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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);
}
Do what bryc suggests ... but before you use his cyrb128 hash function to initialise, note that the return statement throws away 32 bits of entropy. Exclusive-or the four values together = 0. You should probably make the first element (h2^h3^h4) >>> 0.
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))
I am trying to create a function that can take a number and the number of decimal places and round the number to the exact decimal places that are going to be given.
I am using parseInt(prompt()) in order to gave the number and the number of decimal places.
For example,
round(3.141519, 2) -> 3.14
round(5986.32456, 4) -> 5986.3246
Can someone help me with this?
You can use toFixed
check the following
console.log(3.141519.toFixed(2))
console.log(5986.32456.toFixed(4))
Here is a short function that will allow you to specify the precision and returns a number:
function round(number, places) {
number = parseFloat(number, 10);
var e = parseInt(places || 2, 10);
var m = Math.pow(10, e);
return Math.floor(number * m) / m;
}
Or a slightly shorter ES6 function:
const round = (number, places=2) => {
const m = Math.pow(10, places);
return Math.floor(number * m) / m;
}
I was reading code in a library from Adobe (snap.svg.js) and I saw this code, which confused me:
function curveDim(p1x, p1y, c1x, c1y, c2x, c2y, p2x, p2y) {
var a = (c2x - 2 * c1x + p1x) - (p2x - 2 * c2x + c1x),
b = 2 * (c1x - p1x) - 2 * (c2x - c1x),
c = p1x - c1x,
t1 = (-b + Math.sqrt(b * b - 4 * a * c)) / 2 / a,
t2 = (-b - Math.sqrt(b * b - 4 * a * c)) / 2 / a;
Math.abs(t1) > "1e12" && (t1 = .5);
Math.abs(t2) > "1e12" && (t2 = .5);
Since the formula is pretty complicated, I couldn't come up with values to test it, so I wanted to ask the general question: why can you compare Math.abs(t1) to a string '1e12'? Wouldn't that convert the floating point number to a string and then just do lexical comparison? What if the variable a is zero? Is this good code? Any explanation of what the author is trying to do and if it is correct would be great.
No, the > operator converts both operands to numbers (http://es5.github.io/#x11.8.2, http://es5.github.io/#x11.8.5).
See what happens when I convert the string to a number:
> +"1e12"
1000000000000
1e12 is actually a valid number literal and means 1 * 1012. No idea why they used strings instead, Math.abs(t1) > 1e12 would work just as fine.
You can easily test this yourself
var t1 = 10000000000000;
if (Math.abs(t1) > "1e12")
console.log('t1 is greater');
else
console.log('t1 is less or equal');
See JSFiddle
Question
Does anyone know of a way to round a float to the nearest 0.05 in JavaScript?
Example
BEFORE | AFTER
2.51 | 2.55
2.50 | 2.50
2.56 | 2.60
Current Code
var _ceil = Math.ceil;
Math.ceil = function(number, decimals){
if (arguments.length == 1)
return _ceil(number);
multiplier = Math.pow(10, decimals);
return _ceil(number * multiplier) / multiplier;
}
Then elsewhere...
return (Math.ceil((amount - 0.05), 1) + 0.05).toFixed(2);
Which is resulting in...
BEFORE | AFTER
2.51 | 2.55
2.50 | 2.55
2.56 | 2.65
Multiply by 20, then divide by 20:
(Math.ceil(number*20)/20).toFixed(2)
Rob's answer with my addition:
(Math.ceil(number*20 - 0.5)/20).toFixed(2)
Otherwise it always rounds up to the nearest 0.05.
** UPDATE **
Sorry has been pointed out this is not what the orig poster wanted.
I would go for the standard of actually dividing by the number you're factoring it to, and rounding that and multiplying it back again after. That seems to be a proper working method which you can use with any number and maintain the mental image of what you are trying to achieve.
var val = 26.14,
factor = 0.05;
val = Math.round(val / factor) * factor;
This will work for tens, hundreds or any number. If you are specifically rounding to the higher number then use Math.ceil instead of Math.round.
Another method specifically for rounding just to 1 or more decimal places (rather than half a place) is the following:
Number(Number(1.5454545).toFixed(1));
It creates a fixed number string and then turns it into a real Number.
I would write a function that does it for you by
move the decimal over two places (multiply by 100)
then mod (%) that inflatedNumber by 5 and get the remainder
subtract the remainder from 5 so that you know what the 'gap'(ceilGap) is between your number and the next closest .05
finally, divide your inflatedNumber by 100 so that it goes back to your original float, and voila, your num will be rounded up to the nearest .05.
function calcNearestPointZeroFive(num){
var inflatedNumber = num*100,
remainder = inflatedNumber % 5;
ceilGap = 5 - remainder
return (inflatedNumber + ceilGap)/100
}
If you want to leave numbers like 5.50 untouched you can always add this checker:
if (remainder===0){
return num
} else {
var ceilGap = 5 - remainder
return (inflatedNumber + ceilGap)/100
}
You need to put -1 to round half down and after that multiply by -1 like the example down bellow.
<script type="text/javascript">
function roundNumber(number, precision, isDown) {
var factor = Math.pow(10, precision);
var tempNumber = number * factor;
var roundedTempNumber = 0;
if (isDown) {
tempNumber = -tempNumber;
roundedTempNumber = Math.round(tempNumber) * -1;
} else {
roundedTempNumber = Math.round(tempNumber);
}
return roundedTempNumber / factor;
}
</script>
<div class="col-sm-12">
<p>Round number 1.25 down: <script>document.write(roundNumber(1.25, 1, true));</script>
</p>
<p>Round number 1.25 up: <script>document.write(roundNumber(1.25, 1, false));</script></p>
</div>
I ended up using this function in my project, successfully:
roundToNearestFiveCents( number: any ) {
return parseFloat((Math.round(number / 0.05) * 0.05).toFixed(2));
}
Might be of use to someone wanting to simply round to the nearest 5 cents on their monetary results, keeps the result a number, so if you perform addition on it further it won't result in string concatenation; also doesn't unnecessarily round up as a few of the other answers pointed out. Also limits it to two decimals, which is customary with finance.
My solution and test:
let round = function(number, precision = 2, rounding = 0.05) {
let multiply = 1 / rounding;
return parseFloat((Math.round(number * multiply) / multiply)).toFixed(precision);
};
https://jsfiddle.net/maciejSzewczyk/7r1tvhdk/40/
Even though the OP is not explicit about banker rounding, rounding up to the nearest $0.05 (5 cents) should be compatible with banker rounding. What suggested by Arth is more accurate than the accepted answer by Rob W.
(Math.ceil(number*20 - 0.5)/20).toFixed(2)
With banker rounding, you need a basic banker rounding function as suggested at Gaussian/banker's rounding in JavaScript, and I rewrite in TypeScript:
static bankerRound(num: number, decimalPlaces?: number) {
const d = decimalPlaces || 0;
const m = Math.pow(10, d);
const n = +(d ? num * m : num).toFixed(8);
const i = Math.floor(n), f = n - i;
const e = 1e-8;
const r = (f > 0.5 - e && f < 0.5 + e) ?
((i % 2 === 0) ? i : i + 1) : Math.round(n);
return d ? r / m : r;
}
static roundTo5cents(num: number) {
const r = bankerRound(Math.ceil(num * 20 - 0.5) / 20, 2);
return r;
}
The correctness of this algorithm could be verified through MBS Online, e.g. http://www9.health.gov.au/mbs/ready_reckoner.cfm?item_num=60
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);
}
Do what bryc suggests ... but before you use his cyrb128 hash function to initialise, note that the return statement throws away 32 bits of entropy. Exclusive-or the four values together = 0. You should probably make the first element (h2^h3^h4) >>> 0.
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))