ITK  4.1.0
Insight Segmentation and Registration Toolkit
Public Types | Public Member Functions | Protected Member Functions | Private Member Functions
itk::Statistics::WeightedCovarianceSampleFilter< TSample > Class Template Reference

#include <itkWeightedCovarianceSampleFilter.h>

+ Inheritance diagram for itk::Statistics::WeightedCovarianceSampleFilter< TSample >:
+ Collaboration diagram for itk::Statistics::WeightedCovarianceSampleFilter< TSample >:

List of all members.

Public Types

typedef SmartPointer< const SelfConstPointer
typedef
SimpleDataObjectDecorator
< WeightArrayType
InputWeightArrayObjectType
typedef DataObjectDecorator
< WeightingFunctionType
InputWeightingFunctionObjectType
typedef
SimpleDataObjectDecorator
< MatrixType
MatrixDecoratedType
typedef VariableSizeMatrix
< double > 
MatrixType
typedef
Superclass::MeasurementRealType 
MeasurementRealType
typedef
Superclass::MeasurementVectorDecoratedType 
MeasurementVectorDecoratedType
typedef
Superclass::MeasurementVectorRealType 
MeasurementVectorRealType
typedef
Superclass::MeasurementVectorSizeType 
MeasurementVectorSizeType
typedef
Superclass::MeasurementVectorType 
MeasurementVectorType
typedef Superclass::OutputType OutputType
typedef SmartPointer< SelfPointer
typedef Superclass::SampleType SampleType
typedef
WeightedCovarianceSampleFilter 
Self
typedef CovarianceSampleFilter
< TSample > 
Superclass
typedef Array< double > WeightArrayType
typedef FunctionBase
< MeasurementVectorType,
double > 
WeightingFunctionType

Public Member Functions

 itkSetGetDecoratedInputMacro (Weights, WeightArrayType)
 itkSetGetDecoratedObjectInputMacro (WeightingFunction, WeightingFunctionType)

Protected Member Functions

void ComputeCovarianceMatrixWithWeightingFunction ()
void ComputeCovarianceMatrixWithWeights ()
void GenerateData ()
void PrintSelf (std::ostream &os, Indent indent) const
 WeightedCovarianceSampleFilter ()
virtual ~WeightedCovarianceSampleFilter ()

Private Member Functions

void operator= (const Self &)
 WeightedCovarianceSampleFilter (const Self &)
virtual const char * GetNameOfClass () const
virtual ::itk::LightObject::Pointer CreateAnother (void) const
static Pointer New ()

Detailed Description

template<class TSample>
class itk::Statistics::WeightedCovarianceSampleFilter< TSample >

Calculates the covariance matrix of the target sample data. where each measurement vector has an associated weight value.

Weight values can be specified in two ways: using a weighting function or an array containing weight values. If none of these two is specified, the covariance matrix is generated with equal weights.

See also:
CovarianceSampleFilter

Definition at line 43 of file itkWeightedCovarianceSampleFilter.h.


Member Typedef Documentation

template<class TSample >
typedef SmartPointer< const Self > itk::Statistics::WeightedCovarianceSampleFilter< TSample >::ConstPointer

Type of DataObjects to use for the weight array type

Definition at line 81 of file itkWeightedCovarianceSampleFilter.h.

Type of DataObjects to use for Weight function

Definition at line 87 of file itkWeightedCovarianceSampleFilter.h.

VariableSizeMatrix is not a DataObject, we need to decorate it to push it down a ProcessObject's pipeline

Reimplemented from itk::Statistics::CovarianceSampleFilter< TSample >.

Definition at line 75 of file itkWeightedCovarianceSampleFilter.h.

template<class TSample >
typedef VariableSizeMatrix< double > itk::Statistics::WeightedCovarianceSampleFilter< TSample >::MatrixType

Typedef for WeightedCovariance output

Reimplemented from itk::Statistics::CovarianceSampleFilter< TSample >.

Definition at line 68 of file itkWeightedCovarianceSampleFilter.h.

MeasurementVector is not a DataObject, we need to decorate it to push it down a ProcessObject's pipeline

Reimplemented from itk::Statistics::CovarianceSampleFilter< TSample >.

Definition at line 62 of file itkWeightedCovarianceSampleFilter.h.

Type of the measurement vector type

Reimplemented from itk::Statistics::CovarianceSampleFilter< TSample >.

Definition at line 65 of file itkWeightedCovarianceSampleFilter.h.

Length of a measurement vector

Reimplemented from itk::Statistics::CovarianceSampleFilter< TSample >.

Definition at line 61 of file itkWeightedCovarianceSampleFilter.h.

Measurement vector type

Reimplemented from itk::Statistics::CovarianceSampleFilter< TSample >.

Definition at line 60 of file itkWeightedCovarianceSampleFilter.h.

template<class TSample >
typedef SmartPointer< Self > itk::Statistics::WeightedCovarianceSampleFilter< TSample >::Pointer

Traits derived from the base class

Reimplemented from itk::Statistics::CovarianceSampleFilter< TSample >.

Definition at line 55 of file itkWeightedCovarianceSampleFilter.h.

Standard class typedefs.

Reimplemented from itk::Statistics::CovarianceSampleFilter< TSample >.

Definition at line 48 of file itkWeightedCovarianceSampleFilter.h.

template<class TSample >
typedef CovarianceSampleFilter< TSample > itk::Statistics::WeightedCovarianceSampleFilter< TSample >::Superclass
template<class TSample >
typedef Array< double > itk::Statistics::WeightedCovarianceSampleFilter< TSample >::WeightArrayType

Array typedef for weights

Definition at line 78 of file itkWeightedCovarianceSampleFilter.h.

Weight calculation function typedef

Definition at line 71 of file itkWeightedCovarianceSampleFilter.h.


Constructor & Destructor Documentation

template<class TSample >
itk::Statistics::WeightedCovarianceSampleFilter< TSample >::WeightedCovarianceSampleFilter ( ) [protected]
template<class TSample >
virtual itk::Statistics::WeightedCovarianceSampleFilter< TSample >::~WeightedCovarianceSampleFilter ( ) [protected, virtual]
template<class TSample >
itk::Statistics::WeightedCovarianceSampleFilter< TSample >::WeightedCovarianceSampleFilter ( const Self ) [private]

Member Function Documentation

template<class TSample >
void itk::Statistics::WeightedCovarianceSampleFilter< TSample >::ComputeCovarianceMatrixWithWeightingFunction ( ) [protected]

Compute covariance matrix with weights computed from a function

template<class TSample >
void itk::Statistics::WeightedCovarianceSampleFilter< TSample >::ComputeCovarianceMatrixWithWeights ( ) [protected]

Compute covariance matrix with weights specified in an array

template<class TSample >
virtual::itk::LightObject::Pointer itk::Statistics::WeightedCovarianceSampleFilter< TSample >::CreateAnother ( void  ) const [virtual]

Standard Macros

Reimplemented from itk::Statistics::CovarianceSampleFilter< TSample >.

template<class TSample >
void itk::Statistics::WeightedCovarianceSampleFilter< TSample >::GenerateData ( void  ) [protected, virtual]

This method causes the filter to generate its output.

Reimplemented from itk::Statistics::CovarianceSampleFilter< TSample >.

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

Standard Macros

Reimplemented from itk::Statistics::CovarianceSampleFilter< TSample >.

template<class TSample >
itk::Statistics::WeightedCovarianceSampleFilter< TSample >::itkSetGetDecoratedInputMacro ( Weights  ,
WeightArrayType   
)

Method to set the input value of the weight array

template<class TSample >
itk::Statistics::WeightedCovarianceSampleFilter< TSample >::itkSetGetDecoratedObjectInputMacro ( WeightingFunction  ,
WeightingFunctionType   
)

Method to set the weighting function

template<class TSample >
static Pointer itk::Statistics::WeightedCovarianceSampleFilter< TSample >::New ( ) [static]

Standard Macros

Reimplemented from itk::Statistics::CovarianceSampleFilter< TSample >.

template<class TSample >
void itk::Statistics::WeightedCovarianceSampleFilter< TSample >::operator= ( const Self ) [private]

Time when GenerateOutputInformation was last called.

Reimplemented from itk::Statistics::CovarianceSampleFilter< TSample >.

template<class TSample >
void itk::Statistics::WeightedCovarianceSampleFilter< TSample >::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::CovarianceSampleFilter< TSample >.


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