Backport PR matplotlib#27268: Copy-edit various examples.

meeseeksmachine · Nov 5, 2023 · f32d0f1 · f32d0f1
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diff --git a/galleries/examples/color/README.txt b/galleries/examples/color/README.txt
@@ -3,6 +3,5 @@
 Color
 =====
 
-For more in-depth information about the colormaps available in matplotlib
-as well as a description of their properties,
+For a description of the colormaps available in Matplotlib,
 see the :ref:`colormaps tutorial <tutorials-colors>`.
diff --git a/galleries/examples/color/named_colors.py b/galleries/examples/color/named_colors.py
@@ -3,7 +3,7 @@
 List of named colors
 ====================
 
-This plots a list of the named colors supported in matplotlib.
+This plots a list of the named colors supported by Matplotlib.
 For more information on colors in matplotlib see
 
 * the :ref:`colors_def` tutorial;

diff --git a/galleries/examples/images_contours_and_fields/image_demo.py b/galleries/examples/images_contours_and_fields/image_demo.py
@@ -1,9 +1,7 @@
 """
-==========
-Image demo
-==========
-
-Many ways to plot images in Matplotlib.
+========================
+Many ways to plot images
+========================
 
 The most common way to plot images in Matplotlib is with
 `~.axes.Axes.imshow`. The following examples demonstrate much of the

diff --git a/galleries/examples/images_contours_and_fields/pcolor_demo.py b/galleries/examples/images_contours_and_fields/pcolor_demo.py
@@ -1,13 +1,11 @@
 """
-===========
-Pcolor demo
-===========
+=============
+pcolor images
+=============
 
-Generating images with `~.axes.Axes.pcolor`.
-
-Pcolor allows you to generate 2D image-style plots. Below we will show how
-to do so in Matplotlib.
+`~.Axes.pcolor` generates 2D image-style plots, as illustrated below.
 """
+
 import matplotlib.pyplot as plt
 import numpy as np
 

diff --git a/galleries/examples/text_labels_and_annotations/accented_text.py b/galleries/examples/text_labels_and_annotations/accented_text.py
@@ -1,7 +1,7 @@
 r"""
-=================================
-Using accented text in Matplotlib
-=================================
+=============
+Accented text
+=============
 
 Matplotlib supports accented characters via TeX mathtext or Unicode.
 

diff --git a/galleries/examples/text_labels_and_annotations/annotation_demo.py b/galleries/examples/text_labels_and_annotations/annotation_demo.py
@@ -3,7 +3,7 @@
 Annotating Plots
 ================
 
-The following examples show how it is possible to annotate plots in Matplotlib.
+The following examples show ways to annotate plots in Matplotlib.
 This includes highlighting specific points of interest and using various
 visual tools to call attention to this point. For a more complete and in-depth
 description of the annotation and text tools in Matplotlib, see the

diff --git a/galleries/examples/text_labels_and_annotations/font_file.py b/galleries/examples/text_labels_and_annotations/font_file.py
@@ -1,7 +1,7 @@
 r"""
-===================================
-Using a ttf font file in Matplotlib
-===================================
+====================
+Using ttf font files
+====================
 
 Although it is usually not a good idea to explicitly point to a single ttf file
 for a font instance, you can do so by passing a `pathlib.Path` instance as the

diff --git a/galleries/examples/text_labels_and_annotations/legend_demo.py b/galleries/examples/text_labels_and_annotations/legend_demo.py
@@ -3,8 +3,6 @@
 Legend Demo
 ===========
 
-Plotting legends in Matplotlib.
-
 There are many ways to create and customize legends in Matplotlib. Below
 we'll show a few examples for how to do so.
 

diff --git a/galleries/users_explain/axes/constrainedlayout_guide.py b/galleries/users_explain/axes/constrainedlayout_guide.py
@@ -40,15 +40,13 @@
 
 .. warning::
 
-    Calling ``plt.tight_layout()`` will turn off *constrained layout*!
+    Calling `~.pyplot.tight_layout` will turn off *constrained layout*!
 
 Simple example
 ==============
 
-In Matplotlib, the location of Axes (including subplots) are specified in
-normalized figure coordinates. It can happen that your axis labels or titles
-(or sometimes even ticklabels) go outside the figure area, and are thus
-clipped.
+With the default Axes positioning, the axes title, axis labels, or tick labels
+can sometimes go outside the figure area, and thus get clipped.
 """
 
 # sphinx_gallery_thumbnail_number = 18

diff --git a/galleries/users_explain/axes/legend_guide.py b/galleries/users_explain/axes/legend_guide.py
@@ -7,13 +7,10 @@
 Legend guide
 ============
 
-Generating legends flexibly in Matplotlib.
-
 .. currentmodule:: matplotlib.pyplot
 
-This legend guide is an extension of the documentation available at
-:func:`~matplotlib.pyplot.legend` - please ensure you are familiar with
-contents of that documentation before proceeding with this guide.
+This legend guide extends the `~.Axes.legend` docstring -
+please read it before proceeding with this guide.
 
 This guide makes use of some common terms, which are documented here for
 clarity:
@@ -62,8 +59,8 @@
     line_down, = ax.plot([3, 2, 1], label='Line 1')
     ax.legend(handles=[line_up, line_down])
 
-In some cases, it is not possible to set the label of the handle, so it is
-possible to pass through the list of labels to :func:`legend`::
+In the rare case where the labels cannot directly be set on the handles, they
+can also be directly passed to :func:`legend`::
 
     fig, ax = plt.subplots()
     line_up, = ax.plot([1, 2, 3], label='Line 2')

diff --git a/galleries/users_explain/axes/tight_layout_guide.py b/galleries/users_explain/axes/tight_layout_guide.py
@@ -17,15 +17,11 @@
 An alternative to *tight_layout* is :ref:`constrained_layout
 <constrainedlayout_guide>`.
 
-
-Simple Example
+Simple example
 ==============
 
-In matplotlib, the location of axes (including subplots) are specified in
-normalized figure coordinates. It can happen that your axis labels or
-titles (or sometimes even ticklabels) go outside the figure area, and are thus
-clipped.
-
+With the default Axes positioning, the axes title, axis labels, or tick labels
+can sometimes go outside the figure area, and thus get clipped.
 """
 
 # sphinx_gallery_thumbnail_number = 7
@@ -190,8 +186,8 @@ def example_plot(ax, fontsize=12):
 
 # %%
 # You may provide an optional *rect* parameter, which specifies the bounding
-# box that the subplots will be fit inside. The coordinates must be in
-# normalized figure coordinates and the default is (0, 0, 1, 1).
+# box that the subplots will be fit inside. The coordinates are in
+# normalized figure coordinates and default to (0, 0, 1, 1) (the whole figure).
 
 fig = plt.figure()
 
@@ -245,7 +241,7 @@ def example_plot(ax, fontsize=12):
 # Use with AxesGrid1
 # ==================
 #
-# While limited, :mod:`mpl_toolkits.axes_grid1` is also supported.
+# Limited support for :mod:`mpl_toolkits.axes_grid1` is provided.
 
 from mpl_toolkits.axes_grid1 import Grid
 

diff --git a/galleries/users_explain/colors/colormap-manipulation.py b/galleries/users_explain/colors/colormap-manipulation.py
@@ -3,27 +3,25 @@
 
 .. _colormap-manipulation:
 
-********************************
-Creating Colormaps in Matplotlib
-********************************
+******************
+Creating Colormaps
+******************
 
 Matplotlib has a number of built-in colormaps accessible via
 `.matplotlib.colormaps`.  There are also external libraries like
 palettable_ that have many extra colormaps.
 
 .. _palettable: https://jiffyclub.github.io/palettable/
 
-However, we often want to create or manipulate colormaps in Matplotlib.
+However, we may also want to create or manipulate our own colormaps.
 This can be done using the class `.ListedColormap` or
 `.LinearSegmentedColormap`.
-Seen from the outside, both colormap classes map values between 0 and 1 to
-a bunch of colors. There are, however, slight differences, some of which are
-shown in the following.
+Both colormap classes map values between 0 and 1 to colors. There are however
+differences, as explained below.
 
 Before manually creating or manipulating colormaps, let us first see how we
 can obtain colormaps and their colors from existing colormap classes.
 
-
 Getting colormaps and accessing their values
 ============================================
 
@@ -32,7 +30,6 @@
 which returns a colormap object.  The length of the list of colors used
 internally to define the colormap can be adjusted via `.Colormap.resampled`.
 Below we use a modest value of 8 so there are not a lot of values to look at.
-
 """
 
 import matplotlib.pyplot as plt

diff --git a/galleries/users_explain/colors/colormaps.py b/galleries/users_explain/colors/colormaps.py
@@ -3,9 +3,9 @@
 
 .. _colormaps:
 
-********************************
-Choosing Colormaps in Matplotlib
-********************************
+******************
+Choosing Colormaps
+******************
 
 Matplotlib has a number of built-in colormaps accessible via
 `.matplotlib.colormaps`.  There are also external libraries that

diff --git a/galleries/users_explain/text/text_intro.py b/galleries/users_explain/text/text_intro.py
@@ -4,9 +4,9 @@
 
 .. _text_intro:
 
-========================
-Text in Matplotlib Plots
-========================
+==================
+Text in Matplotlib
+==================
 
 Introduction to plotting and working with text in Matplotlib.