Thu, 10 Aug 2023

RcppArmadillo on CRAN: New Upstream

armadillo image

Armadillo is a powerful and expressive C++ template library for linear algebra and scientific computing. It aims towards a good balance between speed and ease of use, has a syntax deliberately close to Matlab, and is useful for algorithm development directly in C++, or quick conversion of research code into production environments. RcppArmadillo integrates this library with the R environment and language–and is widely used by (currently) 1092 other packages on CRAN, downloaded 30.1 million times (per the partial logs from the cloud mirrors of CRAN), and the CSDA paper (preprint / vignette) by Conrad and myself has been cited 545 times according to Google Scholar.

This release brings bugfix upstream release 12.6.1. Conrad release 12.6.0 when CRAN went on summer break. I rolled it up ran the full reverse-depenency check against the now more than 1000 packages. And usage from one those revealed a corner-case bug (of not always ‘flattening’ memory for sparse matrices to zero values) so 12.6.1 followed. This is what was uploaded today. And as I prepared it earlier in the week as CRAN reopened, Conrad released a new 12.6.2. However, its changes are only concerned with settings for Armadillo-internal use of its random number generators (RNGs). And as RcppArmadillo connects Armadillo to the RNGs provided by R, the upgrade does not affect R users at all. However it is available in the github repo, in the Rcpp drap repo and at r-universe.

The set of changes for this RcppArmadillo release follows.

Changes in RcppArmadillo version (2023-07-26)

  • Upgraded to Armadillo release 12.6.1 (Cortisol Retox)

    • faster multiplication of dense vectors by sparse matrices (and vice versa)

    • faster eigs_sym() and eigs_gen()

    • faster conv() and conv2() when using OpenMP

    • added diags() and spdiags() for generating band matrices from set of vectors

Courtesy of my CRANberries, there is a [diffstat report relative to previous release]. More detailed information is on the RcppArmadillo page. Questions, comments etc should go to the rcpp-devel mailing list off the Rcpp R-Forge page.

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This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

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