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CombineFeedDownMCSubtractionMethodsUncertainties.C
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1 #if !defined(__CINT__) || defined(__MAKECINT__)
2 #include "TFile.h"
3 #include "TH1.h"
4 #include "TH1D.h"
5 #include "TH2.h"
6 #include "TH2F.h"
7 #include "TGraphAsymmErrors.h"
8 #include "TCanvas.h"
9 #include "TLegend.h"
10 #include "TMath.h"
11 #include "TROOT.h"
12 #include "TStyle.h"
13 #include "AliHFSystErr.h"
14 #include <Riostream.h>
15 #endif
16 
17 /* $Id$ */
18 
19 
20 //_________________________________________________________________________________________
21 //
22 // Macro to combine the the MonteCarlo B feed-down subtraction uncertainties
23 //
24 // Take as input the output files from the HFPtSpectrum class
25 // from both fc & Nb subtraction methods and combine the uncertainties.
26 // The final central value is set as the one from the Nb-method.
27 // The final uncertainties are defined as the envelope of both fc & Nb
28 // uncertainties with respect to the new central-value.
29 // The final global uncertainties are also defined and a preliminary drawing done.
30 //
31 //
32 // Usage parameters:
33 // 1. HFPtSpectrum fc subtraction file
34 // 2. HFPtSpectrum Nb subtraction file
35 // 3. Output file name
36 // 4. FONLL theoretical predictions file to draw on top
37 // 5. Decay channel as defined in the AliHFSystErr class
38 //
39 //_________________________________________________________________________________________
40 
42 
43 void CombineFeedDownMCSubtractionMethodsUncertainties(const char *fcfilename="HFPtSpectrum_D0Kpi_method1_221110_newnorm.root",
44  const char *nbfilename="HFPtSpectrum_D0Kpi_method2_221110_newnorm.root",
45  const char *outfilename="HFPtSpectrum_D0Kpi_combinedFD.root",
46  const char *thfilename="D0DplusDstarPredictions_y05.root",
47  Int_t decay=1, Int_t centrality=kpp7)
48 {
49 
50  //
51  // Get fc file inputs
52  TFile * fcfile = new TFile(fcfilename,"read");
53  TH1D * histoSigmaCorrFc = (TH1D*)fcfile->Get("histoSigmaCorr");
54  histoSigmaCorrFc->SetNameTitle("histoSigmaCorrFc","histoSigmaCorrFc");
55  TGraphAsymmErrors * gSigmaCorrFc = (TGraphAsymmErrors*)fcfile->Get("gSigmaCorr");
56  gSigmaCorrFc->SetNameTitle("gSigmaCorrFc","gSigmaCorrFc");
57  TGraphAsymmErrors * gSigmaCorrConservativeFc = (TGraphAsymmErrors*)fcfile->Get("gSigmaCorrConservative");
58  gSigmaCorrConservativeFc->SetNameTitle("gSigmaCorrConservativeFc","Cross section (fc prompt fraction)");
59  TGraphAsymmErrors * gFcConservativeFc = (TGraphAsymmErrors*)fcfile->Get("gFcConservative");
60  gFcConservativeFc->SetNameTitle("gFcConservativeFc","fc prompt fraction");
61 
62  //
63  // Get Nb file inputs
64  TFile * nbfile = new TFile(nbfilename,"read");
65  TH1D * histoSigmaCorrNb = (TH1D*)nbfile->Get("histoSigmaCorr");
66  histoSigmaCorrNb->SetNameTitle("histoSigmaCorrNb","histoSigmaCorrNb");
67  TGraphAsymmErrors * gSigmaCorrNb = (TGraphAsymmErrors*)nbfile->Get("gSigmaCorr");
68  gSigmaCorrNb->SetNameTitle("gSigmaCorrNb","gSigmaCorrNb");
69  TGraphAsymmErrors * gSigmaCorrConservativeNb = (TGraphAsymmErrors*)nbfile->Get("gSigmaCorrConservative");
70  gSigmaCorrConservativeNb->SetNameTitle("gSigmaCorrConservativeNb","Cross section (Nb prompt fraction)");
71  TGraphAsymmErrors * gFcConservativeNb = (TGraphAsymmErrors*)nbfile->Get("gFcConservative");
72  gFcConservativeNb->SetNameTitle("gFcConservativeNb","Nb prompt fraction");
73 
74  //
75  // Get the predictions input
76  TFile *thfile = new TFile(thfilename,"read");
77  TGraphAsymmErrors * thD0KpifromBprediction = (TGraphAsymmErrors*)thfile->Get("D0Kpiprediction");
78  TGraphAsymmErrors * thDpluskpipiprediction = (TGraphAsymmErrors*)thfile->Get("Dpluskpipiprediction");
79  TGraphAsymmErrors * thDstarD0piprediction = (TGraphAsymmErrors*)thfile->Get("DstarD0piprediction");
80  TGraphAsymmErrors * thDsKKpiprediction = (TGraphAsymmErrors*)thfile->Get("DsKkpiprediction");
81 
82  thD0KpifromBprediction->SetLineColor(4);
83  thD0KpifromBprediction->SetFillColor(kAzure+9);
84  thDpluskpipiprediction->SetLineColor(4);
85  thDpluskpipiprediction->SetFillColor(kAzure+9);
86  thDstarD0piprediction->SetLineColor(4);
87  thDstarD0piprediction->SetFillColor(kAzure+9);
88  thDsKKpiprediction->SetLineColor(4);
89  thDsKKpiprediction->SetFillColor(kAzure+9);
90 
91  //
92  // Get the spectra bins & limits
93  Int_t nbins = histoSigmaCorrFc->GetNbinsX();
94  Double_t *limits = new Double_t[nbins+1];
95  Double_t xlow=0., binwidth=0.;
96  for (Int_t i=1; i<=nbins; i++) {
97  binwidth = histoSigmaCorrFc->GetBinWidth(i);
98  xlow = histoSigmaCorrFc->GetBinLowEdge(i);
99  limits[i-1] = xlow;
100  }
101  limits[nbins] = xlow + binwidth;
102 
103 
104  //
105  // Define a new histogram with the real-data reconstructed spectrum binning
106  // they will be filled with central value equal to the Nb result
107  // and uncertainties taken from the envelope of the result uncertainties
108  // The systematical unc. (but FD) will also be re-calculated
109  //
110  TH1D * histoSigmaCorr = new TH1D("histoSigmaCorr","corrected cross-section (combined fc and Nb MC feed-down subtraction)",nbins,limits);
111  TGraphAsymmErrors * gSigmaCorr = new TGraphAsymmErrors(nbins+1);
112  gSigmaCorr->SetNameTitle("gSigmaCorr","gSigmaCorr (combined fc and Nb MC FD)");
113  TGraphAsymmErrors * gFcCorrConservative = new TGraphAsymmErrors(nbins+1);
114  gFcCorrConservative->SetNameTitle("gFcCorrConservative","Combined prompt fraction");
115  TGraphAsymmErrors * gSigmaCorrConservative = new TGraphAsymmErrors(nbins+1);
116  gSigmaCorrConservative->SetNameTitle("gSigmaCorrConservative","Cross section (combined prompt fraction)");
117  TGraphAsymmErrors * gSigmaCorrConservativePC = new TGraphAsymmErrors(nbins+1);
118  gSigmaCorrConservativePC->SetNameTitle("gSigmaCorrConservativePC","Conservative gSigmaCorr (combined fc and Nb MC FD) in percentages [for drawing with AliHFSystErr]");
119 
120  //
121  // Call the systematics uncertainty class for a given decay
122  // will help to compute the systematical unc. (but FD)
123  AliHFSystErr systematics;
124  if( centrality==kpp276 ) {
125  systematics.SetIsLowEnergy(true);
126  } else if( centrality!=kpp7 ) {
127  systematics.SetCollisionType(1);
128  if ( centrality == k020 ) {
129  systematics.SetCentrality("020");
130  }
131  else if ( centrality == k4080 ) {
132  systematics.SetCentrality("4080");
133  }
134  else {
135  cout << " Systematics not yet implemented " << endl;
136  return;
137  }
138  }
139  else { systematics.SetCollisionType(0); }
140  systematics.Init(decay);
141 
142  //
143  // Loop on all the bins to do the calculations
144  //
145  Double_t pt=0., average = 0., averageStatUnc=0., avErrx=0., avErryl=0., avErryh=0., avErryfdl=0., avErryfdh=0.;
146  Double_t avErrylPC=0., avErryhPC=0., avErryfdlPC=0., avErryfdhPC=0.;
147  Double_t valFc = 0., valFcErrstat=0., valFcErrx=0., valFcErryl=0., valFcErryh=0., valFcErryfdl=0., valFcErryfdh=0.;
148  Double_t valNb = 0., valNbErrstat=0., valNbErrx=0., valNbErryl=0., valNbErryh=0., valNbErryfdl=0., valNbErryfdh=0.;
149  Double_t corrfd = 0., corrfdl=0., corrfdh=0.;
150  //
151  for(Int_t ibin=1; ibin<=nbins; ibin++){
152 
153  // Get input values from fc method
154  valFc = histoSigmaCorrFc->GetBinContent(ibin);
155  pt = histoSigmaCorrFc->GetBinCenter(ibin);
156  valFcErrstat = histoSigmaCorrFc->GetBinError(ibin);
157  Double_t value =0., ptt=0.;
158  gSigmaCorrConservativeFc->GetPoint(ibin,ptt,value);
159  if (value<=0.) continue;
160  if ( TMath::Abs(valFc-value)>0.1 || TMath::Abs(pt-ptt)>0.1 )
161  cout << "Hey you ! There might be a problem with the fc input file, please, have a look !" << endl;
162  valFcErrx = gSigmaCorrFc->GetErrorXlow(ibin);
163  valFcErryl = gSigmaCorrFc->GetErrorYlow(ibin);
164  valFcErryh = gSigmaCorrFc->GetErrorYhigh(ibin);
165  valFcErryfdl = TMath::Abs( gSigmaCorrConservativeFc->GetErrorYlow(ibin) );
166  valFcErryfdh = TMath::Abs( gSigmaCorrConservativeFc->GetErrorYhigh(ibin) );
167  Double_t valfdFc = 0., x=0.;
168  gFcConservativeFc->GetPoint(ibin,x,valfdFc);
169  Double_t valfdFch = gFcConservativeFc->GetErrorYhigh(ibin);
170  Double_t valfdFcl = gFcConservativeFc->GetErrorYlow(ibin);
171 
172  // Get input values from Nb method
173  valNb = histoSigmaCorrNb->GetBinContent(ibin);
174  pt = histoSigmaCorrNb->GetBinCenter(ibin);
175  valNbErrstat = histoSigmaCorrNb->GetBinError(ibin);
176  gSigmaCorrConservativeNb->GetPoint(ibin,ptt,value);
177  if ( TMath::Abs(valNb-value)>0.1 || TMath::Abs(pt-ptt)>0.1 )
178  cout << "Hey you ! There might be a problem with the Nb input file, please, have a look !" << endl;
179  valNbErrx = gSigmaCorrNb->GetErrorXlow(ibin);
180  valNbErryl = gSigmaCorrNb->GetErrorYlow(ibin);
181  valNbErryh = gSigmaCorrNb->GetErrorYhigh(ibin);
182  valNbErryfdl = gSigmaCorrConservativeNb->GetErrorYlow(ibin);
183  valNbErryfdh = gSigmaCorrConservativeNb->GetErrorYhigh(ibin);
184  Double_t valfdNb = 0.;
185  gFcConservativeNb->GetPoint(ibin,x,valfdNb);
186  Double_t valfdNbh = gFcConservativeNb->GetErrorYhigh(ibin);
187  Double_t valfdNbl = gFcConservativeNb->GetErrorYlow(ibin);
188 
189 
190  // Compute the FD combined value
191  // average = valNb
192  average = valNb ;
193  corrfd = valfdNb;
194  avErrx = valFcErrx;
195  if ( TMath::Abs( valFcErrx - valNbErrx ) > 0.1 )
196  cout << "Hey you ! There might be consistency problem with the fc & Nb input files, please, have a look !" << endl;
197  averageStatUnc = valNbErrstat ;
198 // cout << " pt=" << pt << ", average="<<average<<endl;
199 // cout << " stat unc (pc)=" << averageStatUnc/average << ", stat-fc (pc)="<<(valFcErrstat/valFc) << ", stat-Nb (pc)="<<(valNbErrstat/valNb)<<endl;
200 
201  // now estimate the new feed-down combined uncertainties
202  Double_t minimum[2] = { (valFc - valFcErryfdl), (valNb - valNbErryfdl) };
203  Double_t maximum[2] = { (valFc + valFcErryfdh), (valNb + valNbErryfdh) };
204  avErryfdl = average - TMath::MinElement(2,minimum);
205  avErryfdh = TMath::MaxElement(2,maximum) - average;
206  avErryfdlPC = avErryfdl / average ; // in percentage
207  avErryfdhPC = avErryfdh / average ; // in percentage
208 // cout << " fc : val " << valFc << " + " << valFcErryfdh <<" - " << valFcErryfdl <<endl;
209 // cout << " Nb : val " << valNb << " + " << valNbErryfdh <<" - " << valNbErryfdl <<endl;
210 // cout << " fc & Nb: val " << average << " + " << avErryfdh <<" - " << avErryfdl <<endl;
211  Double_t minimumfc[2] = { (valfdNb - valfdNbl), (valfdFc - valfdFcl) };
212  Double_t maximumfc[2] = { (valfdNb + valfdNbh), (valfdFc + valfdFch) };
213  corrfdl = corrfd - TMath::MinElement(2,minimumfc);
214  corrfdh = TMath::MaxElement(2,maximumfc) - corrfd;
215 
216 
217  // compute the global systematics
218  avErrylPC = systematics.GetTotalSystErr(pt,avErryfdlPC); // in percentage
219  avErryhPC = systematics.GetTotalSystErr(pt,avErryfdhPC); // in percentage
220  avErryl = avErrylPC * average ;
221  avErryh = avErryhPC * average ;
222 // cout << " syst av-l="<<avErryl<<", av-h="<<avErryh<<endl;
223 // cout << " fd-l-pc="<<avErryfdlPC<<", fd-h-pc="<<avErryfdhPC<<", syst err(no fd)-pc="<<systematics.GetTotalSystErr(pt)<<", av-l-pc="<<avErrylPC<<", av-h-pc="<<avErryhPC<<endl;
224 
225  // fill in the histos and TGraphs
226  // fill them only when for non empty bins
227  if ( average > 0.1 ) {
228  histoSigmaCorr->SetBinContent(ibin,average);
229  histoSigmaCorr->SetBinError(ibin,averageStatUnc);
230  gSigmaCorr->SetPoint(ibin,pt,average);
231  gSigmaCorr->SetPointError(ibin,valFcErrx,valFcErrx,avErryl,avErryh);
232  gSigmaCorrConservative->SetPoint(ibin,pt,average);
233  gSigmaCorrConservative->SetPointError(ibin,valFcErrx,valFcErrx,avErryfdl,avErryfdh);
234  gSigmaCorrConservativePC->SetPoint(ibin,pt,0.);
235  gSigmaCorrConservativePC->SetPointError(ibin,valFcErrx,valFcErrx,avErryfdlPC,avErryfdhPC);
236  gFcCorrConservative->SetPoint(ibin,pt,corrfd);
237  gFcCorrConservative->SetPointError(ibin,valFcErrx,valFcErrx,corrfdl,corrfdh);
238  }
239 
240  }
241 
242 
243  gROOT->SetStyle("Plain");
244  gStyle->SetOptTitle(0);
245 
246  //
247  // Plot the results
248  TH2F *histo2Draw = new TH2F("histo2Draw","histo2 (for drawing)",100,0,20.,100,1e3,5e7);
249  histo2Draw->SetStats(0);
250  histo2Draw->GetXaxis()->SetTitle("p_{T} [GeV]");
251  histo2Draw->GetXaxis()->SetTitleSize(0.05);
252  histo2Draw->GetXaxis()->SetTitleOffset(0.95);
253  histo2Draw->GetYaxis()->SetTitle("#frac{1}{BR} #times #frac{d#sigma}{dp_{T}} |_{|y|<0.5}");
254  histo2Draw->GetYaxis()->SetTitleSize(0.05);
255  //
256  TCanvas *combinefdunc = new TCanvas("combinefdunc","show the FD results combination");
257  //
258  histo2Draw->Draw();
259  //
260  histoSigmaCorrFc->SetMarkerStyle(20);
261  histoSigmaCorrFc->SetMarkerColor(kGreen+2);
262  histoSigmaCorrFc->SetLineColor(kGreen+2);
263  histoSigmaCorrFc->Draw("esame");
264  gSigmaCorrConservativeFc->SetMarkerStyle(20);
265  gSigmaCorrConservativeFc->SetMarkerColor(kGreen+2);
266  gSigmaCorrConservativeFc->SetLineColor(kGreen+2);
267  gSigmaCorrConservativeFc->SetFillStyle(3004);//2);
268  gSigmaCorrConservativeFc->SetFillColor(kGreen);
269  gSigmaCorrConservativeFc->Draw("2[]same");
270  //
271  histoSigmaCorrNb->SetMarkerStyle(25);
272  histoSigmaCorrNb->SetMarkerColor(kViolet+5);
273  histoSigmaCorrNb->SetLineColor(kViolet+5);
274  histoSigmaCorrNb->Draw("esame");
275  gSigmaCorrConservativeNb->SetMarkerStyle(25);
276  gSigmaCorrConservativeNb->SetMarkerColor(kOrange+7);//kViolet+5);
277  gSigmaCorrConservativeNb->SetLineColor(kOrange+7);//kOrange+7);//kViolet+5);
278  gSigmaCorrConservativeNb->SetFillStyle(3018);//02);
279  gSigmaCorrConservativeNb->SetFillColor(kMagenta);
280  gSigmaCorrConservativeNb->Draw("2[]same");
281  //
282  gSigmaCorrConservative->SetLineColor(kRed);
283  gSigmaCorrConservative->SetLineWidth(2);
284  gSigmaCorrConservative->SetFillColor(kRed);
285  gSigmaCorrConservative->SetFillStyle(0);
286  gSigmaCorrConservative->Draw("2");
287  histoSigmaCorr->SetMarkerColor(kRed);
288  histoSigmaCorr->Draw("esame");
289  //
290  //
291  TLegend* leg=combinefdunc->BuildLegend();
292  leg->SetFillStyle(0);
293  combinefdunc->SetLogy();
294  combinefdunc->Update();
295 
296  TCanvas *combinefcunc = new TCanvas("combinefcunc","show the fc FD results combination");
297  //
298  TH2F *histo3Draw = new TH2F("histo3Draw","histo3 (for drawing)",100,0,20.,10,0.,1.);
299  histo3Draw->SetStats(0);
300  histo3Draw->GetXaxis()->SetTitle("p_{T} [GeV]");
301  histo3Draw->GetXaxis()->SetTitleSize(0.05);
302  histo3Draw->GetXaxis()->SetTitleOffset(0.95);
303  histo3Draw->GetYaxis()->SetTitle("Prompt fraction of the raw yields");
304  histo3Draw->GetYaxis()->SetTitleSize(0.05);
305  histo3Draw->Draw();
306  //
307  gFcConservativeFc->SetMarkerStyle(20);
308  gFcConservativeFc->SetMarkerColor(kGreen+2);
309  gFcConservativeFc->SetLineColor(kGreen+2);
310  gFcConservativeFc->SetFillStyle(3004);
311  gFcConservativeFc->SetFillColor(kGreen);
312  gFcConservativeFc->Draw("2P");
313  //
314  gFcConservativeNb ->SetMarkerStyle(25);
315  gFcConservativeNb ->SetMarkerSize(1.3);
316  gFcConservativeNb->SetMarkerColor(kOrange+7);//kViolet+5);
317  gFcConservativeNb->SetLineColor(kOrange+7);//kViolet+5);
318  gFcConservativeNb->SetFillStyle(3018);
319  gFcConservativeNb->SetFillColor(kMagenta);
320  gFcConservativeNb->Draw("2P");
321  //
322  gFcCorrConservative->SetMarkerStyle(21);
323  gFcCorrConservative->SetLineColor(kRed);
324  gFcCorrConservative->SetLineWidth(2);
325  gFcCorrConservative->SetFillColor(kRed);
326  gFcCorrConservative->SetFillStyle(0);
327  gFcCorrConservative->Draw("2P");
328  //
329  leg=combinefcunc->BuildLegend();
330  leg->SetFillStyle(0);
331  //
332  combinefcunc->Update();
333 
334  //
335  // Plot the results
336  TCanvas *finalresults = new TCanvas("finalresults","show all combined results");
337  //
338  if ( decay==1 ) {
339  thD0KpifromBprediction->SetLineColor(kGreen+2);
340  thD0KpifromBprediction->SetLineWidth(3);
341  thD0KpifromBprediction->SetFillColor(kGreen-6);
342  thD0KpifromBprediction->Draw("3CA");
343  thD0KpifromBprediction->Draw("CX");
344  }
345  else if ( decay==2 ) {
346  thDpluskpipiprediction->SetLineColor(kGreen+2);
347  thDpluskpipiprediction->SetLineWidth(3);
348  thDpluskpipiprediction->SetFillColor(kGreen-6);
349  thDpluskpipiprediction->Draw("3CA");
350  thDpluskpipiprediction->Draw("CX");
351  }
352  else if ( decay==3 ) {
353  thDstarD0piprediction->SetLineColor(kGreen+2);
354  thDstarD0piprediction->SetLineWidth(3);
355  thDstarD0piprediction->SetFillColor(kGreen-6);
356  thDstarD0piprediction->Draw("3CA");
357  thDstarD0piprediction->Draw("CX");
358  }
359  else if ( decay==4 ) {
360  thDsKKpiprediction->SetLineColor(kGreen+2);
361  thDsKKpiprediction->SetLineWidth(3);
362  thDsKKpiprediction->SetFillColor(kGreen-6);
363  thDsKKpiprediction->Draw("3CA");
364  thDsKKpiprediction->Draw("CX");
365  }
366  //
367  gSigmaCorr->SetLineColor(kRed);
368  gSigmaCorr->SetLineWidth(1);
369  gSigmaCorr->SetFillColor(kRed);
370  gSigmaCorr->SetFillStyle(0);
371  gSigmaCorr->Draw("2");
372  histoSigmaCorr->SetMarkerStyle(21);
373  histoSigmaCorr->SetMarkerColor(kRed);
374  histoSigmaCorr->Draw("esame");
375  //
376  leg = new TLegend(0.7,0.75,0.87,0.5);
377  leg->SetBorderSize(0);
378  leg->SetLineColor(0);
379  leg->SetFillColor(0);
380  leg->SetTextFont(42);
381  if ( decay==1 ) leg->AddEntry(thD0KpifromBprediction,"FONLL ","fl");
382  else if ( decay==2 ) leg->AddEntry(thDpluskpipiprediction,"FONLL ","fl");
383  else if ( decay==3 ) leg->AddEntry(thDstarD0piprediction,"FONLL ","fl");
384  else if ( decay==4 ) leg->AddEntry(thDsKKpiprediction,"FONLL ","fl");
385  leg->AddEntry(histoSigmaCorr,"data stat. unc.","pl");
386  leg->AddEntry(gSigmaCorr,"data syst. unc.","f");
387  leg->Draw();
388  //
389  finalresults->SetLogy();
390  finalresults->Update();
391 
392 
393  //
394  // Draw all the systematics independently
395  systematics.DrawErrors(gSigmaCorrConservativePC);
396 
397 
398  // Write the output to a file
399  TFile * out = new TFile(outfilename,"recreate");
400  histoSigmaCorr->Write();
401  gSigmaCorr->Write();
402  gSigmaCorrConservative->Write();
403  gSigmaCorrConservativePC->Write();
404  gFcCorrConservative->Write();
405  out->Write();
406 
407 }
void SetIsLowEnergy(Bool_t flag)
Definition: AliHFSystErr.h:64
centrality
void SetCentrality(TString centrality)
Definition: AliHFSystErr.h:60
Double_t GetTotalSystErr(Double_t pt, Double_t feeddownErr=0) const
void Init(Int_t decay)
Function to initialize the variables/histograms.
void SetCollisionType(Int_t type)
Definition: AliHFSystErr.h:51
void CombineFeedDownMCSubtractionMethodsUncertainties(const char *fcfilename="HFPtSpectrum_D0Kpi_method1_221110_newnorm.root", const char *nbfilename="HFPtSpectrum_D0Kpi_method2_221110_newnorm.root", const char *outfilename="HFPtSpectrum_D0Kpi_combinedFD.root", const char *thfilename="D0DplusDstarPredictions_y05.root", Int_t decay=1, Int_t centrality=kpp7)
const Int_t nbins
void DrawErrors(TGraphAsymmErrors *grErrFeeddown=0) const