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()
