BeyesianAvg.py

# -*- coding=utf-8 -*-
import collections
 
# Usage:
#   我的做法是把WordsDetector.py里的结果输出到文件，
#   然后把文件名放到下面的names列表中，运行本程序。
 
names = ['name0',
         'name1',
         'name2',
         'name3']
 
words = dict([(i, collections.Counter()) for i in names])
total_words = collections.Counter()
 
for name in names:
    f = open(name)
    for line in f:
        word, freq = line.split()
        words[name][word] += int(freq)
    total_words += words[name]
 
ps = dict([(i, collections.defaultdict(int)) for i in names])
 
for name in names:
    print name
    cnt = total = avg = 0.0 
    for word, freq in words[name].iteritems():
        cnt += 1
        total += total_words[word]
        avg += float(freq) / total_words[word]
    total /= cnt 
    avg /= cnt 
    avg_times_total = total * avg 
    for word, freq in words[name].iteritems():
        ps[name][word] = (float(freq) + avg_times_total) / (total_words[word] + total)
    word_list = list(set(words[name]))
    word_list.sort(cmp = lambda x, y: cmp(ps[name][y], ps[name][x]))
    cnt = 0 
    for word in word_list:
        print '* ', word, ps[name][word]
        cnt += 1
        if cnt >= 10: break