blob: 36fb0a47d7fee3eb3889250aa6114d4cea671126 [file] [log] [blame]
//
//=======================================================================
// Copyright (c) 2004 Kristopher Beevers
//
// 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)
//=======================================================================
//
#include <boost/graph/astar_search.hpp>
#include <boost/graph/adjacency_list.hpp>
#include <boost/graph/random.hpp>
#include <boost/random.hpp>
#include <vector>
#include <list>
#include <iostream>
#include <math.h> // for sqrt
#include <time.h>
using namespace boost;
using namespace std;
// auxiliary types
struct location
{
float y, x; // lat, long
};
typedef float cost;
template <class Name, class LocMap>
class city_writer {
public:
city_writer(Name n, LocMap l, float _minx, float _maxx,
float _miny, float _maxy,
unsigned int _ptx, unsigned int _pty)
: name(n), loc(l), minx(_minx), maxx(_maxx), miny(_miny),
maxy(_maxy), ptx(_ptx), pty(_pty) {}
template <class Vertex>
void operator()(ostream& out, const Vertex& v) const {
float px = 1 - (loc[v].x - minx) / (maxx - minx);
float py = (loc[v].y - miny) / (maxy - miny);
out << "[label=\"" << name[v] << "\", pos=\""
<< static_cast<unsigned int>(ptx * px) << ","
<< static_cast<unsigned int>(pty * py)
<< "\", fontsize=\"11\"]";
}
private:
Name name;
LocMap loc;
float minx, maxx, miny, maxy;
unsigned int ptx, pty;
};
template <class WeightMap>
class time_writer {
public:
time_writer(WeightMap w) : wm(w) {}
template <class Edge>
void operator()(ostream &out, const Edge& e) const {
out << "[label=\"" << wm[e] << "\", fontsize=\"11\"]";
}
private:
WeightMap wm;
};
// euclidean distance heuristic
template <class Graph, class CostType, class LocMap>
class distance_heuristic : public astar_heuristic<Graph, CostType>
{
public:
typedef typename graph_traits<Graph>::vertex_descriptor Vertex;
distance_heuristic(LocMap l, Vertex goal)
: m_location(l), m_goal(goal) {}
CostType operator()(Vertex u)
{
CostType dx = m_location[m_goal].x - m_location[u].x;
CostType dy = m_location[m_goal].y - m_location[u].y;
return ::sqrt(dx * dx + dy * dy);
}
private:
LocMap m_location;
Vertex m_goal;
};
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&) {
if(u == m_goal)
throw found_goal();
}
private:
Vertex m_goal;
};
int main(int, char **)
{
// specify some types
typedef adjacency_list<listS, vecS, undirectedS, no_property,
property<edge_weight_t, cost> > mygraph_t;
typedef property_map<mygraph_t, edge_weight_t>::type WeightMap;
typedef mygraph_t::vertex_descriptor vertex;
typedef mygraph_t::edge_descriptor edge_descriptor;
typedef mygraph_t::vertex_iterator vertex_iterator;
typedef std::pair<int, int> edge;
// specify data
enum nodes {
Troy, LakePlacid, Plattsburgh, Massena, Watertown, Utica,
Syracuse, Rochester, Buffalo, Ithaca, Binghamton, Woodstock,
NewYork, N
};
const char *name[] = {
"Troy", "Lake Placid", "Plattsburgh", "Massena",
"Watertown", "Utica", "Syracuse", "Rochester", "Buffalo",
"Ithaca", "Binghamton", "Woodstock", "New York"
};
location locations[] = { // lat/long
{42.73, 73.68}, {44.28, 73.99}, {44.70, 73.46},
{44.93, 74.89}, {43.97, 75.91}, {43.10, 75.23},
{43.04, 76.14}, {43.17, 77.61}, {42.89, 78.86},
{42.44, 76.50}, {42.10, 75.91}, {42.04, 74.11},
{40.67, 73.94}
};
edge edge_array[] = {
edge(Troy,Utica), edge(Troy,LakePlacid),
edge(Troy,Plattsburgh), edge(LakePlacid,Plattsburgh),
edge(Plattsburgh,Massena), edge(LakePlacid,Massena),
edge(Massena,Watertown), edge(Watertown,Utica),
edge(Watertown,Syracuse), edge(Utica,Syracuse),
edge(Syracuse,Rochester), edge(Rochester,Buffalo),
edge(Syracuse,Ithaca), edge(Ithaca,Binghamton),
edge(Ithaca,Rochester), edge(Binghamton,Troy),
edge(Binghamton,Woodstock), edge(Binghamton,NewYork),
edge(Syracuse,Binghamton), edge(Woodstock,Troy),
edge(Woodstock,NewYork)
};
unsigned int num_edges = sizeof(edge_array) / sizeof(edge);
cost weights[] = { // estimated travel time (mins)
96, 134, 143, 65, 115, 133, 117, 116, 74, 56,
84, 73, 69, 70, 116, 147, 173, 183, 74, 71, 124
};
// create graph
mygraph_t g(N);
WeightMap weightmap = get(edge_weight, g);
for(std::size_t j = 0; j < num_edges; ++j) {
edge_descriptor e; bool inserted;
boost::tie(e, inserted) = add_edge(edge_array[j].first,
edge_array[j].second, g);
weightmap[e] = weights[j];
}
// pick random start/goal
boost::minstd_rand gen(time(0));
vertex start = gen() % num_vertices(g);
vertex goal = gen() % num_vertices(g);
cout << "Start vertex: " << name[start] << endl;
cout << "Goal vertex: " << name[goal] << endl;
vector<mygraph_t::vertex_descriptor> p(num_vertices(g));
vector<cost> d(num_vertices(g));
try {
// call astar named parameter interface
astar_search
(g, start,
distance_heuristic<mygraph_t, cost, location*>
(locations, goal),
predecessor_map(&p[0]).distance_map(&d[0]).
visitor(astar_goal_visitor<vertex>(goal)));
} catch(found_goal fg) { // found a path to the goal
list<vertex> shortest_path;
for(vertex v = goal;; v = p[v]) {
shortest_path.push_front(v);
if(p[v] == v)
break;
}
cout << "Shortest path from " << name[start] << " to "
<< name[goal] << ": ";
list<vertex>::iterator spi = shortest_path.begin();
cout << name[start];
for(++spi; spi != shortest_path.end(); ++spi)
cout << " -> " << name[*spi];
cout << endl << "Total travel time: " << d[goal] << endl;
return 0;
}
cout << "Didn't find a path from " << name[start] << "to"
<< name[goal] << "!" << endl;
return 0;
}