CPointPDFParticles.cpp

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/* +------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)            |
   |                          https://www.mrpt.org/                         |
   |                                                                        |
   | Copyright (c) 2005-2019, 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 "poses-precomp.h"  // Precompiled headers

#include <mrpt/math/ops_containers.h>  // maximum()
#include <mrpt/poses/CPoint3D.h>
#include <mrpt/poses/CPointPDFParticles.h>
#include <mrpt/poses/CPose3D.h>
#include <mrpt/serialization/CArchive.h>
#include <mrpt/system/os.h>
#include <Eigen/Dense>

using namespace mrpt;
using namespace mrpt::poses;
using namespace mrpt::math;
using namespace mrpt::system;

IMPLEMENTS_SERIALIZABLE(CPointPDFParticles, CPointPDF, mrpt::poses)

CPointPDFParticles::CPointPDFParticles(size_t numParticles)
{
    setSize(numParticles);
}

/** Clear all the particles (free memory) */
void CPointPDFParticles::clear() { setSize(0); }
/*---------------------------------------------------------------
        setSize
  ---------------------------------------------------------------*/
void CPointPDFParticles::setSize(
    size_t numberParticles, const mrpt::math::TPoint3Df& defaultValue)
{
    // Free old particles: automatic via smart ptr
    m_particles.resize(numberParticles);
    for (auto& it : m_particles)
    {
        it.log_w = 0;
        it.d.reset(new TPoint3Df(defaultValue));
    }
}

/*---------------------------------------------------------------
                        getMean
  Returns an estimate of the pose, (the mean, or mathematical expectation of the
 PDF)
 ---------------------------------------------------------------*/
void CPointPDFParticles::getMean(CPoint3D& p) const
{
    MRPT_START
    if (m_particles.empty())
        THROW_EXCEPTION("Cannot compute mean since there are zero particles.");

    CParticleList::const_iterator it;
    double sumW = 0;
    double x = 0, y = 0, z = 0;
    for (it = m_particles.begin(); it != m_particles.end(); it++)
    {
        const double w = exp(it->log_w);
        x += it->d->x * w;
        y += it->d->y * w;
        z += it->d->z * w;
        sumW += w;
    }

    ASSERT_(sumW != 0);

    sumW = 1.0 / sumW;

    p.x(x * sumW);
    p.y(y * sumW);
    p.z(z * sumW);

    MRPT_END
}

std::tuple<CMatrixDouble33, CPoint3D> CPointPDFParticles::getCovarianceAndMean()
    const
{
    MRPT_START

    CPoint3D mean;
    CMatrixDouble33 cov;

    getMean(mean);
    cov.setZero();

    size_t i, n = m_particles.size();
    double var_x = 0, var_y = 0, var_p = 0, var_xy = 0, var_xp = 0, var_yp = 0;

    double lin_w_sum = 0;

    for (i = 0; i < n; i++) lin_w_sum += exp(m_particles[i].log_w);
    if (lin_w_sum == 0) lin_w_sum = 1;

    for (i = 0; i < n; i++)
    {
        double w = exp(m_particles[i].log_w) / lin_w_sum;

        double err_x = m_particles[i].d->x - mean.x();
        double err_y = m_particles[i].d->y - mean.y();
        double err_phi = m_particles[i].d->z - mean.z();

        var_x += square(err_x) * w;
        var_y += square(err_y) * w;
        var_p += square(err_phi) * w;
        var_xy += err_x * err_y * w;
        var_xp += err_x * err_phi * w;
        var_yp += err_y * err_phi * w;
    }

    if (n >= 2)
    {
        // Unbiased estimation of variance:
        cov(0, 0) = var_x;
        cov(1, 1) = var_y;
        cov(2, 2) = var_p;

        cov(1, 0) = cov(0, 1) = var_xy;
        cov(2, 0) = cov(0, 2) = var_xp;
        cov(1, 2) = cov(2, 1) = var_yp;
    }

    return {cov, mean};
    MRPT_END
}

uint8_t CPointPDFParticles::serializeGetVersion() const { return 0; }
void CPointPDFParticles::serializeTo(mrpt::serialization::CArchive& out) const
{
    uint32_t N = size();
    out << N;

    for (const auto& m_particle : m_particles)
        out << m_particle.log_w << m_particle.d->x << m_particle.d->y
            << m_particle.d->z;
}

void CPointPDFParticles::serializeFrom(
    mrpt::serialization::CArchive& in, uint8_t version)
{
    switch (version)
    {
        case 0:
        {
            uint32_t N;
            in >> N;
            setSize(N);

            for (auto& m_particle : m_particles)
                in >> m_particle.log_w >> m_particle.d->x >> m_particle.d->y >>
                    m_particle.d->z;
        }
        break;
        default:
            MRPT_THROW_UNKNOWN_SERIALIZATION_VERSION(version);
    };
}

void CPointPDFParticles::copyFrom(const CPointPDF& o)
{
    if (this == &o) return;  // It may be used sometimes

    // Convert to samples:
    THROW_EXCEPTION("NO");
}

/*---------------------------------------------------------------

  ---------------------------------------------------------------*/
bool CPointPDFParticles::saveToTextFile(const std::string& file) const
{
    MRPT_START

    FILE* f = os::fopen(file.c_str(), "wt");
    if (!f) return false;

    size_t i, N = m_particles.size();
    for (i = 0; i < N; i++)
        os::fprintf(
            f, "%f %f %f %e\n", m_particles[i].d->x, m_particles[i].d->y,
            m_particles[i].d->z, m_particles[i].log_w);

    os::fclose(f);
    return true;
    MRPT_END
}

/*---------------------------------------------------------------
                        changeCoordinatesReference
 ---------------------------------------------------------------*/
void CPointPDFParticles::changeCoordinatesReference(
    const CPose3D& newReferenceBase)
{
    TPoint3D pt;
    for (auto& m_particle : m_particles)
    {
        newReferenceBase.composePoint(
            m_particle.d->x, m_particle.d->y, m_particle.d->z,  // In
            pt.x, pt.y, pt.z  // Out
        );
        m_particle.d->x = pt.x;
        m_particle.d->y = pt.y;
        m_particle.d->z = pt.z;
    }
}

/*---------------------------------------------------------------
                        computeKurtosis
 ---------------------------------------------------------------*/
double CPointPDFParticles::computeKurtosis()
{
    MRPT_START

    // kurtosis = \mu^4 / (\sigma^2) -3
    Eigen::Vector3d kurts, mu4, m, var;
    kurts.fill(0);
    mu4.fill(0);
    m.fill(0);
    var.fill(0);

    // Means:
    for (auto& m_particle : m_particles)
    {
        m[0] += m_particle.d->x;
        m[1] += m_particle.d->y;
        m[2] += m_particle.d->z;
    }
    m *= 1.0 / m_particles.size();

    // variances:
    for (auto& m_particle : m_particles)
    {
        var[0] += square(m_particle.d->x - m[0]);
        var[1] += square(m_particle.d->y - m[1]);
        var[2] += square(m_particle.d->z - m[2]);
    }
    var *= 1.0 / m_particles.size();
    var[0] = square(var[0]);
    var[1] = square(var[1]);
    var[2] = square(var[2]);

    // Moment:
    for (auto& m_particle : m_particles)
    {
        mu4[0] += pow(m_particle.d->x - m[0], 4.0);
        mu4[1] += pow(m_particle.d->y - m[1], 4.0);
        mu4[2] += pow(m_particle.d->z - m[2], 4.0);
    }
    mu4 *= 1.0 / m_particles.size();

    // Kurtosis's
    kurts.array() = mu4.array() / var.array();

    return math::maximum(kurts);

    MRPT_END
}

/*---------------------------------------------------------------
                    drawSingleSample
  ---------------------------------------------------------------*/
void CPointPDFParticles::drawSingleSample(CPoint3D& outSample) const
{
    MRPT_UNUSED_PARAM(outSample);
    THROW_EXCEPTION("TO DO!");
}

/*---------------------------------------------------------------
                    bayesianFusion
 ---------------------------------------------------------------*/
void CPointPDFParticles::bayesianFusion(
    const CPointPDF& p1_, const CPointPDF& p2_,
    const double minMahalanobisDistToDrop)
{
    MRPT_UNUSED_PARAM(p1_);
    MRPT_UNUSED_PARAM(p2_);
    MRPT_UNUSED_PARAM(minMahalanobisDistToDrop);
    MRPT_START

    THROW_EXCEPTION("TODO!!!");

    MRPT_END
}