library: libTMVA
#include "TMVA_MethodCuts.h"

TMVA_MethodCuts

class description - source file - inheritance tree (.pdf)

class TMVA_MethodCuts : public TMVA_MethodBase

Inheritance Chart:

TObject

TMVA_MethodBase

TMVA_MethodCuts

    private:

        void Backup(Double_t&, Double_t&, Double_t&, vector<Double_t>*)
        void CheckErr(TString, Int_t)
        void CreateVariablePDFs()
        void Fit()
        void GetEffsfromPDFs(Double_t* cutMin, Double_t* cutMax, Double_t& effS, Double_t& effB)
        void GetEffsfromSelection(Double_t* cutMin, Double_t* cutMax, Double_t& effS, Double_t& effB)
        void InitCuts()
        void InitTMinuitAndFit(TMVA_MethodCuts::FitParameters fitParam = kNotEnforced, vector<Double_t>* parStart = NULL)
        void MatchCutsToPars(Double_t*, Double_t*, Double_t*)
        void MatchParsToCuts(Double_t*, Double_t*, Double_t*)
      Bool_t SanityChecks()

    public:

                              TMVA_MethodCuts(TString jobName, vector<TString>* theVariables, TTree* theTree = 0, TString theOption = MC:150:10000:, TDirectory* theTargetFile = 0)
                              TMVA_MethodCuts(vector<TString>* theVariables, TString theWeightFile, TDirectory* theTargetDir = NULL)
                              TMVA_MethodCuts(const TMVA_MethodCuts&)
                      virtual ~TMVA_MethodCuts()
               static TClass* Class()
                     Double_t ComputeEstimator(Double_t*, Int_t)
             virtual Double_t GetEfficiency(TString, TTree*)
             virtual Double_t GetmuTransform(TTree*)
             virtual Double_t GetMvaValue(TMVA_Event* e)
             virtual Double_t GetSeparation()
             virtual Double_t GetSignificance()
              virtual TClass* IsA() const
             TMVA_MethodCuts& operator=(const TMVA_MethodCuts&)
                 virtual void ReadWeightsFromFile()
                         void SetTestSignalEfficiency(Double_t eff)
                 virtual void ShowMembers(TMemberInspector& insp, char* parent)
                 virtual void Streamer(TBuffer& b)
                         void StreamerNVirtual(TBuffer& b)
                 virtual void TestInitLocal(TTree* testTree)
      static TMVA_MethodCuts* ThisCuts()
                 virtual void Train()
                 virtual void WriteHistosToFile()
                 virtual void WriteWeightsToFile()

Data Members

    private:

      TMVA_MethodCuts::ConstrainType fConstrainType    
      TMVA_MethodCuts::FitMethodType fFitMethod        
          TMVA_MethodCuts::EffMethod fEffMethod        
            TMVA_MethodCuts::FitType fFitType          
              vector<FitParameters>* fFitParams        
                            Double_t fTestSignalEff    
                            Double_t fEffSMin          
                            Double_t fEffSMax          
              TMVA_BinarySearchTree* fBinaryTreeS      
              TMVA_BinarySearchTree* fBinaryTreeB      
                               Int_t fGa_preCalc       
                               Int_t fGa_SC_steps      
                               Int_t fGa_SC_offsteps   
                            Double_t fGa_SC_factor     
                               Int_t fGa_nsteps        
                            Double_t fEffRef           
                               Int_t fNpar             
                      vector<Int_t>* fRangeSign        
                   vector<Double_t>* fPar0             
                            TRandom* fTrandom          
                   vector<Double_t>* fMeanS            
                   vector<Double_t>* fMeanB            
                   vector<Double_t>* fRmsS             
                   vector<Double_t>* fRmsB             
                   vector<Double_t>* fXmin             
                   vector<Double_t>* fXmax             
                                TH1* fEffBvsSLocal     
                       vector<TH1*>* fVarHistS         
                       vector<TH1*>* fVarHistB         
                       vector<TH1*>* fVarHistS_smooth  
                       vector<TH1*>* fVarHistB_smooth  
                  vector<TMVA_PDF*>* fVarPdfS          
                  vector<TMVA_PDF*>* fVarPdfB          
                               Int_t fNRandCuts        
                          Double_t** fCutMin           
                          Double_t** fCutMax           
             static TMVA_MethodCuts* fgThisCuts        

    public:

      static const TMVA_MethodCuts::ConstrainType kConstrainEffS            
      static const TMVA_MethodCuts::ConstrainType kConstrainEffB            
      static const TMVA_MethodCuts::FitMethodType kUseMonteCarlo            
      static const TMVA_MethodCuts::FitMethodType kUseGeneticAlgorithm      
          static const TMVA_MethodCuts::EffMethod kUseEventSelection        
          static const TMVA_MethodCuts::EffMethod kUsePDFs                  
      static const TMVA_MethodCuts::FitParameters kNotEnforced              
      static const TMVA_MethodCuts::FitParameters kStartFromMin             
      static const TMVA_MethodCuts::FitParameters kStartFromCenter          
      static const TMVA_MethodCuts::FitParameters kStartFromMax             
      static const TMVA_MethodCuts::FitParameters kForceMin                 
      static const TMVA_MethodCuts::FitParameters kForceMax                 
      static const TMVA_MethodCuts::FitParameters kForceSmart               
      static const TMVA_MethodCuts::FitParameters kForceVerySmart           
      static const TMVA_MethodCuts::FitParameters kStartingValuesAreGiven   
      static const TMVA_MethodCuts::FitParameters kRandomizeStartingValues  
            static const TMVA_MethodCuts::FitType kMigrad                   
            static const TMVA_MethodCuts::FitType kSimplex

Class Description

 Multivariate optimisation of signal efficiency for given background
 efficiency, using rectangular minimum and maximum requirements on
_______________________________________________________________________

TMVA_MethodCuts( TString jobName, vector<TString>* theVariables, TTree* theTree, TString theOption, TDirectory* theTargetDir ) : TMVA_MethodBase( jobName, theVariables, theTree, theOption, theTargetDir )

TMVA_MethodCuts( vector<TString> *theVariables, TString theWeightFile, TDirectory* theTargetDir ) : TMVA_MethodBase( theVariables, theWeightFile, theTargetDir )

void InitCuts( void )

~TMVA_MethodCuts( void )

Double_t GetMvaValue( TMVA_Event *e )

 evaluation

void Train( void )

 trainning method

Double_t ComputeEstimator( Double_t *par, Int_t /*npar*/ )

 caution: the npar gives the _free_ parameters
 however: the "par" array contains all parameters

void MatchParsToCuts( Double_t* par, Double_t* cutMin, Double_t* cutMax )

void MatchCutsToPars( Double_t* par, Double_t* cutMin, Double_t* cutMax )

void GetEffsfromPDFs( Double_t* cutMin, Double_t* cutMax, Double_t& effS, Double_t& effB )

void GetEffsfromSelection( Double_t* cutMin, Double_t* cutMax, Double_t& effS, Double_t& effB)

void CreateVariablePDFs( void )

 create list of histograms and PDFs

Bool_t SanityChecks( void )

 basic checks to ensure that assumptions on variable order are satisfied

void CheckErr( TString cmd, Int_t errFlag )

void WriteWeightsToFile( void )

 write weights to file
 though we could write the root effBvsS histogram directly, we
 prefer here to put everything into a human-readable form

void ReadWeightsFromFile( void )

 read weights from file
 though we could write the root effBvsS histogram directly, we
 prefer here to put everything into a human-readable form

void WriteHistosToFile( void )

void TestInitLocal( TTree *theTree )

Double_t GetEfficiency( TString theString, TTree * /*theTree*/ )

 parse input string for required background efficiency

Inline Functions

                Double_t GetSignificance()
                Double_t GetSeparation()
                Double_t GetmuTransform(TTree*)
                    void SetTestSignalEfficiency(Double_t eff)
        TMVA_MethodCuts* ThisCuts()
                    void InitTMinuitAndFit(TMVA_MethodCuts::FitParameters fitParam = kNotEnforced, vector<Double_t>* parStart = NULL)
                    void Fit()
                    void Backup(Double_t&, Double_t&, Double_t&, vector<Double_t>*)
                 TClass* Class()
                 TClass* IsA() const
                    void ShowMembers(TMemberInspector& insp, char* parent)
                    void Streamer(TBuffer& b)
                    void StreamerNVirtual(TBuffer& b)
         TMVA_MethodCuts TMVA_MethodCuts(const TMVA_MethodCuts&)
        TMVA_MethodCuts& operator=(const TMVA_MethodCuts&)

Author: Andreas Hoecker, Peter Speckmayer, Helge Voss, Kai Voss
Last update: root/tmva $Id: TMVA_MethodCuts.cxx,v 1.6 2006/05/09 08:37:06 brun Exp $
Copyright (c) 2005: *

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