Random (Java Platform SE 7 )
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Class Random
java.util.Random
All Implemented Interfaces:
Direct Known Subclasses:
public class Random
implements
An instance of this class is used to generate a stream of
pseudorandom numbers. The class uses a 48-bit seed, which is
modified using a linear congruential formula. (See Donald Knuth,
The Art of Computer Programming, Volume 2, Section 3.2.1.)
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
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
in multithreaded
Instances of java.util.Random are not cryptographically
Consider instead using
get a cryptographically secure pseudo-random number generator for use
by security-sensitive applications.
Constructor Summary
Constructors&
Constructor and Description
Creates a new random number generator.
(long&seed)
Creates a new random number generator using a single long seed.
Method Summary
Modifier and Type
Method and Description
protected int
(int&bits)
Generates the next pseudorandom number.
Returns the next pseudorandom, uniformly distributed
boolean value from this random number generator's
(byte[]&bytes)
Generates random bytes and places them into a user-supplied
byte array.
Returns the next pseudorandom, uniformly distributed
double value between 0.0 and
1.0 from this random number generator's sequence.
Returns the next pseudorandom, uniformly distributed float
value between 0.0 and 1.0 from this random
number generator's sequence.
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.
Returns the next pseudorandom, uniformly distributed int
value from this random number generator's sequence.
Returns a pseudorandom, uniformly distributed int value
between 0 (inclusive) and the specified value (exclusive), drawn from
this random number generator's sequence.
Returns the next pseudorandom, uniformly distributed long
value from this random number generator's sequence.
(long&seed)
Sets the seed of this random number generator using a single
long seed.
Methods inherited from class&java.lang.
, , , , , , , , , ,
Constructor Detail
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.
public&Random(long&seed)
Creates a new random number generator using a single long seed.
The seed is the initial value of the internal state of the pseudorandom
number generator which is maintained by method .
The invocation new Random(seed) is equivalent to:
Random rnd = new Random();
rnd.setSeed(seed);
Parameters:seed - the initial seedSee Also:
Method Detail
public&void&setSeed(long&seed)
Sets the seed of this random number generator using a single
long seed. The general contract of setSeed 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 argument seed as a seed. The method
setSeed is implemented by class Random by
atomically updating the seed to
(seed ^ 0x5DEECE66DL) & ((1L && 48) - 1)
and clearing the haveNextNextGaussian flag used by .
The implementation of setSeed by class Random
happens to use only 48 bits of the given seed. In general, however,
an overriding method may use all 64 bits of the long
argument as a seed value.
Parameters:seed - the initial seed
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 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. 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.
Parameters:bits - random bits
Returns:the next pseudorandom value from this random number
generator's sequenceSince:
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 class Random
public void nextBytes(byte[] bytes) {
for (int i = 0; i & bytes. )
for (int rnd = nextInt(), n = Math.min(bytes.length - i, 4);
n-- & 0; rnd &&= 8)
bytes[i++] = (byte)
Parameters:bytes - the byte array to fill with random bytes
- if the byte array is nullSince:
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.
The method nextInt is implemented by class Random
public int nextInt() {
return next(32);
Returns:the next pseudorandom, uniformly distributed int
value from this random number generator's sequence
public&int&nextInt(int&n)
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 n possible
int values are produced with (approximately) equal
probability.
The method nextInt(int n) is implemented by
class Random as if by:
public int nextInt(int n) {
if (n &= 0)
throw new IllegalArgumentException("n must be positive");
if ((n & -n) == n)
// i.e., n is a power of 2
return (int)((n * (long)next(31)) && 31);
bits = next(31);
val = bits %
} while (bits - val + (n-1) & 0);
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 int
values from the stated range with perfect uniformity.
The algorithm is slightly tricky.
It rejects values that would result
in an uneven distribution (due to the fact that 2^31 is not divisible
by n). The probability of a value being rejected depends on n.
worst case is n=2^30+1, for which the probability of a reject is 1/2,
and the expected number of iterations before the loop terminates is 2.
The algorithm treats the case where n is a power of two specially: it
returns the correct number of high-order bits from the underlying
pseudo-random number generator.
In the absence of special treatment,
the correct number of low-order bits would be returned.
congruential pseudo-random number generators such as the one
implemented by this class are known to have short periods in the
sequence of values of their low-order bits.
Thus, this special case
greatly increases the length of the sequence of values returned by
successive calls to this method if n is a small power of two.
Parameters:n - the bound on the random number to be returned.
Returns:the next pseudorandom, uniformly distributed int
value between 0 (inclusive) and n (exclusive)
from this random number generator's sequence
- if n is not positiveSince:
public&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 method nextLong is implemented by class Random
public long nextLong() {
return ((long)next(32) && 32) + next(32);
Because class Random uses a seed with only 48 bits,
this algorithm will not return all possible long values.
Returns:the next pseudorandom, uniformly distributed long
value from this random number generator's sequence
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.
values true and false are produced with
(approximately) equal probability.
The method nextBoolean is implemented by class Random
public boolean nextBoolean() {
return next(1) != 0;
Returns:the next pseudorandom, uniformly distributed
boolean value from this random number generator's
sequenceSince:
public&float&nextFloat()
Returns the next pseudorandom, uniformly distributed float
value between 0.0 and 1.0 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&nbsp2-24, where m is a positive
integer less than 224 , are
produced with (approximately) equal probability.
The method nextFloat is implemented by class Random
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));
This might seem to be equivalent, if not better, but in fact it
introduced a slight nonuniformity because of the bias in the rounding
of floating-point numbers: it was slightly more likely that the
low-order bit of the significand would be 0 than that it would be 1.]
Returns:the next pseudorandom, uniformly distributed float
value between 0.0 and 1.0 from this
random number generator's sequence
nextDouble
public&double&nextDouble()
Returns the next pseudorandom, uniformly distributed
double value between 0.0 and
1.0 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 method nextDouble is implemented by class Random
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 choose
double 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);
This might seem to be equivalent, if not better, but in fact it
introduced a large nonuniformity because of the bias in the rounding
of floating-point numbers: it was three times as likely that the
low-order bit of the significand would be 0 than that it would be 1!
This nonuniformity probably doesn't matter much in practice, but we
strive for perfection.]
Returns:the next pseudorandom, uniformly distributed double
value between 0.0 and 1.0 from this
random number generator's sequenceSee Also:
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.
The method nextGaussian is implemented by class
Random as if by a threadsafe version of the following:
private double nextNextG
private boolean haveNextNextGaussian =
public double nextGaussian() {
if (haveNextNextGaussian) {
haveNextNextGaussian =
return nextNextG
double v1, v2,
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 *
haveNextNextGaussian =
return v1 *
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.
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
For further API reference and developer documentation, see . That documentation contains more detailed, developer-targeted descriptions, with conceptual overviews, definitions of terms, workarounds, and working code examples.
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Characteristic functions of random variables
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