old_contents: # coding=utf-8
  from __future__ import absolute_import, unicode_literals  # noqa
  
  import numpy as np
  import oslotest.base
  
  import lda
  
  
  class TestLDA(oslotest.base.BaseTestCase):
  
      def test_lda_constructor(self):
          n_topics = 10
          model1 = lda.LDA(n_topics)
          self.assertIsNotNone(model1)
          model2 = lda.LDA(n_topics=n_topics)
          self.assertIsNotNone(model2)
  
      def test_lda_params(self):
          n_topics = 10
          model1 = lda.LDA(n_topics, alpha=0.3)
          self.assertIsNotNone(model1)
          model2 = lda.LDA(n_topics=n_topics, alpha=0.3, eta=0.4)
          self.assertIsNotNone(model2)
          self.assertRaises(ValueError, lda.LDA, n_topics, alpha=-3)
          self.assertRaises(ValueError, lda.LDA, n_topics, eta=-3)
          self.assertRaises(ValueError, lda.LDA, n_topics, alpha=-3, eta=-3)
  
      def test_lda_getting_started(self):
          X = np.array([[1, 1], [2, 1], [3, 1], [4, 1], [5, 8], [6, 1]])
          model = lda.LDA(n_topics=2, n_iter=100, random_state=1)
          doc_topic = model.fit_transform(X)
          self.assertIsNotNone(doc_topic)
          self.assertIsNotNone(model.doc_topic_)
          self.assertIsNotNone(model.components_)
  
new_contents: # coding=utf-8
  from __future__ import absolute_import, unicode_literals  # noqa
  
  import numpy as np
  import oslotest.base
  
  import lda
  
  
  class TestLDA(oslotest.base.BaseTestCase):
  
      def test_lda_constructor(self):
          n_topics = 10
          model1 = lda.LDA(n_topics)
          self.assertIsNotNone(model1)
          model2 = lda.LDA(n_topics=n_topics)
          self.assertIsNotNone(model2)
  
      def test_lda_params(self):
          n_topics = 10
          model1 = lda.LDA(n_topics, alpha=0.3)
          self.assertIsNotNone(model1)
          model2 = lda.LDA(n_topics=n_topics, alpha=0.3, eta=0.4)
          self.assertIsNotNone(model2)
          self.assertRaises(ValueError, lda.LDA, n_topics, alpha=-3)
          self.assertRaises(ValueError, lda.LDA, n_topics, eta=-3)
          self.assertRaises(ValueError, lda.LDA, n_topics, alpha=-3, eta=-3)
  
      def test_lda_getting_started(self):
          X = np.array([[1, 1], [2, 1], [3, 1], [4, 1], [5, 8], [6, 1]])
          model = lda.LDA(n_topics=2, n_iter=100, random_state=1)
          doc_topic = model.fit_transform(X)
          self.assertIsNotNone(doc_topic)
          self.assertIsNotNone(model.doc_topic_)
          self.assertIsNotNone(model.components_)
  
      def test_lda_loglikelihoods(self):
          X = np.array([[1, 1], [2, 1], [3, 1], [4, 1], [5, 8], [6, 1]])
          model = lda.LDA(n_topics=2, n_iter=100, random_state=1)
          model.fit(X)
          self.assertGreater(len(model.loglikelihoods_), 1)
  
subject: add test for loglikelihoods_