From 67a28837c6bbb05d2636a70955a665a88696b96f Mon Sep 17 00:00:00 2001
From: Guillaume Horel <guillame.horel@gmail.com>
Date: Sun, 7 Feb 2016 15:04:55 -0500
Subject: passe à quatre espaces pour les tabs
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---
 main.cpp                | 36 +++++++++++++++---------------
 stratified_sampling.cpp | 58 ++++++++++++++++++++++++-------------------------
 2 files changed, 46 insertions(+), 48 deletions(-)

diff --git a/main.cpp b/main.cpp
index c1eb3ec..88617c4 100644
--- a/main.cpp
+++ b/main.cpp
@@ -10,26 +10,26 @@
 
 //--génération quantiles--
 std::vector<double> quantile_norm(int n, double sigma){
-  std::vector<double> q(n);
-  for (int i=0; i<n; i++) {
-    q[i] = gsl_cdf_gaussian_Pinv ((double)(i+1)/n, sigma);
-  }
-  return q;
+    std::vector<double> q(n);
+    for (int i=0; i<n; i++) {
+        q[i] = gsl_cdf_gaussian_Pinv ((double)(i+1)/n, sigma);
+    }
+    return q;
 }
 
 int main()
 {
-  //--- GSL random init ---
-  gsl_rng_env_setup();
-  std::vector<double> q;
-  q = quantile_norm(10, 1);
-  vector<double> p(10, 0.1);
-  vector<gaussian_truncated> gen;
-  gen.push_back(gaussian_truncated(GSL_NEGINF,q[0]));
-  for (int i=1; i<10; i++){
-    gen.push_back(gaussian_truncated(q[i-1],q[i]));
-  }
-  stratified_sampling<gaussian_truncated> S(p, gen);
-  //S.update(1000);
-  return 0;
+    //--- GSL random init ---
+    gsl_rng_env_setup();
+    std::vector<double> q;
+    q = quantile_norm(10, 1);
+    vector<double> p(10, 0.1);
+    vector<gaussian_truncated> gen;
+    gen.push_back(gaussian_truncated(GSL_NEGINF,q[0]));
+    for (int i=1; i<10; i++){
+        gen.push_back(gaussian_truncated(q[i-1],q[i]));
+    }
+    stratified_sampling<gaussian_truncated> S(p, gen);
+    //S.update(1000);
+    return 0;
 }
diff --git a/stratified_sampling.cpp b/stratified_sampling.cpp
index c03d447..b959776 100644
--- a/stratified_sampling.cpp
+++ b/stratified_sampling.cpp
@@ -13,41 +13,39 @@ 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
 template <typename Gen>
 void stratified_sampling<Gen>::update(int Nk) {
-  int I = p.size();
-  //reinitialistation du vecteur M du nombre de tirages par strates
-  if (M.empty()) {
-    M.resize(I,1);
-  }
-  else {
-    for(int i=0; i<I; i++){
-      M[i]=1;
+    int I = p.size();
+    //reinitialistation du vecteur M du nombre de tirages par strates
+    if (M.empty()) {
+        M.resize(I,1);
+    }
+    else {
+        for(int i=0; i<I; i++){
+            M[i]=1;
+        }
     }
-  }
-  
-  std::vector<double> m(I, 0); //le vecteur des m_i idéals
 
-  if (sigma.empty()) {
-    for (int i=0; i<I; i++) {
-      m[i] = (Nk-I)*p[i];
+    std::vector<double> m(I, 0); //le vecteur des m_i idéals
+
+    if (sigma.empty()) {
+        for (int i=0; i<I; i++) {
+            m[i] = (Nk-I)*p[i];
+        }
     }
-  }
-  else {
-    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;
-      std::cout<<m[i]<<std::endl;
+    else {
+        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;
+            std::cout<<m[i]<<std::endl;
+        }
+    }
+    M[0]+=floor(m[0]);
+    double current = m[0];
+    for (int i=1; i<I; i++){
+        M[i] += floor(current+m[i]) - floor(current);
+        current += m[i];
     }
-  }
-  M[0]+=floor(m[0]);
-  double current = m[0];
-  for (int i=1; i<I; i++){
-    M[i] += floor(current+m[i]) - floor(current);
-    current += m[i];
-  }
-  
 }
-			
-
-- 
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