def test_load_model(self):
standardizer = Standardizer(name='TestStandardizer')
standardizer.load(self.base_path)
h5py.File.assert_called_once_with(os.path.join(self.base_path, 'processors/TestStandardizer.h5'), 'r')
pickle.loads.assert_called_once_with('Model')
self.assertEquals('Model', standardizer._model)
def test_save_model(self):
standardizer = Standardizer(name='TestStandardizer')
standardizer.save(self.base_path)
h5py.File.assert_called_once_with(os.path.join(self.base_path, 'processors/TestStandardizer.h5'), 'w')
self.h5f.create_dataset.assert_called_once_with('data', data=np.array('Model dump'))
def test_fit_method(self):
standardizer = Standardizer()
standardizer.fit(self.X)
StandardScaler.fit.assert_called_once_with(self.X['features'])
self.assertNotEquals(standardizer._model, None)
def test_fit_run(self):
standardizer = Standardizer()
Y = standardizer.fit_run(self.X)
np.testing.assert_array_equal(StandardScaler.fit.call_args[0][0], self.features)
np.testing.assert_array_equal(StandardScaler.transform.call_args[0][0], self.features)
self.assertNotEquals(standardizer._model, None)
np.testing.assert_equal(Y['features'], [[0, 1], [2, 3]])
def test_describe(self):
description = Standardizer(name='test_standardizer').__str__()
self.assertEquals(description, '{\'type\': \'Standard Scaler\', \'name\': \'test_standardizer\'}')
def test_run(self):
standardizer = Standardizer()
Y = standardizer.run(self.X)
np.testing.assert_array_equal(StandardScaler.transform.call_args[0][0], self.features)
np.testing.assert_equal(Y['features'], [[0, 1], [2, 3]])
def test_constructor_calls_sklearn_constructor(self):
Standardizer()
StandardScaler.__init__.assert_called_once()