Skip to main content

Discrete probability distributions in Python

Project description

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 3.2.3, type the following command:

pip install lea==3.2.3

Please go on Lea project page (beside) for a comprehensive documentation.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

lea-3.2.3.tar.gz (73.4 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page