Clarify doc for "norm" kwarg to imshow.

anntzer · anntzer · commit e5ec7a5c396f · 2016-07-24T16:41:15.000-07:00
"norm" also applies when X is a 2D-array of integers -- i.e, similarly
to the "cmap" kwarg.  Make the docs for the two kwargs consistent.
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
@@ -4957,8 +4957,8 @@ def imshow(self, X, cmap=None, norm=None, aspect=None,
             normalised.
 
         cmap : `~matplotlib.colors.Colormap`, optional, default: None
-            If None, default to rc `image.cmap` value. `cmap` is ignored when
-            `X` has RGB(A) information
+            If None, default to rc `image.cmap` value. `cmap` is ignored if `X`
+            has RGB(A) information.
 
         aspect : ['auto' | 'equal' | scalar], optional, default: None
             If 'auto', changes the image aspect ratio to match that of the
@@ -4983,10 +4983,10 @@ def imshow(self, X, cmap=None, norm=None, aspect=None,
             'nearest'.
 
         norm : `~matplotlib.colors.Normalize`, optional, default: None
-            A `~matplotlib.colors.Normalize` instance is used to scale
-            luminance data to 0, 1. If `None`, use the default
-            func:`normalize`. `norm` is only used if `X` is an array of
-            floats.
+            A `~matplotlib.colors.Normalize` instance is used to
+            scale luminance data to 0, 1. If `None`, use the default
+            func:`normalize`. `norm` is only used if `X` has RGB(A)
+            information.
 
         vmin, vmax : scalar, optional, default: None
             `vmin` and `vmax` are used in conjunction with norm to normalize
