def test_simulation_add_algorithm_valid(self):
dataset = Dataset('name', 30, 5, 5, 5, [])
simulation = Simulation(dataset=dataset,
n_fes=30,
np=5,
save_to_dir='/notNeeded')
simulation.add_algorithm('GreyWolfOptimizer')
simulation.add_algorithm('GeneticAlgorithm')
added_algorithms = simulation.algorithms()
self.assertEqual('GreyWolfOptimizer', added_algorithms[0])
self.assertEqual('GeneticAlgorithm', added_algorithms[1])
def test_simulation_add_algorithm_none(self):
try:
dataset = Dataset('name', 30, 5, 5, 5, [])
simulation = Simulation(dataset=dataset,
n_fes=30,
np=5,
save_to_dir='/notNeeded')
simulation.add_algorithm(None)
self.fail('None value should not be accepted or ignored')
except InvalidAlgorithmName:
pass
def test_simulation_should_not_start_with_no_save_options(self):
try:
dataset = Dataset('name', 30, 5, 5, 5, [])
simulation = Simulation(dataset=dataset,
n_fes=30,
np=5,
save_to_dir='../results')
simulation.add_algorithm('GreyWolfOptimizer')
simulation.run(sort_by_best=SortAttribute.fitness)
self.fail("Simulation started with no algorithms")
except InvalidSimulationInitialState:
pass
def test_simulation_should_not_start_with_invalid_np(self):
try:
dataset = Dataset('name', 30, 5, 5, 5, [])
simulation = Simulation(dataset=dataset,
n_fes=30,
np=0,
save_to_dir='../results')
simulation.add_algorithm('GreyWolfOptimizer')
simulation.add_save_option(
OutputOptionConfig(class_name='ConsoleOutputOption',
included_kwargs=[]))
simulation.run(sort_by_best=SortAttribute.fitness)
self.fail("Simulation started with no algorithms")
except InvalidSimulationInitialState:
pass
def test_simulation_should_not_start_with_invalid_dir_path(self):
try:
dataset = Dataset('name', 5, 3, 3, 3, [
Package(id_num=1, station_in=1, station_out=2, weight=30),
Package(id_num=2, station_in=2, station_out=3, weight=30),
Package(id_num=3, station_in=1, station_out=3, weight=30),
Package(id_num=4, station_in=2, station_out=3, weight=30),
Package(id_num=5, station_in=1, station_out=2, weight=30)
])
simulation = Simulation(dataset=dataset,
n_fes=30,
np=5,
save_to_dir='../invalidDir')
simulation.add_algorithm('GreyWolfOptimizer')
simulation.add_save_option(
OutputOptionConfig(class_name='ConsoleOutputOption',
included_kwargs=[]))
simulation.run(sort_by_best=SortAttribute.fitness)
self.fail("Simulation started with no algorithms")
except InvalidSimulationInitialState:
pass
try:
config_data = json.load(open(configFile, 'r'))
dataset = CSVDatasetReader().read(config_data['dataset'])
result_dir_path = os.path.join(
config_data['saveToDir'],
datetime.datetime.now().strftime('%Y-%m-%d_%H-%M-%S'))
os.mkdir(path=result_dir_path)
simulation = Simulation(dataset=dataset,
n_fes=config_data['n_fes'],
np=config_data['np'],
save_to_dir=result_dir_path)
for algorithm in config_data['algorithms']:
simulation.add_algorithm(algorithm)
save_opt_configs = [
OutputOptionConfig(class_name=config['class'],
included_kwargs=config['included_kwargs'])
for config in config_data['outputOptions']
]
for output_option in save_opt_configs:
simulation.add_save_option(output_option)
simulation.run(
sort_by_best=SortAttribute[config_data['sortByBest'].lower()])
except Exception as e:
print('Execution stopped with error: {0}'.format(str(e)))