Model/create_table_for_save_as.py

@@ -389,6 +389,10 @@ class CreateTableForSaveAs:
                 )
             )
 
+            logger.debug(f"stg.ind_bottom: {stg.ind_bottom[i]}")
+            logger.debug(np.array([stg.ind_bottom[i]]),
+                         np.array(stg.ind_bottom[i]).shape)
+
         # Commit the transaction after executing INSERT.
         cnx.commit()
 
@@ -442,7 +446,7 @@ class CreateTableForSaveAs:
 
         cur.execute(self.create_SedimentsFile)
 
-        if stg.path_fine != "" and stg.path_sand != "":
+        if stg.path_fine != "" and path_sand != "":
             cur.execute(
                 """
                 INSERT into SedimentsFile(

README.md

@@ -11,13 +11,17 @@ It is divided in six tabs:
 - Calibration : calibration parameter are computed
 - Inversion : inversion method is calculated to provide fine and sand sediments fields
 
-## Installation
+## Software documentation
+
+### Installation
 
 Acoused is developped for Linux and Windows on Python version 3.8 or
 greater. By default, Acoused is developped with Pypi package
 dependencies, but is also possible to use Guix package manager to run
 Acoused.
 
+## Development documentation
+
 ### **TODO** Windows
 
 ### Linux
@@ -45,6 +49,27 @@ script `guix.sh` to run the program.
   guix shell sqlitebrowser -- ./guix.sh
 ```
 
+## License
+
+AcouSed 
+Copyright (C) 2024 - INRAE 
+
+This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. 
+
+This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details. 
+
+You should have received a copy of the GNU General Public License along with this program.  If not, see <https://www.gnu.org/licenses/>.
+
+## Authors & Contacts
+
+- Brahim MOUDJED  2022-2025 ([INRAE](https://www.inrae.fr/))
+- Pierre-Antoine ROUBY  2025 ([TECC](https://parouby.fr))
+
+If you have any questions or suggestions, please contact us to celine.berni@inrae.fr and/or jerome.lecoz@inrae.fr.
+
+## Acknowledgment (Funding)
+This study was conducted within the [Rhône Sediment Observatory](https://observatoire-sediments-rhone.fr/) (OSR), a multi-partner research program funded through the Plan Rhône by the European Regional Development Fund (ERDF), Agence de l’Eau RMC, CNR, EDF and three regional councils (Auvergne-Rhône-Alpes, PACA and Occitanie). It was also support by CNR. 
+
 ## Support files & References 
 
 - [ ] [Acoustic inversion method diagram](https://forgemia.inra.fr/theophile.terraz/acoused/-/blob/main/Acoustic_Inversion_theory.pdf?ref_type=heads) 
@@ -55,24 +80,3 @@ script `guix.sh` to run the program.
 - [ ] [Vergne A., Le Coz J., Berni C., & Pierrefeu G. (2020), Water Resources Research, 56(2)](https://doi.org/10.1029/2019WR024877)
 - [ ] [Vergne A., Berni C., Le Coz J., & Tencé F., (2021), Water Resources Research, 57(9)](https://doi.org/10.1029/2021WR029589)
 
-## Authors & Contacts
-
-- Brahim MOUDJED  2022-2025 ([INRAE](https://www.inrae.fr/))
-- Pierre-Antoine ROUBY  2025 ([TECC](https://parouby.fr))
-
-If you have any questions or suggestions, please contact us to celine.berni@inrae.fr and/or jerome.lecoz@inrae.fr.
-
-## Acknowledgment (Funding)
-
-This study was conducted within the [Rhône Sediment Observatory](https://observatoire-sediments-rhone.fr/) (OSR), a multi-partner research program funded through the Plan Rhône by the European Regional Development Fund (ERDF), Agence de l’Eau RMC, CNR, EDF and three regional councils (Auvergne-Rhône-Alpes, PACA and Occitanie). It was also support by CNR.
-
-## License
-
-AcouSed
-Copyright (C) 2024-2025 - INRAE
-
-This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
-
-This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License along with this program.  If not, see <https://www.gnu.org/licenses/>.

View/acoustic_inversion_tab.py

@@ -20,11 +20,16 @@
 
 # -*- coding: utf-8 -*-
 
-import os
-import numpy as np
-import pandas as pd
 
-from copy import deepcopy
+import pandas as pd
+from PyQt5.QtWidgets import (QWidget, QVBoxLayout, QHBoxLayout, QGroupBox, QComboBox,
+                             QLabel, QPushButton, QSpacerItem,
+                             QSlider, QLineEdit, QMessageBox, QFileDialog)
+
+from PyQt5.QtCore import QCoreApplication, Qt
+from PyQt5.QtGui import QIcon, QPixmap
+
+import numpy as np
 
 import matplotlib.pyplot as plt
 
@@ -32,14 +37,9 @@ 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 (
+from os import chdir
-    QWidget, QVBoxLayout, QHBoxLayout, QGroupBox, QComboBox,
-    QLabel, QPushButton, QSpacerItem, QSlider, QLineEdit,
-    QMessageBox, QFileDialog
-)
 
-from PyQt5.QtCore import QCoreApplication, Qt
+from copy import deepcopy
-from PyQt5.QtGui import QIcon, QPixmap
 
 from View.checkable_combobox import CheckableComboBox
 
@@ -1671,81 +1671,96 @@ class AcousticInversionTab(QWidget):
                 self.figure_measured_vs_inverted_sand.canvas.draw_idle()
 
     def save_result_in_excel_file(self):
+
         if self.combobox_acoustic_data_choice.count() > 0:
+
             name = QFileDialog.getSaveFileName(
-                caption="Save As - Inversion results",
+                caption="Save As - Inversion results", directory="", filter="Excel Files (*.xlsx)",
-                directory="",
+                options=QFileDialog.DontUseNativeDialog)
-                filter="Excel Files (*.xlsx)",
-                options=QFileDialog.DontUseNativeDialog
-            )
 
             if name[0]:
-                dirname = os.path.dirname(name[0])
+                dirname = "/".join(name[0].split("/")[:-1]) + "/"
-                filename = os.path.basename(name[0])
+                filename = name[0].split("/")[-1]
-                os.chdir(dirname)
+                chdir(dirname)
-
-            results = []
 
             for k in range(self.combobox_acoustic_data_choice.count()):
+
                 if stg.time_cross_section[k].shape != (0,):
-                    time_data = stg.time_cross_section
-                else:
-                    time_data = stg.time
 
                     if stg.depth_cross_section[k].shape != (0,):
-                    depth_data = stg.depth_cross_section
-                else:
-                    depth_data = stg.depth
 
+                        t = np.repeat(stg.time_cross_section[k][stg.frequency_for_inversion[1]],
+                                      stg.depth_cross_section[k].shape[1])
 
-                t = np.repeat(
+                        r = np.zeros((stg.depth_cross_section[k].shape[1] *stg.time_cross_section[k].shape[1],1))
-                    time_data[k][stg.frequency_for_inversion[1]],
-                    depth_data[k].shape[1]
-                )
 
-                r = np.zeros(
+                        for i in range(stg.time_cross_section[k].shape[1]):
-                    depth_data[k].shape[1] * time_data[k].shape[1]
+                            for j in range(stg.depth_cross_section[k].shape[1]):
-                )
+                                r[i * stg.depth_cross_section[k].shape[1] + j] = (
-
+                                    stg.depth_cross_section[k][int(stg.frequency_for_inversion[1]), j])
-                for i in range(time_data[k].shape[1]):
-                    for j in range(depth_data[k].shape[1]):
-                        r_id = i * depth_data[k].shape[1] + j
-
-                        r[r_id] = (
-                            depth_data[k][
-                                int(stg.frequency_for_inversion[1]), j
-                            ]
-                        )
 
                         if stg.SSC_fine[k].shape == (0,):
                             stg.SSC_fine[k] = np.zeros(r.shape[0])
                         if stg.SSC_sand[k].shape == (0,):
                             stg.SSC_sand[k] = np.zeros(r.shape[0])
 
-                results.append(
+                    else:
-                    pd.DataFrame(
-                        {
-                            'Time (sec)': list(t),
-                            'Depth (m)': list(r),
-                            'SSC_fine (g/L)': list(
-                                stg.SSC_fine[k].reshape(t.shape[0])
-                            ),
-                            'SSC_sand (g/L)': list(
-                                stg.SSC_sand[k].reshape(t.shape[0])
-                            ),
-                        }
-                    )
-                )
 
-            if os.path.splitext(filename)[1] != ".xlsx":
+                        t = np.repeat(stg.time_cross_section[k][stg.frequency_for_inversion[1]], stg.depth[k].shape[1])
-                filename += ".xlsx"
 
-            with pd.ExcelWriter(
+                        r = np.zeros((stg.depth[k].shape[1] * stg.time_cross_section[k].shape[1], 1))
-                    os.path.join(dirname, filename)
+                        for i in range(stg.time_cross_section[k].shape[1]):
-            ) as writer:
+                            for j in range(stg.depth[k].shape[1]):
+                                r[i * stg.depth[k].shape[1] + j] = (
+                                    stg.depth[k][int(stg.frequency_for_inversion[1]), j])
+
+                        if stg.SSC_fine[k].shape == (0,):
+                            stg.SSC_fine[k] = np.zeros(r.shape[0])
+                        if stg.SSC_sand[k].shape == (0,):
+                            stg.SSC_sand[k] = np.zeros(r.shape[0])
+
+                else:
+
+                    if stg.depth_cross_section[k].shape != (0,):
+
+                        t = np.repeat(stg.time[k][stg.frequency_for_inversion[1]], stg.depth_cross_section[k].shape[1])
+
+                        r = np.zeros((stg.depth_cross_section[k].shape[1] * stg.time[k].shape[1], 1))
+                        for i in range(stg.time[k].shape[1]):
+                            for j in range(stg.depth_cross_section[k].shape[1]):
+                                r[i * stg.depth_cross_section[k].shape[1] + j] = (
+                                    stg.depth_cross_section[k][int(stg.frequency_for_inversion[1]), j])
+
+                        if stg.SSC_fine[k].shape == (0,):
+                            stg.SSC_fine[k] = np.zeros(r.shape[0])
+                        if stg.SSC_sand[k].shape == (0,):
+                            stg.SSC_sand[k] = np.zeros(r.shape[0])
+
+                    else:
+
+                        t = np.repeat(stg.time[k][stg.frequency_for_inversion[1]], stg.depth[k].shape[1])
+
+                        r = np.zeros(stg.depth[k].shape[1] * stg.time[k].shape[1])
+
+                        for i in range(stg.time[k].shape[1]):
+                            for j in range(stg.depth[k].shape[1]):
+                                r[i * stg.depth[k].shape[1] + j] = (
+                                    stg.depth[k][int(stg.frequency_for_inversion[1]), j])
+
+                        if stg.SSC_fine[k].shape == (0,):
+                            stg.SSC_fine[k] = np.zeros(r.shape[0])
+                        if stg.SSC_sand[k].shape == (0,):
+                            stg.SSC_sand[k] = np.zeros(r.shape[0])
+
+                exec("result_" + str(k)  + "= pd.DataFrame({'Time (sec)': t," +
+                                                           "'Depth (m)': r," +
+                                                           "'SSC_fine (g/L)': stg.SSC_fine[" + str(k) + "].reshape(t.shape[0])," +
+                                                           "'SSC_sand (g/L)': stg.SSC_sand[" + str(k) + "].reshape(t.shape[0])})")
+
+
+
+            with pd.ExcelWriter(dirname + filename + '.xlsx') as writer:
                 for k in range(self.combobox_acoustic_data_choice.count()):
-                    results[k].to_excel(
+                    eval("result_" + str(k) + ".to_excel(writer, index=False, " +
-                        writer, index=False,
+                        "engine='xlsxwriter', na_rep='NA', " +
-                        engine='xlsxwriter', na_rep='NA',
+                        "sheet_name=stg.data_preprocessed[" + str(k) + "])")
-                        sheet_name=stg.data_preprocessed[k],
-                    )

View/mainwindow.py

@@ -147,14 +147,12 @@ class Ui_MainWindow(object):
         icon6.addPixmap(QtGui.QPixmap("icons/en.png"), QtGui.QIcon.Normal, QtGui.QIcon.Off)
         self.actionEnglish.setIcon(icon6)
         self.actionEnglish.setObjectName("actionEnglish")
-        self.actionEnglish.setEnabled(False)
 
         self.actionFrench = QtWidgets.QAction(self.mainwindow)
         icon7 = QtGui.QIcon()
         icon7.addPixmap(QtGui.QPixmap("icons/fr.png"), QtGui.QIcon.Normal, QtGui.QIcon.Off)
         self.actionFrench.setIcon(icon7)
         self.actionFrench.setObjectName("actionFrench")
-        self.actionFrench.setEnabled(False)
 
         self.action_ABSCalibrationConstant = QtWidgets.QAction(self.mainwindow)
         self.action_ABSCalibrationConstant.setText("ABS constant calibration kt")
@@ -270,10 +268,7 @@ class Ui_MainWindow(object):
         )
 
     def save(self):
-        if stg.dirname_save_as:
         UpdateTableForSave()
-        else:
-            self.save_as()
 
     def open(self):
         reader = ReadTableForOpen()

View/sediment_calibration_tab.py

@@ -1716,18 +1716,14 @@ 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_calibration_file
+                                                stg.path_BS_raw_data[
-                if stg.path_calibration_file
+                                                    -1] if self.combobox_acoustic_data_choice.count() > 0 else ""][0],
-                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
+        options=QFileDialog.DontUseNativeDialog)
-        )
 
         dir_name = os.path.dirname(filename[0])
         name = os.path.basename(filename[0])
@@ -1740,188 +1736,114 @@ class SedimentCalibrationTab(QWidget):
 
         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()
-        self.label_freq1.setText(
+        self.label_freq1.setText(str(self.combobox_freq1.currentText()))
-            str(self.combobox_freq1.currentText())
-        )
 
     def update_label_freq2_for_calibration(self):
         self.label_freq2.clear()
-        self.label_freq2.setText(
+        self.label_freq2.setText(self.combobox_freq2.currentText())
-            self.combobox_freq2.currentText()
-        )
 
     def update_label_kt_value_for_calibration(self):
-        print("self.combobox_freq1.currentIndex() ",
-              self.combobox_freq1.currentIndex(),
-              self.combobox_freq1.currentText())
-
-        freq_1 = self.combobox_freq1.currentIndex()
-        freq_2 = self.combobox_freq2.currentIndex()
-
         self.label_kt_freq1.clear()
-        if stg.kt_corrected[freq_1] != stg.kt_read[freq_1]:
+        print("self.combobox_freq1.currentIndex() ", self.combobox_freq1.currentIndex(), self.combobox_freq1.currentText())
-            self.label_kt_freq1.setText(
+        if stg.kt_corrected[self.combobox_freq1.currentIndex()] != stg.kt_read[self.combobox_freq1.currentIndex()]:
-                str('%.4f' % stg.kt_corrected[freq_1])
+            self.label_kt_freq1.setText(str('%.4f' % stg.kt_corrected[self.combobox_freq1.currentIndex()]))
-            )
         else:
-            self.label_kt_freq1.setText(
+            self.label_kt_freq1.setText(str('%.4f' % stg.kt_read[self.combobox_freq1.currentIndex()]))
-                str('%.4f' % stg.kt_read[freq_1])
-            )
 
         self.label_kt_freq2.clear()
-        if stg.kt_corrected[freq_2] != stg.kt_read[freq_2]:
+        if stg.kt_corrected[self.combobox_freq2.currentIndex()] != stg.kt_read[self.combobox_freq2.currentIndex()]:
-            self.label_kt_freq2.setText(
+            self.label_kt_freq2.setText(str('%.4f' % stg.kt_corrected[self.combobox_freq2.currentIndex()]))
-                str('%.4f' % stg.kt_corrected[freq_2])
-            )
         else:
-            self.label_kt_freq2.setText(
+            self.label_kt_freq2.setText(str('%.4f' % stg.kt_read[self.combobox_freq2.currentIndex()]))
-                str('%.4f' % stg.kt_read[freq_2])
-            )
 
     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(
+                QPixmap(self._path_icon("no_approved.png")).scaledToHeight(32, Qt.SmoothTransformation))
-                    self._path_icon("no_approved.png")
-                ).scaledToHeight(32, Qt.SmoothTransformation)
-            )
             msgBox.setText("Update data before importing calibration")
             msgBox.setStandardButtons(QMessageBox.Ok)
             msgBox.exec()
 
-        elif 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(stg.path_calibration_file + "/" + stg.filename_calibration_file, header=0, index_col=0)
 
             # --- Fill spinboxes of calibration parameter ---
             self.label_temperature.clear()
-            self.label_temperature.setText(
+            self.label_temperature.setText("T = " + str(stg.temperature) + " °C")
-                "T = " + str(stg.temperature) + " °C"
-            )
 
             self.label_freq1.clear()
             self.label_freq1.setText(data.columns[0])
 
-            data_id = self.combobox_acoustic_data_choice.currentIndex()
+            index_freq1 = np.where(np.asarray(stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()]) ==
-
+                                   data.columns[0])[0][0]
-            index_freq1 = np.where(
-                np.asarray(
-                    stg.freq_text[data_id]
-                ) == data.columns[0]
-            )[0][0]
-
             stg.frequencies_for_calibration.clear()
-            stg.frequencies_for_calibration.append(
+            stg.frequencies_for_calibration.append((stg.freq[self.combobox_acoustic_data_choice.currentIndex()][
-                (
+                                                        index_freq1],
-                    stg.freq[data_id][index_freq1],
+                                                    index_freq1))
-                    index_freq1
-                )
-            )
 
             self.label_freq2.clear()
             self.label_freq2.setText(data.columns[1])
 
-            index_freq2 = np.where(
+            index_freq2 = np.where(np.asarray(stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()]) ==
-                np.asarray(
+                                   data.columns[1])[0][0]
-                    stg.freq_text[data_id]
+            stg.frequencies_for_calibration.append((stg.freq[self.combobox_acoustic_data_choice.currentIndex()][
-                ) == data.columns[1]
+                                                        index_freq2],
-            )[0][0]
+                                                    index_freq2))
-
-            stg.frequencies_for_calibration.append(
-                (
-                    stg.freq[data_id][index_freq2],
-                    index_freq2
-                )
-            )
 
             stg.frequency_for_inversion = tuple()
-            stg.frequency_for_inversion = (
+            stg.frequency_for_inversion = (stg.freq[self.combobox_acoustic_data_choice.currentIndex()][index_freq2],
-                stg.freq[data_id][index_freq2],
+                                           index_freq2)
-                index_freq2
-            )
 
             self.lineEdit_ks_freq1.clear()
-            self.lineEdit_ks_freq1.setText(
+            self.lineEdit_ks_freq1.setText(str("%.5f" % float(data.iloc[0][0])))
-                str("%.5f" % float(data.iloc[0][0]))
-            )
 
             self.lineEdit_ks_freq2.clear()
-            self.lineEdit_ks_freq2.setText(
+            self.lineEdit_ks_freq2.setText(str("%.5f" % float(data.iloc[0][1])))
-                str("%.5f" % float(data.iloc[0][1]))
-            )
 
             stg.ks.clear()
-            stg.ks = [
+            stg.ks = [float(self.lineEdit_ks_freq1.text()), float(self.lineEdit_ks_freq2.text())]
-                float(self.lineEdit_ks_freq1.text()),
-                float(self.lineEdit_ks_freq2.text())
-            ]
 
             self.lineEdit_sv_freq1.clear()
-            self.lineEdit_sv_freq1.setText(
+            self.lineEdit_sv_freq1.setText(str("%.5f" % float(data.iloc[1][0])))
-                str("%.5f" % float(data.iloc[1][0]))
-            )
 
             self.lineEdit_sv_freq2.clear()
-            self.lineEdit_sv_freq2.setText(
+            self.lineEdit_sv_freq2.setText(str("%.5f" % float(data.iloc[1][1])))
-                str("%.5f" % float(data.iloc[1][1]))
-            )
 
             stg.sv.clear()
-            stg.sv = [
+            stg.sv = [float(self.lineEdit_sv_freq1.text()), float(self.lineEdit_sv_freq2.text())]
-                float(self.lineEdit_sv_freq1.text()),
-                float(self.lineEdit_sv_freq2.text())
-            ]
 
             self.lineEdit_X.clear()
-            self.lineEdit_X.setText(
+            self.lineEdit_X.setText(str("%.2f" % float(data.iloc[2][0])))
-                str("%.2f" % float(data.iloc[2][0]))
-            )
 
             stg.X_exponent.clear()
             stg.X_exponent.append(float(self.lineEdit_X.text()))
 
             self.lineEdit_alphas_freq1.clear()
-            self.lineEdit_alphas_freq1.setText(
+            self.lineEdit_alphas_freq1.setText(str("%.5f" % float(data.iloc[3][0])))
-                str("%.5f" % float(data.iloc[3][0]))
-            )
 
             self.lineEdit_alphas_freq2.clear()
-            self.lineEdit_alphas_freq2.setText(
+            self.lineEdit_alphas_freq2.setText(str("%.5f" % float(data.iloc[3][1])))
-                str("%.5f" % float(data.iloc[3][1]))
-            )
 
             stg.alpha_s.clear()
-            stg.alpha_s = [
+            stg.alpha_s = [float(self.lineEdit_alphas_freq1.text()), float(self.lineEdit_alphas_freq2.text())]
-                float(self.lineEdit_alphas_freq1.text()),
-                float(self.lineEdit_alphas_freq2.text())
-            ]
 
             self.lineEdit_zeta_freq1.clear()
-            self.lineEdit_zeta_freq1.setText(
+            self.lineEdit_zeta_freq1.setText(str("%.5f" % float(data.iloc[4][0])))
-                str("%.5f" % float(data.iloc[4][0]))
-            )
 
             self.lineEdit_zeta_freq2.clear()
-            self.lineEdit_zeta_freq2.setText(
+            self.lineEdit_zeta_freq2.setText(str("%.5f" % float(data.iloc[4][1])))
-                str("%.5f" % float(data.iloc[4][1]))
-            )
 
             stg.zeta.clear()
-            stg.zeta = [
+            stg.zeta = [float(self.lineEdit_zeta_freq1.text()), float(self.lineEdit_zeta_freq2.text())]
-                float(self.lineEdit_zeta_freq1.text()),
-                float(self.lineEdit_zeta_freq2.text())
-            ]
 
             self.compute_kt2D_kt3D()
             self.compute_J_cross_section()
@@ -2009,8 +1931,8 @@ class SedimentCalibrationTab(QWidget):
         self.compute_zeta()
 
     def compute_ks(self):
-        data_id = self.combobox_acoustic_data_choice.currentIndex()
 
+        # --- Compute ks ---
         psd_number_of_particles = (
             self.inv_hc.compute_particle_size_distribution_in_number_of_particles(
                 num_sample=stg.sand_sample_target[0][1],
@@ -2021,13 +1943,17 @@ class SedimentCalibrationTab(QWidget):
 
         ks_freq1 = self.inv_hc.ks(
             proba_num=psd_number_of_particles,
-            freq=stg.freq[data_id][self.combobox_freq1.currentIndex()],
+            freq=stg.freq[self.combobox_acoustic_data_choice.currentIndex()][
+                self.combobox_freq1.currentIndex()
+            ],
             C=stg.water_velocity
         )
 
         ks_freq2 = self.inv_hc.ks(
             proba_num=psd_number_of_particles,
-            freq=stg.freq[data_id][self.combobox_freq2.currentIndex()],
+            freq=stg.freq[self.combobox_acoustic_data_choice.currentIndex()][
+                self.combobox_freq2.currentIndex()
+            ],
             C=stg.water_velocity
         )
 
@@ -2035,12 +1961,12 @@ class SedimentCalibrationTab(QWidget):
 
         logger.debug(
             "ks for frequency of "
-            + f"{stg.freq[data_id][self.combobox_freq1.currentIndex()]} : "
+            + f"{stg.freq[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq1.currentIndex()]} : "
             + f"{ks_freq1} m/kg^0.5 \n"
         )
         logger.debug(
             "ks for frequency of "
-            + f"{stg.freq[data_id][self.combobox_freq2.currentIndex()]} : " +
+            + f"{stg.freq[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex()]} : " +
             f"{ks_freq2} m/kg^0.5"
         )
 
@@ -2051,21 +1977,13 @@ class SedimentCalibrationTab(QWidget):
         self.lineEdit_ks_freq2.setText(str("%.5f" % ks_freq2))
 
     def compute_sv(self):
-        data_id = self.combobox_acoustic_data_choice.currentIndex()
-
         sv_freq1 = self.inv_hc.sv(ks=stg.ks[0], M_sand=stg.Ctot_sand[stg.sand_sample_target[0][1]])
         sv_freq2 = self.inv_hc.sv(ks=stg.ks[1], M_sand=stg.Ctot_sand[stg.sand_sample_target[0][1]])
 
         stg.sv = [sv_freq1, sv_freq2]
 
-        print(
+        print(f"sv for frequency of {stg.freq[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq1.currentIndex()]} : {sv_freq1:.8f} /m \n")
-            f"sv for frequency of {stg.freq[data_id][self.combobox_freq1.currentIndex()]}"
+        print(f"sv for frequency of {stg.freq[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex()]} : {sv_freq2:.8f} /m")
-            + f" : {sv_freq1:.8f} /m \n"
-        )
-        print(
-            f"sv for frequency of {stg.freq[data_id][self.combobox_freq2.currentIndex()]}"
-            + f" : {sv_freq2:.8f} /m"
-        )
 
         self.lineEdit_sv_freq1.clear()
         self.lineEdit_sv_freq1.setText(str("%.5f" % sv_freq1))
@@ -2074,13 +1992,9 @@ class SedimentCalibrationTab(QWidget):
         self.lineEdit_sv_freq2.setText(str("%.5f" % sv_freq2))
 
     def compute_X(self):
-        data_id = self.combobox_acoustic_data_choice.currentIndex()
+        X_exponent = self.inv_hc.X_exponent(freq1=stg.freq[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq1.currentIndex()],
-
+                                            freq2=stg.freq[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex()],
-        X_exponent = self.inv_hc.X_exponent(
+                                            sv_freq1=stg.sv[0], sv_freq2=stg.sv[1])
-            freq1=stg.freq[data_id][self.combobox_freq1.currentIndex()],
-            freq2=stg.freq[data_id][self.combobox_freq2.currentIndex()],
-            sv_freq1=stg.sv[0], sv_freq2=stg.sv[1]
-        )
 
         stg.X_exponent.clear()
         stg.X_exponent.append(X_exponent)
@@ -2123,90 +2037,190 @@ class SedimentCalibrationTab(QWidget):
             )
 
     def compute_J_cross_section(self):
-        lst_bs_data = [
-            stg.BS_stream_bed_pre_process_average,
-            stg.BS_stream_bed_pre_process_SNR,
-            stg.BS_stream_bed,
-            stg.BS_cross_section_pre_process_average,
-            stg.BS_cross_section_pre_process_SNR,
-            stg.BS_cross_section,
-            stg.BS_raw_data_pre_process_average,
-            stg.BS_raw_data_pre_process_SNR,
-            stg.BS_raw_data
-        ]
-
         for i in range(self.combobox_acoustic_data_choice.count()):
 
             J_cross_section_freq1 = np.array([])
             J_cross_section_freq2 = np.array([])
 
-            for data in lst_bs_data:
+            # --- Compute J ---
-                if data[i].shape != (0,):
+            if stg.BS_stream_bed_pre_process_average[i].shape != (0,):
-                    bs_data = data
-                    break
-
-            print(f"{stg.depth_2D[i].shape}")
-            print(f"{stg.depth_2D[i]}")
 
                 J_cross_section_freq1 = self.inv_hc.j_cross_section(
-                BS = bs_data[i][
+                    BS=stg.BS_stream_bed_pre_process_average[i][
-                    stg.frequencies_for_calibration[0][1], :, :
+                       stg.frequencies_for_calibration[0][1], :, :],
-                ],
+                    r2D=stg.depth_2D[i][stg.frequencies_for_calibration[0][1],
-                r2D = stg.depth_2D[i][
+                        :, :],
-                        stg.frequencies_for_calibration[0][1], :, :
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
-                ],
-                kt = stg.kt3D[i][
-                    stg.frequencies_for_calibration[0][1], :, :
-                ]
-            )
 
                 J_cross_section_freq2 = self.inv_hc.j_cross_section(
-                BS = bs_data[i][
+                    BS=stg.BS_stream_bed_pre_process_average[i][
-                    stg.frequencies_for_calibration[1][1], :, :
+                       stg.frequencies_for_calibration[1][1], :, :],
-                ],
+                    r2D=stg.depth_2D[i][stg.frequencies_for_calibration[1][1],
-                r2D = stg.depth_2D[i][
+                        :, :],
-                    stg.frequencies_for_calibration[1][1], :, :
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
-                ],
+
-                kt = stg.kt3D[i][
+            elif stg.BS_stream_bed_pre_process_SNR[i].shape != (0,):
-                    stg.frequencies_for_calibration[1][1], :, :
+
-                ]
+                J_cross_section_freq1 = self.inv_hc.j_cross_section(
-            )
+                    BS=stg.BS_stream_bed_pre_process_SNR[i][
+                       stg.frequencies_for_calibration[0][1], :, :],
+                    r2D=stg.depth_2D[i][stg.frequencies_for_calibration[0][1],
+                        :, :],
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
+
+                J_cross_section_freq2 = self.inv_hc.j_cross_section(
+                    BS=stg.BS_stream_bed_pre_process_SNR[i][
+                       stg.frequencies_for_calibration[1][1], :, :],
+                    r2D=stg.depth_2D[i][stg.frequencies_for_calibration[1][1],
+                        :, :],
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
+
+            elif stg.BS_stream_bed[i].shape != (0,):
+
+                J_cross_section_freq1 = self.inv_hc.j_cross_section(
+                    BS=stg.BS_stream_bed[i][stg.frequencies_for_calibration[0][1], :, :],
+                    r2D=stg.depth_2D[i][stg.frequencies_for_calibration[0][1], :, :],
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
+
+                J_cross_section_freq2 = self.inv_hc.j_cross_section(
+                    BS=stg.BS_stream_bed[i][
+                       stg.frequencies_for_calibration[1][1], :, :],
+                    r2D=stg.depth_2D[i][stg.frequencies_for_calibration[1][1], :, :],
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
+
+            elif stg.BS_cross_section_pre_process_average[i].shape != (0,):
+
+                J_cross_section_freq1 = self.inv_hc.j_cross_section(
+                    BS=stg.BS_cross_section_pre_process_average[i][
+                       stg.frequencies_for_calibration[0][1], :, :],
+                    r2D=stg.depth_2D[i][stg.frequencies_for_calibration[0][1],
+                        :, :],
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
+
+                J_cross_section_freq2 = self.inv_hc.j_cross_section(
+                    BS=stg.BS_cross_section_pre_process_average[i][
+                       stg.frequencies_for_calibration[1][1], :, :],
+                    r2D=stg.depth_2D[i][stg.frequencies_for_calibration[1][1],
+                        :, :],
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
+
+            elif stg.BS_cross_section_pre_process_SNR[i].shape != (0,):
+
+                J_cross_section_freq1 = self.inv_hc.j_cross_section(
+                    BS=stg.BS_cross_section_pre_process_SNR[i][
+                       stg.frequencies_for_calibration[0][1], :, :],
+                    r2D=stg.depth_2D[i][stg.frequencies_for_calibration[0][1],
+                        :, :],
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
+
+                J_cross_section_freq2 = self.inv_hc.j_cross_section(
+                    BS=stg.BS_cross_section_pre_process_SNR[i][
+                       stg.frequencies_for_calibration[1][1], :, :],
+                    r2D=stg.depth_2D[i][stg.frequencies_for_calibration[1][1],
+                        :, :],
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
+
+            elif stg.BS_cross_section[i].shape != (0,):
+
+                J_cross_section_freq1 = self.inv_hc.j_cross_section(
+                    BS=stg.BS_cross_section[i][
+                       stg.frequencies_for_calibration[0][1], :, :],
+                    r2D=stg.depth_2D[i, :, :][stg.frequencies_for_calibration[0][1], :, :],
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
+
+                J_cross_section_freq2 = self.inv_hc.j_cross_section(
+                    BS=stg.BS_cross_section[i][
+                       stg.frequencies_for_calibration[1][1], :, :],
+                    r2D=stg.depth_2D[i, :, :][stg.frequencies_for_calibration[1][1], :, :],
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
+
+            elif stg.BS_raw_data_pre_process_average[i].shape != (0,):
+
+                J_cross_section_freq1 = self.inv_hc.j_cross_section(
+                    BS=stg.BS_raw_data_pre_process_average[i][
+                       stg.frequencies_for_calibration[0][1], :, :],
+                    r2D=stg.depth_2D[i][stg.frequencies_for_calibration[0][1], :, :],
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
+
+                J_cross_section_freq2 = self.inv_hc.j_cross_section(
+                    BS=stg.BS_raw_data_pre_process_average[i][
+                       stg.frequencies_for_calibration[1][1], :, :],
+                    r2D=stg.depth_2D[i][stg.frequencies_for_calibration[1][1], :, :],
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
+
+            elif stg.BS_raw_data_pre_process_SNR[i].shape != (0,):
+
+                J_cross_section_freq1 = self.inv_hc.j_cross_section(
+                    BS=stg.BS_raw_data_pre_process_SNR[i][
+                       stg.frequencies_for_calibration[0][1], :, :],
+                    r2D=stg.depth_2D[i][stg.frequencies_for_calibration[0][1], :, :],
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
+
+                J_cross_section_freq2 = self.inv_hc.j_cross_section(
+                    BS=stg.BS_raw_data_pre_process_SNR[i][
+                       stg.frequencies_for_calibration[1][1], :, :],
+                    r2D=stg.depth_2D[i][stg.frequencies_for_calibration[1][1], :, :],
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
+
+            elif stg.BS_raw_data:
+
+                J_cross_section_freq1 = self.inv_hc.j_cross_section(
+                    BS=stg.BS_raw_data[i][
+                       stg.frequencies_for_calibration[0][1], :, :],
+                    r2D=stg.depth_2D[i][stg.frequencies_for_calibration[0][1], :, :],
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
+
+                J_cross_section_freq2 = self.inv_hc.j_cross_section(
+                    BS=stg.BS_raw_data[i][
+                       stg.frequencies_for_calibration[1][1], :, :],
+                    r2D=stg.depth_2D[i][stg.frequencies_for_calibration[1][1], :, :],
+                    kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
 
             stg.J_cross_section[i][0] = J_cross_section_freq1
             stg.J_cross_section[i][1] = J_cross_section_freq2
 
     def compute_alpha_s(self):
-        data_id = self.combobox_acoustic_data_choice.currentIndex()
-        freq_1 = self.combobox_freq1.currentIndex()
-        freq_2 = self.combobox_freq2.currentIndex()
 
-        depth_data = stg.depth
+        # --- Compute alpha_s ---
-        if stg.depth_cross_section[data_id].shape != (0,):
+        if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
-            depth_data = stg.depth_cross_section
 
             alpha_s_freq1 = self.inv_hc.alpha_s(
                 sv=stg.sv[0],
-            j_cross_section=stg.J_cross_section[data_id][0][
+                j_cross_section=stg.J_cross_section[self.combobox_acoustic_data_choice.currentIndex()][0][
-                stg.sand_sample_target_indice[0][0],
+                    stg.sand_sample_target_indice[0][0], stg.sand_sample_target_indice[0][1]],
-                stg.sand_sample_target_indice[0][1]
+                depth=stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
-            ],
+                    self.combobox_freq1.currentIndex(), stg.sand_sample_target_indice[0][0]],
-            depth=depth_data[data_id][
+                alpha_w=stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
-                freq_1, stg.sand_sample_target_indice[0][0]
+                    self.combobox_freq1.currentIndex()])
-            ],
-            alpha_w=stg.water_attenuation[data_id][freq_1]
-        )
 
             alpha_s_freq2 = self.inv_hc.alpha_s(
                 sv=stg.sv[1],
-            j_cross_section=stg.J_cross_section[data_id][1][
+                j_cross_section=stg.J_cross_section[self.combobox_acoustic_data_choice.currentIndex()][1][
-                stg.sand_sample_target_indice[1][0],
+                    stg.sand_sample_target_indice[1][0], stg.sand_sample_target_indice[1][1]],
-                stg.sand_sample_target_indice[1][1]
+                depth=stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
-            ],
+                    self.combobox_freq2.currentIndex(), stg.sand_sample_target_indice[1][0]],
-            depth=depth_data[data_id][
+                alpha_w=stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
-                freq_2, stg.sand_sample_target_indice[1][0]
+                    self.combobox_freq2.currentIndex()])
-            ],
+
-            alpha_w=stg.water_attenuation[data_id][freq_2]
+        else:
-        )
+
+            alpha_s_freq1 = self.inv_hc.alpha_s(
+                sv=stg.sv[0],
+                j_cross_section=stg.J_cross_section[self.combobox_acoustic_data_choice.currentIndex()][0][
+                    stg.sand_sample_target_indice[0][0], stg.sand_sample_target_indice[0][1]],
+                depth=stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                    self.combobox_freq1.currentIndex(), stg.sand_sample_target_indice[0][0]],
+                alpha_w=stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
+                    self.combobox_freq1.currentIndex()])
+
+            alpha_s_freq2 = self.inv_hc.alpha_s(
+                sv=stg.sv[1],
+                j_cross_section=stg.J_cross_section[self.combobox_acoustic_data_choice.currentIndex()][1][
+                    stg.sand_sample_target_indice[1][0], stg.sand_sample_target_indice[1][1]],
+                depth=stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
+                    self.combobox_freq2.currentIndex(), stg.sand_sample_target_indice[1][0]],
+                alpha_w=stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
+                    self.combobox_freq2.currentIndex()])
 
         stg.alpha_s = [alpha_s_freq1, alpha_s_freq2]
 

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.compute_average_profile_tail)
-        # self.pushbutton_update.clicked.connect(self.plot_averaged_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)
 
@@ -501,16 +501,6 @@ 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:
-
-            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()
-
-        else:
 
         self.combobox_acoustic_data_choice.clear()
         self.combobox_acoustic_data_choice.addItems(stg.filename_BS_raw_data)
@@ -532,9 +522,6 @@ class SignalProcessingTab(QWidget):
 
         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()):
             eval("self.lineEdit_list_pre_processed_data_" + str(i) + ".setDisabled(True)")
@@ -667,26 +654,6 @@ class SignalProcessingTab(QWidget):
 
         # --- Plot averaged signal ---
 
-        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 computing noise from profile tail")
-            msgBox.setStandardButtons(QMessageBox.Ok)
-            msgBox.exec()
-
-        elif self.combobox_acoustic_data_choice.count() == 0:
-
-            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()
-
-        else:
-
         if stg.BS_mean[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
 
             self.verticalLayout_groupbox_plot_profile_tail.removeWidget(self.canvas_profile_tail)
@@ -755,18 +722,13 @@ class SignalProcessingTab(QWidget):
 
     def clear_noise_data(self):
 
-        if len(stg.filename_BS_raw_data) == 0:
-
-            pass
-
-        else:
-
         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
 
         stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()] = np.array([])
@@ -777,7 +739,7 @@ class SignalProcessingTab(QWidget):
 
         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()
 
@@ -1259,19 +1221,11 @@ class SignalProcessingTab(QWidget):
 
     def remove_point_with_snr_filter(self):
 
-        if len(stg.filename_BS_raw_data) == 0:
+        if len(stg.BS_noise_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("Define noise data (file or profile tail) before using SNR filter")
+            msgBox.setText("Load Noise data from acoustic data tab before using SNR filter")
             msgBox.setStandardButtons(QMessageBox.Ok)
             msgBox.exec()
 
@@ -1550,24 +1504,6 @@ class SignalProcessingTab(QWidget):
 
     def compute_averaged_BS_data(self):
 
-        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("Define noise data (file or profile tail) before using SNR filter")
-            msgBox.setStandardButtons(QMessageBox.Ok)
-            msgBox.exec()
-
-        else:
-
         kernel_avg = np.ones(2 * int(float(self.lineEdit_horizontal_average.text().replace(",", "."))) + 1)
         print(kernel_avg)