Google Contacts now (Jan 2019) issues a long (19 digit) decimal number id for each contact that you create.
Unfortunately, as discussed in this question the ID cannot be put into a URL to view the contact easily, however if you convert this decimal number to Hex it can be put into the URL.
So the question is, how to convert
c2913347583522826972
to
286E4A310F1EEADC
When I use the Decimal to Hex converter here it gives me
286E4A310F1EEADC if I drop the c (2nd function below is a version of the sites code, but it does use PHP too maybe)
However trying the following functions in Javascript give me mixed results
The first one is from this stack question which is the closest, just 2 digits off
function decimalToHexString(number)
{
number = parseFloat(number);
if (number < 0)
{
number = 0xFFFFFFFF + number + 1;
}
return number.toString(16);
}
console.log(decimalToHexString('2913347583522826972'));
//output 286e4a310f1eea00
function convertDec(inp,outp) {
var pd = '';
var output ;
var input = inp;
for (i=0; i < input.length; i++) {
var e=input[i].charCodeAt(0);var s = "";
output+= e + pd;
}
return output;
}
//return 50574951515255535651535050565054575550
Love to know your thoughts on improving this process
It seems like the limit of digit size. You have to use arrays if you need to convert bigger digits.
You can use hex2dec npm package to convert between hex and dec.
>> converter.decToHex("2913347583522826972", { prefix: false }
//286e4a310f1eeadc
Js example
On python side, you can simply do
dec = 2913347583522826972
// Python implicitly handles prefix
hexa = hex(dec)
print dec == int(hexa, 16)
// True
Python example
For more take a look at the following gist
https://gist.github.com/agirorn/0e740d012b620968225de58859ccef5c
Itroduction
I'm currently working on John Conway's Game of Life in js. I have the game working (view here) and i'm working on extra functionalities such as sharing your "grid / game" to your friends. To do this i'm extracting the value's of the grid (if the cell is alive or dead) into a long string of 0's and 1's.
This string has a variable length since the grid is not always the same size. for example:
grid 1 has a length and width of 30 => so the string's length is 900
grid 2 has a length and width of 50 => so the string's length is 2500
The problem
As you can see these string's of 0's and 1's are way too long to copy around and share.
However hard i try I don't seem to be able to come up with a code that would compress a string this long to a easy to handle one.
Any ideas on how to compress (and decompress) this?
I have considered simply writing down every possible grid option for the gird sizes 1x1 to 100x100 and giving them a key/reference to use as sharable code. Doing that by hand would be madness but maybe any of you has an idea on how to create an algorithm that can do this?
GitHub repository
In case it wasn't already obvious, the string you're trying to store looks like a binary string.
Counting systems
Binary is a number in base-2. This essentially means that there are two characters being used to keep count. Normally we are used to count with base-10 (decimal characters). In computer science the hexadecimal system (base-16) is also widely being used.
Since you're not storing the bits as bits but as bytes (use var a = 0b1100001; if you ever wish to store them like bits) the 'binary' you wish to store just takes as much space as any other random string with the same length.
Since you're using the binary system each position just has 2 possible values. When using the hexadecimal value a single position can hold up to 16 possible values. This is already a big improvement when it comes to storing the data compactly. As an example 0b11111111 and 0xff both represents the decimal number 255.
In your situation that'd shave 6 bytes of every 8 bytes you have to store. In the end you'd be stuck with a string just 1/4th of the length of the original string.
Javascript implementation
Essentially what we want to do is to interpret the string you store as binary and retrieve the hexadecimal value. Luckily JavaScript has built in functionality to achieve stuff like this:
var bin =
'1110101110100011' +
'0000101111100001' +
'1010010101011010' +
'0000110111011111' +
'1111111001010101' +
'0111000011100001' +
'1011010100110001' +
'0111111110010100' +
'0111110110100101' +
'0000111101100111' +
'1100001111011100' +
'0101011100001111' +
'0110011011001101' +
'1000110010001001' +
'1010100010000011' +
'0011110000000000';
var returnValue = '';
for (var i = 0; i < parseInt(bin.length / 8); i++) {
returnValue += parseInt(bin.substr(i*8, 8), 2).toString(16);
}
console.log(bin.length); // Will return 265
console.log(returnValue.length); // Will return 64
We're saying "parse this string and interpret it like a base-2 number and store it as a hexadecimal string".
Decoding is practically the same. Replace all occurrences of the number 8 in the example above with 2 and vice versa.
Please note
A prerequisite for this code to work correctly is that the binary length is dividable by 8. See the following example:
parseInt('00011110', 2).toString(16); // returns '1e'
parseInt('1e', 16).toString(2); // returns '11110'
// Technically both representations still have the same decimal value
When decoding you should add leading zeros until you have a full byte (8 bits).
In case the positions you have to store are not dividable by 8 you can, for example, add padding and add a number to the front of the output string to identify how much positions to strip.
Wait, there's more
To get even shorter strings you can build a lookup table with 265 characters in which you search for the character associated with the specific position. (This works because you're still storing the hexadecimal value as a string.) Sadly neither the ASCII nor the UTF-8 encodings are suited for this as there are blocks with values which have no characters defined.
It may look like:
// Go fill this array until you have 265 values within it.
var lookup = ['A', 'B', 'C', 'D'];
var smallerValue = lookup[0x00];
This way you can have 265 possible values at a single position, AND you have used your byte to the fullest.
Please note that no real compression is happening here. We're rather utilising data types to be used more efficiently for your current use case.
If we make the assumption than the grid contains much more 0's than 1's, you may want to try this simple compression scheme:
convert the binary string to an hexadecimal string
convert '00' sub-strings to 'z' symbol
convert 'zz' sub-strings to 'Z' symbol
we could go further, but let's stop here for the demo
Below is an example with a 16x16 grid:
var bin =
'0000000000000000' +
'0000001000000000' +
'0000011100000000' +
'0000001000000000' +
'0000000000000000' +
'0000000000111000' +
'0000100000111000' +
'0000000000111000' +
'0000000000000000' +
'0000000000000000' +
'0000000010000000' +
'0000000101000000' +
'0000000010000000' +
'0000000000000000' +
'0000100000000000' +
'0000000000000000';
var packed = bin
.match(/(.{4})/g)
.map(function(x) {
return parseInt(x, 2).toString(16);
})
.join('')
.replace(/00/g, 'z')
.replace(/zz/g, 'Z');
This will produce the string "Z02z07z02ZZ380838z38ZZz8z14z08Zz8Zz".
The unpacking process is doing the exact opposite:
var bin = packed
.replace(/Z/g, 'zz')
.replace(/z/g, '00')
.split('')
.map(function(x) {
return ('000' + parseInt(x, 16).toString(2)).substr(-4, 4);
})
.join('');
Note that this code will only work correctly if the length of the input string is a multiple of 4. If it's not the case, you'll have to pad the input and crop the output.
EDIT : 2nd method
If the input is completely random -- with roughly as many 0's as 1's and no specific repeating patterns -- the best you can do is probably to convert the binary string to a BASE64 string. It will be significantly shorter (this time with a fixed compression ratio of about 17%) and can still be copied/pasted by the user.
Packing:
var bin =
'1110101110100011' +
'0000101111100001' +
'1010010101011010' +
'0000110111011111' +
'1111111001010101' +
'0111000011100001' +
'1011010100110001' +
'0111111110010100' +
'0111110110100101' +
'0000111101100111' +
'1100001111011100' +
'0101011100001111' +
'0110011011001101' +
'1000110010001001' +
'1010100010000011' +
'0011110000000000';
var packed =
btoa(
bin
.match(/(.{8})/g)
.map(function(x) {
return String.fromCharCode(parseInt(x, 2));
})
.join('')
);
Will produce the string "66ML4aVaDd/+VXDhtTF/lH2lD2fD3FcPZs2MiaiDPAA=".
Unpacking:
var bin =
atob(packed)
.split('')
.map(function(x) {
return ('0000000' + x.charCodeAt(0).toString(2)).substr(-8, 8);
})
.join('');
Or if you want to go a step further, you can consider using something like base91 instead, for a reduced encoding overhead.
LZ-string
Using LZ-string I was able to compress the "code" quite a bit.
By simply compressing it to base64 like this:
var compressed = LZString.compressToBase64(string)
Decompressing is also just as simple as this:
var decompressed = LZString.decompressFromBase64(compressed)
However the length of this compressed string is still pretty long given that you have about as many 0s as 1s (not given in the example)
example
But the compression does work.
ANSWER
For any of you who are wondering how exactly I ended up doing it, here's how:
First I made sure every string passed in would be padded with leading 0s untill it was devidable by 8. (saving the amount of 0s used to pad, since they're needed while decompressing)
I used Corstian's answer and functions to compress my string (interpreted as binary) into a hexadecimal string. Although i had to make one slight alteration.
Not every binary substring with a lenght of 8 will return exactly 2 hex characters. so for those cases i ended up just adding a 0 in front of the substring. The hex substring will have the same value but it's length will now be 2.
Next up i used a functionality from Arnaulds answer. Taking every double character and replacing it with a single character (one not used in the hexadecimal alphabet to avoid conflict). I did this twice for every hexadecimal character.
For example:
the hex string 11 will become h and hh will become H
01101111 will become 0h0H
Since most grids are gonna have more dead cells then alive ones, I made sure the 0s would be able to compress even further, using Arnaulds method again but going a step further.
00 -> g | gg -> G | GG -> w | ww -> W | WW -> x | xx -> X | XX-> y | yy -> Y | YY -> z | zz -> Z
This resulted in Z representing 4096 (binary) 0s
The last step of the compression was adding the amount of leading 0s in front of the compressed string, so we can shave those off at the end of decompressing.
This is how the returned string looks in the end.
amount of leading 0s-compressed string so a 64*64 empty grid, will result in 0-Z
Decompressing is practically doing everything the other way around.
Firstly splitting the number that represents how many leading 0s we've used as padding from the compressed string.
Then using Arnaulds functionality, turning the further "compressed" characters back into hexadecimal code.
Taking this hex string and turning it back into binary code. Making sure, as Corstian pointed out, that every binary substring will have a length of 8. (ifnot we pad the substrings with leading 0s untill the do, exactly, have a length of 8)
And then the last step is to shave off the leading 0s we've used as padding to make the begin string devidable by 8.
The functions
Function I use to compress:
/**
* Compresses the a binary string into a compressed string.
* Returns the compressed string.
*/
Codes.compress = function(bin) {
bin = bin.toString(); // To make sure the binary is a string;
var returnValue = ''; // Empty string to add our data to later on.
// If the lenght of the binary string is not devidable by 8 the compression
// won't work correctly. So we add leading 0s to the string and store the amount
// of leading 0s in a variable.
// Determining the amount of 'padding' needed.
var padding = ((Math.ceil(bin.length/8))*8)-bin.length;
// Adding the leading 0s to the binary string.
for (var i = 0; i < padding; i++) {
bin = '0'+bin;
}
for (var i = 0; i < parseInt(bin.length / 8); i++) {
// Determining the substring.
var substring = bin.substr(i*8, 8)
// Determining the hexValue of this binary substring.
var hexValue = parseInt(substring, 2).toString(16);
// Not all binary values produce two hex numbers. For example:
// '00000011' gives just a '3' while what we wand would be '03'. So we add a 0 in front.
if(hexValue.length == 1) hexValue = '0'+hexValue;
// Adding this hexValue to the end string which we will return.
returnValue += hexValue;
}
// Compressing the hex string even further.
// If there's any double hex chars in the string it will take those and compress those into 1 char.
// Then if we have multiple of those chars these are compressed into 1 char again.
// For example: the hex string "ff will result in a "v" and "ffff" will result in a "V".
// Also: "11" will result in a "h" and "1111" will result in a "H"
// For the 0s this process is repeated a few times.
// (string with 4096 0s) (this would represent a 64*64 EMPTY grid)
// will result in a "Z".
var returnValue = returnValue.replace(/00/g, 'g')
.replace(/gg/g, 'G')
// Since 0s are probably more likely to exist in our binary and hex, we go a step further compressing them like this:
.replace(/GG/g, 'w')
.replace(/ww/g, 'W')
.replace(/WW/g, 'x')
.replace(/xx/g, 'X')
.replace(/XX/g, 'y')
.replace(/yy/g, 'Y')
.replace(/YY/g, 'z')
.replace(/zz/g, 'Z')
//Rest of the chars...
.replace(/11/g, 'h')
.replace(/hh/g, 'H')
.replace(/22/g, 'i')
.replace(/ii/g, 'I')
.replace(/33/g, 'j')
.replace(/jj/g, 'J')
.replace(/44/g, 'k')
.replace(/kk/g, 'K')
.replace(/55/g, 'l')
.replace(/ll/g, 'L')
.replace(/66/g, 'm')
.replace(/mm/g, 'M')
.replace(/77/g, 'n')
.replace(/nn/g, 'N')
.replace(/88/g, 'o')
.replace(/oo/g, 'O')
.replace(/99/g, 'p')
.replace(/pp/g, 'P')
.replace(/aa/g, 'q')
.replace(/qq/g, 'Q')
.replace(/bb/g, 'r')
.replace(/rr/g, 'R')
.replace(/cc/g, 's')
.replace(/ss/g, 'S')
.replace(/dd/g, 't')
.replace(/tt/g, 'T')
.replace(/ee/g, 'u')
.replace(/uu/g, 'U')
.replace(/ff/g, 'v')
.replace(/vv/g, 'V');
// Adding the number of leading 0s that need to be ignored when decompressing to the string.
returnValue = padding+'-'+returnValue;
// Returning the compressed string.
return returnValue;
}
The function I use to decompress:
/**
* Decompresses the compressed string back into a binary string.
* Returns the decompressed string.
*/
Codes.decompress = function(compressed) {
var returnValue = ''; // Empty string to add our data to later on.
// Splitting the input on '-' to seperate the number of paddin 0s and the actual hex code.
var compressedArr = compressed.split('-');
var paddingAmount = compressedArr[0]; // Setting a variable equal to the amount of leading 0s used while compressing.
compressed = compressedArr[1]; // Setting the compressed variable to the actual hex code.
// Decompressing further compressed characters.
compressed = compressed// Decompressing the further compressed 0s. (even further then the rest of the chars.)
.replace(/Z/g, 'zz')
.replace(/z/g, 'YY')
.replace(/Y/g, 'yy')
.replace(/y/g, 'XX')
.replace(/X/g, 'xx')
.replace(/x/g, 'WW')
.replace(/W/g, 'ww')
.replace(/w/g, 'GG')
.replace(/G/g, 'gg')
.replace(/g/g, '00')
// Rest of chars...
.replace(/H/g, 'hh')
.replace(/h/g, '11')
.replace(/I/g, 'ii')
.replace(/i/g, '22')
.replace(/J/g, 'jj')
.replace(/j/g, '33')
.replace(/K/g, 'kk')
.replace(/k/g, '44')
.replace(/L/g, 'll')
.replace(/l/g, '55')
.replace(/M/g, 'mm')
.replace(/m/g, '66')
.replace(/N/g, 'nn')
.replace(/n/g, '77')
.replace(/O/g, 'oo')
.replace(/o/g, '88')
.replace(/P/g, 'pp')
.replace(/p/g, '99')
.replace(/Q/g, 'qq')
.replace(/q/g, 'aa')
.replace(/R/g, 'rr')
.replace(/r/g, 'bb')
.replace(/S/g, 'ss')
.replace(/s/g, 'cc')
.replace(/T/g, 'tt')
.replace(/t/g, 'dd')
.replace(/U/g, 'uu')
.replace(/u/g, 'ee')
.replace(/V/g, 'vv')
.replace(/v/g, 'ff');
for (var i = 0; i < parseInt(compressed.length / 2); i++) {
// Determining the substring.
var substring = compressed.substr(i*2, 2);
// Determining the binValue of this hex substring.
var binValue = parseInt(substring, 16).toString(2);
// If the length of the binary value is not equal to 8 we add leading 0s (js deletes the leading 0s)
// For instance the binary number 00011110 is equal to the hex number 1e,
// but simply running the code above will return 11110. So we have to add the leading 0s back.
if (binValue.length != 8) {
// Determining how many 0s to add:
var diffrence = 8 - binValue.length;
// Adding the 0s:
for (var j = 0; j < diffrence; j++) {
binValue = '0'+binValue;
}
}
// Adding the binValue to the end string which we will return.
returnValue += binValue
}
var decompressedArr = returnValue.split('');
returnValue = ''; // Emptying the return variable.
// Deleting the not needed leading 0s used as padding.
for (var i = paddingAmount; i < decompressedArr.length; i++) {
returnValue += decompressedArr[i];
}
// Returning the decompressed string.
return returnValue;
}
URL shortener
I still found the "compressed" strings a little long for sharing / pasting around. So i used a simple URL shortener (view here) to make this process a little easier for the user.
Now you might ask, then why did you need to compress this string anyway?
Here's why:
First of all, my project is hosted on github pages (gh-pages). The info page of gh-pages tells us that the url can't be any longer than 2000 chars. This would mean that the max grid size would be the square root of 2000 - length of the base url, which isn't that big. By using this "compression" we are able to share much larger grids.
Now the second reason why is that, it's a challange. I find dealing with problems like these fun and also helpfull since you learn a lot.
Live
You can view the live version of my project here. and/or find the github repository here.
Thankyou
I want to thank everyone who helped me with this problem. Especially Corstian and Arnauld, since i ended up using their answers to reach my final functions.
Sooooo.... thanks guys! apriciate it!
In the Game of Life there is a board of ones and zeros. I want to back up to previous generation - size 4800 - save each 16 cells as hexadecimal = 1/4 the size. http://innerbeing.epizy.com/cwebgl/gameoflife.html [g = Go] [b = Backup]
function drawGen(n) {
stop(); var i = clamp(n,0,brw*brh-1), hex = gensave[i].toString();
echo(":",i, n,nGEN); nGEN = i; var str = '';
for (var i = 0; i < parseInt(hex.length / 4); i++)
str = str + pad(parseInt(hex.substr(i*4,4), 16).toString(2),16,'0');
for (var j=0;j<Board.length;j++) Board[j] = intr(str.substr(j,1));
drawBoard();
}
function Bin2Hex(n) {
var i = n.indexOf("1"); /// leading Zeros = NAN
if (i == -1) return "0000";
i = right(n,i*-1);
return pad(parseInt(i,2).toString(16),4,'0');
}
function saveGen(n) {
var b = Board.join(''), str = ''; /// concat array to string 10101
for (var i = 0; i < parseInt(b.length / 16); i++)
str = str + Bin2Hex(b.substr(i*16,16));
gensave[n] = str;
}
function right(st,n) {
var s = st.toString();
if (!n) return s;
if (n < 0) return s.substr(n * -1,s.length + n);
return s.substr(s.length - n,n);
}
function pad(str, l, padwith) {
var s = str;
while (s.length < l) s = padwith + s;
return s;
}
I've written a JavaScript program that calculates the depth of a binary tree based on the number of elements. My program has been working fine for months, but recently I've found a difference when the web page is viewed in Chrome vs Firefox.
In particular, on Firefox:
Math.log2(8) = 3
but now in Chrome:
Math.log2(8) = 2.9999999999999996
My JavaScript program was originally written to find the depth of the binary tree based on the number of elements as:
var tree_depth = Math.floor(Math.log2(n_elements)) + 1;
I made a simple modification to this formula so that it will still work correctly on Chrome:
var epsilon = 1.e-5;
var tree_depth = Math.floor(Math.log2(n_elements) + epsilon) + 1;
I have 2 questions:
Has anyone else noticed a change in the precision in Chrome recently for Math.log2?
Is there a more elegant modification than the one I made above by adding epsilon?
Note: Math.log2 hasn't actually changed since it's been implemented
in V8. Maybe you remembered incorrectly or you had included a shim that
happened to get the result correct for these special cases before Chrome
included its own implementation of Math.log2.
Also, it seems that you should be using Math.ceil(x) rather than
Math.floor(x) + 1.
How can I solve this?
To avoid relying on Math.log or Math.log2 being accurate amongst different implementations of JavaScript (the algorithm used is implementation-defined), you can use bitwise operators if you have less than 232 elements in your binary tree. This obviously isn't the fastest way of doing this (this is only O(n)), but it's a relatively simple example:
function log2floor(x) {
// match the behaviour of Math.floor(Math.log2(x)), change it if you like
if (x === 0) return -Infinity;
for (var i = 0; i < 32; ++i) {
if (x >>> i === 1) return i;
}
}
console.log(log2floor(36) + 1); // 6
How is Math.log2 currently implemented in different browsers?
The current implementation in Chrome is inaccurate as they rely on multiplying the value of Math.log(x) by Math.LOG2E, making it susceptible to rounding error (source):
// ES6 draft 09-27-13, section 20.2.2.22.
function MathLog2(x) {
return MathLog(x) * 1.442695040888963407; // log2(x) = log(x)/log(2).
}
If you are running Firefox, it either uses the native log2 function (if present), or if not (e.g. on Windows), uses a similar implementation to Chrome (source).
The only difference is that instead of multiplying, they divide by log(2) instead:
#if !HAVE_LOG2
double log2(double x)
{
return log(x) / M_LN2;
}
#endif
Multiplying or dividing: how much of a difference does it make?
To test the difference between dividing by Math.LN2 and multiplying by Math.LOG2E, we can use the following test:
function log2d(x) { return Math.log(x) / Math.LN2; }
function log2m(x) { return Math.log(x) * Math.LOG2E; }
// 2^1024 rounds to Infinity
for (var i = 0; i < 1024; ++i) {
var resultD = log2d(Math.pow(2, i));
var resultM = log2m(Math.pow(2, i));
if (resultD !== i) console.log('log2d: expected ' + i + ', actual ' + resultD);
if (resultM !== i) console.log('log2m: expected ' + i + ', actual ' + resultM);
}
Note that no matter which function you use, they still have floating point errors for certain values1. It just so happens that the floating point representation of log(2) is less than the actual value, resulting in a value higher than the actual value (while log2(e) is lower). This means that using log(2) will round down to the correct value for these special cases.
1: log(pow(2, 29)) / log(2) === 29.000000000000004
You could perhaps do this instead
// Math.log2(n_elements) to 10 decimal places
var tree_depth = Math.floor(Math.round(Math.log2(n_elements) * 10000000000) / 10000000000);
Recently I run into the well known floating point precision errors of Javascript. Usually I would avoid floating point calculations on the thin client & rather leave it to the back-end.
I started using the big.js library created by Michael Mclaughlin. Though it has a square-root method/function, it does not have a nth-root methods/function nor does the power function support fraction values as arguments.
So I was wondering if anyone using the library has extended it to have such a function or at least use it to calculate accurate nth-root results.
Michael Mclaughlin suggested that I implement such a function similar in structure to the square-root function. However my attempts at understanding the logic proofed my maths-disability, resulting in simple calculations yielding very wrong results.
Using the algorithm on Rosetta Code also yields incorrect results.
So I was wondering if anyone using the library has extended it to have such a function or at least use it to calculate accurate nth-root results.
Here is the code to my last attempt:
P['nthrt'] = P['nthroot'] = function (n, prec)
{
var negate, r,
x = this,
xc = x['c'],
i = x['s'],
e = x['e'];
// Argument defaults
n = n || 2;
prec = prec || 12;
// Zero?
if ( !xc[0] ) {
return new Big(x)
}
// Negative?
negate = ( n % 2 == 1 && i < 0 );
// Estimate.
r = new Big(1); // Initial guess.
for (var i = 0; i < prec; i++) {
r = (ONE.div(n)).times(r.times(n-1).plus(x.div(r.pow(n-1))));
}
if (negate) r['s'] = -1;
return r;
};
It does not even get obvious results correct like the 4th root of 81 = 3, instead it gets 3.00000000xxx
Newton's method only gives an approximation for the root, so 3.0000xxx should be expected. If you know that the answer should be an integer, you can round r down (Newton's method overestimates the root) and check that r^n=x.
You can use big-numbers library to solve your problem. They support sqrt, pow, exp and many other features.
The pow method accept positive, negative, integer and floating point numbers:
var bn = new BigNumber();
var value = bn.of('81');
var xRoot = value.pow(0.25);
console.log('Result: ' + bn.format(xRoot));
You can use Basenumber.js to perform nth root. Documentation here.
E.g.
// Set precision decimals required
Base.setDecimals(25);
let x = Base("1e+10");
console.log(x.root(10).toString());
<script src='https://cdn.jsdelivr.net/gh/AlexSp3/Basenumber.js#main/BaseNumber.min.js'></script>
I am looking for a way of performing a bitwise AND on a 64 bit integer in JavaScript.
JavaScript will cast all of its double values into signed 32-bit integers to do the bitwise operations (details here).
Javascript represents all numbers as 64-bit double precision IEEE 754 floating point numbers (see the ECMAscript spec, section 8.5.) All positive integers up to 2^53 can be encoded precisely. Larger integers get their least significant bits clipped. This leaves the question of how can you even represent a 64-bit integer in Javascript -- the native number data type clearly can't precisely represent a 64-bit int.
The following illustrates this. Although javascript appears to be able to parse hexadecimal numbers representing 64-bit numbers, the underlying numeric representation does not hold 64 bits. Try the following in your browser:
<html>
<head>
<script language="javascript">
function showPrecisionLimits() {
document.getElementById("r50").innerHTML = 0x0004000000000001 - 0x0004000000000000;
document.getElementById("r51").innerHTML = 0x0008000000000001 - 0x0008000000000000;
document.getElementById("r52").innerHTML = 0x0010000000000001 - 0x0010000000000000;
document.getElementById("r53").innerHTML = 0x0020000000000001 - 0x0020000000000000;
document.getElementById("r54").innerHTML = 0x0040000000000001 - 0x0040000000000000;
}
</script>
</head>
<body onload="showPrecisionLimits()">
<p>(2^50+1) - (2^50) = <span id="r50"></span></p>
<p>(2^51+1) - (2^51) = <span id="r51"></span></p>
<p>(2^52+1) - (2^52) = <span id="r52"></span></p>
<p>(2^53+1) - (2^53) = <span id="r53"></span></p>
<p>(2^54+1) - (2^54) = <span id="r54"></span></p>
</body>
</html>
In Firefox, Chrome and IE I'm getting the following. If numbers were stored in their full 64-bit glory, the result should have been 1 for all the substractions. Instead, you can see how the difference between 2^53+1 and 2^53 is lost.
(2^50+1) - (2^50) = 1
(2^51+1) - (2^51) = 1
(2^52+1) - (2^52) = 1
(2^53+1) - (2^53) = 0
(2^54+1) - (2^54) = 0
So what can you do?
If you choose to represent a 64-bit integer as two 32-bit numbers, then applying a bitwise AND is as simple as applying 2 bitwise AND's, to the low and high 32-bit 'words'.
For example:
var a = [ 0x0000ffff, 0xffff0000 ];
var b = [ 0x00ffff00, 0x00ffff00 ];
var c = [ a[0] & b[0], a[1] & b[1] ];
document.body.innerHTML = c[0].toString(16) + ":" + c[1].toString(16);
gets you:
ff00:ff0000
Here is code for AND int64 numbers, you can replace AND with other bitwise operation
function and(v1, v2) {
var hi = 0x80000000;
var low = 0x7fffffff;
var hi1 = ~~(v1 / hi);
var hi2 = ~~(v2 / hi);
var low1 = v1 & low;
var low2 = v2 & low;
var h = hi1 & hi2;
var l = low1 & low2;
return h*hi + l;
}
This can now be done with the new BigInt built-in numeric type. BigInt is currently (July 2019) only available in certain browsers, see the following link for details:
https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/BigInt
I have tested bitwise operations using BigInts in Chrome 67 and can confirm that they work as expected with up to 64 bit values.
Javascript doesn't support 64 bit integers out of the box. This is what I ended up doing:
Found long.js, a self contained Long implementation on github.
Convert the string value representing the 64 bit number to a Long.
Extract the high and low 32 bit values
Do a 32 bit bitwise and between the high and low bits, separately
Initialise a new 64 bit Long from the low and high bit
If the number is > 0 then there is correlation between the two numbers
Note: for the code example below to work you need to load
long.js.
// Handy to output leading zeros to make it easier to compare the bits when outputting to the console
function zeroPad(num, places){
var zero = places - num.length + 1;
return Array(+(zero > 0 && zero)).join('0') + num;
}
// 2^3 = 8
var val1 = Long.fromString('8', 10);
var val1High = val1.getHighBitsUnsigned();
var val1Low = val1.getLowBitsUnsigned();
// 2^61 = 2305843009213693960
var val2 = Long.fromString('2305843009213693960', 10);
var val2High = val2.getHighBitsUnsigned();
var val2Low = val2.getLowBitsUnsigned();
console.log('2^3 & (2^3 + 2^63)')
console.log(zeroPad(val1.toString(2), 64));
console.log(zeroPad(val2.toString(2), 64));
var bitwiseAndResult = Long.fromBits(val1Low & val2Low, val1High & val2High, true);
console.log(bitwiseAndResult);
console.log(zeroPad(bitwiseAndResult.toString(2), 64));
console.log('Correlation betwen val1 and val2 ?');
console.log(bitwiseAndResult > 0);
Console output:
2^3
0000000000000000000000000000000000000000000000000000000000001000
2^3 + 2^63
0010000000000000000000000000000000000000000000000000000000001000
2^3 & (2^3 + 2^63)
0000000000000000000000000000000000000000000000000000000000001000
Correlation between val1 and val2?
true
The Closure library has goog.math.Long with a bitwise add() method.
Unfortunately, the accepted answer (and others) appears not to have been adequately tested. Confronted by this problem recently, I initially tried to split my 64-bit numbers into two 32-bit numbers as suggested, but there's another little wrinkle.
Open your JavaScript console and enter:
0x80000001
When you press Enter, you'll obtain 2147483649, the decimal equivalent. Next try:
0x80000001 & 0x80000003
This gives you -2147483647, not quite what you expected. It's clear that in performing the bitwise AND, the numbers are treated as signed 32-bit integers. And the result is wrong. Even if you negate it.
My solution was to apply ~~ to the 32-bit numbers after they were split off, check for a negative sign, and then deal with this appropriately.
This is clumsy. There may be a more elegant 'fix', but I can't see it on quick examination. There's a certain irony that something that can be accomplished by a couple of lines of assembly should require so much more labour in JavaScript.