:ref:`section_ref_algorithm_ExtendedKalmanFilter` or the
:ref:`section_ref_algorithm_UnscentedKalmanFilter`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropNonLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
This residue must remain constantly equal to zero at the accuracy of the
calculation.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
each physical model, making the method not robust. For these reasons, this
method is not proposed nor recommended.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
entries themselves beforehand with the intended test
:ref:`section_ref_algorithm_InputValuesTest`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
augmented weighted least squares function, classically used in data
assimilation.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropNonLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
with or without weights. The default error function is the augmented weighted
least squares function, classically used in data assimilation.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropNonLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
linearity of the observation operator with the help of the
:ref:`section_ref_algorithm_LinearityTest`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
robust performance**, and the other algorithms (in this order) as means to
obtain a less costly data assimilation with (hopefully) the same quality.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelAlgorithm.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
commands to establish a set of error functional values :math:`J` from
observations :math:`\mathbf{y}^o`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelAlgorithm.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
initially provided by the user. To be explicit, unlike Kalman-type filters, the
state error covariance is not updated.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
conducted without any constraint (the variant is named "EKF", and it is not
recommended).
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
entries themselves beforehand with the intended test
:ref:`section_ref_algorithm_InputValuesTest`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
which has to remain stable until the calculation precision is reached.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
whole content of the variables read in printed form for verification (*warning,
if a variable is large in size, this can be difficult*).
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
.. centered::
**General scheme for using the algorithm**
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
can verify the linearity of the operators with the help of a
:ref:`section_ref_algorithm_LinearityTest`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
:ref:`section_ref_algorithm_ExtendedBlue` or a
:ref:`section_ref_algorithm_3DVAR`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
:math:`\alpha`, it is on this sub-domain that the linearity hypothesis of
:math:`F` is verified.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
linearized operator (or the tangent one) :math:`\mathbf{H}` of the
:math:`\mathcal{H}` near the chosen checking point.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
positioning, using the analysis variant "*lcEIM*" or "*lcDEIM*" for a
constrained positioning search.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelAlgorithm.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
In all cases, it is recommended to prefer a :ref:`section_ref_algorithm_3DVAR`
for its stability as for its behavior during optimization.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
entries themselves beforehand with the intended test
:ref:`section_ref_algorithm_InputValuesTest`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
that can be potentially observed. It is activated only on those who are
explicitly associated with the *observer* in its declaration.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
entries themselves beforehand with the intended test
:ref:`section_ref_algorithm_InputValuesTest`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelAlgorithm.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
the calculation of the function to be simulated is not too costly to avoid a
prohibitive optimization time length.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropNonLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelAlgorithm.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
which will allow to determine the model parameters that satisfy to the
quantiles conditions.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
Once the analysis is complete, a summary is displayed and, on request, a
graphical representation of the same information is produced.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
desired variable, the final saving through "*UserPostAnalysis*" or the
treatment during the calculation by well suited "*observer*".
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelAlgorithm.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
to exclude (hence the name *tabu*) the return to the last explored states.
Positions already explored are kept in a list of finite length.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropNonLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
:ref:`section_ref_algorithm_LinearityTest`), and the tangent is valid until the
calculation precision is reached.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
therefore be parallelized or distributed if the function to be simulated
supports this.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelAlgorithm.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
l':ref:`section_ref_algorithm_ExtendedKalmanFilter` ou
l':ref:`section_ref_algorithm_UnscentedKalmanFilter`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropNonLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
Ce résidu doit rester constamment égal à zéro à la précision du calcul.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
la méthode à chaque modèle physique, la rendant non robuste. Pour ces raisons,
cette méthode n'est donc pas proposée.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
vérifier préalablement les entrées elles-mêmes avec le test prévu
:ref:`section_ref_algorithm_InputValuesTest`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
fonctionnelle d'erreur par défaut est celle de moindres carrés pondérés
augmentés, classiquement utilisée en assimilation de données.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropNonLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
défaut est celle de moindres carrés pondérés augmentés, classiquement utilisée
en assimilation de données.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropNonLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
la linéarité de l'opérateur d'observation à l'aide de
l':ref:`section_ref_algorithm_LinearityTest`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
moyens pour obtenir une assimilation de données plus économique et de qualité
(éventuellement) similaire.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelAlgorithm.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
d'échantillonnage pour établir un ensemble de valeurs de fonctionnelle d'erreur
:math:`J` à partir d'observations :math:`\mathbf{y}^o`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelAlgorithm.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
explicite, contrairement aux filtres de type Kalman, la covariance d'erreurs
sur les états n'est pas remise à jour.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
défaut), ou être conduit sans aucune contrainte (cette variante est nommée
"EKF", et elle n'est pas recommandée).
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
vérifier préalablement les entrées elles-mêmes avec le test prévu
:ref:`section_ref_algorithm_InputValuesTest`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
qui doit rester constant jusqu'à ce que l'on atteigne la précision du calcul.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
si une variable est de grande taille, cette restitution peut être
informatiquement problématique*).
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
.. centered::
**Schéma général d'utilisation de l'algorithme**
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
supportent des bornes sur l'état, etc. On peut vérifier la linéarité des
opérateurs à l'aide d'un :ref:`section_ref_algorithm_LinearityTest`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
:ref:`section_ref_algorithm_ExtendedBlue` ou un
:ref:`section_ref_algorithm_3DVAR`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
l'incrément :math:`\alpha`, c'est sur cette partie que l'hypothèse de linéarité
de F est vérifiée.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
est l'opérateur linéarisé (ou opérateur tangent) :math:`\mathbf{H}` de
:math:`\mathcal{H}` autour du point de vérification choisi.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
positionnement des mesures, en utilisant le variant "*lcEIM*" ou "*lcDEIM*"
d'analyse pour une recherche de positionnement contraint.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelAlgorithm.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
:ref:`section_ref_algorithm_3DVAR` pour sa stabilité comme pour son
comportement lors de l'optimisation.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
+.. include:: snippets/FeaturePropParallelDerivativesOnly.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
vérifier préalablement les entrées elles-mêmes avec le test prévu
:ref:`section_ref_algorithm_InputValuesTest`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
activée que sur celles qui sont explicitement associées avec cet *observer*
dans sa déclaration.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
vérifier préalablement les entrées elles-mêmes avec le test prévu
:ref:`section_ref_algorithm_InputValuesTest`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelAlgorithm.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
nécessaire que le calcul de la fonction à simuler ne soit pas trop coûteux
pour éviter une durée d'optimisation rédhibitoire.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropNonLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelAlgorithm.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
quantiles sur les variables observées qui vont permettre de déterminer les
paramètres de modèles satisfaisant aux conditions de quantiles.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
Une fois l'analyse terminée, un résumé est affiché et, sur demande, une
représentation graphique des mêmes informations est produite.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
finale à l'aide du mot-clé "*UserPostAnalysis*" ou le traitement en cours de
calcul à l'aide des "*observer*" adaptés.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelAlgorithm.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
derniers états explorés. Les positions déjà explorées sont conservées dans une
liste de longueur finie.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropNonLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
l':ref:`section_ref_algorithm_LinearityTest`), et le tangent est valide jusqu'à
ce que l'on atteigne la précision du calcul.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropDerivativeNeeded.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
parallélisées ou distribuées dans le cas où la fonction à simuler le
supporte.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo12.rst
+
+.. include:: snippets/FeaturePropLocalOptimization.rst
+
+.. include:: snippets/FeaturePropDerivativeFree.rst
+
+.. include:: snippets/FeaturePropParallelAlgorithm.rst
+
.. ------------------------------------ ..
.. include:: snippets/Header2Algo02.rst
mandatory= ("Xb", "HO"),
optional = ("Y", ),
)
- self.setAttributes(tags=(
- "Checking",
- ))
+ self.setAttributes(
+ tags=(
+ "Checking",
+ ),
+ features=(
+ "DerivativeNeeded",
+ "ParallelDerivativesOnly",
+ ),
+ )
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
self._pre_run(Parameters, Xb, Y, U, HO, EM, CM, R, B, Q)
self.setAttributes(
tags=(
"Checking",
- )
+ ),
+ features=(
+ "DerivativeFree",
+ "ParallelFree",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
"MetaHeuristic",
"Population",
),
+ features=(
+ "NonLocalOptimization",
+ "DerivativeFree",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
"Ensemble",
"Reduction",
),
+ features=(
+ "LocalOptimization",
+ "DerivativeNeeded",
+ "ParallelDerivativesOnly",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
),
features=(
"LocalOptimization",
+ "DerivativeFree",
"ParallelAlgorithm",
),
)
tags=(
"Reduction",
"Checking",
- )
+ ),
+ features=(
+ "DerivativeFree",
+ "ParallelAlgorithm",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
"DataAssimilation",
"NonLinear",
"Filter",
- )
+ ),
+ features=(
+ "LocalOptimization",
+ "DerivativeNeeded",
+ "ParallelDerivativesOnly",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
"NonLinear",
"Filter",
"Dynamic",
- )
+ ),
+ features=(
+ "LocalOptimization",
+ "DerivativeNeeded",
+ "ParallelDerivativesOnly",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
self.setAttributes(
tags=(
"Checking",
- )
+ ),
+ features=(
+ "DerivativeFree",
+ "ParallelFree",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
self.setAttributes(
tags=(
"Checking",
- )
+ ),
+ features=(
+ "DerivativeNeeded",
+ "ParallelDerivativesOnly",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
self.setAttributes(
tags=(
"Checking",
- )
+ ),
+ features=(
+ "DerivativeFree",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
tags=(
"Reduction",
"Interpolation",
- )
+ ),
+ features=(
+ "DerivativeFree",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
tags=(
"Reduction",
"Interpolation",
- )
+ ),
+ features=(
+ "DerivativeFree",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
"Linear",
"Filter",
"Dynamic",
- )
+ ),
+ features=(
+ "LocalOptimization",
+ "DerivativeNeeded",
+ "ParallelDerivativesOnly",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
"Optimization",
"Linear",
"Variational",
- )
+ ),
+ features=(
+ "LocalOptimization",
+ "DerivativeNeeded",
+ "ParallelDerivativesOnly",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
self.setAttributes(
tags=(
"Checking",
- )
+ ),
+ features=(
+ "DerivativeNeeded",
+ "ParallelDerivativesOnly",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
self.setAttributes(
tags=(
"Checking",
- )
+ ),
+ features=(
+ "DerivativeNeeded",
+ "ParallelDerivativesOnly",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
tags=(
"Reduction",
"Checking",
- )
+ ),
+ features=(
+ "DerivativeFree",
+ "ParallelAlgorithm",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
"Optimization",
"NonLinear",
"Variational",
- )
+ ),
+ features=(
+ "LocalOptimization",
+ "DerivativeNeeded",
+ "ParallelDerivativesOnly",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
self.setAttributes(
tags=(
"Checking",
- )
+ ),
+ features=(
+ "DerivativeFree",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
self.setAttributes(
tags=(
"Checking",
- )
+ ),
+ features=(
+ "DerivativeFree",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
self.setAttributes(
tags=(
"Checking",
- )
+ ),
+ features=(
+ "DerivativeFree",
+ "ParallelAlgorithm",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
"NonLinear",
"MetaHeuristic",
"Population",
- )
+ ),
+ features=(
+ "NonLocalOptimization",
+ "DerivativeFree",
+ "ParallelAlgorithm",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
"Optimization",
"Risk",
"Variational",
- )
+ ),
+ features=(
+ "LocalOptimization",
+ "DerivativeNeeded",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
tags=(
"Reduction",
"Checking",
- )
+ ),
+ features=(
+ "DerivativeFree",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
self.setAttributes(
tags=(
"Checking",
- )
+ ),
+ features=(
+ "DerivativeFree",
+ "ParallelAlgorithm",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
"Optimization",
"NonLinear",
"MetaHeuristic",
- )
+ ),
+ features=(
+ "NonLocalOptimization",
+ "DerivativeFree",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
self.setAttributes(
tags=(
"Checking",
- )
+ ),
+ features=(
+ "DerivativeNeeded",
+ ),
)
def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):