59 lines
2.7 KiB
Python
59 lines
2.7 KiB
Python
from pathlib import Path
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import subprocess
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from scripts.ep_workflow import energy_plus_workflow
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from hub.imports.geometry_factory import GeometryFactory
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from hub.helpers.dictionaries import Dictionaries
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from hub.imports.construction_factory import ConstructionFactory
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from hub.imports.usage_factory import UsageFactory
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from hub.imports.weather_factory import WeatherFactory
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import hub.helpers.constants as cte
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from hub.exports.exports_factory import ExportsFactory
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from hub.imports.results_factory import ResultFactory
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import pandas as pd
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from scripts.solar_angles import CitySolarAngles
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from scripts.radiation_tilted import RadiationTilted
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# Specify the GeoJSON file path
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input_files_path = (Path(__file__).parent / 'input_files')
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geojson_file_path = input_files_path / 'Lachine_New_Developments.geojson'
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output_path = (Path(__file__).parent / 'out_files').resolve()
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output_path.mkdir(parents=True, exist_ok=True)
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sra_output_path = output_path / 'sra_outputs'
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sra_output_path.mkdir(parents=True, exist_ok=True)
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# Create city object from GeoJSON file
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city = GeometryFactory('geojson',
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path=geojson_file_path,
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height_field='maximum_roof_height',
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year_of_construction_field='year_built',
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function_field='building_type',
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function_to_hub=Dictionaries().montreal_function_to_hub_function).city
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# Enrich city data
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WeatherFactory('epw', city).enrich()
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ExportsFactory('sra', city, sra_output_path).export()
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sra_path = (sra_output_path / f'{city.name}_sra.xml').resolve()
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subprocess.run(['sra', str(sra_path)])
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ResultFactory('sra', city, sra_output_path).enrich()
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solar_angles = CitySolarAngles(city.name,
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city.latitude,
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city.longitude,
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tilt_angle=45,
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surface_azimuth_angle=180).calculate
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for building in city.buildings:
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ghi = [x / cte.WATTS_HOUR_TO_JULES for x in building.roofs[0].global_irradiance[cte.HOUR]]
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RadiationTilted(building,
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solar_angles,
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tilt_angle=45,
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ghi=ghi).enrich()
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building_names = []
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for building in city.buildings:
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building_names.append(building.name)
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df = pd.DataFrame(columns=building_names)
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df1 = pd.DataFrame(columns=building_names)
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print('test')
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for building in city.buildings:
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# if building.name in selected_buildings_list:
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df[f'{building.name}'] = building.roofs[0].global_irradiance[cte.HOUR]
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df1[f'{building.name}'] = building.roofs[0].global_irradiance_tilted[cte.HOUR]
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df.to_csv('solar_radiation_horizontal_selected_buildings.csv')
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df1.to_csv('solar_radiation_tilted_selected_buildings.csv') |