scipy.linalg._flapack:chegvx

Parameters

a : ndarray

Hermitian matrix of shape (n, n).

b : ndarray

Positive definite matrix of shape (n, n).

itype : int, optional

Which generalized problem to solve: 1 for a @ x = w * b @ x, 2 for a @ b @ x = w * x, 3 for b @ a @ x = w * x. Default is 1.

jobz : str, optional

'V' to compute eigenvectors, 'N' for eigenvalues only. Default is 'V'. This family spells it as a letter where syev uses compute_v.

range : str, optional

'A' for all eigenvalues, 'V' for those in (vl, vu], 'I' for those indexed il through iu. Default is 'A'.

uplo : str, optional

'U' or 'L' for the triangle of a to reference. Default is 'L' -- note that is the opposite of the lower=0 default elsewhere in this group, so the same matrix can give different answers between families.

vl : float, optional

Lower bound of the interval; used only when range is 'V'. Default is 0.0.

vu : float, optional

Upper bound of the interval; used only when range is 'V'. Default is 1.0.

il : int, optional

Index of the smallest eigenvalue to return, 1-based; used only when range is 'I'. Default is 1.

iu : int, optional

Index of the largest eigenvalue to return, 1-based; used only when range is 'I'. Default is n.

abstol : float, optional

Absolute error tolerance for the eigenvalues. Default is 0.0.

lwork : int, optional

Size of the workspace. Default is max(2 * n, 1). Use chegvx_lwork 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.