gemseo / post

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constraints_history module

A matrix of constraint history plots.

class gemseo.post.constraints_history.ConstraintsHistory(opt_problem)[source]

Bases: OptPostProcessor

A matrix of constraint history plots.

A blue line represents the values of a constraint w.r.t. the iterations.

A background color indicates whether the constraint is satisfied (green), active (white) or violated (red).

An horizontal black line indicates the value for which an inequality constraint is active or an equality constraint is satisfied, namely \(0\). An horizontal black dashed line indicates the value below which an inequality constraint is satisfied with a tolerance level, namely \(\varepsilon\).

For an equality constraint, the horizontal dashed black lines indicate the values between which the constraint is satisfied with a tolerance level, namely \(-\varepsilon\) and \(\varepsilon\).

A vertical black line indicates the last iteration (or pseudo-iteration) where the constraint is (or should be) active.

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.

check_options(**options)

Check the options of the post-processor.

Parameters:

**options (int | float | str | bool | Sequence[str] | tuple[float, float]) – The options of the post-processor.

Raises:

InvalidDataError – 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, fig_size=None, **options)

Post-process the optimization problem.

Parameters:

  • save (bool) –

    If True, save the figure.

    By default it is set to True.

  • show (bool) –

    If True, display the figure.

    By default it is set to False.

  • file_path (str | Path | None) – 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 (str | Path | None) – The path of the directory to save the figures. If None, use the current working directory.

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

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

  • fig_size (FigSizeType | None) – The width and height of the figure in inches, e.g. (w, h). If None, use the OptPostProcessor.DEFAULT_FIG_SIZE of the post-processor.

  • **options (OptPostProcessorOptionType) – The options of the post-processor.

Returns:

The figures, to be customized if not closed.

Raises:

ValueError – If the opt_problem.database is empty.

DEFAULT_FIG_SIZE = (11.0, 11.0)

The default width and height of the figure, in inches.

database: Database

The database generated by the optimization problem.

property figures: dict[str, Figure]

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

materials_for_plotting: dict[Any, Any]

The materials to eventually rebuild the plot in another framework.

opt_problem: OptimizationProblem

The optimization problem.

property output_files: list[str]

The paths to the output files.