fipy.solvers.petsc package

fipy.solvers.petsc.DefaultAsymmetricSolver

alias of LinearGMRESSolver

fipy.solvers.petsc.DefaultSolver

alias of LinearGMRESSolver

class fipy.solvers.petsc.DummySolver(*args, **kwargs)

Bases: PETScSolver

Solver that doesn’t do anything.

PETSc is intolerant of having zeros on the diagonal

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.

__del__()

__enter__()

__exit__(exc_type, exc_value, traceback)

__repr__()

Return repr(self).

fipy.solvers.petsc.GeneralSolver

alias of LinearGMRESSolver

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

Bases: PETScKrylovSolver

The LinearBicgSolver is an interface to the biconjugate gradient solver in PETSc, using no preconditioner by default.

Parameters:

• tolerance: The required error tolerance.

• iterations: The maximum number of iterative steps to perform.

• precon: Preconditioner to use (string).

__del__()

__enter__()

__exit__(exc_type, exc_value, traceback)

__repr__()

Return repr(self).

solver = 'bicg'

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

Bases: PETScKrylovSolver

The LinearCGSSolver is an interface to the conjugate gradient squared solver in PETSc, using no preconditioner by default.

Parameters:

• tolerance: The required error tolerance.

• iterations: The maximum number of iterative steps to perform.

• precon: Preconditioner to use (string).

__del__()

__enter__()

__exit__(exc_type, exc_value, traceback)

__repr__()

Return repr(self).

solver = 'cgs'

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

Bases: PETScKrylovSolver

The LinearGMRESSolver is an interface to the GMRES solver in PETSc, using no preconditioner by default.

Parameters:

• tolerance: The required error tolerance.

• iterations: The maximum number of iterative steps to perform.

• precon: Preconditioner to use (string).

__del__()

__enter__()

__exit__(exc_type, exc_value, traceback)

__repr__()

Return repr(self).

solver = 'gmres'

class fipy.solvers.petsc.LinearLUSolver(tolerance=1e-10, iterations=10, precon='lu')

Bases: PETScSolver

The LinearLUSolver is an interface to the LU preconditioner in PETSc. A direct solve is performed.

Parameters:

• tolerance: The required error tolerance.

• iterations: The maximum number of iterative steps to perform.

• precon: Ignored.

__del__()

__enter__()

__exit__(exc_type, exc_value, traceback)

__repr__()

Return repr(self).

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

Bases: PETScKrylovSolver

The LinearPCGSolver is an interface to the cg solver in PETSc, using no preconditioner by default.

Parameters:

• tolerance: The required error tolerance.

• iterations: The maximum number of iterative steps to perform.

• precon: Preconditioner to use (string).

__del__()

__enter__()

__exit__(exc_type, exc_value, traceback)

__repr__()

Return repr(self).

solver = 'cg'

Subpackages

• fipy.solvers.petsc.comms package
  • Submodules
  • fipy.solvers.petsc.comms.parallelPETScCommWrapper module
    • ParallelPETScCommWrapper
      • ParallelPETScCommWrapper.Barrier()
      • ParallelPETScCommWrapper.MaxAll()
      • ParallelPETScCommWrapper.MinAll()
      • ParallelPETScCommWrapper.Norm2()
      • ParallelPETScCommWrapper.Nproc
      • ParallelPETScCommWrapper.__getstate__()
      • ParallelPETScCommWrapper.__repr__()
      • ParallelPETScCommWrapper.__setstate__()
      • ParallelPETScCommWrapper.all()
      • ParallelPETScCommWrapper.allclose()
      • ParallelPETScCommWrapper.allequal()
      • ParallelPETScCommWrapper.allgather()
      • ParallelPETScCommWrapper.any()
      • ParallelPETScCommWrapper.bcast()
      • ParallelPETScCommWrapper.mpi4py_comm
      • ParallelPETScCommWrapper.procID
      • ParallelPETScCommWrapper.sum()
  • fipy.solvers.petsc.comms.petscCommWrapper module
    • PETScCommWrapper
      • PETScCommWrapper.Barrier()
      • PETScCommWrapper.MaxAll()
      • PETScCommWrapper.MinAll()
      • PETScCommWrapper.Norm2()
      • PETScCommWrapper.Nproc
      • PETScCommWrapper.__getstate__()
      • PETScCommWrapper.__repr__()
      • PETScCommWrapper.__setstate__()
      • PETScCommWrapper.all()
      • PETScCommWrapper.allclose()
      • PETScCommWrapper.allequal()
      • PETScCommWrapper.allgather()
      • PETScCommWrapper.any()
      • PETScCommWrapper.bcast()
      • PETScCommWrapper.mpi4py_comm
      • PETScCommWrapper.procID
      • PETScCommWrapper.sum()
  • fipy.solvers.petsc.comms.serialPETScCommWrapper module
    • SerialPETScCommWrapper
      • SerialPETScCommWrapper.Barrier()
      • SerialPETScCommWrapper.MaxAll()
      • SerialPETScCommWrapper.MinAll()
      • SerialPETScCommWrapper.Norm2()
      • SerialPETScCommWrapper.Nproc
      • SerialPETScCommWrapper.__getstate__()
      • SerialPETScCommWrapper.__repr__()
      • SerialPETScCommWrapper.__setstate__()
      • SerialPETScCommWrapper.all()
      • SerialPETScCommWrapper.allclose()
      • SerialPETScCommWrapper.allequal()
      • SerialPETScCommWrapper.allgather()
      • SerialPETScCommWrapper.any()
      • SerialPETScCommWrapper.bcast()
      • SerialPETScCommWrapper.mpi4py_comm
      • SerialPETScCommWrapper.procID
      • SerialPETScCommWrapper.sum()

Submodules

fipy.solvers.petsc.dummySolver module

class fipy.solvers.petsc.dummySolver.DummySolver(*args, **kwargs)

Bases: PETScSolver

Solver that doesn’t do anything.

PETSc is intolerant of having zeros on the diagonal

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.

__del__()

__enter__()

__exit__(exc_type, exc_value, traceback)

__repr__()

Return repr(self).

fipy.solvers.petsc.linearBicgSolver module

class fipy.solvers.petsc.linearBicgSolver.LinearBicgSolver(tolerance=1e-10, iterations=1000, precon=None)

Bases: PETScKrylovSolver

The LinearBicgSolver is an interface to the biconjugate gradient solver in PETSc, using no preconditioner by default.

Parameters:

• tolerance: The required error tolerance.

• iterations: The maximum number of iterative steps to perform.

• precon: Preconditioner to use (string).

__del__()

__enter__()

__exit__(exc_type, exc_value, traceback)

__repr__()

Return repr(self).

solver = 'bicg'

fipy.solvers.petsc.linearCGSSolver module

class fipy.solvers.petsc.linearCGSSolver.LinearCGSSolver(tolerance=1e-10, iterations=1000, precon=None)

Bases: PETScKrylovSolver

The LinearCGSSolver is an interface to the conjugate gradient squared solver in PETSc, using no preconditioner by default.

Parameters:

• tolerance: The required error tolerance.

• iterations: The maximum number of iterative steps to perform.

• precon: Preconditioner to use (string).

__del__()

__enter__()

__exit__(exc_type, exc_value, traceback)

__repr__()

Return repr(self).

solver = 'cgs'

fipy.solvers.petsc.linearGMRESSolver module

class fipy.solvers.petsc.linearGMRESSolver.LinearGMRESSolver(tolerance=1e-10, iterations=1000, precon=None)

Bases: PETScKrylovSolver

The LinearGMRESSolver is an interface to the GMRES solver in PETSc, using no preconditioner by default.

Parameters:

• tolerance: The required error tolerance.

• iterations: The maximum number of iterative steps to perform.

• precon: Preconditioner to use (string).

__del__()

__enter__()

__exit__(exc_type, exc_value, traceback)

__repr__()

Return repr(self).

solver = 'gmres'

fipy.solvers.petsc.linearLUSolver module

class fipy.solvers.petsc.linearLUSolver.LinearLUSolver(tolerance=1e-10, iterations=10, precon='lu')

Bases: PETScSolver

The LinearLUSolver is an interface to the LU preconditioner in PETSc. A direct solve is performed.

Parameters:

• tolerance: The required error tolerance.

• iterations: The maximum number of iterative steps to perform.

• precon: Ignored.

__del__()

__enter__()

__exit__(exc_type, exc_value, traceback)

__repr__()

Return repr(self).

fipy.solvers.petsc.linearPCGSolver module

class fipy.solvers.petsc.linearPCGSolver.LinearPCGSolver(tolerance=1e-10, iterations=1000, precon=None)

Bases: PETScKrylovSolver

The LinearPCGSolver is an interface to the cg solver in PETSc, using no preconditioner by default.

Parameters:

• tolerance: The required error tolerance.

• iterations: The maximum number of iterative steps to perform.

• precon: Preconditioner to use (string).

__del__()

__enter__()

__exit__(exc_type, exc_value, traceback)

__repr__()

Return repr(self).

solver = 'cg'

fipy.solvers.petsc.petscKrylovSolver module

class fipy.solvers.petsc.petscKrylovSolver.PETScKrylovSolver(tolerance=1e-10, iterations=1000, precon=None)

Bases: PETScSolver

Attention

This class is abstract, always create one of its subclasses. It provides the code to call all Krylov solvers from the PETSc package.

Parameters:

• tolerance: The required error tolerance.

• iterations: The maximum number of iterative steps to perform.

• precon: Preconditioner to use (string).

__del__()

__enter__()

__exit__(exc_type, exc_value, traceback)

__repr__()

Return repr(self).

fipy.solvers.petsc.petscSolver module

class fipy.solvers.petsc.petscSolver.PETScSolver(*args, **kwargs)

Bases: Solver

Attention

This class is abstract. Always create one of its subclasses.

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.

__del__()

__enter__()

__exit__(exc_type, exc_value, traceback)

__repr__()

Return repr(self).

Last updated on Jun 27, 2023. Created using Sphinx 6.2.1.