Revision: 6592
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=6592&view=rev
Author: mmetz_bn
Date: 2008-12-12 14:55:12 +0000 (Fri, 12 Dec 2008)
Log Message:
-----------
Added support for weights to axes.hist()
Modified Paths:
--------------
trunk/matplotlib/CHANGELOG
trunk/matplotlib/lib/matplotlib/axes.py
Modified: trunk/matplotlib/CHANGELOG
===================================================================
--- trunk/matplotlib/CHANGELOG 2008-12-12 14:47:38 UTC (rev 6591)
+++ trunk/matplotlib/CHANGELOG 2008-12-12 14:55:12 UTC (rev 6592)
@@ -1,3 +1,6 @@
+2008-12-12 Added support for the numpy.histogram() weights parameter
+ to the axes hist() method. Docs taken from numpy - MM
+
2008-12-12 Fixed warning in hist() with numpy 1.2 - MM
2008-12-12 Removed external packages: configobj and enthought.traits
Modified: trunk/matplotlib/lib/matplotlib/axes.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/axes.py 2008-12-12 14:47:38 UTC (rev
6591)
+++ trunk/matplotlib/lib/matplotlib/axes.py 2008-12-12 14:55:12 UTC (rev
6592)
@@ -6422,9 +6422,10 @@
#### Data analysis
- def hist(self, x, bins=10, range=None, normed=False, cumulative=False,
- bottom=None, histtype='bar', align='mid',
- orientation='vertical', rwidth=None, log=False, **kwargs):
+ def hist(self, x, bins=10, range=None, normed=False, weights=None,
+ cumulative=False, bottom=None, histtype='bar', align='mid',
+ orientation='vertical', rwidth=None, log=False,
+ **kwargs):
"""
call signature::
@@ -6468,6 +6469,13 @@
pdf, bins, patches = ax.hist(...)
print np.sum(pdf * np.diff(bins))
+ *weights*
+ An array of weights, of the same shape as *x*. Each value in
+ *x* only contributes its associated weight towards the bin
+ count (instead of 1). If *normed* is True, the weights are
+ normalized, so that the integral of the density over the range
+ remains 1.
+
*cumulative*:
If *True*, then a histogram is computed where each bin
gives the counts in that bin plus all bins for smaller values.
@@ -6543,7 +6551,7 @@
if not self._hold: self.cla()
# NOTE: the range keyword overwrites the built-in func range !!!
- # needs to be fixed in with numpy !!!
+ # needs to be fixed in numpy !!!
if kwargs.get('width') is not None:
raise DeprecationWarning(
@@ -6566,8 +6574,30 @@
tx.append( np.array(x[i]) )
x = tx
else:
- raise ValueError, 'Can not use providet data to create a
histogram'
+ raise ValueError, 'Can not use provided data to create a
histogram'
+ if weights is not None:
+ try:
+ w = np.transpose(np.array(weights))
+ if len(w.shape)==1:
+ w.shape = (1, w.shape[0])
+ except:
+ if iterable(weights[0]) and not is_string_like(weights[0]):
+ tw = []
+ for i in xrange(len(weights)):
+ tw.append( np.array(weights[i]) )
+ w = tw
+ else:
+ raise ValueError, 'Can not use provided weights to create
a hist'
+
+ if len(x) != len(w):
+ raise ValueError, 'weights should have the same shape as x'
+ for i in xrange(len(x)):
+ if len(x[i]) != len(w[i]):
+ raise ValueError, 'weights should have the same shape as x'
+ else:
+ w = [None]*len(x)
+
# Check whether bins or range are given explicitly. In that
# case do not autoscale axes.
binsgiven = (cbook.iterable(bins) or range != None)
@@ -6584,7 +6614,7 @@
for i in xrange(len(x)):
# this will automatically overwrite bins,
# so that each histogram uses the same bins
- m, bins = np.histogram(x[i], bins, **hist_kwargs)
+ m, bins = np.histogram(x[i], bins, weights=w[i], **hist_kwargs)
n.append(m)
if cumulative:
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