#include "THnSparse.h"
class TF1;
+class TProfile;
+class TRandom3;
class AliCFUnfolding : public TNamed {
AliCFUnfolding& operator= (const AliCFUnfolding& c);
~AliCFUnfolding();
- void SetMaxNumberOfIterations(Int_t n) {fMaxNumIterations=n;}
- void SetMaxChi2(Double_t val) {fMaxChi2=val;}
- void SetMaxChi2PerDOF(Double_t val);
+ void SetMaxNumberOfIterations(Int_t n = 10) {fMaxNumIterations=n; fNRandomIterations=n; }
+
+ /*
+ The following is for correct error estimation
+ thanks to Marta Verweij
+ */
+ void SetUseCorrelatedErrors (Double_t maxConvergence = 1.e-06 , UInt_t randomSeed = 0) {
+ fUseCorrelatedErrors = kTRUE ;
+ fRandomSeed = randomSeed ;
+ SetMaxConvergencePerDOF(maxConvergence) ;
+ }
+ void UnsetCorrelatedErrors() {fUseCorrelatedErrors=kFALSE;}
+
+
void UseSmoothing(TF1* fcn=0x0, Option_t* opt="iremn") { // if fcn=0x0 then smooth using neighbouring bins
fUseSmoothing=kTRUE; // this function must NOT be used if fNVariables > 3
fSmoothFunction=fcn; // the option "opt" is used if "fcn" is specified
void Unfold();
- THnSparse* GetResponse() const {return fResponse;}
- THnSparse* GetInverseResponse() const {return fInverseResponse;}
- THnSparse* GetPrior() const {return fPrior;}
- THnSparse* GetOriginalPrior() const {return fOriginalPrior;}
- THnSparse* GetEfficiency() const {return fEfficiency;}
- THnSparse* GetUnfolded() const {return fUnfolded;}
- THnSparse* GetEstMeasured() const {return fMeasuredEstimate;}
- THnSparse* GetMeasured() const {return fMeasured;}
- THnSparse* GetConditional() const {return fConditional;}
- TF1* GetSmoothFunction() const {return fSmoothFunction;}
+ THnSparse* GetResponse() const {return fResponse;}
+ THnSparse* GetInverseResponse() const {return fInverseResponse;}
+ THnSparse* GetPrior() const {return fPrior;}
+ THnSparse* GetOriginalPrior() const {return fOriginalPrior;}
+ THnSparse* GetEfficiency() const {return fEfficiency;}
+ THnSparse* GetUnfolded() const {return fUnfolded;}
+ THnSparse* GetEstMeasured() const {return fMeasuredEstimate;}
+ THnSparse* GetMeasured() const {return fMeasured;}
+ THnSparse* GetConditional() const {return fConditional;}
+ TF1* GetSmoothFunction() const {return fSmoothFunction;}
+ TProfile* GetDeltaUnfoldedProfile() const {return fDeltaUnfoldedP;}
+ Int_t GetDOF(); // Returns number of degrees of freedom
+
+ static Short_t SmoothUsingNeighbours(THnSparse*); // smoothes the unfolded spectrum using the neighbouring cells
private :
// then will be updated automatically at each iteration
THnSparse *fEfficiency; // Efficiency map : dimensions must be N = number of variables
// this map must be filled only with "true" values of the variables (should not include resolution effects)
- THnSparse *fMeasured; // Measured spectrum to be unfolded : dimensions must be N = number of variables
+ THnSparse *fMeasured; // Measured spectrum to be unfolded : dimensions must be N = number of variables (modified)
+ THnSparse *fMeasuredOrig; // Measured spectrum to be unfolded : dimensions must be N = number of variables (not modified)
Int_t fMaxNumIterations; // Maximum number of iterations to be performed
Int_t fNVariables; // Number of variables used in analysis spectra (pt, y, ...)
- Double_t fMaxChi2; // Maximum Chi2 between unfolded and prior distributions.
- Bool_t fUseSmoothing; // Smooth the unfolded sectrum at each iteration
+/* Double_t fMaxChi2; // Maximum Chi2 between unfolded and prior distributions. */
+ Bool_t fUseSmoothing; // Smooth the unfolded sectrum at each iteration; default is kFALSE
TF1 *fSmoothFunction; // Function used to smooth the unfolded spectrum
Option_t *fSmoothOption; // Option to use during the fit (with fSmoothFunction) ; default is "iremn"
+ /* correlated error calculation */
+ Double_t fMaxConvergence; // Convergence criterion in case of correlated error calculation
+ Bool_t fUseCorrelatedErrors;// Calculate correlated errors for the final unfolded spectrum; default is kTRUE
+ Int_t fNRandomIterations; // Number of random distributed measured spectra
+
// internal settings
THnSparse *fOriginalPrior; // This is the original prior distribution : will not be modified
THnSparse *fInverseResponse; // Inverse response matrix
Int_t *fCoordinates2N; // Coordinates in 2N (measured,true) space
Int_t *fCoordinatesN_M; // Coordinates in measured space
Int_t *fCoordinatesN_T; // Coordinates in true space
-
+
+
+ /* correlated error calculation */
+ THnSparse *fRandomizedDist; // Randomized distribution for each bin of the measured spectrum to calculate correlated errors
+ TRandom3 *fRandom3; // Object to get random number following Poisson distribution
+ THnSparse *fRandomUnfolded;
+ TProfile *fDeltaUnfoldedP; // Profile of the delta-unfolded distribution
+ Int_t fNCalcCorrErrors; // book keeping to prevend infinite loop
+ UInt_t fRandomSeed; // Random seed
+
// functions
void Init(); // initialisation of the internal settings
void CreateFlatPrior(); // creates a flat a priori distribution in case the one given in the constructor is null
Double_t GetChi2(); // returns the chi2 between unfolded and prior spectra
Short_t Smooth(); // function calling smoothing methods
- Short_t SmoothUsingNeighbours(); // smoothes the unfolded spectrum using the neighbouring cells
Short_t SmoothUsingFunction(); // smoothes the unfolded spectrum using a fit function
- ClassDef(AliCFUnfolding,0);
+ /* correlated error calculation */
+ Double_t GetConvergence(); // Returns convergence criterion
+ void CalculateCorrelatedErrors(); // Calculates correlated errors for the final unfolded spectrum
+ void InitDeltaUnfoldedProfile(); // Initializes the fDeltaUnfoldedP Profiles with spread option
+ void CreateRandomizedDist(); // Create randomized dist from measured distribution
+ void FillDeltaUnfoldedProfile(); // Fills the fDeltaUnfoldedP profile
+ void SetMaxConvergencePerDOF (Double_t val);
+
+ ClassDef(AliCFUnfolding,1);
};
#endif
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