similar to: Best practices for writing R functions

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

I am trying to parallelize part of a C function that is called from R (via .C) using OpenMP's "parallel for" pragma. I get mixed results: some runs finish with no problem, but some lead to R crashing after issuing a long error message involving memory violations. I found this post, which describes how a .Call() function can be made to avoid crashing R by raising the stack limit:

Hello, I am in the process of writing an R extension for parallelized MCMC, with heavy use of compiled code (C++). I have been getting my feet wet by implementing a simple matrix-vector multiplication function in C++ (which calls a BLAS level 2 function dgemv), and comparing it to the '%*%' operator in R (which apparently calls a BLAS level 3 function dgemm). Interestingly, I cannot

I have a function in R that takes another function as argument: f <- function(g, ...) { #g is expected to be a function } I want to see if there is a way to implement "f" in C and calling it from R using ".C" interface. I know that I can use function pointers for my C implementation, but I imagine it's going to be nearly impossible to pass a function from R to C. Are

I would like to load a binary file into R using load(), and then assign a new name to it, regardless of the name it was saved under. Can you please provide a code sample? Thank you! -- View this message in context: http://r.789695.n4.nabble.com/Assigning-a-new-name-to-object-loaded-with-load-tp4638144.html Sent from the R help mailing list archive at Nabble.com.

I am writing a wrapper function in C++ that calls a GPU kernel. My array type for the GPU kernel is float, so I would like my wrapper function to receive float arrays from R. I understand that I can use 'as.single' in R to copy a double-precision vector from R in single-precision format while using the '.C' interface, but is there any way to do something similar for

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

Hi, I'm working on coding some more complex things in R and have need to break much of the logic into functions. I have several "global" variables that I want to change with a given function. (The variable has a different value after the function is called.) In other languages like C, this is simple. However, in R, if a function changes a variable, that change only occurs in the

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);

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] <-

Ok, here's another best practices question - let's say I'm writing a package and I want to use a function name that is already claimed by a function in the base R packages. For the sake of argument, let's pretend this function is for profiling the performance of a function (like Rprof for example), and so an obvious name that comes to mind is profile. This, of course, clashes

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 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<-

Further pursuing my curiosity to measure the efficiency of R/C++ interface, I conducted a simple matrix-vector multiplication test using .C and .Call functions in R. In each case, I measured the execution time in R, as well as inside the C++ function. Subtracting the two, I came up with a measure of overhead associated with each call. I assume that this overhead would be non-existent of the entire

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

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