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