combine_eyes

Combines the data from binocular samples into X/Y coordinate pairs. Two
methods can be used: "average" or "best_eye". For "average", the result is based on the average of the two eyes for each sample,
or for samples where there is data from only a single eye, that eye is used. For "best_eye", a summary of the proportion of missing samples
is computed, and the eye with the fewest missing samples is used.

Enables the automation of actions across the pipeline, including
initial steps of transforming binocular data and gap repair to event-based
processing such as fixations, saccades, and entry/duration in Areas of
Interest (AOIs). It also offers visualisation of eye movement and AOI
entries. These tools take relatively raw (trial, time, x, and y form) data
and can be used to return fixations, saccades, and AOI entries and time spent
in AOIs. As the tools rely on this basic data format, the functions can work
with data from any eye tracking device. Implements fixation and saccade
detection using methods proposed by Salvucci and Goldberg (2000)
<doi:10.1145/355017.355028>.

Tom Beesley

eyetools

Analyse Eye Data

Matthew Ivory

combine_eyes function

<dl><dt>data</dt>
<dd>raw data with columns time, left_x, left_y, right_x, right_y, and trial</dd>
<dt>method</dt>
<dd>either "average" or "best_eye" - see description.</dd></dl>

Arguments

Combine binocular data into single X/Y coordinate pairs — combine_eyes

<dl>

<dt>data</dt>
<dd>raw data with columns time, left_x, left_y, right_x, right_y, and trial</dd>


<dt>method</dt>
<dd>either "average" or "best_eye" - see description.</dd>

</dl>

combine_eyes: Combine binocular data into single X/Y coordinate pairs

Description

Usage

Value

Arguments

Examples