Repo for the post-processing and analysis of Pupil, Qualisys, and Unity data that make up the ARGP experience
- set up a python 3.9 environment, using your preferred method of environment building
- make sure the requirements are satisfied (only 4 libraries atm: numpy, matplotlib, pandas and seaborn)'
- this might be handled by pycharm?
- and (in case it wasn't obvious), clone this repository and assign the python 3.9 environment as your interpreter
Warning: the demo should work but it hasn't been tested since early October 2022
- follow this URL to download a zip file containing all the demo files that you'll need
- this contains three files:
2022-08-29_Pilot_Data0002.tsv
<- qualisys data as a.tsv
filepupil_positions.csv
<- pupil labs data, currently not usedqualisys_dict.json
<- the code will create this, but you can point your paths at this file on line 32 ofmain.py
and save yourself time
- fix your paths (lines 16-37 of
main.py
) so that your code is pointed at the correct data (see Demo Data) - put a breakpoint at line 42 in
main.py
- run
main.py
the resulting output will be a frontal view of the 3D skeleton