使用random方法
使用random类生成随机数：
10.9
代码部分：
package lianxi;
import java.util.*;
public class bo {
public static void main(String[] args) {
Random rand = new Random();
System.out.println("rand.nextBoolean()：" + rand.nextBoolean());
byte[] buffer = new byte[16];
rand.nextBytes(buffer);
System.out.println(Arrays.toString(buffer));
//生成0.0~1.0之间的伪随机double数
System.out.println("rand.nextDouble()：" + rand.nextDouble());
//生成0.0~1.0之间的伪随机float数
System.out.println("rand.nextFloat()：" + rand.nextFloat());
//生成平均值是 0.0，标准差是 1.0的伪高斯数
System.out.println("rand.nextGaussian()：" + rand.nextGaussian());
//生成一个处于long整数取值范围的伪随机整数
System.out.println("rand.nextInt()：" + rand.nextInt());
//生成0~26之间的伪随机整数
System.out.println("rand.nextInt(26)：" + rand.nextInt(26));
//生成一个处于long整数取值范围的伪随机整数
System.out.println("rand.nextLong()：" + rand.nextLong());
}
}
运行结果：
代码2：
代码部分：
package lianxi;
import java.util.*;
public class bo {
public static void main(String[] args) {
Random rand = new Random();
System.out.println("rand.nextBoolean()：" + rand.nextBoolean());
byte[] buffer = new byte[16];
rand.nextBytes(buffer);
System.out.println(Arrays.toString(buffer));
//生成0.0~1.0之间的伪随机double数
System.out.println("rand.nextDouble()：" + rand.nextDouble());
//生成0.0~1.0之间的伪随机float数
System.out.println("rand.nextFloat()：" + rand.nextFloat());
//生成平均值是 0.0，标准差是 1.0的伪高斯数
System.out.println("rand.nextGaussian()：" + rand.nextGaussian());
//生成一个处于long整数取值范围的伪随机整数
System.out.println("rand.nextInt()：" + rand.nextInt());
//生成0~26之间的伪随机整数
System.out.println("rand.nextInt(26)：" + rand.nextInt(26));
//生成一个处于long整数取值范围的伪随机整数
System.out.println("rand.nextLong()：" + rand.nextLong()); Random r1 = new Random(50);
System.out.println("第一个种子为50的Random对象");
System.out.println("r1.nextBoolean():\t" + r1.nextBoolean());
System.out.println("r1.nextInt():\t\t" + r1.nextInt());
System.out.println("r1.nextDouble():\t" + r1.nextDouble());
System.out.println("r1.nextGaussian():\t" + r1.nextGaussian());
System.out.println("---------------------------");
Random r2 = new Random(50);
System.out.println("第二个种子为50的Random对象");
System.out.println("r2.nextBoolean():\t" + r2.nextBoolean());
System.out.println("r2.nextInt():\t\t" + r2.nextInt());
System.out.println("r2.nextDouble():\t" + r2.nextDouble());
System.out.println("r2.nextGaussian():\t" + r2.nextGaussian());
System.out.println("---------------------------");
Random r3 = new Random(100);
System.out.println("种子为100的Random对象");
System.out.println("r3.nextBoolean():\t" + r3.nextBoolean());
System.out.println("r3.nextInt():\t\t" + r3.nextInt());
System.out.println("r3.nextDouble():\t" + r3.nextDouble());
System.out.println("r3.nextGaussian():\t" + r3.nextGaussian());
Random r4 = new Random(System.currentTimeMillis());
System.out.println("以当前时间为种子的Random对象");
System.out.println("r3.nextBoolean():\t" + r4.nextBoolean());
System.out.println("r3.nextInt():\t\t" + r4.nextInt());
System.out.println("r3.nextDouble():\t" + r4.nextDouble());
System.out.println("r3.nextGaussian():\t" + r4.nextGaussian());
}
}
运行结果：
