scipy.sparse.linalg.

use_solver#

scipy.sparse.linalg.use_solver(**kwargs)[源代码]#

选择要使用的默认稀疏直接求解器。

参数:
useUmfpackbool，可选

使用 UMFPACK [1], [2], [3], [4]。优于 SuperLU。仅当安装了 scikits.umfpack 时才有效。默认值：True

assumeSortedIndicesbool，可选

允许 UMFPACK 跳过为 CSR/CSC 矩阵排序索引的步骤。仅当 useUmfpack 为 True 且安装了 scikits.umfpack 时才有效。默认值：False

注释

当 UMFPACK 可用时（安装了 scikits.umfpack），默认的稀疏求解器是 UMFPACK。这可以通过传递 useUmfpack = False 来更改，这将导致始终存在的基于 SuperLU 的求解器被使用。

UMFPACK 要求 CSR/CSC 矩阵具有已排序的列/行索引。如果确定矩阵满足此要求，则传递 assumeSortedIndices=True 以获得一些速度。

参考

[1]

T. A. Davis, Algorithm 832: UMFPACK - an unsymmetric-pattern multifrontal method with a column pre-ordering strategy, ACM Trans. on Mathematical Software, 30(2), 2004, pp. 196–199. https://dl.acm.org/doi/abs/10.1145/992200.992206

[2]

T. A. Davis, A column pre-ordering strategy for the unsymmetric-pattern multifrontal method, ACM Trans. on Mathematical Software, 30(2), 2004, pp. 165–195. https://dl.acm.org/doi/abs/10.1145/992200.992205

[3]

T. A. Davis and I. S. Duff, A combined unifrontal/multifrontal method for unsymmetric sparse matrices, ACM Trans. on Mathematical Software, 25(1), 1999, pp. 1–19. https://doi.org/10.1145/305658.287640

[4]

T. A. Davis and I. S. Duff, An unsymmetric-pattern multifrontal method for sparse LU factorization, SIAM J. Matrix Analysis and Computations, 18(1), 1997, pp. 140–158. https://doi.org/10.1137/S0895479894246905T.

示例

>>> import numpy as np
>>> from scipy.sparse.linalg import use_solver, spsolve
>>> from scipy.sparse import csc_array
>>> R = np.random.randn(5, 5)
>>> A = csc_array(R)
>>> b = np.random.randn(5)
>>> use_solver(useUmfpack=False) # enforce superLU over UMFPACK
>>> x = spsolve(A, b)
>>> np.allclose(A.dot(x), b)
True
>>> use_solver(useUmfpack=True) # reset umfPack usage to default
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