On Wed, Feb 16, 2011 at 2:03 PM, <ken.willi...@thomsonreuters.com> wrote:
> On 2/16/11 12:18 PM, "Douglas Bates" <ba...@stat.wisc.edu> wrote: >>The dgCMatrix object is of an S4 class. It's best to use the S4 class >>from Rcpp so you can extract the slots as Rcpp::IntegerVector and >>Rcpp::NumericVector objects. Once you get them in that form the >>pointers are best obtained through the begin() method. > Thanks Doug. > I feel silly asking this, but could you please point me to the docs for > the S4 class? I assume that's the Rcpp::S4 class? I've seen it mentioned > various places (e.g. the Rcpp-introduction vignette) but I can't seem to > find a list of its methods & API. begin() is a method I'd never heard of, > I assume it returns a pointer to the first element of the vector? I decided that it would be simple enough to write a small package to show exactly how you would pass a dgCMatrix to an Rcpp-based C++ function and create a smat object. The package is at http://www.stat.wisc.edu/~bates/spSVD_1.0.tar.gz It manages to pass the values from the dgCMatrix object to the smat struct, although this was somewhat more difficult than I had anticipated because the smat structure uses long int and not int values. So if you look at SVD.cpp in that package you will see that I allocate std::vector<long> objects then copy the contents of the Rcpp::IntegerVector objects into them. There was one more "gotcha". There is a C function called "machar" defined in the las2.c file and there is one in the R API. The one in the R API wins because R is loaded before the dll for the package and the calls are not compatible. I changed the name of the one in las2.c to svd_machar. I'm currently running a test case > library(Matrix) Loading required package: lattice Attaching package: 'Matrix' The following object(s) are masked from 'package:base': det > library(spSVD) Loading required package: Rcpp Warning message: In loadNamespace(package, c(which.lib.loc, lib.loc), keep.source = keep.source) : package 'spSVD' contains no R code > data(KNex) > str(KNex$mm) Formal class 'dgCMatrix' [package "Matrix"] with 6 slots ..@ i : int [1:8755] 0 2 25 27 163 165 1258 1261 1276 1278 ... ..@ p : int [1:713] 0 13 17 26 38 43 52 56 61 67 ... ..@ Dim : int [1:2] 1850 712 ..@ Dimnames:List of 2 .. ..$ : NULL .. ..$ : NULL ..@ x : num [1:8755] 0.277 0.277 0.277 0.277 0.277 ... ..@ factors : list() > .Call("spSVD", KNex$mm, 713L) SOLVING THE [A^TA] EIGENPROBLEM NO. OF ROWS = 1850 NO. OF COLUMNS = 712 NO. OF NON-ZERO VALUES = 8755 MATRIX DENSITY = 0.66% MAX. NO. OF LANCZOS STEPS = 712 MAX. NO. OF EIGENPAIRS = 712 LEFT END OF THE INTERVAL = -1.00E-30 RIGHT END OF THE INTERVAL = 1.00E-30 KAPPA = 1.00E-06 but it is taking a long time. I don't know if it is a programming error or the wrong calling sequence or just a slow algorithm but it has been chugging away for 7 minutes. In constrast, it takes about 2 seconds to calculate the singular values of that matrix as a dense matrix > data(KNex) > mm1 <- as(KNex$mm, "matrix") > str(mm1) num [1:1850, 1:712] 0.277 0 0.277 0 0 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : NULL > system.time(dsvd <- La.svd(mm1, nu=0, nv=0)) user system elapsed 2.280 0.030 2.664 _______________________________________________ Rcpp-devel mailing list Rcpp-devel@lists.r-forge.r-project.org https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel
