lu_solve(lu_and_piv, b, trans=0, overwrite_b=False, check_finite=True)
Factorization of the coefficient matrix a, as given by lu_factor
Right-hand side
Type of system to solve:
===== ========= trans system ===== ========= 0 a x = b 1 a^T x = b 2 a^H x = b ===== =========
Whether to overwrite data in b (may increase performance)
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.
Solution to the system
Solve an equation system, a x = b, given the LU factorization of a
lu_factor
LU factorize a matrix
>>> from scipy.linalg import lu_factor, lu_solveSee :
... 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
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.linalg._decomp_lu.lu_solve
scipy.linalg._decomp_lu.lu_factor
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