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Allow user to attach arbitrary data to violations

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This commit is contained in:
Alinson S. Xavier
2022-01-25 11:39:03 -06:00
parent ba8f5bb2f4
commit 2a76dd42ec
12 changed files with 168 additions and 127 deletions
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31
tests/components/test_dynamic_lazy.py
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@@ -10,6 +10,7 @@ import pytest
from miplearn.classifiers import Classifier
from miplearn.classifiers.threshold import MinProbabilityThreshold
from miplearn.components import classifier_evaluation_dict
from miplearn.components.dynamic_common import DynamicConstraintsComponent
from miplearn.components.dynamic_lazy import DynamicLazyConstraintsComponent
from miplearn.features.sample import MemorySample
from miplearn.instance.base import Instance
@@ -24,13 +25,23 @@ def training_instances() -> List[Instance]:
samples_0 = [
MemorySample(
{
"mip_constr_lazy_enforced": np.array(["c1", "c2"], dtype="S"),
"mip_constr_lazy": DynamicConstraintsComponent.encode(
{
b"c1": 0,
b"c2": 0,
}
),
"static_instance_features": np.array([5.0]),
},
),
MemorySample(
{
"mip_constr_lazy_enforced": np.array(["c2", "c3"], dtype="S"),
"mip_constr_lazy": DynamicConstraintsComponent.encode(
{
b"c2": 0,
b"c3": 0,
}
),
"static_instance_features": np.array([5.0]),
},
),
@@ -55,7 +66,12 @@ def training_instances() -> List[Instance]:
samples_1 = [
MemorySample(
{
"mip_constr_lazy_enforced": np.array(["c3", "c4"], dtype="S"),
"mip_constr_lazy": DynamicConstraintsComponent.encode(
{
b"c3": 0,
b"c4": 0,
}
),
"static_instance_features": np.array([8.0]),
},
)
@@ -83,8 +99,8 @@ def test_sample_xy(training_instances: List[Instance]) -> None:
comp = DynamicLazyConstraintsComponent()
comp.pre_fit(
[
np.array(["c1", "c3", "c4"], dtype="S"),
np.array(["c1", "c2", "c4"], dtype="S"),
{b"c1": 0, b"c3": 0, b"c4": 0},
{b"c1": 0, b"c2": 0, b"c4": 0},
]
)
x_expected = {
@@ -105,7 +121,10 @@ def test_sample_xy(training_instances: List[Instance]) -> None:
def test_sample_predict_evaluate(training_instances: List[Instance]) -> None:
comp = DynamicLazyConstraintsComponent()
comp.known_cids.extend([b"c1", b"c2", b"c3", b"c4"])
comp.known_violations[b"c1"] = 0
comp.known_violations[b"c2"] = 0
comp.known_violations[b"c3"] = 0
comp.known_violations[b"c4"] = 0
comp.thresholds[b"type-a"] = MinProbabilityThreshold([0.5, 0.5])
comp.thresholds[b"type-b"] = MinProbabilityThreshold([0.5, 0.5])
comp.classifiers[b"type-a"] = Mock(spec=Classifier)