LDAMallet load_word_topics() returns value (#767)

piskvorky · Jul 1, 2016 · 003a886 · 003a886
1 parent bf26bdd
commit 003a886
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Showing 2 changed files with 11 additions and 9 deletions.
diff --git a/gensim/models/wrappers/ldamallet.py b/gensim/models/wrappers/ldamallet.py
@@ -182,7 +182,7 @@ def __getitem__(self, bow, iterations=100):
 
     def load_word_topics(self):
         logger.info("loading assigned topics from %s", self.fstate())
-        wordtopics = numpy.zeros((self.num_topics, self.num_terms), dtype=numpy.float32)
+        word_topics = numpy.zeros((self.num_topics, self.num_terms), dtype=numpy.float32)
         if hasattr(self.id2word, 'token2id'):
             word2id = self.id2word.token2id
         else:
@@ -199,10 +199,10 @@ def load_word_topics(self):
                 if token not in word2id:
                     continue
                 tokenid = word2id[token]
-                wordtopics[int(topic), tokenid] += 1.0
-        logger.info("loaded assigned topics for %i tokens", wordtopics.sum())
-        self.wordtopics = wordtopics
+                word_topics[int(topic), tokenid] += 1.0
+        logger.info("loaded assigned topics for %i tokens", word_topics.sum())
         self.print_topics(15)
+        return word_topics
 
     def print_topics(self, num_topics=10, num_words=10):
         return self.show_topics(num_topics, num_words, log=True)
@@ -242,7 +242,9 @@ def show_topics(self, num_topics=10, num_words=10, log=False, formatted=True):
         return shown
 
     def show_topic(self, topicid, topn=10):
-        topic = self.wordtopics[topicid]
+        if self.word_topics is None:
+            logger.warn("Run train or load_word_topics before showing topics.")
+        topic = self.word_topics[topicid]
         topic = topic / topic.sum()  # normalize to probability dist
         bestn = matutils.argsort(topic, topn, reverse=True)
         beststr = [(topic[id], self.id2word[id]) for id in bestn]

diff --git a/gensim/test/test_ldamallet_wrapper.py b/gensim/test/test_ldamallet_wrapper.py
@@ -104,7 +104,7 @@ def testPersistence(self):
         model.save(fname)
         model2 = ldamallet.LdaMallet.load(fname)
         self.assertEqual(model.num_topics, model2.num_topics)
-        self.assertTrue(numpy.allclose(model.wordtopics, model2.wordtopics))
+        self.assertTrue(numpy.allclose(model.word_topics, model2.word_topics))
         tstvec = []
         self.assertTrue(numpy.allclose(model[tstvec], model2[tstvec])) # try projecting an empty vector
 
@@ -116,7 +116,7 @@ def testPersistenceCompressed(self):
         model.save(fname)
         model2 = ldamallet.LdaMallet.load(fname, mmap=None)
         self.assertEqual(model.num_topics, model2.num_topics)
-        self.assertTrue(numpy.allclose(model.wordtopics, model2.wordtopics))
+        self.assertTrue(numpy.allclose(model.word_topics, model2.word_topics))
         tstvec = []
         self.assertTrue(numpy.allclose(model[tstvec], model2[tstvec])) # try projecting an empty vector
 
@@ -132,8 +132,8 @@ def testLargeMmap(self):
         # test loading the large model arrays with mmap
         model2 = ldamodel.LdaModel.load(testfile(), mmap='r')
         self.assertEqual(model.num_topics, model2.num_topics)
-        self.assertTrue(isinstance(model2.wordtopics, numpy.memmap))
-        self.assertTrue(numpy.allclose(model.wordtopics, model2.wordtopics))
+        self.assertTrue(isinstance(model2.word_topics, numpy.memmap))
+        self.assertTrue(numpy.allclose(model.word_topics, model2.word_topics))
         tstvec = []
         self.assertTrue(numpy.allclose(model[tstvec], model2[tstvec])) # try projecting an empty vector