time-to-botec

Benchmark sampling in different programming languages
Log | Files | Refs | README

repl.txt (2833B)


      1 
      2 {{alias}}( [options] )
      3     Returns an iterator for generating pseudorandom integers on the interval
      4     `[1, 2147483646]`.
      5 
      6     If an environment supports Symbol.iterator, the returned iterator is
      7     iterable.
      8 
      9     This pseudorandom number generator (PRNG) is a linear congruential
     10     pseudorandom number generator (LCG) based on Park and Miller.
     11 
     12     The generator has a period of approximately `2.1e9`.
     13 
     14     An LCG is fast and uses little memory. On the other hand, because the
     15     generator is a simple LCG, the generator has recognized shortcomings. By
     16     today's PRNG standards, the generator's period is relatively short. More
     17     importantly, the "randomness quality" of the generator's output is lacking.
     18     These defects make the generator unsuitable, for example, in Monte Carlo
     19     simulations and in cryptographic applications.
     20 
     21     Parameters
     22     ----------
     23     options: Object (optional)
     24         Options.
     25 
     26     options.normalized: boolean (optional)
     27         Boolean indicating whether to return pseudorandom numbers on the
     28         interval `[0,1)`.
     29 
     30     options.seed: integer|ArrayLikeObject<integer> (optional)
     31         Pseudorandom number generator seed. The seed may be either a positive
     32         signed 32-bit integer or, for arbitrary length seeds, an array-like
     33         object containing positive signed 32-bit integers.
     34 
     35     options.state: Int32Array (optional)
     36         Pseudorandom number generator state. If provided, the `seed` option is
     37         ignored.
     38 
     39     options.copy: boolean (optional)
     40         Boolean indicating whether to copy a provided pseudorandom number
     41         generator state. Setting this option to `false` allows sharing state
     42         between two or more pseudorandom number generators. Setting this option
     43         to `true` ensures that a returned iterator has exclusive control over
     44         its internal state. Default: true.
     45 
     46     options.iter: integer (optional)
     47         Number of iterations.
     48 
     49     Returns
     50     -------
     51     iterator: Object
     52         Iterator.
     53 
     54     iterator.next(): Function
     55         Returns an iterator protocol-compliant object containing the next
     56         iterated value (if one exists) and a boolean flag indicating whether the
     57         iterator is finished.
     58 
     59     iterator.return( [value] ): Function
     60         Finishes an iterator and returns a provided value.
     61 
     62     iterator.seed: Int32Array
     63         Pseudorandom number generator seed.
     64 
     65     iterator.seedLength: integer
     66         Length of generator seed.
     67 
     68     iterator.state: Int32Array
     69         Generator state.
     70 
     71     iterator.stateLength: integer
     72         Length of generator state.
     73 
     74     iterator.byteLength: integer
     75         Size (in bytes) of generator state.
     76 
     77     Examples
     78     --------
     79     > var it = {{alias}}();
     80     > var r = it.next().value
     81     <number>
     82     > r = it.next().value
     83     <number>
     84 
     85     See Also
     86     --------
     87