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Vedant Nanda
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Revert "Merge branch 'first_try' of https://github.com/nvedant07/matplotlib into first_try"
This reverts commit 85f63e3, reversing changes made to f32377f.
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‎.coveragerc

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[run]
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branch = true
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source =
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source=
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matplotlib
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mpl_toolkits
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omit = matplotlib/_version.py
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[report]
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exclude_lines =

‎.travis.yml

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env: MOCK=mock NUMPY=numpy==1.7.1
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- python: 3.4
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env: PYTHON_ARGS=-OO
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- python: 3.5
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env: PANDAS=pandas DELETE_FONT_CACHE=1
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- python: 3.5
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env: BUILD_DOCS=true
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- python: 3.5
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# Workaround for pytest-xdist flaky collection order
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# https://github.com/pytest-dev/pytest/issues/920
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# https://github.com/pytest-dev/pytest/issues/1075
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export PYTHONHASHSEED=$(python -c 'import random; print(random.randint(1, 4294967295))')
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export PYTHONHASHSEED=$(shuf -i 1-4294967295 -n 1)
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echo PYTHONHASHSEED=$PYTHONHASHSEED
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echo The following args are passed to pytest $PYTEST_ARGS $RUN_PEP8

‎INSTALL

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python -m pip install matplotlib
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In case Python 2.7 or 3.4 are not installed for all users,
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the Microsoft Visual C++ 2008
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(`64 bit <https://www.microsoft.com/en-us/download/details.aspx?id=15336>`__
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the Microsoft Visual C++ 2008 (
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`64 bit <https://www.microsoft.com/en-us/download/details.aspx?id=15336>`__
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or
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`32 bit <https://www.microsoft.com/en-us/download/details.aspx?id=29>`__
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for Python 2.7) or Microsoft Visual C++ 2010
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(`64 bit <https://www.microsoft.com/en-us/download/details.aspx?id=14632>`__
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for Python 2.7) or Microsoft Visual C++ 2010 (
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`64 bit <https://www.microsoft.com/en-us/download/details.aspx?id=14632>`__
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or
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`32 bit <https://www.microsoft.com/en-us/download/details.aspx?id=5555>`__
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for Python 3.4) redistributable packages need to be installed.
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If you want to try the many demos that come in the matplotlib source
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distribution, download the :file:`*.tar.gz` file and look in the
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:file:`examples` subdirectory.
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To run the test suite:
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* extract the :file:`lib\\matplotlib\\tests` or
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:file:`lib\\mpl_toolkits\\tests` directories from the source distribution;
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* install test dependencies: `pytest <https://pypi.python.org/pypi/pytest>`_,
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`mock <https://pypi.python.org/pypi/mock>`_, Pillow, MiKTeX, GhostScript,
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ffmpeg, avconv, mencoder, ImageMagick, and `Inkscape
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<https://inkscape.org/>`_;
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* run ``py.test path\\to\\tests\\directory``.
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To run the test suite, copy the :file:`lib\\matplotlib\\tests` and
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:file:`lib\\mpl_toolkits\\tests` directories from the source
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distribution to :file:`sys.prefix\\Lib\\site-packages\\matplotlib` and
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:file:`sys.prefix\\Lib\\site-packages\\mpl_toolkits` respectively, and
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install `nose <https://pypi.python.org/pypi/nose>`_, `mock
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<https://pypi.python.org/pypi/mock>`_, Pillow, MiKTeX, GhostScript,
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ffmpeg, avconv, mencoder, ImageMagick, and `Inkscape
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<https://inkscape.org/>`_.
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The standard environment variables `CC`, `CXX`, `PKG_CONFIG` are respected.
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This means you can set them if your toolchain is prefixed. This may be used for
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cross compiling.
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::
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export CC=x86_64-pc-linux-gnu-gcc
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export CXX=x86_64-pc-linux-gnu-g++
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export PKG_CONFIG=x86_64-pc-linux-gnu-pkg-config
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Once you have satisfied the requirements detailed below (mainly
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python, numpy, libpng and freetype), you can build matplotlib.
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::
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python, numpy, libpng and freetype), you can build matplotlib::
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cd matplotlib
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python setup.py build
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Dependencies for python 2
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^^^^^^^^^^^^^^^^^^^^^^^^^
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`backports.functools_lru_cache <https://pypi.python.org/pypi/backports.functools_lru_cache>`_
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`functools32 <https://pypi.python.org/pypi/functools32>`_
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Required for compatibility if running on Python 2.7.
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`subprocess32 <https://pypi.python.org/pypi/subprocess32/>`_

‎README.rst

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After installation, you can launch the test suite::
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py.test
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python tests.py
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Or from the Python interpreter::
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import matplotlib
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matplotlib.test()
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Consider reading http://matplotlib.org/devel/coding_guide.html#testing for
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more information. Note that the test suite requires pytest and, on Python 2.7,
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mock. Please install with pip or your package manager of choice.
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more information. Note that the test suite requires nose and on Python 2.7 mock
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which are not installed by default. Please install with pip or your package
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manager of choice.
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Contact
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=======

‎README.win.md

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# this package is only available in the conda-forge channel
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conda install -c conda-forge msinttypes
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# for python 2.7
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conda install -c conda-forge backports.functools_lru_cache
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conda install -c conda-forge functools32
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# copy the libs which have "wrong" names
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set LIBRARY_LIB=%CONDA_DEFAULT_ENV%\Library\lib

‎appveyor.yml

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CMD_IN_ENV: "cmd /E:ON /V:ON /C obvci_appveyor_python_build_env.cmd"
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# Workaround for https://github.com/conda/conda-build/issues/636
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PYTHONIOENCODING: "UTF-8"
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PYTEST_ARGS: -ra --timeout=300 --durations=25 -n %NUMBER_OF_PROCESSORS% --cov-report= --cov=lib -m "not network"
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PYTEST_ARGS: -ra --timeout=300 --durations=25 -n %NUMBER_OF_PROCESSORS% --cov-report= --cov=lib
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USE_PYTEST: no
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PYTHONHASHSEED: 0 # Workaround for pytest-xdist flaky collection order
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# https://github.com/pytest-dev/pytest/issues/920
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mock sphinx
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- activate test-environment
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- cmd: echo %PYTHON_VERSION% %TARGET_ARCH%
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- cmd: IF %PYTHON_VERSION% == 2.7 conda install -q backports.functools_lru_cache
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- cmd: IF %PYTHON_VERSION% == 2.7 conda install -q functools32
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# pytest-cov>=2.3.1 due to https://github.com/pytest-dev/pytest-cov/issues/124
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- conda install -q pytest "pytest-cov>=2.3.1" pytest-timeout pytest-xdist
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- python visual_tests.py
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- pip install codecov
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- codecov -e PYTHON_VERSION PLATFORM
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- if x%USE_PYTEST% == xyes pip install codecov
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- if x%USE_PYTEST% == xyes codecov -e PYTHON_VERSION PLATFORM
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after_test:
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# After the tests were a success, build packages (wheels and conda)

‎build_alllocal.cmd

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:: # this package is only available in the conda-forge channel
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:: conda install -c conda-forge msinttypes
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:: if you build on py2.7:
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:: conda install -c conda-forge backports.functools_lru_cache
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:: conda install -c conda-forge functools32
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set TARGET=bdist_wheel
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IF [%1]==[] (

‎ci/codecov.yml

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paths: '!lib/.*/tests/.*'
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tests:
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target: 97.9%
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target: 97.7%
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paths: 'lib/.*/tests/.*'

‎ci/conda_recipe/meta.yaml

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- freetype 2.6*
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- msinttypes # [win]
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- cycler >=0.10
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- pytest >=3.0.0
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- nose
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- pyparsing
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- pytz
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# - py2cairo # [linux and py2k]
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- zlib 1.2* # [win]
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- pyqt # [not osx]
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- tk 8.5* # [linux]
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- backports.functools_lru_cache # [py2k]
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- functools32 # [py2k]
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run:
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- python
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- libpng >=1.6.21,<1.7
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- pyqt # [not osx]
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- tk 8.5* # [linux and win]
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- backports.functools_lru_cache # [py2k]
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- functools32 # [py2k]
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test:
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imports:

‎doc/_templates/layout.html

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VERSION: '{{ release|e }}',
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COLLAPSE_INDEX: false,
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FILE_SUFFIX: '{{ '' if no_search_suffix else file_suffix }}',
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HAS_SOURCE: {{ has_source|lower }},
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SOURCELINK_SUFFIX: '{{ sourcelink_suffix }}'
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HAS_SOURCE: {{ has_source|lower }}
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};
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</script>
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{%- for scriptfile in script_files %}

‎doc/api/api_changes.rst

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For new features that were added to Matplotlib, please see
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:ref:`whats-new`.
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API Changes in 2.0.1
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====================
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Extensions to `matplotlib.backend_bases.GraphicsContextBase`
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------------------------------------------------------------
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To better support controlling the color of hatches, the method
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`matplotlib.backend_bases.GraphicsContextBase.set_hatch_color` was
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added to the expected API of ``GraphicsContext`` classes. Calls to
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this method are currently wrapped with a ``try:...except Attribute:``
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block to preserve back-compatibility with any third-party backends
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which do not extend `~matplotlib.backend_bases.GraphicsContextBase`.
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This value can be accessed in the backends via
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`matplotlib.backend_bases.GraphicsContextBase.get_hatch_color` (which
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was added in 2.0 see :ref:`gc_get_hatch_color_wn`) and should be used
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to color the hatches.
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In the future there may also be ``hatch_linewidth`` and
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``hatch_density`` related methods added. It is encouraged, but not
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required that third-party backends extend
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`~matplotlib.backend_bases.GraphicsContextBase` to make adapting to
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these changes easier.
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API Changes in 2.0.0
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====================

‎doc/api/api_changes/2017-01-19-BFLC.rst

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‎doc/api/api_changes/2017-01-30-AL_negative_bar_height_width.rst

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‎doc/api/api_changes/2017-02-12-JKS.rst

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‎doc/api/api_changes/2017-02-25-AL_dbackend.rst

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‎doc/api/dviread.rst

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.. automodule:: matplotlib.dviread
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:members:
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:undoc-members:
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:exclude-members: Dvi
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:show-inheritance:
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.. autoclass:: matplotlib.dviread.Dvi
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:members: __iter__,close
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:show-inheritance:

‎doc/devel/README.txt

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‎doc/devel/coding_guide.rst

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When doing backports please include the branch you backported the
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We do a backport from master to v2.0.x assuming:
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* ``DANGER`` is a read/write remote branch of the matplotlib/matplotlib repo
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Assuming we have ``matplotlib`` as a read-only remote to the
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matplotlib/matplotlib repo and ``DANGER`` as a read/write remote to
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the matplotlib/matplotlib repo, we do a backport from master to 2.x.
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The ``TARGET_SHA`` is the hash of the merge commit you would like to
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backport. This can be read off of the github PR page (in the UI with
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the merge notification) or through the git CLI tools.::
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git fetch matplotlib
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git checkout v2.0.x
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git merge --ff-only matplotlib/v2.0.x
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git checkout v2.x
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git merge --ff-only matplotlib/v2.x
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git cherry-pick -m 1 TARGET_SHA
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git log --graph --decorate # to look at it
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gitk # to look at it
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# local tests? (use your judgment)
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git push DANGER v2.0.x
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git push DANGER v2.x
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# leave a comment on PR noting sha of the resulting commit
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‎doc/devel/contributing.rst

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python tests.py
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.. _pytest: http://doc.pytest.org/en/latest/
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.. _nose: https://nose.readthedocs.io/en/latest/
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.. _pep8: https://pep8.readthedocs.io/en/latest/
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.. _mock: https://docs.python.org/dev/library/unittest.mock.html
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.. _Ghostscript: https://www.ghostscript.com/
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.. _Inkscape: https://inkscape.org>
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.. note::
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**Additional dependencies for testing**: pytest_ (version 3.0 or later),
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mock_ (if python < 3.3), Ghostscript_, Inkscape_
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**Additional dependencies for testing**: nose_ (version 1.0 or later), `mock
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<https://docs.python.org/dev/library/unittest.mock.html>`_ (if python < 3.3), `Ghostscript
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<https://www.ghostscript.com/>`_, `Inkscape <https://inkscape.org>`_
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.. seealso::
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If you are working on a custom backend, the *backend* setting in
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:file:`matplotlibrc` (:ref:`customizing-matplotlib`) supports an
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external backend via the ``module`` directive. If
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external backend via the ``module`` directive. if
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:file:`my_backend.py` is a Matplotlib backend in your
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:envvar:`PYTHONPATH`, you can set it on one of several ways
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* in :file:`matplotlibrc`::
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backend : module://my_backend
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* with the :envvar:`MPLBACKEND` environment variable::
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> export MPLBACKEND="module://my_backend"
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> python simple_plot.py
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* from the command shell with the `-d` flag::
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* with the use directive in your script::
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import matplotlib

‎doc/devel/gitwash/branch_dropdown.png

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