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",
124 "InnovationAtCurrentState",
125 "JacobianMatrixAtBackground",
126 "JacobianMatrixAtOptimum",
127 "KalmanGainAtOptimum",
128 "MahalanobisConsistency",
132 "SimulatedObservationAtBackground",
133 "SimulatedObservationAtCurrentOptimum",
134 "SimulatedObservationAtCurrentState",
135 "SimulatedObservationAtOptimum",
136 "SimulationQuantiles",
140 ``{"StoreSupplementaryCalculations":["BMA", "CurrentState"]}``
142 .. include:: snippets/Variant_3DVAR.rst
144 .. ------------------------------------ ..
145 .. include:: snippets/Header2Algo04.rst
147 .. include:: snippets/Analysis.rst
149 .. include:: snippets/CostFunctionJ.rst
151 .. include:: snippets/CostFunctionJb.rst
153 .. include:: snippets/CostFunctionJo.rst
155 .. ------------------------------------ ..
156 .. include:: snippets/Header2Algo05.rst
158 .. include:: snippets/Analysis.rst
160 .. include:: snippets/APosterioriCorrelations.rst
162 .. include:: snippets/APosterioriCovariance.rst
164 .. include:: snippets/APosterioriStandardDeviations.rst
166 .. include:: snippets/APosterioriVariances.rst
168 .. include:: snippets/BMA.rst
170 .. include:: snippets/CostFunctionJ.rst
172 .. include:: snippets/CostFunctionJAtCurrentOptimum.rst
174 .. include:: snippets/CostFunctionJb.rst
176 .. include:: snippets/CostFunctionJbAtCurrentOptimum.rst
178 .. include:: snippets/CostFunctionJo.rst
180 .. include:: snippets/CostFunctionJoAtCurrentOptimum.rst
182 .. include:: snippets/CurrentIterationNumber.rst
184 .. include:: snippets/CurrentOptimum.rst
186 .. include:: snippets/CurrentState.rst
188 .. include:: snippets/IndexOfOptimum.rst
190 .. include:: snippets/Innovation.rst
192 .. include:: snippets/InnovationAtCurrentState.rst
194 .. include:: snippets/JacobianMatrixAtBackground.rst
196 .. include:: snippets/JacobianMatrixAtOptimum.rst
198 .. include:: snippets/KalmanGainAtOptimum.rst
200 .. include:: snippets/MahalanobisConsistency.rst
202 .. include:: snippets/OMA.rst
204 .. include:: snippets/OMB.rst
206 .. include:: snippets/SigmaObs2.rst
208 .. include:: snippets/SimulatedObservationAtBackground.rst
210 .. include:: snippets/SimulatedObservationAtCurrentOptimum.rst
212 .. include:: snippets/SimulatedObservationAtCurrentState.rst
214 .. include:: snippets/SimulatedObservationAtOptimum.rst
216 .. include:: snippets/SimulationQuantiles.rst
218 .. ------------------------------------ ..
219 .. include:: snippets/Header2Algo09.rst
221 .. include:: scripts/simple_3DVAR.rst
223 .. literalinclude:: scripts/simple_3DVAR.py
225 .. include:: snippets/Header2Algo10.rst
227 .. literalinclude:: scripts/simple_3DVAR.res
229 .. ------------------------------------ ..
230 .. include:: snippets/Header2Algo06.rst
232 - :ref:`section_ref_algorithm_Blue`
233 - :ref:`section_ref_algorithm_ExtendedBlue`
234 - :ref:`section_ref_algorithm_LinearityTest`
236 .. ------------------------------------ ..
237 .. include:: snippets/Header2Algo07.rst