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FIX: add shading='nearest' and warn on mis-sized shading='flat'
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‎doc/users/next_whats_new/2020-01-18-pcolorshadingoptions.rst

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Pcolor and Pcolormesh now accept shading='nearest' and 'auto'
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-------------------------------------------------------------
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Previously `.axes.Axes.pcolor` and `.axes.Axes.pcolormesh` handled
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the situation where *x* and *y* have the same (respective) size as *C* by
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dropping the last row and column of *C*, and *x* and *y* are regarded as the
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edges of the remaining rows and columns in *C*. However, many users probably
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really want *x* and *y* centered on the rows and columns of *C*.
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To accommodate this, ``shading='nearest'`` and ``shading='auto'`` are
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new allowed strings for the ``shading`` kwarg. ``'nearest'`` will center the
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color on *x* and *y* if *x* and *y* have the same dimensions as *C*
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(otherwise an error will be thrown). ``shading='auto'`` will choose 'flat'
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or 'nearest' based on the size of *X*, *Y*, *C*.
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If ``shading='flat'`` then *X*, and *Y* should have dimensions one larger
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than *C*. If *X* and *Y* have the same dimensions as *C*, then the previous
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behavior is used and the last row and column of *C* are dropped, and a
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Deprecation Warning is raised.
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Users can also specify this by the new :rc:`pcolor.shading` in their
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``.matplotlibrc`` or via `.rcParams`.
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See :doc:`pcolormesh </gallery/images_contours_and_fields/pcolormesh_grids>`
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for examples.

‎examples/images_contours_and_fields/pcolormesh_grids.py

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"""
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============================
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Pcolormesh grids and shading
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============================
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`.axes.Axes.pcolormesh` and `~.axes.Axes.pcolor` have a few options for
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how grids are laid out and the shading between the grid points.
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Generally, if *Z* is size *(M, N)* then the grid *X* and *Y* can be
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specified with either size *(M+1, N+1)* or *(M, N)*, depending on the
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argument for the ``shading`` keyword argument. Note that below we specify
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vectors *x* as either length N or N+1 and *y* as length M or M+1, and
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`~.axes.Axes.pcolormesh` internally makes the mesh matrices *X* and *Y* from
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the input vectors.
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"""
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import matplotlib
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import matplotlib.pyplot as plt
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import numpy as np
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###############################################################################
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# Flat Shading
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# ------------
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#
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# The grid specification with the least assumptions is ``shading='flat'``
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# and if the grid is one larger than the data in each dimesion, i.e. has size
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# *(M+1, N+1)*. In that case *X* and *Y* sepcify the corners of quadrilaterals
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# that are colored with the values in *Z*. Here we specify the edges of the
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# *(3, 5)* quadrilaterals with *X* and *Y* that are *(4, 6)*.
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np.random.seed(19680801)
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Z = np.arange(15).reshape(3, 5)
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x = np.arange(6) # len = 6
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y = np.arange(4) # len = 4
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fig, ax = plt.subplots()
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ax.pcolormesh(x, y, Z, shading='flat', vmin=Z.min(), vmax=Z.max())
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def _annote(ax, x, y, title):
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# this all gets repeated below:
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X, Y = np.meshgrid(x, y)
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ax.plot(X.flat, Y.flat, 'o', color='m')
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ax.set_xlim(-0.7, 5.2)
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ax.set_ylim(-0.7, 3.2)
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ax.set_title(title)
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_annote(ax, x, y, "shading='flat'")
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###############################################################################
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# Flat Shading, same size grid
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# ----------------------------
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#
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# Often, however, data is provided where *X* and *Y* match the size of *Z*.
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# As of Matplotlib v3.3, ``shading='flat'`` is deprecated when this is the
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# case, a warning is raised, and the last row and column of *Z* are dropped.
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# This dropping of the last row and column is what Matplotlib did silently
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# previous to v3.3, and is compatible with what Matlab does.
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x = np.arange(5) # len = 5
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y = np.arange(3) # len = 3
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fig, ax = plt.subplots()
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ax.pcolormesh(x, y, Z, shading='flat', vmin=Z.min(), vmax=Z.max())
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_annote(ax, x, y, "shading='flat': X, Y, C same size")
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###############################################################################
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# Nearest Shading, same size grid
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# -------------------------------
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#
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# Usually, dropping a row and column of data is not what the user means when
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# the make *X*, *Y* and *Z* all the same size. For this case, Matplotlib
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# allows ``shading='nearest'`` and centers the colored qudrilaterals on the
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# grid points.
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#
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# If a grid that is not the correct size is passed with ``shading='nearest'``
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# an error is raised.
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fig, ax = plt.subplots()
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ax.pcolormesh(x, y, Z, shading='nearest', vmin=Z.min(), vmax=Z.max())
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_annote(ax, x, y, "shading='nearest'")
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###############################################################################
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# Auto Shading
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# ------------
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#
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# Its possible that the user would like the code to automatically choose
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# which to use, in which case ``shading='auto'`` will decide whether to
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# use 'flat' or 'nearest' shading based on the sizes of *X*, *Y* and *Z*.
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fig, axs = plt.subplots(2, 1, constrained_layout=True)
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ax = axs[0]
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x = np.arange(5) # len = 5
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y = np.arange(3) # len = 3
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ax.pcolormesh(x, y, Z, shading='auto', vmin=Z.min(), vmax=Z.max())
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_annote(ax, x, y, "shading='auto'; X, Y, Z: same size (nearest)")
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ax = axs[1]
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x = np.arange(6) # len = 5
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y = np.arange(4) # len = 3
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ax.pcolormesh(x, y, Z, shading='auto', vmin=Z.min(), vmax=Z.max())
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_annote(ax, x, y, "shading='auto'; X, Y one larger than Z (flat)")
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###############################################################################
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# Gouraud Shading
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# ---------------
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#
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# `Gouraud shading <https://en.wikipedia.org/wiki/Gouraud_shading>`_ can also
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# be specified, where the colour in the quadrilaterals is linearly
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# interpolated between the grid points. The sizes of *X*, *Y*, *Z* must
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# be the same.
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fig, ax = plt.subplots(constrained_layout=True)
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x = np.arange(5) # len = 5
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y = np.arange(3) # len = 3
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ax.pcolormesh(x, y, Z, shading='gouraud', vmin=Z.min(), vmax=Z.max())
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_annote(ax, x, y, "shading='gouruad'; X, Y same size as Z")
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plt.show()
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#############################################################################
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#
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# ------------
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#
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# References
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# """"""""""
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#
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# The use of the following functions and methods is shown in this example:
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matplotlib.axes.Axes.pcolormesh
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matplotlib.pyplot.pcolormesh

‎examples/images_contours_and_fields/pcolormesh_levels.py

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"""
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==========
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pcolormesh
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Pcolormesh
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==========
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Shows how to combine Normalization and Colormap instances to draw "levels" in
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`~.axes.Axes.pcolor`, `~.axes.Axes.pcolormesh` and `~.axes.Axes.imshow` type
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plots in a similar way to the levels keyword argument to contour/contourf.
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`.axes.Axes.pcolormesh` allows you to generate 2-D image-style plots. Note it
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is faster than the similar `~.axes.Axes.pcolor`.
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"""
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import matplotlib
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from matplotlib.ticker import MaxNLocator
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import numpy as np
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###############################################################################
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# Basic Pcolormesh
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# ----------------
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#
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# We usually specify a pcolormesh by defining the edge of quadrilaterals and
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# the value of the quadrilateral. Note that here *x* and *y* each have one
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# extra element than Z in the respective dimension.
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np.random.seed(19680801)
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Z = np.random.rand(6, 10)
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x = np.arange(-0.5, 10, 1) # len = 11
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y = np.arange(4.5, 11, 1) # len = 7
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fig, ax = plt.subplots()
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ax.pcolormesh(x, y, Z)
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###############################################################################
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# Non-rectilinear Pcolormesh
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# --------------------------
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#
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# Note that we can also specify matrices for *X* and *Y* and have
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# non-rectilinear quadrilaterals.
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x = np.arange(-0.5, 10, 1) # len = 11
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y = np.arange(4.5, 11, 1) # len = 7
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X, Y = np.meshgrid(x, y)
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X = X + 0.2 * Y # tilt the coordinates.
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Y = Y + 0.3 * X
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fig, ax = plt.subplots()
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ax.pcolormesh(X, Y, Z)
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###############################################################################
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# Centered Coordinates
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# ---------------------
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#
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# Often a user wants to pass *X* and *Y* with the same sizes as *Z* to
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# `.axes.Axes.pcolormesh`. This is also allowed if ``shading='auto'`` is
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# passed (default set by :rc:`pcolor.shading`). Pre Matplotlib 3.3,
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# ``shading='flat'`` would drop the last column and row of *Z*; while that
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# is still allowed for back compatibility purposes, a Deprecation Warning is
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# raised.
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x = np.arange(10) # len = 10
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y = np.arange(6) # len = 6
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X, Y = np.meshgrid(x, y)
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fig, axs = plt.subplots(2, 1, sharex=True, sharey=True)
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axs[0].pcolormesh(X, Y, Z, vmin=np.min(Z), vmax=np.max(Z), shading='auto')
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axs[0].set_title("shading='auto' = 'nearest'")
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axs[1].pcolormesh(X, Y, Z, vmin=np.min(Z), vmax=np.max(Z), shading='flat')
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axs[1].set_title("shading='flat'")
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###############################################################################
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# Making levels using Norms
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# -------------------------
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#
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# Shows how to combine Normalization and Colormap instances to draw
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# "levels" in `.axes.Axes.pcolor`, `.axes.Axes.pcolormesh`
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# and `.axes.Axes.imshow` type plots in a similar
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# way to the levels keyword argument to contour/contourf.
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# make these smaller to increase the resolution
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dx, dy = 0.05, 0.05

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