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

.. only:: html

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

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

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

.. _sphx_glr_auto_examples_image_plot_dataset_rp.py:


============================
Data set of recurrence plots
============================

A recurrence plot is an image obtained from a time series, representing the
pairwise Euclidean distances for each value (and more generally for each
trajectory) in the time series.
The image can be binarized using a threshold.
It is implemented as :class:`pyts.image.RecurrencePlot`.

In this example, we consider the training samples of the
`GunPoint dataset <http://timeseriesclassification.com/description.php?Dataset=GunPoint>`_,
consisting of 50 univariate time series of length 150.
The recurrence plot of each time series is independently computed and the
50 recurrence plots are plotted.

.. GENERATED FROM PYTHON SOURCE LINES 18-49



.. image-sg:: /auto_examples/image/images/sphx_glr_plot_dataset_rp_001.png
   :alt: Recurrence plots for the 50 time series in the 'GunPoint' dataset
   :srcset: /auto_examples/image/images/sphx_glr_plot_dataset_rp_001.png
   :class: sphx-glr-single-img





.. code-block:: default


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

    import matplotlib.pyplot as plt
    from mpl_toolkits.axes_grid1 import ImageGrid
    from pyts.image import RecurrencePlot
    from pyts.datasets import load_gunpoint

    # Load the GunPoint dataset
    X, _, _, _ = load_gunpoint(return_X_y=True)

    # Get the recurrence plots for all the time series
    rp = RecurrencePlot(threshold='point', percentage=20)
    X_rp = rp.fit_transform(X)

    # Plot the 50 recurrence plots
    fig = plt.figure(figsize=(10, 5))

    grid = ImageGrid(fig, 111, nrows_ncols=(5, 10), axes_pad=0.1, share_all=True)
    for i, ax in enumerate(grid):
        ax.imshow(X_rp[i], cmap='binary', origin='lower')
    grid[0].get_yaxis().set_ticks([])
    grid[0].get_xaxis().set_ticks([])

    fig.suptitle(
        "Recurrence plots for the 50 time series in the 'GunPoint' dataset",
        y=0.92
    )

    plt.show()


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

   **Total running time of the script:** ( 0 minutes  2.972 seconds)


.. _sphx_glr_download_auto_examples_image_plot_dataset_rp.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_dataset_rp.py <plot_dataset_rp.py>`

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

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


.. only:: html

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

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