William,
the check does not apply to binary installations (such as the Mac builds),
because those depend heavily on the static libraries included in the package
binary which can be quite big and generally cannot be reduced in size - for
example:
https://www.r-project.org/nosvn/R.check/r-release
Dear fellow developers,
Is there an easy way to determine how big my packages (psych and psychTools)
will be on various versions of CRAN?
I have been running into the dread 'you are bigger than 5 MB" message for some
installations of R on CRAN but not others. The particular problem seems to
>
> We have one in vctrs but it's not exported:
> https://github.com/r-lib/vctrs/blob/main/src/hash.c
>
> The main use is vectorised hashing:
>
Thanks for showing me this function. I have read the source code. That's a
great idea.
However, I think I might have missed something. When I trie
Hi All,
Figured I'd put my two cents in here as the welch-lab's LIGER package
currently uses mann-whitney on datasets much larger than m = 200. Our
current version uses a modified PRESTO
(https://github.com/immunogenomics/presto) implementation over the
inbuilt tests because of the lack of sc
Hi everyone,
I’ve opened a Bugzilla report for Andreas with the most recent implementation
here: https://bugs.r-project.org/show_bug.cgi?id=18655. Feedback would be
greatly appreciated.
The most straight forward approach is likely to implement both methods and
determine which to use based on
On Friday, January 12th, 2024 at 16:11, Ivan Krylov wrote:
> unlike `which`, `command -v` returns names of shell builtins if
> something is both an executable and a builtin. So for things like `[`,
> Sys.which would behave differently if changed to use command -v
Then can we revisit my simple fi
>
>
> Performance statistics are interesting. If we assume the two populations
> have a total of `m` members, then this implementation runs slightly slower
> for m < 20, and much slower for 50 < m < 100. However, this implementation
> works significantly *faster* for m > 200. The breakpoint is prec
> I think one could implement hashing on the fly without any
> serialization, similarly to how identical works, but I am not aware of
> any existing implementation
We have one in vctrs but it's not exported:
https://github.com/r-lib/vctrs/blob/main/src/hash.c
The main use is vectorised hashing:
On 1/16/24 20:16, Dipterix Wang wrote:
Could you recommend any packages/functions that compute hash such that
the source references and sexpinfo_struct are ignored? Basically a
version of `serialize` that convert R objects to raw without storing
the ancillary source reference and sexpinfo.
I th
