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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.
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* limitations under the License.
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*=========================================================================*/
#ifndef itkSingleValuedVnlCostFunctionAdaptor_h
#define itkSingleValuedVnlCostFunctionAdaptor_h
#include "itkSingleValuedCostFunction.h"
#include "vnl/vnl_cost_function.h"
#include "ITKOptimizersExport.h"
namespace itk
{
/** \class SingleValuedVnlCostFunctionAdaptor
* \brief This class is an Adaptor that allows to pass
* itk::SingleValuedCostFunctions to vnl_optimizers expecting
* a vnl_cost_function.
*
* This class returns a single valued.
*
* \ingroup Numerics Optimizers
* \ingroup ITKOptimizers
*/
class ITKOptimizers_EXPORT SingleValuedVnlCostFunctionAdaptor:
public vnl_cost_function
{
public:
/** InternalParametersType typedef. */
typedef vnl_vector< double > InternalParametersType;
/** InternalMeasureType typedef. */
typedef double InternalMeasureType;
/** InternalGradientType typedef. */
typedef vnl_vector< double > InternalDerivativeType;
/** Parameters of the SingleValuedCostFunction */
typedef SingleValuedCostFunction::ParametersType ParametersType;
/** Derivatives of the SingleValuedCostFunction */
typedef SingleValuedCostFunction::DerivativeType DerivativeType;
/** Type of the SingleValuedCostFunction value */
typedef SingleValuedCostFunction::MeasureType MeasureType;
/** Scales typedef */
typedef Array< double > ScalesType;
/** Constructor with size */
SingleValuedVnlCostFunctionAdaptor(unsigned int spaceDimension);
/** Set the CostFunction deriving from SingleValuedCostFunction */
void SetCostFunction(SingleValuedCostFunction *costFunction)
{ m_CostFunction = costFunction; }
/** Get the CostFunction deriving from SingleValuedCostFunction */
const SingleValuedCostFunction * GetCostFunction(void) const
{ return m_CostFunction; }
/** Delegate computation of the value to the CostFunction. */
virtual InternalMeasureType f(const InternalParametersType & inparameters) ITK_OVERRIDE;
/** Delegate computation of the gradient to the costFunction. */
virtual void gradf(const InternalParametersType & inparameters,
InternalDerivativeType & gradient) ITK_OVERRIDE;
/** Delegate computation of value and gradient to the costFunction. */
virtual void compute(const InternalParametersType & x,
InternalMeasureType *f,
InternalDerivativeType *g) ITK_OVERRIDE;
/** Convert external derviative measures into internal type */
void ConvertExternalToInternalGradient(
const DerivativeType & input,
InternalDerivativeType & output) const;
/** Set current parameters scaling. */
void SetScales(const ScalesType & scales);
/** Set/Get Negate cost function. The purpose of this boolean flag is to make
* possible to take certain VNL optimizers that are only minimizers, and use
* them for maximizing functions. When the boolean flag is set to true, the
* values returned by GetValue in the internal ITK cost function will be
* multiplied by -1 before returning it in the f() function. Similar
* operations will be done for the gradf() and compute() methods. When the
* boolean flag is set to false, then the values returned by the ITK cost
* function will be passed unchanged to the VNL optimizers. */
void SetNegateCostFunction(bool value);
bool GetNegateCostFunction() const;
void NegateCostFunctionOn() { m_NegateCostFunction = true; }
void NegateCostFunctionOff() { m_NegateCostFunction = false; }
/** This AddObserver method allows to simulate that this class derives from
* an itkObject for the purpose of reporting iteration events. The goal of
* this method is to allow ITK-vnl optimizer adaptors to get iteration events
* despite the fact that VNL does not provide callbacks. */
unsigned long AddObserver(const EventObject & event, Command *) const;
/** Return the value of the last evaluation to the value of the cost function.
* Note that this method DOES NOT triggers a computation of the function or
* the derivatives, it only returns previous values. Therefore the values here
* are only valid after you invoke the f() or gradf() methods. */
const MeasureType & GetCachedValue() const;
const DerivativeType & GetCachedDerivative() const;
const ParametersType & GetCachedCurrentParameters() const;
protected:
/** This method is intended to be called by the derived classes in order to
* notify of an iteration event to any Command/Observers */
void ReportIteration(const EventObject & event) const;
private:
/** Get current parameters scaling. */
itkGetConstReferenceMacro(InverseScales, ScalesType);
SingleValuedCostFunction::Pointer m_CostFunction;
bool m_ScalesInitialized;
ScalesType m_InverseScales;
bool m_NegateCostFunction;
Object::Pointer m_Reporter;
mutable MeasureType m_CachedValue;
mutable DerivativeType m_CachedDerivative;
mutable ParametersType m_CachedCurrentParameters;
}; // end of Class CostFunction
} // end namespace itk
#endif
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