Test mutual information

test_mutual_information.py

from scipy import asarray
from random import gauss, randint

def test():
    x= asarray([gauss(0,1) for i in range(1000)])
    y1= asarray([int(e>0) for e in x])
    y2= asarray([randint(0,1) for e in x])

    hx, bx= histogram(x, bins=x.size/10, density=True)
    dx= digitize(x,bx)
    
    print "X ~ N(0,1)"
    print "y1 = 1 <=> x > 0"
    print "y2 = 1 con probabilidad 0.5"
    print
    print "I(y1;x) = H(X) - H(X|Y1) = %.02f" % (mutual_information(x,y1))
    print "I(y1;x) = H(Y1) - H(Y1|X) = %.02f" % (mutual_information(y1,dx))
    print
    print "I(y2;x) = H(X) - H(X|Y2) = %.02f" % (mutual_information(x,y2))
    print "I(y2;x) = H(Y2) - H(Y2|X) = %.02f" % (mutual_information(y2,dx))