Avoid some uses of np.isscalar.

anntzer · anntzer · commit 919939253e2b · 2018-09-09T01:47:11.000+02:00
The numpy docs suggest that checking ndim &gt; 0 is usually better.  In the
cases here, though, we can just broadcast directly.
diff --git a/examples/lines_bars_and_markers/filled_step.py b/examples/lines_bars_and_markers/filled_step.py
@@ -61,9 +61,8 @@ def filled_hist(ax, edges, values, bottoms=None, orientation='v',
                              lb=len(edges), lv=len(values)))
 
     if bottoms is None:
-        bottoms = np.zeros_like(values)
-    if np.isscalar(bottoms):
-        bottoms = np.ones_like(values) * bottoms
+        bottoms = 0
+    bottoms = np.broadcast_to(bottoms, values.shape)
 
     values = np.r_[values, values[-1]]
     bottoms = np.r_[bottoms, bottoms[-1]]
diff --git a/lib/matplotlib/streamplot.py b/lib/matplotlib/streamplot.py
@@ -356,15 +356,12 @@ class StreamMask(object):
     """
 
     def __init__(self, density):
-        if np.isscalar(density):
-            if density <= 0:
-                raise ValueError("If a scalar, 'density' must be positive")
-            self.nx = self.ny = int(30 * density)
-        else:
-            if len(density) != 2:
-                raise ValueError("'density' can have at maximum 2 dimensions")
-            self.nx = int(30 * density[0])
-            self.ny = int(30 * density[1])
+        try:
+            self.nx, self.ny = (30 * np.broadcast_to(density, 2)).astype(int)
+        except ValueError:
+            raise ValueError("'density' must be a scalar or be of length 2")
+        if self.nx < 0 or self.ny < 0:
+            raise ValueError("'density' must be positive")
         self._mask = np.zeros((self.ny, self.nx))
         self.shape = self._mask.shape
 
