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## cern.jet.random.engine
Class MersenneTwister

    java.lang.Object
      cern.colt.PersistentObject
          cern.jet.random.engine.RandomEngine
              cern.jet.random.engine.MersenneTwister

All Implemented Interfaces:
  Cloneable, DoubleFunction, IntFunction, Serializable

Direct Known Subclasses:
  MersenneTwister64

public class MersenneTwister
extends RandomEngine

MersenneTwister (MT19937) is one of the strongest uniform pseudo-random number generators known so far; at the same time it is quick. Produces uniformly distributed `int`'s and `long`'s in the closed intervals `[Integer.MIN_VALUE,Integer.MAX_VALUE]` and `[Long.MIN_VALUE,Long.MAX_VALUE]`, respectively, as well as `float`'s and `double`'s in the open unit intervals `(0.0f,1.0f)` and `(0.0,1.0)`, respectively. The seed can be any 32-bit integer except `0`. Shawn J. Cokus commented that perhaps the seed should preferably be odd.

Quality: MersenneTwister is designed to pass the k-distribution test. It has an astronomically large period of 219937-1 (=106001) and 623-dimensional equidistribution up to 32-bit accuracy. It passes many stringent statistical tests, including the diehard test of G. Marsaglia and the load test of P. Hellekalek and S. Wegenkittl.

Performance: Its speed is comparable to other modern generators (in particular, as fast as `java.util.Random.nextFloat()`). 2.5 million calls to `raw()` per second (Pentium Pro 200 Mhz, JDK 1.2, NT). Be aware, however, that there is a non-negligible amount of overhead required to initialize the data structures used by a MersenneTwister. Code like

            double sum = 0.0;
            for (int i=0; i<100000; ++i) {
               RandomElement twister = new MersenneTwister(new java.util.Date());
               sum += twister.raw();
            }

will be wildly inefficient. Consider using

            double sum = 0.0;
            RandomElement twister = new MersenneTwister(new java.util.Date());
            for (int i=0; i<100000; ++i) {
               sum += twister.raw();
            }

instead. This allows the cost of constructing the MersenneTwister object to be borne only once, rather than once for each iteration in the loop.

Implementation: After M. Matsumoto and T. Nishimura, "Mersenne Twister: A 623-Dimensionally Equidistributed Uniform Pseudo-Random Number Generator", ACM Transactions on Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3--30.

More info on Masumoto's homepage.
More info on Pseudo-random number generators is on the Web.
Yet some more info.

The correctness of this implementation has been verified against the published output sequence mt19937-2.out of the C-implementation mt19937-2.c. (Call `test(1000)` to print the sequence).

Note that this implementation is not synchronized.

Details: MersenneTwister is designed with consideration of the flaws of various existing generators in mind. It is an improved version of TT800, a very successful generator. MersenneTwister is based on linear recurrences modulo 2. Such generators are very fast, have extremely long periods, and appear quite robust. MersenneTwister produces 32-bit numbers, and every `k`-dimensional vector of such numbers appears the same number of times as `k` successive values over the period length, for each `k <= 623` (except for the zero vector, which appears one time less). If one looks at only the first `n <= 16` bits of each number, then the property holds for even larger `k`, as shown in the following table (taken from the publication cited above):

n | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 .. 16 | 17 .. 32
k | 19937 | 9968 | 6240 | 4984 | 3738 | 3115 | 2493 | 2492 | 1869 | 1869 | 1248 | 1246 | 623

MersenneTwister generates random numbers in batches of 624 numbers at a time, so the caching and pipelining of modern systems is exploited. The generator is implemented to generate the output by using the fastest arithmetic operations only: 32-bit additions and bit operations (no division, no multiplication, no mod). These operations generate sequences of 32 random bits (`int`'s). `long`'s are formed by concatenating two 32 bit `int`'s. `float`'s are formed by dividing the interval `[0.0,1.0]` into 232 sub intervals, then randomly choosing one subinterval. `double`'s are formed by dividing the interval `[0.0,1.0]` into 264 sub intervals, then randomly choosing one subinterval.

Version:
  1.0, 09/24/99
See Also:
  `Random`, Serialized Form

Field Summary
`static int` | `DEFAULT_SEED`

Fields inherited from class cern.colt.PersistentObject
`serialVersionUID`

Constructor Summary
`MersenneTwister()` Constructs and returns a random number generator with a default seed, which is a constant.
`MersenneTwister(Date d)` Constructs and returns a random number generator seeded with the given date.
`MersenneTwister(int seed)` Constructs and returns a random number generator with the given seed.

Method Summary
`Object` | `clone()` Returns a copy of the receiver; the copy will produce identical sequences.
`int` | `nextInt()` Returns a 32 bit uniformly distributed random number in the closed interval `[Integer.MIN_VALUE,Integer.MAX_VALUE]` (including `Integer.MIN_VALUE` and `Integer.MAX_VALUE`).

Methods inherited from class cern.jet.random.engine.RandomEngine
`apply, apply, makeDefault, nextDouble, nextFloat, nextLong, raw`

Methods inherited from class java.lang.Object
`equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Field Detail

### DEFAULT_SEED

    public static final int DEFAULT_SEED

See Also:
  Constant Field Values

Constructor Detail

### MersenneTwister

    public MersenneTwister()

  Constructs and returns a random number generator with a default seed, which is a constant. Thus using this constructor will yield generators that always produce exactly the same sequence. This method is mainly intended to ease testing and debugging.

### MersenneTwister

    public MersenneTwister(int seed)

  Constructs and returns a random number generator with the given seed.

### MersenneTwister

    public MersenneTwister(Date d)

  Constructs and returns a random number generator seeded with the given date.

Parameters:
  `d` - typically `new java.util.Date()`

Method Detail

### clone

    public Object clone()

  Returns a copy of the receiver; the copy will produce identical sequences. After this call has returned, the copy and the receiver have equal but separate state.

  Overrides:
    `clone` in class `PersistentObject`
  Returns:
    a copy of the receiver.

### nextInt

    public int nextInt()

  Returns a 32 bit uniformly distributed random number in the closed interval `[Integer.MIN_VALUE,Integer.MAX_VALUE]` (including `Integer.MIN_VALUE` and `Integer.MAX_VALUE`).

  Specified by:
    `nextInt` in class `RandomEngine`

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