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class TKDE: public TNamed

Function Members (Methods)

public:

virtual	~TKDE()
void	TObject::AbstractMethod(const char* method) const
virtual void	TObject::AppendPad(Option_t* option = "")
virtual void	TObject::Browse(TBrowser* b)
static TClass*	Class()
virtual const char*	TObject::ClassName() const
virtual void	TNamed::Clear(Option_t* option = "")
virtual TObject*	TNamed::Clone(const char* newname = "") const
virtual Int_t	TNamed::Compare(const TObject* obj) const
virtual void	TNamed::Copy(TObject& named) const
virtual void	TObject::Delete(Option_t* option = "")MENU
virtual Int_t	TObject::DistancetoPrimitive(Int_t px, Int_t py)
virtual void	Draw(const Option_t* option = "")
virtual void	TObject::DrawClass() constMENU
virtual TObject*	TObject::DrawClone(Option_t* option = "") constMENU
virtual void	TObject::Dump() constMENU
virtual void	TObject::Error(const char* method, const char* msgfmt) const
virtual void	TObject::Execute(const char* method, const char* params, Int_t* error = 0)
virtual void	TObject::Execute(TMethod* method, TObjArray* params, Int_t* error = 0)
virtual void	TObject::ExecuteEvent(Int_t event, Int_t px, Int_t py)
virtual void	TObject::Fatal(const char* method, const char* msgfmt) const
void	Fill(Double_t data)
void	Fill(Double_t data, Double_t weight)
virtual void	TNamed::FillBuffer(char*& buffer)
virtual TObject*	TObject::FindObject(const char* name) const
virtual TObject*	TObject::FindObject(const TObject* obj) const
const Double_t*	GetAdaptiveWeights() const
TF1*	GetApproximateBias(UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)
Double_t	GetBias(Double_t x) const
TF1*	GetDrawnFunction()
TGraphErrors*	GetDrawnGraph()
TF1*	GetDrawnLowerFunction()
TF1*	GetDrawnUpperFunction()
virtual Option_t*	TObject::GetDrawOption() const
static Long_t	TObject::GetDtorOnly()
Double_t	GetError(Double_t x) const
Double_t	GetFixedWeight() const
TF1*	GetFunction(UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)
TGraphErrors*	GetGraphWithErrors(UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)
virtual const char*	TObject::GetIconName() const
TF1*	GetLowerFunction(Double_t confidenceLevel = 0.94999999999999996, UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)
Double_t	GetMean() const
virtual const char*	TNamed::GetName() const
virtual char*	TObject::GetObjectInfo(Int_t px, Int_t py) const
static Bool_t	TObject::GetObjectStat()
virtual Option_t*	TObject::GetOption() const
Double_t	GetRAMISE() const
Double_t	GetSigma() const
virtual const char*	TNamed::GetTitle() const
virtual UInt_t	TObject::GetUniqueID() const
TF1*	GetUpperFunction(Double_t confidenceLevel = 0.94999999999999996, UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)
Double_t	GetValue(Double_t x) const
virtual Bool_t	TObject::HandleTimer(TTimer* timer)
virtual ULong_t	TNamed::Hash() const
virtual void	TObject::Info(const char* method, const char* msgfmt) const
virtual Bool_t	TObject::InheritsFrom(const char* classname) const
virtual Bool_t	TObject::InheritsFrom(const TClass* cl) const
virtual void	TObject::Inspect() constMENU
void	TObject::InvertBit(UInt_t f)
virtual TClass*	IsA() const
virtual Bool_t	TObject::IsEqual(const TObject* obj) const
virtual Bool_t	TObject::IsFolder() const
Bool_t	TObject::IsOnHeap() const
virtual Bool_t	TNamed::IsSortable() const
Bool_t	TObject::IsZombie() const
virtual void	TNamed::ls(Option_t* option = "") const
void	TObject::MayNotUse(const char* method) const
virtual Bool_t	TObject::Notify()
void	TObject::Obsolete(const char* method, const char* asOfVers, const char* removedFromVers) const
void	TObject::operator delete(void* ptr)
void	TObject::operator delete(void* ptr, void* vp)
void	TObject::operator delete[](void* ptr)
void	TObject::operator delete[](void* ptr, void* vp)
void*	TObject::operator new(size_t sz)
void*	TObject::operator new(size_t sz, void* vp)
void*	TObject::operator new[](size_t sz)
void*	TObject::operator new[](size_t sz, void* vp)
Double_t	operator()(Double_t x) const
Double_t	operator()(const Double_t* x, const Double_t* p = 0) const
virtual void	TObject::Paint(Option_t* option = "")
virtual void	TObject::Pop()
virtual void	TNamed::Print(Option_t* option = "") const
virtual Int_t	TObject::Read(const char* name)
virtual void	TObject::RecursiveRemove(TObject* obj)
void	TObject::ResetBit(UInt_t f)
virtual void	TObject::SaveAs(const char* filename = "", Option_t* option = "") constMENU
virtual void	TObject::SavePrimitive(ostream& out, Option_t* option = "")
void	SetBinning(TKDE::EBinning)
void	TObject::SetBit(UInt_t f)
void	TObject::SetBit(UInt_t f, Bool_t set)
virtual void	TObject::SetDrawOption(Option_t* option = "")MENU
static void	TObject::SetDtorOnly(void* obj)
void	SetIteration(TKDE::EIteration iter)
void	SetKernelType(TKDE::EKernelType kern)
void	SetMirror(TKDE::EMirror mir)
virtual void	TNamed::SetName(const char* name)MENU
virtual void	TNamed::SetNameTitle(const char* name, const char* title)
void	SetNBins(UInt_t nbins)
static void	TObject::SetObjectStat(Bool_t stat)
void	SetRange(Double_t xMin, Double_t xMax)
virtual void	TNamed::SetTitle(const char* title = "")MENU
void	SetTuneFactor(Double_t rho)
virtual void	TObject::SetUniqueID(UInt_t uid)
void	SetUseBinsNEvents(UInt_t nEvents)
virtual void	ShowMembers(TMemberInspector& insp) const
virtual Int_t	TNamed::Sizeof() const
virtual void	Streamer(TBuffer&)
void	StreamerNVirtual(TBuffer& ClassDef_StreamerNVirtual_b)
virtual void	TObject::SysError(const char* method, const char* msgfmt) const
Bool_t	TObject::TestBit(UInt_t f) const
Int_t	TObject::TestBits(UInt_t f) const
	TKDE(UInt_t events = 0, const Double_t* data = 0, Double_t xMin = 0., Double_t xMax = 0., const Option_t* option = "KernelType:Gaussian;Iteration:Adaptive;Mirror:noMirror;Binning:RelaxedBinning", Double_t rho = 1.)
	TKDE(UInt_t events, const Double_t* data, const Double_t* dataWeight, Double_t xMin = 0., Double_t xMax = 0., const Option_t* option = "KernelType:Gaussian;Iteration:Adaptive;Mirror:noMirror;Binning:RelaxedBinning", Double_t rho = 1.)
virtual void	TObject::UseCurrentStyle()
virtual void	TObject::Warning(const char* method, const char* msgfmt) const
virtual Int_t	TObject::Write(const char* name = 0, Int_t option = 0, Int_t bufsize = 0)
virtual Int_t	TObject::Write(const char* name = 0, Int_t option = 0, Int_t bufsize = 0) const

protected:

virtual void	TObject::DoError(int level, const char* location, const char* fmt, va_list va) const
void	TObject::MakeZombie()

private:

Double_t	ApproximateBias(const Double_t* x, const Double_t*) const
void	AssureOptions()
Double_t	BiweightKernel(Double_t x) const
void	CheckKernelValidity()
void	CheckOptions(Bool_t isUserDefinedKernel = kFALSE)
void	ComputeDataStats()
Double_t	ComputeKernelIntegral() const
Double_t	ComputeKernelL2Norm() const
Double_t	ComputeKernelMu() const
Double_t	ComputeKernelSigma2() const
Double_t	ComputeMidspread()
Double_t	CosineArchKernel(Double_t x) const
void	DrawConfidenceInterval(TString& drawOpt, double cl = 0.94999999999999996)
void	DrawErrors(TString& drawOpt)
Double_t	EpanechnikovKernel(Double_t x) const
Double_t	GaussianKernel(Double_t x) const
TF1*	GetKDEApproximateBias(UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)
TF1*	GetKDEFunction(UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)
void	GetOptions(string optionType, string option)
TF1*	GetPDFLowerConfidenceInterval(Double_t confidenceLevel = 0.94999999999999996, UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)
TF1*	GetPDFUpperConfidenceInterval(Double_t confidenceLevel = 0.94999999999999996, UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)
UInt_t	Index(Double_t x) const
void	InitFromNewData()
void	Instantiate(TKDE::KernelFunction_Ptr kernfunc, UInt_t events, const Double_t* data, const Double_t* weight, Double_t xMin, Double_t xMax, const Option_t* option, Double_t rho)
Double_t	LowerConfidenceInterval(const Double_t* x, const Double_t* p) const
TKDE	operator=(TKDE& kde)
void	SetBinCentreData(Double_t xmin, Double_t xmax)
void	SetBinCountData()
void	SetCanonicalBandwidths()
void	SetData(const Double_t* data, const Double_t* weights)
void	SetDrawOptions(const Option_t* option, TString& plotOpt, TString& drawOpt)
void	SetHistogram()
void	SetKernel()
void	SetKernelFunction(TKDE::KernelFunction_Ptr kernfunc = 0)
void	SetKernelSigmas2()
void	SetMean()
void	SetMirror()
void	SetMirroredEvents()
void	SetOptions(const Option_t* option, Double_t rho)
void	SetSigma(Double_t R)
void	SetUseBins()
void	SetUserCanonicalBandwidth()
void	SetUserKernelSigma2()
	TKDE(TKDE& kde)
Double_t	UpperConfidenceInterval(const Double_t* x, const Double_t* p) const

Data Members

public:

static TKDE::EIteration	kAdaptive
static TObject::(anonymous)	TObject::kBitMask
static TKDE::EKernelType	kBiweight
static TObject::EStatusBits	TObject::kCanDelete
static TObject::EStatusBits	TObject::kCannotPick
static TKDE::EKernelType	kCosineArch
static TKDE::EKernelType	kEpanechnikov
static TKDE::EIteration	kFixed
static TKDE::EBinning	kForcedBinning
static TKDE::EKernelType	kGaussian
static TObject::EStatusBits	TObject::kHasUUID
static TObject::EStatusBits	TObject::kInvalidObject
static TObject::(anonymous)	TObject::kIsOnHeap
static TObject::EStatusBits	TObject::kIsReferenced
static TKDE::EMirror	kMirrorAsymBoth
static TKDE::EMirror	kMirrorAsymLeft
static TKDE::EMirror	kMirrorAsymLeftRight
static TKDE::EMirror	kMirrorAsymRight
static TKDE::EMirror	kMirrorBoth
static TKDE::EMirror	kMirrorLeft
static TKDE::EMirror	kMirrorLeftAsymRight
static TKDE::EMirror	kMirrorRight
static TObject::EStatusBits	TObject::kMustCleanup
static TObject::EStatusBits	TObject::kNoContextMenu
static TKDE::EMirror	kNoMirror
static TObject::(anonymous)	TObject::kNotDeleted
static TObject::EStatusBits	TObject::kObjInCanvas
static TObject::(anonymous)	TObject::kOverwrite
static TKDE::EBinning	kRelaxedBinning
static TObject::(anonymous)	TObject::kSingleKey
static TKDE::EKernelType	kTotalKernels
static TKDE::EBinning	kUnbinned
static TKDE::EKernelType	kUserDefined
static TObject::(anonymous)	TObject::kWriteDelete
static TObject::(anonymous)	TObject::kZombie

protected:

TString	TNamed::fName	object identifier
TString	TNamed::fTitle	object title

private:

Double_t	fAdaptiveBandwidthFactor	Geometric mean of the kernel density estimation from the data for adaptive iteration
TF1*	fApproximateBias	Output Kernel Density Estimation approximate bias
Bool_t	fAsymLeft
Bool_t	fAsymRight
vector<Double_t>	fBinCount	Number of events per bin for binned data option
TKDE::EBinning	fBinning
vector<Double_t>	fCanonicalBandwidths
vector<Double_t>	fData	Data events
vector<Double_t>	fEventWeights	Original data weights
vector<Double_t>	fEvents	Original data storage
TGraphErrors*	fGraph	Graph with the errors
TKDE::EIteration	fIteration
TKDE::TKernel*	fKernel
TKDE::KernelFunction_Ptr	fKernelFunction
vector<Double_t>	fKernelSigmas2
TKDE::EKernelType	fKernelType
TF1*	fLowerPDF	Output Kernel Density Estimation lower confidence interval PDF function
Double_t	fMean	Data mean
TKDE::EMirror	fMirror
Bool_t	fMirrorLeft
Bool_t	fMirrorRight
UInt_t	fNBins	Number of bins for binned data option
UInt_t	fNEvents	Data's number of events
Bool_t	fNewData	flag to control when new data are given
TF1*	fPDF	Output Kernel Density Estimation PDF function
Double_t	fRho	Adjustment factor for sigma
vector<Bool_t>	fSettedOptions	User input options flag
Double_t	fSigma	Data std deviation
Double_t	fSigmaRob	Data std deviation (robust estimation)
Double_t	fSumOfCounts	Data sum of weights
TF1*	fUpperPDF	Output Kernel Density Estimation upper confidence interval PDF function
Bool_t	fUseBins
UInt_t	fUseBinsNEvents	If the algorithm is allowed to use binning this is the minimum number of events to do so
Bool_t	fUseMinMaxFromData	flag top control if min and max must be used from data
Bool_t	fUseMirroring
Double_t	fWeightSize	Caches the weight size
Double_t	fXMax	Data maximum value
Double_t	fXMin	Data minimum value

Class Charts

Inheritance Chart:

TObject

←

TNamed

←

TKDE

Function documentation

explicit TKDE(UInt_t events = 0, const Double_t* data = 0, Double_t xMin = 0., Double_t xMax = 0., const Option_t* option = "KernelType:Gaussian;Iteration:Adaptive;Mirror:noMirror;Binning:RelaxedBinning", Double_t rho = 1.)

TKDE(UInt_t events, const Double_t* data, const Double_t* dataWeight, Double_t xMin = 0., Double_t xMax = 0., const Option_t* option = "KernelType:Gaussian;Iteration:Adaptive;Mirror:noMirror;Binning:RelaxedBinning", Double_t rho = 1.)

TKDE(const Char_t* /*name*/, const KernelFunction& kernfunc, UInt_t events, const Double_t* data, Double_t xMin = 0.0, Double_t xMax = 0.0, const Option_t* option = "KernelType:UserDefined;Iteration:Adaptive;Mirror:noMirror;Binning:RelaxedBinning", Double_t rho = 1.0)

Instantiate(TKDE::KernelFunction_Ptr kernfunc, UInt_t events, const Double_t* data, const Double_t* weight, Double_t xMin, Double_t xMax, const Option_t* option, Double_t rho)

virtual ~TKDE()

void Fill(Double_t data)

void Fill(Double_t data, Double_t weight)

void SetKernelType(TKDE::EKernelType kern)

void SetIteration(TKDE::EIteration iter)

void SetMirror(TKDE::EMirror mir)

void SetBinning(TKDE::EBinning )

void SetNBins(UInt_t nbins)

void SetUseBinsNEvents(UInt_t nEvents)

void SetTuneFactor(Double_t rho)

void SetRange(Double_t xMin, Double_t xMax)

void Draw(const Option_t* option = "")

Double_t operator()(Double_t x) const

Double_t operator()(const Double_t* x, const Double_t* p = 0) const

Double_t GetValue(Double_t x) const

{ return (*this)(x); }

Double_t GetError(Double_t x) const

Double_t GetBias(Double_t x) const

Double_t GetMean() const

Double_t GetSigma() const

Double_t GetRAMISE() const

Double_t GetFixedWeight() const

TF1* GetFunction(UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)

TF1* GetUpperFunction(Double_t confidenceLevel = 0.94999999999999996, UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)

TF1* GetLowerFunction(Double_t confidenceLevel = 0.94999999999999996, UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)

TF1* GetApproximateBias(UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)

TGraphErrors * GetGraphWithErrors(UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)

TF1 * GetDrawnFunction()

 get the drawn object to chanage settings
 These objects are managed by TKDE and should not be deleted by the user

{ return fPDF;}

TF1 * GetDrawnUpperFunction()

{ return fUpperPDF;}

TF1 * GetDrawnLowerFunction()

{ return fLowerPDF;}

TGraphErrors * GetDrawnGraph()

{ return fGraph;}

const Double_t * GetAdaptiveWeights() const

TKDE operator=(TKDE& kde)

Double_t GaussianKernel(Double_t x) const

 Returns the kernel evaluation at x

Double_t EpanechnikovKernel(Double_t x) const

Double_t BiweightKernel(Double_t x) const

 Returns the kernel evaluation at x

Double_t CosineArchKernel(Double_t x) const

 Returns the kernel evaluation at x

Double_t UpperConfidenceInterval(const Double_t* x, const Double_t* p) const

Double_t LowerConfidenceInterval(const Double_t* x, const Double_t* p) const

Double_t ApproximateBias(const Double_t* x, const Double_t* ) const

{ return GetBias(*x); }

Double_t ComputeKernelL2Norm() const

Double_t ComputeKernelSigma2() const

Double_t ComputeKernelMu() const

Double_t ComputeKernelIntegral() const

Double_t ComputeMidspread()

void ComputeDataStats()

UInt_t Index(Double_t x) const

void SetBinCentreData(Double_t xmin, Double_t xmax)

void SetBinCountData()

void CheckKernelValidity()

void SetUserCanonicalBandwidth()

void SetUserKernelSigma2()

void SetCanonicalBandwidths()

void SetKernelSigmas2()

void SetHistogram()

void SetUseBins()

void SetMirror()

void SetMean()

void SetSigma(Double_t R)

void SetKernel()

void SetKernelFunction(TKDE::KernelFunction_Ptr kernfunc = 0)

void SetOptions(const Option_t* option, Double_t rho)

void CheckOptions(Bool_t isUserDefinedKernel = kFALSE)

void GetOptions(string optionType, string option)

void AssureOptions()

void SetData(const Double_t* data, const Double_t* weights)

void InitFromNewData()

void SetMirroredEvents()

void SetDrawOptions(const Option_t* option, TString& plotOpt, TString& drawOpt)

void DrawErrors(TString& drawOpt)

void DrawConfidenceInterval(TString& drawOpt, double cl = 0.94999999999999996)

TF1* GetKDEFunction(UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)

TF1* GetKDEApproximateBias(UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)

 The density to estimate should be at least twice differentiable.

TF1* GetPDFUpperConfidenceInterval(Double_t confidenceLevel = 0.94999999999999996, UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)

TF1* GetPDFLowerConfidenceInterval(Double_t confidenceLevel = 0.94999999999999996, UInt_t npx = 100, Double_t xMin = 1., Double_t xMax = 0.)