(This article was first published on Thinking inside the box , and kindly contributed toR-bloggers)
The first Armadillo release of the 7.* series is out: a new version 7.100.3. We uploaded RcppArmadillo 0.7.100.3.0 to CRAN and Debian . This followed the usual thorough reverse-dependecy checking of by now 230 packages using it.
This release now requires a recent enough compiler. As
g++ is so common, we explicitly test for version 4.6 or newer. So if you happen to be on an older RHEL or CentOS release, you may need to get yourself a more modern compiler. R on Windows is now at 4.9.3 which is decent (yet stable) choice; the 4.8 series of
g++ will also do. For reference, the current LTS of Ubuntu is at 5.3.1, and we have
g++ 6.1 available in Debian testing.
This new upstream release adds a few new helper functions (which are particularly useful in statistics, but were of course already available to us via Rcpp), more slicing of
Cube data structures and a brand new sparse matrix decomposition module courtesy of Yixuan Qiu — whom R users know as the author of the RSpectra package (which replaces his older rArpack package) and of course all the most excellent work he provided to RcppEigen .
Armadillo is a powerful and expressive C++ template library for linear algebra aiming towards a good balance between speed and ease of use with a syntax deliberately close to a Matlab.
Changes in this release are as follows:
Changes in RcppArmadillo version 0.7.100.3.0 (2016-05-25)
Upgraded to Armadillo test release 7.100.3
.tail_slices()to subcube views
spsolve()now requires SuperLU 5.2
svds()now use a built-in reimplementation of ARPACK for real (non-complex) matrices (code contributed by Yixuan Qiu)
configurecode now checks against old
g++version which are no longer sufficient to build the package.
Courtesy of CRANberries , there is also a diffstat report for this release . As always, more detailed information is on the RcppArmadillo page . Questions, comments etc should go to the rcpp-devel mailing list off the R-Forge page.