Subclass normalizers from Abstract Base Class

patniharshit · patniharshit · commit ad2687dc7a25 · 2017-08-02T14:45:25.000+05:30
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
@@ -5128,8 +5128,7 @@ def imshow(self, X, cmap=None, norm=None, aspect=None,
         if not self._hold:
             self.cla()
 
-        isNorm = isinstance(norm, (mcolors.Normalize, mcolors.BivariateNorm))
-        if norm is not None and not isNorm:
+        if norm is not None and not isinstance(norm, mcolors.Norms):
             msg = "'norm' must be an instance of 'mcolors.Normalize' " \
                   "or 'mcolors.BivariateNorm'"
             raise ValueError(msg)
@@ -5468,8 +5467,7 @@ def pcolor(self, *args, **kwargs):
         collection.set_alpha(alpha)
         collection.set_array(C)
 
-        isNorm = isinstance(norm, (mcolors.Normalize, mcolors.BivariateNorm))
-        if norm is not None and not isNorm:
+        if norm is not None and not isinstance(norm, mcolors.Norms):
             msg = "'norm' must be an instance of 'mcolors.Normalize' " \
                   "or 'mcolors.BivariateNorm'"
             raise ValueError(msg)
@@ -5749,8 +5747,8 @@ def pcolorfast(self, *args, **kwargs):
         cmap = kwargs.pop('cmap', None)
         vmin = kwargs.pop('vmin', None)
         vmax = kwargs.pop('vmax', None)
-        isNorm = isinstance(norm, (mcolors.Normalize, mcolors.BivariateNorm))
-        if norm is not None and not isNorm:
+
+        if norm is not None and not isinstance(norm, mcolors.Norms):
             msg = "'norm' must be an instance of 'mcolors.Normalize' " \
                   "or 'mcolors.BivariateNorm'"
             raise ValueError(msg)
diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py
@@ -68,7 +68,7 @@
 import numpy as np
 import matplotlib.cbook as cbook
 from ._color_data import BASE_COLORS, TABLEAU_COLORS, CSS4_COLORS, XKCD_COLORS
-
+from abc import ABCMeta
 
 class _ColorMapping(dict):
     def __init__(self, mapping):
@@ -882,7 +882,14 @@ def reversed(self, name=None):
         raise NotImplementedError()
 
 
-class Normalize(object):
+class Norms:
+    """
+    Abstract Base Class to group `Normalize` and `BivariateNorm`
+    """
+    __metaclass__ = ABCMeta
+    pass
+
+class Normalize(Norms):
     """
     A class which, when called, can normalize data into
     the ``[0.0, 1.0]`` interval.
@@ -1374,7 +1381,7 @@ def inverse(self, value):
         return value
 
 
-class BivariateNorm:
+class BivariateNorm(Norms):
     """
     Normalize a list of two values corresponding to two 1D normalizers
     """
diff --git a/lib/matplotlib/tests/test_colors.py b/lib/matplotlib/tests/test_colors.py
@@ -708,3 +708,15 @@ def __add__(self, other):
                  mcolors.SymLogNorm(3, vmax=5, linscale=1),
                  mcolors.PowerNorm(1)]:
         assert_array_equal(norm(data.view(MyArray)), norm(data))
+
+
+@pytest.mark.parametrize('norm', [
+        mcolors.Normalize(), mcolors.LogNorm(), mcolors.BivariateNorm()
+    ]
+)
+def test_abstract_base_class_norms(norm):
+    """
+    Test that all types of normalizers subclasses Abstract Base class
+    `colors.Norms`
+    """
+    assert isinstance(norm, mcolors.Norms)
