#!/usr/bin/env python import pylab as P # # The hist() function now has a lot more options # # # first create a single histogram # mu, sigma = 200, 25 x = mu + sigma*P.randn(10000) # the histogram of the data with histtype='step' n, bins, patches = P.hist(x, 50, normed=1, histtype='stepfilled') P.setp(patches, 'facecolor', 'g', 'alpha', 0.75) # add a line showing the expected distribution y = P.normpdf( bins, mu, sigma) l = P.plot(bins, y, 'k--', linewidth=1.5) # # create a histogram by providing the bin edges (unequally spaced) # P.figure() bins = [100,125,150,160,170,180,190,200,210,220,230,240,250,275,300] # the histogram of the data with histtype='step' n, bins, patches = P.hist(x, bins, normed=1, histtype='bar', rwidth=0.8) # # now we create a cumulative histogram of the data # P.figure() n, bins, patches = P.hist(x, 50, normed=1, histtype='step', cumulative=True) # add a line showing the expected distribution y = P.normpdf( bins, mu, sigma).cumsum() y /= y[-1] l = P.plot(bins, y, 'k--', linewidth=1.5) # create a second data-set with a smaller standard deviation sigma2 = 15. x = mu + sigma2*P.randn(10000) n, bins, patches = P.hist(x, bins=bins, normed=1, histtype='step', cumulative=True) # add a line showing the expected distribution y = P.normpdf( bins, mu, sigma2).cumsum() y /= y[-1] l = P.plot(bins, y, 'r--', linewidth=1.5) # finally overplot a reverted cumulative histogram n, bins, patches = P.hist(x, bins=bins, normed=1, histtype='step', cumulative=-1) P.grid(True) P.ylim(0, 1.05) # # histogram has the ability to plot multiple data in parallel ... # P.figure() # create a new data-set x = mu + sigma*P.randn(1000,3) n, bins, patches = P.hist(x, 10, normed=1, histtype='bar') # # ... or we can stack the data # P.figure() n, bins, patches = P.hist(x, 10, normed=1, histtype='barstacked') # # finally: make a multiple-histogram of data-sets with different length # x0 = mu + sigma*P.randn(10000) x1 = mu + sigma*P.randn(7000) x2 = mu + sigma*P.randn(3000) P.figure() n, bins, patches = P.hist( [x0,x1,x2], 10, histtype='bar') P.show()