How to convert an xarray to std::vector? - stdvector

Question

The docs make it quite clear on how to adapt a std::vector to a tensor object.
https://xtensor.readthedocs.io/en/latest/adaptor.html
std::vector<double> v = {1., 2., 3., 4., 5., 6. };
std::vector<std::size_t> shape = { 2, 3 };
auto a1 = xt::adapt(v, shape);
But how can you do it for the other way round?
xt::xarray<double> a2 = { { 1., 2., 3.} };
std::vector<double> a2vector = ?;

Answer 1

You can construct a std::vector from iterators. For your example:
std::vector<double> w(a1.begin(), a1.end());
The complete example then becomes:
#include <vector>
#include <xtensor/xadapt.hpp>
#include <xtensor/xio.hpp>
int main()
{
std::vector<double> v = {1., 2., 3., 4., 5., 6.};
std::vector<std::size_t> shape = {2, 3};
auto a1 = xt::adapt(v, shape);
std::vector<double> w(a1.begin(), a1.end());
return 0;
}
References:
std::vector.
Constructors of std::vector (number (5) is the one relevant here).
xtensor documentation section 1.7.1 Adapting std::vector

Answer 2

Unfortunately Tom de Geus' answer does not maintain dimensionality and hence transforms the xarray of shape {2, 3} into a vector of size 6.
I stepped over this question, when attempting to construct a nested vector in order to plot a xarray with matplotlibcpp. For me it turned out, that Eigen::Matrix.. is a way more suitable class for this purpose. For the 2 dimensional case, one can comfortable convert the Eigen::Matrix to a nested std::vector. For higher dimensions, its worth to have a look here.
Code
transforms xt::xarray to Eigen::MatrixXf to nested std::vector
#include "xtensor/xarray.hpp"
#include "xtensor/xio.hpp"
#include <Eigen/Dense>
//https://stackoverflow.com/questions/8443102/convert-eigen-matrix-to-c-array
Eigen::MatrixXf xarray_to_matrixXf(xt::xarray<float> arr)
{
auto shape = arr.shape();
int nrows = shape[0];
int ncols = shape[1];
Eigen::MatrixXf mat = Eigen::Map<Eigen::MatrixXf>(arr.data(), nrows, ncols);
return mat;
}
// https://stackoverflow.com/a/29243033/7128154
std::vector<std::vector<float>> matrixXf2d_to_vector(Eigen::MatrixXf mat)
{
std::vector<std::vector<float>> vec;
for (int i=0; i<mat.rows(); ++i)
{
const float* begin = &mat.row(i).data()[0];
vec.push_back(std::vector<float>(begin, begin+mat.cols()));
}
return vec;
}
// print a vector
// https://stackoverflow.com/a/31130991/7128154
template<typename T1>
std::ostream& operator <<( std::ostream& out, const std::vector<T1>& object )
{
out << "[";
if ( !object.empty() )
{
for(typename std::vector<T1>::const_iterator
iter = object.begin();
iter != --object.end();
++iter) {
out << *iter << ", ";
}
out << *--object.end();
}
out << "]";
return out;
}
int main()
{
xt::xarray<float> xArr {{nan(""), 9}, {5, -6}, {1, 77}};
std::cout << "xt::xarray<float> xArr = \n" << xArr << std::endl;
Eigen::MatrixXf eigMat = xarray_to_matrixXf(xArr);
std::cout << "Eigen::MatrixXf eigMat = \n" << eigMat << std::endl;
std::vector<std::vector<float>> vec = matrixXf2d_to_vector(eigMat);
std::cout << "std::vector<std::vector<float>> vec = " << vec << std::endl;
return 0;
}
Output
xt::xarray<float> xArr =
{{nan., 9.},
{ 5., -6.},
{ 1., 77.}}
Eigen::MatrixXf eigMat =
nan -6
9 1
5 77
std::vector<std::vector<float>> vec = [[nan, 9], [9, 5], [5, -6]]