mirror of
https://github.com/Hestia-Homes/Model.git
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Added tests for solid walls
This commit is contained in:
Khalim Conn-Kowlessar
parent
482ddb1e98
commit
13490b18ca
2 changed files with 292 additions and 87 deletions
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@ -9,93 +9,100 @@ import pytest
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import pickle
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from tqdm import tqdm
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with open("sap_change_dataset.pickle", "rb") as f:
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sap_change_dataset = pickle.load(f)
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# import pickle
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#
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# with open("sap_change_dataset.pickle", "rb") as f:
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# sap_change_dataset = pickle.load(f)
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#
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# search_from = sap_change_dataset[
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# sap_change_dataset["walls_thermal_transmittance_ENDING"] != sap_change_dataset["walls_thermal_transmittance"]
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# ]
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# search_from = search_from[
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# (search_from["roof_thermal_transmittance_ENDING"] == search_from["roof_thermal_transmittance"]) &
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# (search_from["floor_thermal_transmittance_ENDING"] == search_from["floor_thermal_transmittance"]) &
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# (search_from["MECHANICAL_VENTILATION_ENDING"] == search_from["MECHANICAL_VENTILATION_STARTING"]) &
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# (search_from["SECONDHEAT_DESCRIPTION_ENDING"] == search_from["SECONDHEAT_DESCRIPTION_STARTING"]) &
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# (search_from["GLAZED_TYPE_ENDING"] == search_from["GLAZED_TYPE_STARTING"])
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# ]
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#
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# # Find a record where the only difference is cavity wall getting filled
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# ending_cols = [c for c in search_from.columns if "_ENDING" in c]
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#
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# ignore = [
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# "SAP_ENDING", "HEAT_DEMAND_ENDING", "CARBON_ENDING", "TRANSACTION_TYPE_ENDING", "FLOOR_HEIGHT_ENDING",
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# "DAYS_TO_ENDING", "TOTAL_FLOOR_AREA_ENDING"
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# ]
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#
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# ending_cols = [c for c in ending_cols if c not in ignore]
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#
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# for _, row in tqdm(search_from.iterrows(), total=search_from.shape[0]):
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#
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# same = True
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# starting_cols = []
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# for c in ending_cols:
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#
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# starting_col = c.replace("_ENDING", "")
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# if starting_col not in search_from.columns:
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# starting_col = c.replace("_ENDING", "_STARTING")
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# if starting_col not in search_from.columns:
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# raise Exception("something went wrong")
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#
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# starting_cols.append(starting_col)
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#
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# # We want them to be different
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# if c == "walls_thermal_transmittance_ENDING":
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# if row[c] == row[starting_col]:
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# same = False
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# break
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# else:
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# continue
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#
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# # We now check if the starting and ending values are the same
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# if row[c] != row[starting_col]:
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# same = False
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# break
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#
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# if same:
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# raise Exception("We found one!")
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#
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# fixed_cols = [c for c in search_from.columns if c not in starting_cols + ending_cols]
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#
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# import pandas as pd
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#
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# start = row[starting_cols]
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# start.index = [c.replace("_STARTING", "") for c in start.index]
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# end = row[ending_cols]
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# end.index = [c.replace("_ENDING", "") for c in end.index]
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# start["type"] = "starting"
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# end["type"] = "ending"
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#
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# compare = pd.concat([start, end], axis=1)
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#
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# ending_lmk = "1481856809222016121510000597528546"
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# starting_lmk = "1481856849902016092320290148762028"
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#
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# EPC_AUTH_TOKEN = "a2Nvbm5rb3dsZXNzYXJAZ21haWwuY29tOjY5MGJiMWM0NmIyOGI5ZDUxYzAxMzQzYzNiZGNlZGJjZDNmODQwMzA="
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#
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# client = EpcClient(auth_token=EPC_AUTH_TOKEN)
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# result = client.domestic.search(params={"address": "26, Vicarage Lane", "postcode": "NG32 1SP"})
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# starting_epc = [x for x in result["rows"] if x["lmk-key"] == starting_lmk][0]
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# ending_epc = [x for x in result["rows"] if x["lmk-key"] == ending_lmk][0]
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search_from = sap_change_dataset[
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(sap_change_dataset["walls_thermal_transmittance_ENDING"] != sap_change_dataset["walls_thermal_transmittance"]) &
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(sap_change_dataset["is_solid_brick"])
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]
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search_from = search_from[
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(search_from["roof_thermal_transmittance_ENDING"] == search_from["roof_thermal_transmittance"]) &
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(search_from["floor_thermal_transmittance_ENDING"] == search_from["floor_thermal_transmittance"]) &
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(search_from["MECHANICAL_VENTILATION_ENDING"] == search_from["MECHANICAL_VENTILATION_STARTING"]) &
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(search_from["SECONDHEAT_DESCRIPTION_ENDING"] == search_from["SECONDHEAT_DESCRIPTION_STARTING"]) &
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(search_from["GLAZED_TYPE_ENDING"] == search_from["GLAZED_TYPE_STARTING"])
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]
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# Find a record where the only difference is cavity wall getting filled
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ending_cols = [c for c in search_from.columns if "_ENDING" in c]
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ignore = [
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"SAP_ENDING", "HEAT_DEMAND_ENDING", "CARBON_ENDING", "TRANSACTION_TYPE_ENDING", "FLOOR_HEIGHT_ENDING",
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"DAYS_TO_ENDING", "TOTAL_FLOOR_AREA_ENDING"
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]
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ending_cols = [c for c in ending_cols if c not in ignore]
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for _, row in tqdm(search_from.iterrows(), total=search_from.shape[0]):
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same = True
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starting_cols = []
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for c in ending_cols:
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starting_col = c.replace("_ENDING", "")
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if starting_col not in search_from.columns:
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starting_col = c.replace("_ENDING", "_STARTING")
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if starting_col not in search_from.columns:
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raise Exception("something went wrong")
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starting_cols.append(starting_col)
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# We want them to be different
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if c == "walls_thermal_transmittance_ENDING":
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if row[c] == row[starting_col]:
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same = False
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break
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else:
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continue
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# We want them to be different
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if c == "walls_insulation_thickness_ENDING":
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if row[c] == row[starting_col]:
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same = False
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break
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else:
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continue
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# We now check if the starting and ending values are the same
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if row[c] != row[starting_col]:
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same = False
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break
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if same:
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raise Exception("We found one!")
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fixed_cols = [c for c in search_from.columns if c not in starting_cols + ending_cols]
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import pandas as pd
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start = row[starting_cols]
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start.index = [c.replace("_STARTING", "") for c in start.index]
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end = row[ending_cols]
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end.index = [c.replace("_ENDING", "") for c in end.index]
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start["type"] = "starting"
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end["type"] = "ending"
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compare = pd.concat([start, end], axis=1)
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ending_lmk = "d0fc64d6b80db04c32998c9b846dd04c8f0b486231a11e4c062020b35af1312d"
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starting_lmk = "b0d82f468273bec55ec5676a809b8e36b55db940ffa92f482a482f6aaa38eb1d"
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client = EpcClient(auth_token=EPC_AUTH_TOKEN)
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result = client.domestic.search(params={"address": "FLAT 12, WAREHOUSE W, 3 WESTERN GATEWAY", "postcode": "E16 1BD"})
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starting_epc = [x for x in result["rows"] if x["lmk-key"] == starting_lmk][0]
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ending_epc = [x for x in result["rows"] if x["lmk-key"] == ending_lmk][0]
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# with open("cleaned.pickle", "wb") as f:
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# pickle.dump(cleaned, f)
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# with open(
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# os.path.abspath(os.path.dirname(__file__)) + "/backend/tests/test_data/cleaned.pickle", "rb"
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# ) as f:
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# cleaned = pickle.load(f)
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# with open("cleaning_data.pickle", "wb") as f:
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# pickle.dump(cleaning_data, f)
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# with open(
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# os.path.abspath(os.path.dirname(__file__)) + "/backend/tests/test_data/cleaning_data.pickle", "rb"
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# ) as f:
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# cleaning_data = pickle.load(f)
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class TestSapModelPrep:
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@ -327,5 +334,201 @@ class TestSapModelPrep:
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assert test_record[c].values[0] == row[c]
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def test_solid_wall_insulation(self):
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pass
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def test_solid_wall_insulation(self, cleaned, cleaning_data):
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starting_epc2 = {
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'low-energy-fixed-light-count': '2', 'address': 'FLAT 12, WAREHOUSE W, 3 WESTERN GATEWAY',
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'uprn-source': 'Energy Assessor', 'floor-height': '3.64', 'heating-cost-potential': '465',
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'unheated-corridor-length': '', 'hot-water-cost-potential': '185',
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'construction-age-band': 'England and Wales: 1900-1929', 'potential-energy-rating': 'C',
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'mainheat-energy-eff': 'Very Poor', 'windows-env-eff': 'Average', 'lighting-energy-eff': 'Poor',
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'environment-impact-potential': '51', 'glazed-type': 'double glazing installed during or after 2002',
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'heating-cost-current': '1223', 'address3': '3 WESTERN GATEWAY',
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'mainheatcont-description': 'Programmer and appliance thermostats', 'sheating-energy-eff': 'N/A',
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'property-type': 'Flat', 'local-authority-label': 'Newham', 'fixed-lighting-outlets-count': '12',
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'energy-tariff': 'off-peak 7 hour', 'mechanical-ventilation': 'natural', 'hot-water-cost-current': '342',
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'county': '', 'postcode': 'E16 1BD', 'solar-water-heating-flag': 'N', 'constituency': 'E14001032',
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'co2-emissions-potential': '3.6', 'number-heated-rooms': '2', 'floor-description': '(other premises below)',
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'energy-consumption-potential': '307', 'local-authority': 'E09000025', 'built-form': 'Mid-Terrace',
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'number-open-fireplaces': '0', 'windows-description': 'Partial double glazing', 'glazed-area': 'Normal',
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'inspection-date': '2020-10-14', 'mains-gas-flag': 'N', 'co2-emiss-curr-per-floor-area': '66',
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'address1': 'FLAT 12', 'heat-loss-corridor': 'heated corridor', 'flat-storey-count': '',
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'constituency-label': 'West Ham', 'roof-energy-eff': 'N/A', 'total-floor-area': '70.0',
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'building-reference-number': '10000539740', 'environment-impact-current': '42',
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'co2-emissions-current': '4.6', 'roof-description': '(another dwelling above)', 'floor-energy-eff': 'N/A',
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'number-habitable-rooms': '2', 'address2': 'WAREHOUSE W', 'hot-water-env-eff': 'Poor', 'posttown': 'LONDON',
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'mainheatc-energy-eff': 'Good', 'main-fuel': 'electricity (not community)', 'lighting-env-eff': 'Poor',
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'windows-energy-eff': 'Average', 'floor-env-eff': 'N/A', 'sheating-env-eff': 'N/A',
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'lighting-description': 'Low energy lighting in 17% of fixed outlets', 'roof-env-eff': 'N/A',
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'walls-energy-eff': 'Very Poor', 'photo-supply': '0.0', 'lighting-cost-potential': '67',
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'mainheat-env-eff': 'Poor', 'multi-glaze-proportion': '61', 'main-heating-controls': '',
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'lodgement-datetime': '2020-10-14 00:00:00', 'flat-top-storey': 'N', 'current-energy-rating': 'F',
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'secondheat-description': 'None', 'walls-env-eff': 'Very Poor', 'transaction-type': 'marketed sale',
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'uprn': '10012839482', 'current-energy-efficiency': '33', 'energy-consumption-current': '393',
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'mainheat-description': 'Room heaters, electric', 'lighting-cost-current': '110',
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'lodgement-date': '2020-10-14', 'extension-count': '0', 'mainheatc-env-eff': 'Good',
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'lmk-key': 'b0d82f468273bec55ec5676a809b8e36b55db940ffa92f482a482f6aaa38eb1d', 'wind-turbine-count': '0',
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'tenure': 'Owner-occupied', 'floor-level': '01', 'potential-energy-efficiency': '71',
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'hot-water-energy-eff': 'Very Poor', 'low-energy-lighting': '17',
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'walls-description': 'Solid brick, as built, no insulation (assumed)',
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'hotwater-description': 'Electric immersion, standard tariff'
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}
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row2 = {
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'UPRN': '10012839482', 'RDSAP_CHANGE': 8, 'HEAT_DEMAND_CHANGE': -59,
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'CARBON_CHANGE': -0.5999999999999996, 'SAP_STARTING': 33, 'SAP_ENDING': 41, 'HEAT_DEMAND_STARTING': 393,
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'HEAT_DEMAND_ENDING': 334, 'CARBON_STARTING': 4.6, 'CARBON_ENDING': 4.0, 'PROPERTY_TYPE': 'Flat',
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'BUILT_FORM': 'Mid-Terrace', 'CONSTITUENCY': 'E14001032', 'NUMBER_HABITABLE_ROOMS': 2.0,
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'NUMBER_HEATED_ROOMS': 2.0, 'FIXED_LIGHTING_OUTLETS_COUNT': 12.0,
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'CONSTRUCTION_AGE_BAND': 'England and Wales: 1996-2002', 'TRANSACTION_TYPE_STARTING': 'marketed sale',
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'MECHANICAL_VENTILATION_STARTING': 'natural', 'SECONDHEAT_DESCRIPTION_STARTING': 'None',
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'ENERGY_TARIFF_STARTING': 'off-peak 7 hour', 'SOLAR_WATER_HEATING_FLAG_STARTING': 'N',
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'PHOTO_SUPPLY_STARTING': 0.0, 'GLAZED_TYPE_STARTING': 'double glazing installed during or after 2002',
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'MULTI_GLAZE_PROPORTION_STARTING': 61.0, 'LOW_ENERGY_LIGHTING_STARTING': 17.0,
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'NUMBER_OPEN_FIREPLACES_STARTING': 0.0, 'EXTENSION_COUNT_STARTING': 0.0,
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'TOTAL_FLOOR_AREA_STARTING': 70.0, 'FLOOR_HEIGHT_STARTING': 3.64,
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'TRANSACTION_TYPE_ENDING': 'marketed sale', 'MECHANICAL_VENTILATION_ENDING': 'natural',
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'SECONDHEAT_DESCRIPTION_ENDING': 'None', 'ENERGY_TARIFF_ENDING': 'off-peak 7 hour',
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'SOLAR_WATER_HEATING_FLAG_ENDING': 'N', 'PHOTO_SUPPLY_ENDING': 0.0,
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'GLAZED_TYPE_ENDING': 'double glazing installed during or after 2002',
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'MULTI_GLAZE_PROPORTION_ENDING': 61.0, 'LOW_ENERGY_LIGHTING_ENDING': 17.0,
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'NUMBER_OPEN_FIREPLACES_ENDING': 0.0, 'EXTENSION_COUNT_ENDING': 0.0, 'TOTAL_FLOOR_AREA_ENDING': 70.0,
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'FLOOR_HEIGHT_ENDING': 3.64, 'DAYS_TO_STARTING': 2266, 'DAYS_TO_ENDING': 2307,
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'walls_thermal_transmittance': 0.45, 'is_cavity_wall': False, 'is_filled_cavity': False,
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'is_solid_brick': True, 'is_system_built': False, 'is_timber_frame': False,
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'is_granite_or_whinstone': False, 'is_as_built': True, 'is_cob': False,
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'is_sandstone_or_limestone': False, 'is_park_home': False, 'walls_insulation_thickness': 'none',
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'external_insulation': False, 'internal_insulation': False, 'walls_thermal_transmittance_ENDING': 0.21,
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'is_park_home_ENDING': False, 'walls_insulation_thickness_ENDING': 'average',
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'external_insulation_ENDING': False, 'internal_insulation_ENDING': False,
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'floor_thermal_transmittance': 0.0, 'is_to_unheated_space': False, 'is_to_external_air': False,
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'is_suspended': False, 'is_solid': False, 'another_property_below': True,
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'floor_insulation_thickness': 'none', 'floor_thermal_transmittance_ENDING': 0.0,
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'floor_insulation_thickness_ENDING': 'none', 'roof_thermal_transmittance': 0.0, 'is_pitched': False,
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'is_roof_room': False, 'is_loft': False, 'is_flat': False, 'is_thatched': False, 'is_at_rafters': False,
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'has_dwelling_above': True, 'roof_insulation_thickness': 'none',
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'roof_thermal_transmittance_ENDING': 0.0, 'roof_insulation_thickness_ENDING': 'none',
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'heater_type': 'electric immersion', 'system_type': 'Unknown', 'thermostat_characteristics': 'Unknown',
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'heating_scope': 'Unknown', 'energy_recovery': 'Unknown', 'hotwater_tariff_type': 'standard tariff',
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'extra_features': 'Unknown', 'chp_systems': 'Unknown', 'distribution_system': 'Unknown',
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'no_system_present': 'Unknown', 'appliance': 'Unknown', 'heater_type_ENDING': 'electric immersion',
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'system_type_ENDING': 'Unknown', 'thermostat_characteristics_ENDING': 'Unknown',
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'heating_scope_ENDING': 'Unknown', 'energy_recovery_ENDING': 'Unknown',
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'hotwater_tariff_type_ENDING': 'standard tariff', 'extra_features_ENDING': 'Unknown',
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'chp_systems_ENDING': 'Unknown', 'distribution_system_ENDING': 'Unknown',
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'no_system_present_ENDING': 'Unknown', 'appliance_ENDING': 'Unknown', 'has_radiators': False,
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'has_fan_coil_units': False, 'has_pipes_in_screed_above_insulation': False,
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'has_pipes_in_insulated_timber_floor': False, 'has_pipes_in_concrete_slab': False, 'has_boiler': False,
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'has_air_source_heat_pump': False, 'has_room_heaters': True, 'has_electric_storage_heaters': False,
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'has_warm_air': False, 'has_electric_underfloor_heating': False, 'has_electric_ceiling_heating': False,
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'has_community_scheme': False, 'has_ground_source_heat_pump': False, 'has_no_system_present': False,
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'has_portable_electric_heaters': False, 'has_water_source_heat_pump': False,
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'has_electric_heat_pump': False, 'has_micro-cogeneration': False, 'has_solar_assisted_heat_pump': False,
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'has_exhaust_source_heat_pump': False, 'has_community_heat_pump': False, 'has_electric': True,
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'has_mains_gas': False, 'has_wood_logs': False, 'has_coal': False, 'has_oil': False,
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'has_wood_pellets': False, 'has_anthracite': False, 'has_dual_fuel_mineral_and_wood': False,
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'has_smokeless_fuel': False, 'has_lpg': False, 'has_b30k': False, 'has_electricaire': False,
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'has_assumed_for_most_rooms': False, 'has_underfloor_heating': False, 'has_radiators_ENDING': False,
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'has_fan_coil_units_ENDING': False, 'has_pipes_in_screed_above_insulation_ENDING': False,
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'has_pipes_in_insulated_timber_floor_ENDING': False, 'has_pipes_in_concrete_slab_ENDING': False,
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'has_boiler_ENDING': False, 'has_air_source_heat_pump_ENDING': False, 'has_room_heaters_ENDING': True,
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'has_electric_storage_heaters_ENDING': False, 'has_warm_air_ENDING': False,
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'has_electric_underfloor_heating_ENDING': False, 'has_electric_ceiling_heating_ENDING': False,
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'has_community_scheme_ENDING': False, 'has_ground_source_heat_pump_ENDING': False,
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'has_no_system_present_ENDING': False, 'has_portable_electric_heaters_ENDING': False,
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'has_water_source_heat_pump_ENDING': False, 'has_electric_heat_pump_ENDING': False,
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'has_micro-cogeneration_ENDING': False, 'has_solar_assisted_heat_pump_ENDING': False,
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'has_exhaust_source_heat_pump_ENDING': False, 'has_community_heat_pump_ENDING': False,
|
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'has_electric_ENDING': True, 'has_mains_gas_ENDING': False, 'has_wood_logs_ENDING': False,
|
||||
'has_coal_ENDING': False, 'has_oil_ENDING': False, 'has_wood_pellets_ENDING': False,
|
||||
'has_anthracite_ENDING': False, 'has_dual_fuel_mineral_and_wood_ENDING': False,
|
||||
'has_smokeless_fuel_ENDING': False, 'has_lpg_ENDING': False, 'has_b30k_ENDING': False,
|
||||
'has_electricaire_ENDING': False, 'has_assumed_for_most_rooms_ENDING': False,
|
||||
'has_underfloor_heating_ENDING': False, 'thermostatic_control': 'appliance thermostats',
|
||||
'charging_system': 'Unknown', 'switch_system': 'programmer', 'no_control': 'Unknown',
|
||||
'dhw_control': 'Unknown', 'community_heating': 'Unknown', 'multiple_room_thermostats': False,
|
||||
'auxiliary_systems': 'Unknown', 'trvs': 'Unknown', 'rate_control': 'Unknown',
|
||||
'thermostatic_control_ENDING': 'appliance thermostats', 'charging_system_ENDING': 'Unknown',
|
||||
'switch_system_ENDING': 'programmer', 'no_control_ENDING': 'Unknown', 'dhw_control_ENDING': 'Unknown',
|
||||
'community_heating_ENDING': 'Unknown', 'multiple_room_thermostats_ENDING': False,
|
||||
'auxiliary_systems_ENDING': 'Unknown', 'trvs_ENDING': 'Unknown', 'rate_control_ENDING': 'Unknown',
|
||||
'glazing_type': 'double', 'glazing_type_ENDING': 'double', 'fuel_type': 'electricity',
|
||||
'main-fuel_tariff_type': 'Unknown', 'is_community': False,
|
||||
'no_individual_heating_or_community_network': False, 'complex_fuel_type': 'Unknown',
|
||||
'fuel_type_ENDING': 'electricity', 'main-fuel_tariff_type_ENDING': 'Unknown',
|
||||
'is_community_ENDING': False, 'no_individual_heating_or_community_network_ENDING': False,
|
||||
'complex_fuel_type_ENDING': 'Unknown', 'estimated_perimeter_STARTING': 35.4964786985977,
|
||||
'estimated_perimeter_ENDING': 35.4964786985977
|
||||
}
|
||||
|
||||
home2 = Property(
|
||||
id=0,
|
||||
postcode=starting_epc2["postcode"],
|
||||
address1=starting_epc2["address1"],
|
||||
epc_client=EpcClient(auth_token="notoken"),
|
||||
data=starting_epc2
|
||||
)
|
||||
home2.get_components(cleaned)
|
||||
|
||||
data_processor2 = DataProcessor(None, newdata=True)
|
||||
data_processor2.insert_data(pd.DataFrame([home2.get_model_data()]))
|
||||
|
||||
data_processor2.pre_process()
|
||||
|
||||
starting_epc_data2 = data_processor2.get_component_features(suffix="_STARTING")
|
||||
ending_epc_data2 = data_processor2.get_component_features(suffix="_ENDING")
|
||||
fixed_data2 = data_processor2.get_fixed_features()
|
||||
|
||||
ending_lodgement_date2 = '2020-11-24'
|
||||
|
||||
starting_epc_data2["DAYS_TO_ENDING"] = data_processor2.calculate_days_to(ending_lodgement_date2)
|
||||
|
||||
recommendation2 = {
|
||||
"recommendation_id": 0,
|
||||
"new_u_value": 0.21,
|
||||
"type": "wall_insulation"
|
||||
}
|
||||
|
||||
test_record2 = create_recommendation_scoring_data(
|
||||
property=home2,
|
||||
recommendation=recommendation2,
|
||||
starting_epc_data=starting_epc_data2,
|
||||
ending_epc_data=ending_epc_data2,
|
||||
fixed_data=fixed_data2,
|
||||
)
|
||||
test_record2 = pd.DataFrame([test_record2])
|
||||
|
||||
# Test the final cleaning:
|
||||
test_record2 = DataProcessor.apply_averages_cleaning(
|
||||
data_to_clean=test_record2,
|
||||
cleaning_data=cleaning_data,
|
||||
cols_to_merge_on=COLUMNS_TO_MERGE_ON + ["LOCAL_AUTHORITY"]
|
||||
).drop(columns=["LOCAL_AUTHORITY"])
|
||||
|
||||
test_record2 = DataProcessor.clean_missings_after_description_process(
|
||||
test_record2, [
|
||||
c for c in test_record2.columns if
|
||||
("thermal_transmittance" in c) or ("insulation_thickness" in c)
|
||||
]
|
||||
)
|
||||
|
||||
for c in test_record2.columns:
|
||||
if c in ["id", "SAP_ENDING", "HEAT_DEMAND_ENDING", "CARBON_ENDING"]:
|
||||
continue
|
||||
|
||||
if c == "FLOOR_HEIGHT_ENDING":
|
||||
assert (row2[c] - test_record2[c].values[0]) <= 0.020001
|
||||
continue
|
||||
|
||||
if c == "walls_insulation_thickness_ENDING":
|
||||
assert row2[c] == "average"
|
||||
assert test_record2[c].values[0] == "above average"
|
||||
continue
|
||||
|
||||
if c == "CONSTRUCTION_AGE_BAND":
|
||||
# For this, we have different values in the original data
|
||||
assert row2[c] == "England and Wales: 1996-2002"
|
||||
assert test_record2[c].values[0] == "England and Wales: 1900-1929"
|
||||
continue
|
||||
|
||||
assert test_record2[c].values[0] == row2[c]
|
||||
|
|
|
|||
|
|
@ -499,10 +499,12 @@ def app():
|
|||
# Add some temporal features - we look at the days from the standard starting point in time
|
||||
# for the starting and ending date so all records are from a fixed point
|
||||
data_by_urpn_df["DAYS_TO_STARTING"] = DataProcessor.calculate_days_to(
|
||||
data_by_urpn_df["LODGEMENT_DATE_STARTING"])
|
||||
data_by_urpn_df["LODGEMENT_DATE_STARTING"]
|
||||
)
|
||||
|
||||
data_by_urpn_df["DAYS_TO_ENDING"] = DataProcessor.calculate_days_to(
|
||||
data_by_urpn_df["LODGEMENT_DATE_ENDING"])
|
||||
data_by_urpn_df["LODGEMENT_DATE_ENDING"]
|
||||
)
|
||||
|
||||
data_by_urpn_df = data_by_urpn_df.drop(columns=["LODGEMENT_DATE_STARTING", "LODGEMENT_DATE_ENDING"])
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue