115 lines
4.4 KiB
Python
115 lines
4.4 KiB
Python
"""
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MyClass module
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SPDX - License - Identifier: LGPL - 3.0 - or -later
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Copyright © 2020 Project
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"""
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import pandas as pd
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import parseidf
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class DoeIdf:
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"""
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Idf factory to import schedules into the data model
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"""
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idf_schedule_to_commet_schedule = {'BLDG_LIGHT_SCH': 'Lights',
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'BLDG_OCC_SCH_wo_SB': 'Occupancy',
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'BLDG_EQUIP_SCH': 'Equipment',
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'ACTIVITY_SCH': 'Activity',
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'INFIL_QUARTER_ON_SCH': 'Infiltration'}
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_SCHEDULE_COMPACT_TYPE = 'SCHEDULE:COMPACT'
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_SCHEDULE_TYPE_NAME = 1
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def __init__(self, city, base_path):
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self._hours = []
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panda_hours = pd.timedelta_range(0, periods=24, freq='H')
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for _, hour in enumerate(panda_hours):
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self._hours.append(str(hour).replace('0 days ', '').replace(':00:00', ':00'))
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self._city = city
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self._idf_schedules_path = base_path / 'ASHRAE901_OfficeSmall_STD2019_Buffalo.idf'
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with open(self._idf_schedules_path, 'r') as file:
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idf = parseidf.parse(file.read())
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self._load_schedule(idf, 'small_office')
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self._load_schedule(idf, 'residential')
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def _load_schedule(self, idf, building_usage):
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schedules_day = {}
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for compact_schedule in idf[self._SCHEDULE_COMPACT_TYPE]:
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if compact_schedule[self._SCHEDULE_TYPE_NAME] in self.idf_schedule_to_commet_schedule:
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schedule_type = self.idf_schedule_to_commet_schedule[compact_schedule[self._SCHEDULE_TYPE_NAME]]
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else:
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continue
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days_index = []
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days_schedules = []
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for position, elements in enumerate(compact_schedule):
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element_title = elements.title().replace('For: ', '')
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if elements.title() != element_title:
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days_index.append(position)
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# store a cleaned version of the compact schedule
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days_schedules.append(element_title)
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days_index.append(len(days_schedules))
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# create panda
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data = {'WD': [], 'Sat': [], 'Sun': []}
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rows = []
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for j in range(1, 13):
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rows.append(f'{j}am')
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for j in range(1, 13):
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rows.append(f'{j}pm')
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for i, day_index in enumerate(days_index):
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if day_index == len(days_schedules):
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break
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schedules_day[f'{days_schedules[day_index]}'] = []
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hour_index = 0
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for hours_values in range(day_index + 1, days_index[i + 1] - 1, 2):
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# Create 24h sequence
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for index, hour in enumerate(self._hours[hour_index:]):
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hour_formatted = days_schedules[hours_values].replace("Until: ", "")
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if len(hour_formatted) == 4:
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hour_formatted = f'0{hour_formatted}'
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if hour == hour_formatted:
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hour_index += index
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break
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entry = days_schedules[hours_values + 1]
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schedules_day[f'{days_schedules[day_index]}'].append(entry)
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if 'Weekdays' in days_schedules[day_index]:
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data['WD'] = []
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for entry in schedules_day[f'{days_schedules[day_index]}']:
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data['WD'].append(entry)
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elif 'Alldays' in days_schedules[day_index]:
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data['WD'] = []
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data['Sat'] = []
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data['Sun'] = []
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for entry in schedules_day[f'{days_schedules[day_index]}']:
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data['WD'].append(entry)
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data['Sat'].append(entry)
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data['Sun'].append(entry)
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elif 'Weekends' in days_schedules[day_index]:
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# Weekends schedule present so let's re set the values
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data['Sat'] = []
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data['Sun'] = []
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for entry in schedules_day[f'{days_schedules[day_index]}']:
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data['Sat'].append(entry)
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data['Sun'].append(entry)
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elif 'Saturday' in days_schedules[day_index]:
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data['Sat'] = []
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for entry in schedules_day[f'{days_schedules[day_index]}']:
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data['Sat'].append(entry)
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elif 'Sunday' in days_schedules[day_index]:
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data['Sun'] = []
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for entry in schedules_day[f'{days_schedules[day_index]}']:
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data['Sun'].append(entry)
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else:
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continue
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df = pd.DataFrame(data, index=rows)
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for building in self._city.buildings:
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for usage_zone in building.usage_zones:
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if usage_zone.usage == building_usage:
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if usage_zone.schedules is None:
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usage_zone.schedules = {}
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usage_zone.schedules[schedule_type] = df
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