From ba28c351d91f39d7a43f5ce83932478d53c1f5c7 Mon Sep 17 00:00:00 2001
From: dsquareindia <ashu.9412@gmail.com>
Date: Fri, 24 Jun 2016 17:19:04 -0400
Subject: [PATCH] Added test suite for coherencemodel and aggregation.

---
 gensim/test/test_aggregation.py    | 28 +++++++++++
 gensim/test/test_coherencemodel.py | 75 ++++++++++++++++++++++++++++++
 2 files changed, 103 insertions(+)
 create mode 100644 gensim/test/test_aggregation.py
 create mode 100644 gensim/test/test_coherencemodel.py

diff --git a/gensim/test/test_aggregation.py b/gensim/test/test_aggregation.py
new file mode 100644
index 0000000000..44e3d16f65
--- /dev/null
+++ b/gensim/test/test_aggregation.py
@@ -0,0 +1,28 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2010 Radim Rehurek <radimrehurek@seznam.cz>
+# Licensed under the GNU LGPL v2.1 - http://www.gnu.org/licenses/lgpl.html
+
+"""
+Automated tests for checking transformation algorithms (the models package).
+"""
+
+import logging
+import unittest
+
+from gensim.topic_coherence import aggregation
+
+class TestAggregation(unittest.TestCase):
+    def setUp(self):
+        self.confirmed_measures = [1.1, 2.2, 3.3, 4.4]
+
+    def testArithmeticMean(self):
+        """Test arithmetic_mean()"""
+        obtained = aggregation.arithmetic_mean(self.confirmed_measures)
+        expected = 2.75
+        self.assertEqual(obtained, expected)
+
+if __name__ == '__main__':
+    logging.root.setLevel(logging.WARNING)
+    unittest.main()
diff --git a/gensim/test/test_coherencemodel.py b/gensim/test/test_coherencemodel.py
new file mode 100644
index 0000000000..9291d33825
--- /dev/null
+++ b/gensim/test/test_coherencemodel.py
@@ -0,0 +1,75 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2010 Radim Rehurek <radimrehurek@seznam.cz>
+# Licensed under the GNU LGPL v2.1 - http://www.gnu.org/licenses/lgpl.html
+
+"""
+Automated tests for checking transformation algorithms (the models package).
+"""
+
+import logging
+import unittest
+import os
+import os.path
+import tempfile
+
+import numpy as np
+
+from gensim.models.coherencemodel import CoherenceModel
+from gensim.models.ldamodel import LdaModel
+from gensim.models.wrappers import LdaMallet
+from gensim.models.wrappers import LdaVowpalWabbit
+from gensim.corpora.dictionary import Dictionary
+
+module_path = os.path.dirname(__file__) # needed because sample data files are located in the same folder
+datapath = lambda fname: os.path.join(module_path, 'test_data', fname)
+
+# set up vars used in testing ("Deerwester" from the web tutorial)
+texts = [['human', 'interface', 'computer'],
+         ['survey', 'user', 'computer', 'system', 'response', 'time'],
+         ['eps', 'user', 'interface', 'system'],
+         ['system', 'human', 'system', 'eps'],
+         ['user', 'response', 'time'],
+         ['trees'],
+         ['graph', 'trees'],
+         ['graph', 'minors', 'trees'],
+         ['graph', 'minors', 'survey']]
+dictionary = Dictionary(texts)
+corpus = [dictionary.doc2bow(text) for text in texts]
+
+
+def testfile():
+    # temporary data will be stored to this file
+    return os.path.join(tempfile.gettempdir(), 'gensim_models.tst')
+
+class TestCoherenceModel(unittest.TestCase):
+    def setUp(self):
+        np.random.seed(8)
+        self.badLdaModel = LdaModel(corpus=corpus, num_topics=2, passes=1)  # Bad lda model
+        self.goodLdaModel = LdaModel(corpus=corpus, num_topics=2, passes=50)  # Good lda model
+
+    def testUMassLdaModel(self):
+        """Test U_Mass topic coherence algorithm on LDA Model"""
+        cm1 = CoherenceModel(model=self.badLdaModel, corpus=corpus, dictionary=dictionary, coherence='u_mass')
+        cm2 = CoherenceModel(model=self.goodLdaModel, corpus=corpus, dictionary=dictionary, coherence='u_mass')
+        self.assertTrue(cm1.get_coherence() < cm2.get_coherence())
+
+    def testCvLdaModel(self):
+        """Test C_v topic coherence algorithm on LDA Model"""
+        cm1 = CoherenceModel(model=self.badLdaModel, texts=texts, dictionary=dictionary, coherence='c_v')
+        cm2 = CoherenceModel(model=self.goodLdaModel, texts=texts, dictionary=dictionary, coherence='c_v')
+        self.assertTrue(cm1.get_coherence() < cm2.get_coherence())
+
+    def testErrors(self):
+        """Test if errors are raised on bad input"""
+        # not providing dictionary
+        self.assertRaises(ValueError, CoherenceModel, model=self.goodLdaModel, corpus=corpus, coherence='u_mass')
+        # not providing texts for c_v and instead providing corpus
+        self.assertRaises(ValueError, CoherenceModel, model=self.goodLdaModel, corpus=corpus, dictionary=dictionary, coherence='c_v')
+        # not providing corpus or texts for u_mass
+        self.assertRaises(ValueError, CoherenceModel, self.goodLdaModel, dictionary, 'u_mass')
+
+if __name__ == '__main__':
+    logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.DEBUG)
+    unittest.main()