def test_column_transformer_fit_should_support_multiple_tuples():
# Given
test_case = ColumnChooserTestCase(
data_inputs=np.array([[1, 1, 2, 3], [10, 11, 12, 13], [20, 21, 22,
23]]),
expected_outputs=np.array([[0, 1, 2, 3], [10, 11, 12, 13],
[20, 21, 22, 23]]),
expected_processed_outputs=np.array([[2, 2, 2, 3], [20, 22, 12, 13],
[40, 42, 44, 46]]),
column_transformer_tuple_list=[(slice(0, 2), MultiplyBy2()),
(2, MultiplyBy2())],
n_dimension=3)
data_inputs = test_case.data_inputs
column_transformer = ColumnTransformer(
test_case.column_transformer_tuple_list)
# When
column_transformer = column_transformer.fit(data_inputs,
test_case.expected_outputs)
# Then
actual_fitted_data = column_transformer['2_MultiplyBy2'][
'MultiplyBy2'].fitted_data
expected_fitted_data = [([[2], [12], [22]], [[0, 1, 2, 3],
[10, 11, 12, 13],
[20, 21, 22, 23]])]
assert_data_fitted_properly(actual_fitted_data, expected_fitted_data)
actual_fitted_data = column_transformer['slice(0, 2, None)_MultiplyBy2'][
'MultiplyBy2'].fitted_data
expected_fitted_data = [([[1, 1], [10, 11], [20, 21]], [[0, 1, 2, 3],
[10, 11, 12, 13],
[20, 21, 22, 23]])]
assert_data_fitted_properly(actual_fitted_data, expected_fitted_data)
def test_column_transformer_fit_should_support_indexes(test_case: ColumnChooserTestCase):
data_inputs = test_case.data_inputs
p = ColumnTransformer(test_case.column_transformer_tuple_list, test_case.n_dimension)
p = p.fit(data_inputs, test_case.expected_outputs)
actual_fitted_data = p[test_case.expected_step_key]['MultiplyBy2'].fitted_data
expected_fitted_data = test_case.expected_fitted_data
assert_data_fitted_properly(actual_fitted_data, expected_fitted_data)