问题
I have a program in which I need to calculate repeatedly the column means of each slice of a cube X(nRow, nCol, nSlice)
in Rcpp, with the resulting means forming a matrix M(nCol, nSlice)
. The following code produced an error:
#include <RcppArmadillo.h>
// [[Rcpp::depends(RcppArmadillo)]]
using namespace Rcpp;
using namespace arma;
// [[Rcpp::export]]
mat cubeMeans(arma::cube X){
int nSlice = X.n_slices;
int nCol = X.n_cols;
int nRow = X.n_rows;
arma::vec Vtmp(nCol);
arma::mat Mtmp(nRow, nCol);
arma::mat Means(nCol, nSlice);
for (int i = 0; i < nSlice; i++){
Mtmp = X.slice(i);
for(int j = 0; j < nCol; j++){
Vtmp(j) = sum(Mtmp.col(j))/nRow;
}
Means.col(i) = Vtmp;
}
return(wrap(Means));
}
'/Rcpp/internal/Exporter.h:31:31: error: no matching function for call to 'arma::Cube::Cube(SEXPREC*&)'
I couldn't quite figure it out. I didn't get the error when the input of the function was a matrix (and returned a vector). However, I included the above function as part of my main program i.e.
#include <RcppArmadillo.h>
// [[Rcpp::depends(RcppArmadillo)]]
using namespace Rcpp;
using namespace arma;
mat cubeMeans(arma::cube X){
int nSlice = X.n_slices;
...
return(Means);
}
// [[Rcpp::export]]
main part of program
The program compiled successfully, but it is painfully slow (almost as slow as the R version of the program using colMeans
). Is there a better way to calculate column means on a cube, and why am I getting that compilation error?
I'd appreciate any help.
Regards,
回答1:
I also received this error when attempting to use an arma::cube
as an Rcpp function parameter. Based on the compiler error, I believe this is because there is no † After reading a couple of related examples online, it looks like the typical workaround is to read in your R Rcpp::wrap<arma::cube>
currently defined (which is needed to handle the R object you would pass to the function).array
as a NumericVector
, and since it retains its dims
attribute, use these to set your arma::cube
dimensions. Despite the fact that there is an extra step or two required to account for the missing †, the Armadillo version I put together seems to be quite a bit faster than my R solution:wrap
specialization
#include <RcppArmadillo.h>
// [[Rcpp::depends(RcppArmadillo)]]
// [[Rcpp::export]]
arma::mat cube_means(Rcpp::NumericVector vx) {
Rcpp::IntegerVector x_dims = vx.attr("dim");
arma::cube x(vx.begin(), x_dims[0], x_dims[1], x_dims[2], false);
arma::mat result(x.n_cols, x.n_slices);
for (unsigned int i = 0; i < x.n_slices; i++) {
result.col(i) = arma::conv_to<arma::colvec>::from(arma::mean(x.slice(i)));
}
return result;
}
/*** R
rcube_means <- function(x) t(apply(x, 2, colMeans))
xl <- array(1:10e4, c(100, 100 ,10))
all.equal(rcube_means(xl), cube_means(xl))
#[1] TRUE
R> microbenchmark::microbenchmark(
"R Cube Means" = rcube_means(xl),
"Arma Cube Means" = cube_means(xl),
times = 200L)
Unit: microseconds
expr min lq mean median uq max neval
R Cube Means 6856.691 8204.334 9843.7455 8886.408 9859.385 97857.999 200
Arma Cube Means 325.499 380.540 643.7565 416.863 459.800 3068.367 200
*/
where I am taking advantage of the fact that the arma::mean
function overload for arma::mat
s will calculate column means by default (arma::mean(x.slice(i), 1)
would give you the row means of that slice).
Edit: † On second thought, I'm not really sure if this has to do with Rcpp::wrap
or not - but the issue seems to be related to a missing Exporter<>
specialization for arma::cube
- line 31 of Rcpp's Exporter.h:
template <typename T>
class Exporter{
public:
Exporter( SEXP x ) : t(x){}
inline T get(){ return t ; }
private:
T t ;
} ;
Regardless, NumericVector
/ setting dimensions approach I used seems to be functional solution for now.
Based on the output dimensions you described in your question, I assumed you wanted each column of the resulting matrix to be a vector of column means of the corresponding array slice (column 1 = column means of slice 1, etc...), i.e.
R> x <- array(1:27, c(3, 3, 3))
R> rcube_means(x)
[,1] [,2] [,3]
[1,] 2 11 20
[2,] 5 14 23
[3,] 8 17 26
R> cube_means(x)
[,1] [,2] [,3]
[1,] 2 11 20
[2,] 5 14 23
[3,] 8 17 26
but it would be trivial for you to alter this if needed.
来源:https://stackoverflow.com/questions/30969799/column-means-3d-matrix-cube-rcpp