gemseo / uncertainty / distributions

gemseo.uncertainty.distributions.scipy

• distribution
• exponential
• factory
• joint
• normal
• triangular
• uniform
• weibull

Scipy-based capabilities for probability distributions.

This package interfaces capabilities from the SciPy library.

Interfaced distributions

This package implements the abstract classes BaseDistribution and BaseJointDistribution.

Classical distributions

This module also implements a deliberately limited selection of classical probability distributions in a user-friendly way: SPExponentialDistribution, SPNormalDistribution, SPTriangularDistribution, and SPUniformDistribution. More precisely, the argument whose nature is a dictionary of keyword parameters is replaced with several user-defined keyword arguments. In this way, the use writes SPUniformDistribution('x', -1., 3.) or SPUniformDistribution('x', minimum=-1., maximum=3.) instead of SPDistribution('x', 'Uniform', {"loc": -1, "scale": 4}). Furthermore, these classes inheriting from SPDistribution are documented in such a way that a newbie could easily apprehend them.

Joint probability distribution

A SPDistribution has a SPDistribution.JOINT_DISTRIBUTION_CLASS attribute referencing SPJointDistribution which is a class to build a joint probability distribution related to given random variables from a list of SPDistribution objects implementing the probability distributions of these variables based on the SciPy library and from a copula name.

Note

A copula is a mathematical function used to define the dependence between random variables from their cumulative density functions. See more.