In [3]:

    

%pylab inline
from numpy import *
from pylab import *


    

    




Populating the interactive namespace from numpy and matplotlib

In [8]:

    

xdata = range(0, 1000, 1)


    

In [12]:

    

figure()
hist(xdata)
show()


    

In [14]:

    

# Events are the number of occurrences in each bin
events


    

    
Out[14]:





array([ 100.,  100.,  100.,  100.,  100.,  100.,  100.,  100.,  100.,  100.])

In [15]:

    

#edges are the bounds of each bin. This is what you want to set for your log data.
edges


    

    
Out[15]:





array([   0. ,   99.9,  199.8,  299.7,  399.6,  499.5,  599.4,  699.3,
        799.2,  899.1,  999. ])

In [16]:

    

patches


    

    
Out[16]:





<a list of 10 Patch objects>

In [76]:

    

bins = []
for b in xrange(2, 35):
    if 2**b < 10000:
        bins.append(2**b)


    

In [77]:

    

hist(xdata, bins)
gca().set_xscale("log")


    

In [ ]: