[This article was first published on Rcpp Gallery, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
A while back I saw a post on StackOverflow where the user was trying to use Rcpp::sugar::sum() on an RcppParallel::RVector.
Obviously this doesn’t work and it raised the question “Why doesn’t something more generic exist to provide functions with R
semantics that can be used on arbitrary data structures?” As a result, I set out to create a set of such functions following
the pattern of std::algorithm in Rcpp::algorithm.
Currently Rcpp::algorithm contains only a few simple functions, but if they are found to be useful, more will be added.
Examples of using the currently implemented iterator-based functions are below.
sum, sum_nona, prod, and prod_nona
min, max, and mean
log, exp, and sqrt
Through the coding of these simple “algorithms”, a few needs arose.
First, the ability to deduce the appropriate C numeric type
given an Rcpp iterator was necessary. This gave birth to the Rcpp::algorithm::helpers::decays_to_ctype and
Rcpp::algorithm::helpers::ctype type traits. Given a type, these allow you to determine whether it can be cast to a C numeric
type and which type that would be.
Second, the need arose for more information about R types. This gave birth to the Rcpp::algorithm::helpers::rtype traits. These
are defined as follows:
These additional benefits may actually prove more useful than the algorithms themselves. Only time will tell.
There are now some simple iterator-based algorithms that can be used with any structure that supports iterators. They apply the same semantics
as the analogous Rcpp::sugar functions but give us more flexibility in their usage. If you find these to be useful, feel free to request more.
To leave a comment for the author, please follow the link and comment on their blog: Rcpp Gallery.