PPK2 gives unrealistic measurments after some time

[RehabAbdAllah]

Hi .. I am running PPK2 GUI and it works as expected . trying to automate the current consumption measurement using ppk2-api but after few samples I get unrealistic measurements . I know nothing is wrong with the connections as I get the expected measurement from PPK2 GUI .

My tests takes a long(ish) time as I want to measure consumption as different states . I notice after ~ 20 minutes the samples looks unrealistic giving ~ 933333333 mA .

I set delay_between_samples_in_sec to 1 sec . measurment logic runs in a thread and prints samples

 def _measurement_logic(self):
        while True and not self.stop_thread:
            if self.ongoing_capture:
                read_data = self.ppk2_device.get_data()
                if read_data != b"":
                    samples, _ = self.ppk2_device.get_samples(read_data)
                    self.stored_current_samples += samples
                    print(f"Average of {len(samples)} samples is: {sum(samples) / len(samples)}uA")
            time.sleep(self.delay_between_samples_in_sec)

Script I run to automate measurement - I save all the samples in a csv file to post process it later

if __name__ == "__main__":
    voltage = "3750"  # in mV
    nordic_ppk2 = PPK2(source_voltage_in_mV=voltage)
    nordic_ppk2.initialize_ppk2()
    nordic_ppk2.set_ppk2_power_state_on()
    time.sleep(50)
    csv_file_name = nordic_ppk2.start_capture(file_prefix="1st_run")
    time.sleep(600)
    nordic_ppk2.stop_capture()
    print(f"Generated file: {csv_file_name}")
    df = pd.read_csv(csv_file_name)
    # FINDING AVG,MAX AND MIN
    maximum = float(df.iloc[:,1].max())/1000
    minimum = float(df.iloc[:,1].min())/1000
    average = float(df.iloc[:,1].mean())/1000
    print(f'file = {csv_file_name} \n'
          f'Average = {average} mA\n'
          f'Maximum = {maximum} mA\n'
          f'Minimum = {minimum} mA\n')
    time.sleep(10)
    csv_file_name = nordic_ppk2.start_capture(file_prefix="2nd_run")
    time.sleep(600)
    nordic_ppk2.stop_capture()
    print(f"Generated file: {csv_file_name}")
    df = pd.read_csv(csv_file_name)
    # FINDING AVG,MAX AND MIN
    maximum = float(df.iloc[:,1].max())/1000
    minimum = float(df.iloc[:,1].min())/1000
    average = float(df.iloc[:,1].mean())/1000
    print(f'file = {csv_file_name} \n'
          f'Average = {average} mA\n'
          f'Maximum = {maximum} mA\n'
          f'Minimum = {minimum} mA\n')
    time.sleep(10)
    nordic_ppk2.set_ppk2_power_state_off()
    nordic_ppk2.terminate_ppk2()

Unrealistic output that I get after sometime

Average of 255 samples is: 201.08003375301806uA
Average of 255 samples is: 9180480.471826369uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9433153.33932497uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9610732.127517093uA
Average of 255 samples is: 9433715.411266329uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9530250.845644489uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430043.706021905uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9543359.397351908uA
Average of 255 samples is: 9433184.076690257uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499032.128314802uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499021.454707844uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9464867.022682201uA
Average of 255 samples is: 9528133.342755748uA
Average of 255 samples is: 9429927.242173648uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9562305.30156186uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9492217.184726877uA
Average of 255 samples is: 9498870.427615838uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9441757.668911548uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9450267.254938764uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499020.710508693uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9492365.621076312uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9431206.030643925uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430046.134434432uA
Average of 255 samples is: 9499029.582258144uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9442397.463163968uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430038.49626446uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9561069.033534253uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9519729.856048381uA
Average of 255 samples is: 9460137.32903363uA
Average of 255 samples is: 9532202.159327868uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9498821.900509326uA
Average of 255 samples is: 9430018.578808472uA
Average of 255 samples is: 9499020.710508693uA
Average of 255 samples is: 9440338.992101854uA
Average of 255 samples is: 9499021.454707842uA
Average of 255 samples is: 9438480.773886917uA
Average of 255 samples is: 9552899.290645674uA
Average of 255 samples is: 9430109.921257356uA
Average of 255 samples is: 9499014.443456272uA
Average of 255 samples is: 9430018.578808472uA

[NejcKle]

Hello @RehabAbdAllah Please try the suggestion posted here: https://github.com/IRNAS/ppk2-api-python/issues/36#issuecomment-1708123098

Please report your findings.

[RehabAbdAllah]

Hi @NejcKle Thank you for your reply . I used the suggested fix . but I see a gradual increase to the total samples because the read samples are again unrealistic after a certain amount of time . I cannot add all the samples but this are the samples after 12 seconds and after 599 seconds.

After 12 seconds

Average of 10000 samples is: 1.0613972225712949mA
[12.643112897872925]Average current: 2.5463548116633516mA
[12.648344993591309]Average current: 2.5463548116633516mA
[12.653423070907593]Average current: 2.5463548116633516mA
[12.658760070800781]Average current: 2.5463548116633516mA
[12.663992881774902]Average current: 2.5463548116633516mA
[12.669111013412476]Average current: 2.5463548116633516mA
[12.674423933029175]Average current: 2.5463548116633516mA
[12.67964792251587]Average current: 2.5463548116633516mA
[12.685637950897217]Average current: 2.5463548116633516mA
[12.691624879837036]Average current: 2.5463548116633516mA
[12.698649883270264]Average current: 2.5463548116633516mA
[12.704917907714844]Average current: 2.5463548116633516mA
[12.710555076599121]Average current: 2.5463548116633516mA
[12.71591591835022]Average current: 2.5463548116633516mA
[12.725473880767822]Average current: 2.5463548116633516mA
[12.744505882263184]Average current: 2.5463548116633516mA
[12.756057024002075]Average current: 2.5463548116633516mA
Average of 10000 samples is: 0.8791979206356576mA
[12.769118785858154]Average current: 2.533227592048855mA
[12.77507996559143]Average current: 2.533227592048855mA
[12.780687093734741]Average current: 2.533227592048855mA
[12.786417007446289]Average current: 2.533227592048855mA
[12.791770935058594]Average current: 2.533227592048855mA
[12.797851085662842]Average current: 2.533227592048855mA
[12.803261756896973]Average current: 2.533227592048855mA
[12.810301065444946]Average current: 2.533227592048855mA
[12.822291851043701]Average current: 2.533227592048855mA
[12.831923961639404]Average current: 2.533227592048855mA
[12.842575073242188]Average current: 2.533227592048855mA
Average of 10000 samples is: 1.0778059890655785mA

After 599 seconds

[599.2935330867767]Average current: 7164.5617474398705mA
[599.3699128627777]Average current: 7167.4175782322545mA
[599.4410929679871]Average current: 7167.4175782322545mA
[599.5158860683441]Average current: 7167.4175782322545mA
[599.5906610488892]Average current: 7167.4175782322545mA
[599.6636469364166]Average current: 7167.4175782322545mA
Average of 10000 samples is: 6816.917575591368mA
[599.7597930431366]Average current: 7167.266500644936mA
[599.8310089111328]Average current: 7167.266500644936mA
[599.903904914856]Average current: 7167.266500644936mA
[599.9753179550171]Average current: 7167.266500644936m

[wlgrd]

Have you tried with the official software and confirmed that is behaving correctly?

[RehabAbdAllah]

yes it works fine on GUI application on my Mac and the python scripts works well on Raspberry pi . I can only see this problem with python scripts on Mac M1 . I am asumming it is something to do with the USB ports on Mac but I am not sure . for now I am using RPI to measure the current consumption with PPK2 .