jax.numpy.linalg.eigvalsh#
- jax.numpy.linalg.eigvalsh(a, UPLO='L')[source]#
Compute the eigenvalues of a complex Hermitian or real symmetric matrix.
LAX-backend implementation of
numpy.linalg.eigvalsh().Original docstring below.
Main difference from eigh: the eigenvectors are not computed.
- Parameters:
a ((..., M, M) array_like) – A complex- or real-valued matrix whose eigenvalues are to be computed.
UPLO ({'L', 'U'}, optional) – Specifies whether the calculation is done with the lower triangular part of a (‘L’, default) or the upper triangular part (‘U’). Irrespective of this value only the real parts of the diagonal will be considered in the computation to preserve the notion of a Hermitian matrix. It therefore follows that the imaginary part of the diagonal will always be treated as zero.
- Returns:
w – The eigenvalues in ascending order, each repeated according to its multiplicity.
- Return type:
(…, M,) ndarray