Given a number X, the task is to find the minimum number N such that the total set bits of all numbers from 1 to n is at least X.
Examples:
Input: x = 5 Output: 4 Set bits in 1-> 1 Set bits in 2-> 1 Set bits in 3-> 2 Set bits in 4-> 1 Hence first four numbers add upto 5 Input: x = 20 Output: 11
Approach: Use binary search to get the minimum most number whose sum of bits till N is at least X. At the start, low is 0, and high is initialized according to the constraint. Check if the count of set bits is at least X, every time it is, change high to mid-1, else change it to mid+1. Every time we do high = mid-1, store the minimal of answer.
Below is the implementation of the above approach:
C++
// C++ implementation of the above approach #include <bits/stdc++.h> using namespace std; #define INF 99999 #define size 10 // Function to count sum of set bits // of all numbers till N int getSetBitsFromOneToN( int N) { int two = 2, ans = 0; int n = N; while (n) { ans += (N / two) * (two >> 1); if ((N & (two - 1)) > (two >> 1) - 1) ans += (N & (two - 1)) - (two >> 1) + 1; two <<= 1; n >>= 1; } return ans; } // Function to find the minimum number int findMinimum( int x) { int low = 0, high = 100000; int ans = high; // Binary search for the lowest number while (low <= high) { // Find mid number int mid = (low + high) >> 1; // Check if it is atleast x if (getSetBitsFromOneToN(mid) >= x) { ans = min(ans, mid); high = mid - 1; } else low = mid + 1; } return ans; } // Driver Code int main() { int x = 20; cout << findMinimum(x); return 0; } |
Java
// Java implementation of the above approach import java.util.*; class solution { static int INF = 99999 ; static int size = 10 ; // Function to count sum of set bits // of all numbers till N static int getSetBitsFromOneToN( int N) { int two = 2 , ans = 0 ; int n = N; while (n!= 0 ) { ans += (N / two) * (two >> 1 ); if ((N & (two - 1 )) > (two >> 1 ) - 1 ) ans += (N & (two - 1 )) - (two >> 1 ) + 1 ; two <<= 1 ; n >>= 1 ; } return ans; } // Function to find the minimum number static int findMinimum( int x) { int low = 0 , high = 100000 ; int ans = high; // Binary search for the lowest number while (low <= high) { // Find mid number int mid = (low + high) >> 1 ; // Check if it is atleast x if (getSetBitsFromOneToN(mid) >= x) { ans = Math.min(ans, mid); high = mid - 1 ; } else low = mid + 1 ; } return ans; } // Driver Code public static void main(String args[]) { int x = 20 ; System.out.println(findMinimum(x)); } } //This code is contributed by // Shashank_Sharma |
Python3
# Python3 implementation of the # above approach INF = 99999 size = 10 # Function to count sum of set bits # of all numbers till N def getSetBitsFromOneToN(N): two, ans = 2 , 0 n = N while (n > 0 ): ans + = (N / / two) * (two >> 1 ) if ((N & (two - 1 )) > (two >> 1 ) - 1 ): ans + = (N & (two - 1 )) - (two >> 1 ) + 1 two << = 1 n >> = 1 return ans # Function to find the minimum number def findMinimum(x): low = 0 high = 100000 ans = high # Binary search for the lowest number while (low < = high): # Find mid number mid = (low + high) >> 1 # Check if it is atleast x if (getSetBitsFromOneToN(mid) > = x): ans = min (ans, mid) high = mid - 1 else : low = mid + 1 return ans # Driver Code x = 20 print (findMinimum(x)) # This code is contributed by # Mohit kumar 29 |
C#
// C# implementation of the above approach using System ; class solution { static int INF = 99999; static int size = 10; // Function to count sum of set bits // of all numbers till N static int getSetBitsFromOneToN( int N) { int two = 2, ans = 0; int n = N; while (n!=0) { ans += (N / two) * (two >> 1); if ((N & (two - 1)) > (two >> 1) - 1) ans += (N & (two - 1)) - (two >> 1) + 1; two <<= 1; n >>= 1; } return ans; } // Function to find the minimum number static int findMinimum( int x) { int low = 0, high = 100000; int ans = high; // Binary search for the lowest number while (low <= high) { // Find mid number int mid = (low + high) >> 1; // Check if it is atleast x if (getSetBitsFromOneToN(mid) >= x) { ans = Math.Min(ans, mid); high = mid - 1; } else low = mid + 1; } return ans; } // Driver Code public static void Main() { int x = 20; Console.WriteLine(findMinimum(x)); } // This code is contributed by Ryuga } |
PHP
<?php // PHP implementation of the above approach // Function to count sum of set bits // of all numbers till N function getSetBitsFromOneToN( $N ) { $two = 2; $ans = 0; $n = $N ; while ( $n ) { $ans += (int)( $N / $two ) * ( $two >> 1); if (( $N & ( $two - 1)) > ( $two >> 1) - 1) $ans += ( $N & ( $two - 1)) - ( $two >> 1) + 1; $two <<= 1; $n >>= 1; } return $ans ; } // Function to find the minimum number function findMinimum( $x ) { $low = 0; $high = 100000; $ans = $high ; // Binary search for the lowest number while ( $low <= $high ) { // Find mid number $mid = ( $low + $high ) >> 1; // Check if it is atleast x if (getSetBitsFromOneToN( $mid ) >= $x ) { $ans = min( $ans , $mid ); $high = $mid - 1; } else $low = $mid + 1; } return $ans ; } // Driver Code $x = 20; echo findMinimum( $x ); // This code is contributed // by Sach_Code ?> |
Javascript
<script> // Javascript implementation of the above approach const INF = 99999; const size = 10; // Function to count sum of set bits // of all numbers till N function getSetBitsFromOneToN(N) { let two = 2, ans = 0; let n = N; while (n) { ans += parseInt(N / two) * (two >> 1); if ((N & (two - 1)) > (two >> 1) - 1) ans += (N & (two - 1)) - (two >> 1) + 1; two <<= 1; n >>= 1; } return ans; } // Function to find the minimum number function findMinimum(x) { let low = 0, high = 100000; let ans = high; // Binary search for the lowest number while (low <= high) { // Find mid number let mid = (low + high) >> 1; // Check if it is atleast x if (getSetBitsFromOneToN(mid) >= x) { ans = Math.min(ans, mid); high = mid - 1; } else low = mid + 1; } return ans; } // Driver Code let x = 20; document.write(findMinimum(x)); // This code is contributed by subhammahato348 </script> |
11
Time Complexity: O(log N * log N), the getSetBitsFromOneToN will take logN time as we are using the bitwise right shift in each traversal which is equivalent to floor division with 2 in each traversal so the cost will be 1+1/2+1/4+….+1/2N which is equivalent to logN. We are using binary search and each time we are calling getSetBitsFromOneToN function. Binary Search also takes logN time as we decrement each time by floor division of 2. So, the effective cost of the program will be O(logN*logN).
Auxiliary Space: O(1), as we are not using any extra space.
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