def test_maximize_slacks_usual_weakly_disposable_vars():
categories, xls_data, dmu_name, sheet_name = read_data(
'tests/DEA_example2_data.xls')
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
data = construct_input_data_instance(categories, coefficients)
data.add_input_category('I1')
data.add_input_category('I2')
data.add_input_category('I3')
data.add_output_category('O1')
data.add_output_category('O2')
model = EnvelopmentModelVRSDecorator(
EnvelopmentModelBase(data,
EnvelopmentModelInputOriented(
generate_upper_bound_for_efficiency_score),
DisposableVarsConstraintCreator(
set(['I2', 'O1']))))
model = MaximizeSlacksModel(model)
start_time = datetime.datetime.now()
model_solution = model.run()
end_time = datetime.datetime.now()
utils_for_tests.check_optimal_solution_status_and_sizes(
model_solution, data)
dmus = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K']
utils_for_tests.check_efficiency_scores(dmus, [1, 0.86998617, 1, 1, 1, 1,
1, 1, 1, 0.6386574, 1],
model_solution, data)
work_book = xlwt.Workbook()
writer = XLSWriter(Parameters(), work_book, datetime.datetime.today(),
(end_time - start_time).total_seconds())
writer.write_data(model_solution)
work_book.save('tests/test_max_slacks_weakly_disp_vars_output.xls')
clean_up_pickled_files()
def test_csv_reader():
categories, data, dmu_name, sheet_name = read_data(
'tests/DEA_example2_data.csv')
coefficients, has_same_dmus = convert_to_dictionary(data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
_validate_csv(categories, coefficients)
def test_VRS_env_input_oriented_weakly_disposable_vars():
categories, xls_data, dmu_name, sheet_name = read_data(
'tests/DEA_example2_data.xls')
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
data = construct_input_data_instance(categories, coefficients)
data.add_input_category('I1')
data.add_input_category('I2')
data.add_input_category('I3')
data.add_output_category('O1')
data.add_output_category('O2')
model = EnvelopmentModelVRSDecorator(
EnvelopmentModelBase(data,
EnvelopmentModelInputOriented(
generate_upper_bound_for_efficiency_score),
DisposableVarsConstraintCreator(
set(['I2', 'O1']))))
model_solution = model.run()
utils_for_tests.check_optimal_solution_status_and_sizes(
model_solution, data)
dmus = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K']
utils_for_tests.check_efficiency_scores(dmus, [1, 0.86998617, 1, 1, 1, 1,
1, 1, 1, 0.6386574, 1],
model_solution,
data)
clean_up_pickled_files()
def test_CRS_env_output_oriented_non_disc_vars():
categories, xls_data, dmu_name, sheet_name = read_data(
'tests/DEA_example_data.xls')
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
data = construct_input_data_instance(categories, coefficients)
data.add_input_category('I1')
data.add_input_category('I2')
data.add_output_category('ND1')
data.add_output_category('O1')
data.add_output_category('O2')
model = EnvelopmentModelBase(
data,
EnvelopmentModelOutputOrientedWithNonDiscVars(
set(['ND1']), generate_lower_bound_for_efficiency_score),
DefaultConstraintCreator())
model_solution = model.run()
utils_for_tests.check_optimal_solution_status_and_sizes(
model_solution, data)
dmus = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K']
utils_for_tests.check_efficiency_scores(dmus, [
1, 1, 1 / 1.1698685, 1, 1 / 2.3749162, 1, 1, 1 / 1.3198374,
1 / 1.2115385, 0.5, 1
], model_solution, data)
clean_up_pickled_files()
def test_csv_reader():
categories, data, dmu_name, sheet_name = read_data(
'tests/DEA_example2_data.csv')
coefficients, has_same_dmus = convert_to_dictionary(data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
_validate_csv(categories, coefficients)
def test_CRS_env_output_oriented_non_disc_vars():
categories, xls_data, dmu_name, sheet_name = read_data(
'tests/DEA_example_data.xls')
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
data = construct_input_data_instance(categories, coefficients)
data.add_input_category('I1')
data.add_input_category('I2')
data.add_output_category('ND1')
data.add_output_category('O1')
data.add_output_category('O2')
model = EnvelopmentModelBase(
data,
EnvelopmentModelOutputOrientedWithNonDiscVars(
set(['ND1']),
generate_lower_bound_for_efficiency_score),
DefaultConstraintCreator())
model_solution = model.run()
utils_for_tests.check_optimal_solution_status_and_sizes(model_solution,
data)
dmus = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K']
utils_for_tests.check_efficiency_scores(dmus, [1, 1, 1 / 1.1698685, 1,
1 / 2.3749162, 1,
1, 1 / 1.3198374,
1 / 1.2115385,
0.5, 1], model_solution,
data)
clean_up_pickled_files()
def test_read_data_from_xls_larger_example():
categories, data, dmu_name, sheet_name = read_data(
'tests/DEA_example2_data.xls')
coefficients, has_same_dmus = convert_to_dictionary(data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
input_data = construct_input_data_instance(categories, coefficients)
assert len(input_data.DMU_codes) == 11
assert len(input_data.categories) == 5
categories = ['I1', 'I2', 'I3', 'O1', 'O2']
for category in categories:
assert category in input_data.categories
assert len(input_data.input_categories) == 0
assert len(input_data.output_categories) == 0
dmus = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K']
for dmu in dmus:
assert dmu in input_data._DMU_user_name_to_code
check_coefficients(input_data, 'A', categories, [5, 13, 1, 12, 34])
check_coefficients(input_data, 'B', categories, [16, 12, 2, 14, 13])
check_coefficients(input_data, 'C', categories, [16, 26, 2, 25, 56])
check_coefficients(input_data, 'D', categories, [17, 15, 3, 26, 23])
check_coefficients(input_data, 'E', categories, [18, 14, 1, 8, 18])
check_coefficients(input_data, 'F', categories, [23, 6, 2, 9, 39])
check_coefficients(input_data, 'G', categories, [25, 10, 2, 27, 21])
check_coefficients(input_data, 'H', categories, [27, 22, 3, 30, 10])
check_coefficients(input_data, 'I', categories, [37, 14, 1, 31, 25])
check_coefficients(input_data, 'J', categories, [42, 25, 2, 26.5, 17])
check_coefficients(input_data, 'K', categories, [5, 17, 3, 12, 37])
def test_price_ratio_restrictions_medium_env_model():
categories, data, dmu_name, sheet_name = read_data(
'tests/dataFromDEAbook_page181.xls')
coefficients, has_same_dmus = convert_to_dictionary(data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
data = construct_input_data_instance(categories, coefficients)
print(data.categories)
data.add_input_category('Doctors')
data.add_input_category('Nurses')
data.add_output_category('Outpatients')
data.add_output_category('Inpatients')
model = MultiplierModelBase(data, 0,
MultiplierInputOrientedModel())
ratio_bounds = {('Nurses', 'Doctors'): (0.2, 5),
('Inpatients', 'Outpatients'): (0.2, 5)}
model = MultiplierModelWithPriceRatioConstraints(model, ratio_bounds)
model_solution = model.run()
utils_for_tests.check_if_category_is_within_price_ratio_constraints(
model_solution, ratio_bounds)
utils_for_tests.check_optimal_solution_status_and_sizes(
model_solution, data)
dmus = ['H1', 'H2', 'H3', 'H4', 'H5', 'H6', 'H7',
'H8', 'H9', 'H10', 'H11', 'H12', 'H13', 'H14']
utils_for_tests.check_efficiency_scores(dmus, [0.926, 1, 1, 0.634, 0.82, 1,
0.803, 0.872, 0.982, 1,
0.849,
0.93, 0.74, 0.929],
model_solution, data, 1e-3)
clean_up_pickled_files()
def test_maximize_slacks_usual_weakly_disposable_vars():
categories, xls_data, dmu_name, sheet_name = read_data(
'tests/DEA_example2_data.xls')
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
data = construct_input_data_instance(categories, coefficients)
data.add_input_category('I1')
data.add_input_category('I2')
data.add_input_category('I3')
data.add_output_category('O1')
data.add_output_category('O2')
model = EnvelopmentModelVRSDecorator(
EnvelopmentModelBase(
data,
EnvelopmentModelInputOriented(
generate_upper_bound_for_efficiency_score),
DisposableVarsConstraintCreator(set(['I2', 'O1']))))
model = MaximizeSlacksModel(model)
start_time = datetime.datetime.now()
model_solution = model.run()
end_time = datetime.datetime.now()
utils_for_tests.check_optimal_solution_status_and_sizes(
model_solution, data)
dmus = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K']
utils_for_tests.check_efficiency_scores(
dmus, [1, 0.86998617, 1, 1, 1, 1, 1, 1, 1, 0.6386574, 1],
model_solution, data)
work_book = xlwt.Workbook()
writer = XLSWriter(Parameters(), work_book, datetime.datetime.today(),
(end_time - start_time).total_seconds())
writer.write_data(model_solution)
work_book.save('tests/test_max_slacks_weakly_disp_vars_output.xls')
clean_up_pickled_files()
def test_VRS_env_output_oriented_weakly_disposable_vars():
categories, xls_data, dmu_name, sheet_name = read_data(
'tests/DEA_example2_data.xls')
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
data = construct_input_data_instance(categories, coefficients)
data.add_input_category('I1')
data.add_input_category('I2')
data.add_input_category('I3')
data.add_output_category('O1')
data.add_output_category('O2')
model = EnvelopmentModelVRSDecorator(
EnvelopmentModelBase(
data,
EnvelopmentModelOutputOriented(
generate_lower_bound_for_efficiency_score),
DisposableVarsConstraintCreator(set(['I3', 'O1']))))
model_solution = model.run()
utils_for_tests.check_optimal_solution_status_and_sizes(
model_solution, data)
dmus = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K']
utils_for_tests.check_efficiency_scores(dmus, [1, 1 / 1.4107143, 1, 1,
1 / 1.821256,
1, 1, 1, 1, 1 / 1.1407407,
1], model_solution, data)
clean_up_pickled_files()
def test_read_data_from_xls_larger_example():
categories, data, dmu_name, sheet_name = read_data(
'tests/DEA_example2_data.xls')
coefficients, has_same_dmus = convert_to_dictionary(data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
input_data = construct_input_data_instance(categories, coefficients)
assert len(input_data.DMU_codes) == 11
assert len(input_data.categories) == 5
categories = ['I1', 'I2', 'I3', 'O1', 'O2']
for category in categories:
assert category in input_data.categories
assert len(input_data.input_categories) == 0
assert len(input_data.output_categories) == 0
dmus = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K']
for dmu in dmus:
assert dmu in input_data._DMU_user_name_to_code
check_coefficients(input_data, 'A', categories, [5, 13, 1, 12, 34])
check_coefficients(input_data, 'B', categories, [16, 12, 2, 14, 13])
check_coefficients(input_data, 'C', categories, [16, 26, 2, 25, 56])
check_coefficients(input_data, 'D', categories, [17, 15, 3, 26, 23])
check_coefficients(input_data, 'E', categories, [18, 14, 1, 8, 18])
check_coefficients(input_data, 'F', categories, [23, 6, 2, 9, 39])
check_coefficients(input_data, 'G', categories, [25, 10, 2, 27, 21])
check_coefficients(input_data, 'H', categories, [27, 22, 3, 30, 10])
check_coefficients(input_data, 'I', categories, [37, 14, 1, 31, 25])
check_coefficients(input_data, 'J', categories,
[42, 25, 2, 26.5, 17])
check_coefficients(input_data, 'K', categories, [5, 17, 3, 12, 37])
def test_order_of_dmus():
categories, xls_data, dmu_name, sheet_name = read_data(
'tests/categorical_test_from_book.xls')
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
data = construct_input_data_instance(categories, coefficients)
dmus = ['L1', 'L2', 'L3', 'L4', 'L5', 'L6', 'L7', 'L8', 'L9',
'L10', 'L11', 'L12',
'L13', 'L14', 'L15', 'L16', 'L17', 'L18', 'L19', 'L20',
'L21', 'L22', 'L23']
for count, dmu in enumerate(dmus):
assert data.DMU_codes_in_added_order[
count] == data._DMU_user_name_to_code[dmu]
def categorical_data(request):
categories, xls_data, dmu_name, sheet_name = read_data(
'tests/categorical_test.xls')
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
request.addfinalizer(clean_up_pickled_files)
return construct_input_data_instance(categories, coefficients)
def categorical_data(request):
categories, xls_data, dmu_name, sheet_name = read_data(
'tests/categorical_test.xls')
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
request.addfinalizer(clean_up_pickled_files)
return construct_input_data_instance(categories, coefficients)
def _construct_params_and_input():
filename = 'tests/params_new_format.txt'
params = parse_parameters_from_file(filename)
categories, data, dmu_name, sheet_name = read_data(
params.get_parameter_value('DATA_FILE'))
coefficients, has_same_dmus = convert_to_dictionary(data)
model_input = construct_input_data_instance(categories, coefficients)
return params, model_input
def _construct_params_and_input():
filename = 'tests/params_new_format.txt'
params = parse_parameters_from_file(filename)
categories, data, dmu_name, sheet_name = read_data(
params.get_parameter_value('DATA_FILE'))
coefficients, has_same_dmus = convert_to_dictionary(data)
model_input = construct_input_data_instance(categories, coefficients)
return params, model_input
def test_order_of_dmus():
categories, xls_data, dmu_name, sheet_name = read_data(
'tests/categorical_test_from_book.xls')
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
data = construct_input_data_instance(categories, coefficients)
dmus = [
'L1', 'L2', 'L3', 'L4', 'L5', 'L6', 'L7', 'L8', 'L9', 'L10', 'L11',
'L12', 'L13', 'L14', 'L15', 'L16', 'L17', 'L18', 'L19', 'L20', 'L21',
'L22', 'L23'
]
for count, dmu in enumerate(dmus):
assert data.DMU_codes_in_added_order[
count] == data._DMU_user_name_to_code[dmu]
def test_with_zero_data():
categories, xls_data, dmu_name, sheet_name = read_data(
'tests/with_zeros.xls')
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
data = construct_input_data_instance(categories, coefficients)
data.add_input_category('rein')
data.add_output_category('aus')
model = MultiplierModelBase(data, 0, MultiplierOutputOrientedModel())
model_solution = model.run()
clean_up_pickled_files()
def test_with_zero_data():
categories, xls_data, dmu_name, sheet_name = read_data(
'tests/with_zeros.xls')
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
data = construct_input_data_instance(categories, coefficients)
data.add_input_category('rein')
data.add_output_category('aus')
model = MultiplierModelBase(data, 0,
MultiplierOutputOrientedModel())
model_solution = model.run()
clean_up_pickled_files()
def categorical_from_book(request):
categories, xls_data, dmu_name, sheet_name = read_data(
'tests/categorical_test_from_book.xls')
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
data = construct_input_data_instance(categories, coefficients)
data.add_input_category('Area')
data.add_input_category('Books')
data.add_input_category('Staff')
data.add_output_category('Regist')
data.add_output_category('Borrow')
request.addfinalizer(clean_up_pickled_files)
return data
def categorical_from_book(request):
categories, xls_data, dmu_name, sheet_name = read_data(
'tests/categorical_test_from_book.xls')
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
data = construct_input_data_instance(categories, coefficients)
data.add_input_category('Area')
data.add_input_category('Books')
data.add_input_category('Staff')
data.add_output_category('Regist')
data.add_output_category('Borrow')
request.addfinalizer(clean_up_pickled_files)
return data
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_read_data_from_xls_numeric_dmus():
categories, xls_data, dmu_name, sheet_name = read_data(
'tests/dataForTestingReadXLS_withNumericDMU.xls')
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
input_data = construct_input_data_instance(categories, coefficients)
assert len(input_data.DMU_codes) == 3
assert len(input_data.categories) == 3
categories = [0, 5, 2]
for category in categories:
assert category in input_data.categories
assert len(input_data.input_categories) == 0
assert len(input_data.output_categories) == 0
dmus = [0, 1, 2]
for dmu in dmus:
assert dmu in input_data._DMU_user_name_to_code
check_coefficients(input_data, 0, categories, [10, 1, 2])
check_coefficients(input_data, 1, categories, [4, 5, 20])
check_coefficients(input_data, 2, categories, [1, 1, 1])
def test_read_data_from_xls_numeric_dmus():
categories, xls_data, dmu_name, sheet_name = read_data(
'tests/dataForTestingReadXLS_withNumericDMU.xls')
coefficients, has_same_dmus = convert_to_dictionary(xls_data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
input_data = construct_input_data_instance(categories, coefficients)
assert len(input_data.DMU_codes) == 3
assert len(input_data.categories) == 3
categories = [0, 5, 2]
for category in categories:
assert category in input_data.categories
assert len(input_data.input_categories) == 0
assert len(input_data.output_categories) == 0
dmus = [0, 1, 2]
for dmu in dmus:
assert dmu in input_data._DMU_user_name_to_code
check_coefficients(input_data, 0, categories, [10, 1, 2])
check_coefficients(input_data, 1, categories, [4, 5, 20])
check_coefficients(input_data, 2, categories, [1, 1, 1])
def test_abs_restrictions_env_model_output(data):
filename = 'tests/DEA_Harish_parameters.txt'
params = parse_parameters_from_file(filename)
categories, data, dmu_name, sheet_name = read_data(
params.get_parameter_value('DATA_FILE'))
coefficients, has_same_dmus = convert_to_dictionary(data)
model_input = construct_input_data_instance(categories, coefficients)
models, all_params = build_models(params, model_input)
assert len(models) == 1 and len(all_params) == 1
model = models[0]
start_time = datetime.datetime.now()
model_solution = model.run()
end_time = datetime.datetime.now()
bounds = {'Urban Roads (%)': (None, 0.003)}
utils_for_tests.check_if_category_is_within_abs_limits(
model_solution, bounds)
work_book = xlwt.Workbook()
writer = XLSWriter(Parameters(), work_book, datetime.datetime.today(),
(end_time - start_time).total_seconds())
writer.write_data(model_solution)
work_book.save('tests/test_abs_constraints_env_outoriented_output.xls')
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_abs_restrictions_env_model_output(data):
filename = 'tests/DEA_Harish_parameters.txt'
params = parse_parameters_from_file(filename)
categories, data, dmu_name, sheet_name = read_data(
params.get_parameter_value('DATA_FILE'))
coefficients, has_same_dmus = convert_to_dictionary(data)
model_input = construct_input_data_instance(categories, coefficients)
models, all_params = build_models(params, model_input)
assert len(models) == 1 and len(all_params) == 1
model = models[0]
start_time = datetime.datetime.now()
model_solution = model.run()
end_time = datetime.datetime.now()
bounds = {'Urban Roads (%)': (None, 0.003)}
utils_for_tests.check_if_category_is_within_abs_limits(
model_solution, bounds)
work_book = Workbook()
writer = XLSWriter(Parameters(), work_book, datetime.datetime.today(),
(end_time - start_time).total_seconds())
writer.write_data(model_solution)
work_book.save('tests/test_abs_constraints_env_outoriented_output.xls')
def helper_func(filename):
categories, data, dmu_name, sheet_name = read_data(filename)
coefficients, has_same_dmus = convert_to_dictionary(data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
input_data = construct_input_data_instance(categories, coefficients)
assert len(input_data.DMU_codes) == 4
assert len(input_data.categories) == 4
categories = ['x1', 'x2', 'input with space', 'output starts with space']
for category in categories:
assert category in input_data.categories
assert len(input_data.input_categories) == 0
assert len(input_data.output_categories) == 0
dmus = ['dmu1', 'dmu2', 'dmu with space', 'space in the beginning']
for dmu in dmus:
assert dmu in input_data._DMU_user_name_to_code
check_coefficients(input_data, 'dmu1', categories, [1, 4, 7, 1])
check_coefficients(input_data, 'dmu2', categories, [9, 5, 7, 7])
check_coefficients(input_data, 'dmu with space', categories,
[5.5, 1, 8, 8])
check_coefficients(input_data, 'space in the beginning', categories,
[45, 9, 10, 7.55])
def helper_func(filename):
categories, data, dmu_name, sheet_name = read_data(filename)
coefficients, has_same_dmus = convert_to_dictionary(data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
input_data = construct_input_data_instance(categories, coefficients)
assert len(input_data.DMU_codes) == 4
assert len(input_data.categories) == 4
categories = ['x1', 'x2', 'input with space', 'output starts with space']
for category in categories:
assert category in input_data.categories
assert len(input_data.input_categories) == 0
assert len(input_data.output_categories) == 0
dmus = ['dmu1', 'dmu2', 'dmu with space', 'space in the beginning']
for dmu in dmus:
assert dmu in input_data._DMU_user_name_to_code
check_coefficients(input_data, 'dmu1', categories, [1, 4, 7, 1])
check_coefficients(input_data, 'dmu2', categories, [9, 5, 7, 7])
check_coefficients(input_data, 'dmu with space',
categories, [5.5, 1, 8, 8])
check_coefficients(input_data, 'space in the beginning',
categories, [45, 9, 10, 7.55])
def test_price_ratio_restrictions_medium_env_model():
categories, data, dmu_name, sheet_name = read_data(
'tests/dataFromDEAbook_page181.xls')
coefficients, has_same_dmus = convert_to_dictionary(data)
assert has_same_dmus is False
assert validate_data(categories, coefficients) is True
data = construct_input_data_instance(categories, coefficients)
print(data.categories)
data.add_input_category('Doctors')
data.add_input_category('Nurses')
data.add_output_category('Outpatients')
data.add_output_category('Inpatients')
model = MultiplierModelBase(data, 0, MultiplierInputOrientedModel())
ratio_bounds = {
('Nurses', 'Doctors'): (0.2, 5),
('Inpatients', 'Outpatients'): (0.2, 5)
}
model = MultiplierModelWithPriceRatioConstraints(model, ratio_bounds)
model_solution = model.run()
utils_for_tests.check_if_category_is_within_price_ratio_constraints(
model_solution, ratio_bounds)
utils_for_tests.check_optimal_solution_status_and_sizes(
model_solution, data)
dmus = [
'H1', 'H2', 'H3', 'H4', 'H5', 'H6', 'H7', 'H8', 'H9', 'H10', 'H11',
'H12', 'H13', 'H14'
]
utils_for_tests.check_efficiency_scores(dmus, [
0.926, 1, 1, 0.634, 0.82, 1, 0.803, 0.872, 0.982, 1, 0.849, 0.93, 0.74,
0.929
], model_solution, data, 1e-3)
clean_up_pickled_files()
def get_coefficients(self):
''' See base class.
'''
return convert_to_dictionary(self.data)
def get_coefficients(self):
''' See base class.
'''
return convert_to_dictionary(self.data)
