Code to compute coefficient of determination

Coefficient of Determination

from itertools import imap
import operator
import logicFuncs as lf

def mean_squared_error(r1, p1):
    #assert len(r1) == len(p1)
    return sum([(float(p1[i])-float(r1[i]))**2 for i in range(len(r1))])/float(len(r1))

def hammingDist(str1, str2):
    assert len(str1) == len(str2)
    return sum(imap(operator.ne, str1, str2))

def calculateCoD(y, fx):
    """ 
        Calculate Coefficient of Determination (CoD)
        for X as predictor of Y
        NOTE -> X and Y are required to be discretized
        Steps:
          1. eopt = 0.5
          2. Get mean squared error (eopt) between X and Y
          3. Calculate CoD as:
               CoD = (e0 - eopt)/e0
    """
    return (0.5 - mean_squared_error(y, fx))/0.5

def main():
    # Response variables to comapre
    import itertools
    sixers = list(itertools.product([0, 1], repeat=6))

    # Tests
    y = [1,0,1,0,1,0]
    print y
    for x in sixers:
        tmp1 = calculateCoD(y,x)
        tmp3 = calculateCoD(y,lf.notFunc(x))
        print x, tmp1, tmp3, hammingDist(y,x), hammingDist(y,lf.notFunc(x))

if __name__ == '__main__':
    main()