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Uranie / Sensitivity v4.9.0
/* @license-end */
URANIE::Sensitivity::TJohnsonRW Class Reference

Description of the class TJohnsonRW. More...

#include <TJohnsonRW.h>

Inheritance diagram for URANIE::Sensitivity::TJohnsonRW:
Collaboration diagram for URANIE::Sensitivity::TJohnsonRW:

Public Member Functions

Constructor and Destructor
 TJohnsonRW ()
 Default constructor.
 
 TJohnsonRW (URANIE::DataServer::TDataServer *tds, const char *varexpinput, const char *varexpoutput, Option_t *option="")
 Default constructor with the TDataServer.
 
 TJohnsonRW (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.
 
 TJohnsonRW (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 a pointer to a function.
 
 TJohnsonRW (URANIE::DataServer::TDataServer *tds, URANIE::Launcher::TCode *code, Int_t ns, Option_t *option="")
 Default constructor with TCode arg.
 
 TJohnsonRW (URANIE::DataServer::TDataServer *tds, URANIE::Relauncher::TRun *run, Int_t ns, Option_t *option="")
 Default constructor with TRun arg.
 
virtual ~TJohnsonRW ()
 Default destructor.
 
Parse the option
void parseOption (Option_t *option="")
 Read option specific to TJohnsonRW.
 
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.
 
Getters/Setters
Double_t getR2 ()
 get the coefficient of determination R2
 
Double_t getR2A ()
 get the adjuested coefficient of determination R2A
 
void setCorrelationMatrix (TMatrixD corrMat)
 Set the correlation matrix by hand.
 
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)
 
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

Double_t _dr2
 The R2 define by the formula.
 
Double_t _dr2A
 The R2A define by the formula.
 
bool _busingCorr
 compute the weight from the correlation matrix.
 
bool _bmatCorrSet
 Set the correlation matrix by hand, not using empirical one;.
 
bool _busingSample
 Using a sample provided by fileDataRead.
 
TString _sSampMethod
 The sampling method.
 
TMatrixD _mmatCorr
 Matrix of correlation to be used for coefficient calculation.
 
TMatrixD _mRxxInv
 Inverse input correlation matrix from SVD.
 
TMatrixD _mLambda
 Lambda matrix from Johnson method.
 
TMatrixD _mBetanoY
 Beta matrix from Johnson method up to final output multiplication.
 
int _localYCounter
 Local counter to know how many outputs there are.
 

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 TJohnsonRW.

To be written by the developper.

Constructor & Destructor Documentation

◆ TJohnsonRW() [1/6]

URANIE::Sensitivity::TJohnsonRW::TJohnsonRW ( )

Default constructor.

Referenced by ClassImp().

◆ TJohnsonRW() [2/6]

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

Default constructor with the TDataServer.

◆ TJohnsonRW() [3/6]

URANIE::Sensitivity::TJohnsonRW::TJohnsonRW ( 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.

◆ TJohnsonRW() [4/6]

URANIE::Sensitivity::TJohnsonRW::TJohnsonRW ( 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 a pointer to a function.

◆ TJohnsonRW() [5/6]

URANIE::Sensitivity::TJohnsonRW::TJohnsonRW ( URANIE::DataServer::TDataServer *  tds,
URANIE::Launcher::TCode *  code,
Int_t  ns,
Option_t *  option = "" 
)

Default constructor with TCode arg.

◆ TJohnsonRW() [6/6]

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

Default constructor with TRun arg.

◆ ~TJohnsonRW()

virtual URANIE::Sensitivity::TJohnsonRW::~TJohnsonRW ( )
virtual

Default destructor.

Referenced by ClassImp().

Member Function Documentation

◆ evaluateIndexes()

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

Implements URANIE::Sensitivity::TSensitivity.

Referenced by ClassImp().

◆ getR2()

Double_t URANIE::Sensitivity::TJohnsonRW::getR2 ( )
inline

get the coefficient of determination R2

References _dr2.

◆ getR2A()

Double_t URANIE::Sensitivity::TJohnsonRW::getR2A ( )
inline

get the adjuested coefficient of determination R2A

References _dr2A.

◆ parseOption()

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

Read option specific to TJohnsonRW.

Possible options specific to this methods are

  • "regressors": the computation is done on regressors instead of covariance matrix

Reimplemented from URANIE::Sensitivity::TSensitivity.

Referenced by ClassImp().

◆ preTreatment()

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

Reimplemented from URANIE::Sensitivity::TSensitivity.

Referenced by ClassImp().

◆ setCorrelationMatrix()

void URANIE::Sensitivity::TJohnsonRW::setCorrelationMatrix ( TMatrixD  corrMat)

Set the correlation matrix by hand.

Referenced by ClassImp().

Member Data Documentation

◆ _bmatCorrSet

bool URANIE::Sensitivity::TJohnsonRW::_bmatCorrSet
private

Set the correlation matrix by hand, not using empirical one;.

Referenced by ClassImp().

◆ _busingCorr

bool URANIE::Sensitivity::TJohnsonRW::_busingCorr
private

compute the weight from the correlation matrix.

Referenced by ClassImp().

◆ _busingSample

bool URANIE::Sensitivity::TJohnsonRW::_busingSample
private

Using a sample provided by fileDataRead.

Referenced by ClassImp().

◆ _dr2

Double_t URANIE::Sensitivity::TJohnsonRW::_dr2
private

The R2 define by the formula.

Referenced by ClassImp(), and getR2().

◆ _dr2A

Double_t URANIE::Sensitivity::TJohnsonRW::_dr2A
private

The R2A define by the formula.

Referenced by ClassImp(), and getR2A().

◆ _localYCounter

int URANIE::Sensitivity::TJohnsonRW::_localYCounter
private

Local counter to know how many outputs there are.

Referenced by ClassImp().

◆ _mBetanoY

TMatrixD URANIE::Sensitivity::TJohnsonRW::_mBetanoY
private

Beta matrix from Johnson method up to final output multiplication.

Referenced by ClassImp().

◆ _mLambda

TMatrixD URANIE::Sensitivity::TJohnsonRW::_mLambda
private

Lambda matrix from Johnson method.

Referenced by ClassImp().

◆ _mmatCorr

TMatrixD URANIE::Sensitivity::TJohnsonRW::_mmatCorr
private

Matrix of correlation to be used for coefficient calculation.

Referenced by ClassImp().

◆ _mRxxInv

TMatrixD URANIE::Sensitivity::TJohnsonRW::_mRxxInv
private

Inverse input correlation matrix from SVD.

Referenced by ClassImp().

◆ _sSampMethod

TString URANIE::Sensitivity::TJohnsonRW::_sSampMethod
private

The sampling method.

Referenced by ClassImp().