using elmhurst roof area methodology

backend/Property.py

@@ -623,9 +623,7 @@ class Property:
         self.find_energy_sources()
         self.set_current_energy(kwh_client, kwh_predictions)
 
-    def set_solar_panel_configuration(
+    def set_solar_panel_configuration(self, solar_panel_configuration):
-        self, solar_panel_configuration, roof_area
-    ):
         """
         This funtion inserts the solar panel configuration into the property object
         """
@@ -634,22 +632,11 @@ class Property:
         if not self.roof["is_flat"]:
             default_roof_area = estimate_pitched_roof_area(
                 floor_area=self.insulation_floor_area,
-                floor_height=self.floor_height
             )
         else:
             default_roof_area = self.insulation_floor_area
 
-        # Keep a record
+        self.roof_area = default_roof_area
-        self.roof_area_comparison = {
-            "api": roof_area,
-            "estimated": default_roof_area
-        }
-
-        # We also set the roof area
-        if roof_area is None:
-            self.roof_area = default_roof_area
-        else:
-            self.roof_area = roof_area
 
     def set_current_energy(self, kwh_client, kwh_predictions):
         """

backend/apis/GoogleSolarApi.py

@@ -766,7 +766,6 @@ class GoogleSolarApi:
                         "panel_performance": cls.default_panel_performance(property_instance=property_instance),
                         "unit_share_of_energy": 1
                     },
-                    roof_area=None
                 )
                 continue
 

recommendations/recommendation_utils.py

@@ -205,7 +205,7 @@ def get_wall_u_value(
 
         mapped_value = wall_uvalues_df[
             wall_uvalues_df["Wall_type"] == mapped_description
-        ][age_band].values[0]
+            ][age_band].values[0]
 
         if pd.isnull(mapped_value) and "Park home" in mapped_description:
             # We don't know enough in this case so we default to 0
@@ -505,7 +505,7 @@ def get_floor_u_value(
         insulation_lookup = s11[
             s11["Age_band"].str.contains(age_band) & s11["Floor_construction"]
             == floor_type
-        ]
+            ]
         if insulation_lookup.empty:
             insulation_thickness = 0
         else:
@@ -700,34 +700,17 @@ def convert_thickness_to_numeric(string_thickness, is_pitched, is_flat):
     return int(string_thickness)
 
 
-def estimate_pitched_roof_area(floor_area: float, floor_height: float) -> float:
+def estimate_pitched_roof_area(floor_area: float) -> float:
     """
-    This function will estimate the area of a pitched roof, given the floor area below the roof and the floor
+    This function mimics the methodology for calculating floor area in Elmhurst, so that we can simulate the outcomes
-    height of the property.
+    in a way that is consistent with the Elmhurst methodology.
-
-    Given limited information about the home, this is a very rough method to estimate the roof area and we
-    assume the the room is a gable roof.
-
-    We assume a roughly average pitch of 45 degrees
-
-    Note that both floor area and height should be in the same units. E.g. if floor area is meters squared,
-    floor height should be in meters
 
     :param floor_area:      area of the home's floor
-    :param floor_height:    height of the home's floors
     :return:                Numerical estimate of the surface area of the top of the pitched roof
     """
 
-    # We estimate the length of the wall by just modelling the house as a square
+    scalar = 1.0571283428862048
-    wall_width = np.sqrt(floor_area)
+    return scalar * (floor_area / np.cos(np.radians(30)))
-
-    # We're modelling the roof as two triangles where we know two of the three sides.
-    # The floor height makes up one side and half of the wall width makes up the other side
-    slope = np.sqrt(np.square(wall_width / 2) + np.square(floor_height))
-
-    area = 2 * (slope * wall_width)
-
-    return area
 
 
 def estimate_windows(