graphlayouts

Spec sheet

Purpose

graphlayouts implements graph layout algorithms that are not available in igraph.Read 11 Oct 2026 · schochastics.github.io

Free plan

YesRead 23 Sep 2026 · schochastics.github.io

Integrations

The site demonstrates graphlayouts with ggraph and igraph, and also uses patchwork in examples.Read 11 Oct 2026 · schochastics.github.io

Support

The project directs users to open a GitHub issue for bugs and support questions.Read 11 Oct 2026 · schochastics.github.io

License

The CRAN package listing identifies the license as MIT plus a license file.Read 11 Oct 2026 · stat.ethz.ch

Backbone layout

The backbone layout uses edge embeddedness to help uncover and emphasize potential group structures.Read 11 Oct 2026 · schochastics.github.io

Centrality layout

The centrality layout places the node with the highest centrality at the center, with more peripheral nodes farther out.Read 11 Oct 2026 · schochastics.github.io

Data sources

igraph networks; ggraph; igraphdata; networkdataRead 23 Sep 2026 · schochastics.github.io

Dynamic networks

The dynamic layout visualizes longitudinal network snapshots by anchoring nodes to a reference layout and moving them slightly as edges change.Read 11 Oct 2026 · schochastics.github.io

Focus layout

The focus layout places nodes with the same distance from a focal node on the same circle.Read 11 Oct 2026 · schochastics.github.io

Installation

The package can be installed from CRAN with install.packages("graphlayouts") or from GitHub with remotes::install_github("schochastics/graphlayouts").Read 11 Oct 2026 · schochastics.github.io

Large networks

The site describes two algorithms for large networks, with pivot MDS using a small number of pivot nodes and sparse stress trading runtime for layout quality.Read 11 Oct 2026 · schochastics.github.io

Layout algorithms

The package includes stress majorization, backbone, flexible radial, sparse stress, pivot MDS, dynamic, spectral, multilevel, and UMAP based layouts.Read 11 Oct 2026 · schochastics.github.io

Limits

The site describes its large graph algorithms in the context of networks under 100,000 nodes, while showing a sparse stress example with 165,000 nodes.Read 11 Oct 2026 · schochastics.github.io

Platform

desktopRead 23 Sep 2026 · schochastics.github.io

Requirements

The CRAN listing says the package depends on R 3.6.0 or later and imports igraph 2.0.0 or later and Rcpp.Read 11 Oct 2026 · stat.ethz.ch

Plans and prices

Every graphlayouts plan and price →

Where Specifiction places it

• Data Visualization Software#78 of 987.3