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 does not
work (as Rcpp Sugar pertains to Rcpp types, but not RcppParallel which cannot
rely on SEXP-based representation to allow multi-threaded execution). 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
in Rcpp::algorithm which follow the pattern of std::algorithm.

Rcpp::algorithm

Currently Rcpp::algorithm contains only a few simple
functions. If these 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

Additional Benefits

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.

Wrapping Up

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.