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

Definition at line 51 of file TUnuranSampler.h.

Public Member Functions
	TUnuranSampler ()
	default constructor
	~TUnuranSampler () override
	virtual destructor
virtual bool	Generate (unsigned int nevt, const int *nbins, ROOT::Fit::BinData &data, bool extend=true, bool expErr=true)
	Generate a binned data set.
virtual bool	Generate (unsigned int nevt, double *data, bool eventRow=false)
	Generate a vector of events by filling the passed data vector.
bool	Generate (unsigned int nevt, int nbins, double xmin, double xmax, ROOT::Fit::BinData &data, bool extend=true, bool expErr=true)
	Same as before but passing the range in case of 1 dim data.
virtual bool	Generate (unsigned int nevt, ROOT::Fit::UnBinData &data)
	Generate a un-binned data set by filling the given data set object.
TRandom *	GetRandom () override
	Get the random engine used by the sampler.
bool	HasParentPdf () const
	Check if there is a parent distribution defined.
bool	Init (const char *algo="") override
	initialize the generators with the given algorithm If no algorithm is passed used the default one for the type of distribution
bool	Init (const ROOT::Math::DistSamplerOptions &opt) override
	initialize the generators with the given algorithm If no algorithm is passed used the default one for the type of distribution
virtual TClass *	IsA () const
unsigned int	NDim () const
	return the dimension of the parent distribution (and the data)
const ROOT::Math::IMultiGenFunction &	ParentPdf () const
	Get the parent distribution function (must be called after setting the function).
const double *	Sample ()
	Sample one event and return an array x with sample coordinates values.
bool	Sample (double *x) override
	sample one event in multi-dimension by filling the given array return false if sampling failed
double	Sample1D () override
	sample one event in one dimension better implementation could be provided by the derived classes
bool	SampleBin (double prob, double &value, double *error=nullptr) override
	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
virtual bool	SampleBins (unsigned int n, const double prob, double values, double *errors=nullptr)
	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 independently, SampleBin should be used.
void	SetArea (double area) override
	Set the normalization area of distribution.
void	SetCdf (const ROOT::Math::IGenFunction &cdf) override
	set the cumulative distribution function of the PDF used for random sampling (one dim case)
void	SetDPdf (const ROOT::Math::IGenFunction &dpdf) override
	set the Derivative of the PDF used for random sampling (one dim continuous case)
virtual void	SetFunction (const ROOT::Math::IMultiGenFunction &func)
	set the parent function distribution to use for random sampling (multi-dim case)
template<class Function>
void	SetFunction (Function &func, unsigned int dim)
	set the parent function distribution to use for sampling (generic case)
void	SetFunction (const ROOT::Math::IGenFunction &func) override
	Set the parent function distribution to use for random sampling (one dim case).
void	SetFunction (TF1 *pdf)
	Set the Function using a TF1 pointer.
void	SetMode (const std::vector< double > &modes) override
	Set the mode of the distribution (Multi-dim case).
void	SetMode (double mode) override
	Set the mode of the distribution (1D case).
void	SetPrintLevel (int level)
	Set the print level (if level=-1 use default).
void	SetRandom (TRandom *r) override
	Set the random engine to be used Needs to be called before Init to have effect.
void	SetRange (const double xmin, const double xmax)
	Set the range for all dimensions.
void	SetRange (const ROOT::Fit::DataRange &range)
	Set the range using the ROOT::Fit::DataRange class.
void	SetRange (const std::vector< double > &xmin, const std::vector< double > &xmax)
	Set the range for all dimensions (use std::vector).
void	SetRange (double xmin, double xmax, int icoord=0)
	Set the range in a given dimension.
void	SetSeed (unsigned int seed) override
	Set the random seed for the TRandom instances used by the sampler classes Needs to be called before Init to have effect.
void	SetUseLogPdf (bool on=true) override
	Set using of logarithm of PDF (only for 1D continuous case).
virtual void	Streamer (TBuffer &)
void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

Static Public Member Functions
static TClass *	Class ()
static const char *	Class_Name ()
static constexpr Version_t	Class_Version ()
static const char *	DeclFileName ()

Protected Member Functions
bool	DoInit1D (const char *algo)
	Initialization for 1D distributions.
bool	DoInitDiscrete1D (const char *algo)
	Initialization for 1D discrete distributions.
bool	DoInitND (const char *algo)
	Initialization for multi-dim distributions.
virtual void	DoSetDimension (unsigned int ndim)
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

Private Attributes
double	fArea
	area of dist
const ROOT::Math::IGenFunction *	fCDF = nullptr
	CDF function pointer.
std::vector< double >	fData
	! internal array used to cached the sample data
bool	fDiscrete = false
	flag to indicate if the function is discrete
const ROOT::Math::IGenFunction *	fDPDF = nullptr
	1D Derivative function pointer
const ROOT::Math::IMultiGenFunction *	fFunc
	internal function (ND)
const ROOT::Math::IGenFunction *	fFunc1D = nullptr
	1D function pointer (pdf)
bool	fHasArea = false
	flag to indicate if a area is set
bool	fHasMode = false
	flag to indicate if a mode is set
int	fLevel
	debug level
double	fMode
	mode of dist (1D)
std::vector< double >	fNDMode
	mode of the multi-dim distribution
bool	fOneDim = false
	flag to indicate if the function is 1 dimension
bool	fOwnFunc
	flag to indicate if the function is owned
ROOT::Fit::DataRange *	fRange
	data range
TUnuran *	fUnuran = nullptr
	unuran engine class
bool	fUseLogPdf = false
	flag to indicate if we use the log of the PDF

#include <TUnuranSampler.h>

Inheritance diagram for TUnuranSampler:

Constructor & Destructor Documentation

◆ TUnuranSampler()

TUnuranSampler::TUnuranSampler ( )

default constructor

Definition at line 32 of file TUnuranSampler.cxx.

◆ ~TUnuranSampler()

TUnuranSampler::~TUnuranSampler ( )

override

virtual destructor

Definition at line 42 of file TUnuranSampler.cxx.

Member Function Documentation

◆ Class()

TClass * TUnuranSampler::Class ( )

static

Returns: TClass describing this class

◆ Class_Name()

const char * TUnuranSampler::Class_Name ( )

static

Returns: Name of this class

◆ Class_Version()

constexpr Version_t TUnuranSampler::Class_Version ( )

inlinestaticconstexpr

Returns: Version of this class

Definition at line 198 of file TUnuranSampler.h.

◆ DeclFileName()

const char * TUnuranSampler::DeclFileName ( )

inlinestatic

Returns: Name of the file containing the class declaration

Definition at line 198 of file TUnuranSampler.h.

◆ DoInit1D()

bool TUnuranSampler::DoInit1D ( const char * algo )

protected

Initialization for 1D distributions.

Definition at line 142 of file TUnuranSampler.cxx.

◆ DoInitDiscrete1D()

bool TUnuranSampler::DoInitDiscrete1D ( const char * algo )

protected

Initialization for 1D discrete distributions.

Definition at line 182 of file TUnuranSampler.cxx.

◆ DoInitND()

bool TUnuranSampler::DoInitND ( const char * algo )

protected

Initialization for multi-dim distributions.

Definition at line 223 of file TUnuranSampler.cxx.

◆ DoSetDimension()

void ROOT::Math::DistSampler::DoSetDimension ( unsigned int ndim )

protectedvirtualinherited

Definition at line 78 of file DistSampler.cxx.

◆ DoSetFunction()

void ROOT::Math::DistSampler::DoSetFunction	(	const ROOT::Math::IMultiGenFunction &	func,
		bool	copy )

protectedvirtualinherited

Definition at line 63 of file DistSampler.cxx.

◆ Generate() [1/4]

bool ROOT::Math::DistSampler::Generate	(	unsigned int	nevt,
		const int *	nbins,
		ROOT::Fit::BinData &	data,
		bool	extend = true,
		bool	expErr = true )

virtualinherited

Generate a binned data set.

A range must have been set before (otherwise inf is returned) and the bins are equidistant in the previously defined range bin center values must be present in given data set If the sampler is implemented by a random one, the entries will be binned according to the Poisson distribution It is assumed the distribution is normalized, otherwise the nevt must be scaled accordingly. The expected value/bin nexp = f(x_i) * binArea/ nevt Extend control if use a fixed (i.e. multinomial statistics) or floating total number of events

Definition at line 135 of file DistSampler.cxx.

◆ Generate() [2/4]

bool ROOT::Math::DistSampler::Generate	(	unsigned int	nevt,
		double *	data,
		bool	eventRow = false )

virtualinherited

Generate a vector of events by filling the passed data vector.

The flag eventRow indicates how the events are arranged in the multi-dim case. The can be arranged in rows or in columns. With eventRow=false events are the columns in data: {x1,x2,.....,xn},{y1,....yn} With eventRow=true events are rows in data: {x1,y1},{x2,y2},.....{xn,yn}

Definition at line 115 of file DistSampler.cxx.

◆ Generate() [3/4]

bool ROOT::Math::DistSampler::Generate	(	unsigned int	nevt,
		int	nbins,
		double	xmin,
		double	xmax,
		ROOT::Fit::BinData &	data,
		bool	extend = true,
		bool	expErr = true )

inlineinherited

Same as before but passing the range in case of 1 dim data.

Definition at line 261 of file DistSampler.h.

◆ Generate() [4/4]

bool ROOT::Math::DistSampler::Generate	(	unsigned int	nevt,
		ROOT::Fit::UnBinData &	data )

virtualinherited

Generate a un-binned data set by filling the given data set object.

If the data set object is not empty, the new generated data will be appended to the existing one.

Definition at line 99 of file DistSampler.cxx.

◆ GetRandom()

TRandom * TUnuranSampler::GetRandom ( )

overridevirtual

Get the random engine used by the sampler.

Reimplemented from ROOT::Math::DistSampler.

Definition at line 261 of file TUnuranSampler.cxx.

◆ HasParentPdf()

bool ROOT::Math::DistSampler::HasParentPdf ( ) const

inlineinherited

Check if there is a parent distribution defined.

Definition at line 179 of file DistSampler.h.

◆ Init() [1/2]

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

overridevirtual

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 47 of file TUnuranSampler.cxx.

◆ Init() [2/2]

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

overridevirtual

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 105 of file TUnuranSampler.cxx.

◆ IsA()

virtual TClass * TUnuranSampler::IsA ( ) const

inlinevirtual

Returns: TClass describing current object

Definition at line 198 of file TUnuranSampler.h.

◆ IsInitialized()

bool ROOT::Math::DistSampler::IsInitialized ( )

protectedinherited

Definition at line 89 of file DistSampler.cxx.

◆ NDim()

unsigned int ROOT::Math::DistSampler::NDim ( ) const

inlineinherited

return the dimension of the parent distribution (and the data)

Definition at line 92 of file DistSampler.h.

◆ ParentPdf()

const ROOT::Math::IMultiGenFunction & ROOT::Math::DistSampler::ParentPdf ( ) const

inlineinherited

Get the parent distribution function (must be called after setting the function).

Definition at line 174 of file DistSampler.h.

◆ PdfRange()

const ROOT::Fit::DataRange & ROOT::Math::DistSampler::PdfRange ( ) const

inlineprotectedinherited

return the data range of the Pdf . Must be called after setting the function

Definition at line 277 of file DistSampler.h.

◆ Sample() [1/2]

const double * ROOT::Math::DistSampler::Sample ( )

inlineinherited

Sample one event and return an array x with sample coordinates values.

Definition at line 194 of file DistSampler.h.

◆ Sample() [2/2]

bool TUnuranSampler::Sample ( double * x )

overridevirtual

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

Implements ROOT::Math::DistSampler.

Definition at line 271 of file TUnuranSampler.cxx.

◆ Sample1D()

double TUnuranSampler::Sample1D ( )

overridevirtual

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

Reimplemented from ROOT::Math::DistSampler.

Definition at line 266 of file TUnuranSampler.cxx.

◆ SampleBin()

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

overridevirtual

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 279 of file TUnuranSampler.cxx.

◆ SampleBins()

virtual bool ROOT::Math::DistSampler::SampleBins	(	unsigned int	n,
		const double *	prob,
		double *	values,
		double *	errors = nullptr )

inlinevirtualinherited

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 independently, SampleBin should be used.

Definition at line 224 of file DistSampler.h.

◆ SetArea()

void TUnuranSampler::SetArea ( double )

inlineoverridevirtual

Set the normalization area of distribution.

Implemented by derived classes if needed

Reimplemented from ROOT::Math::DistSampler.

Definition at line 129 of file TUnuranSampler.h.

◆ SetCdf()

void TUnuranSampler::SetCdf ( const ROOT::Math::IGenFunction & cdf )

overridevirtual

set the cumulative distribution function of the PDF used for random sampling (one dim case)

Reimplemented from ROOT::Math::DistSampler.

Definition at line 306 of file TUnuranSampler.cxx.

◆ SetDPdf()

void TUnuranSampler::SetDPdf ( const ROOT::Math::IGenFunction & dpdf )

overridevirtual

set the Derivative of the PDF used for random sampling (one dim continuous case)

Reimplemented from ROOT::Math::DistSampler.

Definition at line 312 of file TUnuranSampler.cxx.

◆ SetFunction() [1/4]

virtual void ROOT::Math::DistSampler::SetFunction ( const ROOT::Math::IMultiGenFunction & func )

inlinevirtualinherited

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

Definition at line 87 of file DistSampler.h.

◆ SetFunction() [2/4]

template<class Function>

void ROOT::Math::DistSampler::SetFunction	(	Function &	func,
		unsigned int	dim )

inlineinherited

set the parent function distribution to use for sampling (generic case)

Definition at line 73 of file DistSampler.h.

◆ SetFunction() [3/4]

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

inlineoverridevirtual

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

Reimplemented from ROOT::Math::DistSampler.

Definition at line 66 of file TUnuranSampler.h.

◆ SetFunction() [4/4]

void TUnuranSampler::SetFunction ( TF1 * pdf )

Set the Function using a TF1 pointer.

Definition at line 246 of file TUnuranSampler.cxx.

◆ SetMode() [1/2]

void TUnuranSampler::SetMode ( const std::vector< double > & )

overridevirtual

Set the mode of the distribution (Multi-dim case).

Reimplemented from ROOT::Math::DistSampler.

Definition at line 288 of file TUnuranSampler.cxx.

◆ SetMode() [2/2]

void TUnuranSampler::SetMode ( double )

inlineoverridevirtual

Set the mode of the distribution (1D case).

It could be useful or needed by some sampling methods. It is implemented by derived classes if needed (e.g. TUnuranSampler)

Reimplemented from ROOT::Math::DistSampler.

Definition at line 115 of file TUnuranSampler.h.

◆ SetPrintLevel()

void TUnuranSampler::SetPrintLevel ( int level )

inline

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

Definition at line 110 of file TUnuranSampler.h.

◆ SetRandom()

void TUnuranSampler::SetRandom ( TRandom * r )

overridevirtual

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

Reimplemented from ROOT::Math::DistSampler.

Definition at line 251 of file TUnuranSampler.cxx.

◆ SetRange() [1/4]

void ROOT::Math::DistSampler::SetRange	(	const double *	xmin,
		const double *	xmax )

inherited

Set the range for all dimensions.

Definition at line 48 of file DistSampler.cxx.

◆ SetRange() [2/4]

void ROOT::Math::DistSampler::SetRange ( const ROOT::Fit::DataRange & range )

inherited

Set the range using the ROOT::Fit::DataRange class.

Definition at line 58 of file DistSampler.cxx.

◆ SetRange() [3/4]

void ROOT::Math::DistSampler::SetRange	(	const std::vector< double > &	xmin,
		const std::vector< double > &	xmax )

inlineinherited

Set the range for all dimensions (use std::vector).

Definition at line 141 of file DistSampler.h.

◆ SetRange() [4/4]

void ROOT::Math::DistSampler::SetRange	(	double	xmin,
		double	xmax,
		int	icoord = 0 )

inherited

Set the range in a given dimension.

Definition at line 40 of file DistSampler.cxx.

◆ SetSeed()

void TUnuranSampler::SetSeed ( unsigned int seed )

overridevirtual

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 256 of file TUnuranSampler.cxx.

◆ SetUseLogPdf()

void TUnuranSampler::SetUseLogPdf ( bool on = true )

inlineoverridevirtual

Set using of logarithm of PDF (only for 1D continuous case).

Reimplemented from ROOT::Math::DistSampler.

Definition at line 135 of file TUnuranSampler.h.

◆ Streamer()

virtual void TUnuranSampler::Streamer ( TBuffer & )

virtual

◆ StreamerNVirtual()

void TUnuranSampler::StreamerNVirtual ( TBuffer & ClassDef_StreamerNVirtual_b )

inline

Definition at line 198 of file TUnuranSampler.h.

Member Data Documentation

◆ fArea

double TUnuranSampler::fArea

private

area of dist

Definition at line 191 of file TUnuranSampler.h.

◆ fCDF

const ROOT::Math::IGenFunction* TUnuranSampler::fCDF = nullptr

private

CDF function pointer.

Definition at line 194 of file TUnuranSampler.h.

◆ fData

std::vector<double> ROOT::Math::DistSampler::fData

mutableprivateinherited

! internal array used to cached the sample data

Definition at line 287 of file DistSampler.h.

◆ fDiscrete

bool TUnuranSampler::fDiscrete = false

private

flag to indicate if the function is discrete

Definition at line 185 of file TUnuranSampler.h.

◆ fDPDF

const ROOT::Math::IGenFunction* TUnuranSampler::fDPDF = nullptr

private

1D Derivative function pointer

Definition at line 195 of file TUnuranSampler.h.

◆ fFunc

const ROOT::Math::IMultiGenFunction* ROOT::Math::DistSampler::fFunc

privateinherited

internal function (ND)

Definition at line 289 of file DistSampler.h.

◆ fFunc1D

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

private

1D function pointer (pdf)

Definition at line 193 of file TUnuranSampler.h.

◆ fHasArea

bool TUnuranSampler::fHasArea = false

private

flag to indicate if a area is set

Definition at line 187 of file TUnuranSampler.h.

◆ fHasMode

bool TUnuranSampler::fHasMode = false

private

flag to indicate if a mode is set

Definition at line 186 of file TUnuranSampler.h.

◆ fLevel

int TUnuranSampler::fLevel

private

debug level

Definition at line 189 of file TUnuranSampler.h.

◆ fMode

double TUnuranSampler::fMode

private

mode of dist (1D)

Definition at line 190 of file TUnuranSampler.h.

◆ fNDMode

std::vector<double> TUnuranSampler::fNDMode

private

mode of the multi-dim distribution

Definition at line 192 of file TUnuranSampler.h.

◆ fOneDim

bool TUnuranSampler::fOneDim = false

private

flag to indicate if the function is 1 dimension

Definition at line 184 of file TUnuranSampler.h.

◆ fOwnFunc

bool ROOT::Math::DistSampler::fOwnFunc

privateinherited

flag to indicate if the function is owned

Definition at line 286 of file DistSampler.h.

◆ fRange

ROOT::Fit::DataRange* ROOT::Math::DistSampler::fRange

privateinherited

data range

Definition at line 288 of file DistSampler.h.

◆ fUnuran

TUnuran* TUnuranSampler::fUnuran = nullptr

private

unuran engine class

Definition at line 196 of file TUnuranSampler.h.

◆ fUseLogPdf

bool TUnuranSampler::fUseLogPdf = false

private

flag to indicate if we use the log of the PDF

Definition at line 188 of file TUnuranSampler.h.

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

math/unuran/inc/TUnuranSampler.h
math/unuran/src/TUnuranSampler.cxx

Public Member Functions

Static Public Member Functions

Protected Member Functions

Private Attributes

Constructor & Destructor Documentation

◆ TUnuranSampler()

◆ ~TUnuranSampler()

Member Function Documentation

◆ Class()

◆ Class_Name()

◆ Class_Version()

◆ DeclFileName()

◆ DoInit1D()

◆ DoInitDiscrete1D()

◆ DoInitND()

◆ DoSetDimension()

◆ DoSetFunction()

◆ Generate() [1/4]

◆ Generate() [2/4]

◆ Generate() [3/4]

◆ Generate() [4/4]

◆ GetRandom()

◆ HasParentPdf()

◆ Init() [1/2]

◆ Init() [2/2]

◆ IsA()

◆ IsInitialized()

◆ NDim()

◆ ParentPdf()

◆ PdfRange()

◆ Sample() [1/2]

◆ Sample() [2/2]

◆ Sample1D()

◆ SampleBin()

◆ SampleBins()

◆ SetArea()

◆ SetCdf()

◆ SetDPdf()

◆ SetFunction() [1/4]

◆ SetFunction() [2/4]

◆ SetFunction() [3/4]

◆ SetFunction() [4/4]

◆ SetMode() [1/2]

◆ SetMode() [2/2]

◆ SetPrintLevel()

◆ SetRandom()

◆ SetRange() [1/4]

◆ SetRange() [2/4]

◆ SetRange() [3/4]

◆ SetRange() [4/4]

◆ SetSeed()

◆ SetUseLogPdf()

◆ Streamer()

◆ StreamerNVirtual()

Member Data Documentation

◆ fArea

◆ fCDF

◆ fData

◆ fDiscrete

◆ fDPDF

◆ fFunc

◆ fFunc1D

◆ fHasArea

◆ fHasMode

◆ fLevel

◆ fMode

◆ fNDMode

◆ fOneDim

◆ fOwnFunc

◆ fRange

◆ fUnuran

◆ fUseLogPdf