Definition at line 50 of file DataLoader.h.

Public Member Functions
	DataLoader (TString thedlName="default")

virtual	~DataLoader ()

void	AddBackgroundTestEvent (const std::vector< Double_t > &event, Double_t weight=1.0)
	add signal training event

void	AddBackgroundTrainingEvent (const std::vector< Double_t > &event, Double_t weight=1.0)
	add signal training event

void	AddBackgroundTree (TString datFileB, Double_t weight=1.0, Types::ETreeType treetype=Types::kMaxTreeType)
	add background tree from text file

void	AddBackgroundTree (TTree *background, Double_t weight, const TString &treetype)

void	AddBackgroundTree (TTree *background, Double_t weight=1.0, Types::ETreeType treetype=Types::kMaxTreeType)
	number of signal events (used to compute significance)

void	AddCut (const TCut &cut, const TString &className="")

void	AddCut (const TString &cut, const TString &className="")

DataSetInfo &	AddDataSet (const TString &)

DataSetInfo &	AddDataSet (DataSetInfo &)

void	AddEvent (const TString &className, Types::ETreeType tt, const std::vector< Double_t > &event, Double_t weight)
	add event vector event : the order of values is: variables + targets + spectators

void	AddRegressionTarget (const TString &expression, const TString &title="", const TString &unit="", Double_t min=0, Double_t max=0)

void	AddRegressionTree (TTree *tree, Double_t weight=1.0, Types::ETreeType treetype=Types::kMaxTreeType)

void	AddSignalTestEvent (const std::vector< Double_t > &event, Double_t weight=1.0)
	add signal testing event

void	AddSignalTrainingEvent (const std::vector< Double_t > &event, Double_t weight=1.0)
	add signal training event

void	AddSignalTree (TString datFileS, Double_t weight=1.0, Types::ETreeType treetype=Types::kMaxTreeType)
	add signal tree from text file

void	AddSignalTree (TTree *signal, Double_t weight, const TString &treetype)

void	AddSignalTree (TTree *signal, Double_t weight=1.0, Types::ETreeType treetype=Types::kMaxTreeType)
	number of signal events (used to compute significance)

void	AddSpectator (const TString &expression, const TString &title="", const TString &unit="", Double_t min=0, Double_t max=0)
	user inserts target in data set info

void	AddTarget (const TString &expression, const TString &title="", const TString &unit="", Double_t min=0, Double_t max=0)
	user inserts target in data set info

void	AddTestEvent (const TString &className, const std::vector< Double_t > &event, Double_t weight)
	add signal test event

void	AddTrainingEvent (const TString &className, const std::vector< Double_t > &event, Double_t weight)
	add signal training event

void	AddTree (TTree *tree, const TString &className, Double_t weight, const TCut &cut, const TString &treeType)
	number of signal events (used to compute significance)

void	AddTree (TTree *tree, const TString &className, Double_t weight=1.0, const TCut &cut="", Types::ETreeType tt=Types::kMaxTreeType)

void	AddVariable (const TString &expression, char type='F', Double_t min=0, Double_t max=0)
	user inserts discriminating variable in data set info

void	AddVariable (const TString &expression, const TString &title, const TString &unit, char type='F', Double_t min=0, Double_t max=0)
	user inserts discriminating variable in data set info

void	AddVariablesArray (const TString &expression, int size, char type='F', Double_t min=0, Double_t max=0)
	user inserts discriminating array of variables in data set info in case input tree provides an array of values

TTree *	CreateEventAssignTrees (const TString &name)
	create the data assignment tree (for event-wise data assignment by user)

DataInputHandler &	DataInput ()

TH2 *	GetCorrelationMatrix (const TString &className)
	returns the correlation matrix of datasets

DataSetInfo &	GetDataSetInfo ()

const DataSetInfo &	GetDefaultDataSetInfo ()

virtual TClass *	IsA () const

DataLoader *	MakeCopy (TString name)
	Copy method use in VI and CV.

void	MakeKFoldDataSet (CvSplit &s)
	Function required to split the training and testing datasets into a number of folds.

void	PrepareFoldDataSet (CvSplit &s, UInt_t foldNumber, Types::ETreeType tt=Types::kTraining)
	Function for assigning the correct folds to the testing or training set.

void	PrepareTrainingAndTestTree (const TCut &cut, const TString &splitOpt)
	prepare the training and test trees -> same cuts for signal and background

void	PrepareTrainingAndTestTree (const TCut &cut, Int_t NsigTrain, Int_t NbkgTrain, Int_t NsigTest, Int_t NbkgTest, const TString &otherOpt="SplitMode=Random:!V")
	prepare the training and test trees

void	PrepareTrainingAndTestTree (const TCut &cut, Int_t Ntrain, Int_t Ntest=-1)
	prepare the training and test trees kept for backward compatibility

void	PrepareTrainingAndTestTree (TCut sigcut, TCut bkgcut, const TString &splitOpt)
	prepare the training and test trees

void	RecombineKFoldDataSet (CvSplit &s, Types::ETreeType tt=Types::kTraining)
	Recombines the dataset.

void	SetBackgroundTree (TTree *background, Double_t weight=1.0)

void	SetBackgroundWeightExpression (const TString &variable)

void	SetCut (const TCut &cut, const TString &className="")

void	SetCut (const TString &cut, const TString &className="")

void	SetInputTrees (const TString &signalFileName, const TString &backgroundFileName, Double_t signalWeight=1.0, Double_t backgroundWeight=1.0)

void	SetInputTrees (TTree *inputTree, const TCut &SigCut, const TCut &BgCut)
	define the input trees for signal and background from single input tree, containing both signal and background events distinguished by the type identifiers: SigCut and BgCut

void	SetInputTrees (TTree signal, TTree background, Double_t signalWeight=1.0, Double_t backgroundWeight=1.0)
	define the input trees for signal and background; no cuts are applied

void	SetInputVariables (std::vector< TString > *theVariables)
	deprecated

void	SetSignalTree (TTree *signal, Double_t weight=1.0)

void	SetSignalWeightExpression (const TString &variable)

void	SetTree (TTree *tree, const TString &className, Double_t weight)
	deprecated

void	SetWeightExpression (const TString &variable, const TString &className="")

virtual void	Streamer (TBuffer &)
	Stream an object of class TObject.

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

Bool_t	UserAssignEvents (UInt_t clIndex)

DataLoader *	VarTransform (TString trafoDefinition)
	Transforms the variables and return a new DataLoader with the transformed variables.

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

virtual	~Configurable ()
	default destructor

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

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

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

template<class T >
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)

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

const char *	GetConfigDescription () const

const char *	GetConfigName () const

const TString &	GetOptions () const

MsgLogger &	Log () const

virtual void	ParseOptions ()
	options parser

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

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

void	ReadOptionsFromXML (void *node)

void	SetConfigDescription (const char *d)

void	SetConfigName (const char *n)

void	SetMsgType (EMsgType t)

void	SetOptions (const TString &s)

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

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

Public Member Functions inherited from TNamed
	TNamed ()

	TNamed (const char name, const char title)

	TNamed (const TNamed &named)
	TNamed copy ctor.

	TNamed (const TString &name, const TString &title)

virtual	~TNamed ()
	TNamed destructor.

void	Clear (Option_t *option="") override
	Set name and title to empty strings ("").

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

Int_t	Compare (const TObject *obj) const override
	Compare two TNamed objects.

void	Copy (TObject &named) const override
	Copy this to obj.

virtual void	FillBuffer (char *&buffer)
	Encode TNamed into output buffer.

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

const char *	GetTitle () const override
	Returns title of object.

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

TClass *	IsA () const override

Bool_t	IsSortable () const override

void	ls (Option_t *option="") const override
	List TNamed name and title.

TNamed &	operator= (const TNamed &rhs)
	TNamed assignment operator.

void	Print (Option_t *option="") const override
	Print TNamed name and title.

virtual void	SetName (const char *name)
	Set the name of the TNamed.

virtual void	SetNameTitle (const char name, const char title)
	Set all the TNamed parameters (name and title).

virtual void	SetTitle (const char *title="")
	Set the title of the TNamed.

virtual Int_t	Sizeof () const
	Return size of the TNamed part of the TObject.

void	Streamer (TBuffer &) override
	Stream an object of class TObject.

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

Public Member Functions inherited from TObject
	TObject ()
	TObject constructor.

	TObject (const TObject &object)
	TObject copy ctor.

virtual	~TObject ()
	TObject destructor.

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

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

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

ULong_t	CheckedHash ()
	Check and record whether this class has a consistent Hash/RecursiveRemove setup (*) and then return the regular Hash value for this object.

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

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

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

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

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

virtual TObject *	DrawClone (Option_t *option="") const
	Draw a clone of this object in the current selected pad with: `gROOT->SetSelectedPad(c1)`.

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

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

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

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

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

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

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

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

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

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

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

virtual Option_t *	GetOption () const

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

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

Bool_t	HasInconsistentHash () const
	Return true is the type of this object is known to have an inconsistent setup for Hash and RecursiveRemove (i.e.

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

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

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

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

void	InvertBit (UInt_t f)

Bool_t	IsDestructed () const
	IsDestructed.

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

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

R__ALWAYS_INLINE Bool_t	IsOnHeap () const

R__ALWAYS_INLINE Bool_t	IsZombie () const

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).

virtual Bool_t	Notify ()
	This method must be overridden to handle object notification (the base implementation is no-op).

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

void	operator delete (void *ptr)
	Operator delete.

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

void *	operator new (size_t sz)

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

void *	operator new[] (size_t sz)

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

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

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

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

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

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

void	ResetBit (UInt_t f)

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

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

void	SetBit (UInt_t f)

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

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

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

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

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

R__ALWAYS_INLINE Bool_t	TestBit (UInt_t f) const

Int_t	TestBits (UInt_t f) const

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

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

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

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

Static Public Member Functions
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

Static Public Member Functions inherited from TMVA::Configurable
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

Static Public Member Functions inherited from TNamed
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

Static Public Member Functions inherited from TObject
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

static Longptr_t	GetDtorOnly ()
	Return destructor only flag.

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

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

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

Private Types
enum	DataAssignType { kUndefined = 0 , kAssignTrees , kAssignEvents }

Private Member Functions
DataSetInfo &	DefaultDataSetInfo ()
	default creation

void	SetInputTreesFromEventAssignTrees ()
	assign event-wise local trees to data set

Private Attributes
Types::EAnalysisType	fAnalysisType
	the training type

std::vector< Float_t >	fATreeEvent
	event variables

Int_t	fATreeType = 0
	type of event (=classIndex)

Float_t	fATreeWeight = 0.0
	weight of the event

DataAssignType	fDataAssignType
	flags for data assigning

DataInputHandler *	fDataInputHandler
	->

DataSetManager *	fDataSetManager

std::vector< TMVA::VariableTransformBase * >	fDefaultTrfs
	list of transformations on default DataSet

TString	fOptions
	option string given by construction (presently only "V")

std::vector< TTree * >	fTestAssignTree
	for each class: tmp tree if user wants to assign the events directly

std::vector< TTree * >	fTrainAssignTree
	for each class: tmp tree if user wants to assign the events directly

TString	fTransformations
	List of transformations to test.

Bool_t	fVerbose
	verbose mode

Friends
void	DataLoaderCopy (TMVA::DataLoader des, TMVA::DataLoader src)

Additional Inherited Members
Public Types inherited from TObject
enum	{ kIsOnHeap = 0x01000000 , kNotDeleted = 0x02000000 , kZombie = 0x04000000 , kInconsistent = 0x08000000 , kBitMask = 0x00ffffff }

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

enum	EDeprecatedStatusBits { kObjInCanvas = (1ULL << ( 3 )) }

enum	EStatusBits { kCanDelete = (1ULL << ( 0 )) , kMustCleanup = (1ULL << ( 3 )) , kIsReferenced = (1ULL << ( 4 )) , kHasUUID = (1ULL << ( 5 )) , kCannotPick = (1ULL << ( 6 )) , kNoContextMenu = (1ULL << ( 8 )) , kInvalidObject = (1ULL << ( 13 )) }

Protected Types inherited from TObject
enum	{ kOnlyPrepStep = (1ULL << ( 3 )) }

Protected Member Functions inherited from TMVA::Configurable
void	EnableLooseOptions (Bool_t b=kTRUE)

const TString &	GetReferenceFile () const

Bool_t	LooseOptionCheckingEnabled () const

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

void	WriteOptionsReferenceToFile ()
	write complete options to output stream

Protected Member Functions inherited from TObject
virtual void	DoError (int level, const char location, const char fmt, va_list va) const
	Interface to ErrorHandler (protected).

void	MakeZombie ()

Protected Attributes inherited from TMVA::Configurable
MsgLogger *	fLogger
	! message logger

Protected Attributes inherited from TNamed
TString	fName

TString	fTitle

#include <TMVA/DataLoader.h>

Inheritance diagram for TMVA::DataLoader:

[legend]

Member Enumeration Documentation

◆ DataAssignType

enum TMVA::DataLoader::DataAssignType

private

Enumerator
kUndefined
kAssignTrees
kAssignEvents

Definition at line 199 of file DataLoader.h.

Constructor & Destructor Documentation

◆ DataLoader()

TMVA::DataLoader::DataLoader ( TString thedlName = "default" )

Definition at line 80 of file DataLoader.cxx.

◆ ~DataLoader()

TMVA::DataLoader::~DataLoader ( void )

virtual

Definition at line 96 of file DataLoader.cxx.

Member Function Documentation

◆ AddBackgroundTestEvent()

void TMVA::DataLoader::AddBackgroundTestEvent	(	const std::vector< Double_t > &	event,
		Double_t	weight = `1.0`
	)

add signal training event

Definition at line 252 of file DataLoader.cxx.

◆ AddBackgroundTrainingEvent()

void TMVA::DataLoader::AddBackgroundTrainingEvent	(	const std::vector< Double_t > &	event,
		Double_t	weight = `1.0`
	)

add signal training event

Definition at line 244 of file DataLoader.cxx.

◆ AddBackgroundTree() [1/3]

void TMVA::DataLoader::AddBackgroundTree	(	TString	datFileB,
		Double_t	weight = `1.0`,
		Types::ETreeType	treetype = `Types::kMaxTreeType`
	)

add background tree from text file

Definition at line 410 of file DataLoader.cxx.

◆ AddBackgroundTree() [2/3]

void TMVA::DataLoader::AddBackgroundTree	(	TTree *	background,
		Double_t	weight,
		const TString &	treetype
	)

Definition at line 425 of file DataLoader.cxx.

◆ AddBackgroundTree() [3/3]

void TMVA::DataLoader::AddBackgroundTree	(	TTree *	background,
		Double_t	weight = `1.0`,
		Types::ETreeType	treetype = `Types::kMaxTreeType`
	)

number of signal events (used to compute significance)

Definition at line 402 of file DataLoader.cxx.

◆ AddCut() [1/2]

void TMVA::DataLoader::AddCut	(	const TCut &	cut,
		const TString &	className = `""`
	)

Definition at line 594 of file DataLoader.cxx.

◆ AddCut() [2/2]

void TMVA::DataLoader::AddCut	(	const TString &	cut,
		const TString &	className = `""`
	)

Definition at line 588 of file DataLoader.cxx.

◆ AddDataSet() [1/2]

TMVA::DataSetInfo & TMVA::DataLoader::AddDataSet ( const TString & dsiName )

Definition at line 126 of file DataLoader.cxx.

◆ AddDataSet() [2/2]

TMVA::DataSetInfo & TMVA::DataLoader::AddDataSet ( DataSetInfo & dsi )

Definition at line 119 of file DataLoader.cxx.

◆ AddEvent()

void TMVA::DataLoader::AddEvent	(	const TString &	className,
		Types::ETreeType	tt,
		const std::vector< Double_t > &	event,
		Double_t	weight
	)

add event vector event : the order of values is: variables + targets + spectators

Definition at line 277 of file DataLoader.cxx.

◆ AddRegressionTarget()

void TMVA::DataLoader::AddRegressionTarget	(	const TString &	expression,
		const TString &	title = `""`,
		const TString &	unit = `""`,
		Double_t	min = `0`,
		Double_t	max = `0`
	)

inline

Definition at line 132 of file DataLoader.h.

◆ AddRegressionTree()

void TMVA::DataLoader::AddRegressionTree	(	TTree *	tree,
		Double_t	weight = `1.0`,
		Types::ETreeType	treetype = `Types::kMaxTreeType`
	)

inline

Definition at line 103 of file DataLoader.h.

◆ AddSignalTestEvent()

void TMVA::DataLoader::AddSignalTestEvent	(	const std::vector< Double_t > &	event,
		Double_t	weight = `1.0`
	)

add signal testing event

Definition at line 236 of file DataLoader.cxx.

◆ AddSignalTrainingEvent()

void TMVA::DataLoader::AddSignalTrainingEvent	(	const std::vector< Double_t > &	event,
		Double_t	weight = `1.0`
	)

add signal training event

Definition at line 228 of file DataLoader.cxx.

◆ AddSignalTree() [1/3]

void TMVA::DataLoader::AddSignalTree	(	TString	datFileS,
		Double_t	weight = `1.0`,
		Types::ETreeType	treetype = `Types::kMaxTreeType`
	)

add signal tree from text file

Definition at line 379 of file DataLoader.cxx.

◆ AddSignalTree() [2/3]

void TMVA::DataLoader::AddSignalTree	(	TTree *	signal,
		Double_t	weight,
		const TString &	treetype
	)

Definition at line 394 of file DataLoader.cxx.

◆ AddSignalTree() [3/3]

void TMVA::DataLoader::AddSignalTree	(	TTree *	signal,
		Double_t	weight = `1.0`,
		Types::ETreeType	treetype = `Types::kMaxTreeType`
	)

number of signal events (used to compute significance)

Definition at line 371 of file DataLoader.cxx.

◆ AddSpectator()

void TMVA::DataLoader::AddSpectator	(	const TString &	expression,
		const TString &	title = `""`,
		const TString &	unit = `""`,
		Double_t	min = `0`,
		Double_t	max = `0`
	)

user inserts target in data set info

Definition at line 524 of file DataLoader.cxx.

◆ AddTarget()

void TMVA::DataLoader::AddTarget	(	const TString &	expression,
		const TString &	title = `""`,
		const TString &	unit = `""`,
		Double_t	min = `0`,
		Double_t	max = `0`
	)

user inserts target in data set info

Definition at line 512 of file DataLoader.cxx.

◆ AddTestEvent()

void TMVA::DataLoader::AddTestEvent	(	const TString &	className,
		const std::vector< Double_t > &	event,
		Double_t	weight
	)

add signal test event

Definition at line 268 of file DataLoader.cxx.

◆ AddTrainingEvent()

void TMVA::DataLoader::AddTrainingEvent	(	const TString &	className,
		const std::vector< Double_t > &	event,
		Double_t	weight
	)

add signal training event

Definition at line 260 of file DataLoader.cxx.

◆ AddTree() [1/2]

void TMVA::DataLoader::AddTree	(	TTree *	tree,
		const TString &	className,
		Double_t	weight,
		const TCut &	cut,
		const TString &	treeType
	)

number of signal events (used to compute significance)

Definition at line 334 of file DataLoader.cxx.

◆ AddTree() [2/2]

void TMVA::DataLoader::AddTree	(	TTree *	tree,
		const TString &	className,
		Double_t	weight = `1.0`,
		const TCut &	cut = `""`,
		Types::ETreeType	tt = `Types::kMaxTreeType`
	)

Definition at line 351 of file DataLoader.cxx.

◆ AddVariable() [1/2]

void TMVA::DataLoader::AddVariable	(	const TString &	expression,
		char	type = `'F'`,
		Double_t	min = `0`,
		Double_t	max = `0`
	)

user inserts discriminating variable in data set info

Definition at line 494 of file DataLoader.cxx.

◆ AddVariable() [2/2]

void TMVA::DataLoader::AddVariable	(	const TString &	expression,
		const TString &	title,
		const TString &	unit,
		char	type = `'F'`,
		Double_t	min = `0`,
		Double_t	max = `0`
	)

user inserts discriminating variable in data set info

Definition at line 485 of file DataLoader.cxx.

◆ AddVariablesArray()

void TMVA::DataLoader::AddVariablesArray	(	const TString &	expression,
		int	size,
		char	type = `'F'`,
		Double_t	min = `0`,
		Double_t	max = `0`
	)

user inserts discriminating array of variables in data set info in case input tree provides an array of values

Definition at line 504 of file DataLoader.cxx.

◆ Class()

static TClass * TMVA::DataLoader::Class ( )

static

Returns: TClass describing this class

◆ Class_Name()

static const char * TMVA::DataLoader::Class_Name ( )

static

Returns: Name of this class

◆ Class_Version()

static constexpr Version_t TMVA::DataLoader::Class_Version ( )

inlinestaticconstexpr

Returns: Version of this class

Definition at line 214 of file DataLoader.h.

◆ CreateEventAssignTrees()

TTree * TMVA::DataLoader::CreateEventAssignTrees ( const TString & name )

create the data assignment tree (for event-wise data assignment by user)

Definition at line 195 of file DataLoader.cxx.

◆ DataInput()

DataInputHandler & TMVA::DataLoader::DataInput ( )

inline

Definition at line 172 of file DataLoader.h.

◆ DeclFileName()

static const char * TMVA::DataLoader::DeclFileName ( )

inlinestatic

Returns: Name of the file containing the class declaration

Definition at line 214 of file DataLoader.h.

◆ DefaultDataSetInfo()

TMVA::DataSetInfo & TMVA::DataLoader::DefaultDataSetInfo ( )

private

default creation

Definition at line 533 of file DataLoader.cxx.

◆ GetCorrelationMatrix()

TH2 * TMVA::DataLoader::GetCorrelationMatrix ( const TString & className )

returns the correlation matrix of datasets

Definition at line 717 of file DataLoader.cxx.

◆ GetDataSetInfo()

TMVA::DataSetInfo & TMVA::DataLoader::GetDataSetInfo ( )

Definition at line 137 of file DataLoader.cxx.

◆ GetDefaultDataSetInfo()

const DataSetInfo & TMVA::DataLoader::GetDefaultDataSetInfo ( )

inline

Definition at line 165 of file DataLoader.h.

◆ IsA()

virtual TClass * TMVA::DataLoader::IsA ( ) const

inlinevirtual

Returns: TClass describing current object

Reimplemented from TMVA::Configurable.

Definition at line 214 of file DataLoader.h.

◆ MakeCopy()

TMVA::DataLoader * TMVA::DataLoader::MakeCopy ( TString name )

Copy method use in VI and CV.

Definition at line 691 of file DataLoader.cxx.

◆ MakeKFoldDataSet()

void TMVA::DataLoader::MakeKFoldDataSet ( CvSplit & s )

Function required to split the training and testing datasets into a number of folds.

Required by the CrossValidation and HyperParameterOptimisation classes. The option to split the training dataset into a training set and a validation set is implemented but not currently used.

Definition at line 662 of file DataLoader.cxx.

◆ PrepareFoldDataSet()

void TMVA::DataLoader::PrepareFoldDataSet	(	CvSplit &	s,
		UInt_t	foldNumber,
		Types::ETreeType	tt = `Types::kTraining`
	)

Function for assigning the correct folds to the testing or training set.

Definition at line 670 of file DataLoader.cxx.

◆ PrepareTrainingAndTestTree() [1/4]

void TMVA::DataLoader::PrepareTrainingAndTestTree	(	const TCut &	cut,
		const TString &	splitOpt
	)

prepare the training and test trees -> same cuts for signal and background

Definition at line 632 of file DataLoader.cxx.

◆ PrepareTrainingAndTestTree() [2/4]

void TMVA::DataLoader::PrepareTrainingAndTestTree	(	const TCut &	cut,
		Int_t	NsigTrain,
		Int_t	NbkgTrain,
		Int_t	NsigTest,
		Int_t	NbkgTest,
		const TString &	otherOpt = `"SplitMode=Random:!V"`
	)

prepare the training and test trees

Definition at line 602 of file DataLoader.cxx.

◆ PrepareTrainingAndTestTree() [3/4]

void TMVA::DataLoader::PrepareTrainingAndTestTree	(	const TCut &	cut,
		Int_t	Ntrain,
		Int_t	Ntest = `-1`
	)

prepare the training and test trees kept for backward compatibility

Definition at line 618 of file DataLoader.cxx.

◆ PrepareTrainingAndTestTree() [4/4]

void TMVA::DataLoader::PrepareTrainingAndTestTree	(	TCut	sigcut,
		TCut	bkgcut,
		const TString &	splitOpt
	)

prepare the training and test trees

Definition at line 644 of file DataLoader.cxx.

◆ RecombineKFoldDataSet()

void TMVA::DataLoader::RecombineKFoldDataSet	(	CvSplit &	s,
		Types::ETreeType	tt = `Types::kTraining`
	)

Recombines the dataset.

The precise semantics depend on the actual split.

Similar to the inverse operation of MakeKFoldDataSet but will differ. See documentation for each particular split for more information.

Definition at line 683 of file DataLoader.cxx.

◆ SetBackgroundTree()

void TMVA::DataLoader::SetBackgroundTree	(	TTree *	background,
		Double_t	weight = `1.0`
	)

Definition at line 439 of file DataLoader.cxx.

◆ SetBackgroundWeightExpression()

void TMVA::DataLoader::SetBackgroundWeightExpression ( const TString & variable )

Definition at line 556 of file DataLoader.cxx.

◆ SetCut() [1/2]

void TMVA::DataLoader::SetCut	(	const TCut &	cut,
		const TString &	className = `""`
	)

Definition at line 581 of file DataLoader.cxx.

◆ SetCut() [2/2]

void TMVA::DataLoader::SetCut	(	const TString &	cut,
		const TString &	className = `""`
	)

Definition at line 575 of file DataLoader.cxx.

◆ SetInputTrees() [1/3]

void TMVA::DataLoader::SetInputTrees	(	const TString &	signalFileName,
		const TString &	backgroundFileName,
		Double_t	signalWeight = `1.0`,
		Double_t	backgroundWeight = `1.0`
	)

Definition at line 464 of file DataLoader.cxx.

◆ SetInputTrees() [2/3]

void TMVA::DataLoader::SetInputTrees	(	TTree *	inputTree,
		const TCut &	SigCut,
		const TCut &	BgCut
	)

define the input trees for signal and background from single input tree, containing both signal and background events distinguished by the type identifiers: SigCut and BgCut

Definition at line 476 of file DataLoader.cxx.

◆ SetInputTrees() [3/3]

void TMVA::DataLoader::SetInputTrees	(	TTree *	signal,
		TTree *	background,
		Double_t	signalWeight = `1.0`,
		Double_t	backgroundWeight = `1.0`
	)

define the input trees for signal and background; no cuts are applied

Definition at line 455 of file DataLoader.cxx.

◆ SetInputTreesFromEventAssignTrees()

void TMVA::DataLoader::SetInputTreesFromEventAssignTrees ( )

private

assign event-wise local trees to data set

Definition at line 319 of file DataLoader.cxx.

◆ SetInputVariables()

void TMVA::DataLoader::SetInputVariables ( std::vector< TString > * theVariables )

deprecated

fill input variables in data set

Definition at line 541 of file DataLoader.cxx.

◆ SetSignalTree()

void TMVA::DataLoader::SetSignalTree	(	TTree *	signal,
		Double_t	weight = `1.0`
	)

Definition at line 432 of file DataLoader.cxx.

◆ SetSignalWeightExpression()

void TMVA::DataLoader::SetSignalWeightExpression ( const TString & variable )

Definition at line 549 of file DataLoader.cxx.

◆ SetTree()

void TMVA::DataLoader::SetTree	(	TTree *	tree,
		const TString &	className,
		Double_t	weight
	)

deprecated

set background tree

Definition at line 447 of file DataLoader.cxx.

◆ SetWeightExpression()

void TMVA::DataLoader::SetWeightExpression	(	const TString &	variable,
		const TString &	className = `""`
	)

Definition at line 563 of file DataLoader.cxx.

◆ Streamer()

virtual void TMVA::DataLoader::Streamer ( TBuffer & R__b )

virtual

Stream an object of class TObject.

Reimplemented from TMVA::Configurable.

◆ StreamerNVirtual()

void TMVA::DataLoader::StreamerNVirtual ( TBuffer & ClassDef_StreamerNVirtual_b )

inline

Definition at line 214 of file DataLoader.h.

◆ UserAssignEvents()

Bool_t TMVA::DataLoader::UserAssignEvents ( UInt_t clIndex )

Definition at line 311 of file DataLoader.cxx.

◆ VarTransform()

TMVA::DataLoader * TMVA::DataLoader::VarTransform ( TString trafoDefinition )

Transforms the variables and return a new DataLoader with the transformed variables.

Definition at line 146 of file DataLoader.cxx.

Friends And Related Symbol Documentation

◆ DataLoaderCopy

void DataLoaderCopy	(	TMVA::DataLoader *	des,
		TMVA::DataLoader *	src
	)

friend

Member Data Documentation

◆ fAnalysisType

Types::EAnalysisType TMVA::DataLoader::fAnalysisType

private

the training type

Definition at line 210 of file DataLoader.h.

◆ fATreeEvent

std::vector<Float_t> TMVA::DataLoader::fATreeEvent

private

event variables

Definition at line 208 of file DataLoader.h.

◆ fATreeType

Int_t TMVA::DataLoader::fATreeType = 0

private

type of event (=classIndex)

Definition at line 206 of file DataLoader.h.

◆ fATreeWeight

Float_t TMVA::DataLoader::fATreeWeight = 0.0

private

weight of the event

Definition at line 207 of file DataLoader.h.

◆ fDataAssignType

DataAssignType TMVA::DataLoader::fDataAssignType

private

flags for data assigning

Definition at line 202 of file DataLoader.h.

◆ fDataInputHandler

DataInputHandler* TMVA::DataLoader::fDataInputHandler

private

->

Definition at line 189 of file DataLoader.h.

◆ fDataSetManager

DataSetManager* TMVA::DataLoader::fDataSetManager

private

Definition at line 186 of file DataLoader.h.

◆ fDefaultTrfs

std::vector<TMVA::VariableTransformBase*> TMVA::DataLoader::fDefaultTrfs

private

list of transformations on default DataSet

Definition at line 191 of file DataLoader.h.

◆ fOptions

TString TMVA::DataLoader::fOptions

private

option string given by construction (presently only "V")

Definition at line 194 of file DataLoader.h.

◆ fTestAssignTree

std::vector<TTree*> TMVA::DataLoader::fTestAssignTree

private

for each class: tmp tree if user wants to assign the events directly

Definition at line 204 of file DataLoader.h.

◆ fTrainAssignTree

std::vector<TTree*> TMVA::DataLoader::fTrainAssignTree

private

for each class: tmp tree if user wants to assign the events directly

Definition at line 203 of file DataLoader.h.

◆ fTransformations

TString TMVA::DataLoader::fTransformations

private

List of transformations to test.

Definition at line 195 of file DataLoader.h.

◆ fVerbose

Bool_t TMVA::DataLoader::fVerbose

private

verbose mode

Definition at line 196 of file DataLoader.h.

Libraries for TMVA::DataLoader:

[legend]

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

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

Public Member Functions

Static Public Member Functions

Private Types

Private Member Functions

Private Attributes

Friends

Additional Inherited Members

Member Enumeration Documentation

◆ DataAssignType

Constructor & Destructor Documentation

◆ DataLoader()

◆ ~DataLoader()

Member Function Documentation

◆ AddBackgroundTestEvent()

◆ AddBackgroundTrainingEvent()

◆ AddBackgroundTree() [1/3]

◆ AddBackgroundTree() [2/3]

◆ AddBackgroundTree() [3/3]

◆ AddCut() [1/2]

◆ AddCut() [2/2]

◆ AddDataSet() [1/2]

◆ AddDataSet() [2/2]

◆ AddEvent()

◆ AddRegressionTarget()

◆ AddRegressionTree()

◆ AddSignalTestEvent()

◆ AddSignalTrainingEvent()

◆ AddSignalTree() [1/3]

◆ AddSignalTree() [2/3]

◆ AddSignalTree() [3/3]

◆ AddSpectator()

◆ AddTarget()

◆ AddTestEvent()

◆ AddTrainingEvent()

◆ AddTree() [1/2]

◆ AddTree() [2/2]

◆ AddVariable() [1/2]

◆ AddVariable() [2/2]

◆ AddVariablesArray()

◆ Class()

◆ Class_Name()

◆ Class_Version()

◆ CreateEventAssignTrees()

◆ DataInput()

◆ DeclFileName()

◆ DefaultDataSetInfo()

◆ GetCorrelationMatrix()

◆ GetDataSetInfo()

◆ GetDefaultDataSetInfo()

◆ IsA()

◆ MakeCopy()

◆ MakeKFoldDataSet()

◆ PrepareFoldDataSet()

◆ PrepareTrainingAndTestTree() [1/4]

◆ PrepareTrainingAndTestTree() [2/4]

◆ PrepareTrainingAndTestTree() [3/4]

◆ PrepareTrainingAndTestTree() [4/4]

◆ RecombineKFoldDataSet()

◆ SetBackgroundTree()

◆ SetBackgroundWeightExpression()

◆ SetCut() [1/2]

◆ SetCut() [2/2]

◆ SetInputTrees() [1/3]

◆ SetInputTrees() [2/3]

◆ SetInputTrees() [3/3]

◆ SetInputTreesFromEventAssignTrees()

◆ SetInputVariables()

◆ SetSignalTree()

◆ SetSignalWeightExpression()

◆ SetTree()

◆ SetWeightExpression()

◆ Streamer()

◆ StreamerNVirtual()

◆ UserAssignEvents()

◆ VarTransform()

Friends And Related Symbol Documentation

◆ DataLoaderCopy

Member Data Documentation

◆ fAnalysisType

◆ fATreeEvent