//*-- Author: Marco van Leeuwen (LBL)
#include "AliEMCALRawUtils.h"
+#include <stdexcept>
#include "TF1.h"
#include "TGraph.h"
} // loop over bunches
- if ( caloFlag < 2 ){ // ALTRO
+ if ( caloFlag < 2 ){ // ALTRO
- Float_t time = 0;
- Float_t amp = 0;
+ Float_t time = 0;
+ Float_t amp = 0;
+ short timeEstimate = 0;
+ Float_t ampEstimate = 0;
+ Bool_t fitDone = kFALSE;
if ( fFittingAlgorithm == kFastFit || fFittingAlgorithm == kNeuralNet || fFittingAlgorithm == kLMS || fFittingAlgorithm == kPeakFinder || fFittingAlgorithm == kCrude) {
// all functionality to determine amp and time etc is encapsulated inside the Evaluate call for these methods
AliCaloFitResults fitResults = fRawAnalyzer->Evaluate( bunchlist, in.GetAltroCFG1(), in.GetAltroCFG2());
amp = fitResults.GetAmp();
- time = fitResults.GetTof();
+ time = fitResults.GetTime();
+ timeEstimate = fitResults.GetMaxTimebin();
+ ampEstimate = fitResults.GetMaxSig();
+ if (fitResults.GetStatus() == AliCaloFitResults::kFitPar) {
+ fitDone = kTRUE;
+ }
}
else { // for the other methods we for now use the functionality of
// AliCaloRawAnalyzer as well, to select samples and prepare for fits,
// if it looks like there is something to fit
// parameters init.
- Float_t ampEstimate = 0;
+ Float_t pedEstimate = 0;
short maxADC = 0;
- short timeEstimate = 0;
- Float_t pedEstimate = 0;
Int_t first = 0;
Int_t last = 0;
Int_t bunchIndex = 0;
time = timeEstimate; // maxrev in AliCaloRawAnalyzer speak; comes with an offset w.r.t. real timebin
Int_t timebinOffset = bunchlist.at(bunchIndex).GetStartBin() - (bunchlist.at(bunchIndex).GetLength()-1);
-
amp = ampEstimate;
if ( nsamples > 1 ) { // possibly something to fit
- FitRaw(first, last, amp, time);
+ FitRaw(first, last, amp, time, fitDone);
time += timebinOffset;
+ timeEstimate += timebinOffset;
}
- if ( amp>0 && time>0 ) { // brief sanity check of fit results
-
- // check fit results: should be consistent with initial estimates
- // more magic numbers, but very loose cuts, for now..
- // We have checked that amp and ampEstimate values are positive so division for assymmetry
- // calculation should be OK/safe
- Float_t ampAsymm = (amp - ampEstimate)/(amp + ampEstimate);
- if ( (TMath::Abs(ampAsymm) > 0.1) ) {
- AliDebug(2,Form("Fit results amp %f time %f not consistent with expectations ped %f max-ped %f time %d",
- amp, time, pedEstimate, ampEstimate, timeEstimate));
-
- // what should do we do then? skip this channel or assign the simple estimate?
- // for now just overwrite the fit results with the simple estimate
- amp = ampEstimate;
- time = timeEstimate;
- } // asymm check
- } // amp & time check
} // ampEstimate check
} // method selection
+
+ if ( fitDone ) { // brief sanity check of fit results
+ Float_t ampAsymm = (amp - ampEstimate)/(amp + ampEstimate);
+ Float_t timeDiff = time - timeEstimate;
+ if ( (TMath::Abs(ampAsymm) > 0.1) || (TMath::Abs(timeDiff) > 2) ) {
+ // AliDebug(2,Form("Fit results amp %f time %f not consistent with expectations amp %f time %d", amp, time, ampEstimate, timeEstimate));
+
+ // for now just overwrite the fit results with the simple/initial estimate
+ amp = ampEstimate;
+ time = timeEstimate;
+ fitDone = kFALSE;
+ }
+ } // fitDone
if (amp > fNoiseThreshold && amp<fgkRawSignalOverflow) { // something to be stored
+ if ( ! fitDone) { // smear ADC with +- 0.5 uniform (avoid discrete effects)
+ amp += (0.5 - gRandom->Rndm()); // Rndm generates a number in ]0,1]
+ }
+
Int_t id = fGeom->GetAbsCellIdFromCellIndexes(in.GetModule(), in.GetRow(), in.GetColumn()) ;
lowGain = in.IsLowGain();
}
//____________________________________________________________________________
-void AliEMCALRawUtils::FitRaw(const Int_t firstTimeBin, const Int_t lastTimeBin, Float_t & amp, Float_t & time) const
+void AliEMCALRawUtils::FitRaw(const Int_t firstTimeBin, const Int_t lastTimeBin, Float_t & amp, Float_t & time, Bool_t & fitDone) const
{ // Fits the raw signal time distribution
//--------------------------------------------------
//Do the fit, different fitting algorithms available
//--------------------------------------------------
int nsamples = lastTimeBin - firstTimeBin + 1;
+ fitDone = kFALSE;
switch(fFittingAlgorithm) {
case kStandard:
signalF->FixParameter(4, 0); // pedestal should be subtracted when we get here
signalF->SetParameter(1, time);
signalF->SetParameter(0, amp);
-
- gSig->Fit(signalF, "QROW"); // Note option 'W': equal errors on all points
-
- // assign fit results
- amp = signalF->GetParameter(0);
- time = signalF->GetParameter(1);
-
+ // set rather loose parameter limits
+ signalF->SetParLimits(0, 0.5*amp, 2*amp );
+ signalF->SetParLimits(1, time - 4, time + 4);
+
+ try {
+ gSig->Fit(signalF, "QROW"); // Note option 'W': equal errors on all points
+ // assign fit results
+ amp = signalF->GetParameter(0);
+ time = signalF->GetParameter(1);
+
+ // cross-check with ParabolaFit to see if the results make sense
+ FitParabola(gSig, amp); // amp is possibly updated
+ fitDone = kTRUE;
+ }
+ catch (const std::exception & e) {
+ AliError( Form("TGraph Fit exception %s", e.what()) );
+ // stay with default amp and time in case of exception, i.e. no special action required
+ fitDone = kFALSE;
+ }
delete signalF;
- // cross-check with ParabolaFit to see if the results make sense
- FitParabola(gSig, amp); // amp is possibly updated
-
//printf("Std : Amp %f, time %g\n",amp, time);
delete gSig; // delete TGraph
Double_t amplog = signalFLog->GetParameter(0); //Not Amp, but Log of Amp
amp = TMath::Exp(amplog);
time = signalFLog->GetParameter(1);
+ fitDone = kTRUE;
delete signalFLog;
//printf("LogFit: Amp %f, time %g\n",amp, time);
git://git.uio.no / u / mrichter / AliRoot.git / blobdiff