mitkPURFClassifier.h

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/*============================================================================
 
The Medical Imaging Interaction Toolkit (MITK)
 
Copyright (c) German Cancer Research Center (DKFZ)
All rights reserved.
 
Use of this source code is governed by a 3-clause BSD license that can be
found in the LICENSE file.
 
============================================================================*/
 
#ifndef mitkPURFClassifier_h
#define mitkPURFClassifier_h
 
#include <MitkCLVigraRandomForestExports.h>
#include <mitkAbstractClassifier.h>
 
//#include <vigra/multi_array.hxx>
#include <vigra/random_forest.hxx>
 
#include <mitkBaseData.h>
 
namespace mitk
{
  class MITKCLVIGRARANDOMFOREST_EXPORT PURFClassifier : public AbstractClassifier
  {
  public:
 
    mitkClassMacro(PURFClassifier, AbstractClassifier);
 
    itkFactorylessNewMacro(Self);
 
    itkCloneMacro(Self);
 
      PURFClassifier();
 
    ~PURFClassifier() override;
 
    void Train(const Eigen::MatrixXd &X, const Eigen::MatrixXi &Y) override;
 
    Eigen::MatrixXi Predict(const Eigen::MatrixXd &X) override;
    Eigen::MatrixXi PredictWeighted(const Eigen::MatrixXd &X);
 
 
    bool SupportsPointWiseWeight() override;
    bool SupportsPointWiseProbability() override;
    void ConvertParameter();
    vigra::ArrayVector<double> CalculateKappa(const Eigen::MatrixXd & X_in, const Eigen::MatrixXi &Y_in);
 
    void SetRandomForest(const vigra::RandomForest<int> & rf);
    const vigra::RandomForest<int> & GetRandomForest() const;
 
    void UsePointWiseWeight(bool) override;
    void SetMaximumTreeDepth(int);
    void SetMinimumSplitNodeSize(int);
    void SetPrecision(double);
    void SetSamplesPerTree(double);
    void UseSampleWithReplacement(bool);
    void SetTreeCount(int);
    void SetWeightLambda(double);
 
    void PrintParameter(std::ostream &str = std::cout);
 
    void SetClassProbabilities(Eigen::VectorXd probabilities);
    Eigen::VectorXd GetClassProbabilites();
 
  private:
    // *-------------------
    // * THREADING
    // *-------------------
 
 
    struct TrainingData;
    struct PredictionData;
    struct EigenToVigraTransform;
    struct Parameter;
 
    vigra::MultiArrayView<2, double> m_Probabilities;
    Eigen::MatrixXd m_TreeWeights;
    Eigen::VectorXd m_ClassProbabilities;
 
    Parameter * m_Parameter;
    vigra::RandomForest<int> m_RandomForest;
 
    static itk::ITK_THREAD_RETURN_TYPE TrainTreesCallback(void *);
    static itk::ITK_THREAD_RETURN_TYPE PredictCallback(void *);
    static itk::ITK_THREAD_RETURN_TYPE PredictWeightedCallback(void *);
    static void VigraPredictWeighted(PredictionData *data, vigra::MultiArrayView<2, double> & X, vigra::MultiArrayView<2, int> & Y, vigra::MultiArrayView<2, double> & P);
  };
}
 
#endif