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

.. only:: html

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

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

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

.. _sphx_glr_auto_examples_classification_plot_bossvs.py:


===========================================
Bag-of-SFA Symbols in Vector Space (BOSSVS)
===========================================

This example shows how the BOSSVS algorithm transforms a dataset
consisting of time series and their corresponding labels into a
document-term matrix using tf-idf statistics. Each class is represented
as a tfidf vector. For an unlabeled time series, the predicted label is
the label of the tfidf vector giving the highest cosine similarity with
the tf vector of the unlabeled time series.
It is implemented as :class:`pyts.classification.BOSSVS`.

.. GENERATED FROM PYTHON SOURCE LINES 14-69



.. image-sg:: /auto_examples/classification/images/sphx_glr_plot_bossvs_001.png
   :alt: BOSSVS, tf-idf vector for each class (training set), Cosine similarity between tf-idf vectors for each class and tf vectors for each sample (test set)
   :srcset: /auto_examples/classification/images/sphx_glr_plot_bossvs_001.png
   :class: sphx-glr-single-img





.. code-block:: default


    # Author: Johann Faouzi <johann.faouzi@gmail.com>
    # License: BSD-3-Clause

    import numpy as np
    import matplotlib.pyplot as plt
    from pyts.classification import BOSSVS
    from pyts.datasets import load_gunpoint

    # Toy dataset
    X_train, X_test, y_train, y_test = load_gunpoint(return_X_y=True)

    # BOSSVS transformation
    bossvs = BOSSVS(word_size=2, n_bins=3, window_size=10)
    bossvs.fit(X_train, y_train)
    tfidf = bossvs.tfidf_
    vocabulary_length = len(bossvs.vocabulary_)
    X_new = bossvs.decision_function(X_test)

    # Visualize the transformation
    plt.figure(figsize=(14, 5))
    width = 0.4

    plt.subplot(121)
    plt.bar(np.arange(vocabulary_length) - width / 2, tfidf[0],
            width=width, label='Class 1')
    plt.bar(np.arange(vocabulary_length) + width / 2, tfidf[1],
            width=width, label='Class 2')
    plt.xticks(np.arange(vocabulary_length),
               np.vectorize(bossvs.vocabulary_.get)(np.arange(vocabulary_length)),
               fontsize=14)
    plt.ylim((0, 7))
    plt.xlabel("Words", fontsize=14)
    plt.ylabel("tf-idf", fontsize=14)
    plt.title("tf-idf vector for each class (training set)", fontsize=15)
    plt.legend(loc='best')

    plt.subplot(122)
    n_samples_plot = 8
    plt.bar(np.arange(n_samples_plot) - width / 2, X_new[:n_samples_plot, 0],
            width=width, label='Class 1')
    plt.bar(np.arange(n_samples_plot) + width / 2, X_new[:n_samples_plot, 1],
            width=width, label='Class 2')
    plt.xticks(np.arange(n_samples_plot), y_test[:n_samples_plot], fontsize=14)
    plt.ylim((0, 1.2))
    plt.xlabel("True label", fontsize=14)
    plt.ylabel("Cosine similarity", fontsize=14)
    plt.title(("Cosine similarity between tf-idf vectors for each class\n"
               "and tf vectors for each sample (test set)"), fontsize=15)
    plt.legend(loc='best')

    plt.suptitle("BOSSVS", y=0.95, fontsize=22)
    plt.tight_layout()
    plt.subplots_adjust(top=0.75)
    plt.show()


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

   **Total running time of the script:** ( 0 minutes  1.530 seconds)


.. _sphx_glr_download_auto_examples_classification_plot_bossvs.py:

.. only:: html

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


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

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

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

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


.. only:: html

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

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