Merge data frames by time interval in R - r

Question

I have two Data Frames. One is an Eye Tracking data frame with subject, condition, timestamp, xposition, and yposition. It has over 400,000 rows. Here's a toy data set for an example:
subid condition time xpos ypos
1 1 1 1.40 195 140
2 1 1 2.50 138 147
3 1 1 3.40 140 162
4 1 1 4.10 188 150
5 1 2 1.10 131 194
6 1 2 2.10 149 111
eyedata <- data.frame(subid = rep(1:2, each = 8),
condition = rep(rep(1:2, each = 4),2),
time = c(1.4, 2.5, 3.4, 4.1,
1.1, 2.1, 3.23, 4.44,
1.33, 2.3, 3.11, 4.1,
.49, 1.99, 3.01, 4.2),
xpos = round(runif(n = 16, min = 100, max = 200)),
ypos = round(runif(n = 16, min = 100, max = 200)))
Then I have a Data Frame with subject, condition, a trial number, and a trial begin and end time. It looks like this:
subid condition trial begin end
1 1 1 1 1.40 2.4
2 1 1 2 2.50 3.2
3 1 1 2 3.21 4.5
4 1 2 1 1.10 1.6
5 1 2 2 2.10 3.3
6 1 2 2 3.40 4.1
7 2 1 1 0.50 1.1
8 2 1 1 1.44 2.9
9 2 1 2 2.97 3.3
10 2 2 1 0.35 1.9
11 2 2 1 2.12 4.5
12 2 2 2 3.20 6.3
trials <- data.frame(subid = rep(1:2, each = 6),
condition = rep(rep(1:2, each = 3),2),
trial= c(rep(c(1,rep(2,2)),2),rep(c(rep(1,2),2),2)),
begin = c(1.4, 2.5, 3.21,
1.10, 2.10, 3.4, .50,
1.44,2.97,.35,2.12,3.20),
end = c(2.4,3.2,4.5,1.6,
3.3,4.1,1.1,2.9,
3.3,1.9,4.5,6.3))
The number of trials in a condition are variable, and I want to add a column to my eyetracking dataframe that specifies the correct trial based upon whether the timestamp falls within the time interval. The time intervals do not overlap, but there will be many rows for the eyetracking data in between trials. In the end I'd like a dataframe like this:
subid condition trial time xpos ypos
1 1 1 1.40 198 106
1 1 2 2.50 166 139
1 1 2 3.40 162 120
1 1 2 4.10 113 164
1 2 1 1.10 162 120
1 2 2 2.10 162 120
I've seen data.table rolling joins, but would prefer a solution with dplyr or fuzzyjoin. Thanks in advance.

Answer 1

Here's what I tried, but I can't figure the discrepancies, so it is likely an incomplete answer. Row 12,13 of this result may be an overlap in time. Also, when using random generation functions such as runif please set.seed -- here xpos and ypos have no bearing on the result, so not an issue.
eyedata %>%
left_join(trials, by = c("subid", "condition")) %>%
filter( (time >= begin & time <= end))
# subid condition time xpos ypos trial begin end
# 1 1 1 1.40 143 101 1 1.40 2.4
# 2 1 1 2.50 152 173 2 2.50 3.2
# 3 1 1 3.40 185 172 2 3.21 4.5
# 4 1 1 4.10 106 119 2 3.21 4.5
# 5 1 2 1.10 155 165 1 1.10 1.6
# 6 1 2 2.10 169 154 2 2.10 3.3
# 7 1 2 3.23 166 134 2 2.10 3.3
# 8 2 1 2.30 197 171 1 1.44 2.9
# 9 2 1 3.11 140 135 2 2.97 3.3
# 10 2 2 0.49 176 139 1 0.35 1.9
# 11 2 2 3.01 187 180 1 2.12 4.5
# 12 2 2 4.20 147 176 1 2.12 4.5
# 13 2 2 4.20 147 176 2 3.20 6.3