| 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 | ! | 
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| 18 | !   Author(s): Javier Lopez 05/2001 <mailto:jlopez@ifae.es> | 
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| 19 | !   Author(s): Thomas Bretz 06/2001 <mailto:tbretz@uni-sw.gwdg.de> | 
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| 20 | ! | 
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| 21 | !   Copyright: MAGIC Software Development, 2000-2001 | 
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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 | /////////////////////////////////////////////////////////////////////////// | 
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| 27 | // | 
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| 28 | //  MMcThresholdCalc | 
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| 29 | // | 
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| 30 | //  Input Containers: | 
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| 31 | //   MMcEvt, MMcTrig;* | 
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| 32 | // | 
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| 33 | //  Output Containers: | 
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| 34 | //   MHMcEnergies | 
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| 35 | // | 
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| 36 | ///////////////////////////////////////////////////////////////////////////// | 
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| 37 |  | 
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| 38 | #include "MMcThresholdCalc.h" | 
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| 39 |  | 
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| 40 | #include <math.h> | 
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| 41 |  | 
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| 42 | #include "MParList.h" | 
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| 43 |  | 
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| 44 | #include "MLog.h" | 
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| 45 | #include "MLogManip.h" | 
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| 46 |  | 
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| 47 | #include "MMcEvt.hxx" | 
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| 48 | #include "MMcTrig.hxx" | 
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| 49 |  | 
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| 50 | #include "MHMcEnergy.h" | 
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| 51 |  | 
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| 52 | ClassImp(MMcThresholdCalc); | 
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| 53 |  | 
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| 54 | const Float_t MMcThresholdCalc::fSqrt2 = sqrt(2); | 
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| 55 |  | 
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| 56 | // -------------------------------------------------------------------------- | 
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| 57 | // | 
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| 58 | // Default Constructor. | 
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| 59 | // | 
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| 60 | // Specify the number of trigger conditions you want to use. | 
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| 61 | // The default is 0. | 
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| 62 | // | 
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| 63 | // dim < 0: use only condition number dim (eg "MMcTrig;3") | 
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| 64 | // dim = 0: use only condition without a number ("MMcTrig") | 
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| 65 | // dim > 0: use conditions up to dim (from "MMcTrig;1" to "MMcTrig;dim") | 
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| 66 | // | 
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| 67 | MMcThresholdCalc::MMcThresholdCalc(const Int_t dim, const char* name, | 
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| 68 | const char* title) | 
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| 69 | : fMcTrig(NULL), fEnergy(NULL) | 
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| 70 | { | 
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| 71 | fName  = name  ? name  : "MMcThresholdCalc"; | 
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| 72 | fTitle = title ? title : "Task to calculate the energy threshold from Monte Carlo"; | 
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| 73 |  | 
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| 74 | fFirst = dim>0 ?   1 : -dim; | 
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| 75 | fLast  = dim>0 ? dim : -dim; | 
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| 76 |  | 
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| 77 | fNum = fLast-fFirst+1; | 
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| 78 |  | 
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| 79 | AddToBranchList("MMcEvt.fEnergy"); | 
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| 80 | AddToBranchList("MMcTrig", "fNumFirstLevel", fFirst, fLast); | 
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| 81 | } | 
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| 82 |  | 
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| 83 | // ------------------------------------------------------------------------- | 
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| 84 | // | 
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| 85 | // Destructor. | 
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| 86 | // | 
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| 87 | MMcThresholdCalc::~MMcThresholdCalc() | 
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| 88 | { | 
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| 89 | if (fMcTrig) | 
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| 90 | delete fMcTrig; | 
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| 91 |  | 
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| 92 | if (fEnergy) | 
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| 93 | delete fEnergy; | 
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| 94 | } | 
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| 95 |  | 
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| 96 | // -------------------------------------------------------------------------- | 
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| 97 | // | 
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| 98 | // connect Monte Carlo data with this task | 
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| 99 | // | 
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| 100 | Bool_t MMcThresholdCalc::PreProcess(MParList* pList) | 
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| 101 | { | 
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| 102 | // | 
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| 103 | // This task takes into accout if the root file has one trigger | 
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| 104 | // condition (MMcTrig) or severl of them (MMcTrig;#.) | 
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| 105 |  | 
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| 106 | fMcEvt = (MMcEvt*)pList->FindObject("MMcEvt"); | 
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| 107 | if (!fMcEvt) | 
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| 108 | { | 
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| 109 | *fLog << err << dbginf << "MMcEvt not found... aborting." << endl; | 
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| 110 | return kFALSE; | 
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| 111 | } | 
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| 112 |  | 
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| 113 | UInt_t num; | 
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| 114 |  | 
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| 115 | fMcTrig = new TObjArray(pList->FindObjectList("MMcTrig", fFirst, fLast)); | 
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| 116 | num = fMcTrig->GetEntriesFast(); | 
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| 117 | if (num != fNum) | 
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| 118 | { | 
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| 119 | *fLog << err << dbginf << fNum << " MMcTrig objects requested, "; | 
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| 120 | *fLog << num << " are available... aborting." << endl; | 
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| 121 | return kFALSE; | 
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| 122 | } | 
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| 123 |  | 
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| 124 | fEnergy = new TObjArray(pList->FindCreateObjList("MHMcEnergy", fFirst, fLast)); | 
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| 125 | num = fMcTrig->GetEntriesFast(); | 
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| 126 | if (num != fNum) | 
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| 127 | { | 
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| 128 | *fLog << err << dbginf << fNum << " MHMcEnergy objects requested, "; | 
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| 129 | *fLog << num << " are available... aborting." << endl; | 
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| 130 | return kFALSE; | 
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| 131 | } | 
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| 132 |  | 
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| 133 | return kTRUE; | 
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| 134 | } | 
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| 135 |  | 
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| 136 | // -------------------------------------------------------------------------- | 
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| 137 | // | 
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| 138 | // The histograms are filled with log10 of the energy for triggered | 
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| 139 | // events and weighted with 1/E because it is needed the dN/dE vs. logE | 
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| 140 | // distribution to get the energy threshold. | 
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| 141 | // | 
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| 142 | Bool_t MMcThresholdCalc::Process() | 
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| 143 | { | 
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| 144 | const Float_t energy   = fMcEvt->GetEnergy(); | 
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| 145 | const Float_t lg10     = log10(energy); | 
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| 146 | const Float_t reciproc = 1./energy; | 
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| 147 |  | 
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| 148 | for (UInt_t i=0; i<fNum; i++) | 
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| 149 | if (GetTrig(i)->GetFirstLevel()>0) | 
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| 150 | GetHEnergy(i)->Fill(lg10, reciproc); | 
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| 151 |  | 
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| 152 | return kTRUE; | 
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| 153 | } | 
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| 154 |  | 
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| 155 | // -------------------------------------------------------------------------- | 
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| 156 | // | 
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| 157 | // fit the energy distribution to get the threshold | 
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| 158 | // Some iterations are done to be sure the fit parameters converge. | 
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| 159 | // | 
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| 160 | Bool_t MMcThresholdCalc::PostProcess() | 
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| 161 | { | 
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| 162 | for (UInt_t i=0; i<fNum; i++) | 
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| 163 | { | 
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| 164 | MHMcEnergy &hist = *GetHEnergy(i); | 
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| 165 |  | 
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| 166 | Float_t peak; | 
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| 167 | Float_t sigma; | 
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| 168 |  | 
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| 169 | hist.Fit(1, 3); | 
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| 170 |  | 
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| 171 | peak  = hist.GetGaussPeak(); | 
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| 172 | sigma = hist.GetGaussSigma(); | 
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| 173 | hist.Fit(peak - 2.   *sigma, peak + 2.   *sigma); | 
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| 174 |  | 
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| 175 | peak  = hist.GetGaussPeak(); | 
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| 176 | sigma = hist.GetGaussSigma(); | 
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| 177 | hist.Fit(peak - fSqrt2*sigma, peak + fSqrt2*sigma); | 
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| 178 |  | 
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| 179 | hist.SetReadyToSave(); | 
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| 180 | } | 
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| 181 | return kTRUE; | 
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| 182 | } | 
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| 183 |  | 
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