/usr/include/ITK-4.5/itkMultipleValuedNonLinearVnlOptimizer.h is in libinsighttoolkit4-dev 4.5.0-3.
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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,
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#ifndef __itkMultipleValuedNonLinearVnlOptimizer_h
#define __itkMultipleValuedNonLinearVnlOptimizer_h
#include "itkMultipleValuedNonLinearOptimizer.h"
#include "itkMultipleValuedVnlCostFunctionAdaptor.h"
#include "itkCommand.h"
namespace itk
{
/** \class MultipleValuedNonLinearVnlOptimizer
* \brief This class is a base for the Optimization methods that
* optimize a multi-valued function.
*
* It is an Adaptor class for optimizers provided by the vnl library
*
* \ingroup Numerics Optimizers
* \ingroup ITKOptimizers
*/
class MultipleValuedNonLinearVnlOptimizer:
public MultipleValuedNonLinearOptimizer
{
public:
/** Standard class typedefs. */
typedef MultipleValuedNonLinearVnlOptimizer Self;
typedef MultipleValuedNonLinearOptimizer Superclass;
typedef SmartPointer< Self > Pointer;
typedef SmartPointer< const Self > ConstPointer;
/** Run-time type information (and related methods). */
itkTypeMacro(MultipleValuedNonLinearVnlOptimizer,
MultipleValueNonLinearOptimizer);
/** ParametersType typedef.
* It defines a position in the optimization search space. */
typedef Superclass::ParametersType ParametersType;
/** Set the cost Function. This method has to be overloaded
* by derived classes because the CostFunctionAdaptor requires
* to know the number of parameters at construction time. This
* number of parameters is obtained at run-time from the itkCostFunction.
* As a consequence each derived optimizer should construct its own
* CostFunctionAdaptor when overloading this method */
virtual void SetCostFunction(MultipleValuedCostFunction *costFunction) = 0;
/** Define if the Cost function should provide a customized
Gradient computation or the gradient can be computed internally
using a default approach */
void SetUseCostFunctionGradient(bool);
void UseCostFunctionGradientOn()
{
this->SetUseCostFunctionGradient(true);
}
void UseCostFunctionGradientOff()
{
this->SetUseCostFunctionGradient(false);
}
bool GetUseCostFunctionGradient() const;
/** Return Cached Values. These method have the advantage of not triggering a
* recomputation of the metric value, but it has the disadvantage of
* returning a value that may not be the one corresponding to the
* current parameters. For GUI update purposes, this method is a
* good option, for mathematical validation you should rather call
* GetValue(). */
itkGetConstReferenceMacro(CachedValue, MeasureType);
itkGetConstReferenceMacro(CachedDerivative, DerivativeType);
itkGetConstReferenceMacro(CachedCurrentPosition, ParametersType);
protected:
MultipleValuedNonLinearVnlOptimizer();
virtual ~MultipleValuedNonLinearVnlOptimizer();
void PrintSelf(std::ostream & os, Indent indent) const;
typedef MultipleValuedVnlCostFunctionAdaptor CostFunctionAdaptorType;
void SetCostFunctionAdaptor(CostFunctionAdaptorType *adaptor);
const CostFunctionAdaptorType * GetCostFunctionAdaptor(void) const;
CostFunctionAdaptorType * GetCostFunctionAdaptor(void);
/** The purpose of this method is to get around the lack of const
* correctness in vnl cost_functions and optimizers */
CostFunctionAdaptorType * GetNonConstCostFunctionAdaptor(void) const;
/** Command observer that will interact with the ITKVNL cost-function
* adaptor in order to generate iteration events. This will allow to overcome
* the limitation of VNL optimizers not offering callbacks for every
* iteration */
typedef ReceptorMemberCommand< Self > CommandType;
private:
MultipleValuedNonLinearVnlOptimizer(const Self &); //purposely not implemented
void operator=(const Self &); //purposely not implemented
/** Callback function for the Command Observer */
void IterationReport(const EventObject & event);
CostFunctionAdaptorType *m_CostFunctionAdaptor;
bool m_UseGradient;
CommandType::Pointer m_Command;
mutable ParametersType m_CachedCurrentPosition;
mutable MeasureType m_CachedValue;
mutable DerivativeType m_CachedDerivative;
};
} // end namespace itk
#endif
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