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92d9f317 | 1 | /************************************************************************** |
2 | * This file is property of and copyright by * | |
3 | * the Relativistic Heavy Ion Group (RHIG), Yale University, US, 2009 * | |
4 | * * | |
5 | * Primary Author: Per Thomas Hille <p.t.hille@fys.uio.no> * | |
6 | * * | |
7 | * Contributors are mentioned in the code where appropriate. * | |
8 | * Please report bugs to p.t.hille@fys.uio.no * | |
9 | * * | |
10 | * Permission to use, copy, modify and distribute this software and its * | |
11 | * documentation strictly for non-commercial purposes is hereby granted * | |
12 | * without fee, provided that the above copyright notice appears in all * | |
13 | * copies and that both the copyright notice and this permission notice * | |
14 | * appear in the supporting documentation. The authors make no claims * | |
15 | * about the suitability of this software for any purpose. It is * | |
16 | * provided "as is" without express or implied warranty. * | |
17 | **************************************************************************/ | |
18 | ||
12543482 | 19 | // |
92d9f317 | 20 | // Extraction of amplitude and peak position |
21 | // FRom CALO raw data using | |
22 | // least square fit for the | |
23 | // Moment assuming identical and | |
24 | // independent errors (equivalent with chi square) | |
25 | // | |
26 | ||
27 | #include "AliCaloRawAnalyzerKStandard.h" | |
28 | #include "AliCaloBunchInfo.h" | |
29 | #include "AliCaloFitResults.h" | |
30 | #include "AliLog.h" | |
31 | #include "TMath.h" | |
32 | #include <stdexcept> | |
33 | #include <iostream> | |
34 | #include "TF1.h" | |
35 | #include "TGraph.h" | |
36 | #include "TRandom.h" | |
37 | ||
92d9f317 | 38 | using namespace std; |
39 | ||
92d9f317 | 40 | ClassImp( AliCaloRawAnalyzerKStandard ) |
41 | ||
42 | ||
396baaf6 | 43 | AliCaloRawAnalyzerKStandard::AliCaloRawAnalyzerKStandard() : AliCaloRawAnalyzerFitter("Chi Square ( kStandard )", "KStandard") |
92d9f317 | 44 | { |
45 | ||
46 | fAlgo = Algo::kStandard; | |
92d9f317 | 47 | } |
48 | ||
49 | ||
50 | AliCaloRawAnalyzerKStandard::~AliCaloRawAnalyzerKStandard() | |
51 | { | |
d44019b7 | 52 | // delete fTf1; |
92d9f317 | 53 | } |
54 | ||
55 | ||
92d9f317 | 56 | AliCaloFitResults |
57 | AliCaloRawAnalyzerKStandard::Evaluate( const vector<AliCaloBunchInfo> &bunchlist, const UInt_t altrocfg1, const UInt_t altrocfg2 ) | |
58 | { | |
92d9f317 | 59 | Float_t pedEstimate = 0; |
60 | short maxADC = 0; | |
61 | Int_t first = 0; | |
62 | Int_t last = 0; | |
63 | Int_t bunchIndex = 0; | |
64 | Float_t ampEstimate = 0; | |
65 | short timeEstimate = 0; | |
66 | Float_t time = 0; | |
67 | Float_t amp=0; | |
68 | Float_t chi2 = 0; | |
69 | Int_t ndf = 0; | |
70 | Bool_t fitDone = kFALSE; | |
92d9f317 | 71 | int nsamples = PreFitEvaluateSamples( bunchlist, altrocfg1, altrocfg2, bunchIndex, ampEstimate, |
12543482 | 72 | maxADC, timeEstimate, pedEstimate, first, last, (int)fAmpCut ); |
92d9f317 | 73 | |
74 | ||
75 | if (ampEstimate >= fAmpCut ) | |
76 | { | |
77 | time = timeEstimate; | |
78 | Int_t timebinOffset = bunchlist.at(bunchIndex).GetStartBin() - (bunchlist.at(bunchIndex).GetLength()-1); | |
79 | amp = ampEstimate; | |
80 | ||
81 | if ( nsamples > 1 && maxADC< OVERFLOWCUT ) | |
82 | { | |
83 | FitRaw(first, last, amp, time, chi2, fitDone); | |
84 | time += timebinOffset; | |
85 | timeEstimate += timebinOffset; | |
86 | ndf = nsamples - 2; | |
87 | } | |
88 | } | |
89 | if ( fitDone ) | |
90 | { | |
91 | Float_t ampAsymm = (amp - ampEstimate)/(amp + ampEstimate); | |
92 | Float_t timeDiff = time - timeEstimate; | |
93 | ||
94 | if ( (TMath::Abs(ampAsymm) > 0.1) || (TMath::Abs(timeDiff) > 2) ) | |
95 | { | |
96 | amp = ampEstimate; | |
97 | time = timeEstimate; | |
98 | fitDone = kFALSE; | |
99 | } | |
100 | } | |
101 | if (amp >= fAmpCut ) | |
102 | { | |
103 | if ( ! fitDone) | |
104 | { | |
105 | amp += (0.5 - gRandom->Rndm()); | |
106 | } | |
92d9f317 | 107 | time = time * TIMEBINWITH; |
92d9f317 | 108 | time -= fL1Phase; |
109 | ||
92d9f317 | 110 | return AliCaloFitResults( -99, -99, fAlgo , amp, time, |
12543482 | 111 | (int)time, chi2, ndf, Ret::kDummy ); |
d44019b7 | 112 | } |
92d9f317 | 113 | return AliCaloFitResults( Ret::kInvalid, Ret::kInvalid ); |
114 | } | |
115 | ||
92d9f317 | 116 | |
117 | //____________________________________________________________________________ | |
118 | void | |
119 | AliCaloRawAnalyzerKStandard::FitRaw(const Int_t firstTimeBin, const Int_t lastTimeBin, Float_t & amp, Float_t & time, Float_t & chi2, Bool_t & fitDone) const | |
d44019b7 | 120 | { |
121 | // Fits the raw signal time distribution | |
92d9f317 | 122 | int nsamples = lastTimeBin - firstTimeBin + 1; |
123 | fitDone = kFALSE; | |
d44019b7 | 124 | if (nsamples < 3) { return; } |
92d9f317 | 125 | |
126 | TGraph *gSig = new TGraph( nsamples); | |
127 | ||
128 | for (int i=0; i<nsamples; i++) | |
129 | { | |
130 | Int_t timebin = firstTimeBin + i; | |
131 | gSig->SetPoint(i, timebin, GetReversed(timebin)); | |
132 | } | |
133 | ||
134 | TF1 * signalF = new TF1("signal", RawResponseFunction, 0, TIMEBINS , 5); | |
135 | signalF->SetParameters(10.,5., TAU ,ORDER,0.); //set all defaults once, just to be safe | |
136 | signalF->SetParNames("amp","t0","tau","N","ped"); | |
d44019b7 | 137 | signalF->FixParameter(2,TAU); |
138 | signalF->FixParameter(3,ORDER); | |
139 | signalF->FixParameter(4, 0); | |
92d9f317 | 140 | signalF->SetParameter(1, time); |
141 | signalF->SetParameter(0, amp); | |
92d9f317 | 142 | signalF->SetParLimits(0, 0.5*amp, 2*amp ); |
143 | signalF->SetParLimits(1, time - 4, time + 4); | |
144 | ||
145 | try { | |
146 | gSig->Fit(signalF, "QROW"); // Note option 'W': equal errors on all points | |
92d9f317 | 147 | amp = signalF->GetParameter(0); |
148 | time = signalF->GetParameter(1); | |
149 | chi2 = signalF->GetChisquare(); | |
150 | fitDone = kTRUE; | |
151 | } | |
152 | catch (const std::exception & e) { | |
153 | AliError( Form("TGraph Fit exception %s", e.what()) ); | |
154 | // stay with default amp and time in case of exception, i.e. no special action required | |
155 | fitDone = kFALSE; | |
156 | } | |
d44019b7 | 157 | |
92d9f317 | 158 | delete signalF; |
92d9f317 | 159 | delete gSig; // delete TGraph |
92d9f317 | 160 | return; |
161 | } | |
162 | ||
163 | ||
164 | //__________________________________________________________________ | |
165 | void | |
166 | AliCaloRawAnalyzerKStandard::FitParabola(const TGraph *gSig, Float_t & amp) const | |
167 | { | |
168 | //BEG YS alternative methods to calculate the amplitude | |
169 | Double_t * ymx = gSig->GetX() ; | |
170 | Double_t * ymy = gSig->GetY() ; | |
171 | const Int_t kN = 3 ; | |
172 | Double_t ymMaxX[kN] = {0., 0., 0.} ; | |
173 | Double_t ymMaxY[kN] = {0., 0., 0.} ; | |
174 | Double_t ymax = 0. ; | |
175 | // find the maximum amplitude | |
176 | Int_t ymiMax = 0 ; | |
177 | for (Int_t ymi = 0; ymi < gSig->GetN(); ymi++) { | |
178 | if (ymy[ymi] > ymMaxY[0] ) { | |
179 | ymMaxY[0] = ymy[ymi] ; //<========== This is the maximum amplitude | |
180 | ymMaxX[0] = ymx[ymi] ; | |
181 | ymiMax = ymi ; | |
182 | } | |
183 | } | |
184 | // find the maximum by fitting a parabola through the max and the two adjacent samples | |
185 | if ( ymiMax < gSig->GetN()-1 && ymiMax > 0) { | |
186 | ymMaxY[1] = ymy[ymiMax+1] ; | |
187 | ymMaxY[2] = ymy[ymiMax-1] ; | |
188 | ymMaxX[1] = ymx[ymiMax+1] ; | |
189 | ymMaxX[2] = ymx[ymiMax-1] ; | |
190 | if (ymMaxY[0]*ymMaxY[1]*ymMaxY[2] > 0) { | |
191 | //fit a parabola through the 3 points y= a+bx+x*x*x | |
192 | Double_t sy = 0 ; | |
193 | Double_t sx = 0 ; | |
194 | Double_t sx2 = 0 ; | |
195 | Double_t sx3 = 0 ; | |
196 | Double_t sx4 = 0 ; | |
197 | Double_t sxy = 0 ; | |
198 | Double_t sx2y = 0 ; | |
199 | for (Int_t i = 0; i < kN ; i++) { | |
200 | sy += ymMaxY[i] ; | |
201 | sx += ymMaxX[i] ; | |
202 | sx2 += ymMaxX[i]*ymMaxX[i] ; | |
203 | sx3 += ymMaxX[i]*ymMaxX[i]*ymMaxX[i] ; | |
204 | sx4 += ymMaxX[i]*ymMaxX[i]*ymMaxX[i]*ymMaxX[i] ; | |
205 | sxy += ymMaxX[i]*ymMaxY[i] ; | |
206 | sx2y += ymMaxX[i]*ymMaxX[i]*ymMaxY[i] ; | |
207 | } | |
208 | Double_t cN = (sx2y*kN-sy*sx2)*(sx3*sx-sx2*sx2)-(sx2y*sx-sxy*sx2)*(sx3*kN-sx*sx2); | |
209 | Double_t cD = (sx4*kN-sx2*sx2)*(sx3*sx-sx2*sx2)-(sx4*sx-sx3*sx2)*(sx3*kN-sx*sx2) ; | |
210 | Double_t c = cN / cD ; | |
211 | Double_t b = ((sx2y*kN-sy*sx2)-c*(sx4*kN-sx2*sx2))/(sx3*kN-sx*sx2) ; | |
212 | Double_t a = (sy-b*sx-c*sx2)/kN ; | |
213 | Double_t xmax = -b/(2*c) ; | |
214 | ymax = a + b*xmax + c*xmax*xmax ;//<========== This is the maximum amplitude | |
215 | amp = ymax; | |
216 | } | |
217 | } | |
218 | ||
219 | Double_t diff = TMath::Abs(1-ymMaxY[0]/amp) ; | |
220 | if (diff > 0.1) | |
d44019b7 | 221 | { |
222 | amp = ymMaxY[0] ; | |
223 | } | |
224 | ||
92d9f317 | 225 | return; |
226 | } | |
227 | ||
228 | ||
92d9f317 | 229 | //__________________________________________________________________ |
230 | Double_t | |
231 | AliCaloRawAnalyzerKStandard::RawResponseFunction(Double_t *x, Double_t *par) | |
232 | { | |
92d9f317 | 233 | Double_t signal = 0.; |
234 | Double_t tau = par[2]; | |
235 | Double_t n = par[3]; | |
236 | Double_t ped = par[4]; | |
237 | Double_t xx = ( x[0] - par[1] + tau ) / tau ; | |
238 | ||
239 | if (xx <= 0) | |
240 | signal = ped ; | |
241 | else { | |
242 | signal = ped + par[0] * TMath::Power(xx , n) * TMath::Exp(n * (1 - xx )) ; | |
243 | } | |
244 | return signal ; | |
245 | } | |
246 |