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DenseMatrix/cxx_main_sym.cpp

This is an example of how to use the Teuchos::SerialSymDenseMatrix class.

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#include "Teuchos_RCP.hpp"
#include "Teuchos_Version.hpp"
int main(int argc, char* argv[])
{
std::cout << Teuchos::Teuchos_Version() << std::endl << std::endl;
// Creating a double-precision matrix can be done in several ways:
// Create an empty matrix with no dimension
// Create an empty 4x4 matrix
// Basic copy of My_Matrix
// (Deep) Copy of principle 3x3 submatrix of My_Matrix
My_Copy2( Teuchos::Copy, My_Matrix, 3 ),
// (Shallow) Copy of 3x3 submatrix of My_Matrix
My_Copy3( Teuchos::View, My_Matrix, 3, 1 );
// The matrix dimensions and strided storage information can be obtained:
int rows, cols, stride;
rows = My_Copy3.numRows(); // number of rows
cols = My_Copy3.numCols(); // number of columns
stride = My_Copy3.stride(); // storage stride
// Matrices can change dimension:
Empty_Matrix.shape( 3 ); // size non-dimensional matrices
My_Matrix.reshape( 3 ); // resize matrices and save values
// Filling matrices with numbers can be done in several ways:
My_Matrix.random(); // random numbers
My_Copy1.putScalar( 1.0 ); // every entry is 1.0
My_Copy1 = 1.0; // every entry is 1.0 (still)
My_Copy2(1,1) = 10.0; // individual element access
Empty_Matrix = My_Matrix; // copy My_Matrix to Empty_Matrix
// Basic matrix arithmetic can be performed:
Teuchos::SerialDenseMatrix<int,double> My_Prod( 4, 3 ), My_GenMatrix( 4, 3 );
My_GenMatrix = 1.0;
// Matrix multiplication ( My_Prod = 1.0*My_GenMatrix*My_Matrix )
My_Prod.multiply( Teuchos::RIGHT_SIDE, 1.0, My_Matrix, My_GenMatrix, 0.0 );
My_Copy2 += My_Matrix; // Matrix addition
My_Copy2 *= 0.5; // Matrix scaling
// Matrices can be compared:
// Check if the matrices are equal in dimension and values
if (Empty_Matrix == My_Matrix) {
std::cout<< "The matrices are the same!" <<std::endl;
}
// Check if the matrices are different in dimension or values
if (My_Copy2 != My_Matrix) {
std::cout<< "The matrices are different!" <<std::endl;
}
// The norm of a matrix can be computed:
double norm_one, norm_inf, norm_fro;
norm_one = My_Matrix.normOne(); // one norm
norm_inf = My_Matrix.normInf(); // infinity norm
norm_fro = My_Matrix.normFrobenius(); // frobenius norm
std::cout << std::endl << "|| My_Matrix ||_1 = " << norm_one << std::endl;
std::cout << "|| My_Matrix ||_Inf = " << norm_inf << std::endl;
std::cout << "|| My_Matrix ||_F = " << norm_fro << std::endl << std::endl;
// A matrix can be factored and solved using Teuchos::SerialDenseSolver.
My_Matrix2.random();
X = 1.0;
B.multiply( Teuchos::LEFT_SIDE, 1.0, My_Matrix2, X, 0.0 );
X = 0.0; // Make sure the computed answer is correct.
int info = 0;
My_Solver.setMatrix( Teuchos::rcp( &My_Matrix2, false ) );
My_Solver.setVectors( Teuchos::rcp( &X, false ), Teuchos::rcp( &B, false ) );
info = My_Solver.factor();
if (info != 0)
std::cout << "Teuchos::SerialSpdDenseSolver::factor() returned : " << info << std::endl;
info = My_Solver.solve();
if (info != 0)
std::cout << "Teuchos::SerialSpdDenseSolver::solve() returned : " << info << std::endl;
// A matrix triple-product can be computed: C = alpha*W'*A*W
double alpha=0.5;
A1(0,0) = 1.0, A1(1,1) = 2.0;
A2(0,0) = 1.0, A2(1,1) = 2.0, A2(2,2) = 3.00;
W = 1.0;
Teuchos::symMatTripleProduct<int,double>( Teuchos::NO_TRANS, alpha, A1, W, C1);
Teuchos::symMatTripleProduct<int,double>( Teuchos::TRANS, alpha, A2, W, C2 );
// A matrix can be sent to the output stream:
std::cout<< My_Matrix << std::endl;
std::cout<< X << std::endl;
return 0;
}