gemseo / post

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correlations module

Correlations in the optimization database.

class gemseo.post.correlations.Correlations(opt_problem)[source]

Bases: OptPostProcessor

Scatter plots of the correlated variables.

These variables can be design variables, constraints, objective or observables. This post-processor considers all the correlations greater than a threshold.

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.

static func_order(func_names, x)[source]

Key function to sort function components.

Parameters:

  • func_names (Sequence[str]) – The functions names in the required order.

  • x (str) – An element from a list.

Returns:

The index to be given to the sort method and the function name associated to that index.

Return type:

tuple[int, str]

DEFAULT_FIG_SIZE = (15.0, 10.0)

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

MAXIMUM_CORRELATION_COEFFICIENT = 0.999999999

The maximum correlation coefficient above which the variable is not plotted.

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.