Rename Variables and Constraints; move to internal.py

tests/components/test_static_lazy.py

@@ -11,9 +11,9 @@ from numpy.testing import assert_array_equal
 from miplearn.classifiers import Classifier
 from miplearn.classifiers.threshold import Threshold, MinProbabilityThreshold
 from miplearn.components.static_lazy import StaticLazyConstraintsComponent
-from miplearn.features import Sample, ConstraintFeatures
+from miplearn.features import Sample
 from miplearn.instance.base import Instance
-from miplearn.solvers.internal import InternalSolver
+from miplearn.solvers.internal import InternalSolver, Constraints
 from miplearn.solvers.learning import LearningSolver
 from miplearn.types import (
     LearningSolveStats,
@@ -118,7 +118,7 @@ def test_usage_with_solver(instance: Instance) -> None:
 
     # Should ask internal solver to verify if constraints in the pool are
     # satisfied and add the ones that are not
-    c = ConstraintFeatures.from_sample(sample)[[False, False, True, False, False]]
+    c = Constraints.from_sample(sample)[[False, False, True, False, False]]
     internal.are_constraints_satisfied.assert_called_once_with(c, tol=1.0)
     internal.are_constraints_satisfied.reset_mock()
     internal.add_constraints.assert_called_once_with(c)

tests/test_features.py

@@ -6,10 +6,9 @@ import numpy as np
 
 from miplearn.features import (
     FeaturesExtractor,
-    VariableFeatures,
-    ConstraintFeatures,
     Sample,
 )
+from miplearn.solvers.internal import Variables, Constraints
 from miplearn.solvers.gurobi import GurobiSolver
 from miplearn.solvers.tests import assert_equals
 
@@ -129,7 +128,7 @@ def test_knapsack() -> None:
 
 
 def test_constraint_getindex() -> None:
-    cf = ConstraintFeatures(
+    cf = Constraints(
         names=["c1", "c2", "c3"],
         rhs=[1.0, 2.0, 3.0],
         senses=["=", "<", ">"],
@@ -150,7 +149,7 @@ def test_constraint_getindex() -> None:
     )
     assert_equals(
         cf[[True, False, True]],
-        ConstraintFeatures(
+        Constraints(
             names=["c1", "c3"],
             rhs=[1.0, 3.0],
             senses=["=", ">"],
@@ -177,8 +176,8 @@ def test_assert_equals() -> None:
         np.array([[1.0, 2.0], [3.0, 4.0]]),
     )
     assert_equals(
-        VariableFeatures(values=np.array([1.0, 2.0])),  # type: ignore
-        VariableFeatures(values=np.array([1.0, 2.0])),  # type: ignore
+        Variables(values=np.array([1.0, 2.0])),  # type: ignore
+        Variables(values=np.array([1.0, 2.0])),  # type: ignore
     )
     assert_equals(np.array([True, True]), [True, True])
     assert_equals((1.0,), (1.0,))