Merge pull request #2336 from pelson/completely_masked

mdboom · mdboom · commit 49b73e7c9cf3 · 2013-09-27T06:14:55.000-07:00
Added check in autoscale_None for completely masked pcolor plots.
diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py
@@ -880,10 +880,10 @@ def __call__(self, value, clip=None):
 
         self.autoscale_None(result)
         vmin, vmax = self.vmin, self.vmax
-        if vmin > vmax:
-            raise ValueError("minvalue must be less than or equal to maxvalue")
-        elif vmin == vmax:
+        if vmin == vmax:
             result.fill(0)   # Or should it be all masked?  Or 0.5?
+        elif vmin > vmax:
+            raise ValueError("minvalue must be less than or equal to maxvalue")
         else:
             vmin = float(vmin)
             vmax = float(vmax)
@@ -921,9 +921,9 @@ def autoscale(self, A):
 
     def autoscale_None(self, A):
         ' autoscale only None-valued vmin or vmax'
-        if self.vmin is None:
+        if self.vmin is None and np.size(A) > 0:
             self.vmin = ma.min(A)
-        if self.vmax is None:
+        if self.vmax is None and np.size(A) > 0:
             self.vmax = ma.max(A)
 
     def scaled(self):
diff --git a/lib/matplotlib/tests/test_colors.py b/lib/matplotlib/tests/test_colors.py
@@ -7,6 +7,9 @@
 from numpy.testing.utils import assert_array_equal
 import matplotlib.colors as mcolors
 import matplotlib.cm as cm
+import matplotlib.pyplot as plt
+from matplotlib.testing.decorators import cleanup
+
 
 def test_colormap_endian():
     """
@@ -23,6 +26,7 @@ def test_colormap_endian():
         #print(anative.dtype.isnative, aforeign.dtype.isnative)
         assert_array_equal(cmap(anative), cmap(aforeign))
 
+
 def test_BoundaryNorm():
     """
     Github issue #1258: interpolation was failing with numpy
@@ -36,6 +40,7 @@ def test_BoundaryNorm():
     ncolors = len(boundaries)
     bn = mcolors.BoundaryNorm(boundaries, ncolors)
     assert_array_equal(bn(vals), expected)
+
     
 def test_LogNorm():
     """
@@ -46,3 +51,10 @@ def test_LogNorm():
     ln = mcolors.LogNorm(clip=True, vmax=5)
     assert_array_equal(ln([1, 6]), [0, 1.0])
 
+
+@cleanup
+def test_autoscale_masked():
+    # Test for #2336. Previously fully masked data would trigger a ValueError.
+    data = np.ma.masked_all((12, 20))
+    plt.pcolor(data)
+    plt.draw()
