[CODE] removed unnecessary comments in simulator_1_2.cpp

src/examples/simulator_1_2.cpp

@@ -106,55 +106,55 @@ int main(int argc, char** argv) {
 
         /* Complex Optimization */
         learning_sequence.optimize(mse1);  // Network training
-//
-//        puts("*********************** 6");
-//
-//        /* Save Neural network parameters to file */
-//        sim.save_text("test_net_Gradient_Descent.4n");
-//
-//        /* PHASE 4 - TESTING DATA */
-//
-//        /* Output file specification */
-//        std::string filename = "simulator_output.txt";
-//        std::ofstream output_file(filename);
-//        if (!output_file.is_open()) {
-//            throw std::runtime_error("File '" + filename + "' can't be opened!");
-//        }
-//
-//        /* Neural network loading */
-//        l4n::NeuralNetwork nn3("test_net_Gradient_Descent.4n");
-//
-//        /* Check of the saved network - write to the file */
-//        output_file << std::endl << "The loaded network info:" << std::endl;
-//        nn3.write_stats(&output_file);
-//        nn3.write_weights(&output_file);
-//        nn3.write_biases(&output_file);
-////
-////        /* Evaluate network on an arbitrary data-set and save results into the file */
-//        l4n::CSVReader reader3("../../../data_files/data_BACK_RH_1.csv", ";", true);  // File, separator, skip 1st line
-//        reader3.read();  // Read from the file
-////
-////        /* Create data set for both the testing of the neural network */
-////        /* Specify which columns are inputs or outputs */
-////
-//        std::shared_ptr<l4n::DataSet> ds3 = reader3.get_data_set(&inputs, &outputs);  // Creation of data-set for NN
-//        ds3.operator->()->set_normalization_strategy( new DoubleUnitStrategy());
-//        if(normalize_data){
-//            ds3.get()->normalize();  // Normalization of data to prevent numerical problems
-//        }
-////
-////        output_file << std::endl << "Evaluating network on the dataset: " << std::endl;
-////        ds3.store_data_text(&output_file);
-////
-//        output_file << "Output and the error:" << std::endl;
-////
-////        /* Error function */
-//        l4n::MSE mse3(&nn3, ds3.get());  // First parameter - neural network, second parameter - data-set
-//
-//        mse3.eval_on_data_set(ds3.get(), &output_file, nullptr, normalize_data, true);
-//
-//        /* Close the output file for writing */
-//        output_file.close();
+
+        puts("*********************** 6");
+
+        /* Save Neural network parameters to file */
+        sim.save_text("test_net_Gradient_Descent.4n");
+
+        /* PHASE 4 - TESTING DATA */
+
+        /* Output file specification */
+        std::string filename = "simulator_output.txt";
+        std::ofstream output_file(filename);
+        if (!output_file.is_open()) {
+            throw std::runtime_error("File '" + filename + "' can't be opened!");
+        }
+
+        /* Neural network loading */
+        l4n::NeuralNetwork nn3("test_net_Gradient_Descent.4n");
+
+        /* Check of the saved network - write to the file */
+        output_file << std::endl << "The loaded network info:" << std::endl;
+        nn3.write_stats(&output_file);
+        nn3.write_weights(&output_file);
+        nn3.write_biases(&output_file);
+
+        /* Evaluate network on an arbitrary data-set and save results into the file */
+        l4n::CSVReader reader3("../../../data_files/data_BACK_RH_1.csv", ";", true);  // File, separator, skip 1st line
+        reader3.read();  // Read from the file
+
+        /* Create data set for both the testing of the neural network */
+        /* Specify which columns are inputs or outputs */
+
+        std::shared_ptr<l4n::DataSet> ds3 = reader3.get_data_set(&inputs, &outputs);  // Creation of data-set for NN
+        ds3.operator->()->set_normalization_strategy( new DoubleUnitStrategy());
+        if(normalize_data){
+            ds3.get()->normalize();  // Normalization of data to prevent numerical problems
+        }
+
+        output_file << std::endl << "Evaluating network on the dataset: " << std::endl;
+        ds3->store_data_text(&output_file);
+
+        output_file << "Output and the error:" << std::endl;
+
+        /* Error function */
+        l4n::MSE mse3(&nn3, ds3.get());  // First parameter - neural network, second parameter - data-set
+
+        mse3.eval_on_data_set(ds3.get(), &output_file, nullptr, normalize_data, true);
+
+        /* Close the output file for writing */
+        output_file.close();
 
         return 0;