def pumping_operation(day,hour,minute,frequency_sampling,num_samples,operate_arduino_object,starting_well=0):
samplingObject=CFlow.sampleHandling()
click_object=CFlow.click(sample_counter=starting_well)
click_object.set_measuring_times(day,hour,minute,frequency_sampling,num_samples) #Set input correctly. day,hour,minute,frequency,num_samples
read_fcs_object=CFlow.read_fcs('C:\\Users\\localadmin\\Desktop\\Results','ecoli')
while click_object.set_waiting_time()==0:
time.sleep(click_object.waiting_time)
logging.info('waiting time until next measurement is: %f',click_object.waiting_time)
samplingObject.bring_sample(operate_arduino_object,sample=click_object.measuring_times[click_object.time_counter][1])
click_object.sample()
click_object.run(click_object.measuring_times[click_object.time_counter][1])
click_object.export()
time.sleep(1)
click_object.moveFiles('C:\\Users\\localadmin\\Desktop','C:\\Users\\localadmin\\Desktop\\Results')###THIS CHANGES FROM COMPUTER TO COMPUTER. THE OUTPUT FOLDER MUST BE CREATED BEFOREHAND
time.sleep(1)
##PERFORM FEEDBACK
##
click_object.backflush()
operate_arduino_object.push_to_cytometer(2)
operate_arduino_object.cytometer_to_waste(2)
operate_arduino_object.push_to_cytometer(2)
operate_arduino_object.cytometer_to_waste(2)
operate_arduino_object.push_to_cytometer(2)
operate_arduino_object.cytometer_to_waste(2)
return
def pumping_operation(day,
hour,
minute,
frequency,
num_samples,
operate_arduino_object,
starting_well=0):
click_object = CFlow.click(sample_counter=starting_well)
click_object.set_measuring_times(
day, hour, minute, frequency, num_samples
) #Set input correctly. day,hour,minute,frequency,num_samples
read_fcs_object = CFlow.read_fcs('C:\\Users\\rumarc\\Desktop\\Results',
'ecoli')
operate_arduino_object.operate_led(1, 256) ####
operate_arduino_object.operate_led(2, 0 * 256) ####
##Feedback constants
I = 0
P = 0
kp = 0.8
ki = 0.08
ref = 0.66 #Reference value for controller
##
while click_object.set_waiting_time() == 0:
time.sleep(click_object.waiting_time)
logging.info('waiting time until next measurement is: %f',
click_object.waiting_time)
bring_sample(operate_arduino_object)
click_object.sample()
click_object.run()
click_object.export()
time.sleep(1)
click_object.moveFiles(
'C:\\Users\\rumarc\\Desktop', 'C:\\Users\\rumarc\\Desktop\\Results'
) ###THIS CHANGES FROM COMPUTER TO COMPUTER. THE OUTPUT FOLDER MUST BE CREATED BEFOREHAND
time.sleep(1)
##PERFORM FEEDBACK
GFP_mean = read_fcs_object.get_last_data(click_object)
logging.info('GFP mean is: %f', GFP_mean)
print(GFP_mean)
I = ki * (ref - GFP_mean) + I
print(I)
logging.info('Integral parameter value is: %f', I)
P = kp * (ref - GFP_mean)
print(P)
logging.info('Proportional parameter value is: %f', P)
LED_signal = P + I
if LED_signal < 0:
LED_signal = 0
elif LED_signal > 1:
LED_signal = 1
logging.info('LED signal is: %f', LED_signal)
print(LED_signal)
LED_signal = LED_signal * 256
operate_arduino_object.operate_led(2, LED_signal)
##
click_object.backflush()
operate_arduino_object.cytometer_to_waste(8)
return
def pumping_operation(day,hour,minute,frequency,num_samples,operate_arduino_object,starting_well=0):
click_object=CFlow.click(sample_counter=starting_well)
click_object.set_measuring_times(day,hour,minute,frequency,num_samples) #Set input correctly. day,hour,minute,frequency,num_samples
read_fcs_object=CFlow.read_fcs('C:\\Users\\rumarc\\Desktop\\Results','ecoli')
operate_arduino_object.operate_led(1,256)####
operate_arduino_object.operate_led(2,0*256)####
##Feedback constants
I=0
P=0
kp=6.8
ki=0.5
ref=0.07 #Reference value for controller
##
while click_object.set_waiting_time()==0:
time.sleep(click_object.waiting_time)
logging.info('waiting time until next measurement is: %f',click_object.waiting_time)
bring_sample(operate_arduino_object)
click_object.sample()
click_object.run()
click_object.export()
time.sleep(1)
click_object.moveFiles('C:\\Users\\rumarc\\Desktop','C:\\Users\\rumarc\\Desktop\\Results')###THIS CHANGES FROM COMPUTER TO COMPUTER. THE OUTPUT FOLDER MUST BE CREATED BEFOREHAND
time.sleep(1)
##PERFORM FEEDBACK
GFP_variance=read_fcs_object.get_last_data(click_object,'variance')
logging.info('GFP variance is: %f',GFP_variance)
if GFP_variance>ref:
kp=13.6
ki=1.5
if GFP_variance<ref*0.9:
kp=6.8
ki=0.5
print(GFP_variance)
I=ki*(ref-GFP_variance)+I
if I<0:
I=0
print(I)
logging.info('Integral parameter value is: %f',I)
P=kp*(ref-GFP_variance)
print(P)
logging.info('Proportional parameter value is: %f',P)
LED_signal=P+I
if LED_signal<0:
LED_signal=0
elif LED_signal>1:
LED_signal=1
logging.info('LED signal is: %f',LED_signal)
print(LED_signal)
LED_signal=LED_signal*256
operate_arduino_object.operate_led(2,LED_signal)
##
click_object.backflush()
operate_arduino_object.cytometer_to_waste(8)
return
def pumping_operation(day,
hour,
minute,
frequency,
num_samples,
operate_arduino_object,
starting_well=0):
click_object = CFlow.click(sample_counter=starting_well)
click_object.set_measuring_times(
day, hour, minute, frequency, num_samples
) #Set input correctly. day,hour,minute,frequency,num_samples
read_fcs_object = CFlow.read_fcs('C:\\Users\\rumarc\\Desktop\\Results',
'ecoli')
operate_arduino_object.operate_led(1, 256) ####
operate_arduino_object.operate_led(2, 0 * 256) ####
##controller setup
controller = CFlow.MPC()
reference = np.zeros(shape=(1, (num_samples + 2))) + 0.66
LED_signal = 0
####Need to add something to subtract initial offset from data!!!
##
cycle = 0
offset = 0 #This is the offset that will be applied to both the GFP mean and the reference value. This is because the model fitting was done subtracting the initial timepoint from all the data.
while click_object.set_waiting_time() == 0:
time.sleep(click_object.waiting_time)
logging.info('waiting time until next measurement is: %f',
click_object.waiting_time)
bring_sample(operate_arduino_object)
click_object.sample()
click_object.run()
click_object.export()
time.sleep(1)
click_object.moveFiles(
'C:\\Users\\rumarc\\Desktop', 'C:\\Users\\rumarc\\Desktop\\Results'
) ###THIS CHANGES FROM COMPUTER TO COMPUTER. THE OUTPUT FOLDER MUST BE CREATED BEFOREHAND
time.sleep(1)
##PERFORM CONTTROL
GFP_mean = read_fcs_object.get_last_data(click_object)
logging.info('GFP mean is: %f', GFP_mean)
print(GFP_mean)
if cycle == 0:
offset = GFP_mean
controller.kalmanFilter(LED_signal, GFP_mean - offset)
LED_signal = controller.multiPrediction(reference[0][cycle:cycle + 5] -
offset) ####!!!!
logging.info('LED signal is: %f', LED_signal)
logging.info('reference is: %f', reference[0][cycle])
print(LED_signal)
operate_arduino_object.operate_led(2, LED_signal * 256)
##
click_object.backflush()
operate_arduino_object.cytometer_to_waste(8)
cycle += 1
return
def pumping_operation(day, hour, minute, frequency, num_samples, operate_arduino_object, starting_well=0):
click_object = CFlow.click(sample_counter=starting_well)
click_object.set_measuring_times(
day, hour, minute, frequency, num_samples
) # Set input correctly. day,hour,minute,frequency,num_samples
read_fcs_object = CFlow.read_fcs("C:\\Users\\rumarc\\Desktop\\Results", "ecoli")
operate_arduino_object.operate_led(1, 256) ####
operate_arduino_object.operate_led(2, 0 * 256) ####
##controller setup
controller = CFlow.newMPC(10)
LED_signal = 0
LED_signalTransformed = 0
####Need to add something to subtract initial offset from data!!!
##
cycle = 0
while click_object.set_waiting_time() == 0:
time.sleep(click_object.waiting_time)
logging.info("waiting time until next measurement is: %f", click_object.waiting_time)
bring_sample(operate_arduino_object)
click_object.sample()
click_object.run()
click_object.export()
time.sleep(1)
click_object.moveFiles(
"C:\\Users\\rumarc\\Desktop", "C:\\Users\\rumarc\\Desktop\\Results"
) ###THIS CHANGES FROM COMPUTER TO COMPUTER. THE OUTPUT FOLDER MUST BE CREATED BEFOREHAND
time.sleep(1)
##PERFORM CONTTROL
GFP_mean = read_fcs_object.get_last_data(click_object)
logging.info("GFP mean is: %f", GFP_mean)
print(GFP_mean)
if cycle == 0:
controller.initialGFPreading = GFP_mean
reference = np.zeros(shape=(1, (num_samples + 6))) + 4
controller.kalmanFilter(LED_signalTransformed, GFP_mean / controller.initialGFPreading)
LED_signalTransformed = controller.multiPrediction(reference[0][cycle : cycle + 5])
LED_signal = controller.ledOutputTransformation(LED_signalTransformed)
if LED_signal > 1:
LED_signal = 1
elif LED_signal < 0:
LED_signal = 0
logging.info("LED signal is: %f", LED_signal)
logging.info("reference is: %f", reference[0][cycle])
print(LED_signal)
operate_arduino_object.operate_led(2, LED_signal * 256)
##
click_object.backflush()
operate_arduino_object.cytometer_to_waste(8)
cycle += 1
return
def pumping_operation(day,hour,minute,frequency,num_samples,operate_arduino_object,starting_well=0):
click_object=CFlow.click(sample_counter=starting_well)
click_object.set_measuring_times(day,hour,minute,frequency,num_samples) #Set input correctly. day,hour,minute,frequency,num_samples
read_fcs_object=CFlow.read_fcs('C:\\Users\\rumarc\\Desktop\\Results','ecoli')
operate_arduino_object.operate_led(1,256)####
operate_arduino_object.operate_led(2,0*256)####
##controller setup
controller=CFlow.newMPC(10)
LED_signal=0
LED_signalTransformed=0
####Need to add something to subtract initial offset from data!!!
##
cycle=0
while click_object.set_waiting_time()==0:
time.sleep(click_object.waiting_time)
logging.info('waiting time until next measurement is: %f',click_object.waiting_time)
bring_sample(operate_arduino_object)
click_object.sample()
click_object.run()
click_object.export()
time.sleep(1)
click_object.moveFiles('C:\\Users\\rumarc\\Desktop','C:\\Users\\rumarc\\Desktop\\Results')###THIS CHANGES FROM COMPUTER TO COMPUTER. THE OUTPUT FOLDER MUST BE CREATED BEFOREHAND
time.sleep(1)
##PERFORM CONTTROL
GFP_mean=read_fcs_object.get_last_data(click_object)
logging.info('GFP mean is: %f',GFP_mean)
print(GFP_mean)
if cycle==0:
controller.initialGFPreading=GFP_mean
reference=np.zeros(shape=(1,(num_samples+6)))+4
controller.kalmanFilter(LED_signalTransformed,GFP_mean/controller.initialGFPreading)
LED_signalTransformed=controller.multiPrediction(reference[0][cycle:cycle+5])
LED_signal=controller.ledOutputTransformation(LED_signalTransformed)
if LED_signal>1:
LED_signal=1
elif LED_signal<0:
LED_signal=0
logging.info('LED signal is: %f',LED_signal)
logging.info('reference is: %f',reference[0][cycle])
print(LED_signal)
operate_arduino_object.operate_led(2,LED_signal*256)
##
click_object.backflush()
operate_arduino_object.cytometer_to_waste(8)
cycle+=1
return
def pumping_operation(day,hour,minute,frequency,num_samples,operate_arduino_object,starting_well=0):
click_object=CFlow.click(sample_counter=starting_well)
click_object.set_measuring_times(day,hour,minute,frequency,num_samples) #Set input correctly. day,hour,minute,frequency,num_samples
read_fcs_object=CFlow.read_fcs('C:\\Users\\rumarc\\Desktop\\Results','ecoli')
operate_arduino_object.operate_led(1,0*256)####
operate_arduino_object.operate_led(2,1*256)####
##Feedback constants
I=0
P=0
kp=0.8
ki=0.06
ref=0.66
##
while click_object.set_waiting_time()==0:
time.sleep(click_object.waiting_time)
logging.info('waiting time until next measurement is: %f',click_object.waiting_time)
bring_sample(operate_arduino_object)
click_object.sample()
click_object.run()
click_object.export()
time.sleep(1)
click_object.moveFiles('C:\\Users\\rumarc\\Desktop','C:\\Users\\rumarc\\Desktop\\Results')###THIS CHANGES FROM COMPUTER TO COMPUTER. THE OUTPUT FOLDER MUST BE CREATED BEFOREHAND
time.sleep(1)
##PERFORM FEEDBACK
GFP_mean=read_fcs_object.get_last_data(click_object)
logging.info('GFP mean is: %f',GFP_mean)
# print(GFP_mean)
# I=ki*(ref-GFP_mean)+I
# print(I)
# logging.info('Integral parameter value is: %f',I)
# P=kp*(ref-GFP_mean)
# print(P)
# logging.info('Proportional parameter value is: %f',P)
# LED_signal=P+I
# if LED_signal<0:
# LED_signal=0
# elif LED_signal>1:
# LED_signal=1
# logging.info('LED signal is: %f',LED_signal)
# print(LED_signal)
# LED_signal=LED_signal*256
# operate_arduino_object.operate_led(2,LED_signal)
##
click_object.backflush()
operate_arduino_object.cytometer_to_waste(7)
return
def pumping_operation(day,
hour,
minute,
frequency_sampling,
num_samples,
operate_arduino_object,
starting_well=0):
samplingObject = CFlow.sampleHandling()
click_object = CFlow.click(sample_counter=starting_well)
click_object.set_measuring_times(
day, hour, minute, frequency_sampling, num_samples
) #Set input correctly. day,hour,minute,frequency,num_samples
read_fcs_object = CFlow.read_fcs('C:\\Users\\localadmin\\Desktop\\Results',
'ecoli')
while click_object.set_waiting_time() == 0:
time.sleep(click_object.waiting_time)
logging.info('waiting time until next measurement is: %f',
click_object.waiting_time)
samplingObject.bring_sample(
operate_arduino_object,
sample=click_object.measuring_times[click_object.time_counter][1])
click_object.sample()
click_object.run(
click_object.measuring_times[click_object.time_counter][1])
click_object.export()
time.sleep(1)
click_object.moveFiles(
'C:\\Users\\localadmin\\Desktop',
'C:\\Users\\localadmin\\Desktop\\Results'
) ###THIS CHANGES FROM COMPUTER TO COMPUTER. THE OUTPUT FOLDER MUST BE CREATED BEFOREHAND
time.sleep(1)
##PERFORM FEEDBACK
##
click_object.backflush()
operate_arduino_object.push_to_cytometer(2)
operate_arduino_object.cytometer_to_waste(2)
operate_arduino_object.push_to_cytometer(2)
operate_arduino_object.cytometer_to_waste(2)
operate_arduino_object.push_to_cytometer(2)
operate_arduino_object.cytometer_to_waste(2)
return
def pumping_operation(day,hour,minute,frequency,num_samples,operate_arduino_object,starting_well=0):
click_object=CFlow.click(sample_counter=starting_well)
click_object.set_measuring_times(day,hour,minute,frequency,num_samples) #Set input correctly. day,hour,minute,frequency,num_samples
read_fcs_object=CFlow.read_fcs('C:\\Users\\rumarc\\Desktop\\Results','ecoli')
operate_arduino_object.operate_led(1,256)####
operate_arduino_object.operate_led(2,0*256)####
##controller setup
controller=CFlow.MPC()
reference=np.zeros(shape=(1,(num_samples+2)))+0.66
LED_signal=0
####Need to add something to subtract initial offset from data!!!
##
cycle=0
offset=0 #This is the offset that will be applied to both the GFP mean and the reference value. This is because the model fitting was done subtracting the initial timepoint from all the data.
while click_object.set_waiting_time()==0:
time.sleep(click_object.waiting_time)
logging.info('waiting time until next measurement is: %f',click_object.waiting_time)
bring_sample(operate_arduino_object)
click_object.sample()
click_object.run()
click_object.export()
time.sleep(1)
click_object.moveFiles('C:\\Users\\rumarc\\Desktop','C:\\Users\\rumarc\\Desktop\\Results')###THIS CHANGES FROM COMPUTER TO COMPUTER. THE OUTPUT FOLDER MUST BE CREATED BEFOREHAND
time.sleep(1)
##PERFORM CONTTROL
GFP_mean=read_fcs_object.get_last_data(click_object)
logging.info('GFP mean is: %f',GFP_mean)
print(GFP_mean)
if cycle==0:
offset=GFP_mean
controller.kalmanFilter(LED_signal,GFP_mean-offset)
LED_signal=controller.multiPrediction(reference[0][cycle:cycle+5]-offset)####!!!!
logging.info('LED signal is: %f',LED_signal)
logging.info('reference is: %f',reference[0][cycle])
print(LED_signal)
operate_arduino_object.operate_led(2,LED_signal*256)
##
click_object.backflush()
operate_arduino_object.cytometer_to_waste(8)
cycle+=1
return
def pumping_operation(day,hour,minute,frequency,num_samples,operate_arduino_object,starting_well=0):
click_object=CFlow.click(sample_counter=starting_well)
click_object.set_measuring_times(day,hour,minute,frequency,num_samples) #Set input correctly. day,hour,minute,frequency,num_samples
read_fcs_object=CFlow.read_fcs('C:\\Users\\localadmin\\Desktop\\Results','ecoli')
##Initial light conditions
LED_signal=0#initial green light
LED_signalTransformed=0
operate_arduino_object.operate_led(1,256)
operate_arduino_object.operate_led(2,LED_signal*256)
##Start up Matlab
matlab = matlab_wrapper.MatlabSession()
matlab.eval("parpool")
matlab.eval("cd('C:\\Users\\localadmin\\Desktop\\Particle Filter')")
##Controller setup
P=5000#number of particles
MPChorizon=3#number of steps that the MPC looks ahead for the optimization
reference=[4,]*(num_samples+MPChorizon)
GFP_measurements=[1]
LEDapplied=[0]#Needs to be from 0 to 4.5!!
##Dose-response Sigmoidal
a=5.828
b=3.353
c=-0.05946
d=-1.3388
##
cycle=0
while click_object.set_waiting_time()==0:
time.sleep(click_object.waiting_time)
logging.info('waiting time until next measurement is: %f',click_object.waiting_time)
bring_sample(operate_arduino_object)
click_object.sample()
click_object.run()
click_object.export()
time.sleep(1)
click_object.moveFiles('C:\\Users\\localadmin\\Desktop','C:\\Users\\localadmin\\Desktop\\Results')###THIS CHANGES FROM COMPUTER TO COMPUTER. THE OUTPUT FOLDER MUST BE CREATED BEFOREHAND
time.sleep(1)
##PERFORM CONTTROL
GFP_mean=read_fcs_object.get_last_data(click_object)
logging.info('GFP mean is: %f',GFP_mean)
print(GFP_mean)
if cycle==0:
initialGFPreading=GFP_mean
GFP_measurements.append(GFP_mean/initialGFPreading)
matlabCommand="LED=MPC_loop(%i,%i,%i,%s,%s,%s)"%(P,frequency,MPChorizon,str(GFP_measurements),str(reference),str(LEDapplied))#!!!Don't apply on the first cycle.
matlab.eval(matlabCommand)
LED_signalTransformed=matlab.get('LED')
LEDapplied.append(LED_signalTransformed)
LED_signal=np.log(a/(b*(LED_signalTransformed-d))-1/b)/(c*100)
if LED_signal>1:
LED_signal=1
elif LED_signal<0:
LED_signal=0
logging.info('LED signal is: %f',LED_signal)
logging.info('reference is: %f',reference[cycle])
print(LED_signal)
operate_arduino_object.operate_led(2,LED_signal*256)
##
click_object.backflush()
operate_arduino_object.cytometer_to_waste(8)
cycle+=1
return
def pumping_operation(day,
hour,
minute,
frequency,
num_samples,
operate_arduino_object,
starting_well=0):
click_object = CFlow.click(sample_counter=starting_well)
click_object.set_measuring_times(
day, hour, minute, frequency, num_samples
) #Set input correctly. day,hour,minute,frequency,num_samples
read_fcs_object = CFlow.read_fcs('C:\\Users\\localadmin\\Desktop\\Results',
'ecoli')
##Initial light conditions
LED_signal = 0 #initial green light
LED_signalTransformed = 0
operate_arduino_object.operate_led(1, 256)
operate_arduino_object.operate_led(2, LED_signal * 256)
##Start up Matlab
matlab = matlab_wrapper.MatlabSession()
matlab.eval("parpool")
matlab.eval("cd('C:\\Users\\localadmin\\Desktop\\Particle Filter')")
##Controller setup
P = 5000 #number of particles
MPChorizon = 3 #number of steps that the MPC looks ahead for the optimization
reference = [
4,
] * (num_samples + MPChorizon)
GFP_measurements = [1]
LEDapplied = [0] #Needs to be from 0 to 4.5!!
##Dose-response Sigmoidal
a = 5.828
b = 3.353
c = -0.05946
d = -1.3388
##
cycle = 0
while click_object.set_waiting_time() == 0:
time.sleep(click_object.waiting_time)
logging.info('waiting time until next measurement is: %f',
click_object.waiting_time)
bring_sample(operate_arduino_object)
click_object.sample()
click_object.run()
click_object.export()
time.sleep(1)
click_object.moveFiles(
'C:\\Users\\localadmin\\Desktop',
'C:\\Users\\localadmin\\Desktop\\Results'
) ###THIS CHANGES FROM COMPUTER TO COMPUTER. THE OUTPUT FOLDER MUST BE CREATED BEFOREHAND
time.sleep(1)
##PERFORM CONTTROL
GFP_mean = read_fcs_object.get_last_data(click_object)
logging.info('GFP mean is: %f', GFP_mean)
print(GFP_mean)
if cycle == 0:
initialGFPreading = GFP_mean
GFP_measurements.append(GFP_mean / initialGFPreading)
matlabCommand = "LED=MPC_loop(%i,%i,%i,%s,%s,%s)" % (
P, frequency, MPChorizon, str(GFP_measurements), str(reference),
str(LEDapplied)) #!!!Don't apply on the first cycle.
matlab.eval(matlabCommand)
LED_signalTransformed = matlab.get('LED')
LEDapplied.append(LED_signalTransformed)
LED_signal = np.log(a /
(b *
(LED_signalTransformed - d)) - 1 / b) / (c * 100)
if LED_signal > 1:
LED_signal = 1
elif LED_signal < 0:
LED_signal = 0
logging.info('LED signal is: %f', LED_signal)
logging.info('reference is: %f', reference[cycle])
print(LED_signal)
operate_arduino_object.operate_led(2, LED_signal * 256)
##
click_object.backflush()
operate_arduino_object.cytometer_to_waste(8)
cycle += 1
return
