# Posts tagged as “sliding window”

There are n engineers numbered from 1 to n and two arrays: speed and efficiency, where speed[i] and efficiency[i] represent the speed and efficiency for the i-th engineer respectively. Return the maximum performance of a team composed of at most k engineers, since the answer can be a huge number, return this modulo 10^9 + 7.

The performance of a team is the sum of their engineers’ speeds multiplied by the minimum efficiency among their engineers.

Example 1:

Input: n = 6, speed = [2,10,3,1,5,8], efficiency = [5,4,3,9,7,2], k = 2
Output: 60
Explanation:
We have the maximum performance of the team by selecting engineer 2 (with speed=10 and efficiency=4) and engineer 5 (with speed=5 and efficiency=7). That is, performance = (10 + 5) * min(4, 7) = 60.


Example 2:

Input: n = 6, speed = [2,10,3,1,5,8], efficiency = [5,4,3,9,7,2], k = 3
Output: 68
Explanation:
This is the same example as the first but k = 3. We can select engineer 1, engineer 2 and engineer 5 to get the maximum performance of the team. That is, performance = (2 + 10 + 5) * min(5, 4, 7) = 68.


Example 3:

Input: n = 6, speed = [2,10,3,1,5,8], efficiency = [5,4,3,9,7,2], k = 4
Output: 72


Constraints:

• 1 <= n <= 10^5
• speed.length == n
• efficiency.length == n
• 1 <= speed[i] <= 10^5
• 1 <= efficiency[i] <= 10^8
• 1 <= k <= n

## Solution: Greedy + Sliding Window

1. Sort engineers by their efficiency in descending order.
2. For each window of K engineers (we can have less than K people in the first k-1 windows), ans is sum(speed) * min(efficiency).

Time complexity: O(nlogn) + O(nlogk)
Space complexity: O(n)

## Python3

Given an array of integers arr and two integers k and threshold.

Return the number of sub-arrays of size k and average greater than or equal to threshold.

Example 1:

Input: arr = [2,2,2,2,5,5,5,8], k = 3, threshold = 4
Output: 3
Explanation: Sub-arrays [2,5,5],[5,5,5] and [5,5,8] have averages 4, 5 and 6 respectively. All other sub-arrays of size 3 have averages less than 4 (the threshold).


Example 2:

Input: arr = [1,1,1,1,1], k = 1, threshold = 0
Output: 5


Example 3:

Input: arr = [11,13,17,23,29,31,7,5,2,3], k = 3, threshold = 5
Output: 6
Explanation: The first 6 sub-arrays of size 3 have averages greater than 5. Note that averages are not integers.


Example 4:

Input: arr = [7,7,7,7,7,7,7], k = 7, threshold = 7
Output: 1


Example 5:

Input: arr = [4,4,4,4], k = 4, threshold = 1
Output: 1


Constraints:

• 1 <= arr.length <= 10^5
• 1 <= arr[i] <= 10^4
• 1 <= k <= arr.length
• 0 <= threshold <= 10^4

## Solution: Sliding Window

1. Window size = k
2. Maintain the sum of the window
3. Check sum >= threshold * k

Time complexity: O(n)
Space complexity: O(1)

## C++

You are given two strings s and t of the same length. You want to change s to t. Changing the i-th character of s to i-th character of t costs |s[i] - t[i]| that is, the absolute difference between the ASCII values of the characters.

You are also given an integer maxCost.

Return the maximum length of a substring of s that can be changed to be the same as the corresponding substring of twith a cost less than or equal to maxCost.

If there is no substring from s that can be changed to its corresponding substring from t, return 0.

Example 1:

Input: s = "abcd", t = "bcdf", cost = 3
Output: 3
Explanation: "abc" of s can change to "bcd". That costs 3, so the maximum length is 3.

Example 2:

Input: s = "abcd", t = "cdef", cost = 3
Output: 1
Explanation: Each charactor in s costs 2 to change to charactor in t, so the maximum length is 1.


Example 3:

Input: s = "abcd", t = "acde", cost = 0
Output: 1
Explanation: You can't make any change, so the maximum length is 1.


Constraints:

• 1 <= s.length, t.length <= 10^5
• 0 <= maxCost <= 10^6
• s and t only contain lower case English letters.

## Solution 1: Binary Search

Time complexity: O(nlogn)
Space complexity: O(n)

## Solution 2: Sliding Window

Time complexity: O(n)
Space complexity: O(1)

## C++

A dieter consumes calories[i] calories on the i-th day.  For every consecutive sequence of k days, they look at T, the total calories consumed during that sequence of k days:

• If T < lower, they performed poorly on their diet and lose 1 point;
• If T > upper, they performed well on their diet and gain 1 point;
• Otherwise, they performed normally and there is no change in points.

Return the total number of points the dieter has after all calories.length days.

Note that: The total points could be negative.

Example 1:

Input: calories = [1,2,3,4,5], k = 1, lower = 3, upper = 3
Output: 0
Explaination: calories[0], calories[1] < lower and calories[3], calories[4] > upper, total points = 0.

Example 2:

Input: calories = [3,2], k = 2, lower = 0, upper = 1
Output: 1
Explaination: calories[0] + calories[1] > upper, total points = 1.


Example 3:

Input: calories = [6,5,0,0], k = 2, lower = 1, upper = 5
Output: 0
Explaination: calories[0] + calories[1] > upper, calories[2] + calories[3] < lower, total points = 0.


Constraints:

• 1 <= k <= calories.length <= 10^5
• 0 <= calories[i] <= 20000
• 0 <= lower <= upper

## Solution: Sliding Window

Maintain the sum of a sliding window length of k.

Time complexity: O(n)
Space complexity: O(1)

## C++

Today, the bookstore owner has a store open for customers.length minutes.  Every minute, some number of customers (customers[i]) enter the store, and all those customers leave after the end of that minute.

On some minutes, the bookstore owner is grumpy.  If the bookstore owner is grumpy on the i-th minute, grumpy[i] = 1, otherwise grumpy[i] = 0.  When the bookstore owner is grumpy, the customers of that minute are not satisfied, otherwise they are satisfied.

The bookstore owner knows a secret technique to keep themselves not grumpy for X minutes straight, but can only use it once.

Return the maximum number of customers that can be satisfied throughout the day.

Example 1:

Input: customers = [1,0,1,2,1,1,7,5], grumpy = [0,1,0,1,0,1,0,1], X = 3
Output: 16
Explanation: The bookstore owner keeps themselves not grumpy for the last 3 minutes.
The maximum number of customers that can be satisfied = 1 + 1 + 1 + 1 + 7 + 5 = 16.


Note:

• 1 <= X <= customers.length == grumpy.length <= 20000
• 0 <= customers[i] <= 1000
• 0 <= grumpy[i] <= 1

## Solution: Sliding Window

Sum the costumers of non grumpy minutes, recording the max sum of the sliding window of size X.

Time complexity: O(n)
Space complexity: o(n)

## C++

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