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/**

* Sliding Window:

* This pattern involve creating a window which can either be

* an array or numbers from one position to another.

*

* Depending on a certain condition, the window either increases

* or closes (and a new window is created).

*

* Very useful for keeping track of a subset of data in an

* array/string etc.

*

* Time Complexity: Best - O(n);

*

* Examples:

* maxSubarraySum([1,2,5,2,8,1,5],2) // returns 10

* maxSubarraySum([1,2,5,2,8,1,5],15) // returns null

* maxSubarraySum([5,2,6,9],3) // returns 17

* @param {[Int]} arr - An array of integers on which we will perform the test.

* @param {Int} num - An integer that displays the size of the window you want to check.

* @returns {Int / Null} - Returns a total of N consecutive numbers or null

*/

function slidingWindow (arr, num) {

// Edge Case:

// If the length of the array shorter than the window size (num) return null.

if (arr.length < num) return null

// The highest amount of consecutive numbers

let maxSum = 0

// Temp amount of consecutive numbers - For comparative purposes

let tempSum = 0

// loop over the array {num} times and save their total amount in {maxSum}

for (let i = 0; i < num; i++) {

maxSum += arr[i]

}

// initialize {tempSum} to {maxSum}.

tempSum = maxSum

// loop over the array n times

for (let i = num; i < arr.length; i++) {

// Add the next num in the array and remove the first one

tempSum = tempSum - arr[i - num] + arr[i]

// save the largest number between {maxNum} and {tempNum} in maxSum.

maxSum = Math.max(maxSum, tempSum)

}

return maxSum

}

export { slidingWindow }