| library: libTMVA #include "MethodBase.h" |
private:
void Init()
protected:
Bool_t CheckSanity(TTree* theTree = 0)
void ResetThisBase()
public:
virtual ~MethodBase()
void AppendToMethodName(TString methodNameSuffix)
static TClass* Class()
TMVA::MethodBase::CutOrientation GetCutOrientation()
Double_t GetEffForRoot(Double_t)
virtual Double_t GetEfficiency(TString, TTree*)
vector<TString>* GetInputVars() const
TString GetJobName() const
TMVA::Types::MVA GetMethod() const
TString GetMethodName() const
virtual Double_t GetmuTransform(TTree*)
virtual Double_t GetMvaValue(TMVA::Event* e)
Int_t GetNvar() const
virtual Double_t GetOptimalSignificance(Double_t SignalEvents, Double_t BackgroundEvents, Double_t& optimal_significance_value) const
TString GetOptions() const
virtual Double_t GetSeparation()
virtual Double_t GetSignificance()
static TMVA::MethodBase* GetThisBase()
TTree* GetTrainingTree() const
TString GetWeightFileDir() const
TString GetWeightFileExtension() const
TString GetWeightFileName()
Double_t GetXmaxNorm(Int_t ivar) const
Double_t GetXmaxNorm(TString var) const
Double_t GetXminNorm(Int_t ivar) const
Double_t GetXminNorm(TString var) const
static Double_t IGetEffForRoot(Double_t)
virtual void InitNorm(TTree* theTree)
virtual TClass* IsA() const
Bool_t IsOK() const
Double_t Norm(Int_t ivar, Double_t x) const
Double_t Norm(TString var, Double_t x) const
TMVA::MethodBase& operator=(const TMVA::MethodBase&)
virtual void PrepareEvaluationTree(TTree* theTestTree)
virtual void ReadWeightsFromFile()
void SetInputVars(vector<TString>* theInputVars)
void SetJobName(TString jobName)
void SetMethodName(TString methodName)
void SetVerbose(Bool_t v = kTRUE)
void SetWeightFileDir(TString fileDir)
void SetWeightFileExtension(TString fileExtension)
void SetWeightFileName()
void SetWeightFileName(TString)
void SetXmaxNorm(Int_t ivar, Double_t x)
void SetXmaxNorm(TString var, Double_t x)
void SetXminNorm(Int_t ivar, Double_t x)
void SetXminNorm(TString var, Double_t x)
virtual void ShowMembers(TMemberInspector& insp, char* parent)
virtual void Streamer(TBuffer& b)
void StreamerNVirtual(TBuffer& b)
virtual void Test(TTree* theTestTree)
virtual void TestInit(TTree* theTestTree)
virtual void TestInitLocal(TTree*)
virtual void Train()
void UpdateNorm(Int_t ivar, Double_t x)
Bool_t Verbose() const
virtual void WriteHistosToFile()
void WriteHistosToFile(TDirectory* targetDir)
virtual void WriteWeightsToFile()
private:
TString fFileExtension extension used in weight files (default: ".weights")
TString fFileDir unix sub-directory for weight files (default: "weights")
TString fWeightFile weight file name
Double_t fMeanS mean (signal)
Double_t fMeanB mean (background)
Double_t fRmsS RMS (signal)
Double_t fRmsB RMS (background)
Double_t fXmin minimum (signal and background)
Double_t fXmax maximum (signal and background)
Bool_t fVerbose
vector<Double_t>* fXminNorm minimum of input variables
vector<Double_t>* fXmaxNorm maximum of input variables
static TMVA::MethodBase* fgThisBase
protected:
TString fJobName name of job -> user defined, appears in weight files
TString fMethodName name of the method (set in derived class)
TMVA::Types::MVA fMethod type of method (set in derived class)
TTree* fTrainingTree training tree
TString fTestvar variable used in evauation, etc (mostly the MVA)
TString fTestvarPrefix 'MVA_' prefix of MVA variable
vector<TString>* fInputVars vector of input variables used in MVA
TString fOptions options string
TDirectory* fBaseDir base director, needed to know where to jump back from localDir
TDirectory* fLocalTDir local directory, used to save monitoring histograms
Int_t fNvar number of input variables
Bool_t fIsOK status of sanity checks
TH1* fHistS_plotbin MVA plots used for graphics representation (signal)
TH1* fHistB_plotbin MVA plots used for graphics representation (background)
TH1* fHistS_highbin MVA plots used for efficiency calculations (signal)
TH1* fHistB_highbin MVA plots used for efficiency calculations (background)
TH1* fEffS efficiency plot (signal)
TH1* fEffB efficiency plot (background)
TH1* fEffBvsS background efficiency versus signal efficiency
TH1* fRejBvsS background rejection (=1-eff.) versus signal efficiency
TH1* fHistBhatS working histograms needed for mu-transform (signal)
TH1* fHistBhatB working histograms needed for mu-transform (background)
TH1* fHistMuS mu-transform (signal)
TH1* fHistMuB mu-transform (background)
Double_t fX
Double_t fMode
TGraph* fGraphS graphs used for splines for efficiency (signal)
TGraph* fGraphB graphs used for splines for efficiency (background)
TGraph* fGrapheffBvsS graphs used for splines for signal eff. versus background eff.
TMVA::PDF* fSplS PDFs of MVA distribution (signal)
TMVA::PDF* fSplB PDFs of MVA distribution (background)
TSpline* fSpleffBvsS splines for signal eff. versus background eff.
Int_t fNbins number of bins in representative histograms
Int_t fNbinsH number of bins in evaluation histograms
TMVA::MethodBase::CutOrientation fCutOrientation +1 if Sig>Bkg, -1 otherwise
TMVA::TSpline1* fSplRefS helper splines for RootFinder (signal)
TMVA::TSpline1* fSplRefB helper splines for RootFinder (background)
public:
static const TMVA::MethodBase::CutOrientation kNegative
static const TMVA::MethodBase::CutOrientation kPositive
static const TMVA::MethodBase::Type kSignal
static const TMVA::MethodBase::Type kBackground
prepare tree branch with the method's discriminating variable
evaluate method (resulting discriminating variable) or input varible
series of sanity checks on input tree (eg, do all the variables really exist in tree, etc)