BUG Fixes API usage

For newer versions of gensim at least, topics are represented as `(word, frequency)`. closesluispedro#21

Author: luispedro

ch04/blei_lda.py

@@ -36,9 +36,9 @@
 # Iterate over all the topics in the model
 fortiinrange(model.num_topics):
 words=model.show_topic(ti, 64)
-tf=sum(fforf, winwords)
+tf=sum(ffor_, finwords)
 withopen('topics.txt', 'w') asoutput:
-output.write('\n'.join('{}:{}'.format(w, int(1000.*f/tf)) forf, winwords))
+output.write('\n'.join('{}:{}'.format(w, int(1000.*f/tf)) forw, finwords))
 output.write("\n\n\n")
 
 # We first identify the most discussed topic, i.e., the one with the

ch04/wordcloud.py

@@ -24,8 +24,6 @@ def create_cloud(oname, words,maxsize=120, fontname='Lobster'):
 # gensim returns a weight between 0 and 1 for each word, while pytagcloud
 # expects an integer word count. So, we multiply by a large number and
 # round. For a visualization this is an adequate approximation.
-# We also need to flip the order as gensim returns (value, word), whilst
-# pytagcloud expects (word, value):
-words= [(w,int(v*10000)) forv,winwords]
+words= [(w,int(v*10000)) forw,vinwords]
 tags=make_tags(words, maxsize=maxsize)
 create_tag_image(tags, oname, size=(1800, 1200), fontname=fontname)