Complete idf schedule import (doe_idf)

exports/formats/idf.py

@@ -105,6 +105,9 @@ class Idf:
     for schedule in self._idf.idfobjects[self._HOURLY_SCHEDULE]:
       if schedule.Name == f'{schedule_type} schedules {usage_zone.usage}':
         return
+    if usage_zone.schedules is None or schedule_type not in usage_zone.schedules:
+      # there are no schedule for this type
+      return
     schedule = self._idf.newidfobject(self._HOURLY_SCHEDULE, Name=f'{schedule_type} schedules {usage_zone.usage}')
     schedule.Schedule_Type_Limits_Name = limit_name
 

imports/schedules/doe_idf.py

@@ -29,7 +29,7 @@ class DoeIdf:
     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 = {}
@@ -47,7 +47,13 @@ class DoeIdf:
         # 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
@@ -63,75 +69,47 @@ class DoeIdf:
               hour_index += index
               break
             else:
-              entry = (hour, days_schedules[hours_values + 1])
+              entry = 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')
+        if 'Weekdays' in days_schedules[day_index]:
+          data['WD'] = []
+          for entry in schedules_day[f'{days_schedules[day_index]}']:
+            data['WD'].append(entry)
 
-  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
+        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
 
-      # 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
-      '''

imports/schedules_factory.py

@@ -22,7 +22,6 @@ class SchedulesFactory:
     ComnetSchedules(self._city, self._base_path)
 
   def _doe_idf(self):
-    print('Idf handler call')
     DoeIdf(self._city, self._base_path)
 
   def enrich(self):

non_functional_tests/test_schedules_factory.py

@@ -44,9 +44,10 @@ class TestSchedulesFactory(TestCase):
     for building in city.buildings:
       self.assertIsNot(len(building.usage_zones), 0, 'no building usage_zones defined')
       for usage_zone in building.usage_zones:
+        print(usage_zone.schedules)
         self.assertTrue(usage_zone.schedules)
 
-  def test_deo_idf_archetypes(self):
+  def test_doe_idf_archetypes(self):
     file = (self._example_path / 'C40_Final.gml').resolve()
     city = self._get_citygml(file)
     occupancy_handler = 'doe_idf'