cat_lines2: Categorize fixations into appropriate text lines
In davebraze/FDBeye: Functions to Ease Work with Eyetracker Data

cat_lines2

R Documentation

Categorize fixations into appropriate text lines

Description

Function to optimize slope, offset and sd for all lines of fixations (extended from original paper)This function uses one slope, offset, sd to fit all lines, and use sum(min y_diff) as target measure for optimization uses.

Usage

cat_lines2(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(min(y_diff)) 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)