def test_add_empty_input_and_output_categories(DEA_example_data):
allParams = Parameters()
allParams.update_parameter('INPUT_CATEGORIES', '')
allParams.update_parameter('OUTPUT_CATEGORIES', 'O1; O2')
with pytest.raises(ValueError) as excinfo:
factory.add_input_and_output_categories(allParams, DEA_example_data)
assert str(
excinfo.value) == 'Both input and output categories must be specified'
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_add_input_and_output_categories(DEA_example_data):
allParams = Parameters()
allParams.update_parameter('INPUT_CATEGORIES', 'I1; I2')
allParams.update_parameter('OUTPUT_CATEGORIES', 'O1; O2')
factory.add_input_and_output_categories(allParams, DEA_example_data)
assert 'I1' in DEA_example_data.input_categories
assert 'I2' in DEA_example_data.input_categories
assert 'O1' in DEA_example_data.output_categories
assert 'O2' in DEA_example_data.output_categories
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 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_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)
