.. image:: https://badges.gitter.im/braindecodechat/community.svg
:alt: Join the chat at https://gitter.im/braindecodechat/community
:target: https://gitter.im/braindecodechat/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge
.. image:: https://github.com/braindecode/braindecode/workflows/docs/badge.svg
:target: https://github.com/braindecode/braindecode/actions
.. image:: https://circleci.com/gh/braindecode/braindecode.svg?style=svg
:target: https://circleci.com/gh/braindecode/braindecode
:alt: Doc build on CircleCI
.. image:: https://codecov.io/gh/braindecode/braindecode/branch/master/graph/badge.svg
: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
^^^^^^^^^
Braindecode is **BSD-licenced** (BSD-3-Clause):
This software is OSI Certified Open Source Software.
OSI Certified is a certification mark of the Open Source Initiative.
Copyright (c) 2011-2022, authors of Braindecode.
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
* Neither the names of braindecode authors nor the names of any
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.
**This software is provided by the copyright holders and contributors
"as is" and any express or implied warranties, including, but not
limited to, the implied warranties of merchantability and fitness for
a particular purpose are disclaimed. In no event shall the copyright
owner or contributors be liable for any direct, indirect, incidental,
special, exemplary, or consequential damages (including, but not
limited to, procurement of substitute goods or services; loss of use,
data, or profits; or business interruption) however caused and on any
theory of liability, whether in contract, strict liability, or tort
(including negligence or otherwise) arising in any way out of the use
of this software, even if advised of the possibility of such
damage.**
Raw data
{
"_id": null,
"home_page": "",
"name": "braindecode",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": "Alexandre Gramfort <agramfort@meta.com>, Bruno Aristimunha Pinto <b.aristimunha@gmail.com>, Robin Tibor Schirrmeister <robintibor@gmail.com>",
"keywords": "python,deep-learning,neuroscience,pytorch,meg,eeg,neuroimaging,electroencephalography,magnetoencephalography,electrocorticography,ecog,electroencephalogram",
"author": "",
"author_email": "Robin Tibor Schirrmeister <robintibor@gmail.com>",
"download_url": "https://files.pythonhosted.org/packages/42/40/a20b82679f738cde851b34a7a5b7a13b2c80685ffd508473b47f79e816a5/braindecode-0.8.1.tar.gz",
"platform": null,
"description": ".. image:: https://badges.gitter.im/braindecodechat/community.svg\n :alt: Join the chat at https://gitter.im/braindecodechat/community\n :target: https://gitter.im/braindecodechat/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge\n\n.. image:: https://github.com/braindecode/braindecode/workflows/docs/badge.svg\n :target: https://github.com/braindecode/braindecode/actions\n\n.. image:: https://circleci.com/gh/braindecode/braindecode.svg?style=svg\n :target: https://circleci.com/gh/braindecode/braindecode\n :alt: Doc build on CircleCI\n\n.. image:: https://codecov.io/gh/braindecode/braindecode/branch/master/graph/badge.svg\n :target: https://codecov.io/gh/braindecode/braindecode\n :alt: Code Coverage\n\n.. |Braindecode| image:: https://user-images.githubusercontent.com/42702466/177958779-b00628aa-9155-4c51-96d1-d8c345aff575.svg\n.. _braindecode: braindecode.org/\n\nBraindecode\n===========\n\nBraindecode is an open-source Python toolbox for decoding raw electrophysiological brain\ndata with deep learning models. It includes dataset fetchers, data preprocessing and\nvisualization tools, as well as implementations of several deep learning\narchitectures and data augmentations for analysis of EEG, ECoG and MEG.\n\nFor neuroscientists who want to work with deep learning and\ndeep learning researchers who want to work with neurophysiological data.\n\n\nInstallation Braindecode\n========================\n\n1. Install pytorch from http://pytorch.org/ (you don't need to install torchvision).\n\n2. If you want to download EEG datasets from `MOABB <https://github.com/NeuroTechX/moabb>`_, install it:\n\n.. code-block:: bash\n\n pip install moabb\n\n3. Install latest release of braindecode via pip:\n\n.. code-block:: bash\n\n pip install braindecode\n\nIf you want to install the latest development version of braindecode, please refer to `contributing page <https://github.com/braindecode/braindecode/blob/master/CONTRIBUTING.md>`__\n\n\nDocumentation\n=============\n\nDocumentation is online under https://braindecode.org, both in the stable and dev versions.\n\n\nContributing to Braindecode\n===========================\n\nGuidelines for contributing to the library can be found on the braindecode github:\n\nhttps://github.com/braindecode/braindecode/blob/master/CONTRIBUTING.md\n\nBraindecode chat\n================\n\nhttps://gitter.im/braindecodechat/community\n\nCiting\n======\n\nIf you use this code in a scientific publication, please cite us as:\n\n.. code-block:: bibtex\n\n @article {HBM:HBM23730,\n author = {Schirrmeister, Robin Tibor and Springenberg, Jost Tobias and Fiederer,\n Lukas Dominique Josef and Glasstetter, Martin and Eggensperger, Katharina and Tangermann, Michael and\n Hutter, Frank and Burgard, Wolfram and Ball, Tonio},\n title = {Deep learning with convolutional neural networks for EEG decoding and visualization},\n journal = {Human Brain Mapping},\n issn = {1097-0193},\n url = {http://dx.doi.org/10.1002/hbm.23730},\n doi = {10.1002/hbm.23730},\n month = {aug},\n year = {2017},\n keywords = {electroencephalography, EEG analysis, machine learning, end-to-end learning, brain\u2013machine interface,\n brain\u2013computer interface, model interpretability, brain mapping},\n }\n\nas well as the `MNE-Python <https://mne.tools>`_ software that is used by braindecode:\n\n.. code-block:: bibtex\n\n @article{10.3389/fnins.2013.00267,\n 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 H\u00e4m\u00e4l\u00e4inen, Matti},\n title={{MEG and EEG data analysis with MNE-Python}},\n journal={Frontiers in Neuroscience},\n volume={7},\n pages={267},\n year={2013},\n url={https://www.frontiersin.org/article/10.3389/fnins.2013.00267},\n doi={10.3389/fnins.2013.00267},\n issn={1662-453X},\n }\n\n\n\n\nLicensing\n^^^^^^^^^\n\nBraindecode is **BSD-licenced** (BSD-3-Clause):\n\n This software is OSI Certified Open Source Software.\n OSI Certified is a certification mark of the Open Source Initiative.\n\n Copyright (c) 2011-2022, authors of Braindecode.\n All rights reserved.\n\n Redistribution and use in source and binary forms, with or without\n modification, are permitted provided that the following conditions are met:\n\n * Redistributions of source code must retain the above copyright notice,\n this list of conditions and the following disclaimer.\n\n * Redistributions in binary form must reproduce the above copyright notice,\n this list of conditions and the following disclaimer in the documentation\n and/or other materials provided with the distribution.\n\n * Neither the names of braindecode authors nor the names of any\n contributors may be used to endorse or promote products derived from\n this software without specific prior written permission.\n\n **This software is provided by the copyright holders and contributors\n \"as is\" and any express or implied warranties, including, but not\n limited to, the implied warranties of merchantability and fitness for\n a particular purpose are disclaimed. In no event shall the copyright\n owner or contributors be liable for any direct, indirect, incidental,\n special, exemplary, or consequential damages (including, but not\n limited to, procurement of substitute goods or services; loss of use,\n data, or profits; or business interruption) however caused and on any\n theory of liability, whether in contract, strict liability, or tort\n (including negligence or otherwise) arising in any way out of the use\n of this software, even if advised of the possibility of such\n damage.**\n",
"bugtrack_url": null,
"license": "BSD-3-Clause",
"summary": "Deep learning software to decode EEG, ECG or MEG signals",
"version": "0.8.1",
"project_urls": {
"documentation": "https://braindecode.org/stable/index.html",
"homepage": "https://braindecode.org",
"repository": "https://github.com/braindecode/braindecode"
},
"split_keywords": [
"python",
"deep-learning",
"neuroscience",
"pytorch",
"meg",
"eeg",
"neuroimaging",
"electroencephalography",
"magnetoencephalography",
"electrocorticography",
"ecog",
"electroencephalogram"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "1592ab003b014a1e712d62502240dd2eacd4d458a3cb8ee2c8f978ae1754458e",
"md5": "d0edd4c5aa0f41a33e3201302df13ede",
"sha256": "6c2a571095a6ca366ade93a1a12bafce3225ce7d395eca6f7e2eb66edb5dd7da"
},
"downloads": -1,
"filename": "braindecode-0.8.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "d0edd4c5aa0f41a33e3201302df13ede",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8",
"size": 165158,
"upload_time": "2023-11-14T13:45:17",
"upload_time_iso_8601": "2023-11-14T13:45:17.168590Z",
"url": "https://files.pythonhosted.org/packages/15/92/ab003b014a1e712d62502240dd2eacd4d458a3cb8ee2c8f978ae1754458e/braindecode-0.8.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "4240a20b82679f738cde851b34a7a5b7a13b2c80685ffd508473b47f79e816a5",
"md5": "62c33232fca6f47e27c2c971b578d851",
"sha256": "e80515c3d20a80f16800770936d1eb0012de15830a8175dce376256bdaf928e7"
},
"downloads": -1,
"filename": "braindecode-0.8.1.tar.gz",
"has_sig": false,
"md5_digest": "62c33232fca6f47e27c2c971b578d851",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 385856,
"upload_time": "2023-11-14T13:45:31",
"upload_time_iso_8601": "2023-11-14T13:45:31.241871Z",
"url": "https://files.pythonhosted.org/packages/42/40/a20b82679f738cde851b34a7a5b7a13b2c80685ffd508473b47f79e816a5/braindecode-0.8.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-11-14 13:45:31",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "braindecode",
"github_project": "braindecode",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"circle": true,
"lcname": "braindecode"
}
JSON
