Description of the class TSobol. More...

#include <TSobol.h>

Inheritance diagram for URANIE::Sensitivity::TSobol:

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Collaboration diagram for URANIE::Sensitivity::TSobol:

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Public Types
enum	ESamplerMethod { kSRS , kLHS , kqMCSobol , kqMCHalton }
	list Of Enum More...

enum	EMatrixMiNi { kMiNiSobol , kMiNiSaltelli }

enum	ESiAlgorithm { kSiSobol93 =0 , kSiSaltelli02 , kSiJansen99 , kSiSumo10 , kSiMartinez11 , kSiOnlyNi =26 , kSiAll =31 }

enum	EStiAlgorithm { kStiHomma96 =0 , kStiSobol07 , kStiJansen99 , kStiSumo10 , kStiMartinez11 , kStiOnlyNi =25 , kStiAll =31 }

Public Types inherited from URANIE::Sensitivity::TSensitivity
enum	ELauncher { kCode , kCodeRemote , kFunction , kRun , kUnknown }

Public Member Functions
Constructor and Destructor
	TSobol ()
	Default constructor.

	TSobol (URANIE::DataServer::TDataServer tds, void(fcn)(Double_t , Double_t ), const char varexpinput, const char varexpoutput, Int_t ns, Option_t *option="")
	Default constructor with the TDataServer.

	TSobol (URANIE::DataServer::TDataServer tds, const char fcn, Int_t ns, const char varexpinput, const char varexpoutput, Option_t *option="")
	Default constructor with the TDataServer.

	TSobol (URANIE::DataServer::TDataServer tds, const char varexpinput, const char varexpoutput, Option_t option="")
	Default constructor with a TDataServer filling.

	TSobol (URANIE::DataServer::TDataServer tds, URANIE::Launcher::TCode fcode, Int_t ns, Option_t *option="")
	Default constructor with a tcode.

	TSobol (URANIE::DataServer::TDataServer tds, URANIE::Relauncher::TRun run, Int_t ns, Option_t *option="")
	Default constructor with a trun.

virtual	~TSobol ()
	Default destructor.

Constructor's helper
void	initForRun (Option_t *option)

Setting and Getting attributs
void	createTuple (Option_t *option="")

Generation of the sample
virtual void	generateSample (Option_t *option="")
	Generates all the matrix of sample.

void	loadOtherSobolFile (const char *filename)

void	evaluateIndexes (Option_t *option="")
	Evaluates the index from a Specific TDataServer.

Printing Log
virtual void	printLog ()

Public Member Functions inherited from URANIE::Sensitivity::TSensitivity
	TSensitivity ()
	Default constructor.

	TSensitivity (URANIE::DataServer::TDataServer tds, const char fcn, Int_t ns, const char varexpinput="", const char varexpoutput="", Option_t *option="")
	Default constructor with the name of a function.

	TSensitivity (URANIE::DataServer::TDataServer tds, void(fcn)(Double_t , Double_t ), const char varexpinput, const char varexpoutput, Int_t ns, Option_t *option="")

	TSensitivity (URANIE::DataServer::TDataServer tds, const char varexpinput, const char varexpoutput, Option_t option="")
	Default constructor.

	TSensitivity (URANIE::DataServer::TDataServer tds, URANIE::Launcher::TCode code, Int_t ns, Option_t *option="")
	Default constructor with TCode arg.

	TSensitivity (URANIE::DataServer::TDataServer tds, URANIE::Relauncher::TRun run, Int_t ns, Option_t *option="")
	Default constructor with TRun arg.

virtual	~TSensitivity ()
	Default destructor.

Int_t	getID ()

virtual TTree *	getResultTuple (bool commonresulttuple=true)
	Get the result ntuple (default parameter unused but for Morris method)

double	getValue (const char sorder="", const char sinputname="", const char *sselect="")

vector< int > *	getAttributeElements (string str)

void	setFunction (void(fct)(Double_t , Double_t *), Int_t nx=-1, Int_t ny=1)

TString	getFunctionName ()

void	setSeed (UInt_t nval)

UInt_t	getSeed ()

virtual void	setMethodName (const char *str)
	Set the Method name.

const char *	getMethodName ()
	Get the method name.

Bool_t	getNoIntermediateSaved ()
	Get the noIntermediateSaved flag.

const char *	getIteratorName ()
	Get the name of the iterator attribut of the method.

void	setSensitivityIteratorName (const char *str)
	Set the iterator name devoted to compute sensitivity indexes.

void	setTimeName (TString sname)
	Set the name of the time attribute (only one)

TString	getTimeName ()
	Get the name of the time attribute.

virtual void	setDrawProgressBar (Bool_t bbool=kTRUE)
	Set the "draw progress bar" flag.

void	setUsingErrors (bool thebool)
	Set the "using error results anyway" option.

Bool_t	getDrawProgressBar ()
	Get the clean flag.

Bool_t	isInputCorrelated ()

TMatrixD	getMatrixInputCorrelation ()

Int_t	getNInput ()
	Get the number of input attributes.

Int_t	getNOutput ()
	Get the number of output attributes.

void	setInputCorrelationMatrix (TMatrixD Corr)

void	checkOutputRequested (string attlist, bool fromoption=false)
	Check the output list requested by the user.

void	computeIndexes (Option_t *option="")
	Compute the Sensitivity Indexes.

void	fillIndex (const char sinputname, const char sorder, Double_t dval, const char *algo="", Double_t dvalCILower=-1.0, Double_t dvalCIUpper=-1.0)
	Method to fill in the tree the value of Sensitivity indexes for an input attribute.

virtual void	drawIndexes (TString sTitre, const char select="", Option_t option="")
	Draws the indexes.

virtual void	setLog ()

void	unsetLog ()

void	changeLog ()

Bool_t	getLog ()

virtual void	printLog (Option_t *option="")

void	setNLauncher (ELauncher codeLauncher)

Public Attributes
Private and Public attributes
Bool_t	_bWithSample
	true if data are provided and used as full sample of 2 times ns samples

Bool_t	_bWithData
	true if data are provided and used as full sample of 2 times ns samples

ESamplerMethod	_nSamplerMethod
	The sampler method to generate the M and N matrix.

EMatrixMiNi	_nMatrixMiNi
	The method to generate the Min and/or Ni matrix (Sobol, Saltelli)

ESiAlgorithm	_nSiAlgorithm
	The algorithm to use to compute the first order algorithm.

EStiAlgorithm	_nStiAlgorithm
	The algorithm to use to compute the total order algorithm.

Method
The method needs two matrix M, N
Int_t	_nSimPerIndex
	The size of the two matrix M et N.

Int_t	_nMethodComputed
	number of method used

TMatrixD	_matM
	The matrix M.

TMatrixD	_matN
	The matrix M.

TEventList *	_telm

TEventList *	_teln
	m and n lit of event in the ntuple

TMatrixD	_valN

TMatrixD	_valM
	values of output for M and N matrix

TMatrixD	_valSi

TMatrixD	_valSti
	values of the first and total sobol indexes

TMatrixD	_valMeanMN

TMatrixD	_valSigmaMN
	complexe matrices to store the mean and variance of used M/N/Mi/Ni matrices

vector< double >	_valMeanYN

vector< double >	_valMeanYM

vector< double >	_valVarYN

vector< double >	_valVarYM

URANIE::DataServer::TDSNtupleD *	_withdatantp

URANIE::DataServer::TDSNtupleD *	_preloadedntp

int *	_useless

Public Attributes inherited from URANIE::Sensitivity::TSensitivity
URANIE::DataServer::TDataServer *	_tds
	Pointeur vers un TDS.

TList *	_listOfInputAttributes
	List of the input branches.

TList *	_listOfOutputAttributes
	List of the input branches.

TString	_sTimeAttribute
	The name of the Time attribute.

Int_t	_nS
	The number of simulation or other information depend on the used method.

Int_t	_nX
	Dimension of the input.

UInt_t	_nY
	Dimension of the target.

UInt_t	_nElY
	Number of element for one selected output.

Int_t	_nbOut
	Total number of Output to be considered.

Int_t	_iOut
	counter for output

unsigned int	_iy
	iterator over number of element

unsigned int	_iely
	iterator over number of element

ELauncher	_nLauncher
	The type of launcher.

TString	_sFunctionName
	The Name of the evaluatuor.

URANIE::Launcher::TCode *	_code
	The tcode.

URANIE::Relauncher::TRun *	_run

TObjArray *	_drawingGarbageCollector
	Garbage collector for prints.

Int_t	_nSeed
	The seed of the random generator.

Bool_t	_bChosenOutputs
	Fact that the input list is provided or not.

Bool_t	_blog
	Boolean for edit the log.

Bool_t	_bdrawProgressBar
	Boolean to know if the progress bar has to be drawn.

Bool_t	_bnoIntermediateSaved
	Boolean to know if the progress bar has to be drawn.

TString	_sIteratorName
	The specific iterator attribute for the method.

TString	_sMethodName
	The method name.

TString	_sSelectedOutput
	The output.

TString	_sSelectedInput
	The input.

map< string, unsigned int >	_mAttributeSize
	Map of size of element for attribute;.

map< string, vector< int > >	_mAttributeElements
	Map of Elements number to run (if vector subselection is requested)

vector< string >	_vOutputNames
	Name of the output.

TCanvas *	_canvas
	Canvas object to deal with.

void(*	_pFunction )(double , double )

TTree *	_ntresult
	The TTree of results.

Protected Member Functions
Visualization and Scan the data
void	initSample (Int_t ns, Option_t *option="")

Parse the option
virtual void	parseOption (Option_t *option="")
	Read option specific to TSobol.

void	preTreatment ()
	Resize matrices and fill many vector/matrice to avroid recompute stat too oftently.

Protected Member Functions inherited from URANIE::Sensitivity::TSensitivity
void	checkCanvasCreation (bool newcan)
	Create a canvas if needed.

void	drawIndexesHistogram (TString sTitre, const char select="", Option_t option="")
	Draws indexes with an histogram.

void	drawIndexesPie (TString sTitre, const char select="", Option_t option="")
	Draws indexes with an pie chart.

virtual void	postTreatment ()
	PostTreatment for every output.

void	setNoIntermediateSaved (Bool_t bbool=kTRUE)
	Set the "only final file" flag.

Additional Inherited Members
Protected Attributes inherited from URANIE::Sensitivity::TSensitivity
Char_t	_sOutputAttribute [MAXLENGTHSTRING]
	The name of the output attribute.

Char_t	_sInputAttribute [MAXLENGTHSTRING]
	The name of the input attribute.

Char_t	_sOrder [MAXLENGTHSTRING]
	The order of sensitivity indexes.

Char_t	_sMethod [MAXLENGTHSTRING]
	The name of the method.

Char_t	_sAlgorithm [MAXLENGTHSTRING]
	The name of the algorithm to compute the index.

Double_t	_valSobolCrt
	The value of sensitivity indexes.

Double_t	_valSobolCILower
	The value of lower Condidence Interval (95)

Double_t	_valSobolCIUpper
	The value of upper Condidence Interval (95)

TMatrixD	_minputCorr
	Input correlation matrix if sample needs to be correlated.

Bool_t	_bisInputCorrelated
	State whether the input correlation matrix is set.

Bool_t	_bgoingThroughError
	State whether the error must not block the computation.

Detailed Description

Description of the class TSobol.

To be written by the developper.

Member Enumeration Documentation

◆ EMatrixMiNi

enum URANIE::Sensitivity::TSobol::EMatrixMiNi

Enumerator
kMiNiSobol
kMiNiSaltelli

◆ ESamplerMethod

enum URANIE::Sensitivity::TSobol::ESamplerMethod

list Of Enum

Enumerator
kSRS
kLHS
kqMCSobol
kqMCHalton

◆ ESiAlgorithm

enum URANIE::Sensitivity::TSobol::ESiAlgorithm

Enumerator
kSiSobol93
kSiSaltelli02
kSiJansen99
kSiSumo10
kSiMartinez11
kSiOnlyNi
kSiAll

◆ EStiAlgorithm

enum URANIE::Sensitivity::TSobol::EStiAlgorithm

Enumerator
kStiHomma96
kStiSobol07
kStiJansen99
kStiSumo10
kStiMartinez11
kStiOnlyNi
kStiAll

Constructor & Destructor Documentation

◆ TSobol() [1/6]

URANIE::Sensitivity::TSobol::TSobol ( )

Default constructor.

Referenced by ClassImp().

◆ TSobol() [2/6]

URANIE::Sensitivity::TSobol::TSobol	(	URANIE::DataServer::TDataServer *	tds,
		void()(Double_t , Double_t *)	fcn,
		const char *	varexpinput,
		const char *	varexpoutput,
		Int_t	ns,
		Option_t *	option = `""`
	)

Default constructor with the TDataServer.

◆ TSobol() [3/6]

URANIE::Sensitivity::TSobol::TSobol	(	URANIE::DataServer::TDataServer *	tds,
		const char *	fcn,
		Int_t	ns,
		const char *	varexpinput,
		const char *	varexpoutput,
		Option_t *	option = `""`
	)

Default constructor with the TDataServer.

◆ TSobol() [4/6]

URANIE::Sensitivity::TSobol::TSobol	(	URANIE::DataServer::TDataServer *	tds,
		const char *	varexpinput,
		const char *	varexpoutput,
		Option_t *	option = `""`
	)

Default constructor with a TDataServer filling.

◆ TSobol() [5/6]

URANIE::Sensitivity::TSobol::TSobol	(	URANIE::DataServer::TDataServer *	tds,
		URANIE::Launcher::TCode *	fcode,
		Int_t	ns,
		Option_t *	option = `""`
	)

Default constructor with a tcode.

◆ TSobol() [6/6]

URANIE::Sensitivity::TSobol::TSobol	(	URANIE::DataServer::TDataServer *	tds,
		URANIE::Relauncher::TRun *	run,
		Int_t	ns,
		Option_t *	option = `""`
	)

Default constructor with a trun.

◆ ~TSobol()

virtual URANIE::Sensitivity::TSobol::~TSobol ( )

virtual

Default destructor.

Referenced by ClassImp().

Member Function Documentation

◆ createTuple()

void URANIE::Sensitivity::TSobol::createTuple ( Option_t * option = "" )

virtual

Reimplemented from URANIE::Sensitivity::TSensitivity.

Referenced by ClassImp().

◆ evaluateIndexes()

void URANIE::Sensitivity::TSobol::evaluateIndexes ( Option_t * option = "" )

virtual

Evaluates the index from a Specific TDataServer.

Implements URANIE::Sensitivity::TSensitivity.

Referenced by ClassImp().

◆ generateSample()

virtual void URANIE::Sensitivity::TSobol::generateSample ( Option_t * option = "" )

virtual

Generates all the matrix of sample.

Implements URANIE::Sensitivity::TSensitivity.

Referenced by ClassImp().

◆ initForRun()

void URANIE::Sensitivity::TSobol::initForRun ( Option_t * option )

Referenced by ClassImp().

◆ initSample()

void URANIE::Sensitivity::TSobol::initSample	(	Int_t	ns,
		Option_t *	option = `""`
	)

protected

Referenced by ClassImp().

◆ loadOtherSobolFile()

void URANIE::Sensitivity::TSobol::loadOtherSobolFile ( const char * filename )

Referenced by ClassImp().

◆ parseOption()

virtual void URANIE::Sensitivity::TSobol::parseOption ( Option_t * option = "" )

protectedvirtual

Read option specific to TSobol.

Possible options specific to this methods are

"srs": generate sample with SRS
"lhs": generate sample with LHS
"qmc=sobol": generate sample with QMC=SOBOL
"qmc=halton": generate sample with QMC=HALTON
"sobol/saltelli": use either the solbol or saltelli implementation (the second one is the default)

Reimplemented from URANIE::Sensitivity::TSensitivity.

Referenced by ClassImp().

◆ preTreatment()

void URANIE::Sensitivity::TSobol::preTreatment ( )

protectedvirtual

Resize matrices and fill many vector/matrice to avroid recompute stat too oftently.

@namePreTreatment

Reimplemented from URANIE::Sensitivity::TSensitivity.

Referenced by ClassImp().

◆ printLog()

virtual void URANIE::Sensitivity::TSobol::printLog ( )

virtual

Referenced by ClassImp().

Member Data Documentation

◆ _bWithData

Bool_t URANIE::Sensitivity::TSobol::_bWithData

true if data are provided and used as full sample of 2 times ns samples

Referenced by ClassImp().

◆ _bWithSample

Bool_t URANIE::Sensitivity::TSobol::_bWithSample

true if data are provided and used as full sample of 2 times ns samples

Referenced by ClassImp().

◆ _matM

TMatrixD URANIE::Sensitivity::TSobol::_matM

The matrix M.

Referenced by ClassImp().

◆ _matN

TMatrixD URANIE::Sensitivity::TSobol::_matN

The matrix M.

Referenced by ClassImp().

◆ _nMatrixMiNi

EMatrixMiNi URANIE::Sensitivity::TSobol::_nMatrixMiNi

The method to generate the Min and/or Ni matrix (Sobol, Saltelli)

Referenced by ClassImp().

◆ _nMethodComputed

Int_t URANIE::Sensitivity::TSobol::_nMethodComputed

number of method used

Referenced by ClassImp().

◆ _nSamplerMethod

ESamplerMethod URANIE::Sensitivity::TSobol::_nSamplerMethod

The sampler method to generate the M and N matrix.

Referenced by ClassImp().

◆ _nSiAlgorithm

ESiAlgorithm URANIE::Sensitivity::TSobol::_nSiAlgorithm

The algorithm to use to compute the first order algorithm.

Referenced by ClassImp().

◆ _nSimPerIndex

Int_t URANIE::Sensitivity::TSobol::_nSimPerIndex

The size of the two matrix M et N.

Referenced by ClassImp().

◆ _nStiAlgorithm

EStiAlgorithm URANIE::Sensitivity::TSobol::_nStiAlgorithm

The algorithm to use to compute the total order algorithm.

Referenced by ClassImp().

◆ _preloadedntp

URANIE::DataServer::TDSNtupleD* URANIE::Sensitivity::TSobol::_preloadedntp

Referenced by ClassImp().

◆ _telm

TEventList* URANIE::Sensitivity::TSobol::_telm

Referenced by ClassImp().

◆ _teln

TEventList * URANIE::Sensitivity::TSobol::_teln

m and n lit of event in the ntuple

Referenced by ClassImp().

◆ _useless

int* URANIE::Sensitivity::TSobol::_useless

◆ _valM

TMatrixD URANIE::Sensitivity::TSobol::_valM

values of output for M and N matrix

Referenced by ClassImp().

◆ _valMeanMN

TMatrixD URANIE::Sensitivity::TSobol::_valMeanMN

Referenced by ClassImp().

◆ _valMeanYM

vector<double> URANIE::Sensitivity::TSobol::_valMeanYM

Referenced by ClassImp().

◆ _valMeanYN

vector<double> URANIE::Sensitivity::TSobol::_valMeanYN

Referenced by ClassImp().

◆ _valN

TMatrixD URANIE::Sensitivity::TSobol::_valN

Referenced by ClassImp().

◆ _valSi

TMatrixD URANIE::Sensitivity::TSobol::_valSi

Referenced by ClassImp().

◆ _valSigmaMN

TMatrixD URANIE::Sensitivity::TSobol::_valSigmaMN

complexe matrices to store the mean and variance of used M/N/Mi/Ni matrices

Referenced by ClassImp().

◆ _valSti

TMatrixD URANIE::Sensitivity::TSobol::_valSti

values of the first and total sobol indexes

Referenced by ClassImp().

◆ _valVarYM

vector<double> URANIE::Sensitivity::TSobol::_valVarYM

Referenced by ClassImp().

◆ _valVarYN

vector<double> URANIE::Sensitivity::TSobol::_valVarYN

Referenced by ClassImp().

◆ _withdatantp

URANIE::DataServer::TDSNtupleD* URANIE::Sensitivity::TSobol::_withdatantp

Referenced by ClassImp().

Documentation / Developer's manual

Available modules

Public Types

Public Member Functions

Public Attributes

Protected Member Functions

Additional Inherited Members

Detailed Description

Member Enumeration Documentation

◆ EMatrixMiNi

◆ ESamplerMethod

◆ ESiAlgorithm

◆ EStiAlgorithm

Constructor & Destructor Documentation

◆ TSobol() [1/6]

◆ TSobol() [2/6]

◆ TSobol() [3/6]

◆ TSobol() [4/6]

◆ TSobol() [5/6]

◆ TSobol() [6/6]

◆ ~TSobol()

Member Function Documentation

◆ createTuple()

◆ evaluateIndexes()

◆ generateSample()

◆ initForRun()

◆ initSample()

◆ loadOtherSobolFile()

◆ parseOption()

◆ preTreatment()

◆ printLog()

Member Data Documentation

◆ _bWithData

◆ _bWithSample

◆ _matM

◆ _matN

◆ _nMatrixMiNi

◆ _nMethodComputed

◆ _nSamplerMethod

◆ _nSiAlgorithm

◆ _nSimPerIndex

◆ _nStiAlgorithm

◆ _preloadedntp

◆ _telm

◆ _teln

◆ _useless

◆ _valM

◆ _valMeanMN

◆ _valMeanYM

◆ _valMeanYN

◆ _valN

◆ _valSi

◆ _valSigmaMN

◆ _valSti

◆ _valVarYM

◆ _valVarYN

◆ _withdatantp