7 // class that implements several unfolding methods
8 // I.e. chi2 minimization and bayesian unfolding
9 // The whole class is static and not thread-safe (due to the fact that MINUIT unfolding is not thread-safe)
12 // TMatrixD, TVectorD defined here, because it does not seem possible to predeclare these (or i do not know how)
14 // $ROOTSYS/include/TVectorDfwd.h:21: conflicting types for `typedef struct TVectorT<Double_t> TVectorD'
15 // PWG0/AliUnfolding.h:21: previous declaration as `struct TVectorD'
28 class AliUnfolding : public TObject
31 enum RegularizationType { kNone = 0, kPol0, kPol1, kLog, kEntropy, kCurvature, kRatio, kPowerLaw, kLogLog };
32 enum MethodType { kInvalid = -1, kChi2Minimization = 0, kBayesian = 1, kFunction = 2};
34 virtual ~AliUnfolding() {};
36 static void SetUnfoldingMethod(MethodType methodType);
37 static void SetCreateOverflowBin(Float_t overflowBinLimit);
38 static void SetSkipBinsBegin(Int_t nBins);
39 static void SetNbins(Int_t nMeasured, Int_t nUnfolded);
40 static void SetChi2Regularization(RegularizationType type, Float_t weight);
41 static void SetMinuitStepSize(Float_t stepSize) { fgMinuitStepSize = stepSize; }
42 static void SetMinuitPrecision(Float_t pres) {fgMinuitPrecision = pres;}
43 static void SetMinuitMaxIterations(Int_t iter) {fgMinuitMaxIterations = iter;}
44 static void SetMinimumInitialValue(Bool_t flag, Float_t value = -1) { fgMinimumInitialValue = flag; fgMinimumInitialValueFix = value; }
45 static void SetNormalizeInput(Bool_t flag) { fgNormalizeInput = flag; }
46 static void SetNotFoundEvents(Float_t notFoundEvents) { fgNotFoundEvents = notFoundEvents; }
47 static void SetSkip0BinInChi2(Bool_t flag) { fgSkipBin0InChi2 = flag; }
48 static void SetBayesianParameters(Float_t smoothing, Int_t nIterations);
49 static void SetFunction(TF1* function);
50 static void SetDebug(Bool_t flag) { fgDebug = flag; }
51 static void SetPowern(Int_t n) {fgPowern = -1*n;}
53 static Int_t Unfold(TH2* correlation, TH1* efficiency, TH1* measured, TH1* initialConditions, TH1* result, Bool_t check = kFALSE);
54 static Int_t UnfoldGetBias(TH2* correlation, TH1* efficiency, TH1* measured, TH1* initialConditions, TH1* result);
56 static TH1* GetPenaltyPlot(Double_t* params);
57 static TH1* GetPenaltyPlot(TH1* corrected);
59 static TH1* GetResidualsPlot(Double_t* params);
60 static TH1* GetResidualsPlot(TH1* corrected);
62 static Double_t GetChi2FromFit() {return fChi2FromFit;}
63 static Double_t GetPenaltyVal() {return fPenaltyVal;}
64 static Double_t GetAvgResidual() {return fAvgResidual;}
66 static void DrawResults(TH2* correlation, TH1* efficiency, TH1* measured, TH1* initialConditions, TCanvas *canvas = 0, Int_t reuseHists = kFALSE,TH1 *unfolded=0);
67 static void InteractiveUnfold(TH2* correlation, TH1* efficiency, TH1* measured, TH1* initialConditions);
68 static void RedrawInteractive();
73 static Int_t UnfoldWithMinuit(TH2* correlation, TH1* efficiency, TH1* measured, TH1* initialConditions, TH1* result, Bool_t check);
74 static Int_t UnfoldWithBayesian(TH2* correlation, TH1* aEfficiency, TH1* measured, TH1* initialConditions, TH1* aResult);
75 static Int_t UnfoldWithFunction(TH2* correlation, TH1* efficiency, TH1* measured, TH1* /* initialConditions */, TH1* aResult);
77 static void CreateOverflowBin(TH2* correlation, TH1* measured);
78 static void SetStaticVariables(TH2* correlation, TH1* measured, TH1* efficiency);
80 static void MakePads();
81 static void DrawGuess(Double_t *params, TVirtualPad *pfolded=0, TVirtualPad *pres=0, TVirtualPad *ppen=0, Int_t reuseHists = kFALSE, TH1* unfolded=0);
83 static Double_t RegularizationPol0(TVectorD& params);
84 static Double_t RegularizationPol1(TVectorD& params);
85 static Double_t RegularizationTotalCurvature(TVectorD& params);
86 static Double_t RegularizationEntropy(TVectorD& params);
87 static Double_t RegularizationLog(TVectorD& params);
88 static Double_t RegularizationRatio(TVectorD& params);
89 static Double_t RegularizationPowerLaw(TVectorD& params);
90 static Double_t RegularizationLogLog(TVectorD& params);
92 static void Chi2Function(Int_t&, Double_t*, Double_t& chi2, Double_t *params, Int_t);
93 static void TF1Function(Int_t& unused1, Double_t* unused2, Double_t& chi2, Double_t *params, Int_t unused3);
95 // static variable to be accessed by MINUIT
96 static TMatrixD* fgCorrelationMatrix; // contains fCurrentCorrelation in matrix form
97 static TMatrixD* fgCorrelationMatrixSquared; // contains squared fCurrentCorrelation in matrix form
98 static TMatrixD* fgCorrelationCovarianceMatrix; // contains the errors of fCurrentESD
99 static TVectorD* fgCurrentESDVector; // contains fCurrentESD
100 static TVectorD* fgEntropyAPriori; // a-priori distribution for entropy regularization
101 static TVectorD* fgEfficiency; // efficiency
103 static TVectorD* fgBinWidths; // bin widths to be taken into account in regularization
104 static TVectorD* fgBinPos; // bin positions of unfolded
106 static TAxis *fgUnfoldedAxis; // bin widths and positions for unfolded
107 static TAxis *fgMeasuredAxis; // bin widths and positions for measured
109 static TF1* fgFitFunction; // fit function
111 // --- configuration params follow ---
112 static MethodType fgMethodType; // unfolding method to be used
113 static Int_t fgMaxParams; // bins in unfolded histogram = number of fit params
114 static Int_t fgMaxInput; // bins in measured histogram
115 static Float_t fgOverflowBinLimit; // to fix fluctuations at high multiplicities, all entries above the limit are summarized in one bin
117 static RegularizationType fgRegularizationType; // regularization that is used during Chi2 method
118 static Float_t fgRegularizationWeight; // factor for regularization term
119 static Int_t fgSkipBinsBegin; // (optional) skip the given number of bins in the regularization
120 static Float_t fgMinuitStepSize; // (usually not needed to be changed) step size in minimization
121 static Float_t fgMinuitPrecision; // precision used by minuit. default = 1e-6
122 static Int_t fgMinuitMaxIterations; // maximum number of iterations used by minuit. default = 5000
123 static Bool_t fgMinimumInitialValue; // set all initial values at least to the smallest value among the initial values
124 static Float_t fgMinimumInitialValueFix; // use this as the minimum initial value instead of determining it automatically
125 static Bool_t fgNormalizeInput; // normalize input spectrum
126 static Float_t fgNotFoundEvents; // constraint on the total number of not found events sum(guess * (1/eff -1))
127 static Bool_t fgSkipBin0InChi2; // skip bin 0 (= 0 measured) in chi2 function
129 static Float_t fgBayesianSmoothing; // smoothing parameter (0 = no smoothing)
130 static Int_t fgBayesianIterations; // number of iterations in Bayesian method
132 static Bool_t fgDebug; // debug flag
133 // --- end of configuration ---
135 static Int_t fgCallCount; // call count to chi2 function
137 static Int_t fgPowern; // power of power law for regularization with power law
139 static Double_t fChi2FromFit; // Chi2 from fit at current iteration
140 static Double_t fPenaltyVal; // Penalty value at current iteration (\beta * PU)
141 static Double_t fAvgResidual; // Sum residuals / nbins
143 static Int_t fgPrintChi2Details; // debug for chi2 calc
145 // Pointers for interactive unfolder
146 static TCanvas *fgCanvas; // Canvas for interactive unfolder
147 static TH1 *fghUnfolded; // Unfolding result for interactive unfolder
148 static TH2 *fghCorrelation; // Response matrix for interactive unfolder
149 static TH1 *fghEfficiency; // Efficiency histo for interactive unfolder
150 static TH1 *fghMeasured; // Measured distribution for interactive unfolder
153 AliUnfolding(const AliUnfolding&);
154 AliUnfolding& operator=(const AliUnfolding&);
156 ClassDef(AliUnfolding, 0);