Carlos-Francisco Méndez-Cruz

LSA soft clustering

......@@ -112,12 +112,12 @@ with open("vectors_file.txt", "w") as f:
p = [dict(pertenence)[x] if x in dict(pertenence) else 0.0
for x in range(n_topics)]
f.write(
"{}\t{}".format("".join(sentence.split("\t")[0].split()), "".join(str(p)[1:].strip("]").split(","))))
"{}\t{}\n".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 range(n_topics)]
f.write("%s\t\t%s" % (pertenence, sentence))
f.write("%s\t\t%s\n" % (pertenence, sentence))
n += 1
else:
break
......