ceph/src/boost/libs/graph/doc/DFSVisitor.html

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   9 <Head>
  10 <Title>DFS Visitor</Title>
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  17
  18 <H1><img src="figs/python.gif" alt="(Python)"/>DFS Visitor Concept</H1>
  19
  20 This concept defines the visitor interface for <a
  21 href="./depth_first_search.html"><tt>depth_first_search()</tt></a>.
  22 Users can define a class with the DFS Visitor interface and pass an
  23 object of the class to <tt>depth_first_search()</tt>, thereby
  24 augmenting the actions taken during the graph search.
  25
  26 <h3>Refinement of</h3>
  27
  28 <a href="../../utility/CopyConstructible.html">Copy Constructible</a>
  29 (copying a visitor should be a lightweight operation).
  30
  31 <h3>Notation</h3>
  32
  33 <Table>
  34 <TR>
  35 <TD><tt>V</tt></TD>
  36 <TD>A type that is a model of DFS Visitor.</TD>
  37 </TR>
  38
  39 <TR>
  40 <TD><tt>vis</tt></TD>
  41 <TD>An object of type <tt>V</tt>.</TD>
  42 </TR>
  43
  44 <TR>
  45 <TD><tt>G</tt></TD>
  46 <TD>A type that is a model of Graph.</TD>
  47 </TR>
  48
  49 <TR>
  50 <TD><tt>g</tt></TD>
  51 <TD>An object of type <tt>G</tt>.</TD>
  52 </TR>
  53
  54 <TR>
  55 <TD><tt>e</tt></TD>
  56 <TD>An object of type <tt>boost::graph_traits&lt;G&gt;::edge_descriptor</tt>.</TD>
  57 </TR>
  58
  59 <TR>
  60 <TD><tt>s,u</tt></TD>
  61 <TD>An object of type <tt>boost::graph_traits&lt;G&gt;::vertex_descriptor</tt>.</TD>
  62 </TR>
  63
  64 </table>
  65
  66 <h3>Associated Types</h3>
  67
  68 none
  69 <p>
  70
  71 <h3>Valid Expressions</h3>
  72
  73 <table border>
  74 <tr>
  75 <th>Name</th><th>Expression</th><th>Return Type</th><th>Description</th>
  76 </tr>
  77
  78 <tr>
  79 <td>Initialize Vertex</td>
  80 <td><tt>vis.initialize_vertex(s, g)</tt></td>
  81 <td><tt>void</tt></td>
  82 <td>
  83 This is invoked on every vertex of the graph before the start of the
  84 graph search.
  85 </td>
  86 </tr>
  87
  88 <tr>
  89 <td>Start Vertex</td>
  90 <td><tt>vis.start_vertex(s, g)</tt></td>
  91 <td><tt>void</tt></td>
  92 <td>
  93 This is invoked on the source vertex once before the start of the
  94 search.
  95 </td>
  96 </tr>
  97
  98 <tr>
  99 <td>Discover Vertex</td>
 100 <td><tt>vis.discover_vertex(u, g)</tt></td>
 101 <td><tt>void</tt></td>
 102 <td>
 103 This is invoked when a vertex is encountered for the first time.
 104 </td>
 105 </tr>
 106
 107 <tr>
 108 <td>Examine Edge</td>
 109 <td><tt>vis.examine_edge(e, g)</tt></td>
 110 <td><tt>void</tt></td>
 111 <td>
 112 This is invoked on every out-edge of each vertex after it is discovered.
 113 </td>
 114 </tr>
 115
 116
 117 <tr>
 118 <td>Tree Edge</td>
 119 <td><tt>vis.tree_edge(e, g)</tt></td>
 120 <td><tt>void</tt></td>
 121 <td>
 122 This is invoked on each edge as it becomes a member of the edges that
 123 form the search tree.</td>
 124 </tr>
 125
 126 <tr>
 127 <td>Back Edge</td>
 128 <td><tt>vis.back_edge(e, g)</tt></td>
 129 <td><tt>void</tt></td>
 130 <td>
 131 This is invoked on the back edges in the graph.  For an undirected
 132 graph there is some ambiguity between tree edges and back edges since
 133 the edge <i>(u,v)</i> and <i>(v,u)</i> are the same edge, but both the
 134 <tt>tree_edge()</tt> and <tt>back_edge()</tt> functions will be
 135 invoked. One way to resolve this ambiguity is to record the tree
 136 edges, and then disregard the back-edges that are already marked as
 137 tree edges.  An easy way to record tree edges is to record
 138 predecessors at the <tt>tree_edge</tt> event point.
 139 </td>
 140 </tr>
 141
 142 <tr>
 143 <td>Forward or Cross Edge</td>
 144 <td><tt>vis.forward_or_cross_edge(e, g)</tt></td>
 145 <td><tt>void</tt></td>
 146 <td>
 147 This is invoked on forward or cross edges in the graph. In an
 148 undirected graph this method is never called.
 149 </td>
 150 </tr>
 151
 152 <tr>
 153 <td>Finish Edge</td>
 154 <td><tt>vis.finish_edge(e, g)</tt></td>
 155 <td><tt>void</tt></td>
 156 <td>
 157 This is invoked on each non-tree edge as well as on each tree edge after
 158 <tt>finish_vertex</tt> has been called on its target vertex.</td>
 159 </tr>
 160
 161 <tr>
 162 <td>Finish Vertex</td>
 163 <td><tt>vis.finish_vertex(u, g)</tt></td>
 164 <td><tt>void</tt></td>
 165 <td>
 166 This is invoked on vertex <tt>u</tt> after <tt>finish_vertex</tt> has
 167 been called for all the vertices in the DFS-tree rooted at vertex
 168 <tt>u</tt>. If vertex <tt>u</tt> is a leaf in the DFS-tree, then
 169 the <tt>finish_vertex</tt> function is called on <tt>u</tt> after
 170 all the out-edges of <tt>u</tt> have been examined.
 171 </td>
 172 </tr>
 173
 174 </table>
 175
 176 <h3>Models</h3>
 177
 178 <ul>
 179  <li><a href="./dfs_visitor.html"><tt>dfs_visitor</tt></a>
 180 </ul>
 181
 182 <a name="python"></a>
 183 <h3>Python</h3>
 184
 185 To implement a model of the <tt>DFSVisitor</tt> concept in Python,
 186 create a new class that derives from the <tt>DFSVisitor</tt> type of
 187 the graph, which will be
 188 named <tt><i>GraphType</i>.DFSVisitor</tt>. The events and syntax are
 189 the same as with visitors in C++. Here is an example for the
 190 Python <tt>bgl.Graph</tt> graph type:
 191
 192 <pre>
 193 class count_tree_edges_dfs_visitor(bgl.Graph.DFSVisitor):
 194   def __init__(self, name_map):
 195     bgl.Graph.DFSVisitor.__init__(self)
 196     self.name_map = name_map
 197
 198   def tree_edge(self, e, g):
 199     (u, v) = (g.source(e), g.target(e))
 200     print "Tree edge ",
 201     print self.name_map[u],
 202     print " -> ",
 203     print self.name_map[v]
 204 </pre>
 205
 206 <br>
 207 <HR>
 208 <TABLE>
 209 <TR valign=top>
 210 <TD nowrap>Copyright &copy; 2000-2001</TD><TD>
 211 <A HREF="http://www.boost.org/people/jeremy_siek.htm">Jeremy Siek</A>,
 212 Indiana University (<A
 213 HREF="mailto:jsiek@osl.iu.edu">jsiek@osl.iu.edu</A>)<br>
 214 <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>
 215 <A HREF="http://www.osl.iu.edu/~lums">Andrew Lumsdaine</A>,
 216 Indiana University (<A
 217 HREF="mailto:lums@osl.iu.edu">lums@osl.iu.edu</A>)
 218 </TD></TR></TABLE>
 219
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