On Wed, Sep 7, 2011 at 3:13 PM, <[email protected]> wrote: > The question absolutely pertains to using the inline functionality.
I think this is a reasonable R/C++ question -- i.e. Rcpp. inline is more or less orthogonal to Rcpp. inline is a great Rcpp jump-starter. > As each new data arrives, I want to pass it to my C++ function. After thinking about this for a bit, this might be a reasonable use case for an Rcpp-module. You can instantiate a module as an R object, it will hold state, and can be easily updated, queried, etc. The key weakness here is that modules can't at present be serialized via save()/load(). So, if you can do all your processing in one R session, you might want to take a look at this. The code ends up clean and powerful. I've been headed this way myself for computationally extensive simulations that depend on time-varying parameters residing in R dataframes. Incidentally, an important question to ask yourself is: where are your bottlenecks? It wasn't clear to me in reading your question *why* you need C++. The most popular use-case of Rcpp seems to be the huge speed advantage. Where/why do you need speed? This should highlight the code that needs to get pushed into C++. R can compete with compiled code in plenty of cases... -xian -- A man, a plan, a cat, a ham, a yak, a yam, a hat, a canal – Panama! _______________________________________________ Rcpp-devel mailing list [email protected] https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel
