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vtkStatisticsAlgorithm.cxx
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vtkStatisticsAlgorithm.cxx
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/*=========================================================================
Program: Visualization Toolkit
Module: vtkStatisticsAlgorithm.cxx
Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
All rights reserved.
See Copyright.txt or http://www.kitware.com/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notice for more information.
=========================================================================*/
/*-------------------------------------------------------------------------
Copyright 2011 Sandia Corporation.
Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
the U.S. Government retains certain rights in this software.
-------------------------------------------------------------------------*/
#include "vtkToolkits.h"
#include "vtkStatisticsAlgorithm.h"
#include "vtkDataObjectCollection.h"
#include "vtkDoubleArray.h"
#include "vtkInformation.h"
#include "vtkInformationVector.h"
#include "vtkObjectFactory.h"
#include "vtkMultiBlockDataSet.h"
#include "vtkSmartPointer.h"
#include "vtkStatisticsAlgorithmPrivate.h"
#include "vtkStringArray.h"
#include "vtkTable.h"
#include "vtkVariantArray.h"
#include <sstream>
vtkCxxSetObjectMacro(vtkStatisticsAlgorithm,AssessNames,vtkStringArray);
// ----------------------------------------------------------------------
vtkStatisticsAlgorithm::vtkStatisticsAlgorithm()
{
this->SetNumberOfInputPorts( 3 );
this->SetNumberOfOutputPorts( 3 );
// If not told otherwise, only run Learn option
this->LearnOption = true;
this->DeriveOption = true;
this->AssessOption = false;
this->TestOption = false;
// Most engines have only 1 primary table.
this->NumberOfPrimaryTables = 1;
this->AssessNames = vtkStringArray::New();
this->Internals = new vtkStatisticsAlgorithmPrivate;
}
// ----------------------------------------------------------------------
vtkStatisticsAlgorithm::~vtkStatisticsAlgorithm()
{
this->SetAssessNames( 0 );
delete this->Internals;
}
// ----------------------------------------------------------------------
void vtkStatisticsAlgorithm::PrintSelf( ostream &os, vtkIndent indent )
{
this->Superclass::PrintSelf( os, indent );
os << indent << "Learn: " << this->LearnOption << endl;
os << indent << "Derive: " << this->DeriveOption << endl;
os << indent << "Assess: " << this->AssessOption << endl;
os << indent << "Test: " << this->TestOption << endl;
os << indent << "NumberOfPrimaryTables: " << this->NumberOfPrimaryTables << endl;
if ( this->AssessNames )
{
this->AssessNames->PrintSelf( os, indent.GetNextIndent() );
}
os << indent << "Internals: " << this->Internals << endl;
}
// ----------------------------------------------------------------------
int vtkStatisticsAlgorithm::FillInputPortInformation( int port, vtkInformation* info )
{
if ( port == INPUT_DATA )
{
info->Set( vtkAlgorithm::INPUT_IS_OPTIONAL(), 1 );
info->Set( vtkAlgorithm::INPUT_REQUIRED_DATA_TYPE(), "vtkTable" );
return 1;
}
else if ( port == INPUT_MODEL )
{
info->Set( vtkAlgorithm::INPUT_IS_OPTIONAL(), 1 );
info->Set( vtkAlgorithm::INPUT_REQUIRED_DATA_TYPE(), "vtkMultiBlockDataSet" );
return 1;
}
else if ( port == LEARN_PARAMETERS )
{
info->Set( vtkAlgorithm::INPUT_IS_OPTIONAL(), 1 );
info->Set( vtkAlgorithm::INPUT_REQUIRED_DATA_TYPE(), "vtkTable" );
return 1;
}
return 0;
}
// ----------------------------------------------------------------------
int vtkStatisticsAlgorithm::FillOutputPortInformation( int port, vtkInformation* info )
{
if ( port == OUTPUT_DATA )
{
info->Set( vtkDataObject::DATA_TYPE_NAME(), "vtkTable" );
return 1;
}
else if ( port == OUTPUT_MODEL )
{
info->Set( vtkDataObject::DATA_TYPE_NAME(), "vtkMultiBlockDataSet" );
return 1;
}
else if ( port == OUTPUT_TEST )
{
info->Set( vtkDataObject::DATA_TYPE_NAME(), "vtkTable" );
return 1;
}
return 0;
}
//---------------------------------------------------------------------------
void vtkStatisticsAlgorithm::SetColumnStatus( const char* namCol, int status )
{
this->Internals->SetBufferColumnStatus( namCol, status );
}
//---------------------------------------------------------------------------
void vtkStatisticsAlgorithm::ResetAllColumnStates()
{
this->Internals->ResetBuffer();
}
//---------------------------------------------------------------------------
int vtkStatisticsAlgorithm::RequestSelectedColumns()
{
return this->Internals->AddBufferToRequests();
}
//---------------------------------------------------------------------------
void vtkStatisticsAlgorithm::ResetRequests()
{
this->Internals->ResetRequests();
}
//---------------------------------------------------------------------------
vtkIdType vtkStatisticsAlgorithm::GetNumberOfRequests()
{
return this->Internals->GetNumberOfRequests();
}
//---------------------------------------------------------------------------
vtkIdType vtkStatisticsAlgorithm::GetNumberOfColumnsForRequest( vtkIdType request )
{
return this->Internals->GetNumberOfColumnsForRequest( request );
}
//---------------------------------------------------------------------------
const char* vtkStatisticsAlgorithm::GetColumnForRequest( vtkIdType r, vtkIdType c )
{
static vtkStdString columnName;
if ( this->Internals->GetColumnForRequest( r, c, columnName ) )
{
return columnName.c_str();
}
return 0;
}
//---------------------------------------------------------------------------
int vtkStatisticsAlgorithm::GetColumnForRequest( vtkIdType r, vtkIdType c, vtkStdString& columnName )
{
return this->Internals->GetColumnForRequest( r, c, columnName ) ? 1 : 0;
}
// ----------------------------------------------------------------------
void vtkStatisticsAlgorithm::AddColumn( const char* namCol )
{
if ( this->Internals->AddColumnToRequests( namCol ) )
{
this->Modified();
}
}
// ----------------------------------------------------------------------
void vtkStatisticsAlgorithm::AddColumnPair( const char* namColX, const char* namColY )
{
if ( this->Internals->AddColumnPairToRequests( namColX, namColY ) )
{
this->Modified();
}
}
// ----------------------------------------------------------------------
bool vtkStatisticsAlgorithm::SetParameter( const char* vtkNotUsed(parameter),
int vtkNotUsed(index),
vtkVariant vtkNotUsed(value) )
{
return false;
}
// ----------------------------------------------------------------------
int vtkStatisticsAlgorithm::RequestData( vtkInformation*,
vtkInformationVector** inputVector,
vtkInformationVector* outputVector )
{
// Extract inputs
vtkTable* inData = vtkTable::GetData( inputVector[INPUT_DATA], 0 );
vtkMultiBlockDataSet* inModel = vtkMultiBlockDataSet::GetData( inputVector[INPUT_MODEL], 0 );
vtkTable* inParameters = vtkTable::GetData( inputVector[LEARN_PARAMETERS], 0 );
// Extract outputs
vtkTable* outData = vtkTable::GetData( outputVector, OUTPUT_DATA );
vtkMultiBlockDataSet* outModel = vtkMultiBlockDataSet::GetData( outputVector, OUTPUT_MODEL );
vtkTable* outTest = vtkTable::GetData( outputVector, OUTPUT_TEST );
// If input data table is not null then shallow copy it to output
if ( inData )
{
outData->ShallowCopy( inData );
}
// If there are any columns selected in the buffer which have not been
// turned into a request by RequestSelectedColumns(), add them now.
// There should be no effect if vtkStatisticsAlgorithmPrivate::Buffer is empty.
// This is here to accommodate the simpler user interfaces in OverView for
// univariate and bivariate algorithms which will not call RequestSelectedColumns()
// on their own.
this->RequestSelectedColumns();
// Calculate primary statistics if requested
if ( this->LearnOption )
{
// First, learn primary statistics from data; otherwise, only use input model as output model
this->Learn( inData, inParameters, outModel );
// Second, aggregate learned models with input model if one is present
if ( inModel )
{
vtkDataObjectCollection* models = vtkDataObjectCollection::New();
models->AddItem( inModel );
models->AddItem( outModel );
this->Aggregate( models, outModel );
models->Delete();
}
}
else
{
// No input data and no input model result in an error condition
if ( ! inModel )
{
vtkErrorMacro( "No model available AND no Learn phase requested. Cannot proceed with statistics algorithm." );
return 1;
}
// Since no learn phase was requested, the output model is equal to the input one
outModel->ShallowCopy( inModel );
}
// Calculate derived statistics if requested
if ( this->DeriveOption )
{
this->Derive( outModel );
}
// Assess data with respect to statistical model if requested
if ( this->AssessOption )
{
this->Assess( inData, outModel, outData );
}
// Calculate test statistics if requested
if ( this->TestOption )
{
this->Test( inData, outModel, outTest );
}
return 1;
}
// ----------------------------------------------------------------------
void vtkStatisticsAlgorithm::Assess( vtkTable* inData,
vtkMultiBlockDataSet* inMeta,
vtkTable* outData,
int numVariables )
{
if ( ! inData )
{
return;
}
if ( ! inMeta )
{
return;
}
// Loop over requests
for ( std::set<std::set<vtkStdString> >::const_iterator rit = this->Internals->Requests.begin();
rit != this->Internals->Requests.end(); ++ rit )
{
// Storage for variable names of the request (smart pointer because of several exit points)
vtkSmartPointer<vtkStringArray> varNames = vtkSmartPointer<vtkStringArray>::New();
varNames->SetNumberOfValues( numVariables );
// Each request must contain numVariables columns of interest (additional columns are ignored)
bool invalidRequest = false;
int v = 0;
for ( std::set<vtkStdString>::const_iterator it = rit->begin();
v < numVariables && it != rit->end(); ++ v, ++ it )
{
// Try to retrieve column with corresponding name in input data
vtkStdString varName = *it;
// If requested column does not exist in input, ignore request
if ( ! inData->GetColumnByName( varName ) )
{
vtkWarningMacro( "InData table does not have a column "
<< varName.c_str()
<< ". Ignoring request containing it." );
invalidRequest = true;
break;
}
// If column with corresponding name was found, store name
varNames->SetValue( v, varName );
}
if ( invalidRequest )
{
continue;
}
// If request is too short, it must also be ignored
if ( v < numVariables )
{
vtkWarningMacro( "Only "
<< v
<< " variables in the request while "
<< numVariables
<< "are needed. Ignoring request." );
continue;
}
// Store names to be able to use SetValueByName, and create the outData columns
vtkIdType nAssessments = this->AssessNames->GetNumberOfValues();
vtkStdString* names = new vtkStdString[nAssessments];
vtkIdType nRowData = inData->GetNumberOfRows();
for ( vtkIdType a = 0; a < nAssessments; ++ a )
{
// Prepare string for numVariables-tuple of variable names
std::ostringstream assessColName;
assessColName << this->AssessNames->GetValue( a )
<< "(";
for ( int i = 0 ; i < numVariables ; ++ i )
{
// Insert comma before each variable name, save the first one
if ( i > 0 )
{
assessColName << ",";
}
assessColName << varNames->GetValue( i );
}
assessColName << ")";
names[a] = assessColName.str().c_str();
// Create assessment columns with names <AssessmentName>(var1,...,varN)
vtkDoubleArray* assessColumn = vtkDoubleArray::New();
assessColumn->SetName( names[a] );
assessColumn->SetNumberOfTuples( nRowData );
outData->AddColumn( assessColumn );
assessColumn->Delete();
}
// Select assess functor
AssessFunctor* dfunc;
this->SelectAssessFunctor( outData,
inMeta,
varNames,
dfunc );
if ( ! dfunc )
{
// Functor selection did not work. Do nothing.
vtkWarningMacro( "AssessFunctors could not be allocated. Ignoring request." );
}
else
{
// Assess each entry of the column
vtkDoubleArray* assessResult = vtkDoubleArray::New();
for ( vtkIdType r = 0; r < nRowData; ++ r )
{
// Apply functor
(*dfunc)( assessResult, r );
for ( vtkIdType a = 0; a < nAssessments; ++ a )
{
// Store each assessment value in corresponding assessment column
outData->SetValueByName( r,
names[a],
assessResult->GetValue( a ) );
}
}
assessResult->Delete();
}
delete dfunc;
delete [] names;
}
}