def test_create_model_VRS(params, DEA_example_data): params.update_parameter('RETURN_TO_SCALE', 'VRS') model = factory.create_model(params, DEA_example_data) assert model.__class__.__name__ == 'EnvelopmentModelVRSDecorator' params.update_parameter('DEA_FORM', 'multi') model = factory.create_model(params, DEA_example_data) assert model.__class__.__name__ == 'MultiplierModelVRSDecorator'
def test_weakly_disposal_categories_creation(params, DEA_example_data): factory.add_input_and_output_categories(params, DEA_example_data) params.update_parameter('WEAKLY_DISPOSAL_CATEGORIES', 'I1; O2') model = factory.create_model(params, DEA_example_data) assert model._constraint_creator.__class__.__name__ == 'DisposableVarsConstraintCreator' params.update_parameter('DEA_FORM', 'multi') model = factory.create_model(params, DEA_example_data) assert model.__class__.__name__ == 'MultiplierModelWithDisposableCategories'
def test_create_model(params, DEA_example_data): factory.add_input_and_output_categories(params, DEA_example_data) model = factory.create_model(params, DEA_example_data) assert model.__class__.__name__ == 'EnvelopmentModelBase' assert model._concrete_model.__class__.__name__ == 'EnvelopmentModelInputOriented' assert model._constraint_creator.__class__.__name__ == 'DefaultConstraintCreator' params.update_parameter('DEA_FORM', 'multi') model = factory.create_model(params, DEA_example_data) assert model.__class__.__name__ == 'MultiplierModelBase' assert model._concrete_model.__class__.__name__ == 'MultiplierInputOrientedModel'
def test_orientation_and_non_disc_variables(params, DEA_example_data): factory.add_input_and_output_categories(params, DEA_example_data) params.update_parameter('ORIENTATION', 'output') model = factory.create_model(params, DEA_example_data) assert model._concrete_model.__class__.__name__ == 'EnvelopmentModelOutputOriented' params.update_parameter('NON_DISCRETIONARY_CATEGORIES', 'O1') model = factory.create_model(params, DEA_example_data) assert model._concrete_model.__class__.__name__ == 'EnvelopmentModelOutputOrientedWithNonDiscVars' params.update_parameter('ORIENTATION', 'input') params.update_parameter('NON_DISCRETIONARY_CATEGORIES', 'I2') model = factory.create_model(params, DEA_example_data) assert model._concrete_model.__class__.__name__ == 'EnvelopmentModelInputOrientedWithNonDiscVars' params.update_parameter('ORIENTATION', 'not valid value') with pytest.raises(ValueError) as excinfo: model = factory.create_model(params, DEA_example_data) assert str(excinfo.value) == 'Unexpected value of parameter <ORIENTATION>'
def run(self): model = factory.create_model(self.__dea_params, self.__dea_data) solution = model.run() r = {} s = solution.efficiency_scores for dmu_key in sorted(s.keys()): r[self.__dea_data.get_dmu_user_name(dmu_key)] = s[dmu_key] return r
def test_create_model_weigth_restrictions(params, DEA_example_data): params.update_parameter('ABS_WEIGHT_RESTRICTIONS', 'I1 >= 1; I2 <= 10; I1 <= 7') model = factory.create_model(params, DEA_example_data) assert model.__class__.__name__ == 'EnvelopmentModelWithAbsoluteWeightRestrictions' params.update_parameter('VIRTUAL_WEIGHT_RESTRICTIONS', 'I1 >= 1; I2 <= 10; I1 <= 7') model = factory.create_model(params, DEA_example_data) assert model.__class__.__name__ == 'EnvelopmentModelWithVirtualWeightRestrictions' assert model.model.__class__.__name__ == 'EnvelopmentModelWithAbsoluteWeightRestrictions' params.update_parameter('PRICE_RATIO_RESTRICTIONS', 'I1/I2 >= 1; I2/I1 <= 10; I1/I2 <= 7') model = factory.create_model(params, DEA_example_data) assert model.__class__.__name__ == 'EnvelopmentModelWithPriceRatioConstraints' assert model.model.__class__.__name__ == 'EnvelopmentModelWithVirtualWeightRestrictions' params.update_parameter('DEA_FORM', 'multi') params.update_parameter('VIRTUAL_WEIGHT_RESTRICTIONS', '') params.update_parameter('PRICE_RATIO_RESTRICTIONS', '') model = factory.create_model(params, DEA_example_data) assert model.__class__.__name__ == 'MultiplierModelWithAbsoluteWeightRestrictions' params.update_parameter('VIRTUAL_WEIGHT_RESTRICTIONS', 'I1 >= 1; I2 <= 10; I1 <= 7') model = factory.create_model(params, DEA_example_data) assert model.__class__.__name__ == 'MultiplierModelWithVirtualWeightRestrictions' assert model._model_to_decorate.__class__.__name__ == 'MultiplierModelWithAbsoluteWeightRestrictions' params.update_parameter('PRICE_RATIO_RESTRICTIONS', 'I1/I2 >= 1; I2/I1 <= 10; I1/I2 <= 7') model = factory.create_model(params, DEA_example_data) assert model.__class__.__name__ == 'MultiplierModelWithPriceRatioConstraints' assert model._model_to_decorate.__class__.__name__ == 'MultiplierModelWithVirtualWeightRestrictions'
def build_models(params, model_input): ''' Creates several models and parameters in the case when RETURN_TO_SCALE or ORIENTATION is set to both. If neither RETURN_TO_SCALE nor ORIENTATION is set to both, then no new models will be created, a copy of the given model and parameters will be returned. Args: params (Parameters): parameters. model_input (InputData): data instance. Returns: tuple of list of ModelBase, list of Parameters: tuple with two lists. The first list contains all created models, the second list contains corresponding parameters. ''' model_factory.add_input_and_output_categories(params, model_input) rts_type = params.get_parameter_value('RETURN_TO_SCALE') list_of_param_objects = [] original_params = Parameters() original_params.copy_all_params(params) list_of_param_objects.append(original_params) if rts_type == 'both': original_params.update_parameter('RETURN_TO_SCALE', 'VRS') params_with_crs = Parameters() params_with_crs.copy_all_params(original_params) params_with_crs.update_parameter('RETURN_TO_SCALE', 'CRS') list_of_param_objects.append(params_with_crs) orientation_type = original_params.get_parameter_value('ORIENTATION') nb_param_objs = len(list_of_param_objects) if orientation_type == 'both': possible_orientation = ['input', 'output'] for count in range(nb_param_objs): assert(count < 2) param_obj = list_of_param_objects[count] param_obj.update_parameter('ORIENTATION', possible_orientation[count]) new_param_obj = Parameters() new_param_obj.copy_all_params(param_obj) new_param_obj.update_parameter('ORIENTATION', possible_orientation[1 - count]) list_of_param_objects.append(new_param_obj) models = [] for param_object in list_of_param_objects: models.append(model_factory.create_model(param_object, model_input)) return models, list_of_param_objects
def test_peel_the_onion_unbounded(): params = parse_parameters_from_file('tests/params_for_linux.txt') categories, xls_data, dmu_name, sheet_name = read_data( params.get_parameter_value('DATA_FILE')) coefficients, has_same_dmus = convert_to_dictionary(xls_data) assert has_same_dmus is False assert validate_data(categories, coefficients) is True model_input = construct_input_data_instance(categories, coefficients) model_factory.add_input_and_output_categories(params, model_input) model = model_factory.create_model(params, model_input) ranks = None model_solution, ranks, state = peel_the_onion_method(model) assert state is True clean_up_pickled_files()
def test_VRS_from_params_file(): params = parse_parameters_from_file('tests/params_new_format.txt') categories, xls_data, dmu_name, sheet_name = read_data( params.get_parameter_value('DATA_FILE')) coefficients, has_same_dmus = convert_to_dictionary(xls_data) assert has_same_dmus is False assert validate_data(categories, coefficients) is True model_input = construct_input_data_instance(categories, coefficients) model_factory.add_input_and_output_categories(params, model_input) model = model_factory.create_model(params, model_input) model_solution = model.run() utils_for_tests.check_optimal_solution_status_and_sizes( model_solution, model_input) dmus = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K'] utils_for_tests.check_efficiency_scores(dmus, [1, 0.86998617, 1, 0.95561335, 0.85, 1, 1, 0.84507042, 1, 0.524, 0.89058524], model_solution, model_input) clean_up_pickled_files()
def test_peel_the_onion_creation(params, DEA_example_data): params.update_parameter('PEEL_THE_ONION', 'yes') factory.add_input_and_output_categories(params, DEA_example_data) model = factory.create_model(params, DEA_example_data) peel_the_onion_method(model)
def test_categorical_model_creation(params, DEA_example_data): params.update_parameter('CATEGORICAL_CATEGORY', 'I1') model = factory.create_model(params, DEA_example_data) assert model.__class__.__name__ == 'ModelWithCategoricalDMUs'
def test_invalid_dea_form(params, DEA_example_data): params.update_parameter('DEA_FORM', 'invalid') with pytest.raises(ValueError) as excinfo: model = factory.create_model(params, DEA_example_data) assert str(excinfo.value) == 'Invalid value of parameter <DEA_FORM>'
def test_super_efficiency_creation(params, DEA_example_data): params.update_parameter('USE_SUPER_EFFICIENCY', 'yes') model = factory.create_model(params, DEA_example_data) assert model.__class__.__name__ == 'SupperEfficiencyModel'
def test_max_slacks_creation(params, DEA_example_data): params.update_parameter('MAXIMIZE_SLACKS', 'yes') model = factory.create_model(params, DEA_example_data) assert model.__class__.__name__ == 'MaximizeSlacksModel'