gistfile1.txt

import scipy.sparse as sp
import numpy as np

def random_walk_transition_probability(n, p):
    keys = p.keys()
    m = 2*max(max(keys),abs(min(keys)))*n+1 # max(max(keys),abs(min(keys))) finds the largest step in the probability array
    A  = sp.csr_matrix((m, m))
    for key in keys:
        A += sp.diags(p[key]*np.ones(m-abs(key)), key)
    x = np.zeros((m,1))
    x[n] = 1.0
    for i in xrange(n):
        x = A.dot(x)
    return x