Update of outputs data from runAll

runAll_maxwell.sh

@@ -13,11 +13,11 @@ if [ "$erased" == "Y" ]; then
 fi
 
 # add of header
-echo 'model_name; vector_size; start; end; nb_zones; metric; mode; train_size; val_size; test_size; train_acc; val_acc; test_acc; mean_acc; F1_train; F1_val; F1_test; F1_mean' >> ${file_path}
+echo 'model_name; vector_size; start; end; nb_zones; metric; mode; tran_size; val_size; test_size; train_pct_size; val_pct_size; test_pct_size; train_acc; val_acc; test_acc; all_acc; F1_train; F1_val; F1_test; F1_all' >> ${file_path}
 
 for size in {"4","8","16","26","32","40"}; do
 
     for metric in {"lab","mscn","mscn_revisited","low_bits_2","low_bits_3","low_bits_4"}; do
-        bash generateAndTrain_maxwell.sh ${size} ${metric} &
+        bash generateAndTrain_maxwell.sh ${size} ${metric}
     done
 done

save_model_result_in_md_maxwell.py

@@ -205,6 +205,10 @@ def main():
     # stats of dataset sizes
     total_samples = final_df_train_size + val_set_size + test_set_size
 
+    model_scores.append(final_df_train_size)
+    model_scores.append(val_set_size)
+    model_scores.append(test_set_size)
+
     model_scores.append(final_df_train_size / total_samples)
     model_scores.append(val_set_size / total_samples)
     model_scores.append(test_set_size / total_samples)