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)