diff -r 000000000000 -r e4d67989cc36 ossrv_pub/boost_apis/boost/graph/gursoy_atun_layout.hpp
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/ossrv_pub/boost_apis/boost/graph/gursoy_atun_layout.hpp	Tue Feb 02 02:01:42 2010 +0200
@@ -0,0 +1,631 @@
+// Copyright 2004 The Trustees of Indiana University.
+
+// Distributed under the Boost Software License, Version 1.0.
+// (See accompanying file LICENSE_1_0.txt or copy at
+// http://www.boost.org/LICENSE_1_0.txt)
+
+//  Authors: Jeremiah Willcock
+//           Douglas Gregor
+//           Andrew Lumsdaine
+#ifndef BOOST_GRAPH_GURSOY_ATUN_LAYOUT_HPP
+#define BOOST_GRAPH_GURSOY_ATUN_LAYOUT_HPP
+
+// Gursoy-Atun graph layout, based on:
+// "Neighbourhood Preserving Load Balancing: A Self-Organizing Approach"
+// in EuroPar 2000, p. 234 of LNCS 1900
+// http://springerlink.metapress.com/link.asp?id=pcu07ew5rhexp9yt
+
+#include <cmath>
+#include <vector>
+#include <exception>
+#include <algorithm>
+
+#include <boost/graph/visitors.hpp>
+#include <boost/graph/properties.hpp>
+#include <boost/random/uniform_01.hpp>
+#include <boost/random/linear_congruential.hpp>
+#include <boost/shared_ptr.hpp>
+#include <boost/graph/breadth_first_search.hpp>
+#include <boost/graph/dijkstra_shortest_paths.hpp>
+#include <boost/graph/named_function_params.hpp>
+
+namespace boost { 
+
+namespace detail {
+
+struct over_distance_limit : public std::exception {};
+
+template <typename PositionMap, typename NodeDistanceMap,  typename Topology,
+          typename Graph>
+struct update_position_visitor {
+  typedef typename Topology::point_type Point;
+  PositionMap position_map;
+  NodeDistanceMap node_distance;
+  const Topology& space;
+  Point input_vector;
+  double distance_limit;
+  double learning_constant;
+  double falloff_ratio;
+
+  typedef boost::on_examine_vertex event_filter;
+
+  typedef typename graph_traits<Graph>::vertex_descriptor
+    vertex_descriptor;
+
+  update_position_visitor(PositionMap position_map,
+                          NodeDistanceMap node_distance,
+                          const Topology& space,
+                          const Point& input_vector,
+                          double distance_limit,
+                          double learning_constant,
+                          double falloff_ratio):
+    position_map(position_map), node_distance(node_distance), 
+    space(space),
+    input_vector(input_vector), distance_limit(distance_limit),
+    learning_constant(learning_constant), falloff_ratio(falloff_ratio) {}
+
+  void operator()(vertex_descriptor v, const Graph&) const 
+  {
+#ifndef BOOST_NO_STDC_NAMESPACE
+    using std::pow;
+#endif
+
+    if (get(node_distance, v) > distance_limit)
+      throw over_distance_limit();
+    Point old_position = get(position_map, v);
+    double distance = get(node_distance, v);
+    double fraction = 
+      learning_constant * pow(falloff_ratio, distance * distance);
+    put(position_map, v,
+        space.move_position_toward(old_position, fraction, input_vector));
+  }
+};
+
+template<typename EdgeWeightMap>
+struct gursoy_shortest
+{
+  template<typename Graph, typename NodeDistanceMap, typename UpdatePosition>
+  static inline void 
+  run(const Graph& g, typename graph_traits<Graph>::vertex_descriptor s,
+      NodeDistanceMap node_distance,  UpdatePosition& update_position,
+      EdgeWeightMap weight)
+  {
+    boost::dijkstra_shortest_paths(g, s, weight_map(weight).
+      visitor(boost::make_dijkstra_visitor(std::make_pair(
+       boost::record_distances(node_distance, boost::on_edge_relaxed()),
+        update_position))));
+  }
+};
+
+template<>
+struct gursoy_shortest<dummy_property_map>
+{
+  template<typename Graph, typename NodeDistanceMap, typename UpdatePosition>
+  static inline void 
+  run(const Graph& g, typename graph_traits<Graph>::vertex_descriptor s,
+      NodeDistanceMap node_distance,  UpdatePosition& update_position,
+      dummy_property_map)
+  {
+    boost::breadth_first_search(g, s,
+      visitor(boost::make_bfs_visitor(std::make_pair(
+        boost::record_distances(node_distance, boost::on_tree_edge()),
+        update_position))));
+  }
+};
+
+} // namespace detail
+
+template <typename VertexListAndIncidenceGraph,  typename Topology,
+          typename PositionMap, typename Diameter, typename VertexIndexMap, 
+          typename EdgeWeightMap>
+void 
+gursoy_atun_step
+  (const VertexListAndIncidenceGraph& graph,  
+   const Topology& space,
+   PositionMap position,
+   Diameter diameter,
+   double learning_constant,
+   VertexIndexMap vertex_index_map,
+   EdgeWeightMap weight)
+{
+#ifndef BOOST_NO_STDC_NAMESPACE
+  using std::pow;
+  using std::exp;
+#endif
+
+  typedef typename graph_traits<VertexListAndIncidenceGraph>::vertex_iterator
+    vertex_iterator;
+  typedef typename graph_traits<VertexListAndIncidenceGraph>::vertex_descriptor
+    vertex_descriptor;
+  typedef typename Topology::point_type point_type;
+  vertex_iterator i, iend;
+  std::vector<double> distance_from_input_vector(num_vertices(graph));
+  typedef boost::iterator_property_map<std::vector<double>::iterator, 
+                                       VertexIndexMap,
+                                       double, double&>
+    DistanceFromInputMap;
+  DistanceFromInputMap distance_from_input(distance_from_input_vector.begin(),
+                                           vertex_index_map);
+  std::vector<double> node_distance_map_vector(num_vertices(graph));
+  typedef boost::iterator_property_map<std::vector<double>::iterator, 
+                                       VertexIndexMap,
+                                       double, double&>
+    NodeDistanceMap;
+  NodeDistanceMap node_distance(node_distance_map_vector.begin(),
+                                vertex_index_map);
+  point_type input_vector = space.random_point();
+  vertex_descriptor min_distance_loc 
+    = graph_traits<VertexListAndIncidenceGraph>::null_vertex();
+  double min_distance = 0.0;
+  bool min_distance_unset = true;
+  for (boost::tie(i, iend) = vertices(graph); i != iend; ++i) {
+    double this_distance = space.distance(get(position, *i), input_vector);
+    put(distance_from_input, *i, this_distance);
+    if (min_distance_unset || this_distance < min_distance) {
+      min_distance = this_distance;
+      min_distance_loc = *i;
+    }
+    min_distance_unset = false;
+  }
+  assert (!min_distance_unset); // Graph must have at least one vertex
+  boost::detail::update_position_visitor<
+      PositionMap, NodeDistanceMap, Topology,
+      VertexListAndIncidenceGraph> 
+    update_position(position, node_distance, space,
+                    input_vector, diameter, learning_constant, 
+                    exp(-1. / (2 * diameter * diameter)));
+  std::fill(node_distance_map_vector.begin(), node_distance_map_vector.end(), 0);
+  try {
+    typedef detail::gursoy_shortest<EdgeWeightMap> shortest;
+    shortest::run(graph, min_distance_loc, node_distance, update_position,
+                  weight);    
+  } catch (detail::over_distance_limit) { 
+    /* Thrown to break out of BFS or Dijkstra early */ 
+  }
+}
+
+template <typename VertexListAndIncidenceGraph,  typename Topology,
+          typename PositionMap, typename VertexIndexMap, 
+          typename EdgeWeightMap>
+void gursoy_atun_refine(const VertexListAndIncidenceGraph& graph,  
+                        const Topology& space,
+                        PositionMap position,
+                        int nsteps,
+                        double diameter_initial,
+                        double diameter_final,
+                        double learning_constant_initial,
+                        double learning_constant_final,
+                        VertexIndexMap vertex_index_map,
+                        EdgeWeightMap weight) 
+{
+#ifndef BOOST_NO_STDC_NAMESPACE
+  using std::pow;
+  using std::exp;
+#endif
+
+  typedef typename graph_traits<VertexListAndIncidenceGraph>::vertex_iterator
+    vertex_iterator;
+  typedef typename graph_traits<VertexListAndIncidenceGraph>::vertex_descriptor
+    vertex_descriptor;
+  typedef typename Topology::point_type point_type;
+  vertex_iterator i, iend;
+  double diameter_ratio = (double)diameter_final / diameter_initial;
+  double learning_constant_ratio = 
+    learning_constant_final / learning_constant_initial;
+  std::vector<double> distance_from_input_vector(num_vertices(graph));
+  typedef boost::iterator_property_map<std::vector<double>::iterator, 
+                                       VertexIndexMap,
+                                       double, double&>
+    DistanceFromInputMap;
+  DistanceFromInputMap distance_from_input(distance_from_input_vector.begin(),
+                                           vertex_index_map);
+  std::vector<int> node_distance_map_vector(num_vertices(graph));
+  typedef boost::iterator_property_map<std::vector<int>::iterator, 
+                                       VertexIndexMap, double, double&>
+    NodeDistanceMap;
+  NodeDistanceMap node_distance(node_distance_map_vector.begin(),
+                                vertex_index_map);
+  for (int round = 0; round < nsteps; ++round) {
+    double part_done = (double)round / (nsteps - 1);
+    int diameter = (int)(diameter_initial * pow(diameter_ratio, part_done));
+    double learning_constant = 
+      learning_constant_initial * pow(learning_constant_ratio, part_done);
+    gursoy_atun_step(graph, space, position, diameter, learning_constant, 
+                     vertex_index_map, weight);
+  }
+}
+
+template <typename VertexListAndIncidenceGraph,  typename Topology,
+          typename PositionMap, typename VertexIndexMap, 
+          typename EdgeWeightMap>
+void gursoy_atun_layout(const VertexListAndIncidenceGraph& graph,  
+                        const Topology& space,
+                        PositionMap position,
+                        int nsteps,
+                        double diameter_initial,
+                        double diameter_final,
+                        double learning_constant_initial,
+                        double learning_constant_final,
+                        VertexIndexMap vertex_index_map,
+                        EdgeWeightMap weight)
+{
+  typedef typename graph_traits<VertexListAndIncidenceGraph>::vertex_iterator
+    vertex_iterator;
+  vertex_iterator i, iend;
+  for (boost::tie(i, iend) = vertices(graph); i != iend; ++i) {
+    put(position, *i, space.random_point());
+  }
+  gursoy_atun_refine(graph, space,
+                     position, nsteps,
+                     diameter_initial, diameter_final, 
+                     learning_constant_initial, learning_constant_final,
+                     vertex_index_map, weight);
+}
+
+template <typename VertexListAndIncidenceGraph,  typename Topology,
+          typename PositionMap, typename VertexIndexMap>
+void gursoy_atun_layout(const VertexListAndIncidenceGraph& graph,  
+                        const Topology& space,
+                        PositionMap position,
+                        int nsteps,
+                        double diameter_initial,
+                        double diameter_final,
+                        double learning_constant_initial,
+                        double learning_constant_final,
+                        VertexIndexMap vertex_index_map)
+{
+  gursoy_atun_layout(graph, space, position, nsteps, 
+                     diameter_initial, diameter_final, 
+                     learning_constant_initial, learning_constant_final, 
+                     vertex_index_map, dummy_property_map());
+}
+
+template <typename VertexListAndIncidenceGraph, typename Topology,
+          typename PositionMap>
+void gursoy_atun_layout(const VertexListAndIncidenceGraph& graph,  
+                        const Topology& space,
+                        PositionMap position,
+                        int nsteps,
+                        double diameter_initial,
+                        double diameter_final = 1.0,
+                        double learning_constant_initial = 0.8,
+                        double learning_constant_final = 0.2)
+{ 
+  gursoy_atun_layout(graph, space, position, nsteps, diameter_initial,
+                     diameter_final, learning_constant_initial,
+                     learning_constant_final, get(vertex_index, graph)); 
+}
+
+template <typename VertexListAndIncidenceGraph, typename Topology,
+          typename PositionMap>
+void gursoy_atun_layout(const VertexListAndIncidenceGraph& graph,  
+                        const Topology& space,
+                        PositionMap position,
+                        int nsteps)
+{
+#ifndef BOOST_NO_STDC_NAMESPACE
+  using std::sqrt;
+#endif
+
+  gursoy_atun_layout(graph, space, position, nsteps, 
+                     sqrt((double)num_vertices(graph)));
+}
+
+template <typename VertexListAndIncidenceGraph, typename Topology,
+          typename PositionMap>
+void gursoy_atun_layout(const VertexListAndIncidenceGraph& graph,  
+                        const Topology& space,
+                        PositionMap position)
+{
+  gursoy_atun_layout(graph, space, position, num_vertices(graph));
+}
+
+template<typename VertexListAndIncidenceGraph, typename Topology,
+         typename PositionMap, typename P, typename T, typename R>
+void 
+gursoy_atun_layout(const VertexListAndIncidenceGraph& graph,  
+                   const Topology& space,
+                   PositionMap position,
+                   const bgl_named_params<P,T,R>& params)
+{
+#ifndef BOOST_NO_STDC_NAMESPACE
+  using std::sqrt;
+#endif
+
+  std::pair<double, double> diam(sqrt(double(num_vertices(graph))), 1.0);
+  std::pair<double, double> learn(0.8, 0.2);
+  gursoy_atun_layout(graph, space, position,
+                     choose_param(get_param(params, iterations_t()),
+                                  num_vertices(graph)),
+                     choose_param(get_param(params, diameter_range_t()), 
+                                  diam).first,
+                     choose_param(get_param(params, diameter_range_t()), 
+                                  diam).second,
+                     choose_param(get_param(params, learning_constant_range_t()), 
+                                  learn).first,
+                     choose_param(get_param(params, learning_constant_range_t()), 
+                                  learn).second,
+                     choose_const_pmap(get_param(params, vertex_index), graph,
+                                       vertex_index),
+                     choose_param(get_param(params, edge_weight), 
+                                  dummy_property_map()));
+}
+
+/***********************************************************
+ * Topologies                                              *
+ ***********************************************************/
+template<std::size_t Dims>
+class convex_topology 
+{
+  struct point 
+  {
+    point() { }
+    double& operator[](std::size_t i) {return values[i];}
+    const double& operator[](std::size_t i) const {return values[i];}
+
+  private:
+    double values[Dims];
+  };
+
+ public:
+  typedef point point_type;
+
+  double distance(point a, point b) const 
+  {
+    double dist = 0;
+    for (std::size_t i = 0; i < Dims; ++i) {
+      double diff = b[i] - a[i];
+      dist += diff * diff;
+    }
+    // Exact properties of the distance are not important, as long as
+    // < on what this returns matches real distances
+    return dist;
+  }
+
+  point move_position_toward(point a, double fraction, point b) const 
+  {
+    point result;
+    for (std::size_t i = 0; i < Dims; ++i)
+      result[i] = a[i] + (b[i] - a[i]) * fraction;
+    return result;
+  }
+};
+
+template<std::size_t Dims,
+         typename RandomNumberGenerator = minstd_rand>
+class hypercube_topology : public convex_topology<Dims>
+{
+  typedef uniform_01<RandomNumberGenerator, double> rand_t;
+
+ public:
+  typedef typename convex_topology<Dims>::point_type point_type;
+
+  explicit hypercube_topology(double scaling = 1.0) 
+    : gen_ptr(new RandomNumberGenerator), rand(new rand_t(*gen_ptr)), 
+      scaling(scaling) 
+  { }
+
+  hypercube_topology(RandomNumberGenerator& gen, double scaling = 1.0) 
+    : gen_ptr(), rand(new rand_t(gen)), scaling(scaling) { }
+                     
+  point_type random_point() const 
+  {
+    point_type p;
+    for (std::size_t i = 0; i < Dims; ++i)
+      p[i] = (*rand)() * scaling;
+    return p;
+  }
+
+ private:
+  shared_ptr<RandomNumberGenerator> gen_ptr;
+  shared_ptr<rand_t> rand;
+  double scaling;
+};
+
+template<typename RandomNumberGenerator = minstd_rand>
+class square_topology : public hypercube_topology<2, RandomNumberGenerator>
+{
+  typedef hypercube_topology<2, RandomNumberGenerator> inherited;
+
+ public:
+  explicit square_topology(double scaling = 1.0) : inherited(scaling) { }
+  
+  square_topology(RandomNumberGenerator& gen, double scaling = 1.0) 
+    : inherited(gen, scaling) { }
+};
+
+template<typename RandomNumberGenerator = minstd_rand>
+class cube_topology : public hypercube_topology<3, RandomNumberGenerator>
+{
+  typedef hypercube_topology<3, RandomNumberGenerator> inherited;
+
+ public:
+  explicit cube_topology(double scaling = 1.0) : inherited(scaling) { }
+  
+  cube_topology(RandomNumberGenerator& gen, double scaling = 1.0) 
+    : inherited(gen, scaling) { }
+};
+
+template<std::size_t Dims,
+         typename RandomNumberGenerator = minstd_rand>
+class ball_topology : public convex_topology<Dims>
+{
+  typedef uniform_01<RandomNumberGenerator, double> rand_t;
+
+ public:
+  typedef typename convex_topology<Dims>::point_type point_type;
+
+  explicit ball_topology(double radius = 1.0) 
+    : gen_ptr(new RandomNumberGenerator), rand(new rand_t(*gen_ptr)), 
+      radius(radius) 
+  { }
+
+  ball_topology(RandomNumberGenerator& gen, double radius = 1.0) 
+    : gen_ptr(), rand(new rand_t(gen)), radius(radius) { }
+                     
+  point_type random_point() const 
+  {
+    point_type p;
+    double dist_sum;
+    do {
+      dist_sum = 0.0;
+      for (std::size_t i = 0; i < Dims; ++i) {
+        double x = (*rand)() * 2*radius - radius;
+        p[i] = x;
+        dist_sum += x * x;
+      }
+    } while (dist_sum > radius*radius);
+    return p;
+  }
+
+ private:
+  shared_ptr<RandomNumberGenerator> gen_ptr;
+  shared_ptr<rand_t> rand;
+  double radius;
+};
+
+template<typename RandomNumberGenerator = minstd_rand>
+class circle_topology : public ball_topology<2, RandomNumberGenerator>
+{
+  typedef ball_topology<2, RandomNumberGenerator> inherited;
+
+ public:
+  explicit circle_topology(double radius = 1.0) : inherited(radius) { }
+  
+  circle_topology(RandomNumberGenerator& gen, double radius = 1.0) 
+    : inherited(gen, radius) { }
+};
+
+template<typename RandomNumberGenerator = minstd_rand>
+class sphere_topology : public ball_topology<3, RandomNumberGenerator>
+{
+  typedef ball_topology<3, RandomNumberGenerator> inherited;
+
+ public:
+  explicit sphere_topology(double radius = 1.0) : inherited(radius) { }
+  
+  sphere_topology(RandomNumberGenerator& gen, double radius = 1.0) 
+    : inherited(gen, radius) { }
+};
+
+template<typename RandomNumberGenerator = minstd_rand>
+class heart_topology 
+{
+  // Heart is defined as the union of three shapes:
+  // Square w/ corners (+-1000, -1000), (0, 0), (0, -2000)
+  // Circle centered at (-500, -500) radius 500*sqrt(2)
+  // Circle centered at (500, -500) radius 500*sqrt(2)
+  // Bounding box (-1000, -2000) - (1000, 500*(sqrt(2) - 1))
+
+  struct point 
+  {
+    point() { values[0] = 0.0; values[1] = 0.0; }
+    point(double x, double y) { values[0] = x; values[1] = y; }
+
+    double& operator[](std::size_t i)       { return values[i]; }
+    double  operator[](std::size_t i) const { return values[i]; }
+
+  private:
+    double values[2];
+  };
+
+  bool in_heart(point p) const 
+  {
+#ifndef BOOST_NO_STDC_NAMESPACE
+    using std::abs;
+    using std::pow;
+#endif
+
+    if (p[1] < abs(p[0]) - 2000) return false; // Bottom
+    if (p[1] <= -1000) return true; // Diagonal of square
+    if (pow(p[0] - -500, 2) + pow(p[1] - -500, 2) <= 500000)
+      return true; // Left circle
+    if (pow(p[0] - 500, 2) + pow(p[1] - -500, 2) <= 500000)
+      return true; // Right circle
+    return false;
+  }
+
+  bool segment_within_heart(point p1, point p2) const 
+  {
+    // Assumes that p1 and p2 are within the heart
+    if ((p1[0] < 0) == (p2[0] < 0)) return true; // Same side of symmetry line
+    if (p1[0] == p2[0]) return true; // Vertical
+    double slope = (p2[1] - p1[1]) / (p2[0] - p1[0]);
+    double intercept = p1[1] - p1[0] * slope;
+    if (intercept > 0) return false; // Crosses between circles
+    return true;
+  }
+
+  typedef uniform_01<RandomNumberGenerator, double> rand_t;
+
+ public:
+  typedef point point_type;
+
+  heart_topology() 
+    : gen_ptr(new RandomNumberGenerator), rand(new rand_t(*gen_ptr)) { }
+
+  heart_topology(RandomNumberGenerator& gen) 
+    : gen_ptr(), rand(new rand_t(gen)) { }
+
+  point random_point() const 
+  {
+#ifndef BOOST_NO_STDC_NAMESPACE
+    using std::sqrt;
+#endif
+
+    point result;
+    double sqrt2 = sqrt(2.);
+    do {
+      result[0] = (*rand)() * (1000 + 1000 * sqrt2) - (500 + 500 * sqrt2);
+      result[1] = (*rand)() * (2000 + 500 * (sqrt2 - 1)) - 2000;
+    } while (!in_heart(result));
+    return result;
+  }
+
+  double distance(point a, point b) const 
+  {
+#ifndef BOOST_NO_STDC_NAMESPACE
+    using std::sqrt;
+#endif
+    if (segment_within_heart(a, b)) {
+      // Straight line
+      return sqrt((b[0] - a[0]) * (b[0] - a[0]) + (b[1] - a[1]) * (b[1] - a[1]));
+    } else {
+      // Straight line bending around (0, 0)
+      return sqrt(a[0] * a[0] + a[1] * a[1]) + sqrt(b[0] * b[0] + b[1] * b[1]);
+    }
+  }
+
+  point move_position_toward(point a, double fraction, point b) const 
+  {
+#ifndef BOOST_NO_STDC_NAMESPACE
+    using std::sqrt;
+#endif
+
+    if (segment_within_heart(a, b)) {
+      // Straight line
+      return point(a[0] + (b[0] - a[0]) * fraction,
+                   a[1] + (b[1] - a[1]) * fraction);
+    } else {
+      double distance_to_point_a = sqrt(a[0] * a[0] + a[1] * a[1]);
+      double distance_to_point_b = sqrt(b[0] * b[0] + b[1] * b[1]);
+      double location_of_point = distance_to_point_a / 
+                                   (distance_to_point_a + distance_to_point_b);
+      if (fraction < location_of_point)
+        return point(a[0] * (1 - fraction / location_of_point), 
+                     a[1] * (1 - fraction / location_of_point));
+      else
+        return point(
+          b[0] * ((fraction - location_of_point) / (1 - location_of_point)),
+          b[1] * ((fraction - location_of_point) / (1 - location_of_point)));
+    }
+  }
+
+ private:
+  shared_ptr<RandomNumberGenerator> gen_ptr;
+  shared_ptr<rand_t> rand;
+};
+
+} // namespace boost
+
+#endif // BOOST_GRAPH_GURSOY_ATUN_LAYOUT_HPP