knitr::opts_chunk$set(collapse = TRUE, comment = "#>", eval = FALSE)
Gazepoint is a first-class source while the downstream representation remains vendor-neutral.
gp_profile_export("data/P001") gp_audit_file_pairs("data/P001") gp_list_export_fields("data/P001/P001-user.csv") gp_validate_export("data/P001")
x <- read_gazepoint_folder( "data/P001", include = c("gaze", "fixations", "events", "biometrics", "aoi"), participant_id = "P001" ) x <- gp_reconstruct_trials( x, start_events = c("TRIAL_START", "START_TRIAL"), end_events = c("TRIAL_END", "END_TRIAL") ) x <- gp_reconstruct_stimuli(x) x <- gp_align_media_ids(x)
gp_check_sampling_rate(x) gp_check_validity_fields(x) gp_check_fixation_ids(x) gp_check_media_timing(x) gp_check_pupil_channels(x) gp_check_biometrics_sync(x)
gaze <- read_gazepoint_gaze("P001-user.csv") bio <- read_gazepoint_biometrics("P001-biometrics.csv") # Marker times may be extracted from each object's event table. source_markers <- bio$events$timestamp_seconds[bio$events$event_name == "SYNC"] target_markers <- gaze$events$timestamp_seconds[gaze$events$event_name == "SYNC"] x <- synchronize_eye_biometrics( gaze, bio, source_markers = source_markers, target_markers = target_markers, method = "linear" )
Different native sampling rates and clocks are preserved. Alignment parameters are recorded in provenance rather than hidden by automatic resampling.
Gazepoint Analysis 7.2.0 may export files named User 3_all_gaze.csv and
User 3_fixations.csv, together with multi-section
Data_Summary_export_*.csv reports. The folder importer pairs these files by
their User N stem:
root <- "C:/path/to/gazepoint-export-folder" gp_pair_exports(root) x <- read_gazepoint_folder(root)
The sample export contains two clocks with different meanings. The
TIMETICK(f=10000000) field remains monotonic across the full recording and is
used to create zero-based timestamp_seconds. The TIME(...) field restarts
when the media item changes and is retained as media_time_seconds. Neither
clock is silently discarded.
Fixation identifiers restart for each media item in these exports. Therefore,
eyeprocess constructs canonical episode identifiers from the recording,
media, and source fixation identifier. The original identifier remains in
source_fixation_id.
summary <- read_gazepoint_summary( file.path(root, "Data_Summary_export_02-20-26-01.28.43.csv") ) summary aoi_data <- read_gazepoint_aoi_statistics(summary$path)
The Data Summary parser retains both its aggregate AOI table and its per-user AOI statistics. Canonical AOI definitions and participant-AOI features are created without inventing spatial geometry that is absent from the report.
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