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 "AliTRDcluster.h"
174 #include "AliTRDcalibDB.h"
175 #include "AliTRDCommonParam.h"
176 #include "Cal/AliTRDCalROC.h"
177 #include "Cal/AliTRDCalDet.h"
180 #include "AliTracker.h"
181 #include "AliCDBManager.h"
184 #include "TObjArray.h"
188 #include "TGraphErrors.h"
194 #include "TLinearFitter.h"
199 ClassImp(AliTRDclusterResolution)
201 const Float_t AliTRDclusterResolution::fgkTimeBinLength = 1./ AliTRDCommonParam::Instance()->GetSamplingFrequency();
202 //_______________________________________________________
203 AliTRDclusterResolution::AliTRDclusterResolution()
219 SetNameTitle("ClErrCalib", "Cluster Error Parameterization");
222 //_______________________________________________________
223 AliTRDclusterResolution::AliTRDclusterResolution(const char *name)
224 : AliTRDrecoTask(name, "Cluster Error Parameterization")
240 memset(fR, 0, 4*sizeof(Float_t));
241 memset(fP, 0, 4*sizeof(Float_t));
243 fAt = new TAxis(kNTB, 0., kNTB*fgkTimeBinLength);
245 // By default register all analysis
246 // The user can switch them off in his steering macro
253 //_______________________________________________________
254 AliTRDclusterResolution::~AliTRDclusterResolution()
258 if(fCanvas) delete fCanvas;
266 //_______________________________________________________
267 void AliTRDclusterResolution::ConnectInputData(Option_t *opt)
269 AliAnalysisTaskSE::ConnectInputData(opt);
270 // overwrite settings from AliTRDrecoTask !!!
271 fInfo = dynamic_cast<TObjArray *>(GetInputData(1));
274 //_______________________________________________________
275 void AliTRDclusterResolution::UserCreateOutputObjects()
277 OpenFile(1, "RECREATE");
278 fContainer = Histos();
281 //_______________________________________________________
282 Bool_t AliTRDclusterResolution::GetRefFigure(Int_t ifig)
284 // Steering function to retrieve performance plots
286 if(!fResults) return kFALSE;
289 TObjArray *arr = NULL;
291 TH2 *h2 = NULL;TH1 *h1 = NULL;
292 TGraphErrors *gm(NULL), *gs(NULL), *gp(NULL);
295 if(!(arr = (TObjArray*)fResults->At(kQRes))) break;
296 if(!(gm = (TGraphErrors*)arr->At(0))) break;
297 if(!(gs = (TGraphErrors*)arr->At(1))) break;
298 if(!(gp = (TGraphErrors*)arr->At(2))) break;
300 gs->GetHistogram()->GetYaxis()->SetRangeUser(-50., 700.);
301 gs->GetHistogram()->SetXTitle("Q [a.u.]");
302 gs->GetHistogram()->SetYTitle("#sigma_{y} / #mu_{y} [#mum] / freq");
307 if(!(arr = (TObjArray*)fResults->At(kCenter))) break;
308 gPad->Divide(2, 1); l = gPad->GetListOfPrimitives();
309 ((TVirtualPad*)l->At(0))->cd();
310 ((TTree*)arr->At(0))->Draw("y:x>>h(23, 0.1, 2.4, 51, -.51, .51)",
311 "m[0]*(ly==0&&abs(m[0])<1.e-1)", "colz");
312 ((TVirtualPad*)l->At(1))->cd();
313 leg= new TLegend(.7, .7, .9, .95);
314 leg->SetBorderSize(0); leg->SetFillColor(0); leg->SetFillStyle(0);
315 leg->SetHeader("TRD Plane");
316 for(Int_t il = 1; il<=AliTRDgeometry::kNlayer; il++){
317 if(!(gm = (TGraphErrors*)arr->At(il))) return kFALSE;
318 gm->Draw(il>1?"pc":"apc"); leg->AddEntry(gm, Form("%d", il-1), "pl");
320 gm->GetHistogram()->SetXTitle("t_{drift} [#mus]");
321 gm->GetHistogram()->SetYTitle("#sigma_{y}(x|cen=0) [#mum]");
322 gm->GetHistogram()->GetYaxis()->SetRangeUser(150., 500.);
327 if(!(t = (TTree*)fResults->At(kSigm))) break;
328 t->Draw("z:t>>h2x(23, 0.1, 2.4, 25, 0., 2.5)","sx*(1)", "lego2fb");
329 h2 = (TH2F*)gROOT->FindObject("h2x");
330 printf(" const Double_t sx[24][25]={\n");
331 for(Int_t ix=1; ix<=h2->GetNbinsX(); ix++){
333 for(Int_t iy=1; iy<h2->GetNbinsY(); iy++){
334 printf("%6.4f ", h2->GetBinContent(ix, iy));
336 printf("%6.4f},\n", h2->GetBinContent(ix, h2->GetNbinsY()));
339 gPad->Divide(2, 1, 1.e-5, 1.e-5); l = gPad->GetListOfPrimitives();
340 ((TVirtualPad*)l->At(0))->cd();
341 h1 = h2->ProjectionX("hsx_pxx"); h1->Scale(1.e4/kND); h1->SetMarkerStyle(24);
342 h1->SetYTitle("<#sigma_{x}> [#mum]");
343 h1->SetXTitle("t_{drift} [#mus]");
344 h1->GetXaxis()->SetRange(2, kNTB-1); h1->Draw("pc");
346 t->Draw("z:t>>h2y(23, 0.1, 2.4, 25, 0., 2.5)","sy*(1)", "lego2fb");
347 h2 = (TH2F*)gROOT->FindObject("h2y");
348 printf(" const Double_t sy[24][25]={\n");
349 for(Int_t ix=1; ix<=h2->GetNbinsX(); ix++){
351 for(Int_t iy=1; iy<h2->GetNbinsY(); iy++){
352 printf("%6.4f ", h2->GetBinContent(ix, iy));
354 printf("%6.4f},\n", h2->GetBinContent(ix, h2->GetNbinsY()));
357 ((TVirtualPad*)l->At(1))->cd();
358 h1 = h2->ProjectionX("hsy_pxx"); h1->Scale(1.e4/kND); h1->SetMarkerStyle(24);
359 h1->SetYTitle("<#sigma_{y}> [#mum]");
360 h1->SetXTitle("t_{drift} [#mus]");
361 h1->GetXaxis()->SetRange(2, kNTB-1); h1->Draw("pc");
364 if(!(t = (TTree*)fResults->At(kMean))) break;
365 t->Draw("z:t>>h2x(23, 0.1, 2.4, 25, 0., 2.5)","dx*(1)", "goff");
366 h2 = (TH2F*)gROOT->FindObject("h2x");
367 printf(" const Double_t dx[24][25]={\n");
368 for(Int_t ix=1; ix<=h2->GetNbinsX(); ix++){
370 for(Int_t iy=1; iy<h2->GetNbinsY(); iy++){
371 printf("%6.4f ", h2->GetBinContent(ix, iy));
373 printf("%6.4f},\n", h2->GetBinContent(ix, h2->GetNbinsY()));
376 gPad->Divide(2, 1, 1.e-5, 1.e-5); l = gPad->GetListOfPrimitives();
377 ((TVirtualPad*)l->At(0))->cd();
378 h1 = h2->ProjectionX("hdx_pxx"); h1->Scale(1.e4/kND); h1->SetMarkerStyle(24);
379 h1->SetYTitle("<dx> [#mum]");
380 h1->SetXTitle("t_{drift} [#mus]");
381 h1->GetXaxis()->SetRange(2, kNTB-1); h1->Draw("pc");
383 t->Draw("z:t>>h2y(23, 0.1, 2.4, 25, 0., 2.5)","dy*(1)", "goff");
384 h2 = (TH2F*)gROOT->FindObject("h2y");
385 printf(" const Double_t dy[24][25]={\n");
386 for(Int_t ix=1; ix<=h2->GetNbinsX(); ix++){
388 for(Int_t iy=1; iy<h2->GetNbinsY(); iy++){
389 printf("%6.4f ", h2->GetBinContent(ix, iy));
391 printf("%6.4f},\n", h2->GetBinContent(ix, h2->GetNbinsY()));
394 ((TVirtualPad*)l->At(1))->cd();
395 h1 = h2->ProjectionX("hdy_pxx"); h1->Scale(1.e4/kND); h1->SetMarkerStyle(24);
396 h1->SetYTitle("<dy> [#mum]");
397 h1->SetXTitle("t_{drift} [#mus]");
398 h1->GetXaxis()->SetRange(2, kNTB-1); h1->Draw("pc");
404 AliWarning("No container/data found.");
408 //_______________________________________________________
409 TObjArray* AliTRDclusterResolution::Histos()
411 // Retrieve histograms array if already build or build it
413 if(fContainer) return fContainer;
414 fContainer = new TObjArray(kNtasks);
415 //fContainer->SetOwner(kTRUE);
418 TObjArray *arr = NULL;
420 fContainer->AddAt(arr = new TObjArray(2*AliTRDgeometry::kNlayer), kCenter);
421 arr->SetName("Center");
422 for(Int_t il=0; il<AliTRDgeometry::kNlayer; il++){
423 // add resolution plot for each layer
424 if(!(h3=(TH3S*)gROOT->FindObject(Form("hCenResLy%d", il)))){
426 Form("hCenResLy%d", il),
427 Form(" ly [%d]", il),
428 kNTB, fAt->GetBinLowEdge(1), fAt->GetBinUpEdge(kNTB), // x
431 h3->SetXTitle("x [#mus]");
432 h3->SetYTitle("y [pw]");
433 h3->SetZTitle("#Delta y[cm]");
436 // add Pull plot for each layer
437 if(!(h3=(TH3S*)gROOT->FindObject(Form("hCenPullLy%d", il)))){
439 Form("hCenPullLy%d", il),
440 Form(" ly [%d]", il),
441 kNTB, fAt->GetBinLowEdge(1), fAt->GetBinUpEdge(kNTB), // x
444 h3->SetXTitle("x [#mus]");
445 h3->SetYTitle("y [pw]");
446 h3->SetZTitle("#Delta y/#sigma_{y}");
448 arr->AddAt(h3, AliTRDgeometry::kNlayer+il);
451 if(!(h3 = (TH3S*)gROOT->FindObject("Charge"))){
452 h3 = new TH3S("Charge", "dy=f(q)", 50, 2.2, 7.5, 60, -.3, .3, 60, -4., 4.);
453 h3->SetXTitle("log(q) [a.u.]");
454 h3->SetYTitle("#Delta y[cm]");
455 h3->SetZTitle("#Delta y/#sigma_{y}");
457 fContainer->AddAt(h3, kQRes);
459 fContainer->AddAt(arr = new TObjArray(kNTB), kSigm);
460 arr->SetName("Resolution");
461 for(Int_t ix=0; ix<kNTB; ix++){
462 if(!(h3=(TH3S*)gROOT->FindObject(Form("hr_x%02d", ix)))){
464 Form("hr_x%02d", ix),
465 Form(" t_{drift}(%3.1f-%3.1f)[#mus]", fAt->GetBinLowEdge(ix+1), fAt->GetBinUpEdge(ix+1)),
467 35, -.35, .35, // tgp
469 h3->SetXTitle("z [mm]");
470 h3->SetYTitle("tg#phi");
471 h3->SetZTitle("#Delta y[cm]");
476 fContainer->AddAt(arr = new TObjArray(kNTB), kMean);
477 arr->SetName("Systematics");
478 for(Int_t ix=0; ix<kNTB; ix++){
479 if(!(h3=(TH3S*)gROOT->FindObject(Form("hs_x%02d", ix)))){
481 Form("hs_x%02d", ix),
482 Form(" t_{drift}(%3.1f-%3.1f)[#mus]", fAt->GetBinLowEdge(ix+1), fAt->GetBinUpEdge(ix+1)),
484 35, -.35, .35, // tgp-h tgt
486 h3->SetXTitle("z [mm]");
487 h3->SetYTitle("tg(#phi) - h*tg(#theta)");
488 h3->SetZTitle("#Delta y[cm]");
496 //_______________________________________________________
497 void AliTRDclusterResolution::UserExec(Option_t *)
499 // Fill container histograms
501 if(!HasExB()) AliWarning("ExB was not set. Call SetExB() before running the task.");
504 Float_t x, y, z, q, dy, dydx, dzdx, cov[3], covcl[3];
507 // define limits around ExB for which x contribution is negligible
508 const Float_t kDtgPhi = 3.5e-2; //(+- 2 deg)
510 TObjArray *arr0 = (TObjArray*)fContainer->At(kCenter);
511 TObjArray *arr1 = (TObjArray*)fContainer->At(kSigm);
512 TObjArray *arr2 = (TObjArray*)fContainer->At(kMean);
514 const AliTRDclusterInfo *cli = NULL;
515 TIterator *iter=fInfo->MakeIterator();
516 while((cli=dynamic_cast<AliTRDclusterInfo*>((*iter)()))){
517 cli->GetCluster(det, x, y, z, q, t, covcl);
518 if(fDet>=0 && fDet!=det) continue;
520 dy = cli->GetResolution();
521 cli->GetGlobalPosition(y, z, dydx, dzdx, &cov[0]);
523 // resolution as a function of cluster charge
524 // only for phi equal exB
525 if(TMath::Abs(dydx-fExB) < kDtgPhi){
526 h3 = (TH3S*)fContainer->At(kQRes);
527 h3->Fill(TMath::Log(q), dy, dy/TMath::Sqrt(covcl[0]));
529 AliDebug(4, Form("q=%4.0f Log(q)=%6.4f dy[um]=%7.2f pull=%5.2f",q, TMath::Log(q), 1.e4*dy, dy/TMath::Sqrt(covcl[0])));
532 // do not use problematic clusters in resolution analysis
533 // TODO define limits as calibration aware (gain) !!
534 if(q<20. || q>250.) continue;
536 x = (t+.5)*fgkTimeBinLength; // conservative approach !!
538 // resolution as a function of y displacement from pad center
539 // only for phi equal exB
540 if(TMath::Abs(dydx-fExB) < kDtgPhi/* &&
541 TMath::Abs(x-0.675)<0.225*/){
542 Int_t ly(AliTRDgeometry::GetLayer(det));
543 h3 = (TH3S*)arr0->At(ly);
544 h3->Fill(x, cli->GetYDisplacement(), dy);
545 h3 = (TH3S*)arr0->At(AliTRDgeometry::kNlayer+ly);
546 h3->Fill(x, cli->GetYDisplacement(), dy/TMath::Sqrt(covcl[0]));
549 Int_t ix = fAt->FindBin(x);
550 if(ix==0 || ix == fAt->GetNbins()+1){
551 AliWarning(Form("Drift time %3.1f outside allowed range", x));
555 // fill histo for resolution (sigma)
556 ((TH3S*)arr1->At(ix-1))->Fill(10.*cli->GetAnisochronity(), dydx, dy);
558 // fill histo for systematic (mean)
559 ((TH3S*)arr2->At(ix-1))->Fill(10.*cli->GetAnisochronity(), dydx-cli->GetTilt()*dzdx, dy);
561 PostData(1, fContainer);
565 //_______________________________________________________
566 Bool_t AliTRDclusterResolution::PostProcess()
568 if(!fContainer) return kFALSE;
569 if(!HasExB()) AliWarning("ExB was not set. Call SetExB() before running the post processing.");
571 TObjArray *arr = NULL;
574 TGraphErrors *g = NULL;
575 fResults = new TObjArray(kNtasks);
576 fResults->SetOwner();
577 fResults->AddAt(arr = new TObjArray(3), kQRes);
579 arr->AddAt(g = new TGraphErrors(), 0);
580 g->SetLineColor(kBlue); g->SetMarkerColor(kBlue);
581 g->SetMarkerStyle(7);
582 arr->AddAt(g = new TGraphErrors(), 1);
583 g->SetLineColor(kRed); g->SetMarkerColor(kRed);
584 g->SetMarkerStyle(23);
585 arr->AddAt(g = new TGraphErrors(), 2);
586 g->SetLineColor(kGreen); g->SetMarkerColor(kGreen);
587 g->SetMarkerStyle(7);
589 // pad center dependence
590 fResults->AddAt(arr = new TObjArray(AliTRDgeometry::kNlayer+1), kCenter);
593 t = new TTree("cent", "dy=f(y,x,ly)"), 0);
594 t->Branch("ly", &fLy, "ly/B");
595 t->Branch("x", &fX, "x/F");
596 t->Branch("y", &fY, "y/F");
597 t->Branch("m", &fR[0], "m[2]/F");
598 t->Branch("s", &fR[2], "s[2]/F");
599 t->Branch("pm", &fP[0], "pm[2]/F");
600 t->Branch("ps", &fP[2], "ps[2]/F");
601 for(Int_t il=1; il<=AliTRDgeometry::kNlayer; il++){
602 arr->AddAt(g = new TGraphErrors(), il);
603 g->SetLineColor(il); g->SetLineStyle(il);
604 g->SetMarkerColor(il);g->SetMarkerStyle(4);
608 fResults->AddAt(t = new TTree("sigm", "dy=f(dw,x,dydx)"), kSigm);
609 t->Branch("t", &fX, "t/F");
610 t->Branch("z", &fZ, "z/F");
611 t->Branch("sx", &fR[0], "sx[2]/F");
612 t->Branch("sy", &fR[2], "sy[2]/F");
615 fResults->AddAt(t = new TTree("mean", "dy=f(dw,x,dydx - h dzdx)"), kMean);
616 t->Branch("t", &fX, "t/F");
617 t->Branch("z", &fZ, "z/F");
618 t->Branch("dx", &fR[0], "dx[2]/F");
619 t->Branch("dy", &fR[2], "dy[2]/F");
622 TIterator *iter=fResults->MakeIterator();
623 while((o=((*iter)()))) o->Clear(); // maybe it is wrong but we should never reach this point
626 // precalculated value of tg^2(alpha_L)
627 Double_t exb2 = fExB*fExB;
628 // square of the mean value of sigma drift length.
629 // has to come from previous calibration
630 //Double_t sxd2 = 1.;// [mm^2]
632 printf("ExB[%e] ExB2[%e]\n", fExB, exb2);
634 // process resolution dependency on charge
635 if(HasProcess(kQRes)) ProcessCharge();
637 // process resolution dependency on y displacement
638 if(HasProcess(kCenter)) ProcessCenterPad();
640 // process resolution dependency on drift legth and drift cell width
641 if(HasProcess(kSigm)) ProcessSigma();
643 // process systematic shift on drift legth and drift cell width
644 if(HasProcess(kMean)) ProcessMean();
649 //_______________________________________________________
650 Bool_t AliTRDclusterResolution::SetExB(Int_t det, Int_t col, Int_t row)
653 AliCDBManager *cdb = AliCDBManager::Instance();
654 if(cdb->GetRun() < 0){
655 AliError("OCDB manager not properly initialized");
659 // check magnetic field
660 if(TMath::Abs(AliTracker::GetBz()) < 1.e-10){
661 AliWarning("B=0. Magnetic field may not be initialized. Continue if you know what you are doing !");
664 // set reference detector if any
665 if(det>=0 && det<AliTRDgeometry::kNdet) fDet = det;
668 AliTRDcalibDB *fCalibration = AliTRDcalibDB::Instance();
669 AliTRDCalROC *fCalVdriftROC = fCalibration->GetVdriftROC(det);
670 const AliTRDCalDet *fCalVdriftDet = fCalibration->GetVdriftDet();
672 fVdrift = fCalVdriftDet->GetValue(det) * fCalVdriftROC->GetValue(col, row);
673 fExB = AliTRDCommonParam::Instance()->GetOmegaTau(fVdrift);
678 //_______________________________________________________
679 void AliTRDclusterResolution::SetVisual()
682 fCanvas = new TCanvas("clResCanvas", "Cluster Resolution Visualization", 10, 10, 600, 600);
685 //_______________________________________________________
686 void AliTRDclusterResolution::ProcessCharge()
688 // Resolution as a function of cluster charge.
690 // As described in the function ProcessCenterPad() the error parameterization for clusters for phi = a_L can be
693 // #sigma_{y}^{2} = #sigma_{y}^{2}|_{B=0} + tg^{2}(#alpha_{L})*#sigma_{x}^{2}
695 // with the contribution in case of B=0 given by:
697 // #sigma_{y}|_{B=0} = #sigma_{diff}*Gauss(0, s_{ly}) + #delta_{#sigma}(q)
699 // which further can be simplified to:
701 // <#sigma_{y}|_{B=0}>(q) = <#sigma_{y}> + #delta_{#sigma}(q)
702 // <#sigma_{y}> = #int{f(q)#sigma_{y}dq}
704 // The results for s_y and f(q) are displayed below:
706 //<img src="TRD/clusterQerror.gif">
708 // The function has to extended to accomodate gain calibration scalling and errors.
711 // Alexandru Bercuci <A.Bercuci@gsi.de>
714 if(!(h2 = (TH2I*)fContainer->At(kQRes))) {
715 AliWarning("Missing dy=f(Q) histo");
718 TF1 f("f", "gaus", -.5, .5);
722 // compute mean error on x
724 for(Int_t ix=5; ix<kNTB; ix++){
725 // retrieve error on the drift length
726 s2x += AliTRDcluster::GetSX(ix);
728 s2x /= (kNTB-5); s2x *= s2x;
729 Double_t exb2 = fExB*fExB;
731 TObjArray *arr = (TObjArray*)fResults->At(kQRes);
732 TGraphErrors *gqm = (TGraphErrors*)arr->At(0);
733 TGraphErrors *gqs = (TGraphErrors*)arr->At(1);
734 TGraphErrors *gqp = (TGraphErrors*)arr->At(2);
735 Double_t q, n = 0., entries;
737 for(Int_t ix=1; ix<=ax->GetNbins(); ix++){
738 q = TMath::Exp(ax->GetBinCenter(ix));
739 if(q<20. || q>250.) continue; // ?!
741 h1 = h2->ProjectionY("py", ix, ix);
742 entries = h1->GetEntries();
743 if(entries < 50) continue;
748 Int_t ip = gqm->GetN();
749 gqm->SetPoint(ip, q, 1.e4*f.GetParameter(1));
750 gqm->SetPointError(ip, 0., 1.e4*f.GetParError(1));
752 // correct sigma for ExB effect
753 gqs->SetPoint(ip, q, 1.e4*(f.GetParameter(2)*f.GetParameter(2)-exb2*s2x));
754 gqs->SetPointError(ip, 0., 1.e4*f.GetParError(2)*f.GetParameter(2));
758 gqp->SetPoint(ip, q, entries);
759 gqp->SetPointError(ip, 0., 0./*TMath::Sqrt(entries)*/);
762 // normalize probability and get mean sy
763 Double_t sm = 0., sy;
764 for(Int_t ip=gqp->GetN(); ip--;){
765 gqp->GetPoint(ip, q, entries);
767 gqp->SetPoint(ip, q, 1.e3*entries);
768 gqs->GetPoint(ip, q, sy);
772 // error parametrization s(q) = <sy> + b(1/q-1/q0)
773 TF1 fq("fq", "[0] + [1]/x", 20., 250.);
774 gqs->Fit(&fq/*, "W"*/);
775 printf("sm=%f [0]=%f [1]=%f\n", 1.e-4*sm, fq.GetParameter(0), fq.GetParameter(1));
776 printf(" const Float_t sq0inv = %f; // [1/q0]\n", (sm-fq.GetParameter(0))/fq.GetParameter(1));
777 printf(" const Float_t sqb = %f; // [cm]\n", 1.e-4*fq.GetParameter(1));
780 //_______________________________________________________
781 void AliTRDclusterResolution::ProcessCenterPad()
783 // Resolution as a function of y displacement from pad center and drift length.
785 // Since the error parameterization of cluster r-phi position can be written as (see AliTRDcluster::SetSigmaY2()):
787 // #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
789 // one can see that for phi = a_L one gets the following expression:
791 // #sigma_{y}^{2} = #sigma_{y}^{2}|_{B=0} + tg^{2}(#alpha_{L})*#sigma_{x}^{2}
793 // where we have explicitely marked the remaining term in case of absence of magnetic field. Thus one can use the
794 // previous equation to estimate s_y for B=0 and than by comparing in magnetic field conditions one can get the s_x.
795 // This is a simplified method to determine the error parameterization for s_x and s_y as compared to the one
796 // implemented in ProcessSigma(). For more details on cluster error parameterization please see also
797 // AliTRDcluster::SetSigmaY2()
799 // The representation of dy=f(y_cen, x_drift| layer) can be also used to estimate the systematic shift in the r-phi
800 // coordinate resulting from imperfection in the cluster shape parameterization. From the expresion of the shift derived
801 // in ProcessMean() with phi=exb one gets:
803 // <#Delta y>= <#delta x> * (tg(#alpha_{L})-h*dz/dx) + <#delta y - #delta x * tg(#alpha_{L})>
804 // <#Delta y>(y_{cen})= -h*<#delta x>(x_{drift}, q_{cl}) * dz/dx + #delta y(y_{cen}, ...)
806 // where all dependences are made explicit. This last expression can be used in two ways:
807 // - by average on the dz/dx we can determine directly dy (the method implemented here)
808 // - by plotting as a function of dzdx one can determine both dx and dy components in an independent method.
810 //<img src="TRD/clusterYcorr.gif">
813 // Alexandru Bercuci <A.Bercuci@gsi.de>
815 TObjArray *arr = (TObjArray*)fContainer->At(kCenter);
817 AliWarning("Missing dy=f(y | x, ly) container");
820 Double_t exb2 = fExB*fExB;
821 Float_t s[AliTRDgeometry::kNlayer];
822 TF1 f("f", "gaus", -.5, .5);
823 TF1 fp("fp", "gaus", -3.5, 3.5);
825 TH1D *h1 = NULL; TH2F *h2 = NULL; TH3S *h3r=NULL, *h3p=NULL;
826 TObjArray *arrRes = (TObjArray*)fResults->At(kCenter);
827 TTree *t = (TTree*)arrRes->At(0);
828 TGraphErrors *gs = NULL;
831 printf(" const Float_t lSy[6][24] = {\n {");
832 const Int_t nl = AliTRDgeometry::kNlayer;
833 for(Int_t il=0; il<nl; il++){
834 if(!(h3r = (TH3S*)arr->At(il))) continue;
835 if(!(h3p = (TH3S*)arr->At(nl+il))) continue;
836 gs = (TGraphErrors*)arrRes->At(il+1);
838 // printf("Ly[%d]\n", il);
839 for(Int_t ix=1; ix<=h3r->GetXaxis()->GetNbins(); ix++){
840 ax = h3r->GetXaxis(); ax->SetRange(ix, ix);
841 ax = h3p->GetXaxis(); ax->SetRange(ix, ix);
842 fX = ax->GetBinCenter(ix);
843 // printf(" x[%2d]=%4.2f\n", ix, fX);
844 for(Int_t iy=1; iy<=h3r->GetYaxis()->GetNbins(); iy++){
845 ax = h3r->GetYaxis(); ax->SetRange(iy, iy);
846 ax = h3p->GetYaxis(); ax->SetRange(iy, iy);
847 fY = ax->GetBinCenter(iy);
848 // printf(" y[%2d]=%5.2f\n", iy, fY);
849 // finish navigation in the HnSparse
851 h1 = (TH1D*)h3r->Project3D("z");
852 Int_t entries = (Int_t)h1->Integral();
853 if(entries < 50) continue;
857 // Fill sy,my=f(y_w,x,ly)
858 fR[0] = f.GetParameter(1); fR[1] = f.GetParError(1);
859 fR[2] = f.GetParameter(2); fR[3] = f.GetParError(2);
861 h1 = (TH1D*)h3p->Project3D("z");
863 fP[0] = fp.GetParameter(1); fP[1] = fp.GetParError(1);
864 fP[2] = fp.GetParameter(2); fP[3] = fp.GetParError(2);
866 //printf("ly[%d] x[%3.1f] y[%+5.2f] m[%5.3f] s[%5.3f] \n", fLy, fX, fY, fR[0], fR[2]);
872 t->Draw("y:x>>h(24, 0., 2.4, 51, -.51, .51)",
873 Form("s[0]*(ly==%d&&abs(m[0])<1.e-1)", fLy),
875 h2=(TH2F*)gROOT->FindObject("h");
876 f.FixParameter(1, 0.);
877 Int_t n = h2->GetXaxis()->GetNbins(), nn(0); s[il]=0.;
879 for(Int_t ix=1; ix<=n; ix++){
881 fX = ax->GetBinCenter(ix);
882 h1 = h2->ProjectionY("hCenPy", ix, ix);
883 //if((Int_t)h1->Integral() < 1.e-10) continue;
885 // Apply lorentz angle correction
886 // retrieve error on the drift length
887 Double_t s2x = AliTRDcluster::GetSX(ix-1); s2x *= s2x;
889 for(Int_t iy=1; iy<=h1->GetNbinsX(); iy++){
890 Double_t s2 = h1->GetBinContent(iy); s2*= s2;
891 // sigma square corrected for Lorentz angle
892 // s2 = s2_y(y_w,x)+exb2*s2_x
893 Double_t sy = TMath::Sqrt(TMath::Max(s2 - exb2*s2x, Double_t(0.)));
894 if(sy<1.e-20) continue;
895 h1->SetBinContent(iy, sy); nnn++;
896 printf("s[%6.2f] sx[%6.2f] sy[%6.2f]\n",
897 1.e4*TMath::Sqrt(s2), 1.e4*TMath::Abs(fExB*AliTRDcluster::GetSX(ix-1)),
898 1.e4*h1->GetBinContent(iy));
900 // do fit only if enough data
904 sPRF = f.GetParameter(2);
908 printf("%6.4f,%s", sPRF, ix%6?" ":"\n ");
909 Int_t jx = gs->GetN();
910 gs->SetPoint(jx, fX, 1.e4*sPRF);
911 gs->SetPointError(jx, 0., 0./*f.GetParError(0)*/);
916 f.ReleaseParameter(2);
919 if(!fCanvas) continue;
921 fCanvas->Modified(); fCanvas->Update();
922 if(IsSaveAs()) fCanvas->SaveAs(Form("Figures/ProcessCenter_ly[%d].gif", fLy));
923 else gSystem->Sleep(100);
926 printf(" const Float_t lPRF[] = {"
927 "%5.3f, %5.3f, %5.3f, %5.3f, %5.3f, %5.3f};\n",
928 s[0], s[1], s[2], s[3], s[4], s[5]);
931 //_______________________________________________________
932 void AliTRDclusterResolution::ProcessSigma()
934 // As the r-phi coordinate is the only one which is measured by the TRD detector we have to rely on it to
935 // estimate both the radial (x) and r-phi (y) errors. This method is based on the following assumptions.
936 // The measured error in the y direction is the sum of the intrinsic contribution of the r-phi measurement
937 // with the contribution of the radial measurement - because x is not a parameter of Alice track model (Kalman).
939 // #sigma^{2}|_{y} = #sigma^{2}_{y*} + #sigma^{2}_{x*}
941 // In the general case
943 // #sigma^{2}_{y*} = #sigma^{2}_{y} + tg^{2}(#alpha_{L})#sigma^{2}_{x_{drift}}
944 // #sigma^{2}_{x*} = tg^{2}(#phi - #alpha_{L})*(#sigma^{2}_{x_{drift}} + #sigma^{2}_{x_{0}} + tg^{2}(#alpha_{L})*x^{2}/12)
946 // where we have explicitely show the lorentz angle correction on y and the projection of radial component on the y
947 // direction through the track angle in the bending plane (phi). Also we have shown that the radial component in the
948 // last equation has twp terms, the drift and the misalignment (x_0). For ideal geometry or known misalignment one
949 // can solve the equation
951 // #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}]
953 // by fitting a straight line:
955 // #sigma^{2}|_{y} = a(x_{cl}, z_{cl}) * tg^{2}(#phi - #alpha_{L}) + b(x_{cl}, z_{cl})
957 // the error parameterization will be given by:
959 // #sigma_{x} (x_{cl}, z_{cl}) = #sqrt{a(x_{cl}, z_{cl}) - tg^{2}(#alpha_{L})*x^{2}/12}
960 // #sigma_{y} (x_{cl}, z_{cl}) = #sqrt{b(x_{cl}, z_{cl}) - #sigma^{2}_{x} (x_{cl}, z_{cl}) * tg^{2}(#alpha_{L})}
962 // Below there is an example of such dependency.
964 //<img src="TRD/clusterSigmaMethod.gif">
967 // The error parameterization obtained by this method are implemented in the functions AliTRDcluster::GetSX() and
968 // AliTRDcluster::GetSYdrift(). For an independent method to determine s_y as a function of drift length check the
969 // function ProcessCenterPad(). One has to keep in mind that while this method return the mean s_y over the distance
970 // to pad center distribution the other method returns the *STANDARD* value at center=0 (maximum). To recover the
971 // standard value one has to solve the obvious equation:
973 // #sigma_{y}^{STANDARD} = #frac{<#sigma_{y}>}{#int{s exp(s^{2}/#sigma) ds}}
975 // with "<s_y>" being the value calculated here and "sigma" the width of the s_y distribution calculated in
976 // ProcessCenterPad().
979 // Alexandru Bercuci <A.Bercuci@gsi.de>
981 TObjArray *arr = (TObjArray*)fContainer->At(kSigm);
983 AliWarning("Missing dy=f(x_d, d_w) container");
987 // init visualization
988 TGraphErrors *ggs = NULL;
991 ggs = new TGraphErrors();
993 line->SetLineColor(kRed);line->SetLineWidth(2);
996 // init logistic support
997 TF1 f("f", "gaus", -.5, .5);
998 TLinearFitter gs(1,"pol1");
1000 TH1D *h1 = NULL; TH3S *h3=NULL;
1002 Double_t exb2 = fExB*fExB, x;
1004 TTree *t = (TTree*)fResults->At(kSigm);
1005 for(Int_t ix=0; ix<kNTB; ix++){
1006 if(!(h3=(TH3S*)arr->At(ix))) continue;
1008 x = c.GetXloc(0., 1.5);
1009 fX= fAt->GetBinCenter(ix+1);
1010 for(Int_t iz=1; iz<=h3->GetXaxis()->GetNbins(); iz++){
1011 ax = h3->GetXaxis();
1012 ax->SetRange(iz, iz);
1013 fZ = ax->GetBinCenter(iz);
1015 // reset visualization
1017 new(ggs) TGraphErrors();
1018 ggs->SetMarkerStyle(7);
1022 for(Int_t ip=1; ip<=h3->GetYaxis()->GetNbins(); ip++){
1023 ax = h3->GetYaxis();
1024 ax->SetRange(ip, ip);
1025 Double_t tgl = ax->GetBinCenter(ip);
1026 // finish navigation in the HnSparse
1028 //if(TMath::Abs(dydx)>0.18) continue;
1029 Double_t tgg = (tgl-fExB)/(1.+tgl*fExB);
1030 Double_t tgg2 = tgg*tgg;
1032 h1 = (TH1D*)h3->Project3D("z");
1033 Int_t entries = (Int_t)h1->Integral();
1034 if(entries < 50) continue;
1038 Double_t s2 = f.GetParameter(2)*f.GetParameter(2);
1039 Double_t s2e = 2.*f.GetParameter(2)*f.GetParError(2);
1040 // Fill sy^2 = f(tg^2(phi-a_L))
1041 gs.AddPoint(&tgg2, s2, s2e);
1044 Int_t jp = ggs->GetN();
1045 ggs->SetPoint(jp, tgg2, s2);
1046 ggs->SetPointError(jp, 0., s2e);
1048 // TODO here a more robust fit method has to be provided
1049 // for which lower boundaries on the parameters have to
1050 // be imposed. Unfortunately the Minuit fit does not work
1051 // for the TGraph in the case of B not 0.
1052 if(gs.Eval()) continue;
1054 fR[0] = gs.GetParameter(1) - x*x*exb2/12.;
1055 printf("s2x+x2=%f ang=%f s2x=%f\n", gs.GetParameter(1), x*x*exb2/12., fR[0]);
1056 fR[0] = TMath::Max(fR[0], Float_t(4.e-4));
1058 // s^2_y = s0^2_y + tg^2(a_L) * s^2_x
1059 // s0^2_y = f(D_L)*x + s_PRF^2
1060 fR[2]= gs.GetParameter(0)-exb2*fR[0];
1061 printf("s2y+s2x=%f s2y=%f\n", fR[0], fR[2]);
1062 fR[2] = TMath::Max(fR[2], Float_t(2.5e-5));
1063 fR[0] = TMath::Sqrt(fR[0]);
1064 fR[1] = .5*gs.GetParError(1)/fR[0];
1065 fR[2] = TMath::Sqrt(fR[2]);
1066 fR[3] = gs.GetParError(0)+exb2*exb2*gs.GetParError(1);
1068 printf(" xd=%4.2f[cm] sx=%6.1f[um] sy=%5.1f[um]\n", x, 1.e4*fR[0], 1.e4*fR[2]);
1070 if(!fCanvas) continue;
1071 fCanvas->cd(); fCanvas->SetLogx(); //fCanvas->SetLogy();
1073 fCanvas->SetMargin(0.15, 0.01, 0.1, 0.01);
1074 hFrame=new TH1I("hFrame", "", 100, 0., .3);
1075 hFrame->SetMinimum(0.);hFrame->SetMaximum(.005);
1076 hFrame->SetXTitle("tg^{2}(#phi-#alpha_{L})");
1077 hFrame->SetYTitle("#sigma^{2}y[cm^{2}]");
1078 hFrame->GetYaxis()->SetTitleOffset(2.);
1079 hFrame->SetLineColor(1);hFrame->SetLineWidth(1);
1081 } else hFrame->Reset();
1082 Double_t xx = 0., dxx=.2/50;
1083 for(Int_t ip=0;ip<50;ip++){
1084 line->SetPoint(ip, xx, gs.GetParameter(0)+xx*gs.GetParameter(1));
1087 ggs->Draw("pl"); line->Draw("l");
1088 fCanvas->Modified(); fCanvas->Update();
1089 if(IsSaveAs()) fCanvas->SaveAs(Form("Figures/ProcessSigma_z[%5.3f]_x[%5.3f].gif", fZ, fX));
1090 else gSystem->Sleep(100);
1096 //_______________________________________________________
1097 void AliTRDclusterResolution::ProcessMean()
1099 // By this method the cluster shift in r-phi and radial directions can be estimated by comparing with the MC.
1100 // The resolution of the cluster corrected for pad tilt with respect to MC in the r-phi (measuring) plane can be
1103 // #Delta y=w - y_{MC}(x_{cl})
1104 // w = y_{cl}^{'} + h*(z_{MC}(x_{cl})-z_{cl})
1105 // y_{MC}(x_{cl}) = y_{0} - dy/dx*x_{cl}
1106 // z_{MC}(x_{cl}) = z_{0} - dz/dx*x_{cl}
1107 // y_{cl}^{'} = y_{cl}-x_{cl}*tg(#alpha_{L})
1109 // where x_cl is the drift length attached to a cluster, y_cl is the r-phi coordinate of the cluster measured by
1110 // charge sharing on adjacent pads and y_0 and z_0 are MC reference points (as example the track references at
1111 // entrance/exit of a chamber). If we suppose that both r-phi (y) and radial (x) coordinate of the clusters are
1112 // affected by errors we can write
1114 // x_{cl} = x_{cl}^{*} + #delta x
1115 // y_{cl} = y_{cl}^{*} + #delta y
1117 // where the starred components are the corrected values. Thus by definition the following quantity
1119 // #Delta y^{*}= w^{*} - y_{MC}(x_{cl}^{*})
1121 // has 0 average over all dependency. Using this decomposition we can write:
1123 // <#Delta y>=<#Delta y^{*}> + <#delta x * (dy/dx-h*dz/dx) + #delta y - #delta x * tg(#alpha_{L})>
1125 // which can be transformed to the following linear dependence:
1127 // <#Delta y>= <#delta x> * (dy/dx-h*dz/dx) + <#delta y - #delta x * tg(#alpha_{L})>
1129 // if expressed as function of dy/dx-h*dz/dx. Furtheremore this expression can be plotted for various clusters
1130 // i.e. we can explicitely introduce the diffusion (x_cl) and drift cell - anisochronity (z_cl) dependences. From
1131 // plotting this dependence and linear fitting it with:
1133 // <#Delta y>= a(x_{cl}, z_{cl}) * (dy/dx-h*dz/dx) + b(x_{cl}, z_{cl})
1135 // the systematic shifts will be given by:
1137 // #delta x (x_{cl}, z_{cl}) = a(x_{cl}, z_{cl})
1138 // #delta y (x_{cl}, z_{cl}) = b(x_{cl}, z_{cl}) + a(x_{cl}, z_{cl}) * tg(#alpha_{L})
1140 // Below there is an example of such dependency.
1142 //<img src="TRD/clusterShiftMethod.gif">
1145 // The occurance of the radial shift is due to the following conditions
1146 // - the approximation of a constant drift velocity over the drift length (larger drift velocities close to
1147 // cathode wire plane)
1148 // - the superposition of charge tails in the amplification region (first clusters appear to be located at the
1150 // - the superposition of charge tails in the drift region (shift towards anode wire)
1151 // - diffusion effects which convolute with the TRF thus enlarging it
1152 // - approximate knowledge of the TRF (approximate measuring in test beam conditions)
1154 // The occurance of the r-phi shift is due to the following conditions
1155 // - approximate model for cluster shape (LUT)
1156 // - rounding-up problems
1158 // The numerical results for ideal simulations for the radial and r-phi shifts are displayed below and used
1159 // for the cluster reconstruction (see the functions AliTRDcluster::GetXcorr() and AliTRDcluster::GetYcorr()).
1161 //<img src="TRD/clusterShiftX.gif">
1162 //<img src="TRD/clusterShiftY.gif">
1164 // More details can be found in the presentation given during the TRD
1165 // software meeting at the end of 2008 and beginning of year 2009, published on indico.cern.ch.
1168 // Alexandru Bercuci <A.Bercuci@gsi.de>
1172 TObjArray *arr = (TObjArray*)fContainer->At(kMean);
1174 AliWarning("Missing dy=f(x_d, d_w) container");
1178 // init logistic support
1179 TF1 f("f", "gaus", -.5, .5);
1180 TF1 line("l", "[0]+[1]*x", -.15, .15);
1181 TGraphErrors *gm = new TGraphErrors();
1183 TH1D *h1 = NULL; TH3S *h3 =NULL;
1188 TTree *t = (TTree*)fResults->At(kMean);
1189 for(Int_t ix=0; ix<kNTB; ix++){
1190 if(!(h3=(TH3S*)arr->At(ix))) continue;
1192 x = c.GetXloc(0., 1.5);
1193 fX= fAt->GetBinCenter(ix+1);
1194 for(Int_t iz=1; iz<=h3->GetXaxis()->GetNbins(); iz++){
1195 ax = h3->GetXaxis();
1196 ax->SetRange(iz, iz);
1197 fZ = ax->GetBinCenter(iz);
1200 new(gm) TGraphErrors();
1201 gm->SetMarkerStyle(7);
1203 for(Int_t ip=1; ip<=h3->GetYaxis()->GetNbins(); ip++){
1204 ax = h3->GetYaxis();
1205 ax->SetRange(ip, ip);
1206 Double_t tgl = ax->GetBinCenter(ip);
1207 // finish navigation in the HnSparse
1209 h1 = (TH1D*)h3->Project3D("z");
1210 Int_t entries = (Int_t)h1->Integral();
1211 if(entries < 50) continue;
1215 // Fill <Dy> = f(dydx - h*dzdx)
1216 Int_t jp = gm->GetN();
1217 gm->SetPoint(jp, tgl, f.GetParameter(1));
1218 gm->SetPointError(jp, 0., f.GetParError(1));
1220 if(gm->GetN()<4) continue;
1222 gm->Fit(&line, "QN");
1223 fR[0] = line.GetParameter(1); // dx
1224 fR[1] = line.GetParError(1);
1225 fR[2] = line.GetParameter(0) + fExB*fR[0]; // xs = dy - tg(a_L)*dx
1227 printf(" xd=%4.2f[cm] dx=%6.2f[um] dy=%6.2f[um]\n", x, 1.e4*fR[0], 1.e4*fR[2]);
1229 if(!fCanvas) continue;
1232 fCanvas->SetMargin(0.1, 0.02, 0.1, 0.01);
1233 hFrame=new TH1I("hFrame", "", 100, -.3, .3);
1234 hFrame->SetMinimum(-.1);hFrame->SetMaximum(.1);
1235 hFrame->SetXTitle("tg#phi-htg#theta");
1236 hFrame->SetYTitle("#Delta y[cm]");
1237 hFrame->GetYaxis()->SetTitleOffset(1.5);
1238 hFrame->SetLineColor(1);hFrame->SetLineWidth(1);
1240 } else hFrame->Reset();
1241 gm->Draw("pl"); line.Draw("same");
1242 fCanvas->Modified(); fCanvas->Update();
1243 if(IsSaveAs()) fCanvas->SaveAs(Form("Figures/ProcessMean_Z[%5.3f]_X[%5.3f].gif", fZ, fX));
1244 else gSystem->Sleep(100);