How to add bits in JavaScript - javascript

Say you have two integers 10 and 20. That is 00001010 and 00010100. I would then like to just basically concat these as strings, but have the result be a new integer.
00001010 + 00010100 == 0000101000010100
That final number is 2580.
However, I am looking for a way to do this without actually converting them to string. Looking for something more efficient that just does some bit twiddling on the integers themselves. I'm not too familiar with that, but I imagine it would be along the lines of:
var a = 00001010 // == 10
var b = 00010100 // == 20
var c = a << b // == 2580
Note, I would like for this to work with any sequences of bits. So even:
var a = 010101
var b = 01110
var c = a + b == 01010101110

You basic equation is:
c = b + (a << 8).
The trick here is that you need to always shift by 8. But since a and b do not always use all 8 bits in the byte, JavaScript will automatically omit any leading zeros. We need to recover the number of leading zeros (of b), or trailing zeros of a, and prepend them back before adding. This way, all the bits stay in their proper position. This requires an equation like this:
c = b + (a << s + r)
Where s is the highest set bit (going from right to left) in b, and r is the remaining number of bits such that s + r = 8.
Essentially, all you are doing is shifting the first operand a over by 8 bits, to effectively add trailing zeros to a or equally speaking, padding leading zeros to the second operand b. Then you add normally. This can be accomplishing using logarithms, and shifting, and bitwise OR operation to provide an O(1) solution for some arbitrary positive integers a and b where the number of bits in a and b do not exceed some positive integer n. In the case of a byte, n = 8.
// Bitwise log base 2 in O(1) time
function log2(n) {
// Check if n > 0
let bits = 0;
if (n > 0xffff) {
n >>= 16;
bits = 0x10;
}
if (n > 0xff) {
n >>= 8;
bits |= 0x8;
}
if (n > 0xf) {
n >>= 4;
bits |= 0x4;
}
if (n > 0x3) {
n >>= 2;
bits |= 0x2;
}
if (n > 0x1) {
bits |= 0x1;
}
return bits;
}
// Computes the max set bit
// counting from the right to left starting
// at 0. For 20 (10100) we get bit # 4.
function msb(n) {
n |= n >> 1;
n |= n >> 2;
n |= n >> 4;
n |= n >> 8;
n |= n >> 16;
n = n + 1;
// We take the log here because
// n would otherwise be the largest
// magnitude of base 2. So, for 20,
// n+1 would be 16. Which, to
// find the number of bits to shift, we must
// take the log base 2
return log2(n >> 1);
}
// Operands
let a = 0b00001010 // 10
let b = 0b00010100 // 20
// Max number of bits in
// in binary number
let n = 8
// Max set bit is the 16 bit, which is in position
// 4. We will need to pad 4 more zeros
let s = msb(b)
// How many zeros to pad on the left
// 8 - 4 = 4
let r = Math.abs(n - s)
// Shift a over by the computed
// number of bits including padded zeros
let c = b + (a << s + r)
console.log(c)
Output:
2580
Notes:
This is NOT commutative.
Add error checking to log2() for negative numbers, and other edge cases.
References:
https://www.geeksforgeeks.org/find-significant-set-bit-number/
https://github.com/N02870941/java_data_structures/blob/master/src/main/java/util/misc/Mathematics.java

so the problem:
a is 10 (in binary 0000 1010)
b is 20 (in binary 0100 0100)
you want to get 2580 using bit shift somehow.
if you right shift a by 8 using a<<=8 (this is the same as multiplying a by 2^8) you get 1010 0000 0000 which is the same as 10*2^8 = 2560. since the lower bits of a are all 0's (when you use << it fills the new bits with 0) you can just add b on top of it 1010 0000 0000 + 0100 0100 gives you 1010 0001 0100.
so in 1 line of code, it's var result = a<<8 + b. Remember in programming languages, most of them have no explicit built-in types for "binary". But everything is binary in its nature. so int is a "binary", an object is "binary" ....etc. When you want to do some binary operations on some data you can just use the datatype you have as operands for binary operations.
this is a more general version of how to concatenate two numbers' binary representations using no string operations and data
/*
This function concate b to the end of a and put 0's in between them.
b will be treated starting with it's first 1 as its most significant bit
b needs to be bigger than 0, otherwise, Math.log2 will give -Infinity for 0 and NaN for negative b
padding is the number of 0's to add at the end of a
*/
function concate_bits(a, b, padding) {
//add the padding 0's to a
a <<= padding;
//this gets the largest power of 2
var power_of_2 = Math.floor(Math.log2(b));
var power_of_2_value;
while (power_of_2 >= 0) {
power_of_2_value = 2 ** power_of_2;
a <<= 1;
if (b >= power_of_2_value) {
a += 1;
b -= power_of_2_value;
}
power_of_2--;
}
return a;
}
//this will print 2580 as the result
let result = concate_bits(10, 20, 3);
console.log(result);

Note, I would like for this to work with any sequences of bits. So even:
var a = 010101
var b = 01110
var c = a + b == 01010101110
This isn't going to be possible unless you convert to a string or otherwise store the number of bits in each number. 10101 010101 0010101 etc are all the same number (21), and once this is converted to a number, there is no way to tell how many leading zeroes the number originally had.

Related

Random from array seeded with today's date in JavaScript [duplicate]

Is it possible to seed the random number generator (Math.random) in JavaScript?
No, it is not possible to seed Math.random(). The ECMAScript specification is intentionally vague on the subject, providing no means for seeding nor require that browsers even use the same algorithm. So such a function must be externally provided, which thankfully isn't too difficult.
I've implemented a number of good, short and fast Pseudorandom number generator (PRNG) functions in plain JavaScript. All of them can be seeded and provide high quality numbers. These are not intended for security purposes--if you need a seedable CSPRNG, look into ISAAC.
First of all, take care to initialize your PRNGs properly. To keep things simple, the generators below have no built-in seed generating procedure, but accept one or more 32-bit numbers as the initial seed state of the PRNG. Similar or sparse seeds (e.g. a simple seed of 1 and 2) have low entropy, and can cause correlations or other randomness quality issues, sometimes resulting in the output having similar properties (such as randomly generated levels being similar). To avoid this, it is best practice to initialize PRNGs with a well-distributed, high entropy seed and/or advancing past the first 15 or so numbers.
There are many ways to do this, but here are two methods. Firstly, hash functions are very good at generating seeds from short strings. A good hash function will generate very different results even when two strings are similar, so you don't have to put much thought into the string. Here's an example hash function:
function cyrb128(str) {
let h1 = 1779033703, h2 = 3144134277,
h3 = 1013904242, h4 = 2773480762;
for (let i = 0, k; i < str.length; i++) {
k = str.charCodeAt(i);
h1 = h2 ^ Math.imul(h1 ^ k, 597399067);
h2 = h3 ^ Math.imul(h2 ^ k, 2869860233);
h3 = h4 ^ Math.imul(h3 ^ k, 951274213);
h4 = h1 ^ Math.imul(h4 ^ k, 2716044179);
}
h1 = Math.imul(h3 ^ (h1 >>> 18), 597399067);
h2 = Math.imul(h4 ^ (h2 >>> 22), 2869860233);
h3 = Math.imul(h1 ^ (h3 >>> 17), 951274213);
h4 = Math.imul(h2 ^ (h4 >>> 19), 2716044179);
return [(h1^h2^h3^h4)>>>0, (h2^h1)>>>0, (h3^h1)>>>0, (h4^h1)>>>0];
}
Calling cyrb128 will produce a 128-bit hash value from a string which can be used to seed a PRNG. Here's how you might use it:
// Create cyrb128 state:
var seed = cyrb128("apples");
// Four 32-bit component hashes provide the seed for sfc32.
var rand = sfc32(seed[0], seed[1], seed[2], seed[3]);
// Only one 32-bit component hash is needed for mulberry32.
var rand = mulberry32(seed[0]);
// Obtain sequential random numbers like so:
rand();
rand();
Note: If you want a slightly more robust 128-bit hash, consider MurmurHash3_x86_128, it's more thorough, but intended for use with large arrays.
Alternatively, simply choose some dummy data to pad the seed with, and advance the generator beforehand a few times (12-20 iterations) to mix the initial state thoroughly. This has the benefit of being simpler, and is often used in reference implementations of PRNGs, but it does limit the number of initial states:
var seed = 1337 ^ 0xDEADBEEF; // 32-bit seed with optional XOR value
// Pad seed with Phi, Pi and E.
// https://en.wikipedia.org/wiki/Nothing-up-my-sleeve_number
var rand = sfc32(0x9E3779B9, 0x243F6A88, 0xB7E15162, seed);
for (var i = 0; i < 15; i++) rand();
Note: the output of these PRNG functions produce a positive 32-bit number (0 to 232-1) which is then converted to a floating-point number between 0-1 (0 inclusive, 1 exclusive) equivalent to Math.random(), if you want random numbers of a specific range, read this article on MDN. If you only want the raw bits, simply remove the final division operation.
JavaScript numbers can only represent whole integers up to 53-bit resolution. And when using bitwise operations, this is reduced to 32. Modern PRNGs in other languages often use 64-bit operations, which require shims when porting to JS that can drastically reduce performance. The algorithms here only use 32-bit operations, as it is directly compatible with JS.
Now, onward to the the generators. (I maintain the full list with references and license info here)
sfc32 (Simple Fast Counter)
sfc32 is part of the PractRand random number testing suite (which it passes of course). sfc32 has a 128-bit state and is very fast in JS.
function sfc32(a, b, c, d) {
return function() {
a >>>= 0; b >>>= 0; c >>>= 0; d >>>= 0;
var t = (a + b) | 0;
a = b ^ b >>> 9;
b = c + (c << 3) | 0;
c = (c << 21 | c >>> 11);
d = d + 1 | 0;
t = t + d | 0;
c = c + t | 0;
return (t >>> 0) / 4294967296;
}
}
You may wonder what the | 0 and >>>= 0 are for. These are essentially 32-bit integer casts, used for performance optimizations. Number in JS are basically floats, but during bitwise operations, they switch into a 32-bit integer mode. This mode is processed faster by JS interpreters, but any multiplication or addition will cause it to switch back to a float, resulting in a performance hit.
Mulberry32
Mulberry32 is a simple generator with a 32-bit state, but is extremely fast and has good quality randomness (author states it passes all tests of gjrand testing suite and has a full 232 period, but I haven't verified).
function mulberry32(a) {
return function() {
var t = a += 0x6D2B79F5;
t = Math.imul(t ^ t >>> 15, t | 1);
t ^= t + Math.imul(t ^ t >>> 7, t | 61);
return ((t ^ t >>> 14) >>> 0) / 4294967296;
}
}
I would recommend this if you just need a simple but decent PRNG and don't need billions of random numbers (see Birthday problem).
xoshiro128**
As of May 2018, xoshiro128** is the new member of the Xorshift family, by Vigna & Blackman (professor Vigna was also responsible for the Xorshift128+ algorithm powering most Math.random implementations under the hood). It is the fastest generator that offers a 128-bit state.
function xoshiro128ss(a, b, c, d) {
return function() {
var t = b << 9, r = a * 5; r = (r << 7 | r >>> 25) * 9;
c ^= a; d ^= b;
b ^= c; a ^= d; c ^= t;
d = d << 11 | d >>> 21;
return (r >>> 0) / 4294967296;
}
}
The authors claim it passes randomness tests well (albeit with caveats). Other researchers have pointed out that it fails some tests in TestU01 (particularly LinearComp and BinaryRank). In practice, it should not cause issues when floats are used (such as in these implementations), but may cause issues if relying on the raw lowest order bit.
JSF (Jenkins' Small Fast)
This is JSF or 'smallprng' by Bob Jenkins (2007), who also made ISAAC and SpookyHash. It passes PractRand tests and should be quite fast, although not as fast as sfc32.
function jsf32(a, b, c, d) {
return function() {
a |= 0; b |= 0; c |= 0; d |= 0;
var t = a - (b << 27 | b >>> 5) | 0;
a = b ^ (c << 17 | c >>> 15);
b = c + d | 0;
c = d + t | 0;
d = a + t | 0;
return (d >>> 0) / 4294967296;
}
}
No, it is not possible to seed Math.random(), but it's fairly easy to write your own generator, or better yet, use an existing one.
Check out: this related question.
Also, see David Bau's blog for more information on seeding.
NOTE: Despite (or rather, because of) succinctness and apparent elegance, this algorithm is by no means a high-quality one in terms of randomness. Look for e.g. those listed in this answer for better results.
(Originally adapted from a clever idea presented in a comment to another answer.)
var seed = 1;
function random() {
var x = Math.sin(seed++) * 10000;
return x - Math.floor(x);
}
You can set seed to be any number, just avoid zero (or any multiple of Math.PI).
The elegance of this solution, in my opinion, comes from the lack of any "magic" numbers (besides 10000, which represents about the minimum amount of digits you must throw away to avoid odd patterns - see results with values 10, 100, 1000). Brevity is also nice.
It's a bit slower than Math.random() (by a factor of 2 or 3), but I believe it's about as fast as any other solution written in JavaScript.
No, but here's a simple pseudorandom generator, an implementation of Multiply-with-carry I adapted from Wikipedia (has been removed since):
var m_w = 123456789;
var m_z = 987654321;
var mask = 0xffffffff;
// Takes any integer
function seed(i) {
m_w = (123456789 + i) & mask;
m_z = (987654321 - i) & mask;
}
// Returns number between 0 (inclusive) and 1.0 (exclusive),
// just like Math.random().
function random()
{
m_z = (36969 * (m_z & 65535) + (m_z >> 16)) & mask;
m_w = (18000 * (m_w & 65535) + (m_w >> 16)) & mask;
var result = ((m_z << 16) + (m_w & 65535)) >>> 0;
result /= 4294967296;
return result;
}
Antti Sykäri's algorithm is nice and short. I initially made a variation that replaced JavaScript's Math.random when you call Math.seed(s), but then Jason commented that returning the function would be better:
Math.seed = function(s) {
return function() {
s = Math.sin(s) * 10000; return s - Math.floor(s);
};
};
// usage:
var random1 = Math.seed(42);
var random2 = Math.seed(random1());
Math.random = Math.seed(random2());
This gives you another functionality that JavaScript doesn't have: multiple independent random generators. That is especially important if you want to have multiple repeatable simulations running at the same time.
Please see Pierre L'Ecuyer's work going back to the late 1980s and early 1990s. There are others as well. Creating a (pseudo) random number generator on your own, if you are not an expert, is pretty dangerous, because there is a high likelihood of either the results not being statistically random or in having a small period. Pierre (and others) have put together some good (pseudo) random number generators that are easy to implement. I use one of his LFSR generators.
https://www.iro.umontreal.ca/~lecuyer/myftp/papers/handstat.pdf
Combining some of the previous answers, this is the seedable random function you are looking for:
Math.seed = function(s) {
var mask = 0xffffffff;
var m_w = (123456789 + s) & mask;
var m_z = (987654321 - s) & mask;
return function() {
m_z = (36969 * (m_z & 65535) + (m_z >>> 16)) & mask;
m_w = (18000 * (m_w & 65535) + (m_w >>> 16)) & mask;
var result = ((m_z << 16) + (m_w & 65535)) >>> 0;
result /= 4294967296;
return result;
}
}
var myRandomFunction = Math.seed(1234);
var randomNumber = myRandomFunction();
It's not possible to seed the builtin Math.random function, but it is possible to implement a high quality RNG in Javascript with very little code.
Javascript numbers are 64-bit floating point precision, which can represent all positive integers less than 2^53. This puts a hard limit to our arithmetic, but within these limits you can still pick parameters for a high quality Lehmer / LCG random number generator.
function RNG(seed) {
var m = 2**35 - 31
var a = 185852
var s = seed % m
return function () {
return (s = s * a % m) / m
}
}
Math.random = RNG(Date.now())
If you want even higher quality random numbers, at the cost of being ~10 times slower, you can use BigInt for the arithmetic and pick parameters where m is just able to fit in a double.
function RNG(seed) {
var m_as_number = 2**53 - 111
var m = 2n**53n - 111n
var a = 5667072534355537n
var s = BigInt(seed) % m
return function () {
return Number(s = s * a % m) / m_as_number
}
}
See this paper by Pierre l'Ecuyer for the parameters used in the above implementations:
https://www.ams.org/journals/mcom/1999-68-225/S0025-5718-99-00996-5/S0025-5718-99-00996-5.pdf
And whatever you do, avoid all the other answers here that use Math.sin!
To write your own pseudo random generator is quite simple.
The suggestion of Dave Scotese is useful but, as pointed out by others, it is not quite uniformly distributed.
However, it is not because of the integer arguments of sin. It's simply because of the range of sin, which happens to be a one dimensional projection of a circle. If you would take the angle of the circle instead it would be uniform.
So instead of sin(x) use arg(exp(i * x)) / (2 * PI).
If you don't like the linear order, mix it a bit up with xor. The actual factor doesn't matter that much either.
To generate n pseudo random numbers one could use the code:
function psora(k, n) {
var r = Math.PI * (k ^ n)
return r - Math.floor(r)
}
n = 42; for(k = 0; k < n; k++) console.log(psora(k, n))
Please also note that you cannot use pseudo random sequences when real entropy is needed.
Many people who need a seedable random-number generator in Javascript these days are using David Bau's seedrandom module.
Math.random no, but the ran library solves this. It has almost all distributions you can imagine and supports seeded random number generation. Example:
ran.core.seed(0)
myDist = new ran.Dist.Uniform(0, 1)
samples = myDist.sample(1000)
Here's the adopted version of Jenkins hash, borrowed from here
export function createDeterministicRandom(): () => number {
let seed = 0x2F6E2B1;
return function() {
// Robert Jenkins’ 32 bit integer hash function
seed = ((seed + 0x7ED55D16) + (seed << 12)) & 0xFFFFFFFF;
seed = ((seed ^ 0xC761C23C) ^ (seed >>> 19)) & 0xFFFFFFFF;
seed = ((seed + 0x165667B1) + (seed << 5)) & 0xFFFFFFFF;
seed = ((seed + 0xD3A2646C) ^ (seed << 9)) & 0xFFFFFFFF;
seed = ((seed + 0xFD7046C5) + (seed << 3)) & 0xFFFFFFFF;
seed = ((seed ^ 0xB55A4F09) ^ (seed >>> 16)) & 0xFFFFFFFF;
return (seed & 0xFFFFFFF) / 0x10000000;
};
}
You can use it like this:
const deterministicRandom = createDeterministicRandom()
deterministicRandom()
// => 0.9872818551957607
deterministicRandom()
// => 0.34880331158638
No, like they said it is not possible to seed Math.random()
but you can install external package which make provision for that. i used these package which can be install using these command
npm i random-seed
the example is gotten from the package documentation.
var seed = 'Hello World',
rand1 = require('random-seed').create(seed),
rand2 = require('random-seed').create(seed);
console.log(rand1(100), rand2(100));
follow the link for documentation https://www.npmjs.com/package/random-seed
SIN(id + seed) is a very interesting replacement for RANDOM functions that cannot be seeded like SQLite:
https://stackoverflow.com/a/75089040/7776828
Most of the answers here produce biased results. So here's a tested function based on seedrandom library from github:
!function(f,a,c){var s,l=256,p="random",d=c.pow(l,6),g=c.pow(2,52),y=2*g,h=l-1;function n(n,t,r){function e(){for(var n=u.g(6),t=d,r=0;n<g;)n=(n+r)*l,t*=l,r=u.g(1);for(;y<=n;)n/=2,t/=2,r>>>=1;return(n+r)/t}var o=[],i=j(function n(t,r){var e,o=[],i=typeof t;if(r&&"object"==i)for(e in t)try{o.push(n(t[e],r-1))}catch(n){}return o.length?o:"string"==i?t:t+"\0"}((t=1==t?{entropy:!0}:t||{}).entropy?[n,S(a)]:null==n?function(){try{var n;return s&&(n=s.randomBytes)?n=n(l):(n=new Uint8Array(l),(f.crypto||f.msCrypto).getRandomValues(n)),S(n)}catch(n){var t=f.navigator,r=t&&t.plugins;return[+new Date,f,r,f.screen,S(a)]}}():n,3),o),u=new m(o);return e.int32=function(){return 0|u.g(4)},e.quick=function(){return u.g(4)/4294967296},e.double=e,j(S(u.S),a),(t.pass||r||function(n,t,r,e){return e&&(e.S&&v(e,u),n.state=function(){return v(u,{})}),r?(c[p]=n,t):n})(e,i,"global"in t?t.global:this==c,t.state)}function m(n){var t,r=n.length,u=this,e=0,o=u.i=u.j=0,i=u.S=[];for(r||(n=[r++]);e<l;)i[e]=e++;for(e=0;e<l;e++)i[e]=i[o=h&o+n[e%r]+(t=i[e])],i[o]=t;(u.g=function(n){for(var t,r=0,e=u.i,o=u.j,i=u.S;n--;)t=i[e=h&e+1],r=r*l+i[h&(i[e]=i[o=h&o+t])+(i[o]=t)];return u.i=e,u.j=o,r})(l)}function v(n,t){return t.i=n.i,t.j=n.j,t.S=n.S.slice(),t}function j(n,t){for(var r,e=n+"",o=0;o<e.length;)t[h&o]=h&(r^=19*t[h&o])+e.charCodeAt(o++);return S(t)}function S(n){return String.fromCharCode.apply(0,n)}if(j(c.random(),a),"object"==typeof module&&module.exports){module.exports=n;try{s=require("crypto")}catch(n){}}else"function"==typeof define&&define.amd?define(function(){return n}):c["seed"+p]=n}("undefined"!=typeof self?self:this,[],Math);
function randIntWithSeed(seed, max=1) {
/* returns a random number between [0,max] including zero and max
seed can be either string or integer */
return Math.round(new Math.seedrandom('seed' + seed)()) * max
}
test for true randomness of this code: https://es6console.com/kkjkgur2/
There are plenty of good answers here but I had a similar issue with the additional requirement that I would like portability between Java's random number generator and whatever I ended up using in JavaScript.
I found the java-random package
These two pieces of code had identical output assuming the seed is the same:
Java:
Random randomGenerator = new Random(seed);
int randomInt;
for (int i=0; i<10; i++) {
randomInt = randomGenerator.nextInt(50);
System.out.println(randomInt);
}
JavaScript:
let Random = require('java-random');
let rng = new Random(seed);
for (let i=0; i<10; i++) {
let val = rng.nextInt(50);
console.log(val);
}
I have written a function that returns a seeded random number, it uses Math.sin to have a long random number and uses the seed to pick numbers from that.
Use :
seedRandom("k9]:2#", 15)
it will return your seeded number
the first parameter is any string value ; your seed.
the second parameter is how many digits will return.
function seedRandom(inputSeed, lengthOfNumber){
var output = "";
var seed = inputSeed.toString();
var newSeed = 0;
var characterArray = ['0','1','2','3','4','5','6','7','8','9','a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','y','x','z','A','B','C','D','E','F','G','H','I','J','K','L','M','N','O','P','Q','U','R','S','T','U','V','W','X','Y','Z','!','#','#','$','%','^','&','*','(',')',' ','[','{',']','}','|',';',':',"'",',','<','.','>','/','?','`','~','-','_','=','+'];
var longNum = "";
var counter = 0;
var accumulator = 0;
for(var i = 0; i < seed.length; i++){
var a = seed.length - (i+1);
for(var x = 0; x < characterArray.length; x++){
var tempX = x.toString();
var lastDigit = tempX.charAt(tempX.length-1);
var xOutput = parseInt(lastDigit);
addToSeed(characterArray[x], xOutput, a, i);
}
}
function addToSeed(character, value, a, i){
if(seed.charAt(i) === character){newSeed = newSeed + value * Math.pow(10, a)}
}
newSeed = newSeed.toString();
var copy = newSeed;
for(var i=0; i<lengthOfNumber*9; i++){
newSeed = newSeed + copy;
var x = Math.sin(20982+(i)) * 10000;
var y = Math.floor((x - Math.floor(x))*10);
longNum = longNum + y.toString()
}
for(var i=0; i<lengthOfNumber; i++){
output = output + longNum.charAt(accumulator);
counter++;
accumulator = accumulator + parseInt(newSeed.charAt(counter));
}
return(output)
}
A simple approach for a fixed seed:
function fixedrandom(p){
const seed = 43758.5453123;
return (Math.abs(Math.sin(p)) * seed)%1;
}
In PHP, there is function srand(seed) which generate fixed random value for particular seed.
But, in JS, there is no such inbuilt function.
However, we can write simple and short function.
Step 1: Choose some Seed (Fix Number).
var seed = 100;
Number should be Positive Integer and greater than 1, further explanation in Step 2.
Step 2: Perform Math.sin() function on Seed, it will give sin value of that number. Store this value in variable x.
var x;
x = Math.sin(seed); // Will Return Fractional Value between -1 & 1 (ex. 0.4059..)
sin() method returns a Fractional value between -1 and 1.And we don't need Negative value, therefore, in first step choose number greater than 1.
Step 3: Returned Value is a Fractional value between -1 and 1. So mulitply this value with 10 for making it more than 1.
x = x * 10; // 10 for Single Digit Number
Step 4: Multiply the value with 10 for additional digits
x = x * 10; // Will Give value between 10 and 99 OR
x = x * 100; // Will Give value between 100 and 999
Multiply as per requirement of digits.
The result will be in decimal.
Step 5: Remove value after Decimal Point by Math's Round (Math.round()) Method.
x = Math.round(x); // This will give Integer Value.
Step 6: Turn Negative Values into Positive (if any) by Math.abs method
x = Math.abs(x); // Convert Negative Values into Positive(if any)
Explanation End.Final Code
var seed = 111; // Any Number greater than 1
var digit = 10 // 1 => single digit, 10 => 2 Digits, 100 => 3 Digits and so. (Multiple of 10)
var x; // Initialize the Value to store the result
x = Math.sin(seed); // Perform Mathematical Sin Method on Seed.
x = x * 10; // Convert that number into integer
x = x * digit; // Number of Digits to be included
x = Math.round(x); // Remove Decimals
x = Math.abs(x); // Convert Negative Number into Positive
Clean and Optimized Functional Code
function random_seed(seed, digit = 1) {
var x = Math.abs(Math.round(Math.sin(seed++) * 10 * digit));
return x;
}
Then Call this function using
random_seed(any_number, number_of_digits)any_number is must and should be greater than 1.number_of_digits is optional parameter and if nothing passed, 1 Digit will return.
random_seed(555); // 1 Digit
random_seed(234, 1); // 1 Digit
random_seed(7895656, 1000); // 4 Digit
For a number between 0 and 100.
Number.parseInt(Math.floor(Math.random() * 100))

Understanding converting big endian to/from string

Looking at these implementations, I am wondering if one could explain the reason behind the specific operations. Not coming from computer science, I am not sure why these decisions were made.
function binb2rstr(input) {
var str = []
for (var i = 0, n = input.length * 32; i < n; i += 8) {
var code = (input[i >> 5] >>> (24 - i % 32)) & 0xFF
var val = String.fromCharCode(code)
str.push(val)
}
return str.join('')
}
function rstr2binb(input) {
var output = Array(input.length >> 2)
for (var i = 0, n = output.length; i < n; i++) {
output[i] = 0
}
for (var i = 0, n = input.length * 8; i < n; i += 8) {
output[i >> 5] |= (input.charCodeAt(i / 8) & 0xFF) << (24 - i % 32)
}
return output
}
What I understand so far are:
i += 8 is for iterating through bytes.
0xFF is 255, which is 2^8 - 1, so 1 byte.
32 which is the size of a word, or 4 bytes
| is bitwise OR, <<, >>>, and & are likewise bit operators.
The % modulus keeps the value within that max value of x = x % max.
What I don't understand is:
i >> 5, how that was picked.
& 0xFF, how that was picked.
24 - i % 32, where the 24 came from.
var code = (input[i >> 5] >>> (24 - i % 32)) & 0xFF, how the character code is computed from that.
input.length >> 2
Wondering if this is just a standard computer science function because it's hard to tell where these variables come from and how this was learned. It seems like these values must be a standard algorithm based on byte length but I can't tell how to get there with these open questions. Thank you for your help.
This code consists of some pretty clever bit-fiddling based on 32-bit values.
But let's work on your points:
i >> 5, how that was picked.
This divides i by 32 --- corresponding to the n = input.length * 32 overall length. Considering the whole algorithm this means that one value is processed four times (0,8,16,24) before selecting the next input value.
& 0xFF, how that was picked.
This simply selects the lowest 8-bit of a n-bit value.
24 - i % 32, where the 24 came from.
This relates to i += 8. The i % 32 indicates four different iterations (32/8=4) which are temp= (0, 8, 16, 24). So 24-temp results in (24,16,8,0).
var code = (input[i >> 5] >>> (24 - i % 32)) & 0xFF, how the character code is computed from that.
1. 1st iteration: i=0 ;24-0=24; input[0] >>> 24 & 0xFF = highest byte of input[0] shifted to lowest
2. 2nd iteration: i=8 ;24-8=16; input[0] >>> 16 & 0xFF = 2nd highest byte of input[0] shifted to 2nd lowest
3. 3rd iteration: i=16;24-16=8; input[0] >>> 8 & 0xFF = 2nd lowest byte of input[0] shifted to 2nd highest
4. 4th iteration: i=8 ;24-24=0; input[0] >>> 0 & 0xFF = lowest byte of input[0] shifted to highest
This was the Big-Endian-Conversion.
The next iteration has i=32 and starts the next iteration input[32/32]=input[1].
Overall this algorithm shifts the 32-bit code to the right and masks the lowest 8-bit to be used as a CharCode by String.fromCharCode(code).
The last one is from a different algorithm and so input.length >> 2 simply does a division by 2 discarding the possible rest of 1.
Concerning your last question:
It seems like these values must be a standard algorithm based on byte length but I can't tell how to get there with these open questions.
This is far from a standard algorithm. It is just a clever bit-manipulation based on bytes.
In assembler this code would be even easier to understand.
There is even one instruction called BSWAP to swap between 32-bit Big-Endian and Little-Endian values in a register.

Decreasing byte size of integer block in socket communication

I am developing a multiplayer game server.
On my case, every single byte that really matter for gaming experience and saving bandwith.
Client and server will send some integer values each other.
Integers mostly will have values lower than 100.
In some cases, that integers could have values between 0 and 100000.
All that integers will be send in same sequence. (Imagine that they are integer array)
Using 8 bit integer array or 16 bit integer array is not an option to me because of possible values greater than 65535.
And, I do not want to use 32 bit integer array just for the values what be in action rarely.
So, I developed an algorithm for that (here is the javascript port):
function write(buffer, number){
while(number > 0x7f){
buffer.push(0x80 | (number & 0x7f));
number >>= 7;
}
buffer.push(number);
}
function read(buffer){
var cur, result = 0, shift = 0x8DC54E1C0; // ((((((28 << 6) | 21) << 6) | 14) << 6) | 7) << 6;
while((cur = buffer.shift()) > 0x7f)
{
result |= (cur & 0x7f) << shift;
shift >>= 6;
}
return result | (cur << shift);
}
var d = [];
var number = 127;
write(d, number);
alert("value bytes: " + d);
var newResult = read(d);
alert("equals : " + (number === newResult));
My question is: Is there a better way to solve that problem ?
Thanks in advance

Bitwise operation on octal number

I want to do some bit operation in javascript on a variable. I have this numbers:
min: 153391689 (base 10) - 1111111111 (base 8)
max: 1073741823 (base 10) - 7777777777 (base 8)
Now I want to use this variable for storing 10 "vars" with options from 0 to 7.
For that, I need to get and set every octal digit (meaning 3 bits).
Unfortunately, I didn't made it, but I came with something:
var num = 153391689;
function set(val, loc) {
num |= val << (loc * 3);
}
function get(loc) {
return (num & 7 << loc * 3) / Math.pow(8, loc);
}
Thank you.
As mentioned by Amit in a comment, your set function doesn't clear the bits before setting the value, so if there is already a value at that location then the new value will be ORed with it.
You can clear the location by ANDing the number with the bitwise NOT of the bitmask for that position. Applying a bitwise NOT to the mask means that only bits that are not in the location you are interested in remain set.
function set(val, loc) {
num &= ~(7 << (loc * 3)); // clear bits
num |= val << (loc * 3); // set bits
}
Note that the brackets around the (loc * 3) are optional, because Javascript's order of operator precedence means that the multiplication will be done before the shift even without them.
Your get function looks like it will work, but you can simplify it. Instead of shifting the bitmask left, ANDing and then shifting right again (by doing a division), you can just shift right and then mask. This moves the bits you are interested in into the least significant 3 bits, and then masks them with the AND:
function get(loc) {
return (num >> (loc * 3)) & 7;
}

What kind of checksum is this function calculating?

This is a function where bytes comes from a string, and each letter's char code was grabbed to create an array of bytyes
function checksum(bytes) {
var a = 0;
var b = 0;
for (var i = 0; i < bytes.length; i++) {
a = (a + bytes[i]) % 0xff;
b = (b + a) % 0xff;
}
return (b << 8) | a;
}
I'm mostly confused at the role of % 0xff and b << 8. Could someone help me break this down?
a is equal to the sum of all the elements modulo 255
b is equal to the sum of all the values that a assumes modulo 255 (so 1 time the last element + 2 times the one before that ....)
The final value is a 16 bit number where the higher 8 bits are b and the lower 8 bits are a.
That is actually a Fletcher's checksum
https://en.wikipedia.org/wiki/Fletcher%27s_checksum
This function calculates a and b, and generates the checksum from it.
a is calculated as follows:
0+the value of the current char
a must be between 0 and 254, hence modulo 255 is applied
b is calculated as the cumulative value of a modulo 255
increase the value of b by a
b must be between 0 and 254, hence modulo 255 is applied
at the end the checksum is generated by concatenating a to b
take b's bits and move them 8 places to the left
set a to the right side of b
The result will have a length of 2 bytes (16 bits), where the first byte is b and the second a.
Example:
(c is the current char value)
c | a |b
----------------
8 |8 |8
13 |21 |29
5 |26 |55
0 |26 |81
180 |206 |287
100 |51 |83
cheksum = 51,83 = 0x3353 = 0011 0011 0101 0011

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