python - How to plot result of np.histogram with matplotlib analog to plt.hist -

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• histogram matplotlib 6 answers

i plot histograms this:

data = [-0.5, 0.5, 0.5, 0.5,      1.5, 2.1, 2.2, 2.3, 2.4, 2.5, 3.1, 3.2]  plt.hist(data, bins=5, range=[-1, 4], histtype='step') 

now, when have somehow large input data (larger memory), need fill histogram chunk chunk. e.g. this:

h, bins = np.histogram([], bins=5, range=[-1, 4]) data in a_lot_of_input_files:     h += np.histogram(data, bins=5, range=[-1, 4])[0] 

but question always, "how plot h again, looks previous matplotlib version.

the solution came with, looks this:

plt.plot(bins, np.insert(h, 0, h[0]), '-', drawstyle='steps') 

however, neither looks result identical, nor feel nice create copy of h plotting it.

is there elegant solution missing? (i did not yet try use plt.bar, because bar-graphs don't work nicely, when 1 wants compare histograms)

not sure mean "bar-graphs don't work nicely, when 1 wants compare histograms",

one way plt.bar:

import matplotlib.pyplot plt import numpy np  data = [-0.5, 0.5, 0.5, 0.5,      1.5, 2.1, 2.2, 2.3, 2.4, 2.5, 3.1, 3.2]  plt.hist(data, bins=5, range=[-1, 4], histtype='step',edgecolor='r',linewidth=3) h, bins = np.histogram(data[:6], bins=5, range=[-1, 4]) h+=np.histogram(data[6:], bins=5,range=[-1, 4])[0]  plt.bar(bins[:-1],h,width=1)  plt.show() 

an alternative plt.step:

import matplotlib.pyplot plt import numpy np  data = [-0.5, 0.5, 0.5, 0.5,      1.5, 2.1, 2.2, 2.3, 2.4, 2.5, 3.1, 3.2]  plt.hist(data, bins=5, range=[-1, 4], histtype='step',edgecolor='r') h, bins = np.histogram(data[:6], bins=5, range=[-1, 4]) h+=np.histogram(data[6:], bins=5,range=[-1, 4])[0]  bincentres = [(bins[i]+bins[i+1])/2. in range(len(bins)-1)] plt.step(bincentres,h,where='mid',color='b',linestyle='--')  plt.ylim(0,6)  plt.show() 

the edges don't quite extend way, might need add 0-bin either end if that's big problem you