#include <TImportanceSampling.h>

Inheritance diagram for URANIE::Sampler::TImportanceSampling:

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Collaboration diagram for URANIE::Sampler::TImportanceSampling:

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Public Types
enum	EQuantileMethod { kQuantile1 , kQuantile2 , kQuantile3 , kQuantile4 , kQuantileUnknown }

Public Member Functions
Constructor and Destructor
	TImportanceSampling (URANIE::DataServer::TDataServer tds, TString xname, URANIE::DataServer::TStochasticAttribute att, Int_t ns)
	Constructor.

virtual	~TImportanceSampling ()
	Destructor.

Setting and Getting global informations
URANIE::DataServer::TDataServer *	getTDS ()
	This method returns the new tds build by the contructor of the object TIportanceSampling.

Compute Statistical parameters
Double_t	computeMean (TString u)
	This method computes the mean of the ouput attribut given in parameter.

Double_t	computeStd (TString u)
	This method computes and returns the stantard deviation of the ouput attribut given in parameter.

Double_t	computeThreshold (TString u, Double_t dThreshold)
	This method computes and returns the probability of threshold crossing of the ouput attribut given in parameter.

Double_t	computeQuantile (TString sVar, Double_t dAlpha, EQuantileMethod nMethod=kQuantile2)

Generates the sample
void	generateSample (Option_t *option="")
	Generates the Sample.

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

Printing Log
void	setLog ()

void	unsetLog ()

void	changeLog ()

Bool_t	getLog ()

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.

void	parseOption (Option_t *option)
	Parse the option.

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
URANIE::DataServer::TDataServer *	_tds_IS
	new tds build by the constructor

URANIE::DataServer::TStochasticAttribute *	_x
	attribut which be subsitute

URANIE::DataServer::TStochasticAttribute *	_is_x
	New law/attribut.

Double_t	_mean
	mean

Double_t	_std
	standart deviation

Double_t	_proba
	probability of threshold crossing

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.

Protected Attributes
Bool_t	_blog
	Boolean for edit the log.

TSampling *	_sampling
	THe TSampling object.

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

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

virtual void	terminate ()
	The post-processing step.

Member Enumeration Documentation

◆ EQuantileMethod

enum URANIE::Sampler::TImportanceSampling::EQuantileMethod

Enumerator
kQuantile1
kQuantile2
kQuantile3
kQuantile4
kQuantileUnknown

Constructor & Destructor Documentation

◆ TImportanceSampling()

URANIE::Sampler::TImportanceSampling::TImportanceSampling	(	URANIE::DataServer::TDataServer *	tds,
		TString	xname,
		URANIE::DataServer::TStochasticAttribute *	att,
		Int_t	ns
	)

Constructor.

Referenced by ClassImp().

◆ ~TImportanceSampling()

virtual URANIE::Sampler::TImportanceSampling::~TImportanceSampling ( )

virtual

Destructor.

Referenced by ClassImp().

Member Function Documentation

◆ changeLog()

void URANIE::Sampler::TImportanceSampling::changeLog ( )

inline

References _blog.

◆ computeMean()

Double_t URANIE::Sampler::TImportanceSampling::computeMean ( TString u )

This method computes the mean of the ouput attribut given in parameter.

Return mean

Parameters

u	: name of the output attribut

Referenced by ClassImp().

◆ computeQuantile()

Double_t URANIE::Sampler::TImportanceSampling::computeQuantile	(	TString	sVar,
		Double_t	dAlpha,
		EQuantileMethod	nMethod = `kQuantile2`
	)

Return the $\alpha$ -quantile of the attribute This method computes and returns the $\alpha$ -quantile of the attribute given in parameter.

Parameters

sVar	: name of the attribute
dAlpha	: the parameter $\alpha$ .

Referenced by ClassImp().

◆ computeStd()

Double_t URANIE::Sampler::TImportanceSampling::computeStd ( TString u )

This method computes and returns the stantard deviation of the ouput attribut given in parameter.

Return the standard deviation

Parameters

u	: name of the output attribut

Referenced by ClassImp().

◆ computeThreshold()

Double_t URANIE::Sampler::TImportanceSampling::computeThreshold	(	TString	u,
		Double_t	dThreshold
	)

This method computes and returns the probability of threshold crossing of the ouput attribut given in parameter.

Return the probability of threshold crossing

Parameters

u	: name of the output attribut,
dThreshold	: the threshold parameter

Referenced by ClassImp().

◆ createListOfAttributes()

void URANIE::Sampler::TImportanceSampling::createListOfAttributes ( )

virtual

Creates the List of attributes to simulate.

Reimplemented from URANIE::Sampler::TSampler.

Referenced by ClassImp().

◆ generateSample()

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

virtual

Generates the Sample.

Implements URANIE::Sampler::TSampler.

Referenced by ClassImp().

◆ getLog()

Bool_t URANIE::Sampler::TImportanceSampling::getLog ( )

inline

References _blog.

◆ getTDS()

URANIE::DataServer::TDataServer * URANIE::Sampler::TImportanceSampling::getTDS ( )

inlinevirtual

This method returns the new tds build by the contructor of the object TIportanceSampling.

Return the tds

This tds is a copy of the iital tds where a attribut was replace by a new attribut which follows the new law given in parameter of the constructor.

The inital attrinut replaced is attached to the new attribute.

Reimplemented from URANIE::Sampler::TSampler.

References _tds_IS.

◆ printLog()

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

virtual

Prints the log.

Reimplemented from URANIE::Sampler::TSamplerStochastic.

Referenced by ClassImp().

◆ setLog()

void URANIE::Sampler::TImportanceSampling::setLog ( )

inline

References _blog.

◆ unsetLog()

void URANIE::Sampler::TImportanceSampling::unsetLog ( )

inline

References _blog.

Member Data Documentation

◆ _blog

Bool_t URANIE::Sampler::TImportanceSampling::_blog

protected

Boolean for edit the log.

Referenced by changeLog(), ClassImp(), getLog(), setLog(), and unsetLog().

◆ _is_x

URANIE::DataServer::TStochasticAttribute* URANIE::Sampler::TImportanceSampling::_is_x

New law/attribut.

Referenced by ClassImp().

◆ _mean

Double_t URANIE::Sampler::TImportanceSampling::_mean

mean

Referenced by ClassImp().

◆ _proba

Double_t URANIE::Sampler::TImportanceSampling::_proba

probability of threshold crossing

Referenced by ClassImp().

◆ _sampling

TSampling* URANIE::Sampler::TImportanceSampling::_sampling

protected

THe TSampling object.

Referenced by ClassImp().

◆ _std

Double_t URANIE::Sampler::TImportanceSampling::_std

standart deviation

Referenced by ClassImp().

◆ _tds_IS

URANIE::DataServer::TDataServer* URANIE::Sampler::TImportanceSampling::_tds_IS

new tds build by the constructor

Referenced by ClassImp(), and getTDS().

◆ _x

URANIE::DataServer::TStochasticAttribute* URANIE::Sampler::TImportanceSampling::_x

attribut which be subsitute

Referenced by ClassImp().

Documentation / Developer's manual

Available modules

Public Types

Public Member Functions

Public Attributes

Protected Attributes

Additional Inherited Members

Member Enumeration Documentation

◆ EQuantileMethod

Constructor & Destructor Documentation

◆ TImportanceSampling()

◆ ~TImportanceSampling()

Member Function Documentation

◆ changeLog()

◆ computeMean()

◆ computeQuantile()

◆ computeStd()

◆ computeThreshold()

◆ createListOfAttributes()

◆ generateSample()

◆ getLog()

◆ getTDS()

◆ printLog()

◆ setLog()

◆ unsetLog()

Member Data Documentation

◆ _blog

◆ _is_x

◆ _mean

◆ _proba

◆ _sampling

◆ _std

◆ _tds_IS

◆ _x