GitLab

This includes the function motif_significance() into the clustering
module.

Individual filters can be stashed and popped by passing keyword
arguments to the respective functions. Additionally the filter state can
be obtained and set directly, with the get_filter_state() and
set_filter_state() functions.

This was not working due to filtering semantics modifications.

This implements an efficient motif counting algorithm.

The edge index housekeeping was not performed on edges which were
deleted due to vertex removal.

This provides a more convenient way of deleting vertices or edges
according to a simple criterion.

Add support for v.{out|in}_neighbours(), for direct iteration over the
neighbours, as well as v.all_edges() and v.all_neighbours(). This also
properly exports the Vertex and Edge classes, with docstrings.

This adds the centrality module, which supports betweenness, eigentrust,
pagerank and absolute trust.

The seed option is now correctly interpreted.

The seed option is now properly passed to graphviz.

Now inline() automatically converts known variables (such as property
maps) and defaults to boost::python objects, instead of scxx objects.

The code now is only generated for the current filtered, reversed and/or
directed status of the graph, reducing compile time and binary size.

Edge modification (remove and add) is now protected by a GraphWrap
class, which takes care of the edge index housekeeping, which does not
need to be done by hand anymore.

The function is also no longer bound to one graph, and can take an
arbitrary number of variables of known or unknown types, including
graphs.

e.g., g.save("~/foo.xml")

i.e. g.degree_property_map("in") will create and return a vertex property map
which corresponds to the in-degrees of the vertices. This is useful for
temporarily modifying or getting an array of degrees.

A property map object has now a get_array() member which returns an internally
owned array pointing to the property values.

Allow direct specification of vertex size, which accepts property maps,
and a couple of bug fixes.

This adds vertex_average() and edge_average() to the stats module.

This includes the community sub-module.

Reduce duplication of code for loading C++ modules.

Add global variables to configure.ac, to avoid unnecessary multiple
definitions.

This also creates the misc sub-module. This may be re-organized in the
future.

This contains at the moment functions to perform basic vertex and edge
searches.

This allows to import all submodules from graph_tool with one command,
e.g.,

   from graph_tool.all import *

This is a re-implementation based on new histogram code, which does not
build a 2D histogram, and is thus more exact and uses less memory.

This fixes a rather central bug, which causes duplicated indexes if
edges are removed and then new ones are added. Edge indexes are now
recycled as they are removed and then new ones are added. This still
guarantees O(1) complexity when adding or removing edges.

Avoids having to do

    g = Graph()
    g.load("foo")

each time. Now one can do simply,

    g = load_graph("foo")

Fantastic.