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1ee39b3a | 1 | /************************************************************************* |
9ec5bce7 | 2 | * Copyright(c) 1998-1999, ALICE Experiment at CERN, All rights reserved. * |
3 | * * | |
4 | * Author: The ALICE Off-line Project. * | |
5 | * Contributors are mentioned in the code where appropriate. * | |
6 | * * | |
7 | * Permission to use, copy, modify and distribute this software and its * | |
8 | * documentation strictly for non-commercialf purposes is hereby granted * | |
9 | * without fee, provided that the above copyright notice appears in all * | |
10 | * copies and that both the copyright notice and this permission notice * | |
11 | * appear in the supporting documentation. The authors make no claims * | |
12 | * about the suitability of this software for any purpose. It is * | |
13 | * provided "as is" without express or implied warranty. * | |
14 | **************************************************************************/ | |
1ee39b3a | 15 | |
16 | /* $Id: AliTRDpidRefMakerNN.cxx 27496 2008-07-22 08:35:45Z cblume $ */ | |
17 | ||
18 | //////////////////////////////////////////////////////////////////////////// | |
19 | // // | |
20 | // Builds the reference tree for the training of neural networks // | |
21 | // // | |
22 | //////////////////////////////////////////////////////////////////////////// | |
23 | ||
24 | #include "TSystem.h" | |
25 | #include "TDatime.h" | |
26 | #include "TPDGCode.h" | |
27 | #include "TH1F.h" | |
28 | #include "TH2F.h" | |
29 | #include "TFile.h" | |
30 | #include "TGraphErrors.h" | |
31 | #include "TTree.h" | |
32 | #include "TEventList.h" | |
33 | #include "TMultiLayerPerceptron.h" | |
34 | ||
35 | #include "AliPID.h" | |
36 | #include "AliESDtrack.h" | |
37 | #include "AliTrackReference.h" | |
38 | ||
39 | #include "AliTRDtrackV1.h" | |
40 | #include "AliTRDReconstructor.h" | |
41 | #include "AliTRDpidUtil.h" | |
42 | #include "AliTRDpidRefMakerNN.h" | |
43 | #include "AliTRDpidUtil.h" | |
44 | ||
da27d983 | 45 | #include "Cal/AliTRDCalPID.h" |
46 | #include "Cal/AliTRDCalPIDNN.h" | |
1ee39b3a | 47 | #include "info/AliTRDtrackInfo.h" |
48 | #include "info/AliTRDv0Info.h" | |
49 | ||
50 | ClassImp(AliTRDpidRefMakerNN) | |
51 | ||
9ec5bce7 | 52 | //________________________________________________________________________ |
53 | AliTRDpidRefMakerNN::AliTRDpidRefMakerNN() | |
54 | :AliTRDpidRefMaker("PIDrefMakerNN", "PID(NN) Reference Maker") | |
55 | ,fNet(0x0) | |
56 | ,fTrainMomBin(kAll) | |
57 | ,fEpochs(1000) | |
58 | ,fMinTrain(100) | |
59 | ,fDate(0) | |
60 | ,fDoTraining(0) | |
61 | ,fContinueTraining(0) | |
62 | ,fTrainPath(0x0) | |
63 | ,fScale(0) | |
64 | ,fLy(0) | |
65 | ,fNtrkl(0) | |
66 | ,fRef(0x0) | |
1ee39b3a | 67 | { |
68 | // | |
69 | // Default constructor | |
70 | // | |
71 | ||
9ec5bce7 | 72 | memset(fTrain, 0, AliTRDCalPID::kNMom*sizeof(TEventList*)); |
73 | memset(fTest, 0, AliTRDCalPID::kNMom*sizeof(TEventList*)); | |
74 | memset(fTrainData, 0, AliTRDCalPID::kNMom*sizeof(TTree*)); | |
1ee39b3a | 75 | |
76 | SetAbundance(.67); | |
77 | SetScaledEdx(Float_t(AliTRDCalPIDNN::kMLPscale)); | |
78 | TDatime datime; | |
79 | fDate = datime.GetDate(); | |
80 | ||
81 | DefineInput(1, TObjArray::Class()); | |
82 | DefineOutput(1, TTree::Class()); | |
83 | } | |
84 | ||
85 | ||
86 | //________________________________________________________________________ | |
87 | AliTRDpidRefMakerNN::~AliTRDpidRefMakerNN() | |
88 | { | |
89 | } | |
90 | ||
91 | ||
92 | //________________________________________________________________________ | |
93 | void AliTRDpidRefMakerNN::CreateOutputObjects() | |
94 | { | |
9ec5bce7 | 95 | // Create output file and tree |
1ee39b3a | 96 | // Called once |
97 | ||
9ec5bce7 | 98 | fRef = new TFile(Form("TRD.Calib%s.root", GetName()), "RECREATE"); |
99 | for(Int_t ip = 0; ip < AliTRDCalPID::kNMom; ip++){ | |
100 | fTrainData[ip] = new TTree(Form("fTrainData_%d", ip), Form("NN Reference Data for MomBin %d", ip)); | |
101 | fTrainData[ip] -> Branch("fdEdx", fdEdx, Form("fdEdx[%d]/F", AliTRDpidUtil::kNNslices)); | |
102 | fTrainData[ip] -> Branch("fPID", fPID, Form("fPID[%d]/F", AliPID::kSPECIES)); | |
103 | fTrainData[ip] -> Branch("fLy", &fLy, "fLy/I"); | |
104 | fTrainData[ip] -> Branch("fNtrkl", &fNtrkl, "fNtrkl/I"); | |
105 | ||
106 | fTrain[ip] = new TEventList(Form("fTrainMom%d", ip), Form("Training list for momentum intervall %d", ip)); | |
107 | fTest[ip] = new TEventList(Form("fTestMom%d", ip), Form("Test list for momentum intervall %d", ip)); | |
108 | } | |
1ee39b3a | 109 | |
1ee39b3a | 110 | } |
111 | ||
112 | ||
113 | ||
114 | //________________________________________________________________________ | |
115 | Bool_t AliTRDpidRefMakerNN::PostProcess() | |
116 | { | |
117 | // Draw result to the screen | |
118 | // Called once at the end of the query | |
119 | ||
9ec5bce7 | 120 | TFile *fCalib = TFile::Open(Form("TRD.CalibPIDrefMaker.root")); |
121 | if (!fCalib) { | |
122 | AliError("Calibration file not available"); | |
123 | return kFALSE; | |
124 | } | |
125 | fData = (TTree*)fCalib->Get("PIDrefMaker"); | |
126 | if (!fData) { | |
127 | AliError("Calibration data not available"); | |
128 | return kFALSE; | |
129 | } | |
130 | TObjArray *o = 0x0; | |
131 | if(!(o = (TObjArray*)fCalib->Get(Form("MoniPIDrefMaker")))){ | |
132 | AliWarning("Missing monitoring container."); | |
133 | return kFALSE; | |
134 | } | |
135 | fContainer = (TObjArray*)o->Clone("monitor"); | |
136 | ||
137 | ||
138 | if (!fRef) { | |
139 | AliDebug(2, Form("Loading file %s", Form("TRD.Calib%s.root", GetName()))); | |
140 | LoadFile(Form("TRD.Calib%s.root", GetName())); | |
141 | } | |
142 | else AliDebug(2, "file available"); | |
143 | ||
144 | if (!fRef) { | |
145 | CreateOutputObjects(); | |
146 | ||
147 | // Convert the CaliPIDrefMaker tree to 11 (different momentum bin) trees for NN training | |
148 | ||
149 | LinkPIDdata(); | |
150 | for(Int_t ip=0; ip < AliTRDCalPID::kNMom; ip++){ | |
151 | for(Int_t is=0; is < AliPID::kSPECIES; is++) { | |
152 | memset(fPID, 0, AliPID::kSPECIES*sizeof(Float_t)); | |
153 | fPID[is] = 1; | |
154 | Int_t n(0); // index of data | |
155 | for(Int_t itrk = 0; itrk<fData->GetEntries() && n<kMaxStat; itrk++){ | |
156 | if(!(fData->GetEntry(itrk))) continue; | |
157 | if(fPIDbin!=is) continue; | |
158 | for(Int_t ily=fPIDdataArray->fNtracklets; ily--;){ | |
159 | fLy = ily; | |
160 | fNtrkl = fPIDdataArray->fNtracklets; | |
161 | if((fPIDdataArray->fData[ily].fPLbin & 0xf)!= ip) continue; | |
162 | memset(fdEdx, 0, AliTRDpidUtil::kNNslices*sizeof(Float_t)); | |
163 | for(Int_t islice=AliTRDCalPID::kNSlicesNN; islice--;){ | |
164 | fdEdx[islice]+=fPIDdataArray->fData[ily].fdEdx[islice]; | |
165 | fdEdx[islice]/=fScale; | |
166 | } | |
167 | fTrainData[ip] -> Fill(); | |
168 | n++; | |
169 | } | |
170 | } | |
171 | AliDebug(2, Form("%d %d %d", ip, is, n)); | |
172 | } | |
173 | } | |
174 | ||
175 | ||
176 | fRef -> cd(); | |
177 | for(Int_t ip = 0; ip < AliTRDCalPID::kNMom; ip++){ | |
178 | fTrainData[ip] -> Write(); | |
179 | } | |
180 | ||
181 | } | |
182 | else AliDebug(2, "file available"); | |
183 | ||
184 | ||
185 | // build the training and the test list for the neural networks | |
186 | for(Int_t ip = 0; ip < AliTRDCalPID::kNMom; ip++){ | |
187 | MakeTrainingLists(ip); | |
188 | } | |
1ee39b3a | 189 | if(!fDoTraining) return kTRUE; |
190 | ||
9ec5bce7 | 191 | |
192 | ||
193 | // train the neural networks | |
1ee39b3a | 194 | gSystem->Exec(Form("mkdir ./Networks_%d/",fDate)); |
195 | AliDebug(2, Form("TrainMomBin [%d] [%d]", fTrainMomBin, kAll)); | |
196 | ||
197 | // train single network for a single momentum (recommended) | |
198 | if(!(fTrainMomBin == kAll)){ | |
9ec5bce7 | 199 | if(fTrain[fTrainMomBin] -> GetN() < fMinTrain){ |
200 | AliError("Warning in AliTRDpidRefMakerNN::PostProcess : Not enough events for training available! Please check Data sample!"); | |
1ee39b3a | 201 | return kFALSE; |
202 | } | |
203 | MakeRefs(fTrainMomBin); | |
1ee39b3a | 204 | MonitorTraining(fTrainMomBin); |
205 | } | |
206 | // train all momenta | |
207 | else{ | |
208 | for(Int_t iMomBin = 0; iMomBin < AliTRDCalPID::kNMom; iMomBin++){ | |
9ec5bce7 | 209 | if(fTrain[iMomBin] -> GetN() < fMinTrain){ |
210 | AliError(Form("Warning in AliTRDpidRefMakerNN::PostProcess : Not enough events for training available for momentum bin [%d]! Please check Data sample!", iMomBin)); | |
211 | continue; | |
1ee39b3a | 212 | } |
213 | MakeRefs(fTrainMomBin); | |
1ee39b3a | 214 | MonitorTraining(iMomBin); |
215 | } | |
216 | } | |
217 | ||
218 | return kTRUE; // testing protection | |
219 | } | |
220 | ||
221 | ||
222 | //________________________________________________________________________ | |
9ec5bce7 | 223 | void AliTRDpidRefMakerNN::MakeTrainingLists(Int_t mombin) |
1ee39b3a | 224 | { |
225 | // | |
226 | // build the training lists for the neural networks | |
227 | // | |
228 | ||
9ec5bce7 | 229 | if (!fRef) { |
230 | LoadFile(Form("TRD.Calib%s.root", GetName())); | |
1ee39b3a | 231 | } |
232 | ||
9ec5bce7 | 233 | if (!fRef) { |
234 | AliError("ERROR file for building training list not available"); | |
1ee39b3a | 235 | return; |
236 | } | |
237 | ||
9ec5bce7 | 238 | AliDebug(2, "\n Making training lists! \n"); |
1ee39b3a | 239 | |
9ec5bce7 | 240 | Int_t nPart[AliPID::kSPECIES]; |
241 | memset(nPart, 0, AliPID::kSPECIES*sizeof(Int_t)); | |
1ee39b3a | 242 | |
243 | // set needed branches | |
9ec5bce7 | 244 | fTrainData[mombin] -> SetBranchAddress("fdEdx", fdEdx); |
245 | fTrainData[mombin] -> SetBranchAddress("fPID", fPID); | |
246 | fTrainData[mombin] -> SetBranchAddress("fLy", &fLy); | |
247 | fTrainData[mombin] -> SetBranchAddress("fNtrkl", &fNtrkl); | |
248 | ||
1ee39b3a | 249 | // start first loop to check total number of each particle type |
9ec5bce7 | 250 | for(Int_t iEv=0; iEv < fTrainData[mombin] -> GetEntries(); iEv++){ |
251 | fTrainData[mombin] -> GetEntry(iEv); | |
1ee39b3a | 252 | |
253 | // use only events with goes through 6 layers TRD | |
9ec5bce7 | 254 | if(fNtrkl != AliTRDgeometry::kNlayer) continue; |
255 | ||
256 | if(fPID[AliPID::kElectron] == 1) | |
257 | nPart[AliPID::kElectron]++; | |
258 | else if(fPID[AliPID::kMuon] == 1) | |
259 | nPart[AliPID::kMuon]++; | |
260 | else if(fPID[AliPID::kPion] == 1) | |
261 | nPart[AliPID::kPion]++; | |
262 | else if(fPID[AliPID::kKaon] == 1) | |
263 | nPart[AliPID::kKaon]++; | |
264 | else if(fPID[AliPID::kProton] == 1) | |
265 | nPart[AliPID::kProton]++; | |
1ee39b3a | 266 | } |
267 | ||
268 | AliDebug(2, "Particle multiplicities:"); | |
9ec5bce7 | 269 | AliDebug(2, Form("Momentum[%d] Elecs[%d] Muons[%d] Pions[%d] Kaons[%d] Protons[%d]", mombin, nPart[AliPID::kElectron], nPart[AliPID::kMuon], nPart[AliPID::kPion], nPart[AliPID::kKaon], nPart[AliPID::kProton])); |
270 | ||
271 | ||
1ee39b3a | 272 | |
9ec5bce7 | 273 | // // implement counter of training and test sample size |
274 | Int_t iTrain = 0, iTest = 0; | |
1ee39b3a | 275 | |
276 | // set training sample size per momentum interval to 2/3 | |
277 | // of smallest particle counter and test sample to 1/3 | |
9ec5bce7 | 278 | iTrain = nPart[0]; |
279 | for(Int_t iPart = 1; iPart < AliPID::kSPECIES; iPart++){ | |
280 | // exclude muons and kaons if not availyable | |
281 | // this is neeeded since we do not have v0 candiates | |
282 | if((iPart == AliPID::kMuon || iPart == AliPID::kKaon) && (nPart[AliPID::kMuon] == 0 || nPart[AliPID::kKaon] == 0)) continue; | |
283 | if(iTrain > nPart[iPart]) | |
284 | iTrain = nPart[iPart]; | |
285 | } | |
286 | iTest = Int_t( iTrain * (1-fFreq)); | |
287 | iTrain = Int_t(iTrain * fFreq); | |
288 | AliDebug(2, Form("Momentum[%d] Train[%d] Test[%d]", mombin, iTrain, iTest)); | |
289 | ||
1ee39b3a | 290 | |
291 | ||
292 | // reset couters | |
9ec5bce7 | 293 | memset(nPart, 0, AliPID::kSPECIES*sizeof(Int_t)); |
1ee39b3a | 294 | |
295 | // start second loop to set the event lists | |
9ec5bce7 | 296 | for(Int_t iEv = 0; iEv < fTrainData[mombin] -> GetEntries(); iEv++){ |
297 | fTrainData[mombin] -> GetEntry(iEv); | |
298 | ||
299 | // set event list | |
300 | for(Int_t is = 0; is < AliPID::kSPECIES; is++){ | |
301 | if(nPart[is] < iTrain && fPID[is] == 1){ | |
302 | fTrain[mombin] -> Enter(iEv); | |
303 | nPart[is]++; | |
304 | } else if(nPart[is] < iTest+iTrain && fPID[is] == 1){ | |
305 | fTest[mombin] -> Enter(iEv); | |
306 | nPart[is]++; | |
1ee39b3a | 307 | } else continue; |
308 | } | |
309 | } | |
310 | ||
311 | AliDebug(2, "Particle multiplicities in both lists:"); | |
9ec5bce7 | 312 | AliDebug(2, Form("Momentum[%d] Elecs[%d] Muons[%d] Pions[%d] Kaons[%d] Protons[%d]", mombin, nPart[AliPID::kElectron], nPart[AliPID::kMuon], nPart[AliPID::kPion], nPart[AliPID::kKaon], nPart[AliPID::kProton])); |
313 | ||
314 | return; | |
1ee39b3a | 315 | } |
316 | ||
317 | ||
318 | //________________________________________________________________________ | |
319 | void AliTRDpidRefMakerNN::MakeRefs(Int_t mombin) | |
320 | { | |
321 | // | |
322 | // train the neural networks | |
323 | // | |
324 | ||
325 | ||
9ec5bce7 | 326 | if (!fTrainData[mombin]) LoadFile(Form("TRD.Calib%s.root", GetName())); |
1ee39b3a | 327 | |
9ec5bce7 | 328 | if (!fTrainData[mombin]) { |
1ee39b3a | 329 | AliError("Tree for training list not available"); |
330 | return; | |
331 | } | |
332 | ||
333 | TDatime datime; | |
334 | fDate = datime.GetDate(); | |
335 | ||
336 | AliDebug(2, Form("Training momentum bin %d", mombin)); | |
337 | ||
338 | // set variable to monitor the training and to save the development of the networks | |
339 | Int_t nEpochs = fEpochs/kMoniTrain; | |
340 | AliDebug(2, Form("Training %d times %d epochs", kMoniTrain, nEpochs)); | |
341 | ||
342 | // make directories to save the networks | |
343 | gSystem->Exec(Form("rm -r ./Networks_%d/MomBin_%d",fDate, mombin)); | |
344 | gSystem->Exec(Form("mkdir ./Networks_%d/MomBin_%d",fDate, mombin)); | |
345 | ||
346 | // variable to check if network can load weights from previous training | |
9ec5bce7 | 347 | Bool_t bFirstLoop = kTRUE; |
1ee39b3a | 348 | |
349 | // train networks over several loops and save them after each loop | |
350 | for(Int_t iLoop = 0; iLoop < kMoniTrain; iLoop++){ | |
9ec5bce7 | 351 | fTrainData[mombin] -> SetEventList(fTrain[mombin]); |
352 | fTrainData[mombin] -> SetEventList(fTest[mombin]); | |
1ee39b3a | 353 | |
9ec5bce7 | 354 | AliDebug(2, Form("Momentum[%d] Trainingloop[%d]", mombin, iLoop)); |
1ee39b3a | 355 | |
9ec5bce7 | 356 | // check if network is already implemented |
357 | if(bFirstLoop == kTRUE){ | |
358 | fNet = new TMultiLayerPerceptron("fdEdx[0],fdEdx[1],fdEdx[2],fdEdx[3],fdEdx[4],fdEdx[5],fdEdx[6],fdEdx[7]:15:7:fPID[0],fPID[1],fPID[2],fPID[3],fPID[4]!",fTrainData[mombin],fTrain[mombin],fTest[mombin]); | |
359 | fNet -> SetLearningMethod(TMultiLayerPerceptron::kStochastic); // set learning method | |
360 | fNet -> TMultiLayerPerceptron::SetEta(0.001); // set learning speed | |
361 | if(!fContinueTraining){ | |
362 | if(AliLog::GetDebugLevel("","AliTRDpidRefMakerNN")>=2) fNet -> Train(nEpochs,"text update=10, graph"); | |
363 | else fNet -> Train(nEpochs,""); | |
1ee39b3a | 364 | } |
9ec5bce7 | 365 | else{ |
366 | fNet -> LoadWeights(Form("./Networks_%d/MomBin_%d/Net_%d",fTrainPath, mombin, kMoniTrain - 1)); | |
367 | if(AliLog::GetDebugLevel("","AliTRDpidRefMakerNN")>=2) fNet -> Train(nEpochs,"text update=10, graph+"); | |
368 | else fNet -> Train(nEpochs,"+"); | |
1ee39b3a | 369 | } |
9ec5bce7 | 370 | bFirstLoop = kFALSE; |
371 | } | |
372 | else{ | |
373 | if(AliLog::GetDebugLevel("","AliTRDpidRefMakerNN")>=2) fNet -> Train(nEpochs,"text update=10, graph+"); | |
374 | else fNet -> Train(nEpochs,"+"); | |
375 | } | |
1ee39b3a | 376 | |
9ec5bce7 | 377 | // save weights for monitoring of the training |
378 | fNet -> DumpWeights(Form("./Networks_%d/MomBin_%d/Net_%d",fDate, mombin, iLoop)); | |
1ee39b3a | 379 | } // end training loop |
380 | } | |
381 | ||
382 | ||
383 | ||
384 | //________________________________________________________________________ | |
385 | void AliTRDpidRefMakerNN::MonitorTraining(Int_t mombin) | |
386 | { | |
387 | // | |
388 | // train the neural networks | |
389 | // | |
390 | ||
9ec5bce7 | 391 | if (!fTrainData[mombin]) LoadFile(Form("TRD.Calib%s.root", GetName())); |
392 | if (!fTrainData[mombin]) { | |
1ee39b3a | 393 | AliError("Tree for training list not available"); |
394 | return; | |
395 | } | |
396 | ||
397 | // init networks and set event list | |
398 | for(Int_t iChamb = 0; iChamb < AliTRDgeometry::kNlayer; iChamb++){ | |
9ec5bce7 | 399 | fNet = new TMultiLayerPerceptron("fdEdx[0],fdEdx[1],fdEdx[2],fdEdx[3],fdEdx[4],fdEdx[5],fdEdx[6],fdEdx[7]:15:7:fPID[0],fPID[1],fPID[2],fPID[3],fPID[4]!",fTrainData[mombin],fTrain[mombin],fTest[mombin]); |
400 | fTrainData[mombin] -> SetEventList(fTrain[mombin]); | |
401 | fTrainData[mombin] -> SetEventList(fTest[mombin]); | |
1ee39b3a | 402 | } |
403 | ||
404 | // implement variables for likelihoods | |
405 | Float_t like[AliPID::kSPECIES][AliTRDgeometry::kNlayer]; | |
406 | memset(like, 0, AliPID::kSPECIES*AliTRDgeometry::kNlayer*sizeof(Float_t)); | |
407 | Float_t likeAll[AliPID::kSPECIES], totProb; | |
408 | ||
409 | Double_t pionEffiTrain[kMoniTrain], pionEffiErrTrain[kMoniTrain]; | |
410 | Double_t pionEffiTest[kMoniTrain], pionEffiErrTest[kMoniTrain]; | |
411 | memset(pionEffiTrain, 0, kMoniTrain*sizeof(Double_t)); | |
412 | memset(pionEffiErrTrain, 0, kMoniTrain*sizeof(Double_t)); | |
413 | memset(pionEffiTest, 0, kMoniTrain*sizeof(Double_t)); | |
414 | memset(pionEffiErrTest, 0, kMoniTrain*sizeof(Double_t)); | |
415 | ||
416 | // init histos | |
417 | const Float_t epsilon = 1/(2*(AliTRDpidUtil::kBins-1)); // get nice histos with bin center at 0 and 1 | |
418 | TH1F *hElecs, *hPions; | |
419 | hElecs = new TH1F("hElecs","Likelihood for electrons", AliTRDpidUtil::kBins, 0.-epsilon, 1.+epsilon); | |
420 | hPions = new TH1F("hPions","Likelihood for pions", AliTRDpidUtil::kBins, 0.-epsilon, 1.+epsilon); | |
421 | ||
9ec5bce7 | 422 | TGraphErrors *gEffisTrain = new TGraphErrors(kMoniTrain); |
423 | gEffisTrain -> SetLineColor(4); | |
424 | gEffisTrain -> SetMarkerColor(4); | |
425 | gEffisTrain -> SetMarkerStyle(29); | |
426 | gEffisTrain -> SetMarkerSize(1); | |
427 | ||
428 | TGraphErrors *gEffisTest = new TGraphErrors(kMoniTrain); | |
429 | gEffisTest -> SetLineColor(2); | |
430 | gEffisTest -> SetMarkerColor(2); | |
431 | gEffisTest -> SetMarkerStyle(29); | |
432 | gEffisTest -> SetMarkerSize(1); | |
1ee39b3a | 433 | |
434 | AliTRDpidUtil *util = new AliTRDpidUtil(); | |
435 | ||
436 | // monitor training progress | |
437 | for(Int_t iLoop = 0; iLoop < kMoniTrain; iLoop++){ | |
438 | ||
439 | // load weights | |
9ec5bce7 | 440 | fNet -> LoadWeights(Form("./Networks_%d/MomBin_%d/Net_%d",fDate, mombin, iLoop)); |
441 | AliDebug(2, Form("./Networks_%d/MomBin_%d/Net_%d",fDate, mombin, iLoop)); | |
1ee39b3a | 442 | |
443 | // event loop training list | |
1ee39b3a | 444 | |
9ec5bce7 | 445 | for(Int_t is = 0; is < AliPID::kSPECIES; is++){ |
1ee39b3a | 446 | |
9ec5bce7 | 447 | if(!((is == AliPID::kElectron) || (is == AliPID::kPion))) continue; |
1ee39b3a | 448 | |
9ec5bce7 | 449 | Int_t iChamb = 0; |
450 | // reset particle probabilities | |
1ee39b3a | 451 | for(Int_t iPart = 0; iPart < AliPID::kSPECIES; iPart++){ |
9ec5bce7 | 452 | likeAll[iPart] = 1./AliPID::kSPECIES; |
1ee39b3a | 453 | } |
9ec5bce7 | 454 | totProb = 0.; |
1ee39b3a | 455 | |
9ec5bce7 | 456 | AliDebug(2, Form("%d",fTrain[mombin] -> GetN())); |
457 | for(Int_t iEvent = 0; iEvent < fTrain[mombin] -> GetN(); iEvent++ ){ | |
458 | fTrainData[mombin] -> GetEntry(fTrain[mombin] -> GetEntry(iEvent)); | |
459 | // use event only if it is electron or pion | |
460 | if(!(fPID[is] == 1.0)) continue; | |
461 | // get the probabilities for each particle type in each chamber | |
462 | for(Int_t iPart = 0; iPart < AliPID::kSPECIES; iPart++){ | |
463 | like[iPart][iChamb] = fNet -> Result(fTrain[mombin] -> GetEntry(iEvent), iPart); | |
464 | likeAll[iPart] *= like[iPart][iChamb]; | |
465 | } | |
466 | //end chamber loop | |
467 | iChamb++; | |
468 | ||
469 | // get total probability and normalize it | |
470 | for(Int_t iPart = 0; iPart < AliPID::kSPECIES; iPart++){ | |
471 | totProb += likeAll[iPart]; | |
472 | } | |
473 | for(Int_t iPart = 0; iPart < AliPID::kSPECIES; iPart++){ | |
474 | likeAll[iPart] /= totProb; | |
475 | } | |
476 | ||
477 | if(iChamb == 5){ | |
478 | // fill likelihood distributions | |
479 | if(fPID[AliPID::kElectron] == 1) | |
480 | hElecs -> Fill(likeAll[AliPID::kElectron]); | |
481 | if(fPID[AliPID::kPion] == 1) | |
482 | hPions -> Fill(likeAll[AliPID::kElectron]); | |
483 | iChamb = 0; | |
484 | // reset particle probabilities | |
485 | for(Int_t iPart = 0; iPart < AliPID::kSPECIES; iPart++){ | |
486 | likeAll[iPart] = 1./AliPID::kSPECIES; | |
487 | } | |
488 | totProb = 0.; | |
489 | } | |
490 | } // end event loop | |
491 | } // end species loop | |
492 | ||
1ee39b3a | 493 | |
494 | // calculate the pion efficiency and fill the graph | |
495 | util -> CalculatePionEffi(hElecs, hPions); | |
496 | pionEffiTrain[iLoop] = util -> GetPionEfficiency(); | |
497 | pionEffiErrTrain[iLoop] = util -> GetError(); | |
498 | ||
499 | gEffisTrain -> SetPoint(iLoop, iLoop+1, pionEffiTrain[iLoop]); | |
500 | gEffisTrain -> SetPointError(iLoop, 0, pionEffiErrTrain[iLoop]); | |
501 | hElecs -> Reset(); | |
502 | hPions -> Reset(); | |
503 | AliDebug(2, Form("TrainingLoop[%d] PionEfficiency[%f +/- %f]", iLoop, pionEffiTrain[iLoop], pionEffiErrTrain[iLoop])); | |
504 | // end training loop | |
505 | ||
506 | ||
507 | ||
9ec5bce7 | 508 | // monitor validation progress |
509 | for(Int_t is = 0; is < AliPID::kSPECIES; is++){ | |
1ee39b3a | 510 | |
9ec5bce7 | 511 | if(!((is == AliPID::kElectron) || (is == AliPID::kPion))) continue; |
512 | ||
513 | Int_t iChamb = 0; | |
1ee39b3a | 514 | // reset particle probabilities |
515 | for(Int_t iPart = 0; iPart < AliPID::kSPECIES; iPart++){ | |
9ec5bce7 | 516 | likeAll[iPart] = 1./AliPID::kSPECIES; |
1ee39b3a | 517 | } |
518 | totProb = 0.; | |
519 | ||
9ec5bce7 | 520 | for(Int_t iEvent = 0; iEvent < fTest[mombin] -> GetN(); iEvent++ ){ |
521 | fTrainData[mombin] -> GetEntry(fTest[mombin] -> GetEntry(iEvent)); | |
522 | // use event only if it is electron or pion | |
523 | if(!(fPID[is] == 1.0)) continue; | |
524 | ||
525 | // get the probabilities for each particle type in each chamber | |
526 | for(Int_t iPart = 0; iPart < AliPID::kSPECIES; iPart++){ | |
527 | like[iPart][iChamb] = fNet -> Result(fTest[mombin] -> GetEntry(iEvent), iPart); | |
528 | likeAll[iPart] *= like[iPart][iChamb]; | |
529 | } | |
530 | iChamb++; | |
531 | ||
532 | // get total probability and normalize it | |
533 | for(Int_t iPart = 0; iPart < AliPID::kSPECIES; iPart++){ | |
534 | totProb += likeAll[iPart]; | |
535 | } | |
536 | for(Int_t iPart = 0; iPart < AliPID::kSPECIES; iPart++){ | |
537 | likeAll[iPart] /= totProb; | |
538 | } | |
539 | ||
540 | if(iChamb == 5){ | |
541 | // fill likelihood distributions | |
542 | if(fPID[AliPID::kElectron] == 1) | |
543 | hElecs -> Fill(likeAll[AliPID::kElectron]); | |
544 | if(fPID[AliPID::kPion] == 1) | |
545 | hPions -> Fill(likeAll[AliPID::kElectron]); | |
546 | iChamb = 0; | |
547 | // reset particle probabilities | |
548 | for(Int_t iPart = 0; iPart < AliPID::kSPECIES; iPart++){ | |
549 | likeAll[iPart] = 1./AliPID::kSPECIES; | |
550 | } | |
551 | totProb = 0.; | |
552 | } | |
553 | } // end event loop | |
554 | } // end species loop | |
555 | ||
1ee39b3a | 556 | // calculate the pion efficiency and fill the graph |
557 | util -> CalculatePionEffi(hElecs, hPions); | |
558 | pionEffiTest[iLoop] = util -> GetPionEfficiency(); | |
559 | pionEffiErrTest[iLoop] = util -> GetError(); | |
560 | ||
561 | gEffisTest -> SetPoint(iLoop, iLoop+1, pionEffiTest[iLoop]); | |
562 | gEffisTest -> SetPointError(iLoop, 0, pionEffiErrTest[iLoop]); | |
563 | hElecs -> Reset(); | |
564 | hPions -> Reset(); | |
565 | AliDebug(2, Form("TestLoop[%d] PionEfficiency[%f +/- %f] \n", iLoop, pionEffiTest[iLoop], pionEffiErrTest[iLoop])); | |
566 | ||
9ec5bce7 | 567 | } // end validation loop |
1ee39b3a | 568 | |
569 | util -> Delete(); | |
570 | ||
571 | gEffisTest -> Draw("PAL"); | |
572 | gEffisTrain -> Draw("PL"); | |
573 | ||
574 | } | |
575 | ||
576 | ||
577 | //________________________________________________________________________ | |
9ec5bce7 | 578 | Bool_t AliTRDpidRefMakerNN::LoadFile(const Char_t *InFileNN) |
1ee39b3a | 579 | { |
580 | // | |
581 | // Loads the files and sets the event list | |
9ec5bce7 | 582 | // for neural network training. |
1ee39b3a | 583 | // Useable for training outside of the makeResults.C macro |
584 | // | |
585 | ||
9ec5bce7 | 586 | fRef = TFile::Open(Form("%s", InFileNN)); |
587 | if(!fRef) return 0; | |
588 | for(Int_t ip = 0; ip < AliTRDCalPID::kNMom; ip++){ | |
589 | fTrainData[ip] = (TTree*)fRef -> Get(Form("fTrainData_%d", ip)); | |
590 | } | |
1ee39b3a | 591 | |
592 | for(Int_t iMom = 0; iMom < AliTRDCalPID::kNMom; iMom++){ | |
9ec5bce7 | 593 | fTrain[iMom] = new TEventList(Form("fTrainMom%d", iMom), Form("Training list for momentum intervall %d", iMom)); |
594 | fTest[iMom] = new TEventList(Form("fTestMom%d", iMom), Form("Test list for momentum intervall %d", iMom)); | |
1ee39b3a | 595 | } |
9ec5bce7 | 596 | return 1; |
1ee39b3a | 597 | } |
598 | ||
599 |