Jpickard1 · Jpickard1 · May 23, 2026 · May 23, 2026 · May 23, 2026 · May 23, 2026
diff --git a/Python/HAT/hypergraph.py b/Python/HAT/hypergraph.py
@@ -89,6 +89,7 @@ def __init__(self,
         )
 
         # Convert all nodes to integers, and build a map between integers and names
+        name_to_int = None
         if edge_list is not None:
             new_edge_list, name_to_int = convert_nodes_to_integers(edge_list)
             original_edge_list = copy.deepcopy(edge_list)

diff --git a/README.md b/README.md
@@ -1,31 +1,108 @@
-# Hypergraph-Analysis-Toolbox (HAT)
+# Hypergraph Analysis Toolbox (HAT)
 
-[![Documentation Status](https://readthedocs.org/projects/hypergraph-analysis-toolbox/badge/?version=latest)](https://hypergraph-analysis-toolbox.readthedocs.io/en/latest/?badge=latest)
-[![View Hypergraph Analysis Toolbox on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://www.mathworks.com/matlabcentral/fileexchange/121013-hypergraph-analysis-toolbox)
+[![Documentation](https://readthedocs.org/projects/hypergraph-analysis-toolbox/badge/?version=latest)](https://hypergraph-analysis-toolbox.readthedocs.io/en/latest/)
+[![MATLAB File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://www.mathworks.com/matlabcentral/fileexchange/121013-hypergraph-analysis-toolbox)
+[![PyPI version](https://img.shields.io/pypi/v/HypergraphAnalysisToolbox)](https://pypi.org/project/HypergraphAnalysisToolbox/)
 
-The [Hypergraph Analysis Toolbox](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011190) is a general purpose software for analyzing the structure and dynamics of Hypergraphs.
+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
 
-Hypergraph Analysis Toolbox (HAT) is a software suite for the analysis and visualization of hypergraphs and higher order structures. Motivated to investigate Pore-C data, HAT is intended as a general prupose, versatile software for hypergraph construction, visualization, and analysis. HAT's main features include:
+---
 
-- Controllability and observability of higher order systems
-- Hypergraph metrics: centrality, similarity, entropy, etc.
-- Tensor based analysis: eigenvalues, decompositions, Kronecker products, etc.
+## Features
 
-Documentation for HAT is found [here](https://hypergraph-analysis-toolbox.readthedocs.io/en/latest/index.html) at: https://hypergraph-analysis-toolbox.readthedocs.io/en/latest/index.html
+- **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
 
-**Papers by the HAT Team**
-HAT was developed to consolidate and facilitate the development of new hypergraph methods. Select papers that motivated this development and whose methods are part of HAT include:
+---
 
-- Scalable Hypergraph Algorithms for Observability of Gene Regulation (*coming soon*)
-- [Kronecker Products of Tensors and Hypergraphs](https://epubs.siam.org/doi/full/10.1137/23M1592547)
-- [Observability of Hypergraphs](https://drive.google.com/file/d/1FQxRj5VdPkY-P64ek7rq4lp9jQW9MLFP/view)
-- [Geometric Apsects of Observability of Hypergraphs](https://drive.google.com/file/d/1-5AL_rOvAm-aUClSfyy9MpED7h7_L76o/view)
-- [HAT: Hypergraph Analysis Toolbox](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011190)
-- [Deciphering Multiway Interactions in the Human Genome](https://drive.google.com/file/d/1rp6ZtKf_DxUL0xOpcUzRg1rJGA6xlu-f/view)
-- [Hypergraph Similarity Measures](https://drive.google.com/file/d/1Dc4nSkkZyk4axOAshdRDXo8Gx24h4M-d/view)
-- [Controllability of Hypergraphs](https://drive.google.com/file/d/12aReE7mE4MVbycZUxUYdtICgrAYlzg8o/view)
-- [Tensor Entropy for Uniform Hypergraphs](https://drive.google.com/file/d/1-d4uR5KT3iDpOd69aCQVjNZzMyILXp5E/view)
-- [Multilinear Control Systems Theory](https://drive.google.com/file/d/1F0ZGoVWeKSWemXvSp6ilTwLS8N7j6n71/view)
+## Installation
 
-<img src="https://github.com/user-attachments/assets/7fbea36e-f1a5-4404-af31-ded51e1ff4fb" alt="HAT_logo_v2" width="250"/>
+### Python
 
+```bash
+pip install HypergraphAnalysisToolbox
+```
+
+Requires Python ≥ 3.11.
+
+### MATLAB
+
+Download from [MATLAB File Exchange](https://www.mathworks.com/matlabcentral/fileexchange/121013-hypergraph-analysis-toolbox) or clone this repository and add the `Matlab/` directory to your MATLAB path.
+
+---
+
+## Quick Start
+
+```python
+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)
+
+```
+
+---
+
+## Documentation
+
+Full documentation — including API reference, tutorials, and examples — is available at:
+
+**https://hypergraph-analysis-toolbox.readthedocs.io**
+
+---
+
+## Related Publications
+
+| Paper | Link |
+|---|---|
+| Structural Controllability of Large-Scale Hypergraphs | [Preprint](https://arxiv.org/pdf/2603.19955) |
+| Data-Driven Tensor Decomposition Identification of Homogeneous Polynomial Dynamical Systems | [Preprint](https://arxiv.org/pdf/2604.03508) |
+| Scalable Hypergraph Algorithms for Observability of Gene Regulation | [European Control Conference](https://ieeexplore.ieee.org/document/11186979) |
+| Deciphering Multiway Interactions in the Human Genome | [Nature Communications](https://drive.google.com/file/d/1rp6ZtKf_DxUL0xOpcUzRg1rJGA6xlu-f/view) |
+| Geometric Aspects of Observability of Hypergraphs | [IFAC Workshop on Lagrangian and Hamiltonian Methods for Non Linear Control](https://drive.google.com/file/d/1-5AL_rOvAm-aUClSfyy9MpED7h7_L76o/view) |
+| Observability of Hypergraphs | [IEEE Conference on Decision and Control](https://drive.google.com/file/d/1FQxRj5VdPkY-P64ek7rq4lp9jQW9MLFP/view) |
+| Kronecker Products of Tensors and Hypergraphs | [SIAM Journal on Matrix Analysis and Applications](https://epubs.siam.org/doi/full/10.1137/23M1592547) |
+| HAT: Hypergraph Analysis Toolbox | [PLOS Computational Biology](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011190) |
+| Hypergraph Similarity Measures | [IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING](https://drive.google.com/file/d/1Dc4nSkkZyk4axOAshdRDXo8Gx24h4M-d/view) |
+| Controllability of Hypergraphs | [IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING](https://drive.google.com/file/d/12aReE7mE4MVbycZUxUYdtICgrAYlzg8o/view) |
+| Tensor Entropy for Uniform Hypergraphs | [Tensor Entropy for Uniform Hypergraphs](https://drive.google.com/file/d/1-d4uR5KT3iDpOd69aCQVjNZzMyILXp5E/view) |
+| Multilinear Control Systems Theory | [SIAM J. CONTROL OPTIM.](https://drive.google.com/file/d/1F0ZGoVWeKSWemXvSp6ilTwLS8N7j6n71/view) |
+
+---
+
+## Citation
+
+If you use HAT in your research, please cite:
+
+```bibtex
+@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}
+}
+```
+
+---
+
+## Contributing
+
+Bug reports and feature requests are welcome via [GitHub Issues](https://github.com/Jpickard1/Hypergraph-Analysis-Toolbox/issues).
diff --git a/Tests/hypergraph_constructors.py b/Tests/hypergraph_constructors.py
@@ -336,7 +336,7 @@ def test_add_edge_2(self):
         edge_df = pd.DataFrame({
             'Nodes': [[0, 1, 2], [0, 1, 3], [2, 3]],
             'Edges': [0,1,2],
-            'weight': [1.5, 2.5, pd.NA]
+            'weight': [1.5, 2.5, np.nan]
         })
 
         # Assert the edges match
@@ -358,7 +358,7 @@ def test_add_edge_3(self):
         edge_df = pd.DataFrame({
             'Nodes': [[0, 1, 2], [0, 1, 3], [2, 3]],
             'Edges': [0,1,2],
-            'weight': [pd.NA, pd.NA, 3.0]
+            'weight': [np.nan, np.nan, 3.0]
         })
 
         # Assert the edges match