pad_gaps: Pad gaps
In WillemSleegers/eyepatch:

pad_gaps removes pupil size measurements that border gaps in the data.

pad_gaps(
  pupil,
  time,
  gap_minimum = 75,
  padding = 50,
  padding_before = NULL,
  padding_after = NULL
)

`pupil`	A numeric vector of pupil size measurements.
`time`	A vector containing the timestamps associated with the pupil size measurements.
`gap_minimum`	A numeric value describing the minimum gap duration.
`padding`	A numeric value describing by how much gaps should be padded.
`padding_before`	A numeric value describing by how much gaps should be padded before a gap.
`padding_after`	A numeric value describing by how much gaps should be padded after a gap.

# Load the "dplyr", "tidyr", and "ggplot2" packages:
library(dplyr)
library(tidyr)
library(ggplot2)

# Example 1: Artificial data
# Create some artificial data:
data <- tibble(
  time = 1:8,
  pupil_left = c(3.11, 3.13, 3.16, NA, NA, NA, 3.16, 3.12),
  pupil_right = c(2.92, 2.95, 2.98, NA, NA, NA, 2.97, 2.95)
)
data

# Pad gaps of the left eye:
mutate(data,
  pupil_left = pad_gaps(pupil_left, time, gap_minimum = 1, padding = 1)
)

# Example 2: Realistic data
gaps

# Pad gaps of the left eye:
gaps <- mutate(gaps,
  pupil_left_new = pad_gaps(pupil_left, timestamp, gap_minimum = 10,
    padding = 4)
  )

# Restructure the data and plot the results to compare the pupil measurements
# before and after padding the gaps:
gaps %>%
  rename(pupil_left_old = pupil_left) %>%
  pivot_longer(
    cols = c(pupil_left_old, pupil_left_new),
    names_to = "status",
    names_pattern = "(old|new)",
    values_to = "pupil_size"
 ) %>%
 ggplot(aes(x = timestamp, y = pupil_size, color = status)) +
   geom_point()