utils_jensen_shannon.py 文件源码

def jensen_shannon_divergence(prob_dist1, prob_dist2, base=math.e):

    # Calculate "M" == (prob_dist1 + prob_dist2) / 2
    # m = []
    len_pd1 = len(prob_dist1)
    m = [0.5 * (prob_dist1[index] + prob_dist2[index]) for index in range(len_pd1)]
    # for index in range(0, len(prob_dist1)):
    #     m.append(0.5 * (prob_dist1[index] + prob_dist2[index]))
    #print 'M: {0}'.format(m)

    # Return Jensen-Shannon Divergence
    jsd = 0.5 * (kullback_leibler_divergence(prob_dist1, m, base) + kullback_leibler_divergence(prob_dist2, m, base))

    #print 'Jensen-Shannon Divergence: {0}'.format(jsd)

    return jsd