Difference between revisions of "DataHub"
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===Versions=== | ===Versions=== | ||
− | The TSG uses the version 1.15.0. Open a command to find | + | The TSG uses the version 1.15.0. Open a command and type the following to find the version used: |
<code style="background-color:#000; color:#fff; padding:1px 3px;">c:>python</code><br/> | <code style="background-color:#000; color:#fff; padding:1px 3px;">c:>python</code><br/> |
Revision as of 09:59, 1 February 2022
Developer(s) | Christian Kothe; Chadwick Boulay. | ||||
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Development status | -in development- | ||||
Written in | C, C++, Python, Java, C#, MATLAB | ||||
Operating system | Windows, Linux, MacOS, Android, iOS | ||||
Type | Data collection | ||||
License | Open source | ||||
Website | LSL webpage | ||||
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The DataHub Makes use of the lab streaming layer. The lab streaming layer (LSL) is a system for the unified collection of measurement time series in research experiments that handles both the networking, time-synchronization, (near-) real-time access as well as optionally the centralized collection, viewing and disk recording of the data.
Installation
Our support for LSL is mainly done in python. Download python here: Please choose a 64 bit version.. Run the installer and make sure to add Python to the file path (it's an option in the installer).
Open a command prompt, start with upgrading the pip installer by typing:
c:>python -m pip install --upgrade pip
Then:
c:>pip install pylsl
more info: cross platform pylsl
Versions
The TSG uses the version 1.15.0. Open a command and type the following to find the version used:
c:>python
>>> import pylsl
>>> print(pylsl.__version__)
Usage
(Under Construction)
We are working on templates and tips. Stay tuned!
Builds
We advise not to run your experiment from the Unity Editor, this will cause unwanted overhead that harms the performance. You can create a PC Standalone build to run it on our lab computers.
References