Metadata-Version: 2.1
Name: boisgera-pioupiou
Version: 0.0a11
Summary: A nano probabilistic programming language for Python
Home-page: https://github.com/boisgera/pioupiou
Author: Sébastien Boisgérault
Author-email: Sebastien.Boisgerault@mines-paristech.fr
License: MIT License
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Education
Classifier: Topic :: Scientific/Engineering :: Mathematics
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: wrapt

Pioupiou 🐤
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[![test](https://github.com/boisgera/pioupiou/actions/workflows/test.yml/badge.svg)](https://github.com/boisgera/pioupiou/actions/workflows/test.yml)
![coverage](https://img.shields.io/endpoint?url=https://gist.githubusercontent.com/boisgera/13615cd4d2f090624f8fa068f29d67f9/raw/test.json)
![stage](https://img.shields.io/badge/stage-pre--alpha-red) 

Introduction
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Pioupiou is a nano probabilistic programming language, embedded into Python.

Use it to define probabilistic models :

    >>> import pioupiou as pp
    >>> a, b = 0.5, 1.0
    >>> X = pp.Uniform(0.0, 1.0)
    >>> E = pp.Normal(0.0, 0.1)
    >>> Y = a * X + b + E

and to simulate them :

    >>> n = 1000 # number of samples
    >>> omega = pp.Omega(n)
    >>> x, y = X(omega), Y(omega)
    >>> x # doctest: +ELLIPSIS
    array([6.36961687e-01, 2.69786714e-01, 4.09735239e-02, ..., 3.80007897e-01])
    >>> y # doctest: +ELLIPSIS
    array([1.09588258, 1.22942954, 1.01954509, 0.99213115, ..., 1.14366864])

That's about it! Use this data as you see fit.

![data](https://boisgera.github.io/pioupiou/images/xy.svg)

Getting started
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Install the latest version of pioupiou with:

    $ pip install --upgrade git+https://github.com/boisgera/pioupiou.git


