pnnl/HyperNetX

RESOURCE

Abstract

HyperNetX is a Python library of classes, algorithms, and generators for working with multi-way and nested relational data. Given a network of nodes and relationships, the base class HyperNetX.Entity is used to instantiate individual data elements along with their relationships to other elements of the network. By exploiting Python's dictionary data structure we capture both multi-way and nested data structures with constant time lookup. The base class HyperNetX.Hypergraph instantiates a network of this data into a hypergraph structure. Many of the common metrics and features of graphs, such as diameter, connectedness, and clustering coefficient, have analogous definitions with respect to hypergraphs, which are computed using algorithms in the HyperNetX library.
Developers:
Praggastis, Brenda [1] Arendt, Dustin [1] Joslyn, Cliff [1] Purvine, Emilie [1] Aksoy, Sinan [1] Monson, Kyle [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Release Date:
2019-01-03
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Programming Languages:
Python
Licenses:
BSD 2-clause "Simplified" License
Sponsoring Org.:
Code ID:
22160
Site Accession Number:
Battelle IPID 31467-E
Research Org.:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Country of Origin:
United States

RESOURCE

Citation Formats

Praggastis, Brenda, Arendt, Dustin, Joslyn, Cliff, Purvine, Emilie, Aksoy, Sinan, and Monson, Kyle. pnnl/HyperNetX. Computer Software. https://github.com/pnnl/HyperNetX. USDOE. 03 Jan. 2019. Web. doi:10.11578/dc.20240614.45.
Praggastis, Brenda, Arendt, Dustin, Joslyn, Cliff, Purvine, Emilie, Aksoy, Sinan, & Monson, Kyle. (2019, January 03). pnnl/HyperNetX. [Computer software]. https://github.com/pnnl/HyperNetX. https://doi.org/10.11578/dc.20240614.45.
Praggastis, Brenda, Arendt, Dustin, Joslyn, Cliff, Purvine, Emilie, Aksoy, Sinan, and Monson, Kyle. "pnnl/HyperNetX." Computer software. January 03, 2019. https://github.com/pnnl/HyperNetX. https://doi.org/10.11578/dc.20240614.45.
@misc{ doecode_22160,
title = {pnnl/HyperNetX},
author = {Praggastis, Brenda and Arendt, Dustin and Joslyn, Cliff and Purvine, Emilie and Aksoy, Sinan and Monson, Kyle},
abstractNote = {HyperNetX is a Python library of classes, algorithms, and generators for working with multi-way and nested relational data. Given a network of nodes and relationships, the base class HyperNetX.Entity is used to instantiate individual data elements along with their relationships to other elements of the network. By exploiting Python's dictionary data structure we capture both multi-way and nested data structures with constant time lookup. The base class HyperNetX.Hypergraph instantiates a network of this data into a hypergraph structure. Many of the common metrics and features of graphs, such as diameter, connectedness, and clustering coefficient, have analogous definitions with respect to hypergraphs, which are computed using algorithms in the HyperNetX library.},
doi = {10.11578/dc.20240614.45},
url = {https://doi.org/10.11578/dc.20240614.45},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20240614.45}},
year = {2019},
month = {jan}
}