The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

Getting Started with eyeprocess

eyeprocess harmonizes heterogeneous eye-tracking, pupil, event, response, and biometric streams without erasing their source semantics. The core object is a relational eye_dataset, not a single wide data frame.

Simulate a complete project

library(eyeprocess)

x <- simulate_eye_dataset(n_person = 20, n_item = 8, seed = 42)
x
summary(x)
validate_eye_dataset(x)
provenance_manifest(x)

Standard workflow

spec <- preprocess_spec(
  gaze_filter = "median",
  pupil_interpolation = "linear",
  pupil_filter = "median",
  fixation_algorithm = "ivt"
)

x <- preprocess_eye(x, spec)
x <- build_aoi_visits(x)
x <- derive_all_features(x)

analysis_readiness(x)
feature_dictionary(x)

Inspect and visualize

trial <- x$intervals$trial_id[1]
plot_eye_overview(x)
plot_scanpath(x, trial_id = trial)
plot_pupil_timeseries(x, trial_id = trial)
plot_transition_matrix(x)

Persist the canonical representation

write_eye_dataset(x, "analysis/eye-dataset.rds")
export_canonical(x, "analysis/canonical-folder")
report_eye_dataset(x, "analysis/eyeprocess-report.md", include_plots = TRUE)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.