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15 <H1><A name=sec:bfs></a><tt>sloan_ordering</tt></H1>
16 <P>
17 <DIV align=left>
18 <TABLE cellPadding=3 border=1>
19 <TBODY>
20 <TR>
21 <TH align=left><B>Graphs:</B></TH>
22 <TD align=left>undirected</TD></TR>
23 <TR>
24 <TH align=left><B>Properties:</B></TH>
25 <TD align=left>color, degree, current_degree, priority</TD>
26 </TR>
27 <TR>
28 <TH align=left><B>Complexity:</B></TH>
29 <TD align=left>time: <I>O(log(m)|E|)</I> where <I>m = max { degree(v) | v
30 in V }</I> </TD></TR></TBODY></TABLE></DIV>
31 <PRE> (1)
32 template &lt;class Graph, class OutputIterator,
33 class ColorMap, class DegreeMap,
34 class PriorityMap, class Weight&gt;
35 OutputIterator
36 sloan_ordering(Graph&amp; g,
37 typename graph_traits&lt;Graph&gt;::vertex_descriptor s,
38 typename graph_traits&lt;Graph&gt;::vertex_descriptor e,
39 OutputIterator permutation,
40 ColorMap color,
41 DegreeMap degree,
42 PriorityMap priority,
43 Weight W1,
44 Weight W2 )
45
46 (2)
47 template &lt;class Graph, class OutputIterator,
48 class ColorMap, class DegreeMap,
49 class PriorityMap, class Weight&gt;
50 OutputIterator
51 sloan_ordering(Graph&amp; g,
52 OutputIterator permutation,
53 ColorMap color,
54 DegreeMap degree,
55 PriorityMap priority,
56 Weight W1,
57 Weight W2 )
58
59
60 (3)
61 template &lt;class Graph, class OutputIterator,
62 class ColorMap, class DegreeMap,
63 class PriorityMap&gt;
64 OutputIterator
65 sloan_ordering(Graph&amp; g,
66 typename graph_traits&lt;Graph&gt;::vertex_descriptor s,
67 typename graph_traits&lt;Graph&gt;::vertex_descriptor e,
68 OutputIterator permutation,
69 ColorMap color,
70 DegreeMap degree,
71 PriorityMap priority )
72
73
74 (4)
75 template &lt;class Graph, class OutputIterator,
76 class ColorMap, class DegreeMap,
77 class PriorityMap&gt;
78 OutputIterator
79 sloan_ordering(Graph&amp; g,
80 OutputIterator permutation,
81 ColorMap color,
82 DegreeMap degree,
83 PriorityMap priority )</PRE>
84 <p>The goal of the Sloan ordering algorithm[1, 2] is to reduce the profile and
85 the wavefront of a graph by reordering the indices assigned to each vertex.
86 The Sloan algorithm needs a start and an end vertex. These vertices can be asigned
87 manually. But there is also an algorithm sloan_starting_nodes that provides
88 usually quite good start and end vertices. Each vertex is asigned with a priority.
89 This priority is a weighted sum of the distance of the vector to the end vertex
90 (a global criterion) and is called the current degree of vertex. This current
91 degree basically reflects the status of the renumbering in the neighborhood
92 of a vertex (a local criterion). Therefore the Sloan algorithm (in contrast
93 to-McKee) takes into account local as well as global criteria for the renumbering
94 sequence. One can play around with the relative weights, but the default values
95 proposed by Sloan (weight1/weight2=1/2) turn out to be pretty good in most cases.
96 </p>
97 <P>Version 1 of the algorithm lets the user choose the start- and end-vertex whereas
98 version 2 finds a good starting vertex using the already mentioned sloan_starting_node
99 algorithm. The choice of these vertices can have a significant effect on the
100 quality of the ordering. Version 3 and 4 are identical to version 1 and 2 respectively,
101 except that for the weights the standard weights W1=1 and W2=2 are used.
102 <P>The output of the algorithm are the vertices in the new ordering. Depending
103 on what kind of output iterator you use, you can get either the Sloan ordering
104 or the reverse Sloan ordering. For example, if you store the output into a vector
105 using the vector's reverse iterator, then you get the reverse Sloan ordering.
106 <PRE> std::vector&lt;vertex_descriptor&gt; inv_perm(num_vertices(G));
107 sloan_ordering(G, inv_perm.rbegin());
108 </PRE>
109 <P>Either way, storing the output into a vector gives you the permutation from
110 the new ordering to the old ordering. <PRE> inv_perm[new_index[u]] == u
111 </PRE>
112 <P>Sometimes, it is the opposite permutation that you want, the permutation from
113 the old index to the new index. This can easily be computed in the following
114 way.
115 <PRE> for (size_type i = 0; i != inv_perm.size(); ++i)
116 perm[old_index[inv_perm[i]]] = i;
117 </PRE>
118 <p>Usually you need the reversed ordering with the Cuthill-McKee algorithm and
119 the direct ordering with the Sloan algorithm.</p>
120 <H3>Parameters</H3>
121 For version 1:
122 <UL>
123 <LI><TT>Graph&amp; g</TT> &nbsp;(IN) <BR>
124 An undirected graph. The graph's type must be a model of <A
125 href="./IncidenceGraph.html">IncidenceGraph</a>.
126 <LI><TT>vertex_descriptor s</TT> &nbsp;(IN) <BR>
127 The starting vertex.
128 <LI><tt>vertex_descriptor e</tt>&nbsp;(IN)<br>
129 The ending vertex<br>
130 <LI><TT>OutputIterator permutation</TT> &nbsp;(OUT) <BR>
131 The new vertex ordering. The vertices are written to the <a
132 href="http://www.sgi.com/tech/stl/OutputIterator.html">output iterator</a> in
133 their new order.
134 <LI><TT>ColorMap color_map</TT> &nbsp;(WORK) <BR>
135 Used internally to keep track of the progress of the algorithm (to avoid visiting
136 the same vertex twice).
137 <LI><tt>PriorityMap priority_map</tt> &nbsp;(IN)<br>
138 Used internally to store the priority for renumbering of each vertex. </LI>
139 <LI><TT>DegreeMap degree_map</TT> &nbsp;(IN) <BR>
140 This must map vertices to their degree. </LI>
141 <LI><tt>Weight W1 &amp; W2</tt> &nbsp;(IN) <br>
142 Heuristical weights for the Sloan algorithm. </LI>
143 </UL>
144 <p>For version 2: </p>
145 <ul>
146 <li><tt>Graph&amp; g</tt> &nbsp;(IN) <br>
147 An undirected graph. The graph's type must be a model of <a
148 href="./IncidenceGraph.html">IncidenceGraph</a>.<br>
149 <li><tt>OutputIterator permutation</tt> &nbsp;(OUT) <br>
150 The new vertex ordering. The vertices are written to the <a
151 href="http://www.sgi.com/tech/stl/OutputIterator.html">output iterator</a> in
152 their new order.
153 <li><tt>ColorMap color_map</tt> &nbsp;(WORK) <br>
154 Used internally to keep track of the progress of the algorithm (to avoid visiting
155 the same vertex twice).
156 <li><tt>PriorityMap priority_map</tt> &nbsp;(IN)<br>
157 Used internally to store the priority for renumbering of each vertex. </li>
158 <li><tt>DegreeMap degree_map</tt> &nbsp;(IN) <br>
159 This must map vertices to their degree. </li>
160 <li><tt>Weight W1 &amp; W2</tt> &nbsp;(IN) <br>
161 Heuristical weights for the Sloan algorithm. </li>
162 </ul>
163 <p>For version 3: </p>
164 <ul>
165 <li><tt>Graph&amp; g</tt> &nbsp;(IN) <br>
166 An undirected graph. The graph's type must be a model of <a
167 href="./IncidenceGraph.html">IncidenceGraph</a>.
168 <li><tt>vertex_descriptor s</tt> &nbsp;(IN) <br>
169 The starting vertex.
170 <li><tt>vertex_descriptor e</tt>&nbsp;(IN)<br>
171 The ending vertex<br>
172 <li><tt>OutputIterator permutation</tt> &nbsp;(OUT) <br>
173 The new vertex ordering. The vertices are written to the <a
174 href="http://www.sgi.com/tech/stl/OutputIterator.html">output iterator</a> in
175 their new order.
176 <li><tt>ColorMap color_map</tt> &nbsp;(WORK) <br>
177 Used internally to keep track of the progress of the algorithm (to avoid visiting
178 the same vertex twice).
179 <li><tt>PriorityMap priority_map</tt> &nbsp;(IN)<br>
180 Used internally to store the priority for renumbering of each vertex. </li>
181 <li><tt>DegreeMap degree_map</tt> &nbsp;(IN) <br>
182 This must map vertices to their degree. </li>
183 </ul>
184 <p>For version 4: </p>
185 <ul>
186 <li><tt>Graph&amp; g</tt> &nbsp;(IN) <br>
187 An undirected graph. The graph's type must be a model of <a
188 href="./IncidenceGraph.html">IncidenceGraph</a>.<br>
189 <li><tt>OutputIterator permutation</tt> &nbsp;(OUT) <br>
190 The new vertex ordering. The vertices are written to the <a
191 href="http://www.sgi.com/tech/stl/OutputIterator.html">output iterator</a> in
192 their new order.
193 <li><tt>ColorMap color_map</tt> &nbsp;(WORK) <br>
194 Used internally to keep track of the progress of the algorithm (to avoid visiting
195 the same vertex twice).
196 <li><tt>PriorityMap priority_map</tt> &nbsp;(IN)<br>
197 Used internally to store the priority for renumbering of each vertex. </li>
198 <li><tt>DegreeMap degree_map</tt> &nbsp;(IN) <br>
199 This must map vertices to their degree. </li>
200 </ul>
201 <p>&nbsp;</p>
202 <H3>Example</H3>
203 See <A
204 href="../example/sloan_ordering.cpp"><TT>example/sloan_ordering.cpp</TT></A>.
205 <H3>See Also</H3>
206 <p><a href="./sloan_start_end_vertices.htm">sloan_start_end_vertices</a>,
207 <A
208 href="./bandwidth.html">bandwidth</a>, <a href="./profile.htm">profile</a>, <a href="./wavefront.htm">wavefront</a>
209 and <TT>degree_property_map</TT> in <TT>boost/graph/properties.hpp</TT>. </p>
210 <p>[1] S. W. Sloan, <i>An algorithm for profile and wavefront reduction of sparse
211 matrices</i>, Int. j. numer. methods eng., <b>23</b>, 239 - 251 (1986)</p>
212 <p>[2] S. W. Sloan, <i>A fortran program for profile and wavefront reduction</i>,
213 Int. j. numer. methods eng., <b>28</b>, 2651 - 2679 (1989)<BR>
214 </p>
215 <HR>
216
217 <TABLE width="718">
218 <TBODY>
219 <TR vAlign=top>
220 <TD noWrap>Copyright © 2001-2002</TD>
221 <TD>Marc Wintermantel, ETH Zurich (<A
222 href="mailto:wintermantel@imes.mavt.ethz.ch">wintermantel@imes.mavt.ethz.ch</a>)
223 </TD>
224 </TR></TBODY></TABLE></BODY></HTML>