Request constraint features/categories in bulk

tests/components/test_dynamic_lazy.py

@@ -6,7 +6,6 @@ from unittest.mock import Mock
 
 import numpy as np
 import pytest
-from numpy.testing import assert_array_equal
 
 from miplearn.classifiers import Classifier
 from miplearn.classifiers.threshold import MinProbabilityThreshold
@@ -42,21 +41,21 @@ def training_instances() -> List[Instance]:
     instances[0].samples[1].after_load.instance.to_list = Mock(  # type: ignore
         return_value=[5.0]
     )
-    instances[0].get_constraint_category = Mock(  # type: ignore
-        side_effect=lambda cid: {
+    instances[0].get_constraint_categories = Mock(  # type: ignore
+        return_value={
             "c1": "type-a",
             "c2": "type-a",
             "c3": "type-b",
             "c4": "type-b",
-        }[cid]
+        }
     )
     instances[0].get_constraint_features = Mock(  # type: ignore
-        side_effect=lambda cid: {
+        return_value={
             "c1": [1.0, 2.0, 3.0],
             "c2": [4.0, 5.0, 6.0],
             "c3": [1.0, 2.0],
             "c4": [3.0, 4.0],
-        }[cid]
+        }
     )
     instances[1].samples = [
         Sample(
@@ -67,20 +66,20 @@ def training_instances() -> List[Instance]:
     instances[1].samples[0].after_load.instance.to_list = Mock(  # type: ignore
         return_value=[8.0]
     )
-    instances[1].get_constraint_category = Mock(  # type: ignore
-        side_effect=lambda cid: {
+    instances[1].get_constraint_categories = Mock(  # type: ignore
+        return_value={
             "c1": None,
             "c2": "type-a",
             "c3": "type-b",
             "c4": "type-b",
-        }[cid]
+        }
     )
     instances[1].get_constraint_features = Mock(  # type: ignore
-        side_effect=lambda cid: {
+        return_value={
             "c2": [7.0, 8.0, 9.0],
             "c3": [5.0, 6.0],
             "c4": [7.0, 8.0],
-        }[cid]
+        }
     )
     return instances
 

tests/test_features.py

@@ -83,7 +83,7 @@ def test_knapsack() -> None:
             sa_rhs_up=[2.0],
             senses=["="],
             slacks=[0.0],
-            user_features=[[0.0]],
+            user_features=[None],
         ),
     )
     assert_equals(