// named parameter versiontemplate <class Graph, class class P, class T, class R> void depth_first_search(Graph& G, const bgl_named_params<P, T, R>& params);// non-named parameter versiontemplate <class Graph, class DFSVisitor, class ColorMap> void depth_first_search(const Graph& g, DFSVisitor vis, ColorMap color) template <class Graph, class DFSVisitor, class ColorMap> void depth_first_search(const Graph& g, DFSVisitor vis, ColorMap color, typename graph_traits<Graph>::vertex_descriptor start)

The `depth_first_search()` function performs a depth-first
traversal of the vertices in a directed 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.

The `depth_first_search()` 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 the 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
`depth_first_search()` 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/depth_first_search.hpp`

A directed graph. The graph type must be a model of Incidence Graph and Vertex 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 typeIN:ColorMapmust 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 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 forward or cross edges in the graph. In an undirected graph this method is never called.`vis.forward_or_cross_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)`

The example in
`examples/dfs-example.cpp` shows DFS applied to the graph in
Figure 1.

[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) |