Fix compilation warnings with boost 1.40, remove unnecessary files, fix
autoconf macros and link with "boost_graph".

This also raises the minimum boost version to 1.40.

This fixes an obvious problem, where the graph gets deleted, and the
descriptors are still lying around. Usage of orphaned descriptors will
now just raise a ValueError.

The __repr__ function of Edge, Vertex, and PropertyMap now give
something more informative about each object.

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.

Fix bad_any_cast bug when passing a weight property.

Thins changes the graph filtering code slightly to wrap graph types with
GraphWrap, which automatically updates the edge index list when edges
are removed and added to the graph.

This also changes how graphs are passed to algorithms, which is now by
reference instead of pointer. (hence this touches lots of code, but
changes are trivial)

This makes the naming more sensible.

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.

Now all symbols are exported by default, except those strictly marked
as hidden.

This includes a new vector property map type (fast_vector_property_map)
which has optional disabling of bounds checking, through its associate
map type (unchecked_fast_vector_property_map). This should improve
performance on algorithms which depend on tight loops which access
property maps.

Bounds checking is only disabled locally just before the algorithms run,
and proper care is taken for bounds checking _beforehand_. The property
maps exposed to python still have internal bounds checking.

i.e. g.degree_property_map("in") will create and return a vertex property map
which corresponds to the in-degrees of the vertices. This is useful for
temporarily modifying or getting an array of degrees.

This makes operations on graphs more flexible in some circumstances.

This fixes a rather central bug, which causes duplicated indexes if
edges are removed and then new ones are added. Edge indexes are now
recycled as they are removed and then new ones are added. This still
guarantees O(1) complexity when adding or removing edges.

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.

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.

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

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.

Some visibility voodoo is necessary to ensure that RTTI work properly
across DSO boundaries, which is necessary to properly handle dynamic
property maps and such. Additionally, the action template must have a
different name each time the action code changes, to avoid additional
weirdness.

This also adds some other utility functions/typedefs to make writing
"inline" c++ code easier.

It is now possible to run arbitrary "inline" C++ code from python, using
scipy.weave, as such:

        g = graph_tool.Graph()
        g.load("foo.xml")
        value = 2.0
        g.run_action('cout << num_vertices(g) << " " << value << endl;',
                     ["value"]);

The code gets compiled the first time, and is reused after that. Python
local and global variables can be passed to C++, as shown above, by
specifying a list of passed variables as the second argument.

The graph object passed to the edit function is now a instance of the
Graph class which wraps GraphInterface, not a GraphInterface instance.

Property maps can now be obtained as such:

         weight = g.edge_properties['weight']
         print weight[v] # v is a Vertex object
         weight[v] = 2.0
         # and so on...

The list of properties is obtained from g.vertex_properties,
g.edge_properties and g.graph_properties, which can be read as
dictionaries. The last can be set also, as such:

         g.graph_properties = {foo:"bar", baz:42}

Functions to add and remove vertices or adges were also added
(add_{vertex|edge}, remove_{vertex|edgge}).

Vertex and Edge types can also now be printed for convenience, as such:

       for v in g.vertices():
           print v
       for e in g.edges():
           print e

which results, for example, in:
0
1
2
3
4
5
6
(0,1)
(1,2)
(2,6)
(3,4)
(4,5)
(4,2)
(5,6)
(6,1)

(this also adds the forgotten graph_tool.py file, which was previously
on .gitignore)

Vertices and edges can be accessed from the graph class, as such:

    import graph_tool
    g = graph_tool.Graph()
    for v in g.vertices():
        for e in v.out_edges():
           # do something...

Additionally, the --edit-{vertex|edge|graph}-property was ported to the
new interface, and is working again, as it used to.

The Vertex and Edge class no longer have the 'get_property' and
'set_property' method. They'll be replaced by a new method of accessing
property maps.

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

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

This reverts commit 1cdbdeef.

The Histogram type 'hist_t' should have a 'double' value, so that
counts of 1/2 can be added when it's known things are going to be
counted twice.

(and I don't know what that 'double_t' thing was doing there)

    
Filtered vertices and edges can be permanently removed from the graph
with --purge-vertices and --purge-edges, respectively. The edge or
vertex filter is automatically removed, afterwards. This is useful if
maximum speed is necessary, and saving and reloading the graph without
filtering is not desired.
    
(this commit also removes some trailing whitespaces)

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

Simplify range filtering, and definitely remove python filtering
    
Simplify range filtering of vertices and edges, by always filtering
both at once, even if all vertices or edges are being considered. This
severely reduces compilation time and memory, at a small potential
cost in run-time speed, which will probably be overshadowed by other
things, such as dynamic_map look-ups ("premature optimization is the
root of all evil"). Also, remove python-filtering, since, in the end,
it is just code bloat, since it is quite slow for most uses and can be
replaced, generally, by python property editing + range filtering.

	* 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

        * 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

* include central point dominance


git-svn-id: https://svn.forked.de/graph-tool/trunk@103 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

* 'Graph' type now available to python editing, with iterators to access all vertices and edges
* out_edges and in_edges return iterators instead of lists for python editing


git-svn-id: https://svn.forked.de/graph-tool/trunk@82 d4600afd-f417-0410-95de-beed9576f240