32 #define VIENNACL_WITH_UBLAS
45 namespace ublas = boost::numeric::ublas;
56 std::cout <<
"Compute eigenvalues and eigenvectors of matrix of size " << sz <<
"-by-" << sz << std::endl << std::endl;
58 std::vector<ScalarType> d(sz), e(sz);
84 std::cout <<
"Eigenvalues: " << std::endl;
85 for (
unsigned int i = 0; i < d.size(); i++)
86 std::cout << std::setprecision(6) << std::fixed << d[i] <<
" ";
87 std::cout << std::endl;
89 std::cout << std::endl;
90 std::cout <<
"Eigenvectors corresponding to the eigenvalues above are the columns: " << std::endl << std::endl;
91 std::cout << Q << std::endl;
96 std::cout << std::endl <<
"--------TUTORIAL COMPLETED----------" << std::endl;
Implementations of dense matrix related operations, including matrix-vector products, using a plain single-threaded or OpenMP-enabled execution on CPU.
A reader and writer for the matrix market format is implemented here.
void tql2(matrix_base< SCALARTYPE, F > &Q, VectorType &d, VectorType &e)
Represents a vector consisting of 1 at a given index and zeros otherwise. To be used as an initialize...
Common routines used for the QR method and SVD. Experimental.
Implementation of the compressed_matrix class.
Implementation of the QR method for eigenvalue computations. Experimental.
The vector type with operator-overloads and proxy classes is defined here. Linear algebra operations ...
Implementation of the ViennaCL scalar class.