#ifndef MARS_MJOptimize #define MARS_MJOptimize #ifndef MARS_MJob #include "MJob.h" #endif #ifndef ROOT_TArrayD #include #endif class TMinuit; class MAlphaFitter; class MEvtLoop; class MParList; class MFilter; class MFilterList; class MFitParameters; class MFitParametersCalc; class MHMatrix; class MGeomCam; class MRead; class MReadTree; class MJOptimize : public MJob { public: enum Optimizer_t { kMigrad, // Minimize by the method of Migrad kSimplex, // Minimize by the method of Simplex kMinimize, // Migrad + Simplex (if Migrad fails) kMinos, // Minos error determination kImprove, // Local minimum search kSeek, // Minimize by the method of Monte Carlo kNone // Skip optimization }; private: Int_t fDebug; // -1 no output, 0 MJOptimize output, 1 PrintStatistics output Int_t fNumEvents; TList fRules; TList fFilter; TList fPreCuts; TList fNamesOn; TList fNamesOff; TString fNameOut; void AddPoint(TList *l, Int_t idx, Float_t val) const; TList *GetPlots() const; void AddRulesToMatrix(MHMatrix &m) const; void SetupFilters(MFilterList &list, MFilter *filter=0) const; Bool_t FillMatrix(MReadTree &read, MParList &l, Bool_t userules=kFALSE); MEvtLoop *fEvtLoop; //! Bool_t AddSequences(MRead &read, TList &list) const; // Minuit Interface static void fcn(Int_t &npar, Double_t *gin, Double_t &f, Double_t *par, Int_t iflag); Double_t Fcn(const TArrayD &par, TMinuit *minuit=0); Int_t Minuit(TMinuit &minuit, const char *cmd) const; Int_t Migrad(TMinuit &minuit) const { return Minuit(minuit, "MIGRAD"); } Int_t Simplex(TMinuit &minuit) const { return Minuit(minuit, "SIMPLEX"); } Int_t Minimize(TMinuit &minuit) const { return Minuit(minuit, "MINIMIZE"); } Int_t Seek(TMinuit &minuit) const { return Minuit(minuit, "SEEK"); } Int_t Improve(TMinuit &minuit) const { return Minuit(minuit, "IMPROVE"); } Int_t Minos(TMinuit &minuit) const { return Minuit(minuit, "MINOS"); } TArrayD fParameters; //! TArrayD fLimLo; //! TArrayD fLimUp; //! TArrayD fStep; //! Optimizer_t fType; UInt_t fNumMaxCalls; Float_t fTolerance; Bool_t Optimize(MEvtLoop &evtloop); public: MJOptimize(); // I/O void AddSequenceOn(const char *fname, const char *dir=""); void AddSequenceOff(const char *fname, const char *dir=""); void ResetSequences(); // Interface for filter cuts Int_t AddParameter(const char *rule); void AddFilter(const char *rule); void AddPreCut(const char *rule); // Steering of optimization void SetNumEvents(UInt_t n); void SetDebug(UInt_t n); void SetNameOut(const char *name="") { fNameOut = name; } void SetOptimizer(Optimizer_t o); void SetNumMaxCalls(UInt_t num=0) { fNumMaxCalls=num; } void SetTolerance(Float_t tol=0) { fTolerance=tol; } // Parameter access void SetParameters(const TArrayD &par); void SetParameter(Int_t idx, Double_t start, Double_t lo=0, Double_t up=0, Double_t step=-1) { if (fParameters.GetSize()<=idx) { fParameters.Set(idx+1); fLimLo.Set(idx+1); fLimUp.Set(idx+1); fStep.Set(idx+1); } fParameters[idx] = start; fLimLo[idx] = lo; fLimUp[idx] = up; if (step<=0) fStep[idx] = start==0 ? 0.1 : TMath::Abs(start*0.15); else fStep[idx] = step; } void FixParameter(Int_t idx, Double_t start) { if (fParameters.GetSize()<=idx) { fParameters.Set(idx+1); fLimLo.Set(idx+1); fLimUp.Set(idx+1); fStep.Set(idx+1); } fParameters[idx] = start; fLimLo[idx] = 0; fLimUp[idx] = 0; fStep[idx] = 0; } const TArrayD &GetParameters() const { return fParameters; } // Generalized optimizing routines Bool_t Optimize(MParList &list); // Special optimizing routines Bool_t Run(const char *fname, MFilter *filter, MAlphaFitter *fit=0); Bool_t Run(const char *fname, MAlphaFitter *fit=0) { return Run(fname, 0, fit); } Bool_t Run(MFilter *filter, MAlphaFitter *fit=0) { return Run(0, filter, fit); } Bool_t Run(MAlphaFitter *fit=0) { return Run(0, 0, fit); } Bool_t RunOnOff(const char *fname, MFilter *filter, MAlphaFitter *fit=0, const char *tree="Events"); Bool_t RunOnOff(const char *fname, MAlphaFitter *fit=0, const char *tree="Events") { return RunOnOff(fname, 0, fit, tree); } Bool_t RunEnergy(const char *fname, const char *rule); Bool_t RunOnOff(MFilter *filter, MAlphaFitter *fit=0, const char *tree="Events") { return RunOnOff(0, filter, fit, tree); } Bool_t RunOnOff(MAlphaFitter *fit=0, const char *tree="Events") { return RunOnOff(fit, tree); } Bool_t RunEnergy(const char *rule) { return RunEnergy(0, rule); } ClassDef(MJOptimize, 0) // Class for optimization of the Supercuts }; #endif