GBRForest2D.h

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#ifndef EGAMMAOBJECTS_GBRForest2D
#define EGAMMAOBJECTS_GBRForest2D
 
//                                                                      //
// GBRForest2D                                                            //
//                                                                      //
// A fast minimal implementation of Gradient-Boosted Regression Trees   //
// which has been especially optimized for size on disk and in memory.  //
//                                                                      //
// Designed to be built from TMVA-trained trees, but could also be      //
// generalized to otherwise-trained trees, classification,              //
//  or other boosting methods in the future                             //
//                                                                      //
//  Josh Bendavid - MIT                                                 //
 
#include "CondFormats/Serialization/interface/Serializable.h"
 
#include "GBRTree2D.h"
#include <cstdio>
#include <vector>
 
class GBRForest2D {
public:
  GBRForest2D();
  ~GBRForest2D() {}
 
  void GetResponse(const float *vector, double &x, double &y) const;
 
  void SetInitialResponse(double x, double y) {
    fInitialResponseX = x;
    fInitialResponseY = y;
  }
 
  std::vector<GBRTree2D> &Trees() { return fTrees; }
  const std::vector<GBRTree2D> &Trees() const { return fTrees; }
 
protected:
  double fInitialResponseX;
  double fInitialResponseY;
  std::vector<GBRTree2D> fTrees;
 
  COND_SERIALIZABLE;
};
 
//_______________________________________________________________________
inline void GBRForest2D::GetResponse(const float *vector, double &x, double &y) const {
  x = fInitialResponseX;
  y = fInitialResponseY;
  double tx, ty;
  for (std::vector<GBRTree2D>::const_iterator it = fTrees.begin(); it != fTrees.end(); ++it) {
    it->GetResponse(vector, tx, ty);
    x += tx;
    y += ty;
  }
  return;
}
 
#endif