Normal Distribution via Box–Muller transform

pnorm.py

from random import random
from math import log, cos, sin, sqrt, pi

# Implementation of Box-Muller transform to
# generate two random numbers from N(mu, sigma) distribution
def pnorm(mu = 0, sigma = 1):
    r = sqrt(-2*log(random()))
    a = 2*pi*random()
    return sigma*r*cos(a) + mu, sigma*r*sin(a) + mu

import matplotlib.pyplot as plt

x = []
for _ in range(50000): x += pnorm(0,1)
plt.hist(x)
plt.show()