Partial implementation for idf schedule import (doe_idf)
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imports/schedules/doe_idf.py
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imports/schedules/doe_idf.py
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"""
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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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This is a import factory to add Idf 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._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 f:
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idf = parseidf.parse(f.read())
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self._load_schedule(idf, 'small_office')
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def _load_schedule(self, idf, building_usage):
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holiday = []
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winter_design_day = []
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summer_design_day = []
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custom_day_1 = []
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custom_day_2 = []
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weekday = []
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weekend = []
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day_types = []
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schedules_day = {'None':[]}
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compact_keywords = ['Weekdays', 'Weekends', 'Alldays', 'AllOtherDays', 'Sunday', 'Monday', 'Tuesday',
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'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Holiday', 'Winterdesignday',
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'Summerdesignday', 'Customday1', 'Customday2']
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j = 0
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for compact_schedule in idf[self._SCHEDULE_COMPACT_TYPE]:
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j = j +1
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if 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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schedule_type = 'Unknown'
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# todo: check this piece of code logic
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days_index = []
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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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day_types.append(element_title)
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days_index.append(len(day_types))
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print(day_types)
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print(days_index)
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'''
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for count, word_day_type in enumerate(day_type):
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if word_day_type in compact_keywords:
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index.append(count)
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index.append(len(day_type))
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'''
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for i, day_index in enumerate(days_index):
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if day_index == len(day_types):
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break
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schedules_day[f'{day_types[day_index]}'] = []
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print(f'{day_types[day_index]}')
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for hours_values in range(day_index+1, days_index[i + 1]-1, 2):
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print(f'{day_types[hours_values]}# {day_types[hours_values+1]} ')
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if j == 2:
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return
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'''
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for i in range(len(index) - 1):
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number_of_day_schedule = list(day_types[index[i] + 1:index[i + 1]])
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hourly_values = list(range(24))
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start_hour = 0
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for num in range(int(len(number_of_day_schedule) / 2)):
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until_time = list(map(int, (number_of_day_schedule[2*num].split('Until: ')[-1]).split(":")[0:]))
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end_hour = int(until_time[0] + until_time[1] / 60)
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value = float(number_of_day_schedule[2 * num + 1])
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for hour in range(start_hour, end_hour):
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hourly_values[hour] = value
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start_hour = end_hour
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print(f'{compact_schedule}')
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print(f'{building_usage} {schedule_type} {hourly_values}')
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if day_type[index[i]] == 'Weekdays':
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weekday.append(hourly_values)
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elif day_type[index[i]] == 'Weekends':
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weekend.append(hourly_values)
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elif day_type[index[i]] == 'Holiday':
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holiday.append(hourly_values)
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elif day_type[index[i]] == 'Winterdesignday':
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winter_design_day.append(hourly_values)
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elif day_type[index[i]] == 'Summerdesignday':
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summer_design_day.append(hourly_values)
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elif day_type[index[i]] == 'Customday1':
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custom_day_1.append(hourly_values)
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elif day_type[index[i]] == 'Customday2':
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custom_day_2.append(hourly_values)
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else:
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raise ValueError('Unknown schedule day type')
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'''
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idf_schedules = pd.DataFrame(
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{'week_day': weekday,
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'Weekends': weekend,
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'Holiday': holiday,
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'Winterdesignday': winter_design_day,
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'Summerdesignday': summer_design_day,
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'Customday1': custom_day_1,
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'Customday2': custom_day_2,
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})
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print(idf_schedules)
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'''
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for building in city.buildings:
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schedules = dict()
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for usage_zone in building.usage_zones:
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usage_schedules = idf_schedules
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# todo: should we save the data type? How?
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number_of_schedule_types = 5
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schedules_per_schedule_type = 6
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idf_day_types = dict({'week_day': 0, 'Weekends': 1, 'Holiday': 2, 'Winterdesignday': 3, 'Summerdesignday':
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4, 'Customday1': 5, 'Customday2': 6})
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for schedule_types in range(0, number_of_schedule_types):
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data = pd.DataFrame()
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columns_names = []
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name = ''
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for schedule_day in range(0, len(idf_schedules)):
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row_cells = usage_schedules.iloc[schedules_per_schedule_type*schedule_types + schedule_day]
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if schedule_day == idf_day_types['week_day']:
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name = row_cells[0]
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columns_names.append(row_cells[2])
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data1 = row_cells[schedules_per_schedule_type:]
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data = pd.concat([data, data1], axis=1)
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data.columns = columns_names
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schedules[name] = data
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usage_zone.schedules = schedules
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'''
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