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

    Click :ref:`here <sphx_glr_download_sphinx_gallery_auto_transparency_xmpl_transparency_pd.py>` to download the full example code or run this example in your browser via Binder
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_sphinx_gallery_auto_transparency_xmpl_transparency_pd.py:


==================================
Using Partial Dependence Explainer
==================================

This example illustrates how to use the Partial Dependence (PD) explainer and
its plotting function. This example only shows how to get the PD array straight
from the data. The calculation of PD required to compute the Individual
Conditional Expectation (ICE) as part of the process. By using the
:func:`fatf.transparency.models.feature_influence.partial_dependence` function
the ICE array is computed, however it is never returned back to the user. If
you want to inspect both ICE and PD then please have a look at the
:ref:`sphx_glr_sphinx_gallery_auto_transparency_xmpl_transparency_pd.py`
example and the two following functions:

* :func:`fatf.transparency.models.feature_influence.individual_conditional_expectation`,
* :func:`fatf.transparency.models.feature_influence.partial_dependence_ice`.


.. image:: /sphinx_gallery_auto/transparency/images/sphx_glr_xmpl_transparency_pd_001.png
    :class: sphx-glr-single-img


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

 Out:

 .. code-block:: none

    Explaining feature (index: 1): sepal width (cm).
    Explaining class (index: 2): virginica.




|


.. code-block:: default

    # Author: Kacper Sokol <k.sokol@bristol.ac.uk>
    # License: new BSD

    import fatf.utils.data.datasets as fatf_datasets
    import fatf.utils.models as fatf_models

    import fatf.transparency.models.feature_influence as fatf_fi

    import fatf.vis.feature_influence as fatf_vis_fi

    print(__doc__)

    # Load data
    iris_data_dict = fatf_datasets.load_iris()
    iris_X = iris_data_dict['data']
    iris_y = iris_data_dict['target'].astype(int)
    iris_feature_names = iris_data_dict['feature_names']
    iris_class_names = iris_data_dict['target_names']

    # Train a model
    clf = fatf_models.KNN()
    clf.fit(iris_X, iris_y)

    # Select a feature to be explained
    selected_feature_index = 1
    selected_feature_name = iris_feature_names[selected_feature_index]
    print('Explaining feature (index: {}): {}.'.format(selected_feature_index,
                                                       selected_feature_name))

    # Select class for which the explanation will be produced
    explanation_class = 2
    explanation_class_name = iris_class_names[explanation_class]
    print('Explaining class (index: {}): {}.'.format(explanation_class,
                                                     explanation_class_name))

    # Define the number of samples to be generated (granularity of the explanation)
    linspace_samples = 25

    # Calculate Partial Dependence
    pd_array, pd_linspace = fatf_fi.partial_dependence(
        iris_X, clf, selected_feature_index, steps_number=linspace_samples)

    # Plot Partial Dependence on its own
    pd_plot_clean = fatf_vis_fi.plot_partial_dependence(
        pd_array,
        pd_linspace,
        explanation_class,
        class_name=explanation_class_name,
        feature_name=selected_feature_name)


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

   **Total running time of the script:** ( 0 minutes  12.853 seconds)


.. _sphx_glr_download_sphinx_gallery_auto_transparency_xmpl_transparency_pd.py:


.. only :: html

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


  .. container:: binder-badge

    .. image:: https://mybinder.org/badge_logo.svg
      :target: https://mybinder.org/v2/gh/fat-forensics/fat-forensics-doc/master?filepath=notebooks/sphinx_gallery_auto/transparency/xmpl_transparency_pd.ipynb
      :width: 150 px


  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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


.. only:: html

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

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