def test_code_words():
dal = ReviewsDAL()
wordcoder = WordCoder()
for index,r in enumerate(dal.sampling(5)):
print "****************** [{}]".format(index+1)
print r.sent.raw
print "\n"
print wordcoder.code(r.sent.words)
coded_words = wordcoder.code(sentence.words)
bow = dictionary.doc2bow(coded_words)
topic_distribution = lda_model[bow]
topic_distribution.sort(key=lambda t: t[1], reverse=True)
tags = None
for index, (topic_id, topic_percentage) in enumerate(topic_distribution):
mt = MixTopic(topic_mapping[topic_id])
mt.weight(topic_percentage)
if tags is None:
tags = mt
else:
tags.add(mt)
tags.normalize()
print tags
if __name__ == "__main__":
dal = ReviewsDAL()
review_stream = dal.sampling(10)
for index,review in enumerate( review_stream):
print "*********** [{}] ***********".format(index+1)
for sentence in sent_tokenizer.tokenize(review.sent.raw):
print_topics(sentence)
dal.close()
