scipy.sparse.linalg.use_solver

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

Select default sparse direct solver to be used.

Parameters

useUmfpackbool, optional

Use UMFPACK over SuperLU. Has effect only if scikits.umfpack is installed. Default: True

assumeSortedIndicesbool, optional

Allow UMFPACK to skip the step of sorting indices for a CSR/CSC matrix. Has effect only if useUmfpack is True and scikits.umfpack is installed. Default: False

Notes

The default sparse solver is umfpack when available (scikits.umfpack is installed). This can be changed by passing useUmfpack = False, which then causes the always present SuperLU based solver to be used.

Umfpack requires a CSR/CSC matrix to have sorted column/row indices. If sure that the matrix fulfills this, pass assumeSortedIndices=True to gain some speed.

Examples

>>> 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