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NOTE

This is a link-repository to the original eeglcf repository, where you will be able to find the code.

eeglcf

This package implements the Localized Component Filtering (LCF) method for EEG artifact rejection:

DelPozo‐Baños, M., & Weidemann, C. T. (2017). Localized component filtering for electroencephalogram artifact rejection. Psychophysiology, 54(4), 608-619. DOI: 10.1111/psyp.12810

Code Example

Let b_data be a numpy.ndarray containing the result of applying a BSS method to EEG data, and a_data be an alternative "cleaner" version of the previous. Let these variable have dimensions CxTxE, where C, T and E are the number of channels, time samples and events respectively. Then, LCF can be applied as:

.. code-block:: python

import eeglcf c_data = eeglcf.lcf(b_data, a_data)

where c_data is a new version of the BSS data built from the mixing of b_data and a_data.

Installation

To install this package, you can use the make file. From the root directory of the package, run:

.. code-block:: bash

make install

.. note::

The installation of the dependencies NumPy_ and SciPy_ may fail. It is recommended to install these packages manually.

Tests

To test the package against your installed python version, from the root directory of the package you can run:

.. code-block:: bash

make test

Issues and comments

Please, file an issue_ if you encounter any problem with the package or if you have any suggestions.

License

The eeglcf framework is open-sourced software licensed under the MIT license <http://opensource.org/licenses/MIT>_.

.. _NumPy: http://www.numpy.org/ .. _SciPy: http://www.scipy.org/ .. _file an issue: https://github.com/mdelpozobanos/eeglcf/issues

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Localized Component Filtering (LCF) method for EEG artifact rejection

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