1 files changed, 13 insertions, 8 deletions

diff --git a/stratified_sampling.hpp b/stratified_sampling.hpp
index 0b0b4ef..e25ac63 100644
--- a/stratified_sampling.hpp
+++ b/stratified_sampling.hpp
@@ -22,33 +22,33 @@ typedef var_alea<double> var_alea_real;
 
 struct gaussian_truncated : public var_alea_real
 {
-    gaussian_truncated(double a, double b, double mean=0, double sigma=1, int seed=0)
-        :a(a), b(b), mean(mean), sigma(sigma), seed(seed) {
+    gaussian_truncated(double a, double b, double mean=0, double sigma2=1, int seed=0)
+        :a(a), b(b), mean(mean), sigma2(sigma2), seed(seed) {
         const gsl_rng_type* type = gsl_rng_default;
         gen = gsl_rng_alloc(type);
         gsl_rng_set(gen, seed);
     };
     gaussian_truncated(gaussian_truncated const &other)
-        :a(other.a),b(other.b), mean(other.mean),sigma(other.sigma){
+        :a(other.a),b(other.b), mean(other.mean),sigma2(other.sigma2){
         gen = gsl_rng_clone(other.gen);
     };
 
     double operator()() {
-        pair<double, double> p = rtnorm(gen, a, b, mean, sigma);
+        pair<double, double> p = rtnorm(gen, a, b, mean, sigma2);
         return value = p.first;
     };
 
     ~gaussian_truncated() { gsl_rng_free(gen); }
 private:
     int seed;
-    double mean, sigma, a, b;
+    double mean, sigma2, a, b;
     gsl_rng *gen;
 };
 
 template <typename Gen>
 struct stratified_sampling {
     stratified_sampling(vector<double> p, vector<Gen> gen)
-        :p(p), gen(gen), mean(p.size(), 0), sigma(p.size(), 0){};
+        :p(p), gen(gen), mean(p.size(), 0), sigma2(p.size(), 0){};
     void update(int N);
     void draw();
     vector<double> get_mean();
@@ -58,7 +58,7 @@ private:
     vector<int> M;
     vector<int> cumM;
     vector<double> mean;
-    vector<double> sigma;
+    vector<double> sigma2;
     vector<Gen> gen;
 
 };
@@ -88,6 +88,11 @@ void stratified_sampling<Gen>::update(int Nk) {
         }
     }
     else {
+				//On remplit un vecter des écarts types à parti de notre vecteur de variance
+				std::vector<double> sigma(p.size(),0);
+				for (int i=0; i < I; i++) {
+					sigma[i]=sqrt(sigma2[i]);
+				}
         double scal = std::inner_product(p.begin(), p.end(), sigma.begin(), (double) 0);
         for (int i=0; i < I; i++) {
             m[i] = (Nk-I)*p[i]*sigma[i]/scal;
@@ -117,7 +122,7 @@ void stratified_sampling<Gen>::draw() {
         }
         oldmean=mean[i];
         mean[i]=(mean[i]*cumM[i]+m)/(cumM[i]+M[i]);
-        sigma[i]=((sigma[i]+oldmean*oldmean)*cumM[i] + s)/(cumM[i]+M[i]) - mean[i]*mean[i];
+        sigma2[i]=((sigma2[i]+oldmean*oldmean)*cumM[i] + s)/(cumM[i]+M[i]) - mean[i]*mean[i];
     }
 };