Sparse matrix in Armadillo

Dirk Eddelbuettel and Binxiang Ni — written Dec 25, 2012 — updated Oct 18, 2018 — source

The Matrix package in R supports sparse matrices, and we can use the S4 class support in Rcpp to attach the different component row indices, column pointers and value which can then be used to initialize an Armadillo sparse matrix.

Let’s start by creating a sparse matrix.

suppressMessages({
  library(methods)
  library(Matrix)
})
i <- c(1,3:8)
j <- c(2,9,6:10)
x <- 7 * (1:7)
A <- sparseMatrix(i, j, x = x)
print(A)

8 x 10 sparse Matrix of class "dgCMatrix"
                             
[1,] . 7 . . .  .  .  .  .  .
[2,] . . . . .  .  .  .  .  .
[3,] . . . . .  .  .  . 14  .
[4,] . . . . . 21  .  .  .  .
[5,] . . . . .  . 28  .  .  .
[6,] . . . . .  .  . 35  .  .
[7,] . . . . .  .  .  . 42  .
[8,] . . . . .  .  .  .  . 49

The following C++ function accesses the corresponding slots of the sparseMatrix object, and creates a sp_mat Armadillo object.

#include <RcppArmadillo.h>
// [[Rcpp::depends(RcppArmadillo)]]

using namespace Rcpp ;

// [[Rcpp::export]]
void convertSparse(S4 mat) {

    // obtain dim, i, p. x from S4 object
    IntegerVector dims = mat.slot("Dim");
    arma::urowvec i = Rcpp::as<arma::urowvec>(mat.slot("i"));
    arma::urowvec p = Rcpp::as<arma::urowvec>(mat.slot("p"));
    arma::vec x     = Rcpp::as<arma::vec>(mat.slot("x"));

    int nrow = dims[0], ncol = dims[1];

    // use Armadillo sparse matrix constructor
    arma::sp_mat res(i, p, x, nrow, ncol);
    Rcout << "SpMat res:\n" << res << std::endl;
}

Running this example shows the same matrix printed to stdout by Armadillo.

convertSparse(A)

SpMat res:
[matrix size: 8x10; n_nonzero: 7; density: 8.75%]

     (0, 1)          7.0000
     (3, 5)         21.0000
     (4, 6)         28.0000
     (5, 7)         35.0000
     (2, 8)         14.0000
     (6, 8)         42.0000
     (7, 9)         49.0000

By now a full eleven types of sparse matrices are supported for automatic conversion by RcppArmadillo. You can just pass one of these eleven types of sparse matrices from R to RcppArmadillo. It will be converted automatically to a sp_mat object.

By the way, back in 2012 when this page was first written, we used the method below to create a sp_mat Armadillo object. But these days arma::memory::acquire_chunked is deprecated and should not be used, we are just showing this to illustrate access to elements of a S4 object.

#include <RcppArmadillo.h>
// [[Rcpp::depends(RcppArmadillo)]]

using namespace Rcpp ;

// [[Rcpp::export]]
void convertSparse2(S4 mat) {         // slight improvement with two non-nested loops

    IntegerVector dims = mat.slot("Dim");
    arma::urowvec i = Rcpp::as<arma::urowvec>(mat.slot("i"));
    arma::urowvec p = Rcpp::as<arma::urowvec>(mat.slot("p"));
    arma::vec x     = Rcpp::as<arma::vec>(mat.slot("x"));

    int nrow = dims[0], ncol = dims[1];
    arma::sp_mat res(nrow, ncol);

    // create space for values, and copy
    arma::access::rw(res.values) = arma::memory::acquire_chunked<double>(x.size() + 1);
    arma::arrayops::copy(arma::access::rwp(res.values), x.begin(), x.size() + 1);

    // create space for row_indices, and copy
    arma::access::rw(res.row_indices) = arma::memory::acquire_chunked<arma::uword>(i.size() + 1);
    arma::arrayops::copy(arma::access::rwp(res.row_indices), i.begin(), i.size() + 1);

    // create space for col_ptrs, and copy
    arma::access::rw(res.col_ptrs) = arma::memory::acquire<arma::uword>(p.size() + 2);
    arma::arrayops::copy(arma::access::rwp(res.col_ptrs), p.begin(), p.size() + 1);

    // important: set the sentinel as well
    arma::access::rwp(res.col_ptrs)[p.size()+1] = std::numeric_limits<arma::uword>::max();

    // set the number of non-zero elements
    arma::access::rw(res.n_nonzero) = x.size();

    Rcout << "SpMat res:\n" << res << std::endl;
}

tags: armadillo matrix sparse

Extending R with C++ and Fortran — Dirk Eddelbuettel and JBrandon Duck-Mayr
Benchmarking Rcpp code with RcppClock — Zach DeBruine
Simulation Smoother using RcppArmadillo — Tomasz Woźniak