Skip to content

tombeesley/eyetools

Repository files navigation

Lifecycle: experimental CRAN downloads CRAN status

eyetools

A set of tools for eye data processing, analysis and visualisation in R

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.

It is free to use under the GNU General Public Licence.

To install use install.packages("eyetools")

Available functions in the latest CRAN version:

Implemented functions Description
AOI_seq() Detect the sequence in which AOIs were entered in a trial
AOI_time() Calculate time on AOIs; works with raw and fixation data
AOI_time_binned() Binned time analysis of area of interest entries
combine_eyes() Combines binocular data (i.e., average or “best eye”) into monocular data
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
create_AOI_df(). Create a blank data frame for populating with AOIs
fixation_dispersion() Dispersion algorithm for fixation detection
fixation_VTI() An algorithm that subtracts saccadic periods for fixation detection
hdf5_to_df() converts eyetracking data retrieved from TOBII eyetrackers to a dataframe
hdf5_get_event() A function to get the message event files from a TOBII-generated hdf5 files to dataframe
interpolate() Interpolates data across gaps; provides a summary report of repair
plot_AOI_growth() Plots absolute or proportional time spent in AOIs over time
plot_heatmap() Plots a heatmap of raw data.
plot_seq() provides a 2D plot of raw data for a single 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

Development version:

The above CRAN version is considered fairly stable and will only be updated every few months. We work on new features in the development version. This version should be considered very experimental and may have bugs. You can install this using devtools::install_github("tombeesley/eyetools@0.X.X") where 0.X.X is the latest version.

The current development version is: 0.8.1

Additional functions that are only available in the latest development version:

Implemented functions Description