我们来看看这个。首先，我们使用srand()函数来为随机化器播种。基本上，计算机可以根据输入给srand()的数字生成随机数。如果你给出相同的种子值，那么每次都会生成相同的随机数。

因此，我们必须用一个总是在变化的值来给随机化器播种。我们通过time()函数将当前时间的值提供给它来实现这一点。

现在，当我们调用rand()时，每次都会产生一个新的随机数。

    #include <stdio.h>

    int random_number(int min_num, int max_num);

    int main(void)
    {
        printf("Min : 1 Max : 40 %d\n", random_number(1,40));
        printf("Min : 100 Max : 1000 %d\n",random_number(100,1000));
        return 0;
    }

    int random_number(int min_num, int max_num)
    {
        int result = 0, low_num = 0, hi_num = 0;

        if (min_num < max_num)
        {
            low_num = min_num;
            hi_num = max_num + 1; // include max_num in output
        } else {
            low_num = max_num + 1; // include max_num in output
            hi_num = min_num;
        }

        srand(time(NULL));
        result = (rand() % (hi_num - low_num)) + low_num;
        return result;
    }

在我最近的应用程序中，我遇到了一个严重的伪随机数生成器问题:我多次通过Python脚本调用我的C程序，并使用以下代码作为种子:

srand(time(NULL))

然而,由于:

Rand将生成相同的伪随机序列，在srand中给出相同的种子(参见man srand); 如前所述，time函数每秒只会变化:如果应用程序在同一秒内运行多次，time每次都会返回相同的值。

我的程序生成了相同的数字序列。 你可以做三件事来解决这个问题:

mix time output with some other information changing on runs (in my application, the output name): srand(time(NULL) | getHashOfString(outputName)) I used djb2 as my hash function. Increase time resolution. On my platform, clock_gettime was available, so I use it: #include<time.h> struct timespec nanos; clock_gettime(CLOCK_MONOTONIC, &nanos) srand(nanos.tv_nsec); Use both methods together: #include<time.h> struct timespec nanos; clock_gettime(CLOCK_MONOTONIC, &nanos) srand(nanos.tv_nsec | getHashOfString(outputName));

选项3确保了你(据我所知)最好的种子随机性，但它可能只会在非常快速的应用中产生差异。 在我看来，选择2是一个安全的赌注。

注意:为了安全性，不要使用rand()。如果您需要加密安全的号码，请参阅此答案。

#include <time.h>
#include <stdlib.h>

srand(time(NULL));   // Initialization, should only be called once.
int r = rand();      // Returns a pseudo-random integer between 0 and RAND_MAX.

在Linux上，您可能更喜欢使用random和srandom。

你也可以使用mathgl库#include <mgl2/mgl_cf.h>(虽然首先你需要安装它，我自己通过MSYS2安装)函数mgl_rnd()。它也有均匀分布，高斯分布等等。这是ez的用法。但我不知道它的特点。

试试这个，我把上面已经提到的一些概念放在一起:

/*    
Uses the srand() function to seed the random number generator based on time value,
then returns an integer in the range 1 to max. Call this with random(n) where n is an integer, and you get an integer as a return value.
 */

int random(int max) {
    srand((unsigned) time(NULL));
    return (rand() % max) + 1;
}

下面是我的方法(围绕rand()的包装器):

我还扩展到允许min为INT_MIN而max为INT_MAX的情况，这通常不可能单独使用rand()，因为它返回从0到RAND_MAX的值，包括(1/2范围)。

像这样使用它:

const int MIN = 1;
const int MAX = 1024;
// Get a pseudo-random number between MIN and MAX, **inclusive**.
// Seeding of the pseudo-random number generator automatically occurs
// the very first time you call it.
int random_num = utils_rand(MIN, MAX);

定义和氧描述:

#include <assert.h>
#include <stdbool.h>
#include <stdlib.h>

/// \brief      Use linear interpolation to rescale, or "map" value `val` from range
///             `in_min` to `in_max`, inclusive, to range `out_min` to `out_max`, inclusive.
/// \details    Similar to Arduino's ingenious `map()` function:
///             https://www.arduino.cc/reference/en/language/functions/math/map/
///
/// TODO(gabriel): turn this into a gcc statement expression instead to prevent the potential for
/// the "double evaluation" bug. See `MIN()` and `MAX()` above.
#define UTILS_MAP(val, in_min, in_max, out_min, out_max) \
    (((val) - (in_min)) * ((out_max) - (out_min)) / ((in_max) - (in_min)) + (out_min))

/// \brief      Obtain a pseudo-random integer value between `min` and `max`, **inclusive**.
/// \details    1. If `(max - min + 1) > RAND_MAX`, then the range of values returned will be
///             **scaled** to the range `max - min + 1`, and centered over the center of the
///             range at `(min + max)/2`. Scaling the numbers means that in the case of scaling,
///             not all numbers can even be reached. However, you will still be assured to have
///             a random distribution of numbers across the full range.
///             2. Also, the first time per program run that you call this function, it will
///             automatically seed the pseudo-random number generator with your system's
///             current time in seconds.
/// \param[in]  min         The minimum pseudo-random number you'd like, inclusive. Can be positive
///                         OR negative.
/// \param[in]  max         The maximum pseudo-random number you'd like, inclusive. Can be positive
///                         OR negative.
/// \return     A pseudo-random integer value between `min` and `max`, **inclusive**.
int utils_rand(int min, int max)
{
    static bool first_run = true;
    if (first_run)
    {
        // seed the pseudo-random number generator with the seconds time the very first run
        time_t time_now_sec = time(NULL);
        srand(time_now_sec);
        first_run = false;
    }

    int range = max - min + 1;
    int random_num = rand();  // random num from 0 to RAND_MAX, inclusive

    if (range > RAND_MAX)
    {
        static_assert(
            sizeof(long int) > sizeof(int),
            "This must be true or else the below mapping/scaling may have undefined overflow "
            "and not work properly. In such a case, try casting to `long long int` instead of "
            "just `long int`, and update this static_assert accordingly.");

        random_num = UTILS_MAP((long int)random_num, (long int)0, (long int)RAND_MAX, (long int)min,
                               (long int)max);
        return random_num;
    }

    // This is presumably a faster approach than the map/scaling function above, so do this faster
    // approach below whenever you don't **have** to do the more-complicated approach above.
    random_num %= range;
    random_num += min;

    return random_num;
}

参见:

[我在写下上面的答案后发现了这个问答，但它显然非常相关，他们对非缩放范围的情况做了同样的事情]我如何从rand()中获得特定的数字范围? [我需要进一步研究和阅读这个答案-似乎有一些好的观点，保持良好的随机性不使用模量]我如何从rand()得到一个特定的数字范围? http://c-faq.com/lib/randrange.html