Merge pull request matplotlib#24526 from oscargus/tutorialspelling

timhoffm · web-flow · commit 6649511e2b75 · 2022-12-10T21:57:48.000+01:00
[Doc] Fix spelling and grammar in tutorials
diff --git a/tutorials/advanced/blitting.py b/tutorials/advanced/blitting.py
@@ -41,7 +41,7 @@
 .. warning::
 
    This code does not work with the OSX backend (but does work with other
-   GUI backends on mac).
+   GUI backends on Mac).
 
 Minimal example
 ---------------
@@ -106,7 +106,7 @@
 # pixels changes (due to either the size or dpi of the figure
 # changing) , the background will be invalid and result in incorrect
 # (but sometimes cool looking!) images.  There is also a global
-# variable and a fair amount of boiler plate which suggests we should
+# variable and a fair amount of boilerplate which suggests we should
 # wrap this in a class.
 #
 # Class-based example
@@ -125,7 +125,7 @@ def __init__(self, canvas, animated_artists=()):
         Parameters
         ----------
         canvas : FigureCanvasAgg
-            The canvas to work with, this only works for sub-classes of the Agg
+            The canvas to work with, this only works for subclasses of the Agg
             canvas which have the `~FigureCanvasAgg.copy_from_bbox` and
             `~FigureCanvasAgg.restore_region` methods.
 
diff --git a/tutorials/advanced/path_tutorial.py b/tutorials/advanced/path_tutorial.py
@@ -9,7 +9,7 @@
 the :class:`~matplotlib.path.Path`, which supports the standard set of
 moveto, lineto, curveto commands to draw simple and compound outlines
 consisting of line segments and splines.  The ``Path`` is instantiated
-with a (N, 2) array of (x, y) vertices, and a N-length array of path
+with a (N, 2) array of (x, y) vertices, and an N-length array of path
 codes.  For example to draw the unit rectangle from (0, 0) to (1, 1), we
 could use this code:
 """
@@ -148,7 +148,7 @@
 #     n, bins = np.histogram(data, 100)
 #
 # We'll now extract the corners of the rectangles.  Each of the
-# ``left``, ``bottom``, etc, arrays below is ``len(n)``, where ``n`` is
+# ``left``, ``bottom``, etc., arrays below is ``len(n)``, where ``n`` is
 # the array of counts for each histogram bar::
 #
 #     # get the corners of the rectangles for the histogram
@@ -161,7 +161,7 @@
 # series of ``MOVETO``, ``LINETO`` and ``CLOSEPOLY`` for each rectangle.
 # For each rectangle, we need five vertices: one for the ``MOVETO``,
 # three for the ``LINETO``, and one for the ``CLOSEPOLY``.  As indicated
-# in the table above, the vertex for the closepoly is ignored but we still
+# in the table above, the vertex for the closepoly is ignored, but we still
 # need it to keep the codes aligned with the vertices::
 #
 #     nverts = nrects*(1+3+1)
diff --git a/tutorials/advanced/transforms_tutorial.py b/tutorials/advanced/transforms_tutorial.py
@@ -9,7 +9,7 @@
 system, and the *display* coordinate system.  In 95% of your plotting, you
 won't need to think about this, as it happens under the hood, but as you push
 the limits of custom figure generation, it helps to have an understanding of
-these objects so you can reuse the existing transformations Matplotlib makes
+these objects, so you can reuse the existing transformations Matplotlib makes
 available to you, or create your own (see :mod:`matplotlib.transforms`).  The
 table below summarizes some useful coordinate systems, a description of each
 system, and the transformation object for going from each coordinate system to
@@ -91,7 +91,7 @@
 Note that specifying the position of Artists in *display* coordinates may
 change their relative location if the ``dpi`` or size of the figure changes.
 This can cause confusion when printing or changing screen resolution, because
-the object can change location and size.  Therefore it is most common for
+the object can change location and size.  Therefore, it is most common for
 artists placed in an Axes or figure to have their transform set to something
 *other* than the `~.transforms.IdentityTransform()`; the default when an artist
 is added to an Axes using `~.axes.Axes.add_artist` is for the transform to be
@@ -291,7 +291,7 @@
 # coordinates is extremely useful, for example to create a horizontal
 # span which highlights some region of the y-data but spans across the
 # x-axis regardless of the data limits, pan or zoom level, etc.  In fact
-# these blended lines and spans are so useful, we have built in
+# these blended lines and spans are so useful, we have built-in
 # functions to make them easy to plot (see
 # :meth:`~matplotlib.axes.Axes.axhline`,
 # :meth:`~matplotlib.axes.Axes.axvline`,
@@ -430,7 +430,7 @@
 # Another use of :class:`~matplotlib.transforms.ScaledTranslation` is to create
 # a new transformation that is
 # offset from another transformation, e.g., to place one object shifted a
-# bit relative to another object.  Typically you want the shift to be in
+# bit relative to another object.  Typically, you want the shift to be in
 # some physical dimension, like points or inches rather than in *data*
 # coordinates, so that the shift effect is constant at different zoom
 # levels and dpi settings.
diff --git a/tutorials/colors/colormapnorms.py b/tutorials/colors/colormapnorms.py
@@ -53,7 +53,7 @@
 X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)]
 
 # A low hump with a spike coming out of the top right.  Needs to have
-# z/colour axis on a log scale so we see both hump and spike.  linear
+# z/colour axis on a log scale, so we see both hump and spike. A linear
 # scale only shows the spike.
 Z1 = np.exp(-X**2 - Y**2)
 Z2 = np.exp(-(X * 10)**2 - (Y * 10)**2)
diff --git a/tutorials/colors/colormaps.py b/tutorials/colors/colormaps.py
@@ -285,7 +285,7 @@ def plot_color_gradients(category, cmap_list):
             # https://stackoverflow.com/q/8202605/
 
             if cmap_category == 'Sequential':
-                # These colormaps all start at high lightness but we want them
+                # These colormaps all start at high lightness, but we want them
                 # reversed to look nice in the plot, so reverse the order.
                 y_ = lab[0, ::-1, 0]
                 c_ = x[::-1]
diff --git a/tutorials/intermediate/arranging_axes.py b/tutorials/intermediate/arranging_axes.py
@@ -111,7 +111,7 @@
 fig.suptitle('plt.subplots()')
 
 ##############################################################################
-# We will annotate a lot of Axes, so lets encapsulate the annotation, rather
+# We will annotate a lot of Axes, so let's encapsulate the annotation, rather
 # than having that large piece of annotation code every time we need it:
 
 
diff --git a/tutorials/intermediate/artists.py b/tutorials/intermediate/artists.py
@@ -556,7 +556,7 @@ class in the Matplotlib API, and the one you will be working with most
 # :attr:`~matplotlib.axes.Axes.yaxis`.  The ``XAxis`` and ``YAxis``
 # containers will be detailed below, but note that the ``Axes`` contains
 # many helper methods which forward calls on to the
-# :class:`~matplotlib.axis.Axis` instances so you often do not need to
+# :class:`~matplotlib.axis.Axis` instances, so you often do not need to
 # work with them directly unless you want to.  For example, you can set
 # the font color of the ``XAxis`` ticklabels using the ``Axes`` helper
 # method::
diff --git a/tutorials/intermediate/constrainedlayout_guide.py b/tutorials/intermediate/constrainedlayout_guide.py
@@ -599,7 +599,7 @@ def example_plot(ax, fontsize=12, hide_labels=False):
 # ======================
 #
 # The algorithm for the constraint is relatively straightforward, but
-# has some complexity due to the complex ways we can layout a figure.
+# has some complexity due to the complex ways we can lay out a figure.
 #
 # Layout in Matplotlib is carried out with gridspecs
 # via the `.GridSpec` class. A gridspec is a logical division of the figure
@@ -611,7 +611,7 @@ def example_plot(ax, fontsize=12, hide_labels=False):
 # for each column, and ``bottom`` and ``top`` variables for each row, and
 # further it has a margin for each of left, right, bottom and top.  In each
 # row, the bottom/top margins are widened until all the decorators
-# in that row are accommodated.  Similarly for columns and the left/right
+# in that row are accommodated.  Similarly, for columns and the left/right
 # margins.
 #
 #
diff --git a/tutorials/intermediate/tight_layout_guide.py b/tutorials/intermediate/tight_layout_guide.py
@@ -161,7 +161,7 @@ def example_plot(ax, fontsize=12):
 #   are rare cases where it is not.
 #
 # * ``pad=0`` can clip some texts by a few pixels. This may be a bug or
-#   a limitation of the current algorithm and it is not clear why it
+#   a limitation of the current algorithm, and it is not clear why it
 #   happens. Meanwhile, use of pad larger than 0.3 is recommended.
 #
 # Use with GridSpec
@@ -213,7 +213,7 @@ def example_plot(ax, fontsize=12):
 # =======================
 #
 # Pre Matplotlib 2.2, legends and annotations were excluded from the bounding
-# box calculations that decide the layout.  Subsequently these artists were
+# box calculations that decide the layout.  Subsequently, these artists were
 # added to the calculation, but sometimes it is undesirable to include them.
 # For instance in this case it might be good to have the axes shrink a bit
 # to make room for the legend:
diff --git a/tutorials/introductory/lifecycle.py b/tutorials/introductory/lifecycle.py
@@ -36,7 +36,7 @@
 
 * The `.Figure` is the final image, and may contain one or more `~.axes.Axes`.
 * The `~.axes.Axes` represents an individual plot (not to be confused with
-   `~.axis.Axis`, which refers to the x/y axis of a plot).
+   `~.axis.Axis`, which refers to the x-, y-, or z-axis of a plot).
 
 We call methods that do the plotting directly from the Axes, which gives
 us much more flexibility and power in customizing our plot.
diff --git a/tutorials/introductory/pyplot.py b/tutorials/introductory/pyplot.py
@@ -11,8 +11,8 @@
 """
 
 ###############################################################################
-# Intro to pyplot
-# ===============
+# Introduction to pyplot
+# ======================
 #
 # :mod:`matplotlib.pyplot` is a collection of functions that make matplotlib
 # work like MATLAB.  Each ``pyplot`` function makes some change to a figure:
@@ -29,11 +29,11 @@
 #
 # .. note::
 #
-#    the implicit pyplot API is generally less verbose but also not as flexible as the
+#    The implicit pyplot API is generally less verbose but also not as flexible as the
 #    explicit API.  Most of the function calls you see here can also be called
 #    as methods from an ``Axes`` object. We recommend browsing the tutorials
 #    and examples to see how this works. See :ref:`api_interfaces` for an
-#    explanation of the trade off of the supported user APIs.
+#    explanation of the trade-off of the supported user APIs.
 #
 # Generating visualizations with pyplot is very quick:
 
@@ -48,7 +48,7 @@
 # `~.pyplot.plot`, matplotlib assumes it is a
 # sequence of y values, and automatically generates the x values for
 # you.  Since python ranges start with 0, the default x vector has the
-# same length as y but starts with 0.  Hence the x data are
+# same length as y but starts with 0; therefore, the x data are
 # ``[0, 1, 2, 3]``.
 #
 # `~.pyplot.plot` is a versatile function, and will take an arbitrary number of
@@ -104,7 +104,7 @@
 # access particular variables with strings. For example, with
 # `numpy.recarray` or `pandas.DataFrame`.
 #
-# Matplotlib allows you provide such an object with
+# Matplotlib allows you to provide such an object with
 # the ``data`` keyword argument. If provided, then you may generate plots with
 # the strings corresponding to these variables.
 
@@ -355,7 +355,7 @@ def f(t):
 # Using mathematical expressions in text
 # --------------------------------------
 #
-# matplotlib accepts TeX equation expressions in any text expression.
+# Matplotlib accepts TeX equation expressions in any text expression.
 # For example to write the expression :math:`\sigma_i=15` in the title,
 # you can write a TeX expression surrounded by dollar signs::
 #
@@ -365,9 +365,9 @@ def f(t):
 # that the string is a *raw* string and not to treat backslashes as
 # python escapes.  matplotlib has a built-in TeX expression parser and
 # layout engine, and ships its own math fonts -- for details see
-# :doc:`/tutorials/text/mathtext`.  Thus you can use mathematical text across platforms
-# without requiring a TeX installation.  For those who have LaTeX and
-# dvipng installed, you can also use LaTeX to format your text and
+# :doc:`/tutorials/text/mathtext`.  Thus, you can use mathematical text across
+# platforms without requiring a TeX installation.  For those who have LaTeX
+# and dvipng installed, you can also use LaTeX to format your text and
 # incorporate the output directly into your display figures or saved
 # postscript -- see :doc:`/tutorials/text/usetex`.
 #
@@ -415,7 +415,7 @@ def f(t):
 #
 #     plt.xscale('log')
 #
-# An example of four plots with the same data and different scales for the y axis
+# An example of four plots with the same data and different scales for the y-axis
 # is shown below.
 
 # Fixing random state for reproducibility
diff --git a/tutorials/introductory/quick_start.py b/tutorials/introductory/quick_start.py
@@ -23,7 +23,7 @@
 # Matplotlib graphs your data on `.Figure`\s (e.g., windows, Jupyter
 # widgets, etc.), each of which can contain one or more `~.axes.Axes`, an
 # area where points can be specified in terms of x-y coordinates (or theta-r
-# in a polar plot, x-y-z in a 3D plot, etc).  The simplest way of
+# in a polar plot, x-y-z in a 3D plot, etc.).  The simplest way of
 # creating a Figure with an Axes is using `.pyplot.subplots`. We can then use
 # `.Axes.plot` to draw some data on the Axes:
 
@@ -113,9 +113,9 @@
 #   b_asarray = np.asarray(b)
 #
 # Most methods will also parse an addressable object like a *dict*, a
-# `numpy.recarray`, or a `pandas.DataFrame`.  Matplotlib allows you provide
-# the ``data`` keyword argument and generate plots passing the strings
-# corresponding to the *x* and *y* variables.
+# `numpy.recarray`, or a `pandas.DataFrame`.  Matplotlib allows you to
+# provide the ``data`` keyword argument and generate plots passing the
+# strings corresponding to the *x* and *y* variables.
 np.random.seed(19680801)  # seed the random number generator.
 data = {'a': np.arange(50),
         'c': np.random.randint(0, 50, 50),
diff --git a/tutorials/provisional/mosaic.py b/tutorials/provisional/mosaic.py
@@ -10,7 +10,7 @@
    make breaking changes in future versions with no warning.
 
 
-Laying out Axes in a Figure in a non uniform grid can be both tedious
+Laying out Axes in a Figure in a non-uniform grid can be both tedious
 and verbose.  For dense, even grids we have `.Figure.subplots` but for
 more complex layouts, such as Axes that span multiple columns / rows
 of the layout or leave some areas of the Figure blank, you can use
@@ -139,8 +139,8 @@ def identify_axes(ax_dict, fontsize=48):
 # Axes spanning multiple rows/columns
 # ===================================
 #
-# Something we can do with `.Figure.subplot_mosaic` that you can not
-# do with `.Figure.subplots` is specify that an Axes should span
+# Something we can do with `.Figure.subplot_mosaic`, that we cannot
+# do with `.Figure.subplots`, is to specify that an Axes should span
 # several rows or columns.
 
 
@@ -289,7 +289,7 @@ def identify_axes(ax_dict, fontsize=48):
 # Nested list input
 # =================
 #
-# Everything we can do with the string short-hand we can also do when
+# Everything we can do with the string shorthand we can also do when
 # passing in a list (internally we convert the string shorthand to a nested
 # list), for example using spans, blanks, and *gridspec_kw*:
 
diff --git a/tutorials/text/annotations.py b/tutorials/text/annotations.py
@@ -317,7 +317,7 @@ def custom_box_style(x0, y0, width, height, mutation_size):
 #
 # The behavior of each connection style is (limitedly) demonstrated in the
 # example below. (Warning: The behavior of the ``bar`` style is currently not
-# well defined and may be changed in the future).
+# well-defined and may be changed in the future).
 #
 # .. figure:: ../../gallery/userdemo/images/sphx_glr_connectionstyle_demo_001.png
 #    :target: ../../gallery/userdemo/connectionstyle_demo.html
@@ -434,7 +434,7 @@ def custom_box_style(x0, y0, width, height, mutation_size):
 # pixel (radius = 10 pixel), you can utilize
 # `~mpl_toolkits.axes_grid1.anchored_artists.AnchoredDrawingArea`. The instance
 # is created with a size of the drawing area (in pixels), and arbitrary artists
-# can added to the drawing area. Note that the extents of the artists that are
+# can be added to the drawing area. Note that the extents of the artists that are
 # added to the drawing area are not related to the placement of the drawing
 # area itself. Only the initial size matters.
 #
@@ -575,7 +575,7 @@ def custom_box_style(x0, y0, width, height, mutation_size):
 #
 # 3. A callable object that takes the renderer instance as single argument, and
 # returns either a `.Transform` or a `.BboxBase`. For example, the return
-# value of `.Artist.get_window_extent` is a bbox, so this method is identical to
+# value of `.Artist.get_window_extent` is a bbox, so this method is identical
 # to (2) passing in the artist:
 
 fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(3, 3))
diff --git a/tutorials/text/text_intro.py b/tutorials/text/text_intro.py
@@ -250,7 +250,7 @@
 # Simple ticks
 # ~~~~~~~~~~~~
 #
-# It often is convenient to simply define the
+# It is often convenient to simply define the
 # tick values, and sometimes the tick labels, overriding the default
 # locators and formatters.  This is discouraged because it breaks interactive
 # navigation of the plot.  It also can reset the axis limits: note that
@@ -323,7 +323,7 @@
 # ``nbins=auto`` uses an algorithm to determine how many ticks will
 # be acceptable based on how long the axis is.  The fontsize of the
 # ticklabel is taken into account, but the length of the tick string
-# is not (because its not yet known.)  In the bottom row, the
+# is not (because it's not yet known.)  In the bottom row, the
 # ticklabels are quite large, so we set ``nbins=4`` to make the
 # labels fit in the right-hand plot.
 

Original file line number	Diff line number	Diff line change
`@@ -599,7 +599,7 @@ def example_plot(ax, fontsize=12, hide_labels=False):`
`599`	`599`	`# ======================`
`600`	`600`	`#`
`601`	`601`	`# The algorithm for the constraint is relatively straightforward, but`
`602`		`-# has some complexity due to the complex ways we can layout a figure.`
	`602`	`+# has some complexity due to the complex ways we can lay out a figure.`
`603`	`603`	`#`
`604`	`604`	`# Layout in Matplotlib is carried out with gridspecs`
`605`	`605`	# via the `.GridSpec` class. A gridspec is a logical division of the figure
`@@ -611,7 +611,7 @@ def example_plot(ax, fontsize=12, hide_labels=False):`
`611`	`611`	# for each column, and ``bottom`` and ``top`` variables for each row, and
`612`	`612`	`# further it has a margin for each of left, right, bottom and top. In each`
`613`	`613`	`# row, the bottom/top margins are widened until all the decorators`
`614`		`-# in that row are accommodated. Similarly for columns and the left/right`
	`614`	`+# in that row are accommodated. Similarly, for columns and the left/right`
`615`	`615`	`# margins.`
`616`	`616`	`#`
`617`	`617`	`#`
Original file line number	Diff line number	Diff line change
`@@ -161,7 +161,7 @@ def example_plot(ax, fontsize=12):`
`161`	`161`	`# are rare cases where it is not.`
`162`	`162`	`#`
`163`	`163`	# * ``pad=0`` can clip some texts by a few pixels. This may be a bug or
`164`		`-# a limitation of the current algorithm and it is not clear why it`
	`164`	`+# a limitation of the current algorithm, and it is not clear why it`
`165`	`165`	`# happens. Meanwhile, use of pad larger than 0.3 is recommended.`
`166`	`166`	`#`
`167`	`167`	`# Use with GridSpec`
`@@ -213,7 +213,7 @@ def example_plot(ax, fontsize=12):`
`213`	`213`	`# =======================`
`214`	`214`	`#`
`215`	`215`	`# Pre Matplotlib 2.2, legends and annotations were excluded from the bounding`
`216`		`-# box calculations that decide the layout. Subsequently these artists were`
	`216`	`+# box calculations that decide the layout. Subsequently, these artists were`
`217`	`217`	`# added to the calculation, but sometimes it is undesirable to include them.`
`218`	`218`	`# For instance in this case it might be good to have the axes shrink a bit`
`219`	`219`	`# to make room for the legend:`