.. only:: html

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

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

    .. _sphx_glr_auto_data_analysis_manage_data_and_samples_plot_sort_sample.py:


Sort a sample
=============

In this example we present useful methods of the `Sample` object such as marginals extraction and various sorting strategies.


.. code-block:: default

    from __future__ import print_function
    import openturns as ot
    ot.Log.Show(ot.Log.NONE)
    ot.RandomGenerator.SetSeed(0)









We start by defining the distribution of a regular non-biased dice.


.. code-block:: default

    dice_distribution = ot.UserDefined([[i] for i in range(1,7)])








We consider now an experiment with two independent dices and build the corresponding random vector :


.. code-block:: default

    two_dices_distribution = ot.ComposedDistribution([dice_distribution]*2)








We now build a sample of size :math:`n=5` from this distribution :


.. code-block:: default

    n = 5
    sample = two_dices_distribution.getSample(n)
    print( sample ) 





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

 Out:

 .. code-block:: none

        [ X0 X1 ]
    0 : [ 1  3  ]
    1 : [ 3  2  ]
    2 : [ 4  3  ]
    3 : [ 4  4  ]
    4 : [ 5  5  ]




Useful methods
--------------

We have access to the marginals by providing a list of the wanted indices :


.. code-block:: default


    # the first marginal
    sample_dice1 = sample.getMarginal([0])

    # the second marginal
    sample_dice2 = sample.getMarginal([1])








Suppose we are interested in the sum of the two dices. This can be done by summing the two samples `dice1` and `dice2`.
Provided the dimensions are the same we can add samples with the `+` operator and produce a new sample :


.. code-block:: default

    experiment = sample_dice1 + sample_dice2








Note that the `+=` operator is defined as well.

We can concatenate two samples having the same size with the `stack` method :


.. code-block:: default

    sample_dice1.stack(sample_dice2)
    print(sample_dice1)





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

 Out:

 .. code-block:: none

        [ X0 X1 ]
    0 : [ 1  3  ]
    1 : [ 3  2  ]
    2 : [ 4  3  ]
    3 : [ 4  4  ]
    4 : [ 5  5  ]




We can split a sample in two by giving an index (here 2).


.. code-block:: default

    remaining = sample_dice1.split(2)
    print( sample_dice1 )
    print( remaining )






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

 Out:

 .. code-block:: none

        [ X0 X1 ]
    0 : [ 1  3  ]
    1 : [ 3  2  ]
        [ X0 X1 ]
    0 : [ 4  3  ]
    1 : [ 4  4  ]
    2 : [ 5  5  ]




Sorting samples
---------------

We can extract any marginal and sort it by ascending order by specifying the index :


.. code-block:: default

    sorted_marginal = sample.sort(1)
    print( sorted_marginal )





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

 Out:

 .. code-block:: none

    0 : [ 2 ]
    1 : [ 3 ]
    2 : [ 3 ]
    3 : [ 4 ]
    4 : [ 5 ]




We can sort the sample in place, that is whithout creating a new sample, as well with sortInPlace. When the dimension is greater than one the sort is made according to the first marginal.


.. code-block:: default

    sample.sortInPlace()
    print( sample )





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

 Out:

 .. code-block:: none

        [ X0 X1 ]
    0 : [ 1  3  ]
    1 : [ 3  2  ]
    2 : [ 4  3  ]
    3 : [ 4  4  ]
    4 : [ 5  5  ]




We can sort the rows according to the second marginal with the `sortAccordingToAComponent` : 


.. code-block:: default

    another_sample = sample.sortAccordingToAComponent(1)
    print( another_sample )





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

 Out:

 .. code-block:: none

        [ X0 X1 ]
    0 : [ 3  2  ]
    1 : [ 1  3  ]
    2 : [ 4  3  ]
    3 : [ 4  4  ]
    4 : [ 5  5  ]




There is also a `sortAccordingToAComponentInPlace` method that does the same without creating a new sample.

We can sort and remove the duplicates at the same time


.. code-block:: default

    print( sample_dice2 )
    print( sample_dice2.sortUnique() )





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

 Out:

 .. code-block:: none

        [ X1 ]
    0 : [ 3  ]
    1 : [ 2  ]
    2 : [ 3  ]
    3 : [ 4  ]
    4 : [ 5  ]
        [ X1 ]
    0 : [ 2  ]
    1 : [ 3  ]
    2 : [ 4  ]
    3 : [ 5  ]




We note that the sample is smaller as expected. Sorting in place is also possible :


.. code-block:: default

    sample_dice2.sortUniqueInPlace()
    print( sample_dice2 )





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

 Out:

 .. code-block:: none

        [ X1 ]
    0 : [ 2  ]
    1 : [ 3  ]
    2 : [ 4  ]
    3 : [ 5  ]




Let's try with the sample in dimension 2 :


.. code-block:: default

    sampleUnique = sample.sortUnique()
    print( sampleUnique )





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

 Out:

 .. code-block:: none

        [ X0 X1 ]
    0 : [ 1  3  ]
    1 : [ 3  2  ]
    2 : [ 4  3  ]
    3 : [ 4  4  ]
    4 : [ 5  5  ]




Nothing happens here because pairs are already unique !


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

   **Total running time of the script:** ( 0 minutes  0.005 seconds)


.. _sphx_glr_download_auto_data_analysis_manage_data_and_samples_plot_sort_sample.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_sort_sample.py <plot_sort_sample.py>`



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

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


.. only:: html

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

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