Sample code for Java to implement an efficient random number algorithm
- 2021-06-28 12:46:52
- OfStack
Preface
It happened when a netizen shared an interesting interview:
Generating ID consisting of 6 digits requires random numbers, no weighting, no self-increasing, and no duplication of numbers.The total number of IDs is tens of thousands.
First Answer
The first thing I thought about was
Generate an ID pool large enough (that is, how much is needed) Random sorting of numbers in ID pool Consume numbers in ID pool in turnUnfortunately, this method wastes 10 minutes of space and has poor performance.
Initial Mason Rotation Algorithm
After consulting a netizen, I learned an efficient random number algorithm: Mason Rotation (Mersenne Twister/MT).By searching for information:
The Mason rotation algorithm (Mersenne twister) is a pseudo-random number generation algorithm.Developed in 1997 by Matsumoto and Nishimura Toshi, linear recursion is based on a matrix over a finite binary field.It can produce high quality pseudo-random numbers quickly, which corrects many defects of classical random number generation algorithm.
One of the most widely used variants of Mersenne Twister is MT19937, which produces 32-bit integer sequences.
PS: This algorithm still does not solve the interview perfectly, but it also learns new knowledge.
Implementation of MT19937 algorithm
Later, through Google, an efficient Java version code of MT19937 was found.The source code link is http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/VERSIONS/JAVA/MTRandom.java
import java.util.Random;
/**
* MT19937 Of Java Realization
*/
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.
* <p>
* 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.
* <p>
* 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.
* <p>
* 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.
* <p>
* 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:
* <pre>
* mt.setSeed(12345);
* int foo = mt.nextInt(16) + (mt.nextInt(16) << 16);</pre>
* will not give the same result as
* <pre>
* mt.setSeed(12345);
* int foo = mt.nextInt(32);</pre>
*
* @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.
* <p>
* If the length of the byte array is not a multiple of 4 then
* it is implicitly padded with zeros as necessary. For example:
* <pre> byte[] { 0x01, 0x02, 0x03, 0x04, 0x05, 0x06 }</pre>
* becomes
* <pre> int[] { 0x04030201, 0x00000605 }</pre>
* <p>
* 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;
}
}
test
Test Code
// MT19937 Of Java Realization
MTRandom mtRandom=new MTRandom();
Map<Integer,Integer> map=new HashMap<>();
// Number of loops
int times=1000000;
long startTime=System.currentTimeMillis();
for(int i=0;i<times;i++){
// Use Map Duplicate removal
map.put(mtRandom.next(32),0);
}
// Number of Print Cycles
System.out.println("times:"+times);
// Print Map Number of
System.out.println("num:"+map.size());
// Print non-repeat ratio
System.out.println("proportion:"+map.size()/(double)times);
// Time spent ( In milliseconds )
System.out.println("time:"+(System.currentTimeMillis()-startTime));
test result
times:1000000
num:999886
proportion:0.999886
time:374