library(compiler)
myfun <- cmpfun(function(m, cl) {
li <- ri <- cl
nc <- ncol(m)
repeat {
li <- li - 1
if(li == 0 || ((m[1, li] != 1) && (m[1, li] + m[2, li] == 2))) {
l <- li
break
}
}
repeat {
ri <- ri + 1
if(ri == nc || ((m[1, ri] != 1) && (m[1, ri] + m[2, ri] == 2))) {
r <- ri
break
}
}
c(l, r)
})
在考虑了@Martin Morgan的意见之后,
set.seed(1)
N <- 1000000
test <- rbind(sample(0:2, N, replace = TRUE),
sample(0:2, N, replace = TRUE))
library(microbenchmark)
microbenchmark(myfun(test, N / 2), fun(test, N / 2), foo(test, N / 2),
AWebb(test, N / 2), RHertel(test, N / 2))
expr min lq mean median uq max neval cld
set.seed(123)
test <- rbind(sample(0:2, N, replace = TRUE, prob = c(5, 90, 5)),
sample(0:2, N, replace = TRUE, prob = c(5, 90, 5)))
microbenchmark(myfun(test, N / 2), fun(test, N / 2), foo(test, N / 2),
AWebb(test, N / 2), RHertel(test, N / 2))