mirror of
https://github.com/Hestia-Homes/Model.git
synced 2026-06-08 11:17:27 +00:00
minor change to mds api
This commit is contained in:
Khalim Conn-Kowlessar
parent
acc45eae64
commit
9217ef67f4
2 changed files with 117 additions and 88 deletions
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@ -841,6 +841,11 @@ async def build_mds(body: MdsRequest):
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epc_before = p.data["current-energy-rating"]
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heat_demand_before = p.data["energy-consumption-current"]
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carbon_before = p.data["co2-emissions-current"]
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current_adjusted_energy = AnnualBillSavings.adjust_energy_to_metered(
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epc_energy_consumption=heat_demand_before * p.floor_area,
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current_epc_rating=epc_before,
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)
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current_energy_bill = AnnualBillSavings.calculate_annual_bill(current_adjusted_energy)
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package_comparison = []
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for _id in recommendations[p.id].keys():
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@ -904,17 +909,11 @@ async def build_mds(body: MdsRequest):
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heat_demand_after = heat_demand_prediction["predictions"].values[-1]
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carbon_after = carbon_prediction["predictions"].values[-1]
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current_adjusted_energy = AnnualBillSavings.adjust_energy_to_metered(
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epc_energy_consumption=heat_demand_before * p.floor_area,
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current_epc_rating=epc_before,
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)
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expected_adjusted_energy = AnnualBillSavings.adjust_energy_to_metered(
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epc_energy_consumption=heat_demand_after * p.floor_area,
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current_epc_rating=epc_before,
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)
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current_energy_bill = AnnualBillSavings.calculate_annual_bill(current_adjusted_energy)
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expected_energy_bill = AnnualBillSavings.calculate_annual_bill(expected_adjusted_energy)
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bill_savings = current_energy_bill - expected_energy_bill
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@ -935,6 +934,7 @@ async def build_mds(body: MdsRequest):
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"carbon_after": carbon_after,
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"bill_savings": bill_savings,
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"energy_savings": energy_savings,
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"current_energy_bill": current_energy_bill,
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"meets_threshold": meets_threshold
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}
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)
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@ -965,6 +965,7 @@ async def build_mds(body: MdsRequest):
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"carbon_after": carbon_before,
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"bill_savings": 0,
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"energy_savings": 0,
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"current_energy_bill": current_energy_bill,
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"meets_threshold": False
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}
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@ -990,81 +991,27 @@ async def build_mds(body: MdsRequest):
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"heat_demand_after": package_comparison["heat_demand_after"],
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"carbon_before": package_comparison["carbon_before"],
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"carbon_after": package_comparison["carbon_after"],
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"bill_savings": package_comparison["bill_savings"],
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"energy_savings": package_comparison["energy_savings"],
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"bill_savings": round(package_comparison["bill_savings"], 2),
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"energy_savings": round(package_comparison["energy_savings"], 2),
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"current_energy_bill": round(package_comparison["current_energy_bill"], 2),
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"EWI": "EWI" if "external_wall_insulation" in package_comparison["measures"] else None,
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"CWI": "CWI" if "cavity_wall_insulation" in package_comparison["measures"] else None,
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"LI": "LI" if "loft_insulation" in package_comparison["measures"] else None,
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"ASHP Htg": "ASHP Htg" if "air_source_heat_pump" in package_comparison["measures"] else None,
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"Elec Storage": (
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"Elec Storage Htrs (Out of scope -Prov sum only)" if "high_heat_retention_storage_heaters" in
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package_comparison["measures"] else None
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),
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"Solar PV": "Solar PV" if "solar_pv" in package_comparison["measures"] else None,
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})
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results = pd.DataFrame(results)
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# For the different measures, we check the impact with a few debugging functions
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def check_mds(results, input_properties, recommendations):
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import ast
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walls_check = []
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hhr_check = []
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for p in input_properties:
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res = results[results["uprn"] == p.uprn]
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wall = p.walls
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heating = p.main_heating
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heating_controls = p.main_heating_controls
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wall_recommendation = [
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x for x in res["measures"].values[0] if
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x in ["internal_wall_insulation", "external_wall_insulation", "cavity_wall_insulation"]
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]
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walls_check, hhr_check = check_mds(results, input_properties, recommendations, optimise_measures)
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hhr_recommendation = [
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x for x in res["measures"].values[0] if
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x in ["high_heat_retention_storage_heaters"]
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]
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possible_measures = [ast.literal_eval(x) for x in list(recommendations[p.id].keys())]
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# Unlist them
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possible_measures = [x for sublist in possible_measures for x in sublist]
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possible_measures = list(set(possible_measures))
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if wall_recommendation:
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if len(wall_recommendation) > 1:
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raise Exception("something went wrong")
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wall_recommendation = wall_recommendation[0]
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else:
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wall_recommendation = None
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hhr_recommendation = hhr_recommendation[0] if hhr_recommendation else None
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walls_check.append(
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{
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"uprn": p.uprn,
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"address": p.address,
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"postcode": p.postcode,
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"conservation_status": p.spatial["conservation_status"],
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"is_listed_building": p.spatial["is_listed_building"],
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"is_heritage_building": p.spatial["is_heritage_building"],
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"wall": wall["clean_description"],
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"recommendation": wall_recommendation,
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"possible_measures": possible_measures,
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"selected_measures": res["measures"].values[0],
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}
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)
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hhr_check.append(
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{
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"uprn": p.uprn,
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"address": p.address,
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"postcode": p.postcode,
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"heating": heating["clean_description"],
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"heating_controls": heating_controls["clean_description"],
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"recommendation": hhr_recommendation,
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"possible_measures": possible_measures,
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"selected_measures": res["measures"].values[0],
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}
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)
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walls_check = pd.DataFrame(walls_check)
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hhr_check = pd.DataFrame(hhr_check)
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return walls_check, hhr_check
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walls_check, hhr_check = check_mds(results, input_properties, recommendations)
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results.to_excel("optimised mds_results 5th June.xlsx")
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results = []
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for p in input_properties:
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@ -1114,11 +1061,14 @@ async def build_mds(body: MdsRequest):
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)
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# TODO: We should determine if the home is gas & electricity or just electricity
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# Determine if the heating and hotwater was previously electric only or both
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current_energy_bill = AnnualBillSavings.calculate_annual_bill(
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current_adjusted_energy,
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kwh=current_adjusted_energy,
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)
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expected_energy_bill = AnnualBillSavings.calculate_annual_bill(
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expected_adjusted_energy,
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kwh=expected_adjusted_energy,
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)
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bill_savings = current_energy_bill - expected_energy_bill
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@ -1133,6 +1083,7 @@ async def build_mds(body: MdsRequest):
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to_append = {
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"config_address": config["address"],
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"config_postcode": config["postcode"],
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"uprn": p.uprn,
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"address": p.address,
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"postcode": p.postcode,
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"measures": measures,
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@ -1146,15 +1097,19 @@ async def build_mds(body: MdsRequest):
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"heat_demand_after": heat_demand_after,
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"carbon_before": carbon_before,
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"carbon_after": carbon_after,
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"bill_savings": bill_savings,
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"energy_savings": energy_savings,
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"bill_savings": round(bill_savings, 2),
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"energy_savings": round(energy_savings, 2),
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"current_energy_bill": round(current_energy_bill, 2),
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"fuel_type": p.main_fuel["fuel_type"],
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}
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results.append(to_append)
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results = pd.DataFrame(results)
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results["sap_uplift"] = results["sap_after"] - results["sap_before"]
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# results.to_excel("mds_results 30th May.xlsx")
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# results.to_excel("mds_results 5th June.xlsx")
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walls_check, hhr_check = check_mds(results, input_properties, recommendations, optimise_measures)
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except IntegrityError:
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logger.error("Database integrity error occurred", exc_info=True)
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@ -1174,3 +1129,80 @@ async def build_mds(body: MdsRequest):
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return Response(status_code=500, content="An unexpected error occurred.")
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finally:
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session.close()
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def check_mds(results, input_properties, recommendations, optimise_measures):
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import ast
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walls_check = []
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hhr_check = []
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for p in input_properties:
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res = results[results["uprn"] == p.uprn]
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wall = p.walls
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heating = p.main_heating
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heating_controls = p.main_heating_controls
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if optimise_measures:
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measures = res["measures"].values[0]
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else:
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measures = [list(z.keys())[0] for z in res["measures"].values[0]]
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wall_recommendation = [
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x for x in measures if
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x in ["internal_wall_insulation", "external_wall_insulation", "cavity_wall_insulation"]
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]
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hhr_recommendation = [
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x for x in measures if
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x in ["high_heat_retention_storage_heaters"]
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]
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if optimise_measures:
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possible_measures = [ast.literal_eval(x) for x in list(recommendations[p.id].keys())]
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# Unlist them
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possible_measures = [x for sublist in possible_measures for x in sublist]
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possible_measures = list(set(possible_measures))
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else:
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possible_measures = p.measures
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if wall_recommendation:
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if len(wall_recommendation) > 1:
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raise Exception("something went wrong")
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wall_recommendation = wall_recommendation[0]
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else:
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wall_recommendation = None
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hhr_recommendation = hhr_recommendation[0] if hhr_recommendation else None
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walls_check.append(
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{
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"uprn": p.uprn,
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"address": p.address,
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"postcode": p.postcode,
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"property_type": p.data['property-type'],
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"conservation_status": p.spatial["conservation_status"],
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"is_listed_building": p.spatial["is_listed_building"],
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"is_heritage_building": p.spatial["is_heritage_building"],
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"wall": wall["clean_description"],
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"recommendation": wall_recommendation,
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"possible_measures": possible_measures,
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"selected_measures": res["measures"].values[0],
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}
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)
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hhr_check.append(
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{
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"uprn": p.uprn,
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"address": p.address,
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"postcode": p.postcode,
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"heating": heating["clean_description"],
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"heating_controls": heating_controls["clean_description"],
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"recommendation": hhr_recommendation,
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"possible_measures": possible_measures,
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"selected_measures": res["measures"].values[0],
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}
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)
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walls_check = pd.DataFrame(walls_check)
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hhr_check = pd.DataFrame(hhr_check)
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return walls_check, hhr_check
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@ -11,8 +11,8 @@ load_dotenv(dotenv_path="backend/.env")
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EPC_AUTH_TOKEN = os.getenv("EPC_AUTH_TOKEN")
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searcher = SearchEpc(
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address1="Flat above 7 Malling Road",
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postcode="ME6 5AA",
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address1="108 Blacklands",
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postcode="ME19 6DP",
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auth_token=EPC_AUTH_TOKEN,
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os_api_key="",
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property_type=None,
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@ -20,11 +20,8 @@ searcher = SearchEpc(
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)
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res = searcher.estimate_epc(
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property_type="Flat",
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built_form="Mid-Terrace",
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lmks_to_drop=[
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"4c3714a59744ab2c6e60441f0fa0eb903f283c6c62d0691e108cadbc7b5a8caa",
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"363197839762013013017062127708717",
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"363197811132009091518041845968302"
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]
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property_type="Bungalow",
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built_form="Detached",
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lmks_to_drop=["849273656952012102323315196229804"],
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exclude_old=True
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)
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