The HyperNetX library provides classes and methods for the analysis and visualization of complex network data modeled as hypergraphs. The library generalizes traditional graph metrics.

HypernetX was developed by the Pacific Northwest National Laboratory for the Hypernets project as part of its High Performance Data Analytics (HPDA) program. PNNL is operated by Battelle Memorial Institute under Contract DE-ACO5-76RL01830.

  • Principle Developer and Designer: Brenda Praggastis

  • Visualization: Dustin Arendt, Ji Young Yun

  • High Performance Computing: Tony Liu, Andrew Lumsdaine

  • Principal Investigator: Cliff Joslyn

  • Program Manager: Mark Raugas, Brian Kritzstein

  • Contributors: Sinan Aksoy, Dustin Arendt, Cliff Joslyn, Nicholas Landry, Andrew Lumsdaine, Tony Liu, Brenda Praggastis, Emilie Purvine, Mirah Shi, Francois Theberge

The code in this repository is intended to support researchers modeling data as hypergraphs. We have a growing community of users and contributors. Documentation is available at: <https://pnnl.github.io/HyperNetX/>

For questions and comments contact the developers directly at: <hypernetx@pnnl.gov>

New Features of Version 1.0:

  1. Hypergraph construction can be sped up by reading in all of the data at once. In particular the hypergraph constructor may read a Pandas dataframe object and create edges and nodes based on column headers. The new hypergraphs are given an attribute static=True.

  2. A C++ addon called [NWHy](docs/build/nwhy.html) can be used in Linux environments to support optimized hypergraph methods such as s-centrality measures.

  3. A JavaScript addon called [Hypernetx-Widget](docs/build/widget.html) can be used to interactively inspect hypergraphs in a Jupyter Notebook.

  4. Four new tutorials highlighting the s-centrality metrics, static Hypergraphs, [NWHy](docs/build/nwhy.html), and [Hypernetx-Widget](docs/build/widget.html).

New Features of Version 1.1

  1. Static Hypergraph refactored to improve performance across all methods.

  2. Added modules and tutorials for Contagion Modeling, Community Detection, Clustering, and Hypergraph Generation.

  3. Cell weights for incidence matrices may be added to static hypergraphs on construction.

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (2.4.3)

3 maintainers

PyPI data
Data sourced directly from PyPI's database.
Avatar for bpraggastis from gravatar.com bpraggastis Avatar for hypernetx from gravatar.com hypernetx Avatar for RyanDanehy from gravatar.com RyanDanehy

Credits

Author: Brenda Praggastis, Dustin Arendt, Sinan Aksoy, Emilie Purvine, Cliff Joslyn, Nicholas Landry

License

3-Clause BSD license

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hypernetx-1.1.1.tar.gz (77.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

hypernetx-1.1.1-py3-none-any.whl (84.4 kB view details)

Uploaded Python 3

File details

Details for the file hypernetx-1.1.1.tar.gz.

File metadata

  • Download URL: hypernetx-1.1.1.tar.gz
  • Upload date:
  • Size: 77.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/3.10.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.7.10

File hashes

Hashes for hypernetx-1.1.1.tar.gz
Algorithm Hash digest
SHA256 bd93bec0e67acf03c5ad3fadab796764b0f510e942fc884452aa4312bc846978
MD5 62d29fd65eeee92dcf3b6a4c9cb13726
BLAKE2b-256 762a879be7396605b410fe667cb6f8d093ee74b458d966631454c5f8a05198ad

See more details on using hashes here.

File details

Details for the file hypernetx-1.1.1-py3-none-any.whl.

File metadata

  • Download URL: hypernetx-1.1.1-py3-none-any.whl
  • Upload date:
  • Size: 84.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/3.10.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.7.10

File hashes

Hashes for hypernetx-1.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 abbc7d4a3e153e15ba840043c2c9e3d40c8f56a41c6a16e72d4d3a123c152f22
MD5 ff02ee321b41d6262845a1d47ca3eee6
BLAKE2b-256 7683a206dbcde1cd82216a2312e29dc98a3f7b6f086a22d1551c6b327326925c

See more details on using hashes here.

Release history Release notifications | RSS feed

2.4.3

2 files

2.4.0

2 files

2.3.13

2 files

2.3.10

2 files

2.3.9

2 files

2.3.8

2 files

2.3.7

2 files

2.3.6

2 files

2.3.5

2 files

2.3.4

2 files

2.3.3

2 files

2.3.2

2 files

2.3.1

2 files

2.3.0

2 files

2.2.0

2 files

2.1.4

2 files

2.1.3

2 files

2.1.2

2 files

2.1.1

2 files

2.1.0

2 files

2.0.5

2 files

2.0.4

2 files

2.0.3

2 files

2.0.2

2 files

2.0.1

2 files

2.0.0.post1

2 files

1.2.5

2 files

1.2.4

2 files

1.2.3

2 files

1.2.2

2 files

1.2

2 files

1.1.3

2 files

1.1.2

2 files

This release

1.1.1 This release

2 files

1.0.4

2 files

1.0.3

2 files

1.0.2

2 files

1.0

2 files

0.3.7

2 files

0.3.6

2 files

0.3.5

2 files

0.3.4

2 files

0.3.2

2 files

0.3.1

2 files

0.3.0

2 files

0.2.7

2 files

0.2.6

2 files

0.2.5

1 file

0.2.4

1 file

0.1.9

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page