本篇文章给大家分享的是有关使用Java怎么实现一个高效随机数算法,小编觉得挺实用的,因此分享给大家学习,希望大家阅读完这篇文章后可以有所收获,话不多说,跟着小编一起来看看吧。
成都创新互联2013年至今,先为振安等服务建站,振安等地企业,进行企业商务咨询服务。为振安企业网站制作PC+手机+微官网三网同步一站式服务解决您的所有建站问题。
MT19937算法实现
import java.util.Random; /** * MT19937的Java实现 */ public class MTRandom extends Random { // Constants used in the original C implementation private final static int UPPER_MASK = 0x80000000; private final static int LOWER_MASK = 0x7fffffff; private final static int N = 624; private final static int M = 397; private final static int MAGIC[] = { 0x0, 0x9908b0df }; private final static int MAGIC_FACTOR1 = 1812433253; private final static int MAGIC_FACTOR2 = 1664525; private final static int MAGIC_FACTOR3 = 1566083941; private final static int MAGIC_MASK1 = 0x9d2c5680; private final static int MAGIC_MASK2 = 0xefc60000; private final static int MAGIC_SEED = 19650218; private final static long DEFAULT_SEED = 5489L; // Internal state private transient int[] mt; private transient int mti; private transient boolean compat = false; // Temporary buffer used during setSeed(long) private transient int[] ibuf; /** * The default constructor for an instance of MTRandom. This invokes * the no-argument constructor for java.util.Random which will result * in the class being initialised with a seed value obtained by calling * System.currentTimeMillis(). */ public MTRandom() { } /** * This version of the constructor can be used to implement identical * behaviour to the original C code version of this algorithm including * exactly replicating the case where the seed value had not been set * prior to calling genrand_int32. ** If the compatibility flag is set to true, then the algorithm will be * seeded with the same default value as was used in the original C * code. Furthermore the setSeed() method, which must take a 64 bit * long value, will be limited to using only the lower 32 bits of the * seed to facilitate seamless migration of existing C code into Java * where identical behaviour is required. *
* Whilst useful for ensuring backwards compatibility, it is advised * that this feature not be used unless specifically required, due to * the reduction in strength of the seed value. * * @param compatible Compatibility flag for replicating original * behaviour. */ public MTRandom(boolean compatible) { super(0L); compat = compatible; setSeed(compat?DEFAULT_SEED:System.currentTimeMillis()); } /** * This version of the constructor simply initialises the class with * the given 64 bit seed value. For a better random number sequence * this seed value should contain as much entropy as possible. * * @param seed The seed value with which to initialise this class. */ public MTRandom(long seed) { super(seed); } /** * This version of the constructor initialises the class with the * given byte array. All the data will be used to initialise this * instance. * * @param buf The non-empty byte array of seed information. * @throws NullPointerException if the buffer is null. * @throws IllegalArgumentException if the buffer has zero length. */ public MTRandom(byte[] buf) { super(0L); setSeed(buf); } /** * This version of the constructor initialises the class with the * given integer array. All the data will be used to initialise * this instance. * * @param buf The non-empty integer array of seed information. * @throws NullPointerException if the buffer is null. * @throws IllegalArgumentException if the buffer has zero length. */ public MTRandom(int[] buf) { super(0L); setSeed(buf); } // Initializes mt[N] with a simple integer seed. This method is // required as part of the Mersenne Twister algorithm but need // not be made public. private final void setSeed(int seed) { // Annoying runtime check for initialisation of internal data // caused by java.util.Random invoking setSeed() during init. // This is unavoidable because no fields in our instance will // have been initialised at this point, not even if the code // were placed at the declaration of the member variable. if (mt == null) mt = new int[N]; // ---- Begin Mersenne Twister Algorithm ---- mt[0] = seed; for (mti = 1; mti < N; mti++) { mt[mti] = (MAGIC_FACTOR1 * (mt[mti-1] ^ (mt[mti-1] >>> 30)) + mti); } // ---- End Mersenne Twister Algorithm ---- } /** * This method resets the state of this instance using the 64 * bits of seed data provided. Note that if the same seed data * is passed to two different instances of MTRandom (both of * which share the same compatibility state) then the sequence * of numbers generated by both instances will be identical. *
* If this instance was initialised in 'compatibility' mode then * this method will only use the lower 32 bits of any seed value * passed in and will match the behaviour of the original C code * exactly with respect to state initialisation. * * @param seed The 64 bit value used to initialise the random * number generator state. */ public final synchronized void setSeed(long seed) { if (compat) { setSeed((int)seed); } else { // Annoying runtime check for initialisation of internal data // caused by java.util.Random invoking setSeed() during init. // This is unavoidable because no fields in our instance will // have been initialised at this point, not even if the code // were placed at the declaration of the member variable. if (ibuf == null) ibuf = new int[2]; ibuf[0] = (int)seed; ibuf[1] = (int)(seed >>> 32); setSeed(ibuf); } } /** * This method resets the state of this instance using the byte * array of seed data provided. Note that calling this method * is equivalent to calling "setSeed(pack(buf))" and in particular * will result in a new integer array being generated during the * call. If you wish to retain this seed data to allow the pseudo * random sequence to be restarted then it would be more efficient * to use the "pack()" method to convert it into an integer array * first and then use that to re-seed the instance. The behaviour * of the class will be the same in both cases but it will be more * efficient. * * @param buf The non-empty byte array of seed information. * @throws NullPointerException if the buffer is null. * @throws IllegalArgumentException if the buffer has zero length. */ public final void setSeed(byte[] buf) { setSeed(pack(buf)); } /** * This method resets the state of this instance using the integer * array of seed data provided. This is the canonical way of * resetting the pseudo random number sequence. * * @param buf The non-empty integer array of seed information. * @throws NullPointerException if the buffer is null. * @throws IllegalArgumentException if the buffer has zero length. */ public final synchronized void setSeed(int[] buf) { int length = buf.length; if (length == 0) throw new IllegalArgumentException("Seed buffer may not be empty"); // ---- Begin Mersenne Twister Algorithm ---- int i = 1, j = 0, k = (N > length ? N : length); setSeed(MAGIC_SEED); for (; k > 0; k--) { mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >>> 30)) * MAGIC_FACTOR2)) + buf[j] + j; i++; j++; if (i >= N) { mt[0] = mt[N-1]; i = 1; } if (j >= length) j = 0; } for (k = N-1; k > 0; k--) { mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >>> 30)) * MAGIC_FACTOR3)) - i; i++; if (i >= N) { mt[0] = mt[N-1]; i = 1; } } mt[0] = UPPER_MASK; // MSB is 1; assuring non-zero initial array // ---- End Mersenne Twister Algorithm ---- } /** * This method forms the basis for generating a pseudo random number * sequence from this class. If given a value of 32, this method * behaves identically to the genrand_int32 function in the original * C code and ensures that using the standard nextInt() function * (inherited from Random) we are able to replicate behaviour exactly. *
* Note that where the number of bits requested is not equal to 32 * then bits will simply be masked out from the top of the returned * integer value. That is to say that: *
* mt.setSeed(12345); * int foo = mt.nextInt(16) + (mt.nextInt(16) << 16);* will not give the same result as ** mt.setSeed(12345); * int foo = mt.nextInt(32);* * @param bits The number of significant bits desired in the output. * @return The next value in the pseudo random sequence with the * specified number of bits in the lower part of the integer. */ protected final synchronized int next(int bits) { // ---- Begin Mersenne Twister Algorithm ---- int y, kk; if (mti >= N) { // generate N words at one time // In the original C implementation, mti is checked here // to determine if initialisation has occurred; if not // it initialises this instance with DEFAULT_SEED (5489). // This is no longer necessary as initialisation of the // Java instance must result in initialisation occurring // Use the constructor MTRandom(true) to enable backwards // compatible behaviour. for (kk = 0; kk < N-M; kk++) { y = (mt[kk] & UPPER_MASK) | (mt[kk+1] & LOWER_MASK); mt[kk] = mt[kk+M] ^ (y >>> 1) ^ MAGIC[y & 0x1]; } for (;kk < N-1; kk++) { y = (mt[kk] & UPPER_MASK) | (mt[kk+1] & LOWER_MASK); mt[kk] = mt[kk+(M-N)] ^ (y >>> 1) ^ MAGIC[y & 0x1]; } y = (mt[N-1] & UPPER_MASK) | (mt[0] & LOWER_MASK); mt[N-1] = mt[M-1] ^ (y >>> 1) ^ MAGIC[y & 0x1]; mti = 0; } y = mt[mti++]; // Tempering y ^= (y >>> 11); y ^= (y << 7) & MAGIC_MASK1; y ^= (y << 15) & MAGIC_MASK2; y ^= (y >>> 18); // ---- End Mersenne Twister Algorithm ---- return (y >>> (32-bits)); } // This is a fairly obscure little code section to pack a // byte[] into an int[] in little endian ordering. /** * This simply utility method can be used in cases where a byte * array of seed data is to be used to repeatedly re-seed the * random number sequence. By packing the byte array into an * integer array first, using this method, and then invoking * setSeed() with that; it removes the need to re-pack the byte * array each time setSeed() is called. ** If the length of the byte array is not a multiple of 4 then * it is implicitly padded with zeros as necessary. For example: *
byte[] { 0x01, 0x02, 0x03, 0x04, 0x05, 0x06 }* becomes *int[] { 0x04030201, 0x00000605 }** Note that this method will not complain if the given byte array * is empty and will produce an empty integer array, but the * setSeed() method will throw an exception if the empty integer * array is passed to it. * * @param buf The non-null byte array to be packed. * @return A non-null integer array of the packed bytes. * @throws NullPointerException if the given byte array is null. */ public static int[] pack(byte[] buf) { int k, blen = buf.length, ilen = ((buf.length+3) >>> 2); int[] ibuf = new int[ilen]; for (int n = 0; n < ilen; n++) { int m = (n+1) << 2; if (m > blen) m = blen; for (k = buf[--m]&0xff; (m & 0x3) != 0; k = (k << 8) | buf[--m]&0xff); ibuf[n] = k; } return ibuf; } }
测试
测试代码
// MT19937的Java实现 MTRandom mtRandom=new MTRandom(); Mapmap=new HashMap<>(); //循环次数 int times=1000000; long startTime=System.currentTimeMillis(); for(int i=0;i 测试结果
times:1000000
num:999886
proportion:0.999886
time:374以上就是使用Java怎么实现一个高效随机数算法,小编相信有部分知识点可能是我们日常工作会见到或用到的。希望你能通过这篇文章学到更多知识。更多详情敬请关注创新互联行业资讯频道。
标题名称:使用Java怎么实现一个高效随机数算法
网页路径:http://cdweb.net/article/pjhogs.html