Handle min, max of possibly all-masked array

efiring · tacaswell · commit 8c3ad29e99bd · 2017-10-12T01:13:29.000-05:00
diff --git a/lib/matplotlib/image.py b/lib/matplotlib/image.py
@@ -368,21 +368,14 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
                     scaled_dtype = A.dtype
                 else:
                     scaled_dtype = np.float32
-                # old versions of numpy do not work with `np.nammin`
-                # and `np.nanmax` as inputs
-                a_min = np.ma.min(A)
-                a_max = np.ma.max(A)
-
-                # we need these try/except blocks to handle
-                # fully-masked/invalid input
-                try:
+                    
+                a_min = A.min()
+                if a_min is np.ma.masked:
+                    a_min, a_max = 0, 1  # all masked, so values don't matter
+                else:
                     a_min = a_min.astype(scaled_dtype)
-                except AttributeError:
-                    a_min = 0
-                try:
-                    a_max = a_max.astype(scaled_dtype)
-                except AttributeError:
-                    a_min = 1
+                    a_max = A.max().astype(scaled_dtype)
+                
                 # scale the input data to [.1, .9].  The Agg
                 # interpolators clip to [0, 1] internally, use a
                 # smaller input scale to identify which of the
