`scipy.linalg._flapack:cptsvx`

Signature

def cptsvx(d, e, b, fact = N, df = None, ef = None)

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

d : ndarray: Diagonal of the matrix, length n. Real for every flavor.
e : ndarray: Off-diagonal, length max(0, n - 1).
b : ndarray: Right-hand side(s) of shape (n, nrhs).
fact : str, optional: 'N' to factorize the matrix, 'F' to reuse the df and ef supplied. Default is 'N'.
df : ndarray, optional: Diagonal of D to reuse when fact='F'; otherwise computed. Real for every flavor.
ef : ndarray, optional: Off-diagonal of L to reuse when fact='F'; otherwise computed.

df : ndarray: Diagonal of D.
ef : ndarray: Off-diagonal of L.
x : ndarray: Solution of the system.
rcond : float: Estimate of the reciprocal condition number.
ferr : ndarray: Estimated forward error bound for each solution vector.
berr : ndarray: Componentwise relative backward error of each solution vector.
info : int: 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.