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.. "examples/post_process/post_process_scenario.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

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

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

.. _sphx_glr_examples_post_process_post_process_scenario.py:


Post-process a scenario
=======================

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.. code-block:: Python


    from __future__ import annotations

    from gemseo import create_design_space
    from gemseo import create_discipline
    from gemseo import create_scenario
    from gemseo import execute_post


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We consider a minimization problem over the interval :math:`[0,1]`
of the :math:`f(x)=x^2` objective function:

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.. code-block:: Python

    discipline = create_discipline("AnalyticDiscipline", expressions={"y": "x**2"})

    design_space = create_design_space()
    design_space.add_variable("x", l_b=0.0, u_b=1.0)

    scenario = create_scenario([discipline], "DisciplinaryOpt", "y", design_space)


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We solve this optimization problem with the gradient-free algorithm COBYLA:

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.. code-block:: Python

    scenario.execute({"algo": "NLOPT_COBYLA", "max_iter": 10})


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Then,
we can post-process this :class:`.MDOScenario`
either with its method :meth:`~.MDOScenario.post_process`:

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.. code-block:: Python

    scenario.post_process("BasicHistory", variable_names=["y"])


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or with the function :func:`.execute_post`:

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.. code-block:: Python

    execute_post(scenario, "BasicHistory", variable_names=["y"])


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.. note::
   By default, |g| saves the images on the disk.
   Use ``save=False`` to not save figures and ``show=True`` to display them on the screen.

.. seealso:: `Post-processing algorithms <index.html#algorithms>`_.


.. _sphx_glr_download_examples_post_process_post_process_scenario.py:

.. only:: html

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

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

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

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

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


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