Ttdfjt

I have a vector of TRUEs and FALSEs:

x <- c(F,F,F,T,T,T,F,F,F,T,T,T,F,T,T)

I'd like to elegantly (and in base) identify the position of the last TRUE before it changes to FALSE.

The following works, though, it seems like it could be simplified:

c((x[-1] != x[-length(x)]),T) & x
> FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE

Input and output:

We may look where x is greater than shifted x with 0 appended.

x>c(x[-1],0)
# [1] FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE

Taking advantage of diff with an appended FALSE to catch the implied TRUE-to-FALSE at the end.

diff(c(x,FALSE)) == -1
# [1] FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE
#[13] FALSE FALSE TRUE

Check rle

rlex = rle(x)
end = cumsum(rlex$lengths)
x&(seq(length(x)) %in% end)
[1] FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE

Another layout suggested by Frank

seq_along(x) %in% with(rle(x), cumsum(lengths)[values])
[1] FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE

Another version with rle

x[setdiff(seq_along(x), with(rle(x), cumsum(lengths) * values))] <- FALSE
x
#[1] FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE

An option with duplicated

library(data.table)
!duplicated(rleid(x), fromLast = TRUE) & x
#[1] FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE

benchmarks

Thanks for all the solutions. If anyone is interested in benchmarks:

library(dplyr)
library(data.table)

set.seed(1)
x <- sample(c(TRUE, FALSE), 1000000, replace = T)
y <- data.frame(x = x) # For M. Viking's solution
x_dt <- x # For Ronak Shah's solution

microbenchmark::microbenchmark(Khaynes = Khaynes <- c((x[-1] != x[-length(x)]),T) & x,
 jay.sf = jay.sf <- x>c(x[-1],0),
 jay.sf_2 = jay.sf_2 <- diff(c(x,0))<0,
 thelatemail = thelatemail <- diff(c(x,FALSE)) == -1, 
 WeNYoBen = rlex = rle(x); end = cumsum(rlex$lengths); WeNYoBen <- x&(seq(length(x)) %in% end), 
 M._Viking = M._Viking <- y %>% mutate(lasttrue = case_when(x > lead(x) ~ T, T ~ F)), 
 akrun = akrun <- !duplicated(rleid(x), fromLast = TRUE) & x,
 frank = frank <- seq_along(x) %in% with(rle(x), cumsum(lengths)[values]), 
 Ronak_Shah = x_dt[setdiff(seq_along(x_dt), with(rle(x_dt), cumsum(lengths) * values))] <- FALSE,
 times = 50)
# Output:
 # Unit: milliseconds
 # expr min lq mean median uq max neval
 # Khaynes 23.0283 26.5010 31.76180 31.71290 37.1449 46.3824 50
 # jay.sf 13.0630 13.5373 17.84056 13.77135 20.5462 73.5926 50
 # jay.sf_2 26.1960 27.7653 35.25296 36.39615 39.3686 61.8858 50
 # thelatemail 24.8204 26.7178 32.51675 33.50165 36.6328 41.9279 50
 # WeNYoBen 83.9070 98.4700 107.79965 101.88475 107.1933 170.2940 50
 # M._Viking 73.5963 83.4467 93.99603 86.58535 94.0915 151.7075 50
 # akrun 42.5265 43.2879 48.42697 44.98085 51.1533 105.2836 50
 # frank 81.9115 90.1559 95.40261 93.97015 98.2921 129.6162 50
 # Ronak_Shah 109.0678 121.8230 133.10690 125.63930 133.7222 231.5350 50

all.equal(Khaynes, jay.sf)
all.equal(Khaynes, jay.sf_2)
all.equal(Khaynes, thelatemail)
all.equal(Khaynes, WeNYoBen)
all.equal(Khaynes, M._Viking$lasttrue) # When the last element is TRUE it will return false.
all.equal(Khaynes, akrun)
all.equal(Khaynes, frank)
all.equal(Khaynes, x_dt) # Ronak Shah solution.

Non-base solution for identifying the last TRUE before a FALSE.

 library(dplyr)

 y <- data.frame(x = c(FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,
 FALSE,TRUE,TRUE,TRUE,FALSE,TRUE,TRUE))

 y %>% 
 mutate(lasttrue = case_when(x == TRUE & lead(x) == FALSE ~ TRUE,
 TRUE ~ FALSE))

Edit:

y %>% 
 mutate(lasttrue = case_when(x > lead(x) ~ T,
 T ~ F))