/usr/include/root/TEfficiency.h is in libroot-hist-dev 5.34.19+dfsg-1.2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 | #ifndef ROOT_TEfficiency
#define ROOT_TEfficiency
//standard header
#include <vector>
#include <utility>
//ROOT header
#ifndef ROOT_TNamed
#include "TNamed.h"
#endif
#ifndef ROOT_TAttLine
#include "TAttLine.h"
#endif
#ifndef ROOT_TAttFill
#include "TAttFill.h"
#endif
#ifndef ROOT_TAttMarker
#include "TAttMarker.h"
#endif
class TCollection;
class TF1;
class TGraphAsymmErrors;
class TH1;
class TH2;
class TList;
//|TEfficiency
//------------------------
class TEfficiency: public TNamed, public TAttLine, public TAttFill, public TAttMarker
{
public:
//enumaration type for different statistic options for calculating confidence intervals
//kF* ... frequentist methods; kB* ... bayesian methods
enum EStatOption {
kFCP = 0, //Clopper-Pearson interval (recommended by PDG)
kFNormal, //normal approximation
kFWilson, //Wilson interval
kFAC, //Agresti-Coull interval
kFFC, //Feldman-Cousins interval
kBJeffrey, //Jeffrey interval (Prior ~ Beta(0.5,0.5)
kBUniform, //Prior ~ Uniform = Beta(1,1)
kBBayesian //user specified Prior ~ Beta(fBeta_alpha,fBeta_beta)
};
protected:
Double_t fBeta_alpha; //global parameter for prior beta distribution (default = 1)
Double_t fBeta_beta; //global parameter for prior beta distribution (default = 1)
std::vector<std::pair<Double_t, Double_t> > fBeta_bin_params; // parameter for prior beta distribution different bin by bin
// (default vector is empty)
Double_t (*fBoundary)(Int_t,Int_t,Double_t,Bool_t); //!pointer to a method calculating the boundaries of confidence intervals
Double_t fConfLevel; //confidence level (default = 0.95)
TDirectory* fDirectory; //!pointer to directory holding this TEfficiency object
TList* fFunctions; //->pointer to list of functions
TGraphAsymmErrors* fPaintGraph; //!temporary graph for painting
TH2* fPaintHisto; //!temporary histogram for painting
TH1* fPassedHistogram; //histogram for events which passed certain criteria
EStatOption fStatisticOption; //defines how the confidence intervals are determined
TH1* fTotalHistogram; //histogram for total number of events
Double_t fWeight; //weight for all events (default = 1)
enum{
kIsBayesian = BIT(14), //bayesian statistics are used
kPosteriorMode = BIT(15), //use posterior mean for best estimate (Bayesian statistics)
kShortestInterval = BIT(16), // use shortest interval
kUseBinPrior = BIT(17), // use a different prior for each bin
kUseWeights = BIT(18) // use weights
};
void Build(const char* name,const char* title);
void FillGraph(TGraphAsymmErrors * graph, Option_t * opt) const;
void FillHistogram(TH2 * h2) const;
public:
TEfficiency();
TEfficiency(const TH1& passed,const TH1& total);
TEfficiency(const char* name,const char* title,Int_t nbins,
const Double_t* xbins);
TEfficiency(const char* name,const char* title,Int_t nbins,Double_t xlow,
Double_t xup);
TEfficiency(const char* name,const char* title,Int_t nbinsx,
Double_t xlow,Double_t xup,Int_t nbinsy,Double_t ylow,
Double_t yup);
TEfficiency(const char* name,const char* title,Int_t nbinsx,
const Double_t* xbins,Int_t nbinsy,const Double_t* ybins);
TEfficiency(const char* name,const char* title,Int_t nbinsx,
Double_t xlow,Double_t xup,Int_t nbinsy,Double_t ylow,
Double_t yup,Int_t nbinsz,Double_t zlow,Double_t zup);
TEfficiency(const char* name,const char* title,Int_t nbinsx,
const Double_t* xbins,Int_t nbinsy,const Double_t* ybins,
Int_t nbinsz,const Double_t* zbins);
TEfficiency(const TEfficiency& heff);
~TEfficiency();
void Add(const TEfficiency& rEff) {*this += rEff;}
TGraphAsymmErrors* CreateGraph(Option_t * opt = "") const;
TH2* CreateHistogram(Option_t * opt = "") const;
virtual Int_t DistancetoPrimitive(Int_t px, Int_t py);
void Draw(Option_t* opt = "");
virtual void ExecuteEvent(Int_t event, Int_t px, Int_t py);
void Fill(Bool_t bPassed,Double_t x,Double_t y=0,Double_t z=0);
void FillWeighted(Bool_t bPassed,Double_t weight,Double_t x,Double_t y=0,Double_t z=0);
Int_t FindFixBin(Double_t x,Double_t y=0,Double_t z=0) const;
Int_t Fit(TF1* f1,Option_t* opt="");
// use trick of -1 to return global parameters
Double_t GetBetaAlpha(Int_t bin = -1) const {return (fBeta_bin_params.size() > (UInt_t)bin) ? fBeta_bin_params[bin].first : fBeta_alpha;}
Double_t GetBetaBeta(Int_t bin = -1) const {return (fBeta_bin_params.size() > (UInt_t)bin) ? fBeta_bin_params[bin].second : fBeta_beta;}
Double_t GetConfidenceLevel() const {return fConfLevel;}
TH1* GetCopyPassedHisto() const;
TH1* GetCopyTotalHisto() const;
Int_t GetDimension() const;
TDirectory* GetDirectory() const {return fDirectory;}
Double_t GetEfficiency(Int_t bin) const;
Double_t GetEfficiencyErrorLow(Int_t bin) const;
Double_t GetEfficiencyErrorUp(Int_t bin) const;
Int_t GetGlobalBin(Int_t binx,Int_t biny=0,Int_t binz=0) const;
TGraphAsymmErrors* GetPaintedGraph() const { return fPaintGraph; }
TH2* GetPaintedHistogram() const { return fPaintHisto; }
TList* GetListOfFunctions();
const TH1* GetPassedHistogram() const {return fPassedHistogram;}
EStatOption GetStatisticOption() const {return fStatisticOption;}
const TH1* GetTotalHistogram() const {return fTotalHistogram;}
Double_t GetWeight() const {return fWeight;}
Long64_t Merge(TCollection* list);
TEfficiency& operator+=(const TEfficiency& rhs);
TEfficiency& operator=(const TEfficiency& rhs);
void Paint(Option_t* opt);
void SavePrimitive(ostream& out,Option_t* opt="");
void SetBetaAlpha(Double_t alpha);
void SetBetaBeta(Double_t beta);
void SetBetaBinParameters(Int_t bin, Double_t alpha, Double_t beta);
void SetConfidenceLevel(Double_t level);
void SetDirectory(TDirectory* dir);
void SetName(const char* name);
Bool_t SetPassedEvents(Int_t bin,Int_t events);
Bool_t SetPassedHistogram(const TH1& rPassed,Option_t* opt);
void SetPosteriorMode(Bool_t on = true) { SetBit(kPosteriorMode,on); SetShortestInterval(on); }
void SetPosteriorAverage(Bool_t on = true) { SetBit(kPosteriorMode,!on); }
void SetShortestInterval(Bool_t on = true) { SetBit(kShortestInterval,on); }
void SetCentralInterval(Bool_t on = true) { SetBit(kShortestInterval,!on); }
void SetStatisticOption(EStatOption option);
Bool_t SetBins(Int_t nx, Double_t xmin, Double_t xmax);
Bool_t SetBins(Int_t nx, const Double_t *xBins);
Bool_t SetBins(Int_t nx, Double_t xmin, Double_t xmax, Int_t ny, Double_t ymin, Double_t ymax);
Bool_t SetBins(Int_t nx, const Double_t *xBins, Int_t ny, const Double_t *yBins);
Bool_t SetBins(Int_t nx, Double_t xmin, Double_t xmax, Int_t ny, Double_t ymin, Double_t ymax,
Int_t nz, Double_t zmin, Double_t zmax);
Bool_t SetBins(Int_t nx, const Double_t *xBins, Int_t ny, const Double_t * yBins, Int_t nz,
const Double_t *zBins);
void SetTitle(const char* title);
Bool_t SetTotalEvents(Int_t bin,Int_t events);
Bool_t SetTotalHistogram(const TH1& rTotal,Option_t* opt);
void SetUseWeightedEvents();
void SetWeight(Double_t weight);
Bool_t UsesBayesianStat() const {return TestBit(kIsBayesian);}
Bool_t UsesPosteriorMode() const {return TestBit(kPosteriorMode) && TestBit(kIsBayesian);}
Bool_t UsesShortestInterval() const {return TestBit(kShortestInterval) && TestBit(kIsBayesian);}
Bool_t UsesPosteriorAverage() const {return !UsesPosteriorMode();}
Bool_t UsesCentralInterval() const {return !UsesShortestInterval();}
Bool_t UsesWeights() const {return TestBit(kUseWeights);}
static Bool_t CheckBinning(const TH1& pass,const TH1& total);
static Bool_t CheckConsistency(const TH1& pass,const TH1& total,Option_t* opt="");
static Bool_t CheckEntries(const TH1& pass,const TH1& total,Option_t* opt="");
static Double_t Combine(Double_t& up,Double_t& low,Int_t n,const Int_t* pass,const Int_t* total,
Double_t alpha,Double_t beta,Double_t level=0.683,
const Double_t* w=0,Option_t* opt="");
static TGraphAsymmErrors* Combine(TCollection* pList,Option_t* opt="",Int_t n=0,const Double_t* w=0);
//calculating boundaries of confidence intervals
static Double_t AgrestiCoull(Int_t total,Int_t passed,Double_t level,Bool_t bUpper);
static Double_t ClopperPearson(Int_t total,Int_t passed,Double_t level,Bool_t bUpper);
static Double_t Normal(Int_t total,Int_t passed,Double_t level,Bool_t bUpper);
static Double_t Wilson(Int_t total,Int_t passed,Double_t level,Bool_t bUpper);
static Double_t FeldmanCousins(Int_t total,Int_t passed,Double_t level,Bool_t bUpper);
static Bool_t FeldmanCousinsInterval(Int_t total,Int_t passed,Double_t level,Double_t & lower, Double_t & upper);
// Bayesian functions
static Double_t Bayesian(Int_t total,Int_t passed,Double_t level,Double_t alpha,Double_t beta,Bool_t bUpper, Bool_t bShortest = false);
// helper functions for Bayesian statistics
static Double_t BetaCentralInterval(Double_t level,Double_t alpha,Double_t beta,Bool_t bUpper);
static Bool_t BetaShortestInterval(Double_t level,Double_t alpha,Double_t beta,Double_t & lower, Double_t & upper);
static Double_t BetaMean(Double_t alpha,Double_t beta);
static Double_t BetaMode(Double_t alpha,Double_t beta);
ClassDef(TEfficiency,2) //calculating efficiencies
};
const TEfficiency operator+(const TEfficiency& lhs,const TEfficiency& rhs);
#endif
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