gemseo / uncertainty / distributions / scipy

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normal module

Class to create a normal distribution from the SciPy library.

This class inherits from SPDistribution.

class gemseo.uncertainty.distributions.scipy.normal.SPNormalDistribution(variable, mu=0.0, sigma=1.0, dimension=1)

Bases: SPDistribution

Create a normal distribution.

Example

>>> from gemseo.uncertainty.distributions.scipy.normal import (
...     SPNormalDistribution
... )
>>> distribution = SPNormalDistribution('x', -1, 2)
>>> print(distribution)
norm(mu=-1, sigma=2)

Parameters:

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

• mu (float) –

  The mean of the normal random variable.

  By default it is set to 0.0.

• sigma (float) –

  The standard deviation of the normal random variable.

  By default it is set to 1.0.

• dimension (int) –

  The dimension of the normal 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.

Examples using SPNormalDistribution

Probability distributions based on SciPy

Probability distributions based on SciPy