Model/read_table_for_open.py

@@ -113,6 +113,7 @@ class ReadTableForOpen:
               WHERE (acoustic_data = {k})
             '''
             data = self.execute(query)[0]
+            print("data acoustic file", data)
 
             stg.filename_BS_raw_data.append(
                 str(data[1]) + '.aqa'
@@ -433,18 +434,10 @@ class ReadTableForOpen:
         for dest, resh in SNR_vars:
             SNR = np_f64_parse(next(it))
 
-            try:
+            if len(SNR) == 0:
-                if len(SNR) != 0:
-                    dest.append(SNR.reshape(resh[i].shape))
-                else:
-                    dest.append(np.array([]))
-            except:
-                logger.warning(
-                    "SQL: read_table_BS_raw_data_SNR: "
-                    + "failed to reshape data from "
-                    + f"{SNR.shape} to {resh[i].shape}"
-                )
                 dest.append(np.array([]))
+            else:
+                dest.append(SNR.reshape(resh[i].shape))
 
     def read_table_BS_raw_data_rest(self, query, i):
         np_f64_parse = lambda d: np.frombuffer(d, dtype=np.float64)

View/acoustic_data_tab.py

@@ -815,7 +815,6 @@ class AcousticDataTab(QWidget):
         self.fill_table()
         self.compute_tmin_tmax()
         self.compute_rmin_rmax()
-        # self.compute_time_cross_section()
         self.update_frequency_combobox()
         # self.fileListWidget.itemSelectionChanged.connect(self.plot_backscattered_acoustic_signal_recording)
         # self.fileListWidget.itemSelectionChanged.connect(self.plot_profile)
@@ -826,13 +825,8 @@ class AcousticDataTab(QWidget):
         self.fileListWidget.blockSignals(False)
 
     def print_selected_file(self):
-        logger.debug(
+        print(f"Selected file in list widget : {self.fileListWidget.selectedItems()}")
-            f"Selected file in list widget : {self.fileListWidget.selectedItems()}"
+        print("self.fileListWidget.selectedItems()[1:] : ", self.fileListWidget.selectedItems()[1:])
-        )
-        logger.debug(
-            "self.fileListWidget.selectedItems()[1:] : "
-            + f"{self.fileListWidget.selectedItems()[1:]}"
-        )
         if len(self.fileListWidget.selectedItems()) > self.max_selected_file:
             self.fileListWidget.setSelectionMode(1)
 
@@ -1250,7 +1244,6 @@ class AcousticDataTab(QWidget):
         self.fill_table()
 
         self.compute_rmin_rmax()
-        self.compute_time_cross_section()
         self.compute_depth_cross_section()
         self.set_range_for_spinboxes_bathymetry()
 
@@ -1455,6 +1448,13 @@ class AcousticDataTab(QWidget):
                 self.fileListWidget.blockSignals(False)
 
     def rename_file_in_ListWidget(self, event):
+        if event == QEvent.MouseButtonPress:
+            print("c'est bon")
+            if event.button == Qt.RightButton:
+                print("Right button clicked")
+            elif event.button == Qt.LeftButton:
+                print("Left button clicked")
+
         if event.type() == QEvent.ContextMenu:
             menu = QMenu()
             menu.addAction('Rename')
@@ -2143,6 +2143,17 @@ class AcousticDataTab(QWidget):
         self.tableModel = TableModel(stg.DataFrame_acoustic)
         self.tableView.setModel(self.tableModel)
 
+    def export_table(self):
+        if self.tableWidget.columnCount() == 10:
+            msgBox = QMessageBox()
+            msgBox.setWindowTitle("Export table Error")
+            msgBox.setIcon(QMessageBox.Warning)
+            msgBox.setText("Fill table before export table")
+            msgBox.setStandardButtons(QMessageBox.Ok)
+            msgBox.exec()
+        else:
+            print("export table")
+
     def transect_xaxis_choice(self):
         if self.groupbox_xaxis_time.isChecked() == True:
             self.groupbox_xaxis_space.setChecked(False)
@@ -2256,7 +2267,7 @@ class AcousticDataTab(QWidget):
                     )
                 )
             )[0][0] + 1,
-            time_max
+        time_max
         ))
 
         stg.time_cross_section[data_id] = (

View/mainwindow.py

@@ -301,6 +301,7 @@ class Ui_MainWindow(object):
             msg_box.exec()
 
     def about_window(self):
+        print("about")
         aw = AboutWindow()
         aw.exec()
 
@@ -313,6 +314,7 @@ class Ui_MainWindow(object):
         )
 
     def open_doc_file(self, filename):
+        print(self.current_file_path("filename.pdf"))
         QtGui.QDesktopServices.openUrl(
             QtCore.QUrl(
                 f"file://{self.current_file_path(filename)}"
@@ -333,11 +335,15 @@ class Ui_MainWindow(object):
             name = QtWidgets.QFileDialog.getExistingDirectory(
                 caption="Select Directory - Acoustic BS raw data Table"
             )
+            print("name table to save ", name)
 
             # --- Save the raw acoustic backscatter data from a
             # --- Dataframe to csv file ---
 
             t0 = time.time()
+            print("len(stg.BS_raw_data_reshape) ",
+                  len(stg.BS_raw_data_reshape))
+
             if name:
                 for i in range(len(stg.BS_raw_data_reshape)):
                     header_list = []
@@ -387,7 +393,8 @@ class Ui_MainWindow(object):
                     )
 
             t1 = time.time() - t0
-            logger.debug(f"Time duration export BS {t1}")
+            print("time duration export BS ", t1)
+            print("table of BS value Export finished")
 
     def retranslateUi(self):
         _translate = QtCore.QCoreApplication.translate

View/sediment_calibration_tab.py

@@ -2003,6 +2003,9 @@ class SedimentCalibrationTab(QWidget):
                     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][
                     stg.frequencies_for_calibration[0][1], :, :

View/signal_processing_tab.py

@@ -548,8 +548,9 @@ class SignalProcessingTab(QWidget):
         )
 
     def update_SignalPreprocessingTab(self):
+
         """ The tab is updated in two cases :
-            - the user remove a file (in the list widget) in the first tab (Acoustic data), so that the combobox
+                - 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:
@@ -626,68 +627,13 @@ class SignalProcessingTab(QWidget):
 
         if stg.noise_method[data_id] == 0:
             if stg.filename_BS_noise_data[data_id] != "":
-                if len(stg.BS_noise_raw_data) == 0:
+                self.load_noise_data_and_compute_SNR()
-                    self.load_noise_data_and_compute_SNR()
-                else:
-                    self.compute_noise()
         elif stg.noise_method[data_id] == 1:
             self.compute_noise_from_profile_tail_value()
 
         self.remove_point_with_snr_filter()
         self.compute_averaged_BS_data()
 
-    def compute_noise(self):
-        data_id = max(0, self.combobox_acoustic_data_choice.currentIndex())
-
-        if stg.time_cross_section[data_id].shape != (0,):
-            stg.time_noise[data_id] = (
-                stg.time_cross_section[data_id]
-            )
-        else:
-            stg.time_noise[data_id] = (
-                stg.time[data_id]
-            )
-        if stg.depth_cross_section[data_id].shape != (0,):
-            stg.depth_noise[data_id] = (
-                stg.depth_cross_section[data_id]
-            )
-        else:
-            stg.depth_noise[data_id] = (
-                stg.depth[data_id]
-            )
-
-        if self._is_correct_shape(stg.BS_stream_bed):
-            BS_data = stg.BS_stream_bed
-            SNR_data = stg.SNR_stream_bed
-        elif self._is_correct_shape(stg.BS_cross_section):
-            BS_data = stg.BS_cross_section
-            SNR_data = stg.SNR_cross_section
-        else:
-            BS_data = stg.BS_raw_data
-            SNR_data = stg.SNR_raw_data
-
-        noise = np.zeros(BS_data[data_id].shape)
-        for f, _ in enumerate(BS_data[data_id]):
-            noise[f, :, :] = np.mean(
-                stg.BS_noise_raw_data[data_id][f, :, :], axis=(0, 1)
-            )
-
-        stg.BS_noise_averaged_data[data_id] = noise
-
-        SNR_data[data_id] = (
-            np.divide(
-                (
-                    BS_data[data_id] - stg.BS_noise_averaged_data[data_id]
-                ) ** 2,
-                stg.BS_noise_averaged_data[data_id] ** 2
-            )
-        )
-
-        self.combobox_frequency_profile.clear()
-        self.combobox_frequency_profile.addItems(
-            [f for f in stg.freq_text[data_id]]
-        )
-
     def replot(self):
         self.plot_averaged_profile_tail()
         self.plot_transect_with_SNR_data()
@@ -963,7 +909,7 @@ class SignalProcessingTab(QWidget):
 
             stg.BS_stream_bed_pre_process_SNR[data_id] = np.array([])
             stg.BS_stream_bed_pre_process_average[data_id] = np.array([])
-
+            print("stg.noise_method[data_id]", stg.noise_method[data_id])
             if stg.noise_method[data_id] == 0:
                 self.lineEdit_noise_file.clear()
 
@@ -1088,42 +1034,50 @@ class SignalProcessingTab(QWidget):
 
         stg.noise_method[data_id] = 0
 
-        noise_data = AcousticDataLoader(
+        noise_data = AcousticDataLoader(stg.path_BS_noise_data[data_id] +
-            os.path.join(
+                                        "/" +
-                stg.path_BS_noise_data[data_id],
+                                        stg.filename_BS_noise_data[data_id])
-                stg.filename_BS_noise_data[data_id]
-            )
-        )
         stg.BS_noise_raw_data[data_id] = noise_data._BS_raw_data
 
         stg.time_noise[data_id] = noise_data._time
         stg.depth_noise[data_id] = noise_data._r
 
         if stg.BS_stream_bed[data_id].shape != (0,):
-            BS_data = stg.BS_stream_bed
+
-            SNR_data = stg.SNR_stream_bed
+            noise = np.zeros(stg.BS_stream_bed[data_id].shape)
+            for f, _ in enumerate(noise_data._freq):
+                noise[f, :, :] = np.mean(
+                    stg.BS_noise_raw_data[data_id][f, :, :], axis=(0, 1))
+            stg.BS_noise_averaged_data[data_id] = noise
+            stg.SNR_stream_bed[data_id] = (
+                np.divide((stg.BS_stream_bed[data_id] -
+                           stg.BS_noise_averaged_data[data_id]) ** 2,
+                          stg.BS_noise_averaged_data[data_id] ** 2))
+
         elif stg.BS_cross_section[data_id].shape != (0,):
-            BS_data = stg.BS_cross_section
+
-            SNR_data = stg.SNR_cross_section
+            noise = np.zeros(stg.BS_cross_section[data_id].shape)
+            for f, _ in enumerate(noise_data._freq):
+                noise[f, :, :] = np.mean(
+                    stg.BS_noise_raw_data[data_id][f, :, :], axis=(0, 1))
+            stg.BS_noise_averaged_data[data_id] = noise
+            stg.SNR_cross_section[data_id] = (
+                np.divide((stg.BS_cross_section[data_id] -
+                           stg.BS_noise_averaged_data[data_id]) ** 2,
+                          stg.BS_noise_averaged_data[data_id] ** 2))
+            # stg.SNR_reshape = np.reshape(stg.SNR_cross_section, (stg.r.shape[1] * stg.t.shape[1], stg.freq.shape[0]), order="F")
+
         else:
-            BS_data = stg.BS_raw_data
-            SNR_data = stg.SNR_raw_data
 
-        noise = np.zeros(BS_data[data_id].shape)
+            noise = np.zeros(stg.BS_raw_data[data_id].shape)
-        for f, _ in enumerate(noise_data._freq):
+            for f, _ in enumerate(noise_data._freq):
-            noise[f, :, :] = np.mean(
+                noise[f, :, :] = np.mean(
-                stg.BS_noise_raw_data[data_id][f, :, :], axis=(0, 1)
+                    stg.BS_noise_raw_data[data_id][f, :, :], axis=(0, 1))
-            )
+            stg.BS_noise_averaged_data[data_id] = noise
-
+            stg.SNR_raw_data[data_id] = (
-        stg.BS_noise_averaged_data[data_id] = noise
+                np.divide((stg.BS_raw_data[data_id] -
-        SNR_data[data_id] = (
+                           stg.BS_noise_averaged_data[data_id]) ** 2,
-            np.divide(
+                          stg.BS_noise_averaged_data[data_id] ** 2))
-                (
-                    BS_data[data_id] - stg.BS_noise_averaged_data[data_id]
-                ) ** 2,
-                stg.BS_noise_averaged_data[data_id] ** 2
-            )
-        )
 
     def open_plot_noise_window(self):
         pnw = PlotNoiseWindow()
@@ -1137,11 +1091,6 @@ class SignalProcessingTab(QWidget):
             float(self.lineEdit_profile_tail_value.text().replace(",", "."))
         )
 
-        self.compute_noise_from_profile_tail_value_compute()
-
-    def compute_noise_from_profile_tail_value_compute(self):
-        data_id = max(0, self.combobox_acoustic_data_choice.currentIndex())
-
         if stg.time_cross_section[data_id].shape != (0,):
             stg.time_noise[data_id] = (
                 stg.time_cross_section[data_id]
@@ -1161,38 +1110,47 @@ class SignalProcessingTab(QWidget):
 
         # --- Compute noise from value and compute SNR ---
         if self._is_correct_shape(stg.BS_stream_bed):
-            BS_data = stg.BS_stream_bed
+            stg.BS_noise_raw_data[data_id] = np.array([])
-            SNR_data = stg.SNR_stream_bed
+            stg.BS_noise_raw_data[data_id] = (
+                np.full(stg.BS_stream_bed[data_id].shape,
+                        float(self.lineEdit_profile_tail_value.text().replace(",", "."))))
+
+            stg.BS_noise_averaged_data[data_id] = (
+                stg.BS_noise_raw_data[data_id][:, :,
+                :stg.BS_stream_bed[data_id].shape[2]])
+            stg.SNR_stream_bed[data_id] = (
+                np.divide((stg.BS_stream_bed[data_id]
+                           - stg.BS_noise_raw_data[data_id]) ** 2,
+                          stg.BS_noise_raw_data[data_id] ** 2))
+
         elif self._is_correct_shape(stg.BS_cross_section):
-            BS_data = stg.BS_cross_section
+            stg.BS_noise_raw_data[data_id] = (
-            SNR_data = stg.SNR_cross_section
+                np.full(stg.BS_cross_section[data_id].shape,
+                        float(self.lineEdit_profile_tail_value.text().replace(",", "."))))
+
+            stg.BS_noise_averaged_data[data_id] = (
+                stg.BS_noise_raw_data[data_id][:, :,
+                :stg.BS_cross_section[data_id].shape[2]])
+            stg.SNR_cross_section[data_id] = (
+                np.divide((stg.BS_cross_section[data_id]
+                           - stg.BS_noise_raw_data[data_id]) ** 2,
+                          stg.BS_noise_raw_data[data_id] ** 2)) #
+
         else:
-            BS_data = stg.BS_raw_data
+            stg.BS_noise_raw_data[data_id] = (
-            SNR_data = stg.SNR_raw_data
+                np.full(stg.BS_raw_data[data_id].shape,
+                        float(self.lineEdit_profile_tail_value.text().replace(",", "."))))
 
-        stg.BS_noise_raw_data[data_id] = (
+            stg.BS_noise_averaged_data[data_id] = (
-            np.full(
+                stg.BS_noise_raw_data[data_id])
-                BS_data[data_id].shape,
+            stg.SNR_raw_data[data_id] = (
-                float(self.lineEdit_profile_tail_value.text().replace(",", "."))
+                np.divide((stg.BS_raw_data[data_id]
-            )
+                           - stg.BS_noise_raw_data[data_id]) ** 2,
-        )
+                          stg.BS_noise_raw_data[data_id] ** 2))
-
-        stg.BS_noise_averaged_data[data_id] = (
-            stg.BS_noise_raw_data[data_id]
-        )
-        SNR_data[data_id] = (
-            np.divide(
-                (
-                    BS_data[data_id] - stg.BS_noise_raw_data[data_id]
-                ) ** 2,
-                stg.BS_noise_raw_data[data_id] ** 2
-            )
-        )
 
         self.combobox_frequency_profile.clear()
         self.combobox_frequency_profile.addItems(
-            [f for f in stg.freq_text[data_id]]
+            [f for f in stg.freq_text[data_id]])
-        )
 
         # --- Trigger graphic widgets ---