def test_returns_tuples_of_features_length(self):
     features = [DumbFeatureA, DumbFeatureA]
     ev = FeatureEvaluator(features)
     ev.fit(SAMPLES)
     Xt = ev.transform(SAMPLES)
     x = Xt.next()
     self.assertIsInstance(x, tuple)
     self.assertEqual(len(x), len(features))
 def test_returns_tuples_of_features_length(self):
     features = [DumbFeatureA, DumbFeatureA]
     ev = FeatureEvaluator(features)
     ev.fit(SAMPLES)
     Xt = ev.transform(SAMPLES)
     x = next(Xt)
     self.assertIsInstance(x, tuple)
     self.assertEqual(len(x), len(features))
 def test_returns_as_many_tuples_as_samples(self):
     ev = FeatureEvaluator([DumbFeatureA])
     ev.fit(SAMPLES)
     Xt = ev.transform(SAMPLES)
     self.assertEqual(len(list(Xt)), len(SAMPLES))
 def test_returns_generator(self):
     ev = FeatureEvaluator([DumbFeatureA])
     ev.fit([])
     Xt = ev.transform([])
     self.assertIsInstance(Xt, types.GeneratorType)
 def test_fit_creates_alive_features_tuple(self):
     ev = FeatureEvaluator([DumbFeatureA])
     self.assertFalse(hasattr(ev, 'alive_features'))
     ev.fit([])
     self.assertTrue(hasattr(ev, 'alive_features'))
 def test_returns_as_many_tuples_as_samples(self):
     ev = FeatureEvaluator([DumbFeatureA])
     ev.fit(SAMPLES)
     Xt = ev.transform(SAMPLES)
     self.assertEqual(len(list(Xt)), len(SAMPLES))
 def test_returns_generator(self):
     ev = FeatureEvaluator([DumbFeatureA])
     ev.fit([])
     Xt = ev.transform([])
     self.assertIsInstance(Xt, types.GeneratorType)
 def test_fit_creates_alive_features_tuple(self):
     ev = FeatureEvaluator([DumbFeatureA])
     self.assertFalse(hasattr(ev, 'alive_features'))
     ev.fit([])
     self.assertTrue(hasattr(ev, 'alive_features'))