gemseo / post

opt_history_view module

Basic display of optimization history: functions and x.

Classes:

OptHistoryView(opt_problem)

The OptHistoryView post processing performs separated plots: the design variables history, the objective function history, the history of hessian approximation of the objective, the inequality constraint history, the equality constraint history, and constraints histories.

class gemseo.post.opt_history_view.OptHistoryView(opt_problem)[source]

Bases: gemseo.post.opt_post_processor.OptPostProcessor

The OptHistoryView post processing performs separated plots: the design variables history, the objective function history, the history of hessian approximation of the objective, the inequality constraint history, the equality constraint history, and constraints histories.

By default, all design variables are considered. A sublist of design variables can be passed as options. Minimum and maximum values for the plot can be passed as options. The objective function can also be represented in terms of difference w.r.t. the initial value It is possible either to save the plot, to show the plot or both.

Attributes
  • opt_problem (OptimizationProblem) – The optimization problem.

  • database (Database) – The database generated by the optimization problem.

  • out_data_dict (Dict[Any,Any]) – The data dict to eventually rebuild the plot in another framework.

Parameters

opt_problem (OptimizationProblem) – The optimization problem to be post-processed.

Raises

ValueError – If the JSON grammar file for the options of the post-processor does not exist.

Return type

None

Methods:

check_options(**options)

Check the options of the post-processor.

execute([save, show, file_path, …])

Post-process the optimization problem.

Attributes:

figures

The Matplotlib figures indexed by a name, or the nameless figure counter.

output_files

The paths to the output files.

check_options(**options)

Check the options of the post-processor.

Parameters
  • **options – The options of the post-processor.

  • options (Union[int, float, str, bool, Sequence[str]]) –

Raises

InvalidDataException – If an option is invalid according to the grammar.

Return type

None

execute(save=True, show=False, file_path=None, directory_path=None, file_name=None, file_extension=None, **options)

Post-process the optimization problem.

Parameters
  • save (bool) – If True, save the figure.

  • show (bool) – If True, display the figure.

  • file_path (Optional[Union[str, pathlib.Path]]) – The path of the file to save the figures. If the extension is missing, use file_extension. If None, create a file path from directory_path, file_name and file_extension.

  • directory_path (Optional[Union[str, pathlib.Path]]) – The path of the directory to save the figures. If None, use the current working directory.

  • file_name (Optional[str]) – The name of the file to save the figures. If None, use a default one generated by the post-processing.

  • file_extension (Optional[str]) – A file extension, e.g. ‘png’, ‘pdf’, ‘svg’, … If None, use a default file extension.

  • **options – The options of the post-processor.

  • options (Union[int, float, str, bool, Sequence[str]]) –

Returns

The figure, to be customized if not closed.

Raises

ValueError – If the opt_problem.database is empty.

Return type

Dict[str, matplotlib.figure.Figure]

property figures

The Matplotlib figures indexed by a name, or the nameless figure counter.

property output_files

The paths to the output files.