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2 Commits
06e31847a5
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d78ab8010c
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d78ab8010c | |||
17fcc5d41f |
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@ -1,185 +0,0 @@
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{
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"type": "FeatureCollection",
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{
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"type": "Feature",
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"id": 5755,
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"ID_UEV": "02039261",
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"CIVIQUE_DE": " 8501",
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"CIVIQUE_FI": " 8501",
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"NOM_RUE": "boulevard Ray-Lawson (ANJ)",
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"SUITE_DEBU": " ",
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"MUNICIPALI": "50",
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"ETAGE_HORS": 0,
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"NOMBRE_LOG": 0,
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"ANNEE_CONS": 1980,
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"CODE_UTILI": "3019",
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"LETTRE_FIN": " ",
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"LIBELLE_UT": "Autres activit\u00c3\u00a9s d'impression commerciale",
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"CATEGORIE_": "R\u00c3\u00a9gulier",
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"MATRICULE8": "0053-00-3380-2-000-0000",
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"SUPERFICIE": 23420,
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"provideren": "Municipal",
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"providerfr": "Municipal",
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"datemin": "20151124",
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"elevmin": 40.63,
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"g_objectid": "893223",
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"g_co_mrc": "66023",
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"g_code_mun": "66023",
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"g_arrond": "REM09",
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"g_anrole": "2019",
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"g_usag_pre": "Industrie l\u00c3\u00a9g\u00c3\u00a8re",
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"g_no_lot": "1005810",
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"g_nb_poly_": "1",
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"g_utilisat": "3019",
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"g_nb_logem": " ",
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"g_nb_locau": "1",
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"g_descript": "Unit\u00c3\u00a9 d'\u00c3\u00a9valuation",
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}
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]
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}
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90
main.py
90
main.py
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@ -10,56 +10,56 @@ from monthly_energy_balance_engine import MonthlyEnergyBalanceEngine
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from sra_engine import SraEngine
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#try:
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file_path = (Path(__file__).parent / 'input_files' / 'neighbours.geojson')
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climate_reference_city = 'Montreal'
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weather_file = 'CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw'
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weather_format = 'epw'
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construction_format = 'nrcan'
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usage_format = 'nrcan'
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attic_heated_case = 0
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basement_heated_case = 1
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try:
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file_path = (Path(__file__).parent / 'input_files' / 'selected_building.geojson')
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climate_reference_city = 'Montreal'
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weather_file = 'CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw'
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weather_format = 'epw'
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construction_format = 'nrcan'
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usage_format = 'nrcan'
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attic_heated_case = 0
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basement_heated_case = 1
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out_path = (Path(__file__).parent / 'output_files')
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tmp_folder = (Path(__file__).parent / 'tmp')
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out_path = (Path(__file__).parent / 'output_files')
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tmp_folder = (Path(__file__).parent / 'tmp')
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print('[simulation start]')
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city = GeometryFactory('geojson',
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path=file_path,
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height_field='citygml_me',
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year_of_construction_field='ANNEE_CONS',
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function_field='CODE_UTILI',
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function_to_hub=Dictionaries().montreal_function_to_hub_function).city
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city.climate_reference_city = climate_reference_city
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city.climate_file = (tmp_folder / f'{climate_reference_city}.cli').resolve()
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print(f'city created from {file_path}')
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WeatherFactory(weather_format, city, file_name=weather_file).enrich()
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print('enrich weather... done')
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ConstructionFactory(construction_format, city).enrich()
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print('enrich constructions... done')
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UsageFactory(usage_format, city).enrich()
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print('enrich usage... done')
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print('[simulation start]')
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city = GeometryFactory('geojson',
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path=file_path,
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height_field='building_height',
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year_of_construction_field='ANNEE_CONS',
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function_field='CODE_UTILI',
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function_to_hub=Dictionaries().montreal_function_to_hub_function).city
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city.climate_reference_city = climate_reference_city
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city.climate_file = (tmp_folder / f'{climate_reference_city}.cli').resolve()
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print(f'city created from {file_path}')
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WeatherFactory(weather_format, city, file_name=weather_file).enrich()
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print('enrich weather... done')
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ConstructionFactory(construction_format, city).enrich()
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print('enrich constructions... done')
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UsageFactory(usage_format, city).enrich()
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print('enrich usage... done')
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print('exporting:')
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sra_file = (tmp_folder / f'{city.name}_sra.xml').resolve()
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SraEngine(city, sra_file, tmp_folder, weather_file)
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# Assign radiation to the city
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print(' sra processed...')
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print('exporting:')
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sra_file = (tmp_folder / f'{city.name}_sra.xml').resolve()
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SraEngine(city, sra_file, tmp_folder, weather_file)
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# Assign radiation to the city
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print(' sra processed...')
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for building in city.buildings:
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building.attic_heated = attic_heated_case
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building.basement_heated = basement_heated_case
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MonthlyEnergyBalanceEngine(city, tmp_folder)
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print(' insel processed...')
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for building in city.buildings:
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building.attic_heated = attic_heated_case
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building.basement_heated = basement_heated_case
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MonthlyEnergyBalanceEngine(city, tmp_folder)
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print(' insel processed...')
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results = Results(city, out_path)
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results.print()
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results = Results(city, out_path)
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results.print()
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print('print results...')
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print('print results...')
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print('[simulation end]')
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print('[simulation end]')
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#except Exception as ex:
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# print(ex)
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# print('error: ', ex)
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# print('[simulation abort]')
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except Exception as ex:
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print(ex)
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print('error: ', ex)
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print('[simulation abort]')
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43
results.py
43
results.py
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@ -12,14 +12,22 @@ class Results:
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print_results = None
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file = 'city name: ' + self._city.name + '\n'
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for building in self._city.buildings:
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heating_results = building.heating[cte.MONTH].rename(columns={cte.INSEL_MEB: f'{building.name} heating Wh'})
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cooling_results = building.cooling[cte.MONTH].rename(columns={cte.INSEL_MEB: f'{building.name} cooling Wh'})
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lighting_results = building.lighting_electrical_demand[cte.MONTH]\
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.rename(columns={cte.INSEL_MEB: f'{building.name} lighting electrical demand Wh'})
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appliances_results = building.appliances_electrical_demand[cte.MONTH]\
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.rename(columns={cte.INSEL_MEB: f'{building.name} appliances electrical demand Wh'})
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dhw_results = building.domestic_hot_water_heat_demand[cte.MONTH]\
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.rename(columns={cte.INSEL_MEB: f'{building.name} domestic hot water demand Wh'})
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if cte.MONTH in building.heating.keys():
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heating_results = building.heating[cte.MONTH].rename(columns={cte.INSEL_MEB: f'{building.name} heating Wh'})
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cooling_results = building.cooling[cte.MONTH].rename(columns={cte.INSEL_MEB: f'{building.name} cooling Wh'})
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lighting_results = building.lighting_electrical_demand[cte.MONTH]\
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.rename(columns={cte.INSEL_MEB: f'{building.name} lighting electrical demand Wh'})
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appliances_results = building.appliances_electrical_demand[cte.MONTH]\
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.rename(columns={cte.INSEL_MEB: f'{building.name} appliances electrical demand Wh'})
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dhw_results = building.domestic_hot_water_heat_demand[cte.MONTH]\
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.rename(columns={cte.INSEL_MEB: f'{building.name} domestic hot water demand Wh'})
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else:
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array = [None] * 12
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heating_results = pd.DataFrame(array, columns=[f'{building.name} heating Wh'])
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cooling_results = pd.DataFrame(array, columns=[f'{building.name} cooling Wh'])
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lighting_results = pd.DataFrame(array, columns=[f'{building.name} lighting electrical demand Wh'])
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appliances_results = pd.DataFrame(array, columns=[f'{building.name} appliances electrical demand Wh'])
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dhw_results = pd.DataFrame(array, columns=[f'{building.name} domestic hot water demand Wh'])
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if print_results is None:
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print_results = heating_results
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else:
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@ -30,16 +38,19 @@ class Results:
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appliances_results,
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dhw_results], axis='columns')
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file += '\n'
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file += 'name: ' + building.name + '\n'
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file += 'year of construction: ' + str(building.year_of_construction) + '\n'
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file += 'function: ' + building.function + '\n'
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file += 'floor area: ' + str(building.floor_area) + '\n'
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file += 'storeys: ' + str(int(building.eave_height / building.average_storey_height)) + '\n'
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file += 'heated_volume: ' + str(0.85 * building.volume) + '\n'
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file += 'volume: ' + str(building.volume) + '\n'
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file += f'name: {building.name}\n'
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file += f'year of construction: {building.year_of_construction}\n'
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file += f'function: {building.function}\n'
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file += f'floor area: {building.floor_area}\n'
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if building.average_storey_height is not None and building.eave_height is not None:
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file += f'storeys: {int(building.eave_height / building.average_storey_height)}\n'
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else:
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file += f'storeys: n/a\n'
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file += f'heated_volume: {0.85 * building.volume}\n'
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file += f'volume: {building.volume}\n'
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full_path_results = Path(self._path / 'demand.csv').resolve()
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print_results.to_csv(full_path_results)
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print_results.to_csv(full_path_results, na_rep='null')
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full_path_metadata = Path(self._path / 'metadata.csv').resolve()
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with open(full_path_metadata, 'w') as metadata_file:
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metadata_file.write(file)
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Loading…
Reference in New Issue
Block a user