Problem Statement:
A peak element is an element that is strictly greater than its neighbors.
Given a 0-indexed integer array nums
, find a peak element, and return its index. If the array contains multiple peaks, return the index to any of the peaks.
You may imagine that nums[-1] = nums[n] = -∞
. In other words, an element is always considered to be strictly greater than a neighbor that is outside the array.
You must write an algorithm that runs in O(log n)
time.
Example 1:
Input: nums = [1,2,3,1] Output: 2 Explanation: 3 is a peak element and your function should return the index number 2.
Example 2:
Input: nums = [1,2,1,3,5,6,4] Output: 5 Explanation: Your function can return either index number 1 where the peak element is 2, or index number 5 where the peak element is 6.
Constraints:
1 <= nums.length <= 1000
-2^31 <= nums[i] <= 2^31 - 1
nums[i] != nums[i + 1]
for all validi
.
Solution:
Note
- No two elements are adjacent. Therefore one neighbour can either be greater than the other neighbour or it can be lesser; equality is not possible.(V Imppp) this means The graph at mid can either be increasing or decreasing.
More Intuitive
class Solution {
public int findPeakElement(int[] nums) {
// If there's only one element, it's the peak by default
if (nums.length == 1) return 0;
int n = nums.length;
// Check if the first or last element is a peak
if (nums[0] > nums[1]) return 0;
if (nums[n - 1] > nums[n - 2]) return n - 1;
// Perform binary search in the remaining array
int start = 1;
int end = n - 2;
while (start <= end) {
int mid = start + (end - start) / 2;
// Check if mid is a peak
if (nums[mid - 1] < nums[mid] && nums[mid] > nums[mid + 1]) return mid;
// If mid is less than its previous element, the peak is in the left half
else if (nums[mid - 1] > nums[mid]) end = mid - 1;
// If mid is less than its next element, the peak is in the right half
else start = mid + 1;
}
// Dummy return, this line should never be reached if input is valid
return -1;
}
}
Little less Intuitive but better solution in terms of clarity and less base cases:
- The condition
start <= end
needs to be carefully managed to avoid infinite loops or incorrect results, hencestart < end
is used.
class Solution {
public int findPeakElement(int[] nums) {
int start = 0;
int end = nums.length - 1;
while (start < end) {
int mid = start + (end - start) / 2;
if (nums[mid] < nums[mid + 1]) {
// If the middle element is less than the next element,
// then the peak is in the right half (excluding mid)
start = mid + 1;
} else {
// If the middle element is greater than or equal to the next element,
// then the peak is in the left half (including mid)
end = mid;
}
}
// When start == end, it will point to the peak element
return start;
}
}