itk::CumulativeGaussianOptimizer Class Reference
[Numerics, Optimizers]

This is an optimizer specific to estimating the parameters of Cumulative Gaussian sampled data. More...

#include <itkCumulativeGaussianOptimizer.h>

Inheritance diagram for itk::CumulativeGaussianOptimizer:

[legend]Collaboration diagram for itk::CumulativeGaussianOptimizer:

[legend]List of all members.

Public Types
typedef CumulativeGaussianOptimizer	Self
typedef MultipleValuedNonLinearOptimizer	Superclass
typedef SmartPointer< Self >	Pointer
typedef SmartPointer< const Self >	ConstPointer
typedef CumulativeGaussianCostFunction	CostFunctionType
typedef CostFunctionType::MeasureType	MeasureType
Public Member Functions
virtual const char *	GetClassName () const
void	SetDataArray (MeasureType *dataArray)
void	StartOptimization ()
void	SetCostFunction (CostFunctionType::Pointer costFunction)
void	PrintArray (MeasureType *array)
virtual void	SetDifferenceTolerance (double _arg)
virtual void	SetVerbose (bool _arg)
virtual double	GetComputedMean ()
virtual double	GetComputedStandardDeviation ()
virtual double	GetUpperAsymptote ()
virtual double	GetLowerAsymptote ()
virtual MeasureType *	GetFinalSampledArray ()
virtual double	GetFitError ()
Static Public Member Functions
Pointer	New ()
Protected Member Functions
	CumulativeGaussianOptimizer ()
virtual	~CumulativeGaussianOptimizer ()
void	PrintSelf (std::ostream &os, Indent indent) const

---

Detailed Description

This is an optimizer specific to estimating the parameters of Cumulative Gaussian sampled data.

This optimizer will only work if the data array is sampled from a Cumulative Gaussian curve. It's more of a curve fitter than an optimizer, with the advantage of being fast and specific. It works by taking the derivative of the Cumulative Gaussian sample then repeatedly extending the tails of the Gaussian and recalculating the Gaussian parameters until the change in iterations is within tolerance or very small. The Gaussian is then integrated to reproduce the Cumulative Gaussian and the asymptotes are estimated by using least squares fit to estimate the constant from integration.

Definition at line 47 of file itkCumulativeGaussianOptimizer.h.

---

Member Typedef Documentation

typedef SmartPointer<const Self> itk::CumulativeGaussianOptimizer::ConstPointer

Reimplemented from itk::MultipleValuedNonLinearOptimizer. Definition at line 57 of file itkCumulativeGaussianOptimizer.h.

typedef CumulativeGaussianCostFunction itk::CumulativeGaussianOptimizer::CostFunctionType

Cost function typedef. NOTE: This optimizer is specific to fitting a Cumulative Gaussian. Definition at line 60 of file itkCumulativeGaussianOptimizer.h.

typedef CostFunctionType::MeasureType itk::CumulativeGaussianOptimizer::MeasureType

Data array typedef. Reimplemented from itk::MultipleValuedNonLinearOptimizer. Definition at line 63 of file itkCumulativeGaussianOptimizer.h.

typedef SmartPointer<Self> itk::CumulativeGaussianOptimizer::Pointer

Reimplemented from itk::MultipleValuedNonLinearOptimizer. Definition at line 56 of file itkCumulativeGaussianOptimizer.h.

typedef CumulativeGaussianOptimizer itk::CumulativeGaussianOptimizer::Self

Standard typedefs. Reimplemented from itk::MultipleValuedNonLinearOptimizer. Definition at line 54 of file itkCumulativeGaussianOptimizer.h.

typedef MultipleValuedNonLinearOptimizer itk::CumulativeGaussianOptimizer::Superclass

Reimplemented from itk::MultipleValuedNonLinearOptimizer. Definition at line 55 of file itkCumulativeGaussianOptimizer.h.

---

Constructor & Destructor Documentation

itk::CumulativeGaussianOptimizer::CumulativeGaussianOptimizer (   )  [protected]

virtual itk::CumulativeGaussianOptimizer::~CumulativeGaussianOptimizer (   )  [protected, virtual]

---

Member Function Documentation

virtual const char* itk::CumulativeGaussianOptimizer::GetClassName (   )  const [virtual]

Run-time type information (and related methods). Reimplemented from itk::MultipleValuedNonLinearOptimizer.

virtual double itk::CumulativeGaussianOptimizer::GetComputedMean (   )  [virtual]

Set and get macros.

virtual double itk::CumulativeGaussianOptimizer::GetComputedStandardDeviation (   )  [virtual]

Set and get macros.

virtual MeasureType* itk::CumulativeGaussianOptimizer::GetFinalSampledArray (   )  [virtual]

Set and get macros.

virtual double itk::CumulativeGaussianOptimizer::GetFitError (   )  [virtual]

Set and get macros.

virtual double itk::CumulativeGaussianOptimizer::GetLowerAsymptote (   )  [virtual]

Set and get macros.

virtual double itk::CumulativeGaussianOptimizer::GetUpperAsymptote (   )  [virtual]

Set and get macros.

Pointer itk::CumulativeGaussianOptimizer::New (   )  [static]

Method for creation through the object factory. Reimplemented from itk::MultipleValuedNonLinearOptimizer.

void itk::CumulativeGaussianOptimizer::PrintArray (  MeasureType *  array  )

Print an array.

void itk::CumulativeGaussianOptimizer::PrintSelf (  std::ostream &  os, Indent  indent )  const [protected, virtual]

Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes. Reimplemented from itk::Optimizer.

void itk::CumulativeGaussianOptimizer::SetCostFunction (  CostFunctionType::Pointer  costFunction  )

Set the cost function.

void itk::CumulativeGaussianOptimizer::SetDataArray (  MeasureType *  dataArray  )

virtual void itk::CumulativeGaussianOptimizer::SetDifferenceTolerance (  double  _arg  )  [virtual]

Set and get macros.

virtual void itk::CumulativeGaussianOptimizer::SetVerbose (  bool  _arg  )  [virtual]

Set and get macros.

void itk::CumulativeGaussianOptimizer::StartOptimization (   )  [virtual]

Start the optimizer. Reimplemented from itk::Optimizer.

---

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

• itkCumulativeGaussianOptimizer.h

---