Boost C++ Libraries

...one of the most highly regarded and expertly designed C++ library projects in the world. Herb Sutter and Andrei Alexandrescu, C++ Coding Standards

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Tutorial

Generating integers in a range
Generating integers with different probabilities
Generating a random password

For the source of this example see die.cpp. First we include the headers we need for mt19937 and uniform_int_distribution.

#include <boost/random/mersenne_twister.hpp>
#include <boost/random/uniform_int_distribution.hpp>

We use mt19937 with the default seed as a source of randomness. The numbers produced will be the same every time the program is run. One common method to change this is to seed with the current time (std::time(0) defined in ctime).

boost::random::mt19937 gen;

[Note] Note

We are using a global generator object here. This is important because we don't want to create a new pseudo-random number generator at every call

Now we can define a function that simulates an ordinary six-sided die.

int roll_die() {
    1boost::random::uniform_int_distribution<> dist(1, 6);
    2return dist(gen);
}

1

mt19937 produces integers in the range [0, 232-1]. However, we want numbers in the range [1, 6]. The distribution uniform_int_distribution performs this transformation.

[Warning] Warning

Contrary to common C++ usage uniform_int_distribution does not take a half-open range. Instead it takes a closed range. Given the parameters 1 and 6, uniform_int_distribution can produce any of the values 1, 2, 3, 4, 5, or 6.

2

A distribution is a function object. We generate a random number by calling dist with the generator.

For the source of this example see weighted_die.cpp.

#include <boost/random/mersenne_twister.hpp>
#include <boost/random/discrete_distribution.hpp>

boost::mt19937 gen;

This time, instead of a fair die, the probability of rolling a 1 is 50% (!). The other five faces are all equally likely.

discrete_distribution works nicely here by allowing us to assign weights to each of the possible outcomes.

[Tip] Tip

If your compiler supports std::initializer_list, you can initialize discrete_distribution directly with the weights.

double probabilities[] = {
    0.5, 0.1, 0.1, 0.1, 0.1, 0.1
};
boost::random::discrete_distribution<> dist(probabilities);

Now define a function that simulates rolling this die.

int roll_weighted_die() {
    1return dist(gen) + 1;
}

1

Add 1 to make sure that the result is in the range [1,6] instead of [0,5].

For the source of this example see password.cpp.

This example demonstrates generating a random 8 character password.

#include <boost/random/random_device.hpp>
#include <boost/random/uniform_int_distribution.hpp>

int main() {
    1std::string chars(
        "abcdefghijklmnopqrstuvwxyz"
        "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
        "1234567890"
        "!@#$%^&*()"
        "`~-_=+[{]}\\|;:'\",<.>/? ");
    2boost::random::random_device rng;
    3boost::random::uniform_int_distribution<> index_dist(0, chars.size() - 1);
    for(int i = 0; i < 8; ++i) {
        std::cout << chars[index_dist(rng)];
    }
    std::cout << std::endl;
}

1

We first define the characters that we're going to allow. This is pretty much just the characters on a standard keyboard.

2

We use random_device as a source of entropy, since we want passwords that are not predictable.

3

Finally we select 8 random characters from the string and print them to cout.


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