Seeding the random number generator in Javascript

Question

Is it possible to seed the random number generator  Math random  in JavaScript

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For a number between 0 and 100   Number parseInt Math floor Math random     100

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Here s the adopted version of Jenkins hash  borrowed from here export function createDeterministicRandom         gt  number     let seed   0x2F6E2B1    return function            Robert Jenkins    32 bit integer hash function     seed     seed   0x7ED55D16     seed  lt  lt  12     amp  0xFFFFFFFF      seed     seed   0xC761C23C     seed  gt  gt  gt  19    amp  0xFFFFFFFF      seed     seed   0x165667B1     seed  lt  lt  5      amp  0xFFFFFFFF      seed     seed   0xD3A2646C     seed  lt  lt  9      amp  0xFFFFFFFF      seed     seed   0xFD7046C5     seed  lt  lt  3      amp  0xFFFFFFFF      seed     seed   0xB55A4F09     seed  gt  gt  gt  16    amp  0xFFFFFFFF      return  seed  amp  0xFFFFFFF    0x10000000          You can use it like this  const deterministicRandom   createDeterministicRandom   deterministicRandom        gt  0 9872818551957607  deterministicRandom        gt  0 34880331158638

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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                            amp                                                         lt         gt                    -                           var longNum                  var counter   0             var accumulator   0              for var i   0  i  lt  seed length  i                     var a   seed length -  i 1                   for var x   0  x  lt  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 lt 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 lt lengthOfNumber  i                     output   output   longNum charAt accumulator                   counter                    accumulator   accumulator   parseInt newSeed charAt counter                            return output

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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

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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 good quality numbers   First of all  take care to initialize your PRNGs properly  Most of the generators below have no built-in seed generating procedure  for sake of simplicity   but accept one or more 32-bit values as the initial state of the PRNG  Similar seeds  e g  a simple seed of 1 and 2  can cause correlations in weaker PRNGs  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 seed   Thankfully  hash functions are very good at generating seeds for PRNGs from short strings  A good hash function will generate very different results even when two strings are similar  Here s an example based on MurmurHash3 s mixing function   function xmur3 str        for var i   0  h   1779033703   str length  i  lt  str length  i            h   Math imul h   str charCodeAt i   3432918353           h   h  lt  lt  13   h  gt  gt  gt  19      return function             h   Math imul h   h  gt  gt  gt  16  2246822507           h   Math imul h   h  gt  gt  gt  13  3266489909           return  h    h  gt  gt  gt  16   gt  gt  gt  0            Each subsequent call to the return function of xmur3 produces a new  random  32-bit hash value to be used as a seed in a PRNG  Here s how you might use it      Create xmur3 state  var seed   xmur3  apples       Output four 32-bit hashes to provide the seed for sfc32  var rand   sfc32 seed    seed    seed    seed         Output one 32-bit hash to provide the seed for mulberry32  var rand   mulberry32 seed         Obtain sequential random numbers like so  rand    rand      Alternatively  simply choose some dummy data to pad the seed with  and advance the generator a few times  12-20 iterations  to mix the initial state thoroughly  This is often seen 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  lt  15  i    rand      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   Another thing to note are the limitations of JS  Numbers can only represent whole integers up to 53-bit resolution  And when using bitwise operations  this is reduced to 32  This makes it difficult to implement algorithms written in C or C    that use 64-bit numbers  Porting 64-bit code requires shims that can drastically reduce performance  So for the sake of simplicity and efficiency  I ve only considered algorithms that use 32-bit math  as it is directly compatible with JS      Now  onward to the the generators   I maintain the full list with references 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  gt  gt  gt   0  b  gt  gt  gt   0  c  gt  gt  gt   0  d  gt  gt  gt   0         var t    a   b    0        a   b   b  gt  gt  gt  9        b   c    c  lt  lt  3    0        c    c  lt  lt  21   c  gt  gt  gt  11         d   d   1   0        t   t   d   0        c   c   t   0        return  t  gt  gt  gt  0    4294967296            Mulberry32  Mulberry32 is a simple generator with a 32-bit state  but is extremely fast and has good quality  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  gt  gt  gt  15  t   1         t    t   Math imul t   t  gt  gt  gt  7  t   61         return   t   t  gt  gt  gt  14   gt  gt  gt  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  amp  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  lt  lt  9  r   a   5  r    r  lt  lt  7   r  gt  gt  gt  25    9          c    a  d    b          b    c  a    d  c    t          d   d  lt  lt  11   d  gt  gt  gt  21          return  r  gt  gt  gt  0    4294967296            The authors claim it passes randomness tests well  albeit with caveats   Other researchers have pointed out that fails some tests in TestU01  particularly LinearComp and BinaryRank   In practice  it should not cause issues when floats are used  such as these implementations   but may cause issues if relying on the raw low bits    JSF  Jenkins  Small Fast   This is JSF or  smallprng  by Bob Jenkins  2007   the guy who made ISAAC and SpookyHash  It passes PractRand tests and should be quite fast  although not as fast as SFC   function jsf32 a  b  c  d        return function             a    0  b    0  c    0  d    0          var t   a -  b  lt  lt  27   b  gt  gt  gt  5    0          a   b    c  lt  lt  17   c  gt  gt  gt  15           b   c   d   0          c   d   t   0          d   a   t   0          return  d  gt  gt  gt  0    4294967296            LCG  aka Lehmer Park-Miller RNG or MCG   LCG is extremely fast and simple  but the quality of its randomness is so low  that improper use can actually cause bugs in your program  Nonetheless  it is significantly better than some answers suggesting to use Math sin or Math PI  It s a one-liner though  which is nice      var LCG s  gt     gt  2  31-1 amp  s Math imul 48271 s    2  31    This implementation is called the minimal standard RNG as proposed by Park   Miller in 1988  amp  1993 and implemented in C  11 as minstd rand  Keep in mind that the state is 31-bit  31 bits give 2 billion possible states  32 bits give double that   This is the very type of PRNG that others are trying to replace   It will work  but I wouldn t use it unless you really need speed and don t care about randomness quality  what is random anyway    Great for a game jam or a demo or something  LCGs suffer from seed correlations  so it is best to discard the first result of an LCG  And if you insist on using an LCG  adding an increment value may improve results  but it is probably an exercise in futility when much better options exist   There seems to be other multipliers offering a 32-bit state  increased state-space     var LCG s  gt     gt  s Math imul 741103597 s  gt  gt  gt 0  2  32  var LCG s  gt     gt  s Math imul 1597334677 s  gt  gt  gt 0  2  32    These LCG values are from  P  L Ecuyer  A table of Linear Congruential Generators of different sizes and good lattice structure  April 30 1997

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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

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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  amp  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   gt  single digit  10   gt  2 Digits  100   gt  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

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A simple approach for a fixed seed   function fixedrandom p       const seed   43758 5453123      return  Math abs Math sin p     seed  1

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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   amp  mask      m z    987654321 - i   amp  mask        Returns number between 0  inclusive  and 1 0  exclusive      just like Math random    function random         m z    36969    m z  amp  65535     m z  gt  gt  16    amp  mask      m w    18000    m w  amp  65535     m w  gt  gt  16    amp  mask      var result     m z  lt  lt  16     m w  amp  65535    gt  gt  gt  0      result    4294967296      return result      EDIT  fixed seed function by making it reset m z EDIT2  Serious implementation flaws have been fixed

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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

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Antti Syk  ri 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

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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  lt  n  k    console log psora k  n     Please also note that you cannot use pseudo random sequences when real entropy is needed

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Many people who need a seedable random-number generator in Javascript these days are using David Bau s seedrandom module

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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   amp  mask      var m z     987654321 - s   amp  mask       return function           m z    36969    m z  amp  65535     m z  gt  gt  gt  16    amp  mask        m w    18000    m w  amp  65535     m w  gt  gt  gt  16    amp  mask         var result     m z  lt  lt  16     m w  amp  65535    gt  gt  gt  0        result    4294967296        return result           var myRandomFunction   Math seed 1234   var randomNumber   myRandomFunction

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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  quot random quot  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 lt g  n  n r  l t  l r u g 1  for  y lt  n  n  2 t  2 r gt  gt  gt  1 return n r  t var o    i j function n t r  var e o    i typeof t if r amp  amp  quot object quot   i for e in t try o push n t e  r-1   catch n   return o length o  quot string quot   i t t  quot  0 quot    t 1  t  entropy  0  t      entropy  n S a   null  n function   try var n return s amp  amp  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 amp  amp 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 amp  amp  e S amp  amp v e u  n state function   return v u       r  c p  n t  n   e i  quot global quot 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 lt l  i e  e   for e 0 e lt l e   i e  i o h amp 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 amp e 1  r r l i h amp  i e  i o h amp 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  quot  quot  o 0 o lt e length  t h amp o  h amp  r  19 t h amp o   e charCodeAt o    return S t  function S n  return String fromCharCode apply 0 n  if j c random   a   quot object quot   typeof module amp  amp module exports  module exports n try s require  quot crypto quot   catch n    else quot function quot   typeof define amp  amp define amd define function   return n   c  quot seed quot  p  n   quot undefined quot   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

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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  Phil Troy

[javascript] Seeding the random number generator in Javascript

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