PKMeansClustering
VTKEx/Cxx/InfoVis/PKMeansClustering
Question
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Code¶
PKMeansClustering.cxx
#include <vtkSmartPointer.h>
#include <vtkProperty.h>
#include <vtkPointData.h>
#include <vtkPolyData.h>
#include <vtkXMLPolyDataWriter.h>
#include <vtkIntArray.h>
#include <vtkMultiBlockDataSet.h>
#include <vtkPoints.h>
#include <vtkTable.h>
#include <vtkDoubleArray.h>
#include <vtkPKMeansStatistics.h>
//display
#include <vtkPolyDataMapper.h>
#include <vtkActor.h>
#include <vtkRenderWindow.h>
#include <vtkRenderer.h>
#include <vtkRenderWindowInteractor.h>
#include <vtkVertexGlyphFilter.h>
#include <vtkInteractorStyleTrackballCamera.h>
#include <sstream>
int main(int, char*[])
{
//create 2 clusters, one near (0,0,0) and the other near (3,3,3)
vtkSmartPointer<vtkPoints> points = vtkSmartPointer<vtkPoints>::New();
points->InsertNextPoint ( 0.0, 0.0, 0.0 );
points->InsertNextPoint ( 3.0, 3.0, 3.0 );
points->InsertNextPoint ( 0.1, 0.1, 0.1 );
points->InsertNextPoint ( 3.1, 3.1, 3.1 );
points->InsertNextPoint ( 0.2, 0.2, 0.2 );
points->InsertNextPoint ( 3.2, 3.2, 3.2 );
// Get the points into the format needed for KMeans
vtkSmartPointer<vtkTable> inputData = vtkSmartPointer<vtkTable>::New();
for ( int c = 0; c < 3; ++c )
{
std::stringstream colName;
colName << "coord " << c;
vtkSmartPointer<vtkDoubleArray> doubleArray = vtkSmartPointer<vtkDoubleArray>::New();
doubleArray->SetNumberOfComponents(1);
doubleArray->SetName( colName.str().c_str() );
doubleArray->SetNumberOfTuples(points->GetNumberOfPoints());
for ( int r = 0; r < points->GetNumberOfPoints(); ++ r )
{
double p[3];
points->GetPoint(r, p);
doubleArray->SetValue( r, p[c] );
}
inputData->AddColumn( doubleArray );
}
vtkSmartPointer<vtkPKMeansStatistics> pKMeansStatistics = vtkSmartPointer<vtkPKMeansStatistics>::New();
//vtkSmartPointer<vtkKMeansStatistics> pKMeansStatistics = vtkSmartPointer<vtkKMeansStatistics>::New();
//pks->SetMaxNumIterations( 10 );
pKMeansStatistics->SetInputData( vtkStatisticsAlgorithm::INPUT_DATA, inputData );
pKMeansStatistics->SetColumnStatus( inputData->GetColumnName( 0 ) , 1 );
pKMeansStatistics->SetColumnStatus( inputData->GetColumnName( 1 ) , 1 );
pKMeansStatistics->SetColumnStatus( inputData->GetColumnName( 2 ) , 1 );
pKMeansStatistics->RequestSelectedColumns();
pKMeansStatistics->SetAssessOption( true );
pKMeansStatistics->SetDefaultNumberOfClusters( 2 );
pKMeansStatistics->Update() ;
// Display the results
pKMeansStatistics->GetOutput()->Dump();
vtkSmartPointer<vtkIntArray> clusterArray = vtkSmartPointer<vtkIntArray>::New();
clusterArray->SetNumberOfComponents(1);
clusterArray->SetName( "ClusterId" );
for(unsigned int r = 0; r < pKMeansStatistics->GetOutput()->GetNumberOfRows(); r++)
{
vtkVariant v = pKMeansStatistics->GetOutput()->GetValue(r, pKMeansStatistics->GetOutput()->GetNumberOfColumns() - 1);
std::cout << "Point " << r << " is in cluster " << v.ToInt() << std::endl;
clusterArray->InsertNextValue(v.ToInt());
}
vtkSmartPointer<vtkPolyData> polydata = vtkSmartPointer<vtkPolyData>::New();
polydata->SetPoints(points);
polydata->GetPointData()->SetScalars(clusterArray);
// Output the cluster centers
vtkMultiBlockDataSet* outputMetaDS = dynamic_cast<vtkMultiBlockDataSet*>( pKMeansStatistics->GetOutputDataObject( vtkStatisticsAlgorithm::OUTPUT_MODEL ) );
vtkSmartPointer<vtkTable> outputMeta = dynamic_cast<vtkTable*>( outputMetaDS->GetBlock( 0 ) );
//vtkSmartPointer<vtkTable> outputMeta = dynamic_cast<vtkTable*>( outputMetaDS->GetBlock( 1 ) );
vtkDoubleArray* coord0 = dynamic_cast<vtkDoubleArray*>(outputMeta->GetColumnByName("coord 0"));
vtkDoubleArray* coord1 = dynamic_cast<vtkDoubleArray*>(outputMeta->GetColumnByName("coord 1"));
vtkDoubleArray* coord2 = dynamic_cast<vtkDoubleArray*>(outputMeta->GetColumnByName("coord 2"));
for(unsigned int i = 0; i < coord0->GetNumberOfTuples(); ++i)
{
std::cout << coord0->GetValue(i) << " " << coord1->GetValue(i) << " " << coord2->GetValue(i) << std::endl;
}
return EXIT_SUCCESS;
}
CMakeLists.txt¶
cmake_minimum_required(VERSION 3.3 FATAL_ERROR)
project(PKMeansClustering)
find_package(VTK COMPONENTS
vtkvtkCommonCore
vtkvtkCommonDataModel
vtkvtkFiltersGeneral
vtkvtkFiltersParallelStatistics
vtkvtkIOXML
vtkvtkInteractionStyle
vtkvtkRenderingContextOpenGL2
vtkvtkRenderingCore
vtkvtkRenderingFreeType
vtkvtkRenderingGL2PSOpenGL2
vtkvtkRenderingOpenGL2 QUIET)
if (NOT VTK_FOUND)
message("Skipping PKMeansClustering: ${VTK_NOT_FOUND_MESSAGE}")
return ()
endif()
message (STATUS "VTK_VERSION: ${VTK_VERSION}")
if (VTK_VERSION VERSION_LESS "8.90.0")
# old system
include(${VTK_USE_FILE})
add_executable(PKMeansClustering MACOSX_BUNDLE PKMeansClustering.cxx )
target_link_libraries(PKMeansClustering PRIVATE ${VTK_LIBRARIES})
else ()
# include all components
add_executable(PKMeansClustering MACOSX_BUNDLE PKMeansClustering.cxx )
target_link_libraries(PKMeansClustering PRIVATE ${VTK_LIBRARIES})
# vtk_module_autoinit is needed
vtk_module_autoinit(
TARGETS PKMeansClustering
MODULES ${VTK_LIBRARIES}
)
endif ()
Download and Build PKMeansClustering¶
Click here to download PKMeansClustering and its CMakeLists.txt file. Once the tarball PKMeansClustering.tar has been downloaded and extracted,
cd PKMeansClustering/build
If VTK is installed:
cmake ..
If VTK is not installed but compiled on your system, you will need to specify the path to your VTK build:
cmake -DVTK_DIR:PATH=/home/me/vtk_build ..
Build the project:
make
and run it:
./PKMeansClustering
WINDOWS USERS
Be sure to add the VTK bin directory to your path. This will resolve the VTK dll's at run time.