from pathlib import Path

from energy_system_modelling_package.energy_system_modelling_factories.energy_system_sizing_factory import \
  EnergySystemsSizingFactory
from energy_system_modelling_package.energy_system_modelling_factories.montreal_energy_system_archetype_modelling_factory import \
  MontrealEnergySystemArchetypesSimulationFactory
from hub.imports.energy_systems_factory import EnergySystemsFactory
from hub.imports.geometry_factory import GeometryFactory
from hub.helpers.dictionaries import Dictionaries
from hub.imports.construction_factory import ConstructionFactory
from hub.imports.usage_factory import UsageFactory
from hub.imports.weather_factory import WeatherFactory
import pandas as pd
import hub.helpers.constants as cte
from costing_package.constants import *
from costing_package.cost import Cost
# Specify the GeoJSON file path
input_files_path = (Path(__file__).parent / 'input_files')
input_files_path.mkdir(parents=True, exist_ok=True)
geojson_file_path = input_files_path / 'rf_building.geojson'
output_path = (Path(__file__).parent / 'out_files').resolve()
output_path.mkdir(parents=True, exist_ok=True)
simulation_results_path = (Path(__file__).parent / 'out_files' / 'simulation_results').resolve()
simulation_results_path.mkdir(parents=True, exist_ok=True)
cost_analysis_output_path = output_path / 'cost_analysis'
cost_analysis_output_path.mkdir(parents=True, exist_ok=True)
city = GeometryFactory(file_type='geojson',
                       path=geojson_file_path,
                       height_field='height',
                       year_of_construction_field='year_of_construction',
                       function_field='function',
                       function_to_hub=Dictionaries().montreal_function_to_hub_function).city
demands = pd.read_csv(input_files_path / 'cbt_data.csv')
city.buildings[0].heating_demand[cte.HOUR] = [x * cte.WATTS_HOUR_TO_JULES * 1000 / 4 for x in demands['total'].to_list()]
city.buildings[0].cooling_demand[cte.HOUR] = [0] * 8760
city.buildings[0].domestic_hot_water_heat_demand[cte.HOUR] = [0] * 8760
city.buildings[0].lighting_electrical_demand[cte.HOUR] = [0] * 8760
city.buildings[0].lighting_electrical_demand[cte.YEAR] = [0]
city.buildings[0].appliances_electrical_demand[cte.YEAR] = [0]
city.buildings[0].appliances_electrical_demand[cte.HOUR] = [0] * 8760
ConstructionFactory('nrcan', city).enrich()
UsageFactory('nrcan', city).enrich()
WeatherFactory('epw', city).enrich()
for building in city.buildings:
  building.energy_systems_archetype_name = ('Central Hydronic Air and Electricity Source Heating System with Unitary '
                                            'Split and Air Source HP DHW')
EnergySystemsFactory('montreal_future', city).enrich()
EnergySystemsSizingFactory('peak_load_sizing', city).enrich()
for building in city.buildings:
  MontrealEnergySystemArchetypesSimulationFactory(f'archetype_cluster_{building.energy_systems_archetype_cluster_id}',
                                                  building,
                                                  simulation_results_path).enrich()
for building in city.buildings:
  cost_retrofit_scenario = SYSTEM_RETROFIT
  lcc_dataframe = Cost(building=building,
                       retrofit_scenario=cost_retrofit_scenario,
                       fuel_tariffs=['Electricity-D', 'Gas-Energir']).life_cycle
  lcc_dataframe.to_csv(cost_analysis_output_path / f'{building.name}_retrofitted_lcc.csv')
print('test')