Temporal process windows and AOI trajectories

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Windowed process representations

extract_process_windows() converts sample-level gaze/pupil streams into a standardized participant x trial x time-window representation while retaining the window specification as provenance.

ws <- process_window_spec(width_ms = 1000, step_ms = 500,
                          start_ms = 0, end_ms = 3000)

w <- extract_process_windows(
  samples,
  person = "person_id", trial = "trial_id", time = "time_ms",
  spec = ws,
  pupil = "pupil_bc", gaze_x = "x", gaze_y = "y", aoi = "aoi"
)

validate_process_windows(w)
summarize_process_windows(w)

A sensitivity audit helps detect results driven by arbitrary window choices.

wsens <- audit_process_window_sensitivity(
  samples,
  widths_ms = c(250, 500, 1000, 1500),
  steps_ms = c(100, 250, 500),
  metric = "pupil_mean",
  person = "person_id", trial = "trial_id", time = "time_ms"
)
plot(wsens)

AOI trajectory features

traj <- aoi_trajectory_features(
  samples,
  person = "person_id", trial = "trial_id", time = "time_ms", aoi = "aoi",
  bin_ms = 100, degree = 3
)
plot(traj)

Linear/quadratic/cubic coefficients summarize temporal shape; they are not causal or latent-strategy parameters by themselves.

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.