Definition at line 75 of file MethodCuts.h.

Public Member Functions
	MethodCuts (const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="MC:150:10000:", TDirectory *theTargetFile=0)

	MethodCuts (DataSetInfo &theData, const TString &theWeightFile, TDirectory *theTargetDir=NULL)
	construction from weight file More...

virtual	~MethodCuts (void)
	destructor More...

virtual Bool_t	HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)
	Cuts can only handle classification with 2 classes. More...

void	Train (void)
	training method: here the cuts are optimised for the training sample More...

void	AddWeightsXMLTo (void *parent) const
	create XML description for LD classification and regression (for arbitrary number of output classes/targets) More...

void	ReadWeightsFromStream (std::istream &i)
	read the cuts from stream More...

void	ReadWeightsFromXML (void *wghtnode)
	read coefficients from xml weight file More...

Double_t	GetMvaValue (Double_t err=0, Double_t errUpper=0)
	cut evaluation: returns 1.0 if event passed, 0.0 otherwise More...

void	WriteMonitoringHistosToFile (void) const
	write histograms and PDFs to file for monitoring purposes More...

void	TestClassification ()
	nothing to test More...

Double_t	GetSeparation (TH1 , TH1 ) const
	compute "separation" defined as <s2> = (1/2) Int_-oo..+oo { (S(x) - B(x))^2/(S(x) + B(x)) dx } More...

Double_t	GetSeparation (PDF =0, PDF =0) const
	compute "separation" defined as <s2> = (1/2) Int_-oo..+oo { (S(x) - B(x))^2/(S(x) + B(x)) dx } More...

Double_t	GetSignificance (void) const
	compute significance of mean difference significance = \|<S> - \|/Sqrt(RMS_S2 + RMS_B2) More...

Double_t	GetmuTransform (TTree *)

Double_t	GetEfficiency (const TString &, Types::ETreeType, Double_t &)

Double_t	GetTrainingEfficiency (const TString &)

Double_t	GetRarity (Double_t, Types::ESBType) const
	compute rarity: R(x) = Integrate_[-oo..x] { PDF(x') dx' } where PDF(x) is the PDF of the classifier's signal or background distribution More...

Double_t	ComputeEstimator (std::vector< Double_t > &)
	returns estimator for "cut fitness" used by GA there are two requirements: 1) the signal efficiency must be equal to the required one in the efficiency scan 2) the background efficiency must be as small as possible the requirement 1) has priority over 2) More...

Double_t	EstimatorFunction (std::vector< Double_t > &)
	returns estimator for "cut fitness" used by GA More...

Double_t	EstimatorFunction (Int_t ievt1, Int_t ievt2)
	for full event scan More...

void	SetTestSignalEfficiency (Double_t effS)

void	PrintCuts (Double_t effS) const
	print cuts More...

Double_t	GetCuts (Double_t effS, std::vector< Double_t > &cutMin, std::vector< Double_t > &cutMax) const
	retrieve cut values for given signal efficiency More...

Double_t	GetCuts (Double_t effS, Double_t cutMin, Double_t cutMax) const
	retrieve cut values for given signal efficiency assume vector of correct size !! More...

const Ranking *	CreateRanking ()

void	DeclareOptions ()
	define the options (their key words) that can be set in the option string know options: Method <string> Minimisation method available values are: MC Monte Carlo <default> GA Genetic Algorithm SA Simulated annealing More...

void	ProcessOptions ()
	process user options sanity check, do not allow the input variables to be normalised, because this only creates problems when interpreting the cuts More...

void	CheckSetup ()
	check may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase) More...

Public Member Functions inherited from TMVA::MethodBase
	MethodBase (const TString &jobName, Types::EMVA methodType, const TString &methodTitle, DataSetInfo &dsi, const TString &theOption="", TDirectory *theBaseDir=0)
	standard constructur More...

	MethodBase (Types::EMVA methodType, DataSetInfo &dsi, const TString &weightFile, TDirectory *theBaseDir=0)
	constructor used for Testing + Application of the MVA, only (no training), using given WeightFiles More...

virtual	~MethodBase ()
	destructor More...

void	SetupMethod ()
	setup of methods More...

void	ProcessSetup ()
	process all options the "CheckForUnusedOptions" is done in an independent call, since it may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase) More...

void	AddOutput (Types::ETreeType type, Types::EAnalysisType analysisType)

void	TrainMethod ()

virtual std::map< TString, Double_t >	OptimizeTuningParameters (TString fomType="ROCIntegral", TString fitType="FitGA")
	call the Optimzier with the set of paremeters and ranges that are meant to be tuned. More...

virtual void	SetTuneParameters (std::map< TString, Double_t > tuneParameters)
	set the tuning parameters accoding to the argument This is just a dummy . More...

void	SetTrainTime (Double_t trainTime)

Double_t	GetTrainTime () const

void	SetTestTime (Double_t testTime)

Double_t	GetTestTime () const

virtual Double_t	GetKSTrainingVsTest (Char_t SorB, TString opt="X")

virtual void	TestMulticlass ()
	test multiclass classification More...

virtual void	TestRegression (Double_t &bias, Double_t &biasT, Double_t &dev, Double_t &devT, Double_t &rms, Double_t &rmsT, Double_t &mInf, Double_t &mInfT, Double_t &corr, Types::ETreeType type)
	calculate <sum-of-deviation-squared> of regression output versus "true" value from test sample More...

virtual void	DeclareCompatibilityOptions ()
	options that are used ONLY for the READER to ensure backward compatibility they are hence without any effect (the reader is only reading the training options that HAD been used at the training of the .xml weightfile at hand More...

virtual void	Reset ()

Double_t	GetMvaValue (const TMVA::Event const ev, Double_t err=0, Double_t *errUpper=0)

const std::vector< Float_t > &	GetRegressionValues (const TMVA::Event *const ev)

virtual const std::vector< Float_t > &	GetRegressionValues ()

virtual const std::vector< Float_t > &	GetMulticlassValues ()

virtual Double_t	GetProba (const Event *ev)

virtual Double_t	GetProba (Double_t mvaVal, Double_t ap_sig)
	compute likelihood ratio More...

virtual void	MakeClass (const TString &classFileName=TString("")) const
	create reader class for method (classification only at present) More...

void	PrintHelpMessage () const
	prints out method-specific help method More...

void	WriteStateToFile () const
	write options and weights to file note that each one text file for the main configuration information and one ROOT file for ROOT objects are created More...

void	ReadStateFromFile ()
	Function to write options and weights to file. More...

void	ReadStateFromStream (std::istream &tf)
	read the header from the weight files of the different MVA methods More...

void	ReadStateFromStream (TFile &rf)
	write reference MVA distributions (and other information) to a ROOT type weight file More...

void	ReadStateFromXMLString (const char *xmlstr)
	for reading from memory More...

virtual void	WriteEvaluationHistosToFile (Types::ETreeType treetype)
	writes all MVA evaluation histograms to file More...

virtual std::vector< Float_t >	GetMulticlassEfficiency (std::vector< std::vector< Float_t > > &purity)

virtual std::vector< Float_t >	GetMulticlassTrainingEfficiency (std::vector< std::vector< Float_t > > &purity)

virtual Double_t	GetROCIntegral (TH1D histS, TH1D histB) const
	calculate the area (integral) under the ROC curve as a overall quality measure of the classification More...

virtual Double_t	GetROCIntegral (PDF pdfS=0, PDF pdfB=0) const
	calculate the area (integral) under the ROC curve as a overall quality measure of the classification More...

virtual Double_t	GetMaximumSignificance (Double_t SignalEvents, Double_t BackgroundEvents, Double_t &optimal_significance_value) const
	plot significance, S/Sqrt(S^2 + B^2), curve for given number of signal and background events; returns cut for maximum significance also returned via reference is the maximum significance More...

virtual void	GetRegressionDeviation (UInt_t tgtNum, Types::ETreeType type, Double_t &stddev, Double_t &stddev90Percent) const

const TString &	GetJobName () const

const TString &	GetMethodName () const

TString	GetMethodTypeName () const

Types::EMVA	GetMethodType () const

const char *	GetName () const
	Returns name of object. More...

const TString &	GetTestvarName () const

const TString	GetProbaName () const

TString	GetWeightFileName () const
	retrieve weight file name More...

void	SetTestvarName (const TString &v="")

UInt_t	GetNvar () const

UInt_t	GetNVariables () const

UInt_t	GetNTargets () const

const TString &	GetInputVar (Int_t i) const

const TString &	GetInputLabel (Int_t i) const

const TString &	GetInputTitle (Int_t i) const

Double_t	GetMean (Int_t ivar) const

Double_t	GetRMS (Int_t ivar) const

Double_t	GetXmin (Int_t ivar) const

Double_t	GetXmax (Int_t ivar) const

Double_t	GetSignalReferenceCut () const

Double_t	GetSignalReferenceCutOrientation () const

void	SetSignalReferenceCut (Double_t cut)

void	SetSignalReferenceCutOrientation (Double_t cutOrientation)

TDirectory *	BaseDir () const
	returns the ROOT directory where info/histograms etc of the corresponding MVA method instance are stored More...

TDirectory *	MethodBaseDir () const
	returns the ROOT directory where all instances of the corresponding MVA method are stored More...

void	SetMethodDir (TDirectory *methodDir)

void	SetBaseDir (TDirectory *methodDir)

void	SetMethodBaseDir (TDirectory *methodDir)

UInt_t	GetTrainingTMVAVersionCode () const

UInt_t	GetTrainingROOTVersionCode () const

TString	GetTrainingTMVAVersionString () const
	calculates the TMVA version string from the training version code on the fly More...

TString	GetTrainingROOTVersionString () const
	calculates the ROOT version string from the training version code on the fly More...

TransformationHandler &	GetTransformationHandler (Bool_t takeReroutedIfAvailable=true)

const TransformationHandler &	GetTransformationHandler (Bool_t takeReroutedIfAvailable=true) const

void	RerouteTransformationHandler (TransformationHandler *fTargetTransformation)

DataSet *	Data () const

DataSetInfo &	DataInfo () const

UInt_t	GetNEvents () const
	temporary event when testing on a different DataSet than the own one More...

const Event *	GetEvent () const

const Event *	GetEvent (const TMVA::Event *ev) const

const Event *	GetEvent (Long64_t ievt) const

const Event *	GetEvent (Long64_t ievt, Types::ETreeType type) const

const Event *	GetTrainingEvent (Long64_t ievt) const

const Event *	GetTestingEvent (Long64_t ievt) const

const std::vector< TMVA::Event * > &	GetEventCollection (Types::ETreeType type)
	returns the event collection (i.e. More...

virtual Bool_t	IsSignalLike ()
	uses a pre-set cut on the MVA output (SetSignalReferenceCut and SetSignalReferenceCutOrientation) for a quick determination if an event would be selected as signal or background More...

virtual Bool_t	IsSignalLike (Double_t mvaVal)
	uses a pre-set cut on the MVA output (SetSignalReferenceCut and SetSignalReferenceCutOrientation) for a quick determination if an event with this mva output value would tbe selected as signal or background More...

Bool_t	HasMVAPdfs () const

virtual void	SetAnalysisType (Types::EAnalysisType type)

Types::EAnalysisType	GetAnalysisType () const

Bool_t	DoRegression () const

Bool_t	DoMulticlass () const

void	DisableWriting (Bool_t setter)

Public Member Functions inherited from TMVA::IMethod
	IMethod ()

virtual	~IMethod ()

Public Member Functions inherited from TMVA::Configurable
	Configurable (const TString &theOption="")

virtual	~Configurable ()
	default destructur More...

virtual void	ParseOptions ()
	options parser More...

void	PrintOptions () const
	prints out the options set in the options string and the defaults More...

const char *	GetConfigName () const

const char *	GetConfigDescription () const

void	SetConfigName (const char *n)

void	SetConfigDescription (const char *d)

template<class T >
OptionBase *	DeclareOptionRef (T &ref, const TString &name, const TString &desc="")

template<class T >
OptionBase *	DeclareOptionRef (T *&ref, Int_t size, const TString &name, const TString &desc="")

template<class T >
void	AddPreDefVal (const T &)

template<class T >
void	AddPreDefVal (const TString &optname, const T &)

void	CheckForUnusedOptions () const
	checks for unused options in option string More...

const TString &	GetOptions () const

void	SetOptions (const TString &s)

void	WriteOptionsToStream (std::ostream &o, const TString &prefix) const
	write options to output stream (e.g. in writing the MVA weight files More...

void	ReadOptionsFromStream (std::istream &istr)
	read option back from the weight file More...

void	AddOptionsXMLTo (void *parent) const
	write options to XML file More...

void	ReadOptionsFromXML (void *node)

void	SetMsgType (EMsgType t)

template<class T >
TMVA::OptionBase *	DeclareOptionRef (T &ref, const TString &name, const TString &desc)

template<class T >
TMVA::OptionBase *	DeclareOptionRef (T *&ref, Int_t size, const TString &name, const TString &desc)

Public Member Functions inherited from TObject
	TObject ()

	TObject (const TObject &object)
	TObject copy ctor. More...

TObject &	operator= (const TObject &rhs)
	TObject assignment operator. More...

virtual	~TObject ()
	TObject destructor. More...

virtual void	AppendPad (Option_t *option="")
	Append graphics object to current pad. More...

virtual void	Browse (TBrowser *b)
	Browse object. May be overridden for another default action. More...

virtual const char *	ClassName () const
	Returns name of class to which the object belongs. More...

virtual void	Clear (Option_t *="")

virtual TObject *	Clone (const char *newname="") const
	Make a clone of an object using the Streamer facility. More...

virtual Int_t	Compare (const TObject *obj) const
	Compare abstract method. More...

virtual void	Copy (TObject &object) const
	Copy this to obj. More...

virtual void	Delete (Option_t *option="")
	Delete this object. More...

virtual Int_t	DistancetoPrimitive (Int_t px, Int_t py)
	Computes distance from point (px,py) to the object. More...

virtual void	Draw (Option_t *option="")
	Default Draw method for all objects. More...

virtual void	DrawClass () const
	Draw class inheritance tree of the class to which this object belongs. More...

virtual TObject *	DrawClone (Option_t *option="") const
	Draw a clone of this object in the current pad. More...

virtual void	Dump () const
	Dump contents of object on stdout. More...

virtual void	Execute (const char method, const char params, Int_t *error=0)
	Execute method on this object with the given parameter string, e.g. More...

virtual void	Execute (TMethod method, TObjArray params, Int_t *error=0)
	Execute method on this object with parameters stored in the TObjArray. More...

virtual void	ExecuteEvent (Int_t event, Int_t px, Int_t py)
	Execute action corresponding to an event at (px,py). More...

virtual TObject *	FindObject (const char *name) const
	Must be redefined in derived classes. More...

virtual TObject *	FindObject (const TObject *obj) const
	Must be redefined in derived classes. More...

virtual Option_t *	GetDrawOption () const
	Get option used by the graphics system to draw this object. More...

virtual UInt_t	GetUniqueID () const
	Return the unique object id. More...

virtual const char *	GetIconName () const
	Returns mime type name of object. More...

virtual Option_t *	GetOption () const

virtual char *	GetObjectInfo (Int_t px, Int_t py) const
	Returns string containing info about the object at position (px,py). More...

virtual const char *	GetTitle () const
	Returns title of object. More...

virtual Bool_t	HandleTimer (TTimer *timer)
	Execute action in response of a timer timing out. More...

virtual ULong_t	Hash () const
	Return hash value for this object. More...

virtual Bool_t	InheritsFrom (const char *classname) const
	Returns kTRUE if object inherits from class "classname". More...

virtual Bool_t	InheritsFrom (const TClass *cl) const
	Returns kTRUE if object inherits from TClass cl. More...

virtual void	Inspect () const
	Dump contents of this object in a graphics canvas. More...

virtual Bool_t	IsFolder () const
	Returns kTRUE in case object contains browsable objects (like containers or lists of other objects). More...

virtual Bool_t	IsEqual (const TObject *obj) const
	Default equal comparison (objects are equal if they have the same address in memory). More...

virtual Bool_t	IsSortable () const

Bool_t	IsOnHeap () const

Bool_t	IsZombie () const

virtual Bool_t	Notify ()
	This method must be overridden to handle object notification. More...

virtual void	ls (Option_t *option="") const
	The ls function lists the contents of a class on stdout. More...

virtual void	Paint (Option_t *option="")
	This method must be overridden if a class wants to paint itself. More...

virtual void	Pop ()
	Pop on object drawn in a pad to the top of the display list. More...

virtual void	Print (Option_t *option="") const
	This method must be overridden when a class wants to print itself. More...

virtual Int_t	Read (const char *name)
	Read contents of object with specified name from the current directory. More...

virtual void	RecursiveRemove (TObject *obj)
	Recursively remove this object from a list. More...

virtual void	SaveAs (const char filename="", Option_t option="") const
	Save this object in the file specified by filename. More...

virtual void	SavePrimitive (std::ostream &out, Option_t *option="")
	Save a primitive as a C++ statement(s) on output stream "out". More...

virtual void	SetDrawOption (Option_t *option="")
	Set drawing option for object. More...

virtual void	SetUniqueID (UInt_t uid)
	Set the unique object id. More...

virtual void	UseCurrentStyle ()
	Set current style settings in this object This function is called when either TCanvas::UseCurrentStyle or TROOT::ForceStyle have been invoked. More...

virtual Int_t	Write (const char *name=0, Int_t option=0, Int_t bufsize=0)
	Write this object to the current directory. More...

virtual Int_t	Write (const char *name=0, Int_t option=0, Int_t bufsize=0) const
	Write this object to the current directory. More...

void *	operator new (size_t sz)

void *	operator new[] (size_t sz)

void *	operator new (size_t sz, void *vp)

void *	operator new[] (size_t sz, void *vp)

void	operator delete (void *ptr)
	Operator delete. More...

void	operator delete[] (void *ptr)
	Operator delete []. More...

void	SetBit (UInt_t f, Bool_t set)
	Set or unset the user status bits as specified in f. More...

void	SetBit (UInt_t f)

void	ResetBit (UInt_t f)

Bool_t	TestBit (UInt_t f) const

Int_t	TestBits (UInt_t f) const

void	InvertBit (UInt_t f)

virtual void	Info (const char method, const char msgfmt,...) const
	Issue info message. More...

virtual void	Warning (const char method, const char msgfmt,...) const
	Issue warning message. More...

virtual void	Error (const char method, const char msgfmt,...) const
	Issue error message. More...

virtual void	SysError (const char method, const char msgfmt,...) const
	Issue system error message. More...

virtual void	Fatal (const char method, const char msgfmt,...) const
	Issue fatal error message. More...

void	AbstractMethod (const char *method) const
	Use this method to implement an "abstract" method that you don't want to leave purely abstract. More...

void	MayNotUse (const char *method) const
	Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary). More...

void	Obsolete (const char method, const char asOfVers, const char *removedFromVers) const
	Use this method to declare a method obsolete. More...

Public Member Functions inherited from TMVA::IFitterTarget
	IFitterTarget ()

virtual	~IFitterTarget ()

virtual void	ProgressNotifier (TString, TString)

Static Public Member Functions
static MethodCuts *	DynamicCast (IMethod *method)

Static Public Member Functions inherited from TObject
static Long_t	GetDtorOnly ()
	Return destructor only flag. More...

static void	SetDtorOnly (void *obj)
	Set destructor only flag. More...

static Bool_t	GetObjectStat ()
	Get status of object stat flag. More...

static void	SetObjectStat (Bool_t stat)
	Turn on/off tracking of objects in the TObjectTable. More...

Static Public Attributes
static const Double_t	fgMaxAbsCutVal

Protected Member Functions
void	MakeClassSpecific (std::ostream &, const TString &) const
	write specific classifier response More...

void	GetHelpMessage () const
	get help message text More...

Protected Member Functions inherited from TMVA::MethodBase
void	NoErrorCalc (Double_t const err, Double_t const errUpper)

virtual void	ReadWeightsFromStream (TFile &)

void	SetWeightFileName (TString)
	set the weight file name (depreciated) More...

const TString &	GetWeightFileDir () const

void	SetWeightFileDir (TString fileDir)
	set directory of weight file More...

Bool_t	IsNormalised () const

void	SetNormalised (Bool_t norm)

Bool_t	Verbose () const

Bool_t	Help () const

const TString &	GetInternalVarName (Int_t ivar) const

const TString &	GetOriginalVarName (Int_t ivar) const

Bool_t	HasTrainingTree () const

virtual void	MakeClassSpecificHeader (std::ostream &, const TString &="") const

void	Statistics (Types::ETreeType treeType, const TString &theVarName, Double_t &, Double_t &, Double_t &, Double_t &, Double_t &, Double_t &)
	calculates rms,mean, xmin, xmax of the event variable this can be either done for the variables as they are or for normalised variables (in the range of 0-1) if "norm" is set to kTRUE More...

Bool_t	TxtWeightsOnly () const

Bool_t	IsConstructedFromWeightFile () const

Bool_t	IgnoreEventsWithNegWeightsInTraining () const

Protected Member Functions inherited from TMVA::Configurable
Bool_t	LooseOptionCheckingEnabled () const

void	EnableLooseOptions (Bool_t b=kTRUE)

void	WriteOptionsReferenceToFile ()
	write complete options to output stream More...

void	ResetSetFlag ()
	resets the IsSet falg for all declare options to be called before options are read from stream More...

const TString &	GetReferenceFile () const

MsgLogger &	Log () const

Protected Member Functions inherited from TObject
void	MakeZombie ()

virtual void	DoError (int level, const char location, const char fmt, va_list va) const
	Interface to ErrorHandler (protected). More...

Private Types
enum	EFitMethodType { kUseMonteCarlo = 0, kUseGeneticAlgorithm, kUseSimulatedAnnealing, kUseMinuit, kUseEventScan, kUseMonteCarloEvents }

enum	EEffMethod { kUseEventSelection = 0, kUsePDFs }

enum	EFitParameters { kNotEnforced = 0, kForceMin, kForceMax, kForceSmart }

Private Member Functions
void	MatchParsToCuts (const std::vector< Double_t > &, Double_t , Double_t )
	translates parameters into cuts More...

void	MatchParsToCuts (Double_t , Double_t , Double_t *)

void	MatchCutsToPars (std::vector< Double_t > &, Double_t , Double_t )
	translates cuts into parameters More...

void	MatchCutsToPars (std::vector< Double_t > &, Double_t , Double_t , Int_t ibin)
	translate the cuts into parameters (obsolete function) More...

void	CreateVariablePDFs (void)
	for PDF method: create efficiency reference histograms and PDFs More...

void	GetEffsfromSelection (Double_t cutMin, Double_t cutMax, Double_t &effS, Double_t &effB)
	compute signal and background efficiencies from event counting for given cut sample More...

void	GetEffsfromPDFs (Double_t cutMin, Double_t cutMax, Double_t &effS, Double_t &effB)
	compute signal and background efficiencies from PDFs for given cut sample More...

void	Init (void)
	default initialisation called by all constructors More...

Private Attributes
TString	fFitMethodS

EFitMethodType	fFitMethod

TString	fEffMethodS

EEffMethod	fEffMethod

std::vector< EFitParameters > *	fFitParams

Double_t	fTestSignalEff

Double_t	fEffSMin

Double_t	fEffSMax

Double_t *	fCutRangeMin

Double_t *	fCutRangeMax

std::vector< Interval * >	fCutRange

BinarySearchTree *	fBinaryTreeS

BinarySearchTree *	fBinaryTreeB

Double_t **	fCutMin

Double_t **	fCutMax

Double_t *	fTmpCutMin

Double_t *	fTmpCutMax

TString *	fAllVarsI

Int_t	fNpar

Double_t	fEffRef

std::vector< Int_t > *	fRangeSign

TRandom *	fRandom

std::vector< Double_t > *	fMeanS

std::vector< Double_t > *	fMeanB

std::vector< Double_t > *	fRmsS

std::vector< Double_t > *	fRmsB

TH1 *	fEffBvsSLocal

std::vector< TH1 * > *	fVarHistS

std::vector< TH1 * > *	fVarHistB

std::vector< TH1 * > *	fVarHistS_smooth

std::vector< TH1 * > *	fVarHistB_smooth

std::vector< PDF * > *	fVarPdfS

std::vector< PDF * > *	fVarPdfB

Bool_t	fNegEffWarning

Additional Inherited Members
Public Types inherited from TMVA::MethodBase
enum	EWeightFileType { kROOT =0, kTEXT }

Public Types inherited from TObject
enum	EStatusBits { kCanDelete = BIT(0), kMustCleanup = BIT(3), kObjInCanvas = BIT(3), kIsReferenced = BIT(4), kHasUUID = BIT(5), kCannotPick = BIT(6), kNoContextMenu = BIT(8), kInvalidObject = BIT(13) }

enum	{ kIsOnHeap = 0x01000000, kNotDeleted = 0x02000000, kZombie = 0x04000000, kBitMask = 0x00ffffff }

enum	{ kSingleKey = BIT(0), kOverwrite = BIT(1), kWriteDelete = BIT(2) }

Public Attributes inherited from TMVA::MethodBase
const Event *	fTmpEvent

Bool_t	fSetupCompleted

Static Protected Member Functions inherited from TMVA::MethodBase
static MethodBase *	GetThisBase ()
	return a pointer the base class of this method More...

Protected Attributes inherited from TMVA::MethodBase
Ranking *	fRanking

std::vector< TString > *	fInputVars

Int_t	fNbins

Int_t	fNbinsMVAoutput

Int_t	fNbinsH

Types::EAnalysisType	fAnalysisType

std::vector< Float_t > *	fRegressionReturnVal

std::vector< Float_t > *	fMulticlassReturnVal

UInt_t	fSignalClass

UInt_t	fBackgroundClass

#include <TMVA/MethodCuts.h>

Inheritance diagram for TMVA::MethodCuts:

Collaboration diagram for TMVA::MethodCuts:

Member Enumeration Documentation

enum TMVA::MethodCuts::EEffMethod

private

Enumerator
kUseEventSelection
kUsePDFs

Definition at line 173 of file MethodCuts.h.

enum TMVA::MethodCuts::EFitMethodType

private

Enumerator
kUseMonteCarlo
kUseGeneticAlgorithm
kUseSimulatedAnnealing
kUseMinuit
kUseEventScan
kUseMonteCarloEvents

Definition at line 162 of file MethodCuts.h.

enum TMVA::MethodCuts::EFitParameters

private

Enumerator
kNotEnforced
kForceMin
kForceMax
kForceSmart

Definition at line 177 of file MethodCuts.h.

Constructor & Destructor Documentation

TMVA::MethodCuts::MethodCuts	(	const TString &	jobName,
		const TString &	methodTitle,
		DataSetInfo &	theData,
		const TString &	theOption = `"MC:150:10000:"`,
		TDirectory *	theTargetFile = `0`
	)

TMVA::MethodCuts::MethodCuts	(	DataSetInfo &	theData,
		const TString &	theWeightFile,
		TDirectory *	theTargetDir = `NULL`
	)

construction from weight file

Definition at line 172 of file MethodCuts.cxx.

TMVA::MethodCuts::~MethodCuts ( void )

virtual

destructor

Definition at line 272 of file MethodCuts.cxx.

Member Function Documentation

void TMVA::MethodCuts::AddWeightsXMLTo ( void * parent ) const

virtual

create XML description for LD classification and regression (for arbitrary number of output classes/targets)

Implements TMVA::MethodBase.

Definition at line 1272 of file MethodCuts.cxx.

void TMVA::MethodCuts::CheckSetup ( )

inlinevirtual

check may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase)

Reimplemented from TMVA::MethodBase.

Definition at line 149 of file MethodCuts.h.

Double_t TMVA::MethodCuts::ComputeEstimator ( std::vector< Double_t > & pars )

returns estimator for "cut fitness" used by GA there are two requirements: 1) the signal efficiency must be equal to the required one in the efficiency scan 2) the background efficiency must be as small as possible the requirement 1) has priority over 2)

Definition at line 878 of file MethodCuts.cxx.

const Ranking* TMVA::MethodCuts::CreateRanking ( )

inlinevirtual

Implements TMVA::MethodBase.

Definition at line 140 of file MethodCuts.h.

void TMVA::MethodCuts::CreateVariablePDFs ( void )

private

for PDF method: create efficiency reference histograms and PDFs

Definition at line 1091 of file MethodCuts.cxx.

void TMVA::MethodCuts::DeclareOptions ( )

virtual

define the options (their key words) that can be set in the option string know options: Method <string> Minimisation method available values are: MC Monte Carlo <default> GA Genetic Algorithm SA Simulated annealing

EffMethod <string> Efficiency selection method available values are: EffSel <default> EffPDF

VarProp <string> Property of variable 1 for the MC method (taking precedence over the globale setting. The same values as for the global option are available. Variables 1..10 can be set this way

CutRangeMin/Max <float> user-defined ranges in which cuts are varied

Implements TMVA::MethodBase.

Definition at line 320 of file MethodCuts.cxx.

static MethodCuts* TMVA::MethodCuts::DynamicCast ( IMethod * method )

inlinestatic

Definition at line 90 of file MethodCuts.h.

Double_t TMVA::MethodCuts::EstimatorFunction ( std::vector< Double_t > & pars )

virtual

returns estimator for "cut fitness" used by GA

Implements TMVA::IFitterTarget.

Definition at line 865 of file MethodCuts.cxx.

Double_t TMVA::MethodCuts::EstimatorFunction	(	Int_t	ievt1,
		Int_t	ievt2
	)

for full event scan

Definition at line 821 of file MethodCuts.cxx.

Double_t TMVA::MethodCuts::GetCuts	(	Double_t	effS,
		std::vector< Double_t > &	cutMin,
		std::vector< Double_t > &	cutMax
	)		const

retrieve cut values for given signal efficiency

Definition at line 551 of file MethodCuts.cxx.

Double_t TMVA::MethodCuts::GetCuts	(	Double_t	effS,
		Double_t *	cutMin,
		Double_t *	cutMax
	)		const

retrieve cut values for given signal efficiency assume vector of correct size !!

Definition at line 536 of file MethodCuts.cxx.

Double_t TMVA::MethodCuts::GetEfficiency	(	const TString &	theString,
		Types::ETreeType	type,
		Double_t &	effSerr
	)

virtual

overloaded function to create background efficiency (rejection) versus signal efficiency plot (first call of this function)
the function returns the signal efficiency at background efficiency indicated in theString

"theString" must have two entries:

[1]: the value of background efficiency at which the signal efficiency is to be returned

Reimplemented from TMVA::MethodBase.

Definition at line 1538 of file MethodCuts.cxx.

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

private

compute signal and background efficiencies from PDFs for given cut sample

Definition at line 1008 of file MethodCuts.cxx.

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

private

compute signal and background efficiencies from event counting for given cut sample

Definition at line 1035 of file MethodCuts.cxx.

void TMVA::MethodCuts::GetHelpMessage ( ) const

protectedvirtual

get help message text

typical length of text line: "|--------------------------------------------------------------|"

Implements TMVA::IMethod.

Definition at line 1702 of file MethodCuts.cxx.

Double_t TMVA::MethodCuts::GetmuTransform ( TTree * )

inline

Definition at line 119 of file MethodCuts.h.

Double_t TMVA::MethodCuts::GetMvaValue	(	Double_t *	err = `0`,
		Double_t *	errUpper = `0`
	)

virtual

cut evaluation: returns 1.0 if event passed, 0.0 otherwise

Implements TMVA::MethodBase.

Definition at line 432 of file MethodCuts.cxx.

Double_t TMVA::MethodCuts::GetRarity	(	Double_t	mvaVal,
		Types::ESBType	reftype
	)		const

inlinevirtual

compute rarity: R(x) = Integrate_[-oo..x] { PDF(x') dx' } where PDF(x) is the PDF of the classifier's signal or background distribution

Reimplemented from TMVA::MethodBase.

Definition at line 124 of file MethodCuts.h.

Double_t TMVA::MethodCuts::GetSeparation	(	TH1 *	histoS,
		TH1 *	histoB
	)		const

inlinevirtual

compute "separation" defined as <s2> = (1/2) Int_-oo..+oo { (S(x) - B(x))^2/(S(x) + B(x)) dx }

Reimplemented from TMVA::MethodBase.

Definition at line 116 of file MethodCuts.h.

Double_t TMVA::MethodCuts::GetSeparation	(	PDF *	pdfS = `0`,
		PDF *	pdfB = `0`
	)		const

inlinevirtual

compute "separation" defined as <s2> = (1/2) Int_-oo..+oo { (S(x) - B(x))^2/(S(x) + B(x)) dx }

Reimplemented from TMVA::MethodBase.

Definition at line 117 of file MethodCuts.h.

Double_t TMVA::MethodCuts::GetSignificance ( void ) const

inlinevirtual

compute significance of mean difference significance = |<S> - |/Sqrt(RMS_S2 + RMS_B2)

Reimplemented from TMVA::MethodBase.

Definition at line 118 of file MethodCuts.h.

Double_t TMVA::MethodCuts::GetTrainingEfficiency ( const TString & theString )

virtual

overloaded function to create background efficiency (rejection) versus signal efficiency plot (first call of this function)
the function returns the signal efficiency at background efficiency indicated in theString

"theString" must have two entries:

[1]: the value of background efficiency at which the signal efficiency is to be returned

Reimplemented from TMVA::MethodBase.

Definition at line 1426 of file MethodCuts.cxx.

Bool_t TMVA::MethodCuts::HasAnalysisType	(	Types::EAnalysisType	type,
		UInt_t	numberClasses,
		UInt_t	numberTargets
	)

virtual

Cuts can only handle classification with 2 classes.

Implements TMVA::IMethod.

Definition at line 213 of file MethodCuts.cxx.

void TMVA::MethodCuts::Init ( void )

privatevirtual

default initialisation called by all constructors

Implements TMVA::MethodBase.

Definition at line 222 of file MethodCuts.cxx.

void TMVA::MethodCuts::MakeClassSpecific	(	std::ostream &	fout,
		const TString &	className
	)		const

protectedvirtual

write specific classifier response

Reimplemented from TMVA::MethodBase.

Definition at line 1690 of file MethodCuts.cxx.

void TMVA::MethodCuts::MatchCutsToPars	(	std::vector< Double_t > &	pars,
		Double_t *	cutMin,
		Double_t *	cutMax
	)

private

translates cuts into parameters

Definition at line 994 of file MethodCuts.cxx.

void TMVA::MethodCuts::MatchCutsToPars	(	std::vector< Double_t > &	pars,
		Double_t **	cutMinAll,
		Double_t **	cutMaxAll,
		Int_t	ibin
	)

private

translate the cuts into parameters (obsolete function)

Definition at line 972 of file MethodCuts.cxx.

void TMVA::MethodCuts::MatchParsToCuts	(	const std::vector< Double_t > &	pars,
		Double_t *	cutMin,
		Double_t *	cutMax
	)

private

translates parameters into cuts

Definition at line 959 of file MethodCuts.cxx.

void TMVA::MethodCuts::MatchParsToCuts	(	Double_t *	,
		Double_t *	,
		Double_t *
	)

private

void TMVA::MethodCuts::PrintCuts ( Double_t effS ) const

print cuts

Definition at line 465 of file MethodCuts.cxx.

void TMVA::MethodCuts::ProcessOptions ( )

virtual

process user options sanity check, do not allow the input variables to be normalised, because this only creates problems when interpreting the cuts

Implements TMVA::MethodBase.

Definition at line 363 of file MethodCuts.cxx.

void TMVA::MethodCuts::ReadWeightsFromStream ( std::istream & i )

virtual

read the cuts from stream

Implements TMVA::MethodBase.

Definition at line 1202 of file MethodCuts.cxx.

void TMVA::MethodCuts::ReadWeightsFromXML ( void * wghtnode )

virtual

read coefficients from xml weight file

Implements TMVA::MethodBase.

Definition at line 1312 of file MethodCuts.cxx.

void TMVA::MethodCuts::SetTestSignalEfficiency ( Double_t effS )

inline

Definition at line 132 of file MethodCuts.h.

Referenced by TMVA::Reader::EvaluateMVA().

void TMVA::MethodCuts::TestClassification ( )

virtual

nothing to test

Reimplemented from TMVA::MethodBase.

Definition at line 814 of file MethodCuts.cxx.

void TMVA::MethodCuts::Train ( void )

virtual

training method: here the cuts are optimised for the training sample

Implements TMVA::MethodBase.

Definition at line 578 of file MethodCuts.cxx.

void TMVA::MethodCuts::WriteMonitoringHistosToFile ( void ) const

virtual

write histograms and PDFs to file for monitoring purposes

Reimplemented from TMVA::MethodBase.

Definition at line 1396 of file MethodCuts.cxx.

Member Data Documentation

TString* TMVA::MethodCuts::fAllVarsI

private

Definition at line 204 of file MethodCuts.h.

BinarySearchTree* TMVA::MethodCuts::fBinaryTreeB

private

Definition at line 197 of file MethodCuts.h.

BinarySearchTree* TMVA::MethodCuts::fBinaryTreeS

private

Definition at line 196 of file MethodCuts.h.

Double_t** TMVA::MethodCuts::fCutMax

private

Definition at line 201 of file MethodCuts.h.

Double_t** TMVA::MethodCuts::fCutMin

private

Definition at line 200 of file MethodCuts.h.

std::vector<Interval*> TMVA::MethodCuts::fCutRange

private

Definition at line 193 of file MethodCuts.h.

Double_t* TMVA::MethodCuts::fCutRangeMax

private

Definition at line 192 of file MethodCuts.h.

Double_t* TMVA::MethodCuts::fCutRangeMin

private

Definition at line 191 of file MethodCuts.h.

TH1* TMVA::MethodCuts::fEffBvsSLocal

private

Definition at line 218 of file MethodCuts.h.

EEffMethod TMVA::MethodCuts::fEffMethod

private

Definition at line 186 of file MethodCuts.h.

TString TMVA::MethodCuts::fEffMethodS

private

Definition at line 185 of file MethodCuts.h.

Double_t TMVA::MethodCuts::fEffRef

private

Definition at line 208 of file MethodCuts.h.

Double_t TMVA::MethodCuts::fEffSMax

private

Definition at line 190 of file MethodCuts.h.

Double_t TMVA::MethodCuts::fEffSMin

private

Definition at line 189 of file MethodCuts.h.

EFitMethodType TMVA::MethodCuts::fFitMethod

private

Definition at line 184 of file MethodCuts.h.

TString TMVA::MethodCuts::fFitMethodS

private

Definition at line 183 of file MethodCuts.h.

std::vector<EFitParameters>* TMVA::MethodCuts::fFitParams

private

Definition at line 187 of file MethodCuts.h.

const Double_t TMVA::MethodCuts::fgMaxAbsCutVal

static

Definition at line 146 of file MethodCuts.h.

std::vector<Double_t>* TMVA::MethodCuts::fMeanB

private

Definition at line 214 of file MethodCuts.h.

std::vector<Double_t>* TMVA::MethodCuts::fMeanS

private

Definition at line 213 of file MethodCuts.h.

Bool_t TMVA::MethodCuts::fNegEffWarning

private

Definition at line 229 of file MethodCuts.h.

Int_t TMVA::MethodCuts::fNpar

private

Definition at line 207 of file MethodCuts.h.

TRandom* TMVA::MethodCuts::fRandom

private

Definition at line 210 of file MethodCuts.h.

std::vector<Int_t>* TMVA::MethodCuts::fRangeSign

private

Definition at line 209 of file MethodCuts.h.

std::vector<Double_t>* TMVA::MethodCuts::fRmsB

private

Definition at line 216 of file MethodCuts.h.

std::vector<Double_t>* TMVA::MethodCuts::fRmsS

private

Definition at line 215 of file MethodCuts.h.

Double_t TMVA::MethodCuts::fTestSignalEff

private

Definition at line 188 of file MethodCuts.h.

Referenced by SetTestSignalEfficiency().

Double_t* TMVA::MethodCuts::fTmpCutMax

private

Definition at line 203 of file MethodCuts.h.

Double_t* TMVA::MethodCuts::fTmpCutMin

private

Definition at line 202 of file MethodCuts.h.

std::vector<TH1*>* TMVA::MethodCuts::fVarHistB

private

Definition at line 222 of file MethodCuts.h.

std::vector<TH1*>* TMVA::MethodCuts::fVarHistB_smooth

private

Definition at line 224 of file MethodCuts.h.

std::vector<TH1*>* TMVA::MethodCuts::fVarHistS

private

Definition at line 221 of file MethodCuts.h.

std::vector<TH1*>* TMVA::MethodCuts::fVarHistS_smooth

private

Definition at line 223 of file MethodCuts.h.

std::vector<PDF*>* TMVA::MethodCuts::fVarPdfB

private

Definition at line 226 of file MethodCuts.h.

std::vector<PDF*>* TMVA::MethodCuts::fVarPdfS

private

Definition at line 225 of file MethodCuts.h.

The documentation for this class was generated from the following files:

tmva/tmva/inc/TMVA/MethodCuts.h
tmva/tmva/src/MethodCuts.cxx

Public Member Functions

Static Public Member Functions

Static Public Attributes

Protected Member Functions

Private Types

Private Member Functions

Private Attributes

Additional Inherited Members

Member Enumeration Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation