On this theme, the following proved sufficient to ingest and
convert sparse csv without column headers or row names:
#include "RcppArmadillo.h"
using namespace Rcpp;
// [[Rcpp::depends(RcppArmadillo)]]
// [[Rcpp::export]]
List parse_sparse_csv_impl(SEXP fname) {
using namespace Rcpp;
std::string v = Rcpp::as<std::string>(fname);
arma::sp_mat D;
D.load(v, arma::csv_ascii);
return Rcpp::List::create(Rcpp::Named("sp")=D);
}
On Mon, May 10, 2021 at 11:19 PM Dirk Eddelbuettel <e...@debian.org> wrote:
>
> Vincent,
>
> In the broad terms of the question the best answer may be a simple "sure".
> More seriously, there have been many approaches. Consider for example the
> recent Rcpp Gallery post lead by Zach (with some edits by me):
> https://gallery.rcpp.org/articles/sparse-matrix-class/
>
> It's focus on not copying <i,p,x> again if we already have them as R
> vectors,
> which is a fair point. If the goal is to get to SuperLU via (Rcpp)Armadillo
> then I do not think you can avoid the (internal) copies. As always, the
> answer may be "it depends".
>
> Hope this helps, happy to refine, Dirk
>
> --
> https://dirk.eddelbuettel.com | @eddelbuettel | e...@debian.org
>
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