Various vertex shapes when plotting igraph graphs
Adjacent vertices of multiple vertices in a graph
Generate an evolving random graph with preferential attachment and aging
Align a vertex layout This function centers a vertex layout on the coordinate system origin and rotates the layout to achieve a visually pleasing alignment with the coordinate axes. Doing this is particularly useful with force-directed layouts such as 'layout_with_fr()'.
Find Bonacich alpha centrality scores of network positions
Articulation points and bridges of a graph
Convert between directed and undirected graphs
Convert igraph objects to adjacency or edge list matrices
Convert between undirected and unundirected graphs
Bipartite adjacency matrix of a bipartite graph
Convert igraph graphs to graphNEL objects from the graph package
Convert a vertex or edge sequence to an ordinary vector
Declare a numeric vector as a membership vector
Kleinberg's hub and authority centrality scores.
Optimal edge curvature when plotting graphs
Generating set of the automorphism group of a graph
Shortest (directed or undirected) paths between vertices
Generate random graphs using preferential attachment
Find Bonacich Power Centrality Scores of Network Positions
Graph generation based on different vertex types
Centralize a graph according to the betweenness of vertices
Theoretical maximum for betweenness centralization
Centralize a graph according to the closeness of vertices
Theoretical maximum for closeness centralization
Centralize a graph according to the degrees of vertices
Theoretical maximum for degree centralization
Centralize a graph according to the eigenvector centrality of vertices
Theoretical maximum for eigenvector centralization
Functions to find cliques, i.e. complete subgraphs in a graph
Community structure detection based on edge betweenness
Community structure via greedy optimization of modularity
Community detection algorithm based on interacting fluids
Finding communities based on propagating labels
Community structure detecting based on the leading eigenvector of the community matrix
Finding community structure of a graph using the Leiden algorithm of Traag, van Eck & Waltman.
Finding community structure by multi-level optimization of modularity
Finding communities in graphs based on statistical meachanics
Community structure via short random walks
Functions to deal with the result of network community detection
Compares community structures using various metrics
Create a consensus tree from several hierarchical random graph models
Contract several vertices into a single one
Find the multiple or loop edges in a graph
Count the number of isomorphic mappings between two graphs
Count the isomorphic mappings between a graph and the subgraphs of another graph
Degree and degree distribution of the vertices
Generate random graphs with a given degree sequence
Dimensionality selection for singular values using profile likelihood.
Rewires the endpoints of the edges of a graph to a random vertex
Helper function for adding and deleting edges
Spectral Embedding of Adjacency Matrices
Spectral Embedding of the Laplacian of a Graph
Generate random graphs according to the Erdős-Rényi model
Find Eigenvector Centrality Scores of Network Positions
Finding a feedback vertex set in a graph
Finds a cycle in a graph, if there is one
Fitting a power-law distribution function to discrete data
Creating igraph graphs from data frames or vice-versa
Find the edge ids based on the incident vertices of the edges
Create an igraph graph from a list of edges, or a notable graph
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.
Create graphs from a bipartite adjacency matrix
Create a graph from an isomorphism class
Create a star graph, a tree with n vertices and n - 1 leaves
Convert graphNEL objects from the graph package to igraph
Find Eulerian paths or cycles in a graph
Create a hierarchical random graph from an igraph graph
Create an igraph graph from a hierarchical random graph model
Sample from a hierarchical random graph model
Predict edges based on a hierarchical random graph model
How igraph functions handle attributes when the graph changes
Getting and setting graph attributes, shortcut
Query or set attributes of the edges in an edge sequence
Query or set attributes of the vertices in a vertex sequence
Incident edges of multiple vertices in a graph
A graph with subgraphs that are each a random graph.
Checks whether the graph has a vertex attribute called 'type'
Check if a degree sequence is valid for a multi-graph
Checks whether the graph has a vertex attribute called 'type'.
Check whether removing this set of vertices would disconnect the graph.
Calculate all isomorphic mappings between the vertices of two graphs
Find the k shortest paths between two vertices
Graph rewiring while preserving the degree distribution
Choose an appropriate graph layout algorithm automatically
Simple two-row layout for bipartite graphs
Grid Fruchterman-Reingold layout, this was removed from igraph
Graph layout by multidimensional scaling
Normalize coordinates for plotting graphs
Randomly place vertices on a plane or in 3d space
The Reingold-Tilford graph layout algorithm
Graph layout with vertices on the surface of a sphere
Spring layout, this was removed from igraph
Generate coordinates to place the vertices of a graph in a star-shape
SVD layout, this was removed from igraph
Create an undirected tree graph from its Prüfer sequence
Match Graphs given a seeding of vertex correspondences
Maximal independent vertex sets in the graph
Modularity of a community structure of a graph
Neighboring (adjacent) vertices in a graph
Helper function to add or delete edges along a path
Plotting the results on multiple SIR model runs
Add vertices, edges or another graph to a graph
Print a hierarchical random graph model to the screen
Print a hierarchical random graph consensus tree to the screen
Creating a bipartite graph from two degree sequences, deterministically
Creating a graph from a given degree sequence, deterministically
Random graph with given expected degrees
Generate a new random graph from a given graph by randomly adding/removing edges
Sample a pair of correlated G(n,p) random graphs
Generate random graphs according to the random dot product graph model
Random graphs from vertex fitness scores
Scale-free random graphs, from vertex fitness scores
Generate random graphs according to the G(n,m) Erdős-Rényi model
Generate random graphs according to the G(n,p) Erdős-Rényi model
Sample the hierarchical stochastic block model
Samples from the spanning trees of a graph randomly and uniformly
Sample vectors uniformly from the surface of a sphere
Sample vectors uniformly from the volume of a sphere
Scan statistics on a time series of graphs
Similarity measures of two vertices (Dice)
Similarity measures of two vertices (inverse log-weighted)
Similarity measures of two vertices (Jaccard)
Constructor modifier to drop multiple and loop edges
Split-join distance of two community structures
List all minimum \((s,t)\)-cuts of a graph
Query and manipulate a graph as it were an adjacency matrix
Query and manipulate a graph as it were an adjacency list
Find subgraph centrality scores of network positions
Decide if a graph is subgraph isomorphic to another one
All isomorphic mappings between a graph and subgraphs of another graph
Convert a tree graph to its Prüfer sequence
Topological sorting of vertices in a graph
Triad census, subgraphs with three vertices
Remove duplicate edges from an edge sequence
Remove duplicate vertices from a vertex sequence
Helper function for adding and deleting vertices
Using pie charts as vertices in graph plots
Functions to find weighted cliques, i.e. vertex-weighted complete subgraphs in a graph
Constructor modifier to add edge attributes
Constructor modifier to add graph attributes
Run code with a temporary igraph options setting
Constructor modifier to add vertex attributes
Construtor modifier to remove all attributes from a graph
Constructor modifier to drop multiple edges
Writing the graph to a file in some format

functions for manipulating graph structure