FiPyfipy.solvers.pysparse.linearCGSSolver¶
Classes
|
The LinearCGSSolver solves a linear system of equations using the conjugate gradient squared method (CGS), a variant of the biconjugate gradient method (BiCG). |
- class fipy.solvers.pysparse.linearCGSSolver.LinearCGSSolver(tolerance='default', criterion='default', iterations='default', precon='default')¶
Bases:
LinearRHSSolverThe LinearCGSSolver solves a linear system of equations using the conjugate gradient squared method (CGS), a variant of the biconjugate gradient method (BiCG). CGS solves linear systems with a general non-symmetric coefficient matrix.
The LinearCGSSolver is a wrapper class for the the Pysparse itsolvers.cgs() method.
Create a LinearCGSSolver object.
- Parameters:
tolerance (
float) – Required error tolerance.criterion (
{'default', 'unscaled', 'RHS', 'matrix', 'initial', 'legacy'}) – Interpretation oftolerance. See Convergence for more information.iterations (
int) – Maximum number of iterative steps to perform.precon (
PysparsePreconditioner) – Preconditioner to use.
- DEFAULT_ITERATIONS = 1000¶
Default maximum number of iterative steps to perform
- DEFAULT_PRECONDITIONER = None¶
Default preconditioner to apply to the matrix
- 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