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a8bb150bf8
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26bd476772
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@ -1177,18 +1177,10 @@ class AcousticDataTab(QWidget):
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str("%4s" % stg.distance_from_ABS_to_free_surface[self.fileListWidget.currentRow()]))
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str("%4s" % stg.distance_from_ABS_to_free_surface[self.fileListWidget.currentRow()]))
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def refresh_distance_from_ABS_to_free_surface(self):
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def refresh_distance_from_ABS_to_free_surface(self):
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self.pushbutton_distance_from_ABS_to_free_surface.blockSignals(True)
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acoustic_data = AcousticDataLoader(
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stg.path_BS_raw_data[self.fileListWidget.currentRow()] + "/" +
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if self.combobox_ABS_system_choice.currentIndex() == 1:
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stg.filename_BS_raw_data[self.fileListWidget.currentRow()]
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acoustic_data = AcousticDataLoader(
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)
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stg.path_BS_raw_data[self.fileListWidget.currentRow()] + "/" +
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stg.filename_BS_raw_data[self.fileListWidget.currentRow()]
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)
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elif self.combobox_ABS_system_choice.currentIndex() == 2:
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acoustic_data = AcousticDataLoaderUBSediFlow(
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stg.path_BS_raw_data[self.fileListWidget.currentRow()] + "/" +
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stg.filename_BS_raw_data[self.fileListWidget.currentRow()]
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)
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stg.depth[self.fileListWidget.currentRow()] = acoustic_data._r
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stg.depth[self.fileListWidget.currentRow()] = acoustic_data._r
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stg.depth_reshape[self.fileListWidget.currentRow()] = acoustic_data.reshape_r()
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stg.depth_reshape[self.fileListWidget.currentRow()] = acoustic_data.reshape_r()
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@ -1214,8 +1206,6 @@ class AcousticDataTab(QWidget):
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self.update_plot_backscattered_acoustic_signal_recording()
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self.update_plot_backscattered_acoustic_signal_recording()
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self.update_plot_profile()
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self.update_plot_profile()
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self.pushbutton_distance_from_ABS_to_free_surface.blockSignals(False)
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def temperature_value(self):
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def temperature_value(self):
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if findall(r",", self.lineEdit_temperature.text()):
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if findall(r",", self.lineEdit_temperature.text()):
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@ -14,7 +14,7 @@
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# #
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# #
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# You should have received a copy of the GNU General Public License #
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# You should have received a copy of the GNU General Public License #
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# along with this program. If not, see <https://www.gnu.org/licenses/>. #
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# along with this program. If not, see <https://www.gnu.org/licenses/>. #
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import math
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# by Brahim MOUDJED #
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# by Brahim MOUDJED #
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# ============================================================================== #
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# ============================================================================== #
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@ -47,8 +47,6 @@ from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as Navigatio
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from matplotlib.colors import LogNorm, BoundaryNorm
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from matplotlib.colors import LogNorm, BoundaryNorm
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from os import path
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from os import path
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from numba.np.arraymath import np_average
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from View.show_popup_combobox import ComboBoxShowPopUpWindow
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from View.show_popup_combobox import ComboBoxShowPopUpWindow
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from View.plot_noise_window import PlotNoiseWindow
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from View.plot_noise_window import PlotNoiseWindow
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@ -1443,7 +1441,8 @@ class SignalProcessingTab(QWidget):
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val_max = np.nanmax(
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val_max = np.nanmax(
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BS_data[data_id][f, :, :]
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BS_data[data_id][f, :, :]
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)
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)
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if val_min == 0 or math.isinf(val_min):
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if val_min == 0:
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val_min = 1e-5
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val_min = 1e-5
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pcm = self.axis_BS[f].pcolormesh(
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pcm = self.axis_BS[f].pcolormesh(
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@ -1479,10 +1478,10 @@ class SignalProcessingTab(QWidget):
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self.fig_BS.supxlabel('Time (sec)', fontsize=10)
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self.fig_BS.supxlabel('Time (sec)', fontsize=10)
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self.fig_BS.supylabel('Depth (m)', fontsize=10)
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self.fig_BS.supylabel('Depth (m)', fontsize=10)
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# cbar = self.fig_BS.colorbar(pcm, ax=self.axis_BS[:],
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cbar = self.fig_BS.colorbar(pcm, ax=self.axis_BS[:],
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# shrink=1, location='right')
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shrink=1, location='right')
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# cbar.set_label(label='Acoustic backscatter signal (V)',
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cbar.set_label(label='Acoustic backscatter signal (V)',
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# rotation=270, labelpad=10)
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rotation=270, labelpad=10)
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self.fig_BS.canvas.draw_idle()
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self.fig_BS.canvas.draw_idle()
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else:
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else:
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self.verticalLayout_groupbox_plot_pre_processed_data_2D_field\
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self.verticalLayout_groupbox_plot_pre_processed_data_2D_field\
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@ -1528,8 +1527,15 @@ class SignalProcessingTab(QWidget):
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msgBox.exec()
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msgBox.exec()
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else:
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else:
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data_id = self.combobox_acoustic_data_choice.currentIndex()
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data_id = self.combobox_acoustic_data_choice.currentIndex()
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n_average = 2 * int(float(self.lineEdit_horizontal_average.text().replace(",", "."))) + 1
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kernel_avg = np.ones(
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kernel_avg = np.ones(n_average)
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2 * int(
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float(
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self.lineEdit_horizontal_average\
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.text()\
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.replace(",", ".")
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)
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) + 1
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)
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logger.debug(f"kernel_avg: {kernel_avg}")
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logger.debug(f"kernel_avg: {kernel_avg}")
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stg.Nb_cells_to_average_BS_signal[data_id] = (
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stg.Nb_cells_to_average_BS_signal[data_id] = (
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@ -1593,34 +1599,16 @@ class SignalProcessingTab(QWidget):
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logger.debug(f"BS_data: {BS_data[data_id].shape}")
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logger.debug(f"BS_data: {BS_data[data_id].shape}")
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# BS_data_ppa[data_id] = deepcopy(BS_data[data_id])
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BS_data_ppa[data_id] = deepcopy(BS_data[data_id])
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#
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# for f, _ in enumerate(stg.freq[data_id]):
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# for i in range(y_depth.shape[1]):
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# BS_data_ppa[data_id][f, i, :] = (
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# convolve(
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# BS_data[data_id][f, i, :],
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# kernel_avg
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# )
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# )
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temp_list = []
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for f, _ in enumerate(stg.freq[data_id]):
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for f, _ in enumerate(stg.freq[data_id]):
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temp0 = np.array([])
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for i in range(y_depth.shape[1]):
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for i in range(y_depth.shape[1]):
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# temp = convolve(BS_data[data_id][f, i, :], kernel_avg, "same") / n_average
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BS_data_ppa[data_id][f, i, :] = (
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temp = convolve(array=BS_data[data_id][f, i, :],
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convolve(
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kernel=kernel_avg,
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BS_data[data_id][f, i, :],
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nan_treatment='interpolate')
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kernel_avg
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if temp0.shape == (0,):
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)
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temp0 = np.array([temp])
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)
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else:
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temp0 = np.append(temp0, np.array([temp]), axis=0)
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temp_list.append(temp0)
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BS_data_ppa[data_id] = np.array([temp_list[0]])
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for j in range(stg.freq[data_id].shape[0]-1):
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BS_data_ppa[data_id] = np.append(BS_data_ppa[data_id], np.array([temp_list[j+1]]), axis=0)
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logger.debug(
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logger.debug(
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f"BS_data_ppa: {BS_data_ppa[data_id].shape}"
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f"BS_data_ppa: {BS_data_ppa[data_id].shape}"
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