Minor docs cleanup

lukelbd · lukelbd · commit 46bb4e1b0d55 · 2021-11-03T01:12:20.000-06:00
diff --git a/docs/basics.py b/docs/basics.py
@@ -224,25 +224,24 @@
 # <https://matplotlib.org/stable/api/index.html>`__ for plotting stuff:
 # a "python-style" object-oriented interface with axes-level commands
 # like `matplotlib.axes.Axes.plot`, and a "MATLAB-style" interface
-# that tracks "current" axes and provides global
-# `~matplotlib.pyplot` commands like `matplotlib.pyplot.plot`.
-# Rather than adding commands to the `~matplotlib.pyplot` module,
+# with global commands like `matplotlib.pyplot.plot` that tracks "current" axes.
+# Rather than adding to the `~matplotlib.pyplot` namespace,
 # proplot uses the intermediate subclass `proplot.axes.PlotAxes`
-# to modify existing axes-level commands and add a few new commands.
+# to modify existing axes-level commands and add a few new ones.
 # While certain `~proplot.axes.PlotAxes` features may be accessible via
 # the relevant `~matplotlib.pyplot` commands, proplot only officially supports
 # the "python-style" object-oriented interface.
 
 # `~proplot.axes.PlotAxes` does not change the usage or syntax of existing commands,
-# which means a shallow learning curve for the average matplotlib user. It also
-# tries to standardize the positional "data" arguments and optional keyword arguments
-# accepted by similar or analogous commands, providing a more intuitive interface
-# for new and old matplotlib users alike.
-# In the below example, we create a 4-panel figure with the familiar "1D"
-# plotting commands `~proplot.axes.PlotAxes.plot` and `~proplot.axes.PlotAxes.scatter`,
-# along with the "2D" plotting commands `~proplot.axes.PlotAxes.pcolormesh` and
-# `~proplot.axes.PlotAxes.contourf`. See the :ref:`1D plotting <ug_1dplots>` and
-# :ref:`2D plotting <ug_2dplots>` sections for details on the features added by proplot.
+# which means a shallow learning curve for the average matplotlib user. It also tries
+# to :ref:`standardize the positional arguments <ug_1dstd>` and optional keyword
+# arguments accepted by similar or analogous commands, providing an arguably more
+# intuitive interface. In the below example, we create a 4-panel figure with the
+# familiar "1D" plotting commands `~proplot.axes.PlotAxes.plot` and
+# `~proplot.axes.PlotAxes.scatter`, along with the "2D" plotting commands
+# `~proplot.axes.PlotAxes.pcolormesh` and `~proplot.axes.PlotAxes.contourf`.
+# See the :ref:`1D plotting <ug_1dplots>` and :ref:`2D plotting <ug_2dplots>`
+# sections for details on the features added by proplot.
 
 
 # %%
@@ -277,10 +276,10 @@
 # Matplotlib includes `two different interfaces
 # <https://matplotlib.org/stable/api/index.html>`__ for formatting stuff:
 # a "python-style" object-oriented interface with instance-level commands
-# like `matplotlib.axes.Axes.set_title`, and a "MATLAB-style" interface that
-# tracks "current" axes and provides global `~matplotlib.pyplot` commands like
+# like `matplotlib.axes.Axes.set_title`, and a "MATLAB-style" interface
+# that tracks current axes and provides global commands like
 # `matplotlib.pyplot.title`. Proplot provides the ``format`` command as a succinct
-# and powerful alternative to these two approaches. While the above one-liner
+# and powerful alternative to these interfaces. While matplotlib's one-liner
 # commands still work, we recommend using ``format`` -- it only needs to
 # be called once, and it tends to cut down on boilerplate code. You can call
 # ``format`` manually or pass ``format`` parameters to axes-creation commands
@@ -300,8 +299,8 @@
 # * Cartesian axes settings (valid only for `~proplot.axes.CartesianAxes`).
 #   These are related to *x* and *y* axis ticks, spines, bounds, and labels --
 #   for example, ``ax.format(xlim=(0, 5))`` changes the x axis bounds.
-#   See `proplot.axes.CartesianAxes.format`
-#   and :ref:`this section <ug_cartesian>` for details.
+#   See `proplot.axes.CartesianAxes.format` and
+#   :ref:`this section <ug_cartesian>` for details.
 #
 # * Polar axes settings (valid only for `~proplot.axes.PolarAxes`).
 #   These are related to azimuthal and radial grid lines, bounds, and labels --
diff --git a/docs/colorbars_legends.py b/docs/colorbars_legends.py
@@ -43,12 +43,12 @@
 #   (e.g., ``loc='right'`` or the shorthand ``loc='r'``). If you draw multiple legends
 #   or colorbars on one side, they are "stacked" on top of each other. Unlike using
 #   `bbox_to_anchor`, the "outer" legend position is adjusted automatically when the
-#   :ref:`tight layout algorithm <ug_tight>` is active for the figure.
+#   :ref:`tight layout algorithm <ug_tight>` is active.
 # * Proplot adds the axes command `proplot.axes.Axes.colorbar`,
 #   analogous to `proplot.axes.Axes.legend` and equivalent to
 #   calling `proplot.figure.Figure.colorbar` with an `ax` keyword.
 #   `~proplot.axes.Axes.colorbar` can draw both "outer" colorbars when you request
-#   a side location (e.g., loc='right'`` or the shorthand ``loc='r'``) and "inset"
+#   a side location (e.g., ``loc='right'`` or the shorthand ``loc='r'``) and "inset"
 #   colorbars when you request an :ref:`inset location <colorbar_table>`
 #   (e.g., ``loc='upper right'`` or the shorthand ``loc='ur'``). Inset
 #   colorbars have optional background "frames" that can be configured
@@ -57,7 +57,7 @@
 # `~proplot.axes.Axes.colorbar` and `~proplot.axes.Axes.legend` also both accept
 # `space` and `pad` keywords. `space` controls the absolute separation of the
 # "outer" colorbar or legend from the parent subplot edge and `pad` controls the
-# :ref:`tight layout <ug_tight>` padding relative to the subplot axis and tick labels
+# :ref:`tight layout <ug_tight>` padding relative to the subplot's tick and axis labels
 # (or, for "inset" locations, the padding between the subplot edge and the inset frame).
 # The below example shows a variety of arrangements of "outer" and "inset"
 # colorbars and legends.
@@ -155,7 +155,7 @@
     colorbar_kw={'length': 0.8, 'label': 'colorbar label'},
 )
 ax.contour(
-    state.rand(10, 10), cmap='Blues1', cmap_kw={'left': 0.1}, levels=9, lw=2,
+    state.rand(10, 10), cmap='Mono', cmap_kw={'left': 0.1}, levels=9, lw=2,
     colorbar='r', colorbar_kw={'label': 'colorbar label', 'length': 0.7},
     label='contour', legend='ul', legend_kw={'label': 'legend from mappable'},
 )
@@ -264,7 +264,7 @@
 #
 # The basic usage of `proplot.axes.Axes.colorbar` and `proplot.figure.Figure.colorbar`
 # includes a few useful improvements compared to the matplotlib commands. The following
-# core feature is useful for labeling discrete plot elements that bear some numeric
+# feature is useful for labeling discrete plot elements that bear some numeric
 # relationship to one another:
 
 # * Calling ``colorbar`` with a list of `~matplotlib.artist.Artist`\ s,
@@ -274,9 +274,9 @@
 #   with :ref:`1D plot commands <ug_1dplots>` like `~proplot.axes.PlotAxes.plot`.
 # * The associated :ref:`colormap normalizer <ug_norm>` can be specified with the
 #   `vmin`, `vmax`, `norm`, and `norm_kw` keywords. The `~proplot.colors.DiscreteNorm`
-#   levels and default tick locations can be specified with `values`, or proplot will
-#   infer them from the `~matplotlib.artist.Artist` labels (non-numeric labels will be
-#   applied to the colorbar as tick labels).
+#   levels can be specified with `values`, or proplot will infer them from the
+#   `~matplotlib.artist.Artist` labels (non-numeric labels will be applied to
+#   the colorbar as tick labels).
 #
 # Proplot also includes improvements for adding ticks and tick labels to colorbars.
 # Similar to `proplot.axes.CartesianAxes.format`, you can flexibly specify
diff --git a/proplot/figure.py b/proplot/figure.py
@@ -1853,7 +1853,7 @@ def gridspec(self):
         --------
         proplot.figure.Figure.subplotgrid
         proplot.gridspec.GridSpec.figure
-        ptoplot.gridspec.SubplotGrid.gridspec
+        proplot.gridspec.SubplotGrid.gridspec
         """
         return self._gridspec
 
@@ -1873,7 +1873,7 @@ def subplotgrid(self):
         See also
         --------
         proplot.figure.Figure.gridspec
-        ptoplot.gridspec.SubplotGrid.figure
+        proplot.gridspec.SubplotGrid.figure
         """
         return pgridspec.SubplotGrid([s for _, s in sorted(self._subplot_dict.items())])
 
