java.util Random

java.util
Random

Declaration
public class Random
java.lang.Object
|
+--java.util.Random
Description
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.


Constructors
Random()
Random(long seed)
Methods
protected int next(int bits)
double nextDouble()
float nextFloat()
int nextInt()
int nextInt(int n)
long nextLong()
void setSeed(long seed)
Methods inherited from class Object

Random()
Inherited Member Summary
Constructors
Random()
Declaration:
public Random()
Description:
Creates a new random number generator. Its seed is initialized to a value based on the current time:
public Random() { this(System.currentTimeMillis()); }
See Also: java.lang.System.currentTimeMillis()
Random(long)
Declaration:
public Random(long seed)
Description:
Creates a new random number generator using a single long seed:
public Random(long seed) { setSeed(seed); }
Used by method next to hold the state of the pseudorandom number generator.
Parameters:
seed - the initial seed.
See Also: setSeed(long)
Methods
setSeed(long)
Declaration:
public void setSeed(long seed)
Description:
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 as follows:
synchronized public void setSeed(long seed) {
this.seed = (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1);
}
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.
equals(Object), getClass(), hashCode(), notify(), notifyAll(), toString(), wait(),
wait(), wait()


next(int)
Declaration:
protected int next(int bits)
Description:
Generates the next pseudorandom number. Subclass 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 as follows:
synchronized protected int next(int bits) {
seed = (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1);
return (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 2: Seminumerical Algorithms, section
3.2.1.
Parameters:
bits - random bits
Returns: the next pseudorandom value from this random number generator’s sequence.
nextInt()
Declaration:
public int nextInt()
Description:
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 as follows:
public int nextInt() { return next(32); }
Returns: the next pseudorandom, uniformly distributed int value from this random number generator’s
sequence.
nextInt(int)
Declaration:
public int nextInt(int n)
Description:
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 follows:


nextLong()
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);
int bits, val;
do {
bits = next(31);
val = bits % n;
} while(bits - val + (n-1) < 0);
return val;
}
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. The 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 highorder
bits from the underlying pseudo-random number generator. In the absence of special treatment, the
correct number of low-order bits would be returned. Linear 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. Must be positive.
Returns: a pseudorandom, uniformly distributed int value between 0 (inclusive) and n (exclusive).
Throws:
java.lang.IllegalArgumentException - n is not positive.
Since: CLDC 1.1
nextLong()
Declaration:
public long nextLong()
Description:
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. All 264 possible long values are produced with (approximately) equal probability. The method
nextLong is implemented by class Random as follows:
public long nextLong() {
return ((long)next(32) << 32) + next(32);
}
Returns: the next pseudorandom, uniformly distributed long value from this random number generator’s
sequence.



nextFloat()
Declaration:
public float nextFloat()
Description:
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 2-24, where m is a positive integer less than 224 , are produced with
(approximately) equal probability. The method nextFloat is implemented by class Random as follows:
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 or 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.
Since: CLDC 1.1
nextDouble()
Declaration:
public double nextDouble()
Description:
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. All 253
possible float values of the form m x 2-53 , where m is a positive integer less than 253, are produced with
(approximately) equal probability. The method nextDouble is implemented by class Random as
follows:
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 or 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:



nextDouble()
286
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 sequence.
Since: CLDC 1.1