solver#

Includes the abstract base class for wave function solvers.

Classes:

WFSolver #

WFSolver(matrix_type: str | None, matrix_view: str | None)

Bases: ABC

Abstract base class for wave function solvers.

Parameters:

matrix_type (str) –

The type of the system matrix. This describes properties like symmetry and definiteness, which can be used by solvers to optimize the solution process. Can be None if the solver does not require this information or if it can be inferred from the matrix itself.
matrix_view (str) –

The view of the system matrix sparsity. This is a hint to the solver about which part of the matrix to use, which can be relevant for symmetric matrices where only the upper or lower part is needed. Can be None if the solver does not require this information or if it can be inferred from the matrix itself.

Methods:

solve(a: spmatrix, b: NDArray, reuse_analysis: bool = False, reuse_factorization: bool = False) -> NDArray

Solves the sparse linear system a @ x = b.

Parameters:

a (spmatrix) –

The sparse system matrix.
b (NDArray) –

The right-hand side vector.
reuse_analysis (bool, default: False ) –

Whether to reuse the analysis phase from a previous solve, by default False. This typically includes symbolic factorization and ordering but can vary between solvers. This is useful when solving multiple linear systems with the same sparsity pattern but different numerical values.
reuse_factorization (bool, default: False ) –

Whether to reuse the numerical factorization from a previous solve, by default False. This can only be True if reuse_analysis is also True. Note that this must only be True if the matrix values have not changed since the last factorization.

Returns: