topology_graphs=[stk.cage.FourPlusSix()],
size=population_size,
random_seed=random_seed,
use_cache=True,
)
# #####################################################################
# Selector for selecting the next generation.
# #####################################################################
generation_selector = stk.Sequence(
stk.AboveAverage(duplicate_mols=False),
stk.RemoveMolecules(
remover=stk.AboveAverage(duplicate_mols=False),
selector=stk.Roulette(
duplicate_mols=False,
random_seed=random_seed,
),
),
num_batches=population_size,
)
# #####################################################################
# Selector for selecting parents.
# #####################################################################
crossover_selector = stk.StochasticUniversalSampling(
num_batches=5,
batch_size=2,
duplicate_batches=False,
random_seed=random_seed,
stk.MoleculeRecord(
topology_graph=get_topology_graph(3), ).with_fitness_value(9),
stk.MoleculeRecord(
topology_graph=get_topology_graph(4), ).with_fitness_value(2),
stk.MoleculeRecord(
topology_graph=get_topology_graph(5), ).with_fitness_value(1),
stk.MoleculeRecord(
topology_graph=get_topology_graph(6), ).with_fitness_value(1),
)
@pytest.fixture(
scope='session',
params=(lambda population: CaseData(
selector=stk.RemoveMolecules(
remover=stk.Best(2),
selector=stk.Best(),
),
population=population,
selected=(
stk.Batch(
records=(population[2], ),
fitness_values={population[2]: 2},
key_maker=stk.Inchi(),
),
stk.Batch(
records=(population[3], ),
fitness_values={population[3]: 1},
key_maker=stk.Inchi(),
),
stk.Batch(
records=(population[4], ),
