rates.py

用python实现的邮件过滤器

#!/usr/bin/env python

"""
rates.py basename ...

Assuming that file

    basename + '.txt'
or
    basename

contains output from one of the test drivers (timcv, mboxtest, timtest),
scans that file for summary statistics, displays them to stdout, and also
writes them to file

    basename + 's.txt'

(where the 's' means 'summary').  This doesn't need a full output file
from a test run, and will display stuff for as far as the output file
has gotten so far.

Two of these summary files can later be fed to cmp.py.
"""

import sys

"""
-> Training on Data/Ham/Set2-3 & Data/Spam/Set2-3 ... 8000 hams & 5500 spams
-> Predicting Data/Ham/Set1 & Data/Spam/Set1 ...
-> <stat> tested 4000 hams & 2750 spams against 8000 hams & 5500 spams
-> <stat> false positive %: 0.025
-> <stat> false negative %: 0.327272727273
-> <stat> 1 new false positives
"""

def doit(basename):
    if basename.endswith('.txt'):
        basename = basename[:-4]
    try:
        ifile = file(basename + '.txt')
    except IOError:
        ifile = file(basename)
    interesting = filter(lambda line: line.startswith('-> '), ifile)
    ifile.close()

    oname = basename + 's.txt'
    ofile = file(oname, 'w')
    print basename, '->', oname

    def dump(*stuff):
        msg = ' '.join(map(str, stuff))
        print msg
        print >> ofile, msg

    ntests = nfn = nfp = 0
    sumfnrate = sumfprate = 0.0

    for line in interesting:
        dump(line[:-1])
        fields = line.split()

        # 0      1      2    3    4 5    6                 -5  -4 -3   -2    -1
        #-> <stat> tested 4000 hams & 2750 spams against 8000 hams & 5500 spams
        if line.startswith('-> <stat> tested '):
            ntests += 1
            continue

        #  0      1     2        3
        # -> <stat> false positive %: 0.025
        # -> <stat> false negative %: 0.327272727273
        if line.startswith('-> <stat> false '):
            kind = fields[3]
            percent = float(fields[-1])
            if kind == 'positive':
                sumfprate += percent
                lastval = percent
            else:
                sumfnrate += percent
                dump('    %7.3f %7.3f' % (lastval, percent))
            continue

        #  0      1 2   3     4         5
        # -> <stat> 1 new false positives
        if len(fields) >= 5 and fields[3] == 'new' and fields[4] == 'false':
            kind = fields[-1]
            count = int(fields[2])
            if kind == 'positives':
                nfp += count
            else:
                nfn += count

    dump('total unique false pos', nfp)
    dump('total unique false neg', nfn)
    dump('average fp %', sumfprate / ntests)
    dump('average fn %', sumfnrate / ntests)

for name in sys.argv[1:]:
    doit(name)