Metadata-Version: 2.4
Name: mne_lsl
Version: 0.0.0
Summary: Real-time framework integrated with MNE-Python for online neuroscience research through LSL-compatible devices.
Author-email: Mathieu Scheltienne <mathieu.scheltienne@gmail.com>
Maintainer-email: Mathieu Scheltienne <mathieu.scheltienne@gmail.com>
License: Copyright © 2023-2024, authors of MNE-LSL
        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 name of the copyright holder nor the names of its
              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 COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY
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        (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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        ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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Project-URL: documentation, https://mne.tools/mne-lsl
Project-URL: homepage, https://mne.tools/mne-lsl
Project-URL: source, https://github.com/mne-tools/mne-lsl
Project-URL: tracker, https://github.com/mne-tools/mne-lsl/issues
Keywords: brain,EEG,eeg,electroencephalography,labstreaminglayer,LSL,neuroimaging,neurophysiology,neuroscience,python,real-time
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: click>=8.1
Requires-Dist: mne>=1.6
Requires-Dist: numpy<3,>=1.21
Requires-Dist: packaging
Requires-Dist: pooch
Requires-Dist: psutil
Requires-Dist: pyqtgraph
Requires-Dist: qtpy
Requires-Dist: scipy
Requires-Dist: tomli; python_version < "3.11"
Dynamic: license-file

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<img align="right" src="https://raw.githubusercontent.com/mne-tools/mne-lsl/main/doc/_static/logos/logo-mne-hex.svg" alt="logo" width="200"/>

**MNE-LSL** [(Documentation website)](https://mne.tools/mne-lsl)
provides a real-time brain signal streaming framework.
**MNE-LSL** contains an improved python-binding for the Lab Streaming Layer C++ library,
`mne_lsl.lsl`, replacing `pylsl`. This low-level binding is used in high-level objects
to interact with LSL streams.

Any signal acquisition system supported by native LSL or OpenVibe is also
supported by MNE-LSL. Since the data communication is based on TCP, signals can be
transmitted wirelessly. For more information about LSL, please visit the
[LSL github](https://github.com/sccn/labstreaminglayer).

# Install

MNE-LSL supports `python ≥ 3.10` and is available on
[PyPI](https://pypi.org/project/mne-lsl/) and on
[conda-forge](https://anaconda.org/conda-forge/mne-lsl).
Install instruction can be found on the
[documentation website](https://mne.tools/mne-lsl/stable/resources/install.html).

# Acknowledgment

<img align="right" src="https://raw.githubusercontent.com/mne-tools/mne-lsl/main/doc/_static/partners/FCBG.svg" width=100>

**MNE-LSL** is based on **BSL** and **NeuroDecode**. The original version developed by
[**Kyuhwa Lee**](https://github.com/dbdq) was recognised at
[Microsoft Brain Signal Decoding competition](https://github.com/dbdq/microsoft_decoding)
with the First Prize Award (2016).
**MNE-LSL** is based on the refactor version, **BSL** by
[**Mathieu Scheltienne**](https://github.com/mscheltienne) and
[**Arnaud Desvachez**](https://github.com/dnastars) for the
[Fondation Campus Biotech Geneva (FCBG)](https://github.com/fcbg-platforms) and
development is still supported by the
[Fondation Campus Biotech Geneva (FCBG)](https://fcbg.ch/).

# Copyright and license

The code is released under the
[BSD 3-Clause License](https://opensource.org/license/bsd-3-clause/).
