import numpy as np
import matplotlib.pyplot as plt
from pymc import Normal, deterministic, MCMC, Matplot
%matplotlib inline

mu = np.random.normal(0.0, 0.1, 100)
plt.hist(mu)

x_sample = np.random.normal(loc=1.0, scale=1.0, size=5)

mu = Normal('mu', 0, 1 / (0.1 ** 2))
x = Normal('x', mu=mu, tau=1/(1.0**2), value=x_sample, observed=True)

M = MCMC(input=[mu, x])
M.sample(iter=10000)

Matplot.plot(mu)

x_sample = np.random.normal(loc=1.0, scale=1.0, size=1000)
mu = Normal('mu', 0, 1 / (0.1 ** 2))
x = Normal('x', mu=mu, tau=1/(1.0**2), value=x_sample, observed=True)

M = MCMC(input=[mu, x])
M.sample(iter=10000)

Matplot.plot(mu)