#include <TSampling.h>

Inheritance diagram for URANIE::Sampler::TSampling:

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Collaboration diagram for URANIE::Sampler::TSampling:

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Public Types
enum	EType { kLHS , kSRS , kUnknown }

Public Member Functions
Constructor and Destructor
	TSampling (URANIE::DataServer::TDataServer tds, Option_t option="lhs", Int_t nCalcul=1000)
	Constructor from a TDataServer, the name of the method and the size of the sample.

virtual	~TSampling ()
	Default destructor.

Generate the sample
We have several methods which can generate the sampler. the prefered method generateSample which used the Devroye algorithm to create permutation. This method does not treat the correlation (2008-04-01 10:13:47). the method from the Dakota module generateSampleByDakota a deprecated method genSample (from version v0.3 to v0.4)
void	generateSample (Option_t *option="")
	Generates the sample.

void	generateSampleByDakota ()
	Generates the sample by the Dakota module.

Correlation matrix
Methods to specify correlation between attributes
void	setUserCorrelation (Int_t indx, Int_t indy, double value)
	Defines a correlation between two attributes given by their indexes.

void	setUserCorrelation (TString xname, TString yname, double value)
	Defines a correlation between two attributes given by their names.

void	setUserCorrelation (URANIE::DataServer::TAttribute x, URANIE::DataServer::TAttribute y, Double_t value)
	Defines a correlation between two attributes.

void	setCorrelationMatrix (TMatrixD corrMat)
	Set the correlation matrix.

void	setSaveRang (Int_t rang=0)
	EMPTY:: TSampling::setSaveRang.

void	setTypeSampling (Option_t *option)

Printing Log
virtual void	printLog (Option_t *option="")
	Prints the log.

Public Member Functions inherited from URANIE::Sampler::TSamplerStochastic
	TSamplerStochastic (URANIE::DataServer::TDataServer tds, Option_t option, Int_t nCalcul)
	Constructor with a dataserver.

virtual	~TSamplerStochastic ()
	Default destructor.

void	setSeed (Int_t ind=0)
	Init the seed.

Int_t	getSeed ()
	Returns the seed value.

Public Member Functions inherited from URANIE::Sampler::TSampler
	TSampler (URANIE::DataServer::TDataServer tds, Option_t option, Int_t nCalcul)
	Constructor with a TDataServer, the options and the size of the sample.

virtual	~TSampler ()
	Default destructor.

Int_t	GetID ()
	Returns the ID of the class.

void	setMethodName (TString str)
	Sets the method name in a global variable.

TString	getMethodName ()
	Gets the method name.

virtual URANIE::DataServer::TDataServer *	getTDS ()
	Return the TDS filling by the sampling algorithm.

void	parseOption (Option_t *option)
	Parse the option.

virtual void	createListOfAttributes ()
	Creates the List of attributes to simulate.

virtual void	createTuple ()
	Creates the TDSNtupleD of data with only the TStochasticAttributes.

URANIE::DataServer::TDSNtupleD *	getTuple ()
	Returns the TDSNtupleD of data.

virtual void	fillOtherAttributes ()
	Fills the TDSNtupleD of data with other TFormulaAttributes.

void	setLog ()

void	unsetLog ()

void	changeLog ()

Bool_t	getLog ()

Public Attributes
LHSInput *	_fLhsInput

TMatrixD	_corrmatrix
	The correlation matrix.

TMatrixD	_corrIndexPosition
	The permutation for giving the rank correlation matrix given by the user.

EType	_ntype
	The type of sampling (SRS, LHS)

bool	_buseSVD
	useSVD instead of Cholesky to factorize the input correlation matrix

bool	_buseSVDquiet
	useSVD instead of Cholesky to factorize the input correlation matrix

Public Attributes inherited from URANIE::Sampler::TSampler
Int_t	_nS
	The size of the sample.

Int_t	_nX
	The size of attributes to sample.

URANIE::DataServer::TDSNtupleD *	_ntsample
	the tntuple of data

TString	_sMethod
	The title of the sampler method.

Bool_t	_blog
	Log Printing.

Bool_t	_bupdateFile
	Update the back up file when generating the attributeformula if there is some.

URANIE::DataServer::TDataServer *	_tds
	Pointer to a TDS.

TList *	_lstOfAttributesToSample
	The list of Stochastic Attributes to sample.

Private Member Functions
private methods
void	CorrelationFactorization ()
	Decomposes the correlation matrix.

void	computeCorrelationMatrix (TMatrixD matOrg)
	Computes the correlation matrix for a TMatrixD.

Additional Inherited Members
Protected Member Functions inherited from URANIE::Sampler::TSamplerStochastic
virtual void	init ()
	The preprocessing step.

virtual void	terminate ()
	The post-processing step.

Protected Attributes inherited from URANIE::Sampler::TSamplerStochastic
Int_t	_nSeed

Member Enumeration Documentation

◆ EType

enum URANIE::Sampler::TSampling::EType

Enumerator
kLHS
kSRS
kUnknown

Constructor & Destructor Documentation

◆ TSampling()

URANIE::Sampler::TSampling::TSampling	(	URANIE::DataServer::TDataServer *	tds,
		Option_t *	option = `"lhs"`,
		Int_t	nCalcul = `1000`
	)

Constructor from a TDataServer, the name of the method and the size of the sample.

Attributes to sample are specified in the TDataServer. The name of the method is "lhs"|"srs". The size is an integer greater than zero.

Default values

Method ="lhs" with default value or when the option is uncorrect
size = 100 with default value.

Parameters

tds	(TDataServer *) the pointer of the TDataServer. It must contains objects from daughter classes of TStochasticAttribute
option	(Option_t *) Method of sampling [lhs]
nCalcul	(Int_t) Size of the sampler to generate [1000]

Referenced by ClassImp().

◆ ~TSampling()

virtual URANIE::Sampler::TSampling::~TSampling ( )

virtual

Default destructor.

Referenced by ClassImp().

Member Function Documentation

◆ computeCorrelationMatrix()

void URANIE::Sampler::TSampling::computeCorrelationMatrix ( TMatrixD matOrg )

private

Computes the correlation matrix for a TMatrixD.

Referenced by ClassImp().

◆ CorrelationFactorization()

void URANIE::Sampler::TSampling::CorrelationFactorization ( )

private

Decomposes the correlation matrix.

Applies the cholesky decomposition

Referenced by ClassImp().

◆ generateSample()

void URANIE::Sampler::TSampling::generateSample ( Option_t * option = "" )

virtual

Generates the sample.

Uses the Devroye algorithm to create permutation

for(Int_t j=nS-1; j>1; j--)
k = (Int_t)gRandom->Integer(j);
swap(Ak, Aj);

Implements URANIE::Sampler::TSampler.

Referenced by ClassImp(), ClassImp(), ClassImp(), and ClassImp().

◆ generateSampleByDakota()

void URANIE::Sampler::TSampling::generateSampleByDakota ( )

Generates the sample by the Dakota module.

The size of sample is limited to 9990.

Referenced by ClassImp().

◆ printLog()

virtual void URANIE::Sampler::TSampling::printLog ( Option_t * option = "" )

virtual

Prints the log.

Reimplemented from URANIE::Sampler::TSamplerStochastic.

Referenced by ClassImp().

◆ setCorrelationMatrix()

void URANIE::Sampler::TSampling::setCorrelationMatrix ( TMatrixD corrMat )

Set the correlation matrix.

The correlation matrix is define from a provided matrix.

Parameters

the	input correlation matrix requested by the user.

Referenced by ClassImp().

◆ setSaveRang()

void URANIE::Sampler::TSampling::setSaveRang ( Int_t rang = 0 )

EMPTY:: TSampling::setSaveRang.

Documentation of the function setSaveRang.

Parameters

rang	(Int_t) (default = 0)

Referenced by ClassImp().

◆ setTypeSampling()

void URANIE::Sampler::TSampling::setTypeSampling ( Option_t * option )

Referenced by ClassImp().

◆ setUserCorrelation() [1/3]

void URANIE::Sampler::TSampling::setUserCorrelation	(	Int_t	indx,
		Int_t	indy,
		double	value
	)

Defines a correlation between two attributes given by their indexes.

Warning: The indexes begin 0 to n-1.

Parameters

indx	(Int_t) the index of the first attribute
indy	(Int_t) the index of the second attribute
value	(Double_t) the correlation factor between the two attributes

Referenced by ClassImp().

◆ setUserCorrelation() [2/3]

void URANIE::Sampler::TSampling::setUserCorrelation	(	TString	xname,
		TString	yname,
		double	value
	)

Defines a correlation between two attributes given by their names.

Parameters

xname	(TString) the first attribute
yname	(TString) the second attribute
value	(Double_t) the correlation factor between x and y

◆ setUserCorrelation() [3/3]

void URANIE::Sampler::TSampling::setUserCorrelation	(	URANIE::DataServer::TAttribute *	x,
		URANIE::DataServer::TAttribute *	y,
		Double_t	value
	)

Defines a correlation between two attributes.

The correlation factor is define as the

Parameters

x	(URANIE::DataServer::TAttribute *) the first attribute
y	(URANIE::DataServer::TAttribute *) the second attribute
value	(Double_t) the correlation factor between x and y

Member Data Documentation

◆ _buseSVD

bool URANIE::Sampler::TSampling::_buseSVD

useSVD instead of Cholesky to factorize the input correlation matrix

Referenced by ClassImp().

◆ _buseSVDquiet

bool URANIE::Sampler::TSampling::_buseSVDquiet

useSVD instead of Cholesky to factorize the input correlation matrix

Referenced by ClassImp().

◆ _corrIndexPosition

TMatrixD URANIE::Sampler::TSampling::_corrIndexPosition

The permutation for giving the rank correlation matrix given by the user.

Referenced by ClassImp().

◆ _corrmatrix

TMatrixD URANIE::Sampler::TSampling::_corrmatrix

The correlation matrix.

Referenced by ClassImp().

◆ _fLhsInput

LHSInput* URANIE::Sampler::TSampling::_fLhsInput

Referenced by ClassImp().

◆ _ntype

EType URANIE::Sampler::TSampling::_ntype

The type of sampling (SRS, LHS)

Referenced by ClassImp().

Documentation / Developer's manual

Available modules

Public Types

Public Member Functions

Public Attributes

Private Member Functions

Additional Inherited Members

Member Enumeration Documentation

◆ EType

Constructor & Destructor Documentation

◆ TSampling()

◆ ~TSampling()

Member Function Documentation

◆ computeCorrelationMatrix()

◆ CorrelationFactorization()

◆ generateSample()

◆ generateSampleByDakota()

◆ printLog()

◆ setCorrelationMatrix()

◆ setSaveRang()

◆ setTypeSampling()

◆ setUserCorrelation() [1/3]

◆ setUserCorrelation() [2/3]

◆ setUserCorrelation() [3/3]

Member Data Documentation

◆ _buseSVD

◆ _buseSVDquiet

◆ _corrIndexPosition

◆ _corrmatrix

◆ _fLhsInput

◆ _ntype