Lea 3.4.1 is now released!

https://pypi.org/project/lea/

What is Lea?
------------
Lea is a Python module for playing with discrete probability distributions
in an intuitive way.
This ranges from simple dice, coin flipping, random sampling . to Bayesian networks, Probabilistic Programming (PP), machine learning and symbolic computation.
One salient feature of Lea is the ability to change the probability representation, viz. float, fractions, decimals, and symbols.
Lea can be used for education, AI, PP, etc. Comprehensive tutorials are available online (see Wiki pages).
For a 5 minutes tour, check out the poster presented at PROBPROG2020 conference:
https://probprog.cc/2020/assets/posters/fri/69.pdf

What's new in Lea 3.4.1?
------------------------
1) Reading BIF files (Bayesian Interchange Format): https://bitbucket.org/piedenis/lea/wiki/Lea3_Tutorial_2
2) Misc corrections on Markov chain advanced functions (repair
dependencies):
https://bitbucket.org/piedenis/lea/issues/63/
3) Enhance the test suite, especially for information theory

To learn more...
----------------
Lea on PyPI -> http://pypi.org/project/lea
Lea project page -> http://bitbucket.org/piedenis/lea
Documentation -> http://bitbucket.org/piedenis/lea/wiki/Home

With the hope that Lea can make this universe less random (or more?),

Pierre Denis

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