squidpony.squidmath

Interface RandomnessSource

All Superinterfaces:

java.io.Serializable

All Known Subinterfaces:

FlawedRandomness, IRNG, IStatefulRNG, SkippingRandomness, StatefulRandomness

All Known Implementing Classes:

AbstractRNG, BasicRandom32, BasicRandom64, ChaosRNG, CriticalRNG, DeckRNG, DharmaRNG, DistinctRNG, DistributedRNG, DiverRNG, EditRNG, FlawedRandomness.AddRotate, FlawedRandomness.BigCounter, FourWheelRNG, GearRNG, GoatRNG, GWTRNG, IsaacRNG, Lathe32RNG, LFSR, LightRNG, LinnormRNG, LongPeriodRNG, MersenneTwister, MiniMover64RNG, MizuchiRNG, MoonwalkRNG, Mover32RNG, Mover64RNG, NLFSR, OrbitRNG, Oriole32RNG, PermutedRNG, PintRNG, PulleyRNG, RNG, RomuTrioRNG, SilkRNG, SobolQRNG, SpecifiedRandomness, Starfish32RNG, StatefulRNG, StrangerRNG, TangleRNG, ThrustAltRNG, TricycleRNG, TrimRNG, TweakRNG, VanDerCorputQRNG, WhiskerRNG, XoRoRNG, XoshiroStarPhi32RNG, XoshiroStarStar64RNG

public interface RandomnessSource
extends java.io.Serializable

This interface defines the interactions required of a random number generator. It is a replacement for Java's built-in Random because for improved performance.

Method Summary

Modifier and Type	Method and Description
RandomnessSource	copy() Produces a copy of this RandomnessSource that, if next() and/or nextLong() are called on this object and the copy, both will generate the same sequence of random numbers from the point copy() was called.
int	next(int bits) Using this method, any algorithm that might use the built-in Java Random can interface with this randomness source.
long	nextLong() Using this method, any algorithm that needs to efficiently generate more than 32 bits of random data can interface with this randomness source.

Method Detail

next

int next(int bits)

Using this method, any algorithm that might use the built-in Java Random can interface with this randomness source.

Parameters:

bits - the number of bits to be returned

Returns:

the integer containing the appropriate number of bits

nextLong

long nextLong()

Using this method, any algorithm that needs to efficiently generate more than 32 bits of random data can interface with this randomness source. Get a random long between Long.MIN_VALUE and Long.MAX_VALUE (both inclusive).

Returns:

a random long between Long.MIN_VALUE and Long.MAX_VALUE (both inclusive)

copy

RandomnessSource copy()

Produces a copy of this RandomnessSource that, if next() and/or nextLong() are called on this object and the copy, both will generate the same sequence of random numbers from the point copy() was called. This just needs to copy the state so it isn't shared, usually, and produce a new value with the same exact state.

Returns:

a copy of this RandomnessSource