Axes.hist: fix bug in handling of weights kwarg; thanks to Jeff Klukas.

efiring · efiring · commit fcae31a73082 · 2010-05-17T19:03:58.000Z
Also use weights kwarg in examples/histogram_demo_extended.

svn path=/trunk/matplotlib/; revision=8317
diff --git a/examples/pylab_examples/histogram_demo_extended.py b/examples/pylab_examples/histogram_demo_extended.py
@@ -1,4 +1,5 @@
 #!/usr/bin/env python
+import numpy as np
 import pylab as P
 
 #
@@ -90,8 +91,20 @@
 x1 = mu + sigma*P.randn(7000)
 x2 = mu + sigma*P.randn(3000)
 
+# and exercise the weights option by arbitrarily giving the first half
+# of each series only half the weight of the others:
+
+w0 = np.ones_like(x0)
+w0[:len(x0)/2] = 0.5
+w1 = np.ones_like(x1)
+w1[:len(x1)/2] = 0.5
+w2 = np.ones_like(x2)
+w0[:len(x2)/2] = 0.5
+
+
+
 P.figure()
 
-n, bins, patches = P.hist( [x0,x1,x2], 10, histtype='bar')
+n, bins, patches = P.hist( [x0,x1,x2], 10, weights=[w0, w1, w2], histtype='bar')
 
 P.show()
diff --git a/lib/matplotlib/axes.py b/lib/matplotlib/axes.py
@@ -7364,7 +7364,7 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
                 raise ValueError("color kwarg must have one color per dataset")
 
         if weights is not None:
-            if isinstance(w, np.ndarray):
+            if isinstance(weights, np.ndarray):
                 w = np.array(weights)
                 if w.ndim == 2:
                     w = w.T
