def test_multiple(self):
multi_f = MultipleFeaturizer([self.single, self.multi])
data = self.make_test_data()
self.assertArrayAlmostEqual([2, 0, 3], multi_f.featurize(1))
self.assertArrayEqual(['A'], multi_f.citations())
implementors = multi_f.implementors()
self.assertIn('Us', implementors)
self.assertIn('Them', implementors)
self.assertEquals(2, len(implementors))
# Ensure BaseFeaturizer operation without overriden featurize_dataframe
with warnings.catch_warnings(record=True) as w:
multi_f.featurize_dataframe(data, 'x')
self.assertEqual(len(w), 0)
self.assertArrayAlmostEqual(data['y'], [2, 3, 4])
self.assertArrayAlmostEqual(data['w'], [0, 1, 2])
self.assertArrayAlmostEqual(data['z'], [3, 4, 5])
# Test handling of Featurizers with overloaded featurize_dataframe
f = FunctionFeaturizer()
multi_f = MultipleFeaturizer([self.single, self.multi, f])
data = self.make_test_data()
with warnings.catch_warnings(record=True) as w:
multi_f.featurize_dataframe(data, 'x')
self.assertEqual(len(w), 1)
def test_multiple(self):
# test iterating over both entries and featurizers
for iter_entries in [True, False]:
multi_f = MultipleFeaturizer([self.single, self.multi],
iterate_over_entries=iter_entries)
data = self.make_test_data()
self.assertArrayAlmostEqual([2, 0, 3], multi_f.featurize(1))
self.assertArrayEqual(['A'], multi_f.citations())
implementors = multi_f.implementors()
self.assertIn('Us', implementors)
self.assertIn('Them', implementors)
self.assertEqual(2, len(implementors))
# Ensure BaseFeaturizer operation without overriden featurize_dataframe
with warnings.catch_warnings(record=True) as w:
data = multi_f.featurize_dataframe(data, 'x')
self.assertEqual(len(w), 0)
self.assertArrayAlmostEqual(data['y'], [2, 3, 4])
self.assertArrayAlmostEqual(data['w'], [0, 1, 2])
self.assertArrayAlmostEqual(data['z'], [3, 4, 5])
f = MatrixFeaturizer()
multi_f = MultipleFeaturizer([self.single, self.multi, f])
data = self.make_test_data()
with warnings.catch_warnings(record=True) as w:
data = multi_f.featurize_dataframe(data, 'x')
self.assertEqual(len(w), 0)
self.assertArrayAlmostEqual(data['representation'][0],
[[1.0, 0.0], [0.0, 1.0]])
def test_multiple(self):
multi_f = MultipleFeaturizer([self.single, self.multi])
data = self.make_test_data()
self.assertArrayAlmostEqual([2, 0, 3], multi_f.featurize(1))
self.assertArrayEqual(['A'], multi_f.citations())
implementors = multi_f.implementors()
self.assertIn('Us', implementors)
self.assertIn('Them', implementors)
self.assertEquals(2, len(implementors))
multi_f.featurize_dataframe(data, 'x')
self.assertArrayAlmostEqual(data['y'], [2, 3, 4])
self.assertArrayAlmostEqual(data['w'], [0, 1, 2])
self.assertArrayAlmostEqual(data['z'], [3, 4, 5])
def test_multiple(self):
# test iterating over both entries and featurizers
for iter_entries in [True, False]:
multi_f = MultipleFeaturizer([self.single, self.multi],
iterate_over_entries=iter_entries)
data = self.make_test_data()
self.assertArrayAlmostEqual([2, 0, 3], multi_f.featurize(1))
self.assertArrayEqual(['A'], multi_f.citations())
implementors = multi_f.implementors()
self.assertIn('Us', implementors)
self.assertIn('Them', implementors)
self.assertEqual(2, len(implementors))
# Ensure BaseFeaturizer operation without overriden featurize_dataframe
with warnings.catch_warnings(record=True) as w:
multi_f.featurize_dataframe(data, 'x')
self.assertEqual(len(w), 0)
self.assertArrayAlmostEqual(data['y'], [2, 3, 4])
self.assertArrayAlmostEqual(data['w'], [0, 1, 2])
self.assertArrayAlmostEqual(data['z'], [3, 4, 5])
f = MatrixFeaturizer()
multi_f = MultipleFeaturizer([self.single, self.multi, f])
data = self.make_test_data()
with warnings.catch_warnings(record=True) as w:
multi_f.featurize_dataframe(data, 'x')
self.assertEqual(len(w), 0)
self.assertArrayAlmostEqual(data['representation'][0],
[[1.0, 0.0], [0.0, 1.0]])
