Difference between revisions of "DataHub"

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===Versions===
 
===Versions===
Unity is constantly updated, and new versions will frequently include Beta features that may not be super reliable and well documented yet. As such it is sometimes quite difficult to figure out which version to use. If you wish to create your own Unity projects, we advise to install the latest long term support (LTS) release. Beware that any tutorials, forum answers and plugins you find online may no longer be compatible with your version, so always check the date and official documentation. Of course you can also come to the TSG for help.
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Version 1.15.0 is the last used version. Open a command to find your version used:
  
 
==Usage==
 
==Usage==

Revision as of 10:41, 1 February 2022

DataHub
Developer(s)Christian Kothe; Chadwick Boulay.
Development status-in development-
Written inC, C++, Python, Java, C#, MATLAB
Operating systemWindows, Linux, MacOS, Android, iOS
TypeData collection
LicenseOpen source
WebsiteLSL webpage
Manuals

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:
python -m pip install --upgrade pip
Then:
pip install pylsl

more info: cross platform pylsl

Versions

Version 1.15.0 is the last used version. Open a command to find your version used:

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


External Links