Given an array arr[] of length N and an integer K, the task is to count the number of pairs (i, j) such that i < j and arr[i] > K * arr[j].
Examples:
Input: arr[] = {5, 6, 2, 5}, K = 2
Output: 2
Explanation: The array consists of two such pairs:
(5, 2): Index of 5 and 2 are 0, 2 respectively. Therefore, the required conditions (0 < 2 and 5 > 2 * 2) are satisfied.
(6, 2): Index of 6 and 2 are 1, 2 respectively. Therefore, the required conditions (0 < 2 and 6 > 2 * 2) are satisfied.Input: arr[] = {4, 6, 5, 1}, K = 2
Output: 3
Naive Approach: The simplest approach to solve the problem is to traverse the array and for every index, find numbers having indices greater than it, such that the element in it when multiplied by K is less than the element at the current index.
Follow the below steps to solve the problem:
- Initialize a variable, say cnt, with 0 to count the total number of required pairs.
- Traverse the array from left to right.
- For each possible index, say i, traverse the indices i + 1 to N – 1 and increase the value of cnt by 1 if any element, say arr[j], is found such that arr[j] * K is less than arr[i].
- After complete traversal of the array, print cnt as the required count of pairs.
Below is the implementation of the above approach:
C++
// C++ program for the above approach #include <bits/stdc++.h> using namespace std; // Function to find the count required pairs int getPairs( int arr[], int N, int K) { // Stores count of pairs int count = 0; // Traverse the array for ( int i = 0; i < N; i++) { for ( int j = i + 1; j < N; j++) { // Check if the condition // is satisfied or not if (arr[i] > K * arr[i + 1]) count++; } } cout << count; } // Driver Code int main() { int arr[] = { 5, 6, 2, 1 }; int N = sizeof (arr) / sizeof (arr[0]); int K = 2; // Function Call getPairs(arr, N, K); return 0; } |
Java
// Java program for the above approach class GFG { // Function to find the count required pairs static void getPairs( int arr[], int N, int K) { // Stores count of pairs int count = 0 ; // Traverse the array for ( int i = 0 ; i < N; i++) { for ( int j = i + 1 ; j < N; j++) { // Check if the condition // is satisfied or not if (arr[i] > K * arr[i + 1 ]) count++; } } System.out.print(count); } // Driver Code public static void main(String[] args) { int arr[] = { 5 , 6 , 2 , 1 }; int N = arr.length; int K = 2 ; // Function Call getPairs(arr, N, K); } } // This code is contributed by 29AjayKumar |
Python3
# Python3 program for the above approach # Function to find the count required pairs def getPairs(arr, N, K): # Stores count of pairs count = 0 # Traverse the array for i in range (N): for j in range (i + 1 , N): # Check if the condition # is satisfied or not if (arr[i] > K * arr[i + 1 ]): count + = 1 print (count) # Driver Code if __name__ = = '__main__' : arr = [ 5 , 6 , 2 , 1 ] N = len (arr) K = 2 # Function Call getPairs(arr, N, K) # This code is contributed by mohit kumar 29 |
C#
// C# program for the above approach using System; class GFG { // Function to find the count required pairs static void getPairs( int []arr, int N, int K) { // Stores count of pairs int count = 0; // Traverse the array for ( int i = 0; i < N; i++) { for ( int j = i + 1; j < N; j++) { // Check if the condition // is satisfied or not if (arr[i] > K * arr[i + 1]) count++; } } Console.Write(count); } // Driver Code public static void Main(String[] args) { int []arr = { 5, 6, 2, 1 }; int N = arr.Length; int K = 2; // Function Call getPairs(arr, N, K); } } // This code is contributed by shikhasingrajput |
2
Time Complexity: O(N2)
Auxiliary Space: O(N)
Efficient Approach: The idea is to use the concept of merge sort and then count pairs according to the given conditions. Follow the steps below to solve the problem:
- Initialize a variable, say answer, to count the number of pairs satisfying the given condition.
- Repeatedly partition the array into two equal halves or almost equal halves until one element is left in each partition.
- Call a recursive function that counts the umber of times the condition arr[i] > K * arr[j] and i < j is satisfied after merging the two partitions.
- Perform it by initializing two variables, say i and j, for the indices of the first and second half respectively.
- Increment j till arr[i] > K * arr[j] and j < size of the second half. Add (j – (mid + 1)) to the answer and increment i.
- After completing the above steps, print the value of answer as the required number of pairs.
Below is the implementation of the above approach:
C++
// C++ program for the above approach #include <bits/stdc++.h> using namespace std; // Function to merge two sorted arrays int merge( int arr[], int temp[], int l, int m, int r, int K) { // i: index to left subarray int i = l; // j: index to right subarray int j = m + 1; // Stores count of pairs that // satisfy the given condition int cnt = 0; for ( int l = 0; i <= m; i++) { bool found = false ; // Traverse to check for the // valid conditions while (j <= r) { // If condition satifies if (arr[i] >= K * arr[j]) { found = true ; } else break ; j++; } // While a[i] > K*a[j] satisfies // increase j // All elements in the right // side of the left subarray // also satisies if (found) { cnt += j - (m + 1); j--; } } // Sort the two given arrays and // store in the resultant array int k = l; i = l; j = m + 1; while (i <= m && j <= r) { if (arr[i] <= arr[j]) temp[k++] = arr[i++]; else temp[k++] = arr[j++]; } // Elements which are left // in the left subarray while (i <= m) temp[k++] = arr[i++]; // Elements which are left // in the right subarray while (j <= r) temp[k++] = arr[j++]; for ( int i = l; i <= r; i++) arr[i] = temp[i]; // Return the count obtained return cnt; } // Function to partiton array into two halves int mergeSortUtil( int arr[], int temp[], int l, int r, int K) { int cnt = 0; if (l < r) { // Same as (l + r) / 2, but avoids // overflow for large l and h int m = (l + r) / 2; // Sort first and second halves cnt += mergeSortUtil(arr, temp, l, m, K); cnt += mergeSortUtil(arr, temp, m + 1, r, K); // Call the merging function cnt += merge(arr, temp, l, m, r, K); } return cnt; } // Function to print the count of // required pairs using Merge Sort int mergeSort( int arr[], int N, int K) { int temp[N]; cout << mergeSortUtil(arr, temp, 0, N - 1, K); } // Driver code int main() { int arr[] = { 5, 6, 2, 5 }; int N = sizeof (arr) / sizeof (arr[0]); int K = 2; // Function Call mergeSort(arr, N, K); return 0; } |
Java
// Java program for the above approach class GFG { // Function to merge two sorted arrays static int merge( int arr[], int temp[], int l, int m, int r, int K) { // i: index to left subarray int i = l; // j: index to right subarray int j = m + 1 ; // Stores count of pairs that // satisfy the given condition int cnt = 0 ; for (i = l; i <= m; i++) { boolean found = false ; // Traverse to check for the // valid conditions while (j <= r) { // If condition satifies if (arr[i] >= K * arr[j]) { found = true ; } else break ; j++; } // While a[i] > K*a[j] satisfies // increase j // All elements in the right // side of the left subarray // also satisies if (found == true ) { cnt += j - (m + 1 ); j--; } } // Sort the two given arrays and // store in the resultant array int k = l; i = l; j = m + 1 ; while (i <= m && j <= r) { if (arr[i] <= arr[j]) temp[k++] = arr[i++]; else temp[k++] = arr[j++]; } // Elements which are left // in the left subarray while (i <= m) temp[k++] = arr[i++]; // Elements which are left // in the right subarray while (j <= r) temp[k++] = arr[j++]; for (i = l; i <= r; i++) arr[i] = temp[i]; // Return the count obtained return cnt; } // Function to partiton array into two halves static int mergeSortUtil( int arr[], int temp[], int l, int r, int K) { int cnt = 0 ; if (l < r) { // Same as (l + r) / 2, but avoids // overflow for large l and h int m = (l + r) / 2 ; // Sort first and second halves cnt += mergeSortUtil(arr, temp, l, m, K); cnt += mergeSortUtil(arr, temp, m + 1 , r, K); // Call the merging function cnt += merge(arr, temp, l, m, r, K); } return cnt; } // Function to print the count of // required pairs using Merge Sort static void mergeSort( int arr[], int N, int K) { int temp[] = new int [N]; System.out.print(mergeSortUtil(arr, temp, 0 , N - 1 , K)); } // Driver code public static void main (String[] args) { int arr[] = { 5 , 6 , 2 , 5 }; int N = arr.length; int K = 2 ; // Function Call mergeSort(arr, N, K); } } // This code is contributed by AnkThon |
Python3
# Python3 program for the above approach # Function to merge two sorted arrays def merge(arr, temp, l, m, r, K) : # i: index to left subarray i = l # j: index to right subarray j = m + 1 # Stores count of pairs that # satisfy the given condition cnt = 0 for l in range (m + 1 ) : found = False # Traverse to check for the # valid conditions while (j < = r) : # If condition satifies if (arr[i] > = K * arr[j]) : found = True else : break j + = 1 # While a[i] > K*a[j] satisfies # increase j # All elements in the right # side of the left subarray # also satisies if (found) : cnt + = j - (m + 1 ) j - = 1 # Sort the two given arrays and # store in the resultant array k = l i = l j = m + 1 while (i < = m and j < = r) : if (arr[i] < = arr[j]) : temp[k] = arr[i] k + = 1 i + = 1 else : temp[k] = arr[j] k + = 1 j + = 1 # Elements which are left # in the left subarray while (i < = m) : temp[k] = arr[i] k + = 1 i + = 1 # Elements which are left # in the right subarray while (j < = r) : temp[k] = arr[j] k + = 1 j + = 1 for i in range (l, r + 1 ) : arr[i] = temp[i] # Return the count obtained return cnt # Function to partiton array into two halves def mergeSortUtil(arr, temp, l, r, K) : cnt = 0 if (l < r) : # Same as (l + r) / 2, but avoids # overflow for large l and h m = (l + r) / / 2 # Sort first and second halves cnt + = mergeSortUtil(arr, temp, l, m, K) cnt + = mergeSortUtil(arr, temp, m + 1 , r, K) # Call the merging function cnt + = merge(arr, temp, l, m, r, K) return cnt # Function to print the count of # required pairs using Merge Sort def mergeSort(arr, N, K) : temp = [ 0 ] * N print (mergeSortUtil(arr, temp, 0 , N - 1 , K)) # Driver code arr = [ 5 , 6 , 2 , 5 ] N = len (arr) K = 2 # Function Call mergeSort(arr, N, K) # This code is contributed by divyeshrabadiya07. |
C#
// C# program for the above approach using System; class GFG { // Function to merge two sorted arrays static int merge( int [] arr, int [] temp, int l, int m, int r, int K) { // i: index to left subarray int i = l; // j: index to right subarray int j = m + 1; // Stores count of pairs that // satisfy the given condition int cnt = 0; for (i = l; i <= m; i++) { bool found = false ; // Traverse to check for the // valid conditions while (j <= r) { // If condition satifies if (arr[i] >= K * arr[j]) { found = true ; } else break ; j++; } // While a[i] > K*a[j] satisfies // increase j // All elements in the right // side of the left subarray // also satisies if (found == true ) { cnt += j - (m + 1); j--; } } // Sort the two given arrays and // store in the resultant array int k = l; i = l; j = m + 1; while (i <= m && j <= r) { if (arr[i] <= arr[j]) temp[k++] = arr[i++]; else temp[k++] = arr[j++]; } // Elements which are left // in the left subarray while (i <= m) temp[k++] = arr[i++]; // Elements which are left // in the right subarray while (j <= r) temp[k++] = arr[j++]; for (i = l; i <= r; i++) arr[i] = temp[i]; // Return the count obtained return cnt; } // Function to partiton array into two halves static int mergeSortUtil( int [] arr, int [] temp, int l, int r, int K) { int cnt = 0; if (l < r) { // Same as (l + r) / 2, but avoids // overflow for large l and h int m = (l + r) / 2; // Sort first and second halves cnt += mergeSortUtil(arr, temp, l, m, K); cnt += mergeSortUtil(arr, temp, m + 1, r, K); // Call the merging function cnt += merge(arr, temp, l, m, r, K); } return cnt; } // Function to print the count of // required pairs using Merge Sort static void mergeSort( int [] arr, int N, int K) { int [] temp = new int [N]; Console.WriteLine( mergeSortUtil(arr, temp, 0, N - 1, K)); } // Driver code static public void Main() { int [] arr = new int [] { 5, 6, 2, 5 }; int N = arr.Length; int K = 2; // Function Call mergeSort(arr, N, K); } } // This code is contributed by Dharanendra L V |
2
Time Complexity: O(N*log N)
Auxiliary Space: O(N)
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