gemseo / post

Quadratic approximations of functions from the optimization history.

And cuts of the approximation.

The function index can be passed as option.

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

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, 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 (tuple[float, float] | 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.

static unnormalize_vector(xn_array, ivar, lower_bounds, upper_bounds)[source]

Unormalize a variable with respect to bounds.

Parameters:
• xn_array (ndarray) – The normalized variable.

• ivar (int) – The index of the variable bound.

• lower_bounds (ndarray) – The lower bounds of the variable.

• upper_bounds (ndarray) – The upper bounds of the variable.

Returns:

The unnormalized variable.

Return type:

ndarray

DEFAULT_FIG_SIZE = (9.0, 6.0)

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

Type:
SR1_APPROX = 'SR1'
database: Database

The database generated by the optimization problem.

property figures: dict[str, matplotlib.figure.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.