.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/plot_example1.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_auto_examples_plot_example1.py>`
        to download the full example code.

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

.. _sphx_glr_auto_examples_plot_example1.py:


Example on 2-d data
===================

.. GENERATED FROM PYTHON SOURCE LINES 7-11

.. code-block:: Python

    import openturns as ot
    import otsliced
    import matplotlib.pyplot as plt








.. GENERATED FROM PYTHON SOURCE LINES 12-13

Create 2-d data X and 1-d feature Y

.. GENERATED FROM PYTHON SOURCE LINES 13-20

.. code-block:: Python

    N = 100
    X = ot.Normal([0.0] * 2, [0.1] * 2).getSample(N)
    X += [[-i / (N - 1), 2 * i / (N - 1)] for i in range(N)]
    X = X - X.computeMean()
    f = ot.SymbolicFunction(["x1", "x2"], ["4*(x1+2*x2)+2"])
    Y = f(X) + ot.Normal(0.0, 0.2).getSample(N)








.. GENERATED FROM PYTHON SOURCE LINES 21-22

Plot data

.. GENERATED FROM PYTHON SOURCE LINES 22-28

.. code-block:: Python

    plt.scatter(X.getMarginal(0), X.getMarginal(1), c=Y)
    plt.xlabel('x1')
    plt.ylabel('x2')
    plt.axis('square')
    plt.title("2D colored Dataset")




.. image-sg:: /auto_examples/images/sphx_glr_plot_example1_001.png
   :alt: 2D colored Dataset
   :srcset: /auto_examples/images/sphx_glr_plot_example1_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none


    Text(0.5, 1.0, '2D colored Dataset')



.. GENERATED FROM PYTHON SOURCE LINES 29-30

Run the SIR algorithm

.. GENERATED FROM PYTHON SOURCE LINES 30-34

.. code-block:: Python

    algo = otsliced.SlicedInverseRegression(X, Y)
    algo.run()
    transformation = algo.getResult().getTransformation()








.. GENERATED FROM PYTHON SOURCE LINES 35-36

Show SIR direction

.. GENERATED FROM PYTHON SOURCE LINES 36-44

.. code-block:: Python

    plt.scatter(X.getMarginal(0), X.getMarginal(1), c=Y)
    plt.xlabel('x1')
    plt.ylabel('x2')
    plt.axis('square')
    plt.title("First direction of SIR")
    dir_sir = algo.getResult().getDirections()
    plt.plot([-dir_sir[0, 0] * 30, dir_sir[0, 0] * 30], [-dir_sir[1, 0] * 30, dir_sir[1, 0] * 30], c='red')




.. image-sg:: /auto_examples/images/sphx_glr_plot_example1_002.png
   :alt: First direction of SIR
   :srcset: /auto_examples/images/sphx_glr_plot_example1_002.png
   :class: sphx-glr-single-img


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

 .. code-block:: none


    [<matplotlib.lines.Line2D object at 0x7f1d0c6c73b0>]



.. GENERATED FROM PYTHON SOURCE LINES 45-46

.. code-block:: Python

    plt.show()








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

   **Total running time of the script:** (0 minutes 0.126 seconds)


.. _sphx_glr_download_auto_examples_plot_example1.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: plot_example1.ipynb <plot_example1.ipynb>`

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

      :download:`Download Python source code: plot_example1.py <plot_example1.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_example1.zip <plot_example1.zip>`