Carlos-Francisco Méndez-Cruz

LSA soft clustering

......@@ -105,12 +105,12 @@ for pertenence, sentence in zip(corpus_lsa, sentences):
if n_docs <= 0:
#print "%s\t\t%s" % (pertenence, sentence.split("\t")[0])
p=[dict(pertenence)[x] if x in dict(pertenence) else 0.0
for x in xrange(n_topics)]
for x in range(n_topics)]
print("{} {}".format("".join(sentence.split("\t")[0].split()), "".join(str(p)[1:].strip("]").split(","))))
else:
if n<n_docs:
pertenence=[dict(pertenence)[x] if x in dict(pertenence) else 0.0
for x in xrange(n_topics)]
for x in range(n_topics)]
print("%s\t\t%s" % (pertenence, sentence))
n+=1
else:
......