gemseo / uncertainty / distributions / scipy

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uniform module

Class to create a uniform distribution from the SciPy library.

This class inherits from SPDistribution.

class gemseo.uncertainty.distributions.scipy.uniform.SPUniformDistribution(variable, minimum=0.0, maximum=1.0, dimension=1)[source]

Bases: SPDistribution

Create a uniform distribution.

Example

>>> from gemseo.uncertainty.distributions.scipy.uniform import (
...     SPUniformDistribution
... )
>>> distribution = SPUniformDistribution('x', -1, 1)
>>> print(distribution)
uniform(lower=-1, upper=1)
Parameters:

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

  • minimum (float) –

    The minimum of the uniform random variable.

    By default it is set to 0.0.

  • maximum (float) –

    The maximum of the uniform random variable.

    By default it is set to 1.0.

  • dimension (int) –

    The dimension of the uniform random variable.

    By default it is set to 1.

dimension: int

The number of dimensions of the random variable.

distribution: type

The probability distribution of the random variable.

distribution_name: str

The name of the probability distribution.

marginals: list[type]

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.