compare_algorithms: A battery of metrics and plots to compare the two algorithms...

In tombeesley/eyetools: Analyse Eye Data

A battery of metrics and plots to compare the two algorithms (dispersion and VTI)

Description

A tool for comparing the two different algorithms present in this package. This function is useful for assessing the data as well as exploring which algorithm is likely to fit data more appropriately. The raw data is run through both algorithms (using the same specified dispersion tolerances, etc.) before making comparisons of the underlying data. Can only be used for single participant data.

Usage

compare_algorithms(
  data,
  plot_fixations = TRUE,
  print_summary = TRUE,
  sample_rate = NULL,
  threshold = 100,
  min_dur = 150,
  min_dur_sac = 20,
  disp_tol = 100,
  NA_tol = 0.25,
  smooth = FALSE
)

Arguments

data	A dataframe with raw data (time, x, y, trial) for one participant
plot_fixations	Whether to plot the detected fixations. default as TRUE
print_summary	Whether to print the summary table. default as TRUE
sample_rate	sample rate of the eye-tracker. If default of NULL, then it will be computed from the timestamp data and the number of samples. Supplied to the VTI algorithm
threshold	velocity threshold (degrees of VA / sec) to be used for identifying saccades. Supplied to the VTI algorithm
min_dur	Minimum duration (in milliseconds) of period over which fixations are assessed. Supplied to both algorithms.
min_dur_sac	Minimum duration (in milliseconds) for saccades to be determined. Supplied to the VTI algorithm
disp_tol	Maximum tolerance (in pixels) for the dispersion of values allowed over fixation period. Supplied to both algorithms
NA_tol	the proportion of NAs tolerated within any window of samples that is evaluated as a fixation. Supplied to the dispersion algorithm
smooth	include a call to eyetools::smoother on each trial. Supplied to the VTI algorithm

Value

a list of the fixation data, correlation output, and data used for plotting

Examples

data <- combine_eyes(HCL)
data <- interpolate(data, participant_ID = "pNum")
compare_algorithms(data[data$pNum == 119,])

tombeesley/eyetools documentation built on Dec. 23, 2024, 12:36 a.m.