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Commit 162bd59

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DOC: More capitalization of Axes
In line with matplotlib#18726. Triggered by matplotlib#22242.
1 parent 027dc6c commit 162bd59

32 files changed

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-70
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‎examples/axes_grid1/demo_colorbar_with_axes_divider.py

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@@ -18,13 +18,13 @@
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im1 = ax1.imshow([[1, 2], [3, 4]])
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ax1_divider = make_axes_locatable(ax1)
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# Add an axes to the right of the main axes.
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# Add an Axes to the right of the main Axes.
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cax1 = ax1_divider.append_axes("right", size="7%", pad="2%")
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cb1 = fig.colorbar(im1, cax=cax1)
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im2 = ax2.imshow([[1, 2], [3, 4]])
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ax2_divider = make_axes_locatable(ax2)
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# Add an axes above the main axes.
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# Add an Axes above the main Axes.
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cax2 = ax2_divider.append_axes("top", size="7%", pad="2%")
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cb2 = fig.colorbar(im2, cax=cax2, orientation="horizontal")
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# Change tick position to top (with the default tick position "bottom", ticks

‎examples/axes_grid1/simple_axes_divider1.py

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@@ -11,7 +11,7 @@
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def label_axes(ax, text):
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"""Place a label at the center of an axes, and remove the axis ticks."""
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"""Place a label at the center of an Axes, and remove the axis ticks."""
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ax.text(.5, .5, text, transform=ax.transAxes,
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horizontalalignment="center", verticalalignment="center")
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ax.tick_params(bottom=False, labelbottom=False,

‎examples/axes_grid1/simple_colorbar.py

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@@ -11,7 +11,7 @@
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ax = plt.subplot()
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im = ax.imshow(np.arange(100).reshape((10, 10)))
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# create an axes on the right side of ax. The width of cax will be 5%
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# create an Axes on the right side of ax. The width of cax will be 5%
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# of ax and the padding between cax and ax will be fixed at 0.05 inch.
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divider = make_axes_locatable(ax)
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cax = divider.append_axes("right", size="5%", pad=0.05)

‎examples/lines_bars_and_markers/fill_between_alpha.py

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###############################################################################
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# Another handy use of filled regions is to highlight horizontal or vertical
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# spans of an axes -- for that Matplotlib has the helper functions
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# spans of an Axes -- for that Matplotlib has the helper functions
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# `~matplotlib.axes.Axes.axhspan` and `~matplotlib.axes.Axes.axvspan`. See
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# :doc:`/gallery/subplots_axes_and_figures/axhspan_demo`.
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‎examples/lines_bars_and_markers/gradient_bar.py

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@@ -12,7 +12,7 @@
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by a unit vector *v*. The values at the corners are then obtained by the
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lengths of the projections of the corner vectors on *v*.
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A similar approach can be used to create a gradient background for an axes.
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A similar approach can be used to create a gradient background for an Axes.
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In that case, it is helpful to uses Axes coordinates (``extent=(0, 1, 0, 1),
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transform=ax.transAxes``) to be independent of the data coordinates.
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‎examples/misc/logos2.py

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@@ -89,7 +89,7 @@ def create_icon_axes(fig, ax_position, lw_bars, lw_grid, lw_border, rgrid):
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def create_text_axes(fig, height_px):
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"""Create an axes in *fig* that contains 'matplotlib' as Text."""
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"""Create an Axes in *fig* that contains 'matplotlib' as Text."""
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ax = fig.add_axes((0, 0, 1, 1))
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ax.set_aspect("equal")
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ax.set_axis_off()

‎examples/spines/spines.py

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@@ -5,9 +5,9 @@
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This demo compares:
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- normal axes, with spines on all four sides;
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- an axes with spines only on the left and bottom;
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- an axes using custom bounds to limit the extent of the spine.
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- normal Axes, with spines on all four sides;
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- an Axes with spines only on the left and bottom;
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- an Axes using custom bounds to limit the extent of the spine.
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"""
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import numpy as np
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import matplotlib.pyplot as plt

‎examples/subplots_axes_and_figures/axes_box_aspect.py

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Axes box aspect
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===============
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This demo shows how to set the aspect of an axes box directly via
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This demo shows how to set the aspect of an Axes box directly via
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`~.Axes.set_box_aspect`. The box aspect is the ratio between axes height
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and axes width in physical units, independent of the data limits.
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This is useful to e.g. produce a square plot, independent of the data it
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~
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#
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# When setting the box aspect, one may still set the data aspect as well.
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# Here we create an axes with a box twice as long as tall and use an "equal"
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# Here we create an Axes with a box twice as long as tall and use an "equal"
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# data aspect for its contents, i.e. the circle actually stays circular.
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fig6, ax = plt.subplots()
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# Box aspect for many subplots
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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#
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# It is possible to pass the box aspect to an axes at initialization. The
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# following creates a 2 by 3 subplot grid with all square axes.
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# It is possible to pass the box aspect to an Axes at initialization. The
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# following creates a 2 by 3 subplot grid with all square Axes.
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fig7, axs = plt.subplots(2, 3, subplot_kw=dict(box_aspect=1),
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sharex=True, sharey=True, constrained_layout=True)

‎examples/subplots_axes_and_figures/shared_axis_demo.py

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===========
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You can share the x or y axis limits for one axis with another by
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passing an axes instance as a *sharex* or *sharey* keyword argument.
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passing an `~.axes.Axes` instance as a *sharex* or *sharey* keyword argument.
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Changing the axis limits on one axes will be reflected automatically
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in the other, and vice-versa, so when you navigate with the toolbar
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the axes will follow each other on their shared axes. Ditto for
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the Axes will follow each other on their shared axis. Ditto for
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changes in the axis scaling (e.g., log vs. linear). However, it is
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possible to have differences in tick labeling, e.g., you can selectively
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turn off the tick labels on one axes.
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turn off the tick labels on one Axes.
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The example below shows how to customize the tick labels on the
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various axes. Shared axes share the tick locator, tick formatter,
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because you may want to make the tick labels smaller on the upper
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axes, e.g., in the example below.
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If you want to turn off the ticklabels for a given axes (e.g., on
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If you want to turn off the ticklabels for a given Axes (e.g., on
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subplot(211) or subplot(212), you cannot do the standard trick::
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setp(ax2, xticklabels=[])
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because this changes the tick Formatter, which is shared among all
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axes. But you can alter the visibility of the labels, which is a
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Axes. But you can alter the visibility of the labels, which is a
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property::
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setp(ax2.get_xticklabels(), visible=False)

‎lib/matplotlib/_constrained_layout.py

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often just set to 1 for an equal grid.
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Subplotspecs that are derived from this gridspec can contain either a
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``SubPanel``, a ``GridSpecFromSubplotSpec``, or an axes. The ``SubPanel`` and
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``GridSpecFromSubplotSpec`` are dealt with recursively and each contain an
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``SubPanel``, a ``GridSpecFromSubplotSpec``, or an ``Axes``. The ``SubPanel``
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and ``GridSpecFromSubplotSpec`` are dealt with recursively and each contain an
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analogous layout.
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Each ``GridSpec`` has a ``_layoutgrid`` attached to it. The ``_layoutgrid``

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