DOC: Fix small issues in new release notes.

Author: QuLogic

doc/api/api_changes.rst

@@ -73,7 +73,7 @@ properties.
 
 The :class:`~matplotlib.legend.Legend` background patch (or 'frame')
 can have its `edgecolor` and `facecolor` determined by the
-corresponding keyword arguments to its initializer, or to any of the
+corresponding keyword arguments to the `Legend` initializer, or to any of the
 methods or functions that call that initializer.  If left to
 their default values of `None`, their values will be taken from
 `rcParams`.  The previously-existing `framealpha` kwarg still
@@ -108,15 +108,15 @@ See the ``draw_image`` docstring for more information.
 --------------------------------------------------
 
 The ``matplotlib.ticker.LinearLocator`` is used to define the range and location
-of tickmarks of a plot when the user wants a exact number of ticks.
+of tick marks of a plot when the user wants an exact number of ticks.
 ``LinearLocator`` thus differs from the default locator ``MaxNLocator``, which
 does not necessarily return the exact user requested number of ticks.
 
 The view range algorithm in ``matplotlib.ticker.LinearLocator`` has been
-changed so that more convenient tick location are chosen. The new algorithm
-returns a plot view range that is a multiple of the user requested number of
-ticks. This ensures tick marks to be located at whole integers more
-constistently. For example, when both y-axis of a``twinx`` plot use
+changed so that more convenient tick locations are chosen. The new algorithm
+returns a plot view range that is a multiple of the user-requested number of
+ticks. This ensures tick marks will be located at whole integers more
+consistently. For example, when both y-axes of a``twinx`` plot use
 ``matplotlib.ticker.LinearLocator`` with the same number of ticks, the grids of
 both axis will be properly aligned at convenient tick locations.
 
@@ -126,7 +126,7 @@ New defaults for 3D quiver function in mpl_toolkits.mplot3d.axes3d.py
 
 Matplotlib has both a 2D and a 3D ``quiver`` function. These changes
 affect only the 3D function and make the default behavior of the 3D
-function match 2D version. There are two changes:
+function match the 2D version. There are two changes:
 
 1) The 3D quiver function previously normalized the arrows to be the
    same length, which makes it unusable for situations where the
@@ -143,7 +143,7 @@ call the function with ::
 
    ax.quiver(x, y, z, u, v, w, normalize=True, pivot='tip')
 
-where "ax" is a axes3d object created with something like ::
+where "ax" is an ``Axes3d`` object created with something like ::
 
    import mpl_toolkits.mplot3d.axes3d
    ax = plt.sublot(111, projection='3d')

doc/users/annotations.rst

@@ -55,9 +55,9 @@ For physical coordinate systems (points or pixels) the origin is the
 however, the origin is from the (right, top) of the figure or axes,
 analogous to negative indexing of sequences.
 
-Optionally, you can specify arrow properties for adding an arrow
-from the text to the annotated point by giving a dictionary of arrow
-properties in the optional keyword argument ``arrowprops``.
+Optionally, you can enable drawing of an arrow from the text to the annotated
+point by giving a dictionary of arrow properties in the optional keyword
+argument ``arrowprops``.
 
 
 ==================== =====================================================
@@ -90,9 +90,8 @@ annotations, including fancy arrows, see :ref:`plotting-guide-annotation`
 and :ref:`pylab_examples-annotation_demo`.
 
 
-Do not proceed unless you already have read :ref:`annotations-tutorial`,
-:func:`~matplotlib.pyplot.text` and
-:func:`~matplotlib.pyplot.annotate`!
+Do not proceed unless you have already read :ref:`annotations-tutorial`,
+:func:`~matplotlib.pyplot.text` and :func:`~matplotlib.pyplot.annotate`!
 
 
 .. _plotting-guide-annotation:
@@ -125,7 +124,7 @@ The patch object associated with the text can be accessed by::
 
 The return value is an instance of FancyBboxPatch and the patch
 properties like facecolor, edgewidth, etc. can be accessed and
-modified as usual. To change the shape of the box, use *set_boxstyle*
+modified as usual. To change the shape of the box, use the *set_boxstyle*
 method. ::
 
   bb.set_boxstyle("rarrow", pad=0.6)
@@ -150,7 +149,7 @@ keyword arguments. Currently, following box styles are implemented.
 .. plot:: mpl_examples/pylab_examples/fancybox_demo2.py
 
 
-Note that the attributes arguments can be specified within the style
+Note that the attribute arguments can be specified within the style
 name with separating comma (this form can be used as "boxstyle" value
 of bbox argument when initializing the text instance) ::
 
@@ -177,7 +176,7 @@ annotated point is specified in the *data* coordinate and the annotating
 text in *offset points*.
 See :func:`~matplotlib.pyplot.annotate` for available coordinate systems.
 
-An arrow connecting two point (xy & xytext) can be optionally drawn by
+An arrow connecting two points (xy & xytext) can be optionally drawn by
 specifying the ``arrowprops`` argument. To draw only an arrow, use
 empty string as the first argument. ::
 
@@ -198,7 +197,7 @@ The arrow drawing takes a few steps.
 2. If patch object is given (*patchA* & *patchB*), the path is clipped to
    avoid the patch.
 
-3. The path is further shrunk by given amount of pixels (*shirnkA*
+3. The path is further shrunk by given amount of pixels (*shrinkA*
    & *shrinkB*)
 
 4. The path is transmuted to arrow patch, which is controlled by the
@@ -209,7 +208,7 @@ The arrow drawing takes a few steps.
 
 
 The creation of the connecting path between two points is controlled by
-``connectionstyle`` key and following styles are available.
+``connectionstyle`` key and the following styles are available.
 
    ==========   =============================================
    Name         Attrs
@@ -223,7 +222,7 @@ The creation of the connecting path between two points is controlled by
 
 Note that "3" in ``angle3`` and ``arc3`` is meant to indicate that the
 resulting path is a quadratic spline segment (three control
-points). As will be discussed below, some arrow style option only can
+points). As will be discussed below, some arrow style options can only
 be used when the connecting path is a quadratic spline.
 
 The behavior of each connection style is (limitedly) demonstrated in the
@@ -255,9 +254,9 @@ an arrow patch, according to the given ``arrowstyle``.
 
 .. plot:: mpl_examples/pylab_examples/fancyarrow_demo.py
 
-Some arrowstyles only work with connection style that generates a
+Some arrowstyles only work with connection styles that generate a
 quadratic-spline segment. They are ``fancy``, ``simple``, and ``wedge``.
-For these arrow styles, you must use "angle3" or "arc3" connection
+For these arrow styles, you must use the "angle3" or "arc3" connection
 style.
 
 If the annotation string is given, the patchA is set to the bbox patch
@@ -281,8 +280,8 @@ lower-left corner and (1,1) means top-right.
 Placing Artist at the anchored location of the Axes
 ---------------------------------------------------
 
-There are class of artist that can be placed at the anchored location
-of the Axes. A common example is the legend.  This type of artists can
+There are classes of artists that can be placed at an anchored location
+in the Axes. A common example is the legend.  This type of artist can
 be created by using the OffsetBox class. A few predefined classes are
 available in ``mpl_toolkits.axes_grid.anchored_artists``. ::
 
@@ -305,10 +304,10 @@ artists) is known in pixel size during the time of creation. For
 example, If you want to draw a circle with fixed size of 20 pixel x 20
 pixel (radius = 10 pixel), you can utilize
 ``AnchoredDrawingArea``. The instance is created with a size of the
-drawing area (in pixel). And user can add arbitrary artist to the
+drawing area (in pixels), and arbitrary artists can added to the
 drawing area. Note that the extents of the artists that are added to
-the drawing area has nothing to do with the placement of the drawing
-area itself. The initial size only matters. ::
+the drawing area are not related to the placement of the drawing
+area itself. Only the initial size matters. ::
 
     from mpl_toolkits.axes_grid.anchored_artists import AnchoredDrawingArea
 
@@ -319,27 +318,27 @@ area itself. The initial size only matters. ::
     p2 = Circle((30, 10), 5, fc="r")
     ada.drawing_area.add_artist(p2)
 
-The artists that are added to the drawing area should not have
-transform set (they will be overridden) and the dimension of those
+The artists that are added to the drawing area should not have a
+transform set (it will be overridden) and the dimensions of those
 artists are interpreted as a pixel coordinate, i.e., the radius of the
-circles in above example are 10 pixel and 5 pixel, respectively.
+circles in above example are 10 pixels and 5 pixels, respectively.
 
 .. plot:: users/plotting/examples/anchored_box02.py
 
-Sometimes, you want to your artists scale with data coordinate (or
-other coordinate than canvas pixel). You can use
+Sometimes, you want your artists to scale with the data coordinate (or
+coordinates other than canvas pixels). You can use
 ``AnchoredAuxTransformBox`` class. This is similar to
 ``AnchoredDrawingArea`` except that the extent of the artist is
 determined during the drawing time respecting the specified transform. ::
 
   from mpl_toolkits.axes_grid.anchored_artists import AnchoredAuxTransformBox
 
   box = AnchoredAuxTransformBox(ax.transData, loc=2)
-  el = Ellipse((0,0), width=0.1, height=0.4, angle=30) # in data coordinates!
+  el = Ellipse((0,0), width=0.1, height=0.4, angle=30)  # in data coordinates!
   box.drawing_area.add_artist(el)
 
 The ellipse in the above example will have width and height
-corresponds to 0.1 and 0.4 in data coordinate and will be
+corresponding to 0.1 and 0.4 in data coordinateing and will be
 automatically scaled when the view limits of the axes change.
 
 .. plot:: users/plotting/examples/anchored_box03.py
@@ -353,10 +352,10 @@ legend (as a matter of fact, this is how the legend is created).
 Note that unlike the legend, the ``bbox_transform`` is set
 to IdentityTransform by default.
 
-Using Complex Coordinate with Annotation
-----------------------------------------
+Using Complex Coordinates with Annotations
+------------------------------------------
 
-The Annotation in matplotlib support several types of coordinate as
+The Annotation in matplotlib supports several types of coordinates as
 described in :ref:`annotations-tutorial`. For an advanced user who wants
 more control, it supports a few other options.
 
@@ -392,16 +391,16 @@ more control, it supports a few other options.
 
     Note that it is your responsibility that the extent of the
     coordinate artist (*an1* in above example) is determined before *an2*
-    gets drawn. In most cases, it means that an2 needs to be drawn
+    gets drawn. In most cases, it means that *an2* needs to be drawn
     later than *an1*.
 
 
  3. A callable object that returns an instance of either
     :class:`~matplotlib.transforms.BboxBase` or
     :class:`~matplotlib.transforms.Transform`. If a transform is
-    returned, it is same as 1 and if bbox is returned, it is same
-    as 2.  The callable object should take a single argument of
-    renderer instance. For example, following two commands give
+    returned, it is the same as 1 and if a bbox is returned, it is the same
+    as 2.  The callable object should take a single argument of the
+    renderer instance. For example, the following two commands give
     identical results ::
 
       an2 = ax.annotate("Test 2", xy=(1, 0.5), xycoords=an1,
@@ -410,22 +409,21 @@ more control, it supports a few other options.
                         xytext=(30,0), textcoords="offset points")
 
 
- 4. A tuple of two coordinate specification. The first item is for
-    x-coordinate and the second is for y-coordinate. For example, ::
+ 4. A tuple of two coordinate specifications. The first item is for the
+    x-coordinate and the second is for the y-coordinate. For example, ::
 
       annotate("Test", xy=(0.5, 1), xycoords=("data", "axes fraction"))
 
-    0.5 is in data coordinate, and 1 is in normalized axes coordinate.
+    0.5 is in data coordinates, and 1 is in normalized axes coordinates.
     You may use an artist or transform as with a tuple. For example,
 
     .. plot:: users/plotting/examples/annotate_simple_coord02.py
        :include-source:
 
 
- 5. Sometimes, you want your annotation with some "offset points", but
-    not from the annotated point but from other
-    point. :class:`~matplotlib.text.OffsetFrom` is a helper class for such
-    case.
+ 5. Sometimes, you want your annotation with some "offset points", not from the
+    annotated point but from some other point.
+    :class:`~matplotlib.text.OffsetFrom` is a helper class for such cases.
 
     .. plot:: users/plotting/examples/annotate_simple_coord03.py
       :include-source:
@@ -435,28 +433,25 @@ more control, it supports a few other options.
 Using ConnectorPatch
 --------------------
 
-The ConnectorPatch is like an annotation without a text.  While the
-annotate function is recommended in most of situation, the
-ConnectorPatch is useful when you want to connect points in different
-axes. ::
+The ConnectorPatch is like an annotation without text. While the annotate
+function is recommended in most situations, the ConnectorPatch is useful when
+you want to connect points in different axes. ::
 
   from matplotlib.patches import ConnectionPatch
   xy = (0.2, 0.2)
   con = ConnectionPatch(xyA=xy, xyB=xy, coordsA="data", coordsB="data",
                         axesA=ax1, axesB=ax2)
   ax2.add_artist(con)
 
-The above code connects point xy in data coordinate of ``ax1`` to
-point xy int data coordinate of ``ax2``. Here is a simple example.
+The above code connects point xy in the data coordinates of ``ax1`` to
+point xy in the data coordinates of ``ax2``. Here is a simple example.
 
 .. plot:: users/plotting/examples/connect_simple01.py
 
 
-While the ConnectorPatch instance can be added to any axes, but you
-may want it to be added to the axes in the latter (?) of the axes
-drawing order to prevent overlap (?) by other axes.
-
-
+While the ConnectorPatch instance can be added to any axes, you may want to add
+it to the axes that is latest in drawing order to prevent overlap by other
+axes.
 
 
 Advanced Topics
@@ -466,7 +461,7 @@ Zoom effect between Axes
 ------------------------
 
 mpl_toolkits.axes_grid.inset_locator defines some patch classes useful
-for interconnect two axes. Understanding the code requires some
+for interconnecting two axes. Understanding the code requires some
 knowledge of how mpl's transform works. But, utilizing it will be
 straight forward.
 
@@ -478,7 +473,7 @@ Define Custom BoxStyle
 ----------------------
 
 You can use a custom box style. The value for the ``boxstyle`` can be a
-callable object in following forms.::
+callable object in the following forms.::
 
         def __call__(self, x0, y0, width, height, mutation_size,
                      aspect_ratio=1.):
@@ -491,7 +486,7 @@ callable object in following forms.::
               - *aspect_ratio* : aspect-ratio for the mutation.
             """
             path = ...
-	    return path
+            return path
 
 Here is a complete example.
 
@@ -504,6 +499,6 @@ matplotlib.patches.BoxStyle._Base as demonstrated below.
    :include-source:
 
 
-Similarly, you can define custom ConnectionStyle and custom ArrowStyle.
+Similarly, you can define a custom ConnectionStyle and a custom ArrowStyle.
 See the source code of ``lib/matplotlib/patches.py`` and check
 how each style class is defined.

doc/users/colors.rst

@@ -9,7 +9,7 @@ it can be provided as:
 
 * a ``(r, g, b)`` tuple
 * a ``(r, g, b, a)`` tuple
-* a hex string RGB or RGBA (ex ``'#0F0F0F'`` or ``'#0F0F0F0F'``)
+* a hex RGB or RGBA string (ex ``'#0F0F0F'`` or ``'#0F0F0F0F'``)
 * a float value in ``[0, 1]`` inclusive for gray level
 * one of ``{'b', 'g', 'r', 'c', 'm', 'y', 'k', 'w'}``
 * a X11/CSS4 color name
@@ -29,9 +29,9 @@ can be used as a 'single character color' in format-string to
 `matplotlib.Axes.plot`.
 
 The single digit is the index into the default property cycle
-(``matplotlib.rcParams['axes.prop_cycle']`` to get the color from.  If
-the property cycle includes ``'color`` then black is returned.  The
-color is evaluated when the artits is created.  For example
+(``matplotlib.rcParams['axes.prop_cycle']``).  If the property cycle does not
+include ``'color`` then black is returned.  The color is evaluated when the
+artist is created.  For example
 
 .. plot::
    :include-source: True

doc/users/customizing.rst

@@ -27,12 +27,13 @@ Defining your own style
 -----------------------
 
 You can create custom styles and use them by calling ``style.use`` with the
-path or URL to the style sheet. Alternatively, if you add your ``<style-name>.mplstyle``
-file to ``mpl_configdir/stylelib``, you can reuse your custom style sheet with a call to
-``style.use(<style-name>)``. By default ``mpl_configdir`` should be ``~/.config/matplotlib``,
-but you can check where yours is with ``matplotlib.get_configdir()``, you may need to
-create this directory. Note that a custom style sheet in ``mpl_configdir/stylelib``
-will override a style sheet defined by matplotlib if the styles have the same name.
+path or URL to the style sheet. Additionally, if you add your
+``<style-name>.mplstyle`` file to ``mpl_configdir/stylelib``, you can reuse
+your custom style sheet with a call to ``style.use(<style-name>)``. By default
+``mpl_configdir`` should be ``~/.config/matplotlib``, but you can check where
+yours is with ``matplotlib.get_configdir()``; you may need to create this
+directory. Note that a custom style sheet in ``mpl_configdir/stylelib`` will
+override a style sheet defined by matplotlib if the styles have the same name.
 
 For example, you might want to create
 ``mpl_configdir/stylelib/presentation.mplstyle`` with the following::
@@ -71,7 +72,7 @@ Temporary styling
 
 If you only want to use a style for a specific block of code but don't want
 to change the global styling, the style package provides a context manager
-for limiting your changes to a specific scope. To isolate the your styling
+for limiting your changes to a specific scope. To isolate your styling
 changes, you can write something like the following::
 
    >>> import numpy as np