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

.. only:: html

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

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

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

.. _sphx_glr_examples_api_plot_optimization.py:


Optimization algorithms
=======================

In this example, we will discover the different functions of the API
related to optimization algorithms.

.. GENERATED FROM PYTHON SOURCE LINES 31-45

.. code-block:: default

    from __future__ import absolute_import, division, print_function, unicode_literals

    from future import standard_library

    from gemseo.api import (
        configure_logger,
        get_algorithm_options_schema,
        get_available_opt_algorithms,
    )

    configure_logger()

    standard_library.install_aliases()








.. GENERATED FROM PYTHON SOURCE LINES 46-51

Get available optimization algorithms
-------------------------------------

The :meth:`~gemseo.api.get_available_opt_algorithms` function returns the list
of optimization algorithms available in |g| or in external modules

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.. code-block:: default

    print(get_available_opt_algorithms())





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

 Out:

 .. code-block:: none

    ['NLOPT_MMA', 'NLOPT_COBYLA', 'NLOPT_SLSQP', 'NLOPT_BOBYQA', 'NLOPT_BFGS', 'NLOPT_NEWUOA', 'SLSQP', 'L-BFGS-B', 'TNC']




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Get options schema
------------------
For a given optimization algorithm, e.g. :code:`"NLOPT_SLSQP"`,
we can get the options; e.g.

.. GENERATED FROM PYTHON SOURCE LINES 58-59

.. code-block:: default

    print(get_algorithm_options_schema("NLOPT_SLSQP"))




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

 Out:

 .. code-block:: none

    {'name': 'NLOPT_options', '$schema': 'http://json-schema.org/draft-04/schema', 'type': 'object', 'properties': {'xtol_rel': {'minimum': 0.0, 'type': 'number', 'description': 'Relative design parameter tolerance\n:type xtol_rel: float\n'}, 'normalize_design_space': {'type': 'boolean', 'description': 'If True, scales variables in [0, 1]\n:type normalize_design_space: bool\n'}, 'xtol_abs': {'minimum': 0.0, 'type': 'number', 'description': 'Design parameter tolerance\n:type xtol_abs: float\n'}, 'ftol_rel': {'minimum': 0.0, 'type': 'number', 'description': 'Relative objective function tolerance\n:type ftol_rel: float\n'}, 'ftol_abs': {'minimum': 0.0, 'type': 'number', 'description': 'Objective function tolerance\n:type ftol_abs: float\n'}, 'max_iter': {'minimum': 1, 'type': 'integer', 'description': 'maximum number of iterations\n:type max_iter: int\n'}, 'max_time': {'minimum': 0.0, 'type': 'number', 'description': 'Maximum time\n:type max_time: float\n'}, 'stopval': {'type': 'number', 'description': 'Stop when an objective value of at least stopval\nis found:\nstop minimizing when an objective value :math:`\\leq` stopval is\nfound,\nor stop maximizing a value :math:`\\geq` stopval is found.\n:type stopval: float\n'}, 'ctol_abs': {'minimum': 0.0, 'type': 'number', 'description': 'Absolute tolerance for constraints\n:type ctol_abs: float\n'}, 'eq_tolerance': {'minimum': 0.0, 'type': 'number', 'description': 'equality tolerance\n:type eq_tolerance: float\n'}, 'ineq_tolerance': {'minimum': 0.0, 'type': 'number', 'description': 'inequality tolerance\n:type ineq_tolerance: float\n'}, 'init_step': {'minimum': 0.0, 'type': 'number', 'description': 'initial step size for derivavtive free algorithms\nincreasing init_step will make the initial DOE in COBYLA\nwider steps in the design variables. By defaults, each variable\nis set to x0 + a perturbation that worths 0.25*(ub_i-x0_i) for i\nin xrange(len(x0))\n:type init_step: float'}}, 'required': ['max_iter']}





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

   **Total running time of the script:** ( 0 minutes  0.002 seconds)


.. _sphx_glr_download_examples_api_plot_optimization.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_optimization.py <plot_optimization.py>`



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

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


.. only:: html

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

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