scipy.sparse.linalg.

use_solver#

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

選擇要使用的預設稀疏直接求解器。

參數:

useUmfpack布林值, 選填: 使用 UMFPACK [1], [2], [3], [4]，而非 SuperLU。僅在安裝 scikits.umfpack 時有效。預設值：True
assumeSortedIndices布林值, 選填: 允許 UMFPACK 跳過排序 CSR/CSC 矩陣索引的步驟。僅在 useUmfpack 為 True 且安裝 scikits.umfpack 時有效。預設值：False

說明

當 UMFPACK 可用時（已安裝 scikits.umfpack），預設的稀疏求解器為 UMFPACK。可以透過傳遞 useUmfpack = False 來更改此設定，這會導致始終存在的基於 SuperLU 的求解器被使用。

UMFPACK 要求 CSR/CSC 矩陣具有排序後的欄/列索引。如果確定矩陣滿足此條件，請傳遞 assumeSortedIndices=True 以獲得一些速度提升。

參考文獻

[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.

範例

>>> 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