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Alexandrescu, C++
Coding Standards

// named parameter versiontemplate <typename Graph, typename ComponentMap, typename OutputIterator, typename P, typename T, typename R> std::pair<std::size_t, OutputIterator> biconnected_components(const Graph& g, ComponentMap comp, OutputIterator out, const bgl_named_params<P, T, R>& params) template <typename Graph, typename ComponentMap, typename P, typename T, typename R> std::size_t biconnected_components(const Graph& g, ComponentMap comp, const bgl_named_params<P, T, R>& params) template <typename Graph, typename OutputIterator, typename P, typename T, typename R> OutputIterator articulation_points(const Graph& g, OutputIterator out, const bgl_named_params<P, T, R>& params)// non-named parameter versiontemplate <typename Graph, typename ComponentMap, typename OutputIterator, typename DiscoverTimeMap, typename LowPointMap> std::pair<std::size_t, OutputIterator> biconnected_components(const Graph& g, ComponentMap comp, OutputIterator out, DiscoverTimeMap discover_time, LowPointMap lowpt); template <typename Graph, typename ComponentMap, typename OutputIterator> std::pair<std::size_t, OutputIterator> biconnected_components(const Graph& g, ComponentMap comp, OutputIterator out); template <typename Graph, typename ComponentMap> std::size_t biconnected_components(const Graph& g, ComponentMap comp); template <typename Graph, typename OutputIterator> OutputIterator articulation_points(const Graph& g, OutputIterator out);

A connected graph is *biconnected* if the removal of any single
vertex (and all edges incident on that vertex) can not disconnect the
graph. More generally, the biconnected components of a graph are the
maximal subsets of vertices such that the removal of a vertex from a
particular component will not disconnect the component. Unlike
connected components, vertices may belong to multiple biconnected
components: those vertices that belong to more than one biconnected
component are called *articulation points* or, equivalently,
*cut vertices*. Articulation points are vertices whose removal
would increase the number of connected components in the graph. Thus,
a graph without articulation points is biconnected. The following
figure illustrates the articulation points and biconnected components
of a small graph:

Vertices can be present in multiple biconnected components, but each
edge can only be contained in a single biconnected component. The
output of the `biconnected_components` algorithm records the
biconnected component number of each edge in the property map
`comp`. Articulation points will be emitted to the (optional)
output iterator argument to `biconnected_components`, or can be
computed without the use of a biconnected component number map via
`articulation_points`. These functions return the number of
biconnected components, the articulation point output iterator, or a
pair of these quantities, depending on what information was
recorded.

The algorithm implemented is due to Tarjan [41].

`boost/graph/biconnected_components.hpp`

An undirected graph. The graph type must be a model of Vertex List Graph and Incidence Graph.OUT:

Python: The parameter is namedgraph.

The algorithm computes how many biconnected components are in the graph, and assigning each component an integer label. The algorithm then records which component each edge in the graph belongs to by recording the component number in the component property map. TheOUT:ComponentMaptype must be a model of Writable Property Map. The value type should be an integer type, preferably the same as theedges_size_typeof the graph. The key type must be the graph's edge descriptor type.

Default:dummy_property_map.

Python: Must be anedge_int_mapfor the graph.

Python default:graph.get_edge_int_map("bicomponent")

The algorithm writes articulation points via this output iterator and returns the resulting iterator.

Default: a dummy iterator that ignores values written to it.

Python: this parameter is not used in Python. Instead, both algorithms return a Pythonlistcontaining the articulation points.

This maps each vertex to an integer in the rangeUTIL/OUT:[0, num_vertices(g)). The typeVertexIndexMapmust be a model of Readable Property Map. The value type of the map must be an integer type. The vertex descriptor type of the graph needs to be usable as the key type of the map.

Default:get(vertex_index, g)

Python: Unsupported parameter.

The discovery time of each vertex in the depth-first search. The typeUTIL/OUT:DiscoverTimeMapmust be a model of Read/Write Property Map. The value type of the map must be an integer type. The vertex descriptor type of the graph needs to be usable as the key type of the map.

Default: an iterator_property_map created from astd::vectorofvertices_size_typeof sizenum_vertices(g)and usingget(vertex_index, g)for the index map.

Python: Unsupported parameter.

The low point of each vertex in the depth-first search, which is the smallest vertex reachable from a given vertex with at most one back edge. The typeUTIL/OUT:LowPointMapmust be a model of Read/Write Property Map. The value type of the map must be an integer type. The vertex descriptor type of the graph needs to be usable as the key type of the map.

Default: an iterator_property_map created from astd::vectorofvertices_size_typeof sizenum_vertices(g)and usingget(vertex_index, g)for the index map.

Python: Unsupported parameter.

The predecessor map records the depth first search tree. TheIN:PredecessorMaptype must be a Read/Write Property Map whose key and value types are the same as the vertex descriptor type of the graph.

Default:an iterator_property_map created from astd::vectorofvertex_descriptorof sizenum_vertices(g)and usingget(vertex_index, g)for the index map.

Python: Must be avertex_vertex_mapfor the graph.

A visitor object that is invoked inside the algorithm at the event-points specified by the DFS Visitor concept. The visitor object is passed by value [1].

Default:dfs_visitor<null_visitor>

Python: The parameter should be an object that derives from theDFSVisitortype of the graph.

The time complexity for the biconnected components and articulation
points algorithms
*O(V + E)*.

The file `examples/biconnected_components.cpp`
contains an example of calculating the biconnected components and
articulation points of an undirected graph.

[1]
Since the visitor parameter is passed by value, if your visitor
contains state then any changes to the state during the algorithm
will be made to a copy of the visitor object, not the visitor object
passed in. Therefore you may want the visitor to hold this state by
pointer or reference.

Copyright © 2000-2004 |
Jeremy Siek, Indiana
University (jsiek@osl.iu.edu) Doug Gregor, Indiana University |