.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/plot_metrics.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_metrics.py>`
        to download the full example code.

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

.. _sphx_glr_auto_examples_plot_metrics.py:

Computing Multi-Objective Quality Metrics
=========================================

TODO: Expand this

.. GENERATED FROM PYTHON SOURCE LINES 7-11

.. code-block:: Python


    import numpy as np
    import moocore








.. GENERATED FROM PYTHON SOURCE LINES 12-14

First, read the datasets.


.. GENERATED FROM PYTHON SOURCE LINES 14-42

.. code-block:: Python


    spherical = moocore.get_dataset("spherical-250-10-3d.txt")
    uniform = moocore.get_dataset("uniform-250-10-3d.txt")

    ref = 1.1
    ref_set = moocore.filter_dominated(
        np.vstack((spherical[:, :-1], uniform[:, :-1]))
    )


    def apply_within_sets(x, fun, **kwargs):
        """Apply ``fun`` for each dataset in ``x``."""
        _, uniq_index = np.unique(x[:, -1], return_index=True)
        x_split = np.vsplit(x[:, :-1], uniq_index[1:])
        return [fun(g, **kwargs) for g in x_split]


    uniform_igd_plus = apply_within_sets(uniform, moocore.igd_plus, ref=ref_set)
    spherical_igd_plus = apply_within_sets(
        spherical, moocore.igd_plus, ref=ref_set
    )

    print(f"""
                Uniform       Spherical
                -------       ---------
    Mean IGD+:  {np.mean(uniform_igd_plus):.5f}       {np.mean(spherical_igd_plus):.5f}

    """)




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

 .. code-block:: none


                Uniform       Spherical
                -------       ---------
    Mean IGD+:  5.96976       0.01988







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

   **Total running time of the script:** (0 minutes 0.145 seconds)


.. _sphx_glr_download_auto_examples_plot_metrics.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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