内容简介:For an undirected graph with tree characteristics, we can choose any node as the root. The result graph is then a rooted tree. Among all possible rooted trees, those with minimum height are called minimum height trees (MHTs). Given such a graph, write a fu
Description
For an undirected graph with tree characteristics, we can choose any node as the root. The result graph is then a rooted tree. Among all possible rooted trees, those with minimum height are called minimum height trees (MHTs). Given such a graph, write a function to find all the MHTs and return a list of their root labels.
Format
The graph contains n nodes which are labeled from 0 to n - 1. You will be given the number n and a list of undirected edges (each edge is a pair of labels).
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.
Example 1 :
Input: n = 4, edges = [[1, 0], [1, 2], [1, 3]] 0 | 1 / \ 2 3 Output: [1]
Example 2 :
Input: n = 6, edges = [[0, 3], [1, 3], [2, 3], [4, 3], [5, 4]] 0 1 2 \ | / 3 | 4 | 5 Output: [3, 4]
Note:
- 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.”
- The height of a rooted tree is the number of edges on the longest downward path between the root and a leaf.
描述
对于一个具有树特征的无向图,我们可选择任何一个节点作为根。图因此可以成为树,在所有可能的树中,具有最小高度的树被称为最小高度树。给出这样的一个图,写出一个函数找到所有的最小高度树并返回他们的根节点。
注意:
该图包含 n 个节点,标记为 0 到 n - 1。给定数字 n 和一个无向边 edges 列表(每一个边都是一对标签)。
你可以假设没有重复的边会出现在 edges 中。由于所有的边都是无向边, [0, 1]和 [1, 0] 是相同的,因此不会同时出现在 edges 里。
示例 1:
输入: n = 4, edges = [[1, 0], [1, 2], [1, 3]] 0 | 1 / \ 2 3 输出: [1]
示例 2:
输入: n = 6, edges = [[0, 3], [1, 3], [2, 3], [4, 3], [5, 4]] 0 1 2 \ | / 3 | 4 | 5 输出: [3, 4]
说明:
- 根据树的定义,树是一个无向图,其中任何两个顶点只通过一条路径连接。 换句话说,一个任何没有简单环路的连通图都是一棵树。
- 树的高度是指根节点和叶子节点之间最长向下路径上边的数量。
思路
- 最小高度树的根节点是图中最长路径的中间节点.
- 我们用一个 List[set()] 的结构存储每个节点可以访问到的其他节点。一般情况下应该使用字典,以节点为键,能够遍历到的节点组成的哈希set为键,但由于题中的节点是从0开始的数字,我们可以用 List 来代替,索引就是键。
- 最长路径的中间节点最多会有两个:最长路径有奇数个节点,则中间节点有 1 个;最长路径有偶数个节点,则中间节点有 2 个。
- 基本思路是:找到所有的叶子节点,去掉所有叶子节点,找到新的所有叶子节点,去掉所有叶子节点 ... 直到剩下的节点个数小于等于2个。
# -*- coding: utf-8 -*- # @Author: 何睿 # @Create Date: 2019-02-17 13:46:09 # @Last Modified by: 何睿 # @Last Modified time: 2019-02-17 14:15:30 class Solution: def findMinHeightTrees(self, n: 'int',edges: 'List[List[int]]') -> 'List[int]': # 如果只有一个节点,直接返回当前节点 if n == 1: return [0] # 路径:记录每个节点可以访问到的所有节点 type:list[set()] # 更一般的情况是利用字典实现,利用节点作为键,节点能够走到的所有节点 # 组成的set作为值,但是题中得节点为从0开始的数值,因此可以用list代替字典 paths = [set() for _ in range(n)] # 找到每个节点可以走到的下一个节点 for node1, node2 in edges: paths[node1].add(node2) paths[node2].add(node1) # 找到所有的叶子节点 leaves = [node for node in range(n) if len(paths[node]) == 1] # root用于记录剩下的节点 roots = n while roots > 2: # 更新剩下的节点个数 roots -= len(leaves) # 新的叶子节点 newleaves = [] for node in leaves: # 获取叶节点的父节点 parent = paths[node].pop() # 从叶节点的父节点中删除当前节点 paths[parent].remove(node) # 如果当前节点的父节点只能访问一个节点,则添加到新叶节点中 if len(paths[parent]) == 1: newleaves.append(parent) leaves = newleaves return leaves
源代码文件在 这里 .
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