fonction d'update du nombres de tirages par strates

1 files changed, 51 insertions, 3 deletions

diff --git a/stratified_sampling.cpp b/stratified_sampling.cpp
index f6c3ff1..4703aba 100644
--- a/stratified_sampling.cpp
+++ b/stratified_sampling.cpp
@@ -1,9 +1,16 @@
 #include <iostream>
 #include <gsl/gsl_rng.h>
-
+#include <vector>
 #include "rtnorm.hpp"
 #include <gsl/gsl_cdf.h>
 #include <gsl/gsl_math.h>
+#define LOW_DISCREPANCY_HPP
+#include <cmath>
+#include <climits>
+#include <list>
+#include <algorithm>
+#include <numeric>
+
 
 //--génération quantiles--
 std::vector<double> quantile_norm(int n, double sigma){
@@ -35,6 +42,37 @@ std::pair<double, double> mean_var( std::vector<double> r){
     p.second -= p.first * p.first;
     return p;
 }
+//actualisation du nombre de tirages à faire par strates
+std::vector<int> update_sampling (std::vector<double> p, 
+std::vector<double> sigma, int n) {
+	std::vector<int> r; // notre vecteur final à retourner
+	std::vector<double> m; //le vecteur des Mi idéals 
+	int s = p.size();
+	if (sigma.empty()) {
+		for (int i = 0; i<s ; i++) {
+			m.push_back(double(n)*p[i]);
+		}
+	}
+	else {
+		double scal = std::inner_product(p.begin(), p.end(), sigma.begin(), (double) 0);
+		for (int i=0; i<s; i++) {
+			double v = p[i]*sigma[i]/scal;
+			m.push_back(v*n);
+			std::cout<<m[i]<<std::endl;
+		}
+	}
+	r.push_back((int)(m[0]));
+	double v1 = 0;
+	for (int i=1; i<s-1; i++){
+		for (int j=0; j<i; j++) {
+			v1=v1+m[j];
+		}
+		r.push_back((int)v1 - (int)(v1-m[i]));
+	}
+	r.push_back(n - std::accumulate( r.begin(), r.end(), 0 ));
+	return r;
+}
+			
 
 int main()
 {
@@ -44,7 +82,7 @@ int main()
   gsl_rng *gen = gsl_rng_alloc (type);          // Rand generator allocation
   std::vector<double> q;
   q = quantile_norm(10, 1);
-  std::cout<<q[5]<<std::endl;
+
 
   std::pair<double, double> p;
   std::pair<double, double> mv;
@@ -65,8 +103,18 @@ int main()
           r[j] = p.first;
       }
       mv = mean_var(r);
-      std::cout<<"mean :"<<mv.first<<" var :"<<mv.second<<std::endl;
+      //std::cout<<"mean :"<<mv.first<<" var :"<<mv.second<<std::endl;
   }
+  std::vector<int> k;
+  std::vector<double> z = {(double)1/3,(double)1/3,(double)1/3};
+	std::vector<double> sigma = {0.1, 0.4, 0.3};
+	k = update_sampling(z, sigma, 10000);
+	for (int j=0; j<k.size(); j++){
+		std::cout<<k[j]<<std::endl;
+	}
   gsl_rng_free(gen);
+
+		
+  
   return 0;
 }