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:
tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (SmoothedAggregationPreconditioner, optional) –
- __del__()¶
- __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:
tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (SmoothedAggregationPreconditioner, optional) –
- __del__()¶
- __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:
- __del__()¶
- __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:
- __del__()¶
- __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:
tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (SmoothedAggregationPreconditioner, optional) –
- __del__()¶
- __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:
tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (SmoothedAggregationPreconditioner, optional) –
- __del__()¶
- __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:
tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (SmoothedAggregationPreconditioner, optional) –
- __del__()¶
- __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:
- __del__()¶
- __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:
- __del__()¶
- __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:
tolerance (float) – Required error tolerance.
iterations (int) – Maximum number of iterative steps to perform.
precon (SmoothedAggregationPreconditioner, optional) –
- __del__()¶
- __enter__()¶
- __exit__(exc_type, exc_value, traceback)¶
- __repr__()¶
Return repr(self).