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scientificComputing/statistics/lecture/diehistograms.py

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Python

import numpy as np
import matplotlib.pyplot as plt
# roll the die:
x1 = np.random.random_integers( 1, 6, 100 )
x2 = np.random.random_integers( 1, 6, 500 )
bins = np.arange(0.5, 7, 1.0)
plt.xkcd()
fig = plt.figure( figsize=(6,4) )
ax = fig.add_subplot( 1, 2, 1 )
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
ax.set_xlabel( 'x' )
ax.set_ylabel( 'Frequency' )
ax.hist([x2, x1], bins, color=['#FFCC00', '#FFFF66' ])
ax = fig.add_subplot( 1, 2, 2 )
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
ax.set_xlabel( 'x' )
ax.set_ylabel( 'Probability' )
ax.hist([x2, x1], bins, normed=True, color=['#FFCC00', '#FFFF66' ])
plt.tight_layout()
fig.savefig( 'diehistograms.pdf' )
#plt.show()