Revision: 5148
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5148&view=rev
Author: mmetz_bn
Date: 2008-05-16 10:06:53 -0700 (Fri, 16 May 2008)
Log Message:
-----------
do not rely on equalwidth bin assumption for cumhist; trapz doesn't work
correctly with new histogram semantic
Modified Paths:
--------------
trunk/matplotlib/lib/matplotlib/axes.py
Modified: trunk/matplotlib/lib/matplotlib/axes.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/axes.py 2008-05-16 14:52:15 UTC (rev
5147)
+++ trunk/matplotlib/lib/matplotlib/axes.py 2008-05-16 17:06:53 UTC (rev
5148)
@@ -5420,9 +5420,9 @@
bottom=None, histtype='bar', align='edge',
orientation='vertical', width=None, log=False, **kwargs):
"""
- HIST(x, bins=10, normed=False, bottom=None, histtype='bar',
- align='edge', orientation='vertical', width=None,
- log=False, **kwargs)
+ HIST(x, bins=10, normed=False, cumulative=False,
+ bottom=None, histtype='bar', align='edge',
+ orientation='vertical', width=None, log=False, **kwargs)
Compute the histogram of x. bins is either an integer number of
bins or a sequence giving the bins. x are the data to be binned.
@@ -5437,13 +5437,13 @@
# trapezoidal integration of the probability density function
pdf, bins, patches = ax.hist(...)
- print np.trapz(pdf, bins)
+ print np.sum(pdf * np.diff(bins))
- If cumulative is True then histogram is computed where each bin
+ If cumulative is True then a histogram is computed where each bin
gives the counts in that bin plus all bins for smaller values.
The last bins gives the total number of datapoints. If normed is
also True then the histogram is normalized such that the last bin
- equals one (assuming equally spaced bins).
+ equals one.
histtype = 'bar' | 'step'. The type of histogram to draw.
'bar' is a traditional bar-type histogram, 'step' generates
@@ -5469,10 +5469,10 @@
normed=bool(normed), new=True)
if cumulative:
- n = n.cumsum()
if normed:
- # normalize to 1
- n *= (bins[1]-bins[0])
+ n = (n * np.diff(bins)).cumsum()
+ else:
+ n = n.cumsum()
if histtype == 'bar':
if width is None:
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