fipy.solvers.pyamgx package¶

Subpackages¶

Submodules¶

fipy.solvers.pyamgx.aggregationAMGSolver module¶

class fipy.solvers.pyamgx.aggregationAMGSolver.AggregationAMGSolver(tolerance=1e-10, iterations=2000, precon=None, smoother={'max_iters': 1, 'solver': 'BLOCK_JACOBI'}, **kwargs)¶

Bases: PyAMGXSolver

The AggregationAMGSolver is an interface to the aggregation AMG solver in AMGX, with a Jacobi smoother by default.

Parameters:

tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (Preconditioner, optional) –
**kwargs – Other AMGX solver options

__enter__()¶

__exit__(*args)¶

__repr__()¶: Return repr(self).

fipy.solvers.pyamgx.classicalAMGSolver module¶

class fipy.solvers.pyamgx.classicalAMGSolver.ClassicalAMGSolver(tolerance=1e-10, iterations=2000, precon=None, smoother={'max_iters': 1, 'solver': 'BLOCK_JACOBI'}, **kwargs)¶

Bases: PyAMGXSolver

The ClassicalAMGSolver is an interface to the classical AMG solver in AMGX, with a Jacobi smoother by default.

Parameters:

tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (Preconditioner, optional) –
smoother (Smoother, optional) –
**kwargs – Other AMGX solver options

__enter__()¶

__exit__(*args)¶

__repr__()¶: Return repr(self).

fipy.solvers.pyamgx.linearBiCGStabSolver module¶

class fipy.solvers.pyamgx.linearBiCGStabSolver.LinearBiCGStabSolver(tolerance=1e-10, iterations=2000, precon={'max_iters': 1, 'solver': 'BLOCK_JACOBI'}, **kwargs)¶

Bases: PyAMGXSolver

The LinearBiCGStabSolver is an interface to the PBICGSTAB solver in AMGX, with a Jacobi preconditioner by default.

Parameters:

tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (Preconditioner, optional) –
**kwargs – Other AMGX solver options

__enter__()¶

__exit__(*args)¶

__repr__()¶: Return repr(self).

fipy.solvers.pyamgx.linearCGSolver module¶

class fipy.solvers.pyamgx.linearCGSolver.LinearCGSolver(tolerance=1e-10, iterations=2000, precon={'max_iters': 1, 'solver': 'BLOCK_JACOBI'}, **kwargs)¶

Bases: PyAMGXSolver

The LinearCGSolver is an interface to the PCG solver in AMGX, with no preconditioning by default.

Parameters:

tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (Preconditioner, optional) –
**kwargs – Other AMGX solver options

__enter__()¶

__exit__(*args)¶

__repr__()¶: Return repr(self).

fipy.solvers.pyamgx.linearCGSolver.LinearPCGSolver¶: alias of LinearCGSolver

fipy.solvers.pyamgx.linearFGMRESSolver module¶

class fipy.solvers.pyamgx.linearFGMRESSolver.LinearFGMRESSolver(tolerance=1e-10, iterations=2000, precon={'max_iters': 1, 'solver': 'BLOCK_JACOBI'}, **kwargs)¶

Bases: PyAMGXSolver

The LinearFGMRESSolver is an interface to the FGMRES solver in AMGX, with a Jacobi preconditioner by default.

Parameters:

tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (Preconditioner, optional) –
**kwargs – Other AMGX solver options

__enter__()¶

__exit__(*args)¶

__repr__()¶: Return repr(self).

fipy.solvers.pyamgx.linearGMRESSolver module¶

class fipy.solvers.pyamgx.linearGMRESSolver.LinearGMRESSolver(tolerance=1e-10, iterations=2000, precon={'max_iters': 1, 'solver': 'BLOCK_JACOBI'}, **kwargs)¶

Bases: PyAMGXSolver

The LinearGMRESSolver is an interface to the GMRES solver in AMGX, with a Jacobi preconditioner by default.

Parameters:

tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (Preconditioner, optional) –
**kwargs – Other AMGX solver options

__enter__()¶

__exit__(*args)¶

__repr__()¶: Return repr(self).

fipy.solvers.pyamgx.linearLUSolver module¶

class fipy.solvers.pyamgx.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.pyamgx.pyAMGXSolver module¶

class fipy.solvers.pyamgx.pyAMGXSolver.PyAMGXSolver(config_dict, tolerance=1e-10, iterations=2000, precon=None, smoother=None, **kwargs)¶

Bases: Solver

Parameters:

config_dict (dict) – AMGX configuration options
tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (Preconditioner, optional) –
smoother (Smoother, optional) –
**kwargs – Other AMGX solver options

__enter__()¶

__exit__(*args)¶

__repr__()¶: Return repr(self).

Module contents¶

class fipy.solvers.pyamgx.AggregationAMGSolver(tolerance=1e-10, iterations=2000, precon=None, smoother={'max_iters': 1, 'solver': 'BLOCK_JACOBI'}, **kwargs)¶

Bases: PyAMGXSolver

The AggregationAMGSolver is an interface to the aggregation AMG solver in AMGX, with a Jacobi smoother by default.

Parameters:

tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (Preconditioner, optional) –
**kwargs – Other AMGX solver options

__enter__()¶

__exit__(*args)¶

__repr__()¶: Return repr(self).

fipy.solvers.pyamgx.DefaultAsymmetricSolver¶: alias of LinearLUSolver

fipy.solvers.pyamgx.DefaultSolver¶: alias of LinearCGSolver

fipy.solvers.pyamgx.DummySolver¶: alias of LinearCGSolver

fipy.solvers.pyamgx.GeneralSolver¶: alias of LinearLUSolver

class fipy.solvers.pyamgx.LinearBiCGStabSolver(tolerance=1e-10, iterations=2000, precon={'max_iters': 1, 'solver': 'BLOCK_JACOBI'}, **kwargs)¶

Bases: PyAMGXSolver

The LinearBiCGStabSolver is an interface to the PBICGSTAB solver in AMGX, with a Jacobi preconditioner by default.

Parameters:

tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (Preconditioner, optional) –
**kwargs – Other AMGX solver options

__enter__()¶

__exit__(*args)¶

__repr__()¶: Return repr(self).

class fipy.solvers.pyamgx.LinearCGSolver(tolerance=1e-10, iterations=2000, precon={'max_iters': 1, 'solver': 'BLOCK_JACOBI'}, **kwargs)¶

Bases: PyAMGXSolver

The LinearCGSolver is an interface to the PCG solver in AMGX, with no preconditioning by default.

Parameters:

tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (Preconditioner, optional) –
**kwargs – Other AMGX solver options

__enter__()¶

__exit__(*args)¶

__repr__()¶: Return repr(self).

class fipy.solvers.pyamgx.LinearFGMRESSolver(tolerance=1e-10, iterations=2000, precon={'max_iters': 1, 'solver': 'BLOCK_JACOBI'}, **kwargs)¶

Bases: PyAMGXSolver

The LinearFGMRESSolver is an interface to the FGMRES solver in AMGX, with a Jacobi preconditioner by default.

Parameters:

tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (Preconditioner, optional) –
**kwargs – Other AMGX solver options

__enter__()¶

__exit__(*args)¶

__repr__()¶: Return repr(self).

class fipy.solvers.pyamgx.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.pyamgx.LinearPCGSolver¶: alias of LinearCGSolver

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