This fixes issue #318

This enables the inclusion of the non-boost tr1 headers if a recent
enough version of libstdc++ is detected. This als fixes a bug with
clang when sparsehash pulls unwanted tr1 headers.

The object may be globally reset via the seed_rng() function.

This implements a layout module (called 'draw' from python) with an
implementation of the arf spring-block layout.

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

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

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.

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.

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.

Line breaks at column 80 were added, and all trailing whitespace was deleted. Code
comments were modified and some more were added.

* removed exeption throwing in scalarS to improve performance


git-svn-id: https://svn.forked.de/graph-tool/trunk@113 d4600afd-f417-0410-95de-beed9576f240

git-svn-id: https://svn.forked.de/graph-tool/trunk@101 d4600afd-f417-0410-95de-beed9576f240

* further code parellelization with openmp (vertex and edge histograms, correlations, and reciprocity)



git-svn-id: https://svn.forked.de/graph-tool/trunk@99 d4600afd-f417-0410-95de-beed9576f240

git-svn-id: https://svn.forked.de/graph-tool/trunk@59 d4600afd-f417-0410-95de-beed9576f240

git-svn-id: https://svn.forked.de/graph-tool/trunk@58 d4600afd-f417-0410-95de-beed9576f240

* fix bug in graph/graph_correlations_combined.cc (precision error when error is very small)


git-svn-id: https://svn.forked.de/graph-tool/trunk@40 d4600afd-f417-0410-95de-beed9576f240

* put combined degree correlation stuff in src/graph/graph_correlations_combined.cc
* some code cleanups in src/graph-tool


git-svn-id: https://svn.forked.de/graph-tool/trunk@29 d4600afd-f417-0410-95de-beed9576f240