// 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();
}
double EPSILON = 1E-12;
if (Math.abs(total - weight()) > 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.connected(v, w)) {
System.err.println("Not a forest");
return false;
}
uf.union(v, w);
}
// check that it is a spanning forest
for (Edge e : edges()) {
int v = e.either(), w = e.other(v);
if (!uf.connected(v, 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()) {
int v = e.either(), w = e.other(v);
// 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.connected(x, y)) {
if (f.weight() < e.weight()) {
System.err.println("Edge " + f + " violates cut optimality conditions");
return false;
}
}
}
}
return true;
}
public PrimMST(EdgeWeightedGraph G) {
edgeTo = new Edge[G.V()];
distTo = new double[G.V()];
marked = new boolean[G.V()];
for (int v = 0; v < G.V(); v++) distTo[v] = Double.POSITIVE_INFINITY;
pq = new IndexMinPQ<Double>(G.V());
distTo[0] = 0.0;
pq.insert(0, 0.0); // Initialize pq with 0, weight 0.
while (!pq.isEmpty()) visit(G, pq.delMin()); // Add closest vertex to tree.
}
/**
* Initializes a new edge-weighted graph that is a deep copy of <tt>G</tt>.
*
* @param G the edge-weighted graph to copy
*/
public EdgeWeightedGraph(EdgeWeightedGraph G) {
this(G.V());
this.E = G.E();
for (int v = 0; v < G.V(); v++) {
// reverse so that adjacency list is in same order as original
Stack<Edge> reverse = new Stack<Edge>();
for (Edge e : G.adj[v]) {
reverse.push(e);
}
for (Edge e : reverse) {
adj[v].add(e);
}
}
}
public KruskalMST(EdgeWeightedGraph G) {
mst = new Queue<Edge>();
MaxPQ<Edge> pq = new MaxPQ<Edge>();
for (Edge e : G.edges()) pq.insert(e); // 将所有的边进入优先队列，按照权重升序排列
UF uf = new UF(G.V()); // 构建union-find对象
while (!pq.isEmpty() && mst.size() < G.V() - 1) {
Edge e = pq.delMax(); // 从pq得到权重最小的边和他的顶点
int v = e.either(), w = e.other(v);
if (uf.connected(v, w)) continue; // 忽略失效的边，两个顶点已经在生成树中了
uf.union(v, w); // 否则将两者合并，在一个树中,顶点
mst.enqueue(e); // 将边添加到最小生成树中
}
}
public MyPrimMST(EdgeWeightedGraph G) {
this.G = G;
pq = new IndexMinPQ<Double>(G.V());
disTo = new double[G.V()];
edges = new Bag<Edge>();
for (int i = 0; i < G.V(); ++i) disTo[i] = Double.POSITIVE_INFINITY;
edgeTo = new int[G.V()];
marked = new boolean[G.V()];
disTo[0] = 0.0;
visit(0);
while (!pq.isEmpty()) {
int v = pq.delMin();
weight += disTo[v];
edges.add(new Edge(v, edgeTo[v], disTo[v]));
visit(v);
}
}
KruskalMST(EdgeWeightedGraph G) {
MinPQ<Edge> pq = new MinPQ<Edge>(); // we dont need to pass a new comparator let it
// follow the natural ordering of edges
double temp_wt = 0;
for (Edge e : G.edges()) pq.insert(e);
UF set = 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 (!set.connected(v, w)) {
set.union(v, w);
mst.add(e);
temp_wt += e.weight();
}
}
this.weight = temp_wt;
}
// Kruskal's algorithm
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.connected(v, 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);
}
/**
* Dado un grafo no dirigido y con pesos, ejecuta el algoritmo de Kruskal para la obtención del su
* árbol de cobertura mínima.
*
* @param G Grafo no dirigido con pesos al cual se le deesea obtener su arbol de cobertura mínima.
*/
public void minimumSpanningTree(EdgeWeightedGraph G) // By Kruskal's algorithm
{
LinkedList<Edge> mst = new LinkedList<>();
MinPQ<Edge> pq = new MinPQ<>(G.E());
for (Edge edge : G.edges()) // Bag<Edge> != Comparator<Edge> :c
pq.insert(edge);
UF uf = new UF(G.V());
while (!pq.isEmpty() && mst.size() < G.V() - 1) {
Edge edge = pq.delMin();
int v = edge.either(), w = edge.other(v);
if (!uf.connected(v, w)) {
uf.union(v, w);
mst.add(edge);
}
}
System.out.println("");
for (Edge edge : mst) System.out.println(edge);
}
public LazyPrimMST(EdgeWeightedGraph G) {
pq = new PriorityQueue<>(Collections.reverseOrder());
marked = new boolean[G.V()];
mst = new LinkedList<>();
visit(G, 0);
while (!pq.isEmpty()) {
Edge e = pq.poll();
int v = e.either();
int w = e.other(v);
if (marked[v] && marked[w]) continue;
mst.offer(e);
if (!marked[v]) visit(G, v);
if (!marked[w]) visit(G, w);
}
}
public LazyPrimMST(EdgeWeightedGraph G) {
pq = new MinPQ<Edge>();
marked = new boolean[G.V()];
mst = new Queue<Edge>();
visit(G, 0); // assumes G is connected (see ex. 4.3.22)
while (!pq.isEmpty()) {
Edge e = pq.delMin(); // Get lowest-weight from pq.
int v = e.either();
int w = e.other(v);
if (marked[v] && marked[w]) {
continue; // Skip if ineligible
}
mst.enqueue(e); // Add edge to tree
if (!marked[v]) { // Add vertex to tree (either v or w).
visit(G, v);
}
if (!marked[w]) {
visit(G, w);
}
}
}