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Convert 32bit data to unsigned long value

I have something like this:
int[0] = 4123;
int[1] = 2571;
I would like to combine them and make one long value in Java.
This is my attempt:
int[] r = { 4123, 2571 };
long result = ( (r[1] & 0xFFFF) << 16 | (rs[0] & 0xFFFF) );
System.out.prinln(result);
The output should be: 10111627 but I get 168497179. Probably I miss something in conversion but don't have idea what...
EDIT
This is example how the value is placed into 32-bit register.

I try the summarize and hopefully clarify what the several comments on your question already indicate:
If you want to get the number from your image which is
00001010 00001011 00010000 00011011 = 0x0A0B101B = 168497179
in one single long value and you have two ints
0001000000011011 = 0x101B = 4123 and
0000101000001011 = 0x0A0B = 2571
than your code is correct.
I would recommend you to get used to hexadecimal numbers as they show easily that there is no binary relation between 0x0A0B & 0x101B and 0x009A4A8B = 10111627.
BTW your image is contradictory: the binary numbers represent as seen above the number 0x0A0B101B but the hexadecimals read 0x0A0B101E (notice the E) while the decimals support the binary value.
Finally, I figured out your flaw:
You seem to expect to get the decimal number concatenated together as result. But unlike the hexadecimals here it does not work this way in decimal!
Let me elaborate that. You have the binary number:
00001010 00001011 00010000 00011011
Which you can easily convert to hex block by block
0x0A 0x0B 0x10 0x1B
and than just join them together
0x0A0B101B
But that magic join is just a simplification only applying to hex (and the reason why hex is so popular among programmers).
The long version is you have to multiply the higher blocks/bytes (towards the left) with the 'basis' of the preceding block (to the right). The right most block is always multiplied by 1. The base for the next block is (since there are 8 bits in the first block) 28 = 256 = 0x100. The base for the third block is (8+8 bits) 216 = 65536 = 0x10000. The last (left most) has to be multiplied by (8+8+8 bits) 224 = 16777216 = 0x1000000.
Lets make an example for the first two blocks:
Hexadecimal:
0x10 || 0x1B
(0x10 * 0x100) + (0x1B* 0x1)
0x1000 + 0x1B = 0x101B
Decimal:
16 || 27
(16 * 256) + (27 * 1)
4096 + 27 = 4123
As you can see on your image they both in it (notice the E/B issue which is in decimal a 6/3 issue) but there is no 1627. So converting binary or hexadecimal numbers to decimal is a nontrivial task (for humans), best to use a calculator.

Bitwise op unexpectedly goes negative

Can someone please explain to me why I'm getting these results?
public static int ipv4ToInt(String address) {
int result = 0;
// iterate over each octet
for(String part : address.split(Pattern.quote("."))) {
// shift the previously parsed bits over by 1 byte
result = result << 8;
System.out.printf("shift = %d\n", result);
// set the low order bits to the current octet
result |= Integer.parseInt(part);
System.out.printf("result = %d\n", result);
}
return result;
}
For ipv4ToInt("10.35.41.134"), I get:
shift = 0
result = 10
shift = 2560
result = 2595
shift = 664320
result = 664361
shift = 170076416
result = 170076550
10.35.41.134 = 170076550
This is the same result that I get when I do the math myself.
For ipv4ToInt("192.168.0.1"), I get:
shift = 0
result = 192
shift = 49152
result = 49320
shift = 12625920
result = 12625920
shift = -1062731776
result = -1062731775
192.168.0.1 = -1062731775
For this one, when I do the math manually, I get 3232235521.
Interestingly:
3232235521 = 11000000101010000000000000000001
And when I enter 1062731775 into my Windows calc and hit the +/- button, I get:
-1062731775 = 11111111111111111111111111111111 11000000101010000000000000000001
The function still works for my purposes, but I'm just really curious to know why on earth result is going negative when I do that last bit shift?

Because of bit overflow in your case!
In Java, the integer is also 32 bits and range is from -2,147,483,648 to 2,147,483,647.
12625920 << 8 crosses the limit of 2^31-1 and hence,the result turns negative...
The result just overturns from -ve side and hence,whatever range is left from the positive side is accompanied by that much from negative side!!!
As suggested by everyone,you should use long variable to avoid overflow!

All primitives in java are signed - They can be positive or negative. The highest bit is used to control this, so when it gets set, the number becomes negative.
Try using a long instead - that will give you the wanted result, as longs can be much larger without overflow being hit.

11000000101010000000000000000001 is 32 bits. The value it represents depends on how you interpret those bits:
as a 32bit signed integer, it is negative (because the left-most bit is 1)
as a 32bit unsigned integer, it is positive (like every other unsigned integer)
as the lowers bits of a long (signed or unsigned), it would give a positive value (if the left-most bits stay 0)
Java uses signed integers, so if you print the value, you'll see a negative number. That does not mean your bits are wrong.

It matters only for printing, you can use these ways for printing a positive integer:
1) change result to long (java will do the work for you).
2) handle signed int as unsigned int by yourself (possibly make a method int2string(int n) or toString(int n).
3) Integer.toUnsignedString(int) is you are using java 8.
As far as I understand, your are parsing an IP address, remember, java use signed data types, you can't have a 32 bits integer.
change result to long to fix that.

How Java processes for overflow integers [duplicate]

This question already has answers here:
Why do these two multiplication operations give different results?
(2 answers)
Closed 9 years ago.
Now signed_int max value is 2,147,483,647 i.e. 2^31 and 1 bit is sign bit, so
when I run long a = 2,147,483,647 + 1;
It gives a = -2,147,483,648 as answer.. This hold good.
But, 24*60*60*1000*1000 = 86400000000 (actually)...
In java, 24*60*60*1000*1000 it equals to 500654080..
I understand that it is because of overflow in integer, but what processing made this value come, What logic was used to get that number by Java. I also refered here.

Multiplication is executed from left to right like this
int x = 24 * 60;
x = x * 60;
x = x * 1000;
x = x * 1000;
first 3 operations produce 86400000 which still fits into Integer.MAX_VALUE. But the last operation produces 86400000000 which is 0x141dd76000 in hex. Bytes above 4 are truncated and we get 0x1dd76000. If we print it
System.out.println(0x1dd76000);
the result will be
500654080

This is quite subtle: when writing long a = 2147483647 + 1, the right hand side is computed first using ints since you have supplied int literals. But that will clock round to a negative (due to overflow) before being converted to a long. So the promotion from int to long is too late for you.
To circumvent this behaviour, you need to promote at least one of the arguments to a long literal by suffixing an L.
This applies to all arithmetic operations using literals (i.e. also your multiplication): you need to promote one of them to a long type.
The fact that your multiplication answer is 500654080 can be seen by looking at
long n = 24L*60*60*1000*1000;
long m = n % 4294967296L; /* % is extracting the int part so m is 500654080
n.b. 4294967296L is 2^32 (using OP notation, not XOR). */
What's happening here is that you are going 'round and round the clock' with the int type. Yes, you are losing the carry bits but that doesn't matter with multiplication.

As the range of int is -2,147,483,648 to 2,147,483,647.
So, when you keep on adding numbers and its exceed the maximum limit it start gain from the left most number i.e. -2,147,483,648, as it works as a cycle. That you had already mentioned in your question.
Similarly when you are computing 24*60*60*1000*1000 which should result 86400000000 as per Maths.
But actually what happens is somehow as follows:
86400000000 can be written as 2147483647+2147483647+2147483647+2147483647+..36 times+500654080
So, after adding 2147483647 for 40 times results 0 and then 500654080 is left which ultimately results in 500654080.
I hope its clear to you.

Add L in your multiplicatoin. If you add L than it multiply you in Long range otherwise in Integer range which overflow. Try to multiply like this.
24L*60*60*1000*1000
This give you a right answer.

An Integer is 32 bit long. Lets take for example a number that is 4 bit long for the sake of simplicity.
It's max positive value would be:
0111 = 7 (first bit is for sign; 0 means positive, 1 means negative)
0000 = 0
It's min negative value would be:
1111 = -8 (first bit is for sign)
1000 = -1
Now, if we call this type fbit, fbit_max is equal to 7.
fbit_max + 1 = -8
because bitwise 0111 + 1 = 1111
Therefore, the span of fbit_min to fbit_max is 16. From -8 to 7.
If you would multiply something like 7*10 and store it in fbit, the result would be:
fbit number = 7 * 10 (actually 70)
fbit number = 7 (to get to from zero to max) + 16 (min to max) + 16 (min to max) + 16 (min to max) + 15 (the rest)
fbit number = 6

24*60*60*1000*1000 = 86400000000
Using MOD as follows: 86400000000 % 2147483648 = 500654080

check number present in a sequences

I am writing a program which I found on a coding competition website, I have sort of figured out how to solve the problem but, I am stuck on a math part of it, I am completely diluting the problem and showing what I need.
first I need to check if a number is part of a sequence, my sequence is 2*a+1 where a is the previous element in the sequence or 2^n-1 to get nth item in the sequence. so it is 1,3,7,15,31,63...
I don't really want to create the whole sequence and check if a number is present, but I am not sure what a quicker method to do this would be.
Second if I am given a number lets say 25, I want to figure out the next highest number in my sequence to this number. So for 25 it would be 31 and for 47 it would be 63, for 8 it would be 13.
How can i do these things without creating the whole sequence.
I have seen similar questions here with different sequences but I am still not sure how to solve this

Start by finding the explicit formula for any term in your sequence. I'm too lazy to write out a proof, so just add 1 to each term in your sequence:
1 + 1 = 2
3 + 1 = 4
7 + 1 = 8
15 + 1 = 16
31 + 1 = 32
63 + 1 = 64
...
You can clearly see that a_n = 2^n - 1.
To check if a particular number is in your sequence, assume that it is:
x = 2^n - 1
x + 1 = 2^n
From Wikipedia:
The binary representation of integers makes it possible to apply a
very fast test to determine whether a given positive integer x is a
power of two:
positive x is a power of two ⇔ (x & (x − 1)) equals to zero.
So to check, just do:
bool in_sequence(int n) {
return ((n + 1) & n) == 0;
}

As #Blender already pointed out your sequence is essentially 2^n - 1, you can use this trick if you use integer format to store it:
boolean inSequence(int value) {
for (int i = 0x7FFF; i != 0; i >>>= 1) {
if (value == i) {
return true;
}
}
return false;
}
Note that for every elements in your sequence, its binary representation will be lots of 0s and then lots of 1s.
For example, 7 in binary is 0000000000000000000000000000111 and 63 in binary is 0000000000000000000000000111111.
This solution starts from 01111111111111111111111111111111 and use an unsigned bitshift, then compare if it is equal to your value.
Nice and simple.

How to find the next higher number :
For example, we get 19 ( 10011 ) , should return 31 (11111)
int findNext(int n){
if(n == 0) return 1;
int ret = 2; // start from 10
while( (n>>1) > 0){ // end with 100000
ret<<1;
}
return ret-1;
}

One-byte bool. Why?

In C++, why does a bool require one byte to store true or false where just one bit is enough for that, like 0 for false and 1 for true? (Why does Java also require one byte?)
Secondly, how much safer is it to use the following?
struct Bool {
bool trueOrFalse : 1;
};
Thirdly, even if it is safe, is the above field technique really going to help? Since I have heard that we save space there, but still compiler generated code to access them is bigger and slower than the code generated to access the primitives.

Why does a bool require one byte to store true or false where just one bit is enough
Because every object in C++ must be individually addressable* (that is, you must be able to have a pointer to it). You cannot address an individual bit (at least not on conventional hardware).
How much safer is it to use the following?
It's "safe", but it doesn't achieve much.
is the above field technique really going to help?
No, for the same reasons as above ;)
but still compiler generated code to access them is bigger and slower than the code generated to access the primitives.
Yes, this is true. On most platforms, this requires accessing the containing byte (or int or whatever), and then performing bit-shifts and bit-mask operations to access the relevant bit.
If you're really concerned about memory usage, you can use a std::bitset in C++ or a BitSet in Java, which pack bits.
* With a few exceptions.

Using a single bit is much slower and much more complicated to allocate. In C/C++ there is no way to get the address of one bit so you wouldn't be able to do &trueOrFalse as a bit.
Java has a BitSet and EnumSet which both use bitmaps. If you have very small number it may not make much difference. e.g. objects have to be atleast byte aligned and in HotSpot are 8 byte aligned (In C++ a new Object can be 8 to 16-byte aligned) This means saving a few bit might not save any space.
In Java at least, Bits are not faster unless they fit in cache better.
public static void main(String... ignored) {
BitSet bits = new BitSet(4000);
byte[] bytes = new byte[4000];
short[] shorts = new short[4000];
int[] ints = new int[4000];
for (int i = 0; i < 100; i++) {
long bitTime = timeFlip(bits) + timeFlip(bits);
long bytesTime = timeFlip(bytes) + timeFlip(bytes);
long shortsTime = timeFlip(shorts) + timeFlip(shorts);
long intsTime = timeFlip(ints) + timeFlip(ints);
System.out.printf("Flip time bits %.1f ns, bytes %.1f, shorts %.1f, ints %.1f%n",
bitTime / 2.0 / bits.size(), bytesTime / 2.0 / bytes.length,
shortsTime / 2.0 / shorts.length, intsTime / 2.0 / ints.length);
}
}
private static long timeFlip(BitSet bits) {
long start = System.nanoTime();
for (int i = 0, len = bits.size(); i < len; i++)
bits.flip(i);
return System.nanoTime() - start;
}
private static long timeFlip(short[] shorts) {
long start = System.nanoTime();
for (int i = 0, len = shorts.length; i < len; i++)
shorts[i] ^= 1;
return System.nanoTime() - start;
}
private static long timeFlip(byte[] bytes) {
long start = System.nanoTime();
for (int i = 0, len = bytes.length; i < len; i++)
bytes[i] ^= 1;
return System.nanoTime() - start;
}
private static long timeFlip(int[] ints) {
long start = System.nanoTime();
for (int i = 0, len = ints.length; i < len; i++)
ints[i] ^= 1;
return System.nanoTime() - start;
}
prints
Flip time bits 5.0 ns, bytes 0.6, shorts 0.6, ints 0.6
for sizes of 40000 and 400K
Flip time bits 6.2 ns, bytes 0.7, shorts 0.8, ints 1.1
for 4M
Flip time bits 4.1 ns, bytes 0.5, shorts 1.0, ints 2.3
and 40M
Flip time bits 6.2 ns, bytes 0.7, shorts 1.1, ints 2.4

If you want to store only one bit of information, there is nothing more compact than a char, which is the smallest addressable memory unit in C/C++. (Depending on the implementation, a bool might have the same size as a char but it is allowed to be bigger.)
A char is guaranteed by the C standard to hold at least 8 bits, however, it can also consist of more. The exact number is available via the CHAR_BIT macro defined in limits.h (in C) or climits (C++). Today, it is most common that CHAR_BIT == 8 but you cannot rely on it (see here). It is guaranteed to be 8, however, on POSIX compliant systems and on Windows.
Though it is not possible to reduce the memory footprint for a single flag, it is of course possible to combine multiple flags. Besides doing all bit operations manually, there are some alternatives:
If you know the number of bits at compile time
bitfields (as in your question). But beware, the ordering of fields is not guaranteed, which may result in portability issues.
std::bitset
If you know the size only at runtime
boost::dynamic_bitset
If you have to deal with large bitvectors, take a look at the BitMagic library. It supports compression and is heavily tuned.
As others have pointed out already, saving a few bits is not always a good idea. Possible drawbacks are:
Less readable code
Reduced execution speed because of the extra extraction code.
For the same reason, increases in code size, which may outweigh the savings in data consumption.
Hidden synchronization issues in multithreaded programs. For example, flipping two different bits by two different threads may result in a race condition. In contrast, it is always safe for two threads to modify two different objects of primitive types (e.g., char).
Typically, it makes sense when you are dealing with huge data because then you will benefit from less pressure on memory and cache.

Why don't you just store the state to a byte? Haven't actually tested the below, but it should give you an idea. You can even utilize a short or an int for 16 or 32 states. I believe I have a working JAVA example as well. I'll post this when I find it.
__int8 state = 0x0;
bool getState(int bit)
{
return (state & (1 << bit)) != 0x0;
}
void setAllOnline(bool online)
{
state = -online;
}
void reverseState(int bit)
{
state ^= (1 << bit);
}
Alright here's the JAVA version. I've stored it to an Int value since. If I remember correctly even using a byte would utilize 4 bytes anyways. And this obviously isn't be utilized as an array.
public class State
{
private int STATE;
public State() {
STATE = 0x0;
}
public State(int previous) {
STATE = previous;
}
/*
* #Usage - Used along side the #setMultiple(int, boolean);
* #Returns the value of a single bit.
*/
public static int valueOf(int bit)
{
return 1 << bit;
}
/*
* #Usage - Used along side the #setMultiple(int, boolean);
* #Returns the value of an array of bits.
*/
public static int valueOf(int... bits)
{
int value = 0x0;
for (int bit : bits)
value |= (1 << bit);
return value;
}
/*
* #Returns the value currently stored or the values of all 32 bits.
*/
public int getValue()
{
return STATE;
}
/*
* #Usage - Turns all bits online or offline.
* #Return - <TRUE> if all states are online. Otherwise <FALSE>.
*/
public boolean setAll(boolean online)
{
STATE = online ? -1 : 0;
return online;
}
/*
* #Usage - sets multiple bits at once to a specific state.
* #Warning - DO NOT SET BITS TO THIS! Use setMultiple(State.valueOf(#), boolean);
* #Return - <TRUE> if states were set to online. Otherwise <FALSE>.
*/
public boolean setMultiple(int value, boolean online)
{
STATE |= value;
if (!online)
STATE ^= value;
return online;
}
/*
* #Usage - sets a single bit to a specific state.
* #Return - <TRUE> if this bit was set to online. Otherwise <FALSE>.
*/
public boolean set(int bit, boolean online)
{
STATE |= (1 << bit);
if(!online)
STATE ^= (1 << bit);
return online;
}
/*
* #return = the new current state of this bit.
* #Usage = Good for situations that are reversed.
*/
public boolean reverse(int bit)
{
return (STATE ^= (1 << bit)) == (1 << bit);
}
/*
* #return = <TRUE> if this bit is online. Otherwise <FALSE>.
*/
public boolean online(int bit)
{
int value = 1 << bit;
return (STATE & value) == value;
}
/*
* #return = a String contains full debug information.
*/
#Override
public String toString()
{
StringBuilder sb = new StringBuilder();
sb.append("TOTAL VALUE: ");
sb.append(STATE);
for (int i = 0; i < 0x20; i++)
{
sb.append("\nState(");
sb.append(i);
sb.append("): ");
sb.append(online(i));
sb.append(", ValueOf: ");
sb.append(State.valueOf(i));
}
return sb.toString();
}
}
Also I should point out that you really shouldn't utilize a special class for this, but to just have the variable stored within the class that'll be most likely utilizing it. If you plan to have 100's or even 1000's of Boolean values consider an array of bytes.
E.g. the below example.
boolean[] states = new boolean[4096];
can be converted into the below.
int[] states = new int[128];
Now you're probably wondering how you'll access index 4095 from a 128 array. So what this is doing is if we simplify it. The 4095 is be shifted 5 bits to the right which is technically the same as divide by 32. So 4095 / 32 = rounded down (127). So we are at index 127 of the array. Then we perform 4095 & 31 which will cast it to a value between 0 and 31. This will only work with powers of two minus 1. E.g. 0,1,3,7,15,31,63,127,255,511,1023, etc...
So now we can access the bit at that position. As you can see this is very very compact and beats having 4096 booleans in a file :) This will also provide a much faster read/write to a binary file. I have no idea what this BitSet stuff is, but it looks like complete garbage and since byte,short,int,long are already in their bit forms technically you might as well use them as is. Then creating some complex class to access the individual bits from memory which is what I could grasp from reading a few posts.
boolean getState(int index)
{
return (states[index >> 5] & 1 << (index & 0x1F)) != 0x0;
}
Further information...
Basically if the above was a bit confusing here's a simplified version of what's happening.
The types "byte", "short", "int", "long" all are data types which have different ranges.
You can view this link: http://msdn.microsoft.com/en-us/library/s3f49ktz(v=vs.80).aspx
To see the data ranges of each.
So a byte is equal to 8 bits. So an int which is 4 bytes will be 32 bits.
Now there isn't any easy way to perform some value to the N power. However thanks to bit shifting we can simulate it somewhat. By performing 1 << N this equates to 1 * 2^N. So if we did 2 << 2^N we'd be doing 2 * 2^N. So to perform powers of two always do "1 << N".
Now we know that a int will have 32 bits so can use each bits so we can just simply index them.
To keep things simple think of the "&" operator as a way to check if a value contains the bits of another value. So let's say we had a value which was 31. To get to 31. we must add the following bits 0 through 4. Which are 1,2,4,8, and 16. These all add up to 31. Now when we performing 31 & 16 this will return 16 because the bit 4 which is 2^4 = 16. Is located in this value. Now let's say we performed 31 & 20 which is checking if bits 2 and 4 are located in this value. This will return 20 since both bits 2 and 4 are located here 2^2 = 4 + 2^4 = 16 = 20. Now let's say we did 31 & 48. This is checking for bits 4 and 5. Well we don't have bit 5 in 31. So this will only return 16. It will not return 0. So when performing multiple checks you must check that it physically equals that value. Instead of checking if it equals 0.
The below will verify if an individual bit is at 0 or 1. 0 being false, and 1 being true.
bool getState(int bit)
{
return (state & (1 << bit)) != 0x0;
}
The below is example of checking two values if they contain those bits. Think of it like each bit is represented as 2^BIT so when we do
I'll quickly go over some of the operators. We've just recently explained the "&" operator slightly. Now for the "|" operator.
When performing the following
int value = 31;
value |= 16;
value |= 16;
value |= 16;
value |= 16;
The value will still be 31. This is because bit 4 or 2^4=16 is already turned on or set to 1. So performing "|" returns that value with that bit turned on. If it's already turned on no changes are made. We utilize "|=" to actually set the variable to that returned value.
Instead of doing -> "value = value | 16;". We just do "value |= 16;".
Now let's look a bit further into how the "&" and "|" can be utilized.
/*
* This contains bits 0,1,2,3,4,8,9 turned on.
*/
const int CHECK = 1 | 2 | 4 | 8 | 16 | 256 | 512;
/*
* This is some value were we add bits 0 through 9, but we skip 0 and 8.
*/
int value = 2 | 4 | 8 | 16 | 32 | 64 | 128 | 512;
So when we perform the below code.
int return_code = value & CHECK;
The return code will be 2 + 4 + 8 + 16 + 512 = 542
So we were checking for 799, but we recieved 542 This is because bits o and 8 are offline we equal 256 + 1 = 257 and 799 - 257 = 542.
The above is great great great way to check if let's say we were making a video game and wanted to check if so and so buttons were pressed if any of them were pressed. We could simply check each of those bits with one check and it would be so many times more efficient than performing a Boolean check on every single state.
Now let's say we have Boolean value which is always reversed.
Normally you'd do something like
bool state = false;
state = !state;
Well this can be done with bits as well utilizing the "^" operator.
Just as we performed "1 << N" to choose the whole value of that bit. We can do the same with the reverse. So just like we showed how "|=" stores the return we will do the same with "^=". So what this does is if that bit is on we turn it off. If it's off we turn it on.
void reverseState(int bit)
{
state ^= (1 << bit);
}
You can even have it return the current state. If you wanted it to return the previous state just swap "!=" to "==". So what this does is performs the reversal then checks the current state.
bool reverseAndGet(int bit)
{
return ((state ^= (1 << bit)) & (1 << bit)) != 0x0;
}
Storing multiple non single bit aka bool values into a int can also be done. Let's say we normally write out our coordinate position like the below.
int posX = 0;
int posY = 0;
int posZ = 0;
Now let's say these never wen't passed 1023. So 0 through 1023 was the maximum distance on all of these. I'm choose 1023 for other purposes as previously mentioned you can manipulate the "&" variable as a way to force a value between 0 and 2^N - 1 values. So let's say your range was 0 through 1023. We can perform "value & 1023" and it'll always be a value between 0 and 1023 without any index parameter checks. Keep in mind as previously mentioned this only works with powers of two minus one. 2^10 = 1024 - 1 = 1023.
E.g. no more if (value >= 0 && value <= 1023).
So 2^10 = 1024, which requires 10 bits in order to hold a number between 0 and 1023.
So 10x3 = 30 which is still less than or equal to 32. Is sufficient for holding all these values in an int.
So we can perform the following. So to see how many bits we used. We do 0 + 10 + 20. The reason I put the 0 there is to show you visually that 2^0 = 1 so # * 1 = #. The reason we need y << 10 is because x uses up 10 bits which is 0 through 1023. So we need to multiple y by 1024 to have unique values for each. Then Z needs to be multiplied by 2^20 which is 1,048,576.
int position = (x << 0) | (y << 10) | (z << 20);
This makes comparisons fast.
We can now do
return this.position == position;
apposed to
return this.x == x && this.y == y && this.z == z;
Now what if we wanted the actual positions of each?
For the x we simply do the following.
int getX()
{
return position & 1023;
}
Then for the y we need to perform a left bit shift then AND it.
int getY()
{
return (position >> 10) & 1023;
}
As you may guess the Z is the same as the Y, but instead of 10 we use 20.
int getZ()
{
return (position >> 20) & 1023;
}
I hope whoever views this will find it worth while information :).

If you really want to use 1 bit, you can use a char to store 8 booleans, and bitshift to get the value of the one you want. I doubt it will be faster, and it's probably going to gives you a lot of headaches working that way, but technically it's possible.
On a side note, an attempt like this could prove useful for systems that don't have a lot of memory available for variables but do have some more processing power then what you need. I highly doubt you will ever need it though.