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close all; clear all; clc;
filename = 'imu.csv';
data = load_IMU_data_from_csv( filename ) ;
t = data.t;
ax = data.ax;
ay = data.ay;
az = data.az;
gx = data.gx;
gy = data.gy;
gz = data.gz;
% analyze the noise (deviation from mean) on each axis and compare the
% emperical distribution to one generated from a quantized Gaussian
% distrubtuion with the same variance.
quantized_accel_noise_gauss_anal( ax , 'x-axis')
quantized_accel_noise_gauss_anal( ay , 'y-axis')
quantized_accel_noise_gauss_anal( az , 'z-axis')