diff --git a/View/sediment_calibration_tab.py b/View/sediment_calibration_tab.py
index 923e576..2d7563a 100644
--- a/View/sediment_calibration_tab.py
+++ b/View/sediment_calibration_tab.py
@@ -876,7 +876,7 @@ class SedimentCalibrationTab(QWidget):
             return
 
         self.update_acoustic_data()
-        # self.compute_depth_2D()
+        self.compute_depth_2D()
 
     def update_acoustic_data(self):
         self.combobox_acoustic_data_choice.clear()
@@ -934,11 +934,13 @@ class SedimentCalibrationTab(QWidget):
         self.compute_FCB()
 
     def plot_acoustic_recording(self):
+        data_id = self.combobox_acoustic_data_choice.currentIndex()
+
         # --- Record frequencies for calibration ---
         stg.frequencies_for_calibration.clear()
         stg.frequencies_for_calibration.append(
             (
-                stg.freq[self.combobox_acoustic_data_choice.currentIndex()][
+                stg.freq[data_id][
                     self.combobox_freq1.currentIndex()
                 ],
                 self.combobox_freq1.currentIndex()
@@ -946,7 +948,7 @@ class SedimentCalibrationTab(QWidget):
         )
         stg.frequencies_for_calibration.append(
             (
-                stg.freq[self.combobox_acoustic_data_choice.currentIndex()][
+                stg.freq[data_id][
                     self.combobox_freq2.currentIndex()
                 ],
                 self.combobox_freq2.currentIndex()
@@ -955,7 +957,7 @@ class SedimentCalibrationTab(QWidget):
 
         stg.frequency_for_inversion = tuple()
         stg.frequency_for_inversion = (
-            stg.freq[self.combobox_acoustic_data_choice.currentIndex()][
+            stg.freq[data_id][
                 self.combobox_freq2.currentIndex()
             ],
             self.combobox_freq2.currentIndex()
@@ -973,18 +975,18 @@ class SedimentCalibrationTab(QWidget):
         self.verticalLayout_groupbox_data_plot.addWidget(self.canvas_BS)
 
         if stg.BS_stream_bed_pre_process_average[
-                self.combobox_acoustic_data_choice.currentIndex()
+                data_id
         ].shape != (0,):
             val_min = np.nanmin(
                 stg.BS_stream_bed_pre_process_average[
-                    self.combobox_acoustic_data_choice.currentIndex()
+                    data_id
                 ][
                     self.combobox_freq2.currentIndex(), :, :
                 ]
             )
             val_max = np.nanmax(
                 stg.BS_stream_bed_pre_process_average[
-                    self.combobox_acoustic_data_choice.currentIndex()
+                    data_id
                 ][
                     self.combobox_freq2.currentIndex(), :, :
                 ]
@@ -992,346 +994,346 @@ class SedimentCalibrationTab(QWidget):
             if val_min == 0:
                 val_min = 1e-5
 
-            if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
-                if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+            if stg.time_cross_section[data_id].shape != (0,):
+                if stg.depth_cross_section[data_id].shape != (0,):
                     self.axis_BS.pcolormesh(
-                        stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time_cross_section[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth_cross_section[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_stream_bed_pre_process_average[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
                 else:
                     self.axis_BS.pcolormesh(
-                        stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time_cross_section[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_stream_bed_pre_process_average[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
             else:
-                if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+                if stg.depth_cross_section[data_id].shape != (0,):
                     self.axis_BS.pcolormesh(
-                        stg.time[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth_cross_section[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_stream_bed_pre_process_average[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
                 else:
                     self.axis_BS.pcolormesh(
-                        stg.time[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_stream_bed_pre_process_average[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
 
 
 
-        elif stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+        elif stg.BS_stream_bed_pre_process_SNR[data_id].shape != (0,):
 
             val_min = np.nanmin(
-                stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][
+                stg.BS_stream_bed_pre_process_SNR[data_id][
                 self.combobox_freq2.currentIndex(), :, :])
             val_max = np.nanmax(
-                stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][
+                stg.BS_stream_bed_pre_process_SNR[data_id][
                 self.combobox_freq2.currentIndex(), :, :])
             if val_min == 0:
                 val_min = 1e-5
 
-            if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
-                if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+            if stg.time_cross_section[data_id].shape != (0,):
+                if stg.depth_cross_section[data_id].shape != (0,):
                     self.axis_BS.pcolormesh(
-                        stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time_cross_section[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth_cross_section[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_stream_bed_pre_process_SNR[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
                 else:
                     self.axis_BS.pcolormesh(
-                        stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time_cross_section[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_stream_bed_pre_process_SNR[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
             else:
-                if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+                if stg.depth_cross_section[data_id].shape != (0,):
                     self.axis_BS.pcolormesh(
-                        stg.time[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth_cross_section[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_stream_bed_pre_process_SNR[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
                 else:
                     self.axis_BS.pcolormesh(
-                        stg.time[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_stream_bed_pre_process_SNR[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
 
-        elif stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+        elif stg.BS_stream_bed[data_id].shape != (0,):
 
             val_min = np.nanmin(
-                stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(),
+                stg.BS_stream_bed[data_id][self.combobox_freq2.currentIndex(),
                 :, :])
             val_max = np.nanmax(
-                stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(),
+                stg.BS_stream_bed[data_id][self.combobox_freq2.currentIndex(),
                 :, :])
             if val_min == 0:
                 val_min = 1e-5
 
-            if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
-                if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+            if stg.time_cross_section[data_id].shape != (0,):
+                if stg.depth_cross_section[data_id].shape != (0,):
                     self.axis_BS.pcolormesh(
-                        stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time_cross_section[data_id][
                     self.combobox_freq2.currentIndex(), :],
-                    -stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                    -stg.depth_cross_section[data_id][
                      self.combobox_freq2.currentIndex(), :],
-                    stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(),
+                    stg.BS_stream_bed[data_id][self.combobox_freq2.currentIndex(),
                     :, :],
                     cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
                 else:
                     self.axis_BS.pcolormesh(
-                        stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time_cross_section[data_id][
                     self.combobox_freq2.currentIndex(), :],
-                    -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                    -stg.depth[data_id][
                      self.combobox_freq2.currentIndex(), :],
-                    stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(),
+                    stg.BS_stream_bed[data_id][self.combobox_freq2.currentIndex(),
                     :, :],
                     cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
 
             else:
-                if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+                if stg.depth_cross_section[data_id].shape != (0,):
                     self.axis_BS.pcolormesh(
-                        stg.time[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time[data_id][
                     self.combobox_freq2.currentIndex(), :],
-                    -stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                    -stg.depth_cross_section[data_id][
                      self.combobox_freq2.currentIndex(), :],
-                    stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(),
+                    stg.BS_stream_bed[data_id][self.combobox_freq2.currentIndex(),
                     :, :],
                     cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
                 else:
                     self.axis_BS.pcolormesh(
-                        stg.time[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time[data_id][
                     self.combobox_freq2.currentIndex(), :],
-                    -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                    -stg.depth[data_id][
                      self.combobox_freq2.currentIndex(), :],
-                    stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(),
+                    stg.BS_stream_bed[data_id][self.combobox_freq2.currentIndex(),
                     :, :],
                     cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
 
-        elif stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+        elif stg.BS_cross_section_pre_process_average[data_id].shape != (0,):
 
             val_min = np.nanmin(
-                stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][
+                stg.BS_cross_section_pre_process_average[data_id][
                 self.combobox_freq2.currentIndex(), :, :])
             val_max = np.nanmax(
-                stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][
+                stg.BS_cross_section_pre_process_average[data_id][
                 self.combobox_freq2.currentIndex(), :, :])
             if val_min == 0:
                 val_min = 1e-5
 
-            if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
-                if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+            if stg.time_cross_section[data_id].shape != (0,):
+                if stg.depth_cross_section[data_id].shape != (0,):
                     self.axis_BS.pcolormesh(
-                        stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time_cross_section[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth_cross_section[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_cross_section_pre_process_average[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
                 else:
                     self.axis_BS.pcolormesh(
-                        stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time_cross_section[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_cross_section_pre_process_average[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
             else:
-                if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+                if stg.depth_cross_section[data_id].shape != (0,):
                     self.axis_BS.pcolormesh(
-                        stg.time[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth_cross_section[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_cross_section_pre_process_average[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
                 else:
                     self.axis_BS.pcolormesh(
-                        stg.time[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_cross_section_pre_process_average[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
 
-        elif stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+        elif stg.BS_cross_section_pre_process_SNR[data_id].shape != (0,):
 
             val_min = np.nanmin(
-                stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][
+                stg.BS_cross_section_pre_process_SNR[data_id][
                 self.combobox_freq2.currentIndex(), :, :])
             val_max = np.nanmax(
-                stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][
+                stg.BS_cross_section_pre_process_SNR[data_id][
                 self.combobox_freq2.currentIndex(), :, :])
             if val_min == 0:
                 val_min = 1e-5
 
-            if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
-                if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0):
+            if stg.time_cross_section[data_id].shape != (0,):
+                if stg.depth_cross_section[data_id].shape != (0):
                     self.axis_BS.pcolormesh(
-                        stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time_cross_section[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth_cross_section[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_cross_section_pre_process_SNR[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
                 else:
                     self.axis_BS.pcolormesh(
-                        stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time_cross_section[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_cross_section_pre_process_SNR[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
             else:
-                if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0):
+                if stg.depth_cross_section[data_id].shape != (0):
                     self.axis_BS.pcolormesh(
-                        stg.time[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth_cross_section[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_cross_section_pre_process_SNR[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
                 else:
                     self.axis_BS.pcolormesh(
-                        stg.time[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_cross_section_pre_process_SNR[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
 
-        elif stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+        elif stg.BS_cross_section[data_id].shape != (0,):
 
             val_min = np.nanmin(
-                stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                stg.BS_cross_section[data_id][
                 self.combobox_freq2.currentIndex(), :, :])
             val_max = np.nanmax(
-                stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                stg.BS_cross_section[data_id][
                 self.combobox_freq2.currentIndex(), :, :])
             if val_min == 0:
                 val_min = 1e-5
 
-            if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
-                if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+            if stg.time_cross_section[data_id].shape != (0,):
+                if stg.depth_cross_section[data_id].shape != (0,):
                     self.axis_BS.pcolormesh(
-                        stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time_cross_section[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth_cross_section[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_cross_section[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
                 else:
                     self.axis_BS.pcolormesh(
-                        stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time_cross_section[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_cross_section[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
             else:
-                if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+                if stg.depth_cross_section[data_id].shape != (0,):
                     self.axis_BS.pcolormesh(
-                        stg.time[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth_cross_section[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_cross_section[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
                 else:
                     self.axis_BS.pcolormesh(
-                        stg.time[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.time[data_id][
                         self.combobox_freq2.currentIndex(), :],
-                        -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                        -stg.depth[data_id][
                          self.combobox_freq2.currentIndex(), :],
-                        stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                        stg.BS_cross_section[data_id][
                         self.combobox_freq2.currentIndex(), :, :],
                         cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
 
 
-        elif stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+        elif stg.BS_raw_data_pre_process_average[data_id].shape != (0,):
 
-            val_min = np.nanmin(stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][
+            val_min = np.nanmin(stg.BS_raw_data_pre_process_average[data_id][
                                 self.combobox_freq2.currentIndex(), :, :])
-            val_max = np.nanmax(stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][
+            val_max = np.nanmax(stg.BS_raw_data_pre_process_average[data_id][
                                 self.combobox_freq2.currentIndex(), :, :])
             if val_min == 0:
                 val_min = 1e-5
 
             self.axis_BS.pcolormesh(
-                stg.time[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :],
-                -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :],
-                stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][
+                stg.time[data_id][self.combobox_freq2.currentIndex(), :],
+                -stg.depth[data_id][self.combobox_freq2.currentIndex(), :],
+                stg.BS_raw_data_pre_process_average[data_id][
                 self.combobox_freq2.currentIndex(), :, :],
                 cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
 
 
 
-        elif stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+        elif stg.BS_raw_data_pre_process_SNR[data_id].shape != (0,):
 
-            val_min = np.nanmin(stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][
+            val_min = np.nanmin(stg.BS_raw_data_pre_process_SNR[data_id][
                                 self.combobox_freq2.currentIndex(), :, :])
-            val_max = np.nanmax(stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][
+            val_max = np.nanmax(stg.BS_raw_data_pre_process_SNR[data_id][
                                 self.combobox_freq2.currentIndex(), :, :])
             if val_min == 0:
                 val_min = 1e-5
 
             self.axis_BS.pcolormesh(
-                stg.time[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :],
-                -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :],
-                stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][
+                stg.time[data_id][self.combobox_freq2.currentIndex(), :],
+                -stg.depth[data_id][self.combobox_freq2.currentIndex(), :],
+                stg.BS_raw_data_pre_process_SNR[data_id][
                 self.combobox_freq2.currentIndex(), :, :],
                 cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
 
-        elif stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+        elif stg.BS_raw_data[data_id].shape != (0,):
 
-            val_min = np.nanmin(stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()][
+            val_min = np.nanmin(stg.BS_raw_data[data_id][
                                 self.combobox_freq2.currentIndex(), :, :])
-            val_max = np.nanmax(stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()][
+            val_max = np.nanmax(stg.BS_raw_data[data_id][
                                 self.combobox_freq2.currentIndex(), :, :])
             if val_min == 0:
                 val_min = 1e-5
 
             self.axis_BS.pcolormesh(
-                stg.time[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :],
-                -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :],
-                stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()][
+                stg.time[data_id][self.combobox_freq2.currentIndex(), :],
+                -stg.depth[data_id][self.combobox_freq2.currentIndex(), :],
+                stg.BS_raw_data[data_id][
                     self.combobox_freq2.currentIndex(), :, :],
                 cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
 
@@ -1370,16 +1372,16 @@ class SedimentCalibrationTab(QWidget):
         # --- Plot vertical red line for position of FCB profile ---
         if stg.sand_sample_target_indice:
 
-            if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+            if stg.depth_cross_section[data_id].shape != (0,):
 
-                if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+                if stg.time_cross_section[data_id].shape != (0,):
 
                     self.red_line_plot_return, = (
                         self.axis_BS.plot(
-                            stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                            stg.time_cross_section[data_id][
                                 self.combobox_freq2.currentIndex(), stg.sand_sample_target_indice[0][1]] *
-                            np.ones(stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape[1]),
-                            -stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                            np.ones(stg.depth_cross_section[data_id].shape[1]),
+                            -stg.depth_cross_section[data_id][
                                 self.combobox_freq2.currentIndex(), :],
                             color='red', linestyle="solid", linewidth=2))
 
@@ -1387,23 +1389,23 @@ class SedimentCalibrationTab(QWidget):
 
                     self.red_line_plot_return, = (
                         self.axis_BS.plot(
-                            stg.time[self.combobox_acoustic_data_choice.currentIndex()][
+                            stg.time[data_id][
                                 self.combobox_freq2.currentIndex(), stg.sand_sample_target_indice[0][1]] *
-                            np.ones(stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape[1]),
-                            -stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                            np.ones(stg.depth_cross_section[data_id].shape[1]),
+                            -stg.depth_cross_section[data_id][
                              self.combobox_freq2.currentIndex(), :],
                             color='red', linestyle="solid", linewidth=2))
 
             else:
 
-                if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+                if stg.time_cross_section[data_id].shape != (0,):
 
                     self.red_line_plot_return, = (
                         self.axis_BS.plot(
-                            stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
+                            stg.time_cross_section[data_id][
                                 self.combobox_freq2.currentIndex(), stg.sand_sample_target_indice[0][1]] *
-                            np.ones(stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape[1]),
-                            -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                            np.ones(stg.depth[data_id].shape[1]),
+                            -stg.depth[data_id][
                              self.combobox_freq2.currentIndex(), :],
                             color='red', linestyle="solid", linewidth=2))
 
@@ -1411,10 +1413,10 @@ class SedimentCalibrationTab(QWidget):
 
                     self.red_line_plot_return, = (
                         self.axis_BS.plot(
-                            stg.time[self.combobox_acoustic_data_choice.currentIndex()][
+                            stg.time[data_id][
                                 self.combobox_freq2.currentIndex(), stg.sand_sample_target_indice[0][1]] *
-                            np.ones(stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape[1]),
-                            -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                            np.ones(stg.depth[data_id].shape[1]),
+                            -stg.depth[data_id][
                              self.combobox_freq2.currentIndex(), :],
                             color='red', linestyle="solid", linewidth=2))
 
@@ -1944,13 +1946,12 @@ class SedimentCalibrationTab(QWidget):
 
     def compute_depth_2D(self):
         if self.combobox_acoustic_data_choice.count() > 0:
-
             for k in range(self.combobox_acoustic_data_choice.count()):
+                while len(stg.depth_2D) <= k:
+                    stg.depth_2D.append(np.array([]))
 
                 if stg.depth_cross_section[k].shape != (0,):
-
                     if stg.time_cross_section[k].shape != (0,):
-
                         stg.depth_2D[k] = (
                             np.zeros((stg.freq[k].shape[0],
                                       stg.depth_cross_section[k].shape[1],
@@ -1964,7 +1965,6 @@ class SedimentCalibrationTab(QWidget):
                                           axis=1))
 
                     elif stg.time[k].shape != (0,):
-
                         stg.depth_2D[k] = (
                             np.zeros((stg.freq[k].shape[0],
                                       stg.depth_cross_section[k].shape[1],
@@ -1979,9 +1979,7 @@ class SedimentCalibrationTab(QWidget):
                                     axis=1))
 
                 elif stg.depth[k].shape != (0,):
-
                     if stg.time_cross_section[k].shape != (0,):
-
                         stg.depth_2D[k] = (
                             np.zeros((stg.freq[k].shape[0],
                                       stg.depth[k].shape[1],
@@ -1996,7 +1994,6 @@ class SedimentCalibrationTab(QWidget):
                                     axis=1))
 
                     elif stg.time[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
-
                         stg.depth_2D[k] = (
                             np.zeros((stg.freq[k].shape[0],
                                       stg.depth[k].shape[1],