root/branches/pgrouting-light/src/astar_boost_wrapper.cpp

/*
 * A* Shortest path algorithm for PostgreSQL
 *
 * Copyright (c) 2006 Anton A. Patrushev, Orkney, Inc.
 *
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 2 of the License, or
 * (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program; if not, write to the Free Software
 * Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
 *
 */

#include <boost/config.hpp>
#include <iostream>
#include <fstream>

#include <boost/graph/graph_traits.hpp>
#include <boost/graph/adjacency_list.hpp>
#include <boost/graph/astar_search.hpp>

#include "astar.h"

#include <math.h>    // for sqrt

using namespace std;
using namespace boost;

// Maximal number of nodes in the path (to avoid infinite loops)
#define MAX_NODES 1000000

struct Edge
{
  int id;
  float8 cost;
  //float8 distance;
};
        
struct Vertex
{
  int id;
  float8 x;
  float8 y;
};


struct found_goal {}; // exception for termination

// visitor that terminates when we find the goal
template <class Vertex>
class astar_goal_visitor : public boost::default_astar_visitor
{
public:
  astar_goal_visitor(Vertex goal) : m_goal(goal) {}
  template <class Graph>
  void examine_vertex(Vertex u, Graph& g) {
    if(u == m_goal)
      throw found_goal();
  }
private:
  Vertex m_goal;
};


template <class Graph, class CostType>
class distance_heuristic : public astar_heuristic<Graph, CostType>
{
public:
  typedef typename graph_traits<Graph>::vertex_descriptor Vertex;
  distance_heuristic(Graph& g, Vertex goal):m_g(g), m_goal(goal){}
  CostType operator()(Vertex u)
  {
    CostType dx = m_g[m_goal].x - m_g[u].x;
    CostType dy = m_g[m_goal].y - m_g[u].y;
    //You can choose any heuristical function from below
    //return ::max(dx, dy);
    //return ::sqrt(dx * dx + dy * dy)/4;
    //return 0;
    return (::fabs(dx)+::fabs(dy))/2;
  } 
private:
  Graph& m_g;
  Vertex m_goal;
};


template <class G, class E>
static void
graph_add_edge(G &graph, int id, int source, int target, 
               float8 cost, float8 s_x, float8 s_y, float8 t_x, float8 t_y)
{
  E e;
  bool inserted;
    
  if (cost < 0) // edges are not inserted in the graph if cost is negative
    return;

  tie(e, inserted) = add_edge(source, target, graph);

  graph[e].cost = cost;
  graph[e].id = id;

  typedef typename graph_traits<G>::vertex_descriptor Vertex;
  Vertex s = vertex(source, graph);
  Vertex t = vertex(target, graph);
  graph[s].x=s_x;
  graph[s].y=s_y;
  graph[t].x=t_x;
  graph[t].y=t_y;
}

int 
boost_astar(edge_astar_t *edges, unsigned int count, 
            int source_vertex_id, int target_vertex_id,
            bool directed, bool has_reverse_cost,
            path_element_t **path, int *path_count, char **err_msg)
{

  // FIXME: use a template for the directedS parameters
  typedef adjacency_list < listS, vecS, directedS, Vertex, Edge> graph_t;

  typedef graph_traits < graph_t >::vertex_descriptor vertex_descriptor;
  typedef graph_traits < graph_t >::edge_descriptor edge_descriptor;

  // FIXME: compute this value
  const unsigned int num_nodes = ((directed && has_reverse_cost ? 2 : 1) * 
                                  count) + 100;

  graph_t graph(num_nodes);

  property_map<graph_t, edge_weight_t>::type weightmap = get(edge_weight, 
                                                             graph);

  for (std::size_t j = 0; j < count; ++j)
    {
      graph_add_edge<graph_t, edge_descriptor>(graph, 
                                               edges[j].id, edges[j].source, 
                                               edges[j].target, edges[j].cost, 
                                               edges[j].s_x, edges[j].s_y, 
                                               edges[j].t_x, edges[j].t_y);

      if (!directed || (directed && has_reverse_cost))
        {
          float8 cost;

          if (has_reverse_cost)
            {
              cost = edges[j].reverse_cost;
            }
          else 
            {
              cost = edges[j].cost;
            }

          graph_add_edge<graph_t, edge_descriptor>(graph, 
                                                   edges[j].id, 
                                                   edges[j].target, 
                                                   edges[j].source, 
                                                   cost, 
                                                   edges[j].s_x, 
                                                   edges[j].s_y, 
                                                   edges[j].t_x, 
                                                   edges[j].t_y);
        }
    }

  std::vector<vertex_descriptor> predecessors(num_vertices(graph));

  vertex_descriptor source_vertex = vertex(source_vertex_id, graph);

  if (source_vertex < 0) 
    {
      *err_msg = "Source vertex not found";
      return -1;
    }

  vertex_descriptor target_vertex = vertex(target_vertex_id, graph);
  if (target_vertex < 0)
    {
      *err_msg = "Target vertex not found";
      return -1;
    }

  std::vector<float8> distances(num_vertices(graph));

  try {
    // call astar named parameter interface
    astar_search
      (graph, source_vertex,
       distance_heuristic<graph_t, float>(graph, target_vertex),
       predecessor_map(&predecessors[0]).
       weight_map(get(&Edge::cost, graph)).
       distance_map(&distances[0]).
       visitor(astar_goal_visitor<vertex_descriptor>(target_vertex)));

  } 
  catch(found_goal fg) {
    vector<int> path_vect;
    int max = MAX_NODES;
    path_vect.push_back(target_vertex);
  
    while (target_vertex != source_vertex) 
      {
        if (target_vertex == predecessors[target_vertex]) 
          {
            *err_msg = "No path found";
            return 0;
            
          }
        target_vertex = predecessors[target_vertex];

        path_vect.push_back(target_vertex);
        if (!max--) 
          {
            *err_msg = "Overflow";
            return -1;
          }
      }

    *path = (path_element_t *) malloc(sizeof(path_element_t) * 
                                      (path_vect.size() + 1));
    *path_count = path_vect.size();

    for(int i = path_vect.size() - 1, j = 0; i >= 0; i--, j++)
      {
        graph_traits < graph_t >::vertex_descriptor v_src;
        graph_traits < graph_t >::vertex_descriptor v_targ;
        graph_traits < graph_t >::edge_descriptor e;
        graph_traits < graph_t >::out_edge_iterator out_i, out_end;

        (*path)[j].vertex_id = path_vect.at(i);

        (*path)[j].edge_id = -1;
        (*path)[j].cost = distances[target_vertex];
        
        if (i == 0) 
          {
            continue;
          }

        v_src = path_vect.at(i);
        v_targ = path_vect.at(i - 1);

        for (tie(out_i, out_end) = out_edges(v_src, graph); 
             out_i != out_end; ++out_i)
          {
            graph_traits < graph_t >::vertex_descriptor v, targ;
            e = *out_i;
            v = source(e, graph);
            targ = target(e, graph);
                                                                
            if (targ == v_targ)
              {
                (*path)[j].edge_id = graph[*out_i].id;
                (*path)[j].cost = graph[*out_i].cost;
                break;
              }
          }
      }

    return EXIT_SUCCESS;
  }
}