How to use the rsmtool.preprocessor.FeatureSubsetProcessor.check_feature_subset_file function in rsmtool

def test_check_feature_subset_file_no_sign_column(self):
        feature_specs = pd.DataFrame({'feature': ['f1', 'f2', 'f3'],
                                      'subset1': [0, 1, 0]})
        FeatureSubsetProcessor.check_feature_subset_file(feature_specs, sign='subset1')

def test_check_feature_subset_file_multiple_sign_columns(self):
        feature_specs = pd.DataFrame({'feature': ['f1', 'f2', 'f3'],
                                      'sign_SYS': ['+', '-', '+'],
                                      'Sign_SYS': ['-', '+', '-']})
        FeatureSubsetProcessor.check_feature_subset_file(feature_specs,
                                                         sign='SYS')

def test_check_feature_subset_file_sign_named_with_Sign(self):
        feature_specs = pd.DataFrame({'feature': ['f1', 'f2', 'f3'],
                                      'Sign_SYS': ['+', '-', '+']})
        FeatureSubsetProcessor.check_feature_subset_file(feature_specs,
                                                         sign='SYS')

def test_check_feature_subset_file_no_subset_column(self):
        feature_specs = pd.DataFrame({'Feature': ['f1', 'f2', 'f3'], 'subset1': [0, 1, 0]})
        FeatureSubsetProcessor.check_feature_subset_file(feature_specs, 'subset2')

def test_check_feature_subset_file_sign_named_with_sign(self):
        feature_specs = pd.DataFrame({'feature': ['f1', 'f2', 'f3'],
                                      'sign_SYS': ['+', '-', '+']})
        FeatureSubsetProcessor.check_feature_subset_file(feature_specs,
                                                         sign='SYS')

def test_check_feature_subset_file_subset_only(self):
        feature_specs = pd.DataFrame({'feature': ['f1', 'f2', 'f3'],
                                      'subset1': [0, 1, 0]})
        FeatureSubsetProcessor.check_feature_subset_file(feature_specs, 'subset1')

def test_check_feature_subset_file_wrong_values_in_sign(self):
        feature_specs = pd.DataFrame({'Feature': ['f1', 'f2', 'f3'],
                                      'sign_SYS1': ['+1', '-1', '+1']})
        FeatureSubsetProcessor.check_feature_subset_file(feature_specs, sign='SYS1')

def test_check_feature_subset_file_sign_named_something_else(self):
        feature_specs = pd.DataFrame({'feature': ['f1', 'f2', 'f3'],
                                      'SYS_sign': ['+', '-', '+']})
        FeatureSubsetProcessor.check_feature_subset_file(feature_specs,
                                                         sign='SYS')

special_report_sections,
                                                                      custom_report_sections,
                                                                      section_order,
                                                                      subgroups,
                                                                      model_type=model_type,
                                                                      context='rsmtool')

        # Location of feature file
        feature_field = config_obj['features']

        feature_subset_field = config_obj['feature_subset']

        # if the user requested feature_subset file and feature subset,
        # read the file and check its format
        if feature_subset is not None and feature_subset_field:
            FeatureSubsetProcessor.check_feature_subset_file(feature_subset)

        # Do we need to automatically find the best transformations/change sign?
        select_transformations = config_obj['select_transformations']
        feature_sign = config_obj['sign']
        requested_features = []
        generate_feature_specs_automatically = True

        # if the feature field is a list, then simply
        # assign it to `requested_features`
        if isinstance(feature_field, list):
            requested_features = feature_field

        elif feature_field is not None:
            generate_feature_specs_automatically = False
            feature_specs = FeatureSpecsProcessor.validate_feature_specs(feature_specs,
                                                                         use_truncations)