RandomMatrices.hpp

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#ifndef RANDOM_MATRICES_HPP
#define RANDOM_MATRICES_HPP
#include "Eigen/Dense"
#include <iostream>
#include <random>
 
template<typename RealType = double>
class GUEgenerator {
    private:
        std::mt19937                       mt;
        std::normal_distribution<RealType> Gaussian;
        mutable unsigned long long         count;
 
    public:
        GUEgenerator(int seed = 0, RealType stddev = 1.0)
            : mt(seed), Gaussian{0.0, stddev}, count{0} {};
 
        template<typename EigenMatrix>
        void operator()(EigenMatrix& mat) {
            mat = mat.NullaryExpr(mat.rows(), mat.cols(), [&]() {
                return Complex_t<RealType>(Gaussian(mt), Gaussian(mt));
            });
            mat = (mat + mat.adjoint().eval()) / 2.0;
            count += 2 * mat.size();
        }
 
        void status(void) const {
            std::cout << "GUEgenerator.status()"
                      << "\n";
            std::cout << "\tMean:   " << Gaussian.mean() << "\n";
            std::cout << "\tStddev: " << Gaussian.stddev() << "\n";
            std::cout << "\tCount:  " << this->count << std::endl;
        }
 
        void discard(unsigned long long num) {
            for(auto j = 0; j < num; ++j) Gaussian(mt);
            count += num;
        }
 
        template<typename EigenMatrix>
        void discard(EigenMatrix const& mat, unsigned long long num) {
            this->discard(num * 2 * mat.size());
        }
};
 
template<typename RealType = double>
class GOEgenerator {
    private:
        std::mt19937                       mt;
        std::normal_distribution<RealType> Gaussian;
        unsigned long long                 count;
 
    public:
        GOEgenerator(int seed = 0, RealType stddev = 1.0)
            : mt(seed), Gaussian{0.0, stddev}, count{0} {};
 
        template<typename EigenMatrix>
        void operator()(EigenMatrix& res) {
            res = res.NullaryExpr(res.rows(), res.cols(), [&]() { return Gaussian(mt); });
            res = (res + res.transpose().eval()) / 2.0;
            count += res.size();
        }
 
        void status(void) const {
            std::cout << "GOEgenerator.status()"
                      << "\n";
            std::cout << "\tMean:   " << Gaussian.mean() << "\n";
            std::cout << "\tStddev: " << Gaussian.stddev() << "\n";
            std::cout << "\tCount:  " << this->count << std::endl;
        }
 
        void discard(unsigned long long num) {
            mt.discard(num);
            count += num;
        }
 
        template<typename EigenMatrix>
        void discard(EigenMatrix const& mat, unsigned long long num = 1) {
            this->discard(num * mat.size());
        }
};
 
#endif