Logo ROOT  
Reference Guide
testUnfold7a.C File Reference

Detailed Description

View in nbviewer Open in SWAN Test program for the classes TUnfoldDensity and TUnfoldBinning.

A toy test of the TUnfold package

This example is documented in conference proceedings:

arXiv:1611.01927 12th Conference on Quark Confinement and the Hadron Spectrum (Confinement XII)

This is an example of unfolding a two-dimensional distribution also using an auxiliary measurement to constrain some background

The example comprises several macros

  • testUnfold7a.C create root files with TTree objects for signal, background and data
    • write files testUnfold7_signal.root testUnfold7_background.root testUnfold7_data.root
  • testUnfold7b.C loop over trees and fill histograms based on the TUnfoldBinning objects
    • read testUnfold7binning.xml testUnfold7_signal.root testUnfold7_background.root testUnfold7_data.root
    • write testUnfold7_histograms.root
  • testUnfold7c.C run the unfolding
    • read testUnfold7_histograms.root
    • write testUnfold7_result.root testUnfold7_result.ps
fill data tree
data event 0
fill signal tree
signal event 0
signal event 100000
signal event 200000
fill background tree
background event 0
#include <iostream>
#include <map>
#include <cmath>
#include <TMath.h>
#include <TRandom3.h>
#include <TFile.h>
#include <TTree.h>
#include <TLorentzVector.h>
#define MASS1 0.511E-3
using namespace std;
TRandom *g_rnd=0;
class ToyEvent7 {
public:
void GenerateDataEvent(TRandom *rnd);
void GenerateSignalEvent(TRandom *rnd);
void GenerateBgrEvent(TRandom *rnd);
// reconstructed quantities
inline Double_t GetMRec(int i) const { return fMRec[i]; }
inline Double_t GetPtRec(int i) const { return fPtRec[i]; }
inline Double_t GetEtaRec(int i) const { return fEtaRec[i]; }
inline Double_t GetDiscriminator(void) const {return fDiscriminator; }
inline Double_t GetPhiRec(int i) const { return fPhiRec[i]; }
inline Bool_t IsTriggered(void) const { return fIsTriggered; }
// generator level quantities
inline Double_t GetMGen(int i) const {
if(IsSignal()) return fMGen[i];
else return -1.0;
}
inline Double_t GetPtGen(int i) const {
if(IsSignal()) return fPtGen[i];
else return -1.0;
}
inline Double_t GetEtaGen(int i) const {
if(IsSignal()) return fEtaGen[i];
else return 999.0;
}
inline Double_t GetPhiGen(int i) const {
if(IsSignal()) return fPhiGen[i];
else return 999.0;
}
inline Bool_t IsSignal(void) const { return fIsSignal; }
protected:
void GenerateSignalKinematics(TRandom *rnd,Bool_t isData);
void GenerateBgrKinematics(TRandom *rnd,Bool_t isData);
void GenerateReco(TRandom *rnd);
// reconstructed quantities
Double_t fMRec[3];
Double_t fPtRec[3];
Double_t fEtaRec[3];
Double_t fPhiRec[3];
Double_t fDiscriminator;
Bool_t fIsTriggered;
// generated quantities
Double_t fMGen[3];
Double_t fPtGen[3];
Double_t fEtaGen[3];
Double_t fPhiGen[3];
Bool_t fIsSignal;
public:
static Double_t kDataSignalFraction;
static Double_t kMCSignalFraction;
};
void testUnfold7a()
{
// random generator
g_rnd=new TRandom3(4711);
// data and MC number of events
Double_t muData0=5000.;
// luminosity error
Double_t muData=muData0*g_rnd->Gaus(1.0,0.03);
// stat error
Int_t neventData = g_rnd->Poisson( muData);
// generated number of MC events
Int_t neventSigmc = 250000;
Int_t neventBgrmc = 100000;
Float_t etaRec[3],ptRec[3],phiRec[3],mRec[3],discr;
Float_t etaGen[3],ptGen[3],phiGen[3],mGen[3];
Float_t weight;
Int_t istriggered,issignal;
//==================================================================
// Step 1: generate data TTree
TFile *dataFile=new TFile("testUnfold7_data.root","recreate");
TTree *dataTree=new TTree("data","event");
dataTree->Branch("etarec",etaRec,"etarec[3]/F");
dataTree->Branch("ptrec",ptRec,"ptrec[3]/F");
dataTree->Branch("phirec",phiRec,"phirec[3]/F");
dataTree->Branch("mrec",mRec,"mrec[3]/F");
dataTree->Branch("discr",&discr,"discr/F");
// for real data, only the triggered events are available
dataTree->Branch("istriggered",&istriggered,"istriggered/I");
// data truth parameters
dataTree->Branch("etagen",etaGen,"etagen[3]/F");
dataTree->Branch("ptgen",ptGen,"ptgen[3]/F");
dataTree->Branch("phigen",phiGen,"phigen[3]/F");
dataTree->Branch("mgen",mGen,"mgen[3]/F");
dataTree->Branch("issignal",&issignal,"issignal/I");
cout<<"fill data tree\n";
//Int_t nEvent=0,nTriggered=0;
for(int ievent=0;ievent<neventData;ievent++) {
ToyEvent7 event;
event.GenerateDataEvent(g_rnd);
for(int i=0;i<3;i++) {
etaRec[i]=event.GetEtaRec(i);
ptRec[i]=event.GetPtRec(i);
phiRec[i]=event.GetPhiRec(i);
mRec[i]=event.GetMRec(i);
etaGen[i]=event.GetEtaGen(i);
ptGen[i]=event.GetPtGen(i);
phiGen[i]=event.GetPhiGen(i);
mGen[i]=event.GetMGen(i);
}
discr=event.GetDiscriminator();
istriggered=event.IsTriggered() ? 1 : 0;
issignal=event.IsSignal() ? 1 : 0;
dataTree->Fill();
if(!(ievent%100000)) cout<<" data event "<<ievent<<"\n";
//if(istriggered) nTriggered++;
//nEvent++;
}
dataTree->Write();
delete dataTree;
delete dataFile;
//==================================================================
// Step 2: generate signal TTree
TFile *signalFile=new TFile("testUnfold7_signal.root","recreate");
TTree *signalTree=new TTree("signal","event");
signalTree->Branch("etarec",etaRec,"etarec[3]/F");
signalTree->Branch("ptrec",ptRec,"ptrec[3]/F");
signalTree->Branch("phirec",ptRec,"phirec[3]/F");
signalTree->Branch("mrec",mRec,"mrec[3]/F");
signalTree->Branch("discr",&discr,"discr/F");
// for real data, only the triggered events are available
signalTree->Branch("istriggered",&istriggered,"istriggered/I");
// data truth parameters
signalTree->Branch("etagen",etaGen,"etagen[3]/F");
signalTree->Branch("ptgen",ptGen,"ptgen[3]/F");
signalTree->Branch("phigen",phiGen,"phigen[3]/F");
signalTree->Branch("weight",&weight,"weight/F");
signalTree->Branch("mgen",mGen,"mgen[3]/F");
cout<<"fill signal tree\n";
weight=ToyEvent7::kMCSignalFraction*muData0/neventSigmc;
for(int ievent=0;ievent<neventSigmc;ievent++) {
ToyEvent7 event;
event.GenerateSignalEvent(g_rnd);
for(int i=0;i<3;i++) {
etaRec[i]=event.GetEtaRec(i);
ptRec[i]=event.GetPtRec(i);
phiRec[i]=event.GetPhiRec(i);
mRec[i]=event.GetMRec(i);
etaGen[i]=event.GetEtaGen(i);
ptGen[i]=event.GetPtGen(i);
phiGen[i]=event.GetPhiGen(i);
mGen[i]=event.GetMGen(i);
}
discr=event.GetDiscriminator();
istriggered=event.IsTriggered() ? 1 : 0;
if(!(ievent%100000)) cout<<" signal event "<<ievent<<"\n";
signalTree->Fill();
}
signalTree->Write();
delete signalTree;
delete signalFile;
// ==============================================================
// Step 3: generate background MC TTree
TFile *bgrFile=new TFile("testUnfold7_background.root","recreate");
TTree *bgrTree=new TTree("background","event");
bgrTree->Branch("etarec",&etaRec,"etarec[3]/F");
bgrTree->Branch("ptrec",&ptRec,"ptrec[3]/F");
bgrTree->Branch("phirec",&phiRec,"phirec[3]/F");
bgrTree->Branch("mrec",&mRec,"mrec[3]/F");
bgrTree->Branch("discr",&discr,"discr/F");
bgrTree->Branch("istriggered",&istriggered,"istriggered/I");
bgrTree->Branch("weight",&weight,"weight/F");
cout<<"fill background tree\n";
weight=(1.-ToyEvent7::kMCSignalFraction)*muData0/neventBgrmc;
for(int ievent=0;ievent<neventBgrmc;ievent++) {
ToyEvent7 event;
event.GenerateBgrEvent(g_rnd);
for(int i=0;i<3;i++) {
etaRec[i]=event.GetEtaRec(i);
ptRec[i]=event.GetPtRec(i);
phiRec[i]=event.GetPhiRec(i);
}
discr=event.GetDiscriminator();
istriggered=event.IsTriggered() ? 1 : 0;
if(!(ievent%100000)) cout<<" background event "<<ievent<<"\n";
bgrTree->Fill();
}
bgrTree->Write();
delete bgrTree;
delete bgrFile;
}
Double_t ToyEvent7::kDataSignalFraction=0.75;
Double_t ToyEvent7::kMCSignalFraction=0.75;
void ToyEvent7::GenerateDataEvent(TRandom *rnd) {
fIsSignal=rnd->Uniform()<kDataSignalFraction;
if(IsSignal()) {
GenerateSignalKinematics(rnd,kTRUE);
} else {
GenerateBgrKinematics(rnd,kTRUE);
}
GenerateReco(rnd);
}
void ToyEvent7::GenerateSignalEvent(TRandom *rnd) {
fIsSignal=1;
GenerateSignalKinematics(rnd,kFALSE);
GenerateReco(rnd);
}
void ToyEvent7::GenerateBgrEvent(TRandom *rnd) {
fIsSignal=0;
GenerateBgrKinematics(rnd,kFALSE);
GenerateReco(rnd);
}
void ToyEvent7::GenerateSignalKinematics(TRandom *rnd,Bool_t isData) {
// fake decay of Z0 to two fermions
double M0=91.1876;
double Gamma=2.4952;
// generated mass
do {
fMGen[2]=rnd->BreitWigner(M0,Gamma);
} while(fMGen[2]<=0.0);
double N_ETA=3.0;
double MU_PT=5.;
double SIGMA_PT=2.0;
double DECAY_A=0.2;
if(isData) {
//N_ETA=2.5;
MU_PT=6.;
SIGMA_PT=1.8;
//DECAY_A=0.5;
}
fEtaGen[2]=TMath::Power(rnd->Uniform(0,1.5),N_ETA);
if(rnd->Uniform(-1.,1.)<0.) fEtaGen[2] *= -1.;
fPhiGen[2]=rnd->Uniform(-M_PI,M_PI);
do {
fPtGen[2]=rnd->Landau(MU_PT,SIGMA_PT);
} while((fPtGen[2]<=0.0)||(fPtGen[2]>500.));
//========================== decay
sum.SetPtEtaPhiM(fPtGen[2],fEtaGen[2],fPhiGen[2],fMGen[2]);
// boost into lab-frame
TVector3 boost=sum.BoostVector();
// decay in rest-frame
double m=MASS1;
double costh;
do {
double r=rnd->Uniform(-1.,1.);
costh=r*(1.+DECAY_A*r*r);
} while(fabs(costh)>=1.0);
double phi=rnd->Uniform(-M_PI,M_PI);
double e=0.5*sum.M();
double ptot=TMath::Sqrt(e+m)*TMath::Sqrt(e-m);
double pz=ptot*costh;
double pt=TMath::Sqrt(ptot+pz)*TMath::Sqrt(ptot-pz);
double px=pt*cos(phi);
double py=pt*sin(phi);
p[0].SetXYZT(px,py,pz,e);
p[1].SetXYZT(-px,-py,-pz,e);
for(int i=0;i<2;i++) {
p[i].Boost(boost);
}
p[2]=p[0]+p[1];
for(int i=0;i<3;i++) {
fPtGen[i]=p[i].Pt();
fEtaGen[i]=p[i].Eta();
fPhiGen[i]=p[i].Phi();
fMGen[i]=p[i].M();
}
}
void ToyEvent7::GenerateBgrKinematics(TRandom *rnd,Bool_t isData) {
for(int i=0;i<3;i++) {
fPtGen[i]=0.0;
fEtaGen[i]=0.0;
fPhiGen[i]=0.0;
}
for(int i=0;i<2;i++) {
p[i].SetPtEtaPhiM(rnd->Exp(15.0),rnd->Uniform(-3.,3.),
rnd->Uniform(-M_PI,M_PI),isData ? MASS1 : MASS1);
}
p[2]=p[0]+p[1];
for(int i=0;i<3;i++) {
fPtRec[i]=p[i].Pt();
fEtaRec[i]=p[i].Eta();
fPhiRec[i]=p[i].Phi();
fMRec[i]=p[i].M();
}
}
void ToyEvent7::GenerateReco(TRandom *rnd) {
if(fIsSignal) {
for(int i=0;i<2;i++) {
Double_t expEta=TMath::Exp(fEtaGen[i]);
Double_t coshEta=(expEta+1./expEta);
Double_t eGen=fPtGen[i]*coshEta;
Double_t sigmaE=
0.1*TMath::Sqrt(eGen)
+1.0*coshEta
+0.01*eGen;
Double_t eRec;
do {
eRec=rnd->Gaus(eGen,sigmaE);
} while(eRec<=0.0);
Double_t sigmaEta=0.1+0.02*TMath::Abs(fEtaGen[i]);
p[i].SetPtEtaPhiM(eRec/(expEta+1./expEta),
rnd->Gaus(fEtaGen[i],sigmaEta),
remainder(rnd->Gaus(fPhiGen[i],0.03),2.*M_PI),
MASS1);
}
p[2]=p[0]+p[1];
for(int i=0;i<3;i++) {
fPtRec[i]=p[i].Pt();
fEtaRec[i]=p[i].Eta();
fPhiRec[i]=p[i].Phi();
fMRec[i]=p[i].M();
}
}
if(fIsSignal) {
do {
Double_t tauDiscr=0.08-0.04/(1.+fPtRec[2]/10.0);
Double_t sigmaDiscr=0.01;
fDiscriminator=1.0-rnd->Exp(tauDiscr)+rnd->Gaus(0.,sigmaDiscr);
} while((fDiscriminator<=0.)||(fDiscriminator>=1.));
} else {
do {
Double_t tauDiscr=0.15-0.05/(1.+fPtRec[2]/5.0)+0.1*fEtaRec[2];
Double_t sigmaDiscr=0.02+0.01*fEtaRec[2];
fDiscriminator=rnd->Exp(tauDiscr)+rnd->Gaus(0.,sigmaDiscr);
} while((fDiscriminator<=0.)||(fDiscriminator>=1.));
}
fIsTriggered=false;
for(int i=0;i<2;i++) {
if(rnd->Uniform()<0.92/(TMath::Exp(-(fPtRec[i]-15.5)/2.5)+1.)) fIsTriggered=true;
}
}
ROOT::R::TRInterface & r
Definition: Object.C:4
#define e(i)
Definition: RSha256.hxx:103
#define M_PI
Definition: Rotated.cxx:105
int Int_t
Definition: RtypesCore.h:43
const Bool_t kFALSE
Definition: RtypesCore.h:90
bool Bool_t
Definition: RtypesCore.h:61
double Double_t
Definition: RtypesCore.h:57
float Float_t
Definition: RtypesCore.h:55
const Bool_t kTRUE
Definition: RtypesCore.h:89
double cos(double)
double sin(double)
A ROOT file is a suite of consecutive data records (TKey instances) with a well defined format.
Definition: TFile.h:53
void SetXYZT(Double_t x, Double_t y, Double_t z, Double_t t)
Double_t Pt() const
void SetPtEtaPhiM(Double_t pt, Double_t eta, Double_t phi, Double_t m)
void Boost(Double_t, Double_t, Double_t)
Random number generator class based on M.
Definition: TRandom3.h:27
This is the base class for the ROOT Random number generators.
Definition: TRandom.h:27
virtual Double_t Gaus(Double_t mean=0, Double_t sigma=1)
Samples a random number from the standard Normal (Gaussian) Distribution with the given mean and sigm...
Definition: TRandom.cxx:263
virtual Int_t Poisson(Double_t mean)
Generates a random integer N according to a Poisson law.
Definition: TRandom.cxx:391
virtual Double_t Exp(Double_t tau)
Returns an exponential deviate.
Definition: TRandom.cxx:240
virtual Double_t Uniform(Double_t x1=1)
Returns a uniform deviate on the interval (0, x1).
Definition: TRandom.cxx:635
virtual Double_t Landau(Double_t mean=0, Double_t sigma=1)
Generate a random number following a Landau distribution with location parameter mu and scale paramet...
Definition: TRandom.cxx:369
virtual Double_t BreitWigner(Double_t mean=0, Double_t gamma=1)
Return a number distributed following a BreitWigner function with mean and gamma.
Definition: TRandom.cxx:214
A TTree represents a columnar dataset.
Definition: TTree.h:78
virtual Int_t Fill()
Fill all branches.
Definition: TTree.cxx:4524
TBranch * Branch(const char *name, T *obj, Int_t bufsize=32000, Int_t splitlevel=99)
Add a new branch, and infer the data type from the type of obj being passed.
Definition: TTree.h:348
virtual Int_t Write(const char *name=0, Int_t option=0, Int_t bufsize=0)
Write this object to the current directory.
Definition: TTree.cxx:9595
TVector3 is a general three vector class, which can be used for the description of different vectors ...
Definition: TVector3.h:22
TPaveText * pt
LVector boost(const LVector &v, const BoostVector &b)
Boost a generic Lorentz Vector class using a generic 3D Vector class describing the boost The only re...
Definition: VectorUtil.h:327
VecExpr< UnaryOp< Fabs< T >, VecExpr< A, T, D >, T >, T, D > fabs(const VecExpr< A, T, D > &rhs)
Double_t Exp(Double_t x)
Definition: TMath.h:717
Double_t Sqrt(Double_t x)
Definition: TMath.h:681
LongDouble_t Power(LongDouble_t x, LongDouble_t y)
Definition: TMath.h:725
Double_t Gamma(Double_t z)
Computation of gamma(z) for all z.
Definition: TMath.cxx:348
Short_t Abs(Short_t d)
Definition: TMathBase.h:120
auto * m
Definition: textangle.C:8
static long int sum(long int i)
Definition: Factory.cxx:2275

Version 17.6, in parallel to changes in TUnfold

This file is part of TUnfold.

TUnfold is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

TUnfold is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with TUnfold. If not, see http://www.gnu.org/licenses/.

Author
Stefan Schmitt DESY, 14.10.2008

Definition in file testUnfold7a.C.