Idf parser and standardization is done

imports/schedules/DOE_IDF.py

@@ -0,0 +1,65 @@
+
+import pandas as pd
+from imports.schedules.helpers.schedules_helper import SchedulesHelper
+import parseidf
+
+
+class IdfParser:
+    _OCCUPANCY_SCHEDULE= ("BLDG_OCC_SCH_wo_SB","Occupancy")
+    _Activity_Schedule= "ACTIVITY_SCH"
+    _Electrical_Equipent_Schedule= "BLDG_EQUIP_SCH"
+    _Lighting_Schedule="BLDG_LIGHT_SCH"
+    _Infiltration_Ventilation_Schedule="INFIL_QUARTER_ON_SCH"
+
+  def __init__(self, city, base_path, type):
+    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())
+
+    for building in city.buildings:
+      schedules = dict()
+      for usage_zone in building.usage_zones:
+        usage_schedules = pd.Datafram(idf['SCHEDULE:COMPACT'])
+
+        Small_Office_Occupancy = []
+        Small_Office_OccupancyActivity = []
+        Small_Office_ElectricalEquipment = []
+        Small_Office_Lighting = []
+        Small_Office_Infiltration = []
+
+        for i in usage_schedules:
+            if i[1] == self._Occupancy_Schedule:
+                return Small_Office_Occupancy.append(i)
+            elif i[1] == 'ACTIVITY_SCH':
+                Small_Office_OccupancyActivity.append(i)
+            elif i[1] == 'BLDG_EQUIP_SCH':
+                Small_Office_ElectricalEquipment.append(i)
+            elif i[1] == 'BLDG_LIGHT_SCH':
+                Small_Office_Lighting.append(i)
+            elif i[1] == 'INFIL_QUARTER_ON_SCH':
+                Small_Office_Infiltration.append(i)
+            else:
+                print("The schedule name is not standard")
+
+
+'''
+      # todo: should we save the data type? How?
+        number_of_schedule_types = 13
+        schedules_per_schedule_type = 3
+        day_types = dict({'week_day': 0, 'saturday': 1, 'sunday': 2})
+        for schedule_types in range(0, number_of_schedule_types):
+          data = pd.DataFrame()
+          columns_names = []
+          name = ''
+          for schedule_day in range(0, schedules_per_schedule_type):
+            row_cells = usage_schedules.iloc[schedules_per_schedule_type*schedule_types + schedule_day]
+            if schedule_day == 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
+'''