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

#include <itkGoodnessOfFitMixtureModelCostFunction.h>

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

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

[legend]List of all members.

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Detailed Description

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

calculates the goodness-of-fit statstics for multivarate mixture model

The goodness-of-fit statistics for a single model is discrepancy between the observed frequency and the expected frequency. To reduce computational load of multivariate case, this class uses projective method.

The projective multivariate goodness-of-fit statistics calculation follows the following steps:

1) creates a subsample that includes the measurement vectors that fall in a spherical kernel. 2) finds the base axes determined by the eigen vectors of the covariance matrix. 3) project the subsample on to one of the base axes (from step 2) 4) calculates the observed frequencies (in an 1D Histogram object) after projection (step 3) and the expected frequencies (in an 1D Histogram object) 5) calculates the discrepancy between the observed histogram and the expected histogram using a goodness-of-fit statistics 6) repeat step 3) - 5) and sum the goodness-of-fit values

For a mixture model, the above procedure is applied independently for each model (module). The sum of the goodness-of-fit values of models is the goodness-of-fit statistics for the mixture model.

The step 1) - 4) is done by the subclasses of GoodnessOfFitComponentBase, and the step 5) is done by the subclasses of GoodnessOfFitFunctionBase.

To see how this class interacts GoodnessOfFitComponentBase objects and GoodnessOfFitFunctionBase objects, please look at the implementation of the GetValue method of this class.

Better fit means smaller goodness-of-fit value in this implementation. This class is following the SingleValuedCostFunction interfaces so that users can uses this function with any subclasses of SingleValuedNonLinearOptimizer class as long as they do not use GetDerivative and GetValueAndDerivative methods.

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.

See also:

GoodnessOfFitFunctionBase, GoodnessOfFitComponentBase, SingleValuedCostFunction, SingleValuedNonLinearOptimizer

Definition at line 80 of file itkGoodnessOfFitMixtureModelCostFunction.h.

Public Types
typedef GoodnessOfFitComponentBase< TInputSample >	ComponentType
typedef std::vector< ComponentType * >	ComponentVectorType
typedef SmartPointer< const Self >	ConstPointer
typedef Array< double >	DerivativeType
typedef GoodnessOfFitFunctionBase< typename ComponentType::HistogramType >	FunctionType
typedef TInputSample	InputSampleType
typedef TInputSample::MeasurementType	MeasurementType
typedef TInputSample::MeasurementVectorSizeType	MeasurementVectorSizeType
typedef TInputSample::MeasurementVectorType	MeasurementVectorType
typedef SingleValuedCostFunction::MeasureType	MeasureType
typedef Superclass::ParametersType	ParametersType
typedef double	ParametersValueType
typedef SingleValuedCostFunction::ParametersType	ParamtersType
typedef SmartPointer< Self >	Pointer
typedef GoodnessOfFitMixtureModelCostFunction	Self
typedef SingleValuedCostFunction	Superclass
Public Member Functions
void	AddComponent (ComponentType *component)
virtual LightObject::Pointer	CreateAnother () const
virtual void	DebugOff () const
virtual void	DebugOn () const
virtual void	Delete ()
Command *	GetCommand (unsigned long tag)
bool	GetDebug () const
virtual void	GetDerivative (const ParametersType &, DerivativeType &) const
FunctionType *	GetFunction ()
const MetaDataDictionary &	GetMetaDataDictionary (void) const
MetaDataDictionary &	GetMetaDataDictionary (void)
virtual unsigned long	GetMTime () const
virtual const char *	GetNameOfClass () const
virtual unsigned int	GetNumberOfParameters () const
virtual int	GetReferenceCount () const
virtual MeasureType	GetValue (const ParametersType &parameters) const
This method returns the value and derivative of the cost function corresponding *to the specified parameters *virtual void	GetValueAndDerivative (const ParametersType &parameters, MeasureType &value, DerivativeType &derivative) const
bool	HasObserver (const EventObject &event) const
void	InvokeEvent (const EventObject &) const
void	InvokeEvent (const EventObject &)
virtual void	Modified () const
void	Print (std::ostream &os, Indent indent=0) const
virtual void	Register () const
void	RemoveAllObservers ()
void	RemoveObserver (unsigned long tag)
void	SetDebug (bool debugFlag) const
void	SetFunction (FunctionType *core)
void	SetMetaDataDictionary (const MetaDataDictionary &rhs)
virtual void	SetReferenceCount (int)
virtual void	UnRegister () const
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 Member Functions
	GoodnessOfFitMixtureModelCostFunction ()
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	~GoodnessOfFitMixtureModelCostFunction ()
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 GoodnessOfFitComponentBase< TInputSample > itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::ComponentType

Definition at line 109 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> typedef std::vector< ComponentType* > itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::ComponentVectorType

Definition at line 110 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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

Reimplemented from itk::SingleValuedCostFunction. Definition at line 88 of file itkGoodnessOfFitMixtureModelCostFunction.h.

typedef Array<double> itk::SingleValuedCostFunction::DerivativeType [inherited]

DerivativeType typedef. It defines a type used to return the cost function derivative. Reimplemented in itk::CompareHistogramImageToImageMetric< TFixedImage, TMovingImage >, itk::CorrelationCoefficientHistogramImageToImageMetric< TFixedImage, TMovingImage >, itk::GradientDifferenceImageToImageMetric< TFixedImage, TMovingImage >, itk::HistogramImageToImageMetric< TFixedImage, TMovingImage >, itk::ImageToImageMetric< TFixedImage, TMovingImage >, itk::ImageToSpatialObjectMetric< TFixedImage, TMovingSpatialObject >, itk::KappaStatisticImageToImageMetric< TFixedImage, TMovingImage >, itk::KullbackLeiblerCompareHistogramImageToImageMetric< TFixedImage, TMovingImage >, itk::MatchCardinalityImageToImageMetric< TFixedImage, TMovingImage >, itk::MattesMutualInformationImageToImageMetric< TFixedImage, TMovingImage >, itk::MeanReciprocalSquareDifferenceImageToImageMetric< TFixedImage, TMovingImage >, itk::MeanReciprocalSquareDifferencePointSetToImageMetric< TFixedPointSet, TMovingImage >, itk::MeanSquaresHistogramImageToImageMetric< TFixedImage, TMovingImage >, itk::MeanSquaresImageToImageMetric< TFixedImage, TMovingImage >, itk::MeanSquaresPointSetToImageMetric< TFixedPointSet, TMovingImage >, itk::MRIBiasEnergyFunction< TImage, TImageMask, TBiasField >, itk::MutualInformationHistogramImageToImageMetric< TFixedImage, TMovingImage >, itk::MutualInformationImageToImageMetric< TFixedImage, TMovingImage >, itk::NormalizedCorrelationImageToImageMetric< TFixedImage, TMovingImage >, itk::NormalizedCorrelationPointSetToImageMetric< TFixedPointSet, TMovingImage >, itk::NormalizedMutualInformationHistogramImageToImageMetric< TFixedImage, TMovingImage >, itk::PointSetToImageMetric< TFixedPointSet, TMovingImage >, and itk::ShapePriorMAPCostFunctionBase< TFeatureImage, TOutputPixel >. Definition at line 54 of file itkSingleValuedCostFunction.h.

template<class TInputSample> typedef GoodnessOfFitFunctionBase< typename ComponentType::HistogramType > itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::FunctionType

Definition at line 113 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> typedef TInputSample itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::InputSampleType

Definition at line 94 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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

Definition at line 97 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> typedef TInputSample::MeasurementVectorSizeType itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::MeasurementVectorSizeType

Definition at line 99 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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

Definition at line 98 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> typedef SingleValuedCostFunction::MeasureType itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::MeasureType

MeasureType typedef. It defines a type used to return the cost function value. Reimplemented from itk::SingleValuedCostFunction. Definition at line 107 of file itkGoodnessOfFitMixtureModelCostFunction.h.

typedef Superclass::ParametersType itk::SingleValuedCostFunction::ParametersType [inherited]

ParametersType typedef. It defines a position in the optimization search space. Reimplemented from itk::CostFunction. Reimplemented in itk::ImageToImageMetric< TFixedImage, TMovingImage >, itk::ImageToSpatialObjectMetric< TFixedImage, TMovingSpatialObject >, itk::MattesMutualInformationImageToImageMetric< TFixedImage, TMovingImage >, itk::MRIBiasEnergyFunction< TImage, TImageMask, TBiasField >, itk::MutualInformationImageToImageMetric< TFixedImage, TMovingImage >, itk::PointSetToImageMetric< TFixedPointSet, TMovingImage >, itk::ShapePriorMAPCostFunction< TFeatureImage, TOutputPixel >, and itk::ShapePriorMAPCostFunctionBase< TFeatureImage, TOutputPixel >. Definition at line 58 of file itkSingleValuedCostFunction.h.

typedef double itk::CostFunction::ParametersValueType [inherited]

ParametersType typedef. It defines a position in the optimization search space. Definition at line 46 of file itkCostFunction.h.

template<class TInputSample> typedef SingleValuedCostFunction::ParametersType itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::ParamtersType

ParametersType typedef. It defines a position in the optimization search space. Definition at line 103 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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

Reimplemented from itk::SingleValuedCostFunction. Definition at line 87 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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

Standard class typedefs Reimplemented from itk::SingleValuedCostFunction. Definition at line 85 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> typedef SingleValuedCostFunction itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::Superclass

Reimplemented from itk::SingleValuedCostFunction. Definition at line 86 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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Constructor & Destructor Documentation

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

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

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Member Function Documentation

template<class TInputSample> void itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::AddComponent (  ComponentType *  component  )

aceesing methods for the sample manipulator

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.

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.

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

Get the value of the debug flag.

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::GetDerivative (  const ParametersType &  , DerivativeType &  )  const [inline, virtual]

This method returns the derivative of the cost function corresponding to the specified parameters. Implements itk::SingleValuedCostFunction. Definition at line 132 of file itkGoodnessOfFitMixtureModelCostFunction.h.

template<class TInputSample> FunctionType* itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::GetFunction (   )  [inline]

Definition at line 121 of file itkGoodnessOfFitMixtureModelCostFunction.h.

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

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::GoodnessOfFitMixtureModelCostFunction< TInputSample >::GetNameOfClass (   )  const [virtual]

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

template<class TInputSample> virtual unsigned int itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::GetNumberOfParameters (   )  const [virtual]

Return the number of parameters required to compute this cost function. This method MUST be overloaded by derived classes. Implements itk::CostFunction.

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> virtual MeasureType itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::GetValue (  const ParametersType &  parameters  )  const [virtual]

This method returns the value of the cost function corresponding to the specified parameters. Implements itk::SingleValuedCostFunction.

This method returns the value and derivative of the cost function corresponding* to the specified parameters* virtual void itk::SingleValuedCostFunction::GetValueAndDerivative (  const ParametersType &  parameters, MeasureType &  value, DerivativeType &  derivative )  const [inline, virtual, inherited]

Reimplemented in itk::ImageToSpatialObjectMetric< TFixedImage, TMovingSpatialObject >, itk::MattesMutualInformationImageToImageMetric< TFixedImage, TMovingImage >, and itk::MutualInformationImageToImageMetric< TFixedImage, TMovingImage >. Definition at line 71 of file itkSingleValuedCostFunction.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.

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::GoodnessOfFitMixtureModelCostFunction< 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> virtual void itk::Statistics::GoodnessOfFitMixtureModelCostFunction< 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::CostFunction.

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.

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

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

template<class TInputSample> void itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >::SetFunction (  FunctionType *  core  )

aceesing methods for the expected probability histogram

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().

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

Returns: Set the MetaDataDictionary

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

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

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

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

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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:

• itkGoodnessOfFitMixtureModelCostFunction.h

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