def __init__(self, tolerance=1e-10, iterations=5, MLOptions={}, testUnsupported = False):
"""
:Parameters:
- `tolerance`: The required error tolerance.
- `iterations`: The maximum number of iterations to perform per test.
- `MLOptions`: Options to pass to ML. A dictionary of {option:value} pairs. This will be passed to ML.SetParameterList.
- `testUnsupported`: test smoothers that are not currently implemented in preconditioner objects.
For detailed information on the possible parameters for ML, see
http://trilinos.sandia.gov/packages/ml/documentation.html
Currently, passing options to Aztec through ML is not supported.
"""
TrilinosSolver.__init__(self, tolerance=tolerance,
iterations=iterations)
self.MLOptions = MLOptions
if "output" not in self.MLOptions:
self.MLOptions["output"] = 0
if "test: max iters" not in self.MLOptions:
self.MLOptions["test: max iters"] = iterations
if "test: tolerance" not in self.MLOptions:
self.MLOptions["test: tolerance"] = tolerance
unsupportedSmoothers = ["Jacobi", "Gauss-Seidel", "block Gauss-Seidel", "ParaSails", "IFPACK", "ML"]
if not testUnsupported:
for smoother in unsupportedSmoothers:
if ("test: " + smoother) not in self.MLOptions:
self.MLOptions["test: " + smoother] = False
def __init__(self, equation, jacobian=None, tolerance=1e-10, iterations=1000,
printingOptions=None, solverOptions=None, linearSolverOptions=None,
lineSearchOptions=None, directionOptions=None, newtonOptions=None):
TrilinosSolver.__init__(self, tolerance=tolerance, iterations=iterations, precon=None)
self.equation = equation
self.jacobian = jacobian
self.nlParams = NOX.Epetra.defaultNonlinearParameters(parallelComm.epetra_comm, 2)
self.nlParams["Printing"] = printingOptions or {
'Output Precision': 3,
'MyPID': 0,
'Output Information': NOX.Utils.OuterIteration,
'Output Processor': 0
}
self.nlParams["Solver Options"] = solverOptions or {
'Status Test Check Type': 'Complete',
'Rescue Bad Newton Solve': 'True'
}
self.nlParams["Linear Solver"] = linearSolverOptions or {
'Aztec Solver': 'GMRES',
'Tolerance': 0.0001,
'Max Age Of Prec': 5,
'Max Iterations': 20,
'Preconditioner': 'Ifpack'
}
self.nlParams["Line Search"] = lineSearchOptions or {'Method': "Polynomial"}
self.nlParams["Direction"] = directionOptions or {'Method': 'Newton'}
self.nlParams["Newton"] = newtonOptions or {'Forcing Term Method': 'Type 2'}
self.nox = _NOXInterface(solver=self)
def __init__(self, equation, jacobian=None, tolerance=1e-10, iterations=1000,
printingOptions=None, solverOptions=None, linearSolverOptions=None,
lineSearchOptions=None, directionOptions=None, newtonOptions=None):
TrilinosSolver.__init__(self, tolerance=tolerance, iterations=iterations, precon=None)
self.equation = equation
self.jacobian = jacobian
self.nlParams = NOX.Epetra.defaultNonlinearParameters(parallelComm.epetra_comm, 2)
self.nlParams["Printing"] = printingOptions or {
'Output Precision': 3,
'MyPID': 0,
'Output Information': NOX.Utils.OuterIteration,
'Output Processor': 0
}
self.nlParams["Solver Options"] = solverOptions or {
'Status Test Check Type': 'Complete',
'Rescue Bad Newton Solve': 'True'
}
self.nlParams["Linear Solver"] = linearSolverOptions or {
'Aztec Solver': 'GMRES',
'Tolerance': 0.0001,
'Max Age Of Prec': 5,
'Max Iterations': 20,
'Preconditioner': 'Ifpack'
}
self.nlParams["Line Search"] = lineSearchOptions or {'Method': "Polynomial"}
self.nlParams["Direction"] = directionOptions or {'Method': 'Newton'}
self.nlParams["Newton"] = newtonOptions or {'Forcing Term Method': 'Type 2'}
self.nox = _NOXInterface(solver=self)
def __init__(self,
tolerance=1e-10,
iterations=10,
precon=None,
maxIterations=10):
"""
:Parameters:
- `tolerance`: The required error tolerance.
- `iterations`: The maximum number of iterative steps to perform.
"""
iterations = min(iterations, maxIterations)
TrilinosSolver.__init__(self,
tolerance=tolerance,
iterations=iterations,
precon=None)
if precon is not None:
import warnings
warnings.warn(
"Trilinos KLU solver does not accept preconditioners.",
UserWarning,
stacklevel=2)
self.Factory = Amesos.Factory()
def __init__(self, tolerance=1e-10, iterations=1000, precon=JacobiPreconditioner()):
"""
:Parameters:
- `tolerance`: The required error tolerance.
- `iterations`: The maximum number of iterative steps to perform.
- `precon`: Preconditioner object to use.
"""
if self.__class__ is TrilinosAztecOOSolver:
raise NotImplementedError, "can't instantiate abstract base class"
TrilinosSolver.__init__(self, tolerance=tolerance,
iterations=iterations, precon=None)
self.preconditioner = precon
def __init__(self, tolerance=1e-10, iterations=10, precon=None, maxIterations=10):
"""
:Parameters:
- `tolerance`: The required error tolerance.
- `iterations`: The maximum number of iterative steps to perform.
"""
iterations = min(iterations, maxIterations)
TrilinosSolver.__init__(self, tolerance=tolerance,
iterations=iterations, precon=None)
if precon is not None:
import warnings
warnings.warn("Trilinos KLU solver does not accept preconditioners.",
UserWarning, stacklevel=2)
self.Factory = Amesos.Factory()
def __init__(self,
tolerance=1e-10,
iterations=1000,
precon=JacobiPreconditioner()):
"""
Parameters
----------
tolerance : float
Required error tolerance.
iterations : int
Maximum number of iterative steps to perform.
precon : ~fipy.solvers.trilinos.preconditioners.preconditioner.Preconditioner
"""
if self.__class__ is TrilinosAztecOOSolver:
raise NotImplementedError("can't instantiate abstract base class")
TrilinosSolver.__init__(self,
tolerance=tolerance,
iterations=iterations,
precon=None)
self.preconditioner = precon