perf(map): simplify preclipped area queries

backend/app/api/routes/datasets.py

@@ -633,16 +633,17 @@ def select_vector_features(
             payload.bbox.model_dump(),
             selection_area.geometry,
         )
-        full_dataset_area = covers_full_area and VectorFeatureService.can_use_full_area_fast_path(
+        dataset_is_preclipped_to_area = VectorFeatureService.can_use_full_area_fast_path(
             dataset,
             selection_area.id,
         )
+        full_dataset_area = covers_full_area and dataset_is_preclipped_to_area
         preclipped_partition_filter = VectorFeatureService.preclipped_partition_filter(
             dataset,
             getattr(selection_area, "name", None),
         )
         selection_kwargs.update(
-            selection_geometry=selection_geometry,
+            selection_geometry=None if dataset_is_preclipped_to_area else selection_geometry,
             selection_area_id=selection_area.id,
             full_dataset_area=full_dataset_area,
             preclipped_partition_filter=preclipped_partition_filter,
@@ -655,7 +656,7 @@ def select_vector_features(
             "total_feature_count": result.get("total_feature_count"),
         }
         if selection_area is not None:
-            summary_kwargs["selection_geometry"] = selection_geometry
+            summary_kwargs["selection_geometry"] = None if dataset_is_preclipped_to_area else selection_geometry
             summary_kwargs["full_dataset_area"] = full_dataset_area
             summary_kwargs["preclipped_partition_filter"] = preclipped_partition_filter
         result["summary"] = VectorFeatureService.summarize_features_by_bbox(db, **summary_kwargs)

backend/tests/test_sprint106_map_bbox_extract.py

@@ -232,6 +232,82 @@ def test_vector_select_route_uses_persisted_area_geometry_when_requested(monkeyp
     assert captured["select"]["full_dataset_area"] is False
 
 
+def test_vector_select_route_uses_bbox_for_dataset_preclipped_to_selected_area(monkeypatch) -> None:
+    from app.api.routes import datasets as dataset_routes
+
+    project_id = uuid.uuid4()
+    dataset_id = uuid.uuid4()
+    area_id = uuid.uuid4()
+    dataset = Dataset(
+        id=dataset_id,
+        project_id=project_id,
+        area_id=area_id,
+        dataset_type="vector",
+        source="fixture",
+        name="Preclipped population",
+        source_metadata={
+            "geometry_clipped_to_area": True,
+            "selection_aggregation": {"method": "feature_count"},
+        },
+    )
+    area = SimpleNamespace(
+        id=area_id,
+        project_id=project_id,
+        geometry=from_shape(box(5.0, 51.0, 5.3, 51.3), srid=4326),
+    )
+    captured: dict[str, dict[str, object]] = {}
+
+    class _AreaSession:
+        @staticmethod
+        def get(model, selected_id):  # noqa: ANN001
+            assert model is dataset_routes.Area
+            assert selected_id == area_id
+            return area
+
+    def select_features(_db, **kwargs):  # noqa: ANN001
+        captured["select"] = kwargs
+        return {
+            "selection_bbox": {"min_x": 4.9, "min_y": 51.1, "max_x": 5.2, "max_y": 51.2, "crs": "EPSG:4326"},
+            "selection_area_id": str(area_id),
+            "feature_count": 1,
+            "total_feature_count": 1,
+            "limit": 25,
+            "truncated": False,
+            "geojson": {"type": "FeatureCollection", "features": []},
+        }
+
+    def summarize_features(_db, **kwargs):  # noqa: ANN001
+        captured["summary"] = kwargs
+        return {
+            "metric_label": "Inwoners",
+            "metric_value": 1,
+            "metric_unit": "inwoners",
+            "aggregation_method": "feature_count",
+            "feature_count": 1,
+            "is_estimate": False,
+        }
+
+    monkeypatch.setattr(dataset_routes.DatasetService, "get_dataset", lambda _db, _id: dataset)
+    monkeypatch.setattr(dataset_routes.VectorFeatureService, "select_features_by_bbox", select_features)
+    monkeypatch.setattr(dataset_routes.VectorFeatureService, "summarize_features_by_bbox", summarize_features)
+
+    dataset_routes.select_vector_features(
+        project_id=project_id,
+        dataset_id=dataset_id,
+        payload=dataset_routes.VectorSelectionRequest(
+            bbox=dataset_routes.VectorSelectionBBox(min_x=4.9, min_y=51.1, max_x=5.2, max_y=51.2),
+            area_id=area_id,
+            limit=25,
+        ),
+        db=_AreaSession(),
+    )
+
+    assert captured["select"]["selection_geometry"] is None
+    assert captured["summary"]["selection_geometry"] is None
+    assert captured["select"]["selection_area_id"] == area_id
+    assert captured["select"]["full_dataset_area"] is False
+
+
 def test_vector_select_route_rejects_area_from_another_project(monkeypatch) -> None:
     from app.api.routes import datasets as dataset_routes