gemseo_umdo / use_cases / beam_model

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uncertain_space module

The uncertain space for the beam use case.

class gemseo_umdo.use_cases.beam_model.uncertain_space.BeamUncertainSpace(uniform=True, **deltas)

Bases: ParameterSpace

The advanced uncertain space for the beam use case.

math:F, \(E\) and \(\sigma_{\text{all}}\) are random variables with nominal values -200000, 73500 and 300 and deviation values 10%, 5% and 5%.

Their probability distribution are centered in these values denoted \(\mu_F\), \(\mu_E\) and \(\mu_{\sigma_{\text{all}}}\).

Precisely, a uniform distribution is defined by the minimum \(\mu (1 - \delta)\) and the maximum \(\mu (1 + \delta)\) and a Gaussian distribution is defined by the mean \(\mu\) and the standard deviation \(|\mu|\delta/3\), where \(\delta\) is an aforementioned deviation value.

Parameters:

• uniform (bool) –

  If True, use uniform distributions; otherwise, use Gaussian ones.

  By default it is set to True.

• **deltas (float) – The percentage variations \(\delta\) around the nominal values of the random variables.

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, Distribution]

The marginal probability distributions of the uncertain variables.

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.