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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkKdTreeTestSamplePoints.cxx
Language: C++
Date: $Date$
Version: $Revision$
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.
=========================================================================*/
#if defined(_MSC_VER)
#pragma warning ( disable : 4786 )
#endif
#include "itkVector.h"
#include "itkMersenneTwisterRandomVariateGenerator.h"
#include "itkListSample.h"
#include "itkKdTree.h"
#include "itkKdTreeGenerator.h"
#include "itkEuclideanDistanceMetric.h"
#include <fstream>
int itkKdTreeTestSamplePoints(int , char *[] )
{
typedef itk::Array< double > MeasurementVectorType;
typedef itk::Statistics::ListSample< MeasurementVectorType > SampleType;
const SampleType::MeasurementVectorSizeType measurementVectorSize = 2;
SampleType::Pointer sample = SampleType::New();
sample->SetMeasurementVectorSize( measurementVectorSize );
const unsigned int numberOfDataPoints = 5;
MeasurementVectorType mv( measurementVectorSize );
mv[0] = 0.0342;
mv[1] = 0.5175;
sample->PushBack( mv );
MeasurementVectorType mv2( measurementVectorSize );
mv2[0] = 0.9650;
mv2[1] = -0.9379;
sample->PushBack( mv2 );
MeasurementVectorType mv3( measurementVectorSize );
mv3[0] = -0.0471;
mv3[1] = 0.8177;
sample->PushBack( mv3 );
MeasurementVectorType mv4( measurementVectorSize );
mv4[0] = 0.4737;
mv4[1] = -1.0447;
sample->PushBack( mv4 );
MeasurementVectorType mv5( measurementVectorSize );
mv5[0] = -0.6307;
mv5[1] = -2.7600;
sample->PushBack( mv5 );
typedef itk::Statistics::KdTreeGenerator< SampleType > TreeGeneratorType;
TreeGeneratorType::Pointer treeGenerator = TreeGeneratorType::New();
const unsigned int bucketSize = 1;
treeGenerator->SetSample( sample );
treeGenerator->SetBucketSize( bucketSize );
treeGenerator->Update();
typedef TreeGeneratorType::KdTreeType TreeType;
typedef TreeType::NearestNeighbors NeighborsType;
typedef TreeType::KdTreeNodeType NodeType;
TreeType::Pointer tree = treeGenerator->GetOutput();
MeasurementVectorType queryPoint( measurementVectorSize );
unsigned int numberOfNeighbors = 1;
TreeType::InstanceIdentifierVectorType neighbors;
MeasurementVectorType result( measurementVectorSize );
MeasurementVectorType test_point( measurementVectorSize );
MeasurementVectorType min_point( measurementVectorSize );
//
// Check that for every point in the sample, its closest point is itself.
//
typedef itk::Statistics::EuclideanDistanceMetric< MeasurementVectorType > DistanceMetricType;
typedef DistanceMetricType::OriginType OriginType;
DistanceMetricType::Pointer distanceMetric = DistanceMetricType::New();
OriginType origin( measurementVectorSize );
for( unsigned int k = 0; k < sample->Size(); k++ )
{
queryPoint = sample->GetMeasurementVector(k);
for ( unsigned int i = 0; i < sample->GetMeasurementVectorSize(); ++i )
{
origin[i] = queryPoint[i];
}
distanceMetric->SetOrigin( origin );
tree->Search( queryPoint, numberOfNeighbors, neighbors );
for ( unsigned int i = 0; i < numberOfNeighbors; ++i )
{
const double distance =
distanceMetric->Evaluate( tree->GetMeasurementVector( neighbors[i] ));
if( distance > vnl_math::eps )
{
std::cerr << "kd-tree knn search result:" << std::endl
<< "query point = [" << queryPoint << "]" << std::endl
<< "k = " << numberOfNeighbors << std::endl;
std::cerr << "measurement vector : distance" << std::endl;
std::cerr << "[" << tree->GetMeasurementVector( neighbors[i] )
<< "] : "
<< distance << std::endl;
}
}
}
double min_dist = itk::NumericTraits< double >::max();
/*
queryPoint[0] = 1.16651;
queryPoint[1] = 0.16395;
*/
/*
queryPoint[0] = 1.0;
queryPoint[1] = 0.12;
*/
queryPoint[0] = 1.0;
queryPoint[1] = 0.1;
tree->Search( queryPoint, numberOfNeighbors, neighbors );
//
// The first neighbor should be the closest point.
//
result = tree->GetMeasurementVector( neighbors[0] );
//
// Compute the distance to the "presumed" nearest neighbor
//
double result_dist = vcl_sqrt(
(result[0] - queryPoint[0]) *
(result[0] - queryPoint[0]) +
(result[1] - queryPoint[1]) *
(result[1] - queryPoint[1])
);
//
// Compute the distance to all other points, to verify
// whether the first neighbor was the closest one or not.
//
for( unsigned int i = 0; i < numberOfDataPoints; ++i )
{
test_point = tree->GetMeasurementVector( i );
std::cout << "Compute distance with: " << test_point;
const double dist = vcl_sqrt(
(test_point[0] - queryPoint[0]) *
(test_point[0] - queryPoint[0]) +
(test_point[1] - queryPoint[1]) *
(test_point[1] - queryPoint[1])
);
std::cout << "\t" << dist << std::endl;
if( dist < min_dist )
{
min_dist = dist;
min_point = test_point;
}
}
if( min_dist < result_dist )
{
std::cerr << "Problem found " << std::endl;
std::cerr << "Query point " << queryPoint << std::endl;
std::cerr << "Reported closest point " << result
<< " distance " << result_dist << std::endl;
std::cerr << "Actual closest point " << min_point
<< " distance " << min_dist << std::endl;
std::cerr << std::endl;
std::cerr << "Test FAILED." << std::endl;
}
//
// Plot out the tree structure to the console in the format used by Graphviz dot
//
std::ofstream plotFile;
plotFile.open( "plot.dot" );
tree->PlotTree( plotFile );
plotFile.close();
return EXIT_SUCCESS;
}
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