Question

好吧，伙计们。我的教授说，没有Python3中任何循环的帮助，有一种方法可以完成这个功能。我没有看到它。她建议使用zip，enumerate，readlines和split（＆＃34 ;;＆＃34;）（每次评论都会跟着＆＃39 ;;＆＃39;，如果连续两行则意味着评论家没有评论电影）。我正在做的是在电影中阅读，在movMat列表中查找比较电影。然后我将它们作为普通评论者进行比较。之后我必须得到Pearson计算，其中包括获得当前电影的常见评论者，目标电影的价值（比较电影），得到所述普通评论者值的平均值，标准偏差以及最后的Pearson R相关。

def pCalc (movMat, movNumber, n) 
    indexes1 = [i for i,x in enumerate(movMat[movNumber][1].split(';')) if x == '1' or x == '2' or x == '3' or x == '4' or x == '5' ]
    indexes2 = [i for i,x in enumerate(movMat[n][1].split(';')) if x == '1' or x == '2' or x == '3' or x == '4' or x == '5' ]

    compare = list(set(indexes1).intersection(indexes2))

    xi = []
    for index, val in enumerate(movMat[movNumber][1].split(';')):
        if index in compare:
             xi.append(int(val))

    average1 = sum(xi)/len(compare)
    stdDev1 = statistics.stdev(xi)

    yi = []
    for index, val in enumerate(movMat[n][1].split(';')):
        if index in compare:
             yi.append(int(val))

    average2 = sum(yi)/len(compare)
    stdDev2 = statistics.stdev(yi)

    r = 0
    newSum = 0

    for i in range(0, len(compare)):
        newSum += ((xi[i]-average1)/stdDev1) * ((yi[i]-average2)/stdDev2)

    r = (1/(len(compare)-1)) * newSum

示例输入是：

该程序的主要部分处理参数调用，文件中的行以及诸如命令行参数＆＃39; 1＆＃39;的输入的示例输出。会调出玩具故事并将其与数据库中的其他电影进行比较，如下所示：

Movie number: Movie  1|Toy Story (1995)

*** No. of rows (movies) in matrix =  1682
*** No. of columns (reviewers) = 943
Output shows r-value, movie no.|name, no. of ratings

compare movie is  1|Toy Story (1995)
no. of common reviewers 452
target avg   3.8783185840707963
compare avg  3.8783185840707963
target std   0.9278967014291252
compare std  0.9278967014291252
r            0.999999999999991

compare movie is  2|GoldenEye (1995)
no. of common reviewers 104
target avg   3.8653846153846154
compare avg  3.201923076923077
target std   0.9456871165874381
compare std  0.9177833965361495
r            0.22178411018797187

compare movie is  3|Four Rooms (1995)
no. of common reviewers 78
target avg   3.717948717948718
compare avg  2.9358974358974357
target std   0.9520645495064435
compare std  1.2096982943568881
r            0.1757942980351483

compare movie is  4|Get Shorty (1995)
no. of common reviewers 149
target avg   3.87248322147651
compare avg  3.530201342281879
target std   0.9247979370536794
compare std  0.9970025819307402
r            0.10313529410109303

什么是更多＆＃34; pythonic方式＆＃34;做皮尔逊计算

0 个答案: