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DenseMatrix/cxx_main.cpp

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

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// Teuchos: Common Tools Package
// Copyright (2004) Sandia Corporation
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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 << printMat(My_Matrix) << std::endl;
std::cout<< printMat(X) << std::endl;
return 0;
}
Reference-counted pointer class and non-member templated function implementations.
Templated serial dense matrix class.
Templated class for solving dense linear problems.
Templated serial dense vector class.
This class creates and provides basic support for dense rectangular matrix of templated type.
ScalarTraits< ScalarType >::magnitudeType normOne() const
Returns the 1-norm of the matrix.
int reshape(OrdinalType numRows, OrdinalType numCols)
Reshaping method for changing the size of a SerialDenseMatrix, keeping the entries.
int scale(const ScalarType alpha)
Scale this matrix by alpha; *this = alpha**this.
OrdinalType stride() const
Returns the stride between the columns of this matrix in memory.
int random()
Set all values in the matrix to be random numbers.
ScalarTraits< ScalarType >::magnitudeType normInf() const
Returns the Infinity-norm of the matrix.
OrdinalType numRows() const
Returns the row dimension of this matrix.
ScalarType * values() const
Data array access method.
int multiply(ETransp transa, ETransp transb, ScalarType alpha, const SerialDenseMatrix< OrdinalType, ScalarType > &A, const SerialDenseMatrix< OrdinalType, ScalarType > &B, ScalarType beta)
Multiply A * B and add them to this; this = beta * this + alpha*A*B.
ScalarTraits< ScalarType >::magnitudeType normFrobenius() const
Returns the Frobenius-norm of the matrix.
OrdinalType numCols() const
Returns the column dimension of this matrix.
int shape(OrdinalType numRows, OrdinalType numCols)
Shape method for changing the size of a SerialDenseMatrix, initializing entries to zero.
A class for solving dense linear problems.
int setMatrix(const RCP< SerialDenseMatrix< OrdinalType, ScalarType > > &A)
Sets the pointers for coefficient matrix.
int factor()
Computes the in-place LU factorization of the matrix using the LAPACK routine _GETRF.
int setVectors(const RCP< SerialDenseMatrix< OrdinalType, ScalarType > > &X, const RCP< SerialDenseMatrix< OrdinalType, ScalarType > > &B)
Sets the pointers for left and right hand side vector(s).
int solve()
Computes the solution X to AX = B for the this matrix and the B provided to SetVectors()....
This class creates and provides basic support for dense vectors of templated type as a specialization...
#define TEUCHOS_ASSERT_EQUALITY(val1, val2)
This macro is checks that to numbers are equal and if not then throws an exception with a good error ...
TEUCHOS_DEPRECATED RCP< T > rcp(T *p, Dealloc_T dealloc, bool owns_mem)
Deprecated.