News

About igraph releases and other things

python-igraph 0.7.0

Release Notes

There are a bunch of new features in the library itself, and other important changes in the life of the project. Thanks everyone for sending code and reporting bugs!

igraph @ github

igraph’s development has moved from Launchpad to github. This has actually happened several month ago, but never announced officially. The place for reporting bugs is at https://github.com/igraph/igraph/issues.

New homepage

igraph’s homepage is now hosted at http://igraph.org, and it is brand new. We wanted to make it easier to use and modern.

Better nightly downloads

You can download nightly builds from igraph at http://igraph.org/nightly. Source and binary R packages (for windows and OSX), C library bundles, and Python source packages are built currently. We are planning to add binary Python packages soon.

Other news and fixes

  • Support edge weights in leading eigenvector community detection.
  • Added the LAD library for checking (sub)graph isomorphism, version 1.
  • Support incidence matrices in bipartite Pajek files.
  • Added Graph.layout_bipartite() function, a simple two-column layout for bipartite graphs.
  • Pajek files in matrix format are now directed by default, unless they are bipartite.
  • Support weighted (and signed) networks in Pajek when file is in matrix format.
  • Fixed a bug in Barabasi(), algorithm psumtree-multiple just froze.
  • Added support for Boolean attributes in the GraphML and GML readers and writer.
  • Added support for Boolean attributes
  • Change MDS layout coordinates, first dim is according to first eigenvalue, etc.
  • Add Graph.st_mincut() method, to find a minimal s-t cut in a graph.
  • Added support for the source= and target= parameters in Graph.mincut().
  • Graph.rewire(): now supports the generation and destruction of loops.
  • Erdos-Renyi type bipartite random graphs: Graph.Random_Bipartite().
  • Python: moved igraph.nexus to igraph.remote.nexus
  • Fix modularity values of multilevel community if there are no merges at all.
  • Added keep_aspect_ratio option to Graph.__plot__().
  • Fixed a potential crash in igraph_edge_connectivity(), because of an un-initialized variable in the C code.
  • VertexSeq and EdgeSeq can now be indexed with NumPy integers
  • Avoiding overflow in Graph.closeness() and related functions.
  • Show plots inline in IPython.
  • Fixed an invalid memory read (and a potential crash) in the infomap community detection.
  • Fix a bug in triad census that set the first element of the result to NaN.
  • Fixed a bug in weighted mudularity calculation, sum of the weights was truncated to an integer.
  • Fixed a bug in weighted multilevel communtiies, the maximum weight was rounded to an integer.
  • Reimplement push-relabel maximum flow with gap heuristics.
  • Fixed invalid return value of RunningMean.__length__().
  • Fixed missing whitespace in Pajek writer when the ID attribute was numeric.
  • Fixed a bug that caused the GML reader to crash when the ID attribute was non-numeric.
  • Added Vertex.graph and Edge.graph attributes.
  • Fix dyad census instability, sometimes incorrect results were reported.
  • Dyad census detects integer overflow now and gives a warning.
  • Added a Gomory-Hu tree implementation: Graph.gomory_hu_tree().
  • sorted out return type inconsistency for Vertex.constraint(), closes #259.
  • Added weights support for Graph.community_optimal_modularity(), closes #511.
  • Faster maximal clique finding.
  • Fixed a bug in Graph.isomorphic_vf2(), edge colors were ignored.
  • Added rudimentary support for drawing edge labels.
  • Generate graphs from a stochastic block model: Graph.SBM().
  • We use PRPACK to calculate PageRank scores see https://github.com/dgleich/prpack
  • Implement the start argument in igraph_hrg_fit (#225).
  • Fixed a bug in graph density that resulted in incorrect values for undirected graphs with loops.
  • Fixed a bug that made Bellman-Ford shortest paths calculations fail.
  • Fixed a minimum cut bug for weighted undirected graphs (#564).
  • Fixed argument ordering in minimum cut and related functions.