Reputation: 147
How can I add an Eigen's SparseMatrix to an Eigen's Tensor?
The following code (which does not compile) explains what I am trying to do.
#include <iostream>
#include <Eigen/Sparse>
#include <unsupported/Eigen/CXX11/Tensor>
using Eigen::Tensor;
using Eigen::SparseMatrix;
int main()
{
Tensor<double, 2> tensor(10, 10);
for(int i=0; i < 10; i++) {
for(int j=0; j < 10; j++) {
tensor(i, j) = i * 10 + j;
}
}
SparseMatrix<double> sparse(10, 10);
auto tensor2 = tensor;
tensor2 += sparse;
std::cout << tensor2 << std::endl;
}
Upvotes: 0
Views: 513
Reputation: 497
Do you mean in the +=
method :
lhs(it.row(), it.col()) += it.value();
and not
lhs(it.row(), it.col()) = it.value();
?
Upvotes: 0
Reputation: 10939
Obviously, this is not implemented. You have to overload operator+=
for these two types yourself. See this table for the correct signature. See also »Iterating over the nonzero coefficients « in the Eigen docs on how to efficiently iterate over a sparse matrix.
#include <iostream>
#include <Eigen/Sparse>
#include <unsupported/Eigen/CXX11/Tensor>
using Eigen::Tensor;
using Eigen::SparseMatrix;
template < typename T >
Tensor<T,2>& operator+=(Tensor<T,2>& lhs, SparseMatrix<T> const& rhs)
{
for (int k = 0; k < rhs.outerSize(); ++k)
for (typename SparseMatrix<T>::InnerIterator it(rhs,k); it; ++it)
lhs(it.row(), it.col()) = it.value();
return lhs;
}
int main()
{
Tensor<double, 2> tensor(10, 10);
for(int i=0; i < 10; i++) {
for(int j=0; j < 10; j++) {
tensor(i, j) = i * 10 + j;
}
}
// We want a sparse matrix that is not only zeros
Eigen::MatrixXd m = Eigen::MatrixXd::Zero(10,10);
m(0,0) = 1;
SparseMatrix<double> sparse(10, 10);
sparse = m.sparseView();
auto tensor2 = tensor;
tensor2 += sparse;
std::cout << tensor2 << std::endl;
}
Upvotes: 1