A class for multivariate principal component analysis. More...

#include <vtkPCAStatistics.h>

Inheritance diagram for vtkPCAStatistics:

Collaboration diagram for vtkPCAStatistics:

Public Types
typedef vtkMultiCorrelativeStatistics	Superclass


enum	NormalizationType { NONE, TRIANGLE_SPECIFIED, DIAGONAL_SPECIFIED, DIAGONAL_VARIANCE, NUM_NORMALIZATION_SCHEMES }


enum	ProjectionType { FULL_BASIS, FIXED_BASIS_SIZE, FIXED_BASIS_ENERGY, NUM_BASIS_SCHEMES }

Public Types inherited from vtkMultiCorrelativeStatistics
typedef vtkStatisticsAlgorithm	Superclass

Public Types inherited from vtkStatisticsAlgorithm
typedef vtkTableAlgorithm	Superclass

enum	InputPorts { INPUT_DATA = 0, LEARN_PARAMETERS = 1, INPUT_MODEL = 2 }

enum	OutputIndices { OUTPUT_DATA = 0, OUTPUT_MODEL = 1, OUTPUT_TEST = 2 }

Public Types inherited from vtkTableAlgorithm
typedef vtkAlgorithm	Superclass

Public Types inherited from vtkAlgorithm
typedef vtkObject	Superclass

enum	DesiredOutputPrecision { SINGLE_PRECISION, DOUBLE_PRECISION, DEFAULT_PRECISION }

Public Types inherited from vtkObject
typedef vtkObjectBase	Superclass

Public Member Functions
virtual int	IsA (const char *type)

vtkPCAStatistics *	NewInstance () const

virtual void	PrintSelf (ostream &os, vtkIndent indent)


virtual void	SetNormalizationScheme (int)

virtual int	GetNormalizationScheme ()

virtual void	SetNormalizationSchemeByName (const char *sname)

virtual const char *	GetNormalizationSchemeName (int scheme)


virtual vtkTable *	GetSpecifiedNormalization ()

virtual void	SetSpecifiedNormalization (vtkTable *)


void	GetEigenvalues (int request, vtkDoubleArray *)

void	GetEigenvalues (vtkDoubleArray *)

double	GetEigenvalue (int request, int i)

double	GetEigenvalue (int i)


void	GetEigenvectors (int request, vtkDoubleArray *eigenvectors)

void	GetEigenvectors (vtkDoubleArray *eigenvectors)

void	GetEigenvector (int i, vtkDoubleArray *eigenvector)

void	GetEigenvector (int request, int i, vtkDoubleArray *eigenvector)


virtual void	SetBasisScheme (int)

virtual int	GetBasisScheme ()

virtual const char *	GetBasisSchemeName (int schemeIndex)

virtual void	SetBasisSchemeByName (const char *schemeName)


virtual void	SetFixedBasisSize (int)

virtual int	GetFixedBasisSize ()


virtual void	SetFixedBasisEnergy (double)

virtual double	GetFixedBasisEnergy ()


virtual bool	SetParameter (const char *parameter, int index, vtkVariant value)

Public Member Functions inherited from vtkMultiCorrelativeStatistics
vtkMultiCorrelativeStatistics *	NewInstance () const

virtual void	Aggregate (vtkDataObjectCollection , vtkMultiBlockDataSet )

virtual void	SetMedianAbsoluteDeviation (bool)

virtual bool	GetMedianAbsoluteDeviation ()

virtual void	MedianAbsoluteDeviationOn ()

virtual void	MedianAbsoluteDeviationOff ()

Public Member Functions inherited from vtkStatisticsAlgorithm
vtkStatisticsAlgorithm *	NewInstance () const

void	PrintSelf (ostream &os, vtkIndent indent)

virtual void	SetColumnStatus (const char *namCol, int status)

virtual void	ResetAllColumnStates ()

virtual int	RequestSelectedColumns ()

virtual void	ResetRequests ()

virtual vtkIdType	GetNumberOfRequests ()

virtual vtkIdType	GetNumberOfColumnsForRequest (vtkIdType request)

void	AddColumn (const char *namCol)

void	AddColumnPair (const char namColX, const char namColY)

virtual void	SetLearnOptionParameterConnection (vtkAlgorithmOutput *params)

virtual void	SetLearnOptionParameters (vtkDataObject *params)

virtual void	SetInputModelConnection (vtkAlgorithmOutput *model)

virtual void	SetInputModel (vtkDataObject *model)

virtual void	SetLearnOption (bool)

virtual bool	GetLearnOption ()

virtual void	SetDeriveOption (bool)

virtual bool	GetDeriveOption ()

virtual void	SetAssessOption (bool)

virtual bool	GetAssessOption ()

virtual void	SetTestOption (bool)

virtual bool	GetTestOption ()

virtual void	SetNumberOfPrimaryTables (vtkIdType)

virtual vtkIdType	GetNumberOfPrimaryTables ()

virtual void	SetAssessNames (vtkStringArray *)

virtual vtkStringArray *	GetAssessNames ()

virtual const char *	GetColumnForRequest (vtkIdType r, vtkIdType c)

virtual int	GetColumnForRequest (vtkIdType r, vtkIdType c, vtkStdString &columnName)

Public Member Functions inherited from vtkTableAlgorithm
vtkTableAlgorithm *	NewInstance () const

virtual int	ProcessRequest (vtkInformation , vtkInformationVector , vtkInformationVector )

vtkTable *	GetOutput ()

vtkTable *	GetOutput (int index)

void	SetInputData (vtkDataObject *obj)

void	SetInputData (int index, vtkDataObject *obj)

Public Member Functions inherited from vtkAlgorithm
vtkAlgorithm *	NewInstance () const

int	HasExecutive ()

vtkExecutive *	GetExecutive ()

virtual void	SetExecutive (vtkExecutive *executive)

virtual int	ModifyRequest (vtkInformation *request, int when)

vtkInformation *	GetInputPortInformation (int port)

vtkInformation *	GetOutputPortInformation (int port)

int	GetNumberOfInputPorts ()

int	GetNumberOfOutputPorts ()

void	UpdateProgress (double amount)

vtkInformation *	GetInputArrayInformation (int idx)

void	RemoveAllInputs ()

vtkDataObject *	GetOutputDataObject (int port)

virtual void	RemoveInputConnection (int port, vtkAlgorithmOutput *input)

virtual void	RemoveInputConnection (int port, int idx)

virtual void	RemoveAllInputConnections (int port)

int	GetNumberOfInputConnections (int port)

int	GetTotalNumberOfInputConnections ()

vtkAlgorithmOutput *	GetInputConnection (int port, int index)

vtkAlgorithm *	GetInputAlgorithm (int port, int index, int &algPort)

vtkAlgorithm *	GetInputAlgorithm (int port, int index)

vtkExecutive *	GetInputExecutive (int port, int index)

vtkInformation *	GetInputInformation (int port, int index)

vtkInformation *	GetOutputInformation (int port)

virtual void	UpdateInformation ()

virtual void	UpdateDataObject ()

virtual void	PropagateUpdateExtent ()

virtual void	UpdateWholeExtent ()

void	ConvertTotalInputToPortConnection (int ind, int &port, int &conn)

int	SetUpdateExtentToWholeExtent (int port)

int	SetUpdateExtentToWholeExtent ()

void	SetUpdateExtent (int port, int extent[6])

int	ProcessRequest (vtkInformation request, vtkCollection inInfo, vtkInformationVector *outInfo)

virtual int	ComputePipelineMTime (vtkInformation request, vtkInformationVector inInfoVec, vtkInformationVector outInfoVec, int requestFromOutputPort, unsigned long *mtime)

virtual vtkInformation *	GetInformation ()

virtual void	SetInformation (vtkInformation *)

virtual void	Register (vtkObjectBase *o)

virtual void	UnRegister (vtkObjectBase *o)

virtual void	SetAbortExecute (int)

virtual int	GetAbortExecute ()

virtual void	AbortExecuteOn ()

virtual void	AbortExecuteOff ()

virtual void	SetProgress (double)

virtual double	GetProgress ()

void	SetProgressText (const char *ptext)

virtual char *	GetProgressText ()

virtual unsigned long	GetErrorCode ()

virtual void	SetInputArrayToProcess (int idx, int port, int connection, int fieldAssociation, const char *name)

virtual void	SetInputArrayToProcess (int idx, int port, int connection, int fieldAssociation, int fieldAttributeType)

virtual void	SetInputArrayToProcess (int idx, vtkInformation *info)

virtual void	SetInputArrayToProcess (int idx, int port, int connection, const char fieldAssociation, const char attributeTypeorName)

vtkDataObject *	GetInputDataObject (int port, int connection)

virtual void	SetInputConnection (int port, vtkAlgorithmOutput *input)

virtual void	SetInputConnection (vtkAlgorithmOutput *input)

virtual void	AddInputConnection (int port, vtkAlgorithmOutput *input)

virtual void	AddInputConnection (vtkAlgorithmOutput *input)

virtual void	SetInputDataObject (int port, vtkDataObject *data)

virtual void	SetInputDataObject (vtkDataObject *data)

virtual void	AddInputDataObject (int port, vtkDataObject *data)

virtual void	AddInputDataObject (vtkDataObject *data)

vtkAlgorithmOutput *	GetOutputPort (int index)

vtkAlgorithmOutput *	GetOutputPort ()

vtkAlgorithm *	GetInputAlgorithm ()

vtkExecutive *	GetInputExecutive ()

vtkInformation *	GetInputInformation ()

virtual void	Update (int port)

virtual void	Update ()

virtual void	SetReleaseDataFlag (int)

virtual int	GetReleaseDataFlag ()

void	ReleaseDataFlagOn ()

void	ReleaseDataFlagOff ()

int	UpdateExtentIsEmpty (vtkInformation pinfo, vtkDataObject output)

int	UpdateExtentIsEmpty (vtkInformation *pinfo, int extentType)

void	SetUpdateExtent (int port, int piece, int numPieces, int ghostLevel)

void	SetUpdateExtent (int piece, int numPieces, int ghostLevel)

void	SetUpdateExtent (int extent[6])

int *	GetUpdateExtent ()

int *	GetUpdateExtent (int port)

void	GetUpdateExtent (int &x0, int &x1, int &y0, int &y1, int &z0, int &z1)

void	GetUpdateExtent (int port, int &x0, int &x1, int &y0, int &y1, int &z0, int &z1)

void	GetUpdateExtent (int extent[6])

void	GetUpdateExtent (int port, int extent[6])

int	GetUpdatePiece ()

int	GetUpdatePiece (int port)

int	GetUpdateNumberOfPieces ()

int	GetUpdateNumberOfPieces (int port)

int	GetUpdateGhostLevel ()

int	GetUpdateGhostLevel (int port)

void	SetProgressObserver (vtkProgressObserver *)

virtual vtkProgressObserver *	GetProgressObserver ()

Public Member Functions inherited from vtkObject
vtkObject *	NewInstance () const

virtual void	DebugOn ()

virtual void	DebugOff ()

bool	GetDebug ()

void	SetDebug (bool debugFlag)

virtual void	Modified ()

virtual unsigned long	GetMTime ()

unsigned long	AddObserver (unsigned long event, vtkCommand *, float priority=0.0f)

unsigned long	AddObserver (const char event, vtkCommand , float priority=0.0f)

vtkCommand *	GetCommand (unsigned long tag)

void	RemoveObserver (vtkCommand *)

void	RemoveObservers (unsigned long event, vtkCommand *)

void	RemoveObservers (const char event, vtkCommand )

int	HasObserver (unsigned long event, vtkCommand *)

int	HasObserver (const char event, vtkCommand )

void	RemoveObserver (unsigned long tag)

void	RemoveObservers (unsigned long event)

void	RemoveObservers (const char *event)

void	RemoveAllObservers ()

int	HasObserver (unsigned long event)

int	HasObserver (const char *event)

template<class U , class T >
unsigned long	AddObserver (unsigned long event, U observer, void(T::*callback)(), float priority=0.0f)

template<class U , class T >
unsigned long	AddObserver (unsigned long event, U observer, void(T::callback)(vtkObject , unsigned long, void *), float priority=0.0f)

template<class U , class T >
unsigned long	AddObserver (unsigned long event, U observer, bool(T::callback)(vtkObject , unsigned long, void *), float priority=0.0f)

int	InvokeEvent (unsigned long event, void *callData)

int	InvokeEvent (const char event, void callData)

int	InvokeEvent (unsigned long event)

int	InvokeEvent (const char *event)

Public Member Functions inherited from vtkObjectBase
const char *	GetClassName () const

virtual void	Delete ()

virtual void	FastDelete ()

void	Print (ostream &os)

void	SetReferenceCount (int)

void	PrintRevisions (ostream &)

virtual void	PrintHeader (ostream &os, vtkIndent indent)

virtual void	PrintTrailer (ostream &os, vtkIndent indent)

int	GetReferenceCount ()

Static Public Member Functions
static int	IsTypeOf (const char *type)

static vtkPCAStatistics *	SafeDownCast (vtkObjectBase *o)

static vtkPCAStatistics *	New ()

Static Public Member Functions inherited from vtkMultiCorrelativeStatistics
static int	IsTypeOf (const char *type)

static vtkMultiCorrelativeStatistics *	SafeDownCast (vtkObjectBase *o)

static vtkMultiCorrelativeStatistics *	New ()

Static Public Member Functions inherited from vtkStatisticsAlgorithm
static int	IsTypeOf (const char *type)

static vtkStatisticsAlgorithm *	SafeDownCast (vtkObjectBase *o)

Static Public Member Functions inherited from vtkTableAlgorithm
static vtkTableAlgorithm *	New ()

static int	IsTypeOf (const char *type)

static vtkTableAlgorithm *	SafeDownCast (vtkObjectBase *o)

Static Public Member Functions inherited from vtkAlgorithm
static vtkAlgorithm *	New ()

static int	IsTypeOf (const char *type)

static vtkAlgorithm *	SafeDownCast (vtkObjectBase *o)

static vtkInformationIntegerKey *	INPUT_IS_OPTIONAL ()

static vtkInformationIntegerKey *	INPUT_IS_REPEATABLE ()

static vtkInformationInformationVectorKey *	INPUT_REQUIRED_FIELDS ()

static vtkInformationStringVectorKey *	INPUT_REQUIRED_DATA_TYPE ()

static vtkInformationInformationVectorKey *	INPUT_ARRAYS_TO_PROCESS ()

static vtkInformationIntegerKey *	INPUT_PORT ()

static vtkInformationIntegerKey *	INPUT_CONNECTION ()

static vtkInformationIntegerKey *	CAN_PRODUCE_SUB_EXTENT ()

static vtkInformationIntegerKey *	CAN_HANDLE_PIECE_REQUEST ()

static void	SetDefaultExecutivePrototype (vtkExecutive *proto)

Static Public Member Functions inherited from vtkObject
static int	IsTypeOf (const char *type)

static vtkObject *	SafeDownCast (vtkObjectBase *o)

static vtkObject *	New ()

static void	BreakOnError ()

static void	SetGlobalWarningDisplay (int val)

static void	GlobalWarningDisplayOn ()

static void	GlobalWarningDisplayOff ()

static int	GetGlobalWarningDisplay ()

Static Public Member Functions inherited from vtkObjectBase
static int	IsTypeOf (const char *name)

static vtkObjectBase *	New ()

Protected Member Functions
virtual vtkObjectBase *	NewInstanceInternal () const

	vtkPCAStatistics ()

	~vtkPCAStatistics ()

virtual int	FillInputPortInformation (int port, vtkInformation *info)

virtual void	Derive (vtkMultiBlockDataSet *)

virtual vtkDoubleArray *	CalculatePValues (vtkIdTypeArray , vtkDoubleArray )


virtual void	Test (vtkTable , vtkMultiBlockDataSet , vtkTable *)


virtual void	Assess (vtkTable , vtkMultiBlockDataSet , vtkTable *)


virtual void	SelectAssessFunctor (vtkTable inData, vtkDataObject inMeta, vtkStringArray rowNames, AssessFunctor &dfunc)

Protected Member Functions inherited from vtkMultiCorrelativeStatistics
	vtkMultiCorrelativeStatistics ()

	~vtkMultiCorrelativeStatistics ()

virtual void	ComputeMedian (vtkTable inData, vtkTable outData)

virtual vtkOrderStatistics *	CreateOrderStatisticsInstance ()

virtual void	Learn (vtkTable , vtkTable , vtkMultiBlockDataSet *)

Protected Member Functions inherited from vtkStatisticsAlgorithm
	vtkStatisticsAlgorithm ()

	~vtkStatisticsAlgorithm ()

virtual int	FillOutputPortInformation (int port, vtkInformation *info)

virtual int	RequestData (vtkInformation , vtkInformationVector , vtkInformationVector )

void	Assess (vtkTable , vtkMultiBlockDataSet , vtkTable *, int)

Protected Member Functions inherited from vtkTableAlgorithm
	vtkTableAlgorithm ()

	~vtkTableAlgorithm ()

virtual int	RequestInformation (vtkInformation request, vtkInformationVector inputVector, vtkInformationVector outputVector)

virtual int	RequestUpdateExtent (vtkInformation , vtkInformationVector , vtkInformationVector )

Protected Member Functions inherited from vtkAlgorithm
	vtkAlgorithm ()

	~vtkAlgorithm ()

virtual void	SetNumberOfInputPorts (int n)

virtual void	SetNumberOfOutputPorts (int n)

int	InputPortIndexInRange (int index, const char *action)

int	OutputPortIndexInRange (int index, const char *action)

int	GetInputArrayAssociation (int idx, vtkInformationVector **inputVector)

virtual vtkExecutive *	CreateDefaultExecutive ()

virtual void	ReportReferences (vtkGarbageCollector *)

virtual void	SetNumberOfInputConnections (int port, int n)

int	GetInputArrayAssociation (int idx, int connection, vtkInformationVector **inputVector)

int	GetInputArrayAssociation (int idx, vtkDataObject *input)

vtkDataArray *	GetInputArrayToProcess (int idx, vtkInformationVector **inputVector)

vtkDataArray *	GetInputArrayToProcess (int idx, vtkInformationVector **inputVector, int &association)

vtkDataArray *	GetInputArrayToProcess (int idx, int connection, vtkInformationVector **inputVector)

vtkDataArray *	GetInputArrayToProcess (int idx, int connection, vtkInformationVector **inputVector, int &association)

vtkDataArray *	GetInputArrayToProcess (int idx, vtkDataObject *input)

vtkDataArray *	GetInputArrayToProcess (int idx, vtkDataObject *input, int &association)

vtkAbstractArray *	GetInputAbstractArrayToProcess (int idx, vtkInformationVector **inputVector)

vtkAbstractArray *	GetInputAbstractArrayToProcess (int idx, vtkInformationVector **inputVector, int &association)

vtkAbstractArray *	GetInputAbstractArrayToProcess (int idx, int connection, vtkInformationVector **inputVector)

vtkAbstractArray *	GetInputAbstractArrayToProcess (int idx, int connection, vtkInformationVector **inputVector, int &association)

vtkAbstractArray *	GetInputAbstractArrayToProcess (int idx, vtkDataObject *input)

vtkAbstractArray *	GetInputAbstractArrayToProcess (int idx, vtkDataObject *input, int &association)

vtkInformation *	GetInputArrayFieldInformation (int idx, vtkInformationVector **inputVector)

virtual void	SetNthInputConnection (int port, int index, vtkAlgorithmOutput *input)

void	SetInputDataInternal (int port, vtkDataObject *input)

void	AddInputDataInternal (int port, vtkDataObject *input)

virtual void	SetErrorCode (unsigned long)

Protected Member Functions inherited from vtkObject
	vtkObject ()

virtual	~vtkObject ()

virtual void	RegisterInternal (vtkObjectBase *, int check)

virtual void	UnRegisterInternal (vtkObjectBase *, int check)

void	InternalGrabFocus (vtkCommand mouseEvents, vtkCommand keypressEvents=NULL)

void	InternalReleaseFocus ()

Protected Member Functions inherited from vtkObjectBase
	vtkObjectBase ()

virtual	~vtkObjectBase ()

virtual void	CollectRevisions (ostream &)

	vtkObjectBase (const vtkObjectBase &)

void	operator= (const vtkObjectBase &)

Protected Attributes
int	NormalizationScheme

int	BasisScheme

int	FixedBasisSize

double	FixedBasisEnergy

Protected Attributes inherited from vtkMultiCorrelativeStatistics
bool	MedianAbsoluteDeviation

Protected Attributes inherited from vtkStatisticsAlgorithm
vtkIdType	NumberOfPrimaryTables

bool	LearnOption

bool	DeriveOption

bool	AssessOption

bool	TestOption

vtkStringArray *	AssessNames

vtkStatisticsAlgorithmPrivate *	Internals

Protected Attributes inherited from vtkAlgorithm
vtkInformation *	Information

double	Progress

char *	ProgressText

vtkProgressObserver *	ProgressObserver

unsigned long	ErrorCode

Protected Attributes inherited from vtkObject
bool	Debug

vtkTimeStamp	MTime

vtkSubjectHelper *	SubjectHelper

Protected Attributes inherited from vtkObjectBase
vtkAtomicInt32	ReferenceCount

vtkWeakPointerBase **	WeakPointers

Static Protected Attributes
static const char *	BasisSchemeEnumNames [NUM_BASIS_SCHEMES+1]

static const char *	NormalizationSchemeEnumNames [NUM_NORMALIZATION_SCHEMES+1]

Static Protected Attributes inherited from vtkAlgorithm
static vtkExecutive *	DefaultExecutivePrototype

Additional Inherited Members
Public Attributes inherited from vtkAlgorithm
int	AbortExecute

Static Protected Member Functions inherited from vtkAlgorithm
static vtkInformationIntegerKey *	PORT_REQUIREMENTS_FILLED ()

Detailed Description

A class for multivariate principal component analysis.

This class derives from the multi-correlative statistics algorithm and uses the covariance matrix and Cholesky decomposition computed by it. However, when it finalizes the statistics in learn operation, the PCA class computes the SVD of the covariance matrix in order to obtain its eigenvectors.

In the assess operation, the input data are

projected into the basis defined by the eigenvectors,
the energy associated with each datum is computed,
or some combination thereof. Additionally, the user may specify some threshold energy or eigenvector entry below which the basis is truncated. This allows projection into a lower-dimensional state while minimizing (in a least squares sense) the projection error.

In the test operation, a Jarque-Bera-Srivastava test of n-d normality is performed.

The Robust PCA can be computed by using the median instead of the mean, and the MAD matrix (Median Absolute Deviation) instead of the covariance matrix. This can be done by activating the MedianAbsoluteDeviation boolean (declared in the superclass).

Thanks:: Thanks to David Thompson, Philippe Pebay and Jackson Mayo from Sandia National Laboratories for implementing this class. Updated by Philippe Pebay, Kitware SAS 2012 Updated by Tristan Coulange and Joachim Pouderoux, Kitware SAS 2013

Tests:: vtkPCAStatistics (Tests)

Definition at line 64 of file vtkPCAStatistics.h.

Member Typedef Documentation

typedef vtkMultiCorrelativeStatistics vtkPCAStatistics::Superclass

Definition at line 67 of file vtkPCAStatistics.h.

Member Enumeration Documentation

enum vtkPCAStatistics::NormalizationType

Methods by which the covariance matrix may be normalized.

Enumerator
NONE	The covariance matrix should be used as computed.
TRIANGLE_SPECIFIED	Normalize cov(i,j) by V(i,j) where V is supplied by the user.
DIAGONAL_SPECIFIED	Normalize cov(i,j) by sqrt(V(i)*V(j)) where V is supplied by the user.
DIAGONAL_VARIANCE	Normalize cov(i,j) by sqrt(cov(i,i)*cov(j,j)).
NUM_NORMALIZATION_SCHEMES	The number of normalization schemes.

Definition at line 74 of file vtkPCAStatistics.h.

enum vtkPCAStatistics::ProjectionType

These are the enumeration values that SetBasisScheme() accepts and GetBasisScheme returns.

Enumerator
FULL_BASIS	Use all entries in the basis matrix.
FIXED_BASIS_SIZE	Use the first N entries in the basis matrix.
FIXED_BASIS_ENERGY	Use consecutive basis matrix entries whose energies sum to at least T.
NUM_BASIS_SCHEMES	The number of schemes (not a valid scheme).

Definition at line 87 of file vtkPCAStatistics.h.

Constructor & Destructor Documentation

vtkPCAStatistics::vtkPCAStatistics ( )

protected

vtkPCAStatistics::~vtkPCAStatistics ( )

protected

Member Function Documentation

static int vtkPCAStatistics::IsTypeOf ( const char * type )

static

virtual int vtkPCAStatistics::IsA ( const char * name )

virtual

Return 1 if this class is the same type of (or a subclass of) the named class. Returns 0 otherwise. This method works in combination with vtkTypeMacro found in vtkSetGet.h.

Reimplemented from vtkMultiCorrelativeStatistics.

Reimplemented in vtkPCAStatisticsGnuR, and vtkPPCAStatistics.

static vtkPCAStatistics* vtkPCAStatistics::SafeDownCast ( vtkObjectBase * o )

static

virtual vtkObjectBase* vtkPCAStatistics::NewInstanceInternal ( ) const

protectedvirtual

Reimplemented from vtkMultiCorrelativeStatistics.

Reimplemented in vtkPCAStatisticsGnuR, and vtkPPCAStatistics.

vtkPCAStatistics* vtkPCAStatistics::NewInstance ( ) const

virtual void vtkPCAStatistics::PrintSelf	(	ostream &	os,
		vtkIndent	indent
	)

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 vtkMultiCorrelativeStatistics.

Reimplemented in vtkPCAStatisticsGnuR, and vtkPPCAStatistics.

static vtkPCAStatistics* vtkPCAStatistics::New ( )

static

virtual void vtkPCAStatistics::SetNormalizationScheme ( int )

virtual

This determines how (or if) the covariance matrix cov is normalized before PCA. When set to NONE, no normalization is performed. This is the default. When set to TRIANGLE_SPECIFIED, each entry cov(i,j) is divided by V(i,j). The list V of normalization factors must be set using the SetNormalization method before the filter is executed. When set to DIAGONAL_SPECIFIED, each entry cov(i,j) is divided by sqrt(V(i)*V(j)). The list V of normalization factors must be set using the SetNormalization method before the filter is executed. When set to DIAGONAL_VARIANCE, each entry cov(i,j) is divided by sqrt(cov(i,i)*cov(j,j)). Warning: Although this is accepted practice in some fields, some people think you should not turn this option on unless there is a good physically-based reason for doing so. Much better instead to determine how component magnitudes should be compared using physical reasoning and use DIAGONAL_SPECIFIED, TRIANGLE_SPECIFIED, or perform some pre-processing to shift and scale input data columns appropriately than to expect magical results from a shady normalization hack.

virtual int vtkPCAStatistics::GetNormalizationScheme ( )

virtual

This determines how (or if) the covariance matrix cov is normalized before PCA. When set to NONE, no normalization is performed. This is the default. When set to TRIANGLE_SPECIFIED, each entry cov(i,j) is divided by V(i,j). The list V of normalization factors must be set using the SetNormalization method before the filter is executed. When set to DIAGONAL_SPECIFIED, each entry cov(i,j) is divided by sqrt(V(i)*V(j)). The list V of normalization factors must be set using the SetNormalization method before the filter is executed. When set to DIAGONAL_VARIANCE, each entry cov(i,j) is divided by sqrt(cov(i,i)*cov(j,j)). Warning: Although this is accepted practice in some fields, some people think you should not turn this option on unless there is a good physically-based reason for doing so. Much better instead to determine how component magnitudes should be compared using physical reasoning and use DIAGONAL_SPECIFIED, TRIANGLE_SPECIFIED, or perform some pre-processing to shift and scale input data columns appropriately than to expect magical results from a shady normalization hack.

virtual void vtkPCAStatistics::SetNormalizationSchemeByName ( const char * sname )

virtual

This determines how (or if) the covariance matrix cov is normalized before PCA. When set to NONE, no normalization is performed. This is the default. When set to TRIANGLE_SPECIFIED, each entry cov(i,j) is divided by V(i,j). The list V of normalization factors must be set using the SetNormalization method before the filter is executed. When set to DIAGONAL_SPECIFIED, each entry cov(i,j) is divided by sqrt(V(i)*V(j)). The list V of normalization factors must be set using the SetNormalization method before the filter is executed. When set to DIAGONAL_VARIANCE, each entry cov(i,j) is divided by sqrt(cov(i,i)*cov(j,j)). Warning: Although this is accepted practice in some fields, some people think you should not turn this option on unless there is a good physically-based reason for doing so. Much better instead to determine how component magnitudes should be compared using physical reasoning and use DIAGONAL_SPECIFIED, TRIANGLE_SPECIFIED, or perform some pre-processing to shift and scale input data columns appropriately than to expect magical results from a shady normalization hack.

virtual const char* vtkPCAStatistics::GetNormalizationSchemeName ( int scheme )

virtual

This determines how (or if) the covariance matrix cov is normalized before PCA. When set to NONE, no normalization is performed. This is the default. When set to TRIANGLE_SPECIFIED, each entry cov(i,j) is divided by V(i,j). The list V of normalization factors must be set using the SetNormalization method before the filter is executed. When set to DIAGONAL_SPECIFIED, each entry cov(i,j) is divided by sqrt(V(i)*V(j)). The list V of normalization factors must be set using the SetNormalization method before the filter is executed. When set to DIAGONAL_VARIANCE, each entry cov(i,j) is divided by sqrt(cov(i,i)*cov(j,j)). Warning: Although this is accepted practice in some fields, some people think you should not turn this option on unless there is a good physically-based reason for doing so. Much better instead to determine how component magnitudes should be compared using physical reasoning and use DIAGONAL_SPECIFIED, TRIANGLE_SPECIFIED, or perform some pre-processing to shift and scale input data columns appropriately than to expect magical results from a shady normalization hack.

virtual vtkTable* vtkPCAStatistics::GetSpecifiedNormalization ( )

virtual

These methods allow you to set/get values used to normalize the covariance matrix before PCA. The normalization values apply to all requests, so you do not specify a single vector but a 3-column table. The first two columns contain the names of columns from input 0 and the third column contains the value to normalize the corresponding entry in the covariance matrix. The table must always have 3 columns even when the NormalizationScheme is DIAGONAL_SPECIFIED. When only diagonal entries are to be used, only table rows where the first two columns are identical to one another will be employed. If there are multiple rows specifying different values for the same pair of columns, the entry nearest the bottom of the table takes precedence. These functions are actually convenience methods that set/get the third input of the filter. Because the table is the third input, you may use other filters to produce a table of normalizations and have the pipeline take care of updates. Any missing entries will be set to 1.0 and a warning issued. An error will occur if the third input to the filter is not set and the NormalizationScheme is DIAGONAL_SPECIFIED or TRIANGLE_SPECIFIED. NOTE: SetSpecifiedNormalization( table ) is equivalent to SetInputData(3, table) and therefore does not make a pipeline connection.

virtual void vtkPCAStatistics::SetSpecifiedNormalization ( vtkTable * )

virtual

These methods allow you to set/get values used to normalize the covariance matrix before PCA. The normalization values apply to all requests, so you do not specify a single vector but a 3-column table. The first two columns contain the names of columns from input 0 and the third column contains the value to normalize the corresponding entry in the covariance matrix. The table must always have 3 columns even when the NormalizationScheme is DIAGONAL_SPECIFIED. When only diagonal entries are to be used, only table rows where the first two columns are identical to one another will be employed. If there are multiple rows specifying different values for the same pair of columns, the entry nearest the bottom of the table takes precedence. These functions are actually convenience methods that set/get the third input of the filter. Because the table is the third input, you may use other filters to produce a table of normalizations and have the pipeline take care of updates. Any missing entries will be set to 1.0 and a warning issued. An error will occur if the third input to the filter is not set and the NormalizationScheme is DIAGONAL_SPECIFIED or TRIANGLE_SPECIFIED. NOTE: SetSpecifiedNormalization( table ) is equivalent to SetInputData(3, table) and therefore does not make a pipeline connection.

void vtkPCAStatistics::GetEigenvalues	(	int	request,
		vtkDoubleArray *
	)

Get the eigenvalues. The eigenvalues are ordered according from largest to smallest. This function: void GetEigenvalues(int request, int i, vtkDoubleArray*); does all of the work. The other functions simply call this function with the appropriate parameters. These functions are not valid unless Update() has been called and the Derive option is turned on.

void vtkPCAStatistics::GetEigenvalues ( vtkDoubleArray * )

Get the eigenvalues. The eigenvalues are ordered according from largest to smallest. This function: void GetEigenvalues(int request, int i, vtkDoubleArray*); does all of the work. The other functions simply call this function with the appropriate parameters. These functions are not valid unless Update() has been called and the Derive option is turned on.

double vtkPCAStatistics::GetEigenvalue	(	int	request,
		int	i
	)

Get the eigenvalues. The eigenvalues are ordered according from largest to smallest. This function: void GetEigenvalues(int request, int i, vtkDoubleArray*); does all of the work. The other functions simply call this function with the appropriate parameters. These functions are not valid unless Update() has been called and the Derive option is turned on.

double vtkPCAStatistics::GetEigenvalue ( int i )

Get the eigenvalues. The eigenvalues are ordered according from largest to smallest. This function: void GetEigenvalues(int request, int i, vtkDoubleArray*); does all of the work. The other functions simply call this function with the appropriate parameters. These functions are not valid unless Update() has been called and the Derive option is turned on.

void vtkPCAStatistics::GetEigenvectors	(	int	request,
		vtkDoubleArray *	eigenvectors
	)

Get the eigenvectors. The eigenvectors are ordered according to the magnitude of their associated eigenvalues, sorted from largest to smallest. That is, eigenvector 0 corresponds to the largest eigenvalue. This function: void GetEigenvectors(int request, vtkDoubleArray* eigenvectors) does all of the work. The other functions are convenience functions that call this function with default arguments. These functions are not valid unless Update() has been called and the Derive option is turned on.

void vtkPCAStatistics::GetEigenvectors ( vtkDoubleArray * eigenvectors )

Get the eigenvectors. The eigenvectors are ordered according to the magnitude of their associated eigenvalues, sorted from largest to smallest. That is, eigenvector 0 corresponds to the largest eigenvalue. This function: void GetEigenvectors(int request, vtkDoubleArray* eigenvectors) does all of the work. The other functions are convenience functions that call this function with default arguments. These functions are not valid unless Update() has been called and the Derive option is turned on.

void vtkPCAStatistics::GetEigenvector	(	int	i,
		vtkDoubleArray *	eigenvector
	)

Get the eigenvectors. The eigenvectors are ordered according to the magnitude of their associated eigenvalues, sorted from largest to smallest. That is, eigenvector 0 corresponds to the largest eigenvalue. This function: void GetEigenvectors(int request, vtkDoubleArray* eigenvectors) does all of the work. The other functions are convenience functions that call this function with default arguments. These functions are not valid unless Update() has been called and the Derive option is turned on.

void vtkPCAStatistics::GetEigenvector	(	int	request,
		int	i,
		vtkDoubleArray *	eigenvector
	)

Get the eigenvectors. The eigenvectors are ordered according to the magnitude of their associated eigenvalues, sorted from largest to smallest. That is, eigenvector 0 corresponds to the largest eigenvalue. This function: void GetEigenvectors(int request, vtkDoubleArray* eigenvectors) does all of the work. The other functions are convenience functions that call this function with default arguments. These functions are not valid unless Update() has been called and the Derive option is turned on.

virtual void vtkPCAStatistics::SetBasisScheme ( int )

virtual

This variable controls the dimensionality of output tuples in Assess operation. Consider the case where you have requested a PCA on D columns. When set to vtkPCAStatistics::FULL_BASIS, the entire set of basis vectors is used to derive new coordinates for each tuple being assessed. In this mode, you are guaranteed to have output tuples of the same dimension as the input tuples. (That dimension is D, so there will be D additional columns added to the table for the request.) When set to vtkPCAStatistics::FIXED_BASIS_SIZE, only the first N basis vectors are used to derive new coordinates for each tuple being assessed. In this mode, you are guaranteed to have output tuples of dimension min(N,D). You must set N prior to assessing data using the SetFixedBasisSize() method. When N < D, this turns the PCA into a projection (instead of change of basis). When set to vtkPCAStatistics::FIXED_BASIS_ENERGY, the number of basis vectors used to derive new coordinates for each tuple will be the minimum number of columns N that satisfy

$\frac{\sum_{i=1}^{N} \lambda_i}{\sum_{i=1}^{D} \lambda_i} < T$

You must set T prior to assessing data using the SetFixedBasisEnergy() method. When T < 1, this turns the PCA into a projection (instead of change of basis). By default BasisScheme is set to vtkPCAStatistics::FULL_BASIS.

virtual int vtkPCAStatistics::GetBasisScheme ( )

virtual

This variable controls the dimensionality of output tuples in Assess operation. Consider the case where you have requested a PCA on D columns. When set to vtkPCAStatistics::FULL_BASIS, the entire set of basis vectors is used to derive new coordinates for each tuple being assessed. In this mode, you are guaranteed to have output tuples of the same dimension as the input tuples. (That dimension is D, so there will be D additional columns added to the table for the request.) When set to vtkPCAStatistics::FIXED_BASIS_SIZE, only the first N basis vectors are used to derive new coordinates for each tuple being assessed. In this mode, you are guaranteed to have output tuples of dimension min(N,D). You must set N prior to assessing data using the SetFixedBasisSize() method. When N < D, this turns the PCA into a projection (instead of change of basis). When set to vtkPCAStatistics::FIXED_BASIS_ENERGY, the number of basis vectors used to derive new coordinates for each tuple will be the minimum number of columns N that satisfy

$\frac{\sum_{i=1}^{N} \lambda_i}{\sum_{i=1}^{D} \lambda_i} < T$

You must set T prior to assessing data using the SetFixedBasisEnergy() method. When T < 1, this turns the PCA into a projection (instead of change of basis). By default BasisScheme is set to vtkPCAStatistics::FULL_BASIS.

virtual const char* vtkPCAStatistics::GetBasisSchemeName ( int schemeIndex )

virtual

This variable controls the dimensionality of output tuples in Assess operation. Consider the case where you have requested a PCA on D columns. When set to vtkPCAStatistics::FULL_BASIS, the entire set of basis vectors is used to derive new coordinates for each tuple being assessed. In this mode, you are guaranteed to have output tuples of the same dimension as the input tuples. (That dimension is D, so there will be D additional columns added to the table for the request.) When set to vtkPCAStatistics::FIXED_BASIS_SIZE, only the first N basis vectors are used to derive new coordinates for each tuple being assessed. In this mode, you are guaranteed to have output tuples of dimension min(N,D). You must set N prior to assessing data using the SetFixedBasisSize() method. When N < D, this turns the PCA into a projection (instead of change of basis). When set to vtkPCAStatistics::FIXED_BASIS_ENERGY, the number of basis vectors used to derive new coordinates for each tuple will be the minimum number of columns N that satisfy

$\frac{\sum_{i=1}^{N} \lambda_i}{\sum_{i=1}^{D} \lambda_i} < T$

You must set T prior to assessing data using the SetFixedBasisEnergy() method. When T < 1, this turns the PCA into a projection (instead of change of basis). By default BasisScheme is set to vtkPCAStatistics::FULL_BASIS.

virtual void vtkPCAStatistics::SetBasisSchemeByName ( const char * schemeName )

virtual

This variable controls the dimensionality of output tuples in Assess operation. Consider the case where you have requested a PCA on D columns. When set to vtkPCAStatistics::FULL_BASIS, the entire set of basis vectors is used to derive new coordinates for each tuple being assessed. In this mode, you are guaranteed to have output tuples of the same dimension as the input tuples. (That dimension is D, so there will be D additional columns added to the table for the request.) When set to vtkPCAStatistics::FIXED_BASIS_SIZE, only the first N basis vectors are used to derive new coordinates for each tuple being assessed. In this mode, you are guaranteed to have output tuples of dimension min(N,D). You must set N prior to assessing data using the SetFixedBasisSize() method. When N < D, this turns the PCA into a projection (instead of change of basis). When set to vtkPCAStatistics::FIXED_BASIS_ENERGY, the number of basis vectors used to derive new coordinates for each tuple will be the minimum number of columns N that satisfy

$\frac{\sum_{i=1}^{N} \lambda_i}{\sum_{i=1}^{D} \lambda_i} < T$

You must set T prior to assessing data using the SetFixedBasisEnergy() method. When T < 1, this turns the PCA into a projection (instead of change of basis). By default BasisScheme is set to vtkPCAStatistics::FULL_BASIS.

virtual void vtkPCAStatistics::SetFixedBasisSize ( int )

virtual

The number of basis vectors to use. See SetBasisScheme() for more information. When FixedBasisSize <= 0 (the default), the fixed basis size scheme is equivalent to the full basis scheme.

virtual int vtkPCAStatistics::GetFixedBasisSize ( )

virtual

The number of basis vectors to use. See SetBasisScheme() for more information. When FixedBasisSize <= 0 (the default), the fixed basis size scheme is equivalent to the full basis scheme.

virtual void vtkPCAStatistics::SetFixedBasisEnergy ( double )

virtual

The minimum energy the new basis should use, as a fraction. See SetBasisScheme() for more information. When FixedBasisEnergy >= 1 (the default), the fixed basis energy scheme is equivalent to the full basis scheme.

virtual double vtkPCAStatistics::GetFixedBasisEnergy ( )

virtual

The minimum energy the new basis should use, as a fraction. See SetBasisScheme() for more information. When FixedBasisEnergy >= 1 (the default), the fixed basis energy scheme is equivalent to the full basis scheme.

virtual bool vtkPCAStatistics::SetParameter	(	const char *	parameter,
		int	index,
		vtkVariant	value
	)

virtual

A convenience method (in particular for access from other applications) to set parameter values. Return true if setting of requested parameter name was excuted, false otherwise.

Reimplemented from vtkStatisticsAlgorithm.

virtual int vtkPCAStatistics::FillInputPortInformation	(	int	port,
		vtkInformation *	info
	)

protectedvirtual

This algorithm accepts a vtkTable containing normalization values for its fourth input (port 3). We override FillInputPortInformation to indicate this.

Reimplemented from vtkStatisticsAlgorithm.

virtual void vtkPCAStatistics::Derive ( vtkMultiBlockDataSet * )

protectedvirtual

Execute the calculations required by the Derive option.

Reimplemented from vtkMultiCorrelativeStatistics.

virtual void vtkPCAStatistics::Test	(	vtkTable *	,
		vtkMultiBlockDataSet *	,
		vtkTable *
	)

protectedvirtual

Execute the calculations required by the Test option.

Reimplemented from vtkMultiCorrelativeStatistics.

Reimplemented in vtkPPCAStatistics.

virtual void vtkPCAStatistics::Assess	(	vtkTable *	,
		vtkMultiBlockDataSet *	,
		vtkTable *
	)

protectedvirtual

Execute the calculations required by the Assess option.

Reimplemented from vtkMultiCorrelativeStatistics.

virtual vtkDoubleArray* vtkPCAStatistics::CalculatePValues	(	vtkIdTypeArray *	,
		vtkDoubleArray *
	)

protectedvirtual

Calculate p-value. This will be overridden using the object factory with an R implementation if R is present.

Reimplemented in vtkPCAStatisticsGnuR.

virtual void vtkPCAStatistics::SelectAssessFunctor	(	vtkTable *	inData,
		vtkDataObject *	inMeta,
		vtkStringArray *	rowNames,
		AssessFunctor *&	dfunc
	)

protectedvirtual

Provide the appropriate assessment functor.

Reimplemented from vtkMultiCorrelativeStatistics.

Member Data Documentation

int vtkPCAStatistics::NormalizationScheme

protected

Definition at line 268 of file vtkPCAStatistics.h.

int vtkPCAStatistics::BasisScheme

protected

Definition at line 269 of file vtkPCAStatistics.h.

int vtkPCAStatistics::FixedBasisSize

protected

Definition at line 270 of file vtkPCAStatistics.h.

double vtkPCAStatistics::FixedBasisEnergy

protected

Definition at line 271 of file vtkPCAStatistics.h.

const char* vtkPCAStatistics::BasisSchemeEnumNames[NUM_BASIS_SCHEMES+1]

staticprotected

Definition at line 274 of file vtkPCAStatistics.h.

const char* vtkPCAStatistics::NormalizationSchemeEnumNames[NUM_NORMALIZATION_SCHEMES+1]

staticprotected

Definition at line 275 of file vtkPCAStatistics.h.

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

/home/boeckb/code/depot/group-kitware/vtk/build-release/Utilities/Doxygen/dox/Filters/Statistics/vtkPCAStatistics.h

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