之前已经问过这个问题(stackoverflow)但是(接受的)答案并不令人满意。
以下示例保存并加载状态,但取决于它生成的值的生成数量,或者它没有:
#include <fstream>
#include <iostream>
#include <random>
#include <cassert>
int main()
{
const int preN = 4;
const int middleN = 0;
// initialize randGen
std::mt19937 randGen1;
std::normal_distribution<double> distribution1;
// print some initial random numbers
for (int i=0;i<preN;++i)
std::cout << distribution1(randGen1)<<" ";
// save state
std::cout << std::endl << "Saving...\n";
{
std::ofstream fout("seed.dat");
fout << randGen1;
}
// maybe advance randGen1
for (int i=0;i<middleN;++i)
std::cout << distribution1(randGen1)<<" ";
// load saved state into randGen2
std::cout << std::endl << "Loading...\n";
std::ifstream fin("seed.dat");
std::mt19937 randGen2;
fin >> randGen2;
std::normal_distribution<double> distribution2;
// are both randGen equal?
assert(randGen1 == randGen2);
// print numbers from both generators
std::cout << "Generator1\tGenerator2\n";
std::cout << distribution1(randGen1) << "\t"
<< distribution2(randGen2) << "\n";
return 0;
}
使用这些参数,它可以像预期的那样工作。但是,如果我设置preN=3
,则输出如下:
0.13453 -0.146382 0.46065
Saving...
Loading...
Generator1 Generator2
-1.87138 0.163712
为什么声明不适用?现在我设置preN=3
和middleN=1
,输出为
0.13453 -0.146382 0.46065
Saving...
-1.87138
Loading...
Generator1 Generator2
0.163712 0.163712
如果我将middleN
设置为大于1的任何值,则断言适用。
谁能解释一下发生了什么?我做错了什么或不理解?
在Linux上使用GCC5.4.0和CLANG3.8.0进行测试
答案 0 :(得分:4)
问题不在于随机数生成器的状态。问题是您的分发状态。是的,分发也可以有状态。
通过使用reset
重置正态分布状态,您可以获得相同的值。或者,您也可以使用<<
和>>
preserve and reconstitute发布状态。
答案 1 :(得分:1)
感谢上面Nicol Bolas的答案,我可以在下面添加更正后的代码:
#include <fstream>
#include <iostream>
#include <random>
#include <cassert>
int main()
{
const int preN = 7;
const int middleN = 0;
// initialize another randGen
std::mt19937 randGen1;
std::normal_distribution<double> distribution1;
// print some initial random numbers
for (int i=0;i<preN;++i)
std::cout << distribution1(randGen1)<<" ";
// save state
std::cout << std::endl << "Saving...\n";
{
std::ofstream fout("seed.dat");
fout << randGen1;
fout.close();
std::ofstream fout2("distribution.dat");
fout2 << distribution1;
fout2.close();
}
// maybe advance randGen
for (int i=0;i<middleN;++i)
std::cout << distribution1(randGen1)<<" ";
// load saved state into randGen2
std::cout << std::endl << "Loading...\n";
std::mt19937 randGen2;
std::normal_distribution<double> distribution2;
{
std::ifstream fin("seed.dat");
fin >> randGen2;
fin.close();
std::ifstream fin2("distribution.dat");
fin2 >> distribution2;
fin2.close();
}
// are both randGen equal?
assert(randGen1 == randGen2);
assert(distribution1 == distribution2);
// print numbers from both generators
std::cout << "Generator1\tGenerator2\n";
std::cout << distribution1(randGen1) << "\t"
<< distribution2(randGen2) << "\n";
return 0;
}
答案 2 :(得分:0)
这是一种可以保存和恢复双精度浮点数的种子随机数的方法。整数应该类似-使用jrand48而不是erand48。
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
int main(int argc, char **argv)
{
unsigned short savedseed[3];
unsigned short currentseed[3];
double x;
/*-- initialize ramdom seed to whatever --*/
currentseed[0]= 23;
currentseed[1]= 45;
currentseed[2]= 67;
printf("\n");
/*-- generate three random numbers --*/
x = erand48(currentseed); printf("%g\n", x);
x = erand48(currentseed); printf("%g\n", x);
x = erand48(currentseed); printf("%g\n", x);
printf("\n");
/*-- save seed --*/
memcpy(savedseed, currentseed, 3*sizeof(unsigned short));
/*-- generate next three random numbers --*/
x = erand48(currentseed); printf("%g\n", x);
x = erand48(currentseed); printf("%g\n", x);
x = erand48(currentseed); printf("%g\n", x);
printf("\n", x);
/*-- restore seed --*/
memcpy(currentseed, savedseed, 3*sizeof(unsigned short));
/*-- generate the same three random numbers again --*/
x = erand48(currentseed); printf("%g\n", x);
x = erand48(currentseed); printf("%g\n", x);
x = erand48(currentseed); printf("%g\n", x);
printf("\n");
}