Graph < Integer, Integer> g = new SparseMultigraph<Integer, Integer>();
    g.addVertex(1);g.addVertex(2);g.addVertex(3);
    g.addEdge(0,1,2 ,EdgeType.DIRECTED);g.addEdge(1,2,3 ,EdgeType.DIRECTED);g.addEdge(2,3,1 ,EdgeType.DIRECTED);g.addEdge(3,1,3 ,EdgeType.DIRECTED);


考虑到它是有向图,如何将它转换成邻接矩阵。

最佳答案

在这篇文章中,您可以找到一个邻接矩阵:

Breadth and depth first search - part 3

如何执行呢?

// Adjacency matrix
int map[21][21] = {

/*   A B C D E F G H I L M N O P R S T U V Z */
  {0,1,2,3,4,5,6,7,8,9,0,1,2,3,4,5,6,7,8,9,0},
  {1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1}, // Arad
  {2,0,0,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,1,0,0}, // Bucharest
  {3,0,0,0,1,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0}, // Craiova
  {4,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0}, // Dobreta
  {5,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0}, // Eforie
  {6,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0}, // Fagaras
  {7,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}, // Girgiu
  {8,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0}, // Hirsova
  {9,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0}, // Iasi
  {0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0}, // Lugoj
  {1,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0}, // Mehadia
  {2,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0}, // Neamt
  {3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1}, // Oradea
  {4,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0}, // Pitesti
  {5,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0}, // Rimnicu Vilcea
  {6,1,0,0,0,0,1,0,0,0,0,0,0,1,0,1,0,0,0,0,0}, // Sibiu
  {7,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0}, // Timisoara
  {8,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0}, // Urziceni
  {9,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0}, // Vaslui
  {0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0}  // Zerind
};


请注意,第一条注释行代表每个城市名称的首字母。使用邻接矩阵完成的映射引用了这些字母,因此更易于理解。例如,获得引用Arad的邻接矩阵的第一项:我们拥有Arad的路径将我们引向锡比乌,蒂米什瓦拉和泽林德,因此在这种情况下,我们将代表这些城市的列的值设为1 ,即字母S,T和Z下方的列。这就是完成映射的方式。我们在其他列上设置了0值,以表明没有通往我们这些城市的路径。

给定您的图形,对其边缘进行迭代并创建邻接矩阵。

10-08 03:12