pyavs.load_and_enrich_eye_events

pyavs.load_and_enrich_eye_events(subjects: List[int], sessions: List[int], data_path: str | None = None, output_prefix: str = 'as', preprocessed: bool = True, fix_multi_saccades: bool = True, verbose: bool = True, include_fixation_zero: bool = False, offset_scene_triggers_ms: int = 20, add_event_sequence_positions: bool = True, add_pupil_dilation: bool = False, **kwargs) → Tuple[DataFrame, DataFrame][source]

Load and enrich eye tracking events for multiple subjects/sessions.

This function combines fixation events from all subjects into one dataframe and enriches it with: - Trial, block, and scene ID information - Scene vs caption task recording type - Timing information relative to trial onset - Fixation sequence positions

Parameters:

  • subjects (list of int) – List of subject IDs to include

  • sessions (list of int) – List of session numbers to include

  • data_path (str, optional) – Path to data directory. If None, uses configured data path

  • output_prefix (str, optional) – Output file prefix (default: ‘as’)

  • preprocessed (bool, optional) – Whether to load preprocessed data (default: True)

  • fix_multi_saccades (bool, optional) – Whether to fix multi-saccade artifacts (default: True)

  • verbose (bool, optional) – Whether to print progress information (default: True)

  • include_fixation_zero (bool, optional) – Whether to include fixations that partially overlap with fixation cross (default: False)

  • offset_scene_triggers_ms (int, optional) – Offset to fix scene trigger delay in milliseconds (default: 20)

  • add_pupil_dilation (bool, optional) – Whether to compute and add pa_mean and pa_sd per fixation from cleaned samples (default: False). Requires cleaned_samples file to be present.

Returns:

(experiment_log_df, events_df) - Combined experiment log and events dataframes

Return type:

tuple