similar to: suggest that as.double( something double ) not make a copy

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

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.

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:

Hi Expert I want to use dtrace to monitor the content change of one file. I made following scripts, #!/usr/sbin/dtrace -s inline int MYPID = $1; syscall::write:entry /pid == MYPID/ { tracemem(arg1, arg2); printf("\n"); } It always has an following error bash-3.00$ sudo dumpFIFO.dtrace 3836 dtrace: failed to compile script ./dumpFIFO.dtrace: line 19: tracemem( ) argument #2

Hi, I've noticed that as.vector() always allocates a new object, e.g. > x <- 1:10; > x <- as.vector(x); > tracemem(x); [1] "<0x0000000005622db8" > x <- as.vector(x); tracemem[0x0000000005622db8 -> 0x0000000005622ec0]: as.vector > x <- as.vector(x); tracemem[0x0000000005622ec0 -> 0x0000000005622f18]: as.vector > x <- as.vector(x);

Hi All, i have a problem in understanding what the assignment operator '<-' really is doing. If i create two numeric arrays in R and copy one into the other with '<-' and afterwards change one array by calling a C function, both arrays are changed! The problem I am facing can easily be seen in the following example: (The following R code and the C function is attached and

N_conreq:entry { self->x=1; calledaddr=(struct xaddrf *)arg3; callingaddr=(struct xaddrf *)arg4; trace(calledaddr->link_id); tracemem(calledaddr->DTE_MAC.lsap_add, 80); trace(callingaddr->link_id); tracemem(callingaddr->DTE_MAC.lsap_add, 80); } 0 -> N_conreq 255

Hi all, I've been trying to get a better handle on what manipulations lead R to duplicate a vector, creating small experiments and using tracemem to observe what happens (all in 2.15.1). That's lead me to a few questions, illustrated using the snippet below. x <- 1:10 tracemem(x) # [1] "<0x1058f8238>" x[5] <- 5 # tracemem[0x1058f8238 -> 0x105994ab0]: x[11] <-

Hello all, A friend recently brought to my attention that vector assignment actually recreates the entire vector on which the assignment is performed. So for example, the code: x[10]<- NA # The original call (short version) Is really doing this: x<- replace(x, list=10, values=NA) # The original call (long version) # assigning a whole new vector to x Which is actually doing this: x<-

Hi, $ R --vanilla R version 2.14.1 (2011-12-22) Platform: i686-pc-linux-gnu (32-bit) > DF = data.frame(a=1:3,b=4:6) > DF a b 1 1 4 2 2 5 3 3 6 > tracemem(DF) [1] "<0x8898098>" > names(DF)[2]="B" tracemem[0x8898098 -> 0x8763e18]: tracemem[0x8763e18 -> 0x8766be8]: tracemem[0x8766be8 -> 0x8766b68]: > DF a B 1 1 4 2 2 5 3 3 6 > Are those 3

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 was trying to use tracemem to look at mblk contents. First, I tried to use mblk->b_wptr - mblk->b_rptr as the size, and was told that it had to be a constant. Foo. (RFE #1). Then, I tried to use 8 as the size, and kept getting decimal numbers printed. Stumbled on #pragma D option rawbytes=true (is the =true necessary, btw?) and that didn''t help. Then, in desperation, I

Is putting a variable into a list a deep copy (and is tracemem the correct way to confirm)? warmstrong at krypton:~/dvl/R.packages$ R > x <- rnorm(1000) > tracemem(x) [1] "<0x3214c90>" > x.list <- list(x.in.list=x) tracemem[0x3214c90 -> 0x2af0a20]: > Is it possible to put a variable into a list without causing a deep copy (i.e. if you _really_ want the

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

On Fri, 5 Aug 2016, Winston Chang wrote: > 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

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 [<- >

Gabriel Becker writes: AFAIK R does not automatically copy function arguments. R actually tries very hard to avoid copying while maintaining "pass by value" functionality. ... R only copies data when you modify an object, not when you simply pass it to a function. This is a bit misleading. R tries to avoid copying by maintaining a count of how many references there are to an

Hi When I try to update an number in a large data.frame by its pos It's really slow it take almost a sec to do this and I wonder why and if where is any faster way to update a number in a data.frame ive tried DF$col[POS]<-number DF[xPOS,yPOS]<-number Thx //Joel -- View this message in context: http://r.789695.n4.nabble.com/Slow-update-insert-on-Data-frame-tp3055707p3055707.html

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?

I'm interested in the difference between these two intuitively equivalent sequences that produce different results (in R version 2.13.1 (2011-07-08) 32-bit). I think R's reference counting optimization is causing this difference in behavior. > a <- 1 > a+{a[1] <- 20} [1] 21 > a <- 1 > a[1] <- 1 > a+{a[1] <- 20} [1] 40 Is one of these the "correct"