8000 Merge pull request #22567 from ianthomas23/use_contourpy · matplotlib/matplotlib@52b122e · GitHub
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Merge pull request #22567 from ianthomas23/use_contourpy
Use contourpy for quad contour calculations
2 parents a4f62d4 + 57b167e commit 52b122e

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‎.github/workflows/tests.yml

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# Install dependencies from PyPI.
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python -m pip install --upgrade $PRE \
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cycler fonttools kiwisolver numpy packaging pillow pyparsing \
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contourpy>=1.0.1 cycler fonttools kiwisolver numpy packaging pillow pyparsing \
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python-dateutil setuptools-scm \
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-r requirements/testing/all.txt \
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${{ matrix.extra-requirements }}

‎doc/api/next_api_changes/behavior/22229-TAC.rst

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AritistList proxies copy contents on iteration
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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ArtistList proxies copy contents on iteration
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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When iterating over the contents of the the dynamically generated proxy lists
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for the Artist-type accessors (see :ref:`Behavioural API Changes 3.5 - Axes

‎doc/api/next_api_changes/behavior/22567-IT.rst

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New algorithm keyword argument to contour and contourf
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The contouring functions `~matplotlib.axes.Axes.contour` and
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`~matplotlib.axes.Axes.contourf` have a new keyword argument *algorithm* to
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control which algorithm is used to calculate the contours. There is a choice
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of four algorithms to use, and the default is to use ``algorithm='mpl2014'``
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which is the same algorithm that Matplotlib has been using since 2014.
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Other possible values of the *algorithm* keyword argument are ``'mpl2005'``,
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``'serial'`` and ``'threaded'``; see the
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`ContourPy documentation <https://contourpy.readthedocs.io>`_ for further
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details.

‎doc/users/next_whats_new/use_contourpy.rst

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New external dependency ContourPy used for quad contour calculations
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--------------------------------------------------------------------
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Previously Matplotlib shipped its own C++ code for calculating the contours of
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quad grids. Now the external library
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`ContourPy <https://github.com/contourpy/contourpy>`_ is used instead. There
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is a choice of four algorithms to use, controlled by the *algorithm* keyword
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argument to the functions `~matplotlib.axes.Axes.contour` and
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`~matplotlib.axes.Axes.contourf`. The default behaviour is to use
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``algorithm='mpl2014'`` which is the same algorithm that Matplotlib has been
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using since 2014.
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See the `ContourPy documentation <https://contourpy.readthedocs.io>`_ for
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further details of the different algorithms.
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.. note::
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Contour lines and polygons produced by ``algorithm='mpl2014'`` will be the
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same as those produced before this change to within floating-point
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tolerance. The exception is for duplicate points, i.e. contours containing
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adjacent (x, y) points that are identical; previously the duplicate points
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were removed, now they are kept. Contours affected by this will produce the
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same visual output, but there will be a greater number of points in the
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contours.
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The locations of contour labels obtained by using
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`~matplotlib.axes.Axes.clabel` may also be different.

‎environment.yml

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- conda-forge
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dependencies:
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- cairocffi
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- contourpy>=1.0.1
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- cycler>=0.10.0
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- fonttools>=4.22.0
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- kiwisolver>=1.0.1

‎lib/matplotlib/contour.py

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@@ -1420,7 +1420,7 @@ class QuadContourSet(ContourSet):
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%(contour_set_attributes)s
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"""
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def _process_args(self, *args, corner_mask=None, **kwargs):
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def _process_args(self, *args, corner_mask=None, algorithm=None, **kwargs):
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"""
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Process args and kwargs.
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"""
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contour_generator = args[0]._contour_generator
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self._mins = args[0]._mins
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self._maxs = args[0]._maxs
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self._algorithm = args[0]._algorithm
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else:
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import matplotlib._contour as _contour
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import contourpy
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if algorithm is None:
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algorithm = mpl.rcParams['contour.algorithm']
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mpl.rcParams.validate["contour.algorithm"](algorithm)
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self._algorithm = algorithm
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if corner_mask is None:
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corner_mask = mpl.rcParams['contour.corner_mask']
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if self._algorithm == "mpl2005":
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# mpl2005 does not support corner_mask=True so if not
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# specifically requested then disable it.
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corner_mask = False
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else:
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corner_mask = mpl.rcParams['contour.corner_mask']
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self._corner_mask = corner_mask
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x, y, z = self._contour_args(args, kwargs)
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_mask = ma.getmask(z)
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if _mask is ma.nomask or not _mask.any():
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_mask = None
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contour_generator = _contour.QuadContourGenerator(
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x, y, z.filled(), _mask, self._corner_mask, self.nchunk)
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contour_generator = contourpy.contour_generator(
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x, y, z, name=self._algorithm, corner_mask=self._corner_mask,
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line_type=contourpy.LineType.SeparateCode,
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fill_type=contourpy.FillType.OuterCode,
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chunk_size=self.nchunk)
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t = self.get_transform()
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Hatching is supported in the PostScript, PDF, SVG and Agg
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backends only.
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algorithm : {'mpl2005', 'mpl2014', 'serial', 'threaded'}, optional
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Which contouring algorithm to use to calculate the contour lines and
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polygons. The algorithms are implemented in
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`ContourPy <https://github.com/contourpy/contourpy>`_, consult the
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`ContourPy documentation <https://contourpy.readthedocs.io>`_ for
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further information.
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The default is taken from :rc:`contour.algorithm`.
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data : indexable object, optional
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DATA_PARAMETER_PLACEHOLDER
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3. `.contour` and `.contourf` use a `marching squares
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<https://en.wikipedia.org/wiki/Marching_squares>`_ algorithm to
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compute contour locations. More information can be found in
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the source ``src/_contour.h``.
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`ContourPy documentation <https://contourpy.readthedocs.io>`_.
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""")

‎lib/matplotlib/mpl-data/matplotlibrc

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## * CONTOUR PLOTS *
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## ***************************************************************************
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#contour.negative_linestyle: dashed # string or on-off ink sequence
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#contour.corner_mask: True # {True, False, legacy}
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#contour.corner_mask: True # {True, False}
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#contour.linewidth: None # {float, None} Size of the contour line
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# widths. If set to None, it falls back to
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# `line.linewidth`.
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#contour.algorithm: mpl2014 # {mpl2005, mpl2014, serial, threaded}
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## ***************************************************************************

‎lib/matplotlib/rcsetup.py

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"contour.negative_linestyle": _validate_linestyle,
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"contour.corner_mask": validate_bool,
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"contour.linewidth": validate_float_or_None,
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"contour.algorithm": ["mpl2005", "mpl2014", "serial", "threaded"],
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# errorbar props
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"errorbar.capsize": validate_float,

‎lib/matplotlib/tests/baseline_images/test_contour/contour_all_algorithms.png

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‎lib/matplotlib/tests/baseline_images/test_patheffects/patheffect2.pdf

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‎lib/matplotlib/tests/baseline_images/test_patheffects/patheffect2.png

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