.. only:: html

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

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

    .. _sphx_glr_auto_probabilistic_modeling_distributions_plot_random_vector_manipulation.py:


Random vector manipulation
==========================

The RandomVector object represents the concept of random variable.

In this example we are going to exhibit some of its main methods.


.. code-block:: default

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








Create a random vector


.. code-block:: default

    dist3d = ot.Normal(3)
    X = ot.RandomVector(dist3d)








Get the dimension


.. code-block:: default

    X.getDimension()





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

 Out:

 .. code-block:: none


    3



Get the mean


.. code-block:: default

    X.getMean()






.. raw:: html

    <p>[0,0,0]</p>
    <br />
    <br />

Get the covariance


.. code-block:: default

    X.getCovariance()






.. raw:: html

    <p>[[ 1 0 0 ]<br>
     [ 0 1 0 ]<br>
     [ 0 0 1 ]]</p>
    <br />
    <br />

Draw a sample


.. code-block:: default

    X.getSample(5)






.. raw:: html

    <TABLE><TR><TD></TD><TH>X0</TH><TH>X1</TH><TH>X2</TH></TR>
    <TR><TH>0</TH><TD>0.2394903</TD><TD>1.008846</TD><TD>-0.3819995</TD></TR>
    <TR><TH>1</TH><TD>0.1030435</TD><TD>-0.4948338</TD><TD>-1.717802</TD></TR>
    <TR><TH>2</TH><TD>0.1429553</TD><TD>-0.6950194</TD><TD>-0.1156185</TD></TR>
    <TR><TH>3</TH><TD>-1.687796</TD><TD>-0.114902</TD><TD>-1.712393</TD></TR>
    <TR><TH>4</TH><TD>-1.07275</TD><TD>-0.4745819</TD><TD>1.040955</TD></TR>
    </TABLE>
    <br />
    <br />

Extract a single component


.. code-block:: default

    X1 = X.getMarginal(1)
    X1.getSample(5)






.. raw:: html

    <TABLE><TR><TD></TD><TH>X1</TH></TR>
    <TR><TH>0</TH><TD>0.672975</TD></TR>
    <TR><TH>1</TH><TD>1.292529</TD></TR>
    <TR><TH>2</TH><TD>1.163747</TD></TR>
    <TR><TH>3</TH><TD>0.2549519</TD></TR>
    <TR><TH>4</TH><TD>-1.431553</TD></TR>
    </TABLE>
    <br />
    <br />

Extract several components


.. code-block:: default

    X02 = X.getMarginal([0, 2])
    X02.getSample(5)





.. raw:: html

    <TABLE><TR><TD></TD><TH>X0</TH><TH>X2</TH></TR>
    <TR><TH>0</TH><TD>0.1996158</TD><TD>0.07590005</TD></TR>
    <TR><TH>1</TH><TD>1.021166</TD><TD>-1.149774</TD></TR>
    <TR><TH>2</TH><TD>0.6065979</TD><TD>0.4826356</TD></TR>
    <TR><TH>3</TH><TD>-0.6285791</TD><TD>-0.05952591</TD></TR>
    <TR><TH>4</TH><TD>1.304801</TD><TD>-0.8920438</TD></TR>
    </TABLE>
    <br />
    <br />


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

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


.. _sphx_glr_download_auto_probabilistic_modeling_distributions_plot_random_vector_manipulation.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_random_vector_manipulation.py <plot_random_vector_manipulation.py>`



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

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


.. only:: html

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

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