我必须使用一个伪随机数生成器在不同平台上使用相同的种子获得相同的数字。
我试图设置＆＃34;种子＆＃34;在Android（java）和Arduino（c）的随机类中，它们给出了不同的数字和相同的种子，我需要的是两个系统中带有SAME种子的SAME编号。
所以，我试过＆＃34; Mersenne Twister＆＃34;在两个系统中获得相同的伪随机数。
这是我在Arduino Library中的代码：
/*
A C-program for MT19937, with initialization improved 2002/1/26.
Coded by Takuji Nishimura and Makoto Matsumoto.
Before using, initialize the state by using init_genrand(seed)
or init_by_array(init_key, key_length).
Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
3. The names of its contributors may not be used to endorse or promote
products derived from this software without specific prior written
permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Any feedback is very welcome.
http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html
email: m-mat @ math.sci.hiroshima-u.ac.jp (remove space)
*/
//#include <stdio.h>
/* Period parameters */
#define N 624
#define M 397
#define MATRIX_A 0x9908b0dfUL /* constant vector a */
#define UPPER_MASK 0x80000000UL /* most significant w-r bits */
#define LOWER_MASK 0x7fffffffUL /* least significant r bits */
static unsigned int mt[N]; /* the array for the state vector */
static int mti=N+1; /* mti==N+1 means mt[N] is not initialized */
/* initializes mt[N] with a seed */
void init_genrand(unsigned long s)
{
mt[0]= s & 0xffffffffUL;
for (mti=1; mti<N; mti++) {
mt[mti] =
(1812433253UL * (mt[mti-1] ^ (mt[mti-1] >> 30)) + mti);
/* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */
/* In the previous versions, MSBs of the seed affect */
/* only MSBs of the array mt[]. */
/* 2002/01/09 modified by Makoto Matsumoto */
mt[mti] &= 0xffffffffUL;
/* for >32 bit machines */
}
}
/* initialize by an array with array-length */
/* init_key is the array for initializing keys */
/* key_length is its length */
/* slight change for C++, 2004/2/26 */
void init_by_array(unsigned long init_key[], int key_length)
{
int i, j, k;
init_genrand(19650218UL);
i=1; j=0;
k = (N>key_length ? N : key_length);
for (; k; k--) {
mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >> 30)) * 1664525UL))
+ init_key[j] + j; /* non linear */
mt[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */
i++; j++;
if (i>=N) { mt[0] = mt[N-1]; i=1; }
if (j>=key_length) j=0;
}
for (k=N-1; k; k--) {
mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >> 30)) * 1566083941UL))
- i; /* non linear */
mt[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */
i++;
if (i>=N) { mt[0] = mt[N-1]; i=1; }
}
mt[0] = 0x80000000UL; /* MSB is 1; assuring non-zero initial array */
}
/* generates a random number on [0,0xffffffff]-interval */
unsigned long genrand_int32(void)
{
unsigned long y;
static unsigned long mag01[2]={0x0UL, MATRIX_A};
/* mag01[x] = x * MATRIX_A for x=0,1 */
if (mti >= N) { /* generate N words at one time */
int kk;
if (mti == N+1) /* if init_genrand() has not been called, */
init_genrand(5489UL); /* a default initial seed is used */
for (kk=0;kk<N-M;kk++) {
y = (mt[kk]&UPPER_MASK)|(mt[kk+1]&LOWER_MASK);
mt[kk] = mt[kk+M] ^ (y >> 1) ^ mag01[y & 0x1UL];
}
for (;kk<N-1;kk++) {
y = (mt[kk]&UPPER_MASK)|(mt[kk+1]&LOWER_MASK);
mt[kk] = mt[kk+(M-N)] ^ (y >> 1) ^ mag01[y & 0x1UL];
}
y = (mt[N-1]&UPPER_MASK)|(mt[0]&LOWER_MASK);
mt[N-1] = mt[M-1] ^ (y >> 1) ^ mag01[y & 0x1UL];
mti = 0;
}
y = mt[mti++];
/* Tempering */
y ^= (y >> 11);
y ^= (y << 7) & 0x9d2c5680UL;
y ^= (y << 15) & 0xefc60000UL;
y ^= (y >> 18);
return y;
}
/* generates a random number on [0,0x7fffffff]-interval */
long genrand_int31(void)
{
return (long)(genrand_int32()>>1);
}
unsigned long generate_long(unsigned long n)
{
unsigned long bits, val;
do {
bits = (genrand_int31() << 1);
val = bits % n;
}
while(bits - val + (n-1) < 0);
return val;
}
/* generates a random number on [0,1]-real-interval */
double genrand_real1(void)
{
return genrand_int32()*(1.0/4294967295.0);
/* divided by 2^32-1 */
}
/* generates a random number on [0,1)-real-interval */
double genrand_real2(void)
{
return genrand_int32()*(1.0/4294967296.0);
/* divided by 2^32 */
}
/* generates a random number on (0,1)-real-interval */
double genrand_real3(void)
{
return (((double)genrand_int32()) + 0.5)*(1.0/4294967296.0);
/* divided by 2^32 */
}
/* generates a random number on [0,1) with 53-bit resolution*/
double genrand_res53(void)
{
unsigned long a=genrand_int32()>>5, b=genrand_int32()>>6;
return(a*67108864.0+b)*(1.0/9007199254740992.0);
}
/* These real versions are due to Isaku Wada, 2002/01/09 added */
这是我在Java中的Mersenne Twister： http://www.cs.gmu.edu/~sean/research/mersenne/MersenneTwister.java或http://www.cs.gmu.edu/~sean/research/mersenne/MersenneTwisterFast.java .java中的代码或多或少相等，至少结果是相同的。
你可以帮我解释为什么我不能得到相同的伪随机数吗？
提前致谢， 最好的问候。
答案 0 :(得分：1)
最初的Mersenne Twister不能在带有2KB Ram的MCU上运行。
你将mt []从long更改为int break是它。
答案 1 :(得分：0)
如果您想坚持使用Mercenne Twister，请尝试TinyMT。或者您甚至可以尝试xoroshiro+ or XorShift+，它的代码要小得多。