.. only:: html

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

        Click :ref:`here <sphx_glr_download_auto_probabilistic_modeling_copulas_plot_composed_copula.py>`     to download the full example code
    .. rst-class:: sphx-glr-example-title

    .. _sphx_glr_auto_probabilistic_modeling_copulas_plot_composed_copula.py:


Assemble copulas
================

In this example we are going to merge a collection of independent copulas into one.



.. code-block:: default

    from __future__ import print_function
    import openturns as ot
    import openturns.viewer as viewer
    from matplotlib import pylab as plt
    ot.Log.Show(ot.Log.NONE)








create a collection of copulas


.. code-block:: default

    R = ot.CorrelationMatrix(3)
    R[0, 1] = 0.5
    R[0, 2] = 0.25
    collection = [ot.FrankCopula(3.0), ot.NormalCopula(R), ot.ClaytonCopula(2.0)]








merge the copulas


.. code-block:: default

    copula = ot.ComposedCopula(collection)
    print(copula)




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

 Out:

 .. code-block:: none

    ComposedCopula(FrankCopula(theta = 3), NormalCopula(R = [[ 1    0.5  0.25 ]
     [ 0.5  1    0    ]
     [ 0.25 0    1    ]]), ClaytonCopula(theta = 2))





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

   **Total running time of the script:** ( 0 minutes  0.001 seconds)


.. _sphx_glr_download_auto_probabilistic_modeling_copulas_plot_composed_copula.py:


.. only :: html

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



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

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



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

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


.. only:: html

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

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