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regarded and expertly designed C++ library projects in the
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— Herb Sutter and Andrei
Alexandrescu, C++
Coding Standards

// named parameter versiontemplate <typename Graph, typename P, typename T, typename R> void undirected_dfs(Graph& G, const bgl_named_params<P, T, R>& params);// non-named parameter versiontemplate <typename Graph, typename DFSVisitor, typename VertexColorMap, typename EdgeColorMap> void undirected_dfs(const Graph& g, DFSVisitor vis, VertexColorMap vertex_color, EdgeColorMap edge_color) template <typename Graph, typename DFSVisitor, typename VertexColorMap, typename EdgeColorMap> void undirected_dfs(const Graph& g, DFSVisitor vis, VertexColorMap vertex_color, EdgeColorMap edge_color, typename graph_traits<Graph>::vertex_descriptor start)

The `undirected_dfs()` function performs a depth-first
traversal of the vertices in an undirected graph. When possible, a
depth-first traversal chooses a vertex adjacent to the current vertex
to visit next. If all adjacent vertices have already been discovered,
or there are no adjacent vertices, then the algorithm backtracks to
the last vertex that had undiscovered neighbors. Once all reachable
vertices have been visited, the algorithm selects from any remaining
undiscovered vertices and continues the traversal. The algorithm
finishes when all vertices have been visited. Depth-first search is
useful for categorizing edges in a graph, and for imposing an ordering
on the vertices. Section Depth-First
Search describes the various properties of DFS and walks through
an example.

Similar to BFS, color markers are used to keep track of which vertices have been discovered. White marks vertices that have yet to be discovered, gray marks a vertex that is discovered but still has vertices adjacent to it that are undiscovered. A black vertex is discovered vertex that is not adjacent to any white vertices.

Edges are also colored during the search to disambiguate tree and back edges.

The `undirected_dfs()` function invokes user-defined actions at
certain event-points within the algorithm. This provides a mechanism
for adapting the generic DFS algorithm to the many situations in which
it can be used. In the pseudo-code below, the event points for DFS
are indicated in by the triangles and labels on the right. The
user-defined actions must be provided in the form of a visitor object,
that is, an object whose type meets the requirements for a DFS Visitor. In the pseudo-code we show
the algorithm computing predecessors *p*, discover time *d*
and finish time *t*. By default, the `undirected_dfs()`
function does not compute these properties, however there are
pre-defined visitors such as `predecessor_recorder`
and `time_stamper` that can
be used to do this.

DFS( |
- - initialize vertex |

`boost/graph/undirected_dfs.hpp`

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

Python: The parameter is namedgraph.

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].UTIL/OUT:

Default:dfs_visitor<null_visitor>

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

This is used by the algorithm to keep track of its progress through the graph. The typeUTIL:VertexColorMapmust be a model of Read/Write Property Map and its key type must be the graph's vertex descriptor type and the value type of the color map must model ColorValue.

Default:an iterator_property_map created from astd::vectorofdefault_color_typeof sizenum_vertices(g)and using thei_mapfor the index map.

Python: The color map must be avertex_color_mapfor the graph.

This is used by the algorithm to keep track of which edges have been visited. The typeIN:EdgeColorMapmust be a model of Read/Write Property Map and its key type must be the graph's edge descriptor type and the value type of the color map must model ColorValue.

Default:none.

Python: The color map must be anedge_color_mapfor the graph.

This specifies the vertex that the depth-first search should originate from. The type is the type of a vertex descriptor for the given graph.IN:

Default:*vertices(g).first

This maps each vertex to an integer in the range[0, num_vertices(g)). This parameter is only necessary when the default color property map is used. 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)Note: if you use this default, make sure your graph has an internalvertex_indexproperty. For example,adjacenty_listwithVertexList=listSdoes not have an internalvertex_indexproperty.

Python: Unsupported parameter.

The time complexity is *O(E + V)*.

is invoked on every vertex of the graph before the start of the graph search.`vis.initialize_vertex(s, g)`is invoked on the source vertex once before the start of the search.`vis.start_vertex(s, g)`is invoked when a vertex is encountered for the first time.`vis.discover_vertex(u, g)`is invoked on every out-edge of each vertex after it is discovered.`vis.examine_edge(e, g)`is invoked on each edge as it becomes a member of the edges that form the search tree. If you wish to record predecessors, do so at this event point.`vis.tree_edge(e, g)`is invoked on the back edges in the graph.`vis.back_edge(e, g)`is invoked on the back edges in the graph as well as on each tree edge after its target vertex is finished.`vis.finish_edge(e, g)`is invoked on a vertex after all of its out edges have been added to the search tree and all of the adjacent vertices have been discovered (but before their out-edges have been examined).`vis.finish_vertex(u, g)`

An example is in
`examples/undirected_dfs.cpp`.

[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 © 2000-2001 |
Jeremy Siek,
Indiana University (jsiek@osl.iu.edu) Lie-Quan Lee, Indiana University (llee@cs.indiana.edu) Andrew Lumsdaine, Indiana University (lums@osl.iu.edu) |