RcppBDT 0.2.0

(This article was first published on Thinking inside the box , and kindly contributed to R-bloggers)

A new release of the RcppBDT package appeared on
CRAN earlier today.

RcppBDT uses Rcpp,
and in particular the nifty Rcpp modules feature of wrapping C++
code for R just by declaring the (class or function) interfaces. It uses
this to bring in some useful functions from
Boost Date.Time to
R so that one can do things like

R> library(RcppBDT)
R> sapply(2012:2016, function(year)
+         format(getNthDayOfWeek(first, Mon, Sep, year)))
[1] "2012-09-03" "2013-09-02" "2014-09-01" "2015-09-07" "2016-09-05"

to compute the next five Labor Day dates in the US, given the year and the
first Monday of September requirement. More examples are e.g. on the
earlier blog post announcing version 0.1.0.

Changes are mostly internal. R 2.15.1 brough a better / easier way to load
such ‘modules’ into R, and Rcpp 0.9.13 allows us to use this. So RcppBDT
continues to be useful as an example package for Rcpp modules. I also
streamlines the interface a little: identifiers are now directly accessible
in the package’s NAMESPACE rather than just via the an instantiated object.

I also added a NEWS file, using the .Rd format so that we can
import the marked-up text:

News for Package RcppBDT

Changes in version 0.2.0 (2012-07-02)
  • The core module, which wraps what in C++ is
    boost::gregorian::date, is now exposed as an Rcpp module bdtDate.
    As all example and demos operated off a (package-global) variable
    ‘bdt’, no user visible change was needed outside of the code
    instantiating at package load.

  • Updated package instantiation to the new facilities offered by
    the current versions R 2.15.1 and Rcpp 0.9.13 which make Rcpp module
    initialization easier and more streamlined.

Changes in version 0.1.0 (2011-01-17)
  • First CRAN upload (and see ChangeLog for more granular
    details) bug fix in svm cross validation

Courtesy of
CRANberries, there
is also a diffstat report
for 0.2.0 relative to 0.1.0.
As always, feedback is welcome and the
rcpp-devel mailing list
off the R-Forge page for Rcpp is
the best place to start a discussion.

To leave a comment for the author, please follow the link and comment on their blog: Thinking inside the box .

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.


Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)