updated ngrams script so it can also use the nltk model
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1 changed files with 61 additions and 23 deletions
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@ -1,11 +1,12 @@
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#!/usr/bin/env python
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import sys
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import os
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import pickle
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libdir = os.path.join(os.path.dirname(os.path.realpath(__file__)), '../lib')
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sys.path.append(libdir)
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import jdecode
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import nltk_model as model
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def update_ngrams(lines, gramdict, grams):
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for line in lines:
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@ -35,34 +36,66 @@ def describe_bins(gramdict, bins):
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print (' ' + (str(bins[i]) if i < len(bins) else str(bins[-1]) + '+')
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+ ': ' + str(counts[i]))
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def main(fname, oname, gmin = 2, gmax = 8, verbose = True):
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gmin = int(gmin)
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gmax = int(gmax)
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bins = [1, 2, 3, 10, 30, 100, 300, 1000]
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if gmin < 2 or gmax < gmin:
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print 'invalid gram sizes: ' + str(gmin) + '-' + str(gmax)
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exit(1)
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def extract_language(cards, separate_lines = True):
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if separate_lines:
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lang = [line.vectorize() for card in cards for line in card.text_lines]
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else:
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lang = [card.text.vectorize() for card in cards]
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return map(lambda s: s.split(), lang)
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def build_ngram_model(cards, n, separate_lines = True, verbose = False):
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if verbose:
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print('generating ' + str(n) + '-gram model')
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lang = extract_language(cards, separate_lines=separate_lines)
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if verbose:
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print('found ' + str(len(lang)) + ' sentences')
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lm = model.NgramModel(n, lang)
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if verbose:
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print(lm)
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return lm
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def main(fname, oname, gmin = 2, gmax = 8, nltk = False, sep = False, verbose = False):
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# may need to set special arguments here
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cards = jdecode.mtg_open_file(fname, verbose=verbose)
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gmin = int(gmin)
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gmax = int(gmax)
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for grams in range(gmin, gmax+1):
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if nltk:
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n = gmin
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lm = build_ngram_model(cards, n, separate_lines=sep, verbose=verbose)
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if verbose:
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print 'generating ' + str(grams) + '-grams...'
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gramdict = {}
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for card in cards:
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update_ngrams(card.text_lines_words, gramdict, grams)
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oname_full = oname + '.' + str(grams) + 'g'
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teststr = 'when @ enters the battlefield'
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print('litmus test: perplexity of ' + repr(teststr))
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print(' ' + str(lm.perplexity(teststr.split())))
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if verbose:
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print ' writing ' + str(len(gramdict)) + ' unique ' + str(grams) + '-grams to ' + oname_full
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describe_bins(gramdict, bins)
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print('pickling module to ' + oname)
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with open(oname, 'wb') as f:
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pickle.dump(lm, f)
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with open(oname_full, 'wt') as f:
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for ngram in sorted(gramdict,
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lambda x,y: cmp(gramdict[x], gramdict[y]),
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reverse = True):
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f.write((ngram + ': ' + str(gramdict[ngram]) + '\n').encode('utf-8'))
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else:
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bins = [1, 2, 3, 10, 30, 100, 300, 1000]
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if gmin < 2 or gmax < gmin:
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print 'invalid gram sizes: ' + str(gmin) + '-' + str(gmax)
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exit(1)
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for grams in range(gmin, gmax+1):
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if verbose:
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print 'generating ' + str(grams) + '-grams...'
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gramdict = {}
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for card in cards:
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update_ngrams(card.text_lines_words, gramdict, grams)
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oname_full = oname + '.' + str(grams) + 'g'
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if verbose:
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print(' writing ' + str(len(gramdict)) + ' unique ' + str(grams)
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+ '-grams to ' + oname_full)
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describe_bins(gramdict, bins)
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with open(oname_full, 'wt') as f:
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for ngram in sorted(gramdict,
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lambda x,y: cmp(gramdict[x], gramdict[y]),
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reverse = True):
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f.write((ngram + ': ' + str(gramdict[ngram]) + '\n').encode('utf-8'))
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if __name__ == '__main__':
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@ -77,9 +110,14 @@ if __name__ == '__main__':
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help='minimum gram size to compute')
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parser.add_argument('-max', '--max', action='store', default='8',
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help='maximum gram size to compute')
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parser.add_argument('-nltk', '--nltk', action='store_true',
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help='use nltk model.NgramModel, with n = min')
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parser.add_argument('-s', '--separate', action='store_true',
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help='separate card text into lines when constructing nltk model')
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parser.add_argument('-v', '--verbose', action='store_true',
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help='verbose output')
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args = parser.parse_args()
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main(args.infile, args.outfile, gmin=args.min, gmax=args.max, verbose=args.verbose)
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main(args.infile, args.outfile, gmin=args.min, gmax=args.max, nltk=args.nltk,
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sep=args.separate, verbose=args.verbose)
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exit(0)
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