itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample > Class Template Reference

#include <itkGaussianGoodnessOfFitComponent.h>

Inheritance diagram for itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >:

[legend]Collaboration diagram for itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >:

[legend]List of all members.

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Detailed Description

template<class TInputSample>
class itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >

is a GoodnessOfFitComponent for Gaussian distribution.

Among the GoodnessOfFitComponentBase's methods, this class provides implementations for the CalculateProjectionAxess, the GetCumulativeProbability (univariate CDF), and the GetProbabilityDensity (multivariate PDF)methods.

The CalculateProjectionAxes method creats an array of projection axes that are the eigen vectors generated from the weighted covariance matrix of the resampled sample using a spherical kernel.

Recent API changes: The static const macro to get the length of a measurement vector, MeasurementVectorSize has been removed to allow the length of a measurement vector to be specified at run time. This is now obtained from the input sample.

See also:

GoodnessOfFitComponentBase, GoodnessOfFitMixtureModelCostFunction

Definition at line 51 of file itkGaussianGoodnessOfFitComponent.h.

Public Types
typedef Superclass::CenterType	CenterType
typedef SmartPointer< const Self >	ConstPointer
typedef WeightedCovarianceCalculator< ResampledSampleType >	CovarianceCalculatorType
typedef ProbabilityDensityFunctionType::CovarianceType	CovarianceType
typedef Array< double >	EigenValuesArrayType
typedef HistogramType::ConstPointer	HistogramConstPointer
typedef HistogramType::Pointer	HistogramPointer
typedef Histogram< float, 1 >	HistogramType
typedef TInputSample	InputSampleType
typedef Superclass::MeanType	MeanType
typedef TInputSample::MeasurementType	MeasurementType
typedef Superclass::MeasurementVectorSizeType	MeasurementVectorSizeType
typedef TInputSample::MeasurementVectorType	MeasurementVectorType
typedef Array< double >	ParametersType
typedef SmartPointer< Self >	Pointer
typedef GaussianDensityFunction< MeasurementVectorType >	ProbabilityDensityFunctionType
typedef Superclass::ProjectionAxisArrayType	ProjectionAxisArrayType
typedef SymmetricEigenAnalysis< ProjectionAxisArrayType, EigenValuesArrayType >	ProjectionAxisCalculatorType
typedef Superclass::RadiusType	RadiusType
typedef Superclass::ResampledSampleType	ResampledSampleType
typedef GaussianGoodnessOfFitComponent	Self
typedef Superclass::StandardDeviationType	StandardDeviationType
typedef GoodnessOfFitComponentBase< TInputSample >	Superclass
Public Member Functions
virtual LightObject::Pointer	CreateAnother () const
virtual void	CreateHistograms ()
virtual void	DebugOff () const
virtual void	DebugOn () const
virtual void	Delete ()
CenterType *	GetCenter ()
Command *	GetCommand (unsigned long tag)
double	GetCumulativeProbability (double x) const
bool	GetDebug () const
HistogramType *	GetExpectedHistogram ()
ParametersType	GetFullParameters () const
double	GetHistogramBinOverlap ()
double	GetHistogramExtent ()
int	GetHistogramNumberOfBins ()
bool	GetHistogramUseEquiProbableBins ()
const TInputSample *	GetInputSample () const
MeanType *	GetMean ()
virtual MeasurementVectorSizeType	GetMeasurementVectorSize () const
const MetaDataDictionary &	GetMetaDataDictionary (void) const
MetaDataDictionary &	GetMetaDataDictionary (void)
virtual unsigned long	GetMTime () const
virtual const char *	GetNameOfClass () const
unsigned int	GetNumberOfParameters () const
HistogramType *	GetObservedHistogram ()
ParametersType *	GetParameters ()
double	GetProbabilityDensity (MeasurementVectorType &measurements) const
virtual double	GetProportion () const
RadiusType *	GetRadius ()
virtual int	GetReferenceCount () const
ResampledSampleType *	GetResampledSample ()
virtual unsigned int	GetResampledSampleSize ()
StandardDeviationType *	GetStandardDeviation ()
double *	GetTotalObservedScale ()
bool	HasObserver (const EventObject &event) const
Set Gets the nubmer of bins of	histograms (expected and observed)*/void SetHistogramNumberOfBins(int numberOfBins)
void	InvokeEvent (const EventObject &) const
void	InvokeEvent (const EventObject &)
virtual void	Modified () const
void	Print (std::ostream &os, Indent indent=0) const
void	PrintParameters (std::ostream &os) const
virtual void	Project (int projectionAxisIndex)
virtual void	Register () const
void	RemoveAllObservers ()
void	RemoveObserver (unsigned long tag)
virtual void	Resample ()
void	SetDebug (bool debugFlag) const
Set Get the overlapping effects extent *void	SetHistogramBinOverlap (double overlap)
Set Gets the extent of histogram from the mean in terms of *standard deivation *void	SetHistogramExtent (double extent)
Set Gets the flag that indicates the probability of each bins in the *histograms should be equal This can be achieved by varying the *interval of bins *void	SetHistogramUseEquiProbableBins (bool flag)
virtual void	SetInputSample (const TInputSample *sample)
void	SetMetaDataDictionary (const MetaDataDictionary &rhs)
void	SetParameters (const ParametersType &parameter)
virtual void	SetReferenceCount (int)
void	SetUseExpectedHistogram (bool flag)
virtual void	UnRegister () const
virtual void	UpdateExpectedHistogram ()
Static Public Member Functions
static void	BreakOnError ()
static bool	GetGlobalWarningDisplay ()
static void	GlobalWarningDisplayOff ()
static void	GlobalWarningDisplayOn ()
static Pointer	New ()
This is a global flag that controls whether any warning *or error messages are displayed *static void	SetGlobalWarningDisplay (bool flag)
Public Attributes
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 unsigned lon	AddObserver )(const EventObject &event, Command *) const
This is a global flag that controls whether any	debug
Protected Types
typedef SampleToHistogramProjectionFilter< ResampledSampleType, float >	ProjectorType
typedef NeighborhoodSampler< TInputSample >	ResamplerType
Protected Member Functions
virtual void	CalculateProjectionAxes ()
virtual void	CreateEquiProbableBins ()
virtual void	CreateEquiRangeBins ()
	GaussianGoodnessOfFitComponent ()
ProjectionAxisArrayType *	GetProjectionAxes ()
bool	PrintObservers (std::ostream &os, Indent indent) const
virtual void	PrintSelf (std::ostream &os, Indent indent) const
virtual void	PrintTrailer (std::ostream &os, Indent indent) const
virtual	~GaussianGoodnessOfFitComponent ()
Protected Attributes
int	m_ReferenceCount
SimpleFastMutexLock	m_ReferenceCountLock
Methods invoked by virtual 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.*/virtual void PrintSelf(std voi	PrintHeader )(std::ostream &os, Indent indent) const

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Member Typedef Documentation

template<class TInputSample> typedef Superclass::CenterType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::CenterType

Typedefs from Superclass Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >. Definition at line 74 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef SmartPointer< const Self > itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::ConstPointer

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >. Definition at line 59 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef WeightedCovarianceCalculator< ResampledSampleType > itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::CovarianceCalculatorType

Type of the covariance calculator. the output of this calculator is a covariance matrix that is used as the input of the Projection calculator Definition at line 94 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef ProbabilityDensityFunctionType::CovarianceType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::CovarianceType

Definition at line 88 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef Array< double > itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::EigenValuesArrayType

Default projection axis calculator type. Definition at line 97 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef HistogramType::ConstPointer itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::HistogramConstPointer [inherited]

Definition at line 117 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> typedef HistogramType::Pointer itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::HistogramPointer [inherited]

Definition at line 116 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> typedef Histogram< float, 1 > itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::HistogramType [inherited]

Histogram type that will be used for observed and expected histogram Definition at line 115 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> typedef TInputSample itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::InputSampleType [inherited]

TInputSample type alias Definition at line 100 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> typedef Superclass::MeanType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::MeanType

Type of the mean of the distribution Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >. Definition at line 76 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef TInputSample::MeasurementType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::MeasurementType

Typedefs from input sample Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >. Definition at line 66 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef Superclass::MeasurementVectorSizeType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::MeasurementVectorSizeType

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >. Definition at line 80 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef TInputSample::MeasurementVectorType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::MeasurementVectorType

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >. Definition at line 71 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef Array< double > itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::ParametersType

Type of the array of component parameters Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >. Definition at line 81 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef SmartPointer< Self > itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::Pointer

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >. Definition at line 58 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef GaussianDensityFunction< MeasurementVectorType > itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::ProbabilityDensityFunctionType

Weight function type. The density values are used as weights of each instance (measurement vector) for the Covariance calulator Definition at line 86 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef Superclass::ProjectionAxisArrayType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::ProjectionAxisArrayType

projection axis array type. The type of output from CalculateProjectionAxis(). The number of projection axis are fixed equal to the number of components of a measurement vector. Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >. Definition at line 79 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef SymmetricEigenAnalysis< ProjectionAxisArrayType, EigenValuesArrayType > itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::ProjectionAxisCalculatorType

Definition at line 99 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef SampleToHistogramProjectionFilter< ResampledSampleType, float > itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::ProjectorType [protected, inherited]

default projection filter type Definition at line 262 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> typedef Superclass::RadiusType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::RadiusType

Type of the radius of the hyperspherical neighborhood sampling Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >. Definition at line 75 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef Superclass::ResampledSampleType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::ResampledSampleType

Resample() output type Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >. Definition at line 78 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef NeighborhoodSampler< TInputSample > itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::ResamplerType [protected, inherited]

default resampler type and realted types Definition at line 258 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> typedef GaussianGoodnessOfFitComponent itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::Self

Standard class typedefs Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >. Definition at line 56 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef Superclass::StandardDeviationType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::StandardDeviationType

Type of standard deviation of the distribution Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >. Definition at line 77 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample> typedef GoodnessOfFitComponentBase< TInputSample > itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::Superclass

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >. Definition at line 57 of file itkGaussianGoodnessOfFitComponent.h.

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Constructor & Destructor Documentation

template<class TInputSample> itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GaussianGoodnessOfFitComponent (   )  [protected]

template<class TInputSample> virtual itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::~GaussianGoodnessOfFitComponent (   )  [protected, virtual]

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Member Function Documentation

static void itk::LightObject::BreakOnError (   )  [static, inherited]

This method is called when itkExceptionMacro executes. It allows the debugger to break on error.

template<class TInputSample> virtual void itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::CalculateProjectionAxes (   )  [protected, virtual]

Calculates the base axes for projection Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

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.

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::CreateEquiProbableBins (   )  [protected, virtual, inherited]

Creates an empty histogram with bins having same probability based on the distribution parameters

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::CreateEquiRangeBins (   )  [protected, virtual, inherited]

Creates an empty histogram with bins having same interval

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::CreateHistograms (   )  [virtual, inherited]

Generates the histogram (expected and observed)

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.

template<class TInputSample> CenterType* itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetCenter (   )  [virtual]

Gets the center point for the neighborhood sampling Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

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.

template<class TInputSample> double itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetCumulativeProbability (  double  x  )  const [virtual]

Univariate (standard) cumulative probability function Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

bool itk::Object::GetDebug (   )  const [inherited]

Get the value of the debug flag.

template<class TInputSample> HistogramType* itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetExpectedHistogram (   )  [inherited]

Gets the expected historm

template<class TInputSample> ParametersType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetFullParameters (   )  const [virtual]

Gets the full distribution parameters which consists of mean vector and covariance matrix in a single array Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

static bool itk::Object::GetGlobalWarningDisplay (   )  [static, inherited]

template<class TInputSample> double itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetHistogramBinOverlap (   )  [inline, inherited]

Definition at line 170 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> double itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetHistogramExtent (   )  [inline, inherited]

Definition at line 177 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> int itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetHistogramNumberOfBins (   )  [inline, inherited]

Definition at line 156 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> bool itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetHistogramUseEquiProbableBins (   )  [inline, inherited]

Definition at line 164 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> const TInputSample* itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetInputSample (   )  const [inherited]

template<class TInputSample> MeanType* itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetMean (   )  [virtual]

Gets the mean of the distributon Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

template<class TInputSample> virtual MeasurementVectorSizeType itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetMeasurementVectorSize (   )  const [virtual, inherited]

Get Macro to get the length of a measurement vector. This is equal to the length of each measurement vector contained in the samples that are plugged in as input to this class. GetMeasurementVectorSize() will return zero until the SetInputSample() method has been called Referenced by itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetNumberOfParameters().

const MetaDataDictionary& itk::Object::GetMetaDataDictionary (  void   )  const [inherited]

Returns: A constant reference to this objects MetaDataDictionary.

MetaDataDictionary& itk::Object::GetMetaDataDictionary (  void   )  [inherited]

Returns: A reference to this objects MetaDataDictionary. Warning: This reference may be changed.

virtual unsigned long itk::Object::GetMTime (   )  const [virtual, inherited]

Return this objects modified time. Reimplemented in itk::ImageRegistrationMethod< TFixedImage, TMovingImage >, itk::DeformationFieldSource< TOutputImage >, itk::InverseDeformationFieldImageFilter< TInputImage, TOutputImage >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::VectorResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::BoundingBox< TPointIdentifier, VPointDimension, TCoordRep, TPointsContainer >, itk::SceneSpatialObject< SpaceDimension >, and itk::SceneSpatialObject< NDimensions >.

template<class TInputSample> virtual const char* itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetNameOfClass (   )  const [virtual]

Run-time type information (and related methods). Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

template<class TInputSample> unsigned int itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetNumberOfParameters (  void   )  const [inline, virtual]

Gets the size of parameters which consists of mean and standard deviation Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >. Definition at line 103 of file itkGaussianGoodnessOfFitComponent.h. References itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetMeasurementVectorSize().

template<class TInputSample> HistogramType* itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetObservedHistogram (   )  [inherited]

Gets the observed historm

template<class TInputSample> ParametersType* itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetParameters (  void   )  [inline, inherited]

Definition at line 146 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> double itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetProbabilityDensity (  MeasurementVectorType &  measurements  )  const [virtual]

Multivariate probability density function Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

template<class TInputSample> ProjectionAxisArrayType* itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetProjectionAxes (   )  [inline, protected, inherited]

Definition at line 271 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> virtual double itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetProportion (   )  const [inline, virtual, inherited]

Gets the proportion of this component among multiple components. Definition at line 231 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> RadiusType* itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetRadius (   )  [virtual]

Gets the radius for the neighborhood sampling Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

virtual int itk::LightObject::GetReferenceCount (   )  const [inline, virtual, inherited]

Gets the reference count on this object. Definition at line 98 of file itkLightObject.h.

template<class TInputSample> ResampledSampleType* itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetResampledSample (   )  [inline, inherited]

Gets the sampled data set Definition at line 200 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> virtual unsigned int itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetResampledSampleSize (   )  [virtual, inherited]

Gest the size of the sampled data set

template<class TInputSample> StandardDeviationType* itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetStandardDeviation (   )  [virtual]

Gets the standard deviation of the distribution Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

template<class TInputSample> double* itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetTotalObservedScale (   )  [inline, inherited]

Gets the total scale of the observed histogram Definition at line 218 of file itkGoodnessOfFitComponentBase.h.

static void itk::Object::GlobalWarningDisplayOff (   )  [inline, static, inherited]

Definition at line 100 of file itkObject.h. References itk::Object::SetGlobalWarningDisplay().

static void itk::Object::GlobalWarningDisplayOn (   )  [inline, static, inherited]

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.

template<class TInputSample> Set Gets the nubmer of bins of itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::histograms (  expected and  observed  )  [inherited]

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::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. Referenced by itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetCenter(), itk::HistogramAlgorithmBase< TInputHistogram >::SetInputHistogram(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetMatrix(), 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< typename ComponentType::HistogramType >::SetTotalObservedScale(), and itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetTranslation().

template<class TInputSample> static Pointer itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::New (   )  [static]

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

void itk::LightObject::Print (  std::ostream &  os, Indent  indent = 0 )  const [inherited]

Cause the object to print itself out.

bool itk::Object::PrintObservers (  std::ostream &  os, Indent  indent )  const [protected, inherited]

template<class TInputSample> void itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::PrintParameters (  std::ostream &  os  )  const [virtual]

Prints all the parameters. Usually for debugging. Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

template<class TInputSample> virtual void itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::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::Statistics::GoodnessOfFitComponentBase< TInputSample >.

virtual void itk::LightObject::PrintTrailer (  std::ostream &  os, Indent  indent )  const [protected, virtual, inherited]

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::Project (  int  projectionAxisIndex  )  [virtual, inherited]

Projects measurement vectors onto the projection axis calculated by the CalculateProjectionAxes method.

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.

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::Resample (   )  [virtual, inherited]

Samples measurement vectors using the center and radius

void itk::Object::SetDebug (  bool  debugFlag  )  const [inherited]

Set the value of the debug flag. A non-zero value turns debugging on.

This is a global flag that controls whether any warning* or error messages are displayed* static void itk::Object::SetGlobalWarningDisplay (  bool  flag  )  [static, inherited]

Referenced by itk::Object::GlobalWarningDisplayOff(), and itk::Object::GlobalWarningDisplayOn().

template<class TInputSample> Set Get the overlapping effects extent* void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::SetHistogramBinOverlap (  double  overlap  )  [inherited]

template<class TInputSample> Set Gets the extent of histogram from the mean in terms of* standard deivation* void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::SetHistogramExtent (  double  extent  )  [inherited]

template<class TInputSample> Set Gets the flag that indicates the probability of each bins in the* histograms should be equal This can be achieved by varying the* interval of bins* void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::SetHistogramUseEquiProbableBins (  bool  flag  )  [inherited]

template<class TInputSample> virtual void itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::SetInputSample (  const TInputSample *  sample  )  [virtual]

Set the input sample Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

void itk::Object::SetMetaDataDictionary (  const MetaDataDictionary &  rhs  )  [inherited]

Returns: Set the MetaDataDictionary

template<class TInputSample> void itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::SetParameters (  const ParametersType &  parameter  )  [virtual]

Sets the component distribution parameters Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

virtual void itk::Object::SetReferenceCount (  int   )  [virtual, inherited]

Sets the reference count (use with care) Reimplemented from itk::LightObject.

template<class TInputSample> void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::SetUseExpectedHistogram (  bool  flag  )  [inherited]

Sets the flag that indicates this component uses the histogram generated with expected distribution from the parameters.

virtual void itk::Object::UnRegister (   )  const [virtual, inherited]

Decrease the reference count (release by another object). Reimplemented from itk::LightObject.

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::UpdateExpectedHistogram (   )  [virtual, inherited]

Fills up the expected histogram based on the distribution parameters

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Member Data Documentation

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 unsigned lon itk::Object::AddObserver)(const EventObject &event, Command *) const [inherited]

This is a global flag that controls whether any itk::Object::debug [inherited]

Definition at line 94 of file itkObject.h.

int itk::LightObject::m_ReferenceCount [mutable, protected, inherited]

Number of uses of this object by other objects. Definition at line 119 of file itkLightObject.h.

SimpleFastMutexLock itk::LightObject::m_ReferenceCountLock [mutable, protected, inherited]

Mutex lock to protect modification to the reference count Definition at line 122 of file itkLightObject.h.

Methods invoked by virtual 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. */ virtual void PrintSelf(std voi itk::LightObject::PrintHeader)(std::ostream &os, Indent indent) const [protected, inherited]

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

• itkGaussianGoodnessOfFitComponent.h

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