Acoustic recording data is updated. If data are pre-processed in the previous tab then pre-processed data of the acoustic recording are provided in Sample data tab. If data are not pre-processed, then raw data are provided in sample data tab.
brahim
parent
1b2c5954ee
commit
011cfd536e
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@ -1109,7 +1109,16 @@ class SampleDataTab(QWidget):
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def fill_comboboxes_and_plot_transect(self):
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self.combobox_acoustic_data.clear()
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self.combobox_acoustic_data.addItems(stg.filename_BS_raw_data)
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for n, m in enumerate(stg.noise_method):
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print("n = ", n, "m = ", m)
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if stg.noise_method[n] == 0:
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print("stg.filename_BS_raw_data ", stg.filename_BS_raw_data)
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self.combobox_acoustic_data.addItem(stg.filename_BS_raw_data[n])
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elif stg.noise_method[n]!=0:
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print("stg.data_preprocessed ", stg.data_preprocessed)
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print("stg.data_preprocessed[n] ", stg.data_preprocessed[n])
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self.combobox_acoustic_data.addItem(stg.data_preprocessed[n])
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self.plot_sample_position_on_transect()
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self.combobox_acoustic_data.currentIndexChanged.connect(self.update_plot_sample_position_on_transect)
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self.combobox_frequencies.currentIndexChanged.connect(self.update_plot_sample_position_on_transect)
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@ -1131,12 +1140,62 @@ class SampleDataTab(QWidget):
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# self.combobox_frequencies.currentTextChanged.connect(self.update_plot_sample_position_on_transect)
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self.verticalLayout_groupbox_plot_transect.removeWidget(self.canvas_plot_sample_position_on_transect)
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self.figure_plot_sample_position_on_transect, self.axis_plot_sample_position_on_transect = \
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plt.subplots(nrows=1, ncols=1, layout="constrained")
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self.canvas_plot_sample_position_on_transect = FigureCanvas(self.figure_plot_sample_position_on_transect)
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self.verticalLayout_groupbox_plot_transect.addWidget(self.canvas_plot_sample_position_on_transect)
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if stg.BS_stream_bed[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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if stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :])
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val_max = np.nanmax(stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :])
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if val_min == 0:
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val_min = 1e-5
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self.axis_plot_sample_position_on_transect.pcolormesh(
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stg.time_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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-stg.depth_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :],
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cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
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self.axis_plot_sample_position_on_transect.plot(
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stg.time_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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-stg.depth_bottom[self.combobox_acoustic_data.currentIndex()], color='black', linewidth=1,
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linestyle="solid")
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elif stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :])
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val_max = np.nanmax(stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :])
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if val_min == 0:
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val_min = 1e-5
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self.axis_plot_sample_position_on_transect.pcolormesh(
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stg.time_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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-stg.depth_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :],
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cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
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self.axis_plot_sample_position_on_transect.plot(
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stg.time_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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-stg.depth_bottom[self.combobox_acoustic_data.currentIndex()], color='black', linewidth=1,
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linestyle="solid")
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elif stg.BS_stream_bed[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(stg.BS_stream_bed[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(), :, :])
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val_max = np.nanmax(stg.BS_stream_bed[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(), :, :])
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@ -1153,6 +1212,46 @@ class SampleDataTab(QWidget):
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stg.time_cross_section[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(), :],
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-stg.depth_bottom[self.combobox_acoustic_data.currentIndex()], color='black', linewidth=1, linestyle="solid")
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elif stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(
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stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :])
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val_max = np.nanmax(
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stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :])
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if val_min == 0:
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val_min = 1e-5
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self.axis_plot_sample_position_on_transect.pcolormesh(
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stg.time_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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-stg.depth_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :],
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cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
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elif stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(
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stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :])
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val_max = np.nanmax(
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stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :])
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if val_min == 0:
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val_min = 1e-5
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self.axis_plot_sample_position_on_transect.pcolormesh(
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stg.time_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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-stg.depth_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :],
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cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
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elif stg.BS_cross_section[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(
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@ -1168,6 +1267,38 @@ class SampleDataTab(QWidget):
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stg.BS_cross_section[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(), :, :],
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cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
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elif stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :])
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val_max = np.nanmax(stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :])
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if val_min == 0:
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val_min = 1e-5
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self.axis_plot_sample_position_on_transect.pcolormesh(
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stg.time[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(), :],
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-stg.depth[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(), :],
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stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :],
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cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
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elif stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :])
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val_max = np.nanmax(stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :])
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if val_min == 0:
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val_min = 1e-5
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self.axis_plot_sample_position_on_transect.pcolormesh(
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stg.time[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(), :],
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-stg.depth[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(), :],
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stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :, :],
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cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
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elif stg.BS_raw_data[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(stg.BS_raw_data[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(), :, :])
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@ -1190,7 +1321,59 @@ class SampleDataTab(QWidget):
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self.axis_plot_sample_position_on_transect.cla()
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# --- Create canvas of Matplotlib figure ---
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if stg.BS_stream_bed[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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if stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(
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stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(),
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:, :])
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val_max = np.nanmax(
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stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(),
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:, :])
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if val_min == 0:
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val_min = 1e-5
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self.axis_plot_sample_position_on_transect.pcolormesh(
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stg.time_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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-stg.depth_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(),
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:, :],
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cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
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self.axis_plot_sample_position_on_transect.plot(
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stg.time_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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-stg.depth_bottom[self.combobox_acoustic_data.currentIndex()],
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color='black', linewidth=1, linestyle="solid")
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elif stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(
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stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(),
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:, :])
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val_max = np.nanmax(
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stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(),
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:, :])
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if val_min == 0:
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val_min = 1e-5
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self.axis_plot_sample_position_on_transect.pcolormesh(
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stg.time_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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-stg.depth_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(),
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:, :],
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cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
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self.axis_plot_sample_position_on_transect.plot(
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stg.time_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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-stg.depth_bottom[self.combobox_acoustic_data.currentIndex()],
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color='black', linewidth=1, linestyle="solid")
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elif stg.BS_stream_bed[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(stg.BS_stream_bed[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(), :, :])
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val_max = np.nanmax(stg.BS_stream_bed[self.combobox_acoustic_data.currentIndex()][self.combobox_frequencies.currentIndex(), :, :])
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@ -1208,6 +1391,52 @@ class SampleDataTab(QWidget):
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-stg.depth_bottom[self.combobox_acoustic_data.currentIndex()],
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color='black', linewidth=1, linestyle="solid")
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elif stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(
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stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(),
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:, :])
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val_max = np.nanmax(
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stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(),
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:, :])
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if val_min == 0:
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val_min = 1e-5
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self.axis_plot_sample_position_on_transect.pcolormesh(
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stg.time_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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-stg.depth_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(),
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:, :],
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cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
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elif stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(
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stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(),
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:, :])
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val_max = np.nanmax(
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stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(),
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:, :])
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if val_min == 0:
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val_min = 1e-5
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self.axis_plot_sample_position_on_transect.pcolormesh(
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stg.time_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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-stg.depth_cross_section[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(),
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:, :],
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cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
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elif stg.BS_cross_section[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(
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@ -1228,6 +1457,52 @@ class SampleDataTab(QWidget):
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:, :],
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cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
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elif stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(
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stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(),
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:, :])
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val_max = np.nanmax(
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stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(),
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:, :])
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if val_min == 0:
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val_min = 1e-5
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self.axis_plot_sample_position_on_transect.pcolormesh(
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stg.time[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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-stg.depth[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(), :],
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stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(),
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:, :],
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cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
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elif stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data.currentIndex()].shape != (0,):
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val_min = np.nanmin(
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stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][
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self.combobox_frequencies.currentIndex(),
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:, :])
|
||||
val_max = np.nanmax(
|
||||
stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][
|
||||
self.combobox_frequencies.currentIndex(),
|
||||
:, :])
|
||||
if val_min == 0:
|
||||
val_min = 1e-5
|
||||
|
||||
self.axis_plot_sample_position_on_transect.pcolormesh(
|
||||
stg.time[self.combobox_acoustic_data.currentIndex()][
|
||||
self.combobox_frequencies.currentIndex(), :],
|
||||
-stg.depth[self.combobox_acoustic_data.currentIndex()][
|
||||
self.combobox_frequencies.currentIndex(), :],
|
||||
stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data.currentIndex()][
|
||||
self.combobox_frequencies.currentIndex(),
|
||||
:, :],
|
||||
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
|
||||
|
||||
elif stg.BS_raw_data[self.combobox_acoustic_data.currentIndex()].shape != (0,):
|
||||
|
||||
val_min = np.nanmin(
|
||||
|
|
|
|||
Loading…
Reference in New Issue