CPose3DPDFGaussianInf.cpp

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/* +------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)            |
   |                          https://www.mrpt.org/                         |
   |                                                                        |
   | Copyright (c) 2005-2020, 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/matrix_serialization.h>
#include <mrpt/math/ops_matrices.h>
#include <mrpt/math/wrap2pi.h>
#include <mrpt/poses/CPose3D.h>
#include <mrpt/poses/CPose3DPDFGaussian.h>
#include <mrpt/poses/CPose3DPDFGaussianInf.h>
#include <mrpt/poses/CPose3DQuatPDFGaussian.h>
#include <mrpt/poses/CPosePDFGaussianInf.h>
#include <mrpt/random.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::random;
using namespace mrpt::system;
using namespace std;

IMPLEMENTS_SERIALIZABLE(CPose3DPDFGaussianInf, CPose3DPDF, mrpt::poses)

/*---------------------------------------------------------------
    Constructor
  ---------------------------------------------------------------*/
CPose3DPDFGaussianInf::CPose3DPDFGaussianInf() : mean(0, 0, 0), cov_inv() {}
/*---------------------------------------------------------------
    Constructor
  ---------------------------------------------------------------*/
CPose3DPDFGaussianInf::CPose3DPDFGaussianInf(
    TConstructorFlags_Poses constructor_dummy_param)
    : mean(UNINITIALIZED_POSE), cov_inv(UNINITIALIZED_MATRIX)
{
    MRPT_UNUSED_PARAM(constructor_dummy_param);
}

/*---------------------------------------------------------------
    Constructor
  ---------------------------------------------------------------*/
CPose3DPDFGaussianInf::CPose3DPDFGaussianInf(
    const CPose3D& init_Mean, const CMatrixDouble66& init_Cov)
    : mean(init_Mean), cov_inv(init_Cov)
{
}

/*---------------------------------------------------------------
    Constructor
  ---------------------------------------------------------------*/
CPose3DPDFGaussianInf::CPose3DPDFGaussianInf(const CPose3D& init_Mean)
    : mean(init_Mean), cov_inv()
{
}

/*---------------------------------------------------------------
                    CPose3DPDFGaussianInf
 ---------------------------------------------------------------*/
CPose3DPDFGaussianInf::CPose3DPDFGaussianInf(const CPose3DQuatPDFGaussian& o)
    : mean(UNINITIALIZED_POSE), cov_inv(UNINITIALIZED_MATRIX)
{
    this->copyFrom(o);
}

/*---------------------------------------------------------------
                        copyFrom
 ---------------------------------------------------------------*/
void CPose3DPDFGaussianInf::copyFrom(const CPose3DQuatPDFGaussian& o)
{
    const CPose3DPDFGaussian p(o);
    this->copyFrom(p);
}

uint8_t CPose3DPDFGaussianInf::serializeGetVersion() const { return 0; }
void CPose3DPDFGaussianInf::serializeTo(
    mrpt::serialization::CArchive& out) const
{
    out << mean;
    mrpt::math::serializeSymmetricMatrixTo(cov_inv, out);
}
void CPose3DPDFGaussianInf::serializeFrom(
    mrpt::serialization::CArchive& in, uint8_t version)
{
    switch (version)
    {
        case 0:
        {
            in >> mean;
            mrpt::math::deserializeSymmetricMatrixFrom(cov_inv, in);
        }
        break;
        default:
            MRPT_THROW_UNKNOWN_SERIALIZATION_VERSION(version);
    };
}

void CPose3DPDFGaussianInf::copyFrom(const CPose3DPDF& o)
{
    if (this == &o) return;  // It may be used sometimes

    if (IS_CLASS(o, CPose3DPDFGaussianInf))
    {  // It's my same class:
        const auto* ptr = dynamic_cast<const CPose3DPDFGaussianInf*>(&o);
        ASSERT_(ptr != nullptr);
        mean = ptr->mean;
        cov_inv = ptr->cov_inv;
    }
    else
    {
        // Convert to gaussian pdf:
        CMatrixDouble66 cov(UNINITIALIZED_MATRIX);
        o.getCovarianceAndMean(cov, mean);
        this->cov_inv = cov.inverse_LLt();
    }
}

void CPose3DPDFGaussianInf::copyFrom(const CPosePDF& o)
{
    if (IS_CLASS(o, CPosePDFGaussianInf))
    {  // cov is already inverted, but it's a 2D pose:
        const auto* ptr = dynamic_cast<const CPosePDFGaussianInf*>(&o);
        ASSERT_(ptr != nullptr);

        mean = CPose3D(ptr->mean);

        // 3x3 inv_cov -> 6x6 inv_cov
        cov_inv.setZero();
        cov_inv(0, 0) = ptr->cov_inv(0, 0);
        cov_inv(1, 1) = ptr->cov_inv(1, 1);
        cov_inv(3, 3) = ptr->cov_inv(2, 2);

        cov_inv(0, 1) = cov_inv(1, 0) = ptr->cov_inv(0, 1);
        cov_inv(0, 3) = cov_inv(3, 0) = ptr->cov_inv(0, 2);
        cov_inv(1, 3) = cov_inv(3, 1) = ptr->cov_inv(1, 2);
    }
    else
    {
        CPose3DPDFGaussian p(UNINITIALIZED_POSE);
        p.copyFrom(o);
        this->copyFrom(p);
    }
}

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

  ---------------------------------------------------------------*/
bool CPose3DPDFGaussianInf::saveToTextFile(const string& file) const
{
    FILE* f = os::fopen(file.c_str(), "wt");
    if (!f) return false;

    os::fprintf(
        f, "%e %e %e %e %e %e\n", mean.x(), mean.y(), mean.z(), mean.yaw(),
        mean.pitch(), mean.roll());

    for (unsigned int i = 0; i < 6; i++)
        os::fprintf(
            f, "%e %e %e %e %e %e\n", cov_inv(i, 0), cov_inv(i, 1),
            cov_inv(i, 2), cov_inv(i, 3), cov_inv(i, 4), cov_inv(i, 5));

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

/*---------------------------------------------------------------
                        changeCoordinatesReference
 ---------------------------------------------------------------*/
void CPose3DPDFGaussianInf::changeCoordinatesReference(
    const CPose3D& newReferenceBase)
{
    MRPT_START

    CPose3DPDFGaussian a;
    a.copyFrom(*this);
    a.changeCoordinatesReference(newReferenceBase);
    this->copyFrom(a);

    MRPT_END
}

/*---------------------------------------------------------------
                    drawSingleSample
 ---------------------------------------------------------------*/
void CPose3DPDFGaussianInf::drawSingleSample(CPose3D& outPart) const
{
    MRPT_UNUSED_PARAM(outPart);
    MRPT_START

    const CMatrixDouble66 cov = cov_inv.inverse_LLt();

    CVectorDouble v;
    getRandomGenerator().drawGaussianMultivariate(v, cov);

    outPart.setFromValues(
        mean.x() + v[0], mean.y() + v[1], mean.z() + v[2], mean.yaw() + v[3],
        mean.pitch() + v[4], mean.roll() + v[5]);

    MRPT_END_WITH_CLEAN_UP(cov_inv.saveToTextFile(
        "__DEBUG_EXC_DUMP_drawSingleSample_COV_INV.txt"););
}

/*---------------------------------------------------------------
                    drawManySamples
 ---------------------------------------------------------------*/
void CPose3DPDFGaussianInf::drawManySamples(
    size_t N, vector<CVectorDouble>& outSamples) const
{
    MRPT_START

    CMatrixDouble66 cov = this->cov_inv.inverse_LLt();

    getRandomGenerator().drawGaussianMultivariateMany(outSamples, N, cov);

    for (auto& outSample : outSamples)
    {
        outSample[0] += mean.x();
        outSample[1] += mean.y();
        outSample[2] += mean.z();
        outSample[3] = math::wrapToPi(outSample[3] + mean.yaw());
        outSample[4] = math::wrapToPi(outSample[4] + mean.pitch());
        outSample[5] = math::wrapToPi(outSample[5] + mean.roll());
    }

    MRPT_END
}

/*---------------------------------------------------------------
                    bayesianFusion
 ---------------------------------------------------------------*/
void CPose3DPDFGaussianInf::bayesianFusion(
    const CPose3DPDF& p1_, const CPose3DPDF& p2_)
{
    MRPT_UNUSED_PARAM(p1_);
    MRPT_UNUSED_PARAM(p2_);

    THROW_EXCEPTION("TO DO!!!");
}

/*---------------------------------------------------------------
                    inverse
 ---------------------------------------------------------------*/
void CPose3DPDFGaussianInf::inverse(CPose3DPDF& o) const
{
    ASSERT_(o.GetRuntimeClass() == CLASS_ID(CPose3DPDFGaussianInf));
    auto& out = dynamic_cast<CPose3DPDFGaussianInf&>(o);

    // This is like: b=(0,0,0)
    //  OUT = b - THIS
    CPose3DPDFGaussianInf b;  // Init: all zeros.
    out = b - *this;
}

/*---------------------------------------------------------------
                            +=
 ---------------------------------------------------------------*/
void CPose3DPDFGaussianInf::operator+=(const CPose3D& Ap)
{
    // COV:
    const CMatrixDouble66 OLD_COV_INV = this->cov_inv;
    CMatrixDouble66 df_dx(UNINITIALIZED_MATRIX), df_du(UNINITIALIZED_MATRIX);

    CPose3DPDF::jacobiansPoseComposition(
        this->mean,  // x
        Ap,  // u
        df_dx, df_du);

    // this->cov = H1*this->cov*H1' + H2*Ap.cov*H2';
    // cov_inv   = ... => The same than above!
    cov_inv = mrpt::math::multiply_HCHt(df_dx, OLD_COV_INV);
    // df_du: Nothing to do, since COV(Ap) = zeros

    // MEAN:
    this->mean = this->mean + Ap;
}

/*---------------------------------------------------------------
                            +=
 ---------------------------------------------------------------*/
void CPose3DPDFGaussianInf::operator+=(const CPose3DPDFGaussianInf& Ap)
{
    CPose3DPDFGaussian a(UNINITIALIZED_POSE);
    CPose3DPDFGaussian b(UNINITIALIZED_POSE);
    a.copyFrom(*this);
    b.copyFrom(Ap);

    a += b;

    this->mean = a.mean;
    cov_inv = a.cov.inverse_LLt();
}

/*---------------------------------------------------------------
                            -=
 ---------------------------------------------------------------*/
void CPose3DPDFGaussianInf::operator-=(const CPose3DPDFGaussianInf& Ap)
{
    CPose3DPDFGaussian a(UNINITIALIZED_POSE);
    CPose3DPDFGaussian b(UNINITIALIZED_POSE);
    a.copyFrom(*this);
    b.copyFrom(Ap);

    a -= b;

    this->mean = a.mean;
    cov_inv = a.cov.inverse_LLt();
}

/*---------------------------------------------------------------
                        evaluatePDF
 ---------------------------------------------------------------*/
double CPose3DPDFGaussianInf::evaluatePDF(const CPose3D& x) const
{
    MRPT_UNUSED_PARAM(x);
    THROW_EXCEPTION("TO DO!!!");
}

/*---------------------------------------------------------------
                        evaluateNormalizedPDF
 ---------------------------------------------------------------*/
double CPose3DPDFGaussianInf::evaluateNormalizedPDF(const CPose3D& x) const
{
    MRPT_UNUSED_PARAM(x);
    THROW_EXCEPTION("TO DO!!!");
}

/*---------------------------------------------------------------
                        enforceCovSymmetry
 ---------------------------------------------------------------*/
void CPose3DPDFGaussianInf::enforceCovSymmetry()
{
    // Differences, when they exist, appear in the ~15'th significant
    //  digit, so... just take one of them arbitrarily!
    for (int i = 0; i < cov_inv.rows() - 1; i++)
        for (int j = i + 1; j < cov_inv.rows(); j++)
            cov_inv(i, j) = cov_inv(j, i);
}

/*---------------------------------------------------------------
                        mahalanobisDistanceTo
 ---------------------------------------------------------------*/
double CPose3DPDFGaussianInf::mahalanobisDistanceTo(
    const CPose3DPDFGaussianInf& theOther)
{
    MRPT_START

    const CMatrixDouble66 cov = this->cov_inv.inverse_LLt();
    const CMatrixDouble66 cov2 = theOther.cov_inv.inverse_LLt();

    CMatrixDouble66 COV_ = cov + cov2;
    CMatrixDouble61 MU = CMatrixDouble61(theOther.mean) - CMatrixDouble61(mean);

    for (int i = 0; i < 6; i++)
    {
        if (COV_(i, i) == 0)
        {
            if (MU(i, 0) != 0)
                return std::numeric_limits<double>::infinity();
            else
                COV_(i, i) = 1;  // Any arbitrary value since
            // MU(i)=0, and this value doesn't
            // affect the result.
        }
    }

    return std::sqrt(mrpt::math::multiply_HtCH_scalar(MU, COV_.inverse_LLt()));

    MRPT_END
}

/*---------------------------------------------------------------
                        operator <<
 ---------------------------------------------------------------*/
ostream& mrpt::poses::operator<<(ostream& out, const CPose3DPDFGaussianInf& obj)
{
    out << "Mean: " << obj.mean << "\n";
    out << "Inverse cov:\n" << obj.cov_inv << "\n";

    return out;
}

/*---------------------------------------------------------------
                        getInvCovSubmatrix2D
 ---------------------------------------------------------------*/
void CPose3DPDFGaussianInf::getInvCovSubmatrix2D(CMatrixDouble& out_cov) const
{
    out_cov.setSize(3, 3);

    for (int i = 0; i < 3; i++)
    {
        int a = i == 2 ? 3 : i;
        for (int j = i; j < 3; j++)
        {
            int b = j == 2 ? 3 : j;
            double f = cov_inv(a, b);
            out_cov(i, j) = f;
            out_cov(j, i) = f;
        }
    }
}

bool mrpt::poses::operator==(
    const CPose3DPDFGaussianInf& p1, const CPose3DPDFGaussianInf& p2)
{
    return p1.mean == p2.mean && p1.cov_inv == p2.cov_inv;
}

CPose3DPDFGaussianInf mrpt::poses::operator+(
    const CPose3DPDFGaussianInf& x, const CPose3DPDFGaussianInf& u)
{
    CPose3DPDFGaussianInf res(x);
    res += u;
    return res;
}

CPose3DPDFGaussianInf mrpt::poses::operator-(
    const CPose3DPDFGaussianInf& x, const CPose3DPDFGaussianInf& u)
{
    CPose3DPDFGaussianInf res(x);
    res -= u;
    return res;
}