LeetCode 164. Maximum Gap
原题链接在这里:https://leetcode.com/problems/maximum-gap/
题目:
Given an unsorted array, find the maximum difference between the successive elements in its sorted form.
Try to solve it in linear time/space.
Return 0 if the array contains less than 2 elements.
You may assume all elements in the array are non-negative integers and fit in the 32-bit signed integer range.
题解:
桶排序(bucket sort)
假设有N个元素A到B.
bucket(桶)的大小bucketLen = max(1,(B - A) / (N - 1)), 注意bucketLen为0的情况,则最多会有(B - A) / bucketLen + 1个桶
对于数组中的任意整数K, 很容易通过算式loc = (K - A) / bucketLen找出其桶的位置,然后维护每一个桶的最大值和最小值
由于同一个桶内的元素之间的差值至多为bucketLen - 1,因此最终答案不会从同一个桶中选择,否则整体的range达不到B-A.
对于每一个非空的桶p,找出下一个非空的桶q,则q.min - p.max可能就是备选答案。返回所有这些可能值中的最大值。
Note: corner case [1,1,1,1]若元素都相同,range就是0,16行算bucket时需要保持bucket的长度大于等于1.否则17行就有除以0的error.
同时此情况maxGap = 0. 所以maxGap的初始化是0而不是Integer.MIN_VALUE.
Time Complexity: O(n).
Space O(n).
AC Java:
1 public class Solution { 2 public int maximumGap(int[] nums) { 3 if(nums == null || nums.length < 2){ 4 return 0; 5 } 6 //Calculate the range 7 int max = Integer.MIN_VALUE; 8 int min = Integer.MAX_VALUE; 9 int len = nums.length; 10 for(int i = 0; i<len; i++){ 11 max = Math.max(max,nums[i]); 12 min = Math.min(min,nums[i]); 13 } 14 15 //bucket length and number 16 int bucketLen = Math.max(1,(max-min)/(len-1)); //error 17 int buckNum = (max-min)/bucketLen + 1; 18 19 //calculate nums[i] position in buckets and maintain the maximun and minmum of each bucket 20 int [] maxArr = new int[buckNum]; 21 int [] minArr = new int[buckNum]; 22 Arrays.fill(maxArr, Integer.MIN_VALUE); 23 Arrays.fill(minArr, Integer.MAX_VALUE); 24 for(int i = 0; i<len; i++){ 25 int loc = (nums[i]-min)/bucketLen; 26 maxArr[loc] = Math.max(maxArr[loc],nums[i]); 27 minArr[loc] = Math.min(minArr[loc],nums[i]); 28 } 29 //Calculate maximum gap 30 int maxGap = 0; 31 int preMax = maxArr[0]; 32 for(int i = 1; i<buckNum; i++){ 33 if(maxArr[i] == Integer.MIN_VALUE || minArr[i] == Integer.MAX_VALUE){ 34 continue; 35 } 36 maxGap = Math.max(maxGap, minArr[i]-preMax); 37 preMax = maxArr[i]; 38 } 39 return maxGap; 40 } 41 }