Preprocess all available Gazepoint channels — preprocess_gazepoint

Runs a conservative, beginner-friendly preprocessing sequence over a Gazepoint data frame or imported session list. Available channels are detected heuristically. Missing numeric signal gaps can be imputed, pupil blinks cleaned, and gaze samples filtered when the relevant functions and columns are available.

Usage

preprocess_gazepoint_all(
  data,
  impute_missing = TRUE,
  clean_pupil = TRUE,
  filter_gaze = TRUE,
  max_gap = 10,
  screen_bounds = c(0, 1, 0, 1),
  max_velocity = Inf,
  verbose = TRUE
)

Arguments

data: Data frame or list of data frames.
impute_missing: If TRUE, impute short missing gaps in numeric columns.
clean_pupil: If TRUE, clean detected pupil columns.
filter_gaze: If TRUE, filter detected gaze coordinates.
max_gap: Maximum gap length in samples for imputation.
screen_bounds: Screen bounds for gaze filtering.
max_velocity: Maximum gaze velocity for gaze filtering.
verbose: If TRUE, print a compact preprocessing log.

Value

A preprocessed object of the same basic structure as data, with a preprocessing_log attribute.

Examples

dat <- data.frame(time_s = 1:5, GSR = c(1, NA, 3, 4, 5))
preprocess_gazepoint_all(dat)
#>   table           step  status
#> 1  data impute_missing      ok
#> 2  data    clean_pupil skipped
#> 3  data    filter_gaze skipped
#>                                             message
#> 1                                      Columns: GSR
#> 2          No pupil columns or cleaner unavailable.
#> 3 No gaze coordinate columns or filter unavailable.
#>   time_s GSR GSR_was_imputed
#> 1      1   1           FALSE
#> 2      2   2            TRUE
#> 3      3   3           FALSE
#> 4      4   4           FALSE
#> 5      5   5           FALSE