scipy.linalg.lapack.dptsvx

scipy.linalg.lapack.dptsvx(d, e, b, fact='N', df=None, ef=None) = <flapack function dptsvx>

Solve a positive definite tridiagonal system with condition estimation and error bounds (LAPACK dptsvx).

Parameters:

dndarray

Diagonal of the matrix, length n. Real for every flavor.

endarray

Off-diagonal, length max(0, n - 1).

bndarray

Right-hand side(s) of shape (n, nrhs).

factstr, optional

'N' to factorize the matrix, 'F' to reuse the df and ef supplied. Default is 'N'.

dfndarray, optional

Diagonal of D to reuse when fact='F'; otherwise computed. Real for every flavor.

efndarray, optional

Off-diagonal of L to reuse when fact='F'; otherwise computed.

Returns:

dfndarray

Diagonal of D.

efndarray

Off-diagonal of L.

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, the leading minor of order info is not positive definite; if info = n+1, the matrix is singular to working precision and x may be inaccurate.