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"])