Correction of average filter button (if no acoustic data) #33
brahim
parent
df68a862fc
commit
06056d4865
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@ -1551,105 +1551,123 @@ class SignalProcessingTab(QWidget):
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def compute_averaged_BS_data(self):
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kernel_avg = np.ones(2 * int(float(self.lineEdit_horizontal_average.text().replace(",", "."))) + 1)
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print(kernel_avg)
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if len(stg.filename_BS_raw_data) == 0:
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msgBox = QMessageBox()
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msgBox.setWindowTitle("Compute noise from profile tail error")
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msgBox.setIcon(QMessageBox.Warning)
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msgBox.setText("Download acoustic data in previous tab before applying SNR filter")
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msgBox.setStandardButtons(QMessageBox.Ok)
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msgBox.exec()
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stg.Nb_cells_to_average_BS_signal[self.combobox_acoustic_data_choice.currentIndex()] = (
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float(self.lineEdit_horizontal_average.text().replace(",", ".")))
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if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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x_time = stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
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y_depth = stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
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elif stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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x_time = stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
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y_depth = stg.depth[self.combobox_acoustic_data_choice.currentIndex()]
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elif len(stg.BS_noise_raw_data) == 0:
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msgBox = QMessageBox()
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msgBox.setWindowTitle("SNR filter Error")
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msgBox.setIcon(QMessageBox.Warning)
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msgBox.setText("Define noise data (file or profile tail) before using SNR filter")
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msgBox.setStandardButtons(QMessageBox.Ok)
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msgBox.exec()
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else:
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if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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kernel_avg = np.ones(2 * int(float(self.lineEdit_horizontal_average.text().replace(",", "."))) + 1)
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print(kernel_avg)
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x_time = stg.time[self.combobox_acoustic_data_choice.currentIndex()]
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y_depth = stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
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stg.Nb_cells_to_average_BS_signal[self.combobox_acoustic_data_choice.currentIndex()] = (
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float(self.lineEdit_horizontal_average.text().replace(",", ".")))
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elif stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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x_time = stg.time[self.combobox_acoustic_data_choice.currentIndex()]
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y_depth = stg.depth[self.combobox_acoustic_data_choice.currentIndex()]
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if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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if stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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x_time = stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
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y_depth = stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
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stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
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stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
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elif stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
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for i in range(y_depth.shape[1]):
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x_time = stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
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y_depth = stg.depth[self.combobox_acoustic_data_choice.currentIndex()]
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stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
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convolve(stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
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kernel_avg))
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else:
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elif stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
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stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
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x_time = stg.time[self.combobox_acoustic_data_choice.currentIndex()]
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y_depth = stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
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for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
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for i in range(y_depth.shape[1]):
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elif stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
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convolve(stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
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kernel_avg))
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x_time = stg.time[self.combobox_acoustic_data_choice.currentIndex()]
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y_depth = stg.depth[self.combobox_acoustic_data_choice.currentIndex()]
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elif stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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if stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
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stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
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stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
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stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
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for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
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for i in range(y_depth.shape[1]):
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for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
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for i in range(y_depth.shape[1]):
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stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
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convolve(stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
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kernel_avg))
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stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
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convolve(stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
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kernel_avg))
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elif stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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elif stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
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stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()]))
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stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
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stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
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for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
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for i in range(y_depth.shape[1]):
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stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
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convolve(stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][f, i, :], kernel_avg))
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for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
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for i in range(y_depth.shape[1]):
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elif stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
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convolve(stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
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kernel_avg))
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stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
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stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()]))
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elif stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
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for i in range(y_depth.shape[1]):
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stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
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convolve(stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
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kernel_avg))
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stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
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stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
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elif stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
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for i in range(y_depth.shape[1]):
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stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
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stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()]))
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stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
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convolve(stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
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kernel_avg))
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for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
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for i in range(y_depth.shape[1]):
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stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
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convolve(stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()][f, i, :], kernel_avg))
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elif stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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self.plot_pre_processed_BS_signal()
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self.update_plot_pre_processed_profile()
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stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
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stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()]))
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for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
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for i in range(y_depth.shape[1]):
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stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
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convolve(stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][f, i, :], kernel_avg))
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elif stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
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stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()]))
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for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
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for i in range(y_depth.shape[1]):
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stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
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convolve(stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
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kernel_avg))
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elif stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
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stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()]))
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for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
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for i in range(y_depth.shape[1]):
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stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
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convolve(stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()][f, i, :], kernel_avg))
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self.plot_pre_processed_BS_signal()
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self.update_plot_pre_processed_profile()
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def plot_pre_processed_profile(self):
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