LMU/musrfit
LMU/musrfit
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proper normalization for NOT lifetime corrected signals

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This commit is contained in:
suter_a 2011-10-14 13:23:31 +00:00
parent 57d68e7133
commit cbacba3f2c
1 changed files with 12 additions and 15 deletions
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27
src/classes/PRunSingleHisto.cpp
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@ -852,6 +852,14 @@ Bool_t PRunSingleHisto::PrepareRawViewData(PRawRunData* runData, const UInt_t hi
packing = fMsrInfo->GetMsrPlotList()->at(0).fViewPacking;
}
// calculate necessary norms
Double_t dataNorm = 1.0, theoryNorm = 1.0;
if (fScaleN0AndBkg) {
dataNorm = 1.0/ (packing * (fTimeResolution * 1.0e3)); // fTimeResolution us->ns
} else if (!fScaleN0AndBkg && (fMsrInfo->GetMsrPlotList()->at(0).fViewPacking > 0)) {
theoryNorm = (Double_t)fMsrInfo->GetMsrPlotList()->at(0).fViewPacking/(Double_t)fRunInfo->GetPacking();
}
// raw data, since PMusrCanvas is doing ranging etc.
// start = the first bin which is a multiple of packing backward from first good data bin
Int_t start = fRunInfo->GetDataRange(0) - (fRunInfo->GetDataRange(0)/packing)*packing;
@ -897,31 +905,18 @@ Bool_t PRunSingleHisto::PrepareRawViewData(PRawRunData* runData, const UInt_t hi
Double_t normalizer = 1.0;
for (Int_t i=start; i<end; i++) {
if (((i-start) % packing == 0) && (i != start)) { // fill data
// in order that after rebinning the fit does not need to be redone (important for plots)
// the value is normalize to per 1 nsec
if (fScaleN0AndBkg)
normalizer = packing * (fTimeResolution * 1e3); // fTimeResolution us->ns
value /= normalizer;
value *= dataNorm;
fData.AppendValue(value);
if (value == 0.0)
fData.AppendErrorValue(1.0);
else
fData.AppendErrorValue(TMath::Sqrt(value/normalizer));
fData.AppendErrorValue(TMath::Sqrt(value*dataNorm));
// reset values
value = 0.0;
}
value += runData->GetDataBin(histoNo)->at(i);
}
// // count the number of bins
// fNoOfFitBins=0;
//
// Double_t time;
// for (UInt_t i=0; i<fData.GetValue()->size(); i++) {
// time = fData.GetDataTimeStart() + (Double_t)i*fData.GetDataTimeStep();
// if ((time >= fFitStartTime) && (time <= fFitEndTime))
// fNoOfFitBins++;
// }
CalcNoOfFitBins();
// fill theory vector for kView
@ -942,6 +937,7 @@ Bool_t PRunSingleHisto::PrepareRawViewData(PRawRunData* runData, const UInt_t hi
// evaluate function
N0 = fMsrInfo->EvalFunc(funNo, *fRunInfo->GetMap(), par);
}
N0 *= theoryNorm;
// get tau
Double_t tau;
@ -974,6 +970,7 @@ Bool_t PRunSingleHisto::PrepareRawViewData(PRawRunData* runData, const UInt_t hi
} else { // bkg fitted
bkg = par[fRunInfo->GetBkgFitParamNo()-1];
}
bkg *= theoryNorm;
// calculate functions
for (Int_t i=0; i<fMsrInfo->GetNoOfFuncs(); i++) {