def test_acq_with_poi():
util = UtilityFunction(kind="poi", kappa=1.0, xi=1e-4)
episilon = 1e-2
y_max = 2.0
max_arg = acq_max(
util.utility,
GP,
y_max,
bounds=np.array([[0, 1], [0, 1]]),
random_state=ensure_rng(0),
n_iter=200,
)
_, brute_max_arg = brute_force_maximum(MESH, GP, kind='poi', kappa=1.0, xi=1e-4)
assert all(abs(brute_max_arg - max_arg) < episilon)
def test_acq_with_ucb():
util = UtilityFunction(kind="ucb", kappa=1.0, xi=1.0)
episilon = 1e-2
y_max = 2.0
max_arg = acq_max(util.utility,
GP,
y_max,
bounds=np.array([[0, 1], [0, 1]]),
btypes=[float, float],
random_state=ensure_rng(0),
n_iter=20)
_, brute_max_arg = brute_force_maximum(MESH,
GP,
kind='ucb',
kappa=1.0,
xi=1.0)
assert all(abs(brute_max_arg - max_arg) < episilon)
print("Connecting to database...")
database = SQLDatabase("sqlite:///test.db", "my_function", arg_types,
return_type)
print("Checking existing number of evaluations...")
if len(database) < 2: # Check if there are enough existing datapoints
initial_targets = []
for point in initial_points:
target = black_box_function(**point)
database.add((point, target))
print("Creating optimizer and utility function...")
optimizer = BayesianOptimization(f=None, pbounds=pbounds, random_state=1)
utility_funcs = [
UtilityFunction(kind="ucb", kappa=3, xi=1),
...,
]
print("Registering evaluations with optimizer...")
for (point, target) in database:
optimizer.register(point, target)
while True:
try:
points = []
for uf in utility_funcs:
points.append(optimizer.suggest(uf))
create_slurm_job(points)
run_job()