diff --git a/View/signal_processing_tab.py b/View/signal_processing_tab.py
index 4f313c0..833dff8 100644
--- a/View/signal_processing_tab.py
+++ b/View/signal_processing_tab.py
@@ -625,12 +625,14 @@ class SignalProcessingTab(QWidget):
         self.compute_average_profile_tail()
 
         if stg.noise_method[data_id] == 0:
-            if stg.filename_BS_noise_data[data_id] != "":
-                if len(stg.BS_noise_raw_data) == 0:
-                    self.load_noise_data_and_compute_SNR()
-                else:
-                    for i in range(self.combobox_acoustic_data_choice.count()):
-                        self.compute_noise(i)
+            if stg.filename_BS_noise_data[data_id] == "":
+                return
+
+            if len(stg.BS_noise_raw_data) == 0:
+                self.load_noise_data_and_compute_SNR()
+            else:
+                for i in range(self.combobox_acoustic_data_choice.count()):
+                    self.compute_noise(i)
         elif stg.noise_method[data_id] == 1:
             self.compute_noise_from_profile_tail_value()
 
@@ -920,8 +922,6 @@ class SignalProcessingTab(QWidget):
 
         self.compute_average_profile_tail()
 
-        logger.debug(f"stg.SNR_filter_value: {stg.SNR_filter_value}")
-
         self.lineEdit_profile_tail_value.setText(
             str(stg.noise_value[data_id])
         )
@@ -1649,7 +1649,6 @@ class SignalProcessingTab(QWidget):
             BS_data_ppa = stg.BS_raw_data_pre_process_average
             for i in range(len(BS)):
                 bs = BS[i]
-                logger.debug(f"BS data shape {bs[data_id].shape}")
                 if bs[data_id].shape == (0,):
                     continue
 
@@ -1658,7 +1657,6 @@ class SignalProcessingTab(QWidget):
                     BS_data_ppa = BS_ppa[i]
                     break
 
-            logger.debug(f"BS_data: {BS_data[data_id].shape}")
 
             # BS_data_ppa[data_id] = deepcopy(BS_data[data_id])
             #
@@ -1687,11 +1685,11 @@ class SignalProcessingTab(QWidget):
 
             BS_data_ppa[data_id] = np.array([temp_list[0]])
             for j in range(stg.freq[data_id].shape[0]-1):
-                BS_data_ppa[data_id] = np.append(BS_data_ppa[data_id], np.array([temp_list[j+1]]), axis=0)
-
-            logger.debug(
-                f"BS_data_ppa: {BS_data_ppa[data_id].shape}"
-            )
+                BS_data_ppa[data_id] = np.append(
+                    BS_data_ppa[data_id],
+                    np.array([temp_list[j+1]]),
+                    axis=0
+                )
 
     def plot_pre_processed_profile(self):
         data_id = max(0, self.combobox_acoustic_data_choice.currentIndex())