LMU/musrfit
5
0
Fork 0
Code Issues 6 Pull Requests Actions Packages Projects Releases 4 Activity

added expected chisq calculation for single histogram fits (MUSR-194)

Browse Source
This commit is contained in:
nemu
2011-07-09 16:26:42 +00:00
parent 0ab456e5f5
commit d9f1f1235e
18 changed files with 606 additions and 84 deletions
Download Patch File Download Diff File Expand all files Collapse all files

101
src/classes/PRunSingleHisto.cpp
View File

@ -185,6 +185,99 @@ Double_t PRunSingleHisto::CalcChiSquare(const std::vector<Double_t>& par)
return chisq;
}
//--------------------------------------------------------------------------
// CalcChiSquareExpected (public)
//--------------------------------------------------------------------------
/**
* <p>Calculate expected chi-square.
*
* <b>return:</b>
* - chisq value
*
* \param par parameter vector iterated by minuit2
*/
Double_t PRunSingleHisto::CalcChiSquareExpected(const std::vector<Double_t>& par)
{
Double_t chisq = 0.0;
Double_t diff = 0.0;
Double_t theo = 0.0;
Double_t N0 = 0.0;
// check if norm is a parameter or a function
if (fRunInfo->GetNormParamNo() < MSR_PARAM_FUN_OFFSET) { // norm is a parameter
N0 = par[fRunInfo->GetNormParamNo()-1];
} else { // norm is a function
// get function number
UInt_t funNo = fRunInfo->GetNormParamNo()-MSR_PARAM_FUN_OFFSET;
// evaluate function
N0 = fMsrInfo->EvalFunc(funNo, *fRunInfo->GetMap(), par);
}
// get tau
Double_t tau;
if (fRunInfo->GetLifetimeParamNo() != -1)
tau = par[fRunInfo->GetLifetimeParamNo()-1];
else
tau = PMUON_LIFETIME;
// get background
Double_t bkg;
if (fRunInfo->GetBkgFitParamNo() == -1) { // bkg not fitted
if (fRunInfo->GetBkgFix(0) == PMUSR_UNDEFINED) { // no fixed background given (background interval)
bkg = fBackground;
} else { // fixed bkg given
bkg = fRunInfo->GetBkgFix(0);
}
} else { // bkg fitted
bkg = par[fRunInfo->GetBkgFitParamNo()-1];
}
// calculate functions
for (Int_t i=0; i<fMsrInfo->GetNoOfFuncs(); i++) {
Int_t funcNo = fMsrInfo->GetFuncNo(i);
fFuncValues[i] = fMsrInfo->EvalFunc(funcNo, *fRunInfo->GetMap(), par);
}
// calculate chi square
Double_t time(1.0);
Int_t i, N(static_cast<Int_t>(fData.GetValue()->size()));
// In order not to have an IF in the next loop, determine the start and end bins for the fit range now
Int_t startTimeBin = static_cast<Int_t>(ceil((fFitStartTime - fData.GetDataTimeStart())/fData.GetDataTimeStep()));
if (startTimeBin < 0)
startTimeBin = 0;
Int_t endTimeBin = static_cast<Int_t>(floor((fFitEndTime - fData.GetDataTimeStart())/fData.GetDataTimeStep())) + 1;
if (endTimeBin > N)
endTimeBin = N;
// Calculate the theory function once to ensure one function evaluation for the current set of parameters.
// This is needed for the LF and user functions where some non-thread-save calculations only need to be calculated once
// for a given set of parameters---which should be done outside of the parallelized loop.
// For all other functions it means a tiny and acceptable overhead.
time = fTheory->Func(time, par, fFuncValues);
#ifdef HAVE_GOMP
Int_t chunk = (endTimeBin - startTimeBin)/omp_get_num_procs();
if (chunk < 10)
chunk = 10;
#pragma omp parallel for default(shared) private(i,time,diff) schedule(dynamic,chunk) reduction(+:chisq)
#endif
for (i=startTimeBin; i < endTimeBin; ++i) {
time = fData.GetDataTimeStart() + (Double_t)i*fData.GetDataTimeStep();
theo = N0*TMath::Exp(-time/tau)*(1.0+fTheory->Func(time, par, fFuncValues))+bkg;
diff = fData.GetValue()->at(i) - theo;
chisq += diff*diff / theo;
}
// the correction factor is need since the data scales like pack*t_res,
// whereas the error scales like sqrt(pack*t_res)
if (fScaleN0AndBkg)
chisq *= fRunInfo->GetPacking() * (fTimeResolution * 1.0e3);
return chisq;
}
//--------------------------------------------------------------------------
// CalcMaxLikelihood (public)
//--------------------------------------------------------------------------
@ -360,14 +453,6 @@ void PRunSingleHisto::CalcTheory()
*/
UInt_t PRunSingleHisto::GetNoOfFitBins()
{
// 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();
return fNoOfFitBins;