Fix minor typos in colormap manipulation tutorial.

Author: QuLogic

tutorials/colors/colormap-manipulation.py

@@ -48,7 +48,7 @@
 # ListedColormap
 # --------------
 #
-# `.ListedColormap` s store their color values in a ``.colors`` attribute.
+# `.ListedColormap`\s store their color values in a ``.colors`` attribute.
 # The list of colors that comprise the colormap can be directly accessed using
 # the ``colors`` property,
 # or it can be accessed indirectly by calling  ``viridis`` with an array
@@ -68,7 +68,7 @@
 ##############################################################################
 # LinearSegmentedColormap
 # -----------------------
-# `.LinearSegmentedColormap` s do not have a ``.colors`` attribute.
+# `.LinearSegmentedColormap`\s do not have a ``.colors`` attribute.
 # However, one may still call the colormap with an integer array, or with a
 # float array between 0 and 1.
 
@@ -114,7 +114,7 @@ def plot_examples(colormaps):
 
 ##############################################################################
 # In fact, that list may contain any valid
-# :doc:`matplotlib color specification </tutorials/colors/colors>`.
+# :doc:`Matplotlib color specification </tutorials/colors/colors>`.
 # Particularly useful for creating custom colormaps are Nx4 numpy arrays.
 # Because with the variety of numpy operations that we can do on a such an
 # array, carpentry of new colormaps from existing colormaps become quite
@@ -168,7 +168,7 @@ def plot_examples(colormaps):
 # Creating linear segmented colormaps
 # ===================================
 #
-# `.LinearSegmentedColormap` class specifies colormaps using anchor points
+# The `.LinearSegmentedColormap` class specifies colormaps using anchor points
 # between which RGB(A) values are interpolated.
 #
 # The format to specify these colormaps allows discontinuities at the anchor
@@ -177,7 +177,7 @@ def plot_examples(colormaps):
 # ``yleft[i]`` and ``yright[i]`` are the values of the color on either
 # side of the anchor point.
 #
-# If there are no discontinuities, then ``yleft[i]=yright[i]``:
+# If there are no discontinuities, then ``yleft[i] == yright[i]``:
 
 cdict = {'red':   [[0.0,  0.0, 0.0],
                    [0.5,  1.0, 1.0],
@@ -221,9 +221,10 @@ def plot_linearmap(cdict):
 #
 # In the example below there is a discontinuity in red at 0.5.  The
 # interpolation between 0 and 0.5 goes from 0.3 to 1, and between 0.5 and 1
-# it goes from 0.9 to 1.  Note that red[0, 1], and red[2, 2] are both
-# superfluous to the interpolation because red[0, 1] is the value to the
-# left of 0, and red[2, 2] is the value to the right of 1.0.
+# it goes from 0.9 to 1.  Note that ``red[0, 1]``, and ``red[2, 2]`` are both
+# superfluous to the interpolation because ``red[0, 1]`` (i.e., ``yleft[0]``)
+# is the value to the left of 0, and ``red[2, 2]`` (i.e., ``yright[2]``) is the
+# value to the right of 1, which are outside the color mapping domain.
 
 cdict['red'] = [[0.0,  0.0, 0.3],
                 [0.5,  1.0, 0.9],
@@ -234,7 +235,7 @@ def plot_linearmap(cdict):
 # Directly creating a segmented colormap from a list
 # --------------------------------------------------
 #
-# The above described is a very versatile approach, but admittedly a bit
+# The approach described above is very versatile, but admittedly a bit
 # cumbersome to implement. For some basic cases, the use of
 # `.LinearSegmentedColormap.from_list` may be easier. This creates a segmented
 # colormap with equal spacings from a supplied list of colors.
@@ -243,8 +244,8 @@ def plot_linearmap(cdict):
 cmap1 = LinearSegmentedColormap.from_list("mycmap", colors)
 
 #############################################################################
-# If desired, the nodes of the colormap can be given as numbers
-# between 0 and 1. E.g. one could have the reddish part take more space in the
+# If desired, the nodes of the colormap can be given as numbers between 0 and
+# 1. For example, one could have the reddish part take more space in the
 # colormap.
 
 nodes = [0.0, 0.4, 0.8, 1.0]