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Lab Streaming Layer library

The lab streaming layer is a simple all-in-one approach to streaming experiment data between applications in a lab, e.g. instrument time series, event markers, audio, and so on. For more information, please read the online documentation

These repository is for the core library: liblsl

Getting and using liblsl

The most up-to-date instructions to use liblsl are in the quick start online documentation.

You might also be interested in apps to connect to recording equipment and the LabRecorder to record streams to disk.

To retrieve the latest liblsl release, you have a few options.

Precompiled packages are uploaded

liblsl is also available via the following package managers:

If you cannot find a liblsl for you via any of the above methods, then fear not because for most users it is simple to build.

Building liblsl

To compile the library yourself from source, please follow the online documentation.

For single board computers running linux, you can also try standalone_compilation_linux.sh.

Design goals

The design goals of the library are: a) The interface shall be as simple as possible, allowing programs or drivers to send or receive data in just 3-5 lines of code. b) The library should be available for a variety of languages (currently C, C++, Matlab, Python, Java) and platforms (Windows, Mac OS X, Linux, 32/64 bit) and be fully interoperable between them. c) Data transmission should work "out of the box", even across networks with no need to configure IP addresses / hostnames and such (thanks to on-the-fly service discovery), also time synchronization and failure recovery should work out of the box. d) The library should be fully featured. It should cover the relevant streaming data formats incl. multi-channel signals, regular/irregular sampling rate and the major channel data types (int8, int16, int32, float, double, string) in a simple interface. Generic stream meta-data should be supported. Advanced transmission features should be available if desired (but not in the way for simple uses), including custom ways of chunking and buffering the data. It should be possible to configure and tune the behavior of the library (e.g. networking features) via configuration files in a way that is transparent to the applications. e) Network and processor overhead should be reasonably low to not get in the way.

Package overview:

To connect an application to the lab streaming layer:

The library and example applications are licensed under the MIT license.
The library uses code that is licensed under the Boost software license.

Acknowledgements

The original version of this software was written at the Swartz Center for Computational Neuroscience, UCSD. This work was funded by the Army Research Laboratory under Cooperative Agreement Number W911NF-10-2-0022 as well as through NINDS grant 3R01NS047293-06S1.

Citing liblsl

DOI

Information about versioning: https://help.zenodo.org/#versioning