Git: Simplify 'requirements.txt'.

Model/create_table_for_save_as.py

@@ -45,7 +45,7 @@ class CreateTableForSaveAs:
           ABS_name STRING,
           path_BS_noise_data STRING,
           filename_BS_noise_data STRING,
-          noise_method FLOAT,
+          noise_method INTERGER,
           noise_value FLOAT,
           data_preprocessed STRING
         )
@@ -104,7 +104,7 @@ class CreateTableForSaveAs:
           tmax_index INTEGER, tmax_value FLOAT,
           rmin_index INTEGER, rmin_value FLOAT,
           rmax_index INTEGER, rmax_value FLOAT,
-          freq_bottom_detection_index FLOAT,
+          freq_bottom_detection_index INTEGER,
           freq_bottom_detection_value STRING,
           depth_bottom_detection_min FLOAT,
           depth_bottom_detection_max FLOAT,
@@ -455,9 +455,9 @@ class CreateTableForSaveAs:
                     int(stg.rmax[i][0]), stg.rmax[i][1],
                     stg.freq_bottom_detection[i][0],
                     stg.freq_bottom_detection[i][1],
-                    stg.depth_bottom_detection_min,
-                    stg.depth_bottom_detection_max,
-                    stg.depth_bottom_detection_interval,
+                    stg.depth_bottom_detection_min[i],
+                    stg.depth_bottom_detection_max[i],
+                    stg.depth_bottom_detection_interval[i],
                     stg.SNR_filter_value[i],
                     stg.Nb_cells_to_average_BS_signal[i]
                 )

Model/read_table_for_open.py

@@ -528,9 +528,9 @@ class ReadTableForOpen:
             stg.rmin.append((next(it), next(it)))
             stg.rmax.append((next(it), next(it)))
             stg.freq_bottom_detection.append((next(it), next(it)))
-            stg.depth_bottom_detection_min = next(it)
-            stg.depth_bottom_detection_max = next(it)
-            stg.depth_bottom_detection_interval = next(it)
+            stg.depth_bottom_detection_min.append(next(it))
+            stg.depth_bottom_detection_max.append(next(it))
+            stg.depth_bottom_detection_interval.append(next(it))
             stg.SNR_filter_value.append(next(it))
             stg.Nb_cells_to_average_BS_signal.append(next(it))
 

View/acoustic_data_tab.py

@@ -41,7 +41,7 @@ from PyQt5.QtWidgets import (
     QPushButton, QComboBox, QLineEdit, QLabel,
     QGridLayout, QTableView, QSpacerItem, QSizePolicy,
     QFileDialog, QMessageBox, QScrollArea,
-    QSlider, QMenu, QCheckBox
+    QSlider, QMenu, QCheckBox, QAbstractItemView
 )
 from PyQt5.QtGui import QPixmap, QIcon
 from PyQt5.QtCore import (
@@ -161,6 +161,7 @@ class AcousticDataTab(QWidget):
         self.gridLayout_groupbox_acoustic_file.addWidget(self.clearBtn, 0, 4, 1, 1)
 
         self.fileListWidget = FileListWidget()
+        self.fileListWidget.setSelectionMode(QAbstractItemView.SingleSelection)
         self.gridLayout_groupbox_acoustic_file.addWidget(self.fileListWidget, 1, 0, 1, 5)
 
         # ++++++++++++++++++++++++++++++++++++++
@@ -760,7 +761,6 @@ class AcousticDataTab(QWidget):
         self.water_attenuation()
         self.compute_tmin_tmax()
         self.compute_rmin_rmax()
-        self.set_range_for_spinboxes_bathymetry()
 
         self.combobox_ABS_system_choice.blockSignals(False)
         self.fileListWidget.blockSignals(False)
@@ -821,7 +821,7 @@ class AcousticDataTab(QWidget):
         # self.fileListWidget.itemSelectionChanged.connect(self.plot_profile)
         self.update_plot_backscattered_acoustic_signal_recording()
         self.update_plot_profile()
-        self.set_range_for_spinboxes_bathymetry()
+        self.update_bottom_detection_settings()
 
         self.fileListWidget.blockSignals(False)
 
@@ -1351,7 +1351,6 @@ class AcousticDataTab(QWidget):
             ("UBSediFlow file", "UBSediFlow file (*.udt)"),
         ]
 
-
         system = self.combobox_ABS_system_choice.currentIndex()
 
         if system == 0:
@@ -1454,42 +1453,7 @@ class AcousticDataTab(QWidget):
             del current_item
 
         # --- Clear variables ---
-        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):
-                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.depth_cross_section,
-                stg.BS_cross_section
-            ]
-
-            for k in list_to_pop2:
-                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:
-                s.pop(current_row)
+        self.pop_setting_parameters(current_row)
 
         if self.fileListWidget.count() == 0:
             self.clear_files_from_ListWidget_reset()
@@ -1688,6 +1652,9 @@ class AcousticDataTab(QWidget):
         stg.val_bottom.append([])
         stg.ind_bottom.append([])
         stg.freq_bottom_detection.append((0, 0))
+        stg.depth_bottom_detection_min.append(0.0)
+        stg.depth_bottom_detection_max.append(0.0)
+        stg.depth_bottom_detection_interval.append(0.0)
 
         stg.BS_mean.append(np.array([]))
         stg.BS_noise_raw_data.append(np.array([]))
@@ -1724,6 +1691,93 @@ class AcousticDataTab(QWidget):
         stg.SSC_fine.append(np.array([]))
         stg.SSC_sand.append(np.array([]))
 
+    def pop_setting_parameters(self, data_id):
+        stg.acoustic_data = list(
+            range(
+                self.fileListWidget.count()
+            )
+        )
+
+        stg.path_BS_raw_data.pop(data_id)
+        stg.filename_BS_raw_data.pop(data_id)
+
+        stg.ABS_name.pop(data_id)
+        stg.BS_raw_data.pop(data_id)
+        stg.BS_raw_data_reshape.pop(data_id)
+        stg.depth.pop(data_id)
+        stg.depth_2D.pop(data_id)
+        stg.depth_reshape.pop(data_id)
+        stg.time.pop(data_id)
+        stg.time_reshape.pop(data_id)
+        stg.freq.pop(data_id)
+        stg.freq_text.pop(data_id)
+        stg.date.pop(data_id)
+        stg.hour.pop(data_id)
+        stg.distance_from_ABS_to_free_surface.pop(data_id)
+        stg.nb_profiles.pop(data_id)
+        stg.nb_profiles_per_sec.pop(data_id)
+        stg.nb_cells.pop(data_id)
+        stg.cell_size.pop(data_id)
+        stg.pulse_length.pop(data_id)
+        stg.nb_pings_per_sec.pop(data_id)
+        stg.nb_pings_averaged_per_profile.pop(data_id)
+
+        stg.gain_rx.pop(data_id)
+        stg.gain_tx.pop(data_id)
+        stg.water_attenuation.pop(data_id)
+
+        self.pop_setting_parameters_others(data_id)
+
+    def pop_setting_parameters_others(self, data_id):
+        stg.BS_cross_section.pop(data_id)
+        stg.depth_cross_section.pop(data_id)
+        stg.time_cross_section.pop(data_id)
+
+        stg.tmin.pop(data_id)
+        stg.tmax.pop(data_id)
+        stg.rmin.pop(data_id)
+        stg.rmax.pop(data_id)
+
+        stg.BS_stream_bed.pop(data_id)
+        stg.depth_bottom.pop(data_id)
+        stg.val_bottom.pop(data_id)
+        stg.ind_bottom.pop(data_id)
+        stg.freq_bottom_detection.pop(data_id)
+        stg.depth_bottom_detection_min.pop(data_id)
+        stg.depth_bottom_detection_max.pop(data_id)
+        stg.depth_bottom_detection_interval.pop(data_id)
+
+        stg.BS_mean.pop(data_id)
+        stg.BS_noise_raw_data.pop(data_id)
+        stg.BS_noise_averaged_data.pop(data_id)
+        stg.SNR_raw_data.pop(data_id)
+        stg.SNR_cross_section.pop(data_id)
+        stg.SNR_stream_bed.pop(data_id)
+        stg.time_noise.pop(data_id)
+        stg.depth_noise.pop(data_id)
+        stg.noise_method.pop(data_id)
+        stg.noise_value.pop(data_id)
+        stg.SNR_filter_value.pop(data_id)
+        stg.Nb_cells_to_average_BS_signal.pop(data_id)
+        stg.filename_BS_noise_data.pop(data_id)
+        stg.path_BS_noise_data.pop(data_id)
+
+        stg.BS_raw_data_pre_process_SNR.pop(data_id)
+        stg.BS_raw_data_pre_process_average.pop(data_id)
+
+        stg.BS_cross_section_pre_process_SNR.pop(data_id)
+        stg.BS_cross_section_pre_process_average.pop(data_id)
+
+        stg.BS_stream_bed_pre_process_SNR.pop(data_id)
+        stg.BS_stream_bed_pre_process_average.pop(data_id)
+
+        stg.kt2D.pop(data_id)
+        stg.kt3D.pop(data_id)
+        stg.J_cross_section.pop(data_id)
+        stg.VBI_cross_section.pop(data_id)
+        stg.SSC_fine.pop(data_id)
+        stg.SSC_sand.pop(data_id)
+
     def fill_measurements_information_groupbox(self):
         if self.fileListWidget.currentRow() == -1:
             return
@@ -2314,83 +2368,41 @@ class AcousticDataTab(QWidget):
         ''' rmin and rmax are updated with double slider of depth '''
         data_id = self.fileListWidget.currentRow()
 
+        round_depth = np.round(stg.depth[data_id][0, :], 2)
+        depth_max = float(
+            "".join(
+                findall(
+                    "[.0-9]",
+                    self.lineEdit_depth_max_limits.text()
+                )
+            )
+        )
+        depth_min = float(
+            "".join(
+                findall(
+                    "[.0-9]",
+                    self.lineEdit_depth_min_limits.text()
+                )
+            )
+        )
+
+        diff_max = np.abs(round_depth - depth_max)
+        diff_min = np.abs(round_depth - depth_min)
+
         stg.rmin[data_id] = ((
-            np.where(
-                np.abs(
-                    np.round(
-                        stg.depth[data_id][0, :], 2
-                    ) - float(
-                        "".join(
-                            findall(
-                                "[.0-9]",
-                                self.lineEdit_depth_max_limits.text()
-                            )
-                        )
-                    )
-                ) == np.nanmin(
-                    np.abs(
-                        np.round(stg.depth[data_id][0, :], 2)
-                        - float(
-                            "".join(
-                                findall(
-                                    "[.0-9]",
-                                    self.lineEdit_depth_max_limits.text()
-                                )
-                            )
-                        )
-                    )
-                )
-            )[0][0]+1,
-            float(
-                "".join(
-                    findall(
-                        "[.0-9]",
-                        self.lineEdit_depth_max_limits.text()
-                    )
-                )
-            )
+            np.where(diff_max == np.nanmin(diff_max))[0][0]+1,
+            depth_max
         ))
 
         stg.rmax[data_id] = ((
-            np.where(
-                np.abs(
-                    np.round(
-                        stg.depth[data_id][0, :], 2
-                    ) - float(
-                        "".join(
-                            findall(
-                                "[.0-9]",
-                                self.lineEdit_depth_min_limits.text()
-                            )
-                        )
-                    )
-                ) == np.nanmin(
-                    np.abs(
-                        np.round(stg.depth[data_id][0, :], 2)
-                        - float(
-                            "".join(
-                                findall(
-                                    "[.0-9]",
-                                    self.lineEdit_depth_min_limits.text()
-                                )
-                            )
-                        )
-                    )
-                )
-            )[0][0],
-            float(
-                "".join(
-                    findall(
-                        "[.0-9]",
-                        self.lineEdit_depth_min_limits.text()
-                    )
-                )
-            )
+            np.where(diff_min == np.nanmin(diff_min))[0][0],
+            depth_min
         ))
 
         stg.depth_cross_section[data_id] = (
-            stg.depth[data_id][:,
-            stg.rmin[data_id][0]:stg.rmax[data_id][0]]
+            stg.depth[data_id][
+                :, stg.rmin[data_id][0]:stg.rmax[data_id][0]
+            ]
         )
 
     def compute_BS_cross_section(self):
@@ -2868,28 +2880,44 @@ class AcousticDataTab(QWidget):
             self.lineEdit_slider.setText(
                 str(stg.time[self.fileListWidget.currentRow()][self.combobox_frequency_profile.currentIndex(), self.slider.value()-1]))
 
-
     def update_bottom_detection_settings(self):
+        data_id = max(0, self.fileListWidget.currentRow())
+
+        if stg.depth_bottom_detection_interval[data_id] == 0.0:
+            self.set_range_for_spinboxes_bathymetry()
+            return
+
+        self.combobox_frequency_bathymetry.setCurrentIndex(
+            int(stg.freq_bottom_detection[data_id][0])
+        )
+
         self.lineEdit_depth_min_bathy.setText(
-            str(stg.depth_bottom_detection_min)
+            str(stg.depth_bottom_detection_min[data_id])
         )
 
         self.lineEdit_depth_max_bathy.setText(
-            str(stg.depth_bottom_detection_max)
+            str(stg.depth_bottom_detection_max[data_id])
         )
 
         self.lineEdit_next_cell_bathy.setText(
-            str(stg.depth_bottom_detection_interval)
+            str(stg.depth_bottom_detection_interval[data_id])
         )
 
     def save_bottom_detection_settings(self):
-        stg.depth_bottom_detection_min = float(
+        data_id = max(0, self.fileListWidget.currentRow())
+
+        stg.freq_bottom_detection[data_id] = (
+            int(self.combobox_frequency_bathymetry.currentIndex()),
+            str(self.combobox_frequency_bathymetry.currentText()),
+        )
+
+        stg.depth_bottom_detection_min[data_id] = float(
             self.lineEdit_depth_min_bathy.text()
         )
-        stg.depth_bottom_detection_max = float(
+        stg.depth_bottom_detection_max[data_id] = float(
             self.lineEdit_depth_max_bathy.text()
         )
-        stg.depth_bottom_detection_interval = float(
+        stg.depth_bottom_detection_interval[data_id] = float(
             self.lineEdit_next_cell_bathy.text()
         )
 

View/acoustic_inversion_tab.py

@@ -936,6 +936,7 @@ class AcousticInversionTab(QWidget):
     def fill_combobox_fine_sample(self):
         data_id = self.combobox_acoustic_data_choice.currentIndex()
 
+        self.combobox_fine_sample_choice.clear()
         self.combobox_fine_sample_choice.addItems(
             [f for f, _ in stg.sample_fine]
         )
@@ -1507,121 +1508,39 @@ class AcousticInversionTab(QWidget):
     # --- Plot sand SSC : measured vs inverted ---
 
     def fill_combobox_sand_sample(self):
+        data_id = self.combobox_acoustic_data_choice.currentIndex()
 
-        self.combobox_sand_sample_choice.addItems([f for f, _ in stg.sample_sand])
+        self.combobox_sand_sample_choice.clear()
+        self.combobox_sand_sample_choice.addItems(
+            [f for f, _ in stg.sample_sand]
+        )
 
         # --- Get position (index, value) of sample in acoustic measurement space ---
-        if ((stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,)) and
-                (stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,))):
+        if stg.time_cross_section[data_id].shape != (0,):
+            time_data = stg.time_cross_section
+        else:
+            time_data = stg.time
 
+        if stg.depth_cross_section[data_id].shape != (0,):
+            depth_data = stg.depth_cross_section
+        else:
+            depth_data = stg.depth
+
+        freq = stg.frequency_for_inversion[1]
         for j in range(len(stg.time_sand)):
+            time_diff = np.abs(time_data[data_id][freq] - stg.time_sand[j])
+            depth_diff = np.abs(depth_data[data_id][freq] - (-stg.depth_sand[j]))
 
-                (stg.sand_sample_position.
-                    append(
+            stg.sand_sample_position.append(
                 (
                     np.where(
-                                    np.abs(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
-                                               stg.frequency_for_inversion[1]] - stg.time_sand[j])
-                                    ==
-                                    np.nanmin(np.abs(stg.time_cross_section[
-                                                         self.combobox_acoustic_data_choice.currentIndex()][
-                                                         stg.frequency_for_inversion[1]] - stg.time_sand[j]))
+                        time_diff == np.nanmin(time_diff)
                     )[0][0],
                     np.where(
-                                    np.abs(stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
-                                               stg.frequency_for_inversion[1]] - (-stg.depth_sand[j]))
-                                    ==
-                                    np.nanmin(np.abs(stg.depth_cross_section[
-                                                         self.combobox_acoustic_data_choice.currentIndex()][
-                                                         stg.frequency_for_inversion[1]] - (-stg.depth_sand[j])))
+                        depth_diff == np.nanmin(depth_diff)
                     )[0][0]
                 )
             )
-                )
-
-        elif ((stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,)) and
-                  (stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,))):
-
-            for j in range(len(stg.time_sand)):
-
-                (stg.sand_sample_position.
-                    append(
-                            (
-                                np.where(
-                                    np.abs(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
-                                               stg.frequency_for_inversion[1]] - stg.time_sand[j])
-                                    ==
-                                    np.nanmin(np.abs(stg.time_cross_section[
-                                                         self.combobox_acoustic_data_choice.currentIndex()][
-                                                         stg.frequency_for_inversion[1]] - stg.time_sand[j]))
-                                )[0][0],
-                                np.where(
-                                    np.abs(stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
-                                               stg.frequency_for_inversion[1]] - (-stg.depth_sand[j]))
-                                    ==
-                                    np.nanmin(np.abs(stg.depth[
-                                                         self.combobox_acoustic_data_choice.currentIndex()][
-                                                         stg.frequency_for_inversion[1]] - (-stg.depth_sand[j])))
-                                )[0][0]
-                            )
-                           )
-                )
-
-        elif ((stg.time[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,)) and
-                  (stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,))):
-
-            for j in range(len(stg.time_sand)):
-
-                (stg.sand_sample_position.
-                    append(
-                            (
-                                np.where(
-                                    np.abs(stg.time[self.combobox_acoustic_data_choice.currentIndex()][
-                                               stg.frequency_for_inversion[1]] - stg.time_sand[j])
-                                    ==
-                                    np.nanmin(np.abs(stg.time[
-                                                         self.combobox_acoustic_data_choice.currentIndex()][
-                                                         stg.frequency_for_inversion[1]] - stg.time_sand[j]))
-                                )[0][0],
-                                np.where(
-                                    np.abs(stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
-                                               stg.frequency_for_inversion[1]] - (-stg.depth_sand[j]))
-                                    ==
-                                    np.nanmin(np.abs(stg.depth_cross_section[
-                                                         self.combobox_acoustic_data_choice.currentIndex()][
-                                                         stg.frequency_for_inversion[1]] - (-stg.depth_sand[j])))
-                                )[0][0]
-                            )
-                           )
-                )
-
-        elif ((stg.time[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,)) and
-                  (stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,))):
-
-            for j in range(len(stg.time_sand)):
-
-                (stg.sand_sample_position.
-                    append(
-                            (
-                                np.where(
-                                    np.abs(stg.time[self.combobox_acoustic_data_choice.currentIndex()][
-                                               stg.frequency_for_inversion[1]] - stg.time_sand[j])
-                                    ==
-                                    np.nanmin(np.abs(stg.time[
-                                                         self.combobox_acoustic_data_choice.currentIndex()][
-                                                         stg.frequency_for_inversion[1]] - stg.time_sand[j]))
-                                )[0][0],
-                                np.where(
-                                    np.abs(stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
-                                               stg.frequency_for_inversion[1]] - (-stg.depth_sand[j]))
-                                    ==
-                                    np.nanmin(np.abs(stg.depth[
-                                                         self.combobox_acoustic_data_choice.currentIndex()][
-                                                         stg.frequency_for_inversion[1]] - (-stg.depth_sand[j])))
-                                )[0][0]
-                            )
-                           )
-                )
 
     def plot_measured_vs_inverted_SSC_sand(self):
 

View/sediment_calibration_tab.py

@@ -67,7 +67,9 @@ class SedimentCalibrationTab(QWidget):
         self._setup_widgets()
 
     def _path_icon(self, icon):
-        return os.path.join("icons", icon)
+        return os.path.join(
+            os.path.dirname(__file__), "..", "icons", icon
+        )
 
     def _setup_icons(self):
         self.icon_folder = QIcon(self._path_icon("folder.png"))
@@ -1994,7 +1996,6 @@ 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([])
 
@@ -2065,119 +2066,128 @@ class SedimentCalibrationTab(QWidget):
 
         stg.alpha_s = [alpha_s_freq1, alpha_s_freq2]
 
-        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")
+        logger.debug(
+            f"\u03B1s for frequency of freq1 : {alpha_s_freq1:.2f} / m"
+        )
+        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))
+        self.lineEdit_alphas_freq1.setText(f"{alpha_s_freq1:.5f}")
 
         self.lineEdit_alphas_freq2.clear()
-        self.lineEdit_alphas_freq2.setText(str("%.5f" % alpha_s_freq2))
+        self.lineEdit_alphas_freq2.setText(f"{alpha_s_freq2:.5f}")
+
+        title = "Alpha computation error"
+        icon = self._path_icon("no_approved.png")
 
         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.setText("Sediment sound attenuation is negative !")
-            msgBox.setStandardButtons(QMessageBox.Ok)
-            msgBox.exec()
-
+            text = "Sediment sound attenuation is negative !"
         elif isinf(alpha_s_freq1) or isinf(alpha_s_freq2):
-
-            msgBox = QMessageBox()
-            msgBox.setWindowTitle("Alpha computation error")
-            msgBox.setIconPixmap(
-                QPixmap(self._path_icon("no_approved.png")).scaledToHeight(32, Qt.SmoothTransformation))
-            msgBox.setText("Sediment sound attenuation is infinite !")
-            msgBox.setStandardButtons(QMessageBox.Ok)
-            msgBox.exec()
-
+            text = "Sediment sound attenuation is infinite !"
         else:
+            title = "Alpha computation validation"
+            icon = self._path_icon("approved.png")
+            text = "Sediment sound attenuation is positive."
 
         msgBox = QMessageBox()
-            msgBox.setWindowTitle("Alpha computation validation")
-            msgBox.setIconPixmap(QPixmap(self._path_icon("approved.png")).scaledToHeight(32, Qt.SmoothTransformation))
-            msgBox.setText("Sediment sound attenuation is positive.")
+        msgBox.setWindowTitle(title)
+        msgBox.setIconPixmap(
+            QPixmap(icon).scaledToHeight(
+                32, Qt.SmoothTransformation
+            )
+        )
+        msgBox.setText(text)
         msgBox.setStandardButtons(QMessageBox.Ok)
         msgBox.exec()
 
     def compute_zeta(self):
-
-        # --- Compute zeta ---
         if stg.M_profile_fine.shape == (0,):
-
             msgBox = QMessageBox()
             msgBox.setWindowTitle("Zeta computation error")
             msgBox.setIcon(QMessageBox.Warning)
             msgBox.setText("Please interpolate fine profile")
             msgBox.setStandardButtons(QMessageBox.Ok)
             msgBox.exec()
+            return
 
+        data_id = self.combobox_acoustic_data_choice.currentIndex()
+        freq_1 = self.combobox_freq1.currentIndex()
+        freq_2 = self.combobox_freq2.currentIndex()
+
+        if stg.depth_cross_section[data_id].shape != (0,):
+            depth_data = stg.depth_cross_section
         else:
+            depth_data = stg.depth
 
-            if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
-
-                zeta_freq1 = self.inv_hc.zeta(alpha_s=stg.alpha_s[0],
-                                              r=stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
-                                                self.combobox_freq1.currentIndex(), :],
-                                              M_profile_fine=stg.M_profile_fine)
-                zeta_freq2 = self.inv_hc.zeta(alpha_s=stg.alpha_s[1],
-                                              r=stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
-                                                self.combobox_freq2.currentIndex(), :],
-                                              M_profile_fine=stg.M_profile_fine)
-
-            else:
-                zeta_freq1 = self.inv_hc.zeta(alpha_s=stg.alpha_s[0],
-                                              r=stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
-                                                self.combobox_freq1.currentIndex(), :],
-                                              M_profile_fine=stg.M_profile_fine)
-                zeta_freq2 = self.inv_hc.zeta(alpha_s=stg.alpha_s[1],
-                                              r=stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
-                                                self.combobox_freq2.currentIndex(), :],
-                                              M_profile_fine=stg.M_profile_fine)
+        zeta_freq1 = self.inv_hc.zeta(
+            alpha_s = stg.alpha_s[0],
+            r = depth_data[data_id][freq_1, :],
+            M_profile_fine = stg.M_profile_fine
+        )
+        zeta_freq2 = self.inv_hc.zeta(
+            alpha_s = stg.alpha_s[1],
+            r = depth_data[data_id][freq_2, :],
+            M_profile_fine = stg.M_profile_fine
+        )
 
         stg.zeta = [zeta_freq1, zeta_freq2]
 
-            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")
+        logger.debug(
+            f"\u03B6 for frequency of freq1 : {zeta_freq1:.3f} / m"
+        )
+        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))
+        self.lineEdit_zeta_freq1.setText(f"{zeta_freq1:.5f}")
 
         self.lineEdit_zeta_freq2.clear()
-            self.lineEdit_zeta_freq2.setText(str("%.5f" % zeta_freq2))
+        self.lineEdit_zeta_freq2.setText(f"{zeta_freq2:.5f}")
 
     def save_calibration(self):
+        data_id = self.combobox_acoustic_data_choice.currentIndex()
+
+        freq1 = stg.frequencies_for_calibration[0][1]
+        freq2 = stg.frequencies_for_calibration[1][1]
 
         if stg.alpha_s:
+            directory = ""
+            if stg.path_calibration_file != "":
+                directory = stg.path_calibration_file
+            elif self.combobox_acoustic_data_choice.count() > 0:
+                directory = stg.path_BS_raw_data[-1]
 
             dir_save_cal = QFileDialog.getExistingDirectory(
                 caption="Save calibration",
-                directory=[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],
-                options=QFileDialog.DontUseNativeDialog)
+                directory=directory,
+                options=QFileDialog.DontUseNativeDialog
+            )
 
             if dir_save_cal:
-
                 stg.path_calibration_file = os.path.dirname(dir_save_cal)
 
-                cal_array = [[' ', stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()][stg.frequencies_for_calibration[0][1]],
-                                    stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()][stg.frequencies_for_calibration[1][1]]],
+                cal_array = [
+                    [
+                        ' ', stg.freq_text[data_id][freq1],
+                        stg.freq_text[data_id][freq2]
+                    ],
                     ['ks', stg.ks[0], stg.ks[1]],
                     ['sv', stg.sv[0], stg.sv[1]],
                     ['X', stg.X_exponent[0], 0],
                     ['alphas', stg.alpha_s[0], stg.alpha_s[1]],
-                             ['zeta', stg.zeta[0], stg.zeta[1]]]
-
-                eval("np.savetxt('"+ dir_save_cal + "/Sediment_calibration_" +
-                                    str(stg.filename_BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()][:-4]) + ".csv' ," +
-                                "cal_array, " +
-                                "delimiter=',' ," +
-                                "fmt ='% s'" +
-                                ")")
+                    ['zeta', stg.zeta[0], stg.zeta[1]]
+                ]
 
+                np.savetxt(
+                    f"{dir_save_cal}/Sediment_calibration_"
+                    + f"{stg.filename_BS_raw_data[data_id][:-4]}.csv",
+                    cal_array,
+                    delimiter=',', fmt ='% s'
+                )
         else:
-
             msgBox = QMessageBox()
             msgBox.setWindowTitle("Save Error")
             msgBox.setIcon(QMessageBox.Warning)
@@ -2190,68 +2200,49 @@ class SedimentCalibrationTab(QWidget):
     # ------------ Computing real cell size ------------ #
     def range_cells_function(self):
         """ Computing the real cell size, that depends on the temperature """
-
-        if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
+        data_id = self.combobox_acoustic_data_choice.currentIndex()
 
         aquascat_cell_size = []
         tau = []
         real_cell_size = []
 
-            stg.depth_real = np.zeros(stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape)
+        if stg.depth_cross_section[data_id].shape != (0,):
+            depth_data = stg.depth_cross_section
+        else:
+            depth_data = stg.depth
 
-            for f in range(stg.freq[self.combobox_acoustic_data_choice.currentIndex()].shape[0]):
+        stg.depth_real = np.zeros(depth_data[data_id].shape)
+
+        for f in range(stg.freq[data_id].shape[0]):
             # defaut Aquascat cell size
             aquascat_cell_size.append(
-                    stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, 1] -
-                    stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, 0])
+                depth_data[data_id][f, 1] - depth_data[data_id][f, 0]
+            )
 
-                # Pulse duration
-                tau.append(aquascat_cell_size[f] * 2 / 1500)  # figure 2.9  1500 vitesse du son entrée pour le paramètrage des mesures aquascat
+            # Pulse duration: figure 2.9 1500 vitesse du son entrée
+            # pour le paramètrage des mesures aquascat
+            tau.append(aquascat_cell_size[f] * 2 / 1500)
 
-                # Real cell size
-                real_cell_size.append(stg.water_velocity * tau[f] / 2)  # voir fig 2.9
+            # voir fig 2.9
+            real_cell_size.append(stg.water_velocity * tau[f] / 2)
 
             # Converting to real cell profile
-                stg.depth_real[f, :] = (stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, :]
-                                        / aquascat_cell_size[f] * real_cell_size[f])
+            stg.depth_real[f, :] = (
+                depth_data[data_id][f, :]
+                / aquascat_cell_size[f]
+                * real_cell_size[f]
+            )
 
+
+        if stg.time_cross_section[data_id].shape != (0,):
+            time_data = stg.time_cross_section
         else:
+            time_data = stg.time
 
-            aquascat_cell_size = []
-            tau = []
-            real_cell_size = []
-
-            stg.depth_real = (np.zeros(stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape))
-
-            for f in range(stg.freq[self.combobox_acoustic_data_choice.currentIndex()].shape[0]):
-
-                # defaut Aquascat cell size
-                aquascat_cell_size.append(
-                    stg.depth[self.combobox_acoustic_data_choice.currentIndex()][f, 1] -
-                    stg.depth[self.combobox_acoustic_data_choice.currentIndex()][f, 0])
-
-                # Pulse duration
-                tau.append(aquascat_cell_size[f] * 2 / 1500)  # figure 2.9  1500 vitesse du son entrée pour le paramètrage des mesures aquascat
-
-                # Real cell size
-                real_cell_size.append(stg.water_velocity * tau[f] / 2)  # voir fig 2.9
-
-                # Converting to real cell profile
-
-                stg.depth_real[f, :] = (stg.depth[self.combobox_acoustic_data_choice.currentIndex()][f, :] /
-                                            aquascat_cell_size[f] * real_cell_size[f])
-
-        if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
-
-            stg.depth_real = \
-                (np.repeat(stg.depth_real[:, :, np.newaxis],
-                           stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape[1], axis=2))
-
-        else:
-
-            stg.depth_real = (
-                np.repeat(stg.depth_real[:, :, np.newaxis],
-                          stg.time[self.combobox_acoustic_data_choice.currentIndex()].shape[1], axis=2))
+        stg.depth_real = np.repeat(
+            stg.depth_real[:, :, np.newaxis],
+            time_data[data_id].shape[1], axis=2
+        )
 
     def compute_FCB(self):
         data_id = self.combobox_acoustic_data_choice.currentIndex()
@@ -2414,6 +2405,10 @@ class SedimentCalibrationTab(QWidget):
         data_id = self.combobox_acoustic_data_choice.currentIndex()
         fcb_id = self.combobox_frequency_FCB.currentIndex()
 
+        if (self.lineEdit_FCB_from.text() == ''
+            or self.lineEdit_FCB_to.text() == ''):
+            return
+
         self.update_plot_FCB()
 
         if stg.FCB.shape == (0,):
@@ -2437,8 +2432,7 @@ class SedimentCalibrationTab(QWidget):
             np.round(
                 np.abs(
                     x - float(
-                        self.lineEdit_FCB_from\
-                            .text().replace(',','.')
+                        self.lineEdit_FCB_from.text().replace(',','.')
                     )
                 ), 2
             ) == np.min(

View/signal_processing_tab.py

@@ -625,7 +625,9 @@ class SignalProcessingTab(QWidget):
         self.compute_average_profile_tail()
 
         if stg.noise_method[data_id] == 0:
-            if stg.filename_BS_noise_data[data_id] != "":
+            if stg.filename_BS_noise_data[data_id] == "":
+                return
+
             if len(stg.BS_noise_raw_data) == 0:
                 self.load_noise_data_and_compute_SNR()
             else:
@@ -920,7 +922,9 @@ class SignalProcessingTab(QWidget):
 
         self.compute_average_profile_tail()
 
-        logger.debug(f"stg.SNR_filter_value: {stg.SNR_filter_value}")
+        self.lineEdit_profile_tail_value.setText(
+            str(stg.noise_value[data_id])
+        )
 
         self.lineEdit_SNR_criterion.setText(
             str(stg.SNR_filter_value[data_id])
@@ -1029,22 +1033,30 @@ class SignalProcessingTab(QWidget):
             self.slider.setMaximum(10)
 
     def open_dialog_box(self):
+        data_id = self.combobox_acoustic_data_choice.currentIndex()
 
         if self.combobox_acoustic_data_choice.count() > 0:
-            filename = QFileDialog.getOpenFileNames(self, "AQUAscat Noise file",
-                                                   [stg.path_BS_raw_data[-1] if self.combobox_acoustic_data_choice.count() > 0 else ""][0],
+            directory = ""
+            if self.combobox_acoustic_data_choice.count() > 0:
+                directory = stg.path_BS_raw_data[-1]
+
+            filename, _ = QFileDialog.getOpenFileName(
+                self, "AQUAscat Noise file",
+                directory,
                 "Aquascat file (*.aqa)",
-                                                    options=QFileDialog.DontUseNativeDialog)
-            if filename[0]:
-                dir_name = path.dirname(filename[0][0])
-                name = path.basename(filename[0][0])
-                stg.path_BS_noise_data[self.combobox_acoustic_data_choice.currentIndex()] = dir_name
-                stg.filename_BS_noise_data[self.combobox_acoustic_data_choice.currentIndex()] = name
+                options=QFileDialog.DontUseNativeDialog
+            )
+
+            if filename == "":
+                return
+
+            dir_name = path.dirname(filename)
+            name = path.basename(filename)
+            stg.path_BS_noise_data[data_id] = dir_name
+            stg.filename_BS_noise_data[data_id] = name
 
             try:
-
                 self.load_noise_data_and_compute_SNR()
-
             except ValueError as e:
                 msgBox = QMessageBox()
                 msgBox.setWindowTitle("Download Error")
@@ -1052,34 +1064,35 @@ class SignalProcessingTab(QWidget):
                 msgBox.setText("Please select a file")
                 msgBox.setStandardButtons(QMessageBox.Ok)
                 msgBox.exec()
-
             else:
-                self.lineEdit_noise_file.setText(stg.filename_BS_noise_data[self.combobox_acoustic_data_choice.currentIndex()])
-                self.lineEdit_noise_file.setToolTip(stg.path_BS_noise_data[self.combobox_acoustic_data_choice.currentIndex()])
+                self.lineEdit_noise_file.setText(stg.filename_BS_noise_data[data_id])
+                self.lineEdit_noise_file.setToolTip(stg.path_BS_noise_data[data_id])
                 self.plot_transect_with_SNR_data()
 
                 self.combobox_frequency_profile.clear()
-                self.combobox_frequency_profile.addItems([f for f in stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()]])
-                self.combobox_frequency_profile.currentIndexChanged.connect(self.plot_pre_processed_BS_signal)
-                self.combobox_frequency_profile.currentIndexChanged.connect(self.update_plot_pre_processed_profile)
+                self.combobox_frequency_profile.addItems(
+                    [f for f in stg.freq_text[data_id]]
+                )
 
-                if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
-
-                    self.slider.setMaximum(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape[1])
+                self.combobox_frequency_profile\
+                    .currentIndexChanged\
+                    .connect(self.plot_pre_processed_BS_signal)
+                self.combobox_frequency_profile\
+                    .currentIndexChanged\
+                    .connect(self.update_plot_pre_processed_profile)
 
+                if stg.time_cross_section[data_id].shape != (0,):
+                    self.slider.setMaximum(stg.time_cross_section[data_id].shape[1])
                 else:
-
-                    self.slider.setMaximum(stg.time[self.combobox_acoustic_data_choice.currentIndex()].shape[1])
+                    self.slider.setMaximum(stg.time[data_id].shape[1])
 
                 self.plot_pre_processed_BS_signal()
                 self.plot_pre_processed_profile()
 
-                stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] = 0
+                stg.noise_method[data_id] = 0
 
                 self.activate_list_of_pre_processed_data()
-
         else:
-
             msgBox = QMessageBox()
             msgBox.setWindowTitle("Download Error")
             msgBox.setIcon(QMessageBox.Warning)
@@ -1636,7 +1649,6 @@ class SignalProcessingTab(QWidget):
             BS_data_ppa = stg.BS_raw_data_pre_process_average
             for i in range(len(BS)):
                 bs = BS[i]
-                logger.debug(f"BS data shape {bs[data_id].shape}")
                 if bs[data_id].shape == (0,):
                     continue
 
@@ -1645,7 +1657,6 @@ class SignalProcessingTab(QWidget):
                     BS_data_ppa = BS_ppa[i]
                     break
 
-            logger.debug(f"BS_data: {BS_data[data_id].shape}")
 
             # BS_data_ppa[data_id] = deepcopy(BS_data[data_id])
             #
@@ -1674,10 +1685,10 @@ class SignalProcessingTab(QWidget):
 
             BS_data_ppa[data_id] = np.array([temp_list[0]])
             for j in range(stg.freq[data_id].shape[0]-1):
-                BS_data_ppa[data_id] = np.append(BS_data_ppa[data_id], np.array([temp_list[j+1]]), axis=0)
-
-            logger.debug(
-                f"BS_data_ppa: {BS_data_ppa[data_id].shape}"
+                BS_data_ppa[data_id] = np.append(
+                    BS_data_ppa[data_id],
+                    np.array([temp_list[j+1]]),
+                    axis=0
                 )
 
     def plot_pre_processed_profile(self):

virtualenv/requirements.txt

@@ -1,41 +1,15 @@
 astropy==6.1.7
-astropy-iers-data==0.2025.3.3.0.34.45
-contourpy==1.0.7
-cycler==0.11.0
-defusedxml==0.7.1
-et-xmlfile==1.1.0
-fonttools==4.38.0
-importlib-resources==5.12.0
-joblib==1.2.0
-kiwisolver==1.4.4
-llvmlite==0.39.1
 matplotlib==3.6.3
 numba==0.56.4
 numpy==1.23.5
-odfpy==1.4.1
-openpyxl==3.0.10
-packaging==23.0
 pandas==1.5.3
-Pillow==9.4.0
-profilehooks==1.12.0
-pyerfa==2.0.1.5
-pyparsing==3.0.9
-pyqt-checkbox-table-widget==0.0.14
-pyqt-file-list-widget==0.0.1
-pyqt-files-already-exists-dialog==0.0.1
-pyqt-tooltip-list-widget==0.0.1
 PyQt5==5.15.9
 PyQt5-Qt5==5.15.2
 PyQt5-sip==12.11.0
 python-dateutil==2.8.2
-pytz==2022.7.1
-PyYAML==6.0.2
 scikit-learn==1.2.1
 scipy==1.10.0
-simplePyQt5==0.0.1
-six==1.16.0
-threadpoolctl==3.1.0
-utm==0.7.0
-xlrd==2.0.1
-xmltodict==0.13.0
-zipp==3.15.0
+odfpy==1.4.1
+openpyxl==3.0.10
+pyinstaller==6.12.0
+pyqt_file_list_widget==0.0.1