Abstract base class for computing statistics with vtkStatistics. More...

#include <vtkSciVizStatistics.h>

Inheritance diagram for vtkSciVizStatistics:

Collaboration diagram for vtkSciVizStatistics:

Public Types
enum	Tasks { MODEL_INPUT, CREATE_MODEL, ASSESS_INPUT, MODEL_AND_ASSESS }
	Possible tasks the filter can perform. More...
Public Member Functions
virtual const char *	GetClassName ()
virtual int	IsA (const char *type)
virtual void	PrintSelf (ostream &os, vtkIndent indent)
int	GetNumberOfAttributeArrays ()
const char *	GetAttributeArrayName (int n)
int	GetAttributeArrayStatus (const char *arrName)
vtkInformationIntegerKey *	MULTIPLE_MODELS ()

virtual int	GetAttributeMode ()
virtual void	SetAttributeMode (int)

void	EnableAttributeArray (const char *arrName)
void	ClearAttributeArrays ()

virtual void	SetTrainingFraction (double)
virtual double	GetTrainingFraction ()

virtual void	SetTask (int)
virtual int	GetTask ()
Static Public Member Functions
static int	IsTypeOf (const char *type)
static vtkSciVizStatistics *	SafeDownCast (vtkObject *o)
Protected Member Functions
	vtkSciVizStatistics ()
virtual	~vtkSciVizStatistics ()
virtual int	FillInputPortInformation (int port, vtkInformation *info)
virtual int	FillOutputPortInformation (int port, vtkInformation *info)
virtual int	ProcessRequest (vtkInformation request, vtkInformationVector input, vtkInformationVector output)
virtual int	RequestDataObject (vtkInformation request, vtkInformationVector input, vtkInformationVector output)
virtual int	RequestData (vtkInformation request, vtkInformationVector input, vtkInformationVector output)
virtual int	RequestData (vtkCompositeDataSet compDataOu, vtkCompositeDataSet compModelOu, vtkCompositeDataSet compDataIn, vtkCompositeDataSet compModelIn, vtkDataObject *singleModel)
virtual int	RequestData (vtkDataObject observationsOut, vtkDataObject modelOut, vtkDataObject observationsIn, vtkDataObject modelIn)
virtual int	PrepareFullDataTable (vtkTable table, vtkFieldData dataAttrIn)
virtual int	PrepareTrainingTable (vtkTable trainingTable, vtkTable fullDataTable, vtkIdType numObservations)
virtual int	LearnAndDerive (vtkMultiBlockDataSet model, vtkTable inData)=0
virtual int	AssessData (vtkTable observations, vtkDataObject dataset, vtkMultiBlockDataSet *model)=0
virtual vtkIdType	GetNumberOfObservationsForTraining (vtkTable *observations)
Protected Attributes
int	AttributeMode
int	Task
double	TrainingFraction
vtkSciVizStatisticsP *	P

Detailed Description

Abstract base class for computing statistics with vtkStatistics.

This filter either computes a statistical model of a dataset or takes such a model as its second input. Then, the model (however it is obtained) may optionally be used to assess the input dataset.

This class serves as a base class that handles table conversion, interfacing with the array selection in the ParaView user interface, and provides a simplified interface to vtkStatisticsAlgorithm.

Thanks:: Thanks to David Thompson and Philippe Pebay from Sandia National Laboratories for implementing this class. Updated by Philippe Pebay, Kitware SAS 2012

Definition at line 49 of file vtkSciVizStatistics.h.

Member Enumeration Documentation

enum vtkSciVizStatistics::Tasks

Possible tasks the filter can perform.

The MODEL_AND_ASSESS task is not recommended; you should never evaluate data with a model if that data was used to create the model. Doing so can result in a too-liberal estimate of model error, especially if overfitting occurs. Because we expect that MODEL_AND_ASSESS, despite being ill-advised, will be frequently used the TrainingFraction parameter has been created.

Enumerator:

MODEL_INPUT	Execute Learn and Derive operations of a statistical engine on the input dataset.
CREATE_MODEL	Create a statistical model from a random subset the input dataset.
ASSESS_INPUT	Assess the input dataset using a statistical model from input port 1.
MODEL_AND_ASSESS	Create a statistical model of the input dataset and use it to assess the dataset. This is a bad idea.

Definition at line 104 of file vtkSciVizStatistics.h.

Constructor & Destructor Documentation

vtkSciVizStatistics::vtkSciVizStatistics ( ) [protected]

virtual vtkSciVizStatistics::~vtkSciVizStatistics ( ) [protected, virtual]

Member Function Documentation

virtual const char* vtkSciVizStatistics::GetClassName ( ) [virtual]

Reimplemented from vtkTableAlgorithm.

Reimplemented in vtkPSciVizMultiCorrelativeStats, vtkPSciVizPCAStats, vtkPSciVizContingencyStats, vtkPSciVizKMeans, and vtkPSciVizDescriptiveStats.

static int vtkSciVizStatistics::IsTypeOf ( const char * type ) [static]

Reimplemented from vtkTableAlgorithm.

Reimplemented in vtkPSciVizMultiCorrelativeStats, vtkPSciVizPCAStats, vtkPSciVizContingencyStats, vtkPSciVizKMeans, and vtkPSciVizDescriptiveStats.

virtual int vtkSciVizStatistics::IsA ( const char * type ) [virtual]

Reimplemented from vtkTableAlgorithm.

Reimplemented in vtkPSciVizMultiCorrelativeStats, vtkPSciVizPCAStats, vtkPSciVizContingencyStats, vtkPSciVizKMeans, and vtkPSciVizDescriptiveStats.

static vtkSciVizStatistics* vtkSciVizStatistics::SafeDownCast ( vtkObject * o ) [static]

Reimplemented from vtkTableAlgorithm.

Reimplemented in vtkPSciVizMultiCorrelativeStats, vtkPSciVizPCAStats, vtkPSciVizContingencyStats, vtkPSciVizKMeans, and vtkPSciVizDescriptiveStats.

virtual void vtkSciVizStatistics::PrintSelf	(	ostream &	os,
		vtkIndent	indent
	)		`[virtual]`

Reimplemented from vtkTableAlgorithm.

Reimplemented in vtkPSciVizMultiCorrelativeStats, vtkPSciVizPCAStats, vtkPSciVizContingencyStats, vtkPSciVizKMeans, and vtkPSciVizDescriptiveStats.

virtual int vtkSciVizStatistics::GetAttributeMode ( ) [virtual]

Set/get the type of field attribute (cell, point, field)

virtual void vtkSciVizStatistics::SetAttributeMode ( int ) [virtual]

Set/get the type of field attribute (cell, point, field)

int vtkSciVizStatistics::GetNumberOfAttributeArrays ( )

Return the number of columns available for the current value of AttributeMode.

const char* vtkSciVizStatistics::GetAttributeArrayName ( int n )

Get the name of the n-th array ffor the current value of AttributeMode.

int vtkSciVizStatistics::GetAttributeArrayStatus ( const char * arrName )

Get the status of the specified array (i.e., whether or not it is a column of interest).

void vtkSciVizStatistics::EnableAttributeArray ( const char * arrName )

An alternate interface for preparing a selection of arrays in ParaView.

void vtkSciVizStatistics::ClearAttributeArrays ( )

An alternate interface for preparing a selection of arrays in ParaView.

virtual void vtkSciVizStatistics::SetTrainingFraction ( double ) [virtual]

Set/get the amount of data to be used for training. When 0.0 < TrainingFraction < 1.0, a randomly-sampled subset of the data is used for training. When an assessment is requested, all data (including the training data) is assessed, regardless of the value of TrainingFraction. The default value is 0.1. The random sample of the original dataset (say, of size N) is obtained by choosing N random numbers in [0,1). Any sample where the random number is less than TrainingFraction is included in the training data. Samples are then randomly added or removed from the training data until it is the desired size.

virtual double vtkSciVizStatistics::GetTrainingFraction ( ) [virtual]

Set/get the amount of data to be used for training. When 0.0 < TrainingFraction < 1.0, a randomly-sampled subset of the data is used for training. When an assessment is requested, all data (including the training data) is assessed, regardless of the value of TrainingFraction. The default value is 0.1. The random sample of the original dataset (say, of size N) is obtained by choosing N random numbers in [0,1). Any sample where the random number is less than TrainingFraction is included in the training data. Samples are then randomly added or removed from the training data until it is the desired size.

virtual void vtkSciVizStatistics::SetTask ( int ) [virtual]

Set/get whether this filter should create a model of the input or assess the input or both. This should take on a value from the Tasks enum. The default is MODEL_AND_ASSESS.

virtual int vtkSciVizStatistics::GetTask ( ) [virtual]

Set/get whether this filter should create a model of the input or assess the input or both. This should take on a value from the Tasks enum. The default is MODEL_AND_ASSESS.

vtkInformationIntegerKey* vtkSciVizStatistics::MULTIPLE_MODELS ( )

A key used to mark the output model data object (output port 0) when it is a multiblock of models (any of which may be multiblock dataset themselves) as opposed to a multiblock dataset containing a single model.

virtual int vtkSciVizStatistics::FillInputPortInformation	(	int	port,
		vtkInformation *	info
	)		`[protected, virtual]`

Reimplemented from vtkTableAlgorithm.

virtual int vtkSciVizStatistics::FillOutputPortInformation	(	int	port,
		vtkInformation *	info
	)		`[protected, virtual]`

Reimplemented from vtkTableAlgorithm.

virtual int vtkSciVizStatistics::ProcessRequest	(	vtkInformation *	request,
		vtkInformationVector **	input,
		vtkInformationVector *	output
	)		`[protected, virtual]`

Reimplemented from vtkTableAlgorithm.

virtual int vtkSciVizStatistics::RequestDataObject	(	vtkInformation *	request,
		vtkInformationVector **	input,
		vtkInformationVector *	output
	)		`[protected, virtual]`

virtual int vtkSciVizStatistics::RequestData	(	vtkInformation *	request,
		vtkInformationVector **	input,
		vtkInformationVector *	output
	)		`[protected, virtual]`

Reimplemented from vtkTableAlgorithm.

virtual int vtkSciVizStatistics::RequestData	(	vtkCompositeDataSet *	compDataOu,
		vtkCompositeDataSet *	compModelOu,
		vtkCompositeDataSet *	compDataIn,
		vtkCompositeDataSet *	compModelIn,
		vtkDataObject *	singleModel
	)		`[protected, virtual]`

virtual int vtkSciVizStatistics::RequestData	(	vtkDataObject *	observationsOut,
		vtkDataObject *	modelOut,
		vtkDataObject *	observationsIn,
		vtkDataObject *	modelIn
	)		`[protected, virtual]`

virtual int vtkSciVizStatistics::PrepareFullDataTable	(	vtkTable *	table,
		vtkFieldData *	dataAttrIn
	)		`[protected, virtual]`

virtual int vtkSciVizStatistics::PrepareTrainingTable	(	vtkTable *	trainingTable,
		vtkTable *	fullDataTable,
		vtkIdType	numObservations
	)		`[protected, virtual]`

virtual int vtkSciVizStatistics::LearnAndDerive	(	vtkMultiBlockDataSet *	model,
		vtkTable *	inData
	)		`[protected, pure virtual]`

Method subclasses must override to calculate a full model from the given input data. The model should be placed on the first output port of the passed vtkInformationVector as well as returned in the model parameter.

Implemented in vtkPSciVizMultiCorrelativeStats, vtkPSciVizPCAStats, vtkPSciVizKMeans, vtkPSciVizContingencyStats, and vtkPSciVizDescriptiveStats.

virtual int vtkSciVizStatistics::AssessData	(	vtkTable *	observations,
		vtkDataObject *	dataset,
		vtkMultiBlockDataSet *	model
	)		`[protected, pure virtual]`

Method subclasses must override to assess an input table given a model of the proper type. The dataset parameter contains a shallow copy of input port 0 and should be modified to include the assessment. Adding new arrays to point/cell/vertex/edge data should not pose a problem, but any alterations to the dataset itself will probably require that you create a deep copy before modification.

Parameters:

observations	- a table containing the field data of the dataset converted to a table
dataset	- a shallow copy of the input dataset that should be altered to include an assessment of the output.
model	- the statistical model with which to assess the observations.

Implemented in vtkPSciVizMultiCorrelativeStats, vtkPSciVizPCAStats, vtkPSciVizKMeans, vtkPSciVizContingencyStats, and vtkPSciVizDescriptiveStats.

virtual vtkIdType vtkSciVizStatistics::GetNumberOfObservationsForTraining ( vtkTable * observations ) [protected, virtual]

Subclasses may (but need not) override this function to guarantee that some minimum number of observations are included in the training data. By default, it returns the maximum of: observations->GetNumberOfRows() * this->TrainingFraction and min( observations->GetNumberOfRows(), 100 ). Thus, it will require the entire set of observations unless there are more than 100. [in] observations - a table containing the full number of available observations (in this process).