summer_course_2024/imports/schedules/doe_idf.py

"""
MyClass module
SPDX - License - Identifier: LGPL - 3.0 - or -later
Copyright © 2020 Project
"""
import pandas as pd
import parseidf


class DoeIdf:
  """
  This is a import factory to add Idf schedules into the data model
  """
  idf_schedule_to_commet_schedule = {'BLDG_LIGHT_SCH': 'Lights',
                                     'BLDG_OCC_SCH_wo_SB': 'Occupancy',
                                     'BLDG_EQUIP_SCH': 'Equipment',
                                     'ACTIVITY_SCH': 'Activity',
                                     'INFIL_QUARTER_ON_SCH': 'Infiltration'}

  _SCHEDULE_COMPACT_TYPE = 'SCHEDULE:COMPACT'
  _SCHEDULE_TYPE_NAME = 1

  def __init__(self, city, base_path):
    self._hours = []
    panda_hours = pd.timedelta_range(0, periods=24, freq='H')
    for i, hour in enumerate(panda_hours):
      self._hours.append(str(hour).replace('0 days ', '').replace(':00:00', ':00'))
    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())
    self._load_schedule(idf, 'small_office')

  def _load_schedule(self, idf, building_usage):
    schedules_day = {}
    for compact_schedule in idf[self._SCHEDULE_COMPACT_TYPE]:
      if compact_schedule[self._SCHEDULE_TYPE_NAME] in self.idf_schedule_to_commet_schedule:
        schedule_type = self.idf_schedule_to_commet_schedule[compact_schedule[self._SCHEDULE_TYPE_NAME]]
      else:
        continue
      days_index = []
      days_schedules = []
      for position, elements in enumerate(compact_schedule):
        element_title = elements.title().replace('For: ', '')
        if elements.title() != element_title:
          days_index.append(position)
        # store a cleaned version of the compact schedule
        days_schedules.append(element_title)
      days_index.append(len(days_schedules))

      for i, day_index in enumerate(days_index):
        if day_index == len(days_schedules):
          break
        schedules_day[f'{days_schedules[day_index]}'] = []
        hour_index = 0
        for hours_values in range(day_index + 1, days_index[i + 1] - 1, 2):
          # Create 24h sequence
          for index, hour in enumerate(self._hours[hour_index:]):
            hour_formatted = days_schedules[hours_values].replace("Until: ", "")
            if len(hour_formatted) == 4:
              hour_formatted = f'0{hour_formatted}'
            if hour == hour_formatted:
              hour_index += index
              break
            else:
              entry = (hour, days_schedules[hours_values + 1])
              schedules_day[f'{days_schedules[day_index]}'].append(entry)

        print(schedules_day[f'{days_schedules[day_index]}'])
      '''
      for i in range(len(index) - 1):
          number_of_day_schedule = list(day_types[index[i] + 1:index[i + 1]])
          hourly_values = list(range(24))
          start_hour = 0
          for num in range(int(len(number_of_day_schedule) / 2)):
              until_time = list(map(int, (number_of_day_schedule[2*num].split('Until: ')[-1]).split(":")[0:]))
              end_hour = int(until_time[0] + until_time[1] / 60)
              value = float(number_of_day_schedule[2 * num + 1])
              for hour in range(start_hour, end_hour):
                  hourly_values[hour] = value
              start_hour = end_hour
              print(f'{compact_schedule}')
              print(f'{building_usage} {schedule_type} {hourly_values}')
          if day_type[index[i]] == 'Weekdays':
              weekday.append(hourly_values)
          elif day_type[index[i]] == 'Weekends':
              weekend.append(hourly_values)
          elif day_type[index[i]] == 'Holiday':
              holiday.append(hourly_values)
          elif day_type[index[i]] == 'Winterdesignday':
              winter_design_day.append(hourly_values)
          elif day_type[index[i]] == 'Summerdesignday':
              summer_design_day.append(hourly_values)
          elif day_type[index[i]] == 'Customday1':
              custom_day_1.append(hourly_values)
          elif day_type[index[i]] == 'Customday2':
              custom_day_2.append(hourly_values)
          else:
              raise ValueError('Unknown schedule day type')

  idf_schedules = pd.DataFrame(
      {'week_day': schedules_day['Weekdays'],
       'Weekends': schedules_day['Weekends'],
       'Holiday': schedules_day['Holiday'],
       'Winterdesignday': schedules_day['Winterdesignday'],
       'Summerdesignday': schedules_day['Summerdesignday'],
       'Customday1': schedules_day['Customday1'],
       'Customday2': schedules_day['Customday2']
       })
  print(idf_schedules)
'''
    '''
    for building in city.buildings:
      schedules = dict()
      for usage_zone in building.usage_zones:
        usage_schedules = idf_schedules

      # todo: should we save the data type? How?
        number_of_schedule_types = 5
        schedules_per_schedule_type = 6
        idf_day_types = dict({'week_day': 0, 'Weekends': 1, 'Holiday': 2, 'Winterdesignday': 3, 'Summerdesignday': 
        4, 'Customday1': 5, 'Customday2': 6})
        for schedule_types in range(0, number_of_schedule_types):
          data = pd.DataFrame()
          columns_names = []
          name = ''
          for schedule_day in range(0, len(idf_schedules)):
            row_cells = usage_schedules.iloc[schedules_per_schedule_type*schedule_types + schedule_day]
            if schedule_day == idf_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
      '''