jax.numpy.linalg.cholesky#
- jax.numpy.linalg.cholesky(a, *, upper=False)[source]#
Cholesky decomposition.
LAX-backend implementation of
numpy.linalg.cholesky().Original docstring below.
Return the Cholesky decomposition, L * L.H, of the square matrix a, where L is lower-triangular and .H is the conjugate transpose operator (which is the ordinary transpose if a is real-valued). a must be Hermitian (symmetric if real-valued) and positive-definite. No checking is performed to verify whether a is Hermitian or not. In addition, only the lower-triangular and diagonal elements of a are used. Only L is actually returned.
- Parameters:
a ((..., M, M) array_like) – Hermitian (symmetric if all elements are real), positive-definite input matrix.
upper (
bool)
- Returns:
L – Lower-triangular Cholesky factor of a. Returns a matrix object if a is a matrix object.
- Return type:
(…, M, M) array_like