I decided to do a direct comparison of transpose and sweep.
library(microbenchmark)
NN <- matrix(c(1, 2, 3, 4, 5, 6), nrow = 2, byrow = TRUE) # Example matrix
lambda <- c(2, 3, 4) # Example vector
colNN <- t(NN)
microbenchmark(
sweep = sweep(NN, 2, lambda, "/"),
transpose = t(t(NN)/lambda),
colNN = colNN/lambda
)
Unit: nanoseconds
expr min lq mean median uq max neval cld
sweep 13817 14145 15115.06 14350 14657.5 75932 100 a
transpose 1845 1927 2151.68 2132 2214.0 7093 100 b
colNN 82 123 141.86 123 164.0 492 100 c
Note that transpose is much faster than sweep because it is doing less work,
I believe essentially just changing the order of indexing.
Using the natural sequencing for column-ordered matrices is much much faster.
> On Feb 28, 2024, at 18:43, peter dalgaard <pda...@gmail.com> wrote:
>
>> rbind(1:3,4:6)/t(matrix(c(2,3,4), 3,2))
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