def test_optimization_problem():
parameter1 = Parameter(
name="param1", category="categorical", search_space={"values": ["a", "b"]}
)
parameter2 = Parameter(name="param2", category="uniform", search_space={"low": 1, "high": 2})
parameters = [parameter1, parameter2]
optimization_problem = OptimizationProblem(parameters)
observation1 = Observation(sample={"param1": "a", "param2": 1.5}, loss=1.5)
optimization_problem.add_observation(observation1)
observation2 = Observation(sample={"param1": "b", "param2": 1.8}, loss=1.8)
optimization_problem.add_observation(observation2)
observation3 = Observation(sample={"param1": "b", "param2": 1.05}, loss=0.1)
optimization_problem.add_observation(observation3)
assert type(optimization_problem.parameters) == list
assert len(optimization_problem.observations) == 3
assert optimization_problem.parameters_name == set(["param1", "param2"])
assert observation1.sample in optimization_problem.samples
assert len(optimization_problem.samples) == 3
assert optimization_problem.best_sample == {"param1": "b", "param2": 1.05}
assert optimization_problem.sorted_observations[0].sample == {"param1": "b", "param2": 1.05}
assert optimization_problem.finite is False
assert len(optimization_problem.find_observations({"param1": "b", "param2": 1.05})) == 1
a, b = optimization_problem.observations_quantile(0.5)
assert len(a) == 1
assert len(b) == 2
assert optimization_problem.get_best_k_samples(1)[0].sample == {"param1": "b", "param2": 1.05}
def test_optimization_problem_bad_param_type():
with pytest.raises(ValidationError):
OptimizationProblem(["lol"])
