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timhoffmtimhoffm
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Merge pull request #19703 from jklymak/doc-new-gallery
DOC: new plot gallery
2 parents 10a0e82 + 6e4c4be commit 183018c

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‎doc/_templates/layout.html

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<li><a href="{{ pathto('users/installing') }}">Installation</a></li>
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<li><a href="{{ pathto('contents') }}">Documentation</a></li>
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<li><a href="{{ pathto('api/index') }}">API</a></li>
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<li><a href="{{ pathto('plot_types/index') }}">Plot Types</a></li>
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<li><a href="{{ pathto('gallery/index') }}">Examples</a></li>
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<li><a href="{{ pathto('tutorials/index') }}">Tutorials</a></li>
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<li><a href="{{ pathto('devel/index') }}">Contributing</a></li>

‎doc/conf.py

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# Sphinx gallery configuration
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sphinx_gallery_conf = {
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'examples_dirs': ['../examples', '../tutorials'],
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'examples_dirs': ['../examples', '../tutorials', '../plot_types'],
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'filename_pattern': '^((?!sgskip).)*$',
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'gallery_dirs': ['gallery', 'tutorials'],
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'gallery_dirs': ['gallery', 'tutorials', 'plot_types'],
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'doc_module': ('matplotlib', 'mpl_toolkits'),
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'reference_url': {
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'matplotlib': None,

‎doc/sphinxext/gallery_order.py

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'../examples/showcase',
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'../tutorials/introductory',
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'../tutorials/intermediate',
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'../tutorials/advanced']
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'../tutorials/advanced',
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'../plot_types/basic',
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'../plot_types/arrays',
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'../plot_types/stats',
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'../plot_types/unstructured',
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]
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class MplExplicitOrder(ExplicitOrder):
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"color_demo",
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# pies
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"pie_features", "pie_demo2",
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# **Plot Types
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# Basic
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"plot", "scatter_plot", "bar", "stem", "step", "pie", "fill_between",
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# Arrays
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"imshow", "pcolormesh", "contourf", "quiver", "streamplot",
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# Stats
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"hist_plot", "boxplot_plot", "errorbar_plot", "violin",
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"barbs", "eventplot", "hist2d", "hexbin",
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# Unstructured
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"tricontour", "tripcolor", "triplot",
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]
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explicit_subsection_order = [item + ".py" for item in list_all]
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‎lib/matplotlib/mpl-data/stylelib/mpl_plot_gallery.mplstyle

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# from the Matplotlib cheatsheet as used in our gallery:
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axes.grid: True
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axes.axisbelow: True
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figure.figsize: 2, 2
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# make it so the axes labels don't show up. Obviously
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# not good style for any quantitative analysis:
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figure.subplot.left: 0.01
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figure.subplot.right: 0.99
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figure.subplot.bottom: 0.01
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figure.subplot.top: 0.99
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xtick.major.size: 0.0
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ytick.major.size: 0.0
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# colors:
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image.cmap : Blues
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# axes.prop_cycle: cycler('color', ['FF7F0E', '1F77B4', '2CA02C'])

‎plot_types/README.rst

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.. _plot_types:
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Plot types
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==========
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This gallery lists many of the plotting commands in Matplotlib,
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(but not all of them!).
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Note that we have stripped all labels, but they are present by default.
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See the `gallery <../gallery/index.html>`_ for many more examples and
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the `tutorials page <../tutorials/index.html>`_ for longer examples.

‎plot_types/arrays/README.rst

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.. _array_plots:
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Plots of arrays and fields
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--------------------------
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Plotting for arrays of data ``Z(x, y)`` and fields ``U(x, y), V(x, y)``

‎plot_types/arrays/contourf.py

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"""
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=====================================
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contour[f]([X, Y], Z, [levels=], ...)
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=====================================
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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plt.style.use('mpl_plot_gallery')
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# make data
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X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
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Z = (1 - X/2. + X**5 + Y**3)*np.exp(-X**2-Y**2)
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Z = Z - Z.min()
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levs = np.linspace(np.min(Z), np.max(Z), 7)
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# plot
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fig, ax = plt.subplots()
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plt.contourf(X, Y, Z, levels=levs)
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plt.contour(X, Y, Z, levels=levs, colors="white", linewidths=0.5)
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plt.show()

‎plot_types/arrays/imshow.py

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"""
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=======================
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imshow(Z, [cmap=], ...)
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=======================
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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plt.style.use('mpl_plot_gallery')
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# make data
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X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
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Z = (1 - X/2. + X**5 + Y**3) * np.exp(-X**2 - Y**2)
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Z = Z - Z.min()
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Z = Z[::16, ::16]
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# plot
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fig, ax = plt.subplots()
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ax.imshow(Z, extent=[0, 8, 0, 8], interpolation="nearest",
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cmap=plt.get_cmap('Blues'), vmin=0, vmax=1.6)
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ax.set_xticks([])
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ax.set_yticks([])
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plt.show()

‎plot_types/arrays/pcolormesh.py

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"""
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===================================
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pcolormesh([X, Y], Z, [cmap=], ...)
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===================================
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`~.axes.Axes.pcolormesh` is more flexible than `~.axes.Axes.imshow` in that
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the x and y vectors need not be equally spaced (indeed they can be skewed).
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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plt.style.use('mpl_plot_gallery')
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# make full-res data
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X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
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Z = (1 - X/2. + X**5 + Y**3) * np.exp(-X**2 - Y**2)
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Z = Z - Z.min()
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# sample unevenly in x:
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dx = np.sqrt((np.arange(16) - 8)**2) + 6
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dx = np.floor(dx / sum(dx) * 255)
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xint = np.cumsum(dx).astype('int')
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X = X[0, xint]
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Y = Y[::8, 0]
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Z = Z[::8, :][:, xint]
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# plot
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fig, ax = plt.subplots()
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ax.pcolormesh(X, Y, Z, vmin=0, vmax=1.5, shading='nearest')
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plt.show()

‎plot_types/arrays/quiver.py

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"""
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=========================
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quiver([X, Y], U, V, ...)
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=========================
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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plt.style.use('mpl_plot_gallery')
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# make data
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T = np.linspace(0, 2*np.pi, 8)
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X, Y = 4 + 1 * np.cos(T), 4 + 1 * np.sin(T)
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U, V = 1.5 * np.cos(T), 1.5 * np.sin(T)
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# plot
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fig, ax = plt.subplots()
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plt.quiver(X, Y, U, V, color="C0", angles='xy',
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scale_units='xy', scale=0.5, width=.05)
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ax.set_xlim(0, 8)
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ax.set_xticks(np.arange(1, 8))
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ax.set_ylim(0, 8)
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ax.set_yticks(np.arange(1, 8))
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plt.show()

‎plot_types/arrays/streamplot.py

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"""
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========================
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streamplot([X, Y], U, V)
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========================
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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plt.style.use('mpl_plot_gallery')
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# make a stream function:
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X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
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Z = (1 - X/2. + X**5 + Y**3) * np.exp(-X**2 - Y**2)
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Z = Z - Z.min()
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# make U and V out of the streamfunction:
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V = np.diff(Z[1:, :], axis=1)
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U = -np.diff(Z[:, 1:], axis=0)
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# plot:
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fig, ax = plt.subplots()
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# contour stream function
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ax.contour(X, Y, Z, colors='C1', alpha=0.5, zorder=1, linewidths=3)
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# plot stream plot
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ax.streamplot(X[1:, 1:], Y[1:, 1:], U, V, zorder=2)
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plt.show()

‎plot_types/basic/README.rst

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.. _basic_plots:
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Basic
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-----
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Basic plot types, usually x versus y.

‎plot_types/basic/bar.py

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"""
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======================
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bar[h](x, height, ...)
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======================
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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plt.style.use('mpl_plot_gallery')
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# make data:
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np.random.seed(3)
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X = 0.5 + np.arange(8)
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Y = np.random.uniform(2, 7, len(X))
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# plot
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fig, ax = plt.subplots()
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ax.bar(X, Y, width=1, edgecolor="white", linewidth=0.7)
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ax.set_xlim(0, 8)
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ax.set_xticks(np.arange(1, 8))
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ax.set_ylim(0, 8)
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ax.set_yticks(np.arange(1, 8))
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plt.show()

‎plot_types/basic/pie.py

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"""
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====================
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pie(X, explode, ...)
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====================
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"""
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import matplotlib as mpl
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import matplotlib.pyplot as plt
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import numpy as np
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plt.style.use('mpl_plot_gallery')
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# make data
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X = [1, 2, 3, 4]
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colors = np.zeros((len(X), 4))
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colors[:] = mpl.colors.to_rgba("C0")
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colors[:, 3] = np.linspace(0.25, 0.75, len(X))
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# plot
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fig, ax = plt.subplots()
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ax.pie(X, colors=["white"]*len(X), radius=3, center=(4, 4),
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wedgeprops={"linewidth": 1, "edgecolor": "white"}, frame=True)
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ax.pie(X, colors=colors, radius=3, center=(4, 4),
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wedgeprops={"linewidth": 1, "edgecolor": "white"}, frame=True)
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ax.set_xlim(0, 8)
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ax.set_xticks(np.arange(1, 8))
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ax.set_ylim(0, 8)
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ax.set_yticks(np.arange(1, 8))
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plt.show()

‎plot_types/basic/plot.py

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"""
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======================
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plot([X], Y, [fmt]...)
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======================
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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plt.style.use('mpl_plot_gallery')
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# make data
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X = np.linspace(0, 10, 100)
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Y = 4 + 2 * np.sin(2 * X)
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# plot
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fig, ax = plt.subplots()
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ax.plot(X, Y, linewidth=2.0)
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ax.set_xlim(0, 8)
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ax.set_xticks(np.arange(1, 8))
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ax.set_ylim(0, 8)
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ax.set_yticks(np.arange(1, 8))
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plt.show()

‎plot_types/basic/scatter_plot.py

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"""
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==================
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scatter(X, Y, ...)
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==================
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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plt.style.use('mpl_plot_gallery')
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# make the data
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np.random.seed(3)
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X = 4 + np.random.normal(0, 2, 24)
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Y = 4 + np.random.normal(0, 2, len(X))
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# size and color:
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S = np.random.uniform(15, 80, len(X))
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# plot
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fig, ax = plt.subplots()
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ax.scatter(X, Y, s=S, c=-S, cmap=plt.get_cmap('Blues'), vmin=-100, vmax=0)
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ax.set_xlim(0, 8)
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ax.set_xticks(np.arange(1, 8))
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ax.set_ylim(0, 8)
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ax.set_yticks(np.arange(1, 8))
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plt.show()

‎plot_types/basic/stem.py

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"""
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=================
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stem([x], y, ...)
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=================
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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plt.style.use('mpl_plot_gallery')
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# make data
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np.random.seed(3)
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X = 0.5 + np.arange(8)
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Y = np.random.uniform(2, 7, len(X))
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# plot
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fig, ax = plt.subplots()
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ax.stem(X, Y, bottom=0, linefmt="-", markerfmt="d")
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ax.set_xlim(0, 8)
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ax.set_xticks(np.arange(1, 8))
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ax.set_ylim(0, 8)
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ax.set_yticks(np.arange(1, 8))
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plt.show()

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