]>
Commit | Line | Data |
---|---|---|
b188dc47 | 1 | #ifndef ALIHFPTSPECTRUM_H |
2 | #define ALIHFPTSPECTRUM_H | |
3 | ||
4 | /* Copyright(c) 1998-2010, ALICE Experiment at CERN, All rights reserved. * | |
5 | * See cxx source for full Copyright notice */ | |
6 | ||
7 | /* $Id$ */ | |
8 | ||
9 | //*********************************************************************** | |
10 | // Class AliHFPtSpectrum | |
11 | // Base class for feed-down corrections on heavy-flavour decays | |
12 | // computes the cross-section via one of the three implemented methods: | |
13 | // 0) Consider no feed-down prediction | |
14 | // 1) Subtract the feed-down with the "fc" method | |
15 | // Yield = Reco * fc; where fc = 1 / ( 1 + (eff_b/eff_c)*(N_b/N_c) ) ; | |
16 | // 2) Subtract the feed-down with the "Nb" method | |
17 | // Yield = Reco - Feed-down (exact formula on the function implementation) | |
18 | // | |
19 | // (the corrected yields per bin are divided by the bin-width) | |
20 | // | |
21 | // | |
22 | // In HIC you can also evaluate how the feed-down correction is influenced by an energy loss hypothesis: | |
23 | // Raa(c-->D) / Raa(b-->D) defined here as Rcb for the "fc" method | |
24 | // Raa(b-->D) defined here as Rb for the "Nb" method | |
25 | // | |
26 | // Author: Z.Conesa, zconesa@in2p3.fr | |
27 | //*********************************************************************** | |
28 | ||
29 | #include "TNamed.h" | |
30 | #include "TMath.h" | |
31 | ||
32 | #include "AliLog.h" | |
33 | ||
34 | class TH1; | |
35 | class TH2; | |
36 | class TNtuple; | |
37 | class TGraphAsymmErrors; | |
38 | ||
39 | ||
40 | class AliHFPtSpectrum: public TNamed | |
41 | { | |
42 | ||
43 | public: | |
44 | ||
45 | // Constructor | |
46 | AliHFPtSpectrum(const char* name="AliHFPtSpectrum", const char* title="HF feed down correction class", Int_t option=1); | |
47 | // Copy constructor | |
48 | AliHFPtSpectrum(const AliHFPtSpectrum &rhs); | |
49 | // Assignment operator | |
50 | AliHFPtSpectrum& operator=(const AliHFPtSpectrum &source); | |
51 | // Destructor | |
52 | virtual ~AliHFPtSpectrum(); | |
53 | ||
54 | // | |
55 | // Setters | |
56 | // | |
57 | // Set the theoretical direct & feeddown pt spectrum | |
58 | void SetMCptSpectra(TH1D *hDirect, TH1D *hFeedDown); | |
59 | // Set the theoretical feeddown pt spectrum | |
60 | void SetFeedDownMCptSpectra(TH1D *hFeedDown); | |
61 | // Set the theoretical direct & feeddown pt spectrum upper and lower bounds | |
62 | void SetMCptDistributionsBounds(TH1D *hDirectMax, TH1D *hDirectMin, TH1D *hFeedDownMax, TH1D *hFeedDownMin); | |
63 | // Set the theoretical feeddown pt spectrum upper and lower bounds | |
64 | void SetFeedDownMCptDistributionsBounds(TH1D *hFeedDownMax, TH1D *hFeedDownMin); | |
65 | // Set the acceptance and efficiency corrections for direct | |
66 | void SetDirectAccEffCorrection(TH1D *hDirectEff); | |
67 | // Set the acceptance and efficiency corrections for direct & feeddown | |
68 | void SetAccEffCorrection(TH1D *hDirectEff, TH1D *hFeedDownEff); | |
69 | // Set the reconstructed spectrum | |
70 | void SetReconstructedSpectrum(TH1D *hRec); | |
71 | void SetReconstructedSpectrumSystematics(TGraphAsymmErrors *gRec); | |
72 | // Set the calculation option flag for feed-down correction: 0=none, 1=fc , 2=Nb | |
73 | void SetFeedDownCalculationOption(Int_t option){ fFeedDownOption = option; } | |
74 | // Set if the calculation has to consider asymmetric uncertaInt_ties or not | |
75 | void SetComputeAsymmetricUncertainties(Bool_t flag){ fAsymUncertainties = flag; } | |
76 | // Set if the yield is for particle plus anti-particle or not | |
77 | void SetIsParticlePlusAntiParticleYield(Bool_t flag){ | |
78 | if (flag) { fParticleAntiParticle = 2; AliInfo(" Setting for particle + anti-particle yields"); } | |
79 | else { fParticleAntiParticle = 1; AliInfo(" Setting for only (anti)particle yields, not the sum of both"); } | |
80 | } | |
81 | // | |
82 | void SetfIsStatUncEff(Bool_t flag){ fIsStatUncEff = flag; } | |
83 | // Set if the calculation has to consider Ratio(c/b eloss) hypothesis | |
84 | void SetComputeElossHypothesis(Bool_t flag){ fPbPbElossHypothesis = flag; } | |
85 | // Set the luminosity and its uncertainty | |
86 | void SetLuminosity(Double_t luminosity, Double_t unc){ | |
87 | fLuminosity[0]=luminosity; fLuminosity[1]=unc; | |
88 | } | |
89 | // Set the trigger efficiency and its uncertainty | |
90 | void SetTriggerEfficiency(Double_t efficiency, Double_t unc){ | |
91 | fTrigEfficiency[0]=efficiency; fTrigEfficiency[1]=unc; | |
92 | } | |
93 | // Set global acceptance x efficiency correction uncertainty (in percentages) | |
94 | void SetAccEffPercentageUncertainty(Double_t globalEffUnc, Double_t globalBCEffRatioUnc){ | |
95 | fGlobalEfficiencyUncertainties[0] = globalEffUnc; | |
96 | fGlobalEfficiencyUncertainties[1] = globalBCEffRatioUnc; | |
97 | } | |
98 | // Set the normalization factors | |
99 | void SetNormalization(Double_t normalization){ | |
100 | fLuminosity[0]=normalization; | |
101 | } | |
102 | void SetNormalization(Int_t nevents, Double_t sigma){ | |
103 | fLuminosity[0]=nevents/sigma; | |
104 | fNevts = nevents; | |
105 | } | |
106 | void SetNormalization(Int_t nevents, Double_t sigma, Double_t sigmaunc){ | |
107 | fLuminosity[0] = nevents/sigma; | |
108 | fLuminosity[1] = fLuminosity[0] * TMath::Sqrt( (1/nevents) + (sigmaunc/sigma)*(sigmaunc/sigma) ); | |
109 | fNevts = nevents; | |
110 | } | |
111 | // | |
112 | // Set the Tab parameter and its uncertainty | |
113 | void SetTabParameter(Double_t tabvalue, Double_t uncertainty){ | |
114 | fTab[0] = tabvalue; | |
115 | fTab[1] = uncertainty; | |
116 | } | |
117 | ||
118 | ||
119 | // | |
120 | // Getters | |
121 | // | |
122 | // Return the theoretical predictions used for the calculation (rebinned if needed) | |
123 | TH1D * GetDirectTheoreticalSpectrum() const { return (fhDirectMCpt ? (TH1D*)fhDirectMCpt : NULL); } | |
124 | TH1D * GetDirectTheoreticalUpperLimitSpectrum() const { return (fhDirectMCptMax ? (TH1D*)fhDirectMCptMax : NULL); } | |
125 | TH1D * GetDirectTheoreticalLowerLimitSpectrum() const { return (fhDirectMCptMin ? (TH1D*)fhDirectMCptMin : NULL); } | |
126 | TH1D * GetFeedDownTheoreticalSpectrum() const { return (fhFeedDownMCpt ? (TH1D*)fhFeedDownMCpt : NULL); } | |
127 | TH1D * GetFeedDownTheoreticalUpperLimitSpectrum() const { return (fhFeedDownMCptMax ? (TH1D*)fhFeedDownMCptMax : NULL); } | |
128 | TH1D * GetFeedDownTheoreticalLowerLimitSpectrum() const { return (fhFeedDownMCptMin ? (TH1D*)fhFeedDownMCptMin : NULL); } | |
129 | // Return the acceptance and efficiency corrections (rebinned if needed) | |
130 | TH1D * GetDirectAccEffCorrection() const { return (fhDirectEffpt ? (TH1D*)fhDirectEffpt : NULL); } | |
131 | TH1D * GetFeedDownAccEffCorrection() const { return (fhFeedDownEffpt ? (TH1D*)fhFeedDownEffpt : NULL); } | |
132 | // Return whether the Ratio(c/b eloss) hypothesis has been considered | |
133 | Bool_t IsElossHypothesisCalculated(){ return fPbPbElossHypothesis; } | |
134 | // Return the TGraphAsymmErrors of the feed-down correction (extreme systematics) | |
135 | TGraphAsymmErrors * GetFeedDownCorrectionFcExtreme() const { return (fgFcExtreme ? fgFcExtreme : NULL); } | |
136 | // Return the TGraphAsymmErrors of the feed-down correction (conservative systematics) | |
137 | TGraphAsymmErrors * GetFeedDownCorrectionFcConservative() const { return (fgFcConservative ? fgFcConservative : NULL); } | |
138 | // Return the histogram of the feed-down correction | |
139 | TH1D * GetHistoFeedDownCorrectionFc() const { return (fhFc ? (TH1D*)fhFc : NULL); } | |
140 | // Return the histograms of the feed-down correction bounds | |
141 | TH1D * GetHistoUpperLimitFeedDownCorrectionFc() const { return (fhFcMax ? (TH1D*)fhFcMax : NULL); } | |
142 | TH1D * GetHistoLowerLimitFeedDownCorrectionFc() const { return (fhFcMin ? (TH1D*)fhFcMin : NULL); } | |
143 | // Return the histogram of the feed-down correction times the Ratio(c/b eloss) | |
144 | TH2D * GetHistoFeedDownCorrectionFcVsEloss() const { return (fhFcRcb ? (TH2D*)fhFcRcb : NULL); } | |
145 | // Return the TGraphAsymmErrors of the yield after feed-down correction (systematics but feed-down) | |
146 | TGraphAsymmErrors * GetFeedDownCorrectedSpectrum() const { return (fgYieldCorr ? fgYieldCorr : NULL); } | |
147 | // Return the TGraphAsymmErrors of the yield after feed-down correction (feed-down extreme systematics) | |
148 | TGraphAsymmErrors * GetFeedDownCorrectedSpectrumExtreme() const { return (fgYieldCorrExtreme ? fgYieldCorrExtreme : NULL); } | |
149 | // Return the TGraphAsymmErrors of the yield after feed-down correction (feed-down conservative systematics) | |
150 | TGraphAsymmErrors * GetFeedDownCorrectedSpectrumConservative() const { return (fgYieldCorrConservative ? fgYieldCorrConservative : NULL); } | |
151 | // Return the histogram of the yield after feed-down correction | |
152 | TH1D * GetHistoFeedDownCorrectedSpectrum() const { return (fhYieldCorr ? (TH1D*)fhYieldCorr : NULL); } | |
153 | // Return the histogram of the yield after feed-down correction bounds | |
154 | TH1D * GetHistoUpperLimitFeedDownCorrectedSpectrum() const { return (fhYieldCorrMax ? (TH1D*)fhYieldCorrMax : NULL); } | |
155 | TH1D * GetHistoLowerLimitFeedDownCorrectedSpectrum() const { return (fhYieldCorrMin ? (TH1D*)fhYieldCorrMin : NULL); } | |
156 | // Return the histogram of the yield after feed-down correction vs the Ratio(c/b eloss) | |
157 | TH2D * GetHistoFeedDownCorrectedSpectrumVsEloss() const { return (fhYieldCorrRcb ? (TH2D*)fhYieldCorrRcb : NULL); } | |
158 | // Return the equivalent invariant cross-section TGraphAsymmErrors (systematics but feed-down) | |
159 | TGraphAsymmErrors * GetCrossSectionFromYieldSpectrum() const { return (fgSigmaCorr ? fgSigmaCorr : NULL); } | |
160 | // Return the equivalent invariant cross-section TGraphAsymmErrors (feed-down extreme systematics) | |
161 | TGraphAsymmErrors * GetCrossSectionFromYieldSpectrumExtreme() const { return (fgSigmaCorrExtreme ? fgSigmaCorrExtreme : NULL); } | |
162 | // Return the equivalent invariant cross-section TGraphAsymmErrors (feed-down conservative systematics) | |
163 | TGraphAsymmErrors * GetCrossSectionFromYieldSpectrumConservative() const { return (fgSigmaCorrConservative ? fgSigmaCorrConservative : NULL); } | |
164 | // Return the equivalent invariant cross-section histogram | |
165 | TH1D * GetHistoCrossSectionFromYieldSpectrum() const { return (fhSigmaCorr ? (TH1D*)fhSigmaCorr : NULL); } | |
166 | // Return the equivalent invariant cross-section histogram bounds | |
167 | TH1D * GetHistoUpperLimitCrossSectionFromYieldSpectrum() const { return (fhSigmaCorrMax ? (TH1D*)fhSigmaCorrMax : NULL); } | |
168 | TH1D * GetHistoLowerLimitCrossSectionFromYieldSpectrum() const { return (fhSigmaCorrMin ? (TH1D*)fhSigmaCorrMin : NULL); } | |
169 | // Return the cross section systematics from data systematics | |
170 | TH1D * GetHistoCrossSectionDataSystematics() const { return (fhSigmaCorrDataSyst ? (TH1D*)fhSigmaCorrDataSyst : NULL); } | |
171 | // | |
172 | // PbPb special calculations | |
173 | // Return the equivalent invariant cross-section histogram vs the Ratio(c/b eloss) | |
174 | TH2D * GetHistoCrossSectionFromYieldSpectrumVsEloss() const { return (fhSigmaCorrRcb ? (TH2D*)fhSigmaCorrRcb : NULL); } | |
175 | // Return the ntuple of the calculation vs the Ratio(c/b eloss) | |
176 | TNtuple * GetNtupleCrossSectionVsEloss() { return (fnSigma ? (TNtuple*)fnSigma : NULL); } | |
177 | // | |
178 | // | |
179 | // Histograms to keep track of the influence of the efficiencies statistical uncertainty on the cross-section | |
180 | TH1D * GetDirectStatEffUncOnSigma() const { return (TH1D*)fhStatUncEffcSigma; } | |
181 | TH1D * GetFeedDownStatEffUncOnSigma() const { return (TH1D*)fhStatUncEffbSigma; } | |
182 | // Histograms to keep track of the influence of the efficiencies statistical uncertainty on the feed-down correction factor | |
183 | TH1D * GetDirectStatEffUncOnFc() const { return (TH1D*)fhStatUncEffcFD; } | |
184 | TH1D * GetFeedDownStatEffUncOnFc() const { return (TH1D*)fhStatUncEffbFD; } | |
185 | ||
186 | ||
187 | // | |
188 | // Main function: | |
189 | // Compute the invariant cross-section from the yield (correct it) | |
190 | // variables : analysed delta_y, BR for the final correction, BR b --> decay (relative to the input theoretical prediction) | |
191 | void ComputeHFPtSpectrum(Double_t deltaY=1.0, Double_t branchingRatioC=1.0, Double_t branchingRatioBintoFinalDecay=1.0); | |
192 | ||
193 | // Compute the systematic uncertainties | |
194 | // taking as input the AliHFSystErr uncertainties | |
195 | void ComputeSystUncertainties(AliHFSystErr *systematics, Bool_t combineFeedDown); | |
196 | // | |
197 | // Drawing the corrected spectrum comparing to theoretical prediction | |
198 | void DrawSpectrum(TGraphAsymmErrors *gPrediction); | |
199 | ||
200 | // | |
201 | // Basic functions | |
202 | // | |
203 | void EstimateAndSetDirectEfficiencyRecoBin(TH1D *hSimu, TH1D *hReco); | |
204 | void EstimateAndSetFeedDownEfficiencyRecoBin(TH1D *hSimu, TH1D *hReco); | |
205 | ||
206 | // | |
207 | // Functions to reweight histograms for testing purposes: | |
208 | // to reweight the simulation: hToReweight is reweighted as hReference/hToReweight | |
209 | TH1D * ReweightHisto(TH1D *hToReweight, TH1D *hReference); | |
210 | // to reweight the reco-histos: hRecToReweight is reweighted as hReference/hMCToReweight | |
211 | TH1D * ReweightRecHisto(TH1D *hRecToReweight, TH1D *hMCToReweight, TH1D *hMCReference); | |
212 | // Functionality to find the y-axis bin of a TH2 for a given y-value | |
213 | Int_t FindTH2YBin(TH2D *histo, Float_t yvalue); | |
214 | ||
215 | ||
216 | protected: | |
217 | ||
218 | // Initialization | |
219 | Bool_t Initialize(); | |
220 | ||
221 | // Basic functions | |
222 | // | |
223 | // Compute the feed-down correction via fc-method | |
224 | void CalculateFeedDownCorrectionFc(); | |
225 | // Correct the yield for feed-down correction via fc-method | |
226 | void CalculateFeedDownCorrectedSpectrumFc(); | |
227 | // Correct the yield for feed-down correction via Nb-method | |
228 | void CalculateFeedDownCorrectedSpectrumNb(Double_t deltaY, Double_t branchingRatioBintoFinalDecay); | |
229 | ||
230 | // Check histograms consistency function | |
231 | Bool_t CheckHistosConsistency(TH1D *h1, TH1D *h2); | |
232 | // Function to rebin the theoretical spectra in the data-reconstructed spectra binning | |
233 | TH1D * RebinTheoreticalSpectra(TH1D *hTheory, const char *name); | |
234 | // Function to estimate the efficiency in the data-reconstructed spectra binning | |
235 | TH1D * EstimateEfficiencyRecoBin(TH1D *hSimu, TH1D *hReco, const char *name); | |
236 | // Reset stat unc on the efficiencies | |
237 | void ResetStatUncEff(); | |
238 | ||
239 | ||
240 | // | |
241 | // Input spectra | |
242 | // | |
243 | TH1D *fhDirectMCpt; // Input MC c-->D spectra | |
244 | TH1D *fhFeedDownMCpt; // Input MC b-->D spectra | |
245 | TH1D *fhDirectMCptMax; // Input MC maximum c-->D spectra | |
246 | TH1D *fhDirectMCptMin; // Input MC minimum c-->D spectra | |
247 | TH1D *fhFeedDownMCptMax; // Input MC maximum b-->D spectra | |
248 | TH1D *fhFeedDownMCptMin; // Input MC minimum b-->D spectra | |
249 | TH1D *fhDirectEffpt; // c-->D Acceptance and efficiency correction | |
250 | TH1D *fhFeedDownEffpt; // b-->D Acceptance and efficiency correction | |
251 | TH1D *fhRECpt; // all reconstructed D | |
252 | // | |
253 | TGraphAsymmErrors *fgRECSystematics; // all reconstructed D Systematic uncertainties | |
254 | // | |
255 | // Normalization factors | |
256 | Int_t fNevts; // nb of analyzed events | |
257 | Double_t fLuminosity[2]; // analyzed luminosity & uncertainty | |
258 | Double_t fTrigEfficiency[2]; // trigger efficiency & uncertainty | |
259 | Double_t fGlobalEfficiencyUncertainties[2]; // uncertainties on the efficiency [0]=c, b, [1]=b/c | |
260 | Double_t fTab[2]; // Tab parameter and its uncertainty | |
261 | ||
262 | // | |
263 | // Output spectra | |
264 | // | |
265 | TH1D *fhFc; // Correction histo fc = 1 / ( 1 + (eff_b/eff_c)*(N_b/N_c) ) | |
266 | TH1D *fhFcMax; // Maximum fc histo | |
267 | TH1D *fhFcMin; // Minimum fc histo | |
268 | TH2D *fhFcRcb; // Correction histo fc vs the Ratio(c/b eloss) | |
269 | TGraphAsymmErrors * fgFcExtreme; // Extreme correction as TGraphAsymmErrors | |
270 | TGraphAsymmErrors * fgFcConservative; // Extreme correction as TGraphAsymmErrors | |
271 | TH1D *fhYieldCorr; // Corrected yield (stat unc. only) | |
272 | TH1D *fhYieldCorrMax; // Maximum corrected yield | |
273 | TH1D *fhYieldCorrMin; // Minimum corrected yield | |
274 | TH2D *fhYieldCorrRcb; // Corrected yield (stat unc. only) vs the Ratio(c/b eloss) | |
275 | TGraphAsymmErrors * fgYieldCorr; // Corrected yield as TGraphAsymmErrors (syst but feed-down) | |
276 | TGraphAsymmErrors * fgYieldCorrExtreme; // Extreme corrected yield as TGraphAsymmErrors (syst from feed-down) | |
277 | TGraphAsymmErrors * fgYieldCorrConservative; // Conservative corrected yield as TGraphAsymmErrors (syst from feed-down) | |
278 | TH1D *fhSigmaCorr; // Corrected cross-section (stat unc. only) | |
279 | TH1D *fhSigmaCorrMax; // Maximum corrected cross-section | |
280 | TH1D *fhSigmaCorrMin; // Minimum corrected cross-section | |
281 | TH1D *fhSigmaCorrDataSyst; // Corrected cross-section (syst. unc. from data only) | |
282 | TH2D *fhSigmaCorrRcb; // Corrected cross-section (stat unc. only) vs the Ratio(c/b eloss) | |
283 | TGraphAsymmErrors * fgSigmaCorr; // Corrected cross-section as TGraphAsymmErrors (syst but feed-down) | |
284 | TGraphAsymmErrors * fgSigmaCorrExtreme; // Extreme corrected cross-section as TGraphAsymmErrors (syst from feed-down) | |
285 | TGraphAsymmErrors * fgSigmaCorrConservative; // Conservative corrected cross-section as TGraphAsymmErrors (syst from feed-down) | |
286 | // | |
287 | TNtuple *fnSigma; // Ntuple of the calculation vs the Ratio(c/b eloss) | |
288 | TNtuple *fnHypothesis; // Ntuple of the calculation vs the Ratio(c/b eloss) | |
289 | ||
290 | // | |
291 | Int_t fFeedDownOption; // feed-down correction flag: 0=none, 1=fc, 2=Nb | |
292 | Bool_t fAsymUncertainties; // flag: asymmetric uncertainties are (1) or not (0) considered | |
293 | Bool_t fPbPbElossHypothesis; // flag: whether to do estimates vs Ratio(c/b eloss) hypothesis | |
294 | Bool_t fIsStatUncEff; // flag : consider (1) or not (0) the stat unc on the efficiencies | |
295 | Int_t fParticleAntiParticle; // 1: only one sign, 2: yield is for particle+anti-particle | |
296 | ||
297 | // | |
298 | TH1D *fhStatUncEffcSigma; // Uncertainty on the cross-section due to the prompt efficiency statistical uncertainty | |
299 | TH1D *fhStatUncEffbSigma; // Uncertainty on the cross-section due to the feed-down efficiency statistical uncertainty | |
300 | TH1D *fhStatUncEffcFD; // Uncertainty on the feed-down correction due to the prompt efficiency statistical uncertainty | |
301 | TH1D *fhStatUncEffbFD; // Uncertainty on the feed-down correction due to the feed-down efficiency statistical uncertainty | |
302 | ||
303 | ClassDef(AliHFPtSpectrum,3) // Class for Heavy Flavor spectra corrections | |
304 | }; | |
305 | ||
306 | #endif |