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vtkStatisticsAlgorithm Class Referenceabstract

Base class for statistics algorithms. More...

#include <vtkStatisticsAlgorithm.h>

Inheritance diagram for vtkStatisticsAlgorithm:
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Collaboration diagram for vtkStatisticsAlgorithm:
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Classes

class  AssessFunctor
 

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 int IsA (const char *type)
 
vtkStatisticsAlgorithmNewInstance () 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)
 
virtual bool SetParameter (const char *parameter, int index, vtkVariant value)
 
virtual void Aggregate (vtkDataObjectCollection *, vtkMultiBlockDataSet *)=0
 

Static Public Member Functions

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

Protected Member Functions

virtual vtkObjectBase * NewInstanceInternal () const
 
 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 (vtkMultiBlockDataSet *)=0
 
virtual void Learn (vtkTable *, vtkTable *, vtkMultiBlockDataSet *)=0
 
virtual void Assess (vtkTable *, vtkMultiBlockDataSet *, vtkTable *)=0
 
void Assess (vtkTable *, vtkMultiBlockDataSet *, vtkTable *, int)
 
virtual void Test (vtkTable *, vtkMultiBlockDataSet *, vtkTable *)=0
 
virtual void SelectAssessFunctor (vtkTable *outData, vtkDataObject *inMeta, vtkStringArray *rowNames, AssessFunctor *&dfunc)=0
 

Protected Attributes

int NumberOfPrimaryTables
 
bool LearnOption
 
bool DeriveOption
 
bool AssessOption
 
bool TestOption
 
vtkStringArray * AssessNames
 
vtkStatisticsAlgorithmPrivateInternals
 

Detailed Description

Base class for statistics algorithms.

All statistics algorithms can conceptually be operated with several operations: 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 ports 3 optional input ports: Data (vtkTable) Parameters to the learn operation (vtkTable) Input model (vtkMultiBlockDataSet) 3 output ports: Data (input annotated with assessments when the Assess operation is ON). Output model (identical to the the input model when Learn operation is OFF). Output of statistical tests. Some engines do not offer such tests yet, in which case this output will always be empty even when the Test operation is ON.

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

Definition at line 75 of file vtkStatisticsAlgorithm.h.

Member Typedef Documentation

typedef vtkTableAlgorithm vtkStatisticsAlgorithm::Superclass

Definition at line 78 of file vtkStatisticsAlgorithm.h.

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 84 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)

Definition at line 94 of file vtkStatisticsAlgorithm.h.

Constructor & Destructor Documentation

vtkStatisticsAlgorithm::vtkStatisticsAlgorithm ( )
protected
vtkStatisticsAlgorithm::~vtkStatisticsAlgorithm ( )
protected

Member Function Documentation

static int vtkStatisticsAlgorithm::IsTypeOf ( const char *  type)
static
virtual int vtkStatisticsAlgorithm::IsA ( const char *  type)
virtual
static vtkStatisticsAlgorithm* vtkStatisticsAlgorithm::SafeDownCast ( vtkObjectBase *  o)
static
virtual vtkObjectBase* vtkStatisticsAlgorithm::NewInstanceInternal ( ) const
protectedvirtual
vtkStatisticsAlgorithm* vtkStatisticsAlgorithm::NewInstance ( ) const
void vtkStatisticsAlgorithm::PrintSelf ( ostream &  os,
vtkIndent  indent 
)
virtual void vtkStatisticsAlgorithm::SetLearnOptionParameterConnection ( vtkAlgorithmOutput *  params)
inlinevirtual

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 110 of file vtkStatisticsAlgorithm.h.

virtual void vtkStatisticsAlgorithm::SetLearnOptionParameters ( vtkDataObject *  params)
inlinevirtual

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

Definition at line 118 of file vtkStatisticsAlgorithm.h.

virtual void vtkStatisticsAlgorithm::SetInputModelConnection ( vtkAlgorithmOutput *  model)
inlinevirtual

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 126 of file vtkStatisticsAlgorithm.h.

virtual void vtkStatisticsAlgorithm::SetInputModel ( vtkDataObject *  model)
inlinevirtual

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

Definition at line 133 of file vtkStatisticsAlgorithm.h.

virtual void vtkStatisticsAlgorithm::SetLearnOption ( bool  )
virtual

Set/Get the Learn operation.

virtual bool vtkStatisticsAlgorithm::GetLearnOption ( )
virtual

Set/Get the Learn operation.

virtual void vtkStatisticsAlgorithm::SetDeriveOption ( bool  )
virtual

Set/Get the Derive operation.

virtual bool vtkStatisticsAlgorithm::GetDeriveOption ( )
virtual

Set/Get the Derive operation.

virtual void vtkStatisticsAlgorithm::SetAssessOption ( bool  )
virtual

Set/Get the Assess operation.

virtual bool vtkStatisticsAlgorithm::GetAssessOption ( )
virtual

Set/Get the Assess operation.

virtual void vtkStatisticsAlgorithm::SetTestOption ( bool  )
virtual

Set/Get the Test operation.

virtual bool vtkStatisticsAlgorithm::GetTestOption ( )
virtual

Set/Get the Test operation.

virtual void vtkStatisticsAlgorithm::SetNumberOfPrimaryTables ( vtkIdType  )
virtual

Set/Get the number of tables in the primary model.

virtual vtkIdType vtkStatisticsAlgorithm::GetNumberOfPrimaryTables ( )
virtual

Set/Get the number of tables in the primary model.

virtual void vtkStatisticsAlgorithm::SetAssessNames ( vtkStringArray *  )
virtual

Set/get assessment names.

virtual vtkStringArray* vtkStatisticsAlgorithm::GetAssessNames ( )
virtual

Set/get assessment names.

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.

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.

void vtkStatisticsAlgorithm::AddColumn ( const char *  namCol)

Convenience method to create a request with a single column name namCol in a single call; this is the preferred method to select columns, ensuring selection consistency (a single column per request). Warning: no name checking is performed on namCol; it is the user's responsibility to use valid column names.

void vtkStatisticsAlgorithm::AddColumnPair ( const char *  namColX,
const char *  namColY 
)

Convenience method to create a request with a single column name pair (namColX, namColY) in a single call; this is the preferred method to select columns pairs, ensuring selection consistency (a pair of columns per request). Unlike SetColumnStatus(), you need not call RequestSelectedColumns() after AddColumnPair(). Warning: namColX and namColY are only checked for their validity as strings; no check is made that either are valid column names.

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 vtkPCAStatistics, vtkKMeansStatistics, and vtkOrderStatistics.

virtual void vtkStatisticsAlgorithm::Aggregate ( vtkDataObjectCollection *  ,
vtkMultiBlockDataSet *   
)
pure virtual
virtual int vtkStatisticsAlgorithm::FillInputPortInformation ( int  port,
vtkInformation *  info 
)
protectedvirtual

Reimplemented in vtkPCAStatistics.

virtual int vtkStatisticsAlgorithm::FillOutputPortInformation ( int  port,
vtkInformation *  info 
)
protectedvirtual
virtual int vtkStatisticsAlgorithm::RequestData ( vtkInformation *  ,
vtkInformationVector **  ,
vtkInformationVector *   
)
protectedvirtual
virtual void vtkStatisticsAlgorithm::Learn ( vtkTable *  ,
vtkTable *  ,
vtkMultiBlockDataSet *   
)
protectedpure virtual
virtual void vtkStatisticsAlgorithm::Derive ( vtkMultiBlockDataSet *  )
protectedpure virtual
virtual void vtkStatisticsAlgorithm::Assess ( vtkTable *  ,
vtkMultiBlockDataSet *  ,
vtkTable *   
)
protectedpure virtual
void vtkStatisticsAlgorithm::Assess ( vtkTable *  ,
vtkMultiBlockDataSet *  ,
vtkTable *  ,
int   
)
protected

A convenience implementation for generic assessment with variable number of variables.

virtual void vtkStatisticsAlgorithm::Test ( vtkTable *  ,
vtkMultiBlockDataSet *  ,
vtkTable *   
)
protectedpure virtual
virtual void vtkStatisticsAlgorithm::SelectAssessFunctor ( vtkTable *  outData,
vtkDataObject *  inMeta,
vtkStringArray *  rowNames,
AssessFunctor *&  dfunc 
)
protectedpure virtual

Member Data Documentation

int vtkStatisticsAlgorithm::NumberOfPrimaryTables
protected

Definition at line 325 of file vtkStatisticsAlgorithm.h.

bool vtkStatisticsAlgorithm::LearnOption
protected

Definition at line 326 of file vtkStatisticsAlgorithm.h.

bool vtkStatisticsAlgorithm::DeriveOption
protected

Definition at line 327 of file vtkStatisticsAlgorithm.h.

bool vtkStatisticsAlgorithm::AssessOption
protected

Definition at line 328 of file vtkStatisticsAlgorithm.h.

bool vtkStatisticsAlgorithm::TestOption
protected

Definition at line 329 of file vtkStatisticsAlgorithm.h.

vtkStringArray* vtkStatisticsAlgorithm::AssessNames
protected

Definition at line 330 of file vtkStatisticsAlgorithm.h.

vtkStatisticsAlgorithmPrivate* vtkStatisticsAlgorithm::Internals
protected

Definition at line 331 of file vtkStatisticsAlgorithm.h.


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