LeetCode 261. Graph Valid Tree(判断图是否为树)
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原题网址:https://leetcode.com/problems/graph-valid-tree/
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:
- Given
n = 5
andedges = [[0, 1], [1, 2], [3, 4]]
, what should your return? Is this case a valid tree? - According to the definition of tree on Wikipedia: “a tree is an undirected graph in which any two vertices are connected by exactly one path. In other words, any connected graph without simple cycles is a tree.”
注意,这里的树是普通的树,不是二叉树!
思路:要判断一个图是否为树,首先要知道树的定义。一棵树必须具备如下特性:
(1)是一个全连通图(所有节点相通)
(2)无回路
其中(2)等价于:(3)图的边数=节点数-1
因此我们可以利用特性(1)(2)或者(1)(3)来判断。
方法一:广度优先搜索。要判断连通性,广度优先搜索法是一个天然的选择,时间复杂度O(n),空间复杂度O(n)。
public class Solution
public boolean validTree(int n, int[][] edges)
Map<Integer, Set<Integer>> graph = new HashMap<>();
for(int i=0; i<edges.length; i++)
for(int j=0; j<2; j++)
Set<Integer> pairs = graph.get(edges[i][j]);
if (pairs == null)
pairs = new HashSet<>();
graph.put(edges[i][j], pairs);
pairs.add(edges[i][1-j]);
Set<Integer> visited = new HashSet<>();
Set<Integer> current = new HashSet<>();
visited.add(0);
current.add(0);
while (!current.isEmpty())
Set<Integer> next = new HashSet<>();
for(Integer node: current)
Set<Integer> pairs = graph.get(node);
if (pairs == null) continue;
for(Integer pair: pairs)
if (visited.contains(pair)) return false;
next.add(pair);
visited.add(pair);
graph.get(pair).remove(node);
current = next;
return visited.size() == n;
方法二:深度优先搜索,搜索目标是遍历全部节点。参考文章:http://buttercola.blogspot.com/2015/08/leetcode-graph-valid-tree.html
public class Solution
private boolean[] visited;
private int visits = 0;
private boolean isTree = true;
private void check(int prev, int curr, List<Integer>[] graph)
if (!isTree) return;
if (visited[curr])
isTree = false;
return;
visited[curr] = true;
visits ++;
for(int next: graph[curr])
if (next == prev) continue;
check(curr, next, graph);
if (!isTree) return;
public boolean validTree(int n, int[][] edges)
visited = new boolean[n];
List<Integer>[] graph = new List[n];
for(int i=0; i<n; i++) graph[i] = new ArrayList<>();
for(int[] edge: edges)
graph[edge[0]].add(edge[1]);
graph[edge[1]].add(edge[0]);
check(-1, 0, graph);
return isTree && visits == n;
方法三:按节点大小对边进行排序,原理类似并查集。
public class Solution
public boolean validTree(int n, int[][] edges)
if (edges.length != n-1) return false;
Arrays.sort(edges, new Comparator<int[]>()
@Override
public int compare(int[] e1, int[] e2)
return e1[0] - e2[0];
);
int[] sets = new int[n];
for(int i=0; i<n; i++) sets[i] = i;
for(int i=0; i<edges.length; i++)
if (sets[edges[i][0]] == sets[edges[i][1]]) return false;
if (sets[edges[i][0]] == 0)
sets[edges[i][1]] = 0;
else if (sets[edges[i][1]] == 0)
sets[edges[i][0]] = 0;
else
sets[edges[i][1]] = sets[edges[i][0]];
return true;
方法四:Union-Find
public class Solution
public boolean validTree(int n, int[][] edges)
if (edges.length != n-1) return false;
int[] roots = new int[n];
for(int i=0; i<n; i++) roots[i] = i;
for(int i=0; i<edges.length; i++)
int root1 = root(roots, edges[i][0]);
int root2 = root(roots, edges[i][1]);
if (root1 == root2) return false;
roots[root2] = root1;
return true;
private int root(int[] roots, int id)
if (id == roots[id]) return id;
return root(roots, roots[id]);
参考文章:
http://blog.csdn.net/dm_vincent/article/details/7655764
http://www.elvisyu.com/graph-valid-tree-union-and-find/
http://blog.csdn.net/pointbreak1/article/details/48796691
http://buttercola.blogspot.com/2015/08/leetcode-graph-valid-tree.html
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LeetCode 261. Graph Valid Tree(判断图是否为树)