其实写这篇文章的原由是最近准备在Java上写一个Perlin噪声的插件,所以对各种噪声函数有了一丢丢的了解,若有问题还请大家指正。转载的话希望能注明出处。
注意,本教程中的随机函数均是形参为整形,返回值为区间[0,1)内的单精浮点数的函数。测试均为1~10000的随机数生成速度测试(1D – 输入x、2D – 输入x, y)。
更新记录
2016.1.22 – 初稿。
2016.1.28 (1) – 更新了Wichman-Hill随机数的算法,修改内容。增加了几个随机算法。
(2) – 统计出了各个方法比较后的分数。
随机方法
1.Wichman-Hill 随机数产生器
Excel的随机函数曾用的方法,参考文献:
- Wichman, B.A. 和 I.D. Hill,Algorithm AS 183:An Efficient and Portable Pseudo-Random Number Generator,《Applied Statistics》,31,188-190,1982。
- Wichman, B.A. 和 I.D. Hill,Building a Random-Number Generator,BYTE,第127-128 页,1987 年 3 月。
- Rotz, W. 和 E. Falk,D. Wood 和 J. Mulrow,A Comparison of Random Number Generators Used in Business,发表于 2001 年在佐治亚州亚特兰大市举行的“统计学联合会议”上。
直接上源码(2D请前去Github上查看):
/** * This is a method of Wichman-Hill random number generator. * * @param x * A seed for generator. * @return A float random value between [0.0,1.0) */ public static float randomWH(java.lang.Integer x) { int[] seed = new int[3]; seed[0] = (171 * x) % 30269; seed[1] = (172 * (30000 - x)) % 30307; seed[2] = (170 * x) % 30323; return (x / Math.abs(x)) * (seed[0] / 30269.0F + seed[1] / 30307.0F + seed[2] / 30323.0F) % 1.0F; }
以下是测试结果:
Start testing randomWH(), test: Generate 10000 numbers(1D).
Testing randomWH() completed, using time: 10 ms.Start testing randomWH(), test: Generate 10000 numbers(2D).
Testing randomWH() completed, using time: 7 ms.
还蛮乐观,但是图像就…
无论怎么改,还是呈现了线性的趋势,波动很小……Orz
2.RSA 随机数产生器
RSA公钥算法大家都不会不熟悉吧,公认很靠谱的密钥算法。这里就是用了RSA的随机算法。参考:
- Wikipedia – RSA problem
其公式:C = (x * exp P) mod N(P是质数,N是两个质数之积)
这是Java代码:
/** * This is a method of RSA. * * @param x * A seed for generator. * @return A float random value between [0.0,1.0) */ public static float randomRSA(java.lang.Integer x) { return (float) (x * Math.exp(seedRSA[0]) % seedRSA[1] / seedRSA[1]); }
测试结果:
Start testing randomRSA(), test: Generate 10000 numbers(1D).
Testing randomRSA() completed, using time: 10 ms.Start testing randomRSA(), test: Generate 10000 numbers(2D).
Testing randomRSA() completed, using time: 9 ms.
从图像看出,这个算法的随机性很赞。况且运算速度也不赖,适合使用。
3.Java 随机数产生器
Java自带的随机数(就是java.util.Random类),用过的都知道吧。那就直接上代码:
/** * This is a method of Java random number generator. * * @param x * A seed for generator. * @return A float random value between [0.0,1.0) */ public static float randomJava(java.lang.Integer x) { return (float) (new java.util.Random(1000 * x).nextDouble()); //乘1000来让种子间差距增大 }
这是测试数据:
Start testing randomJava(), test: Generate 10000 numbers(1D).
Testing randomJava() completed, using time: 11 ms.Start testing randomJava(), test: Generate 10000 numbers(2D).
Testing randomJava() completed, using time: 8 ms.
非常优秀的随机数算法,速度快而且基本看不出规律。
4.简单的随机数产生器
又是扫荡Google的战利品,很抱歉忘记出处惹……代码:
/** * This is a method of basic random generator. * * @param x * A seed for generator. * @return A float random value between [0.0,1.0) */ public static float randomBasic(java.lang.Integer x) { x = (x << 13) ^ x; return (float) Math .abs((1.0 - ((x * (x * x * 15731 + 789221) + 1376312589) & 0x7fffffff) / 1073741824.0)); }
测试结果:
Start testing randomBasic(), test: Generate 10000 numbers(1D).
Testing randomBasic() completed, using time: 9 ms.Start testing randomBasic(), test: Generate 10000 numbers(2D).
Testing randomBasic() completed, using time: 8 ms.
也是非常优秀的算法,随机的效果很棒,且用时也不长。
5.dotNet 随机数产生器
写了尼玛整整一个类啊我擦,不过是源码转写进来的,也没费什么力气。代码:
(DotNetRandom 类)
package kaaass.perlin2d.random; /** * This is a random generator which translated from dotNet. * * @author dotNet, KAAAsS(Translate) * */ class DotNetRandom { private final static int MBIG = Integer.MAX_VALUE; private final static int MSEED = 161803398; private int inext, inextp; private int[] SeedArray = new int[56]; public DotNetRandom() { this((int) System.currentTimeMillis()); } public DotNetRandom(int Seed) { int ii; int mj, mk; mj = MSEED - Math.abs(Seed); SeedArray[55] = mj; mk = 1; for (int i = 1; i < 55; i++) { /* * Apparently the range [1..55] is special (Knuth) and so we're * wasting the 0'th position. */ ii = (21 * i) % 55; SeedArray[ii] = mk; mk = mj - mk; if (mk < 0) mk += MBIG; mj = SeedArray[ii]; } for (int k = 1; k < 5; k++) { for (int i = 1; i < 56; i++) { SeedArray[i] -= SeedArray[1 + (i + 30) % 55]; if (SeedArray[i] < 0) SeedArray[i] += MBIG; } } inext = 0; inextp = 21; Seed = 1; } /** * Return a new random number [0,1) and reSeed the Seed array. * @return A double [0,1) */ protected double rand() { int retVal; int locINext = inext; int locINextp = inextp; if (++locINext >= 56) locINext = 1; if (++locINextp >= 56) locINextp = 1; retVal = SeedArray[locINext] - SeedArray[locINextp]; if (retVal < 0) retVal += MBIG; SeedArray[locINext] = retVal; inext = locINext; inextp = locINextp; /* * Including this division at the end gives us significantly improved * random number distribution. */ return (retVal * (1.0 / MBIG)); } }
(调用)
/** * This is a method of doNet random number generator. * * @param x * A seed for generator. * @return A float random value between [0.0,1.0) */ public static float randomDoNet(java.lang.Integer x) { return (float) new DotNetRandom(1000 * x).rand(); }
测试:
Start testing randomDoNet(), test: Generate 10000 numbers(1D).
Testing randomDoNet() completed, using time: 61 ms.Start testing randomDoNet(), test: Generate 10000 numbers(2D).
Testing randomDoNet() completed, using time: 109 ms.
这速度,这质量……是我的锅吗……
统计
经过比对之后,终于得到了大致的评分表(已按高低名次排序):
看来Java的综合实力不差。同样可以在图表中看到实际上Basic的效率是最好的,然而与Java的差距也只有1毫秒。但是Java的质量要好上不少。RSA质量不错,基本和Basic持平,但是速度上还是差了一丢丢。
什么?你说其他两种?(尼玛dotNet画不下啊)
这里是对比方法:
- 速度:1-D、2-D随机数生成速度排序(上图表格中给出的是ms成绩),打出得分:1~5(各占20%)
- 随机程度:通过方差以及其他统计分析得出,打出得分:1~5(最好~最差)(占40%)
- 重复率:通过对插值图像的分析得出,打出得分:1~5(最好~最差)(占20%)
- 结果按百分制处理后,求出与100的差为最终成绩
当然本对比可能不是严谨科学,仅供参考。
附测试代码:
public static void testRandom(String method) { RandomGenerator obj = new RandomGenerator(); Method m; try { long t; // 1-D tests m = RandomGenerator.class.getMethod(method, Integer.class); t = System.currentTimeMillis(); System.out.println("Start testing " + method + "(), test: Generate 10000 numbers(1D)."); for (int i = 1; i <= 10000; i++) { m.invoke(obj, i); } System.out.println("Testing " + method + "() completed, using time: " + (System.currentTimeMillis() - t) + " ms.\n"); // 2-D tests m = RandomGenerator.class.getMethod(method, Integer.class, Integer.class); t = System.currentTimeMillis(); System.out.println("Start testing " + method + "(), test: Generate 10000 numbers(2D)."); for (int i = 1; i <= 100; i++) { for (int ii = 1; ii <= 100; ii++) { m.invoke(obj, i, ii); } } System.out.println("Testing " + method + "() completed, using time: " + (System.currentTimeMillis() - t) + " ms.\n"); // Generate data m = RandomGenerator.class.getMethod(method, Integer.class); String s1 = ""; String s2 = ""; for (int i = 1; i <= 50; i++) { if (s1.equals("")) { s1 = String.valueOf(i); } else { s1 = s1 + "," + String.valueOf(i); } if (s2.equals("")) { s2 = "" + (float) m.invoke(obj, i); } else { s2 = s2 + "," + (float) m.invoke(obj, i); } } System.out.println(s1); System.out.println(s2); } catch (NoSuchMethodException | SecurityException e) { e.printStackTrace(); return; } catch (IllegalAccessException e) { // TODO 自动生成的 catch 块 e.printStackTrace(); } catch (IllegalArgumentException e) { // TODO 自动生成的 catch 块 e.printStackTrace(); } catch (InvocationTargetException e) { // TODO 自动生成的 catch 块 e.printStackTrace(); } }
详情请看我的Github。
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