Source code for implementations.convergence_controller_classes.step_size_limiter

import numpy as np
from pySDC.core.ConvergenceController import ConvergenceController


[docs] class StepSizeLimiter(ConvergenceController): """ Class to set limits to adaptive step size computation during run time Please supply dt_min or dt_max in the params to limit in either direction """
[docs] def setup(self, controller, params, description, **kwargs): """ Define parameters here Args: 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: (dict): The updated params dictionary """ defaults = { "control_order": +92, "dt_min": 0, "dt_max": np.inf, } return {**defaults, **super().setup(controller, params, description, **kwargs)}
[docs] def dependencies(self, controller, description, **kwargs): """ Load the slope limiter if needed. Args: controller (pySDC.Controller): The controller description (dict): The description object used to instantiate the controller Returns: None """ slope_limiter_keys = ['dt_slope_min', 'dt_slope_max'] available_keys = [me for me in slope_limiter_keys if me in self.params.__dict__.keys()] if len(available_keys) > 0: slope_limiter_params = {key: self.params.__dict__[key] for key in available_keys} slope_limiter_params['control_order'] = self.params.control_order - 1 controller.add_convergence_controller( StepSizeSlopeLimiter, params=slope_limiter_params, description=description ) return None
[docs] def get_new_step_size(self, controller, S, **kwargs): """ Enforce an upper and lower limit to the step size here. Be aware that this is only tested when a new step size has been determined. That means if you set an initial value for the step size outside of the limits, and you don't do any further step size control, that value will go through. Also, the final step is adjusted such that we reach Tend as best as possible, which might give step sizes below the lower limit set here. Args: controller (pySDC.Controller): The controller S (pySDC.Step): The current step Returns: None """ for L in S.levels: if L.status.dt_new is not None: if L.status.dt_new < self.params.dt_min: self.log( f"Step size is below minimum, increasing from {L.status.dt_new:.2e} to \ {self.params.dt_min:.2e}", S, ) L.status.dt_new = self.params.dt_min elif L.status.dt_new > self.params.dt_max: self.log( f"Step size exceeds maximum, decreasing from {L.status.dt_new:.2e} to {self.params.dt_max:.2e}", S, ) L.status.dt_new = self.params.dt_max return None
[docs] class StepSizeSlopeLimiter(ConvergenceController): """ Class to set limits to adaptive step size computation during run time Please supply dt_min or dt_max in the params to limit in either direction """
[docs] def setup(self, controller, params, description, **kwargs): """ Define parameters here Args: 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: (dict): The updated params dictionary """ defaults = { "control_order": 91, "dt_slope_min": 0, "dt_slope_max": np.inf, } return {**defaults, **super().setup(controller, params, description, **kwargs)}
[docs] def get_new_step_size(self, controller, S, **kwargs): """ Enforce an upper and lower limit to the slope of the step size here. The final step is adjusted such that we reach Tend as best as possible, which might give step sizes below the lower limit set here. Args: controller (pySDC.Controller): The controller S (pySDC.Step): The current step Returns: None """ for L in S.levels: if L.status.dt_new is not None: if L.status.dt_new / L.params.dt < self.params.dt_slope_min: dt_new = L.params.dt * self.params.dt_slope_min self.log( f"Step size slope is below minimum, increasing from {L.status.dt_new:.2e} to \ {dt_new:.2e}", S, ) L.status.dt_new = dt_new elif L.status.dt_new / L.params.dt > self.params.dt_slope_max: dt_new = L.params.dt * self.params.dt_slope_max self.log( f"Step size slope exceeds maximum, decreasing from {L.status.dt_new:.2e} to \ {dt_new:.2e}", S, ) L.status.dt_new = dt_new return None