diff --git a/phasenet/predict.py b/phasenet/predict.py
index e7fc465..80c4cf2 100755
--- a/phasenet/predict.py
+++ b/phasenet/predict.py
@@ -144,30 +144,30 @@ def pred_fn(args, data_reader, figure_dir=None, prob_dir=None, log_dir=None):
 
             picks.extend(picks_)
 
-            ## save pick per file
-            if (len(fname_batch) == 1) & (len(picks_) > 0):
-                df = pd.DataFrame(picks_)
-                df = df[df["phase_index"] > 10]
-                if not os.path.exists(os.path.join(args.result_dir, "picks")):
-                    os.makedirs(os.path.join(args.result_dir, "picks"))
-                df = df[
-                    [
-                        "station_id",
-                        "begin_time",
-                        "phase_index",
-                        "phase_time",
-                        "phase_score",
-                        "phase_type",
-                        "phase_amplitude",
-                        "dt",
-                    ]
-                ]
-                df.to_csv(
-                    os.path.join(
-                        args.result_dir, "picks", fname_batch[0].decode().split("/")[-1].rstrip(".mseed") + ".csv"
-                    ),
-                    index=False,
-                )
+            # ## save pick per file
+            # if (len(fname_batch) == 1) & (len(picks_) > 0):
+            #     df = pd.DataFrame(picks_)
+            #     df = df[df["phase_index"] > 10]
+            #     if not os.path.exists(os.path.join(args.result_dir, "picks")):
+            #         os.makedirs(os.path.join(args.result_dir, "picks"))
+            #     df = df[
+            #         [
+            #             "station_id",
+            #             "begin_time",
+            #             "phase_index",
+            #             "phase_time",
+            #             "phase_score",
+            #             "phase_type",
+            #             "phase_amplitude",
+            #             "dt",
+            #         ]
+            #     ]
+            #     df.to_csv(
+            #         os.path.join(
+            #             args.result_dir, "picks", fname_batch[0].decode().split("/")[-1].rstrip(".mseed") + ".csv"
+            #         ),
+            #         index=False,
+            #     )
 
             if args.plot_figure:
                 if not (isinstance(fname_batch, np.ndarray) or isinstance(fname_batch, list)):