import sys
assert(sys.version_info.major>2)
import gridlabd
# construct the command line (gridlabd hasn't started yet)
gridlabd.command('example.glm')
gridlabd.command('-D')
gridlabd.command('suppress_repeat_messages=FALSE')
#gridlabd.command('--debug')
# start gridlabd and wait for it to complete
gridlabd.start('wait')
# send the final model state to a file
gridlabd.save('done.json');
import requests
print('Requests imported')
###USER input
ind = 1
ip_address = '192.168.1.67'
#write global file with settings from csv file: HH_global.py
df_settings = pandas.read_csv('settings_TESS.csv',
index_col=[0],
parse_dates=['start_time', 'end_time'])
import global_functions
global_functions.write_global(df_settings.loc[ind], ind, ip_address)
#Base case
if ind == 0:
#Rewrites glm file: start and end date, tmy, outputfile
import glm_functions_sparse
glm_functions_sparse.rewrite_glmfile()
#This a newly randomly generated model
gridlabd.command('model.glm')
gridlabd.start('wait')
gridlabd.save('model_bc.glm')
#Test cases
else:
#This uses the saved model of the first basecase run
#import glm_functions_sparse
#glm_functions_sparse.modify_glmfile() #creates model_ts from model_bc (include module gridlabd_functions) - make sure it's identical!
gridlabd.command('model_ts.glm')
gridlabd.start('wait')