| 1 | /* ======================================================================== *\ | 
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| 2 | ! | 
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| 3 | ! * | 
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| 4 | ! * This file is part of MARS, the MAGIC Analysis and Reconstruction | 
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| 5 | ! * Software. It is distributed to you in the hope that it can be a useful | 
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| 6 | ! * and timesaving tool in analysing Data of imaging Cerenkov telescopes. | 
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| 7 | ! * It is distributed WITHOUT ANY WARRANTY. | 
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| 8 | ! * | 
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| 9 | ! * Permission to use, copy, modify and distribute this software and its | 
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| 10 | ! * documentation for any purpose is hereby granted without fee, | 
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| 11 | ! * provided that the above copyright notice appear in all copies and | 
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| 12 | ! * that both that copyright notice and this permission notice appear | 
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| 13 | ! * in supporting documentation. It is provided "as is" without express | 
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| 14 | ! * or implied warranty. | 
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| 15 | ! * | 
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| 16 | ! | 
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| 17 | !   Author(s): Javier Rico     02/2005 <mailto:jrico@ifae.es> | 
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| 18 | ! | 
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| 19 | !   Copyright: MAGIC Software Development, 2000-2005 | 
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| 20 | ! | 
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| 21 | ! | 
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| 22 | \* ======================================================================== */ | 
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| 23 |  | 
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| 24 | ////////////////////////////////////////////////////////////////////////////// | 
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| 25 | // | 
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| 26 | // MHMcUnfoldCoeff | 
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| 27 | // Container that stores the coefficients to convert from estimated to real | 
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| 28 | // (unfolded) energy. | 
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| 29 | // It is filled by MMcUnfoldCoeffCalc | 
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| 30 | // Events are weighted from any initial spectrum to a tentative spectrum | 
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| 31 | // that must be set through MMcUnfoldCoeffCalc::SetSpectrum method. | 
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| 32 | // | 
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| 33 | ////////////////////////////////////////////////////////////////////////////// | 
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| 34 |  | 
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| 35 | #include <fstream> | 
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| 36 | #include <math.h> | 
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| 37 |  | 
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| 38 | #include "TH1D.h" | 
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| 39 | #include "TH2D.h" | 
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| 40 | #include "TF1.h" | 
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| 41 | #include "TCanvas.h" | 
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| 42 | #include "TArrayD.h" | 
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| 43 |  | 
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| 44 | #include "MHMcUnfoldCoeff.h" | 
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| 45 |  | 
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| 46 | #include "MBinning.h" | 
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| 47 |  | 
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| 48 | #include "MLog.h" | 
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| 49 | #include "MLogManip.h" | 
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| 50 |  | 
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| 51 | ClassImp(MHMcUnfoldCoeff); | 
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| 52 |  | 
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| 53 | using namespace std; | 
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| 54 |  | 
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| 55 |  | 
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| 56 | // ------------------------------------------------------------------------- | 
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| 57 | // | 
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| 58 | // Constructor: Define and configure the different histograms to be filled | 
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| 59 | // | 
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| 60 | MHMcUnfoldCoeff::MHMcUnfoldCoeff(const char *name, const char *title) : | 
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| 61 | fNsubbins(20), fEmin(1.), fEmax(100000.), fNumMin(10), fFineBinning(NULL) | 
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| 62 | { | 
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| 63 | fName  = name  ? name  : "MHMcUnfoldCoeff"; | 
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| 64 | fTitle = title ? title : "Unfolding Coefficients vs. Theta vs. Energy"; | 
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| 65 |  | 
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| 66 | // define histos | 
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| 67 | fHistAll    = new TH1D(); | 
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| 68 | fHistWeight = new TH1D(); | 
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| 69 | fHistMcE    = new TH2D(); | 
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| 70 | fHistEstE   = new TH2D(); | 
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| 71 | fHistCoeff  = new TH2D(); | 
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| 72 |  | 
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| 73 | // set histo names | 
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| 74 | fHistAll->SetName("AllEvents"); | 
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| 75 | fHistWeight->SetName("Weights"); | 
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| 76 | fHistMcE->SetName("MCEnergy"); | 
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| 77 | fHistEstE->SetName("EstimatedEnergy"); | 
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| 78 | fHistCoeff->SetName("UnfoldCoeff"); | 
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| 79 |  | 
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| 80 | // set histo titles | 
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| 81 | fHistAll->SetTitle("MC energy for all generated events"); | 
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| 82 | fHistWeight->SetTitle("Weights"); | 
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| 83 | fHistMcE->SetTitle("MC energy for survivors"); | 
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| 84 | fHistEstE->SetTitle("Estimate energy for survivors"); | 
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| 85 | fHistCoeff->SetTitle(fTitle); | 
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| 86 |  | 
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| 87 | // histos directory | 
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| 88 | fHistAll->SetDirectory(NULL); | 
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| 89 | fHistWeight->SetDirectory(NULL); | 
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| 90 | fHistMcE->SetDirectory(NULL); | 
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| 91 | fHistEstE->SetDirectory(NULL); | 
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| 92 | fHistCoeff->SetDirectory(NULL); | 
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| 93 |  | 
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| 94 | // histos style | 
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| 95 | fHistAll->UseCurrentStyle(); | 
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| 96 | fHistWeight->UseCurrentStyle(); | 
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| 97 | fHistMcE->UseCurrentStyle(); | 
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| 98 | fHistEstE->UseCurrentStyle(); | 
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| 99 | fHistCoeff->UseCurrentStyle(); | 
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| 100 |  | 
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| 101 | // labels | 
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| 102 | fHistAll->SetXTitle("E [GeV]"); | 
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| 103 | fHistWeight->SetXTitle("E [GeV]"); | 
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| 104 | fHistMcE->SetXTitle("E_{MC} [GeV]"); | 
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| 105 | fHistEstE->SetXTitle("E_{est} [GeV]"); | 
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| 106 | fHistCoeff->SetXTitle("E_{est} [GeV]"); | 
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| 107 |  | 
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| 108 | fHistWeight->SetYTitle("weight"); | 
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| 109 | fHistMcE->SetYTitle("\\theta [\\circ]"); | 
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| 110 | fHistEstE->SetYTitle("\\theta [\\circ]"); | 
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| 111 | fHistCoeff->SetYTitle("\\theta [\\circ]"); | 
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| 112 |  | 
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| 113 | fHistMcE->SetZTitle("weighted entries"); | 
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| 114 | fHistEstE->SetZTitle("weighted entries"); | 
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| 115 | fHistCoeff->SetZTitle("Coefficient"); | 
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| 116 | } | 
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| 117 |  | 
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| 118 | // ------------------------------------------------------------------------- | 
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| 119 | // | 
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| 120 | // Destructor: Delete all the histograms | 
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| 121 | // | 
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| 122 | MHMcUnfoldCoeff::~MHMcUnfoldCoeff() | 
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| 123 | { | 
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| 124 | delete fHistAll; | 
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| 125 | delete fHistWeight; | 
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| 126 | delete fHistMcE; | 
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| 127 | delete fHistEstE; | 
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| 128 | delete fHistCoeff; | 
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| 129 |  | 
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| 130 | if(fFineBinning) | 
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| 131 | delete fFineBinning; | 
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| 132 | } | 
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| 133 |  | 
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| 134 | // -------------------------------------------------------------------------- | 
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| 135 | // | 
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| 136 | // Set the histograms binning. The coarse binning has to be provided | 
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| 137 | // from outside (in the parameter list) whereas the fine binning for | 
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| 138 | // energy is computed from the former. | 
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| 139 | // The subbinning is set logarithmicaly (linearly) for a logarithmic | 
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| 140 | // (linear) coarse binning. | 
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| 141 | // It is extended down to fEmin and up to fEmax | 
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| 142 | // The number of subbins per coarse bins may be changed using | 
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| 143 | // SetNsubbins() method | 
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| 144 | // The maximum and minimum energies of the fine binning histograms | 
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| 145 | // may be changed with the SetEmin() and SetEmax() methods | 
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| 146 | // | 
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| 147 | void MHMcUnfoldCoeff::SetCoarseBinnings(const MBinning &binsEnergy, | 
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| 148 | const MBinning &binsTheta) | 
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| 149 | { | 
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| 150 | // set histo binning (for coarse bin histos) | 
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| 151 | MH::SetBinning(fHistMcE,&binsEnergy,&binsTheta); | 
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| 152 | MH::SetBinning(fHistEstE,&binsEnergy,&binsTheta); | 
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| 153 | MH::SetBinning(fHistCoeff,&binsEnergy,&binsTheta); | 
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| 154 |  | 
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| 155 | // good errors | 
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| 156 | fHistMcE->Sumw2(); | 
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| 157 | fHistEstE->Sumw2(); | 
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| 158 |  | 
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| 159 | // define fine binning from coarse one | 
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| 160 | const Int_t nbins = binsEnergy.GetNumBins(); | 
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| 161 | const TArrayD edges = binsEnergy.GetEdgesD(); | 
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| 162 | const Bool_t isLinear = binsEnergy.IsLinear(); | 
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| 163 |  | 
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| 164 | // compute bins needed to extend down to fEmin and up to fEmax | 
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| 165 | Double_t dedown, deup; | 
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| 166 | Int_t binsdown,binsup; | 
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| 167 | MBinning dbin; | 
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| 168 | MBinning ubin; | 
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| 169 | if(isLinear) | 
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| 170 | { | 
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| 171 | dedown   = (edges[1]-edges[0])/fNsubbins; | 
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| 172 | deup     = (edges[nbins]-edges[nbins-1])/fNsubbins; | 
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| 173 | binsdown = (fEmin<edges[0])     ? Int_t((edges[0]-fEmin)/dedown) : 0; | 
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| 174 | binsup   = (fEmax>edges[nbins]) ? Int_t((fEmax-edges[nbins])/deup) : 0; | 
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| 175 | if(binsdown) dbin.SetEdges(binsdown,fEmin,edges[0]); | 
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| 176 | if(binsup)   ubin.SetEdges(binsup,edges[nbins],fEmax); | 
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| 177 | } | 
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| 178 | else | 
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| 179 | { | 
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| 180 | dedown   = (TMath::Log10(edges[1])-TMath::Log10(edges[0]))/fNsubbins; | 
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| 181 | deup     = (TMath::Log10(edges[nbins])-TMath::Log10(edges[nbins-1]))/fNsubbins; | 
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| 182 | binsdown = (fEmin<edges[0])    ? Int_t((TMath::Log10(edges[0])-TMath::Log10(fEmin))/dedown) : 0; | 
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| 183 | binsup   = (fEmax>edges[nbins])? Int_t((TMath::Log10(fEmax)-TMath::Log10(edges[nbins]))/deup) : 0; | 
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| 184 | if(binsdown) dbin.SetEdgesLog(binsdown,fEmin,edges[0]); | 
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| 185 | if(binsup)   ubin.SetEdgesLog(binsup,edges[nbins],fEmax); | 
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| 186 | } | 
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| 187 |  | 
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| 188 | // fill the subins' edges | 
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| 189 | TArrayD fineedges(binsdown+nbins*fNsubbins+binsup+1); | 
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| 190 |  | 
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| 191 | for(Int_t i=0;i<binsdown;i++) | 
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| 192 | fineedges[i] = dbin.GetEdgesD().At(i); | 
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| 193 |  | 
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| 194 | for(Int_t i=0;i<nbins;i++) | 
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| 195 | { | 
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| 196 | MBinning coarb; | 
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| 197 | if(isLinear) | 
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| 198 | coarb.SetEdges(fNsubbins,edges[i],edges[i+1]); | 
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| 199 | else | 
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| 200 | coarb.SetEdgesLog(fNsubbins,edges[i],edges[i+1]); | 
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| 201 |  | 
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| 202 | for(Int_t j=0;j<fNsubbins;j++) | 
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| 203 | fineedges[binsdown+i*fNsubbins+j] = coarb.GetEdgesD().At(j); | 
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| 204 | } | 
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| 205 |  | 
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| 206 | for(Int_t i=0;i<binsup;i++) | 
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| 207 | fineedges[binsdown+nbins*fNsubbins+i] = ubin.GetEdgesD().At(i); | 
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| 208 |  | 
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| 209 | fineedges[binsdown+nbins*fNsubbins+binsup] = binsup ? ubin.GetEdgesD().At(binsup): edges[nbins]; | 
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| 210 |  | 
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| 211 | // define fine binning object | 
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| 212 | fFineBinning = new MBinning; | 
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| 213 | fFineBinning->SetEdges(fineedges); | 
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| 214 |  | 
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| 215 | // apply fine binning to histograms that need it | 
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| 216 | fFineBinning->Apply(*fHistAll); | 
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| 217 | fFineBinning->Apply(*fHistWeight); | 
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| 218 | } | 
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| 219 |  | 
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| 220 | // ------------------------------------------------------------------------- | 
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| 221 | // | 
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| 222 | // Compute the weights for a particular tentative spectrum. | 
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| 223 | // For each energy (fine) bin we compute it as the value of the input function | 
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| 224 | // divided by the number of entries in the actual energy histogram. | 
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| 225 | // First and last bin are not filled since they could be biased | 
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| 226 | // | 
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| 227 | void MHMcUnfoldCoeff::ComputeWeights(TF1* spectrum) | 
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| 228 | { | 
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| 229 | Bool_t first=kTRUE; | 
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| 230 | Int_t  lastb=0; | 
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| 231 | for(Int_t i=0;i<fHistAll->GetNbinsX();i++) | 
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| 232 | { | 
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| 233 | const Float_t denom = fHistAll->GetBinContent(i+1); // number of events in initial spectrum | 
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| 234 | const Float_t ew    = fHistAll->GetBinCenter(i+1);  // energy associated to the bin | 
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| 235 | const Float_t numer = spectrum->Eval(ew);           // number of events for the required spectrum | 
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| 236 |  | 
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| 237 | if(denom>fNumMin) | 
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| 238 | { | 
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| 239 | // do not fill it if it is the first one | 
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| 240 | if(first) | 
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| 241 | { | 
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| 242 | fHistWeight->SetBinContent(i+1,-1); | 
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| 243 | first=kFALSE; | 
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| 244 | } | 
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| 245 | else | 
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| 246 | { | 
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| 247 | fHistWeight->SetBinContent(i+1,numer/denom); | 
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| 248 | lastb=i+1; | 
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| 249 | } | 
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| 250 | } | 
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| 251 | else | 
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| 252 | fHistWeight->SetBinContent(i+1,-1); | 
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| 253 | } | 
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| 254 |  | 
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| 255 | //remove last filled bin | 
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| 256 | if(lastb) | 
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| 257 | fHistWeight->SetBinContent(lastb,-1); | 
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| 258 | } | 
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| 259 |  | 
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| 260 | // -------------------------------------------------------------- | 
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| 261 | // | 
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| 262 | // Compute the coefficients used for the (iterative) unfolding | 
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| 263 | // The coefficients are the ratio between the contents of the | 
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| 264 | // mc energy and estimate energy histograms (filled with weighted | 
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| 265 | // events | 
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| 266 | // Errors are computed as if estimated and MC energy histos where | 
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| 267 | // uncorrelated | 
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| 268 | // | 
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| 269 | void MHMcUnfoldCoeff::ComputeCoefficients() | 
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| 270 | { | 
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| 271 | for(Int_t j=0;j<fHistEstE->GetNbinsY();j++) | 
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| 272 | for(Int_t i=0;i<fHistEstE->GetNbinsX();i++) | 
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| 273 | { | 
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| 274 | const Float_t num = fHistMcE->GetBinContent(i+1,j+1); | 
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| 275 | const Float_t den = fHistEstE->GetBinContent(i+1,j+1); | 
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| 276 |  | 
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| 277 | if(den>0) | 
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| 278 | { | 
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| 279 | const Float_t cf  = num/den; | 
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| 280 | fHistCoeff->SetBinContent(i+1,j+1,cf); | 
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| 281 |  | 
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| 282 | if(num>0) | 
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| 283 | { | 
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| 284 | const Float_t ernum = fHistMcE->GetBinError(i+1,j+1); | 
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| 285 | const Float_t erden = fHistEstE->GetBinError(i+1,j+1); | 
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| 286 | const Float_t ercf  = cf*(TMath::Sqrt(ernum/num*ernum/num+erden/den*erden/den)); | 
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| 287 | fHistCoeff->SetBinError(i+1,j+1,ercf); | 
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| 288 | } | 
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| 289 | else | 
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| 290 | fHistCoeff->SetBinError(i+1,j+1,0); | 
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| 291 | } | 
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| 292 | else | 
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| 293 | { | 
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| 294 | *fLog << warn << "MHMcUnfoldCoeff::ComputeCoefficients Warning: energy bin " << i << ", thetabin " << j << " has no survivors, setting coefficient to 0" << endl; | 
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| 295 | fHistCoeff->SetBinContent(i+1,j+1,0.); | 
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| 296 | fHistCoeff->SetBinError(i+1,j+1,0.); | 
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| 297 | } | 
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| 298 | } | 
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| 299 | } | 
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| 300 |  | 
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| 301 | // -------------------------------------------------------------------------- | 
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| 302 | // | 
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| 303 | // Fill data into the histogram which contains all showers | 
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| 304 | // | 
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| 305 | void MHMcUnfoldCoeff::FillAll(Double_t energy) | 
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| 306 | { | 
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| 307 | fHistAll->Fill(energy); | 
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| 308 | } | 
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| 309 |  | 
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| 310 | // -------------------------------------------------------------------------- | 
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| 311 | // | 
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| 312 | // Fill data into the histograms which contain survivors | 
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| 313 | // each event is introduced with a weight depending on its (MC) energy | 
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| 314 | // | 
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| 315 | void MHMcUnfoldCoeff::FillSel(Double_t mcenergy,Double_t estenergy,Double_t theta) | 
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| 316 | { | 
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| 317 | // bin of the corresponding weight | 
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| 318 | const Int_t wbin = fFineBinning->FindHiEdge(mcenergy); | 
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| 319 |  | 
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| 320 | if(wbin>0) | 
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| 321 | { | 
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| 322 | // weight | 
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| 323 | const Double_t weight = fHistWeight->GetBinContent(wbin); | 
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| 324 |  | 
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| 325 | if(weight>0) | 
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| 326 | { | 
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| 327 | fHistMcE->Fill(mcenergy,theta,weight); | 
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| 328 | fHistEstE->Fill(estenergy,theta,weight); | 
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| 329 | } | 
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| 330 | //      else | 
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| 331 | //      *fLog << warn << "MHMcUnfoldCoeff::FillSel Warning: event with energy " << mcenergy << " has no computed weight (lack of MC statistics), skipping" << endl; | 
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| 332 | } | 
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| 333 | // the event has an energy out of the considered range | 
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| 334 | else | 
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| 335 | *fLog << warn << "MHMcUnfoldCoeff::FillSel Warning: event with energy " << mcenergy << " has energy out of bounds, skipping" << endl; | 
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| 336 | } | 
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| 337 |  | 
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| 338 | // -------------------------------------------------------------------------- | 
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| 339 | // | 
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| 340 | // Draw | 
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| 341 | // | 
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| 342 | void MHMcUnfoldCoeff::Draw(Option_t* option) | 
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| 343 | { | 
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| 344 | TCanvas *c1 = new TCanvas(); | 
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| 345 | c1->SetLogx(); | 
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| 346 | c1->SetLogy(); | 
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| 347 | c1->SetGridx(); | 
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| 348 | c1->SetGridy(); | 
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| 349 |  | 
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| 350 | fHistCoeff->Draw(""); | 
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| 351 | } | 
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| 352 |  | 
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