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

.. only:: html

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

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

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

.. _sphx_glr_auto_reliability_sensitivity_design_of_experiments_plot_deterministic_design.py:


Deterministic design of experiments
===================================

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In this example we present the available deterministic design of experiments.

Four types of deterministic design of experiments are available:

- `Axial`
- `Factorial`
- `Composite`
- `Box`

Each type of deterministic design is discretized differently according to a number of levels.

Functionally speaking, a design is a `Sample` that lies within the unit cube :math:`(0,1)^d` and can be scaled and moved to cover the desired box.

.. GENERATED FROM PYTHON SOURCE LINES 20-27

.. code-block:: Python

    import openturns as ot
    import openturns.viewer as viewer
    from matplotlib import pylab as plt

    ot.Log.Show(ot.Log.NONE)









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We will use the following function to plot bi-dimensional samples.

.. GENERATED FROM PYTHON SOURCE LINES 32-40

.. code-block:: Python

    def drawBidimensionalSample(sample, title):
        n = sample.getSize()
        graph = ot.Graph("%s, size=%d" % (title, n), "X1", "X2", True, "")
        cloud = ot.Cloud(sample)
        graph.add(cloud)
        return graph









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Axial design
------------

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.. code-block:: Python

    levels = [1.0, 1.5, 3.0]
    experiment = ot.Axial(2, levels)
    sample = experiment.generate()
    graph = drawBidimensionalSample(sample, "Axial")
    view = viewer.View(graph)




.. image-sg:: /auto_reliability_sensitivity/design_of_experiments/images/sphx_glr_plot_deterministic_design_001.png
   :alt: Axial, size=13
   :srcset: /auto_reliability_sensitivity/design_of_experiments/images/sphx_glr_plot_deterministic_design_001.png
   :class: sphx-glr-single-img





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Scale and to get desired location.

.. GENERATED FROM PYTHON SOURCE LINES 55-60

.. code-block:: Python

    sample *= 2.0
    sample += [5.0, 8.0]
    graph = drawBidimensionalSample(sample, "Axial")
    view = viewer.View(graph)




.. image-sg:: /auto_reliability_sensitivity/design_of_experiments/images/sphx_glr_plot_deterministic_design_002.png
   :alt: Axial, size=13
   :srcset: /auto_reliability_sensitivity/design_of_experiments/images/sphx_glr_plot_deterministic_design_002.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 61-64

Factorial design
----------------


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.. code-block:: Python

    experiment = ot.Factorial(2, levels)
    sample = experiment.generate()
    sample *= 2.0
    sample += [5.0, 8.0]
    graph = drawBidimensionalSample(sample, "Factorial")
    view = viewer.View(graph)




.. image-sg:: /auto_reliability_sensitivity/design_of_experiments/images/sphx_glr_plot_deterministic_design_003.png
   :alt: Factorial, size=13
   :srcset: /auto_reliability_sensitivity/design_of_experiments/images/sphx_glr_plot_deterministic_design_003.png
   :class: sphx-glr-single-img





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Composite design
----------------

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.. code-block:: Python

    experiment = ot.Composite(2, levels)
    sample = experiment.generate()
    sample *= 2.0
    sample += [5.0, 8.0]
    graph = drawBidimensionalSample(sample, "Composite")
    view = viewer.View(graph)




.. image-sg:: /auto_reliability_sensitivity/design_of_experiments/images/sphx_glr_plot_deterministic_design_004.png
   :alt: Composite, size=25
   :srcset: /auto_reliability_sensitivity/design_of_experiments/images/sphx_glr_plot_deterministic_design_004.png
   :class: sphx-glr-single-img





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Grid design
-----------


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.. code-block:: Python

    levels = [3, 4]
    experiment = ot.Box(levels)
    sample = experiment.generate()
    sample *= 2.0
    sample += [5.0, 8.0]
    graph = drawBidimensionalSample(sample, "Box")
    view = viewer.View(graph)
    plt.show()



.. image-sg:: /auto_reliability_sensitivity/design_of_experiments/images/sphx_glr_plot_deterministic_design_005.png
   :alt: Box, size=30
   :srcset: /auto_reliability_sensitivity/design_of_experiments/images/sphx_glr_plot_deterministic_design_005.png
   :class: sphx-glr-single-img






.. _sphx_glr_download_auto_reliability_sensitivity_design_of_experiments_plot_deterministic_design.py:

.. only:: html

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

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

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

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

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