zozo/recontest

calculate_score.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-

import sys

# File format : GROUPID,GOODSID,VIEWRATE,BUYRATE
# Usage : calculate_score.py target.csv predict.csv

def read_submit_file(submit_file):
    viewrate = {}
    buyrate = {}
    with open(submit_file) as f:
        for line in f:
            if line != "GROUPID,GOODSID,VIEWRATE,BUYRATE":
                l = line.rstrip().split(",")
                if l[0] in viewrate.keys():
                    viewrate[l[0]][l[1]] = l[2]
                else:
                    viewrate[l[0]] = {l[1]:l[2]}

                if l[0] in buyrate.keys():
                    buyrate[l[0]][l[1]] = l[3]
                else:
                    buyrate[l[0]] = {l[1]:l[3]}

    return viewrate,buyrate

def calculate_group_error(y,x):
    s = {}
    for g in map(str,range(1,96)):
        group_score = 0.0
        for k,v in y[g].items():
            if k in x[g].keys():
                group_score += abs(float(v) - float(x[g][k]))
            else:
                group_score += 1.0
        s[g] = group_score
    return s


if __name__ == "__main__":
    y_view, y_buy = read_submit_file(sys.argv[1])
    x_view, x_buy = read_submit_file(sys.argv[2])

    view_error_dict = calculate_group_error(y_view, x_view)
    buy_error_dict = calculate_group_error(y_buy, x_buy)

    score = sum(view_error_dict.values()) + sum(buy_error_dict.values())

    print "view error:  " + str(sum(view_error_dict.values()))
    print "buy error:   " + str(sum(buy_error_dict.values()))
    print "total score: " + str(score)