【LeetCode】Find Minimum in Rotated Sorted Array 解题报告

今天看到LeetCode OJ题目下方多了“Show Tags”功能。我觉着挺好，方便刚開始学习的人分类练习。同一时候也是解题时的思路提示。

【题目】

Suppose a sorted array is rotated at some pivot unknown to you beforehand.

(i.e., 0 1 2 4 5 6 7 might become 4 5 6 7 0 1 2).

Find the minimum element.

You may assume no duplicate exists in the array.

【解法】

题目比較简单，直接看代码吧，可是要想把代码写得美丽并不easy啊。

O(n)非常好写，O(lgn)要好好捋捋思路。

public class Solution {
    // O(n) simple
    public int findMin1(int[] num) {
        int len = num.length;
        if (len == 1) {
            return num[0];
        }
        
        for (int i = 1; i < len; i++) {
            if (num[i] < num[i-1]) {
                return num[i];
            }
        }
        
        return num[0];
        
        // 尼玛，看成找中间数了
        // if (len % 2 != 0) { //len is odd
        //     return num[(begin+len/2)%len];
        // } else {    //len is even
        //     return (num[(begin+len/2-1)%len] + num[(begin+len/2)%len]) / 2;
        // }
    }
    
    
    // O(lgn) not that good
    public int findMin2(int[] num) {
        int len = num.length;
        if (len == 1) return num[0];
        
        int left = 0, right = len-1;
        while (left < right) {
            if ((right-left) == 1) return Math.min(num[left], num[right]);
            
            if (num[left] <= num[right]) return num[left];
            
            int mid = (left + right) / 2;
            if (num[mid] < num[right]) {
                right = mid;
            } else if (num[left] < num[mid]) {
                left = mid;
            }
        }
        
        return num[left];
    }
    
    
    // O(lgn) optimized iteratively
    public int findMin3(int[] num) {
        int len = num.length;
        if (len == 1) return num[0];
        int left = 0, right = len-1;
        while (num[left] > num[right]) { // good idea
            int mid = (left + right) / 2;
            if (num[mid] > num[right]) {
                left = mid + 1;
            } else {
                right = mid; // be careful, not mid-1, as num[mid] maybe the minimum
            }
        }
        return num[left];
    }
    
    
    // O(lgn) optimized recursively
    public int findMin(int[] num) {
        return find(num, 0, num.length-1);
    }
    
    public int find(int[] num, int left, int right) {
        if (num[left] <= num[right]) {
            return num[left];
        }
        int mid = (left + right) / 2;
        if (num[mid] > num[right]) {
            return find(num, mid+1, right);
        }
        return find(num, left, mid);
    }
}