Mainwindow: Minor change.

View/about_window.py

@@ -31,13 +31,13 @@ class AboutWindow(QDialog):
 
         super().__init__()
 
-        self.logo_path = "./Logo"
-        self.logo_AcouSed = QPixmap(self.logo_path + "/" + "Logo_AcouSed_AboutAcouSedWindow.png")
+        self.logo_path = "./logos"
+        self.logo_AcouSed = QPixmap(self.logo_path + "/" + "AcouSed.png")
         self.logo_AcouSed.scaled(16, 16, Qt.KeepAspectRatio, Qt.SmoothTransformation)
 
         self.logo_INRAE = QPixmap(self.logo_path + "/" + "BlocMarque-INRAE-Inter.jpg")
 
-        self.setGeometry(400, 200, 300, 200)
+        self.setGeometry(400, 200, 350, 200)
 
         self.setWindowTitle("About AcouSed")
 
@@ -51,7 +51,7 @@ class AboutWindow(QDialog):
 
         self.label_logo_AcouSed = QLabel()
         self.label_logo_AcouSed.setPixmap(self.logo_AcouSed.scaledToHeight(128, Qt.SmoothTransformation))
-        self.gridLayout.addWidget(self.label_logo_AcouSed, 0, 0, 3, 1, Qt.AlignCenter)
+        self.gridLayout.addWidget(self.label_logo_AcouSed, 0, 0, 5, 1, Qt.AlignCenter)
 
         self.label_acoused = QLabel()
         self.label_acoused.setText("Acoused 2.0")
@@ -70,7 +70,13 @@ class AboutWindow(QDialog):
         self.label_contact = QLabel()
         self.label_contact.setText("Contact : celine.berni@inrae.fr \n"
                                    "                   jerome.lecoz@inrae.fr")
-        self.gridLayout.addWidget(self.label_contact, 3, 1, 1, 1, Qt.AlignLeft)
+        self.gridLayout.addWidget(self.label_contact, 3, 1, 1, 1, Qt.AlignCenter)
+
+        self.label_link = QLabel()
+        self.label_link.setText("< a href = https://forgemia.inra.fr/theophile.terraz/acoused > "
+                                "https://forgemia.inra.fr/theophile.terraz/acoused </a>")
+        self.label_link.setOpenExternalLinks(True)
+        self.gridLayout.addWidget(self.label_link, 4, 1, 1, 1, Qt.AlignCenter)
 
         # ----------------------------------------------------------
 
@@ -179,7 +185,7 @@ class Support(QDialog):
 
         super().__init__()
 
-        self.logo_path = "./Logo"
+        self.logo_path = "./logos"
 
         self.logo_OSR = QPixmap(self.logo_path + '/' + "OSR.png")
         self.logo_CNR = QPixmap(self.logo_path + '/' + "CNR.png")

View/acoustic_data_tab.py

@@ -626,17 +626,19 @@ class AcousticDataTab(QWidget):
         self.delBtn.clicked.connect(self.remove_file_from_ListWidget)
         self.clearBtn.clicked.connect(self.clear_files_from_ListWidget)
 
-        self.fileListWidget.itemSelectionChanged.connect(self.print_selected_file)
-        self.fileListWidget.itemSelectionChanged.connect(self.fill_measurements_information_groupbox)
-        self.fileListWidget.itemSelectionChanged.connect(self.fill_table)
-        self.fileListWidget.itemSelectionChanged.connect(self.compute_tmin_tmax)
-        self.fileListWidget.itemSelectionChanged.connect(self.compute_rmin_rmax)
-        self.fileListWidget.itemSelectionChanged.connect(self.update_frequency_combobox)
-        # self.fileListWidget.itemSelectionChanged.connect(self.plot_backscattered_acoustic_signal_recording)
-        self.fileListWidget.itemSelectionChanged.connect(self.plot_profile)
-        self.fileListWidget.itemSelectionChanged.connect(self.update_plot_backscattered_acoustic_signal_recording)
-        self.fileListWidget.itemSelectionChanged.connect(self.update_plot_profile)
-        self.fileListWidget.itemSelectionChanged.connect(self.set_range_for_spinboxes_bathymetry)
+        self.fileListWidget.itemSelectionChanged.connect(self.fileListWidget_event)
+
+        # self.fileListWidget.itemSelectionChanged.connect(self.print_selected_file)
+        # self.fileListWidget.itemSelectionChanged.connect(self.fill_measurements_information_groupbox)
+        # self.fileListWidget.itemSelectionChanged.connect(self.fill_table)
+        # self.fileListWidget.itemSelectionChanged.connect(self.compute_tmin_tmax)
+        # self.fileListWidget.itemSelectionChanged.connect(self.compute_rmin_rmax)
+        # self.fileListWidget.itemSelectionChanged.connect(self.update_frequency_combobox)
+        # # self.fileListWidget.itemSelectionChanged.connect(self.plot_backscattered_acoustic_signal_recording)
+        # # self.fileListWidget.itemSelectionChanged.connect(self.plot_profile)
+        # self.fileListWidget.itemSelectionChanged.connect(self.update_plot_backscattered_acoustic_signal_recording)
+        # self.fileListWidget.itemSelectionChanged.connect(self.update_plot_profile)
+        # self.fileListWidget.itemSelectionChanged.connect(self.set_range_for_spinboxes_bathymetry)
 
         self.combobox_ABS_name.currentIndexChanged.connect(self.fill_measurements_information_groupbox)
 
@@ -744,6 +746,20 @@ class AcousticDataTab(QWidget):
 
         self.groupbox_transect_2Dplot_raw_BS_data.setTitle(_translate("CONSTANT_STRING", cs.RAW_ACOUSTIC_DATA_2D_FIELD))
 
+    def fileListWidget_event(self):
+
+        self.print_selected_file()
+        self.fill_measurements_information_groupbox()
+        self.fill_table()
+        self.compute_tmin_tmax()
+        self.compute_rmin_rmax()
+        self.update_frequency_combobox()
+        # self.fileListWidget.itemSelectionChanged.connect(self.plot_backscattered_acoustic_signal_recording)
+        # self.fileListWidget.itemSelectionChanged.connect(self.plot_profile)
+        self.update_plot_backscattered_acoustic_signal_recording()
+        self.update_plot_profile()
+        self.set_range_for_spinboxes_bathymetry()
+
     def print_selected_file(self):
         print(f"Selected file in list widget : {self.fileListWidget.selectedItems()}")
         print("self.fileListWidget.selectedItems()[1:] : ", self.fileListWidget.selectedItems()[1:])
@@ -1327,8 +1343,12 @@ class AcousticDataTab(QWidget):
                 self.fill_measurements_information_groupbox()
                 self.fill_table()
                 self.plot_backscattered_acoustic_signal_recording()
+                self.plot_profile()
                 self.update_frequency_combobox()
                 self.water_attenuation()
+                self.compute_tmin_tmax()
+                self.compute_rmin_rmax()
+                self.set_range_for_spinboxes_bathymetry()
 
                 stg.acoustic_data = list(
                     range(
@@ -1361,26 +1381,39 @@ class AcousticDataTab(QWidget):
                 del current_item
 
             # --- Clear variables ---
-            list_to_pop1 = ["stg.acoustic_data", "stg.date", "stg.hour", "stg.freq", "stg.freq_text", "stg.temperature",
-                            "stg.nb_profiles", "stg.nb_profiles_per_sec", "stg.nb_cells", "stg.cell_size",
-                            "stg.pulse_length", "stg.nb_pings_per_sec", "stg.nb_pings_averaged_per_profile",
-                            "stg.kt_read", "stg.kt_corrected", "stg.gain_rx", "stg.gain_tx",
-                            "stg.filename_BS_raw_data", "stg.path_BS_raw_data",
-                            "stg.BS_raw_data", "stg.time", "stg.depth",
-                            "stg.BS_raw_data_reshape", "stg.time_reshape", "stg.depth_reshape"]
+            list_to_pop1 = [
+                "stg.acoustic_data", "stg.date", "stg.hour",
+                "stg.freq", "stg.freq_text",
+                "stg.nb_profiles", "stg.nb_profiles_per_sec",
+                "stg.nb_cells", "stg.cell_size",
+                "stg.pulse_length", "stg.nb_pings_per_sec",
+                "stg.nb_pings_averaged_per_profile",
+                "stg.kt_read", "stg.kt_corrected", "stg.gain_rx", "stg.gain_tx",
+                "stg.filename_BS_raw_data", "stg.path_BS_raw_data",
+                "stg.BS_raw_data", "stg.time", "stg.depth",
+                "stg.BS_raw_data_reshape", "stg.time_reshape", "stg.depth_reshape"
+            ]
 
             for p in list_to_pop1:
-                if isinstance(p, list):
+                if isinstance(eval(p), list):
                     exec(p + ".pop(current_row)")
 
             if stg.BS_cross_section:
 
                 list_to_pop2 = ["stg.rmin", "stg.rmax", "stg.tmin", "stg.tmax",
-                                "stg.time_cross_section", "stg.BS_cross_section"]
+                                "stg.time_cross_section", "stg.depth_cross_section", "stg.BS_cross_section"]
 
                 for k in list_to_pop2:
                     exec(k + ".pop(current_row)")
 
+            if stg.BS_stream_bed:
+
+                list_to_pop3 = ["stg.BS_stream_bed", "stg.depth_bottom",
+                                "stg.val_bottom", "stg.ind_bottom", "stg.freq_bottom_detection"]
+
+                for s in list_to_pop3:
+                    exec(s + ".pop(current_row)")
+
             if self.fileListWidget.count() == 0:
 
                 # --- Clear measurements information ---
@@ -1459,24 +1492,26 @@ class AcousticDataTab(QWidget):
 
         list_to_clear = [
             "stg.acoustic_data", "stg.date", "stg.hour",
-            "stg.freq", "stg.freq_text", "stg.temperature",
+            "stg.freq", "stg.freq_text",
             "stg.nb_profiles", "stg.nb_profiles_per_sec",
             "stg.nb_cells", "stg.cell_size",
             "stg.pulse_length", "stg.nb_pings_per_sec",
             "stg.nb_pings_averaged_per_profile",
             "stg.kt_read", "stg.kt_corrected", "stg.gain_rx", "stg.gain_tx",
+            "stg.filename_BS_raw_data", "stg.path_BS_raw_data",
             "stg.BS_raw_data", "stg.time", "stg.depth",
             "stg.BS_raw_data_reshape", "stg.time_reshape", "stg.depth_reshape",
             "stg.rmin", "stg.rmax", "stg.tmin", "stg.tmax",
             "stg.time_cross_section", "stg.depth_cross_section",
-            "stg.BS_cross_section"
+            "stg.BS_cross_section", "stg.BS_stream_bed"
         ]
 
         for k in list_to_clear:
-            if isinstance(k, list):
+            if isinstance(eval(k), list):
                 exec(k + ".clear()")
 
         self.fileListWidget.clear()
+        # self.fileListWidget.takeItem(0)
 
         if self.fileListWidget.count() == 0:
             # --- Clear measurmeents information ---
@@ -1683,9 +1718,13 @@ class AcousticDataTab(QWidget):
         self.fill_measurements_information_groupbox_kt()
 
     def fill_measurements_information_groupbox_datetime(self):
+        file_id = self.fileListWidget.currentRow()
+        print("file_id ", file_id)
+        print("stg.date ", stg.date)
         self.label_date_acoustic_file.clear()
+
         self.label_date_acoustic_file.setText(
-            "Date: " + str(stg.date[self.fileListWidget.currentRow()])
+            "Date: " + str(stg.date[file_id])
         )
         self.gridLayout_groupbox_info.addWidget(
             self.label_date_acoustic_file,
@@ -1695,7 +1734,7 @@ class AcousticDataTab(QWidget):
 
         self.label_hour_acoustic_file.clear()
         self.label_hour_acoustic_file.setText(
-            "Hour: " + str(stg.hour[self.fileListWidget.currentRow()])
+            "Hour: " + str(stg.hour[file_id])
         )
         self.gridLayout_groupbox_info.addWidget(
             self.label_hour_acoustic_file,
@@ -2012,7 +2051,8 @@ class AcousticDataTab(QWidget):
             )
 
     def fill_table(self):
-        if self.fileListWidget.currentRow() != -1:
+        # if self.fileListWidget.currentRow() != -1:
+        if self.fileListWidget.selectedItems() != []:
             file_id = self.fileListWidget.currentRow()
 
             header_list = []

View/mainwindow.py

@@ -39,6 +39,7 @@ from View.about_window import AboutWindow
 import settings as stg
 
 import numpy as np
+import pandas as pd
 from subprocess import Popen
 
 import time
@@ -325,23 +326,21 @@ class Ui_MainWindow(object):
         self.open_doc_file('Tutorial_AQUAscat_software.pdf')
 
     def export_table_of_acoustic_BS_values_to_excel_or_libreOfficeCalc_file(self):
-
         if len(stg.BS_raw_data_reshape) != 0:
-
-            # --- Open file dialog to select the directory ---
-
-            name = QtWidgets.QFileDialog.getExistingDirectory(caption="Select Directory - Acoustic BS raw data Table")
+            name = QtWidgets.QFileDialog.getExistingDirectory(
+                caption="Select Directory - Acoustic BS raw data Table"
+            )
             print("name table to save ", name)
 
-            # --- Save the raw acoustic backscatter data from a Dataframe to csv file ---
+            # --- Save the raw acoustic backscatter data from a
+            # --- Dataframe to csv file ---
 
             t0 = time.time()
-            print("len(stg.BS_raw_data_reshape) ", len(stg.BS_raw_data_reshape))
+            print("len(stg.BS_raw_data_reshape) ",
+                  len(stg.BS_raw_data_reshape))
 
             if name:
-
                 for i in range(len(stg.BS_raw_data_reshape)):
-
                     header_list = []
                     header_list.clear()
                     table_data = np.array([[]])
@@ -351,27 +350,42 @@ class Ui_MainWindow(object):
                         header_list.append("BS - " + freq_value)
 
                         if freq_ind == 0:
-                            table_data = np.vstack((np.vstack((stg.time_reshape[i][:, freq_ind],
-                                                               stg.depth_reshape[i][:, freq_ind])),
-                                                               stg.BS_raw_data_reshape[i][:, freq_ind]))
+                            table_data = np.vstack(
+                                (
+                                    np.vstack(
+                                        (stg.time_reshape[i][:, freq_ind],
+                                         stg.depth_reshape[i][:, freq_ind])),
+                                    stg.BS_raw_data_reshape[i][:, freq_ind]
+                                )
+                            )
 
                         else:
-                            table_data = np.vstack((table_data,
-                                                    np.vstack((np.vstack(
-                                                        (stg.time_reshape[i][:, freq_ind],
-                                                         stg.depth_reshape[i][:, freq_ind])),
-                                                         stg.BS_raw_data_reshape[i][:, freq_ind]))
-                                                    ))
+                            table_data = np.vstack(
+                                (
+                                    table_data,
+                                    np.vstack((
+                                        np.vstack((
+                                            stg.time_reshape[i][:, freq_ind],
+                                            stg.depth_reshape[i][:, freq_ind]
+                                        )),
+                                        stg.BS_raw_data_reshape[i][:, freq_ind]
+                                    ))
+                                )
+                            )
 
-                    exec("DataFrame_acoustic_" + str(i) + "= pd.DataFrame(None)")
-                    exec("DataFrame_acoustic_" + str(i) + "= pd.DataFrame(data=table_data.transpose(), columns=header_list)")
+                    DataFrame_acoustic = pd.DataFrame(None)
+                    DataFrame_acoustic = pd.DataFrame(
+                        data=table_data.transpose(), columns=header_list
+                    )
 
-                    exec("DataFrame_acoustic_" + str(i) + ".to_csv(" +
-                         "path_or_buf=" +
-                         "'" + name + "/" + "Table_" +
-                         str(stg.filename_BS_raw_data[i][:-4]) + ".csv'" + ", " +
-                         "sep=" + "',' " + ", " +
-                         "header=DataFrame_acoustic_" + str(i) + ".columns" + ")")
+                    DataFrame_acoustic.to_csv(
+                        path_or_buf=os.path.join(
+                            name,
+                            f"Table_{str(stg.filename_BS_raw_data[i][:-4])}.csv"
+                        ),
+                        header=DataFrame_acoustic.columns,
+                        sep=',',
+                    )
 
             t1 = time.time() - t0
             print("time duration export BS ", t1)

View/sediment_calibration_tab.py

@@ -1716,32 +1716,47 @@ class SedimentCalibrationTab(QWidget):
         self.animaiton_groupbox_compute.start()
 
     def import_calibration_file(self):
-        filename = QFileDialog.getOpenFileName(
-            self, "Open calibration",
-            [
-                stg.path_calibration_file
-                if stg.path_calibration_file
-                else stg.path_BS_raw_data[-1]
-                if self.combobox_acoustic_data_choice.count() > 0
-                else ""
-            ][0],
-            "Calibration file (*.xls, *.ods, *csv)",
-            options=QFileDialog.DontUseNativeDialog
-        )
 
-        dir_name = os.path.dirname(filename[0])
-        name = os.path.basename(filename[0])
+        if self.combobox_acoustic_data_choice.count() == 0:
+            msgBox = QMessageBox()
+            msgBox.setWindowTitle("Calibration import error")
+            msgBox.setIconPixmap(
+                QPixmap(
+                    self._path_icon("no_approved.png")
+                ).scaledToHeight(32, Qt.SmoothTransformation)
+            )
+            msgBox.setText("Update data before importing calibration")
+            msgBox.setStandardButtons(QMessageBox.Ok)
+            msgBox.exec()
 
-        stg.path_calibration_file = dir_name
-        stg.filename_calibration_file = name
+        else:
 
-        self.lineEdit_import_calibration.clear()
-        self.lineEdit_import_calibration.setText(name)
+            filename = QFileDialog.getOpenFileName(
+                self, "Open calibration",
+                [
+                    stg.path_calibration_file
+                    if stg.path_calibration_file
+                    else stg.path_BS_raw_data[-1]
+                    if self.combobox_acoustic_data_choice.count() > 0
+                    else ""
+                ][0],
+                "Calibration file (*.xls, *.ods, *csv)",
+                options=QFileDialog.DontUseNativeDialog
+            )
 
-        self.lineEdit_import_calibration.setToolTip(dir_name)
+            dir_name = os.path.dirname(filename[0])
+            name = os.path.basename(filename[0])
 
-        self.compute_depth_2D()
-        self.read_calibration_file_and_fill_parameter()
+            stg.path_calibration_file = dir_name
+            stg.filename_calibration_file = name
+
+            self.lineEdit_import_calibration.clear()
+            self.lineEdit_import_calibration.setText(name)
+
+            self.lineEdit_import_calibration.setToolTip(dir_name)
+
+            self.compute_depth_2D()
+            self.read_calibration_file_and_fill_parameter()
 
     def update_label_freq1_for_calibration(self):
         self.label_freq1.clear()
@@ -1784,26 +1799,14 @@ class SedimentCalibrationTab(QWidget):
             )
 
     def read_calibration_file_and_fill_parameter(self):
-        if self.combobox_acoustic_data_choice.count() == 0:
-            msgBox = QMessageBox()
-            msgBox.setWindowTitle("Calibration import error")
-            msgBox.setIconPixmap(
-                QPixmap(
-                    self._path_icon("no_approved.png")
-                ).scaledToHeight(32, Qt.SmoothTransformation)
-            )
-            msgBox.setText("Update data before importing calibration")
-            msgBox.setStandardButtons(QMessageBox.Ok)
-            msgBox.exec()
+
+        if stg.filename_calibration_file == "":
+
+            pass
+
         else:
             # --- Read calibration file ---
-            data = pd.read_csv(
-                os.path.join(
-                    stg.path_calibration_file,
-                    stg.filename_calibration_file
-                ),
-                header=0, index_col=0
-            )
+            data = pd.read_csv(os.path.join(stg.path_calibration_file, stg.filename_calibration_file), header=0, index_col=0)
 
             # --- Fill spinboxes of calibration parameter ---
             self.label_temperature.clear()
@@ -1997,17 +2000,31 @@ class SedimentCalibrationTab(QWidget):
 
     def function_pushbutton_compute_calibration(self):
 
-        self.label_temperature.clear()
-        self.label_temperature.setText("T = " + str(stg.temperature) + " °C")
+        if self.combobox_acoustic_data_choice.count() == 0:
+            msgBox = QMessageBox()
+            msgBox.setWindowTitle("Calibration computation error")
+            msgBox.setIconPixmap(
+                QPixmap(
+                    self._path_icon("no_approved.png")
+                ).scaledToHeight(32, Qt.SmoothTransformation)
+            )
+            msgBox.setText("Update data before importing calibration")
+            msgBox.setStandardButtons(QMessageBox.Ok)
+            msgBox.exec()
 
-        self.compute_depth_2D()
-        self.compute_ks()
-        self.compute_sv()
-        self.compute_X()
-        self.compute_kt2D_kt3D()
-        self.compute_J_cross_section()
-        self.compute_alpha_s()
-        self.compute_zeta()
+        else:
+
+            self.label_temperature.clear()
+            self.label_temperature.setText("T = " + str(stg.temperature) + " °C")
+
+            self.compute_depth_2D()
+            self.compute_ks()
+            self.compute_sv()
+            self.compute_X()
+            self.compute_kt2D_kt3D()
+            self.compute_J_cross_section()
+            self.compute_alpha_s()
+            self.compute_zeta()
 
     def compute_ks(self):
         data_id = self.combobox_acoustic_data_choice.currentIndex()
@@ -2059,11 +2076,11 @@ class SedimentCalibrationTab(QWidget):
 
         stg.sv = [sv_freq1, sv_freq2]
 
-        print(
+        logger.debug(
             f"sv for frequency of {stg.freq[data_id][self.combobox_freq1.currentIndex()]}"
             + f" : {sv_freq1:.8f} /m \n"
         )
-        print(
+        logger.debug(
             f"sv for frequency of {stg.freq[data_id][self.combobox_freq2.currentIndex()]}"
             + f" : {sv_freq2:.8f} /m"
         )
@@ -2086,7 +2103,7 @@ class SedimentCalibrationTab(QWidget):
         stg.X_exponent.clear()
         stg.X_exponent.append(X_exponent)
 
-        print(f"Exponent X = {X_exponent:.2f}\n")
+        logger.debug(f"Exponent X = {X_exponent:.2f}\n")
 
         self.lineEdit_X.setText(str("%.2f" % X_exponent))
 
@@ -2137,6 +2154,7 @@ class SedimentCalibrationTab(QWidget):
         ]
 
         for i in range(self.combobox_acoustic_data_choice.count()):
+
             J_cross_section_freq1 = np.array([])
             J_cross_section_freq2 = np.array([])
 
@@ -2210,8 +2228,8 @@ class SedimentCalibrationTab(QWidget):
 
         stg.alpha_s = [alpha_s_freq1, alpha_s_freq2]
 
-        print(f"\u03B1s for frequency of freq1 : {alpha_s_freq1:.2f} /m \n")
-        print(f"\u03B1s for frequency of freq2 : {alpha_s_freq2:.2f} /m")
+        logger.debug(f"\u03B1s for frequency of freq1 : {alpha_s_freq1:.2f} /m \n")
+        logger.debug(f"\u03B1s for frequency of freq2 : {alpha_s_freq2:.2f} /m")
 
         self.lineEdit_alphas_freq1.clear()
         self.lineEdit_alphas_freq1.setText(str("%.5f" % alpha_s_freq1))
@@ -2220,25 +2238,19 @@ class SedimentCalibrationTab(QWidget):
         self.lineEdit_alphas_freq2.setText(str("%.5f" % alpha_s_freq2))
 
         if (alpha_s_freq1 < 0) or (alpha_s_freq2 < 0):
+
             msgBox = QMessageBox()
             msgBox.setWindowTitle("Alpha computation error")
-            msgBox.setIconPixmap(
-                QPixmap(
-                    self._path_icon("no_approved.png")
-                ).scaledToHeight(32, Qt.SmoothTransformation)
-            )
+            msgBox.setIconPixmap(QPixmap(self._path_icon("no_approved.png")).scaledToHeight(32, Qt.SmoothTransformation))
             msgBox.setText("Sediment sound attenuation is negative !")
             msgBox.setStandardButtons(QMessageBox.Ok)
             msgBox.exec()
 
         else:
+
             msgBox = QMessageBox()
             msgBox.setWindowTitle("Alpha computation validation")
-            msgBox.setIconPixmap(
-                QPixmap(
-                    self._path_icon("approved.png")
-                ).scaledToHeight(32, Qt.SmoothTransformation)
-            )
+            msgBox.setIconPixmap(QPixmap(self._path_icon("approved.png")).scaledToHeight(32, Qt.SmoothTransformation))
             msgBox.setText("Sediment sound attenuation is positive.")
             msgBox.setStandardButtons(QMessageBox.Ok)
             msgBox.exec()
@@ -2280,8 +2292,8 @@ class SedimentCalibrationTab(QWidget):
 
             stg.zeta = [zeta_freq1, zeta_freq2]
 
-            print(f"\u03B6 for frequency of freq1 : {zeta_freq1:.3f} /m \n")
-            print(f"\u03B6 for frequency of freq2 : {zeta_freq2:.3f} /m")
+            logger.debug(f"\u03B6 for frequency of freq1 : {zeta_freq1:.3f} /m \n")
+            logger.debug(f"\u03B6 for frequency of freq2 : {zeta_freq2:.3f} /m")
 
             self.lineEdit_zeta_freq1.clear()
             self.lineEdit_zeta_freq1.setText(str("%.5f" % zeta_freq1))
@@ -2739,3 +2751,4 @@ class SedimentCalibrationTab(QWidget):
             self.lineEdit_slider_FCB.setText(
                 str(stg.time[self.combobox_acoustic_data_choice.currentIndex()][
                         self.combobox_frequency_FCB.currentIndex(), self.slider_FCB.value()-1]))
+

View/signal_processing_tab.py

@@ -447,8 +447,8 @@ class SignalProcessingTab(QWidget):
         # --------------------------------------------------------------------------------------------------------------
 
         self.pushbutton_update.clicked.connect(self.update_SignalPreprocessingTab)
-        self.pushbutton_update.clicked.connect(self.compute_average_profile_tail)
-        self.pushbutton_update.clicked.connect(self.plot_averaged_profile_tail)
+        # self.pushbutton_update.clicked.connect(self.compute_average_profile_tail)
+        # self.pushbutton_update.clicked.connect(self.plot_averaged_profile_tail)
 
         self.combobox_acoustic_data_choice.currentIndexChanged.connect(self.combobox_acoustic_data_choice_change_index)
 
@@ -501,26 +501,39 @@ class SignalProcessingTab(QWidget):
                 - the user remove a file (in the list widget) in the first tab (Acoustic data), so that the combobox
                     of data to be processed is updated,
                 - the user change the limits of one or all the records in the first tab (Acoustic data) """
+        if len(stg.filename_BS_raw_data) == 0:
 
-        self.combobox_acoustic_data_choice.clear()
-        self.combobox_acoustic_data_choice.addItems(stg.filename_BS_raw_data)
+            msgBox = QMessageBox()
+            msgBox.setWindowTitle("Compute noise from profile tail error")
+            msgBox.setIcon(QMessageBox.Warning)
+            msgBox.setText("Download acoustic data in previous tab before updating data")
+            msgBox.setStandardButtons(QMessageBox.Ok)
+            msgBox.exec()
 
-        if stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 0:
+        else:
 
-            self.groupbox_download_noise_file.setChecked(True)
-            self.groupbox_compute_noise_from_profile_tail.setChecked(False)
-            self.groupbox_download_noise_file_toggle()
+            self.combobox_acoustic_data_choice.clear()
+            self.combobox_acoustic_data_choice.addItems(stg.filename_BS_raw_data)
 
-        elif stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 1:
+            if stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 0:
 
-            self.groupbox_download_noise_file.setChecked(False)
-            self.groupbox_compute_noise_from_profile_tail.setChecked(True)
-            self.groupbox_option_profile_tail_toggle()
+                self.groupbox_download_noise_file.setChecked(True)
+                self.groupbox_compute_noise_from_profile_tail.setChecked(False)
+                self.groupbox_download_noise_file_toggle()
 
-        self.combobox_freq_noise_from_profile_tail.clear()
-        self.combobox_freq_noise_from_profile_tail.addItems(stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()])
+            elif stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 1:
 
-        self.combobox_acoustic_data_choice.currentIndexChanged.connect(self.combobox_acoustic_data_choice_change_index)
+                self.groupbox_download_noise_file.setChecked(False)
+                self.groupbox_compute_noise_from_profile_tail.setChecked(True)
+                self.groupbox_option_profile_tail_toggle()
+
+            self.combobox_freq_noise_from_profile_tail.clear()
+            self.combobox_freq_noise_from_profile_tail.addItems(stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()])
+
+            self.combobox_acoustic_data_choice.currentIndexChanged.connect(self.combobox_acoustic_data_choice_change_index)
+
+            self.compute_average_profile_tail()
+            self.plot_averaged_profile_tail()
 
     def activate_list_of_pre_processed_data(self):
         for i in range(self.combobox_acoustic_data_choice.count()):
@@ -654,45 +667,65 @@ class SignalProcessingTab(QWidget):
 
         # --- Plot averaged signal ---
 
-        if stg.BS_mean[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+        if len(stg.filename_BS_raw_data) == 0:
 
-            self.verticalLayout_groupbox_plot_profile_tail.removeWidget(self.canvas_profile_tail)
+            msgBox = QMessageBox()
+            msgBox.setWindowTitle("Compute noise from profile tail error")
+            msgBox.setIcon(QMessageBox.Warning)
+            msgBox.setText("Download acoustic data in previous tab before computing noise from profile tail")
+            msgBox.setStandardButtons(QMessageBox.Ok)
+            msgBox.exec()
 
-            self.fig_profile_tail, self.axis_profile_tail = plt.subplots(nrows=1, ncols=1, layout='constrained')
-            self.canvas_profile_tail = FigureCanvas(self.fig_profile_tail)
+        elif self.combobox_acoustic_data_choice.count() == 0:
 
-            self.verticalLayout_groupbox_plot_profile_tail.addWidget(self.canvas_profile_tail)
+            msgBox = QMessageBox()
+            msgBox.setWindowTitle("Compute noise from profile tail error")
+            msgBox.setIcon(QMessageBox.Warning)
+            msgBox.setText("Refresh acoustic data before computing noise from profile tail")
+            msgBox.setStandardButtons(QMessageBox.Ok)
+            msgBox.exec()
 
-            self.axis_profile_tail.plot(
-                    -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq_noise_from_profile_tail.currentIndex()],
-                    stg.BS_mean[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq_noise_from_profile_tail.currentIndex()],
-                    color="blue", linewidth=1)
-            self.axis_profile_tail.plot(
-                    -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
-                        self.combobox_freq_noise_from_profile_tail.currentIndex()],
-                    float(self.lineEdit_profile_tail_value.text().replace(",", ".")) *
-                        np.ones(stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
-                            self.combobox_freq_noise_from_profile_tail.currentIndex()].shape[0]),
-                    linestyle='dashed', linewidth=2, color='red')
+        else:
 
-            self.axis_profile_tail.set_yscale('log')
-            self.axis_profile_tail.tick_params(axis='both', labelsize=8)
-            self.axis_profile_tail.text(.98, .03, "Depth (m)",
-                                        fontsize=8, fontweight='bold', fontname="Ubuntu", c="black", alpha=0.9,
-                                        horizontalalignment='right', verticalalignment='bottom', rotation='horizontal',
-                                        transform=self.axis_profile_tail.transAxes)
-            self.axis_profile_tail.text(.1, .45, "BS signal (v)",
-                                        fontsize=8, fontweight='bold', fontname="Ubuntu", c="black", alpha=0.9,
-                                        horizontalalignment='right', verticalalignment='bottom', rotation='vertical',
-                                        transform=self.axis_profile_tail.transAxes)
-            self.axis_profile_tail.text(.98, .85,
-                                        stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()][
-                                            self.combobox_freq_noise_from_profile_tail.currentIndex()],
-                                        fontsize=10, fontweight='bold', fontname="Ubuntu", c="black", alpha=0.5,
-                                        horizontalalignment='right', verticalalignment='bottom',
-                                        transform=self.axis_profile_tail.transAxes)
+            if stg.BS_mean[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
 
-            self.fig_profile_tail.canvas.draw_idle()
+                self.verticalLayout_groupbox_plot_profile_tail.removeWidget(self.canvas_profile_tail)
+
+                self.fig_profile_tail, self.axis_profile_tail = plt.subplots(nrows=1, ncols=1, layout='constrained')
+                self.canvas_profile_tail = FigureCanvas(self.fig_profile_tail)
+
+                self.verticalLayout_groupbox_plot_profile_tail.addWidget(self.canvas_profile_tail)
+
+                self.axis_profile_tail.plot(
+                        -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq_noise_from_profile_tail.currentIndex()],
+                        stg.BS_mean[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq_noise_from_profile_tail.currentIndex()],
+                        color="blue", linewidth=1)
+                self.axis_profile_tail.plot(
+                        -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                            self.combobox_freq_noise_from_profile_tail.currentIndex()],
+                        float(self.lineEdit_profile_tail_value.text().replace(",", ".")) *
+                            np.ones(stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                                self.combobox_freq_noise_from_profile_tail.currentIndex()].shape[0]),
+                        linestyle='dashed', linewidth=2, color='red')
+
+                self.axis_profile_tail.set_yscale('log')
+                self.axis_profile_tail.tick_params(axis='both', labelsize=8)
+                self.axis_profile_tail.text(.98, .03, "Depth (m)",
+                                            fontsize=8, fontweight='bold', fontname="Ubuntu", c="black", alpha=0.9,
+                                            horizontalalignment='right', verticalalignment='bottom', rotation='horizontal',
+                                            transform=self.axis_profile_tail.transAxes)
+                self.axis_profile_tail.text(.1, .45, "BS signal (v)",
+                                            fontsize=8, fontweight='bold', fontname="Ubuntu", c="black", alpha=0.9,
+                                            horizontalalignment='right', verticalalignment='bottom', rotation='vertical',
+                                            transform=self.axis_profile_tail.transAxes)
+                self.axis_profile_tail.text(.98, .85,
+                                            stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()][
+                                                self.combobox_freq_noise_from_profile_tail.currentIndex()],
+                                            fontsize=10, fontweight='bold', fontname="Ubuntu", c="black", alpha=0.5,
+                                            horizontalalignment='right', verticalalignment='bottom',
+                                            transform=self.axis_profile_tail.transAxes)
+
+                self.fig_profile_tail.canvas.draw_idle()
 
     # ------------------------------------------------------
 
@@ -722,82 +755,87 @@ class SignalProcessingTab(QWidget):
 
     def clear_noise_data(self):
 
-        stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
-        stg.BS_noise_averaged_data[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
-        stg.SNR_raw_data[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
-        stg.SNR_cross_section[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
-        stg.SNR_stream_bed[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
-        stg.time_noise[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
-        stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] = 0
-        stg.SNR_filter_value[self.combobox_acoustic_data_choice.currentIndex()] = 0
+        if len(stg.filename_BS_raw_data) == 0:
 
-        stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
-        stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
+            pass
 
-        stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
-        stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
+        else:
 
-        stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
-        stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
+            stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
+            stg.BS_noise_averaged_data[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
+            stg.SNR_raw_data[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
+            stg.SNR_cross_section[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
+            stg.SNR_stream_bed[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
+            stg.time_noise[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
+            stg.SNR_filter_value[self.combobox_acoustic_data_choice.currentIndex()] = 0
 
-        if stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 0:
-            self.lineEdit_noise_file.clear()
+            stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
+            stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
 
-        elif stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 1:
-            self.lineEdit_val1.clear()
-            self.lineEdit_val1.setText("0.00")
+            stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
+            stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
 
-            self.lineEdit_val2.clear()
-            self.lineEdit_val2.setText("0.00")
+            stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
+            stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
+            print("stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()]", stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()])
+            if stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 0:
+                self.lineEdit_noise_file.clear()
 
-            self.lineEdit_profile_tail_value.clear()
-            self.lineEdit_profile_tail_value.setText("0.0000")
+            elif stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 1:
+                self.lineEdit_val1.clear()
+                self.lineEdit_val1.setText("0.00")
 
-            self.verticalLayout_groupbox_plot_profile_tail.removeWidget(self.canvas_profile_tail)
-            self.canvas_profile_tail = FigureCanvas()
-            self.verticalLayout_groupbox_plot_profile_tail.addWidget(self.canvas_profile_tail)
+                self.lineEdit_val2.clear()
+                self.lineEdit_val2.setText("0.00")
 
-        self.lineEdit_SNR_criterion.setText("0.00")
-        self.lineEdit_horizontal_average.setText("0.00")
+                self.lineEdit_profile_tail_value.clear()
+                self.lineEdit_profile_tail_value.setText("0.0000")
 
-        # --- Clear SNR plot ---
-        self.verticalLayout_groupbox_plot_SNR.removeWidget(self.toolbar_SNR)
-        self.verticalLayout_groupbox_plot_SNR.removeWidget(self.scroll_SNR)
+                self.verticalLayout_groupbox_plot_profile_tail.removeWidget(self.canvas_profile_tail)
+                self.canvas_profile_tail = FigureCanvas()
+                self.verticalLayout_groupbox_plot_profile_tail.addWidget(self.canvas_profile_tail)
 
-        self.canvas_SNR = FigureCanvas()
-        self.toolbar_SNR = NavigationToolBar(self.canvas_SNR, self)
-        self.scroll_SNR.setWidget(self.canvas_SNR)
+            self.lineEdit_SNR_criterion.setText("0.00")
+            self.lineEdit_horizontal_average.setText("0.00")
 
-        self.verticalLayout_groupbox_plot_SNR.addWidget(self.toolbar_SNR)
-        self.verticalLayout_groupbox_plot_SNR.addWidget(self.scroll_SNR)
+            # --- Clear SNR plot ---
+            self.verticalLayout_groupbox_plot_SNR.removeWidget(self.toolbar_SNR)
+            self.verticalLayout_groupbox_plot_SNR.removeWidget(self.scroll_SNR)
 
-        # --- Clear BS plot ---
-        self.verticalLayout_groupbox_plot_pre_processed_data_2D_field.removeWidget(self.toolbar_BS)
-        self.verticalLayout_groupbox_plot_pre_processed_data_2D_field.removeWidget(self.scroll_BS)
+            self.canvas_SNR = FigureCanvas()
+            self.toolbar_SNR = NavigationToolBar(self.canvas_SNR, self)
+            self.scroll_SNR.setWidget(self.canvas_SNR)
 
-        self.canvas_BS = FigureCanvas()
-        self.toolbar_BS = NavigationToolBar(self.canvas_BS, self)
-        self.scroll_BS.setWidget(self.canvas_BS)
+            self.verticalLayout_groupbox_plot_SNR.addWidget(self.toolbar_SNR)
+            self.verticalLayout_groupbox_plot_SNR.addWidget(self.scroll_SNR)
 
-        self.verticalLayout_groupbox_plot_pre_processed_data_2D_field.addWidget(self.toolbar_BS)
-        self.verticalLayout_groupbox_plot_pre_processed_data_2D_field.addWidget(self.scroll_BS)
+            # --- Clear BS plot ---
+            self.verticalLayout_groupbox_plot_pre_processed_data_2D_field.removeWidget(self.toolbar_BS)
+            self.verticalLayout_groupbox_plot_pre_processed_data_2D_field.removeWidget(self.scroll_BS)
 
-        self.combobox_frequency_profile.clear()
+            self.canvas_BS = FigureCanvas()
+            self.toolbar_BS = NavigationToolBar(self.canvas_BS, self)
+            self.scroll_BS.setWidget(self.canvas_BS)
 
-        self.verticalLayout_groupbox_plot_profile.removeWidget(self.toolbar_profile)
-        self.verticalLayout_groupbox_plot_profile.removeWidget(self.canvas_profile)
+            self.verticalLayout_groupbox_plot_pre_processed_data_2D_field.addWidget(self.toolbar_BS)
+            self.verticalLayout_groupbox_plot_pre_processed_data_2D_field.addWidget(self.scroll_BS)
 
-        self.canvas_profile = FigureCanvas()
-        self.toolbar_profile = NavigationToolBar(self.canvas_profile, self)
+            self.combobox_frequency_profile.clear()
 
-        self.verticalLayout_groupbox_plot_profile.addWidget(self.toolbar_profile)
-        self.verticalLayout_groupbox_plot_profile.addWidget(self.canvas_profile)
+            self.verticalLayout_groupbox_plot_profile.removeWidget(self.toolbar_profile)
+            self.verticalLayout_groupbox_plot_profile.removeWidget(self.canvas_profile)
 
-        self.slider.setValue(1)
-        self.slider.setMaximum(10)
+            self.canvas_profile = FigureCanvas()
+            self.toolbar_profile = NavigationToolBar(self.canvas_profile, self)
 
-        self.slider.setValue(0)
-        self.slider.setMaximum(10)
+            self.verticalLayout_groupbox_plot_profile.addWidget(self.toolbar_profile)
+            self.verticalLayout_groupbox_plot_profile.addWidget(self.canvas_profile)
+
+            self.slider.setValue(1)
+            self.slider.setMaximum(10)
+
+            self.slider.setValue(0)
+            self.slider.setMaximum(10)
 
     def open_dialog_box(self):
 
@@ -1221,11 +1259,19 @@ class SignalProcessingTab(QWidget):
 
     def remove_point_with_snr_filter(self):
 
-        if len(stg.BS_noise_raw_data) == 0:
+        if len(stg.filename_BS_raw_data) == 0:
+            msgBox = QMessageBox()
+            msgBox.setWindowTitle("Compute noise from profile tail error")
+            msgBox.setIcon(QMessageBox.Warning)
+            msgBox.setText("Download acoustic data in previous tab before applying SNR filter")
+            msgBox.setStandardButtons(QMessageBox.Ok)
+            msgBox.exec()
+
+        elif len(stg.BS_noise_raw_data) == 0:
             msgBox = QMessageBox()
             msgBox.setWindowTitle("SNR filter Error")
             msgBox.setIcon(QMessageBox.Warning)
-            msgBox.setText("Load Noise data from acoustic data tab before using SNR filter")
+            msgBox.setText("Define noise data (file or profile tail) before using SNR filter")
             msgBox.setStandardButtons(QMessageBox.Ok)
             msgBox.exec()
 
@@ -1504,105 +1550,123 @@ class SignalProcessingTab(QWidget):
 
     def compute_averaged_BS_data(self):
 
-        kernel_avg = np.ones(2 * int(float(self.lineEdit_horizontal_average.text().replace(",", "."))) + 1)
-        print(kernel_avg)
+        if len(stg.filename_BS_raw_data) == 0:
+            msgBox = QMessageBox()
+            msgBox.setWindowTitle("Compute noise from profile tail error")
+            msgBox.setIcon(QMessageBox.Warning)
+            msgBox.setText("Download acoustic data in previous tab before applying SNR filter")
+            msgBox.setStandardButtons(QMessageBox.Ok)
+            msgBox.exec()
 
-        stg.Nb_cells_to_average_BS_signal[self.combobox_acoustic_data_choice.currentIndex()] = (
-            float(self.lineEdit_horizontal_average.text().replace(",", ".")))
-
-        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,):
-
-                x_time = stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
-                y_depth = stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
-
-            elif stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
-
-                x_time = stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
-                y_depth = stg.depth[self.combobox_acoustic_data_choice.currentIndex()]
+        elif len(stg.BS_noise_raw_data) == 0:
+            msgBox = QMessageBox()
+            msgBox.setWindowTitle("SNR filter Error")
+            msgBox.setIcon(QMessageBox.Warning)
+            msgBox.setText("Define noise data (file or profile tail) before using SNR filter")
+            msgBox.setStandardButtons(QMessageBox.Ok)
+            msgBox.exec()
 
         else:
 
-            if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+            kernel_avg = np.ones(2 * int(float(self.lineEdit_horizontal_average.text().replace(",", "."))) + 1)
+            print(kernel_avg)
 
-                x_time = stg.time[self.combobox_acoustic_data_choice.currentIndex()]
-                y_depth = stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
+            stg.Nb_cells_to_average_BS_signal[self.combobox_acoustic_data_choice.currentIndex()] = (
+                float(self.lineEdit_horizontal_average.text().replace(",", ".")))
 
-            elif stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+            if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
 
-                x_time = stg.time[self.combobox_acoustic_data_choice.currentIndex()]
-                y_depth = stg.depth[self.combobox_acoustic_data_choice.currentIndex()]
+                if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
 
-        if stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+                    x_time = stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
+                    y_depth = stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
 
-            stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
-                stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
+                elif stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
 
-            for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
-                for i in range(y_depth.shape[1]):
+                    x_time = stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
+                    y_depth = stg.depth[self.combobox_acoustic_data_choice.currentIndex()]
 
-                    stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
-                        convolve(stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
-                                 kernel_avg))
+            else:
 
-        elif stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+                if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
 
-            stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
-                stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
+                    x_time = stg.time[self.combobox_acoustic_data_choice.currentIndex()]
+                    y_depth = stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
 
-            for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
-                for i in range(y_depth.shape[1]):
+                elif stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
 
-                    stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
-                        convolve(stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
-                                 kernel_avg))
+                    x_time = stg.time[self.combobox_acoustic_data_choice.currentIndex()]
+                    y_depth = stg.depth[self.combobox_acoustic_data_choice.currentIndex()]
 
-        elif stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+            if stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
 
-            stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
-                stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
+                stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
+                    stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
 
-            for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
-                for i in range(y_depth.shape[1]):
+                for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
+                    for i in range(y_depth.shape[1]):
 
-                    stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
-                        convolve(stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
-                                 kernel_avg))
+                        stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
+                            convolve(stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
+                                     kernel_avg))
 
-        elif stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+            elif stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
 
-            stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
-                stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()]))
+                stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
+                    stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
 
-            for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
-                for i in range(y_depth.shape[1]):
-                    stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
-                        convolve(stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][f, i, :], kernel_avg))
+                for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
+                    for i in range(y_depth.shape[1]):
 
-        elif stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+                        stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
+                            convolve(stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
+                                     kernel_avg))
 
-            stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
-                stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()]))
+            elif stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
 
-            for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
-                for i in range(y_depth.shape[1]):
-                    stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
-                        convolve(stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
-                                 kernel_avg))
+                stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
+                    stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
 
-        elif stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+                for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
+                    for i in range(y_depth.shape[1]):
 
-            stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
-                stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()]))
+                        stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
+                            convolve(stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
+                                     kernel_avg))
 
-            for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
-                for i in range(y_depth.shape[1]):
-                    stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
-                        convolve(stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()][f, i, :], kernel_avg))
+            elif stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
 
-        self.plot_pre_processed_BS_signal()
-        self.update_plot_pre_processed_profile()
+                stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
+                    stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()]))
+
+                for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
+                    for i in range(y_depth.shape[1]):
+                        stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
+                            convolve(stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][f, i, :], kernel_avg))
+
+            elif stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+
+                stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
+                    stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()]))
+
+                for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
+                    for i in range(y_depth.shape[1]):
+                        stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
+                            convolve(stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
+                                     kernel_avg))
+
+            elif stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+
+                stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
+                    stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()]))
+
+                for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
+                    for i in range(y_depth.shape[1]):
+                        stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
+                            convolve(stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()][f, i, :], kernel_avg))
+
+            self.plot_pre_processed_BS_signal()
+            self.update_plot_pre_processed_profile()
 
     def plot_pre_processed_profile(self):