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Update DynamicLazyConstraintsComponent

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This commit is contained in:
Alinson S. Xavier
2021-04-13 08:42:06 -05:00
parent b5411b8950
commit a4433916e5
8 changed files with 144 additions and 63 deletions
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77
tests/components/test_dynamic_lazy.py
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@@ -83,15 +83,20 @@ def training_instances() -> List[Instance]:
instances = [cast(Instance, Mock(spec=Instance)) for _ in range(2)]
instances[0].samples = [
Sample(
after_lp=Features(
instance=InstanceFeatures(),
),
after_lp=Features(instance=InstanceFeatures()),
after_mip=Features(extra={"lazy_enforced": {"c1", "c2"}}),
)
),
Sample(
after_lp=Features(instance=InstanceFeatures()),
after_mip=Features(extra={"lazy_enforced": {"c2", "c3"}}),
),
]
instances[0].samples[0].after_lp.instance.to_list = Mock( # type: ignore
return_value=[5.0]
)
instances[0].samples[1].after_lp.instance.to_list = Mock( # type: ignore
return_value=[5.0]
)
instances[0].get_constraint_category = Mock( # type: ignore
side_effect=lambda cid: {
"c1": "type-a",
@@ -108,7 +113,30 @@ def training_instances() -> List[Instance]:
"c4": [3.0, 4.0],
}[cid]
)
instances[1].samples = [
Sample(
after_lp=Features(instance=InstanceFeatures()),
after_mip=Features(extra={"lazy_enforced": {"c3", "c4"}}),
)
]
instances[1].samples[0].after_lp.instance.to_list = Mock( # type: ignore
return_value=[8.0]
)
instances[1].get_constraint_category = Mock( # type: ignore
side_effect=lambda cid: {
"c1": None,
"c2": "type-a",
"c3": "type-b",
"c4": "type-b",
}[cid]
)
instances[1].get_constraint_features = Mock( # type: ignore
side_effect=lambda cid: {
"c2": [7.0, 8.0, 9.0],
"c3": [5.0, 6.0],
"c4": [7.0, 8.0],
}[cid]
)
return instances
@@ -131,11 +159,11 @@ def test_sample_xy(training_instances: List[Instance]) -> None:
assert_equals(y_actual, y_expected)
def test_fit_old(training_instances_old: List[Instance]) -> None:
def test_fit(training_instances: List[Instance]) -> None:
clf = Mock(spec=Classifier)
clf.clone = Mock(side_effect=lambda: Mock(spec=Classifier))
comp = DynamicLazyConstraintsComponent(classifier=clf)
comp.fit_old(training_instances_old)
comp.fit(training_instances)
assert clf.clone.call_count == 2
assert "type-a" in comp.classifiers
@@ -145,11 +173,11 @@ def test_fit_old(training_instances_old: List[Instance]) -> None:
clf_a.fit.call_args[0][0], # type: ignore
np.array(
[
[50.0, 1.0, 2.0, 3.0],
[50.0, 4.0, 5.0, 6.0],
[50.0, 1.0, 2.0, 3.0],
[50.0, 4.0, 5.0, 6.0],
[80.0, 7.0, 8.0, 9.0],
[5.0, 1.0, 2.0, 3.0],
[5.0, 4.0, 5.0, 6.0],
[5.0, 1.0, 2.0, 3.0],
[5.0, 4.0, 5.0, 6.0],
[8.0, 7.0, 8.0, 9.0],
]
),
)
@@ -173,12 +201,12 @@ def test_fit_old(training_instances_old: List[Instance]) -> None:
clf_b.fit.call_args[0][0], # type: ignore
np.array(
[
[50.0, 1.0, 2.0],
[50.0, 3.0, 4.0],
[50.0, 1.0, 2.0],
[50.0, 3.0, 4.0],
[80.0, 5.0, 6.0],
[80.0, 7.0, 8.0],
[5.0, 1.0, 2.0],
[5.0, 3.0, 4.0],
[5.0, 1.0, 2.0],
[5.0, 3.0, 4.0],
[8.0, 5.0, 6.0],
[8.0, 7.0, 8.0],
]
),
)
@@ -197,7 +225,7 @@ def test_fit_old(training_instances_old: List[Instance]) -> None:
)
def test_sample_predict_evaluate_old(training_instances_old: List[Instance]) -> None:
def test_sample_predict_evaluate(training_instances: List[Instance]) -> None:
comp = DynamicLazyConstraintsComponent()
comp.known_cids.extend(["c1", "c2", "c3", "c4"])
comp.thresholds["type-a"] = MinProbabilityThreshold([0.5, 0.5])
@@ -211,15 +239,14 @@ def test_sample_predict_evaluate_old(training_instances_old: List[Instance]) ->
side_effect=lambda _: np.array([[0.9, 0.1], [0.1, 0.9]])
)
pred = comp.sample_predict(
training_instances_old[0],
training_instances_old[0].training_data[0],
training_instances[0],
training_instances[0].samples[0],
)
assert pred == ["c1", "c4"]
ev = comp.sample_evaluate_old(
training_instances_old[0],
training_instances_old[0].training_data[0],
ev = comp.sample_evaluate(
training_instances[0],
training_instances[0].samples[0],
)
print(ev)
assert ev == {
"type-a": classifier_evaluation_dict(tp=1, fp=0, tn=0, fn=1),
"type-b": classifier_evaluation_dict(tp=0, fp=1, tn=1, fn=0),