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

    Click :ref:`here <sphx_glr_download_auto_examples_Phase_examples_plot_itpc_example.py>` to download the full example code
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_Phase_examples_plot_itpc_example.py:


==============================
 Inter-Trial Phase Clustering
==============================

This example shows how to compute and plot the ITPC : Inter-Trial Phase Coherence from a SabDataset instance




.. code-block:: python


    # import matplotlib
    # matplotlib.use('TkAgg')
    import numpy as np
    import matplotlib.pyplot as plt
    from os.path import isdir, join
    plt.rcParams['image.cmap'] = 'viridis'
    from sab_dataset import *
    import seaborn as sns
    sns.set()
    sns.set_context('paper')







Load the data : sab dataset



.. code-block:: python

    sab_dataset_dirpath = join('pySAB', 'sample_data') if isdir('pySAB') else join('..', '..', 'pySAB', 'sample_data')
    sab_dataset_filename = 'sab_dataset_rec_subject_id_040119_1153.p'
    rec_dataset = load_sab_dataset(join(sab_dataset_dirpath, sab_dataset_filename))







Print dataset information



.. code-block:: python

    print(rec_dataset)





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

 Out:

 .. code-block:: none

    SAB dataset REC - subject_id
    7 channels, 359 points [-0.10, 0.60s], sampling rate 512.0 Hz
    356 trials : 183 hits, 173 correct rejects, 0 omissions, 0 false alarms
    Channel Info : 7 channels and 1 electrodes
    7 EEG channels - 0 non-EEG channels
    1 EEG electrodes - 0 non-EEG electrodes


Downsample the dataset



.. code-block:: python

    rec_dataset.downsample(2)





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

 Out:

 .. code-block:: none

    New sampling rate is 256.0


Select filter center frequencies and filter bandwidth



.. code-block:: python

    n_filters = 30
    filt_cf = np.logspace(np.log10(3), np.log10(70), n_filters)
    filt_bw = np.logspace(np.log10(1.5), np.log10(20), n_filters)
    f = plt.figure()
    ax = f.add_subplot(111)
    ax.scatter(np.arange(n_filters), filt_cf, zorder=2)
    ax.vlines(np.arange(n_filters), filt_cf-filt_bw/2, filt_cf+filt_bw/2, zorder=1)
    ax.set(title='Filters center frequency and bandwidth', xlabel='Filter index', ylabel='(Hz)')
    plt.legend(['Center frequency', 'Bandwidth'])




.. image:: /auto_examples/Phase_examples/images/sphx_glr_plot_itpc_example_001.png
    :class: sphx-glr-single-img




Compute and plot the ITPC of channel 4, for hits trials



.. code-block:: python

    rec_dataset.plot_itpc(4, rec_dataset.hits, filt_cf, filt_bw, n_monte_carlo=1, contour_plot=1)




.. image:: /auto_examples/Phase_examples/images/sphx_glr_plot_itpc_example_002.png
    :class: sphx-glr-single-img




**Total running time of the script:** ( 0 minutes  34.629 seconds)


.. _sphx_glr_download_auto_examples_Phase_examples_plot_itpc_example.py:


.. only :: html

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



  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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


.. only:: html

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

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