similar to: Understanding modification in place

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

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

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?

Hello, Doing typeof() on an object appears to reset the "named" field in its sxpinfo header to 2, which can change the way that subsequent subassignment operations are carried out: X <- 1:5e7 .Internal(inspect(X)) # @4eeb0008 13 INTSXP g0c7 [NAM(1)] (len=50000000, tl=0) 1,2,3,4,5,... system.time(X[1] <- 9L) # user system elapsed # 0 0 0 typeof(X)

Hi Kylie, For your question, I don't think a wrapper can completely solve your problem. The duplication occurs since your variable y has more than 1 reference number( Please see highlighted), so even you have a wrapper, any changes on the value of the wrapper still can trigger the duplication. > .Internal(inspect(y)) > @7fb0ce78c0f0 13 INTSXP g0c0 *[NAM(7)]* matter vector (mode=3,

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.

> .Internal(inspect(1:10)) @300e4e8 13 INTSXP g0c0 [NAM(3)] 1 : 10 (compact) > .Internal(inspect(seq(1,10))) @3b6e1f8 13 INTSXP g0c4 [] (len=10, tl=0) 1,2,3,4,5,... > system.time(1:1e7) user system elapsed 0 0 0 > system.time(seq(1,1e7)) user system elapsed 0.05 0.00 0.04 It seems that result of function 'seq' doesn't use compact

Thanks -- I'll commit a fix after some testing. Best, luke On 04/29/2018 06:22 AM, Duncan Murdoch wrote: > On 28/04/2018 11:11 PM, Suharto Anggono Suharto Anggono via R-devel wrote: >>> .Internal(inspect(1:10)) >> @300e4e8 13 INTSXP g0c0 [NAM(3)]? 1 : 10 (compact) >>> .Internal(inspect(seq(1,10))) >> @3b6e1f8 13 INTSXP g0c4 [] (len=10, tl=0) 1,2,3,4,5,...

Hi Lille, Is it possible you're looking for tracemem() or inspect() ? > x <- data.frame(z = 1:10)> tracemem(x)[1] "<0x55aa743e0bc0>" > x[1] <- 2Ltracemem[0x55aa743e0bc0 -> 0x55aa778f6ad0]: tracemem[0x55aa778f6ad0 -> 0x55aa778f6868]: [<-.data.frame [<- tracemem[0x55aa778f6868 -> 0x55aa778f5b48]: [<-.data.frame [<- >

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] > >

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

Hello, Since people have whisperred about Rcpp, I'd like to play too. > On 11/15/2010 07:45 AM, Patrick Leyshock wrote: >> Very helpful, thank you. >> >> A couple other questions, please: >> >> 1. I've got a function written in C, named "my_c_function". In my R >> code I call this function, passing to it an INTSXP and a STRSXP, >>

Hi, I am trying to use existing C++ code from R. I have no problems compiling C code and using it in R, but with C++ I'm running into problems. Here's the compiler output: Macintosh-10:~/Desktop/dissertation/Model - CPP version/R labguest$ g++ -I/Library/Frameworks/R.framework/Resources/include -I/Library/Frameworks/R.framework/Resources/include/i386 *.cpp In file included from

On 1/22/19 6:17 PM, Kevin Ushey wrote: > I think that object.size() is most commonly used to answer the question, > "what R objects are consuming the most memory currently in my R session?" > and for that reason I think returning the size of the internal > representations of objects (for e.g. ALTREP objects; unevaluated promises) > is the right default behavior. I

Thanks Duncan. I can't tell you how helpful all your terrific replies have been. I think the biggest surprise is that nobody appears to be using Java and R together like I"m trying to do. I suppose it should be a surprise since there are no books on the subject and almost no technical documentation other than a few sites here and there. ----- I originally had the "int" as the

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

Dear list, On a follow up from my previous email, I am now trying to allocate vectors of length larger than 32-bit in C. >From the R internals documentation, I read that: "The sxpinfo header is defined as a 32-bit C structure..." and "A SEXPREC is a C structure containing the 32-bit header..." The question is: does the INTSXP allow vectors larger than 32-bit? A test

>>>>> Martin Maechler >>>>> on Tue, 8 Sep 2020 10:40:24 +0200 writes: >>>>> Hugh Parsonage >>>>> on Tue, 8 Sep 2020 18:08:11 +1000 writes: >> I can only reproduce on Windows, but reliably (both 4.0.0 and 4.0.2): >> $> R --vanilla >> x <- c(0L, -2e9:2e9) >> # > Segmentation

Dear core group, Which operation in R guarantees to get a true copy of an atomic vector, not just a second symbol pointing to the same shared memory? y <- x[] #? y <- x y[1] <- y[1] #? Is there any function that returns its argument as a non-shared atomic but only copies if the argument was shared? Given an atomic vector x, what is the best official way to find out whether other