Pass -x flag setting to cmd_csv

MBI.py

@@ -657,7 +657,7 @@ def cmd_csv(rootdir, toolnames):
             results[toolname].append(resulting_categorization)
 
     pd.set_option('display.max_columns',14)
-    for toolname in ["itac", "must", "parcoach"]:
+    for toolname in toolnames:
         df = pd.DataFrame(results[toolname])
 
         df["TP_base"] = df["ERROR_EXPECTED"] & df["any_error_reported"] & (df["CE"] == False) & (df["RE"] == False) 
@@ -679,7 +679,6 @@ def cmd_csv(rootdir, toolnames):
             df_classified.to_csv(f'{outpath}/{toolname}_{colname}_full.csv', index=False)
             df_result = aggregate_metrics_per_category(df_classified)
             df_result.to_csv(f'{outpath}/{toolname}_{colname}.csv', index=True)
-            if colname == "base":
             print(f"\n{colname}:")
             print(df_result[["CE", "RE", "TP", "TN", "FP", "FN", "coverage", "conclusiveness", "specificity", "recall", "precision", "f1", "overallaccuracy"]])
             df_result[["CE", "RE", "TP", "TN", "FP", "FN", "coverage", "conclusiveness", "specificity", "recall", "precision", "f1", "overallaccuracy"]].style.format(precision=2).to_latex(f'{outpath}/{toolname}_{colname}.tex')
@@ -1979,6 +1978,9 @@ elif args.c == 'latex':
     cmd_latex(rootdir, toolnames=['itac', 'must', 'parcoach'])
 elif args.c == 'csv':
     extract_all_todo_from_logdir(args.x, args.logs_dir)
+    if arg_tools:
+        cmd_csv(rootdir, toolnames=arg_tools)
+    else:
         cmd_csv(rootdir, toolnames=['itac', 'must', 'parcoach'])
 elif args.c == 'html':
     extract_all_todo_from_logdir(args.x, args.logs_dir)