normal_distribution Class

 

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Generates a normal distribution.

class normal_distribution  
   {  
   public:  // types  
   typedef RealType result_type;  
   struct param_type;  // constructors and reset functions  
   explicit normal_distribution(RealType mean = 0.0, RealType stddev = 1.0);
   explicit normal_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  
   RealType mean() const;
   RealType stddev() 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>.

The template class describes a distribution that produces values of a user-specified integral type, or type double if none is provided, distributed according to the Normal Distribution. The following table links to articles about individual members.

normal_distribution::normal_distributionnormal_distribution::meannormal_distribution::param
normal_distribution::operator()normal_distribution::stddevnormal_distribution::param_type

The property functions mean() and stddev() return the values for the stored distribution parameters mean and stddev respectively.

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

For detailed information about the Normal distribution, see the Wolfram MathWorld article Normal Distribution.

// compile with: /EHsc /W4  
#include <random>   
#include <iostream>  
#include <iomanip>  
#include <string>  
#include <map>  
  
using namespace std;  
  
void test(const double m, const double s, const int samples) {  
  
    // uncomment to use a non-deterministic seed  
    //    random_device gen;  
    //    mt19937 gen(rd());  
    mt19937 gen(1701);  
  
    normal_distribution<> distr(m, s);  
  
    cout << endl;  
    cout << "min() == " << distr.min() << endl;  
    cout << "max() == " << distr.max() << endl;  
    cout << "m() == " << fixed << setw(11) << setprecision(10) << distr.mean() << endl;  
    cout << "s() == " << fixed << setw(11) << setprecision(10) << distr.stddev() << endl;  
  
    // generate the distribution as a histogram  
    map<double, int> histogram;  
    for (int i = 0; i < samples; ++i) {  
        ++histogram[distr(gen)];  
    }  
  
    // print results  
    cout << "Distribution for " << samples << " samples:" << endl;  
    int counter = 0;  
    for (const auto& elem : histogram) {  
        cout << fixed << setw(11) << ++counter << ": "  
            << setw(14) << setprecision(10) << elem.first << endl;  
    }  
    cout << endl;  
}  
  
int main()  
{  
    double m_dist = 1;  
    double s_dist = 1;  
    int samples = 10;  
  
    cout << "Use CTRL-Z to bypass data entry and run using default values." << endl;  
    cout << "Enter a floating point value for the 'mean' distribution parameter: ";  
    cin >> m_dist;  
    cout << "Enter a floating point value for the 'stddev' distribution parameter (must be greater than zero): ";  
    cin >> s_dist;  
    cout << "Enter an integer value for the sample count: ";  
    cin >> samples;  
  
    test(m_dist, s_dist, samples);  
}  
  

Use CTRL-Z to bypass data entry and run using default values.  
Enter a floating point value for the 'mean' distribution parameter: 0  
Enter a floating point value for the 'stddev' distribution parameter (must be greater than zero): 1  
Enter an integer value for the sample count: 10  
 
min() == -1.79769e+308  
max() == 1.79769e+308  
m() == 0.0000000000  
s() == 1.0000000000  
Distribution for 10 samples:  
    1: -0.8845823965  
    2: -0.1995761116  
    3: -0.1162665130  
    4: -0.0685154932  
    5: 0.0403741461  
    6: 0.1591327792  
    7: 1.0414389924  
    8: 1.5876269426  
    9: 1.6362637713  
    10: 2.7821317338  

Header: <random>

Namespace: std

Constructs the distribution.

explicit normal_distribution(RealType mean = 0.0, RealType stddev = 1.0);

 
explicit normal_distribution(const param_type& parm);

Parameters

mean
The mean distribution parameter.

stddev
The stddev distribution parameter.

parm
The parameter structure used to construct the distribution.

Remarks

Precondition: 0.0 ≤ stddev

The first constructor constructs an object whose stored mean value holds the value mean and whose stored stddev value holds the value stddev.

The second constructor constructs an object whose stored parameters are initialized from parm. You can obtain and set the current parameters of an existing distribution by calling the param() member function.

Stores the parameters of the distribution.

struct param_type {  
   typedef normal_distribution<RealType> distribution_type;  
   param_type(RealType mean = 0.0, RealType stddev = 1.0);
   RealType mean() const;
   RealType stddev() const;
   .....  
   bool operator==(const param_type& right) const;
   bool operator!=(const param_type& right) const;
   };  

Parameters

See parent topic normal_distribution Class.

Remarks

Precondition: 0.0 ≤ stddev

This structure can be passed to the distribution's class constructor at instantiation, to the param() member function to set the stored parameters of an existing distribution, and to operator() to be used in place of the stored parameters.

<random>

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