counts: (a, b) # (2, 1), (2, 2) # (2, 1), (2, 2) # (4, 1), (4, 2), (4, 4), (4, 4) assert mir_eval.hierarchy._count_inversions(a, b) == 8 # count: (b, a) # (2, 2), (2, 2) # (4, 2), (4, 2), (4, 4) # (4, 2), (4, 2), (4, 4) assert mir_eval.hierarchy._count_inversions(b, a) == 8 def test_meet(): frame_size = 1 int_hier = [ np.array([[0, 10]]), np.array([[0, 6], [6, 10]]), np.array([[0, 2], [2, 4], [4, 6], [6, 8], [8, 10]]), ] lab_hier = [["X"], ["A", "B"], ["a", "b", "a", "c", "b"]] # Target output meet_truth = np.asarray( [ [3, 3, 2, 2, 3, 3, 1, 1, 1, 1], # (XAa) [3, 3, 2, 2, 3, 3, 1, 1, 1, 1], # (XAa) [2, 2, 3, 3, 2, 2, 1, 1, 3, 3], # (XAb) [2, 2, 3, 3, 2, 2, 1, 1, 3, 3], # (XAb) [3, 3, 2, 2, 3, 3, 1, 1, 1, 1], # (XAa) [3, 3, 2, 2, 3, 3, 1, 1, 1, 1], # (XAa) [1, 1, 1, 1, 1, 1, 3, 3, 2, 2], # (XBc) [1, 1, 1, 1, 1, 1, 3, 3, 2, 2], # (XBc) [1, 1, 3, 3, 1, 1, 2, 2, 3, 3], # (XBb) [1, 1, 3, 3, 1, 1, 2, 2, 3, 3], # (XBb) ] ) meet = mir_eval.hierarchy._meet(int_hier, lab_hier, frame_size) # Is it the right type? assert isinstance(meet, scipy.sparse.csr_matrix) meet = meet.toarray() # Does it have the right shape? assert meet.shape == (10, 10) # Does it have the right value? assert np.all(meet == meet_truth) def test_compare_frame_rankings(): # number of pairs (i, j) # where ref[i] < ref[j] and est[i] >= est[j] ref = np.asarray([1, 2, 3, 3]) # ref pairs (transitive) # (1, 2), (1, 3), (1, 3), (2, 3), (2, 3) # ref pairs (non-transitive) # (1, 2), (2, 3), (2, 3) # Just count the normalizers # No self-inversions are possible from ref to itself inv, norm = mir_eval.hierarchy._compare_frame_rankings(ref, ref, transitive=True) assert inv == 0 assert norm == 5.0 inv, norm = mir_eval.hierarchy._compare_frame_rankings(ref, ref, transitive=False) assert inv == 0 assert norm == 3.0 est = np.asarray([1, 2, 1, 3]) # In the transitive case, we lose two pairs # (1, 3) and (2, 2) -> (1, 1), (2, 1) inv, norm = mir_eval.hierarchy._compare_frame_rankings(ref, est, transitive=True) assert inv == 2 assert norm == 5.0 # In the non-transitive case, we only lose one pair # because (1,3) was not counted inv, norm = mir_eval.hierarchy._compare_frame_rankings(ref, est, transitive=False) assert inv == 1 assert norm == 3.0 # Do an all-zeros test ref = np.asarray([1, 1, 1, 1]) inv, norm = mir_eval.hierarchy._compare_frame_rankings(ref, ref, transitive=True) assert inv == 0 assert norm == 0.0 mir_eval-0.8.2/tests/test_input_output.py000066400000000000000000000171441475740344600206760ustar00rootroot00000000000000"""Unit tests for input/output functions""" import numpy as np import json import mir_eval import warnings import pathlib import tempfile import pytest def test_load_delimited(): # Test for ValueError when a non-string or file handle is passed with pytest.raises(IOError): mir_eval.io.load_delimited(None, [int]) # Test for a value error when the wrong number of columns is passed with tempfile.TemporaryFile("r+") as f: f.write("10 20") f.seek(0) with pytest.raises(ValueError): mir_eval.io.load_delimited(f, [int, int, int]) # Test for a value error on conversion failure with tempfile.TemporaryFile("r+") as f: f.write("10 a 30") f.seek(0) with pytest.raises(ValueError): mir_eval.io.load_delimited(f, [int, int, int]) def test_load_delimited_commented(): with tempfile.TemporaryFile("r+") as f: f.write("; some comment\n10 20\n30 50") f.seek(0) col1, col2 = mir_eval.io.load_delimited(f, [int, int], comment=";") assert np.allclose(col1, [10, 30]) assert np.allclose(col2, [20, 50]) # Rewind and try with the default comment character f.seek(0) with pytest.raises(ValueError): mir_eval.io.load_delimited(f, [int, int]) # Rewind and try with no comment support f.seek(0) with pytest.raises(ValueError): mir_eval.io.load_delimited(f, [int, int], comment=None) def test_load_delimited_nocomment(): with tempfile.TemporaryFile("r+") as f: f.write("10 20\n30 50") f.seek(0) col1, col2 = mir_eval.io.load_delimited(f, [int, int]) assert np.allclose(col1, [10, 30]) assert np.allclose(col2, [20, 50]) # Rewind and try with a different comment char f.seek(0) col1, col2 = mir_eval.io.load_delimited(f, [int, int], comment=";") assert np.allclose(col1, [10, 30]) assert np.allclose(col2, [20, 50]) # Rewind and try with no different comment string f.seek(0) col1, col2 = mir_eval.io.load_delimited(f, [int, int], comment=None) assert np.allclose(col1, [10, 30]) assert np.allclose(col2, [20, 50]) @pytest.mark.parametrize( "file_or_path", ["data/beat/ref01.txt", pathlib.Path("data/beat/ref01.txt")] ) def test_load_delimited_file_or_path(file_or_path): # Tests the load_delimited routine with either a string or a # pathlib.Path object as the first argument data = mir_eval.io.load_delimited(file_or_path, [float]) assert len(data) == 635 def test_load_events(): # Test for a warning when invalid events are supplied with tempfile.TemporaryFile("r+") as f: with pytest.warns(UserWarning, match="Events should be in increasing order."): # Non-increasing is invalid f.write("10\n9") f.seek(0) events = mir_eval.io.load_events(f) # Make sure events were read in correctly assert np.all(events == [10, 9]) def test_load_labeled_events(): # Test for a value error when invalid labeled events are supplied with tempfile.TemporaryFile("r+") as f: with pytest.warns(UserWarning, match="Events should be in increasing order."): # Non-increasing is invalid f.write("10 a\n9 b") f.seek(0) events, labels = mir_eval.io.load_labeled_events(f) # Make sure events were read in correctly assert np.all(events == [10, 9]) # Make sure labels were read in correctly assert labels == ["a", "b"] def test_load_intervals(): # Test for a value error when invalid labeled events are supplied with tempfile.TemporaryFile("r+") as f: with pytest.warns( UserWarning, match="All interval durations must be strictly positive" ): # Non-increasing is invalid f.write("10 9\n9 10") f.seek(0) intervals = mir_eval.io.load_intervals(f) # Make sure intervals were read in correctly assert np.all(intervals == [[10, 9], [9, 10]]) def test_load_labeled_intervals(): # Test for a value error when invalid labeled events are supplied with tempfile.TemporaryFile("r+") as f: with pytest.warns( UserWarning, match="All interval durations must be strictly positive" ): # Non-increasing is invalid f.write("10 9 a\n9 10 b") f.seek(0) intervals, labels = mir_eval.io.load_labeled_intervals(f) # Make sure intervals were read in correctly assert np.all(intervals == [[10, 9], [9, 10]]) assert labels == ["a", "b"] def test_load_valued_intervals(): # Test for a value error when invalid valued events are supplied with tempfile.TemporaryFile("r+") as f: with pytest.warns( UserWarning, match="All interval durations must be strictly positive" ): # Non-increasing is invalid f.write("10 9 5\n9 10 6") f.seek(0) intervals, values = mir_eval.io.load_valued_intervals(f) # Make sure intervals were read in correctly assert np.all(intervals == [[10, 9], [9, 10]]) assert np.all(values == [5, 6]) def test_load_ragged_time_series(): # Test for ValueError when a non-string or file handle is passed with pytest.raises(IOError): mir_eval.io.load_ragged_time_series(None, float, header=False) # Test for a value error on conversion failure with tempfile.TemporaryFile("r+") as f: f.write("10 a 30") f.seek(0) with pytest.raises(ValueError): mir_eval.io.load_ragged_time_series(f, float, header=False) # Test for a value error on invalid time stamp with tempfile.TemporaryFile("r+") as f: f.write("a 10 30") f.seek(0) with pytest.raises(ValueError): mir_eval.io.load_ragged_time_series(f, int, header=False) # Test for a value error on invalid time stamp with header with tempfile.TemporaryFile("r+") as f: f.write("x y z\na 10 30") f.seek(0) with pytest.raises(ValueError): mir_eval.io.load_ragged_time_series(f, int, header=True) with tempfile.TemporaryFile("r+") as f: f.write("#comment\n0 1 2\n3 4\n# comment\n5 6 7") f.seek(0) times, values = mir_eval.io.load_ragged_time_series( f, int, header=False, comment="#" ) assert np.allclose(times, [0, 3, 5]) assert np.allclose(values[0], [1, 2]) assert np.allclose(values[1], [4]) assert np.allclose(values[2], [6, 7]) # Rewind with a wrong comment string f.seek(0) with pytest.raises(ValueError): mir_eval.io.load_ragged_time_series(f, int, header=False, comment="%") # Rewind with no comment string f.seek(0) with pytest.raises(ValueError): mir_eval.io.load_ragged_time_series(f, int, header=False, comment=None) def test_load_tempo(): # Test the tempo loader tempi, weight = mir_eval.io.load_tempo("data/tempo/ref01.lab") assert np.allclose(tempi, [60, 120]) assert weight == 0.5 @pytest.mark.xfail(raises=ValueError) def test_load_tempo_multiline(): tempi, weight = mir_eval.io.load_tempo("data/tempo/bad00.lab") @pytest.mark.xfail(raises=ValueError) def test_load_tempo_badweight(): tempi, weight = mir_eval.io.load_tempo("data/tempo/bad01.lab") def test_load_bad_tempi(): with pytest.warns(UserWarning, match="non-negative numbers"): tempi, weight = mir_eval.io.load_tempo("data/tempo/bad02.lab") mir_eval-0.8.2/tests/test_key.py000066400000000000000000000033561475740344600167070ustar00rootroot00000000000000""" Tests for mir_eval.key """ import mir_eval import pytest import glob import json import numpy as np A_TOL = 1e-12 # Path to the fixture files REF_GLOB = "data/key/ref*.txt" EST_GLOB = "data/key/est*.txt" SCORES_GLOB = "data/key/output*.json" ref_files = sorted(glob.glob(REF_GLOB)) est_files = sorted(glob.glob(EST_GLOB)) sco_files = sorted(glob.glob(SCORES_GLOB)) assert len(ref_files) == len(est_files) == len(sco_files) > 0 file_sets = list(zip(ref_files, est_files, sco_files)) @pytest.mark.parametrize( "good_key", ["C major", "c major", "C# major", "Bb minor", "db minor", "X", "x", "C other"], ) @pytest.mark.parametrize( "bad_key", ["C maj", "Cb major", "C", "K major", "F## minor" "X other", "x minor"] ) def test_key_function_fail(good_key, bad_key): score = mir_eval.key.weighted_score(good_key, good_key) assert score == 1.0 with pytest.raises(ValueError): mir_eval.key.weighted_score(good_key, bad_key) with pytest.raises(ValueError): mir_eval.key.weighted_score(bad_key, good_key) @pytest.fixture def key_data(request): ref_f, est_f, sco_f = request.param with open(sco_f) as f: expected_scores = json.load(f) reference_key = mir_eval.io.load_key(ref_f) estimated_key = mir_eval.io.load_key(est_f) return reference_key, estimated_key, expected_scores @pytest.mark.parametrize("key_data", file_sets, indirect=True) def test_key_functions(key_data): reference_key, estimated_key, expected_scores = key_data # Compute scores scores = mir_eval.key.evaluate(reference_key, estimated_key) # Compare them assert scores.keys() == expected_scores.keys() for metric in scores: assert np.allclose(scores[metric], expected_scores[metric], atol=A_TOL) mir_eval-0.8.2/tests/test_melody.py000066400000000000000000000370071475740344600174100ustar00rootroot00000000000000# CREATED: 4/15/14 9:42 AM by Justin Salamon """ Unit tests for mir_eval.melody """ import numpy as np import json import mir_eval import glob import pytest A_TOL = 1e-12 # Path to the fixture files REF_GLOB = "data/melody/ref*.txt" EST_GLOB = "data/melody/est*.txt" SCORES_GLOB = "data/melody/output*.json" ref_files = sorted(glob.glob(REF_GLOB)) est_files = sorted(glob.glob(EST_GLOB)) sco_files = sorted(glob.glob(SCORES_GLOB)) assert len(ref_files) == len(est_files) == len(sco_files) > 0 file_sets = list(zip(ref_files, est_files, sco_files)) @pytest.fixture def melody_data(request): ref_f, est_f, sco_f = request.param with open(sco_f) as f: expected_scores = json.load(f) # Load in reference melody ref_time, ref_freq = mir_eval.io.load_time_series(ref_f) # Load in estimated melody est_time, est_freq = mir_eval.io.load_time_series(est_f) return ref_time, ref_freq, est_time, est_freq, expected_scores def test_hz2cents(): # Unit test some simple values hz = np.array([0.0, 10.0, 5.0, 320.0, 1420.31238974231]) # Expected cent conversion expected_cent = np.array([0.0, 0.0, -1200.0, 6000.0, 8580.0773605]) assert np.allclose(mir_eval.melody.hz2cents(hz), expected_cent) def test_freq_to_voicing(): # Unit test some simple values hz = np.array([0.0, 100.0, -132.0]) expected_hz = np.array([0.0, 100.0, 132.0]) expected_voicing = np.array([0, 1, 0]) # Check voicing conversion res_hz, res_voicing = mir_eval.melody.freq_to_voicing(hz) assert np.all(res_hz == expected_hz) assert np.all(res_voicing == expected_voicing) # Unit test some simple values where voicing is given hz = np.array([0.0, 100.0, -132.0, 0, 131.0]) voicing = np.array([0.8, 0.0, 1.0, 0.0, 0.5]) expected_hz = np.array([0.0, 100.0, 132.0, 0.0, 131.0]) expected_voicing = np.array([0.0, 0.0, 1.0, 0.0, 0.5]) # Check voicing conversion res_hz, res_voicing = mir_eval.melody.freq_to_voicing(hz, voicing=voicing) assert np.all(res_hz == expected_hz) assert np.all(res_voicing == expected_voicing) def test_constant_hop_timebase(): hop = 0.1 end_time = 0.35 expected_times = np.array([0, 0.1, 0.2, 0.3]) res_times = mir_eval.melody.constant_hop_timebase(hop, end_time) assert np.allclose(res_times, expected_times) def test_resample_melody_series(): # Check for a small example including a zero transition times = np.arange(4) / 35.0 cents = np.array([2.0, 0.0, -1.0, 1.0]) voicing = np.array([1, 0, 1, 1]) times_new = np.linspace(0, 0.08, 9) expected_cents = np.array([2.0, 2.0, 2.0, 0.0, 0.0, 0.0, -0.8, -0.1, 0.6]) expected_voicing = np.array([1, 1, 1, 0, 0, 0, 1, 1, 1]) (res_cents, res_voicing) = mir_eval.melody.resample_melody_series( times, cents, voicing, times_new ) assert np.allclose(res_cents, expected_cents) assert np.allclose(res_voicing, expected_voicing) # Check for a small example including a zero transition - nonbinary voicing times = np.arange(4) / 35.0 cents = np.array([2.0, 0.0, -1.0, 1.0]) voicing = np.array([0.8, 0.0, 0.2, 1.0]) times_new = np.linspace(0, 0.08, 9) expected_cents = np.array([2.0, 2.0, 2.0, 0.0, 0.0, 0.0, -0.8, -0.1, 0.6]) expected_voicing = np.array([0.8, 0.52, 0.24, 0.01, 0.08, 0.15, 0.28, 0.56, 0.84]) (res_cents, res_voicing) = mir_eval.melody.resample_melody_series( times, cents, voicing, times_new ) assert np.allclose(res_cents, expected_cents) assert np.allclose(res_voicing, expected_voicing) def test_resample_melody_series_same_times(): # Check the case where the time bases are identical times = np.array([0.0, 0.1, 0.2, 0.3]) times_new = np.array([0.0, 0.1, 0.2, 0.3]) cents = np.array([2.0, 0.0, -1.0, 1.0]) voicing = np.array([0, 0, 1, 1]) expected_cents = np.array([2.0, 0.0, -1.0, 1.0]) expected_voicing = np.array([False, False, True, True]) (res_cents, res_voicing) = mir_eval.melody.resample_melody_series( times, cents, voicing, times_new ) assert np.allclose(res_cents, expected_cents) assert np.allclose(res_voicing, expected_voicing) # Check the case where the time bases are identical - nonbinary voicing times = np.array([0.0, 0.1, 0.2, 0.3]) times_new = np.array([0.0, 0.1, 0.2, 0.3]) cents = np.array([2.0, 0.0, -1.0, 1.0]) voicing = np.array([0.5, 0.8, 0.9, 1.0]) expected_cents = np.array([2.0, 0.0, -1.0, 1.0]) expected_voicing = np.array([0.5, 0.8, 0.9, 1.0]) (res_cents, res_voicing) = mir_eval.melody.resample_melody_series( times, cents, voicing, times_new ) assert np.allclose(res_cents, expected_cents) assert np.allclose(res_voicing, expected_voicing) def test_to_cent_voicing(): # We'll just test a few values from one of the test annotations ref_file = sorted(glob.glob(REF_GLOB))[0] ref_time, ref_freq = mir_eval.io.load_time_series(ref_file) est_file = sorted(glob.glob(EST_GLOB))[0] est_time, est_freq = mir_eval.io.load_time_series(est_file) ref_v, ref_c, est_v, est_c = mir_eval.melody.to_cent_voicing( ref_time, ref_freq, est_time, est_freq ) # Expected values test_range = np.arange(220, 225) expected_ref_v = np.array([False, False, False, True, True]) expected_ref_c = np.array([0.0, 0.0, 0.0, 6056.8837818916609, 6028.5504583021921]) expected_est_v = np.array([False] * 5) expected_est_c = np.array([5351.3179423647571] * 5) assert np.allclose(ref_v[test_range], expected_ref_v) assert np.allclose(ref_c[test_range], expected_ref_c) assert np.allclose(est_v[test_range], expected_est_v) assert np.allclose(est_c[test_range], expected_est_c) # Test that a 0 is added to the beginning for return_item in mir_eval.melody.to_cent_voicing( np.array([1.0, 2.0]), np.array([440.0, 442.0]), np.array([1.0, 2.0]), np.array([441.0, 443.0]), ): assert len(return_item) == 3 assert return_item[0] == return_item[1] # Test custom voicings ref_time, ref_freq = mir_eval.io.load_time_series(ref_file) _, ref_reward = mir_eval.io.load_time_series("data/melody/reward00.txt") _, est_voicing = mir_eval.io.load_time_series("data/melody/voicingest00.txt") (ref_v, ref_c, est_v, est_c) = mir_eval.melody.to_cent_voicing( ref_time, ref_freq, est_time, est_freq, est_voicing=est_voicing, ref_reward=ref_reward, ) # Expected values test_range = np.arange(220, 225) expected_ref_v = np.array([0.0, 0.0, 0.0, 1.0, 0.3]) expected_ref_c = np.array([0.0, 0.0, 0.0, 6056.8837818916609, 6028.5504583021921]) expected_est_v = np.array([0.2, 0.2, 0.2, 0.2, 0.2]) expected_est_c = np.array([5351.3179423647571] * 5) assert np.allclose(ref_v[test_range], expected_ref_v) assert np.allclose(ref_c[test_range], expected_ref_c) assert np.allclose(est_v[test_range], expected_est_v) assert np.allclose(est_c[test_range], expected_est_c) # We can ignore this warning, which occurs when testing with all-zeros reward @pytest.mark.filterwarnings("ignore:Reference melody has no voiced frames") def test_continuous_voicing_metrics(): ref_time = np.array([0.0, 0.1, 0.2, 0.3]) ref_freq = np.array([440.0, 0.0, 220.0, 220.0]) est_time = np.array([0.0, 0.1, 0.2, 0.3]) est_freq = np.array([440.1, 330.0, 440.0, 330.0]) # test different estimate voicings all_est_voicing = [ np.array([1.0, 0.0, 1.0, 1.0]), # perfect np.array([0.0, 1.0, 0.0, 0.0]), # all wrong np.array([0.5, 0.5, 0.5, 0.5]), # all 0.5 np.array([0.8, 0.2, 0.8, 0.8]), # almost right np.array([0.2, 0.8, 0.2, 0.2]), # almost wrong ] all_expected = [ # perfect { "Voicing Recall": 1.0, "Voicing False Alarm": 0.0, "Raw Pitch Accuracy": 1.0 / 3.0, "Raw Chroma Accuracy": 2.0 / 3.0, "Overall Accuracy": 0.5, }, # all wrong { "Voicing Recall": 0.0, "Voicing False Alarm": 1.0, "Raw Pitch Accuracy": 1.0 / 3.0, "Raw Chroma Accuracy": 2.0 / 3.0, "Overall Accuracy": 0.0, }, # all 0.5 { "Voicing Recall": 0.5, "Voicing False Alarm": 0.5, "Raw Pitch Accuracy": 1.0 / 3.0, "Raw Chroma Accuracy": 2.0 / 3.0, "Overall Accuracy": 0.25, }, # almost right { "Voicing Recall": 0.8, "Voicing False Alarm": 0.2, "Raw Pitch Accuracy": 1.0 / 3.0, "Raw Chroma Accuracy": 2.0 / 3.0, "Overall Accuracy": 0.4, }, # almost wrong { "Voicing Recall": 0.2, "Voicing False Alarm": 0.8, "Raw Pitch Accuracy": 1.0 / 3.0, "Raw Chroma Accuracy": 2.0 / 3.0, "Overall Accuracy": 0.1, }, ] for est_voicing, expected_scores in zip(all_est_voicing, all_expected): actual_scores = mir_eval.melody.evaluate( ref_time, ref_freq, est_time, est_freq, est_voicing=est_voicing ) for metric in actual_scores: assert np.isclose(actual_scores[metric], expected_scores[metric]) # test different rewards all_rewards = [ np.array([0.5, 0.5, 0.5, 0.5]), # uniform np.array([0.3, 0.3, 0.3, 0.3]), # uniform - different number np.array([0.0, 0.0, 0.0, 0.0]), # all zero np.array([1.0, 0.0, 0.0, 0.0]), # one weight np.array([1.0, 0.0, 1.0, 0.0]), # two weights np.array([1.0, 0.0, 0.5, 0.5]), # slightly generous np.array([0.1, 0.0, 0.1, 0.8]), # big penalty ] est_voicing = np.array([1.0, 0.0, 1.0, 1.0]) all_expected = [ # uniform { "Voicing Recall": 1.0, "Voicing False Alarm": 0.0, "Raw Pitch Accuracy": 1.0 / 3.0, "Raw Chroma Accuracy": 2.0 / 3.0, "Overall Accuracy": 0.5, }, # uniform - different number { "Voicing Recall": 1.0, "Voicing False Alarm": 0.0, "Raw Pitch Accuracy": 1.0 / 3.0, "Raw Chroma Accuracy": 2.0 / 3.0, "Overall Accuracy": 0.5, }, # all zero { "Voicing Recall": 1.0, "Voicing False Alarm": 0.75, "Raw Pitch Accuracy": 0.0, "Raw Chroma Accuracy": 0.0, "Overall Accuracy": 0.25, }, # one weight { "Voicing Recall": 1.0, "Voicing False Alarm": 2.0 / 3.0, "Raw Pitch Accuracy": 1.0, "Raw Chroma Accuracy": 1.0, "Overall Accuracy": 0.5, }, # two weights { "Voicing Recall": 1.0, "Voicing False Alarm": 0.5, "Raw Pitch Accuracy": 0.5, "Raw Chroma Accuracy": 1.0, "Overall Accuracy": 0.5, }, # slightly generous { "Voicing Recall": 1.0, "Voicing False Alarm": 0.0, "Raw Pitch Accuracy": 0.5, "Raw Chroma Accuracy": 0.75, "Overall Accuracy": 0.625, }, # big penalty { "Voicing Recall": 1.0, "Voicing False Alarm": 0.0, "Raw Pitch Accuracy": 0.1, "Raw Chroma Accuracy": 0.2, "Overall Accuracy": 0.325, }, ] for ref_reward, expected_scores in zip(all_rewards, all_expected): actual_scores = mir_eval.melody.evaluate( ref_time, ref_freq, est_time, est_freq, est_voicing=est_voicing, ref_reward=ref_reward, ) for metric in actual_scores: assert np.isclose(actual_scores[metric], expected_scores[metric]) def test_voicing_measures_empty(): # We need a special test for voicing_measures because it only takes 2 args with pytest.warns() as w: # First, test for warnings due to empty voicing arrays score = mir_eval.melody.voicing_measures(np.array([]), np.array([])) assert len(w) == 4 assert np.all([issubclass(wrn.category, UserWarning) for wrn in w]) assert [str(wrn.message) for wrn in w] == [ "Reference voicing array is empty.", "Estimated voicing array is empty.", "Reference melody has no voiced frames.", "Estimated melody has no voiced frames.", ] # And that the metric is 0 assert np.allclose(score, 0) def test_voicing_measures_unvoiced(): with pytest.warns() as w: # Also test for a warning when the arrays have non-voiced content mir_eval.melody.voicing_measures(np.ones(10), np.zeros(10)) assert len(w) == 1 assert issubclass(w[-1].category, UserWarning) assert str(w[-1].message) == "Estimated melody has no voiced frames." @pytest.mark.xfail(raises=ValueError) def test_melody_voicing_badlength(): # ref and est voicings must be the same length mir_eval.melody.voicing_measures(np.ones(10), np.ones(11)) @pytest.mark.parametrize( "metric", [ mir_eval.melody.raw_pitch_accuracy, mir_eval.melody.raw_chroma_accuracy, mir_eval.melody.overall_accuracy, ], ) def test_melody_function_empty(metric): with pytest.warns() as w: # First, test for warnings due to empty voicing arrays score = metric(np.array([]), np.array([]), np.array([]), np.array([])) assert len(w) == 6 assert np.all([issubclass(wrn.category, UserWarning) for wrn in w]) assert [str(wrn.message) for wrn in w] == [ "Reference voicing array is empty.", "Estimated voicing array is empty.", "Reference melody has no voiced frames.", "Estimated melody has no voiced frames.", "Reference frequency array is empty.", "Estimated frequency array is empty.", ] # And that the metric is 0 assert np.allclose(score, 0) # Also test for a warning when the arrays have non-voiced content metric(np.ones(10), np.arange(10), np.zeros(10), np.arange(10)) assert len(w) == 7 assert issubclass(w[-1].category, UserWarning) assert str(w[-1].message) == "Estimated melody has no voiced frames." @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize( "metric", [ mir_eval.melody.raw_pitch_accuracy, mir_eval.melody.raw_chroma_accuracy, mir_eval.melody.overall_accuracy, ], ) @pytest.mark.parametrize( "ref_freq, est_freq", [(np.ones(11), np.ones(10)), (np.ones(10), np.ones(11))] ) def test_melody_badlength(metric, ref_freq, est_freq): # frequency and time must be the same length metric(np.ones(10), ref_freq, np.ones(10), est_freq) @pytest.mark.parametrize("melody_data", file_sets, indirect=True) @pytest.mark.parametrize("voicing", [False, True]) def test_melody_functions(melody_data, voicing): ref_time, ref_freq, est_time, est_freq, expected_scores = melody_data # When voicing=True, do the continuous voicing equivalence check if voicing: ref_reward = np.ones_like(ref_time) est_voicing = (est_freq >= 0).astype(float) else: ref_reward = None est_voicing = None scores = mir_eval.melody.evaluate( ref_time, ref_freq, est_time, est_freq, est_voicing=est_voicing, ref_reward=ref_reward, ) assert scores.keys() == expected_scores.keys() for metric in scores: assert np.allclose(scores[metric], expected_scores[metric], atol=A_TOL) mir_eval-0.8.2/tests/test_multipitch.py000066400000000000000000000234631475740344600203020ustar00rootroot00000000000000""" Unit tests for mir_eval.multipitch """ import numpy as np import json import mir_eval import glob import warnings import pytest A_TOL = 1e-12 # Path to the fixture files REF_GLOB = "data/multipitch/ref*.txt" EST_GLOB = "data/multipitch/est*.txt" SCORES_GLOB = "data/multipitch/output*.json" ref_files = sorted(glob.glob(REF_GLOB)) est_files = sorted(glob.glob(EST_GLOB)) sco_files = sorted(glob.glob(SCORES_GLOB)) assert len(ref_files) == len(est_files) == len(sco_files) > 0 file_sets = list(zip(ref_files, est_files, sco_files)) @pytest.fixture def multipitch_data(request): ref_f, est_f, sco_f = request.param with open(sco_f) as f_handle: expected_score = json.load(f_handle) ref_times, ref_freqs = mir_eval.io.load_ragged_time_series(ref_f) est_times, est_freqs = mir_eval.io.load_ragged_time_series(est_f) return ref_times, ref_freqs, est_times, est_freqs, expected_score def __frequencies_equal(freqs_a, freqs_b): if len(freqs_a) != len(freqs_b): return False else: equal = True for freq_a, freq_b in zip(freqs_a, freqs_b): if freq_a.size != freq_b.size: return False equal = equal and np.allclose(freq_a, freq_b, atol=A_TOL) return equal def __scores_equal(score_a, score_b): keys_a = set(list(score_a.keys())) keys_b = set(list(score_b.keys())) if keys_a != keys_b: return False else: equal = True for k in keys_a: value_a = score_a[k] value_b = score_b[k] equal = equal and np.allclose(value_a, value_b, atol=A_TOL) return equal def test_resample_multif0(): times = np.array([0.00, 0.01, 0.02, 0.03]) empty_times = np.array([]) freqs = [ np.array([200.0]), np.array([]), np.array([300.0, 400.0, 500.0]), np.array([300.0, 500.0]), ] empty_freqs = [] target_times1 = times target_times2 = np.array([0.001, 0.002, 0.01, 0.029, 0.05]) target_times3 = empty_times expected_freqs1 = freqs expected_freqs2 = [ np.array([200.0]), np.array([200.0]), np.array([]), np.array([300.0, 500.0]), np.array([]), ] expected_freqs3 = empty_freqs expected_freqs4 = [np.array([])] * 4 actual_freqs1 = mir_eval.multipitch.resample_multipitch(times, freqs, target_times1) actual_freqs2 = mir_eval.multipitch.resample_multipitch(times, freqs, target_times2) actual_freqs3 = mir_eval.multipitch.resample_multipitch(times, freqs, target_times3) actual_freqs4 = mir_eval.multipitch.resample_multipitch( empty_times, empty_freqs, target_times1 ) assert __frequencies_equal(actual_freqs1, expected_freqs1) assert __frequencies_equal(actual_freqs2, expected_freqs2) assert __frequencies_equal(actual_freqs3, expected_freqs3) assert __frequencies_equal(actual_freqs4, expected_freqs4) def test_frequencies_to_midi(): frequencies = [ np.array([440.0]), np.array([]), np.array([220.0, 660.0, 512.0]), np.array([300.0, 512.0]), ] expected = [ np.array([69.0]), np.array([]), np.array([57.0, 76.01955000865388, 71.623683437704088]), np.array([62.369507723654657, 71.623683437704088]), ] actual = mir_eval.multipitch.frequencies_to_midi(frequencies) assert __frequencies_equal(actual, expected) def test_midi_to_chroma(): midi_frequencies = [ np.array([69.0]), np.array([]), np.array([57.0, 76.01955000865388, 71.623683437704088]), np.array([62.369507723654657, 71.623683437704088]), ] expected = [ np.array([9.0]), np.array([]), np.array([9.0, 4.01955000865388, 11.623683437704088]), np.array([2.3695077236546567, 11.623683437704088]), ] actual = mir_eval.multipitch.midi_to_chroma(midi_frequencies) assert __frequencies_equal(actual, expected) def test_compute_num_freqs(): frequencies = [ np.array([256.0]), np.array([]), np.array([362.03867196751236, 128.0, 512.0]), np.array([300.0, 512.0]), ] expected = np.array([1, 0, 3, 2]) actual = mir_eval.multipitch.compute_num_freqs(frequencies) assert np.allclose(actual, expected, atol=A_TOL) def test_compute_num_true_positives(): ref_freqs = [ np.array([96.0, 100.0]), np.array([]), np.array([81.0]), np.array([102.0, 84.0, 108.0]), np.array([98.745824285950576, 108.0]), ] est_freqs = [ np.array([96.0]), np.array([]), np.array([200.0, 82.0]), np.array([102.0, 84.0, 108.0]), np.array([99.0, 108.0]), ] expected = np.array([1, 0, 0, 3, 2]) actual = mir_eval.multipitch.compute_num_true_positives(ref_freqs, est_freqs) assert np.allclose(actual, expected, atol=A_TOL) ref_freqs_chroma = [ np.array([0.0, 1.5]), np.array([]), np.array([2.0]), np.array([5.1, 6.0, 11.0]), np.array([11.9, 11.9]), ] est_freqs_chroma = [ np.array([0.0]), np.array([]), np.array([5.0, 2.6]), np.array([5.1, 6.0, 11.0]), np.array([0.2, 11.5]), ] expected = np.array([1, 0, 0, 3, 2]) actual = mir_eval.multipitch.compute_num_true_positives( ref_freqs_chroma, est_freqs_chroma, chroma=True ) assert np.allclose(actual, expected, atol=A_TOL) def test_accuracy_metrics(): true_positives = np.array([1, 0, 0, 3, 2]) n_ref = np.array([2, 0, 1, 3, 2]) n_est = np.array([1, 0, 2, 3, 2]) expected_precision = 0.75 expected_recall = 0.75 expected_accuracy = 0.6 ( actual_precision, actual_recall, actual_accuarcy, ) = mir_eval.multipitch.compute_accuracy(true_positives, n_ref, n_est) assert np.allclose(actual_precision, expected_precision, atol=A_TOL) assert np.allclose(actual_recall, expected_recall, atol=A_TOL) assert np.allclose(actual_accuarcy, expected_accuracy, atol=A_TOL) def test_error_score_metrics(): true_positives = np.array([1, 0, 0, 3, 2]) n_ref = np.array([2, 0, 1, 3, 2]) n_est = np.array([1, 0, 2, 3, 2]) expected_esub = 0.125 expected_emiss = 0.125 expected_efa = 0.125 expected_etot = 0.375 ( actual_esub, actual_emiss, actual_efa, actual_etot, ) = mir_eval.multipitch.compute_err_score(true_positives, n_ref, n_est) assert np.allclose(actual_esub, expected_esub, atol=A_TOL) assert np.allclose(actual_emiss, expected_emiss, atol=A_TOL) assert np.allclose(actual_efa, expected_efa, atol=A_TOL) assert np.allclose(actual_etot, expected_etot, atol=A_TOL) def unit_test_metrics(): empty_array = np.array([]) ref_time = np.array([0.0, 0.1]) ref_freqs = [np.array([201.0]), np.array([])] est_time = np.array([0.0, 0.1]) est_freqs = [np.array([200.0]), np.array([])] # ref sizes unequal with pytest.raises(ValueError): mir_eval.multipitch.metrics(np.array([0.0]), ref_freqs, est_time, est_freqs) # est sizes unequal with pytest.raises(ValueError): mir_eval.multipitch.metrics(ref_time, ref_freqs, np.array([0.0]), est_freqs) with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") # Test for warnings on empty values actual_score = mir_eval.multipitch.metrics( ref_time, [empty_array, empty_array], est_time, [empty_array, empty_array] ) assert len(w) == 6 assert issubclass(w[-1].category, UserWarning) assert str(w[-1].message) == "Reference frequencies are all empty." with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") # Test for warnings on empty values # test all inputs empty mir_eval.multipitch.metrics(empty_array, [], empty_array, []) assert len(w) == 10 assert issubclass(w[-1].category, UserWarning) assert str(w[-1].message) == "Reference frequencies are all empty." with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") # reference empty mir_eval.multipitch.metrics(empty_array, [], est_time, est_freqs) assert len(w) == 9 assert issubclass(w[-1].category, UserWarning) assert str(w[-1].message) == "Reference frequencies are all empty." with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") # estimate empty mir_eval.multipitch.metrics(ref_time, ref_freqs, empty_array, []) assert len(w) == 5 assert issubclass(w[-1].category, UserWarning) assert str(w[-1].message) == "Estimate frequencies are all empty." expected_score = ( 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ) assert np.allclose(actual_score, expected_score) # test perfect estimate ref_time = np.array([0.0, 0.1, 0.2]) ref_freqs = [np.array([201.0]), np.array([]), np.array([300.5, 87.1])] actual_score = mir_eval.multipitch.metrics(ref_time, ref_freqs, ref_time, ref_freqs) expected_score = ( 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, ) assert np.allclose(actual_score, expected_score) @pytest.mark.parametrize("multipitch_data", file_sets, indirect=True) def test_evaluate_regression(multipitch_data): ref_times, ref_freqs, est_times, est_freqs, expected_score = multipitch_data actual_score = mir_eval.multipitch.evaluate( ref_times, ref_freqs, est_times, est_freqs ) assert __scores_equal(actual_score, expected_score) mir_eval-0.8.2/tests/test_onset.py000066400000000000000000000044221475740344600172420ustar00rootroot00000000000000""" Unit tests for mir_eval.onset """ import numpy as np import pytest import json import mir_eval import glob import warnings A_TOL = 1e-12 # Path to the fixture files REF_GLOB = "data/onset/ref*.txt" EST_GLOB = "data/onset/est*.txt" SCORES_GLOB = "data/onset/output*.json" ref_files = sorted(glob.glob(REF_GLOB)) est_files = sorted(glob.glob(EST_GLOB)) sco_files = sorted(glob.glob(SCORES_GLOB)) assert len(ref_files) == len(est_files) == len(sco_files) > 0 file_sets = list(zip(ref_files, est_files, sco_files)) @pytest.fixture def onset_data(request): ref_f, est_f, sco_f = request.param with open(sco_f) as f: expected_scores = json.load(f) reference_onsets = mir_eval.io.load_events(ref_f) estimated_onsets = mir_eval.io.load_events(est_f) return reference_onsets, estimated_onsets, expected_scores def test_onset_empty_warnings(): with pytest.warns(UserWarning, match="Reference onsets are empty."): mir_eval.onset.f_measure(np.array([]), np.arange(10)) with pytest.warns(UserWarning, match="Estimated onsets are empty."): mir_eval.onset.f_measure(np.arange(10), np.array([])) with pytest.warns(UserWarning, match="onsets are empty"): # Also verify that the score is 0 assert np.allclose(mir_eval.onset.f_measure(np.array([]), np.array([])), 0) @pytest.mark.xfail(raisses=ValueError) @pytest.mark.parametrize( "onsets", [ np.array([[1.0, 2.0]]), # must be 1d ndarray np.array([1e10, 1e11]), # must not be huge np.array([2.0, 1.0]), # must be sorted ], ) def test_onset_fail(onsets): mir_eval.onset.f_measure(onsets, onsets) def test_onset_match(): # Valid onsets which are the same produce a score of 1 for all metrics onsets = np.arange(10, dtype=np.float64) assert np.allclose(mir_eval.onset.f_measure(onsets, onsets), 1.0) @pytest.mark.parametrize("onset_data", file_sets, indirect=True) def test_onset_functions(onset_data): reference_onsets, estimated_onsets, expected_scores = onset_data # Compute scores scores = mir_eval.onset.evaluate(reference_onsets, estimated_onsets) # Compare them assert scores.keys() == expected_scores.keys() for metric in scores: assert np.allclose(scores[metric], expected_scores[metric], atol=A_TOL) mir_eval-0.8.2/tests/test_pattern.py000066400000000000000000000063341475740344600175730ustar00rootroot00000000000000""" Some unit tests for the pattern discovery task. """ import numpy as np import json import mir_eval import glob import pytest A_TOL = 1e-12 # Path to the fixture files REF_GLOB = "data/pattern/ref*.txt" EST_GLOB = "data/pattern/est*.txt" SCORES_GLOB = "data/pattern/output*.json" ref_files = sorted(glob.glob(REF_GLOB)) est_files = sorted(glob.glob(EST_GLOB)) sco_files = sorted(glob.glob(SCORES_GLOB)) assert len(ref_files) == len(est_files) == len(sco_files) > 0 file_sets = list(zip(ref_files, est_files, sco_files)) @pytest.fixture def pattern_data(request): ref_f, est_f, sco_f = request.param with open(sco_f) as f: expected_scores = json.load(f) reference_patterns = mir_eval.io.load_patterns(ref_f) estimated_patterns = mir_eval.io.load_patterns(est_f) return reference_patterns, estimated_patterns, expected_scores @pytest.mark.parametrize( "metric", [ mir_eval.pattern.standard_FPR, mir_eval.pattern.establishment_FPR, mir_eval.pattern.occurrence_FPR, mir_eval.pattern.three_layer_FPR, mir_eval.pattern.first_n_three_layer_P, mir_eval.pattern.first_n_target_proportion_R, ], ) def test_pattern_empty(metric): # First, test for a warning on empty pattern with pytest.warns(UserWarning, match="Reference patterns are empty"): metric([[[]]], [[[(100, 20)]]]) with pytest.warns(UserWarning, match="Estimated patterns are empty"): metric([[[(100, 20)]]], [[[]]]) with pytest.warns(UserWarning, match="patterns are empty"): # And that the metric is 0 assert np.allclose(metric([[[]]], [[[]]]), 0) @pytest.mark.parametrize( "metric", [ mir_eval.pattern.standard_FPR, mir_eval.pattern.establishment_FPR, mir_eval.pattern.occurrence_FPR, mir_eval.pattern.three_layer_FPR, mir_eval.pattern.first_n_three_layer_P, mir_eval.pattern.first_n_target_proportion_R, ], ) @pytest.mark.parametrize( "patterns", [ [[[(100, 20)]], []], # patterns must have at least one occurrence [[[(100, 20, 3)]]], # (onset, midi) tuple must contain 2 elements ], ) @pytest.mark.xfail(raises=ValueError) def test_pattern_failure(metric, patterns): metric(patterns, patterns) @pytest.mark.parametrize( "metric", [ mir_eval.pattern.standard_FPR, mir_eval.pattern.establishment_FPR, mir_eval.pattern.occurrence_FPR, mir_eval.pattern.three_layer_FPR, mir_eval.pattern.first_n_three_layer_P, mir_eval.pattern.first_n_target_proportion_R, ], ) def test_pattern_perfect(metric): # Valid patterns which are the same produce a score of 1 for all metrics patterns = [[[(100, 20), (200, 30)]]] assert np.allclose(metric(patterns, patterns), 1) @pytest.mark.parametrize("pattern_data", file_sets, indirect=True) def test_pattern_functions(pattern_data): reference_patterns, estimated_patterns, expected_scores = pattern_data # Compute scores scores = mir_eval.pattern.evaluate(reference_patterns, estimated_patterns) # Compare them assert scores.keys() == expected_scores.keys() for metric in scores: assert np.allclose(scores[metric], expected_scores[metric], atol=A_TOL) mir_eval-0.8.2/tests/test_segment.py000066400000000000000000000155711475740344600175630ustar00rootroot00000000000000""" Unit tests for mir_eval.segment """ import numpy as np import json import mir_eval import glob import pytest A_TOL = 1e-12 # Path to the fixture files REF_GLOB = "data/segment/ref*.lab" EST_GLOB = "data/segment/est*.lab" SCORES_GLOB = "data/segment/output*.json" ref_files = sorted(glob.glob(REF_GLOB)) est_files = sorted(glob.glob(EST_GLOB)) sco_files = sorted(glob.glob(SCORES_GLOB)) assert len(ref_files) == len(est_files) == len(sco_files) > 0 file_sets = list(zip(ref_files, est_files, sco_files)) @pytest.fixture def segment_data(request): ref_f, est_f, sco_f = request.param with open(sco_f) as f: expected_scores = json.load(f) # Load in an example segmentation annotation ref_intervals, ref_labels = mir_eval.io.load_labeled_intervals(ref_f) # Load in an example segmentation tracker output est_intervals, est_labels = mir_eval.io.load_labeled_intervals(est_f) return ref_intervals, ref_labels, est_intervals, est_labels, expected_scores @pytest.mark.parametrize( "metric", [mir_eval.segment.detection, mir_eval.segment.deviation] ) def test_segment_boundary_empty(metric): with pytest.warns(UserWarning, match="Reference intervals are empty"): metric(np.zeros((0, 2)), np.array([[1, 2], [2, 3]]), trim=False) with pytest.warns(UserWarning, match="Estimated intervals are empty"): metric(np.array([[1, 2], [2, 3]]), np.array([[1, 2]]), trim=True) with pytest.warns(UserWarning, match="intervals are empty"): empty_intervals = np.zeros((0, 2)) if metric == mir_eval.segment.detection: assert np.allclose(metric(empty_intervals, empty_intervals), 0) else: assert np.all(np.isnan(metric(empty_intervals, empty_intervals))) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize( "metric", [mir_eval.segment.detection, mir_eval.segment.deviation] ) @pytest.mark.parametrize( "intervals", [ # Now test validation function - intervals must be n by 2 np.array([1, 2, 3, 4]), # Interval boundaries must be positive np.array([[-1, 2], [2, 3]]), # Positive interval durations np.array([[2, 1], [2, 3]]), ], ) def test_segment_boundary_errors(metric, intervals): metric(intervals, intervals) def test_segment_boundary_detection_perfect(): correct_intervals = np.array([[0, 1], [1, 2]]) assert np.allclose( mir_eval.segment.detection(correct_intervals, correct_intervals), 1 ) def test_segment_boundary_deviation_perfect(): correct_intervals = np.array([[0, 1], [1, 2]]) assert np.allclose( mir_eval.segment.deviation(correct_intervals, correct_intervals), 0 ) @pytest.mark.parametrize( "metric", [ mir_eval.segment.pairwise, mir_eval.segment.rand_index, mir_eval.segment.ari, mir_eval.segment.mutual_information, mir_eval.segment.nce, mir_eval.segment.vmeasure, ], ) def test_segment_structure_empty(metric): with pytest.warns(UserWarning, match="Reference intervals are empty"): metric(np.zeros((0, 2)), [], np.array([[0, 1]]), ["foo"]) with pytest.warns(UserWarning, match="Estimated intervals are empty"): metric(np.array([[0, 1]]), ["foo"], np.zeros((0, 2)), []) with pytest.warns(UserWarning, match="intervals are empty"): empty_intervals = np.zeros((0, 2)) assert np.allclose(metric(empty_intervals, [], empty_intervals, []), 0) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize( "metric", [ mir_eval.segment.pairwise, mir_eval.segment.rand_index, mir_eval.segment.ari, mir_eval.segment.mutual_information, mir_eval.segment.nce, mir_eval.segment.vmeasure, ], ) @pytest.mark.parametrize( "intervals, labels", [ # Test for non-matching numbers of intervals and labels (np.array([[2, 1], [2, 3]]), ["a", "b", "c"]), # Now test validation function - intervals must be n by 2 (np.arange(4), ["a", "b", "c", "d"]), # Interval boundaries must be positive (np.array([[-1, 2], [2, 3]]), ["a", "b"]), # Positive interval durations (np.array([[2, 1], [2, 3]]), ["a", "b"]), # Number of intervals must match number of labels (np.array([[2, 1], [2, 3]]), ["a"]), # Intervals must start at 0 (np.array([[1, 2], [2, 3]]), ["a", "b"]), ], ) def test_segment_structure_fail(metric, intervals, labels): metric(intervals, labels, intervals, labels) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize( "metric", [ mir_eval.segment.pairwise, mir_eval.segment.rand_index, mir_eval.segment.ari, mir_eval.segment.mutual_information, mir_eval.segment.nce, mir_eval.segment.vmeasure, ], ) def test_segment_structure_end_mismatch(metric): reference_intervals = np.array([[0, 1], [1, 2]]) estimated_intervals = np.array([[0, 1], [1, 3]]) labels = ["a", "b"] metric(reference_intervals, labels, estimated_intervals, labels) @pytest.mark.parametrize( "metric", [ mir_eval.segment.pairwise, mir_eval.segment.rand_index, mir_eval.segment.ari, mir_eval.segment.mutual_information, mir_eval.segment.nce, mir_eval.segment.vmeasure, ], ) def test_segment_structure_perfect(metric): reference_intervals = np.array([[0, 1], [1, 2]]) estimated_intervals = np.array([[0, 1], [1, 2]]) labels = ["a", "b"] if metric == mir_eval.segment.mutual_information: assert np.allclose( metric(reference_intervals, labels, estimated_intervals, labels), [np.log(2), 1, 1], ) else: assert np.allclose( metric(reference_intervals, labels, estimated_intervals, labels), 1 ) @pytest.mark.parametrize("segment_data", file_sets, indirect=True) def test_segment_functions(segment_data): ref_intervals, ref_labels, est_intervals, est_labels, expected_scores = segment_data # Compute scores scores = mir_eval.segment.evaluate( ref_intervals, ref_labels, est_intervals, est_labels ) assert scores.keys() == expected_scores.keys() for metric in scores: assert np.allclose(scores[metric], expected_scores[metric], atol=A_TOL) @pytest.mark.parametrize("segment_data", file_sets, indirect=True) def test_segment_functions_permuted(segment_data): ref_intervals, ref_labels, est_intervals, est_labels, expected_scores = segment_data # Also check with permuted references idx = np.random.permutation(np.arange(len(ref_intervals))) perm_int = ref_intervals[idx] perm_lab = [ref_labels[_] for _ in idx] scores = mir_eval.segment.evaluate(perm_int, perm_lab, est_intervals, est_labels) assert scores.keys() == expected_scores.keys() for metric in scores: assert np.allclose(scores[metric], expected_scores[metric], atol=A_TOL) mir_eval-0.8.2/tests/test_separation.py000066400000000000000000000355301475740344600202630ustar00rootroot00000000000000""" unit tests for mir_eval.separation load randomly generated source and estimated source signals and the output from BSS_eval MATLAB implementation, make sure the results from mir_eval numerically match. """ import numpy as np import mir_eval import glob import pytest import json import os A_TOL = 1e-2 REF_GLOB = "data/separation/ref*" EST_GLOB = "data/separation/est*" SCORES_GLOB = "data/separation/output*.json" ref_files = sorted(glob.glob(REF_GLOB)) est_files = sorted(glob.glob(EST_GLOB)) sco_files = sorted(glob.glob(SCORES_GLOB)) assert len(ref_files) == len(est_files) == len(sco_files) > 0 file_sets = list(zip(ref_files, est_files, sco_files)) # Skip separation tests since deprecation pytest.skip(allow_module_level=True) @pytest.fixture def separation_data(request): ref_f, est_f, sco_f = request.param with open(sco_f) as f: expected_results = json.load(f) expected_sources = expected_results["Sources"] expected_frames = expected_results["Framewise"] expected_images = expected_results["Images"] expected_image_frames = expected_results["Images Framewise"] # Load in example source separation data ref_sources = __load_and_stack_wavs(ref_f) est_sources = __load_and_stack_wavs(est_f) # Test inference for single source passed as single dimensional array if ref_sources.shape[0] == 1 and est_sources.shape[0] == 1: ref_sources = ref_sources[0] est_sources = est_sources[0] return ( ref_sources, est_sources, expected_sources, expected_frames, expected_images, expected_image_frames, ) @pytest.fixture(autouse=True) def seed_rng(): # Seed the RNG before each test run np.random.seed(1999) def __load_and_stack_wavs(directory): """Load all wavs in a directory and stack them vertically into a matrix""" stacked_audio_data = [] global_fs = None for f in sorted(glob.glob(os.path.join(directory, "*.wav"))): audio_data, fs = mir_eval.io.load_wav(f) assert global_fs is None or fs == global_fs global_fs = fs stacked_audio_data.append(audio_data) return np.vstack(stacked_audio_data) def __generate_multichannel(mono_sig, nchan=2, gain=1.0, reverse=False): """Turn a single channel (ie. mono) audio sample into a multichannel (e.g. stereo) Note: to achieve channels of silence pass gain=0 """ # add the channels dimension input_3d = np.atleast_3d(mono_sig) # get the desired number of channels stackin = [input_3d] * nchan # apply the gain to the new channels stackin[1:] = np.multiply(gain, stackin[1:]) if reverse: # reverse the new channels stackin[1:] = stackin[1:][:][::-1] return np.dstack(stackin) @pytest.mark.parametrize( "metric", [ mir_eval.separation.bss_eval_sources, mir_eval.separation.bss_eval_sources_framewise, mir_eval.separation.bss_eval_images, mir_eval.separation.bss_eval_images_framewise, ], ) def test_empty_input(metric): if ( metric == mir_eval.separation.bss_eval_sources or metric == mir_eval.separation.bss_eval_images ): args = [np.array([]), np.array([])] elif ( metric == mir_eval.separation.bss_eval_sources_framewise or metric == mir_eval.separation.bss_eval_images_framewise ): args = [np.array([]), np.array([]), 40, 20] with pytest.warns(UserWarning, match="is empty") as record: # First, test for a warning on empty audio data metric(*args) # And that the metric returns empty arrays assert np.allclose(metric(*args), np.array([])) # These warning counters are now offset by 1 because of the deprecation message assert "reference_sources is empty" in str(record[1].message) assert "estimated_sources is empty" in str(record[2].message) @pytest.mark.parametrize( "metric", [ mir_eval.separation.bss_eval_sources, mir_eval.separation.bss_eval_sources_framewise, mir_eval.separation.bss_eval_images, mir_eval.separation.bss_eval_images_framewise, ], ) def test_silent_input(metric): # Test for error when there is a silent reference/estimated source if ( metric == mir_eval.separation.bss_eval_images or metric == mir_eval.separation.bss_eval_images_framewise ): ref_sources = np.vstack( (np.zeros((1, 100, 2)), np.random.random_sample((2, 100, 2))) ) est_sources = np.vstack( (np.zeros((1, 100, 2)), np.random.random_sample((2, 100, 2))) ) else: ref_sources = np.vstack((np.zeros(100), np.random.random_sample((2, 100)))) est_sources = np.vstack((np.zeros(100), np.random.random_sample((2, 100)))) if ( metric == mir_eval.separation.bss_eval_sources or metric == mir_eval.separation.bss_eval_images ): with pytest.raises(ValueError): metric(ref_sources[:2], est_sources[1:]) with pytest.raises(ValueError): metric(ref_sources[1:], est_sources[:2]) elif ( metric == mir_eval.separation.bss_eval_sources_framewise or metric == mir_eval.separation.bss_eval_images_framewise ): with pytest.raises(ValueError): metric(ref_sources[:2], est_sources[1:], 40, 20) with pytest.raises(ValueError): metric(ref_sources[1:], est_sources[:2], 40, 20) @pytest.mark.parametrize( "metric", [ mir_eval.separation.bss_eval_sources_framewise, mir_eval.separation.bss_eval_images_framewise, ], ) def test_partial_silence(metric): # Test for a full window of silence in reference/estimated source if metric == mir_eval.separation.bss_eval_sources_framewise: silence = np.zeros((2, 20)) sound = np.random.random_sample((2, 20)) elif metric == mir_eval.separation.bss_eval_images_framewise: silence = np.zeros((2, 20, 2)) sound = np.random.random_sample((2, 20, 2)) # test with silence in the reference results = metric( np.concatenate((sound, silence, sound), axis=1), np.concatenate((sound, sound, sound), axis=1), window=10, hop=10, ) for measure in results: for idx, source in enumerate(measure): if idx < 2 or idx > 3: assert not np.isnan(source[idx]) elif idx < 4: assert np.isnan(source[idx]) else: raise ValueError("Testing error in partial silence test") # test with silence in the estimate results = metric( np.concatenate((sound, sound, sound), axis=1), np.concatenate((sound, silence, sound), axis=1), window=10, hop=10, ) for measure in results: for idx, source in enumerate(measure): if idx < 2 or idx > 3: assert not np.isnan(source[idx]) elif idx < 4: assert np.isnan(source[idx]) else: raise ValueError("Testing error in partial silence test") @pytest.mark.parametrize( "metric", [ mir_eval.separation.bss_eval_sources, mir_eval.separation.bss_eval_sources_framewise, mir_eval.separation.bss_eval_images, mir_eval.separation.bss_eval_images_framewise, ], ) def test_incompatible_shapes(metric): # Test for error when shape is different if ( metric == mir_eval.separation.bss_eval_images or metric == mir_eval.separation.bss_eval_images_framewise ): sources_4 = np.random.random_sample((4, 100, 2)) sources_3 = np.random.random_sample((3, 100, 2)) sources_4_chan = np.random.random_sample((4, 100, 3)) else: sources_4 = np.random.random_sample((4, 100)) sources_3 = np.random.random_sample((3, 100)) if ( metric == mir_eval.separation.bss_eval_sources or metric == mir_eval.separation.bss_eval_images ): args1 = [sources_3, sources_4] args2 = [sources_4, sources_3] elif ( metric == mir_eval.separation.bss_eval_sources_framewise or metric == mir_eval.separation.bss_eval_images_framewise ): args1 = [sources_3, sources_4, 40, 20] args2 = [sources_4, sources_3, 40, 20] with pytest.raises(ValueError): metric(*args1) with pytest.raises(ValueError): metric(*args2) if ( metric == mir_eval.separation.bss_eval_images or metric == mir_eval.separation.bss_eval_images_framewise ): with pytest.raises(ValueError): metric(sources_4, sources_4_chan) @pytest.mark.parametrize( "metric", [ mir_eval.separation.bss_eval_sources, mir_eval.separation.bss_eval_sources_framewise, mir_eval.separation.bss_eval_images, mir_eval.separation.bss_eval_images_framewise, ], ) def test_too_many_sources(metric): # Test for error when too many sources or references are provided many_sources = np.random.random_sample((mir_eval.separation.MAX_SOURCES * 2, 400)) if metric == mir_eval.separation.bss_eval_sources: with pytest.raises(ValueError): metric(many_sources, many_sources) elif metric == mir_eval.separation.bss_eval_sources_framewise: with pytest.raises(ValueError): metric(many_sources, many_sources, 40, 20) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize( "metric", [ mir_eval.separation.bss_eval_sources, mir_eval.separation.bss_eval_sources_framewise, mir_eval.separation.bss_eval_images, mir_eval.separation.bss_eval_images_framewise, ], ) def test_too_many_dimensions(metric): # Test for detection of too high dimensioned images ref_sources = np.random.random_sample((4, 100, 2, 3)) est_sources = np.random.random_sample((4, 100, 2, 3)) metric(ref_sources, est_sources) @pytest.mark.parametrize( "metric", [mir_eval.separation.bss_eval_sources, mir_eval.separation.bss_eval_images], ) def test_default_permutation(metric): # Test for default permutation matrix when not computing permutation if metric == mir_eval.separation.bss_eval_sources: ref_sources = np.random.random_sample((4, 100)) est_sources = np.random.random_sample((4, 100)) elif metric == mir_eval.separation.bss_eval_images: ref_sources = np.random.random_sample((4, 100, 2)) est_sources = np.random.random_sample((4, 100, 2)) results = metric(ref_sources, est_sources, compute_permutation=False) assert np.array_equal(results[-1], np.asarray([0, 1, 2, 3])) @pytest.mark.parametrize( "metric", [ mir_eval.separation.bss_eval_sources_framewise, mir_eval.separation.bss_eval_images_framewise, ], ) def test_framewise_small_window(metric): # Test for invalid win/hop parameter detection if metric == mir_eval.separation.bss_eval_sources_framewise: ref_sources = np.random.random_sample((4, 100)) est_sources = np.random.random_sample((4, 100)) comparison_fcn = mir_eval.separation.bss_eval_sources elif metric == mir_eval.separation.bss_eval_images_framewise: ref_sources = np.random.random_sample((4, 100, 2)) est_sources = np.random.random_sample((4, 100, 2)) comparison_fcn = mir_eval.separation.bss_eval_images # Test with window larger than source length assert np.allclose( np.squeeze(metric(ref_sources, est_sources, window=120, hop=20)), comparison_fcn(ref_sources, est_sources, False), atol=A_TOL, ) # Test with hop larger than source length assert np.allclose( np.squeeze(metric(ref_sources, est_sources, window=20, hop=120)), comparison_fcn(ref_sources, est_sources, False), atol=A_TOL, ) @pytest.mark.parametrize("separation_data", file_sets, indirect=True) def test_separation_functions(separation_data): ( ref_sources, est_sources, expected_sources, expected_frames, expected_images, expected_image_frames, ) = separation_data # Compute scores scores = mir_eval.separation.evaluate( ref_sources, est_sources, window=expected_frames["win"], hop=expected_frames["hop"], ) # Compare them for key in scores: if "Sources - " in key: test_data_name = key.replace("Sources - ", "") assert np.allclose( scores[key], expected_sources[test_data_name], atol=A_TOL ) elif "Sources Frames - " in key: test_data_name = key.replace("Sources Frames - ", "") assert np.allclose(scores[key], expected_frames[test_data_name], atol=A_TOL) @pytest.mark.parametrize("separation_data", file_sets, indirect=True) def test_separation_images(separation_data): ( ref_sources, est_sources, expected_sources, expected_frames, expected_images, expected_image_frames, ) = separation_data # Compute scores with images ref_images = __generate_multichannel(ref_sources, expected_images["nchan"]) est_images = __generate_multichannel( est_sources, expected_images["nchan"], expected_images["gain"], expected_images["reverse"], ) image_scores = mir_eval.separation.evaluate(ref_images, est_images) # Compare them for key in image_scores: if "Images - " in key: test_data_name = key.replace("Images - ", "") assert np.allclose( image_scores[key], expected_images[test_data_name], atol=A_TOL ) @pytest.mark.parametrize("separation_data", file_sets, indirect=True) def test_separation_images_framewise(separation_data): ( ref_sources, est_sources, expected_sources, expected_frames, expected_images, expected_image_frames, ) = separation_data # Compute scores with images framewise ref_images = __generate_multichannel(ref_sources, expected_image_frames["nchan"]) est_images = __generate_multichannel( est_sources, expected_image_frames["nchan"], expected_image_frames["gain"], expected_image_frames["reverse"], ) imageframe_scores = mir_eval.separation.evaluate( ref_images, est_images, window=expected_image_frames["win"], hop=expected_image_frames["hop"], ) # Compare them for key in imageframe_scores: if "Images Frames - " in key: test_data_name = key.replace("Images Frames - ", "") assert np.allclose( imageframe_scores[key], expected_image_frames[test_data_name], atol=A_TOL, ) # Catch a few exceptions in the evaluate function image_scores = mir_eval.separation.evaluate(ref_images, est_images) # make sure sources is not being evaluated on images assert "Sources - Source to Distortion" not in image_scores mir_eval-0.8.2/tests/test_sonify.py000066400000000000000000000131521475740344600174210ustar00rootroot00000000000000"""Unit tests for sonification methods""" import pytest import mir_eval import numpy as np import scipy @pytest.mark.parametrize("times", [np.array([1.0]), np.arange(10.0)]) @pytest.mark.parametrize("fs", [8000, 44100]) def test_clicks(times, fs): # Test output length for a variety of parameter settings click_signal = mir_eval.sonify.clicks(times, fs) assert len(click_signal) == times.max() * fs + int(fs * 0.1) + 1 click_signal = mir_eval.sonify.clicks(times, fs, length=1000) assert len(click_signal) == 1000 click_signal = mir_eval.sonify.clicks(times, fs, click=np.zeros(1000)) assert len(click_signal) == times.max() * fs + 1000 + 1 @pytest.mark.parametrize("fs", [8000, 44100]) def test_time_frequency(fs): # Test length for different inputs signal = mir_eval.sonify.time_frequency( np.random.standard_normal((100, 1000)), np.arange(1, 101), np.linspace(0, 10, 1000), fs, ) assert len(signal) == 10 * fs # Make one longer signal = mir_eval.sonify.time_frequency( np.random.standard_normal((100, 1000)), np.arange(1, 101), np.linspace(0, 10, 1000), fs, length=fs * 11, ) assert len(signal) == 11 * fs # Make one shorter signal = mir_eval.sonify.time_frequency( np.random.standard_normal((100, 1000)), np.arange(1, 101), np.linspace(0, 10, 1000), fs, length=fs * 5, ) assert len(signal) == 5 * fs def test_time_frequency_const(): # Sonify with a single interval to hit the const interpolator s1 = mir_eval.sonify.time_frequency( np.ones((1, 1)), np.array([60]), np.array([[0, 1]]), 8000, ) # Sonify with two tiem intervals to hit the regular interpolator # but the second frequency will have no energy, so it doesn't # change the resulting signal s2 = mir_eval.sonify.time_frequency( np.array([[1, 1], [0, 0]]), np.array([60, 90]), np.array([[0, 1], [0, 1]]), 8000, ) assert np.allclose(s1, s2) def test_time_frequency_offset(): fs = 8000 # Length is 3 seconds, first interval starts at 5. # Should produce an empty signal. signal = mir_eval.sonify.time_frequency( np.random.standard_normal((100, 100)), np.arange(1, 101), np.linspace(5, 10, 100), fs, length=fs * 3, ) assert len(signal) == 3 * fs assert np.allclose(signal, 0) @pytest.mark.xfail(raises=ValueError) def test_time_frequency_badtime(): fs = 8000 gram = np.ones((10, 20)) times = np.arange(10) mir_eval.sonify.time_frequency(gram, np.arange(1, 11), times, fs) @pytest.mark.xfail(raises=ValueError) def test_time_frequency_badintervals(): fs = 8000 gram = np.ones((10, 20)) times = np.ones((11, 2)) mir_eval.sonify.time_frequency(gram, np.arange(1, 11), times, fs) @pytest.mark.xfail(raises=ValueError) def test_time_frequency_frequency(): fs = 8000 gram = np.ones((10, 20)) times = np.arange(20) mir_eval.sonify.time_frequency(gram, np.arange(1, 8), times, fs) @pytest.mark.parametrize("fs", [8000, 44100]) def test_chroma(fs): signal = mir_eval.sonify.chroma( np.random.standard_normal((12, 1000)), np.linspace(0, 10, 1000), fs ) assert len(signal) == 10 * fs signal = mir_eval.sonify.chroma( np.random.standard_normal((12, 1000)), np.linspace(0, 10, 1000), fs, length=fs * 11, ) assert len(signal) == 11 * fs @pytest.mark.parametrize("fs", [8000, 44100]) def test_chords(fs): intervals = np.array([np.arange(10), np.arange(1, 11)]).T signal = mir_eval.sonify.chords( ["C", "C:maj", "D:min7", "E:min", "C#", "C", "C", "C", "C", "C"], intervals, fs ) assert len(signal) == 10 * fs signal = mir_eval.sonify.chords( ["C", "C:maj", "D:min7", "E:min", "C#", "C", "C", "C", "C", "C"], intervals, fs, length=fs * 11, ) assert len(signal) == 11 * fs def test_chord_x(): # This test verifies that X sonifies as silence intervals = np.array([[0, 1]]) signal = mir_eval.sonify.chords(["X"], intervals, 8000) assert not np.any(signal), signal def test_pitch_contour(): # Generate some random pitch fs = 8000 times = np.linspace(0, 5, num=5 * fs, endpoint=True) noise = scipy.ndimage.gaussian_filter1d(np.random.randn(len(times)), sigma=256) freqs = 440.0 * 2.0 ** (16 * noise) amps = np.linspace(0, 1, num=5 * fs, endpoint=True) # negate a bunch of sequences idx = np.unique(np.random.randint(0, high=len(times), size=32)) for start, end in zip(idx[::2], idx[1::2]): freqs[start:end] *= -1 # Test with inferring duration x = mir_eval.sonify.pitch_contour(times, freqs, fs) assert len(x) == fs * 5 # Test with an explicit duration # This forces the interpolator to go off the end of the sampling grid, # which should result in a constant sequence in the output x = mir_eval.sonify.pitch_contour(times, freqs, fs, length=fs * 7) assert len(x) == fs * 7 assert np.allclose(x[-fs * 2 :], x[-fs * 2]) # Test with an explicit duration and a fixed offset # This forces the interpolator to go off the beginning of # the sampling grid, which should result in a constant output x = mir_eval.sonify.pitch_contour(times + 5.0, freqs, fs, length=fs * 7) assert len(x) == fs * 7 assert np.allclose(x[: fs * 5], x[0]) # Test with explicit amplitude x = mir_eval.sonify.pitch_contour(times, freqs, fs, length=fs * 7, amplitudes=amps) assert len(x) == fs * 7 assert np.allclose(x[0], 0) mir_eval-0.8.2/tests/test_tempo.py000066400000000000000000000072031475740344600172360ustar00rootroot00000000000000#!/usr/bin/env python """ Unit tests for mir_eval.tempo """ import numpy as np import mir_eval import json import glob import pytest A_TOL = 1e-12 REF_GLOB = "data/tempo/ref*.lab" EST_GLOB = "data/tempo/est*.lab" SCORES_GLOB = "data/tempo/output*.json" ref_files = sorted(glob.glob(REF_GLOB)) est_files = sorted(glob.glob(EST_GLOB)) sco_files = sorted(glob.glob(SCORES_GLOB)) assert len(ref_files) == len(est_files) == len(sco_files) > 0 file_sets = list(zip(ref_files, est_files, sco_files)) @pytest.fixture def tempo_data(request): ref_f, est_f, sco_f = request.param with open(sco_f) as f: expected_scores = json.load(f) def _load_tempi(filename): values = mir_eval.io.load_delimited(filename, [float] * 3) return np.concatenate(values[:2]), values[-1][0] reference_tempi, ref_weight = _load_tempi(ref_f) estimated_tempi, _ = _load_tempi(est_f) return reference_tempi, ref_weight, estimated_tempi, expected_scores def test_zero_tolerance_pass(): good_ref = np.array([60, 120]) good_weight = 0.5 good_est = np.array([120, 180]) zero_tol = 0.0 with pytest.warns( UserWarning, match="A tolerance of 0.0 may not lead to the results you expect" ): mir_eval.tempo.detection(good_ref, good_weight, good_est, tol=zero_tol) def test_tempo_pass(): good_ref = np.array([60, 120]) good_weight = 0.5 good_est = np.array([120, 180]) good_tol = 0.08 for good_tempo in [np.array([50, 50]), np.array([0, 50]), np.array([50, 0])]: mir_eval.tempo.detection(good_tempo, good_weight, good_est, good_tol) mir_eval.tempo.detection(good_ref, good_weight, good_tempo, good_tol) # allow both estimates to be zero mir_eval.tempo.detection(good_ref, good_weight, np.array([0, 0]), good_tol) @pytest.mark.xfail(raises=ValueError) def test_tempo_zero_ref(): # Both references cannot be zero mir_eval.tempo.detection(np.array([0.0, 0.0]), 0.5, np.array([60, 120])) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize("weight", [-1, 1.5]) def test_tempo_weight_range(weight): # Weight needs to be in the range [0, 1] mir_eval.tempo.detection(np.array([60, 120]), weight, np.array([120, 180])) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize("tol", [-1, 1.5]) def test_tempo_tol_range(tol): # Weight needs to be in the range [0, 1] mir_eval.tempo.detection(np.array([60, 120]), 0.5, np.array([120, 180]), tol=tol) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize( "bad_tempo", [ np.array([-1, -1]), np.array([-1, 0]), np.array([-1, 50]), np.array([0, 1, 2]), np.array([0]), ], ) def test_tempo_fail_bad_reftempo(bad_tempo): good_ref = np.array([60, 120]) good_est = np.array([120, 180]) mir_eval.tempo.detection(bad_tempo, 0.5, good_est, 0.08) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize( "bad_tempo", [ np.array([-1, -1]), np.array([-1, 0]), np.array([-1, 50]), np.array([0, 1, 2]), np.array([0]), ], ) def test_tempo_fail_bad_esttempo(bad_tempo): good_ref = np.array([60, 120]) good_est = np.array([120, 180]) mir_eval.tempo.detection(good_ref, 0.5, bad_tempo, 0.08) @pytest.mark.parametrize("tempo_data", file_sets, indirect=True) def test_tempo_regression(tempo_data): ref_tempi, ref_weight, est_tempi, expected_scores = tempo_data scores = mir_eval.tempo.evaluate(ref_tempi, ref_weight, est_tempi) assert scores.keys() == expected_scores.keys() for metric in scores: assert np.allclose(scores[metric], expected_scores[metric], atol=A_TOL) mir_eval-0.8.2/tests/test_transcription.py000066400000000000000000000221461475740344600210140ustar00rootroot00000000000000# CREATED: 2/9/16 2:27 PM by Justin Salamon import mir_eval import numpy as np import glob import json import pytest A_TOL = 1e-12 # Path to the fixture files REF_GLOB = "data/transcription/ref*.txt" EST_GLOB = "data/transcription/est*.txt" SCORES_GLOB = "data/transcription/output*.json" ref_files = sorted(glob.glob(REF_GLOB)) est_files = sorted(glob.glob(EST_GLOB)) sco_files = sorted(glob.glob(SCORES_GLOB)) assert len(ref_files) == len(est_files) == len(sco_files) > 0 file_sets = list(zip(ref_files, est_files, sco_files)) @pytest.fixture def transcription_data(request): ref_f, est_f, sco_f = request.param with open(sco_f) as f: expected_scores = json.load(f) # Load in an example segmentation annotation ref_int, ref_pitch = mir_eval.io.load_valued_intervals(ref_f) # Load in estimated transcription est_int, est_pitch = mir_eval.io.load_valued_intervals(est_f) return ref_int, ref_pitch, est_int, est_pitch, expected_scores REF = np.array( [ [0.100, 0.300, 220.000], [0.300, 0.400, 246.942], [0.500, 0.600, 277.183], [0.550, 0.650, 293.665], ] ) EST = np.array( [ [0.120, 0.290, 225.000], [0.300, 0.340, 246.942], [0.500, 0.600, 500.000], [0.550, 0.600, 293.665], [0.560, 0.650, 293.665], ] ) SCORES = { "Precision": 0.4, "Recall": 0.5, "F-measure": 0.4444444444444445, "Average_Overlap_Ratio": 0.675, "Precision_no_offset": 0.6, "Recall_no_offset": 0.75, "F-measure_no_offset": 0.6666666666666665, "Average_Overlap_Ratio_no_offset": 0.5833333333333333, } ONSET_SCORES = { "Onset_Precision": 0.8, "Onset_Recall": 1.0, "Onset_F-measure": 0.8888888888888889, } OFFSET_SCORES = { "Offset_Precision": 0.6, "Offset_Recall": 0.75, "Offset_F-measure": 0.6666666666666665, } def test_match_note_offsets(): ref_int = REF[:, :2] est_int = EST[:, :2] matching = mir_eval.transcription.match_note_offsets(ref_int, est_int) assert matching == [(0, 0), (2, 2), (3, 3)] def test_match_note_offsets_strict(): ref_int = REF[:, :2] est_int = EST[:, :2] matching = mir_eval.transcription.match_note_offsets(ref_int, est_int, strict=True) assert matching == [(0, 0), (2, 2), (3, 4)] def test_match_note_onsets(): ref_int = REF[:, :2] est_int = EST[:, :2] matching = mir_eval.transcription.match_note_onsets(ref_int, est_int) assert matching == [(0, 0), (1, 1), (2, 2), (3, 3)] def test_match_note_onsets_strict(): ref_int = REF[:, :2] est_int = EST[:, :2] matching = mir_eval.transcription.match_note_onsets(ref_int, est_int, strict=True) assert matching == [(0, 0), (1, 1), (2, 2), (3, 3)] def test_match_notes(): ref_int, ref_pitch = REF[:, :2], REF[:, 2] est_int, est_pitch = EST[:, :2], EST[:, 2] matching = mir_eval.transcription.match_notes( ref_int, ref_pitch, est_int, est_pitch ) assert matching == [(0, 0), (3, 3)] matching = mir_eval.transcription.match_notes( ref_int, ref_pitch, est_int, est_pitch, offset_ratio=None ) assert matching == [(0, 0), (1, 1), (3, 3)] def test_match_notes_strict(): ref_int, ref_pitch = np.array([[0, 1]]), np.array([100]) est_int, est_pitch = np.array([[0.05, 1]]), np.array([100]) matching = mir_eval.transcription.match_notes( ref_int, ref_pitch, est_int, est_pitch, strict=True ) assert matching == [] def test_precision_recall_f1_overlap(): # load test data ref_int, ref_pitch = REF[:, :2], REF[:, 2] est_int, est_pitch = EST[:, :2], EST[:, 2] ( precision, recall, f_measure, avg_overlap_ratio, ) = mir_eval.transcription.precision_recall_f1_overlap( ref_int, ref_pitch, est_int, est_pitch ) scores_gen = np.array([precision, recall, f_measure, avg_overlap_ratio]) scores_exp = np.array( [ SCORES["Precision"], SCORES["Recall"], SCORES["F-measure"], SCORES["Average_Overlap_Ratio"], ] ) assert np.allclose(scores_exp, scores_gen, atol=A_TOL) ( precision, recall, f_measure, avg_overlap_ratio, ) = mir_eval.transcription.precision_recall_f1_overlap( ref_int, ref_pitch, est_int, est_pitch, offset_ratio=None ) scores_gen = np.array([precision, recall, f_measure, avg_overlap_ratio]) scores_exp = np.array( [ SCORES["Precision_no_offset"], SCORES["Recall_no_offset"], SCORES["F-measure_no_offset"], SCORES["Average_Overlap_Ratio_no_offset"], ] ) assert np.allclose(scores_exp, scores_gen, atol=A_TOL) def test_onset_precision_recall_f1(): # load test data ref_int = REF[:, :2] est_int = EST[:, :2] precision, recall, f_measure = mir_eval.transcription.onset_precision_recall_f1( ref_int, est_int ) scores_gen = np.array([precision, recall, f_measure]) scores_exp = np.array( [ ONSET_SCORES["Onset_Precision"], ONSET_SCORES["Onset_Recall"], ONSET_SCORES["Onset_F-measure"], ] ) assert np.allclose(scores_exp, scores_gen, atol=A_TOL) def test_offset_precision_recall_f1(): # load test data ref_int = REF[:, :2] est_int = EST[:, :2] precision, recall, f_measure = mir_eval.transcription.offset_precision_recall_f1( ref_int, est_int ) scores_gen = np.array([precision, recall, f_measure]) scores_exp = np.array( [ OFFSET_SCORES["Offset_Precision"], OFFSET_SCORES["Offset_Recall"], OFFSET_SCORES["Offset_F-measure"], ] ) assert np.allclose(scores_exp, scores_gen, atol=A_TOL) @pytest.mark.parametrize("transcription_data", file_sets, indirect=True) def test_regression(transcription_data): ref_int, ref_pitch, est_int, est_pitch, expected_scores = transcription_data scores = mir_eval.transcription.evaluate(ref_int, ref_pitch, est_int, est_pitch) assert scores.keys() == expected_scores.keys() for metric in scores: assert np.allclose(scores[metric], expected_scores[metric], atol=A_TOL) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize( "ref_pitch, est_pitch", [(np.array([-100]), np.array([100])), (np.array([100]), np.array([-100]))], ) def test_invalid_pitch(ref_pitch, est_pitch): ref_int = np.array([[0, 1]]) mir_eval.transcription.validate(ref_int, ref_pitch, ref_int, est_pitch) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize( "ref_int, est_int", [ (np.array([[0, 1], [2, 3]]), np.array([[0, 1]])), (np.array([[0, 1]]), np.array([[0, 1], [2, 3]])), ], ) def test_inconsistent_int_pitch(ref_int, est_int): ref_pitch = np.array([100]) mir_eval.transcription.validate(ref_int, ref_pitch, est_int, ref_pitch) def test_empty_ref(): ref_int, ref_pitch = np.empty(shape=(0, 2)), np.array([]) est_int, est_pitch = np.array([[0, 1]]), np.array([100]) with pytest.warns(UserWarning, match="Reference notes are empty"): mir_eval.transcription.validate(ref_int, ref_pitch, est_int, est_pitch) def test_empty_est(): ref_int, ref_pitch = np.array([[0, 1]]), np.array([100]) est_int, est_pitch = np.empty(shape=(0, 2)), np.array([]) with pytest.warns(UserWarning, match="Estimated notes are empty"): mir_eval.transcription.validate(ref_int, ref_pitch, est_int, est_pitch) @pytest.mark.filterwarnings("ignore:.*notes are empty") def test_precision_recall_f1_overlap_empty(): ref_int, ref_pitch = np.empty(shape=(0, 2)), np.array([]) est_int, est_pitch = np.array([[0, 1]]), np.array([100]) ( precision, recall, f1, avg_overlap_ratio, ) = mir_eval.transcription.precision_recall_f1_overlap( ref_int, ref_pitch, est_int, est_pitch ) assert (precision, recall, f1) == (0, 0, 0) ( precision, recall, f1, avg_overlap_ratio, ) = mir_eval.transcription.precision_recall_f1_overlap( est_int, est_pitch, ref_int, ref_pitch ) assert (precision, recall, f1) == (0, 0, 0) @pytest.mark.filterwarnings("ignore:.*notes are empty") def test_onset_precision_recall_f1_empty(): ref_int = np.empty(shape=(0, 2)) est_int = np.array([[0, 1]]) precision, recall, f1 = mir_eval.transcription.onset_precision_recall_f1( ref_int, est_int ) assert (precision, recall, f1) == (0, 0, 0) precision, recall, f1 = mir_eval.transcription.onset_precision_recall_f1( est_int, ref_int ) assert (precision, recall, f1) == (0, 0, 0) @pytest.mark.filterwarnings("ignore:.*notes are empty") def test_offset_precision_recall_f1_empty(): ref_int = np.empty(shape=(0, 2)) est_int = np.array([[0, 1]]) precision, recall, f1 = mir_eval.transcription.offset_precision_recall_f1( ref_int, est_int ) assert (precision, recall, f1) == (0, 0, 0) precision, recall, f1 = mir_eval.transcription.offset_precision_recall_f1( est_int, ref_int ) assert (precision, recall, f1) == (0, 0, 0) mir_eval-0.8.2/tests/test_transcription_velocity.py000066400000000000000000000112031475740344600227220ustar00rootroot00000000000000import pytest import mir_eval import numpy as np import glob import json A_TOL = 1e-12 # Path to the fixture files REF_GLOB = "data/transcription_velocity/ref*.txt" EST_GLOB = "data/transcription_velocity/est*.txt" SCORES_GLOB = "data/transcription_velocity/output*.json" ref_files = sorted(glob.glob(REF_GLOB)) est_files = sorted(glob.glob(EST_GLOB)) sco_files = sorted(glob.glob(SCORES_GLOB)) assert len(ref_files) == len(est_files) == len(sco_files) > 0 file_sets = list(zip(ref_files, est_files, sco_files)) def _load_transcription_velocity(filename): """Loader for data in the format start, end, pitch, velocity.""" starts, ends, pitches, velocities = mir_eval.io.load_delimited( filename, [float, float, int, int] ) # Stack into an interval matrix intervals = np.array([starts, ends]).T # return pitches and velocities as np.ndarray pitches = np.array(pitches) velocities = np.array(velocities) return intervals, pitches, velocities @pytest.fixture def velocity_data(request): ref_f, est_f, sco_f = request.param with open(sco_f) as f: expected_scores = json.load(f) # Load in reference transcription ref_int, ref_pitch, ref_vel = _load_transcription_velocity(ref_f) # Load in estimated transcription est_int, est_pitch, est_vel = _load_transcription_velocity(est_f) return (ref_int, ref_pitch, ref_vel), (est_int, est_pitch, est_vel), expected_scores def test_negative_velocity(): good_i, good_p, good_v = np.array([[0, 1]]), np.array([100]), np.array([1]) bad_i, bad_p, bad_v = np.array([[0, 1]]), np.array([100]), np.array([-1]) with pytest.raises(ValueError): mir_eval.transcription_velocity.validate( bad_i, bad_p, bad_v, good_i, good_p, good_v ) with pytest.raises(ValueError): mir_eval.transcription_velocity.validate( good_i, good_p, good_v, bad_i, bad_p, bad_v ) def test_wrong_shape_velocity(): good_i, good_p, good_v = np.array([[0, 1]]), np.array([100]), np.array([1]) bad_i, bad_p, bad_v = np.array([[0, 1]]), np.array([100]), np.array([1, 2]) with pytest.raises(ValueError): mir_eval.transcription_velocity.validate( bad_i, bad_p, bad_v, good_i, good_p, good_v ) with pytest.raises(ValueError): mir_eval.transcription_velocity.validate( good_i, good_p, good_v, bad_i, bad_p, bad_v ) def test_precision_recall_f1_overlap(): # Simple unit test ref_i = np.array([[0, 1], [0.5, 0.7], [1, 2]]) ref_p = np.array([100, 110, 80]) ref_v = np.array([10, 90, 110]) est_i = np.array([[0, 1], [0.5, 0.7], [1, 2]]) est_p = np.array([100, 110, 80]) est_v = np.array([10, 70, 110]) p, r, f, o = mir_eval.transcription_velocity.precision_recall_f1_overlap( ref_i, ref_p, ref_v, est_i, est_p, est_v ) assert np.allclose((p, r, f, o), (2 / 3.0, 2 / 3.0, 2 / 3.0, 1.0)) p, r, f, o = mir_eval.transcription_velocity.precision_recall_f1_overlap( ref_i, ref_p, ref_v, est_i, est_p, est_v, velocity_tolerance=0.3 ) assert np.allclose((p, r, f, o), (1.0, 1.0, 1.0, 1.0)) # Suppressing this warning. We know the notes are empty, that's not the point. @pytest.mark.filterwarnings("ignore:.*notes are empty") def test_precision_recall_f1_overlap_empty(): good_i, good_p, good_v = np.array([[0, 1]]), np.array([100]), np.array([1]) bad_i, bad_p, bad_v = np.empty((0, 2)), np.array([]), np.array([]) p, r, f, o = mir_eval.transcription_velocity.precision_recall_f1_overlap( good_i, good_p, good_v, bad_i, bad_p, bad_v ) assert (p, r, f, o) == (0.0, 0.0, 0.0, 0.0) p, r, f, o = mir_eval.transcription_velocity.precision_recall_f1_overlap( bad_i, bad_p, bad_v, good_i, good_p, good_v ) assert (p, r, f, o) == (0.0, 0.0, 0.0, 0.0) def test_precision_recall_f1_overlap_no_overlap(): p, r, f, o = mir_eval.transcription_velocity.precision_recall_f1_overlap( np.array([[1, 2]]), np.array([1]), np.array([1]), np.array([[3, 4]]), np.array([1]), np.array([1]), ) assert (p, r, f, o) == (0.0, 0.0, 0.0, 0.0) @pytest.mark.parametrize("velocity_data", file_sets, indirect=True) def test_regression(velocity_data): ( (ref_int, ref_pitch, ref_vel), (est_int, est_pitch, est_vel), expected_scores, ) = velocity_data scores = mir_eval.transcription_velocity.evaluate( ref_int, ref_pitch, ref_vel, est_int, est_pitch, est_vel ) assert scores.keys() == expected_scores.keys() for metric in scores: assert np.allclose(scores[metric], expected_scores[metric], atol=A_TOL), metric mir_eval-0.8.2/tests/test_util.py000066400000000000000000000253021475740344600170670ustar00rootroot00000000000000"""Unit tests for utils""" import collections import pytest import numpy as np import mir_eval from mir_eval import util def test_interpolate_intervals(): """Check that an interval set is interpolated properly, with boundaries conditions and out-of-range values. """ labels = list("abc") intervals = np.array([(n, n + 1.0) for n in range(len(labels))]) time_points = [-1.0, 0.1, 0.9, 1.0, 2.3, 4.0] expected_ans = ["N", "a", "a", "b", "c", "N"] assert ( util.interpolate_intervals(intervals, labels, time_points, "N") == expected_ans ) def test_interpolate_intervals_gap(): """Check that an interval set is interpolated properly, with gaps.""" labels = list("abc") intervals = np.array([[0.5, 1.0], [1.5, 2.0], [2.5, 3.0]]) time_points = [0.0, 0.75, 1.25, 1.75, 2.25, 2.75, 3.5] expected_ans = ["N", "a", "N", "b", "N", "c", "N"] assert ( util.interpolate_intervals(intervals, labels, time_points, "N") == expected_ans ) @pytest.mark.xfail(raises=ValueError) def test_interpolate_intervals_badtime(): """Check that interpolate_intervals throws an exception if input is unordered. """ labels = list("abc") intervals = np.array([(n, n + 1.0) for n in range(len(labels))]) time_points = [-1.0, 0.1, 0.9, 0.8, 2.3, 4.0] mir_eval.util.interpolate_intervals(intervals, labels, time_points) def test_intervals_to_samples(): """Check that an interval set is sampled properly, with boundaries conditions and out-of-range values. """ labels = list("abc") intervals = np.array([(n, n + 1.0) for n in range(len(labels))]) expected_times = [0.0, 0.5, 1.0, 1.5, 2.0, 2.5] expected_labels = ["a", "a", "b", "b", "c", "c"] result = util.intervals_to_samples( intervals, labels, offset=0, sample_size=0.5, fill_value="N" ) assert result[0] == expected_times assert result[1] == expected_labels expected_times = [0.25, 0.75, 1.25, 1.75, 2.25, 2.75] expected_labels = ["a", "a", "b", "b", "c", "c"] result = util.intervals_to_samples( intervals, labels, offset=0.25, sample_size=0.5, fill_value="N" ) assert result[0] == expected_times assert result[1] == expected_labels def test_intersect_files(): """Check that two non-identical produce correct results.""" flist1 = ["/a/b/abc.lab", "/c/d/123.lab", "/e/f/xyz.lab"] flist2 = ["/g/h/xyz.npy", "/i/j/123.txt", "/k/l/456.lab"] sublist1, sublist2 = util.intersect_files(flist1, flist2) assert sublist1 == ["/e/f/xyz.lab", "/c/d/123.lab"] assert sublist2 == ["/g/h/xyz.npy", "/i/j/123.txt"] sublist1, sublist2 = util.intersect_files(flist1[:1], flist2[:1]) assert sublist1 == [] assert sublist2 == [] def test_merge_labeled_intervals(): """Check that two labeled interval sequences merge correctly.""" x_intvs = np.array([[0.0, 0.44], [0.44, 2.537], [2.537, 4.511], [4.511, 6.409]]) x_labels = ["A", "B", "C", "D"] y_intvs = np.array([[0.0, 0.464], [0.464, 2.415], [2.415, 4.737], [4.737, 6.409]]) y_labels = [0, 1, 2, 3] expected_intvs = [ [0.0, 0.44], [0.44, 0.464], [0.464, 2.415], [2.415, 2.537], [2.537, 4.511], [4.511, 4.737], [4.737, 6.409], ] expected_x_labels = ["A", "B", "B", "B", "C", "D", "D"] expected_y_labels = [0, 0, 1, 2, 2, 2, 3] new_intvs, new_x_labels, new_y_labels = util.merge_labeled_intervals( x_intvs, x_labels, y_intvs, y_labels ) assert new_x_labels == expected_x_labels assert new_y_labels == expected_y_labels assert new_intvs.tolist() == expected_intvs # Check that invalid inputs raise a ValueError y_intvs[-1, -1] = 10.0 with pytest.raises(ValueError): util.merge_labeled_intervals(x_intvs, x_labels, y_intvs, y_labels) def test_boundaries_to_intervals(): # Basic tests boundaries = np.arange(10) correct_intervals = np.array([np.arange(10 - 1), np.arange(1, 10)]).T intervals = mir_eval.util.boundaries_to_intervals(boundaries) assert np.all(intervals == correct_intervals) def test_adjust_events(): # Test appending at the end events = np.arange(1, 11) labels = [str(n) for n in range(10)] new_e, new_l = mir_eval.util.adjust_events(events, labels, 0.0, 11.0) assert new_e[0] == 0.0 assert new_l[0] == "__T_MIN" assert new_e[-1] == 11.0 assert new_l[-1] == "__T_MAX" assert np.all(new_e[1:-1] == events) assert new_l[1:-1] == labels # Test trimming new_e, new_l = mir_eval.util.adjust_events(events, labels, 0.0, 9.0) assert new_e[0] == 0.0 assert new_l[0] == "__T_MIN" assert new_e[-1] == 9.0 assert np.all(new_e[1:] == events[:-1]) assert new_l[1:] == labels[:-1] def test_bipartite_match(): # This test constructs a graph as follows: # v9 -- (u0) # v8 -- (u0, u1) # v7 -- (u0, u1, u2) # ... # v0 -- (u0, u1, ..., u9) # # This structure and ordering of this graph should force Hopcroft-Karp to # hit each algorithm/layering phase # G = collections.defaultdict(list) u_set = [f"u{_:d}" for _ in range(10)] v_set = [f"v{_:d}" for _ in range(len(u_set) + 1)] for i, u in enumerate(u_set): for v in v_set[: -i - 1]: G[v].append(u) matching = util._bipartite_match(G) # Make sure that each u vertex is matched assert len(matching) == len(u_set) # Make sure that there are no duplicate keys lhs = {k for k in matching} rhs = {matching[k] for k in matching} assert len(matching) == len(lhs) assert len(matching) == len(rhs) # Finally, make sure that all detected edges are present in G for k in matching: v = matching[k] assert v in G[k] or k in G[v] def test_outer_distance_mod_n(): ref = [1.0, 2.0, 3.0] est = [1.1, 6.0, 1.9, 5.0, 10.0] expected = np.array( [ [0.1, 5.0, 0.9, 4.0, 3.0], [0.9, 4.0, 0.1, 3.0, 4.0], [1.9, 3.0, 1.1, 2.0, 5.0], ] ) actual = mir_eval.util._outer_distance_mod_n(ref, est) assert np.allclose(actual, expected) ref = [13.0, 14.0, 15.0] est = [1.1, 6.0, 1.9, 5.0, 10.0] expected = np.array( [ [0.1, 5.0, 0.9, 4.0, 3.0], [0.9, 4.0, 0.1, 3.0, 4.0], [1.9, 3.0, 1.1, 2.0, 5.0], ] ) actual = mir_eval.util._outer_distance_mod_n(ref, est) assert np.allclose(actual, expected) def test_match_events(): ref = [1.0, 2.0, 3.0] est = [1.1, 6.0, 1.9, 5.0, 10.0] expected = [(0, 0), (1, 2)] actual = mir_eval.util.match_events(ref, est, 0.5) assert actual == expected ref = [1.0, 2.0, 3.0, 11.9] est = [1.1, 6.0, 1.9, 5.0, 10.0, 0.0] expected = [(0, 0), (1, 2), (3, 5)] actual = mir_eval.util.match_events( ref, est, 0.5, distance=mir_eval.util._outer_distance_mod_n ) assert actual == expected def test_fast_hit_windows(): ref = [1.0, 2.0, 3.0] est = [1.1, 6.0, 1.9, 5.0, 10.0] ref_fast, est_fast = mir_eval.util._fast_hit_windows(ref, est, 0.5) ref_slow, est_slow = np.where(np.abs(np.subtract.outer(ref, est)) <= 0.5) assert np.all(ref_fast == ref_slow) assert np.all(est_fast == est_slow) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize( "intervals", [ # Test for ValueError when interval shape is invalid np.array([[1.0], [2.5], [5.0]]), # Test for ValueError when times are negative np.array([[1.0, -2.0], [2.5, 3.0], [5.0, 6.0]]), # Test for ValueError when duration is zero np.array([[1.0, 2.0], [2.5, 2.5], [5.0, 6.0]]), # Test for ValueError when duration is negative np.array([[1.0, 2.0], [2.5, 1.5], [5.0, 6.0]]), ], ) def test_validate_intervals(intervals): mir_eval.util.validate_intervals(intervals) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize( "events", [ # Test for ValueError when max_time is violated np.array([100.0, 100000.0]), # Test for ValueError when events aren't 1-d arrays np.array([[1.0, 2.0], [3.0, 4.0]]), # Test for ValueError when event times are not increasing np.array([1.0, 2.0, 5.0, 3.0]), ], ) def test_validate_events(events): mir_eval.util.validate_events(events) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize( "freqs", [ # Test for ValueError when max_freq is violated np.array([100, 10000]), # Test for ValueError when min_freq is violated np.array([2, 200]), # Test for ValueError when events aren't 1-d arrays np.array([[100, 200], [300, 400]]), # Test for ValueError when allow_negatives is false and negative values # are passed np.array([-100, 200]), ], ) def test_validate_frequencies(freqs): mir_eval.util.validate_frequencies(freqs, 5000, 20, allow_negatives=False) @pytest.mark.xfail(raises=ValueError) @pytest.mark.parametrize( "freqs", [ # Test for ValueError when max_freq is violated and allow_negatives=True np.array([100, -100000]), # Test for ValueError when min_freq is violated and allow_negatives=True np.array([-2, 200]), ], ) def test_validate_frequencies_negative(freqs): mir_eval.util.validate_frequencies(freqs, 5000, 20, allow_negatives=True) def test_has_kwargs(): def __test(target, f): assert target == mir_eval.util.has_kwargs(f) def f1(_): return None def f2(_=5): return None def f3(*_): return None def f4(_, **kw): return None def f5(_=5, **kw): return None assert not mir_eval.util.has_kwargs(f1) assert not mir_eval.util.has_kwargs(f2) assert not mir_eval.util.has_kwargs(f3) assert mir_eval.util.has_kwargs(f4) assert mir_eval.util.has_kwargs(f5) @pytest.mark.parametrize( "x,labels,x_true,lab_true", [ ( np.asarray([[10, 20], [0, 10]]), ["a", "b"], np.asarray([[0, 10], [10, 20]]), ["b", "a"], ), ( np.asarray([[0, 10], [10, 20]]), ["b", "a"], np.asarray([[0, 10], [10, 20]]), ["b", "a"], ), ], ) def test_sort_labeled_intervals_with_labels(x, labels, x_true, lab_true): xs, ls = mir_eval.util.sort_labeled_intervals(x, labels) assert np.allclose(xs, x_true) assert ls == lab_true @pytest.mark.parametrize( "x,x_true", [ (np.asarray([[10, 20], [0, 10]]), np.asarray([[0, 10], [10, 20]])), (np.asarray([[0, 10], [10, 20]]), np.asarray([[0, 10], [10, 20]])), ], ) def test_sort_labeled_intervals_without_labels(x, x_true): xs = mir_eval.util.sort_labeled_intervals(x) assert np.allclose(xs, x_true)