eyetools is a package that provides a set of simple tools that will facilitate common steps in the processing and analysis of eye data. It is intended for use with data from psychological experiments. The idea is to have a workflow which is aided by these functions, going from processing of the raw data, to extraction of event related data (i.e., fixations, saccades), to summarising those data at the trial level (e.g., time on areas of interest).
For an indepth guide to using eyetools, see the Get Started page.
Warning - still in somewhat experimental form! Please check results carefully
to install:
devtools::install_github("tombeesley/eyetools")
It is free to use under the GNU General Public Licence.
Available functions:
| Implemented functions | Description |
|---|---|
AOI_seq() |
Detect the sequence in which AOIs were entered in a trial |
AOI_time() |
Time on AOIs; works with rectangular and circular AOIs; works with raw and fixation data |
combine_eyes() |
Combines binocular data (i.e., average or “best eye”) |
compare_algorithms() |
Provides a comparison between the dispersion and VTI fixation algorithms with correlations and plot |
conditional_transform() |
Implements a single-axis flip for specific trials to normalise data with counterbalanced designs |
fixation_dispersion() |
Dispersion algorithm for fixation detection |
fixation_VTI() |
An inverse saccade algorithm for fixation detection |
hdf5_to_csv() |
converts eyetracking data retrieved from TOBII eyetrackers to csv |
interpolate() |
Interpolates data across gaps; provides a summary report of repair |
plot_seq() |
provides a 2D plot of raw data in one trial. Data can be split into time bins |
plot_spatial() |
provides a 2D plot of raw data, fixations, saccades, and AOIs |
saccade_VTI() |
Velocity threshold algorithm for saccade detection. Provides summary of velocity, location, duration |
smoother() |
smooths data for use in saccade algorithms |