matplotlib
diff --git a/‎examples/images_contours_and_fields/bivariate_demo.py
Copy file name to clipboardExpand all lines: examples/images_contours_and_fields/bivariate_demo.py
+8-4Lines changed: 8 additions & 4 deletions b/‎examples/images_contours_and_fields/bivariate_demo.py
Copy file name to clipboardExpand all lines: examples/images_contours_and_fields/bivariate_demo.py
+8-4Lines changed: 8 additions & 4 deletions
diff --git a/‎lib/matplotlib/axes/_axes.py
Copy file name to clipboardExpand all lines: lib/matplotlib/axes/_axes.py
+3-3Lines changed: 3 additions & 3 deletions b/‎lib/matplotlib/axes/_axes.py
Copy file name to clipboardExpand all lines: lib/matplotlib/axes/_axes.py
+3-3Lines changed: 3 additions & 3 deletions
@@ -1,7 +1,7 @@
 """
-===========
+==============
 Bivariate Demo
-===========
+==============
 
 Plotting bivariate data.
 
@@ -28,13 +28,17 @@
 
 bivariate = [air_temp, surf_pres]
 
-# to distinguish bivariate data either BivariateNorm or BivariateColormap must
+###############################################################################
+# To distinguish bivariate data either BivariateNorm or BivariateColormap must
 # be passed in as argument
+
 cax = ax.imshow(bivariate, norm=colors.BivariateNorm(),
                 cmap=colors.BivariateColormap())
 
-# if input data is bivariate then colorbar automatically draws colorsquare
+###############################################################################
+# If input data is bivariate then colorbar automatically draws colorsquare
 # instead of colorbar
+
 cbar = fig.colorbar(cax, xlabel='air_temp', ylabel='surf_pres')
 
 plt.show()
@@ -5302,11 +5302,11 @@ def pcolor(self, *args, **kwargs):
             vectors, they will be expanded as needed into the appropriate 2-D
             arrays, making a rectangular grid.
 
-        cmap : `~matplotlib.colors.Colormap` or
+        cmap : `~matplotlib.colors.Colormap` or \
             `matplotlib.colors.BivariateColormap`, optional, default: None
             If `None`, default to rc settings.
 
-        norm : `matplotlib.colors.Normalize` or
+        norm : `matplotlib.colors.Normalize` or \
             `matplotlib.colors.BivariateNorm`, optional, default: None
             An instance is used to scale luminance data to (0, 1).
             If `None`, defaults to :func:`normalize`.
@@ -5575,7 +5575,7 @@ def pcolormesh(self, *args, **kwargs):
 
           *cmap*: [ *None* | Colormap ]
             A :class:`matplotlib.colors.Colormap` or
-            :class:`matplotlib.colors.BivariateColormap`instance. If *None*,
+            :class:`matplotlib.colors.BivariateColormap` instance. If *None*,
             use rc settings.
 
           *norm*: [ *None* | Normalize ]