// @(#)root/fumili:$Id: TFumili.h 20882 2007-11-19 11:31:26Z rdm $ // Author: Rene Brun 31/08/99 ///////////////////////////////////////////////////////////////////////// // // // TFumili // // // // The FUMILI Minimization package // // // ///////////////////////////////////////////////////////////////////////// #ifndef ROOT_TFumili #define ROOT_TFumili #ifndef ROOT_TVirtualFitter #include "TVirtualFitter.h" #endif class TF1; class TFumili : public TVirtualFitter { private: Int_t fMaxParam; // Int_t fMaxParam2; // fMaxParam*fMaxParam Int_t fNlog; // Int_t fNfcn; // Number of FCN calls; Int_t fNED1; // Number of experimental vectors X=(x1,x2,...xK) Int_t fNED2; // K - Length of vector X plus 2 (for chi2) Int_t fNED12; // fNED1+fNED2 Int_t fNpar; // fNpar - number of parameters Int_t fNstepDec; // fNstepDec - maximum number of step decreasing counter Int_t fNlimMul; // fNlimMul - after fNlimMul successful iterations permits four-fold increasing of fPL Int_t fNmaxIter; // fNmaxIter - maximum number of iterations Int_t fLastFixed; // Last fixed parameter number Int_t fENDFLG; // End flag of fit Int_t fINDFLG[5]; // internal flags; Bool_t fGRAD; // user calculated gradients Bool_t fWARN; // warnings Bool_t fDEBUG; // debug info Bool_t fLogLike; // LogLikelihood flag Bool_t fNumericDerivatives; // Double_t *fZ0; //[fMaxParam2] Matrix of approximate second derivatives of objective function // This matrix is diagonal and always contain only variable parameter's // derivatives Double_t *fZ; //[fMaxParam2] Invers fZ0 matrix - covariance matrix Double_t *fGr; //[fMaxParam] Gradients of objective function Double_t *fParamError; //[fMaxParam] Parameter errors Double_t *fSumLog; //[fNlog] Double_t *fEXDA; //[fNED12] experimental data poInt_ter // don't calculate parameter errors - take them from fParamError array Double_t *fA; //[fMaxParam] Fit parameter array Double_t *fPL0; //[fMaxParam] Step initial bounds Double_t *fPL; //[fMaxParam] Limits for parameters step. If <0, then parameter is fixed // Defines multidimensional parallelepiped with center in param. vector Double_t *fDA; //[fMaxParam] Parameter step Double_t *fAMX; //[fMaxParam] Maximum param value Double_t *fAMN; //[fMaxParam] Minimum param value Double_t *fR; //[fMaxParam] Correlation factors Double_t *fDF; //[fMaxParam] // First derivatives of theoretical function Double_t *fCmPar; //[fMaxParam] parameters of commands Double_t fS; // fS - objective function value (return) Double_t fEPS; // fEPS - required precision of parameters. If fEPS<0 then Double_t fRP; // Precision of fit ( machine zero on CDC 6000) quite old yeh? Double_t fAKAPPA; // Double_t fGT; // Expected function change in next iteration TString *fANames; //[fMaxParam] Parameter names TString fCword; // Command string // TF1 *fTFNF1; //Pointer to theoretical function // void (*fFCN) (Int_t &, Double_t *, Double_t &f, Double_t *, Int_t); // // //wrapper function to calculate functional value, gradients and Z-matrix // Double_t (*fTFN)(Double_t *, Double_t *, Double_t*); // Wrapper function for TFN public: TFumili(Int_t maxpar=25); virtual ~TFumili(); void BuildArrays(); virtual Double_t Chisquare(Int_t npar, Double_t *params) const; virtual void Clear(Option_t *opt=""); void DeleteArrays(); void Derivatives(Double_t*,Double_t*); Int_t Eval(Int_t& npar, Double_t *grad, Double_t &fval, Double_t *par, Int_t flag); // Evaluate the minimisation function Double_t EvalTFN(Double_t *,Double_t*); virtual Int_t ExecuteCommand(const char *command, Double_t *args, Int_t nargs); Int_t ExecuteSetCommand(Int_t ); virtual void FitChisquare(Int_t &npar, Double_t *gin, Double_t &f, Double_t *u, Int_t flag); virtual void FitChisquareI(Int_t &npar, Double_t *gin, Double_t &f, Double_t *u, Int_t flag); virtual void FitLikelihood(Int_t &npar, Double_t *gin, Double_t &f, Double_t *u, Int_t flag); virtual void FitLikelihoodI(Int_t &npar, Double_t *gin, Double_t &f, Double_t *u, Int_t flag); virtual void FixParameter(Int_t ipar); virtual Double_t *GetCovarianceMatrix() const; virtual Double_t GetCovarianceMatrixElement(Int_t i, Int_t j) const; virtual Int_t GetErrors(Int_t ipar,Double_t &eplus, Double_t &eminus, Double_t &eparab, Double_t &globcc) const; virtual Int_t GetNumberTotalParameters() const; virtual Int_t GetNumberFreeParameters() const; Double_t* GetPL0() const { return fPL0;} virtual Double_t GetParError(Int_t ipar) const; virtual Double_t GetParameter(Int_t ipar) const ; virtual Int_t GetParameter(Int_t ipar,char *name,Double_t &value,Double_t &verr,Double_t &vlow, Double_t &vhigh) const; virtual const char *GetParName(Int_t ipar) const; virtual Int_t GetStats(Double_t &amin, Double_t &edm, Double_t &errdef, Int_t &nvpar, Int_t &nparx) const; virtual Double_t GetSumLog(Int_t ); Double_t* GetZ() const { return fZ;} void InvertZ(Int_t); virtual Bool_t IsFixed(Int_t ipar) const; Int_t Minimize(); virtual void PrintResults(Int_t k,Double_t p) const; virtual void ReleaseParameter(Int_t ipar); Int_t SGZ(); void SetData(Double_t *,Int_t,Int_t); virtual void SetFitMethod(const char *name); virtual Int_t SetParameter(Int_t ipar,const char *parname,Double_t value,Double_t verr,Double_t vlow, Double_t vhigh); void SetParNumber(Int_t ParNum) { fNpar = ParNum;}; ClassDef(TFumili,0) //The FUMILI Minimization package }; R__EXTERN TFumili * gFumili; #endif