Return the static LDA topic for a term in the corpus vocabulary. (#706)

CHANGELOG.txt

@@ -1,6 +1,7 @@
 Changes
 =======
 0.12.5, 2016
+* added term-topics API for most probable topic for word in vocab. (@bhargavvader, #706)
 * build_vocab takes progress_per parameter for smaller output (@zer0n, #624)
 * Control whether to use lowercase for computing word2vec accuracy. (@alantian, #607)
 * Easy import of GloVe vectors using Gensim (Manas Ranjan Kar, #625)

gensim/models/ldamodel.py

@@ -905,6 +905,27 @@ def get_document_topics(self, bow, minimum_probability=None):
         return [(topicid, topicvalue) for topicid, topicvalue in enumerate(topic_dist)
                 if topicvalue >= minimum_probability]
 
+    def get_term_topics(self, word_id, minimum_probability=None):
+        """
+        Returns most likely topics for a particular word in vocab.
+
+        """
+        if minimum_probability is None:
+            minimum_probability = self.minimum_probability
+        minimum_probability = max(minimum_probability, 1e-8)  # never allow zero values in sparse output
+
+        # if user enters word instead of id in vocab, change to get id
+        if isinstance(word_id, str):
+            word_id = self.id2word.doc2bow([word_id])[0][0]
+
+        values = []
+        for topic_id in range(0, self.num_topics):
+            if self.expElogbeta[topic_id][word_id] >= minimum_probability:
+                values.append((topic_id, self.expElogbeta[topic_id][word_id]))
+
+        return values
+
+
     def __getitem__(self, bow, eps=None):
         """
         Return topic distribution for the given document `bow`, as a list of

gensim/test/test_ldamodel.py

@@ -265,6 +265,22 @@ def testGetDocumentTopics(self):
             self.assertTrue(isinstance(k, int))
             self.assertTrue(isinstance(v, float))
 
+    def testTermTopics(self):
+
+        numpy.random.seed(0)
+        model = self.class_(self.corpus, id2word=dictionary, num_topics=2, passes=100)
+
+        # check with id 
+        result = model.get_term_topics(2)
+        expected = [(1, 0.1066)]
+        self.assertEqual(result[0][0], expected[0][0])
+        self.assertAlmostEqual(result[0][1], expected[0][1], places=2)
+
+        # if user has entered word instead, check with word
+        result = model.get_term_topics(str(model.id2word[2]))
+        expected = [(1, 0.1066)]
+        self.assertEqual(result[0][0], expected[0][0])
+        self.assertAlmostEqual(result[0][1], expected[0][1], places=2)
 
     def testPasses(self):
         # long message includes the original error message with a custom one