tighten conditions for making recommendations

backend/app/plan/router.py

@@ -157,12 +157,6 @@ async def trigger_plan(body: PlanTriggerRequest):
             data_processor = DataProcessor(None, newdata=True)
             data_processor.insert_data(pd.DataFrame([p.get_model_data()]))
             data_processor.pre_process()
-            data_processor.data = data_processor.clean_missings_after_description_process(
-                data_processor.data, [
-                    c for c in data_processor.data.columns if
-                    ("thermal_transmittance" in c) or ("insulation_thickness" in c)
-                ]
-            )
 
             starting_epc_data = data_processor.get_component_features(suffix="_STARTING")
             ending_epc_data = data_processor.get_component_features(suffix="_ENDING")
@@ -180,38 +174,6 @@ async def trigger_plan(body: PlanTriggerRequest):
                         ending_epc_data=ending_epc_data,
                         fixed_data=fixed_data,
                     )
-                    if i == 0:
-                        none_cols = []
-                        for col in scoring_dict.keys():
-                            if col in [
-                                "UPRN", "id", "LOCAL_AUTHORITY",
-                            ]:
-                                continue
-
-                            if col in [
-                                "SAP_STARTING", "HEAT_DEMAND_STARTING", "CARBON_STARTING", "FLOOR_HEIGHT_STARTING",
-                                "TOTAL_FLOOR_AREA_STARTING", "DAYS_TO_STARTING", "estimated_perimeter_STARTING",
-                                "SAP_ENDING", "HEAT_DEMAND_ENDING",
-                                "CARBON_ENDING", "FLOOR_HEIGHT_ENDING",
-                                "TOTAL_FLOOR_AREA_ENDING", "DAYS_TO_ENDING", "estimated_perimeter_ENDING"
-                            ]:
-                                try:
-                                    if scoring_dict[col] is None:
-                                        blah1
-                                    float(scoring_dict[col])
-                                    continue
-                                except:
-                                    raise Exception("wtf")
-
-                            unique_vals = sap_change_dataset[col].unique()
-                            if scoring_dict[col] not in unique_vals:
-                                if scoring_dict[col] is None:
-                                    none_cols.append(col)
-                                    continue
-                                blah
-
-                        if none_cols:
-                            blahblah
 
                     recommendations_scoring_data.append(scoring_dict)
 
@@ -224,6 +186,13 @@ async def trigger_plan(body: PlanTriggerRequest):
         # Merge the cleaning data onto recommendations_scoring_data
 
         # Perform the same cleaning as in the model
+        recommendations_scoring_data = DataProcessor.clean_missings_after_description_process(
+            recommendations_scoring_data, [
+                c for c in recommendations_scoring_data.columns if
+                ("thermal_transmittance" in c) or ("insulation_thickness" in c)
+            ]
+        )
+
         recommendations_scoring_data = DataProcessor.apply_averages_cleaning(
             data_to_clean=recommendations_scoring_data,
             cleaning_data=cleaning_data,

backend/app/plan/utils.py

@@ -126,7 +126,7 @@ def create_recommendation_scoring_data(
         scoring_dict["floor_insulation_thickness"] = "none"
 
     if scoring_dict["roof_insulation_thickness"] is None:
-        scoring_dict["floor_insulation_thickness"] = "none"
+        scoring_dict["roof_insulation_thickness"] = "none"
 
     # We update the description to indicate it's insulated
     if recommendation["type"] == "wall_insulation":

recommendations/FloorRecommendations.py

@@ -57,8 +57,11 @@ class FloorRecommendations(Definitions):
 
         year_built = self.property.year_built
 
-        if self.property.floor["another_property_below"]:
-            # If there's another property below, it's likely impractical to recommend a floor upgrade
+        if self.property.floor["another_property_below"] | (self.property.floor["insulation_thickness"] in [
+            "average", "above average"
+        ]):
+            # If there's another property below, it's likely impractical to recommend a floor upgrade,
+            # or if the floor is already insualted
             return
 
         # If the property is a flat that isn't at ground level, it's likely impractical to recommend a floor upgrade

recommendations/WallRecommendations.py

@@ -73,7 +73,7 @@ class WallRecommendations(Definitions):
         insulation_thickness = self.property.walls["insulation_thickness"]
 
         # We check if the wall is already insulated and if so, we exit
-        if insulation_thickness in ["average", "above average"]:
+        if (insulation_thickness in ["average", "above average"]) or self.property.walls["is_filled_cavity"]:
             return
 
         if u_value:

recommendations/config.py

@@ -4,6 +4,8 @@ UPGRADES_MAP = {
     'Solid brick, as built, no insulation': 'Solid brick, as built, insulated',
     'Suspended, no insulation': 'Suspended, insulated',
     'Solid, no insulation': 'Solid, insulated',
+    'Cavity wall, as built, no insulation': 'Cavity wall, as built, insulated',
+    'Cavity wall, as built, partial insulation': 'Cavity wall, as built, insulated',
 }
 
 PARTIAL_CAVITY_DESCRIPTIONS = [