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DenseMatrix/cxx_main.cpp

This is an example of how to use the Teuchos::SerialDenseMatrix 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 3x4 matrix
// Basic copy of My_Matrix
// (Deep) Copy of principle 3x3 submatrix of My_Matrix
My_Copy2( Teuchos::Copy, My_Matrix, 3, 3 ),
// (Shallow) Copy of 2x3 submatrix of My_Matrix
My_Copy3( Teuchos::View, My_Matrix, 2, 3, 1, 1 );
// Create a double-precision vector:
// 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, 3 ); // size non-dimensional matrices
My_Matrix.reshape( 3, 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_Copy2(1,1) = 10.0; // individual element access
Empty_Matrix = My_Matrix; // copy My_Matrix to Empty_Matrix
x = 1.0; // every entry of vector is 1.0
y = 1.0;
// Basic matrix arithmetic can be performed:
double d;
// Matrix multiplication ( My_Prod = 1.0*My_Matrix*My_Copy^T )
1.0, My_Matrix, My_Copy3, 0.0 );
My_Copy2 += My_Matrix; // Matrix addition
My_Copy2.scale( 0.5 ); // Matrix scaling
d = x.dot( y ); // Vector dot product
(void)d; // Not used!
// The pointer to the array of matrix values can be obtained:
double *My_Array=0, *My_Column=0;
My_Array = My_Matrix.values(); // pointer to matrix values
My_Column = My_Matrix[2]; // pointer to third column values
(void)My_Array; // Not used!
(void)My_Column; // Not used!
// 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
(void)norm_one; // Not used!
(void)norm_inf; // Not used!
(void)norm_fro; // Not used!
// 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;
}
// A matrix can be factored and solved using Teuchos::SerialDenseSolver.
X.putScalar(1.0);
B.multiply( Teuchos::NO_TRANS, Teuchos::NO_TRANS, 1.0, My_Matrix, X, 0.0 );
X.putScalar(0.0); // Make sure the computed answer is correct.
int info = 0;
My_Solver.setMatrix( Teuchos::rcp( &My_Matrix, false ) );
My_Solver.setVectors( Teuchos::rcp( &X, false ), Teuchos::rcp( &B, false ) );
info = My_Solver.factor();
if (info != 0)
std::cout << "Teuchos::SerialDenseSolver::factor() returned : " << info << std::endl;
info = My_Solver.solve();
if (info != 0)
std::cout << "Teuchos::SerialDenseSolver::solve() returned : " << info << std::endl;
// A matrix can be sent to the output stream:
std::cout<< std::endl << My_Matrix << std::endl;
std::cout<< X << std::endl;
return 0;
}