from pymodelica import compile_fmu

from pyfmi import load_fmu

import numpy as np

# Model files

model_name = 'TestSys.HVACv6a_3room'

mo_file1 = 'C:\\Users\\James\\OneDrive\\Documents\\Berkeley\\HVAC\\Modelica\\Test\\TestSys\\TestSys'

mo_file2 = 'C:\\Users\\James\\Desktop\\Buildings 4.0.0'

mo_files = mo_file1 + ',' + mo_file2

# File path

filePath = 'C:\\Users\\Public\\Documents\\JModelica.org\\'

fileName = (model_name).replace('.','_')

# Compile FMU, can skip if already compiled before

# fmu = compile_fmu(model_name,mo_files)

# Load compiled FMU

fmu = fileName + '.fmu'

# Load weather_file

w_filePath = 'L:\\HVAC_ModelicaModel_Data\\NOAA_WeatherData'

w_fileName = 'SF2010_TemperatureData.csv' #'Boston2010_TemperatureData.csv'

weather_file = w_filePath + '\\' + w_fileName

# # Load load_file: This is the room heat load data

# l_filePath = 'L:\\HVAC_ModelicaModel_Data\\Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States'

# l_fileName = 'SF_LargeOfficeNew2004.csv' # 'SF_SmallOfficeNew2004.csv' # 'SF_PrimarySchoolNew2004.csv'

# load_file = l_filePath + '\\' + l_fileName

# Load multiple load_files:

l_filePath = 'L:\\HVAC_ModelicaModel_Data\\Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States'

l_fileNames = ['SF_LargeOfficeNew2004.csv','SF_LargeOfficeNew2004.csv','SF_LargeOfficeNew2004.csv']#['SF_SmallOfficeNew2004.csv','SF_LargeOfficeNew2004.csv','SF_PrimarySchoolNew2004.csv']

load_files = []

for l_fileName in l_fileNames:

load_file = l_filePath + '\\' + l_fileName

load_files.append(load_file)

# Load selected variables

s_filePath = 'C:\\Users\\James\\OneDrive\\Documents\\Berkeley\\HVAC\\Modelica\\Test'

s_fileName = 'selected_variable_list_for_HVACv6a_3room' # 'selected_variable_list'

selected_variable_list = s_filePath + '\\' + s_fileName

# Set parameter

# param = 'TemperatureSetpoint.k'

# param_range = np.linspace(273.15+20,273.15+30,6)

# Run time

start_time = 0.

final_time = 86400.

data_points = 4320#8640

# run simulations

# for param_val in param_range:

# model = load_fmu(fmu) # if fmu already compiled, can use model = load_fmu(fileName+'.fmu')

# model.set(param,param_val)

# opts = model.simulate_options()

# opts['ncp'] = data_points # Changing the number of communication points

# res = model.simulate(start_time = start_time, final_time = final_time, options=opts)

#

# # export selected variables

# variables = SelectedVars(filePath+fileName + '_selected_variables')

# ExportVars(res,variables,filePath+fileName + '_' + str(param) + '_' + str(param_val))

# # Run for single room models:

# # Run simulations over days in dataset

# days = WeatherDataShape(weather_file)[1] # number of days in the dataset

# days = np.arange(1,days) # list(range(1,days)) # list of days, days start from 1 (NOT 0) to end

# # hldays = check_weekday(days,max_d=2,weekends=[0,1])

#

# # Using a list to exclude non-workdays for heatload data

# non_workdays_file = r'L:\HVAC_ModelicaModel_Data\Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States\SF_smalloffice_weekends+holidays.csv'

# non_workdays = np.loadtxt(non_workdays_file)

# hldays = check_workday(days,non_workdays,max_d=2)

# # hldays = days

#

# for i,day in enumerate(days):

# model = load_fmu(fmu) # if fmu already compiled, can use model = load_fmu(fileName+'.fmu')

# LoadWeatherData(model,weather_file,day = day) # set weather data

# LoadHeatLoadData(model,load_file,day = hldays[i]) # set room heat load data

# opts = model.simulate_options()

# opts['ncp'] = data_points # Changing the number of communication points

# res = model.simulate(start_time = start_time, final_time = final_time, options=opts)

#

# # export selected variables

# exportPath = 'L:\\HVAC_ModelicaModel_Data\\160_HVACv4a_Boston+LargeOffice_Workday\\'

# variables = SelectedVars(selected_variable_list)

# ExportVars(res,variables,exportPath+fileName + WeatherDataDate(weather_file,day) + '_' + str(hldays[i]))

# Run for multiroom models:

# Run simulations over days in dataset

max_days = WeatherDataShape(weather_file)[1] # number of days in the dataset

days = np.arange(1,max_days) # list(range(1,days)) # list of days, days start from 1 (NOT 0) to end

# Using a list to exclude non-workdays for heatload data

non_workdays_file = r'L:\HVAC_ModelicaModel_Data\Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States\SF_smalloffice_weekends+holidays.csv'

non_workdays = np.loadtxt(non_workdays_file)

hlparam_names = ['RoomLoadData','RoomLoadData2','RoomLoadData3']

n_rooms = len(hlparam_names)

hldays_set = []

for i in range(n_rooms):

# hldays = days

# hldays = check_workday(days,non_workdays,max_d=2)

hldays = neighbor_days2(days,non_workdays,max_d=2,max_days = max_days)

hldays_set.append(hldays)

for i,day in enumerate(days):

model = load_fmu(fmu) # if fmu already compiled, can use model = load_fmu(fileName+'.fmu')

# model.set('_log_level', 6)

LoadWeatherData(model,weather_file,day = day) # set weather data

# LoadHeatLoadData(model,load_file,day = hldays[i]) # set room heat load data

multi_hldays = [hldays_set[j][i] for j in range(n_rooms)] # set multiple room heat load data

LoadMultiHeatLoadData(model,load_files,days = multi_hldays,param_names = hlparam_names,scale_factor=0.7)

opts = model.simulate_options()

opts['ncp'] = data_points # Changing the number of communication points

res = model.simulate(start_time = start_time, final_time = final_time, options=opts)

# export selected variables

exportPath = 'L:\\HVAC_ModelicaModel_Data\\230_HVACv6a_3room_SF+LargeOffice_Workday\\'

variables = SelectedVars(selected_variable_list)

ExportVars(res,variables,exportPath+fileName + WeatherDataDate(weather_file,day) + '_' + str(multi_hldays))

## Functions

'''

# Read in selected variables.

# Input: fileName, Output: list of variable names

'''

def SelectedVars(fileName):

return(variables)

'''

# Export selected variables.

# Input: res(model.simulation result), variables(list of variable names), fileName

# Saves selected variables' data to csv file

'''

def ExportVars(res,variables,fileName):

print(fileName + '.csv' + ' has been saved.\n')

'''

This script is used to modify the values of TimeTable component, WeatherData, in HVACv3a_weather.mo

For CombiTimeTable doesn't work in this model for some reason(don't ask me why).

# Changes weatherData in the model

'''

def LoadWeatherData(model,weather_file,day = 123): # day starts from 1 NOT 0

print('Weather data set')

'''

Input: weather csv file(from NOAA_Data_export.py

Output: weather data shape

'''

def WeatherDataShape(weather_file):

weatherData = np.loadtxt(open(weather_file, "rb"), delimiter=",", skiprows=1,dtype = np.object)

return(weatherData.shape)

'''

Input: weather csv file(from NOAA_Data_export.py, day(integer)

Output: corresponding date of day

'''

def WeatherDataDate(weather_file,day):

weatherData = np.loadtxt(open(weather_file, "rb"), delimiter=",", dtype = np.object)

date = weatherData[0,day]

return(date)

'''

This script is used to modify the values of TimeTable component, RoomLoadData, in HVACv3a_weather_load.mo

For CombiTimeTable doesn't work in this model for some reason(don't ask me why).

# Changes loadData in the model

'''

def LoadHeatLoadData(model,load_file,day = 123): # day starts from 1 NOT 0

print('Heat load data set')

'''

This script is used to modify the values of TimeTable component,

RoomLoadData, RoomLoadData2, and RoomLoadData3, in HVACv6_3room.mo

length of load_files,days, and RoomLoadData parameters have to be the same

For CombiTimeTable doesn't work in this model for some reason(don't ask me why).

# Changes loadData in the model

'''

def LoadMultiHeatLoadData(model,load_files,days = [1,2,3],param_names = ['RoomLoadData','RoomLoadData2','RoomLoadData3'],scale_factor = 0.3): # day starts from 1 NOT 0

print('Heat load data for {} set'.format(param_name))

'''

This function is to make sure the days are all weekdays

Input:

- wdays: given weather days, np.array

- max_d: if the corresponding wday isn't a weekday, then a random day will be assigned

to for the heat load day within a distance of max_d

- weekends: a list of integers, defining the weekends.

Output:

- hldays: an array of heat load days, which has no weekend days

'''

def check_weekday(wdays,max_d=2,weekends=[0,6]):

return(hldays)

'''

This function is to make sure the days are not weekends nor holidays by checking

the non_workdays list

Input:

- wdays: given weather days, np.array

- max_d: if the corresponding wday isn't a weekday, then a random day will be assigned

to for the heat load day within a distance of max_d

- non_workdays: a list of integers, defining the weekends and holidays.

Output:

- hldays: an array of heat load days, which has no weekends nor holidays

'''

def check_workday(wdays,non_workdays,max_d=2):

return(hldays)

'''

Use neighboring days instead of random days for heatload

This function is to make sure the days are all weekdays

Input:

- wdays: given weather days

- max_d: if the corresponding wday isn't a weekday, then a random day will be assigned

to for the heat load day within a distance of max_d

- weekends: a list of integers, defining the weekends.

Output:

- hldays: an array of heat load days

'''

def neighbor_days(wdays,max_d,max_days = 360,weekends=[0,1]):

return(hldays)

'''

Use neighboring days instead of random days for heatload

This function is to make sure the days are all workdays

Similar to function check_workday(), but improved by not using the shape of the input array

Input:

- wdays: given weather days

- max_d: if the corresponding wday isn't a weekday, then a random day will be assigned

to for the heat load day within a distance of max_d

- non_workdays: a list of integers, defining the weekends and holidays.

- max_days: the maximum days, used for modulo operation, e.g. 360->1

Output:

- hldays: an array of heat load days

'''

def neighbor_days2(wdays,non_workdays,max_d,max_days = 360):

return(hldays)