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std::normal_distribution

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std::normal_distribution
 
Defined in header <random>
template< class RealType = double >
class normal_distribution;
(since C++11)

Generates random numbers according to the Normal (or Gaussian) random number distribution. It is defined as:

f(x; μ,σ) =
1
σ
exp

-1
2


x-μ
σ


2


Here μ is the Mean and σ is the Standard deviation (stddev).

std::normal_distribution satisfies all requirements of RandomNumberDistribution.

Contents

[edit] Template parameters

RealType - The result type generated by the generator. The effect is undefined if this is not one of float, double, or long double.

[edit] Member types

Member type Definition
result_type (C++11) RealType
param_type (C++11) the type of the parameter set, see RandomNumberDistribution.

[edit] Member functions

constructs new distribution
(public member function) [edit]
(C++11)
resets the internal state of the distribution
(public member function) [edit]
Generation
generates the next random number in the distribution
(public member function) [edit]
Characteristics
returns the distribution parameters
(public member function) [edit]
(C++11)
gets or sets the distribution parameter object
(public member function) [edit]
(C++11)
returns the minimum potentially generated value
(public member function) [edit]
(C++11)
returns the maximum potentially generated value
(public member function) [edit]

[edit] Non-member functions

(C++11)(C++11)(removed in C++20)
compares two distribution objects
(function) [edit]
performs stream input and output on pseudo-random number distribution
(function template) [edit]

[edit] Example

#include <cmath>
#include <iomanip>
#include <iostream>
#include <map>
#include <random>
#include <string>
 
int main()
{
    std::random_device rd{};
    std::mt19937 gen{rd()};
 
    // values near the mean are the most likely
    // standard deviation affects the dispersion of generated values from the mean
    std::normal_distribution d{5.0, 2.0};
 
    // draw a sample from the normal distribution and round it to an integer
    auto random_int = [&d, &gen]{ return std::round(d(gen)); };
 
    std::map<int, int> hist{};
    for (int n = 0; n != 10000; ++n)
        ++hist[random_int()];
 
    for (auto [x, y] : hist)
        std::cout << std::setw(2) << x << ' ' << std::string(y / 200, '*') << '\n';
}

Possible output:

-2
-1
 0
 1 *
 2 ***
 3 ******
 4 ********
 5 **********
 6 ********
 7 *****
 8 ***
 9 *
10
11
12

[edit] External links

1.  Weisstein, Eric W. "Normal Distribution." From MathWorld — A Wolfram Web Resource.
2.  Normal distribution — From Wikipedia.