ANN: Lea 2.2.0

Pierre Denis pie.denis at
Wed May 4 09:57:37 EDT 2016

Lea 2.2.0 is now released!

What is Lea?
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, finance,
weather, etc. It offers high-level modeling features for probabilistic
programming and bayesian inference. Lea has several original features: the
storage of probabilities as integer weights, an inference algorithm that
produces *exact* results and a strong emphasis on ease-of-use. Lea is
lightweight, open-source (LGPL) and pure Python, with support of versions 2
and 3). See project page below for installation, tutorials, examples, etc.

What's new in Lea 2.2.0?
Compared to latest version (2.1.2), many things have been made to improve
ease-of-use and overall performance. Maybe one of the most notable feature
is that you can now get individual probabilities very easily, as a fraction
or float, thanks to the new 'P' and 'Pf' functions. Here are some examples
that you can type in your Python console:

	>>> P(dice <= 5)
	>>> Pf(dice <= 5)
	>>> P(rain.given(grassWet))
	>>> Pf(rain.given(grassWet))

Other new features include:
- build joint probability distributions from CSV files or Pandas dataframes
- pmf histograms using matplotlib
- Monte-Carlo sampling estimation
- multi-arguments 'given' method (ANDing of evidences)
- likelihood ratio
- extended 'draw' method: with/without sorting, with/without replacement
- machine learning (experimental)
- built-in functions and distributions for games
- various optimizations

Most of the new features are documented in a new tutorial on Lea's wiki

Thanks to all of you for this large bunch of feedbacks, encouragements and
suggestions! In particular, the present version owes much to Paul Moore, who
made important contributions; among other things, Paul fixed the
installation procedure, set up a test suite using the Tox tool and created
an efficient algorithm for calculating probability distribution resulting
from a drawing process. Thanks Paul for making the package more mature!

Lea project page

Download Lea (PyPI)

With the hope that Lea can make your joy less random,

Pierre Denis

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