How to print the LDA topics models from gensim? Python

问题:

Using gensim I was able to extract topics from a set of documents in LSA but how do I access the topics generated from the LDA models?

When printing the lda.print_topics(10) the code gave the following error because print_topics() return a NoneType:

Traceback (most recent call last):   File "/home/alvas/workspace/XLINGTOP/xlingtop.py", line 93, in      for top in lda.print_topics(2): TypeError: 'NoneType' object is not iterable 

The code:

from gensim import corpora, models, similarities from gensim.models import hdpmodel, ldamodel from itertools import izip  documents = ["Human machine interface for lab abc computer applications",               "A survey of user opinion of computer system response time",               "The EPS user interface management system",               "System and human system engineering testing of EPS",               "Relation of user perceived response time to error measurement",               "The generation of random binary unordered trees",               "The intersection graph of paths in trees",               "Graph minors IV Widths of trees and well quasi ordering",               "Graph minors A survey"]  # remove common words and tokenize stoplist = set('for a of the and to in'.split()) texts = [[word for word in document.lower().split() if word not in stoplist]          for document in documents]  # remove words that appear only once all_tokens = sum(texts, []) tokens_once = set(word for word in set(all_tokens) if all_tokens.count(word) == 1) texts = [[word for word in text if word not in tokens_once]          for text in texts]  dictionary = corpora.Dictionary(texts) corpus = [dictionary.doc2bow(text) for text in texts]  # I can print out the topics for LSA lsi = models.LsiModel(corpus_tfidf, id2word=dictionary, num_topics=2) corpus_lsi = lsi[corpus]  for l,t in izip(corpus_lsi,corpus):   print l,"#",t print for top in lsi.print_topics(2):   print top  # I can print out the documents and which is the most probable topics for each doc. lda = ldamodel.LdaModel(corpus, id2word=dictionary, num_topics=50) corpus_lda = lda[corpus]  for l,t in izip(corpus_lda,corpus):   print l,"#",t print  # But I am unable to print out the topics, how should i do it? for top in lda.print_topics(10):   print top 

回答1:

After some messing around, it seems like print_topics(numoftopics) for the ldamodel has some bug. So my workaround is to use print_topic(topicid):

>>> print lda.print_topics() None >>> for i in range(0, lda.num_topics-1): >>>  print lda.print_topic(i) 0.083*response + 0.083*interface + 0.083*time + 0.083*human + 0.083*user + 0.083*survey + 0.083*computer + 0.083*eps + 0.083*trees + 0.083*system ... 

回答2:

I think syntax of show_topics has changed over time:

show_topics(num_topics=10, num_words=10, log=False, formatted=True) 

For num_topics number of topics, return num_words most significant words (10 words per topic, by default).

If log is True, also output this result to log.

Unlike LSA, there is no natural ordering between the topics in LDA. The returned num_topics

回答3:

Are you using any logging? print_topics prints to the logfile as stated in the docs.

As @mac389 says, lda.show_topics() is the way to go to print to screen.

回答4:

you can use:

for i in  lda_model.show_topics():     print i[0], i[1] 

回答5:

Here is sample code to print topics:

def ExtractTopics(filename, numTopics=5):     # filename is a pickle file where I have lists of lists containing bag of words     texts = pickle.load(open(filename, "rb"))      # generate dictionary     dict = corpora.Dictionary(texts)      # remove words with low freq.  3 is an arbitrary number I have picked here     low_occerance_ids = [tokenid for tokenid, docfreq in dict.dfs.iteritems() if docfreq == 3]     dict.filter_tokens(low_occerance_ids)     dict.compactify()     corpus = [dict.doc2bow(t) for t in texts]     # Generate LDA Model     lda = models.ldamodel.LdaModel(corpus, num_topics=numTopics)     i = 0     # We print the topics     for topic in lda.show_topics(num_topics=numTopics, formatted=False, topn=20):         i = i + 1         print "Topic #" + str(i) + ":",         for p, id in topic:             print dict[int(id)],          print "" 

回答6:

Recently, came across a similar issue while working with Python 3 and Gensim 2.3.0. print_topics() and show_topics() weren't giving any error but also not printing anything. Turns out that show_topics() returns a list. So one can simply do:

topic_list = show_topics() print(topic_list) 

文章来源: How to print the LDA topics models from gensim? Python