:orphan:



.. _sphx_glr_auto_paper:

.. _paper:

Reproducing paper results
=========================

The following scripts allow to preprocess the open-source data set used 
in our paper [1]_, and to reproduce the corresponding results.

The data set is downloaded from the OpenNeuro repository, accession number: ds003490 [2]_.

To run the analysis, download all codes in this page  in the same folder. Then, please add to the
folder the requirements.txt file at this
`link <https://github.com/elisabettavallarino/transfreq/blob/master/examples_paper/requirements.txt>`_.

The results of the paper can be obtained by running the following commands in a terminal.

.. code::

	python3 -m venv transfreq_env
	source transfreq_env/bin/activate
	# In Windows replace the previous command with
	# transfreq_env\Scripts\activate 
	pip install --upgrade pip
	python3 -m pip install -r requirements.txt
	pip install transfreq
	python3 00_fetch_data.py
	python3 01_preprocessing.py
	python3 02_psd.py
	python3 03_compute_transfreq.py
	python3 04_plots.py
 
.. [1] E. Vallarino, S. Sommariva, D. Arnaldi, F. Famà, M. Piana, F. Nobili. Transfreq: a Python package for computing the theta-to-alpha transition frequency from resting state EEG data. Submitted.
.. [2] J.F. Cavanagh, P. Kumar, A.A. Mueller, S.P. Richardson, A. Mueen. Diminished  EEG habituation  to novel  events  effectively  classifies  Parkinson’s patients. Clinical Neurophysiology 129, 409–418 (2018).



.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="Part 1: Fetch data">

.. only:: html

 .. figure:: /auto_paper/images/thumb/sphx_glr_00_fetch_data_thumb.png
     :alt: Part 1: Fetch data

     :ref:`sphx_glr_auto_paper_00_fetch_data.py`

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /auto_paper/00_fetch_data

.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="Part 2: Preprocessing">

.. only:: html

 .. figure:: /auto_paper/images/thumb/sphx_glr_01_preprocessing_thumb.png
     :alt: Part 2: Preprocessing

     :ref:`sphx_glr_auto_paper_01_preprocessing.py`

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /auto_paper/01_preprocessing

.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="Part 3: Compute power spectra">

.. only:: html

 .. figure:: /auto_paper/images/thumb/sphx_glr_02_psd_thumb.png
     :alt: Part 3: Compute power spectra

     :ref:`sphx_glr_auto_paper_02_psd.py`

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /auto_paper/02_psd

.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="Part 4: Compute transition frequency">

.. only:: html

 .. figure:: /auto_paper/images/thumb/sphx_glr_03_compute_transfreq_thumb.png
     :alt: Part 4: Compute transition frequency

     :ref:`sphx_glr_auto_paper_03_compute_transfreq.py`

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /auto_paper/03_compute_transfreq

.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="Part 5: Plot results">

.. only:: html

 .. figure:: /auto_paper/images/thumb/sphx_glr_04_plots_thumb.png
     :alt: Part 5: Plot results

     :ref:`sphx_glr_auto_paper_04_plots.py`

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /auto_paper/04_plots

.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="  * Selection of proper time-interval   * Band pass filtering in [2, 50]Hz   * Mark bad segment...">

.. only:: html

 .. figure:: /auto_paper/images/thumb/sphx_glr_preprocessing_info_thumb.png
     :alt: Preprocessing routine

     :ref:`sphx_glr_auto_paper_preprocessing_info.py`

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /auto_paper/preprocessing_info
.. raw:: html

    <div class="sphx-glr-clear"></div>



.. only :: html

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


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

    :download:`Download all examples in Python source code: auto_paper_python.zip </auto_paper/auto_paper_python.zip>`



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

    :download:`Download all examples in Jupyter notebooks: auto_paper_jupyter.zip </auto_paper/auto_paper_jupyter.zip>`


.. only:: html

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

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