def measure(self, init_data=np.zeros((3,1)), abs_error=0.0, unit='position', dt=1.0):

"""

try:

# initial data

truth_value = init_data[0]

init_guess = init_data[1]

time_sec = init_data[2]

time_array = np.arange(0, time_sec, dt)

# assign truth value

if type(truth_value[0]) == float:

init_value = truth_value[0]

truth_value = np.ones((int(time_sec/dt), 1))

else:

cols = len(truth_value[0][0,:])

if unit == 'position':

init_value = truth_value[0]

elif unit == 'velocity':

init_value = truth_value[1]

elif unit == 'acceleration':

init_value = truth_value[2]

truth_value = np.ones((int(time_sec/dt), cols))

# reassign truth values

k = 0

for i in range(len(init_value)):

for j in range(int(1/dt)):

if i == len(init_value)-1 or j == int(1/dt)-1:

truth_value[k] = init_value[i]

elif j == int(1/dt):

truth_value[k] = init_value[i]

else:

truth_value[k] = init_value[i] + (init_value[i+1] - init_value[i]) * dt * j

k += 1

sigma = abs_error / 2

# determine observations

array_size = truth_value.shape

observations = np.ones(array_size)

observations = np.random.normal(truth_value, sigma, size=array_size)

return observations, time_array

except Exception as e:

print('Exception: '.upper(), e)

traceback.print_tb(e.__traceback__)