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contourpy algorithm kwarg, tests and docs
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‎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.

‎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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"""
@@ -1433,17 +1433,28 @@ def _process_args(self, *args, corner_mask=None, **kwargs):
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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 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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contour_generator = contourpy.contour_generator(
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x, y, z, name="mpl2014", corner_mask=self._corner_mask,
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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)
@@ -1771,6 +1782,15 @@ def _initialize_x_y(self, z):
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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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@@ -1791,5 +1811,5 @@ def _initialize_x_y(self, z):
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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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@@ -960,6 +960,7 @@ def _convert_validator_spec(key, conv):
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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/test_contour.py

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import platform
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import re
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import contourpy
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import numpy as np
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from numpy.testing import assert_array_almost_equal
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import matplotlib as mpl
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assert all(isinstance(a, LineCollection) for a in artists)
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assert all(same_color(a.get_color(), c)
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for a, c in zip(artists, colors))
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@pytest.mark.parametrize("algorithm, klass",
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[('mpl2005', contourpy.Mpl2005ContourGenerator),
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('mpl2014', contourpy.Mpl2014ContourGenerator),
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('serial', contourpy.SerialContourGenerator),
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('threaded', contourpy.ThreadedContourGenerator),
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('invalid', None)])
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def test_algorithm_name(algorithm, klass):
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z = np.array([[1.0, 2.0], [3.0, 4.0]])
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if klass is not None:
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cs = plt.contourf(z, algorithm=algorithm)
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assert isinstance(cs._contour_generator, klass)
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else:
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with pytest.raises(ValueError):
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plt.contourf(z, algorithm=algorithm)
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@pytest.mark.parametrize("algorithm",
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['mpl2005', 'mpl2014', 'serial', 'threaded'])
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def test_algorithm_supports_corner_mask(algorithm):
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z = np.array([[1.0, 2.0], [3.0, 4.0]])
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# All algorithms support corner_mask=False
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plt.contourf(z, algorithm=algorithm, corner_mask=False)
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# Only some algorithms support corner_mask=True
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if algorithm != 'mpl2005':
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plt.contourf(z, algorithm=algorithm, corner_mask=True)
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else:
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with pytest.raises(ValueError):
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plt.contourf(z, algorithm=algorithm, corner_mask=True)
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@image_comparison(baseline_images=['contour_all_algorithms'],
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extensions=['png'], remove_text=True)
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def test_all_algorithms():
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algorithms = ['mpl2005', 'mpl2014', 'serial', 'threaded']
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rng = np.random.default_rng(2981)
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x, y = np.meshgrid(np.linspace(0.0, 1.0, 10), np.linspace(0.0, 1.0, 6))
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z = np.sin(15*x)*np.cos(10*y) + rng.normal(scale=0.5, size=(6, 10))
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mask = np.zeros_like(z, dtype=bool)
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mask[3, 7] = True
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z = np.ma.array(z, mask=mask)
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_, axs = plt.subplots(2, 2)
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for ax, algorithm in zip(axs.ravel(), algorithms):
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ax.contourf(x, y, z, algorithm=algorithm)
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ax.contour(x, y, z, algorithm=algorithm, colors='k')
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ax.set_title(algorithm)

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