`
ant04444
  • 浏览: 22077 次
  • 性别: Icon_minigender_1
  • 来自: 广州
最近访客 更多访客>>
社区版块
存档分类
最新评论

Generate random numbers

    博客分类:
  • java
 
阅读更多
There are two means of generating random (really pseudo-random) numbers :
the Random class generates random integers, doubles, longs and so on, in various ranges.
the static method Math.random generates doubles between 0 (inclusive) and 1 (exclusive).
To generate random integers :
do not use Math.random (it produces doubles, not integers)
use the Random class to generate random integers between 0 and N.
To generate a series of random numbers as a unit, you need to use a single Random object - do not create a new Random object for each new random number. See also the related Sun Tech Tip.

Another alternative is SecureRandom, a cryptographically strong subclass of Random.

Example 1

import java.util.Random;

/** Generate 10 random integers in the range 0..99. */
public final class RandomInteger {
 
  public static final void main(String... aArgs){
    log("Generating 10 random integers in range 0..99.");
   
    //note a single Random object is reused here
    Random randomGenerator = new Random();
    for (int idx = 1; idx <= 10; ++idx){
      int randomInt = randomGenerator.nextInt(100);
      log("Generated : " + randomInt);
    }
   
    log("Done.");
  }
 
  private static void log(String aMessage){
    System.out.println(aMessage);
  }
}


Example run of this class :
Generating 10 random integers in range 0..99.
Generated : 44
Generated : 81
Generated : 69
Generated : 31
Generated : 10
Generated : 64
Generated : 74
Generated : 57
Generated : 56
Generated : 93
Done.
Example 2

This example generates random integers in a specific range.

import java.util.Random;

/** Generate random integers in a certain range. */
public final class RandomRange {
 
  public static final void main(String... aArgs){
    log("Generating random integers in the range 1..10.");
   
    int START = 1;
    int END = 10;
    Random random = new Random();
    for (int idx = 1; idx <= 10; ++idx){
      showRandomInteger(START, END, random);
    }
   
    log("Done.");
  }
 
  private static void showRandomInteger(int aStart, int aEnd, Random aRandom){
    if ( aStart > aEnd ) {
      throw new IllegalArgumentException("Start cannot exceed End.");
    }
    //get the range, casting to long to avoid overflow problems
    long range = (long)aEnd - (long)aStart + 1;
    // compute a fraction of the range, 0 <= frac < range
    long fraction = (long)(range * aRandom.nextDouble());
    int randomNumber =  (int)(fraction + aStart);   
    log("Generated : " + randomNumber);
  }
 
  private static void log(String aMessage){
    System.out.println(aMessage);
  }
}


An example run of this class :
Generating random integers in the range 1..10.
Generated : 9
Generated : 3
Generated : 3
Generated : 9
Generated : 4
Generated : 1
Generated : 3
Generated : 9
Generated : 10
Generated : 10
Done.
Example 3

This example generates random floating point numbers in a Gaussian (normal) distribution.

import java.util.Random;

/**
Generate pseudo-random floating point values, with an
approximately Gaussian (normal) distribution.

Many physical measurements have an approximately Gaussian
distribution; this provides a way of simulating such values.
*/
public final class RandomGaussian {
 
  public static void main(String... aArgs){
    RandomGaussian gaussian = new RandomGaussian();
    double MEAN = 100.0f;
    double VARIANCE = 5.0f;
    for (int idx = 1; idx <= 10; ++idx){
      log("Generated : " + gaussian.getGaussian(MEAN, VARIANCE));
    }
  }
   
  private Random fRandom = new Random();
 
  private double getGaussian(double aMean, double aVariance){
      return aMean + fRandom.nextGaussian() * aVariance;
  }

  private static void log(Object aMsg){
    System.out.println(String.valueOf(aMsg));
  }
}


An example run of this class :
Generated : 99.38221153454624
Generated : 100.95717075067498
Generated : 106.78740794978813
Generated : 105.57315286730545
Generated : 97.35077643206589
Generated : 92.56233774920052
Generated : 98.29311772993057
Generated : 102.04954815575822
Generated : 104.88458607780176
Generated : 97.11126014402141
分享到:
评论

相关推荐

Global site tag (gtag.js) - Google Analytics