Looking at |, it is described as a bitwise operator OR.
So, in this code example:
private int getColorRGB(int color) { // 255255255 would be white, 000255000 green, etc.
if (color < 0) return -1;
int r = color / 1000000 % 1000;
int g = color / 1000 % 1000;
int b = color % 1000;
if (r > 255 || g > 255 || b > 255) throw new IllegalArgumentException("RGB values cannot exceed 255.");
return (r >> 16) | (g >> 8) | b; // POINT OF INTEREST
}
I can replace the 2 | at the line marked with POINT OF INTEREST with +, and I still get the same output.
The method takes an int rrrgggbbb, so 255 would be blue, 200200200 would be light gray, etc.
So, my question is; what is the difference between the two
a = 2; // binary 0x10
b = 2; // binary 0x10
c = a + b; // c = 4
c = a | b; // c = 2
| is a bit operation and it doesn't equals +
Sometimes it gives the same result: 2+1 and 2|1 for example; but it isn't a rule
| takes the bitwise OR means takes the greater corresponding bit of the two numbers while + takes the addition of the two corresponding bits and takes further carries which means 1+1 gives us as 10 while 1|1 will stops only to 1. | will never cause out of range if larger argument is in range while + can have out or range if if sum of both causes a number out of range.
If in two numbers, corresponding bits are different, then only in that case | acts as + because during summation, carries never produces.
Remember | and + are 2 different operators. That being said, sometimes they can have the same result, like 1*1 and 1/1. While they have the same result, they do not go through the same process.
Related
Question
I was impressed by tricks like the xor-swap algorithm and similar. So I asked myself, is it possible to assign a variable a value, but only if the value is positive - without using any sort of if or hidden conditionals; just pure math.
Alternative
Basically, this but without the if:
int a = ...
int b = ...
if (b >= 0) {
a = b;
}
Examples
Here are some example input/output setups to illustrate the desired logic:
a = 1, b = 10 -> a = 10 // b is positive
a = 1, b = 0 -> a = 0 // b is 0, also positive
a = 1, b = -10 -> a = 1 // b is negative
tl;dr
int a = ...
int b = ...
int isNegative = b >>> 31; // 1 if negative, 0 if positive
int isPositive = 1 - isNegative; // 0 if negative, 1 if positive
a = isPositive * b + isNegative * a;
Signum
An easy way to achieve the task is to try to aquire some sort of signum, or more specifically a way to get a factor of
either 0, if b is positive
or 1 if b is negative, or vice-versa.
Now, if you take a look at how int is represented internally with its 32-bits (this is called Two's complement):
// 1234
00000000 00000000 00000100 11010010
// -1234
11111111 11111111 11111011 00101110
You see that it has the so called sign-bit on the very left, the most-significant-bit. Turns out, you can easily extract that bit with a simple bit-shift that just moves the whole bit-pattern 31 times to the right, only leaving the 32-th bit, i.e. the sign-bit:
int isNegative = b >>> 31; // 1 if negative, 0 if positive
Now, to get the opposite direction, you simply negate it and add 1 on top of it:
int isPositive = 1 - isNegative; // 0 if negative, 1 if positive
Annihilator and Identity
Once you have that, you can easily construct your desired value by exploiting the fact that
multiplication with 0 basically erases the argument (0 is an annihilator of *)
and addition with 0 does not change the value (0 is an identity element of +).
So, coming back to the logic we want to achieve in the first place:
we want b if b is positive
and we want a if b is negative
Hence, we just do b * isPositive and a * isNegative and add them together:
a = isPositive * b + isNegative * a;
Now, if b is positive, you will get:
a = 1 * b + 0 * a
= b + 0
= b
and if it is negative, you will get:
a = 0 * b + 1 * a
= 0 + a
= a
Other datatypes
The same approach can also be applied to any other signed data type, such as byte, short, long, float and double.
For example, here is a version for double:
double a = ...
double b = ...
long isNegative = Double.doubleToLongBits(b) >>> 63;
long isPositive = 1 - isNegative;
a = isPositive * b + isNegative * a;
Unfortunately, in Java you can not use >>> directly on double (since it usually also makes no sense to mess up the exponent and mantissa), but therefore you have the helper Double#doubleToLongBits which basically reinterprets the double as long.
I need to compare two integer using Bit operator.
I faced a problem where I have to compare two integers without using comparison operator.Using bit operator would help.But how?
Lets say
a = 4;
b = 5;
We have to show a is not equal to b.
But,I would like to extend it further ,say,we will show which is greater.Here b is greater..
You need at least comparison to 0 and notionally this is what the CPU does for a comparison. e.g.
Equals can be modelled as ^ as the bits have to be the same to return 0
(a ^ b) == 0
if this was C you could drop the == 0 as this can be implied with
!(a ^ b)
but in Java you can't convert an int to a boolean without at least some comparison.
For comparison you usually do a subtraction, though one which handles overflows.
(long) a - b > 0 // same as a > b
subtraction is the same as adding a negative and negative is the same as ~x+1 so you can do
(long) a + ~ (long) b + 1 > 0
to drop the +1 you can change this to
(long) a + ~ (long) b >= 0 // same as a > b
You could implement + as a series of bit by bit operations with >> << & | and ^ but I wouldn't inflict that on you.
You cannot convert 1 or 0 to bool without a comparison operator like Peter mentioned. It is still possible to get max without a comparison operator.
I'm using bit (1 or 0) instead of int to avoid confusion.
bit msb(x):
return lsb(x >> 31)
bit lsb(x):
return x &1
// returns 1 if x < 0, 0 if x >= 0
bit isNegative(x):
return msb(x)
With these helpers isGreater(a, b) looks like,
// BUG: bug due to overflow when a is -ve and b is +ve
// returns 1 if a > b, 0 if a <= b
bit isGreater_BUG(a, b):
return isNegative(b - a) // possible overflow
We need two helpers functions to detect same and different signs,
// toggles lsb only
bit toggle(x):
return lsb(~x)
// returns 1 if a, b have same signs (0 is considered +ve).
bit isSameSigns(a, b):
return toggle(isDiffSigns(a, b))
// returns 1 if a, b have different signs (0 is considered +ve).
bit isDiffSigns(a, b):
return msb(a ^ b)
So with the overflow issue fix,
// returns 1 if a > b, 0 if a <= b
bit isGreater(a, b):
return
(isSameSigns(a, b) & isNegative(b - a)) |
(isDiffSigns(a, b) & isNegative(b))
Note that isGreater works correctly for inputs 5, 0 and 0, -5 also.
It's trickier to implement isPositive(x) properly as 0 will also be considered positive. So instead of using isPositive(a - b) above, isNegative(b - a) is used as isNegative(x) works correctly for 0.
Now max can be implemented as,
// BUG: returns 0 when a == b instead of a (or b)
// returns a if a > b, b if b > a
int max_BUG(a, b):
return
isGreater(a, b) * a + // returns 0 when a = b
isGreater(b, a) * b //
To fix that, helper isZero(x) is used,
// returns 1 if x is 0, else 0
bit isZero(x):
// x | -x will have msb 1 for a non-zero integer
// and 0 for 0
return toggle(msb(x | -x))
So with the fix when a = b,
// returns 1 if a == b else 0
bit isEqual(a, b):
return isZero(a - b) // or isZero(a ^ b)
int max(a, b):
return
isGreater(a, b) * a + // a > b, so a
isGreater(b, a) * b + // b > a, so b
isEqual(a, b) * a // a = b, so a (or b)
That said, if isPositive(0) returns 1 then max(5, 5) will return 10 instead of 5. So a correct isPositive(x) implementation will be,
// returns 1 if x > 0, 0 if x <= 0
bit isPositive(x):
return isNotZero(x) & toggle(isNegative(x))
// returns 1 if x != 0, else 0
bit isNotZero(x):
return msb(x | -x)
Using binary two’s complement notation
int findMax( int x, int y)
{
int z = x - y;
int i = (z >> 31) & 0x1;
int max = x - i * z;
return max;
}
Reference: Here
a ^ b = c // XOR the inputs
// If a equals b, c is zero. Else c is some other value
c[0] | c[1] ... | c[n] = d // OR the bits
// If c equals zero, d equals zero. Else d equals 1
Note: a,b,c are n-bit integers and d is a bit
The solution in java without using a comparator operator:
int a = 10;
int b = 12;
boolean[] bol = new boolean[] {true};
try {
boolean c = bol[a ^ b];
System.out.println("The two integers are equal!");
} catch (java.lang.ArrayIndexOutOfBoundsException e) {
System.out.println("The two integers are not equal!");
int z = a - b;
int i = (z >> 31) & 0x1;
System.out.println("The bigger integer is " + (a - i * z));
}
I am going to assume you need an integer (0 or 1) because you will need a comparison to get a boolean from integer in java.
Here, is a simple solution that doesn't use comparison but uses subtraction which can actually be done using bitwise operations (but not recommended because it takes a lot of cycles in software).
// For equality,
// 1. Perform r=a^b.
// If they are equal you get all bits 0. Otherwise some bits are 1.
// 2. Cast it to a larger datatype 0 to have an extra bit for sign.
// You will need to clear the high bits because of signed casting.
// You can split it into two parts if you can't cast.
// 3. Perform -r.
// If all bits are 0, you will get 0.
// If some bits are not 0, then you get a negative number.
// 4. Shift right to extract MSB.
// This will give -1 (because of sign extension) for not equal and 0 for equal.
// You can easily convert it to 0 and 1 by adding 1 (I didn't include it in below function).
int equality(int a, int b) {
long r = ((long)(a^b)) ^0xffffffffl;
return (int)(((long)-r) >> 63);
}
// For greater_than,
// 1. Cast a and b to larger datatype to get more bits.
// You can split it into two parts if you can't cast.
// 2. Perform b-a.
// If a>b, then negative number (MSB is 1)
// If a<=b, then positive number or zero (MSB is 0)
// 3. Shift right to extract MSB.
// This will give -1 (because of sign extension) for greater than and 0 for not.
// You can easily convert it to 0 and 1 by negating it (I didn't include it in below function).
int greater_than(int a, int b) {
long r = (long)b-(long)a;
return (int)(r >> 63);
}
Less than is similar to greater but you swap a and b.
Trivia: These comparison functions are actually used in security (Cryptography) because the CPU comparison is not constant-time; aka not secure against timing attacks.
public class Operator {
public static void main(String[] args) {
byte a = 5;
int b = 10;
int c = a >> 2 + b >> 2;
System.out.print(c); //prints 0
}
}
when 5 right shifted with 2 bits is 1 and 10 right shifted with 2 bits is 2 then adding the values will be 3 right? How come it prints 0 I am not able to understand even with debugging.
This table provided in JavaDocs will help you understand Operator Precedence in Java
additive + - /\ High Precedence
||
shift << >> >>> || Lower Precedence
So your expression will be
a >> 2 + b >> 2;
a >> 12 >> 2; // hence 0
It's all about operator precedence. Addition operator has more precedence over shift operators.
Your expression is same as:
int c = a >> (2 + b) >> 2;
Is this what you want?
int c = ((a >> 2) + b) >> 2;
You were shifting to the right by whatever is 2+b. I assume you wanted to shift 5 by 2 positions, right?
b000101 >> 2 == b0001øø
| |___________________|_|
| |
|_____________________|
i.e. the leftmost bit shifts to the right by 2 positions and right most bit does as well (but is has no more valid positions left on its right side so it simply disappears) and the number becomes what's left - in this case '1'. If you shift number 5 by 12 positions you will get zero as 5 has less than 12 positions in binary form. In case of '5' you can shift by 2 positions at most if you want to preserve non-zero value.
Question is based on this site.
Could someone explain the meaning of these lines:
private int getBitValue(int n, int location) {
int v = n & (int) Math.round(Math.pow(2, location));
return v==0?0:1;
}
and
private int setBitValue(int n, int location, int bit) {
int toggle = (int) Math.pow(2, location), bv = getBitValue(n, location);
if(bv == bit)
return n;
if(bv == 0 && bit == 1)
n |= toggle;
else if(bv == 1 && bit == 0)
n ^= toggle;
return n;
}
int v = n & (int) Math.round(Math.pow(2, location));
Math.pow(2, location) raises 2 to the given power. This is rounded and converted to an integer. In binary, this will be 00000001 if location==0, 00000010 if location==1, 00000100 if location==2, etc. (Much better would be 1 << location which shifts a "1" by a certain number of bits, filling in 0 bits at the right. Using Math.pow will probably try to compute the logarithm of 2 every time it's called.)
n & ... is a bitwise AND. Since the item on the right has just one bit set, the effect is to zero out every bit in n except for that one bit, and put the result in v. This means that v will be 0 if that one bit is 0 in n, and something other than 0 if that bit is `, which means
return v==0?0:1;
returns 0 if the bit is clear and 1 if it's set.
int toggle = (int) Math.pow(2, location), bv = getBitValue(n, location);
toggle is set to that Math.pow thing I already described. bv is set to the bit that's already in n, which is 0 or 1. If this equals the thing you're setting it to, then we don't need to do anything to n:
if(bv == bit)
return n;
Otherwise, either we need to set it to 1 (remember that toggle will have just one bit set). n |= toggle is the same as n = n | toggle. | is a bit-wise OR, so that one bit will be set in n and all other bits in n will remain the same"
if(bv == 0 && bit == 1)
n |= toggle;
Or we need to set the bit to 0. n ^= toggle is the same as n = n ^ toggle. n is an exclusive OR. If we get here, then the bit in n is 1, and the bit in toggle is 1, and we want to set the bit in n to 0, so exclusive OR will change that bit to 0 while leaving every other bit the same:
else if(bv == 1 && bit == 0)
n ^= toggle;
The getBitValue just gets the value of a specified bit (on a certain location)
The setBitValue sets the value of a bit on the matched specific location.
These getter/setter methods are usually used for image processing, i.e. if you have a musk and you want to change a specific bit value.
Nothing more or less.
Here is the problem:
You're given 2 32-bit numbers, N & M, and two bit positions, i & j. write a method to set all bits between i and j in N equal to M (e.g. M becomes a substring of N at locating at i
and starting at j)
For example:
input:
int N = 10000000000, M = 10101, i = 2, j = 6;
output:
int N = 10001010100
My solution:
step 1: compose one mask to clear sets from i to j in N
mask= ( ( ( ((1<<(31-j))-1) << (j-i+1) ) + 1 ) << i ) - 1
for the example, we have
mask= 11...10000011
step 2:
(N & mask) | (M<<i)
Question:
what is the convenient data type to implement the algorithm? for example
we have int n = 0x100000 in C, so that we can apply bitwise operators on n.
in Java, we have BitSet class, it has clear, set method, but doesnt support
left/right shift operator; if we use int, it supports left/right shift, but
doesnt have binary representation (I am not talking about binary string representation)
what is the best way to implement this?
Code in java (after reading all comments):
int x = Integer.parseInt("10000000000",2);
int x = Integer.parseInt("10101",2);
int i = 2, j = 6;
public static int F(int x, int y, int i, int j){
int mask = (-1<<(j+1)) | (-1>>>(32-i));
return (mask & x ) | (y<<i);
}
the bit-wise operators |, &, ^ and ~ and the hex literal (0x1010) are all available in java
32 bit numbers are ints if that constraint remains int will be a valid data type
btw
mask = (-1<<j)|(-1>>>(32-i));
is a slightly clearer construction of the mask
Java's int has all the operations you need. I did not totally understand your question (too tired now), so I'll not give you a complete answer, just some hints. (I'll revise it later, if needed.)
Here are j ones in a row: (1 << j)-1.
Here are j ones in a row, followed by i zeros: ((1 << j) - 1) << i.
Here is a bitmask which masks out j positions in the middle of x: x & ~(((1 << j) - 1) << i).
Try these with Integer.toBinaryString() to see the results. (They might also give strange results for negative or too big values.)
I think you're misunderstanding how Java works. All values are represented as 'a series of bits' under the hood, ints and longs are included in that.
Based on your question, a rough solution is:
public static int applyBits(int N, int M, int i, int j) {
M = M << i; // Will truncate left-most bits if too big
// Assuming j > i
for(int loopVar = i; loopVar < j; loopVar++) {
int bitToApply = 1 << loopVar;
// Set the bit in N to 0
N = N & ~bitToApply;
// Apply the bit if M has it set.
N = (M & bitToApply) | N;
}
return N;
}
My assumptions are:
i is the right-most (least-significant) bit that is being set in N.
M's right-most bit maps to N's ith bit from the right.
That premature optimization is the root of all evil - this is O(j-i). If you used a complicated mask like you did in the question you can do it in O(1), but it won't be as readable, and readable code is 97% of the time more important than efficient code.