.. _sphx_glr_auto_examples_plot_mtf.py:


=======================
Markov Transition Field
=======================

This example shows how you can transform a time series into a Markov Transition
Field using :class:`pyts.image.MTF`.




.. image:: /auto_examples/images/sphx_glr_plot_mtf_001.png
    :align: center





.. code-block:: python


    import numpy as np
    import matplotlib.pyplot as plt
    from pyts.image import MTF

    # Parameters
    n_samples, n_features = 100, 144

    # Toy dataset
    rng = np.random.RandomState(41)
    X = rng.randn(n_samples, n_features)

    # MTF transformation
    image_size = 24
    mtf = MTF(image_size)
    X_mtf = mtf.fit_transform(X)

    # Show the results for the first time series
    plt.figure(figsize=(8, 8))
    plt.imshow(X_mtf[0], cmap='rainbow', origin='lower')
    plt.show()

**Total running time of the script:** ( 0 minutes  0.460 seconds)



.. only :: html

 .. container:: sphx-glr-footer


  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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


.. only:: html

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

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