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Make sample_ method accept instance

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This commit is contained in:
Alinson S. Xavier
2021-04-06 06:48:47 -05:00
parent bb91c83187
commit c6aee4f90d
8 changed files with 91 additions and 72 deletions
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24
tests/components/test_primal.py
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@@ -8,7 +8,7 @@ import numpy as np
from numpy.testing import assert_array_equal
from scipy.stats import randint
from miplearn import Classifier, LearningSolver
from miplearn import Classifier, LearningSolver, Instance
from miplearn.classifiers.threshold import Threshold
from miplearn.components import classifier_evaluation_dict
from miplearn.components.primal import PrimalSolutionComponent
@@ -38,6 +38,8 @@ def test_xy() -> None:
}
}
)
instance = Mock(spec=Instance)
instance.features = features
sample = TrainingSample(
solution={
"x": {
@@ -70,7 +72,7 @@ def test_xy() -> None:
[True, False],
]
}
xy = PrimalSolutionComponent.sample_xy(features, sample)
xy = PrimalSolutionComponent.sample_xy(instance, sample)
assert xy is not None
x_actual, y_actual = xy
assert x_actual == x_expected
@@ -99,6 +101,8 @@ def test_xy_without_lp_solution() -> None:
}
}
)
instance = Mock(spec=Instance)
instance.features = features
sample = TrainingSample(
solution={
"x": {
@@ -123,7 +127,7 @@ def test_xy_without_lp_solution() -> None:
[True, False],
]
}
xy = PrimalSolutionComponent.sample_xy(features, sample)
xy = PrimalSolutionComponent.sample_xy(instance, sample)
assert xy is not None
x_actual, y_actual = xy
assert x_actual == x_expected
@@ -161,6 +165,8 @@ def test_predict() -> None:
}
}
)
instance = Mock(spec=Instance)
instance.features = features
sample = TrainingSample(
lp_solution={
"x": {
@@ -170,11 +176,11 @@ def test_predict() -> None:
}
}
)
x, _ = PrimalSolutionComponent.sample_xy(features, sample)
x, _ = PrimalSolutionComponent.sample_xy(instance, sample)
comp = PrimalSolutionComponent()
comp.classifiers = {"default": clf}
comp.thresholds = {"default": thr}
solution_actual = comp.sample_predict(features, sample)
solution_actual = comp.sample_predict(instance, sample)
clf.predict_proba.assert_called_once()
assert_array_equal(x["default"], clf.predict_proba.call_args[0][0])
thr.predict.assert_called_once()
@@ -243,7 +249,7 @@ def test_evaluate() -> None:
4: 1.0,
}
}
features = Features(
features: Features = Features(
variables={
"x": {
0: VariableFeatures(),
@@ -254,7 +260,9 @@ def test_evaluate() -> None:
}
}
)
sample = TrainingSample(
instance = Mock(spec=Instance)
instance.features = features
sample: TrainingSample = TrainingSample(
solution={
"x": {
0: 1.0,
@@ -265,7 +273,7 @@ def test_evaluate() -> None:
}
}
)
ev = comp.sample_evaluate(features, sample)
ev = comp.sample_evaluate(instance, sample)
assert ev == {
0: classifier_evaluation_dict(tp=1, fp=1, tn=3, fn=0),
1: classifier_evaluation_dict(tp=2, fp=0, tn=1, fn=2),