ITK  4.2.0
Insight Segmentation and Registration Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Private Member Functions | Private Attributes
itk::CumulativeGaussianOptimizer Class Reference

#include <itkCumulativeGaussianOptimizer.h>

+ Inheritance diagram for itk::CumulativeGaussianOptimizer:
+ Collaboration diagram for itk::CumulativeGaussianOptimizer:

List of all members.

Public Types

typedef SmartPointer< const SelfConstPointer
typedef
CumulativeGaussianCostFunction 
CostFunctionType
typedef
CostFunctionType::MeasureType 
MeasureType
typedef SmartPointer< SelfPointer
typedef CumulativeGaussianOptimizer Self
typedef
MultipleValuedNonLinearOptimizer 
Superclass
- Public Types inherited from itk::MultipleValuedNonLinearOptimizer
typedef CostFunctionType::Pointer CostFunctionPointer
typedef Array2D< double > DerivativeType
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 ::itk::LightObject::Pointer CreateAnother (void) const
virtual const char * GetNameOfClass () const
const std::string GetStopConditionDescription () const
void PrintArray (MeasureType *array)
void SetDataArray (MeasureType *dataArray)
void StartOptimization ()
virtual void SetDifferenceTolerance (double _arg)
virtual void SetVerbose (bool _arg)
virtual double GetComputedMean ()
virtual double GetComputedStandardDeviation ()
virtual double GetUpperAsymptote ()
virtual double GetLowerAsymptote ()
virtual MeasureTypeGetFinalSampledArray ()
virtual double GetFitError ()
- Public Member Functions inherited from itk::MultipleValuedNonLinearOptimizer
virtual void SetCostFunction (CostFunctionType *costFunction)

Static Public Member Functions

static Pointer New ()

Protected Member Functions

 CumulativeGaussianOptimizer ()
void PrintSelf (std::ostream &os, Indent indent) const
virtual ~CumulativeGaussianOptimizer ()
- Protected Member Functions inherited from itk::MultipleValuedNonLinearOptimizer
 MultipleValuedNonLinearOptimizer ()
virtual ~MultipleValuedNonLinearOptimizer ()
 NonLinearOptimizer ()
virtual ~NonLinearOptimizer ()
- Protected Member Functions inherited from itk::Optimizer
 Optimizer ()
virtual void SetCurrentPosition (const ParametersType &param)
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

MeasureTypeExtendGaussian (MeasureType *originalArray, MeasureType *extendedArray, int startingPointForInsertion)
double FindAverageSumOfSquaredDifferences (MeasureType *array1, MeasureType *array2)
void FindParametersOfGaussian (MeasureType *sampledGaussianArray)
void MeasureGaussianParameters (MeasureType *array)
void PrintComputedParameterHeader ()
void PrintComputedParameters ()
MeasureTypeRecalculateExtendedArrayFromGaussianParameters (MeasureType *originalArray, MeasureType *extendedArray, int startingPointForInsertion)
double VerticalBestShift (MeasureType *originalArray, MeasureType *newArray)

Private Attributes

double m_ComputedAmplitude
double m_ComputedMean
double m_ComputedStandardDeviation
double m_ComputedTransitionHeight
MeasureTypem_CumulativeGaussianArray
double m_DifferenceTolerance
MeasureTypem_FinalSampledArray
double m_FitError
double m_LowerAsymptote
double m_OffsetForMean
std::ostringstream m_StopConditionDescription
double m_UpperAsymptote
bool m_Verbose

Additional Inherited Members

- Protected Attributes inherited from itk::MultipleValuedNonLinearOptimizer
CostFunctionPointer m_CostFunction

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

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Definition at line 56 of file itkCumulativeGaussianOptimizer.h.

Cost function typedef. NOTE: This optimizer is specific to fitting a Cumulative Gaussian.

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Definition at line 60 of file itkCumulativeGaussianOptimizer.h.

Data array typedef.

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Definition at line 63 of file itkCumulativeGaussianOptimizer.h.

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Definition at line 55 of file itkCumulativeGaussianOptimizer.h.

Standard typedefs.

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Definition at line 53 of file itkCumulativeGaussianOptimizer.h.

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Definition at line 54 of file itkCumulativeGaussianOptimizer.h.


Constructor & Destructor Documentation

itk::CumulativeGaussianOptimizer::CumulativeGaussianOptimizer ( )
protected
virtual itk::CumulativeGaussianOptimizer::~CumulativeGaussianOptimizer ( )
protectedvirtual

Member Function Documentation

virtual::itk::LightObject::Pointer itk::CumulativeGaussianOptimizer::CreateAnother ( void  ) const
virtual

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::MultipleValuedNonLinearOptimizer.

MeasureType* itk::CumulativeGaussianOptimizer::ExtendGaussian ( MeasureType originalArray,
MeasureType extendedArray,
int  startingPointForInsertion 
)
private

Extend the tails of the Gaussian.

double itk::CumulativeGaussianOptimizer::FindAverageSumOfSquaredDifferences ( MeasureType array1,
MeasureType array2 
)
private

Calculates the squared difference error between each Gaussian iteration loop.

void itk::CumulativeGaussianOptimizer::FindParametersOfGaussian ( MeasureType sampledGaussianArray)
private

Given an array sampled from a Gaussin, compute the final parameters.

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 const char* itk::CumulativeGaussianOptimizer::GetNameOfClass ( ) const
virtual

Run-time type information (and related methods).

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

const std::string itk::CumulativeGaussianOptimizer::GetStopConditionDescription ( ) const
virtual

Report the reason for stopping.

Reimplemented from itk::Optimizer.

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

Set and get macros.

void itk::CumulativeGaussianOptimizer::MeasureGaussianParameters ( MeasureType array)
private

Measure the parameters of a Gaussian sampled array.

static 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::PrintComputedParameterHeader ( )
private

Print the header for output table.

void itk::CumulativeGaussianOptimizer::PrintComputedParameters ( )
private

Print the computed parameters.

void itk::CumulativeGaussianOptimizer::PrintSelf ( std::ostream &  os,
Indent  indent 
) const
protectedvirtual

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::MultipleValuedNonLinearOptimizer.

MeasureType* itk::CumulativeGaussianOptimizer::RecalculateExtendedArrayFromGaussianParameters ( MeasureType originalArray,
MeasureType extendedArray,
int  startingPointForInsertion 
)
private

Recalulate the parameters of the extended Gaussian array.

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.

double itk::CumulativeGaussianOptimizer::VerticalBestShift ( MeasureType originalArray,
MeasureType newArray 
)
private

Find the constant of the integrated sample.


Member Data Documentation

double itk::CumulativeGaussianOptimizer::m_ComputedAmplitude
private

The final amplitude of the Gaussian.

Definition at line 110 of file itkCumulativeGaussianOptimizer.h.

double itk::CumulativeGaussianOptimizer::m_ComputedMean
private

The final mean of the Cumulative Gaussian.

Definition at line 104 of file itkCumulativeGaussianOptimizer.h.

double itk::CumulativeGaussianOptimizer::m_ComputedStandardDeviation
private

The final standard deviation of the Cumulative Gaussian.

Definition at line 107 of file itkCumulativeGaussianOptimizer.h.

double itk::CumulativeGaussianOptimizer::m_ComputedTransitionHeight
private

The transition height (distance between upper and lower asymptotes) of the Cumulative Gaussian.

Definition at line 114 of file itkCumulativeGaussianOptimizer.h.

MeasureType* itk::CumulativeGaussianOptimizer::m_CumulativeGaussianArray
private

Original data array.

Definition at line 136 of file itkCumulativeGaussianOptimizer.h.

double itk::CumulativeGaussianOptimizer::m_DifferenceTolerance
private

When to stop the iteration for the Gaussian extension loop.

Definition at line 101 of file itkCumulativeGaussianOptimizer.h.

MeasureType* itk::CumulativeGaussianOptimizer::m_FinalSampledArray
private

Array of values computed from the final parameters of the Cumulative Gaussian.

Definition at line 133 of file itkCumulativeGaussianOptimizer.h.

double itk::CumulativeGaussianOptimizer::m_FitError
private

Least squares fit error as a measure of goodness.

Definition at line 129 of file itkCumulativeGaussianOptimizer.h.

double itk::CumulativeGaussianOptimizer::m_LowerAsymptote
private

The final lower asymptote of the Cumulative Gaussian.

Definition at line 120 of file itkCumulativeGaussianOptimizer.h.

double itk::CumulativeGaussianOptimizer::m_OffsetForMean
private

Offset for the mean calculation.

Definition at line 123 of file itkCumulativeGaussianOptimizer.h.

std::ostringstream itk::CumulativeGaussianOptimizer::m_StopConditionDescription
private

Describe the stop condition

Definition at line 166 of file itkCumulativeGaussianOptimizer.h.

double itk::CumulativeGaussianOptimizer::m_UpperAsymptote
private

The final upper asymptote of the Cumulative Gaussian.

Definition at line 117 of file itkCumulativeGaussianOptimizer.h.

bool itk::CumulativeGaussianOptimizer::m_Verbose
private

Flag to print iteration results.

Definition at line 126 of file itkCumulativeGaussianOptimizer.h.


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