speakeasyR
Fast and Robust Multi-Scale Graph Clustering
A graph community detection algorithm that aims to be performant on large graphs and robust, returning consistent results across runs. SpeakEasy 2 (SE2), the underlying algorithm, is described in Chris Gaiteri, David R. Connell & Faraz A. Sultan et al. (2023) doi:10.1186/s13059-023-03062-0. The core algorithm is written in 'C', providing speed and keeping the memory requirements low. This implementation can take advantage of multiple computing cores without increasing memory usage. SE2 can detect community structure across scales, making it a good choice for biological data, which often has hierarchical structure. Graphs can be passed to the algorithm as adjacency matrices using base 'R' matrices, the 'Matrix' library, 'igraph' graphs, or any data that can be coerced into a matrix.
- Version0.1.4
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?Yes
- Last release09/24/2024
Documentation
Team
David Connell
Gábor Csárdi
Show author detailsRolesCopyright holder, ContributorThe R Core Team
Show author detailsRolesCopyright holderMelissa O'Neill
Show author detailsRolesCopyright holder, ContributorRoss Ihaka
Show author detailsRolesCopyright holder, ContributorMinh Nguyen
Show author detailsRolesCopyright holder, ContributorThe R Development Core Team
Show author detailsRolesCopyright holderThe Regents of the University of California
Show author detailsRolesCopyright holderRoyal Statistical Society
Show author detailsRolesCopyright holderFree Software Foundation, Inc.
Show author detailsRolesCopyright holderFabio Zanini
Steven Johnson
Show author detailsRolesCopyright holder, ContributorTamás Nepusz
Vincent Traag
Szabolcs Horvát
Daniel Noom
Show author detailsRolesCopyright holder, ContributorTimothy Davis
Show author detailsRolesCopyright holder, ContributorChris Gaiteri
Show author detailsRolesCopyright holderThe igraph development team
Show author detailsRolesCopyright holderRichard Lehoucq
Show author detailsRolesCopyright holder, ContributorDanny Scrensen
Show author detailsRolesCopyright holder, ContributorPhuong Vu
Show author detailsRolesCopyright holder, ContributorChao Yang
Show author detailsRolesCopyright holder, ContributorAllan Cornet
Show author detailsRolesCopyright holder, ContributorSylvestre Ledru
Show author detailsRolesCopyright holder, ContributorRice University
Show author detailsRolesCopyright holderScilab Enterprises
Show author detailsRolesCopyright holderDaniel G.
Show author detailsRolesCopyright holder, ContributorMarc Stevens
Show author detailsRolesCopyright holder, ContributorElliot Paquette
Show author detailsRolesCopyright holder, ContributorPascal Pons
Show author detailsRolesCopyright holder, ContributorJordi Hermoso
Show author detailsRolesCopyright holder, ContributorSébastien Fabbro
Show author detailsRolesCopyright holder, ContributorShinya Tasaki
Show author detailsRolesCopyright holder, Contributor
Insights
Last 30 days
This package has been downloaded 158 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 7 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 1,734 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Sep 26, 2024 with 52 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports1 package
- Suggests4 packages