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jax.scipy.linalg.cho_factor

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jax.scipy.linalg.cho_factor#

jax.scipy.linalg.cho_factor(a, lower=False, overwrite_a=False, check_finite=True)[source]#

Compute the Cholesky decomposition of a matrix, to use in cho_solve

LAX-backend implementation of scipy.linalg._decomp_cholesky.cho_factor().

Does not support the Scipy argument check_finite=True, because compiled JAX code cannot perform checks of array values at runtime.

Does not support the Scipy argument overwrite_*=True.

Original docstring below.

Returns a matrix containing the Cholesky decomposition, A = L L* or A = U* U of a Hermitian positive-definite matrix a. The return value can be directly used as the first parameter to cho_solve.

Warning

The returned matrix also contains random data in the entries not used by the Cholesky decomposition. If you need to zero these entries, use the function cholesky instead.

Parameters:

  • a ((M, M) array_like) – Matrix to be decomposed

  • lower (bool, optional) – Whether to compute the upper or lower triangular Cholesky factorization (Default: upper-triangular)

  • overwrite_a (bool)

  • check_finite (bool)

Return type:

tuple[Array, bool]

Returns:

  • c ((M, M) ndarray) – Matrix whose upper or lower triangle contains the Cholesky factor of a. Other parts of the matrix contain random data.

  • lower (bool) – Flag indicating whether the factor is in the lower or upper triangle

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