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.