Rename xy_sample to xy

This commit is contained in:
2021-04-02 06:26:48 -05:00
parent bc8fe4dc98
commit ef556f94f0
8 changed files with 37 additions and 64 deletions

View File

@@ -57,7 +57,7 @@ def test_xy_instance():
instance_2 = Mock(spec=Instance)
instance_2.training_data = ["s3"]
instance_2.features = {}
comp.xy_sample = _xy_sample
comp.xy = _xy_sample
x_expected = {
"category_a": [
[1, 2, 3],

View File

@@ -286,7 +286,7 @@ def test_xy_sample() -> None:
[False, True],
],
}
xy = StaticLazyConstraintsComponent.xy_sample(features, sample)
xy = StaticLazyConstraintsComponent.xy(features, sample)
assert xy is not None
x_actual, y_actual = xy
assert x_actual == x_expected

View File

@@ -125,7 +125,7 @@ def test_xy_sample_with_lp() -> None:
"Lower bound": [[1.0]],
"Upper bound": [[2.0]],
}
xy = ObjectiveValueComponent.xy_sample(features, sample)
xy = ObjectiveValueComponent.xy(features, sample)
assert xy is not None
x_actual, y_actual = xy
assert x_actual == x_expected
@@ -150,7 +150,7 @@ def test_xy_sample_without_lp() -> None:
"Lower bound": [[1.0]],
"Upper bound": [[2.0]],
}
xy = ObjectiveValueComponent.xy_sample(features, sample)
xy = ObjectiveValueComponent.xy(features, sample)
assert xy is not None
x_actual, y_actual = xy
assert x_actual == x_expected

View File

@@ -8,15 +8,14 @@ import numpy as np
from numpy.testing import assert_array_equal
from scipy.stats import randint
from miplearn import Classifier, LearningSolver, GurobiSolver, GurobiPyomoSolver
from miplearn import Classifier, LearningSolver
from miplearn.classifiers.threshold import Threshold
from miplearn.components.primal import PrimalSolutionComponent
from miplearn.problems.tsp import TravelingSalesmanGenerator
from miplearn.types import TrainingSample, Features
from tests.fixtures.knapsack import get_knapsack_instance
def test_xy_sample_with_lp_solution() -> None:
def test_xy() -> None:
features: Features = {
"Variables": {
"x": {
@@ -70,14 +69,14 @@ def test_xy_sample_with_lp_solution() -> None:
[True, False],
]
}
xy = PrimalSolutionComponent.xy_sample(features, sample)
xy = PrimalSolutionComponent.xy(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:
def test_xy_without_lp_solution() -> None:
features: Features = {
"Variables": {
"x": {
@@ -123,7 +122,7 @@ def test_xy_sample_without_lp_solution() -> None:
[True, False],
]
}
xy = PrimalSolutionComponent.xy_sample(features, sample)
xy = PrimalSolutionComponent.xy(features, sample)
assert xy is not None
x_actual, y_actual = xy
assert x_actual == x_expected
@@ -170,7 +169,7 @@ def test_predict() -> None:
}
}
}
x = PrimalSolutionComponent.x_sample(features, sample)
x, _ = PrimalSolutionComponent.xy(features, sample)
comp = PrimalSolutionComponent()
comp.classifiers = {"default": clf}
comp.thresholds = {"default": thr}