add grouping number based on consecutive TRUE/FALSE column values - r

Question

Given this data frame:
library(dplyr)
dat <- data.frame(
bar = c(letters[1:10]),
foo = c(1,2,3,5,8,9,11,13,14,15)
)
bar foo
1 a 1
2 b 2
3 c 3
4 d 5
5 e 8
6 f 9
7 g 11
8 h 13
9 i 14
10 j 15
I first want to identify groups, if the foo number is consecutive:
dat <- dat %>% mutate(in_cluster =
ifelse( lead(foo) == foo +1 | lag(foo) == foo -1,
TRUE,
FALSE))
Which leads to the following data frame:
bar foo in_cluster
1 a 1 TRUE
2 b 2 TRUE
3 c 3 TRUE
4 d 5 FALSE
5 e 8 TRUE
6 f 9 TRUE
7 g 11 FALSE
8 h 13 TRUE
9 i 14 TRUE
10 j 15 TRUE
As can be seen, the values 1,2,3 form a group, then value 5 is on it's own and does not belong to a cluster, then values 8,9 form another cluster and so on.
I would like to add cluster numbers to these "groups".
Expected output:
bar foo in_cluster cluster_number
1 a 1 TRUE 1
2 b 2 TRUE 1
3 c 3 TRUE 1
4 d 5 FALSE NA
5 e 8 TRUE 2
6 f 9 TRUE 2
7 g 11 FALSE NA
8 h 13 TRUE 3
9 i 14 TRUE 3
10 j 15 TRUE 3

Answer 1

There is probably a better tidverse approach for something like this. For example, group_indices could be used if in_cluster is defined through an arbitrary length case_when. However, we can also implement our own method to specifically deal with logical value run lengths, using the rle function.
solution 1 (R version > 3.5)
lgl_indices <- function(var){
x <- rle(var)
cumsum(x[[2]]) |> (\(.){ .[which(!x[[2]], T)] <- NA ; .})() |> rep(x[[1]])
}
solution 2
lgl_indices <- function(var){
x <- rle(var)
y <- cumsum(x$values)
y[which(x$values == F)] <- NA
rep(y, x$lengths)
}
solution 3
lgl_indices <- function(var){
x <- rle(var)
l <- vector("list", length(x))
n <- 1L
for (i in seq_along(x[[1]])) {
if(!x$values[i]) grp <- NA else {
grp <- n
n <- n + 1L
}
l[[i]] <- rep(grp, x$lengths[i])
}
Reduce(c, l)
}
dat %>%
mutate(cluster_number = lgl_indices(in_cluster))
bar foo in_cluster cluster_number
1 a 1 TRUE 1
2 b 2 TRUE 1
3 c 3 TRUE 1
4 d 5 FALSE NA
5 e 8 TRUE 2
6 f 9 TRUE 2

Answer 2

This may not be the efficient way. Still, this works:
# Cumuative sum of the logical
dat$new_cluster <- cumsum(!dat$in_cluster)+1
# using the in_cluster to subset and replacing the cluster number for FALSE by NA
dat[!dat$in_cluster,]$new_cluster <- NA
dat
bar foo in_cluster new_cluster
1 a 1 TRUE 1
2 b 2 TRUE 1
3 c 3 TRUE 1
4 d 5 FALSE NA
5 e 8 TRUE 2
6 f 9 TRUE 2