gemseo / uncertainty / use_cases / ishigami

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ishigami_space module

The uncertain space used in the Ishigami use case.

class gemseo.uncertainty.use_cases.ishigami.ishigami_space.IshigamiSpace(uniform_distribution_name=UniformDistribution.SCIPY)[source]

Bases: ParameterSpace

The uncertain space used in the Ishigami use case.

\(X_1,X_2,X_3\) are independent random variables uniformly distributed between \(-\pi\) and \(\pi\).

This uncertain space uses the class SPUniformDistribution.

See [IH90].

Parameters:

uniform_distribution_name (UniformDistribution) –

The name of the class implementing the uniform distribution.

By default it is set to “SPUniformDistribution”.

class UniformDistribution(value)[source]

Bases: StrEnum

The name of the class implementing the uniform distribution.

OPENTURNS = 'OTUniformDistribution'
SCIPY = 'SPUniformDistribution'
dimension: int

The total dimension of the space, corresponding to the sum of the sizes of the variables.

distribution: ComposedDistribution

The joint probability distribution of the uncertain variables.

distributions: dict[str, ComposedDistribution]

The marginal probability distributions of the uncertain variables.

These variables are defined as random vectors with independent components.

name: str | None

The name of the space.

normalize: dict[str, ndarray]

The normalization policies of the variables components indexed by the variables names; if True, the component can be normalized.

uncertain_variables: list[str]

The names of the uncertain variables.

variable_names: list[str]

The names of the variables.

variable_sizes: dict[str, int]

The sizes of the variables.

variable_types: dict[str, ndarray]

The types of the variables components, which can be any DesignSpace.DesignVariableType.

Examples using IshigamiSpace

Comparing sensitivity indices

Comparing sensitivity indices

Correlation analysis

Correlation analysis

Morris analysis

Morris analysis

Sobol’ analysis

Sobol' analysis