scipy.sparse.linalg.spilu¶
- scipy.sparse.linalg.spilu(A, drop_tol=None, fill_factor=None, drop_rule=None, permc_spec=None, diag_pivot_thresh=None, relax=None, panel_size=None, options=None)[source]¶
Compute an incomplete LU decomposition for a sparse, square matrix.
The resulting object is an approximation to the inverse of A.
Parameters: A : (N, N) array_like
Sparse matrix to factorize
drop_tol : float, optional
Drop tolerance (0 <= tol <= 1) for an incomplete LU decomposition. (default: 1e-4)
fill_factor : float, optional
Specifies the fill ratio upper bound (>= 1.0) for ILU. (default: 10)
drop_rule : str, optional
Comma-separated string of drop rules to use. Available rules: basic, prows, column, area, secondary, dynamic, interp. (Default: basic,area)
See SuperLU documentation for details.
Remaining other options
Same as for splu
Returns: invA_approx : scipy.sparse.linalg.SuperLU
Object, which has a solve method.
See also
- splu
- complete LU decomposition
Notes
To improve the better approximation to the inverse, you may need to increase fill_factor AND decrease drop_tol.
This function uses the SuperLU library.