plot_filter_results: Plot validity measures from one or more fixation detection...

In kollaR: Filtering, Visualization and Analysis of Eye Tracking Data

Plot validity measures from one or more fixation detection algorithms

Description

This function visualizes validity measures of fixations detected with one or more fixation detection algorithms. The function is tested for fixation data frames generated with kollaR event detection algorithms. By default, the function can plot Root Mean Square Deviations of detected fixations, fixation duration and the proportion of missing raw samples. The output data is a ggplot which can be modified further outside the function. If you want to use this function to compare more than one fixation detection algorithms, combine them using the function rbind in base R. For example, rbind(my_data1[["fixations"]], my_data2[["fixations"]]) would generate a combined data frame with the fixations detected by two event classification procedures.

Usage

plot_filter_results(data_in, plot.variable = "rmsd")

Arguments

data_in	Data frame with fixations to plot
plot.variable	Variable to plot. If left empty, RMSD of fixations are plotted. Alternatives are "rmsd", "duration", "missing.samples"

Value

A ggplot with visualizations of the selected validity measure

Examples

plot_filter_results(data_in = sample.data.fixations, plot.variable = "rmsd")

kollaR documentation built on April 13, 2025, 5:11 p.m.