Debugging dwelling below for floor uvalue

model_data/simulation_system/generate_rdsap_change.py

@@ -1,4 +1,5 @@
 import pandas as pd
+import numpy as np
 from tqdm import tqdm
 import msgpack
 
@@ -253,6 +254,7 @@ def make_uvalues(df):
         # ~~~~~~~~~~~~~~~~~~
         # Roof
         # ~~~~~~~~~~~~~~~~~~
+
         starting_roof_uvalue = x["roof_thermal_transmittance"]
         if pd.isnull(starting_roof_uvalue):
             starting_roof_uvalue = get_roof_u_value(
@@ -296,24 +298,28 @@ def make_uvalues(df):
         floor_type = "suspended" if x["is_suspended"] else "solid"
         wall_type = get_wall_type(**x)
 
-        starting_floor_uvalue = x["floor_thermal_transmittance"]
+        if x["another_property_below"]:
+            starting_floor_uvalue, ending_floor_uvalue = 0, 0
+        else:
+            starting_floor_uvalue = x["floor_thermal_transmittance"]
+            ending_floor_uvalue = x["floor_thermal_transmittance_ENDING"]
+
         if pd.isnull(starting_floor_uvalue):
             starting_floor_uvalue = get_floor_u_value(
                 floor_type=floor_type,
                 perimeter=perimeters["estimated_perimeter_STARTING"],
                 area=x[f"TOTAL_FLOOR_AREA_STARTING"],
-                insulation_thickness=extract_insulation_thickness(x["floor_insulation_thickness"]),
+                insulation_thickness=x["floor_insulation_thickness"],
                 wall_type=wall_type,
                 age_band=age_band
             )
 
-        ending_floor_uvalue = x["floor_thermal_transmittance_ENDING"]
         if pd.isnull(ending_floor_uvalue):
             ending_floor_uvalue = get_floor_u_value(
                 floor_type=floor_type,
                 perimeter=perimeters["estimated_perimeter_ENDING"],
                 area=x[f"TOTAL_FLOOR_AREA_ENDING"],
-                insulation_thickness=extract_insulation_thickness(x["floor_insulation_thickness_ENDING"]),
+                insulation_thickness=x["floor_insulation_thickness_ENDING"],
                 wall_type=wall_type,
                 age_band=age_band
             )
@@ -322,8 +328,8 @@ def make_uvalues(df):
             {
                 "UPRN": uprn,
                 "row_index": row_index,
-                "starting_wall_uvalue": starting_wall_uvalue,
+                "starting_walls_uvalue": starting_wall_uvalue,
-                "ending_wall_uvalue": ending_wall_uvalue,
+                "ending_walls_uvalue": ending_wall_uvalue,
                 "starting_roof_uvalue": starting_roof_uvalue,
                 "ending_roof_uvalue": ending_roof_uvalue,
                 "starting_floor_uvalue": starting_floor_uvalue,
@@ -338,6 +344,39 @@ def make_uvalues(df):
         uvalues, how="left", on=["UPRN", "row_index"]
     ).drop(columns="row_index")
 
+    # Fill missings
+    for component in ["walls", "floor", "roof"]:
+        for suffix in ["", "_ENDING"]:
+            fill_col = f"starting_{component}_uvalue" if suffix == "" else f"ending_{component}_uvalue"
+
+            df[f"{component}_thermal_transmittance{suffix}"] = np.where(
+                pd.isnull(df[f"{component}_thermal_transmittance{suffix}"]),
+                df[fill_col],
+                df[f"{component}_thermal_transmittance{suffix}"]
+            )
+
+    df = df.drop(
+        columns=[
+            "starting_walls_uvalue", "ending_walls_uvalue", "starting_roof_uvalue",
+            "ending_roof_uvalue", "starting_floor_uvalue", "ending_floor_uvalue"
+        ]
+    )
+
+    return df
+
+
+def clean_missings_after_description_process(df):
+    missings = pd.isnull(df).sum()
+    missings = missings[missings > 0]
+    for col in missings.index:
+        unique_values = df[col].unique()
+        if True in unique_values or False in unique_values:
+            df[col] = df[col].fillna(False)
+        if "none" in unique_values:
+            df[col] = df[col].fillna("none")
+        else:
+            df[col] = df[col].fillna("Unknown")
+
     return df
 
 
@@ -489,8 +528,11 @@ def app():
             columns=["walls_clean_description", "walls_clean_description_ENDING"]
         )
 
-        def clean_missings():
+        # TODO: For some of the features that we clean, we have either a true, false or possibly null value
-            pass
+        #       Those nulls should be False. clean_missings_after_description_process handles this but shouldn't
+        #       need to
+
+        data_by_urpn_df = clean_missings_after_description_process(data_by_urpn_df)
 
         if pd.isnull(data_by_urpn_df).sum().sum():
             raise ValueError("Null values found in dataset after process_and_prune_desriptions")

recommendations/recommendation_utils.py

@@ -401,6 +401,9 @@ def get_floor_u_value(floor_type, area, perimeter, age_band, wall_type, insulati
        0.701
     """
 
+    # Cleans our regularly inputted insulation thickness for usage in this function
+    insulation_thickness = extract_insulation_thickness(insulation_thickness)
+
     # Define constants
     lambda_g = 1.5  # thermal conductivity of soil in W/m·K
     Rsi = 0.17  # in m²K/W
@@ -507,3 +510,5 @@ def get_wall_type(
 
     if is_park_home:
         return "park home"
+
+    return None