Find a peak element using iterative Binary search

Below is the idea to solve the problem.

Using Binary Search, check if the middle element is the peak element or not. If the middle element the peak element terminate the while loop and print middle element, then check if the element on the right side is greater than the middle element then there is always a peak element on the right side. If the element on the left side is greater than the middle element then there is always a peak element on the left side

Follow the steps below to implement the idea:

  • Create two variables, l and r, initialize l = 0 and r = n-1
  • Run a while loop till l <= r, lowerbound is less than the upperbound
    • Check if the mid value or index mid = low + (high – low) / 2, is the peak element or not, if yes then print the element and terminate.
    • Else if the element on the left side of the middle element is greater then check for peak element on the left side, i.e. update r = mid – 1
    • Else if the element on the right side of the middle element is greater then check for peak element on the right side, i.e. update [Tex]l = mid + 1 [/Tex]

The below-given code is the iterative version of the above explained and demonstrated recursive based divide and conquer technique.

C++

// A C++ program to find a peak element // using divide and conquer #include <bits/stdc++.h> using namespace std; // A binary search based function // that returns index of a peak element int findPeak(int arr[], int n) { int l = 0; int r = n-1; int mid; while (l <= r) { // finding mid by binary right shifting. mid = (l + r) >> 1; // first case if mid is the answer if ((mid == 0 || arr[mid - 1] <= arr[mid]) and (mid == n - 1 || arr[mid + 1] <= arr[mid])) break; // move the right pointer if (mid > 0 and arr[mid - 1] > arr[mid]) r = mid - 1; // move the left pointer else l = mid + 1; } return mid; } // Driver Code int main() { int arr[] = { 1, 3, 20, 4, 1, 0 }; int N = sizeof(arr) / sizeof(arr[0]); cout << "Index of a peak point is " << findPeak(arr, N); return 0; } // This code is contributed by Rajdeep Mallick (rajdeep999)

C

// A C program to find a peak element using divide and // conquer #include <stdio.h> // A binary search based function // that returns index of a peak element int findPeak(int arr[], int n) { int l = 0; int r = n-1; int mid; while (l <= r) { // finding mid by binary right shifting. mid = (l + r) >> 1; // first case if mid is the answer if ((mid == 0 || arr[mid - 1] <= arr[mid]) && (mid == n - 1 || arr[mid + 1] <= arr[mid])) break; // move the right pointer if (mid > 0 && arr[mid - 1] > arr[mid]) r = mid - 1; // move the left pointer else l = mid + 1; } return mid; } // Driver Code int main() { int arr[] = { 1, 3, 20, 4, 1, 0 }; int n = sizeof(arr) / sizeof(arr[0]); printf("Index of a peak point is %d", findPeak(arr, n)); return 0; } // This code is contributed by Rajdeep Mallick (rajdeep999)

Java

// A Java program to find a peak element using divide and // conquer import java.io.*; class GFG { // A binary search based function that returns index of // a peak element static int findPeak(int arr[], int n) { int l = 0; int r = n-1; int mid = 0; while (l <= r) { // finding mid by binary right shifting. mid = (l + r) >> 1; // first case if mid is the answer if ((mid == 0 || arr[mid - 1] <= arr[mid]) && (mid == n - 1 || arr[mid + 1] <= arr[mid])) break; // move the right pointer if (mid > 0 && arr[mid - 1] > arr[mid]) r = mid - 1; // move the left pointer else l = mid + 1; } return mid; } // Driver Code public static void main(String args[]) { int arr[] = { 1, 3, 20, 4, 1, 0 }; int n = arr.length; System.out.println("Index of a peak point is " + findPeak(arr, n)); } } // This code is contributed by Rajdeep Mallick (rajdeep999)

Python

# A Python program to find a peak element # using divide and conquer # A binary search based function # that returns index of a peak element def findPeak(arr, n): l = 0 r = n-1 while(l <= r): # finding mid by binary right shifting. mid = (l + r) >> 1 # first case if mid is the answer if((mid == 0 or arr[mid - 1] <= arr[mid]) and (mid == n - 1 or arr[mid + 1] <= arr[mid])): break # move the right pointer if(mid > 0 and arr[mid - 1] > arr[mid]): r = mid - 1 # move the left pointer else: l = mid + 1 return mid # Driver Code arr = [1, 3, 20, 4, 1, 0] n = len(arr) print(f"Index of a peak point is {findPeak(arr, n)}") # This code is contributed by Rajdeep Mallick (rajdeep999)

C#

// A C# program to find a peak element // using divide and conquer using System; public class GFG { // A binary search based function // that returns index of a peak element static int findPeak(int[] arr, int n) { int l = 0; int r = n-1; int mid = 0; while (l <= r) { // finding mid by binary right shifting. mid = (l + r) >> 1; // first case if mid is the answer if ((mid == 0 || arr[mid - 1] <= arr[mid] && (mid == n - 1 || arr[mid + 1] <= arr[mid]))) break; // move the right pointer if (mid > 0 && arr[mid - 1] > arr[mid]) r = mid - 1; // move the left pointer else l = mid + 1; } return mid; } // Driver Code public static void Main(String[] args) { int[] arr = { 1, 3, 20, 4, 1, 0 }; int n = arr.Length; Console.WriteLine("Index of a peak point is " + findPeak(arr, n)); } } // This code is contributed by Rajdeep Mallick (rajdeep999)

Javascript

// A JavaScript program to find a peak element // using divide and conquer // A binary search based function // that returns index of a peak element function findPeakUtil(arr, low, high, n) { let l = low; let r = high - 1; let mid; while(l <= r) { // finding the mid index by right shifting mid = (l + r) >> 1; // first case if mid is the answer if((mid == 0 || arr[mid - 1] <= arr[mid]) && (mid == n - 1 || arr[mid + 1] <= arr[mid])) break; // change the right pointer to mid-1 if(mid > 0 && arr[mid - 1] > arr[mid]) r = mid - 1; // change the left pointer to mid+1 else l = mid + 1; } return mid; } // A wrapper over recursive function findPeakUtil() function findPeak(arr,n) { return findPeakUtil(arr, 0, n, n); } // Driver Code let arr = [ 1, 3, 20, 4, 1, 0 ]; let n = arr.length; console.log("Index of a peak point is " +findPeak(arr, n)); // This code is contributed by Rajdeep Mallick (rajdeep999)


Output

Index of a peak point is 2

Time Complexity: O(log N), Where n is the number of elements in the input array. In each step our search becomes half. So it can be compared to Binary search, So the time complexity is O(log N)
Auxiliary Space: O(1), No extra space is required, so the space complexity is constant.

Exercise: 
Consider the following modified definition of peak element. An array element is a peak if it is greater than its neighbors. Note that an array may not contain a peak element with this modified definition.

Related Problem: 
Find local minima in an array



Find a peak element which is not smaller than its neighbours

Given an array arr of n elements that is first strictly increasing and then maybe strictly decreasing, find the maximum element in the array.

Note: If the array is increasing then just print the last element will be the maximum value.

Example:

Input: array[]= {5, 10, 20, 15}
Output: 20
Explanation: The element 20 has neighbors 10 and 15, both of them are less than 20.

Input: array[] = {10, 20, 15, 2, 23, 90, 67}
Output: 20 or 90
Explanation: The element 20 has neighbors 10 and 15, both of them are less than 20, similarly 90 has neighbors 23 and 67.

The following corner cases give a better idea about the problem. 

  1. If the input array is sorted in a strictly increasing order, the last element is always a peak element. For example, 50 is peak element in {10, 20, 30, 40, 50}.
  2. If the input array is sorted in a strictly decreasing order, the first element is always a peak element. 100 is the peak element in {100, 80, 60, 50, 20}.
  3. If all elements of the input array are the same, every element is a peak element.

It is clear from the above examples that there is always a peak element in the input array.

Recommended Problem
Peak element
Solve Problem

The array can be traversed and the element whose neighbors are less than that element can be returned.

Follow the below steps to Implement the idea: 

  • If the first element is greater than the second or the last element is greater than the second last, print the respective element and terminate the program.
  • Else traverse the array from the second index to the second last index i.e. 1 to N – 1  
    • If for an element array[i] is greater than both its neighbors, i.e., array[i] > =array[i-1]  and array[i] > =array[i+1] , then print that element and terminate.

Below is the implementation of above idea.

C++

// A C++ program to find a peak element #include <bits/stdc++.h> using namespace std; // Find the peak element in the array int findPeak(int arr[], int n) { // first or last element is peak element if (n == 1) return 0; if (arr[0] >= arr[1]) return 0; if (arr[n - 1] >= arr[n - 2]) return n - 1; // check for every other element for (int i = 1; i < n - 1; i++) { // check if the neighbors are smaller if (arr[i] >= arr[i - 1] && arr[i] >= arr[i + 1]) return i; } } // Driver Code int main() { int arr[] = { 1, 3, 20, 4, 1, 0 }; int n = sizeof(arr) / sizeof(arr[0]); cout << "Index of a peak point is " << findPeak(arr, n); return 0; } // This code is contributed by Aditya Kumar (adityakumar129)

C

// A C program to find a peak element #include <stdio.h> // Find the peak element in the array int findPeak(int arr[], int n) { // first or last element is peak element if (n == 1) return 0; if (arr[0] >= arr[1]) return 0; if (arr[n - 1] >= arr[n - 2]) return n - 1; // check for every other element for (int i = 1; i < n - 1; i++) { // check if the neighbors are smaller if (arr[i] >= arr[i - 1] && arr[i] >= arr[i + 1]) return i; } } // Driver Code int main() { int arr[] = { 1, 3, 20, 4, 1, 0 }; int n = sizeof(arr) / sizeof(arr[0]); printf("Index of a peak point is %d",findPeak(arr, n)); return 0; } // This code is contributed by Aditya Kumar (adityakumar129)

Java

// A Java program to find a peak element import java.util.*; class GFG { // Find the peak element in the array static int findPeak(int arr[], int n) { // First or last element is peak element if (n == 1) return 0; if (arr[0] >= arr[1]) return 0; if (arr[n - 1] >= arr[n - 2]) return n - 1; // Check for every other element for (int i = 1; i < n - 1; i++) { // Check if the neighbors are smaller if (arr[i] >= arr[i - 1] && arr[i] >= arr[i + 1]) return i; } return 0; } // Driver Code public static void main(String[] args) { int arr[] = { 1, 3, 20, 4, 1, 0 }; int n = arr.length; System.out.print("Index of a peak point is " + findPeak(arr, n)); } } // This code is contributed by Aditya Kumar (adityakumar129)

Python

# A Python3 program to find a peak element # Find the peak element in the array def findPeak(arr, n) : # first or last element is peak element if (n == 1) : return 0 if (arr[0] >= arr[1]) : return 0 if (arr[n - 1] >= arr[n - 2]) : return n - 1 # check for every other element for i in range(1, n - 1) : # check if the neighbors are smaller if (arr[i] >= arr[i - 1] and arr[i] >= arr[i + 1]) : return i # Driver code. arr = [ 1, 3, 20, 4, 1, 0 ] n = len(arr) print("Index of a peak point is", findPeak(arr, n)) # This code is contributed by divyeshrabadiya07

C#

// A C# program to find a peak element using System; public class GFG{ // Find the peak element in the array static int findPeak(int []arr, int n) { // First or last element is peak element if (n == 1) return 0; if (arr[0] >= arr[1]) return 0; if (arr[n - 1] >= arr[n - 2]) return n - 1; // Check for every other element for(int i = 1; i < n - 1; i++) { // Check if the neighbors are smaller if (arr[i] >= arr[i - 1] && arr[i] >= arr[i + 1]) return i; } return 0; } // Driver Code public static void Main(String[] args) { int []arr = { 1, 3, 20, 4, 1, 0 }; int n = arr.Length; Console.Write("Index of a peak point is " + findPeak(arr, n)); } } // This code is contributed by 29AjayKumar

Javascript

// A JavaScript program to find a peak element // Find the peak element in the array function findPeak(arr, n) { // first or last element is peak element if (n == 1) return 0; if (arr[0] >= arr[1]) return 0; if (arr[n - 1] >= arr[n - 2]) return n - 1; // check for every other element for (var i = 1; i < n - 1; i++) { // check if the neighbors are smaller if (arr[i] >= arr[i - 1] && arr[i] >= arr[i + 1]) return i; } } // Driver Code var arr = [1, 3, 20, 4, 1, 0]; var n = arr.length; console.log("Index of a peak point is " + findPeak(arr, n)); // This code is contributed by rdtank.


Output

Index of a peak point is 2

Time complexity: O(n), One traversal is needed so the time complexity is O(n)
Auxiliary Space: O(1), No extra space is needed, so space complexity is constant

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