..
   Copyright 2021 IRT Saint-Exupéry, https://www.irt-saintexupery.com

   This work is licensed under the Creative Commons Attribution-ShareAlike 4.0
   International License. To view a copy of this license, visit
   http://creativecommons.org/licenses/by-sa/4.0/ or send a letter to Creative
   Commons, PO Box 1866, Mountain View, CA 94042, USA.

.. _gen_doe_algos:

DOE algorithms
==============

.. warning::
   Some capabilities may require the :ref:`installation <installation>` of |g| with :ref:`all its features <dependencies>`
   and some others may depend on :ref:`plugins <plugins>`.

.. warning::
   All the features of the wrapped libraries may not be exposed through |g|.


.. note::
   The algorithm settings can be passed to a function of the form

   .. code-block:: python

      function(..., settings_model: AlgorithmSettings | None = None, **settings: Any)

   either one by one:

   .. code-block:: python

      function(..., setting_name_1=setting_name_1, setting_name_2=setting_name_2, ...)

   or using the argument name ``"settings_model"`` and the Pydantic model associated with the algorithm:

   .. code-block:: python

      settings_model = AlgorithmSettings(setting_name_1=setting_name_1, setting_name_2=setting_name_2, ...)
      function(..., settings_model=settings_model)




.. seealso::
   You can find more information about this family of algorithms in :ref:`the user guide <doe>`.





.. _CustomDOE_options:

CustomDOE
---------



Module: :class:`gemseo.algos.doe.custom_doe.custom_doe`


This samples are provided either as a file in text or csv format or as a sequence of sequences of numbers.



.. code-block:: python
   :caption: Pydantic model of the settings for CustomDOE

   from gemseo.settings.doe import CustomDOE_Settings


































































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**comments** : *str | collections.abc.Sequence[str], optional*

The (list of) characters used to indicate the start of a comment.

No comments if empty.


By default it is set to #.


.. raw:: html

    </li>

    <li>

**delimiter** : *<class 'str'>, optional*

The character used to separate values.


By default it is set to ,.


.. raw:: html

    </li>

    <li>

**doe_file** : *str | pathlib.Path*

The path to the file containing the input samples.

If empty, use ``samples``.


By default it is set to .


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**samples** : *gemseo.utils.pydantic_ndarray._NDArrayPydantic[typing.Any, numpy.dtype[+_ScalarType_co]] | collections.abc.Mapping[str, gemseo.utils.pydantic_ndarray._NDArrayPydantic[typing.Any, numpy.dtype[+_ScalarType_co]]] | collections.abc.Sequence[collections.abc.Mapping[str, gemseo.utils.pydantic_ndarray._NDArrayPydantic[typing.Any, numpy.dtype[+_ScalarType_co]]]], optional*

The input samples.

They must be at least a 2D-array, a dictionary of 2D-arrays
or a list of dictionaries of 1D-arrays. If empty, use ``doe_file``.


By default it is set to {}.


.. raw:: html

    </li>

    <li>

**skiprows** : *<class 'int'>, optional*

The number of first lines to skip.


By default it is set to 0.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _DiagonalDOE_options:

DiagonalDOE
-----------



Module: :class:`gemseo.algos.doe.diagonal_doe.diagonal_doe`


Diagonal design of experiments



.. code-block:: python
   :caption: Pydantic model of the settings for DiagonalDOE

   from gemseo.settings.doe import DiagonalDOE_Settings
















































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**n_samples** : *<class 'int'>, optional*

The number of samples.

The number of samples must be greater than or equal than 2.


By default it is set to 2.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**reverse** : *collections.abc.Sequence[str], optional*

The dimensions or variables to sample from upper to lower bounds.

If empty, every dimension will be sampled from lower to upper bounds.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _Halton_options:

Halton
------



Module: :class:`gemseo.algos.doe.scipy.scipy_doe`


Halton sequence



.. code-block:: python
   :caption: Pydantic model of the settings for Halton

   from gemseo.settings.doe import Halton_Settings


























































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**optimization** : *gemseo.algos.doe.scipy.settings.base_scipy_doe_settings.Optimizer | None, optional*

The name of an optimization scheme to improve the DOE's quality.

If ``None``, use the DOE as is. New in SciPy 1.10.0.


By default it is set to None.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**scramble** : *<class 'bool'>, optional*

Whether to use scrambling (Owen type).

Only available with SciPy >= 1.10.0.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :attr:`.seed`.


By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _LHS_options:

LHS
---



Module: :class:`gemseo.algos.doe.scipy.scipy_doe`


Latin hypercube sampling (LHS)



.. code-block:: python
   :caption: Pydantic model of the settings for LHS

   from gemseo.settings.doe import LHS_Settings
































































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**optimization** : *gemseo.algos.doe.scipy.settings.base_scipy_doe_settings.Optimizer | None, optional*

The name of an optimization scheme to improve the DOE's quality.

If ``None``, use the DOE as is. New in SciPy 1.10.0.


By default it is set to None.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**scramble** : *<class 'bool'>, optional*

Whether to use scrambling (Owen type).

Only available with SciPy >= 1.10.0.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :attr:`.seed`.


By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**strength** : *<enum 'Strength'>, optional*

The strength of the LHS.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _MC_options:

MC
--



Module: :class:`gemseo.algos.doe.scipy.scipy_doe`


Monte Carlo sampling



.. code-block:: python
   :caption: Pydantic model of the settings for MC

   from gemseo.settings.doe import MC_Settings














































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :attr:`.seed`.


By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _MorrisDOE_options:

MorrisDOE
---------



Module: :class:`gemseo.algos.doe.morris_doe.morris_doe`


The DOE used by the Morris sensitivity analysis.



.. code-block:: python
   :caption: Pydantic model of the settings for MorrisDOE

   from gemseo.settings.doe import MorrisDOE_Settings




























































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**doe_algo_name** : *<class 'str'>, optional*

The name of the DOE algorithm to repeat the OAT DOE.


By default it is set to PYDOE_LHS.


.. raw:: html

    </li>

    <li>

**doe_algo_settings** : *collections.abc.Mapping[str, typing.Any], optional*

The options of the DOE algorithm.


By default it is set to {}.


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**n_samples** : *<class 'int'>, optional*

The maximum number of samples required by the user.

            If 0, deduce it from the design space dimension and ``n_replicates``.
            


By default it is set to 0.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**step** : *<class 'float'>, optional*

The relative step of the OAT DOE.


By default it is set to 0.05.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _OATDOE_options:

OATDOE
------



Module: :class:`gemseo.algos.doe.oat_doe.oat_doe`


The DOE used by a One-factor-at-a-Time sensitivity analysis.



.. code-block:: python
   :caption: Pydantic model of the settings for OATDOE

   from gemseo.settings.doe import OATDOE_Settings














































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**initial_point** : *gemseo.utils.pydantic_ndarray._NDArrayPydantic[typing.Any, numpy.dtype[+_ScalarType_co]]*

The initial point of the OAT DOE.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**step** : *<class 'float'>, optional*

The relative step of the OAT DOE.

The step in the ``x`` direction is
step*(max_x-min_x)`` if ``x+step*(max_x-min_x)<=max_x`` and
``-step*(max_x- min_x)`` otherwise.


By default it is set to 0.05.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _OT_AXIAL_options:

OT_AXIAL
--------



Module: :class:`gemseo.algos.doe.openturns.openturns`


Axial design



.. code-block:: python
   :caption: Pydantic model of the settings for OT_AXIAL

   from gemseo.settings.doe import OT_AXIAL_Settings




More details about the algorithm and its settings on http://openturns.github.io/openturns/latest/user_manual/_generated/openturns.Axial.html.

























































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**centers** : *collections.abc.Sequence[float] | float, optional*

The center of DOE in the unit hypercube.

This option is available for the axial, composite and factorial DOE
algorithm. If scalar, this value is applied to each direction of the
hypercube; the values must be in :math:`]0,1[`.



By default it is set to 0.5.


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**levels** : *float | collections.abc.Sequence[float], optional*

The levels.

In the case of axial, composite and factorial DOEs, the positions of the levels
relative to the center; the levels will be equispaced and symmetrical relative
to the center; e.g. ``[0.2, 0.8]`` in dimension 1 will generate the samples
``[0.15, 0.6, 0.75, 0.8, 0.95, 1]`` for an axial DOE; the values must be in
:math:`]0,1]`.

In the case of a full-factorial DOE, the number of levels per input direction;
if scalar, this value is applied to each input direction.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**n_samples** : *<class 'int'>, optional*

The number of samples.

If 0, set from the options.


By default it is set to 0.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :class:`~.BaseDOELibrary.seed`.



By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _OT_COMPOSITE_options:

OT_COMPOSITE
------------



Module: :class:`gemseo.algos.doe.openturns.openturns`


Composite design



.. code-block:: python
   :caption: Pydantic model of the settings for OT_COMPOSITE

   from gemseo.settings.doe import OT_COMPOSITE_Settings




More details about the algorithm and its settings on http://openturns.github.io/openturns/latest/user_manual/_generated/openturns.Composite.html.

























































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**centers** : *collections.abc.Sequence[float] | float, optional*

The center of DOE in the unit hypercube.

This option is available for the axial, composite and factorial DOE
algorithm. If scalar, this value is applied to each direction of the
hypercube; the values must be in :math:`]0,1[`.



By default it is set to 0.5.


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**levels** : *float | collections.abc.Sequence[float], optional*

The levels.

In the case of axial, composite and factorial DOEs, the positions of the levels
relative to the center; the levels will be equispaced and symmetrical relative
to the center; e.g. ``[0.2, 0.8]`` in dimension 1 will generate the samples
``[0.15, 0.6, 0.75, 0.8, 0.95, 1]`` for an axial DOE; the values must be in
:math:`]0,1]`.

In the case of a full-factorial DOE, the number of levels per input direction;
if scalar, this value is applied to each input direction.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**n_samples** : *<class 'int'>, optional*

The number of samples.

If 0, set from the options.


By default it is set to 0.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :class:`~.BaseDOELibrary.seed`.



By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _OT_FACTORIAL_options:

OT_FACTORIAL
------------



Module: :class:`gemseo.algos.doe.openturns.openturns`


Factorial design



.. code-block:: python
   :caption: Pydantic model of the settings for OT_FACTORIAL

   from gemseo.settings.doe import OT_FACTORIAL_Settings




More details about the algorithm and its settings on http://openturns.github.io/openturns/latest/user_manual/_generated/openturns.Factorial.html.

























































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**centers** : *collections.abc.Sequence[float] | float, optional*

The center of DOE in the unit hypercube.

This option is available for the axial, composite and factorial DOE
algorithm. If scalar, this value is applied to each direction of the
hypercube; the values must be in :math:`]0,1[`.



By default it is set to 0.5.


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**levels** : *float | collections.abc.Sequence[float], optional*

The levels.

In the case of axial, composite and factorial DOEs, the positions of the levels
relative to the center; the levels will be equispaced and symmetrical relative
to the center; e.g. ``[0.2, 0.8]`` in dimension 1 will generate the samples
``[0.15, 0.6, 0.75, 0.8, 0.95, 1]`` for an axial DOE; the values must be in
:math:`]0,1]`.

In the case of a full-factorial DOE, the number of levels per input direction;
if scalar, this value is applied to each input direction.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**n_samples** : *<class 'int'>, optional*

The number of samples.

If 0, set from the options.


By default it is set to 0.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :class:`~.BaseDOELibrary.seed`.



By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _OT_FAURE_options:

OT_FAURE
--------



Module: :class:`gemseo.algos.doe.openturns.openturns`


Faure sequence



.. code-block:: python
   :caption: Pydantic model of the settings for OT_FAURE

   from gemseo.settings.doe import OT_FAURE_Settings




More details about the algorithm and its settings on http://openturns.github.io/openturns/latest/user_manual/_generated/openturns.FaureSequence.html.











































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :class:`~.BaseDOELibrary.seed`.



By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _OT_FULLFACT_options:

OT_FULLFACT
-----------



Module: :class:`gemseo.algos.doe.openturns.openturns`


Full factorial design



.. code-block:: python
   :caption: Pydantic model of the settings for OT_FULLFACT

   from gemseo.settings.doe import OT_FULLFACT_Settings




More details about the algorithm and its settings on http://openturns.github.io/openturns/latest/user_manual/_generated/openturns.Box.html.



















































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**levels** : *typing.Union[typing.Annotated[int, Gt(gt=0)], collections.abc.Sequence[typing.Annotated[int, Gt(gt=0)]]], optional*

The number of levels per input direction.

If scalar, this value is applied to each input direction.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**n_samples** : *<class 'int'>, optional*

The number of samples.

If 0, set from the options.


By default it is set to 0.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :class:`~.BaseDOELibrary.seed`.



By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _OT_HALTON_options:

OT_HALTON
---------



Module: :class:`gemseo.algos.doe.openturns.openturns`


Halton sequence



.. code-block:: python
   :caption: Pydantic model of the settings for OT_HALTON

   from gemseo.settings.doe import OT_HALTON_Settings




More details about the algorithm and its settings on http://openturns.github.io/openturns/latest/user_manual/_generated/openturns.HaltonSequence.html.











































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :class:`~.BaseDOELibrary.seed`.



By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _OT_HASELGROVE_options:

OT_HASELGROVE
-------------



Module: :class:`gemseo.algos.doe.openturns.openturns`


Haselgrove sequence



.. code-block:: python
   :caption: Pydantic model of the settings for OT_HASELGROVE

   from gemseo.settings.doe import OT_HASELGROVE_Settings




More details about the algorithm and its settings on http://openturns.github.io/openturns/latest/user_manual/_generated/openturns.HaselgroveSequence.html.











































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :class:`~.BaseDOELibrary.seed`.



By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _OT_LHS_options:

OT_LHS
------



Module: :class:`gemseo.algos.doe.openturns.openturns`


Latin Hypercube Sampling



.. code-block:: python
   :caption: Pydantic model of the settings for OT_LHS

   from gemseo.settings.doe import OT_LHS_Settings




More details about the algorithm and its settings on http://openturns.github.io/openturns/latest/user_manual/_generated/openturns.LHSExperiment.html.











































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :class:`~.BaseDOELibrary.seed`.



By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _OT_LHSC_options:

OT_LHSC
-------



Module: :class:`gemseo.algos.doe.openturns.openturns`


Centered Latin Hypercube Sampling



.. code-block:: python
   :caption: Pydantic model of the settings for OT_LHSC

   from gemseo.settings.doe import OT_LHSC_Settings




More details about the algorithm and its settings on http://openturns.github.io/openturns/latest/user_manual/_generated/openturns.LHSExperiment.html.











































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :class:`~.BaseDOELibrary.seed`.



By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _OT_MONTE_CARLO_options:

OT_MONTE_CARLO
--------------



Module: :class:`gemseo.algos.doe.openturns.openturns`


Monte Carlo sequence



.. code-block:: python
   :caption: Pydantic model of the settings for OT_MONTE_CARLO

   from gemseo.settings.doe import OT_MONTE_CARLO_Settings




More details about the algorithm and its settings on http://openturns.github.io/openturns/latest/user_manual/_generated/openturns.Uniform.html.











































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :class:`~.BaseDOELibrary.seed`.



By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _OT_OPT_LHS_options:

OT_OPT_LHS
----------



Module: :class:`gemseo.algos.doe.openturns.openturns`


Optimal Latin Hypercube Sampling



.. code-block:: python
   :caption: Pydantic model of the settings for OT_OPT_LHS

   from gemseo.settings.doe import OT_OPT_LHS_Settings




More details about the algorithm and its settings on http://openturns.github.io/openturns/latest/user_manual/_generated/openturns.SimulatedAnnealingLHS.html.



































































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**annealing** : *<class 'bool'>, optional*

Whether to use simulated annealing to optimize the LHS.

If ``False``, the crude Monte Carlo method is used.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**criterion** : *<enum 'SpaceFillingCriterion'>, optional*

The space-filling criterion.


By default it is set to C2.


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**n_replicates** : *<class 'int'>, optional*

The number of Monte Carlo replicates to optimize LHS.


By default it is set to 1000.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :class:`~.BaseDOELibrary.seed`.



By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**temperature** : *<enum 'TemperatureProfile'>, optional*

The temperature profile for simulated annealing.

Either "Geometric" or "Linear".


By default it is set to Geometric.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _OT_RANDOM_options:

OT_RANDOM
---------



Module: :class:`gemseo.algos.doe.openturns.openturns`


Random sampling



.. code-block:: python
   :caption: Pydantic model of the settings for OT_RANDOM

   from gemseo.settings.doe import OT_RANDOM_Settings




More details about the algorithm and its settings on http://openturns.github.io/openturns/latest/user_manual/_generated/openturns.Uniform.html.











































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :class:`~.BaseDOELibrary.seed`.



By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _OT_REVERSE_HALTON_options:

OT_REVERSE_HALTON
-----------------



Module: :class:`gemseo.algos.doe.openturns.openturns`


Reverse Halton



.. code-block:: python
   :caption: Pydantic model of the settings for OT_REVERSE_HALTON

   from gemseo.settings.doe import OT_REVERSE_HALTON_Settings




More details about the algorithm and its settings on http://openturns.github.io/openturns/latest/user_manual/_generated/openturns.ReverseHaltonSequence.html.











































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :class:`~.BaseDOELibrary.seed`.



By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _OT_SOBOL_options:

OT_SOBOL
--------



Module: :class:`gemseo.algos.doe.openturns.openturns`


Sobol sequence



.. code-block:: python
   :caption: Pydantic model of the settings for OT_SOBOL

   from gemseo.settings.doe import OT_SOBOL_Settings




More details about the algorithm and its settings on http://openturns.github.io/openturns/latest/user_manual/_generated/openturns.SobolSequence.html.











































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :class:`~.BaseDOELibrary.seed`.



By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _OT_SOBOL_INDICES_options:

OT_SOBOL_INDICES
----------------



Module: :class:`gemseo.algos.doe.openturns.openturns`


DOE for Sobol indices



.. code-block:: python
   :caption: Pydantic model of the settings for OT_SOBOL_INDICES

   from gemseo.settings.doe import OT_SOBOL_INDICES_Settings




More details about the algorithm and its settings on http://openturns.github.io/openturns/latest/user_manual/_generated/openturns.SobolIndicesAlgorithm.html.

















































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**eval_second_order** : *<class 'bool'>, optional*

Whether to build a DOE to evaluate also the second-order indices.

If ``False``, the DOE is designed for first and total-order indices only.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :class:`~.BaseDOELibrary.seed`.



By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _PYDOE_BBDESIGN_options:

PYDOE_BBDESIGN
--------------



Module: :class:`gemseo.algos.doe.pydoe.pydoe`


Box-Behnken design



.. code-block:: python
   :caption: Pydantic model of the settings for PYDOE_BBDESIGN

   from gemseo.settings.doe import PYDOE_BBDESIGN_Settings




More details about the algorithm and its settings on https://pythonhosted.org/pyDOE/rsm.html#box-behnken.







































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**center** : *typing.Optional[typing.Annotated[int, Gt(gt=0)]], optional*

The number of center points for the Box-Behnken design.

If ``None``, use a pre-determined number of points.


By default it is set to None.


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _PYDOE_CCDESIGN_options:

PYDOE_CCDESIGN
--------------



Module: :class:`gemseo.algos.doe.pydoe.pydoe`


Central Composite



.. code-block:: python
   :caption: Pydantic model of the settings for PYDOE_CCDESIGN

   from gemseo.settings.doe import PYDOE_CCDESIGN_Settings




More details about the algorithm and its settings on https://pythonhosted.org/pyDOE/rsm.html#central-composite.



















































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**alpha** : *<enum 'Alpha'>, optional*

A parameter to describe how the variance is distributed.

Either "orthogonal" or "rotatable".


By default it is set to orthogonal.


.. raw:: html

    </li>

    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**center** : *tuple[int, int], optional*

The 2-tuple of center points for the central composite design.


By default it is set to (4, 4).


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**face** : *<enum 'Face'>, optional*

The relation between the start and corner (factorial) points.


By default it is set to circumscribed.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _PYDOE_FF2N_options:

PYDOE_FF2N
----------



Module: :class:`gemseo.algos.doe.pydoe.pydoe`


2-Level Full-Factorial



.. code-block:: python
   :caption: Pydantic model of the settings for PYDOE_FF2N

   from gemseo.settings.doe import PYDOE_FF2N_Settings




More details about the algorithm and its settings on https://pythonhosted.org/pyDOE/factorial.html#level-full-factorial.

































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _PYDOE_FULLFACT_options:

PYDOE_FULLFACT
--------------



Module: :class:`gemseo.algos.doe.pydoe.pydoe`


Full-Factorial



.. code-block:: python
   :caption: Pydantic model of the settings for PYDOE_FULLFACT

   from gemseo.settings.doe import PYDOE_FULLFACT_Settings




More details about the algorithm and its settings on https://pythonhosted.org/pyDOE/factorial.html#general-full-factorial.













































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**levels** : *typing.Union[collections.abc.Sequence[typing.Annotated[int, Gt(gt=0)]], typing.Annotated[int, Gt(gt=0)]], optional*

The levels.

One must either specify ``n_samples`` or ``levels``.  The levels are
inferred from the number of samples if the former is specified.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**n_samples** : *<class 'int'>, optional*

The number of samples.

If 0, set from the settings.


By default it is set to 0.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _PYDOE_LHS_options:

PYDOE_LHS
---------



Module: :class:`gemseo.algos.doe.pydoe.pydoe`


Latin Hypercube Sampling



.. code-block:: python
   :caption: Pydantic model of the settings for PYDOE_LHS

   from gemseo.settings.doe import PYDOE_LHS_Settings




More details about the algorithm and its settings on https://pythonhosted.org/pyDOE/randomized.html#latin-hypercube.























































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**criterion** : *gemseo.algos.doe.pydoe.settings.pydoe_lhs.Criterion | None, optional*

The criterion to use when sampling the points.

If ``None``, randomize the points within the intervals.


By default it is set to None.


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**iterations** : *<class 'int'>, optional*

The number of iterations in the ``correlation``/``maximin`` algorithms.


By default it is set to 5.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**random_state** : *typing.Optional[typing.Annotated[int, Gt(gt=0)]], optional*

The seed used for reproducibility reasons.

If ``None``, use :class:`~.BaseDOELibrary.seed`.


By default it is set to None.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _PYDOE_PBDESIGN_options:

PYDOE_PBDESIGN
--------------



Module: :class:`gemseo.algos.doe.pydoe.pydoe`


Plackett-Burman design



.. code-block:: python
   :caption: Pydantic model of the settings for PYDOE_PBDESIGN

   from gemseo.settings.doe import PYDOE_PBDESIGN_Settings




More details about the algorithm and its settings on https://pythonhosted.org/pyDOE/factorial.html#plackett-burman.

































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _PoissonDisk_options:

PoissonDisk
-----------



Module: :class:`gemseo.algos.doe.scipy.scipy_doe`


Poisson disk sampling



.. code-block:: python
   :caption: Pydantic model of the settings for PoissonDisk

   from gemseo.settings.doe import PoissonDisk_Settings






































































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**hypersphere** : *<enum 'Hypersphere'>, optional*

The sampling strategy to generate potential candidates.

The candidates will be added in the final sample.


By default it is set to volume.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**ncandidates** : *<class 'int'>, optional*

The number of candidates to sample per iteration.


By default it is set to 30.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**optimization** : *gemseo.algos.doe.scipy.settings.base_scipy_doe_settings.Optimizer | None, optional*

The name of an optimization scheme to improve the DOE's quality.

If ``None``, use the DOE as is. New in SciPy 1.10.0.


By default it is set to None.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**radius** : *<class 'float'>, optional*

The minimal distance to keep between points when sampling new candidates.


By default it is set to 0.05.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :attr:`.seed`.


By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _Sobol_options:

Sobol
-----



Module: :class:`gemseo.algos.doe.scipy.scipy_doe`


Engine for generating (scrambled) Sobol' sequences



.. code-block:: python
   :caption: Pydantic model of the settings for Sobol

   from gemseo.settings.doe import Sobol_Settings
































































































































































.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Required settings</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**n_samples** : *<class 'int'>*

The number of samples.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. raw:: html

    <dl class="field-list simple">
    <dt class="field-odd">Optional settings</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**bits** : *<class 'int'>, optional*

The number of bits of the generator.


By default it is set to 30.


.. raw:: html

    </li>

    <li>

**callbacks** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int, tuple[dict[str, float | numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]], dict[str, numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.floating[typing.Any]]]]]], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called after evaluating the function of interest.

A callback must be called as ``callback(sample_index, (output, Jacobian))``.


By default it is set to ().


.. raw:: html

    </li>

    <li>

**enable_progress_bar** : *bool | None, optional*

Whether to enable the progress bar in the optimization log.

If ``None``, use the global value of ``enable_progress_bar`` (see the
``configure`` function to change it globally).


By default it is set to None.


.. raw:: html

    </li>

    <li>

**eq_tolerance** : *<class 'float'>, optional*

The tolerance on the equality constraints.


By default it is set to 0.01.


.. raw:: html

    </li>

    <li>

**eval_func** : *<class 'bool'>, optional*

Whether to sample the function computing the output values.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**eval_jac** : *<class 'bool'>, optional*

Whether to sample the function computing the Jacobian data.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**ineq_tolerance** : *<class 'float'>, optional*

The tolerance on the inequality constraints.


By default it is set to 0.0001.


.. raw:: html

    </li>

    <li>

**log_problem** : *<class 'bool'>, optional*

Whether to log the definition and result of the problem.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**max_time** : *<class 'float'>, optional*

The maximum runtime in seconds, disabled if 0.


By default it is set to 0.0.


.. raw:: html

    </li>

    <li>

**n_processes** : *<class 'int'>, optional*

The maximum number of processes to parallelize the execution.


By default it is set to 1.


.. raw:: html

    </li>

    <li>

**normalize_design_space** : *<class 'bool'>, optional*

Whether to normalize the design space variables between 0 and 1.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**optimization** : *gemseo.algos.doe.scipy.settings.base_scipy_doe_settings.Optimizer | None, optional*

The name of an optimization scheme to improve the DOE's quality.

If ``None``, use the DOE as is. New in SciPy 1.10.0.


By default it is set to None.


.. raw:: html

    </li>

    <li>

**preprocessors** : *collections.abc.Sequence[typing.Annotated[collections.abc.Callable[[int], typing.Any], WithJsonSchema(json_schema={}, mode=None)]], optional*

The functions called
before evaluating the function of interest.

A preprocessor must be called as ``preprocessor(sample_index)``.

This option is not compatible with the vectorization of functions evaluations.



By default it is set to ().


.. raw:: html

    </li>

    <li>

**progress_bar_data_name** : *<enum 'ProgressBarDataName'>, optional*

The name of a :class:`.BaseProgressBarData` class
to define the data of an evaluation problem to be displayed in the progress bar.


By default it is set to ProgressBarData.


.. raw:: html

    </li>

    <li>

**reset_iteration_counters** : *<class 'bool'>, optional*

Whether to reset the iteration counters before each execution.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**round_ints** : *<class 'bool'>, optional*

Whether to round the integer variables.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**scramble** : *<class 'bool'>, optional*

Whether to use scrambling (Owen type).

Only available with SciPy >= 1.10.0.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**seed** : *int | None, optional*

The seed used for reproducibility reasons.

If ``None``, use :attr:`.seed`.


By default it is set to None.


.. raw:: html

    </li>

    <li>

**store_jacobian** : *<class 'bool'>, optional*

Whether to store the Jacobian matrices in the database.

    This argument is ignored when the ``use_database`` option is ``False``.
    If a gradient-based algorithm is used,
    this option cannot be set along with kkt options.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_database** : *<class 'bool'>, optional*

Whether to wrap the functions in the database.


By default it is set to True.


.. raw:: html

    </li>

    <li>

**use_one_line_progress_bar** : *<class 'bool'>, optional*

Whether to log the progress bar on a single line.


By default it is set to False.


.. raw:: html

    </li>

    <li>

**vectorize** : *<class 'bool'>, optional*

Whether to vectorize the functions evaluations.


By default it is set to False.


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    </li>

    <li>

**wait_time_between_samples** : *<class 'float'>, optional*

The time to wait between each sample evaluation, in seconds.


By default it is set to 0.0.


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    </li>

    </ul>
    </dd>
    </dl>