Optimize threshold determination with algorithm=2

[xrobin]

Too much time is spent in roc.utils.R:60 in roc.utils.perfs.all.fast:

dups.sesp <- duplicated(matrix(c(se, sp), ncol=2), MARGIN=1)

There must be a better way to do it. Here is some benchmarking code:

n <- 1e6
dat <- data.frame(x = rnorm(n), y = sample(c(0:1), size = n, replace = TRUE))

library(profvis)
profvis({
    for (i in 1:10) {
        pROC::roc(dat$y, dat$x, algorithm = 2)
    }

})

[xrobin]

It turns out duplicated.matrix is slow. It can be replaced by two calls to duplicated.vector and a vector &.

Using the benchmarks from the cutpointr vignette, we are down to nearly the speed of ROCR, despite some remaining inefficient calls to sort, unique, duplicated and %in%.