--- /dev/null
+/* $Id$ */
+
+#ifndef ALIUNFOLDING_H
+#define ALIUNFOLDING_H
+
+//
+// class that implements several unfolding methods
+// E.g. chi2 minimization and bayesian unfolding
+//
+
+// TMatrixD, TVectorD 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<Double_t> TVectorD'
+// PWG0/AliUnfolding.h:21: previous declaration as `struct TVectorD'
+
+#include "TObject.h"
+#include <TMatrixD.h>
+#include <TVectorD.h>
+
+class TH1;
+class TH2;
+class TH1F;
+class TH2F;
+class TH3F;
+class TF1;
+class TCollection;
+
+class AliUnfolding : public TObject
+{
+ public:
+ enum RegularizationType { kNone = 0, kPol0, kPol1, kLog, kEntropy, kCurvature };
+ enum MethodType { kChi2Minimization = 0, kBayesian = 1 };
+
+ AliUnfolding();
+ virtual ~AliUnfolding();
+
+ void SetInput(TH2* correlationMatrix, TH1* efficiency, TH1* measured) { fCurrentCorrelation = correlationMatrix; fCurrentEfficiency = efficiency; fCurrentESD = measured; }
+ void SetInitialConditions(TH1* initialConditions) { fInitialConditions = initialConditions; }
+ const TH1* GetResult() const { return fResult; }
+
+ static void SetParameters(Int_t measuredBins, Int_t unfoldedBins, Bool_t bigbin) { fMaxInput = measuredBins; fMaxParams = unfoldedBins; fgCreateBigBin = bigbin; }
+ static void SetChi2MinimizationParameters(RegularizationType type, Float_t weight) { fgRegularizationType = type; fgRegularizationWeight = weight; }
+ static void SetRegularizationRange(Int_t start, Int_t end) { fgRegularizationRangeStart = start; fgRegularizationRangeEnd = end; }
+ static void SetBayesianParameters(Float_t smoothing, Int_t nIterations) { fgBayesianSmoothing = smoothing; fgBayesianIterations = nIterations; }
+
+ Int_t ApplyMinuitFit(Bool_t check = kFALSE);
+ Int_t ApplyBayesianMethod(Bool_t determineError = kTRUE);
+ Int_t ApplyNBDFit();
+ Int_t ApplyLaszloMethod();
+
+ TH1* StatisticalUncertainty(MethodType methodType, Bool_t randomizeMeasured, Bool_t randomizeResponse, TH1* compareTo = 0);
+
+ protected:
+ 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 UnfoldWithBayesian(* aEfficiency, TH1* measured, TH1* initialConditions, TH1* aResult, Float_t regPar, Int_t nIterations);
+ Int_t UnfoldWithMinuit(TH1* correlation, TH1* aEfficiency, TH1* measured, TH1* initialConditions, TH1* result, Bool_t check);
+
+ Float_t BayesCovarianceDerivate(Float_t matrixM[251][251], TH2* hResponse, Int_t k, Int_t i, Int_t r, Int_t u);
+
+ TH1* fCurrentESD; //! measured spectrum
+ TH2* fCurrentCorrelation; //! correlation matrix
+ TH1* fCurrentEfficiency; //! efficiency
+ TH1* fInitialConditions; //! initial conditions
+ TH1* fResult; //! unfolding result
+
+ // 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 Int_t fgMaxParams; //! bins in unfolded histogram = number of fit params
+ static Int_t fgMaxInput; //! bins in measured histogram
+
+ // configuration params follow
+ static RegularizationType fgRegularizationType; //! regularization that is used during Chi2 method
+ static Float_t fgRegularizationWeight; //! factor for regularization term
+ static Int_t fgRegularizationRangeStart; //! first bin where regularization is applied
+ static Int_t fgRegularizationRangeEnd; //! last bin + 1 where regularization is applied
+ static Bool_t fgCreateBigBin; //! to fix fluctuations at high multiplicities, all entries above a certain limit are summarized in one bin
+
+ static Float_t fgBayesianSmoothing; //! smoothing parameter (0 = no smoothing)
+ static Int_t fgBayesianIterations; //! number of iterations in Bayesian method
+ // end of configuration
+
+ private:
+ AliUnfolding(const AliUnfolding&);
+ AliUnfolding& operator=(const AliUnfolding&);
+
+ ClassDef(AliUnfolding, 0);
+};
+
+#endif
+