GitLab

Fix possible deadlock condition in random graph generation with
no_parallel and/or no_self_loops.

Graphs are now exactly copied, including filter state and filter
property maps.

Use tr1::tuple instead of boost::tuple to get around maximum tuple size
limit (this requires GCC 4.3). Introduce get_prop<> template function to
facilitate access of property maps from inline C++ code.

Also, get rid of g.underlying_graph(), and rely on "private" variable
g._Graph__graph instead.

Betweenness centrality should be differently normalized for undirected
and directed graphs, i.e., (n-2)*(n-1)/2 vs. (n-2)*(n-1),
respectively. Also, edge centrality should be respectively normalized
with n*(n-1)/2 and n*(n-1).

No longer functional or relevant.

A new 'clustering' sub-module was created.

This commit removes the internal property maps from the GraphInterface
class, and makes all property maps external by default. The internal
property maps were moved to the python layer.

This is to avoid a common error of not being able to correctly normalize
a histogram because of truncated integer division.

Other objects are now automatically converted (tuple, lists, dicts,
str).

This fixes the representation of property maps which don't have a
value type included in the value_types list, such as index properties.

It was needlessly O(E^2), and now is O(E).

Edge indexes weren't properly copied.

Python binding will follow

GCC 4.3 complains when a typedef overrides the meaning of another type.

Avoiding use of lambda::bind when not necessary (or very convenient).

A couple of bugs fixed. Local frame dict is read-only in python, so the
updated arguments are returned in a dict instead.

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.

It is now much simpler, and works better.

This adds the graph_tool.test module, which can be run with
graph_tool.test.run()

Put the run_action function in a separate submodule, and make it work
properly with the new code.

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