search for: xplusi

Hello R experts I am googling and reading around, however, I can't get it working (perhaps because I do not understand much C, however, I'll give it a try). I am trying to include C++ code into an R routine, where the C++ code looks: #include <iostream> using namespace std; void foo (double* x, double* y, double* out) { out[0] = x[0] + y[0]; } Back in R, the command R CMD

Hi Gordon, Gordon Henriksen wrote: > Nicholas, > > I guess you're trying to solve the fragile base-class problem by > deferring field offset calculations until JIT compilation time? > > No. I'm deferring field offset calculation until /execution /time. > Perhaps I'm missing something, but can't you accomplish this by using > external constants in

Nicholas, I guess you're trying to solve the fragile base-class problem by deferring field offset calculations until JIT compilation time? Perhaps I'm missing something, but can't you accomplish this by using external constants in the source program, to be supplied at JIT/link time? external constant i32 @obj.x.offs; external constant i32 @obj.y.offs; define

Hi everyone, I would like to implement an equivalent mechanism of function callbacks in the JIT, but for fields. Typically in Java, when you compile a method, there may be some instructions (getfield, putfield) that depend on a type which is not yet resolved. I think the best way to do this in LLVM is to add an intrinsic. The intrinsic would be only valid if we jit, and would be lowered only in

Hello (Heinrich), I did not know I could do this. It doesn't seem to be documented anywhere. Thought this would be helpful to the fraction of the community using package R.oo. Note the call of a setMethodS3 method, xOne, in the setConstructorS3. This is extremely useful if xOne (in this case) is a very complex method (that you always want to be called every time you create a new object). If I

Dear R-experts! I am currently running a meta-analysis with the help of the great metafor package. However I have some difficulties setting up my raw data to enter it to the meta-analysis models. I have a group of subjects that have been measured in two continuous variables (A & B). I have the information about the mean of the two variables, the group size (n) and the standard deviations of

On 2007-11-06, at 11:29, Nicolas Geoffray wrote: >> Or, quite similarly, accessor functions also to be supplied by the >> JIT/ >> linker: >> > > You lose performance here, because you have to call the accessor > function each time you call the xPlusY function. My goal is to patch > the > native code so that you do not need to call these accessor