Use xgboost by default.

17_apply_to_proteome.py

@@ -110,7 +110,7 @@ if __name__ == '__main__':
     parent_parser.add_argument('--modal-keggs', help='modal keggs', default=os.path.join(data_dir, 'ModalKEGGs.tsv'))
     parent_parser.add_argument('--modal-keggs-with-names', help='modal keggs with names', default=os.path.join(data_dir, 'modal_keggs_with_names.csv'))
     # ./12_apply_model.py --model the.model -x the.x --training-data-header <(head the.training-data-header)
-    parent_parser.add_argument('--models', nargs='+', help='models to use')
+    parent_parser.add_argument('--models', nargs='+', help='models to use', default=[os.path.join(data_dir, '..', 'XGBoost.model')])
 
     parent_parser.add_argument('--training-data-header', help='header of training data', default=os.path.join(data_dir, 'training_data_header.tsv'))