.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples/post_process/plot_som.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        Click :ref:`here <sphx_glr_download_examples_post_process_plot_som.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_examples_post_process_plot_som.py:


Self-Organizing Map
===================

In this example, we illustrate the use of the :class:`~gemseo.post.som.SOM` plot
on the Sobieski's SSBJ problem.

.. GENERATED FROM PYTHON SOURCE LINES 30-34

.. code-block:: default

    from __future__ import absolute_import, division, print_function, unicode_literals

    from future import standard_library








.. GENERATED FROM PYTHON SOURCE LINES 35-39

Import
------
The first step is to import some functions from the API
and a method to get the design space.

.. GENERATED FROM PYTHON SOURCE LINES 39-46

.. code-block:: default

    from gemseo.api import configure_logger, create_discipline, create_scenario
    from gemseo.problems.sobieski.core import SobieskiProblem

    configure_logger()

    standard_library.install_aliases()








.. GENERATED FROM PYTHON SOURCE LINES 47-51

Create disciplines
------------------
Then, we instantiate the disciplines of the Sobieski's SSBJ problem:
Propulsion, Aerodynamics, Structure and Mission

.. GENERATED FROM PYTHON SOURCE LINES 51-60

.. code-block:: default

    disciplines = create_discipline(
        [
            "SobieskiPropulsion",
            "SobieskiAerodynamics",
            "SobieskiStructure",
            "SobieskiMission",
        ]
    )








.. GENERATED FROM PYTHON SOURCE LINES 61-64

Create design space
-------------------
We also read the design space from the :class:`.SobieskiProblem`.

.. GENERATED FROM PYTHON SOURCE LINES 64-66

.. code-block:: default

    design_space = SobieskiProblem().read_design_space()








.. GENERATED FROM PYTHON SOURCE LINES 67-73

Create and execute scenario
---------------------------
The next step is to build a MDO scenario in order to maximize the range,
encoded 'y_4', with respect to the design parameters, while satisfying the
inequality constraints 'g_1', 'g_2' and 'g_3'. We can use the MDF formulation,
the Monte Carlo DOE algorithm and 30 samples.

.. GENERATED FROM PYTHON SOURCE LINES 73-86

.. code-block:: default

    scenario = create_scenario(
        disciplines,
        formulation="MDF",
        objective_name="y_4",
        maximize_objective=True,
        design_space=design_space,
        scenario_type="DOE",
    )
    scenario.set_differentiation_method("user")
    for constraint in ["g_1", "g_2", "g_3"]:
        scenario.add_constraint(constraint, "ineq")
    scenario.execute({"algo": "OT_MONTE_CARLO", "n_samples": 30})





.. rst-class:: sphx-glr-script-out

 Out:

 .. code-block:: none


    {'eval_jac': False, 'algo': 'OT_MONTE_CARLO', 'n_samples': 30}



.. GENERATED FROM PYTHON SOURCE LINES 87-92

Post-process scenario
---------------------
Lastly, we post-process the scenario by means of the
:class:`~gemseo.post.som.SOM` plot which performs a self organizing map
clustering on optimization history.

.. GENERATED FROM PYTHON SOURCE LINES 92-93

.. code-block:: default

    scenario.post_process("SOM", save=False, show=True)



.. image:: /examples/post_process/images/sphx_glr_plot_som_001.png
    :alt: Self Organizing Maps of the design space, -y_4, g_1_0, g_1_1, g_1_2, g_1_3, g_1_4, g_1_5, g_1_6, g_2, g_3_0, g_3_1, g_3_2, g_3_3
    :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 Out:

 .. code-block:: none


    <gemseo.post.som.SOM object at 0x7fc298921280>




.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  2.432 seconds)


.. _sphx_glr_download_examples_post_process_plot_som.py:


.. only :: html

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



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

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



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

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


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_