cashocs.space_mapping.optimal_control.ParameterExtraction#

class cashocs.space_mapping.optimal_control.ParameterExtraction(coarse_model: CoarseModel, cost_functional_form: list[_typing.CostFunctional] | _typing.CostFunctional, states: list[fenics.Function] | fenics.Function, controls: list[fenics.Function] | fenics.Function, config: io.Config | None = None, desired_weights: list[float] | None = None, mode: str = 'initial')[source]#

Bases: object

Parameter extraction for optimal control problems.

Initializes self.

Parameters:

  • coarse_model (CoarseModel) – The coarse model optimization problem

  • cost_functional_form (list[_typing.CostFunctional] | _typing.CostFunctional) – The cost functional for the parameter extraction

  • states (list[fenics.Function] | fenics.Function) – The state variables for the parameter extraction

  • controls (list[fenics.Function] | fenics.Function) – The control variables for the parameter extraction

  • config (io.Config | None) – config: The config file for the problem, generated via cashocs.load_config(). Alternatively, this can also be None, in which case the default configurations are used, except for the optimization algorithm. This has then to be specified in the solve method. The default is None.

  • desired_weights (list[float] | None) – The list of desired weights for the parameter extraction

  • mode (str) – The mode used for the initial guess of the parameter extraction. If this is coarse_optimum, the default, then the coarse model optimum is used as initial guess, if this is initial, then the initial guess for the optimization is used.

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