Package com.github.tommyettinger.random

Class EnhancedRandom

java.lang.Object

java.util.Random

com.github.tommyettinger.random.EnhancedRandom

All Implemented Interfaces:

Externalizable, Serializable, RandomGenerator

Direct Known Subclasses:

AceRandom, ArchivalWrapper, Bear32Random, Chill32Random, Chip32Random, Choo32Random, ChopRandom, Crand64Random, DistinctRandom, DistributedRandom, FlowRandom, FourWheelRandom, GoldenQuasiRandom, HornRandom, InterpolatedRandom, Jsf32Random, KnownSequenceRandom, LaserRandom, LCG64Random, LFSR64QuasiRandom, LowChangeQuasiRandom, MaceRandom, MizuchiRandom, Mx3Random, OrbitalRandom, PasarRandom, PcgRXSMXSRandom, PouchRandom, Respite32Random, ReverseWrapper, RomuTrioRandom, ScruffRandom, Sfc64Random, SoloRandom, StrangerRandom, Taxon32Random, ThrashRandom, ThrooshRandom, TraceRandom, TricycleRandom, TrimRandom, TupleQuasiRandom, VanDerCorputQuasiRandom, WhiskerRandom, Xoroshiro128StarStarRandom, Xoshiro128PlusPlusRandom, Xoshiro160RoadroxoRandom, Xoshiro256MX3Random, Xoshiro256StarStarRandom

public abstract class EnhancedRandom
extends Random
implements Externalizable

A superset of the functionality in Random, meant for random number generators that would be too bare-bones with just Random's methods.

See Also:

• Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from interface java.util.random.RandomGenerator

RandomGenerator.ArbitrarilyJumpableGenerator, RandomGenerator.JumpableGenerator, RandomGenerator.LeapableGenerator, RandomGenerator.SplittableGenerator, RandomGenerator.StreamableGenerator

Constructor Summary

Constructors

Constructor	Description
EnhancedRandom()
EnhancedRandom(long seed)

Method Summary

Modifier and Type	Method	Description
<T extends CharSequence & Appendable> T	appendSerialized(T sb)	Serializes the current state of this EnhancedRandom and appends it to an Appendable CharSequence (such as a StringBuilder), which may be used by stringDeserialize(String) to load this state at another time.
<T extends CharSequence & Appendable> T	appendSerialized(T sb, com.github.tommyettinger.digital.Base base)	Serializes the current state of this EnhancedRandom and appends it to an Appendable CharSequence (such as a StringBuilder), which may be used by stringDeserialize(String) to load this state at another time.
static boolean	areEqual(EnhancedRandom left, EnhancedRandom right)	Given two EnhancedRandom objects that could have the same or different classes, this returns true if they have the same class and same state, or false otherwise.
abstract EnhancedRandom	copy()	Creates a new EnhancedRandom with identical states to this one, so if the same EnhancedRandom methods are called on this object and its copy (in the same order), the same outputs will be produced.
static long	fixGamma(long gamma)	Attempts to improve the quality of a "gamma" increment for an additive sequence.
static long	fixGamma(long gamma, int threshold)	Attempts to improve the quality of a "gamma" increment for an additive sequence.
BigInteger	getMinimumPeriod()	Gets the guaranteed lowest number of different results this can return from its main generating method, which is normally nextLong() unless mainlyGeneratesInt() returns true (then it is nextInt()).
long	getSelectedState(int selection)	Gets a selected state value from this EnhancedRandom.
int	getStateCount()	Gets the number of possible state variables that can be selected with getSelectedState(int) or setSelectedState(int, long).
abstract String	getTag()	Gets the tag used to identify this type of EnhancedRandom, as a String.
static BigInteger	lcm(BigInteger a, BigInteger b)	Gets the least common multiple (lcm) of two BigInteger values, which here are usually returned by getMinimumPeriod().
boolean	mainlyGeneratesInt()	Returns true if this generator mainly operates via its nextInt() method internally, which means its nextLong() must generate two int values instead of naturally producing one long.
double	maxDoubleOf(double innerBound, double outerBound, int trials)	Returns the maximum result of trials calls to nextDouble(double, double) using the given innerBound and outerBound.
float	maxFloatOf(float innerBound, float outerBound, int trials)	Returns the maximum result of trials calls to nextFloat(float, float) using the given innerBound and outerBound.
int	maxIntOf(int innerBound, int outerBound, int trials)	Returns the maximum result of trials calls to nextSignedInt(int, int) using the given innerBound and outerBound.
long	maxLongOf(long innerBound, long outerBound, int trials)	Returns the maximum result of trials calls to nextSignedLong(long, long) using the given innerBound and outerBound.
double	minDoubleOf(double innerBound, double outerBound, int trials)	Returns the minimum result of trials calls to nextDouble(double, double) using the given innerBound and outerBound.
float	minFloatOf(float innerBound, float outerBound, int trials)	Returns the minimum result of trials calls to nextFloat(float, float) using the given innerBound and outerBound.
int	minIntOf(int innerBound, int outerBound, int trials)	Returns the minimum result of trials calls to nextSignedInt(int, int) using the given innerBound and outerBound.
long	minLongOf(long innerBound, long outerBound, int trials)	Returns the minimum result of trials calls to nextSignedLong(long, long) using the given innerBound and outerBound.
int	next(int bits)	Generates the next pseudorandom number with a specific maximum size in bits (not a max number).
boolean	nextBoolean()	Returns the next pseudorandom, uniformly distributed boolean value from this random number generator's sequence.
boolean	nextBoolean(float chance)	Returns true if a random value between 0 and 1 is less than the specified value.
void	nextBytes(byte[] bytes)	Generates random bytes and places them into a user-supplied byte array.
double	nextDouble()	Returns the next pseudorandom, uniformly distributed double value between 0.0 (inclusive) and 1.0 (exclusive) from this random number generator's sequence.
double	nextDouble(double outerBound)	Gets a pseudo-random double between 0 (inclusive) and outerBound (exclusive).
double	nextDouble(double innerBound, double outerBound)	Gets a pseudo-random double between innerBound (inclusive) and outerBound (exclusive).
double	nextExclusiveDouble()	Gets a random double between 0.0 and 1.0, exclusive at both ends; this method is also more uniform than nextDouble() if you use the bit-patterns of the returned doubles.
double	nextExclusiveDouble(double outerBound)	Just like nextDouble(double), but this is exclusive on both 0.0 and outerBound.
double	nextExclusiveDouble(double innerBound, double outerBound)	Just like nextDouble(double, double), but this is exclusive on both innerBound and outerBound.
double	nextExclusiveDoubleEquidistant()	Gets a random double between 0.0 and 1.0, exclusive at both ends.
float	nextExclusiveFloat()	Gets a random float between 0.0 and 1.0, exclusive at both ends.
float	nextExclusiveFloat(float outerBound)	Just like nextFloat(float), but this is exclusive on both 0.0 and outerBound.
float	nextExclusiveFloat(float innerBound, float outerBound)	Just like nextFloat(float, float), but this is exclusive on both innerBound and outerBound.
float	nextExclusiveFloatEquidistant()	Gets a random float between 0.0 and 1.0, exclusive at both ends.
double	nextExclusiveSignedDouble()	Gets a random double that may be positive or negative, but cannot be 0, and always has a magnitude less than 1.
float	nextExclusiveSignedFloat()	Gets a random float that may be positive or negative, but cannot be 0, and always has a magnitude less than 1.
double	nextExponential()	Returns a non-negative double value pseudorandomly chosen from an exponential distribution whose mean is 1.
float	nextFloat()	Returns the next pseudorandom, uniformly distributed float value between 0.0 (inclusive) and 1.0 (exclusive) from this random number generator's sequence.
float	nextFloat(float outerBound)	Gets a pseudo-random float between 0 (inclusive) and outerBound (exclusive).
float	nextFloat(float innerBound, float outerBound)	Gets a pseudo-random float between innerBound (inclusive) and outerBound (exclusive).
double	nextGaussian()	Returns the next pseudorandom, Gaussian ("normally") distributed double value with mean 0.0 and standard deviation 1.0 from this random number generator's sequence.
double	nextGaussian(double mean, double stddev)	Returns the next pseudorandom, Gaussian ("normally") distributed double value with the specified mean and standard deviation from this random number generator's sequence.
float	nextGaussianFloat()	Returns the next pseudorandom, Gaussian ("normally") distributed float value with mean 0.0 and standard deviation 1.0 from this random number generator's sequence.
float	nextGaussianFloat(float mean, float stddev)	Returns the next pseudorandom, Gaussian ("normally") distributed float value with the specified mean and standard deviation from this random number generator's sequence.
double	nextInclusiveDouble()	This is just like nextDouble(), returning a double between 0 and 1, except that it is inclusive on both 0.0 and 1.0.
double	nextInclusiveDouble(double outerBound)	Just like nextDouble(double), but this is inclusive on both 0.0 and outerBound.
double	nextInclusiveDouble(double innerBound, double outerBound)	Just like nextDouble(double, double), but this is inclusive on both innerBound and outerBound.
float	nextInclusiveFloat()	This is just like nextFloat(), returning a float between 0 and 1, except that it is inclusive on both 0.0 and 1.0.
float	nextInclusiveFloat(float outerBound)	Just like nextFloat(float), but this is inclusive on both 0.0 and outerBound.
float	nextInclusiveFloat(float innerBound, float outerBound)	Just like nextFloat(float, float), but this is inclusive on both innerBound and outerBound.
int	nextInt()	Returns the next pseudorandom, uniformly distributed int value from this random number generator's sequence.
int	nextInt(int bound)	Returns a pseudorandom, uniformly distributed int value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence.
int	nextInt(int innerBound, int outerBound)	Returns a pseudorandom, uniformly distributed int value between the specified innerBound (inclusive) and the specified outerBound (exclusive).
abstract long	nextLong()	Returns the next pseudorandom, uniformly distributed long value from this random number generator's sequence.
long	nextLong(long bound)	Returns a pseudorandom, uniformly distributed long value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence.
long	nextLong(long inner, long outer)	Returns a pseudorandom, uniformly distributed long value between the specified innerBound (inclusive) and the specified outerBound (exclusive).
int	nextSign()	Returns -1 or 1, randomly.
int	nextSignedInt(int outerBound)	Returns a pseudorandom, uniformly distributed int value between an inner bound of 0 (inclusive) and the specified outerBound (exclusive).
int	nextSignedInt(int innerBound, int outerBound)	Returns a pseudorandom, uniformly distributed int value between the specified innerBound (inclusive) and the specified outerBound (exclusive).
long	nextSignedLong(long outerBound)	Returns a pseudorandom, uniformly distributed long value between an inner bound of 0 (inclusive) and the specified outerBound (exclusive).
long	nextSignedLong(long inner, long outer)	Returns a pseudorandom, uniformly distributed long value between the specified innerBound (inclusive) and the specified outerBound (exclusive).
float	nextTriangular()	Returns a triangularly distributed random number between -1.0 (exclusive) and 1.0 (exclusive), where values around zero are more likely.
float	nextTriangular(float max)	Returns a triangularly distributed random number between -max (exclusive) and max (exclusive), where values around zero are more likely.
float	nextTriangular(float min, float max)	Returns a triangularly distributed random number between min (inclusive) and max (exclusive), where the mode argument defaults to the midpoint between the bounds, giving a symmetric distribution.
float	nextTriangular(float min, float max, float mode)	Returns a triangularly distributed random number between min (inclusive) and max (exclusive), where values around mode are more likely.
int	nextUnsignedInt(int bound)	Returns a pseudorandom, uniformly distributed int value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence.
int	previousInt()	Optional; moves the state to its previous value and returns the previous int that would have been produced by nextInt().
long	previousLong()	Optional; moves the state to its previous value and returns the previous long that would have been produced by nextLong().
static double	probit(double d)	A way of taking a double in the (0.0, 1.0) range and mapping it to a Gaussian or normal distribution, so high inputs correspond to high outputs, and similarly for the low range.
<T> T	randomElement(List<T> list)	Gets a randomly selected item from the given List, such as an ArrayList.
<T> T	randomElement(T[] array)	Gets a randomly-selected item from the given array, which must be non-null and non-empty
static int	rateGamma(long gamma)	Attempts to check the quality of a "gamma" increment for an additive sequence.
void	readExternal(ObjectInput in)	The object implements the readExternal method to restore its contents by calling the methods of DataInput for primitive types and readObject for objects, strings and arrays.
static long	seedFromMath()	Uses Math.random() to hastily put together a not-especially-uniform long value, meant only to produce a seed when no seed was specified (the "I don't care" seed).
abstract void	setSeed(long seed)	Sets the seed of this random number generator using a single long seed.
void	setSelectedState(int selection, long value)	Sets a selected state value to the given long value.
void	setState(long state)	Sets each state variable to the given state.
void	setState(long... states)	Sets all state variables to alternating values chosen from states.
void	setState(long stateA, long stateB)	Sets each state variable to either stateA or stateB, alternating.
void	setState(long stateA, long stateB, long stateC)	Sets each state variable to stateA, stateB, or stateC, alternating.
void	setState(long stateA, long stateB, long stateC, long stateD)	Sets each state variable to stateA, stateB, stateC, or stateD, alternating.
void	setState(long stateA, long stateB, long stateC, long stateD, long stateE)	Sets each state variable to stateA, stateB, stateC, stateD, or stateE, alternating.
void	setState(long stateA, long stateB, long stateC, long stateD, long stateE, long stateF)	Sets each state variable to stateA, stateB, stateC, stateD, or stateE, alternating.
void	setWith(EnhancedRandom other)	Similar to copy(), but fills this EnhancedRandom with the state of another EnhancedRandom, usually (but not necessarily) one of the same type.
void	shuffle(boolean[] items)	Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.
void	shuffle(boolean[] items, int offset, int length)	Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.
void	shuffle(byte[] items)	Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.
void	shuffle(byte[] items, int offset, int length)	Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.
void	shuffle(char[] items)	Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.
void	shuffle(char[] items, int offset, int length)	Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.
void	shuffle(double[] items)	Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.
void	shuffle(double[] items, int offset, int length)	Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.
void	shuffle(float[] items)	Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.
void	shuffle(float[] items, int offset, int length)	Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.
void	shuffle(int[] items)	Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.
void	shuffle(int[] items, int offset, int length)	Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.
void	shuffle(long[] items)	Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.
void	shuffle(long[] items, int offset, int length)	Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.
void	shuffle(short[] items)	Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.
void	shuffle(short[] items, int offset, int length)	Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.
<T> void	shuffle(List<T> items)	Shuffles the given List in-place pseudo-randomly, using this to determine how to shuffle.
<T> void	shuffle(List<T> items, int offset, int length)	Shuffles a section of the given List in-place pseudo-randomly, using this to determine how to shuffle.
<T> void	shuffle(T[] items)	Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.
<T> void	shuffle(T[] items, int offset, int length)	Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.
long	skip(long advance)	Optional; advances or rolls back the EnhancedRandom' state without actually generating each number.
EnhancedRandom	stringDeserialize(String data)	Given a String in the format produced by stringSerialize(), this will attempt to set this EnhancedRandom object to match the state in the serialized data.
EnhancedRandom	stringDeserialize(String data, com.github.tommyettinger.digital.Base base)	Given a String in the format produced by stringSerialize(Base), and the same Base used by the serialization, this will attempt to set this EnhancedRandom object to match the state in the serialized data.
String	stringSerialize()	Serializes the current state of this EnhancedRandom to a String that can be used by stringDeserialize(String) to load this state at another time.
String	stringSerialize(com.github.tommyettinger.digital.Base base)	Serializes the current state of this EnhancedRandom to a String that can be used by stringDeserialize(String) to load this state at another time.
void	writeExternal(ObjectOutput out)	The object implements the writeExternal method to save its contents by calling the methods of DataOutput for its primitive values or calling the writeObject method of ObjectOutput for objects, strings, and arrays.

Methods inherited from class java.util.Random

doubles, doubles, doubles, doubles, ints, ints, ints, ints, longs, longs, longs, longs

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface java.util.random.RandomGenerator

isDeprecated

Constructor Details

EnhancedRandom

public EnhancedRandom()

EnhancedRandom

public EnhancedRandom(long seed)

Method Details

getTag

public abstract String getTag()

Gets the tag used to identify this type of EnhancedRandom, as a String. This tag should be unique, and for uniformity purposes, all tags used in this library are 4 characters long. User-defined tags should have a different length.

Returns:

a unique String identifier for this type of EnhancedRandom; usually 4 chars long.

mainlyGeneratesInt

public boolean mainlyGeneratesInt()

Returns true if this generator mainly operates via its nextInt() method internally, which means its nextLong() must generate two int values instead of naturally producing one long. This affects how the minimum period is measured for getMinimumPeriod(). Most generators not intentionally targeting Google Web Toolkit mainly operate via nextLong() here, and return false. A generator that returns true here does not necessarily use 32-bit math; a generator can use 64-bit math internally but only produce 32 bits at a time by truncating its results.

Returns:

true if measurements of the period measure calls to nextInt() instead of nextLong()

See Also:

• This is closely related to the minimum period length.

getMinimumPeriod

public BigInteger getMinimumPeriod()

Gets the guaranteed lowest number of different results this can return from its main generating method, which is normally nextLong() unless mainlyGeneratesInt() returns true (then it is nextInt()). The maximum period is not known for many generators, but the minimum is, even if it is only 1 for a generator that can be initialized badly and return the same value every time on that cycle. If the minimum period is not known, this should not be overridden; its default result is the constant BigInteger.ONE. If this is the only JavaDoc for this method, the minimum period is not known, and is possibly 1 in the worst case.
This is relevant when determining if, when two different generators are combined, their period will change. The minimum period of two generators run simultaneously and both used fully in the result is the least common multiple of their minimum periods. This can be computed conveniently with lcm(BigInteger, BigInteger) given the minimum period of two different EnhancedRandom generators.
Implementations are strongly encouraged to compute this value once, if it needs computation at all, and store it in a private static final BigInteger MINIMUM_PERIOD;, which this method simply returns. Classes are not required to have a MINIMUM_PERIOD field or to make it accessible. Calling this method should generally not create a new BigInteger.

Returns:

the minimum guaranteed period, or the shortest cycle length possible for the main generating method

lcm

public static BigInteger lcm(BigInteger a,
 BigInteger b)

Gets the least common multiple (lcm) of two BigInteger values, which here are usually returned by getMinimumPeriod().

Parameters:

a - must be greater than 0; typically the result of getMinimumPeriod()

b - must be greater than 0; typically the result of getMinimumPeriod()

Returns:

the least common multiple of a and b, as a BigInteger

seedFromMath

public static long seedFromMath()

Uses Math.random() to hastily put together a not-especially-uniform long value, meant only to produce a seed when no seed was specified (the "I don't care" seed).

Returns:

a kind-of-uniform long value

setSeed

public abstract void setSeed(long seed)

Sets the seed of this random number generator using a single long seed. This should behave exactly the same as if a new object of this type was created with the constructor that takes a single long value. This does not necessarily assign the state variable(s) of the implementation with the exact contents of seed, so getSelectedState(int) should not be expected to return seed after this, though it may. If this implementation has more than one long of state, then the expectation is that none of those state variables will be exactly equal to seed (almost all the time).

Overrides:

setSeed in class Random

Parameters:

seed - the initial seed

getStateCount

public int getStateCount()

Gets the number of possible state variables that can be selected with getSelectedState(int) or setSelectedState(int, long). This defaults to returning 0, making no state variable available for reading or writing. An implementation that has only one long state, like DistinctRandom generator, should return 1. A generator that permits setting two different long values, like LaserRandom, should return 2. Much larger values are possible for types like the Mersenne Twister or some CMWC generators.

Returns:

the non-negative number of selections possible for state variables

getSelectedState

public long getSelectedState(int selection)

Gets a selected state value from this EnhancedRandom. The number of possible selections is up to the implementing class, and is accessible via getStateCount(), but negative values for selection are typically not tolerated. This should return the exact value of the selected state, assuming it is implemented. The default implementation throws an UnsupportedOperationException, and implementors only have to allow reading the state if they choose to implement this differently. If this method is intended to be used, getStateCount() must also be implemented.

Parameters:

selection - used to select which state variable to get; generally non-negative

Returns:

the exact value of the selected state

setSelectedState

public void setSelectedState(int selection,
 long value)

Sets a selected state value to the given long value. The number of possible selections is up to the implementing class, but negative values for selection are typically not tolerated. Implementors are permitted to change value if it is not valid, but they should not alter it if it is valid. The public implementation calls setSeed(long) with value, which doesn't need changing if the generator has one state that is set verbatim by setSeed(). Otherwise, this method should be implemented when getSelectedState(int) is and the state is allowed to be set by users. Having accurate ways to get and set the full state of a random number generator makes it much easier to serialize and deserialize that class.

Parameters:

selection - used to select which state variable to set; generally non-negative

value - the exact value to use for the selected state, if valid

setState

public void setState(long state)

Sets each state variable to the given state. If getStateCount() is 1, then this should set the whole state to the given value using setSelectedState(int, long). If getStateCount() is more than 1, then all states will be set in the same way (using setSelectedState(), all to state).

Parameters:

state - the long value to use for each state variable

setState

public void setState(long stateA,
 long stateB)

Sets each state variable to either stateA or stateB, alternating. This uses setSelectedState(int, long) to set the values. If there is one state variable (getStateCount() is 1), then this only sets that state variable to stateA. If there are two state variables, the first is set to stateA, and the second to stateB. If there are more, it reuses stateA, then stateB, then stateA, and so on until all variables are set.

Parameters:

stateA - the long value to use for states at index 0, 2, 4, 6...

stateB - the long value to use for states at index 1, 3, 5, 7...

setState

public void setState(long stateA,
 long stateB,
 long stateC)

Sets each state variable to stateA, stateB, or stateC, alternating. This uses setSelectedState(int, long) to set the values. If there is one state variable (getStateCount() is 1), then this only sets that state variable to stateA. If there are two state variables, the first is set to stateA, and the second to stateB. With three state variables, the first is set to stateA, the second to stateB, and the third to stateC. If there are more, it reuses stateA, then stateB, then stateC, then stateA, and so on until all variables are set.

Parameters:

stateA - the long value to use for states at index 0, 3, 6, 9...

stateB - the long value to use for states at index 1, 4, 7, 10...

stateC - the long value to use for states at index 2, 5, 8, 11...

setState

public void setState(long stateA,
 long stateB,
 long stateC,
 long stateD)

Sets each state variable to stateA, stateB, stateC, or stateD, alternating. This uses setSelectedState(int, long) to set the values. If there is one state variable (getStateCount() is 1), then this only sets that state variable to stateA. If there are two state variables, the first is set to stateA, and the second to stateB. With three state variables, the first is set to stateA, the second to stateB, and the third to stateC. With four state variables, the first is set to stateA, the second to stateB, the third to stateC, and the fourth to stateD. If there are more, it reuses stateA, then stateB, then stateC, then stateD, then stateA, and so on until all variables are set.

Parameters:

stateA - the long value to use for states at index 0, 4, 8, 12...

stateB - the long value to use for states at index 1, 5, 9, 13...

stateC - the long value to use for states at index 2, 6, 10, 14...

stateD - the long value to use for states at index 3, 7, 11, 15...

setState

public void setState(long stateA,
 long stateB,
 long stateC,
 long stateD,
 long stateE)

Sets each state variable to stateA, stateB, stateC, stateD, or stateE, alternating. This uses setSelectedState(int, long) to set the values. If there is one state variable (getStateCount() is 1), then this only sets that state variable to stateA. If there are two state variables, the first is set to stateA, and the second to stateB. With three state variables, the first is set to stateA, the second to stateB, and the third to stateC. With four state variables, the first is set to stateA, the second to stateB, the third to stateC, and the fourth to stateD. If there are more, it reuses stateA, then stateB, then stateC, then stateD, then stateE, then stateA, and so on until all variables are set.

Parameters:

stateA - the long value to use for states at index 0, 5, 10, 15...

stateB - the long value to use for states at index 1, 6, 11, 16...

stateC - the long value to use for states at index 2, 7, 12, 17...

stateD - the long value to use for states at index 3, 8, 13, 18...

stateE - the long value to use for states at index 4, 9, 14, 19...

setState

public void setState(long stateA,
 long stateB,
 long stateC,
 long stateD,
 long stateE,
 long stateF)

Sets each state variable to stateA, stateB, stateC, stateD, or stateE, alternating. This uses setSelectedState(int, long) to set the values. If there is one state variable (getStateCount() is 1), then this only sets that state variable to stateA. If there are two state variables, the first is set to stateA, and the second to stateB. With three state variables, the first is set to stateA, the second to stateB, and the third to stateC. With four state variables, the first is set to stateA, the second to stateB, the third to stateC, and the fourth to stateD. If there are more, it reuses stateA, then stateB, then stateC, then stateD, then stateE, then stateF, then stateA, and so on until all variables are set.

Parameters:

stateA - the long value to use for states at index 0, 6, 12, 18...

stateB - the long value to use for states at index 1, 7, 13, 19...

stateC - the long value to use for states at index 2, 8, 14, 20...

stateD - the long value to use for states at index 3, 9, 15, 21...

stateE - the long value to use for states at index 4, 10, 16, 22...

stateF - the long value to use for states at index 5, 11, 17, 23...

setState

public void setState(long... states)

Sets all state variables to alternating values chosen from states. If states is empty, then this does nothing, and leaves the current generator unchanged. This works for generators with any getStateCount(), but may allocate an array if states is used as a varargs (you can pass an existing array without needing to allocate). This uses setSelectedState(int, long) to change the states.

Parameters:

states - an array or varargs of long values to use as states

next

public int next(int bits)

Generates the next pseudorandom number with a specific maximum size in bits (not a max number). If you want to get a random number in a range, you should usually use nextInt(int) instead. For some specific cases, this method is more efficient and less biased than nextInt(int). For bits values between 1 and 30, this should be similar in effect to nextInt(1 << bits); though it won't typically produce the same values, they will have the correct range. If bits is 31, this can return any non-negative int; note that nextInt(1 << 31) won't behave this way because 1 << 31 is negative. If bits is 32 (or 0), this can return any int.

The general contract of next is that it returns an int value and if the argument bits is between 1 and 32 (inclusive), then that many low-order bits of the returned value will be (approximately) independently chosen bit values, each of which is (approximately) equally likely to be 0 or 1.

Note that you can give this values for bits that are outside its expected range of 1 to 32, but the value used, as long as bits is positive, will effectively be bits % 32. As stated before, a value of 0 for bits is the same as a value of 32.

Overrides:

next in class Random

Parameters:

bits - the amount of random bits to request, from 1 to 32

Returns:

the next pseudorandom value from this random number generator's sequence

nextBytes

public void nextBytes(byte[] bytes)

Generates random bytes and places them into a user-supplied byte array. The number of random bytes produced is equal to the length of the byte array.

Specified by:

nextBytes in interface RandomGenerator

Overrides:

nextBytes in class Random

Parameters:

bytes - the byte array to fill with random bytes

Throws:

NullPointerException - if the byte array is null

nextInt

public int nextInt()

Returns the next pseudorandom, uniformly distributed int value from this random number generator's sequence. The general contract of nextInt is that one int value is pseudorandomly generated and returned. All 2³² possible int values are produced with (approximately) equal probability.

Specified by:

nextInt in interface RandomGenerator

Overrides:

nextInt in class Random

Returns:

the next pseudorandom, uniformly distributed int value from this random number generator's sequence

nextInt

public int nextInt(int bound)

Returns a pseudorandom, uniformly distributed int value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence. The general contract of nextInt is that one int value in the specified range is pseudorandomly generated and returned. All bound possible int values are produced with (approximately) equal probability.
This method clamps bound to be at least 0; it never returns a negative int.
It should be mentioned that the technique this uses has some bias, depending on bound, but it typically isn't measurable without specifically looking for it. Using the method this does allows this method to always advance the state by one step, instead of a varying and unpredictable amount with the more typical ways of rejection-sampling random numbers and only using numbers that can produce an int within the bound without bias. See M.E. O'Neill's blog about random numbers for discussion of alternative, unbiased methods.

Specified by:

nextInt in interface RandomGenerator

Overrides:

nextInt in class Random

Parameters:

bound - the upper bound (exclusive). If negative or 0, this always returns 0.

Returns:

the next pseudorandom, uniformly distributed int value between zero (inclusive) and bound (exclusive) from this random number generator's sequence

nextUnsignedInt

public int nextUnsignedInt(int bound)

Returns a pseudorandom, uniformly distributed int value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence. The general contract of nextInt is that one int value in the specified range is pseudorandomly generated and returned. All bound possible int values are produced with (approximately) equal probability.
This method treats the outer bound as unsigned, so if a negative int is passed as bound, it will be treated as positive and larger than Integer.MAX_VALUE. That means this can produce results that are positive or negative, but when you mask the result and the bound with 0xFFFFFFFFL (to treat them as unsigned), the result will always be between 0L (inclusive) and the masked bound (exclusive).
This is primarily useful as a building block for other methods in this class.

Parameters:

bound - the upper bound (exclusive); treated as unsigned

Returns:

the next pseudorandom, uniformly distributed int value between zero (inclusive) and bound (exclusive), treated as unsigned, from this random number generator's sequence

nextSignedInt

public int nextSignedInt(int outerBound)

Returns a pseudorandom, uniformly distributed int value between an inner bound of 0 (inclusive) and the specified outerBound (exclusive). This is meant for cases where the outer bound may be negative, especially if the bound is unknown or may be user-specified. A negative outer bound is used as the lower bound; a positive outer bound is used as the upper bound. An outer bound of -1, 0, or 1 will always return 0, keeping the bound exclusive (except for outer bound 0). This method is slightly slower than nextInt(int).

Parameters:

outerBound - the outer exclusive bound; may be any int value, allowing negative

Returns:

a pseudorandom int between 0 (inclusive) and outerBound (exclusive)

See Also:

• Here's a note about the bias present in the bounded generation.

nextInt

public int nextInt(int innerBound,
 int outerBound)

Returns a pseudorandom, uniformly distributed int value between the specified innerBound (inclusive) and the specified outerBound (exclusive). If outerBound is less than or equal to innerBound, this always returns innerBound.
For any case where outerBound might be valid but less than innerBound, you can use nextSignedInt(int, int). If outerBound is less than innerBound here, this simply returns innerBound.

Specified by:

nextInt in interface RandomGenerator

Parameters:

innerBound - the inclusive inner bound; may be any int, allowing negative

outerBound - the exclusive outer bound; must be greater than innerBound (otherwise this returns innerBound)

Returns:

a pseudorandom int between innerBound (inclusive) and outerBound (exclusive)

See Also:

• Here's a note about the bias present in the bounded generation.

nextSignedInt

public int nextSignedInt(int innerBound,
 int outerBound)

Returns a pseudorandom, uniformly distributed int value between the specified innerBound (inclusive) and the specified outerBound (exclusive). This is meant for cases where either bound may be negative, especially if the bounds are unknown or may be user-specified.

Parameters:

innerBound - the inclusive inner bound; may be any int, allowing negative

outerBound - the exclusive outer bound; may be any int, allowing negative

Returns:

a pseudorandom int between innerBound (inclusive) and outerBound (exclusive)

See Also:

• Here's a note about the bias present in the bounded generation.

nextLong

public abstract long nextLong()

Returns the next pseudorandom, uniformly distributed long value from this random number generator's sequence. The general contract of nextLong is that one long value is pseudorandomly generated and returned.
The only methods that need to be implemented by this interface are this and copy(), though other methods can be implemented as appropriate for generators that, for instance, natively produce ints rather than longs.

Specified by:

nextLong in interface RandomGenerator

Overrides:

nextLong in class Random

Returns:

the next pseudorandom, uniformly distributed long value from this random number generator's sequence

nextLong

public long nextLong(long bound)

Returns a pseudorandom, uniformly distributed long value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence. The general contract of nextLong is that one long value in the specified range is pseudorandomly generated and returned. All bound possible long values are produced with (approximately) equal probability, though there is a small amount of bias depending on the bound.
Note that this advances the state by the same amount as a single call to nextLong(), which allows methods like skip(long) to function correctly, but introduces some bias when bound is very large. This will also advance the state if bound is 0 or negative, so usage with a variable bound will advance the state reliably.
This method has some bias, particularly on larger bounds. Actually measuring bias with bounds in the trillions or greater is challenging but not impossible, so don't use this for a real-money gambling purpose. The bias isn't especially significant, though.

Specified by:

nextLong in interface RandomGenerator

Parameters:

bound - the upper bound (exclusive). If negative or 0, this always returns 0.

Returns:

the next pseudorandom, uniformly distributed long value between zero (inclusive) and bound (exclusive) from this random number generator's sequence

See Also:

• Here's a note about the bias present in the bounded generation.

nextSignedLong

public long nextSignedLong(long outerBound)

Returns a pseudorandom, uniformly distributed long value between an inner bound of 0 (inclusive) and the specified outerBound (exclusive). This is meant for cases where the outer bound may be negative, especially if the bound is unknown or may be user-specified. A negative outer bound is used as the lower bound; a positive outer bound is used as the upper bound. An outer bound of -1, 0, or 1 will always return 0, keeping the bound exclusive (except for outer bound 0).

Note that this advances the state by the same amount as a single call to nextLong(), which allows methods like skip(long) to function correctly, but introduces some bias when bound is very large. This method should be about as fast as nextLong(long) , unlike the speed difference between nextInt(int) and nextSignedInt(int).

Parameters:

outerBound - the outer exclusive bound; may be any long value, allowing negative

Returns:

a pseudorandom long between 0 (inclusive) and outerBound (exclusive)

See Also:

• Here's a note about the bias present in the bounded generation.

nextLong

public long nextLong(long inner,
 long outer)

Returns a pseudorandom, uniformly distributed long value between the specified innerBound (inclusive) and the specified outerBound (exclusive). If outerBound is less than or equal to innerBound, this always returns innerBound.
For any case where outerBound might be valid but less than innerBound, you can use nextSignedLong(long, long).

Specified by:

nextLong in interface RandomGenerator

Parameters:

inner - the inclusive inner bound; may be any long, allowing negative

outer - the exclusive outer bound; must be greater than innerBound (otherwise this returns innerBound)

Returns:

a pseudorandom long between innerBound (inclusive) and outerBound (exclusive)

See Also:

• Here's a note about the bias present in the bounded generation.

nextSignedLong

public long nextSignedLong(long inner,
 long outer)

Returns a pseudorandom, uniformly distributed long value between the specified innerBound (inclusive) and the specified outerBound (exclusive). This is meant for cases where either bound may be negative, especially if the bounds are unknown or may be user-specified.

Parameters:

inner - the inclusive inner bound; may be any long, allowing negative

outer - the exclusive outer bound; may be any long, allowing negative

Returns:

a pseudorandom long between innerBound (inclusive) and outerBound (exclusive)

See Also:

• Here's a note about the bias present in the bounded generation.

nextBoolean

public boolean nextBoolean()

Returns the next pseudorandom, uniformly distributed boolean value from this random number generator's sequence. The general contract of nextBoolean is that one boolean value is pseudorandomly generated and returned. The values true and false are produced with (approximately) equal probability.
The public implementation simply returns a sign check on nextLong(), returning true if the generated long is negative. This is typically the safest way to implement this method; many types of generators have less statistical quality on their lowest bit, so just returning based on the lowest bit isn't always a good idea.

Specified by:

nextBoolean in interface RandomGenerator

Overrides:

nextBoolean in class Random

Returns:

the next pseudorandom, uniformly distributed boolean value from this random number generator's sequence

nextFloat

public float nextFloat()

Returns the next pseudorandom, uniformly distributed float value between 0.0 (inclusive) and 1.0 (exclusive) from this random number generator's sequence.

The general contract of nextFloat is that one float value, chosen (approximately) uniformly from the range 0.0f (inclusive) to 1.0f (exclusive), is pseudorandomly generated and returned. All 2²⁴ possible float values of the form m x 2^-24, where m is a positive integer less than 2²⁴, are produced with (approximately) equal probability.

The public implementation uses the upper 24 bits of nextLong(), with an unsigned right shift and a multiply by a very small float (5.9604645E-8f or 0x1p-24f). It tends to be fast if nextLong() is fast, but alternative implementations could use 24 bits of nextInt() (or just next(int), giving it 24) if that generator doesn't efficiently generate 64-bit longs.

Specified by:

nextFloat in interface RandomGenerator

Overrides:

nextFloat in class Random

Returns:

the next pseudorandom, uniformly distributed float value between 0.0 and 1.0 from this random number generator's sequence

nextFloat

public float nextFloat(float outerBound)

Gets a pseudo-random float between 0 (inclusive) and outerBound (exclusive). The outerBound may be positive or negative. Exactly the same as nextFloat() * outerBound.

Specified by:

nextFloat in interface RandomGenerator

Parameters:

outerBound - the exclusive outer bound

Returns:

a float between 0 (inclusive) and outerBound (exclusive)

nextFloat

public float nextFloat(float innerBound,
 float outerBound)

Gets a pseudo-random float between innerBound (inclusive) and outerBound (exclusive). Either, neither, or both of innerBound and outerBound may be negative; this does not change which is inclusive and which is exclusive.

Specified by:

nextFloat in interface RandomGenerator

Parameters:

innerBound - the inclusive inner bound; may be negative

outerBound - the exclusive outer bound; may be negative

Returns:

a float between innerBound (inclusive) and outerBound (exclusive)

nextDouble

public double nextDouble()

Returns the next pseudorandom, uniformly distributed double value between 0.0 (inclusive) and 1.0 (exclusive) from this random number generator's sequence.

The general contract of nextDouble is that one double value, chosen (approximately) uniformly from the range 0.0d (inclusive) to 1.0d (exclusive), is pseudorandomly generated and returned.

The public implementation uses the upper 53 bits of nextLong(), with an unsigned right shift and a multiply by a very small double (1.1102230246251565E-16, or 0x1p-53). It should perform well if nextLong() performs well, and is expected to perform less well if the generator naturally produces 32 or fewer bits at a time.

Specified by:

nextDouble in interface RandomGenerator

Overrides:

nextDouble in class Random

Returns:

the next pseudorandom, uniformly distributed double value between 0.0 and 1.0 from this random number generator's sequence

nextDouble

public double nextDouble(double outerBound)

Gets a pseudo-random double between 0 (inclusive) and outerBound (exclusive). The outerBound may be positive or negative. Exactly the same as nextDouble() * outerBound.

Specified by:

nextDouble in interface RandomGenerator

Parameters:

outerBound - the exclusive outer bound

Returns:

a double between 0 (inclusive) and outerBound (exclusive)

nextDouble

public double nextDouble(double innerBound,
 double outerBound)

Gets a pseudo-random double between innerBound (inclusive) and outerBound (exclusive). Either, neither, or both of innerBound and outerBound may be negative; this does not change which is inclusive and which is exclusive.

Specified by:

nextDouble in interface RandomGenerator

Parameters:

innerBound - the inclusive inner bound; may be negative

outerBound - the exclusive outer bound; may be negative

Returns:

a double between innerBound (inclusive) and outerBound (exclusive)

nextInclusiveDouble

public double nextInclusiveDouble()

This is just like nextDouble(), returning a double between 0 and 1, except that it is inclusive on both 0.0 and 1.0. It returns 1.0 rarely, 0.000000000000000005421010862427522% of the time if there is no bias in the generator, but it can happen.
This method does not return purely-equidistant doubles, because there the resolution of possible doubles it can generate is higher as it approaches 0.0 . The smallest non-zero double this can return is 2.710505431213763e-20 (0x1.0000000000003p-65 in hex), and the largest non-one double this can return is 0.9999999999999999 (0x1.fffffffffffffp-1 in hex). This uses nearly identical code to nextExclusiveDouble(), but does some really unusual operations on both the bits and the double value to be able to produce 0.0 and 1.0 . This retains the exclusive version's quality of having approximately uniform distributions for every mantissa bit, unlike most ways of generating random floating-point numbers.

Returns:

a double between 0.0, inclusive, and 1.0, inclusive

nextInclusiveDouble

public double nextInclusiveDouble(double outerBound)

Just like nextDouble(double), but this is inclusive on both 0.0 and outerBound. It may be important to note that it returns outerBound on only 0.000000000000011102230246251565% of calls.

Parameters:

outerBound - the outer inclusive bound; may be positive or negative

Returns:

a double between 0.0, inclusive, and outerBound, inclusive

nextInclusiveDouble

public double nextInclusiveDouble(double innerBound,
 double outerBound)

Just like nextDouble(double, double), but this is inclusive on both innerBound and outerBound. It may be important to note that it returns outerBound on only 0.000000000000011102230246251565% of calls, if it can return it at all because of floating-point imprecision when innerBound is a larger number.

Parameters:

innerBound - the inner inclusive bound; may be positive or negative

outerBound - the outer inclusive bound; may be positive or negative

Returns:

a double between innerBound, inclusive, and outerBound, inclusive

nextInclusiveFloat

public float nextInclusiveFloat()

This is just like nextFloat(), returning a float between 0 and 1, except that it is inclusive on both 0.0 and 1.0. It returns 1.0 rarely, 0.000000000000000005421010862427522% of the time if there is no bias in the generator, but it can happen.
This method does not return purely-equidistant floats, because there the resolution of possible floats it can generate is higher as it approaches 0.0 . The smallest non-zero float this can return is 2.7105064E-20 (0x1.000006p-65 in hex), and the largest non-one float this can return is 0.99999994f (0x1.fffffep-1 in hex). This uses nearly identical code to nextExclusiveFloat(), but does some really unusual operations on both the bits and the float value to be able to produce 0.0f and 1.0f . This retains the exclusive version's quality of having approximately uniform distributions for every mantissa bit, unlike most ways of generating random floating-point numbers.

Returns:

a float between 0.0, inclusive, and 1.0, inclusive

nextInclusiveFloat

public float nextInclusiveFloat(float outerBound)

Just like nextFloat(float), but this is inclusive on both 0.0 and outerBound. It may be important to note that it returns outerBound on only 0.00000596046412226771% of calls.

Parameters:

outerBound - the outer inclusive bound; may be positive or negative

Returns:

a float between 0.0, inclusive, and outerBound, inclusive

nextInclusiveFloat

public float nextInclusiveFloat(float innerBound,
 float outerBound)

Just like nextFloat(float, float), but this is inclusive on both innerBound and outerBound. It may be important to note that it returns outerBound on only 0.00000596046412226771% of calls, if it can return it at all because of floating-point imprecision when innerBound is a larger number.

Parameters:

innerBound - the inner inclusive bound; may be positive or negative

outerBound - the outer inclusive bound; may be positive or negative

Returns:

a float between innerBound, inclusive, and outerBound, inclusive

nextExclusiveDouble

public double nextExclusiveDouble()

Gets a random double between 0.0 and 1.0, exclusive at both ends; this method is also more uniform than nextDouble() if you use the bit-patterns of the returned doubles. This is a simplified version of this algorithm by Allen Downey. This can return double values between 2.710505431213761E-20 and 0.9999999999999999, or 0x1.0p-65 and 0x1.fffffffffffffp-1 in hex notation. It cannot return 0 or 1. Some cases can prefer nextExclusiveDoubleEquidistant(), which is implemented more traditionally but may have slower performance. This method can also return doubles that are extremely close to 0, but can't return doubles that are as close to 1, due to how floating-point numbers work. However, nextExclusiveDoubleEquidistant() can return only a minimum value that is as distant from 0 as its maximum value is distant from 1.
To compare, nextDouble() and nextExclusiveDoubleEquidistant() are less likely to produce a "1" bit for their lowest 5 bits of mantissa/significand (the least significant bits numerically, but potentially important for some uses), with the least significant bit produced half as often as the most significant bit in the mantissa. As for this method, it has approximately the same likelihood of producing a "1" bit for any position in the mantissa.
The implementation may have different performance characteristics than nextDouble(), because this doesn't perform any floating-point multiplication or division, and instead assembles bits obtained by one call to nextLong(). This uses BitConversion.longBitsToDouble(long) and BitConversion.countLeadingZeros(long), both of which typically have optimized intrinsics on HotSpot, and this is branchless and loopless, unlike the original algorithm by Allen Downey. When compared with nextExclusiveDoubleEquidistant(), this method performs better on at least HotSpot JVMs. On GraalVM 17, this is over twice as fast as nextExclusiveDoubleEquidistant().

Returns:

a random uniform double between 2.710505431213761E-20 and 0.9999999999999999 (both inclusive)

nextExclusiveDoubleEquidistant

public double nextExclusiveDoubleEquidistant()

Gets a random double between 0.0 and 1.0, exclusive at both ends. This can return double values between 1.1102230246251565E-16 and 0.9999999999999999, or 0x1.0p-53 and 0x1.fffffffffffffp-1 in hex notation. It cannot return 0 or 1, and its minimum and maximum results are equally distant from 0 and from 1, respectively. Many usages may prefer nextExclusiveDouble(), which is better-distributed if you consider the bit representation of the returned doubles, tends to perform better, and can return doubles that much closer to 0 than this can.
The implementation simply uses nextLong(long) to get a uniformly-chosen long between 1 and (2 to the 53) - 1, both inclusive, and multiplies it by (2 to the -53). Using larger values than (2 to the 53) would cause issues with the double math.

Returns:

a random uniform double between 0 and 1 (both exclusive)

nextExclusiveDouble

public double nextExclusiveDouble(double outerBound)

Just like nextDouble(double), but this is exclusive on both 0.0 and outerBound. Like nextExclusiveDouble(), which this uses, this may have better bit-distribution of double values, and it may also be better able to produce very small doubles when outerBound is large. It should typically be a little faster than nextDouble(double).

Parameters:

outerBound - the outer exclusive bound; may be positive or negative

Returns:

a double between 0.0, exclusive, and outerBound, exclusive

nextExclusiveDouble

public double nextExclusiveDouble(double innerBound,
 double outerBound)

Just like nextDouble(double, double), but this is exclusive on both innerBound and outerBound. Like nextExclusiveDouble(), which this uses,, this may have better bit-distribution of double values, and it may also be better able to produce doubles close to innerBound when outerBound - innerBound is large. It should typically be a little faster than nextDouble(double, double).

Parameters:

innerBound - the inner exclusive bound; may be positive or negative

outerBound - the outer exclusive bound; may be positive or negative

Returns:

a double between innerBound, exclusive, and outerBound, exclusive

nextExclusiveSignedDouble

public double nextExclusiveSignedDouble()

Gets a random double that may be positive or negative, but cannot be 0, and always has a magnitude less than 1.
This is a modified version of this algorithm by Allen Downey. This version can return double values between -0.9999999999999999 and -5.421010862427522E-20, as well as between 5.421010862427522E-20 and 0.9999999999999999, or -0x1.fffffffffffffp-1 to -0x1.0p-64 as well as between 0x1.0p-64 and 0x1.fffffffffffffp-1 in hex notation. It cannot return -1, 0 or 1. It has much more uniform bit distribution across its mantissa/significand bits than Random.nextDouble(), especially when the result of nextDouble() is expanded to the -1.0 to 1.0 range (such as with 2.0 * (nextDouble() - 0.5)). Where that code using nextDouble() is unable to produce a "1" bit for its lowest bit of mantissa (the least significant bits numerically, but potentially important for some uses), this has approximately the same likelihood of producing a "1" bit for any positions in the mantissa, and also equal odds for the sign bit.
Some useful properties here are that this produces a negative result exactly as often as the underlying generator produces a negative result with nextLong(), and the least-significant bits that the underlying generator produces with nextLong() are also the least-significant in magnitude here. This could be used with lower-quality randomness, like a linear congruential generator, and the flaws those have with their low-order bits would barely affect floating-point results here. This generator also produces results that are symmetrical around 0.0, with every possible positive number having a possible negative number of equal magnitude, if the underlying generator is at least 1-dimensionally equidistributed. Note that generators such as Xoroshiro128StarStarRandom and Xoshiro256StarStarRandom cannot return 0L from nextLong() as frequently as other results, so this is not (technically) true of those. Those generators (and other LFSR-type generators) will produce 5.421010862427522E-20 less frequently than -5.421010862427522E-20 .

Returns:

a random uniform double between -1 and 1 with a tiny hole around 0 (all exclusive)

nextExclusiveFloat

public float nextExclusiveFloat()

Gets a random float between 0.0 and 1.0, exclusive at both ends. This method is also more uniform than nextFloat() if you use the bit-patterns of the returned floats. This is a simplified version of this algorithm by Allen Downey. This version can return float values between 2.7105054E-20 to 0.99999994, or 0x1.0p-65 to 0x1.fffffep-1 in hex notation. It cannot return 0 or 1. To compare, nextFloat() is less likely to produce a "1" bit for its lowest 5 bits of mantissa/significand (the least significant bits numerically, but potentially important for some uses), with the least significant bit produced half as often as the most significant bit in the mantissa. As for this method, it has approximately the same likelihood of producing a "1" bit for any position in the mantissa.
The implementation may have different performance characteristics than nextFloat(), because this doesn't perform any floating-point multiplication or division, and instead assembles bits obtained by one call to nextLong(). This uses BitConversion.intBitsToFloat(int) and BitConversion.countLeadingZeros(long), both of which typically have optimized intrinsics on HotSpot, and this is branchless and loopless, unlike the original algorithm by Allen Downey. When compared with nextExclusiveFloatEquidistant(), this method performs better on at least HotSpot JVMs. On GraalVM 17, this is over twice as fast as nextExclusiveFloatEquidistant().

Returns:

a random uniform float between 0 and 1 (both exclusive)

nextExclusiveFloatEquidistant

public float nextExclusiveFloatEquidistant()

Gets a random float between 0.0 and 1.0, exclusive at both ends. This can return float values between 5.9604645E-8 and 0.99999994, or 0x1.0p-24 and 0x1.fffffep-1 in hex notation. It cannot return 0 or 1, and its minimum and maximum results are equally distant from 0 and from 1, respectively. Most usages might prefer nextExclusiveFloat(), which is better-distributed if you consider the bit representation of the returned floats, tends to perform better, and can return floats that much closer to 0 than this can.
The implementation simply uses nextInt(int) to get a uniformly-chosen int between 1 and (2 to the 24) - 1, both inclusive, and multiplies it by (2 to the -24). Using larger values than (2 to the 24) would cause issues with the float math.

Returns:

a random uniform float between 0 and 1 (both exclusive)

nextExclusiveFloat

public float nextExclusiveFloat(float outerBound)

Just like nextFloat(float), but this is exclusive on both 0.0 and outerBound. Like nextExclusiveFloat(), this may have better bit-distribution of float values, and it may also be better able to produce very small floats when outerBound is large. It should be a little faster than nextFloat(float).

Parameters:

outerBound - the outer exclusive bound; may be positive or negative

Returns:

a float between 0.0, exclusive, and outerBound, exclusive

nextExclusiveFloat

public float nextExclusiveFloat(float innerBound,
 float outerBound)

Just like nextFloat(float, float), but this is exclusive on both innerBound and outerBound. Like nextExclusiveFloat(), this may have better bit-distribution of float values, and it may also be better able to produce floats close to innerBound when outerBound - innerBound is large. It should be a little faster than nextFloat(float, float).

Parameters:

innerBound - the inner exclusive bound; may be positive or negative

outerBound - the outer exclusive bound; may be positive or negative

Returns:

a float between innerBound, exclusive, and outerBound, exclusive

nextExclusiveSignedFloat

public float nextExclusiveSignedFloat()

Gets a random float that may be positive or negative, but cannot be 0, and always has a magnitude less than 1.
This is a modified version of this algorithm by Allen Downey. This version can return float values between -0.99999994 and -5.421011E-20, as well as between 5.421011E-20 and 0.99999994, or -0x1.fffffep-1 to -0x1.0p-64 as well as between 0x1.0p-64 and 0x1.fffffep-1 in hex notation. It cannot return -1, 0 or 1. It has much more uniform bit distribution across its mantissa/significand bits than Random.nextFloat(), especially when the result of nextFloat() is expanded to the -1.0 to 1.0 range (such as with 2.0 * (nextFloat() - 0.5)). Where the given example code is unable to produce a "1" bit for its lowest bit of mantissa (the least significant bits numerically, but potentially important for some uses), this has approximately the same likelihood of producing a "1" bit for any positions in the mantissa, and also equal odds for the sign bit.
Some useful properties here are that this produces a negative result exactly as often as the underlying generator produces a negative result with nextLong(), and the least-significant bits that the underlying generator produces with nextLong() are also the least-significant in magnitude here. This could be used with lower-quality randomness, like a linear congruential generator, and the flaws those have with their low-order bits would barely affect floating-point results here. This generator also produces results that are symmetrical around 0.0, with every possible positive number having a possible negative number of equal magnitude, if the underlying generator is at least 1-dimensionally equidistributed. Note that generators such as Xoroshiro128StarStarRandom and Xoshiro256StarStarRandom cannot return 0L from nextLong() as frequently as other results, so this is not (technically) true of those. Those generators (and other LFSR-type generators) will produce 5.421011E-20 less frequently than -5.421011E-20 .

Returns:

a random uniform float between -1 and 1 with a tiny hole around 0 (all exclusive)

nextGaussian

public double nextGaussian()

Returns the next pseudorandom, Gaussian ("normally") distributed double value with mean 0.0 and standard deviation 1.0 from this random number generator's sequence.

The general contract of nextGaussian is that one double value, chosen from (approximately) the usual normal distribution with mean 0.0 and standard deviation 1.0, is pseudorandomly generated and returned.

This does not use a rough approximation, which is a departure from earlier versions; instead, it uses the Ziggurat method, which produces high-quality variables very quickly. Like earlier versions that used probit() or a bit-counting approximation, this requests exactly one long from the generator's sequence (using nextLong()). This makes it different from code like java.util.Random's nextGaussian() method, which can (rarely) fetch a higher number of random doubles.

The implementation here was ported from code by Olaf Berstein, based on a paper by Jorgen A. Doornik and some steps from a paper by George Marsaglia. Distributor has more information, for the curious.

Specified by:

nextGaussian in interface RandomGenerator

Overrides:

nextGaussian in class Random

Returns:

the next pseudorandom, Gaussian ("normally") distributed double value with mean 0.0 and standard deviation 1.0 from this random number generator's sequence

nextGaussian

public double nextGaussian(double mean,
 double stddev)

Returns the next pseudorandom, Gaussian ("normally") distributed double value with the specified mean and standard deviation from this random number generator's sequence.
This defaults to simply returning mean + stddev * nextGaussian().

Specified by:

nextGaussian in interface RandomGenerator

Parameters:

mean - the mean of the Gaussian distribution to be drawn from

stddev - the standard deviation (square root of the variance) of the Gaussian distribution to be drawn from

Returns:

a Gaussian distributed double with the specified mean and standard deviation

nextGaussianFloat

public float nextGaussianFloat()

Returns the next pseudorandom, Gaussian ("normally") distributed float value with mean 0.0 and standard deviation 1.0 from this random number generator's sequence.

The general contract of nextGaussianFloat is that one float value, chosen from (approximately) the usual normal distribution with mean 0.0 and standard deviation 1.0, is pseudorandomly generated and returned.

This uses RoughMath.normalRough(long), which actually appears to approximate the normal distribution better than Distributor.normalF(long), though not quite as well as Distributor.normal(long) (which is used by nextGaussian()). Like nextGaussian(), this requests exactly one long from the generator's sequence (using nextLong()). This makes it different from code like java.util.Random's nextGaussian() method, which can (rarely) fetch an arbitrarily higher number of random doubles.

The implementation here was ported from code by Marc B. Reynolds and modified to only require one call to nextLong().

Returns:

the next pseudorandom, Gaussian ("normally") distributed float value with mean 0.0 and standard deviation 1.0 from this random number generator's sequence

nextGaussianFloat

public float nextGaussianFloat(float mean,
 float stddev)

Returns the next pseudorandom, Gaussian ("normally") distributed float value with the specified mean and standard deviation from this random number generator's sequence.
This defaults to simply returning mean + stddev * nextGaussianFloat().

Parameters:

mean - the mean of the Gaussian distribution to be drawn from

stddev - the standard deviation (square root of the variance) of the Gaussian distribution to be drawn from

Returns:

a Gaussian distributed float with the specified mean and standard deviation

nextExponential

public double nextExponential()

Returns a non-negative double value pseudorandomly chosen from an exponential distribution whose mean is 1.

Specified by:

nextExponential in interface RandomGenerator

Returns:

a non-negative double value pseudorandomly chosen from an exponential distribution with a mean of 1

skip

public long skip(long advance)

Optional; advances or rolls back the EnhancedRandom' state without actually generating each number. Skips forward or backward a number of steps specified by advance, where a step is equal to one call to nextLong(), and returns the random number produced at that step. Negative numbers can be used to step backward, or 0 can be given to get the most-recently-generated long from nextLong().

The public implementation throws an UnsupportedOperationException. Many types of random number generator do not have an efficient way of skipping arbitrarily through the state sequence, and those types should not implement this method differently.

Parameters:

advance - Number of future generations to skip over; can be negative to backtrack, 0 gets the most-recently-generated number

Returns:

the random long generated after skipping forward or backwards by advance numbers

previousLong

public long previousLong()

Optional; moves the state to its previous value and returns the previous long that would have been produced by nextLong(). This can be equivalent to calling skip(long) with -1L, but not always; many generators can't efficiently skip long distances, but can step back by one value.
Generators that natively generate int results typically produce long values by generating an int for the high 32 bits and an int for the low 32 bits. When producing the previous long, the order the high and low bits are generated, such as by previousInt(), should be reversed. Generators that natively produce long values usually don't need to implement previousInt(), but those that produce int usually should implement it, and may optionally call previousInt() twice in this method.
If you know how to implement the reverse of a particular random number generator, it is recommended you do so here, rather than rely on skip(). This isn't always easy, but should always be possible for any decent PRNG (some historical PRNGs, such as the Middle-Square PRNG, cannot be reversed at all). If a generator cannot be reversed because multiple initial states can transition to the same subsequent state, it is known to have statistical problems that are not necessarily present in a generator that matches one initial state to one subsequent state.
The public implementation calls skip(long) with -1L, and if skip() has not been implemented differently, then it will throw an UnsupportedOperationException.

Returns:

the previous number this would have produced with nextLong()

previousInt

public int previousInt()

Optional; moves the state to its previous value and returns the previous int that would have been produced by nextInt(). This can be equivalent to calling previousLong() and casting to int, but not always; generators that natively generate int results typically move the state once in nextInt() and twice in nextLong(), and should move the state back once here.
If nextInt() is implemented using a call to nextLong(), the implementation in this class is almost always sufficient and correct. If nextInt() changes state differently from nextLong(), then this should be implemented, if feasible, and previousLong() can be implemented using this method. If you know how to implement the reverse of a particular random number generator, it is recommended you do so here, rather than rely on skip(). This isn't always easy, but should always be possible for any decent PRNG (some historical PRNGs, such as the Middle-Square PRNG, cannot be reversed at all). If a generator cannot be reversed because multiple initial states can transition to the same subsequent state, it is known to have statistical problems that are not necessarily present in a generator that matches one initial state to one subsequent state.
The public implementation calls previousLong() and casts it to int, and if previousLong() and skip() have not been implemented differently, then it will throw an UnsupportedOperationException.

Returns:

the previous number this would have produced with nextInt()

copy

public abstract EnhancedRandom copy()

Creates a new EnhancedRandom with identical states to this one, so if the same EnhancedRandom methods are called on this object and its copy (in the same order), the same outputs will be produced. This is not guaranteed to copy the inherited state of any parent class, so if you call methods that are only implemented by a superclass (like Random) and not this one, the results may differ.

Returns:

a deep copy of this EnhancedRandom.

setWith

public void setWith(EnhancedRandom other)

Similar to copy(), but fills this EnhancedRandom with the state of another EnhancedRandom, usually (but not necessarily) one of the same type. If this class has the same getStateCount() as other's class, then this method copies the full state of other into this object. Otherwise, if this class has a larger state count than other's class, then all of other's state is copied into the same selections in this object, and the rest of this object's state is filled with -1L using setSelectedState(int, long). If this class has a smaller state count than other's class, then only part of other's state is copied, and this method stops when all of this object's states have been assigned.
If this class has restrictions on its state, they will be respected by the public implementation of this method as long as setSelectedState(int, long) behaves correctly for those restrictions. Note that this method will public to throwing an UnsupportedOperationException unless getSelectedState(int) is implemented by other so its state can be accessed. This may also behave badly if setSelectedState(int, long) isn't implemented (it may be fine for some cases where the state count is 1, but don't count on it). If other's class doesn't implement getStateCount(), then this method sets the entire state of this object to -1L; if this class doesn't implement getStateCount(), then this method does nothing.

Parameters:

other - another EnhancedRandom, typically with the same class as this one, to copy its state into this

probit

public static double probit(double d)

A way of taking a double in the (0.0, 1.0) range and mapping it to a Gaussian or normal distribution, so high inputs correspond to high outputs, and similarly for the low range. This is centered on 0.0 and its standard deviation seems to be 1.0 (the same as Random.nextGaussian()). If this is given an input of 0.0 or less, it returns -38.5, which is slightly less than the result when given Double.MIN_VALUE. If it is given an input of 1.0 or more, it returns 38.5, which is significantly larger than the result when given the largest double less than 1.0 (this value is further from 1.0 than Double.MIN_VALUE is from 0.0). If given Double.NaN, it returns whatever Math.copySign(double, double) returns for the arguments 38.5, Double.NaN, which is implementation-dependent. It uses an algorithm by Peter John Acklam, as implemented by Sherali Karimov. Original source. Information on the algorithm. Wikipedia's page on the probit function may help, but is more likely to just be confusing.
Acklam's algorithm and Karimov's implementation are both quite fast. This appears faster than generating Gaussian-distributed numbers using either the Box-Muller Transform or Marsaglia's Polar Method, though it isn't as precise and can't produce as extreme min and max results in the extreme cases they should appear. If given a typical uniform random double that's exclusive on 1.0, it won't produce a result higher than 8.209536145151493, and will only produce results of at least -8.209536145151493 if 0.0 is excluded from the inputs (if 0.0 is an input, the result is -38.5). A chief advantage of using this with a random number generator is that it only requires one random double to obtain one Gaussian value; Random.nextGaussian() generates at least two random doubles for each two Gaussian values, but may rarely require much more random generation. Note that this method isn't used by default for nextGaussian(), because it uses a very different approximation that is faster but less precise.
This can be used both as an optimization for generating Gaussian random values, and as a way of generating Gaussian values that match a pattern present in the inputs (which you could have by using a sub-random sequence as the input, such as those produced by a van der Corput, Halton, Sobol or R2 sequence). Most methods of generating Gaussian values (e.g. Box-Muller and Marsaglia polar) do not have any way to preserve a particular pattern.

Parameters:

d - should be between 0 and 1, exclusive, but other values are tolerated

Returns:

a normal-distributed double centered on 0.0; all results will be between -38.5 and 38.5, both inclusive

fixGamma

public static long fixGamma(long gamma)

Attempts to improve the quality of a "gamma" increment for an additive sequence. This is stricter than the checks in Java 8's SplittableRandom. The goal here is to make sure the gamma is "sufficiently random" to avoid patterns when used as an increment. Examples of gamma values that aren't random enough include 1L, 3L, 0xFFFFFFFFFFFFFFFFL, 0xAAAAAAAAAAAAAAABL, and so on. It rejects any gamma value where any of four bit counts are less than 24 or greater than 40. The values that have their bits counted are:

• The gamma itself,
• The Gray code of the gamma, defined as (gamma ^ (gamma >>> 1)),
• The MathTools.modularMultiplicativeInverse(long) of the gamma,
• And the Gray code of the above inverse of the gamma.

If a gamma is rejected, this multiplies it by an LCG constant, 0xD1342543DE82EF95L, adds an increasing even number (first 2, then 4, then 6, and so on) and tries again repeatedly. It returns the first gamma that wasn't rejected, which could be the original gamma.
This simply calls fixGamma(long, int) with the given gamma and a threshold of 8.

Parameters:

gamma - any long, though almost always an odd number, that would be added as an increment in a sequence

Returns:

gamma or a modification upon it such that its bits are "sufficiently random" to be a good increment

See Also:

• This was informed by O'Neill's blog post about SplittableRandom's gamma.

fixGamma

public static long fixGamma(long gamma,
 int threshold)

Attempts to improve the quality of a "gamma" increment for an additive sequence. This is stricter than the checks in Java 8's SplittableRandom. The goal here is to make sure the gamma is "sufficiently random" to avoid patterns when used as an increment. Examples of gamma values that aren't random enough include 1L, 3L, 0xFFFFFFFFFFFFFFFFL, 0xAAAAAAAAAAAAAAABL, and so on. It rejects any gamma value where any of four bit counts are less than 32 - threshold or greater than 32 + threshold. The values that have their bits counted are:

• The gamma itself,
• The Gray code of the gamma, defined as (gamma ^ (gamma >>> 1)),
• The MathTools.modularMultiplicativeInverse(long) of the gamma,
• And the Gray code of the above inverse of the gamma.

If a gamma is rejected, this multiplies it by an LCG constant, 0xD1342543DE82EF95L, adds an increasing even number (first 2, then 4, then 6, and so on) and tries again repeatedly. It returns the first gamma that wasn't rejected, which could be the original gamma.

Parameters:

gamma - any long, though almost always an odd number, that would be added as an increment in a sequence

threshold - the maximum acceptable "score" as evaluated by rateGamma(long)

Returns:

gamma or a modification upon it such that its bits are "sufficiently random" to be a good increment

See Also:

• This was informed by O'Neill's blog post about SplittableRandom's gamma.

rateGamma

public static int rateGamma(long gamma)

Attempts to check the quality of a "gamma" increment for an additive sequence. This is stricter than the checks in Java 8's SplittableRandom. The goal here is to see if the gamma is "sufficiently random" to avoid patterns when used as an increment. Examples of gamma values that aren't random enough include 1L, 3L, 0xFFFFFFFFFFFFFFFFL, 0xAAAAAAAAAAAAAAABL, and so on. It returns the "score" for any gamma value, where the score is the maximum difference of four bit counts from an ideal of 32. The values that have their bits counted are:

• The gamma itself,
• The Gray code of the gamma, defined as (gamma ^ (gamma >>> 1)),
• The MathTools.modularMultiplicativeInverse(long) of the gamma,
• And the Gray code of the above inverse of the gamma.

A score of 9 can typically be considered "potentially problematic," and though it isn't necessarily a real problem, there are so many other possible gammas that it should be avoided. Scores higher than 9 can be considered more "problematic," and scores less than 9 are probably fine for SplitMix gammas.
If the given gamma is even, it is not suitable as a SplitMix gamma automatically, and the maximum (worst) rating is returned, 32.

Parameters:

gamma - any long, though almost always an odd number, that would be added as an increment in a sequence

Returns:

how far the given gamma is from an optimal score of 0

See Also:

• This was informed by O'Neill's blog post about SplittableRandom's gamma.

areEqual

public static boolean areEqual(EnhancedRandom left,
 EnhancedRandom right)

Given two EnhancedRandom objects that could have the same or different classes, this returns true if they have the same class and same state, or false otherwise. Both of the arguments should implement getSelectedState(int), or this will throw an UnsupportedOperationException. This can be useful for comparing EnhancedRandom classes that do not implement equals(), for whatever reason. This returns true if both arguments are null, but false if only one is null.

Parameters:

left - an EnhancedRandom to compare for equality

right - another EnhancedRandom to compare for equality

Returns:

true if the two EnhancedRandom objects have the same class and state, or false otherwise

nextBoolean

public boolean nextBoolean(float chance)

Returns true if a random value between 0 and 1 is less than the specified value.

Parameters:

chance - a float between 0.0 and 1.0; higher values are more likely to result in true

Returns:

a boolean selected with the given chance of being true

nextSign

public int nextSign()

Returns -1 or 1, randomly.

Returns:

-1 or 1, selected with approximately equal likelihood

nextTriangular

public float nextTriangular()

Returns a triangularly distributed random number between -1.0 (exclusive) and 1.0 (exclusive), where values around zero are more likely. Advances the state twice.

This is an optimized version of nextTriangular(-1, 1, 0)

nextTriangular

public float nextTriangular(float max)

Returns a triangularly distributed random number between -max (exclusive) and max (exclusive), where values around zero are more likely. Advances the state twice.

This is an optimized version of nextTriangular(-max, max, 0)

Parameters:

max - the upper limit

nextTriangular

public float nextTriangular(float min,
 float max)

Returns a triangularly distributed random number between min (inclusive) and max (exclusive), where the mode argument defaults to the midpoint between the bounds, giving a symmetric distribution. Advances the state once.

This method is equivalent to nextTriangular(min, max, (min + max) * 0.5f)

Parameters:

min - the lower limit

max - the upper limit

nextTriangular

public float nextTriangular(float min,
 float max,
 float mode)

Returns a triangularly distributed random number between min (inclusive) and max (exclusive), where values around mode are more likely. Advances the state once.

Parameters:

min - the lower limit

max - the upper limit

mode - the point around which the values are more likely

minIntOf

public int minIntOf(int innerBound,
 int outerBound,
 int trials)

Returns the minimum result of trials calls to nextSignedInt(int, int) using the given innerBound and outerBound. The innerBound is inclusive; the outerBound is exclusive. The higher trials is, the lower the average value this returns.

Parameters:

innerBound - the inner inclusive bound; may be positive or negative

outerBound - the outer exclusive bound; may be positive or negative

trials - how many random numbers to acquire and compare

Returns:

the lowest random number between innerBound (inclusive) and outerBound (exclusive) this found

maxIntOf

public int maxIntOf(int innerBound,
 int outerBound,
 int trials)

Returns the maximum result of trials calls to nextSignedInt(int, int) using the given innerBound and outerBound. The innerBound is inclusive; the outerBound is exclusive. The higher trials is, the higher the average value this returns.

Parameters:

innerBound - the inner inclusive bound; may be positive or negative

outerBound - the outer exclusive bound; may be positive or negative

trials - how many random numbers to acquire and compare

Returns:

the highest random number between innerBound (inclusive) and outerBound (exclusive) this found

minLongOf

public long minLongOf(long innerBound,
 long outerBound,
 int trials)

Returns the minimum result of trials calls to nextSignedLong(long, long) using the given innerBound and outerBound. The innerBound is inclusive; the outerBound is exclusive. The higher trials is, the lower the average value this returns.

Parameters:

innerBound - the inner inclusive bound; may be positive or negative

outerBound - the outer exclusive bound; may be positive or negative

trials - how many random numbers to acquire and compare

Returns:

the lowest random number between innerBound (inclusive) and outerBound (exclusive) this found

maxLongOf

public long maxLongOf(long innerBound,
 long outerBound,
 int trials)

Returns the maximum result of trials calls to nextSignedLong(long, long) using the given innerBound and outerBound. The innerBound is inclusive; the outerBound is exclusive. The higher trials is, the higher the average value this returns.

Parameters:

innerBound - the inner inclusive bound; may be positive or negative

outerBound - the outer exclusive bound; may be positive or negative

trials - how many random numbers to acquire and compare

Returns:

the highest random number between innerBound (inclusive) and outerBound (exclusive) this found

minDoubleOf

public double minDoubleOf(double innerBound,
 double outerBound,
 int trials)

Returns the minimum result of trials calls to nextDouble(double, double) using the given innerBound and outerBound. The innerBound is inclusive; the outerBound is exclusive. The higher trials is, the lower the average value this returns.

Parameters:

innerBound - the inner inclusive bound; may be positive or negative

outerBound - the outer exclusive bound; may be positive or negative

trials - how many random numbers to acquire and compare

Returns:

the lowest random number between innerBound (inclusive) and outerBound (exclusive) this found

maxDoubleOf

public double maxDoubleOf(double innerBound,
 double outerBound,
 int trials)

Returns the maximum result of trials calls to nextDouble(double, double) using the given innerBound and outerBound. The innerBound is inclusive; the outerBound is exclusive. The higher trials is, the higher the average value this returns.

Parameters:

innerBound - the inner inclusive bound; may be positive or negative

outerBound - the outer exclusive bound; may be positive or negative

trials - how many random numbers to acquire and compare

Returns:

the highest random number between innerBound (inclusive) and outerBound (exclusive) this found

minFloatOf

public float minFloatOf(float innerBound,
 float outerBound,
 int trials)

Returns the minimum result of trials calls to nextFloat(float, float) using the given innerBound and outerBound. The innerBound is inclusive; the outerBound is exclusive. The higher trials is, the lower the average value this returns.

Parameters:

innerBound - the inner inclusive bound; may be positive or negative

outerBound - the outer exclusive bound; may be positive or negative

trials - how many random numbers to acquire and compare

Returns:

the lowest random number between innerBound (inclusive) and outerBound (exclusive) this found

maxFloatOf

public float maxFloatOf(float innerBound,
 float outerBound,
 int trials)

Returns the maximum result of trials calls to nextFloat(float, float) using the given innerBound and outerBound. The innerBound is inclusive; the outerBound is exclusive. The higher trials is, the higher the average value this returns.

Parameters:

innerBound - the inner inclusive bound; may be positive or negative

outerBound - the outer exclusive bound; may be positive or negative

trials - how many random numbers to acquire and compare

Returns:

the highest random number between innerBound (inclusive) and outerBound (exclusive) this found

randomElement

public <T> T randomElement(T[] array)

Gets a randomly-selected item from the given array, which must be non-null and non-empty

Type Parameters:

T - any reference type

Parameters:

array - a non-null, non-empty array of T items

Returns:

a random item from array

Throws:

NullPointerException - if array is null

IndexOutOfBoundsException - if array is empty

randomElement

public <T> T randomElement(List<T> list)

Gets a randomly selected item from the given List, such as an ArrayList. If the List is empty, this throws an IndexOutOfBoundsException.

Type Parameters:

T - the type of items

Parameters:

list - a non-empty implementation of List, such as ArrayList

Returns:

a randomly-selected item from list

shuffle

public void shuffle(int[] items)

Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - an int array; must be non-null

shuffle

public void shuffle(int[] items,
 int offset,
 int length)

Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - an int array; must be non-null

offset - the index of the first element of the array that can be shuffled

length - the length of the section to shuffle

shuffle

public void shuffle(long[] items)

Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - a long array; must be non-null

shuffle

public void shuffle(long[] items,
 int offset,
 int length)

Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - a long array; must be non-null

offset - the index of the first element of the array that can be shuffled

length - the length of the section to shuffle

shuffle

public void shuffle(float[] items)

Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - a float array; must be non-null

shuffle

public void shuffle(float[] items,
 int offset,
 int length)

Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - a float array; must be non-null

offset - the index of the first element of the array that can be shuffled

length - the length of the section to shuffle

shuffle

public void shuffle(char[] items)

Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - a char array; must be non-null

shuffle

public void shuffle(char[] items,
 int offset,
 int length)

Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - a char array; must be non-null

offset - the index of the first element of the array that can be shuffled

length - the length of the section to shuffle

shuffle

public void shuffle(byte[] items)

Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - a byte array; must be non-null

shuffle

public void shuffle(byte[] items,
 int offset,
 int length)

Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - a byte array; must be non-null

offset - the index of the first element of the array that can be shuffled

length - the length of the section to shuffle

shuffle

public void shuffle(double[] items)

Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - a double array; must be non-null

shuffle

public void shuffle(double[] items,
 int offset,
 int length)

Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - a double array; must be non-null

offset - the index of the first element of the array that can be shuffled

length - the length of the section to shuffle

shuffle

public void shuffle(short[] items)

Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - a short array; must be non-null

shuffle

public void shuffle(short[] items,
 int offset,
 int length)

Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - a short array; must be non-null

offset - the index of the first element of the array that can be shuffled

length - the length of the section to shuffle

shuffle

public void shuffle(boolean[] items)

Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - a boolean array; must be non-null

shuffle

public void shuffle(boolean[] items,
 int offset,
 int length)

Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - a boolean array; must be non-null

offset - the index of the first element of the array that can be shuffled

length - the length of the section to shuffle

shuffle

public <T> void shuffle(T[] items)

Shuffles the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - an array of some reference type; must be non-null but may contain null items

shuffle

public <T> void shuffle(T[] items,
 int offset,
 int length)

Shuffles a section of the given array in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - an array of some reference type; must be non-null but may contain null items

offset - the index of the first element of the array that can be shuffled

length - the length of the section to shuffle

shuffle

public <T> void shuffle(List<T> items)

Shuffles the given List in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - a List of some type T; must be non-null but may contain null items

shuffle

public <T> void shuffle(List<T> items,
 int offset,
 int length)

Shuffles a section of the given List in-place pseudo-randomly, using this to determine how to shuffle.

Parameters:

items - a List of some type T; must be non-null but may contain null items

offset - the index of the first element of the array that can be shuffled

length - the length of the section to shuffle

stringSerialize

public String stringSerialize()

Serializes the current state of this EnhancedRandom to a String that can be used by stringDeserialize(String) to load this state at another time. This always uses Base.BASE16 for its conversions.

Returns:

a String storing all data from the EnhancedRandom part of this generator

stringSerialize

public String stringSerialize(com.github.tommyettinger.digital.Base base)

Serializes the current state of this EnhancedRandom to a String that can be used by stringDeserialize(String) to load this state at another time. May use any Base; Base.BASE10 and Base.BASE16 are the most intuitive, but Base.SIMPLE64 and especially Base.BASE90 will be more compact.

Parameters:

base - which Base to use, from the "digital" library, such as Base.BASE10

Returns:

a String storing all data from the EnhancedRandom part of this generator

appendSerialized

public <T extends CharSequence & Appendable> T appendSerialized(T sb)

Serializes the current state of this EnhancedRandom and appends it to an Appendable CharSequence (such as a StringBuilder), which may be used by stringDeserialize(String) to load this state at another time. Always uses base 16.

Type Parameters:

T - any type that is both a CharSequence and an Appendable, such as StringBuilder, StringBuffer, or CharBuffer

Parameters:

sb - an Appendable CharSequence that will be modified

Returns:

sb, for chaining

appendSerialized

public <T extends CharSequence & Appendable> T appendSerialized(T sb,
 com.github.tommyettinger.digital.Base base)

Serializes the current state of this EnhancedRandom and appends it to an Appendable CharSequence (such as a StringBuilder), which may be used by stringDeserialize(String) to load this state at another time. May use any Base; Base.BASE10 and Base.BASE16 are the most intuitive, but Base.SIMPLE64 and especially Base.BASE90 will be more compact.

Type Parameters:

T - any type that is both a CharSequence and an Appendable, such as StringBuilder, StringBuffer, or CharBuffer

Parameters:

sb - an Appendable CharSequence that will be modified

base - which Base to use, from the "digital" library, such as Base.BASE10

Returns:

sb, for chaining

stringDeserialize

public EnhancedRandom stringDeserialize(String data)

Given a String in the format produced by stringSerialize(), this will attempt to set this EnhancedRandom object to match the state in the serialized data. This only works if this EnhancedRandom is the same implementation that was serialized. Always uses Base.BASE16. Returns this EnhancedRandom, after possibly changing its state.

Parameters:

data - a String probably produced by stringSerialize()

Returns:

this, after setting its state

See Also:

• You can deserialize a serialized EnhancedRandom String to its correct type using Deserializer.

stringDeserialize

public EnhancedRandom stringDeserialize(String data,
 com.github.tommyettinger.digital.Base base)

Given a String in the format produced by stringSerialize(Base), and the same Base used by the serialization, this will attempt to set this EnhancedRandom object to match the state in the serialized data. This only works if this EnhancedRandom is the same implementation that was serialized, and also needs the Bases to be identical. Returns this EnhancedRandom, after possibly changing its state.

Parameters:

data - a String probably produced by stringSerialize(Base)

base - which Base to use, from the "digital" library, such as Base.BASE10

Returns:

this, after setting its state

See Also:

• You can deserialize a serialized EnhancedRandom String to its correct type using Deserializer.

writeExternal

public void writeExternal(ObjectOutput out)
                   throws IOException

The object implements the writeExternal method to save its contents by calling the methods of DataOutput for its primitive values or calling the writeObject method of ObjectOutput for objects, strings, and arrays.

Specified by:

writeExternal in interface Externalizable

Parameters:

out - the stream to write the object to

Throws:

IOException - Includes any I/O exceptions that may occur

readExternal

public void readExternal(ObjectInput in)
                  throws IOException,
ClassNotFoundException

The object implements the readExternal method to restore its contents by calling the methods of DataInput for primitive types and readObject for objects, strings and arrays. The readExternal method must read the values in the same sequence and with the same types as were written by writeExternal.

Specified by:

readExternal in interface Externalizable

Parameters:

in - the stream to read data from in order to restore the object

Throws:

IOException - if I/O errors occur

ClassNotFoundException