python - Gaussian distribution with mean and sigma in C++11 -

i trying gaussian distribution mean , sigma in c++11. have been successful @ converting python c++ have doubt way initializing random generator. need call random_device() , mt19937() inside call distribution or can call them once statically , re-use time? cost of leaving code is?

# python  # random.gauss(mu, sigma) # gaussian distribution. mu mean, , sigma standard deviation.  import random  result = random.gauss(mu, sigma)   // c++11  #include <random>  std::random_device rd; std::mt19937 e2(rd());  float res = std::normal_distribution<float>(m, s)(e2); 

there 2 parts of algorithm:

• uniform random number generator,
• and convert uniform random number random number according gaussian distribution.

in case, e2 uniform random number generator given seed rd, std::normal_distribution<float>(m, s) generates object 2nd part of algorithm.

the best way is:

// call first time (initialization) std::random_device rd; std::mt19937 e2(rd()); std::normal_distribution<float> dist(m, s); // bind distribution generator , uniform generator auto gen_gaussian = std::bind(dist, e2);  // call when need generate random number float gaussian = gen_gaussian(); 

if don't care uniform random number generator use, can use std::default_random_engine instead of std:mt19937.