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.. "examples/api/plot_mda.py"
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.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_examples_api_plot_mda.py>`
        to download the full example code

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.. _sphx_glr_examples_api_plot_mda.py:


MDA
===

In this example, we will discover the different high-level functions
related to MDAs, which are the |g|' objects dedicated to the
feasibility of the multidisciplinary coupling. All classes
implementing MDAs inherit from :class:`.BaseMDA` which is an abstract class.

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.. code-block:: Python


    from __future__ import annotations

    from gemseo import configure_logger
    from gemseo import create_discipline
    from gemseo import create_mda
    from gemseo import get_available_mdas
    from gemseo import get_mda_options_schema

    configure_logger()






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    <RootLogger root (INFO)>



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Get available MDA
-----------------

The :func:`.get_available_mdas` function returns the list
of MDAs available in |g| or in external modules

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.. code-block:: Python

    get_available_mdas()





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    ['MDAChain', 'MDAGSNewton', 'MDAGaussSeidel', 'MDAJacobi', 'MDANewtonRaphson', 'MDAQuasiNewton', 'MDASequential']



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Get MDA options schema
----------------------
For a given MDA algorithm, e.g. ``"MDAGaussSeidel"``,
we can get the options; e.g.

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.. code-block:: Python

    get_mda_options_schema("MDAGaussSeidel")





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    {'$schema': 'http://json-schema.org/schema#', 'type': 'object', 'properties': {'name': {'description': 'The name to be given to the MDA. If ``None``, use the name of the class.', 'type': 'null'}, 'max_mda_iter': {'description': 'The maximum iterations number for the MDA algorithm.', 'type': 'integer'}, 'grammar_type': {'description': 'The type of the input and output grammars.', 'type': 'string'}, 'tolerance': {'description': 'The tolerance of the iterative direct coupling solver; the norm of the current residuals divided by initial residuals norm shall be lower than the tolerance to stop iterating.', 'type': 'number'}, 'linear_solver_tolerance': {'description': 'The tolerance of the linear solver in the adjoint equation.', 'type': 'number'}, 'warm_start': {'description': 'Whether the second iteration and ongoing start from the previous coupling solution.', 'type': 'boolean'}, 'use_lu_fact': {'description': 'Whether to store a LU factorization of the matrix when using adjoint/forward differentiation. to solve faster multiple RHS problem.', 'type': 'boolean'}, 'over_relax_factor': {'description': 'Deprecated, please consider using :attr:`MDA.over_relaxation_factor` instead. The relaxation coefficient, used to make the method more robust, if ``0<over_relax_factor<1`` or faster if ``1<over_relax_factor<=2``. If ``over_relax_factor =1.``, it is deactivated.', 'type': 'null'}, 'coupling_structure': {'description': 'The coupling structure to be used by the MDA. If ``None``, it is created from `disciplines`.', 'type': 'null'}, 'log_convergence': {'description': 'Whether to log the MDA convergence, expressed in terms of normed residuals.', 'type': 'boolean'}, 'linear_solver': {'description': 'The name of the linear solver.', 'type': 'string'}, 'linear_solver_options': {'description': 'The options passed to the linear solver factory.', 'type': 'null'}, 'acceleration_method': {'description': 'The acceleration method to be used to improve the convergence rate of the fixed point iteration method.', 'type': 'string'}, 'over_relaxation_factor': {'description': 'The over-relaxation factor.', 'type': 'number'}}}



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Create an MDA
-------------
The high-level function :func:`~gemseo.create_mda` can be used
to create a scenario:

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.. code-block:: Python

    disciplines = create_discipline(["Sellar1", "Sellar2"])
    mda = create_mda("MDAGaussSeidel", disciplines)
    output_data = mda.execute()
    output_data




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    {'y_2': (1.80000000566577+0j), 'x_local': 0j, 'x_shared': array([1.+0.j, 0.+0.j]), 'y_1': (0.80000000566577+0j), 'MDA residuals norm': array([4.79612702e-07])}




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   **Total running time of the script:** (0 minutes 0.016 seconds)


.. _sphx_glr_download_examples_api_plot_mda.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_mda.ipynb <plot_mda.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_mda.py <plot_mda.py>`


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