HAT is a general-purpose software suite for constructing, analyzing, and visualizing hypergraphs and higher-order structures. Originally motivated by the analysis of Pore-C genomic data, HAT is designed to be versatile and extensible across domains with a focus on tensor, dynamics, and control based algorithms for higher order networks
- Flexible construction — build hypergraphs from edge lists, incidence matrices, or adjacency tensors; directed and undirected; weighted and unweighted
- Metrics — centrality, similarity, entropy, and more
- Spectral methods — Laplacians and related operators
- Tensor analysis — eigenvalues, decompositions, and Kronecker products
- Controllability and observability — analysis of higher-order dynamical systems
- Visualization — hypergraph drawing utilities
- Interoperability — import/export with HIF, HyperNetX, and HypergraphX
pip install HypergraphAnalysisToolboxRequires Python ≥ 3.11.
Download from MATLAB File Exchange or clone this repository and add the Matlab/ directory to your MATLAB path.
import numpy as np
from HAT import Hypergraph
# Construct from an edge list
H = Hypergraph(edge_list=[[0, 1, 2], [0, 1, 3]])
# Construct from an incidence matrix
D = np.array([[1, 1],
[1, 1],
[1, 0],
[0, 1]])
H = Hypergraph(incidence_matrix=D)Full documentation — including API reference, tutorials, and examples — is available at:
https://hypergraph-analysis-toolbox.readthedocs.io
| Paper | Link |
|---|---|
| Structural Controllability of Large-Scale Hypergraphs | Preprint |
| Data-Driven Tensor Decomposition Identification of Homogeneous Polynomial Dynamical Systems | Preprint |
| Scalable Hypergraph Algorithms for Observability of Gene Regulation | European Control Conference |
| Deciphering Multiway Interactions in the Human Genome | Nature Communications |
| Geometric Aspects of Observability of Hypergraphs | IFAC Workshop on Lagrangian and Hamiltonian Methods for Non Linear Control |
| Observability of Hypergraphs | IEEE Conference on Decision and Control |
| Kronecker Products of Tensors and Hypergraphs | SIAM Journal on Matrix Analysis and Applications |
| HAT: Hypergraph Analysis Toolbox | PLOS Computational Biology |
| Hypergraph Similarity Measures | IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING |
| Controllability of Hypergraphs | IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING |
| Tensor Entropy for Uniform Hypergraphs | Tensor Entropy for Uniform Hypergraphs |
| Multilinear Control Systems Theory | SIAM J. CONTROL OPTIM. |
If you use HAT in your research, please cite:
@article{pickard2023hat,
title={HAT: Hypergraph analysis toolbox},
author={Pickard, Joshua and Chen, Can and Salman, Rahmy and Stansbury, Cooper and Kim, Sion and Surana, Amit and Bloch, Anthony and Rajapakse, Indika},
journal={PLOS Computational Biology},
volume={19},
number={6},
pages={e1011190},
year={2023},
publisher={Public Library of Science San Francisco, CA USA}
}Bug reports and feature requests are welcome via GitHub Issues.