The Schur form depends on the order of the eigenvalues on the diagonal
of T and this may optionally be chosen by the user. Suppose the user chooses
that ,
1 < = j < = n, appear in the upper left
corner of T. Then the first j columns of Z span the right invariant
subspace of A corresponding to .
The following routines perform this re-ordering and also compute condition numbers for eigenvalues, eigenvectors, and invariant subspaces:
See Table 2.11 for a complete list of the routines.
----------------------------------------------------------------------------- Type of matrix Single precision Double precision and storage scheme Operation real complex real complex ----------------------------------------------------------------------------- general Hessenberg reduction SGEHRD CGEHRD DGEHRD ZGEHRD balancing SGEBAL CGEBAL DGEBAL ZGEBAL backtransforming SGEBAK CGEBAK DGEBAK ZGEBAK ----------------------------------------------------------------------------- orthogonal/unitary generate matrix after SORGHR CUNGHR DORGHR ZUNGHR Hessenberg reduction multiply matrix after SORMHR CUNMHR DORMHR ZUNMHR Hessenberg reduction ----------------------------------------------------------------------------- Hessenberg Schur factorization SHSEQR CHSEQR DHSEQR ZHSEQR eigenvectors by SHSEIN CHSEIN DHSEIN ZHSEIN inverse iteration ----------------------------------------------------------------------------- (quasi)triangular eigenvectors STREVC CTREVC DTREVC ZTREVC reordering Schur STREXC CTREXC DTREXC ZTREXC factorization Sylvester equation STRSYL CTRSYL DTRSYL ZTRSYL condition numbers of STRSNA CTRSNA DTRSNA ZTRSNA eigenvalues/vectors condition numbers of STRSEN CTRSEN DTRSEN ZTRSEN eigenvalue cluster/ invariant subspace -----------------------------------------------------------------------------Table 2.11: Computational routines for the nonsymmetric eigenproblem