#include <iostream>
#include <cla3p/dense.hpp>
#include <culite/dense.hpp>
#include <culite/svd.hpp>
int main()
{
HostA >> A;
std::cout << "A:\n" << A;
std::cout << "SVD Decomposition of A\n";
std::cout << "----------------------\n";
std::cout
std::cout << "SVD Decomposition of A (no V)\n";
std::cout << "-----------------------------\n";
std::cout
return 0;
}
static XxMatrix< T_Scalar > random(int_t nr, int_t nc, const Property &pr=Property::General(), T_RScalar lo=T_RScalar(0), T_RScalar hi=T_RScalar(1))
Singular Value Decomposition (SVD) solver using cuSOLVER.
Definition default_svd.hpp:66
const T_Matrix & rightSingularVectors() const
Gets the computed right singular vectors.
Definition default_svd.hpp:185
const T_Matrix & leftSingularVectors() const
Gets the computed left singular vectors.
Definition default_svd.hpp:176
const T_RVector & singularValues() const
Gets the computed singular values.
Definition default_svd.hpp:167
void decompose(const T_Matrix &mat)
Performs singular value decomposition on the input matrix.
XxMatrix< real_t > RdMatrix
::cla3p::svdPolicy_t svdPolicy_t
Singular vector computation policy enumeration.
Definition enums.hpp:95
XxMatrix< real_t > RdMatrix
Double precision real matrix.
Definition dense.hpp:55