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.