xtensor buffer adaptor for eigen VectorXd and MatrixXd

eigen_xtensor_buf.cpp

#include <stdexcept>
#include "xtensor/xarray.hpp"
#include "xtensor/xio.hpp"
#include "xtensor/xbuffer_adaptor.hpp"
#include "Eigen/Dense"

auto to_xarray(Eigen::VectorXd& in) {
  using buf = xt::xbuffer_adaptor<double>;
  using xbuf_arr = xt::xarray_container<buf, xt::layout_type::column_major, std::vector<std::size_t>>;

  std::size_t len = in.size();

  std::vector<std::size_t> shape = {len};
  std::vector<std::size_t> strides(1);
  // strides[0] = 1;
  xt::compute_strides(shape, xt::layout_type::column_major, strides);
  std::cout << "strides[0] = " << strides[0] << std::endl;

  auto arr = xbuf_arr(buf(in.data(), len), std::move(shape), std::move(strides));
  return arr;
}

auto to_xarray(Eigen::MatrixXd& in) {
  using buf = xt::xbuffer_adaptor<double>;
  using xbuf_arr = xt::xarray_container<buf, xt::layout_type::column_major, std::vector<std::size_t>>;

  std::size_t nrow = in.rows();
  std::size_t ncol = in.cols();

  std::vector<std::size_t> shape = {nrow, ncol};
  std::vector<std::size_t> strides(2);
  // strides[0] = 1;
  xt::compute_strides(shape, xt::layout_type::column_major, strides);
  std::cout << "strides[0] = " << strides[0] << std::endl;
  std::cout << "strides[1] = " << strides[1] << std::endl;

  auto arr = xbuf_arr(buf(in.data(), nrow*ncol), std::move(shape), std::move(strides));
  return arr;
}

int main() {

    Eigen::VectorXd myvec = Eigen::VectorXd::LinSpaced(10, 0.0, 0.9);
    auto arr = to_xarray(myvec);
    std::cout << arr << std::endl;
    std::cout << "\n\n" << myvec << "\n\n" << std::endl;

    auto my_data = myvec.data();
    std::cout << "my_data = " << my_data << std::endl;
    for (size_t i = 0; i < myvec.size(); i++) {
      std::cout << "my_data[" << i << "] = " << my_data[i] << std::endl;
    }

    std::cout << "\n\nMatrix example\n\n" << std::endl;

    Eigen::MatrixXd mymat = Eigen::MatrixXd::Random(3, 4);
    auto arr_mat = to_xarray(mymat);
    std::cout << arr_mat << std::endl;
    std::cout << "\n\n" << mymat << "\n\n" << std::endl;
}

output

strides[0] = 1
{ 0.      ,  0.1     ,  0.2     ,  0.3     ,  0.4     ,  0.5     ,
  0.6     ,  0.7     ,  0.8     ,  0.9     }


  0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9


my_data = 0x7fecbed00000
my_data[0] = 0
my_data[1] = 0.1
my_data[2] = 0.2
my_data[3] = 0.3
my_data[4] = 0.4
my_data[5] = 0.5
my_data[6] = 0.6
my_data[7] = 0.7
my_data[8] = 0.8
my_data[9] = 0.9


Matrix example


strides[0] = 1
strides[1] = 3
{{-0.999984, -0.0827  , -0.905911,  0.869386},
 {-0.736924,  0.065534,  0.357729, -0.232996},
 { 0.511211, -0.562082,  0.358593,  0.038833}}


 -0.999984 -0.0826997  -0.905911   0.869386
 -0.736924  0.0655345   0.357729  -0.232996
  0.511211  -0.562082   0.358593  0.0388327