matplotlib
diff --git a/‎lib/matplotlib/image.py
Copy file name to clipboardExpand all lines: lib/matplotlib/image.py
+13-2Lines changed: 13 additions & 2 deletions b/‎lib/matplotlib/image.py
Copy file name to clipboardExpand all lines: lib/matplotlib/image.py
+13-2Lines changed: 13 additions & 2 deletions
diff --git a/‎lib/matplotlib/tests/test_image.py
Copy file name to clipboardExpand all lines: lib/matplotlib/tests/test_image.py
+10Lines changed: 10 additions & 0 deletions b/‎lib/matplotlib/tests/test_image.py
Copy file name to clipboardExpand all lines: lib/matplotlib/tests/test_image.py
+10Lines changed: 10 additions & 0 deletions
@@ -367,8 +367,19 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
                     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).astype(scaled_dtype)
-                a_max = np.ma.max(A).astype(scaled_dtype)
+                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.astype(scaled_dtype)
+                except AttributeError:
+                    a_min = 0
+                try:
+                    a_max = a_max.astype(scaled_dtype)
+                except AttributeError:
+                    a_min = 1
                 # 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
 
@@ -825,3 +825,13 @@ def test_imshow_float128():
 def test_imshow_bool():
     fig, ax = plt.subplots()
     ax.imshow(np.array([[True, False], [False, True]], dtype=bool))
+
+
+def test_full_invalid():
+    x = np.ones((10, 10))
+    x[:] = np.nan
+
+    f, ax = plt.subplots()
+    ax.imshow(x)
+
+    f.canvas.draw()