Make Sample abstract; create MemorySample

tests/components/test_dynamic_lazy.py

@@ -11,7 +11,7 @@ from miplearn.classifiers import Classifier
 from miplearn.classifiers.threshold import MinProbabilityThreshold
 from miplearn.components import classifier_evaluation_dict
 from miplearn.components.dynamic_lazy import DynamicLazyConstraintsComponent
-from miplearn.features.sample import Sample
+from miplearn.features.sample import Sample, MemorySample
 from miplearn.instance.base import Instance
 from miplearn.solvers.tests import assert_equals
 
@@ -22,13 +22,13 @@ E = 0.1
 def training_instances() -> List[Instance]:
     instances = [cast(Instance, Mock(spec=Instance)) for _ in range(2)]
     samples_0 = [
-        Sample(
+        MemorySample(
             {
                 "lazy_enforced": {"c1", "c2"},
                 "instance_features_user": [5.0],
             },
         ),
-        Sample(
+        MemorySample(
             {
                 "lazy_enforced": {"c2", "c3"},
                 "instance_features_user": [5.0],
@@ -53,7 +53,7 @@ def training_instances() -> List[Instance]:
         }
     )
     samples_1 = [
-        Sample(
+        MemorySample(
             {
                 "lazy_enforced": {"c3", "c4"},
                 "instance_features_user": [8.0],

tests/components/test_objective.py

@@ -10,14 +10,14 @@ from numpy.testing import assert_array_equal
 
 from miplearn.classifiers import Regressor
 from miplearn.components.objective import ObjectiveValueComponent
-from miplearn.features.sample import Sample
+from miplearn.features.sample import Sample, MemorySample
 from miplearn.solvers.learning import LearningSolver
 from miplearn.solvers.pyomo.gurobi import GurobiPyomoSolver
 
 
 @pytest.fixture
 def sample() -> Sample:
-    sample = Sample(
+    sample = MemorySample(
         {
             "mip_lower_bound": 1.0,
             "mip_upper_bound": 2.0,

tests/components/test_primal.py

@@ -12,7 +12,7 @@ from miplearn.classifiers import Classifier
 from miplearn.classifiers.threshold import Threshold
 from miplearn.components import classifier_evaluation_dict
 from miplearn.components.primal import PrimalSolutionComponent
-from miplearn.features.sample import Sample
+from miplearn.features.sample import Sample, MemorySample
 from miplearn.problems.tsp import TravelingSalesmanGenerator
 from miplearn.solvers.learning import LearningSolver
 from miplearn.solvers.tests import assert_equals
@@ -20,7 +20,7 @@ from miplearn.solvers.tests import assert_equals
 
 @pytest.fixture
 def sample() -> Sample:
-    sample = Sample(
+    sample = MemorySample(
         {
             "var_names": ["x[0]", "x[1]", "x[2]", "x[3]"],
             "var_categories": ["default", None, "default", "default"],

tests/components/test_static_lazy.py

@@ -11,7 +11,7 @@ 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.sample import Sample
+from miplearn.features.sample import Sample, MemorySample
 from miplearn.instance.base import Instance
 from miplearn.solvers.internal import InternalSolver, Constraints
 from miplearn.solvers.learning import LearningSolver
@@ -22,7 +22,7 @@ from miplearn.types import (
 
 @pytest.fixture
 def sample() -> Sample:
-    sample = Sample(
+    sample = MemorySample(
         {
             "constr_categories": [
                 "type-a",

tests/test_features.py

@@ -5,7 +5,7 @@
 import numpy as np
 
 from miplearn.features.extractor import FeaturesExtractor
-from miplearn.features.sample import Sample
+from miplearn.features.sample import Sample, MemorySample
 from miplearn.solvers.internal import Variables, Constraints
 from miplearn.solvers.gurobi import GurobiSolver
 from miplearn.solvers.tests import assert_equals
@@ -19,7 +19,7 @@ def test_knapsack() -> None:
     model = instance.to_model()
     solver.set_instance(instance, model)
     extractor = FeaturesExtractor()
-    sample = Sample()
+    sample = MemorySample()
 
     # after-load
     # -------------------------------------------------------