diff g_collocation.py @ 0:e991d4e60c17 draft

planemo upload commit 0203cb3a0b40d9348674b2b098af805e2986abca-dirty

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/g_collocation.py	Wed Oct 12 22:17:53 2016 -0400
@@ -0,0 +1,48 @@
+import sys
+import os
+import nltk
+from nltk.collocations import *
+import argparse
+
+def Parser():
+    the_parser = argparse.ArgumentParser(description="Parse the sentence using Chart Parser and a supplied grammar")
+    the_parser.add_argument('--input', required=True, action="store", type=str, help="input text file")
+    the_parser.add_argument('--output', required=True, action="store", type=str, help="output file path")
+    the_parser.add_argument('--freq_filter', required=True, action="store", type=str, help="The minimum number of required occurrences in the corpus")
+    the_parser.add_argument('--results', required=True, action="store", type=str, help="The maximum number of collocations to show in the results")
+    the_parser.add_argument('--coll_type', required=True, action="store", type=str, help="Type of collocations to find")
+    the_parser.add_argument('--pos', required=True, action="store", type=str, help="Data input is a set of POS tags")
+
+    args = the_parser.parse_args()
+    return args
+
+def collocation(inp, outp, freq_filter, results, coll_type, pos):
+    pos = bool(pos == 'true')
+    i = str(unicode(open(inp, 'r').read(), errors='ignore'))
+    o = open(outp, 'w')
+    all_words = []
+    if pos:
+        text = i.split(' ')[:-1]
+        all_words = [x[0:x.index('/')] if x != '\n' else x for x in text]
+        all_words = [x.strip(' ').strip('\n') for x in all_words]
+    else:
+        sents = nltk.sent_tokenize(i)
+        for sent in sents:
+            all_words += nltk.word_tokenize(sent)
+    if coll_type == 'bigram':
+        measures = nltk.collocations.BigramAssocMeasures()
+        finder = BigramCollocationFinder.from_words(all_words)
+    else:
+        measures = nltk.collocations.TrigramAssocMeasures()
+        finder = TrigramCollocationFinder.from_words(all_words)
+    finder.apply_freq_filter(int(freq_filter))
+    colls = finder.nbest(measures.pmi, int(results))
+    for coll in colls:
+        o.write("%s\t%s" % coll)
+        o.write('\n')
+    o.close()
+
+if __name__ == '__main__':
+    args = Parser()
+
+    collocation(args.input, args.output, args.freq_filter, args.results, args.coll_type, args.pos)