Given two arrays arr1[] and arr2[] of lengths N and M respectively, the task is to find the maximum number of pairs (i, j) such that 2 * arr1[i] ≤ arr2[j] (1 ≤ i ≤ N and 1 ≤ j ≤ M).
Note: Any array element can be part of a single pair.
Examples:
Input: N = 3, arr1[] = {3, 2, 1}, M = 4, arr2[] = {3, 4, 2, 1}
Output: 2
Explanation:
Only two pairs can be chosen:
- (1, 3): Choose elements arr1[3] and arr2[1].
Therefore, pair = (arr1[3], arr2[1]) = (1, 3). Also, 2 * arr1[3] ≤ arr2[1].
Now elements at positions 3 and 1 of arr1[] and arr2[] respectively, cannot be chosen.- (2, 2): Choose elements arr1[2] and arr2[2].
Therefore, pair = (arr1[2], arr2[2]) = (2, 4). Also, 2*arr1[2] <= arr2[2].
Now elements at position 2 of arr1[] and arr2[] cannot be chosen.Input: N = 1, arr1[] = {40}, M = 4, arr2[] = {10, 20, 30, 40}
Output: 0
Explanation:
No Possible Pair exists which satisfies the condition.
Naive Approach: The simplest approach is to first sort both the arrays and for each element arr1[i], greedily find the element that is just greater than or equal to the value 2 * arr1[i] in the given array arr2[] and then remove that element from arr2[] by incrementing the total number of required pairs by 1. After traversing the whole array arr1[], print the number of pairs.
Time Complexity: O(N * M), where N and M are the lengths of the given array.
Auxiliary Space: O(N+M)
Efficient Approach: The idea is to use the Greedy Algorithm by finding an element in arr2[] that is just greater than or equal to the value 2*arr1[i] where 0<=i<=N-1. Follow the below steps to solve the problem:
- Sort the array arr1[] and initialize a variable ans to store the maximum number of pairs.
- Add all the elements of arr2[] in Max Heap.
- Traverse the array arr1[] from i = (N – 1) to 0 in non-increasing order.
- For each element arr1[i], remove the peek element from the Max Heap until 2*arr1[i] becomes smaller than or equal to the peek element and increment ans by 1 if such element is found.
- After traversing the whole array, print ans as the maximum number of pairs.
Below is the implementation of the above approach:
// C++ program for the above approach #include <bits/stdc++.h> using namespace std;
// Function to return the maximum // number of required pairs int numberOfPairs( int arr1[], int n,
int arr2[], int m)
{ // Max Heap to add values of arar2[]
priority_queue< int > pq;
int i, j;
// Sort the array arr1[]
sort(arr1, arr1 + n);
// Push all arr2[] into Max Heap
for (j = 0; j < m; j++) {
pq.push(arr2[j]);
}
// Initialize the ans
int ans = 0;
// Traverse the arr1[] in
// decreasing order
for (i = n - 1; i >= 0; i--) {
// Remmove element until a
// required pair is found
if (pq.top() >= 2 * arr1[i]) {
ans++;
pq.pop();
}
}
// Return maximum number of pairs
return ans;
} // Driver Code int main()
{ // Given arrays
int arr1[] = { 3, 1, 2 };
int arr2[] = { 3, 4, 2, 1 };
int N = sizeof (arr1) / sizeof (arr1[0]);
int M = sizeof (arr2) / sizeof (arr2[0]);
// Function Call
cout << numberOfPairs(arr1, N,
arr2, M);
return 0;
} |
// Java program for the above approach import java.io.*;
import java.util.*;
class GFG{
// Function to return the maximum // number of required pairs static int numberOfPairs( int [] arr1, int n,
int [] arr2, int m)
{ // Max Heap to add values of arr2[]
PriorityQueue<Integer> pQueue =
new PriorityQueue<Integer>(
new Comparator<Integer>()
{
public int compare(Integer lhs,
Integer rhs)
{
if (lhs < rhs)
{
return + 1 ;
}
if (lhs.equals(rhs))
{
return 0 ;
}
return - 1 ;
}
});
int i, j;
// Sort the array arr1[]
Arrays.sort(arr1);
// Push all arr2[] into Max Heap
for (j = 0 ; j < m; j++)
{
pQueue.add(arr2[j]);
}
// Initialize the ans
int ans = 0 ;
// Traverse the arr1[] in
// decreasing order
for (i = n - 1 ; i >= 0 ; i--)
{
// Remove element until a
// required pair is found
if (pQueue.peek() >= 2 * arr1[i])
{
ans++;
pQueue.poll();
}
}
// Return maximum number of pairs
return ans;
} // Driver Code public static void main (String[] args)
{ // Given arrays
int [] arr1 = { 3 , 1 , 2 };
int [] arr2 = { 3 , 4 , 2 , 1 };
int N = 3 ;
int M = 4 ;
// Function call
System.out.println(numberOfPairs(arr1, N,
arr2, M));
} } // This code is contributed by sallagondaavinashreddy7 |
# Python3 program for the above approach # Function to return the maximum # number of required pairs def numberOfPairs(arr1, n, arr2, m):
# Max Heap to add values of arr2[]
pq = []
# Sort the array arr1[]
arr1.sort(reverse = False )
# Push all arr2[] into Max Heap
for j in range (m):
pq.append(arr2[j])
# Initialize the ans
ans = 2
# Traverse the arr1[] in
# decreasing order
i = n - 1
while (i > = 0 ):
# Remove element until a
# required pair is found
pq.sort(reverse = False )
if (pq[ 0 ] > = 2 * arr1[i]):
ans + = 1
print (pq[ 0 ])
pq.remove(pq[ 0 ])
i - = 1
# Return maximum number of pairs
return ans
# Driver Code if __name__ = = '__main__' :
# Given arrays
arr1 = [ 3 , 2 , 1 ]
arr2 = [ 3 , 4 , 2 , 1 ]
N = len (arr1)
M = len (arr2)
# Function Call
print (numberOfPairs(arr1, N, arr2, M))
# This code is contributed by ipg2016107 |
2
Time Complexity: O(N*log N + M*log M), where N and M are the lengths of the given array.
Auxiliary Space: O(N+M)
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