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066998f0 | 1 | #include "TFile.h" |
2 | #include "TH1.h" | |
3 | #include "TH1D.h" | |
4 | #include "TH2.h" | |
5 | #include "TH2F.h" | |
6 | #include "TGraphAsymmErrors.h" | |
7 | #include "TCanvas.h" | |
8 | #include "TLegend.h" | |
9 | #include "TMath.h" | |
10 | #include "TROOT.h" | |
11 | #include "TStyle.h" | |
12 | ||
13 | #include "AliHFSystErr.h" | |
14 | ||
15 | #include <Riostream.h> | |
16 | ||
17 | //_________________________________________________________________________________________ | |
18 | // | |
19 | // Macro to combine the the MonteCarlo B feed-down subtraction uncertainties | |
20 | // | |
21 | // Take as input the output files from the HFPtSpectrum class | |
22 | // from both fc & Nb subtraction methods and combine the uncertainties. | |
23 | // The final central value is set as the one from the Nb-method. | |
24 | // The final uncertainties are defined as the envelope of both fc & Nb | |
25 | // uncertainties with respect to the new central-value. | |
26 | // The final global uncertainties are also defined and a preliminary drawing done. | |
27 | // | |
28 | // | |
29 | // Usage parameters: | |
30 | // 1. HFPtSpectrum fc subtraction file | |
31 | // 2. HFPtSpectrum Nb subtraction file | |
32 | // 3. Output file name | |
33 | // 4. FONLL theoretical predictions file to draw on top | |
34 | // 5. Decay channel as defined in the AliHFSystErr class | |
35 | // | |
36 | //_________________________________________________________________________________________ | |
37 | ||
066c6b9b | 38 | enum centrality{ kpp7, kpp276, k010, k020, k2040, k4060, k6080, k4080, k80100 }; |
066998f0 | 39 | |
40 | void CombineFeedDownMCSubtractionMethodsUncertainties(const char *fcfilename="HFPtSpectrum_D0Kpi_method1_221110_newnorm.root", | |
41 | const char *nbfilename="HFPtSpectrum_D0Kpi_method2_221110_newnorm.root", | |
42 | const char *outfilename="HFPtSpectrum_D0Kpi_combinedFD.root", | |
43 | const char *thfilename="D0DplusDstarPredictions_y05.root", | |
066c6b9b | 44 | Int_t decay=1, Int_t centrality=kpp7) |
066998f0 | 45 | { |
46 | ||
47 | // | |
48 | // Get fc file inputs | |
49 | TFile * fcfile = new TFile(fcfilename,"read"); | |
50 | TH1D * histoSigmaCorrFc = (TH1D*)fcfile->Get("histoSigmaCorr"); | |
51 | histoSigmaCorrFc->SetNameTitle("histoSigmaCorrFc","histoSigmaCorrFc"); | |
52 | TGraphAsymmErrors * gSigmaCorrFc = (TGraphAsymmErrors*)fcfile->Get("gSigmaCorr"); | |
53 | gSigmaCorrFc->SetNameTitle("gSigmaCorrFc","gSigmaCorrFc"); | |
54 | TGraphAsymmErrors * gSigmaCorrConservativeFc = (TGraphAsymmErrors*)fcfile->Get("gSigmaCorrConservative"); | |
ce4c4d27 | 55 | gSigmaCorrConservativeFc->SetNameTitle("gSigmaCorrConservativeFc","Cross section (fc prompt fraction)"); |
56 | TGraphAsymmErrors * gFcConservativeFc = (TGraphAsymmErrors*)fcfile->Get("gFcConservative"); | |
57 | gFcConservativeFc->SetNameTitle("gFcConservativeFc","fc prompt fraction"); | |
066998f0 | 58 | |
59 | // | |
60 | // Get Nb file inputs | |
61 | TFile * nbfile = new TFile(nbfilename,"read"); | |
62 | TH1D * histoSigmaCorrNb = (TH1D*)nbfile->Get("histoSigmaCorr"); | |
63 | histoSigmaCorrNb->SetNameTitle("histoSigmaCorrNb","histoSigmaCorrNb"); | |
64 | TGraphAsymmErrors * gSigmaCorrNb = (TGraphAsymmErrors*)nbfile->Get("gSigmaCorr"); | |
65 | gSigmaCorrNb->SetNameTitle("gSigmaCorrNb","gSigmaCorrNb"); | |
66 | TGraphAsymmErrors * gSigmaCorrConservativeNb = (TGraphAsymmErrors*)nbfile->Get("gSigmaCorrConservative"); | |
ce4c4d27 | 67 | gSigmaCorrConservativeNb->SetNameTitle("gSigmaCorrConservativeNb","Cross section (Nb prompt fraction)"); |
68 | TGraphAsymmErrors * gFcConservativeNb = (TGraphAsymmErrors*)nbfile->Get("gFcConservative"); | |
69 | gFcConservativeNb->SetNameTitle("gFcConservativeNb","Nb prompt fraction"); | |
066998f0 | 70 | |
71 | // | |
72 | // Get the predictions input | |
73 | TFile *thfile = new TFile(thfilename,"read"); | |
74 | TGraphAsymmErrors * thD0KpifromBprediction = (TGraphAsymmErrors*)thfile->Get("D0Kpiprediction"); | |
75 | TGraphAsymmErrors * thDpluskpipiprediction = (TGraphAsymmErrors*)thfile->Get("Dpluskpipiprediction"); | |
76 | TGraphAsymmErrors * thDstarD0piprediction = (TGraphAsymmErrors*)thfile->Get("DstarD0piprediction"); | |
77 | thD0KpifromBprediction->SetLineColor(4); | |
78 | thD0KpifromBprediction->SetFillColor(kAzure+9); | |
79 | thDpluskpipiprediction->SetLineColor(4); | |
80 | thDpluskpipiprediction->SetFillColor(kAzure+9); | |
81 | thDstarD0piprediction->SetLineColor(4); | |
82 | thDstarD0piprediction->SetFillColor(kAzure+9); | |
83 | ||
84 | // | |
85 | // Get the spectra bins & limits | |
86 | Int_t nbins = histoSigmaCorrFc->GetNbinsX(); | |
87 | Double_t *limits = new Double_t[nbins+1]; | |
88 | Double_t xlow=0., binwidth=0.; | |
89 | for (Int_t i=1; i<=nbins; i++) { | |
90 | binwidth = histoSigmaCorrFc->GetBinWidth(i); | |
91 | xlow = histoSigmaCorrFc->GetBinLowEdge(i); | |
92 | limits[i-1] = xlow; | |
93 | } | |
94 | limits[nbins] = xlow + binwidth; | |
95 | ||
96 | ||
97 | // | |
98 | // Define a new histogram with the real-data reconstructed spectrum binning | |
99 | // they will be filled with central value equal to the Nb result | |
100 | // and uncertainties taken from the envelope of the result uncertainties | |
101 | // The systematical unc. (but FD) will also be re-calculated | |
102 | // | |
103 | TH1D * histoSigmaCorr = new TH1D("histoSigmaCorr","corrected cross-section (combined fc and Nb MC feed-down subtraction)",nbins,limits); | |
104 | TGraphAsymmErrors * gSigmaCorr = new TGraphAsymmErrors(nbins+1); | |
105 | gSigmaCorr->SetNameTitle("gSigmaCorr","gSigmaCorr (combined fc and Nb MC FD)"); | |
ce4c4d27 | 106 | TGraphAsymmErrors * gFcCorrConservative = new TGraphAsymmErrors(nbins+1); |
107 | gFcCorrConservative->SetNameTitle("gFcCorrConservative","Combined prompt fraction"); | |
066998f0 | 108 | TGraphAsymmErrors * gSigmaCorrConservative = new TGraphAsymmErrors(nbins+1); |
ce4c4d27 | 109 | gSigmaCorrConservative->SetNameTitle("gSigmaCorrConservative","Cross section (combined prompt fraction)"); |
066998f0 | 110 | TGraphAsymmErrors * gSigmaCorrConservativePC = new TGraphAsymmErrors(nbins+1); |
111 | gSigmaCorrConservativePC->SetNameTitle("gSigmaCorrConservativePC","Conservative gSigmaCorr (combined fc and Nb MC FD) in percentages [for drawing with AliHFSystErr]"); | |
112 | ||
113 | // | |
114 | // Call the systematics uncertainty class for a given decay | |
115 | // will help to compute the systematical unc. (but FD) | |
6ad825bf | 116 | AliHFSystErr systematics; |
066c6b9b | 117 | if( centrality==kpp276 ) { |
118 | systematics.SetIsLowEnergy(true); | |
119 | } else if( centrality!=kpp7 ) { | |
6ad825bf | 120 | systematics.SetCollisionType(1); |
121 | if ( centrality == k020 ) { | |
066c6b9b | 122 | systematics.SetCentrality("020"); |
6ad825bf | 123 | } |
124 | else if ( centrality == k4080 ) { | |
066c6b9b | 125 | systematics.SetCentrality("4080"); |
6ad825bf | 126 | } |
127 | else { | |
128 | cout << " Systematics not yet implemented " << endl; | |
129 | return; | |
130 | } | |
131 | } | |
132 | else { systematics.SetCollisionType(0); } | |
133 | systematics.Init(decay); | |
066998f0 | 134 | |
135 | // | |
136 | // Loop on all the bins to do the calculations | |
137 | // | |
138 | Double_t pt=0., average = 0., averageStatUnc=0., avErrx=0., avErryl=0., avErryh=0., avErryfdl=0., avErryfdh=0.; | |
139 | Double_t avErrylPC=0., avErryhPC=0., avErryfdlPC=0., avErryfdhPC=0.; | |
140 | Double_t valFc = 0., valFcErrstat=0., valFcErrx=0., valFcErryl=0., valFcErryh=0., valFcErryfdl=0., valFcErryfdh=0.; | |
141 | Double_t valNb = 0., valNbErrstat=0., valNbErrx=0., valNbErryl=0., valNbErryh=0., valNbErryfdl=0., valNbErryfdh=0.; | |
ce4c4d27 | 142 | Double_t corrfd = 0., corrfdl=0., corrfdh=0.; |
066998f0 | 143 | // |
144 | for(Int_t ibin=1; ibin<=nbins; ibin++){ | |
145 | ||
146 | // Get input values from fc method | |
147 | valFc = histoSigmaCorrFc->GetBinContent(ibin); | |
148 | pt = histoSigmaCorrFc->GetBinCenter(ibin); | |
149 | valFcErrstat = histoSigmaCorrFc->GetBinError(ibin); | |
150 | Double_t value =0., ptt=0.; | |
151 | gSigmaCorrConservativeFc->GetPoint(ibin,ptt,value); | |
066c6b9b | 152 | if (value<=0.) continue; |
066998f0 | 153 | if ( TMath::Abs(valFc-value)>0.1 || TMath::Abs(pt-ptt)>0.1 ) |
154 | cout << "Hey you ! There might be a problem with the fc input file, please, have a look !" << endl; | |
155 | valFcErrx = gSigmaCorrFc->GetErrorXlow(ibin); | |
156 | valFcErryl = gSigmaCorrFc->GetErrorYlow(ibin); | |
157 | valFcErryh = gSigmaCorrFc->GetErrorYhigh(ibin); | |
158 | valFcErryfdl = TMath::Abs( gSigmaCorrConservativeFc->GetErrorYlow(ibin) ); | |
159 | valFcErryfdh = TMath::Abs( gSigmaCorrConservativeFc->GetErrorYhigh(ibin) ); | |
ce4c4d27 | 160 | Double_t valfdFc = 0., x=0.; |
161 | gFcConservativeFc->GetPoint(ibin,x,valfdFc); | |
162 | Double_t valfdFch = gFcConservativeFc->GetErrorYhigh(ibin); | |
163 | Double_t valfdFcl = gFcConservativeFc->GetErrorYlow(ibin); | |
066998f0 | 164 | |
165 | // Get input values from Nb method | |
166 | valNb = histoSigmaCorrNb->GetBinContent(ibin); | |
167 | pt = histoSigmaCorrNb->GetBinCenter(ibin); | |
168 | valNbErrstat = histoSigmaCorrNb->GetBinError(ibin); | |
169 | gSigmaCorrConservativeNb->GetPoint(ibin,ptt,value); | |
170 | if ( TMath::Abs(valNb-value)>0.1 || TMath::Abs(pt-ptt)>0.1 ) | |
171 | cout << "Hey you ! There might be a problem with the Nb input file, please, have a look !" << endl; | |
172 | valNbErrx = gSigmaCorrNb->GetErrorXlow(ibin); | |
173 | valNbErryl = gSigmaCorrNb->GetErrorYlow(ibin); | |
174 | valNbErryh = gSigmaCorrNb->GetErrorYhigh(ibin); | |
175 | valNbErryfdl = gSigmaCorrConservativeNb->GetErrorYlow(ibin); | |
176 | valNbErryfdh = gSigmaCorrConservativeNb->GetErrorYhigh(ibin); | |
ce4c4d27 | 177 | Double_t valfdNb = 0.; |
178 | gFcConservativeNb->GetPoint(ibin,x,valfdNb); | |
179 | Double_t valfdNbh = gFcConservativeNb->GetErrorYhigh(ibin); | |
180 | Double_t valfdNbl = gFcConservativeNb->GetErrorYlow(ibin); | |
066998f0 | 181 | |
182 | ||
183 | // Compute the FD combined value | |
184 | // average = valNb | |
185 | average = valNb ; | |
ce4c4d27 | 186 | corrfd = valfdNb; |
066998f0 | 187 | avErrx = valFcErrx; |
188 | if ( TMath::Abs( valFcErrx - valNbErrx ) > 0.1 ) | |
189 | cout << "Hey you ! There might be consistency problem with the fc & Nb input files, please, have a look !" << endl; | |
190 | averageStatUnc = valNbErrstat ; | |
191 | // cout << " pt=" << pt << ", average="<<average<<endl; | |
192 | // cout << " stat unc (pc)=" << averageStatUnc/average << ", stat-fc (pc)="<<(valFcErrstat/valFc) << ", stat-Nb (pc)="<<(valNbErrstat/valNb)<<endl; | |
193 | ||
194 | // now estimate the new feed-down combined uncertainties | |
195 | Double_t minimum[2] = { (valFc - valFcErryfdl), (valNb - valNbErryfdl) }; | |
196 | Double_t maximum[2] = { (valFc + valFcErryfdh), (valNb + valNbErryfdh) }; | |
197 | avErryfdl = average - TMath::MinElement(2,minimum); | |
198 | avErryfdh = TMath::MaxElement(2,maximum) - average; | |
199 | avErryfdlPC = avErryfdl / average ; // in percentage | |
200 | avErryfdhPC = avErryfdh / average ; // in percentage | |
201 | // cout << " fc : val " << valFc << " + " << valFcErryfdh <<" - " << valFcErryfdl <<endl; | |
202 | // cout << " Nb : val " << valNb << " + " << valNbErryfdh <<" - " << valNbErryfdl <<endl; | |
203 | // cout << " fc & Nb: val " << average << " + " << avErryfdh <<" - " << avErryfdl <<endl; | |
ce4c4d27 | 204 | Double_t minimumfc[2] = { (valfdNb - valfdNbl), (valfdFc - valfdFcl) }; |
205 | Double_t maximumfc[2] = { (valfdNb + valfdNbh), (valfdFc + valfdFch) }; | |
206 | corrfdl = corrfd - TMath::MinElement(2,minimumfc); | |
207 | corrfdh = TMath::MaxElement(2,maximumfc) - corrfd; | |
066998f0 | 208 | |
209 | ||
210 | // compute the global systematics | |
211 | avErrylPC = systematics.GetTotalSystErr(pt,avErryfdlPC); // in percentage | |
212 | avErryhPC = systematics.GetTotalSystErr(pt,avErryfdhPC); // in percentage | |
213 | avErryl = avErrylPC * average ; | |
214 | avErryh = avErryhPC * average ; | |
215 | // cout << " syst av-l="<<avErryl<<", av-h="<<avErryh<<endl; | |
216 | // 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; | |
217 | ||
218 | // fill in the histos and TGraphs | |
219 | // fill them only when for non empty bins | |
220 | if ( average > 0.1 ) { | |
221 | histoSigmaCorr->SetBinContent(ibin,average); | |
222 | histoSigmaCorr->SetBinError(ibin,averageStatUnc); | |
223 | gSigmaCorr->SetPoint(ibin,pt,average); | |
224 | gSigmaCorr->SetPointError(ibin,valFcErrx,valFcErrx,avErryl,avErryh); | |
225 | gSigmaCorrConservative->SetPoint(ibin,pt,average); | |
226 | gSigmaCorrConservative->SetPointError(ibin,valFcErrx,valFcErrx,avErryfdl,avErryfdh); | |
227 | gSigmaCorrConservativePC->SetPoint(ibin,pt,0.); | |
228 | gSigmaCorrConservativePC->SetPointError(ibin,valFcErrx,valFcErrx,avErryfdlPC,avErryfdhPC); | |
ce4c4d27 | 229 | gFcCorrConservative->SetPoint(ibin,pt,corrfd); |
230 | gFcCorrConservative->SetPointError(ibin,valFcErrx,valFcErrx,corrfdl,corrfdh); | |
066998f0 | 231 | } |
232 | ||
233 | } | |
234 | ||
235 | ||
236 | gROOT->SetStyle("Plain"); | |
237 | gStyle->SetOptTitle(0); | |
238 | ||
239 | // | |
240 | // Plot the results | |
ce4c4d27 | 241 | TH2F *histo2Draw = new TH2F("histo2Draw","histo2 (for drawing)",100,0,20.,100,1e3,5e7); |
066998f0 | 242 | histo2Draw->SetStats(0); |
243 | histo2Draw->GetXaxis()->SetTitle("p_{T} [GeV]"); | |
244 | histo2Draw->GetXaxis()->SetTitleSize(0.05); | |
245 | histo2Draw->GetXaxis()->SetTitleOffset(0.95); | |
246 | histo2Draw->GetYaxis()->SetTitle("#frac{1}{BR} #times #frac{d#sigma}{dp_{T}} |_{|y|<0.5}"); | |
247 | histo2Draw->GetYaxis()->SetTitleSize(0.05); | |
248 | // | |
249 | TCanvas *combinefdunc = new TCanvas("combinefdunc","show the FD results combination"); | |
250 | // | |
251 | histo2Draw->Draw(); | |
252 | // | |
253 | histoSigmaCorrFc->SetMarkerStyle(20); | |
254 | histoSigmaCorrFc->SetMarkerColor(kGreen+2); | |
255 | histoSigmaCorrFc->SetLineColor(kGreen+2); | |
256 | histoSigmaCorrFc->Draw("esame"); | |
257 | gSigmaCorrConservativeFc->SetMarkerStyle(20); | |
258 | gSigmaCorrConservativeFc->SetMarkerColor(kGreen+2); | |
259 | gSigmaCorrConservativeFc->SetLineColor(kGreen+2); | |
ce4c4d27 | 260 | gSigmaCorrConservativeFc->SetFillStyle(3004);//2); |
066998f0 | 261 | gSigmaCorrConservativeFc->SetFillColor(kGreen); |
262 | gSigmaCorrConservativeFc->Draw("2[]same"); | |
263 | // | |
264 | histoSigmaCorrNb->SetMarkerStyle(25); | |
265 | histoSigmaCorrNb->SetMarkerColor(kViolet+5); | |
266 | histoSigmaCorrNb->SetLineColor(kViolet+5); | |
267 | histoSigmaCorrNb->Draw("esame"); | |
268 | gSigmaCorrConservativeNb->SetMarkerStyle(25); | |
ce4c4d27 | 269 | gSigmaCorrConservativeNb->SetMarkerColor(kOrange+7);//kViolet+5); |
270 | gSigmaCorrConservativeNb->SetLineColor(kOrange+7);//kOrange+7);//kViolet+5); | |
271 | gSigmaCorrConservativeNb->SetFillStyle(3018);//02); | |
066998f0 | 272 | gSigmaCorrConservativeNb->SetFillColor(kMagenta); |
273 | gSigmaCorrConservativeNb->Draw("2[]same"); | |
274 | // | |
275 | gSigmaCorrConservative->SetLineColor(kRed); | |
ce4c4d27 | 276 | gSigmaCorrConservative->SetLineWidth(2); |
066998f0 | 277 | gSigmaCorrConservative->SetFillColor(kRed); |
278 | gSigmaCorrConservative->SetFillStyle(0); | |
279 | gSigmaCorrConservative->Draw("2"); | |
280 | histoSigmaCorr->SetMarkerColor(kRed); | |
281 | histoSigmaCorr->Draw("esame"); | |
282 | // | |
ce4c4d27 | 283 | // |
284 | TLegend* leg=combinefdunc->BuildLegend(); | |
285 | leg->SetFillStyle(0); | |
066998f0 | 286 | combinefdunc->SetLogy(); |
287 | combinefdunc->Update(); | |
288 | ||
ce4c4d27 | 289 | TCanvas *combinefcunc = new TCanvas("combinefcunc","show the fc FD results combination"); |
290 | // | |
291 | TH2F *histo3Draw = new TH2F("histo3Draw","histo3 (for drawing)",100,0,20.,10,0.,1.); | |
292 | histo3Draw->SetStats(0); | |
293 | histo3Draw->GetXaxis()->SetTitle("p_{T} [GeV]"); | |
294 | histo3Draw->GetXaxis()->SetTitleSize(0.05); | |
295 | histo3Draw->GetXaxis()->SetTitleOffset(0.95); | |
296 | histo3Draw->GetYaxis()->SetTitle("Prompt fraction of the raw yields"); | |
297 | histo3Draw->GetYaxis()->SetTitleSize(0.05); | |
298 | histo3Draw->Draw(); | |
299 | // | |
300 | gFcConservativeFc->SetMarkerStyle(20); | |
301 | gFcConservativeFc->SetMarkerColor(kGreen+2); | |
302 | gFcConservativeFc->SetLineColor(kGreen+2); | |
303 | gFcConservativeFc->SetFillStyle(3004); | |
304 | gFcConservativeFc->SetFillColor(kGreen); | |
305 | gFcConservativeFc->Draw("2P"); | |
306 | // | |
307 | gFcConservativeNb ->SetMarkerStyle(25); | |
308 | gFcConservativeNb ->SetMarkerSize(1.3); | |
309 | gFcConservativeNb->SetMarkerColor(kOrange+7);//kViolet+5); | |
310 | gFcConservativeNb->SetLineColor(kOrange+7);//kViolet+5); | |
311 | gFcConservativeNb->SetFillStyle(3018); | |
312 | gFcConservativeNb->SetFillColor(kMagenta); | |
313 | gFcConservativeNb->Draw("2P"); | |
314 | // | |
315 | gFcCorrConservative->SetMarkerStyle(21); | |
316 | gFcCorrConservative->SetLineColor(kRed); | |
317 | gFcCorrConservative->SetLineWidth(2); | |
318 | gFcCorrConservative->SetFillColor(kRed); | |
319 | gFcCorrConservative->SetFillStyle(0); | |
320 | gFcCorrConservative->Draw("2P"); | |
321 | // | |
322 | leg=combinefcunc->BuildLegend(); | |
323 | leg->SetFillStyle(0); | |
324 | // | |
325 | combinefcunc->Update(); | |
326 | ||
066998f0 | 327 | // |
328 | // Plot the results | |
329 | TCanvas *finalresults = new TCanvas("finalresults","show all combined results"); | |
330 | // | |
331 | if ( decay==1 ) { | |
332 | thD0KpifromBprediction->SetLineColor(kGreen+2); | |
333 | thD0KpifromBprediction->SetLineWidth(3); | |
334 | thD0KpifromBprediction->SetFillColor(kGreen-6); | |
335 | thD0KpifromBprediction->Draw("3CA"); | |
336 | thD0KpifromBprediction->Draw("CX"); | |
337 | } | |
338 | else if ( decay==2 ) { | |
339 | thDpluskpipiprediction->SetLineColor(kGreen+2); | |
340 | thDpluskpipiprediction->SetLineWidth(3); | |
341 | thDpluskpipiprediction->SetFillColor(kGreen-6); | |
342 | thDpluskpipiprediction->Draw("3CA"); | |
343 | thDpluskpipiprediction->Draw("CX"); | |
344 | } | |
345 | else if ( decay==3 ) { | |
346 | thDstarD0piprediction->SetLineColor(kGreen+2); | |
347 | thDstarD0piprediction->SetLineWidth(3); | |
348 | thDstarD0piprediction->SetFillColor(kGreen-6); | |
349 | thDstarD0piprediction->Draw("3CA"); | |
350 | thDstarD0piprediction->Draw("CX"); | |
351 | } | |
352 | // | |
353 | gSigmaCorr->SetLineColor(kRed); | |
354 | gSigmaCorr->SetLineWidth(1); | |
355 | gSigmaCorr->SetFillColor(kRed); | |
356 | gSigmaCorr->SetFillStyle(0); | |
357 | gSigmaCorr->Draw("2"); | |
358 | histoSigmaCorr->SetMarkerStyle(21); | |
359 | histoSigmaCorr->SetMarkerColor(kRed); | |
360 | histoSigmaCorr->Draw("esame"); | |
361 | // | |
ce4c4d27 | 362 | leg = new TLegend(0.7,0.75,0.87,0.5); |
066998f0 | 363 | leg->SetBorderSize(0); |
364 | leg->SetLineColor(0); | |
365 | leg->SetFillColor(0); | |
366 | leg->SetTextFont(42); | |
367 | if ( decay==1 ) leg->AddEntry(thD0KpifromBprediction,"FONLL ","fl"); | |
368 | else if ( decay==2 ) leg->AddEntry(thDpluskpipiprediction,"FONLL ","fl"); | |
369 | else if ( decay==3 ) leg->AddEntry(thDstarD0piprediction,"FONLL ","fl"); | |
370 | leg->AddEntry(histoSigmaCorr,"data stat. unc.","pl"); | |
371 | leg->AddEntry(gSigmaCorr,"data syst. unc.","f"); | |
372 | leg->Draw(); | |
373 | // | |
374 | finalresults->SetLogy(); | |
375 | finalresults->Update(); | |
376 | ||
377 | ||
378 | // | |
379 | // Draw all the systematics independently | |
380 | systematics.DrawErrors(gSigmaCorrConservativePC); | |
381 | ||
382 | ||
383 | // Write the output to a file | |
384 | TFile * out = new TFile(outfilename,"recreate"); | |
385 | histoSigmaCorr->Write(); | |
386 | gSigmaCorr->Write(); | |
387 | gSigmaCorrConservative->Write(); | |
388 | gSigmaCorrConservativePC->Write(); | |
ce4c4d27 | 389 | gFcCorrConservative->Write(); |
066998f0 | 390 | out->Write(); |
391 | ||
392 | } |