Description of the class TRegression. More...

#include <TRegression.h>

Inheritance diagram for URANIE::Sensitivity::TRegression:

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Collaboration diagram for URANIE::Sensitivity::TRegression:

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Public Types
enum	EMethod { kSRC , kSRRC , kPCC , kPRCC , kUnknown }

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

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

	TRegression (URANIE::DataServer::TDataServer tds, const char varexpinput, const char varexpoutput, Option_t option="src")
	Default constructor with the TDataServer.

virtual	~TRegression ()
	Default destructor.

Setter and Getter for the method
void	setMethod (EMethod nmethod)
	Sets the method.

void	clearMethod ()
	Clear the method index.

int	getMethod ()
	Gets the transform function.

Generation of the sample
In this case, there is noting to do
void	generateSample (Option_t *option="")

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

void	preTreatment ()
	PreTreatment for every output.

void	getUncertaintyFromRhoTransformation (double &rho, double &CImin, double &CImax)
	Compute the CI from the rho estimation (handmade)

Getters/Setters
Double_t	getR2 ()
	get the coefficient of determination R2

Double_t	getR2A ()
	get the adjuested coefficient of determination R2A

Double_t	getSumOfSquareIndexes ()
	Get the sum of square indexes.

Printing Log
virtual void	printLog (Option_t *option="")

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)

virtual void	parseOption (Option_t *option="")
	Read the possible options.

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	createTuple (Option_t *option="")

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

virtual void	setLog ()

void	unsetLog ()

void	changeLog ()

Bool_t	getLog ()

void	setNLauncher (ELauncher codeLauncher)

Private Attributes
int	_nMethod
	The type of method. Changed to int for convenience (see setMethod)

Double_t	_dr2
	The R2 define by the formula.

Double_t	_dr2A
	The R2A define by the formula.

Double_t	_dSumOfSquareIndexes
	The sum of square indexes $\sum_{i} S_i^2$ .

TMatrixD	_mmatCorr
	Matrix of correlation to be used for coefficient calculation.

TMatrixD	_mmatCorrRank
	Matrix of rank correlation to be used for coefficient calculation.

URANIE::DataServer::UMessageLogger *	_fLogger
	Message logger.

TString	_sCompleteMethod

URANIE::DataServer::TDataServer *	_fake

Additional Inherited Members
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 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.

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 TRegression.

To be written by the developper.

Member Enumeration Documentation

◆ EMethod

enum URANIE::Sensitivity::TRegression::EMethod

Enumerator
kSRC
kSRRC
kPCC
kPRCC
kUnknown

Constructor & Destructor Documentation

◆ TRegression() [1/2]

URANIE::Sensitivity::TRegression::TRegression ( )

Default constructor.

Referenced by ClassImp().

◆ TRegression() [2/2]

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

Default constructor with the TDataServer.

◆ ~TRegression()

virtual URANIE::Sensitivity::TRegression::~TRegression ( )

virtual

Default destructor.

Referenced by ClassImp().

Member Function Documentation

◆ clearMethod()

void URANIE::Sensitivity::TRegression::clearMethod ( )

inline

Clear the method index.

References _nMethod.

◆ evaluateIndexes()

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

virtual

Evaluates the index from a Specific TDataServer.

The TDS must contain an attribute Name + "n__iter__sobol" with values

-1 : for the M matrix
0 : for the N matrix
ix+1 : for the matrix Mi
100*_nX+ ix+1 : for the matrix Ni

Parameters

option (Option_t *) option to pass [""]

Implements URANIE::Sensitivity::TSensitivity.

Referenced by ClassImp().

◆ generateSample()

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

inlinevirtual

Implements URANIE::Sensitivity::TSensitivity.

◆ getMethod()

int URANIE::Sensitivity::TRegression::getMethod ( )

inline

Gets the transform function.

References _nMethod.

◆ getR2()

Double_t URANIE::Sensitivity::TRegression::getR2 ( )

inline

get the coefficient of determination R2

References _dr2.

◆ getR2A()

Double_t URANIE::Sensitivity::TRegression::getR2A ( )

inline

get the adjuested coefficient of determination R2A

References _dr2A.

◆ getSumOfSquareIndexes()

Double_t URANIE::Sensitivity::TRegression::getSumOfSquareIndexes ( )

inline

Get the sum of square indexes.

the returned parameter is define by the formula

$\sum_{i=1}^{nX}{\alpha_i^2}$

References _dSumOfSquareIndexes.

◆ getUncertaintyFromRhoTransformation()

void URANIE::Sensitivity::TRegression::getUncertaintyFromRhoTransformation	(	double &	rho,
		double &	CImin,
		double &	CImax
	)

Compute the CI from the rho estimation (handmade)

Referenced by ClassImp().

◆ preTreatment()

void URANIE::Sensitivity::TRegression::preTreatment ( )

virtual

PreTreatment for every output.

Doing a pre-treatment when running over outputs.

Reimplemented from URANIE::Sensitivity::TSensitivity.

Referenced by ClassImp().

◆ printLog()

virtual void URANIE::Sensitivity::TRegression::printLog ( Option_t * option = "" )

virtual

Reimplemented from URANIE::Sensitivity::TSensitivity.

Referenced by ClassImp().

◆ setMethod()

void URANIE::Sensitivity::TRegression::setMethod ( EMethod nmethod )

inline

Sets the method.

The _nMethod is now a int so that one can ask for several calculation at the same time Possibilities are now: SRC, SRRC, PCC and PRCC

References _nMethod.

Member Data Documentation

◆ _dr2

Double_t URANIE::Sensitivity::TRegression::_dr2

private

The R2 define by the formula.

Referenced by ClassImp(), and getR2().

◆ _dr2A

Double_t URANIE::Sensitivity::TRegression::_dr2A

private

The R2A define by the formula.

Referenced by ClassImp(), and getR2A().

◆ _dSumOfSquareIndexes

Double_t URANIE::Sensitivity::TRegression::_dSumOfSquareIndexes

private

The sum of square indexes $\sum_{i} S_i^2$ .

Referenced by ClassImp(), and getSumOfSquareIndexes().

◆ _fake

URANIE::DataServer::TDataServer* URANIE::Sensitivity::TRegression::_fake

private

Referenced by ClassImp().

◆ _fLogger

URANIE::DataServer::UMessageLogger* URANIE::Sensitivity::TRegression::_fLogger

private

Message logger.

Referenced by ClassImp().

◆ _mmatCorr

TMatrixD URANIE::Sensitivity::TRegression::_mmatCorr

private

Matrix of correlation to be used for coefficient calculation.

Referenced by ClassImp().

◆ _mmatCorrRank

TMatrixD URANIE::Sensitivity::TRegression::_mmatCorrRank

private

Matrix of rank correlation to be used for coefficient calculation.

Referenced by ClassImp().

◆ _nMethod

int URANIE::Sensitivity::TRegression::_nMethod

private

The type of method. Changed to int for convenience (see setMethod)

Referenced by ClassImp(), clearMethod(), getMethod(), and setMethod().

◆ _sCompleteMethod

TString URANIE::Sensitivity::TRegression::_sCompleteMethod

private

Referenced by ClassImp().

Documentation / Manuel développeur

Modules disponibles

Public Types

Public Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Member Enumeration Documentation

◆ EMethod

Constructor & Destructor Documentation

◆ TRegression() [1/2]

◆ TRegression() [2/2]

◆ ~TRegression()

Member Function Documentation

◆ clearMethod()

◆ evaluateIndexes()

◆ generateSample()

◆ getMethod()

◆ getR2()

◆ getR2A()

◆ getSumOfSquareIndexes()

◆ getUncertaintyFromRhoTransformation()

◆ preTreatment()

◆ printLog()

◆ setMethod()

Member Data Documentation

◆ _dr2

◆ _dr2A

◆ _dSumOfSquareIndexes

◆ _fake

◆ _fLogger

◆ _mmatCorr

◆ _mmatCorrRank

◆ _nMethod

◆ _sCompleteMethod