相似性計算（euclidean, cosine, pearson）

#!/usr/bin/pythonfrom math import sqrtdef euclidean(v1, v2):    length = min(len(v1), len(v2))    if length == 0: return 0        d = 0    for i in range(length):        d += pow((v1[i] - v2[i]), 2)    #return sqrt(d)    return 1 / float(1+d)def cosine(v1, v2):    length = min(len(v1), len(v2))    if length == 0: return 0        dp = 0 #dot product    m1 = 0 #modulus of v1    m2 = 0 #modulus of v2    for i in range(length):        dp += v1[i] * v2[i]        m1 += v1[i] * v1[i]        m2 += v2[i] * v2[i]        if m1 == 0 or m2 == 0: return 0    distance = dp / (sqrt(m1) * sqrt(m2))    return distancedef pearson(v1, v2):    length = min(len(v1), len(v2))    if length == 0: return 0        #e of v1 v2    e1 = 0    e2 = 0    for i in range(length):        e1 += v1[i]        e2 += v2[i]    e1 /= float(length)    e2 /= float(length)        cov = 0 #cov of v1 v2    d1 = 0 #variance of v2    d2 = 0 #variance of v2    for i in range(length):        diff1 = v1[i] - e1        diff2 = v2[i] - e2        cov += diff1 * diff2        d1 += diff1 * diff1        d2 += diff2 * diff2    cov /= float(length)    d1 /= float(length)    d2 /= float(length)        if d1 == 0 or d2 == 0: return 0    return cov / sqrt(d1 * d2)