ANN: Lea 3.1.0 released

Pierre Denis pie.denis at
Mon Mar 25 17:11:27 EDT 2019

Lea 3.1.0 final is now released!


What is Lea?
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, Bayesian
networks, joint probability distributions, Markov chains and symbolic
computation. Lea can be used for AI, PP, gambling, education, ...

LGPL - Python 2.6+ / Python 3 supported

What's new in Lea 3.1.0?
The present version essentially consolidates the previous one (3.0.1),
adding just few new features. The main changes are:

- new switch_func method, for defining CPT by a function (far less
memory-consuming for models like noisy-or, noisy-max)
- improvements on Markov chain functions, including calculation of absorbing
- optimization of lea.max_of, lea.min_of functions
- bug fixes for symbolic calculation (in particular for Python 2.7)
- numerous addings/improvements on wiki tutorials and documentation,
especially on Lea API

Many thanks...
... to Paul Moore, Jens Finkhaeuser and Rasmus Bonnevie who provided
proposals, contributions, feedbacks that gave the impetus for the present

To learn more...
Lea 3 on PyPI     ->
Lea project page  ->
Documentation     ->
Statues algorithm ->

With the hope that Lea can make this Universe less hazardous,

Pierre Denis

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