public SymmetricQRAlgorithmDecomposition_DDRM(TridiagonalSimilarDecomposition_F64 <DMatrixRMaj> decomp,
bool computeVectors)
{
this.decomp = decomp;
this.computeVectors = computeVectors;
helper = new SymmetricQREigenHelper_DDRM();
vector = new SymmetricQrAlgorithm_DDRM(helper);
}
/**
* <p>
* Returns an {@link EigenDecomposition} which is specialized for symmetric matrices or the general problem.
* </p>
*
* @param matrixSize Number of rows and columns that the returned decomposition is optimized for.
* @param computeVectors Should it compute the eigenvectors or just eigenvalues.
* @param isSymmetric If true then the returned algorithm is specialized only for symmetric matrices, if false
* then a general purpose algorithm is returned.
* @return EVD for any matrix.
*/
public static EigenDecomposition_F64 <DMatrixRMaj> eig(int matrixSize, bool computeVectors,
bool isSymmetric)
{
if (isSymmetric)
{
TridiagonalSimilarDecomposition_F64 <DMatrixRMaj> decomp =
DecompositionFactory_DDRM.tridiagonal(matrixSize);
return(new SymmetricQRAlgorithmDecomposition_DDRM(decomp, computeVectors));
}
else
{
return(new WatchedDoubleStepQRDecomposition_DDRM(computeVectors));
}
}
