class ObjectiveTest(TestCase):
def setUp(self):
self.metrics = {
"m1": Metric(name="m1"),
"m2": Metric(name="m2", lower_is_better=True),
"m3": Metric(name="m3", lower_is_better=False),
}
self.objective = Objective(metric=self.metrics["m1"], minimize=False)
self.multi_objective = MultiObjective(metrics=[
self.metrics["m1"], self.metrics["m2"], self.metrics["m3"]
])
self.scalarized_objective = ScalarizedObjective(
metrics=[self.metrics["m1"], self.metrics["m2"]])
def testBadInit(self):
with self.assertRaises(ValueError):
self.scalarized_objective_weighted = ScalarizedObjective(
metrics=[self.metrics["m1"], self.metrics["m2"]],
weights=[1.0])
def testMultiObjective(self):
with self.assertRaises(NotImplementedError):
return self.multi_objective.metric
self.assertEqual(self.multi_objective.metrics,
list(self.metrics.values()))
weights = [mw[1] for mw in self.multi_objective.metric_weights]
self.assertEqual(weights, [1.0, -1.0, 1.0])
self.assertEqual(self.multi_objective.clone(), self.multi_objective)
self.assertEqual(
str(self.multi_objective),
"MultiObjective(metric_names=['m1', 'm2', 'm3'], minimize=False)",
)
def testScalarizedObjective(self):
with self.assertRaises(NotImplementedError):
return self.scalarized_objective.metric
self.assertEqual(self.scalarized_objective.metrics,
[self.metrics["m1"], self.metrics["m2"]])
weights = [mw[1] for mw in self.scalarized_objective.metric_weights]
self.assertEqual(weights, [1.0, 1.0])
self.assertEqual(self.scalarized_objective.clone(),
self.scalarized_objective)
self.assertEqual(
str(self.scalarized_objective),
("ScalarizedObjective(metric_names=['m1', 'm2'], weights=[1.0, 1.0], "
"minimize=False)"),
)
class ObjectiveTest(TestCase):
def setUp(self):
self.metrics = {
"m1": Metric(name="m1"),
"m2": Metric(name="m2", lower_is_better=True),
"m3": Metric(name="m3", lower_is_better=False),
}
self.objective = Objective(metric=self.metrics["m1"], minimize=False)
self.multi_objective = MultiObjective(metrics=[
self.metrics["m1"], self.metrics["m2"], self.metrics["m3"]
])
self.scalarized_objective = ScalarizedObjective(
metrics=[self.metrics["m1"], self.metrics["m2"]])
def testInit(self):
with self.assertRaises(ValueError):
ScalarizedObjective(
metrics=[self.metrics["m1"], self.metrics["m2"]],
weights=[1.0])
warnings.resetwarnings()
warnings.simplefilter("always", append=True)
with warnings.catch_warnings(record=True) as ws:
Objective(metric=self.metrics["m1"])
self.assertTrue(
any(issubclass(w.category, DeprecationWarning) for w in ws))
self.assertTrue(
any("Defaulting to `minimize=False`" in str(w.message)
for w in ws))
with warnings.catch_warnings(record=True) as ws:
Objective(Metric(name="m4", lower_is_better=True), minimize=False)
self.assertTrue(
any("Attempting to maximize" in str(w.message) for w in ws))
with warnings.catch_warnings(record=True) as ws:
Objective(Metric(name="m4", lower_is_better=False), minimize=True)
self.assertTrue(
any("Attempting to minimize" in str(w.message) for w in ws))
self.assertEqual(self.objective.get_unconstrainable_metrics(),
[self.metrics["m1"]])
def testMultiObjective(self):
with self.assertRaises(NotImplementedError):
return self.multi_objective.metric
self.assertEqual(self.multi_objective.metrics,
list(self.metrics.values()))
weights = [mw[1] for mw in self.multi_objective.metric_weights]
self.assertEqual(weights, [1.0, -1.0, 1.0])
self.assertEqual(self.multi_objective.clone(), self.multi_objective)
self.assertEqual(
str(self.multi_objective),
"MultiObjective(metric_names=['m1', 'm2', 'm3'], minimize=False)",
)
self.assertEqual(self.multi_objective.get_unconstrainable_metrics(),
[])
def testScalarizedObjective(self):
with self.assertRaises(NotImplementedError):
return self.scalarized_objective.metric
self.assertEqual(self.scalarized_objective.metrics,
[self.metrics["m1"], self.metrics["m2"]])
weights = [mw[1] for mw in self.scalarized_objective.metric_weights]
self.assertEqual(weights, [1.0, 1.0])
self.assertEqual(self.scalarized_objective.clone(),
self.scalarized_objective)
self.assertEqual(
str(self.scalarized_objective),
("ScalarizedObjective(metric_names=['m1', 'm2'], weights=[1.0, 1.0], "
"minimize=False)"),
)
self.assertEqual(
self.scalarized_objective.get_unconstrainable_metrics(), [])
