uniform_real_distribution Class

Generates a uniform (every value is equally probable) floating-point distribution within an output range that is inclusive-exclusive.

template<class RealType = double>
class uniform_real_distribution
{
public:
    // types
    typedef RealType result_type;
    struct param_type;
    // constructors and reset functions
    explicit uniform_real_distribution(RealType a = 0.0, RealType b = 1.0);
    explicit uniform_real_distribution(const param_type& parm);
    void reset();
    // generating functions
    template<class URNG>
    result_type operator()(URNG& gen);
    template<class URNG>
    result_type operator()(URNG& gen, const param_type& parm);
    // property functions
    result_type a() const;
    result_type b() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
};

Parameters

• RealType
  The floating-point result type, defaults to double. For possible types, see <random>.

Remarks

The template class describes an inclusive-exclusive distribution that produces values of a user-specified integral floating point type with a distribution so that every value is equally probable. The following table links to articles about individual members.

The property member a() returns the currently stored minimum bound of the distribution, while b() returns the currently stored maximum bound. For this distribution class, these minimum and maximum values are the same as those returned by the common property functions min() and max() described in the <random> topic.

For more information about distribution classes and their members, see <random>.

Example

// compile with: /EHsc /W4
#include <random> 
#include <iostream>
#include <iomanip>
#include <string>
#include <map>

void test(const double a, const double b, const int s) {

    // uncomment to use a non-deterministic seed
    //    std::random_device rd;
    //    std::mt19937 gen(rd());
    std::mt19937 gen(1729);

    std::uniform_real_distribution<> distr(a,b);

    std::cout << "lower bound == " << distr.a() << std::endl;
    std::cout << "upper bound == " << distr.b() << std::endl;

    // generate the distribution as a histogram
    std::map<double, int> histogram;
    for (int i = 0; i < s; ++i) {
        ++histogram[distr(gen)];
    }

    // print results
    std::cout << "Distribution for " << s << " samples:" << std::endl;
    int counter = 0;
    for (const auto& elem : histogram) {
        std::cout << std::fixed << std::setw(11) << ++counter << ": " 
            << std::setprecision(10) << elem.first << std::endl;
    }
    std::cout << std::endl;
}

int main()
{
    double a_dist = 1.0;
    double b_dist = 1.5;

    int samples = 10;

    std::cout << "Use CTRL-Z to bypass data entry and run using default values." << std::endl;
    std::cout << "Enter a floating point value for the lower bound of the distribution: ";
    std::cin >> a_dist;
    std::cout << "Enter a floating point value for the upper bound of the distribution: ";
    std::cin >> b_dist;
    std::cout << "Enter an integer value for the sample count: ";
    std::cin >> samples;

    test(a_dist, b_dist, samples);
}

Output

Use CTRL-Z to bypass data entry and run using default values.
Enter a floating point value for the lower bound of the distribution: .5
Enter a floating point value for the upper bound of the distribution: 1
Enter an integer value for the sample count: 20
lower bound == 0.5
upper bound == 1
Distribution for 20 samples:
          1: 0.5144304741
          2: 0.6003997192
          3: 0.6060792968
          4: 0.6270416650
          5: 0.6295091197
          6: 0.6437749373
          7: 0.6513740058
          8: 0.7062379346
          9: 0.7117609406
         10: 0.7206888566
         11: 0.7423223702
         12: 0.7826033033
         13: 0.8112872958
         14: 0.8440467608
         15: 0.8461254641
         16: 0.8598305065
         17: 0.8640874069
         18: 0.8770968361
         19: 0.9397858282
         20: 0.9804645012

Requirements

Header: <random>

Namespace: std

See Also

Reference

<random>