marginal improved error estimate for single histo RRF
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@ -58,7 +58,8 @@ using namespace std;
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PRunSingleHistoRRF::PRunSingleHistoRRF() : PRunBase()
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{
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fNoOfFitBins = 0;
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fBackground = 0;
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fBackground = 0.0;
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fBkgErr = 1.0;
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fRRFPacking = -1;
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// the 2 following variables are need in case fit range is given in bins, and since
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@ -612,7 +613,7 @@ Bool_t PRunSingleHistoRRF::PrepareFitData(PRawRunData* runData, const UInt_t his
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exp_t_tau = exp(time_tau);
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fForward[i] *= exp_t_tau;
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fM.push_back(fForward[i]); // i.e. M(t) = [N(t)-Nbkg] exp(+t/tau); needed to estimate N0 later on
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fMerr.push_back(exp_t_tau*sqrt(rawNt[i]-fBackground));
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fMerr.push_back(exp_t_tau*sqrt(rawNt[i]+fBkgErr*fBkgErr));
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}
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// calculate weights
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@ -620,7 +621,7 @@ Bool_t PRunSingleHistoRRF::PrepareFitData(PRawRunData* runData, const UInt_t his
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if (fMerr[i] > 0.0)
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fW.push_back(1.0/(fMerr[i]*fMerr[i]));
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else
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fW.push_back(0.0);
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fW.push_back(1.0);
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}
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// now fForward = exp(+t/tau) [N(t)-Nbkg] = M(t)
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@ -1188,7 +1189,12 @@ Bool_t PRunSingleHistoRRF::EstimateBkg(UInt_t histoNo)
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fBackground = bkg; // keep background (per bin)
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cout << endl << "info> fBackground=" << fBackground << endl;
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bkg = 0.0;
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for (UInt_t i=start; i<end; i++)
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bkg += pow(fForward[i]-fBackground, 2.0);
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fBkgErr = sqrt(bkg/(static_cast<Double_t>(end - start)));
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cout << endl << "info> fBackground=" << fBackground << "(" << fBkgErr << ")" << endl;
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fRunInfo->SetBkgEstimated(fBackground, 0);
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@ -65,6 +65,7 @@ class PRunSingleHistoRRF : public PRunBase
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UInt_t fNoOfFitBins; ///< number of bins to be fitted
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Double_t fBackground; ///< needed if background range is given (units: 1/bin)
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Double_t fBkgErr; ///< estimate error on the estimated background
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Int_t fRRFPacking; ///< RRF packing for this particular run. Given in the GLOBAL-block.
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Int_t fGoodBins[2]; ///< keep first/last good bins. 0=fgb, 1=lgb
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