similar to: Fast way to call an R function from C++?

For reference, your benchmark using UNWIND_PROTECT: > system.time(test(testFunc, evn$x)) user system elapsed 0.331 0.000 0.331 > system.time(test(C_test1, testFunc, evn$x)) user system elapsed 2.029 0.000 2.036 > system.time(test(C_test2, expr, evn)) user system elapsed 2.307 0.000 2.313 > system.time(test(C_test3, testFunc, evn$x)) user system

Hello Kevin and I?aki, Thanks for your quick responses. I sincerely appreciate them! I can see how complicated it is to interact with R in C. I?aki's suggestion is very helpful, I saw there is a lot of performance gain by turning the flag on, but sadly the best performance it can offer still cannot beat R itself. It is interesting to see that C++ is worse than R in this special case despite

Hi, This is my first post, sorry if not in the right format. I am stuck at a place where I have a code fragment that runs in normal gcc but fails when I give -fplugin=dragonegg.so extern int *testfunc(); extern __typeof (testfunc) testfunc __asm__ ("" "__GI_testfunc") __attribute__ ((visibility ("hidden"))); extern __typeof(testfunc) __testfunc; extern __typeof

I am trying to do parallel programming and I tried this library(doSNOW) library(foreach) testfunc<-function(x){ x<-x+1 x } noc<-2 cl <- makeCluster(do.call(rbind,rep(list("localhost"),noc)), type = "SOCK") registerDoSNOW(cl) clusterExport(cl=cl,c("testfunc.r")) testl<-foreach(pp=1:2) %dopar% { testfunc(pp) } And this works but if I try to

BLAST! LLVM mailing list headers are still royally screwed up... My message is below... On Sun, Aug 30, 2009 at 2:20 PM, Talin<viridia at gmail.com> wrote: > Hey all, it's been a while since I have posted on this list, but I've > been continuing my work with LLVM and getting lots done :) > > One question I wanted to ask is whether anyone had any advice on how to >

Hello Group, I'm trying to learn R and am having a problem getting output from a function I'm trying to write. The problem is clearly one of scope, but I can't find the documentation that tells me how to get around the issue. Here is an example of my problem. testfunc<-function(x) { y<-10 print(y) print(x) } testfunc(4) The variables x and y are accessible during execution

First off, thanks for the help so far. >From what I have been able to tell, emitPrologue kicks in after the arguments for the function have been copied. For example, consider the function int testfunc( int foo, int bar ); Emitting assembly code from the llvm-gcc frontend in a small test program gives the following for the call to testfunc movl $1338, (%esp) movl $1339, 4(%esp) call

I noticed this oddity about [ and setMethod. First, I define testFunc, which sorts a data frame by the first column and returns the entries that aren't NAs, and testIt, which runs testFunc repeatedly on a random large data frame, each time saving the return into a dummy placeholder (for demonstration's sake). > require(methods) Loading required package: methods [1] TRUE > testFunc

I noticed this oddity about [ and setMethod. First, I define testFunc, which sorts a data frame by the first column and returns the entries that aren't NAs, and testIt, which runs testFunc repeatedly on a random large data frame, each time saving the return into a dummy placeholder (for demonstration's sake). > require(methods) Loading required package: methods [1] TRUE > testFunc

Hello, I'm trying to combine the parallel computing power available through NVIDIA CUDA (www.nvidia.com/cuda) from within R. CUDA is an extension to the C language, so I thought it would be possible to do this. If I have a C file with an empty function which includes a needed CUDA library (cutil.h) and compile this to an .so file using a NVIDIA compiler (nvcc), called 'myFunc.so' I

Hi! We have started to use deopt operand bundle to make our native stacktrace deoptimizable and garbage collectable. We stumbled upon an issue and we don't know if it is really an issue on our side or really a problem within LLVM. For example, for this input: declare { i8*, i8* } @getCode() define void @testFunc() { entry: %0 = call { i8*, i8* } @getCode() %1 = extractvalue { i8*, i8* }

Dear all, I'm looking for a function comparable to switch, to categorize a continuous variable in a few levels. Off course that can be done with a series of ifelse statements, but that looks rather clumsy. I looked at switch, but couldn't figure out how to use it for this. I guess that's not possible, as it only works with characters or integers, not with intervals. Basically,

Hi, I'm trying to follow the advice from this message: http://lists.cs.uiuc.edu/pipermail/llvmdev/2008-October/017574.html, to create a call instruction from a function pointer. But I'm getting... Assertion failed: (isa<X>(Val) && "cast<Ty>() argument of incompatible type!"), function cast, file /usr/local/include/llvm/Support/Casting.h, line 202.

Hello! I have the problem that in my function the passed variable is not used, but the variable name of the dataframe itself?- difficult to explain, but an easy example: TestFunc<-function(df, group) { ??? print(names(subset(df, select=group))) } df1<-data.frame(group="G1", visit="V1", value=0.9) TestFunc(df1, c("group", "visit")) Result: [1]

** Sorry to repost. I forgot to include a function necessary to make the example work ** I apologize up front for this being a little long. I hope it's understandable. Please let me know if I need to clarify anything. Several months ago I wrote a series of functions to help me take my R analyses and build custom reports in html files. Each function either builds or modifies a string of

Hi there R-helpers: I'm having problems with the function ode() found in the package deSolve. It seems that when my state variables are too numerous (>33000 elements), the function throws the following error: Error in vode(y, times, func, parms, ...) : cannot allocate memory block of size 137438953456.0 Gb In addition: Warning message: In vode(y, times, func, parms, ...) : NAs

On Jan 17, 2011, at 5:01 PM, Rob Nikander wrote: > Hi, > > I'm trying to follow the advice from this message: > http://lists.cs.uiuc.edu/pipermail/llvmdev/2008-October/017574.html, > to create a call instruction from a function pointer. But I'm > getting... > > Assertion failed: (isa<X>(Val) && "cast<Ty>() argument of > incompatible

On Mon, Jan 17, 2011 at 8:36 PM, Eric Christopher <echristo at apple.com> wrote: > >    id testfunc(id a, id b) { ... } >    ... >    FunctionType *fn_type = FunctionType::get(id_type, argtypes, false); >    Value *fn = ConstantExpr::getIntToPtr(ConstantInt::get(int64_type, > reinterpret_cast<int64_t>(testfunc)), fn_type); >    return builder.CreateCall2(fn,

I'd like to be able to specify a data frame by name in a function call. Any ideas how this can be done? dfm <- data.frame(x=1:10) testfunc <- function(data="dfm") { dat <- data sum(dat$x) } print(testfunc()) -- View this message in context: http://r.789695.n4.nabble.com/specify-data-frame-by-name-tp2996534p2996534.html Sent from the R help mailing list archive at

I am running into problems calling the library function nlme from within another function. Basically,the following function (with v a list containing data and initialization values) > testfunc function(dat=v) { test<-nlsList(result~a+(b-a)/(1+(conc/(c+z*cdiff))^d) |rep,start=dat$init,data=dat$mixeddat) return(nlme(test,random=b~1)) } produces the error message Error in eval(expr, envir,