Eye Tracking Utils
Note
THIS PACKAGE IS UNDER DEVELOPMENT AND IS NOT READY FOR USE
Though we have hopes for this repository to be a registered package in the future, it is only for testing purposes, to be used in parallel to other tools, at this point in time. This project is currently worked on by Alexandros Tantos, Jake Ireland, and others.
It is preferrable that you have coreutils
(or something similar, giving you access to realpath
) installed for the project path to be interpretted by the shebang correctly.
Introduction
This is a Julia implementation of a robust data-preparation and -analysis package using data from eye tracking experiments. This package is designed modelling an R package called eyetrackingR
. This package is not to be confused with the "EyeTracking.jl" package (at time of writing; October, 2020), which seems to be a GUI-style experimental interface (at first glance, perhaps similar to PyGaze).
Installation and Set Up
Ensure you cd
into the EyeTrackingUtils.jl
directory after clone
ing it, and run
julia -E 'import Pkg; etu_home = dirname(@__FILE__); Pkg.activate(etu_home), Pkg.instantiate()'
To obtain any dependencies. This step will not be necessary once this package is registered.
How it works
This package has two main steps in the workflow, whose second step has three paths. This workflow is drawn from eyetrackingR
.
- Data cleaning — obtain data and information about data from various eye-tracking sources (this step should be extremely robust), and puts data into a standardised format for analyses.
- Analyses —:
a) Overall Looking;
b) Onset-Contingent;
c) Time-Course of Looking.
Timeline of Progression
- cdf151e — Began working on the package.
To Do
A Note on running on BSD:
The default JuliaPlots backend GR
does not provide binaries for FreeBSD. Here's how you can build it from source.. That said, StatsPlots
is only a dependency for an example, and not for the main package.