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https://github.com/Hestia-Homes/Model.git
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Added ashp unit tests
This commit is contained in:
Khalim Conn-Kowlessar
parent
f21221d721
commit
56472f201e
4 changed files with 883 additions and 2 deletions
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.idea/Model.iml
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.idea/Model.iml
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@ -7,7 +7,7 @@
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<sourceFolder url="file://$MODULE_DIR$/open_uprn" isTestSource="false" />
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<sourceFolder url="file://$MODULE_DIR$/recommendations" isTestSource="false" />
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</content>
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<orderEntry type="jdk" jdkName="Python 3.10 (backend)" jdkType="Python SDK" />
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<orderEntry type="jdk" jdkName="Python 3.10 (model_data)" jdkType="Python SDK" />
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<orderEntry type="sourceFolder" forTests="false" />
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</component>
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<component name="PyNamespacePackagesService">
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2
.idea/misc.xml
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2
.idea/misc.xml
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@ -3,7 +3,7 @@
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<component name="Black">
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<option name="sdkName" value="Python 3.10 (backend)" />
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</component>
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<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10 (backend)" project-jdk-type="Python SDK" />
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<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10 (model_data)" project-jdk-type="Python SDK" />
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<component name="PythonCompatibilityInspectionAdvertiser">
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<option name="version" value="3" />
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</component>
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@ -391,3 +391,17 @@ def app():
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investment_50m = combined_aggregate[combined_aggregate["cumulative_value"] <= 51_000_000]
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properties["WALLS_DESCRIPTION"].value_counts(normalize=True)
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def company_aggregation():
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company_ownership = pd.read_csv("/Users/khalimconn-kowlessar/Downloads/CCOD_FULL_2024_04.csv")
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aggregation = (
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company_ownership
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.groupby(["Proprietor Name (1)", "Company Registration No. (1)"])
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["Property Address"]
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.count()
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.reset_index(name="Number of Properties")
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)
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aggregation = aggregation.sort_values("Number of Properties", ascending=False)
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aggregation.to_excel("Company ownership aggregation.xlsx")
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@ -1,6 +1,154 @@
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import pandas as pd
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import msgpack
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from datetime import datetime
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from utils.s3 import read_dataframe_from_s3_parquet, read_from_s3
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from backend.Property import Property
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from recommendations.HeatingRecommender import HeatingRecommender
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from recommendations.Recommendations import Recommendations
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from etl.epc.Record import EPCRecord
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from etl.solar.SolarPhotoSupply import SolarPhotoSupply
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from backend.ml_models.api import ModelApi
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def find_examples():
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""" Some scrappy helper code to find EPC examples"""
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# Let's look for some testing data, where the only thing different pre and post is the installation of an
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# air source heat pump
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data = read_dataframe_from_s3_parquet(
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bucket_name="retrofit-data-dev",
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file_key="sap_change_model/2024-03-24-15-51-13/dataset_no_cleaning.parquet"
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)
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# Firstly, take records where before there was no air source heat pump and afterwards there was
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data = data[
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data["has_air_source_heat_pump_ending"] & ~data["has_air_source_heat_pump"]
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]
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# Start with a property that has a boiler
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data = data[data["has_boiler"]]
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static_columns = [
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# Walls
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'walls_thermal_transmittance_ending',
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'is_filled_cavity_ending',
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'is_park_home_ending',
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'walls_insulation_thickness_ending',
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'external_insulation_ending',
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'internal_insulation_ending',
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# Floors
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# 'floor_thermal_transmittance_ending', # Don't subset on this, because it changes based on floor area
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'floor_insulation_thickness_ending',
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# Roof
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'roof_thermal_transmittance_ending',
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'is_at_rafters_ending',
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'roof_insulation_thickness_ending',
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# Hot water - air source heat pump will shange the hot water system (probably from whatever it was -> main)
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# 'heater_type_ending',
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# 'system_type_ending',
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# 'thermostat_characteristics_ending',
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# 'heating_scope_ending',
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# 'energy_recovery_ending',
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# 'hotwater_tariff_type_ending',
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# 'extra_features_ending',
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# 'chp_systems_ending',
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# 'distribution_system_ending',
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# 'no_system_present_ending',
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# 'appliance_ending',
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# Heating - Will change when installing an ASHP
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# 'has_radiators_ending',
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# 'has_fan_coil_units_ending',
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# 'has_pipes_in_screed_above_insulation_ending',
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# 'has_pipes_in_insulated_timber_floor_ending',
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# 'has_pipes_in_concrete_slab_ending',
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# 'has_boiler_ending',
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# 'has_air_source_heat_pump_ending', # We want the air source heat pump to change
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# 'has_room_heaters_ending',
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# 'has_electric_storage_heaters_ending',
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# 'has_warm_air_ending',
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# 'has_electric_underfloor_heating_ending',
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# 'has_electric_ceiling_heating_ending',
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# 'has_community_scheme_ending',
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# 'has_ground_source_heat_pump_ending',
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# 'has_no_system_present_ending',
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# 'has_portable_electric_heaters_ending',
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# 'has_water_source_heat_pump_ending',
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# 'has_electric_heat_pump_ending',
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# 'has_micro-cogeneration_ending',
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# 'has_solar_assisted_heat_pump_ending',
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# 'has_exhaust_source_heat_pump_ending',
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# 'has_community_heat_pump_ending',
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# 'has_electric_ending',
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# 'has_mains_gas_ending',
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# 'has_wood_logs_ending', 'has_coal_ending', 'has_oil_ending',
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# 'has_wood_pellets_ending', 'has_anthracite_ending', 'has_dual_fuel_mineral_and_wood_ending',
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# 'has_smokeless_fuel_ending', 'has_lpg_ending', 'has_b30k_ending', 'has_electricaire_ending',
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# 'has_assumed_for_most_rooms_ending', 'has_underfloor_heating_ending',
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# 'thermostatic_control_ending',
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# 'charging_system_ending',
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# 'switch_system_ending',
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# 'no_control_ending',
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# 'dhw_control_ending',
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# 'community_heating_ending',
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# 'multiple_room_thermostats_ending',
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# 'auxiliary_systems_ending',
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# 'trvs_ending',
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# 'rate_control_ending',
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# Window
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'glazing_type_ending',
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# Fuel - could change with ASHP
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# 'fuel_type_ending',
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# 'main-fuel_tariff_type_ending',
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# 'is_community_ending',
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# 'no_individual_heating_or_community_network_ending',
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# 'complex_fuel_type_ending',
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'mechanical_ventilation_ending', 'secondheat_description_ending', 'glazed_type_ending',
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'multi_glaze_proportion_ending', 'low_energy_lighting_ending', 'number_open_fireplaces_ending',
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'solar_water_heating_flag_ending',
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'photo_supply_ending',
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'energy_tariff_ending',
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'extension_count_ending',
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'total_floor_area_ending',
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# 'hot_water_energy_eff_ending',
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'floor_energy_eff_ending',
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'windows_energy_eff_ending',
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'walls_energy_eff_ending',
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'sheating_energy_eff_ending',
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'roof_energy_eff_ending',
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# 'mainheat_energy_eff_ending',
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# 'mainheatc_energy_eff_ending',
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'lighting_energy_eff_ending',
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'number_habitable_rooms_ending',
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'number_heated_rooms_ending',
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]
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for col in static_columns:
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base_starting = col.split("_ending")[0]
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if base_starting + "_starting" in data.columns:
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starting_col = base_starting + "_starting"
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else:
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starting_col = base_starting
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# Filter
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print("Column: %s" % col)
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print("Starting size: %s" % data.shape[0])
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data = data[data[starting_col] == data[col]]
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print("Ending size: %s" % data.shape[0])
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z = data[['uprn', col, starting_col]]
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# Great example UPRNs
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# 100030969273
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# 10034685399 - Completely transforms the heating and hot water systems in the home (goes from oil -> electricity)
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# 100091200828 - goes from a liquid petroleum gas boiler to ashp
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# Look for starting with a gas boiler
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data[
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data["has_boiler"] & data["has_radiators"] & data["has_mains_gas"] & ~data["has_boiler_ending"]
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]
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# UPRN: 100011776843
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class TestAirSourceHeatPump:
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@ -75,3 +223,722 @@ class TestAirSourceHeatPump:
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recommender.recommend(phase=0)
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assert recommender.recommendation is None
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def test_air_source_heat_pump_gas_boiler_starting(self):
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starting_epc = {
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'low-energy-fixed-light-count': '', 'address': '430 Gidlow Lane', 'uprn-source': 'Energy Assessor',
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'floor-height': '2.62', 'heating-cost-potential': '599', 'unheated-corridor-length': '',
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'hot-water-cost-potential': '67', 'construction-age-band': 'England and Wales: 1950-1966',
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'potential-energy-rating': 'C', 'mainheat-energy-eff': 'Good', 'windows-env-eff': 'Good',
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'lighting-energy-eff': 'Very Good', 'environment-impact-potential': '72',
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'glazed-type': 'double glazing installed during or after 2002', 'heating-cost-current': '913',
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'address3': '', 'mainheatcont-description': 'Programmer, no room thermostat', 'sheating-energy-eff': 'N/A',
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'property-type': 'House', 'local-authority-label': 'Wigan', 'fixed-lighting-outlets-count': '9',
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'energy-tariff': 'Single', 'mechanical-ventilation': 'natural', 'hot-water-cost-current': '210',
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'county': '', 'postcode': 'WN6 8RG', 'solar-water-heating-flag': 'N', 'constituency': 'E14001039',
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'co2-emissions-potential': '2.6', 'number-heated-rooms': '4',
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'floor-description': 'Solid, no insulation (assumed)', 'energy-consumption-potential': '180',
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'local-authority': 'E08000010', 'built-form': 'Mid-Terrace', 'number-open-fireplaces': '0',
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'windows-description': 'Fully double glazed', 'glazed-area': 'Normal', 'inspection-date': '2022-02-15',
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'mains-gas-flag': 'Y', 'co2-emiss-curr-per-floor-area': '78', 'address1': '430 Gidlow Lane',
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'heat-loss-corridor': '', 'flat-storey-count': '', 'constituency-label': 'Wigan',
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'roof-energy-eff': 'Very Poor', 'total-floor-area': '80.0', 'building-reference-number': '10002334112',
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'environment-impact-current': '38', 'co2-emissions-current': '6.2',
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'roof-description': 'Pitched, no insulation (assumed)', 'floor-energy-eff': 'N/A',
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'number-habitable-rooms': '4', 'address2': '', 'hot-water-env-eff': 'Poor', 'posttown': 'WIGAN',
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'mainheatc-energy-eff': 'Very Poor', 'main-fuel': 'mains gas (not community)',
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'lighting-env-eff': 'Very Good', 'windows-energy-eff': 'Good', 'floor-env-eff': 'N/A',
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'sheating-env-eff': 'N/A', 'lighting-description': 'Low energy lighting in all fixed outlets',
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'roof-env-eff': 'Very Poor', 'walls-energy-eff': 'Average', 'photo-supply': '0.0',
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'lighting-cost-potential': '67', 'mainheat-env-eff': 'Good', 'multi-glaze-proportion': '100',
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'main-heating-controls': '', 'lodgement-datetime': '2022-02-23 16:39:41', 'flat-top-storey': '',
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'current-energy-rating': 'E', 'secondheat-description': 'Room heaters, mains gas',
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'walls-env-eff': 'Average', 'transaction-type': 'ECO assessment', 'uprn': '100011776843',
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'current-energy-efficiency': '45', 'energy-consumption-current': '441',
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'mainheat-description': 'Boiler and radiators, mains gas', 'lighting-cost-current': '67',
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'lodgement-date': '2022-02-23', 'extension-count': '1', 'mainheatc-env-eff': 'Very Poor',
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'lmk-key': '46cb404438a6d88ddff8965cab8b3027ec15c32d93e0b6a5f0381a5109b9bb0d', 'wind-turbine-count': '0',
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'tenure': 'Owner-occupied', 'floor-level': '', 'potential-energy-efficiency': '77',
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'hot-water-energy-eff': 'Poor', 'low-energy-lighting': '100',
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'walls-description': 'Cavity wall, filled cavity',
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'hotwater-description': 'From main system, no cylinder thermostat'
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}
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ending_epc = {
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'low-energy-fixed-light-count': '', 'address': '430 Gidlow Lane', 'uprn-source': 'Energy Assessor',
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'floor-height': '2.62', 'heating-cost-potential': '803', 'unheated-corridor-length': '',
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'hot-water-cost-potential': '292', 'construction-age-band': 'England and Wales: 1950-1966',
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'potential-energy-rating': 'C', 'mainheat-energy-eff': 'Very Good', 'windows-env-eff': 'Good',
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'lighting-energy-eff': 'Very Good', 'environment-impact-potential': '78',
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'glazed-type': 'double glazing installed during or after 2002', 'heating-cost-current': '861',
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'address3': '', 'mainheatcont-description': 'Time and temperature zone control',
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'sheating-energy-eff': 'N/A', 'property-type': 'House', 'local-authority-label': 'Wigan',
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'fixed-lighting-outlets-count': '9', 'energy-tariff': 'Single', 'mechanical-ventilation': 'natural',
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'hot-water-cost-current': '434', 'county': '', 'postcode': 'WN6 8RG', 'solar-water-heating-flag': 'N',
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'constituency': 'E14001039', 'co2-emissions-potential': '2.0', 'number-heated-rooms': '4',
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'floor-description': 'Solid, no insulation (assumed)', 'energy-consumption-potential': '147',
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'local-authority': 'E08000010', 'built-form': 'Mid-Terrace', 'number-open-fireplaces': '0',
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'windows-description': 'Fully double glazed', 'glazed-area': 'Normal', 'inspection-date': '2022-05-11',
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'mains-gas-flag': 'Y', 'co2-emiss-curr-per-floor-area': '43', 'address1': '430 Gidlow Lane',
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'heat-loss-corridor': '', 'flat-storey-count': '', 'constituency-label': 'Wigan',
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'roof-energy-eff': 'Very Poor', 'total-floor-area': '80.0', 'building-reference-number': '10002334112',
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'environment-impact-current': '63', 'co2-emissions-current': '3.4',
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'roof-description': 'Pitched, no insulation (assumed)', 'floor-energy-eff': 'N/A',
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'number-habitable-rooms': '4', 'address2': '', 'hot-water-env-eff': 'Poor', 'posttown': 'WIGAN',
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'mainheatc-energy-eff': 'Very Good', 'main-fuel': 'electricity (not community)',
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'lighting-env-eff': 'Very Good', 'windows-energy-eff': 'Good', 'floor-env-eff': 'N/A',
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'sheating-env-eff': 'N/A', 'lighting-description': 'Low energy lighting in all fixed outlets',
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'roof-env-eff': 'Very Poor', 'walls-energy-eff': 'Average', 'photo-supply': '0.0',
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'lighting-cost-potential': '67', 'mainheat-env-eff': 'Very Good', 'multi-glaze-proportion': '100',
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'main-heating-controls': '', 'lodgement-datetime': '2022-06-06 13:01:20', 'flat-top-storey': '',
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'current-energy-rating': 'E', 'secondheat-description': 'Room heaters, mains gas',
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'walls-env-eff': 'Average', 'transaction-type': 'ECO assessment', 'uprn': '100011776843',
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'current-energy-efficiency': '53', 'energy-consumption-current': '252',
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'mainheat-description': 'Air source heat pump, radiators, electric', 'lighting-cost-current': '67',
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'lodgement-date': '2022-06-06', 'extension-count': '1', 'mainheatc-env-eff': 'Very Good',
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'lmk-key': '672d5947f3d4a55d97255af71651d6127a939418fa66a687070af77e0ba90df2', 'wind-turbine-count': '0',
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'tenure': 'Owner-occupied', 'floor-level': '', 'potential-energy-efficiency': '70',
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'hot-water-energy-eff': 'Very Poor', 'low-energy-lighting': '100',
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'walls-description': 'Cavity wall, filled cavity', 'hotwater-description': 'From main system'
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}
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# differences = []
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# for k, v in ending_epc.items():
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# if v != starting_epc[k]:
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# differences.append(
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# {
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# "variable": k,
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# "starting_value": starting_epc[k],
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# "ending_value": v
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# }
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# )
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# differences = pd.DataFrame(differences)
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#
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# diffs = differences[
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# differences["variable"].isin(
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# [
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# "mainheat-energy-eff",
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# "mainheatcont-description",
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# "mainheatc-energy-eff",
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# "main-fuel",
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# "mainheat-env-eff",
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# "mainheat-description",
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# "hot-water-energy-eff",
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# "hotwater-description"
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# ]
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# )
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# ]
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cleaning_data = read_dataframe_from_s3_parquet(
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bucket_name="retrofit-data-dev", file_key="sap_change_model/cleaning_dataset.parquet",
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)
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cleaned = read_from_s3(
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s3_file_name="cleaned_epc_data/cleaned.bson",
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bucket_name="retrofit-data-dev"
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)
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cleaned = msgpack.unpackb(cleaned, raw=False)
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photo_supply_lookup, floor_area_decile_thresholds = SolarPhotoSupply.load(bucket="retrofit-data-dev")
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epc = EPCRecord(
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epc_records={
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'original_epc': starting_epc,
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'full_sap_epc': {},
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'old_data': []
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},
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run_mode="newdata",
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cleaning_data=cleaning_data
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)
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home = Property(
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id=0,
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address="",
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postcode="",
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epc_record=epc,
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already_installed={},
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non_invasive_recommendations={},
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)
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home.in_conservation_area = False
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home.is_listed = False
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home.is_heritage = False
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home.restricted_measures = True
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home.get_components(
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cleaned=cleaned,
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photo_supply_lookup=photo_supply_lookup,
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floor_area_decile_thresholds=floor_area_decile_thresholds
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)
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recommender = HeatingRecommender(property_instance=home)
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recommender.recommend_air_source_heat_pump(phase=0, has_cavity_or_loft_recommendations=False)
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# Patch - for this property, the hot water energy efficiency is very poor. it's not clear why this is,
|
||||
# but we insert this for this test
|
||||
recommender.heating_recommendations[0]["simulation_config"]["hot_water_energy_eff_ending"] = "Very Poor"
|
||||
|
||||
property_recommendations = Recommendations.insert_temp_recommendation_id([recommender.heating_recommendations])
|
||||
|
||||
assert len(recommender.heating_recommendations) == 1
|
||||
|
||||
home.create_base_difference_epc_record(cleaned_lookup=cleaned)
|
||||
home.adjust_difference_record_with_recommendations(
|
||||
property_recommendations, []
|
||||
)
|
||||
|
||||
scoring_data = pd.DataFrame(home.recommendations_scoring_data).drop(
|
||||
columns=["rdsap_change", "heat_demand_change", "carbon_change", "sap_ending", "heat_demand_ending",
|
||||
"carbon_ending"]
|
||||
)
|
||||
|
||||
model_api = ModelApi(portfolio_id="ashp-test", timestamp=datetime.now().isoformat())
|
||||
model_api.MODEL_PREFIXES = ["sap_change_predictions"]
|
||||
|
||||
predictions_dict = model_api.predict_all(
|
||||
df=scoring_data,
|
||||
bucket="retrofit-data-dev",
|
||||
prediction_buckets={
|
||||
"sap_change_predictions": "retrofit-sap-predictions-dev",
|
||||
}
|
||||
)
|
||||
assert predictions_dict["sap_change_predictions"]["predictions"].values[0] == 52.2
|
||||
|
||||
def test_air_source_heat_pump_gas_boiler_starting_2(self):
|
||||
"""
|
||||
This property seems to have miniscule movement in SAP - just 2 poins
|
||||
:return:
|
||||
"""
|
||||
|
||||
starting_epc = {
|
||||
'low-energy-fixed-light-count': '', 'address': '31 Whinney Hill Park', 'uprn-source': 'Energy Assessor',
|
||||
'floor-height': '2.3', 'heating-cost-potential': '394', 'unheated-corridor-length': '',
|
||||
'hot-water-cost-potential': '48', 'construction-age-band': 'England and Wales: 1967-1975',
|
||||
'potential-energy-rating': 'B', 'mainheat-energy-eff': 'Good', 'windows-env-eff': 'Average',
|
||||
'lighting-energy-eff': 'Good', 'environment-impact-potential': '87',
|
||||
'glazed-type': 'double glazing, unknown install date', 'heating-cost-current': '487', 'address3': '',
|
||||
'mainheatcont-description': 'Programmer, room thermostat and TRVs', 'sheating-energy-eff': 'N/A',
|
||||
'property-type': 'Bungalow', 'local-authority-label': 'Calderdale', 'fixed-lighting-outlets-count': '5',
|
||||
'energy-tariff': 'Single', 'mechanical-ventilation': 'natural', 'hot-water-cost-current': '86',
|
||||
'county': '', 'postcode': 'HD6 2PX', 'solar-water-heating-flag': 'N', 'constituency': 'E14000614',
|
||||
'co2-emissions-potential': '0.8', 'number-heated-rooms': '2',
|
||||
'floor-description': 'Solid, no insulation (assumed)', 'energy-consumption-potential': '105',
|
||||
'local-authority': 'E08000033', 'built-form': 'End-Terrace', 'number-open-fireplaces': '0',
|
||||
'windows-description': 'Fully double glazed', 'glazed-area': 'Normal', 'inspection-date': '2021-11-25',
|
||||
'mains-gas-flag': 'Y', 'co2-emiss-curr-per-floor-area': '56', 'address1': '31 Whinney Hill Park',
|
||||
'heat-loss-corridor': '', 'flat-storey-count': '', 'constituency-label': 'Calder Valley',
|
||||
'roof-energy-eff': 'Good', 'total-floor-area': '44.0', 'building-reference-number': '10001772583',
|
||||
'environment-impact-current': '62', 'co2-emissions-current': '2.5',
|
||||
'roof-description': 'Pitched, 250 mm loft insulation', 'floor-energy-eff': 'N/A',
|
||||
'number-habitable-rooms': '2', 'address2': '', 'hot-water-env-eff': 'Good', 'posttown': 'BRIGHOUSE',
|
||||
'mainheatc-energy-eff': 'Good', 'main-fuel': 'mains gas (not community)', 'lighting-env-eff': 'Good',
|
||||
'windows-energy-eff': 'Average', 'floor-env-eff': 'N/A', 'sheating-env-eff': 'N/A',
|
||||
'lighting-description': 'Low energy lighting in 60% of fixed outlets', 'roof-env-eff': 'Good',
|
||||
'walls-energy-eff': 'Average', 'photo-supply': '0.0', 'lighting-cost-potential': '40',
|
||||
'mainheat-env-eff': 'Good', 'multi-glaze-proportion': '100', 'main-heating-controls': '',
|
||||
'lodgement-datetime': '2021-11-25 11:39:35', 'flat-top-storey': '', 'current-energy-rating': 'D',
|
||||
'secondheat-description': 'Room heaters, electric', 'walls-env-eff': 'Average',
|
||||
'transaction-type': 'rental', 'uprn': '100051304421', 'current-energy-efficiency': '62',
|
||||
'energy-consumption-current': '322', 'mainheat-description': 'Boiler and radiators, mains gas',
|
||||
'lighting-cost-current': '56', 'lodgement-date': '2021-11-25', 'extension-count': '0',
|
||||
'mainheatc-env-eff': 'Good', 'lmk-key': '077f70657e9c3f1f0ce5392798398398616b159493b2a8ca2338961596631c27',
|
||||
'wind-turbine-count': '0', 'tenure': 'Rented (social)', 'floor-level': '',
|
||||
'potential-energy-efficiency': '86', 'hot-water-energy-eff': 'Good', 'low-energy-lighting': '60',
|
||||
'walls-description': 'Cavity wall, filled cavity', 'hotwater-description': 'From main system'
|
||||
}
|
||||
|
||||
ending_epc = {
|
||||
'low-energy-fixed-light-count': '', 'address': '31 Whinney Hill Park',
|
||||
'uprn-source': 'Energy Assessor', 'floor-height': '2.3', 'heating-cost-potential': '277',
|
||||
'unheated-corridor-length': '', 'hot-water-cost-potential': '266',
|
||||
'construction-age-band': 'England and Wales: 1967-1975', 'potential-energy-rating': 'B',
|
||||
'mainheat-energy-eff': 'Very Good', 'windows-env-eff': 'Average', 'lighting-energy-eff': 'Good',
|
||||
'environment-impact-potential': '90', 'glazed-type': 'double glazing, unknown install date',
|
||||
'heating-cost-current': '331', 'address3': '',
|
||||
'mainheatcont-description': 'Programmer and room thermostat', 'sheating-energy-eff': 'N/A',
|
||||
'property-type': 'Bungalow', 'local-authority-label': 'Calderdale',
|
||||
'fixed-lighting-outlets-count': '5', 'energy-tariff': 'Single',
|
||||
'mechanical-ventilation': 'natural', 'hot-water-cost-current': '404', 'county': '',
|
||||
'postcode': 'HD6 2PX', 'solar-water-heating-flag': 'N', 'constituency': 'E14000614',
|
||||
'co2-emissions-potential': '0.7', 'number-heated-rooms': '2',
|
||||
'floor-description': 'Solid, no insulation (assumed)', 'energy-consumption-potential': '92',
|
||||
'local-authority': 'E08000033', 'built-form': 'End-Terrace', 'number-open-fireplaces': '0',
|
||||
'windows-description': 'Fully double glazed', 'glazed-area': 'Normal',
|
||||
'inspection-date': '2021-11-25', 'mains-gas-flag': 'Y', 'co2-emiss-curr-per-floor-area': '48',
|
||||
'address1': '31 Whinney Hill Park', 'heat-loss-corridor': '', 'flat-storey-count': '',
|
||||
'constituency-label': 'Calder Valley', 'roof-energy-eff': 'Good', 'total-floor-area': '44.0',
|
||||
'building-reference-number': '10001772583', 'environment-impact-current': '68',
|
||||
'co2-emissions-current': '2.1', 'roof-description': 'Pitched, 250 mm loft insulation',
|
||||
'floor-energy-eff': 'N/A', 'number-habitable-rooms': '2', 'address2': '',
|
||||
'hot-water-env-eff': 'Poor', 'posttown': 'BRIGHOUSE', 'mainheatc-energy-eff': 'Average',
|
||||
'main-fuel': 'electricity (not community)', 'lighting-env-eff': 'Good',
|
||||
'windows-energy-eff': 'Average', 'floor-env-eff': 'N/A', 'sheating-env-eff': 'N/A',
|
||||
'lighting-description': 'Low energy lighting in 60% of fixed outlets', 'roof-env-eff': 'Good',
|
||||
'walls-energy-eff': 'Average', 'photo-supply': '0.0', 'lighting-cost-potential': '40',
|
||||
'mainheat-env-eff': 'Very Good', 'multi-glaze-proportion': '100', 'main-heating-controls': '',
|
||||
'lodgement-datetime': '2022-03-23 16:06:21', 'flat-top-storey': '', 'current-energy-rating': 'D',
|
||||
'secondheat-description': 'Room heaters, electric', 'walls-env-eff': 'Average',
|
||||
'transaction-type': 'rental', 'uprn': '100051304421', 'current-energy-efficiency': '64',
|
||||
'energy-consumption-current': '283',
|
||||
'mainheat-description': 'Air source heat pump, radiators, electric',
|
||||
'lighting-cost-current': '57', 'lodgement-date': '2022-03-23', 'extension-count': '0',
|
||||
'mainheatc-env-eff': 'Average',
|
||||
'lmk-key': '6296248141447b53426a40f1c39da17dad5f4786485db55ee38737891111a4d4',
|
||||
'wind-turbine-count': '0', 'tenure': 'Rented (social)', 'floor-level': '',
|
||||
'potential-energy-efficiency': '89', 'hot-water-energy-eff': 'Very Poor',
|
||||
'low-energy-lighting': '60', 'walls-description': 'Cavity wall, filled cavity',
|
||||
'hotwater-description': 'From main system'
|
||||
}
|
||||
|
||||
# differences = []
|
||||
# for k, v in ending_epc.items():
|
||||
# if v != starting_epc[k]:
|
||||
# differences.append(
|
||||
# {
|
||||
# "variable": k,
|
||||
# "starting_value": starting_epc[k],
|
||||
# "ending_value": v
|
||||
# }
|
||||
# )
|
||||
# differences = pd.DataFrame(differences)
|
||||
#
|
||||
# diffs = differences[
|
||||
# differences["variable"].isin(
|
||||
# [
|
||||
# "mainheat-energy-eff",
|
||||
# "mainheatcont-description",
|
||||
# "mainheatc-energy-eff",
|
||||
# "main-fuel",
|
||||
# "mainheat-env-eff",
|
||||
# "mainheat-description",
|
||||
# "hot-water-energy-eff",
|
||||
# "hotwater-description"
|
||||
# ]
|
||||
# )
|
||||
# ]
|
||||
|
||||
cleaning_data = read_dataframe_from_s3_parquet(
|
||||
bucket_name="retrofit-data-dev", file_key="sap_change_model/cleaning_dataset.parquet",
|
||||
)
|
||||
|
||||
cleaned = read_from_s3(
|
||||
s3_file_name="cleaned_epc_data/cleaned.bson",
|
||||
bucket_name="retrofit-data-dev"
|
||||
)
|
||||
cleaned = msgpack.unpackb(cleaned, raw=False)
|
||||
|
||||
photo_supply_lookup, floor_area_decile_thresholds = SolarPhotoSupply.load(bucket="retrofit-data-dev")
|
||||
|
||||
epc = EPCRecord(
|
||||
epc_records={
|
||||
'original_epc': starting_epc,
|
||||
'full_sap_epc': {},
|
||||
'old_data': []
|
||||
},
|
||||
run_mode="newdata",
|
||||
cleaning_data=cleaning_data
|
||||
)
|
||||
|
||||
home = Property(
|
||||
id=0,
|
||||
address="",
|
||||
postcode="",
|
||||
epc_record=epc,
|
||||
already_installed={},
|
||||
non_invasive_recommendations={},
|
||||
)
|
||||
home.in_conservation_area = False
|
||||
home.is_listed = False
|
||||
home.is_heritage = False
|
||||
home.restricted_measures = True
|
||||
home.get_components(
|
||||
cleaned=cleaned,
|
||||
photo_supply_lookup=photo_supply_lookup,
|
||||
floor_area_decile_thresholds=floor_area_decile_thresholds
|
||||
)
|
||||
|
||||
recommender = HeatingRecommender(property_instance=home)
|
||||
recommender.recommend_air_source_heat_pump(phase=0, has_cavity_or_loft_recommendations=False)
|
||||
property_recommendations = Recommendations.insert_temp_recommendation_id([recommender.heating_recommendations])
|
||||
|
||||
assert len(recommender.heating_recommendations) == 1
|
||||
|
||||
home.create_base_difference_epc_record(cleaned_lookup=cleaned)
|
||||
home.adjust_difference_record_with_recommendations(
|
||||
property_recommendations, []
|
||||
)
|
||||
|
||||
scoring_data = pd.DataFrame(home.recommendations_scoring_data).drop(
|
||||
columns=["rdsap_change", "heat_demand_change", "carbon_change", "sap_ending", "heat_demand_ending",
|
||||
"carbon_ending"]
|
||||
)
|
||||
|
||||
model_api = ModelApi(portfolio_id="ashp-test", timestamp=datetime.now().isoformat())
|
||||
model_api.MODEL_PREFIXES = ["sap_change_predictions"]
|
||||
|
||||
predictions_dict = model_api.predict_all(
|
||||
df=scoring_data,
|
||||
bucket="retrofit-data-dev",
|
||||
prediction_buckets={
|
||||
"sap_change_predictions": "retrofit-sap-predictions-dev",
|
||||
}
|
||||
)
|
||||
assert predictions_dict["sap_change_predictions"]["predictions"].values[0] == 69.3
|
||||
|
||||
# In actuality with this property, the heating controls get downgraded, so we test a manual patch of this
|
||||
patched_simulation_config = {
|
||||
'mainheat_energy_eff_ending': "Very Good",
|
||||
'hot_water_energy_eff_ending': 'Very Poor',
|
||||
'has_boiler_ending': False,
|
||||
'has_air_source_heat_pump_ending': True,
|
||||
'has_electric_ending': True,
|
||||
'has_mains_gas_ending': False,
|
||||
'fuel_type_ending': 'electricity',
|
||||
'trvs_ending': None,
|
||||
"mainheatc_energy_eff_ending": 'Average'
|
||||
}
|
||||
|
||||
# PATCHING
|
||||
property_recommendations_patch = Recommendations.insert_temp_recommendation_id(
|
||||
[recommender.heating_recommendations]
|
||||
)
|
||||
property_recommendations_patch[0][0]["simulation_config"] = patched_simulation_config
|
||||
|
||||
home.create_base_difference_epc_record(cleaned_lookup=cleaned)
|
||||
home.adjust_difference_record_with_recommendations(
|
||||
property_recommendations_patch, []
|
||||
)
|
||||
|
||||
scoring_data_patch = pd.DataFrame(home.recommendations_scoring_data).drop(
|
||||
columns=["rdsap_change", "heat_demand_change", "carbon_change", "sap_ending", "heat_demand_ending",
|
||||
"carbon_ending"]
|
||||
)
|
||||
|
||||
model_api = ModelApi(portfolio_id="ashp-test", timestamp=datetime.now().isoformat())
|
||||
model_api.MODEL_PREFIXES = ["sap_change_predictions"]
|
||||
|
||||
predictions_dict_patch = model_api.predict_all(
|
||||
df=scoring_data_patch,
|
||||
bucket="retrofit-data-dev",
|
||||
prediction_buckets={
|
||||
"sap_change_predictions": "retrofit-sap-predictions-dev",
|
||||
}
|
||||
)
|
||||
# The error is only 0.3, so the model is working
|
||||
assert predictions_dict_patch["sap_change_predictions"]["predictions"].values[0] == 64.3
|
||||
assert ending_epc["current-energy-efficiency"] == '64'
|
||||
|
||||
def test_air_source_heat_pump_lpg_boiler(self):
|
||||
starting_epc = {
|
||||
'low-energy-fixed-light-count': '', 'address': 'Holly Lodge, The Drive, Perry',
|
||||
'uprn-source': 'Energy Assessor', 'floor-height': '2.8', 'heating-cost-potential': '1628',
|
||||
'unheated-corridor-length': '', 'hot-water-cost-potential': '175',
|
||||
'construction-age-band': 'England and Wales: 1950-1966', 'potential-energy-rating': 'D',
|
||||
'mainheat-energy-eff': 'Poor', 'windows-env-eff': 'Average', 'lighting-energy-eff': 'Average',
|
||||
'environment-impact-potential': '70', 'glazed-type': 'double glazing, unknown install date',
|
||||
'heating-cost-current': '2158', 'address3': 'Perry',
|
||||
'mainheatcont-description': 'No time or thermostatic control of room temperature',
|
||||
'sheating-energy-eff': 'N/A', 'property-type': 'Bungalow', 'local-authority-label': 'Huntingdonshire',
|
||||
'fixed-lighting-outlets-count': '12', 'energy-tariff': 'Single', 'mechanical-ventilation': 'natural',
|
||||
'hot-water-cost-current': '257', 'county': 'Cambridgeshire', 'postcode': 'PE28 0SX',
|
||||
'solar-water-heating-flag': 'N', 'constituency': 'E14000757', 'co2-emissions-potential': '3.3',
|
||||
'number-heated-rooms': '5', 'floor-description': 'Solid, no insulation (assumed)',
|
||||
'energy-consumption-potential': '128', 'local-authority': 'E07000011', 'built-form': 'Semi-Detached',
|
||||
'number-open-fireplaces': '0', 'windows-description': 'Fully double glazed', 'glazed-area': 'Normal',
|
||||
'inspection-date': '2023-08-31', 'mains-gas-flag': 'N', 'co2-emiss-curr-per-floor-area': '51',
|
||||
'address1': 'Holly Lodge', 'heat-loss-corridor': '', 'flat-storey-count': '',
|
||||
'constituency-label': 'Huntingdon', 'roof-energy-eff': 'Good', 'total-floor-area': '117.0',
|
||||
'building-reference-number': '10005199915', 'environment-impact-current': '50',
|
||||
'co2-emissions-current': '5.9', 'roof-description': 'Pitched, 270 mm loft insulation',
|
||||
'floor-energy-eff': 'N/A', 'number-habitable-rooms': '5', 'address2': 'The Drive',
|
||||
'hot-water-env-eff': 'Good', 'posttown': 'HUNTINGDON', 'mainheatc-energy-eff': 'Very Poor',
|
||||
'main-fuel': 'LPG (not community)', 'lighting-env-eff': 'Average', 'windows-energy-eff': 'Average',
|
||||
'floor-env-eff': 'N/A', 'sheating-env-eff': 'N/A',
|
||||
'lighting-description': 'Low energy lighting in 33% of fixed outlets', 'roof-env-eff': 'Good',
|
||||
'walls-energy-eff': 'Average', 'photo-supply': '0.0', 'lighting-cost-potential': '166',
|
||||
'mainheat-env-eff': 'Good', 'multi-glaze-proportion': '100', 'main-heating-controls': '',
|
||||
'lodgement-datetime': '2023-10-30 13:46:54', 'flat-top-storey': '', 'current-energy-rating': 'F',
|
||||
'secondheat-description': 'Room heaters, electric', 'walls-env-eff': 'Average',
|
||||
'transaction-type': 'ECO assessment', 'uprn': '100091200828', 'current-energy-efficiency': '32',
|
||||
'energy-consumption-current': '243', 'mainheat-description': 'Boiler and radiators, LPG',
|
||||
'lighting-cost-current': '277', 'lodgement-date': '2023-10-30', 'extension-count': '0',
|
||||
'mainheatc-env-eff': 'Very Poor',
|
||||
'lmk-key': 'f1d3bd4b8b50bc9b006231ccb158537c408523b748b3f4ef7e98cd03b144afa5', 'wind-turbine-count': '0',
|
||||
'tenure': 'Owner-occupied', 'floor-level': '', 'potential-energy-efficiency': '56',
|
||||
'hot-water-energy-eff': 'Poor', 'low-energy-lighting': '33',
|
||||
'walls-description': 'Cavity wall, filled cavity', 'hotwater-description': 'From main system'
|
||||
}
|
||||
|
||||
ending_epc = {
|
||||
'low-energy-fixed-light-count': '', 'address': 'Holly Lodge, The Drive, Perry',
|
||||
'uprn-source': 'Energy Assessor', 'floor-height': '2.8', 'heating-cost-potential': '917',
|
||||
'unheated-corridor-length': '', 'hot-water-cost-potential': '328',
|
||||
'construction-age-band': 'England and Wales: 1950-1966', 'potential-energy-rating': 'A',
|
||||
'mainheat-energy-eff': 'Very Good', 'windows-env-eff': 'Average', 'lighting-energy-eff': 'Average',
|
||||
'environment-impact-potential': '96', 'glazed-type': 'double glazing, unknown install date',
|
||||
'heating-cost-current': '1098', 'address3': 'Perry',
|
||||
'mainheatcont-description': 'Programmer, TRVs and bypass', 'sheating-energy-eff': 'N/A',
|
||||
'property-type': 'Bungalow', 'local-authority-label': 'Huntingdonshire',
|
||||
'fixed-lighting-outlets-count': '12', 'energy-tariff': 'Single', 'mechanical-ventilation': 'natural',
|
||||
'hot-water-cost-current': '328', 'county': 'Cambridgeshire', 'postcode': 'PE28 0SX',
|
||||
'solar-water-heating-flag': 'N', 'constituency': 'E14000757', 'co2-emissions-potential': '0.3',
|
||||
'number-heated-rooms': '5', 'floor-description': 'Solid, no insulation (assumed)',
|
||||
'energy-consumption-potential': '16', 'local-authority': 'E07000011', 'built-form': 'Semi-Detached',
|
||||
'number-open-fireplaces': '0', 'windows-description': 'Fully double glazed', 'glazed-area': 'Normal',
|
||||
'inspection-date': '2023-10-05', 'mains-gas-flag': 'N', 'co2-emiss-curr-per-floor-area': '6',
|
||||
'address1': 'Holly Lodge', 'heat-loss-corridor': '', 'flat-storey-count': '',
|
||||
'constituency-label': 'Huntingdon', 'roof-energy-eff': 'Good', 'total-floor-area': '117.0',
|
||||
'building-reference-number': '10005199915', 'environment-impact-current': '92',
|
||||
'co2-emissions-current': '0.7', 'roof-description': 'Pitched, 270 mm loft insulation',
|
||||
'floor-energy-eff': 'N/A', 'number-habitable-rooms': '5', 'address2': 'The Drive',
|
||||
'hot-water-env-eff': 'Very Good', 'posttown': 'HUNTINGDON', 'mainheatc-energy-eff': 'Average',
|
||||
'main-fuel': 'electricity (not community)', 'lighting-env-eff': 'Average', 'windows-energy-eff': 'Average',
|
||||
'floor-env-eff': 'N/A', 'sheating-env-eff': 'N/A',
|
||||
'lighting-description': 'Low energy lighting in 33% of fixed outlets', 'roof-env-eff': 'Good',
|
||||
'walls-energy-eff': 'Average', 'photo-supply': '', 'lighting-cost-potential': '166',
|
||||
'mainheat-env-eff': 'Very Good', 'multi-glaze-proportion': '100', 'main-heating-controls': '',
|
||||
'lodgement-datetime': '2023-11-01 16:29:16', 'flat-top-storey': '', 'current-energy-rating': 'A',
|
||||
'secondheat-description': 'Room heaters, electric', 'walls-env-eff': 'Average',
|
||||
'transaction-type': 'ECO assessment', 'uprn': '100091200828', 'current-energy-efficiency': '92',
|
||||
'energy-consumption-current': '37', 'mainheat-description': 'Air source heat pump, radiators, electric',
|
||||
'lighting-cost-current': '277', 'lodgement-date': '2023-11-01', 'extension-count': '0',
|
||||
'mainheatc-env-eff': 'Average',
|
||||
'lmk-key': 'cb7f2838b727907767c8c2a385cd22f722b1e4745463391d910d228e52124515', 'wind-turbine-count': '0',
|
||||
'tenure': 'Owner-occupied', 'floor-level': '', 'potential-energy-efficiency': '95',
|
||||
'hot-water-energy-eff': 'Good', 'low-energy-lighting': '33',
|
||||
'walls-description': 'Cavity wall, filled cavity', 'hotwater-description': 'From main system'
|
||||
}
|
||||
|
||||
cleaning_data = read_dataframe_from_s3_parquet(
|
||||
bucket_name="retrofit-data-dev", file_key="sap_change_model/cleaning_dataset.parquet",
|
||||
)
|
||||
|
||||
cleaned = read_from_s3(
|
||||
s3_file_name="cleaned_epc_data/cleaned.bson",
|
||||
bucket_name="retrofit-data-dev"
|
||||
)
|
||||
cleaned = msgpack.unpackb(cleaned, raw=False)
|
||||
|
||||
photo_supply_lookup, floor_area_decile_thresholds = SolarPhotoSupply.load(bucket="retrofit-data-dev")
|
||||
|
||||
epc = EPCRecord(
|
||||
epc_records={
|
||||
'original_epc': starting_epc,
|
||||
'full_sap_epc': {},
|
||||
'old_data': []
|
||||
},
|
||||
run_mode="newdata",
|
||||
cleaning_data=cleaning_data
|
||||
)
|
||||
|
||||
home = Property(
|
||||
id=0,
|
||||
address="",
|
||||
postcode="",
|
||||
epc_record=epc,
|
||||
already_installed={},
|
||||
non_invasive_recommendations={},
|
||||
)
|
||||
home.in_conservation_area = False
|
||||
home.is_listed = False
|
||||
home.is_heritage = False
|
||||
home.restricted_measures = True
|
||||
home.get_components(
|
||||
cleaned=cleaned,
|
||||
photo_supply_lookup=photo_supply_lookup,
|
||||
floor_area_decile_thresholds=floor_area_decile_thresholds
|
||||
)
|
||||
|
||||
recommender = HeatingRecommender(property_instance=home)
|
||||
recommender.recommend_air_source_heat_pump(phase=0, has_cavity_or_loft_recommendations=False)
|
||||
property_recommendations = Recommendations.insert_temp_recommendation_id([recommender.heating_recommendations])
|
||||
|
||||
assert len(recommender.heating_recommendations) == 1
|
||||
|
||||
home.create_base_difference_epc_record(cleaned_lookup=cleaned)
|
||||
home.adjust_difference_record_with_recommendations(
|
||||
property_recommendations, []
|
||||
)
|
||||
|
||||
scoring_data = pd.DataFrame(home.recommendations_scoring_data).drop(
|
||||
columns=["rdsap_change", "heat_demand_change", "carbon_change", "sap_ending", "heat_demand_ending",
|
||||
"carbon_ending"]
|
||||
)
|
||||
|
||||
model_api = ModelApi(portfolio_id="ashp-test", timestamp=datetime.now().isoformat())
|
||||
model_api.MODEL_PREFIXES = ["sap_change_predictions"]
|
||||
|
||||
predictions_dict = model_api.predict_all(
|
||||
df=scoring_data,
|
||||
bucket="retrofit-data-dev",
|
||||
prediction_buckets={
|
||||
"sap_change_predictions": "retrofit-sap-predictions-dev",
|
||||
}
|
||||
)
|
||||
# We predict a huge uplift but not quite as much as the EPC, due to some distinct differences between our
|
||||
# recommendation and the EPC
|
||||
assert predictions_dict["sap_change_predictions"]["predictions"].values[0] == 81.3
|
||||
assert ending_epc['current-energy-efficiency'] == '92'
|
||||
|
||||
# PATCH
|
||||
# We patch the simulation config, to reflect the ending EPC, to see if we get the ending EPC's config
|
||||
patched_simulation_config = {
|
||||
'mainheat_energy_eff_ending': "Very Good",
|
||||
'hot_water_energy_eff_ending': 'Good',
|
||||
'has_boiler_ending': False,
|
||||
'has_air_source_heat_pump_ending': True,
|
||||
'has_electric_ending': True,
|
||||
'has_lpg_ending': False,
|
||||
'fuel_type_ending': 'electricity',
|
||||
'switch_system_ending': 'programmer',
|
||||
'no_control_ending': None,
|
||||
'auxiliary_systems_ending': 'bypass',
|
||||
'trvs_ending': 'trvs',
|
||||
"mainheatc_energy_eff_ending": 'Average'
|
||||
}
|
||||
|
||||
# PATCHING
|
||||
property_recommendations_patch = Recommendations.insert_temp_recommendation_id(
|
||||
[recommender.heating_recommendations]
|
||||
)
|
||||
property_recommendations_patch[0][0]["simulation_config"] = patched_simulation_config
|
||||
|
||||
home.create_base_difference_epc_record(cleaned_lookup=cleaned)
|
||||
home.adjust_difference_record_with_recommendations(
|
||||
property_recommendations_patch, []
|
||||
)
|
||||
|
||||
scoring_data_patch = pd.DataFrame(home.recommendations_scoring_data).drop(
|
||||
columns=["rdsap_change", "heat_demand_change", "carbon_change", "sap_ending", "heat_demand_ending",
|
||||
"carbon_ending"]
|
||||
)
|
||||
|
||||
model_api = ModelApi(portfolio_id="ashp-test", timestamp=datetime.now().isoformat())
|
||||
model_api.MODEL_PREFIXES = ["sap_change_predictions"]
|
||||
|
||||
predictions_dict_patch = model_api.predict_all(
|
||||
df=scoring_data_patch,
|
||||
bucket="retrofit-data-dev",
|
||||
prediction_buckets={
|
||||
"sap_change_predictions": "retrofit-sap-predictions-dev",
|
||||
}
|
||||
)
|
||||
|
||||
assert predictions_dict_patch["sap_change_predictions"]["predictions"].values[0] == 88.9
|
||||
# We still underpredict but the improvement is notable
|
||||
|
||||
def test_offgrid(self):
|
||||
"""
|
||||
We test on a property we've worked with before, where we compare two options
|
||||
a) Upgrading to a boiler
|
||||
b) Upgrading to a heat pump
|
||||
:return:
|
||||
"""
|
||||
|
||||
starting_epc = {
|
||||
'low-energy-fixed-light-count': '', 'address': '6 Beech Road', 'uprn-source': 'Energy Assessor',
|
||||
'floor-height': '2.4', 'heating-cost-potential': '612', 'unheated-corridor-length': '',
|
||||
'hot-water-cost-potential': '123', 'construction-age-band': 'England and Wales: 1930-1949',
|
||||
'potential-energy-rating': 'B', 'mainheat-energy-eff': 'Very Poor', 'windows-env-eff': 'Good',
|
||||
'lighting-energy-eff': 'Good', 'environment-impact-potential': '87',
|
||||
'glazed-type': 'double glazing installed during or after 2002', 'heating-cost-current': '2278',
|
||||
'address3': '', 'mainheatcont-description': 'Appliance thermostats', 'sheating-energy-eff': 'N/A',
|
||||
'property-type': 'House', 'local-authority-label': 'Dudley', 'fixed-lighting-outlets-count': '9',
|
||||
'energy-tariff': 'Single', 'mechanical-ventilation': 'natural', 'hot-water-cost-current': '604',
|
||||
'county': '', 'postcode': 'DY1 4BP', 'solar-water-heating-flag': 'N', 'constituency': 'E14000671',
|
||||
'co2-emissions-potential': '1.0', 'number-heated-rooms': '4',
|
||||
'floor-description': 'Solid, no insulation (assumed)', 'energy-consumption-potential': '93',
|
||||
'local-authority': 'E08000027', 'built-form': 'End-Terrace', 'number-open-fireplaces': '0',
|
||||
'windows-description': 'Fully double glazed', 'glazed-area': 'Normal', 'inspection-date': '2024-03-13',
|
||||
'mains-gas-flag': 'Y', 'co2-emiss-curr-per-floor-area': '83', 'address1': '6 Beech Road',
|
||||
'heat-loss-corridor': '', 'flat-storey-count': '', 'constituency-label': 'Dudley North',
|
||||
'roof-energy-eff': 'Very Poor', 'total-floor-area': '60.0', 'building-reference-number': '10005780080',
|
||||
'environment-impact-current': '41', 'co2-emissions-current': '5.0',
|
||||
'roof-description': 'Pitched, 12 mm loft insulation', 'floor-energy-eff': 'N/A',
|
||||
'number-habitable-rooms': '4', 'address2': '', 'hot-water-env-eff': 'Poor', 'posttown': 'DUDLEY',
|
||||
'mainheatc-energy-eff': 'Good', 'main-fuel': 'electricity (not community)', 'lighting-env-eff': 'Good',
|
||||
'windows-energy-eff': 'Good', 'floor-env-eff': 'N/A', 'sheating-env-eff': 'N/A',
|
||||
'lighting-description': 'Low energy lighting in 67% of fixed outlets', 'roof-env-eff': 'Very Poor',
|
||||
'walls-energy-eff': 'Average', 'photo-supply': '0.0', 'lighting-cost-potential': '113',
|
||||
'mainheat-env-eff': 'Poor', 'multi-glaze-proportion': '100', 'main-heating-controls': '',
|
||||
'lodgement-datetime': '2024-03-13 11:29:11', 'flat-top-storey': '', 'current-energy-rating': 'F',
|
||||
'secondheat-description': 'None', 'walls-env-eff': 'Average', 'transaction-type': 'rental',
|
||||
'uprn': '90055152', 'current-energy-efficiency': '32', 'energy-consumption-current': '491',
|
||||
'mainheat-description': 'Room heaters, electric', 'lighting-cost-current': '113',
|
||||
'lodgement-date': '2024-03-13', 'extension-count': '1', 'mainheatc-env-eff': 'Good',
|
||||
'lmk-key': '78ddf851b660e599a0894924d0e6b503980f5e0ad1aa711f8411718dc2989c44', 'wind-turbine-count': '0',
|
||||
'tenure': 'Rented (social)', 'floor-level': '', 'potential-energy-efficiency': '87',
|
||||
'hot-water-energy-eff': 'Very Poor', 'low-energy-lighting': '67',
|
||||
'walls-description': 'Cavity wall, filled cavity',
|
||||
'hotwater-description': 'Electric immersion, standard tariff'
|
||||
}
|
||||
|
||||
cleaning_data = read_dataframe_from_s3_parquet(
|
||||
bucket_name="retrofit-data-dev", file_key="sap_change_model/cleaning_dataset.parquet",
|
||||
)
|
||||
|
||||
cleaned = read_from_s3(
|
||||
s3_file_name="cleaned_epc_data/cleaned.bson",
|
||||
bucket_name="retrofit-data-dev"
|
||||
)
|
||||
cleaned = msgpack.unpackb(cleaned, raw=False)
|
||||
|
||||
photo_supply_lookup, floor_area_decile_thresholds = SolarPhotoSupply.load(bucket="retrofit-data-dev")
|
||||
|
||||
epc = EPCRecord(
|
||||
epc_records={
|
||||
'original_epc': starting_epc,
|
||||
'full_sap_epc': {},
|
||||
'old_data': []
|
||||
},
|
||||
run_mode="newdata",
|
||||
cleaning_data=cleaning_data
|
||||
)
|
||||
|
||||
home = Property(
|
||||
id=0,
|
||||
address="",
|
||||
postcode="",
|
||||
epc_record=epc,
|
||||
already_installed={},
|
||||
non_invasive_recommendations={},
|
||||
)
|
||||
home.in_conservation_area = False
|
||||
home.is_listed = False
|
||||
home.is_heritage = False
|
||||
home.restricted_measures = True
|
||||
home.get_components(
|
||||
cleaned=cleaned,
|
||||
photo_supply_lookup=photo_supply_lookup,
|
||||
floor_area_decile_thresholds=floor_area_decile_thresholds
|
||||
)
|
||||
|
||||
recommender = HeatingRecommender(property_instance=home)
|
||||
recommender.recommend_air_source_heat_pump(phase=0, has_cavity_or_loft_recommendations=False)
|
||||
recommender.recommend_boiler_upgrades(phase=0, system_change=True, exising_room_heaters=False)
|
||||
|
||||
assert len(recommender.heating_recommendations) == 3
|
||||
|
||||
property_recommendations = Recommendations.insert_temp_recommendation_id([recommender.heating_recommendations])
|
||||
|
||||
home.create_base_difference_epc_record(cleaned_lookup=cleaned)
|
||||
home.adjust_difference_record_with_recommendations(
|
||||
property_recommendations, []
|
||||
)
|
||||
|
||||
scoring_data = pd.DataFrame(home.recommendations_scoring_data).drop(
|
||||
columns=["rdsap_change", "heat_demand_change", "carbon_change", "sap_ending", "heat_demand_ending",
|
||||
"carbon_ending"]
|
||||
)
|
||||
|
||||
model_api = ModelApi(portfolio_id="ashp-test", timestamp=datetime.now().isoformat())
|
||||
model_api.MODEL_PREFIXES = ["sap_change_predictions"]
|
||||
|
||||
predictions_dict = model_api.predict_all(
|
||||
df=scoring_data,
|
||||
bucket="retrofit-data-dev",
|
||||
prediction_buckets={
|
||||
"sap_change_predictions": "retrofit-sap-predictions-dev",
|
||||
}
|
||||
)
|
||||
|
||||
# The ASHP isn't better under SAP, compared to a gas boiler with good heat controls
|
||||
assert predictions_dict["sap_change_predictions"]["predictions"].tolist() == [66.9, 65.5, 65.9]
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue