def test_bo_gp_mcmc_model():
domain = Domain({"x": [-1., 6.]})
bayes_opt = bo.BayesianOptimization(domain=domain, seed=7)
test_utils.evaluate_continuous_1d(bayes_opt,
batch_size=1,
n_steps=7,
model="GP_MCMC",
evaluator_type="sequential")
def test_bo_simple_mixed():
domain = Domain({"x": [-5., 6.], "y": {"sin", "sqr"}, "z": set(range(4))})
bayes_opt = bo.BayesianOptimization(domain=domain, seed=7)
test_utils.evaluate_heterogeneous_3d(bayes_opt, batch_size=7, n_steps=3)
def test_bo_simple_continuous():
domain = Domain({"x": [-1., 6.]})
bayes_opt = bo.BayesianOptimization(domain=domain, seed=7)
test_utils.evaluate_continuous_1d(bayes_opt, batch_size=2, n_steps=7)