1
0
Fork 0
mirror of https://github.com/sccn/liblsl.git synced 2025-12-06 02:49:17 +00:00
No description
Find a file
2025-11-29 13:07:50 -05:00
.github ARM runners, arm packages (rpi, jetson compatible) 2025-11-29 13:01:41 -05:00
cmake option -> cmake_dependent_option 2025-11-29 13:07:50 -05:00
conda Move conda build from azure pipelines into separate repository, remove OS X specific hacks 2019-07-17 10:12:51 +02:00
docs Allow force enabling C++11 support in C++ API by defining LSL_CPP11 2020-12-26 18:40:59 +01:00
examples examples - find_package must search in Frameworks subdirectory if APPLE. 2025-07-27 12:01:20 -06:00
include Update docs 2025-03-23 22:03:21 +08:00
lslboost/boost Update boost (with update script) to version v1.89.0 2025-11-05 14:09:52 +01:00
project Remove MSVC2013 project files 2020-07-21 00:42:30 -04:00
scripts Merge upstream cboulay/apple_framework 2025-11-10 07:05:15 +01:00
src Allow liblsl compilation with c++14. 2025-04-02 12:34:25 +02:00
testing Intermittent failure on OSX runners in stream resolution, fix part 2 2025-11-29 13:03:36 -05:00
thirdparty Update pugixml to v1.15 2025-11-05 14:07:36 +01:00
.appveyor_disabled.yml CI: set install prefix / build type explicitly, disable appveyor for now 2020-11-19 11:37:41 +01:00
.artifactignore CI: publish build artifacts 2019-07-01 11:51:05 +02:00
.clang-format Add editorconfig / clang-format config from main repository 2020-11-02 08:38:32 +01:00
.clang-tidy Bump build/CI config to C++17 with MSVC 2019 2023-06-12 19:39:57 +02:00
.editorconfig ARM runners, arm packages (rpi, jetson compatible) 2025-11-29 13:01:41 -05:00
.gitignore Remove examples from primary build because they were relying on in-tree artifacts and thus were masking installation issues 2025-07-27 11:29:28 -06:00
.readthedocs.yml Disable deprecated use_system_packages in .readthedocs.yml 2023-08-08 07:09:17 +02:00
azure-pipelines.yml Revert "Revert "CI: remove manylinux1 target" because manylinux2010 problematic for some pylsl users." 2021-05-11 02:34:55 -04:00
CHANGELOG.md Update changelog for 1.16 2022-02-22 17:22:41 +01:00
CMakeLists.txt Fixup iOS builds 2025-07-27 12:01:20 -06:00
LICENSE Add used third party packages to the LICENSE file 2021-06-10 12:01:56 +02:00
lsl.entitlements Add preliminary support for Xcode and building universal dylib 2025-07-27 12:00:49 -06:00
pi.cmake RaspberriPi cross-compiling... but not working. 2018-08-16 12:44:20 -04:00
README.md Delete deprecated travis config and badge 2025-07-27 11:29:28 -06:00

GitHub Actions Status Azure Build Status DOI

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:

  • The API headers are in the include/ directory.
  • The library source code is in the src/ directory.
  • Unit tests are in the testing/ directory

To connect an application to the lab streaming layer:

  • Include the header for your language (lsl_c.h for C, lsl_cpp.h for C++) (automatically done when using CMake) or get bindings for your preferred language
  • Make sure that the library file (liblsl.so/liblsl.dylib/lsl.dll) is found by your application. On Windows, it should be enough to put it in the same folder as your executable. When building a Windows app, also make sure that the lsl.lib file is visible to your build environment.
  • To provide data, create a new streaminfo to describe your stream and create a new outlet with that info. Push samples into the outlet as your app produces them. Destroy the outlet when you're done.
  • To receive data, resolve a stream that matches your citeria (e.g. name or type), which gives you a streaminfo and create a new inlet with that streaminfo. Pull samples from the inlet. Destroy the inlet when you're done.
  • Have a look at the example sources in the examples/ folder.

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