LSA soft clustering

@@ -109,7 +109,7 @@ n = 0
 with open("vectors_file.txt", "w") as f:
     for pertenence, sentence in zip(corpus_lsa, sentences):
         if n_docs <= 0:
-            # print "%s\t\t%s" % (pertenence, sentence.split("\t")[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 range(n_topics)]
             f.write(