cat_lines1: Categorize fixations into appropriate text lines
In davebraze/FDBeye: Functions to Ease Work with Eyetracker Data

cat_lines1

R Documentation

Categorize fixations into appropriate text lines

Description

This function follows closely upon that described in Cohen's paper

Usage

cat_lines1(params, fit_it = TRUE, data, start_pts, k_bounds, o_bounds,
  s_bounds, den_sd_cutoff, den_ratio_cutoff, num_checkFirst = 5,
  num_checkLast = 10)

Arguments

`params`	A vector of parameters for optimization, the three values in it refer to slope, offset, and sd
`fit_it`	A bollean variable; if it is TRUE, the function will return fit measure; if it is FALSE, the function will return fit information
`data`	A data.frame storing the fixation data including at least the x_pos and y_pos of each fixation
`start_pts`	A data.frame containing the starting position of each text line. It has three columns: x_pos: x position of the first word in each text line. y_pos: y position of the first word in each text line. trial_num: the trial number of the current start_pts
`k_bounds`	A list containing the lower and upper boundaries of slope; default value is [-0.1, 0.1]
`o_bounds`	A list containing the lower and upper boundaries of offset; defaul value is [-0.5dist of adjacent text lines, 0.5dist of adjacent text line])
`s_bounds`	A list containing the lower and upper boundaries of sd; default value is [1, 20]
`den_sd_cutoff`	A float variable for cutoff threshold for density; If it is Inf, use mean(inv_dnorm(exp(data_den_max))) + 3*sd(inv_dnorm(exp(data_den_max))) as cutoff (99.7% are accepted)
`den_ratio_cutoff`	A float variable for cutoff threshold for density ratio (ratio between the maximum density and second maximum density)
`num_checkFirst`	An integer denoting the number of starting fixations used for checking start-reading bound; default value is 5
`num_checkLast`	An integer denoting the number of ending fixations used for checking end-reading bound; default value is 10

Details

This function optimizes the slope, offset and sd for all lines of fixations. It uses -sum(data_den_max) as fit measure for optimization.

Value

A data.frame including fixation data, and fitting data including fit measures and fitted lines information. It adds the following columns:

line: Text line that each fixation belongs to
y_line: y position of the text line that each fixation is assigned to
y_res: Residualized y position of each fixation y_line + y_res will give the original y position of each fixation
slope: Optimized slope value for all fitted lines
offset: Optimizaed offset value for all fitted lines
sd: Optimized sd value for all fitted lines
fit_den: fitted density value
fit_y_diff: fitted y difference (accumulated y differences between each fixation and the fitted line)