conversion between igraph and graphNEL graphs
Generate an evolving random graph with preferential attachment and aging
Find Bonacich alpha centrality scores of network positions
Convert between directed and undirected graphs
How igraph functions handle attributes when the graph changes
Optimal edge curvature when plotting graphs
Generate scale-free graphs according to the Barabasi-Albert model
Find Bonacich Power Centrality Scores of Network Positions
The functions find cliques, ie. complete subgraphs in a graph
Functions to deal with the result of network community detection
Community structure detection based on edge betweenness
Common functions supporting community detection algorithms
Compares community structures using various metrics
Contract several vertices into a single one
Convert a graph to an adjacency matrix or an edge list
Degree and degree distribution of the vertices
Generate random graphs with a given degree sequence
Generate random graphs according to the Erdos-Renyi model
Find Eigenvector Centrality Scores of Network Positions
Measuring the driving force in evolving networks
Community structure via greedy optimization of modularity
Find the edge ids based on the incident vertices of the edges
Creating igraph graphs from data frames or vice-versa
Eigenvalues and eigenvectors of the adjacency matrix of a graph
Creating (small) graphs via a simple interface
Load a graph from the graph database for testing graph isomorphism.
Method for structural manipulation of graphs
Convert igraph graphs to graphNEL objects or back
Various vertex shapes when plotting igraph graphs
A graph with subgraphs that are each a random graph.
Find the multiple or loop edges in a graph
Finding communities based on propagating labels
Generate coordinates for plotting graphs
Simple two-row layout for bipartite graphs
Graph layout by multidimensional scaling
Generate coordinates to place the vertices of a graph in a star-shape
Community structure detecting based on the leading eigenvector of the community matrix
Modularity of a community structure of a graph
Finding community structure by multi-level optimization of modularity
Query and download from the Nexus network repository
Plotting the results on multiple SIR model runs
Fitting a power-law distribution function to discrete data
Rewires the endpoints of the edges of a graph randomly
All-in-one Function for the SCG of Matrices and Graphs
Shortest (directed or undirected) paths between vertices
Finding communities in graphs based on statistical meachanics
Random graphs from vertex fitness scores
Scale-free random graphs, from vertex fitness scores
Gaining information about graph structure
Find subgraph centrality scores of network positions
Topological sorting of vertices in a graph
Graph generation based on different vertex types
Triad census, subgraphs with three vertices
Undocumented and unsupportted igraph functions
Using pie charts as vertices in graph plots
Community strucure via short random walks
Writing the graph to a file in some format