2019-03-08 23:06:28 +08:00
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<!-- GFM-TOC -->
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* [前言](#前言)
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* [Quick Find](#quick-find)
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* [Quick Union](#quick-union)
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* [加权 Quick Union](#加权-quick-union)
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* [路径压缩的加权 Quick Union](#路径压缩的加权-quick-union)
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* [比较](#比较)
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<!-- GFM-TOC -->
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# 前言
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用于解决动态连通性问题,能动态连接两个点,并且判断两个点是否连通。
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2019-03-20 13:07:49 +08:00
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<div align="center"> <img src="https://gitee.com/CyC2018/CS-Notes/raw/master/docs/pics/9d0a637c-6a8f-4f5a-99b9-fdcfa26793ff.png" width="400"/> </div><br>
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2019-03-08 23:06:28 +08:00
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| 方法 | 描述 |
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| :---: | :---: |
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| UF(int N) | 构造一个大小为 N 的并查集 |
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| void union(int p, int q) | 连接 p 和 q 节点 |
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| int find(int p) | 查找 p 所在的连通分量编号 |
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| boolean connected(int p, int q) | 判断 p 和 q 节点是否连通 |
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```java
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public abstract class UF {
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protected int[] id;
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public UF(int N) {
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id = new int[N];
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for (int i = 0; i < N; i++) {
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id[i] = i;
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}
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}
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public boolean connected(int p, int q) {
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return find(p) == find(q);
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}
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public abstract int find(int p);
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public abstract void union(int p, int q);
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}
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```
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# Quick Find
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可以快速进行 find 操作,也就是可以快速判断两个节点是否连通。
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需要保证同一连通分量的所有节点的 id 值相等。
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但是 union 操作代价却很高,需要将其中一个连通分量中的所有节点 id 值都修改为另一个节点的 id 值。
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2019-03-20 13:07:49 +08:00
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<div align="center"> <img src="https://gitee.com/CyC2018/CS-Notes/raw/master/docs/pics/8f0cc500-5994-4c7a-91a9-62885d658662.png" width="350"/> </div><br>
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2019-03-08 23:06:28 +08:00
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```java
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public class QuickFindUF extends UF {
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public QuickFindUF(int N) {
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super(N);
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}
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@Override
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public int find(int p) {
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return id[p];
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}
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@Override
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public void union(int p, int q) {
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int pID = find(p);
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int qID = find(q);
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if (pID == qID) {
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return;
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}
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for (int i = 0; i < id.length; i++) {
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if (id[i] == pID) {
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id[i] = qID;
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}
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}
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}
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}
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```
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# Quick Union
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可以快速进行 union 操作,只需要修改一个节点的 id 值即可。
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但是 find 操作开销很大,因为同一个连通分量的节点 id 值不同,id 值只是用来指向另一个节点。因此需要一直向上查找操作,直到找到最上层的节点。
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2019-03-20 13:07:49 +08:00
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<div align="center"> <img src="https://gitee.com/CyC2018/CS-Notes/raw/master/docs/pics/5d4a5181-65fb-4bf2-a9c6-899cab534b44.png" width="350"/> </div><br>
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2019-03-08 23:06:28 +08:00
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```java
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public class QuickUnionUF extends UF {
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public QuickUnionUF(int N) {
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super(N);
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}
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@Override
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public int find(int p) {
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while (p != id[p]) {
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p = id[p];
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}
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return p;
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}
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@Override
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public void union(int p, int q) {
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int pRoot = find(p);
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int qRoot = find(q);
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if (pRoot != qRoot) {
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id[pRoot] = qRoot;
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}
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}
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}
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```
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这种方法可以快速进行 union 操作,但是 find 操作和树高成正比,最坏的情况下树的高度为节点的数目。
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2019-03-20 13:07:49 +08:00
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<div align="center"> <img src="https://gitee.com/CyC2018/CS-Notes/raw/master/docs/pics/bfbb11e2-d208-4efa-b97b-24cd40467cd8.png" width="130"/> </div><br>
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2019-03-08 23:06:28 +08:00
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# 加权 Quick Union
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为了解决 quick-union 的树通常会很高的问题,加权 quick-union 在 union 操作时会让较小的树连接较大的树上面。
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理论研究证明,加权 quick-union 算法构造的树深度最多不超过 logN。
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2019-03-20 13:07:49 +08:00
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<div align="center"> <img src="https://gitee.com/CyC2018/CS-Notes/raw/master/docs/pics/a4c17d43-fa5e-4935-b74e-147e7f7e782c.png" width="170"/> </div><br>
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2019-03-08 23:06:28 +08:00
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```java
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public class WeightedQuickUnionUF extends UF {
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// 保存节点的数量信息
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private int[] sz;
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public WeightedQuickUnionUF(int N) {
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super(N);
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this.sz = new int[N];
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for (int i = 0; i < N; i++) {
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this.sz[i] = 1;
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}
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}
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@Override
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public int find(int p) {
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while (p != id[p]) {
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p = id[p];
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}
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return p;
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}
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@Override
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public void union(int p, int q) {
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int i = find(p);
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int j = find(q);
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if (i == j) return;
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if (sz[i] < sz[j]) {
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id[i] = j;
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sz[j] += sz[i];
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} else {
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id[j] = i;
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sz[i] += sz[j];
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}
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}
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}
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```
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# 路径压缩的加权 Quick Union
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在检查节点的同时将它们直接链接到根节点,只需要在 find 中添加一个循环即可。
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# 比较
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| 算法 | union | find |
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| :---: | :---: | :---: |
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| Quick Find | N | 1 |
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| Quick Union | 树高 | 树高 |
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| 加权 Quick Union | logN | logN |
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| 路径压缩的加权 Quick Union | 非常接近 1 | 非常接近 1 |
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2019-03-11 09:50:13 +08:00
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2019-03-20 00:00:07 +08:00
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2019-03-18 10:34:46 +08:00
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