import numpy as np
import matplotlib.pyplot as plt
from plotstyle import *

# roll the die:
rng = np.random.RandomState(57281)
x1 = rng.randint(1, 7, 100)
x2 = rng.randint(1, 7, 500)
bins = np.arange(0.5, 7, 1.0)

fig, (ax1, ax2) = plt.subplots(1, 2)
fig.subplots_adjust(**adjust_fs(bottom=2.7, top=0.1))
ax1.set_xlim(0, 7)
ax1.set_xticks(range(1, 7))
ax1.set_xlabel('x')
ax1.set_ylim(0, 98)
ax1.set_ylabel('Frequency')
fs = dict(**fsC)
fs['color'] = [fsC['facecolor'], fsE['facecolor']]
del fs['facecolor']
ax1.hist([x2, x1], bins, **fs)

ax2.set_xlim(0, 7)
ax2.set_xticks(range(1, 7))
ax2.set_xlabel('x')
ax2.set_ylim(0, 0.23)
ax2.set_ylabel('Probability')
ax2.plot([0.2, 6.8], [1.0/6.0, 1.0/6.0], zorder=-10, **lsAm)
h1, b1 = np.histogram(x1, bins)
h2, b2 = np.histogram(x2, bins)
h1 = h1/np.sum(h1)
h2 = h2/np.sum(h2)
ax2.bar(b1[:-1]+0.3, h1, zorder=-5, width=0.4, **fsC)
ax2.bar(b2[:-1]+0.7, h2, zorder=-5, width=0.4, **fsE)
fig.subplots_adjust(left=0.125)
fig.savefig('diehistograms.pdf')