scipy.sparse.linalg.

use_solver

scipy.sparse.linalg.use_solver(**kwargs)

选择默认的稀疏直接求解器。

参数:

useUmfpackbool, 可选

使用 UMFPACK [1], [2], [3], [4]. 而不是 SuperLU。仅在安装了 scikits.umfpack 时有效。默认值：True

assumeSortedIndicesbool, 可选

允许 UMFPACK 跳过对 CSR/CSC 矩阵的索引排序步骤。仅在使用 Umfpack 为 True 且安装了 scikits.umfpack 时有效。默认值：False

注释

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

UMFPACK 要求 CSR/CSC 矩阵的列/行索引已排序。如果确定矩阵满足此条件，请传递 assumeSortedIndices=True 以提高速度。

参考文献

[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

Try it in your browser!

>>> import numpy as np
>>> from scipy.sparse.linalg import use_solver, spsolve
>>> from scipy.sparse import csc_matrix
>>> R = np.random.randn(5, 5)
>>> A = csc_matrix(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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