itkMultipleValuedVnlCostFunctionAdaptor.h

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 *
 *  Copyright NumFOCUS
 *
 *  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
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 *         https://www.apache.org/licenses/LICENSE-2.0.txt
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 *  distributed under the License is distributed on an "AS IS" BASIS,
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 *  See the License for the specific language governing permissions and
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#ifndef itkMultipleValuedVnlCostFunctionAdaptor_h
#define itkMultipleValuedVnlCostFunctionAdaptor_h
 
#include "itkMultipleValuedCostFunction.h"
#include "vnl/vnl_least_squares_function.h"
#include "ITKOptimizersExport.h"
 
namespace itk
{
class ITKOptimizers_EXPORT MultipleValuedVnlCostFunctionAdaptor : public vnl_least_squares_function
{
public:
  using InternalParametersType = vnl_vector<double>;
 
  using InternalMeasureType = vnl_vector<double>;
 
  using InternalDerivativeType = vnl_matrix<double>;
 
  using MeasureType = MultipleValuedCostFunction::MeasureType;
 
  using ParametersType = MultipleValuedCostFunction::ParametersType;
 
  using DerivativeType = MultipleValuedCostFunction::DerivativeType;
 
  using ScalesType = Array<double>;
 
  MultipleValuedVnlCostFunctionAdaptor(unsigned int spaceDimension, unsigned int numberOfValues);
 
  void
  SetCostFunction(MultipleValuedCostFunction * costFunction)
  {
    m_CostFunction = costFunction;
  }
 
  const MultipleValuedCostFunction *
  GetCostFunction() const
  {
    return m_CostFunction;
  }
 
  void
  f(const InternalParametersType & inparameters, InternalMeasureType & measures) override;
 
  void
  gradf(const InternalParametersType & inparameters, InternalDerivativeType & gradient) override;
 
  virtual void
  compute(const InternalParametersType & x, InternalMeasureType * ff, InternalDerivativeType * g);
 
  void
  ConvertExternalToInternalGradient(const DerivativeType & input, InternalDerivativeType & output);
 
  void
  ConvertExternalToInternalMeasures(const MeasureType & input, InternalMeasureType & output);
 
  void
  SetUseGradient(bool);
 
  void
  UseGradientOn()
  {
    this->SetUseGradient(true);
  }
  void
  UseGradientOff()
  {
    this->SetUseGradient(false);
  }
  bool
  GetUseGradient() const;
 
  void
  SetScales(const ScalesType & scales);
 
  unsigned long
  AddObserver(const EventObject & event, Command *) const;
 
  const MeasureType &
  GetCachedValue() const;
 
  const DerivativeType &
  GetCachedDerivative() const;
 
  const ParametersType &
  GetCachedCurrentParameters() const;
 
protected:
  void
  ReportIteration(const EventObject & event) const;
 
private:
  itkGetConstReferenceMacro(InverseScales, ScalesType);
 
  MultipleValuedCostFunction::Pointer m_CostFunction{};
 
  bool            m_ScalesInitialized{};
  ScalesType      m_InverseScales{};
  Object::Pointer m_Reporter{};
 
  mutable MeasureType    m_CachedValue{};
  mutable DerivativeType m_CachedDerivative{};
  mutable ParametersType m_CachedCurrentParameters{};
}; // end of Class CostFunction
} // end namespace itk
 
#endif