TUnuranSampler class class implementing the ROOT::Math::DistSampler interface using the UNU.RAN package for sampling distributions.

Definition at line 49 of file TUnuranSampler.h.

Public Member Functions
	TUnuranSampler ()
	default constructor More...

virtual	~TUnuranSampler ()
	virtual destructor More...

TRandom *	GetRandom ()
	Get the random engine used by the sampler. More...

bool	Init (const char *algo="")
	initialize the generators with the given algorithm If no algorithm is passed used the default one for the type of distribution More...

bool	Init (const ROOT::Math::DistSamplerOptions &opt)
	initialize the generators with the given algorithm If no algorithm is passed used the default one for the type of distribution More...

bool	Sample (double *x)
	sample one event in multi-dimension by filling the given array return false if sampling failed More...

double	Sample1D ()
	sample one event in one dimension better implementation could be provided by the derived classes More...

bool	SampleBin (double prob, double &value, double *error=0)
	sample one bin given an estimated of the pdf in the bin (this can be function value at the center or its integral in the bin divided by the bin width) By default do not do random sample, just return the function values More...

void	SetArea (double area)
	set the normalization area of distribution implemented by derived classes if needed More...

void	SetFunction (const ROOT::Math::IGenFunction &func)
	set the parent function distribution to use for random sampling (one dim case) More...

void	SetFunction (TF1 *pdf)
	set the Function using a TF1 pointer More...

void	SetMode (double mode)
	set the mode of the distribution (could be useful to some methods) implemented by derived classes if needed More...

void	SetPrintLevel (int level)
	Set the print level (if level=-1 use default) More...

void	SetRandom (TRandom *r)
	Set the random engine to be used Needs to be called before Init to have effect. More...

void	SetSeed (unsigned int seed)
	Set the random seed for the TRandom instances used by the sampler classes Needs to be called before Init to have effect. More...

Public Member Functions inherited from ROOT::Math::DistSampler
	DistSampler ()
	default constructor More...

virtual	~DistSampler ()
	virtual destructor More...

virtual bool	Generate (unsigned int nevt, const int *nbins, ROOT::Fit::BinData &data, bool extend=true)
	generate a bin data set . More...

bool	Generate (unsigned int nevt, int nbins, double xmin, double xmax, ROOT::Fit::BinData &data, bool extend=true)
	same as before but passing the range in case of 1 dim data More...

virtual bool	Generate (unsigned int nevt, ROOT::Fit::UnBinData &data)
	generate a un-binned data sets (fill the given data set) if dataset has already data append to it More...

virtual TRandom *	GetRandom ()
	Get the random engine used by the sampler To be implemented by the derived classes who needs it Returns zero by default. More...

virtual bool	Init (const char *="")
	initialize the generators with the given algorithm Implemented by derived classes who needs it (like UnuranSampler) If nothing is specified use default algorithm from DistSamplerOptions::SetDefaultAlgorithm More...

virtual bool	Init (const DistSamplerOptions &opt)
	initialize the generators with the given option which my include the algorithm but also more if the method is re-impelmented by derived class The default implementation calls the above method passing just the algorithm name More...

unsigned int	NDim () const
	return the dimension of the parent distribution (and the data) More...

const ROOT::Math::IMultiGenFunction &	ParentPdf () const
	get the parent distribution function (must be called after setting the function) More...

const double *	Sample ()
	sample one event and rerturning array x with coordinates More...

virtual bool	Sample (double *x)=0
	sample one event in multi-dimension by filling the given array return false if sampling failed More...

virtual double	Sample1D ()
	sample one event in one dimension better implementation could be provided by the derived classes More...

virtual bool	SampleBin (double prob, double &value, double *error=0)
	sample one bin given an estimated of the pdf in the bin (this can be function value at the center or its integral in the bin divided by the bin width) By default do not do random sample, just return the function values Typically Poisson statistics will be used More...

virtual bool	SampleBins (unsigned int n, const double prob, double values, double *errors=0)
	sample a set of bins given a vector of probabilities Typically multinomial statistics will be used and the sum of the probabilities will be equal to the total number of events to be generated For sampling the bins indipendently, SampleBin should be used More...

virtual void	SetArea (double)
	set the normalization area of distribution implemented by derived classes if needed More...

virtual void	SetFunction (const ROOT::Math::IGenFunction &func)
	set the parent function distribution to use for random sampling (one dim case) More...

virtual void	SetFunction (const ROOT::Math::IMultiGenFunction &func)
	set the parent function distribution to use for random sampling (multi-dim case) More...

template<class Function >
void	SetFunction (Function &func, unsigned int dim)
	set the parent function distribution to use for sampling (generic case) More...

virtual void	SetMode (double)
	set the mode of the distribution (could be useful to some methods) implemented by derived classes if needed More...

virtual void	SetRandom (TRandom *)
	Set the random engine to be used To be implemented by the derived classes who provides random sampling. More...

void	SetRange (const double xmin, const double xmax)
	set range for all dimensions More...

void	SetRange (const ROOT::Fit::DataRange &range)
	set range using DataRange class More...

void	SetRange (double xmin, double xmax, int icoord=0)
	set range in a given dimension More...

virtual void	SetSeed (unsigned int)
	Set the random seed for the TRandom instances used by the sampler classes To be implemented by the derived classes who provides random sampling. More...

Protected Member Functions
bool	DoInit1D (const char *algo)

bool	DoInitDiscrete1D (const char *algo)

bool	DoInitND (const char *algo)

Protected Member Functions inherited from ROOT::Math::DistSampler
virtual void	DoSetFunction (const ROOT::Math::IMultiGenFunction &func, bool copy)

bool	IsInitialized ()

const ROOT::Fit::DataRange &	PdfRange () const
	return the data range of the Pdf . Must be called after setting the function More...

Private Attributes
double	fArea

bool	fDiscrete

const ROOT::Math::IGenFunction *	fFunc1D

bool	fHasArea

bool	fHasMode

int	fLevel

double	fMode

bool	fOneDim

TUnuran *	fUnuran

#include <TUnuranSampler.h>

Inheritance diagram for TUnuranSampler:

[legend]

Constructor & Destructor Documentation

◆ TUnuranSampler()

TUnuranSampler::TUnuranSampler ( )

default constructor

Definition at line 32 of file TUnuranSampler.cxx.

◆ ~TUnuranSampler()

TUnuranSampler::~TUnuranSampler ( )

virtual

virtual destructor

Definition at line 43 of file TUnuranSampler.cxx.

Member Function Documentation

◆ DoInit1D()

bool TUnuranSampler::DoInit1D ( const char * algo )

protected

Definition at line 100 of file TUnuranSampler.cxx.

◆ DoInitDiscrete1D()

bool TUnuranSampler::DoInitDiscrete1D ( const char * algo )

protected

Definition at line 130 of file TUnuranSampler.cxx.

◆ DoInitND()

bool TUnuranSampler::DoInitND ( const char * algo )

protected

Definition at line 165 of file TUnuranSampler.cxx.

◆ GetRandom()

TRandom * TUnuranSampler::GetRandom ( )

virtual

Get the random engine used by the sampler.

Reimplemented from ROOT::Math::DistSampler.

Definition at line 201 of file TUnuranSampler.cxx.

◆ Init() [1/2]

bool TUnuranSampler::Init ( const char * algo = "" )

virtual

initialize the generators with the given algorithm If no algorithm is passed used the default one for the type of distribution

Reimplemented from ROOT::Math::DistSampler.

Definition at line 48 of file TUnuranSampler.cxx.

◆ Init() [2/2]

bool TUnuranSampler::Init ( const ROOT::Math::DistSamplerOptions & opt )

virtual

initialize the generators with the given algorithm If no algorithm is passed used the default one for the type of distribution

Reimplemented from ROOT::Math::DistSampler.

Definition at line 93 of file TUnuranSampler.cxx.

◆ Sample()

bool TUnuranSampler::Sample ( double * x )

virtual

sample one event in multi-dimension by filling the given array return false if sampling failed

Implements ROOT::Math::DistSampler.

Definition at line 211 of file TUnuranSampler.cxx.

◆ Sample1D()

double TUnuranSampler::Sample1D ( )

virtual

sample one event in one dimension better implementation could be provided by the derived classes

Reimplemented from ROOT::Math::DistSampler.

Definition at line 206 of file TUnuranSampler.cxx.

◆ SampleBin()

bool TUnuranSampler::SampleBin	(	double	prob,
		double &	value,
		double *	error = `0`
	)

virtual

sample one bin given an estimated of the pdf in the bin (this can be function value at the center or its integral in the bin divided by the bin width) By default do not do random sample, just return the function values

Reimplemented from ROOT::Math::DistSampler.

Definition at line 219 of file TUnuranSampler.cxx.

◆ SetArea()

void TUnuranSampler::SetArea ( double )

inlinevirtual

set the normalization area of distribution implemented by derived classes if needed

Reimplemented from ROOT::Math::DistSampler.

Definition at line 116 of file TUnuranSampler.h.

◆ SetFunction() [1/2]

void TUnuranSampler::SetFunction ( const ROOT::Math::IGenFunction & func )

inlinevirtual

set the parent function distribution to use for random sampling (one dim case)

Reimplemented from ROOT::Math::DistSampler.

Definition at line 64 of file TUnuranSampler.h.

◆ SetFunction() [2/2]

void TUnuranSampler::SetFunction ( TF1 * pdf )

set the Function using a TF1 pointer

Definition at line 186 of file TUnuranSampler.cxx.

◆ SetMode()

void TUnuranSampler::SetMode ( double )

inlinevirtual

set the mode of the distribution (could be useful to some methods) implemented by derived classes if needed

Reimplemented from ROOT::Math::DistSampler.

Definition at line 108 of file TUnuranSampler.h.

◆ SetPrintLevel()

void TUnuranSampler::SetPrintLevel ( int level )

inline

Set the print level (if level=-1 use default)

Definition at line 103 of file TUnuranSampler.h.

◆ SetRandom()

void TUnuranSampler::SetRandom ( TRandom * r )

virtual

Set the random engine to be used Needs to be called before Init to have effect.

Reimplemented from ROOT::Math::DistSampler.

Definition at line 191 of file TUnuranSampler.cxx.

◆ SetSeed()

void TUnuranSampler::SetSeed ( unsigned int seed )

virtual

Set the random seed for the TRandom instances used by the sampler classes Needs to be called before Init to have effect.

Reimplemented from ROOT::Math::DistSampler.

Definition at line 196 of file TUnuranSampler.cxx.

Member Data Documentation

◆ fArea

double TUnuranSampler::fArea

private

Definition at line 174 of file TUnuranSampler.h.

◆ fDiscrete

bool TUnuranSampler::fDiscrete

private

Definition at line 169 of file TUnuranSampler.h.

◆ fFunc1D

const ROOT::Math::IGenFunction* TUnuranSampler::fFunc1D

private

Definition at line 175 of file TUnuranSampler.h.

◆ fHasArea

bool TUnuranSampler::fHasArea

private

Definition at line 171 of file TUnuranSampler.h.

◆ fHasMode

bool TUnuranSampler::fHasMode

private

Definition at line 170 of file TUnuranSampler.h.

◆ fLevel

int TUnuranSampler::fLevel

private

Definition at line 172 of file TUnuranSampler.h.

◆ fMode

double TUnuranSampler::fMode

private

Definition at line 173 of file TUnuranSampler.h.

◆ fOneDim

bool TUnuranSampler::fOneDim

private

Definition at line 168 of file TUnuranSampler.h.

◆ fUnuran

TUnuran* TUnuranSampler::fUnuran

private

Definition at line 176 of file TUnuranSampler.h.

Libraries for TUnuranSampler:

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Public Member Functions

Protected Member Functions

Private Attributes

Constructor & Destructor Documentation

◆ TUnuranSampler()

◆ ~TUnuranSampler()

Member Function Documentation

◆ DoInit1D()

◆ DoInitDiscrete1D()

◆ DoInitND()

◆ GetRandom()

◆ Init() [1/2]

◆ Init() [2/2]

◆ Sample()

◆ Sample1D()

◆ SampleBin()

◆ SetArea()

◆ SetFunction() [1/2]

◆ SetFunction() [2/2]

◆ SetMode()

◆ SetPrintLevel()

◆ SetRandom()

◆ SetSeed()

Member Data Documentation

◆ fArea

◆ fDiscrete

◆ fFunc1D

◆ fHasArea

◆ fHasMode

◆ fLevel

◆ fMode

◆ fOneDim

◆ fUnuran