General Matrices

Functions for calculating eigenvalues and eigenvectors of a square matrix using classical algorithms. It provides various methods for working with both real and complex matrices, allowing you to solve linear algebra problems with a choice of methods for calculating eigenvectors.

Function

Action

EigenSolver

Compute eigenvalues and eigenvectors of a regular square matrix using the classical algorithm (lapack function GEEV).

EigenSolverX

Compute eigenvalues and eigenvectors of a regular square matrix in Expert mode, i.e. with the ability to influence the computation algorithm and the ability to obtain accompanying computation data (lapack function GEEVX).

EigenSolverShur

Compute eigenvalues, upper triangular matrix in Schur form, and matrix of Schur vectors (lapack function GEES). See also Schur decomposition.

EigenSolver2

Compute generalized eigenvalues and eigenvectors for a pair of ordinary square matrices (lapack function GGEV).

EigenSolver2X

Compute generalized eigenvalues and eigenvectors for a pair of regular square matrices in Expert mode, i.e. with the ability to influence the computation algorithm and the ability to obtain accompanying computation data (lapack function GGEVX). Both matrices must be the same size.

EigenSolver2Shur

Compute a pair of ordinary square matrices of generalized eigenvalues,  generalized eigenvectors, generalized Schur forms, as well as left and right Schur vectors (lapack function GGES).

EigenSolver2Blocked

Compute generalized eigenvalues and eigenvectors for a pair of regular square matrices using a block algorithm (lapack function GGEV3). Both matrices must be the same size. The method parameters are exactly the same as EigenSolver2.

EigenSolver2ShurBlocked

Compute a pair of regular square matrices of generalized eigenvalues,  generalized eigenvectors, generalized Schur forms, as well as left and right Schur vectors (lapack function GGES3).