Continue refactoring

src/CMakeLists.txt

@@ -28,6 +28,7 @@ add_executable(
     results/Result.cpp
     experimental_clfs/XA1DE.cpp
     experimental_clfs/XBAODE.cpp
+    experimental_clfs/ExpClf.cpp
 )
 target_link_libraries(b_best Boost::boost "${PyClassifiers}" "${BayesNet}" fimdlp ${Python3_LIBRARIES} "${TORCH_LIBRARIES}" ${LIBTORCH_PYTHON} Boost::python Boost::numpy "${XLSXWRITER_LIB}")
 
@@ -41,6 +42,7 @@ add_executable(b_grid commands/b_grid.cpp ${grid_sources}
     results/Result.cpp
     experimental_clfs/XA1DE.cpp
     experimental_clfs/XBAODE.cpp
+    experimental_clfs/ExpClf.cpp
 )
 target_link_libraries(b_grid ${MPI_CXX_LIBRARIES} "${PyClassifiers}" "${BayesNet}" fimdlp ${Python3_LIBRARIES} "${TORCH_LIBRARIES}" ${LIBTORCH_PYTHON} Boost::python Boost::numpy)
 
@@ -52,6 +54,7 @@ add_executable(b_list commands/b_list.cpp
     results/Result.cpp results/ResultsDatasetExcel.cpp results/ResultsDataset.cpp results/ResultsDatasetConsole.cpp
     experimental_clfs/XA1DE.cpp
     experimental_clfs/XBAODE.cpp
+    experimental_clfs/ExpClf.cpp
 )
 target_link_libraries(b_list "${PyClassifiers}" "${BayesNet}" fimdlp ${Python3_LIBRARIES} "${TORCH_LIBRARIES}" ${LIBTORCH_PYTHON} Boost::python Boost::numpy "${XLSXWRITER_LIB}")
 
@@ -64,6 +67,7 @@ add_executable(b_main commands/b_main.cpp ${main_sources}
     results/Result.cpp
     experimental_clfs/XA1DE.cpp
     experimental_clfs/XBAODE.cpp
+    experimental_clfs/ExpClf.cpp
 )
 target_link_libraries(b_main "${PyClassifiers}" "${BayesNet}" fimdlp ${Python3_LIBRARIES} "${TORCH_LIBRARIES}" ${LIBTORCH_PYTHON} Boost::python Boost::numpy)
 

src/experimental_clfs/ExpClf.cpp

@@ -8,7 +8,7 @@
 #include "TensorUtils.hpp"
 
 namespace platform {
-    ExpClf::ExpClf() : semaphore_{ CountingSemaphore::getInstance() }
+    ExpClf::ExpClf() : semaphore_{ CountingSemaphore::getInstance() }, Boost(false)
     {
     }
     void ExpClf::setHyperparameters(const nlohmann::json& hyperparameters)

src/experimental_clfs/ExpClf.h

@@ -12,14 +12,14 @@
 #include <cmath>
 #include <algorithm>
 #include <limits>
-#include "bayesnet/BaseClassifier.h"
+#include "bayesnet/ensembles/Boost.h"
 #include "common/Timer.hpp"
 #include "CountingSemaphore.hpp"
 #include "Xaode.hpp"
 
 namespace platform {
 
-    class ExpClf : public bayesnet::BaseClassifier {
+    class ExpClf : public bayesnet::Boost {
     public:
         ExpClf();
         virtual ~ExpClf() = default;

src/experimental_clfs/XBAODE.cpp

@@ -13,14 +13,14 @@
 #include <loguru.hpp>
 
 namespace platform {
-    XBAODE::XBAODE() : Boost(false)
+    XBAODE::XBAODE()
     {
-        Boost::validHyperparameters = { "alpha_block", "order", "convergence", "convergence_best", "bisection", "threshold", "maxTolerance",
+        validHyperparameters = { "alpha_block", "order", "convergence", "convergence_best", "bisection", "threshold", "maxTolerance",
             "predict_voting", "select_features" };
     }
     void XBAODE::trainModel(const torch::Tensor& weights, const bayesnet::Smoothing_t smoothing)
     {
-        Boost::fitted = true;
+        fitted = true;
         X_train_ = TensorUtils::to_matrix(X_train);
         y_train_ = TensorUtils::to_vector<int>(y_train);
         X_test_ = TensorUtils::to_matrix(X_test);
@@ -44,7 +44,7 @@ namespace platform {
         if (selectFeatures) {
             featuresUsed = featureSelection(weights_);
             set_active_parents(featuresUsed);
-            Boost::notes.push_back("Used features in initialization: " + std::to_string(featuresUsed.size()) + " of " + std::to_string(features.size()) + " with " + select_features_algorithm);
+            notes.push_back("Used features in initialization: " + std::to_string(featuresUsed.size()) + " of " + std::to_string(features.size()) + " with " + select_features_algorithm);
             auto ypred = ExpClf::predict(X_train);
             std::tie(weights_, alpha_t, finished) = update_weights(y_train, ypred, weights_);
             // Update significance of the models
@@ -146,7 +146,7 @@ namespace platform {
         }
         if (tolerance > maxTolerance) {
             if (numItemsPack < n_models) {
-                Boost::notes.push_back("Convergence threshold reached & " + std::to_string(numItemsPack) + " models eliminated");
+                notes.push_back("Convergence threshold reached & " + std::to_string(numItemsPack) + " models eliminated");
                 VLOG_SCOPE_F(4, "Convergence threshold reached & %d models eliminated of %d", numItemsPack, n_models);
                 for (int i = featuresUsed.size() - 1; i >= featuresUsed.size() - numItemsPack; --i) {
                     aode_.remove_last_parent();
@@ -155,15 +155,15 @@ namespace platform {
                 }
                 VLOG_SCOPE_F(4, "*Convergence threshold %d models left & %d features used.", n_models, featuresUsed.size());
             } else {
-                Boost::notes.push_back("Convergence threshold reached & 0 models eliminated");
+                notes.push_back("Convergence threshold reached & 0 models eliminated");
                 VLOG_SCOPE_F(4, "Convergence threshold reached & 0 models eliminated n_models=%d numItemsPack=%d", n_models, numItemsPack);
             }
         }
         if (featuresUsed.size() != features.size()) {
-            Boost::notes.push_back("Used features in train: " + std::to_string(featuresUsed.size()) + " of " + std::to_string(features.size()));
+            notes.push_back("Used features in train: " + std::to_string(featuresUsed.size()) + " of " + std::to_string(features.size()));
-            Boost::status = bayesnet::WARNING;
+            status = bayesnet::WARNING;
         }
-        Boost::notes.push_back("Number of models: " + std::to_string(n_models));
+        notes.push_back("Number of models: " + std::to_string(n_models));
         return;
     }
 }

src/experimental_clfs/XBAODE.h

@@ -12,11 +12,10 @@
 #include <algorithm>
 #include <limits>
 #include "common/Timer.hpp"
-#include "bayesnet/ensembles/Boost.h"
 #include "ExpClf.h"
 
 namespace platform {
-    class XBAODE : public bayesnet::Boost, public ExpClf {
+    class XBAODE : public ExpClf {
     public:
         XBAODE();
         virtual ~XBAODE() = default;