`scipy.linalg._flapack:dggev`

Signature

def dggev(a, b, compute_vl = 1, compute_vr = 1, lwork = Ellipsis, overwrite_a = 0, overwrite_b = 0)

Solve the generalized eigenproblem a @ v = (alpha / beta) * b @ v (LAPACK dggev).

a : ndarray: Square matrix of shape (n, n).
b : ndarray: Square matrix of shape (n, n), the second member of the pair.
compute_vl : int, optional: If nonzero, left eigenvectors are computed. Default is 1.
compute_vr : int, optional: If nonzero, right eigenvectors are computed. Default is 1.
lwork : int, optional: Size of the workspace. Default is 8 * n. Use the value reported in work[0] for the optimal value.
overwrite_a : int, optional: If nonzero, a may be overwritten in place. Default is 0.
overwrite_b : int, optional: If nonzero, b may be overwritten in place. Default is 0.

alphar : ndarray: Real parts of the numerators of alpha / beta.
alphai : ndarray: Imaginary parts of the numerators of alpha / beta.
beta : ndarray: Denominators; an eigenvalue is infinite where beta is zero.
vl : ndarray: Left eigenvectors, or a (1, n) placeholder when compute_vl is 0.
vr : ndarray: Right eigenvectors, or a (1, n) placeholder when compute_vr is 0.
work : ndarray: Workspace actually used; work[0] is the optimal lwork.
info : int: 0 on success; if negative, the -info-th argument had an illegal value; if positive, the algorithm failed to converge.