def test_feature_vector_construction(self): TestAuthor.drop_collection() a = TestAuthor() a.screen_name = "ianinegypt" a.tweets = docs1 a.followers_count = 100 a.friends_count = 4 fv = a.update_feature_vector() expected = [0.17948718, 0.05128205, 0.0685413, 0.0512820512, 0.02564102564, 25.] self.assertAlmostEqual(numpy.sum(numpy.array(expected) - numpy.array(fv)), 0) TestAuthor.drop_collection()
def test_author_stats_single_author(self): TestAuthor.drop_collection() a = TestAuthor() a.screen_name = "ianinegypt" a.tweets = docs1 a.calculate_author_stats() expected = [7, 2, 569, 2, 1] calculated = [a.retweets, a.links, a.retweeted_tweets, a.replies_to_others, a.mentions_to_others] self.assertEqual(expected, calculated) TestAuthor.drop_collection()
def test_author_stats_single_author(self): a = TestAuthor() a.screen_name = "ianinegypt" a.tweets = docs1 a.calculate_author_stats() expected = [7, 2, 569, 1, 0] calculated = [a.retweets, a.links, a.retweeted_tweets, a.replies_to_others, a.mentions_by_others] self.assertEqual(expected, calculated) TestAuthor.drop_collection()
def test_feature_vector_construction(self): a = TestAuthor() a.screen_name = "ianinegypt" a.tweets = docs1 a.followers_count = 100 a.friends_count = 4 fv = a.get_feature_vector() expected = [0.17948718, 0.05128205, 0.0685413, 0.02564103, 0., 25.] self.assertAlmostEqual(numpy.sum(expected - fv), 0)
def test_author_stats_multiple_authors(self): a1 = TestAuthor() a1.screen_name = "ianinegypt1" a1.tweets = [docs2[0], docs2[1], docs2[2]] a1.save() a2 = TestAuthor() a2.screen_name = "ianinegypt2" a2.tweets = [docs2[3]] a2.save() a1.calculate_author_stats() calculated1 = [a1.retweets, a1.links, a1.retweeted_tweets, a1.replies_to_others, a1.mentions_by_others] a2.calculate_author_stats() calculated2 = [a2.retweets, a2.links, a2.retweeted_tweets, a2.replies_to_others, a2.mentions_by_others] expected1 = [1, 2, 20, 2, 0] expected2 = [0, 1, 16, 1, 0] self.assertEqual(expected1, calculated1) self.assertEqual(expected2, calculated2)
def test_feature_vector_construction_after_update(self): TestAuthor.drop_collection() a = TestAuthor() a.screen_name = "ianinegypt" a.tweets = docs1 a.followers_count = 100 a.friends_count = 4 fv = a.update_feature_vector() expected = [0.17948718, 0.05128205, 0.0685413, 0.0512820512, 0.02564102564, 25.] self.assertAlmostEqual(numpy.sum(numpy.array(expected) - numpy.array(fv)), 0) #Then append some new docs a.tweets.extend(docs2) fv = a.update_feature_vector() expected = [0.18604651162790697, 0.11627906976744186, 0.07557117750439367, 0.06976744186046512, 0.06976744186046512, 25.0] self.assertAlmostEqual(numpy.sum(numpy.array(expected) - numpy.array(fv)), 0) TestAuthor.drop_collection()