fix a few more sphinx warnings

Author: ddale

doc/devel/documenting_mpl.rst

@@ -176,6 +176,7 @@ working with Sphinx in general. Here are a few additional things to keep in mind
 * The autodoc extension will handle index entries for the API, but additional
   entries in the index_ need to be explicitly added.
 
+.. _Sphinx: http://sphinx.pocoo.org
 .. _documentation: http://sphinx.pocoo.org/contents.html
 .. _`inline markup`: http://sphinx.pocoo.org/markup/inline.html
 .. _index: http://sphinx.pocoo.org/markup/para.html#index-generating-markup

doc/faq/installing_faq.rst

@@ -277,8 +277,9 @@ Compile matplotlib with PyGTK-2.4
 -------------------------------------------
 
 There is a `bug in PyGTK-2.4`_. You need to edit
-:file:`pygobject.h` to add the :cmacro:`G_BEGIN_DECLS` and :cmacro:`G_END_DECLS`
-macros, and rename :cdata:`typename` parameter to :cdata:`typename_`::
+:file:`pygobject.h` to add the :c:macro:`G_BEGIN_DECLS` and
+:c:macro:`G_END_DECLS` macros, and rename :c:data:`typename` parameter to
+:c:data:`typename_`::
 
   -                       const char *typename,
   +                       const char *typename_,

doc/users/image_tutorial.rst

@@ -228,7 +228,7 @@ object:
 
 There are many other colormap schemes available.  See the `list and images of the colormaps <http://matplotlib.sourceforge.net/examples/pylab_examples/show_colormaps.html>`_.
 
-.. _`Color Bars`
+.. _`Color Bars`:
 
 Color scale reference
 ------------------------
@@ -256,7 +256,7 @@ automatically change if you change you switch to a different
 colormap - you have to re-create your plot, and add in the colorbar
 again.
 
-.. _`Data ranges`
+.. _`Data ranges`:
 
 Examining a specific data range
 ---------------------------------

doc/users/recipes.rst

@@ -101,7 +101,7 @@ objects in a numpy record array::
   array([2004-08-19, 2004-08-20, 2004-08-23, ..., 2008-10-10, 2008-10-13,
 	 2008-10-14], dtype=object)
 
-The dtype of the numpy record array for the field 'date' is '|O4'
+The dtype of the numpy record array for the field ``date`` is ``|O4``
 which means it is a 4-byte python object pointer; in this case the
 objects are datetime.date instances, which we can see when we print
 some samples in the ipython terminal window.
@@ -130,7 +130,7 @@ the x locations are formatted the same way the tick labels are, eg
 "Dec 2004".  What we'd like is for the location in the toolbar to have
 a higher degree of precision, eg giving us the exact date out mouse is
 hovering over.  To fix the first problem, we can use
-method:`matplotlib.figure.Figure.autofmt_xdate` and to fix the second
+:func:`matplotlib.figure.Figure.autofmt_xdate` and to fix the second
 problem we can use the ``ax.fmt_xdata`` attribute which can be set to
 any function that takes a scalar and returns a string.  matplotlib has
 a number of date formatters built in, so we'll use one of those.

lib/matplotlib/axes.py

@@ -3819,7 +3819,7 @@ def plot_date(self, x, y, fmt='bo', tz=None, xdate=True, ydate=False,
         """
         call signature::
 
-          plot_date(x, y, fmt='bo', tz=None, xdate=True, ydate=False, **kwargs)
+           plot_date(x, y, fmt='bo', tz=None, xdate=True, ydate=False, **kwargs)
 
         Similar to the :func:`~matplotlib.pyplot.plot` command, except
         the *x* or *y* (or both) data is considered to be dates, and the
@@ -3830,18 +3830,18 @@ def plot_date(self, x, y, fmt='bo', tz=None, xdate=True, ydate=False,
 
         Keyword arguments:
 
-          *fmt*: string
-            The plot format string.
+        *fmt*: string
+           The plot format string.
 
-          *tz*: [ None | timezone string ]
-            The time zone to use in labeling dates. If *None*, defaults to rc
-            value.
+        *tz*: [ None | timezone string ]
+           The time zone to use in labeling dates. If *None*, defaults to rc
+           value.
 
-          *xdate*: [ True | False ]
-            If *True*, the *x*-axis will be labeled with dates.
+        *xdate*: [ True | False ]
+           If *True*, the *x*-axis will be labeled with dates.
 
-          *ydate*: [ False | True ]
-            If *True*, the *y*-axis will be labeled with dates.
+        *ydate*: [ False | True ]
+           If *True*, the *y*-axis will be labeled with dates.
 
         Note if you are using custom date tickers and formatters, it
         may be necessary to set the formatters/locators after the call
@@ -3861,14 +3861,12 @@ def plot_date(self, x, y, fmt='bo', tz=None, xdate=True, ydate=False,
 
         .. seealso::
 
-           :mod:`~matplotlib.dates`
-              for helper functions
+           :mod:`~matplotlib.dates` for helper functions
 
            :func:`~matplotlib.dates.date2num`,
            :func:`~matplotlib.dates.num2date` and
-           :func:`~matplotlib.dates.drange`
-              for help on creating the required floating point
-              dates.
+           :func:`~matplotlib.dates.drange` for help on creating the required
+           floating point dates.
         """
 
         if not self._hold: self.cla()
@@ -5907,12 +5905,12 @@ def hexbin(self, x, y, C = None, gridsize = 100, bins = None,
         """
         call signature::
 
-          hexbin(x, y, C = None, gridsize = 100, bins = None,
-                 xscale = 'linear', yscale = 'linear',
-                 cmap=None, norm=None, vmin=None, vmax=None,
-                 alpha=None, linewidths=None, edgecolors='none'
-                 reduce_C_function = np.mean, mincnt=None, marginals=True
-                 **kwargs)
+           hexbin(x, y, C = None, gridsize = 100, bins = None,
+                  xscale = 'linear', yscale = 'linear',
+                  cmap=None, norm=None, vmin=None, vmax=None,
+                  alpha=None, linewidths=None, edgecolors='none'
+                  reduce_C_function = np.mean, mincnt=None, marginals=True
+                  **kwargs)
 
         Make a hexagonal binning plot of *x* versus *y*, where *x*,
         *y* are 1-D sequences of the same length, *N*. If *C* is None
@@ -5931,84 +5929,84 @@ def hexbin(self, x, y, C = None, gridsize = 100, bins = None,
 
         Optional keyword arguments:
 
-          *gridsize*: [ 100 | integer ]
-            The number of hexagons in the *x*-direction, default is
-            100. The corresponding number of hexagons in the
-            *y*-direction is chosen such that the hexagons are
-            approximately regular. Alternatively, gridsize can be a
-            tuple with two elements specifying the number of hexagons
-            in the *x*-direction and the *y*-direction.
+        *gridsize*: [ 100 | integer ]
+           The number of hexagons in the *x*-direction, default is
+           100. The corresponding number of hexagons in the
+           *y*-direction is chosen such that the hexagons are
+           approximately regular. Alternatively, gridsize can be a
+           tuple with two elements specifying the number of hexagons
+           in the *x*-direction and the *y*-direction.
 
-          *bins*: [ None | 'log' | integer | sequence ]
-            If *None*, no binning is applied; the color of each hexagon
-            directly corresponds to its count value.
+        *bins*: [ None | 'log' | integer | sequence ]
+           If *None*, no binning is applied; the color of each hexagon
+           directly corresponds to its count value.
 
-            If 'log', use a logarithmic scale for the color
-            map. Internally, :math:`log_{10}(i+1)` is used to
-            determine the hexagon color.
+           If 'log', use a logarithmic scale for the color
+           map. Internally, :math:`log_{10}(i+1)` is used to
+           determine the hexagon color.
 
-            If an integer, divide the counts in the specified number
-            of bins, and color the hexagons accordingly.
+           If an integer, divide the counts in the specified number
+           of bins, and color the hexagons accordingly.
 
-            If a sequence of values, the values of the lower bound of
-            the bins to be used.
+           If a sequence of values, the values of the lower bound of
+           the bins to be used.
 
-          *xscale*: [ 'linear' | 'log' ]
-            Use a linear or log10 scale on the horizontal axis.
+        *xscale*: [ 'linear' | 'log' ]
+           Use a linear or log10 scale on the horizontal axis.
 
-          *scale*: [ 'linear' | 'log' ]
-            Use a linear or log10 scale on the vertical axis.
+        *scale*: [ 'linear' | 'log' ]
+           Use a linear or log10 scale on the vertical axis.
 
-          *mincnt*: None | a positive integer
-            If not None, only display cells with more than *mincnt*
-            number of points in the cell
+        *mincnt*: None | a positive integer
+           If not None, only display cells with more than *mincnt*
+           number of points in the cell
 
-          *marginals*: True|False
-            if marginals is True, plot the marginal density as
-            colormapped rectagles along the bottom of the x-axis and
-            left of the y-axis
+        *marginals*: True|False
+           if marginals is True, plot the marginal density as
+           colormapped rectagles along the bottom of the x-axis and
+           left of the y-axis
 
-          *extent*: [ None | scalars (left, right, bottom, top) ]
-            The limits of the bins. The default assigns the limits
-            based on gridsize, x, y, xscale and yscale.
+        *extent*: [ None | scalars (left, right, bottom, top) ]
+           The limits of the bins. The default assigns the limits
+           based on gridsize, x, y, xscale and yscale.
 
         Other keyword arguments controlling color mapping and normalization
         arguments:
 
-          *cmap*: [ None | Colormap ]
-            a :class:`matplotlib.cm.Colormap` instance. If *None*,
-            defaults to rc ``image.cmap``.
+        *cmap*: [ None | Colormap ]
+           a :class:`matplotlib.cm.Colormap` instance. If *None*,
+           defaults to rc ``image.cmap``.
 
-          *norm*: [ None | Normalize ]
-            :class:`matplotlib.colors.Normalize` instance is used to
-            scale luminance data to 0,1.
+        *norm*: [ None | Normalize ]
+           :class:`matplotlib.colors.Normalize` instance is used to
+           scale luminance data to 0,1.
 
-          *vmin*/*vmax*: scalar
-            *vmin* and *vmax* are used in conjunction with *norm* to normalize
-            luminance data.  If either are *None*, the min and max of the color
-            array *C* is used.  Note if you pass a norm instance, your settings
-            for *vmin* and *vmax* will be ignored.
+        *vmin*/*vmax*: scalar
+           *vmin* and *vmax* are used in conjunction with *norm* to normalize
+           luminance data.  If either are *None*, the min and max of the color
+           array *C* is used.  Note if you pass a norm instance, your settings
+           for *vmin* and *vmax* will be ignored.
 
-          *alpha*: scalar between 0 and 1, or None
-            the alpha value for the patches
+        *alpha*: scalar between 0 and 1, or None
+           the alpha value for the patches
 
-          *linewidths*: [ None | scalar ]
-            If *None*, defaults to rc lines.linewidth. Note that this
-            is a tuple, and if you set the linewidths argument you
-            must set it as a sequence of floats, as required by
-            :class:`~matplotlib.collections.RegularPolyCollection`.
+        *linewidths*: [ None | scalar ]
+           If *None*, defaults to rc lines.linewidth. Note that this
+           is a tuple, and if you set the linewidths argument you
+           must set it as a sequence of floats, as required by
+           :class:`~matplotlib.collections.RegularPolyCollection`.
 
         Other keyword arguments controlling the Collection properties:
 
-          *edgecolors*: [ None | mpl color | color sequence ]
-            If 'none', draws the edges in the same color as the fill color.
-            This is the default, as it avoids unsightly unpainted pixels
-            between the hexagons.
+        *edgecolors*: [ None | mpl color | color sequence ]
+           If 'none', draws the edges in the same color as the fill color.
+           This is the default, as it avoids unsightly unpainted pixels
+           between the hexagons.
 
-            If *None*, draws the outlines in the default color.
+           If *None*, draws the outlines in the default color.
 
-            If a matplotlib color arg or sequence of rgba tuples, draws the
-            outlines in the specified color.
+           If a matplotlib color arg or sequence of rgba tuples, draws the
+           outlines in the specified color.
 
         Here are the standard descriptions of all the
         :class:`~matplotlib.collections.Collection` kwargs:

lib/matplotlib/pyplot.py

@@ -1140,7 +1140,7 @@ def xscale(*args, **kwargs):
     ax = gca()
     ax.set_xscale(*args, **kwargs)
     draw_if_interactive()
-    
+
 @docstring.dedent_interpd
 def yscale(*args, **kwargs):
     """
@@ -1157,7 +1157,7 @@ def yscale(*args, **kwargs):
     ax = gca()
     ax.set_yscale(*args, **kwargs)
     draw_if_interactive()
-    
+
 def xticks(*args, **kwargs):
     """
     Set/Get the xlimits of the current ticklocs and labels::

lib/matplotlib/sphinxext/plot_directive.py

@@ -20,13 +20,13 @@
 
   2. Included as inline content to the directive::
 
-     .. plot::
+       .. plot::
 
-        import matplotlib.pyplot as plt
-        import matplotlib.image as mpimg
-        import numpy as np
-        img = mpimg.imread('_static/stinkbug.png')
-        imgplot = plt.imshow(img)
+          import matplotlib.pyplot as plt
+          import matplotlib.image as mpimg
+          import numpy as np
+          img = mpimg.imread('_static/stinkbug.png')
+          imgplot = plt.imshow(img)
 
 In HTML output, `plot` will include a .png file with a link to a high-res
 .png and .pdf.  In LaTeX output, it will include a .pdf.