Discrete probability distributions in Python
Lea is a Python package aiming at working with discrete probability distributions in an intuitive way. It allows you to model a broad range of random phenomenons, like dice throwing, coin tossing, gambling, weather, finance, etc. More generally, Lea may be used for any finite set of discrete values having known probability: numbers, booleans, date/times, symbols, … Each probability distribution is modeled as a plain object, which can be named, displayed, queried or processed to produce new probability distributions.
Lea also provides advanced functions that target Probabilistic Programming (PP); these include conditional probabilities, Bayes inference and Markov chains. To ease interactive calculations, an optional PP language (PPL), called “Leapp”, is included in the package; it extends Python syntax with few constructs to define and manipulate probabilistic models in an extremely concise way.
Lea can run on Python 2.6, Python 2.7 or Python 3.
To install the present version of Lea, type the following command:
pip install lea==2.3.5
Please go on project home page below for a comprehensive documentation.