Lea documentation
=================

.. include:: ./description.rst

**Features:**

  * **discrete probability distributions** - support: any object!
  * **probabilistic arithmetic**: arithmetic, comparison, logical operators and functions
  * **probabilistic programming (PP)**: Bayesian reasoning, CPT, BN, JPD, MC sampling, Markov chains, …
  * **machine learning**: maximum likelihood & EM algorithms
  * **standard indicators** + **information theory**
  * **multiple probability representations**: float, decimal, fraction, …
  * **symbolic computation**, i.e. producing probability formulas instead of numbers, using the `SymPy library`_
  * **exact probabilistic inference** based on Python generators
  * **random sampling**
  * **comprehensive tutorials** (Wiki)
  * **Python 3.8+** supported (for Python 2.6+, use Lea 3)
  * **open-source** - LGPL license

.. _SymPy library: http://www.sympy.org

lea module
==========

.. toctree::
   :maxdepth: 2

   lea_module_doc