- All Implemented Interfaces:
-
Serializable
,RandomGenerator
- Direct Known Subclasses:
-
SecureRandom
,ThreadLocalRandom
public class Random extends RandomSupport.AbstractSpliteratorGenerator implements Serializable
If two instances of Random
are created with the same seed, and the same sequence of method calls is made for each, they will generate and return identical sequences of numbers. In order to guarantee this property, particular algorithms are specified for the class Random
. Java implementations must use all the algorithms shown here for the class Random
, for the sake of absolute portability of Java code. However, subclasses of class Random
are permitted to use other algorithms, so long as they adhere to the general contracts for all the methods.
The algorithms implemented by class Random
use a protected
utility method that on each invocation can supply up to 32 pseudorandomly generated bits.
Many applications will find the method Math.random()
simpler to use.
Instances of java.util.Random
are threadsafe. However, the concurrent use of the same java.util.Random
instance across threads may encounter contention and consequent poor performance. Consider instead using ThreadLocalRandom
in multithreaded designs.
Instances of java.util.Random
are not cryptographically secure. Consider instead using SecureRandom
to get a cryptographically secure pseudo-random number generator for use by security-sensitive applications.
- Since:
- 1.0
- See Also:
- Serialized Form
-
Nested Class Summary
Nested classes/interfaces declared in interface java.util.random.RandomGenerator
RandomGenerator.ArbitrarilyJumpableGenerator, RandomGenerator.JumpableGenerator, RandomGenerator.LeapableGenerator, RandomGenerator.RandomGeneratorProperty, RandomGenerator.SplittableGenerator, RandomGenerator.StreamableGenerator
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Field Summary
Fields declared in interface java.util.random.RandomGenerator
HUGE_PERIOD, TRULY_RANDOM, UNKNOWN_PERIOD
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionprotected int
next(int bits)
Generates the next pseudorandom number.boolean
Returns the next pseudorandom, uniformly distributedboolean
value from this random number generator's sequence.void
nextBytes(byte[] bytes)
Generates random bytes and places them into a user-supplied byte array.double
Returns the next pseudorandom, uniformly distributeddouble
value between0.0
and1.0
from this random number generator's sequence.float
Returns the next pseudorandom, uniformly distributedfloat
value between0.0
and1.0
from this random number generator's sequence.double
Returns the next pseudorandom, Gaussian ("normally") distributeddouble
value with mean0.0
and standard deviation1.0
from this random number generator's sequence.int
nextInt()
Returns the next pseudorandom, uniformly distributedint
value from this random number generator's sequence.int
nextInt(int bound)
Returns a pseudorandomint
value between zero (inclusive) and the specified bound (exclusive).long
nextLong()
Returns the next pseudorandom, uniformly distributedlong
value from this random number generator's sequence.void
setSeed(long seed)
Sets the seed of this random number generator using a singlelong
seed.Methods declared in class jdk.internal.util.random.RandomSupport.AbstractSpliteratorGenerator
doubles, doubles, doubles, doubles, ints, ints, ints, ints, longs, longs, longs, longs, makeDoublesSpliterator, makeIntsSpliterator, makeLongsSpliterator
Methods declared in class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
Methods declared in interface java.util.random.RandomGenerator
nextDouble, nextDouble, nextExponential, nextFloat, nextFloat, nextGaussian, nextInt, nextLong, nextLong
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Constructor Details
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Random
public Random()Creates a new random number generator. This constructor sets the seed of the random number generator to a value very likely to be distinct from any other invocation of this constructor. -
Random
public Random(long seed)Creates a new random number generator using a singlelong
seed. The seed is the initial value of the internal state of the pseudorandom number generator which is maintained by methodnext(int)
.The invocation
new Random(seed)
is equivalent to:Random rnd = new Random(); rnd.setSeed(seed);
- Parameters:
-
seed
- the initial seed - See Also:
-
setSeed(long)
-
-
Method Details
-
setSeed
public void setSeed(long seed)Sets the seed of this random number generator using a singlelong
seed. The general contract ofsetSeed
is that it alters the state of this random number generator object so as to be in exactly the same state as if it had just been created with the argumentseed
as a seed. The methodsetSeed
is implemented by classRandom
by atomically updating the seed to(seed ^ 0x5DEECE66DL) & ((1L << 48) - 1)
haveNextNextGaussian
flag used bynextGaussian()
.The implementation of
setSeed
by classRandom
happens to use only 48 bits of the given seed. In general, however, an overriding method may use all 64 bits of thelong
argument as a seed value.- Parameters:
-
seed
- the initial seed
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next
protected int next(int bits)Generates the next pseudorandom number. Subclasses should override this, as this is used by all other methods.The general contract of
next
is that it returns anint
value and if the argumentbits
is between1
and32
(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 be0
or1
. The methodnext
is implemented by classRandom
by atomically updating the seed to(seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1)
(int)(seed >>> (48 - bits))
.- Parameters:
-
bits
- random bits - Returns:
- the next pseudorandom value from this random number generator's sequence
- Since:
- 1.1
-
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.The method
nextBytes
is implemented by classRandom
as if by:public void nextBytes(byte[] bytes) { for (int i = 0; i < bytes.length; ) for (int rnd = nextInt(), n = Math.min(bytes.length - i, 4); n-- > 0; rnd >>= 8) bytes[i++] = (byte)rnd; }
- Specified by:
-
nextBytes
in interfaceRandomGenerator
- Parameters:
-
bytes
- the byte array to fill with random bytes - Throws:
-
NullPointerException
- if the byte array is null - Since:
- 1.1
-
nextInt
public int nextInt()Returns the next pseudorandom, uniformly distributedint
value from this random number generator's sequence. The general contract ofnextInt
is that oneint
value is pseudorandomly generated and returned. All 232 possibleint
values are produced with (approximately) equal probability.The method
nextInt
is implemented by classRandom
as if by:public int nextInt() { return next(32); }
- Specified by:
-
nextInt
in interfaceRandomGenerator
- Returns:
-
the next pseudorandom, uniformly distributed
int
value from this random number generator's sequence
-
nextInt
public int nextInt(int bound)Returns a pseudorandomint
value between zero (inclusive) and the specified bound (exclusive).- Specified by:
-
nextInt
in interfaceRandomGenerator
- Parameters:
-
bound
- the upper bound (exclusive). Must be positive. - Returns:
-
a pseudorandom
int
value between zero (inclusive) and the bound (exclusive) - Throws:
-
IllegalArgumentException
- ifbound
is not positive
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nextLong
public long nextLong()Returns the next pseudorandom, uniformly distributedlong
value from this random number generator's sequence. The general contract ofnextLong
is that onelong
value is pseudorandomly generated and returned.The method
nextLong
is implemented by classRandom
as if by:public long nextLong() { return ((long)next(32) << 32) + next(32); }
Random
uses a seed with only 48 bits, this algorithm will not return all possiblelong
values.- Specified by:
-
nextLong
in interfaceRandomGenerator
- Returns:
-
the next pseudorandom, uniformly distributed
long
value from this random number generator's sequence
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nextBoolean
public boolean nextBoolean()Returns the next pseudorandom, uniformly distributedboolean
value from this random number generator's sequence. The general contract ofnextBoolean
is that oneboolean
value is pseudorandomly generated and returned. The valuestrue
andfalse
are produced with (approximately) equal probability.The method
nextBoolean
is implemented by classRandom
as if by:public boolean nextBoolean() { return next(1) != 0; }
- Specified by:
-
nextBoolean
in interfaceRandomGenerator
- Returns:
-
the next pseudorandom, uniformly distributed
boolean
value from this random number generator's sequence - Since:
- 1.2
-
nextFloat
public float nextFloat()Returns the next pseudorandom, uniformly distributedfloat
value between0.0
and1.0
from this random number generator's sequence.The general contract of
nextFloat
is that onefloat
value, chosen (approximately) uniformly from the range0.0f
(inclusive) to1.0f
(exclusive), is pseudorandomly generated and returned. All 224 possiblefloat
values of the form m x 2-24, where m is a positive integer less than 224, are produced with (approximately) equal probability.The method
nextFloat
is implemented by classRandom
as if by:public float nextFloat() { return next(24) / ((float)(1 << 24)); }
The hedge "approximately" is used in the foregoing description only because the next method is only approximately an unbiased source of independently chosen bits. If it were a perfect source of randomly chosen bits, then the algorithm shown would choose
float
values from the stated range with perfect uniformity.[In early versions of Java, the result was incorrectly calculated as:
return next(30) / ((float)(1 << 30));
- Specified by:
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nextFloat
in interfaceRandomGenerator
- Returns:
-
the next pseudorandom, uniformly distributed
float
value between0.0
and1.0
from this random number generator's sequence
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nextDouble
public double nextDouble()Returns the next pseudorandom, uniformly distributeddouble
value between0.0
and1.0
from this random number generator's sequence.The general contract of
nextDouble
is that onedouble
value, chosen (approximately) uniformly from the range0.0d
(inclusive) to1.0d
(exclusive), is pseudorandomly generated and returned.The method
nextDouble
is implemented by classRandom
as if by:public double nextDouble() { return (((long)next(26) << 27) + next(27)) / (double)(1L << 53); }
The hedge "approximately" is used in the foregoing description only because the
next
method is only approximately an unbiased source of independently chosen bits. If it were a perfect source of randomly chosen bits, then the algorithm shown would choosedouble
values from the stated range with perfect uniformity.[In early versions of Java, the result was incorrectly calculated as:
return (((long)next(27) << 27) + next(27)) / (double)(1L << 54);
- Specified by:
-
nextDouble
in interfaceRandomGenerator
- Returns:
-
the next pseudorandom, uniformly distributed
double
value between0.0
and1.0
from this random number generator's sequence - See Also:
-
Math.random()
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nextGaussian
public double nextGaussian()Returns the next pseudorandom, Gaussian ("normally") distributeddouble
value with mean0.0
and standard deviation1.0
from this random number generator's sequence.The general contract of
nextGaussian
is that onedouble
value, chosen from (approximately) the usual normal distribution with mean0.0
and standard deviation1.0
, is pseudorandomly generated and returned.The method
nextGaussian
is implemented by classRandom
as if by a threadsafe version of the following:private double nextNextGaussian; private boolean haveNextNextGaussian = false; public double nextGaussian() { if (haveNextNextGaussian) { haveNextNextGaussian = false; return nextNextGaussian; } else { double v1, v2, s; do { v1 = 2 * nextDouble() - 1; // between -1.0 and 1.0 v2 = 2 * nextDouble() - 1; // between -1.0 and 1.0 s = v1 * v1 + v2 * v2; } while (s >= 1 || s == 0); double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)/s); nextNextGaussian = v2 * multiplier; haveNextNextGaussian = true; return v1 * multiplier; } }
StrictMath.log
and one call toStrictMath.sqrt
.- Specified by:
-
nextGaussian
in interfaceRandomGenerator
- Returns:
-
the next pseudorandom, Gaussian ("normally") distributed
double
value with mean0.0
and standard deviation1.0
from this random number generator's sequence
-