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#定义几种距离计算函数

#更高效的方式为把得分向量化之后使用scipy中定义的distance方法

from math import sqrt

def euclidean_dis(rating1, rating2): #欧式距离计算

“””计算2个打分序列间的欧式距离. 输入的rating1和rating2都是打分dict

格式为{‘小时代4’: 1.0, ‘疯狂动物城’: 5.0}”””

distance = 0

commonRatings = False

for key in rating1:

if key in rating2:

distance += (rating1[key] – rating2[key])^2

commonRatings = True

#两个打分序列之间有公共打分电影

if commonRatings:

return distance

#无公共打分电影

else:

return -1

def manhattan_dis(rating1, rating2): #曼哈顿距离计算

“””计算2个打分序列间的曼哈顿距离. 输入的rating1和rating2都是打分dict

格式为{‘小时代4’: 1.0, ‘疯狂动物城’: 5.0}”””

distance = 0

commonRatings = False

for key in rating1:

if key in rating2:

distance +=