KrylovLinearSolver

class KrylovLinearSolver

Bases: LinearSolver

KrylovLinearSolver class for setting up the Krylov linear solver.

When used as the linear_solver on NavierStokesSolver, max_iterations is interpreted as the Krylov iterations.

Example

>>> fl.KrylovLinearSolver(
...     max_iterations=15,
...     max_preconditioner_iterations=25,
...     relative_tolerance=0.05,
... )

Attributes

max_iterations: int

Number of Krylov iterations.

Default:

15

absolute_tolerance: float, optional

The linear solver converges when the final residual of the pseudo steps below this value.Either absolute tolerance or relative tolerance can be used to determine convergence.

Default:

None

relative_tolerance: float

Relative tolerance for the Krylov linear solver convergence.

Default:

0.05

max_preconditioner_iterations: int

Number of preconditioner sweeps per Krylov iteration.

Default:

25

Additional Constructors

classmethod from_file(filename)

Loads a Flow360BaseModel from .json, or .yaml file.

Parameters:

filename (str) – Full path to the .yaml or .json file to load the Flow360BaseModel from.

Returns:

An instance of the component class calling load.

Return type:

Flow360BaseModel

Example

>>> params = Flow360BaseModel.from_file(filename='folder/sim.json') 

Methods

help(methods=False)

Prints message describing the fields and methods of a Flow360BaseModel.

Parameters:

methods (bool = False) – Whether to also print out information about object’s methods.

Return type:

None

Example

>>> params.help(methods=True) 

to_file(filename, **kwargs)

Exports Flow360BaseModel instance to .json or .yaml file

Parameters:

filename (str) – Full path to the .json or .yaml or file to save the Flow360BaseModel to.

Return type:

None

Example

>>> params.to_file(filename='folder/flow360.json')