# -*- coding: utf-8 -*-
# scistattest1.py

from scipy.stats import norm
import matplotlib.pyplot as plt
import numpy as np
import statistics

rx = norm.rvs(size=100)

ave = statistics.mean(rx); stdev = statistics.stdev(rx)
print(ave, stdev)

pp = [0.9, 0.95, 0.975, 0.99, 0.995]
print(norm.ppf(pp))


fig, (ax1, ax2) = plt.subplots(1, 2)
fig.suptitle('pdf, cdf of normal with data')
x = np.linspace(-3, 3, 100)
rx.sort()

ax1.plot(x, norm.pdf(x, loc=ave, scale=stdev), 'r-', lw=2, alpha=0.6, label='norm pdf')
ax1.plot(x, norm().pdf(x), 'k-', lw=2, label='pdf from data')
ax1.hist(rx, density=True, histtype='stepfilled', alpha=0.2)
ax1.legend(loc='best', frameon=False)

ax2.plot(x, norm.cdf(x, loc=ave, scale=stdev), 'r-', lw=2, alpha=0.6, label='norm cdf')
ax2.plot(x, norm().cdf(x), 'k-', lw=2, label='cdf from data')
ax2.hist(rx, density=True, histtype='stepfilled', alpha=0.2, cumulative=True, 
         color='blue', edgecolor='red')
ax2.legend(loc='best', frameon=True)
plt.show()