itkRBFNetwork.h

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/*=========================================================================
 *
 *  Copyright Insight Software Consortium
 *
 *  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.txt
 *
 *  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 itkRBFNetwork_h
#define itkRBFNetwork_h

#include "itkMultilayerNeuralNetworkBase.h"
#include "itkBackPropagationLayer.h"
#include "itkSigmoidTransferFunction.h"
#include "itkLogSigmoidTransferFunction.h"
#include "itkTanSigmoidTransferFunction.h"
#include "itkHardLimitTransferFunction.h"
#include "itkSignedHardLimitTransferFunction.h"
#include "itkGaussianTransferFunction.h"
#include "itkIdentityTransferFunction.h"
#include "itkSumInputFunction.h"

#include "itkSymmetricSigmoidTransferFunction.h"
#include "itkTanHTransferFunction.h"
#include "itkRBFLayer.h"

namespace itk
{
namespace Statistics
{
template<typename TMeasurementVector, typename TTargetVector>
class ITK_TEMPLATE_EXPORT RBFNetwork :
    public MultilayerNeuralNetworkBase<TMeasurementVector, TTargetVector, BackPropagationLayer<TMeasurementVector, TTargetVector> >
{
public:
  typedef RBFNetwork               Self;
  typedef MultilayerNeuralNetworkBase<TMeasurementVector, TTargetVector , BackPropagationLayer<TMeasurementVector, TTargetVector> >
                                   Superclass;
  typedef SmartPointer<Self>       Pointer;
  typedef SmartPointer<const Self> ConstPointer;

  typedef typename Superclass::ValueType             ValueType;
  typedef typename Superclass::MeasurementVectorType MeasurementVectorType;
  typedef typename Superclass::TargetVectorType      TargetVectorType;
  typedef typename Superclass::NetworkOutputType     NetworkOutputType;

  typedef typename Superclass::LayerInterfaceType LayerInterfaceType;
  typedef typename Superclass::LearningLayerType  LearningLayerType;

  typedef typename Superclass::WeightVectorType WeightVectorType;
  typedef typename Superclass::LayerVectorType  LayerVectorType;

  typedef typename Superclass::TransferFunctionInterfaceType TransferFunctionInterfaceType;
  typedef typename Superclass::InputFunctionInterfaceType    InputFunctionInterfaceType;

  // Specializations for RBF Networks
  typedef Array<ValueType>                            ArrayType;
  typedef EuclideanDistanceMetric<ArrayType>          DistanceMetricType;
  typedef RadialBasisFunctionBase<ValueType>          RBFTransferFunctionType;
  typedef RBFLayer<TMeasurementVector, TTargetVector> HiddenLayerType;

  itkSetMacro(Classes, unsigned int);
  itkGetConstReferenceMacro(Classes, unsigned int);
  void SetCenter(TMeasurementVector c);
  void SetRadius(ValueType r);
  void SetDistanceMetric(DistanceMetricType* f);
  void InitializeWeights();

  itkTypeMacro(RBFNetwork,
               MultilayerNeuralNetworkBase);
  itkNewMacro(Self);

  //Add the layers to the network.
  // 1 input, 1 hidden, 1 output
  void Initialize() ITK_OVERRIDE;

  itkSetMacro(NumOfInputNodes, unsigned int);
  itkGetConstReferenceMacro(NumOfInputNodes, unsigned int);

  itkSetMacro(NumOfFirstHiddenNodes, unsigned int);
  itkGetConstReferenceMacro(NumOfFirstHiddenNodes, unsigned int);

  itkSetMacro(NumOfOutputNodes, unsigned int);
  itkGetConstReferenceMacro(NumOfOutputNodes, unsigned int);

  itkSetMacro(FirstHiddenLayerBias, ValueType);
  itkGetConstReferenceMacro(FirstHiddenLayerBias, ValueType);

  //#define __USE_OLD_INTERFACE  Comment out to ensure that new interface works
#ifdef __USE_OLD_INTERFACE
  //Original Function name before consistency naming changes
  inline void SetNumOfHiddenNodes(const unsigned int & x) { SetNumOfFirstHiddenNodes(x); }
  inline unsigned int GetNumOfHiddenNodes(void) const { return GetNumOfFirstHiddenNodes(); }
  inline void SetHiddenLayerBias(const ValueType & bias) { SetFirstHiddenLayerBias(bias); }
  ValueType GetHiddenLayerBias(void) const { return GetFirstHiddenLayerBias();}
#endif
  itkSetMacro(OutputLayerBias, ValueType);
  itkGetConstReferenceMacro(OutputLayerBias, ValueType);

  virtual NetworkOutputType GenerateOutput(TMeasurementVector samplevector) ITK_OVERRIDE;

  void SetInputFunction(InputFunctionInterfaceType* f);
  void SetInputTransferFunction(TransferFunctionInterfaceType* f);
#ifdef __USE_OLD_INTERFACE
  //Original Function name before consistency naming changes
  inline void SetHiddenTransferFunction(TransferFunctionInterfaceType* f) { SetFirstHiddenTransferFunction (f); }
#endif
  void SetFirstHiddenTransferFunction(TransferFunctionInterfaceType* f);
  void SetOutputTransferFunction(TransferFunctionInterfaceType* f);

protected:

  RBFNetwork();
  virtual ~RBFNetwork() ITK_OVERRIDE {};

  virtual void PrintSelf( std::ostream& os, Indent indent ) const ITK_OVERRIDE;

private:

  typename DistanceMetricType::Pointer            m_DistanceMetric;
  std::vector<TMeasurementVector>                 m_Centers;  // ui....uc
  std::vector<double>                             m_Radii;

  unsigned int m_Classes;
  unsigned int m_NumOfInputNodes;
  unsigned int m_NumOfFirstHiddenNodes;
  unsigned int m_NumOfOutputNodes;

  ValueType m_FirstHiddenLayerBias;
  ValueType m_OutputLayerBias;

  typename InputFunctionInterfaceType::Pointer    m_InputFunction;
  typename TransferFunctionInterfaceType::Pointer m_InputTransferFunction;
  typename RBFTransferFunctionType::Pointer       m_FirstHiddenTransferFunction;
  typename TransferFunctionInterfaceType::Pointer m_OutputTransferFunction;
};

} // end namespace Statistics
} // end namespace itk

#ifndef ITK_MANUAL_INSTANTIATION
#include "itkRBFNetwork.hxx"
#endif

#endif