def test_constraint_from_str(self):
with self.assertRaisesRegex(ValueError, "Bound for sum constraint"):
constraint_from_str(
"x1 + x2 <= not_numerical_bound", {"x1": None, "x2": None}
)
with self.assertRaisesRegex(ValueError, "Outcome constraint bound"):
outcome_constraint_from_str("m1 <= not_numerical_bound")
def with_evaluation_function(
parameters: List[TParameterRepresentation],
evaluation_function: TEvaluationFunction,
experiment_name: Optional[str] = None,
objective_name: Optional[str] = None,
minimize: bool = False,
parameter_constraints: Optional[List[str]] = None,
outcome_constraints: Optional[List[str]] = None,
total_trials: int = 20,
arms_per_trial: int = 1,
wait_time: int = 0,
random_seed: Optional[int] = None,
generation_strategy: Optional[GenerationStrategy] = None,
) -> "OptimizationLoop":
"""Constructs a synchronous `OptimizationLoop` using an evaluation
function."""
exp_parameters = [parameter_from_json(p) for p in parameters]
parameter_map = {p.name: p for p in exp_parameters}
experiment = SimpleExperiment(
name=experiment_name,
search_space=SearchSpace(
parameters=exp_parameters,
parameter_constraints=None
if parameter_constraints is None else [
constraint_from_str(c, parameter_map)
for c in parameter_constraints
],
),
objective_name=objective_name,
evaluation_function=evaluation_function,
minimize=minimize,
outcome_constraints=[
outcome_constraint_from_str(c)
for c in (outcome_constraints or [])
],
)
return OptimizationLoop(
experiment=experiment,
total_trials=total_trials,
arms_per_trial=arms_per_trial,
random_seed=random_seed,
wait_time=wait_time,
generation_strategy=generation_strategy,
)
def test_constraint_from_str(self):
with self.assertRaisesRegex(ValueError, "Bound for sum constraint"):
constraint_from_str("x1 + x2 <= not_numerical_bound", {
"x1": None,
"x2": None
})
with self.assertRaisesRegex(ValueError, "Outcome constraint bound"):
outcome_constraint_from_str("m1 <= not_numerical_bound")
three_val_constaint = constraint_from_str(
"x1 + x2 + x3 <= 3",
{
"x1":
RangeParameter(name="x1",
parameter_type=ParameterType.FLOAT,
lower=0.1,
upper=2.0),
"x2":
RangeParameter(name="x2",
parameter_type=ParameterType.FLOAT,
lower=0.1,
upper=2.0),
"x3":
RangeParameter(name="x3",
parameter_type=ParameterType.FLOAT,
lower=0.1,
upper=2.0),
},
)
self.assertEqual([p.name for p in three_val_constaint.parameters],
["x1", "x2", "x3"])
self.assertTrue(three_val_constaint._is_upper_bound)
self.assertEqual(three_val_constaint.bound, 3.0)
with self.assertRaisesRegex(ValueError, "Parameter constraint should"):
constraint_from_str("x1 + x2 + <= 3", {
"x1": None,
"x2": None,
"x3": None
})
with self.assertRaisesRegex(ValueError, "Parameter constraint should"):
constraint_from_str("x1 + x2 + x3 = 3", {
"x1": None,
"x2": None,
"x3": None
})
def test_constraint_from_str(self):
with self.assertRaisesRegex(ValueError, "Bound for the constraint"):
constraint_from_str("x1 + x2 <= not_numerical_bound", {
"x1": None,
"x2": None
})
with self.assertRaisesRegex(ValueError, "Outcome constraint bound"):
outcome_constraint_from_str("m1 <= not_numerical_bound")
three_val_constaint = constraint_from_str(
"x1 + x2 + x3 <= 3",
{
"x1":
RangeParameter(name="x1",
parameter_type=ParameterType.FLOAT,
lower=0.1,
upper=2.0),
"x2":
RangeParameter(name="x2",
parameter_type=ParameterType.FLOAT,
lower=0.1,
upper=2.0),
"x3":
RangeParameter(name="x3",
parameter_type=ParameterType.FLOAT,
lower=0.1,
upper=2.0),
},
)
self.assertEqual(three_val_constaint.bound, 3.0)
with self.assertRaisesRegex(ValueError, "Parameter constraint should"):
constraint_from_str("x1 + x2 + <= 3", {
"x1": None,
"x2": None,
"x3": None
})
with self.assertRaisesRegex(ValueError, "Parameter constraint should"):
constraint_from_str("x1 + x2 + x3 = 3", {
"x1": None,
"x2": None,
"x3": None
})
three_val_constaint2 = constraint_from_str(
"-x1 + 2.1*x2 - 4*x3 <= 3",
{
"x1":
RangeParameter(name="x1",
parameter_type=ParameterType.FLOAT,
lower=0.1,
upper=4.0),
"x2":
RangeParameter(name="x2",
parameter_type=ParameterType.FLOAT,
lower=0.1,
upper=4.0),
"x3":
RangeParameter(name="x3",
parameter_type=ParameterType.FLOAT,
lower=0.1,
upper=4.0),
},
)
self.assertEqual(three_val_constaint2.bound, 3.0)
self.assertEqual(three_val_constaint2.constraint_dict, {
"x1": -1.0,
"x2": 2.1,
"x3": -4.0
})
with self.assertRaisesRegex(ValueError, "Multiplier should be float"):
constraint_from_str("x1 - e*x2 + x3 <= 3", {
"x1": None,
"x2": None,
"x3": None
})
with self.assertRaisesRegex(ValueError,
"A linear constraint should be"):
constraint_from_str("x1 - 2 *x2 + 3 *x3 <= 3", {
"x1": None,
"x2": None,
"x3": None
})
with self.assertRaisesRegex(ValueError,
"A linear constraint should be"):
constraint_from_str("x1 - 2* x2 + 3* x3 <= 3", {
"x1": None,
"x2": None,
"x3": None
})
with self.assertRaisesRegex(ValueError,
"A linear constraint should be"):
constraint_from_str("x1 - 2 * x2 + 3*x3 <= 3", {
"x1": None,
"x2": None,
"x3": None
})