gemseo / uncertainty / distributions / openturns

# dirac module¶

The Dirac distribution based on OpenTURNS.

class gemseo.uncertainty.distributions.openturns.dirac.OTDiracDistribution(variable, variable_value=0.0, dimension=1, transformation=None, lower_bound=None, upper_bound=None, threshold=0.5)[source]

Bases: OTDistribution

The Dirac distribution.

Example

>>> from gemseo.uncertainty.distributions.openturns.distribution import (
...     OTDistribution
... )
>>> distribution = OTDistribution('x', 'Exponential', (3, 2))
>>> print(distribution)
Exponential(3, 2)

Parameters:
• variable (str) – The name of the random variable.

• variable_value (float) –

The value of the random variable.

By default it is set to 0.0.

• dimension (int) –

The dimension of the random variable.

By default it is set to 1.

• transformation (str | None) – A transformation applied to the random variable, e.g. $$\sin(x)$$. If None, no transformation.

• lower_bound (float | None) – A lower bound to truncate the probability distribution. If None, no lower truncation.

• upper_bound (float | None) – An upper bound to truncate the probability distribution. If None, no upper truncation.

• threshold (float) –

A threshold in [0,1].

By default it is set to 0.5.

dimension: int

The number of dimensions of the random variable.

distribution_name: str

The name of the probability distribution.

marginals: list[ot.Distribution]

The marginal distributions of the components of the random variable.

math_lower_bound: ndarray

The mathematical lower bound of the random variable.

math_upper_bound: ndarray

The mathematical upper bound of the random variable.

num_lower_bound: ndarray

The numerical lower bound of the random variable.

num_upper_bound: ndarray

The numerical upper bound of the random variable.

parameters: tuple[Any] | dict[str, Any]

The parameters of the probability distribution.

standard_parameters: dict[str, str] | None

The standard representation of the parameters of the distribution, used for its string representation.

transformation: str

The transformation applied to the random variable, e.g. ‘sin(x)’.

variable_name: str

The name of the random variable.