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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkWeightedCentroidKdTreeGenerator.txx,v $
Language: C++
Date: $Date: 2009-03-04 19:29:54 $
Version: $Revision: 1.11 $
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/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 notices for more information.
=========================================================================*/
#ifndef __itkWeightedCentroidKdTreeGenerator_txx
#define __itkWeightedCentroidKdTreeGenerator_txx
namespace itk {
namespace Statistics {
template< class TSample >
WeightedCentroidKdTreeGenerator< TSample >
::WeightedCentroidKdTreeGenerator()
{
}
template< class TSample >
void
WeightedCentroidKdTreeGenerator< TSample >
::PrintSelf(std::ostream& os, Indent indent) const
{
Superclass::PrintSelf(os,indent);
}
template< class TSample >
inline typename WeightedCentroidKdTreeGenerator< TSample >::KdTreeNodeType*
WeightedCentroidKdTreeGenerator< TSample >
::GenerateNonterminalNode(unsigned int beginIndex,
unsigned int endIndex,
MeasurementVectorType &lowerBound,
MeasurementVectorType &upperBound,
unsigned int level)
{
MeasurementType dimensionLowerBound;
MeasurementType dimensionUpperBound;
MeasurementType partitionValue;
unsigned int partitionDimension = 0;
unsigned int i;
unsigned int j;
MeasurementType spread;
MeasurementType maxSpread;
unsigned int medianIndex;
SubsamplePointer subsample = this->GetSubsample();
// Sanity check. Verify that the subsample has measurement vectors of the
// same length as the sample generated by the tree.
if( this->GetMeasurementVectorSize() != subsample->GetMeasurementVectorSize() )
{
itkExceptionMacro( << "Measurement Vector Length mismatch" );
}
// calculates the weighted centroid which is the vector sum
// of all the associated instances.
typename KdTreeNodeType::CentroidType weightedCentroid;
MeasurementVectorTraits::SetLength( weightedCentroid, this->GetMeasurementVectorSize() );
MeasurementVectorType tempVector;
weightedCentroid.Fill(NumericTraits< MeasurementType >::Zero);
for (i = beginIndex; i < endIndex; i++)
{
tempVector = subsample->GetMeasurementVectorByIndex(i);
for(j = 0; j < this->GetMeasurementVectorSize(); j++)
{
weightedCentroid[j] += tempVector[j];
}
}
// find most widely spread dimension
FindSampleBoundAndMean< SubsampleType >(this->GetSubsample(),
beginIndex, endIndex,
m_TempLowerBound, m_TempUpperBound,
m_TempMean);
maxSpread = NumericTraits< MeasurementType >::NonpositiveMin();
for (i = 0; i < this->GetMeasurementVectorSize(); i++)
{
spread = m_TempUpperBound[i] - m_TempLowerBound[i];
if (spread >= maxSpread)
{
maxSpread = spread;
partitionDimension = i;
}
}
medianIndex = (endIndex - beginIndex) / 2;
//
// Find the medial element by using the NthElement function
// based on the STL implementation of the QuickSelect algorithm.
//
partitionValue =
NthElement< SubsampleType >(this->GetSubsample(),
partitionDimension,
beginIndex, endIndex,
medianIndex);
medianIndex += beginIndex;
// save bounds for cutting dimension
dimensionLowerBound = lowerBound[partitionDimension];
dimensionUpperBound = upperBound[partitionDimension];
upperBound[partitionDimension] = partitionValue;
const unsigned int beginLeftIndex = beginIndex;
const unsigned int endLeftIndex = medianIndex;
KdTreeNodeType* left = GenerateTreeLoop(beginLeftIndex, endLeftIndex, lowerBound, upperBound, level + 1);
upperBound[partitionDimension] = dimensionUpperBound;
lowerBound[partitionDimension] = partitionValue;
const unsigned int beginRightIndex = medianIndex+1;
const unsigned int endRighIndex = endIndex;
KdTreeNodeType* right = GenerateTreeLoop(beginRightIndex, endRighIndex, lowerBound, upperBound, level + 1);
lowerBound[partitionDimension] = dimensionLowerBound;
typedef KdTreeWeightedCentroidNonterminalNode< TSample > KdTreeNonterminalNodeType;
KdTreeNonterminalNodeType * nonTerminalNode =
new KdTreeNonterminalNodeType( partitionDimension,
partitionValue,
left, right,
weightedCentroid,
endIndex - beginIndex);
nonTerminalNode->AddInstanceIdentifier(
subsample->GetInstanceIdentifier( medianIndex ) );
return nonTerminalNode;
}
} // end of namespace Statistics
} // end of namespace itk
#endif
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