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Creating a Gaussian Random Generator with a mean and standard deviation

I am trying to create a one dimensional array and use a random number generator(Gaussian generator that generates a random number with means of 70 and a standard deviation of 10) to populate the array with at least 100 numbers between 0 and 100 inclusive.

How would i go about doing this in C++?

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coder_For_Life22 Avatar asked Nov 13 '13 02:11

coder_For_Life22


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2 Answers

In C++11 this is relatively straight forward using the random header and std::normal_distribution (live example):

#include <iostream>
#include <iomanip>
#include <string>
#include <map>
#include <random>

int main()
{
    std::random_device rd;

    std::mt19937 e2(rd());

    std::normal_distribution<> dist(70, 10);

    std::map<int, int> hist;
    for (int n = 0; n < 100000; ++n) {
        ++hist[std::round(dist(e2))];
    }

    for (auto p : hist) {
        std::cout << std::fixed << std::setprecision(1) << std::setw(2)
                  << p.first << ' ' << std::string(p.second/200, '*') << '\n';
    }
}

If C++11 is not an option than boost also provides a library(live example):

#include <iostream>
#include <iomanip>
#include <string>
#include <map>
#include <random>
#include <boost/random.hpp>
#include <boost/random/normal_distribution.hpp>

int main()
{

  boost::mt19937 *rng = new boost::mt19937();
  rng->seed(time(NULL));

  boost::normal_distribution<> distribution(70, 10);
  boost::variate_generator< boost::mt19937, boost::normal_distribution<> > dist(*rng, distribution);

  std::map<int, int> hist;
  for (int n = 0; n < 100000; ++n) {
    ++hist[std::round(dist())];
  }

  for (auto p : hist) {
    std::cout << std::fixed << std::setprecision(1) << std::setw(2)
              << p.first << ' ' << std::string(p.second/200, '*') << '\n';
  }
}

and if for some reason neither of these options is possible then you can roll your own Box-Muller transform, the code provided in the link looks reasonable.

like image 177
Shafik Yaghmour Avatar answered Oct 29 '22 22:10

Shafik Yaghmour


Use the Box Muller distribution (from here):

double rand_normal(double mean, double stddev)
{//Box muller method
    static double n2 = 0.0;
    static int n2_cached = 0;
    if (!n2_cached)
    {
        double x, y, r;
        do
        {
            x = 2.0*rand()/RAND_MAX - 1;
            y = 2.0*rand()/RAND_MAX - 1;

            r = x*x + y*y;
        }
        while (r == 0.0 || r > 1.0);
        {
            double d = sqrt(-2.0*log(r)/r);
            double n1 = x*d;
            n2 = y*d;
            double result = n1*stddev + mean;
            n2_cached = 1;
            return result;
        }
    }
    else
    {
        n2_cached = 0;
        return n2*stddev + mean;
    }
}

you can read more at: wolframe math world

like image 20
samad montazeri Avatar answered Oct 29 '22 23:10

samad montazeri