knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
When preprocessing .asc
EyeLink files with eyeris
, returned objects will be
of the class eyeris
, and will contain key components used throughout the
package's backend.
The key components are:
file
: the original file path of the source .asc
filetimeseries
: a list of data frames (1 df per identified recording block per file) which contains the following columns:block
: block numbertime_orig
: raw tracker time (ms)eye_x
: eye position x-coordinateeye_y
: eye position y-coordinateeye
: which eye (Left or Right) the recorded data are sourced fromhz
: tracker sampling rate (hz)type
: whether source data were recorded using the diameter
or area
methodpupil_raw
: raw recorded pupil source data in arbitrary units (a.u.) You'll notice that for each preprocessing step run, a new column will be added after
the pupil_raw
column; these new columns follow a structure where each subsequent
step is appended to the previous columns name
(i.e., pupil_raw_{previous steps}_{current_step}
). To illustrate:
pupil_raw
-> pupil_raw_deblink
-> pupil_raw_deblink_detransient
-> and so on...
events
: a list of data frames containing trial event messages and timestamps
blinks
: a list of data frames containing start/stop/durations for blinksinfo
: EyeLink EDF header data parsed into a data framelatest
: internal tracker used for assessing which steps have been run so farparams
: detailed list of steps run and parameters passed to each stepepoch_{name}
: list of data frames for any given epoched timeseriesNow that we've explained what you can expect to see after running the eyeris
glassbox()
function, we'll demonstrate what the glassbox()
wrapper is
generally comprised of in terms of the steps and defaults that are implemented.
While we strongly recommend against manually constructing the pipeline as will
be shown below (given that using the glassbox()
will provide maximum
opportunities for reproducibility and reduction of accidental errors), more
advanced users may want to see how the individual steps can be used like
building blocks to iteratively test out parameters, switch steps around / remove
steps
(again, we strongly recommend against doing this unless you know what
you're doing), etc.
glassbox()
Steps and Parameters, Deconstructed:system.file("extdata", "memory.asc", package = "eyeris") |> eyeris::load_asc(block = "auto") |> eyeris::deblink(extend = 50) |> eyeris::detransient(n = 16) |> eyeris::interpolate() |> eyeris::lpfilt(wp = 4, ws = 8, rp = 1, rs = 35, plot_freqz = TRUE) |> eyeris::zscore()
eyeris
citation("eyeris")
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.