Release notes

There are a lot of improvements and corrections in this version. We would like to thank all the people who sent comments, bug reports, patches, or just questions. Without their contribution igraph would be definitely much less and worse than it is now. Please keep sending your comments and ideas!

Here is a list of major changes, with links to the relevant sections of the documentation. See below for the complete list of changes.

Graph isomorphism

igraph includes the BLISS graph isomorphism algorithm and implementation now. This and the improved VF2 implementation, which can now calculate subgraph isomorphism, make igraph support the bleeding edge of graph isomorphism algorithms. Many thanks to the authors of BLISS. See the details in the Reference Manual, in the R documentation or in the Python documentation.

ARPACK for eigenvalue problems

ARPACK is a library for solving large scale sparse eigenvalue problems. In igraph it is very handy, as many centrality problems are in fact eigenvalue problems: Kleinberg’s hub and authority scores, PageRank, the leading eigenvector community detection algorithm are some examples. Many thanks to the authors of ARPACK and James Fowler, who suggested to include it in igraph.

See the details in the documentation.

Other bits

Create famous graphs easily

Some classic graphs can be created by giving their name. This is very handy if one needs a test graph quickly. See graph.famous(). (The idea is based on Combinatorica, a Mathematica extension.)

Create graphs using formulas

The new graph.formula() function provides a simple, concise way to create (small) graphs. Numerous examples are included in the manual page.

Improvements for weighted graphs

Many functions were updated to handle weighted graphs: fast greedy community detection (fastgreedy.community) Page Rank (page.rank), modularity calculation (modularity), the Fruchterman-Reingold layout algorithm (layout.fruchterman.reingold.

Non-simple graphs

Some functions were added and improved to handle non-simple graphs (i.e. graphs with loop and/or multiple edges) better: testing that a graph is simple (simplify), testing for loop edges (is.loop), testing for multiple edges (is.multiple) and counting the multiplicity of edges (count.multiple.

The graphopt layout algorithm

This is a nice force-based layout algorithm. See the documentation for details.

Support for the DOT file format

igraph can now write graphs to files in the DOT format, used by GraphViz. See the documentation.

Dyad and triad census

Classic social network analysis tools for classifying the dyads (dyad.census) and triads (triad.census.

Biconnected components and articulation points

igraph is now able to calculate biconnected components and
articulation points.

R graphics improvements

There were some minor improvements in R graphics. New graphical parameters: frame, asp, rescale and shape for different vertex shapes, right now only circles and squares are supported. plot.igraph has as argument (add) to plot many graphs on the same plot, maybe on top of each other. It also supports the main and sub arguments now. See more here.

Always free memory in R after an interrupted calculation

In previous versions of the igraph R package the allocated memory was not freed if the computation was interrupted. This surely affected MS Windows platforms, maybe also OSX. (Not Linux.) igraph 0.5 correctly deallocates all memory on all platforms after an interruption.

Estimating closeness and betweenness

These measures can be quickly estimated by specifying an upper bound for path lengths to be considered. This is useful for larger graphs, for which the calculation takes a long time. See documentation for closeness, betweenness, and edge betweenness.

Functions for vertex similarity measures

Two vertex similarity measures based on the number of common neighbors are introduced, the Jaccard and Dice similarities. See the manual for details.

Proper warnings in R

Up to now igraph warnings were dumped to the console when using the igraph R package. In many cases this meant that they were effectively lost. In the new version igraph warnings are converted to proper R warnings.

New in the R interface

• The rescale, asp and frame graphical parameters were added
• Create graphs from a formula notation (graph.formula)
• Handle graph attributes properly
• Calculate the actual minimum cut for undirected graphs
• Adjacency lists, get.adjlist and get.adjedgelist added
• Eigenvector centrality computation is much faster now
• Proper R warnings, instead of writing the warning to the terminal
• R checks graphical parameters now, the unknown ones are not just ignored, but an error message is given.
• plot.igraph has an add argument now to compose plots with multiple graphs
• plot.igraph supports the main and sub arguments
• layout.norm is public now, it can normalize a layout
• It is possible to supply startup positions to layout generators
• Always free memory when CTRL+C/ESC is pressed, in all operating systems
• plot.igraph can plot square vertices now, see the shape parameter
• graph.adjacency rewritten when creating weighted graphs

• We use match.arg whenever possible. This means that character scalar options can be abbreviated and they are always case insensitive

• VF2 graph isomorphism routines can check subgraph isomorphism now, and they are able to return matching(s)
• The BLISS graph isomorphism algorithm is included in igraph now. See canonical.permutation, graph.isomorphic.bliss
• We use ARPACK for eigenvalue/eigenvector calculation. This means that the following functions were rewritten: page.rank, leading.eigenvector.community.*, evcent. New functions based on ARPACK: hub.score, authority.score, arpack.
• Edge weights for Fruchterman-Reingold layout (layout.fruchterman.reingold).
• Line graph calculation (line.graph)
• Kautz and de Bruijn graph generators (graph.kautz, graph.de.bruijn)
• Support for writing graphs in DOT format
• Jaccard and Dice similarity coefficients added (similarity.jaccard, similarity.dice)
• Counting the multiplicity of edges (count.multiple)
• The graphopt layout algorithm was added, layout.graphopt
• Generation of “famous” graphs (graph.famous).
• Create graphs from LCF notation (graph.cf).
• Dyad census and triad cencus functions (dyad.census, triad.census)
• Cheking for simple graphs (is.simple)
• Create full citation networks (graph.full.citation)
• Create a histogram of path lengths (path.length.hist)
• Forest fire model added (forest.fire.game)
• DIMACS reader can handle different file types now
• Biconnected components and articulation points (biconnected.components, articulation.points)
• Kleinberg’s hub and authority scores (hub.score, authority.score)
• as.undirected handles attributes now
• Geometric random graph generator (grg.game) can return the coordinates of the vertices
• Function added to convert leading eigenvector community structure result to a membership vector (community.le.to.membership)
• Weighted fast greedy community detection
• Weighted page rank calculation
• Functions for estimating closeness, betweenness, edge betweenness by introducing a cutoff for path lengths (closeness.estimate, betweenness.estimate, edge.betweenness.estimate)
• Weighted modularity calculation
• Function for permuting vertices (permute.vertices)
• Betweenness and closeness calculations are speeded up
• read.graph can handle all possible line terminators now (\r, \n, \r\n, \n\r)
• Error handling was rewritten for walktrap community detection, the calculation can be interrupted now
• The maxflow/mincut functions allow to supply NULL pointer for edge capacities, implying unit capacities for all edges

Bugs corrected in the R interface

• Fixed a bug in cohesive.blocks, cohesive blocks were sometimes not calculated correctly