Remove invalid data before plotting histograms.

TrishGillett · TrishGillett · commit a537aaaf9502 · 2016-09-18T07:10:34.000-04:00
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
@@ -6142,6 +6142,16 @@ def _normalize_input(inp, ename='input'):
         if len(w) != nx:
             raise ValueError('weights should have the same shape as x')
 
+        # Masking invalid data:
+        # Where an element of x[i] is invalid (NaN or inf), it and the
+        # corresponding element of weights[i] (if weights used) will be masked.
+        for i in range(len(x)):
+            xi_mask = np.ma.masked_invalid(x[i]).mask
+            x[i] = np.ma.masked_array(x[i], mask=xi_mask).compressed()
+            if weights[i]:
+                weights[i] = np.ma.masked_array(
+                    weights[i], mask=xi_mask).compressed()
+
         for xi, wi in zip(x, w):
             if wi is not None and len(wi) != len(xi):
                 raise ValueError(
