1 /**************************************************************************
2 * This file is property of and copyright by the Experimental Nuclear *
3 * Physics Group, Dep. of Physics *
4 * University of Oslo, Norway, 2007 *
6 * Author: Per Thomas Hille <perthomas.hille@yale.edu> *
7 * for the ALICE HLT Project. *
8 * Contributors are mentioned in the code where appropriate. *
9 * Please report bugs to perthi@fys.uio.no *
11 * Permission to use, copy, modify and distribute this software and its *
12 * documentation strictly for non-commercial purposes is hereby granted *
13 * without fee, provided that the above copyright notice appears in all *
14 * copies and that both the copyright notice and this permission notice *
15 * appear in the supporting documentation. The authors make no claims *
16 * about the suitability of this software for any purpose. It is *
17 * provided "as is" without express or implied warranty. *
18 **************************************************************************/
20 // Evaluation of peak position
21 // and amplitude using Neural Networks (NN)
27 #include "AliCaloRawAnalyzerNN.h"
28 #include "AliCaloNeuralFit.h"
29 #include "AliCaloFitResults.h"
30 #include "AliCaloBunchInfo.h"
36 ClassImp( AliCaloRawAnalyzerNN )
38 AliCaloRawAnalyzerNN::AliCaloRawAnalyzerNN() : AliCaloRawAnalyzer("Neural Network", "NN"), fNeuralNet(0)
42 fNeuralNet = new AliCaloNeuralFit();
44 for(int i=0; i < 5 ; i++)
52 AliCaloRawAnalyzerNN::~AliCaloRawAnalyzerNN()
59 AliCaloRawAnalyzerNN::Evaluate( const vector<AliCaloBunchInfo> &bunchvector,
60 const UInt_t altrocfg1, const UInt_t altrocfg2 )
62 // The eveluation of Peak position and amplitude using the Neural Network
63 if( bunchvector.size() <= 0 )
65 return AliCaloFitResults(AliCaloFitResults::kInvalid, AliCaloFitResults::kInvalid);
71 int index = SelectBunch( bunchvector, &maxampindex , &maxamp ) ;
75 return AliCaloFitResults(AliCaloFitResults::kInvalid, AliCaloFitResults::kInvalid);
78 Float_t ped = ReverseAndSubtractPed( &(bunchvector.at( index ) ) , altrocfg1, altrocfg2, fReversed );
79 short timebinOffset = maxampindex - (bunchvector.at(index).GetLength()-1);
80 double maxf = maxamp - ped;
82 if( maxf < fAmpCut || ( maxamp - ped) > fOverflowCut ) // (maxamp - ped) > fOverflowCut = Close to saturation (use low gain then)
84 return AliCaloFitResults( maxamp, ped, AliCaloFitResults::kCrude, maxf, timebinOffset);
89 short maxrev = maxampindex - bunchvector.at(index).GetStartBin();
90 SelectSubarray( fReversed, bunchvector.at(index).GetLength(), maxrev , &first, &last);
96 if ( ( maxrev - first) < 2 && (last - maxrev ) < 2)
98 chi2 = CalculateChi2(maxf, maxrev, first, last);
99 ndf = last - first - 1; // nsamples - 2
100 return AliCaloFitResults( maxamp, ped, AliCaloFitResults::kCrude, maxf, timebinOffset,
101 timebinOffset, chi2, ndf, AliCaloFitResults::kDummy, AliCaloFitSubarray(index, maxrev, first, last) );
106 for(int i=0; i < 5 ; i++)
108 fNNInput[i] = fReversed[maxrev-2 +i]/(maxamp -ped);
112 double amp = (maxamp - ped)*fNeuralNet->Value( 0, fNNInput[0], fNNInput[1], fNNInput[2], fNNInput[3], fNNInput[4]);
113 double tof = (fNeuralNet->Value( 1, fNNInput[0], fNNInput[1], fNNInput[2], fNNInput[3], fNNInput[4]) + timebinOffset ) ;
115 // use local-array time for chi2 estimate
116 chi2 = CalculateChi2(amp, tof-timebinOffset+maxrev, first, last);
117 ndf = last - first - 1; // nsamples - 2
118 return AliCaloFitResults( maxamp, ped , AliCaloFitResults::kFitPar, amp , tof, timebinOffset, chi2, ndf,
119 AliCaloFitResults::kDummy, AliCaloFitSubarray(index, maxrev, first, last) );
123 chi2 = CalculateChi2(maxf, maxrev, first, last);
124 ndf = last - first - 1; // nsamples - 2
125 return AliCaloFitResults( maxamp, ped, AliCaloFitResults::kCrude, maxf, timebinOffset,
126 timebinOffset, chi2, ndf, AliCaloFitResults::kDummy, AliCaloFitSubarray(index, maxrev, first, last) );