This switches the edge_descriptor type in adj_list<> from std::tuple to
a custom struct.

Ensure in/out_edge/adjacency_iterator and associated are random access in adj_ist<> and UndirectedAdaptor<>

The edge and adjacency iterators of UndirectedAdaptor are now
implemented using Boost.Iterators and Boost.Range. Among other things,
this preserves underlying properties of the original iterators, such as
random access.

This removes reverse_graph.hpp, reverse_graph.hpp and copy.hpp, and
introduces some modifications in graph_adaptor.hh. This modification
fixes compilation problems across different boost versions.

This also keeps compatibility with earlier versions of boost.

This also maintains compatibility with older boost versions.

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.

	* src/boost-workaround/boost/graph/kamada_kawai_spring_layout.hpp: annotated code with openmp constructs.

	* src/graph/graph_adaptor.hh: graph_type should be a typedef to the original graph.

	* src/graph/graph_properties.hh, src/graph/graph_properties.cc: added pos_t type.

	* src/boost-workaround/boost/graph/fruchterman_reingold.hpp: annotated code with openmp constructs.

	* src/graph/graph_layout.cc: new file with graph layout routines.

	* src/graph/graph.cc: removed graph layout routines.

	* src/graph/graph_community_network.cc (struct get_community_network): fixed inversion of directedness test.

	* src/graph/graph.cc (GraphInterface::LabelComponents): use vector_property_map instead of HashedDescriptor. Don't use a static map!

	* src/graph/graph_adaptor.hh: fixed edge descriptor equality comparison, which must rely on underlying edge, regardless of whether it's inverted or not.


git-svn-id: https://svn.forked.de/graph-tool/trunk@121 d4600afd-f417-0410-95de-beed9576f240

* change from HashedDescriptorMap to vector_property_map in several
  algorithms to save memory and increase speed in the most common
  case, where the graph is unfiltered.




git-svn-id: https://svn.forked.de/graph-tool/trunk@102 d4600afd-f417-0410-95de-beed9576f240

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

git-svn-id: https://svn.forked.de/graph-tool/trunk@80 d4600afd-f417-0410-95de-beed9576f240

* fix python filtering in-edges bug


git-svn-id: https://svn.forked.de/graph-tool/trunk@79 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

* Range filters now support all kinds of scalar properties without falling back to python code


git-svn-id: https://svn.forked.de/graph-tool/trunk@46 d4600afd-f417-0410-95de-beed9576f240

git-svn-id: https://svn.forked.de/graph-tool/trunk@1 d4600afd-f417-0410-95de-beed9576f240