
Gazepoint and Gazepoint Biometrics Workflows
Source:vignettes/gazepoint-workflows.Rmd
gazepoint-workflows.RmdGazepoint is a first-class source while the downstream representation remains vendor-neutral.
Profile before import
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")Folder import
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)Separate biometrics and synchronization
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 paired exports
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.