2 * Everything that needs the Boost Graph Library and C++ templates etc.
3 * (and what a crazy set of stuff that all is)
10 #include <boost/config.hpp>
11 #include <boost/iterator/iterator_facade.hpp>
12 #include <boost/graph/graph_traits.hpp>
13 #include <boost/graph/graph_concepts.hpp>
14 #include <boost/graph/dijkstra_shortest_paths.hpp>
15 #include <boost/graph/properties.hpp>
16 #include <boost/iterator/counting_iterator.hpp>
17 #include <boost/iterator/iterator_categories.hpp>
25 * edge descriptor f = 00 | e | y | x
28 * e is 0..5. The edge is edge e out of vertex (x,y).
30 * BGL expects an undirected graph's edges to have two descriptors
31 * each, one in each direction.
35 * We use BGL's implementation of Dijkstra's single source shortest
36 * paths. We really want all pairs shortest paths, so Johnson All
37 * Pairs Shortest Paths would seem sensible. But actually Johnson's
38 * algorithm is just a wrapper around Dijkstra's; the extra
39 * functionality is just to deal with -ve edge weights, which we don't
40 * have. So we can use Dijkstra directly and save some cpu (and some
41 * code: we don't have to supply all of the machinery needed for
42 * Johnson's invocation of Bellman-Ford). The overall time cost is
43 * O(VE log V); I think the space used is O(E).
46 #define VMASK (YMASK|XMASK)
47 #define ESHIFT (YBITS|XBITS)
49 class Graph { }; // this is a dummy as our graph has no actual representation
51 struct OutEdgeIncrable {
53 OutEdgeIncrable& operator++() { f += 1<<ESHIFT; return *this; }
54 OutEdgeIncrable(int v, int e) : f(v | (e << ESHIFT)) { }
58 // We make Graph a model of various BGL Graph concepts.
59 // This mainly means that graph_traits<Graph> has lots of stuff.
61 // First, some definitions used later:
63 struct layout_graph_traversal_category :
64 public virtual incidence_graph_tag,
65 public virtual vertex_list_graph_tag,
66 public virtual edge_list_graph_tag { };
68 struct graph_traits<Graph> {
72 typedef int vertex_descriptor; /* vertex number, -1 => none */
73 typedef int edge_descriptor; /* see above */
74 typedef undirected_tag directed_category;
75 typedef disallow_parallel_edge_tag edge_parallel_category;
76 typedef layout_graph_traversal_category traversal_category;
77 inline int null_vertex() { return -1; }
79 // Concept IncidenceGraph:
81 typedef counting_iterator<OutEdgeIncrable,
82 std::forward_iterator_tag> out_edge_iterator;
83 typedef unsigned degree_size_type;
85 inline int source(int f, const Graph&) { return f&VMASK; }
86 inline int target(int f, const Graph&) { return EDGE_END2(f&VMASK, f>>ESHIFT); }
87 inline std::pair<out_edge_iterator,out_edge_iterator>
88 out_edges(int v, const Graph&) {
89 return std::make_pair(out_edge_iterator(OutEdgeIncrable(v, VE_MIN(v))),
90 out_edge_iterator(OutEdgeIncrable(v, VE_MAX(v))));
92 inline unsigned out_degree(int v, const Graph&) {
93 return VE_MAX(v) - VE_MIN(v);
96 // Concept VertexListGraph:
97 typedef counting_iterator<int> vertex_iterator;
98 typedef unsigned vertices_size_type;
99 inline std::pair<vertex_iterator,vertex_iterator>
100 vertices(const Graph&) {
101 return std::make_pair(vertex_iterator(0), vertex_iterator(N));
103 inline unsigned num_vertices(const Graph&) { return N; }
107 static void single_source_shortest_paths(int v1,
108 const double edge_weights[/*f*/],
109 double vertex_distances[/*v*/]) {
112 boost::dijkstra_shortest_paths(g, v1,
113 weight_map(edge_weights).
114 vertex_index_map(identity_property_map()).
115 distance_map(vertex_distances));
118 double graph_layout_cost(const Vertices v, const double vertex_areas[N]) {
119 /* For each (vi,vj) computes shortest path s_ij = |vi..vj|
120 * along edges, and actual distance d_ij = |vi-vj|.
122 * We will also use the `vertex areas': for each vertex vi the
123 * vertex area a_vi is the mean area of the incident triangles.
124 * This is computed elsewhere.
126 * Energy contribution is proportional to
129 * a a . d . [ (s/d) - 1 ]
132 * (In practice we compute d^2+epsilon and use it for the
133 * divisions, to avoid division by zero.)
135 static const d2_epsilon= 1e-6;
137 double edge_weights[N*V6], vertex_distances[N], total_cost;
142 edge_weights[f]= NaN)
143 edge_weights[f]= hypotD(v[v1], v[v2]);
146 double a1= vertex_areas[v1];
147 single_source_shortest_paths(v1, edge_weights, vertex_distances);
149 double a2= vertex_areas[v2];
150 double d2= hypotD2plus(v[v1],v[v2], d2_epsilon);
151 double sd= vertex_distances[v2] / d2;
153 total_cost += a1*a2 * (sd2 - 1) / (d2*d2);