https://github.com/reactivebayes/bipartitefactorgraphs.jl

A Julia package for working with bipartite factor graphs
https://github.com/reactivebayes/bipartitefactorgraphs.jl

bayesian-inference bayesian-network bipartite-graphs graphs

Last synced: 7 months ago
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A Julia package for working with bipartite factor graphs

• Host: GitHub
• URL: https://github.com/reactivebayes/bipartitefactorgraphs.jl
• Owner: ReactiveBayes
• License: mit
• Created: 2025-04-25T09:40:04.000Z (11 months ago)
• Default Branch: main
• Last Pushed: 2025-06-11T09:23:37.000Z (9 months ago)
• Last Synced: 2025-08-01T12:52:19.508Z (7 months ago)
• Topics: bayesian-inference, bayesian-network, bipartite-graphs, graphs
• Language: Julia
• Homepage: https://reactivebayes.github.io/BipartiteFactorGraphs.jl/
• Size: 531 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
![BipartiteFactorGraphs.jl](docs/src/assets/logo.png)

# BipartiteFactorGraphs.jl

[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://reactiveBayes.github.io/BipartiteFactorGraphs.jl/stable/)

[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://reactiveBayes.github.io/BipartiteFactorGraphs.jl/dev/)

[![Build Status](https://github.com/ReactiveBayes/BipartiteFactorGraphs.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/ReactiveBayes/BipartiteFactorGraphs.jl/actions/workflows/CI.yml?query=branch%3Amain)

[![Coverage](https://codecov.io/gh/ReactiveBayes/BipartiteFactorGraphs.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/ReactiveBayes/BipartiteFactorGraphs.jl)

[![Aqua](https://raw.githubusercontent.com/JuliaTesting/Aqua.jl/master/badge.svg)](https://github.com/JuliaTesting/Aqua.jl)

A Julia package for working with bipartite factor graphs, providing efficient data structures and algorithms for graph-based probabilistic inference.

The package is built on top of and is fully compatible with the [Graphs.jl](https://github.com/JuliaGraphs/Graphs.jl) package.

## Installation

```julia

using Pkg

Pkg.add("BipartiteFactorGraphs")

```

Or in Julia REPL press `]` to enter Pkg mode:

```julia

] add BipartiteFactorGraphs

```

## Features

- Flexible representation of bipartite factor graphs

- Efficient manipulation of graph structure

- Support for common graph operations

- Type-stable implementation for performance

## Basic Usage

```julia

using BipartiteFactorGraphs

# Create a new factor graph

g = BipartiteFactorGraph()

# Add variable and factor nodes

v1 = add_variable!(g)

v2 = add_variable!(g)

f1 = add_factor!(g, [v1, v2])

# Check connectivity

@assert is_connected(v1, f1)

@assert is_connected(v2, f1)

# Access node neighbors

neighbors_of_v1 = neighbors(g, v1)

neighbors_of_f1 = neighbors(g, f1)

# Get graph properties

@assert num_variables(g) == 2

@assert num_factors(g) == 1

```

## Documentation

For more detailed information about the package functionality, please refer to the [documentation](https://reactiveBayes.github.io/BipartiteFactorGraphs.jl/stable/).

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository

2. Create your feature branch (`git checkout -b my-new-feature`)

3. Commit your changes (`git commit -am 'Add some feature'`)

4. Push to the branch (`git push origin my-new-feature`)

5. Create a new Pull Request

## License

This package is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details.