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testUnfold5b.C File Reference

Detailed Description

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Test program for the classes TUnfoldDensity and TUnfoldBinning.

A toy test of the TUnfold package

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

The example comprises several macros

  • testUnfold5a.C create root files with TTree objects for signal, background and data
    • write files testUnfold5_signal.root testUnfold5_background.root testUnfold5_data.root
  • testUnfold5b.C create a root file with the TUnfoldBinning objects
    • write file testUnfold5_binning.root
  • testUnfold5c.C loop over trees and fill histograms based on the TUnfoldBinning objects
    • read testUnfold5_binning.root testUnfold5_signal.root testUnfold5_background.root testUnfold5_data.root
    • write testUnfold5_histograms.root
  • testUnfold5d.C run the unfolding
    • read testUnfold5_histograms.root
    • write testUnfold5_result.root testUnfold5_result.ps
TUnfoldBinning "generator" has 115 bins [1,116] nTH1x=115
TUnfoldBinning "signal" has 25 bins [1,26] nTH1x=25
distribution: 25 bins
"ptgen" nbin=3 plus underflow plus overflow
"etagen" nbin=3 plus underflow plus overflow
TUnfoldBinning "background" has 90 bins [26,116] nTH1x=90
distribution: 90 bins
"ptrec" nbin=8 plus overflow
"etarec" nbin=10
#include <iostream>
#include <fstream>
#include <TFile.h>
#include <TF2.h>
using std::ofstream;
{
// write binning schemes to root file
TFile *binningSchemes=new TFile("testUnfold5_binning.root","recreate");
// reconstructed pt, eta, discriminator
#define NBIN_PT_FINE 8
#define NBIN_ETA_FINE 10
#define NBIN_DISCR 4
// generated pt, eta
#define NBIN_PT_COARSE 3
#define NBIN_ETA_COARSE 3
// pt binning
{3.5,4.0,4.5,5.0,6.0,7.0,8.0,10.0,13.0};
{ 4.0, 5.0, 7.0, 10.0};
// eta binning
{-3.,-2.5,-2.0,-1.,-0.5,0.0,0.5,1.,2.,2.5,3.};
{ -2.0, -0.5, 0.5, 2. };
// discriminator bins
Double_t discrBins[NBIN_DISCR+1]={0.,0.15,0.5,0.85,1.0};
//=======================================================================
// detector level binning scheme
// highest discriminator bin has fine binning
detectorBinning->AddBinning("detectordistribution");
false, // no underflow bin (not reconstructed)
true // overflow bin
);
false, // no underflow bin (not reconstructed)
false // no overflow bin (not reconstructed)
);
detectorDistribution->AddAxis("discriminator",NBIN_DISCR,discrBins,
false, // no underflow bin (empty)
false // no overflow bin (empty)
);
/* TUnfoldBinning *detectorExtra=
detectorBinning->AddBinning("detectorextra",7,"one;zwei;three");
detectorBinning->PrintStream(cout); */
//=======================================================================
// generator level binning
// signal distribution is measured with coarse binning
// underflow and overflow bins are needed ot take care of
// what happens outside the phase-space
TUnfoldBinning *signalBinning = generatorBinning->AddBinning("signal");
true, // underflow bin
true // overflow bin
);
true, // underflow bin
true // overflow bin
);
// this is just an example how to set bin-dependent factors
// for the regularisation
TF2 *userFunc=new TF2("userfunc","1./x+0.2*y^2",ptBinsCoarse[0],
signalBinning->SetBinFactorFunction(1.0,userFunc);
// background distribution is unfolded with fine binning
// !!! in the reconstructed variable !!!
//
// This has the effect of "normalizing" the background in each
// pt,eta bin to the low discriminator values
// Only the shape of the discriminator in each (pt,eta) bin
// is taken from Monte Carlo
//
// This method has been applied e.g. in
// H1 Collaboration, "Prompt photons in Photoproduction"
// Eur.Phys.J. C66 (2010) 17
//
TUnfoldBinning *bgrBinning = generatorBinning->AddBinning("background");
false, // no underflow bin (not reconstructed)
true // overflow bin
);
false, // no underflow bin (not reconstructed)
false // no overflow bin (not reconstructed)
);
generatorBinning->PrintStream(cout);
detectorBinning->Write();
generatorBinning->Write();
ofstream xmlOut("testUnfold5binning.xml");
xmlOut.close();
}
constexpr Bool_t kFALSE
Definition RtypesCore.h:94
double Double_t
Definition RtypesCore.h:59
constexpr Bool_t kTRUE
Definition RtypesCore.h:93
ROOT::Detail::TRangeCast< T, true > TRangeDynCast
TRangeDynCast is an adapter class that allows the typed iteration through a TCollection.
A 2-Dim function with parameters.
Definition TF2.h:29
A ROOT file is an on-disk file, usually with extension .root, that stores objects in a file-system-li...
Definition TFile.h:131
static Int_t ExportXML(const TUnfoldBinning &binning, std::ostream &out, Bool_t writeHeader, Bool_t writeFooter, Int_t indent=0)
export a binning scheme to a stream in XML format
static void WriteDTD(const char *fileName="tunfoldbinning.dtd")
write dtd file
Binning schemes for use with the unfolding algorithm TUnfoldDensity.

Version 17.6, in parallel to changes in TUnfold

History:

  • Version 17.5, updated for writing out XML code
  • Version 17.4, updated for writing out XML code
  • Version 17.3, updated for writing out XML code
  • Version 17.2, updated for writing out XML code
  • Version 17.1, in parallel to changes in TUnfold
  • Version 17.0 example for multi-dimensional unfolding

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 testUnfold5b.C.