ITK
4.2.0
Insight Segmentation and Registration Toolkit
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#include <itkSingleValuedNonLinearVnlOptimizer.h>
Public Types | |
typedef ReceptorMemberCommand < Self > | CommandType |
typedef SmartPointer< const Self > | ConstPointer |
typedef SmartPointer< Self > | Pointer |
typedef SingleValuedNonLinearVnlOptimizer | Self |
typedef SingleValuedNonLinearOptimizer | Superclass |
Public Types inherited from itk::SingleValuedNonLinearOptimizer | |
typedef CostFunctionType::Pointer | CostFunctionPointer |
typedef SingleValuedCostFunction | CostFunctionType |
typedef CostFunctionType::DerivativeType | DerivativeType |
typedef CostFunctionType::MeasureType | MeasureType |
typedef Superclass::ParametersType | ParametersType |
Public Types inherited from itk::NonLinearOptimizer | |
typedef Superclass::ScalesType | ScalesType |
Public Types inherited from itk::Optimizer | |
Public Types inherited from itk::Object | |
Public Types inherited from itk::LightObject |
Public Member Functions | |
virtual const char * | GetNameOfClass () const |
virtual void | SetCostFunction (SingleValuedCostFunction *costFunction)=0 |
virtual const bool & | GetMaximize () |
virtual void | SetMaximize (bool _arg) |
virtual void | MaximizeOn () |
virtual void | MaximizeOff () |
bool | GetMinimize () const |
void | SetMinimize (bool v) |
void | MinimizeOn () |
void | MinimizeOff () |
Public Member Functions inherited from itk::SingleValuedNonLinearOptimizer | |
virtual ::itk::LightObject::Pointer | CreateAnother (void) const |
virtual const CostFunctionType * | GetCostFunction () |
MeasureType | GetValue (const ParametersType ¶meters) const |
virtual void | SetCostFunction (CostFunctionType *costFunction) |
Protected Types | |
typedef SingleValuedVnlCostFunctionAdaptor | CostFunctionAdaptorType |
Protected Member Functions | |
const CostFunctionAdaptorType * | GetCostFunctionAdaptor (void) const |
CostFunctionAdaptorType * | GetCostFunctionAdaptor (void) |
CostFunctionAdaptorType * | GetNonConstCostFunctionAdaptor (void) const |
void | PrintSelf (std::ostream &os, Indent indent) const |
void | SetCostFunctionAdaptor (CostFunctionAdaptorType *adaptor) |
Protected Member Functions inherited from itk::SingleValuedNonLinearOptimizer | |
SingleValuedNonLinearOptimizer () | |
virtual | ~SingleValuedNonLinearOptimizer () |
NonLinearOptimizer () | |
virtual | ~NonLinearOptimizer () |
Protected Member Functions inherited from itk::Optimizer | |
Optimizer () | |
virtual void | SetCurrentPosition (const ParametersType ¶m) |
virtual | ~Optimizer () |
Protected Member Functions inherited from itk::Object | |
Object () | |
bool | PrintObservers (std::ostream &os, Indent indent) const |
virtual void | SetTimeStamp (const TimeStamp &time) |
virtual | ~Object () |
Protected Member Functions inherited from itk::LightObject | |
virtual LightObject::Pointer | InternalClone () const |
LightObject () | |
virtual void | PrintHeader (std::ostream &os, Indent indent) const |
virtual void | PrintTrailer (std::ostream &os, Indent indent) const |
virtual | ~LightObject () |
Private Member Functions | |
void | IterationReport (const EventObject &event) |
void | operator= (const Self &) |
SingleValuedNonLinearVnlOptimizer (const Self &) |
Private Attributes | |
ParametersType | m_CachedCurrentPosition |
DerivativeType | m_CachedDerivative |
MeasureType | m_CachedValue |
CommandType::Pointer | m_Command |
CostFunctionAdaptorType * | m_CostFunctionAdaptor |
bool | m_Maximize |
virtual const MeasureType & | GetCachedValue () |
virtual const DerivativeType & | GetCachedDerivative () |
virtual const ParametersType & | GetCachedCurrentPosition () |
SingleValuedNonLinearVnlOptimizer () | |
virtual | ~SingleValuedNonLinearVnlOptimizer () |
Additional Inherited Members | |
Static Public Member Functions inherited from itk::SingleValuedNonLinearOptimizer | |
static Pointer | New () |
Protected Attributes inherited from itk::SingleValuedNonLinearOptimizer | |
CostFunctionPointer | m_CostFunction |
This class is a base for the Optimization methods that optimize a single valued function.
It is an Adaptor class for optimizers provided by the vnl library
Definition at line 36 of file itkSingleValuedNonLinearVnlOptimizer.h.
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
Definition at line 48 of file itkSingleValuedNonLinearVnlOptimizer.h.
typedef SmartPointer< const Self > itk::SingleValuedNonLinearVnlOptimizer::ConstPointer |
Reimplemented from itk::SingleValuedNonLinearOptimizer.
Reimplemented in itk::AmoebaOptimizer, itk::LBFGSBOptimizer, itk::ConjugateGradientOptimizer, and itk::LBFGSOptimizer.
Definition at line 44 of file itkSingleValuedNonLinearVnlOptimizer.h.
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Reimplemented in itk::LBFGSBOptimizer, itk::AmoebaOptimizer, itk::LBFGSOptimizer, and itk::ConjugateGradientOptimizer.
Definition at line 95 of file itkSingleValuedNonLinearVnlOptimizer.h.
Reimplemented from itk::SingleValuedNonLinearOptimizer.
Reimplemented in itk::AmoebaOptimizer, itk::LBFGSBOptimizer, itk::ConjugateGradientOptimizer, and itk::LBFGSOptimizer.
Definition at line 43 of file itkSingleValuedNonLinearVnlOptimizer.h.
Standard class typedefs.
Reimplemented from itk::SingleValuedNonLinearOptimizer.
Reimplemented in itk::AmoebaOptimizer, itk::LBFGSBOptimizer, itk::ConjugateGradientOptimizer, and itk::LBFGSOptimizer.
Definition at line 41 of file itkSingleValuedNonLinearVnlOptimizer.h.
Reimplemented from itk::SingleValuedNonLinearOptimizer.
Reimplemented in itk::AmoebaOptimizer, itk::LBFGSBOptimizer, itk::ConjugateGradientOptimizer, and itk::LBFGSOptimizer.
Definition at line 42 of file itkSingleValuedNonLinearVnlOptimizer.h.
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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().
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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().
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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().
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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().
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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().
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Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.
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Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.
Definition at line 72 of file itkSingleValuedNonLinearVnlOptimizer.h.
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Run-time type information (and related methods).
Reimplemented from itk::SingleValuedNonLinearOptimizer.
Reimplemented in itk::AmoebaOptimizer, itk::LBFGSBOptimizer, itk::ConjugateGradientOptimizer, and itk::LBFGSOptimizer.
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The purpose of this method is to get around the lack of const-correctness in VNL cost-functions and optimizers
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Callback function for the Command Observer
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Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.
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Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.
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Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.
Definition at line 78 of file itkSingleValuedNonLinearVnlOptimizer.h.
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inline |
Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.
Definition at line 76 of file itkSingleValuedNonLinearVnlOptimizer.h.
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Types inherited from the superclass
Reimplemented from itk::SingleValuedNonLinearOptimizer.
Reimplemented in itk::LBFGSBOptimizer, itk::AmoebaOptimizer, itk::LBFGSOptimizer, and itk::ConjugateGradientOptimizer.
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Print out internal state
Reimplemented from itk::SingleValuedNonLinearOptimizer.
Reimplemented in itk::LBFGSBOptimizer, itk::AmoebaOptimizer, and itk::LBFGSOptimizer.
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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
Implemented in itk::LBFGSBOptimizer, itk::AmoebaOptimizer, itk::ConjugateGradientOptimizer, and itk::LBFGSOptimizer.
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Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.
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Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.
Definition at line 74 of file itkSingleValuedNonLinearVnlOptimizer.h.
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Definition at line 123 of file itkSingleValuedNonLinearVnlOptimizer.h.
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Definition at line 125 of file itkSingleValuedNonLinearVnlOptimizer.h.
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Definition at line 124 of file itkSingleValuedNonLinearVnlOptimizer.h.
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Definition at line 121 of file itkSingleValuedNonLinearVnlOptimizer.h.
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Definition at line 117 of file itkSingleValuedNonLinearVnlOptimizer.h.
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Definition at line 119 of file itkSingleValuedNonLinearVnlOptimizer.h.