vtkStatisticsAlgorithm Class Reference

#include <vtkStatisticsAlgorithm.h>

Inheritance diagram for vtkStatisticsAlgorithm:

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Collaboration diagram for vtkStatisticsAlgorithm:

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List of all members.


Detailed Description

Base class for statistics algorithms.

All statistics algorithms can conceptually be operated with several options: Learn: given an input data set, calculate a minimal statistical model (e.g., sums, raw moments, joint probabilities). Derive: given an input minimal statistical model, derive the full model (e.g., descriptive statistics, quantiles, correlations, conditional probabilities). Assess: given an input data set, input statistics, and some form of threshold, assess a subset of the data set. Therefore, a vtkStatisticsAlgorithm has the following vtkTable ports 2 input ports: Data (mandatory) Input model (optional) 3 output port (called Output): Data (annotated with assessments when the Assess option is ON). Output model (identical to the the input model when Learn option is OFF). Meta information about the model and/or the overall fit of the data to the model; is filled only when the Assess option is ON.

Thanks:
Thanks to Philippe Pebay and David Thompson from Sandia National Laboratories for implementing this class.

Definition at line 57 of file vtkStatisticsAlgorithm.h.


Public Types

typedef vtkTableAlgorithm Superclass

Public Member Functions

virtual const char * GetClassName ()
virtual int IsA (const char *type)
void PrintSelf (ostream &os, vtkIndent indent)
virtual void SetInputStatisticsConnection (vtkAlgorithmOutput *)
virtual int IsFullModelDerived ()
void SetAssessParameter (vtkIdType id, vtkStdString name)
vtkStdString GetAssessParameter (vtkIdType id)
virtual void SetColumnStatus (const char *namCol, int status)
virtual void ResetAllColumnStates ()
virtual int RequestSelectedColumns ()
virtual void ResetRequests ()
virtual void SetNumberOfVariables (vtkIdType)
virtual vtkIdType GetNumberOfVariables ()
virtual void SetSampleSize (vtkIdType)
virtual vtkIdType GetSampleSize ()
virtual void SetLearn (bool)
virtual bool GetLearn ()
virtual void SetDerive (bool)
virtual bool GetDerive ()
virtual void SetAssess (bool)
virtual bool GetAssess ()
virtual void SelectAssessFunctor (vtkTable *outData, vtkDataObject *inMeta, vtkStringArray *rowNames, AssessFunctor *&dfunc)=0

Static Public Member Functions

static int IsTypeOf (const char *type)
static vtkStatisticsAlgorithmSafeDownCast (vtkObject *o)

Protected Member Functions

 vtkStatisticsAlgorithm ()
 ~vtkStatisticsAlgorithm ()
virtual int FillInputPortInformation (int port, vtkInformation *info)
virtual int FillOutputPortInformation (int port, vtkInformation *info)
virtual int RequestData (vtkInformation *, vtkInformationVector **, vtkInformationVector *)
virtual void ExecuteLearn (vtkTable *, vtkDataObject *)=0
virtual void ExecuteDerive (vtkDataObject *)=0
virtual void ExecuteAssess (vtkTable *, vtkDataObject *, vtkTable *, vtkDataObject *)=0

Protected Attributes

vtkIdType NumberOfVariables
vtkIdType SampleSize
bool Learn
bool Derive
bool Assess
bool FullWasDerived
vtkStringArrayAssessParameters
vtkStringArrayAssessNames
vtkStatisticsAlgorithmPrivateInternals

Classes

class  AssessFunctor

Member Typedef Documentation


Constructor & Destructor Documentation

vtkStatisticsAlgorithm::vtkStatisticsAlgorithm (  )  [protected]

vtkStatisticsAlgorithm::~vtkStatisticsAlgorithm (  )  [protected]


Member Function Documentation

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

static int vtkStatisticsAlgorithm::IsTypeOf ( const char *  name  )  [static]

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

Reimplemented from vtkTableAlgorithm.

Reimplemented in vtkBivariateStatisticsAlgorithm, vtkContingencyStatistics, vtkCorrelativeStatistics, vtkDescriptiveStatistics, vtkMultiCorrelativeStatistics, vtkOrderStatistics, vtkPCAStatistics, vtkPCorrelativeStatistics, vtkPDescriptiveStatistics, vtkPMultiCorrelativeStatistics, vtkPPCAStatistics, and vtkUnivariateStatisticsAlgorithm.

virtual int vtkStatisticsAlgorithm::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 vtkTypeRevisionMacro found in vtkSetGet.h.

Reimplemented from vtkTableAlgorithm.

Reimplemented in vtkBivariateStatisticsAlgorithm, vtkContingencyStatistics, vtkCorrelativeStatistics, vtkDescriptiveStatistics, vtkMultiCorrelativeStatistics, vtkOrderStatistics, vtkPCAStatistics, vtkPCorrelativeStatistics, vtkPDescriptiveStatistics, vtkPMultiCorrelativeStatistics, vtkPPCAStatistics, and vtkUnivariateStatisticsAlgorithm.

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

void vtkStatisticsAlgorithm::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 vtkTableAlgorithm.

Reimplemented in vtkBivariateStatisticsAlgorithm, vtkContingencyStatistics, vtkCorrelativeStatistics, vtkDescriptiveStatistics, vtkMultiCorrelativeStatistics, vtkOrderStatistics, vtkPCAStatistics, vtkPCorrelativeStatistics, vtkPDescriptiveStatistics, vtkPMultiCorrelativeStatistics, vtkPPCAStatistics, and vtkUnivariateStatisticsAlgorithm.

virtual void vtkStatisticsAlgorithm::SetInputStatisticsConnection ( vtkAlgorithmOutput  )  [virtual]

A convenience method for setting the statistics table input. NB: This is mainly for the benefit of the VTK client/server layer, vanilla VTKcode should use, e.g: stats_algo2->SetInputConnection( 1, stats_algo1->output() );

virtual void vtkStatisticsAlgorithm::SetNumberOfVariables ( vtkIdType   )  [virtual]

Set the number of variables.

virtual vtkIdType vtkStatisticsAlgorithm::GetNumberOfVariables (  )  [virtual]

Get the number of variables.

virtual void vtkStatisticsAlgorithm::SetSampleSize ( vtkIdType   )  [virtual]

Set the sample size.

virtual vtkIdType vtkStatisticsAlgorithm::GetSampleSize (  )  [virtual]

Get the sample size.

virtual void vtkStatisticsAlgorithm::SetLearn ( bool   )  [virtual]

Set the Learn option.

virtual bool vtkStatisticsAlgorithm::GetLearn (  )  [virtual]

Get the Learn option.

virtual void vtkStatisticsAlgorithm::SetDerive ( bool   )  [virtual]

Set the Derive option.

virtual bool vtkStatisticsAlgorithm::GetDerive (  )  [virtual]

Get the Derive option.

virtual void vtkStatisticsAlgorithm::SetAssess ( bool   )  [virtual]

Set the Assess option.

virtual bool vtkStatisticsAlgorithm::GetAssess (  )  [virtual]

Get the Assess option.

virtual int vtkStatisticsAlgorithm::IsFullModelDerived (  )  [inline, virtual]

Let the user know whether the full statistical model (when available) was indeed derived from the underlying minimal model. NB: It may be, or not be, a problem that a full model was not derived. For instance, when doing parallel calculations, one only wants to derive the full model after all partial calculations have completed. On the other hand, one can also directly provide a full model, that was previously calculated or guessed, and not derive a new one; in this case, IsFullModelDerived() will always return false, but this does not mean that the full model is invalid (nor does it mean that it is valid).

Definition at line 128 of file vtkStatisticsAlgorithm.h.

void vtkStatisticsAlgorithm::SetAssessParameter ( vtkIdType  id,
vtkStdString  name 
)

Set the name of a parameter of the Assess option

vtkStdString vtkStatisticsAlgorithm::GetAssessParameter ( vtkIdType  id  ) 

Get the name of a parameter of the Assess option

virtual void vtkStatisticsAlgorithm::SelectAssessFunctor ( vtkTable outData,
vtkDataObject inMeta,
vtkStringArray rowNames,
AssessFunctor *&  dfunc 
) [pure virtual]

A pure virtual method to select the appropriate assessment functor.

Implemented in vtkContingencyStatistics, vtkCorrelativeStatistics, vtkDescriptiveStatistics, vtkMultiCorrelativeStatistics, vtkOrderStatistics, and vtkPCAStatistics.

virtual void vtkStatisticsAlgorithm::SetColumnStatus ( const char *  namCol,
int  status 
) [virtual]

Add or remove a column from the current analysis request. Once all the column status values are set, call RequestSelectedColumns() before selecting another set of columns for a different analysis request. The way that columns selections are used varies from algorithm to algorithm. Note: the set of selected columns is maintained in vtkStatisticsAlgorithmPrivate::Buffer until RequestSelectedColumns() is called, at which point the set is appended to vtkStatisticsAlgorithmPrivate::Requests. If there are any columns in vtkStatisticsAlgorithmPrivate::Buffer at the time RequestData() is called, RequestSelectedColumns() will be called and the selection added to the list of requests.

Reimplemented in vtkBivariateStatisticsAlgorithm, and vtkUnivariateStatisticsAlgorithm.

virtual void vtkStatisticsAlgorithm::ResetAllColumnStates (  )  [virtual]

Set the the status of each and every column in the current request to OFF (0).

virtual int vtkStatisticsAlgorithm::RequestSelectedColumns (  )  [virtual]

Use the current column status values to produce a new request for statistics to be produced when RequestData() is called. See SetColumnStatus() for more information.

virtual void vtkStatisticsAlgorithm::ResetRequests (  )  [virtual]

Empty the list of current requests.

virtual int vtkStatisticsAlgorithm::FillInputPortInformation ( int  port,
vtkInformation info 
) [protected, virtual]

Fill the input port information objects for this algorithm. This is invoked by the first call to GetInputPortInformation for each port so subclasses can specify what they can handle.

Reimplemented from vtkTableAlgorithm.

Reimplemented in vtkMultiCorrelativeStatistics, and vtkPCAStatistics.

virtual int vtkStatisticsAlgorithm::FillOutputPortInformation ( int  port,
vtkInformation info 
) [protected, virtual]

Fill the output port information objects for this algorithm. This is invoked by the first call to GetOutputPortInformation for each port so subclasses can specify what they can handle.

Reimplemented from vtkTableAlgorithm.

Reimplemented in vtkMultiCorrelativeStatistics.

virtual int vtkStatisticsAlgorithm::RequestData ( vtkInformation request,
vtkInformationVector **  inputVector,
vtkInformationVector outputVector 
) [protected, virtual]

This is called by the superclass. This is the method you should override.

Reimplemented from vtkTableAlgorithm.

virtual void vtkStatisticsAlgorithm::ExecuteLearn ( vtkTable ,
vtkDataObject  
) [protected, pure virtual]

virtual void vtkStatisticsAlgorithm::ExecuteDerive ( vtkDataObject  )  [protected, pure virtual]

Execute the required calculations in the specified execution modes

Implemented in vtkContingencyStatistics, vtkCorrelativeStatistics, vtkDescriptiveStatistics, vtkMultiCorrelativeStatistics, vtkOrderStatistics, and vtkPCAStatistics.

virtual void vtkStatisticsAlgorithm::ExecuteAssess ( vtkTable ,
vtkDataObject ,
vtkTable ,
vtkDataObject  
) [protected, pure virtual]

Execute the required calculations in the specified execution modes

Implemented in vtkBivariateStatisticsAlgorithm, vtkMultiCorrelativeStatistics, vtkPCAStatistics, and vtkUnivariateStatisticsAlgorithm.


Member Data Documentation

Definition at line 204 of file vtkStatisticsAlgorithm.h.

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Definition at line 208 of file vtkStatisticsAlgorithm.h.

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Definition at line 210 of file vtkStatisticsAlgorithm.h.

Definition at line 211 of file vtkStatisticsAlgorithm.h.


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

Generated on Wed Jun 3 19:36:21 2009 for VTK by  doxygen 1.5.6