Showing 10 of total 10 results (show query)
thomasp85
tidygraph:A Tidy API for Graph Manipulation
A graph, while not "tidy" in itself, can be thought of as two tidy data frames describing node and edge data respectively. 'tidygraph' provides an approach to manipulate these two virtual data frames using the API defined in the 'dplyr' package, as well as provides tidy interfaces to a lot of common graph algorithms.
Maintained by Thomas Lin Pedersen. Last updated 2 months ago.
graph-algorithmsgraph-manipulationigraphnetwork-analysistidyversecpp
553 stars 14.74 score 4.6k scripts 136 dependents
bwlewis
threejs:Interactive 3D Scatter Plots, Networks and Globes
Create interactive 3D scatter plots, network plots, and globes using the 'three.js' visualization library (<https://threejs.org>).
Maintained by B. W. Lewis. Last updated 3 years ago.
data-visualizationgraph-animationigraphthreejswebgl
304 stars 11.67 score 522 scripts 28 dependents
timelyportfolio
d3r:'d3.js' Utilities for R
Provides a suite of functions to help ease the use of 'd3.js' in R. These helpers include 'htmltools::htmlDependency' functions, hierarchy builders, and conversion tools for 'partykit', 'igraph,' 'table', and 'data.frame' R objects into the 'JSON' that 'd3.js' expects.
Maintained by Kent Russell. Last updated 2 years ago.
d3hierarchieshierarchyigraphjavascriptjson
154 stars 8.01 score 174 scripts 5 dependents
usccana
netplot:Beautiful Graph Drawing
A graph visualization engine that emphasizes on aesthetics at the same time providing default parameters that yield out-of-the-box-nice visualizations. The package is built on top of 'The Grid Graphics Package' and seamlessly work with 'igraph' and 'network' objects.
Maintained by George Vega Yon. Last updated 5 months ago.
graph-visualizationigraphnetscinetwork-analysisnetwork-visualizationsnastatnet
51 stars 6.90 score 78 scripts
stocnet
migraph:Univariate and Multivariate Tests for Multimodal and Other Networks
A set of tools for testing networks. It includes functions for univariate and multivariate conditional uniform graph and quadratic assignment procedure testing, and network regression. The package is a complement to 'Multimodal Political Networks' (2021, ISBN:9781108985000), and includes various datasets used in the book. Built on the 'manynet' package, all functions operate with matrices, edge lists, and 'igraph', 'network', and 'tidygraph' objects, and on one-mode and two-mode (bipartite) networks.
Maintained by James Hollway. Last updated 4 months ago.
igraphmultilevel-networksmultimodal-networknetwork-analysissna
41 stars 6.37 score 33 scripts
frankkramer-lab
mully:Create, Modify and Visualize Multi-Layered Networks
Allows the user to create graphs with multiple layers. The user can also modify the layers, the nodes, and the edges. The graph can also be visualized. Zaynab Hammoud and Frank Kramer (2018) <doi:10.3390/genes9110519>. More about multilayered graphs and their usage can be found in our review paper: Zaynab Hammoud and Frank Kramer (2020) <doi:10.1186/s41044-020-00046-0>.
Maintained by Zaynab Hammoud. Last updated 2 years ago.
big-networksdata-visualizationgraph-theorygraphsigraphmultilayer-networksnode-colored-graphs
45 stars 5.95 score 6 scripts
benyamindsmith
ig.degree.betweenness:"Smith-Pittman Community Detection Algorithm for 'igraph' Objects (2024)"
Implements the "Smith-Pittman" community detection algorithm for network analysis using 'igraph' objects. This algorithm combines node degree and betweenness centrality measures to identify communities within networks, with a gradient evident in social partitioning. The package provides functions for community detection, visualization, and analysis of the resulting community structure. Methods are based on results from Smith, Pittman and Xu (2024) <doi:10.48550/arXiv.2411.01394>.
Maintained by Benjamin Smith. Last updated 18 days ago.
community-detection-algorithmsigraph
38 stars 5.50 score 11 scripts
santikka
causaleffect:Deriving Expressions of Joint Interventional Distributions and Transport Formulas in Causal Models
Functions for identification and transportation of causal effects. Provides a conditional causal effect identification algorithm (IDC) by Shpitser, I. and Pearl, J. (2006) <http://ftp.cs.ucla.edu/pub/stat_ser/r329-uai.pdf>, an algorithm for transportability from multiple domains with limited experiments by Bareinboim, E. and Pearl, J. (2014) <http://ftp.cs.ucla.edu/pub/stat_ser/r443.pdf>, and a selection bias recovery algorithm by Bareinboim, E. and Tian, J. (2015) <http://ftp.cs.ucla.edu/pub/stat_ser/r445.pdf>. All of the previously mentioned algorithms are based on a causal effect identification algorithm by Tian , J. (2002) <http://ftp.cs.ucla.edu/pub/stat_ser/r309.pdf>.
Maintained by Santtu Tikka. Last updated 2 years ago.
causal-inferencecausal-modelscausality-algorithmsdirected-acyclic-graphgraphsidentifiabilityidentificationigraph
29 stars 5.28 score 44 scripts 1 dependents
jonnob
rsetse:Strain Elevation Tension Spring Embedding
An R implementation for the Strain Elevation and Tension embedding algorithm from Bourne (2020) <doi:10.1007/s41109-020-00329-4>. The package embeds graphs and networks using the Strain Elevation and Tension embedding (SETSe) algorithm. SETSe represents the network as a physical system, where edges are elastic, and nodes exert a force either up or down based on node features. SETSe positions the nodes vertically such that the tension in the edges of a node is equal and opposite to the force it exerts for all nodes in the network. The resultant structure can then be analysed by looking at the node elevation and the edge strain and tension. This algorithm works on weighted and unweighted networks as well as networks with or without explicit node features. Edge elasticity can be created from existing edge weights or kept as a constant.
Maintained by Jonathan Bourne. Last updated 3 years ago.
embeddingembedding-graphsgraph-embeddingigraphnetworksnetworkscienceunsupervised-learningopenblascppopenmp
7 stars 4.85 score 8 scripts
hypertidy
scgraph:Common Forms for Graph Structures
Provides support for the 'silicate' common form data structure for igraph.
Maintained by Michael D. Sumner. Last updated 6 years ago.
7 stars 2.54 score 10 scripts