Use np.ma.masked_invalid to mask NaNs.

tonysyu · tonysyu · commit f4e8b58d62be · 2012-08-24T22:12:15.000-04:00
diff --git a/lib/matplotlib/axes.py b/lib/matplotlib/axes.py
@@ -6718,9 +6718,9 @@ def fill_between(self, x, y1, y2=0, where=None, interpolate=False,
         self._process_unit_info(ydata=y2)
 
         # Convert the arrays so we can work with them
-        x = np.asanyarray(self.convert_xunits(x))
-        y1 = np.asanyarray(self.convert_yunits(y1))
-        y2 = np.asanyarray(self.convert_yunits(y2))
+        x = ma.masked_invalid(self.convert_xunits(x))
+        y1 = ma.masked_invalid(self.convert_yunits(y1))
+        y2 = ma.masked_invalid(self.convert_yunits(y2))
 
         if y1.ndim == 0:
             y1 = np.ones_like(x)*y1
@@ -6735,8 +6735,7 @@ def fill_between(self, x, y1, y2=0, where=None, interpolate=False,
         if not (x.shape == y1.shape == y2.shape == where.shape):
             raise ValueError("Argument dimensions are incompatible")
 
-        mask = reduce(ma.mask_or, [f(a) for f in (ma.getmask, np.isnan)
-                                        for a in (x, y1, y2)])
+        mask = reduce(ma.mask_or, [ma.getmask(a) for a in (x, y1, y2)])
         if mask is not ma.nomask:
             where &= ~mask
 
@@ -6851,9 +6850,9 @@ def fill_betweenx(self, y, x1, x2=0, where=None, **kwargs):
         self._process_unit_info(xdata=x2)
 
         # Convert the arrays so we can work with them
-        y = np.asanyarray(self.convert_yunits(y))
-        x1 = np.asanyarray(self.convert_xunits(x1))
-        x2 = np.asanyarray(self.convert_xunits(x2))
+        y = ma.masked_invalid(self.convert_yunits(y))
+        x1 = ma.masked_invalid(self.convert_xunits(x1))
+        x2 = ma.masked_invalid(self.convert_xunits(x2))
 
         if x1.ndim == 0:
             x1 = np.ones_like(y)*x1
@@ -6868,8 +6867,7 @@ def fill_betweenx(self, y, x1, x2=0, where=None, **kwargs):
         if not (y.shape == x1.shape == x2.shape == where.shape):
             raise ValueError("Argument dimensions are incompatible")
 
-        mask = reduce(ma.mask_or, [f(a) for f in (ma.getmask, np.isnan)
-                                        for a in (y, x1, x2)])
+        mask = reduce(ma.mask_or, [ma.getmask(a) for a in (y, x1, x2)])
         if mask is not ma.nomask:
             where &= ~mask
 
