//
// class that implements several unfolding methods
-// E.g. chi2 minimization and bayesian unfolding
+// I.e. chi2 minimization and bayesian unfolding
+// The whole class is static and not thread-safe (due to the fact that MINUIT unfolding is not thread-safe)
//
// TMatrixD, TVectorD defined here, because it does not seem possible to predeclare these (or i do not know how)
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; }
+ enum RegularizationType { kNone = 0, kPol0, kPol1, kLog, kEntropy, kCurvature, kRatio };
+ enum MethodType { kInvalid = -1, kChi2Minimization = 0, kBayesian = 1, kFunction = 2};
+
+ virtual ~AliUnfolding() {};
+
+ static void SetUnfoldingMethod(MethodType methodType);
+ static void SetCreateOverflowBin(Float_t overflowBinLimit);
+ static void SetSkipBinsBegin(Int_t nBins);
+ static void SetNbins(Int_t nMeasured, Int_t nUnfolded);
+ static void SetChi2Regularization(RegularizationType type, Float_t weight);
+ static void SetMinuitStepSize(Float_t stepSize) { fgMinuitStepSize = stepSize; }
+ static void SetMinimumInitialValue(Bool_t flag, Float_t value = -1) { fgMinimumInitialValue = flag; fgMinimumInitialValueFix = value; }
+ static void SetNormalizeInput(Bool_t flag) { fgNormalizeInput = flag; }
+ static void SetNotFoundEvents(Float_t notFoundEvents) { fgNotFoundEvents = notFoundEvents; }
+ static void SetSkip0BinInChi2(Bool_t flag) { fgSkipBin0InChi2 = flag; }
+ static void SetBayesianParameters(Float_t smoothing, Int_t nIterations);
+ static void SetFunction(TF1* function);
+ static void SetDebug(Bool_t flag) { fgDebug = flag; }
+
+ static Int_t Unfold(TH2* correlation, TH1* efficiency, TH1* measured, TH1* initialConditions, TH1* result, Bool_t check = kFALSE);
+ static Int_t UnfoldGetBias(TH2* correlation, TH1* efficiency, TH1* measured, TH1* initialConditions, TH1* result);
+
+ static TH1* GetPenaltyPlot(Double_t* params);
+ static TH1* GetPenaltyPlot(TH1* corrected);
+
+ protected:
+ AliUnfolding() {};
- Int_t ApplyMinuitFit(Bool_t check = kFALSE);
- Int_t ApplyBayesianMethod(Bool_t determineError = kTRUE);
- Int_t ApplyNBDFit();
- Int_t ApplyLaszloMethod();
+ static Int_t UnfoldWithMinuit(TH2* correlation, TH1* efficiency, TH1* measured, TH1* initialConditions, TH1* result, Bool_t check);
+ static Int_t UnfoldWithBayesian(TH2* correlation, TH1* aEfficiency, TH1* measured, TH1* initialConditions, TH1* aResult);
+ static Int_t UnfoldWithFunction(TH2* correlation, TH1* efficiency, TH1* measured, TH1* /* initialConditions */, TH1* aResult);
- TH1* StatisticalUncertainty(MethodType methodType, Bool_t randomizeMeasured, Bool_t randomizeResponse, TH1* compareTo = 0);
+ static void DrawGuess(Double_t *params);
+ static void CreateOverflowBin(TH2* correlation, TH1* measured);
+ static void SetStaticVariables(TH2* correlation, TH1* measured, TH1* efficiency);
- 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 Double_t RegularizationRatio(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 void Chi2Function(Int_t&, Double_t*, Double_t& chi2, Double_t *params, Int_t);
+ static void TF1Function(Int_t& unused1, Double_t* unused2, Double_t& chi2, Double_t *params, Int_t unused3);
// 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:
+ static TMatrixD* fgCorrelationMatrix; // contains fCurrentCorrelation in matrix form
+ static TMatrixD* fgCorrelationMatrixSquared; // contains squared 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 TVectorD* fgEfficiency; // efficiency
+ static TVectorD* fgBinWidths; // bin widths to be taken into account in regularization
+
+ static TF1* fgFitFunction; // fit function
+
+ // --- configuration params follow ---
+ static MethodType fgMethodType; // unfolding method to be used
+ static Int_t fgMaxParams; // bins in unfolded histogram = number of fit params
+ static Int_t fgMaxInput; // bins in measured histogram
+ static Float_t fgOverflowBinLimit; // to fix fluctuations at high multiplicities, all entries above the limit are summarized in one bin
+
+ static RegularizationType fgRegularizationType; // regularization that is used during Chi2 method
+ static Float_t fgRegularizationWeight; // factor for regularization term
+ static Int_t fgSkipBinsBegin; // (optional) skip the given number of bins in the regularization
+ static Float_t fgMinuitStepSize; // (usually not needed to be changed) step size in minimization
+ static Bool_t fgMinimumInitialValue; // set all initial values at least to the smallest value among the initial values
+ static Float_t fgMinimumInitialValueFix; // use this as the minimum initial value instead of determining it automatically
+ static Bool_t fgNormalizeInput; // normalize input spectrum
+ static Float_t fgNotFoundEvents; // constraint on the total number of not found events sum(guess * (1/eff -1))
+ static Bool_t fgSkipBin0InChi2; // skip bin 0 (= 0 measured) in chi2 function
+
+ static Float_t fgBayesianSmoothing; // smoothing parameter (0 = no smoothing)
+ static Int_t fgBayesianIterations; // number of iterations in Bayesian method
+
+ static Bool_t fgDebug; // debug flag
+ // --- end of configuration ---
+
+ static Int_t fgCallCount; // call count to chi2 function
+
+private:
AliUnfolding(const AliUnfolding&);
AliUnfolding& operator=(const AliUnfolding&);
git://git.uio.no / u / mrichter / AliRoot.git / blobdiff