/* $Id$ */ #ifndef ALIMULTIPLICITYCORRECTION_H #define ALIMULTIPLICITYCORRECTION_H #include "TNamed.h" // // class that contains the correction matrix and the functions for // correction the multiplicity spectrum // implements a several unfolding methods: e.g. chi2 minimization and bayesian unfolding // class TH1; class TH2; class TH1F; class TH2F; class TH3F; class TF1; class TCollection; // defined here, because it does not seem possible to predeclare these (or i do not know how) // --> // $ROOTSYS/include/TVectorDfwd.h:21: conflicting types for `typedef struct TVectorT TVectorD' // PWG0/dNdEta/AliMultiplicityCorrection.h:21: previous declaration as `struct TVectorD' #include #include class AliMultiplicityCorrection : public TNamed { public: enum EventType { kTrVtx = 0, kMB, kINEL }; enum RegularizationType { kNone = 0, kPol0, kPol1, kLog, kEntropy, kCurvature }; enum MethodType { kChi2Minimization = 0, kBayesian = 1 }; enum { kESDHists = 4, kMCHists = 5, kCorrHists = 8, kQualityRegions = 3 }; AliMultiplicityCorrection(); AliMultiplicityCorrection(const Char_t* name, const Char_t* title); virtual ~AliMultiplicityCorrection(); virtual Long64_t Merge(TCollection* list); void FillMeasured(Float_t vtx, Int_t measured05, Int_t measured10, Int_t measured15, Int_t measured20); void FillGenerated(Float_t vtx, Bool_t triggered, Bool_t vertex, Int_t generated05, Int_t generated10, Int_t generated15, Int_t generated20, Int_t generatedAll); void FillCorrection(Float_t vtx, Int_t generated05, Int_t generated10, Int_t generated15, Int_t generated20, Int_t generatedAll, Int_t measured05, Int_t measured10, Int_t measured15, Int_t measured20); Bool_t LoadHistograms(const Char_t* dir = 0); void SaveHistograms(); void DrawHistograms(); void DrawComparison(const char* name, Int_t inputRange, Bool_t fullPhaseSpace, Bool_t normalizeESD, TH1* mcHist, Bool_t simple = kFALSE); Int_t ApplyMinuitFit(Int_t inputRange, Bool_t fullPhaseSpace, EventType eventType, Bool_t check = kFALSE, TH1* initialConditions = 0); void SetRegularizationParameters(RegularizationType type, Float_t weight); void SetBayesianParameters(Float_t smoothing, Int_t nIterations); void ApplyNBDFit(Int_t inputRange, Bool_t fullPhaseSpace); void ApplyBayesianMethod(Int_t inputRange, Bool_t fullPhaseSpace, EventType eventType, Float_t regPar = 1, Int_t nIterations = 100, TH1* initialConditions = 0, Bool_t determineError = kTRUE); TH1* StatisticalUncertainty(MethodType methodType, Int_t inputRange, Bool_t fullPhaseSpace, EventType eventType, Bool_t randomizeMeasured, Bool_t randomizeResponse, TH1* compareTo = 0); void ApplyGaussianMethod(Int_t inputRange, Bool_t fullPhaseSpace); void ApplyLaszloMethod(Int_t inputRange, Bool_t fullPhaseSpace, EventType eventType); TH2F* GetMultiplicityESD(Int_t i) { return fMultiplicityESD[i]; } TH2F* GetMultiplicityVtx(Int_t i) { return fMultiplicityVtx[i]; } TH2F* GetMultiplicityMB(Int_t i) { return fMultiplicityMB[i]; } TH2F* GetMultiplicityINEL(Int_t i) { return fMultiplicityINEL[i]; } TH2F* GetMultiplicityMC(Int_t i, EventType eventType); TH3F* GetCorrelation(Int_t i) { return fCorrelation[i]; } TH1F* GetMultiplicityESDCorrected(Int_t i) { return fMultiplicityESDCorrected[i]; } void SetMultiplicityESD(Int_t i, TH2F* hist) { fMultiplicityESD[i] = hist; } void SetMultiplicityVtx(Int_t i, TH2F* hist) { fMultiplicityVtx[i] = hist; } void SetMultiplicityMB(Int_t i, TH2F* hist) { fMultiplicityMB[i] = hist; } void SetMultiplicityINEL(Int_t i, TH2F* hist) { fMultiplicityINEL[i] = hist; } void SetCorrelation(Int_t i, TH3F* hist) { fCorrelation[i] = hist; } void SetMultiplicityESDCorrected(Int_t i, TH1F* hist) { fMultiplicityESDCorrected[i] = hist; } void SetGenMeasFromFunc(TF1* inputMC, Int_t id); TH2F* CalculateMultiplicityESD(TH1* inputMC, Int_t correlationMap); static void NormalizeToBinWidth(TH1* hist); static void NormalizeToBinWidth(TH2* hist); void GetComparisonResults(Float_t* mc = 0, Int_t* mcLimit = 0, Float_t* residuals = 0, Float_t* ratioAverage = 0) const; TH1* GetEfficiency(Int_t inputRange, EventType eventType); static void SetQualityRegions(Bool_t SPDStudy); Float_t GetQuality(Int_t region) const { return fQuality[region]; } void FFT(Int_t dir, Int_t m, Double_t *x, Double_t *y); protected: static const Int_t fgkMaxParams; //! bins in unfolded histogram = number of fit params static const Int_t fgkMaxInput; //! bins in measured histogram static Double_t RegularizationPol0(TVectorD& params); static Double_t RegularizationPol1(TVectorD& params); static Double_t RegularizationTotalCurvature(TVectorD& params); static Double_t RegularizationEntropy(TVectorD& params); static Double_t RegularizationLog(TVectorD& params); static void MinuitFitFunction(Int_t&, Double_t*, Double_t& chi2, Double_t *params, Int_t); static void MinuitNBD(Int_t& unused1, Double_t* unused2, Double_t& chi2, Double_t *params, Int_t unused3); void SetupCurrentHists(Int_t inputRange, Bool_t fullPhaseSpace, EventType eventType, Bool_t createBigBin); Float_t BayesCovarianceDerivate(Float_t matrixM[251][251], TH2* hResponse, Int_t k, Int_t i, Int_t r, Int_t u); static Int_t UnfoldWithBayesian(TH1* correlation, TH1* aEfficiency, TH1* measured, TH1* initialConditions, TH1* aResult, Float_t regPar, Int_t nIterations); static Int_t UnfoldWithMinuit(TH1* correlation, TH1* aEfficiency, TH1* measured, TH1* initialConditions, TH1* result, Bool_t check); TH1* fCurrentESD; //! static variable to be accessed by MINUIT TH1* fCurrentCorrelation; //! static variable to be accessed by MINUIT TH1* fCurrentEfficiency; //! static variable to be accessed by MINUIT // static variable to be accessed by MINUIT static TMatrixD* fgCorrelationMatrix; //! contains fCurrentCorrelation in matrix form static TMatrixD* fgCorrelationCovarianceMatrix; //! contains the errors of fCurrentESD static TVectorD* fgCurrentESDVector; //! contains fCurrentESD static TVectorD* fgEntropyAPriori; //! a-priori distribution for entropy regularization static TF1* fgNBD; //! negative binomial distribution static RegularizationType fgRegularizationType; //! regularization that is used during Chi2 method static Float_t fgRegularizationWeight; //! factor for regularization term static Float_t fgBayesianSmoothing; //! smoothing parameter (0 = no smoothing) static Int_t fgBayesianIterations; //! number of iterations in Bayesian method TH2F* fMultiplicityESD[kESDHists]; // multiplicity histogram: vtx vs multiplicity; array: |eta| < 0.5, 0.9, 1.5, 2 (0..3) TH2F* fMultiplicityVtx[kMCHists]; // multiplicity histogram of events that have a reconstructed vertex : vtx vs multiplicity; array: |eta| < 0.5, 0.9, 1.5, 2, inf (0..4) TH2F* fMultiplicityMB[kMCHists]; // multiplicity histogram of triggered events : vtx vs multiplicity; array: |eta| < 0.5, 0.9, 1.5, 2, inf (0..4) TH2F* fMultiplicityINEL[kMCHists]; // multiplicity histogram of all (inelastic) events : vtx vs multiplicity; array: |eta| < 0.5, 0.9, 1.5, 2, inf (0..4) TH3F* fCorrelation[kCorrHists]; // vtx vs. (gene multiplicity (trig+vtx)) vs. (meas multiplicity); array: |eta| < 0.5, 1, 1.5, 2 (0..3 and 4..7), the first corrects to the eta range itself, the second to full phase space TH1F* fMultiplicityESDCorrected[kCorrHists]; // corrected histograms Float_t fLastChi2MC; //! last Chi2 between MC and unfolded ESD (calculated in DrawComparison) Int_t fLastChi2MCLimit; //! bin where the last chi2 breached a certain threshold, used to evaluate the multiplicity reach (calc. in DrawComparison) Float_t fLastChi2Residuals; //! last Chi2 of the ESD and the folded unfolded ESD (calculated in DrawComparison) Float_t fRatioAverage; //! last average of |ratio-1| where ratio = unfolded / mc (bin 2..150) static Int_t fgQualityRegionsB[kQualityRegions]; //! begin, given in multiplicity units static Int_t fgQualityRegionsE[kQualityRegions]; //! end Float_t fQuality[kQualityRegions]; //! stores the quality of the last comparison (calculated in DrawComparison). Contains 3 values that are averages of (MC - unfolded) / e(MC) in 3 regions, these are defined in fQualityRegionB,E private: AliMultiplicityCorrection(const AliMultiplicityCorrection&); AliMultiplicityCorrection& operator=(const AliMultiplicityCorrection&); ClassDef(AliMultiplicityCorrection, 2); }; #endif