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

.. only:: html

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

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

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

.. _sphx_glr_auto_examples_plot_transformer.py:


===================
Transform example
===================

Rank similarity transform makes an unsupervised non-linear transform, here on
the digits dataset. By plotting the first two dimensions, e.g. responses of the
first two filters you can see which digits they are sensitive to.

.. GENERATED FROM PYTHON SOURCE LINES 13-29



.. image-sg:: /auto_examples/images/sphx_glr_plot_transformer_001.png
   :alt: plot transformer
   :srcset: /auto_examples/images/sphx_glr_plot_transformer_001.png
   :class: sphx-glr-single-img





.. code-block:: default


    import numpy as np
    from matplotlib import pyplot as plt
    from ranksim import RankSimilarityTransform

    from sklearn.datasets import load_digits
    X, y = load_digits(return_X_y=True)

    embedding = RankSimilarityTransform(n_filters=10, n_iter=20, 
                                            random_state=0)
    X_transformed = embedding.fit_transform(X)

    plt.figure(figsize=(10,8))
    plt.scatter(X_transformed[:,0], X_transformed[:,1], c=y, cmap='tab10')
    plt.colorbar(boundaries=np.arange(11)-0.5).set_ticks(np.arange(10))
    plt.show()


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

   **Total running time of the script:** ( 0 minutes  0.379 seconds)


.. _sphx_glr_download_auto_examples_plot_transformer.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_transformer.py <plot_transformer.py>`



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

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


.. only:: html

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

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