Nanga Parbat 1.1.0
A TMD fitting framework
Trainingcut.h
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1//
2// Authors: Valerio Bertone: valerio.bertone@cern.ch
3//
4
5#pragma once
6
7#include "NangaParbat/cut.h"
8#include <algorithm>
9
10namespace NangaParbat
11{
16 class TrainingCut: public Cut
17 {
18 public:
27 TrainingCut(DataHandler const& dataset,
28 std::vector<std::shared_ptr<NangaParbat::Cut>> const& kincuts,
29 double const& TrainingFrac,
30 gsl_rng* rng,
31 int const& NMin = 10);
32
39 TrainingCut(TrainingCut const& cut, bool const& invert = false, std::vector<std::shared_ptr<NangaParbat::Cut>> const& kincuts = {});
40
45 void EnforceCut();
46 private:
47 gsl_rng* const _rng;
48 int const _NMin;
49 };
50}
Purely virtual mother class that implements the main feautures of a cut function on a given dataset....
Definition: cut.h:20
The "DataHandler" class provides a common interface to all datasets. It provides methods to get kinem...
Definition: datahandler.h:23
Derivation of the class Cut to impose Cross Validation cut.
Definition: Trainingcut.h:17
int const _NMin
Definition: Trainingcut.h:48
TrainingCut(DataHandler const &dataset, std::vector< std::shared_ptr< NangaParbat::Cut > > const &kincuts, double const &TrainingFrac, gsl_rng *rng, int const &NMin=10)
The "Trainingcut" constructor.
void EnforceCut()
Purely virtual function to be used implemented in the derived class to eforce the cut.
gsl_rng *const _rng
Definition: Trainingcut.h:47
TrainingCut(TrainingCut const &cut, bool const &invert=false, std::vector< std::shared_ptr< NangaParbat::Cut > > const &kincuts={})
The "TrainingCut" copy constructor.
Definition: bstar.h:12