2 Copyright (C) 2008-2021 EDF R&D
4 This file is part of SALOME ADAO module.
6 This library is free software; you can redistribute it and/or
7 modify it under the terms of the GNU Lesser General Public
8 License as published by the Free Software Foundation; either
9 version 2.1 of the License, or (at your option) any later version.
11 This library is distributed in the hope that it will be useful,
12 but WITHOUT ANY WARRANTY; without even the implied warranty of
13 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
14 Lesser General Public License for more details.
16 You should have received a copy of the GNU Lesser General Public
17 License along with this library; if not, write to the Free Software
18 Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
20 See http://www.salome-platform.org/ or email : webmaster.salome@opencascade.com
22 Author: Jean-Philippe Argaud, jean-philippe.argaud@edf.fr, EDF R&D
24 .. index:: single: 3DVAR
25 .. index:: single: 3D-Var
26 .. _section_ref_algorithm_3DVAR:
28 Algorithme de calcul "*3DVAR*"
29 ------------------------------
31 .. ------------------------------------ ..
32 .. include:: snippets/Header2Algo01.rst
34 Cet algorithme réalise une estimation d'état par minimisation variationnelle de
35 la fonctionnelle :math:`J` d'écart classique en assimilation de données
38 .. math:: J(\mathbf{x})=(\mathbf{x}-\mathbf{x}^b)^T.\mathbf{B}^{-1}.(\mathbf{x}-\mathbf{x}^b)+(\mathbf{y}^o-H(\mathbf{x}))^T.\mathbf{R}^{-1}.(\mathbf{y}^o-H(\mathbf{x}))
40 qui est usuellement désignée comme la fonctionnelle "*3D-Var*" (voir par
41 exemple [Talagrand97]_). Les dénominations "*3D-Var*", "*3D-VAR*" et "*3DVAR*"
44 Il existe diverses variantes de cet algorithme. On propose ici des formulations stables et robustes suivantes :
48 pair: Variant ; 3DVAR-VAN
49 pair: Variant ; 3DVAR-Incr
50 pair: Variant ; 3DVAR-PSAS
52 - "3DVAR" (3D Variational analysis, voir [Lorenc86]_, [LeDimet86]_, [Talagrand97]_), algorithme d'origine et très robuste,
53 - "3DVAR-VAN" (3D Variational Analysis with No inversion of B, voir [Lorenc88]_), algorithme similaire mais permettant d'éviter l'inversion de la matrice de covariance B,
54 - "3DVAR-Incr" (Incremental 3DVAR, voir [Courtier94]_), algorithme plus économique mais impliquant une approximation des opérateurs non-linéaires,
55 - "3DVAR-PSAS" (Physical-space Statistical Analysis Scheme for 3DVAR, voir [Courtier97]_, [Cohn98]_), algorithme parfois plus économique car opérant dans un autre espace, mais impliquant une approximation des opérateurs non-linéaires.
57 On recommande d'utiliser le 3DVAR d'origine.
59 .. ------------------------------------ ..
60 .. include:: snippets/Header2Algo02.rst
62 .. include:: snippets/Background.rst
64 .. include:: snippets/BackgroundError.rst
66 .. include:: snippets/Observation.rst
68 .. include:: snippets/ObservationError.rst
70 .. include:: snippets/ObservationOperator.rst
72 .. ------------------------------------ ..
73 .. include:: snippets/Header2Algo03AdOp.rst
75 .. include:: snippets/BoundsWithNone.rst
77 .. include:: snippets/CostDecrementTolerance.rst
79 .. include:: snippets/GradientNormTolerance.rst
81 .. include:: snippets/InitializationPoint.rst
83 .. include:: snippets/MaximumNumberOfSteps.rst
85 .. include:: snippets/Minimizer_xDVAR.rst
87 .. include:: snippets/NumberOfSamplesForQuantiles.rst
89 .. include:: snippets/ProjectedGradientTolerance.rst
91 .. include:: snippets/Quantiles.rst
93 .. include:: snippets/SetSeed.rst
95 .. include:: snippets/SimulationForQuantiles.rst
97 StoreSupplementaryCalculations
98 .. index:: single: StoreSupplementaryCalculations
100 *Liste de noms*. Cette liste indique les noms des variables supplémentaires
101 qui peuvent être disponibles au cours du déroulement ou à la fin de
102 l'algorithme, si elles sont initialement demandées par l'utilisateur. Cela
103 implique potentiellement des calculs ou du stockage coûteux. La valeur par
104 défaut est une liste vide, aucune de ces variables n'étant calculée et
105 stockée par défaut sauf les variables inconditionnelles. Les noms possibles
106 sont dans la liste suivante : [
108 "APosterioriCorrelations",
109 "APosterioriCovariance",
110 "APosterioriStandardDeviations",
111 "APosterioriVariances",
114 "CostFunctionJAtCurrentOptimum",
116 "CostFunctionJbAtCurrentOptimum",
118 "CostFunctionJoAtCurrentOptimum",
119 "CurrentIterationNumber",
125 "InnovationAtCurrentState",
126 "JacobianMatrixAtBackground",
127 "JacobianMatrixAtOptimum",
128 "KalmanGainAtOptimum",
129 "MahalanobisConsistency",
133 "SimulatedObservationAtBackground",
134 "SimulatedObservationAtCurrentOptimum",
135 "SimulatedObservationAtCurrentState",
136 "SimulatedObservationAtOptimum",
137 "SimulationQuantiles",
141 ``{"StoreSupplementaryCalculations":["BMA", "CurrentState"]}``
143 .. include:: snippets/Variant_3DVAR.rst
145 .. ------------------------------------ ..
146 .. include:: snippets/Header2Algo04.rst
148 .. include:: snippets/Analysis.rst
150 .. include:: snippets/CostFunctionJ.rst
152 .. include:: snippets/CostFunctionJb.rst
154 .. include:: snippets/CostFunctionJo.rst
156 .. ------------------------------------ ..
157 .. include:: snippets/Header2Algo05.rst
159 .. include:: snippets/Analysis.rst
161 .. include:: snippets/APosterioriCorrelations.rst
163 .. include:: snippets/APosterioriCovariance.rst
165 .. include:: snippets/APosterioriStandardDeviations.rst
167 .. include:: snippets/APosterioriVariances.rst
169 .. include:: snippets/BMA.rst
171 .. include:: snippets/CostFunctionJ.rst
173 .. include:: snippets/CostFunctionJAtCurrentOptimum.rst
175 .. include:: snippets/CostFunctionJb.rst
177 .. include:: snippets/CostFunctionJbAtCurrentOptimum.rst
179 .. include:: snippets/CostFunctionJo.rst
181 .. include:: snippets/CostFunctionJoAtCurrentOptimum.rst
183 .. include:: snippets/CurrentIterationNumber.rst
185 .. include:: snippets/CurrentOptimum.rst
187 .. include:: snippets/CurrentState.rst
189 .. include:: snippets/ForecastState.rst
191 .. include:: snippets/IndexOfOptimum.rst
193 .. include:: snippets/Innovation.rst
195 .. include:: snippets/InnovationAtCurrentState.rst
197 .. include:: snippets/JacobianMatrixAtBackground.rst
199 .. include:: snippets/JacobianMatrixAtOptimum.rst
201 .. include:: snippets/KalmanGainAtOptimum.rst
203 .. include:: snippets/MahalanobisConsistency.rst
205 .. include:: snippets/OMA.rst
207 .. include:: snippets/OMB.rst
209 .. include:: snippets/SigmaObs2.rst
211 .. include:: snippets/SimulatedObservationAtBackground.rst
213 .. include:: snippets/SimulatedObservationAtCurrentOptimum.rst
215 .. include:: snippets/SimulatedObservationAtCurrentState.rst
217 .. include:: snippets/SimulatedObservationAtOptimum.rst
219 .. include:: snippets/SimulationQuantiles.rst
221 .. ------------------------------------ ..
222 .. include:: snippets/Header2Algo09.rst
224 .. include:: scripts/simple_3DVAR.rst
226 .. literalinclude:: scripts/simple_3DVAR.py
228 .. include:: snippets/Header2Algo10.rst
230 .. literalinclude:: scripts/simple_3DVAR.res
232 .. ------------------------------------ ..
233 .. include:: snippets/Header2Algo06.rst
235 - :ref:`section_ref_algorithm_Blue`
236 - :ref:`section_ref_algorithm_ExtendedBlue`
237 - :ref:`section_ref_algorithm_LinearityTest`
239 .. ------------------------------------ ..
240 .. include:: snippets/Header2Algo07.rst