import pandas as pd
from imports.schedules.helpers.schedules_helper import SchedulesHelper
import parseidf


class IdfParser:
    _OCCUPANCY_SCHEDULE= ("BLDG_OCC_SCH_wo_SB","Occupancy")
    _Activity_Schedule= "ACTIVITY_SCH"
    _Electrical_Equipent_Schedule= "BLDG_EQUIP_SCH"
    _Lighting_Schedule="BLDG_LIGHT_SCH"
    _Infiltration_Ventilation_Schedule="INFIL_QUARTER_ON_SCH"

  def __init__(self, city, base_path, type):
    self._city = city
    self._idf_schedules_path = base_path / 'ASHRAE901_OfficeSmall_STD2019_Buffalo.idf'
    with open(self._idf_schedules_path, 'r') as f:
        idf = parseidf.parse(f.read())

    for building in city.buildings:
      schedules = dict()
      for usage_zone in building.usage_zones:
        usage_schedules = pd.Datafram(idf['SCHEDULE:COMPACT'])

        Small_Office_Occupancy = []
        Small_Office_OccupancyActivity = []
        Small_Office_ElectricalEquipment = []
        Small_Office_Lighting = []
        Small_Office_Infiltration = []

        for i in usage_schedules:
            if i[1] == self._Occupancy_Schedule:
                return Small_Office_Occupancy.append(i)
            elif i[1] == 'ACTIVITY_SCH':
                Small_Office_OccupancyActivity.append(i)
            elif i[1] == 'BLDG_EQUIP_SCH':
                Small_Office_ElectricalEquipment.append(i)
            elif i[1] == 'BLDG_LIGHT_SCH':
                Small_Office_Lighting.append(i)
            elif i[1] == 'INFIL_QUARTER_ON_SCH':
                Small_Office_Infiltration.append(i)
            else:
                print("The schedule name is not standard")


'''
      # todo: should we save the data type? How?
        number_of_schedule_types = 13
        schedules_per_schedule_type = 3
        day_types = dict({'week_day': 0, 'saturday': 1, 'sunday': 2})
        for schedule_types in range(0, number_of_schedule_types):
          data = pd.DataFrame()
          columns_names = []
          name = ''
          for schedule_day in range(0, schedules_per_schedule_type):
            row_cells = usage_schedules.iloc[schedules_per_schedule_type*schedule_types + schedule_day]
            if schedule_day == day_types['week_day']:
              name = row_cells[0]
            columns_names.append(row_cells[2])
            data1 = row_cells[schedules_per_schedule_type:]
            data = pd.concat([data, data1],  axis=1)
          data.columns = columns_names
          schedules[name] = data
        usage_zone.schedules = schedules
'''