Metadata-Version: 2.1
Name: gprob
Version: 0.1.0
Summary: Probabilistic programming with arrays of Gaussian variables.
Author-email: Sergey Fedorov <fedorov.s.a@outlook.com>
License: MIT License
        
        Copyright (c) 2024 Sergey A. Fedorov
        
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Keywords: Gaussian distribution,Noise,Random variables,Stochastic processes,Gaussian processes,Probabilistic programming,Python,Numpy
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy

# gprob
gprob is a probabilistic programming language for Gaussian random variables with exact conditioning, implemented as a python package.

A brief example:
```python
from gprob import normal

# Initializing two independent normal variables.
x = normal(0, 1)
y = normal(0, 1)

# The joint distribution of x and y under the contition that 
# their sum is zero is obtained as 
z = (x & y) | {x-y: 0}

z.cov()
```



## Requirements
* python >= 3.7
* [numpy](https://numpy.org/)

## Installation

```
pip install gprob
```

## Acknowledgements
gprob was inspired by [GaussianInfer](https://github.com/damast93/GaussianInfer), an accompaniment for the paper

D. Stein and S. Staton, "Compositional Semantics for Probabilistic Programs with Exact Conditioning," 2021 36th Annual ACM/IEEE Symposium on Logic in Computer Science (LICS), Rome, Italy, 2021, pp. 1-13, doi: 10.1109/LICS52264.2021.9470552

