I have the pleasure to announce the release of Lea 1.1.
Lea is a Python package aiming at working with discrete probability distributions in an intuitive way.
It allows modelling a broad range of random discrete phenomenons. Then, it allows calculating probabilities of events, whether atomic, aggregated or combined through given operations. A typical example is the probabilities of the sum of N dice having known, possibly unfair, probability distributions.
Here are the main features of Lea:
- models finite discrete probability distributions - standard distribution indicators (mean, standard deviation,.) - arithmetic and logical operators on probability distribution - cartesian products, conditional probabilities, joint distributions - generation of random samples - open-source project, LGPL license - pure Python module, lightweight - no package dependency - probabilities stored as integers (no floating-point biases)
(with wiki documentation including tutorials, examples and API)
Hoping this could be helpful in this uncertain universe...