lu_solve — SciPy v1.15.3 Manual (original) (raw)
scipy.linalg.
scipy.linalg.lu_solve(lu_and_piv, b, trans=0, overwrite_b=False, check_finite=True)[source]#
Solve an equation system, a x = b, given the LU factorization of a
Parameters:
(lu, piv)
Factorization of the coefficient matrix a, as given by lu_factor. In particular piv are 0-indexed pivot indices.
barray
Right-hand side
trans{0, 1, 2}, optional
Type of system to solve:
| trans | system |
|---|---|
| 0 | a x = b |
| 1 | a^T x = b |
| 2 | a^H x = b |
overwrite_bbool, optional
Whether to overwrite data in b (may increase performance)
check_finitebool, optional
Whether to check that the input matrices contain 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:
xarray
Solution to the system
Examples
import numpy as np from scipy.linalg import lu_factor, lu_solve A = np.array([[2, 5, 8, 7], [5, 2, 2, 8], [7, 5, 6, 6], [5, 4, 4, 8]]) b = np.array([1, 1, 1, 1]) lu, piv = lu_factor(A) x = lu_solve((lu, piv), b) np.allclose(A @ x - b, np.zeros((4,))) True