通过RInside了解将犰狳矩阵传递给R函数

Question

我试图通过RInside在C++中使用R. 我无法将犰狳矩阵传递给R并返回结果.下面我能够从R库函数返回结果,但是我得到了错误的结果.我正在使用moment包中的skewness函数作为示例,它在R中应该起作用.我检查了来自RInside的示例,我仍然不确定如何使用RcppArmadillo.如何将c ++中的犰狳矩阵正确传递给R？

    #include <RInside.h>                   
    #include <RcppArmadillo.h>

    using namespace std;
    using namespace arma;

    int main(int argc, char *argv[]) {
        RInside R(argc, argv);  


        string R_libs = "suppressMessages(library(moments));";

        R.parseEvalQ(R_libs);

        mat A = randu<mat>(5,5);

        R["A"] = A;

        string R_skewness = "B <- skewness(A);";
        //this fails
        mat B = Rcpp::as<mat>(R.parseEval(R_skewness)); //terminate called after throwing an instance of 'Rcpp::not_a_matrix'   

        //this works but wrong
        mat B = Rcpp::as<vec>(R.parseEval(R_skewness)); // returns only 1 number, should be 5 ( 1 for each columnn), same result if i change mat B to vec B
        exit(0);
 }

Answer 1

我们实现的方式as<mat>要求您传递的R对象是一个矩阵.在你的例子中B是一个向量:

> A <- matrix( runif(25), ncol = 5)
> A
           [,1]      [,2]       [,3]       [,4]      [,5]
[1,] 0.19215339 0.5857249 0.14345222 0.32154176 0.6162155
[2,] 0.95753898 0.9618379 0.06239842 0.06200197 0.7044018
[3,] 0.33575790 0.1372804 0.03027635 0.62662467 0.9778451
[4,] 0.16504957 0.1919765 0.49176372 0.94841456 0.2914772
[5,] 0.01570709 0.8055231 0.51218581 0.79562809 0.6939380
> B <- skewness( A )
> B
[1]  1.15196587 -0.04547576  0.32186257 -0.30788111 -0.29251009

转换为arma::vecI时,不会重现您看到的行为.在arma::vec有3个要素:

require( RcppArmadillo )    ## and make sure you have Rcpp 0.10.0 or later

sourceCpp( code = '
// [[Rcpp::depends("RcppArmadillo")]]

#include <RcppArmadillo.h>

using namespace arma ; 
using namespace Rcpp ;

// [[Rcpp::export]]
List foo( NumericVector x){
    vec B = Rcpp::as<vec>(x); 

    return List::create( 
        _["nrows"] = B.n_rows,
        _["ncols"] = B.n_cols
    ) ;

}
')
foo( c(1, 2, 3 ) )
# $nrows
# [1] 3
# 
# $ncols
# [1] 1