additional fixes for EPC C properties

backend/Funding.py

@@ -566,6 +566,10 @@ class Funding:
             measure_code = "LI_lessequal100" if existing_li_thickness <= 100 else "LI_greater100"
             pps = filtered_pps_matrix[filtered_pps_matrix["Measure_Type"] == measure_code]
 
+            # There's no funding for EPC C or above
+            if self.starting_sap_band in ["Low_C", "High_C", "Low_B", "High_B", "Low_A", "High_A"]:
+                return 0
+
             if pps.shape[0] != 1:
                 raise ValueError(f"Invalid LI category: {measure_code}")
             return pps.squeeze()["Cost Savings"]
@@ -597,6 +601,10 @@ class Funding:
             return pps.squeeze()["Cost Savings"]
 
         if measure_type == "solid_floor_insulation":
+            if self.starting_sap_band in ["Low_C", "High_C", "Low_B", "High_B", "Low_A", "High_A"]:
+                # We don't fund SFI for properties starting at C or above
+                return 0
+
             pps = filtered_pps_matrix[filtered_pps_matrix["Measure_Type"] == "SFI"]
             if pps.shape[0] != 1:
                 raise ValueError("Invalid SFI category")
@@ -607,9 +615,20 @@ class Funding:
                 (filtered_pps_matrix["Measure_Type"] == "Solar_PV") &
                 (filtered_pps_matrix["Pre_Main_Heating_Source"] == pre_heating_system)
                 ]
+
+            if solar_pps_df.empty and self.starting_sap_band in [
+                "Low_C", "High_C", "Low_B", "High_B", "Low_B", "High_A"
+            ]:
+                # No funding for EPC C or above
+                return 0
             return solar_pps_df.squeeze()["Cost Savings"]
 
         if measure_type == "air_source_heat_pump":
+
+            # No funding for EPC C or above
+            if self.starting_sap_band in ["Low_C", "High_C", "Low_B", "High_B", "Low_A", "High_A"]:
+                return 0
+
             pps = filtered_pps_matrix[
                 (filtered_pps_matrix["Pre_Main_Heating_Source"] == pre_heating_system) &
                 (filtered_pps_matrix["Post_Main_Heating_Source"] == "Air to Water ASHP") &

backend/apis/GoogleSolarApi.py

@@ -900,8 +900,7 @@ class GoogleSolarApi:
 
         return input_properties
 
-    @classmethod
-    def default_panel_performance(cls, property_instance):
+    def default_panel_performance(self, property_instance):
         """
         In a small number of cases, where properties have simulated uprns, we do not have a longitude and latitude
         value and therefore we just return a default panel performance
@@ -911,6 +910,20 @@ class GoogleSolarApi:
 
         cost_instance = Costs(property_instance=property_instance)
 
+        material_1_6 = next(
+            (m for m in self.solar_materials if m["type"] == "solar_pv" and
+             abs(m["size"] - 1.6) < 0.1 and not m["includes_battery"]),
+            None
+        )
+        material_3_2 = next(
+            (m for m in self.solar_materials if m["type"] == "solar_pv" and
+             abs(m["size"] - 3.2) < 0.1 and not m["includes_battery"]),
+            None
+        )
+
+        if material_1_6 is None or material_3_2 is None:
+            raise ValueError("No suitable solar product found for the default configuration.")
+
         # We return a 1.6 and 3.2 kwp system
         panel_performance = pd.DataFrame(
             [
@@ -918,7 +931,12 @@ class GoogleSolarApi:
                     'n_panels': 8,
                     'yearly_dc_energy': 3200 * assumptions.MEDIAN_WATTAGE_TO_DC,
                     'total_cost': cost_instance.solar_pv(
-                        n_panels=8, has_battery=False, n_floors=property_instance.number_of_floors
+                        solar_product=material_1_6,
+                        scaffolding_options=[
+                            {"total_cost": 1000, "size": property_instance.number_of_floors},
+                            {"total_cost": 1000, "size": 3}
+                        ],
+                        n_floors=property_instance.number_of_floors
                     )["total"],
                     'weighted_ratio': None,
                     'panneled_roof_area': 8 * assumptions.RDSAP_AREA_PER_PANEL,
@@ -938,7 +956,12 @@ class GoogleSolarApi:
                     'n_panels': 4,
                     'yearly_dc_energy': 1600 * assumptions.MEDIAN_WATTAGE_TO_DC,
                     'total_cost': cost_instance.solar_pv(
-                        n_panels=6, has_battery=False, n_floors=property_instance.number_of_floors
+                        solar_product=material_3_2,
+                        scaffolding_options=[
+                            {"total_cost": 1000, "size": property_instance.number_of_floors},
+                            {"total_cost": 1000, "size": 3}
+                        ],
+                        n_floors=property_instance.number_of_floors
                     )["total"],
                     'weighted_ratio': None,
                     'panneled_roof_area': 4 * assumptions.RDSAP_AREA_PER_PANEL,

backend/engine/engine.py

@@ -894,6 +894,7 @@ async def model_engine(body: PlanTriggerRequest):
                             0, 0, 0, 0
                         )
                         continue
+
                     (
                         r["partial_project_score"], r["partial_project_funding"], r["innovation_uplift"],
                         r["uplift_project_score"]