forked from trekhleb/javascript-algorithms
-
Notifications
You must be signed in to change notification settings - Fork 0
/
dpMaximumSubarray.js
45 lines (39 loc) · 1.44 KB
/
dpMaximumSubarray.js
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
/**
* Dynamic Programming solution.
* Complexity: O(n)
*
* @param {Number[]} inputArray
* @return {Number[]}
*/
export default function dpMaximumSubarray(inputArray) {
// We iterate through the inputArray once, using a greedy approach to keep track of the maximum
// sum we've seen so far and the current sum.
//
// The currentSum variable gets reset to 0 every time it drops below 0.
//
// The maxSum variable is set to -Infinity so that if all numbers are negative, the highest
// negative number will constitute the maximum subarray.
let maxSum = -Infinity;
let currentSum = 0;
// We need to keep track of the starting and ending indices that contributed to our maxSum
// so that we can return the actual subarray. From the beginning let's assume that whole array
// is contributing to maxSum.
let maxStartIndex = 0;
let maxEndIndex = inputArray.length - 1;
let currentStartIndex = 0;
inputArray.forEach((currentNumber, currentIndex) => {
currentSum += currentNumber;
// Update maxSum and the corresponding indices if we have found a new max.
if (maxSum < currentSum) {
maxSum = currentSum;
maxStartIndex = currentStartIndex;
maxEndIndex = currentIndex;
}
// Reset currentSum and currentStartIndex if currentSum drops below 0.
if (currentSum < 0) {
currentSum = 0;
currentStartIndex = currentIndex + 1;
}
});
return inputArray.slice(maxStartIndex, maxEndIndex + 1);
}