如何并排显示数据(How to display the data side by side)

 使用armadillo的.memptr()类成员函数，我们可以提取内存指针。 从这里，我们可以使用Eigen的Map<T>()构造函数来创建一个特征矩阵。 
 
 现在，我们可以使用.data()成员函数从Eigen矩阵中提取一个指向Eigen内存结构的点。 然后，使用arma::mat的高级构造函数选项，我们可以创建一个armadillo 矩阵 。 
 
 例如： 
 
#include <RcppArmadillo.h>
#include <RcppEigen.h>

// [[Rcpp::depends(RcppEigen)]]

// [[Rcpp::depends(RcppArmadillo)]]

// [[Rcpp::export]]
Eigen::MatrixXd example_cast_eigen(arma::mat arma_A) {

  Eigen::MatrixXd eigen_B = Eigen::Map<Eigen::MatrixXd>(arma_A.memptr(),
                                                        arma_A.n_rows,
                                                        arma_A.n_cols);

  return eigen_B;
}

// [[Rcpp::export]]
arma::mat example_cast_arma(Eigen::MatrixXd eigen_A) {

  arma::mat arma_B = arma::mat(eigen_A.data(), eigen_A.rows(), eigen_A.cols(),
                               false, false);

  return arma_B;
}

/***R
(x = matrix(1:4, ncol = 2))
example_cast_eigen(x)
example_cast_arma(x)
*/
 
 结果： 
 
(x = matrix(1:4, ncol = 2))
#      [,1] [,2]
# [1,]    1    3
# [2,]    2    4

example_cast_eigen(x)
#      [,1] [,2]
# [1,]    1    3
# [2,]    2    4

example_cast_arma(x)
#      [,1] [,2]
# [1,]    1    3
# [2,]    2    4
 
 快速说一句：如果您使用的是Eigen的映射函数，那么您应该自动对Armadillo矩阵进行更改（反之亦然），例如 
 
#include <RcppArmadillo.h>
#include <RcppEigen.h>

// [[Rcpp::depends(RcppEigen)]]

// [[Rcpp::depends(RcppArmadillo)]]

// [[Rcpp::export]]
void map_update(Eigen::MatrixXd eigen_A) {

  Rcpp::Rcout << "Eigen Matrix on Entry: " << std::endl << eigen_A << std::endl;

  arma::mat arma_B = arma::mat(eigen_A.data(), eigen_A.rows(), eigen_A.cols(),
                               false, false);

  arma_B(0, 0) = 10;
  arma_B(1, 1) = 20;

  Rcpp::Rcout << "Armadill Matrix after modification: " << std::endl << arma_B << std::endl;

  Rcpp::Rcout << "Eigen Matrix after modification: " << std::endl << eigen_A << std::endl;
}
 
 跑： 
 
map_update(x)
 
 输出： 
 
Eigen Matrix on Entry: 
1 3
2 4

Armadill Matrix after modification: 
   10.0000    3.0000
    2.0000   20.0000

Eigen Matrix after modification: 
10  3
 2 20

Using armadillo's .memptr() class member function, we are able to extract the memory pointer. From here, we can use Eigen's Map<T>() constructor to create an Eigen matrix.
 
Now, we can go from the Eigen matrix using the .data() member function to extract a point to Eigen's memory structure. Then, using the advanced constructor options of arma::mat we can create an armadillo matrix.
 
For example:
 
#include <RcppArmadillo.h>
#include <RcppEigen.h>

// [[Rcpp::depends(RcppEigen)]]

// [[Rcpp::depends(RcppArmadillo)]]

// [[Rcpp::export]]
Eigen::MatrixXd example_cast_eigen(arma::mat arma_A) {

  Eigen::MatrixXd eigen_B = Eigen::Map<Eigen::MatrixXd>(arma_A.memptr(),
                                                        arma_A.n_rows,
                                                        arma_A.n_cols);

  return eigen_B;
}

// [[Rcpp::export]]
arma::mat example_cast_arma(Eigen::MatrixXd eigen_A) {

  arma::mat arma_B = arma::mat(eigen_A.data(), eigen_A.rows(), eigen_A.cols(),
                               false, false);

  return arma_B;
}

/***R
(x = matrix(1:4, ncol = 2))
example_cast_eigen(x)
example_cast_arma(x)
*/
 
Results: 
 
(x = matrix(1:4, ncol = 2))
#      [,1] [,2]
# [1,]    1    3
# [2,]    2    4

example_cast_eigen(x)
#      [,1] [,2]
# [1,]    1    3
# [2,]    2    4

example_cast_arma(x)
#      [,1] [,2]
# [1,]    1    3
# [2,]    2    4
 
One quick remark: If you are using Eigen's Mapping function, then you should automatically have the change in the Armadillo matrix (and vice versa), e.g.
 
#include <RcppArmadillo.h>
#include <RcppEigen.h>

// [[Rcpp::depends(RcppEigen)]]

// [[Rcpp::depends(RcppArmadillo)]]

// [[Rcpp::export]]
void map_update(Eigen::MatrixXd eigen_A) {

  Rcpp::Rcout << "Eigen Matrix on Entry: " << std::endl << eigen_A << std::endl;

  arma::mat arma_B = arma::mat(eigen_A.data(), eigen_A.rows(), eigen_A.cols(),
                               false, false);

  arma_B(0, 0) = 10;
  arma_B(1, 1) = 20;

  Rcpp::Rcout << "Armadill Matrix after modification: " << std::endl << arma_B << std::endl;

  Rcpp::Rcout << "Eigen Matrix after modification: " << std::endl << eigen_A << std::endl;
}
 
Run:
 
map_update(x)
 
Output: 
 
Eigen Matrix on Entry: 
1 3
2 4

Armadill Matrix after modification: 
   10.0000    3.0000
    2.0000   20.0000

Eigen Matrix after modification: 
10  3
 2 20