gemseo_umdo / use_cases / beam_model

# uncertain_space module¶

The uncertain space for the beam use case.

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

Bases: ParameterSpace

The advanced uncertain space for the beam use case.

$F$, $E$ 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.