• 261. Graph Valid Tree


    题目:

    Given n nodes labeled from 0 to n - 1 and a list of undirected edges (each edge is a pair of nodes), write a function to check whether these edges make up a valid tree.

    For example:

    Given n = 5 and edges = [[0, 1], [0, 2], [0, 3], [1, 4]], return true.

    Given n = 5 and edges = [[0, 1], [1, 2], [2, 3], [1, 3], [1, 4]], return false.

    Hint:

    1. Given n = 5 and edges = [[0, 1], [1, 2], [3, 4]], what should your return? Is this case a valid tree? Show More Hint 

    Note: you can assume that no duplicate edges will appear in edges. Since all edges are undirected, [0, 1] is the same as [1, 0] and thus will not appear together in edges.

    链接: http://leetcode.com/problems/graph-valid-tree/

    题解:

    验证输入数组是否能组成一个树。看了一些资料,这属于并查集的问题。首先我们明确一下满足要求的解的条件:

    1. 题目给定了n个node,则假如能组成一棵树,则这棵树的edge数目为n - 1,所以我们一开始要判断edges.length == n - 1
    2. 不可以有环路,即这个无向图必须是acyclic的, 所有的edges最后也只能组成一个connected components

    在判断完edges.length == n - 1后, 我们可以想到使用Union-Find中的Quick-Find。先构造一个长为节点数n的数组id,初始化数组每个元素与他们的index相等。接下来遍历无向图的edges矩阵,假如edges[i][0]和edges[i][1]已经联通,则这个图存在环,我们返回false,否则我们把这两个元素联通起来 - 遍历id数组,将其中所有值为pid的元素值更新为qid。数组遍历结束之后返回true。  Quadratic time还是非常巨大,所以我们还可以继续对这个方法进行优化,接下来的就是Weighted Quick Union + Path Compression了, 留给二刷,继续前进。 收获是接触到了并查集的概念,很高兴。

    Time Complexity - O(n2), Space Complexity - O(n)

    public class Solution {
        public boolean validTree(int n, int[][] edges) {        // dynamic connectivity
            if(n < 0 || edges == null || edges.length != n - 1)
                return false;
            int[] id = new int[n];
            for(int i = 0; i < id.length; i++) {
                id[i] = i;
            }
            
            for(int i = 0; i < edges.length; i++) {
                if(!connected(id, edges[i][0], edges[i][1])) {
                    union(id, edges[i][0], edges[i][1]);
                } else {
                    return false;
                }
            }
            return true;
        }
        
        private boolean connected(int[] id, int p, int q) {
            return id[p] == id[q];
        }
        
        private void union(int[] id, int p, int q) {
            int pid = id[p];
            int qid = id[q];
            for(int i = 0; i < id.length; i++) {
                if(id[i] == pid) {
                    id[i] = qid;
                }
            }
        }
    }

    二刷:

    首先检测边界条件, 是否edges.length == n - 1。 其次转化为无向图检测环路,我们可以使用Union-Find来做。

    下面是Weighted Quick Union + Path Compression,一如Sedgewick大神教授的。

    Java:

    public class Solution {
        private int[] id;
        private int[] sz;
        public boolean validTree(int n, int[][] edges) {
            if (n < 0 || edges == null || edges.length != n - 1) {
                return false;
            }
            id = new int[n];
            sz = new int[n];
            for (int i = 0; i < n; i++) {
                id[i] = i;
                sz[i] = 1;
            }
            for (int i = 0; i < edges.length; i++) {
                if (!isConnected(edges[i][0], edges[i][1])) {
                    union(edges[i][0], edges[i][1]);
                } else {
                    return false;
                }
            }
            return true;
        }
        
        private int getRoot(int i) {
            while (i != id[i]) {
                id[i] = id[id[i]];
                i = id[i];
            }
            return i;
        }
        
        private void union(int i, int j) {
            int rootI = getRoot(i);
            int rootJ = getRoot(j);
            if (rootI == rootJ) {
                return;
            }
            if (sz[rootI] < sz[rootJ]) {
                id[rootI] = rootJ;
                sz[rootJ] += sz[rootI];
            } else {
                id[rootJ] = rootI;
                sz[rootI] += sz[rootJ];
            }
        }
        
        private boolean isConnected(int i, int j) {
            return getRoot(i) == getRoot(j);
        }
    }

    Reference:

    https://en.wikipedia.org/wiki/Disjoint-set_data_structure

    https://www.youtube.com/watch?v=4SZTsQO9d6k&index=3&list=PLe-ggMe31CTexoNYnMhbHaWhQ0dvcy43t

    https://en.wikipedia.org/wiki/Tree_(data_structure)

    http://segmentfault.com/a/1190000003791051

    http://blog.csdn.net/dm_vincent/article/details/7655764

    http://blog.csdn.net/pointbreak1/article/details/48796691

    http://nb4799.neu.edu/wordpress/?p=1143

    http://algorithmsandme.in/2014/06/graphs-detecting-cycle-in-undirected-graph/

    http://www.cs.nyu.edu/courses/summer04/G22.1170-001/6a-Graphs-More.pdf

    https://www.me.utexas.edu/~bard/IP/Handouts/cycles.pdf

    https://www.cs.princeton.edu/~rs/AlgsDS07/01UnionFind.pdf

    http://www.eecs.wsu.edu/~ananth/CptS223/Lectures/UnionFind.pdf

    https://leetcode.com/discuss/52610/8-10-lines-union-find-dfs-and-bfs

    https://leetcode.com/discuss/52563/ac-java-union-find-solution

    https://leetcode.com/discuss/58600/a-java-solution-with-dfs

    https://leetcode.com/discuss/72645/compressed-weighted-quick-union-solution-in-java-2ms

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  • 原文地址:https://www.cnblogs.com/yrbbest/p/5018217.html
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