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TMVA::MethodPDEFoam Class Reference

Definition at line 99 of file MethodPDEFoam.h.

Public Types

enum  EKernel { kNone =0, kGaus =1, kLinN =2 }
 
typedef enum
TMVA::MethodPDEFoam::EKernel 
EKernel
 
- Public Types inherited from TMVA::MethodBase
enum  EWeightFileType { kROOT =0, kTEXT }
 
- Public Types inherited from TObject
enum  EStatusBits {
  kCanDelete = BIT(0), kMustCleanup = BIT(3), kObjInCanvas = BIT(3), kIsReferenced = BIT(4),
  kHasUUID = BIT(5), kCannotPick = BIT(6), kNoContextMenu = BIT(8), kInvalidObject = BIT(13)
}
 
enum  { kIsOnHeap = 0x01000000, kNotDeleted = 0x02000000, kZombie = 0x04000000, kBitMask = 0x00ffffff }
 
enum  { kSingleKey = BIT(0), kOverwrite = BIT(1), kWriteDelete = BIT(2) }
 

Public Member Functions

 MethodPDEFoam (const TString &jobName, const TString &methodTitle, DataSetInfo &dsi, const TString &theOption="PDEFoam", TDirectory *theTargetDir=0)
 
 MethodPDEFoam (DataSetInfo &dsi, const TString &theWeightFile, TDirectory *theTargetDir=NULL)
 constructor from weight file More...
 
virtual ~MethodPDEFoam (void)
 destructor More...
 
virtual Bool_t HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)
 PDEFoam can handle classification with multiple classes and regression with one or more regression-targets. More...
 
void Train (void)
 Train PDE-Foam depending on the set options. More...
 
void TrainMonoTargetRegression (void)
 Training one (mono target regression) foam, whose cells contain the average 0th target. More...
 
void TrainMultiTargetRegression (void)
 Training one (multi target regression) foam, whose cells contain the average event density. More...
 
void TrainSeparatedClassification (void)
 Creation of 2 separated foams: one for signal events, one for backgound events. More...
 
void TrainUnifiedClassification (void)
 Create only one unified foam (fFoam[0]) whose cells contain the average discriminator (N_sig)/(N_sig + N_bg) More...
 
void TrainMultiClassification ()
 Create one unified foam (see TrainUnifiedClassification()) for each class, where the cells of foam i (fFoam[i]) contain the average fraction of events of class i, i.e. More...
 
void AddWeightsXMLTo (void *parent) const
 create XML output of PDEFoam method variables More...
 
void ReadWeightsFromStream (std::istream &i)
 read options and internal parameters More...
 
void ReadWeightsFromXML (void *wghtnode)
 read PDEFoam variables from xml weight file More...
 
void WriteFoamsToFile () const
 Write PDEFoams to file. More...
 
void ReadFoamsFromFile ()
 read foams from file More...
 
PDEFoamReadClonedFoamFromFile (TFile *, const TString &)
 Reads a foam with name 'foamname' from file, and returns a clone of the foam. More...
 
Double_t GetMvaValue (Double_t *err=0, Double_t *errUpper=0)
 Return Mva-Value. More...
 
const std::vector< Float_t > & GetMulticlassValues ()
 Get the multiclass MVA response for the PDEFoam classifier. More...
 
virtual const std::vector
< Float_t > & 
GetRegressionValues ()
 Return regression values for both multi- and mono-target regression. More...
 
virtual void Reset ()
 reset MethodPDEFoam: More...
 
const RankingCreateRanking ()
 Compute ranking of input variables from the number of cuts made in each PDEFoam dimension. More...
 
void GetNCuts (PDEFoamCell *cell, std::vector< UInt_t > &nCuts)
 Fill in 'nCuts' the number of cuts made in every foam dimension, starting at the root cell 'cell'. More...
 
EKernel GetKernel (void)
 
UInt_t KernelToUInt (EKernel ker) const
 
EKernel UIntToKernel (UInt_t iker)
 convert UInt_t to EKernel (used for reading weight files) More...
 
UInt_t TargetSelectionToUInt (ETargetSelection ts) const
 
ETargetSelection UIntToTargetSelection (UInt_t its)
 convert UInt_t to ETargetSelection (used for reading weight files) More...
 
- Public Member Functions inherited from TMVA::MethodBase
 MethodBase (const TString &jobName, Types::EMVA methodType, const TString &methodTitle, DataSetInfo &dsi, const TString &theOption="", TDirectory *theBaseDir=0)
 standard constructur More...
 
 MethodBase (Types::EMVA methodType, DataSetInfo &dsi, const TString &weightFile, TDirectory *theBaseDir=0)
 constructor used for Testing + Application of the MVA, only (no training), using given WeightFiles More...
 
virtual ~MethodBase ()
 destructor More...
 
void SetupMethod ()
 setup of methods More...
 
void ProcessSetup ()
 process all options the "CheckForUnusedOptions" is done in an independent call, since it may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase) More...
 
virtual void CheckSetup ()
 check may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase) More...
 
void AddOutput (Types::ETreeType type, Types::EAnalysisType analysisType)
 
void TrainMethod ()
 
virtual std::map< TString,
Double_t
OptimizeTuningParameters (TString fomType="ROCIntegral", TString fitType="FitGA")
 call the Optimzier with the set of paremeters and ranges that are meant to be tuned. More...
 
virtual void SetTuneParameters (std::map< TString, Double_t > tuneParameters)
 set the tuning parameters accoding to the argument This is just a dummy . More...
 
void SetTrainTime (Double_t trainTime)
 
Double_t GetTrainTime () const
 
void SetTestTime (Double_t testTime)
 
Double_t GetTestTime () const
 
virtual void TestClassification ()
 initialization More...
 
virtual Double_t GetKSTrainingVsTest (Char_t SorB, TString opt="X")
 
virtual void TestMulticlass ()
 test multiclass classification More...
 
virtual void TestRegression (Double_t &bias, Double_t &biasT, Double_t &dev, Double_t &devT, Double_t &rms, Double_t &rmsT, Double_t &mInf, Double_t &mInfT, Double_t &corr, Types::ETreeType type)
 calculate <sum-of-deviation-squared> of regression output versus "true" value from test sample More...
 
Double_t GetMvaValue (const TMVA::Event *const ev, Double_t *err=0, Double_t *errUpper=0)
 
const std::vector< Float_t > & GetRegressionValues (const TMVA::Event *const ev)
 
virtual Double_t GetProba (const Event *ev)
 
virtual Double_t GetProba (Double_t mvaVal, Double_t ap_sig)
 compute likelihood ratio More...
 
virtual Double_t GetRarity (Double_t mvaVal, Types::ESBType reftype=Types::kBackground) const
 compute rarity: R(x) = Integrate_[-oo..x] { PDF(x') dx' } where PDF(x) is the PDF of the classifier's signal or background distribution More...
 
virtual void MakeClass (const TString &classFileName=TString("")) const
 create reader class for method (classification only at present) More...
 
void PrintHelpMessage () const
 prints out method-specific help method More...
 
void WriteStateToFile () const
 write options and weights to file note that each one text file for the main configuration information and one ROOT file for ROOT objects are created More...
 
void ReadStateFromFile ()
 Function to write options and weights to file. More...
 
void ReadStateFromStream (std::istream &tf)
 read the header from the weight files of the different MVA methods More...
 
void ReadStateFromStream (TFile &rf)
 write reference MVA distributions (and other information) to a ROOT type weight file More...
 
void ReadStateFromXMLString (const char *xmlstr)
 for reading from memory More...
 
virtual void WriteEvaluationHistosToFile (Types::ETreeType treetype)
 writes all MVA evaluation histograms to file More...
 
virtual void WriteMonitoringHistosToFile () const
 write special monitoring histograms to file dummy implementation here --------------— More...
 
virtual Double_t GetEfficiency (const TString &, Types::ETreeType, Double_t &err)
 fill background efficiency (resp. More...
 
virtual Double_t GetTrainingEfficiency (const TString &)
 
virtual std::vector< Float_tGetMulticlassEfficiency (std::vector< std::vector< Float_t > > &purity)
 
virtual std::vector< Float_tGetMulticlassTrainingEfficiency (std::vector< std::vector< Float_t > > &purity)
 
virtual Double_t GetSignificance () const
 compute significance of mean difference significance = |<S> - |/Sqrt(RMS_S2 + RMS_B2) More...
 
virtual Double_t GetROCIntegral (TH1D *histS, TH1D *histB) const
 calculate the area (integral) under the ROC curve as a overall quality measure of the classification More...
 
virtual Double_t GetROCIntegral (PDF *pdfS=0, PDF *pdfB=0) const
 calculate the area (integral) under the ROC curve as a overall quality measure of the classification More...
 
virtual Double_t GetMaximumSignificance (Double_t SignalEvents, Double_t BackgroundEvents, Double_t &optimal_significance_value) const
 plot significance, S/Sqrt(S^2 + B^2), curve for given number of signal and background events; returns cut for maximum significance also returned via reference is the maximum significance More...
 
virtual Double_t GetSeparation (TH1 *, TH1 *) const
 compute "separation" defined as <s2> = (1/2) Int_-oo..+oo { (S(x) - B(x))^2/(S(x) + B(x)) dx } More...
 
virtual Double_t GetSeparation (PDF *pdfS=0, PDF *pdfB=0) const
 compute "separation" defined as <s2> = (1/2) Int_-oo..+oo { (S(x) - B(x))^2/(S(x) + B(x)) dx } More...
 
virtual void GetRegressionDeviation (UInt_t tgtNum, Types::ETreeType type, Double_t &stddev, Double_t &stddev90Percent) const
 
const TStringGetJobName () const
 
const TStringGetMethodName () const
 
TString GetMethodTypeName () const
 
Types::EMVA GetMethodType () const
 
const char * GetName () const
 Returns name of object. More...
 
const TStringGetTestvarName () const
 
const TString GetProbaName () const
 
TString GetWeightFileName () const
 retrieve weight file name More...
 
void SetTestvarName (const TString &v="")
 
UInt_t GetNvar () const
 
UInt_t GetNVariables () const
 
UInt_t GetNTargets () const
 
const TStringGetInputVar (Int_t i) const
 
const TStringGetInputLabel (Int_t i) const
 
const TStringGetInputTitle (Int_t i) const
 
Double_t GetMean (Int_t ivar) const
 
Double_t GetRMS (Int_t ivar) const
 
Double_t GetXmin (Int_t ivar) const
 
Double_t GetXmax (Int_t ivar) const
 
Double_t GetSignalReferenceCut () const
 
Double_t GetSignalReferenceCutOrientation () const
 
void SetSignalReferenceCut (Double_t cut)
 
void SetSignalReferenceCutOrientation (Double_t cutOrientation)
 
TDirectoryBaseDir () const
 returns the ROOT directory where info/histograms etc of the corresponding MVA method instance are stored More...
 
TDirectoryMethodBaseDir () const
 returns the ROOT directory where all instances of the corresponding MVA method are stored More...
 
void SetMethodDir (TDirectory *methodDir)
 
void SetBaseDir (TDirectory *methodDir)
 
void SetMethodBaseDir (TDirectory *methodDir)
 
UInt_t GetTrainingTMVAVersionCode () const
 
UInt_t GetTrainingROOTVersionCode () const
 
TString GetTrainingTMVAVersionString () const
 calculates the TMVA version string from the training version code on the fly More...
 
TString GetTrainingROOTVersionString () const
 calculates the ROOT version string from the training version code on the fly More...
 
TransformationHandlerGetTransformationHandler (Bool_t takeReroutedIfAvailable=true)
 
const TransformationHandlerGetTransformationHandler (Bool_t takeReroutedIfAvailable=true) const
 
void RerouteTransformationHandler (TransformationHandler *fTargetTransformation)
 
DataSetData () const
 
DataSetInfoDataInfo () const
 
UInt_t GetNEvents () const
 temporary event when testing on a different DataSet than the own one More...
 
const EventGetEvent () const
 
const EventGetEvent (const TMVA::Event *ev) const
 
const EventGetEvent (Long64_t ievt) const
 
const EventGetEvent (Long64_t ievt, Types::ETreeType type) const
 
const EventGetTrainingEvent (Long64_t ievt) const
 
const EventGetTestingEvent (Long64_t ievt) const
 
const std::vector< TMVA::Event * > & GetEventCollection (Types::ETreeType type)
 returns the event collection (i.e. More...
 
virtual Bool_t IsSignalLike ()
 uses a pre-set cut on the MVA output (SetSignalReferenceCut and SetSignalReferenceCutOrientation) for a quick determination if an event would be selected as signal or background More...
 
virtual Bool_t IsSignalLike (Double_t mvaVal)
 uses a pre-set cut on the MVA output (SetSignalReferenceCut and SetSignalReferenceCutOrientation) for a quick determination if an event with this mva output value would tbe selected as signal or background More...
 
Bool_t HasMVAPdfs () const
 
virtual void SetAnalysisType (Types::EAnalysisType type)
 
Types::EAnalysisType GetAnalysisType () const
 
Bool_t DoRegression () const
 
Bool_t DoMulticlass () const
 
void DisableWriting (Bool_t setter)
 
- Public Member Functions inherited from TMVA::IMethod
 IMethod ()
 
virtual ~IMethod ()
 
- Public Member Functions inherited from TMVA::Configurable
 Configurable (const TString &theOption="")
 
virtual ~Configurable ()
 default destructur More...
 
virtual void ParseOptions ()
 options parser More...
 
void PrintOptions () const
 prints out the options set in the options string and the defaults More...
 
const char * GetConfigName () const
 
const char * GetConfigDescription () const
 
void SetConfigName (const char *n)
 
void SetConfigDescription (const char *d)
 
template<class T >
OptionBaseDeclareOptionRef (T &ref, const TString &name, const TString &desc="")
 
template<class T >
OptionBaseDeclareOptionRef (T *&ref, Int_t size, const TString &name, const TString &desc="")
 
template<class T >
void AddPreDefVal (const T &)
 
template<class T >
void AddPreDefVal (const TString &optname, const T &)
 
void CheckForUnusedOptions () const
 checks for unused options in option string More...
 
const TStringGetOptions () const
 
void SetOptions (const TString &s)
 
void WriteOptionsToStream (std::ostream &o, const TString &prefix) const
 write options to output stream (e.g. in writing the MVA weight files More...
 
void ReadOptionsFromStream (std::istream &istr)
 read option back from the weight file More...
 
void AddOptionsXMLTo (void *parent) const
 write options to XML file More...
 
void ReadOptionsFromXML (void *node)
 
void SetMsgType (EMsgType t)
 
template<class T >
TMVA::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)
 
- Public Member Functions inherited from TObject
 TObject ()
 
 TObject (const TObject &object)
 TObject copy ctor. More...
 
TObjectoperator= (const TObject &rhs)
 TObject assignment operator. More...
 
virtual ~TObject ()
 TObject destructor. More...
 
virtual void AppendPad (Option_t *option="")
 Append graphics object to current pad. More...
 
virtual void Browse (TBrowser *b)
 Browse object. May be overridden for another default action. More...
 
virtual const char * ClassName () const
 Returns name of class to which the object belongs. More...
 
virtual void Clear (Option_t *="")
 
virtual TObjectClone (const char *newname="") const
 Make a clone of an object using the Streamer facility. More...
 
virtual Int_t Compare (const TObject *obj) const
 Compare abstract method. More...
 
virtual void Copy (TObject &object) const
 Copy this to obj. More...
 
virtual void Delete (Option_t *option="")
 Delete this object. More...
 
virtual Int_t DistancetoPrimitive (Int_t px, Int_t py)
 Computes distance from point (px,py) to the object. More...
 
virtual void Draw (Option_t *option="")
 Default Draw method for all objects. More...
 
virtual void DrawClass () const
 Draw class inheritance tree of the class to which this object belongs. More...
 
virtual TObjectDrawClone (Option_t *option="") const
 Draw a clone of this object in the current pad. More...
 
virtual void Dump () const
 Dump contents of object on stdout. More...
 
virtual void Execute (const char *method, const char *params, Int_t *error=0)
 Execute method on this object with the given parameter string, e.g. More...
 
virtual void Execute (TMethod *method, TObjArray *params, Int_t *error=0)
 Execute method on this object with parameters stored in the TObjArray. More...
 
virtual void ExecuteEvent (Int_t event, Int_t px, Int_t py)
 Execute action corresponding to an event at (px,py). More...
 
virtual TObjectFindObject (const char *name) const
 Must be redefined in derived classes. More...
 
virtual TObjectFindObject (const TObject *obj) const
 Must be redefined in derived classes. More...
 
virtual Option_tGetDrawOption () const
 Get option used by the graphics system to draw this object. More...
 
virtual UInt_t GetUniqueID () const
 Return the unique object id. More...
 
virtual const char * GetIconName () const
 Returns mime type name of object. More...
 
virtual Option_tGetOption () const
 
virtual char * GetObjectInfo (Int_t px, Int_t py) const
 Returns string containing info about the object at position (px,py). More...
 
virtual const char * GetTitle () const
 Returns title of object. More...
 
virtual Bool_t HandleTimer (TTimer *timer)
 Execute action in response of a timer timing out. More...
 
virtual ULong_t Hash () const
 Return hash value for this object. More...
 
virtual Bool_t InheritsFrom (const char *classname) const
 Returns kTRUE if object inherits from class "classname". More...
 
virtual Bool_t InheritsFrom (const TClass *cl) const
 Returns kTRUE if object inherits from TClass cl. More...
 
virtual void Inspect () const
 Dump contents of this object in a graphics canvas. More...
 
virtual Bool_t IsFolder () const
 Returns kTRUE in case object contains browsable objects (like containers or lists of other objects). More...
 
virtual Bool_t IsEqual (const TObject *obj) const
 Default equal comparison (objects are equal if they have the same address in memory). More...
 
virtual Bool_t IsSortable () const
 
Bool_t IsOnHeap () const
 
Bool_t IsZombie () const
 
virtual Bool_t Notify ()
 This method must be overridden to handle object notification. More...
 
virtual void ls (Option_t *option="") const
 The ls function lists the contents of a class on stdout. More...
 
virtual void Paint (Option_t *option="")
 This method must be overridden if a class wants to paint itself. More...
 
virtual void Pop ()
 Pop on object drawn in a pad to the top of the display list. More...
 
virtual void Print (Option_t *option="") const
 This method must be overridden when a class wants to print itself. More...
 
virtual Int_t Read (const char *name)
 Read contents of object with specified name from the current directory. More...
 
virtual void RecursiveRemove (TObject *obj)
 Recursively remove this object from a list. More...
 
virtual void SaveAs (const char *filename="", Option_t *option="") const
 Save this object in the file specified by filename. More...
 
virtual void SavePrimitive (std::ostream &out, Option_t *option="")
 Save a primitive as a C++ statement(s) on output stream "out". More...
 
virtual void SetDrawOption (Option_t *option="")
 Set drawing option for object. More...
 
virtual void SetUniqueID (UInt_t uid)
 Set the unique object id. More...
 
virtual void UseCurrentStyle ()
 Set current style settings in this object This function is called when either TCanvas::UseCurrentStyle or TROOT::ForceStyle have been invoked. More...
 
virtual Int_t Write (const char *name=0, Int_t option=0, Int_t bufsize=0)
 Write this object to the current directory. More...
 
virtual Int_t Write (const char *name=0, Int_t option=0, Int_t bufsize=0) const
 Write this object to the current directory. More...
 
voidoperator new (size_t sz)
 
voidoperator new[] (size_t sz)
 
voidoperator new (size_t sz, void *vp)
 
voidoperator new[] (size_t sz, void *vp)
 
void operator delete (void *ptr)
 Operator delete. More...
 
void operator delete[] (void *ptr)
 Operator delete []. More...
 
void SetBit (UInt_t f, Bool_t set)
 Set or unset the user status bits as specified in f. More...
 
void SetBit (UInt_t f)
 
void ResetBit (UInt_t f)
 
Bool_t TestBit (UInt_t f) const
 
Int_t TestBits (UInt_t f) const
 
void InvertBit (UInt_t f)
 
virtual void Info (const char *method, const char *msgfmt,...) const
 Issue info message. More...
 
virtual void Warning (const char *method, const char *msgfmt,...) const
 Issue warning message. More...
 
virtual void Error (const char *method, const char *msgfmt,...) const
 Issue error message. More...
 
virtual void SysError (const char *method, const char *msgfmt,...) const
 Issue system error message. More...
 
virtual void Fatal (const char *method, const char *msgfmt,...) const
 Issue fatal error message. More...
 
void AbstractMethod (const char *method) const
 Use this method to implement an "abstract" method that you don't want to leave purely abstract. More...
 
void MayNotUse (const char *method) const
 Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary). More...
 
void Obsolete (const char *method, const char *asOfVers, const char *removedFromVers) const
 Use this method to declare a method obsolete. More...
 

Protected Member Functions

void MakeClassSpecific (std::ostream &, const TString &) const
 write PDEFoam-specific classifier response NOT IMPLEMENTED YET! More...
 
void GetHelpMessage () const
 provide help message More...
 
Double_t CalculateMVAError ()
 Calculate the error on the Mva value. More...
 
void CalcXminXmax ()
 Determine foam range [fXmin, fXmax] for all dimensions, such that a fraction of 'fFrac' events lie outside the foam. More...
 
void SetXminXmax (TMVA::PDEFoam *)
 Set Xmin, Xmax for every dimension in the given pdefoam object. More...
 
PDEFoamInitFoam (TString, EFoamType, UInt_t cls=0)
 Create a new PDEFoam, set the PDEFoam options (nCells, nBin, Xmin, Xmax, etc.) and initialize the PDEFoam by calling pdefoam->Initialize(). More...
 
PDEFoamKernelBaseCreatePDEFoamKernel ()
 create a pdefoam kernel estimator, depending on the current value of fKernel More...
 
void DeleteFoams ()
 Deletes all trained foams. More...
 
void FillVariableNamesToFoam () const
 store the variable names in all foams More...
 
- Protected Member Functions inherited from TMVA::MethodBase
void NoErrorCalc (Double_t *const err, Double_t *const errUpper)
 
virtual void ReadWeightsFromStream (TFile &)
 
void SetWeightFileName (TString)
 set the weight file name (depreciated) More...
 
const TStringGetWeightFileDir () const
 
void SetWeightFileDir (TString fileDir)
 set directory of weight file More...
 
Bool_t IsNormalised () const
 
void SetNormalised (Bool_t norm)
 
Bool_t Verbose () const
 
Bool_t Help () const
 
const TStringGetInternalVarName (Int_t ivar) const
 
const TStringGetOriginalVarName (Int_t ivar) const
 
Bool_t HasTrainingTree () const
 
virtual void MakeClassSpecificHeader (std::ostream &, const TString &="") const
 
void Statistics (Types::ETreeType treeType, const TString &theVarName, Double_t &, Double_t &, Double_t &, Double_t &, Double_t &, Double_t &)
 calculates rms,mean, xmin, xmax of the event variable this can be either done for the variables as they are or for normalised variables (in the range of 0-1) if "norm" is set to kTRUE More...
 
Bool_t TxtWeightsOnly () const
 
Bool_t IsConstructedFromWeightFile () const
 
Bool_t IgnoreEventsWithNegWeightsInTraining () const
 
- Protected Member Functions inherited from TMVA::Configurable
Bool_t LooseOptionCheckingEnabled () const
 
void EnableLooseOptions (Bool_t b=kTRUE)
 
void WriteOptionsReferenceToFile ()
 write complete options to output stream More...
 
void ResetSetFlag ()
 resets the IsSet falg for all declare options to be called before options are read from stream More...
 
const TStringGetReferenceFile () const
 
MsgLoggerLog () const
 
- Protected Member Functions inherited from TObject
void MakeZombie ()
 
virtual void DoError (int level, const char *location, const char *fmt, va_list va) const
 Interface to ErrorHandler (protected). More...
 

Private Member Functions

void DeclareOptions ()
 Declare MethodPDEFoam options. More...
 
void DeclareCompatibilityOptions ()
 options that are used ONLY for the READER to ensure backward compatibility More...
 
void ProcessOptions ()
 process user options More...
 
void PrintCoefficients (void)
 
template<typename T >
T Sqr (T x) const
 
void Init (void)
 default initialization called by all constructors More...
 

Private Attributes

Bool_t fSigBgSeparated
 
Float_t fFrac
 
Float_t fDiscrErrCut
 
Float_t fVolFrac
 
Int_t fnCells
 
Int_t fnActiveCells
 
Int_t fnSampl
 
Int_t fnBin
 
Int_t fEvPerBin
 
Bool_t fCompress
 
Bool_t fMultiTargetRegression
 
UInt_t fNmin
 
Bool_t fCutNmin
 
UInt_t fMaxDepth
 
TString fKernelStr
 
EKernel fKernel
 
PDEFoamKernelBasefKernelEstimator
 
TString fTargetSelectionStr
 
ETargetSelection fTargetSelection
 
Bool_t fFillFoamWithOrigWeights
 
Bool_t fUseYesNoCell
 
TString fDTLogic
 
EDTSeparation fDTSeparation
 
Bool_t fPeekMax
 
std::vector< Float_tfXmin
 
std::vector< Float_tfXmax
 
std::vector< PDEFoam * > fFoam
 

Additional Inherited Members

- Static Public Member Functions inherited from TObject
static Long_t GetDtorOnly ()
 Return destructor only flag. More...
 
static void SetDtorOnly (void *obj)
 Set destructor only flag. More...
 
static Bool_t GetObjectStat ()
 Get status of object stat flag. More...
 
static void SetObjectStat (Bool_t stat)
 Turn on/off tracking of objects in the TObjectTable. More...
 
- Public Attributes inherited from TMVA::MethodBase
const EventfTmpEvent
 
Bool_t fSetupCompleted
 
- Static Protected Member Functions inherited from TMVA::MethodBase
static MethodBaseGetThisBase ()
 return a pointer the base class of this method More...
 
- Protected Attributes inherited from TMVA::MethodBase
RankingfRanking
 
std::vector< TString > * fInputVars
 
Int_t fNbins
 
Int_t fNbinsMVAoutput
 
Int_t fNbinsH
 
Types::EAnalysisType fAnalysisType
 
std::vector< Float_t > * fRegressionReturnVal
 
std::vector< Float_t > * fMulticlassReturnVal
 
UInt_t fSignalClass
 
UInt_t fBackgroundClass
 

#include <TMVA/MethodPDEFoam.h>

Inheritance diagram for TMVA::MethodPDEFoam:
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Member Typedef Documentation

Member Enumeration Documentation

Enumerator
kNone 
kGaus 
kLinN 

Definition at line 104 of file MethodPDEFoam.h.

Constructor & Destructor Documentation

TMVA::MethodPDEFoam::MethodPDEFoam ( const TString jobName,
const TString methodTitle,
DataSetInfo dsi,
const TString theOption = "PDEFoam",
TDirectory theTargetDir = 0 
)
TMVA::MethodPDEFoam::MethodPDEFoam ( DataSetInfo dsi,
const TString theWeightFile,
TDirectory theTargetDir = NULL 
)

constructor from weight file

Definition at line 123 of file MethodPDEFoam.cxx.

TMVA::MethodPDEFoam::~MethodPDEFoam ( void  )
virtual

destructor

Definition at line 313 of file MethodPDEFoam.cxx.

Member Function Documentation

void TMVA::MethodPDEFoam::AddWeightsXMLTo ( void parent) const
virtual

create XML output of PDEFoam method variables

Implements TMVA::MethodBase.

Definition at line 1152 of file MethodPDEFoam.cxx.

Double_t TMVA::MethodPDEFoam::CalculateMVAError ( )
protected

Calculate the error on the Mva value.

If fSigBgSeparated == true the error is calculated from the number of events in the signal and background PDEFoam cells.

If fSigBgSeparated == false, the error is taken directly from the PDEFoam cell.

Definition at line 757 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::CalcXminXmax ( )
protected

Determine foam range [fXmin, fXmax] for all dimensions, such that a fraction of 'fFrac' events lie outside the foam.

Definition at line 325 of file MethodPDEFoam.cxx.

TMVA::PDEFoamKernelBase * TMVA::MethodPDEFoam::CreatePDEFoamKernel ( )
protected

create a pdefoam kernel estimator, depending on the current value of fKernel

Definition at line 1103 of file MethodPDEFoam.cxx.

const TMVA::Ranking * TMVA::MethodPDEFoam::CreateRanking ( )
virtual

Compute ranking of input variables from the number of cuts made in each PDEFoam dimension.

The PDEFoam dimension (the variable) for which the most cuts were done is ranked highest.

Implements TMVA::MethodBase.

Definition at line 825 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::DeclareCompatibilityOptions ( )
privatevirtual

options that are used ONLY for the READER to ensure backward compatibility

Reimplemented from TMVA::MethodBase.

Definition at line 246 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::DeclareOptions ( )
privatevirtual

Declare MethodPDEFoam options.

Implements TMVA::MethodBase.

Definition at line 211 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::DeleteFoams ( )
protected

Deletes all trained foams.

Definition at line 1122 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::FillVariableNamesToFoam ( ) const
protected

store the variable names in all foams

Definition at line 1484 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::GetHelpMessage ( ) const
protectedvirtual

provide help message

Implements TMVA::IMethod.

Definition at line 1507 of file MethodPDEFoam.cxx.

EKernel TMVA::MethodPDEFoam::GetKernel ( void  )
inline

Definition at line 161 of file MethodPDEFoam.h.

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

Get the multiclass MVA response for the PDEFoam classifier.

The returned MVA values are normalized, i.e. their sum equals 1.

Reimplemented from TMVA::MethodBase.

Definition at line 791 of file MethodPDEFoam.cxx.

Double_t TMVA::MethodPDEFoam::GetMvaValue ( Double_t err = 0,
Double_t errUpper = 0 
)
virtual

Return Mva-Value.

In case of 'fSigBgSeparated==false' (one unifiend PDEFoam was trained) the function returns the content of the cell, which corresponds to the current TMVA::Event, i.e. D = N_sig/(N_bg+N_sig).

In case of 'fSigBgSeparated==true' (two separate PDEFoams were trained) the function returns

D = Density_sig/(Density_sig+Density_bg)

where 'Density_sig' is the content of the cell in the signal PDEFoam (fFoam[0]) and 'Density_bg' is the content of the cell in the background PDEFoam (fFoam[1]).

In both cases the error on the discriminant is stored in 'err' and 'errUpper'. (Of course err and errUpper must be non-zero and point to valid address to make this work.)

Implements TMVA::MethodBase.

Definition at line 711 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::GetNCuts ( PDEFoamCell cell,
std::vector< UInt_t > &  nCuts 
)

Fill in 'nCuts' the number of cuts made in every foam dimension, starting at the root cell 'cell'.

Parameters:

  • cell - root cell to start the counting from
  • nCuts - the number of cuts are saved in this vector

Definition at line 878 of file MethodPDEFoam.cxx.

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

Return regression values for both multi- and mono-target regression.

Reimplemented from TMVA::MethodBase.

Definition at line 1051 of file MethodPDEFoam.cxx.

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

PDEFoam can handle classification with multiple classes and regression with one or more regression-targets.

Implements TMVA::IMethod.

Definition at line 161 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::Init ( void  )
privatevirtual

default initialization called by all constructors

Implements TMVA::MethodBase.

Definition at line 172 of file MethodPDEFoam.cxx.

TMVA::PDEFoam * TMVA::MethodPDEFoam::InitFoam ( TString  foamcaption,
EFoamType  ft,
UInt_t  cls = 0 
)
protected

Create a new PDEFoam, set the PDEFoam options (nCells, nBin, Xmin, Xmax, etc.) and initialize the PDEFoam by calling pdefoam->Initialize().

Parameters:

Definition at line 935 of file MethodPDEFoam.cxx.

UInt_t TMVA::MethodPDEFoam::KernelToUInt ( EKernel  ker) const
inline

Definition at line 162 of file MethodPDEFoam.h.

void TMVA::MethodPDEFoam::MakeClassSpecific ( std::ostream &  ,
const TString  
) const
protectedvirtual

write PDEFoam-specific classifier response NOT IMPLEMENTED YET!

Reimplemented from TMVA::MethodBase.

Definition at line 1500 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::PrintCoefficients ( void  )
private

Definition at line 1146 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::ProcessOptions ( )
privatevirtual

process user options

Implements TMVA::MethodBase.

Definition at line 255 of file MethodPDEFoam.cxx.

TMVA::PDEFoam * TMVA::MethodPDEFoam::ReadClonedFoamFromFile ( TFile file,
const TString foamname 
)

Reads a foam with name 'foamname' from file, and returns a clone of the foam.

The given ROOT file must be open. (The ROOT file will not be closed in this function.)

Parameters:

  • file - an open ROOT file
  • foamname - name of foam to load from the file

Returns:

If a foam with name 'foamname' exists in the file, then it is read from the file, cloned and returned. If a foam with name 'foamname' does not exist in the file or the clone operation does not succeed, then NULL is returned.

Definition at line 1374 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::ReadFoamsFromFile ( )

read foams from file

Definition at line 1400 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::ReadWeightsFromStream ( std::istream &  i)
virtual

read options and internal parameters

Implements TMVA::MethodBase.

Definition at line 1227 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::ReadWeightsFromXML ( void wghtnode)
virtual

read PDEFoam variables from xml weight file

Implements TMVA::MethodBase.

Definition at line 1283 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::Reset ( void  )
virtual

reset MethodPDEFoam:

  • delete all PDEFoams
  • delete the kernel estimator

Reimplemented from TMVA::MethodBase.

Definition at line 1134 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::SetXminXmax ( TMVA::PDEFoam pdefoam)
protected

Set Xmin, Xmax for every dimension in the given pdefoam object.

Definition at line 894 of file MethodPDEFoam.cxx.

template<typename T >
T TMVA::MethodPDEFoam::Sqr ( T  x) const
inlineprivate

Definition at line 207 of file MethodPDEFoam.h.

UInt_t TMVA::MethodPDEFoam::TargetSelectionToUInt ( ETargetSelection  ts) const
inline

Definition at line 164 of file MethodPDEFoam.h.

void TMVA::MethodPDEFoam::Train ( void  )
virtual

Train PDE-Foam depending on the set options.

Implements TMVA::MethodBase.

Definition at line 433 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::TrainMonoTargetRegression ( void  )

Training one (mono target regression) foam, whose cells contain the average 0th target.

The dimension of the foam = number of non-targets (= number of variables).

Definition at line 597 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::TrainMultiClassification ( )

Create one unified foam (see TrainUnifiedClassification()) for each class, where the cells of foam i (fFoam[i]) contain the average fraction of events of class i, i.e.

D = number events of class i / total number of events

Definition at line 558 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::TrainMultiTargetRegression ( void  )

Training one (multi target regression) foam, whose cells contain the average event density.

The dimension of the foam = number of non-targets + number of targets.

Definition at line 638 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::TrainSeparatedClassification ( void  )

Creation of 2 separated foams: one for signal events, one for backgound events.

At the end the foam cells of fFoam[0] will contain the average number of signal events and fFoam[1] will contain the average number of background events.

Definition at line 483 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::TrainUnifiedClassification ( void  )

Create only one unified foam (fFoam[0]) whose cells contain the average discriminator (N_sig)/(N_sig + N_bg)

Definition at line 522 of file MethodPDEFoam.cxx.

TMVA::MethodPDEFoam::EKernel TMVA::MethodPDEFoam::UIntToKernel ( UInt_t  iker)

convert UInt_t to EKernel (used for reading weight files)

Definition at line 1453 of file MethodPDEFoam.cxx.

TMVA::ETargetSelection TMVA::MethodPDEFoam::UIntToTargetSelection ( UInt_t  its)

convert UInt_t to ETargetSelection (used for reading weight files)

Definition at line 1469 of file MethodPDEFoam.cxx.

void TMVA::MethodPDEFoam::WriteFoamsToFile ( ) const

Write PDEFoams to file.

Definition at line 1195 of file MethodPDEFoam.cxx.

Member Data Documentation

Bool_t TMVA::MethodPDEFoam::fCompress
private

Definition at line 220 of file MethodPDEFoam.h.

Bool_t TMVA::MethodPDEFoam::fCutNmin
private

Definition at line 223 of file MethodPDEFoam.h.

Float_t TMVA::MethodPDEFoam::fDiscrErrCut
private

Definition at line 212 of file MethodPDEFoam.h.

TString TMVA::MethodPDEFoam::fDTLogic
private

Definition at line 233 of file MethodPDEFoam.h.

EDTSeparation TMVA::MethodPDEFoam::fDTSeparation
private

Definition at line 234 of file MethodPDEFoam.h.

Int_t TMVA::MethodPDEFoam::fEvPerBin
private

Definition at line 218 of file MethodPDEFoam.h.

Bool_t TMVA::MethodPDEFoam::fFillFoamWithOrigWeights
private

Definition at line 231 of file MethodPDEFoam.h.

std::vector<PDEFoam*> TMVA::MethodPDEFoam::fFoam
private

Definition at line 239 of file MethodPDEFoam.h.

Float_t TMVA::MethodPDEFoam::fFrac
private

Definition at line 211 of file MethodPDEFoam.h.

EKernel TMVA::MethodPDEFoam::fKernel
private

Definition at line 227 of file MethodPDEFoam.h.

Referenced by GetKernel().

PDEFoamKernelBase* TMVA::MethodPDEFoam::fKernelEstimator
private

Definition at line 228 of file MethodPDEFoam.h.

TString TMVA::MethodPDEFoam::fKernelStr
private

Definition at line 226 of file MethodPDEFoam.h.

UInt_t TMVA::MethodPDEFoam::fMaxDepth
private

Definition at line 224 of file MethodPDEFoam.h.

Bool_t TMVA::MethodPDEFoam::fMultiTargetRegression
private

Definition at line 221 of file MethodPDEFoam.h.

Int_t TMVA::MethodPDEFoam::fnActiveCells
private

Definition at line 215 of file MethodPDEFoam.h.

Int_t TMVA::MethodPDEFoam::fnBin
private

Definition at line 217 of file MethodPDEFoam.h.

Int_t TMVA::MethodPDEFoam::fnCells
private

Definition at line 214 of file MethodPDEFoam.h.

UInt_t TMVA::MethodPDEFoam::fNmin
private

Definition at line 222 of file MethodPDEFoam.h.

Int_t TMVA::MethodPDEFoam::fnSampl
private

Definition at line 216 of file MethodPDEFoam.h.

Bool_t TMVA::MethodPDEFoam::fPeekMax
private

Definition at line 235 of file MethodPDEFoam.h.

Bool_t TMVA::MethodPDEFoam::fSigBgSeparated
private

Definition at line 210 of file MethodPDEFoam.h.

ETargetSelection TMVA::MethodPDEFoam::fTargetSelection
private

Definition at line 230 of file MethodPDEFoam.h.

TString TMVA::MethodPDEFoam::fTargetSelectionStr
private

Definition at line 229 of file MethodPDEFoam.h.

Bool_t TMVA::MethodPDEFoam::fUseYesNoCell
private

Definition at line 232 of file MethodPDEFoam.h.

Float_t TMVA::MethodPDEFoam::fVolFrac
private

Definition at line 213 of file MethodPDEFoam.h.

std::vector<Float_t> TMVA::MethodPDEFoam::fXmax
private

Definition at line 237 of file MethodPDEFoam.h.

std::vector<Float_t> TMVA::MethodPDEFoam::fXmin
private

Definition at line 237 of file MethodPDEFoam.h.

Collaboration diagram for TMVA::MethodPDEFoam:
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The documentation for this class was generated from the following files: