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Rename features.variables to variables_old; update FeatureExtractor

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This commit is contained in:
Alinson S. Xavier
2021-04-15 06:54:27 -05:00
parent 08f0bedbe0
commit fec0113722
9 changed files with 150 additions and 173 deletions
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12
tests/components/test_primal.py
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@@ -28,7 +28,7 @@ def sample() -> Sample:
sample = Sample(
after_load=Features(
instance=InstanceFeatures(),
variables={
variables_old={
"x[0]": Variable(category="default"),
"x[1]": Variable(category=None),
"x[2]": Variable(category="default"),
@@ -36,7 +36,7 @@ def sample() -> Sample:
},
),
after_lp=Features(
variables={
variables_old={
"x[0]": Variable(),
"x[1]": Variable(),
"x[2]": Variable(),
@@ -44,7 +44,7 @@ def sample() -> Sample:
},
),
after_mip=Features(
variables={
variables_old={
"x[0]": Variable(value=0.0),
"x[1]": Variable(value=1.0),
"x[2]": Variable(value=1.0),
@@ -53,13 +53,13 @@ def sample() -> Sample:
),
)
sample.after_load.instance.to_list = Mock(return_value=[5.0]) # type: ignore
sample.after_lp.variables["x[0]"].to_list = Mock( # type: ignore
sample.after_lp.variables_old["x[0]"].to_list = Mock( # type: ignore
return_value=[0.0, 0.0]
)
sample.after_lp.variables["x[2]"].to_list = Mock( # type: ignore
sample.after_lp.variables_old["x[2]"].to_list = Mock( # type: ignore
return_value=[1.0, 0.0]
)
sample.after_lp.variables["x[3]"].to_list = Mock( # type: ignore
sample.after_lp.variables_old["x[3]"].to_list = Mock( # type: ignore
return_value=[1.0, 1.0]
)
return sample

28
tests/problems/test_tsp.py
View File

@@ -43,13 +43,13 @@ def test_instance() -> None:
assert instance.samples[0].after_mip is not None
features = instance.samples[0].after_mip
assert features is not None
assert features.variables is not None
assert features.variables["x[(0, 1)]"].value == 1.0
assert features.variables["x[(0, 2)]"].value == 0.0
assert features.variables["x[(0, 3)]"].value == 1.0
assert features.variables["x[(1, 2)]"].value == 1.0
assert features.variables["x[(1, 3)]"].value == 0.0
assert features.variables["x[(2, 3)]"].value == 1.0
assert features.variables_old is not None
assert features.variables_old["x[(0, 1)]"].value == 1.0
assert features.variables_old["x[(0, 2)]"].value == 0.0
assert features.variables_old["x[(0, 3)]"].value == 1.0
assert features.variables_old["x[(1, 2)]"].value == 1.0
assert features.variables_old["x[(1, 3)]"].value == 0.0
assert features.variables_old["x[(2, 3)]"].value == 1.0
assert features.mip_solve is not None
assert features.mip_solve.mip_lower_bound == 4.0
assert features.mip_solve.mip_upper_bound == 4.0
@@ -79,12 +79,12 @@ def test_subtour() -> None:
lazy_enforced = features.extra["lazy_enforced"]
assert lazy_enforced is not None
assert len(lazy_enforced) > 0
assert features.variables is not None
assert features.variables["x[(0, 1)]"].value == 1.0
assert features.variables["x[(0, 4)]"].value == 1.0
assert features.variables["x[(1, 2)]"].value == 1.0
assert features.variables["x[(2, 3)]"].value == 1.0
assert features.variables["x[(3, 5)]"].value == 1.0
assert features.variables["x[(4, 5)]"].value == 1.0
assert features.variables_old is not None
assert features.variables_old["x[(0, 1)]"].value == 1.0
assert features.variables_old["x[(0, 4)]"].value == 1.0
assert features.variables_old["x[(1, 2)]"].value == 1.0
assert features.variables_old["x[(2, 3)]"].value == 1.0
assert features.variables_old["x[(3, 5)]"].value == 1.0
assert features.variables_old["x[(4, 5)]"].value == 1.0
solver.fit([instance])
solver.solve(instance)

28
tests/solvers/test_learning_solver.py
View File

@@ -39,12 +39,12 @@ def test_learning_solver(
after_mip = sample.after_mip
assert after_mip is not None
assert after_mip.variables is not None
assert after_mip.variables_old is not None
assert after_mip.mip_solve is not None
assert after_mip.variables["x[0]"].value == 1.0
assert after_mip.variables["x[1]"].value == 0.0
assert after_mip.variables["x[2]"].value == 1.0
assert after_mip.variables["x[3]"].value == 1.0
assert after_mip.variables_old["x[0]"].value == 1.0
assert after_mip.variables_old["x[1]"].value == 0.0
assert after_mip.variables_old["x[2]"].value == 1.0
assert after_mip.variables_old["x[3]"].value == 1.0
assert after_mip.mip_solve.mip_lower_bound == 1183.0
assert after_mip.mip_solve.mip_upper_bound == 1183.0
assert after_mip.mip_solve.mip_log is not None
@@ -52,16 +52,16 @@ def test_learning_solver(
after_lp = sample.after_lp
assert after_lp is not None
assert after_lp.variables is not None
assert after_lp.variables_old is not None
assert after_lp.lp_solve is not None
assert after_lp.variables["x[0]"].value is not None
assert after_lp.variables["x[1]"].value is not None
assert after_lp.variables["x[2]"].value is not None
assert after_lp.variables["x[3]"].value is not None
assert round(after_lp.variables["x[0]"].value, 3) == 1.000
assert round(after_lp.variables["x[1]"].value, 3) == 0.923
assert round(after_lp.variables["x[2]"].value, 3) == 1.000
assert round(after_lp.variables["x[3]"].value, 3) == 0.000
assert after_lp.variables_old["x[0]"].value is not None
assert after_lp.variables_old["x[1]"].value is not None
assert after_lp.variables_old["x[2]"].value is not None
assert after_lp.variables_old["x[3]"].value is not None
assert round(after_lp.variables_old["x[0]"].value, 3) == 1.000
assert round(after_lp.variables_old["x[1]"].value, 3) == 0.923
assert round(after_lp.variables_old["x[2]"].value, 3) == 1.000
assert round(after_lp.variables_old["x[3]"].value, 3) == 0.000
assert after_lp.lp_solve.lp_value is not None
assert round(after_lp.lp_solve.lp_value, 3) == 1287.923
assert after_lp.lp_solve.lp_log is not None

135
tests/test_features.py
View File

@@ -7,9 +7,15 @@ from miplearn.features import (
InstanceFeatures,
Variable,
Constraint,
VariableFeatures,
)
from miplearn.solvers.gurobi import GurobiSolver
from miplearn.solvers.tests import assert_equals, _round_variables, _round_constraints
from miplearn.solvers.tests import (
assert_equals,
_round_variables,
_round_constraints,
_round,
)
inf = float("inf")
@@ -22,113 +28,36 @@ def test_knapsack() -> None:
solver.solve_lp()
features = FeaturesExtractor(solver).extract(instance)
assert features.variables is not None
assert features.variables_old is not None
assert features.constraints is not None
assert features.instance is not None
assert_equals(
_round_variables(features.variables),
{
"x[0]": Variable(
basis_status="U",
category="default",
lower_bound=0.0,
obj_coeff=505.0,
reduced_cost=193.615385,
sa_lb_down=-inf,
sa_lb_up=1.0,
sa_obj_down=311.384615,
sa_obj_up=inf,
sa_ub_down=0.913043,
sa_ub_up=2.043478,
type="B",
upper_bound=1.0,
user_features=[23.0, 505.0],
value=1.0,
alvarez_2017=[1.0, 0.32899, 0.0, 0.0, 1.0, 1.0, 5.265874, 46.051702],
_round(features.variables),
VariableFeatures(
names=("x[0]", "x[1]", "x[2]", "x[3]", "z"),
basis_status=("U", "B", "U", "L", "U"),
categories=("default", "default", "default", "default", None),
lower_bounds=(0.0, 0.0, 0.0, 0.0, 0.0),
obj_coeffs=(505.0, 352.0, 458.0, 220.0, 0.0),
reduced_costs=(193.615385, 0.0, 187.230769, -23.692308, 13.538462),
sa_lb_down=(-inf, -inf, -inf, -0.111111, -inf),
sa_lb_up=(1.0, 0.923077, 1.0, 1.0, 67.0),
sa_obj_down=(311.384615, 317.777778, 270.769231, -inf, -13.538462),
sa_obj_up=(inf, 570.869565, inf, 243.692308, inf),
sa_ub_down=(0.913043, 0.923077, 0.9, 0.0, 43.0),
sa_ub_up=(2.043478, inf, 2.2, inf, 69.0),
types=("B", "B", "B", "B", "C"),
upper_bounds=(1.0, 1.0, 1.0, 1.0, 67.0),
user_features=(
(23.0, 505.0),
(26.0, 352.0),
(20.0, 458.0),
(18.0, 220.0),
None,
),
"x[1]": Variable(
basis_status="B",
category="default",
lower_bound=0.0,
obj_coeff=352.0,
reduced_cost=0.0,
sa_lb_down=-inf,
sa_lb_up=0.923077,
sa_obj_down=317.777778,
sa_obj_up=570.869565,
sa_ub_down=0.923077,
sa_ub_up=inf,
type="B",
upper_bound=1.0,
user_features=[26.0, 352.0],
value=0.923077,
alvarez_2017=[
1.0,
0.229316,
0.0,
0.076923,
1.0,
1.0,
3.532875,
5.388476,
],
),
"x[2]": Variable(
basis_status="U",
category="default",
lower_bound=0.0,
obj_coeff=458.0,
reduced_cost=187.230769,
sa_lb_down=-inf,
sa_lb_up=1.0,
sa_obj_down=270.769231,
sa_obj_up=inf,
sa_ub_down=0.9,
sa_ub_up=2.2,
type="B",
upper_bound=1.0,
user_features=[20.0, 458.0],
value=1.0,
alvarez_2017=[1.0, 0.298371, 0.0, 0.0, 1.0, 1.0, 5.232342, 46.051702],
),
"x[3]": Variable(
basis_status="L",
category="default",
lower_bound=0.0,
obj_coeff=220.0,
reduced_cost=-23.692308,
sa_lb_down=-0.111111,
sa_lb_up=1.0,
sa_obj_down=-inf,
sa_obj_up=243.692308,
sa_ub_down=0.0,
sa_ub_up=inf,
type="B",
upper_bound=1.0,
user_features=[18.0, 220.0],
value=0.0,
alvarez_2017=[1.0, 0.143322, 0.0, 0.0, 1.0, -1.0, 46.051702, 3.16515],
),
"z": Variable(
basis_status="U",
category=None,
lower_bound=0.0,
obj_coeff=0.0,
reduced_cost=13.538462,
sa_lb_down=-inf,
sa_lb_up=67.0,
sa_obj_down=-13.538462,
sa_obj_up=inf,
sa_ub_down=43.0,
sa_ub_up=69.0,
type="C",
upper_bound=67.0,
user_features=None,
value=67.0,
alvarez_2017=[0.0, 0.0, 0.0, 0.0, 1.0, -1.0, 0.0, 0.0],
),
},
values=(1.0, 0.923077, 1.0, 0.0, 67.0),
),
)
assert_equals(
_round_constraints(features.constraints),