• 0240. Search a 2D Matrix II (M)


    Search a 2D Matrix II (M)

    题目

    Write an efficient algorithm that searches for a value in an m x n matrix. This matrix has the following properties:

    • Integers in each row are sorted in ascending from left to right.
    • Integers in each column are sorted in ascending from top to bottom.

    Example:

    Consider the following matrix:

    [
      [1,   4,  7, 11, 15],
      [2,   5,  8, 12, 19],
      [3,   6,  9, 16, 22],
      [10, 13, 14, 17, 24],
      [18, 21, 23, 26, 30]
    ]
    

    Given target = 5, return true.

    Given target = 20, return false.


    题意

    判断在一个行元素递增、列元素也递增的矩阵中能否找到目标值。

    思路

    二分法:本来想着先用二分找到行数的下界,但发现即使找到了下界down,也需要再重新遍历 0 - (down-1) 这些行,对每行进行二分查找。这样不如直接从上到下遍历所有行,如果当前行行尾元素小于target,说明该行可以跳过;如果当前行行首元素大于target,说明剩余行不可能存在target,可以直接跳出循环;其余情况则对当前行进行二分查找。时间复杂度为(O(MlogN))

    分治法:从矩阵的左下角元素X出发,根据矩阵的性质,如果target>X,以X作一条垂直线,则target只可能在该线右侧的矩阵里;如果target<X,以X作一条水平线,则target只可能在该线上侧的矩阵里。因此每次都可以将问题转化为在一个更小的矩阵里找到target。当然也可以以矩阵的右上角元素作为起点。时间复杂度为(O(M+N))


    代码实现

    Java

    二分法

    class Solution {
        public boolean searchMatrix(int[][] matrix, int target) {
            if (matrix.length == 0 || matrix[0].length == 0) {
                return false;
            }
    
            int m = matrix.length, n = matrix[0].length;
    
            for (int i = 0; i < m; i++) {
                if (matrix[i][n - 1] < target) {
                    continue;
                } else if (matrix[i][0] > target) {
                    break;
                } else {
                    int left = 0, right = n - 1;
                    while (left <= right) {
                        int mid = (right - left) / 2 + left;
                        if (matrix[i][mid] < target) {
                            left = mid + 1;
                        } else if (matrix[i][mid] > target) {
                            right = mid - 1;
                        } else {
                            return true;
                        }
                    }
                }
            }
    
            return false;
        }
    }
    

    分治法

    class Solution {
        public boolean searchMatrix(int[][] matrix, int target) {
            if (matrix.length == 0 || matrix[0].length == 0) {
                return false;
            }
    
            int m = matrix.length, n = matrix[0].length;
    
            int i = m - 1, j = 0;
    
            while (i >= 0 && j < n) {
                if (matrix[i][j] < target) {
                    j++;
                } else if (matrix[i][j] > target) {
                    i--;
                } else {
                    return true;
                } 
            }
    
            return false;
        }
    }
    

    JavaScript

    /**
     * @param {number[][]} matrix
     * @param {number} target
     * @return {boolean}
     */
    var searchMatrix = function (matrix, target) {
      const m = matrix.length
      const n = matrix[0].length
    
      let i = m - 1
      let j = 0
    
      while (i >= 0 && j < n) {
        if (matrix[i][j] < target) {
          j++
        } else if (matrix[i][j] > target) {
          i--
        } else {
          return true
        }
      }
    
      return false
    }
    
  • 相关阅读:
    vue-router总结2
    vue-router总结
    react中的路由模块化
    react路由嵌套
    Javascript设计模式之我见:迭代器模式
    Javascript设计模式之我见:观察者模式
    【C语言】格式符
    【编译原理】代码在编译器中的完整处理过程
    【数据库】增删改查操作
    测试
  • 原文地址:https://www.cnblogs.com/mapoos/p/14436732.html
Copyright © 2020-2023  润新知