Metadata-Version: 2.4
Name: braindecode
Version: 1.3.0.dev176529508
Summary: Deep learning software to decode EEG, ECG or MEG signals
Author-email: Robin Tibor Schirrmeister <robintibor@gmail.com>
Maintainer-email: Alexandre Gramfort <agramfort@meta.com>, Bruno Aristimunha Pinto <b.aristimunha@gmail.com>, Robin Tibor Schirrmeister <robintibor@gmail.com>
License: BSD-3-Clause
Project-URL: homepage, https://braindecode.org
Project-URL: repository, https://github.com/braindecode/braindecode
Project-URL: documentation, https://braindecode.org/stable/index.html
Keywords: python,deep-learning,neuroscience,pytorch,meg,eeg,neuroimaging,electroencephalography,magnetoencephalography,electrocorticography,ecog,electroencephalogram
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Software Development :: Build Tools
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.10
Description-Content-Type: text/x-rst
License-File: LICENSE.txt
License-File: NOTICE.txt
Requires-Dist: mne>=1.10.0
Requires-Dist: mne_bids>=0.16
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: h5py
Requires-Dist: skorch>=1.2.0
Requires-Dist: torch<3.0,>=2.0
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Requires-Dist: linear_attention_transformer
Requires-Dist: docstring_inheritance
Requires-Dist: rotary_embedding_torch
Provides-Extra: moabb
Requires-Dist: moabb>=1.2.0; extra == "moabb"
Provides-Extra: eegprep
Requires-Dist: eegprep[eeglabio]>=0.1.1; extra == "eegprep"
Provides-Extra: hug
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Provides-Extra: all
Requires-Dist: braindecode[docs,eegprep,hug,moabb,tests]; extra == "all"
Dynamic: license-file

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   :target: https://codecov.io/gh/braindecode/braindecode
   :alt: Code Coverage

.. |Braindecode| image:: https://user-images.githubusercontent.com/42702466/177958779-b00628aa-9155-4c51-96d1-d8c345aff575.svg
.. _braindecode: braindecode.org/

Braindecode
===========

Braindecode is an open-source Python toolbox for decoding raw electrophysiological brain
data with deep learning models. It includes dataset fetchers, data preprocessing and
visualization tools, as well as implementations of several deep learning
architectures and data augmentations for analysis of EEG, ECoG and MEG.

For neuroscientists who want to work with deep learning and
deep learning researchers who want to work with neurophysiological data.


Installation Braindecode
========================

1. Install pytorch from http://pytorch.org/ (you don't need to install torchvision).

2. If you want to download EEG datasets from `MOABB <https://github.com/NeuroTechX/moabb>`_, install it:

.. code-block:: bash

  pip install moabb

3. Install latest release of braindecode via pip:

.. code-block:: bash

  pip install braindecode

If you want to install the latest development version of braindecode, please refer to `contributing page <https://github.com/braindecode/braindecode/blob/master/CONTRIBUTING.md>`__


Documentation
=============

Documentation is online under https://braindecode.org, both in the stable and dev versions.


Contributing to Braindecode
===========================

Guidelines for contributing to the library can be found on the braindecode github:

https://github.com/braindecode/braindecode/blob/master/CONTRIBUTING.md

Braindecode chat
================

https://gitter.im/braindecodechat/community

Citing
======

If you use this code in a scientific publication, please cite us as:

.. code-block:: bibtex

  @article {HBM:HBM23730,
  author = {Schirrmeister, Robin Tibor and Springenberg, Jost Tobias and Fiederer,
    Lukas Dominique Josef and Glasstetter, Martin and Eggensperger, Katharina and Tangermann, Michael and
    Hutter, Frank and Burgard, Wolfram and Ball, Tonio},
  title = {Deep learning with convolutional neural networks for EEG decoding and visualization},
  journal = {Human Brain Mapping},
  issn = {1097-0193},
  url = {http://dx.doi.org/10.1002/hbm.23730},
  doi = {10.1002/hbm.23730},
  month = {aug},
  year = {2017},
  keywords = {electroencephalography, EEG analysis, machine learning, end-to-end learning, brain–machine interface,
    brain–computer interface, model interpretability, brain mapping},
  }

as well as the `MNE-Python <https://mne.tools>`_ software that is used by braindecode:

.. code-block:: bibtex

  @article{10.3389/fnins.2013.00267,
  author={Gramfort, Alexandre and Luessi, Martin and Larson, Eric and Engemann, Denis and Strohmeier, Daniel and Brodbeck, Christian and Goj, Roman and Jas, Mainak and Brooks, Teon and Parkkonen, Lauri and Hämäläinen, Matti},
  title={{MEG and EEG data analysis with MNE-Python}},
  journal={Frontiers in Neuroscience},
  volume={7},
  pages={267},
  year={2013},
  url={https://www.frontiersin.org/article/10.3389/fnins.2013.00267},
  doi={10.3389/fnins.2013.00267},
  issn={1662-453X},
  }




Licensing
^^^^^^^^^

This project is primarily licensed under the BSD-3-Clause License.

Additional Components
~~~~~~~~~~~~~~~~~~~~~

Some components within this repository are licensed under the Creative Commons Attribution-NonCommercial 4.0 International
License.

Please refer to the ``LICENSE`` and ``NOTICE`` files for more detailed
information.
