/usr/include/ITK-4.5/itkLBFGSBOptimizer.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,
* 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 __itkLBFGSBOptimizer_h
#define __itkLBFGSBOptimizer_h
#include "itkIntTypes.h"
#include "itkSingleValuedNonLinearVnlOptimizer.h"
namespace itk
{
/* Necessary forward declaration see below for definition */
/** \class LBFGSBOptimizerHelper
* \brief Wrapper helper around vnl_lbfgsb.
*
* This class is used to translate iteration events, etc, from
* vnl_lbfgsb into iteration events in ITK.
* \ingroup ITKOptimizers
*/
class LBFGSBOptimizerHelper;
/** \class LBFGSBOptimizer
* \brief Limited memory Broyden Fletcher Goldfarb Shannon minimization with simple bounds.
*
* This class is a wrapper for converted fortan code for performing limited
* memory Broyden Fletcher Goldfarb Shannon minimization with simple bounds.
* The algorithm miminizes a nonlinear function f(x) of n variables subject to
* simple bound constraints of l <= x <= u.
*
* See also the documentation in Numerics/lbfgsb.c
*
* References:
*
* [1] R. H. Byrd, P. Lu and J. Nocedal.
* A Limited Memory Algorithm for Bound Constrained Optimization, (1995),
* SIAM Journal on Scientific and Statistical Computing ,
* 16, 5, pp. 1190-1208.
*
* [2] C. Zhu, R. H. Byrd and J. Nocedal.
* L-BFGS-B: Algorithm 778: L-BFGS-B, FORTRAN routines for large scale
* bound constrained optimization (1997),
* ACM Transactions on Mathematical Software,
* Vol 23, Num. 4, pp. 550 - 560.
*
* \ingroup Numerics Optimizers
* \ingroup ITKOptimizers
*/
class LBFGSBOptimizer:
public SingleValuedNonLinearVnlOptimizer
{
public:
/** Standard "Self" typedef. */
typedef LBFGSBOptimizer Self;
typedef SingleValuedNonLinearVnlOptimizer Superclass;
typedef SmartPointer< Self > Pointer;
typedef SmartPointer< const Self > ConstPointer;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Run-time type information (and related methods). */
itkTypeMacro(LBFGSBOptimizer, SingleValuedNonLinearVnlOptimizer);
/** BoundValue type.
* Use for defining the lower and upper bounds on the variables.
*/
typedef Array< double > BoundValueType;
/** BoundSelection type
* Use for defining the boundary condition for each variables.
*/
typedef Array< long > BoundSelectionType;
/** Internal boundary value storage type */
typedef vnl_vector< double > InternalBoundValueType;
/** Internal boundary selection storage type */
typedef vnl_vector< long > InternalBoundSelectionType;
/** The vnl optimizer */
typedef LBFGSBOptimizerHelper InternalOptimizerType;
/** Start optimization with an initial value. */
void StartOptimization(void);
/** Plug in a Cost Function into the optimizer */
virtual void SetCostFunction(SingleValuedCostFunction *costFunction);
/** Set/Get the optimizer trace flag. If set to true, the optimizer
* prints out information every iteration.
*/
virtual void SetTrace(bool flag);
itkGetMacro(Trace, bool);
itkBooleanMacro(Trace);
/** Set the lower bound value for each variable. */
virtual void SetLowerBound(const BoundValueType & value);
itkGetConstReferenceMacro(LowerBound,BoundValueType);
/** Set the upper bound value for each variable. */
virtual void SetUpperBound(const BoundValueType & value);
itkGetConstReferenceMacro(UpperBound,BoundValueType);
/** Set the boundary condition for each variable, where
* select[i] = 0 if x[i] is unbounded,
* = 1 if x[i] has only a lower bound,
* = 2 if x[i] has both lower and upper bounds, and
* = 3 if x[1] has only an upper bound
*/
virtual void SetBoundSelection(const BoundSelectionType & select);
itkGetConstReferenceMacro(BoundSelection,BoundSelectionType);
/** Set/Get the CostFunctionConvergenceFactor. Algorithm terminates
* when the reduction in cost function is less than factor * epsmcj
* where epsmch is the machine precision.
* Typical values for factor: 1e+12 for low accuracy;
* 1e+7 for moderate accuracy and 1e+1 for extremely high accuracy.
*/
virtual void SetCostFunctionConvergenceFactor(double);
itkGetMacro(CostFunctionConvergenceFactor, double);
/** Set/Get the ProjectedGradientTolerance. Algorithm terminates
* when the project gradient is below the tolerance. Default value
* is 1e-5.
*/
virtual void SetProjectedGradientTolerance(double);
itkGetMacro(ProjectedGradientTolerance, double);
/** Set/Get the MaximumNumberOfIterations. Default is 500 */
virtual void SetMaximumNumberOfIterations(unsigned int);
itkGetMacro(MaximumNumberOfIterations, unsigned int);
/** Set/Get the MaximumNumberOfEvaluations. Default is 500 */
virtual void SetMaximumNumberOfEvaluations(unsigned int);
itkGetMacro(MaximumNumberOfEvaluations, unsigned int);
/** Set/Get the MaximumNumberOfCorrections. Default is 5 */
virtual void SetMaximumNumberOfCorrections(unsigned int);
itkGetMacro(MaximumNumberOfCorrections, unsigned int);
/** This optimizer does not support scaling of the derivatives. */
void SetScales(const ScalesType &)
{
itkExceptionMacro(<< "This optimizer does not support scales.");
}
/** Get the current iteration number. */
itkGetConstReferenceMacro(CurrentIteration, unsigned int);
/** Get the current cost function value. */
MeasureType GetValue() const;
/** Get the current infinity norm of the project gradient of the cost
* function. */
itkGetConstReferenceMacro(InfinityNormOfProjectedGradient, double);
/** Get the reason for termination */
const std::string GetStopConditionDescription() const;
protected:
LBFGSBOptimizer();
virtual ~LBFGSBOptimizer();
void PrintSelf(std::ostream & os, Indent indent) const;
typedef Superclass::CostFunctionAdaptorType CostFunctionAdaptorType;
private:
LBFGSBOptimizer(const Self &); //purposely not implemented
void operator=(const Self &); //purposely not implemented
// give the helper access to member variables, to update iteration
// counts, etc.
friend class LBFGSBOptimizerHelper;
bool m_Trace;
bool m_OptimizerInitialized;
double m_CostFunctionConvergenceFactor;
double m_ProjectedGradientTolerance;
unsigned int m_MaximumNumberOfIterations;
unsigned int m_MaximumNumberOfEvaluations;
unsigned int m_MaximumNumberOfCorrections;
unsigned int m_CurrentIteration;
double m_InfinityNormOfProjectedGradient;
InternalOptimizerType * m_VnlOptimizer;
BoundValueType m_LowerBound;
BoundValueType m_UpperBound;
BoundSelectionType m_BoundSelection;
};
} // end namespace itk
#endif
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