On Friday 19 January 2007 1:29 pm, Gabor Grothendieck wrote: > > If you decide to use C++ with R you should check out the documentation > > that comes with the package RcppTemplate, and the sample code that > > comes with that package. In my experience C++ (or C or FORTRAN) is > > needed for many compute intensive tasks, and the R framework provides > > a nice front-end with its extensive collection of visualization and > > statistical analysis tools. > > Actually I have found the opposite. I have never found C/C++ to be > necessary. I have always been able to optimize the R code itself to get it > to run sufficiently fast for my purposes. >
The nice thing about being able to use C code is that this provides confidence that however slowly your R script runs right now you will be able to make it faster - no matter what. On quite a few occasions I have started writing C code and after thinking about how I would structure it realized that I can do the same thing in R and still get 50% of the speed improvement I get from C. Also, I am not sure whether this is mentioned anywhere, but I found it to be more convenient to use dyn.load directly instead of creating a full-blown R package. This way the edit-compile-test cycle is much more convenient. best Vladimir Dergachev ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel