This class simply holds a sampling distribution of some test statistic.

The distribution can either be an empirical distribution (eg. the samples themselves) or a weighted set of points (eg. for the FFT method). The class supports merging.

Definition at line 28 of file SamplingDistribution.h.

Public Member Functions
	SamplingDistribution ()
	Default constructor for SamplingDistribution.

	SamplingDistribution (const char name, const char title, const char *varName=0)
	SamplingDistribution constructor (with name and title)

	SamplingDistribution (const char name, const char title, RooDataSet &dataSet, const char columnName=0, const char varName=0)
	Creates a SamplingDistribution from a RooDataSet for debugging purposes; e.g.

	SamplingDistribution (const char name, const char title, std::vector< Double_t > &samplingDist, const char *varName=0)
	Constructor for SamplingDistribution.

	SamplingDistribution (const char name, const char title, std::vector< Double_t > &samplingDist, std::vector< Double_t > &sampleWeights, const char *varName=0)
	SamplingDistribution constructor.

virtual	~SamplingDistribution ()
	Destructor of SamplingDistribution.

void	Add (const SamplingDistribution *other)
	merge two sampling distributions

Double_t	CDF (Double_t x) const
	calculate CDF as a special case of Integral(...) with lower limit equal to -inf

const std::vector< Double_t > &	GetSampleWeights () const
	Get the sampling weights.

const std::vector< Double_t > &	GetSamplingDistribution () const
	Get test statistics values.

Int_t	GetSize () const
	size of samples

const TString	GetVarName () const

Double_t	Integral (Double_t low, Double_t high, Bool_t normalize=kTRUE, Bool_t lowClosed=kTRUE, Bool_t highClosed=kFALSE) const
	numerical integral in these limits

Double_t	IntegralAndError (Double_t &error, Double_t low, Double_t high, Bool_t normalize=kTRUE, Bool_t lowClosed=kTRUE, Bool_t highClosed=kFALSE) const
	numerical integral in these limits including error estimation

Double_t	InverseCDF (Double_t pvalue)
	get the inverse of the Cumulative distribution function

Double_t	InverseCDF (Double_t pvalue, Double_t sigmaVariaton, Double_t &inverseVariation)
	get the inverse of the Cumulative distribution function together with the inverse based on sampling variation

Double_t	InverseCDFInterpolate (Double_t pvalue)
	get the inverse of the Cumulative distribution function

Public Member Functions inherited from TNamed
	TNamed ()

	TNamed (const char name, const char title)

	TNamed (const TNamed &named)
	TNamed copy ctor.

	TNamed (const TString &name, const TString &title)

virtual	~TNamed ()
	TNamed destructor.

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

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

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

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

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

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

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

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

virtual Bool_t	IsSortable () const

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

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

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

virtual void	SetName (const char *name)
	Set the name of the TNamed.

virtual void	SetNameTitle (const char name, const char title)
	Set all the TNamed parameters (name and title).

virtual void	SetTitle (const char *title="")
	Set the title of the TNamed.

virtual Int_t	Sizeof () const
	Return size of the TNamed part of the TObject.

Public Member Functions inherited from TObject
	TObject ()
	TObject constructor.

	TObject (const TObject &object)
	TObject copy ctor.

virtual	~TObject ()
	TObject destructor.

void	AbstractMethod (const char *method) const
	Use this method to implement an "abstract" method that you don't want to leave purely abstract.

virtual void	AppendPad (Option_t *option="")
	Append graphics object to current pad.

virtual void	Browse (TBrowser *b)
	Browse object. May be overridden for another default action.

ULong_t	CheckedHash ()
	Check and record whether this class has a consistent Hash/RecursiveRemove setup (*) and then return the regular Hash value for this object.

virtual const char *	ClassName () const
	Returns name of class to which the object belongs.

virtual void	Delete (Option_t *option="")
	Delete this object.

virtual Int_t	DistancetoPrimitive (Int_t px, Int_t py)
	Computes distance from point (px,py) to the object.

virtual void	Draw (Option_t *option="")
	Default Draw method for all objects.

virtual void	DrawClass () const
	Draw class inheritance tree of the class to which this object belongs.

virtual TObject *	DrawClone (Option_t *option="") const
	Draw a clone of this object in the current selected pad for instance with: `gROOT->SetSelectedPad(gPad)`.

virtual void	Dump () const
	Dump contents of object on stdout.

virtual void	Error (const char method, const char msgfmt,...) const
	Issue error message.

virtual void	Execute (const char method, const char params, Int_t *error=0)
	Execute method on this object with the given parameter string, e.g.

virtual void	Execute (TMethod method, TObjArray params, Int_t *error=0)
	Execute method on this object with parameters stored in the TObjArray.

virtual void	ExecuteEvent (Int_t event, Int_t px, Int_t py)
	Execute action corresponding to an event at (px,py).

virtual void	Fatal (const char method, const char msgfmt,...) const
	Issue fatal error message.

virtual TObject *	FindObject (const char *name) const
	Must be redefined in derived classes.

virtual TObject *	FindObject (const TObject *obj) const
	Must be redefined in derived classes.

virtual Option_t *	GetDrawOption () const
	Get option used by the graphics system to draw this object.

virtual const char *	GetIconName () const
	Returns mime type name of object.

virtual char *	GetObjectInfo (Int_t px, Int_t py) const
	Returns string containing info about the object at position (px,py).

virtual Option_t *	GetOption () const

virtual UInt_t	GetUniqueID () const
	Return the unique object id.

virtual Bool_t	HandleTimer (TTimer *timer)
	Execute action in response of a timer timing out.

Bool_t	HasInconsistentHash () const
	Return true is the type of this object is known to have an inconsistent setup for Hash and RecursiveRemove (i.e.

virtual void	Info (const char method, const char msgfmt,...) const
	Issue info message.

virtual Bool_t	InheritsFrom (const char *classname) const
	Returns kTRUE if object inherits from class "classname".

virtual Bool_t	InheritsFrom (const TClass *cl) const
	Returns kTRUE if object inherits from TClass cl.

virtual void	Inspect () const
	Dump contents of this object in a graphics canvas.

void	InvertBit (UInt_t f)

Bool_t	IsDestructed () const
	IsDestructed.

virtual Bool_t	IsEqual (const TObject *obj) const
	Default equal comparison (objects are equal if they have the same address in memory).

virtual Bool_t	IsFolder () const
	Returns kTRUE in case object contains browsable objects (like containers or lists of other objects).

R__ALWAYS_INLINE Bool_t	IsOnHeap () const

R__ALWAYS_INLINE Bool_t	IsZombie () const

void	MayNotUse (const char *method) const
	Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary).

virtual Bool_t	Notify ()
	This method must be overridden to handle object notification.

void	Obsolete (const char method, const char asOfVers, const char *removedFromVers) const
	Use this method to declare a method obsolete.

void	operator delete (void *ptr)
	Operator delete.

void	operator delete[] (void *ptr)
	Operator delete [].

void *	operator new (size_t sz)

void *	operator new (size_t sz, void *vp)

void *	operator new[] (size_t sz)

void *	operator new[] (size_t sz, void *vp)

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

virtual void	Paint (Option_t *option="")
	This method must be overridden if a class wants to paint itself.

virtual void	Pop ()
	Pop on object drawn in a pad to the top of the display list.

virtual Int_t	Read (const char *name)
	Read contents of object with specified name from the current directory.

virtual void	RecursiveRemove (TObject *obj)
	Recursively remove this object from a list.

void	ResetBit (UInt_t f)

virtual void	SaveAs (const char filename="", Option_t option="") const
	Save this object in the file specified by filename.

virtual void	SavePrimitive (std::ostream &out, Option_t *option="")
	Save a primitive as a C++ statement(s) on output stream "out".

void	SetBit (UInt_t f)

void	SetBit (UInt_t f, Bool_t set)
	Set or unset the user status bits as specified in f.

virtual void	SetDrawOption (Option_t *option="")
	Set drawing option for object.

virtual void	SetUniqueID (UInt_t uid)
	Set the unique object id.

virtual void	SysError (const char method, const char msgfmt,...) const
	Issue system error message.

R__ALWAYS_INLINE Bool_t	TestBit (UInt_t f) const

Int_t	TestBits (UInt_t f) const

virtual void	UseCurrentStyle ()
	Set current style settings in this object This function is called when either TCanvas::UseCurrentStyle or TROOT::ForceStyle have been invoked.

virtual void	Warning (const char method, const char msgfmt,...) const
	Issue warning message.

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

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

Protected Member Functions
void	SortValues () const
	Cached vector with sum of the weight used to compute integral error.

Protected Member Functions inherited from TObject
virtual void	DoError (int level, const char location, const char fmt, va_list va) const
	Interface to ErrorHandler (protected).

void	MakeZombie ()

Private Attributes
std::vector< Double_t >	fSampleWeights
	vector of points for the sampling distribution

std::vector< Double_t >	fSamplingDist

std::vector< Double_t >	fSumW

std::vector< Double_t >	fSumW2
	Cached vector with sum of the weight used to compute integral.

TString	fVarName
	vector of weights for the samples

Additional Inherited Members
Public Types inherited from TObject
enum	{ kIsOnHeap = 0x01000000 , kNotDeleted = 0x02000000 , kZombie = 0x04000000 , kInconsistent = 0x08000000 , kBitMask = 0x00ffffff }

enum	{ kSingleKey = BIT(0) , kOverwrite = BIT(1) , kWriteDelete = BIT(2) }

enum	EDeprecatedStatusBits { kObjInCanvas = BIT(3) }

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

Static Public Member Functions inherited from TObject
static Longptr_t	GetDtorOnly ()
	Return destructor only flag.

static Bool_t	GetObjectStat ()
	Get status of object stat flag.

static void	SetDtorOnly (void *obj)
	Set destructor only flag.

static void	SetObjectStat (Bool_t stat)
	Turn on/off tracking of objects in the TObjectTable.

Protected Types inherited from TObject
enum	{ kOnlyPrepStep = BIT(3) }

Protected Attributes inherited from TNamed
TString	fName

TString	fTitle

#include <RooStats/SamplingDistribution.h>

Inheritance diagram for RooStats::SamplingDistribution:

[legend]

Constructor & Destructor Documentation

◆ SamplingDistribution() [1/5]

SamplingDistribution::SamplingDistribution	(	const char *	name,
		const char *	title,
		std::vector< Double_t > &	samplingDist,
		const char *	varName = `0`
	)

Constructor for SamplingDistribution.

SamplingDistribution constructor.

Definition at line 43 of file SamplingDistribution.cxx.

◆ SamplingDistribution() [2/5]

SamplingDistribution::SamplingDistribution	(	const char *	name,
		const char *	title,
		std::vector< Double_t > &	samplingDist,
		std::vector< Double_t > &	sampleWeights,
		const char *	varName = `0`
	)

SamplingDistribution constructor.

Definition at line 60 of file SamplingDistribution.cxx.

◆ SamplingDistribution() [3/5]

SamplingDistribution::SamplingDistribution	(	const char *	name,
		const char *	title,
		const char *	varName = `0`
	)

SamplingDistribution constructor (with name and title)

Definition at line 75 of file SamplingDistribution.cxx.

◆ SamplingDistribution() [4/5]

SamplingDistribution::SamplingDistribution	(	const char *	name,
		const char *	title,
		RooDataSet &	dataSet,
		const char *	_columnName = `0`,
		const char *	varName = `0`
	)

Creates a SamplingDistribution from a RooDataSet for debugging purposes; e.g.

if you need a Gaussian type SamplingDistribution you can generate it from a Gaussian pdf and use the resulting RooDataSet with this constructor.

The result is the projected distribution onto varName marginalizing the other variables.

If varName is not given, the first variable will be used. This is useful mostly for RooDataSets with only one observable.

Definition at line 93 of file SamplingDistribution.cxx.

◆ SamplingDistribution() [5/5]

SamplingDistribution::SamplingDistribution ( )

Default constructor for SamplingDistribution.

SamplingDistribution default constructor.

Definition at line 134 of file SamplingDistribution.cxx.

◆ ~SamplingDistribution()

SamplingDistribution::~SamplingDistribution ( )

virtual

Destructor of SamplingDistribution.

SamplingDistribution destructor.

Definition at line 142 of file SamplingDistribution.cxx.

Member Function Documentation

◆ Add()

void SamplingDistribution::Add ( const SamplingDistribution * other )

merge two sampling distributions

Merge SamplingDistributions (does nothing if NULL is given).

If variable name was not set before, it is copied from the added SamplingDistribution.

Definition at line 153 of file SamplingDistribution.cxx.

◆ CDF()

Double_t SamplingDistribution::CDF ( Double_t x ) const

calculate CDF as a special case of Integral(...) with lower limit equal to -inf

returns the closed integral [-inf,x]

Definition at line 310 of file SamplingDistribution.cxx.

◆ GetSampleWeights()

const std::vector< Double_t > & RooStats::SamplingDistribution::GetSampleWeights ( ) const

inline

Get the sampling weights.

Definition at line 67 of file SamplingDistribution.h.

◆ GetSamplingDistribution()

const std::vector< Double_t > & RooStats::SamplingDistribution::GetSamplingDistribution ( ) const

inline

Get test statistics values.

Definition at line 65 of file SamplingDistribution.h.

◆ GetSize()

Int_t RooStats::SamplingDistribution::GetSize ( ) const

inline

size of samples

Definition at line 62 of file SamplingDistribution.h.

◆ GetVarName()

const TString RooStats::SamplingDistribution::GetVarName ( ) const

inline

Definition at line 69 of file SamplingDistribution.h.

◆ Integral()

Double_t SamplingDistribution::Integral	(	Double_t	low,
		Double_t	high,
		Bool_t	normalize = `kTRUE`,
		Bool_t	lowClosed = `kTRUE`,
		Bool_t	highClosed = `kFALSE`
	)		const

numerical integral in these limits

Returns the integral in the open/closed/mixed interval.

Default is [low,high) interval. Normalization can be turned off.

Definition at line 188 of file SamplingDistribution.cxx.

◆ IntegralAndError()

Double_t SamplingDistribution::IntegralAndError	(	Double_t &	error,
		Double_t	low,
		Double_t	high,
		Bool_t	normalize = `kTRUE`,
		Bool_t	lowClosed = `kTRUE`,
		Bool_t	highClosed = `kFALSE`
	)		const

numerical integral in these limits including error estimation

Returns the integral in the open/closed/mixed interval.

Default is [low,high) interval. Normalization can be turned off. compute also the error on the integral

Definition at line 238 of file SamplingDistribution.cxx.

◆ InverseCDF() [1/2]

Double_t SamplingDistribution::InverseCDF ( Double_t pvalue )

get the inverse of the Cumulative distribution function

returns the inverse of the cumulative distribution function

Definition at line 317 of file SamplingDistribution.cxx.

◆ InverseCDF() [2/2]

Double_t SamplingDistribution::InverseCDF	(	Double_t	pvalue,
		Double_t	sigmaVariaton,
		Double_t &	inverseVariation
	)

get the inverse of the Cumulative distribution function together with the inverse based on sampling variation

returns the inverse of the cumulative distribution function, with variations depending on number of samples

Definition at line 326 of file SamplingDistribution.cxx.

◆ InverseCDFInterpolate()

Double_t SamplingDistribution::InverseCDFInterpolate ( Double_t pvalue )

get the inverse of the Cumulative distribution function

returns the inverse of the cumulative distribution function

Definition at line 406 of file SamplingDistribution.cxx.

◆ SortValues()

void SamplingDistribution::SortValues ( ) const

protected

Cached vector with sum of the weight used to compute integral error.

first need to sort the values and then compute the running sum of the weights and of the weight square needed later for computing the integral

internal function to sort values

Definition at line 200 of file SamplingDistribution.cxx.

Member Data Documentation

◆ fSampleWeights

std::vector<Double_t> RooStats::SamplingDistribution::fSampleWeights

mutableprivate

vector of points for the sampling distribution

Definition at line 84 of file SamplingDistribution.h.

◆ fSamplingDist

std::vector<Double_t> RooStats::SamplingDistribution::fSamplingDist

mutableprivate

Definition at line 83 of file SamplingDistribution.h.

◆ fSumW

std::vector<Double_t> RooStats::SamplingDistribution::fSumW

mutableprivate

Definition at line 89 of file SamplingDistribution.h.

◆ fSumW2

std::vector<Double_t> RooStats::SamplingDistribution::fSumW2

mutableprivate

Cached vector with sum of the weight used to compute integral.

Definition at line 90 of file SamplingDistribution.h.

◆ fVarName

TString RooStats::SamplingDistribution::fVarName

private

vector of weights for the samples

Definition at line 87 of file SamplingDistribution.h.

Libraries for RooStats::SamplingDistribution:

[legend]

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

roofit/roostats/inc/RooStats/SamplingDistribution.h
roofit/roostats/src/SamplingDistribution.cxx

Public Member Functions

Protected Member Functions

Private Attributes

Additional Inherited Members

Constructor & Destructor Documentation

◆ SamplingDistribution() [1/5]

◆ SamplingDistribution() [2/5]

◆ SamplingDistribution() [3/5]

◆ SamplingDistribution() [4/5]

◆ SamplingDistribution() [5/5]

◆ ~SamplingDistribution()

Member Function Documentation

◆ Add()

◆ CDF()

◆ GetSampleWeights()

◆ GetSamplingDistribution()

◆ GetSize()

◆ GetVarName()

◆ Integral()

◆ IntegralAndError()

◆ InverseCDF() [1/2]

◆ InverseCDF() [2/2]

◆ InverseCDFInterpolate()

◆ SortValues()

Member Data Documentation

◆ fSampleWeights

◆ fSamplingDist

◆ fSumW

◆ fSumW2

◆ fVarName