implemented unheated space floor u-value

backend/Property.py

@@ -597,9 +597,26 @@ class Property(Definitions):
     def set_floor_type(self):
         """
         This method sets the floor type of the property, which is used for calculating u-values
-        :return:
+
+        Section 5.6 of the BRE indicates that
+        "to simplify data collection no distinction is made in terms of U-value between an exposed floor (to
+        outside air below) and a semi-exposed floor (to an enclosed but unheated space below)
+        and the U-values in Table S12 are used.
+
+        Therefore, we treat the exposed floor and suspended floor as the same type of floor, which is used for
+        calculating u-values
         """
-        self.floor_type = "suspended" if self.floor["is_suspended"] else "solid"
+
+        if self.floor["is_suspended"] | self.floor["another_property_below"]:
+            self.floor_type = "suspended"
+        elif self.floor["is_solid"]:
+            self.floor_type = "solid"
+        elif self.floor["is_to_unheated_space"] | self.floor["is_to_external_air"]:
+            self.floor_type = "exposed_floor"
+        elif self.floor["thermal_transmittance"] is not None:
+            self.floor_type = "solid"
+        else:
+            raise NotImplementedError("Implement this floor type")
 
     @staticmethod
     def _extract_component(component_data, component_rename_cols, component_drop_cols, rename_prefix=None):

backend/app/plan/router.py

@@ -121,7 +121,7 @@ async def trigger_plan(body: PlanTriggerRequest):
 
         # TODO: Move this to a class. We probably want a Recommender class which takes the injects the optimisers
         #      in as a dependency and then the optimisers can take the input measures in as part of the setup() method
-        
+
         # import pickle
         # with open("input_properties.pickle", "rb") as f:
         #     input_properties = pickle.load(f)
@@ -132,7 +132,7 @@ async def trigger_plan(body: PlanTriggerRequest):
 
         # import pickle
         # with open("cleaned.pickle", "rb") as f:
-        #     cleaned = pickle.dump(f)
+        #     cleaned = pickle.load(f)
 
         # with open("sap_dataset.pickle", "rb") as f:
         #     sap_dataset = pickle.load(f)
@@ -144,11 +144,11 @@ async def trigger_plan(body: PlanTriggerRequest):
         recommendations_scoring_data = []
 
         for p in input_properties:
-            property_recommendations = []
-
             # Property recommendations
             p.get_components(cleaned)
 
+            property_recommendations = []
+
             # Floor recommendations
             floor_recommender = FloorRecommendations(property_instance=p, materials=materials_by_type["floor"])
             floor_recommender.recommend()

etl/epc/property_change_app.py

@@ -415,13 +415,11 @@ def app():
     all_equal_rows = []
 
     for directory in tqdm(directories):
-
         filepath = directory / "certificates.csv"
 
         data_processor = DataProcessor(filepath=filepath)
 
         df = data_processor.pre_process()
-        df[df["WALLS_DESCRIPTION"].str.contains("Cavity")]["WALLS_DESCRIPTION"].unique()
 
         cleaning_averages = data_processor.make_cleaning_averages()
 

recommendations/FloorRecommendations.py

@@ -97,6 +97,8 @@ class FloorRecommendations(Definitions):
             # Given the U-value, we recommend solid floor insulation options which are usually solid foam
             self.recommend_floor_insulation(u_value=u_value, parts=self.solid_floor_insulation_parts)
 
+        raise NotImplementedError("Implement me!")
+
     @staticmethod
     def _make_floor_description(part, depth):
         return f"Install {depth}{part['depth_unit']} {part['description']} insulation"

recommendations/rdsap_tables.py

@@ -463,6 +463,34 @@ s11_list = [
 
 table_s11 = pd.DataFrame(s11_list)
 
+########################################################################################################################
+# Table s12 is used for assigning the u-values of floors to unheated spaces or external air
+# which can be found on page 26 of the BRE document, section 5.6
+# https://bregroup.com/wp-content/uploads/2019/09/RdSAP_2012_9.94-20-09-2019.pdf
+#
+# the insulation_{thickness} fields indicate the u-value at that insulation thickness
+########################################################################################################################
+
+s12_list = [
+    {"age_band": "A", "insulation_0": 1.2, "insulation_50": 0.5, "insulation_100": 0.3, "insulation_150": 0.22},
+    {"age_band": "B", "insulation_0": 1.2, "insulation_50": 0.5, "insulation_100": 0.3, "insulation_150": 0.22},
+    {"age_band": "C", "insulation_0": 1.2, "insulation_50": 0.5, "insulation_100": 0.3, "insulation_150": 0.22},
+    {"age_band": "D", "insulation_0": 1.2, "insulation_50": 0.5, "insulation_100": 0.3, "insulation_150": 0.22},
+    {"age_band": "E", "insulation_0": 1.2, "insulation_50": 0.5, "insulation_100": 0.3, "insulation_150": 0.22},
+    {"age_band": "F", "insulation_0": 1.2, "insulation_50": 0.5, "insulation_100": 0.3, "insulation_150": 0.22},
+    {"age_band": "G", "insulation_0": 1.2, "insulation_50": 0.5, "insulation_100": 0.3, "insulation_150": 0.22},
+
+    {"age_band": "H", "insulation_0": 0.51, "insulation_50": 0.5, "insulation_100": 0.3, "insulation_150": 0.22},
+    {"age_band": "I", "insulation_0": 0.51, "insulation_50": 0.5, "insulation_100": 0.3, "insulation_150": 0.22},
+
+    {"age_band": "J", "insulation_0": 0.25, "insulation_50": 0.25, "insulation_100": 0.25, "insulation_150": 0.22},
+
+    {"age_band": "K", "insulation_0": 0.22, "insulation_50": 0.22, "insulation_100": 0.22, "insulation_150": 0.22},
+    {"age_band": "L", "insulation_0": 0.22, "insulation_50": 0.22, "insulation_100": 0.22, "insulation_150": 0.22},
+]
+
+table_s12 = pd.DataFrame(s12_list)
+
 
 ########################################################################################################################
 #

recommendations/recommendation_utils.py

@@ -5,7 +5,7 @@ import pandas as pd
 
 from recommendations.rdsap_tables import (
     epc_wall_description_map, wall_uvalues_df, default_wall_thickness, table_s9 as s9, table_s10 as s10,
-    table_s11 as s11
+    table_s11 as s11, table_s12 as s12
 )
 from recommendations.config import PARTIALLY_FILLED_PERCENTAGE_ASSUMPTION, PARTIAL_CAVITY_DESCRIPTIONS
 
@@ -340,6 +340,32 @@ def estimate_perimeter(floor_area, num_rooms):
     return perimeter
 
 
+def get_exposed_floor_uvalue(insulation_thickness_str, age_band):
+    """
+    We implement the methodology as defined in section 5.6 and table S12 of the RdSAP document
+    :param insulation_thickness_str:
+    :return:
+    """
+
+    if age_band in ["A", "B", "C", "D", "E", "F", "G", "H", "I"]:
+        # As directed by the documentation, if the insulation thickness is not known, we assume it's
+        # 50mm for these age bands
+        if insulation_thickness_str in ["below_average", "average", "above_average"]:
+            insulation_thickness = 50
+    elif insulation_thickness_str in ["none", None]:
+        insulation_thickness = 0
+    elif insulation_thickness_str in ["below_average"]:
+        insulation_thickness = 50
+    elif insulation_thickness_str == "average":
+        insulation_thickness = 100
+    elif insulation_thickness_str == "above_average":
+        insulation_thickness = 150
+    else:
+        insulation_thickness = int(insulation_thickness_str.replace("mm", ""))
+
+    return s12[s12["age_band"] == age_band][f"insulation_{insulation_thickness}"].values[0]
+
+
 def get_floor_u_value(floor_type, area, perimeter, age_band, wall_type, insulation_thickness=None):
     """
     Estimate the u-value of a suspended floor, based on RdSap methodology
@@ -372,6 +398,12 @@ def get_floor_u_value(floor_type, area, perimeter, age_band, wall_type, insulati
        0.701
     """
 
+    if floor_type == "exposed_floor":
+        # In this case, we extract the u-value from table s12
+        # See section 5.6 of the RdSAP document for more details
+        # https://bregroup.com/wp-content/uploads/2019/09/RdSAP_2012_9.94-20-09-2019.pdf
+        return get_exposed_floor_uvalue(insulation_thickness, age_band)
+
     # Cleans our regularly inputted insulation thickness for usage in this function
     insulation_thickness = extract_insulation_thickness(insulation_thickness)