The igraph library

igraph 0.6.5 Release Notes

igraph 0.6.5 is a minor release that contains only few big changes, and fixes a number of very annoying bugs.

See the news page for the complete list of changes. Here we only mention the most important new features and changes.

Vertex shape API in R

It is now possible to create user-defined vertex shapes for drawing graphs in R. See vertex.shapes() in the R manual.

Convert graphs to data frames in R

Function get.data.frame() does the opposite of graph.data.frame(), it converts a graph to one or two data frames that contain vertex and/or edge data.

Convert lists of tuples to graphs in Python

The Graph.TupleList() static method in Python now allows easy conversion of lists of tuples (such as database records or contents of CSV files) into graphs with named vertices and edge attributes.

Pajek reader supports bipartite graphs

See more in the R manual, Python documentation or C reference.

Graphical degree sequences

We added some new functions if a sequence of integers is graphial, i.e. it can be the degree sequence of a simple graph. See more in the R manual Python documentation or in the C reference.

k-regular random graphs

It is possible now to generate regular random graphs, faster than the general degree sequence based generator. See more in the R manual, Python documentation or the C reference.

Fitting power law distributions

This release includes the plfit library to maximum likelihood fit power laws to discrete or contiouous data. See more in the R manual, Python documentation or the C reference.

Speedup in R

Many basic graph operations (eg. printing the summary to the screen, querying attribute values) now avoid copying the graph, so these operations are now much faster in R.