def test_create_swarm(self):
gso_parameters = GSOParameters()
number_of_glowworms = 5
seed = 324324
random_number_generator = MTGenerator(seed)
initializer = LightdockFromFileInitializer(
[self.adapter], [self.scoring_function], number_of_glowworms,
gso_parameters, 7,
self.golden_data_path / 'initial_positions_1PPE.txt', 0.5, 0.5,
random_number_generator, 0.5, 10, 10)
swarm = initializer.generate_glowworms()
assert number_of_glowworms == swarm.get_size()
def test_generate_landscape_positions_num_glowworms_different(self):
gso_parameters = GSOParameters()
number_of_glowworms = 10
seed = 324324
random_number_generator = MTGenerator(seed)
initializer = LightdockFromFileInitializer(
self.adapter, self.scoring_function, number_of_glowworms,
gso_parameters, 7,
self.golden_data_path / 'initial_positions_1PPE.txt', 0.5, 0.5,
random_number_generator, 0.5, 10, 10)
swarm = initializer.generate_glowworms()
assert swarm.get_size() > 0
def create_from_file(self, number_of_glowworms, random_number_generator, gso_parameters,
adapters, scoring_functions, bounding_box, initial_population_file,
step_translation, step_rotation, step_nmodes, local_minimization,
anm_rec, anm_lig):
"""Creates a new GSO instance of the algorithm reading the initial position of the glowworms
agents from initial_population_file and using the scoring function adapter.
"""
self._initializer = LightdockFromFileInitializer(adapters, scoring_functions, number_of_glowworms,
gso_parameters, bounding_box.dimension,
initial_population_file, step_translation, step_rotation,
random_number_generator, step_nmodes, anm_rec, anm_lig)
return GSO(self._initializer.generate_glowworms(), gso_parameters, random_number_generator,
local_minimization=local_minimization)