gemseo / post

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variable_influence module

Plot the partial sensitivity of the functions.


Bases: OptPostProcessor

First order variable influence analysis.

This post-processing computes \(\frac{\partial f(x)}{\partial x_i}\left(x_i^* - x_i^{(0)}\right)\) where \(x_i^{(0)}\) is the initial value of the variable and \(x_i^*\) is the optimal value of the variable.

Options of the plot method are:

  • proportion of the total sensitivity to use as a threshold to filter the variables,

  • the use of a logarithmic scale,

  • the possibility to save the indices of the influential variables indices in a NumPy file.


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


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

DEFAULT_FIG_SIZE = (20.0, 5.0)

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

database: Database

The database generated by the optimization problem.

materials_for_plotting: dict[Any, Any]

The materials to eventually rebuild the plot in another framework.

opt_problem: OptimizationProblem

The optimization problem.