LeetCode 690. Employee Importance
原题链接在这里:https://leetcode.com/problems/employee-importance/description/
题目:
You are given a data structure of employee information, which includes the employee's unique id, his importance value and his directsubordinates' id.
For example, employee 1 is the leader of employee 2, and employee 2 is the leader of employee 3. They have importance value 15, 10 and 5, respectively. Then employee 1 has a data structure like [1, 15, [2]], and employee 2 has [2, 10, [3]], and employee 3 has [3, 5, []]. Note that although employee 3 is also a subordinate of employee 1, the relationship is not direct.
Now given the employee information of a company, and an employee id, you need to return the total importance value of this employee and all his subordinates.
Example 1:
Input: [[1, 5, [2, 3]], [2, 3, []], [3, 3, []]], 1 Output: 11 Explanation: Employee 1 has importance value 5, and he has two direct subordinates: employee 2 and employee 3. They both have importance value 3. So the total importance value of employee 1 is 5 + 3 + 3 = 11.
Note:
- One employee has at most one direct leader and may have several subordinates.
- The maximum number of employees won't exceed 2000.
题解:
类似Clone Graph, Nested List Weight Sum.
可以采用BFS. 每层的Employee挨个加进去.
Time Complexity: O(n). n是root id的所有下属个数, 包括直系下属和非直系下属.
Space: O(employees.size()). 全部员工生成的map.
AC Java:
1 /* 2 // Employee info 3 class Employee { 4 // It's the unique id of each node; 5 // unique id of this employee 6 public int id; 7 // the importance value of this employee 8 public int importance; 9 // the id of direct subordinates 10 public List<Integer> subordinates; 11 }; 12 */ 13 class Solution { 14 public int getImportance(List<Employee> employees, int id) { 15 int res = 0; 16 17 HashMap<Integer, Employee> hm = new HashMap<Integer, Employee>(); 18 for(Employee employee : employees){ 19 hm.put(employee.id, employee); 20 } 21 22 LinkedList<Employee> que = new LinkedList<Employee>(); 23 que.add(hm.get(id)); 24 while(!que.isEmpty()){ 25 Employee cur = que.poll(); 26 res += cur.importance; 27 for(int subId : cur.subordinates){ 28 que.add(hm.get(subId)); 29 } 30 } 31 32 return res; 33 } 34 }
AC Python:
1 """ 2 # Definition for Employee. 3 class Employee: 4 def __init__(self, id: int, importance: int, subordinates: List[int]): 5 self.id = id 6 self.importance = importance 7 self.subordinates = subordinates 8 """ 9 10 class Solution: 11 def getImportance(self, employees: List['Employee'], id: int) -> int: 12 hm = {e.id : e for e in employees} 13 que = deque([id]) 14 res = 0 15 while que: 16 cur = hm[que.popleft()] 17 res += cur.importance 18 que.extend(cur.subordinates) 19 return res 20
DFS.逐层往深dfs.
Time Complexity: O(n). n是root id的所有下属个数, 包括直系下属和非直系下属.
Space: O(employees.size()). 全部员工生成的map.
AC Java:
1 /* 2 // Employee info 3 class Employee { 4 // It's the unique id of each node; 5 // unique id of this employee 6 public int id; 7 // the importance value of this employee 8 public int importance; 9 // the id of direct subordinates 10 public List<Integer> subordinates; 11 }; 12 */ 13 class Solution { 14 public int getImportance(List<Employee> employees, int id) { 15 HashMap<Integer, Employee> hm = new HashMap<Integer, Employee>(); 16 for(Employee employee : employees){ 17 hm.put(employee.id, employee); 18 } 19 20 return dfs(hm, id); 21 } 22 23 private int dfs(HashMap<Integer, Employee> hm, int id){ 24 int res = 0; 25 Employee cur = hm.get(id); 26 27 res += cur.importance; 28 for(int subId : cur.subordinates){ 29 res += dfs(hm, subId); 30 } 31 return res; 32 } 33 }
AC Python:
1 """ 2 # Definition for Employee. 3 class Employee: 4 def __init__(self, id: int, importance: int, subordinates: List[int]): 5 self.id = id 6 self.importance = importance 7 self.subordinates = subordinates 8 """ 9 10 class Solution: 11 def getImportance(self, employees: List['Employee'], id: int) -> int: 12 hm = {e.id : e for e in employees} 13 14 def dfs(hm, id): 15 cur = hm[id] 16 res = cur.importance 17 for next in cur.subordinates: 18 res += dfs(hm, next) 19 return res 20 21 return dfs(hm, id)