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/*=========================================================================

  Program:   ORFEO Toolbox
  Language:  C++
  Date:      $Date$
  Version:   $Revision$


  Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
  See OTBCopyright.txt for details.

  Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
  See IMTCopyright.txt for details.

     This software is distributed WITHOUT ANY WARRANTY; without even
     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
     PURPOSE.  See the above copyright notices for more information.

=========================================================================*/

#ifndef otbPeriodicSOM_txx
#define otbPeriodicSOM_txx

#include "itkNumericTraits.h"
#include "itkNeighborhoodIterator.h"

#include "otbPeriodicSOM.h"

namespace otb
{

/**
 * Update the output map with a new sample.
 * \param sample The new sample to learn,
 * \param beta The learning coefficient,
 * \param radius The radius of the neighbourhood.
 */
template <class TListSample, class TMap,
    class TSOMLearningBehaviorFunctor,
    class TSOMNeighborhoodBehaviorFunctor>
void
PeriodicSOM<TListSample, TMap, TSOMLearningBehaviorFunctor, TSOMNeighborhoodBehaviorFunctor>
::UpdateMap(const NeuronType& sample, double beta, SizeType& radius)
{
  unsigned int i, j;

  // output map pointer
  MapPointerType map = this->GetOutput(0);

  // winner index in the map
  IndexType  position = map->GetWinner(sample);
  NeuronType winner = map->GetPixel(position);

  // Local neighborhood definition
  typedef typename MapType::Superclass            ImageMapType;
  typedef itk::NeighborhoodIterator<ImageMapType> NeighborhoodIteratorType;
  typename MapType::RegionType mapRegion = map->GetLargestPossibleRegion();
  NeighborhoodIteratorType it(radius, map, mapRegion);

  // Here, the periodic update is achieved 'by hand' since
  // PeriodicBoundaryCondition does not allow modifying
  // VectorImage contents
  SizeType  mapSize = mapRegion.GetSize();
  IndexType positionToUpdate;

  // Iterate over the neighborhood ot the winner neuron
  it.SetLocation(position);

  for (i = 0; i < it.Size(); ++i)
    {
    typename NeighborhoodIteratorType::OffsetType offset = it.GetOffset(i);

    // The neighborhood is of elliptic shape
    double theDistance = itk::NumericTraits<double>::Zero;
    for (j = 0; j < MapType::ImageDimension; ++j)
      theDistance += pow(static_cast<double>(offset[j]), 2.0)
                     / pow(static_cast<double>(radius[j]), 2.0);

    if (theDistance <= 1.0)
      {
      for (j = 0; j < MapType::ImageDimension; ++j)
        {
        int pos = offset[j] + position[j];
        positionToUpdate[j] = (pos >= 0) ?
                              pos % mapSize[j] :
                              (mapSize[j] - ((-pos) % mapSize[j])) % mapSize[j];
        }

      NeuronType tempNeuron = it.GetPixel(i);
      // NeuronType newNeuron ( tempNeuron.Size() );
      // newNeuron.Fill( 0.0 ); // FIXME
      NeuronType newNeuron(tempNeuron);

      double tempBeta = beta / (1.0 + theDistance);
      for (j = 0; j < newNeuron.Size(); ++j)
        {
        newNeuron[j] += static_cast<typename NeuronType::ValueType>(
          (sample[j] - tempNeuron[j]) * tempBeta);
        }
      map->SetPixel(positionToUpdate, newNeuron);
      }
    }

}

} // end of namespace otb

#endif