Discrete probability distributions in Python
Lea is a Python module aiming at working with discrete probability distributions in an intuitive way.
It allows you modeling a broad range of random phenomena: 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 and Probabilistic Programming (PP) features; these include conditional probabilities, JPD, CPT, BN, Markov chains and symbolic computation.
Lea can be used for AI, machine learning, education, …
To install Lea 3.0.1, type the following command:
pip install lea==3.0.1
Please go on Lea project page (beside) for a comprehensive documentation.