Adding filtering step. TODO: Bug in python

sigopt · Jan 13, 2018 · 6ed8282 · 6ed8282
1 parent ee8e5f9
commit 6ed8282
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Showing 13 changed files with 2,765 additions and 1,292 deletions.
diff --git a/CMakeLists.txt b/CMakeLists.txt
@@ -87,6 +87,7 @@ SET( BAYESOPT_SRCS
   ./src/bayesoptdisc.cpp
   ./src/bayesoptbase.cpp
   ./src/bopt_state.cpp
+  ./src/robust_filtering.cpp
   ./src/posteriormodel.cpp
   ./src/posterior_fixed.cpp
   ./src/posterior_empirical.cpp

diff --git a/include/bayesopt/bayesoptbase.hpp b/include/bayesopt/bayesoptbase.hpp
@@ -45,6 +45,7 @@ namespace bayesopt {
   class ProbabilityDistribution;
   class Dataset;
   class BOptState;
+  class RobustFiltering;
 
   typedef boost::numeric::ublas::vector<double>                   vectord;
   typedef boost::numeric::ublas::vector<int>                      vectori;
@@ -203,10 +204,11 @@ namespace bayesopt {
 
   private:
     boost::scoped_ptr<PosteriorModel> mModel;
-    boost::scoped_ptr<PosteriorModel> mRobustModel;
+    boost::scoped_ptr<RobustFiltering> mFilter;
     double mYPrev;
     size_t mCounterStuck;
     bool mUseRobust;
+
   private:
 
     BayesOptBase();

diff --git a/include/bayesopt/parameters.h b/include/bayesopt/parameters.h
@@ -128,6 +128,11 @@ extern "C" {
     char* crit_name;             /**< Name of the criterion */
     double crit_params[128];     /**< Criterion hyperparameters (if needed) */
     size_t n_crit_params;        /**< Number of criterion hyperparameters */
+
+    int filtering_startup;
+    int filtering_interval;
+    double up_margin;
+    double low_margin;
   } bopt_params;
 
   /*-----------------------------------------------------------*/

diff --git a/include/bayesopt/parameters.hpp b/include/bayesopt/parameters.hpp
@@ -109,7 +109,13 @@ namespace bayesopt {
 
         std::string crit_name;      /**< Name of the criterion */
         vectord crit_params;        /**< Criterion hyperparameters (if needed) */
-
+
+        int filtering_startup;
+        int filtering_interval;
+        double up_margin;
+        double low_margin;
+
+
         /*
          * Class member functions 
          */

diff --git a/include/dataset.hpp b/include/dataset.hpp
@@ -73,7 +73,7 @@ namespace bayesopt
   inline void Dataset::addSample(const vectord &x, double y)
   {
     mX.push_back(x); utils::append(mY,y);
-    updateMinMax(mY.size()-1);
+    updateMinMax();
   }
 
   inline double Dataset::getSampleY(size_t index) const

diff --git a/include/gauss_distribution.hpp b/include/gauss_distribution.hpp
@@ -51,13 +51,13 @@ namespace bayesopt
      */
     double pdf(double x) 
     {
-      x = (x - mean_) / std_;
-      return boost::math::pdf(d_,x); 
+      double xu = (x - mean_) / std_;
+      return boost::math::pdf(d_,xu); 
     };
 
     double quantile(double p) 
     {
-      x = boost::math::quantile(d_,p);
+      double x = boost::math::quantile(d_,p);
       return (x - mean_) / std_;
     };
 

diff --git a/include/posteriormodel.hpp b/include/posteriormodel.hpp
@@ -80,7 +80,7 @@ namespace bayesopt {
     vectord getPointAtMinimum();
 
     void plotDataset(TLogLevel level);
-i
+
     const Dataset* getData();
     void setData(const Dataset* data);
     void copyData(const Dataset* data);

diff --git a/include/student_t_distribution.hpp b/include/student_t_distribution.hpp
@@ -62,13 +62,13 @@ namespace bayesopt
      */
     double pdf(double x) 
     {
-      x = (x - mean_) / std_;
-      return boost::math::pdf(d_,x); 
+      double xu = (x - mean_) / std_;
+      return boost::math::pdf(d_,xu); 
     };
 
     double quantile(double p) 
     {
-      x = boost::math::quantile(d_,p);
+      double x = boost::math::quantile(d_,p);
       return (x - mean_) / std_;
     };