================================================================================
The aim of the ADAO module is **to help using data assimilation or optimization
-methodology in conjunction with other modules or simulation codes in SALOME**.
-The ADAO module provides interface to some standard algorithms of data
-assimilation or optimization, and allows integration of their use in a SALOME
-study. Calculation or simulation modules have to provide one or more specific
-calling methods in order to be callable in the SALOME/ADAO framework, and all
-the SALOME modules can be used through YACS integration of ADAO.
+methodology in conjunction with other modules or simulation codes in Python
+[Python]_ or SALOME context [Salome]_**. The ADAO module provides a simple
+interface to some standard algorithms of data assimilation or optimization, as
+well as test or verification ones. It allows integration of their use in a
+Python or SALOME study. Calculation or simulation user modules have to provide
+one or more specific calling methods in order to be callable in the Python or
+SALOME framework. All the SALOME modules can be used through Python or YACS
+integration.
Its main objective is **to provide the use of various standard data
-assimilation or optimization methods, while remaining easy to use and providing
-a path to help the implementation**. For an end user, having already gathered
-his physical input information, it's a matter of "point\&click" to build an
-ADAO valid case and to evaluate it.
+assimilation or optimization methods, while remaining easy to setup, and
+providing a simplified path to help the implementation**. For the end user, who
+has previously collected information on his physical problem, the environment
+allows him to have an approach focused on simply declaring this information to
+build a valid ADAO case, to evaluate it, and to draw the physical results he
+needs
The module covers a wide variety of practical applications, in a robust way,
-allowing real engineering applications but also quick experimental methodology
-setup to be performed. Its methodological and numerical scalability gives way to
-extend the application domain.
+allowing real engineering applications, but also quick experimental methodology
+setup to be performed. Its methodological and numerical scalability give way to
+extend its applied domain. It is based on usage of other SALOME modules, namely
+YACS and EFICAS if they are available, and on usage of a generic underlying
+data assimilation library.
Calculation algorithm "*3DVAR*"
-------------------------------
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm performs a state estimation by variational minimization of the
classical :math:`J` function in static data assimilation:
which is usually designed as the "*3D-VAR*" function (see for example
[Talagrand97]_).
-Optional and required commands
-++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
-The general required commands, available in the editing user interface, are the
-following:
+.. include:: snippets/Background.rst
- .. include:: snippets/Background.rst
+.. include:: snippets/BackgroundError.rst
- .. include:: snippets/BackgroundError.rst
+.. include:: snippets/Observation.rst
- .. include:: snippets/Observation.rst
+.. include:: snippets/ObservationError.rst
- .. include:: snippets/ObservationError.rst
+.. include:: snippets/ObservationOperator.rst
- .. include:: snippets/ObservationOperator.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03AdOp.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allows to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
+.. include:: snippets/BoundsWithNone.rst
-The options of the algorithm are the following:
+.. include:: snippets/CostDecrementTolerance.rst
- Minimizer
- .. index:: single: Minimizer
+.. include:: snippets/GradientNormTolerance.rst
- This key allows to choose the optimization minimizer. The default choice is
- "LBFGSB", and the possible ones are "LBFGSB" (nonlinear constrained
- minimizer, see [Byrd95]_, [Morales11]_ and [Zhu97]_), "TNC" (nonlinear
- constrained minimizer), "CG" (nonlinear unconstrained minimizer), "BFGS"
- (nonlinear unconstrained minimizer), "NCG" (Newton CG minimizer). It is
- strongly recommended to stay with the default.
+.. include:: snippets/MaximumNumberOfSteps.rst
- Example :
- ``{"Minimizer":"LBFGSB"}``
+Minimizer
+ .. index:: single: Minimizer
- .. include:: snippets/BoundsWithNone.rst
+ This key allows to choose the optimization minimizer. The default choice is
+ "LBFGSB", and the possible ones are "LBFGSB" (nonlinear constrained
+ minimizer, see [Byrd95]_, [Morales11]_ and [Zhu97]_), "TNC" (nonlinear
+ constrained minimizer), "CG" (nonlinear unconstrained minimizer), "BFGS"
+ (nonlinear unconstrained minimizer), "NCG" (Newton CG minimizer). It is
+ strongly recommended to stay with the default.
- .. include:: snippets/MaximumNumberOfSteps.rst
+ Example :
+ ``{"Minimizer":"LBFGSB"}``
- .. include:: snippets/CostDecrementTolerance.rst
+.. include:: snippets/NumberOfSamplesForQuantiles.rst
- .. include:: snippets/ProjectedGradientTolerance.rst
+.. include:: snippets/ProjectedGradientTolerance.rst
- .. include:: snippets/GradientNormTolerance.rst
+.. include:: snippets/Quantiles.rst
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
+.. include:: snippets/SetSeed.rst
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["APosterioriCorrelations",
- "APosterioriCovariance", "APosterioriStandardDeviations",
- "APosterioriVariances", "BMA", "CostFunctionJ", "CostFunctionJb",
- "CostFunctionJo", "CostFunctionJAtCurrentOptimum",
- "CostFunctionJbAtCurrentOptimum", "CostFunctionJoAtCurrentOptimum",
- "CurrentOptimum", "CurrentState", "IndexOfOptimum", "Innovation",
- "InnovationAtCurrentState", "MahalanobisConsistency", "OMA", "OMB",
- "SigmaObs2", "SimulatedObservationAtBackground",
- "SimulatedObservationAtCurrentOptimum",
- "SimulatedObservationAtCurrentState", "SimulatedObservationAtOptimum",
- "SimulationQuantiles"].
+.. include:: snippets/SimulationForQuantiles.rst
- Example :
- ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
- .. include:: snippets/Quantiles.rst
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: [
+ "APosterioriCorrelations",
+ "APosterioriCovariance",
+ "APosterioriStandardDeviations",
+ "APosterioriVariances",
+ "BMA",
+ "CostFunctionJ",
+ "CostFunctionJAtCurrentOptimum",
+ "CostFunctionJb",
+ "CostFunctionJbAtCurrentOptimum",
+ "CostFunctionJo",
+ "CostFunctionJoAtCurrentOptimum",
+ "CurrentOptimum",
+ "CurrentState",
+ "IndexOfOptimum",
+ "Innovation",
+ "InnovationAtCurrentState",
+ "JacobianMatrixAtBackground",
+ "JacobianMatrixAtOptimum",
+ "KalmanGainAtOptimum",
+ "MahalanobisConsistency",
+ "OMA",
+ "OMB",
+ "SigmaObs2",
+ "SimulatedObservationAtBackground",
+ "SimulatedObservationAtCurrentOptimum",
+ "SimulatedObservationAtCurrentState",
+ "SimulatedObservationAtOptimum",
+ "SimulationQuantiles",
+ ].
- .. include:: snippets/SetSeed.rst
+ Example :
+ ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
- .. include:: snippets/NumberOfSamplesForQuantiles.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
- .. include:: snippets/SimulationForQuantiles.rst
+.. include:: snippets/Analysis.rst
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+.. include:: snippets/CostFunctionJ.rst
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. include:: snippets/CostFunctionJb.rst
-The unconditional outputs of the algorithm are the following:
+.. include:: snippets/CostFunctionJo.rst
- .. include:: snippets/Analysis.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo05.rst
- .. include:: snippets/CostFunctionJ.rst
+.. include:: snippets/APosterioriCorrelations.rst
- .. include:: snippets/CostFunctionJb.rst
+.. include:: snippets/APosterioriCovariance.rst
- .. include:: snippets/CostFunctionJo.rst
+.. include:: snippets/APosterioriStandardDeviations.rst
-The conditional outputs of the algorithm are the following:
+.. include:: snippets/APosterioriVariances.rst
- .. include:: snippets/APosterioriCorrelations.rst
+.. include:: snippets/BMA.rst
- .. include:: snippets/APosterioriCovariance.rst
+.. include:: snippets/CostFunctionJAtCurrentOptimum.rst
- .. include:: snippets/APosterioriStandardDeviations.rst
+.. include:: snippets/CostFunctionJbAtCurrentOptimum.rst
- .. include:: snippets/APosterioriVariances.rst
+.. include:: snippets/CostFunctionJoAtCurrentOptimum.rst
- .. include:: snippets/BMA.rst
+.. include:: snippets/CurrentOptimum.rst
- .. include:: snippets/CostFunctionJAtCurrentOptimum.rst
+.. include:: snippets/CurrentState.rst
- .. include:: snippets/CostFunctionJbAtCurrentOptimum.rst
+.. include:: snippets/IndexOfOptimum.rst
- .. include:: snippets/CostFunctionJoAtCurrentOptimum.rst
+.. include:: snippets/Innovation.rst
- .. include:: snippets/CurrentOptimum.rst
+.. include:: snippets/InnovationAtCurrentState.rst
- .. include:: snippets/CurrentState.rst
+.. include:: snippets/JacobianMatrixAtBackground.rst
- .. include:: snippets/IndexOfOptimum.rst
+.. include:: snippets/JacobianMatrixAtOptimum.rst
- .. include:: snippets/Innovation.rst
+.. include:: snippets/KalmanGainAtOptimum.rst
- .. include:: snippets/InnovationAtCurrentState.rst
+.. include:: snippets/MahalanobisConsistency.rst
- .. include:: snippets/MahalanobisConsistency.rst
+.. include:: snippets/OMA.rst
- .. include:: snippets/OMA.rst
+.. include:: snippets/OMB.rst
- .. include:: snippets/OMB.rst
+.. include:: snippets/SigmaObs2.rst
- .. include:: snippets/SigmaObs2.rst
+.. include:: snippets/SimulatedObservationAtBackground.rst
- .. include:: snippets/SimulatedObservationAtBackground.rst
+.. include:: snippets/SimulatedObservationAtCurrentOptimum.rst
- .. include:: snippets/SimulatedObservationAtCurrentOptimum.rst
+.. include:: snippets/SimulatedObservationAtCurrentState.rst
- .. include:: snippets/SimulatedObservationAtCurrentState.rst
+.. include:: snippets/SimulatedObservationAtOptimum.rst
- .. include:: snippets/SimulatedObservationAtOptimum.rst
+.. include:: snippets/SimulationQuantiles.rst
- .. include:: snippets/SimulationQuantiles.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
-See also
-++++++++
+- :ref:`section_ref_algorithm_Blue`
+- :ref:`section_ref_algorithm_ExtendedBlue`
+- :ref:`section_ref_algorithm_LinearityTest`
-References to other sections:
- - :ref:`section_ref_algorithm_Blue`
- - :ref:`section_ref_algorithm_ExtendedBlue`
- - :ref:`section_ref_algorithm_LinearityTest`
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo07.rst
-Bibliographical references:
- - [Byrd95]_
- - [Morales11]_
- - [Talagrand97]_
- - [Zhu97]_
+- [Byrd95]_
+- [Morales11]_
+- [Talagrand97]_
+- [Zhu97]_
Calculation algorithm "*4DVAR*"
-------------------------------
-.. warning::
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo00.rst
- in its present version, this algorithm is experimental, and so changes can be
- required in forthcoming versions.
-
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm realizes an estimation of the state of a dynamic system, by a
variational minimization method of the classical :math:`J` function in data
filters, specially the :ref:`section_ref_algorithm_ExtendedKalmanFilter` or the
:ref:`section_ref_algorithm_UnscentedKalmanFilter`.
-Optional and required commands
-++++++++++++++++++++++++++++++
-
-
-The general required commands, available in the editing user interface, are the
-following:
-
- .. include:: snippets/Background.rst
-
- .. include:: snippets/BackgroundError.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
- .. include:: snippets/EvolutionError.rst
+.. include:: snippets/Background.rst
- .. include:: snippets/EvolutionModel.rst
+.. include:: snippets/BackgroundError.rst
- .. include:: snippets/Observation.rst
+.. include:: snippets/EvolutionError.rst
- .. include:: snippets/ObservationError.rst
+.. include:: snippets/EvolutionModel.rst
- .. include:: snippets/ObservationOperator.rst
+.. include:: snippets/Observation.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allows to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
+.. include:: snippets/ObservationError.rst
-The options of the algorithm are the following:
+.. include:: snippets/ObservationOperator.rst
- Minimizer
- .. index:: single: Minimizer
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03AdOp.rst
- This key allows to choose the optimization minimizer. The default choice is
- "LBFGSB", and the possible ones are "LBFGSB" (nonlinear constrained
- minimizer, see [Byrd95]_, [Morales11]_ and [Zhu97]_), "TNC" (nonlinear
- constrained minimizer), "CG" (nonlinear unconstrained minimizer), "BFGS"
- (nonlinear unconstrained minimizer), "NCG" (Newton CG minimizer). It is
- strongly recommended to stay with the default.
+Minimizer
+ .. index:: single: Minimizer
- Example :
- ``{"Minimizer":"LBFGSB"}``
+ This key allows to choose the optimization minimizer. The default choice is
+ "LBFGSB", and the possible ones are "LBFGSB" (nonlinear constrained
+ minimizer, see [Byrd95]_, [Morales11]_ and [Zhu97]_), "TNC" (nonlinear
+ constrained minimizer), "CG" (nonlinear unconstrained minimizer), "BFGS"
+ (nonlinear unconstrained minimizer), "NCG" (Newton CG minimizer). It is
+ strongly recommended to stay with the default.
- .. include:: snippets/BoundsWithNone.rst
+ Example :
+ ``{"Minimizer":"LBFGSB"}``
- .. include:: snippets/ConstrainedBy.rst
+.. include:: snippets/BoundsWithNone.rst
- .. include:: snippets/MaximumNumberOfSteps.rst
+.. include:: snippets/ConstrainedBy.rst
- .. include:: snippets/CostDecrementTolerance.rst
+.. include:: snippets/MaximumNumberOfSteps.rst
- .. include:: snippets/EstimationOf.rst
+.. include:: snippets/CostDecrementTolerance.rst
- .. include:: snippets/ProjectedGradientTolerance.rst
+.. include:: snippets/EstimationOf.rst
- .. include:: snippets/GradientNormTolerance.rst
+.. include:: snippets/ProjectedGradientTolerance.rst
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
+.. include:: snippets/GradientNormTolerance.rst
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["BMA", "CostFunctionJ",
- "CostFunctionJb", "CostFunctionJo", "CostFunctionJAtCurrentOptimum",
- "CostFunctionJbAtCurrentOptimum", "CostFunctionJoAtCurrentOptimum",
- "CurrentOptimum", "CurrentState", "IndexOfOptimum"].
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
- Example : ``{"StoreSupplementaryCalculations":["BMA", "CurrentState"]}``
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: [
+ "BMA",
+ "CostFunctionJ",
+ "CostFunctionJb",
+ "CostFunctionJo",
+ "CostFunctionJAtCurrentOptimum",
+ "CostFunctionJbAtCurrentOptimum",
+ "CostFunctionJoAtCurrentOptimum",
+ "CurrentOptimum",
+ "CurrentState",
+ "IndexOfOptimum",
+ ].
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+ Example : ``{"StoreSupplementaryCalculations":["BMA", "CurrentState"]}``
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
-The unconditional outputs of the algorithm are the following:
+.. include:: snippets/Analysis.rst
- .. include:: snippets/Analysis.rst
+.. include:: snippets/CostFunctionJ.rst
- .. include:: snippets/CostFunctionJ.rst
+.. include:: snippets/CostFunctionJb.rst
- .. include:: snippets/CostFunctionJb.rst
+.. include:: snippets/CostFunctionJo.rst
- .. include:: snippets/CostFunctionJo.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo05.rst
-The conditional outputs of the algorithm are the following:
+.. include:: snippets/BMA.rst
- .. include:: snippets/BMA.rst
+.. include:: snippets/CostFunctionJAtCurrentOptimum.rst
- .. include:: snippets/CostFunctionJAtCurrentOptimum.rst
+.. include:: snippets/CostFunctionJbAtCurrentOptimum.rst
- .. include:: snippets/CostFunctionJbAtCurrentOptimum.rst
+.. include:: snippets/CostFunctionJoAtCurrentOptimum.rst
- .. include:: snippets/CostFunctionJoAtCurrentOptimum.rst
+.. include:: snippets/CurrentOptimum.rst
- .. include:: snippets/CurrentOptimum.rst
+.. include:: snippets/CurrentState.rst
- .. include:: snippets/CurrentState.rst
+.. include:: snippets/IndexOfOptimum.rst
- .. include:: snippets/IndexOfOptimum.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
-See also
-++++++++
+- :ref:`section_ref_algorithm_3DVAR`
+- :ref:`section_ref_algorithm_KalmanFilter`
+- :ref:`section_ref_algorithm_ExtendedKalmanFilter`
+- :ref:`section_ref_algorithm_EnsembleKalmanFilter`
-References to other sections:
- - :ref:`section_ref_algorithm_3DVAR`
- - :ref:`section_ref_algorithm_KalmanFilter`
- - :ref:`section_ref_algorithm_ExtendedKalmanFilter`
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo07.rst
-Bibliographical references:
- - [Byrd95]_
- - [Morales11]_
- - [Talagrand97]_
- - [Zhu97]_
+- [Byrd95]_
+- [Morales11]_
+- [Talagrand97]_
+- [Zhu97]_
Checking algorithm "*AdjointTest*"
----------------------------------
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm allows to check the quality of the adjoint operator, by
calculating a residue with known theoretical properties.
:math:`\mathbf{y}` has to be in the image of :math:`F`. If it is not given, one
take :math:`\mathbf{y} = F(\mathbf{x})`.
-Optional and required commands
-++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
+.. include:: snippets/CheckingPoint.rst
-The general required commands, available in the editing user interface, are the
-following:
+.. include:: snippets/ObservationOperator.rst
- .. include:: snippets/CheckingPoint.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03Chck.rst
- .. include:: snippets/ObservationOperator.rst
+.. include:: snippets/AmplitudeOfInitialDirection.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allow to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
+.. include:: snippets/EpsilonMinimumExponent.rst
-The options of the algorithm are the following:
+.. include:: snippets/InitialDirection.rst
- .. include:: snippets/AmplitudeOfInitialDirection.rst
+.. include:: snippets/SetSeed.rst
- .. include:: snippets/EpsilonMinimumExponent.rst
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
- .. include:: snippets/InitialDirection.rst
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: [
+ "CurrentState",
+ "Residu",
+ "SimulatedObservationAtCurrentState",
+ ].
- .. include:: snippets/SetSeed.rst
+ Example :
+ ``{"StoreSupplementaryCalculations":["CurrentState"]}``
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["CurrentState", "Residu",
- "SimulatedObservationAtCurrentState"].
+.. include:: snippets/Residu.rst
- Example :
- ``{"StoreSupplementaryCalculations":["CurrentState"]}``
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo05.rst
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+.. include:: snippets/CurrentState.rst
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. include:: snippets/SimulatedObservationAtCurrentState.rst
-The unconditional outputs of the algorithm are the following:
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
- .. include:: snippets/Residu.rst
-
-The conditional outputs of the algorithm are the following:
-
- .. include:: snippets/CurrentState.rst
-
- .. include:: snippets/SimulatedObservationAtCurrentState.rst
-
-See also
-++++++++
-
-References to other sections:
- - :ref:`section_ref_algorithm_FunctionTest`
- - :ref:`section_ref_algorithm_LinearityTest`
- - :ref:`section_ref_algorithm_TangentTest`
- - :ref:`section_ref_algorithm_GradientTest`
+- :ref:`section_ref_algorithm_FunctionTest`
+- :ref:`section_ref_algorithm_LinearityTest`
+- :ref:`section_ref_algorithm_TangentTest`
+- :ref:`section_ref_algorithm_GradientTest`
+- :ref:`section_ref_algorithm_LocalSensitivityTest`
Calculation algorithm "*Blue*"
------------------------------
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm realizes a BLUE (Best Linear Unbiased Estimator) type estimation
of the state of a system. More precisely, it is an Aitken estimator.
:ref:`section_ref_algorithm_ExtendedBlue` or the
:ref:`section_ref_algorithm_3DVAR`.
-Optional and required commands
-++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
+.. include:: snippets/Background.rst
-The general required commands, available in the editing user interface, are the
-following:
+.. include:: snippets/BackgroundError.rst
- .. include:: snippets/Background.rst
+.. include:: snippets/Observation.rst
- .. include:: snippets/BackgroundError.rst
+.. include:: snippets/ObservationError.rst
- .. include:: snippets/Observation.rst
+.. include:: snippets/ObservationOperator.rst
- .. include:: snippets/ObservationError.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03AdOp.rst
- .. include:: snippets/ObservationOperator.rst
+.. include:: snippets/NumberOfSamplesForQuantiles.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allows to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
+.. include:: snippets/Quantiles.rst
-The options of the algorithm are the following:
+.. include:: snippets/SetSeed.rst
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
+.. include:: snippets/SimulationForQuantiles.rst
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["APosterioriCorrelations",
- "APosterioriCovariance", "APosterioriStandardDeviations",
- "APosterioriVariances", "BMA", "OMA", "OMB", "CurrentState",
- "CostFunctionJ", "CostFunctionJb", "CostFunctionJo", "Innovation",
- "SigmaBck2", "SigmaObs2", "MahalanobisConsistency", "SimulationQuantiles",
- "SimulatedObservationAtBackground", "SimulatedObservationAtCurrentState",
- "SimulatedObservationAtOptimum"].
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
- Example :
- ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: [
+ "APosterioriCorrelations",
+ "APosterioriCovariance",
+ "APosterioriStandardDeviations",
+ "APosterioriVariances",
+ "BMA",
+ "CostFunctionJ",
+ "CostFunctionJAtCurrentOptimum",
+ "CostFunctionJb",
+ "CostFunctionJbAtCurrentOptimum",
+ "CostFunctionJo",
+ "CostFunctionJoAtCurrentOptimum",
+ "CurrentOptimum",
+ "CurrentState",
+ "Innovation",
+ "MahalanobisConsistency",
+ "OMA",
+ "OMB",
+ "SigmaBck2",
+ "SigmaObs2",
+ "SimulatedObservationAtBackground",
+ "SimulatedObservationAtCurrentOptimum",
+ "SimulatedObservationAtCurrentState",
+ "SimulatedObservationAtOptimum",
+ "SimulationQuantiles",
+ ].
- .. include:: snippets/Quantiles.rst
+ Example :
+ ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
- .. include:: snippets/SetSeed.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
- .. include:: snippets/NumberOfSamplesForQuantiles.rst
+.. include:: snippets/Analysis.rst
- .. include:: snippets/SimulationForQuantiles.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo05.rst
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+.. include:: snippets/APosterioriCorrelations.rst
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. include:: snippets/APosterioriCovariance.rst
-The unconditional outputs of the algorithm are the following:
+.. include:: snippets/APosterioriStandardDeviations.rst
- .. include:: snippets/Analysis.rst
+.. include:: snippets/APosterioriVariances.rst
-The conditional outputs of the algorithm are the following:
+.. include:: snippets/BMA.rst
- .. include:: snippets/APosterioriCorrelations.rst
+.. include:: snippets/CostFunctionJ.rst
- .. include:: snippets/APosterioriCovariance.rst
+.. include:: snippets/CostFunctionJAtCurrentOptimum.rst
- .. include:: snippets/APosterioriStandardDeviations.rst
+.. include:: snippets/CostFunctionJb.rst
- .. include:: snippets/APosterioriVariances.rst
+.. include:: snippets/CostFunctionJbAtCurrentOptimum.rst
- .. include:: snippets/BMA.rst
+.. include:: snippets/CostFunctionJo.rst
- .. include:: snippets/CostFunctionJ.rst
+.. include:: snippets/CostFunctionJoAtCurrentOptimum.rst
- .. include:: snippets/CostFunctionJb.rst
+.. include:: snippets/CurrentOptimum.rst
- .. include:: snippets/CostFunctionJo.rst
+.. include:: snippets/CurrentState.rst
- .. include:: snippets/Innovation.rst
+.. include:: snippets/Innovation.rst
- .. include:: snippets/MahalanobisConsistency.rst
+.. include:: snippets/MahalanobisConsistency.rst
- .. include:: snippets/OMA.rst
+.. include:: snippets/OMA.rst
- .. include:: snippets/OMB.rst
+.. include:: snippets/OMB.rst
- .. include:: snippets/SigmaBck2.rst
+.. include:: snippets/SigmaBck2.rst
- .. include:: snippets/SigmaObs2.rst
+.. include:: snippets/SigmaObs2.rst
- .. include:: snippets/SimulatedObservationAtBackground.rst
+.. include:: snippets/SimulatedObservationAtBackground.rst
- .. include:: snippets/SimulatedObservationAtOptimum.rst
+.. include:: snippets/SimulatedObservationAtOptimum.rst
- .. include:: snippets/SimulationQuantiles.rst
+.. include:: snippets/SimulatedObservationAtCurrentState.rst
+.. include:: snippets/SimulatedObservationAtOptimum.rst
-See also
-++++++++
+.. include:: snippets/SimulationQuantiles.rst
-References to other sections:
- - :ref:`section_ref_algorithm_ExtendedBlue`
- - :ref:`section_ref_algorithm_3DVAR`
- - :ref:`section_ref_algorithm_LinearityTest`
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
-Bibliographical references:
- - [Bouttier99]_
+- :ref:`section_ref_algorithm_ExtendedBlue`
+- :ref:`section_ref_algorithm_3DVAR`
+- :ref:`section_ref_algorithm_LinearityTest`
+
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo07.rst
+
+- [Bouttier99]_
Calculation algorithm "*DerivativeFreeOptimization*"
----------------------------------------------------
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm realizes an estimation of the state of a system by minimization
of a cost function :math:`J` without gradient. It is a method that does not use
the derivatives of the cost function. It falls in the same category than the
-:ref:`section_ref_algorithm_ParticleSwarmOptimization` or the
-:ref:`section_ref_algorithm_DifferentialEvolution`.
+:ref:`section_ref_algorithm_ParticleSwarmOptimization`, the
+:ref:`section_ref_algorithm_DifferentialEvolution` or the
+:ref:`section_ref_algorithm_TabuSearch`.
This is an optimization method allowing for global minimum search of a general
error function :math:`J` of type :math:`L^1`, :math:`L^2` or :math:`L^{\infty}`,
with or without weights. The default error function is the augmented weighted
least squares function, classically used in data assimilation.
-Optional and required commands
-++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
-The general required commands, available in the editing user interface, are the
-following:
+.. include:: snippets/Background.rst
- .. include:: snippets/Background.rst
+.. include:: snippets/BackgroundError.rst
- .. include:: snippets/BackgroundError.rst
+.. include:: snippets/Observation.rst
- .. include:: snippets/Observation.rst
+.. include:: snippets/ObservationError.rst
- .. include:: snippets/ObservationError.rst
+.. include:: snippets/ObservationOperator.rst
- .. include:: snippets/ObservationOperator.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03AdOp.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allows to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
+.. include:: snippets/Minimizer_DFO.rst
-The options of the algorithm are the following:
+.. include:: snippets/BoundsWithNone.rst
- .. include:: snippets/Minimizer_DFO.rst
+.. include:: snippets/MaximumNumberOfSteps.rst
- .. include:: snippets/BoundsWithNone.rst
+.. include:: snippets/MaximumNumberOfFunctionEvaluations.rst
- .. include:: snippets/MaximumNumberOfSteps.rst
+.. include:: snippets/StateVariationTolerance.rst
- .. include:: snippets/MaximumNumberOfFunctionEvaluations.rst
+.. include:: snippets/CostDecrementTolerance.rst
- .. include:: snippets/StateVariationTolerance.rst
+.. include:: snippets/QualityCriterion.rst
- .. include:: snippets/CostDecrementTolerance.rst
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
- .. include:: snippets/QualityCriterion.rst
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: [
+ "BMA",
+ "CostFunctionJ",
+ "CostFunctionJAtCurrentOptimum",
+ "CostFunctionJb",
+ "CostFunctionJbAtCurrentOptimum",
+ "CostFunctionJo",
+ "CostFunctionJoAtCurrentOptimum",
+ "CurrentOptimum",
+ "CurrentState",
+ "IndexOfOptimum",
+ "Innovation",
+ "InnovationAtCurrentState",
+ "OMA",
+ "OMB",
+ "SimulatedObservationAtBackground",
+ "SimulatedObservationAtCurrentOptimum",
+ "SimulatedObservationAtCurrentState",
+ "SimulatedObservationAtOptimum",
+ ].
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
+ Example :
+ ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["BMA", "CostFunctionJ",
- "CostFunctionJAtCurrentOptimum", "CostFunctionJb",
- "CostFunctionJbAtCurrentOptimum", "CostFunctionJo",
- "CostFunctionJoAtCurrentOptimum", "CurrentOptimum", "CurrentState",
- "IndexOfOptimum", "Innovation", "InnovationAtCurrentState", "OMA", "OMB",
- "SimulatedObservationAtBackground", "SimulatedObservationAtCurrentOptimum",
- "SimulatedObservationAtCurrentState", "SimulatedObservationAtOptimum"].
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
- Example :
- ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
+.. include:: snippets/Analysis.rst
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+.. include:: snippets/CostFunctionJ.rst
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. include:: snippets/CostFunctionJb.rst
-The unconditional outputs of the algorithm are the following:
+.. include:: snippets/CostFunctionJo.rst
- .. include:: snippets/Analysis.rst
+.. include:: snippets/CurrentState.rst
- .. include:: snippets/CostFunctionJ.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo05.rst
- .. include:: snippets/CostFunctionJb.rst
+.. include:: snippets/BMA.rst
- .. include:: snippets/CostFunctionJo.rst
+.. include:: snippets/CostFunctionJAtCurrentOptimum.rst
- .. include:: snippets/CurrentState.rst
+.. include:: snippets/CostFunctionJbAtCurrentOptimum.rst
-The conditional outputs of the algorithm are the following:
+.. include:: snippets/CostFunctionJoAtCurrentOptimum.rst
- .. include:: snippets/BMA.rst
+.. include:: snippets/CurrentOptimum.rst
- .. include:: snippets/CostFunctionJAtCurrentOptimum.rst
+.. include:: snippets/IndexOfOptimum.rst
- .. include:: snippets/CostFunctionJbAtCurrentOptimum.rst
+.. include:: snippets/Innovation.rst
- .. include:: snippets/CostFunctionJoAtCurrentOptimum.rst
+.. include:: snippets/InnovationAtCurrentState.rst
- .. include:: snippets/CurrentOptimum.rst
+.. include:: snippets/OMA.rst
- .. include:: snippets/IndexOfOptimum.rst
+.. include:: snippets/OMB.rst
- .. include:: snippets/Innovation.rst
+.. include:: snippets/SimulatedObservationAtBackground.rst
- .. include:: snippets/InnovationAtCurrentState.rst
+.. include:: snippets/SimulatedObservationAtCurrentOptimum.rst
- .. include:: snippets/OMA.rst
+.. include:: snippets/SimulatedObservationAtCurrentState.rst
- .. include:: snippets/OMB.rst
+.. include:: snippets/SimulatedObservationAtOptimum.rst
- .. include:: snippets/SimulatedObservationAtBackground.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
- .. include:: snippets/SimulatedObservationAtCurrentOptimum.rst
+- :ref:`section_ref_algorithm_ParticleSwarmOptimization`
+- :ref:`section_ref_algorithm_DifferentialEvolution`
+- :ref:`section_ref_algorithm_TabuSearch`
- .. include:: snippets/SimulatedObservationAtCurrentState.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo07.rst
- .. include:: snippets/SimulatedObservationAtOptimum.rst
-
-See also
-++++++++
-
-References to other sections:
- - :ref:`section_ref_algorithm_ParticleSwarmOptimization`
- - :ref:`section_ref_algorithm_DifferentialEvolution`
-
-Bibliographical references:
- - [Johnson08]_
- - [Nelder65]_
- - [Powell64]_
- - [Powell94]_
- - [Powell98]_
- - [Powell04]_
- - [Powell07]_
- - [Powell09]_
- - [Rowan90]_
+- [Johnson08]_
+- [Nelder65]_
+- [Powell64]_
+- [Powell94]_
+- [Powell98]_
+- [Powell04]_
+- [Powell07]_
+- [Powell09]_
+- [Rowan90]_
Calculation algorithm "*DifferentialEvolution*"
----------------------------------------------------
-.. warning::
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo00.rst
- in its present version, this algorithm is experimental, and so changes can be
- required in forthcoming versions.
-
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm realizes an estimation of the state of a system by minimization
of a cost function :math:`J` by using an evolutionary strategy of differential
evolution. It is a method that does not use the derivatives of the cost
function. It falls in the same category than the
-:ref:`section_ref_algorithm_DerivativeFreeOptimization` or the
-:ref:`section_ref_algorithm_ParticleSwarmOptimization`.
+:ref:`section_ref_algorithm_DerivativeFreeOptimization`, the
+:ref:`section_ref_algorithm_ParticleSwarmOptimization` or the
+:ref:`section_ref_algorithm_TabuSearch`.
This is an optimization method allowing for global minimum search of a general
error function :math:`J` of type :math:`L^1`, :math:`L^2` or :math:`L^{\infty}`,
with or without weights. The default error function is the augmented weighted
least squares function, classically used in data assimilation.
-Optional and required commands
-++++++++++++++++++++++++++++++
-
-The general required commands, available in the editing user interface, are the
-following:
-
- .. include:: snippets/Background.rst
-
- .. include:: snippets/BackgroundError.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
- .. include:: snippets/Observation.rst
+.. include:: snippets/Background.rst
- .. include:: snippets/ObservationError.rst
+.. include:: snippets/BackgroundError.rst
- .. include:: snippets/ObservationOperator.rst
+.. include:: snippets/Observation.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allows to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
+.. include:: snippets/ObservationError.rst
-The options of the algorithm are the following:
+.. include:: snippets/ObservationOperator.rst
- .. include:: snippets/Minimizer_DE.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03AdOp.rst
- .. include:: snippets/BoundsWithExtremes.rst
+.. include:: snippets/Minimizer_DE.rst
- .. include:: snippets/CrossOverProbability_CR.rst
+.. include:: snippets/BoundsWithExtremes.rst
- .. include:: snippets/MaximumNumberOfSteps.rst
+.. include:: snippets/CrossOverProbability_CR.rst
- .. include:: snippets/MaximumNumberOfFunctionEvaluations.rst
+.. include:: snippets/MaximumNumberOfSteps.rst
- .. include:: snippets/MutationDifferentialWeight_F.rst
+.. include:: snippets/MaximumNumberOfFunctionEvaluations.rst
- .. include:: snippets/PopulationSize.rst
+.. include:: snippets/MutationDifferentialWeight_F.rst
- .. include:: snippets/QualityCriterion.rst
+.. include:: snippets/PopulationSize.rst
- .. include:: snippets/SetSeed.rst
+.. include:: snippets/QualityCriterion.rst
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
+.. include:: snippets/SetSeed.rst
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["BMA", "CostFunctionJ",
- "CostFunctionJAtCurrentOptimum", "CostFunctionJb",
- "CostFunctionJbAtCurrentOptimum", "CostFunctionJo",
- "CostFunctionJoAtCurrentOptimum", "CurrentOptimum", "CurrentState",
- "IndexOfOptimum", "Innovation", "InnovationAtCurrentState", "OMA", "OMB",
- "SimulatedObservationAtBackground", "SimulatedObservationAtCurrentOptimum",
- "SimulatedObservationAtCurrentState", "SimulatedObservationAtOptimum"].
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
- Example :
- ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: [
+ "BMA",
+ "CostFunctionJ",
+ "CostFunctionJAtCurrentOptimum",
+ "CostFunctionJb",
+ "CostFunctionJbAtCurrentOptimum",
+ "CostFunctionJo",
+ "CostFunctionJoAtCurrentOptimum",
+ "CurrentOptimum",
+ "CurrentState",
+ "IndexOfOptimum",
+ "Innovation",
+ "InnovationAtCurrentState",
+ "OMA",
+ "OMB",
+ "SimulatedObservationAtBackground",
+ "SimulatedObservationAtCurrentOptimum",
+ "SimulatedObservationAtCurrentState",
+ "SimulatedObservationAtOptimum",
+ ].
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+ Example :
+ ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
-The unconditional outputs of the algorithm are the following:
+.. include:: snippets/Analysis.rst
- .. include:: snippets/Analysis.rst
+.. include:: snippets/CostFunctionJ.rst
- .. include:: snippets/CostFunctionJ.rst
+.. include:: snippets/CostFunctionJb.rst
- .. include:: snippets/CostFunctionJb.rst
+.. include:: snippets/CostFunctionJo.rst
- .. include:: snippets/CostFunctionJo.rst
+.. include:: snippets/CurrentState.rst
- .. include:: snippets/CurrentState.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo05.rst
-The conditional outputs of the algorithm are the following:
+.. include:: snippets/BMA.rst
- .. include:: snippets/BMA.rst
+.. include:: snippets/CostFunctionJAtCurrentOptimum.rst
- .. include:: snippets/CostFunctionJAtCurrentOptimum.rst
+.. include:: snippets/CostFunctionJbAtCurrentOptimum.rst
- .. include:: snippets/CostFunctionJbAtCurrentOptimum.rst
+.. include:: snippets/CostFunctionJoAtCurrentOptimum.rst
- .. include:: snippets/CostFunctionJoAtCurrentOptimum.rst
+.. include:: snippets/CurrentOptimum.rst
- .. include:: snippets/CurrentOptimum.rst
+.. include:: snippets/IndexOfOptimum.rst
- .. include:: snippets/IndexOfOptimum.rst
+.. include:: snippets/Innovation.rst
- .. include:: snippets/Innovation.rst
+.. include:: snippets/InnovationAtCurrentState.rst
- .. include:: snippets/InnovationAtCurrentState.rst
+.. include:: snippets/OMA.rst
- .. include:: snippets/OMA.rst
+.. include:: snippets/OMB.rst
- .. include:: snippets/OMB.rst
+.. include:: snippets/SimulatedObservationAtBackground.rst
- .. include:: snippets/SimulatedObservationAtBackground.rst
+.. include:: snippets/SimulatedObservationAtCurrentOptimum.rst
- .. include:: snippets/SimulatedObservationAtCurrentOptimum.rst
+.. include:: snippets/SimulatedObservationAtCurrentState.rst
- .. include:: snippets/SimulatedObservationAtCurrentState.rst
+.. include:: snippets/SimulatedObservationAtOptimum.rst
- .. include:: snippets/SimulatedObservationAtOptimum.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
-See also
-++++++++
+- :ref:`section_ref_algorithm_DerivativeFreeOptimization`
+- :ref:`section_ref_algorithm_ParticleSwarmOptimization`
+- :ref:`section_ref_algorithm_TabuSearch`
-References to other sections:
- - :ref:`section_ref_algorithm_DerivativeFreeOptimization`
- - :ref:`section_ref_algorithm_ParticleSwarmOptimization`
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo07.rst
-Bibliographical references:
- - [Chakraborty08]_
- - [Price05]_
- - [Storn97]_
+- [Chakraborty08]_
+- [Price05]_
+- [Storn97]_
Calculation algorithm "*EnsembleBlue*"
--------------------------------------
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm realizes a BLUE (Best Linear Unbiased Estimator, which is here an
Aitken estimator) type estimation of the state of a system by an ensemble
linearity of the observation operator with the help of the
:ref:`section_ref_algorithm_LinearityTest`.
-Optional and required commands
-++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
+.. include:: snippets/Background.rst
-The general required commands, available in the editing user interface, are the
-following:
+.. include:: snippets/BackgroundError.rst
- .. include:: snippets/Background.rst
+.. include:: snippets/Observation.rst
- .. include:: snippets/BackgroundError.rst
+.. include:: snippets/ObservationError.rst
- .. include:: snippets/Observation.rst
+.. include:: snippets/ObservationOperator.rst
- .. include:: snippets/ObservationError.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03AdOp.rst
- .. include:: snippets/ObservationOperator.rst
+.. include:: snippets/SetSeed.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allows to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
-The options of the algorithm are the following:
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: [
+ "CurrentState",
+ "Innovation",
+ "SimulatedObservationAtBackground",
+ "SimulatedObservationAtCurrentState",
+ "SimulatedObservationAtOptimum",
+ ].
- .. include:: snippets/SetSeed.rst
+ Example :
+ ``{"StoreSupplementaryCalculations":["CurrentState", "Innovation"]}``
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["CurrentState", "Innovation",
- "SimulatedObservationAtBackground", "SimulatedObservationAtCurrentState",
- "SimulatedObservationAtOptimum"].
+.. include:: snippets/Analysis.rst
- Example :
- ``{"StoreSupplementaryCalculations":["CurrentState", "Innovation"]}``
+.. include:: snippets/CurrentState.rst
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+.. include:: snippets/Innovation.rst
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
-The unconditional outputs of the algorithm are the following:
-
- .. include:: snippets/Analysis.rst
-
- .. include:: snippets/CurrentState.rst
-
- .. include:: snippets/Innovation.rst
-
-See also
-++++++++
-
-References to other sections:
- - :ref:`section_ref_algorithm_Blue`
+- :ref:`section_ref_algorithm_Blue`
+- :ref:`section_ref_algorithm_EnsembleKalmanFilter`
Calculation algorithm "*EnsembleKalmanFilter*"
----------------------------------------------
-.. warning::
-
- in its present version, this algorithm is experimental, and so changes can be
- required in forthcoming versions.
-
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm realizes an estimation of the state of a dynamic system by a
Ensemble Kalman Filter (EnKF), avoiding to have to perform the tangent and
to evaluate on small systems. One can verify the linearity of the operators
with the help of the :ref:`section_ref_algorithm_LinearityTest`.
-Commandes requises et optionnelles
-++++++++++++++++++++++++++++++++++
-
-The general required commands, available in the editing user interface, are the
-following:
-
- .. include:: snippets/Background.rst
-
- .. include:: snippets/BackgroundError.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
- .. include:: snippets/EvolutionError.rst
+.. include:: snippets/Background.rst
- .. include:: snippets/EvolutionModel.rst
+.. include:: snippets/BackgroundError.rst
- .. include:: snippets/Observation.rst
+.. include:: snippets/EvolutionError.rst
- .. include:: snippets/ObservationError.rst
+.. include:: snippets/EvolutionModel.rst
- .. include:: snippets/ObservationOperator.rst
+.. include:: snippets/Observation.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allows to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
+.. include:: snippets/ObservationError.rst
-The options of the algorithm are the following:
+.. include:: snippets/ObservationOperator.rst
- .. include:: snippets/NumberOfMembers.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03AdOp.rst
- .. include:: snippets/EstimationOf.rst
+.. include:: snippets/EstimationOf.rst
- .. include:: snippets/SetSeed.rst
+.. include:: snippets/NumberOfMembers.rst
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
+.. include:: snippets/SetSeed.rst
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["APosterioriCorrelations",
- "APosterioriCovariance", "APosterioriStandardDeviations",
- "APosterioriVariances", "BMA", "CostFunctionJ", "CostFunctionJb",
- "CostFunctionJo", "CurrentState"].
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
- Example :
- ``{"StoreSupplementaryCalculations":["CurrentState"]}``
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: [
+ "APosterioriCorrelations",
+ "APosterioriCovariance",
+ "APosterioriStandardDeviations",
+ "APosterioriVariances",
+ "BMA",
+ "CostFunctionJ",
+ "CostFunctionJb",
+ "CostFunctionJo",
+ "CurrentState",
+ ].
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+ Example :
+ ``{"StoreSupplementaryCalculations":["CurrentState"]}``
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
-The unconditional outputs of the algorithm are the following:
+.. include:: snippets/Analysis.rst
- .. include:: snippets/Analysis.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo05.rst
-The conditional outputs of the algorithm are the following:
+.. include:: snippets/APosterioriCorrelations.rst
- .. include:: snippets/APosterioriCorrelations.rst
+.. include:: snippets/APosterioriCovariance.rst
- .. include:: snippets/APosterioriCovariance.rst
+.. include:: snippets/APosterioriStandardDeviations.rst
- .. include:: snippets/APosterioriStandardDeviations.rst
+.. include:: snippets/APosterioriVariances.rst
- .. include:: snippets/APosterioriVariances.rst
+.. include:: snippets/BMA.rst
- .. include:: snippets/BMA.rst
+.. include:: snippets/CostFunctionJ.rst
- .. include:: snippets/CostFunctionJ.rst
+.. include:: snippets/CostFunctionJb.rst
- .. include:: snippets/CostFunctionJb.rst
+.. include:: snippets/CostFunctionJo.rst
- .. include:: snippets/CostFunctionJo.rst
+.. include:: snippets/CurrentState.rst
- .. include:: snippets/CurrentState.rst
+.. include:: snippets/Innovation.rst
- .. include:: snippets/Innovation.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
-See also
-++++++++
+- :ref:`section_ref_algorithm_KalmanFilter`
+- :ref:`section_ref_algorithm_ExtendedKalmanFilter`
+- :ref:`section_ref_algorithm_UnscentedKalmanFilter`
-References to other sections:
- - :ref:`section_ref_algorithm_KalmanFilter`
- - :ref:`section_ref_algorithm_ExtendedKalmanFilter`
- - :ref:`section_ref_algorithm_UnscentedKalmanFilter`
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo07.rst
-Bibliographical references:
- - [Evensen94]_
- - [Burgers98]_
- - [Evensen03]_
- - [WikipediaEnKF]_
+- [Evensen94]_
+- [Burgers98]_
+- [Evensen03]_
+- [WikipediaEnKF]_
Calculation algorithm "*ExtendedBlue*"
--------------------------------------
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm realizes an extended BLUE (Best Linear Unbiased Estimator) type
estimation of the state of a system.
In case of non-linearity, it is close to the :ref:`section_ref_algorithm_3DVAR`,
without being entirely equivalent.
-Optional and required commands
-++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
-The general required commands, available in the editing user interface, are the
-following:
+.. include:: snippets/Background.rst
- .. include:: snippets/Background.rst
+.. include:: snippets/BackgroundError.rst
- .. include:: snippets/BackgroundError.rst
+.. include:: snippets/Observation.rst
- .. include:: snippets/Observation.rst
+.. include:: snippets/ObservationError.rst
- .. include:: snippets/ObservationError.rst
+.. include:: snippets/ObservationOperator.rst
- .. include:: snippets/ObservationOperator.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03AdOp.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allows to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
+.. include:: snippets/NumberOfSamplesForQuantiles.rst
-The options of the algorithm are the following:
+.. include:: snippets/Quantiles.rst
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
+.. include:: snippets/SetSeed.rst
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["APosterioriCorrelations",
- "APosterioriCovariance", "APosterioriStandardDeviations",
- "APosterioriVariances", "BMA", "OMA", "OMB", "CurrentState",
- "CostFunctionJ", "CostFunctionJb", "CostFunctionJo", "Innovation",
- "SigmaBck2", "SigmaObs2", "MahalanobisConsistency", "SimulationQuantiles",
- "SimulatedObservationAtBackground", "SimulatedObservationAtCurrentState",
- "SimulatedObservationAtOptimum"].
+.. include:: snippets/SimulationForQuantiles.rst
- Example :
- ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
- .. include:: snippets/Quantiles.rst
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: [
+ "APosterioriCorrelations",
+ "APosterioriCovariance",
+ "APosterioriStandardDeviations",
+ "APosterioriVariances",
+ "BMA",
+ "OMA",
+ "OMB",
+ "CurrentState",
+ "CostFunctionJ",
+ "CostFunctionJb",
+ "CostFunctionJo",
+ "Innovation",
+ "SigmaBck2",
+ "SigmaObs2",
+ "MahalanobisConsistency",
+ "SimulationQuantiles",
+ "SimulatedObservationAtBackground",
+ "SimulatedObservationAtCurrentState",
+ "SimulatedObservationAtOptimum",
+ ].
- .. include:: snippets/SetSeed.rst
+ Example :
+ ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
- .. include:: snippets/NumberOfSamplesForQuantiles.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
- .. include:: snippets/SimulationForQuantiles.rst
+.. include:: snippets/Analysis.rst
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo05.rst
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. include:: snippets/APosterioriCorrelations.rst
-The unconditional outputs of the algorithm are the following:
+.. include:: snippets/APosterioriCovariance.rst
- .. include:: snippets/Analysis.rst
+.. include:: snippets/APosterioriStandardDeviations.rst
-The conditional outputs of the algorithm are the following:
+.. include:: snippets/APosterioriVariances.rst
- .. include:: snippets/APosterioriCorrelations.rst
+.. include:: snippets/BMA.rst
- .. include:: snippets/APosterioriCovariance.rst
+.. include:: snippets/CostFunctionJ.rst
- .. include:: snippets/APosterioriStandardDeviations.rst
+.. include:: snippets/CostFunctionJb.rst
- .. include:: snippets/APosterioriVariances.rst
+.. include:: snippets/CostFunctionJo.rst
- .. include:: snippets/BMA.rst
+.. include:: snippets/Innovation.rst
- .. include:: snippets/CostFunctionJ.rst
+.. include:: snippets/MahalanobisConsistency.rst
- .. include:: snippets/CostFunctionJb.rst
+.. include:: snippets/OMA.rst
- .. include:: snippets/CostFunctionJo.rst
+.. include:: snippets/OMB.rst
- .. include:: snippets/Innovation.rst
+.. include:: snippets/SigmaBck2.rst
- .. include:: snippets/MahalanobisConsistency.rst
+.. include:: snippets/SigmaObs2.rst
- .. include:: snippets/OMA.rst
+.. include:: snippets/SimulatedObservationAtBackground.rst
- .. include:: snippets/OMB.rst
+.. include:: snippets/SimulatedObservationAtOptimum.rst
- .. include:: snippets/SigmaBck2.rst
+.. include:: snippets/SimulationQuantiles.rst
- .. include:: snippets/SigmaObs2.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
- .. include:: snippets/SimulatedObservationAtBackground.rst
-
- .. include:: snippets/SimulatedObservationAtOptimum.rst
-
- .. include:: snippets/SimulationQuantiles.rst
-
-See also
-++++++++
-
-References to other sections:
- - :ref:`section_ref_algorithm_Blue`
- - :ref:`section_ref_algorithm_3DVAR`
- - :ref:`section_ref_algorithm_LinearityTest`
+- :ref:`section_ref_algorithm_Blue`
+- :ref:`section_ref_algorithm_3DVAR`
+- :ref:`section_ref_algorithm_LinearityTest`
Calculation algorithm "*ExtendedKalmanFilter*"
----------------------------------------------
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm realizes an estimation of the state of a dynamic system by a
extended Kalman Filter, using a non-linear calculation of the state and the
adapted to non-linear behavior but more costly. One can verify the linearity of
the operators with the help of the :ref:`section_ref_algorithm_LinearityTest`.
-Optional and required commands
-++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
-The general required commands, available in the editing user interface, are the
-following:
+.. include:: snippets/Background.rst
- .. include:: snippets/Background.rst
+.. include:: snippets/BackgroundError.rst
- .. include:: snippets/BackgroundError.rst
+.. include:: snippets/EvolutionError.rst
- .. include:: snippets/EvolutionError.rst
+.. include:: snippets/EvolutionModel.rst
- .. include:: snippets/EvolutionModel.rst
+.. include:: snippets/Observation.rst
- .. include:: snippets/Observation.rst
+.. include:: snippets/ObservationError.rst
- .. include:: snippets/ObservationError.rst
+.. include:: snippets/ObservationOperator.rst
- .. include:: snippets/ObservationOperator.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03AdOp.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allows to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
+.. include:: snippets/BoundsWithExtremes.rst
-The options of the algorithm are the following:
+.. include:: snippets/ConstrainedBy.rst
- .. include:: snippets/BoundsWithExtremes.rst
+.. include:: snippets/EstimationOf.rst
- .. include:: snippets/ConstrainedBy.rst
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
- .. include:: snippets/EstimationOf.rst
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: [
+ "APosterioriCorrelations",
+ "APosterioriCovariance",
+ "APosterioriStandardDeviations",
+ "APosterioriVariances",
+ "BMA",
+ "CostFunctionJ",
+ "CostFunctionJb",
+ "CostFunctionJo",
+ "CurrentState",
+ "Innovation",
+ ].
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
+ Example :
+ ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["APosterioriCorrelations",
- "APosterioriCovariance", "APosterioriStandardDeviations",
- "APosterioriVariances", "BMA", "CostFunctionJ", "CostFunctionJb",
- "CostFunctionJo", "CurrentState", "Innovation"].
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
- Example :
- ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
+.. include:: snippets/Analysis.rst
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo05.rst
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. include:: snippets/APosterioriCorrelations.rst
-The unconditional outputs of the algorithm are the following:
+.. include:: snippets/APosterioriCovariance.rst
- .. include:: snippets/Analysis.rst
+.. include:: snippets/APosterioriStandardDeviations.rst
-The conditional outputs of the algorithm are the following:
+.. include:: snippets/APosterioriVariances.rst
- .. include:: snippets/APosterioriCorrelations.rst
+.. include:: snippets/BMA.rst
- .. include:: snippets/APosterioriCovariance.rst
+.. include:: snippets/CostFunctionJ.rst
- .. include:: snippets/APosterioriStandardDeviations.rst
+.. include:: snippets/CostFunctionJb.rst
- .. include:: snippets/APosterioriVariances.rst
+.. include:: snippets/CostFunctionJo.rst
- .. include:: snippets/BMA.rst
+.. include:: snippets/CurrentState.rst
- .. include:: snippets/CostFunctionJ.rst
+.. include:: snippets/Innovation.rst
- .. include:: snippets/CostFunctionJb.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
- .. include:: snippets/CostFunctionJo.rst
-
- .. include:: snippets/CurrentState.rst
-
- .. include:: snippets/Innovation.rst
-
-See also
-++++++++
-
-References to other sections:
- - :ref:`section_ref_algorithm_KalmanFilter`
- - :ref:`section_ref_algorithm_EnsembleKalmanFilter`
- - :ref:`section_ref_algorithm_UnscentedKalmanFilter`
+- :ref:`section_ref_algorithm_KalmanFilter`
+- :ref:`section_ref_algorithm_EnsembleKalmanFilter`
+- :ref:`section_ref_algorithm_UnscentedKalmanFilter`
Checking algorithm "*GradientTest*"
-----------------------------------
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm allows to check the quality of the adjoint operator, by
calculating a residue with known theoretical properties. Different residue
which has to remain stable until the calculation precision is reached.
-Optional and required commands
-++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
-.. index:: single: AlgorithmParameters
-.. index:: single: CheckingPoint
-.. index:: single: ObservationOperator
-.. index:: single: AmplitudeOfInitialDirection
-.. index:: single: EpsilonMinimumExponent
-.. index:: single: InitialDirection
-.. index:: single: ResiduFormula
-.. index:: single: SetSeed
-.. index:: single: StoreSupplementaryCalculations
+.. include:: snippets/CheckingPoint.rst
-The general required commands, available in the editing user interface, are the
-following:
+.. include:: snippets/ObservationOperator.rst
- .. include:: snippets/CheckingPoint.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03Chck.rst
- .. include:: snippets/ObservationOperator.rst
+.. include:: snippets/AmplitudeOfInitialDirection.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allow to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
+.. include:: snippets/EpsilonMinimumExponent.rst
-The options of the algorithm are the following:
+.. include:: snippets/InitialDirection.rst
- .. include:: snippets/AmplitudeOfInitialDirection.rst
+.. include:: snippets/SetSeed.rst
- .. include:: snippets/EpsilonMinimumExponent.rst
+ResiduFormula
+ .. index:: single: ResiduFormula
- .. include:: snippets/InitialDirection.rst
+ This key indicates the residue formula that has to be used for the test. The
+ default choice is "Taylor", and the possible ones are "Taylor" (normalized
+ residue of the Taylor development of the operator, which has to decrease
+ with the square power of the perturbation), "TaylorOnNorm" (residue of the
+ Taylor development of the operator with respect to the perturbation to the
+ square, which has to remain constant) and "Norm" (residue obtained by taking
+ the norm of the Taylor development at zero order approximation, which
+ approximate the gradient, and which has to remain constant).
- .. include:: snippets/SetSeed.rst
+ Example :
+ ``{"ResiduFormula":"Taylor"}``
- ResiduFormula
- .. index:: single: ResiduFormula
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
- This key indicates the residue formula that has to be used for the test. The
- default choice is "Taylor", and the possible ones are "Taylor" (normalized
- residue of the Taylor development of the operator, which has to decrease
- with the square power of the perturbation), "TaylorOnNorm" (residue of the
- Taylor development of the operator with respect to the perturbation to the
- square, which has to remain constant) and "Norm" (residue obtained by taking
- the norm of the Taylor development at zero order approximation, which
- approximate the gradient, and which has to remain constant).
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: [
+ "CurrentState",
+ "Residu",
+ "SimulatedObservationAtCurrentState",
+ ].
- Example :
- ``{"ResiduFormula":"Taylor"}``
+ Example :
+ ``{"StoreSupplementaryCalculations":["CurrentState"]}``
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["CurrentState", "Residu",
- "SimulatedObservationAtCurrentState"].
+.. include:: snippets/Residu.rst
- Example :
- ``{"StoreSupplementaryCalculations":["CurrentState"]}``
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo05.rst
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+.. include:: snippets/CurrentState.rst
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. include:: snippets/SimulatedObservationAtCurrentState.rst
-The unconditional outputs of the algorithm are the following:
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
- .. include:: snippets/Residu.rst
-
-The conditional outputs of the algorithm are the following:
-
- .. include:: snippets/CurrentState.rst
-
- .. include:: snippets/SimulatedObservationAtCurrentState.rst
-
-See also
-++++++++
-
-References to other sections:
- - :ref:`section_ref_algorithm_FunctionTest`
- - :ref:`section_ref_algorithm_LinearityTest`
- - :ref:`section_ref_algorithm_TangentTest`
- - :ref:`section_ref_algorithm_AdjointTest`
+- :ref:`section_ref_algorithm_FunctionTest`
+- :ref:`section_ref_algorithm_LinearityTest`
+- :ref:`section_ref_algorithm_TangentTest`
+- :ref:`section_ref_algorithm_AdjointTest`
+- :ref:`section_ref_algorithm_LocalSensitivityTest`
Calculation algorithm "*KalmanFilter*"
--------------------------------------
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm realizes an estimation of the state of a dynamic system by a
Kalman Filter.
:ref:`section_ref_algorithm_UnscentedKalmanFilter` and the
:ref:`section_ref_algorithm_UnscentedKalmanFilter` that are more powerful.
-Optional and required commands
-++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
-The general required commands, available in the editing user interface, are the
-following:
+.. include:: snippets/Background.rst
- .. include:: snippets/Background.rst
+.. include:: snippets/BackgroundError.rst
- .. include:: snippets/BackgroundError.rst
+.. include:: snippets/EvolutionError.rst
- .. include:: snippets/EvolutionError.rst
+.. include:: snippets/EvolutionModel.rst
- .. include:: snippets/EvolutionModel.rst
+.. include:: snippets/Observation.rst
- .. include:: snippets/Observation.rst
+.. include:: snippets/ObservationError.rst
- .. include:: snippets/ObservationError.rst
+.. include:: snippets/ObservationOperator.rst
- .. include:: snippets/ObservationOperator.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03AdOp.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allows to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
+.. include:: snippets/EstimationOf.rst
-The options of the algorithm are the following:
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
- .. include:: snippets/EstimationOf.rst
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: [
+ "APosterioriCorrelations",
+ "APosterioriCovariance",
+ "APosterioriStandardDeviations",
+ "APosterioriVariances",
+ "BMA",
+ "CostFunctionJ",
+ "CostFunctionJb",
+ "CostFunctionJo",
+ "CurrentState",
+ "Innovation",
+ ].
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
+ Example : ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["APosterioriCorrelations",
- "APosterioriCovariance", "APosterioriStandardDeviations",
- "APosterioriVariances", "BMA", "CostFunctionJ", "CostFunctionJb",
- "CostFunctionJo", "CurrentState", "Innovation"].
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
- Example : ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
+.. include:: snippets/Analysis.rst
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo05.rst
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. include:: snippets/APosterioriCorrelations.rst
-The unconditional outputs of the algorithm are the following:
+.. include:: snippets/APosterioriCovariance.rst
- .. include:: snippets/Analysis.rst
+.. include:: snippets/APosterioriStandardDeviations.rst
-The conditional outputs of the algorithm are the following:
+.. include:: snippets/APosterioriVariances.rst
- .. include:: snippets/APosterioriCorrelations.rst
+.. include:: snippets/BMA.rst
- .. include:: snippets/APosterioriCovariance.rst
+.. include:: snippets/CostFunctionJ.rst
- .. include:: snippets/APosterioriStandardDeviations.rst
+.. include:: snippets/CostFunctionJb.rst
- .. include:: snippets/APosterioriVariances.rst
+.. include:: snippets/CostFunctionJo.rst
- .. include:: snippets/BMA.rst
+.. include:: snippets/CurrentState.rst
- .. include:: snippets/CostFunctionJ.rst
+.. include:: snippets/Innovation.rst
- .. include:: snippets/CostFunctionJb.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
- .. include:: snippets/CostFunctionJo.rst
-
- .. include:: snippets/CurrentState.rst
-
- .. include:: snippets/Innovation.rst
-
-See also
-++++++++
-
-References to other sections:
- - :ref:`section_ref_algorithm_ExtendedKalmanFilter`
- - :ref:`section_ref_algorithm_UnscentedKalmanFilter`
+- :ref:`section_ref_algorithm_ExtendedKalmanFilter`
+- :ref:`section_ref_algorithm_EnsembleKalmanFilter`
+- :ref:`section_ref_algorithm_UnscentedKalmanFilter`
Checking algorithm "*LinearityTest*"
------------------------------------
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm allows to check the linear quality of the operator, by
calculating a residue with known theoretical properties. Different residue
:math:`\alpha`, it is on this sub-domain that the linearity hypothesis of
:math:`F` is verified.
-Optional and required commands
-++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
-The general required commands, available in the editing user interface, are the
-following:
+.. include:: snippets/CheckingPoint.rst
- .. include:: snippets/CheckingPoint.rst
+.. include:: snippets/ObservationOperator.rst
- .. include:: snippets/ObservationOperator.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03Chck.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allow to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
+.. include:: snippets/AmplitudeOfInitialDirection.rst
-The options of the algorithm are the following:
+.. include:: snippets/EpsilonMinimumExponent.rst
- .. include:: snippets/AmplitudeOfInitialDirection.rst
+.. include:: snippets/InitialDirection.rst
- .. include:: snippets/EpsilonMinimumExponent.rst
+.. include:: snippets/SetSeed.rst
- .. include:: snippets/InitialDirection.rst
+ResiduFormula
+ .. index:: single: ResiduFormula
- .. include:: snippets/SetSeed.rst
+ This key indicates the residue formula that has to be used for the test. The
+ default choice is "CenteredDL", and the possible ones are "CenteredDL"
+ (residue of the difference between the function at nominal point and the
+ values with positive and negative increments, which has to stay very small),
+ "Taylor" (residue of the Taylor development of the operator normalized by
+ the nominal value, which has to stay very small), "NominalTaylor" (residue
+ of the order 1 approximations of the operator, normalized to the nominal
+ point, which has to stay close to 1), and "NominalTaylorRMS" (residue of the
+ order 1 approximations of the operator, normalized by RMS to the nominal
+ point, which has to stay close to 0).
- ResiduFormula
- .. index:: single: ResiduFormula
+ Example :
+ ``{"ResiduFormula":"CenteredDL"}``
- This key indicates the residue formula that has to be used for the test. The
- default choice is "CenteredDL", and the possible ones are "CenteredDL"
- (residue of the difference between the function at nominal point and the
- values with positive and negative increments, which has to stay very small),
- "Taylor" (residue of the Taylor development of the operator normalized by
- the nominal value, which has to stay very small), "NominalTaylor" (residue
- of the order 1 approximations of the operator, normalized to the nominal
- point, which has to stay close to 1), and "NominalTaylorRMS" (residue of the
- order 1 approximations of the operator, normalized by RMS to the nominal
- point, which has to stay close to 0).
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
- Example :
- ``{"ResiduFormula":"CenteredDL"}``
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: [
+ "CurrentState",
+ "Residu",
+ "SimulatedObservationAtCurrentState",
+ ].
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
+ Example :
+ ``{"StoreSupplementaryCalculations":["CurrentState"]}``
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["CurrentState", "Residu",
- "SimulatedObservationAtCurrentState"].
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
- Example :
- ``{"StoreSupplementaryCalculations":["CurrentState"]}``
+.. include:: snippets/Residu.rst
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo05.rst
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. include:: snippets/CurrentState.rst
-The unconditional outputs of the algorithm are the following:
+.. include:: snippets/SimulatedObservationAtCurrentState.rst
- .. include:: snippets/Residu.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
-The conditional outputs of the algorithm are the following:
-
- .. include:: snippets/CurrentState.rst
-
- .. include:: snippets/SimulatedObservationAtCurrentState.rst
-
-See also
-++++++++
-
-References to other sections:
- - :ref:`section_ref_algorithm_FunctionTest`
+- :ref:`section_ref_algorithm_FunctionTest`
Calculation algorithm "*NonLinearLeastSquares*"
-----------------------------------------------
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm realizes a state estimation by variational minimization of the
classical :math:`J` function of weighted "Least Squares":
In all cases, it is recommended to prefer the :ref:`section_ref_algorithm_3DVAR`
for its stability as for its behavior during optimization.
-Optional and required commands
-++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
-The general required commands, available in the editing user interface, are the
-following:
+.. include:: snippets/Background.rst
- .. include:: snippets/Background.rst
+.. include:: snippets/Observation.rst
- .. include:: snippets/Observation.rst
+.. include:: snippets/ObservationError.rst
- .. include:: snippets/ObservationError.rst
+.. include:: snippets/ObservationOperator.rst
- .. include:: snippets/ObservationOperator.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03AdOp.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allows to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
+Minimizer
+ .. index:: single: Minimizer
-The options of the algorithm are the following:
+ This key allows to choose the optimization minimizer. The default choice is
+ "LBFGSB", and the possible ones are "LBFGSB" (nonlinear constrained
+ minimizer, see [Byrd95]_, [Morales11]_ and [Zhu97]_), "TNC" (nonlinear
+ constrained minimizer), "CG" (nonlinear unconstrained minimizer), "BFGS"
+ (nonlinear unconstrained minimizer), "NCG" (Newton CG minimizer). It is
+ strongly recommended to stay with the default.
- Minimizer
- .. index:: single: Minimizer
+ Example :
+ ``{"Minimizer":"LBFGSB"}``
- This key allows to choose the optimization minimizer. The default choice is
- "LBFGSB", and the possible ones are "LBFGSB" (nonlinear constrained
- minimizer, see [Byrd95]_, [Morales11]_ and [Zhu97]_), "TNC" (nonlinear
- constrained minimizer), "CG" (nonlinear unconstrained minimizer), "BFGS"
- (nonlinear unconstrained minimizer), "NCG" (Newton CG minimizer). It is
- strongly recommended to stay with the default.
+.. include:: snippets/BoundsWithNone.rst
- Example :
- ``{"Minimizer":"LBFGSB"}``
+.. include:: snippets/MaximumNumberOfSteps.rst
- .. include:: snippets/BoundsWithNone.rst
+.. include:: snippets/CostDecrementTolerance.rst
- .. include:: snippets/MaximumNumberOfSteps.rst
+.. include:: snippets/ProjectedGradientTolerance.rst
- .. include:: snippets/CostDecrementTolerance.rst
+.. include:: snippets/GradientNormTolerance.rst
- .. include:: snippets/ProjectedGradientTolerance.rst
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
- .. include:: snippets/GradientNormTolerance.rst
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: ["BMA", "CostFunctionJ",
+ "CostFunctionJb", "CostFunctionJo", "CostFunctionJAtCurrentOptimum",
+ "CostFunctionJbAtCurrentOptimum", "CostFunctionJoAtCurrentOptimum",
+ "CurrentState", "CurrentOptimum", "IndexOfOptimum", "Innovation",
+ "InnovationAtCurrentState", "OMA", "OMB",
+ "SimulatedObservationAtBackground", "SimulatedObservationAtCurrentState",
+ "SimulatedObservationAtOptimum", "SimulatedObservationAtCurrentOptimum"].
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
-
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["BMA", "CostFunctionJ",
- "CostFunctionJb", "CostFunctionJo", "CostFunctionJAtCurrentOptimum",
- "CostFunctionJbAtCurrentOptimum", "CostFunctionJoAtCurrentOptimum",
- "CurrentState", "CurrentOptimum", "IndexOfOptimum", "Innovation",
- "InnovationAtCurrentState", "OMA", "OMB",
- "SimulatedObservationAtBackground", "SimulatedObservationAtCurrentState",
- "SimulatedObservationAtOptimum", "SimulatedObservationAtCurrentOptimum"].
-
- Example :
- ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
+ Example :
+ ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
*Tips for this algorithm:*
command is not required for this algorithm, and will not be used. The
simplest way is to give "1" as a STRING.
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
-
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
-The unconditional outputs of the algorithm are the following:
+.. include:: snippets/Analysis.rst
- .. include:: snippets/Analysis.rst
+.. include:: snippets/CostFunctionJ.rst
- .. include:: snippets/CostFunctionJ.rst
+.. include:: snippets/CostFunctionJb.rst
- .. include:: snippets/CostFunctionJb.rst
+.. include:: snippets/CostFunctionJo.rst
- .. include:: snippets/CostFunctionJo.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo05.rst
-The conditional outputs of the algorithm are the following:
+.. include:: snippets/BMA.rst
- .. include:: snippets/BMA.rst
+.. include:: snippets/CostFunctionJAtCurrentOptimum.rst
- .. include:: snippets/CostFunctionJAtCurrentOptimum.rst
+.. include:: snippets/CostFunctionJbAtCurrentOptimum.rst
- .. include:: snippets/CostFunctionJbAtCurrentOptimum.rst
+.. include:: snippets/CostFunctionJoAtCurrentOptimum.rst
- .. include:: snippets/CostFunctionJoAtCurrentOptimum.rst
+.. include:: snippets/CurrentOptimum.rst
- .. include:: snippets/CurrentOptimum.rst
+.. include:: snippets/CurrentState.rst
- .. include:: snippets/CurrentState.rst
+.. include:: snippets/IndexOfOptimum.rst
- .. include:: snippets/IndexOfOptimum.rst
+.. include:: snippets/Innovation.rst
- .. include:: snippets/Innovation.rst
+.. include:: snippets/InnovationAtCurrentState.rst
- .. include:: snippets/InnovationAtCurrentState.rst
+.. include:: snippets/OMA.rst
- .. include:: snippets/OMA.rst
+.. include:: snippets/OMB.rst
- .. include:: snippets/OMB.rst
+.. include:: snippets/SimulatedObservationAtBackground.rst
- .. include:: snippets/SimulatedObservationAtBackground.rst
+.. include:: snippets/SimulatedObservationAtCurrentOptimum.rst
- .. include:: snippets/SimulatedObservationAtCurrentOptimum.rst
+.. include:: snippets/SimulatedObservationAtCurrentState.rst
- .. include:: snippets/SimulatedObservationAtCurrentState.rst
+.. include:: snippets/SimulatedObservationAtOptimum.rst
- .. include:: snippets/SimulatedObservationAtOptimum.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
-See also
-++++++++
+- :ref:`section_ref_algorithm_3DVAR`
-References to other sections:
- - :ref:`section_ref_algorithm_3DVAR`
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo07.rst
-Bibliographical references:
- - [Byrd95]_
- - [Morales11]_
- - [Zhu97]_
+- [Byrd95]_
+- [Morales11]_
+- [Zhu97]_
Checking algorithm "*ObserverTest*"
-----------------------------------
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm allows to verify an external function, given by the user, used as
an *observer*. This external function can be applied to every of the variables
that can be potentially observed. It is activated only on those who are
explicitly associated with the *observer* in the interface.
-Optional and required commands
-++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
-The general required commands, available in the editing user interface, are the
-following:
-
- .. include:: snippets/Observers.rst
+.. include:: snippets/Observers.rst
The general optional commands, available in the editing user interface, are
indicated in :ref:`section_ref_assimilation_keywords`.
Calculation algorithm "*ParticleSwarmOptimization*"
---------------------------------------------------
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm realizes an estimation of the state of a system by minimization
of a cost function :math:`J` by using an evolutionary strategy of particle
swarm. It is a method that does not use the derivatives of the cost function.
It falls in the same category than the
-:ref:`section_ref_algorithm_DerivativeFreeOptimization` or the
-:ref:`section_ref_algorithm_DifferentialEvolution`.
+:ref:`section_ref_algorithm_DerivativeFreeOptimization`, the
+:ref:`section_ref_algorithm_DifferentialEvolution` or the
+:ref:`section_ref_algorithm_TabuSearch`.
This is an optimization method allowing for global minimum search of a general
error function :math:`J` of type :math:`L^1`, :math:`L^2` or :math:`L^{\infty}`,
with or without weights. The default error function is the augmented weighted
least squares function, classically used in data assimilation.
-Optional and required commands
-++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
-The general required commands, available in the editing user interface, are the
-following:
+.. include:: snippets/Background.rst
- .. include:: snippets/Background.rst
+.. include:: snippets/BackgroundError.rst
- .. include:: snippets/BackgroundError.rst
+.. include:: snippets/Observation.rst
- .. include:: snippets/Observation.rst
+.. include:: snippets/ObservationError.rst
- .. include:: snippets/ObservationError.rst
+.. include:: snippets/ObservationOperator.rst
- .. include:: snippets/ObservationOperator.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03AdOp.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allows to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
-
-The options of the algorithm are the following:
.. index:: single: NumberOfInsects
.. index:: single: SwarmVelocity
.. index:: single: GroupRecallRate
.. index:: single: QualityCriterion
.. index:: single: BoxBounds
- .. include:: snippets/MaximumNumberOfSteps_50.rst
-
- .. include:: snippets/MaximumNumberOfFunctionEvaluations.rst
+.. include:: snippets/MaximumNumberOfSteps_50.rst
- .. include:: snippets/QualityCriterion.rst
+.. include:: snippets/MaximumNumberOfFunctionEvaluations.rst
- NumberOfInsects
- This key indicates the number of insects or particles in the swarm. The
- default is 100, which is a usual default for this algorithm.
+.. include:: snippets/QualityCriterion.rst
- Example :
- ``{"NumberOfInsects":100}``
+NumberOfInsects
+ This key indicates the number of insects or particles in the swarm. The
+ default is 100, which is a usual default for this algorithm.
- SwarmVelocity
- This key indicates the part of the insect velocity which is imposed by the
- swarm. It is a positive floating point value. The default value is 1.
+ Example :
+ ``{"NumberOfInsects":100}``
- Example :
- ``{"SwarmVelocity":1.}``
+SwarmVelocity
+ This key indicates the part of the insect velocity which is imposed by the
+ swarm. It is a positive floating point value. The default value is 1.
- GroupRecallRate
- This key indicates the recall rate at the best swarm insect. It is a
- floating point value between 0 and 1. The default value is 0.5.
+ Example :
+ ``{"SwarmVelocity":1.}``
- Example :
- ``{"GroupRecallRate":0.5}``
+GroupRecallRate
+ This key indicates the recall rate at the best swarm insect. It is a
+ floating point value between 0 and 1. The default value is 0.5.
- BoxBounds
- This key allows to define upper and lower bounds for *increments* on every
- state variable being optimized (and not on state variables themselves).
- Bounds have to be given by a list of list of pairs of lower/upper bounds for
- each increment on variable, with extreme values every time there is no bound
- (``None`` is not allowed when there is no bound). This key is required and
- there is no default values.
+ Example :
+ ``{"GroupRecallRate":0.5}``
- Example :
- ``{"BoxBounds":[[-0.5,0.5], [0.01,2.], [0.,1.e99], [-1.e99,1.e99]]}``
+BoxBounds
+ This key allows to define upper and lower bounds for *increments* on every
+ state variable being optimized (and not on state variables themselves).
+ Bounds have to be given by a list of list of pairs of lower/upper bounds for
+ each increment on variable, with extreme values every time there is no bound
+ (``None`` is not allowed when there is no bound). This key is required and
+ there is no default values.
- .. include:: snippets/SetSeed.rst
+ Example :
+ ``{"BoxBounds":[[-0.5,0.5], [0.01,2.], [0.,1.e99], [-1.e99,1.e99]]}``
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
+.. include:: snippets/SetSeed.rst
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["BMA", "CostFunctionJ", "CostFunctionJb",
- "CostFunctionJo", "CurrentState", "OMA", "OMB", "Innovation",
- "SimulatedObservationAtBackground", "SimulatedObservationAtCurrentState",
- "SimulatedObservationAtOptimum"].
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
- Example :
- ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: [
+ "BMA",
+ "CostFunctionJ",
+ "CostFunctionJb",
+ "CostFunctionJo",
+ "CurrentState",
+ "OMA",
+ "OMB",
+ "Innovation",
+ "SimulatedObservationAtBackground",
+ "SimulatedObservationAtCurrentState",
+ "SimulatedObservationAtOptimum",
+ ].
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+ Example :
+ ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
-The unconditional outputs of the algorithm are the following:
+.. include:: snippets/Analysis.rst
- .. include:: snippets/Analysis.rst
+.. include:: snippets/CostFunctionJ.rst
- .. include:: snippets/CostFunctionJ.rst
+.. include:: snippets/CostFunctionJb.rst
- .. include:: snippets/CostFunctionJb.rst
+.. include:: snippets/CostFunctionJo.rst
- .. include:: snippets/CostFunctionJo.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo05.rst
-The conditional outputs of the algorithm are the following:
+.. include:: snippets/BMA.rst
- .. include:: snippets/BMA.rst
+.. include:: snippets/CurrentState.rst
- .. include:: snippets/CurrentState.rst
+.. include:: snippets/Innovation.rst
- .. include:: snippets/Innovation.rst
+.. include:: snippets/OMA.rst
- .. include:: snippets/OMA.rst
+.. include:: snippets/OMB.rst
- .. include:: snippets/OMB.rst
+.. include:: snippets/SimulatedObservationAtBackground.rst
- .. include:: snippets/SimulatedObservationAtBackground.rst
+.. include:: snippets/SimulatedObservationAtCurrentState.rst
- .. include:: snippets/SimulatedObservationAtCurrentState.rst
+.. include:: snippets/SimulatedObservationAtOptimum.rst
- .. include:: snippets/SimulatedObservationAtOptimum.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
-See also
-++++++++
+- :ref:`section_ref_algorithm_DerivativeFreeOptimization`
+- :ref:`section_ref_algorithm_DifferentialEvolution`
+- :ref:`section_ref_algorithm_TabuSearch`
-References to other sections:
- - :ref:`section_ref_algorithm_DerivativeFreeOptimization`
- - :ref:`section_ref_algorithm_DifferentialEvolution`
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo07.rst
-Bibliographical references:
- - [WikipediaPSO]_
+- [WikipediaPSO]_
Calculation algorithm "*QuantileRegression*"
--------------------------------------------
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm allows to estimate the conditional quantiles of the state
parameters distribution, expressed with a model of the observed variables. These
are then the quantiles on the observed variables which will allow to determine
the model parameters that satisfy to the quantiles conditions.
-Optional and required commands
-++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
-The general required commands, available in the editing user interface, are the
-following:
+.. include:: snippets/Background.rst
- .. include:: snippets/Background.rst
+.. include:: snippets/Observation.rst
- .. include:: snippets/Observation.rst
+.. include:: snippets/ObservationOperator.rst
- .. include:: snippets/ObservationOperator.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03AdOp.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allows to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
+.. include:: snippets/Quantile.rst
-The options of the algorithm are the following:
+.. include:: snippets/MaximumNumberOfSteps.rst
- .. include:: snippets/Quantile.rst
+.. include:: snippets/CostDecrementTolerance_6.rst
- .. include:: snippets/MaximumNumberOfSteps.rst
+.. include:: snippets/BoundsWithNone.rst
- .. include:: snippets/CostDecrementTolerance_6.rst
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
- .. include:: snippets/BoundsWithNone.rst
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: [
+ "BMA",
+ "CostFunctionJ",
+ "CostFunctionJb",
+ "CostFunctionJo",
+ "CurrentState",
+ "OMA",
+ "OMB",
+ "Innovation",
+ "SimulatedObservationAtBackground",
+ "SimulatedObservationAtCurrentState",
+ "SimulatedObservationAtOptimum",
+ ].
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
-
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["BMA", "CostFunctionJ", "CostFunctionJb",
- "CostFunctionJo", "CurrentState", "OMA", "OMB", "Innovation",
- "SimulatedObservationAtBackground", "SimulatedObservationAtCurrentState",
- "SimulatedObservationAtOptimum"].
-
- Example :
- ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
+ Example :
+ ``{"StoreSupplementaryCalculations":["BMA", "Innovation"]}``
*Tips for this algorithm:*
value, even if these commands are not required for this algorithm, and will
not be used. The simplest way is to give "1" as a STRING for both.
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
-
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
-The unconditional outputs of the algorithm are the following:
+.. include:: snippets/Analysis.rst
- .. include:: snippets/Analysis.rst
+.. include:: snippets/CostFunctionJ.rst
- .. include:: snippets/CostFunctionJ.rst
+.. include:: snippets/CostFunctionJb.rst
- .. include:: snippets/CostFunctionJb.rst
+.. include:: snippets/CostFunctionJo.rst
- .. include:: snippets/CostFunctionJo.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo05.rst
-The conditional outputs of the algorithm are the following:
+.. include:: snippets/BMA.rst
- .. include:: snippets/BMA.rst
+.. include:: snippets/CurrentState.rst
- .. include:: snippets/CurrentState.rst
+.. include:: snippets/Innovation.rst
- .. include:: snippets/Innovation.rst
+.. include:: snippets/OMA.rst
- .. include:: snippets/OMA.rst
+.. include:: snippets/OMB.rst
- .. include:: snippets/OMB.rst
+.. include:: snippets/SimulatedObservationAtBackground.rst
- .. include:: snippets/SimulatedObservationAtBackground.rst
+.. include:: snippets/SimulatedObservationAtCurrentState.rst
- .. include:: snippets/SimulatedObservationAtCurrentState.rst
+.. include:: snippets/SimulatedObservationAtOptimum.rst
- .. include:: snippets/SimulatedObservationAtOptimum.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
-See also
-++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo07.rst
-Bibliographical references:
- - [Buchinsky98]_
- - [Cade03]_
- - [Koenker00]_
- - [Koenker01]_
- - [WikipediaQR]_
+- [Buchinsky98]_
+- [Cade03]_
+- [Koenker00]_
+- [Koenker01]_
+- [WikipediaQR]_
Checking algorithm "*SamplingTest*"
-----------------------------------
-Description
-+++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo01.rst
This algorithm allows to calculate the values, linked to a :math:`\mathbf{x}`
state, of a general error function :math:`J` of type :math:`L^1`, :math:`L^2` or
To perform distributed or more complex sampling, see OPENTURNS module available
in SALOME.
-Optional and required commands
-++++++++++++++++++++++++++++++
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo02.rst
-The general required commands, available in the editing user interface, are the
-following:
+.. include:: snippets/CheckingPoint.rst
- .. include:: snippets/CheckingPoint.rst
+.. include:: snippets/BackgroundError.rst
- .. include:: snippets/BackgroundError.rst
+.. include:: snippets/Observation.rst
- .. include:: snippets/Observation.rst
+.. include:: snippets/ObservationError.rst
- .. include:: snippets/ObservationError.rst
+.. include:: snippets/ObservationOperator.rst
- .. include:: snippets/ObservationOperator.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo03Chck.rst
-The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
-of the command "*AlgorithmParameters*" allow to choose the specific options,
-described hereafter, of the algorithm. See
-:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
-command.
+.. include:: snippets/QualityCriterion.rst
-The options of the algorithm are the following:
-.. index:: single: SampleAsnUplet
-.. index:: single: SampleAsExplicitHyperCube
-.. index:: single: SampleAsMinMaxStepHyperCube
-.. index:: single: SampleAsIndependantRandomVariables
+.. include:: snippets/SampleAsExplicitHyperCube.rst
- SampleAsnUplet
- This key describes the calculations points as a list of n-uplets, each
- n-uplet being a state.
+.. include:: snippets/SampleAsIndependantRandomVariables.rst
- Example :
- ``{"SampleAsnUplet":[[0,1,2,3],[4,3,2,1],[-2,3,-4,5]]}`` for 3 points in a state space of dimension 4
+.. include:: snippets/SampleAsMinMaxStepHyperCube.rst
- SampleAsExplicitHyperCube
- This key describes the calculations points as an hyper-cube, from a given
- list of explicit sampling of each variable as a list. That is then a list of
- lists, each of them being potentially of different size.
+.. include:: snippets/SampleAsnUplet.rst
- Example : ``{"SampleAsExplicitHyperCube":[[0.,0.25,0.5,0.75,1.], [-2,2,1]]}`` for a state space of dimension 2
+.. include:: snippets/SetDebug.rst
- SampleAsMinMaxStepHyperCube
- This key describes the calculations points as an hyper-cube, from a given
- list of implicit sampling of each variable by a triplet *[min,max,step]*.
- That is then a list of the same size than the one of the state. The bounds
- are included.
+.. include:: snippets/SetSeed.rst
- Example :
- ``{"SampleAsMinMaxStepHyperCube":[[0.,1.,0.25],[-1,3,1]]}`` for a state space of dimension 2
+StoreSupplementaryCalculations
+ .. index:: single: StoreSupplementaryCalculations
- SampleAsIndependantRandomVariables
- This key describes the calculations points as an hyper-cube, for which the
- points on each axis come from a independent random sampling of the axis
- variable, under the specification of the distribution, its parameters and
- the number of points in the sample, as a list ``['distribution',
- [parameters], number]`` for each axis. The possible distributions are
- 'normal' of parameters (mean,std), 'lognormal' of parameters (mean,sigma),
- 'uniform' of parameters (low,high), or 'weibull' of parameter (shape). That
- is then a list of the same size than the one of the state.
+ This list indicates the names of the supplementary variables that can be
+ available at the end of the algorithm. It involves potentially costly
+ calculations or memory consumptions. The default is a void list, none of
+ these variables being calculated and stored by default. The possible names
+ are in the following list: [
+ "CostFunctionJ",
+ "CostFunctionJb",
+ "CostFunctionJo",
+ "CurrentState",
+ "InnovationAtCurrentState",
+ "SimulatedObservationAtCurrentState",
+ ].
- Example :
- ``{"SampleAsIndependantRandomVariables":[ ['normal',[0.,1.],3], ['uniform',[-2,2],4]]`` for a state space of dimension 2
+ Example :
+ ``{"StoreSupplementaryCalculations":["CostFunctionJ", "SimulatedObservationAtCurrentState"]}``
- .. include:: snippets/QualityCriterion.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo04.rst
- .. include:: snippets/SetDebug.rst
+.. include:: snippets/CostFunctionJ.rst
- .. include:: snippets/SetSeed.rst
+.. include:: snippets/CostFunctionJb.rst
- StoreSupplementaryCalculations
- .. index:: single: StoreSupplementaryCalculations
+.. include:: snippets/CostFunctionJo.rst
- This list indicates the names of the supplementary variables that can be
- available at the end of the algorithm. It involves potentially costly
- calculations or memory consumptions. The default is a void list, none of
- these variables being calculated and stored by default. The possible names
- are in the following list: ["CostFunctionJ", "CostFunctionJb",
- "CostFunctionJo", "CurrentState", "InnovationAtCurrentState",
- "SimulatedObservationAtCurrentState"].
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo05.rst
- Example :
- ``{"StoreSupplementaryCalculations":["CostFunctionJ", "SimulatedObservationAtCurrentState"]}``
+.. include:: snippets/CurrentState.rst
-Information and variables available at the end of the algorithm
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+.. include:: snippets/InnovationAtCurrentState.rst
-At the output, after executing the algorithm, there are variables and
-information originating from the calculation. The description of
-:ref:`section_ref_output_variables` show the way to obtain them by the method
-named ``get`` of the variable "*ADD*" of the post-processing. The input
-variables, available to the user at the output in order to facilitate the
-writing of post-processing procedures, are described in the
-:ref:`subsection_r_o_v_Inventaire`.
+.. include:: snippets/SimulatedObservationAtCurrentState.rst
-The unconditional outputs of the algorithm are the following:
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo06.rst
- .. include:: snippets/CostFunctionJ.rst
+- :ref:`section_ref_algorithm_FunctionTest`
+- :ref:`section_ref_algorithm_LocalSensitivityTest`
- .. include:: snippets/CostFunctionJb.rst
+.. ------------------------------------ ..
+.. include:: snippets/Header2Algo08.rst
- .. include:: snippets/CostFunctionJo.rst
-
-The conditional outputs of the algorithm are the following:
-
- .. include:: snippets/CurrentState.rst
-
- .. include:: snippets/InnovationAtCurrentState.rst
-
- .. include:: snippets/SimulatedObservationAtCurrentState.rst
-
-See also
-++++++++
-
-References to other sections:
- - :ref:`section_ref_algorithm_FunctionTest`
-
-References to other SALOME modules:
- - OPENTURNS, see the *User guide of OPENTURNS module* in the main "*Help*" menu of SALOME platform
+- OPENTURNS, see the *User guide of OPENTURNS module* in the main "*Help*" menu of SALOME platform
module, etc.
Other usage examples are also given for :ref:`section_u_step4` of the
-:ref:`section_using` section, or in part :ref:`section_examples`.
+:ref:`section_gui_in_salome` section, or in part :ref:`section_tutorials_in_salome`.
Cross compliance of the information available at the output
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
================================================================================
The following sections present the reference description of the ADAO commands
-and keywords available through the GUI or through scripts. Two first common
-sections present the :ref:`section_reference_entry` and the
-:ref:`section_reference_special_entry`. After that, one describes successively
-the :ref:`section_reference_assimilation` and the
+and keywords available through the textual interface (TUI), the graphical
+interface (GUI) or through scripts. Two first common sections present the
+:ref:`section_reference_entry` and the :ref:`section_reference_special_entry`.
+After that, one describes successively the
+:ref:`section_reference_assimilation` and the
:ref:`section_reference_checking`.
-Each command or keyword to be defined through the ADAO GUI has some properties.
-The first property is to be *required*, *optional* or only factual, describing a
-type of input. The second property is to be an "open" variable with a fixed type
-but with any value allowed by the type, or a "restricted" variable, limited to
-some specified values. The embedded case editor GUI having build-in validating
-capacities, the properties of the commands or keywords given through this GUI
-are automatically correct.
+Each command or keyword to be defined through the ADAO TUI or GUI has some
+properties. The first property is to be *required*, *optional* or only factual,
+describing a type of input. The second property is to be an "open" variable
+with a fixed type but with any value allowed by the type, or a "restricted"
+variable, limited to some specified values. The embedded case editor GUI having
+build-in validating capacities, the properties of the commands or keywords
+given through this interface are automatically correct.
.. _section_reference_entry:
available in ADAO, detailing their usage characteristics and their options.
Some examples on these commands usage are available in the section
-:ref:`section_examples` and in the sample files installed with the ADAO module.
+:ref:`section_tutorials_in_salome`, in the section
+:ref:`section_tutorials_in_python` and in the sample files installed with ADAO.
The mathematical notations used afterward are explained in the section
:ref:`section_theory`.
.. toctree::
:maxdepth: 1
- ref_assimilation_keywords
ref_algorithm_3DVAR
ref_algorithm_4DVAR
ref_algorithm_Blue
ref_algorithm_NonLinearLeastSquares
ref_algorithm_ParticleSwarmOptimization
ref_algorithm_QuantileRegression
+ ref_algorithm_TabuSearch
ref_algorithm_UnscentedKalmanFilter
+ ref_assimilation_keywords
.. _section_reference_checking:
their usage characteristics and their options.
Some examples on these commands usage are available in the section
-:ref:`section_examples` and in the sample files installed with the ADAO module.
+:ref:`section_tutorials_in_salome`, in the section
+:ref:`section_tutorials_in_python` and in the sample files installed with ADAO.
The mathematical notations used afterward are explained in the section
:ref:`section_theory`.
.. toctree::
:maxdepth: 1
- ref_checking_keywords
ref_algorithm_AdjointTest
ref_algorithm_FunctionTest
ref_algorithm_GradientTest
ref_algorithm_LinearityTest
+ ref_algorithm_LocalSensitivityTest
ref_algorithm_ObserverTest
ref_algorithm_SamplingTest
ref_algorithm_TangentTest
+ ref_checking_keywords
