def test_init(self):
#test default parameters
exp = Experiment("test", {"x": MinMaxNumericParamDef(0, 1)})
opt = BayesianOptimizer(exp)
assert_equal(opt.initial_random_runs, 10)
assert_is_none(opt.acquisition_hyperparams)
assert_equal(opt.num_gp_restarts, 10)
assert_true(isinstance(opt.acquisition_function, ExpectedImprovement))
assert_dict_equal(opt.kernel_params, {})
assert_equal(opt.kernel, "matern52")
#test correct initialization
opt_arguments = {
"initial_random_runs": 5,
"acquisition_hyperparams": {},
"num_gp_restarts": 5,
"acquisition": ProbabilityOfImprovement,
"kernel_params": {},
"kernel": "matern52",
"mcmc": True,
}
opt = BayesianOptimizer(exp, opt_arguments)
assert_equal(opt.initial_random_runs, 5)
assert_dict_equal(opt.acquisition_hyperparams, {})
assert_equal(opt.num_gp_restarts, 5)
assert_true(
isinstance(opt.acquisition_function, ProbabilityOfImprovement))
assert_dict_equal(opt.kernel_params, {})
assert_equal(opt.kernel, "matern52")
def test_get_next_candidate(self):
exp = Experiment("test", {"x": MinMaxNumericParamDef(0, 1),
"y": NominalParamDef(["A", "B", "C"])})
opt = BayesianOptimizer(exp, {"initial_random_runs": 3})
for i in range(5):
cand = opt.get_next_candidates()[0]
assert_true(isinstance(cand, Candidate))
cand.result = 2
exp.add_finished(cand)
opt.update(exp)
cands = opt.get_next_candidates(num_candidates=3)
assert_less_equal(len(cands), 3)
def test_EI(self):
exp = Experiment("test", {"x": MinMaxNumericParamDef(0, 1)})
opt = BayesianOptimizer(exp, {
"initial_random_runs": 3,
"max_searcher": "LBFGSB"
})
for i in range(3):
cands = opt.get_next_candidates(2)
cand_one = cands[0]
cand_two = cands[1]
assert_true(isinstance(cand_one, Candidate))
cand_one.result = 2
exp.add_finished(cand_one)
opt.update(exp)
assert_true(isinstance(cand_two, Candidate))
cand_two.result = 2
exp.add_finished(cand_two)
opt.update(exp)
cands = opt.get_next_candidates(num_candidates=5)
assert_equal(len(cands), 5)
opt.acquisition_function.params["multi_searcher"] = "random_best"
cands = opt.get_next_candidates(2)
def test_EI(self):
exp = Experiment("test", {"x": MinMaxNumericParamDef(0, 1)})
opt = BayesianOptimizer(exp, {"initial_random_runs": 3, "max_searcher": "LBFGSB"})
for i in range(3):
cands = opt.get_next_candidates(2)
cand_one = cands[0]
cand_two = cands[1]
assert_true(isinstance(cand_one, Candidate))
cand_one.result = 2
exp.add_finished(cand_one)
opt.update(exp)
assert_true(isinstance(cand_two, Candidate))
cand_two.result = 2
exp.add_finished(cand_two)
opt.update(exp)
cands = opt.get_next_candidates(num_candidates=5)
assert_equal(len(cands), 5)
opt.acquisition_function.params["multi_searcher"] = "random_best"
cands = opt.get_next_candidates(2)
def test_get_next_candidate(self):
exp = Experiment(
"test", {
"x": MinMaxNumericParamDef(0, 1),
"y": NominalParamDef(["A", "B", "C"])
})
opt = BayesianOptimizer(exp, {"initial_random_runs": 3})
for i in range(5):
cand = opt.get_next_candidates()[0]
assert_true(isinstance(cand, Candidate))
cand.result = 2
exp.add_finished(cand)
opt.update(exp)
cands = opt.get_next_candidates(num_candidates=3)
assert_less_equal(len(cands), 3)
def test_PoI(self):
exp = Experiment("test", {"x": MinMaxNumericParamDef(0, 1)})
opt = BayesianOptimizer(exp, {"initial_random_runs": 3, "acquisition": ProbabilityOfImprovement})
assert_true(isinstance(opt.acquisition_function, ProbabilityOfImprovement))
for i in range(3):
cands = opt.get_next_candidates(2)
cand_one = cands[0]
cand_two = cands[1]
assert_true(isinstance(cand_one, Candidate))
cand_one.result = 2
exp.add_finished(cand_one)
opt.update(exp)
assert_true(isinstance(cand_two, Candidate))
cand_two.result = 2
exp.add_finished(cand_two)
opt.update(exp)
cands = opt.get_next_candidates(num_candidates=3)
assert_equal(len(cands), 3)
def test_PoI(self):
exp = Experiment("test", {"x": MinMaxNumericParamDef(0, 1)})
opt = BayesianOptimizer(exp, {
"initial_random_runs": 3,
"acquisition": ProbabilityOfImprovement
})
assert_true(
isinstance(opt.acquisition_function, ProbabilityOfImprovement))
for i in range(3):
cands = opt.get_next_candidates(2)
cand_one = cands[0]
cand_two = cands[1]
assert_true(isinstance(cand_one, Candidate))
cand_one.result = 2
exp.add_finished(cand_one)
opt.update(exp)
assert_true(isinstance(cand_two, Candidate))
cand_two.result = 2
exp.add_finished(cand_two)
opt.update(exp)
cands = opt.get_next_candidates(num_candidates=3)
assert_equal(len(cands), 3)
