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Uranie / Optimizer v4.9.0
/* @license-end */
URANIE::Optimizer::TBestEstimate Class Reference

Description of the class TBestEstimate. More...

#include <TBestEstimate.h>

Inheritance diagram for URANIE::Optimizer::TBestEstimate:
Collaboration diagram for URANIE::Optimizer::TBestEstimate:

Public Member Functions

Constructor and Destructor
 TBestEstimate ()
 Empty constructor.
 
 TBestEstimate (Int_t nParam, TMatrixD a, Int_t nResp, TMatrixD m, TMatrixD r, TMatrixD ca, TMatrixD cm, TMatrixD s, TMatrixD car)
 Constructor with only matrices.
 
 TBestEstimate (TDataServer *tdsParam, TDataServer *tdsMeasures, TDataServer *tdsResponses, TMatrixD sMatrix, TMatrixD carMatrix)
 Constructor with a user given sensitivity matrix.
 
 TBestEstimate (TDataServer *tdsParam, TDataServer *tdsMeasures, TDataServer *tdsResponses, TDataServer *tdsOATSampling, TMatrixD carMatrix)
 Constructor with results of an OAT design instead of a sensitivity matrix.
 
virtual ~TBestEstimate ()
 Default destructor.
 
Set/Get parameters
void setParameterData (TDataServer *tds)
 
TDataServer * getParameterData ()
 
void setMeasureData (TDataServer *tds)
 
TDataServer * getMeasureData ()
 
void setResponseData (TDataServer *tds)
 
TDataServer * getResponseData ()
 
void setOATSamplingData (TDataServer *tds)
 
TDataServer * getOATSamplingData ()
 
void setSensitivityMatrix (TMatrixD matrix)
 
TMatrixD getSensitivityMatrix ()
 
void setParameterResponseCovMatrix (TMatrixD matrix)
 
TMatrixD getParameterResponseCovMatrix ()
 
TMatrixD getParameterMatrix ()
 
TMatrixD getMeasureMatrix ()
 
TMatrixD getResponseMatrix ()
 
TMatrixD getParameterCovMatrix ()
 
TMatrixD getMeasureCovMatrix ()
 
TMatrixD getResponsesCovMatrix ()
 
TMatrixD getDifferencesCovMatrix ()
 
TMatrixD getBestEstParameterMatrix ()
 
TMatrixD getBestEstResponseMatrix ()
 
TMatrixD getBestEstParameterCovMatrix ()
 
TMatrixD getBestEstResponsesCovMatrix ()
 
TMatrixD getBestEstParameterResponsesCovMatrix ()
 
Double_t getChi2 ()
 
Double_t getConsistencyMeasure ()
 
Int_t getNInputParameter ()
 
Int_t getNResponses ()
 
Int_t getNTimeStepsInputParameter ()
 
Int_t getNTimeStepsResponses ()
 
Other functions
void buildMatrices ()
 
void buildSensitivityMatrix ()
 
void runBestEstimate ()
 
Printing Log
void setLog ()
 Print the state of the algorithm of optimization.
 
void unsetLog ()
 
void changeLog ()
 
Bool_t getLog ()
 
virtual void printLog (Option_t *option="")
 

Private Attributes

Bool_t _blog
 
TDataServer * _tdsParam
 
TDataServer * _tdsResp
 
TDataServer * _tdsMeas
 
TDataServer * _tdsOAT
 
Int_t _nParam
 
Int_t _nResp
 
Int_t _nParamTimeSteps
 
Int_t _nRespTimeSteps
 
TMatrixD _a
 
TMatrixD _m
 
TMatrixD _r
 
TMatrixD _ca
 
TMatrixD _cm
 
TMatrixD _car
 
TMatrixD _s
 
TMatrixD _d
 
TMatrixD _cr
 
TMatrixD _cd
 
TMatrixD _aBE
 
TMatrixD _rBE
 
TMatrixD _caBE
 
TMatrixD _crBE
 
TMatrixD _carBE
 
Double_t _chi2
 

Detailed Description

Description of the class TBestEstimate.

To be written by the developper.

Constructor & Destructor Documentation

◆ TBestEstimate() [1/4]

URANIE::Optimizer::TBestEstimate::TBestEstimate ( )

Empty constructor.

Referenced by ClassImp().

◆ TBestEstimate() [2/4]

URANIE::Optimizer::TBestEstimate::TBestEstimate ( Int_t  nParam,
TMatrixD  a,
Int_t  nResp,
TMatrixD  m,
TMatrixD  r,
TMatrixD  ca,
TMatrixD  cm,
TMatrixD  s,
TMatrixD  car 
)

Constructor with only matrices.

This constructor receives all the necessary matrices as parameters

Parameters
nParam(Int_t) number of input parameters.
a(TMatrixD) the matrix containing the nominal values of the parameters.
nResp(Int_t) number of responses.
m(TMatrixD) the matrix containing the measured responses.
r(TMatrixD) the matrix containing the computed responses.
ca(TMatrixD) the covariance matrix of the parameters.
cm(TMatrixD) the covariance matrix of the measured responses.
s(TMatrixD) the matrix containing the sensitivities of the computed repsonses to each parameter.
car(TMatrixD) the matrix of the correlation between parameters and responses.

◆ TBestEstimate() [3/4]

URANIE::Optimizer::TBestEstimate::TBestEstimate ( TDataServer *  tdsParam,
TDataServer *  tdsMeasures,
TDataServer *  tdsResponses,
TMatrixD  sMatrix,
TMatrixD  carMatrix 
)

Constructor with a user given sensitivity matrix.

This constructor receives a user given sensitivity matrix.

Parameters
tdsParam(URANIE::DataServer::TDataServer*) the data server containing the nominal values of the parameters and their covariance matrix, if any.
tdsMeasures(URANIE::DataServer::TDataServer*) the data server containing the measured (experimental) responses and their covariance matrix, if any.
tdsResponses(URANIE::DataServer::TDataServer*) the data server containing the computed responses.
sMatrix(TMatrixD) the matrix containing the sensitivities of the computed repsonses to each parameter.
carMatrix(TMatrixD) the matrix of the correlation between parameters and responses.

◆ TBestEstimate() [4/4]

URANIE::Optimizer::TBestEstimate::TBestEstimate ( TDataServer *  tdsParam,
TDataServer *  tdsMeasures,
TDataServer *  tdsResponses,
TDataServer *  tdsOATSampling,
TMatrixD  carMatrix 
)

Constructor with results of an OAT design instead of a sensitivity matrix.

This constructor receives a user given tds with the results of an OAT sampling to build the sensitivity matrix. This is necessary when dealing with time dependent model parameters and responses.

Parameters
tdsParam(URANIE::DataServer::TDataServer*) the data server containing the nominal values of the parameters and their covariance matrix, if any.
tdsMeasures(URANIE::DataServer::TDataServer*) the data server containing the measured (experimental) responses and their covariance matrix, if any.
tdsResponses(URANIE::DataServer::TDataServer*) the data server containing the computed responses.
tdsOATSampling(URANIE::DataServer::TDataServer*) the data server containing the results of an OAT sampling on time dependent parameters and responses. The sensitivity matrix will be constructed from it.
carMatrix(TMatrixD) the matrix of the correlation between parameters and responses.

◆ ~TBestEstimate()

virtual URANIE::Optimizer::TBestEstimate::~TBestEstimate ( )
virtual

Default destructor.

Referenced by ClassImp().

Member Function Documentation

◆ buildMatrices()

void URANIE::Optimizer::TBestEstimate::buildMatrices ( )

Referenced by ClassImp().

◆ buildSensitivityMatrix()

void URANIE::Optimizer::TBestEstimate::buildSensitivityMatrix ( )

Referenced by ClassImp().

◆ changeLog()

void URANIE::Optimizer::TBestEstimate::changeLog ( )
inline

References _blog.

◆ getBestEstParameterCovMatrix()

TMatrixD URANIE::Optimizer::TBestEstimate::getBestEstParameterCovMatrix ( )
inline

References _caBE.

◆ getBestEstParameterMatrix()

TMatrixD URANIE::Optimizer::TBestEstimate::getBestEstParameterMatrix ( )
inline

References _aBE.

◆ getBestEstParameterResponsesCovMatrix()

TMatrixD URANIE::Optimizer::TBestEstimate::getBestEstParameterResponsesCovMatrix ( )
inline

References _carBE.

◆ getBestEstResponseMatrix()

TMatrixD URANIE::Optimizer::TBestEstimate::getBestEstResponseMatrix ( )
inline

References _rBE.

◆ getBestEstResponsesCovMatrix()

TMatrixD URANIE::Optimizer::TBestEstimate::getBestEstResponsesCovMatrix ( )
inline

References _crBE.

◆ getChi2()

Double_t URANIE::Optimizer::TBestEstimate::getChi2 ( )
inline

References _chi2.

◆ getConsistencyMeasure()

Double_t URANIE::Optimizer::TBestEstimate::getConsistencyMeasure ( )
inline

References _chi2, _nResp, and _nRespTimeSteps.

◆ getDifferencesCovMatrix()

TMatrixD URANIE::Optimizer::TBestEstimate::getDifferencesCovMatrix ( )
inline

References _cd.

◆ getLog()

Bool_t URANIE::Optimizer::TBestEstimate::getLog ( )
inline

References _blog.

◆ getMeasureCovMatrix()

TMatrixD URANIE::Optimizer::TBestEstimate::getMeasureCovMatrix ( )
inline

References _cm.

◆ getMeasureData()

TDataServer * URANIE::Optimizer::TBestEstimate::getMeasureData ( )
inline

References _tdsMeas.

◆ getMeasureMatrix()

TMatrixD URANIE::Optimizer::TBestEstimate::getMeasureMatrix ( )
inline

References _m.

◆ getNInputParameter()

Int_t URANIE::Optimizer::TBestEstimate::getNInputParameter ( )
inline

References _nParam.

◆ getNResponses()

Int_t URANIE::Optimizer::TBestEstimate::getNResponses ( )
inline

References _nResp.

◆ getNTimeStepsInputParameter()

Int_t URANIE::Optimizer::TBestEstimate::getNTimeStepsInputParameter ( )
inline

References _nParamTimeSteps.

◆ getNTimeStepsResponses()

Int_t URANIE::Optimizer::TBestEstimate::getNTimeStepsResponses ( )
inline

References _nRespTimeSteps.

◆ getOATSamplingData()

TDataServer * URANIE::Optimizer::TBestEstimate::getOATSamplingData ( )
inline

References _tdsOAT.

◆ getParameterCovMatrix()

TMatrixD URANIE::Optimizer::TBestEstimate::getParameterCovMatrix ( )
inline

References _ca.

◆ getParameterData()

TDataServer * URANIE::Optimizer::TBestEstimate::getParameterData ( )
inline

References _tdsParam.

◆ getParameterMatrix()

TMatrixD URANIE::Optimizer::TBestEstimate::getParameterMatrix ( )
inline

References _a.

◆ getParameterResponseCovMatrix()

TMatrixD URANIE::Optimizer::TBestEstimate::getParameterResponseCovMatrix ( )
inline

References _car.

◆ getResponseData()

TDataServer * URANIE::Optimizer::TBestEstimate::getResponseData ( )
inline

References _tdsResp.

◆ getResponseMatrix()

TMatrixD URANIE::Optimizer::TBestEstimate::getResponseMatrix ( )
inline

References _r.

◆ getResponsesCovMatrix()

TMatrixD URANIE::Optimizer::TBestEstimate::getResponsesCovMatrix ( )
inline

References _cr.

◆ getSensitivityMatrix()

TMatrixD URANIE::Optimizer::TBestEstimate::getSensitivityMatrix ( )
inline

References _s.

◆ printLog()

virtual void URANIE::Optimizer::TBestEstimate::printLog ( Option_t *  option = "")
virtual

Referenced by ClassImp().

◆ runBestEstimate()

void URANIE::Optimizer::TBestEstimate::runBestEstimate ( )

Referenced by ClassImp().

◆ setLog()

void URANIE::Optimizer::TBestEstimate::setLog ( )
inline

Print the state of the algorithm of optimization.

References _blog.

◆ setMeasureData()

void URANIE::Optimizer::TBestEstimate::setMeasureData ( TDataServer *  tds)

Referenced by ClassImp().

◆ setOATSamplingData()

void URANIE::Optimizer::TBestEstimate::setOATSamplingData ( TDataServer *  tds)

Referenced by ClassImp().

◆ setParameterData()

void URANIE::Optimizer::TBestEstimate::setParameterData ( TDataServer *  tds)

Referenced by ClassImp().

◆ setParameterResponseCovMatrix()

void URANIE::Optimizer::TBestEstimate::setParameterResponseCovMatrix ( TMatrixD  matrix)

Referenced by ClassImp().

◆ setResponseData()

void URANIE::Optimizer::TBestEstimate::setResponseData ( TDataServer *  tds)

Referenced by ClassImp().

◆ setSensitivityMatrix()

void URANIE::Optimizer::TBestEstimate::setSensitivityMatrix ( TMatrixD  matrix)

Referenced by ClassImp().

◆ unsetLog()

void URANIE::Optimizer::TBestEstimate::unsetLog ( )
inline

References _blog.

Member Data Documentation

◆ _a

TMatrixD URANIE::Optimizer::TBestEstimate::_a
private

Referenced by ClassImp(), and getParameterMatrix().

◆ _aBE

TMatrixD URANIE::Optimizer::TBestEstimate::_aBE
private

◆ _blog

Bool_t URANIE::Optimizer::TBestEstimate::_blog
private

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

◆ _ca

TMatrixD URANIE::Optimizer::TBestEstimate::_ca
private

Referenced by ClassImp(), and getParameterCovMatrix().

◆ _caBE

TMatrixD URANIE::Optimizer::TBestEstimate::_caBE
private

◆ _car

TMatrixD URANIE::Optimizer::TBestEstimate::_car
private

◆ _carBE

TMatrixD URANIE::Optimizer::TBestEstimate::_carBE
private

◆ _cd

TMatrixD URANIE::Optimizer::TBestEstimate::_cd
private

◆ _chi2

Double_t URANIE::Optimizer::TBestEstimate::_chi2
private

◆ _cm

TMatrixD URANIE::Optimizer::TBestEstimate::_cm
private

Referenced by ClassImp(), and getMeasureCovMatrix().

◆ _cr

TMatrixD URANIE::Optimizer::TBestEstimate::_cr
private

Referenced by ClassImp(), and getResponsesCovMatrix().

◆ _crBE

TMatrixD URANIE::Optimizer::TBestEstimate::_crBE
private

◆ _d

TMatrixD URANIE::Optimizer::TBestEstimate::_d
private

Referenced by ClassImp().

◆ _m

TMatrixD URANIE::Optimizer::TBestEstimate::_m
private

Referenced by ClassImp(), and getMeasureMatrix().

◆ _nParam

Int_t URANIE::Optimizer::TBestEstimate::_nParam
private

Referenced by ClassImp(), and getNInputParameter().

◆ _nParamTimeSteps

Int_t URANIE::Optimizer::TBestEstimate::_nParamTimeSteps
private

◆ _nResp

Int_t URANIE::Optimizer::TBestEstimate::_nResp
private

◆ _nRespTimeSteps

Int_t URANIE::Optimizer::TBestEstimate::_nRespTimeSteps
private

◆ _r

TMatrixD URANIE::Optimizer::TBestEstimate::_r
private

Referenced by ClassImp(), and getResponseMatrix().

◆ _rBE

TMatrixD URANIE::Optimizer::TBestEstimate::_rBE
private

◆ _s

TMatrixD URANIE::Optimizer::TBestEstimate::_s
private

Referenced by ClassImp(), and getSensitivityMatrix().

◆ _tdsMeas

TDataServer* URANIE::Optimizer::TBestEstimate::_tdsMeas
private

Referenced by ClassImp(), and getMeasureData().

◆ _tdsOAT

TDataServer* URANIE::Optimizer::TBestEstimate::_tdsOAT
private

Referenced by ClassImp(), and getOATSamplingData().

◆ _tdsParam

TDataServer* URANIE::Optimizer::TBestEstimate::_tdsParam
private

Referenced by ClassImp(), and getParameterData().

◆ _tdsResp

TDataServer* URANIE::Optimizer::TBestEstimate::_tdsResp
private

Referenced by ClassImp(), and getResponseData().