8000 MNT: effect pcolorarg deprecation and change default shading to auto · matplotlib/matplotlib@c1c02f0 · GitHub
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jklymakjklymak
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MNT: effect pcolorarg deprecation and change default shading to auto
TST: udate tests for new pcolormeshdefault DOC
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-29
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‎doc/api/next_api_changes/behavior/20268-JMK.rst‎

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pcolor(mesh) shading defaults to auto
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The *shading* kwarg for `.Axes.pcolormesh` and `.Axes.pcolor` default
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has been changed to 'auto'.
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Passing ``Z(M, N)``, ``x(N)``, ``y(M)`` to ``pcolormesh`` with
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``shading='flat'`` will now raise a ``TypeError``. Use
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``shading='auto'`` or ``shading='nearest'`` for ``x`` and ``y``
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to be treated as cell centers, or drop the last column and row
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of ``Z`` to get the old behavior with ``shading='flat'``.

‎lib/matplotlib/axes/_axes.py‎

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Original file line numberDiff line numberDiff line change
@@ -5603,7 +5603,7 @@ def imshow(self, X, cmap=None, norm=None, aspect=None,
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self.add_image(im)
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return im
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def _pcolorargs(self, funcname, *args, shading='flat', **kwargs):
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def _pcolorargs(self, funcname, *args, shading='auto', **kwargs):
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# - create X and Y if not present;
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# - reshape X and Y as needed if they are 1-D;
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# - check for proper sizes based on `shading` kwarg;
@@ -5675,25 +5675,16 @@ def _pcolorargs(self, funcname, *args, shading='flat', **kwargs):
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shading = 'flat'
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if shading == 'flat':
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if not (ncols in (Nx, Nx - 1) and nrows in (Ny, Ny - 1)):
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if (Nx, Ny) != (ncols + 1, nrows + 1):
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raise TypeError('Dimensions of C %s are incompatible with'
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' X (%d) and/or Y (%d); see help(%s)' % (
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C.shape, Nx, Ny, funcname))
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if (ncols == Nx or nrows == Ny):
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_api.warn_deprecated(
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"3.3", message="shading='flat' when X and Y have the same "
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"dimensions as C is deprecated since %(since)s. Either "
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"specify the corners of the quadrilaterals with X and Y, "
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"or pass shading='auto', 'nearest' or 'gouraud', or set "
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"rcParams['pcolor.shading']. This will become an error "
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"%(removal)s.")
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C = C[:Ny - 1, :Nx - 1]
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else: # ['nearest', 'gouraud']:
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if (Nx, Ny) != (ncols, nrows):
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raise TypeError('Dimensions of C %s are incompatible with'
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' X (%d) and/or Y (%d); see help(%s)' % (
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C.shape, Nx, Ny, funcname))
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if shading in ['nearest', 'auto']:
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if shading == 'nearest':
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# grid is specified at the center, so define corners
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# at the midpoints between the grid centers and then use the
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# flat algorithm.

‎lib/matplotlib/mpl-data/matplotlibrc‎

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@@ -130,7 +130,7 @@
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#markers.fillstyle: full # {full, left, right, bottom, top, none}
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#pcolor.shading: flat
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#pcolor.shading: auto
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#pcolormesh.snap: True # Whether to snap the mesh to pixel boundaries. This is
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# provided solely to allow old test images to remain
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# unchanged. Set to False to obtain the previous behavior.

‎lib/matplotlib/tests/test_axes.py‎

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Original file line numberDiff line numberDiff line change
@@ -1243,22 +1243,14 @@ def test_pcolornearestunits(fig_test, fig_ref):
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ax.pcolormesh(x2, y2, Z, shading='nearest')
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@check_figures_equal(extensions=["png"])
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def test_pcolordropdata(fig_test, fig_ref):
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ax = fig_test.subplots()
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x = np.arange(0, 10)
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y = np.arange(0, 4)
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def test_pcolorflaterror():
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fig, ax = plt.subplots()
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x = np.arange(0, 9)
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y = np.arange(0, 3)
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np.random.seed(19680801)
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Z = np.random.randn(3, 9)
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# fake dropping the data
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ax.pcolormesh(x[:-1], y[:-1], Z[:-1, :-1], shading='flat')
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ax = fig_ref.subplots()
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# test dropping the data...
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x2 = x[:-1]
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y2 = y[:-1]
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with pytest.warns(MatplotlibDeprecationWarning):
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ax.pcolormesh(x2, y2, Z, shading='flat')
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with pytest.raises(TypeError, match='Dimensions of C'):
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ax.pcolormesh(x, y, Z, shading='flat')
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@check_figures_equal(extensions=["png"])
@@ -1268,13 +1260,15 @@ def test_pcolorauto(fig_test, fig_ref):
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y = np.arange(0, 4)
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np.random.seed(19680801)
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Z = np.random.randn(3, 9)
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ax.pcolormesh(x, y, Z, shading='auto')
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# this is the same as flat; note that auto is default
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ax.pcolormesh(x, y, Z)
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ax = fig_ref.subplots()
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# specify the centers
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x2 = x[:-1] + np.diff(x) / 2
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y2 = y[:-1] + np.diff(y) / 2
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ax.pcolormesh(x2, y2, Z, shading='auto')
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# this is 4E1E same as nearest:
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ax.pcolormesh(x2, y2, Z)
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@image_comparison(['canonical'])

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