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_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_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()
