1 files changed, 0 insertions, 127 deletions
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 <vector>
-#include <gsl/gsl_cdf.h>
-#include "var_alea.hpp"
-
-
-double frac_part(double x);
-
-//fonctions de compositions de monte_carlo.hpp
-
-template <class _Result>
-struct generator 
-{
-	typedef _Result result_type;
-};
-
-template <typename Fct, typename VA>
-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 <typename Fct, typename VA>
-inline compose_t<Fct, VA>
-compose(Fct f, VA X) {
-    return compose_t<Fct, VA>(f, X);
-};
-
-template <typename VA>
-struct mean_t: public generator<double>
-{
-    mean_t(int n, VA X): n(n), X(X) {};
-    double operator()(){
-        double sum = 0;
-        for(int i=0; i<n; i++){
-            sum+=X();
-        }
-        return sum/n;
-    }
-    private :
-        int n; VA X;
-    };
-    
-template <typename VA>
-inline mean_t<VA>
-mean(int n, VA X){
-    return mean_t<VA>(n, X);
-};
-
-
-//Les classes de monte-Carlo
-
-template <typename L>
-std::vector<double> monte_carlo(int n, L X)
-{
-	std::vector<double> 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 <typename L, typename Fct>
-std::vector<double> monte_carlo(int n, Fct f, L X)
-{
-	return monte_carlo(n, compose(f, X)); 
-};
-
-//Les classes de quasi-mean
-
-template <typename LDS>
-struct quasi_gaussian : public var_alea<std::vector<double> >
-{
-    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<d; i++) {seed[i]=U();}
-                };
-    std::vector<double> operator ()(){
-        std::vector<double> result = s();
-        for(int i=0;i<d; i++){
-            result[i] = mean + gsl_cdf_gaussian_Pinv(frac_part(result[i]+seed[i]), std);
-        }
-        return value = result;
-    }
-    private: 
-    int d;
-    double mean, std;
-    LDS s;
-    uniform U;
-    std::vector<double> seed;
-};
-
-
-
-struct gaussian_d : public var_alea<std::vector<double> >
-{
-    gaussian_d(int d, double mean = 0, double std =1)
-        : d(d), mean(mean), std(std), G(mean, std) {};
-    std::vector<double> operator ()(){
-        std::vector<double> result(d);
-        for(int i=0;i<d; i++){
-            result[i] = G();
-        }
-        return value = result;
-    }
-    private: 
-    int d;
-    double mean, std;
-    gaussian G;
-};
-
-
-
-
-
-