test_postprocessing.py 文件源码

def test_axis_statistics():
    adel_output_df = pd.read_csv(INPUTS_DIRPATH/ADEL_OUTPUT_FILENAME)
    adel_output_df['species'] = '0'
    axis_statistics_df, intermediate_df = pp.axis_statistics(adel_output_df, domain_area=1)
    axis_statistics_df.drop('species', 1, inplace=True)
    intermediate_df.drop('species', 1, inplace=True)
    axis_statistics_df.to_csv(OUTPUTS_DIRPATH/'actual_axis_statistics.csv', index=False, na_rep='NA')
    intermediate_df.to_csv(OUTPUTS_DIRPATH/'actual_intermediate.csv', index=False, na_rep='NA')

    desired_axis_statistics_df = pd.read_csv(OUTPUTS_DIRPATH/'desired_axis_statistics.csv')
    desired_axis_statistics_df.drop('has_ear', 1, inplace=True)
    axis_statistics_df = axis_statistics_df.select_dtypes(include=[np.number])
    desired_axis_statistics_df = desired_axis_statistics_df.select_dtypes(include=[np.number])
    np.testing.assert_allclose(axis_statistics_df.values, desired_axis_statistics_df.values, RELATIVE_TOLERANCE, ABSOLUTE_TOLERANCE)

    desired_intermediate_df = pd.read_csv(OUTPUTS_DIRPATH/'desired_intermediate.csv')
    desired_intermediate_df.drop('has_ear', 1, inplace=True)
    intermediate_df = intermediate_df.select_dtypes(include=[np.number])
    desired_intermediate_df = desired_intermediate_df.select_dtypes(include=[np.number])
    np.testing.assert_allclose(intermediate_df.values, desired_intermediate_df.values, RELATIVE_TOLERANCE, ABSOLUTE_TOLERANCE)