Description of the class TMorris. More...

#include <TMorris.h>

Inheritance diagram for URANIE::Sensitivity::TMorris:

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Collaboration diagram for URANIE::Sensitivity::TMorris:

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Public Member Functions
Constructor and Destructor
	TMorris (URANIE::DataServer::TDataServer tds, const char fcn, Int_t nReplique, Int_t level, Double_t delta=0, TString sout="")
	Default constructor with the name of a function.

	TMorris (URANIE::DataServer::TDataServer tds, void(fcn)(Double_t , Double_t ), TString sin, TString sout, Int_t nReplique, Int_t level, Double_t delta=0)
	Default constructor with a function.

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

	TMorris (URANIE::DataServer::TDataServer tds, URANIE::Launcher::TCode fcode, Int_t nReplique, Int_t level, Double_t delta=0)
	Default constructor with a tcode.

	TMorris (URANIE::DataServer::TDataServer tds, URANIE::Relauncher::TRun run, Int_t nReplique, Int_t level, Double_t delta=0)
	Default constructor with a trun.

	~TMorris ()
	Default destructor.

Setting and Getting attributs
URANIE::DataServer::TDSNtupleD *	getMorrisResults ()
	Get Morris results.

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

void	setLevel (Int_t val)
	Sets the level.

Int_t	getLevel ()
	Gets the level.

void	setDelta (Double_t val)
	Sets the delta.

Double_t	getDelta ()
	Gets the delta.

Int_t	getNReplica ()
	Gets the number of replica.

Generation of the sample
virtual void	generateSample (Option_t *option="")

void	computeOrientationMatrixOld ()
	Computes the orientation matrix $B^{\star}$ .

void	computeOrientationMatrix ()

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

void	preTreatment ()
	PreTreatment for every output.

visualization and Scan the data
virtual void	createTuple ()

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

void	drawSample (TString svar="", Int_t nreplique=0, Option_t *option="")

void	drawIndexes (Option_t *option="", bool internalCall=kFALSE)

void	drawIndexesAll (Option_t *option="")

void	pyDrawIndexes (Option_t *option="")

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

Public Member Functions inherited from URANIE::Sensitivity::TScreeming
	TScreeming (URANIE::DataServer::TDataServer tds, const char fcn, Int_t ns=-1, const char varexpinput="", const char varexpoutput="")
	Default constructor with the name of a function.

	TScreeming (URANIE::DataServer::TDataServer tds, void(fcn)(Double_t , Double_t ), const char varexpinput, const char varexpoutput, Int_t ns=-1)

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

	TScreeming (URANIE::DataServer::TDataServer tds, URANIE::Launcher::TCode code, Int_t ns=100)
	Default constructor with TCode arg.

	TScreeming (URANIE::DataServer::TDataServer tds, URANIE::Relauncher::TRun code, Int_t ns=100)
	Default constructor with TRun arg.

virtual	~TScreeming ()
	Default destructor.

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 ()

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 Member Functions
void	stdInit ()
	constructor helpers

Private Attributes
Double_t	_delta
	The Delta parameter.

Int_t	_level
	The level parameter (known as p)

TMatrixD	_matB

TVectorD	_vecDirection
	Matrix of $B^{\star}$ .

TNtupleD *	_ntdatamorris
	Vector of direction.

URANIE::DataServer::TDSNtupleD *	_ntmorrisresult
	The tntuple of result $(\mu, \sigma)$ .

TRandom2 *	_rand

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

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 TMorris.

The method recommended by Morris (1991) is valid for p even, and the value for $\Delta$ is given by the relation

$\Delta = \frac{p}{2(p-1)}$

where is the level.

The number for the code evaluation is given by the relation

$n_{evak} = r * ( n_X + 1 )$

Using TMorris class inside a script

This is the use of TMorris class. For a generic documentation, please refer to the section Using the TSensitivity class.

TMorris * scmo = new TMorris(tds, function, replique, level);
TMorris * scmo = new TMorris(tds, TCode, replique, level);



scmo->generateSample();
scmo->computeIndexes();
scmo->drawIndexes("ddpie", "", "nonewcanv,pie,first");
ntsampl->Print();

Constructor & Destructor Documentation

◆ TMorris() [1/5]

URANIE::Sensitivity::TMorris::TMorris	(	URANIE::DataServer::TDataServer *	tds,
		const char *	fcn,
		Int_t	nReplique,
		Int_t	level,
		Double_t	delta = `0`,
		TString	sout = `""`
	)

Default constructor with the name of a function.

Referenced by ClassImp().

◆ TMorris() [2/5]

URANIE::Sensitivity::TMorris::TMorris	(	URANIE::DataServer::TDataServer *	tds,
		void()(Double_t , Double_t *)	fcn,
		TString	sin,
		TString	sout,
		Int_t	nReplique,
		Int_t	level,
		Double_t	delta = `0`
	)

Default constructor with a function.

◆ TMorris() [3/5]

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

Default constructor with a TDataServer filling.

◆ TMorris() [4/5]

URANIE::Sensitivity::TMorris::TMorris	(	URANIE::DataServer::TDataServer *	tds,
		URANIE::Launcher::TCode *	fcode,
		Int_t	nReplique,
		Int_t	level,
		Double_t	delta = `0`
	)

Default constructor with a tcode.

◆ TMorris() [5/5]

URANIE::Sensitivity::TMorris::TMorris	(	URANIE::DataServer::TDataServer *	tds,
		URANIE::Relauncher::TRun *	run,
		Int_t	nReplique,
		Int_t	level,
		Double_t	delta = `0`
	)

Default constructor with a trun.

◆ ~TMorris()

URANIE::Sensitivity::TMorris::~TMorris ( )

Default destructor.

Referenced by ClassImp().

Member Function Documentation

◆ computeOrientationMatrix()

void URANIE::Sensitivity::TMorris::computeOrientationMatrix ( )

Referenced by ClassImp().

◆ computeOrientationMatrixOld()

void URANIE::Sensitivity::TMorris::computeOrientationMatrixOld ( )

Computes the orientation matrix $B^{\star}$ .

algorithme

The matrix $\tilde{B} =$ dï¿½fined in the paper of Morris is computed

Warning: the author underlines the fact that the column of the matrix colonne is either the matrix of B, or the column of B by replacing the 0 by 1 or reciprocally the 1 by 0. Thus, we can even compute $\Delta \tilde{B}$ .

Referenced by ClassImp().

◆ createTuple()

virtual void URANIE::Sensitivity::TMorris::createTuple ( )

virtual

Referenced by ClassImp().

◆ drawIndexes() [1/2]

void URANIE::Sensitivity::TMorris::drawIndexes	(	Option_t *	option = `""`,
		bool	internalCall = `kFALSE`
	)

◆ drawIndexes() [2/2]

virtual void URANIE::Sensitivity::TMorris::drawIndexes	(	TString	sTitre,
		const char *	select = `""`,
		Option_t *	option = `""`,
		bool	internalCall = `kFALSE`
	)

virtual

Draws the indexes.

Referenced by ClassImp().

◆ drawIndexesAll()

void URANIE::Sensitivity::TMorris::drawIndexesAll ( Option_t * option = "" )

Referenced by ClassImp().

◆ drawSample()

void URANIE::Sensitivity::TMorris::drawSample	(	TString	svar = `""`,
		Int_t	nreplique = `0`,
		Option_t *	option = `""`
	)

Referenced by ClassImp().

◆ evaluateIndexes()

void URANIE::Sensitivity::TMorris::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()

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

virtual

Implements URANIE::Sensitivity::TSensitivity.

Referenced by ClassImp().

◆ getDelta()

Double_t URANIE::Sensitivity::TMorris::getDelta ( )

inline

Gets the delta.

References _delta.

◆ getLevel()

Int_t URANIE::Sensitivity::TMorris::getLevel ( )

inline

Gets the level.

References _level.

◆ getMorrisResults()

URANIE::DataServer::TDSNtupleD * URANIE::Sensitivity::TMorris::getMorrisResults ( )

inline

Get Morris results.

References _ntmorrisresult.

◆ getNReplica()

Int_t URANIE::Sensitivity::TMorris::getNReplica ( )

inline

Gets the number of replica.

References URANIE::Sensitivity::TSensitivity::_nS.

◆ getResultTuple()

TTree * URANIE::Sensitivity::TMorris::getResultTuple ( bool commonresulttuple = false )

virtual

Get the result ntuple (default parameter unused but for Morris method)

Reimplemented from URANIE::Sensitivity::TSensitivity.

Referenced by ClassImp().

◆ preTreatment()

void URANIE::Sensitivity::TMorris::preTreatment ( )

virtual

PreTreatment for every output.

Doing a pre-treatment when running over outputs.

Reimplemented from URANIE::Sensitivity::TSensitivity.

Referenced by ClassImp().

◆ printLog()

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

virtual

Reimplemented from URANIE::Sensitivity::TScreeming.

Referenced by ClassImp().

◆ pyDrawIndexes()

void URANIE::Sensitivity::TMorris::pyDrawIndexes ( Option_t * option = "" )

Referenced by ClassImp().

◆ setDelta()

void URANIE::Sensitivity::TMorris::setDelta ( Double_t val )

inline

Sets the delta.

References _delta.

◆ setLevel()

void URANIE::Sensitivity::TMorris::setLevel ( Int_t val )

inline

Sets the level.

References _level.

◆ stdInit()

void URANIE::Sensitivity::TMorris::stdInit ( )

private

constructor helpers

Referenced by ClassImp().

Member Data Documentation

◆ _delta

Double_t URANIE::Sensitivity::TMorris::_delta

private

The Delta parameter.

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

◆ _level

Int_t URANIE::Sensitivity::TMorris::_level

private

The level parameter (known as p)

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

◆ _matB

TMatrixD URANIE::Sensitivity::TMorris::_matB

private

Referenced by ClassImp().

◆ _ntdatamorris

TNtupleD* URANIE::Sensitivity::TMorris::_ntdatamorris

private

Vector of direction.

The tntuple of data

Referenced by ClassImp().

◆ _ntmorrisresult

URANIE::DataServer::TDSNtupleD* URANIE::Sensitivity::TMorris::_ntmorrisresult

private

The tntuple of result $(\mu, \sigma)$ .

Referenced by ClassImp(), and getMorrisResults().

◆ _rand

TRandom2* URANIE::Sensitivity::TMorris::_rand

private

Referenced by ClassImp().

◆ _vecDirection

TVectorD URANIE::Sensitivity::TMorris::_vecDirection

private

Matrix of $B^{\star}$ .

Referenced by ClassImp().

Documentation / Manuel développeur

Modules disponibles

Public Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Using TMorris class inside a script

Constructor & Destructor Documentation

◆ TMorris() [1/5]

◆ TMorris() [2/5]

◆ TMorris() [3/5]

◆ TMorris() [4/5]

◆ TMorris() [5/5]

◆ ~TMorris()

Member Function Documentation

◆ computeOrientationMatrix()

◆ computeOrientationMatrixOld()

algorithme

◆ createTuple()

◆ drawIndexes() [1/2]

◆ drawIndexes() [2/2]

◆ drawIndexesAll()

◆ drawSample()

◆ evaluateIndexes()

◆ generateSample()

◆ getDelta()

◆ getLevel()

◆ getMorrisResults()

◆ getNReplica()

◆ getResultTuple()

◆ preTreatment()

◆ printLog()

◆ pyDrawIndexes()

◆ setDelta()

◆ setLevel()

◆ stdInit()

Member Data Documentation

◆ _delta

◆ _level

◆ _matB

◆ _ntdatamorris

◆ _ntmorrisresult

◆ _rand

◆ _vecDirection