FIX + ENH: Fixed network dimensions according to the new data. Now handling...

FIX + ENH: Fixed network dimensions according to the new data. Now handling even 'bad argument' exceptions.

src/examples/simulator.cpp

@@ -39,12 +39,13 @@ int main(int argc, char** argv){
     try {
 
         /* Read data from the file */
-        l4n::CSVReader reader("/home/martin/Desktop/ANN_DATA_1_SET.txt", "\t", true);
+//        l4n::CSVReader reader("/home/martin/Desktop/ANN_DATA_1_SET.txt", "\t", true);
+        l4n::CSVReader reader("/tmp/data_Heaviside.txt", "\t", false);
         reader.read();
 
         /* Create data set for both the training and testing of the neural network */
-        std::vector<unsigned int> inputs = { 2, 3, 4, 5, 6, 7, 8, 27, 28, 29 };
-        std::vector<unsigned int> outputs = {18, 19, 20, 21, 22, 23, 24, 25, 26};
+        std::vector<unsigned int> inputs = { 0 };
+        std::vector<unsigned int> outputs = { 1 };
 
         l4n::DataSet ds = reader.get_data_set(&inputs, &outputs);
         ds.normalize();
@@ -52,7 +53,7 @@ int main(int argc, char** argv){
 //        ds.print_data();
 
         /* Neural network construction */
-        std::vector<unsigned int> neuron_numbers_in_layers = {1, 10, 10, 9};
+        std::vector<unsigned int> neuron_numbers_in_layers = {1, 10, 10, 1};
         l4n::FullyConnectedFFN nn(&neuron_numbers_in_layers, l4n::NEURON_TYPE::LOGISTIC);
 
         /* Error function */
@@ -124,10 +125,13 @@ int main(int argc, char** argv){
         return 0;
 
     } catch(const std::runtime_error& e) {
-        std::cerr << e.what();
+        std::cerr << e.what() << std::endl;
         exit(EXIT_FAILURE);
     } catch(const std::out_of_range& e) {
-        std::cerr << e.what();
+        std::cerr << e.what() << std::endl;
+        exit(EXIT_FAILURE);
+    } catch(const std::invalid_argument& e) {
+        std::cerr << e.what() << std::endl;
         exit(EXIT_FAILURE);
     }