fipy.solvers.pyAMG package

Subpackages

Submodules

fipy.solvers.pyAMG.linearCGSSolver module

class fipy.solvers.pyAMG.linearCGSSolver.LinearCGSSolver(tolerance=1e-15, iterations=2000, precon=<fipy.solvers.pyAMG.preconditioners.smoothedAggregationPreconditioner.SmoothedAggregationPreconditioner object>)

Bases: LinearCGSSolver

The LinearCGSSolver is an interface to the CGS solver in Scipy, using the PyAMG SmoothedAggregationPreconditioner by default.

Parameters:
__enter__()
__exit__(exc_type, exc_value, traceback)
__repr__()

Return repr(self).

fipy.solvers.pyAMG.linearGMRESSolver module

class fipy.solvers.pyAMG.linearGMRESSolver.LinearGMRESSolver(tolerance=1e-15, iterations=2000, precon=<fipy.solvers.pyAMG.preconditioners.smoothedAggregationPreconditioner.SmoothedAggregationPreconditioner object>)

Bases: LinearGMRESSolver

The LinearGMRESSolver is an interface to the GMRES solver in Scipy, using the PyAMG SmoothedAggregationPreconditioner by default.

Parameters:
__enter__()
__exit__(exc_type, exc_value, traceback)
__repr__()

Return repr(self).

fipy.solvers.pyAMG.linearGeneralSolver module

class fipy.solvers.pyAMG.linearGeneralSolver.LinearGeneralSolver(tolerance=1e-10, iterations=1000, precon=None)

Bases: _ScipySolver

The LinearGeneralSolver is an interface to the generic PyAMG, which solves the arbitrary system Ax=b with the best out-of-the box choice for a solver. See pyAMG.solve for details.

Create a Solver object.

Parameters:
  • tolerance (float) – Required error tolerance.

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

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

__enter__()
__exit__(exc_type, exc_value, traceback)
__repr__()

Return repr(self).

fipy.solvers.pyAMG.linearLUSolver module

class fipy.solvers.pyAMG.linearLUSolver.LinearLUSolver(tolerance=1e-10, iterations=1000, precon=None)

Bases: _ScipySolver

The LinearLUSolver solves a linear system of equations using LU-factorization. The LinearLUSolver is a wrapper class for the the Scipy scipy.sparse.linalg.splu module.

Create a Solver object.

Parameters:
  • tolerance (float) – Required error tolerance.

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

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

__enter__()
__exit__(exc_type, exc_value, traceback)
__repr__()

Return repr(self).

fipy.solvers.pyAMG.linearPCGSolver module

class fipy.solvers.pyAMG.linearPCGSolver.LinearPCGSolver(tolerance=1e-15, iterations=2000, precon=<fipy.solvers.pyAMG.preconditioners.smoothedAggregationPreconditioner.SmoothedAggregationPreconditioner object>)

Bases: LinearPCGSolver

The LinearPCGSolver is an interface to the PCG solver in Scipy, using the PyAMG SmoothedAggregationPreconditioner by default.

Parameters:
__enter__()
__exit__(exc_type, exc_value, traceback)
__repr__()

Return repr(self).

Module contents

fipy.solvers.pyAMG.DefaultAsymmetricSolver

alias of LinearLUSolver

fipy.solvers.pyAMG.DefaultSolver

alias of LinearGMRESSolver

fipy.solvers.pyAMG.DummySolver

alias of LinearGMRESSolver

fipy.solvers.pyAMG.GeneralSolver

alias of LinearGeneralSolver

class fipy.solvers.pyAMG.LinearCGSSolver(tolerance=1e-15, iterations=2000, precon=<fipy.solvers.pyAMG.preconditioners.smoothedAggregationPreconditioner.SmoothedAggregationPreconditioner object>)

Bases: LinearCGSSolver

The LinearCGSSolver is an interface to the CGS solver in Scipy, using the PyAMG SmoothedAggregationPreconditioner by default.

Parameters:
__enter__()
__exit__(exc_type, exc_value, traceback)
__repr__()

Return repr(self).

class fipy.solvers.pyAMG.LinearGMRESSolver(tolerance=1e-15, iterations=2000, precon=<fipy.solvers.pyAMG.preconditioners.smoothedAggregationPreconditioner.SmoothedAggregationPreconditioner object>)

Bases: LinearGMRESSolver

The LinearGMRESSolver is an interface to the GMRES solver in Scipy, using the PyAMG SmoothedAggregationPreconditioner by default.

Parameters:
__enter__()
__exit__(exc_type, exc_value, traceback)
__repr__()

Return repr(self).

class fipy.solvers.pyAMG.LinearGeneralSolver(tolerance=1e-10, iterations=1000, precon=None)

Bases: _ScipySolver

The LinearGeneralSolver is an interface to the generic PyAMG, which solves the arbitrary system Ax=b with the best out-of-the box choice for a solver. See pyAMG.solve for details.

Create a Solver object.

Parameters:
  • tolerance (float) – Required error tolerance.

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

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

__enter__()
__exit__(exc_type, exc_value, traceback)
__repr__()

Return repr(self).

class fipy.solvers.pyAMG.LinearLUSolver(tolerance=1e-10, iterations=1000, precon=None)

Bases: _ScipySolver

The LinearLUSolver solves a linear system of equations using LU-factorization. The LinearLUSolver is a wrapper class for the the Scipy scipy.sparse.linalg.splu module.

Create a Solver object.

Parameters:
  • tolerance (float) – Required error tolerance.

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

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

__enter__()
__exit__(exc_type, exc_value, traceback)
__repr__()

Return repr(self).

class fipy.solvers.pyAMG.LinearPCGSolver(tolerance=1e-15, iterations=2000, precon=<fipy.solvers.pyAMG.preconditioners.smoothedAggregationPreconditioner.SmoothedAggregationPreconditioner object>)

Bases: LinearPCGSolver

The LinearPCGSolver is an interface to the PCG solver in Scipy, using the PyAMG SmoothedAggregationPreconditioner by default.

Parameters:
__enter__()
__exit__(exc_type, exc_value, traceback)
__repr__()

Return repr(self).

Last updated on Jun 15, 2022. Created using Sphinx 5.0.1.