def test_feat_agg(): """Assert that the TPOT FeatureAgglomeration preprocessor outputs the input dataframe when the number of training features is 0""" tpot_obj = TPOT() assert np.array_equal(tpot_obj._feat_agg(training_testing_data.ix[:, -3:], 5, 1, 1), training_testing_data.ix[:, -3:])
def test_feat_agg(): """Assert that the TPOT FeatureAgglomeration preprocessor outputs the input dataframe when the number of training features is 0""" tpot_obj = TPOT() assert np.array_equal(tpot_obj._feat_agg(training_testing_data.ix[:, -3:], 5, 1, 1), training_testing_data.ix[:, -3:])
def test_feat_agg_2(): """Assert that FeatureAgglomeration returns the same object type as the input object type. Also assert that the number of rows is identical between the input dataframe and output dataframe. """ tpot_obj = TPOT() input_df = training_testing_data output_df = tpot_obj._feat_agg(input_df, 5, 1, 1) assert type(input_df) == type(output_df) (in_rows, in_cols) = input_df.shape (out_rows, out_cols) = output_df.shape assert in_rows == out_rows
def test_feat_agg_2(): """Assert that FeatureAgglomeration returns the same object type as the input object type. Also assert that the number of rows is identical between the input dataframe and output dataframe. """ tpot_obj = TPOT() input_df = training_testing_data output_df = tpot_obj._feat_agg(input_df, 5, 1, 1) assert type(input_df) == type(output_df) (in_rows, in_cols) = input_df.shape (out_rows, out_cols) = output_df.shape assert in_rows == out_rows