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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 <vector>
class GBRForest2D {
public:
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 = 0.0;
double fInitialResponseY = 0.0;
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
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