This makes sphinx's autodoc slightly happier.

This module contains several search algorithms and a visitor interface.

This includes generations of releated matrices for spectral analysis,
such as the adjacency matrix, laplacian matrix and incidence matrix.

This includes the edmonds karp, push relabel and kolmogorov maximum flow
algorithms from the BGL.

We will rely on sphinx + docstrings instead.

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

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.

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 adds a graph_draw() functions which draws graphs in variety of
layouts and formats, and also to the screen, using the python graphviz
bindings.

The whole histogram code has been redone, and the code has been
simplified. The three-point vertex-edge-vertex correlation has been
scrapped, since it's not frequently used, and would make compilation
even more expensive.

This also adds some missing files to the generation routine.

Now graphml files properly contain all the supported value types, which
are all perfectly preserved when read (floating point data is now saved
in hexadecimal format). Several other improvements were made, such as
the ability to read and write to python file-like objects.

It is also now possible to have arbitrary python object properties, and
store them persistently (which is done internally with the pickling
interface).

vector<bool> was totally abolished, since its implementation is quite
broken. See: http://www.gotw.ca/publications/N1211.pdf and
http://www.gotw.ca/publications/N1185.pdf Now a uint8_t (aka. char) is
used in graph properties instead of a bool.

Graph types can now be fully pickled (this may not be feasible
memory-wise if the graph is too large, since the whole XML
representation is dumped to a string before it is saved on disc).

This commit splits libraph_tool into different libraries:
 
   - libgraph_tool_core
   - libgraph_tool_clustering (*)
   - libgraph_tool_community (*)
   - libgraph_tool_correlations (*)
   - libgraph_tool_distance (*)
   - libgraph_tool_generation (*)
   - libgraph_tool_layout (*)
   - libgraph_tool_misc (*)
   - libgraph_tool_stats (*)

It also adds the python sub-module 'test', which provides extensive unit
testing of the core functionality. The core library is fully functional
and all test pass successfully.

(*) -> module needs to be ported to new refactoring, and does not yet build

Everything was moved into the graph_tool directory, which should have,
after installation, the following structure:

graph_tool/                          Top-level package
      __init__.py                    Initialize the graph_tool package
      libgraph_tool.so               libgraph_tool submodule
      libgraph_tool.la               libtool file for libgraph_tool
      include/                       C++ include files for dynamically
                                     compiled code