print(
" ======================================== CALCULATING SVMS ======================================== "
)
LA.accelerometer.calculate_svms()
LW.accelerometer.calculate_svms()
RA.accelerometer.calculate_svms()
RW.accelerometer.calculate_svms()
t3 = datetime.datetime.now()
print("Finished Calculating SVMs, Took {} Seconds".format((t3 - t2).seconds))
# Checking for NonWear
print(
" ======================================== LEFT WRIST NONWEAR ========================================"
)
LW.NonWear()
LW.Check_Temperature()
t4 = datetime.datetime.now()
print("Finished Left Wrist Nonwear, Took {} Seconds".format((t4 - t3).seconds))
print(
" ======================================== RIGHT WRIST NONWEAR ========================================"
)
RW.NonWear()
RW.Check_Temperature()
t5 = datetime.datetime.now()
print("Finished Right Wrist Nonwear, Took {} Seconds".format(
(t5 - t4).seconds))
print(
" ======================================== LEFT ANKLE NONWEAR ========================================"
datetime.datetime(year=2019, month=11, day=19, hour=23, minute=2, second=2)] # ======================================== COMPARISON OF VAN HEES AND DING ALGORITHMS S.accelerometer.calculate_svms() # Using VanHees S.VanHeesNonWear() S.Check_Temperature() VanHeesStarts_NT = S.start_indices VanHeesEnds_NT = S.end_indices VanHeesStarts_T = S.non_wear_starts VanheesEnds_T = S.non_wear_ends # Using Ding S.NonWear() S.Check_Temperature() DingStarts_NT = S.start_indices DingEnds_NT = S.end_indices DingStarts_T = S.non_wear_starts DingEnds_T = S.non_wear_ends # ======================================== GRAPHICAL OUTPUT ======================================== sns.set() fig, ((ax1, ax2), (ax3, ax4), (ax5, ax6)) = plt.subplots(3, 2, figsize=(12, 8), sharex=True) ax1.plot(TIMES, S.accelerometer.svms) ax2.plot(TIMES, S.accelerometer.svms) for i in ACTUAL_NON_WEAR_STARTS:
