• LeetCode 778. Swim in Rising Water


    原题链接在这里:https://leetcode.com/problems/swim-in-rising-water/

    题目:

    On an N x N grid, each square grid[i][j] represents the elevation at that point (i,j).

    Now rain starts to fall. At time t, the depth of the water everywhere is t. You can swim from a square to another 4-directionally adjacent square if and only if the elevation of both squares individually are at most t. You can swim infinite distance in zero time. Of course, you must stay within the boundaries of the grid during your swim.

    You start at the top left square (0, 0). What is the least time until you can reach the bottom right square (N-1, N-1)?

    Example 1:

    Input: [[0,2],[1,3]]
    Output: 3
    Explanation:
    At time 0, you are in grid location (0, 0).
    You cannot go anywhere else because 4-directionally adjacent neighbors have a higher elevation than t = 0.
    
    You cannot reach point (1, 1) until time 3.
    When the depth of water is 3, we can swim anywhere inside the grid.
    

    Example 2:

    Input: [[0,1,2,3,4],[24,23,22,21,5],[12,13,14,15,16],[11,17,18,19,20],[10,9,8,7,6]]
    Output: 16
    Explanation:
     0  1  2  3  4
    24 23 22 21  5
    12 13 14 15 16
    11 17 18 19 20
    10  9  8  7  6
    
    The final route is marked in bold.
    We need to wait until time 16 so that (0, 0) and (4, 4) are connected.
    

    Note:

    1. 2 <= N <= 50.
    2. grid[i][j] is a permutation of [0, ..., N*N - 1].

    题解:

    Eventually, we want to hit the bottom right.

    Every time we try to find the minimum surroundings.

    Keep a minHeap based on elevation, when poll out from minHeap, update max elevation. 

    And if current position is bottom right, return res.

    Otherwise, for 4 directions, check if it is not visited, add {x, y, elevation} to minHeap.

    Time Complexity: O(N^2*logN). N = grid.length.

    Space: O(N^2). heap size.

    AC Java:

     1 class Solution {
     2     public int swimInWater(int[][] grid) {
     3         int N = grid.length;
     4         PriorityQueue<int []> minHeap = new PriorityQueue<>((a, b) -> a[2] - b[2]);
     5         boolean [][] visited = new boolean[N][N];
     6         
     7         minHeap.add(new int[]{0, 0, grid[0][0]});
     8         visited[0][0] = true;
     9         int res = 0;
    10         int[][] dirs = new int[][]{{1, 0}, {0, 1}, {-1, 0}, {0, -1}};
    11         
    12         while(!minHeap.isEmpty()){
    13             int [] cur = minHeap.poll();
    14             res = Math.max(res, cur[2]);
    15             if(cur[0] == N - 1 && cur[1] == N - 1){
    16                 return res;
    17             }
    18             
    19             for(int [] dir : dirs){
    20                 int x = cur[0] + dir[0];
    21                 int y = cur[1] + dir[1];
    22                 if(x < 0 || x >= N || y < 0 || y >= N || visited[x][y]){
    23                     continue;
    24                 }
    25                 
    26                 visited[x][y] = true;
    27                 minHeap.add(new int[]{x, y, grid[x][y]});
    28             }    
    29         }
    30         
    31         return -1;
    32     }
    33 }
  • 相关阅读:
    UIView的clipsToBounds属性,layoutSubViews及触摸事件传递(默认情况下)总结
    ISO中运行时简单使用及KVC补充
    IOS中UISearchBar的使用
    oc的block
    oc的协议(protocol)
    oc的分类category
    oc内存的理解
    oc笔记(转载)
    oc对象中属性总结
    servlet,struts1,struts2,spring
  • 原文地址:https://www.cnblogs.com/Dylan-Java-NYC/p/12248820.html
Copyright © 2020-2023  润新知