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.
We took some step towards turning igraph to an efficient platform for implementing graph algorithms. In particular, we have a set of utility types that support general scientific computing and working with graphs: vectors, matrices, stacks, queues, heaps, adjacency lists, etc.
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.
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 Reference Manual.
Some classic graphs can be created by giving their name. This is
very handy if one needs a test graph quickly. See
(The idea is based on Combinatorica, a Mathematica extension.)
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 (
testing for multiple edges (
igraph_is_multiple), and counting the multiplicity of
This is a nice force-based layout algorithm. See the documentation of
igraph can now write graphs to files in the DOT format, used by
GraphViz. See documentation:
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
igraph_betweenness_estimate), and edge betweenness
An experimental C attribute interface was added. This allows using graph/vertex/edge attributes when programming from C. See more here.
igraph_community_leading_eigenvector_*. New functions based on
Experimental C attribute interface added. I.e. it is possible to use graph/vertex/edge attributes from C code now.
igraph_is_multiple “return” boolean vectors
igraph_add_edge adds a single edge to the graph
igraph_full_citation to create full citation networks
igraph_path_length_hist, create a histogram of path lengths
igraph_read_graph_* functions can handle all possible line
terminators now (\r, \n, \r\n, \n\r)
cut vector was used