implementations.convergence_controller_classes.check_iteration_estimator module

class CheckIterationEstimatorNonMPI(controller, params, description, **kwargs)[source]

Bases: ConvergenceController

check_iteration_status(controller, S, **kwargs)[source]
Parameters:

  • controller (pySDC.Controller) – The controller

  • S (pySDC.step) – The current step

Returns:

None

check_parameters(controller, params, description, **kwargs)[source]

Check whether parameters are compatible with whatever assumptions went into the step size functions etc. In this case, we need the user to supply a tolerance.

Parameters:

  • controller (pySDC.Controller) – The controller

  • params (dict) – The params passed for this specific convergence controller

  • description (dict) – The description object used to instantiate the controller

Returns:

Whether the parameters are compatible str: The error message

Return type:

bool

dependencies(controller, description, **kwargs)[source]

Need to store the solution of previous iterations.

Parameters:

  • controller (pySDC.Controller) – The controller

  • description (dict) – The description object used to instantiate the controller

Returns:

None

reset_buffers_nonMPI(controller, **kwargs)[source]

Reset buffers used to immitate communication in non MPI version.

Parameters:

controller (pySDC.controller) – The controller

Returns:

None

setup(controller, params, description, **kwargs)[source]

Setup parameters. Here we only give a default value for the control order.

Parameters:

  • controller (pySDC.Controller) – The controller

  • params (dict) – Parameters for the convergence controller

  • description (dict) – The description object used to instantiate the controller

Returns:

The updated parameters

Return type:

dict

setup_status_variables(controller, **kwargs)[source]

Setup storage variables for the differences between sweeps for all steps.

Parameters:

controller (pySDC.Controller) – The controller

Returns:

None