from pathlib import Path
import subprocess
from building_modelling.ep_run_enrich import energy_plus_workflow
from energy_system_modelling_package.energy_system_modelling_factories.montreal_energy_system_archetype_modelling_factory import \
  MontrealEnergySystemArchetypesSimulationFactory
from energy_system_modelling_package.energy_system_modelling_factories.system_sizing_methods.genetic_algorithm.multi_objective_genetic_algorithm import MultiObjectiveGeneticAlgorithm
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
from hub.imports.results_factory import ResultFactory
import hub.helpers.constants as cte
from building_modelling.geojson_creator import process_geojson
from energy_system_modelling_package import random_assignation
from hub.imports.energy_systems_factory import EnergySystemsFactory
from energy_system_modelling_package.energy_system_modelling_factories.energy_system_sizing_factory import \
  EnergySystemsSizingFactory
from energy_system_modelling_package.energy_system_retrofit.energy_system_retrofit_results import consumption_data, \
  cost_data
from costing_package.cost import Cost
from costing_package.constants import *
from hub.exports.exports_factory import ExportsFactory

# Specify the GeoJSON file path
input_files_path = (Path(__file__).parent / 'input_files')
input_files_path.mkdir(parents=True, exist_ok=True)
geojson_file = process_geojson(x=-73.5681295982132, y=45.49218262677643, diff=0.00006)
geojson_file_path = input_files_path / 'output_buildings.geojson'
output_path = (Path(__file__).parent / 'out_files').resolve()
output_path.mkdir(parents=True, exist_ok=True)
energy_plus_output_path = output_path / 'energy_plus_outputs'
energy_plus_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)
sra_output_path = output_path / 'sra_outputs'
sra_output_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
ConstructionFactory('nrcan', city).enrich()
UsageFactory('nrcan', city).enrich()
WeatherFactory('epw', city).enrich()
ExportsFactory('sra', city, sra_output_path).export()
sra_path = (sra_output_path / f'{city.name}_sra.xml').resolve()
subprocess.run(['sra', str(sra_path)])
ResultFactory('sra', city, sra_output_path).enrich()
energy_plus_workflow(city, energy_plus_output_path)
random_assignation.call_random(city.buildings, random_assignation.residential_new_systems_percentage)
EnergySystemsFactory('montreal_future', city).enrich()
for building in city.buildings:
  design_period_demands = MultiObjectiveGeneticAlgorithm(optimization_scenario='energy-consumption_cost').design_period_identification(city.buildings[0])
  heating_demand = design_period_demands[cte.HEATING]['demands']