Example: random_examples

MRPT includes a C++ platform-independent implementation of the MT19937 algorithm for generating high-quality pseudo-random numbers. The following example demonstrates:

• The usage of random number generators in MRPT. See mrpt::random for the detailed documentation of C++ classes and methods.

• The class mrpt::math::CHistogram.

• The usage of MATLAB-like plots.

C++ example source code:

/* +------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)            |
   |                          https://www.mrpt.org/                         |
   |                                                                        |
   | Copyright (c) 2005-2023, 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/distributions.h>
#include <mrpt/random.h>

#include <iostream>

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

// not run by default. Uncomment corresponding line in the main function.
void TestHist()
{
    CHistogram hist(0.0, 100.0, 10u);
    hist.add(86);
    hist.add(7);
    hist.add(45);

    cout << "Histogram test:" << endl;
    cout << "Should be 1: " << hist.getBinCount(0) << endl;  // Result: "1"
    cout << "Should be 0.33: " << hist.getBinRatio(0)
         << endl;  // Result: "0.33"
}

// ------------------------------------------------------
//              TestRandomGenerators
// ------------------------------------------------------
void TestRandomGenerators()
{
    vector<double> x, y;

    getRandomGenerator().randomize();

    // Uniform numbers integers:
    CDisplayWindowPlots win1("Unif(0,5) (integers)");
    win1.setPos(10, 10);
    win1.resize(400, 400);
    {
        // CVectorDouble v1(100000);
        std::vector<size_t> v1(100000);
        getRandomGenerator().drawUniformVector(v1, 0, 5.999);

        CHistogram hist(-2, 15, 100);
        hist.add(v1);
        hist.getHistogramNormalized(x, y);

        win1.plot(x, y, "b");

        win1.axis_fit();
    }

    // Normalized Gauss:
    CDisplayWindowPlots win2("N(mean=0,std=1)");
    win2.setPos(420, 10);
    win2.resize(400, 400);
    {
        CVectorDouble v1(100000);
        getRandomGenerator().drawGaussian1DVector(v1, 0, 1);

        CHistogram hist(-5, 5, 100);
        hist.add(v1);
        hist.getHistogramNormalized(x, y);

        win2.plot(x, y, "b");

        CVectorDouble y_real(y.size());
        for (CVectorDouble::Index k = 0; k < y_real.size(); k++)
            y_real[k] = mrpt::math::normalPDF(x[k], 0, 1);
        win2.plot(x, y_real, "k-", "real");

        win2.axis_fit();
    }

    // Example Gauss:
    CDisplayWindowPlots win3("N(mean=3,std=2)");
    win3.setPos(10, 430);
    win3.resize(400, 400);
    {
        CVectorDouble v1(100000);
        getRandomGenerator().drawGaussian1DVector(v1, 3, 2);

        CHistogram hist(-5, 15, 100);
        hist.add(v1);
        hist.getHistogramNormalized(x, y);

        win3.plot(x, y, "b");

        CVectorDouble y_real(y.size());
        for (CVectorDouble::Index k = 0; k < y_real.size(); k++)
            y_real[k] = mrpt::math::normalPDF(x[k], 3, 2);
        win3.plot(x, y_real, "k-", "real");

        win3.axis_fit();
    }

    // Example multi-variate Gauss:
    CDisplayWindowPlots win4("N(mean=[3 4],var=[4 -2;-2 4])");
    win4.setPos(420, 430);
    win4.resize(400, 400);
    {
        vector<CVectorDouble> v1;
        CVectorDouble Mean(2);
        Mean[0] = 3;
        Mean[1] = 2;

        CMatrixDouble22 cov;
        cov.fromMatlabStringFormat("[7.5 -7;-7 8]");

        getRandomGenerator().drawGaussianMultivariateMany(
            v1, 10000, cov, &Mean);

#if 0
        CVectorDouble m;
        CMatrixDouble c;
        mrpt::math::meanAndCov(v1,m,c);
        cout << "Mean: " << m << endl;
        cout << "Std: " << endl << c << endl;
#endif

        // pass to (x,y) vectors:
        CVectorDouble vx(v1.size()), vy(v1.size());
        for (size_t i = 0; i < v1.size(); i++)
        {
            vx[i] = v1[i][0];
            vy[i] = v1[i][1];
        }

        win4.plot(vx, vy, "b.3");

        win4.plotEllipse(
            Mean[0], Mean[1], cov, 3.0, "k-2", "99% ellipse", true);

        win4.axis_fit();
    }

    win4.waitForKey();
}

// ------------------------------------------------------
//                      MAIN
// ------------------------------------------------------
int main()
{
    try
    {
        // TestHist();
        TestRandomGenerators();

        return 0;
    }
    catch (const std::exception& e)
    {
        std::cerr << "MRPT error: " << mrpt::exception_to_str(e) << std::endl;
        return -1;
    }
}