The most common operation in graph theory is to traverse adjacent edges, traversing related adjacent edges through a vertex. The time complexity of traversing the adjacent edges of the adjacency matrix is O (V), and the adjacency table can be found directly, which is more efficient.
邻接矩阵迭代:
...
public Iterable<Integer> adj(int v) {
assert v >= 0 && v < n;
Vector<Integer> adjV = new Vector<Integer>();
for(int i = 0 ; i < n ; i ++ )
if( g[v][i] )
adjV.add(i);
return adjV;
}
...
邻接表迭代：
...
// 返回图中一个顶点的所有邻边
// 由于java使用引用机制，返回一个Vector不会带来额外开销,
public Iterable<Integer> adj(int v) {
assert v >= 0 && v < n;
return g[v];
}
...
For the expression of these two graphs, we can abstract an interface and generate the framework of this algorithm, regardless of whether the underlying layer is the adjacency table or the adjacency matrix.
This section writes a test case GraphReadTest, which can be viewed in the read package by calling the abstract interface implementation diagram.
/*\*
\* 图的抽象接口
*/
public interface Graph {
public int V();
public int E();
public void addEdge( int v , int w );
boolean hasEdge( int v , int w );
void show();
public Iterable<Integer> adj(int v);
}
5.29.1. Java instance code ¶
源码包下载： Download
（1）邻接矩阵迭代 （2）邻接表迭代 Src/runoob/graph/DenseGraphIterater.java file code: ¶
package runoob.graph;
import java.util.Vector;
/*\*
\* 邻接矩阵迭代
*/
public class DenseGraphIterater {
// 节点数
private int n;
// 边数
private int m;
// 是否为有向图
private boolean directed;
// 图的具体数据
private boolean[][] g;
// 构造函数
public DenseGraphIterater( int n , boolean directed ){
assert n >= 0;
this.n = n;
this.m = 0;
this.directed = directed;
// g初始化为n*n的布尔矩阵, 每一个g[i][j]均为false,
表示没有任和边
// false为boolean型变量的默认值
g = new boolean[n][n];
}
// 返回节点个数
public int V(){ return n;}
// 返回边的个数
public int E(){ return m;}
// 向图中添加一个边
public void addEdge( int v , int w ){
assert v >= 0 && v < n ;
assert w >= 0 && w < n ;
if( hasEdge( v , w ) )
return;
g[v][w] = true;
if( !directed )
g[w][v] = true;
m ++;
}
// 验证图中是否有从v到w的边
boolean hasEdge( int v , int w ){
assert v >= 0 && v < n ;
assert w >= 0 && w < n ;
return g[v][w];
}
// 返回图中一个顶点的所有邻边
// 由于java使用引用机制，返回一个Vector不会带来额外开销,
public Iterable<Integer> adj(int v) {
assert v >= 0 && v < n;
Vector<Integer> adjV = new Vector<Integer>();
for(int i = 0 ; i < n ; i ++ )
if( g[v][i] )
adjV.add(i);
return adjV;
}
}
Src/runoob/graph/SparseGraphIterater.java file code: ¶
package runoob.graph;
import java.util.Vector;
/*\*
\* 邻接表迭代
*/
public class SparseGraphIterater {
private int n; // 节点数
private int m; // 边数
private boolean directed; // 是否为有向图
private Vector<Integer>[] g; // 图的具体数据
// 构造函数
public SparseGraphIterater( int n , boolean directed ){
assert n >= 0;
this.n = n;
this.m = 0; // 初始化没有任何边
this.directed = directed;
// g初始化为n个空的vector, 表示每一个g[i]都为空, 即没有任和边
g = (Vector<Integer>[])new Vector[n];
for(int i = 0 ; i < n ; i ++)
g[i] = new Vector<Integer>();
}
public int V(){ return n;} // 返回节点个数
public int E(){ return m;} // 返回边的个数
// 向图中添加一个边
public void addEdge( int v, int w ){
assert v >= 0 && v < n ;
assert w >= 0 && w < n ;
g[v].add(w);
if( v != w && !directed )
g[w].add(v);
m ++;
}
// 验证图中是否有从v到w的边
boolean hasEdge( int v , int w ){
assert v >= 0 && v < n ;
assert w >= 0 && w < n ;
for( int i = 0 ; i < g[v].size() ; i ++ )
if( g[v].elementAt(i) == w )
return true;
return false;
}
// 返回图中一个顶点的所有邻边
// 由于java使用引用机制，返回一个Vector不会带来额外开销,
public Iterable<Integer> adj(int v) {
assert v >= 0 && v < n;
return g[v];
}
}