我很难确定Mersenne C++11提供的哪一种变体。本文以松本和西村在MT19937
.的论文为例,给出了该算法的实现方法,并称之为Mersenne龙卷风:一种623维等分布均匀伪随机数发生器。
然而,当我用下面的小程序测试C++11的同名生成器时,我无法复制松本和西村的MT19937创建的流。流不同于最初产生的32位字。
C++11提供了哪一种默森扭动器?
下面的程序是使用GCC、-std=c++11
和GNU的stdlibc++
在Fedora 22上运行的。
std::mt19937 prng(102013);
for (unsigned int i = 0; i <= 625; i++)
{
cout << std::hex << prng();
if(i+1 != 625)
cout << ",";
if(i && i%8 == 0)
cout << endl;
}
发布于 2015-10-08 17:15:51
从您的链接到纸张的MT19937和标准定义的MT19937来看,它们看起来是相同的,但是增加了一层回火和一个初始化倍增器。
如果我们看一下rand.predef 26.5.5(3)定义的值与本文定义的参数相比,就会发现
32,624,397,31,0x9908b0df,11,0xffffffff,7,0x9d2c5680,15,0xefc60000,18,1812433253 <- standard
w ,n ,m ,r ,a ,u ,d ,s,b ,t ,c ,l ,f
32,624,397,31,0x9908b0df,11, ,7,0x9d2c5680,15,0xefc60000,18, <- paper
这就是不同之处所在。按照标准,std::mt19937
的第10,000次迭代也是399268537
发布于 2015-10-08 19:20:29
似乎C++11提供了改进初始化的Mersenne Twister
我刚刚提取了原始的C实现,并与C++进行了比较。
#include <iostream>
#include <cstdio>
#include <random>
#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 long mt[N]; /* the array for the state vector */
static int mti=N+1; /* mti==N+1 means mt[N] is not initialized */
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);
mt[mti] &= 0xffffffffUL;
}
}
unsigned long genrand_int32()
{
unsigned long y;
static unsigned long mag01[2]={0x0UL, MATRIX_A};
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++];
y ^= (y >> 11);
y ^= (y << 7) & 0x9d2c5680UL;
y ^= (y << 15) & 0xefc60000UL;
y ^= (y >> 18);
return y;
}
int main()
{
init_genrand(102013);
std::mt19937 prng(102013);
for (size_t i = 0; i < 10000; ++i) {
if (genrand_int32() != prng()) {
std::cout << "ERROR" << std::endl;
return 1;
}
}
std::cout << "OK" << std::endl;
return 0;
}
发布于 2015-10-08 20:30:46
我应该指出,C++11实际上通过模板类提供了许多:
template <class UIntType,
size_t word_size,
size_t state_size,
size_t shift_size,
size_t mask_bits,
UIntType xor_mask,
size_t tempering_u,
UIntType tempering_d,
size_t tempering_s,
UIntType tempering_b,
size_t tempering_t,
UIntType tempering_c,
size_t tempering_l,
UIntType initialization_multiplier>
class mersenne_twister_engine;
如果有人有勇气探索这些杠杆和旋钮..。当然,有两个标准的实例化:
using mt19937
= mersenne_twister_engine<uint_fast32_t,
32,
624,
397,
31,
0x9908b0df,
11,
0xffffffff,
7,
0x9d2c5680,
15,
0xefc60000,
18,
1812433253>;
64位版本:
using mt19937_64
= mersenne_twister_engine<uint_fast64_t,
64,
312,
156,
31,
0xb5026f5aa96619e9,
29,
0x5555555555555555,
17,
0x71d67fffeda60000,
37,
0xfff7eee000000000,
43,
6364136223846793005>;
我认为最好提供一个工具箱来检查RNG的质量,以便人们可以尝试新的实例化。
下面是模板parms的比较:
32,624,397,31, 0x9908b0df,11, 0xffffffff,7 , 0x9d2c5680,15, 0xefc60000,18,1812433253 <- std::mt19937
64,312,156,31,0xb5026f5aa96619e9,29,0x5555555555555555,17,0x71d67fffeda60000,37,0xfff7eee000000000,43,6364136223846793005 <- std::mt19937_64
w ,n ,m ,r ,a ,u ,d ,s ,b ,t ,c ,l ,f
32,624,397,31, 0x9908b0df,11, ,7 , 0x9d2c5680,15, 0xefc60000,18, <- paper
感谢@NathanOliver。
https://stackoverflow.com/questions/33021455
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