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https://github.com/Hestia-Homes/Model.git
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fixed error in reference to fuel type
This commit is contained in:
Khalim Conn-Kowlessar
parent
a9018a541e
commit
62d92f29e6
2 changed files with 56 additions and 25 deletions
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@ -1,6 +1,8 @@
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from enum import Enum
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from typing import List
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import pandas as pd
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from backend.app.plan.schemas import HousingType, WALL_INSULATION_MEASURES, ROOF_INSULATION_MEASURES, MEASURE_MAP
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@ -38,11 +40,6 @@ class Funding:
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self.floor_area_band = None
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self.project_scores_matrix = project_scores_matrix
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self.partial_project_scores_matrix = partial_project_scores_matrix
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# Filter on the starting band and floor area so we only do this once
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self.partial_project_scores_matrix = self.partial_project_scores_matrix[
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(self.partial_project_scores_matrix["Total Floor Area Band"] == self.floor_area_band) &
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(self.partial_project_scores_matrix["Starting Band"] == self.starting_sap_band)
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]
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self.whlg_eligible_postcodes = whlg_eligible_postcodes
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@ -408,16 +405,16 @@ class Funding:
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]:
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return 'Electric Storage Heaters Responsiveness >0.2'
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if mainheating["has_room_heaters"] and main_fuel["fuel_tye"] == "lpg":
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if mainheating["has_room_heaters"] and main_fuel["fuel_type"] == "lpg":
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return 'Bottled LPG Room Heaters'
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if mainheating["has_room_heaters"] and main_fuel["fuel_tye"] == "electricity":
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if mainheating["has_room_heaters"] and main_fuel["fuel_type"] == "electricity":
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return 'Electric Room Heaters'
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if mainheating["has_room_heaters"] and main_fuel["fuel_tye"] == "mains gas":
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if mainheating["has_room_heaters"] and main_fuel["fuel_type"] == "mains gas":
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return 'Gas Room Heaters'
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if mainheating["has_room_heaters"] and main_fuel["fuel_tye"] in [
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if mainheating["has_room_heaters"] and main_fuel["fuel_type"] in [
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"dual fuel appliance mineral and wood", "manufactured smokeless fuel"
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]:
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return 'Solid Fossil Room Heaters'
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@ -430,6 +427,7 @@ class Funding:
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mainheating: dict,
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main_fuel: dict,
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mainheat_energy_eff: str,
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filtered_pps_matrix: pd.DataFrame,
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current_wall_uvalue: float = None,
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is_partial: bool = False,
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existing_li_thickness: float = None,
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@ -438,7 +436,7 @@ class Funding:
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"""
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Calculate the partial project ABS score for a single measure.
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"""
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df = self.partial_project_scores_matrix
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# Filter on the starting band and floor area so we only do this once
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if measure_type == "internal_wall_insulation":
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if current_wall_uvalue is None:
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@ -446,7 +444,7 @@ class Funding:
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starting_str, ending_str = self.get_starting_ending_uvalues(current_wall_uvalue)
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measure_code = f"IWI_solid_{starting_str}_{ending_str}"
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pps = df[df["Measure_Type"] == measure_code]
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pps = filtered_pps_matrix[filtered_pps_matrix["Measure_Type"] == measure_code]
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if pps.shape[0] != 1:
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raise ValueError(f"Invalid IWI category: {measure_code}")
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@ -458,7 +456,7 @@ class Funding:
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starting_str, ending_str = self.get_starting_ending_uvalues(current_wall_uvalue)
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measure_code = f"EWI_solid_{starting_str}_{ending_str}"
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pps = df[df["Measure_Type"] == measure_code]
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pps = filtered_pps_matrix[filtered_pps_matrix["Measure_Type"] == measure_code]
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if pps.shape[0] != 1:
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raise ValueError(f"Invalid EWI category: {measure_code}")
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@ -466,7 +464,7 @@ class Funding:
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if measure_type == "cavity_wall_insulation":
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measure_code = "CWI_partial_fill" if is_partial else "CWI_0.033"
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pps = df[df["Measure_Type"] == measure_code]
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pps = filtered_pps_matrix[filtered_pps_matrix["Measure_Type"] == measure_code]
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if pps.shape[0] != 1:
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raise ValueError(f"Invalid CWI category: {measure_code}")
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@ -477,14 +475,14 @@ class Funding:
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raise ValueError("existing_li_thickness is required for LI")
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measure_code = "LI_lessequal100" if existing_li_thickness <= 100 else "LI_greater100"
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pps = df[df["Measure_Type"] == measure_code]
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pps = filtered_pps_matrix[filtered_pps_matrix["Measure_Type"] == measure_code]
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if pps.shape[0] != 1:
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raise ValueError(f"Invalid LI category: {measure_code}")
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return pps.squeeze()["Cost Savings"]
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if measure_type == "flat_roof_insulation":
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pps = df[df["Measure_Type"] == "FRI"]
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pps = filtered_pps_matrix[filtered_pps_matrix["Measure_Type"] == "FRI"]
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if pps.shape[0] != 1:
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raise ValueError("Invalid FRI category")
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return pps.squeeze()["Cost Savings"]
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@ -493,36 +491,38 @@ class Funding:
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# Use the more conservative score (unin is usually lower)
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# code = "RIRI_res_unin" if not is_roof_insulated else "RIRI_res_in"
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code = "RIRI_res_unin"
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pps = df[df["Measure_Type"] == code]
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pps = filtered_pps_matrix[filtered_pps_matrix["Measure_Type"] == code]
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if pps.shape[0] != 1:
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raise ValueError(f"Invalid RIRI category: {code}")
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return pps.squeeze()["Cost Savings"]
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if measure_type == "suspended_floor_insulation":
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pps = df[df["Measure_Type"] == "UFI"]
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pps = filtered_pps_matrix[filtered_pps_matrix["Measure_Type"] == "UFI"]
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if pps.shape[0] != 1:
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raise ValueError("Invalid UFI category")
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return pps.squeeze()["Cost Savings"]
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if measure_type == "solid_floor_insulation":
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pps = df[df["Measure_Type"] == "SFI"]
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pps = filtered_pps_matrix[filtered_pps_matrix["Measure_Type"] == "SFI"]
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if pps.shape[0] != 1:
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raise ValueError("Invalid SFI category")
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return pps.squeeze()["Cost Savings"]
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if measure_type == "solar_pv":
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pre_heating_system = self._map_to_pre_main_heating(mainheating, main_fuel, mainheat_energy_eff)
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solar_pps_df = df[
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(df["Measure_Type"] == "Solar_PV") & (df["Pre_Main_Heating_Source"] == pre_heating_system)
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solar_pps_df = filtered_pps_matrix[
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(filtered_pps_matrix["Measure_Type"] == "Solar_PV") &
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(filtered_pps_matrix["Pre_Main_Heating_Source"] == pre_heating_system)
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]
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return solar_pps_df.squeeze()["Cost Savings"]
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if measure_type == "air_source_heat_pump":
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pre_heating_system = self._map_to_pre_main_heating(mainheating, main_fuel, mainheat_energy_eff)
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pps = df[
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(df["Pre_Main_Heating_Source"] == pre_heating_system) &
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(df["Post_Main_Heating_Source"] == "Air to Water ASHP") &
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(df["Measure_Type"] == "B_Upgrade_nopreHCs") # We assume we'll be making a heating system upgrade
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pps = filtered_pps_matrix[
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(filtered_pps_matrix["Pre_Main_Heating_Source"] == pre_heating_system) &
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(filtered_pps_matrix["Post_Main_Heating_Source"] == "Air to Water ASHP") &
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(filtered_pps_matrix["Measure_Type"] == "B_Upgrade_nopreHCs")
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# We assume we'll be making a heating system upgrade
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]
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if pps.shape[0] != 1:
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@ -763,6 +763,11 @@ class Funding:
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self.ending_sap_band = self.get_sap_band(ending_sap)
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self.floor_area_band = self.get_floor_area_band(floor_area)
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filtered_pps_matrix = self.partial_project_scores_matrix[
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(self.partial_project_scores_matrix["Total Floor Area Band"] == self.floor_area_band) &
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(self.partial_project_scores_matrix["Starting Band"] == self.starting_sap_band)
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].copy()
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if self.tenure == "Private":
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# ECO4 PRS
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self.eco4_prs_eligibility(starting_sap, ending_sap, measure_types, has_solar, solar_eligible)
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@ -774,7 +779,6 @@ class Funding:
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self.eco4_funding = self.full_project_abs * (
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self.private_cavity_abs_rate if is_cavity else self.private_solid_abs_rate)
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elif self.tenure == "Social":
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# ECO4 Social
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self.eco4_sh_eligibility(
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@ -791,6 +795,11 @@ class Funding:
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# We calculate uplift innovation, where required
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project_uplifts = []
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for i, measure in enumerate(measure_types):
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if not innovation_flags[i]:
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# Capture 0 innovation uplift for debugging
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project_uplifts.append(0)
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continue
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pps = self.calculate_partial_project_abs(
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measure_type=measure,
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mainheating=mainheating,
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@ -799,6 +808,7 @@ class Funding:
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current_wall_uvalue=current_wall_uvalue,
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is_partial=is_partial,
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existing_li_thickness=existing_li_thickness,
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filtered_pps_matrix=filtered_pps_matrix,
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)
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project_uplifts.append(pps * uplifts[i])
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total_uplift = sum(project_uplifts)
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@ -817,6 +827,7 @@ class Funding:
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current_wall_uvalue=current_wall_uvalue,
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is_partial=is_partial,
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existing_li_thickness=existing_li_thickness,
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filtered_pps_matrix=filtered_pps_matrix
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)
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@ -994,8 +994,11 @@ def test_uplift(
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measures = [
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{"type": "solar_pv", "is_innovation": True, "uplift": 0.45},
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{"type": "internal_wall_insulation", "is_innovation": False, "uplift": 0},
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{"type": "cavity_wall_insulation", "is_innovation": False, "uplift": 0},
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{"type": "external_wall_insulation", "is_innovation": False, "uplift": 0},
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{"type": "loft_insulation", "is_innovation": False, "uplift": 0},
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{"type": "air_source_heat_pump", "is_innovation": False, "uplift": 0},
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{"type": "double_glazing", "is_innovation": False, "uplift": 0},
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{"type": "cavity_wall_insulation", "is_innovation": True, "uplift": 0.25},
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{"type": "high_heat_retention_storage_heaters", "is_innovation": False, "uplift": 0},
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]
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@ -1030,6 +1033,23 @@ for _, x in tqdm(epc_df.iterrows(), total=len(epc_df)):
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tenure="Social"
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)
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self = funding
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measures = measures
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starting_sap = 33
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ending_sap = 69
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floor_area = 71
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mainheat_description = x["MAINHEAT_DESCRIPTION"]
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heating_control_description = x["MAINHEATCONT_DESCRIPTION"]
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is_cavity = True
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current_wall_uvalue = 2
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is_partial = False
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existing_li_thickness = 0
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has_wall_insulation_recommendation = True
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has_roof_insulation_recommendation = True
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mainheating = h
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main_fuel = f
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mainheat_energy_eff = mainheat_energy_eff
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funding.check_funding(
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measures=measures,
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starting_sap=33,
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