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TMVA::DataLoader Class Reference

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="")
 
DataSetInfoAddDataSet (const TString &)
 
DataSetInfoAddDataSet (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
 
TTreeCreateEventAssignTrees (const TString &name)
 create the data assignment tree (for event-wise data assignment by user)
 
DataInputHandlerDataInput ()
 
TH2GetCorrelationMatrix (const TString &className)
 returns the correlation matrix of datasets
 
DataSetInfoGetDataSetInfo ()
 
const DataSetInfoGetDefaultDataSetInfo ()
 
DataLoaderMakeCopy (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)
 
DataLoaderVarTransform (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::OptionBaseDeclareOptionRef (T &ref, const TString &name, const TString &desc)
 
template<class T >
OptionBaseDeclareOptionRef (T &ref, const TString &name, const TString &desc="")
 
template<class T >
TMVA::OptionBaseDeclareOptionRef (T *&ref, Int_t size, const TString &name, const TString &desc)
 
template<class T >
OptionBaseDeclareOptionRef (T *&ref, Int_t size, const TString &name, const TString &desc="")
 
const char * GetConfigDescription () const
 
const char * GetConfigName () const
 
const TStringGetOptions () const
 
MsgLoggerLog () 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 TObjectClone (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.
 
TNamedoperator= (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 TObjectDrawClone (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 TObjectFindObject (const char *name) const
 Must be redefined in derived classes.
 
virtual TObjectFindObject (const TObject *obj) const
 Must be redefined in derived classes.
 
virtual Option_tGetDrawOption () 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_tGetOption () 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 [].
 
voidoperator new (size_t sz)
 
voidoperator new (size_t sz, void *vp)
 
voidoperator new[] (size_t sz)
 
voidoperator new[] (size_t sz, void *vp)
 
TObjectoperator= (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

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

Private Attributes

Types::EAnalysisType fAnalysisType
 
std::vector< Float_tfATreeEvent
 
Int_t fATreeType = 0
 
Float_t fATreeWeight = 0.0
 
DataAssignType fDataAssignType
 
DataInputHandlerfDataInputHandler
 
DataSetManagerfDataSetManager
 
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 TStringGetReferenceFile () 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
MsgLoggerfLogger
 
- Protected Attributes inherited from TNamed
TString fName
 
TString fTitle
 

#include <TMVA/DataLoader.h>

Inheritance diagram for TMVA::DataLoader:
[legend]

Member Enumeration Documentation

◆ DataAssignType

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:

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