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backup_1_updated_ct_script_e_bg_based.py
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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 = 200
#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")