def evolution_customer_mutate(space1):
"""Return an instance of EvolutionES."""
return EvolutionES(
space1,
repetitions=1,
nums_population=4,
mutate="orion.core.utils.tests.customized_mutate_example",
)
def test_customized_mutate_population(space1, rung_3, budgets):
"""Verify customized mutated candidates is generated correctly."""
customerized_dict = {
"function": "orion.testing.state.customized_mutate_example",
"multiply_factor": 2.0,
"add_factor": 1,
}
algo = EvolutionES(
space1, repetitions=1, nums_population=4, mutate=customerized_dict
)
algo.brackets[0] = BracketEVES(algo, budgets, 1, space1)
red_team = [0, 2]
blue_team = [1, 3]
population_range = 4
for i in range(4):
for j in [1, 2]:
algo.brackets[0].eves.population[j][i] = list(rung_3["results"].values())[
i
][1][j]
algo.brackets[0].eves.performance[i] = list(rung_3["results"].values())[i][0]
org_data = np.stack(
(
list(algo.brackets[0].eves.population.values())[0],
list(algo.brackets[0].eves.population.values())[1],
),
axis=0,
).T
org_data = copy.deepcopy(org_data)
algo.brackets[0]._mutate_population(
red_team, blue_team, rung_3["results"], population_range
)
mutated_data = np.stack(
(
list(algo.brackets[0].eves.population.values())[0],
list(algo.brackets[0].eves.population.values())[1],
),
axis=0,
).T
# Winner team will be [0, 2], so [0, 2] will be remained, [1, 3] will be mutated.
assert org_data.shape == mutated_data.shape
assert (mutated_data[0] == org_data[0]).all()
assert (mutated_data[2] == org_data[2]).all()
assert (mutated_data[1] != org_data[1]).any()
assert (mutated_data[3] != org_data[3]).any()
assert (mutated_data[1] != org_data[0]).any()
assert (mutated_data[3] != org_data[2]).any()
# For each individual, mutation occurs in only one dimension chosen from two.
# Customized test mutation function is divided by 2 for real type.
if mutated_data[1][0] == org_data[0][0] / customerized_dict["multiply_factor"]:
assert mutated_data[1][1] == org_data[0][1]
else:
assert (
mutated_data[1][1] == org_data[0][1] / customerized_dict["multiply_factor"]
)
if mutated_data[3][0] == org_data[2][0] / customerized_dict["multiply_factor"]:
assert mutated_data[3][1] == org_data[2][1]
else:
assert (
mutated_data[3][1] == org_data[2][1] / customerized_dict["multiply_factor"]
)
def evolution(space1):
"""Return an instance of EvolutionES."""
return EvolutionES(space1, repetitions=1, nums_population=4)
def test_customized_mutate_population(
space1: Space, rung_3: RungDict, budgets: list[BudgetTuple]
):
"""Verify customized mutated candidates is generated correctly."""
customerized_dict = {
"function": "orion.testing.algo.customized_mutate_example",
"multiply_factor": 2.0,
"add_factor": 1,
}
population_range = len(rung_3["results"])
algo = EvolutionES(
space1,
repetitions=1,
nums_population=population_range,
mutate=customerized_dict,
)
algo.brackets[0] = BracketEVES(algo, budgets, 1)
red_team = [0, 2]
blue_team = [1, 3]
rung_trials = list(rung_3["results"].values())
for trial_index in range(population_range):
objective, trial = rung_trials[trial_index]
algo.performance[trial_index] = objective
for ith_dim in [1, 2]:
algo.population[ith_dim][trial_index] = trial.params[
algo.space[ith_dim].name
]
org_data = np.stack(
(
list(algo.brackets[0].owner.population.values())[0],
list(algo.brackets[0].owner.population.values())[1],
),
axis=0,
).T
org_data = copy.deepcopy(org_data)
algo.brackets[0]._mutate_population(
red_team, blue_team, rung_3["results"], population_range, fidelity=2
)
mutated_data = np.stack(
(
list(algo.brackets[0].owner.population.values())[0],
list(algo.brackets[0].owner.population.values())[1],
),
axis=0,
).T
# Winner team will be [0, 2], so [0, 2] will be remained, [1, 3] will be mutated.
assert org_data.shape == mutated_data.shape
assert (mutated_data[0] == org_data[0]).all()
assert (mutated_data[2] == org_data[2]).all()
assert (mutated_data[1] != org_data[1]).any()
assert (mutated_data[3] != org_data[3]).any()
assert (mutated_data[1] != org_data[0]).any()
assert (mutated_data[3] != org_data[2]).any()
# For each individual, mutation occurs in only one dimension chosen from two.
# Customized test mutation function is divided by 2 for real type.
if mutated_data[1][0] == org_data[0][0] / customerized_dict["multiply_factor"]:
assert mutated_data[1][1] == org_data[0][1]
else:
assert (
mutated_data[1][1] == org_data[0][1] / customerized_dict["multiply_factor"]
)
if mutated_data[3][0] == org_data[2][0] / customerized_dict["multiply_factor"]:
assert mutated_data[3][1] == org_data[2][1]
else:
assert (
mutated_data[3][1] == org_data[2][1] / customerized_dict["multiply_factor"]
)