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<Head>
<Title>Boost Graph Library: Bellman Ford Visitor</Title>
<BODY BGCOLOR="#ffffff" LINK="#0000ee" TEXT="#000000" VLINK="#551a8b" 
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<IMG SRC="../../../boost.png" 
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<BR Clear>

<H1><img src="figs/python.gif" alt="(Python)"/>Bellman Ford Visitor Concept</H1>

This concept defines the visitor interface for <a
href="./bellman_ford_shortest.html"><tt>bellman_ford_shortest_paths()</tt></a>.
Users can define a class with the Bellman Ford Visitor interface and
pass and object of the class to <tt>bellman_ford_shortest_paths()</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 Bellman Ford 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>Examine Edge</td>
<td><tt>vis.examine_edge(e, g)</tt></td>
<td><tt>void</tt></td>
<td>
This is invoked on every edge in the graph <tt>num_vertices(g)</tt> times.
</td>
</tr>


<tr>
<td>Edge Relaxed</td>
<td><tt>vis.edge_relaxed(e, g)</tt></td>
<td><tt>void</tt></td>
<td>
Upon examination, if the following condition holds then the edge
is relaxed (its distance is reduced), and this method is invoked.<br>
<tt>
tie(u,v) = incident(e, g);<br>
D d_u = get(d, u), d_v = get(d, v);<br>
W w_e = get(w, e);<br>
assert(compare(combine(d_u, w_e), d_v));<br>
</tt>
</td>
</tr>

<tr>
<td>Edge Not Relaxed</td>
<td><tt>edge_not_relaxed(e, g)</tt></td>
<td><tt>void</tt></td>
<td>
Upon examination, if the edge is not relaxed (see above) then
this method is invoked.
</td>
</tr>

<tr>
<td>Edge Minimized</td>
<td><tt>vis.edge_minimized(e, g)</tt></td>
<td><tt>void</tt></td>
<td>
After <tt>num_vertices(g)</tt> iterations through the edge set
of the graph are completed, one last iteration is made to test whether
each edge was minimized. If the edge is minimized then this function
is invoked.
</td>
</tr>

<tr>
<td>Edge Not Minimized</td>
<td><tt>edge_not_minimized(e, g)</tt></td>
<td><tt>void</tt></td>
<td>
If the edge is not minimized, this function is invoked. This happens
when there is a negative cycle in the graph.
</td>
</tr>

</table>


<h3>Models</h3>

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

<a name="python"></a>
<h3>Python</h3>

To implement a model of the <tt>BellmanFordVisitor</tt> concept in Python,
create a new class that derives from the <tt>BellmanFordVisitor</tt> type of
the graph, which will be
named <tt><i>GraphType</i>.BellmanFordVisitor</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_bellman_ford_visitor(bgl.Graph.BellmanFordVisitor):
  def __init__(self, name_map):
    bgl.Graph.BellmanFordVisitor.__init__(self)
    self.name_map = name_map

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

<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="https://homes.cs.washington.edu/~al75">Andrew Lumsdaine</A>,
Indiana University (<A
HREF="mailto:lums@osl.iu.edu">lums@osl.iu.edu</A>)
</TD></TR></TABLE>

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