About igraph releases and other things

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.

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 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.

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.)

The new
`graph.formula()`

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

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`

.

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`

.

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

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

Classic social network analysis tools for classifying the dyads
(`dyad.census`

) and triads
(`triad.census`

.

igraph is now able to calculate
biconnected components and

articulation points.

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.

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.

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.

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

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.

- 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

- Fixed a bug in
`cohesive.blocks`

, cohesive blocks were sometimes not calculated correctly