pymatsolver.SolverLU#
- class pymatsolver.SolverLU(A, is_symmetric=None, is_positive_definite=False, is_hermitian=None, check_accuracy=False, check_rtol=1e-06, check_atol=0, **kwargs)[source]#
Wrapped SolverLU solver, using scipy.sparse.linalg.splu.
The transposed solver (
.T) re-uses this solver’s LU factorization instead of factoringA.T. Transposed and conjugated solvers share this factorization, and are updated along with it when it is re-factored.- Parameters:
- A
The matrix to use for the solver.
- is_symmetricbool,
optional Whether the matrix is symmetric. By default, it will perform some simple tests to check for symmetry, and default to
Falseif those fail.- is_positive_definitebool,
optional Whether the matrix is positive definite.
- is_hermitianbool,
optional Whether the matrix is hermitian.
- check_accuracybool,
optional Whether to check the accuracy of the solution.
- check_rtol
float,optional The relative tolerance to check against for accuracy.
- check_atol
float,optional The absolute tolerance to check against for accuracy.
- **kwargs
Extra keyword arguments which will attempted to be passed to scipy.sparse.linalg.splu.
- Attributes:
AThe matrix to solve with.
TThe transposed solve operator
check_accuracyWhether the check the accuracy after a solve.
check_atolThe absolute tolerance used to check the solve operation.
check_rtolThe relative tolerance used to check the solve operation.
dtypeThe data type of the matrix.
is_hermitianWhether the matrix is hermitian.
is_positive_definiteWhether the matrix is positive definite.
is_realWhether the matrix is real.
is_symmetricWhether the matrix is symmetric.
shapeThe input matrix dimensions.
solverThe underlying solver object shared by this solver’s transposed and conjugated views.
Methods
conj()Return the complex conjugate version of this solver.
Return the complex conjugate version of this solver.
factor([A])(Re)factor the matrix.
solve(rhs)Solves the system of equations for the given right hand side.
Return the transposed solve operator.
clean
get_attributes