Seedable JavaScript random number generator

Question

The JavaScript Math random   function returns a random value between 0 and 1  automatically seeded based on the current time  similar to Java I believe    However  I don t think there s any way to set you own seed for it   How can I make a random number generator that I can provide my own seed value for  so that I can have it produce a repeatable sequence of  pseudo random numbers

User · Answer

I use a JavaScript port of the Mersenne Twister   https   gist github com 300494 It allows you to set the seed manually  Also  as mentioned in other answers  the Mersenne Twister is a really good PRNG

User · Answer

I use a JavaScript port of the Mersenne Twister   https   gist github com 300494 It allows you to set the seed manually  Also  as mentioned in other answers  the Mersenne Twister is a really good PRNG

User · Answer

OK  here s the solution I settled on   First you create a seed value using the  newseed    function  Then you pass the seed value to the  srandom    function  Lastly  the  srandom    function returns a pseudo random value between 0 and 1   The crucial bit is that the seed value is stored inside an array  If it were simply an integer or float  the value would get overwritten each time the function were called  since the values of integers  floats  strings and so forth are stored directly in the stack versus just the pointers as in the case of arrays and other objects  Thus  it s possible for the value of the seed to remain persistent   Finally  it is possible to define the  srandom    function such that it is a method of the  Math  object  but I ll leave that up to you to figure out      Good luck   JavaScript      Global variables used for the seeded random functions  below  var seedobja   1103515245 var seedobjc   12345 var seedobjm   4294967295   0x100000000     Creates a new seed for seeded functions such as srandom    function newseed seednum        return  seednum        Works like Math random    except you provide your own seed as the first argument  function srandom seedobj        seedobj 0     seedobj 0    seedobja   seedobjc    seedobjm     return seedobj 0     seedobjm - 1        Store some test values in variables  var my seed value   newseed 230951  var my random value 1   srandom my seed value  var my random value 2   srandom my seed value  var my random value 3   srandom my seed value      Print the values to console  Replace  WScript Echo    with  alert    if inside a Web browser  WScript Echo my random value 1  WScript Echo my random value 2  WScript Echo my random value 3    Lua 4  my personal target environment    -- Global variables used for the seeded random functions  below  seedobja   1103515 245 seedobjc   12345 seedobjm   4294967 295 --0x100000000  -- Creates a new seed for seeded functions such as srandom    function newseed seednum      return  seednum  end  -- Works like random    except you provide your own seed as the first argument  function srandom seedobj      seedobj 1    mod seedobj 1    seedobja   seedobjc  seedobjm      return seedobj 1     seedobjm - 1  end  -- Store some test values in variables  my seed value   newseed 230951  my random value 1   srandom my seed value  my random value 2   srandom my seed value  my random value 3   srandom my seed value   -- Print the values to console  print my random value 1  print my random value 2  print my random value 3

User · Answer

Note  This code was originally included in the question above   In the interests of keeping the question short and focused  I ve moved it to this Community Wiki answer    I found this code kicking around and it appears to work fine for getting a random number and then using the seed afterward but I m not quite sure how the logic works  e g  where the 2345678901  48271  amp  2147483647 numbers came from    function nextRandomNumber      var hi   this seed   this Q    var lo   this seed   this Q    var test   this A   lo - this R   hi    if test  gt  0       this seed   test      else       this seed   test   this M        return  this seed   this oneOverM      function RandomNumberGenerator      var d   new Date      this seed   2345678901    d getSeconds     0xFFFFFF     d getMinutes     0xFFFF     this A   48271    this M   2147483647    this Q   this M   this A    this R   this M   this A    this oneOverM   1 0   this M    this next   nextRandomNumber    return this     function createRandomNumber Min  Max     var rand   new RandomNumberGenerator      return Math round  Max-Min    rand next     Min        Thus I can now do  var letters     a   b   c   d   e   f   g   h   i   j   k   l   m   n   o   p   q   r   s   t   u   v   w   x   y   z    var numbers     1   2   3   4   5   6   7   8   9   10    var colors     red   orange   yellow   green   blue   indigo   violet    var first   letters createRandomNumber 0  letters length    var second   numbers createRandomNumber 0  numbers length    var third   colors createRandomNumber 0  colors length     alert  Today s show was brought to you by the letter      first      the number     second      and the color     third               If I could pass my own seed into the createRandomNumber min  max  seed     function then I could reproduce a random output later if desired

User · Answer

The code you listed kind of looks like a Lehmer RNG  If this is the case  then 2147483647 is the largest 32-bit signed integer  2147483647 is the largest 32-bit prime  and 48271 is a full-period multiplier that is used to generate the numbers   If this is true  you could modify RandomNumberGenerator to take in an extra parameter seed  and then set this seed to seed  but you d have to be careful to make sure the seed would result in a good distribution of random numbers  Lehmer can be weird like that  -- but most seeds will be fine

User · Answer

The following is a PRNG that may be fed a custom seed  Calling SeedRandom will return a random generator function  SeedRandom can be called with no arguments in order to seed the returned random function with the current time  or it can be called with either 1 or 2 non-negative inters as arguments in order to seed it with those integers  Due to float point accuracy seeding with only 1 value will only allow the generator to be initiated to one of 2 53 different states   The returned random generator function takes 1 integer argument named limit  the limit must be in the range 1 to 4294965886  the function will return a number in the range 0 to limit-1   function SeedRandom state1 state2       var mod1 4294967087     var mul1 65539     var mod2 4294965887     var mul2 65537     if typeof state1   number            state1  new Date             if typeof state2   number            state2 state1           state1 state1  mod1-1  1     state2 state2  mod2-1  1     function random limit           state1  state1 mul1  mod1         state2  state2 mul2  mod2         if state1 lt limit  amp  amp  state2 lt limit  amp  amp  state1 lt mod1 limit  amp  amp  state2 lt mod2 limit               return random limit                    return  state1 state2  limit           return random     Example use   var generator1 SeedRandom     Seed with current time var randomVariable generator1 7    Generate one of the numbers  0 1 2 3 4 5 6  var generator2 SeedRandom 42    Seed with a specific seed var fixedVariable generator2 7    First value of this generator will always be                                   1 because of the specific seed    This generator exhibit the following properties    It has approximately 2 64 different possible inner states  It has a period of approximately 2 63  plenty more than anyone will ever realistically need in a JavaScript program  Due to the mod values being primes there is no simple pattern in the output  no matter the chosen limit  This is unlike some simpler PRNGs that exhibit some quite systematic patterns  It discards some results in order to get a perfect distribution no matter the limit  It is relatively slow  runs around 10 000 000 times per second on my machine

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If you want to be able to specify the seed  you just need to replace the calls to getSeconds   and getMinutes     You could pass in an int and use half of it mod 60 for the seconds value and the other half modulo 60 to give you the other part   That being said  this method looks like garbage   Doing proper random number generation is very hard   The obvious problem with this is that the random number seed is based on seconds and minutes   To guess the seed and recreate your stream of random numbers only requires trying 3600 different second and minute combinations   It also means that there are only 3600 different possible seeds   This is correctable  but I d be suspicious of this RNG from the start   If you want to use a better RNG  try the Mersenne Twister   It is a well tested and fairly robust RNG with a huge orbit and excellent performance   EDIT  I really should be correct and refer to this as a Pseudo Random Number Generator or PRNG       Anyone who uses arithmetic methods to produce random numbers is in a state of sin      nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp --- John von Neumann

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The code you listed kind of looks like a Lehmer RNG  If this is the case  then 2147483647 is the largest 32-bit signed integer  2147483647 is the largest 32-bit prime  and 48271 is a full-period multiplier that is used to generate the numbers   If this is true  you could modify RandomNumberGenerator to take in an extra parameter seed  and then set this seed to seed  but you d have to be careful to make sure the seed would result in a good distribution of random numbers  Lehmer can be weird like that  -- but most seeds will be fine

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If you don t need the seeding capability just use Math random   and build helper functions around it  eg  randRange start  end     I m not sure what RNG you re using  but it s best to know and document it so you re aware of its characteristics and limitations   Like Starkii said  Mersenne Twister is a good PRNG  but it isn t easy to implement  If you want to do it yourself try implementing a LCG - it s very easy  has decent randomness qualities  not as good as Mersenne Twister   and you can use some of the popular constants   EDIT  consider the great options at this answer for short seedable RNG implementations  including an LCG option    x000D   x000D  function RNG seed    x000D       LCG using GCC s constants x000D    this m   0x80000000     2  31  x000D    this a   1103515245  x000D    this c   12345  x000D   x000D    this state   seed   seed   Math floor Math random      this m - 1    x000D    x000D  RNG prototype nextInt   function     x000D    this state    this a   this state   this c    this m  x000D    return this state  x000D    x000D  RNG prototype nextFloat   function     x000D       returns in range  0 1  x000D    return this nextInt      this m - 1   x000D    x000D  RNG prototype nextRange   function start  end    x000D       returns in range  start  end   including start  excluding end x000D       can t modulu nextInt because of weak randomness in lower bits x000D    var rangeSize   end - start  x000D    var randomUnder1   this nextInt     this m  x000D    return start   Math floor randomUnder1   rangeSize   x000D    x000D  RNG prototype choice   function array    x000D    return array this nextRange 0  array length    x000D    x000D   x000D  var rng   new RNG 20   x000D  for  var i   0  i  lt  10  i    x000D    console log rng nextRange 10  50    x000D   x000D  var digits     0    1    2    3    4    5    6    7    8    9    x000D  for  var i   0  i  lt  10  i    x000D    console log rng choice digits    x000D   x000D   x000D

User · Answer

If you want to be able to specify the seed  you just need to replace the calls to getSeconds   and getMinutes     You could pass in an int and use half of it mod 60 for the seconds value and the other half modulo 60 to give you the other part   That being said  this method looks like garbage   Doing proper random number generation is very hard   The obvious problem with this is that the random number seed is based on seconds and minutes   To guess the seed and recreate your stream of random numbers only requires trying 3600 different second and minute combinations   It also means that there are only 3600 different possible seeds   This is correctable  but I d be suspicious of this RNG from the start   If you want to use a better RNG  try the Mersenne Twister   It is a well tested and fairly robust RNG with a huge orbit and excellent performance   EDIT  I really should be correct and refer to this as a Pseudo Random Number Generator or PRNG       Anyone who uses arithmetic methods to produce random numbers is in a state of sin      nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp --- John von Neumann

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OK  here s the solution I settled on   First you create a seed value using the  newseed    function  Then you pass the seed value to the  srandom    function  Lastly  the  srandom    function returns a pseudo random value between 0 and 1   The crucial bit is that the seed value is stored inside an array  If it were simply an integer or float  the value would get overwritten each time the function were called  since the values of integers  floats  strings and so forth are stored directly in the stack versus just the pointers as in the case of arrays and other objects  Thus  it s possible for the value of the seed to remain persistent   Finally  it is possible to define the  srandom    function such that it is a method of the  Math  object  but I ll leave that up to you to figure out      Good luck   JavaScript      Global variables used for the seeded random functions  below  var seedobja   1103515245 var seedobjc   12345 var seedobjm   4294967295   0x100000000     Creates a new seed for seeded functions such as srandom    function newseed seednum        return  seednum        Works like Math random    except you provide your own seed as the first argument  function srandom seedobj        seedobj 0     seedobj 0    seedobja   seedobjc    seedobjm     return seedobj 0     seedobjm - 1        Store some test values in variables  var my seed value   newseed 230951  var my random value 1   srandom my seed value  var my random value 2   srandom my seed value  var my random value 3   srandom my seed value      Print the values to console  Replace  WScript Echo    with  alert    if inside a Web browser  WScript Echo my random value 1  WScript Echo my random value 2  WScript Echo my random value 3    Lua 4  my personal target environment    -- Global variables used for the seeded random functions  below  seedobja   1103515 245 seedobjc   12345 seedobjm   4294967 295 --0x100000000  -- Creates a new seed for seeded functions such as srandom    function newseed seednum      return  seednum  end  -- Works like random    except you provide your own seed as the first argument  function srandom seedobj      seedobj 1    mod seedobj 1    seedobja   seedobjc  seedobjm      return seedobj 1     seedobjm - 1  end  -- Store some test values in variables  my seed value   newseed 230951  my random value 1   srandom my seed value  my random value 2   srandom my seed value  my random value 3   srandom my seed value   -- Print the values to console  print my random value 1  print my random value 2  print my random value 3

User · Answer

If you want to be able to specify the seed  you just need to replace the calls to getSeconds   and getMinutes     You could pass in an int and use half of it mod 60 for the seconds value and the other half modulo 60 to give you the other part   That being said  this method looks like garbage   Doing proper random number generation is very hard   The obvious problem with this is that the random number seed is based on seconds and minutes   To guess the seed and recreate your stream of random numbers only requires trying 3600 different second and minute combinations   It also means that there are only 3600 different possible seeds   This is correctable  but I d be suspicious of this RNG from the start   If you want to use a better RNG  try the Mersenne Twister   It is a well tested and fairly robust RNG with a huge orbit and excellent performance   EDIT  I really should be correct and refer to this as a Pseudo Random Number Generator or PRNG       Anyone who uses arithmetic methods to produce random numbers is in a state of sin      nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp --- John von Neumann

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The code you listed kind of looks like a Lehmer RNG  If this is the case  then 2147483647 is the largest 32-bit signed integer  2147483647 is the largest 32-bit prime  and 48271 is a full-period multiplier that is used to generate the numbers   If this is true  you could modify RandomNumberGenerator to take in an extra parameter seed  and then set this seed to seed  but you d have to be careful to make sure the seed would result in a good distribution of random numbers  Lehmer can be weird like that  -- but most seeds will be fine

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If you program in Typescript  I adapted the Mersenne Twister implementation that was brought in Christoph Henkelmann s answer to this thread as a typescript class          copied almost directly from Mersenne Twister implementation found in https   gist github com banksean 300494    all rights reserved to him      export class Random       static N   624      static M   397      static MATRIX A   0x9908b0df         constant vector a        static UPPER MASK   0x80000000         most significant w-r bits        static LOWER MASK   0x7fffffff         least significant r bits         mt   new Array Random N          the array for the state vector        mti   Random N   1         mti  N 1 means mt N  is not initialized         constructor seed number   null            if  seed    null                seed   new Date   getTime                       this init genrand seed              private init genrand s number            this mt 0    s  gt  gt  gt  0          for  this mti   1  this mti  lt  Random N  this mti                  var s   this mt this mti - 1     this mt this mti - 1   gt  gt  gt  30               this mt this mti         s  amp  0xffff0000   gt  gt  gt  16    1812433253   lt  lt  16     s  amp  0x0000ffff    1812433253                    this mti                 See Knuth TAOCP Vol2  3rd Ed  P 106 for multiplier                    In the previous versions  MSBs of the seed affect                     only MSBs of the array mt                                             2002 01 09 modified by Makoto Matsumoto                            this mt this mti   gt  gt  gt   0                 for  gt 32 bit machines                                    generates a random number on  0 0xffffffff -interval         private             private  nextInt32   number           var y number          var mag01   new Array 0x0  Random MATRIX A              mag01 x    x   MATRIX A  for x 0 1             if  this mti  gt   Random N       generate N words at one time                var kk number               if  this mti    Random N   1       if init genrand   has not been called                     this init genrand 5489                  a default initial seed is used                 for  kk   0  kk  lt  Random N - Random M  kk                      y    this mt kk   amp  Random UPPER MASK     this mt kk   1   amp  Random LOWER MASK                   this mt kk    this mt kk   Random M     y  gt  gt  gt  1    mag01 y  amp  0x1                             for    kk  lt  Random N - 1  kk                      y    this mt kk   amp  Random UPPER MASK     this mt kk   1   amp  Random LOWER MASK                   this mt kk    this mt kk    Random M - Random N      y  gt  gt  gt  1    mag01 y  amp  0x1                             y    this mt Random N - 1   amp  Random UPPER MASK     this mt 0   amp  Random LOWER MASK               this mt Random N - 1    this mt Random M - 1     y  gt  gt  gt  1    mag01 y  amp  0x1                this mti   0                     y   this mt this mti                 Tempering            y     y  gt  gt  gt  11           y     y  lt  lt  7   amp  0x9d2c5680          y     y  lt  lt  15   amp  0xefc60000          y     y  gt  gt  gt  18            return y  gt  gt  gt  0                        generates an int32 pseudo random number         param range  an optional  from  to  range  if not specified the result will be in range  0 0xffffffff          return  number              nextInt32 range  number  number    null  number           var result   this  nextInt32            if  range    null                return result                     return  result    range 1  - range 0      range 0                         generates a random number on  0 0x7fffffff -interval             nextInt31   number           return  this  nextInt32    gt  gt  gt  1                         generates a random number on  0 1 -real-interval             nextNumber   number           return this  nextInt32      1 0   4294967295 0                         generates a random number on  0 1  with 53-bit resolution             nextNumber53   number           var a   this  nextInt32    gt  gt  gt  5  b   this  nextInt32    gt  gt  gt  6          return  a   67108864 0   b     1 0   9007199254740992 0             you can than use it as follows   var random   new Random 132   random nextInt32      return a pseudo random int32 number random nextInt32  10 20      return a pseudo random int in range  10 20  random nextNumber      return a a pseudo random number in range  0 1    check the source for more methods

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If you program in Typescript  I adapted the Mersenne Twister implementation that was brought in Christoph Henkelmann s answer to this thread as a typescript class          copied almost directly from Mersenne Twister implementation found in https   gist github com banksean 300494    all rights reserved to him      export class Random       static N   624      static M   397      static MATRIX A   0x9908b0df         constant vector a        static UPPER MASK   0x80000000         most significant w-r bits        static LOWER MASK   0x7fffffff         least significant r bits         mt   new Array Random N          the array for the state vector        mti   Random N   1         mti  N 1 means mt N  is not initialized         constructor seed number   null            if  seed    null                seed   new Date   getTime                       this init genrand seed              private init genrand s number            this mt 0    s  gt  gt  gt  0          for  this mti   1  this mti  lt  Random N  this mti                  var s   this mt this mti - 1     this mt this mti - 1   gt  gt  gt  30               this mt this mti         s  amp  0xffff0000   gt  gt  gt  16    1812433253   lt  lt  16     s  amp  0x0000ffff    1812433253                    this mti                 See Knuth TAOCP Vol2  3rd Ed  P 106 for multiplier                    In the previous versions  MSBs of the seed affect                     only MSBs of the array mt                                             2002 01 09 modified by Makoto Matsumoto                            this mt this mti   gt  gt  gt   0                 for  gt 32 bit machines                                    generates a random number on  0 0xffffffff -interval         private             private  nextInt32   number           var y number          var mag01   new Array 0x0  Random MATRIX A              mag01 x    x   MATRIX A  for x 0 1             if  this mti  gt   Random N       generate N words at one time                var kk number               if  this mti    Random N   1       if init genrand   has not been called                     this init genrand 5489                  a default initial seed is used                 for  kk   0  kk  lt  Random N - Random M  kk                      y    this mt kk   amp  Random UPPER MASK     this mt kk   1   amp  Random LOWER MASK                   this mt kk    this mt kk   Random M     y  gt  gt  gt  1    mag01 y  amp  0x1                             for    kk  lt  Random N - 1  kk                      y    this mt kk   amp  Random UPPER MASK     this mt kk   1   amp  Random LOWER MASK                   this mt kk    this mt kk    Random M - Random N      y  gt  gt  gt  1    mag01 y  amp  0x1                             y    this mt Random N - 1   amp  Random UPPER MASK     this mt 0   amp  Random LOWER MASK               this mt Random N - 1    this mt Random M - 1     y  gt  gt  gt  1    mag01 y  amp  0x1                this mti   0                     y   this mt this mti                 Tempering            y     y  gt  gt  gt  11           y     y  lt  lt  7   amp  0x9d2c5680          y     y  lt  lt  15   amp  0xefc60000          y     y  gt  gt  gt  18            return y  gt  gt  gt  0                        generates an int32 pseudo random number         param range  an optional  from  to  range  if not specified the result will be in range  0 0xffffffff          return  number              nextInt32 range  number  number    null  number           var result   this  nextInt32            if  range    null                return result                     return  result    range 1  - range 0      range 0                         generates a random number on  0 0x7fffffff -interval             nextInt31   number           return  this  nextInt32    gt  gt  gt  1                         generates a random number on  0 1 -real-interval             nextNumber   number           return this  nextInt32      1 0   4294967295 0                         generates a random number on  0 1  with 53-bit resolution             nextNumber53   number           var a   this  nextInt32    gt  gt  gt  5  b   this  nextInt32    gt  gt  gt  6          return  a   67108864 0   b     1 0   9007199254740992 0             you can than use it as follows   var random   new Random 132   random nextInt32      return a pseudo random int32 number random nextInt32  10 20      return a pseudo random int in range  10 20  random nextNumber      return a a pseudo random number in range  0 1    check the source for more methods

User · Answer

If you want to be able to specify the seed  you just need to replace the calls to getSeconds   and getMinutes     You could pass in an int and use half of it mod 60 for the seconds value and the other half modulo 60 to give you the other part   That being said  this method looks like garbage   Doing proper random number generation is very hard   The obvious problem with this is that the random number seed is based on seconds and minutes   To guess the seed and recreate your stream of random numbers only requires trying 3600 different second and minute combinations   It also means that there are only 3600 different possible seeds   This is correctable  but I d be suspicious of this RNG from the start   If you want to use a better RNG  try the Mersenne Twister   It is a well tested and fairly robust RNG with a huge orbit and excellent performance   EDIT  I really should be correct and refer to this as a Pseudo Random Number Generator or PRNG       Anyone who uses arithmetic methods to produce random numbers is in a state of sin      nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp  nbsp --- John von Neumann

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One option is http   davidbau com seedrandom which is a seedable RC4-based Math random   drop-in replacement with nice properties

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The code you listed kind of looks like a Lehmer RNG  If this is the case  then 2147483647 is the largest 32-bit signed integer  2147483647 is the largest 32-bit prime  and 48271 is a full-period multiplier that is used to generate the numbers   If this is true  you could modify RandomNumberGenerator to take in an extra parameter seed  and then set this seed to seed  but you d have to be careful to make sure the seed would result in a good distribution of random numbers  Lehmer can be weird like that  -- but most seeds will be fine

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If you don t need the seeding capability just use Math random   and build helper functions around it  eg  randRange start  end     I m not sure what RNG you re using  but it s best to know and document it so you re aware of its characteristics and limitations   Like Starkii said  Mersenne Twister is a good PRNG  but it isn t easy to implement  If you want to do it yourself try implementing a LCG - it s very easy  has decent randomness qualities  not as good as Mersenne Twister   and you can use some of the popular constants   EDIT  consider the great options at this answer for short seedable RNG implementations  including an LCG option    x000D   x000D  function RNG seed    x000D       LCG using GCC s constants x000D    this m   0x80000000     2  31  x000D    this a   1103515245  x000D    this c   12345  x000D   x000D    this state   seed   seed   Math floor Math random      this m - 1    x000D    x000D  RNG prototype nextInt   function     x000D    this state    this a   this state   this c    this m  x000D    return this state  x000D    x000D  RNG prototype nextFloat   function     x000D       returns in range  0 1  x000D    return this nextInt      this m - 1   x000D    x000D  RNG prototype nextRange   function start  end    x000D       returns in range  start  end   including start  excluding end x000D       can t modulu nextInt because of weak randomness in lower bits x000D    var rangeSize   end - start  x000D    var randomUnder1   this nextInt     this m  x000D    return start   Math floor randomUnder1   rangeSize   x000D    x000D  RNG prototype choice   function array    x000D    return array this nextRange 0  array length    x000D    x000D   x000D  var rng   new RNG 20   x000D  for  var i   0  i  lt  10  i    x000D    console log rng nextRange 10  50    x000D   x000D  var digits     0    1    2    3    4    5    6    7    8    9    x000D  for  var i   0  i  lt  10  i    x000D    console log rng choice digits    x000D   x000D   x000D

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One option is http   davidbau com seedrandom which is a seedable RC4-based Math random   drop-in replacement with nice properties

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Note  This code was originally included in the question above   In the interests of keeping the question short and focused  I ve moved it to this Community Wiki answer    I found this code kicking around and it appears to work fine for getting a random number and then using the seed afterward but I m not quite sure how the logic works  e g  where the 2345678901  48271  amp  2147483647 numbers came from    function nextRandomNumber      var hi   this seed   this Q    var lo   this seed   this Q    var test   this A   lo - this R   hi    if test  gt  0       this seed   test      else       this seed   test   this M        return  this seed   this oneOverM      function RandomNumberGenerator      var d   new Date      this seed   2345678901    d getSeconds     0xFFFFFF     d getMinutes     0xFFFF     this A   48271    this M   2147483647    this Q   this M   this A    this R   this M   this A    this oneOverM   1 0   this M    this next   nextRandomNumber    return this     function createRandomNumber Min  Max     var rand   new RandomNumberGenerator      return Math round  Max-Min    rand next     Min        Thus I can now do  var letters     a   b   c   d   e   f   g   h   i   j   k   l   m   n   o   p   q   r   s   t   u   v   w   x   y   z    var numbers     1   2   3   4   5   6   7   8   9   10    var colors     red   orange   yellow   green   blue   indigo   violet    var first   letters createRandomNumber 0  letters length    var second   numbers createRandomNumber 0  numbers length    var third   colors createRandomNumber 0  colors length     alert  Today s show was brought to you by the letter      first      the number     second      and the color     third               If I could pass my own seed into the createRandomNumber min  max  seed     function then I could reproduce a random output later if desired

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If you don t need the seeding capability just use Math random   and build helper functions around it  eg  randRange start  end     I m not sure what RNG you re using  but it s best to know and document it so you re aware of its characteristics and limitations   Like Starkii said  Mersenne Twister is a good PRNG  but it isn t easy to implement  If you want to do it yourself try implementing a LCG - it s very easy  has decent randomness qualities  not as good as Mersenne Twister   and you can use some of the popular constants   EDIT  consider the great options at this answer for short seedable RNG implementations  including an LCG option    x000D   x000D  function RNG seed    x000D       LCG using GCC s constants x000D    this m   0x80000000     2  31  x000D    this a   1103515245  x000D    this c   12345  x000D   x000D    this state   seed   seed   Math floor Math random      this m - 1    x000D    x000D  RNG prototype nextInt   function     x000D    this state    this a   this state   this c    this m  x000D    return this state  x000D    x000D  RNG prototype nextFloat   function     x000D       returns in range  0 1  x000D    return this nextInt      this m - 1   x000D    x000D  RNG prototype nextRange   function start  end    x000D       returns in range  start  end   including start  excluding end x000D       can t modulu nextInt because of weak randomness in lower bits x000D    var rangeSize   end - start  x000D    var randomUnder1   this nextInt     this m  x000D    return start   Math floor randomUnder1   rangeSize   x000D    x000D  RNG prototype choice   function array    x000D    return array this nextRange 0  array length    x000D    x000D   x000D  var rng   new RNG 20   x000D  for  var i   0  i  lt  10  i    x000D    console log rng nextRange 10  50    x000D   x000D  var digits     0    1    2    3    4    5    6    7    8    9    x000D  for  var i   0  i  lt  10  i    x000D    console log rng choice digits    x000D   x000D   x000D

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If you don t need the seeding capability just use Math random   and build helper functions around it  eg  randRange start  end     I m not sure what RNG you re using  but it s best to know and document it so you re aware of its characteristics and limitations   Like Starkii said  Mersenne Twister is a good PRNG  but it isn t easy to implement  If you want to do it yourself try implementing a LCG - it s very easy  has decent randomness qualities  not as good as Mersenne Twister   and you can use some of the popular constants   EDIT  consider the great options at this answer for short seedable RNG implementations  including an LCG option    x000D   x000D  function RNG seed    x000D       LCG using GCC s constants x000D    this m   0x80000000     2  31  x000D    this a   1103515245  x000D    this c   12345  x000D   x000D    this state   seed   seed   Math floor Math random      this m - 1    x000D    x000D  RNG prototype nextInt   function     x000D    this state    this a   this state   this c    this m  x000D    return this state  x000D    x000D  RNG prototype nextFloat   function     x000D       returns in range  0 1  x000D    return this nextInt      this m - 1   x000D    x000D  RNG prototype nextRange   function start  end    x000D       returns in range  start  end   including start  excluding end x000D       can t modulu nextInt because of weak randomness in lower bits x000D    var rangeSize   end - start  x000D    var randomUnder1   this nextInt     this m  x000D    return start   Math floor randomUnder1   rangeSize   x000D    x000D  RNG prototype choice   function array    x000D    return array this nextRange 0  array length    x000D    x000D   x000D  var rng   new RNG 20   x000D  for  var i   0  i  lt  10  i    x000D    console log rng nextRange 10  50    x000D   x000D  var digits     0    1    2    3    4    5    6    7    8    9    x000D  for  var i   0  i  lt  10  i    x000D    console log rng choice digits    x000D   x000D   x000D

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The following is a PRNG that may be fed a custom seed  Calling SeedRandom will return a random generator function  SeedRandom can be called with no arguments in order to seed the returned random function with the current time  or it can be called with either 1 or 2 non-negative inters as arguments in order to seed it with those integers  Due to float point accuracy seeding with only 1 value will only allow the generator to be initiated to one of 2 53 different states   The returned random generator function takes 1 integer argument named limit  the limit must be in the range 1 to 4294965886  the function will return a number in the range 0 to limit-1   function SeedRandom state1 state2       var mod1 4294967087     var mul1 65539     var mod2 4294965887     var mul2 65537     if typeof state1   number            state1  new Date             if typeof state2   number            state2 state1           state1 state1  mod1-1  1     state2 state2  mod2-1  1     function random limit           state1  state1 mul1  mod1         state2  state2 mul2  mod2         if state1 lt limit  amp  amp  state2 lt limit  amp  amp  state1 lt mod1 limit  amp  amp  state2 lt mod2 limit               return random limit                    return  state1 state2  limit           return random     Example use   var generator1 SeedRandom     Seed with current time var randomVariable generator1 7    Generate one of the numbers  0 1 2 3 4 5 6  var generator2 SeedRandom 42    Seed with a specific seed var fixedVariable generator2 7    First value of this generator will always be                                   1 because of the specific seed    This generator exhibit the following properties    It has approximately 2 64 different possible inner states  It has a period of approximately 2 63  plenty more than anyone will ever realistically need in a JavaScript program  Due to the mod values being primes there is no simple pattern in the output  no matter the chosen limit  This is unlike some simpler PRNGs that exhibit some quite systematic patterns  It discards some results in order to get a perfect distribution no matter the limit  It is relatively slow  runs around 10 000 000 times per second on my machine

[javascript] Seedable JavaScript random number generator

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