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/*
* Copyright (C) 2005-2020 Centre National d'Etudes Spatiales (CNES)
* Copyright (C) 2007-2012 Institut Mines Telecom / Telecom Bretagne
*
* This file is part of Orfeo Toolbox
*
* https://www.orfeo-toolbox.org/
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef otbSOMMap_h
#define otbSOMMap_h
#include "itkVariableLengthVector.h"
#include "itkEuclideanDistanceMetric.h"
#include "otbVectorImage.h"
namespace otb
{
/**
* \class SOMMap
* \brief This class represent a Self Organizing Map.
*
* The Self organizing map (or Kohonen map) is a type of neural networks. It is based on an analogy with
* the visual cortex, where similar inputs activate neighbor neurons.
*
* This class extends the Image object, where each pixel represents a neuron in the map.
* It is templated with a distance parameter used to compute the neuron response to an input.
* Thanks to the extension of the Image object, reading and writing is supported through standard image
* readers and writers.
*
* The training is done via the SOM class, and the activation map can be produced with the SOMActivationBuilder
* class.
*
* \sa SOM
* \sa SOMActivationBuilder
*
* \ingroup OTBSOM
*/
template <class TNeuron = itk::VariableLengthVector<double>, class TDistance = itk::Statistics::EuclideanDistanceMetric<TNeuron>,
unsigned int VMapDimension = 2>
class ITK_EXPORT SOMMap : public otb::VectorImage<typename TNeuron::ComponentType, VMapDimension>
{
public:
/** Standard typedefs */
typedef SOMMap Self;
typedef otb::VectorImage<typename TNeuron::ComponentType, VMapDimension> Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
/** Creation through object factory macro */
itkNewMacro(Self);
/**
* There is no runtime information macro since
* this class has to be considered to as a simple VectorImage
* // itkTypeMacro(SOMMap, VectorImage);
* */
/** Template parameters related typedefs */
typedef TNeuron NeuronType;
typedef TDistance DistanceType;
typedef typename DistanceType::Pointer DistancePointerType;
/** Superclass related typedefs */
typedef typename Superclass::IndexType IndexType;
typedef typename Superclass::SizeType SizeType;
typedef typename Superclass::DirectionType DirectionType;
typedef typename Superclass::RegionType RegionType;
typedef typename Superclass::SpacingType SpacingType;
typedef typename Superclass::PointType PointType;
/**
* Get The index of the winning neuron for a sample.
* \param sample the sample.
* \return The index of the winning neuron.
*/
IndexType GetWinner(const NeuronType& sample);
protected:
/** Constructor */
SOMMap();
/** Destructor */
~SOMMap() override;
/** PrintSelf method */
void PrintSelf(std::ostream& os, itk::Indent indent) const override;
private:
SOMMap(const Self&) = delete;
void operator=(const Self&) = delete;
};
} // end namespace otb
#ifndef OTB_MANUAL_INSTANTIATION
#include "otbSOMMap.hxx"
#endif
#endif
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