armadillo

I have a large existing Xcode project and now I want to add the armadillo library to it . http://arma.sourceforge.net/ I have downloaded it (with macports) and got it working using Cmake (just as a C++ terminal app). I am not using Cmake for my large project (iPad app) so I have tried to link the library. I looked in the xcode-project file that I got working with cmake and added the same to my project. Added: header search path: /opt/local/include Library search path: /opt/local/lib Other linker flags: -larmadillo I also added the libarmadillo.3.4.0.dylib to "link library with binaries" ld:

How can I convert from an Armadillo Matrix to an Eigen MatrixXd and vice versa? I have nu as an arma::vec of size N , z as arma::mat of dimension N x 3 . I want to compute a matrix P such as the entry P_ij is Pij=exp(nu(i) + nu(j) + z.row(j)*z.row(j))) Thus I used this code int N=z.n_rows; mat P= exp(nu*ones(1,N) + one(N,1)*(nu.t()) + z*(z.t())); But the computation takes too long. In particular, for N = 50,000 the run time is far to high. It seems that using Eigen can be faster. But my matrix are Armadillo. How can I use Eigen operations ? Or how can I do this operation faster. Using

I have prepared a package in R by using RcppArmadillo and OpenMP libraries and following commands: RcppArmadillo.package.skeleton("mypackage") compileAttributes(verbose=TRUE) Also, in the DESCRIPTION file I added: Imports: Rcpp (>= 0.12.8), RcppArmadillo LinkingTo:Rcpp, RcppArmadillo Depends: RcppArmadillo and in the NAMESPACE file I added: import(RcppArmadillo) importFrom(Rcpp, evalCpp) Then I run the following codes in cmd : R CMD build mypackage R CMD INSTALL mypackage.tar.gz I build and install the package in my computer and I use it now. But my colleges and friends are not able to install

My task it to rewrite a R function in C++ to accelerate the while loops. All R codes has been rewritten in the help of Rcpp and Armadillo except the .Fortran() . I try to use Rinside to at first and it works at a very slow speed as Dirk indicated. (It is expensive for data to go through R -> C++ -> R -> Fortran) Since I don't want to rewrite the Fortran codes in C++ and vice versa, it looks natural to accelerate the programs by linking C++ directly to Fortran: R -> C++ -> Fortran. // [[Rcpp::depends(RcppArmadillo)]] #include <RcppArmadillo.h> using namespace Rcpp; extern "C"{ List f_(int *n

I am trying to convert RcppArmadillo vector (e.g. arma::colvec ) to a Rcpp vector ( NumericVector ). I know I can first convert arma::colvec to SEXP and then convert SEXP to NumericVector (e.g. as<NumericVector>(wrap(temp) ), assuming temp is an arma::colvec object). But what is a good way to do that? I want to do that simply because I am unsure if it is okay to pass arma::colvec object as a parameter to an Rcpp::Function object. I was trying to Evaluate a Rcpp::Function with argument arma::vec , it seems that it takes the argument in three forms without compilation errors. That is, if f is a

I did a comparison between blitz++, armadillo, boost::MultiArray with the following code (borrowed from an old post ) #include <iostream> using namespace std; #include <windows.h> #define _SCL_SECURE_NO_WARNINGS #define BOOST_DISABLE_ASSERTS #include <boost/multi_array.hpp> #include <blitz/array.h> #include <armadillo> int main(int argc, char* argv[]) { const int X_SIZE = 1000; const int Y_SIZE = 1000; const int ITERATIONS = 100; unsigned int startTime = 0; unsigned int endTime = 0; // Create the boost array //------------------Measure boost Loop------------------------------------------ {

We have been using the sample function from RcppArmadillo to randomly sample a NumericVector object. However, we have noticed that it isn't possible to use the same function on Armadillo types ( vec or uvec ). We have looked at the function definitions from the sample.h file and it looks like a templated function that should be able to work with these types, but we haven't been able to figure out how to make it work with Armadillo classes without doing a lot of conversions to and from the NumericVector or IntegerVector types from the Rcpp library. For example, we have this function written in

I know the problem I have is a thread-safety issue. As the code I have now will execute with 'seThreadOptions(1)'. My question is what would be a good practice to overcome this. I know this: Threadsafe function pointer with Rcpp and RcppParallel via std::shared_ptr Will come into play somehow. And I have also been thinking/playing around with making the internal function part of the structure for the parallel worker. Realistically, I am calling two internal functions and I would like one to be variable and the other to be constant, this tends me to think that i will need 2 solutions. The error