ROOT  6.07/01
Reference Guide
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Properties Friends Macros Groups Pages
List of all members | Public Member Functions | Static Public Member Functions | Static Public Attributes | Protected Member Functions | Private Types | Private Member Functions | Private Attributes | List of all members
TMVA::MethodCuts Class Reference

Definition at line 75 of file MethodCuts.h.

Public Member Functions

 MethodCuts (const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="MC:150:10000:", TDirectory *theTargetFile=0)
 
 MethodCuts (DataSetInfo &theData, const TString &theWeightFile, TDirectory *theTargetDir=NULL)
 construction from weight file More...
 
virtual ~MethodCuts (void)
 destructor More...
 
virtual Bool_t HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)
 Cuts can only handle classification with 2 classes. More...
 
void Train (void)
 training method: here the cuts are optimised for the training sample More...
 
void AddWeightsXMLTo (void *parent) const
 create XML description for LD classification and regression (for arbitrary number of output classes/targets) More...
 
void ReadWeightsFromStream (std::istream &i)
 read the cuts from stream More...
 
void ReadWeightsFromXML (void *wghtnode)
 read coefficients from xml weight file More...
 
Double_t GetMvaValue (Double_t *err=0, Double_t *errUpper=0)
 cut evaluation: returns 1.0 if event passed, 0.0 otherwise More...
 
void WriteMonitoringHistosToFile (void) const
 write histograms and PDFs to file for monitoring purposes More...
 
void TestClassification ()
 nothing to test More...
 
Double_t GetSeparation (TH1 *, TH1 *) const
 compute "separation" defined as <s2> = (1/2) Int_-oo..+oo { (S(x) - B(x))^2/(S(x) + B(x)) dx } More...
 
Double_t GetSeparation (PDF *=0, PDF *=0) const
 compute "separation" defined as <s2> = (1/2) Int_-oo..+oo { (S(x) - B(x))^2/(S(x) + B(x)) dx } More...
 
Double_t GetSignificance (void) const
 compute significance of mean difference significance = |<S> - |/Sqrt(RMS_S2 + RMS_B2) More...
 
Double_t GetmuTransform (TTree *)
 
Double_t GetEfficiency (const TString &, Types::ETreeType, Double_t &)
 
Double_t GetTrainingEfficiency (const TString &)
 
Double_t GetRarity (Double_t, Types::ESBType) const
 compute rarity: R(x) = Integrate_[-oo..x] { PDF(x') dx' } where PDF(x) is the PDF of the classifier's signal or background distribution More...
 
Double_t ComputeEstimator (std::vector< Double_t > &)
 returns estimator for "cut fitness" used by GA there are two requirements: 1) the signal efficiency must be equal to the required one in the efficiency scan 2) the background efficiency must be as small as possible the requirement 1) has priority over 2) More...
 
Double_t EstimatorFunction (std::vector< Double_t > &)
 returns estimator for "cut fitness" used by GA More...
 
Double_t EstimatorFunction (Int_t ievt1, Int_t ievt2)
 for full event scan More...
 
void SetTestSignalEfficiency (Double_t effS)
 
void PrintCuts (Double_t effS) const
 print cuts More...
 
Double_t GetCuts (Double_t effS, std::vector< Double_t > &cutMin, std::vector< Double_t > &cutMax) const
 retrieve cut values for given signal efficiency More...
 
Double_t GetCuts (Double_t effS, Double_t *cutMin, Double_t *cutMax) const
 retrieve cut values for given signal efficiency assume vector of correct size !! More...
 
const RankingCreateRanking ()
 
void DeclareOptions ()
 define the options (their key words) that can be set in the option string know options: Method <string> Minimisation method available values are: MC Monte Carlo <default> GA Genetic Algorithm SA Simulated annealing More...
 
void ProcessOptions ()
 process user options sanity check, do not allow the input variables to be normalised, because this only creates problems when interpreting the cuts More...
 
void CheckSetup ()
 check may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase) More...
 
- Public Member Functions inherited from TMVA::MethodBase
 MethodBase (const TString &jobName, Types::EMVA methodType, const TString &methodTitle, DataSetInfo &dsi, const TString &theOption="", TDirectory *theBaseDir=0)
 standard constructur More...
 
 MethodBase (Types::EMVA methodType, DataSetInfo &dsi, const TString &weightFile, TDirectory *theBaseDir=0)
 constructor used for Testing + Application of the MVA, only (no training), using given WeightFiles More...
 
virtual ~MethodBase ()
 destructor More...
 
void SetupMethod ()
 setup of methods More...
 
void ProcessSetup ()
 process all options the "CheckForUnusedOptions" is done in an independent call, since it may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase) More...
 
void AddOutput (Types::ETreeType type, Types::EAnalysisType analysisType)
 
void TrainMethod ()
 
virtual std::map< TString,
Double_t
OptimizeTuningParameters (TString fomType="ROCIntegral", TString fitType="FitGA")
 call the Optimzier with the set of paremeters and ranges that are meant to be tuned. More...
 
virtual void SetTuneParameters (std::map< TString, Double_t > tuneParameters)
 set the tuning parameters accoding to the argument This is just a dummy . More...
 
void SetTrainTime (Double_t trainTime)
 
Double_t GetTrainTime () const
 
void SetTestTime (Double_t testTime)
 
Double_t GetTestTime () const
 
virtual Double_t GetKSTrainingVsTest (Char_t SorB, TString opt="X")
 
virtual void TestMulticlass ()
 test multiclass classification More...
 
virtual void TestRegression (Double_t &bias, Double_t &biasT, Double_t &dev, Double_t &devT, Double_t &rms, Double_t &rmsT, Double_t &mInf, Double_t &mInfT, Double_t &corr, Types::ETreeType type)
 calculate <sum-of-deviation-squared> of regression output versus "true" value from test sample More...
 
virtual void DeclareCompatibilityOptions ()
 options that are used ONLY for the READER to ensure backward compatibility they are hence without any effect (the reader is only reading the training options that HAD been used at the training of the .xml weightfile at hand More...
 
virtual void Reset ()
 
Double_t GetMvaValue (const TMVA::Event *const ev, Double_t *err=0, Double_t *errUpper=0)
 
const std::vector< Float_t > & GetRegressionValues (const TMVA::Event *const ev)
 
virtual const std::vector
< Float_t > & 
GetRegressionValues ()
 
virtual const std::vector
< Float_t > & 
GetMulticlassValues ()
 
virtual Double_t GetProba (const Event *ev)
 
virtual Double_t GetProba (Double_t mvaVal, Double_t ap_sig)
 compute likelihood ratio More...
 
virtual void MakeClass (const TString &classFileName=TString("")) const
 create reader class for method (classification only at present) More...
 
void PrintHelpMessage () const
 prints out method-specific help method More...
 
void WriteStateToFile () const
 write options and weights to file note that each one text file for the main configuration information and one ROOT file for ROOT objects are created More...
 
void ReadStateFromFile ()
 Function to write options and weights to file. More...
 
void ReadStateFromStream (std::istream &tf)
 read the header from the weight files of the different MVA methods More...
 
void ReadStateFromStream (TFile &rf)
 write reference MVA distributions (and other information) to a ROOT type weight file More...
 
void ReadStateFromXMLString (const char *xmlstr)
 for reading from memory More...
 
virtual void WriteEvaluationHistosToFile (Types::ETreeType treetype)
 writes all MVA evaluation histograms to file More...
 
virtual std::vector< Float_tGetMulticlassEfficiency (std::vector< std::vector< Float_t > > &purity)
 
virtual std::vector< Float_tGetMulticlassTrainingEfficiency (std::vector< std::vector< Float_t > > &purity)
 
virtual Double_t GetROCIntegral (TH1D *histS, TH1D *histB) const
 calculate the area (integral) under the ROC curve as a overall quality measure of the classification More...
 
virtual Double_t GetROCIntegral (PDF *pdfS=0, PDF *pdfB=0) const
 calculate the area (integral) under the ROC curve as a overall quality measure of the classification More...
 
virtual Double_t GetMaximumSignificance (Double_t SignalEvents, Double_t BackgroundEvents, Double_t &optimal_significance_value) const
 plot significance, S/Sqrt(S^2 + B^2), curve for given number of signal and background events; returns cut for maximum significance also returned via reference is the maximum significance More...
 
virtual void GetRegressionDeviation (UInt_t tgtNum, Types::ETreeType type, Double_t &stddev, Double_t &stddev90Percent) const
 
const 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...
 
- Public Member Functions inherited from TMVA::IFitterTarget
 IFitterTarget ()
 
virtual ~IFitterTarget ()
 
virtual void ProgressNotifier (TString, TString)
 

Static Public Member Functions

static MethodCutsDynamicCast (IMethod *method)
 
- Static Public Member Functions inherited from TObject
static Long_t GetDtorOnly ()
 Return destructor only flag. More...
 
static void SetDtorOnly (void *obj)
 Set destructor only flag. More...
 
static Bool_t GetObjectStat ()
 Get status of object stat flag. More...
 
static void SetObjectStat (Bool_t stat)
 Turn on/off tracking of objects in the TObjectTable. More...
 

Static Public Attributes

static const Double_t fgMaxAbsCutVal
 

Protected Member Functions

void MakeClassSpecific (std::ostream &, const TString &) const
 write specific classifier response More...
 
void GetHelpMessage () const
 get help message text More...
 
- Protected Member Functions inherited from TMVA::MethodBase
void NoErrorCalc (Double_t *const err, Double_t *const errUpper)
 
virtual void ReadWeightsFromStream (TFile &)
 
void SetWeightFileName (TString)
 set the weight file name (depreciated) More...
 
const 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 Types

enum  EFitMethodType {
  kUseMonteCarlo = 0, kUseGeneticAlgorithm, kUseSimulatedAnnealing, kUseMinuit,
  kUseEventScan, kUseMonteCarloEvents
}
 
enum  EEffMethod { kUseEventSelection = 0, kUsePDFs }
 
enum  EFitParameters { kNotEnforced = 0, kForceMin, kForceMax, kForceSmart }
 

Private Member Functions

void MatchParsToCuts (const std::vector< Double_t > &, Double_t *, Double_t *)
 translates parameters into cuts More...
 
void MatchParsToCuts (Double_t *, Double_t *, Double_t *)
 
void MatchCutsToPars (std::vector< Double_t > &, Double_t *, Double_t *)
 translates cuts into parameters More...
 
void MatchCutsToPars (std::vector< Double_t > &, Double_t **, Double_t **, Int_t ibin)
 translate the cuts into parameters (obsolete function) More...
 
void CreateVariablePDFs (void)
 for PDF method: create efficiency reference histograms and PDFs More...
 
void GetEffsfromSelection (Double_t *cutMin, Double_t *cutMax, Double_t &effS, Double_t &effB)
 compute signal and background efficiencies from event counting for given cut sample More...
 
void GetEffsfromPDFs (Double_t *cutMin, Double_t *cutMax, Double_t &effS, Double_t &effB)
 compute signal and background efficiencies from PDFs for given cut sample More...
 
void Init (void)
 default initialisation called by all constructors More...
 

Private Attributes

TString fFitMethodS
 
EFitMethodType fFitMethod
 
TString fEffMethodS
 
EEffMethod fEffMethod
 
std::vector< EFitParameters > * fFitParams
 
Double_t fTestSignalEff
 
Double_t fEffSMin
 
Double_t fEffSMax
 
Double_tfCutRangeMin
 
Double_tfCutRangeMax
 
std::vector< Interval * > fCutRange
 
BinarySearchTreefBinaryTreeS
 
BinarySearchTreefBinaryTreeB
 
Double_t ** fCutMin
 
Double_t ** fCutMax
 
Double_tfTmpCutMin
 
Double_tfTmpCutMax
 
TStringfAllVarsI
 
Int_t fNpar
 
Double_t fEffRef
 
std::vector< Int_t > * fRangeSign
 
TRandomfRandom
 
std::vector< Double_t > * fMeanS
 
std::vector< Double_t > * fMeanB
 
std::vector< Double_t > * fRmsS
 
std::vector< Double_t > * fRmsB
 
TH1fEffBvsSLocal
 
std::vector< TH1 * > * fVarHistS
 
std::vector< TH1 * > * fVarHistB
 
std::vector< TH1 * > * fVarHistS_smooth
 
std::vector< TH1 * > * fVarHistB_smooth
 
std::vector< PDF * > * fVarPdfS
 
std::vector< PDF * > * fVarPdfB
 
Bool_t fNegEffWarning
 

Additional Inherited Members

- Public Types inherited from TMVA::MethodBase
enum  EWeightFileType { kROOT =0, kTEXT }
 
- Public Types inherited from TObject
enum  EStatusBits {
  kCanDelete = BIT(0), kMustCleanup = BIT(3), kObjInCanvas = BIT(3), kIsReferenced = BIT(4),
  kHasUUID = BIT(5), kCannotPick = BIT(6), kNoContextMenu = BIT(8), kInvalidObject = BIT(13)
}
 
enum  { kIsOnHeap = 0x01000000, kNotDeleted = 0x02000000, kZombie = 0x04000000, kBitMask = 0x00ffffff }
 
enum  { kSingleKey = BIT(0), kOverwrite = BIT(1), kWriteDelete = BIT(2) }
 
- Public Attributes inherited from TMVA::MethodBase
const 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/MethodCuts.h>

Inheritance diagram for TMVA::MethodCuts:
[legend]

Member Enumeration Documentation

Enumerator
kUseEventSelection 
kUsePDFs 

Definition at line 173 of file MethodCuts.h.

Enumerator
kUseMonteCarlo 
kUseGeneticAlgorithm 
kUseSimulatedAnnealing 
kUseMinuit 
kUseEventScan 
kUseMonteCarloEvents 

Definition at line 162 of file MethodCuts.h.

Enumerator
kNotEnforced 
kForceMin 
kForceMax 
kForceSmart 

Definition at line 177 of file MethodCuts.h.

Constructor & Destructor Documentation

TMVA::MethodCuts::MethodCuts ( const TString jobName,
const TString methodTitle,
DataSetInfo theData,
const TString theOption = "MC:150:10000:",
TDirectory theTargetFile = 0 
)
TMVA::MethodCuts::MethodCuts ( DataSetInfo theData,
const TString theWeightFile,
TDirectory theTargetDir = NULL 
)

construction from weight file

Definition at line 182 of file MethodCuts.cxx.

TMVA::MethodCuts::~MethodCuts ( void  )
virtual

destructor

Definition at line 282 of file MethodCuts.cxx.

Member Function Documentation

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

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

Implements TMVA::MethodBase.

Definition at line 1282 of file MethodCuts.cxx.

void TMVA::MethodCuts::CheckSetup ( )
inlinevirtual

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

Reimplemented from TMVA::MethodBase.

Definition at line 149 of file MethodCuts.h.

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

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

Definition at line 888 of file MethodCuts.cxx.

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

Implements TMVA::MethodBase.

Definition at line 140 of file MethodCuts.h.

void TMVA::MethodCuts::CreateVariablePDFs ( void  )
private

for PDF method: create efficiency reference histograms and PDFs

Definition at line 1101 of file MethodCuts.cxx.

void TMVA::MethodCuts::DeclareOptions ( )
virtual

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

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

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

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

Implements TMVA::MethodBase.

Definition at line 330 of file MethodCuts.cxx.

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

Definition at line 90 of file MethodCuts.h.

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

returns estimator for "cut fitness" used by GA

Implements TMVA::IFitterTarget.

Definition at line 875 of file MethodCuts.cxx.

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

for full event scan

Definition at line 831 of file MethodCuts.cxx.

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

retrieve cut values for given signal efficiency

Definition at line 561 of file MethodCuts.cxx.

Referenced by TMVAClassificationApplication().

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

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

Definition at line 546 of file MethodCuts.cxx.

Double_t TMVA::MethodCuts::GetEfficiency ( const TString theString,
Types::ETreeType  type,
Double_t effSerr 
)
virtual
  • overloaded function to create background efficiency (rejection) versus signal efficiency plot (first call of this function)
  • the function returns the signal efficiency at background efficiency indicated in theString

"theString" must have two entries: [1]: the value of background efficiency at which the signal efficiency is to be returned

Reimplemented from TMVA::MethodBase.

Definition at line 1548 of file MethodCuts.cxx.

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

compute signal and background efficiencies from PDFs for given cut sample

Definition at line 1018 of file MethodCuts.cxx.

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

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

Definition at line 1045 of file MethodCuts.cxx.

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

get help message text

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

Implements TMVA::IMethod.

Definition at line 1712 of file MethodCuts.cxx.

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

Definition at line 119 of file MethodCuts.h.

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

cut evaluation: returns 1.0 if event passed, 0.0 otherwise

Implements TMVA::MethodBase.

Definition at line 442 of file MethodCuts.cxx.

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

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

Reimplemented from TMVA::MethodBase.

Definition at line 124 of file MethodCuts.h.

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

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

Reimplemented from TMVA::MethodBase.

Definition at line 116 of file MethodCuts.h.

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

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

Reimplemented from TMVA::MethodBase.

Definition at line 117 of file MethodCuts.h.

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

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

Reimplemented from TMVA::MethodBase.

Definition at line 118 of file MethodCuts.h.

Double_t TMVA::MethodCuts::GetTrainingEfficiency ( const TString theString)
virtual
  • overloaded function to create background efficiency (rejection) versus signal efficiency plot (first call of this function)
  • the function returns the signal efficiency at background efficiency indicated in theString

"theString" must have two entries: [1]: the value of background efficiency at which the signal efficiency is to be returned

Reimplemented from TMVA::MethodBase.

Definition at line 1436 of file MethodCuts.cxx.

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

Cuts can only handle classification with 2 classes.

Implements TMVA::IMethod.

Definition at line 223 of file MethodCuts.cxx.

void TMVA::MethodCuts::Init ( void  )
privatevirtual

default initialisation called by all constructors

Implements TMVA::MethodBase.

Definition at line 232 of file MethodCuts.cxx.

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

write specific classifier response

Reimplemented from TMVA::MethodBase.

Definition at line 1700 of file MethodCuts.cxx.

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

translates cuts into parameters

Definition at line 1004 of file MethodCuts.cxx.

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

translate the cuts into parameters (obsolete function)

Definition at line 982 of file MethodCuts.cxx.

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

translates parameters into cuts

Definition at line 969 of file MethodCuts.cxx.

void TMVA::MethodCuts::MatchParsToCuts ( Double_t ,
Double_t ,
Double_t  
)
private
void TMVA::MethodCuts::PrintCuts ( Double_t  effS) const

print cuts

Definition at line 475 of file MethodCuts.cxx.

void TMVA::MethodCuts::ProcessOptions ( )
virtual

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

Implements TMVA::MethodBase.

Definition at line 373 of file MethodCuts.cxx.

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

read the cuts from stream

Implements TMVA::MethodBase.

Definition at line 1212 of file MethodCuts.cxx.

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

read coefficients from xml weight file

Implements TMVA::MethodBase.

Definition at line 1322 of file MethodCuts.cxx.

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

Definition at line 132 of file MethodCuts.h.

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

void TMVA::MethodCuts::TestClassification ( )
virtual

nothing to test

Reimplemented from TMVA::MethodBase.

Definition at line 824 of file MethodCuts.cxx.

void TMVA::MethodCuts::Train ( void  )
virtual

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

Implements TMVA::MethodBase.

Definition at line 588 of file MethodCuts.cxx.

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

write histograms and PDFs to file for monitoring purposes

Reimplemented from TMVA::MethodBase.

Definition at line 1406 of file MethodCuts.cxx.

Member Data Documentation

TString* TMVA::MethodCuts::fAllVarsI
private

Definition at line 204 of file MethodCuts.h.

BinarySearchTree* TMVA::MethodCuts::fBinaryTreeB
private

Definition at line 197 of file MethodCuts.h.

BinarySearchTree* TMVA::MethodCuts::fBinaryTreeS
private

Definition at line 196 of file MethodCuts.h.

Double_t** TMVA::MethodCuts::fCutMax
private

Definition at line 201 of file MethodCuts.h.

Double_t** TMVA::MethodCuts::fCutMin
private

Definition at line 200 of file MethodCuts.h.

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

Definition at line 193 of file MethodCuts.h.

Double_t* TMVA::MethodCuts::fCutRangeMax
private

Definition at line 192 of file MethodCuts.h.

Double_t* TMVA::MethodCuts::fCutRangeMin
private

Definition at line 191 of file MethodCuts.h.

TH1* TMVA::MethodCuts::fEffBvsSLocal
private

Definition at line 218 of file MethodCuts.h.

EEffMethod TMVA::MethodCuts::fEffMethod
private

Definition at line 186 of file MethodCuts.h.

TString TMVA::MethodCuts::fEffMethodS
private

Definition at line 185 of file MethodCuts.h.

Double_t TMVA::MethodCuts::fEffRef
private

Definition at line 208 of file MethodCuts.h.

Double_t TMVA::MethodCuts::fEffSMax
private

Definition at line 190 of file MethodCuts.h.

Double_t TMVA::MethodCuts::fEffSMin
private

Definition at line 189 of file MethodCuts.h.

EFitMethodType TMVA::MethodCuts::fFitMethod
private

Definition at line 184 of file MethodCuts.h.

TString TMVA::MethodCuts::fFitMethodS
private

Definition at line 183 of file MethodCuts.h.

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

Definition at line 187 of file MethodCuts.h.

const Double_t TMVA::MethodCuts::fgMaxAbsCutVal
static

Definition at line 146 of file MethodCuts.h.

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

Definition at line 214 of file MethodCuts.h.

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

Definition at line 213 of file MethodCuts.h.

Bool_t TMVA::MethodCuts::fNegEffWarning
private

Definition at line 229 of file MethodCuts.h.

Int_t TMVA::MethodCuts::fNpar
private

Definition at line 207 of file MethodCuts.h.

TRandom* TMVA::MethodCuts::fRandom
private

Definition at line 210 of file MethodCuts.h.

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

Definition at line 209 of file MethodCuts.h.

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

Definition at line 216 of file MethodCuts.h.

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

Definition at line 215 of file MethodCuts.h.

Double_t TMVA::MethodCuts::fTestSignalEff
private

Definition at line 188 of file MethodCuts.h.

Referenced by SetTestSignalEfficiency().

Double_t* TMVA::MethodCuts::fTmpCutMax
private

Definition at line 203 of file MethodCuts.h.

Double_t* TMVA::MethodCuts::fTmpCutMin
private

Definition at line 202 of file MethodCuts.h.

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

Definition at line 222 of file MethodCuts.h.

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

Definition at line 224 of file MethodCuts.h.

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

Definition at line 221 of file MethodCuts.h.

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

Definition at line 223 of file MethodCuts.h.

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

Definition at line 226 of file MethodCuts.h.

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

Definition at line 225 of file MethodCuts.h.

Collaboration diagram for TMVA::MethodCuts:
[legend]

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