Kruskal算法
1.算法简单描述
1).记Graph中有v个顶点,e个边
2).新建图Graphnew,Graphnew中拥有原图中相同的e个顶点,但没有边
3).将原图Graph中所有e个边按权值从小到大排序
4).循环:从权值最小的边开始遍历每条边 直至图Graph中所有的节点都在同一个连通分量中
if 这条边连接的两个节点于图Graphnew中不在同一个连通分量中
添加这条边到图Graphnew中
public class KruskalMST { private static final double FLOATING_POINT_EPSILON = 1E-12; private double weight; // weight of MST private Queue<Edge> mst = new Queue<Edge>(); // edges in MST /** * Compute a minimum spanning tree (or forest) of an edge-weighted graph. * @param G the edge-weighted graph */ public KruskalMST(EdgeWeightedGraph G) { // more efficient to build heap by passing array of edges MinPQ<Edge> pq = new MinPQ<Edge>(); for (Edge e : G.edges()) { pq.insert(e); } // run greedy algorithm UF uf = new UF(G.V()); while (!pq.isEmpty() && mst.size() < G.V() - 1) { Edge e = pq.delMin(); int v = e.either(); int w = e.other(v); if (uf.find(v) != uf.find(w)) { // v-w does not create a cycle uf.union(v, w); // merge v and w components mst.enqueue(e); // add edge e to mst weight += e.weight(); } } // check optimality conditions assert check(G); } /** * Returns the edges in a minimum spanning tree (or forest). * @return the edges in a minimum spanning tree (or forest) as * an iterable of edges */ public Iterable<Edge> edges() { return mst; } /** * Returns the sum of the edge weights in a minimum spanning tree (or forest). * @return the sum of the edge weights in a minimum spanning tree (or forest) */ public double weight() { return weight; } // check optimality conditions (takes time proportional to E V lg* V) private boolean check(EdgeWeightedGraph G) { // check total weight double total = 0.0; for (Edge e : edges()) { total += e.weight(); } if (Math.abs(total - weight()) > FLOATING_POINT_EPSILON) { System.err.printf("Weight of edges does not equal weight(): %f vs. %f\n", total, weight()); return false; } // check that it is acyclic UF uf = new UF(G.V()); for (Edge e : edges()) { int v = e.either(), w = e.other(v); if (uf.find(v) == uf.find(w)) { System.err.println("Not a forest"); return false; } uf.union(v, w); } // check that it is a spanning forest for (Edge e : G.edges()) { int v = e.either(), w = e.other(v); if (uf.find(v) != uf.find(w)) { System.err.println("Not a spanning forest"); return false; } } // check that it is a minimal spanning forest (cut optimality conditions) for (Edge e : edges()) { // all edges in MST except e uf = new UF(G.V()); for (Edge f : mst) { int x = f.either(), y = f.other(x); if (f != e) uf.union(x, y); } // check that e is min weight edge in crossing cut for (Edge f : G.edges()) { int x = f.either(), y = f.other(x); if (uf.find(x) != uf.find(y)) { if (f.weight() < e.weight()) { System.err.println("Edge " + f + " violates cut optimality conditions"); return false; } } } } return true; } /** * Unit tests the {@code KruskalMST} data type. * * @param args the command-line arguments */ public static void main(String[] args) { In in = new In(args[0]); EdgeWeightedGraph G = new EdgeWeightedGraph(in); KruskalMST mst = new KruskalMST(G); for (Edge e : mst.edges()) { StdOut.println(e); } StdOut.printf("%.5f\n", mst.weight()); } }