1 /**************************************************************************
2 * Copyright(c) 1998-1999, ALICE Experiment at CERN, All rights reserved. *
4 * Author: The ALICE Off-line Project. *
5 * Contributors are mentioned in the code where appropriate. *
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 **************************************************************************/
16 /* $Id: AliTRDclusterResolution.cxx */
18 ///////////////////////////////////////////////////////////////////////////////
20 // TRD cluster error parameterization //
22 // This class is designed to produce the reference plots for a detailed study//
23 // and parameterization of TRD cluster errors. The following effects are taken//
25 // - dependence with the total charge of the cluster //
26 // - dependence with the distance from the center pad. This is monitored
27 // for each layer individually since the pad size varies with layer
28 // - dependence with the drift length - here the influence of anisochronity
29 // and diffusion are searched
30 // - dependence with the distance to the anode wire - anisochronity effects
31 // - dependence with track angle (for y resolution)
32 // The correlation between effects is taken into account.
34 // Since magnetic field plays a very important role in the TRD measurement
35 // the ExB correction is forced by the setter function SetExB(Int_t). The
36 // argument is the detector index, if none is specified all will be
39 // Two cases are of big importance.
40 // - comparison with MC
41 // - comparison with Kalman fit. In this case the covariance matrix of the
42 // Kalman fit are needed.
44 // The functionalities implemented in this class are based on the storage
45 // class AliTRDclusterInfo.
50 // The method to disentangle s_y and s_x is based on the relation (see also fig.)
52 // #sigma^{2} = #sigma^{2}_{y} + tg^{2}(#alpha_{L})*#sigma^{2}_{x_{d}} + tg^{2}(#phi-#alpha_{L})*(#sigma^{2}_{x_{d}}+#sigma^{2}_{x_{c}})
56 // #sigma^{2}_{x_{c}} #approx 0
58 // we suppose the chamber is well calibrated for t_{0} and aligned in
61 // Clusters can be radially shifted due to three causes:
62 // - globally shifted - due to residual misalignment/miscalibration(t0)
63 // - locally shifted - due to different local drift velocity from the mean
64 // - randomly shifted - due to neighboring (radial direction) clusters
65 // charge induced by asymmetry of the TRF.
67 // We estimate this effects by the relations:
69 // #mu_{y} = tg(#alpha_{L})*#Delta x_{d}(...) + tg(#phi-#alpha_{L})*(#Delta x_{c}(...) + #Delta x_{d}(...))
73 // #Delta x_{d}(...) = (<v_{d}> + #delta v_{d}(x_{d}, d)) * (t + t^{*}(Q))
75 // and we specified explicitely the variation of drift velocity parallel
76 // with the track (x_{d}) and perpendicular to it due to anisochronity (d).
78 // For estimating the contribution from asymmetry of TRF the following
79 // parameterization is being used
81 // t^{*}(Q) = #delta_{0} * #frac{Q_{t+1} - Q_{t-1}}{Q_{t-1} + Q_{t} + Q_{t+1}}
85 // Clusters can also be r-phi shifted due to:
86 // - wrong PRF or wrong cuts at digits level
87 //The following correction is applied :
89 // <#Delta y> = a + b * sin(c*y_{pw})
94 // Parameterization against total charge
96 // Obtained for B=0T at phi=0. All other effects integrated out.
98 // #sigma^{2}_{y}(Q) = #sigma^{2}_{y}(...) + b(#frac{1}{Q} - #frac{1}{Q_{0}})
100 // For B diff 0T the error of the average ExB correction error has to be subtracted !!
102 // Parameterization Sx
104 // The parameterization of the error in the x direction can be written as
106 // #sigma_{x} = #sigma_{x}^{||} + #sigma_{x}^{#perp}
109 // where the parallel component is given mainly by the TRF width while
110 // the perpendicular component by the anisochronity. The model employed for
111 // the parallel is gaus(0)+expo(3) with the following parameters
112 // 1 C 5.49018e-01 1.23854e+00 3.84540e-04 -8.21084e-06
113 // 2 M 7.82999e-01 6.22531e-01 2.71272e-04 -6.88485e-05
114 // 3 S 2.74451e-01 1.13815e+00 2.90667e-04 1.13493e-05
115 // 4 E1 2.53596e-01 1.08646e+00 9.95591e-05 -2.11625e-05
116 // 5 E2 -2.40078e-02 4.26520e-01 4.67153e-05 -2.35392e-04
118 // and perpendicular to the track is pol2 with the parameters
120 // Par_0 = 0.190676 +/- 0.41785
121 // Par_1 = -3.9269 +/- 7.49862
122 // Par_2 = 14.7851 +/- 27.8012
124 // Parameterization Sy
126 // The parameterization of the error in the y direction along track uses
128 // #sigma_{y}^{||} = #sigma_{y}^{0} -a*exp(1/(x-b))
131 // with following values for the parameters:
132 // 1 sy0 2.60967e-01 2.99652e-03 7.82902e-06 -1.89636e-04
133 // 2 a -7.68941e+00 1.87883e+00 3.84539e-04 9.38268e-07
134 // 3 b -3.41160e-01 7.72850e-02 1.63231e-05 2.51602e-05
136 //==========================================================================
137 // Example how to retrive reference plots from the task
138 // void steerClErrParam(Int_t fig=0)
140 // gSystem->Load("libANALYSIS.so");
141 // gSystem->Load("libTRDqaRec.so");
143 // // initialize DB manager
144 // AliCDBManager *cdb = AliCDBManager::Instance();
145 // cdb->SetDefaultStorage("local://$ALICE_ROOT/OCDB");
147 // // initialize magnetic field.
148 // AliMagFCheb *field=new AliMagFCheb("Maps","Maps", 2, 1., 10., AliMagFCheb::k5kG);
149 // AliTracker::SetFieldMap(field, kTRUE);
151 // AliTRDclusterResolution *res = new AliTRDclusterResolution();
153 // res->Load("TRD.TaskClErrParam.root");
156 // //res->SetSaveAs();
157 // res->SetProcessCharge(kFALSE);
158 // res->SetProcessCenterPad(kFALSE);
159 // //res->SetProcessMean(kFALSE);
160 // res->SetProcessSigma(kFALSE);
161 // if(!res->PostProcess()) return;
163 // res->GetRefFigure(fig);
167 // Alexandru Bercuci <A.Bercuci@gsi.de> //
168 ////////////////////////////////////////////////////////////////////////////
170 #include "AliTRDclusterResolution.h"
171 #include "info/AliTRDclusterInfo.h"
172 #include "AliTRDgeometry.h"
173 #include "AliTRDpadPlane.h"
174 #include "AliTRDcluster.h"
175 #include "AliTRDseedV1.h"
176 #include "AliTRDcalibDB.h"
177 #include "AliTRDCommonParam.h"
178 #include "Cal/AliTRDCalROC.h"
179 #include "Cal/AliTRDCalDet.h"
181 #include "AliESDEvent.h"
182 #include "AliCDBManager.h"
185 #include "TObjArray.h"
189 #include "TGraphErrors.h"
195 #include "TLinearFitter.h"
196 #include "TGeoGlobalMagField.h"
201 ClassImp(AliTRDclusterResolution)
203 const Float_t AliTRDclusterResolution::fgkTimeBinLength = 1./ AliTRDCommonParam::Instance()->GetSamplingFrequency();
204 //_______________________________________________________
205 AliTRDclusterResolution::AliTRDclusterResolution()
226 SetNameTitle("ClErrCalib", "Cluster Error Parameterization");
227 memset(fR, 0, 4*sizeof(Float_t));
228 memset(fP, 0, 4*sizeof(Float_t));
231 //_______________________________________________________
232 AliTRDclusterResolution::AliTRDclusterResolution(const char *name)
233 : AliTRDrecoTask(name, "Cluster Error Parameterization")
254 memset(fR, 0, 4*sizeof(Float_t));
255 memset(fP, 0, 4*sizeof(Float_t));
257 // By default register all analysis
258 // The user can switch them off in his steering macro
265 //_______________________________________________________
266 AliTRDclusterResolution::~AliTRDclusterResolution()
270 if(fCanvas) delete fCanvas;
277 //_______________________________________________________
278 void AliTRDclusterResolution::UserCreateOutputObjects()
280 fContainer = Histos();
281 PostData(1, fContainer);
284 //_______________________________________________________
285 Bool_t AliTRDclusterResolution::GetRefFigure(Int_t ifig)
287 // Steering function to retrieve performance plots
289 if(!fResults) return kFALSE;
292 TObjArray *arr = NULL;
294 TH2 *h2 = NULL;TH1 *h1 = NULL;
295 TGraphErrors *gm(NULL), *gs(NULL), *gp(NULL);
298 if(!(arr = (TObjArray*)fResults->At(kQRes))) break;
299 if(!(gm = (TGraphErrors*)arr->At(0))) break;
300 if(!(gs = (TGraphErrors*)arr->At(1))) break;
301 if(!(gp = (TGraphErrors*)arr->At(2))) break;
302 leg= new TLegend(.7, .7, .9, .95);
303 leg->SetBorderSize(0); leg->SetFillColor(0); leg->SetFillStyle(0);
304 gs->Draw("apl"); leg->AddEntry(gs, "Sigma / Resolution", "pl");
305 gs->GetHistogram()->GetYaxis()->SetRangeUser(-50., 700.);
306 gs->GetHistogram()->SetXTitle("Q [a.u.]");
307 gs->GetHistogram()->SetYTitle("y - x tg(#alpha_{L}) [#mum]");
308 gm->Draw("pl");leg->AddEntry(gm, "Mean / Systematics", "pl");
309 gp->Draw("pl");leg->AddEntry(gp, "Abundance / Probability", "pl");
313 if(!(arr = (TObjArray*)fResults->At(kCenter))) break;
314 gPad->Divide(2, 1); l = gPad->GetListOfPrimitives();
315 ((TVirtualPad*)l->At(0))->cd();
316 ((TTree*)arr->At(0))->Draw(Form("y:t>>h(%d, -0.5, %f, 51, -.51, .51)",AliTRDseedV1::kNtb, AliTRDseedV1::kNtb-0.5),
317 "m[0]*(ly==0&&abs(m[0])<1.e-1)", "colz");
318 ((TVirtualPad*)l->At(1))->cd();
319 leg= new TLegend(.7, .7, .9, .95);
320 leg->SetBorderSize(0); leg->SetFillColor(0); leg->SetFillStyle(0);
321 leg->SetHeader("TRD Plane");
322 for(Int_t il = 1; il<=AliTRDgeometry::kNlayer; il++){
323 if(!(gm = (TGraphErrors*)arr->At(il))) return kFALSE;
324 gm->Draw(il>1?"pc":"apc"); leg->AddEntry(gm, Form("%d", il-1), "pl");
326 gm->GetHistogram()->SetXTitle("t_{drift} [tb]");
327 gm->GetHistogram()->SetYTitle("#sigma_{y}(x|cen=0) [#mum]");
328 gm->GetHistogram()->GetYaxis()->SetRangeUser(150., 500.);
333 if(!(t = (TTree*)fResults->At(kSigm))) break;
334 t->Draw("z:t>>h2x(23, 0.1, 2.4, 25, 0., 2.5)","sx*(1)", "lego2fb");
335 h2 = (TH2F*)gROOT->FindObject("h2x");
336 printf(" const Double_t sx[24][25]={\n");
337 for(Int_t ix=1; ix<=h2->GetNbinsX(); ix++){
339 for(Int_t iy=1; iy<h2->GetNbinsY(); iy++){
340 printf("%6.4f ", h2->GetBinContent(ix, iy));
342 printf("%6.4f},\n", h2->GetBinContent(ix, h2->GetNbinsY()));
345 gPad->Divide(2, 1, 1.e-5, 1.e-5); l = gPad->GetListOfPrimitives();
346 ((TVirtualPad*)l->At(0))->cd();
347 h1 = h2->ProjectionX("hsx_pxx"); h1->Scale(1.e4/kND); h1->SetMarkerStyle(24);
348 h1->SetYTitle("<#sigma_{x}> [#mum]");
349 h1->SetXTitle("t_{drift} [#mus]");
350 h1->GetXaxis()->SetRange(2, AliTRDseedV1::kNtb-1); h1->Draw("pc");
352 t->Draw("z:t>>h2y(23, 0.1, 2.4, 25, 0., 2.5)","sy*(1)", "lego2fb");
353 h2 = (TH2F*)gROOT->FindObject("h2y");
354 printf(" const Double_t sy[24][25]={\n");
355 for(Int_t ix=1; ix<=h2->GetNbinsX(); ix++){
357 for(Int_t iy=1; iy<h2->GetNbinsY(); iy++){
358 printf("%6.4f ", h2->GetBinContent(ix, iy));
360 printf("%6.4f},\n", h2->GetBinContent(ix, h2->GetNbinsY()));
363 ((TVirtualPad*)l->At(1))->cd();
364 h1 = h2->ProjectionX("hsy_pxx"); h1->Scale(1.e4/kND); h1->SetMarkerStyle(24);
365 h1->SetYTitle("<#sigma_{y}> [#mum]");
366 h1->SetXTitle("t_{drift} [#mus]");
367 h1->GetXaxis()->SetRange(2, AliTRDseedV1::kNtb-1); h1->Draw("pc");
370 if(!(t = (TTree*)fResults->At(kMean))) break;
371 if(!t->Draw(Form("z:t>>h2x(%d, -0.5, %3.1f, %d, 0., 2.5)",
372 AliTRDseedV1::kNtb, AliTRDseedV1::kNtb-0.5, kND),
373 "dx*(1)", "goff")) break;
374 h2 = (TH2F*)gROOT->FindObject("h2x");
375 printf(" const Double_t dx[%d][%d]={\n", AliTRDseedV1::kNtb, kND);
376 for(Int_t ix=1; ix<=h2->GetNbinsX(); ix++){
378 for(Int_t iy=1; iy<h2->GetNbinsY(); iy++){
379 printf("%+6.4e, ", h2->GetBinContent(ix, iy));
381 printf("%+6.4e},\n", h2->GetBinContent(ix, h2->GetNbinsY()));
384 gPad->Divide(2, 2, 1.e-5, 1.e-5); l = gPad->GetListOfPrimitives();
385 ((TVirtualPad*)l->At(0))->cd();
387 ((TVirtualPad*)l->At(2))->cd();
388 h1 = h2->ProjectionX("hdx_pxx"); h1->Scale(1.e4/kND); h1->SetMarkerStyle(24);
389 h1->SetYTitle("<#deltax> [#mum]");
390 h1->SetXTitle("t_{drift} [tb]");
391 //h1->GetXaxis()->SetRange(2, AliTRDseedV1::kNtb-1);
394 if(!t->Draw(Form("z:t>>h2y(%d, -0.5, %3.1f, %d, 0., 2.5)",
395 AliTRDseedV1::kNtb, AliTRDseedV1::kNtb-0.5, kND),
396 "dy*(1)", "goff")) break;
397 h2 = (TH2F*)gROOT->FindObject("h2y");
398 printf(" const Double_t dy[%d][%d]={\n", AliTRDseedV1::kNtb, kND);
399 for(Int_t ix=1; ix<=h2->GetNbinsX(); ix++){
401 for(Int_t iy=1; iy<h2->GetNbinsY(); iy++){
402 printf("%+6.4e ", h2->GetBinContent(ix, iy));
404 printf("%+6.4e},\n", h2->GetBinContent(ix, h2->GetNbinsY()));
407 ((TVirtualPad*)l->At(1))->cd();
409 ((TVirtualPad*)l->At(3))->cd();
410 h1 = h2->ProjectionX("hdy_pxx"); h1->Scale(1.e4/kND); h1->SetMarkerStyle(24);
411 h1->SetYTitle("<#deltay> [#mum]");
412 h1->SetXTitle("t_{drift} [tb]");
413 //h1->GetXaxis()->SetRange(2, AliTRDseedV1::kNtb-1);
420 AliWarning("No container/data found.");
424 //_______________________________________________________
425 TObjArray* AliTRDclusterResolution::Histos()
427 // Retrieve histograms array if already build or build it
429 if(fContainer) return fContainer;
430 fContainer = new TObjArray(kNtasks);
431 //fContainer->SetOwner(kTRUE);
434 TObjArray *arr = NULL;
436 // add resolution/pulls plots for dydx=ExB
437 fContainer->AddAt(arr = new TObjArray(2), kCenter);
438 arr->SetName("Center");
439 if(!(h3=(TH3S*)gROOT->FindObject(Form("hCenRes%03d",fDet)))) {
441 Form("hCenRes%03d",fDet),
442 Form(" Det[%d] Col[%d] Row[%d];t [bin];y [pw];#Delta y[cm]", fDet, fCol, fRow),
443 AliTRDseedV1::kNtb, -.5, AliTRDseedV1::kNtb-0.5, // x
445 60, -fDyRange, fDyRange); // dy
448 // add Pull plot for each layer
449 if(!(h3=(TH3S*)gROOT->FindObject(Form("hCenPull%03d", fDet)))){
451 Form("hCenPull%03d", fDet),
452 Form(" Det[%d] Col[%d] Row[%d];t [bin];y [pw];#Delta y[cm]/#sigma_{y}", fDet, fCol, fRow),
453 AliTRDseedV1::kNtb, -0.5, AliTRDseedV1::kNtb-0.5, // x
455 60, -4., 4.); // dy/sy
459 if(!(h3 = (TH3S*)gROOT->FindObject(Form("Charge%03d", fDet)))){
460 h3 = new TH3S(Form("Charge%03d", fDet),
461 "dy=f(q);log(q) [a.u.];#Delta y[cm];#Delta y/#sigma_{y}",
462 50, 2.2, 7.5, 60, -fDyRange, fDyRange, 60, -4., 4.);
464 fContainer->AddAt(h3, kQRes);
466 fContainer->AddAt(arr = new TObjArray(AliTRDseedV1::kNtb), kSigm);
467 arr->SetName("Resolution");
468 for(Int_t it=0; it<AliTRDseedV1::kNtb; it++){
469 if(!(h3=(TH3S*)gROOT->FindObject(Form("hr%03d_t%02d", fDet, it)))){
471 Form("hr%03d_t%02d", fDet, it),
472 Form(" Det[%d] t_{drift}(%2d)[bin];z [mm];tg#phi;#Delta y[cm]", fDet, it),
474 35, -.35, .35, // tgp
475 60, -fDyRange, fDyRange); // dy
480 fContainer->AddAt(arr = new TObjArray(AliTRDseedV1::kNtb), kMean);
481 arr->SetName("Systematics");
482 for(Int_t it=0; it<AliTRDseedV1::kNtb; it++){
483 if(!(h3=(TH3S*)gROOT->FindObject(Form("hs%03d_t%02d", fDet, it)))){
485 Form("hs%03d_t%02d", fDet, it),
486 Form(" Det[%d] t_{drift}(%2d)[bin];z [mm];tg#phi - h*tg(#theta);#Delta y[cm]", fDet, it),
488 35, -.35, .35, // tgp-h tgt
489 60, -fDyRange, fDyRange); // dy
497 //_______________________________________________________
498 void AliTRDclusterResolution::UserExec(Option_t *)
500 // Fill container histograms
503 fInfo = dynamic_cast<TObjArray *>(GetInputData(1));
504 AliDebug(2, Form("Clusters[%d]", fInfo->GetEntriesFast(), fDet, fCol, fRow));
508 AliWarning("Loading the calibration settings failed. Check OCDB access.");
514 Float_t x, y, z, q, dy, dydx, dzdx, cov[3], covcl[3];
517 // define limits around ExB for which x contribution is negligible
518 const Float_t kDtgPhi = 3.5e-2; //(+- 2 deg)
520 TObjArray *arr0 = (TObjArray*)fContainer->At(kCenter);
521 TObjArray *arr1 = (TObjArray*)fContainer->At(kSigm);
522 TObjArray *arr2 = (TObjArray*)fContainer->At(kMean);
524 const AliTRDclusterInfo *cli = NULL;
525 TIterator *iter=fInfo->MakeIterator();
526 while((cli=dynamic_cast<AliTRDclusterInfo*>((*iter)()))){
527 cli->GetCluster(det, x, y, z, q, t, covcl);
529 // select cluster according to detector region if specified
530 if(fDet>=0 && fDet!=det) continue;
531 if(fCol>=0 && fRow>=0){
533 cli->GetCenterPad(c, r);
534 if(TMath::Abs(fCol-c) > 5) continue;
535 if(TMath::Abs(fRow-r) > 2) continue;
537 dy = cli->GetResolution();
538 AliDebug(4, Form("det[%d] tb[%2d] q[%4.0f Log[%6.4f]] dy[%7.2f][um] ypull[%5.2f]", det, t, q, TMath::Log(q), 1.e4*dy, dy/TMath::Sqrt(covcl[0])));
540 cli->GetGlobalPosition(y, z, dydx, dzdx, &cov[0]);
542 // resolution as a function of cluster charge
543 // only for phi equal exB
544 if(TMath::Abs(dydx-fExB) < kDtgPhi){
545 h3 = (TH3S*)fContainer->At(kQRes);
546 h3->Fill(TMath::Log(q), dy, dy/TMath::Sqrt(covcl[0]));
549 // do not use problematic clusters in resolution analysis
550 // TODO define limits as calibration aware (gain) !!
551 if(q<20.*fGain || q>250.*fGain) continue;
553 //x = (t+.5)*fgkTimeBinLength; // conservative approach !!
555 // resolution as a function of y displacement from pad center
556 // only for phi equal exB
557 if(TMath::Abs(dydx-fExB) < kDtgPhi){
558 h3 = (TH3S*)arr0->At(0);
559 h3->Fill(t, cli->GetYDisplacement(), dy);
560 h3 = (TH3S*)arr0->At(1);
561 h3->Fill(t, cli->GetYDisplacement(), dy/TMath::Sqrt(covcl[0]));
564 Int_t it(((TH3S*)arr0->At(0))->GetXaxis()->FindBin(t));
566 // fill histo for resolution (sigma)
567 ((TH3S*)arr1->At(it-1))->Fill(10.*cli->GetAnisochronity(), dydx, dy);
569 // fill histo for systematic (mean)
570 ((TH3S*)arr2->At(it-1))->Fill(10.*cli->GetAnisochronity(), dydx-cli->GetTilt()*dzdx, dy);
575 //_______________________________________________________
576 Bool_t AliTRDclusterResolution::PostProcess()
578 if(!fContainer) return kFALSE;
580 AliWarning("Not calibrated.");
583 TObjArray *arr = NULL;
586 TGraphErrors *g = NULL;
587 fResults = new TObjArray(kNtasks);
588 fResults->SetOwner();
589 fResults->AddAt(arr = new TObjArray(3), kQRes);
591 arr->AddAt(g = new TGraphErrors(), 0);
592 g->SetLineColor(kBlue); g->SetMarkerColor(kBlue);
593 g->SetMarkerStyle(7);
594 arr->AddAt(g = new TGraphErrors(), 1);
595 g->SetLineColor(kRed); g->SetMarkerColor(kRed);
596 g->SetMarkerStyle(23);
597 arr->AddAt(g = new TGraphErrors(), 2);
598 g->SetLineColor(kGreen); g->SetMarkerColor(kGreen);
599 g->SetMarkerStyle(7);
601 // pad center dependence
602 fResults->AddAt(arr = new TObjArray(AliTRDgeometry::kNlayer+1), kCenter);
605 t = new TTree("cent", "dy=f(y,x,ly)"), 0);
606 t->Branch("ly", &fLy, "ly/B");
607 t->Branch("t", &fT, "t/F");
608 t->Branch("y", &fY, "y/F");
609 t->Branch("m", &fR[0], "m[2]/F");
610 t->Branch("s", &fR[2], "s[2]/F");
611 t->Branch("pm", &fP[0], "pm[2]/F");
612 t->Branch("ps", &fP[2], "ps[2]/F");
613 for(Int_t il=1; il<=AliTRDgeometry::kNlayer; il++){
614 arr->AddAt(g = new TGraphErrors(), il);
615 g->SetLineColor(il); g->SetLineStyle(il);
616 g->SetMarkerColor(il);g->SetMarkerStyle(4);
620 fResults->AddAt(t = new TTree("sigm", "dy=f(dw,x,dydx)"), kSigm);
621 t->Branch("t", &fT, "t/F");
622 t->Branch("x", &fX, "x/F");
623 t->Branch("z", &fZ, "z/F");
624 t->Branch("sx", &fR[0], "sx[2]/F");
625 t->Branch("sy", &fR[2], "sy[2]/F");
628 fResults->AddAt(t = new TTree("mean", "dy=f(dw,x,dydx - h dzdx)"), kMean);
629 t->Branch("t", &fT, "t/F");
630 t->Branch("x", &fX, "x/F");
631 t->Branch("z", &fZ, "z/F");
632 t->Branch("dx", &fR[0], "dx[2]/F");
633 t->Branch("dy", &fR[2], "dy[2]/F");
636 TIterator *iter=fResults->MakeIterator();
637 while((o=((*iter)()))) o->Clear(); // maybe it is wrong but we should never reach this point
640 // process resolution dependency on charge
641 if(HasProcess(kQRes)) ProcessCharge();
643 // process resolution dependency on y displacement
644 if(HasProcess(kCenter)) ProcessCenterPad();
646 // process resolution dependency on drift legth and drift cell width
647 if(HasProcess(kSigm)) ProcessSigma();
649 // process systematic shift on drift legth and drift cell width
650 if(HasProcess(kMean)) ProcessMean();
655 //_______________________________________________________
656 Bool_t AliTRDclusterResolution::LoadCalibration()
658 // Retrieve calibration parameters from OCDB, drift velocity and t0 for the detector region specified by
659 // a previous call to AliTRDclusterResolution::SetCalibrationRegion().
661 AliCDBManager *cdb = AliCDBManager::Instance(); // init OCDB
662 if(cdb->GetRun() < 0){
663 AliError("OCDB manager not properly initialized");
667 // check magnetic field
668 AliESDEvent *esd = dynamic_cast<AliESDEvent*>(InputEvent());
670 AliError("Failed retrieving ESD event");
673 if(!TGeoGlobalMagField::Instance()->IsLocked() && !esd->InitMagneticField()){
674 AliError("Magnetic field failed initialization.");
678 // check pad for detector
679 if(fCol>=0 && fRow>=0){
681 AliTRDpadPlane *pp(geo.GetPadPlane(fDet));
682 if(fCol>=pp->GetNcols() ||
683 fRow>=pp->GetNrows()){
684 AliWarning(Form("Pad coordinates col[%d] or row[%d] incorrect for det[%d].\nLimits are max col[%d] max row[%d]. Reset to default", fCol, fRow, fDet, pp->GetNcols(), pp->GetNrows()));
689 AliTRDcalibDB *fCalibration = AliTRDcalibDB::Instance();
690 AliTRDCalROC *fCalVdriftROC(fCalibration->GetVdriftROC(fDet>=0?fDet:0))
691 ,*fCalT0ROC(fCalibration->GetT0ROC(fDet>=0?fDet:0));
692 const AliTRDCalDet *fCalVdriftDet = fCalibration->GetVdriftDet();
693 const AliTRDCalDet *fCalT0Det = fCalibration->GetT0Det();
695 fVdrift = fCalVdriftDet->GetValue(fDet>=0?fDet:0);
696 if(fCol>=0 && fRow>=0) fVdrift*= fCalVdriftROC->GetValue(fCol, fRow);
697 fExB = AliTRDCommonParam::Instance()->GetOmegaTau(fVdrift);
698 fT0 = fCalT0Det->GetValue(fDet>=0?fDet:0);
699 if(fCol>=0 && fRow>=0) fT0 *= fCalT0ROC->GetValue(fCol, fRow);
700 fGain = (fCol>=0 && fRow>=0)?fCalibration-> GetGainFactor(fDet, fCol, fRow):fCalibration-> GetGainFactorAverage(fDet);
703 AliDebug(1, Form("Calibrate for Det[%3d] Col[%3d] Row[%2d] : \n t0[%5.3f] vd[%5.3f] gain[%5.3f] ExB[%f]", fDet, fCol, fRow, fT0, fVdrift, fGain, fExB));
708 //_______________________________________________________
709 void AliTRDclusterResolution::SetCalibrationRegion(Int_t det, Int_t col, Int_t row)
711 // Set calibration region in terms of detector and pad.
712 // By default detector 0 mean values are considered.
714 if(det>=0 && det<AliTRDgeometry::kNdet){
716 if(col>=0 && row>=0){
722 AliError(Form("Detector index outside range [0 %d].", AliTRDgeometry::kNdet));
725 //_______________________________________________________
726 void AliTRDclusterResolution::SetVisual()
729 fCanvas = new TCanvas("clResCanvas", "Cluster Resolution Visualization", 10, 10, 600, 600);
732 //_______________________________________________________
733 void AliTRDclusterResolution::ProcessCharge()
735 // Resolution as a function of cluster charge.
737 // As described in the function ProcessCenterPad() the error parameterization for clusters for phi = a_L can be
740 // #sigma_{y}^{2} = #sigma_{y}^{2}|_{B=0} + tg^{2}(#alpha_{L})*#sigma_{x}^{2}
742 // with the contribution in case of B=0 given by:
744 // #sigma_{y}|_{B=0} = #sigma_{diff}*Gauss(0, s_{ly}) + #delta_{#sigma}(q)
746 // which further can be simplified to:
748 // <#sigma_{y}|_{B=0}>(q) = <#sigma_{y}> + #delta_{#sigma}(q)
749 // <#sigma_{y}> = #int{f(q)#sigma_{y}dq}
751 // The results for s_y and f(q) are displayed below:
753 //<img src="TRD/clusterQerror.gif">
755 // The function has to extended to accomodate gain calibration scalling and errors.
758 // Alexandru Bercuci <A.Bercuci@gsi.de>
761 if(!(h3 = (TH3S*)fContainer->At(kQRes))) {
762 AliWarning("Missing dy=f(Q) histo");
765 TF1 f("f", "gaus", -.5, .5);
769 // compute mean error on x
771 for(Int_t ix=5; ix<AliTRDseedV1::kNtb; ix++){
772 // retrieve error on the drift length
773 s2x += AliTRDcluster::GetSX(ix);
775 s2x /= (AliTRDseedV1::kNtb-5); s2x *= s2x;
776 //Double_t exb2 = fExB*fExB;
778 TObjArray *arr = (TObjArray*)fResults->At(kQRes);
779 TGraphErrors *gqm = (TGraphErrors*)arr->At(0);
780 TGraphErrors *gqs = (TGraphErrors*)arr->At(1);
781 TGraphErrors *gqp = (TGraphErrors*)arr->At(2);
782 Double_t q, n = 0., entries;
784 for(Int_t ix=1; ix<=ax->GetNbins(); ix++){
785 q = TMath::Exp(ax->GetBinCenter(ix));
786 ax->SetRange(ix, ix);
787 h1 = h3->Project3D("y");
788 entries = h1->GetEntries();
789 if(entries < 150) continue;
793 Int_t ip = gqm->GetN();
794 gqm->SetPoint(ip, q, 1.e4*f.GetParameter(1));
795 gqm->SetPointError(ip, 0., 1.e4*f.GetParError(1));
797 // correct sigma for ExB effect
798 gqs->SetPoint(ip, q, 1.e4*f.GetParameter(2)/**f.GetParameter(2)-exb2*s2x)*/);
799 gqs->SetPointError(ip, 0., 1.e4*f.GetParError(2)/**f.GetParameter(2)*/);
803 gqp->SetPoint(ip, q, entries);
804 gqp->SetPointError(ip, 0., 0./*TMath::Sqrt(entries)*/);
807 // normalize probability and get mean sy
808 Double_t sm = 0., sy;
809 for(Int_t ip=gqp->GetN(); ip--;){
810 gqp->GetPoint(ip, q, entries);
812 gqp->SetPoint(ip, q, 1.e4*entries);
813 gqs->GetPoint(ip, q, sy);
817 // error parametrization s(q) = <sy> + b(1/q-1/q0)
818 TF1 fq("fq", "[0] + [1]/x", 20., 250.);
819 gqs->Fit(&fq/*, "W"*/);
820 printf("sm=%f [0]=%f [1]=%f\n", 1.e-4*sm, fq.GetParameter(0), fq.GetParameter(1));
821 printf(" const Float_t sq0inv = %f; // [1/q0]\n", (sm-fq.GetParameter(0))/fq.GetParameter(1));
822 printf(" const Float_t sqb = %f; // [cm]\n", 1.e-4*fq.GetParameter(1));
825 //_______________________________________________________
826 void AliTRDclusterResolution::ProcessCenterPad()
828 // Resolution as a function of y displacement from pad center and drift length.
830 // Since the error parameterization of cluster r-phi position can be written as (see AliTRDcluster::SetSigmaY2()):
832 // #sigma_{y}^{2} = (#sigma_{diff}*Gauss(0, s_{ly}) + #delta_{#sigma}(q))^{2} + tg^{2}(#alpha_{L})*#sigma_{x}^{2} + tg^{2}(#phi-#alpha_{L})*#sigma_{x}^{2}+[tg(#phi-#alpha_{L})*tg(#alpha_{L})*x]^{2}/12
834 // one can see that for phi = a_L one gets the following expression:
836 // #sigma_{y}^{2} = #sigma_{y}^{2}|_{B=0} + tg^{2}(#alpha_{L})*#sigma_{x}^{2}
838 // where we have explicitely marked the remaining term in case of absence of magnetic field. Thus one can use the
839 // previous equation to estimate s_y for B=0 and than by comparing in magnetic field conditions one can get the s_x.
840 // This is a simplified method to determine the error parameterization for s_x and s_y as compared to the one
841 // implemented in ProcessSigma(). For more details on cluster error parameterization please see also
842 // AliTRDcluster::SetSigmaY2()
844 // The representation of dy=f(y_cen, x_drift| layer) can be also used to estimate the systematic shift in the r-phi
845 // coordinate resulting from imperfection in the cluster shape parameterization. From the expresion of the shift derived
846 // in ProcessMean() with phi=exb one gets:
848 // <#Delta y>= <#delta x> * (tg(#alpha_{L})-h*dz/dx) + <#delta y - #delta x * tg(#alpha_{L})>
849 // <#Delta y>(y_{cen})= -h*<#delta x>(x_{drift}, q_{cl}) * dz/dx + #delta y(y_{cen}, ...)
851 // where all dependences are made explicit. This last expression can be used in two ways:
852 // - by average on the dz/dx we can determine directly dy (the method implemented here)
853 // - by plotting as a function of dzdx one can determine both dx and dy components in an independent method.
855 //<img src="TRD/clusterYcorr.gif">
858 // Alexandru Bercuci <A.Bercuci@gsi.de>
860 TObjArray *arr = (TObjArray*)fContainer->At(kCenter);
862 AliWarning("Missing dy=f(y | x, ly) container");
865 Double_t exb2 = fExB*fExB;
866 Float_t s[AliTRDgeometry::kNlayer];
867 TF1 f("f", "gaus", -.5, .5);
868 TF1 fp("fp", "gaus", -3.5, 3.5);
870 TH1D *h1 = NULL; TH2F *h2 = NULL; TH3S *h3r=NULL, *h3p=NULL;
871 TObjArray *arrRes = (TObjArray*)fResults->At(kCenter);
872 TTree *t = (TTree*)arrRes->At(0);
873 TGraphErrors *gs = NULL;
876 AliDebug(1, Form("Calibrate for Det[%3d] t0[%5.3f] vd[%5.3f]", fDet, fT0, fVdrift));
878 const Int_t nl = AliTRDgeometry::kNlayer;
879 printf(" const Float_t lSy[%d][%d] = {\n {", nl, AliTRDseedV1::kNtb);
880 for(Int_t il=0; il<nl; il++){
881 if(!(h3r = (TH3S*)arr->At(il))) continue;
882 if(!(h3p = (TH3S*)arr->At(nl+il))) continue;
883 gs = (TGraphErrors*)arrRes->At(il+1);
885 for(Int_t ix=1; ix<=h3r->GetXaxis()->GetNbins(); ix++){
886 ax = h3r->GetXaxis(); ax->SetRange(ix, ix);
887 ax = h3p->GetXaxis(); ax->SetRange(ix, ix);
888 fT = ax->GetBinCenter(ix);
889 for(Int_t iy=1; iy<=h3r->GetYaxis()->GetNbins(); iy++){
890 ax = h3r->GetYaxis(); ax->SetRange(iy, iy);
891 ax = h3p->GetYaxis(); ax->SetRange(iy, iy);
892 fY = ax->GetBinCenter(iy);
893 // finish navigation in the HnSparse
895 h1 = (TH1D*)h3r->Project3D("z");
896 Int_t entries = (Int_t)h1->Integral();
897 if(entries < 50) continue;
901 // Fill sy,my=f(y_w,x,ly)
902 fR[0] = f.GetParameter(1); fR[1] = f.GetParError(1);
903 fR[2] = f.GetParameter(2); fR[3] = f.GetParError(2);
905 h1 = (TH1D*)h3p->Project3D("z");
907 fP[0] = fp.GetParameter(1); fP[1] = fp.GetParError(1);
908 fP[2] = fp.GetParameter(2); fP[3] = fp.GetParError(2);
910 AliDebug(4, Form("ly[%d] tb[%2d] y[%+5.2f] m[%5.3f] s[%5.3f] pm[%5.3f] ps[%5.3f]", fLy, (Int_t)fT, fY, fR[0], fR[2], fP[0], fP[2]));
914 t->Draw(Form("y:t>>h(%d, -0.5, %f, 51, -.51, .51)", AliTRDseedV1::kNtb, AliTRDseedV1::kNtb-0.5),
915 Form("s[0]*(ly==%d&&abs(m[0])<1.e-1)", fLy),
917 h2=(TH2F*)gROOT->FindObject("h");
918 f.FixParameter(1, 0.);
919 Int_t n = h2->GetXaxis()->GetNbins(), nn(0); s[il]=0.;
921 for(Int_t ix=1; ix<=n; ix++){
923 fT = ax->GetBinCenter(ix);
924 h1 = h2->ProjectionY("hCenPy", ix, ix);
925 //if((Int_t)h1->Integral() < 1.e-10) continue;
927 // Apply lorentz angle correction
928 // retrieve error on the drift length
929 Double_t s2x = AliTRDcluster::GetSX(ix-1); s2x *= s2x;
931 for(Int_t iy=1; iy<=h1->GetNbinsX(); iy++){
932 Double_t s2 = h1->GetBinContent(iy); s2*= s2;
933 // sigma square corrected for Lorentz angle
934 // s2 = s2_y(y_w,x)+exb2*s2_x
935 Double_t sy = TMath::Sqrt(TMath::Max(s2 - exb2*s2x, Double_t(0.)));
936 if(sy<1.e-20) continue;
937 h1->SetBinContent(iy, sy); nnn++;
938 AliDebug(4, Form("s[%6.2f] sx[%6.2f] sy[%6.2f]\n",
939 1.e4*TMath::Sqrt(s2), 1.e4*TMath::Abs(fExB*AliTRDcluster::GetSX(ix-1)),
940 1.e4*h1->GetBinContent(iy)));
942 // do fit only if enough data
946 sPRF = f.GetParameter(2); nn++;
949 printf("%6.4f,%s", sPRF, ix%6?" ":"\n ");
950 Int_t jx = gs->GetN();
951 gs->SetPoint(jx, fT, 1.e4*sPRF);
952 gs->SetPointError(jx, 0., 0./*f.GetParError(0)*/);
957 f.ReleaseParameter(1);
960 if(!fCanvas) continue;
962 fCanvas->Modified(); fCanvas->Update();
963 if(IsSaveAs()) fCanvas->SaveAs(Form("Figures/ProcessCenter_ly[%d].gif", fLy));
964 else gSystem->Sleep(100);
967 printf(" const Float_t lPRF[] = {"
968 "%5.3f, %5.3f, %5.3f, %5.3f, %5.3f, %5.3f};\n",
969 s[0], s[1], s[2], s[3], s[4], s[5]);
972 //_______________________________________________________
973 void AliTRDclusterResolution::ProcessSigma()
975 // As the r-phi coordinate is the only one which is measured by the TRD detector we have to rely on it to
976 // estimate both the radial (x) and r-phi (y) errors. This method is based on the following assumptions.
977 // The measured error in the y direction is the sum of the intrinsic contribution of the r-phi measurement
978 // with the contribution of the radial measurement - because x is not a parameter of Alice track model (Kalman).
980 // #sigma^{2}|_{y} = #sigma^{2}_{y*} + #sigma^{2}_{x*}
982 // In the general case
984 // #sigma^{2}_{y*} = #sigma^{2}_{y} + tg^{2}(#alpha_{L})#sigma^{2}_{x_{drift}}
985 // #sigma^{2}_{x*} = tg^{2}(#phi - #alpha_{L})*(#sigma^{2}_{x_{drift}} + #sigma^{2}_{x_{0}} + tg^{2}(#alpha_{L})*x^{2}/12)
987 // where we have explicitely show the lorentz angle correction on y and the projection of radial component on the y
988 // direction through the track angle in the bending plane (phi). Also we have shown that the radial component in the
989 // last equation has twp terms, the drift and the misalignment (x_0). For ideal geometry or known misalignment one
990 // can solve the equation
992 // #sigma^{2}|_{y} = tg^{2}(#phi - #alpha_{L})*(#sigma^{2}_{x} + tg^{2}(#alpha_{L})*x^{2}/12)+ [#sigma^{2}_{y} + tg^{2}(#alpha_{L})#sigma^{2}_{x}]
994 // by fitting a straight line:
996 // #sigma^{2}|_{y} = a(x_{cl}, z_{cl}) * tg^{2}(#phi - #alpha_{L}) + b(x_{cl}, z_{cl})
998 // the error parameterization will be given by:
1000 // #sigma_{x} (x_{cl}, z_{cl}) = #sqrt{a(x_{cl}, z_{cl}) - tg^{2}(#alpha_{L})*x^{2}/12}
1001 // #sigma_{y} (x_{cl}, z_{cl}) = #sqrt{b(x_{cl}, z_{cl}) - #sigma^{2}_{x} (x_{cl}, z_{cl}) * tg^{2}(#alpha_{L})}
1003 // Below there is an example of such dependency.
1005 //<img src="TRD/clusterSigmaMethod.gif">
1008 // The error parameterization obtained by this method are implemented in the functions AliTRDcluster::GetSX() and
1009 // AliTRDcluster::GetSYdrift(). For an independent method to determine s_y as a function of drift length check the
1010 // function ProcessCenterPad(). One has to keep in mind that while this method return the mean s_y over the distance
1011 // to pad center distribution the other method returns the *STANDARD* value at center=0 (maximum). To recover the
1012 // standard value one has to solve the obvious equation:
1014 // #sigma_{y}^{STANDARD} = #frac{<#sigma_{y}>}{#int{s exp(s^{2}/#sigma) ds}}
1016 // with "<s_y>" being the value calculated here and "sigma" the width of the s_y distribution calculated in
1017 // ProcessCenterPad().
1020 // Alexandru Bercuci <A.Bercuci@gsi.de>
1022 TObjArray *arr = (TObjArray*)fContainer->At(kSigm);
1024 AliWarning("Missing dy=f(x_d, d_w) container");
1028 // init visualization
1029 TGraphErrors *ggs = NULL;
1030 TGraph *line = NULL;
1032 ggs = new TGraphErrors();
1033 line = new TGraph();
1034 line->SetLineColor(kRed);line->SetLineWidth(2);
1037 // init logistic support
1038 TF1 f("f", "gaus", -.5, .5);
1039 TLinearFitter gs(1,"pol1");
1041 TH1D *h1 = NULL; TH3S *h3=NULL;
1043 Double_t exb2 = fExB*fExB;
1045 TTree *t = (TTree*)fResults->At(kSigm);
1046 for(Int_t ix=0; ix<AliTRDseedV1::kNtb; ix++){
1047 if(!(h3=(TH3S*)arr->At(ix))) continue;
1049 fX = c.GetXloc(fT0, fVdrift);
1050 fT = c.GetLocalTimeBin(); // ideal
1051 printf(" pad time[%d] local[%f]\n", ix, fT);
1052 for(Int_t iz=1; iz<=h3->GetXaxis()->GetNbins(); iz++){
1053 ax = h3->GetXaxis();
1054 ax->SetRange(iz, iz);
1055 fZ = ax->GetBinCenter(iz);
1057 // reset visualization
1059 new(ggs) TGraphErrors();
1060 ggs->SetMarkerStyle(7);
1064 for(Int_t ip=1; ip<=h3->GetYaxis()->GetNbins(); ip++){
1065 ax = h3->GetYaxis();
1066 ax->SetRange(ip, ip);
1067 Double_t tgl = ax->GetBinCenter(ip);
1068 // finish navigation in the HnSparse
1070 //if(TMath::Abs(dydx)>0.18) continue;
1071 Double_t tgg = (tgl-fExB)/(1.+tgl*fExB);
1072 Double_t tgg2 = tgg*tgg;
1074 h1 = (TH1D*)h3->Project3D("z");
1075 Int_t entries = (Int_t)h1->Integral();
1076 if(entries < 50) continue;
1080 Double_t s2 = f.GetParameter(2)*f.GetParameter(2);
1081 Double_t s2e = 2.*f.GetParameter(2)*f.GetParError(2);
1082 // Fill sy^2 = f(tg^2(phi-a_L))
1083 gs.AddPoint(&tgg2, s2, s2e);
1086 Int_t jp = ggs->GetN();
1087 ggs->SetPoint(jp, tgg2, s2);
1088 ggs->SetPointError(jp, 0., s2e);
1090 // TODO here a more robust fit method has to be provided
1091 // for which lower boundaries on the parameters have to
1092 // be imposed. Unfortunately the Minuit fit does not work
1093 // for the TGraph in the case of B not 0.
1094 if(gs.Eval()) continue;
1096 fR[0] = gs.GetParameter(1) - fX*fX*exb2/12.;
1097 AliDebug(3, Form(" s2x+x2=%f ang=%f s2x=%f", gs.GetParameter(1), fX*fX*exb2/12., fR[0]));
1098 fR[0] = TMath::Max(fR[0], Float_t(4.e-4));
1100 // s^2_y = s0^2_y + tg^2(a_L) * s^2_x
1101 // s0^2_y = f(D_L)*x + s_PRF^2
1102 fR[2]= gs.GetParameter(0)-exb2*fR[0];
1103 AliDebug(3, Form(" s2y+s2x=%f s2y=%f", fR[0], fR[2]));
1104 fR[2] = TMath::Max(fR[2], Float_t(2.5e-5));
1105 fR[0] = TMath::Sqrt(fR[0]);
1106 fR[1] = .5*gs.GetParError(1)/fR[0];
1107 fR[2] = TMath::Sqrt(fR[2]);
1108 fR[3] = gs.GetParError(0)+exb2*exb2*gs.GetParError(1);
1110 AliDebug(2, Form("xd=%4.2f[cm] sx=%6.1f[um] sy=%5.1f[um]", fX, 1.e4*fR[0], 1.e4*fR[2]));
1112 if(!fCanvas) continue;
1113 fCanvas->cd(); fCanvas->SetLogx(); //fCanvas->SetLogy();
1115 fCanvas->SetMargin(0.15, 0.01, 0.1, 0.01);
1116 hFrame=new TH1I("hFrame", "", 100, 0., .3);
1117 hFrame->SetMinimum(0.);hFrame->SetMaximum(.005);
1118 hFrame->SetXTitle("tg^{2}(#phi-#alpha_{L})");
1119 hFrame->SetYTitle("#sigma^{2}y[cm^{2}]");
1120 hFrame->GetYaxis()->SetTitleOffset(2.);
1121 hFrame->SetLineColor(1);hFrame->SetLineWidth(1);
1123 } else hFrame->Reset();
1124 Double_t xx = 0., dxx=.2/50;
1125 for(Int_t ip=0;ip<50;ip++){
1126 line->SetPoint(ip, xx, gs.GetParameter(0)+xx*gs.GetParameter(1));
1129 ggs->Draw("pl"); line->Draw("l");
1130 fCanvas->Modified(); fCanvas->Update();
1131 if(IsSaveAs()) fCanvas->SaveAs(Form("Figures/ProcessSigma_z[%5.3f]_x[%5.3f].gif", fZ, fX));
1132 else gSystem->Sleep(100);
1138 //_______________________________________________________
1139 void AliTRDclusterResolution::ProcessMean()
1141 // By this method the cluster shift in r-phi and radial directions can be estimated by comparing with the MC.
1142 // The resolution of the cluster corrected for pad tilt with respect to MC in the r-phi (measuring) plane can be
1145 // #Delta y=w - y_{MC}(x_{cl})
1146 // w = y_{cl}^{'} + h*(z_{MC}(x_{cl})-z_{cl})
1147 // y_{MC}(x_{cl}) = y_{0} - dy/dx*x_{cl}
1148 // z_{MC}(x_{cl}) = z_{0} - dz/dx*x_{cl}
1149 // y_{cl}^{'} = y_{cl}-x_{cl}*tg(#alpha_{L})
1151 // where x_cl is the drift length attached to a cluster, y_cl is the r-phi coordinate of the cluster measured by
1152 // charge sharing on adjacent pads and y_0 and z_0 are MC reference points (as example the track references at
1153 // entrance/exit of a chamber). If we suppose that both r-phi (y) and radial (x) coordinate of the clusters are
1154 // affected by errors we can write
1156 // x_{cl} = x_{cl}^{*} + #delta x
1157 // y_{cl} = y_{cl}^{*} + #delta y
1159 // where the starred components are the corrected values. Thus by definition the following quantity
1161 // #Delta y^{*}= w^{*} - y_{MC}(x_{cl}^{*})
1163 // has 0 average over all dependency. Using this decomposition we can write:
1165 // <#Delta y>=<#Delta y^{*}> + <#delta x * (dy/dx-h*dz/dx) + #delta y - #delta x * tg(#alpha_{L})>
1167 // which can be transformed to the following linear dependence:
1169 // <#Delta y>= <#delta x> * (dy/dx-h*dz/dx) + <#delta y - #delta x * tg(#alpha_{L})>
1171 // if expressed as function of dy/dx-h*dz/dx. Furtheremore this expression can be plotted for various clusters
1172 // i.e. we can explicitely introduce the diffusion (x_cl) and drift cell - anisochronity (z_cl) dependences. From
1173 // plotting this dependence and linear fitting it with:
1175 // <#Delta y>= a(x_{cl}, z_{cl}) * (dy/dx-h*dz/dx) + b(x_{cl}, z_{cl})
1177 // the systematic shifts will be given by:
1179 // #delta x (x_{cl}, z_{cl}) = a(x_{cl}, z_{cl})
1180 // #delta y (x_{cl}, z_{cl}) = b(x_{cl}, z_{cl}) + a(x_{cl}, z_{cl}) * tg(#alpha_{L})
1182 // Below there is an example of such dependency.
1184 //<img src="TRD/clusterShiftMethod.gif">
1187 // The occurance of the radial shift is due to the following conditions
1188 // - the approximation of a constant drift velocity over the drift length (larger drift velocities close to
1189 // cathode wire plane)
1190 // - the superposition of charge tails in the amplification region (first clusters appear to be located at the
1192 // - the superposition of charge tails in the drift region (shift towards anode wire)
1193 // - diffusion effects which convolute with the TRF thus enlarging it
1194 // - approximate knowledge of the TRF (approximate measuring in test beam conditions)
1196 // The occurance of the r-phi shift is due to the following conditions
1197 // - approximate model for cluster shape (LUT)
1198 // - rounding-up problems
1200 // The numerical results for ideal simulations for the radial and r-phi shifts are displayed below and used
1201 // for the cluster reconstruction (see the functions AliTRDcluster::GetXcorr() and AliTRDcluster::GetYcorr()).
1203 //<img src="TRD/clusterShiftX.gif">
1204 //<img src="TRD/clusterShiftY.gif">
1206 // More details can be found in the presentation given during the TRD
1207 // software meeting at the end of 2008 and beginning of year 2009, published on indico.cern.ch.
1210 // Alexandru Bercuci <A.Bercuci@gsi.de>
1214 TObjArray *arr = (TObjArray*)fContainer->At(kMean);
1216 AliWarning("Missing dy=f(x_d, d_w) container");
1220 // init logistic support
1221 TF1 f("f", "gaus", -.5, .5);
1222 TF1 line("l", "[0]+[1]*x", -.15, .15);
1223 TGraphErrors *gm = new TGraphErrors();
1225 TH1D *h1 = NULL; TH3S *h3 =NULL;
1228 AliDebug(1, Form("Calibrate for Det[%3d] t0[%5.3f] vd[%5.3f]", fDet, fT0, fVdrift));
1231 TTree *t = (TTree*)fResults->At(kMean);
1232 for(Int_t ix=0; ix<AliTRDseedV1::kNtb; ix++){
1233 if(!(h3=(TH3S*)arr->At(ix))) continue;
1235 fX = c.GetXloc(fT0, fVdrift);
1236 fT = c.GetLocalTimeBin();
1237 for(Int_t iz=1; iz<=h3->GetXaxis()->GetNbins(); iz++){
1238 ax = h3->GetXaxis();
1239 ax->SetRange(iz, iz);
1240 fZ = ax->GetBinCenter(iz);
1243 new(gm) TGraphErrors();
1244 gm->SetMarkerStyle(7);
1246 for(Int_t ip=1; ip<=h3->GetYaxis()->GetNbins(); ip++){
1247 ax = h3->GetYaxis();
1248 ax->SetRange(ip, ip);
1249 Double_t tgl = ax->GetBinCenter(ip);
1250 // finish navigation in the HnSparse
1252 h1 = (TH1D*)h3->Project3D("z");
1253 Int_t entries = (Int_t)h1->Integral();
1254 if(entries < 50) continue;
1258 // Fill <Dy> = f(dydx - h*dzdx)
1259 Int_t jp = gm->GetN();
1260 gm->SetPoint(jp, tgl, f.GetParameter(1));
1261 gm->SetPointError(jp, 0., f.GetParError(1));
1263 if(gm->GetN()<10) continue;
1265 gm->Fit(&line, "QN");
1266 fR[0] = line.GetParameter(1); // dx
1267 fR[1] = line.GetParError(1);
1268 fR[2] = line.GetParameter(0) + fExB*fR[0]; // xs = dy - tg(a_L)*dx
1270 AliDebug(2, Form("tb[%02d] xd=%4.2f[cm] dx=%6.2f[um] dy=%6.2f[um]", ix, fX, 1.e4*fR[0], 1.e4*fR[2]));
1271 if(!fCanvas) continue;
1275 fCanvas->SetMargin(0.1, 0.02, 0.1, 0.01);
1276 hFrame=new TH1I("hFrame", "", 100, -.3, .3);
1277 hFrame->SetMinimum(-.1);hFrame->SetMaximum(.1);
1278 hFrame->SetXTitle("tg#phi-htg#theta");
1279 hFrame->SetYTitle("#Delta y[cm]");
1280 hFrame->GetYaxis()->SetTitleOffset(1.5);
1281 hFrame->SetLineColor(1);hFrame->SetLineWidth(1);
1283 } else hFrame->Reset();
1284 gm->Draw("pl"); line.Draw("same");
1285 fCanvas->Modified(); fCanvas->Update();
1286 if(IsSaveAs()) fCanvas->SaveAs(Form("Figures/ProcessMean_Z[%5.3f]_TB[%02d].gif", fZ, ix));
1287 else gSystem->Sleep(100);