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 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 evcent, pagerank, hub_score, etc. functions in the Python documentation.

Plotting functionality based on the Cairo graphics library (so you need to install python-cairo if you want to use it). Currently the following objects can be plotted: graphs, adjacency matrices and dendrograms. Some crude support for plotting histograms is also implemented. Plots can be saved in PNG, SVG and PDF formats.

See the details in the documentation.

igraph can now be invoked by calling the script called
`igraph`

from the command line. The script launches the
Python interpreter and automatically imports igraph functions into the
main namespace.

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

Many functions were updated to handle weighted graphs: fast greedy community detection, Page Rank, modularity calculation, the Fruchterman-Reingold layout algorithm.

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 loop edges, testing for multiple edges) and counting the multiplicity of edges.

igraph Graph objects can be serialized (pickled) in Python.

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

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

Classic social network analysis tools for classifying the dyads and triads of a network.

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

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 Jaccard and the Dice similarities.

- Added shell interface: igraph can now be invoked by calling the script called
`igraph`

from the command line. The script launches the Python interpreter and automatically imports igraph functions into the main namespace - Pickling (serialization) support for
`Graph`

objects - Plotting functionality based on the Cairo graphics library (so you need to install python-cairo if you want to use it). Currently the following objects can be plotted: graphs, adjacency matrices and dendrograms. Some crude support for plotting histograms is also implemented. Plots can be saved in PNG, SVG and PDF formats.
- Unified
`Graph.layout`

method for accessing layout algorithms - Added interfaces to walktrap community detection and the BLISS isomorphism algorithm
- Added dyad and triad census functionality and motif counting
`VertexSeq`

and`EdgeSeq`

objects can now be restricted to subsets of the whole network (e.g., you can select vertices/edges based on attributes, degree, centrality and so on)

- Many types (stack, matrix, dqueue, etc.) are templates now They were also rewritten to provide a better organized interface
- 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
`igraph_canonical_permutation`

,`igraph_isomorphic_bliss`

- We use ARPACK for eigenvalue/eigenvector calculation. This means that the
following functions were rewritten:
`igraph_pagerank`

,`igraph_community_leading_eigenvector_*`

. New functions based on ARPACK:`igraph_eigenvector_centrality`

,`igraph_hub_score`

,`igraph_authority_score`

,`igraph_arpack_rssolve`

,`igraph_arpack_rnsolve`

Experimental C attribute interface added. I.e. it is possible to use graph/vertex/edge attributes from C code now.

Edge weights for Fruchterman-Reingold layout.

Line graph calculation.

Kautz and de Bruijn graph generators

Support for writing graphs in DOT format

Jaccard and Dice similarity coefficients added

`igraph_count_multiple`

added`igraph_is_loop`

and`igraph_is_multiple`

"return" boolean vectorsThe graphopt layout algorithm was added,

`igraph_layout_graphopt`

Generation of "famous" graphs,

`igraph_famous`

Create graphs from LCF notation,

`igraph_lcf`

,`igraph_lcf_vector`

`igraph_add_edge`

adds a single edge to the graphDyad census and triad cencus functions added

`igraph_is_simple`

addedprogress handlers are allowed to stop calculation

`igraph_full_citation`

to create full citation networks`igraph_path_length_hist`

, create a histogram of path lengthsforest fire model added

DIMACS reader can handle different file types now

Adjacency list types made public now (

`igraph_adjlist_t`

,`igraph_adjedgelist_t`

)Biconnected components and articulation points can be computed

Eigenvector centrality computation

Kleinberg's hub and authority scores

igraph

*to*undirected handles attributes nowGeometric random graph generator can return the coordinates of the vertices

Function added to convert leading eigenvector community structure result to a membership vector (

`igraph_le_community_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

Weighted modularity calculation

`igraph_permute_vertices`

addedBetweenness ans closeness calculations are speeded up

Startup positions can be supplied to the Kamada-Kawai layout algorithms

`igraph_read_graph_*`

functions 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 a null pointer for edge capacities, implying unit capacities for all edges

- Memory leak fixed in adjacency list handling
- Memory leak fixed in maximal independent vertex set calculation
- Fixed a bug when rewiring undirected graphs with igraph_rewire
- Fixed edge betweenness community structure detection for unconnected graphs
- Make igraph compile with Sun Studio
- Betweenness bug fixed, when not computing for all vertices
- memory usage of clique finding reduced
- Corrected bugs for motif counts when not all motifs were counted,
but a
`cut`

vector was used - Bugs fixed in trait games and cited type game
- Accept underscore as letter in GML files
- GML file directedness notation reversed, more logical this way