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

.. only:: html

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

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

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

.. _sphx_glr_auto_data_analysis_sample_analysis_plot_visualize_empirical_cdf.py:


Draw the empirical CDF
======================

.. GENERATED FROM PYTHON SOURCE LINES 7-8

In this example we are going to draw the empirical CDF of an unidimensional sample.

.. GENERATED FROM PYTHON SOURCE LINES 10-16

.. code-block:: Python

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

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








.. GENERATED FROM PYTHON SOURCE LINES 17-18

Then create a sample from a gaussian distribution.

.. GENERATED FROM PYTHON SOURCE LINES 20-24

.. code-block:: Python

    size = 100
    normal = ot.Normal(1)
    sample = normal.getSample(size)








.. GENERATED FROM PYTHON SOURCE LINES 25-27

We draw the empirical CDF based on the `UserDefined` distribution.
By default, the `drawCDF` method requires no input argument.

.. GENERATED FROM PYTHON SOURCE LINES 29-33

.. code-block:: Python

    distribution = ot.UserDefined(sample)
    graph = distribution.drawCDF()
    view = viewer.View(graph)




.. image-sg:: /auto_data_analysis/sample_analysis/images/sphx_glr_plot_visualize_empirical_cdf_001.png
   :alt: X0 CDF
   :srcset: /auto_data_analysis/sample_analysis/images/sphx_glr_plot_visualize_empirical_cdf_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 34-36

If required, we can specify the interval that we want to draw.
In the following example, these bounds are computed from the minimum and the maximum of the sample.

.. GENERATED FROM PYTHON SOURCE LINES 38-43

.. code-block:: Python

    xmin = sample.getMin()[0] - 2.0
    xmax = sample.getMax()[0] + 2.0
    graph = ot.UserDefined(sample).drawCDF(xmin, xmax)
    view = viewer.View(graph)
    plt.show()



.. image-sg:: /auto_data_analysis/sample_analysis/images/sphx_glr_plot_visualize_empirical_cdf_002.png
   :alt: X0 CDF
   :srcset: /auto_data_analysis/sample_analysis/images/sphx_glr_plot_visualize_empirical_cdf_002.png
   :class: sphx-glr-single-img






.. _sphx_glr_download_auto_data_analysis_sample_analysis_plot_visualize_empirical_cdf.py:

.. only:: html

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

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

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

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

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