refactoring

mlmc/src/Main.hpp

@@ -6,7 +6,7 @@
 #include "MultilevelMonteCarlo.hpp"
 #include "MonteCarlo.hpp"
 
-#include "IEstimator.hpp"
+#include "Estimator.hpp"
 
 
 bool PowerOfTwo(int n) {
@@ -14,7 +14,7 @@ bool PowerOfTwo(int n) {
   return (ceil(log2(n)) == floor(log2(n)));
 }
 
-std::unique_ptr<IEstimator> CreateEstimator(const std::string &estimator) {
+std::unique_ptr<Estimator> CreateEstimator(const std::string &estimator) {
   if (estimator == "MultilevelStochasticCollocation")
     return std::make_unique<MultilevelStochasticCollocation>();
   if (estimator == "StochasticCollocation")
@@ -33,7 +33,7 @@ private:
   std::string estimatorName = "MultilevelMonteCarlo";
 
 public:
-  std::unique_ptr<IEstimator> estimator;
+  std::unique_ptr<Estimator> estimator;
 
   MainProgram() {
     config.get("MainVerbose", verbose);

mlmc/src/estimators/CMakeLists.txt

 add_library(MONTECARLO STATIC
         MonteCarlo.cpp
         MultilevelMonteCarlo.cpp
-        datastructure/Errors.cpp
+        datastructure/MultilevelErrors.cpp
         datastructure/Exponents.cpp
         datastructure/WelfordAggregate.cpp
         datastructure/EmpiricMeasureLevelMaps.cpp

mlmc/src/estimators/IEstimator.hpp → mlmc/src/estimators/Estimator.hpp

-#ifndef IESTIMATOR_HPP
-#define IESTIMATOR_HPP
+#ifndef ESTIMATOR_HPP
+#define ESTIMATOR_HPP
 
-#include "Config.hpp"
+#include "WelfordAggregate.hpp"
 
-//#include "Errors.hpp"
+#include "Errors.hpp"
 
 struct Exponents;
 
-class IEstimator {
+class Estimator {
 protected:
   double epsilon = 0.0;
 
-//  Errors errors;
+  Errors errors;
 
 public:
-  IEstimator() {
+  WelfordAggregate aggregate;
+
+  Estimator() {
     config.get("epsilon", epsilon);
   }
 
@@ -24,11 +26,11 @@ public:
 
   double Epsilon() const { return epsilon; }
 
-  virtual void Method() = 0;
+  virtual void Method() {};
 
-  virtual std::string Name() const = 0;
+  virtual std::string Name() const { return "Estimator"; };
 
-  virtual void EstimatorResults() const = 0;
+  virtual void EstimatorResults() const {};
 
   virtual void MultilevelResults() const {};
 
@@ -36,4 +38,4 @@ public:
 
 };
 
-#endif //IESTIMATOR_HPP
+#endif //ESTIMATOR_HPP

mlmc/src/estimators/MonteCarlo.hpp

@@ -3,12 +3,12 @@
 
 #include "WelfordAggregate.hpp"
 #include "PDESolverCreator.hpp"
-#include "IEstimator.hpp"
+#include "Estimator.hpp"
 
 #include "MeshesCreator.hpp"
 
 
-class MonteCarlo : public IEstimator {
+class MonteCarlo : public Estimator {
 protected:
   int verbose = 1;
 

mlmc/src/estimators/MultilevelMonteCarlo.hpp

@@ -4,17 +4,15 @@
 #include "EmpiricMeasureLevelMaps.hpp"
 #include "MonteCarlo.hpp"
 #include "Exponents.hpp"
-#include "Errors.hpp"
+#include "MultilevelErrors.hpp"
 #include "Utilities.hpp"
-#include "IEstimator.hpp"
+#include "Estimator.hpp"
 
 
-class MultilevelMonteCarlo : public IEstimator {
+class MultilevelMonteCarlo : public Estimator {
 private:
   int verbose = 1;
 
-  bool mcOnly = false;
-
   // Levels init{3, 4, 5};
   std::vector<int> initLevels{3, 4, 5};
 
@@ -22,20 +20,16 @@ private:
   std::vector<int> initSampleAmount{12, 6, 3};
 
 public:
-  double epsilon = 0.0;
-
-  MonteCarloMap mcMap;
-// Here Could be EstimatorMap
+  EstimatorMap mcMap;
 
   MultilevelData data;
 
   Exponents exponents;
 
-  Errors errors;
+  MultilevelErrors errors;
 
-  MultilevelMonteCarlo() : IEstimator() {
+  MultilevelMonteCarlo() : Estimator() {
     config.get("MLMCVerbose", verbose);
-    config.get("mcOnly", mcOnly);
     config.get("initLevels", initLevels);
     config.get("initSampleAmount", initSampleAmount);
 

mlmc/src/estimators/MultilevelStochasticCollocation.hpp

 #ifndef MULTILEVELSTOCHASTICCOLLOCATION_HPP
 #define MULTILEVELSTOCHASTICCOLLOCATION_HPP
 
-#include "IEstimator.hpp"
+#include "Estimator.hpp"
 
 
-class MultilevelStochasticCollocation : public IEstimator {
+class MultilevelStochasticCollocation : public Estimator {
 private:
 
 public:

mlmc/src/estimators/StochasticCollocation.hpp

 #ifndef STOCHASTICCOLLOCATION_HPP
 #define STOCHASTICCOLLOCATION_HPP
 
-#include "IEstimator.hpp"
+#include "Estimator.hpp"
 
 
-class StochasticCollocation : public IEstimator {
+class StochasticCollocation : public Estimator {
 private:
 
 public:

mlmc/src/estimators/datastructure/EmpiricMeasureLevelMaps.cpp

@@ -2,7 +2,7 @@
 #include "Exponents.hpp"
 
 
-void MonteCarloMap::UpdateSampleCounter(double epsilon) {
+void EstimatorMap::UpdateSampleCounter(double epsilon) {
   int optimalM;
 
   double factor = 0.0;
@@ -17,7 +17,7 @@ void MonteCarloMap::UpdateSampleCounter(double epsilon) {
   }
 }
 
-void MonteCarloMap::AppendLevel(double epsilon, Exponents exponents, int newLevel) {
+void EstimatorMap::AppendLevel(double epsilon, Exponents exponents, int newLevel) {
   if (newLevel <= maxLevel) {
     auto oldLevel = this->rbegin();
     double sVarY = oldLevel->second.aggregate.sVar.Y / pow(2.0, exponents.beta);
@@ -29,13 +29,14 @@ void MonteCarloMap::AppendLevel(double epsilon, Exponents exponents, int newLeve
 
     _levelMap.find(newLevel)->second.aggregate.sVar.Y = sVarY;
     _levelMap.find(newLevel)->second.aggregate.mean.C = avgsCost;
+
     this->UpdateSampleCounter(epsilon);
   } else {
     Exit ("Maximum level has been reached.")
   }
 }
 
-void SampleCounterMap::Update(const MonteCarloMap &mcMap) {
+void SampleCounterMap::Update(const EstimatorMap &mcMap) {
   for (auto &[level, mc]: mcMap)
     _levelMap[level] = SampleCounter(mc.aggregate.ctr);
 }
@@ -50,7 +51,7 @@ bool SampleCounterMap::NoSamplesLeft() {
   return noSamplesLeft;
 }
 
-void MeanMap::Update(const MonteCarloMap &mcMap) {
+void MeanMap::Update(const EstimatorMap &mcMap) {
   for (auto &&[level, mc]: mcMap) {
     _levelMap[level] = mc.aggregate.mean;
     Q += mc.aggregate.mean.Y;
@@ -58,12 +59,12 @@ void MeanMap::Update(const MonteCarloMap &mcMap) {
   }
 }
 
-void SVarMap::Update(const MonteCarloMap &mcMap) {
+void SVarMap::Update(const EstimatorMap &mcMap) {
   for (auto &[level, mc]: mcMap)
     _levelMap[level] = mc.aggregate.sVar;
 }
 
-void KurtosisMap::Update(const MonteCarloMap &mcMap) {
+void KurtosisMap::Update(const EstimatorMap &mcMap) {
   for (auto &[level, mc]: mcMap)
     _levelMap[level] = mc.aggregate.kurtosis;
 }

mlmc/src/estimators/datastructure/EmpiricMeasureLevelMaps.hpp

@@ -10,16 +10,16 @@
 
 struct Exponents;
 
-struct MonteCarloMap : public LevelMap<MonteCarlo> {
+struct EstimatorMap : public LevelMap<Estimator> {
 
   int maxLevel = 10;
 
-  MonteCarloMap() {
+  EstimatorMap() {
     config.get("maxLevel", maxLevel);
   };
 
-  MonteCarloMap(std::initializer_list<std::pair<int, MonteCarlo>> mcMap) :
-    LevelMap<MonteCarlo>(mcMap) {
+  EstimatorMap(std::initializer_list<std::pair<int, Estimator>> mcMap) :
+    LevelMap<Estimator>(mcMap) {
     config.get("maxLevel", maxLevel);
   };
 
@@ -35,7 +35,7 @@ struct SampleCounterMap : public LevelMap<SampleCounter> {
   SampleCounterMap(std::initializer_list<std::pair<int, SampleCounter>> ctrs) :
     LevelMap<SampleCounter>(ctrs) {};
 
-  void Update(const MonteCarloMap &mcMap);
+  void Update(const EstimatorMap &mcMap);
 
   bool NoSamplesLeft();
 };
@@ -49,11 +49,11 @@ struct MeanMap : public LevelMap<Mean> {
   MeanMap(std::initializer_list<std::pair<int, Mean>> avgs) :
     LevelMap<Mean>(avgs) {};
 
-  MeanMap(const MonteCarloMap &mcMap) {
+  MeanMap(const EstimatorMap &mcMap) {
     Update(mcMap);
   };
 
-  void Update(const MonteCarloMap &mcMap);
+  void Update(const EstimatorMap &mcMap);
 };
 
 struct SVarMap : public LevelMap<SVar> {
@@ -63,11 +63,11 @@ struct SVarMap : public LevelMap<SVar> {
   SVarMap(std::initializer_list<std::pair<int, SVar>> vars) :
     LevelMap<SVar>(vars) {};
 
-  SVarMap(const MonteCarloMap &mcMap) {
+  SVarMap(const EstimatorMap &mcMap) {
     Update(mcMap);
   };
 
-  void Update(const MonteCarloMap &mcMap);
+  void Update(const EstimatorMap &mcMap);
 };
 
 struct KurtosisMap : LevelMap<Kurtosis> {
@@ -77,11 +77,11 @@ struct KurtosisMap : LevelMap<Kurtosis> {
   KurtosisMap(std::initializer_list<std::pair<int, Kurtosis>> kurtosis) :
     LevelMap<Kurtosis>(kurtosis) {};
 
-  KurtosisMap(const MonteCarloMap &mcMap) {
+  KurtosisMap(const EstimatorMap &mcMap) {
     Update(mcMap);
   };
 
-  void Update(const MonteCarloMap &mcMap);
+  void Update(const EstimatorMap &mcMap);
 };
 
 struct MultilevelData {
@@ -95,7 +95,7 @@ struct MultilevelData {
 
   MultilevelData() {};
 
-  MultilevelData(const MonteCarloMap &mcMap) {
+  MultilevelData(const EstimatorMap &mcMap) {
     ExtractDataFrom(mcMap);
   }
 
@@ -103,7 +103,7 @@ struct MultilevelData {
                  const SVarMap &vars, const KurtosisMap &kurtosis) :
     ctrs(ctrs), means(avgs), sVars(vars), kurtosis(kurtosis) {};
 
-  void ExtractDataFrom(const MonteCarloMap &mcMap) {
+  void ExtractDataFrom(const EstimatorMap &mcMap) {
     ctrs.Update(mcMap);
     means.Update(mcMap);
     sVars.Update(mcMap);
@@ -130,7 +130,7 @@ struct MultilevelData {
              << "kurtosis=" << data.kurtosis.GetYVector() << endl
              << "E(cost)=" << data.means.GetCostVector() << endl
              << "Used Levels=" << data.means.GetLevelVector() << endl
-             << "Used Samples" << data.ctrs.GetMVector() << endl;
+             << "Used Samples=" << data.ctrs.GetMVector() << endl;
   }
 };
 

mlmc/src/estimators/datastructure/Exponents.cpp

 #include "Exponents.hpp"
 
-void Exponents::ComputeExponents(const MonteCarloMap &mcMap) {
+void Exponents::ComputeExponents(const EstimatorMap &mcMap) {
     ComputeExponents(MultilevelData(mcMap));
 }
 

mlmc/src/estimators/datastructure/Exponents.hpp

@@ -11,7 +11,7 @@ struct Exponents {
 
     Exponents() {};
 
-    Exponents(const MonteCarloMap &mcMap) {
+    Exponents(const EstimatorMap &mcMap) {
         ComputeExponents(mcMap);
     };
 
@@ -21,7 +21,7 @@ struct Exponents {
 
     void ComputeExponents(const MultilevelData &data);
 
-    void ComputeExponents(const MonteCarloMap &mcMap);
+    void ComputeExponents(const EstimatorMap &mcMap);
 
     void ComputeExponents(const MeanMap &mean, const SVarMap &sVar);
 

mlmc/src/estimators/datastructure/Errors.cpp → mlmc/src/estimators/datastructure/MultilevelErrors.cpp

-#include "Errors.hpp"
+#include "MultilevelErrors.hpp"
 
 
-void Errors::Estimate(const MonteCarloMap &mcMap) {
+void MultilevelErrors::Estimate(const EstimatorMap &mcMap) {
   Estimate(MultilevelData(mcMap));
 }
 
-void Errors::Estimate(const MultilevelData &data) {
+void MultilevelErrors::Estimate(const MultilevelData &data) {
   exponents.ComputeExponents(data);
   numeric = EstimateNumeric(data);
   stochastic = EstimateStochastic(data);
   total = numeric + stochastic;
 }
 
-double Errors::EstimateNumeric(const MultilevelData &data) {
+double MultilevelErrors::EstimateNumeric(const MultilevelData &data) {
   exponents.ComputeExponents(data);
   return EstimateNumeric(data.means);
 }
 
-double Errors::EstimateNumeric(const MeanMap &avgs) {
-  auto _levels = avgs.GetLevelVector();
-  auto _avgs = avgs.GetYVector();
+double MultilevelErrors::EstimateNumeric(const MeanMap &means) {
+  auto _levels = means.GetLevelVector();
+  auto _avgs = means.GetYVector();
   double alpha = exponents.alpha;
 
-  if (alpha == 0.0) alpha = exponents.ComputeAlpha(avgs);
+  if (alpha == 0.0) alpha = exponents.ComputeAlpha(means);
 
   double err = 0.0;
-  int integer = avgs.size() - 2;
+  int integer = means.size() - 2;
   for (int i = 1; i < _levels.size(); i++) {
     err = max(_avgs[i] / (pow(2.0, alpha) - 1) / (pow(2.0, integer)), err);
     integer--;
@@ -34,13 +34,13 @@ double Errors::EstimateNumeric(const MeanMap &avgs) {
   return err;
 }
 
-double Errors::EstimateStochastic(const MultilevelData &data) {
+double MultilevelErrors::EstimateStochastic(const MultilevelData &data) {
   return EstimateStochastic(data.ctrs, data.sVars);
 }
 
-double Errors::EstimateStochastic(const SampleCounterMap &ctrs, const SVarMap &vars) {
+double MultilevelErrors::EstimateStochastic(const SampleCounterMap &ctrs, const SVarMap &sVars) {
   auto _ctrs = ctrs.GetMVector();
-  auto _vars = vars.GetYVector();
+  auto _vars = sVars.GetYVector();
 
   double err = 0.0;
   for (int i = 0; i < _ctrs.size(); i++)