similar to: R Lapack – why a subset?

Peter, Is there not already a significant maintenance burden from cherry-picking routines? From my own experience (https://bugs.r-project.org/bugzilla/show_bug.cgi?id=16482 <https://bugs.r-project.org/bugzilla/show_bug.cgi?id=16482>) this is a painful process. And while users may not call these complex routines directly, R is often used as a front-end for libraries that do, so

I'm not too happy with this either, but I believe the reason is that there would be a significant extra maintenance burden consisting of things that is not being used by R itself. In particular, complex math routines are little used and have historically caused a number of issues with correct argument and return-value passing. Notice that it is a bit of a can of worms involving matching up C

Le 10/01/2023 ? 11:37, Serguei Sokol a ?crit?: > Le 10/01/2023 ? 10:44, RICHET Yann a ?crit?: >> Dear R-devel people, >> >> We are working to submit a package which is mainly a binding over a >> C++ lib (https://github.com/libKriging) using armadillo. >> It is _not_ a standard RcppArmadillo package, because we also had to >> provide a python binding... so

Thank you for your answer. In facts, 10 threads are asked by armadillo for some LinAlg, which backs to two threads as warned. But I cannot imagine this costs so much time just for that... A deeper analysis of time spent seems to point that a large time was mainly spent on testthat and Rcpp dependencies compilation... But other recent packages depending on these also are not spending so much time.

Dear all, I am testing a simple C++ function that takes a double matrix as argument and which uses routines provided by the C++ Armadillo package. I am aware of the nice capabilities of Rcpp and RcppArmadillo which helps simplifying a lot and that I have already successfully tested. However, I had a hard time trying to figure out how the coercion from a REALSPX matrix to an arma::mat =

Dear R-devel people, We are working to submit a package which is mainly a binding over a C++ lib (https://github.com/libKriging) using armadillo. It is _not_ a standard RcppArmadillo package, because we also had to provide a python binding... so there is a huge layer of cmake & scripting to make it work with a standard armadillo (but using same version that RcppArmadillo). It seems now

Hi there, I'm trying to install the package RcppArmadillo in my R 2.11.1 which I installed and regularly update via Ubuntu's repositories. When I try to install RcppArmadillo from CRAN I get: > install.packages('RcppArmadillo', lib='~/myRlibs') [...] g++ -shared -o RcppArmadillo.so RcppArmadillo.o fastLm.o -L/home/matias/myRlibs/Rcpp/lib -lRcpp

Le 10/01/2023 ? 10:44, RICHET Yann a ?crit?: > Dear R-devel people, > > We are working to submit a package which is mainly a binding over a C++ lib (https://github.com/libKriging) using armadillo. > It is _not_ a standard RcppArmadillo package, because we also had to provide a python binding... so there is a huge layer of cmake & scripting to make it work with a standard armadillo

Hi, I can not install packages from source which links to RcppArmadillo on Ubuntu 20.04 (after upgrading from 18.04). The following problem occurs: ** testing if installed package can be loaded from temporary location Error: package or namespace load failed for 'myPackage' in dyn.load(file, DLLpath = DLLpath, ...): unable to load shared object

Is there anyway with some experience in using armadillo in R C++ extensions? My problem is the following: I programmed a function in a header looking like #include <armadillo> inline arma::vec foo(input) { ... do something return an arma::vec object } compiling this via R CMD INSTALL packagename (PKG_CXXFLAGS = -I/folder/of/armadillo and armadillo_bits in my package) I get the

What is the RcppArmadillo way to make binomial draws from a vector of probs, similar to what rbinom does in R? Thanx! -- View this message in context: http://r.789695.n4.nabble.com/rbinom-in-RcppArmadillo-tp4683593.html Sent from the R devel mailing list archive at Nabble.com.

Dirk, thank you a thousand times. Indeed, src/Makevars was wrong. I modified Makevars so that now looks like the below and the package now compiled and linked properly. CXX_STD = CXX11 PKG_LIBS += $(SHLIB_OPENMP_CXXFLAGS) $(LAPACK_LIBS) $(BLAS_LIBS) $(FLIBS) $(shell ${R_HOME}/bin/Rscript -e "RcppParallel::RcppParallelLibs()") PKG_CXXFLAGS = $(SHLIB_OPENMP_CXXFLAGS) -I../inst/include

On Thu, Apr 14, 2011 at 7:02 PM, <rcpp-devel-request at r-forge.wu-wien.ac.at> wrote: > I was able to write a very short C++ function using the Rcpp package > that provided about a 1000-fold increase in speed relative to the best > I could do in R. ?I don't have the script on this computer so I will > post it tomorrow when I am back on the computer at the office. > >

Dear R-devel: The Cluster administrators at KU got enthusiastic about testing R-3.2.2 with Intel MKL when I asked for some BLAS integration. Below I forward a performance report, which is encouraging, and thought you would like to know the numbers. Appears to my untrained eye there are some extraordinary speedups on Cholesky decomposition, determinants, and matrix inversion. They had

===== Summary ===== Version 0.9.0 of the Rcpp package is now on CRAN and its mirrors. This release marks another step in the development of the package, and a few key points are highlighted below. More details are in the NEWS and ChangeLog files included in the package. ===== Overview ===== Rcpp is an R package and associated C++ library that facilitates integration of C++ code in R

===== Summary ===== Version 0.9.0 of the Rcpp package is now on CRAN and its mirrors. This release marks another step in the development of the package, and a few key points are highlighted below. More details are in the NEWS and ChangeLog files included in the package. ===== Overview ===== Rcpp is an R package and associated C++ library that facilitates integration of C++ code in R

DeaR list, I happily use eigen() to compute the eigenvalues and eigenvectors of a fairly large matrix (200x200, say), but it seems over-killed as its rank is limited to typically 2 or 3. I sort of remember being taught that numerical techniques can find iteratively decreasing eigenvalues and corresponding orthogonal eigenvectors, which would provide a nice alternative (once I have the

Dear list, I read in ?plotmath that I can use bgroup to draw scalable delimiters such as [ ] and ( ). The same technique fails with < > however, and I cannot find a workaround, grid.text(expression(bgroup("<",atop(x,y),">"))) Error in bgroup("<", atop(x, y), ">") : invalid group delimiter Regards, baptiste sessionInfo() R version

Dear list, I read in ?plotmath that I can use bgroup to draw scalable delimiters such as [ ] and ( ). The same technique fails with < > however, and I cannot find a workaround, grid.text(expression(bgroup("<",atop(x,y),">"))) Error in bgroup("<", atop(x, y), ">") : invalid group delimiter Regards, baptiste sessionInfo() R version

Dear list, subset has a 'drop' argument that I had often mistaken for the one in [.factor which removes unused levels. Clearly it doesn't work that way, as shown below, d <- data.frame(x = factor(letters[1:15]), y = factor(LETTERS[1:3])) s <- subset(d, y=="A", drop=TRUE) str(s) 'data.frame': 5 obs. of 2 variables: $ x: Factor w/ 15 levels