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vtkPSciVizKMeans Class Reference

Find k cluster centers and/or assess the closest center and distance to it for each datum. More...

#include <vtkPSciVizKMeans.h>

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Public Types

typedef vtkSciVizStatistics Superclass
 
- Public Types inherited from vtkSciVizStatistics
enum  Tasks { MODEL_INPUT, CREATE_MODEL, ASSESS_INPUT, MODEL_AND_ASSESS }
 Possible tasks the filter can perform. More...
 
typedef vtkTableAlgorithm Superclass
 

Public Member Functions

virtual const char * GetClassName ()
 
virtual int IsA (const char *type)
 
virtual void PrintSelf (ostream &os, vtkIndent indent)
 
virtual void SetK (int)
 The number of cluster centers. More...
 
virtual int GetK ()
 The number of cluster centers. More...
 
virtual void SetMaxNumIterations (int)
 The maximum number of iterations to perform when converging on cluster centers. More...
 
virtual int GetMaxNumIterations ()
 The maximum number of iterations to perform when converging on cluster centers. More...
 
virtual void SetTolerance (double)
 The relative tolerance on cluster centers that will cause early termination of the algorithm. More...
 
virtual double GetTolerance ()
 The relative tolerance on cluster centers that will cause early termination of the algorithm. More...
 
- Public Member Functions inherited from vtkSciVizStatistics
int GetNumberOfAttributeArrays ()
 Return the number of columns available for the current value of AttributeMode. More...
 
const char * GetAttributeArrayName (int n)
 Get the name of the n-th array ffor the current value of AttributeMode. More...
 
int GetAttributeArrayStatus (const char *arrName)
 Get the status of the specified array (i.e., whether or not it is a column of interest). More...
 
vtkInformationIntegerKey * 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. More...
 
virtual int GetAttributeMode ()
 Set/get the type of field attribute (cell, point, field) More...
 
virtual void SetAttributeMode (int)
 Set/get the type of field attribute (cell, point, field) More...
 
void EnableAttributeArray (const char *arrName)
 An alternate interface for preparing a selection of arrays in ParaView. More...
 
void ClearAttributeArrays ()
 An alternate interface for preparing a selection of arrays in ParaView. More...
 
virtual void SetTrainingFraction (double)
 Set/get the amount of data to be used for training. More...
 
virtual double GetTrainingFraction ()
 Set/get the amount of data to be used for training. More...
 
virtual void SetTask (int)
 Set/get whether this filter should create a model of the input or assess the input or both. More...
 
virtual int GetTask ()
 Set/get whether this filter should create a model of the input or assess the input or both. More...
 

Static Public Member Functions

static vtkPSciVizKMeansNew ()
 
static int IsTypeOf (const char *type)
 
static vtkPSciVizKMeansSafeDownCast (vtkObject *o)
 
- Static Public Member Functions inherited from vtkSciVizStatistics
static int IsTypeOf (const char *type)
 
static vtkSciVizStatisticsSafeDownCast (vtkObject *o)
 

Protected Member Functions

 vtkPSciVizKMeans ()
 
virtual ~vtkPSciVizKMeans ()
 
virtual int LearnAndDerive (vtkMultiBlockDataSet *model, vtkTable *inData)
 Method subclasses must override to calculate a full model from the given input data. More...
 
virtual int AssessData (vtkTable *observations, vtkDataObject *dataset, vtkMultiBlockDataSet *model)
 Method subclasses must override to assess an input table given a model of the proper type. More...
 
- Protected Member Functions inherited from vtkSciVizStatistics
 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 vtkIdType GetNumberOfObservationsForTraining (vtkTable *observations)
 Subclasses may (but need not) override this function to guarantee that some minimum number of observations are included in the training data. More...
 

Protected Attributes

int K
 
int MaxNumIterations
 
double Tolerance
 
- Protected Attributes inherited from vtkSciVizStatistics
int AttributeMode
 
int Task
 
double TrainingFraction
 
vtkSciVizStatisticsPP
 

Detailed Description

Find k cluster centers and/or assess the closest center and distance to it for each datum.

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 filter iteratively computes the center of k clusters in a space whose coordinates are specified by the arrays you select. The clusters are chosen as local minima of the sum of square Euclidean distances from each point to its nearest cluster center. The model is then a set of cluster centers. Data is assessed by assigning a cluster center and distance to the cluster to each point in the input data set.

Definition at line 40 of file vtkPSciVizKMeans.h.

Member Typedef Documentation

◆ Superclass

Definition at line 44 of file vtkPSciVizKMeans.h.

Constructor & Destructor Documentation

◆ vtkPSciVizKMeans()

vtkPSciVizKMeans::vtkPSciVizKMeans ( )
protected

◆ ~vtkPSciVizKMeans()

virtual vtkPSciVizKMeans::~vtkPSciVizKMeans ( )
protectedvirtual

Member Function Documentation

◆ New()

static vtkPSciVizKMeans* vtkPSciVizKMeans::New ( )
static

◆ GetClassName()

virtual const char* vtkPSciVizKMeans::GetClassName ( )
virtual

Reimplemented from vtkSciVizStatistics.

◆ IsTypeOf()

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

◆ IsA()

virtual int vtkPSciVizKMeans::IsA ( const char *  type)
virtual

Reimplemented from vtkSciVizStatistics.

◆ SafeDownCast()

static vtkPSciVizKMeans* vtkPSciVizKMeans::SafeDownCast ( vtkObject *  o)
static

◆ PrintSelf()

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

Reimplemented from vtkSciVizStatistics.

◆ SetK()

virtual void vtkPSciVizKMeans::SetK ( int  )
virtual

The number of cluster centers.

The initial centers will be chosen randomly. In the future the filter will accept an input table of initial cluster positions. The default value of K is 5.

◆ GetK()

virtual int vtkPSciVizKMeans::GetK ( )
virtual

The number of cluster centers.

The initial centers will be chosen randomly. In the future the filter will accept an input table of initial cluster positions. The default value of K is 5.

◆ SetMaxNumIterations()

virtual void vtkPSciVizKMeans::SetMaxNumIterations ( int  )
virtual

The maximum number of iterations to perform when converging on cluster centers.

The default value is 50 iterations.

◆ GetMaxNumIterations()

virtual int vtkPSciVizKMeans::GetMaxNumIterations ( )
virtual

The maximum number of iterations to perform when converging on cluster centers.

The default value is 50 iterations.

◆ SetTolerance()

virtual void vtkPSciVizKMeans::SetTolerance ( double  )
virtual

The relative tolerance on cluster centers that will cause early termination of the algorithm.

The default value is 0.01: a 1 percent change in cluster coordinates.

◆ GetTolerance()

virtual double vtkPSciVizKMeans::GetTolerance ( )
virtual

The relative tolerance on cluster centers that will cause early termination of the algorithm.

The default value is 0.01: a 1 percent change in cluster coordinates.

◆ LearnAndDerive()

virtual int vtkPSciVizKMeans::LearnAndDerive ( vtkMultiBlockDataSet *  model,
vtkTable *  inData 
)
protectedvirtual

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.

Implements vtkSciVizStatistics.

◆ AssessData()

virtual int vtkPSciVizKMeans::AssessData ( vtkTable *  observations,
vtkDataObject *  dataset,
vtkMultiBlockDataSet *  model 
)
protectedvirtual

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.

Implements vtkSciVizStatistics.

Member Data Documentation

◆ K

int vtkPSciVizKMeans::K
protected

Definition at line 84 of file vtkPSciVizKMeans.h.

◆ MaxNumIterations

int vtkPSciVizKMeans::MaxNumIterations
protected

Definition at line 85 of file vtkPSciVizKMeans.h.

◆ Tolerance

double vtkPSciVizKMeans::Tolerance
protected

Definition at line 86 of file vtkPSciVizKMeans.h.


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