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igraph (version 0.4.3)

Routines for simple graphs, network analysis.

Description

Routines for simple graphs and network analysis. igraph can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality indices and much more.

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Install

install.packages('igraph')

Monthly Downloads

733,150

Version

0.4.3

License

GPL version 2 or later (June, 1991)

Maintainer

Gabor Csardi

Last Published

February 10th, 2023

Functions in igraph (0.4.3)

Is this object a graph?

Rewires the endpoints of the edges of a graph randomly

Common functions supporting community detection algorithms

decompose.graph

Decompose a graph into components

Closeness centrality of vertices

edge.connectivity

Edge connectivity.

Vertex and edge betweenness centrality

Vertex and edge sequences and iterators

minimum.spanning.tree

Minimum spanning tree

graph-isomorphism

Graph Isomorphism

degree.sequence.game

Generate random graphs with a given degree sequence

Merging graph layouts

Modularity of a community structure of a graph

Convert a graph to an adjacency matrix or an edge list

Shortest (directed or undirected) paths between vertices

K-core decomposition of graphs

Fitting a power-law distribution function to discrete data

growing.random.game

Growing random graph generation

graph.structure

Method for structural manipulation of graphs

igraph.undocumented

Undocumented and unsupportted igraph functions

graph.laplacian

Graph Laplacian

Print graphs to the terminal

Interactive plotting of graphs

topological.sort

Topological sorting of vertices in a graph

Diameter of a graph

Neighborhood of graph vertices

Convert between directed and undirected graphs

independent.vertex.sets

Independent vertex sets

Graph, vertex and edge attributes

The functions find cliques, ie. complete subgraphs in a graph

Generate coordinates for plotting graphs

Load a graph from the graph database for testing graph isomorphism.

walktrap.community

Community strucure via short random walks

leading.eigenvector.community

Community structure detecting based on the leading eigenvector of the community matrix

The Page Rank algorithm

alpha.centrality

Find Bonacich alpha centrality scores of network positions

fastgreedy.community

Community structure via greedy optimization of modularity

graph-operators

Graph operators

Geometric random graphs

aging.prefatt.game

Generate an evolving random graph with preferential attachment and aging

In- or out- component of a vertex

preference.game

Trait-based random generation

Running mean of a time series

Girth of a graph

Remove loop and/or multiple edges from a graph

Reciprocity of graphs

igraph-parameters

Parameters for the igraph package

spinglass.community

Finding communities in graphs based on statistical meachanics

edge.betweenness.community

Community structure detection based on edge betweenness

Measuring the driving force in evolving networks

Subgraph of a graph

Connected components of a graph

Cocitation coupling

measure.dynamics

Measuring the driving force in evolving networks

erdos.renyi.game

Generate random graphs according to the Erdos-Renyi model

Writing the graph to a file in some format

Plotting of graphs

Burt's constraint

Graph generation based on different vertex types

Find Eigenvector Centrality Scores of Network Positions

Gaining information about graph structure

Transitivity of a graph

Reading foreign file formats

watts.strogatz.game

The Watts-Strogatz small-world model

graph.constructors

Various methods for creating graphs

Generate scale-free graphs according to the Barabasi-Albert model

Find Bonacich Power Centrality Scores of Network Positions

Degree and degree distribution of the vertices

Sampling a random integer sequence

3D plotting of graphs with OpenGL

Maximum flow in a network

vertex.connectivity

Vertex connectivity.