backup_4_updated_ct_script.py

from subprocess import call
import json
import datetime
#from datetime import datetime,timedelta
import time
import os
from matplotlib import pyplot as plt

openaps_rate = []
wrapper_rate = []
running_temp = []

track_increase = {"iteration": 0, "num_of_increase":0}
track_decrease = {"iteration": 0, "num_of_decrease":0}

gt_target_visit_stat = 0
lt_target_rising_visit_stat = 0
lt_target_falling_visit_stat = 0
init_ebg_pointer = 0

fault_occurrence = 0

#Input to the algo_bw.js. algo_bw.js format all the info and send to glucosym server. An algorithm is running in glucosym server that calculated next glucose and send the value back.
algo_input_list = {"index":0,"BGTarget":95,"sens":45,"deltat_v":20,"dia":4,"dt":5.0,"time":6000,"bioavail":6.0,"Vg":253.0,"IRss":1.3,"events":{"bolus":[{ "amt": 0.0, "start":0}],"basal":[{ "amt":0, "start":0,"length":0}],"carb":[{"amt":0.0,"start":0,"length":0},{"amt":0.0,"start":0,"length":0}]}}

#write the algo_input_list to a file named algo_input.json so that algo_bw.js can read the input from that file
with open("../glucosym/closed_loop_algorithm_samples/algo_input.json", "w") as write_algo_input_init:
	json.dump(algo_input_list, write_algo_input_init, indent=4)
	write_algo_input_init.close()


suggested_data_to_dump = {}
list_suggested_data_to_dump = []

iteration_num = 140

#record the time 5 minutes ago, we need this time to attach with the recent glucose value
#time_5_minutes_back = ((time.time())*1000)-3000


for _ in range(iteration_num):
	
	with open("../glucosym/closed_loop_algorithm_samples/algo_input.json") as update_algo_input:
		loaded_algo_input = json.load(update_algo_input)
		update_algo_input.close()
		
	loaded_algo_input_copy = loaded_algo_input.copy()
	loaded_algo_input_copy['index'] = _
	
	#print(loaded_algo_input_copy)
	
	with open("monitor/glucose.json") as f:
		data = json.load(f)
		f.close()

	
	
	
	data_to_prepend = data[0].copy()

	
	read_glucose_from_glucosym = open("../glucosym/closed_loop_algorithm_samples/glucose_output_algo_bw.txt", "r")
	loaded_glucose = read_glucose_from_glucosym.read()
	
	
	data_to_prepend["glucose"] = loaded_glucose
	
	data_to_prepend["date"] = int(time.time())*1000

	
	data.insert(0, data_to_prepend)
	

	with open('monitor/glucose.json', 'w') as outfile:
		json.dump(data, outfile, indent=4)
		outfile.close()
	

	#current_timestamp = datetime.datetime.fromtimestamp(time.time()).strftime('%Y-%m-%dT%H:%M:%S-07:00')
	#with open('monitor/clock.json','w') as update_clock:
	#	json.dump(current_timestamp, update_clock)
	
	##For the very first time get the time of 5 minutes ago from now and set it to the first glucose data
	#if _==0:
	#	call("date -Ins -s $(date -Ins -d '-5 minute')", shell=True)
	#	first_glucose_to_prepend = data[0].copy()
	#	first_glucose_to_prepend["date"]=int(time.time())*1000
	#	print(data[0])
	#	print(data[0]["date"])
	#	with open("monitor/glucose.json", "w") as dump_first_glucose:
	#		json.dump(data[0], dump_first_glucose, indent=4)
	#		dump_first_glucose.close()	
	#	#print(data_to_prepend["date"])	
	
	
	call("date -Ins -s $(date -Ins -d '+5 minute')", shell=True)
		
	
	current_timestamp = datetime.datetime.fromtimestamp(time.time()).strftime('%Y-%m-%dT%H:%M:%S-07:00')
	with open('monitor/clock.json','w') as update_clock:
		json.dump(current_timestamp, update_clock)

	
	
	call(["openaps", "report", "invoke", "settings/profile.json"])
	call(["openaps", "report", "invoke", "monitor/iob.json"])
	
        #run openaps to get suggested tempbasal
	
	call(["openaps", "report", "invoke", "enact/suggested.json"])
	
#	current_timestamp = datetime.datetime.fromtimestamp(time.time()).strftime('%Y-%m-%dT%H:%M:%S-07:00')
	
	#read the output in suggested.json and append it to list_suggested_data_to_dump list. Basically we are trying to get all the suggest	    ed data and dump make a list lf that and then dump it to all_suggested.json file		
	with open("enact/suggested.json") as read_suggested:
		loaded_suggested_data = json.load(read_suggested)
		#list_suggested_data_to_dump.insert(0,loaded_suggested_data)
		#list_suggested_data_to_dump.append(loaded_suggested_data)
		read_suggested.close()

#################################### Context table check #################################################################

	bg_target = 110
	
	if "eventualBG" in loaded_suggested_data:
		e_bg = loaded_suggested_data["eventualBG"]
	glucose = float(loaded_glucose)
	running_temp_rate = loaded_suggested_data["running_temp"]["rate"]
	basal = loaded_suggested_data["basal"]

	if glucose < 39:
		init_ebg_pointer = 0
	else:
		init_ebg_pointer = init_ebg_pointer + 1

	if _ == 0 and glucose >= 39:
		prev_e_bg = e_bg
	
	elif init_ebg_pointer == 1:
		prev_e_bg = e_bg	
	
#	if "short_avgdelta" in loaded_suggested_data:
#		short_avgdelta = loaded_suggested_data["short_avgdelta"]
#	if "bgi" in loaded_suggested_data:
#		bgi = loaded_suggested_data["bgi"]	
	
	################# Context table first row ########################
	if glucose < 39:
		if running_temp_rate >= basal:
			if loaded_suggested_data["rate"] == 0 and loaded_suggested_data["duration"] == 0 :
				print("\nNO Fault\n")
			else:
				print("\n***************************************")
				print("********** Faultiy !!!!! *************")
				print("Glucose < 39, Cancel_temp was not provided")  	
				print("***************************************\n")
				fault_occurrence += 1


	################# Context table second row ########################
	
	elif glucose >=39 and glucose < 75:
		if loaded_suggested_data["rate"] == 0 or loaded_suggested_data["rate"] == basal:
			print("\n NO fault\n")
		else:
			loaded_suggested_data["fault"] = "yes"
			loaded_suggested_data["fault_reason"] = "Reason: 39 =< glucose <75; recommended rate is not equal to 0 or basal"	
			print("\n***************************************")
			print("********** Faultiy !!!!! *************")
			print("Reason: 39 =< glucose <=75; recommended rate is not equal to 0 or basal")  	
			print("***************************************\n")
			fault_occurrence += 1

	################# Context table third row (if E_BG is above BG_Target)  ########################

	elif glucose >= 75:
		recommended_change_rate = loaded_suggested_data["rate"] - running_temp_rate

		if e_bg > bg_target:

			if e_bg - prev_e_bg > 0:
				if recommended_change_rate >= 0 or loaded_suggested_data["rate"] == basal:
					print("\nNO Fault\n")
				else:
					loaded_suggested_data["fault"] = "yes"
					loaded_suggested_data["fault_reason"] = "Reason: glucose > threshold(75); e_bg > bg_target; e_bg is rising; recommended_rate decreases" 
					print("\n***************************************")
					print("********** Faultiy !!!!! *************")  	
					print("Reason: glucose > threshhold(75); e_bg > bg_target; e_bg is rising; recommended_rate decreases")
					print("***************************************\n")
					fault_occurrence += 1
				
		
	################# Context table fourth and fifth row ########################
		elif e_bg < bg_target:
			if e_bg - prev_e_bg > 0:
			#	lt_target_rising_visit_stat = 0
				if recommended_change_rate < 0:
					loaded_suggested_data["fault"] = "yes"
					loaded_suggested_data["fault_reason"] = "e_bg > 75; e_bg < bg_target; bg is rising; rate decreases, but it should not decrease"
					print("\n***************************************")
					print("********** Faultiy !!!!! *************") 
					print("Reason: e_bg > 75; e_bg < bg_target; bg is rising; rate should not decrease, but it decrease twice") 	
					print("***************************************\n")
					fault_occurrence += 1
				else:
					print("\nNO Fault\n")	

			elif e_bg - prev_e_bg < 0:
			#	lt_target_rising_visit_stat = 0
				if recommended_change_rate > 0:
					loaded_suggested_data["fault"] = "yes"
					loaded_suggested_data["fault_reason"] = "e_bg > 75; e_bg < bg_target and rising; rate should not decrease "
					print("\n***************************************")
					print("********** Faultiy !!!!! *************") 
					print("Reason: e_bg > 75; e_bg < bg_target and rising; rate should not decrease") 	
					print("***************************************\n")
					fault_occurrence += 1
				else:
					print("\nNO Fault\n")
			
			elif e_bg - prev_e_bg == 0:
				if recommended_change_rate > 0:
					loaded_suggested_data["fault"] = "yes"
					loaded_suggested_data["fault_reason"] = "e_bg > 75; e_bg < bg_target; neither rising nor falling; rate should not increase"
					print("\n***************************************")
					print("********** Faultiy !!!!! *************") 
					print("Reason:e_bg > 75; e_bg < bg_target; neither rising nor falling; rate should not increase") 	
					print("***************************************\n")
					fault_occurrence += 1
				else:
					print("\nNO Fault\n")
		
	
		print("\nprev_e_bg: ", prev_e_bg)
		print("e_bg: ", e_bg,"\n")
	
	if glucose >= 39:				
		prev_e_bg = e_bg
	

	list_suggested_data_to_dump.insert(0,loaded_suggested_data)
	#read the output in suggested.json and append it to list_suggested_data_to_dump list. Basically we are trying to get all the suggest	    ed data and dump make a list lf that and then dump it to all_suggested.json file		
#	with open("enact/suggested.json") as read_suggested:
#		loaded_suggested_data = json.load(read_suggested)
#		list_suggested_data_to_dump.insert(0,loaded_suggested_data)
#		#list_suggested_data_to_dump.append(loaded_suggested_data)
#		read_suggested.close()
	
	
	#################### Update pumphistory at very begining ##################
	if _==0:
		if  'duration' in loaded_suggested_data.keys():
		
			with open("monitor/pumphistory.json") as read_pump_history:
				loaded_pump_history = json.load(read_pump_history) # read whole pump_history.json
				pump_history_0 = loaded_pump_history[0].copy()	#load first element
				pump_history_1 = loaded_pump_history[1].copy() #load second element, fist and second are both for one temp basal
				pump_history_0['duration (min)'] = loaded_suggested_data['duration'] #update the values
				pump_history_1['rate'] = loaded_suggested_data['rate']
				pump_history_0['timestamp'] = current_timestamp
				pump_history_1['timestamp'] = current_timestamp

				loaded_pump_history.insert(0, pump_history_1) # insert second element back to whatever we loaded from pumphistory
				loaded_pump_history.insert(0, pump_history_0) #insert first element back to whatever we loaded from pumphistory
	                    
				read_pump_history.close();
		
			with open("monitor/pumphistory.json", "w") as write_pump_history:
				json.dump(loaded_pump_history, write_pump_history, indent=4)
	
################ Update temp_basal.json with the current temp_basal rate and duration ####################
	
	#load temp_basal.json
	with open("monitor/temp_basal.json") as read_temp_basal:
		loaded_temp_basal = json.load(read_temp_basal)
		loaded_temp_basal['duration']-=5
		
		if loaded_temp_basal['duration']<=0:
			loaded_temp_basal['duration'] = 0
		
		if "doing nothing" not in loaded_suggested_data['reason']:

			if loaded_temp_basal['duration']==0:
				loaded_temp_basal['duration'] = loaded_suggested_data['duration']
				loaded_temp_basal['rate'] = loaded_suggested_data['rate']

				######################### Update input of glucosym based on new temp ##############
				if loaded_suggested_data['rate'] == 0 and loaded_suggested_data['duration'] == 0:
					loaded_algo_input_copy["events"]['basal'][0]['amt'] = loaded_suggested_data['basal']
					loaded_algo_input_copy["events"]['basal'][0]['length'] = 30
					loaded_algo_input_copy["events"]['basal'][0]['start'] = _*5
				else:
					
					loaded_algo_input_copy["events"]['basal'][0]['amt'] = loaded_suggested_data['rate']
					loaded_algo_input_copy["events"]['basal'][0]['length'] = loaded_suggested_data['duration']
					loaded_algo_input_copy["events"]['basal'][0]['start'] = _*5
				
				##################### Uppdate Pupmphistory ####################################
					
				with open("monitor/pumphistory.json") as read_pump_history:
					loaded_pump_history = json.load(read_pump_history) # read whole pump_history.json
					pump_history_0 = loaded_pump_history[0].copy()	#load first element
					pump_history_1 = loaded_pump_history[1].copy() #load second element, fist and second are both for one temp basal
					pump_history_0['duration (min)'] = loaded_suggested_data['duration'] #update the values
					pump_history_1['rate'] = loaded_suggested_data['rate']
					pump_history_0['timestamp'] = current_timestamp
					pump_history_1['timestamp'] = current_timestamp

					loaded_pump_history.insert(0, pump_history_1) # insert second element back to whatever we loaded from pumphistory
					loaded_pump_history.insert(0, pump_history_0) #insert first element back to whatever we loaded from pumphistory
		                    
					read_pump_history.close();
			
				with open("monitor/pumphistory.json", "w") as write_pump_history:
					json.dump(loaded_pump_history, write_pump_history, indent=4)
				
			
			else:	
		    
				if loaded_temp_basal['rate']!=loaded_suggested_data['rate']:
					loaded_temp_basal['rate']=loaded_suggested_data['rate']
					loaded_temp_basal['duration']=loaded_suggested_data['duration']

					####################### Update input of glucosym based on new temp ###########
					
					loaded_algo_input_copy["events"]['basal'][0]['amt'] = loaded_suggested_data['rate']
					loaded_algo_input_copy["events"]['basal'][0]['length'] = loaded_suggested_data['duration']
					loaded_algo_input_copy["events"]['basal'][0]['start'] = _*5

					#################### Uppdate Pumphistory ############################
					
					with open("monitor/pumphistory.json") as read_pump_history:
						loaded_pump_history = json.load(read_pump_history) # read whole pump_history.json
						pump_history_0 = loaded_pump_history[0].copy()	#load first element
						pump_history_1 = loaded_pump_history[1].copy() #load second element, fist and second are both for one temp basal
						pump_history_0['duration (min)'] = loaded_suggested_data['duration'] #update the values
						pump_history_1['rate'] = loaded_suggested_data['rate']
						pump_history_0['timestamp'] = current_timestamp
						pump_history_1['timestamp'] = current_timestamp

						loaded_pump_history.insert(0, pump_history_1) # insert second element back to whatever we loaded from pumphistory
						loaded_pump_history.insert(0, pump_history_0) #insert first element back to whatever we loaded from pumphistory
		        	            
						read_pump_history.close();
				
					with open("monitor/pumphistory.json", "w") as write_pump_history:
						json.dump(loaded_pump_history, write_pump_history, indent=4)
		

#		else:
#			if loaded_temp_basal['duration']<=0:
#				loaded_temp_basal['duration'] = 0
		
		read_temp_basal.close()
		#print(loaded_algo_input_copy)
           # if loaded_temp_basal['duration']<=0:
           # 	if 'duration' in loaded_suggested_data:
           #         loaded_temp_basal['duration'] = loaded_suggested_data['duration']
           #         loaded_temp_basal['rate'] = loaded_suggested_data['rate']
        
           # read_temp_basal.close()
            #if loaded_temp_basal['duration']<=0:
    	    #    loaded_temp_basal['duration']=0
        
    #	if 'rate' in loaded_suggested_data.keys():
           # loaded_temp_basal['duration'] = loaded_suggested_data['duration']
           # loaded_temp_basal['rate'] = loaded_suggested_data['rate']
           # read_temp_basal.close()
			
    #if "no temp required" in loaded_suggested_data['reason']:
    #	loaded_temp_basal['duration'] = loaded_temp_basal['duration']
    #	loaded_temp_basal['rate'] = loaded_temp_basal['rate']
	
		
	with open("monitor/temp_basal.json", "w") as write_temp_basal:
		json.dump(loaded_temp_basal, write_temp_basal, indent=4)		
			
	
	#print(suggested_data_to_dump)
	#write the list_suggested_data_to_dump into all_suggested.json file
	with open("enact/all_suggested.json", "w") as dump_suggested:
		json.dump(list_suggested_data_to_dump, dump_suggested, indent=4)
		dump_suggested.close()	

	#if 'rate' in loaded_suggested_data.keys():
      	#update the insulin parameter input of glucosym. This insulin parameters is received from openaps(suggested.json)
	#	algo_input_list["events"]['basal'][0]['amt'] = loaded_suggested_data['rate']
	#	algo_input_list["events"]['basal'][0]['length'] = loaded_suggested_data['duration']
	#	algo_input_list["events"]['basal'][0]['start'] = _*5
	
	
	
	#os.chdir("../glucosym/closed_loop_algorithm_samples")
	
	####################### Write algo_input having the suggested output from openaps ##########################
	
	with open("../glucosym/closed_loop_algorithm_samples/algo_input.json", "w") as write_algo_input:
		json.dump(loaded_algo_input_copy, write_algo_input, indent=4)
	
	
	call(["node", "../glucosym/closed_loop_algorithm_samples/algo_bw.js"]);
	
		
	#loaded_algo_input['index'] = loaded_algo_input['index']+1

	#print(algo_input_list)

	#with open("../glucosym/closed_loop_algorithm_samples/algo_input.json", "w") as write_algo_input:
	#	json.dump(algo_input_list, write_algo_input, indent=4)
	#os.chdir("../../myopenaps")

	
		
#	data_to_prepend = data[0].copy()
	#current_time = data_to_prepend["display_time"]
	#mytime = datetime.strptime(current_time,"%Y-%m-%dT%H:%M:%S-07:00")
	#dt = timedelta(minutes = 5)
	#mytime += dt

	#make_time_str = str(mytime).split(' ')
	#new_time_str = make_time_str[0]+"T"+make_time_str[1]+"-07:00"

	#data_to_prepend["display_time"] = new_time_str
	#data_to_prepend["dateString"] = new_time_str

	#current_time = data_to_prepend["system_time"]
	#mytime = datetime.strptime(current_time,"%Y-%m-%dT%H:%M:%S-07:00")
	#dt = timedelta(minutes = 5)
	#mytime += dt

	#make_time_str = str(mytime).split(' ')
	#new_time_str = make_time_str[0]+"T"+make_time_str[1]+"-07:00"

	#data_to_prepend["system_time"] =  new_time_str

#	read_glucose_from_glucosym = open("../glucosym/closed_loop_algorithm_samples/glucose_output_algo_bw.txt", "r")
#	loaded_glucose = read_glucose_from_glucosym.read()

	#data_to_prepend["glucose"] = int(data_to_prepend["glucose"])-5
#	data_to_prepend["glucose"] = loaded_glucose
	
#	data_to_prepend["date"]+= 300000
#	call("date -Ins -s $(date -Ins -d '+5 minute')", shell=True)	
#	data.insert(0, data_to_prepend)
	

#	with open('monitor/glucose.json', 'w') as outfile:
#		json.dump(data, outfile, indent=4)
#		outfile.close()


	#This part is for ploting glucose and insulin data over the time. This section starts after all the iteration is finished
#if _ == iteration_num:
#	with open("enact/all_suggested.json") as read_all_suggested:
#		loaded_all_suggested = json.load(read_all_suggested)
	#y_list = [{"a":1, "b":1},{"a":4, "b":2},{"a":9, "b":3},{"a":16, "b":4}] 
   
	#print(loaded_all_suggested)
 
#glucose = []
#insulin = []
#time = []
 
#time_index = 0
 
#for _ in loaded_all_suggested:
#	if 'bg' in _.keys() and 'rate' in _.keys():
#		glucose.insert(0,_['bg'])
#		insulin.insert(0,_['rate'])
#		time.append(time_index)
#		time_index+=5
	#print(glucose)
	#print(time)
#plt.plot(time, glucose)
#plt.plot(time, insulin)
#plt.ylabel("glucose and Insulin")
#plt.xlabel("time")
#plt.show()
	#print("glucose",glucose)
	#print("insulin",insulin)
	#print("time",time)
print("\n ########################################")
print("Fault Occurrence:", fault_occurrence, " times")
print("########################################\n")