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). 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. Assess: given an input data set, input statistics, and some form of threshold, assess a subset of the data set. Test: perform at least one statistical test. Therefore, a vtkStatisticsAlgorithm has the following vtkTable ports 3 input ports: Data (mandatory) Parameters to the learn phase (optional) 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.
Tests:
vtkStatisticsAlgorithm (Tests)

Definition at line 69 of file vtkStatisticsAlgorithm.h.


Public Types

typedef vtkTableAlgorithm Superclass
enum  InputPorts { INPUT_DATA = 0, LEARN_PARAMETERS = 1, INPUT_MODEL = 2 }
enum  OutputIndices { OUTPUT_DATA = 0, OUTPUT_MODEL = 1, ASSESSMENT = 2, OUTPUT_TEST = 2 }

Public Member Functions

virtual const char * GetClassName ()
virtual int IsA (const char *type)
void PrintSelf (ostream &os, vtkIndent indent)
void SetAssessOptionParameter (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 vtkIdType GetNumberOfRequests ()
virtual vtkIdType GetNumberOfColumnsForRequest (vtkIdType request)
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 SetAssessParameters (vtkStringArray *)
virtual vtkStringArrayGetAssessParameters ()
virtual void SetAssessNames (vtkStringArray *)
virtual vtkStringArrayGetAssessNames ()
virtual const char * GetColumnForRequest (vtkIdType r, vtkIdType c)
virtual int GetColumnForRequest (vtkIdType r, vtkIdType c, vtkStdString &columnName)
virtual bool SetParameter (const char *parameter, int index, vtkVariant value)
virtual void Aggregate (vtkDataObjectCollection *, vtkDataObject *)=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 Derive (vtkDataObject *)=0
virtual void Learn (vtkTable *, vtkTable *, vtkDataObject *)=0
virtual void Assess (vtkTable *, vtkDataObject *, vtkTable *)=0
virtual void Test (vtkTable *, vtkDataObject *, vtkDataObject *)=0
virtual void SelectAssessFunctor (vtkTable *outData, vtkDataObject *inMeta, vtkStringArray *rowNames, AssessFunctor *&dfunc)=0

Protected Attributes

bool LearnOption
bool DeriveOption
bool AssessOption
bool TestOption
vtkStringArrayAssessParameters
vtkStringArrayAssessNames
vtkStatisticsAlgorithmPrivateInternals

Classes

class  AssessFunctor

Member Typedef Documentation


Member Enumeration Documentation

enumeration values to specify input port types

Enumerator:
INPUT_DATA  Port 0 is for learn data.
LEARN_PARAMETERS  Port 1 is for learn parameters (initial guesses, etc.).
INPUT_MODEL  Port 2 is for a priori models.

Definition at line 78 of file vtkStatisticsAlgorithm.h.

enumeration values to specify output port types

Enumerator:
OUTPUT_DATA  Output 0 mirrors the input data, plus optional assessment columns.
OUTPUT_MODEL  Output 1 contains any generated model.
ASSESSMENT  This is an old, deprecated name for OUTPUT_TEST.
OUTPUT_TEST  Output 2 contains result of statistical test(s).

Reimplemented in vtkExtractHistogram2D, and vtkPairwiseExtractHistogram2D.

Definition at line 88 of file vtkStatisticsAlgorithm.h.


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]

virtual int vtkStatisticsAlgorithm::IsA ( const char *  name  )  [virtual]

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

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

virtual void vtkStatisticsAlgorithm::SetLearnOptionParameterConnection ( vtkAlgorithmOutput params  )  [inline, virtual]

A convenience method for setting learn input parameters (if one is expected or allowed). It is equivalent to calling SetInputConnection( 1, params );

Definition at line 102 of file vtkStatisticsAlgorithm.h.

virtual void vtkStatisticsAlgorithm::SetLearnOptionParameters ( vtkDataObject params  )  [inline, virtual]

A convenience method for setting learn input parameters (if one is expected or allowed). It is equivalent to calling SetInput( 1, params );

Definition at line 110 of file vtkStatisticsAlgorithm.h.

virtual void vtkStatisticsAlgorithm::SetInputModelConnection ( vtkAlgorithmOutput model  )  [inline, virtual]

A convenience method for setting the input model connection (if one is expected or allowed). It is equivalent to calling SetInputConnection( 2, model );

Definition at line 118 of file vtkStatisticsAlgorithm.h.

virtual void vtkStatisticsAlgorithm::SetInputModel ( vtkDataObject model  )  [inline, virtual]

A convenience method for setting the input model (if one is expected or allowed). It is equivalent to calling SetInput( 2, model );

Definition at line 125 of file vtkStatisticsAlgorithm.h.

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

Set/Get the Learn option.

virtual bool vtkStatisticsAlgorithm::GetLearnOption (  )  [virtual]

Set/Get the Learn option.

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

Set/Get the Derive option.

virtual bool vtkStatisticsAlgorithm::GetDeriveOption (  )  [virtual]

Set/Get the Derive option.

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

Set/Get the Assess option.

virtual bool vtkStatisticsAlgorithm::GetAssessOption (  )  [virtual]

Set/Get the Assess option.

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

Set/Get the Test option.

virtual bool vtkStatisticsAlgorithm::GetTestOption (  )  [virtual]

Set/Get the Test option.

virtual void vtkStatisticsAlgorithm::SetAssessParameters ( vtkStringArray  )  [virtual]

Set/get assessment parameters.

virtual vtkStringArray* vtkStatisticsAlgorithm::GetAssessParameters (  )  [virtual]

Set/get assessment parameters.

virtual void vtkStatisticsAlgorithm::SetAssessNames ( vtkStringArray  )  [virtual]

Set/get assessment names.

virtual vtkStringArray* vtkStatisticsAlgorithm::GetAssessNames (  )  [virtual]

Set/get assessment names.

void vtkStatisticsAlgorithm::SetAssessOptionParameter ( 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::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.

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.

Reimplemented in vtkBivariateStatisticsAlgorithm, and vtkUnivariateStatisticsAlgorithm.

virtual void vtkStatisticsAlgorithm::ResetRequests (  )  [virtual]

Empty the list of current requests.

virtual vtkIdType vtkStatisticsAlgorithm::GetNumberOfRequests (  )  [virtual]

Return the number of requests. This does not include any request that is in the column-status buffer but for which RequestSelectedColumns() has not yet been called (even though it is possible this request will be honored when the filter is run -- see SetColumnStatus() for more information).

virtual vtkIdType vtkStatisticsAlgorithm::GetNumberOfColumnsForRequest ( vtkIdType  request  )  [virtual]

Return the number of columns for a given request.

virtual const char* vtkStatisticsAlgorithm::GetColumnForRequest ( vtkIdType  r,
vtkIdType  c 
) [virtual]

Provide the name of the c-th column for the r-th request. For the version of this routine that returns an integer, if the request or column does not exist because r or c is out of bounds, this routine returns 0 and the value of columnName is unspecified. Otherwise, it returns 1 and the value of columnName is set. For the version of this routine that returns const char*, if the request or column does not exist because r or c is out of bounds, the routine returns NULL. Otherwise it returns the column name. This version is not thread-safe.

virtual int vtkStatisticsAlgorithm::GetColumnForRequest ( vtkIdType  r,
vtkIdType  c,
vtkStdString columnName 
) [virtual]

Provide the name of the c-th column for the r-th request. For the version of this routine that returns an integer, if the request or column does not exist because r or c is out of bounds, this routine returns 0 and the value of columnName is unspecified. Otherwise, it returns 1 and the value of columnName is set. For the version of this routine that returns const char*, if the request or column does not exist because r or c is out of bounds, the routine returns NULL. Otherwise it returns the column name. This version is not thread-safe.

virtual bool vtkStatisticsAlgorithm::SetParameter ( const char *  parameter,
int  index,
vtkVariant  value 
) [virtual]

A convenience method (in particular for access from other applications) to set parameter values of Learn mode. Return true if setting of requested parameter name was excuted, false otherwise. NB: default method (which is sufficient for most statistics algorithms) does not have any Learn parameters to set and always returns false.

Reimplemented in vtkOrderStatistics, and vtkPCAStatistics.

virtual void vtkStatisticsAlgorithm::Aggregate ( vtkDataObjectCollection ,
vtkDataObject  
) [pure virtual]

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 vtkContingencyStatistics, vtkKMeansStatistics, 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 vtkContingencyStatistics, vtkExtractHistogram2D, vtkKMeansStatistics, vtkMultiCorrelativeStatistics, and vtkPairwiseExtractHistogram2D.

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::Learn ( vtkTable ,
vtkTable ,
vtkDataObject  
) [protected, pure virtual]

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

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

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

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


Member Data Documentation

Definition at line 300 of file vtkStatisticsAlgorithm.h.

Definition at line 301 of file vtkStatisticsAlgorithm.h.

Definition at line 302 of file vtkStatisticsAlgorithm.h.

Definition at line 303 of file vtkStatisticsAlgorithm.h.

Definition at line 304 of file vtkStatisticsAlgorithm.h.

Definition at line 305 of file vtkStatisticsAlgorithm.h.

Definition at line 306 of file vtkStatisticsAlgorithm.h.


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

Generated on Mon Sep 27 18:52:14 2010 for VTK by  doxygen 1.5.6