MersenneTwisterFast

Full name Microsoft.VisualBasic.Math.MersenneTwisterFast Assembly Microsoft.VisualBasic.Math.Randomizer Members 22

MersenneTwisterFast:

A simulation quality fast random number generator (MT19937) with the same public methods as java.util.Random.

About the Mersenne Twister. This is a Java version of the C-program for MT19937: Integer version. next(32) generates one pseudorandom unsigned integer (32bit) which is uniformly distributed among 0 to 2^32-1 for each call. next(int bits) >>>'s by (32-bits) to get a value ranging between 0 and 2^bits-1 long inclusive; hope that's correct. setSeed(seed) set initial values to the working area of 624 words. For setSeed(seed), seed is any 32-bit integer except for 0.

Reference. 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.

Bug Fixes. This implementation implements the bug fixes made in Java 1.2's version of Random, which means it can be used with earlier versions of Java. See the JDK 1.2 java.util.Random documentation for further documentation on the random-number generation contracts made. Additionally, there's an undocumented bug in the JDK java.util.Random.nextBytes() method, which this code fixes.

Important Note. Just like java.util.Random, this generator accepts a long seed but doesn't use all of it. java.util.Random uses 48 bits. The Mersenne Twister instead uses 32 bits (int size). So it's best if your seed does not exceed the int range.

Sean Luke's web page

added shuffling method (Alexei Drummond)

added gamma RV method (Marc Suchard)

This is now package private - it should be accessed using the instance in Random

01 Syntax

Microsoft.VisualBasic.Math.MersenneTwisterFast

02 Methods

Name	Overloads	Summary
.ctor	2	Constructor using the time of day as default seed.
nextInt	2
permute	1	Returns a uniform random permutation of int objects in array
shuffle	2	Shuffles an array. Shuffles numberOfShuffles times
shuffled	1	Returns an array of shuffled indices of length l.
permuted	1	Returns a uniform random permutation of ints 0,...,l-1
nextGamma	1	Gamma Distribution - Acceptance Rejection combined with * Acceptance Complement * * * FUNCTION: - gds samples a random number from the standard * gamma distribution with para…
nextShort	1
nextChar	1
nextBoolean	1
nextByte	1
nextBytes	1
nextLong	1
nextDouble	1
nextGaussian	1
nextFloat	1

03 Properties

Name	Overloads	Summary
Seed	1	Initalize the pseudo random number generator.

04 Fields

Name	Overloads	Summary
serialVersionUID	1
DEFAULT_INSTANCE	1

05 Members

method .ctor #

#ctor

Constructor using the time of day as default seed.

method .ctor overload 2 #

#ctor(Int64)

Constructor using a given seed. Though you pass this seed in as a long, it's best to make sure it's actually an integer.

Parameters

Name	Type	Description
`seed`	`Int64`	generator starting number, often the time of day.

method nextInt overload 2 #

nextInt(Int32)

Returns an integer drawn uniformly from 0 to n-1. Suffice it to say, n must be > 0, or an IllegalArgumentException is raised.

method permute #

permute(Int32())

Returns a uniform random permutation of int objects in array

method shuffle overload 2 #

shuffle(Int32())

Shuffles an array.

method shuffle #

shuffle(Int32(), Int32)

Shuffles an array. Shuffles numberOfShuffles times

method shuffled #

shuffled(Int32)

Returns an array of shuffled indices of length l.

Parameters

Name	Type	Description
`l`	`Int32`	length of the array required.

method permuted #

permuted(Int32)

Returns a uniform random permutation of ints 0,...,l-1

Parameters

Name	Type	Description
`l`	`Int32`	length of the array required.

method nextGamma #

nextGamma(Double, Double)

Gamma Distribution - Acceptance Rejection combined with *

Acceptance Complement

FUNCTION: - gds samples a random number from the standard * gamma

distribution with parameter a > 0. Acceptance Rejection gs for a < 1 , Acceptance Complement gd for a >= 1 . REFERENCES: - J.H. Ahrens, U. Dieter (1974): Computer methods for sampling from gamma, beta, Poisson and binomial distributions, Computing 12, 223-246.

J.H. Ahrens, U. Dieter (1982): Generating gamma * variates by a

modified rejection technique, * Communications of the ACM 25, 47-54.

SUBPROGRAMS: - drand(seed) ... (0,1)-Uniform generator with *

unsigned long integer seed - NORMAL(seed) ... Normal generator N(0,1).

property Seed #

Seed

Initalize the pseudo random number generator. The Mersenne Twister only uses an integer for its seed; It's best that you don't pass in a long that's bigger than an int.

field serialVersionUID #

serialVersionUID

field DEFAULT_INSTANCE #

DEFAULT_INSTANCE

method nextInt #

nextInt()

method nextShort #

nextShort()

method nextChar #

nextChar()

method nextBoolean #

nextBoolean()

method nextByte #

nextByte()

method nextBytes #

nextBytes(SByte())

method nextLong #

nextLong()

method nextDouble #

nextDouble()

method nextGaussian #

nextGaussian()

method nextFloat #

nextFloat()