fixations_to_timeseries: Convert a dataframe of fixation intervals to an evenly spaced...

In BergelsonLab/blabr: a toolbox for working in the BLAB

Convert a dataframe of fixation intervals to an evenly spaced timeseries

Description

• The fixations are first dropped/trimmed if t_max is set.

• The fixation interval boundaries are then rounded up to the nearest multiples of t_step.

• Each fixation row is then duplicated as many time as there are time points (also multiples of t_step) falling within the rounded up intervals. The timepoins are stored in a new column time.

• If a timepoint falls within multiple fixations, only the row with the later fixation is kept.

• If a timepoint doesn't fall within any fixations in a given trial, it won't appear in the output at all.

Usage

fixations_to_timeseries(fixations, t_step = 20, t_max = NULL)

Arguments

fixations	A dataframe that must minimally contain the following columns: recording_id and trial_index that uniquely identify trials. t_start, t_end - the start and end times of the fixations in ms. Use ⁠read_*_report⁠, ⁠split_*_report⁠, and merge_split_reports to get such a dataframe.
t_step	The time step in ms.
t_max	Optional. The maximum time in ms. Fixations that start after this time will be removed and the end time of fixations that end after this time will be set to this time.

Value

A dataframe with similar columns as the input dataframe but with many more rows. Here are the differences in columns:0

• A new column time was added that contains the time points that are multiples of t_step and are within the fixation interval after it was rounded up to the nearest multiple of t_step.

• The t_start and t_end columns were renamed to fixation_start and fixation_end.

• Some fixations may have been dropped if they started after t_max or if they were all in one time bin and it was shared with another fixation.

Examples

fixations <- data.frame(
  recording_id = seq(1, 3),
  trial_index = seq(1, 3),
  t_start = c(105, 202, 256),
  t_end = c(155, 241, 560),
  x = c(0, -50, 50),
  y = rep(0, 3))
t_step <- 20
t_max <- 400
fixations_to_timeseries(fixations, t_step, t_max)

BergelsonLab/blabr documentation built on Dec. 22, 2024, 9:32 p.m.