CGasConcentrationGridMap2D.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 "maps-precomp.h"  // Precomp header

#include <mrpt/core/round.h>  // round()
#include <mrpt/img/color_maps.h>
#include <mrpt/io/CFileGZInputStream.h>
#include <mrpt/io/CFileGZOutputStream.h>
#include <mrpt/maps/CGasConcentrationGridMap2D.h>
#include <mrpt/math/CMatrixF.h>
#include <mrpt/math/ops_containers.h>
#include <mrpt/obs/CObservationGasSensors.h>
#include <mrpt/opengl/CArrow.h>
#include <mrpt/opengl/CSetOfObjects.h>
#include <mrpt/serialization/CArchive.h>
#include <mrpt/system/CTicTac.h>
#include <mrpt/system/datetime.h>
#include <mrpt/system/filesystem.h>
#include <mrpt/system/os.h>

using namespace mrpt;
using namespace mrpt::maps;
using namespace mrpt::obs;
using namespace mrpt::io;
using namespace mrpt::poses;
using namespace mrpt::img;
using namespace std;
using namespace mrpt::math;

//  =========== Begin of Map definition ============
MAP_DEFINITION_REGISTER(
    "mrpt::maps::CGasConcentrationGridMap2D,gasGrid",
    mrpt::maps::CGasConcentrationGridMap2D)

CGasConcentrationGridMap2D::TMapDefinition::TMapDefinition()

    = default;

void CGasConcentrationGridMap2D::TMapDefinition::
	loadFromConfigFile_map_specific(
        const mrpt::config::CConfigFileBase& source,
        const std::string& sectionNamePrefix)
{
    // [<sectionNamePrefix>+"_creationOpts"]
    const std::string sSectCreation =
        sectionNamePrefix + string("_creationOpts");
    MRPT_LOAD_CONFIG_VAR(min_x, float, source, sSectCreation);
    MRPT_LOAD_CONFIG_VAR(max_x, float, source, sSectCreation);
    MRPT_LOAD_CONFIG_VAR(min_y, float, source, sSectCreation);
    MRPT_LOAD_CONFIG_VAR(max_y, float, source, sSectCreation);
    MRPT_LOAD_CONFIG_VAR(resolution, float, source, sSectCreation);
    mapType = source.read_enum<CGasConcentrationGridMap2D::TMapRepresentation>(
        sSectCreation, "mapType", mapType);

    insertionOpts.loadFromConfigFile(
        source, sectionNamePrefix + string("_insertOpts"));
}

void CGasConcentrationGridMap2D::TMapDefinition::dumpToTextStream_map_specific(
    std::ostream& out) const
{
    out << mrpt::format(
        "MAP TYPE                                  = %s\n",
        mrpt::typemeta::TEnumType<
            CGasConcentrationGridMap2D::TMapRepresentation>::value2name(mapType)
            .c_str());
    LOADABLEOPTS_DUMP_VAR(min_x, float);
    LOADABLEOPTS_DUMP_VAR(max_x, float);
    LOADABLEOPTS_DUMP_VAR(min_y, float);
    LOADABLEOPTS_DUMP_VAR(max_y, float);
    LOADABLEOPTS_DUMP_VAR(resolution, float);

    this->insertionOpts.dumpToTextStream(out);
}

mrpt::maps::CMetricMap*
    CGasConcentrationGridMap2D::internal_CreateFromMapDefinition(
        const mrpt::maps::TMetricMapInitializer& _def)
{
    const CGasConcentrationGridMap2D::TMapDefinition& def =
        *dynamic_cast<const CGasConcentrationGridMap2D::TMapDefinition*>(&_def);
    auto* obj = new CGasConcentrationGridMap2D(
        def.mapType, def.min_x, def.max_x, def.min_y, def.max_y,
        def.resolution);
    obj->insertionOptions = def.insertionOpts;
    return obj;
}
//  =========== End of Map definition Block =========

IMPLEMENTS_SERIALIZABLE(
    CGasConcentrationGridMap2D, CRandomFieldGridMap2D, mrpt::maps)

// Short-cut:
#define LUT_TABLE (*(LUT.table))

/*---------------------------------------------------------------
                        Constructor
  ---------------------------------------------------------------*/
CGasConcentrationGridMap2D::CGasConcentrationGridMap2D(
    TMapRepresentation mapType, float x_min, float x_max, float y_min,
    float y_max, float resolution)
    : CRandomFieldGridMap2D(mapType, x_min, x_max, y_min, y_max, resolution),
      insertionOptions()
{
    // Override defaults:
    insertionOptions.GMRF_saturate_min = 0;
    insertionOptions.GMRF_saturate_max = 1;
    insertionOptions.GMRF_lambdaObsLoss = 1.0;

    // Set the grid to initial values (and adjust covariance matrices,...)
    //  Also, calling clear() is mandatory to end initialization of our base
    //  class (read note in CRandomFieldGridMap2D::CRandomFieldGridMap2D)
    CMetricMap::clear();

    // Create WindGrids with same dimensions that the original map
    windGrid_module.setSize(x_min, x_max, y_min, y_max, resolution);
    windGrid_direction.setSize(x_min, x_max, y_min, y_max, resolution);

    // initialize counter for advection simulation
    timeLastSimulated = mrpt::system::now();
}

CGasConcentrationGridMap2D::~CGasConcentrationGridMap2D() = default;
/*---------------------------------------------------------------
                        clear
  ---------------------------------------------------------------*/
void CGasConcentrationGridMap2D::internal_clear()
{
    // Just do the generic clear:
    CRandomFieldGridMap2D::internal_clear();

    // Anything else special for this derived class?

    if (insertionOptions.useWindInformation)
    {
        // Set default values of the wind grid
        windGrid_module.fill(insertionOptions.default_wind_speed);
        windGrid_direction.fill(insertionOptions.default_wind_direction);

        /*float S = windGrid_direction.getSizeX() *
windGrid_direction.getSizeY();

        for( unsigned int y=windGrid_direction.getSizeY()/2;
y<windGrid_direction.getSizeY(); y++ )
        {
            for( unsigned int x=0; x<windGrid_direction.getSizeX(); x++ )
            {
                double * wind_cell = windGrid_direction.cellByIndex(x,y);
                *wind_cell =  3*3.141516/2;
}
        }*/

        // Generate Look-Up Table of the Gaussian weights due to wind advection.
        if (!build_Gaussian_Wind_Grid())
        {
            // mrpt::system::pause();
            THROW_EXCEPTION("Problem with LUT wind table");
        }
    }
}

/*---------------------------------------------------------------
                        insertObservation
  ---------------------------------------------------------------*/
bool CGasConcentrationGridMap2D::internal_insertObservation(
    const CObservation& obs, const CPose3D* robotPose)
{
    MRPT_START

    CPose2D robotPose2D;
    CPose3D robotPose3D;

    if (robotPose)
    {
        robotPose2D = CPose2D(*robotPose);
        robotPose3D = (*robotPose);
    }
    else
    {
        // Default values are (0,0,0)
    }

    if (IS_CLASS(obs, CObservationGasSensors))
    {
        /********************************************************************
                    OBSERVATION TYPE: CObservationGasSensors
        ********************************************************************/
        const auto& o = dynamic_cast<const CObservationGasSensors&>(obs);

        if (o.sensorLabel.compare(insertionOptions.gasSensorLabel) == 0)
        {
            float sensorReading;
            CPose2D sensorPose;

            if (o.sensorLabel.compare("MCEnose") == 0 ||
                o.sensorLabel.compare("Full_MCEnose") == 0)
            {
                ASSERT_(o.m_readings.size() > insertionOptions.enose_id);
                const CObservationGasSensors::TObservationENose* it =
                    &o.m_readings[insertionOptions.enose_id];

                // Compute the 3D sensor pose in world coordinates:
                sensorPose = CPose2D(
                    CPose3D(robotPose2D) + CPose3D(it->eNosePoseOnTheRobot));

                // Compute the sensor reading value (Volts):
                if (insertionOptions.gasSensorType == 0x0000)
                {  // compute the mean
                    sensorReading = d2f(math::mean(it->readingsVoltage));
                }
                else
                {
                    // Look for the correct sensor type
                    size_t i;
                    for (i = 0; i < it->sensorTypes.size(); i++)
                    {
                        if (it->sensorTypes.at(i) ==
                            int(insertionOptions.gasSensorType))
                            break;
                    }

                    if (i < it->sensorTypes.size())
                    {
                        sensorReading = it->readingsVoltage[i];
                    }
                    else
                    {
                        cout << "Sensor especified not found, compute default "
                                "mean value"
                             << endl;
                        sensorReading = d2f(math::mean(it->readingsVoltage));
                    }
                }
            }
            else  //"GDM, RAE_PID, ENOSE_SIMUL
            {
                const CObservationGasSensors::TObservationENose* it =
                    &o.m_readings[0];
                // Compute the 3D sensor pose in world coordinates:
                sensorPose = CPose2D(
                    CPose3D(robotPose2D) + CPose3D(it->eNosePoseOnTheRobot));
                sensorReading = it->readingsVoltage[0];
            }

            // Normalization:
            sensorReading = (sensorReading - insertionOptions.R_min) /
                            (insertionOptions.R_max - insertionOptions.R_min);

            // Update the gross estimates of mean/vars for the whole reading
            // history (see IROS2009 paper):
            m_average_normreadings_mean =
                (sensorReading +
                 m_average_normreadings_count * m_average_normreadings_mean) /
                (1 + m_average_normreadings_count);
            m_average_normreadings_var =
                (square(sensorReading - m_average_normreadings_mean) +
                 m_average_normreadings_count * m_average_normreadings_var) /
                (1 + m_average_normreadings_count);
            m_average_normreadings_count++;

            // Finally, do the actual map update with that value:
            this->insertIndividualReading(
                sensorReading,
                mrpt::math::TPoint2D(sensorPose.x(), sensorPose.y()));
            return true;  // Done!
        }  // endif correct "gasSensorLabel"
    }  // end if "CObservationGasSensors"

    return false;
    MRPT_END
}

/*---------------------------------------------------------------
                        computeObservationLikelihood
  ---------------------------------------------------------------*/
double CGasConcentrationGridMap2D::internal_computeObservationLikelihood(
    [[maybe_unused]] const CObservation& obs,
    [[maybe_unused]] const CPose3D& takenFrom)
{
    THROW_EXCEPTION("Not implemented yet!");
}

uint8_t CGasConcentrationGridMap2D::serializeGetVersion() const { return 5; }
void CGasConcentrationGridMap2D::serializeTo(
    mrpt::serialization::CArchive& out) const
{
    dyngridcommon_writeToStream(out);

    // To assure compatibility: The size of each cell:
    auto n = static_cast<uint32_t>(sizeof(TRandomFieldCell));
    out << n;

    // Save the map contents:
    n = static_cast<uint32_t>(m_map.size());
    out << n;

// Save the "m_map": This requires special handling for big endian systems:
#if MRPT_IS_BIG_ENDIAN
    for (uint32_t i = 0; i < n; i++)
    {
        out << m_map[i].kf_mean() << m_map[i].dm_mean << m_map[i].dmv_var_mean;
    }
#else
    // Little endian: just write all at once:
    out.WriteBuffer(
        &m_map[0],
        sizeof(m_map[0]) * m_map.size());  // TODO: Do this endianness safe!!
#endif

    // Version 1: Save the insertion options:
    out << uint8_t(m_mapType) << m_cov << m_stackedCov;

    out << insertionOptions.sigma << insertionOptions.cutoffRadius
        << insertionOptions.R_min << insertionOptions.R_max
        << insertionOptions.KF_covSigma << insertionOptions.KF_initialCellStd
        << insertionOptions.KF_observationModelNoise
        << insertionOptions.KF_defaultCellMeanValue
        << insertionOptions.KF_W_size;

    // New in v3:
    out << m_average_normreadings_mean << m_average_normreadings_var
        << uint64_t(m_average_normreadings_count);

    out << genericMapParams;  // v4
}

// Aux struct used below (must be at global scope for STL):
struct TOldCellTypeInVersion1
{
    float mean, std;
    float w, wr;
};

void CGasConcentrationGridMap2D::serializeFrom(
    mrpt::serialization::CArchive& in, uint8_t version)
{
    switch (version)
    {
        case 0:
        case 1:
        case 2:
        case 3:
        case 4:
        case 5:
        {
            dyngridcommon_readFromStream(in, version < 5);

            // To assure compatibility: The size of each cell:
            uint32_t n;
            in >> n;

            if (version < 2)
            {  // Converter from old versions <=1
                ASSERT_(
                    n == static_cast<uint32_t>(sizeof(TOldCellTypeInVersion1)));
                // Load the map contents in an aux struct:
                in >> n;
                vector<TOldCellTypeInVersion1> old_map(n);
                in.ReadBuffer(&old_map[0], sizeof(old_map[0]) * old_map.size());

                // Convert to newer format:
                m_map.resize(n);
                for (size_t k = 0; k < n; k++)
                {
                    m_map[k].kf_mean() =
                        (old_map[k].w != 0) ? old_map[k].wr : old_map[k].mean;
                    m_map[k].kf_std() =
                        (old_map[k].w != 0) ? old_map[k].w : old_map[k].std;
                }
            }
            else
            {
                ASSERT_EQUAL_(
                    n, static_cast<uint32_t>(sizeof(TRandomFieldCell)));
                // Load the map contents:
                in >> n;
                m_map.resize(n);

// Read the note in writeToStream()
#if MRPT_IS_BIG_ENDIAN
                for (uint32_t i = 0; i < n; i++)
                    in >> m_map[i].kf_mean() >> m_map[i].dm_mean >>
                        m_map[i].dmv_var_mean;
#else
                // Little endian: just read all at once:
                in.ReadBuffer(&m_map[0], sizeof(m_map[0]) * m_map.size());
#endif
            }

            // Version 1: Insertion options:
            if (version >= 1)
            {
                uint8_t i;
                in >> i;
                m_mapType = TMapRepresentation(i);

                in >> m_cov >> m_stackedCov;

                in >> insertionOptions.sigma >> insertionOptions.cutoffRadius >>
                    insertionOptions.R_min >> insertionOptions.R_max >>
                    insertionOptions.KF_covSigma >>
                    insertionOptions.KF_initialCellStd >>
                    insertionOptions.KF_observationModelNoise >>
                    insertionOptions.KF_defaultCellMeanValue >>
                    insertionOptions.KF_W_size;
            }

            if (version >= 3)
            {
                uint64_t N;
                in >> m_average_normreadings_mean >>
                    m_average_normreadings_var >> N;
                m_average_normreadings_count = N;
            }

            if (version >= 4) in >> genericMapParams;

            m_hasToRecoverMeanAndCov = true;
        }
        break;
        default:
            MRPT_THROW_UNKNOWN_SERIALIZATION_VERSION(version);
    };
}

/*---------------------------------------------------------------
                    TInsertionOptions
 ---------------------------------------------------------------*/
CGasConcentrationGridMap2D::TInsertionOptions::TInsertionOptions()
    :

      gasSensorLabel("MCEnose"),
      // By default use the mean between all e-nose sensors
      windSensorLabel("windSensor")

{
}

void CGasConcentrationGridMap2D::TInsertionOptions::dumpToTextStream(
    std::ostream& out) const
{
    out << "\n----------- [CGasConcentrationGridMap2D::TInsertionOptions] "
           "------------ \n\n";
    out << "[TInsertionOptions.Common] ------------ \n\n";
    internal_dumpToTextStream_common(
        out);  // Common params to all random fields maps:

    out << "[TInsertionOptions.GasSpecific] ------------ \n\n";
    out << mrpt::format(
        "gasSensorLabel                         = %s\n",
        gasSensorLabel.c_str());
    out << mrpt::format(
        "enose_id                               = %u\n", (unsigned)enose_id);
    out << mrpt::format(
        "gasSensorType                          = %u\n",
        (unsigned)gasSensorType);
    out << mrpt::format(
        "windSensorLabel                            = %s\n",
        windSensorLabel.c_str());
    out << mrpt::format(
        "useWindInformation                     = %u\n", useWindInformation);

    out << mrpt::format(
        "advectionFreq                          = %f\n", advectionFreq);
    out << mrpt::format(
        "default_wind_direction                 = %f\n",
        default_wind_direction);
    out << mrpt::format(
        "default_wind_speed                     = %f\n", default_wind_speed);
    out << mrpt::format(
        "std_windNoise_phi                      = %f\n", std_windNoise_phi);
    out << mrpt::format(
        "std_windNoise_mod                      = %f\n", std_windNoise_mod);

    out << "\n";
}

/*---------------------------------------------------------------
                    loadFromConfigFile
  ---------------------------------------------------------------*/
void CGasConcentrationGridMap2D::TInsertionOptions::loadFromConfigFile(
    const mrpt::config::CConfigFileBase& iniFile, const std::string& section)
{
    // Common data fields for all random fields maps:
    internal_loadFromConfigFile_common(iniFile, section);

    // Specific data fields for gasGridMaps
    gasSensorLabel = iniFile.read_string(
        section.c_str(), "gasSensorLabel", "Full_MCEnose", true);
    enose_id = iniFile.read_int(section.c_str(), "enoseID", enose_id);
    // Read sensor type in hexadecimal
    {
        std::string sensorType_str =
            iniFile.read_string(section.c_str(), "gasSensorType", "-1", true);
        int tmpSensorType;
        stringstream convert(sensorType_str);
        convert >> std::hex >> tmpSensorType;

        if (tmpSensorType >= 0)
        {
            // Valid number found:
            gasSensorType = tmpSensorType;
        }
        else
        {  // fall back to old name, or default to current value:
            gasSensorType = iniFile.read_int(
                section.c_str(), "KF_sensorType", gasSensorType, true);
        }
    }
    windSensorLabel = iniFile.read_string(
        section.c_str(), "windSensorLabel", "Full_MCEnose", true);

    // Indicates if wind information must be used for Advection Simulation
    useWindInformation =
        iniFile.read_bool(section.c_str(), "useWindInformation", "false", true);

    //(rad) The initial/default value of the wind direction
    default_wind_direction =
        iniFile.read_float(section.c_str(), "default_wind_direction", 0, false);
    //(m/s) The initial/default value of the wind speed
    default_wind_speed =
        iniFile.read_float(section.c_str(), "default_wind_speed", 0, false);

    //(rad) The noise in the wind direction
    std_windNoise_phi =
        iniFile.read_float(section.c_str(), "std_windNoise_phi", 0, false);
    //(m/s) The noise in the wind strenght
    std_windNoise_mod =
        iniFile.read_float(section.c_str(), "std_windNoise_mod", 0, false);

    //(m/s) The noise in the wind strenght
    advectionFreq =
        iniFile.read_float(section.c_str(), "advectionFreq", 1, true);
}

/*---------------------------------------------------------------
                        getAs3DObject
---------------------------------------------------------------*/
void CGasConcentrationGridMap2D::getAs3DObject(
    mrpt::opengl::CSetOfObjects::Ptr& outObj) const
{
    MRPT_START
    if (!genericMapParams.enableSaveAs3DObject) return;
    CRandomFieldGridMap2D::getAs3DObject(outObj);
    MRPT_END
}

/*---------------------------------------------------------------
                        getAs3DObject
---------------------------------------------------------------*/
void CGasConcentrationGridMap2D::getAs3DObject(
    mrpt::opengl::CSetOfObjects::Ptr& meanObj,
    mrpt::opengl::CSetOfObjects::Ptr& varObj) const
{
    MRPT_START
    if (!genericMapParams.enableSaveAs3DObject) return;
    CRandomFieldGridMap2D::getAs3DObject(meanObj, varObj);
    MRPT_END
}

/*---------------------------------------------------------------
                        getWindAs3DObject
---------------------------------------------------------------*/
void CGasConcentrationGridMap2D::getWindAs3DObject(
    mrpt::opengl::CSetOfObjects::Ptr& windObj) const
{
    // Return an arrow map of the wind state (module(color) and direction).
    float scale = 0.2f;
    size_t arrow_separation =
        5;  // distance between arrows, expresed as times the cell resolution

    // map limits
    float x_min = d2f(getXMin());
    float x_max = d2f(getXMax());
    float y_min = d2f(getYMin());
    float y_max = d2f(getYMax());
    float resol = d2f(getResolution());

    // Ensure map dimensions match with wind map
    unsigned int wind_map_size =
        windGrid_direction.getSizeX() * windGrid_direction.getSizeY();
    ASSERT_(
        wind_map_size ==
        windGrid_module.getSizeX() * windGrid_module.getSizeY());
    if (m_map.size() != wind_map_size)
    {
        cout << " GAS MAP DIMENSIONS DO NOT MATCH WIND MAP " << endl;
        // mrpt::system::pause();
    }

    size_t cx, cy;
    vector<float> xs, ys;

    // xs: array of X-axis values
    xs.resize(floor((x_max - x_min) / (arrow_separation * resol)));
    for (cx = 0; cx < xs.size(); cx++)
        xs[cx] = x_min + arrow_separation * resol * cx;

    // ys: array of X-axis values
    ys.resize(floor((y_max - y_min) / (arrow_separation * resol)));
    for (cy = 0; cy < ys.size(); cy++)
        ys[cy] = y_min + arrow_separation * resol * cy;

    for (cy = 0; cy < ys.size(); cy++)
    {
        for (cx = 0; cx < xs.size(); cx++)
        {
            // Cell values [0,inf]:
            double dir_xy = *windGrid_direction.cellByPos(xs[cx], ys[cy]);
            double mod_xy = *windGrid_module.cellByPos(xs[cx], ys[cy]);

            auto obj = mrpt::opengl::CArrow::Create(
                xs[cx], ys[cy], 0.f, xs[cx] + scale * (float)cos(dir_xy),
                ys[cy] + scale * (float)sin(dir_xy), 0.f, 1.15f * scale,
                0.3f * scale, 0.35f * scale);

            float r, g, b;
            jet2rgb(mod_xy, r, g, b);
            obj->setColor(r, g, b);

            windObj->insert(obj);
        }
    }
}

/*---------------------------------------------------------------
                        increaseUncertainty
---------------------------------------------------------------*/
void CGasConcentrationGridMap2D::increaseUncertainty(
    const double STD_increase_value)
{
    // Increase cell variance
    //  unsigned int cx,cy;
    //  double memory_retention;

    m_hasToRecoverMeanAndCov = true;
    for (size_t it = 0; it < m_map.size(); it++)
    {
        m_stackedCov(it, 0) = m_stackedCov(it, 0) + STD_increase_value;
    }

    // Update m_map.kf_std
    recoverMeanAndCov();

    // for (cy=0; cy<m_size_y; cy++)
    //   {
    //       for (cx=0; cx<m_size_x; cx++)
    //       {
    //      // Forgetting_curve --> memory_retention =
    // exp(-time/memory_relative_strenght)
    //      memory_retention = exp(- mrpt::system::timeDifference(m_map[cx +
    // cy*m_size_x].last_updated, now()) / memory_relative_strenght);
    //      //Update Uncertainty (STD)
    //      m_map[cx + cy*m_size_x].kf_std = 1 - ( (1-m_map[cx +
    // cy*m_size_x].updated_std) * memory_retention );
    //       }
    //   }
}

/*---------------------------------------------------------------
                        simulateAdvection
---------------------------------------------------------------*/
bool CGasConcentrationGridMap2D::simulateAdvection(double STD_increase_value)
{
    /* 1- Ensure we can use Wind Information
    -------------------------------------------------*/
    if (!insertionOptions.useWindInformation) return false;

    // Get time since last simulation
    double At =
        mrpt::system::timeDifference(timeLastSimulated, mrpt::system::now());
    cout << endl << " - At since last simulation = " << At << "seconds" << endl;
    // update time of last updated.
    timeLastSimulated = mrpt::system::now();

    /* 3- Build Transition Matrix (SA)
      This Matrix contains the probabilities of each cell
      to "be displaced" to other cells by the wind effect.
    ------------------------------------------------------*/
    mrpt::system::CTicTac tictac;
    size_t i = 0, c = 0;
    int cell_i_cx, cell_i_cy;
    float mu_phi, mu_r, mu_modwind;
    const size_t N = m_map.size();
    mrpt::math::CMatrixF A(N, N);
    A.fill(0.0);
    // std::vector<double> row_sum(N,0.0);
    auto* row_sum = (double*)calloc(N, sizeof(double));

    try
    {
        // Ensure map dimensions match with wind map
        unsigned int wind_map_size =
            windGrid_direction.getSizeX() * windGrid_direction.getSizeY();
        ASSERT_(
            wind_map_size ==
            windGrid_module.getSizeX() * windGrid_module.getSizeY());
        if (N != wind_map_size)
        {
            cout << " GAS MAP DIMENSIONS DO NOT MATCH WIND INFORMATION "
                 << endl;
            // mrpt::system::pause();
        }

        tictac.Tic();

        // Generate Sparse Matrix of the wind advection SA
        for (i = 0; i < N; i++)
        {
            // Cell_i indx and coordinates
            idx2cxcy(i, cell_i_cx, cell_i_cy);

            // Read dirwind value of cell i
            mu_phi = *windGrid_direction.cellByIndex(
                cell_i_cx, cell_i_cy);  //[0,2*pi]
            unsigned int phi_indx = round(mu_phi / LUT.phi_inc);

            // Read modwind value of cell i
            mu_modwind =
                *windGrid_module.cellByIndex(cell_i_cx, cell_i_cy);  //[0,inf)
            mu_r = mu_modwind * At;
            if (mu_r > LUT.max_r) mu_r = LUT.max_r;
            unsigned int r_indx = round(mu_r / LUT.r_inc);

            // Evaluate LUT
            ASSERT_(phi_indx < LUT.phi_count);
            ASSERT_(r_indx < LUT.r_count);

            // define label
            vector<TGaussianCell>& cells_to_update =
                LUT_TABLE[phi_indx][r_indx];

            // Generate Sparse Matrix with the wind weights "SA"
            for (auto& ci : cells_to_update)
            {
                int final_cx = cell_i_cx + ci.cx;
                int final_cy = cell_i_cy + ci.cy;
                // Check if affected cells is within the map
                if ((final_cx >= 0) && (final_cx < (int)getSizeX()) &&
                    (final_cy >= 0) && (final_cy < (int)getSizeY()))
                {
                    int final_idx = final_cx + final_cy * getSizeX();

                    // Add Value to SA Matrix
                    if (ci.value != 0.0)
                    {
                        A(final_idx, i) = ci.value;
                        row_sum[final_idx] += ci.value;
                    }
                }
            }  // end-for ci
        }  // end-for cell i

        cout << " - SA matrix computed in " << tictac.Tac() << "s" << endl
             << endl;
    }
    catch (const std::exception& e)
    {
        cout << " #########  EXCEPTION computing Transition Matrix (A) "
                "##########\n: "
             << e.what() << endl;
        cout << "on cell i= " << i << "  c=" << c << endl << endl;
        return false;
    }

    /* Update Mean + Variance as a Gaussian Mixture
    ------------------------------------------------*/
    try
    {
        tictac.Tic();
        // std::vector<double> new_means(N,0.0);
        auto* new_means = (double*)calloc(N, sizeof(double));
        // std::vector<double> new_variances(N,0.0);
        auto* new_variances = (double*)calloc(N, sizeof(double));

        for (size_t it_i = 0; it_i < N; it_i++)
        {
            //--------
            // mean
            //--------
            for (size_t it_j = 0; it_j < N; it_j++)
            {
                if (m_map[it_j].kf_mean() != 0 && A(it_i, it_j) != 0)
                {
                    if (row_sum[it_i] >= 1)
                        new_means[it_i] += (A(it_i, it_j) / row_sum[it_i]) *
                                           m_map[it_j].kf_mean();
                    else
                        new_means[it_i] +=
                            A(it_i, it_j) * m_map[it_j].kf_mean();
                }
            }

            //----------
            // variance
            //----------
            // Consider special case (borders cells)
            if (row_sum[it_i] < 1)
                new_variances[it_i] =
                    (1 - row_sum[it_i]) *
                    square(insertionOptions.KF_initialCellStd);

            for (size_t it_j = 0; it_j < N; it_j++)
            {
                if (A(it_i, it_j) != 0)
                {
                    if (row_sum[it_i] >= 1)
                        new_variances[it_i] +=
                            (A(it_i, it_j) / row_sum[it_i]) *
                            (m_stackedCov(it_j, 0) +
                             square(m_map[it_j].kf_mean() - new_means[it_i]));
                    else
                        new_variances[it_i] +=
                            A(it_i, it_j) *
                            (m_stackedCov(it_j, 0) +
                             square(m_map[it_j].kf_mean() - new_means[it_i]));
                }
            }
        }

        // Update means and Cov of the Kalman filter state
        for (size_t it_i = 0; it_i < N; it_i++)
        {
            m_map[it_i].kf_mean() = new_means[it_i];  // means

            // Variances
            // Scale the Current Covariances with the new variances
            for (size_t it_j = 0; it_j < N; it_j++)
            {
                m_stackedCov(it_i, it_j) =
                    (m_stackedCov(it_i, it_j) / m_stackedCov(it_i, it_i)) *
                    new_variances[it_i];  // variances
                m_stackedCov(it_j, it_i) = m_stackedCov(it_i, it_j);
            }
        }
        m_hasToRecoverMeanAndCov = true;
        recoverMeanAndCov();

        cout << " - Mean&Var updated in " << tictac.Tac() << "s" << endl;

        // Free Memory
        free(row_sum);
        free(new_means);
        free(new_variances);
    }
    catch (const std::exception& e)
    {
        cout << " #########  EXCEPTION Updating Covariances ##########\n: "
             << e.what() << endl;
        cout << "on row i= " << i << "  column c=" << c << endl << endl;
        return false;
    }

    // cout << " Increasing general STD..." << endl;
    increaseUncertainty(STD_increase_value);

    return true;
}

/*---------------------------------------------------------------
                        build_Gaussian_Wind_Grid
---------------------------------------------------------------*/

bool CGasConcentrationGridMap2D::build_Gaussian_Wind_Grid()
/** Builds a LookUp table with the values of the Gaussian Weights result of the
wind advection
*   for a specific condition.
*
*   The LUT contains the values of the Gaussian Weigths and the references to
the cell indexes to be applied.
*   Since the LUT is independent of the wind direction and angle, it generates
the Gaussian Weights for different configurations
*   of wind angle and module values.
*
*   To increase precission, each cell of the grid is sub-divided in subcells of
smaller size.

*   cell_i --> Cell origin (We consider our reference system in the bottom left
corner of cell_i ).
               Is the cell that contains the gas measurement which will be
propagated by the wind.
               The wind propagates in the shape of a 2D Gaussian with center in
the target cell (cell_j)
*   cell_j --> Target cell. Is the cell where falls the center of the Gaussian
that models the propagation of the gas comming from cell_i.
*/

{
    cout << endl << "---------------------------------" << endl;
    cout << " BUILDING GAUSSIAN WIND WEIGHTS " << endl;
    cout << "---------------------------------" << endl << endl;

    //-----------------------------
    //          PARAMS
    //-----------------------------
    LUT.resolution = getResolution();  // resolution of the grid-cells (m)
    LUT.std_phi =
        insertionOptions
            .std_windNoise_phi;  // Standard Deviation in wind Angle (cte)
    LUT.std_r = insertionOptions.std_windNoise_mod /
                insertionOptions
                    .advectionFreq;  // Standard Deviation in wind module (cte)
    std::string filename = format(
        "Gaussian_Wind_Weights_res(%f)_stdPhi(%f)_stdR(%f).gz", LUT.resolution,
        LUT.std_phi, LUT.std_r);

    // Fixed Params:
    LUT.phi_inc = M_PIf / 8;  // Increment in the wind Angle. (rad)
    LUT.phi_count =
        round(2 * M_PI / LUT.phi_inc) + 1;  // Number of angles to generate
    LUT.r_inc = 0.1f;  // Increment in the wind Module. (m)
    LUT.max_r = 2;  // maximum distance (m) to simulate
    LUT.r_count =
        round(LUT.max_r / LUT.r_inc) + 1;  // Number of wind modules to simulate

    LUT.table = new vector<vector<vector<TGaussianCell>>>(
        LUT.phi_count,
        vector<vector<TGaussianCell>>(LUT.r_count, vector<TGaussianCell>()));

    // LUT.table = new
    // vector<vector<vector<vector<vector<TGaussianCell>>>>>(LUT.subcell_count,
    // vector<vector<vector<vector<TGaussianCell>>>>(LUT.subcell_count,
    // vector<vector<vector<TGaussianCell>>>(LUT.phi_count,
    // vector<vector<TGaussianCell>>(LUT.r_count,vector<TGaussianCell>()) ) ) );

    //-----------------------------
    //    Check if file exists
    //-----------------------------

    cout << "Looking for file: " << filename.c_str() << endl;

    if (mrpt::system::fileExists(filename.c_str()))
    {
        // file exists. Load lookUptable from file
        cout << "LookUp table found for this configuration. Loading..." << endl;
        return load_Gaussian_Wind_Grid_From_File();
    }
    else
    {
        // file does not exists. Generate LookUp table.
        cout << "LookUp table NOT found. Generating table..." << endl;

        bool debug = true;
        FILE* debug_file;

        if (debug)
        {
            debug_file = fopen("simple_LUT.txt", "w");
            fprintf(
                debug_file, " phi_inc = %.4f \n r_inc = %.4f \n", LUT.phi_inc,
                LUT.r_inc);
            fprintf(
                debug_file, " std_phi = %.4f \n std_r = %.4f \n", LUT.std_phi,
                LUT.std_r);
            fprintf(debug_file, "[ phi ] [ r ] ---> (cx,cy)=Value\n");
            fprintf(debug_file, "----------------------------------\n");
        }

        // For the different possible angles (phi)
        for (size_t phi_indx = 0; phi_indx < LUT.phi_count; phi_indx++)
        {
            // mean of the phi value
            float phi = phi_indx * LUT.phi_inc;

            // For the different and possibe wind modules (r)
            for (size_t r_indx = 0; r_indx < LUT.r_count; r_indx++)
            {
                // mean of the radius value
                float r = r_indx * LUT.r_inc;

                if (debug)
                {
                    fprintf(debug_file, "\n[%.2f] [%.2f] ---> ", phi, r);
                }

                // Estimates Cell_i_position
                // unsigned int cell_i_cx = 0;
                // unsigned int cell_i_cy = 0;
                float cell_i_x = LUT.resolution / 2.0;
                float cell_i_y = LUT.resolution / 2.0;

                // Estimate target position according to the mean value of wind.
                // float x_final = cell_i_x + r*cos(phi);
                // float y_final = cell_i_y + r*sin(phi);

                // Determine cell_j coordinates respect to origin_cell
                // int cell_j_cx = static_cast<int>(floor(
                // (x_final)/LUT.resolution ));
                // int cell_j_cy = static_cast<int>(floor(
                // (y_final)/LUT.resolution ));
                // Center of cell_j
                // float cell_j_x = (cell_j_cx+0.5f)*LUT.resolution;
                // float cell_j_y = (cell_j_cy+0.5f)*LUT.resolution;
                // left bottom corner of cell_j
                // float cell_j_xmin = cell_j_x - LUT.resolution/2.0;
                // float cell_j_ymin = cell_j_y - LUT.resolution/2.0;

                /* ---------------------------------------------------------------------------------
                    Generate bounding-box  (+/- 3std) to determine which cells
                to update
                ---------------------------------------------------------------------------------*/
                std::vector<double> vertex_x, vertex_y;
                vertex_x.resize(14);
                vertex_y.resize(14);
                // Bounding-Box initialization
                double minBBox_x = 1000;
                double maxBBox_x = -1000;
                double minBBox_y = 1000;
                double maxBBox_y = -1000;

                // Consider special case for high uncertainty in PHI. The shape
                // of the polygon is a donut.
                double std_phi_BBox = LUT.std_phi;
                if (std_phi_BBox > M_PI / 3)
                {
                    std_phi_BBox = M_PI / 3;  // To avoid problems generating
                    // the bounding box. For std>pi/3
                    // the shape is always a donut.
                }

                // Calculate bounding box limits
                size_t indx = 0;
                int sr = 3;
                for (int sd = (-3); sd <= (3); sd++)
                {
                    vertex_x[indx] =
                        cell_i_x +
                        (r + sr * LUT.std_r) * cos(phi + sd * std_phi_BBox);
                    if (vertex_x[indx] < minBBox_x) minBBox_x = vertex_x[indx];
                    if (vertex_x[indx] > maxBBox_x) maxBBox_x = vertex_x[indx];

                    vertex_y[indx] =
                        cell_i_y +
                        (r + sr * LUT.std_r) * sin(phi + sd * std_phi_BBox);
                    if (vertex_y[indx] < minBBox_y) minBBox_y = vertex_y[indx];
                    if (vertex_y[indx] > maxBBox_y) maxBBox_y = vertex_y[indx];

                    indx++;
                }
                sr = -3;
                for (int sd = (3); sd >= (-3); sd--)
                {
                    vertex_x[indx] =
                        cell_i_x +
                        (r + sr * LUT.std_r) * cos(phi + sd * std_phi_BBox);
                    if (vertex_x[indx] < minBBox_x) minBBox_x = vertex_x[indx];
                    if (vertex_x[indx] > maxBBox_x) maxBBox_x = vertex_x[indx];

                    vertex_y[indx] =
                        cell_i_y +
                        (r + sr * LUT.std_r) * sin(phi + sd * std_phi_BBox);
                    if (vertex_y[indx] < minBBox_y) minBBox_y = vertex_y[indx];
                    if (vertex_y[indx] > maxBBox_y) maxBBox_y = vertex_y[indx];

                    indx++;
                }

                /* ------------------------------------------------------------------------
                   Determine range of cells to update according to the
                Bounding-Box limits.
                   Origin cell is cx=cy= 0   x[0,res), y[0,res)
                ---------------------------------------------------------------------------*/
                int min_cx =
                    static_cast<int>(floor(minBBox_x / LUT.resolution));
                int max_cx =
                    static_cast<int>(floor(maxBBox_x / LUT.resolution));
                int min_cy =
                    static_cast<int>(floor(minBBox_y / LUT.resolution));
                int max_cy =
                    static_cast<int>(floor(maxBBox_y / LUT.resolution));

                int num_cells_affected =
                    (max_cx - min_cx + 1) * (max_cy - min_cy + 1);

                if (num_cells_affected == 1)
                {
                    // Concentration of cell_i moves to cell_a (cx,cy)
                    TGaussianCell gauss_info;
                    gauss_info.cx = min_cx;  // since max_cx == min_cx
                    gauss_info.cy = min_cy;
                    gauss_info.value = 1;  // prob = 1

                    // Add cell volume to LookUp Table
                    LUT_TABLE[phi_indx][r_indx].push_back(gauss_info);

                    if (debug)
                    {
                        // Save to file (debug)
                        fprintf(
                            debug_file, "(%d,%d)=%.4f", gauss_info.cx,
                            gauss_info.cy, gauss_info.value);
                    }
                }
                else
                {
                    // Estimate volume of the Gaussian under each affected cell

                    float subcell_pres = LUT.resolution / 10;
                    // Determine the number of subcells inside the Bounding-Box
                    const int BB_x_subcells =
                        (int)(floor((maxBBox_x - minBBox_x) / subcell_pres) + 1);
                    const int BB_y_subcells =
                        (int)(floor((maxBBox_y - minBBox_y) / subcell_pres) + 1);

                    double subcell_pres_x =
                        (maxBBox_x - minBBox_x) / BB_x_subcells;
                    double subcell_pres_y =
                        (maxBBox_y - minBBox_y) / BB_y_subcells;

                    // Save the W value of each cell using a map
                    std::map<std::pair<int, int>, float> w_values;
                    std::map<std::pair<int, int>, float>::iterator it;
                    float sum_w = 0;

                    for (int scy = 0; scy < BB_y_subcells; scy++)
                    {
                        for (int scx = 0; scx < BB_x_subcells; scx++)
                        {
                            // P-Subcell coordinates (center of the p-subcell)
                            float subcell_a_x =
                                minBBox_x + (scx + 0.5f) * subcell_pres_x;
                            float subcell_a_y =
                                minBBox_y + (scy + 0.5f) * subcell_pres_y;

                            // distance and angle between cell_i and subcell_a
                            float r_ia = sqrt(
                                square(subcell_a_x - cell_i_x) +
                                square(subcell_a_y - cell_i_y));
                            float phi_ia = atan2(
                                subcell_a_y - cell_i_y, subcell_a_x - cell_i_x);

                            // Volume Approximation of subcell_a (Gaussian
                            // Bivariate)
                            float w =
                                (1 / (2 * M_PI * LUT.std_r * LUT.std_phi)) *
                                exp(-0.5 *
                                    (square(r_ia - r) / square(LUT.std_r) +
                                     square(phi_ia - phi) /
                                         square(LUT.std_phi)));
                            w += (1 / (2 * M_PI * LUT.std_r * LUT.std_phi)) *
                                 exp(-0.5 *
                                     (square(r_ia - r) / square(LUT.std_r) +
                                      square(phi_ia + 2 * M_PI - phi) /
                                          square(LUT.std_phi)));
                            w += (1 / (2 * M_PI * LUT.std_r * LUT.std_phi)) *
                                 exp(-0.5 *
                                     (square(r_ia - r) / square(LUT.std_r) +
                                      square(phi_ia - 2 * M_PI - phi) /
                                          square(LUT.std_phi)));

                            // Since we work with a cell grid, approximate the
                            // weight of the gaussian by the volume of the
                            // subcell_a
                            if (r_ia != 0.0)
                                w =
                                    (w * (subcell_pres_x * subcell_pres_y) /
                                     r_ia);

                            // Determine cell index of the current subcell
                            int cell_cx = static_cast<int>(
                                floor(subcell_a_x / LUT.resolution));
                            int cell_cy = static_cast<int>(
                                floor(subcell_a_y / LUT.resolution));

                            // Save w value
                            it =
                                w_values.find(std::make_pair(cell_cx, cell_cy));
                            if (it != w_values.end())  // already exists
                                w_values[std::make_pair(cell_cx, cell_cy)] += w;
                            else
                                w_values[std::make_pair(cell_cx, cell_cy)] = w;

                            sum_w = sum_w + w;
                        }  // end-for scx
                    }  // end-for scy

                    // SAVE to LUT
                    for (it = w_values.begin(); it != w_values.end(); it++)
                    {
                        float w_final =
                            (it->second) / sum_w;  // normalization to 1

                        if (w_final >= 0.001)
                        {
                            // Save the weight of the gaussian volume for cell_a
                            // (cx,cy)
                            TGaussianCell gauss_info;
                            gauss_info.cx = it->first.first;
                            gauss_info.cy = it->first.second;
                            gauss_info.value = w_final;

                            // Add cell volume to LookUp Table
                            LUT_TABLE[phi_indx][r_indx].push_back(gauss_info);

                            if (debug)
                            {
                                // Save to file (debug)
                                fprintf(
                                    debug_file, "(%d,%d)=%.6f    ",
                                    gauss_info.cx, gauss_info.cy,
                                    gauss_info.value);
                            }
                        }
                    }

                    // OLD WAY

                    /* ---------------------------------------------------------
                       Estimate the volume of the Gaussian on each affected cell
                    //-----------------------------------------------------------*/
                    // for(int cx=min_cx; cx<=max_cx; cx++)
                    //{
                    //  for(int cy=min_cy; cy<=max_cy; cy++)
                    //  {
                    //      // Coordinates of affected cell (center of the cell)
                    //      float cell_a_x = (cx+0.5f)*LUT.resolution;
                    //      float cell_a_y = (cy+0.5f)*LUT.resolution;
                    //      float w_cell_a = 0.0;   //initial Gaussian value of
                    // cell afected

                    //      // Estimate volume of the Gaussian under cell (a)
                    //      // Partition each cell into (p x p) subcells and
                    // evaluate the gaussian.
                    //      int p = 40;
                    //      float subcell_pres = LUT.resolution/p;
                    //      float cell_a_x_min = cell_a_x - LUT.resolution/2.0;
                    //      float cell_a_y_min = cell_a_y - LUT.resolution/2.0;

                    //
                    //      for(int scy=0; scy<p; scy++)
                    //      {
                    //          for(int scx=0; scx<p; scx++)
                    //          {
                    //              //P-Subcell coordinates (center of the
                    // p-subcell)
                    //              float subcell_a_x = cell_a_x_min +
                    //(scx+0.5f)*subcell_pres;
                    //              float subcell_a_y = cell_a_y_min +
                    //(scy+0.5f)*subcell_pres;

                    //              //distance and angle between cell_i and
                    // subcell_a
                    //              float r_ia = sqrt(
                    // square(subcell_a_x-cell_i_x)
                    //+
                    // square(subcell_a_y-cell_i_y) );
                    //              float phi_ia = atan2(subcell_a_y-cell_i_y,
                    // subcell_a_x-cell_i_x);

                    //              //Volume Approximation of subcell_a
                    //(Gaussian
                    // Bivariate)
                    //              float w = (1/(2*M_PI*LUT.std_r*LUT.std_phi))
                    //*
                    // exp(-0.5*( square(r_ia-r)/square(LUT.std_r) +
                    // square(phi_ia-phi)/square(LUT.std_phi) ) );
                    //              w += (1/(2*M_PI*LUT.std_r*LUT.std_phi)) *
                    // exp(-0.5*( square(r_ia-r)/square(LUT.std_r) +
                    // square(phi_ia+2*M_PI-phi)/square(LUT.std_phi) ) );
                    //              w += (1/(2*M_PI*LUT.std_r*LUT.std_phi)) *
                    // exp(-0.5*( square(r_ia-r)/square(LUT.std_r) +
                    // square(phi_ia-2*M_PI-phi)/square(LUT.std_phi) ) );
                    //
                    //              //Since we work with a cell grid,
                    // approximate
                    // the
                    // weight of the gaussian by the volume of the subcell_a
                    //              if (r_ia != 0.0)
                    //                  w_cell_a = w_cell_a + (w *
                    // square(subcell_pres)/r_ia);
                    //          }//end-for scx
                    //      }//end-for scy

                    //      //Save the weight of the gaussian volume for cell_a
                    //(cx,cy)
                    //      TGaussianCell gauss_info;
                    //      gauss_info.cx = cx;
                    //      gauss_info.cy = cy;
                    //      gauss_info.value = w_cell_a;

                    //      //Add cell volume to LookUp Table
                    //      LUT_TABLE[phi_indx][r_indx].push_back(gauss_info);

                    //      if (debug)
                    //      {
                    //          //Save to file (debug)
                    //          fprintf(debug_file, "(%d,%d)=%.6f
                    //",gauss_info.cx, gauss_info.cy, gauss_info.value);
                    //      }
                    //
                    //
                    //  }//end-for cy
                    //}//end-for cx

                }  // end-if only one affected cell

            }  // end-for r
        }  // end-for phi

        if (debug) fclose(debug_file);

        // Save LUT to File
        return save_Gaussian_Wind_Grid_To_File();

    }  // end-if table not available
}

bool CGasConcentrationGridMap2D::save_Gaussian_Wind_Grid_To_File()
{
    // Save LUT to file
    cout << "Saving to File ....";

    CFileGZOutputStream fo(format(
        "Gaussian_Wind_Weights_res(%f)_stdPhi(%f)_stdR(%f).gz", LUT.resolution,
        LUT.std_phi, LUT.std_r));
    if (!fo.fileOpenCorrectly())
    {
        return false;
        cout << "WARNING: Gaussian_Wind_Weights file NOT SAVED" << endl;
    }
    auto f = mrpt::serialization::archiveFrom(fo);

    try
    {
        // Save params first
        f << LUT.resolution;  // cell resolution used
        f << LUT.std_phi;  // std_phi used
        f << LUT.std_r;

        f << LUT.phi_inc;  // rad
        f << (float)LUT.phi_count;
        f << LUT.r_inc;  // m
        f << LUT.max_r;  // maximum distance (m)
        f << (float)LUT.r_count;

        // Save Multi-table
        // vector< vector< vector<TGaussianCell>>>>> *table;

        for (size_t phi_indx = 0; phi_indx < LUT.phi_count; phi_indx++)
        {
            for (size_t r_indx = 0; r_indx < LUT.r_count; r_indx++)
            {
                // save all cell values.
                size_t N = LUT_TABLE[phi_indx][r_indx].size();
                f << (float)N;

                for (size_t i = 0; i < N; i++)
                {
                    f << (float)LUT_TABLE[phi_indx][r_indx][i].cx;
                    f << (float)LUT_TABLE[phi_indx][r_indx][i].cy;
                    f << LUT_TABLE[phi_indx][r_indx][i].value;
                }
            }
        }
        cout << "DONE" << endl;
        return true;
    }
    catch (const std::exception& e)
    {
        cout << endl
             << "------------------------------------------------------------"
             << endl;
        cout << "EXCEPTION WHILE SAVING LUT TO FILE" << endl;
        cout << "Exception = " << e.what() << endl;
        return false;
    }
}

bool CGasConcentrationGridMap2D::load_Gaussian_Wind_Grid_From_File()
{
    // LOAD LUT from file
    cout << "Loading from File ....";

    try
    {
        CFileGZInputStream fi(format(
            "Gaussian_Wind_Weights_res(%f)_stdPhi(%f)_stdR(%f).gz",
            LUT.resolution, LUT.std_phi, LUT.std_r));
        if (!fi.fileOpenCorrectly())
        {
            cout << "WARNING WHILE READING FROM: Gaussian_Wind_Weights" << endl;
            return false;
        }
        auto f = mrpt::serialization::archiveFrom(fi);

        float t_float;
        unsigned int t_uint;
        // Ensure params from file are correct with the specified in the ini
        // file
        f >> t_float;
        ASSERT_(LUT.resolution == t_float);

        f >> t_float;
        ASSERT_(LUT.std_phi == t_float);

        f >> t_float;
        ASSERT_(LUT.std_r == t_float);

        f >> t_float;
        ASSERT_(LUT.phi_inc == t_float);

        f >> t_float;
        t_uint = (unsigned int)t_float;
        ASSERT_(LUT.phi_count == t_uint);

        f >> t_float;
        ASSERT_(LUT.r_inc == t_float);

        f >> t_float;
        ASSERT_(LUT.max_r == t_float);

        f >> t_float;
        t_uint = (unsigned int)t_float;
        ASSERT_(LUT.r_count == t_uint);

        // Load Multi-table
        // vector< vector< vector<TGaussianCell>>>>> *table;

        for (size_t phi_indx = 0; phi_indx < LUT.phi_count; phi_indx++)
        {
            for (size_t r_indx = 0; r_indx < LUT.r_count; r_indx++)
            {
                // Number of cells to update
                size_t N;
                f >> t_float;
                N = (size_t)t_float;

                for (size_t i = 0; i < N; i++)
                {
                    TGaussianCell gauss_info;
                    f >> t_float;
                    gauss_info.cx = (int)t_float;

                    f >> t_float;
                    gauss_info.cy = (int)t_float;

                    f >> gauss_info.value;

                    // Add cell volume to LookUp Table
                    LUT_TABLE[phi_indx][r_indx].push_back(gauss_info);
                }
            }
        }
        cout << "DONE" << endl;
        return true;
    }
    catch (const std::exception& e)
    {
        cout << endl
             << "------------------------------------------------------------"
             << endl;
        cout << "EXCEPTION WHILE LOADING LUT FROM FILE" << endl;
        cout << "Exception = " << e.what() << endl;
        return false;
    }
}