Alternative to mapply to select samples

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Alternative to mapply to select samples

Chao Liu
Dear R-Help,

I created a mapply function to select samples from a dataset but are there
any faster ways to do it by avoiding mapply because it is slow and I have a
larger dataset? My goal is to use more matrix / vector operations and less
in terms of lists (the format of the output can be flexible). Ideally, I
would like to stick to base R methods without the aid of parallel process
or packages. Any ideas will be appreciated!

#A list of a set of data to be selected
bl <- list(list(c(1, 2),c(2, 3), c(3, 4), c(4, 5), c(5, 6), c(6, 7), c(7,
8), c(8, 9)),
         list(c(1, 2, 3), c(2, 3, 4), c(3, 4, 5), c(4, 5, 6), c(5, 6, 7),
c(6, 7, 8)),
         list(c(1, 2, 3, 4, 5), c(2, 3, 4, 5, 6), c(3, 4, 5, 6, 7), c(4, 5,
6, 7, 8), c(5, 6, 7, 8, 9)))
#Number of elements to be selected
kn <- c(5, 4, 3)
#Total number of elements in each set
nb <- c(8, 6, 5)
#This output a list but preferably I would like a matrix
bl_func <- function() mapply(function(x, y, z) {
  x[sample.int(y, z, replace = TRUE)]
}, bl, nb, kn, SIMPLIFY = FALSE)

Best,

Chao


        [[alternative HTML version deleted]]

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Re: Alternative to mapply to select samples

PIKAL Petr
Hi

I am not sure if I understand your function but simple mapply gives you probably the same result and may be quicker.

> set.seed(111)
> blf <- bl_func()
> set.seed(111)
> blm <- mapply(sample, bl, kn, replace=TRUE)
> all.equal(blf, blm)
[1] TRUE
 
> Cheers
Petr

> -----Original Message-----
> From: R-help <[hidden email]> On Behalf Of Chao Liu
> Sent: Tuesday, February 2, 2021 3:32 PM
> To: r-help <[hidden email]>
> Subject: [R] Alternative to mapply to select samples
>
> Dear R-Help,
>
> I created a mapply function to select samples from a dataset but are there
> any faster ways to do it by avoiding mapply because it is slow and I have a
> larger dataset? My goal is to use more matrix / vector operations and less
> in terms of lists (the format of the output can be flexible). Ideally, I
> would like to stick to base R methods without the aid of parallel process
> or packages. Any ideas will be appreciated!
>
> #A list of a set of data to be selected
> bl <- list(list(c(1, 2),c(2, 3), c(3, 4), c(4, 5), c(5, 6), c(6, 7), c(7,
> 8), c(8, 9)),
>          list(c(1, 2, 3), c(2, 3, 4), c(3, 4, 5), c(4, 5, 6), c(5, 6, 7),
> c(6, 7, 8)),
>          list(c(1, 2, 3, 4, 5), c(2, 3, 4, 5, 6), c(3, 4, 5, 6, 7), c(4, 5,
> 6, 7, 8), c(5, 6, 7, 8, 9)))
> #Number of elements to be selected
> kn <- c(5, 4, 3)
> #Total number of elements in each set
> nb <- c(8, 6, 5)
> #This output a list but preferably I would like a matrix
> bl_func <- function() mapply(function(x, y, z) {
>   x[sample.int(y, z, replace = TRUE)]
> }, bl, nb, kn, SIMPLIFY = FALSE)
>
> Best,
>
> Chao
> ᐧ
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> and provide commented, minimal, self-contained, reproducible code.

______________________________________________
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Re: Alternative to mapply to select samples

Chao Liu
Thank you for your input, Petr. I will give it a try.

Best,

Chao


On Wed, Feb 3, 2021 at 4:32 AM PIKAL Petr <[hidden email]> wrote:

> Hi
>
> I am not sure if I understand your function but simple mapply gives you
> probably the same result and may be quicker.
>
> > set.seed(111)
> > blf <- bl_func()
> > set.seed(111)
> > blm <- mapply(sample, bl, kn, replace=TRUE)
> > all.equal(blf, blm)
> [1] TRUE
>
> > Cheers
> Petr
>
> > -----Original Message-----
> > From: R-help <[hidden email]> On Behalf Of Chao Liu
> > Sent: Tuesday, February 2, 2021 3:32 PM
> > To: r-help <[hidden email]>
> > Subject: [R] Alternative to mapply to select samples
> >
> > Dear R-Help,
> >
> > I created a mapply function to select samples from a dataset but are
> there
> > any faster ways to do it by avoiding mapply because it is slow and I
> have a
> > larger dataset? My goal is to use more matrix / vector operations and
> less
> > in terms of lists (the format of the output can be flexible). Ideally, I
> > would like to stick to base R methods without the aid of parallel process
> > or packages. Any ideas will be appreciated!
> >
> > #A list of a set of data to be selected
> > bl <- list(list(c(1, 2),c(2, 3), c(3, 4), c(4, 5), c(5, 6), c(6, 7), c(7,
> > 8), c(8, 9)),
> >          list(c(1, 2, 3), c(2, 3, 4), c(3, 4, 5), c(4, 5, 6), c(5, 6, 7),
> > c(6, 7, 8)),
> >          list(c(1, 2, 3, 4, 5), c(2, 3, 4, 5, 6), c(3, 4, 5, 6, 7), c(4,
> 5,
> > 6, 7, 8), c(5, 6, 7, 8, 9)))
> > #Number of elements to be selected
> > kn <- c(5, 4, 3)
> > #Total number of elements in each set
> > nb <- c(8, 6, 5)
> > #This output a list but preferably I would like a matrix
> > bl_func <- function() mapply(function(x, y, z) {
> >   x[sample.int(y, z, replace = TRUE)]
> > }, bl, nb, kn, SIMPLIFY = FALSE)
> >
> > Best,
> >
> > Chao
> > ᐧ
> >
> >       [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-
> > guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>

        [[alternative HTML version deleted]]

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.