import math

import numpy as np

import matplotlib.mlab as mlab

import matplotlib.pyplot as plt

mu=2

variance=1

sigma = math.sqrt(variance)

x = np.linspace(mu - 3*sigma, mu + 3*sigma, 100)

#y=mlab.normpdf(x, mu, sigma)

y=[1/(sigma*(math.sqrt(2*math.pi)))*math.exp(-(1/2)*(math.pow((item-mu)/sigma,2)) ) for item in x ]

plt.plot(x,y)

plt.show()