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):
    file = 'city name: ' + self._city.name + '\n'
    for building in self._city.buildings:
      if cte.MONTH in building.heating_demand.keys():
        heating_results = building.heating_demand[cte.MONTH]
      else:
        heating_results = [None] * 12
      if cte.MONTH in building.cooling_demand.keys():
        cooling_results = building.cooling_demand[cte.MONTH]
      else:
        cooling_results = [None] * 12
      if cte.MONTH in building.lighting_electrical_demand.keys():
        lighting_results = building.lighting_electrical_demand[cte.MONTH]
      else:
        lighting_results = [None] * 12
      if cte.MONTH in building.appliances_electrical_demand.keys():
        appliances_results = building.appliances_electrical_demand[cte.MONTH]
      else:
        appliances_results = [None] * 12
      if cte.MONTH in building.domestic_hot_water_heat_demand.keys():
        dhw_results = building.domestic_hot_water_heat_demand[cte.MONTH]
      else:
        dhw_results = [None] * 12

      if cte.MONTH in building.heating_consumption.keys():
        heating_consumption_results = building.heating_consumption[cte.MONTH]
      else:
        heating_consumption_results = [None] * 12
      if cte.MONTH in building.cooling_consumption.keys():
        cooling_consumption_results = building.cooling_consumption[cte.MONTH]
      else:
        cooling_consumption_results = [None] * 12
      if cte.MONTH in building.domestic_hot_water_consumption.keys():
        dhw_consumption_results = building.domestic_hot_water_consumption[cte.MONTH]
      else:
        dhw_consumption_results = [None] * 12

      if cte.MONTH in building.heating_peak_load.keys():
        heating_peak_load_results = building.heating_peak_load[cte.MONTH]
      else:
        heating_peak_load_results = [None] * 12
      if cte.MONTH in building.cooling_peak_load.keys():
        cooling_peak_load_results = building.cooling_peak_load[cte.MONTH]
      else:
        cooling_peak_load_results = [None] * 12
      heating = 0
      cooling = 0
      for system in building.energy_systems:
        for demand_type in system.demand_types:
          if demand_type == cte.HEATING:
            heating = 1
          if demand_type == cte.COOLING:
            cooling = 1
      if cte.MONTH in building.heating_peak_load.keys() and cte.MONTH in building.cooling_peak_load.keys():
        peak_lighting = 0
        peak_appliances = 0
        thermal_zone = building.thermal_zones_from_internal_zones[0]
        lighting = thermal_zone.lighting
        for schedule in lighting.schedules:
          for value in schedule.values:
            if value * lighting.density * thermal_zone.total_floor_area > peak_lighting:
              peak_lighting = value * lighting.density * thermal_zone.total_floor_area
        appliances = thermal_zone.appliances
        for schedule in appliances.schedules:
          for value in schedule.values:
            if value * appliances.density * thermal_zone.total_floor_area > peak_appliances:
              peak_appliances = value * appliances.density * thermal_zone.total_floor_area

        monthly_electricity_peak = [0.9 * peak_lighting + 0.7 * peak_appliances] * 12
        conditioning_peak = []
        for i, value in enumerate(building.heating_peak_load[cte.MONTH]):
          if cooling * building.cooling_peak_load[cte.MONTH][i] > heating * value:
            conditioning_peak.append(cooling * building.cooling_peak_load[cte.MONTH][i])
          else:
            conditioning_peak.append(heating * value)
          monthly_electricity_peak[i] += 0.8 * conditioning_peak[i]

        electricity_peak_load_results = monthly_electricity_peak
      else:
        electricity_peak_load_results = [None] * 12

      if cte.MONTH in building.onsite_electrical_production.keys():
        monthly_onsite_electrical_production = building.onsite_electrical_production[cte.MONTH]
        onsite_electrical_production = monthly_onsite_electrical_production
      else:
        onsite_electrical_production = [None] * 12

      if cte.MONTH in building.distribution_systems_electrical_consumption.keys():
        extra_electrical_consumption = building.distribution_systems_electrical_consumption[cte.MONTH]
      else:
        extra_electrical_consumption = [None] * 12

      columns_names = [f'{building.name} heating demand J',
                       f'{building.name} cooling demand J',
                       f'{building.name} lighting demand J',
                       f'{building.name} appliances demand J',
                       f'{building.name} domestic hot water demand J',
                       f'{building.name} heating consumption J',
                       f'{building.name} cooling consumption J',
                       f'{building.name} domestic hot water consumption J',
                       f'{building.name} heating peak load W',
                       f'{building.name} cooling peak load W',
                       f'{building.name} electricity peak load W',
                       f'{building.name} onsite electrical production J',
                       f'{building.name} extra electrical consumption J'
                       ]
      print_results = pd.DataFrame([heating_results,
                                   cooling_results,
                                   lighting_results,
                                   appliances_results,
                                   dhw_results,
                                   heating_consumption_results,
                                   cooling_consumption_results,
                                   dhw_consumption_results,
                                   heating_peak_load_results,
                                   cooling_peak_load_results,
                                   electricity_peak_load_results,
                                   onsite_electrical_production,
                                   extra_electrical_consumption]).T
      print_results.columns = columns_names
      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'volume: {building.volume}\n'

      full_path_results = Path(self._path / f'demand_{building.name}.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)