Yes, you have misunderstood what memoise is for.
First, it is for when you call your function with the same inputs frequently as
part of your calling-level algorithm. For your iterative calculation you would
have a stuck (cycling) process if the same value of current were to be
revisited... ever.
Second, it is for when your nextstep function is very slow to compute, since
the memoisation process is non-trivial... certainly it takes much more work to
keep the previous results around than your example nextstep algorithm would
take to simply recompute the answer.
On November 15, 2018 4:44:05 AM PST, "Martin Møller Skarbiniks Pedersen"
<traxpla...@gmail.com> wrote:
>Hi,
>
> I want to compute a lot of values and I have tried to use
>memoise::memoise to speed-up the computation.
> However it is much slower using the memoised version.
>
>I guess I have misunderstood how to use the package memoise or the
>purpose of the package.
>
>The code takes more than 2 minutes to finish but if I remove the line:
>"nextstep <- memoise(nextstep)" the code runs in less than 1 second. I
>was expecting a
>total different result.
>
>Here are the code:
>
>library(memoise)
>
>nextstep <- function(num) {
> if (num %% 2 == 0) {
> return(num/2)
> }
> num*3+1
>}
>
>nextstep <- memoise(nextstep)
>
>for (idx in 1:1e4) {
> steps <- 0
> current <- idx
> while (current != 1) {
> steps <- steps + 1
> current <- nextstep(current)
> }
> cat(idx,steps,"\n")
>}
>
>
>Regards
>Martin
>
>______________________________________________
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--
Sent from my phone. Please excuse my brevity.
______________________________________________
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