fipy.solvers.pysparse.linearPCGSolver

Classes

LinearPCGSolver([tolerance, criterion, ...])

The LinearPCGSolver solves a linear system of equations using the preconditioned conjugate gradient method (PCG) with symmetric successive over-relaxation (SSOR) preconditioning by default.

class fipy.solvers.pysparse.linearPCGSolver.LinearPCGSolver(tolerance='default', criterion='default', iterations='default', precon='default')

Bases: LinearRHSSolver

The LinearPCGSolver solves a linear system of equations using the preconditioned conjugate gradient method (PCG) with symmetric successive over-relaxation (SSOR) preconditioning by default. Alternatively, Jacobi preconditioning can be specified through precon. The PCG method solves systems with a symmetric positive definite coefficient matrix.

The LinearPCGSolver is a wrapper class for the the Pysparse itsolvers.pcg() and precon.ssor() methods.

Create a Solver object.

Parameters:

• tolerance (float) – Required residual tolerance.

• criterion ({'default', 'initial', 'unscaled', 'RHS', 'matrix', 'solution', 'preconditioned', 'natural', 'legacy'}, optional) – Interpretation of tolerance. See Convergence for more information.

• iterations (int) – Maximum number of iterative steps to perform.

• precon (Preconditioner) – Preconditioner to use. Not all solver suites support preconditioners.

DEFAULT_ITERATIONS = 1000

Default maximum number of iterative steps to perform

DEFAULT_PRECONDITIONER

alias of SSORPreconditioner

DEFAULT_TOLERANCE = 1e-05

Default tolerance for linear solves unless criterion=”legacy”

LEGACY_TOLERANCE = 1e-10

Default tolerance for linear solves if criterion=”legacy”

__repr__()

Return repr(self).

property default_tolerance

Default tolerance for linear solve

Last updated on Jun 26, 2024. Created using Sphinx 7.1.2.