SciPy

scipy.linalg.cholesky_banded

scipy.linalg.cholesky_banded(ab, overwrite_ab=False, lower=False, check_finite=True)[source]

Cholesky decompose a banded Hermitian positive-definite matrix

The matrix a is stored in ab either in lower diagonal or upper diagonal ordered form:

ab[u + i - j, j] == a[i,j]        (if upper form; i <= j)
ab[    i - j, j] == a[i,j]        (if lower form; i >= j)

Example of ab (shape of a is (6,6), u=2):

upper form:
*   *   a02 a13 a24 a35
*   a01 a12 a23 a34 a45
a00 a11 a22 a33 a44 a55

lower form:
a00 a11 a22 a33 a44 a55
a10 a21 a32 a43 a54 *
a20 a31 a42 a53 *   *
Parameters:

ab : (u + 1, M) array_like

Banded matrix

overwrite_ab : bool, optional

Discard data in ab (may enhance performance)

lower : bool, optional

Is the matrix in the lower form. (Default is upper form)

check_finite : bool, optional

Whether to check that the input matrix contains only finite numbers. Disabling may give a performance gain, but may result in problems (crashes, non-termination) if the inputs do contain infinities or NaNs.

Returns:

c : (u + 1, M) ndarray

Cholesky factorization of a, in the same banded format as ab