Hi James,
On 16 August 2013 at 12:57, James Li wrote:
| Hi Dirk,
|
| N could be anywhere between 3-10.
Eek. 10 is a lot.
| Thanks! I will definitely look into how to do those.
|
| Also, if
|
| Rcpp::NumericVector vec3 =Rcpp::NumericVector( Rcpp::Dimension(4, 5, 6));
|
| In this case, how do we access element vec3[1,2,3]?
Well a) you cannot use [] to index, only () as the [] only allows a single
index (and , is a special operator for C/C++). Romain already sent you a
first cut at something homegrown.
Alternatively, if you find a matrix library dealing with N up to 10 ... you
may want to consider writing glue code to access it from R via Rcpp.
Cheers, Dirk
| Thanks again,
| James
|
| On Friday, August 16, 2013, Dirk Eddelbuettel wrote:
|
|
| Hi James,
|
| On 16 August 2013 at 11:59, James Li wrote:
| | Dear Dirk and Rcpp-devel members,
| |
| | I am currently passing a multidimensional (N > 2) array (i.e.
| | array(NA, dim = rep(3,5)) ) from R via Rcpp using
|
|
| How big is 'N' going to be?
|
| | "in C++:"
| |
| | //[[Rcpp::export]]
| | Rcpp::List check_arrayC (Rcpp::NumericVector x, Rcpp::IntegerVector
| modes){
| | //do stuff to x
| | return Rcpp::List::create(Rcpp::_["data"] = x, Rcpp::_["modes"] =
| modes);
| | }
| |
| |
| | "in R:"
| |
| | a <- array(1:32, dim=rep(2,5))
| | b <- check_arrayC(a, dim(a))
| |
| | While I know that a multidimensional array is stored as a contiguous
| | array internally, is there currently a more natural/efficient way to
| | pass it back and forth within Rcpp?
| |
| | Also from Dirk's book, it seems that an instance of
| | Rcpp::NumericVector can be instantiated into a multidimensional array
| | via
| |
| | Rcpp::NumericVector vec3 =Rcpp::NumericVector( Rcpp::Dimension(4, 5,
6));
| |
| | In this case, how do we access element vec3[1,2,3]?
| |
| | Some background about what I am trying to do: I would like to create a
| | multidimensional array wrapper class around the base R multi-way array
| | class. I would also like to be able to pass this multidimensional
| | array via Rcpp to do all the heavy-lifting in c++. Ideally, I could
| | also convert the mda into a Boost::multi_array.
|
| For a moderately-sized project (at work, not open source) I had a very
good
| experience using Armadillo 'cubes' (3-d matrices) which I occassionally
| stored in 'fields' (which I though of as lists of such cubes). I think in
| most (all?) cases I reduces data to 2-d matrices before returning that
| R. That worked great.
|
| Beyond that ... you are on your own as there is very little C++ support
| already useable by Rcpp. You'd have to write custom as<>() and wrap()
| methods (which is not hard and may well be worth it).
|
| Cheers, Dirk
|
| | Thanks in advance for any help.
| |
| | -James
| |
| | --
| | James Li | Ph.D. Candidate | http://jamesyili.com/
| | Dept. of Statistical Science | Cornell University
| | _______________________________________________
| | 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
|
| --
| Dirk Eddelbuettel | e...@debian.org | http://dirk.eddelbuettel.com
|
|
|
| --
| James Li | Ph.D. Candidate | http://jamesyili.com/
| Dept. of Statistical Science | Cornell University
--
Dirk Eddelbuettel | e...@debian.org | http://dirk.eddelbuettel.com
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