energy_validation_tool/meb_results.py

57 lines
2.8 KiB
Python

from pathlib import Path
import pandas as pd
import hub.helpers.constants as cte
class Results:
def __init__(self, city, path):
self._city = city
self._path = path
def print(self):
print_results = None
file = 'city name: ' + self._city.name + '\n'
for building in self._city.buildings:
if cte.MONTH in building.heating.keys():
heating_results = building.heating[cte.MONTH].rename(columns={cte.INSEL_MEB: f'{building.name} heating Wh'})
cooling_results = building.cooling[cte.MONTH].rename(columns={cte.INSEL_MEB: f'{building.name} cooling Wh'})
lighting_results = building.lighting_electrical_demand[cte.MONTH]\
.rename(columns={cte.INSEL_MEB: f'{building.name} lighting electrical demand Wh'})
appliances_results = building.appliances_electrical_demand[cte.MONTH]\
.rename(columns={cte.INSEL_MEB: f'{building.name} appliances electrical demand Wh'})
dhw_results = building.domestic_hot_water_heat_demand[cte.MONTH]\
.rename(columns={cte.INSEL_MEB: f'{building.name} domestic hot water demand Wh'})
else:
array = [None] * 12
heating_results = pd.DataFrame(array, columns=[f'{building.name} heating Wh'])
cooling_results = pd.DataFrame(array, columns=[f'{building.name} cooling Wh'])
lighting_results = pd.DataFrame(array, columns=[f'{building.name} lighting electrical demand Wh'])
appliances_results = pd.DataFrame(array, columns=[f'{building.name} appliances electrical demand Wh'])
dhw_results = pd.DataFrame(array, columns=[f'{building.name} domestic hot water demand Wh'])
if print_results is None:
print_results = heating_results
else:
print_results = pd.concat([print_results, heating_results], axis='columns')
print_results = pd.concat([print_results,
cooling_results,
lighting_results,
appliances_results,
dhw_results], axis='columns')
file += '\n'
file += f'name: {building.name}\n'
file += f'year of construction: {building.year_of_construction}\n'
file += f'function: {building.function}\n'
file += f'floor area: {building.floor_area}\n'
if building.average_storey_height is not None and building.eave_height is not None:
file += f'storeys: {int(building.eave_height / building.average_storey_height)}\n'
else:
file += f'storeys: n/a\n'
file += f'heated_volume: {0.85 * building.volume}\n'
file += f'volume: {building.volume}\n'
full_path_results = Path(self._path / 'demand.csv').resolve()
print_results.to_csv(full_path_results, na_rep='null')
full_path_metadata = Path(self._path / 'metadata.csv').resolve()
with open(full_path_metadata, 'w') as metadata_file:
metadata_file.write(file)