similar to: Language definition question - order of argument side effects

My understanding is that R will not make copies of lists if there is only one reference to the object. However, I've encountered a case where R does make copies, even though (I think) there should be only one reference to the object. I hope that someone could shed some light on why this is happening. I'll start with a simple example. Below, x is a list with one element, and changing that

I've been playing with passing arguments to .C(), and found that replacing as.double(x) with if(is.double(x)) x else as.double(x) saves time and avoids one copy, in the case that x is already double. I suggest modifying as.double to avoid the extra copy and just return x, when x is already double. Similarly for as.integer, etc. [[alternative HTML version deleted]]

Hello, I?m experimenting with ALTREP and was wondering if there is a preferred way to create an ALTREP wrapper vector without using .Internal(wrap_meta(?)), which R CMD check doesn?t like since it uses an .Internal() function. I was trying to create a factor that used an ALTREP integer, but attempting to set the class and levels attributes always ended up duplicating and materializing the

Hello, I've created this class: setClass("example", representation ( size = "numeric", id = "character" ) ) Suppose I create a new instance of this class: > x <- new("example", 4, "id_value") This creates an S4 object with two slots. Am I correct in thinking that slots are "filled" by SEXPs?

I ran into strange behavior when removing names. Two ways of removing names: i <- rep(1:4, length.out=20000) k <- c(a=1, b=2, c=3, d=4) x1 <- unname(k[i]) x2 <- k[i] x2 <- unname(x2) Are they identical? identical(x1,x2) # TRUE but no identical(serialize(x1,NULL),serialize(x2,NULL)) # FALSE But problem is with serialization type 3, cause:

Hello, I would like for my C function to be able to manipulate some values stored in an R data frame. To achieve this, a need the (real) memory address where the R data frame stores its data (hopefully in a contiguous way). Then, from R, I call the C function and passing this memory address as a parameter. The question: how can we get the memory address of the R data frame? Thank you! L.

Hello, I was wondering if there were any plans for ALTREP lists (VECSXP)? It seems to me that they could be supported in a similar way to how ALTSTRING works, with Elt() and Set_elt() methods, or would there be some problems with that I?m not seeing due to lists not being atomic vectors? I was taking an approach of converting each list element (of a file-based list data structure) to an ALTREP

Hi, I expected NAMED to be 1 in all these three cases. It is for one of them, but not the other two? > R --vanilla R version 2.14.0 (2011-10-31) Platform: i386-pc-mingw32/i386 (32-bit) > x = 1L > .Internal(inspect(x)) # why NAM(2)? expected NAM(1) @2514aa0 13 INTSXP g0c1 [NAM(2)] (len=1, tl=0) 1 > y = 1:10 > .Internal(inspect(y)) # NAM(1) as expected but why different to x?

Hi, I would like to know if it's ok to use .Internal(inspect(x)) in order to detect vector copying. Take for example the following silly code: f <- function() { x = seq(10) print(.Internal(inspect(x))) for(i in seq(10)) { x[i] <- x[i] + 1 print(.Internal(inspect(x))) } } The output of f() was: @bd7acf0 13 INTSXP g0c4 [NAM(1)] (len=10, tl=0) 1,2,3,4,5,... [1] 1 2

Hi Kylie, Is it a list with only numerics in it? (I only see REALSXPs there, but obviously inspect isn't showing all of them). If so, you could load it up into one big vector and then also keep partitioning information around. Bioconductor does this (see ?IRanges::CompressedList ). The potential benefit here being that the underlying large vector could then be a big out-of-memory altrep. How

Hi Jiefei and Kylie, Great to see people engaging with the ALTREP framework and identifying places we may need more tooling. Comments inline. On Thu, Jul 18, 2019 at 12:22 PM King Jiefei <szwjf08 at gmail.com> wrote: > > If that is the case and you are 100% sure the reference number should be 1 > for your variable *y*, my solution is to call *SET_NAMED *in C++ to reset > the

I'm confused by this: > identical(function() {}, function() {}) [1] FALSE Yet, after loading the Matrix package (which redefines det), the following is checked (in library.checkConflicts): > identical(get("det", baseenv()), get("det", asNamespace("Matrix")), ignore.environment=T) [1] TRUE I've looked at the code in identical.c and for closures it

I can work on this. Thanks Luke. ~G On Wed, Jul 24, 2019 at 8:25 AM Tierney, Luke <luke-tierney at uiowa.edu> wrote: > If one of you wanted to try to create a patch to support ALTREP > generic vectors here are some notes: > > The main challenge I am aware of (there might be others): Allowing > DATAPTR to return a writable pointer would be too dangerous because > the GC

Hello, I have encountered two bugs when using ALTREP APIs. 1. STDVEC_DATAPTR >From RInternal.h file it has a comment: /* ALTREP support */ > void *(STDVEC_DATAPTR)(SEXP x); However, this comment might not be true, the easiest way to verify it is to define a C++ function: void C_testFunc(SEXP a) > { > STDVEC_DATAPTR(a); > } and call it in R via > a=1:10 > >

Hello Luke and Gabriel, Thank you very much for your quick responses. The explanation of STDVEC is very helpful and I appreciate it! For the wrapper, I have a few new questions. 1. Like Luke said a mutable object is not possible. However, I noticed that there is one extra argument *deep* in the function duplicate. I've googled all the available documentation for ALTREP but I did not find

Hi, I just found a strange increase in the reference number and I'm wondering if there is any reason for it, here is the code. > a=c(1,2,3) > .Internal(inspect(a)) @0x000000001bf0b9b0 14 REALSXP g0c3 [NAM(1)] (len=3, tl=0) 1,2,3 > is.vector(a) [1] TRUE > .Internal(inspect(a)) @0x000000001bf0b9b0 14 REALSXP g0c3 [NAM(7)] (len=3, tl=0) 1,2,3 The variable *a* initially has one

On Mon, 21 Jan 2019, Martin Maechler wrote: >>>>>> Travers Ching >>>>>> on Tue, 15 Jan 2019 12:50:45 -0800 writes: > > > I have a toy alt-rep string package that generates > > randomly seeded strings. example: library(altstringisode) > > x <- altrandomStrings(1e8) head(x) [1] > >

Reading "R Internals" made me believe that R_UnboundValue was a placeholder that would be skipped over in variable lookup. viz. the section of R Internals "Hash tables" says "items are not actually deleted but have their value set to R_UnboundValue.", which seems to align with what I read in envir.c. So, I reasoned, if I have a function that returns R_UnboundValue,

Hi Jiefei and Duncan, I suspect what is likely happening is that one of ENSURE_NAMEDMAX or MARK_NOT_MUTABLE are being hit for x. These used to set named to 3, but now set it to 7 (ie the previous and current NAMEDMAX value, respectively). Because these are macros rather than C functions, its not easy to figure out why one of them is being invoked from do_isvector (a cursory exploration

I have a toy alt-rep string package that generates randomly seeded strings. example: library(altstringisode) x <- altrandomStrings(1e8) head(x) [1] "2PN0bdwPY7CA8M06zVKEkhHgZVgtV1" "5PN2qmWqBlQ9wQj99nsQzldVI5ZuGX" ... etc object.size(1e8) Object.size will call the set_altstring_Elt_method for every single element, materializing (slowly) every element of the vector. This