Open In App

Minimum number of changes such that elements are first Negative and then Positive

Last Updated : 09 Jun, 2022
Comments
Improve
Suggest changes
Like Article
Like
Report

Given an array arr[] of size N. The task is to find the minimum number of changes required to convert the array such that for any index 0 ? k < N, the elements in the array upto k-th index will be less than zero and after k-th index will be greater than zero.
That is: 
 

arr[0] < 0, arr[1] < 0, ..., arr[k] < 0 and arr[k + 1] > 0, arr[k + 2] > 0, ..., arr[N - 1] > 0
 


Examples: 
 

Input: arr[] = { -1, 1, 2, -1} 
Output:
Replace last -1 with any positive integer.
Input: arr[] = { -1, 0, 1, 2 } 
Output:
Replace 0 with any negative integer. 
 


 


Approach: First, find for each valid k, the number of non-negative integers to the left of it and the number of non-positive integers to the right. Now, run a loop for each valid k (0 ? k <n) and find the sum of the number of non-negative integers left to it and number of non-positive integers right to it, and the minimum of these values for every k is our required answer.
Below is the implementation of the above approach: 
 

C++
// C++ implementation of the approach
#include <bits/stdc++.h>
using namespace std;

// Function to return the count
// of minimum operations required
int Minimum_Operations(int a[], int n)
{

    // To store the count of negative integers
    // on the right of the current index (inclusive)
    int np[n + 1];
    np[n] = 0;

    // Find the count of negative integers
    // on the right
    for (int i = n - 1; i >= 0; i--) {
        np[i] = np[i + 1];

        // If current element is negative
        if (a[i] <= 0)
            np[i]++;
    }

    // To store the count of positive elements
    int pos = 0;
    int ans = n;

    // Find the positive integers
    // on the left
    for (int i = 0; i < n - 1; i++) {

        // If current element is positive
        if (a[i] >= 0)
            pos++;

        // Update the answer
        ans = min(ans, pos + np[i + 1]);
    }

    // Return the required answer
    return ans;
}

// Driver code
int main()
{
    int a[] = { -1, 0, 1, 2 };
    int n = sizeof(a) / sizeof(a[0]);
    cout << Minimum_Operations(a, n);

    return 0;
}
Java
// Java implementation of the approach 
class GFG
{
    
// Function to return the count 
// of minimum operations required 
static int Minimum_Operations(int []a, int n) 
{ 

    // To store the count of negative integers 
    // on the right of the current index (inclusive) 
    int[] np = new int[n + 1]; 
    np[n] = 0; 

    // Find the count of negative integers 
    // on the right 
    for (int i = n - 1; i >= 0; i--)
    { 
        np[i] = np[i + 1]; 

        // If current element is negative 
        if (a[i] <= 0) 
            np[i]++; 
    } 

    // To store the count of positive elements 
    int pos = 0; 
    int ans = n; 

    // Find the positive integers 
    // on the left 
    for (int i = 0; i < n - 1; i++) 
    { 

        // If current element is positive 
        if (a[i] >= 0) 
            pos++; 

        // Update the answer 
        ans = Math.min(ans, pos + np[i + 1]); 
    } 

    // Return the required answer 
    return ans; 
} 

// Driver code 
public static void main(String args[]) 
{ 
    int []a = { -1, 0, 1, 2 }; 
    int n = a.length; 
    System.out.print(Minimum_Operations(a, n)); 
} 
}

// This code is contributed by Akanksha Rai
Python3
# Python3 implementation of the approach

# Function to return the count
# of minimum operations required
def Minimum_Operations(a, n):

    # To store the count of negative integers
    # on the right of the current index (inclusive)
    np = [0 for i in range(n + 1)]

    # Find the count of negative integers
    # on the right
    for i in range(n - 1, -1, -1):
        np[i] = np[i + 1]

        # If current element is negative
        if (a[i] <= 0):
            np[i] += 1

    # To store the count of positive elements
    pos = 0
    ans = n

    # Find the positive integers
    # on the left
    for i in range(n - 1):

        # If current element is positive
        if (a[i] >= 0):
            pos += 1

        # Update the answer
        ans = min(ans, pos + np[i + 1])

    # Return the required answer
    return ans

# Driver code
a = [-1, 0, 1, 2]
n = len(a)
print(Minimum_Operations(a, n))

# This code is contributed by mohit kumar
C#
// C# implementation of the approach 
using System; 

class GFG
{
    
// Function to return the count 
// of minimum operations required 
static int Minimum_Operations(int []a, int n) 
{ 

    // To store the count of negative integers 
    // on the right of the current index (inclusive) 
    int[] np = new int[n + 1]; 
    np[n] = 0; 

    // Find the count of negative integers 
    // on the right 
    for (int i = n - 1; i >= 0; i--)
    { 
        np[i] = np[i + 1]; 

        // If current element is negative 
        if (a[i] <= 0) 
            np[i]++; 
    } 

    // To store the count of positive elements 
    int pos = 0; 
    int ans = n; 

    // Find the positive integers 
    // on the left 
    for (int i = 0; i < n - 1; i++) 
    { 

        // If current element is positive 
        if (a[i] >= 0) 
            pos++; 

        // Update the answer 
        ans = Math.Min(ans, pos + np[i + 1]); 
    } 

    // Return the required answer 
    return ans; 
} 

// Driver code 
static void Main() 
{ 
    int []a = { -1, 0, 1, 2 }; 
    int n = a.Length; 
    Console.WriteLine(Minimum_Operations(a, n)); 
} 
}

// This code is contributed by mits
PHP
<?php
// PHP implementation of the approach 

// Function to return the count 
// of minimum operations required 
function Minimum_Operations($a, $n) 
{ 

    // To store the count of negative 
    // integers on the right of the 
    // current index (inclusive) 
    $np = array(); 
    $np[$n] = 0; 

    // Find the count of negative 
    // integers on the right 
    for ($i = $n - 1; $i >= 0; $i--) 
    { 
        $np[$i] = $np[$i + 1]; 

        // If current element is negative 
        if ($a[$i] <= 0) 
            $np[$i]++; 
    } 

    // To store the count of positive elements 
    $pos = 0; 
    $ans = $n; 

    // Find the positive integers 
    // on the left 
    for ($i = 0; $i < $n - 1; $i++)
    { 

        // If current element is positive 
        if ($a[$i] >= 0) 
            $pos++; 

        // Update the answer 
        $ans = min($ans, $pos + $np[$i + 1]); 
    } 

    // Return the required answer 
    return $ans; 
} 

// Driver code 
$a = array( -1, 0, 1, 2 ); 
$n = count($a) ;

echo Minimum_Operations($a, $n); 

// This code is contributed by Ryuga
?>
JavaScript
<script>

// JavaScript implementation of the approach

// Function to return the count 
// of minimum operations required 
function Minimum_Operations(a, n) 
{ 
  
    // To store the count of negative integers 
    // on the right of the current index (inclusive) 
    let np = Array(n+1).fill(0);
    np[n] = 0; 
  
    // Find the count of negative integers 
    // on the right 
    for (let i = n - 1; i >= 0; i--)
    { 
        np[i] = np[i + 1]; 
  
        // If current element is negative 
        if (a[i] <= 0) 
            np[i]++; 
    } 
  
    // To store the count of positive elements 
    let pos = 0; 
    let ans = n; 
  
    // Find the positive integers 
    // on the left 
    for (let i = 0; i < n - 1; i++) 
    { 
  
        // If current element is positive 
        if (a[i] >= 0) 
            pos++; 
  
        // Update the answer 
        ans = Math.min(ans, pos + np[i + 1]); 
    } 
  
    // Return the required answer 
    return ans; 
} 
          
// Driver Code

    let a = [ -1, 0, 1, 2 ]; 
    let n = a.length; 
    document.write(Minimum_Operations(a, n)); 
          
</script>

Output: 
1

 

Time Complexity: O(n)
Auxiliary Space: O(n)


Next Article

Similar Reads