public class ThreadLocalRandom extends Random
Random
generator used by the Math
class, a ThreadLocalRandom
is initialized
with an internally generated seed that may not otherwise be
modified. When applicable, use of ThreadLocalRandom
rather
than shared Random
objects in concurrent programs will
typically encounter much less overhead and contention. Use of
ThreadLocalRandom
is particularly appropriate when multiple
tasks (for example, each a ForkJoinTask
) use random numbers
in parallel in thread pools.
Usages of this class should typically be of the form:
ThreadLocalRandom.current().nextX(...)
(where
X
is Int
, Long
, etc).
When all usages are of this form, it is never possible to
accidently share a ThreadLocalRandom
across multiple threads.
This class also provides additional commonly used bounded random generation methods.
Modifier and Type  Method and Description 

static ThreadLocalRandom 
current()
Returns the current thread's
ThreadLocalRandom . 
DoubleStream 
doubles()
Returns a stream of pseudorandom, uniformly distributed
double values between 0.0 and 1.0
from this random number generator's sequence. 
DoubleStream 
gaussians()
Returns a stream of pseudorandom, Gaussian ("normally")
distributed
double values with mean 0.0
and standard deviation 1.0 from this random number
generator's sequence. 
IntStream 
ints()
Returns a stream of pseudorandom, uniformly distributed
integer values from this random number generator's
sequence. 
LongStream 
longs()
Returns a stream of pseudorandom, uniformly distributed
long values from this random number generator's
sequence. 
protected int 
next(int bits)
Generates the next pseudorandom number.

double 
nextDouble(double n)
Returns a pseudorandom, uniformly distributed
double value
between 0 (inclusive) and the specified value (exclusive). 
double 
nextDouble(double least,
double bound)
Returns a pseudorandom, uniformly distributed value between the
given least value (inclusive) and bound (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. 
int 
nextInt(int least,
int bound)
Returns a pseudorandom, uniformly distributed value between the
given least value (inclusive) and bound (exclusive).

long 
nextLong(long n)
Returns a pseudorandom, uniformly distributed value
between 0 (inclusive) and the specified value (exclusive).

long 
nextLong(long least,
long bound)
Returns a pseudorandom, uniformly distributed value between the
given least value (inclusive) and bound (exclusive).

void 
setSeed(long seed)
Throws
UnsupportedOperationException . 
nextBoolean, nextBytes, nextDouble, nextFloat, nextInt, nextInt, nextLong
public static ThreadLocalRandom current()
ThreadLocalRandom
.ThreadLocalRandom
public void setSeed(long seed)
UnsupportedOperationException
. Setting seeds in
this generator is not supported.setSeed
in class Random
seed
 the initial seedUnsupportedOperationException
 alwaysprotected int next(int bits)
Random
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 loworder
bits of the returned value will be (approximately) independently
chosen bit values, each of which is (approximately) equally
likely to be 0
or 1
. The method next
is
implemented by class Random
by atomically updating the seed to
(seed * 0x5DEECE66DL + 0xBL) & ((1L << 48)  1)
and returning
(int)(seed >>> (48  bits))
.
This is a linear congruential pseudorandom number generator, as
defined by D. H. Lehmer and described by Donald E. Knuth in
The Art of Computer Programming, Volume 3:
Seminumerical Algorithms, section 3.2.1.public int nextInt(int least, int bound)
least
 the least value returnedbound
 the upper bound (exclusive)IllegalArgumentException
 if least greater than or equal
to boundpublic long nextLong(long n)
n
 the bound on the random number to be returned. Must be
positive.IllegalArgumentException
 if n is not positivepublic IntStream ints()
Random
integer
values from this random number generator's
sequence. Values are obtained as needed by calling
Random.nextInt()
.public LongStream longs()
Random
long
values from this random number generator's
sequence. Values are obtained as needed by calling
Random.nextLong()
.public DoubleStream doubles()
Random
double
values between 0.0
and 1.0
from this random number generator's sequence. Values are
obtained as needed by calling Random.nextDouble()
.public DoubleStream gaussians()
Random
double
values with mean 0.0
and standard deviation 1.0
from this random number
generator's sequence. Values are obtained as needed by
calling Random.nextGaussian()
.public long nextLong(long least, long bound)
least
 the least value returnedbound
 the upper bound (exclusive)IllegalArgumentException
 if least greater than or equal
to boundpublic double nextDouble(double n)
double
value
between 0 (inclusive) and the specified value (exclusive).n
 the bound on the random number to be returned. Must be
positive.IllegalArgumentException
 if n is not positivepublic double nextDouble(double least, double bound)
least
 the least value returnedbound
 the upper bound (exclusive)IllegalArgumentException
 if least greater than or equal
to boundpublic double nextGaussian()
Random
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.
The method nextGaussian
is implemented by class
Random
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;
}
}
This uses the polar method of G. E. P. Box, M. E. Muller, and
G. Marsaglia, as described by Donald E. Knuth in The Art of
Computer Programming, Volume 3: Seminumerical Algorithms,
section 3.4.1, subsection C, algorithm P. Note that it generates two
independent values at the cost of only one call to StrictMath.log
and one call to StrictMath.sqrt
.nextGaussian
in class Random
double
value with mean 0.0
and
standard deviation 1.0
from this random number
generator's sequence
For further API reference and developer documentation, see Java SE Documentation. That documentation contains more detailed, developertargeted descriptions, with conceptual overviews, definitions of terms, workarounds, and working code examples.
Copyright © 1993, 2013, Oracle and/or its affiliates. All rights reserved.
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