adding ventilation handling to prevent extremem values

backend/engine/engine.py

@@ -980,12 +980,12 @@ async def model_engine(body: PlanTriggerRequest):
 
         logger.info("Preparing data for scoring in sap change api")
         recommendations_scoring_data = pd.DataFrame(recommendations_scoring_data)
+        # Temp putting this here
+        recommendations_scoring_data["is_post_sap10_ending"] = True
 
         recommendations_scoring_data = recommendations_scoring_data.drop(
-            columns=[
+            columns=["rdsap_change", "heat_demand_change", "carbon_change", "sap_ending", "heat_demand_ending",
-                "rdsap_change", "heat_demand_change", "carbon_change", "sap_ending", "heat_demand_ending",
+                     "carbon_ending"]
-                "carbon_ending"
-            ]
         )
 
         all_predictions = await model_api.async_paginated_predictions(

recommendations/Recommendations.py

@@ -615,7 +615,7 @@ class Recommendations:
                         if metric == "sap":
                             property_phase_impact[metric] = round(property_phase_impact[metric], 2)
                     else:
-                        # We prevent these from being positive
+                        # We prevent mechanical ventilation from being positive
                         property_phase_impact[metric] = (
                             0 if property_phase_impact[metric] > 0 else property_phase_impact[metric]
                         )
@@ -632,6 +632,38 @@ class Recommendations:
                         property_phase_impact["carbon"], rec["co2_equivalent_savings"]
                     )
 
+                    # Update the current phase values
+                    current_phase_values["sap"] = previous_phase_values["sap"] + property_phase_impact["sap"]
+                    current_phase_values["carbon"] = previous_phase_values["carbon"] - property_phase_impact["carbon"]
+
+                # We also ensure that mechanical ventilation doesn't have an ovely strong negative SAP impact
+                if rec["type"] == "mechanical_ventilation":
+                    # ventilation is capped by having no greater and a -4 impact
+                    ventilation_sap_limit = -4
+
+                    def _check_veniltation_out_of_bounds(sap_impact):
+                        return (sap_impact < ventilation_sap_limit) or (sap_impact >= 0)
+
+                    def _adjust_ventilation_sap(sap_impact):
+                        if sap_impact >= 0:
+                            return -1
+                        if sap_impact < ventilation_sap_limit:
+                            return ventilation_sap_limit
+
+                    ventilation_out_of_bounds = _check_veniltation_out_of_bounds(property_phase_impact["sap"])
+
+                    if ventilation_out_of_bounds:
+                        previous_modelled_sap = previous_phase_values.get("sap_prediction", 0)
+                        proposed_sap_impact = current_phase_sap - previous_modelled_sap
+                        proposal_out_of_bounds = _check_veniltation_out_of_bounds(proposed_sap_impact)
+                        if proposal_out_of_bounds:
+                            property_phase_impact["sap"] = _adjust_ventilation_sap(proposed_sap_impact)
+                        else:
+                            property_phase_impact["sap"] = proposed_sap_impact
+
+                        # Update the current phase values
+                        current_phase_values["sap"] = previous_phase_values["sap"] + property_phase_impact["sap"]
+
                 if rec["type"] == "loft_insulation":
                     # When we have a loft insulation recommendation, where there is an extension and the existing
                     # amount of loft insulation is already good, we limit the SAP points
@@ -642,6 +674,8 @@ class Recommendations:
                     )
                     if li_sap_limit is not None:
                         property_phase_impact["sap"] = min(property_phase_impact["sap"], li_sap_limit)
+                        # Update the current phase values
+                        current_phase_values["sap"] = previous_phase_values["sap"] + property_phase_impact["sap"]
 
                 if rec["type"] == "solar_pv":
                     # We use the SAP points in the recommendation as a minimum
@@ -649,6 +683,8 @@ class Recommendations:
                         rec["sap_points"] if property_phase_impact["sap"] < rec["sap_points"] else
                         property_phase_impact["sap"]
                     )
+                    # Update the current phase values
+                    current_phase_values["sap"] = previous_phase_values["sap"] + property_phase_impact["sap"]
 
                 # Insert this information into the recommendation.
                 if not rec.get("survey", False):
@@ -669,7 +705,8 @@ class Recommendations:
                         "representative": rec["recommendation_id"] in representative_ids,
                         "recommendation_id": rec["recommendation_id"],
                         "measure_type": rec["measure_type"],
-                        **current_phase_values
+                        **current_phase_values,
+                        "sap_prediction": phase_energy_efficiency_metrics["sap_change"]
                     }
                 )