From 4e5104a0186bd705b5ed1f57f73375ace60587f6 Mon Sep 17 00:00:00 2001
From: Guillaume Horel <guillaume.horel@serenitascapital.com>
Date: Tue, 12 Apr 2016 12:23:13 -0400
Subject: Rename f_mu as exponential_tilt

and template it instead of having it depend on asian_option
---
 src/projet.cpp              |  8 +++++---
 src/stratified_sampling.hpp | 29 ++++++++++++++---------------
 2 files changed, 19 insertions(+), 18 deletions(-)

(limited to 'src')

diff --git a/src/projet.cpp b/src/projet.cpp
index b4fa5f9..c4bd6d8 100644
--- a/src/projet.cpp
+++ b/src/projet.cpp
@@ -6,6 +6,7 @@
 #include <cmath>
 #include <algorithm>
 #include "opti.hpp"
+#include "option.hpp"
 
 using namespace std;
 
@@ -49,8 +50,9 @@ void exemple1_stratified() {
      vector<double> q = quantile_norm(100, 1);
      vector<double> p(100, 0.01);
      asian_option A(0.05, 1.0, 50, 0.1, d, 45);
-     f_mu G(mu,A);
-     std::vector<compose_t <f_mu, multi_gaussian_truncated> > X;
+     exponential_tilt<asian_option> G(mu, A);
+     typedef compose_t<exponential_tilt<asian_option>, multi_gaussian_truncated> tilted_option;
+     std::vector<tilted_option> X;
      X.push_back(compose(G, multi_gaussian_truncated(GSL_NEGINF,q[0], u)));
      for(int i=1; i<100; i++) {
          X.push_back(compose(G, multi_gaussian_truncated(q[i-1],q[i], u)));
@@ -58,7 +60,7 @@ void exemple1_stratified() {
      for(int i=0; i<100; i=i+10){
          std::cout<<X[i]()<<endl;
      }
-     stratified_sampling<compose_t <f_mu, multi_gaussian_truncated> > S(p, X);
+     stratified_sampling<tilted_option> S(p, X);
      S.draw(1000);
      cout<<"l'estimateur de la moyenne est :"<<S.estimator().first<<endl;
 }
diff --git a/src/stratified_sampling.hpp b/src/stratified_sampling.hpp
index 9099e38..9175f75 100644
--- a/src/stratified_sampling.hpp
+++ b/src/stratified_sampling.hpp
@@ -3,7 +3,6 @@
 #include <iostream>
 #include "var_alea.hpp"
 #include <gsl/gsl_cdf.h>
-#include "option.hpp"
 
 using namespace std;
 
@@ -14,14 +13,14 @@ struct gaussian_truncated : var_alea<double>
 {
     gaussian_truncated(double a, double b, double mu = 0, double sigma = 1)
         :a(a), b(b), V(gsl_cdf_ugaussian_P(a), gsl_cdf_ugaussian_P(b)), mu(mu), sigma(sigma) {};
-    
+
     double operator()() {
         double v = V();
         return mu + gsl_cdf_gaussian_Pinv(v,sigma);
     }
-    
+
     private:
-        double a, b;        
+        double a, b;
         uniform V;
         double mu;
         double sigma;
@@ -31,7 +30,7 @@ struct multi_gaussian_truncated : public var_alea<std::vector<double> >
 {
     multi_gaussian_truncated(double a, double b, const std::vector<double> u)
         :a(a), b(b), V(gsl_cdf_ugaussian_P(a), gsl_cdf_ugaussian_P(b)), G(0,1), u(u), d(u.size()) {};
-    
+
     std::vector<double> operator()() {
         double v = V();
         double Z = gsl_cdf_gaussian_Pinv(v,1);
@@ -49,9 +48,9 @@ struct multi_gaussian_truncated : public var_alea<std::vector<double> >
         }
         return X;
     }
-    
+
     private:
-        double a, b;        
+        double a, b;
         uniform V;
         gaussian G;
         std::vector<double> u;
@@ -180,15 +179,16 @@ pair<double,double> stratified_sampling<L>::estimator() const {
 	return {est_mean, est_std};
 }
 
-struct f_mu : public std::unary_function<std::vector<double>, double> 
+template <typename Fct>
+struct exponential_tilt : public std::unary_function<std::vector<double>, double>
 {
-    f_mu(std::vector<double> mu, asian_option A) : mu(mu), A(A){
+    exponential_tilt(std::vector<double> mu, Fct f) : mu(mu), f(f){
         norm_mu = 0;
         for(unsigned int i=0; i<mu.size(); i++) {
             norm_mu += mu[i]*mu[i];
         }
     };
-    
+
     double operator()(std::vector<double> X) {
         std::vector<double> Y(X.size());
         double scal = 0;
@@ -196,12 +196,11 @@ struct f_mu : public std::unary_function<std::vector<double>, double>
             Y[i] = X[i] + mu[i];
             scal+=X[i]*mu[i];
         }
-        return A(Y)*exp(-scal-0.5*norm_mu);
+        return f(Y) * exp(-scal-0.5*norm_mu);
     };
-        
-    private :
+
+    private:
         std::vector<double> mu;
-        asian_option A;
+        Fct f;
         double norm_mu;
     };
-
-- 
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