From d2b133901a65244934eb642ec8e20c797efaf650 Mon Sep 17 00:00:00 2001 From: Bertrand Date: Fri, 19 Feb 2016 15:03:51 +0000 Subject: nettoyage du dépôt MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- rqmc.hpp | 127 --------------------------------------------------------------- 1 file changed, 127 deletions(-) delete mode 100644 rqmc.hpp (limited to 'rqmc.hpp') diff --git a/rqmc.hpp b/rqmc.hpp deleted file mode 100644 index 1b33713..0000000 --- a/rqmc.hpp +++ /dev/null @@ -1,127 +0,0 @@ -#include "low_discrepancy.hpp" -#include -#include -#include "var_alea.hpp" - - -double frac_part(double x); - -//fonctions de compositions de monte_carlo.hpp - -template -struct generator -{ - typedef _Result result_type; -}; - -template -struct compose_t : public generator< typename Fct::result_type > -{ - compose_t(Fct f, VA X) : f(f), X(X) {}; - typename Fct::result_type operator()() { - return f(X()); - }; - private: - Fct f; VA X; -}; - -template -inline compose_t -compose(Fct f, VA X) { - return compose_t(f, X); -}; - -template -struct mean_t: public generator -{ - mean_t(int n, VA X): n(n), X(X) {}; - double operator()(){ - double sum = 0; - for(int i=0; i -inline mean_t -mean(int n, VA X){ - return mean_t(n, X); -}; - - -//Les classes de monte-Carlo - -template -std::vector monte_carlo(int n, L X) -{ - std::vector result(3,0); - double x; - for (int j = 0; j < n; j++) { - x = X(); - result[0] += x; - result[1] += x*x; - } - result[0] /= (double) n; - result[1] = (result[1] - n*result[0]*result[0])/(double)(n-1); - result[2] = 1.96*sqrt(result[1]/(double) n); - return result; -}; - -template -std::vector monte_carlo(int n, Fct f, L X) -{ - return monte_carlo(n, compose(f, X)); -}; - -//Les classes de quasi-mean - -template -struct quasi_gaussian : public var_alea > -{ - quasi_gaussian (int d, double mean = 0, double std =1) - : d(d), mean(mean), std(std), s(d), U(0,1), seed(d) { - for(int i=0; i operator ()(){ - std::vector result = s(); - for(int i=0;i seed; -}; - - - -struct gaussian_d : public var_alea > -{ - gaussian_d(int d, double mean = 0, double std =1) - : d(d), mean(mean), std(std), G(mean, std) {}; - std::vector operator ()(){ - std::vector result(d); - for(int i=0;i