[抄題]:node
給定一個包含 n 個整數的數組,和一個大小爲 k 的滑動窗口,從左到右在數組中滑動這個窗口,找到數組中每一個窗口內的中位數。(若是數組個數是偶數,則在該窗口排序數字後,返回第 N/2 個數字。)算法
對於數組 [1,2,7,8,5]
, 滑動大小 k = 3 的窗口時,返回 [2,7,7]
數組
最初,窗口的數組是這樣的:數據結構
[ | 1,2,7 | ,8,5]
, 返回中位數 2
;ide
接着,窗口繼續向前滑動一次。函數
[1, | 2,7,8 | ,5]
, 返回中位數 7
;this
接着,窗口繼續向前滑動一次。spa
[1,2, | 7,8,5 | ]
, 返回中位數 7
;debug
[暴力解法]:rest
時間分析:
空間分析:
[思惟問題]:
[一句話思路]:
窗口移動就是加一個元素、減一個元素,用倆函數實現,因此能夠放在maxheap minheap中
[輸入量]:空: 正常狀況:特大:特小:程序裏處理到的特殊狀況:異常狀況(不合法不合理的輸入):
[畫圖]:
[一刷]:
[二刷]:
[三刷]:
[四刷]:
[五刷]:
[五分鐘肉眼debug的結果]:
[總結]:
參數須要邊分析邊寫,留意leetcode lintcode接口是否是不同
[複雜度]:Time complexity: O(n個數*左右treeset體積lgk) Space complexity: O(n)
[英文數據結構或算法,爲何不用別的數據結構或算法]:
[關鍵模板化代碼]:
[其餘解法]:
[Follow Up]:
[LC給出的題目變變變]:
class Node implements Comparable<Node>{ int id; int val; Node (int id, int val){ this.id = id; this.val = val; } public int compareTo(Node other) { Node a = other; if (this.val == a.val) { return this.id - a.id; }else { return this.val - a.val; } } } public class Solution { /* * @param nums: A list of integers * @param k: An integer * @return: The median of the element inside the window at each moving */ public double[] medianSlidingWindow(int[] nums, int k) { //corner case int n = nums.length; double[] result = new double[n]; if (nums == null || k == 0) { return result; } TreeSet<Node> minHeap = new TreeSet<>(); TreeSet<Node> maxHeap = new TreeSet<>(); //add all nums into window, rest int half = (k + 1) / 2; int index = 0; for (int i = 0; i < k - 1; i++) { add(minHeap, maxHeap, half, new Node(i, nums[i])); } for (int i = k - 1; i < n; i++) { add(minHeap, maxHeap, half, new Node(i, nums[i])); nums[index] = minHeap.last().val; index++; remove(minHeap, maxHeap, new Node(i - k + 1, nums[i - k + 1])); } return result; } // write reference first! void add(TreeSet<Node> minHeap, TreeSet<Node> maxHeap, int size, Node node) { if (minHeap.size() < size) { minHeap.add(node); }else { maxHeap.add(node); } if (minHeap.size() == size) { //don't forget just minheap, need to ensure if (maxHeap.size() > 0 && minHeap.last().val > maxHeap.first().val) { Node b = minHeap.last(); Node s = maxHeap.first(); minHeap.remove(b); minHeap.add(s); maxHeap.remove(s); maxHeap.add(b); } } } void remove(TreeSet<Node> minHeap, TreeSet<Node> maxHeap, Node node) { if (minHeap.contains(node)) { minHeap.remove(node); }else { maxHeap.remove(node); } } }
[代碼風格] :