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/*
* Copyright (C) 2020 Open Source Robotics Foundation
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
//! [complete]
#include <iostream>
#include <ignition/math/GaussMarkovProcess.hh>
// You can plot the data generated by this program by following these
// steps.
//
// 1. Run this program and save the output to a file:
// ./gauss_markov_process > plot.data
//
// 2. Use gnuplot to create a plot:
// gnuplot -e 'set terminal jpeg; plot "plot.data" with lines' > out.jpg
int main(int argc, char **argv)
{
// Create the process with:
// * Start value of 20.2
// * Theta (rate at which the process should approach the mean) of 0.1
// * Mu (mean value) 0.
// * Sigma (volatility) of 0.5.
ignition::math::GaussMarkovProcess gmp(20.2, 0.1, 0, 0.5);
std::chrono::steady_clock::duration dt = std::chrono::milliseconds(100);
// This process should decrease toward the mean value of 0.
// With noise of 0.5, the process will walk a bit.
for (int i = 0; i < 1000; ++i)
{
double value = gmp.Update(dt);
std::cout << value << std::endl;
}
return 0;
}
//! [complete]
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