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 ()

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)
	fill input variables in data set

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

void	SetSignalWeightExpression (const TString &variable)

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

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

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	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.

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

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

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

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

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

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

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

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

virtual Bool_t	IsSortable () const

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

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

virtual void	Print (Option_t *option="") const
	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.

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 for instance with: `gROOT->SetSelectedPad(gPad)`.

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=0)
	Execute method on this object with the given parameter string, e.g.

virtual void	Execute (TMethod method, TObjArray params, Int_t *error=0)
	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)

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.

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.

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=0, Int_t option=0, Int_t bufsize=0)
	Write this object to the current directory.

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

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

std::vector< Float_t >	fATreeEvent

Int_t	fATreeType = 0

Float_t	fATreeWeight = 0.0

DataAssignType	fDataAssignType

DataInputHandler *	fDataInputHandler

DataSetManager *	fDataSetManager

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

TString	fOptions

std::vector< TTree * >	fTestAssignTree

std::vector< TTree * >	fTrainAssignTree

TString	fTransformations

Bool_t	fVerbose

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 = BIT(0) , kOverwrite = BIT(1) , kWriteDelete = BIT(2) }

enum	EDeprecatedStatusBits { kObjInCanvas = BIT(3) }

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

Static Public Member Functions inherited from TObject
static Long_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.

Protected Types inherited from TObject
enum	{ kOnlyPrepStep = BIT(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

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 251 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 243 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 409 of file DataLoader.cxx.

◆ AddBackgroundTree() [2/3]

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

Definition at line 424 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 401 of file DataLoader.cxx.

◆ AddCut() [1/2]

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

Definition at line 593 of file DataLoader.cxx.

◆ AddCut() [2/2]

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

Definition at line 587 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 276 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 235 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 227 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 378 of file DataLoader.cxx.

◆ AddSignalTree() [2/3]

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

Definition at line 393 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 370 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 523 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 511 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 267 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 259 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 333 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 350 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 493 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 484 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 503 of file DataLoader.cxx.

◆ CreateEventAssignTrees()

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

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

Definition at line 194 of file DataLoader.cxx.

◆ DataInput()

DataInputHandler & TMVA::DataLoader::DataInput ( )

inline

Definition at line 172 of file DataLoader.h.

◆ DefaultDataSetInfo()

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

private

default creation

Definition at line 532 of file DataLoader.cxx.

◆ GetCorrelationMatrix()

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

returns the correlation matrix of datasets

Definition at line 716 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.

◆ MakeCopy()

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

Copy method use in VI and CV.

Definition at line 690 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 661 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 669 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 631 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 601 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 617 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 643 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 682 of file DataLoader.cxx.

◆ SetBackgroundTree()

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

Definition at line 438 of file DataLoader.cxx.

◆ SetBackgroundWeightExpression()

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

Definition at line 555 of file DataLoader.cxx.

◆ SetCut() [1/2]

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

Definition at line 580 of file DataLoader.cxx.

◆ SetCut() [2/2]

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

Definition at line 574 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 463 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 475 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 454 of file DataLoader.cxx.

◆ SetInputTreesFromEventAssignTrees()

void TMVA::DataLoader::SetInputTreesFromEventAssignTrees ( )

private

assign event-wise local trees to data set

Definition at line 318 of file DataLoader.cxx.

◆ SetInputVariables()

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

fill input variables in data set

Definition at line 540 of file DataLoader.cxx.

◆ SetSignalTree()

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

Definition at line 431 of file DataLoader.cxx.

◆ SetSignalWeightExpression()

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

Definition at line 548 of file DataLoader.cxx.

◆ SetTree()

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

set background tree

Definition at line 446 of file DataLoader.cxx.

◆ SetWeightExpression()

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

Definition at line 562 of file DataLoader.cxx.

◆ UserAssignEvents()

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

Definition at line 310 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

Definition at line 210 of file DataLoader.h.

◆ fATreeEvent

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

private

Definition at line 208 of file DataLoader.h.

◆ fATreeType

Int_t TMVA::DataLoader::fATreeType = 0

private

Definition at line 206 of file DataLoader.h.

◆ fATreeWeight

Float_t TMVA::DataLoader::fATreeWeight = 0.0

private

Definition at line 207 of file DataLoader.h.

◆ fDataAssignType

DataAssignType TMVA::DataLoader::fDataAssignType

private

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

Definition at line 191 of file DataLoader.h.

◆ fOptions

TString TMVA::DataLoader::fOptions

private

Definition at line 194 of file DataLoader.h.

◆ fTestAssignTree

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

private

Definition at line 204 of file DataLoader.h.

◆ fTrainAssignTree

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

private

Definition at line 203 of file DataLoader.h.

◆ fTransformations

TString TMVA::DataLoader::fTransformations

private

Definition at line 195 of file DataLoader.h.

◆ fVerbose

Bool_t TMVA::DataLoader::fVerbose

private

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

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()

◆ CreateEventAssignTrees()

◆ DataInput()

◆ DefaultDataSetInfo()

◆ GetCorrelationMatrix()

◆ GetDataSetInfo()

◆ GetDefaultDataSetInfo()

◆ 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()

◆ UserAssignEvents()

◆ VarTransform()

Friends And Related Symbol Documentation

◆ DataLoaderCopy

Member Data Documentation

◆ fAnalysisType

◆ fATreeEvent

◆ fATreeType

◆ fATreeWeight

◆ fDataAssignType

◆ fDataInputHandler

◆ fDataSetManager

◆ fDefaultTrfs

◆ fOptions

◆ fTestAssignTree