80 lines
2.9 KiB
Matlab
80 lines
2.9 KiB
Matlab
% ****************************************************************************
|
|
% *
|
|
% * Copyright (C) 2015 PX4 Development Team. All rights reserved.
|
|
% * Author: Eddy Scott <scott.edward@aurora.aero>
|
|
% *
|
|
% * Redistribution and use in source and binary forms, with or without
|
|
% * modification, are permitted provided that the following conditions
|
|
% * are met:
|
|
% *
|
|
% * 1. Redistributions of source code must retain the above copyright
|
|
% * notice, this list of conditions and the following disclaimer.
|
|
% * 2. Redistributions in binary form must reproduce the above copyright
|
|
% * notice, this list of conditions and the following disclaimer in
|
|
% * the documentation and/or other materials provided with the
|
|
% * distribution.
|
|
% * 3. Neither the name PX4 nor the names of its contributors may be
|
|
% * used to endorse or promote products derived from this software
|
|
% * without specific prior written permission.
|
|
% *
|
|
% * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
|
|
% * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
|
|
% * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
|
|
% * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
|
|
% * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
|
|
% * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
|
|
% * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
|
|
% * OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
|
|
% * AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
|
|
% * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
|
|
% * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
|
|
% * POSSIBILITY OF SUCH DAMAGE.
|
|
% *
|
|
% ****************************************************************************/
|
|
%% Clean work environment
|
|
clear all
|
|
close all
|
|
clc
|
|
%% Compile and run the noise cpp program
|
|
system('g++ gaussian_noise.cpp -o generate_noise_csv');
|
|
mu_des = 0.0;
|
|
std_des = 0.02;
|
|
var_des = std_des^2;
|
|
num_samples = 10000;
|
|
num_runs = 100;
|
|
if exist('generated_noise.csv','file')
|
|
system('rm generated_noise.csv')
|
|
end
|
|
system(sprintf('./generate_noise_csv %s %s %s %s',num2str(mu_des),num2str(var_des),num2str(num_runs),num2str(num_samples)))
|
|
%% Load the generated noise values
|
|
noise_vals = load('generated_noise.csv');
|
|
for i = 1:size(noise_vals,1);
|
|
run_mean = mean(noise_vals(i,:));
|
|
run_std = std(noise_vals(i,:));
|
|
mean_array(i) = run_mean;
|
|
std_array(i) = run_std;
|
|
end
|
|
%%%%% Display statisitcs of means generated
|
|
max_mean = max(mean_array);
|
|
min_mean = min(mean_array);
|
|
max_std = max(std_array);
|
|
min_std = min(std_array);
|
|
|
|
figure
|
|
hist(mean_array)
|
|
ylabel('Occurances')
|
|
xlabel('Mean Value')
|
|
title('Histogram of mean values')
|
|
|
|
figure
|
|
hist(std_array)
|
|
ylabel('Occurances')
|
|
xlabel('Std Value')
|
|
title('Histogram of std values')
|
|
|
|
table(min_mean, mu_des, max_mean, min_std, std_des, max_std)
|
|
|
|
|
|
|
|
|