与srand()的rand()给出了奇怪的相似结果.rand()的返回非常相似

Question

这是一个看似常见的问题,所以我希望我听起来并不多余.但是从rand()返回的范围应该在0和RAND_MAX之间,但是,当我做一个非常简单的rand语句时,我总是在很小的范围内得到回报.

此范围类似于1,4XX,XXX,XXX.我认为这可能是一个时钟的东西,所以我等了三十分钟,我仍然得到相同范围内的数字.

以下是20分钟前的一些示例输出:

Matthews-Macbook-Pro:Data_Structures matthewwright$ ./main
1439810968
80
Matthews-Macbook-Pro:Data_Structures matthewwright$ ./main
1439827775
29
Matthews-Macbook-Pro:Data_Structures matthewwright$ ./main
1439827775
29
Matthews-Macbook-Pro:Data_Structures matthewwright$ ./main
1439844582
78
Matthews-Macbook-Pro:Data_Structures matthewwright$ ./main
1439878196
29
Matthews-Macbook-Pro:Data_Structures matthewwright$ ./main
1439895003
78

这是刚刚的示例输出:

Matthews-Macbook-Pro:Data_Structures matthewwright$ ./main
1456483512
78
Matthews-Macbook-Pro:Data_Structures matthewwright$ ./main
1456500319
80
Matthews-Macbook-Pro:Data_Structures matthewwright$ ./main
1456500319
80
Matthews-Macbook-Pro:Data_Structures matthewwright$ ./main
1456517126
29
Matthews-Macbook-Pro:Data_Structures matthewwright$ ./main
1456533933
78

我知道rand()并不完美,但这似乎太相似了.如果范围是0 - RAND_MAX,则返回的每个数字都在相同的范围内似乎很奇怪.

这是我测试的代码:

#include <iostream>
#include <stdio.h>      /* printf, scanf, puts, NULL */
#include <stdlib.h>     /* srand, rand */
#include <time.h>       /* time */

int main(int argc, char const *argv[])
{
    /* declarations */
    srand(time(NULL));

    std::cout << std::rand() << std::endl;
    std::cout << std::rand()%100 << std::endl;
    return 0;
}

我不认为我需要所有那些#include语句,但我看到其他人使用它们所以我包括它们以防万一它会影响我的输出,但事实并非如此.

编辑

所以@Mgetz和@Curious提供的链接非常有用.巩固,

信息页面:http://en.cppreference.com/w/cpp/numeric/random/uniform_int_distribution

超级有用的讲座(真实的,请看这个):https://channel9.msdn.com/Events/GoingNative/2013/rand-Considered-Harmful

我总结了我在讲座中听到的关于我自己的笔记的内容,所以如果我忘记的话,我将不必再重新研究这个.我没有在这里编写代码,大部分代码都在上面链接的"信息页面"中.大多数评论都包含来自讲座的信息,尽管它不是从讲座中逐字逐句.再次,我真的建议观看.它密集,信息良好.

#include <iostream>
#include <random>

int main(int argc, char const *argv[])
{
    /* https://channel9.msdn.com/Events/GoingNative/2013/rand-Considered-Harmful */

    /* Randomness Verson 1 : Deterministic */
    std::mt19937 mt(1234);
    std::uniform_int_distribution<int> dist(0,127);
    /* Default is int, but we could specify others.
     * The range is [inclusive, inclusive]
     * 
     * Above is Mersenne Twister RNG. It is deterministic, meaning we can get the same result
     * if we use "std::mt19937 mt(1234)"; or something like that. This could be useful for some
     * people (He mentions games, some experiments, et cetera). It is stupid fast.
     * 
     * However, it isn't cryptographically secure, but it pretty random as random goes. If you
     * track the output though, you could guess the next numbers, so don't use it for anything
     * secure.
     */

    /* Randomness Verson 2 */
    std::random_device rd;  //Will be used to obtain a seed for the random number engine
    std::mt19937 gen(rd()); //Standard mersenne_twister_engine seeded with rd()
    std::uniform_int_distribution<int> dis(0, 127); // Inclusive
    /* This is not reproducible. This is not deterministic.
     * "Possibly Crypto-secure." Seems like using Random Device makes this near perfect random,
     * assuming some conditions. I'm not a man who's written security software, and if you are 
     * writing security software, I assume you're not looking at StackOverflow to figure out how
     * to do random numbers. The way he talked about it in the lecture made this seem much more 
     * secure, but I'm not sure what I'm talking about when it comes to these things
     */

    for (int i = 0; i < 3; ++i)
    {
        /* Below would output the pure Mersenne Twister output, deterministic. This seems to
         * be pretty random, but it isn't totally random. */
        std::cout << dist(mt) << " ";

        /* And below would output the random device output. This should be slower, but
         * more truly random. */

        //Use dis to transform the random unsigned int generated by gen into an int in [1, 6]
        std::cout << dis(gen) << " ";

        std::cout<< std::endl;
    }
}

Answer 1

使用模数运算符会在得到的"随机数"中产生一定量的偏差.此外,该rand()功能的工作是实现定义的,并不遵循跨平台的标准算法.

考虑使用更现代的C++ 11随机数生成功能,这些功能使用标准的广泛接受的随机数生成算法,这些算法在不同平台上运行相同(当然,给定相同的种子).

请参阅std :: uniform_int_distribution的cppreference页面中的以下示例

#include <random>
#include <iostream>

int main()
{
    std::random_device rd;  //Will be used to obtain a seed for the random number engine
    std::mt19937 gen(rd()); //Standard mersenne_twister_engine seeded with rd()
    std::uniform_int_distribution<> dis(1, 6);

    for (int n=0; n<10; ++n)
        //Use dis to transform the random unsigned int generated by gen into an int in [1, 6]
        std::cout << dis(gen) << ' ';
    std::cout << '\n';
}

这里是链接史蒂芬Levavej一个伟大的谈话转到此更深入https://channel9.msdn.com/Events/GoingNative/2013/rand-Considered-Harmful