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Posts tagged as “sliding window”

花花酱 LeetCode 904. Fruit Into Baskets

Problem

In a row of trees, the i-th tree produces fruit with type tree[i].

You start at any tree of your choice, then repeatedly perform the following steps:

  1. Add one piece of fruit from this tree to your baskets.  If you cannot, stop.
  2. Move to the next tree to the right of the current tree.  If there is no tree to the right, stop.

Note that you do not have any choice after the initial choice of starting tree: you must perform step 1, then step 2, then back to step 1, then step 2, and so on until you stop.

You have two baskets, and each basket can carry any quantity of fruit, but you want each basket to only carry one type of fruit each.

What is the total amount of fruit you can collect with this procedure?

Example 1:

Input: [1,2,1]
Output: 3
Explanation: We can collect [1,2,1].

Example 2:

Input: [0,1,2,2]
Output: 3
Explanation: We can collect [1,2,2].
If we started at the first tree, we would only collect [0, 1].

Example 3:

Input: [1,2,3,2,2]
Output: 4
Explanation: We can collect [2,3,2,2].
If we started at the first tree, we would only collect [1, 2].

Example 4:

Input: [3,3,3,1,2,1,1,2,3,3,4]
Output: 5
Explanation: We can collect [1,2,1,1,2].
If we started at the first tree or the eighth tree, we would only collect 4 fruits.

Note:

  1. 1 <= tree.length <= 40000
  2. 0 <= tree[i] < tree.length

Solution: Hashtable + Sliding window

Time complexity: O(n)

Space complexity: O(1)

Keep track of the last index of each element. If a third type of fruit comes in, the new window starts after the fruit with smaller last index. Otherwise extend the current window.

[1 3 1 3 1 1] 4 1 4 … <- org window, 3 has a smaller last index than 1.

1 3 1 3 [1 1 4] 1 4 … <- new window

C++

花花酱 LeetCode 643. Maximum Average Subarray I

Problem

题目大意:找出k长度的子数组的平均值的最大值。

https://leetcode.com/problems/maximum-average-subarray-i/description/

Given an array consisting of n integers, find the contiguous subarray of given length k that has the maximum average value. And you need to output the maximum average value.

Example 1:

Input: [1,12,-5,-6,50,3], k = 4
Output: 12.75
Explanation: Maximum average is (12-5-6+50)/4 = 51/4 = 12.75

Note:

  1. 1 <= k <= n <= 30,000.
  2. Elements of the given array will be in the range [-10,000, 10,000].

Solution: Sliding Window

Time complexity: O(n)

Space complexity: O(1)

C++

Related Problems

花花酱 LeetCode 567. Permutation in String

Problem

题目大意:给你s1, s2,问你s2的子串中是否存在s1的一个排列。

https://leetcode.com/problems/permutation-in-string/description/

Given two strings s1 and s2, write a function to return true if s2 contains the permutation of s1. In other words, one of the first string’s permutations is the substring of the second string.

Example 1:

Input:s1 = "ab" s2 = "eidbaooo"
Output:True
Explanation: s2 contains one permutation of s1 ("ba").

Example 2:

Input:s1= "ab" s2 = "eidboaoo"
Output: False

Note:

  1. The input strings only contain lower case letters.
  2. The length of both given strings is in range [1, 10,000].

Solution: Sliding Window

Time Complexity: O(l1 + l2 * 26) = O(l1 + l2)

Space Complexity: O(26 * 2) = O(1)

C++

Related Problems

花花酱 LeetCode 480. Sliding Window Median

题目大意:让你求移动窗口的中位数。

Problem:

Median is the middle value in an ordered integer list. If the size of the list is even, there is no middle value. So the median is the mean of the two middle value.

Examples:

[2,3,4] , the median is 3

[2,3], the median is (2 + 3) / 2 = 2.5

Given an array nums, there is a sliding window of size k which is moving from the very left of the array to the very right. You can only see the k numbers in the window. Each time the sliding window moves right by one position. Your job is to output the median array for each window in the original array.

For example,
Given nums = [1,3,-1,-3,5,3,6,7], and k = 3.

Therefore, return the median sliding window as [1,-1,-1,3,5,6].

Note: 
You may assume k is always valid, ie: k is always smaller than input array’s size for non-empty array.



Solution 0: Brute Force

Time complexity: O(n*klogk) TLE 32/42 test cases passed

Solution 1: Insertion Sort

Time complexity: O(k*logk +  (n – k + 1)*k)

Space complexity: O(k)

C++ / vector

C++ / vector + binary_search for deletion.

Java

Java / Binary Search

 

Python

Solution 2: BST

 

Related Problems: