Inheritance diagram for java::util::Random:

Collaboration diagram for java::util::Random:

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 `random`

method in class `Math`

simpler to use.

**Version:**- 1.34, 02/02/00

**See also:**- java.lang.Math::random()

**Since:**- JDK1.0

## Public Member Functions | |

Random () | |

Creates a new random number generator. | |

Random (jlong seed) | |

Creates a new random number generator using a single `long` seed: <blockquote>. | |

virtual void | setSeed (jlong seed) |

Sets the seed of this random number generator using a single `long` seed. | |

virtual void | nextBytes (Array< jbyte > &bytes) |

Generates random bytes and places them into a user-supplied byte array. | |

virtual jint | nextInt () |

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

virtual jint | nextInt (jint n) |

Returns a pseudorandom, uniformly distributed `int` value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence. | |

virtual jlong | nextLong () |

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

virtual jboolean | nextBoolean () |

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

virtual jfloat | nextFloat () |

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

virtual jdouble | nextDouble () |

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

virtual jdouble | 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. | |

## Protected Member Functions | |

virtual jint | next (jint bits) |

Generates the next pseudorandom number. |

java::util::Random::Random | ( | ) |

Creates a new random number generator.

Its seed is initialized to a value based on the current time: <blockquote>

public Random() { this(System.currentTimeMillis()); }</blockquote>

java::util::Random::Random | ( | jlong | seed |
) |

Creates a new random number generator using a single `long`

seed: <blockquote>.

public Random(long seed) { setSeed(seed); }</blockquote> Used by method

`next`

to hold the state of the pseudorandom number generator.

**Parameters:**-
*seed*the initial seed.

virtual void java::util::Random::setSeed | ( | jlong | seed |
) | ` [virtual]` |

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: <blockquote>

synchronized public void setSeed(long seed) { this.seed = (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1); haveNextNextGaussian = false; }</blockquote> 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.

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.

**Parameters:**-
*bytes*the non-null byte array in which to put the random bytes.

**Since:**- JDK1.1

virtual jint java::util::Random::nextInt | ( | ) | ` [virtual]` |

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 2<font size="-1">^{32 }</font> possible `int`

values are produced with (approximately) equal probability. The method `nextInt`

is implemented by class `Random`

as follows: <blockquote>

public int nextInt() { return next(32); }</blockquote>

**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.

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: <blockquote>

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; }</blockquote>

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 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. 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).

**Exceptions:**-
*IllegalArgumentException*n is not positive.

**Since:**- 1.2

virtual jlong java::util::Random::nextLong | ( | ) | ` [virtual]` |

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 2<font size="-1">^{64}</font> possible `long`

values are produced with (approximately) equal probability. The method `nextLong`

is implemented by class `Random`

as follows: <blockquote>

public long nextLong() { return ((long)next(32) << 32) + next(32); }</blockquote>

**Returns:**- the next pseudorandom, uniformly distributed
`long`

value from this random number generator's sequence.

virtual jboolean java::util::Random::nextBoolean | ( | ) | ` [virtual]` |

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 method `nextBoolean`

is implemented by class `Random`

as follows: <blockquote>

public boolean nextBoolean() {return next(1) != 0;}</blockquote>

**Returns:**- the next pseudorandom, uniformly distributed
`boolean`

value from this random number generator's sequence.

**Since:**- 1.2

virtual jfloat java::util::Random::nextFloat | ( | ) | ` [virtual]` |

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 2<font size="-1">^{24}</font> possible `float`

values of the form *m x *2<font size="-1">^{-24}</font>, where *m* is a positive integer less than 2<font size="-1">^{24} </font>, are produced with (approximately) equal probability. The method `nextFloat`

is implemented by class `Random`

as follows: <blockquote>

public float nextFloat() { return next(24) / ((float)(1 << 24)); }</blockquote> 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: <blockquote>

return next(30) / ((float)(1 << 30));</blockquote> 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.

virtual jdouble java::util::Random::nextDouble | ( | ) | ` [virtual]` |

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 2<font size="-1">^{53}</font> possible `float`

values of the form *m x *2<font size="-1">^{-53} </font>, where *m* is a positive integer less than 2<font size="-1">^{53}</font>, are produced with (approximately) equal probability. The method `nextDouble`

is implemented by class `Random`

as follows: <blockquote>

public double nextDouble() { return (((long)next(26) << 27) + next(27)) / (double)(1L << 53); }</blockquote>

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: <blockquote>

return (((long)next(27) << 27) + next(27)) / (double)(1L << 54);</blockquote> 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.

virtual jdouble java::util::Random::nextGaussian | ( | ) | ` [virtual]` |

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 follows: <blockquote>

synchronized 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 = Math.sqrt(-2 * Math.log(s)/s); nextNextGaussian = v2 * multiplier; haveNextNextGaussian = true; return v1 * multiplier; } }</blockquote> This uses the

`Math.log`

and one call to `Math.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.

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: <blockquote>

synchronized protected int next(int bits) { seed = (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1); return (int)(seed >>> (48 - bits)); }</blockquote> This is a linear congruential pseudorandom number generator, as defined by D. H. Lehmer and described by Donald E. Knuth in

**Parameters:**-
*bits*random bits

**Returns:**- the next pseudorandom value from this random number generator's sequence.

**Since:**- JDK1.1

The documentation for this class was generated from the following file:

Generated on Fri May 16 11:56:51 2008 for CrossPlatformJavaLikeC++API by 1.5.3