mirror of
https://github.com/Hestia-Homes/Model.git
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creating aiha output
This commit is contained in:
Khalim Conn-Kowlessar
parent
bfded2aaf9
commit
ce9b3e5e20
1 changed files with 448 additions and 4 deletions
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@ -1,5 +1,8 @@
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import os
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from io import BytesIO
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import pandas as pd
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from etl.xml_survey_extraction.XmlParser import XmlParser
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SURVEY_FOLDER_PATH = "/Users/khalimconn-kowlessar/Documents/hestia/Customers/AIHA/RESIDENT SURVEYS"
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@ -22,7 +25,8 @@ def main():
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xml_files = [f for f in os.listdir(subfolder) if f.endswith('.xml')]
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if not xml_files:
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raise FileNotFoundError(f"No XML files found in subfolder: {subfolder}")
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print(f"No XML files found in subfolder: {subfolder}")
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continue
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# If any XML files are found, perform the data extraction. We use the subfolder name as the survey key.
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for xml_file in xml_files:
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@ -44,16 +48,456 @@ def main():
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# Run the parser to extract the data
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xml_parser.run()
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if not xml_parser.epc:
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# If we don't have a lig xml
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continue
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# Store the extracted data for further processing
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extracted_surveys.append({
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"epc": xml_parser.epc,
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"additional_data": xml_parser.additional_data,
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"subfolder": subfolder
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"survey_key": subfolder.split("/")[-1],
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**xml_parser.epc,
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**xml_parser.additional_data
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})
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print(f"Extracted {len(extracted_surveys)} surveys.")
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# Process the extracted_surveys as needed, for example, save to a database or write to a file.
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extracted_surveys = pd.DataFrame(extracted_surveys)
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# THis is the data we need for the AIHA project
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measures_data = extracted_surveys[
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["survey_key", "address", "postcode", "current-energy-efficiency", "current-energy-rating"]
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]
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measures_data = measures_data.sort_values("survey_key", ascending=True)
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# Note:
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# The properties will still have "Very poor" ratings for their hot water
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# TODO
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# - AIH001-03 has a basement and so we should discount this area from the ground floor
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# - AIH001-03 has a loft that is inaccessible - ask Chenai about why this property didn't have access to the loft
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# - AIH001-03 instead of cylinder insulation, we could install an air source heat pump but it might not be the
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# best option for this property due to it being extrememly large and the walls being uninsulated. It might not
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# be performant enough in the winter, when COP will be more like 1.5.
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# - AIH001-03 - can add additional 1.6kWp solar PV to flat roof to get close to EPC C. How many occupants are
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# in the property? Does it make sense to have such a large solar PV system (5.6kWp)?
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# - AIH001-04 why couldn't the cylinder be accessed? - treating this could get to the EPC C
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# - Generally, should we consider insulated doors?
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# - AIH001-08 and AIH001-09, check if it's freehold - could solar work as both of these units are part of the same
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# buulding
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# - AIH001-09 - The extension is 1900-1929 but has a cavity wall
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# - AIH001-09 - Is it not possible to install a loft hatch?
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# - AIH001-09 - Why is there assumed secondary heating?
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# - AIH001-09 - Is there definitely an immersion water heater? Is this definitely the case for the other units?
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# - AIH001-11 - The layout of this unit is confusing, is there roof access?
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# - AIH001-12 - Why was there not access to the cylinder?
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#
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recommended_measures = [
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{
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"survey_key": "AIH001-01",
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"starting_sap": 69,
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"recommended_measures": [],
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"notes": "Is EPC C"
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},
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{
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"survey_key": "AIH001-03",
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"starting_sap": 43,
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"recommended_measures": [
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{
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"measure": "Cylinder Insulation",
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"description": "80mm cylinder insulation",
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"sap_points": 1,
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"ending_sap": 44,
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},
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{
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"measure": "Solar PV",
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"description": "Solar PV system with various configurations",
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"config": [
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{
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"size": "4kWp",
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"orientation": "East",
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"elavation": 30,
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"overshading": "Modest",
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},
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{
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"size": "1.6kWp",
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"orientation": "Horizontal",
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"elavation": "Horizontal",
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"overshading": "Modest",
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}
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],
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"sap_points": 7,
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"ending_sap": 53
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},
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{
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"measure": "Loft Insulation",
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"description": "300mm of loft insulation",
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"sap_points": 8,
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"ending_sap": 61
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},
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{
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"measure": "TTZC",
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"description": "Thermostatic Time Zone Control",
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"sap_points": 3,
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"ending_sap": 64
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}
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],
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"notes": "There was no access to the loft for this property and so a loft hatch would need to be "
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"installed..."
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},
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{
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"survey_key": "AIH001-04",
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"starting_sap": 48,
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"recommended_measures": [
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{
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"measure": "Flat Roof Insulation",
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"description": "100mm flat roof insulation",
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"sap_points": 4,
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"ending_sap": 52
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},
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{
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"measure": "TTZC",
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"description": "Thermostatic Time Zone Control",
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"sap_points": 3,
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"ending_sap": 55
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},
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{
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"measure": "Solar PV",
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"description": "Solar PV system with 4kW capacity, south-facing",
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"config": [
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{
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"size": "4kW",
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"orientation": "South",
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"elavation": 30,
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"overshading": "Modest",
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}
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],
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"sap_points": 12,
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"ending_sap": 67
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}
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],
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"notes": ""
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},
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{
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"survey_key": "AIH001-05",
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"starting_sap": 54,
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"recommended_measures": [
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{
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"measure": "Flat Roof Insulation",
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"description": "100mm flat roof insulation",
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"sap_points": 5,
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"ending_sap": 59,
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},
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{
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"measure": "Cylinder Insulation",
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"description": "80mm cylinder insulation",
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"sap_points": 2,
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"ending_sap": 61,
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},
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{
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"measure": "Solar PV",
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"description": "Solar PV system with 4kW capacity, horizontal orientation",
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"config": [
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{
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"size": "4kW",
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"orientation": "Horizontal",
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"elavation": 30,
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"overshading": "Modest",
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}
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],
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"sap_points": 9,
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"ending_sap": 70
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},
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{
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"measure": "TTZC",
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"description": "Thermostatic Time Zone Control",
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"sap_points": 3,
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"ending_sap": 73
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}
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],
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"notes": ""
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},
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{
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"survey_key": "AIH001-06",
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"starting_sap": 62,
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"recommended_measures": [
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{
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"measure": "Cylinder Insulation",
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"description": "80mm cylinder insulation",
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"sap_points": 2,
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"ending_sap": 64,
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},
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{
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"measure": "Solar PV",
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"description": "Solar PV system with 2kW capacity, south-facing",
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"config": [
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{
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"size": "2kW",
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"orientation": "South",
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"elavation": 30,
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"overshading": "Modest",
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}
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],
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"sap_points": 6,
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"ending_sap": 70
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}
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]
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},
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{
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"survey_key": "AIH001-07",
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"starting_sap": 74,
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"recommended_measures": [],
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"notes": "Is EPC C"
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},
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{
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"survey_key": "AIH001-08",
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"starting_sap": 56,
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"recommended_measures": [
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{
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"measure": "Loft Insulation",
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"description": "300mm of loft insulation",
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"sap_points": 2,
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"ending_sap": 58,
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},
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{
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"measure": "Cylinder Insulation",
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"description": "80mm cylinder insulation",
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"sap_points": 4,
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"ending_sap": 62,
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},
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{
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"measure": "Internal Wall Insulation",
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"description": "100mm internal wall insulation",
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"sap_points": 5,
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"ending_sap": 69,
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},
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{
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"measure": "Ventilation",
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"description": "Ventilation improvement",
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"sap_points": 0,
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"ending_sap": 69,
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}
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]
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},
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{
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"survey_key": "AIH001-09",
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"starting_sap": 44,
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"recommended_measures": [
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{
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"measure": "Internal Wall Insulation",
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"description": "100mm internal wall insulation",
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"sap_points": 8,
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"ending_sap": 52,
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},
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{
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"measure": "Cavity Wall Insulation",
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"description": "Cavity wall insulation for extensions",
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"sap_points": 1,
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"ending_sap": 53,
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},
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{
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"measure": "Ventilation",
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"description": "Ventilation improvement",
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"sap_points": 0,
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"ending_sap": 53,
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},
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{
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"measure": "TTZC",
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"description": "Thermostatic Time Zone Control",
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"sap_points": 3,
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"ending_sap": 56,
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}
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]
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},
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{
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"survey_key": "AIH001-11",
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"starting_sap": 59,
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"recommended_measures": [
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{
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"measure": "TTZC",
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"description": "Thermostatic Time Zone Control",
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"sap_points": 4,
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"ending_sap": 63,
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},
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{
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"measure": "Internal Wall Insulation",
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"description": "100mm internal wall insulation",
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"sap_points": 5,
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"ending_sap": 68,
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},
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{
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"measure": "Cylinder Insulation",
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"description": "80mm cylinder insulation",
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"sap_points": 1,
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"ending_sap": 69,
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}
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]
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},
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{
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"survey_key": "AIH001-12",
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"starting_sap": 46,
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"recommended_measures": [
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{
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"measure": "Double Glazing",
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"description": "Installation of double glazing",
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"sap_points": 2,
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"ending_sap": 48,
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},
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{
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"measure": "Draught Proofing",
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"description": "Draught proofing improvements",
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"sap_points": 1,
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"ending_sap": 49,
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},
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{
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"measure": "Solar PV",
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"description": "Solar PV system with 3.2kW capacity, east-facing",
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"config": [
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{
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"size": "3.2W",
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"orientation": "East",
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"elavation": 30,
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"overshading": "Little or none",
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}
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],
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"sap_points": 9,
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"ending_sap": 58
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},
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{
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"measure": "Air Source Heat Pump",
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"description": "Ecoforest ecoAIR EVI 4-20 20kW air source heat pump",
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"sap_points": 15,
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"ending_sap": 73
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},
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{
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"measure": "Tariff Review",
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"description": "Switch to 24-hour tariff",
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"sap_points": 15,
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"ending_sap": 88
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}
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]
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},
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{
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"survey_key": "AIH001-13",
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"starting_sap": 53,
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"recommended_measures": [
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{
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"measure": "Roof Insulation",
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"description": "100mm+ insulation on all surfaces (ceiling u=0.16, walls u=0.3)",
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"sap_points": 6,
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"ending_sap": 59,
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},
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{
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"measure": "Flat Roof Insulation",
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"description": "Flat roof insulation",
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"sap_points": 2,
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"ending_sap": 61,
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},
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{
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"measure": "Cavity Wall Insulation",
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"description": "Cavity wall insulation",
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"sap_points": 6,
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"ending_sap": 67,
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},
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{
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"measure": "Ventilation",
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"description": "Ventilation improvement",
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"sap_points": 0,
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"ending_sap": 67,
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},
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{
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"measure": "TTZC",
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"description": "Thermostatic Time Zone Control",
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"sap_points": 2,
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"ending_sap": 69,
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},
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{
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"measure": "Solar PV",
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"description": "Solar PV system with 4kW capacity, flat roof installation",
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"config": [
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{
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"size": "4kW",
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"orientation": "Horizontal",
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"elavation": 30,
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"overshading": "None or little",
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}
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],
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"sap_points": 9,
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"ending_sap": 78
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}
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]
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},
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{
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"survey_key": "AIH001-14",
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"starting_sap": 63,
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"recommended_measures": [
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{
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"measure": "Cavity Wall Insulation",
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"description": "Insulation for cavity walls",
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"sap_points": 5,
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"ending_sap": 68,
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},
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{
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"measure": "Ventilation",
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"description": "Ventilation improvement",
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"sap_points": 0,
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"ending_sap": 68,
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},
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{
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"measure": "Loft Insulation",
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"description": "Installation of loft insulation",
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"sap_points": 1,
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"ending_sap": 69,
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},
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{
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"measure": "Solar PV",
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"description": "Solar PV system with 10kW capacity",
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"sap_points": 10,
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"ending_sap": 79,
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}
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]
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},
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]
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# Step 1: Normalize the recommended_measures data into a DataFrame.
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normalized_measures = []
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for survey in recommended_measures:
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survey_key = survey["survey_key"]
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starting_sap = survey["starting_sap"]
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for measure in survey.get("recommended_measures", []):
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normalized_measures.append({
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"survey_key": survey_key,
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"starting_sap": starting_sap,
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"measure": measure["measure"],
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"description": measure.get("description", "")
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})
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# Convert the normalized list into a DataFrame.
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measures_df = pd.DataFrame(normalized_measures)
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# Step 2: Pivot the measures_df to have a column for each measure type, using the description as values.
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pivoted_measures = measures_df.pivot_table(
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index="survey_key",
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columns="measure",
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values="description",
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aggfunc=lambda x: ' '.join(x), # Concatenate descriptions if there are multiple entries.
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fill_value=None
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).reset_index()
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# Step 3: Extract starting SAP for each survey key.
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starting_sap_df = measures_df.drop_duplicates(subset=["survey_key"])[["survey_key", "starting_sap"]]
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# Merge starting SAP back onto pivoted measures.
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result_df = pd.merge(pivoted_measures, starting_sap_df, on="survey_key", how="left")
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# Step 4: Calculate the ending SAP using the total sap points.
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# Note: If you want to use total sap points, you'll need to update the total calculation accordingly.
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# Step 5: Merge the result with the measures_data to get the final DataFrame.
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final_measures = measures_data.merge(
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result_df, how="left", on="survey_key"
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)
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if __name__ == "__main__":
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