test.cpp

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/* +------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)            |
   |                          http://www.mrpt.org/                          |
   |                                                                        |
   | Copyright (c) 2005-2018, Individual contributors, see AUTHORS file     |
   | See: http://www.mrpt.org/Authors - All rights reserved.                |
   | Released under BSD License. See details in http://www.mrpt.org/License |
   +------------------------------------------------------------------------+ */
 
/**
 * Execute a least squares approximation of the given x,y data.
 */
 
#include <mrpt/math/types_math.h>  // CVectorDouble
#include <mrpt/gui.h>
#include <mrpt/math/interp_fit.hpp>
#include <mrpt/math/utils.h>  // normalize()
#include <iostream>
 
using namespace mrpt::math;
using namespace mrpt::gui;
using namespace std;
 
// ------------------------------------------------------
//                              TestLeastSquares
// ------------------------------------------------------
void TestLeastSquares()
{
        CVectorDouble x, y;
        normalize(x, y);
 
        /**
         * for convenience, first initialize the data as C arrays and then define
         * std;:vectors from
         * that data
         *
         * loadVector
         * Assignment operator for initializing a std::vector from a C array
         * refer to
         * http://reference.mrpt.org/stable/group__container__ops__grp.html#ga40e8e47dea9f504a28d2a70ea8ddb158
         */
        const double X[] = {1, 2, 3, 4};
        const double Y[] = {6, 5, 7, 10};
        loadVector(x, X);
        loadVector(y, Y);
 
        // x points for plotting the least squres line against.
        CVectorDouble Ts;
        linspace(-3.0, 8.0, 100, Ts);
        CVectorDouble Is;
 
        /**
         * Least squares line approximation, based on the provided x,y vectors.
         */
        mrpt::math::leastSquareLinearFit(Ts, Is, x, y);
 
        CDisplayWindowPlots win("Result of linear least squares");
 
        win.plot(Ts, Is);
        win.axis_fit();
        win.axis_equal();
 
        win.plot(x, y, ".3r", "training_points");
 
        win.waitForKey();
}
 
int main(int argc, char** argv)
{
        try
        {
                TestLeastSquares();
 
                return 0;
        }
        catch (std::exception& e)
        {
                std::cout << "MRPT exception caught: " << e.what() << std::endl;
                return -1;
        }
        catch (...)
        {
                printf("Another exception!!");
                return -1;
        }
}