标签:
Given an array of n positive integers and a positive integer s, find the minimal length of a subarray of which the sum ≥ s. If there isn‘t one, return 0 instead. For example, given the array [2,3,1,2,4,3] and s = 7, the subarray [4,3] has the minimal length under the problem constraint. click to show more practice. More practice: If you have figured out the O(n) solution, try coding another solution of which the time complexity is O(n log n).
Haven‘t think about the O(nlogn) solution.
O(n) solution is to maintain a window
1 public class Solution { 2 public int minSubArrayLen(int s, int[] nums) { 3 int minWin = Integer.MAX_VALUE; 4 int l=0, r=0; 5 if (nums==null || nums.length==0) return 0; 6 int sum = 0; 7 while (r < nums.length) { 8 sum += nums[r]; 9 while (sum >= s) { 10 minWin = Math.min(minWin, r-l+1); 11 sum -= nums[l++]; 12 } 13 r++; 14 } 15 if (r==nums.length && l==0 && sum<s) return 0; 16 return minWin; 17 } 18 }
Initially I‘m concerning I should maintain the window to have its sum always be >= s, and l should always fall at a place maintaining this property. But the solution above proves that I need not do this. Anyway, my solution also works as follows:
1 public class Solution { 2 public int minSubArrayLen(int s, int[] nums) { 3 int minWin = Integer.MAX_VALUE; 4 int l=0, r=0; 5 if (nums==null || nums.length==0) return 0; 6 int sum = 0; 7 while (r < nums.length) { 8 sum += nums[r]; 9 if (sum >= s) { //found one feasible window, try to shrink the window 10 while (l<=r && sum-nums[l] >= s) { 11 sum -= nums[l++]; 12 } 13 minWin = Math.min(minWin, r-l+1); 14 } 15 r++; 16 } 17 if (r==nums.length && l==0 && sum<s) return 0; 18 return minWin; 19 } 20 }
Leetcode: Minimum Size Subarray Sum
标签:
原文地址:http://www.cnblogs.com/EdwardLiu/p/5052889.html