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

.. only:: html

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

        Click :ref:`here <sphx_glr_download_auto_examples_queries_plot_marginalize.py>`
        to download the full example code

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

.. _sphx_glr_auto_examples_queries_plot_marginalize.py:


.. _marginalizing_an_spn:

====================
Marginalizing an SPN
====================

"Marginalizing an SPN" means summing out all other non-relevant variables.

.. GENERATED FROM PYTHON SOURCE LINES 10-19

.. code-block:: default



    from spn.structure.leaves.parametric.Parametric import Categorical
    from spn.structure.Base import Sum, Product
    from spn.structure.Base import assign_ids, rebuild_scopes_bottom_up

    from spn.io.Graphics import draw_spn
    import matplotlib.pyplot as plt








.. GENERATED FROM PYTHON SOURCE LINES 21-23

We will start with the Sum-Product Network structure from the
:ref:`composing_spn_object_hierarchy` example.

.. GENERATED FROM PYTHON SOURCE LINES 23-37

.. code-block:: default


    p0 = Product(children=[Categorical(p=[0.3, 0.7], scope=1), Categorical(p=[0.4, 0.6], scope=2)])
    p1 = Product(children=[Categorical(p=[0.5, 0.5], scope=1), Categorical(p=[0.6, 0.4], scope=2)])
    s1 = Sum(weights=[0.3, 0.7], children=[p0, p1])
    p2 = Product(children=[Categorical(p=[0.2, 0.8], scope=0), s1])
    p3 = Product(children=[Categorical(p=[0.2, 0.8], scope=0), Categorical(p=[0.3, 0.7], scope=1)])
    p4 = Product(children=[p3, Categorical(p=[0.4, 0.6], scope=2)])
    spn = Sum(weights=[0.4, 0.6], children=[p2, p4])

    assign_ids(spn)
    rebuild_scopes_bottom_up(spn)

    ax = draw_spn(spn)




.. image-sg:: /auto_examples/queries/images/sphx_glr_plot_marginalize_001.png
   :alt: plot marginalize
   :srcset: /auto_examples/queries/images/sphx_glr_plot_marginalize_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 38-40

If we want to marginalize this SPN by summing out all other variables
to leave variables 1 and 2, we can do this as follows:

.. GENERATED FROM PYTHON SOURCE LINES 40-45

.. code-block:: default


    from spn.algorithms.Marginalization import marginalize

    spn_marg = marginalize(spn, [1, 2])








.. GENERATED FROM PYTHON SOURCE LINES 46-49

This marginalizes all the variables *not* in :math:`[1, 2]`, and create a
*new* structure that knows nothing about the previous one nor about the
variable 0.

.. GENERATED FROM PYTHON SOURCE LINES 49-51

.. code-block:: default


    draw_spn(spn_marg)



.. image-sg:: /auto_examples/queries/images/sphx_glr_plot_marginalize_002.png
   :alt: plot marginalize
   :srcset: /auto_examples/queries/images/sphx_glr_plot_marginalize_002.png
   :class: sphx-glr-single-img


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

 Out:

 .. code-block:: none


    <module 'matplotlib.pyplot' from '/opt/hostedtoolcache/Python/3.6.15/x64/lib/python3.6/site-packages/matplotlib/pyplot.py'>




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

   **Total running time of the script:** ( 0 minutes  0.454 seconds)


.. _sphx_glr_download_auto_examples_queries_plot_marginalize.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_marginalize.py <plot_marginalize.py>`



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

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


.. only:: html

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

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