[Rcpp-devel] [RcppArmadillo] Result of Rcpp Wrap() for Sparse Matrix

[Douglas Bates]

On Wed, Jun 14, 2017 at 9:06 AM Serguei Sokol <serguei.sokol at gmail.com>
wrote:

> Le 14/06/2017 à 15:21, Douglas Bates a écrit :
> >
> >
> > On Wed, Jun 14, 2017 at 3:59 AM Serguei Sokol <serguei.sokol at gmail.com
> <mailto:serguei.sokol at gmail.com>> wrote:
> >
> >     Le 13/06/2017 à 18:24, Douglas Bates a écrit :
> >      > On Tue, Jun 13, 2017 at 10:56 AM Binxiang Ni <
> binxiangni at gmail.com <mailto:binxiangni at gmail.com> <mailto:
> binxiangni at gmail.com
> >     <mailto:binxiangni at gmail.com>>> wrote:
> >      >
> >      >     Hi,
> >      >
> >      >     I am working on fixing sparse matrix conversion for
> RcppArmadillo. Now a problem comes up to me: what kind of sparse matrix is
> expected to pass from
> >      >     Armadillo to R? That is, what should the result of wrap() be?
> dgCMatrix(if logical, lgCMatrix or ngCMatrix)  or their original type?
> >      >
> >      >
> >      > What do you mean by "their original type"?
> >      >
> >      > It seems that the correspondence is
> >      > Armadillo           Matrix package
> >      > sp_mat       <=> dgCMatrix
> >      > sp_cx_mat <=> zgCMatrix
> >      > sp_imat      <=> igCMatrix
> >     I would also consider the format used in a package slam.
> >     It simply stores the indexes and non-zero values in a triplet
> (i,j,v).
> >
> >
> > That is the format of the dgTMatrix class from the Matrix package for R
> but not, as far as I can tell, in Armadillo.  A brief glance at the
> Armadillo
> > documentation indicates that sparse matrices are always in the
> compressed sparse column (CSC) format.
> Indeed, but nothing prevents Binxiang to develop a wrap() that will convert
> armadillo format to one or many of R formats, right?
>

Why? Is there a reason for doing type conversion from the dgCMatrix format
to another format in an Rcpp wrap function instead of with the existing
functions from the Matrix package?

Bear in mind that dgCMatrix is an efficient format both in terms of the
amount of memory required  (that's the "compressed" part of the name) and
in terms of performing operations with the matrix.  Most operations on
sparse matrices stored in the triplet format start by creating a CSC or CSR
(compressed sparse row) form of the matrix anyway.
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