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<Title>Boost Graph Library: Cuthill-Mckee Ordering</Title>
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<TT>cuthill_mckee_ordering</TT>
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<P>
<DIV ALIGN="LEFT">
<TABLE CELLPADDING=3 border>
<TR><TH ALIGN="LEFT"><B>Graphs:</B></TH>
<TD ALIGN="LEFT">undirected</TD>
</TR>
<TR><TH ALIGN="LEFT"><B>Properties:</B></TH>
<TD ALIGN="LEFT">color, degree</TD>
</TR>
<TR><TH ALIGN="LEFT"><B>Complexity:</B></TH>
<TD ALIGN="LEFT">time: <i>O(m log(m)|V|)</i> where <i>m = max { degree(v) | v in V }</i> </TD>
</TR>
</TABLE>
</DIV>
<pre>
(1)
template <class IncidenceGraph, class OutputIterator,
class ColorMap, class DegreeMap>
OutputIterator
cuthill_mckee_ordering(const IncidenceGraph& g,
typename graph_traits<IncidenceGraph>::vertex_descriptor s,
OutputIterator inverse_permutation,
ColorMap color, DegreeMap degree)
(2)
template <class VertexListGraph, class OutputIterator>
OutputIterator
cuthill_mckee_ordering(const VertexListGraph& g, OutputIterator inverse_permutation);
template <class VertexListGraph, class OutputIterator, class VertexIndexMap>
OutputIterator
cuthill_mckee_ordering(const VertexListGraph& g, OutputIterator inverse_permutation,
VertexIndexMap index_map);
template <class VertexListGraph, class OutputIterator,
class ColorMap, class DegreeMap>
OutputIterator
cuthill_mckee_ordering(const VertexListGraph& g, OutputIterator inverse_permutation,
ColorMap color, DegreeMap degree)
(3)
template <class IncidenceGraph, class OutputIterator,
class ColorMap, class DegreeMap>
OutputIterator
cuthill_mckee_ordering(const IncidenceGraph& g,
std::deque< typename
graph_traits<IncidenceGraph>::vertex_descriptor > vertex_queue,
OutputIterator inverse_permutation,
ColorMap color, DegreeMap degree)
</pre>
The goal of the Cuthill-Mckee (and reverse Cuthill-Mckee) ordering
algorithm[<A
HREF="bibliography.html#george81:__sparse_pos_def">14</A>, <A
HREF="bibliography.html#cuthill69:reducing_bandwith">43</A>, <a
href="bibliography.html#liu75:anal_cm_rcm">44</a>, <a
href="bibliography.html#george71:fem">45</a> ] is to reduce the <a
href="./bandwidth.html">bandwidth</a> of a graph by reordering the
indices assigned to each vertex. The Cuthill-Mckee ordering algorithm
works by a local minimization of the i-th bandwidths. The vertices are
basically assigned a breadth-first search order, except that at each
step, the adjacent vertices are placed in the queue in order of
increasing degree.
<p>
Version 1 of the algorithm lets the user choose the ``starting
vertex'', version 2 finds a good starting vertex using the
pseudo-peripheral pair heuristic (among each component), while version 3
contains the starting nodes for each vertex in the deque. The choice of the
``starting vertex'' can have a significant effect on the quality of the
ordering. For versions 2 and 3, <tt>find_starting_vertex</tt> will be called
for each component in the graph, increasing run time significantly.
</p>
<p>
The output of the algorithm are the vertices in the new ordering.
Depending on what kind of output iterator you use, you can get either
the Cuthill-Mckee ordering or the reverse Cuthill-McKee ordering. For
example, if you store the output into a vector using the vector's
reverse iterator, then you get the reverse Cuthill-McKee ordering.
</p>
<pre>
std::vector<vertex_descriptor> inv_perm(num_vertices(G));
cuthill_mckee_ordering(G, inv_perm.rbegin(), ...);
</pre>
<p>
Either way, storing the output into a vector gives you the
permutation from the new ordering to the old ordering.
</p>
<pre>
inv_perm[new_index[u]] == u
</pre>
<p>
Often times, it is the opposite permutation that you want, the
permutation from the old index to the new index. This can easily be
computed in the following way.
</p>
<pre>
for (size_type i = 0; i != inv_perm.size(); ++i)
perm[old_index[inv_perm[i]]] = i;
</pre>
<h3>Parameters</h3>
For version 1:
<ul>
<li> <tt>IncidenceGraph& g</tt> (IN) <br>
An undirected graph. The graph's type must be a model of <a
href="./IncidenceGraph.html">IncidenceGraph</a>.<br>
<b>Python</b>: The parameter is named <tt>graph</tt>.
<li> <tt>vertex_descriptor s</tt>  (IN) <br>
The starting vertex.<br>
<b>Python</b>: Unsupported parameter.
<li> <tt>OutputIterator inverse_permutation</tt>  (OUT) <br>
The new vertex ordering. The vertices are written to the <a
href="http://www.sgi.com/tech/stl/OutputIterator.html">output
iterator</a> in their new order.<br>
<b>Python</b>: This parameter is unused in Python. The new vertex
ordering is returned as a Python <tt>list</tt>.
<li> <tt>ColorMap color_map</tt>  (WORK) <br>
Used internally to keep track of the progress of the algorithm
(to avoid visiting the same vertex twice).<br>
<b>Python</b>: Unsupported parameter.
<li> <tt>DegreeMap degree_map</tt>  (IN) <br>
This must map vertices to their degree.<br>
<b>Python</b>: Unsupported parameter.
</ul>
For version 2:
<ul>
<li> <tt>VertexListGraph& g</tt> (IN) <br>
An undirected graph. The graph's type must be a model of <a
href="./VertexListGraph.html">VertexListGraph</a> and <a href="./IncidenceGraph.html">IncidenceGraph</a>.<br>
<b>Python</b>: The parameter is named <tt>graph</tt>.
<li> <tt><a href="http://www.sgi.com/tech/stl/OutputIterator.html">
OutputIterator</a> inverse_permutation</tt>  (OUT) <br>
The new vertex ordering. The vertices are written to the
output iterator in their new order.<br>
<b>Python</b>: This parameter is unused in Python. The new vertex
ordering is returned as a Python <tt>list</tt>.
<li> <tt>ColorMap color_map</tt>  (WORK) <br>
Used internally to keep track of the progress of the algorithm
(to avoid visiting the same vertex twice).<br>
<b>Python</b>: Unsupported parameter.
<li> <tt>DegreeMap degree_map</tt>  (IN) <br>
This must map vertices to their degree.<br>
<b>Python</b>: Unsupported parameter.
</ul>
For version 3:
<ul>
<li> <tt>IncidenceGraph& g</tt> (IN) <br>
An undirected graph. The graph's type must be a model of <a
href="./IncidenceGraph.html">IncidenceGraph</a>.<br>
<b>Python</b>: The parameter is named <tt>graph</tt>.
<li> <tt> std::deque< typename graph_traits<Graph>::vertex_descriptor > vertex_queue </tt>  (IN) <br>
The deque containing the starting vertices for each component.<br>
<b>Python</b>: Unsupported parameter.
<li> <tt>OutputIterator inverse_permutation</tt>  (OUT) <br>
The new vertex ordering. The vertices are written to the <a
href="http://www.sgi.com/tech/stl/OutputIterator.html">output
iterator</a> in their new order.<br>
<b>Python</b>: This parameter is unused in Python. The new vertex
ordering is returned as a Python <tt>list</tt>.
<li> <tt>ColorMap color_map</tt>  (WORK) <br>
Used internally to keep track of the progress of the algorithm
(to avoid visiting the same vertex twice).<br>
<b>Python</b>: Unsupported parameter.
<li> <tt>DegreeMap degree_map</tt>  (IN) <br>
This must map vertices to their degree.<br>
<b>Python</b>: Unsupported parameter.
</ul>
<h3>Example</h3>
See <a
href="../example/cuthill_mckee_ordering.cpp"><tt>example/cuthill_mckee_ordering.cpp</tt></a>.
<h3>See Also</h3>
<a href="./bandwidth.html">bandwidth</tt></a>,
and <tt>degree_property_map</tt> in <tt>boost/graph/properties.hpp</tt>.
<br>
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<TD nowrap>Copyright © 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>)
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