I am having hard time understanding below solution in leetcode. Why int powerOfTwo = -1 is initialized with -1 as we have already handled divide(INT_MIN, -1) case
:
Adding problem statement -
Given two integers dividend and divisor, divide two integers without using multiplication, division, and mod operator.
Return the quotient after dividing dividend by divisor.
The integer division should truncate toward zero, which means losing its fractional part. For example, truncate(8.345) = 8 and truncate(-2.7335) = -2.
Note:
Assume we are dealing with an environment that could only store integers within the 32-bit signed integer range: [−2^31, 2^31 − 1]. For this problem, assume that your function returns 2^31 − 1 when the division result overflows.
Example 1:
Input: dividend = 10, divisor = 3
Output: 3
Explanation: 10/3 = truncate(3.33333..) = 3.
https://leetcode.com/problems/divide-two-integers/solution/
private static int HALF_INT_MIN = -1073741824;
public int divide(int dividend, int divisor) {
// Special case: overflow.
if (dividend == Integer.MIN_VALUE && divisor == -1) {
return Integer.MAX_VALUE;
}
/* We need to convert both numbers to negatives.
* Also, we count the number of negatives signs. */
int negatives = 2;
if (dividend > 0) {
negatives--;
dividend = -dividend;
}
if (divisor > 0) {
negatives--;
divisor = -divisor;
}
int quotient = 0;
/* Once the divisor is bigger than the current dividend,
* we can't fit any more copies of the divisor into it. */
while (divisor >= dividend) {
/* We know it'll fit at least once as divivend >= divisor.
* Note: We use a negative powerOfTwo as it's possible we might have
* the case divide(INT_MIN, -1). */
int powerOfTwo = -1;
int value = divisor;
/* Check if double the current value is too big. If not, continue doubling.
* If it is too big, stop doubling and continue with the next step */
while (value >= HALF_INT_MIN && value + value >= dividend) {
value += value;
powerOfTwo += powerOfTwo;
}
// We have been able to subtract divisor another powerOfTwo times.
quotient += powerOfTwo;
// Remove value so far so that we can continue the process with remainder.
dividend -= value;
}
/* If there was originally one negative sign, then
* the quotient remains negative. Otherwise, switch
* it to positive. */
if (negatives != 1) {
return -quotient;
}
return quotient;
}
I hava see this code in HashMap:
/**
* Returns index for hash code h.
*/
static int indexFor(int h, int length) {
// assert Integer.bitCount(length) == 1 : "length must be a non-zero power of 2";
return h & (length-1);
}
The HashMap has this document:
when length is a power of two then h & (length-1) is equals h%length
I want to know the principle in math
just is why h & (length-1) == h%length (length is a power of two)
First you can think what it looks like when you take any integer n mod power of 2.
WLOG let this power of 2 is 10000 in binary (indeed it must be of the form 100...0), what does its multiples looks like? Its multiples must look like...whatever digit...0000. The last 4 digit must be zero.
So what is a number n mod 10000? Let this number n be ...whatever digit...1011. This number can be expressed as ...whatever digit...0000 + 1011, now it is obvious that n mod 10000 indeed only the last 4 digits is left.
In general, let length be a power of 2 which has x zeros, then n%length is the least x significant digits of n
So legnth - 1is indeed 111..111 (x digit 1), and when you take bitwise and with the number n, the least x significant digits of n is preserved and returned, which is what we want. Using the same example above,
Length = 10000, Length - 1 = 1111
n = 101001101 = 101000000 + 1101
=> n % Length = 1101
n & (Length - 1) = 1101
= n % Length
Just imagine: any power of two contains single bit set and has binary representation like this:
l = 00010000
if you subtract 1, it will contain ones at the right places
m = l-1 = 00001111
binary AND operation with any h makes all most significant bits zero, leaving less significant ones
10101010 & 00001111 = 00001010
This is equivalent to modulo operation with modulo l
Here is the description:
In order to stop the Mad Coder evil genius you need to decipher the encrypted message he sent to his minions. The message contains several numbers that, when typed into a supercomputer, will launch a missile into the sky blocking out the sun, and making all the people on Earth grumpy and sad.
You figured out that some numbers have a modified single digit in their binary representation. More specifically, in the given number n the kth bit from the right was initially set to 0, but its current value might be different. It's now up to you to write a function that will change the kth bit of n back to 0.
Example
For n = 37 and k = 3, the output should be
killKthBit(n, k) = 33.
3710 = 1001012 ~> 1000012 = 3310.
For n = 37 and k = 4, the output should be
killKthBit(n, k) = 37.
The 4th bit is 0 already (looks like the Mad Coder forgot to encrypt this number), so the answer is still 37."
Here is a solution I found and I cannot understand it:
int killKthBit(int n, int k)
{
return n & ~(1 << (k - 1)) ;
}
Can someone explain what the solution does and its syntax?
Detailed explanation of your function
The expression 1 << (k - 1) shifts the number 1 exactly k-1 times to the left so as an example for an 8 Bit number and k = 4:
Before shift: 00000001
After Shift: 00010000
This marks the bit to kill. You see, 1 was shifted to the fourth position, as it was on position zero. The operator ~ negates each bit, meaning 1 becomes 0 and 0 becomes 1. For our example:
Before negation: 00010000
After negation: 11101111
At last, & executes a bit-wise AND on two operands. Let us say, we have a number n = 17, which is 00010001 in binary. Our example now is:
00010001 & 11101111 = 00000001
This is, because each bit of both numbers is compared by AND on the same position. Only positions, where both numbers have a 1 remain 1, all others are set to 0. Consequently, only position zero remains 1.
Overall your method int killKthBit(int n, int k) does exactly that with binary operators, it sets the bit on position k of number n to 0.
Here is my try
//Returns a number that has all bits same as n
// except the k'th bit which is made 0
int turnOffK(int n, int k)
{
// k must be greater than 0
if (k <= 0) return n;
// Do & of n with a number with all set bits except
// the k'th bit
return (n & ~(1 << (k - 1)));
}
I want to implement a function to get the absolute value of a number in java: do nothing if it is positive, if it is negative, convert to positive.
I want to do this only using bit manipulations and no number comparators.
Please help
Well a negation:
-n
Is the same as the two's complement:
~n + 1
The problem is here you only want to negate if the value is < 0. You can find that out by using a logical shift to see if the MSB is set:
n >>> 31
A complement would be the same as an XOR with all 1's, something like (for a 4-bit integer):
~1010 == 1010 ^ 1111
And we can get a mask with the arithmetic right shift:
n >> 31
Absolute value says:
if n is < 0, negate it (take the complement and add 1 to it)
else, do nothing to it
So putting it together we can do the following:
static int abs(int n) {
return (n ^ (n >> 31)) + (n >>> 31);
}
Which computes:
if n is < 0, XOR it with all 1's and add 1 to it
else, XOR it with all 0's and add 0 to it
I'm not sure there's an easy way to do it without the addition. Addition involves any number of carries, even for a simple increment.
For example 2 + 1 has no carry:
10 + 1 == 11
But 47 + 1 has 4 carries:
101111 + 1 == 110000
Doing the add and carry with bitwise/bit shifts would basically just be a loop unroll and pointless.
(Edit!)
Just to be silly, here is an increment and carry:
static int abs(int n) {
int s = n >>> 31;
n ^= n >> 31;
int c;
do {
c = (n & s) << 1;
n ^= s;
} while((s = c) != 0);
return n;
}
The way it works is it flips the first bit, then keeps flipping until it finds a 0. So then the job is just to unroll the loop. The loop body can be represented by a somewhat ridiculous compound one-liner.
static int abs(int n) {
int s = n >>> 31;
n ^= n >> 31;
int c = (n & s) << 1;
c = ((n ^= s) & (s = c)) << 1; // repeat this line 30 more times
n ^= s;
return n;
}
So there's an abs using only bitwise and bit shifts.
These aren't faster than Math.abs. Math.abs just returns n < 0 ? -n : n which is trivial. And actually the loop unroll totally sucks in comparison. Just a curiosity I guess. Here's my benchmark:
Math.abs: 4.627323150634766ns
shift/xor/add abs: 6.729459762573242ns
loop abs: 12.028789520263672ns
unrolled abs: 32.47122764587402ns
bit hacks abs: 6.380939483642578ns
(The bit hacks abs is the non-patented one shown here which is basically the same idea as mine except a little harder to understand.)
you can turn a two's-compliment number positive or negative by taking it's logical negation
i = ~i; // i equals not i
You can use the Math.max() function to always get the positive
public static int abs(int i) {
return Math.max(i,~i);
}
This depends on what type of number you are using. For an int, use
int sign = i >> 31;
This gets the sign bit, which is 0 for positive numbers, and 1 for negative numbers. For other primitive types, replace 31 with the number of bits used for the primitive minus 1.
You can then use that sign in your if statement.
if (sign == 1)
i = ~i + 1;
I think you'll find that this little ditty is what you're looking for:
int abs(int v) {
int mask = v >> Integer.SIZE - 1;
return v + mask ^ mask;
}
It's based on Bit Twiddling Hacks absolute value equation and uses no comparison operations. If you aren't allowed to use addition, then (v ^ mask) - mask is an alternative. The value of this function is fairly questionable; since it's nearly as clear as the implementation of Math.abs and it's only marginally faster (at least on a i7):
v + mask ^ mask: 2.0844380704220384 abs/ns
(v ^ mask) - mask: 2.0819764093030244 abs/ns
Math.abs: 2.2636355843860656 abs/ns
Here's a test that proves that it works over the entire range of integers (the test runs in less than 2 minutes on an i7 processor under Java 7 update 51):
package test;
import org.hamcrest.core.Is;
import org.junit.Assert;
import org.junit.Test;
public class AbsTest {
#Test
public void test() {
long processedCount = 0L;
long numberOfIntegers = 1L << Integer.SIZE; //4294967296L
int value;
for (value = Integer.MIN_VALUE; processedCount < numberOfIntegers; value++) {
Assert.assertEquals((long) abs(value), (long) StrictMath.abs(value));
if (processedCount % 1_000_000L == 0L) {
System.out.print(".");
}
processedCount++;
}
System.out.println();
Assert.assertThat(processedCount, Is.is(numberOfIntegers));
Assert.assertThat(value - 1, Is.is(Integer.MAX_VALUE));
}
private static int abs(int v) {
int mask = v >> Integer.SIZE - 1;
return v + mask ^ mask;
}
}
This problem can be broken down into 2 simple steps:
1.
If >= 0 then just return the number.
2.
If smaller than 0 (ie. negative), then flip the first bit that indicates that the number is negative. This can easily be done with an XOR operation with -1 and the number; Then simply add +1 to deal with the offset (signed integers start at -1 not 0).
public static int absolute(int a) {
if (a >= 0) {
return a;
} else {
return (a ^ -1) + 1;
}
}
I need to find the largest power of 2 less than the given number.
And I stuck and can't find any solution.
Code:
public class MathPow {
public int largestPowerOf2 (int n) {
int res = 2;
while (res < n) {
res =(int) Math.pow(res, 2);
}
return res;
}
}
This doesn't work correctly.
Testing output:
Arguments Actual Expected
-------------------------
9 16 8
100 256 64
1000 65536 512
64 256 32
How to solve this issue?
Integer.highestOneBit(n-1);
For n <= 1 the question doesn't really make sense. What to do in that range is left to the interested reader.
The's a good collection of bit twiddling algorithms in Hacker's Delight.
Change res =(int)Math.pow(res, 2); to res *= 2; This will return the next power of 2 greater than res.
The final result you are looking for will therefore finally be res / 2 after the while has ended.
To prevent the code from overflowing the int value space you should/could change the type of res to double/long, anything that can hold higher values than int. In the end you would have to cast one time.
You can use this bit hack:
v--;
v |= v >> 1;
v |= v >> 2;
v |= v >> 4;
v |= v >> 8;
v |= v >> 16;
v++;
v >>= 1;
Why not use logs?
public int largestPowerOf2(int n) {
return (int)Math.pow(2, Math.floor(Math.log(n) / Math.log(2));
}
log(n) / log(2) tells you the number of times 2 goes into a number. By taking the floor of it, gets you the integer value rounding down.
There's a nice function in Integer that is helpful, numberOfLeadingZeros.
With it you can do
0x80000000 >>> Integer.numberOfLeadingZeros(n - 1);
Which does weird things when n is 0 or 1, but for those inputs there is no well-defined "highest power of two less than n".
edit: this answer is even better
You could eliminate the least significant bit in n until n is a power of 2. You could use the bitwise operator AND with n and n-1, which would eliminate the least significant bit in n until n would be a power of 2. If originally n would be a power of 2 then all you would have to do is reduce n by 1.
public class MathPow{
public int largestPowerOf2(int n){
if((n & n-1) == 0){ //this checks if n is a power of 2
n--; //Since n is a power of 2 we have to subtract 1
}
while((n & n-1) != 0){ //the while will keep on going until n is a power of 2, in which case n will only have 1 bit on which is the maximum power of 2 less than n. You could eliminate the != 0 but just for clarity I left it in
n = n & n-1; //we will then perform the bitwise operation AND with n and n-1 to eliminate the least significant bit of n
}
return n;
}
}
EXPLANATION:
When you have a number n (that is not a power of 2), the largest power of 2 that is less than n is always the most significant bit in n. In case of a number n that is a power of 2, the largest power of 2 less than n is the bit right before the only bit that is on in n.
For example if we had 8 (which is 2 to the 3rd power), its binary representation is 1000 the 0 that is bold would be the largest power of 2 before n. Since we know that each digit in binary represents a power of 2, then if we have n as a number that's a power of 2, the greatest power of 2 less than n would be the power of 2 before it, which would be the bit before the only bit on in n.
With a number n, that is not a power of 2 and is not 0, we know that in the binary representation n would have various bits on, these bits would only represent a sum of various powers of 2, the most important of which would be the most significant bit. Then we could deduce that n is only the most significant bit plus some other bits. Since n is represented in a certain length of bits and the most significant bit is the highest power of 2 we can represent with that number of bits, but it is also the lowest number we can represent with that many bits, then we can conclude that the most significant bit is the highest power of 2 lower than n, because if we add another bit to represent the next power of 2 we will have a power of 2 greater than n.
EXAMPLES:
For example, if we had 168 (which is 10101000 in binary) the while would take 168 and subtract 1 which is 167 (which is 10100111 in binary). Then we would do the bitwise AND on both numbers.
Example:
10101000
& 10100111
------------
10100000
We now have the binary number 10100000. If we subtract 1 from it and we use the bitwise AND on both numbers we get 10000000 which is 128, which is 2 to the power of 7.
Example:
10100000
& 10011111
-------------
10000000
If n were to be originally a power of 2 then we have to subtract 1 from n. For example if n was 16, which is 10000 in binary, we would subtract 1 which would leave us with 15, which is 1111 in binary, and we store it in n (which is what the if does). We then go into the while which does the bitwise operator AND with n and n-1, which would be 15 (in binary 1111) & 14 (in binary 1110).
Example:
1111
& 1110
--------
1110
Now we are left with 14. We then perform the bitwise AND with n and n-1, which is 14 (binary 1110) & 13 (binary 1101).
Example:
1110
& 1101
---------
1100
Now we have 12 and we only need to eliminate one last least significant bit. Again, we then execute the bitwise AND on n and n-1, which is 12 (in binary 1100) and 11 (in binary 1011).
Example
1100
& 1011
--------
1000
We are finally left with 8 which is the greatest power of 2 less than 16.
You are squaring res each time, meaning you calculate 2^2^2^2 instead of 2^k.
Change your evaluation to following:
int res = 2;
while (res * 2 < n) {
res *= 2;
}
Update:
Of course, you need to check for overflow of int, in that case checking
while (res <= (n - 1) / 2)
seems much better.
Here is a recursive bit-shifting method I wrote for this purpose:
public static int nextPowDown(int x, int z) {
if (x == 1)
return z;
return nextPowDown(x >> 1, z << 1);
}
Or shorter definition:
public static int nextPowTailRec(int x) {
return x <= 2 ? x : nextPowTailRec(x >> 1) << 1;
}
So in your main method let the z argument always equal 1. It's a pity default parameters aren't available here:
System.out.println(nextPowDown(60, 1)); // prints 32
System.out.println(nextPowDown(24412, 1)); // prints 16384
System.out.println(nextPowDown(Integer.MAX_VALUE, 1)); // prints 1073741824
A bit late but...
(Assuming 32 bit number.)
n|=(n>>1);
n|=(n>>2);
n|=(n>>4);
n|=(n>>8);
n|=(n>>16);
n=n^(n>>1);
Explanation:
The first | makes sure the original top bit and the 2nd highest top bit are set. The second | makes sure those two, and the next two are, etc, until you potentially hit all 32 bits. Ie
100010101 -> 111111111
Then we remove all but the top bit by xor'ing the string of 1's with that string of 1's shifted one to the left, and we end up with just the one top bit followed by 0's.
public class MathPow {
public int largestPowerOf2 (int n) {
int res = 2;
while (res < n) {
res = res * 2;
}
return res;
}
}
Find the first set bit from left to right and make all other set bits 0s.
If there is only 1 set bit then shift right by one.
I think this is the simplest way to do it.
Integer.highestOneBit(n-1);
public class MathPow
{
public int largestPowerOf2(int n)
{
int res = 1;
while (res <= (n-1)/2)
{
res = res * 2;
}
return res;
}
}
If the number is an integer you can always change it to binary then find out the number of digits.
n = (x>>>0).toString(2).length-1
p=2;
while(p<=n)
{
p=2*p;
}
p=p/2;
If the number is a power of two then the answer is obvious. (just bit shift) if not well then it is also can be achieved by bit shifting.
find the length of the given number in binary representation. (13 in binary = 1101 ; length is 4)
then
shift 2 by (4-2) // 4 is the length of the given number in binary
the below java code will solve this for BigIntegers(so basically for all numbers).
BufferedReader br = new BufferedReader(new InputStreamReader(System.in));
String num = br.readLine();
BigInteger in = new BigInteger(num);
String temp = in.toString(2);
System.out.println(new BigInteger("2").shiftLeft(temp.length() - 2));
I saw another BigInteger solution above, but that is actually quite slow. A more effective way if we are to go beyond integer and long is
BigInteger nvalue = TWO.pow(BigIntegerMath.log2(value, RoundingMode.FLOOR));
where TWO is simply BigInteger.valueOf(2L)
and BigIntegerMath is taken from Guava.
Simple bit operations should work
public long largestPowerOf2 (long n)
{
//check already power of two? if yes simply left shift
if((num &(num-1))==0){
return num>>1;
}
// assuming long can take 64 bits
for(int bits = 63; bits >= 0; bits--) {
if((num & (1<<bits)) != 0){
return (1<<bits);
}
}
// unable to find any power of 2
return 0;
}
/**
* Find the number of bits for a given number. Let it be 'k'.
* So the answer will be 2^k.
*/
public class Problem010 {
public static void highestPowerOf2(int n) {
System.out.print("The highest power of 2 less than or equal to " + n + " is ");
int k = 0;
while(n != 0) {
n = n / 2;
k++;
}
System.out.println(Math.pow(2, k - 1) + "\n");
}
public static void main(String[] args) {
highestPowerOf2(10);
highestPowerOf2(19);
highestPowerOf2(32);
}
}
if(number>=2){
while(result < number){
result *=2;
}
result = result/ 2;
System.out.println(result);
}