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"""
Code by Tae-Hwan Hung(@graykode)
https://en.wikipedia.org/wiki/Binomial_distribution
"""
import numpy as np
from matplotlib import pyplot as plt
import operator as op
from functools import reduce
def const(n, r):
r = min(r, n-r)
numer = reduce(op.mul, range(n, n-r, -1), 1)
denom = reduce(op.mul, range(1, r+1), 1)
return numer / denom
def binomial(n, p):
q = 1 - p
y = [const(n, k) * (p ** k) * (q ** (n-k)) for k in range(n)]
return y, np.mean(y), np.std(y)
for ls in [(0.5, 20), (0.7, 40), (0.5, 40)]:
p, n_experiment = ls[0], ls[1]
x = np.arange(n_experiment)
y, u, s = binomial(n_experiment, p)
plt.scatter(x, y, label=r'$\mu=%.2f,\ \sigma=%.2f$' % (u, s))
plt.legend()
plt.savefig('graph/binomial.png')
plt.show()
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