scipy.linalg.lapack.csysvx#

scipy.linalg.lapack.csysvx(a, b, af=None, ipiv=None, lwork=max(3 * n, 1), factored=0, lower=0, overwrite_a=0, overwrite_b=0) = <flapack function csysvx>#

Solve a symmetric indefinite system with condition estimation and error bounds (LAPACK csysvx).

Parameters:

andarray: Symmetric matrix of shape (n, n).
bndarray: Right-hand side(s) of shape (n, nrhs).
afndarray, optional: Factorization to reuse when factored=1; otherwise it is computed.
ipivndarray, optional: Pivot indices to reuse when factored=1, 1-based; otherwise computed.
lworkint, optional: Size of the workspace. Default is max(3 * n, 1); the minimum is 3 * n for the real flavors and 2 * n for the complex ones. Use sysvx_lwork for the optimal value.
factoredint, optional: If nonzero, af and ipiv already hold the factorization and are reused. An integer here rather than the 'F'/'N' letter gesvx takes. Default is 0.
lowerint, optional: If nonzero, the lower triangle of a is referenced; otherwise the upper. Default is 0.
overwrite_aint, optional: If nonzero, a may be overwritten in place. Default is 0.
overwrite_bint, optional: If nonzero, b may be overwritten in place. Default is 0.

Returns:

a_sndarray: a, unchanged; returned so the caller can chain calls.
udutndarray: The block diagonal D and the multipliers.
ipivndarray: Pivot indices describing the interchanges and the 1x1 / 2x2 block structure, 1-based. Pass them on to sytrs/sytri/sycon unchanged.
b_sndarray: b, unchanged.
xndarray: Solution of the system.
rcondfloat: Estimate of the reciprocal condition number.
ferrndarray: Estimated forward error bound for each solution vector.
berrndarray: Componentwise relative backward error of each solution vector.
infoint: 0 on success; if negative, the -info-th argument had an illegal value; if 0 < info <= n, d[info-1, info-1] is exactly zero; if info = n+1, the matrix is singular to working precision.