Find the closest integer with same weight O(1) - algorithm

Question

I am solving this problem:
The count of ones in binary representation of integer number is called the weight of that number. The following algorithm finds the closest integer with the same weight. For example, for 123 (0111 1011)₂, the closest integer number is 125 (0111 1101)₂.
The solution for O(n)
where n is the width of the input number is by swapping the positions of the first pair of consecutive bits that differ.
Could someone give me some hints for solving in it in O(1) runtime and space ?
Thanks

Answer 1

As already commented by ajayv this cannot really be done in O(1) as the answer always depends on the number of bits the input has. However, if we interpret the O(1) to mean that we have as an input some primitive integer data and all the logic and arithmetic operations we perform on that integer are O(1) (no loops over the bits), the problem can be solved in constant time. Of course, if we changed from 32bit integer to 64bit integer the running time would increase as the arithmetic operations would take longer on hardware.
One possible solution is to use following functions. The first gives you a number where only the lowest set bit of x is set
int lowestBitSet(int x){
( x & ~(x-1) )
}
and the second the lowest bit not set
int lowestBitNotSet(int x){
return ~x & (x+1);
}
If you work few examples of these on paper you see how they work.
Now you can find the bits you need to change using these two functions and then use the algorithm you already described.
A c++ implementation (not checking for cases where there are no answer)
unsigned int closestInt(unsigned int x){
unsigned int ns=lowestBitNotSet(x);
unsigned int s=lowestBitSet(x);
if (ns>s){
x|=ns;
x^=ns>>1;
}
else{
x^=s;
x|=s>>1;
}
return x;
}

Answer 2

To solve this problem in O(1) time complexity it can be considered that there are two main cases:
1) When LSB is '0':
In this case, the first '1' must be shifted with one position to the right.
Input : "10001000"
Out ::: "10000100"
2) When LSB is '1':
In this case the first '0' must be set to '1', and first '1' must be set to '0'.
Input : "10000111"
Out ::: "10001110"
The next method in Java represents one solution.
private static void findClosestInteger(String word) { // ex: word = "10001000"
System.out.println(word); // Print initial binary format of the number
int x = Integer.parseInt(word, 2); // Convert String to int
if((x & 1) == 0) { // Evaluates LSB value
// Case when LSB = '0':
// Input: x = 10001000
int firstOne = x & ~(x -1); // get first '1' position (from right to left)
// firstOne = 00001000
x = x & (x - 1); // set first '1' to '0'
// x = 10000000
x = x | (firstOne >> 1); // "shift" first '1' with one position to right
// x = 10000100
} else {
// Case when LSB = '1':
// Input: x = 10000111
int firstZero = ~x & ~(~x - 1); // get first '0' position (from right to left)
// firstZero = 00001000
x = x & (~1); // set first '1', which is the LSB, to '0'
// x = 10000110
x = x | firstZero; // set first '0' to '1'
// x = 10001110
}
for(int i = word.length() - 1; i > -1 ; i--) { // print the closest integer with same weight
System.out.print("" + ( ( (x & 1 << i) != 0) ? 1 : 0) );
}
}

Answer 3

The problem can be viewed as "which differing bits to swap in a bit representation of a number, so that the resultant number is closest to the original?"
So, if we we're to swap bits at indices k1 & k2, with k2 > k1, the difference between the numbers would be 2^k2 - 2^k1. Our goal is to minimize this difference. Assuming that the bit representation is not all 0s or all 1s, a simple observation yields that the difference would be least if we kept |k2 - k1| as minimum. The minimum value can be 1. So, if we're able to find two consecutive different bits, starting from the least significant bit (index = 0), our job is done.
The case where bits starting from Least Significant Bit to the right most set bit are all 1s
k2
|
7 6 5 4 3 2 1 0
---------------
n: 1 1 1 0 1 0 1 1
rightmostSetBit: 0 0 0 0 0 0 0 1
rightmostNotSetBit: 0 0 0 0 0 1 0 0 rightmostNotSetBit > rightmostSetBit so,
difference: 0 0 0 0 0 0 1 0 i.e. rightmostNotSetBit - (rightmostNotSetBit >> 1):
---------------
n + difference: 1 1 1 0 1 1 0 1
The case where bits starting from Least Significant Bit to the right most set bit are all 0s
k2
|
7 6 5 4 3 2 1 0
---------------
n: 1 1 1 0 1 1 0 0
rightmostSetBit: 0 0 0 0 0 1 0 0
rightmostNotSetBit: 0 0 0 0 0 0 0 1 rightmostSetBit > rightmostNotSetBit so,
difference: 0 0 0 0 0 0 1 0 i.e. rightmostSetBit -(rightmostSetBit>> 1)
---------------
n - difference: 1 1 1 0 1 0 1 0
The edge case, of course the situation where we have all 0s or all 1s.
public static long closestToWeight(long n){
if(n <= 0 /* If all 0s */ || (n+1) == Integer.MIN_VALUE /* n is MAX_INT */)
return -1;
long neg = ~n;
long rightmostSetBit = n&~(n-1);
long rightmostNotSetBit = neg&~(neg-1);
if(rightmostNotSetBit > rightmostSetBit){
return (n + (rightmostNotSetBit - (rightmostNotSetBit >> 1)));
}
return (n - (rightmostSetBit - (rightmostSetBit >> 1)));
}

Answer 4

Attempted the problem in Python. Can be viewed as a translation of Ari's solution with the edge case handled:
def closest_int_same_bit_count(x):
# if all bits of x are 0 or 1, there can't be an answer
if x & sys.maxsize in {sys.maxsize, 0}:
raise ValueError("All bits are 0 or 1")
rightmost_set_bit = x & ~(x - 1)
next_un_set_bit = ~x & (x + 1)
if next_un_set_bit > rightmost_set_bit:
# 0 shifted to the right e.g 0111 -> 1011
x ^= next_un_set_bit | next_un_set_bit >> 1
else:
# 1 shifted to the right 1000 -> 0100
x ^= rightmost_set_bit | rightmost_set_bit >> 1
return x
Similarly jigsawmnc's solution is provided below:
def closest_int_same_bit_count(x):
# if all bits of x are 0 or 1, there can't be an answer
if x & sys.maxsize in {sys.maxsize, 0}:
raise ValueError("All bits are 0 or 1")
rightmost_set_bit = x & ~(x - 1)
next_un_set_bit = ~x & (x + 1)
if next_un_set_bit > rightmost_set_bit:
# 0 shifted to the right e.g 0111 -> 1011
x += next_un_set_bit - (next_un_set_bit >> 1)
else:
# 1 shifted to the right 1000 -> 0100
x -= rightmost_set_bit - (rightmost_set_bit >> 1)
return x

Answer 5

Java Solution:
//Swap the two rightmost consecutive bits that are different
for (int i = 0; i < 64; i++) {
if ((((x >> i) & 1) ^ ((x >> (i+1)) & 1)) == 1) {
// then swap them or flip their bits
int mask = (1 << i) | (1 << i + 1);
x = x ^ mask;
System.out.println("x = " + x);
return;
}
}

Answer 6

static void findClosestIntWithSameWeight(uint x)
{
uint xWithfirstBitSettoZero = x & (x - 1);
uint xWithOnlyfirstbitSet = x & ~(x - 1);
uint xWithNextTofirstBitSet = xWithOnlyfirstbitSet >> 1;
uint closestWeightNum = xWithfirstBitSettoZero | xWithNextTofirstBitSet;
Console.WriteLine("Closet Weight for {0} is {1}", x, closestWeightNum);
}

Answer 7

Code in python:
def closest_int_same_bit_count(x):
if (x & 1) != ((x >> 1) & 1):
return x ^ 0x3
diff = x ^ (x >> 1)
rbs = diff & ~(diff - 1)
i = int(math.log(rbs, 2))
return x ^ (1 << i | 1 << i + 1)

Answer 8

A great explanation of this problem can be found on question 4.4 in EPI.
(Elements of Programming Interviews)
Another place would be this link on geeksforgeeks.org if you don't own the book.
(Time complexity may be wrong on this link)
Two things you should keep in mind here is (Hint if you're trying to solve this for yourself):
You can use x & (x - 1) to clear the lowest set-bit (not to get confused with LSB - least significant bit)
You can use x & ~(x - 1) to get/extract the lowest set bit
If you know the O(n) solution you know that we need to find the index of the first bit that differs from LSB.
If you don't know what the LBS is:
0000 0000
^ // it's bit all the way to the right of a binary string.
Take the base two number 1011 1000 (184 in decimal)
The first bit that differs from LSB:
1011 1000
^ // this one
We'll record this as K1 = 0000 1000
Then we need to swap it with the very next bit to the right:
0000 1000
^ // this one
We'll record this as K2 = 0000 0100
Bitwise OR K1 and K2 together and you'll get a mask
mask = K1 | k2 // 0000 1000 | 0000 0100 -> 0000 1100
Bitwise XOR the mask with the original number and you'll have the correct output/swap
number ^ mask // 1011 1000 ^ 0000 1100 -> 1011 0100
Now before we pull everything together we have to consider that fact that the LSB could be 0001, and so could a bunch of bits after that 1000 1111. So we have to deal with the two cases of the first bit that differs from the LSB; it may be a 1 or 0.
First we have a conditional that test the LSB to be 1 or 0: x & 1
IF 1 return x XORed with the return of a helper function
This helper function has a second argument which its value depends on whether the condition is true or not. func(x, 0xFFFFFFFF) // if true // 0xFFFFFFFF 64 bit word with all bits set to 1
Otherwise we'll skip the if statement and return a similar expression but with a different value provided to the second argument.
return x XORed with func(x, 0x00000000) // 64 bit word with all bits set to 0. You could alternatively just pass 0 but I did this for consistency
Our helper function returns a mask that we are going to XOR with the original number to get our output.
It takes two arguments, our original number and a mask, used in this expression:
(x ^ mask) & ~((x ^ mask) - 1)
which gives us a new number with the bit at index K1 always set to 1.
It then shifts that bit 1 to the right (i.e index K2) then ORs it with itself to create our final mask
0000 1000 >> 1 -> 0000 0100 | 0001 0000 -> 0000 1100
This all implemented in C++ looks like:
unsigned long long int closestIntSameBitCount(unsigned long long int n)
{
if (n & 1)
return n ^= getSwapMask(n, 0xFFFFFFFF);
return n ^= getSwapMask(n, 0x00000000);
}
// Helper function
unsigned long long int getSwapMask(unsigned long long int n, unsigned long long int mask)
{
unsigned long long int swapBitMask = (n ^ mask) & ~((n ^ mask) - 1);
return swapBitMask | (swapBitMask >> 1);
}
Keep note of the expression (x ^ mask) & ~((x ^ mask) - 1)
I'll now run through this code with my example 1011 1000:
// start of closestIntSameBitCount
if (0) // 1011 1000 & 1 -> 0000 0000
// start of getSwapMask
getSwapMask(1011 1000, 0x00000000)
swapBitMask = (x ^ mask) & ~1011 0111 // ((x ^ mask) - 1) = 1011 1000 ^ .... 0000 0000 -> 1011 1000 - 1 -> 1011 0111
swapBitMask = (x ^ mask) & 0100 1000 // ~1011 0111 -> 0100 1000
swapBitMask = 1011 1000 & 0100 1000 // (x ^ mask) = 1011 1000 ^ .... 0000 0000 -> 1011 1000
swapBitMask = 0000 1000 // 1011 1000 & 0100 1000 -> 0000 1000
return swapBitMask | 0000 0100 // (swapBitMask >> 1) = 0000 1000 >> 1 -> 0000 0100
return 0000 1100 // 0000 1000 | 0000 0100 -> 0000 11000
// end of getSwapMask
return 1011 0100 // 1011 1000 ^ 0000 11000 -> 1011 0100
// end of closestIntSameBitCount
Here is a full running example if you would like compile and run it your self:
#include <iostream>
#include <stdio.h>
#include <bitset>
unsigned long long int closestIntSameBitCount(unsigned long long int n);
unsigned long long int getSwapMask(unsigned long long int n, unsigned long long int mask);
int main()
{
unsigned long long int number;
printf("Pick a number: ");
std::cin >> number;
std::bitset<64> a(number);
std::bitset<64> b(closestIntSameBitCount(number));
std::cout << a
<< "\n"
<< b
<< std::endl;
}
unsigned long long int closestIntSameBitCount(unsigned long long int n)
{
if (n & 1)
return n ^= getSwapMask(n, 0xFFFFFFFF);
return n ^= getSwapMask(n, 0x00000000);
}
// Helper function
unsigned long long int getSwapMask(unsigned long long int n, unsigned long long int mask)
{
unsigned long long int swapBitMask = (n ^ mask) & ~((n ^ mask) - 1);
return swapBitMask | (swapBitMask >> 1);
}

Answer 9

This was my solution to the problem. I guess #jigsawmnc explains pretty well why we need to have |k2 -k1| to a minimum. So in order to find the closest integer, with the same weight, we would want to find the location where consecutive bits are flipped and then flip them again to get the answer. In order to do that we can shift the number 1 unit. Take the XOR with the same number. This will set bits at all locations where there is a flip. Find the least significant bit for the XOR. This will give you the smallest location to flip. Create a mask for the location and next bit. Take an XOR and that should be the answer. This won't work, if the digits are all 0 or all 1
Here is the code for it.
def variant_closest_int(x: int) -> int:
if x == 0 or ~x == 0:
raise ValueError('All bits are 0 or 1')
x_ = x >> 1
lsb = x ^ x_
mask_ = lsb & ~(lsb - 1)
mask = mask_ | (mask_ << 1)
return x ^ mask

Answer 10

My solution, takes advantage of the parity of the integer. I think the way I got the LSB masks can be simplified
def next_weighted_int(x):
if x % 2 == 0:
lsb_mask = ( ((x - 1) ^ x) >> 1 ) + 1 # Gets a mask for the first 1
x ^= lsb_mask
x |= (lsb_mask >> 1)
return x
lsb_mask = ((x ^ (x + 1)) >> 1 ) + 1 # Gets a mask for the first 0
x |= lsb_mask
x ^= (lsb_mask >> 1)
return x

Answer 11

Just sharing my python solution for this problem:
def same closest_int_same_bit_count(a):
x = a + (a & 1) # change last bit to 0
bit = (x & ~(x-1)) # get last set bit
return a ^ (bit | bit >> 1) # swap set bit with unset bit

Answer 12

func findClosestIntegerWithTheSameWeight2(x int) int {
rightMost0 := ^x & (x + 1)
rightMost1 := x & (-x)
if rightMost0 > 1 {
return (x ^ rightMost0) ^ (rightMost0 >> 1)
} else {
return (x ^ rightMost1) ^ (rightMost1 >> 1)
}
}