Partial implementation for idf schedule import (doe_idf)

.idea/misc.xml

@@ -1,4 +1,4 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project version="4">
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.9 (libs_EPlus)" project-jdk-type="Python SDK" />
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8 (libs) (2)" project-jdk-type="Python SDK" />
 </project>

city_model_structure/transport/traffic_network.py

@@ -6,8 +6,6 @@ Contributor Milad milad.aghamohamadnia@concordia.ca
 Contributor Guille guille.gutierrezmorote@concordia.ca
 """
 
-from typing import List
-from city_model_structure.attributes.node import Node
 from city_model_structure.network import Network
 
 

exports/exports_factory.py

@@ -4,12 +4,15 @@ SPDX - License - Identifier: LGPL - 3.0 - or -later
 Copyright © 2020 Project Author Guille Gutierrez guillermo.gutierrezmorote@concordia.ca
 """
 
+from pathlib import Path
+from os.path import exists
+
 from exports.formats.stl import Stl
 from exports.formats.obj import Obj
 from exports.formats.energy_ade import EnergyAde
 from exports.formats.simplified_radiosity_algorithm import SimplifiedRadiosityAlgorithm
 from exports.formats.idf import Idf
-from pathlib import Path
+
 
 
 class ExportsFactory:
@@ -67,9 +70,10 @@ class ExportsFactory:
     Export the city to Energy+ idf format
     :return:
     """
-    data_path = (Path(__file__).parent / '../tests/tests_data/').resolve()
+    idf_data_path = (Path(__file__).parent / './formats/idf_files/').resolve()
-    Idf(self._city, self._path, (data_path / f'minimal.idf').resolve(), (data_path / f'energy+.idd').resolve(),
+    # todo: create a get epw file function based on the city
-               (data_path / f'montreal.epw').resolve())
+    weather_path = (Path(__file__).parent / '../data/weather/epw/CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw').resolve()
+    Idf(self._city, self._path, (idf_data_path / f'Minimal.idf'), (idf_data_path / f'Energy+.idd'), weather_path)
 
   @property
   def _sra(self):

exports/formats/idf.py

@@ -14,14 +14,20 @@ class Idf:
   _CONSTRUCTION = 'CONSTRUCTION'
   _MATERIAL = 'MATERIAL'
   _MATERIAL_NOMASS = 'MATERIAL:NOMASS'
-  _ROUGHNESS = "MediumRough"
+  _ROUGHNESS = 'MediumRough'
-  _HOURLY_SCHEDULE = "SCHEDULE:DAY:HOURLY"
+  _HOURLY_SCHEDULE = 'SCHEDULE:DAY:HOURLY'
-  _ZONE = "ZONE"
+  _ZONE = 'ZONE'
-  _LIGHTS = "LIGHTS"
+  _LIGHTS = 'LIGHTS'
-  _PEOPLE = "PEOPLE"
+  _PEOPLE = 'PEOPLE'
-  _ELECTRIC_EQUIPMEN = "ELECTRICEQUIPMENT"
+  _ELECTRIC_EQUIPMENT = 'ELECTRICEQUIPMENT'
-  _INFILTRATION = "ZONEINFILTRATION:DESIGNFLOWRATE"
+  _INFILTRATION = 'ZONEINFILTRATION:DESIGNFLOWRATE'
-  _BUILDING_SURFACE = "BuildingSurfaceDetailed"
+  _BUILDING_SURFACE = 'BuildingSurfaceDetailed'
+  _SCHEDULE_LIMIT = 'SCHEDULETYPELIMITS'
+  _ON_OFF = 'On/Off'
+  _FRACTION = 'Fraction'
+  _ANY_NUMBER = 'Any Number'
+  _CONTINUOUS = 'CONTINUOUS'
+  _DISCRETE = 'DISCRETE'
 
   idf_surfaces = {
     # todo: make an enum for all the surface types
@@ -43,6 +49,11 @@ class Idf:
     self._epw_file_path = str(epw_file_path)
     IDF.setiddname(self._idd_file_path)
     self._idf = IDF(self._idf_file_path, self._epw_file_path)
+    self._idf.newidfobject(self._SCHEDULE_LIMIT, Name=self._ANY_NUMBER)
+    self._idf.newidfobject(self._SCHEDULE_LIMIT, Name=self._FRACTION, Lower_Limit_Value=0.0, Upper_Limit_Value=1.0,
+                           Numeric_Type=self._CONTINUOUS)
+    self._idf.newidfobject(self._SCHEDULE_LIMIT, Name=self._ON_OFF, Lower_Limit_Value=0, Upper_Limit_Value=1,
+                           Numeric_Type=self._DISCRETE)
     self._export()
 
   @staticmethod
@@ -90,13 +101,12 @@ class Idf:
                              Visible_Absorptance=layer.material.visible_absorptance
                              )
 
-  def _add_schedule(self, usage_zone, schedule_type):
+  def _add_schedule(self, usage_zone, schedule_type, limit_name='Any Number'):
     for schedule in self._idf.idfobjects[self._HOURLY_SCHEDULE]:
       if schedule.Name == f'{schedule_type} schedules {usage_zone.usage}':
         return
-    schedule = self._idf.newidfobject(self._HOURLY_SCHEDULE)
+    schedule = self._idf.newidfobject(self._HOURLY_SCHEDULE, Name=f'{schedule_type} schedules {usage_zone.usage}')
-    schedule.Name = f'{schedule_type} schedules {usage_zone.usage}'
+    schedule.Schedule_Type_Limits_Name = limit_name
-    schedule.Schedule_Type_Limits_Name = 'Any Number'
 
     schedule.Hour_1 = usage_zone.schedules[schedule_type]["WD"][0]
     schedule.Hour_2 = usage_zone.schedules[schedule_type]["WD"][1]
@@ -148,7 +158,7 @@ class Idf:
       if zone.Name == usage_zone.id:
         return
     # todo: what does we need to define a zone in energy plus?
-    self._idf.newidfobject(self._ZONE, Name=usage_zone.id)
+    self._idf.newidfobject(self._ZONE, Name=usage_zone.id, Volume=usage_zone.volume)
     self._add_heating_system(usage_zone)
 
   def _add_thermostat(self, usage_zone):
@@ -166,9 +176,9 @@ class Idf:
       if air_system.Zone_Name == usage_zone.id:
         return
     thermostat = self._add_thermostat(usage_zone)
-    # todo: doesn't the air system have name?
     self._idf.newidfobject(self._IDEAL_LOAD_AIR_SYSTEM,
                            Zone_Name=usage_zone.id,
+                           Cooling_Availability_Schedule_Name=f'Refrigeration schedules {usage_zone.usage}',
                            Template_Thermostat_Name=thermostat.Name)
 
   def _add_occupancy(self, usage_zone):
@@ -193,6 +203,8 @@ class Idf:
 
   def _add_infiltration(self, usage_zone):
     for zone in self._idf.idfobjects["ZONE"]:
+      if zone.Name == f'{usage_zone.id}_infiltration':
+        return
     self._idf.newidfobject(self._INFILTRATION,
                            Name=f'{usage_zone.id}_infiltration',
                            Zone_or_ZoneList_Name=usage_zone.id,
@@ -215,14 +227,17 @@ class Idf:
         self._add_schedule(usage_zone, "Infiltration")
         self._add_schedule(usage_zone, "Lights")
         self._add_schedule(usage_zone, "Occupancy")
+        self._add_schedule(usage_zone, "Refrigeration", self._ON_OFF)
+
         self._add_zone(usage_zone)
         self._add_heating_system(usage_zone)
+        # self._add_infiltration(usage_zone)
+        # self._add_occupancy(usage_zone)
       for thermal_zone in building.thermal_zones:
         for thermal_boundary in thermal_zone.bounded:
           self._add_construction(thermal_boundary)
 
       if self._export_type == "Surfaces":
-        print(len(building.surfaces))
         self._add_surfaces(building)
       else:
         self._add_block(building)
@@ -249,10 +264,11 @@ class Idf:
   def _add_surfaces(self, building):
     for thermal_zone in building.thermal_zones:
       for boundary in thermal_zone.bounded:
-        idf_surface = self.idf_surfaces[boundary.surface.type]
+        idf_surface_type = self.idf_surfaces[boundary.surface.type]
         for usage_zone in thermal_zone.usage_zones:
+
           surface = self._idf.newidfobject(self._SURFACE, Name=f'{boundary.surface.name}',
-                                           Surface_Type=idf_surface, Zone_Name=usage_zone.id,
+                                           Surface_Type=idf_surface_type, Zone_Name=usage_zone.id,
                                            Construction_Name=boundary.construction_name)
           coordinates = self._matrix_to_list(boundary.surface.solid_polygon.coordinates)
           surface.setcoords(coordinates)

imports/schedules/DOE_IDF.py

@@ -1,105 +0,0 @@
-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):
-        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())
-        print(idf.keys())  # lists the object types in the idf file
-        print(idf['SCHEDULE:COMPACT'])  # lists all the Output:Variable objects in the idf file
-        Holiday = []
-        Winterdesignday = []
-        Summerdesignday = []
-        Customday1 = []
-        Customday2 = []
-        Weekday = []
-        Weekend = []
-        dayType = []
-        compactKeywords = ['Weekdays', 'Weekends', 'Alldays', 'AllOtherDays', 'Sunday', 'Monday', 'Tuesday', 'Wednesday',
-                           'Thursday', 'Friday', 'Saturday', 'Holiday', 'Winterdesignday', 'Summerdesignday', 'Customday1',
-                           'Customday2']
-        for val in idf['SCHEDULE:COMPACT']:
-            if val[1] == 'BLDG_LIGHT_SCH':
-                count = 0
-                for words in val:
-                    dayType.append(words.title().split('For: ')[-1])
-                    index = []
-                    for count, word_dayType in enumerate(dayType):
-                        if word_dayType in compactKeywords:
-                            index.append(count)
-                index.append(len(dayType))
-                for i in range(len(index) - 1):
-                    numberOfDaySch = list(dayType[index[i] + 1:index[i + 1]])
-                    hourlyValues = list(range(24))
-                    startHour = 0
-                    for num in range(int(len(numberOfDaySch) / 2)):
-                        untilTime = list(map(int, (numberOfDaySch[2 * num].split('Until: ')[-1]).split(":")[0:]))
-                        endHour = int(untilTime[0] + untilTime[1] / 60)
-                        value = float(numberOfDaySch[2 * num + 1])
-                        for hour in range(startHour, endHour):
-                            hourlyValues[hour] = value
-                            print(hour, value)
-                        startHour = endHour
-                    if dayType[index[i]] == 'Weekdays':
-                        Weekday.append(hourlyValues)
-                    elif dayType[index[i]] == 'Weekends':
-                        Weekend.append(hourlyValues)
-                    elif dayType[index[i]] == 'Holiday':
-                        Holiday.append(hourlyValues)
-                    elif dayType[index[i]] == 'Winterdesignday':
-                        Winterdesignday.append(hourlyValues)
-                    elif dayType[index[i]] == 'Summerdesignday':
-                        Summerdesignday.append(hourlyValues)
-                    elif dayType[index[i]] == 'Customday1':
-                        Customday1.append(hourlyValues)
-                    elif dayType[index[i]] == 'Customday2':
-                        Customday2.append(hourlyValues)
-                    else:
-                        print('its none of them')
-        idf_schedules = pd.DataFrame(
-            {'week_day': Weekday,
-             'Weekends': Weekend,
-             'Holiday': Holiday,
-             'Winterdesignday': Winterdesignday,
-             'Summerdesignday': Summerdesignday,
-             'Customday1': Customday1,
-             'Customday2': Customday2,
-             })
-        print(idf_schedules)
-
-        for building in city.buildings:
-          schedules = dict()
-          for usage_zone in building.usage_zones:
-            usage_schedules = idf_schedules
-
-          # 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

@@ -6,6 +6,7 @@ Copyright © 2020 Project Author Guille Gutierrez guillermo.gutierrezmorote@conc
 
 from pathlib import Path
 from imports.schedules.comnet_schedules_parameters import ComnetSchedules
+from imports.schedules.doe_idf import DoeIdf
 
 
 class SchedulesFactory:
@@ -20,6 +21,10 @@ class SchedulesFactory:
   def _comnet(self):
     ComnetSchedules(self._city, self._base_path)
 
+  def _doe_idf(self):
+    print('Idf handler call')
+    DoeIdf(self._city, self._base_path)
+
   def enrich(self):
     """
     Enrich the city with the schedules information

imports/usage/ca_usage_parameters.py

@@ -41,6 +41,7 @@ class CaUsageParameters(HftUsageInterface):
         # just one usage_zone
         for thermal_zone in building.thermal_zones:
           usage_zone = UsageZone()
+          usage_zone.volume = thermal_zone.volume
           self._assign_values(usage_zone, archetype)
           thermal_zone.usage_zones = [usage_zone]
 

requirements.txt

@@ -12,3 +12,5 @@ PyWavefront~=1.3.3
 xlrd~=2.0.1
 openpyxl~=3.0.7
 networkx~=2.5.1
+parseidf~=1.0.0
+ply~=3.11

tests/tests_data/minimal.idf

@@ -13,7 +13,7 @@
 ! HVAC: None.
 !
 
-  Version,9.4;
+  Version,9.5;
 
   Timestep,4;
 
@@ -148,4 +148,3 @@
 
   Output:Table:SummaryReports,
     AllSummary;              !- Report 1 Name
-