Prepare Gazepoint events for MNE-Python — prepare_gazepoint_mne

Creates an integer MNE-style event matrix with columns representing sample number, previous value, and event code. Input may be an event table, numeric event-time vector, or continuous table containing marker columns.

Usage

prepare_gazepoint_mne_events(
  events,
  event_time_col = NULL,
  event_label_col = NULL,
  event_code_col = NULL,
  marker_cols = NULL,
  participant_col = NULL,
  trial_col = NULL,
  time_unit = c("auto", "seconds", "milliseconds", "samples"),
  sampling_rate_hz,
  recording_start_s = 0,
  first_samp = 0L,
  event_id = NULL,
  previous_value = 0L,
  marker_onset = c("change", "nonzero"),
  duplicate = c("error", "allow"),
  export_csv = NULL
)

Arguments

events: Numeric event-time vector or data frame.
event_time_col: Event-time column for event-table input.
event_label_col: Optional event-label column.
event_code_col: Optional positive integer event-code column.
marker_cols: Optional marker or TTL columns in continuous input.
participant_col: Optional participant column retained in the audit.
trial_col: Optional trial column retained in the audit.
time_unit: Time unit: "auto", "seconds", "milliseconds", or "samples".
sampling_rate_hz: Positive sampling frequency used to convert event times to MNE sample numbers.
recording_start_s: Recording start in seconds in the same clock domain as the converted event times.
first_samp: Integer MNE first-sample offset.
event_id: Optional named integer event dictionary or data frame with event_label and event_code.
previous_value: Integer previous-event value placed in the second event-matrix column.
marker_onset: Whether marker input creates events only on value changes or for every non-zero row.
duplicate: Handling of repeated event sample numbers.
export_csv: Optional path for a headerless three-column event file.

Value

A "gazepoint_mne_events" object containing the event matrix, event table, event dictionary, audit, and settings.