CPosePDFGrid.h

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/* +---------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)               |
   |                          http://www.mrpt.org/                             |
   |                                                                           |
   | Copyright (c) 2005-2014, Individual contributors, see AUTHORS file        |
   | See: http://www.mrpt.org/Authors - All rights reserved.                   |
   | Released under BSD License. See details in http://www.mrpt.org/License    |
   +---------------------------------------------------------------------------+ */
#ifndef CPosePDFGrid_H
#define CPosePDFGrid_H

#include <mrpt/poses/CPosePDF.h>
#include <mrpt/poses/CPose2DGridTemplate.h>

namespace mrpt
{
namespace poses
{
        using mrpt::utils::DEG2RAD;

        // This must be added to any CSerializable derived class:
        DEFINE_SERIALIZABLE_PRE_CUSTOM_BASE( CPosePDFGrid, CPosePDF   )

        /** Declares a class that represents a Probability Distribution
         *    function (PDF) of a 2D pose (x,y,phi).
         *   This class implements that PDF using a 3D grid.
         *
         * \sa CPose2D, CPosePDF, CPose2DGridTemplate
         * \ingroup poses_pdf_grp
         */
        class BASE_IMPEXP CPosePDFGrid : public CPosePDF, public CPose2DGridTemplate<double>
        {
                // This must be added to any CSerializable derived class:
                DEFINE_SERIALIZABLE( CPosePDFGrid )

         protected:


         public:
                /** Constructor: Initializes a, uniform distribution over the whole given range.
                  */
                CPosePDFGrid(
                        double          xMin = -1.0f,
                        double          xMax = 1.0f,
                        double          yMin = -1.0f,
                        double          yMax = 1.0f,
                        double          resolutionXY = 0.5f,
                        double          resolutionPhi = DEG2RAD(180),
                        double          phiMin = -M_PIf,
                        double          phiMax = M_PIf
                        );

                /** Destructor
                 */
                virtual ~CPosePDFGrid();

                /** Copy operator, translating if necesary (for example, between particles and gaussian representations)
                  */
                void  copyFrom(const CPosePDF &o);

                /** Normalizes the PDF, such as all cells sum the unity.
                  */
                void  normalize();

                /** Assigns the same value to all the cells in the grid, so the sum 1.
                  */
                void  uniformDistribution();

                 /** Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF).
                   * \sa getCovariance
                   */
                void getMean(CPose2D &mean_pose) const;

                /** Returns an estimate of the pose covariance matrix (3x3 cov matrix) and the mean, both at once.
                  * \sa getMean
                  */
                void getCovarianceAndMean(mrpt::math::CMatrixDouble33 &cov,CPose2D &mean_point) const;

                /** Save the contents of the 3D grid in one file, as a vertical concatenation of rectangular matrix for the different "PHI" discrete levels, and the size in X,Y,and PHI in another file named "<filename>_dims.txt"
                 */
                void   saveToTextFile(const std::string &dataFile) const;

                /** this = p (+) this. This can be used to convert a PDF from local coordinates to global, providing the point (newReferenceBase) from which
                  *   "to project" the current pdf. Result PDF substituted the currently stored one in the object.
                  */
                void  changeCoordinatesReference( const CPose3D &newReferenceBase );

                /** Bayesian fusion of 2 densities (In the grid representation this becomes a pointwise multiplication)
                  */
                void  bayesianFusion(const  CPosePDF &p1,const  CPosePDF &p2, const double &minMahalanobisDistToDrop = 0 );

                /** Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF
                  */
                void  inverse(CPosePDF &o) const;

                /** Draws a single sample from the distribution (WARNING: weights are assumed to be normalized!)
                  */
                void  drawSingleSample( CPose2D &outPart ) const;

                /** Draws a number of samples from the distribution, and saves as a list of 1x3 vectors, where each row contains a (x,y,phi) datum.
                  */
                void  drawManySamples( size_t N, std::vector<CVectorDouble> & outSamples ) const;

        }; // End of class def.
        DEFINE_SERIALIZABLE_POST_CUSTOM_BASE( CPosePDFGrid, CPosePDF   )


        } // End of namespace
} // End of namespace

#endif