Make xy_sample receive features, not instances

miplearn/components/component.py

@@ -3,11 +3,11 @@
 #  Released under the modified BSD license. See COPYING.md for more details.
 
 import numpy as np
-from typing import Any, List, Union, TYPE_CHECKING, Tuple, Dict
+from typing import Any, List, Union, TYPE_CHECKING, Tuple, Dict, Optional
 
 from miplearn.extractors import InstanceIterator
 from miplearn.instance import Instance
-from miplearn.types import LearningSolveStats, TrainingSample
+from miplearn.types import LearningSolveStats, TrainingSample, Features
 
 if TYPE_CHECKING:
     from miplearn.solvers.learning import LearningSolver
@@ -133,14 +133,16 @@ class Component:
 
     @staticmethod
     def xy_sample(
-        instance: Any,
-        training_sample: TrainingSample,
-    ) -> Tuple[Dict, Dict]:
+        features: Features,
+        sample: TrainingSample,
+    ) -> Optional[Tuple[Dict, Dict]]:
         """
-        Given a training sample, returns a pair of x and y dictionaries containing,
-        respectively, the matrices of ML features and the labels for the sample.
+        Given a set of features and a training sample, returns a pair of x and y
+        dictionaries containing, respectively, the matrices of ML features and the
+        labels for the sample. If the training sample does not include label
+        information, returns None.
         """
-        return {}, {}
+        return None
 
     def xy_instances(
         self,
@@ -149,8 +151,12 @@ class Component:
         x_combined: Dict = {}
         y_combined: Dict = {}
         for instance in InstanceIterator(instances):
+            assert isinstance(instance, Instance)
             for sample in instance.training_data:
-                x_sample, y_sample = self.xy_sample(instance, sample)
+                xy = self.xy_sample(instance.features, sample)
+                if xy is None:
+                    continue
+                x_sample, y_sample = xy
                 for cat in x_sample.keys():
                     if cat not in x_combined:
                         x_combined[cat] = []