Hi all,
In my latest post, I wanted to use the mpl.hist() function in a different way,
i.e.:
x = datalist
bins= 100
hist(x,bins,normed=0) #returns a tupple (n,bins,patches)
Instead of ploting the number of counts n, I wanted to plot the relative
percentage of counts, i.e. n/len(x). I can't really use the option normed=1
which returns n/(len(x)*dbin). In the axes.py module, this would simply mean
adding an argument e.g. relpercent = 1. I added the code line to show how this
could be done (in major cap). If this is useful, how could it be modified in
the distribution ?
def hist(self, x, bins=10, RELPERCENT = 1, normed=0, bottom=None,
align='edge', orientation='vertical', width=None,
log=False, **kwargs):
"""
if not self._hold: self.cla()
n, bins = npy.histogram(x, bins, range=None, normed=normed)
IF NOT NORMED AND RELPERCENT: N = N/FLOAT(LEN(X))
if width is None: width = 0.9*(bins[1]-bins[0])
if orientation == 'horizontal':
patches = self.barh(bins, n, height=width, left=bottom,
align=align, log=log)
elif orientation == 'vertical':
patches = self.bar(bins, n, width=width, bottom=bottom,
align=align, log=log)
else:
raise ValueError, 'invalid orientation: %s' % orientation
for p in patches:
p.update(kwargs)
return n, bins, cbook.silent_list('Patch', patches)
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