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Make xy_sample receive features, not instances

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Alinson S. Xavier
2021-03-31 09:57:57 -05:00
parent 8fc9979b37
commit fe7bad885c
12 changed files with 158 additions and 119 deletions
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84
tests/components/test_primal.py
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@@ -1,22 +1,22 @@
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
from typing import cast, List
from unittest.mock import Mock, call
from typing import cast
from unittest.mock import Mock
import numpy as np
from numpy.testing import assert_array_equal
from miplearn import Classifier
from miplearn.classifiers.threshold import Threshold, MinPrecisionThreshold
from miplearn.classifiers.threshold import Threshold
from miplearn.components.primal import PrimalSolutionComponent
from miplearn.instance import Instance
from miplearn.types import TrainingSample
from miplearn.types import TrainingSample, Features
def test_xy_sample_with_lp_solution() -> None:
instance = cast(Instance, Mock(spec=Instance))
instance.features = {
features: Features = {
"Variables": {
"x": {
0: {
@@ -56,34 +56,28 @@ def test_xy_sample_with_lp_solution() -> None:
},
}
x_expected = {
"default": np.array(
[
[0.0, 0.0, 0.1],
[1.0, 0.0, 0.1],
[1.0, 1.0, 0.1],
]
)
"default": [
[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],
]
)
"default": [
[True, False],
[False, True],
[True, False],
]
}
x_actual, y_actual = PrimalSolutionComponent.xy_sample(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"])
xy = PrimalSolutionComponent.xy_sample(features, sample)
assert xy is not None
x_actual, y_actual = xy
assert x_actual == x_expected
assert y_actual == y_expected
def test_xy_sample_without_lp_solution() -> None:
comp = PrimalSolutionComponent()
instance = cast(Instance, Mock(spec=Instance))
instance.features = {
features: Features = {
"Variables": {
"x": {
0: {
@@ -115,28 +109,24 @@ def test_xy_sample_without_lp_solution() -> None:
},
}
x_expected = {
"default": np.array(
[
[0.0, 0.0],
[1.0, 0.0],
[1.0, 1.0],
]
)
"default": [
[0.0, 0.0],
[1.0, 0.0],
[1.0, 1.0],
]
}
y_expected = {
"default": np.array(
[
[True, False],
[False, True],
[True, False],
]
)
"default": [
[True, False],
[False, True],
[True, False],
]
}
x_actual, y_actual = comp.xy_sample(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"])
xy = PrimalSolutionComponent.xy_sample(features, sample)
assert xy is not None
x_actual, y_actual = xy
assert x_actual == x_expected
assert y_actual == y_expected
def test_predict() -> None: