scipy.linalg.lapack.sgees

scipy.linalg.lapack.sgees(sselect, a, compute_v=1, sort_t=0, lwork=3 * n, sselect_extra_args=(), overwrite_a=0) = <flapack function sgees>

Compute the Schur factorization of a general matrix (LAPACK sgees).

Parameters:

sselectcallable

Eigenvalue selector, called as sselect(wr, wi) with the real and imaginary parts. Used only when sort_t is nonzero; return true to move that eigenvalue to the leading block.

andarray

Square matrix of shape (n, n).

compute_vint, optional

If nonzero, the Schur vectors are computed. Default is 1.

sort_tint, optional

If nonzero, eigenvalues are sorted using the selector. Default is 0.

lworkint, optional

Size of the workspace. Default is 3 * n. Use the value reported in work[0] for the optimal value.

sselect_extra_argstuple, optional

Extra positional arguments appended to every selector call. Default is ().

overwrite_aint, optional

If nonzero, a may be overwritten in place. Default is 0.

Returns:

tndarray

Schur form of a.

sdimint

Number of eigenvalues the selector accepted; 0 when sort_t is 0.

wrndarray

Real parts of the eigenvalues.

windarray

Imaginary parts of the eigenvalues; conjugate pairs appear adjacently.

vsndarray

Schur vectors, or a (1, n) placeholder when compute_v is 0.

workndarray

Workspace actually used; work[0] is the optimal lwork.

infoint

0 on success; if negative, the -info-th argument had an illegal value; if positive, the QR algorithm failed or the selected block could not be reordered.