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Add Component.xy and PrimalSolutionComponent.xy

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This commit is contained in:
Alinson S. Xavier
2021-03-30 17:08:10 -05:00
parent 75d1eee424
commit 9266743940
3 changed files with 172 additions and 2 deletions
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117
tests/components/test_primal.py
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@@ -11,6 +11,123 @@ from miplearn import Classifier
from miplearn.classifiers.threshold import Threshold, MinPrecisionThreshold
from miplearn.components.primal import PrimalSolutionComponent
from miplearn.instance import Instance
from miplearn.types import TrainingSample
def test_xy_with_lp_solution() -> None:
comp = PrimalSolutionComponent()
instance = cast(Instance, Mock(spec=Instance))
instance.get_variable_category = Mock( # type: ignore
side_effect=lambda var_name, index: {
0: "default",
1: None,
2: "default",
3: "default",
}[index]
)
instance.get_variable_features = Mock( # type: ignore
side_effect=lambda var, index: {
0: [0.0, 0.0],
1: [0.0, 1.0],
2: [1.0, 0.0],
3: [1.0, 1.0],
}[index]
)
sample: TrainingSample = {
"Solution": {
"x": {
0: 0.0,
1: 1.0,
2: 1.0,
3: 0.0,
}
},
"LP solution": {
"x": {
0: 0.1,
1: 0.1,
2: 0.1,
3: 0.1,
}
},
}
x_expected = {
"default": np.array(
[
[0.0, 0.0, 0.1],
[1.0, 0.0, 0.1],
[1.0, 1.0, 0.1],
]
)
}
y_expected = {
"default": np.array(
[
[True, False],
[False, True],
[True, False],
]
)
}
x_actual, y_actual = comp.xy(instance, sample)
assert len(x_actual.keys()) == 1
assert len(y_actual.keys()) == 1
assert_array_equal(x_actual["default"], x_expected["default"])
assert_array_equal(y_actual["default"], y_expected["default"])
def test_xy_without_lp_solution() -> None:
comp = PrimalSolutionComponent()
instance = cast(Instance, Mock(spec=Instance))
instance.get_variable_category = Mock( # type: ignore
side_effect=lambda var_name, index: {
0: "default",
1: None,
2: "default",
3: "default",
}[index]
)
instance.get_variable_features = Mock( # type: ignore
side_effect=lambda var, index: {
0: [0.0, 0.0],
1: [0.0, 1.0],
2: [1.0, 0.0],
3: [1.0, 1.0],
}[index]
)
sample: TrainingSample = {
"Solution": {
"x": {
0: 0.0,
1: 1.0,
2: 1.0,
3: 0.0,
}
},
}
x_expected = {
"default": np.array(
[
[0.0, 0.0],
[1.0, 0.0],
[1.0, 1.0],
]
)
}
y_expected = {
"default": np.array(
[
[True, False],
[False, True],
[True, False],
]
)
}
x_actual, y_actual = comp.xy(instance, sample)
assert len(x_actual.keys()) == 1
assert len(y_actual.keys()) == 1
assert_array_equal(x_actual["default"], x_expected["default"])
assert_array_equal(y_actual["default"], y_expected["default"])
def test_x_y_fit() -> None: