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<Title>Boost Graph Library: BFSVisitor</Title>
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<H1><img src="figs/python.gif" alt="(Python)"/>BFS Visitor Concept</H1>

This concept defines the visitor interface for <a
href="./breadth_first_search.html"><tt>breadth_first_search()</tt></a>.
Users can define a class with the BFS Visitor interface and pass and
object of the class to <tt>breadth_first_search()</tt>, thereby
augmenting the actions taken during the graph search.

<h3>Refinement of</h3>

<a href="../../utility/CopyConstructible.html">Copy Constructible</a>
(copying a visitor should be a lightweight operation).


<h3>Notation</h3>

<Table>
<TR>
<TD><tt>V</tt></TD>
<TD>A type that is a model of BFS Visitor.</TD>
</TR>

<TR>
<TD><tt>vis</tt></TD>
<TD>An object of type <tt>V</tt>.</TD>
</TR>

<TR>
<TD><tt>G</tt></TD>
<TD>A type that is a model of Graph.</TD>
</TR>

<TR>
<TD><tt>g</tt></TD>
<TD>An object of type <tt>G</tt>.</TD>
</TR>

<TR>
<TD><tt>e</tt></TD>
<TD>An object of type <tt>boost::graph_traits&lt;G&gt;::edge_descriptor</tt>.</TD>
</TR>

<TR>
<TD><tt>s,u</tt></TD>
<TD>An object of type <tt>boost::graph_traits&lt;G&gt;::vertex_descriptor</tt>.</TD>
</TR>

</table>

<h3>Associated Types</h3>

none
<p>

<h3>Valid Expressions</h3>

<table border>
<tr>
<th>Name</th><th>Expression</th><th>Return Type</th><th>Description</th>
</tr>

<tr>
<td>Initialize Vertex</td>
<td><tt>vis.initialize_vertex(s, g)</tt></td>
<td><tt>void</tt></td>
<td>
This is invoked on every vertex of the graph before the start of the
graph search.
</td>
</tr>

<tr>
<td>Discover Vertex</td>
<td><tt>vis.discover_vertex(u, g)</tt></td>
<td><tt>void</tt></td>
<td>
This is invoked when a vertex is encountered for the first time.
</td>
</tr>

<tr>
<td>Examine Vertex</td>
<td><tt>vis.examine_vertex(u, g)</tt></td>
<td><tt>void</tt></td>
<td>
This is invoked on a vertex as it is popped from the queue. This
happens immediately before <tt>examine_edge()</tt> is invoked
on each of the out-edges of vertex <tt>u</tt>.
</td>
</tr>

<tr>
<td>Examine Edge</td>
<td><tt>vis.examine_edge(e, g)</tt></td>
<td><tt>void</tt></td>
<td>
This is invoked on every out-edge of each vertex after it is discovered.
</td>
</tr>


<tr>
<td>Tree Edge</td>
<td><tt>vis.tree_edge(e, g)</tt></td>
<td><tt>void</tt></td>
<td>
This is invoked on each edge as it becomes a member of the edges that
form the search tree.</td>
</tr>

<tr>
<td>Non-Tree Edge</td>
<td><tt>vis.non_tree_edge(e, g)</tt></td>
<td><tt>void</tt></td>
<td>
This is invoked on back or cross edges for directed graphs and cross
edges for undirected graphs.
</td>
</tr>

<tr>
<td>Gray Target</td>
<td><tt>vis.gray_target(e, g)</tt></td>
<td><tt>void</tt></td>
<td>
This is invoked on the subset of non-tree edges whose target vertex is
colored gray at the time of examination. The color gray indicates
that the vertex is currently in the queue. 
</td>
</tr>

<tr>
<td>Black Target</td>
<td><tt>vis.black_target(e, g)</tt></td>
<td><tt>void</tt></td>
<td>
This is invoked on the subset of non-tree edges whose target vertex is
colored black at the time of examination. The color black indicates
that the vertex has been removed from the queue.
</td>
</tr>

<tr>
<td>Finish Vertex</td>
<td><tt>vis.finish_vertex(u, g)</tt></td>
<td><tt>void</tt></td>
<td>
This 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 the out-edges of the adjacent vertices have been examined).
</td>
</tr>

</table>

<h3>Models</h3>

<ul>
 <li><a href="./bfs_visitor.html"><tt>bfs_visitor</tt></a>
</ul>

<a name="python"></a><h3>Python</h3>
To implement a model of the <tt>BFSVisitor</tt> concept in Python,
create a new class that derives from the <tt>BFSVisitor</tt> type of
the graph, which will be
named <tt><i>GraphType</i>.BFSVisitor</tt>. The events and syntax are
the same as with visitors in C++. Here is an example for the
Python <tt>bgl.Graph</tt> graph type:

<pre>
class count_tree_edges_bfs_visitor(bgl.Graph.BFSVisitor):
  def __init__(self, name_map):
    bgl.Graph.BFSVisitor.__init__(self)
    self.name_map = name_map

  def tree_edge(self, e, g):
    (u, v) = (g.source(e), g.target(e))
    print "Tree edge ",
    print self.name_map[u],
    print " -> ",
    print self.name_map[v]
</pre>

<h3>See also</h3>

<a href="./visitor_concepts.html">Visitor concepts</a>

<br>
<HR>
<TABLE>
<TR valign=top>
<TD nowrap>Copyright &copy; 2000-2001</TD><TD>
<A HREF="http://www.boost.org/people/jeremy_siek.htm">Jeremy Siek</A>,
Indiana University (<A
HREF="mailto:jsiek@osl.iu.edu">jsiek@osl.iu.edu</A>)<br>
<A HREF="http://www.boost.org/people/liequan_lee.htm">Lie-Quan Lee</A>, Indiana University (<A HREF="mailto:llee@cs.indiana.edu">llee@cs.indiana.edu</A>)<br>
<A HREF="http://www.osl.iu.edu/~lums">Andrew Lumsdaine</A>,
Indiana University (<A
HREF="mailto:lums@osl.iu.edu">lums@osl.iu.edu</A>)
</TD></TR></TABLE>

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