scipy.linalg.lapack.strsen#

scipy.linalg.lapack.strsen(select, t, q, job='B', wantq=1, lwork=max(1, n), liwork=1, overwrite_t=0, overwrite_q=0) = <flapack function strsen>#

Reorder a Schur decomposition to gather selected eigenvalues into a leading cluster (LAPACK strsen).

Parameters:

selectndarray: Boolean mask of length n: the eigenvalues it marks are gathered into the leading block. A bool array works; LAPACK reads it as a Fortran LOGICAL.
tndarray: Upper (quasi-)triangular Schur form of shape (n, n).
qndarray: Matrix of Schur vectors; updated when wantq is nonzero.
jobstr, optional: What to compute besides the reordering: 'N' nothing, 'E' the cluster condition number s, 'V' the separation sep, 'B' both. Default is 'B'.
wantqint, optional: If nonzero, the transformation is accumulated into q. Default is 1.
lworkint, optional: Workspace size; -1 requests the query. Default is max(1, n). The default is a bare minimum for the cheapest job only – what is actually needed depends on the cluster size, so query the matching _lwork routine.
liworkint, optional: Integer workspace size; -1 requests the query. Default is 1. The complex flavors have no integer workspace and take no liwork.
overwrite_tint, optional: If nonzero, t may be overwritten in place. Default is 0.
overwrite_qint, optional: If nonzero, q may be overwritten in place. Default is 0.

Returns:

tsndarray: The reordered Schur form.
qsndarray: The updated Schur vectors.
wrndarray: Real parts of the reordered eigenvalues, length n.
windarray: Imaginary parts of the reordered eigenvalues, length n.
mint: Size of the selected cluster.
sfloat: Condition number of the selected cluster; 0 unless job asked for it.
sepfloat: Separation of the cluster; 0 unless job asked for it.
infoint: 0 on success; if negative, the -info-th argument had an illegal value.