Wednesday, July 3, 2024
HomeData ModellingDynamic ProgrammingLength of longest subset consisting of A 0s and B 1s from...

Length of longest subset consisting of A 0s and B 1s from an array of strings | Set 2

Given an array arr[] consisting of N binary strings, and two integers A and B, the task is to find the length of the longest subset consisting of at most A 0s and B 1s.

Examples:

Input: arr[] = {“1”, “0”, “0001”, “10”, “111001”}, A = 5, B = 3
Output: 4
Explanation: 
One possible way is to select the subset {arr[0], arr[1], arr[2], arr[3]}.
Total number of 0s and 1s in all these strings are 5 and 3 respectively.
Also, 4 is the length of the longest subset possible.

Input: arr[] = {“0”, “1”, “10”}, A = 1, B = 1
Output: 2
Explanation: 
One possible way is to select the subset {arr[0], arr[1]}.
Total number of 0s and 1s in all these strings is 1 and 1 respectively.
Also, 2 is the length of the longest subset possible.

Naive Approach: Refer to the previous post of this article for the simplest approach to solve the problem. 
Time Complexity: O(2N)
Auxiliary Space: O(1)

Dynamic Programming Approach: Refer to the previous post of this article for the Dynamic Programming approach. 
Time Complexity: O(N*A*B)
Auxiliary Space: O(N * A * B)

Space-Optimized Dynamic Programming Approach: The space complexity in the above approach can be optimized based on the following observations:

  • Initialize a 2D array, dp[A][B], where dp[i][j] represents the length of the longest subset consisting of at most i number of 0s and j number of 1s.
  • To optimize the auxiliary space from the 3D table to the 2D table, the idea is to traverse the inner loops in reverse order.
  • This ensures that whenever a value in dp[][] is changed, it will not be needed anymore in the current iteration.
  • Therefore, the recurrence relation looks like this:

dp[i][j] = max (dp[i][j], dp[i – zeros][j – ones] + 1)
where zeros is the count of 0s and ones is the count of 1s in the current iteration.

Follow the steps below to solve the problem:

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 length of the
// longest subset of an array of strings
// with at most A 0s and B 1s
int MaxSubsetlength(vector<string> arr,
                    int A, int B)
{
    // Initialize a 2D array with its
    // entries as 0
    int dp[A + 1][B + 1];
    memset(dp, 0, sizeof(dp));
 
    // Traverse the given array
    for (auto& str : arr) {
 
        // Store the count of 0s and 1s
        // in the current string
        int zeros = count(str.begin(),
                          str.end(), '0');
        int ones = count(str.begin(),
                         str.end(), '1');
 
        // Iterate in the range [A, zeros]
        for (int i = A; i >= zeros; i--)
 
            // Iterate in the range [B, ones]
            for (int j = B; j >= ones; j--)
 
                // Update the value of dp[i][j]
                dp[i][j] = max(
                    dp[i][j],
                    dp[i - zeros][j - ones] + 1);
    }
 
    // Print the result
    return dp[A][B];
}
 
// Driver Code
int main()
{
    vector<string> arr
        = { "1", "0", "0001",
            "10", "111001" };
    int A = 5, B = 3;
    cout << MaxSubsetlength(arr, A, B);
 
    return 0;
}


Java




// Java program for the above approach
import java.io.*;
import java.lang.*;
import java.util.*;
 
class GFG{
 
// Function to find the length of the
// longest subset of an array of strings
// with at most A 0s and B 1s
static int MaxSubsetlength(String arr[],
                           int A, int B)
{
     
    // Initialize a 2D array with its
    // entries as 0
    int dp[][] = new int[A + 1][B + 1];
 
    // Traverse the given array
    for(String str : arr)
    {
         
        // Store the count of 0s and 1s
        // in the current string
        int zeros = 0, ones = 0;
        for(char ch : str.toCharArray())
        {
            if (ch == '0')
                zeros++;
            else
                ones++;
        }
 
        // Iterate in the range [A, zeros]
        for(int i = A; i >= zeros; i--)
         
            // Iterate in the range [B, ones]
            for(int j = B; j >= ones; j--)
 
                // Update the value of dp[i][j]
                dp[i][j] = Math.max(
                    dp[i][j],
                    dp[i - zeros][j - ones] + 1);
    }
 
    // Print the result
    return dp[A][B];
}
 
// Driver Code
public static void main(String[] args)
{
    String arr[] = { "1", "0", "0001",
                     "10", "111001" };
    int A = 5, B = 3;
     
    System.out.println(MaxSubsetlength(arr, A, B));
}
}
 
// This code is contributed by Kingash


Python3




# Python3 program for the above approach
 
# Function to find the length of the
# longest subset of an array of strings
# with at most A 0s and B 1s
def MaxSubsetlength(arr, A, B):
     
    # Initialize a 2D array with its
    # entries as 0
    dp = [[0 for i in range(B + 1)]
             for i in range(A + 1)]
 
    # Traverse the given array
    for str in arr:
         
        # Store the count of 0s and 1s
        # in the current string
        zeros = str.count('0')
        ones = str.count('1')
 
        # Iterate in the range [A, zeros]
        for i in range(A, zeros - 1, -1):
 
            # Iterate in the range [B, ones]
            for j in range(B, ones - 1, -1):
 
                # Update the value of dp[i][j]
                dp[i][j] = max(dp[i][j],
                               dp[i - zeros][j - ones] + 1)
 
    # Print the result
    return dp[A][B]
 
# Driver Code
if __name__ == '__main__':
     
    arr = [ "1", "0", "0001", "10", "111001" ]
    A, B = 5, 3
     
    print (MaxSubsetlength(arr, A, B))
 
# This code is contributed by mohit kumar 29


C#




// C# program for the above approach
using System;
 
class GFG {
 
  // Function to find the length of the
  // longest subset of an array of strings
  // with at most A 0s and B 1s
  static int MaxSubsetlength(string[] arr, int A, int B)
  {
 
    // Initialize a 2D array with its
    // entries as 0
    int[, ] dp = new int[A + 1, B + 1];
 
    // Traverse the given array
    foreach(string str in arr)
    {
 
      // Store the count of 0s and 1s
      // in the current string
      int zeros = 0, ones = 0;
      foreach(char ch in str.ToCharArray())
      {
        if (ch == '0')
          zeros++;
        else
          ones++;
      }
 
      // Iterate in the range [A, zeros]
      for (int i = A; i >= zeros; i--)
 
        // Iterate in the range [B, ones]
        for (int j = B; j >= ones; j--)
 
          // Update the value of dp[i][j]
          dp[i, j] = Math.Max(
          dp[i, j],
          dp[i - zeros, j - ones] + 1);
    }
 
    // Print the result
    return dp[A, B];
  }
 
  // Driver Code
  public static void Main(string[] args)
  {
    string[] arr = { "1", "0", "0001", "10", "111001" };
    int A = 5, B = 3;
 
    Console.WriteLine(MaxSubsetlength(arr, A, B));
  }
}
 
// This code is contributed by ukasp.


Javascript




<script>
 
// Javascript program for the above approach
 
// Function to find the length of the
// longest subset of an array of strings
// with at most A 0s and B 1s
function MaxSubsetlength(arr, A, B)
{
     
    // Initialize a 2D array with its
    // entries as 0
    var dp = Array.from(Array(A + 1),
         ()=>Array(B + 1).fill(0));
 
    // Traverse the given array
    arr.forEach(str => {
         
        // Store the count of 0s and 1s
        // in the current string
        var zeros = [...str].filter(x => x == '0').length;
        var ones = [...str].filter(x => x == '1').length;
 
        // Iterate in the range [A, zeros]
        for(var i = A; i >= zeros; i--)
 
            // Iterate in the range [B, ones]
            for(var j = B; j >= ones; j--)
 
                // Update the value of dp[i][j]
                dp[i][j] = Math.max(dp[i][j],
                    dp[i - zeros][j - ones] + 1);
    });
 
    // Print the result
    return dp[A][B];
}
 
// Driver Code
var arr = [ "1", "0", "0001",
            "10", "111001" ];
var A = 5, B = 3;
 
document.write(MaxSubsetlength(arr, A, B));
 
// This code is contributed by noob2000
 
</script>


Output: 

4

 

Time Complexity: O(N * A * B)
Auxiliary Space: O(A * B)

Efficient Approach : using array instead of 2d matrix to optimize space complexity 

The optimization comes from the fact that the in this approach we use a 1D array, which requires less memory compared to a 2D array. However, in this approach code requires an additional condition to check if the number of zeros is less than or equal to the allowed limit. 

Implementations Steps:

  • Initialize an array dp of size B+1 with all entries as 0.
  • Traverse through the given array of strings and for each string, count the number of 0’s and 1’s in it.
  • For each string, iterate from B to the number of 1’s in the string and update the value of dp[j] as maximum of dp[j] and dp[j – ones] + (1 if (j >= ones && A >= zeros) else 0).
  • Finally, return dp[B] as the length of the longest subset of strings with at most A 0’s and B 1’s.

Implementation:

C++




// C++ program for above approach
#include <bits/stdc++.h>
using namespace std;
 
// Function to find the length of the
// longest subset of an array of strings
// with at most A 0s and B 1s
int MaxSubsetlength(vector<string> arr, int A, int B)
{
    // Initialize a 1D array with its
    // entries as 0
    int dp[B + 1];
    memset(dp, 0, sizeof(dp));
 
    // Traverse the given array
    for (auto& str : arr) {
 
        // Store the count of 0s and 1s
        // in the current string
        int zeros = count(str.begin(), str.end(), '0');
        int ones = count(str.begin(), str.end(), '1');
 
        // Iterate in the range [B, ones]
        for (int j = B; j >= ones; j--)
 
            // Update the value of dp[j]
            dp[j] = max(
                dp[j],
                dp[j - ones]
                    + ((j >= ones && A >= zeros) ? 1 : 0));
    }
 
    // Print the result
    return dp[B];
}
 
// Driver Code
int main()
{
    vector<string> arr
        = { "1", "0", "0001", "10", "111001" };
    int A = 5, B = 3;
    cout << MaxSubsetlength(arr, A, B);
 
    return 0;
}
 
// this code is contributed by bhardwajji


Java




import java.util.*;
 
class Main {
    // Function to find the length of the
    // longest subset of an array of strings
    // with at most A 0s and B 1s
    static int MaxSubsetlength(List<String> arr, int A, int B) {
        // Initialize a 1D array with its
        // entries as 0
        int[] dp = new int[B + 1];
        Arrays.fill(dp, 0);
 
        // Traverse the given array
        for (String str : arr) {
 
            // Store the count of 0s and 1s
            // in the current string
            int zeros = 0, ones = 0;
            for (int i = 0; i < str.length(); i++) {
                if (str.charAt(i) == '0') zeros++;
                else ones++;
            }
 
            // Iterate in the range [B, ones]
            for (int j = B; j >= ones; j--) {
                // Update the value of dp[j]
                dp[j] = Math.max(dp[j], dp[j - ones] + ((j >= ones && A >= zeros) ? 1 : 0));
            }
        }
 
        // Print the result
        return dp[B];
    }
 
    // Driver Code
    public static void main(String[] args) {
        List<String> arr = Arrays.asList("1", "0", "0001", "10", "111001");
        int A = 5, B = 3;
        System.out.println(MaxSubsetlength(arr, A, B));
    }
}


Python3




# Python program for above approach
 
# Function to find the length of the
# longest subset of an array of strings
# with at most A 0s and B 1s
 
 
def MaxSubsetlength(arr, A, B):
    # Initialize a 1D array with its
    # entries as 0
    dp = [0] * (B + 1)
 
    # Traverse the given array
    for str in arr:
 
        # Store the count of 0s and 1s
        # in the current string
        zeros = str.count('0')
        ones = str.count('1')
 
        # Iterate in the range [B, ones]
        for j in range(B, ones - 1, -1):
 
            # Update the value of dp[j]
            dp[j] = max(
                dp[j],
                dp[j - ones]
                + ((j >= ones and A >= zeros) == True))
 
    # Print the result
    return dp[B]
 
 
# Driver Code
arr = ["1", "0", "0001", "10", "111001"]
A, B = 5, 3
print(MaxSubsetlength(arr, A, B))


C#




// importing necessary namespaces
using System;
using System.Collections.Generic;
 
// defining main class
class MainClass
{
 
  // Function to find the length of the longest subset
  // of an array of strings with at most A 0s and B 1s
  static int MaxSubsetlength(List<string> arr, int A, int B)
  {
 
    // Initialize a 1D array with its entries as 0
    int[] dp = new int[B + 1];
    Array.Fill(dp, 0);
 
    // Traverse the given array
    foreach (string str in arr)
    {
 
      // Store the count of 0s and 1s in the current string
      int zeros = 0, ones = 0;
      foreach (char c in str) {
        if (c == '0') zeros++;
        else ones++;
      }
 
      // Iterate in the range [B, ones]
      for (int j = B; j >= ones; j--)
      {
 
        // Update the value of dp[j]
        dp[j] = Math.Max(dp[j], dp[j - ones] + ((j >= ones && A >= zeros) ? 1 : 0));
      }
    }
 
    // Return the result
    return dp[B];
  }
 
  // Driver Code
  public static void Main(string[] args)
  {
 
    // Define the input
    List<string> arr = new List<string> {"1", "0", "0001", "10", "111001"};
    int A = 5, B = 3;
 
    // Call the function and print the result
    Console.WriteLine(MaxSubsetlength(arr, A, B));
  }
}


Javascript




// Function to find the length of the
// longest subset of an array of strings
// with at most A 0s and B 1s
function MaxSubsetlength(arr, A, B) {
  // Initialize a 1D array with its
  // entries as 0
  let dp = new Array(B + 1).fill(0);
 
  // Traverse the given array
  for (let i = 0; i < arr.length; i++) {
    const str = arr[i];
 
    // Store the count of 0s and 1s
    // in the current string
    let zeros = 0,
      ones = 0;
    for (let j = 0; j < str.length; j++) {
      if (str.charAt(j) === '0') zeros++;
      else ones++;
    }
 
    // Iterate in the range [B, ones]
    for (let j = B; j >= ones; j--) {
      // Update the value of dp[j]
      dp[j] = Math.max(dp[j], dp[j - ones] + ((j >= ones && A >= zeros) ? 1 : 0));
    }
  }
 
  // Print the result
  return dp[B];
}
 
// Driver Code
const arr = ["1", "0", "0001", "10", "111001"];
const A = 5,
  B = 3;
console.log(MaxSubsetlength(arr, A, B));


Output :

4

Time Complexity: O(N * A * B)
Auxiliary Space: O(B)

Feeling lost in the world of random DSA topics, wasting time without progress? It’s time for a change! Join our DSA course, where we’ll guide you on an exciting journey to master DSA efficiently and on schedule.
Ready to dive in? Explore our Free Demo Content and join our DSA course, trusted by over 100,000 neveropen!

Dominic Rubhabha Wardslaus
Dominic Rubhabha Wardslaushttps://neveropen.dev
infosec,malicious & dos attacks generator, boot rom exploit philanthropist , wild hacker , game developer,
RELATED ARTICLES

LEAVE A REPLY

Please enter your comment!
Please enter your name here

Most Popular

Recent Comments