This makes the code more efficient if the input parameter combinations
are much larger than the graph itself.

This changes stlightly the information passed to the auxiliary functions
provided by the user, so that more arbitrary structures can be
constructed more easily.

This implements a general "blockmodel" generation / rewiring algorithm,
using Gibbs acceptence / rejection sampling (a.k.a Metropolis-Hastings).

This also implements some optimizations in the rewiring code, which
makes it more efficient on filtered graphs.

This introduces several simplifications and corrections to the graph
rewire algorithm, to guarantee unbiased sampling.

Now a move is outright rejected if it produces a
self-loop/parallel-edge, instead of retried. This also adds a
"non-sweep" mode, where edges are rewired randomly, possibly with
repetition.

The edge moves are now simplified to the target of the edges only,
since swaping sources is redundant.

The number of iterations can now be explicitly modified, so it is not
necessary to call the function more than once, and it is emphasized in
the documentation that only after sufficiently many iterations can the
graph be guaranteed to be fully mixed.

This enables support for older versions of GCC (>=4.2), by falling back
to the boost tr1 implementation when the GCC version is less than 4.4.

This includes also some internal refactoring, and bug fixes.

This implements a simpler rewire strategy where the edges are randomly
placed, without preserving the degrees of the vertices.

This is a large commit which replaces lambda::bind with boost::bind in
most parts of the code. This improves compilation time, and slightly
decreases compilation memory usage in some cases.

No longer only thrown GraphError upon any error, but instead throw
specific exceptions which are more meaninful and are mapped to standard
python exceptions, such as IOError, ValueError and RuntimeError.

The generators from boost::random seem to have a bug which causes them
to be biased. The generators from tr1::random seem to be in better
shape.

See: http://thread.gmane.org/gmane.comp.lib.boost.user/48006

graph_rewiring.cc: use static_cast<rng_t::result_type> instead of
uint32_t to convert the seed value for the rng_t constructor, so
the code becomes compatible with any rng_t.

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

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

This is a huge commit which completely refactors the metaprogramming
engine which generates and selects (at run time) the graph view type and
the desired algorithm implementation (template instantiation) that runs
on it.

Things are laid out now as following. There exists a main underlying
graph type (GraphInterface::multigraph_t) and several other template
classes that mask it some way or another, in a hierarchic fashion:

     multigraph_t -> filtered_graph (edges only, vertices only, both)
         |                               |           |           |
         |                               |           |           |
         |-------(reversed_graph)--------|-----------|-----------|
         |                               |           |           |
         \------(UndirectedAdaptor)------------------------------/

The filtered_graph filters out edges and/or vertices from the graph
based on some scalar boolean property. The reversed_graph reversed the
direction of the edges and, finally, the UndirectedAdaptor treats the
original directed graphs as undirected, transversing the in- and
out-edges of each vertex indifferently. Thus, the total number of graph
view types is 12. (The option --disable-graph-filtering can be passed to
the configure script, which will disable graph filtering altogether and
bring the total number down to 3, to reduce compile time and memory
usage)

In general, some specific algorithm, implemented as a template function
object, needs to be instantiated for each of those types. Furthermore,
the algorithm may also depend on other types, such as specific
property_maps. Thus, the following scheme is used:

    struct my_algorithm // algorithm to be implemented
    {
        template <class Graph, class PropertyMap>
        void operator()(Graph *g, PropertyMap p, double& result) const
        {
            // ...
        }
    };

    // in order for the above code to be instantiated at compile time
    // and selected at run time, the run_action template function object
    // is used from a member function of the GraphInterface class:

    double GraphInterface::MyAlgorithm(string prop_name)
    {
        double result;
        boost::any vprop = prop(property, _vertex_index, _properties);
        run_action<>()(*this, bind<void>(my_algorithm(), _1, _2,
                                         var(result)),
                       vertex_scalar_properties())(vprop);
        return result;
    }

The whole code was changed to reflect this scheme, but now things are
more centralized and less ad-hoc code needed to be
written. Unfortunately, due to GCC's high memory usage during template
instantiations, some of the code (namely all the degree correlation
things) had to be split in multiple compilation units... Maybe this will
change in the future if GCC gets optimized.

This commit also touches other parts of code. More specifically, the way
filtering gets done is very different. Now we only filter on boolean
properties, and with the above scheme, the desired implementation runs
with the correct chosen type, and no implicit type conversions should
ever happen, which would have a bad impact on performance.

Move remaining parallelism check out of the outer/inner loops and into the parallel_check() function.

3) missing parallel edge check in uncorrelated strategy
2) "_in()" for target and source of "target swap edge"
1) order of arguments of swap_edge_triad::parallel_check

melodrama time...
"premature optimization is the root of all evil"
"careless abstraction are the fruits of its tree"

The check for parallel edges was cleaned up and abstracted into a
function, and other minor things were changed. Code comments were added
to places where it might have been hard to understand.

Major changes to both correlated and uncorrelated rewiring code.
Both cases are now functional and use iterative shuffling.
Uncorrelated picks edges to rewire directly, correlated picks
vertices in order to choose edges.

Several changes in the random rewiring code, making it fully
functional for the correlated case.
The reshuffling operations lag in efficiency, even though already
the algorithm runs in little time.

It's still buggy (of course), but now we'll try to fix it in it's own
 branch.

This reverts commit 1cdbdeef.

Remove graph rewiring for now, since it's quite buggy. It will be
re-commited when ready.

* src/Makefile.am: removed 'boost_workaround' dist files

* src/graph/graph_rewiring.cc: deleted blank lines.


git-svn-id: https://svn.forked.de/graph-tool/trunk@116 d4600afd-f417-0410-95de-beed9576f240

        * ChangeLog: updated ChangeLog file with svn history

        * src/graph/graph_filtering.hh: added add_edge() and remove_edge() functions for filtered graphs

        * src/graph/shared_map.hh: included SharedContainer

        * src/graph/graph_rewiring.cc: initial support for random graph rewiring



git-svn-id: https://svn.forked.de/graph-tool/trunk@114 d4600afd-f417-0410-95de-beed9576f240