matplotlib
diff --git a/‎lib/matplotlib/tests/test_colors.py
Lines changed: 7 additions & 4 deletions b/‎lib/matplotlib/tests/test_colors.py
Lines changed: 7 additions & 4 deletions
@@ -122,6 +122,7 @@ def test_cmap_and_norm_from_levels_and_colors2():
     clr = mcolors.colorConverter.to_rgba_array(colors)
     bad = (0.1, 0.1, 0.1, 0.1)
     no_color = (0.0, 0.0, 0.0, 0.0)
+    masked_value = 'masked value'
 
     # Define the test values which are of interest.
     # Note: levels are lev[i] <= v < lev[i+1]
@@ -131,38 +132,40 @@ def test_cmap_and_norm_from_levels_and_colors2():
                              2.25: clr[2],
                              3: clr[4],
                              3.5: clr[4],
-                             np.ma.array(1, mask=True): bad}),
+                             masked_value: bad}),
 
              ('min', -1, {-2: clr[0],
                           -1: clr[1],
                           2: clr[2],
                           2.25: clr[2],
                           3: no_color,
                           3.5: no_color,
-                          np.ma.array(1, mask=True): bad}),
+                          masked_value: bad}),
 
              ('max', -1, {-2: no_color,
                           -1: clr[0],
                           2: clr[1],
                           2.25: clr[1],
                           3: clr[3],
                           3.5: clr[3],
-                          np.ma.array(1, mask=True): bad}),
+                          masked_value: bad}),
 
              ('neither', -2, {-2: no_color,
                               -1: clr[0],
                               2: clr[1],
                               2.25: clr[1],
                               3: no_color,
                               3.5: no_color,
-                              np.ma.array(1, mask=True): bad}),
+                              masked_value: bad}),
              ]
 
     for extend, i1, cases in tests:
         cmap, norm = mcolors.from_levels_and_colors(levels, colors[0:i1],
                                                     extend=extend)
         cmap.set_bad(bad)
         for d_val, expected_color in sorted(cases.items()):
+            if d_val == masked_value:
+                d_val = np.ma.array(1, mask=True)
             assert_array_equal(expected_color, cmap(norm([d_val]))[0],
                                'Wih extend={0!r} and data '
                                'value={1!r}'.format(extend, d_val))