Very nice, thanks Dirk and Jeff Well i think i will accept a RObject and if it's a DataFrame I convert to Matrix and it continue working
I will benchmark the differences to understand it better. --- Other two doubt and I think that's all: 1) If dataset is too big (size is bigger than ram) is there a standard lib to use it, or should i consider that using dataframe/matrix types will work? 2) I never used GPU in R, I used keras with python, dash and others python libs that handle bigdata / gpu math. Is there something related to GPU and RCpp/R? Any standard to consider? Thanks again! Em dom., 1 de mai. de 2022 às 03:05, Dirk Eddelbuettel <e...@debian.org> escreveu: > > > This is not a well-posed Rcpp question as > > - matrix and data.frame are _fundamentally_ two different data types > > - matrix being _one_ and only one storage type, or class, stored > as one vector with dimension attribute of size two for rows and cols; > this makes it _efficient_ and you will see a matrix type used quite a bit > in internal R functions > > - data.frame being a special case of the catch-all type list with each > column being of same length but possibly different types -- and for that > reason we do not have too much tooling for this 'list of vectors' in Rcpp > besides the basics > > So in short you may want to work out first what you want you algorithm to be > and maybe use higher-level converters in R to accomodate. > > Dirk > > -- > dirk.eddelbuettel.com | @eddelbuettel | e...@debian.org -- Roberto Spadim SPAEmpresarial - Software ERP/Scada Eng. Automação e Controle, Eng. Financeira _______________________________________________ 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
