diff --git a/View/sediment_calibration_tab.py b/View/sediment_calibration_tab.py
index 6061be9..970241c 100644
--- a/View/sediment_calibration_tab.py
+++ b/View/sediment_calibration_tab.py
@@ -21,9 +21,18 @@
 # -*- coding: utf-8 -*-
 
 import os
+import logging
+
+from scipy.stats import linregress
+
+import numpy as np
+import pandas as pd
 
 import matplotlib.pyplot as plt
-import pandas as pd
+from matplotlib.colors import LogNorm
+from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
+from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as NavigationToolBar
+
 from PyQt5.QtWidgets import (
     QWidget, QVBoxLayout, QHBoxLayout, QGroupBox, QComboBox,
     QGridLayout, QLabel, QPushButton, QSlider, QLineEdit,
@@ -35,18 +44,10 @@ from PyQt5.QtGui import QIcon, QPixmap, QFont
 
 import settings as stg
 
-import numpy as np
-
-from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
-from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as NavigationToolBar
-from matplotlib.colors import LogNorm
-
-from scipy.stats import linregress
-
 from View.checkable_combobox import CheckableComboBox
-
 from Model.acoustic_inversion_method_high_concentration import AcousticInversionMethodHighConcentration
 
+logger = logging.getLogger()
 
 class SedimentCalibrationTab(QWidget):
 
@@ -861,7 +862,6 @@ class SedimentCalibrationTab(QWidget):
         self.compute_FCB()
 
     def update_acoustic_data(self):
-
         self.combobox_acoustic_data_choice.clear()
         self.combobox_acoustic_data_choice.addItems(stg.data_preprocessed)
         self.combobox_acoustic_data_choice.currentIndexChanged.connect(self.plot_acoustic_recording)
@@ -1510,89 +1510,64 @@ class SedimentCalibrationTab(QWidget):
                                marker="*", mfc="b", mec="b", ms=8, ls="None")
 
     def interpolate_Mfine_profile(self):
+        data_choice = self.combobox_acoustic_data_choice.currentIndex()
 
-        if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
-
-            print("test find indice of time ", np.where( np.abs(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :]
-                        - (stg.time_fine[stg.fine_sample_profile[-1][1]])) ==
-                        np.nanmin(np.abs(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :]
-                        - (stg.time_fine[stg.fine_sample_profile[-1][1]]))) ))
-            print(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :])
-            print(stg.time_fine[stg.fine_sample_profile[-1][1]])
-
-            if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
-
-                stg.range_lin_interp, stg.M_profile_fine = (
-                    self.inv_hc.M_profile_SCC_fine_interpolated(
-                        sample_depth=[-stg.depth_fine[k[1]] for k in stg.fine_sample_profile],
-                        M_profile=[stg.Ctot_fine[k[1]] for k in stg.fine_sample_profile],
-                        range_cells=stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :],
-                        r_bottom=stg.depth_bottom[self.combobox_acoustic_data_choice.currentIndex()]
-                                    [
-                            np.where( np.abs(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :]
-                            - stg.time_fine[stg.fine_sample_profile[-1][1]]) ==
-                            np.nanmin(np.abs(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :]
-                            - stg.time_fine[stg.fine_sample_profile[-1][1]])) )[0][0]
-                                    ]
-                                                                )
-                                                    )
+        if stg.depth_cross_section[data_choice].shape != (0,):
+            range_cells = stg.depth_cross_section[data_choice][
+                self.combobox_freq2.currentIndex(), :
+            ]
 
+            if stg.time_cross_section[data_choice].shape != (0,):
+                time_data = stg.time_cross_section
             else:
-
-                stg.range_lin_interp, stg.M_profile_fine = (
-                    self.inv_hc.M_profile_SCC_fine_interpolated(
-                        sample_depth=[-stg.depth_fine[k[1]] for k in stg.fine_sample_profile],
-                        M_profile=[stg.Ctot_fine[k[1]] for k in stg.fine_sample_profile],
-                        range_cells=stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :],
-                        r_bottom=stg.depth_bottom[self.combobox_acoustic_data_choice.currentIndex()]
-                                    [
-                            np.where( np.abs(stg.time[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :]
-                            - stg.time_fine[stg.fine_sample_profile[-1][1]]) ==
-                            np.nanmin(np.abs(stg.time[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :]
-                            - stg.time_fine[stg.fine_sample_profile[-1][1]])) )[0][0]
-                                    ]
-                                                                )
-                                                    )
+                time_data = stg.time
 
         else:
+            range_cells=stg.depth[data_choice][
+                self.combobox_freq2.currentIndex(), :
+            ]
 
-            if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
-
-                stg.range_lin_interp, stg.M_profile_fine = (
-                    self.inv_hc.M_profile_SCC_fine_interpolated(
-                        sample_depth=[-stg.depth_fine[k[1]] for k in stg.fine_sample_profile],
-                        M_profile=[stg.Ctot_fine[k[1]] for k in stg.fine_sample_profile],
-                        range_cells=stg.depth[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :],
-                        r_bottom=stg.depth_bottom[self.combobox_acoustic_data_choice.currentIndex()]
-                        [
-                            np.where(np.abs(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
-                                            self.combobox_freq2.currentIndex(), :]
-                                            - stg.time_fine[stg.fine_sample_profile[-1][1]]) ==
-                                     np.nanmin(np.abs(
-                                         stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
-                                         self.combobox_freq2.currentIndex(), :]
-                                         - stg.time_fine[stg.fine_sample_profile[-1][1]])))[0][0]
-                        ]
-                    ))
-
+            if stg.time_cross_section[data_choice].shape != (0,):
+                time_data = stg.time_cross_sectino
             else:
+                time_data = stg.time
 
-                stg.range_lin_interp, stg.M_profile_fine = (
-                    self.inv_hc.M_profile_SCC_fine_interpolated(
-                        sample_depth=[-stg.depth_fine[k[1]] for k in stg.fine_sample_profile],
-                        M_profile=[stg.Ctot_fine[k[1]] for k in stg.fine_sample_profile],
-                        range_cells=stg.depth[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :],
-                        r_bottom=stg.depth_bottom[self.combobox_acoustic_data_choice.currentIndex()]
-                        [
-                            np.where(np.abs(stg.time[self.combobox_acoustic_data_choice.currentIndex()][
-                                            self.combobox_freq2.currentIndex(), :]
-                                            - stg.time_fine[stg.fine_sample_profile[-1][1]]) ==
-                                     np.nanmin(np.abs(
-                                         stg.time[self.combobox_acoustic_data_choice.currentIndex()][
-                                         self.combobox_freq2.currentIndex(), :]
-                                         - stg.time_fine[stg.fine_sample_profile[-1][1]])))[0][0]
-                        ]
-                    ))
+        sample_depth = [-stg.depth_fine[k[1]] for k in stg.fine_sample_profile]
+        M_profile = [stg.Ctot_fine[k[1]] for k in stg.fine_sample_profile]
+
+        r_bottom = stg.depth_bottom[data_choice][
+            np.where(
+                np.abs(
+                    time_data[data_choice][
+                        self.combobox_freq2.currentIndex(), :
+                    ]
+                    - stg.time_fine[stg.fine_sample_profile[-1][1]]
+                ) == np.nanmin(
+                    np.abs(
+                        time_data[data_choice][
+                            self.combobox_freq2.currentIndex(), :
+                    ]
+                        - stg.time_fine[stg.fine_sample_profile[-1][1]])
+                )
+            )[0][0]
+        ]
+
+        logger.debug(
+            "call 'inv_hc.M_profile_SCC_fine_interpolated' params:"
+        )
+        logger.debug(f"sample_depth = {sample_depth}")
+        logger.debug(f"M_profile = {M_profile}")
+        logger.debug(f"range_cells = {range_cells}")
+        logger.debug(f"r_bottom = {r_bottom}")
+
+        stg.range_lin_interp, stg.M_profile_fine = (
+            self.inv_hc.M_profile_SCC_fine_interpolated(
+                sample_depth=sample_depth,
+                M_profile=M_profile,
+                range_cells=range_cells,
+                r_bottom=r_bottom
+            )
+        )
 
         stg.range_lin_interp = stg.range_lin_interp
         stg.M_profile_fine = stg.M_profile_fine