Refactor experiment crossvalidation

sample/CMakeLists.txt

@@ -3,5 +3,5 @@ include_directories(${BayesNet_SOURCE_DIR}/src/BayesNet)
 include_directories(${BayesNet_SOURCE_DIR}/lib/Files)
 include_directories(${BayesNet_SOURCE_DIR}/lib/mdlp)
 include_directories(${BayesNet_SOURCE_DIR}/lib/argparse/include)
-add_executable(BayesNetSample sample.cc ${BayesNet_SOURCE_DIR}/src/Platform/Folding.cc) 
+add_executable(BayesNetSample sample.cc ${BayesNet_SOURCE_DIR}/src/Platform/Folding.cc ${BayesNet_SOURCE_DIR}/src/Platform/Models.cc) 
 target_link_libraries(BayesNetSample BayesNet ArffFiles mdlp "${TORCH_LIBRARIES}")

sample/sample.cc

@@ -4,16 +4,12 @@
 #include <thread>
 #include <map>
 #include <argparse/argparse.hpp>
-#include "BaseClassifier.h"
 #include "ArffFiles.h"
-#include "Network.h"
 #include "BayesMetrics.h"
 #include "CPPFImdlp.h"
-#include "KDB.h"
-#include "SPODE.h"
-#include "AODE.h"
-#include "TAN.h"
 #include "Folding.h"
+#include "Models.h"
+#include "modelRegister.h"
 
 
 using namespace std;
@@ -73,9 +69,8 @@ int main(int argc, char** argv)
             {"mfeat-factors",      true},
     };
     auto valid_datasets = vector<string>();
-    for (auto dataset : datasets) {
+    transform(datasets.begin(), datasets.end(), back_inserter(valid_datasets),
-        valid_datasets.push_back(dataset.first);
+        [](const pair<string, bool>& pair) { return pair.first; });
-    }
     argparse::ArgumentParser program("BayesNetSample");
     program.add_argument("-d", "--dataset")
         .help("Dataset file name")
@@ -91,13 +86,13 @@ int main(int argc, char** argv)
         .default_value(string{ PATH }
     );
     program.add_argument("-m", "--model")
-        .help("Model to use {AODE, KDB, SPODE, TAN}")
+        .help("Model to use " + platform::Models::instance()->toString())
         .action([](const std::string& value) {
-        static const vector<string> choices = { "AODE", "KDB", "SPODE", "TAN" };
+        static const vector<string> choices = platform::Models::instance()->getNames();
         if (find(choices.begin(), choices.end(), value) != choices.end()) {
             return value;
         }
-        throw runtime_error("Model must be one of {AODE, KDB, SPODE, TAN}");
+        throw runtime_error("Model must be one of " + platform::Models::instance()->toString());
             }
     );
     program.add_argument("--discretize").help("Discretize input dataset").default_value(false).implicit_value(true);

src/Platform/Experiment.cc

@@ -85,11 +85,25 @@ namespace platform {
         file << data;
         file.close();
     }
+
     void Experiment::show()
     {
         json data = build_json();
         cout << data.dump(4) << endl;
     }
+
+    void Experiment::go(vector<string> filesToProcess, const string& path)
+    {
+        cout << "*** Starting experiment: " << title << " ***" << endl;
+        for (auto fileName : filesToProcess) {
+            cout << "- " << setw(20) << left << fileName << " " << right << flush;
+            auto result = cross_validation(path, fileName);
+            result.setDataset(fileName);
+            addResult(result);
+            cout << endl;
+        }
+    }
+
     Result Experiment::cross_validation(const string& path, const string& fileName)
     {
         auto datasets = platform::Datasets(path, true, platform::ARFF);

src/Platform/Experiment.h

@@ -106,6 +106,7 @@ namespace platform {
         string get_file_name();
         void save(string path);
         Result cross_validation(const string& path, const string& fileName);
+        void go(vector<string> filesToProcess, const string& path);
         void show();
     };
 }

src/Platform/main.cc

@@ -5,7 +5,7 @@
 #include "Datasets.h"
 #include "DotEnv.h"
 #include "Models.h"
-
+#include "modelRegister.h"
 
 using namespace std;
 const string PATH_RESULTS = "results";
@@ -78,19 +78,11 @@ argparse::ArgumentParser manageArguments(int argc, char** argv)
 }
 void registerModels()
 {
-    static platform::Registrar registrarT("TAN",
+
-        [](void) -> bayesnet::BaseClassifier* { return new bayesnet::TAN();});
-    static platform::Registrar registrarS("SPODE",
-        [](void) -> bayesnet::BaseClassifier* { return new bayesnet::SPODE(2);});
-    static platform::Registrar registrarK("KDB",
-        [](void) -> bayesnet::BaseClassifier* { return new bayesnet::KDB(2);});
-    static platform::Registrar registrarA("AODE",
-        [](void) -> bayesnet::BaseClassifier* { return new bayesnet::AODE();});
 }
 
 int main(int argc, char** argv)
 {
-    registerModels();
     auto program = manageArguments(argc, argv);
     bool saveResults = false;
     auto file_name = program.get<string>("dataset");
@@ -128,15 +120,8 @@ int main(int argc, char** argv)
         experiment.addRandomSeed(seed);
     }
     platform::Timer timer;
-    cout << "*** Starting experiment: " << title << " ***" << endl;
     timer.start();
-    for (auto fileName : filesToProcess) {
+    experiment.go(filesToProcess, path);
-        cout << "- " << setw(20) << left << fileName << " " << right << flush;
-        auto result = experiment.cross_validation(path, fileName);
-        result.setDataset(fileName);
-        experiment.addResult(result);
-        cout << endl;
-    }
     experiment.setDuration(timer.getDuration());
     if (saveResults)
         experiment.save(PATH_RESULTS);

src/Platform/modelRegister.h

@@ -0,0 +1,11 @@
+#ifndef MODEL_REGISTER_H
+#define MODEL_REGISTER_H
+static platform::Registrar registrarT("TAN",
+    [](void) -> bayesnet::BaseClassifier* { return new bayesnet::TAN();});
+static platform::Registrar registrarS("SPODE",
+    [](void) -> bayesnet::BaseClassifier* { return new bayesnet::SPODE(2);});
+static platform::Registrar registrarK("KDB",
+    [](void) -> bayesnet::BaseClassifier* { return new bayesnet::KDB(2);});
+static platform::Registrar registrarA("AODE",
+    [](void) -> bayesnet::BaseClassifier* { return new bayesnet::AODE();});
+#endif