8000 Merge pull request #27420 from meeseeksmachine/auto-backport-of-pr-27… · matplotlib/matplotlib@77f79fa · GitHub
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Merge pull request #27420 from meeseeksmachine/auto-backport-of-pr-27325-on-v3.8.x
Backport PR #27325 on branch v3.8.x (Fixing Sentence Case on Section Titles in users_explain)
2 parents a669991 + 08cc8cb commit 77f79fa

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‎galleries/users_explain/animations/animations.py

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import matplotlib.animation as animation
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# %%
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# Animation Classes
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# Animation classes
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# =================
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#
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# The animation process in Matplotlib can be thought of in 2 different ways:
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plt.show()
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# %%
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# Animation Writers
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# Animation writers
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# =================
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#
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# Animation objects can be saved to disk using various multimedia writers

‎galleries/users_explain/artists/patheffects_guide.py

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# automatically followed with the "normal" effect, whereas the latter
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# explicitly defines the two path effects to draw.
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#
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# Making an artist stand out
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# Making an Artist stand out
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# --------------------------
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#
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# One nice way of making artists visually stand out is to draw an outline in
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# its user interface.
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#
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#
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# Greater control of the path effect artist
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# Greater control of the path effect Artist
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# -----------------------------------------
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#
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# As already mentioned, some of the path effects operate at a lower level

‎galleries/users_explain/axes/autoscale.py

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.. _autoscale:
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Autoscaling
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===========
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Autoscaling Axis
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================
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The limits on an axis can be set manually (e.g. ``ax.set_xlim(xmin, xmax)``)
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or Matplotlib can set them automatically based on the data already on the axes.

‎galleries/users_explain/axes/axes_ticks.py

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.. _user_axes_ticks:
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==========
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Axis Ticks
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Axis ticks
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==========
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The x and y Axis on each Axes have default tick "locators" and "formatters"
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‎galleries/users_explain/axes/colorbar_placement.py

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.. redirect-from:: /gallery/subplots_axes_and_figures/colorbar_placement
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=================
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Placing Colorbars
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Placing colorbars
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=================
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Colorbars indicate the quantitative extent of image data. Placing in

‎galleries/users_explain/axes/constrainedlayout_guide.py

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.. _constrainedlayout_guide:
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========================
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Constrained Layout Guide
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Constrained layout guide
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========================
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Use *constrained layout* to fit plots within your figure cleanly.

‎galleries/users_explain/axes/legend_guide.py

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plt.show()
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# %%
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# Legend Handlers
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# Legend handlers
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# ===============
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#
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# In order to create legend entries, handles are given as an argument to an

‎galleries/users_explain/axes/tight_layout_guide.py

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.. _tight_layout_guide:
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==================
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Tight Layout guide
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Tight layout guide
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==================
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How to use tight-layout to fit plots within your figure cleanly.
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An alternative to *tight_layout* is :ref:`constrained_layout
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<constrainedlayout_guide>`.
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Simple example
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==============
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# %%
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# Legends and Annotations
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# Legends and annotations
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# =======================
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#
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# Pre Matplotlib 2.2, legends and annotations were excluded from the bounding

‎galleries/users_explain/colors/colorbar_only.py

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"""
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.. redirect-from:: /tutorials/colors/colorbar_only
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====================
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Standalone colorbars
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====================
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=============================
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Customized Colorbars Tutorial
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=============================
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This tutorial shows how to build and customize standalone colorbars, i.e.
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without an attached plot.

‎galleries/users_explain/colors/colormap-manipulation.py

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.. _colormap-manipulation:
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******************
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Creating Colormaps
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******************
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********************************
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Creating Colormaps in Matplotlib
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********************************
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Matplotlib has a number of built-in colormaps accessible via
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`.matplotlib.colormaps`. There are also external libraries like

‎galleries/users_explain/colors/colormapnorms.py

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.. _colormapnorms:
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Colormap Normalization
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Colormap normalization
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======================
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Objects that use colormaps by default linearly map the colors in the

‎galleries/users_explain/colors/colormaps.py

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.. _colormaps:
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Choosing Colormaps
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******************
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********************************
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Choosing Colormaps in Matplotlib
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********************************
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Matplotlib has a number of built-in colormaps accessible via
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`.matplotlib.colormaps`. There are also external libraries that

‎galleries/users_explain/toolkits/axes_grid.rst

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:target: /gallery/axes_grid1/demo_axes_grid.html
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:align: center
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AxesDivider Class
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AxesDivider class
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-----------------
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Behind the scenes, ImageGrid (and RGBAxes, described below) rely on

‎galleries/users_explain/toolkits/axisartist.rst

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:target: /gallery/axisartist/demo_parasite_axes2.html
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:align: center
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Curvilinear Grid
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Curvilinear grid
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The motivation behind the AxisArtist module is to support a curvilinear grid
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To change the pad between ticklabels and axis label,
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axis.label.set_pad method.
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Rotation and Alignment of TickLabels
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Rotation and alignment of TickLabels
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====================================
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This is also quite different from standard Matplotlib and can be
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See the first example of this page.
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Current Limitations and TODO's
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Current limitations and TODO's
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==============================
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The code need more refinement. Here is a incomplete list of issues and TODO's

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