jax.numpy.linalg.eigh#
- jax.numpy.linalg.eigh(a, UPLO=None, symmetrize_input=True)[source]#
Return the eigenvalues and eigenvectors of a complex Hermitian
LAX-backend implementation of
numpy.linalg.eigh()
.Original docstring below.
(conjugate symmetric) or a real symmetric matrix.
Returns two objects, a 1-D array containing the eigenvalues of a, and a 2-D square array or matrix (depending on the input type) of the corresponding eigenvectors (in columns).
- Parameters:
a ((..., M, M) array) – Hermitian or real symmetric matrices whose eigenvalues and eigenvectors 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.
- Return type:
- Returns:
A namedtuple with the following attributes
eigenvalues ((…, M) ndarray) – The eigenvalues in ascending order, each repeated according to its multiplicity.
eigenvectors ({(…, M, M) ndarray, (…, M, M) matrix}) – The column
eigenvectors[:, i]
is the normalized eigenvector corresponding to the eigenvalueeigenvalues[i]
. Will return a matrix object if a is a matrix object.
References
- Parameters:
symmetrize_input (
bool
) –