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MIPLearn/tests/test_features.py

57 lines
2.0 KiB

# 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 miplearn import GurobiSolver
from miplearn.features import FeaturesExtractor
from miplearn.types import VariableFeatures, InstanceFeatures
from tests.fixtures.knapsack import get_knapsack_instance
def test_knapsack() -> None:
for solver_factory in [GurobiSolver]:
solver = solver_factory()
instance = get_knapsack_instance(solver)
model = instance.to_model()
solver.set_instance(instance, model)
FeaturesExtractor(solver).extract(instance)
assert instance.features.variables == {
"x": {
0: VariableFeatures(
category="default",
user_features=[23.0, 505.0],
),
1: VariableFeatures(
category="default",
user_features=[26.0, 352.0],
),
2: VariableFeatures(
category="default",
user_features=[20.0, 458.0],
),
3: VariableFeatures(
category="default",
user_features=[18.0, 220.0],
),
}
}
assert instance.features.constraints == {
"eq_capacity": {
"LHS": {
"x[0]": 23.0,
"x[1]": 26.0,
"x[2]": 20.0,
"x[3]": 18.0,
},
"Sense": "<",
"RHS": 67.0,
"Lazy": False,
"Category": "eq_capacity",
"User features": [0.0],
}
}
assert instance.features.instance == InstanceFeatures(
user_features=[67.0, 21.75],
lazy_constraint_count=0,
)