gemseo / uncertainty / distributions / openturns

# exponential module¶

Class to create an exponential distribution from the OpenTURNS library.

This class inherits from OTDistribution.

class gemseo.uncertainty.distributions.openturns.exponential.OTExponentialDistribution(variable, rate=1.0, loc=0.0, dimension=1, transformation=None, lower_bound=None, upper_bound=None, threshold=0.5)[source]

Bases: OTDistribution

Create an exponential distribution.

Example

>>> from gemseo.uncertainty.distributions.openturns.exponential import (
...     OTExponentialDistribution
... )
>>> distribution = OTExponentialDistribution('x', 2, 3)
>>> print(distribution)
Exponential(loc=3, rate=2)

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

• rate (float) –

The rate of the exponential random variable.

By default it is set to 1.0.

• loc (float) –

The location of the exponential random variable.

By default it is set to 0.0.

• dimension (int) –

The dimension of the exponential 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 distribution. If None, no lower truncation.

• upper_bound (float | None) – An upper bound to truncate the 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.