222 lines
5.5 KiB
HTML
222 lines
5.5 KiB
HTML
<HTML>
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<!--
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Copyright (c) Jeremy Siek, Lie-Quan Lee, and Andrew Lumsdaine 2000
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Distributed under the Boost Software License, Version 1.0.
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(See accompanying file LICENSE_1_0.txt or copy at
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http://www.boost.org/LICENSE_1_0.txt)
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-->
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<Head>
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<Title>DFS Visitor</Title>
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<BODY BGCOLOR="#ffffff" LINK="#0000ee" TEXT="#000000" VLINK="#551a8b"
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ALINK="#ff0000">
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<IMG SRC="../../../boost.png"
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ALT="C++ Boost" width="277" height="86">
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<BR Clear>
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<H1><img src="figs/python.gif" alt="(Python)"/>DFS Visitor Concept</H1>
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This concept defines the visitor interface for <a
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href="./depth_first_search.html"><tt>depth_first_search()</tt></a>.
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Users can define a class with the DFS Visitor interface and pass an
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object of the class to <tt>depth_first_search()</tt>, thereby
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augmenting the actions taken during the graph search.
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<h3>Refinement of</h3>
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<a href="../../utility/CopyConstructible.html">Copy Constructible</a>
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(copying a visitor should be a lightweight operation).
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<h3>Notation</h3>
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<Table>
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<TR>
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<TD><tt>V</tt></TD>
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<TD>A type that is a model of DFS Visitor.</TD>
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</TR>
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<TR>
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<TD><tt>vis</tt></TD>
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<TD>An object of type <tt>V</tt>.</TD>
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</TR>
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<TR>
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<TD><tt>G</tt></TD>
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<TD>A type that is a model of Graph.</TD>
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</TR>
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<TR>
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<TD><tt>g</tt></TD>
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<TD>An object of type <tt>G</tt>.</TD>
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</TR>
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<TR>
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<TD><tt>e</tt></TD>
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<TD>An object of type <tt>boost::graph_traits<G>::edge_descriptor</tt>.</TD>
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</TR>
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<TR>
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<TD><tt>s,u</tt></TD>
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<TD>An object of type <tt>boost::graph_traits<G>::vertex_descriptor</tt>.</TD>
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</TR>
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</table>
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<h3>Associated Types</h3>
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none
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<p>
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<h3>Valid Expressions</h3>
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<table border>
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<tr>
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<th>Name</th><th>Expression</th><th>Return Type</th><th>Description</th>
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</tr>
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<tr>
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<td>Initialize Vertex</td>
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<td><tt>vis.initialize_vertex(s, g)</tt></td>
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<td><tt>void</tt></td>
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<td>
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This is invoked on every vertex of the graph before the start of the
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graph search.
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</td>
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</tr>
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<tr>
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<td>Start Vertex</td>
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<td><tt>vis.start_vertex(s, g)</tt></td>
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<td><tt>void</tt></td>
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<td>
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This is invoked on the source vertex once before the start of the
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search.
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</td>
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</tr>
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<tr>
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<td>Discover Vertex</td>
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<td><tt>vis.discover_vertex(u, g)</tt></td>
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<td><tt>void</tt></td>
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<td>
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This is invoked when a vertex is encountered for the first time.
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</td>
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</tr>
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<tr>
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<td>Examine Edge</td>
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<td><tt>vis.examine_edge(e, g)</tt></td>
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<td><tt>void</tt></td>
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<td>
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This is invoked on every out-edge of each vertex after it is discovered.
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</td>
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</tr>
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<tr>
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<td>Tree Edge</td>
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<td><tt>vis.tree_edge(e, g)</tt></td>
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<td><tt>void</tt></td>
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<td>
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This is invoked on each edge as it becomes a member of the edges that
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form the search tree.</td>
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</tr>
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<tr>
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<td>Back Edge</td>
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<td><tt>vis.back_edge(e, g)</tt></td>
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<td><tt>void</tt></td>
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<td>
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This is invoked on the back edges in the graph. For an undirected
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graph there is some ambiguity between tree edges and back edges since
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the edge <i>(u,v)</i> and <i>(v,u)</i> are the same edge, but both the
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<tt>tree_edge()</tt> and <tt>back_edge()</tt> functions will be
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invoked. One way to resolve this ambiguity is to record the tree
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edges, and then disregard the back-edges that are already marked as
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tree edges. An easy way to record tree edges is to record
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predecessors at the <tt>tree_edge</tt> event point.
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</td>
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</tr>
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<tr>
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<td>Forward or Cross Edge</td>
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<td><tt>vis.forward_or_cross_edge(e, g)</tt></td>
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<td><tt>void</tt></td>
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<td>
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This is invoked on forward or cross edges in the graph. In an
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undirected graph this method is never called.
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</td>
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</tr>
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<tr>
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<td>Finish Edge</td>
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<td><tt>vis.finish_edge(e, g)</tt></td>
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<td><tt>void</tt></td>
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<td>
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This is invoked on each non-tree edge as well as on each tree edge after
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<tt>finish_vertex</tt> has been called on its target vertex.</td>
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</tr>
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<tr>
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<td>Finish Vertex</td>
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<td><tt>vis.finish_vertex(u, g)</tt></td>
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<td><tt>void</tt></td>
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<td>
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This is invoked on vertex <tt>u</tt> after <tt>finish_vertex</tt> has
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been called for all the vertices in the DFS-tree rooted at vertex
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<tt>u</tt>. If vertex <tt>u</tt> is a leaf in the DFS-tree, then
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the <tt>finish_vertex</tt> function is called on <tt>u</tt> after
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all the out-edges of <tt>u</tt> have been examined.
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</td>
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</tr>
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</table>
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<h3>Models</h3>
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<ul>
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<li><a href="./dfs_visitor.html"><tt>dfs_visitor</tt></a>
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</ul>
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<a name="python"></a>
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<h3>Python</h3>
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To implement a model of the <tt>DFSVisitor</tt> concept in Python,
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create a new class that derives from the <tt>DFSVisitor</tt> type of
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the graph, which will be
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named <tt><i>GraphType</i>.DFSVisitor</tt>. The events and syntax are
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the same as with visitors in C++. Here is an example for the
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Python <tt>bgl.Graph</tt> graph type:
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<pre>
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class count_tree_edges_dfs_visitor(bgl.Graph.DFSVisitor):
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def __init__(self, name_map):
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bgl.Graph.DFSVisitor.__init__(self)
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self.name_map = name_map
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def tree_edge(self, e, g):
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(u, v) = (g.source(e), g.target(e))
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print "Tree edge ",
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print self.name_map[u],
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print " -> ",
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print self.name_map[v]
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</pre>
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<br>
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<HR>
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<TABLE>
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<TR valign=top>
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<TD nowrap>Copyright © 2000-2001</TD><TD>
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<A HREF="http://www.boost.org/people/jeremy_siek.htm">Jeremy Siek</A>,
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Indiana University (<A
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HREF="mailto:jsiek@osl.iu.edu">jsiek@osl.iu.edu</A>)<br>
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<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>
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<A HREF="https://homes.cs.washington.edu/~al75">Andrew Lumsdaine</A>,
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Indiana University (<A
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HREF="mailto:lums@osl.iu.edu">lums@osl.iu.edu</A>)
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</TD></TR></TABLE>
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</BODY>
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</HTML>
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