PKMeansClustering

// This example needs someone to fugure out how to use vtkPKMeansStatistics.

#include <vtkDoubleArray.h>
#include <vtkIntArray.h>
#include <vtkKMeansStatistics.h>
#include <vtkMultiBlockDataSet.h>
#include <vtkNew.h>
#include <vtkPKMeansStatistics.h>
#include <vtkPointData.h>
#include <vtkPoints.h>
#include <vtkPolyData.h>
#include <vtkProperty.h>
#include <vtkStatisticalModel.h>
#include <vtkStatisticsAlgorithm.h>
#include <vtkTable.h>
#include <vtkXMLPolyDataWriter.h>

// display
#include <vtkActor.h>
#include <vtkInteractorStyleTrackballCamera.h>
#include <vtkPolyDataMapper.h>
#include <vtkRenderWindow.h>
#include <vtkRenderWindowInteractor.h>
#include <vtkRenderer.h>
#include <vtkVertexGlyphFilter.h>

#include <sstream>

int main(int, char*[])
{
  // create 2 clusters, one near (0,0,0) and the other near (3,3,3)
  vtkNew<vtkPoints> points;

  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
  vtkNew<vtkTable> inputData;

  for (int c = 0; c < 3; ++c)
  {
    std::stringstream colName;
    colName << "coord " << c;
    vtkNew<vtkDoubleArray> doubleArray;
    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);
  }

  // vtkNew<vtkPKMeansStatistics> pKMeansStatistics;
  vtkNew<vtkKMeansStatistics> pKMeansStatistics;
  // 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();

  vtkNew<vtkIntArray> clusterArray;
  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());
  }

  vtkNew<vtkPolyData> polydata;
  polydata->SetPoints(points);
  polydata->GetPointData()->SetScalars(clusterArray);

  // Output the cluster centers.
  auto outputMetaDS =
      vtkStatisticalModel::SafeDownCast(pKMeansStatistics->GetOutputDataObject(
          vtkStatisticsAlgorithm::OUTPUT_MODEL));
  if (outputMetaDS != nullptr)
  {
    auto outputMeta = outputMetaDS->GetTable(vtkStatisticalModel::Learned, 0);
    auto coord0 =
        dynamic_cast<vtkDoubleArray*>(outputMeta->GetColumnByName("coord 0"));
    auto coord1 =
        dynamic_cast<vtkDoubleArray*>(outputMeta->GetColumnByName("coord 1"));
    auto coord2 =
        dynamic_cast<vtkDoubleArray*>(outputMeta->GetColumnByName("coord 2"));
    std::cout << "Cluster centers:" << std::endl;
    for (unsigned int i = 0; i < coord0->GetNumberOfTuples(); ++i)
    {
      std::cout << "Cluster " << i << ": " << coord0->GetValue(i) << " "
                << coord1->GetValue(i) << " " << coord2->GetValue(i) << ")"
                << std::endl;
    }
  }
  else
  {
    std::cout << "Cluster centers not found." << std::endl;
  }

  return EXIT_SUCCESS;
}

cmake_minimum_required(VERSION 3.12 FATAL_ERROR)

project(PKMeansClustering)

find_package(VTK COMPONENTS 
  CommonCore
  CommonDataModel
  FiltersGeneral
  FiltersParallelStatistics
  IOXML
  InteractionStyle
  RenderingContextOpenGL2
  RenderingCore
  RenderingFreeType
  RenderingGL2PSOpenGL2
  RenderingOpenGL2
)

if (NOT VTK_FOUND)
  message(FATAL_ERROR "PKMeansClustering: Unable to find the VTK build folder.")
endif()

# Prevent a "command line is too long" failure in Windows.
set(CMAKE_NINJA_FORCE_RESPONSE_FILE "ON" CACHE BOOL "Force Ninja to use response files.")
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}
)

cd PKMeansClustering/build

cmake ..

cmake -DVTK_DIR:PATH=/home/me/vtk_build ..

make

./PKMeansClustering