146 lines
7.1 KiB
Python
146 lines
7.1 KiB
Python
import json
|
|
from pathlib import Path
|
|
import pandas as pd
|
|
import geopandas as gpd
|
|
# Specify the GeoJSON file path
|
|
input_files_path = (Path(__file__).parent / 'input_files')
|
|
geojson_file_path = input_files_path / 'Lachine_moved_existing_year_type.geojson'
|
|
#read it to use later
|
|
gdf = gpd.read_file(geojson_file_path)
|
|
#define output path
|
|
output_path = (Path(__file__).parent / 'out_files').resolve()
|
|
output_path.mkdir(parents=True, exist_ok=True)
|
|
# Define output folders
|
|
output_folders = ['building_type', 'building_type_2', 'building_type_3']
|
|
#output paths containing energy+ results are read
|
|
|
|
gdf_building_outputs={}
|
|
|
|
output_paths = {}
|
|
# Create directories for the output folders
|
|
for folder in output_folders:
|
|
path = output_path / folder
|
|
path.mkdir(parents=True, exist_ok=True)
|
|
output_paths[folder] = path
|
|
# Read the resulting GeoDataFrames saved in each folder
|
|
gdf_building_outputs = {}
|
|
for folder in output_folders:
|
|
path = output_paths[folder] / 'updated_buildings.geojson'
|
|
if path.exists():
|
|
gdf_building_outputs[folder] = gpd.read_file(path)
|
|
else:
|
|
gdf_building_outputs[folder] = gpd.GeoDataFrame()
|
|
|
|
|
|
|
|
|
|
|
|
percentage_data = {
|
|
1646: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1647: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1648: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1649: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1650: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1651: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1652: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1653: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1654: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1655: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1656: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1657: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1658: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1659: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1660: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1661: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1662: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1663: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1664: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1665: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1666: {"type1_%": 0.891045711, "type2_%": 0.108954289, "type3_%": 0},
|
|
1667: {"type1_%": 0.8, "type2_%": 0.2, "type3_%": 0},
|
|
1668: {"type1_%": 0.666666667, "type2_%": 0.333333333, "type3_%": 0},
|
|
1669: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1673: {"type1_%": 0.666666667, "type2_%": 0.3, "type3_%": 0},
|
|
1674: {"type1_%": 0.666666667, "type2_%": 0.3, "type3_%": 0},
|
|
1675: {"type1_%": 0.666666667, "type2_%": 0.3, "type3_%": 0},
|
|
1676: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1677: {"type1_%": 1, "type2_%": 0, "type3_%": 0},
|
|
1678: {"type1_%": 0.666666667, "type2_%": 0.3, "type3_%": 0},
|
|
1679: {"type1_%": 0.666666667, "type2_%": 0.3, "type3_%": 0},
|
|
1680: {"type1_%": 0.666666667, "type2_%": 0.3, "type3_%": 0},
|
|
1681: {"type1_%": 0.666666667, "type2_%": 0.3, "type3_%": 0},
|
|
1687: {"type1_%": 0.606611029, "type2_%": 0.28211422, "type3_%": 0.11127475},
|
|
1688: {"type1_%": 0.92, "type2_%": 0.1, "type3_%": 0},
|
|
1689: {"type1_%": 0.96, "type2_%": 0, "type3_%": 0},
|
|
1690: {"type1_%": 0.94, "type2_%": 0.1, "type3_%": 0},
|
|
1691: {"type1_%": 0.75, "type2_%": 0.3, "type3_%": 0},
|
|
}
|
|
|
|
|
|
# Define a function to calculate new demands based on percentages
|
|
def calculate_demands(building_id, percentages, gdf_building_type, gdf_building_type_2, gdf_building_type_3):
|
|
new_demands = {}
|
|
for demand_type in [
|
|
'heating_demand_kWh', 'cooling_demand_kWh',
|
|
'domestic_hot_water_heat_demand_kWh',
|
|
'appliances_electrical_demand_kWh',
|
|
'lighting_electrical_demand_kWh']:
|
|
demand_type_1 = gdf_building_type.loc[gdf_building_type['id'] == building_id, demand_type].values[
|
|
0] if not gdf_building_type.empty else 0
|
|
demand_type_2 = gdf_building_type_2.loc[gdf_building_type_2['id'] == building_id, demand_type].values[
|
|
0] if not gdf_building_type_2.empty else 0
|
|
demand_type_3 = gdf_building_type_3.loc[gdf_building_type_3['id'] == building_id, demand_type].values[
|
|
0] if not gdf_building_type_3.empty else 0
|
|
|
|
new_demand = (
|
|
demand_type_1 * percentages['type1_%'] +
|
|
demand_type_2 * percentages['type2_%'] +
|
|
demand_type_3 * percentages['type3_%']
|
|
)
|
|
new_demands[demand_type] = new_demand
|
|
return new_demands
|
|
|
|
|
|
# Process each building in the GeoJSON
|
|
for idx, feature in gdf.iterrows():
|
|
building_id = feature['id'] # Adjust this based on your GeoJSON structure
|
|
if building_id == 1673:
|
|
percentages = percentage_data[building_id]
|
|
print(percentages)
|
|
new_demands = calculate_demands(building_id, percentages,
|
|
gdf_building_outputs.get('building_type', gpd.GeoDataFrame()),
|
|
gdf_building_outputs.get('building_type_2', gpd.GeoDataFrame()),
|
|
gdf_building_outputs.get('building_type_3', gpd.GeoDataFrame()))
|
|
print(new_demands)
|
|
# Update the properties of the feature
|
|
gdf.at[idx, 'heating_demand_kWh'] = new_demands['heating_demand_kWh']
|
|
gdf.at[idx, 'cooling_demand_kWh'] = new_demands['cooling_demand_kWh']
|
|
gdf.at[idx, 'domestic_hot_water_heat_demand_kWh'] = new_demands['domestic_hot_water_heat_demand_kWh']
|
|
gdf.at[idx, 'appliances_electrical_demand_kWh'] = new_demands['appliances_electrical_demand_kWh']
|
|
gdf.at[idx, 'lighting_electrical_demand_kWh'] = new_demands['lighting_electrical_demand_kWh']
|
|
|
|
print('test')
|
|
|
|
#
|
|
# if building_id in percentage_data:
|
|
# percentages = percentage_data[building_id]
|
|
# new_demands = calculate_demands(building_id, percentages,
|
|
# gdf_building_outputs.get('building_type', gpd.GeoDataFrame()),
|
|
# gdf_building_outputs.get('building_type_2', gpd.GeoDataFrame()),
|
|
# gdf_building_outputs.get('building_type_3', gpd.GeoDataFrame()))
|
|
#
|
|
# # Update the properties of each feature
|
|
# gdf.at[idx, 'heating_demand_kWh'] = new_demands['heating_demand_kWh']
|
|
# gdf.at[idx, 'cooling_demand_kWh'] = new_demands['cooling_demand_kWh']
|
|
# gdf.at[idx, 'domestic_hot_water_heat_demand_kWh'] = new_demands['domestic_hot_water_heat_demand_kWh']
|
|
# gdf.at[idx, 'appliances_electrical_demand_kWh'] = new_demands['appliances_electrical_demand_kWh']
|
|
# gdf.at[idx, 'lighting_electrical_demand_kWh'] = new_demands['lighting_electrical_demand_kWh']
|
|
#
|
|
# # Save the updated GeoDataFrame to the appropriate folder
|
|
# for folder, key in zip(output_folders, ['type1_%', 'type2_%', 'type3_%']):
|
|
# if percentages[key] > 0:
|
|
# output_gdf = gdf_building_outputs[folder]
|
|
# output_gdf = output_gdf.append(gdf.iloc[[idx]], ignore_index=True)
|
|
# output_gdf.to_file(output_paths[folder] / 'buildings.geojson', driver='GeoJSON')
|
|
#
|