from gensim import corpora, models
import numpy.random
numpy.random.seed(10)

doc0 = [(0, 1), (1, 1)]
doc1 = [(0,1)]
doc2 = [(0, 1), (1, 1)]
doc3 = [(0, 3), (1, 1)]

corpus = [doc0,doc1,doc2,doc3]
dictionary = corpora.Dictionary(corpus)

tfidf = models.TfidfModel(corpus)
corpus_tfidf = tfidf[corpus]
corpus_tfidf.save('x.corpus_tfidf')

corpus_tfidf = corpora.MmCorpus.load('x.corpus_tfidf')

lda = models.ldamodel.LdaModel(corpus_tfidf, id2word=dictionary, num_topics=2)

#which one i should use from this
**corpus_lda = lda[corpus]**          #this one
**corpus_LDA = lda[corpus_tfidf ]**   #or this one?


corpus_lda.save('x.corpus_lda')

for i,j in enumerate(corpus_lda):
    print j, corpus[i]