itk::LBFGSBOptimizer Class Reference
[Numerics, Optimizers]
#include <itkLBFGSBOptimizer.h>
Detailed Description
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.
Definition at line 59 of file itkLBFGSBOptimizer.h.
Member Typedef Documentation
| typedef Array<long> itk::LBFGSBOptimizer::BoundSelectionType |
BoundSelection type Use for defining the boundary condition for each variables.
Definition at line 83 of file itkLBFGSBOptimizer.h.
| typedef Array<double> itk::LBFGSBOptimizer::BoundValueType |
BoundValue type. Use for defining the lower and upper bounds on the variables.
Definition at line 73 of file itkLBFGSBOptimizer.h.
typedef ReceptorMemberCommand< Self > itk::SingleValuedNonLinearVnlOptimizer::CommandType [inherited] |
Command observer that will interact with the ITK-VNL 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::LBFGSBOptimizer::ConstPointer |
Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.
Definition at line 67 of file itkLBFGSBOptimizer.h.
typedef Superclass::CostFunctionAdaptorType itk::LBFGSBOptimizer::CostFunctionAdaptorType [protected] |
Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.
Definition at line 175 of file itkLBFGSBOptimizer.h.
typedef CostFunctionType::Pointer itk::SingleValuedNonLinearOptimizer::CostFunctionPointer [inherited] |
Reimplemented in itk::FRPROptimizer, itk::OnePlusOneEvolutionaryOptimizer, itk::PowellOptimizer, and itk::RegularStepGradientDescentOptimizer.
Definition at line 56 of file itkSingleValuedNonLinearOptimizer.h.
typedef SingleValuedCostFunction itk::SingleValuedNonLinearOptimizer::CostFunctionType [inherited] |
Type of the Cost Function
Reimplemented in itk::FRPROptimizer, itk::OnePlusOneEvolutionaryOptimizer, itk::PowellOptimizer, and itk::RegularStepGradientDescentOptimizer.
Definition at line 55 of file itkSingleValuedNonLinearOptimizer.h.
typedef CostFunctionType::DerivativeType itk::SingleValuedNonLinearOptimizer::DerivativeType [inherited] |
Derivative type. It defines a type used to return the cost function derivative.
Definition at line 64 of file itkSingleValuedNonLinearOptimizer.h.
| typedef vnl_vector<long> itk::LBFGSBOptimizer::InternalBoundSelectionType |
Internal boundary selection storage type
Definition at line 89 of file itkLBFGSBOptimizer.h.
| typedef vnl_vector<double> itk::LBFGSBOptimizer::InternalBoundValueType |
Internal boundary value storage type
Definition at line 86 of file itkLBFGSBOptimizer.h.
The vnl optimizer
Definition at line 92 of file itkLBFGSBOptimizer.h.
typedef int itk::LightObject::InternalReferenceCountType [protected, inherited] |
Define the type of the reference count according to the target. This allows the use of atomic operations
Definition at line 139 of file itkLightObject.h.
typedef CostFunctionType::MeasureType itk::SingleValuedNonLinearOptimizer::MeasureType [inherited] |
Measure type. It defines a type used to return the cost function value.
Definition at line 60 of file itkSingleValuedNonLinearOptimizer.h.
typedef Superclass::ParametersType itk::SingleValuedNonLinearOptimizer::ParametersType [inherited] |
Parameters type. It defines a position in the optimization search space.
Reimplemented from itk::NonLinearOptimizer.
Reimplemented in itk::AmoebaOptimizer, itk::FRPROptimizer, itk::PowellOptimizer, and itk::QuaternionRigidTransformGradientDescentOptimizer.
Definition at line 48 of file itkSingleValuedNonLinearOptimizer.h.
Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.
Definition at line 66 of file itkLBFGSBOptimizer.h.
typedef Superclass::ScalesType itk::NonLinearOptimizer::ScalesType [inherited] |
Scale type. This array defines scale to be applied to parameters before being evaluated in the cost function. This allows to map to a more convenient space. In particular this is used to normalize parameter spaces in which some parameters have a different dynamic range.
Reimplemented from itk::Optimizer.
Definition at line 52 of file itkNonLinearOptimizer.h.
Standard "Self" typedef.
Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.
Definition at line 64 of file itkLBFGSBOptimizer.h.
Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.
Definition at line 65 of file itkLBFGSBOptimizer.h.
Constructor & Destructor Documentation
| itk::LBFGSBOptimizer::LBFGSBOptimizer | ( | ) | [protected] |
| virtual itk::LBFGSBOptimizer::~LBFGSBOptimizer | ( | ) | [protected, virtual] |
Member Function Documentation
| unsigned long itk::Object::AddObserver | ( | const EventObject & | event, | |
| Command * | ||||
| ) | const [inherited] |
Allow people to add/remove/invoke observers (callbacks) to any ITK object. This is an implementation of the subject/observer design pattern. An observer is added by specifying an event to respond to and an itk::Command to execute. It returns an unsigned long tag which can be used later to remove the event or retrieve the command. The memory for the Command becomes the responsibility of this object, so don't pass the same instance of a command to two different objects
| unsigned long itk::Object::AddObserver | ( | const EventObject & | event, | |
| Command * | ||||
| ) | [inherited] |
Allow people to add/remove/invoke observers (callbacks) to any ITK object. This is an implementation of the subject/observer design pattern. An observer is added by specifying an event to respond to and an itk::Command to execute. It returns an unsigned long tag which can be used later to remove the event or retrieve the command. The memory for the Command becomes the responsibility of this object, so don't pass the same instance of a command to two different objects
| static void itk::LightObject::BreakOnError | ( | ) | [static, inherited] |
This method is called when itkExceptionMacro executes. It allows the debugger to break on error.
| virtual LightObject::Pointer itk::Object::CreateAnother | ( | ) | const [virtual, inherited] |
Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.
Reimplemented from itk::LightObject.
| virtual void itk::Object::DebugOff | ( | ) | const [virtual, inherited] |
Turn debugging output off.
| virtual void itk::Object::DebugOn | ( | ) | const [virtual, inherited] |
Turn debugging output on.
| virtual void itk::LightObject::Delete | ( | ) | [virtual, inherited] |
Delete an itk object. This method should always be used to delete an object when the new operator was used to create it. Using the C delete method will not work with reference counting.
| virtual const BoundSelectionType& itk::LBFGSBOptimizer::GetBoundSelection | ( | ) | [virtual] |
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 const ParametersType& itk::SingleValuedNonLinearVnlOptimizer::GetCachedCurrentPosition | ( | ) | [virtual, inherited] |
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().
| virtual const DerivativeType& itk::SingleValuedNonLinearVnlOptimizer::GetCachedDerivative | ( | ) | [virtual, inherited] |
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().
| virtual const MeasureType& itk::SingleValuedNonLinearVnlOptimizer::GetCachedValue | ( | ) | [virtual, inherited] |
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().
| Command* itk::Object::GetCommand | ( | unsigned long | tag | ) | [inherited] |
Get the command associated with the given tag. NOTE: This returns a pointer to a Command, but it is safe to asign this to a Command::Pointer. Since Command inherits from LightObject, at this point in the code, only a pointer or a reference to the Command can be used.
| virtual const CostFunctionType* itk::SingleValuedNonLinearOptimizer::GetCostFunction | ( | ) | [virtual, inherited] |
Get the cost function.
| CostFunctionAdaptorType* itk::SingleValuedNonLinearVnlOptimizer::GetCostFunctionAdaptor | ( | void | ) | [protected, inherited] |
| const CostFunctionAdaptorType* itk::SingleValuedNonLinearVnlOptimizer::GetCostFunctionAdaptor | ( | void | ) | const [protected, inherited] |
| virtual double itk::LBFGSBOptimizer::GetCostFunctionConvergenceFactor | ( | ) | [virtual] |
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 const unsigned int& itk::LBFGSBOptimizer::GetCurrentIteration | ( | ) | [virtual] |
Get the current iteration number.
| virtual const ParametersType& itk::Optimizer::GetCurrentPosition | ( | ) | [virtual, inherited] |
Get current position of the optimization.
| bool itk::Object::GetDebug | ( | ) | const [inherited] |
Get the value of the debug flag.
| static bool itk::Object::GetGlobalWarningDisplay | ( | ) | [static, inherited] |
This is a global flag that controls whether any debug, warning or error messages are displayed.
| virtual const double& itk::LBFGSBOptimizer::GetInfinityNormOfProjectedGradient | ( | ) | [virtual] |
Get the current infinity norm of the project gradient of the cost function.
| virtual const ParametersType& itk::Optimizer::GetInitialPosition | ( | ) | [virtual, inherited] |
Get the position to initialize the optimization.
| virtual const BoundValueType& itk::LBFGSBOptimizer::GetLowerBound | ( | ) | [virtual] |
Set the lower bound value for each variable.
| virtual const bool& itk::SingleValuedNonLinearVnlOptimizer::GetMaximize | ( | ) | [virtual, inherited] |
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.
| virtual unsigned int itk::LBFGSBOptimizer::GetMaximumNumberOfCorrections | ( | ) | [virtual] |
Set/Get the MaximumNumberOfCorrections. Default is 5
| virtual unsigned int itk::LBFGSBOptimizer::GetMaximumNumberOfEvaluations | ( | ) | [virtual] |
Set/Get the MaximumNumberOfEvaluations. Default is 500
| virtual unsigned int itk::LBFGSBOptimizer::GetMaximumNumberOfIterations | ( | ) | [virtual] |
Set/Get the MaximumNumberOfIterations. Default is 500
| const MetaDataDictionary& itk::Object::GetMetaDataDictionary | ( | void | ) | const [inherited] |
- Returns:
- A constant reference to this objects MetaDataDictionary.
| MetaDataDictionary& itk::Object::GetMetaDataDictionary | ( | void | ) | [inherited] |
| bool itk::SingleValuedNonLinearVnlOptimizer::GetMinimize | ( | ) | const [inline, inherited] |
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.
| virtual unsigned long itk::Object::GetMTime | ( | ) | const [virtual, inherited] |
Return this objects modified time.
Reimplemented in itk::ImageRegistrationMethod< TFixedImage, TMovingImage >, itk::ImageToSpatialObjectRegistrationMethod< TFixedImage, TMovingSpatialObject >, itk::MultiResolutionImageRegistrationMethod< TFixedImage, TMovingImage >, itk::PointSetToImageRegistrationMethod< TFixedPointSet, TMovingImage >, itk::PointSetToPointSetRegistrationMethod< TFixedPointSet, TMovingPointSet >, itk::DeformationFieldSource< TOutputImage >, itk::InverseDeformationFieldImageFilter< TInputImage, TOutputImage >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::VectorResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::BoundingBox< TPointIdentifier, VPointDimension, TCoordRep, TPointsContainer >, itk::ImageAdaptor< TImage, TAccessor >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::TransformToDeformationFieldSource< TOutputImage, TTransformPrecisionType >, itk::ImageSpatialObject< TDimension, TPixelType >, itk::MeshSpatialObject< TMesh >, itk::SceneSpatialObject< TSpaceDimension >, itk::SpatialObject< TDimension >, itk::ImageAdaptor< TImage, itk::Accessor::AsinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::AbsPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::LogPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::ComplexToPhasePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::Log10PixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::ExpPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::AddPixelAccessor< TImage::PixelType > >, itk::ImageAdaptor< itk::VectorImage< TPixelType, Dimension >, itk::Accessor::VectorImageToImagePixelAccessor< TPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::RGBToVectorPixelAccessor< TImage::PixelType::ComponentType > >, itk::ImageAdaptor< TImage, itk::PixelAccessor< TInternalType, TExternalType > >, itk::ImageAdaptor< TImage, itk::Accessor::SqrtPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::AcosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::ComplexToModulusPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::ExpNegativePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::VectorToRGBPixelAccessor< TImage::PixelType::ValueType > >, itk::ImageAdaptor< TImage, itk::Accessor::TanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::ComplexToRealPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::RGBToLuminancePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::AtanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::SinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::ComplexToImaginaryPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::CosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageSpatialObject< TDimension, unsigned char >, itk::SpatialObject< 3 >, and itk::SpatialObject< ::itk::GetMeshDimension< TMesh >::PointDimension >.
Referenced by itk::SpatialObject< ::itk::GetMeshDimension< TMesh >::PointDimension >::GetObjectMTime().
| virtual const char* itk::LBFGSBOptimizer::GetNameOfClass | ( | ) | const [virtual] |
Run-time type information (and related methods).
Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.
| CostFunctionAdaptorType* itk::SingleValuedNonLinearVnlOptimizer::GetNonConstCostFunctionAdaptor | ( | void | ) | const [protected, inherited] |
The purpose of this method is to get around the lack of const-correctness in VNL cost-functions and optimizers
| virtual double itk::LBFGSBOptimizer::GetProjectedGradientTolerance | ( | ) | [virtual] |
Set/Get the ProjectedGradientTolerance. Algorithm terminates when the project gradient is below the tolerance. Default value is 1e-5.
| virtual int itk::LightObject::GetReferenceCount | ( | ) | const [inline, virtual, inherited] |
Gets the reference count on this object.
Definition at line 106 of file itkLightObject.h.
| virtual const ScalesType& itk::Optimizer::GetScales | ( | ) | [virtual, inherited] |
Get current parameters scaling.
| virtual const BoundValueType& itk::LBFGSBOptimizer::GetUpperBound | ( | ) | [virtual] |
Set the upper bound value for each variable.
| MeasureType itk::SingleValuedNonLinearOptimizer::GetValue | ( | const ParametersType & | parameters | ) | const [inherited] |
Get the cost function value at the given parameters.
Reimplemented in itk::SPSAOptimizer.
| virtual const MeasureType& itk::LBFGSBOptimizer::GetValue | ( | ) | [virtual] |
Get the current cost function value.
| static void itk::Object::GlobalWarningDisplayOff | ( | ) | [inline, static, inherited] |
This is a global flag that controls whether any debug, warning or error messages are displayed.
Definition at line 100 of file itkObject.h.
References itk::Object::SetGlobalWarningDisplay().
| static void itk::Object::GlobalWarningDisplayOn | ( | ) | [inline, static, inherited] |
This is a global flag that controls whether any debug, warning or error messages are displayed.
Definition at line 98 of file itkObject.h.
References itk::Object::SetGlobalWarningDisplay().
| bool itk::Object::HasObserver | ( | const EventObject & | event | ) | const [inherited] |
Return true if an observer is registered for this event.
| void itk::Object::InvokeEvent | ( | const EventObject & | ) | const [inherited] |
Call Execute on all the Commands observing this event id. The actions triggered by this call doesn't modify this object.
| void itk::Object::InvokeEvent | ( | const EventObject & | ) | [inherited] |
Call Execute on all the Commands observing this event id.
| virtual void itk::SingleValuedNonLinearVnlOptimizer::MaximizeOff | ( | ) | [virtual, inherited] |
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.
| virtual void itk::SingleValuedNonLinearVnlOptimizer::MaximizeOn | ( | ) | [virtual, inherited] |
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.
| void itk::SingleValuedNonLinearVnlOptimizer::MinimizeOff | ( | void | ) | [inline, inherited] |
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.
| void itk::SingleValuedNonLinearVnlOptimizer::MinimizeOn | ( | void | ) | [inline, inherited] |
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.
| virtual void itk::Object::Modified | ( | ) | const [virtual, inherited] |
Update the modification time for this object. Many filters rely on the modification time to determine if they need to recompute their data.
Reimplemented in itk::NormalizeImageFilter< TInputImage, TOutputImage >, itk::ImageAdaptor< TImage, TAccessor >, itk::MiniPipelineSeparableImageFilter< TInputImage, TOutputImage, TFilter >, itk::GrayscaleDilateImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleErodeImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleMorphologicalClosingImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleMorphologicalOpeningImageFilter< TInputImage, TOutputImage, TKernel >, itk::MorphologicalGradientImageFilter< TInputImage, TOutputImage, TKernel >, itk::ImageAdaptor< TImage, itk::Accessor::AsinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::AbsPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::LogPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::ComplexToPhasePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::Log10PixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::ExpPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::AddPixelAccessor< TImage::PixelType > >, itk::ImageAdaptor< itk::VectorImage< TPixelType, Dimension >, itk::Accessor::VectorImageToImagePixelAccessor< TPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::RGBToVectorPixelAccessor< TImage::PixelType::ComponentType > >, itk::ImageAdaptor< TImage, itk::PixelAccessor< TInternalType, TExternalType > >, itk::ImageAdaptor< TImage, itk::Accessor::SqrtPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::AcosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::ComplexToModulusPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::ExpNegativePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::VectorToRGBPixelAccessor< TImage::PixelType::ValueType > >, itk::ImageAdaptor< TImage, itk::Accessor::TanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::ComplexToRealPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::RGBToLuminancePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::AtanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::SinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::ComplexToImaginaryPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, itk::Accessor::CosPixelAccessor< TImage::PixelType, TOutputPixelType > >, and itk::MiniPipelineSeparableImageFilter< TInputImage, TOutputImage, itk::RankImageFilter< TInputImage, TInputImage, itk::FlatStructuringElement< ::itk::GetImageDimension< TInputImage >::ImageDimension > > >.
Referenced by itk::NarrowBandImageFilterBase< TInputImage, itk::Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::InsertNarrowBandNode(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetCenter(), itk::HistogramAlgorithmBase< TInputHistogram >::SetInputHistogram(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetMatrix(), itk::NarrowBandImageFilterBase< TInputImage, itk::Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBand(), itk::NarrowBandImageFilterBase< TInputImage, itk::Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBandInnerRadius(), itk::NarrowBandImageFilterBase< TInputImage, itk::Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBandTotalRadius(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetOffset(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetRealThresholds(), itk::CollidingFrontsImageFilter< TInputImage, TOutputImage >::SetSeedPoints1(), itk::CollidingFrontsImageFilter< TInputImage, TOutputImage >::SetSeedPoints2(), itk::NonUniformBSpline< TDimension >::SetSplineOrder(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetThresholds(), itk::Statistics::GoodnessOfFitFunctionBase< TInputHistogram >::SetTotalObservedScale(), and itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetTranslation().
| static Pointer itk::LBFGSBOptimizer::New | ( | ) | [static] |
Method for creation through the object factory.
Reimplemented from itk::SingleValuedNonLinearOptimizer.
| void itk::LightObject::Print | ( | std::ostream & | os, | |
| Indent | indent = 0 | |||
| ) | const [inherited] |
Cause the object to print itself out.
Referenced by itk::WeakPointer< itk::ProcessObject >::Print(), and itk::SmartPointer< itk::MutualInformationImageToImageMetric >::Print().
| virtual void itk::LightObject::PrintHeader | ( | std::ostream & | os, | |
| Indent | indent | |||
| ) | const [protected, virtual, inherited] |
| bool itk::Object::PrintObservers | ( | std::ostream & | os, | |
| Indent | indent | |||
| ) | const [protected, inherited] |
| void itk::LBFGSBOptimizer::PrintSelf | ( | std::ostream & | os, | |
| Indent | indent | |||
| ) | const [protected, virtual] |
Print out internal state
Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.
| virtual void itk::LightObject::PrintTrailer | ( | std::ostream & | os, | |
| Indent | indent | |||
| ) | const [protected, virtual, inherited] |
| virtual void itk::Object::Register | ( | ) | const [virtual, inherited] |
Increase the reference count (mark as used by another object).
Reimplemented from itk::LightObject.
| void itk::Object::RemoveAllObservers | ( | ) | [inherited] |
Remove all observers .
| void itk::Object::RemoveObserver | ( | unsigned long | tag | ) | [inherited] |
Remove the observer with this tag value.
| virtual void itk::LBFGSBOptimizer::SetBoundSelection | ( | const BoundSelectionType & | select | ) | [virtual] |
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 itk::SingleValuedNonLinearOptimizer::SetCostFunction | ( | CostFunctionType * | costFunction | ) | [virtual, inherited] |
Set the cost function.
| virtual void itk::LBFGSBOptimizer::SetCostFunction | ( | SingleValuedCostFunction * | costFunction | ) | [virtual] |
Plug in a Cost Function into the optimizer
Implements itk::SingleValuedNonLinearVnlOptimizer.
| void itk::SingleValuedNonLinearVnlOptimizer::SetCostFunctionAdaptor | ( | CostFunctionAdaptorType * | adaptor | ) | [protected, inherited] |
| virtual void itk::LBFGSBOptimizer::SetCostFunctionConvergenceFactor | ( | double | ) | [virtual] |
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 itk::Optimizer::SetCurrentPosition | ( | const ParametersType & | param | ) | [protected, virtual, inherited] |
Set the current position.
| void itk::Object::SetDebug | ( | bool | debugFlag | ) | const [inherited] |
Set the value of the debug flag. A non-zero value turns debugging on.
| static void itk::Object::SetGlobalWarningDisplay | ( | bool | flag | ) | [static, inherited] |
This is a global flag that controls whether any debug, warning or error messages are displayed.
Referenced by itk::Object::GlobalWarningDisplayOff(), and itk::Object::GlobalWarningDisplayOn().
| virtual void itk::Optimizer::SetInitialPosition | ( | const ParametersType & | param | ) | [virtual, inherited] |
Set the position to initialize the optimization.
| virtual void itk::LBFGSBOptimizer::SetLowerBound | ( | const BoundValueType & | value | ) | [virtual] |
Set the lower bound value for each variable.
| virtual void itk::SingleValuedNonLinearVnlOptimizer::SetMaximize | ( | bool | _arg | ) | [virtual, inherited] |
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.
| virtual void itk::LBFGSBOptimizer::SetMaximumNumberOfCorrections | ( | unsigned | int | ) | [virtual] |
Set/Get the MaximumNumberOfCorrections. Default is 5
| virtual void itk::LBFGSBOptimizer::SetMaximumNumberOfEvaluations | ( | unsigned | int | ) | [virtual] |
Set/Get the MaximumNumberOfEvaluations. Default is 500
| virtual void itk::LBFGSBOptimizer::SetMaximumNumberOfIterations | ( | unsigned | int | ) | [virtual] |
Set/Get the MaximumNumberOfIterations. Default is 500
| void itk::Object::SetMetaDataDictionary | ( | const MetaDataDictionary & | rhs | ) | [inherited] |
- Returns:
- Set the MetaDataDictionary
| void itk::SingleValuedNonLinearVnlOptimizer::SetMinimize | ( | bool | v | ) | [inline, inherited] |
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.
| virtual void itk::LBFGSBOptimizer::SetProjectedGradientTolerance | ( | double | ) | [virtual] |
Set/Get the ProjectedGradientTolerance. Algorithm terminates when the project gradient is below the tolerance. Default value is 1e-5.
| virtual void itk::Object::SetReferenceCount | ( | int | ) | [virtual, inherited] |
Sets the reference count (use with care)
Reimplemented from itk::LightObject.
| void itk::Optimizer::SetScales | ( | const ScalesType & | scales | ) | [inherited] |
Set current parameters scaling.
| void itk::LBFGSBOptimizer::SetScales | ( | const ScalesType & | ) | [inline] |
This optimizer does not support scaling of the derivatives.
Definition at line 155 of file itkLBFGSBOptimizer.h.
References itkExceptionMacro.
| virtual void itk::LBFGSBOptimizer::SetUpperBound | ( | const BoundValueType & | value | ) | [virtual] |
Set the upper bound value for each variable.
| void itk::LBFGSBOptimizer::StartOptimization | ( | void | ) | [virtual] |
Start optimization with an initial value.
Reimplemented from itk::Optimizer.
| virtual void itk::Object::UnRegister | ( | ) | const [virtual, inherited] |
Decrease the reference count (release by another object).
Reimplemented from itk::LightObject.
Referenced by itk::SmartPointer< itk::MutualInformationImageToImageMetric >::operator=().
Friends And Related Function Documentation
friend class LBFGSBOptimizerHelper [friend] |
Definition at line 183 of file itkLBFGSBOptimizer.h.
Member Data Documentation
CostFunctionPointer itk::SingleValuedNonLinearOptimizer::m_CostFunction [protected, inherited] |
Definition at line 80 of file itkSingleValuedNonLinearOptimizer.h.
ParametersType itk::Optimizer::m_CurrentPosition [protected, inherited] |
Definition at line 95 of file itkOptimizer.h.
InternalReferenceCountType itk::LightObject::m_ReferenceCount [mutable, protected, inherited] |
Number of uses of this object by other objects.
Definition at line 144 of file itkLightObject.h.
SimpleFastMutexLock itk::LightObject::m_ReferenceCountLock [mutable, protected, inherited] |
Mutex lock to protect modification to the reference count
Definition at line 147 of file itkLightObject.h.
bool itk::Optimizer::m_ScalesInitialized [protected, inherited] |
Definition at line 90 of file itkOptimizer.h.
The documentation for this class was generated from the following file:
