edits, bib additions

[SVN r7748]

docs/bibliography.html

@@ -218,6 +218,22 @@ Computer Journal, 10:85-86, 1967.
 <EM>New methods to color the vertices of a graph</EM><br>
 Communications of the ACM, vol. 22, 1979, pp. 251-256.
 
+<P></P><DT><A NAME="heber99:_saw">33</a>
+<DD>G. Heber, R. Biswas, G.R. Gao<BR>
+<EM>Self-Avoiding Walks over Adaptive Unstructured Grids</EM><br>
+Parallel and Distributed Processing, LNCS 1586,
+Springer-Verlag, 1999, pp. 968-977
+
+
+<P></P><DT><A NAME="ng-raghavan">34</a>
+<DD>Esmond G. Ng amd Padma Raghavan<BR>
+<EM>Performance of greedy ordering heuristics for sparse {C}holesky factorization</EM><br>
+SIAM Journal on Matrix Analysis and Applications (To appear)
+
+<P></P><DT><A NAME="George:evolution">35</a>
+<DD>Alan George and Joseph W. H. Liu<BR>
+<EM>The Evolution of the Minimum Degree Ordering Algorithm</EM><br>
+SIAM Review, March 1989, vol. 31, num. 1, pp. 1-19.
 
 </DL>
 

docs/distance_recorder.html

@@ -124,7 +124,7 @@ Construct a distance recorder object with distance property accessor
 
 <tr>
 <td><tt>
-template &lt;class Edge, class Graph&gt;
+template &lt;class Edge, class Graph&gt;<br>
 void operator()(Edge e, const Graph& g);
 </tt></td>
 <td>

docs/predecessor_recorder.html

@@ -123,7 +123,7 @@ Construct a predecessor recorder object with predecessor property accessor
 
 <tr>
 <td><tt>
-template &lt;class Edge, class Graph&gt;
+template &lt;class Edge, class Graph&gt;<br>
 void operator()(Edge e, const Graph& g);
 </tt></td>
 <td>

docs/property_writer.html

@@ -145,7 +145,7 @@ Construct a property writer object with the property accessor
 
 <tr>
 <td><tt>
-template &lt;class X, class Graph&gt;
+template &lt;class X, class Graph&gt;<br>
 void operator()(X x, const Graph& g);
 </tt></td>
 <td>

docs/sparse_matrix_ordering.html

@@ -83,15 +83,17 @@ of <i>L</i> that are not present in the non-zero structure of
 <i>A</i>), the ordering has a significant impact on the memory and
 computational requirements for the latter stages.  However, finding
 the optimal ordering for <i>A</i> (in the sense of minimizing fill-in)
-has been proven to be NP-complete&nbsp;[] requiring that heuristics be
-used for all but simple (or specially structured) cases.
+has been proven to be NP-complete&nbsp;[<a
+href="bibliography.html#garey79:computers-and-intractability">30</a>]
+requiring that heuristics be used for all but simple (or specially
+structured) cases.
 
 <P>
 A widely used but rather simple ordering algorithm is a variant of the
 Cuthill-McKee orderings, the reverse Cuthill-McKee ordering algorithm.
 This algorithm can be used as a preordering method to improve ordering
 in more sophisticated methods such as minimum degree
-algorithms&nbsp;[].
+algorithms&nbsp;[<a href="bibliography.html#LIU:MMD">21</a>].
 
 <P>
 
@@ -138,11 +140,17 @@ namespace boost {
   template &lt;class Graph, class Vertex, class Color, class Degree&gt;
   Vertex 
   pseudo_peripheral_pair(Graph& G, const Vertex& u, int& ecc,
-                         Color c, Degree d) {
-    typedef typename detail::property_accessor_adaptor&lt;Degree&gt;
-      ::type DegreeDecorator;
-    rcm_queue&lt;Vertex, DegreeDecorator&gt; Q(d);
-    _breadth_first_search(G, u, Q, null_visitor(), c);
+                         Color color, Degree degree)
+  {
+    typename property_traits&lt;Color&gt;::value_type c = get(color, u);
+
+    rcm_queue&lt;Vertex, Degree&gt; Q(degree);
+    
+    typename boost::graph_traits&lt;Graph&gt;::vertex_iterator ui, ui_end;
+    for (tie(ui, ui_end) = vertices(G); ui != ui_end; ++ui)
+      put(color, *ui, white(c));
+    breadth_first_search(G, u, Q, bfs_visitor&lt;&gt;(), color);
+
     ecc = Q.eccentricity(); 
     return Q.spouse();
   }
@@ -198,19 +206,21 @@ from GGCL can be reused.
   cuthill_mckee_ordering(Graph& G, 
                          Vertex s,
                          OutputIterator inverse_permutation, 
-                         Color c, Degree d)
+                         Color color, Degree degree)
   {
     typedef typename property_traits&lt;Degree&gt;::value_type DS;
+    typename property_traits&lt;Color&gt;::value_type c = get(color, s);
     typedef indirect_cmp&lt;Degree, std::greater&lt;DS&gt; &gt; Compare;
-    Compare comp(d);
+    Compare comp(degree);
     fenced_priority_queue&lt;Vertex, Compare &gt; Q(comp);
 
     typedef cuthill_mckee_visitor&lt;OutputIterator&gt;  CMVisitor;
     CMVisitor cm_visitor(inverse_permutation);
     
-    bfs_visitor&lt;Color, CMVisitor&gt; visitor(c, cm_visitor);
-    initialize_graph(G, visitor);
-    breadth_first_search(G, s, Q, visitor, detail::null_operation() );
+    typename boost::graph_traits&lt;Graph&gt;::vertex_iterator ui, ui_end;
+    for (tie(ui, ui_end) = vertices(G); ui != ui_end; ++ui)
+      put(color, *ui, white(c));
+    breadth_first_search(G, s, Q, cm_visitor, color);
   }  
 </pre>
 </td></tr></table>
@@ -231,7 +241,7 @@ wide use is based on a greedy approach such that the ordering is
 chosen to minimize some quantity at each step of a simulated -step
 symmetric Gaussian elimination process.  The algorithms using such an
 approach are typically distinguished by their greedy minimization
-criteria&nbsp;[].
+criteria&nbsp;[<a href="bibliography.html#ng-raghavan">34</a>].
 
 <P>
 In graph terms, the basic ordering process used by most greedy
@@ -263,12 +273,12 @@ v<sup>1</sup>,...}</i> selected by the algorithm.
 One of the most important examples of such an algorithm is the
 <I>Minimum Degree</I> algorithm.  At each step the minimum degree
 algorithm chooses the vertex with minimum degree in the corresponding
-graph as <i>v<sup>k</sup></i>.
-A number of enhancements to the basic minimum degree algorithm have
-been developed, such as the use of a quotient graph representation,
-mass elimination, incomplete degree update, multiple elimination, and
-external degree.  See&nbsp;[] for a historical survey
-of the minimum degree algorithm.
+graph as <i>v<sup>k</sup></i>.  A number of enhancements to the basic
+minimum degree algorithm have been developed, such as the use of a
+quotient graph representation, mass elimination, incomplete degree
+update, multiple elimination, and external degree.  See&nbsp;[<A
+href="bibliography.html#George:evolution">35</a>] for a historical
+survey of the minimum degree algorithm.
 
 <P>
 The BGL implementation of the Minimum Degree algorithm closely follows
@@ -355,9 +365,9 @@ edge between two vertices in the dual graph. By using a dual graph of
 a mesh, one way to implement the algorithm family of constructing a
 PSAW is to reuse  BGL algorithms such as BFS and DFS with a customized
 visitor to provide operations during
-traversal. The customized visitor has the function <TT>explore()</TT>
+traversal. The customized visitor has the function <TT>tree_edge()</TT>
 which is to extend partial PSAW in case by case and function
-<TT>start()</TT> which is to set up the PSAW for the starting vertex.
+<TT>start_vertex()</TT> which is to set up the PSAW for the starting vertex.
 
 <br>
 <HR>

docs/time_stamper.html

@@ -144,7 +144,7 @@ Construct a time stamper object with time property accessor
 
 <tr>
 <td><tt>
-template &lt;class X, class Graph&gt;
+template &lt;class X, class Graph&gt;<br>
 void operator()(X x, const Graph& g);
 </tt></td>
 <td>

include/boost/graph/detail/self_avoiding_walk.hpp

@@ -158,7 +158,9 @@ namespace boost {
    * a point though.
    */
   template < class TriangleDecorator, class HList, class IteratorD>
-  class SAW_visitor  : public null_visitor  {
+  class SAW_visitor
+    : public bfs_visitor<>, public dfs_visitor<>
+  {
     typedef typename boost::property_traits<IteratorD>::value_type iter;
     /*use boost shared_ptr*/
     typedef typename HList::element_type::value_type::second_type     Line;
@@ -169,8 +171,8 @@ namespace boost {
     inline SAW_visitor(TriangleDecorator _td, HList _hlist, IteratorD ia)
       : td(_td), hlist(_hlist), iter_d(ia) {}
 
-    template <class Vertex>
-    inline void start(Vertex v) {
+    template <class Vertex, class Graph>
+    inline void start_vertex(Vertex v, Graph&) {
       Line l1;
       l1.first = SAW_SENTINAL;
       l1.second = SAW_SENTINAL;
@@ -186,7 +188,7 @@ namespace boost {
       w(i) ^ w(i+1): the line or point w go over from w(i) to w(i+1)
     */
     template <class Edge, class Graph>
-    bool explore(Edge e, Graph& G) {
+    bool tree_edge(Edge e, Graph& G) {
 	  using std::make_pair;
       typedef typename boost::graph_traits<Graph>::vertex_descriptor Vertex;
       Vertex tau = target(e, G);

include/boost/graph/visitors.hpp

@@ -35,6 +35,8 @@
 
 namespace boost {
 
+  // This is a bit more convenient than std::numeric_limits because
+  // you don't have to explicitly provide type T.
   template <class T>
   inline T numeric_limits_max(T) { return std::numeric_limits<T>::max(); }
 
@@ -64,15 +66,16 @@ namespace boost {
   struct false_tag { enum { num = FALSE_TAG }; };
 
   //========================================================================
-  // base_visitor and null_visitor
+  // null_visitor and base_visitor
 
-  template <class Visitor>
-  struct base_visitor {
+  struct null_visitor {
     typedef void event_filter;
     template <class T, class Graph>
     void operator()(T, Graph&) { }
   };
-  struct null_visitor {
+  // needed for MSVC workaround
+  template <class Visitor>
+  struct base_visitor {
     typedef void event_filter;
     template <class T, class Graph>
     void operator()(T, Graph&) { }
@@ -123,7 +126,9 @@ namespace boost {
   // predecessor_recorder
 
   template <class PredecessorPA, class Tag>
-  struct predecessor_recorder {
+  struct predecessor_recorder
+    : public base_visitor<predecessor_recorder<PredecessorPA, Tag> >
+  {
     typedef Tag event_filter;
     predecessor_recorder(PredecessorPA pa) : m_predecessor(pa) { }
     template <class Edge, class Graph>
@@ -142,7 +147,9 @@ namespace boost {
   // distance_recorder
 
   template <class DistancePA, class Tag>
-  struct distance_recorder {
+  struct distance_recorder
+    : public base_visitor<distance_recorder<DistancePA, Tag> >
+  {
     typedef Tag event_filter;
     distance_recorder(DistancePA pa) : m_distance(pa) { }
     template <class Edge, class Graph>
@@ -164,7 +171,9 @@ namespace boost {
 
   
   template <class TimePA, class TimeT, class Tag>
-  struct time_stamper {
+  struct time_stamper
+    : public base_visitor<time_stamper<TimePA, TimeT, Tag> >
+  {
     typedef Tag event_filter;
     time_stamper(TimePA pa, TimeT& t) : m_time_pa(pa), m_time(t) { }
     template <class Vertex, class Graph>
@@ -184,7 +193,9 @@ namespace boost {
   // property_writer
 
   template <class PA, class OutputIterator, class Tag>
-  struct property_writer {
+  struct property_writer
+    : public base_visitor<property_writer<PA, OutputIterator, Tag> >
+  {
     typedef Tag event_filter;
 
     property_writer(PA pa, OutputIterator out) : m_pa(pa), m_out(out) { }