TGaussianSampling.h

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// Copyright (C) 2013-2024 CEA/DES
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU Lesser General Public License as published
// by the Free Software Foundation, either version 3 of the License, or any
// later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// GNU Lesser General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public License
// along with this program. If not, see <http://www.gnu.org/licenses/>.
// $Id$
// $Author$
// $Date$
// $Revision$
// $State$

#ifndef TGAUSSIANSAMPLING_H
#define TGAUSSIANSAMPLING_H

#ifndef ROOT_TMatrixD
#include "TMatrixD.h"
#endif
#ifndef ROOT_TVectorD
#include "TVectorD.h"
#endif
#ifndef ROOT_TNtuple
#include "TNtuple.h"
#endif
#ifndef ROOT_TString
#include "TString.h"
#endif
#ifndef ROOT_TNtupleD
#include "TNtupleD.h"
#endif
#ifndef ROOT_TNamed
#include "TNamed.h"
#endif

// Uranie
#include "TSamplerStochastic.h"
#include "TAttribute.h"
#include "TStochAttribut.h"
#include "TDataServer.h"

namespace URANIE
{
namespace Sampler
{
class TGaussianSampling: public TSamplerStochastic
{
    // Associations

    // Attributes
public:
    enum EType
    {
        kLHS, kSRS, kUnknown
    };
    TMatrixD _corrmatrix;           
    TMatrixD _covmatrix;            
    EType _ntype;                

    // Operations
private:
    void splitMatrixVarCoVar(TMatrixD matVarCovar, TVectorD vecOfUnit,
                             TMatrixD &matVarCovar0, TMatrixD &matVarCovar1, TMatrixD &matVarCovar01);

    void generatenStandardPoints(TMatrixD &matPoints);
    TString _sIteratorNameNo;        
    TString _sIteratorNameNi;        

public:
    //---------------------------------------------

    TGaussianSampling(URANIE::DataServer::TDataServer *tds, Option_t *option =
            "lhs", Int_t nCalcul = 100);

    virtual ~TGaussianSampling();

    //---------------------------------------------
    virtual void init();
    virtual void terminate();

    //---------------------------------------------
    void generateSample(Option_t *option = "");

    void generateConditionalSample(TVectorD  vecOf01, Int_t no, Int_t ni);

    void setIteratorNameNo(TString sNameNo) {
        _sIteratorNameNo = sNameNo.Data();
    }

    void setIteratorNameNi(TString sNameNi) {
        _sIteratorNameNi = sNameNi.Data();
    }

    const char * getIteratorNameNo() {
        return _sIteratorNameNo.Data();
    }
    const char * getIteratorNameNi() {
        return _sIteratorNameNi.Data();
    }

    //---------------------------------------------

    void setUserCorrelation(Int_t indx, Int_t indy, double value);
    void setUserVarianceCovarianceMatrix(Int_t indx, Int_t indy, double value);


    void setUserCorrelation(TString xname, TString yname, double value);


    void setUserCorrelation(URANIE::DataServer::TAttribute *x,
            URANIE::DataServer::TAttribute *y, Double_t value);


    void setFixedSumCovariance(TString method = "simple");

    TMatrixD getCorrelationMatrix()
    {
        return _corrmatrix;
    }

    TMatrixD getCovarianceMatrix()
    {
        return _covmatrix;
    }

    //---------------------------------------------
    virtual void printLog(Option_t *option = "");

    ClassDef(URANIE::Sampler::TGaussianSampling, ID_SAMPLER)
    //Definition d'un plan d'experience
};

} // Fin du namespace Sampler
} // Fin du namespace URANIE
#endif
// fin du fichier $RCSfile$.