.. only:: html

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

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

    .. _sphx_glr_auto_probabilistic_modeling_stochastic_processes_plot_aggregated_process.py:


Aggregate processes
===================

In this example we are going to concatenate several processes that share the same mesh.


.. 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 processes to aggregate


.. code-block:: default

    myMesher = ot.IntervalMesher(ot.Indices([100,10]))
    lowerbound = [0.0, 0.0]
    upperBound = [2.0, 4.0]
    myInterval = ot.Interval(lowerbound, upperBound)
    myMesh = myMesher.build(myInterval)
    myProcess1 = ot.WhiteNoise(ot.Normal(), myMesh)
    myProcess2 = ot.WhiteNoise(ot.Triangular(), myMesh)









Draw values of a realization of the 2nd process


.. code-block:: default

    marginal = ot.HistogramFactory().build(myProcess1.getRealization().getValues())
    graph = marginal.drawPDF()
    view = viewer.View(graph)




.. image:: /auto_probabilistic_modeling/stochastic_processes/images/sphx_glr_plot_aggregated_process_001.png
    :alt: X0 PDF
    :class: sphx-glr-single-img





Create an aggregated process


.. code-block:: default

    myAggregatedProcess = ot.AggregatedProcess([myProcess1, myProcess2])








Draw values of the realization on the 2nd marginal


.. code-block:: default

    marginal = ot.HistogramFactory().build(myAggregatedProcess.getRealization().getValues().getMarginal(0))
    graph = marginal.drawPDF()
    viewer.View(graph)
    plt.show()



.. image:: /auto_probabilistic_modeling/stochastic_processes/images/sphx_glr_plot_aggregated_process_002.png
    :alt: X0 PDF
    :class: sphx-glr-single-img






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

   **Total running time of the script:** ( 0 minutes  0.144 seconds)


.. _sphx_glr_download_auto_probabilistic_modeling_stochastic_processes_plot_aggregated_process.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_aggregated_process.py <plot_aggregated_process.py>`



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

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


.. only:: html

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

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