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# Source Code for Module translate.lang.ngram

      1  #!/usr/bin/env python
      2  # -*- coding: utf-8 -*-
      3  #
      4  # Copyright (c) 2006 Thomas Mangin
      5  # Copyright (c) 2009 Zuza Software Foundation
      6  #
      7  # This program is distributed under Gnu General Public License
      8  # (cf. the file COPYING in distribution). Alternatively, you can use
      9  # the program under the conditions of the Artistic License (as Perl).
     10  #
     11  # This program is free software; you can redistribute it and/or modify
     12  # it under the terms of the GNU General Public License as published by
     13  # the Free Software Foundation; either version 2 of the License, or
     14  # (at your option) any later version.
     15  #
     16  # This program is distributed in the hope that it will be useful,
     17  # but WITHOUT ANY WARRANTY; without even the implied warranty of
     18  # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
     19  # GNU General Public License for more details.
     20  #
     21  # You should have received a copy of the GNU General Public License
     22  # along with this program; if not, write to the Free Software
     23  # Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
     24  #
     25  # Orignal file from http://thomas.mangin.me.uk/data/source/ngram.py
     26
     27  import re
     28
     29  nb_ngrams = 400
     30
     31 -class _NGram:
     32 -    def __init__(self, arg={}):
     33          if isinstance(arg, basestring):
     34              self.addText(arg)
     35              self.normalise()
     36          elif isinstance(arg, dict):
     37              self.ngrams = arg
     38              self.normalise()
     39          else:
     40              self.ngrams = dict()
     41
     42 -    def addText(self, text):
     43          if isinstance(text, str):
     44              text = text.decode('utf-8')
     45
     46          ngrams = dict()
     47
     48          text = text.replace('\n', ' ')
     49          text = re.sub('\s+', ' ', text)
     50          words = text.split(' ')
     51
     52          for word in words:
     53              word = '_'+word+'_'
     54              size = len(word)
     55              for i in xrange(size):
     56                  for s in (1, 2, 3, 4):
     57                      sub = word[i:i+s]
     58                      if not ngrams.has_key(sub):
     59                          ngrams[sub] = 0
     60                      ngrams[sub] += 1
     61
     62                      if i+s >= size:
     63                          break
     64          self.ngrams = ngrams
     65          return self
     66
     67 -    def sorted(self):
     68          sorted = [(self.ngrams[k], k) for k in self.ngrams.keys()]
     69          sorted.sort()
     70          sorted.reverse()
     71          sorted = sorted[:nb_ngrams]
     72          return sorted
     73
     74 -    def normalise(self):
     75          count = 0
     76          ngrams = {}
     77          for v, k in self.sorted():
     78              ngrams[k] = count
     79              count += 1
     80
     81          self.ngrams = ngrams
     82          return self
     83
     84 -    def addValues(self, key, value):
     85          self.ngrams[key] = value
     86          return self
     87
     88 -    def compare(self, ngram):
     89          d = 0
     90          ngrams = ngram.ngrams
     91          for k in self.ngrams.keys():
     92              if ngrams.has_key(k):
     93                  d += abs(ngrams[k] - self.ngrams[k])
     94              else:
     95                  d += nb_ngrams
     96          return d
     97
     98
     99  import os
    100  import glob
    101
    102 -class NGram:
    103 -    def __init__(self, folder, ext='.lm'):
    104          self.ngrams = dict()
    105          folder = os.path.join(folder, '*'+ext)
    106          size = len(ext)
    107          count = 0
    108
    109          for fname in glob.glob(os.path.normcase(folder)):
    110              count += 1
    111              lang = os.path.split(fname)[-1][:-size]
    112              ngrams = {}
    113              lines = open(fname, 'r').readlines()
    114
    115              try:
    116                  i = len(lines)
    117                  for line in lines:
    118                      line = line.decode('utf-8')
    119                      parts = line[:-1].split()
    120                      if len(parts) != 2:
    121                          try:
    122                              ngrams[parts[0]] = i
    123                          except IndexError:
    124                              pass # Line probably only contained spaces, if anything
    125                      else:
    126                          ngrams[parts[0]] = int(parts[1])
    127                      i -= 1
    128              except UnicodeDecodeError, e:
    129                  continue
    130
    131              if ngrams:
    132                  self.ngrams[lang] = _NGram(ngrams)
    133
    134          if not count:
    135              raise ValueError("no language files found")
    136
    137 -    def classify(self, text):
    138          ngram = _NGram(text)
    139          r = 'guess'
    140
    141          langs = self.ngrams.keys()
    142          r = langs.pop()
    143          min = self.ngrams[r].compare(ngram)
    144
    145          for lang in langs:
    146              d = self.ngrams[lang].compare(ngram)
    147              if d < min:
    148                  min = d
    149                  r = lang
    150
    151          if min > 0.8 * (nb_ngrams**2):
    152              r = ''
    153          return r
    154
    155 -class Generate:
    156 -    def __init__(self, folder, ext='.txt'):
    157          self.ngrams = dict()
    158          folder = os.path.join(folder, '*'+ext)
    159          size = len(ext)
    160
    161          for fname in glob.glob(os.path.normcase(folder)):
    162              lang = os.path.split(fname)[-1][:-size]
    163              n = _NGram()
    164
    165              file = open(fname,'r')
    166              for line in file.readlines():
    167                  n.addText(line)
    168              file.close()
    169
    170              n.normalise()
    171              self.ngrams[lang] = n
    172
    173 -    def save(self, folder, ext='.lm'):
    174          for lang in self.ngrams.keys():
    175              fname = os.path.join(folder, lang+ext)
    176              file = open(fname, 'w')
    177              for v, k in self.ngrams[lang].sorted():
    178                  file.write("%s\t %d\n" % (k, v))
    179              file.close()
    180
    181  if __name__ == '__main__':
    182      import sys
    183
    184      # Should you want to generate your own .lm files
    185      #conf = Generate('/tmp')
    186      #conf.save('/tmp')
    187
    188      text = sys.stdin.readline()
    189      from translate.misc.file_discovery import get_abs_data_filename
    190      l = NGram(get_abs_data_filename('langmodels'))
    191      print l.classify(text)
    192