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POAny way to create histogram with matplotlib.pyplot without plotting the histogram?
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copied!<p>I am using matplotlib.pyplot to create histograms. I'm not actually interested in the plots of these histograms, but interested in the frequencies and bins (I know I can write my own code to do this, but would prefer to use this package).</p> <p>I know I can do the following,</p> <pre><code>import numpy as np import matplotlib.pyplot as plt x1 = np.random.normal(1.5,1.0) x2 = np.random.normal(0,1.0) freq, bins, patches = plt.hist([x1,x1],50,histtype='step') </code></pre> <p>to create a histogram. All I need is <code>freq[0]</code>, <code>freq[1]</code>, and <code>bins[0]</code>. The problem occurs when I try and use,</p> <pre><code>freq, bins, patches = plt.hist([x1,x1],50,histtype='step') </code></pre> <p>in a function. For example,</p> <pre><code>def func(x, y, Nbins): freq, bins, patches = plt.hist([x,y],Nbins,histtype='step') # create histogram bincenters = 0.5*(bins[1:] + bins[:-1]) # center bins xf= [float(i) for i in freq[0]] # convert integers to float xf = [float(i) for i in freq[1]] p = [ (bincenters[j], (1.0 / (xf[j] + yf[j] )) for j in range(Nbins) if (xf[j] + yf[j]) != 0] Xt = [j for i,j in p] # separate pairs formed in p Yt = [i for i,j in p] Y = np.array(Yt) # convert to arrays for later fitting X = np.array(Xt) return X, Y # return arrays X and Y </code></pre> <p>When I call <code>func(x1,x2,Nbins)</code> and plot or print <code>X</code> and <code>Y</code>, I do not get my expected curve/values. I suspect it something to do with <code>plt.hist</code>, since there is a partial histogram in my plot.</p>

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