anima::NNLSOptimizer Class Reference

Non negative least squares optimizer. Implements Lawson et al method, of squared problem is activated, assumes we pass AtA et AtB and uses Bro and de Jong method. More...

#include <animaNNLSOptimizer.h>

Inheritance diagram for anima::NNLSOptimizer:

Collaboration diagram for anima::NNLSOptimizer:

Public Types
typedef itk::SmartPointer< const Self >	ConstPointer
typedef vnl_matrix< double >	MatrixType
typedef Superclass::ParametersType	ParametersType
typedef itk::SmartPointer< Self >	Pointer
typedef NNLSOptimizer	Self
typedef itk::Optimizer	Superclass
typedef vnl_vector< double >	VectorType

Public Member Functions
virtual ::itk::LightObject::Pointer	CreateAnother (void) const
double	GetCurrentResidual ()
virtual const char *	GetNameOfClass () const
void	SetDataMatrix (const MatrixType &data)
void	SetPoints (const ParametersType &points)
virtual void	SetSquaredProblem (bool _arg)
void	StartOptimization () ITK_OVERRIDE

Static Public Member Functions
static Pointer	New ()

Protected Member Functions
	NNLSOptimizer ()
virtual	~NNLSOptimizer () ITK_OVERRIDE

Detailed Description

Non negative least squares optimizer. Implements Lawson et al method, of squared problem is activated, assumes we pass AtA et AtB and uses Bro and de Jong method.

Definition at line 19 of file animaNNLSOptimizer.h.

Member Typedef Documentation

ConstPointer

typedef itk::SmartPointer<const Self> anima::NNLSOptimizer::ConstPointer

Definition at line 26 of file animaNNLSOptimizer.h.

MatrixType

typedef vnl_matrix<double> anima::NNLSOptimizer::MatrixType

Type of the input matrix data

Definition at line 37 of file animaNNLSOptimizer.h.

ParametersType

typedef Superclass::ParametersType anima::NNLSOptimizer::ParametersType

Definition at line 28 of file animaNNLSOptimizer.h.

Pointer

typedef itk::SmartPointer<Self> anima::NNLSOptimizer::Pointer

Definition at line 25 of file animaNNLSOptimizer.h.

Self

typedef NNLSOptimizer anima::NNLSOptimizer::Self

Standard class typedefs.

Definition at line 23 of file animaNNLSOptimizer.h.

Superclass

typedef itk::Optimizer anima::NNLSOptimizer::Superclass

Definition at line 24 of file animaNNLSOptimizer.h.

VectorType

typedef vnl_vector<double> anima::NNLSOptimizer::VectorType

Definition at line 38 of file animaNNLSOptimizer.h.

Constructor & Destructor Documentation

NNLSOptimizer()

anima::NNLSOptimizer::NNLSOptimizer ( )

inlineprotected

Definition at line 51 of file animaNNLSOptimizer.h.

~NNLSOptimizer()

virtual anima::NNLSOptimizer::~NNLSOptimizer ( )

inlineprotectedvirtual

Definition at line 56 of file animaNNLSOptimizer.h.

Member Function Documentation

CreateAnother()

virtual::itk::LightObject::Pointer anima::NNLSOptimizer::CreateAnother

(

void

)

const

GetCurrentResidual()

double anima::NNLSOptimizer::GetCurrentResidual

(

)

Definition at line 234 of file animaNNLSOptimizer.cxx.

Referenced by anima::MultiT2RelaxometryEstimationImageFilter< TPixelScalarType >::ComputeTikhonovRegularizedSolution().

GetNameOfClass()

virtual const char* anima::NNLSOptimizer::GetNameOfClass ( ) const

virtual

Run-time type information (and related methods).

New()

static Pointer anima::NNLSOptimizer::New ( )

static

Method for creation through the object factory.

Referenced by anima::B1GammaMixtureT2RelaxometryCostFunction::B1GammaMixtureT2RelaxometryCostFunction(), anima::B1GMMRelaxometryCostFunction::B1GMMRelaxometryCostFunction(), anima::GaussianMCMVariableProjectionCost::GaussianMCMVariableProjectionCost(), and anima::MCMEstimatorImageFilter< InputPixelType, OutputPixelType >::SparseInitializeSticks().

SetDataMatrix()

void anima::NNLSOptimizer::SetDataMatrix ( const MatrixType &  data )

inline

Definition at line 43 of file animaNNLSOptimizer.h.

Referenced by anima::MultiT2RelaxometryEstimationImageFilter< TPixelScalarType >::ComputeTikhonovRegularizedSolution().

SetPoints()

void anima::NNLSOptimizer::SetPoints ( const ParametersType &  points )

inline

Definition at line 44 of file animaNNLSOptimizer.h.

Referenced by anima::MultiT2RelaxometryEstimationImageFilter< TPixelScalarType >::ComputeTikhonovRegularizedSolution().

SetSquaredProblem()

virtual void anima::NNLSOptimizer::SetSquaredProblem ( bool  _arg )

virtual

StartOptimization()

void anima::NNLSOptimizer::StartOptimization

(

)

Start optimization.

Definition at line 9 of file animaNNLSOptimizer.cxx.

References anima::CholeskyDecomposition::PerformDecomposition(), anima::CholeskyDecomposition::SetInputMatrix(), and anima::CholeskyDecomposition::SolveLinearSystemInPlace().

Referenced by anima::MultiT2RelaxometryEstimationImageFilter< TPixelScalarType >::ComputeTikhonovRegularizedSolution().

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The documentation for this class was generated from the following files:

• animaNNLSOptimizer.h
• animaNNLSOptimizer.cxx