I agree that we might want to have these things in a package say RcppBase. Then Rcpp can remain the R to cpp layer. And anybody who want to implement an R base function in cpp, can contribute it to RcppBase.
Willem On Fri, Nov 16, 2012 at 8:56 AM, Romain Francois <rom...@r-enthusiasts.com>wrote: > We need to fond the right compromise between bloating Rcpp (which is > already quite huge: > > wc src/* inst/include/**/** inst/include/* 2> /dev/null | tail -n1 > 66180 784183 6425152 total > > and support generic enough things. > > I can see things like union and setdiff being generic enough (we already > have unique btw). > > > Then for other things, being in another package is not that bad. > An after all, this is what Rcpp really is about: give others the tools. > > Romain > > Le 15/11/12 20:07, Søren Højsgaard a écrit : > > Dear list >> >> [>>] I am not sure if Hadleys remark below was an invitation to make a >> "wishlish", but I'll take the risk: >> >> 1) I have made several packages related to graphical models for >> multivariate data. Much of these packages deals with "book keeping": >> operations on sets of subsets of a finite set of variables, so in these >> packages there is much use of union(), setdiff(), etc and these function >> all heavily use match(). The same applies to unique() which is also based >> on match(). It would be very nice to have these in c++ form. Hence, with a >> c++ version of match() these should be low-hanging apples. >> >> 2) Also of relevance to the graphical model packages is a c++ version of >> aperm() for permuting an array. >> >> 3) There are operations on such arrays which I imagine could be >> conveniently made in the Rcpp-framwork. Consider a 2x2x2 contingency table >> with dimnames a,b,c. Call this table n(a,b,c). The all-two-factor >> log-linear model will have generators (a,b)(a,c)(c,b). Iterative >> proportional fitting works as follows: Let m(a,b,c) denotes the array of >> fitted values (at the current iteration). Then the update for the (c,b) >> generator is >> >> m(a,b,c) <- m(a,b,c) n(c,b)/m(c,b) >> >> To do this one must have >> marginalization: n(a,b,c) -> n(b,c) >> permutation: n(b,c) -> n(c,b) >> division: n(c,b)/m(c,b) >> multiplication: m(a,b,c) * ( n(c,b)/m(c,b) ) >> >> I am aware that iterative proportional fitting is already implemented in >> loglin, but there are other kind of (graphical) models where similar >> updates are needed. In connection with message passing in Bayesian >> networks, one operation often needed is >> >> m(a,b,c) <- n(a,b) * n(c,b) >> >> which will result in an array with dimensions (a,b,c). All of this stuff >> is implemented in the gRbase backage as R functions, and it would be very >> convenient to have these operations as c++ functions. In the gRbase >> implementation it is required that the arrays do have dimnames, and I guess >> it must be so also in c++. >> >> I am perfectly aware that I should program these facilities in c++ using >> Rcpp, but I just can't resist to mention these wishes, in case they are >> "almost there" in c++. >> >> Best regards >> Søren >> >> >> >> >> >> >> >> >> >> >> Hmmm - see >> http://cran.r-project.org/web/**packages/fastmatch/index.html<http://cran.r-project.org/web/packages/fastmatch/index.html> >> >> Hadley >> >> PS. Would you be interested in a set of R functions that from a quick >> skim of the R sources that I think could be much much faster if implemented >> in Rcpp? >> >> >> -- >> RStudio / Rice University >> http://had.co.nz/ >> >> > > -- > Romain Francois > Professional R Enthusiast > +33(0) 6 28 91 30 30 > > R Graph Gallery: > http://gallery.r-enthusiasts.**com<http://gallery.r-enthusiasts.com> > `- http://bit.ly/SweN1Z : SuperStorm Sandy > > blog: > http://romainfrancois.blog.**free.fr<http://romainfrancois.blog.free.fr> > |- http://bit.ly/RE6sYH : OOP with Rcpp modules > `- http://bit.ly/Thw7IK : Rcpp modules more flexible > > ______________________________**_________________ > Rcpp-devel mailing list > Rcpp-devel@lists.r-forge.r-**project.org<Rcpp-devel@lists.r-forge.r-project.org> > https://lists.r-forge.r-**project.org/cgi-bin/mailman/** > listinfo/rcpp-devel<https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel> >
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