Revision: 8607
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8607&view=rev
Author: jdh2358
Date: 2010-07-31 18:20:30 +0000 (Sat, 31 Jul 2010)
Log Message:
-----------
use asarray in hist
Modified Paths:
--------------
trunk/matplotlib/examples/pylab_examples/agg_buffer_to_array.py
trunk/matplotlib/lib/matplotlib/axes.py
Modified: trunk/matplotlib/examples/pylab_examples/agg_buffer_to_array.py
===================================================================
--- trunk/matplotlib/examples/pylab_examples/agg_buffer_to_array.py
2010-07-31 09:18:25 UTC (rev 8606)
+++ trunk/matplotlib/examples/pylab_examples/agg_buffer_to_array.py
2010-07-31 18:20:30 UTC (rev 8607)
@@ -1,5 +1,5 @@
import matplotlib
-matplotlib.use('Agg')
+#matplotlib.use('Agg')
from pylab import figure, show
import numpy as np
Modified: trunk/matplotlib/lib/matplotlib/axes.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/axes.py 2010-07-31 09:18:25 UTC (rev
8606)
+++ trunk/matplotlib/lib/matplotlib/axes.py 2010-07-31 18:20:30 UTC (rev
8607)
@@ -7401,11 +7401,13 @@
**kwargs):
"""
call signature::
+
+ def hist(x, bins=10, range=None, normed=False, weights=None,
+ cumulative=False, bottom=None, histtype='bar', align='mid',
+ orientation='vertical', rwidth=None, log=False,
+ color=None, label=None,
+ **kwargs):
- hist(x, bins=10, range=None, normed=False, cumulative=False,
- bottom=None, histtype='bar', align='mid',
- orientation='vertical', rwidth=None, log=False, **kwargs)
-
Compute and draw the histogram of *x*. The return value is a
tuple (*n*, *bins*, *patches*) or ([*n0*, *n1*, ...], *bins*,
[*patches0*, *patches1*,...]) if the input contains multiple
@@ -7567,7 +7569,7 @@
'this looks transposed (shape is %d x %d)' % x.shape[::-1])
else:
# multiple hist with data of different length
- x = [np.array(xi) for xi in x]
+ x = [np.asarray(xi) for xi in x]
nx = len(x) # number of datasets
@@ -7582,7 +7584,7 @@
# We need to do to 'weights' what was done to 'x'
if weights is not None:
if isinstance(weights, np.ndarray) or not iterable(weights[0]) :
- w = np.array(weights)
+ w = np.asarray(weights)
if w.ndim == 2:
w = w.T
elif w.ndim == 1:
@@ -7590,7 +7592,7 @@
else:
raise ValueError("weights must be 1D or 2D")
else:
- w = [np.array(wi) for wi in weights]
+ w = [np.asarray(wi) for wi in weights]
if len(w) != nx:
raise ValueError('weights should have the same shape as x')
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