scipy.sparse.linalg.
factorized#
- scipy.sparse.linalg.factorized(A)[source]#
Return a function for solving a sparse linear system, with A pre-factorized.
- Parameters:
- A(N, N) array_like
Input. A in CSC format is most efficient. A CSR format matrix will be converted to CSC before factorization.
- Returns:
- solvecallable
To solve the linear system of equations given in A, the solve callable should be passed an ndarray of shape (N,).
Examples
>>> import numpy as np >>> from scipy.sparse.linalg import factorized >>> from scipy.sparse import csc_matrix >>> A = np.array([[ 3. , 2. , -1. ], ... [ 2. , -2. , 4. ], ... [-1. , 0.5, -1. ]]) >>> solve = factorized(csc_matrix(A)) # Makes LU decomposition. >>> rhs1 = np.array([1, -2, 0]) >>> solve(rhs1) # Uses the LU factors. array([ 1., -2., -2.])