Prefer a MAIN-bearing prediction template so EPC-less dwellings predict 🟥

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

tests/domain/epc_prediction/test_epc_prediction.py

@@ -9,6 +9,7 @@ from datetime import date
 from typing import Optional, Union
 
 from datatypes.epc.domain.epc_property_data import (
+    BuildingPartIdentifier,
     EpcPropertyData,
     MainHeatingDetail,
     SapBuildingPart,
@@ -32,6 +33,7 @@ from domain.epc_prediction.prediction_target import PredictionTarget
 def _epc(
     *,
     building_parts: int = 1,
+    identifier: BuildingPartIdentifier = BuildingPartIdentifier.MAIN,
     floor_area: float = 80.0,
     wall_construction: Union[int, str] = 1,
     wall_insulation_type: Union[int, str] = 1,
@@ -57,6 +59,7 @@ def _epc(
     parts: list[SapBuildingPart] = []
     for _ in range(building_parts):
         part: SapBuildingPart = object.__new__(SapBuildingPart)
+        part.identifier = identifier
         part.wall_construction = wall_construction
         part.wall_insulation_type = wall_insulation_type
         part.construction_age_band = construction_age_band
@@ -148,6 +151,31 @@ def test_template_is_the_member_closest_to_the_cohort_median_size() -> None:
     assert predicted.total_floor_area_m2 == 80.0
 
 
+def test_template_skips_a_main_less_member_so_the_prediction_has_a_main_part() -> None:
+    # Arrange — the size-median member is OTHER-only (the gov API lodged its part
+    # with a null identifier), but the cohort holds MAIN-bearing neighbours at
+    # other sizes. The structural template must be a MAIN-bearing member so the
+    # predicted dwelling presents a main dwelling — else the modelling handler's
+    # MAIN-part guard rejects an otherwise-rich cohort as "not predictable".
+    cohort = _cohort(
+        _epc(floor_area=80.0, identifier=BuildingPartIdentifier.OTHER),
+        _epc(floor_area=30.0, identifier=BuildingPartIdentifier.MAIN),
+        _epc(floor_area=200.0, identifier=BuildingPartIdentifier.MAIN),
+    )
+
+    # Act
+    predicted: EpcPropertyData = EpcPrediction().predict(
+        PredictionTarget(postcode="LS6 1AA", property_type="2"), cohort
+    )
+
+    # Assert — the predicted dwelling has a MAIN part (seeded from a MAIN-bearing
+    # neighbour), not the OTHER-only median member.
+    assert any(
+        part.identifier is BuildingPartIdentifier.MAIN
+        for part in predicted.sap_building_parts
+    )
+
+
 def test_sets_main_wall_construction_to_the_cohort_mode() -> None:
     # Arrange — the template (members[0]) is solid brick (2), but the cohort
     # majority is cavity (1). The homogeneous categorical should follow the mode,