Example: math_kmeans_example

C++ example source code:

/* +------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)            |
   |                          https://www.mrpt.org/                         |
   |                                                                        |
   | Copyright (c) 2005-2022, Individual contributors, see AUTHORS file     |
   | See: https://www.mrpt.org/Authors - All rights reserved.               |
   | Released under BSD License. See: https://www.mrpt.org/License          |
   +------------------------------------------------------------------------+ */

#include <mrpt/gui/CDisplayWindowPlots.h>
#include <mrpt/math/CVectorFixed.h>
#include <mrpt/math/TPoint2D.h>
#include <mrpt/math/kmeans.h>
#include <mrpt/random.h>
#include <mrpt/system/CTicTac.h>

#include <iostream>
#include <vector>

using namespace mrpt::math;
using namespace mrpt::gui;
using namespace mrpt::random;
using namespace mrpt::system;
using namespace std;

// ------------------------------------------------------
//              TestKMeans
// ------------------------------------------------------
void TestKMeans()
{
    typedef CVectorFixedDouble<2> CPointType;
    // typedef CVectorFixedFloat<2>  CPointType;

    getRandomGenerator().randomize();
    CTicTac tictac;

    CDisplayWindowPlots win("k-means results");

    cout << "Close the window to end.\n";

    while (win.isOpen())
    {
        // Generate N clusters of random points:
        std::vector<CPointType> points;
        const size_t nClusters =
            2 + (getRandomGenerator().drawUniform32bit() % 4);

        for (size_t cl = 0; cl < nClusters; cl++)
        {
            const size_t nPts = getRandomGenerator().drawUniform<size_t>(5, 50);

            TPoint2D clCenter;
            clCenter.x = getRandomGenerator().drawUniform(0, 10);
            clCenter.y = getRandomGenerator().drawUniform(0, 10);

            for (size_t p = 0; p < nPts; p++)
            {
                CPointType v;
                v[0] = clCenter.x + getRandomGenerator().drawGaussian1D(0, 1);
                v[1] = clCenter.y + getRandomGenerator().drawGaussian1D(0, 1);
                points.push_back(v);
            }
        }

        // do k-means
        std::vector<CPointType> centers;
        vector<int> assignments;
        tictac.Tic();

        const double cost =
            mrpt::math::kmeanspp(nClusters, points, assignments, &centers);

        cout << "Took: " << tictac.Tac() * 1e3 << " ms.\n";
        cout << "cost: " << cost << endl;

        // Show:
        win.clf();
        win.hold_on();
        static const char colors[6] = {'b', 'r', 'k', 'g', 'm', 'c'};

        for (size_t c = 0; c < nClusters; c++)
        {
            CVectorDouble xs, ys;

            for (size_t i = 0; i < points.size(); i++)
            {
                if (size_t(assignments[i]) == c)
                {
                    xs.push_back(points[i][0]);
                    ys.push_back(points[i][1]);
                }
            }
            win.plot(xs, ys, mrpt::format(".4%c", colors[c % 6]));
        }
        win.axis_fit();
        win.axis_equal();

        cout << "Press any key to generate another random dataset...\n";
        win.waitForKey();
    };
}

int main(int argc, char** argv)
{
    try
    {
        TestKMeans();
        return 0;
    }
    catch (const std::exception& e)
    {
        std::cerr << "MRPT error: " << mrpt::exception_to_str(e) << std::endl;
        return -1;
    }
    catch (...)
    {
        printf("Another exception!!");
        return -1;
    }
}