Refactor into library

Makefile

@@ -4,8 +4,8 @@ SHELL := /bin/bash
 
 f_release = build_release
 f_debug = build_debug
-app_targets = main
-test_targets = unit_tests_bayesnet unit_tests_platform
+app_targets = example
+test_targets = unit_tests_pywrap
 n_procs = -j 16
 
 define ClearTests
@@ -31,21 +31,6 @@ setup: ## Install dependencies for tests and coverage
 		pip install gcovr; \
 	fi
 
-dest ?= ${HOME}/bin
-install: ## Copy binary files to bin folder
-	@echo "Destination folder: $(dest)"
-	make buildr
-	@echo ">>> Copying files to $(dest)"
-	@cp $(f_release)/src/Platform/b_main $(dest)
-	@cp $(f_release)/src/Platform/b_list $(dest)
-	@cp $(f_release)/src/Platform/b_manage $(dest)
-	@cp $(f_release)/src/Platform/b_best $(dest)
-
-dependency: ## Create a dependency graph diagram of the project (build/dependency.png)
-	@echo ">>> Creating dependency graph diagram of the project...";
-	$(MAKE) debug
-	cd $(f_debug) && cmake .. --graphviz=dependency.dot && dot -Tpng dependency.dot -o dependency.png
-
 buildd: ## Build the debug targets
 	cmake --build $(f_debug) -t $(app_targets) $(n_procs)
 

src/CMakeLists.txt

@@ -3,6 +3,9 @@ include_directories(${PyWrap_SOURCE_DIR}/lib/json/include)
 include_directories(${Python3_INCLUDE_DIRS})
 include_directories(${TORCH_INCLUDE_DIRS})
 
-add_executable(main main.cc STree.cc SVC.cc RandomForest.cc PyClassifier.cc PyWrap.cc)
 
-target_link_libraries(main ${Python3_LIBRARIES} "${TORCH_LIBRARIES}" ${LIBTORCH_PYTHON} Boost::boost Boost::python Boost::numpy ArffFiles)
+add_library(PyWrap SHARED PyWrap.cc STree.cc SVC.cc RandomForest.cc PyClassifier.cc)
+target_link_libraries(PyWrap ${Python3_LIBRARIES} "${TORCH_LIBRARIES}" ${LIBTORCH_PYTHON} Boost::boost Boost::python Boost::numpy ArffFiles)
+
+add_executable(example example.cc)
+target_link_libraries(example PyWrap)

src/PyClassifier.cc

@@ -1,5 +1,4 @@
 #include "PyClassifier.h"
-#include <iostream>
 namespace pywrap {
     namespace bp = boost::python;
     namespace np = boost::python::numpy;
@@ -7,7 +6,6 @@ namespace pywrap {
     {
         // This id allows to have more than one instance of the same module/class
         id = reinterpret_cast<clfId_t>(this);
-        std::cout << "PyClassifier: Creating instance of " << module << " and class " << className << " id " << id << std::endl;
         pyWrap = PyWrap::GetInstance();
         pyWrap->importClass(id, module, className);
     }
@@ -40,7 +38,6 @@ namespace pywrap {
     PyClassifier& PyClassifier::fit(torch::Tensor& X, torch::Tensor& y, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states)
     {
         if (!fitted && hyperparameters.size() > 0) {
-            std::cout << "PyClassifier: Setting hyperparameters" << std::endl;
             pyWrap->setHyperparameters(id, hyperparameters);
         }
         auto [Xn, yn] = tensors2numpy(X, y);

src/PyWrap.cc

@@ -3,7 +3,6 @@
 #include "PyWrap.h"
 #include <string>
 #include <map>
-#include <iostream>
 #include <sstream>
 #include <boost/python/numpy.hpp>
 
@@ -117,7 +116,6 @@ namespace pywrap {
     void PyWrap::setHyperparameters(const clfId_t id, const json& hyperparameters)
     {
         // Set hyperparameters as attributes of the class
-        std::cout << "Building dictionary of arguments" << std::endl;
         PyObject* pValue;
         PyObject* instance = getClass(id);
         for (const auto& [key, value] : hyperparameters.items()) {