boost random number library, use same random number generator for different variate generators

It seems that one can use the following code to produce random numbers from a particular Normal distribution:

float mean = 0, variance = 1;
boost::mt19937 randgen(static_cast<unsigned int>(std::time(0)));
boost::normal_distribution<float> noise(mean, variance);
variate_generator<mt19937, normal_distribution<float> > nD(randgen, noise);

float random = nD();

This works fine, however, I would like to be able to draw numbers from several distributions, i.e. one would think something like:

float mean1 = 0, variance1 = 1, mean2 = 10, variance2 = 0.25;
boost::mt19937 randgen(static_cast<unsigned int>(std::time(0)));
boost::normal_distribution<float> noise1(mean1, variance1);
boost::normal_distribution<float> noise2(mean2, variance2);
variate_generator<mt19937, normal_distribution<float> > nD(randgen, noise1);
variate_generator<mt19937, normal_distribution<float> > nC(randgen, noise2);

float random1 = nD();
float random2 = nC();

However, the problem appears to be that nD() and nC() are generating similar sequences of numbers. I hypothesize this is because the constructor for variate_generator appears to make a copy of randgen, not use it explicitly. Thus, the same psuedo-random sequence is being generated and simply pushed through different transformations (due to the different parameters of the distributions).

Does anyone know if there is a way, in Boost, to create a single random number generator and use it for multiple distributions? Alternatively, does the design of the Boost random开发者_如何学编程 library intend users to create one random number generator per distribution? Obviously, I could write code to transform a sequence of uniform random numbers to a sequence from an arbitrary distribution, but I'm looking for something simple and already built-in to the library.

Thanks in advance for your help.

Your hypothesis is correct. You want both variate_generator instances to use the same random number generator instance. So use a reference to mt19937 as your template parameter.

variate_generator<mt19937 &, normal_distribution<float> > nD(randgen, noise1);
variate_generator<mt19937 &, normal_distribution<float> > nC(randgen, noise2);

Obviously you'll have to ensure randgen does not go out of scope before nD and nC do.