city_retrofit/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')
    self._load_schedule(idf, 'residential')

  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))
      # create panda
      data = {'WD': [], 'Sat': [], 'Sun': []}
      rows = []
      for j in range(1, 13):
        rows.append(f'{j}am')
      for j in range(1, 13):
        rows.append(f'{j}pm')
      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 = days_schedules[hours_values + 1]
              schedules_day[f'{days_schedules[day_index]}'].append(entry)

        if 'Weekdays' in days_schedules[day_index]:
          data['WD'] = []
          for entry in schedules_day[f'{days_schedules[day_index]}']:
            data['WD'].append(entry)

        elif 'Alldays' in days_schedules[day_index]:
          data['WD'] = []
          data['Sat'] = []
          data['Sun'] = []
          for entry in schedules_day[f'{days_schedules[day_index]}']:
            data['WD'].append(entry)
            data['Sat'].append(entry)
            data['Sun'].append(entry)

        elif 'Weekends' in days_schedules[day_index]:
          # Weekends schedule present so let's re set the values
          data['Sat'] = []
          data['Sun'] = []
          for entry in schedules_day[f'{days_schedules[day_index]}']:
            data['Sat'].append(entry)
            data['Sun'].append(entry)

        elif 'Saturday' in days_schedules[day_index]:
          data['Sat'] = []
          for entry in schedules_day[f'{days_schedules[day_index]}']:
            data['Sat'].append(entry)

        elif 'Sunday' in days_schedules[day_index]:
            data['Sun'] = []
            for entry in schedules_day[f'{days_schedules[day_index]}']:
              data['Sun'].append(entry)
        else:
          continue
      df = pd.DataFrame(data, index=rows)
      for building in self._city.buildings:
        for usage_zone in building.usage_zones:
          if usage_zone.usage == building_usage:
            if usage_zone.schedules is None:
              usage_zone.schedules = {}
            usage_zone.schedules[schedule_type] = df