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Diffstat (limited to 'silpa/modules/ngram/sample_ngram.py')
| -rw-r--r-- | silpa/modules/ngram/sample_ngram.py | 64 |
1 files changed, 64 insertions, 0 deletions
diff --git a/silpa/modules/ngram/sample_ngram.py b/silpa/modules/ngram/sample_ngram.py new file mode 100644 index 0000000..0f46ad6 --- /dev/null +++ b/silpa/modules/ngram/sample_ngram.py @@ -0,0 +1,64 @@ +#! /usr/bin/env python +# -*- coding: utf-8 -*- +# Ngram +# Copyright 2009 Jinesh K J <jinesh.k@gmail.com> +# Copyright 2009 Swathantra Malayalam Computing <smc-discuss@googlegroups.com> +# http://www.smc.org.in +# +# This program is free software; you can redistribute it and/or modify +# it under the terms of the GNU General Public License as published by +# the Free Software Foundation; either version 3 of the License, or +# (at your option) any later version. +# +# This program is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +# GNU Library General Public License for more details. +# +# You should have received a copy of the GNU General Public License +# along with this program; if not, write to the Free Software +# Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. +# +# If you find any bugs or have any suggestions email: jinesh.k@gmail.com or smc-discuss@googlegroups.com +# URL: http://www.smc.org.in +import pydot +import codecs +import pickle +import sys +from visualizer import NGramVisualizer +def genCorpus(infile,corpus): + ngv=NGramVisualizer () + try: + corpusfile = open(corpus) + except IOError: + graph_dict = dict() + else: + graph_dict = pickle.load(corpusfile) +# corpusfile.close() + graph_dict=ngv.loadCorpus (infile,graph_dict) + pickle.dump(graph_dict,open(corpus,'w')) +def printGraph(corpus,start_word): + ngv=NGramVisualizer () + graph_dict=pickle.load(open(corpus)) + graph=pydot.Dot() + uni_start_word = start_word.decode("utf-8") +# print start_word +# print uni_start_word + graph=ngv.generate_graph(graph_dict, graph,uni_start_word) + print graph.to_string().encode("utf-8") + +if __name__ == "__main__": + """ + python sample_ngram.py <input file> <corpus path> 1 + this will generate the corpus for the given input file, if corpus specified at + corpus path is empty. Else it will recreate the corpus for the with the additional files. + + python sample_ngram.py <corpus path> <start word> 2 + this will generate the graph for the given start word in the given corpus at corpus path. + + This is just a crude attempt, a lot more improvement is to be done. + """ + if sys.argv[3] == "1": + genCorpus(sys.argv[1],sys.argv[2]) + elif sys.argv[3] == "2": + printGraph(sys.argv[1],sys.argv[2]) |