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Uranie / Calibration v4.9.0
/* @license-end */
TLinearBayesian.h
Go to the documentation of this file.
1
2// Copyright (C) 2013-2024 CEA/DES
3//
4// This program is free software: you can redistribute it and/or modify
5// it under the terms of the GNU Lesser General Public License as published
6// by the Free Software Foundation, either version 3 of the License, or any
7// later version.
8//
9// This program is distributed in the hope that it will be useful,
10// but WITHOUT ANY WARRANTY; without even the implied warranty of
11// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
12// GNU Lesser General Public License for more details.
13//
14// You should have received a copy of the GNU Lesser General Public License
15// along with this program. If not, see <http://www.gnu.org/licenses/>.
17// TLinearBayesian
19// $Id$
20// $Author$
21// $Date$
22// $Revision$
23// $State$
25
42#ifndef TLINEARBAYESIAN_H
43#define TLINEARBAYESIAN_H
44
45// Uranie
46#include "TCalibration.h"
47
48namespace URANIE
49{
50namespace Calibration
51{
52
54
55protected:
56
57 void (*_fTransfoParam)(double *, double*);
58 vector<double> _aPrioriMode;
59
60 TMatrixD _mParCovariance;
61 TMatrixD _mParValues;
63
64 TMatrixD _mH;
65 vector<string> _vRegName;
66 string _regname;
67public:
68
69 //---------------------------------------------
73
75
82 TLinearBayesian(URANIE::DataServer::TDataServer *tds, URANIE::Relauncher::TRun *run, Int_t ns=1, Option_t * option = "");
83
92 TLinearBayesian(URANIE::DataServer::TDataServer *tds, void (*fcn)(Double_t*,Double_t*), const char *varexpinput, const char *varexpoutput, int ns = 1, Option_t * option = "");
93
102 TLinearBayesian(URANIE::DataServer::TDataServer *tds, const char *fcn, const char *varexpinput, const char *varexpoutput, int ns = 1, Option_t * option = "");
103
110 TLinearBayesian(URANIE::DataServer::TDataServer *tds, URANIE::Launcher::TCode *fcode, int ns = 1, const char *option = "");
111
115
116
117 //---------------------------------------------
121
129 void computePredictionVariance(URANIE::DataServer::TDataServer *tds_new, string outname);
131
132
133 //---------------------------------------------
137
145 void setParameterTransformationFunction( void (*fTransfoParam)(double *, double*)){ _fTransfoParam = fTransfoParam; }
146
150 void setRegressorName(const char *regName);
151
165 void setDistanceAndReference(const char *funcName, URANIE::DataServer::TDataServer *tdsRef, const char *input, const char *output, const char *weight="");
166
175 void setDistanceAndReference(URANIE::Calibration::TDistanceFunction *distFunc, URANIE::DataServer::TDataServer *tdsRef, const char *input, const char *output, const char *weight="");
176
181
186
191
193
194 //---------------------------------------------
198
211 void drawParameters(TString sTitre, const char *variable = "*", const char *select = "1>0", Option_t * option = "");
212
216 void printLog(Option_t *option = "");
217
219
220protected:
221 void computeParameters(Option_t *option="");
226
227 ClassDef(URANIE::Calibration::TLinearBayesian, ID_CALIBRATION)
228
229
230};
231
232} // Fin du namespace Calibration
233} // Fin du namespace URANIE
234
235#endif
Interface of class URANIE::Calibration::TCalibration.
Description of the class TCalibration.
Definition TCalibration.h:64
Description of the class TDistanceFunction.
Definition TDistanceFunction.h:68
Description of the class TLinearBayesian.
Definition TLinearBayesian.h:53
TMatrixD _mH
Regressor matrix.
Definition TLinearBayesian.h:64
TMatrixD getParameterValueMatrix()
get the matrix of parameter values
Definition TLinearBayesian.h:180
void setDistanceAndReference(URANIE::Calibration::TDistanceFunction *distFunc, URANIE::DataServer::TDataServer *tdsRef, const char *input, const char *output, const char *weight="")
Set the distance function and some needed informations.
TLinearBayesian(URANIE::DataServer::TDataServer *tds, URANIE::Launcher::TCode *fcode, int ns=1, const char *option="")
Default Calibration constructor with the code argument: it contains the assessor to be used.
void printLog(Option_t *option="")
dump content
TLinearBayesian(URANIE::DataServer::TDataServer *tds, const char *fcn, const char *varexpinput, const char *varexpoutput, int ns=1, Option_t *option="")
Default Calibration constructor with the function argument: it contains the assessor to be used.
void computeParameters(Option_t *option="")
internal method in which the estimation is performed for all inheriting classes
void setRegressorName(const char *regName)
Set the regressor matrix by providing the variables to be extracted from tdsObs.
TMatrixD _mTransfoParValues
Parametres matrix.
Definition TLinearBayesian.h:62
TLinearBayesian(URANIE::DataServer::TDataServer *tds, void(*fcn)(Double_t *, Double_t *), const char *varexpinput, const char *varexpoutput, int ns=1, Option_t *option="")
Default Calibration constructor with the function argument: it contains the assessor to be used.
void(* _fTransfoParam)(double *, double *)
Parameter transformation function.
Definition TLinearBayesian.h:57
void setParameterTransformationFunction(void(*fTransfoParam)(double *, double *))
Set parameter transformation function Sometimes the calibration is performed on transformed variables...
Definition TLinearBayesian.h:145
TMatrixD getTransfParameterValueMatrix()
get the matrix of parameter values
Definition TLinearBayesian.h:185
string _regname
regressor name
Definition TLinearBayesian.h:66
vector< double > _aPrioriMode
A priori modes of the laws.
Definition TLinearBayesian.h:58
void setDistanceAndReference(const char *funcName, URANIE::DataServer::TDataServer *tdsRef, const char *input, const char *output, const char *weight="")
Set the distance function and some needed informations.
vector< string > _vRegName
Regressor names.
Definition TLinearBayesian.h:65
void drawParameters(TString sTitre, const char *variable="*", const char *select="1>0", Option_t *option="")
TMatrixD _mParCovariance
Parameters covariance matrix.
Definition TLinearBayesian.h:60
void computePredictionVariance(URANIE::DataServer::TDataServer *tds_new, string outname)
Set parameter transformation function Sometimes the calibration is performed on transformed variables...
TMatrixD getParameterCovarianceMatrix()
get the matrix of parameter covariances
Definition TLinearBayesian.h:190
TMatrixD _mParValues
Parametres matrix.
Definition TLinearBayesian.h:61
TLinearBayesian(URANIE::DataServer::TDataServer *tds, URANIE::Relauncher::TRun *run, Int_t ns=1, Option_t *option="")
Default constructor with TRun arg.
virtual ~TLinearBayesian()
Default destructor.
Definition TABC.cxx:46