Exceptions for download file are added. Exceptions for FCB are added. Exception for computing averaged backscatter signal is added (enter an odd number)
parent
e8438ec46b
commit
cd33f9d85c
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@ -357,23 +357,42 @@ class SampleDataTab(QWidget):
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filename_fine_sediment = QFileDialog.getOpenFileName(self, "Open file",
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"/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/Granulo_data",
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"Fine sediment file (*.xls, *.ods)")
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stg.fine_sediment_path = path.dirname(filename_fine_sediment[0])
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stg.fine_sediment_filename = path.basename(filename_fine_sediment[0])
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self.load_fine_sediment_data()
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self.lineEdit_fine_sediment.setText(stg.fine_sediment_filename)
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self.lineEdit_fine_sediment.setToolTip(stg.fine_sediment_path)
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try:
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stg.fine_sediment_path = path.dirname(filename_fine_sediment[0])
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stg.fine_sediment_filename = path.basename(filename_fine_sediment[0])
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self.load_fine_sediment_data()
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except IsADirectoryError:
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msgBox = QMessageBox()
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msgBox.setWindowTitle("Download Error")
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msgBox.setIcon(QMessageBox.Warning)
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msgBox.setText("Please select a file")
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msgBox.setStandardButtons(QMessageBox.Ok)
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msgBox.exec()
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else:
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self.lineEdit_fine_sediment.setText(stg.fine_sediment_filename)
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self.lineEdit_fine_sediment.setToolTip(stg.fine_sediment_path)
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# --- Function to select directory and file name of sand sediments sample data ---
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def open_dialog_box_sand_sediment(self):
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filename_sand_sediment = QFileDialog.getOpenFileName(self, "Open file",
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"/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/Granulo_data",
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"Sand sediment file (*.xls, *.ods)")
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stg.sand_sediment_path = path.dirname(filename_sand_sediment[0])
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stg.sand_sediment_filename = path.basename(filename_sand_sediment[0])
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self.load_sand_sediment_data()
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self.lineEdit_sand.setText(stg.sand_sediment_filename)
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self.lineEdit_sand.setToolTip(stg.sand_sediment_path)
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try:
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stg.sand_sediment_path = path.dirname(filename_sand_sediment[0])
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stg.sand_sediment_filename = path.basename(filename_sand_sediment[0])
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self.load_sand_sediment_data()
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except IsADirectoryError:
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msgBox = QMessageBox()
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msgBox.setWindowTitle("Download Error")
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msgBox.setIcon(QMessageBox.Warning)
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msgBox.setText("Please select a file")
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msgBox.setStandardButtons(QMessageBox.Ok)
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msgBox.exec()
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else:
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self.lineEdit_sand.setText(stg.sand_sediment_filename)
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self.lineEdit_sand.setToolTip(stg.sand_sediment_path)
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def load_fine_sediment_data(self):
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fine_granulo_data = GranuloLoader(stg.fine_sediment_path + "/" + stg.fine_sediment_filename)
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@ -331,7 +331,7 @@ class SignalProcessingTab(QWidget):
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self.gridLayout_groupbox_fit_regression.addWidget(self.pushbutton_plot_FCB, 2, 0, 1, 1)
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self.pushbutton_plot_FCB.clicked.connect(self.compute_FCB)
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self.pushbutton_plot_FCB.clicked.connect(self.plot_FCB)
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# self.pushbutton_plot_FCB.clicked.connect(self.plot_FCB)
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self.pushbutton_fit_linear_regression = QPushButton()
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self.pushbutton_fit_linear_regression.setText("Fit && Compute \u03B1s")
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@ -672,24 +672,32 @@ class SignalProcessingTab(QWidget):
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msgBox.setStandardButtons(QMessageBox.Ok)
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msgBox.exec()
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else:
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filter_convolve = np.ones(self.spinbox_average_horizontal.value())
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if self.spinbox_average_horizontal.value() % 2 == 0:
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msgBox = QMessageBox()
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msgBox.setWindowTitle("Average Backscatter signal Error")
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msgBox.setIcon(QMessageBox.Warning)
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msgBox.setText("Please enter an odd number")
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msgBox.setStandardButtons(QMessageBox.Ok)
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msgBox.exec()
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else:
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filter_convolve = np.ones(self.spinbox_average_horizontal.value())
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stg.BS_data_section_averaged = np.zeros((stg.r.shape[0], stg.freq.shape[0], stg.t.shape[0]))
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for f in range(stg.freq.shape[0]):
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for i in range(stg.r.shape[0]):
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stg.BS_data_section_averaged[i, f, :] \
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= convolve1d(stg.BS_data_section[i, f, :], weights=filter_convolve) / filter_convolve.shape[0]
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stg.BS_data_section_averaged = np.zeros((stg.r.shape[0], stg.freq.shape[0], stg.t.shape[0]))
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for f in range(stg.freq.shape[0]):
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for i in range(stg.r.shape[0]):
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stg.BS_data_section_averaged[i, f, :] \
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= convolve1d(stg.BS_data_section[i, f, :], weights=filter_convolve) / filter_convolve.shape[0]
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self.label_cells_horizontal.clear()
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self.label_cells_horizontal.setText(
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"cells = +/- " + str((self.spinbox_average_horizontal.value() // 2)*(1/stg.nb_profiles_per_sec)) + " sec")
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self.label_cells_horizontal.clear()
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self.label_cells_horizontal.setText(
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"cells = +/- " + str((self.spinbox_average_horizontal.value() // 2)*(1/stg.nb_profiles_per_sec)) + " sec")
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# self.label_cells_vertical.clear()
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# self.label_cells_vertical.setText(
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# "cells = +/- " + str((self.spinbox_average_vertical.value() // 2) * (1 / stg.nb_profiles_per_sec)) + " sec")
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# self.label_cells_vertical.clear()
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# self.label_cells_vertical.setText(
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# "cells = +/- " + str((self.spinbox_average_vertical.value() // 2) * (1 / stg.nb_profiles_per_sec)) + " sec")
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self.plot_averaged_profile()
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self.update_plot_profile_position_on_transect()
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self.plot_averaged_profile()
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self.update_plot_profile_position_on_transect()
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# ---------------------------------------- Connect Groupbox filter with SNR ----------------------------------------
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@ -790,68 +798,90 @@ class SignalProcessingTab(QWidget):
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return R_real
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def compute_FCB(self):
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R_real = np.repeat(self.range_cells_function()[:, :, np.newaxis], stg.t.shape[0], axis=2)
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if (stg.BS_data_section_averaged.size == 0) and (stg.BS_data_section_SNR_filter.size == 0):
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stg.FCB = (np.log(stg.BS_data_section) + np.log(R_real) +
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2 * stg.water_attenuation * R_real)
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elif stg.BS_data_section_SNR_filter.size == 0:
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stg.FCB = (np.log(stg.BS_data_section_averaged) + np.log(R_real) +
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2 * stg.water_attenuation * R_real)
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if stg.BS_data_section.size == 0:
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msgBox = QMessageBox()
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msgBox.setWindowTitle("FCB Error")
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msgBox.setIcon(QMessageBox.Warning)
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msgBox.setText("Load Backscatter data from acoustic data tab and compute water attenuation")
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msgBox.setStandardButtons(QMessageBox.Ok)
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msgBox.exec()
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else:
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stg.FCB = (np.log(stg.BS_data_section_SNR_filter) + np.log(R_real) +
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2 * stg.water_attenuation * R_real)
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R_real = np.repeat(self.range_cells_function()[:, :, np.newaxis], stg.t.shape[0], axis=2)
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if (stg.BS_data_section_averaged.size == 0) and (stg.BS_data_section_SNR_filter.size == 0):
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stg.FCB = (np.log(stg.BS_data_section) + np.log(R_real) +
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2 * stg.water_attenuation * R_real)
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elif stg.BS_data_section_SNR_filter.size == 0:
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stg.FCB = (np.log(stg.BS_data_section_averaged) + np.log(R_real) +
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2 * stg.water_attenuation * R_real)
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else:
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stg.FCB = (np.log(stg.BS_data_section_SNR_filter) + np.log(R_real) +
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2 * stg.water_attenuation * R_real)
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self.plot_FCB()
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def fit_FCB_profile_with_linear_regression_and_compute_alphaS(self):
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y0 = stg.FCB[:, self.combobox_frequency_compute_alphaS.currentIndex(), self.slider.value()]
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y = y0[np.where(np.isnan(y0) == False)]
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print("y : ", y)
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if stg.FCB.size == 0:
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msgBox = QMessageBox()
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msgBox.setWindowTitle("Linear regression error")
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msgBox.setIcon(QMessageBox.Warning)
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msgBox.setText("Please compute FCB before")
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msgBox.setStandardButtons(QMessageBox.Ok)
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msgBox.exec()
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else:
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try:
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y0 = stg.FCB[:, self.combobox_frequency_compute_alphaS.currentIndex(), self.slider.value()]
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y = y0[np.where(np.isnan(y0) == False)]
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x0 = stg.r.reshape(-1)
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x = x0[np.where(np.isnan(y0) == False)]
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x0 = stg.r.reshape(-1)
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x = x0[np.where(np.isnan(y0) == False)]
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value1 = np.where(np.round(np.abs(x - self.spinbox_alphaS_computation_from.value()), 2)
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== np.min(np.round(np.abs(x - self.spinbox_alphaS_computation_from.value()), 2)))
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value2 = np.where(np.round(np.abs(x - self.spinbox_alphaS_computation_to.value()), 2)
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== np.min(np.round(np.abs(x - self.spinbox_alphaS_computation_to.value()), 2)))
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value1 = np.where(np.round(np.abs(x - self.spinbox_alphaS_computation_from.value()), 2)
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== np.min(np.round(np.abs(x - self.spinbox_alphaS_computation_from.value()), 2)))
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value2 = np.where(np.round(np.abs(x - self.spinbox_alphaS_computation_to.value()), 2)
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== np.min(np.round(np.abs(x - self.spinbox_alphaS_computation_to.value()), 2)))
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print(np.round(np.abs(x - self.spinbox_alphaS_computation_from.value()), 2))
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print("value1 ", value1[0][0])
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print(np.round(np.abs(x - self.spinbox_alphaS_computation_to.value()), 2))
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print("value2 ", value2[0][0])
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# print(np.round(np.abs(x - self.spinbox_alphaS_computation_from.value()), 2))
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# # print("value1 ", value1[0][0])
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# print(np.round(np.abs(x - self.spinbox_alphaS_computation_to.value()), 2))
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# print("value2 ", value2[0][0])
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print("y limited ", y[value1[0][0]:value2[0][0]])
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# print("y limited ", y[value1[0][0]:value2[0][0]])
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# y = stg.FCB[value1:value2, self.combobox_frequency_compute_alphaS.currentIndex(), self.slider.value()]
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# print("y : ", y)
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lin_reg_compute = stats.linregress(x[value1[0][0]:value2[0][0]], y[value1[0][0]:value2[0][0]])
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except ValueError:
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msgBox = QMessageBox()
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msgBox.setWindowTitle("Linear regression error")
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msgBox.setIcon(QMessageBox.Warning)
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msgBox.setText("Please check boundaries to fit a linear line")
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msgBox.setStandardButtons(QMessageBox.Ok)
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msgBox.exec()
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else:
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stg.lin_reg = (lin_reg_compute.slope, lin_reg_compute.intercept)
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# print(f"y = {stg.lin_reg[0]}x + {stg.lin_reg[1]}")
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lin_reg_compute = stats.linregress(x[value1[0][0]:value2[0][0]], y[value1[0][0]:value2[0][0]])
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stg.lin_reg = (lin_reg_compute.slope, lin_reg_compute.intercept)
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print(f"y = {stg.lin_reg[0]}x + {stg.lin_reg[1]}")
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self.label_alphaS.clear()
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self.label_alphaS.setText(f"\u03B1s = {-0.5*stg.lin_reg[0]:.4f} dB/m")
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self.label_alphaS.clear()
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self.label_alphaS.setText(f"\u03B1s = {-0.5*stg.lin_reg[0]:.4f} dB/m")
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# for i, value_freq in enumerate(stg.freq):
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# for k, value_t in enumerate(stg.t):
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# # print(f"indice i: {i}, indice k: {k}")
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# # print(f"values of FCB: {stg.FCB[:, i, k]}")
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# y = stg.FCB[:, i, k]
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# # print("y : ", y)
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# # print(f"values of FCB where FCB is not Nan {y[np.where(np.isnan(y) == False)]}")
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# # print(f"values of r where FCB is not Nan {x[np.where(np.isnan(y) == False)]}")
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# lin_reg_compute = stats.linregress(x[np.where(np.isnan(y) == False)], y[np.where(np.isnan(y) == False)])
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# lin_reg_tuple = (lin_reg_compute.slope, lin_reg_compute.intercept)
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# stg.lin_reg.append(lin_reg_tuple)
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# for i, value_freq in enumerate(stg.freq):
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# for k, value_t in enumerate(stg.t):
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# # print(f"indice i: {i}, indice k: {k}")
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# # print(f"values of FCB: {stg.FCB[:, i, k]}")
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# y = stg.FCB[:, i, k]
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# # print("y : ", y)
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# # print(f"values of FCB where FCB is not Nan {y[np.where(np.isnan(y) == False)]}")
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# # print(f"values of r where FCB is not Nan {x[np.where(np.isnan(y) == False)]}")
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# lin_reg_compute = stats.linregress(x[np.where(np.isnan(y) == False)], y[np.where(np.isnan(y) == False)])
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# lin_reg_tuple = (lin_reg_compute.slope, lin_reg_compute.intercept)
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# stg.lin_reg.append(lin_reg_tuple)
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# print(f"y = {lin_reg.slope}x + {lin_reg.intercept}")
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# print(f"y = {lin_reg.slope}x + {lin_reg.intercept}")
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# plt.figure()
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# plt.plot(stg.r, stg.FCB[:, 0, 825], 'k-', stg.r, lin_reg.slope*stg.r + lin_reg.intercept, "b--")
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# plt.show()
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# plt.figure()
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# plt.plot(stg.r, stg.FCB[:, 0, 825], 'k-', stg.r, lin_reg.slope*stg.r + lin_reg.intercept, "b--")
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# plt.show()
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# print("lin_reg length ", len(stg.lin_reg))
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# print("lin_reg ", stg.lin_reg)
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# print("lin_reg length ", len(stg.lin_reg))
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# print("lin_reg ", stg.lin_reg)
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# ---------------------------------------- PLOT PROFILE POSITION ON TRANSECT ---------------------------------------
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